CONTAMINANT EMISSIONS IN THE LOS ANGELES BASIN-
THEIR SOURCES, RATES, AND DISTRIBUTION
Appendix A
of
Development of a Simulation Model
for Estimating Ground Level Concentrations
of Photochemical Pollutants
Prepared by
Systems Applications, Inc.
Beverly Hills, California 90212
for the
A1r Pollution Control Office
of the Environmental Protection Agency
Durham. North Carolina 27701
-------
CQft'AMINANT EMISSIONS IN THE LOS ANGELES BASIN--
THEIR SOU~S, ~TES, AND DISTRIBUTION
Appendix A
of
Developlllent of a Simulation Mpdel
for Estimating Ground Leve} Concentrations
of Photochemical Pollutants
Philip J. W. Roberts
Philip M. Roth
Clarence L. He 180n
Report 71SAI-6
March 1971
Prepared by
Systems Applications, Inc.
Beverly Bills, California
90212
for the
Air Pollution Control office
of the Environmental Protection Agency
Durham, North Carolina 27701
under Contract CPA 70-148
-------
ACKNOWLEDGMENTS
Many people have contributed to the development of this emissions
inventory, and we wish to acknowledge their help. We are indebted to
Mr. Wallace Braff of the Los Angeles Traffic Department for his kindness
and cooperation in providing us with mountains of traffic data, as well
as with much information that is not available in written form, to
Messrs. Albe!t Wheelock and A. D. Young of the State of California
Division of Highways, for supplying freeway traffic data; and to Mr. Arthur
Hocker of the State of California Air Resources Board, who provided
virtually all of the automobile emissions data. ~le also wish to grate-
fully acknowledge the assistance we received from staff members of the
traffic departments of the nearly 100 municipalities in the Basin.
"
Special thanks are due to those who undertook the long and laborious
task of determining the spatial distribution of traffic in the Los Angeles
Basin. This project was indeed arduous, yet all participants worked with
zeal and dedication. They are Vikram Budhraja, Kathleen Carlberg, Robert
Chin, Victoria Harris, Ronald Jonas, Carlos Patrickson, Shirley Svorny,
- Sandra Tripp, and Rockford Zee.
,
A number of individuals provided us with air traffic information:
Mr. Allen D. Carter, of the Systems Planni~g Staff of the Federal Aviation
Administration, Mr. Donald-J. Haugen, Chief, and Mr. Francis p. Scollick,
Operations Officer, of the Los Angeles International Airport Control
T?Wer, Mr. Hbward N. Peterson, Chief, and Mr. Norman C. Norton, Supervisory
Air Traffic Control Specialist of the Van Nuys AirPOrt Control Tower,
Mr. R. N. Lemmer, Chief, and Mr. G. W. Hoy, Operations Officer, of the
Hollywood-Burbank Airport Control Tower, and other Air Traffic Control
Tower personnel to whom we spoke. To all these people we wish to extend
our thanks.
We wish to express our appreciation to several employees of the local
power companies who have been most cooperative in supplying infoDnation on
power plant emissions. These are: Mr. Frank A~ McCrackin and Mr. M. J. Ziol
of the Southern California Edison Company, Hr. Floyd L. Goss of the
Los Angeles Department of Water and Power, Mr. John Healy of the City of
Pasadena, and Mr. Winfield Miller of the City of Glendale. Mr. Ziol was
particularly helpful, in that he carried out a number of detailed
calculations involving the operations of the Edison Company's local plants
for one of the validation days in question.
-------
CONTENTS
INTRODUCTION .
III.
I.
II.
. . . .
. . . . .
.....
. . . . . . . . .
AUTOMOTIVE EMISSIONS
. . . .
. . . . .
. .
. . .
. . . . . . .
A.
Automobile Emissions Model
......
. . . .
.....
1.
2.
3.
Exhaust emissions
Crankcase emissions
Evaporative losses.
. . .
. . 8, . . .
.....
. .
. . .
......
......
. . . .
. . .
. . .
. . .
. . .
B.
Summary of Major Assumptions and Presentation of
Resul ts ......... . . . . . . .
. . . .
C.
The Calculations and Data Sources
. . . .
. .
1.
2.
3.
Spatial distribution of traffic . . . . . . .
~emporal distribution of traffic. . . . . . . . . . .
Pollutant emissions rates. . . . . . . . . . . . . .
References. . . . . .
. . .
. .
. . . . . . .
. . .
. . . .
AIRCRAFT E~ISSIONS . .
. . .
. . . . . . .
. .
. . . . . . . .
A.
Aircraft Emissions Model. .
. . . .. . . .
. . . . . . . .
B.
Emissions and Airport Data
. . . .
.....
. . . .
References.
. . .
. .
. . . .
......
.....
. .
FIXED SOURCE EMISSIONS--POWER PLANTS AND REFINERIES
.....
A.
Power Plant Model
. . . . . . . . . . . .
. . . .
. . .
1.
Treatment of point
sources. . . . .
Emissions and. other
. .
source emissions as volume
.....
. . . .
. . . .
.....
relevant data
2.
. . . .
. . . .
B.
Oil Refinery Model. .
. . . .
.....
. . . .
.....
1.
2.
Distribution of emissions . . . . .
Emissions and other relevant data. . .
. . . . . . .
. . . . . .
C.
Alternate Models for Large Point Sources.
. . . . .
. ". .
Page
. .
A-l
A-l
.
A-4
A-S
A-7
A-a
A-a
A-1S
A-IS
A-17
A-19
A-32
A-33
A-33
A-38
A-47
A-47
.
A-47
A-49
A-49
A-59
.
A-59
A-59
A-65
1. Estimation of local concentrations 'for steady state,
non-reacting plumes . . . . . . . . . . . . . . . . . A-65
2. Further suggestions for the treatment of large
point sources . . . . . . . . . . . . . . . . . . . . A-69
References. . . . . .
.......
. . . .
. . . . . . . . .
A-70
-------
IV.
V.
FIXED SOU~E EMISSIONS--DISTRIBUTED SOURCES. . . . . . . . .
A.
Oxides of Nitrogen
. . . .. . . . . . . . . . . .". . . .
B.
Organic Gases.
. . .
. . . . . . . . . . . . . . . . . 8,
..
C.
Carbon Monoxide.
. . . . . . . . . . . . . . .
.....
CONTAMINANT EMISSIONS INVENTORY OF THE LOS ANGELES BASIN
~,
Pa<;{e
A-71
A-71
A-76
A-77
. .
A-SO
-------
INTRODUCTION
Perhaps the most tedious and mundane aspect in the development
and validation of a simulation model of reaction and dispersion processes
in the atmosphere is the compilation of a complete contaminant emissions
inve~tory. Yet, such an inventory is a sine qua non in model validation
. and, if done properly, the emissions estimates probably constitute the
most precise segment of requisite input data. Contrast, for example,
the relatively low magnitudes of errors in emissions esti~4tes with the
imprecision of wind speed and direction estimates, both at the surface
and aloft, as well as with the uncertainties in estimates of the
variation in mixing depth wi th location and time. Furthermore, an
emissions inventory need be carried out but once to serve as an adequate
representation of a region, whereas meteorological data must be collected
for each validation day, And for the purposes of this modeling venture,
represented through hourly variation in wind field and mixing depth.
It thus seemed wise to put a considerable effort into the establishment
of an accurate emissions inventory for the Los Angeles Basin.
Particular 'emphasis was placed on developing a deta~led representation
of the spatial and temporal traffic distribution in the B~sin, as
vehicular emissions account for approximately 91\ of CO, 85\ of reactive
hydrocarbon, and 62\ of NOx emissions. Attention was also given to those
sources which, while responsible for only a small proportion of emissions
on an area-wide basis, contribute heavily to pollutant concentration
levels in their own locale--airports, power plants, and refineries. (We
have indicated in Figure A-I the locations of these major sources, as well
as the locations of all freeways and monitoring stations.) In this
Appendix, we present in detail the emissions inventories developed for
the major moving and fixed sources of pollution in the Los Angeles Basin.
I.
AUTOMOTIVE EMISSIONS
The magnitude of contaminant emissions from a motor vehicle is a
variable in time and is a function of the percentage of time the vehicle
is operated in each driving mode (accelerate, cruise, decelerate, ,idle).
The modal split is in turn dependent on the habits of the driver, the
type of street on which the vehicle is operated, and the deqree of
congestion on that street. Also affecting emissions are the presence
or absence of a smog control device, the condition of the car, its size,
and other factors. The distribution of vehicles in time and location
throughout an urban area is similarly governed bya number of factors--
commuting routes, distribution of centers of employment, shopping centers,
residential and recreational areas, topography, the occurrence of special
events, etc. ' Thus, precise calculation of the maqnitude of emissions as
a function of location and time is clearly not possible.
A number of studies have been conducted in recent years having as
their objective the development of a vehicle emissions inventory for
Figure .A-:I follows
-------
14
I;
17
.,
2
If.
Figure A-I. Location of Primary Sources and
Monitoring Stations in the Los Angeles Basin
'- - freeways
. - oil refineries
A - power plants
. - airports
. 0 - contaminant monitoring
stations
.' "
A-2
-------
a particular urban area. In a study published in 1955, Larson, et al.
(a paper often incorrectly attributed to D.M. Teague) describe an
inventory undertaken for the County of Los Angeles. In this effort,
emissions rates were measured for a number of vehicles, and traffic
count data were used to obtain the geographical and temporal distri-
bution of traffic in the area. Ozolins and Smith (1968) discuss a
procedure based on gasoline sales figures, traffic flow maps and
average emissions rates to obtain total daily vehicle emissions and an
approximate measure of their spatial variation over an area. Rehmann
(1968) performed an inventory for Gary, Indiana, using for emissions
data the results of a study reported by Rose, et al. (1965). [Vehicle
emissions rates reported by Rose (and obtained from ~ests on 1955-1963
automobiles) are presented as a function of average route speed.] Rehmann
assumed in his study that emissions fro~ a vehicle are a function only
of its average speed. He used traffic counts and traffic flow maps,
along with estimates of average speeds On different classes of streets,
to obtain the spatial'variation of automobile emissions in the city.
Lamb (1968) compiled an inventory of the Los Angeles Basin in a manner
similar to that of Rehmann. LamQ, as Rehmann, adopted the emissions
figures published by Rose. He also applied an average temporal distribution
of ~~affic flow to obtain the variation of emissions through the day.
However, Lamb did not include in his report the geographical distribution
of traffic which he der~ved.
For the purpose of our modeling venture, the effort to obtain an
accurate vehicle emissions inventory of the Los Angeles Basin was
separated into two detailed studies:
(1)
Estimation of spatial and temporal distrjnution of traffic, and
(2)
Estimation of average vehicle emissions rates applicable to
traffic in the area.
Geographical and temporal variations of vehicle emissions in the area
were then derived, based on the results of these studies.
As there have been no recent results published regarding the spatial
distribution of traffic in the basin, we undertook our own study based
on existing traffic count data. These data were obtained from nearly 100
municipalities and are very extensive, with counts being available for all
but minor residential streets. The mOdeling area (50 miles square) was
divided into 625 grid squares of 2x2 miles each. Using the traffic count
data, estimates were made of the vehicle miles driven per day in each
two mile square area. Although this part of the study required a large
and time consuming effort, it was considered to beworthwl\ile as the
results should be valId for several years, with only occasional updating.
The temporal distribution of traffic over the area, represented as hourly
variations in vehicular flow, was also computed from these count data.
Freeways and surface streets were treated separately in the derivation of
both the temporal and spatial distributions.
The automobile emissions data~sed in our study are those published by
the State of California Air Resources Board (ARB). These data are based
on emissions measurements made by the ARB on a sample of approximately
A-3
-------
7,500 automobiles of model years 1966 to 1969, and on measurements made
under a joint Federal/State/City program on a sample of approxin\ately
1,000 pre-1964 model year automobiles. These data are well suited to
an inventory of the Los Angeles Basin, as the emissions measurements
were made on privately owned cars actually operated in the area. How-
ever, while the driving cycle used by the ARB in measuring automobile
emissions is based on a typical Los Angeles commuter run, the degree to
'which it is actually representative of vehicle emissions patterns is not
known. (See page A-19 for a discussion of this question.) Finally, by
usinq a test 'procedure based on a driving cycle, it is possible to ex-
press the emissions rate of each contaminant as a single figure. This,
figure, as we have suggested, takes into account the effects on emissions
'of the different driving modes in which vehicles are actually operated.
This method of expressing emissions obviates the necessity of estimating
average route speeds, which would require a street classification scheme.
In the sections that follow we first describe the automobile emissions
model adopted. We then summarize the major results of the emissions inventory:
spatial and temporal distributions of traffic"knd vehicle emissions rates.
Finally, the calculational procedures and data used in the study are detailed.
A.
Automobile Emissions Model
,
Emissions are attributable to t~e fOllowing three sources in an
uncontrolled automobile:
(1)
Exhaust emissions account for approximately 65\ of
hydrocarbons and 100% of nitrogen oxides and carbon
monoxide: '
(2)
Crankcase leakage (or blow-by) accounts for approximately
20% of hydrocarbons,
(3)
Evaporation from the fuel tank and carburetor accounts
for approximately 15% of hydrocarbons.
As a result of vehicle modifications and changing legislation for auto-
mobile emissions through the 1960's, the magnitudes and relative
contributions of these three sources vary with vehicle model year.
In this section we present a model for each of these three
automobile emissions sources. Average pollutant emissions rates of
Los Angeles Basin vehicles are then calculated, and the results presented
in summary form. Emissions rates are expressed in grams/mile for exhaust
and blow-by, and grams/day for evaporation. The flux of emissions into
a grid square resulting from exhaust and blow-by is then simply the
product of the emissions rate and the number of vehicle miles driven per
time period in that square. The total daily evaporative loss from all
vehicles in the basin is estimated, and is distributed in proportion to
the daily non-freeway vehicle mileage driven in each square. As the
estimation of daily vehicle mileage was a substantial undertaking,
we describe in some detail the means by which these estimates were derived.
~4
-------
1.
Exhaust emissions
The emissions rate of species k from the exhaust of an
average automobile in the Los Angeles Basin, in grams per mile, is
given by:
5 4
2k = I: xi ~ y ijeijkKijk .
i=l )=1 .
where
Xi = fraction of total cars in the Los Angeles Basin of
model year i
whe re
i = 1
2
3
4
5
up to
1966
1967
1968
1969
I .
and 'including 1965
T c total number of cars in Los Angeles Basin in Fall 1969
Yij = fraction of
j &:I 1
2
3
4
XiT
manufactured by
General Motors Corporation
Chrysler Corporation
Ford Motor Company .
Foreign Manufacturers
k
from cars
.' eijk ... volumetric exhaust emissions rate of species
manufactured by maker j of model year i
where
k = 1
2
3
CO (in ')
Hydrocar~ons
NOx (in ppm)
(in ppm)
Kijk &:I constant from table, a multiplier to convert pprn (or") to
grams per mile
= f (W. .) where ~'li)' = average weight of car. in model year
1) .
manufactured by jth manufacturer.
Assumptions:
i
The California Driving Cycle is representative of driving
in the Los Angeles Basin. (See page A-19 for a discussion of
this point.)
(1)
(2)
Emissions rates based on the California Driving Cycle can be
taken as average emissions for automobiles traveling on sur-
face streets and freeways.
A-S
-------
(3)
Emissions rates, eijk' in addition to being a function of
manufacturer and model year, are a function of average vehicle
mileage and are independent of engine size. (The latter
assumption has been confirmed through analysis of emissions
data. ) , -
(4)
All automobiles travel about 11,000 miles per year, and all
were purchased at the middle of the model year--about
March I-April 1. *
Formulation of the model in this way enables us to take advantage of
the vast data base amassed by the California'State Air Resources Board
(ARB) in recent years.
Calculation of-average automobile emissions rates is based on data
relating to cars comprising approximately 90% of the total registration
in Los Angeles and Orange Counties. Of this 90%, however, approximately
65% (i.e., 59% of the total) are pre-1966 models for which only overall
average emissions figures are available. The other 10% of the automobile
registration consists mainly of pick-ups and AMC automobiles, none of
which could be included, due to an absence of emissions data. Division
of the vehicle population by manufacturer was made only to take advan-
tage of correlations derived by the ARB through regression analysis.
For a given grid square, the grams of species k emitted as-
engine ,exhaust per hour (for the tth hour) into a cell (or assignable
to anode at the center of a cell) =
(0. 9rams - ) (M vehicle miles)
~k vehicle mile t - hour
*Calculations are made as of October 1, 1969.
mileages are as follows:
Thus, average automobile
Vehicle Model Year
Odometer Reading
(miles)
1969
1968
1967
1966
1965 and older
5,000
16,000
27,000
38,000
> 50,000
Emissions calculations are based on these average mileages, as taken
from regression analyses (presented as emissions of species, k from a
vehicle of model year i as a function of 'mileage) reported by
Hocker (1970a, 1970b). .
A-6
-------
Calculation of Mt:
For surface streets--
s
Ht = dR, L: nutu
u=l
where
n =
u
vehicles per day (given as
traffic counts at a point,
assignable to a segment of
road)
t = miles Qf road segment to which
u
count nu is assigned
d1 = fraction of da~ly (24-hour)
traffic count .assigneble to
hourly period t
s = nurooer of road segments
contained in the grid square.
For free\'1ays--
Same calculation, using different distribution,
dR, .
Traffic counts for virtually all free\.rays, arterials, and main
streets are available. Counts for minor residential streets are
sparse and are thus estimated. .
The data base consists of counts made by
(a)
State of. California for freeways and state highways
(b)
Los Angeles County for small towns and unincorporated
areas
(c) Municipalities
(1)
(2)
Los Angeles County--about 70 incorporated. cities
Orange County--about 20 incorporated cities
2.
Crankcase emissions
positive Crankcase Ventilation (PCV) devices have been in-
stalled on automobiles in recent years to prevent the loss of hydro-
carbons to the atmosphere resulting from leakage bet~reen the piston
and cylinder during the compression stroke. As these devices re-
cycle crankcase fumes through the carburetor air intake, blm...-by
A-7
-------
losses from properly equipped vehicles have been virtually elim-
inated.
California law requires that PCV devices be fitted to all autos
.
of domestic manufacture of model year 1963 and later
of domestic manufacture of 1955-1962 vintage upon
change of ownership
of foreign manufacture of model year 1965 and later.
.
However, these devices
California as early as
years became effective
were installed on new domestic cars sold in
1961, and the. law concerning 1955 to 1962 model
in 1964.
Since it is estimated that only 15% of all automobiles are not
equipped with PCV valves, crankcase losses contribute but a small
fraction of total emitted hydrocarbons. OUr estimated figure for
blow-by losses (see Section 3 of Part C for details) is 0.7 grams/
mile for the average vehicle in the Los Angeles Basin. .
3.
Evaporative losses
Evaporative losses occur at the fuel tank and the carburetor and
involve only hydrocarbons. These losses have been estimated at approxi-
mately 72 grams/day (See Part C, section 3 for details). While tank losses
occur primarily during vehicle operation and carburetor losses during
the periods after a hot engine is stopped, elevated daytime tempera-
tures and exposure to the sun serv.e to enhance evaporation rates. In
the absence of definitive data we have chosen to distribute the daily
10ss evenly between the daylight hours of 7 a.m. to 7 p.m. PDT (6 a.m.
to 6 p.m. PST), assuming nighttime evaporative losses to be small.
The total evaporative loss from over 4.1 million vehicles at a
rate of 6 grams/vehicle/hour is distributed OVer the Basin area in
proportion to the non-freeway vehicle mileage in each grid square
(totaZ daily non-freeway vehicle mileage for the Basin ~ 72.4 x 106).
We believe that this distribution approximates actual vehicle distri-
bution (fixed and moving) as closely as any distribution available.
Under this assumption, evaporative emissions for each grid square
equal 0.343mij ki1ograrns/houi, where mij= thousands of non-fre~way
vehicle miles per day driven in square ij.
B.
Summary of Major Assumptions and Presentation of Results
The major assumptions on which the model formulation is based are
summarized as follows:
(1)
Automobile emissions may be represented by the
results of tests using the hot start California
Driving Cycle. Furthermore, these emissions may
be expressed as "lumped" or "single figure" rates
. I
A-a
-------
for Los Angeles Basin traffic, independent of average speed,
m~dal split, etc.
(2)
All arteries, freeways and surface streets may be treated
as area sources. (This assumption is questionable in the
case of freeways and will be examined in depth during exercise
of the overall model.)
(3)
Emissions. rates for all vehicles in the basin are typified by the
data obtained from the 8500 automobiles and 135 trucks tested.
, This sample excludes many imports, automobiles produced by the
smaller I domestic manufacturers, and all 1964 and 1965 autos.
(4 )
The temporal distributions estimated for freeways and surface
streets may be applied to the total daily vehicle mileages
calculated for each grid square.
The major results of the automotive emi~sions inventory are now
presented.
Area surveyed: 50 mile x 50 mile, predominantly urban area having
as its boundaries:
longitude west 118° 38' IS"
east 117° 46' 3"
latitude north 34° 17' 30"
south 33° 34' 2"
The area is divided into 625 grid squares, eacl1 2 miles x miles.*
Spatial. distribution of traffic, ~ nutu' for each grid sqUal'e:
u
freeways
Figure A-2
non-freeways
Figure A-3
Temporal distribution of traffic , dR,:
freeways
Figure A-4 and Table A-I
non-freeways
Figure A-4 and Table A-I
Emissions rates, ~:
Table A-2
. -,-
. ~~ ..'''' -.'.) ,
.........
~ .; .,.,:,' ~,'
"
*For further reference, the-center of the
lies on Century Boulevard, O.l,mile south
Highway, in the Cit~~,of Linwood. -
area, 25 miles from each border,
of its intersection with Imperial
A-9
Figures A-2 to A-4
and Tables A-I and A-2 follow
-------
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o JI
12
3
"
Fiqure A-~. Spatial Distribution of Freeway Traffic
(thousand vehicle miles per day)
A-10
-------
"W"
1:\:
I
\'
26rl"'r1I~~L~~r~ j~6.L;~r~ l.,i i~ r';':r ;2l;} I~ L')'i~r,;! '/~'I"'CJ'~;:r2"i"1=~r27l4 i-~J
5 35: U }U1~~;T~~'~- ~;;:-;~~r~-3r'2;r.;;-_.1~T~T-;T"~r;--'~~';~~T~-~ '-:~cT-o 2S
21. 6-;t-~;. '~~;;~'r;~' ';;~\~~I--~~r-~~1' ~~ '7;t"~';"-21--~':-0--"; ~.._;~..~t...~!-.~ -~t-:r-2T~~-: u
~ . . .._-~- -~-i--t---1- .- ----'-:"'-:0-"":--' _..... .--.-1-.... r"'" .- ..-t-,ur' .- '--, ..--
23137:255 238:238!266 295i:!51i233j 54; 20 27;1'57,50.' 4 0 O' 1 0' OJ 0 0; 0; 2' O~ 023
H-~-'-- -~-t--'_;""---r---' ._.~m__._._.. -.------- --~--~.__..!-...:_~- -.....-..--'-'-._--~-
21 ~~r:~~Oj.264 -~~~~.~~~~~6~~1:2.l~1.5. -~.~~~.~.~~~~~__~~~3_. -~-~-:-._~--~[__.~l.__o ._~~-~L-~~~0 a
2.' 139! 118! 107 194 : 182 350: 26~.; 280 21\71180 204' 204' 21' 173.241 212 156 91' 57: 1 6; 6: 2 ~ 0; 0 2.'
2e 25; 30 I 17: 12 ! 59 6J! 121 ! 155: 116: 25 245.242 191 162 318 308: 241 218' 183; 77 126 '149' 151' 76: 3~20
Iii 9 i ~-;:-";r3~' . ;o-j-;; t-;~~r~;~l~' ~':~-~71~;:-;;~';36' -;;7-~;;~-'-~~'-;6-~'~-1~~ '~;:;3-;-~-~~;:---~:--7-7 Ii
: +--.......-.. n u..-+.-- -t---~ ..--.l.-.... ......-:.. --' ;"'--":'-'''~'-' -. . - i' . ~. - ..:... _..~.._.. '--~.'-~-'.-r-"-" ---
IS o! 18 i 0 I 7! 98 283 i 403 ~ 549' 512 :572 473: 226 . 217 '229~85 243' 250 . 242: 114: 190 280 244 i 71' 10: 99 IF
- ..-..-.-......... ----.,....-... ..----'--_&_.-..-.-----...- ._,--.- ,...- -..--.-. -...- ---, ...- ., --. --.,-.... .___10...--.. ----"''''-r--
n 47: 64! 99: 117 '231 512 I 3~' 1459 418 ;468 642.579. 290 199:186 75: 108 : 173: 131 ~ 180 142. 18: 49' 50: 13 17
" ~~r ; ;-~76 ;;;:-;;':;61' m :413 ~-1-2-~2~--~~9;\~- ~:;~;'~-~-~;r-~~7 '-;;;::;:~5-;:;~T-'~"
-.
l:i
305 .255 . 255 311 '478 477 -: 364 . 292 273 299 'i~8 195' 69 21 82 42! 90' 33. 12; 0 IS"
-----!-.--:..._~-_.._~~-- -----.---;-.--,..-. .~.- -----_.~ --;----:-._- - --"t--r---'"'I---:-- l
06 .266,413 392 ;331 393 273 '322' 305 265 253 '190 295. 119' 42 22: 1 I 37': l' 5 It
.. ~~--~. -. -~-..- -7.,,-" -.- .:-- --7' -- ~--_.:-._. - .._~_. .----i'-.'''~'''- ....:.- j-'1-'---T-~~-'
.~-~: ~~~ 29~._:':.~- ~~~-~~..~~~5~~ ~~~:Z~_~~~;.:40 -~~{O!-r. ~i. 9!~.13
; 89 . 255 : 328 358 176 26S; 2'3 . 257 ~298 241: 230 . 135 ' 114 ~ 62 129 h14 : 95 I 57 4.1
....; .-:._..:..._~_.. ...... .._..._"_.~. ~_. - - -.......t.. :- . ....t-.-". ..i...- ...-.
11 ~ ; 21S: 412 :322 210 121' 270 .312 ;301 93' 96 104: 270: 179 290~197: 82; 48 30i"
--.tJ' ~ ; ~.6~_..' _3~4ni~~I- ~2..1. ...79. ~2~~: ~~~ ~4~~... 2~~ ;.~~.8_._~~~.L.3~~1 ~~2. . 3.~3 j ~~ J!~.~--~IL1~,o
I I' .. I " I I . . 'I
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--~~~1!~~;l~1.~; :~;~; ::H-: -;;~i:;:I~~~;:;j;;;-t!~~:I' ~;1~
. ---!'\~I'--2-5-:;;;-l(r" .-- i ----1 ..\ . '-r~~ ~';I'~'!'I~-~r~~; -~;;';;3"!1~;;1 -;; .~~ l.
. '. ~"., , '. I , .
1 '" i', "I: i Is
-~.._-~-_.tl_-!j _.~ _:. - -~_._~ - ..j...- -_..; .~_.~ ~~-t' ~~~1 ~~~~~~.~.'_4. _8~~ -~1. -2~i
; . iI, '; 126 I 107 248 1215 100 I 29 15,4
i ; ! I I :, i .
-"1'--- ---+----- _..- ---~_.!-._-t.. --:-f--' -J~~~ ;;~+ 94, ~1-~~ --~ 3
I . ! I t I -. ...- __1_..- -... .....-
--;-li---- --;----. --r-r- --rr--j-- --,~.!,~.~ ~ 0- --~12
--rl-rT---rh-TTTI , ~ ~...~. . .
_..._.l-.J.._-~-_. ------_.~.--- --~.__I..._....£,.- ~L. _u
Eo 7' 8 q 10 " 12. '3 It, 15" '7 18 lit 10 z., 2.2 Z-;, 1.4- lS
: i
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13
12
-- ~... . ~ .. ; ... ~ .
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s
Figure A-3.
Spatial Distribution of Non-Freeway Traffic
(thousand vehicle miles per day)
A-ll
-------
.09 -
freeways
.----
I I surface streets
I
't1 I
0
...t
k I
U G)
.,.fa.
11-1 J
11-1:>" .06 -. r----
IISM
k k I I
-+'::1 I
0 I L
:>...s:: I -,
M
...t 0 , I
III+'
't1 I I
:r OJ I
II-IM
.... o~ , I
t.) g ~
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+, en
U en .03 - --' t- -
lIS III
k
11-1 1/1 period being
+' "
a modeled
8
I
_1
0
midnight 6 a.m. noon 4 p.m. midnight
Figure A-4.
Temporal Distribution of Traffic for Freeways and Surface Streets
-------
, ,
Table A-I.
Temporal Distribution of Traffic
Hourly Period*
(local time)
Fraction of
Daily Traffic
,
I
Freeways
12-5 a.m.
5-6
6-7
7-8
8-9
9-10
10 a.m.-2 p.m.
2-3
3-6
6-7
.7-12
.0388
.0178
.0591
.0768
.0'648
.0536
.1977
.0569
.2238
.0598,
.1511
Surface Streets
12-6 a.m.
6-7
7-9
9~11
11 a.m.-4 p.m.
4-6
6-8
8-12
.0407
.0293
.1302
.1004
.3044
.1639
.1081
.1231
*Distributions are approximately uniform for the day tight time periods
i~dicated. However, traffic is not uniformly distributed within the
periods 7 p.m. to 5 a.m. for freeways, 8 p.m. to 5 a.m. for surface
streetS. These groupings are included only for completeness.
A-13
-------
'l'ab1e A-2.
+
Vehicle Emissions Factors - Qk
Exhaust:
QCO
*
QHC
QNO
x
63.9 grams/vehicle mile
8.3 grams/vehicle mile
4.4 grams/vehicle mile
*Additions to QHC
blow-by
0.7 grams/vehicle mile
**
evaporation
72.0 grams/vehicle/day
A
+Computed for the average vehicle in the Los Angeles Basin
as of September 1969. Automobile exhaust emissions are
based on hot start California Driving Cycle. See page A-26
for a comparison of these emissions factors with those
based on the 1972 Federal test procedure.
*
Hydrocarbon emissions: 85\ reactive, 15\ unreactive.
Table A-IO.)
(See
**Computed as 343mij grams/hour for each grid square for
the period 7 a.m.-? p.m. PST, where mij is thousands of
non-freeway vehicle miles/day driven in ,square ij, no
emissions for the nighttime period, 7 p~m.-7 a.m.
A-14
-------
C.
The Calculations and Data Sources
In this section, we will describe in some detail the calculational
aspects of the automotive emissions inventory, as well as data sources.
1.
Spatial distribution of traffic
The major question of strategy in planning the computation of
the spatial distribution was whether the calculations should be
carried out manually or by computer. A cursory analysis indicated
that the cost of computerization far exceeded that for manual
calculations. Unless the computer-based procedures were to be
exercised repeatedly, manual computations were clearly favored. It
should be mentioned that the Bureau of the 'Census is currently
developing a map encoding technique known as DIME (Dual Ind~pendent
Map Encoding) which, when available, can be extended and modified
for use in the analysis of automotive emis~ions. However, the DIME
file for Los Angeles, according to current estimates, will not
become available for some time.
The second strategic issue involved the level of detail we
wished to incorporate into the procedure. Were we to include traffic
counts only for freeways and major and minor arteries, ignoring
residential and side streets, or were we to include all streets?
Since this effort was to be undertaken only once, we were inclined
to make as complete an inventory as possible. However, there exists
a dearth of data for the smaller streets, so we compromised by
adopting the -policy of using all available counts and estimating
traffic flow on the remaining streets from the local traffic data in
the area, the type of neighborhood, and reference to counts on
similar streets.
We began by acquiring the U.s. Geological Survey topographic maps
(7 1/2' series) of the 50 mile x 50 mile area encompassing the
Los Angeles Basin and ruling off 625 2 mile x 2 mile grid squares.
For each grid square, a team of two students each, using roadmaps
and vehicle count data (acquired from the state, two counties, and
90 municipalities), filled in worksheets such as that shown in
Figure A-5. The pair of students would enter all mileages and counts
on the sheet, a third student would do all multiplications and additions,
and a fourth would quickly check for accuracy. Two to four teams,
along with one or two students carrying out the computations, were
involved throughout the seven-week effort. Freeway computations were
carried out and recorded separately. The total effort involved over
1400 man-hours of student labor, excluding the time required for
formulation of the model, organization of the effort (including
hiring and administration), preparation of maps, and the substantial
effort required for acquisition of data. In contrast, the more
extensive effort (estimated time: six to twelve months) of creating
a computerized data base and automating the manual procedure would
have represented a cost 25 to 50 times that incurred. (If the DIME
file were available at the inception of the project, estimated costs
would have exceeded incurred costs by a factor of 3 to 8.)
A-IS
Figure A-S follows
-------
. FJ~~r~'-'--- 'c;t>(u~ '1- 1'7---'--- t.~~:=~~fb-(tS~Vh1~i--'
. . . A J 0. TRAFFIC
STREET . Ivue:J1f J'O&ITH" COUNT ~
. I ON WHICH . TABULATED BE USED
I TRAFFIC FIRST SECOND TRAFFIC A IN C~~UTING VEHICLE MILES I
I IS COUNTED INTERSECTION INTERSECTION COUNT V (ACTUAL or AVG) MILES PER DAY __I
'L~. ~.IO tfdc..11 /T)O..' ~3~~""""2.Jl.~'o .P~ 1/~8 !
- to(J(¥1"~)" ll:(&.l 4-/.rOh -. '3S-() l/-1J .k~ 7I~. 78/
O'}j.;': \Jj./,~~~ 'A-4-60.5"" ()."3 osc. .1 4- 306
"\).,:" ',I D',ct:.; 4-~~'4';4~;1C1 ,II leSSO
I.i . ",;f;:;;: 'I'1~A' IJ. S~4-'')f~'( 50111 .IJJ. ...... ~ 001 :
. fA d ChI/.-, £..~.. (' ~:a ~... s- Jq..o 0 @J 2 "10
I -.-J £dql!... p..u.;' :Ll ('/I '1 ?~. OJ ,1< !S 628
4'..if'~ hJAt;l'I~ .13JIV ~ -;)..7813 .,1., I~ 016
/.j..."-;f~. /f,./..!! f/'IPJ/~ 3aq63 .& ':.~-'B
(;(//.../I. ~~n .... '-IV}'JI "OS 72>-41
I II":'.. ,"", . FJ!1t> nl,
~N\fJ./:}..'.f P~1I Cf 503 'if ~q'~.4- '356S"
0,',,,-,> \/.,.,,;/7; "fJ~n '7 102.'12. ..3 ;038
---'-.
!DIIN 5 I."i I" wI" I.)M t... ,'~ 1/",.-0 I () <2 - f- 'O~ I. 'it; I e9
: '()r...,~ iu..' tAr.p .J (J(lIof\It. nl~r_' '5h,,~ -fI->- ."'J C 1402.
! ()/ '~VV\.n;'; c..i. Vi',ni- J:-;. 1.1 q 7" M ; 2iq 3 I ~~1,_._... .
i ~o.!. \I,'~~": ~ P'.~.I'> '-,0 ~ 7 '" '5~It\ 7. 1 bS"
f P ;'11 Vi' . _Ll"J,.I.fU.'1 .r /..I1s1 1~5 1 I gq
:rthl(;.Rnf\Lf (lJl:IJ:_~ ;2. 17Q ~ z.eG I. 5 4'2-Z0
j Po" L" .J. . , 41 5 - ,!J - 0 -
! f.1eaJflu.l~f'I( P". t_. ..J q.qcJ '- .- 4qq ,.~t; 42.4
I i/.,A..... A, '" n ~/"""n (J ,,;.. ~(f Yo V; 1/1 ~.~ Q.-H. () ~ l) %0 ...!:f5- .Ji1:.p'.--- ...
I ~,JI\/if/l'''~ PI;"~ ".o~r..1 1020(, ..2.5' '2.'551.
I P'A-f!> t.!oA....:'n l'l.tI-Ott ,> \11~O ..2 2?>4w
I \I c>..... ~" f ,\.. .1.' .. n.l~~ Q : Ii t;"~ > 10 (\8' . 3 Yl" 4
l.~. .\' ;..,.. AJ" ~ .-1 9-nl;' I f eo').. . 8' 1 041
I') ~ J 'un" 410'~. or;. (~
nln."", ",,' 1U..h')I\«"I, _0- - ()-
rJlJr'.. lJ ,i;' liOn r 1481Q ..3 4~~3
1h1! QM.r UII)4J II 500 I. 2 'bOO
. ".
i ,A
, VII '/111/1,,-:
Ul ql t.twl
,-I
I
~.
,
/
...
.-.. --
-
-
_.~--
-
.-..-."
Square
Paae
Cf- 17-
I. fJ+ 4
Total VMpn 1'04' 4111 I c.p=
M...,.!. "..,,...,..tft,,lkl/~flf:r 12.1.C~
I
Ini tiah !
.
If Manual, mark *
If Estimate, mark **
. --.--------
Figure A-S.
Typical Worksheet Used in the Computation of Vehicle Mileage
A-l6
-------
We estimate that Enutu for each grid square is almost
certainly accurate to flO% and very likely to tS% or less. Thus,
a figure of 400,000 vehicle miles/day should be read 400,000 t 20,000.
Finally, all worksheets and raw data have been preserved and are avail-
able to those interested. .
.2.
Temporal distribution of traffic
It is commonly accepted that the hourly variation in weekday
traffic flow may be represented over a 24-hour period by a bimodal
distribution having peaks at the morning and afternoon rush hours
and a high plateau between these peaks. However, the parameters
n"eeded to describe this distribution--the height of each peak, the
height of the plateau, the time interval encompassing each peak--vary
from street to street. Shopping areas have a high frequency of traffic
between peak hours. . Streets in lower middle class neighborhoods
experience earlier morning and afternoon peaks than do streets in upper middle
class neighborhoods. Downtown streets carry light traffic fOllowing
the afternoon peak, whereas suburban and residential arterials have
higher traffic loads at this time. Ideally then, one would like to .
classify streets in accordance with a workable identification scheme,
applying an appropriate distribution for each class.
Classification was more easily postulated as theory than applied
in practice. We examined classifications of streets according to
geographical area, type of street (business, residential, warehouse,
etc.), and distance from major working centers, all with a notable lack
of success. The first and third classification schemes were probably
unsuccessful because of the large number of employment centers in
Los Angeles. Most large cities experience morning flows into vs.
out of town (and afternoon flows out vs. into town) in ratios of
between 2 and 3 to 1. In Los Angeles the ratio is more nearly 1 to 1.
The second scheme suggested proved most difficult to implement, as
the effort of classific.ation is so large.
Prior to examining classification schemes, however, we tested
the hypothesis that the traffic counts on 2S randomly selected streets
. (stratified with respect to the magnitude of daily traffic flow) represent
draws from a cOIlU1\on population--the "grand" distribution. * As might be
inferred from our need to examine classification schemes, the variability
among the distributions of traffic on the various streets was sUfficiently
great that, on statistical grounds, traffic flows could not be
represented by a "grand" distribution. However, we goon realized
that the 2 mile x 2 mile grid squares, the smallest spatial unit'
under consideration, commonly contained streets of many classifications.
Why not develop a "grand" distribution which, if not statistically
justified from street to street, was applicable to groupings of streets
defined by the grid system? .
sheets of the City of
summarized as number of
IS-minute interval
these statistics into
..
*Data were taken from the 24-hour traffic count
Los Angeles Department of Traffic. Counts were
vehicles passing over a pneumatic tube for each
throughout the day. For our analysis we lumped
hourly intervals. .
A-17
-------
In order to examine this question, we first derived an hourly
distribution of vehicle counts (i.e., the fraction of daily traffic
assignable to eaCh of 24 hourly periods) based on. an average of 52
randomly selected city streets .(again, the' sample being stratified
according to the magnitude of daily traffic flow), the counts on individual
streets being weighted in proportion to the magnitude of traffic flow on the
street. The resulting distribution was then multiplied by total
vehicle mileage per day for a particular grid square. These
calculated hourly vehicle mileages were then compared with hourly
vehicle mileages for the same grid square, determined using actual
hourly traffic counts. The calculated discrepancies in vehicle
mileage for each time period for the prototype grid square ares
Time Perio~*
Discrepancy
Approximate Percentage
of Dai~y Traffic Flow
6-7 a.m. **
7-9 a.m.
9-11 a.m.
11 a.m.-4 p.m.
4-6 p.m.
6-8 p.m.
-10.5\
0.3
- 7.0
4.0
- 6.0
- 3.1
3'
13
10
30
16
11
Given the levels of error inherent. in establishing photoche~cal reaction
rates, wind fields, and inversion heights--largely due to a paucity of
data--we believe that the magnitudes of these discrepancies fall within
acceptable limits. (Note: Traffic flows for the 6-7 a.m. period are
highly variable. While the 10.5\ discrepancy is somewhat large, its
net effect will be small due to the low traffic flow characteristic
of the time period).
The temporal distribution for freeways, not considered as a part
of the analysis just described, was more easily treated. ~7e were able
to acquire 15 minute count data for a 24-hour period at 31 locations
scattered throughout the Basin. As counts were available for 7 to 14
day periods, we computed an average figure for the Monday to Thursday
period. These averages exhibited only minor variations when compared
to an overall computed average ternpora1 distribution. Thus, this
overall distribution was taken as representative of temporal
variations in traffic flow on the freeways. . The temporal distributions
for both freeways and non-freeways are shown in Figure A-4 and Table A-I.
As was the case for the spatial distribution of traffic, all
calculations, worksheets, and data have been preserved and are
available to those interested.
*Local time.
times.
PDT when daylight savings time is in force, PST at other
**Note: Hourly traffic counts remain approximately constant within the
time intervals listed.
A-18
-------
3.
Pollutant. emissions rates
In this discussion we consider the three major automotive emissions
sources. Reference will ~e made to xi' Yij' e!jk' Kijk' and Wij'
as defined in section 1 of Part ~ describing the model.
Exhaust
Several test procedures for measuring exhaust emissions have been
proposed in recent years. These procedures have as their common aim
the simulation of emissions in a stationary test of a vehicle being
operated in traffic. There is currently considerable debate concerning
the degree to which the various test procedures are representative of
actual vehicular emissions, or, indeed, if it is possible to simulate
the emissions of a vehicle by any test procedure. A choice must also
be made between the use of a hot start and a cold start procedure.
A method which has enjoyed widespread use in recent years, includ-
ing adoption as the Federal testing procedure up to 1971, is the
California Driving Cycle (CDC). This is a seven-mode test procedure
and is based on a Los Angeles c~mnuter run (see State of California ARB
(1968». Recently, however, the representativeness of the CDC has been
questioned, and a new method, the 1972 Federal test procedure, has been
proposed. This procedure employs a cold start and a driving cycle (the
LA-4 cycle) derived from a Los Angeles driving route during he~vy
traffic periods. Actual mass emissions are monitored over the entire
driving cycle, in contrast to the CDC, in which concentrations are
measured. The differences between the three procedures -- hot start
and cold start CDCand 1972 Federal procedure -- are illust~ated by the
following figures (Siqworth (1971»1
Approximate increase in
emissions rates when
measured by cold start
CDC, as compared with'
hot start CDC (all
vehicles).
Approximate increase in
emissions rates when
measured by 1972 Federal
procedure, as compared
with cold start COC.
pre-1966
vehicles
1966-1969
vehicles
HC
CO
NOx
+30%
+0-10%
- 5%
+40%
+60\
+60\
+90%
+100%
+30%
It is apparent from these figures that measured emissions rates are
strongly dependent on the testing procedure employed.
A-19
-------
The purpose of this effort is to estimate an average emissions
factor applicable to vehicles operating on'both surface streets and
freeways in the Los Angeles Basin. It was felt that data obtained
using the 1972 Federal procedure, which was derived for heavy traffic
conditions, would result in inflated emissions rates when applied to
the whole basin. We thus based our calculations on data obtained
using the hot start CDC.We present in comparison, however, emissions
factors based on the 1972 Federal test procedure, which were derived
by the Air pollution Control Office, Environmental Protection Agency.
In the discussion that follows, calculational aspects central to the
estimation of exhaust emissions factors are outlined.
The total motor vehicle registrations for Los Angeles and Orange
Counties by make and model year are shown in Table A-3. The total of
pre-1958 autos was estimated from the California car age distribution,
Figure A-6, to be 12% of the total registration, and this figure was
distributed among the four manufacturers in proportion to their total
registrations from 1958 to 1969, less weighb being given to imported
models. Note that the age distribution given in Figure A-6 is derived
from 1967 data, as these are the most recent data available, it was
thus necessary to assume that the age distribution has not changed
between 1967 and 1969. xi and Yij' were computed directly from
Table A-3, and the results are shown in Table A-4.
The values of the volumetric exhaust emissions factors eijkwere
then estimated, using the data published by Hocker (1970a, 1970D) and
the mileage assumptions outlined in Section AI. These values of eijk'
shown .in Table A-5, are weighted according to the California car popula-
tion. For example, the emissions figures shown for Ford vehicles are
weighted in proportion to the numbers of Lincolns, Mustangs, etc., sold
in California, so as to account for ,different emissions rates from these
models.
The values of the conversion factors to cQnvert exhaust volume
emissions rates to grams/mile are given as a function of automobile
weight and are different for a vehicle equipped with automatic trans-
mission from one equipped with manual transmission (see Table A-8). The
average automobile weights, Wij, are shown in Table A-6. The figures
given are weighted in proportion to the number of a particular automobile
type sold by each manufacturer, as reflected by the national new car
registrations for that year.
To calculate
Kijk
'(= f (Wij»), we write:
Kijk = ~ij~jk + (1 - Vij)~jk
where
Ktjk =
K!jk =
constant for automatic transmission, Table A-8
constant for manual transmissions, Table A-8
~ij
... fraction of cars by jth manufacturer of model year
1 having automatic transmissions.
A-20
Figure A-6 and
Tables A-3 to A-8 follow'
-------
. +..- ++ -
'" 12
- -. ..- --. +
~~ . .-.--
cumulative distribution
extrapolated prior to 1960
:r
N
o
ill
~
Q) 10
>,
....
~
~
>,
.Q
(f) 8
s:::
0
-....
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k
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tJ\
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k 6
Q)
....
....
~
0
+'
::I
C1S
~ 4
0
Q)
tJ\
C1S
~
s::
Q)
U
k 20
Q) 2
a. t-
l,
100
-
. ..-
-
-
,..
..".
80.
...-.. ... ..
-+ . .'. -+. - - --.. . ... + -.-
... &
lIS
~
r::
Q)
to)
).I
Q)
60 a.
Q)
>
.....
~
C1S
....
~
to)
L..
40
i.
1
.
o
1969
'68
'67
'66
'65
'64
'63
'62
'61
'60
'59
'58
'57
'56
o .
Figure A-6. Age Distribution of California Automobiles
(1967 registration figures, updated to 1969)
[Taken from "Automotive Industries," March 15, 1968, p. 114]
-------
Table A-3. Total Vehicle Registrations in Los Angeles and Orange Counties*
(As of September 30, 1969)
Model Pre-
year 1958 1958-
Manufacture (Approx. ) 1965 1966 1967 1968 1969
- - -
General Motors
Corporation 233,723 948,665 156,550 143,327 127,866 75,197
Chrys 1er Corp. 63,568 227,571 48,955 4'3,529 47,960 22,530
Ford Motor
Company 138,927 545,338 112,555 94,338 64,611 41,144
Foreign 60,000 244,220 66,208 79,774 77,163 57,205
Total 3,720,924
:r
IIJ
....
Automobiles manufactured by General Motors, Chrysler, Ford, and
foreign corporations not included above (out of state, not
running, etc.)
110,110
, Automobiles manufactured by American Motors Corporation, Studebaker
COrPOration, Kaiser Jeep Corporation, Checker Motors
154,543
Miscellaneous
18,619
Unaccounted for (pick-ups, campers, etc.)
130,956
Total
4.135.152
In addition:
Motorcycles
Trucks
1'16,139
548,092
*Departuent of Motor Vehicles, State of California
-------
Table A-4. Fraction of the Total Automobiles in the
Los Angeles B&sin, by Model Year and Manufacturer
i &:0 Yij
i xi 1 2 3 4 5
1 0.662 j = 1 0.480 0.407 0.397 0.403 0.384
2 0.103 2 0.118 o. i27 0.120 0.151 0.115
3 0.097 3 0.278 0.293 0.261 0.203 0.210
4 0.085 4 0.124 0.124 0.221 0.243 0.292
..J
5 O. 053
Xi a fraction of total cars in the Los Angeles Basin of
model year i
where
i = 1
2
3
4
5
and including 1965
up to
1966
1967
1968
1969
T a total number of cars in Los Angeles Basin in Fall 1969
Yij a fraction of
XiT manufactured by
j = 1
2
3
4
General l~tors Corporation
Chrysler Cor,poration
Ford Motor Company
Foreign Manufacturers
A-22
-------
Table A-5. Concentrations of Volumetric Automo~ile
Exhaust Emissions, eijk *
i == 1 2 3 4 5
(pre-l966) (1966) (1967) (1968) (1969)
k == 1 (CO, %) 3.00 1.46 1.17 1.27 1.12
j == 1 (General Motors) 2 (HC,. ppm) 850 300 274 285 250
3 (NOx, ppm) 1075 1430 1480 1415 1525
1 3.00 1.65 1.40 1.10 0.75
2 (Chrysler) 2 850 .375 330 278 245
3 1075 1390 1535 1600 1665
1 3.00 1.57 1. 37 1.05 0.68
3 (Ford) 2 850 .360 320 295 260
3 1075 1540 1370 1495 1720
1 4.05 4.05 4.05 2.23 1.50
4 (Imports) 2 1732 1500 1300 526 362
3 1560 1560 1560 1424 1650
*Data for NOx emissions from domestic automobiles are obtained from Hocker (1970a),
for hydrocarbons and CO from domestic automobiles, from Hocker (197Ob). The data
for pre-1966 automobiles in these references were taken from a joint Federal,
State and Los Angeles City study, carried out in 1963. This study was based on
a 1000 car survey of vehicle population at that time. Data for imported
automobiles were obtained from A. J. Hocker, California Air Resources Board,
private communication.
A-23
-------
Table A-6. Average Automobile Weights, Wij*
(in pO\1I1ds)
j\i 1 2 3 4 5
- -
1 '\13600 3575 3575 3500 3650
2 '\13500 3475 3450 3400 3475
3 '\13300 3225 3325 3375 3500
4 '\12100 2100 2100 2125 2175
.J
Table A-7. Fraction of Automobiles Equipped with
Automatic Transmission, v..*
1J
j\i 1 2 3 4 5
1 0.75 0.859 0.879 0.898 0.912
2 0.75 0.900 0.917 0.924 0.917
3 0.75 0.819 0.862 0.906 0.882
4 0.00 0.010 0.030 0.060 0.100
*"Automotive Industries," Statistical Edition, published on March 15
of each year.
A-24
-------
~ab1e A-8. Multiplication Factors to Convert Exhaust Emission
Concentrations to Grams/Mile, Expressed as a Function of Vehicle Weight*
transmission Automatic Manual
weigh type
(~ounds ) HC x 10-3 CO NOx x 10-3 HC x 10-3 CO NOx x 10-3
1500 5.34 10.03 1.64 4.81 9.04 1.48
1750 6.28 11.79 1.93 5.64 10.60 1.73
2000 7.18 13.48 2.20 6.45 12.12 1.98
2250 8.02 15.07 2.46 7.16 13 . 54 2.22
25()0 8.82 16.56 2.71 7.92 14.86 2.43
2750 9.58 17.98 2.94 8.60 16.16 2.64
3000 10.28 19.30 3.16 9.24 17.35 2.84
3500 11.57 21.72 3.55 10.50 19.53 3.20
. 4000 12.70 23.84 3.90 11.39 21.39 3.50
4500 13.63 25.59 4.19 12.24 22.98 3~ 76
5000 14.39 27.02 4.42 12.92 24.27 3.97
5500 14.97 28.11 4.60 13.44 25.23 4.13
*State of California Air Resources Board
A-25
-------
The values of Vij are shown in Table A-7 and are weighted in the same
manner as Wij. Using the data contained in Tables A-6, A-7 and A-a, the
values of Kijk were estimated. The results are shown in Table A-9.
Finally, using the figures from Tables A-4, A-5 and A-9, the automobile
exhaust emission rates, ~,wer~ calculated. They are:
2co
... 51.0 "'e;,rams/mile
a
7.9 grams/mile
Q}{c
2Nox =
4.0 grams/mile
In addition to reporting an emissions factor for hydrocarbons, it is
necessary in the s~mulation of atmospheric reactions to consider separately
reactive and unreactive components in the exhaust. The composition of
automobile exhaust emissions have been determined in tests made by the
California Air Resources Board. The results obtained by them are reported
as percentages of "hydrocarbon compo~ents in the exhaust of controlled and
uncontrolled automobiles and are shown in Table A-lO.
Exhaust emissions measurements made on 135 gasoline powered trucks and
buses of all weight classes have been reported by Springer (1969). using
a driving cycle to simulate a Los Angeles truck route, he obtained the
following average emissions factors.
2co a 150 grams/mile
~C .. 11 grams/mile
2No "" 7 grams/mile
x
As trucks comprise 13% of the total vehicle registration in the Los Angeles
Basin (Table A-3), the exhaust emissions factors corrected for heavy-duty
vehicles, are:
Qco ... 0.87 x 51.0 + 0.13 x 150.0 "" 63.9 grams/mile
ORc
.. 0.87 x
7.9 + 0.13 x
11.0 ...
8.3 grams/mile
2No ... 0.87 x
x
4.0 + 0.13 x
7.0 ...
4.4 grams/mile
Previous comments concerning the representativeness of automobile emissions
factors also apply to those for trucks.
In contrast, the Air Pollution Control Office (Slgworth (1971» has
estimated the following exhaust emissions factors to be applicable to
the Los Angeles area as of 1969:
Qco
.. 91.0 grams/mile
QHc " II: 11.7 grams/mile (including blow-by)
2No ...
x
7.0 grams/mile
Tables A-9 and A-I0 follow
A-26
-------
Table A-9. Multiplication Factors to Convert Volumetric
Exhaust Emission Concentrations to Gramsj}fi1e, Kijk
i .. 1 2 3 4 5
- - -
k = 1 21.625 21.690 21.'734 21.480 22.107
j a 1 2 (x 10-3) 11.505 11.545 11.567 11.433 11.799
I
3 (x 10-3) 3.533 3.551 3.558 3.514 3.623
1 21.160 21.380 21.299 21.113 21.417
2 2 (x 10-3) 11.263 11.388 11.309 11.216 11.408
3 (x 10-3) 3.463 3.494 3.482 3.444 3.499
1 20.200 20.061 20.593 20.944 21.445
3 2 (x 10-3) 10.810 10.701 10.965 11.174 11.414
3 (x 10-3) 3.315 3.318 3.371 3.423 3.509
1 12.700 12.714 12.743 12.928 13.322
4 2 (x 10-3) 6.750 6.758 6.773 6.848 7 .073
3 (x 10- 3) 2 . 070 2.072 2.077 2.115 2.165
A-27
-------
, ,
Table A-lO. Mean Concentrations of C2-C6 Hydrocarbons
in Automobile Exhaust*
(based on California Driving Cycle)
Controlled Uncontrolled
Cars Cars
Composite " Composite
Compound ppm C wt \C ppm C wt \C
Ethane ** 11.3 1.5 27.6 1.4
Ethylene 177 24.1 367 17.8
Acetylene ** 98 13.2 252 13.6
Propane 0 0 0 0
I
Propylene 7B 10.5 204 9.9
Isobutane B.7 1.2 24.3 1.1
Propadiene + He Acetylene 22.4 3.1 36.4 1.B
n-Bu tane 39.5 5.5 116 5.5
Isobutene + Butene-1 41.3 5.7 106 5.2
Butene-2, cis & trans 19.2 2.7 76 3.6
Isopentane 77 10.5 242 11.4
B-MethYlbutene-l 9 1.2 18 0.9
n-Pentane 42 5.B 129 6.1
Pentene-1 14.5 2.1 50 2.3
Pentene-2, c & t 3.5 0.5 37 1.7
2,2-Dimethy1butane 1.0 0.1 0 0
2-Methy1butadiene-l,3 10 1.5 6B 3.1
2-Methy1pentane 37 5.0 114 5.4
4-Methylpentene-2 12 1.7 58 2.8
3-l-1ethy 1pentane 15 2.1 46 2.2
Unidentified 0 0 19 0.9
n-Hexane 13 1.8 52 2.5
Hexene-1 3 0.4 21 1.0
Totals 732 100.2 2090 100.2
.. ~J .1
. J
.1 J
& J.L -----
*Taken from: "Light Hydrocarbons in Engine Exhaust and the Los Angeles Atmosphere,"
Air Resources Board, State of California, Fall 1969. .
**Assumed unreactive. All other hydrocarbons considered reactive.
A-28
-------
These figures are based on the 1972 Federal test procedure, yet were
derived from esse~tially the same emissions data base used by us. It
should be understood that while CDC emissions factors have been
adopted for the current study, we are unable to assess the degree,to
which the two driving cycles (or,' for that matter, any driving cycle)
are representative of actual vehicle performance in a particular
locale. Hence, our figures may be subject to revision as more data
become available.
Blow-by
The approximate magnitude and composition of blow-by emissions
from an uncontrolled automobile are shown in Table A-II.
Estimates of blow-by emissions rate have been made by the Air
Pollution Control Office (Si~lorth (1971». 'Their estimate for the'
blow-by rate from an uncontrolled automobile;(pre-196l domestic or
pre-1965 import) is 4.1 ,grams/mile. The PCV devices on 1961, 1962,
and 1963 domestic vehicles are assumed to be about 80% effective in
controlling blow-bY1 emissions from these vehicles are thus about
0.8 grams/mile. The PCV devices on 1964 and later cars are assumed
to be 100% effective, hence there are no blow-by emissions from these
vehicles.
unfortunately, there appears to be no way of finding the number of
1955-1962 domestic autos which have been resold between 1964 and 1969,
thus necessitating the fitting of a PCV valve. We have estimated the
number of pre-196l domestic autos fitted with PCV valves to be 60% of
the total. Using the vehicle age distribution curve, Figure A-I and
Table A-3, pre-19~1, 1961 to 1963 domestic and pre-1965 imported auto-
mobiles are seen to comprise approximately 19~, 20%, and 7%, respective-
ly, of the total automobile registration. Hence, blow-by emissions from
the average vehicle,in the Los Angeles Basin (automobiles comprise 87%
of all vehicles) are:, ' '
'-
0.87 (0.4 x 0.19 x 4.1 + 0.07 x 4.1 + 0.20 x 0.8) = 0.7 grams/mile
Evaporation
Evaporative losses from autos are very difficult to measure and
are subject to wide variations in magnitude resulting from different
auto operating conditions, weather conditions and automobile design.
The subject is discussed by Hurn (1968, page 62), who reports for
evaporative losses the figures reproduced in Table A-12. using Hurn's
figures, the total daily evaporative loss per vehicle is:
(0.068 + 0.091) pounds/day = ~2 grams/day
A-29
Tables A-II and A-12 follow
-------
Table A-ll. Estimated Automobile Emissions Attributable
to Exhaust and Blow-By*
Blow-By Exhaust
Weight Weight
Component Concentration (pounds/day) Concentration (pounds/daY)
CO Trace Nil .3.12\ 4.160
NOx Trace Nil 850 ppm 0.202
Hydrocarbons
Paraffins
:r Cl-C5 3150 ppm 0.033 130 ppm O. 034
w
0 C6 & heavier 4780 ppm 0.072 155 ppm 0.073
Olefins
C2-C4. 230 ppm 0.001 500 ppm 0.079
C5 & heavier 1420 ppm 0.017 30 ppm 0~012
Aromatics
Total less benzene 5150 ppm 0.089 190 ppm 0.100
Benzene 270 ppm O. 003 75 ppm 0.029
Acetylenes 60 ppm O. 001 285 ppm 0.036
Total Hydrocarbons 15060 ppm 0.216 1365 ppm 0.363
*Taken from Hum, R. W., "Air POllution," (A. Stern, Ed.>, Vol. III, Academic Press, 2nd Edition
(1968).
- ,
-------
Table A-12.
Evaporative Losses From Automobiles.
Co:mponent
Hydrocarbons (pound/day)
Tank Loss Carburetor Loss
Paraffins
C1-CS
C6. & heavier
0.039
0.010
0.029
0.040
01efins
C2-C4
Cs & heavier
O. 001
0.013
0.001
0.016
Aromatics
Total 1ess"benzene
Benzene
0.003
0.002
0.004
0.001
Total
0.068
0.091
*Taken from Hurn, R. w., "Air POllution," (A. Stem, Ed.), Vol. III,
Academic Press, 2nd Edition (196B}.
A-31
",
-------
Carburetor evaporative losses occur mainly during the periods
after a hot engine is stopped. The loss during this period is about
o
18 grams for a 90 F ambient temperature (see Hurn (1968), Figure .5,.
page 64). Tank losses occur primarily as a result of temperature
changes in the tank fuel and in the vapor volume, which induce a
pumping action alternately admitting air into and expelling vapor
from the tank. Depending on the direction of temperature changes,
tank fill, and tank agitation, the vapors may be discharged at any
time, with the vehicle either operating or stationary.
In order to distribute the evaporative emissions, it was assumed
that these losses occur mainly during the hours 7 a.m.-7 p.m. PDT and
that they are evenly distributed over this period. Hence, the. evapora-
tive emissions rate from the 4,135,000 automobiles registered in Los
Angeles and Orange Counties is 4,135,000 x (72 grams/vehicle/day) or
(4,135,000 x 6) grams/hour.
The evaporative emissions in each square are assumed to be propor-
tional to the number of non-freeway vehicle miles in that square. Non-
freeway vehicle mileage was chosen as being more representative than
any other figure of driving conditions leading to high evaporative
emissions, in particular, cars being parked and stop-go driving. The
total non-freeway vehicle mileage in the Los Angeles Basin is 72,367,000,
thus, the evaporative emissions for squareij are
mij
x
4 135 000 -3
i2,3~7 x 6 x 10 = 0.343mij ki10grams/hour
where
mij
= thousands of non-freeway vehicle miles per day driven in
square ij, as given in Figure A-3.
References
Hocker, A. J., "Surveillance of Motor Vehicle Emissions in California,"
Quarterly Progress Report *19, California Air Resources Board
(March 1970). [aJ .
Hocker, A. J., "Exhaust Emissions from Privately owned 1966-1969
california Automobiles: A Statistical Evaluation of Surveillance
Data," Supplement to Quarterly Progress Report #19, California'
Air Resources Board (July 1970). [bJ
Burn, R. W., "Air Pollution,", (A. Stern, ~d.), yolo III, Academic
Press, 2nd edition (1968). .
Larson, G. P., et al., "Distribution and Effects of Automotive Exhaust
Gases in Los Angeles," S.A.E. Technical Progress Series, Vol. 6
(1955) .
Ozolins, G. and R. Smith, "Rapid Survey Technique for Estimating
Community Air Pollution Emissions," Public Health Service Pub.
No. 999-AP-29 (1966).
A-32
-------
Rehmann, C. R., "Motor vehicle Exhaust-Emissions--Gary, Indiana,"
public Health Service, National Center for Air Pollution Control
publication APTD-68-5 (1968), CFSTI #PB195l56.
Rose, A. H., Jr., et al., "Comparison of Auto Exhaust Emissions from
Two Major Cities,"JAPCA, '15, (August, 1965).
-
Siqworth, H. W., Bureau of Air Pollution Sciences, Environmental
, Protection Agency, private communication (May, 1971).
Springer, K. J., "An Investigation of Emis~ions from Trucks Above
6000 lb-GVW Powered by Spark-Ignited Engines,"Final Report
prepared for U.S. Public Health Service, under Contract No.
PH 86-67-72, Southwest Research Institute (March, 1969).
State of California Air Resources Board (ARB), "California Exhaust
Emissions Standards for Test Procedures for Gasoline-Powered
Motor Vehicles," (November 20, 1968).
II.
AIRCRAFT EMISSIONS
Aircraft operating from the fifteen airports in the Los Angeles
Basin contribute approximately 2\ of nitrogen oxides, 4\ of organic
qases and 3% of carbon monoxide from all sources in the Basin (See
Section V). Whereas the contribution of aircraft emissions to the
total contaminant load in the Basin is small, the percentages of
pollutants in the local environs that are attributable to aircraft
operations is quite significant. Furthermore, several of the con-
taminant monitoring stations are located in the vicinity of airports.
Thus, it was necessary to devise a special model to account properly
for the local impact of aircraft emissions.
The aircraft emissions modei developed for this project consists
of two major parts: ground operations and airborne operations.
Emissions' from these operations are treated as lumped volume sources~
generated in the cell into which they are injected. The first part
of this section describes the emissions model adopted, and the second
part presents relevant data.
A.
Aircraft Emissions Model
Aircraft operations are classified as ground operations and
airborne operatio's. Ground operations consist of three distinct modes:
(1)
Taxi mode
.
taxi between runway and satellite upon landing,
taxi between satellite and end of runway and
await clearance for take~off, and
idle at satellite.
.
.
(2)
Landing mode
.
touchdown on runway to turn-off from runway.
A-33
-------
(3)
Take-off mode
start of take-off run .to lift-off from runway.
Airborne operations are comprised of two modes:
(1) Approach mode
.
descent from invers~on height*-to touchdown,
(2)
Climb-out mode
. lift-off to attainment of inversion height.
A .flight, whether for fixed wing aircraft or rotocraf~, is defined to
consist of the five modes cited.
Several assumptions apply to the treatment of aircraft operations
in the emissions model:
(1)
For every aircraft arrival, there is one departure.
Furthermore, arrival and departure rates are equal within
each time period. (Pertinent tirne periocs arc shown in Table A-l9.)
(2)
Aircraft follow straight line flight paths from inversion
height to touchd~~n and from lift-off to inversion height.**
(3)
The angles of ascent and descent of all aircraft at a
.p~rticular airport are assu~ed to be fixed and equal to
those angles associated with the class of craft (e.g.,
medium range jet transport, business jet, etc.) having
the highest fraction of total operations at that facility.***
(4)
Flight paths originate and terminate at the most frequently
used .runway at each airport.
(5)
The proportion of aircraft of a given class that arrive and
depart from each airport is invariant with time.
.
*Inversion height refers to the elevation of the base of the inversion
above sea level.
**Many light aircraft never reach inversion height and in fact often do
not follow straight line paths above 800 feet. However, information
concerning these departures from linear flight paths is not available.
***This assumption is reasonable for twelve of the fifteen Los Angeles
Basin Airports; as at these facilities the fraction of total operations
assignable to a particular class of aircraft exceeds 0.81. (See Table
A-18.) The exceptions are Los Angeles International (LAX), Hollywood/
Burbank (LK) and Culver City (CC) Airports. At LAX Class 1 and Class
.2 aircraft, transports having similar flight paths, coroprise 63\ of total
daily flights and contribute by far the greatest fraction of contaminants.
Class 6 aircraft represent 68\ of air traffic at k~, while at CC.
total daily traffic is very light.
f.1oreaccurate, but thus far unwarranted, alternative calculations
include:
(a)
Angles of ascent and descent compute~ as the weighted sum of the
angles assign~~le to each class of aircraft, weighting being in
proportion to the mass emissions of each class.
(b) computation of individual flight paths for each class.
A-34
-------
(6)
The temporal distribution of flight operations at a Basin
ai~ort, if not known, may be represented by the temporal'
distribution measur~d at an. ai~ort at which the mix of
aircraft, by class, most closely resembles the mix of .
aircraft at the airport in question.*
It should be noted that emissions along flight paths contained within,
but originating from airports lying just outside of, the Basin boundary
are ignored (e.g., Ontario International, El ToroMarine Base, etc.)
Turning now to aircraft emissions, we have made the following
assUllq)tions:
(1)
For each class of aircraft, pollutants are emitted at a
uniform rate during each of the five operating modes.
Thus, for airborne operations, the amount of contaminants
injected into a cell is proportional to the length of the
flight path occupying that cell.
(2)
Aircraft emissions can be treated as volume sources, well-
mixed in the cell into which they are injected. [This is
in contrast to the treatment of automobile emissions, which
are taken to be fluxes at the ground.]
(3)
Emissions from aircraft can be treated as continuous
releases, emitted at a uniform rate and averaged over a
one-hour time period, one hour being the resolution of the
temporal distribution of airport traffic.*.
(4)
Emissions indices measured for one aircraft are representa-
tive of all aircraft of that class.
Groound Ope rations Mode l
The amount of contaminant species k emitted into a surface cell
during ground operations is equal to the summed products of average
emissions rates and residence times in each of three modes--taxi, landing,
and take-off. The rate of emissions, in pounds per minute, into any
ground cell ijl due to ground operations for the hourly period t is
given by: .
1 -3 7 3
~jm.t ,m=l = 0 K dtClij L nuMuI; f~Cgu
u=l gel
*Tempora1 distributions are available for the. following airports: Los
Angeles International (Class 1 aircraft predominate), Van Nuys (Class 6)
and HOllywood/Burbank (Class 6). Of the remaining twelve airports, ten
are predominantly Class 6 (the exceptions being Los Alamitos and Culver
City), and the Van Nuys distribution is assumed to be representative of
flight operations at these airports.
**This assumption is reasonable when the time step for numerical integration
of the overall airshed model is comparatively long (5 to 10 minutes in
the case of non-reacting species), but may be questionable in treating
photochemical reactions, when shorter time steps are required.
A-35
-------
where
,and
i,j are indices for the x,y (horizontal) coordinates,
m is an index for the z (vertical) coordinate and m. ~ 1
for the ground 'cells,
1 is an index representing the hourly period of the day,
k is an index representing individual pollutants
1
2
3
4
CO
hydrocarbons
NO
N02
. ,
9 is an index denoting ground operations modes
1
2
3
taxi
landing
take-off
u is an index denoting aircraft class
1
2
3
4
5
6
7
long-range jet transport
medium range jet transport
business jet
turboprop transport
piston engine transport
piston engine utility
turbine engine helicopter
k
Qijm1 = emissions rate of species k into cell
time period 1 (pounds per minute)
ijm
during
dt = fraction of total daily flights assigned to hourly
period 1 (see Table A-19)
aij = fraction of airport area assignable to ground cell
ijl
K = 60 (minutes/hour)
nu = number of flights per day of aircraft of class
Table A-IS) .
u
(see
Mu = average number of engines per aircraft of class
(see Table A-IS)
u
f~ = pounds of pollutant k
consumed by aircraft of
9 (see Table A-14)
emitted per 1,000 pounds fuel
class. u operating in mode
Cgu = pounds of fuel consumed per engine of aircraft of class
u operating in mode g (see Table A-IS).
A-36
"
-------
Flight Operations Mode],
The mass of species k emitt~d into cell ijm during app~oach
is assumed to be proportional to the length of the flight path
occupying that cell. The correspond~ng rate of emissions is given
by:
k 10-3dR,Pijm ~ k ~
Qij~ = ~nuMufucu ;r
K u=l -u
(A-I)
where
tu = time spent in descent from inversion height to touchdown
by aircraft of class u
~ :: time spent in descent from 3000 feet above ground elevation
to touchdo'Nn by aircraft of class u (see Table A-16)
f~ :: pounds of pollutant k emitted by aircraft of class u
per 1,000 pounds fuel consumed during descent (see Table A-14)
Cu = pounds of fuel consumed per engine of aircraft of class u
during descent from 3000 feet above ground elevation (see Table A-IS)
Pijm:: fraction of the,length of the flight path* assignable to cell
The mass of species k emitted into cell ijm during oZimb-out is
also given by Equation (A-I), where tu and f~ now apply to an
aircraft ascending from lift-off to inversion height, and tu and
Cu to an aircraft ascending to 3000 feet above ground elevation.
ljm**
As all concentration units in the airshed model are expressed as
parts per million (ppm), the following conversion formula is used:
~jm (~:) = 106vQ~~m
. V ijmW
where
~jm D emissions rate of species
k
(pounds per minute)
*The length of the flight path is measured from the base of the inversion to
touchdown.
**Cells' ijm vary in height from column to column (i.e., over i and
j) to account for spatial variations in inve~sion height at any instant
in time. This peculiarity in the definition of cells complicates the
calculation of Pijm. The algorithm we have employed for this computation
is thus somewhat involved and will not be described here. For full details
see the description and listing of the computer program in Appendix F.
A-37
-------
Wk = molecular weight of species
k
Vijm = volume of cell
ijm,
cubic feet
v = 319 cubic feet per pound mole, the molal volume of an ideal
gas at 1 atmosphere and 600 F.
B.
Emissions and Airport Data
As was the case for automobile emissions, the aircraft emissions
model has been formulated to utilize available data as effectively as
possible. Data may be conveniently classified as infoDnation pertaining
to (1) aircraft location and (2) aircraft emissions. Included in the
former category are airport location and, for each airport, flight
paths and runway and taxi-way coordinates. This infoDnation is available
from U.S. Geological Survey maps, FAA documents and maps, and the.
administrations of individual airports.
Major aircraft emissions studies have been reported by the Los
Angeles County Air Pollution Control District (Lemke, et ale (1965)
and George, et ale (1969», the National Air Pollution Control Administra-
tion (Hochheiser and Lozano (1968) and Lozano, et ale (1968», and
Northern Research and Engineering Corporation (Northern Research (1968)
and Bastress and Fletcher (1969». [The three groups will be referred
to as LACAPCD, NAPCA, and NREC, respectively]. The NREC study is the
most recent and comprehensive of the three, and includes the results
of the LACAPCD and NAPCA efforts. For this reason we have relied
primarily upon emissions statistics cited in Northern Research (1968).
Pertinent emissions data are given in Tables A-14 and A-IS, while
airport and aircraft classification and operations data are presented
in the remaining tables in this section and in Pigure A-7. In particular,
classification of aircraft by type (definition of subscript u) is shown
in Table A-13. Mass emissions of pollutants per unit of fuel consumed
are tabulated in Table A-14 for the various classes of aircraft and
operating modes. Fuel consumption rates as a function of aircraft
classification and mode of operation are given in Table A-IS.
Aircraft performance characteristics for flight operations and
take-off and landing are presented in Tables A-16 and A-17. Character-
istics include, for each class of craft, the average distance over which
the operation is performed, the time required, and, for approach and
climb-out, the angles of descent and ascent. The average number of
flight operations occurring per day at each of the fifteen Basin airports
is tabulated, by class of aircraft, in Table A-IS. The distribution of
daily operations, by hour, for three major Basin airports is given in
Table A-19. Finally, the primary flight paths for each airport are
shown in Figure A-7.
Figure A-7 and
Tables A-l3 to A-19 follow
A-38
-------
:1
25
M
-'--~- ..,.....
23
22 2'1
11 ,2.1
2-D
(8
, J7
-t- "
(,
. I j IS'
'-- I
If
1
,
Figure A-7.
Approach and Climb-Out Paths for the Fifteen Los Angeles Basin Airports
center of .#-
ai'Port", ~approaCh
~mb-out path.
path*
*Approach and climb-out
are measured from 3500
rum-lay elevation.
distances
feet above
A-39
-------
Table A-13. Aircraft Classifications
(Northern Research (1968»
Representative Engine
Aircraft Manufacturer
u Type. Examples and Model ~
1 Long-range Boeing 707 Pratt & \'lhitney Turbofan
jet transport Douglas DC-a JT3D.,
2 Medium-range Boeing 727 Pratt & \'lhi tney Turbofan
jet transport Douglas DC-9 JT8D
3 Business jet Lockheed Jetstar Pratt & Whi tney Turbojet,
North American JT12
Sabreliner
4 Turboprop Lockheed Electra Allison Turboprop
transport Fairchild Hiller 50l-D13
FH-227
5 Piston-engine Douglas DC-6 Pratt & Whitney Radial
transport Convair 440 R-2800 piston
6 Piston-engine Cessna 210 Continental Opposed
utili ty Centurion 10-520-A piston
Piper 32-300
Cherokee Six
7 Turbine-engine Sikorsky 5-61 General Electric Turboshaft
helicopter Vertol 107 CT58
*The dates chosen for validation of the overall airshed model are
September 29 and 30, 1969. An eighth aircraft type, the jumbo jet
transport, is not included in this list, as the Boeing 747 was not
in service at this time. '
A-40
-------
Table A-14. Emissipns Factors, fyu and f~
(Northern Research (1968)
Emission factors, f~u and f~
(pounds/lOOO pound~ of fuel)
Aircraft Operating
Class Mode CO Organics NOx
u = 1 Idle & Taxi 174 75 2.0
Approach 8.7 16 2.7
LTC. 0.7 0.1 4.3
2 Idle & Taxi 50 9.6 2.0
Approach 6.6 1.4 2.7
LTC 1.2 0.6 4.3
3 Idle & Taxi 118 11.5 2.0
Approach 11 0.6 2.7
LTC 4 0.3 4.3
4 Idle & Taxi 24.8 8.1 3.7
Approach 1.6 0 2.9
LTC 2.3 3.2 3.1
5 Idle 600 160 0
Taxi 900 90 3
Approach 800 60 5
LTC 1250 190 0
6 Idle 600 160 0
Taxi 900 90 3
Approach 800 60 5
LTC 1050 110 1
7 Idle & Taxi 118 11.5 2.0
Approach 11 0.6 2.7
Climb-out 4 0.3 4.3
*Land, Take-Off and Climb~Out
A-41,
"
-------
Table A-IS. Fuel Consumption Durinq Landinq and Take-Off
Operations for Representative Enqines
(Northern Research (1968»
Fue 1 Consumed, Cqu and Cu (pounds per enqine)
Take- Total
Aircraft Representative Landinq Off Climb- LTO-
Class Engine Taxi Idle Run Run A£Proach'" Out:" ~c1e
-
u = 1 Pratt & Nhitney 217.4 18.1 36.4 158.5 298.2 279.0 1007.6
JT3D
I
2 Pratt & Whitney 184.0 15.3 16.1 103.5 141.3 196.7 656.9
JT8D
3 Pratt & Whitney 108.0 9.0 12.9 22.3 47.1 22.3 221.7
JT12
:r 4 Allison 118.8 8.5 4.9 20.4 66.9 97.8 317.4
A 501-D13
I>J
5 Pratt & Whitney 72.0 2.7 5.3 21.0 36.8 140.0 277.8
R-2800
6 Continental 5.6 0.4 0.1 0.9 2.7 4.7 14.4
10-520-A
7 General Electric 37.0 3.0 0.0 0.0 59.4 77.0 176.4
CT58
*Between qround elevation and 3000 feet.
-------
Table A-16.
Aircraft Performance Characteristics During
Approach and Landing Operations
(Northern Research (1968»
'~-..... .
I .
i I ~ - -'
I Approach I
I
Landing
I
I
C
Stop
A
Aircraft at
3000 feet*
B
Touchdown
SAB
~ = tAB
Distance A to B
SBC
Distance B to C
Time to Travel A to B
tBC
Time to Travel Bto C
A Angle of Descent
Aircraft SAB tAB Sse tse ).
Class (Miles) (l-1inutes) (Feet) (Minutes) (Degrees)
,
u a 1 9.4 3.6 2800 0.4 3.46
2 9.0 3.0 1900 0.3 3.61
3 6.0 1.6 1900 0.4 5.41
4 10.3 4.5 1700 0.3 3.16
5 9.0 4.6 2330 0.6 3.61
6 5.0 3.8 1000 0.3 6.48
7 15.0 6.5 0 0 2.17
Durations of idle and taxi modes are assumed to be 1 and 12 minutes
respectively for classes 1 through 6, and 1 and 6 minutes for class
7 (helicopters).
*Above ground elevation.
A-43
-------
Table A-17.
Aircraft Performance Characteristics During
Take-Off and Climb-Out Operations
(Northern Research (1968»
I
I
Climb-Out I
I
F
Aircraft at
3000 feet
I Take-Off
I
D
Start Take-
Off
I
I
E
Lift-Off
SDE
Distance D to E
~EF
..D>istance E to F
tDE
Time to Travel D to E
tu = tEF.
Time to Travel E to F
e Angle of Ascent
Aircraft SDE tDE SEF. .tEF e
Class (Feet) (Minutes) (Miles) (Minutes) (Degrees).
u II: 1 9300 1.0 8.1 2.2 4.01
2 6075 0.8 6.5 1.9 5.00
3 2800 0.4 4.0 0.5 8.08
4 3280 0.6 10.6 3.6 3.07
5 3150 0.6 14.8 5.0 2.20
6 1545 0.4 6.3 2.5 5.15
7 0 0 15.0 6.5 2.17
r
A-44
-------
Table A-18. Average Number of Aircraft Flights Per Day at Los Angeles Basin Airportsl,2
~rcraft
Airport Class 1. 2 3 4 5 6 7
-
Brackett. 0 0 6(1.5) 0 0 288 (1.0) 10(1.0)
CoItpton 0 0 0 0 0 191 (1.0) 0
Culver City 0 0 125 (1.0) 0 0 21(1.9) 20(1.0)
El Honte 0 0 0 0 0 700 (1.0) 0
Hawthorne 0 0 0 0 0 428 (1.0) 0
Hollywood/Burbank 0 47(2.5) 19(2.0) 4(2.8) 25 (4.0) 225 (1.6) 10(1.0)
Long Beach 0 0 2(2.0) 0 67 (4.0) 591(1.4)3 25 (1.0)
Los Alamitos4 0 0 3005 (1.0) 0 50(2.0) 0 0
Los Angeles Int'l. 331(4.0) 196(2.9) 9 (1. 0) 57(2.9) 21(3.2) 159(1.4)3 58 (2. 0)
Orange County 0 12 (2.0) 0 0 0 850(1.4)3 0
San Fernando 0 0 0 0 0 100 (1.1) 0
Santa Monica 0 0 3 (2.0) 0 0 525 (1.1) .25 (1.0)
-:r Torrance 0 0 0 0 0 500(1.1) 0
01:00 Van Nuys 0 0 25(2.0) 0 14 (4.0) 720(1.0) 125(1.0)
V1
Whiteman '0 0 0 0 0 200(1.1) 0
11968 'data.
2Numbers in parentheses are average numbers of engine per aircraft.
3 (Northern Research (1968».
Total national average--FAA controlled terminals
4Airport closed March 1, 1971.
5Class 3 activity at this tennina1is mostly military aircraft. Military engines are estimated to be
equivalent to six Class 3 aircraft engines. Thus, numbers of flights shown are actual flights "..
multiplied by six.
-------
Table A-19. Temporal Distributions of Daily Flights
at Three Los Angeles Basin Airports
Time Period*
Fraction of
Daily Traffic
Los Angeles Internationa1**
11 p.m.-1 a.m.
1-7
7-8
8 a.m.-6 p.m.
6-8
8-9
9-11
.048
.051
.043
.629
.109
.048
.072
Van Nuys***
10 p.m.-8 a.m.
8-9
9-10
10-12 noon
12-4
4-5
5-7
7-8
8-9
9-10
.017
.014
.056
.156
.511
.078
.103
.036
.021
.008
~.oll)'Wood/Burbank * * *
11 p.m.-1 a.m.
1-7
7-9
9-12 noon
12-1
1-4
4-8
8-9
9-11
.026
.021
.063
.193
.087
.164
.314
.062
.070
*Distributions are approximately uniform within each time
period.
,
**Derived from hourly distributions for the period
June 1, 1970 through June 30, 1970.
***Derived from hourly distributions at an unspecified
weekday in 1970.
A-46
-------
References
Bastress, E. K. and R. S. Fletcher, "Aircraft Engine Exhaust Emissions,"
presented at American Society of Mechanical Engineers Annual
Winter Meeting, Los Angeles (November 16-20, 1969)..
George, R. E., J. A. Verssen, R. L. Chass, "Jet Aircraft--A ~rowing
Pollution Source," presented at 62nd Annual l1eeting of APCA,
paper 69-191 (June 1969).
Hochheiser, S. and E. R. Lozano, "Air Pollution Emissions from Jet
Aircraft Operating in the New York l-Ietropoli tan Area," presented
at Air Transportation Heeting, New York (April 29-May 2, 1968).
Lemke, E. E., N. R. Shaffer, and J. A. Verssen, "Air Pollution From
Aircraft in Los Angeles County," report of the Los Angeles County
Air Pollution Control District (December 1965).
Lozano, E. R., ~1. ~1. Melvin, Jr., S. Hcchheiser, "Air Pollution
Emissions From Jet Engines," JAPCA, !! (June 1968) p. 392-394.
Northern Research and Engineering Corporation, "Nature and Control of
Aircraft Engine Exhaust Emissions," (November 1968) CFSTI #PB 187771.
III.
FIXED SOURCE EMISSIONS--pa1ER PLANTS AND REFINERIES
The eleven power plants situated in the Los Angeles Basin emit
approximately 17% of NOx from all Basin sources. The fifteen oil
refineries contribute an additional 9 % of NOx and 7, of organic gas'
emissions (see Section V). Although emissions from these large point
sources can result in elevated groun~ concentrations in their immediate
vicinity, we have chosen not to incorporate calculations in the present
grid model to account for this effect. However, because of the high
emissions rates from. these sources, and their special emission character-
istics, it is unrealistic to treat them simply as area sources. In the
first two parts of this Section, we describe the methods of incorporating
the emissions into the overall grid model and summarize pertinent data
relating to power plants and refineries. Finally, in the third part, we
describe in detail a method for estimating concentrations resulting from
large point sources. We then make suggestions for possible methods of
estimating concentrations for reacting gases and unsteady conditions.
A.
Power Plant Model
High emissions rates from point sources can result in high local
ground concentrations. For power plants of the size found in the
A-47
-------
Los Angeles Basin and under typical meteorological conditions, maximum
ground concentrations occur at distances from the plant of the order
of two miles. If the power plants were treated simply as area sources,
it would not be possible to predict these high concentrations and the
locations of their occurrence using a grid of two-mile resolution. On
the other hand, one can argue that a more detailed treatment of plumes
(such as the use of established plume dispersion models) may not be
warranted, given the expected accuracy of prediction associated with
a two-mile grid. However, such a treatment of plumes may in fact be
necessary in model validation when the air quality data with which
predictions are to be compared are collected at monitoring stations in
the immediate vicinity of a power plant.
If power plants are to be treated as point sources, it is necessary
to perform a plume calculation in addition to the calculation of
concentrations through numerical integration of the continuity equations.
Ground level concentrations of non-reacting contaminants at a point
are computed by adding concentrations due to power plant emissions to
concentrations at that point resulting from contaminant emissions from
other sources. Before adopting this procedure, however, it seemed wise
to determine if it was required for validation of September 29 .and 30
data.
Of the sixteen contaminant monitoring stations in the Basin, only
those at Redondo Beach (RB), Burbank (BURK), and Pasadena (PASA) are
located within five miles of power plants. RB measures 502 alone. The
power station at Burbank is located a mere 100 to 200 meters from BURK;
BURK thus receives virtually no NOx from that source under normal daytime
conditions. (Early morning fumigation will give rise to high concentra-
tions at BURK. No attempt was made to model this phenomenon ,in the
current study.) Only PASA, about 2,000 meters ENE of the Pasadena power
station, is likely to detect elevated NOx emissions. The data of
September 29 and 30, 1969, however, do not confirm this hypothesis.
NOx levels at PASA follow the pattern. observed at other stations, and
in fact are quite low during the day. Since none of the air quality
lI'easurernents used for validation were likely to be influenced by the
presence of power plants, we chose not to include plume dispersion
calculations in the model for the current validation studies. However,
we have proposed a simple method for handling these calculations, should
they be required in future validation programs and in the exercise of
the model. This procedure, applicable to steady-stat~ non-reacting
plumes, is described in some detail in Part C.
While power plant and refinery emissions are not treated as plumes
in the model, it was believed inappropriate simply to consider power
plant emissions as well mixed in the cell into which they are injected.
Instead, these emissions are distributed as volume sources downwind of
the plant, in cells where the plume width has grown to be of the order
of the 'cell size. This procedure is outlined in the first section of this
Part. In the second section we present all pertinent data relating to
power plants and their emissions. In contrast, refinery emissions are
treated as area sources and are discussed in Part B.
A-48
-------
1.
Treatment of point-source emissions as volume sources
A Gaussian dispersion model was used tq evaluate the possibility
of treating point source emissions as volume sources centered in grid
squares dowmdnd of the square in which the point source is located. .
Pollutant concentrations are assumed to be normally distributed in
the horizontal and vertical planes with dispersion parameters, 0y
and oz, respectively. (For a description of the plume dispersion
model, see Part C, section 1.) The half-width, b, of the plume is
defined as 2.1Soy and is the horizontal distance from the plume center-
line to the point at which the concentration is 10% of its center-line
value. (See Figure A-17.) The parameters Oy and Oz are functions
both of downwind distance and of atmospheric stability. Correlations
of Oy andoz with these variables are shown in Figures A-a and
A-9, the different stability classes being defined in Table A-20.
Having defined the half-width, b, we can now estimate plume
spread as a function of downwind distance using the plume dispersion
model. The result of this calculation, shown in Figure A-IO, indicates
that the plume width for stability class B (the most prevalent during
daytime hours) is about two miles at 3.75 miles downwind. It is .
therefore reasonable to treat emissions as volume sources in adjacent
2x2 mile grid squares do...m\.,ind of the plant. Furthermore, the values
of Oz shown in Figure A-9 suggest that at this distance the plume
is well mixed up to the inversion base (assumed to be located at a
maximum elevation of 3,000 feet). The volume sources are therefore
distributed evenly in the column of cells up to tl\e inversion base.
Emissions from a point source of strength V (pounds/hour)
located in the ground cell (ijl) are distributed in the following
manner. (See Figure A-II.) A straight line is drawn starting
at the source location parallel to 'and in the direction of the wind
in that square. This line extends to the farthest edge of that
square either touching or immediately diagonal to the square containing
the source. The emissions from the point source are then apportioned
as volume sources in the two or three columns of cells through which
this line passes. The strength of the volume source in each cell is
proportional to the length of the line contained in that cell, with
the sum of the volume sources being equal to the strength of the
point source. For example, referring to the situation shown in
Figure A-II, the volume source strength allocated to the column of'
cells whose base is square i+l,j is equal to V x r2/(rl + r2 + r3).
2.
Emissions and other relevant data
Of the eleven power plants in the Los Angeles Basin, four are
operated by the Southern California Edison Company, four by the Los
Angeles Department of Water and Power, and one each by the cities of
Pasadena, Burbank and Glendale. Data relating to plant locations and
electric capacities are given in Table A-21" and Figure A-12. Finally,
emissions data f~r each plant are shown in Table A-22. These data
were obtained from the authorities cited:
Figures A-a to A-12
and Tables A-20 to A-22 follow
A-49
-------
10,000
0.1
DISTAIICE DO'.ItIWIND t
10
ki.lometers
100
Figure A-8. Horizontal Di5persion Coefficient as a Fun~tion
of Downwind Distance From the Source (Turner (1969))
(See Table A-20 for key
to stability categories.)
A-50
-------
1.0
0.1
DIS T AtlCE DOWpn'/IND.
10
ki lorreters
100
Fi~ure A-9. Vertical Disp~rsion Coefficient as
of Downwind Distance From t~e Source (Turner
(See Table A-20 for key to, stability categories.)
a Function
(1969) )
~
.~
A-51
;!~ I
"
-------
10,000
1,000
I/)
~
2j
m
..
.Q
~I;:
" -l.b.
'..,f,
0". .~
;"-r
, ,
'...."
~'.,
3?t ':~~;:;;.,..
.:. . ':,.:~~.
..''',"
. ,
'. -~
100'
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- tI"'" '- ~ -- _~I I, I.. I I I, I n I . 1-..- I'. I I I . I
I
"
,
10
0.1
1
10.
distance downwind, kilometers
Figure A-IO. Plume Half-\,lidth as a Function of
Downwind Distance From the Source
A-52
-------
(i+l,j+l)
"
/
,
(i+l,j) lJ
N
wind direction
in square (i,j)
Figure A-II. Distribution of Point Source Emissions
as Volume Sources in Adjacent Cells
A-53
-------
I 1 -;!- -'" 2...-.A:1- ._~_. L i.f?- -iL 12 IJI.!.~ IS' .J.!!._.!.7 '8 '9 ~ 2/ 22 H.l4r-
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23 : -~ -1- '---r- --r-r-' '-1"-' r-- --t--: '--,--- -'-r--["." 23
21 ----:-1jfl~-- --'1=- .--tl---r -'r--:- --T-- ,-- - -;-- -- 1'1
--r- -i-- ----'--- ~-- .---....-..j-'--r-t--.. .--. -1-' -~-- --i--W-+.
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, . . I I I .
2D , . - . I : I '. 9 Ii I. : j 2 0
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18 I ~- 1--' -_. _._.~._._- --I-.-t-'-i--;'..-- --~---r'-"'+'--' '---r-'-,---I--~ -"8
11 .+- --j-.T. ... -t--- --.t-r-lu.._"Lr-t-t-.- .--. .--- .__.t--~- 17
r~. -- '-1 -H--- .1-.- -t--..- -- ._~-- -
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. I 'I I I I I I I I : L' . I:;'
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12 --+-.+_ut-j .-- .;-r--:-r- "n --~T - - 11
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, I I' .' . l. I I I 1
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"liE' ,I. I I
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I: . I' I
. . ' - . I.,
1 2. 3 ". S E. '1 ~ q - 10 II li"'iTi" I,." 1"1 78- iT ~o 2.1 22 1-.3 2.~ 25
Figure A-l2.
Power Plant Locations
(See Table A-21 for numerical coding.)
A-54
-------
Table A-20. Key to Stabi1i~y categories (Turner (1969»
Surface Wind Day Ni9h t
Speed (at 10 meters) , Incoming Solar Radiation Thinly OVercast ~3/8
meters/second. Strong Hoderate Sli<.{ht or ~4/a Low Cloud Cloud
c
< 2 IA A-B B
2-3 A-B B C E F
3-5 B B-C C D E
5-6 C C-D D D D
> 6 C D D D D
The neutral class, D, should be assumed for overcast conditions during day or
night.
"Strong" incoming solar radiation corresponds to a solar altitude
greater thM 60° with clear skies; "slight". insolation corresponds to
a solar altitude from 15° to 35° with clear skies. Table 170, Solar
Altitude and Azimuth, in the Smithsonian Meteorological Tables (List,
1951) can be used in determining the solar altitude. Cloudiness will
decrease incoming solar radiation and should be considered. along with
solar altitude in determining solar radiation. Incoming radiation that
would be strong with clear skies can be expected to be reduced to moderate
with broken (5/8 to 7/8 cloud cover) middle clouds and to slight with
broken low clouds. An objective system of classifying stability from
hourly meteorological observations based on the above methods has been
suggested (Turner, 1961).
A-55
-------
Table A-2l. Locations and Capacities of
Los Angeles Basin Power Plants
Coordinates* of Electric
Plant Plant Location Plant Location Capaci ty
Number** Name (Square Number**) (miles) (Megawatts)
Southern California Edison
1 Los Alamitos 16,7*** 0.8, 1.9 1950
2 El Segundo 7,12 0.2, 1.7 1020
3 Redondo Beach 8,10 0.0, 1.5 1530
4 Huntington Beach 19,3 1.8, 1.4 880
(Orange County)
Los Angeles Depar>tment of
Water> & PO/JJer>
5 Harbor 11,8 1.4, 0.0 355
6 Haynes 16,7 1.1, 1.4 1580
7 Scattergood 6,14 0.9, 1.3 312
8 Valley 8,24 0.1, 0.7 512
Ci ty of Pasadena
9 Broadway & G1enarmt 15,20 0.1, 0.5 230
City of Bur>bank.
10 Magnolia & Olivet 10,22 0.6, 0.1 174
City of Glendale
11 San Fernando & Highlandt 11 ,21 0.7, 0.5 153
*Horizonta1 and vertical distances, respectively, measured from the lower left-
hand corner of the square containing the plant.
**See Figure A-l2 for plant locations.
***Horizontal and vertical coordinates, respectively, with the crigin at the south-
west corner of the 50xSO mile area under consideration. (See Figure A-12.)
tLocation, rather than name.
A-56
-------
Table A-22. Power Plant Data
Stack Flue Gas Out 'of 'Stack NOx Emissions
Mass Flow Vo1utre F10wl Stack
Plant Unit Height Diameter (103 pounds/ ( 103 cubi c Tempera- Velocity
Number6 Number (feet) (feet) hour) feet/minute) ture (OF) (feet/second) (~) (pounds/hour) ~
1 217 12.0 200 75 50~
2 217 12.0 200 75 500
1 3 214 14.0 250 85 600
4 214 14.0 250 85 600
5 214 17.0 200 85 1200
6 214 17.0 200 85 1200
1 222 12.0 210 75 800
2 2 222 12.0 210 75 800
3 220 14.0 205 80 600
11 219 14.0 90 30 20
5 219 12.0 200 70 750
3 6 219 12.0 200 70 750
7 214 17.0 210 90 1450
)t 8 214 17.0 210 90 1450
I
U1
~
4 1&2 211 17.2 230 / 40 900
3&4 211 17.2 185 88 1800
5 1&2 250 8.7 705 243 338 78 3842 294
3,4&5 250 9.7 1060 365 339 89 384 441
1&2 240 13.1 1880 585 260 75 160 328
6 3&4 240 10.53 1960 306 263 62 180 194
5&6 240 18.5 2720 850 268 55 280 821
7 1&2 300 240.04 1640 543 308 605 96 171
1&2 250 12.5 1033 - 362 350 52 128 144
8 3&4.. 250 15.0 1590 532 314 52 152 265
-------
Table A-22 (continued)
Stack Flue Gas Out of Stack NOx Emissions
Mass FloW Volume F lowl Stack
Plant Unit Height Diameter (103 pounds / (103 cubic Tempera- Velocity
Number6 Number (feet) (feet) hour) feet/minute) ture (oF) (feet/second) (~ (Pounds/hour)
1&2 60 11.4 375 220 180 34
9 3 60 11.4 375 220 180 34
10 60 9.5 600 250 88 400 465
1&2 48 5.3 10 300 50 "'6
11 3 68 5.3 90 280 60 '1.20
4 88 8.0 300 321 220 70
5 88 8.0 488 190 .130 37
:r
VI
Q)
lAt stack exit temperature.
2Volume concentration at 20\ excess' air and wet for plants operated by the LADWP (plants 5, 6, 7 and 8)
3TwO stacks per unit.
Each stack has a diameter of 126 inches.
40ne stack for both units..
SE .
x~t gas velocity with both uni~s operating.
6See Figure A-12 and Table A-2l for plant identification and location.
-------
t
Southern California Edison--Figures shu~n are interpolated
from emissions tests made at an unspecified date, using power
output records for 30 September 1969.
.
Los Angeles Department of Water and Power--The figures shown
are obtained from emissions measurements made at an unspecified
date. NOx mass flow rates are calculated from volumetric flow
rate data.
.
City of Pasadena--Data are based on emissions tests on one stack,
and are inferred from these tests for the other stacks.
.
City of Burbank--No data are available, figures are estimated.
.
City of Glendale--Data are based on emissions tests made at an
unspecified time.
.'
B.
Oil Refinery Model
Pollutants emitted by oil refineries are released from an array of
stacks which are usually distributed over a large area and are of varying
height. For this reason, and because individual refinery emissions data
are not available to us, refinery emissions are treated as area sources,
assumed to be well-mixed in the cell into which they are injected.
Refineries are considered separately here because of the possible future
need to deal with them in a different manner. ~le first describe the
method whereby the emissions from each plant were estimated and
then present the relevant data.
1.
Distribution of emissions
As was mentioned, data relating to emissions from each individual
refinery are not available. It was therefore necessary to make
certain assun~tions to arrive at usable figures. The total daily
refinery emissions in Los Angeles County, as reported by the Los Angeles
County Air Pollution Control District (~ee Section V), are:
Nitrogen Oxides
Low Reactivity Organic Gases
High Reactivity Organic Gases
65 tons
49 tons
5 tons
These emissions are distributed uniformly OVer 24 hours and in
proportion to the crude capacity of each refinery. (See Table A-23.)
2.
Emissions and relevant data
There are fifteen oil refineries located in the Los Angeles
Basin. Data relating to oil refinery locations and ~heir crude
capacities are given in Table A-23. The number and location of each
refinery are shown in Figure A-13. The emissions of nitrogen oxides
and high and low reactivity organic gases are shown in Figures A-14,
A-IS, and A-16.
A-59
Figures A-13 to A-16
and Table A-23 follow
-------
, .
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tI - -r- -I-r- ~- --t---- -+-:-rt- --r-;-tT-- -t+T i u
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. I I ' .
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: --~--i---~-: u_' '-+-I-~~r'l-h - -I -+- _un +- .-.. --- ;
7-. !-)-:--( -, --L.. - - ..-, - ----r--;-- ----- -- -- ------ 7
. . ~++-I--. i +- - - ,-- ! --:-1- - .- m - -I- - -- -- -------- .
~; ..~... ..j-+-I---H--+-I--=lf-II- --+_1___. - -- - ..-. =--- :
3 .,,01-"'-'--:, -...+-- _... t'--"'I-.-t--~.._. ._-- --r---+--r--'--li-- - -._- ---. -.-- - ---_. -- 3
1 : - --to --!--.- ._n.t--'-r- ._-- _...- _U' -- +...-1- '-1"-. _.. - ..--- j- - - :.. . .. --.. ...-- -- -_. 1
, . - --T-~" '-."--- - _. .---- -..-'" -+.._-jl-.-t-----r-'" .. - --- .--. - ---- - ..- -.-:. -- - I
I I'
I 2. 34- S E. " S q 10 " Il"""';~ ,,. ,,- 17 18- Iq fo- 2., 2.2 1.3 2.4- 2S
Figure A-13.
Oil Refinery Locations
(See Table A-23 for numerical coding.)
A-GO
-------
. I t. .1.'1.£1'-~' .J~'J-i '-~-'r.Cji" .!.r?. }Lr!.!J' .lJTi'~-r€ ~_~.!.71!8 r'~~ !.!.I2]2 ~
~~--:-....:.. _..-.. '.0,_'00_._.- 00'" .,-. - 'l-I"'-r'-r-- -'-+'-+-00'--'1"""- .._.._~-_.--!--t..- :: .
23 j--+- '~--I - - t --. '---r--L'-r-!-oo -_oo.-j- -I'"~ t..- .----..---'" -- -'j--',--'-j -- 23
l' '-J I. I 'I -J . '
21 I -~ 1-- -~~- --r' 100--' '-r:-r--r--r-- "-"~'-T- r- i --r-- --,-+- l~
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2-D . I. i i: i: i i : i i . ,,,
Iq' .- ---_..-- _"+_h' _./---- ._- -i""'" j'---I-_o(,oo --l---r'---j' -t--.- '--i--t-~-r-- -- ,~
18 . '. , .-'- -_._~...-- ---r--'-'-' '''''-'I--\''---r--j ...... . '--1.......!---t.--t-.. '--j'---j--i---.l.__. /8
17 ....'-1 -. ":"i--+-- -_.- _. -~~'I- -r--~'--~-~:"- .---.,.-.-t-,,-,!--,ooJ--' --i---- .._.~---1-'-'7
II =+. - : ' : --iTct-i---i--I-T-I-- ---- -++ II
-, i ,'. I, I ; I .! I I II ., ' -
I~ i' I { i' I : I I ! J I ~
ICtH-'-j-'T !~I':---r- ~~--'I~'---r-+--'" I "-1- I~
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-----. .-._~._------ -- --"""---"--1'--- --r.-----L- ----'- . -J.
I . I " I' I
:; .....1: I . !- j. . . t SS~I----T-- .._. -....i 'I"h;"h~~ --0011.3:._'_. -.-!-.- --.-j'-""I-' _.-.;;
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8 '--i--- --tT- --1''''''"-- -- . --:;;;- ~;. - .. . -1..-1.- ----.- -+-. -- _. 8 .
): j-T T ---1---- -_. u, - - -- ..j_...~..J. - -'----..-- -- -. --- 1
J 1 ---T--'-- - 'l~---I-I -. -- i - ,-- ~_h'- -- ._~--- -j .- - - --- - -... .- ou_.. .-- -- . -. l.
.. I . 1 Tt'
. . '. I" .. I
: :-1-.. ..1..-.,. ...1---. ---~--+--J.--. '- --..- ---~.I--c..- -.... -.. f--- --,--- on" .... -'.- - - .-.. _h' :
2 1- -'--1---'-'.-' .-.-t.---. -, ----.. --- -- --_...J.,...- --- "". ... -.- -.... ..--.. ---- ...-. _.-- ..-- -'- -... 2-
I T -;--t---r-'- _u- -.+.1---.---- --.- 'u -'--- -- -- I
I 2 3 ~ S ~ ., Sq 10 II 12.~ 1ft I,. ,,- '7 ;"6'~ iiI a,o 1.' 2.2 1.3 l~ 25 .
Figure A-14.
NOx Emissions (ki1ogr~~/hour) From 011 Refineries
A-61
-------
I L .1.1-~'"- E '-~-r3-1-~f' ~~- .1'1 _U"r!J'r/}-r!.~~ J.~.';""'-7.I,f'8 ...rJ..~- ~Il22 2 3 l~ P.:,- ,
~~ -"-, - _..,-,_.- .._-, --',---- -.-- '_'''.n' - '-.-" '1-- 'j"~-'!-~" '----'~-"r.--I... --~--- .---1..--- -.-++.::
'23 i - --1- .-. - '-'-r-J.-r-j "--'j'-"r-~' ------ _.,- ---..t-... ,--:oo..~. .. 23
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. . I 'I . ~.
21 I :' I I I i I; . i 2'2.
- - :..... - - ---1 -- - ' I. I I I '
2J I t --r I' .-- -~'----r--i----t- ---T-;-- -T .-.i---- .-r--t-- 2.'
I j I I ! I I I
~: 1---. -.. .-..J 00- .-- ..--- -,-- ' -. +-.' . - .too-i. --- ._--t--- j,-t'---f-_oo_-.~.--i"'~'-T - ::
'& !--j -- -+-- ,-+- ---r--~ T+ -- '-'~E"----' -.. ---t-i--;...-t-_. If!
I) -t-Lj---r ---+-- -t--t- --t+J_-~.- --,.J"--r---I--- -on ---+---!'--rj---17
I -' - .-- I oo .-+ -~_..J...J_._- -- __LoO '-- --Lt--..- --
Ii I-t-, 'I " 'I
U I :: i: ! I I I I I ' : Ii,
I~I I H: I I:, 'i I I, I. ii, L 1 I I~-.
'It -t- --I' ---r--+--f--' - ~-~--'r-r-;t- ~>-t---I-I---+- --t--- -. - It
'J --t--i-+--:~- ---I-!-t- ---t--j--I--'+- ---1- -;r-H- --t+-1--- -- 13
;; ~=tt-T----'- --- --, "T=+=T=~=; +- t-; =;==~l--~~ ,-It- =;;
~ '; +-t-- ---- -,..-' --..j._~~.' -.. ~:+;:~---j --l-.. . .--j.---l-- --- .---.. ." - --- ..--i.- --. :
8 -----; ..- (-~-- -'1-' oo.-- __nOO . --.t--- ---- '''--;--;4+--1'-2- . -_. .. -'1"-+- - -'U -.. --.. ._. -- - .'- 8 .
7~r~ J=-J-== ..-:- ~- =~~ -: ,~~, :T=~-:=l=L -==_::-- --:_-= :: 7
~: : i I '++ . i,
:; -i---. -I.--+--H-- -----IJ--. +--- -- --4--_U ---- - :
3--j- :--:-1---;-.. -- --- --- -t--'-1---"""---' ..- - -- -,-i..- -.. ..-.. _..- --- 00"- 3
2. ..- j...--t.- -nO ---. --_.._-- ..-- -----+..--. ,-- n -" roo. . _G'.'" .......-..- _. ..- ---- --- -- - 2
,- '-ri--:-- --- - .-.- ---..-- ..-- ~. "1----' --.. .-..' ~...~--- ._- -_... -- .. ---. -. --- I
-L-.i. ~-
, 2.. '3 4- ~ 6 7 '8 q '0 " 12. '3 l't '1" , 7 , 8 I q lO L' Z. Z z.J 2.4- 2:>
Figure A-IS. High Reactivity Organic Gas Emissions
(ki1ograms/hour) From Oil Refineries
A-62
-------
I .L ..3--1'-~-' E '-~J .7_rJ~' !j' .!..t!....1l'T!J-'1='3T~~-r1! .L~-!..7,!.p__,-1...2!:... .~.!..ti22 'W-
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11 ---y- --+- -:- -,---..,.-, ----!-r+-;--- -TTur-- n,_~_, .."
.~: ..L T-'-l-"'~ .----1.-----\--- --- ---I--'r; -.t--.L--- -n- -...--i-.t.- .-' "---j'-i-n+--- n.::
18 . i . -,-- --!--~c-r--- --- [---,--j---j- --- --i-1-""'1---' --- '-"i-'--i---_.i .... /8
I),r----,+---+-~T'- --H-T- _nLr--,- ___uL -i-L-"
,t =-j. .-.. I,"--r- --1--: ----~-t._- ~I -J--+-r -- _L -r-+"
I . , . I t I
I . ,: I I I I: I t. !. I. t. I I I ,.-
~ I I I I . I , ''''
14H-t--t-.-t--. -'-l---l--t--+--- -~j---- -tt- --'j'-+--j - - ,,---- "'+-1"._L- I}
,3!hj-I+--f- -T--'--i-t----!-j--+-r '-'-T~;i----l-'----- ...-J-. -~"-~-'--13
Ill-....t--r-t---;-- --d---;---j --1---t--+j~; 'I~:i'-I-I -.1- t.- - 11-
I' ,I: I .
,,-' 1 !',!, 1"" I"!" 'T-'- .--. - --;. --1 ---T;;" --no ",'--,1 --'1--- ..- ,.-. --.. -"..--.- "
'. I . I I I' . I I I I
~ I-~J- i-tun ---('~ u- -;:! .:qnui u-- -- Idd _fhU - -- __dO. - -. --t -- - ~
~. -. "r..... . -- [-- i"'" . ..-., -.. i -- ----t- - i --, -". .-_.- _. ---../.. - . -. ...-. -.--... .----. -- ....- un 6
~ ~...!._+._+._.-L'.---~~t--i---'- ..-- --+-~- ---1!'~- .---..-1 ----. .'n... .-.. ~-.. ".--- h- -- :
3 t ---I' "-1-- -T- .---. ___..LoOt...._-. .- -. u. ..-- ..:-t ..-. ---. --+-,.. -.- -... .- .. - ._-- -.... . 3
: ~+--- =Ff~ -- =~-~ -~~,-~---F-F :-~F :+-.i:~ ..--:_- -C'- ~- :~ -~ ~
C I . ~ ..... - __.J-_L:-x _. --'-
. I 2. 3 ". 5 Eo 7 8 q 10 II tl " 14 ,,. I' '7 '11 Iq ~o 2.' 2.2 2.3 2.'- 25.
Figure A-16. Low Reactivity Organic Gas Emissions
(kilograms/hour) From oil Refineries
A-63
-------
Table A-23. Locations and Capacities of Los Angeles Basin Refineries
Coordinates" of
Refinery Refinery Location Refinery Location Crude Capacity**
Number!" Name (Square NUIt'.bert) (miles) (barrels/stream day:)
-
1 Atlantic Richfield Co. U,gtt 1.2,0.3 173,000
2 Douglas Oil Co.: of California 15 , 12 0.2,0.9 26,000
3 Edgington Oil Refineries, Inc. 14,11 1.3,0.9 16,000
4 Fletcher Oil &.Refinin~ Co. 11,9 0.6,1.2 13 ,000
5 Carson Oil Co.;. Inc. 10 , 10 0.3,0.8 10,000
6 Gulf Oil corporation 17,12 1.7,1.7 51,000
7 Lunday-Thagard Oil Co. 14,14 1.1,0.5 3,000
:r
0\ 8 MacMillan Ring-Free Oil Co. 14,8 1.0,1.4 10,000
~
9; Mobil Oil Corporation 9,10 1.1,1.7 130,000
.1
10 Powerine Oil Co. 17,13 0.7,1.3 30,000
11 Shell Oil Company 12,10 0-. 9 , 1. 0 44,000
12 Shell Oil Company 12,9 0.6,0.8 44,000
13 Standard Oil of California 7,i2 1.0,1.6 210,000
14 Texaco, Inc. 12,~ 1.1,1.3 61,000
15 Union Oil Co. of California . 12,8 0.7,0.6 107,000
*Horizontal and vertical distances, respectively, measured to the approximate center of the area covered by
the refinery from the lower left-hand corner of the square containing the refinery.
**Oil and Gas Journal, April 6, 1970.
tSee Figure A-13 for refinery locations.
ttHorizontal and vertical coordinates, respectively, with the origin at the southwest corner of the SOxSO
mile area under consideration. (See Figure A-13.)
-------
c.
Alternate Models for Large Point Sources
In this section we consider procedures for estimating contaminant
cOncentrations due to large point sources. . Existing procedures provide
only crude estimates of ground concentrations Owing to the difficulty
in describing mathematically the complexities of plume phenomena--
chemical reactions in the plurne, unsteady emissions rates, varying
meteorological conditions, uncertainty of plume trajectories, and the
difficulty of accurately determining atmospheric dispersion coefficients.
In the first part of this section, we describe in some detail a method
of estimating concentrations applicable to steady-state, non-reacting
plumes. The second part contains suggestions for more advanced treat-
ments, useful for unsteady conditions and for reacting pl~mes.
1.
Estimation of local concentrations for steady-state, non-reacting
plumes
The problem of modeling a steady-state, non-reacting plume which
results from a point source consists of two parts:
(1)
Estimation of the height at which the buoyant plume
becomes essentially horizontal (plume rise).
(2)
Estimation of the concentration distribution in the
plume.
In order to estimate plume rise, it is necessary to choose a suitable
formula from the many suggested for this purpose. The "best" formula
is probably one derived from tests on stacks having geometries,
and operated under conditions, similar to those being considered.
It is also desirable that the tests be made under meteorological conditions
resembling those of the locale of interest. Reference should be made
to the literature on the subject for guidance in making a choice,
particularly useful are the review articles of Briggs (1969) and Strom
(1968). Estimates of contaminant levels in a dispersing plume are
usually based on the assumption of a normal concentration distribution.
Turner (1968) and Strom (1968) discuss this and other formulations
that have been proposed. In this section we first suggest a useful
plume rise formula and then outline a method of estimating contaminant
levels for various inversion c~ditions, based on the assumption of a
normal concentration distribution.*
*The origin of the coordinate system to which we will refer is
at ground level, at or beneath the point of emission, with the x-axis
extending horizontally in the direction of the mean wind. The y-axis
is in the horizontal plane perpendicular to' the x-axis, and the z-axis
extends vertically. The plume travels along or parallel to the x-axis.
Figure A-17 illustrates the coordinate system.
A-65
Figure A-I? follows
-------
I
x
(x.-y.Z)
(x...y.o)
H
h
Figure A-17. Coordinate System Showing Gaussian Distributions
in the Horizontal and Vertical and Plume Half-Xidth
A-66
-------
PZUTOO Rise
An equation that might be used to describe plume rise from power
plants of the type found in the Los Angeles Basin is due to Holland
(1953) :
AH = Vsd(l.S +.2.68 x 10-3p Ts - Ta d)
U Ts
(A-2 )
(f~r neutral atmospheric stability)
where
AH = the rise of the plume above the stack, meters
Vs = stack gas exit velocity, meters/second
d = the inside stack diameter, meters
u = wind speed, meters/second
p = atmospheric pressure, millibars
Ts = stack gas temperature,
OK
Ta = air temperature,
OK
To account for atmospheric conditions
sU9gests multiplying the value of AH
by a, where:
other than neutral, Holland
calculated from Equation (A-2)
1. 1 < a < 1.2
for unstable conditions;
0.8 < a < 0.9
for stable conditions.
This empiri~al equation was derived from experimental observations
made at the Oak Ridge and the Watts Bar steam plants in Tennessee.
These stacks are similar to those found in the Los Angeles Basin
(stack diameters from 1.7 to 4.3 meters and exit temperatures from
82 to 204°C). The tests, however, were conducted in a rural area
and under atmospheric stability conditions dissimilar to those
common to Los Angeles. It should also be noted that Holland's
equation was based on photographic data that followed the plumes only
600 feet downwind. If this equation is extrapolated to downwind
distances of the order of a few miles, appreciable errors may result.
PZuroo Dispersion
The steady state contaminant concentration,
x, y, z, resulting from a continuous sourc~ with
height H,. is given by:
"',. at any point
an effective emissi~n
*H is the sum of stack height,
h,
and plume rise,
AH.
A-67
-------
w(x,y,z) ~ 2'C;CZU ex{ ~ (~Y]{ex{ ~ (" :ZHYJ
+ ex{ ~ (Z ;ZHrJ }
(A-3)
This relationship was developed with the follrn~ing assumptions (see
Turner (1969»:
the plume concentration is normally distributed in the horizontal
and vertical planes, with standard deviations 0y and Oz
respectively; .
.
the mean wind speed affecting the plume is
UI
.
the uniform emissions rate of pollutants is
V; and
.
total reflection of the plume takes place at the earth's
surface.
To estimate concentrations when an inversion is present, the
following procedures are recommended:
(1)
Effective emission height less than inversion hei[ht
(Turner 1969)
Allow Oz to increase with distance downwind until
it becomes equal to 0.47 (L - H), where L is the
height of the inversion base. At this distance, xL'
the plume is assumed to have a Gaussian distribution in
the vertical. Assume that by the ti~e the plume travels
twice this far, 2XL, the plume is uniformly distributed
between the earth's surface and the inversion height, L.
Thus:
.
For X < xL (but greater than a few hundred meters) ,
Equation (A-3) is applicable.
For
X > 2xL,
v
1/!(x,y,z) =
ffi 0IJU
exp ~ ~ (a~n
For xL < X < 2xLC the best approximation of the concentra-
tion is that read from a straight line drawn between the
calculated concentrations at points xL and 2xL on a
log-log plot of concentration as a function of distance.
A-68
-------
(2)
Effective emission height greater than inversion height
This situation is discussed by Roberts, et ale (1970),
who made the following assumptions:
(a)
If the physical stack height
an infinite value for L is
and dispersion estimated for
conditions.
h is greater than L,
assumed, with plume ri se
stable atmospheric
(b)
If the stack height h is less than L, a minimum
plume rise 6Hmin is calculated, based on the
coefficients for stably stratified air.
.
If the minimum effective emission height,
H = h + 6Hmin, is greater than the lid height
L, H is used as 'the effective emission height.
The plume is then analyzed as described in (a).
.
If (h + 6Hmin) < L and if the plume rise 6H
based on the actual stability class yields an
effective emission'height greater than L, i.e.,
if (h + 6Hmin < L) and (h + 6H ~ L), the
effective emission height is restricted to the lid
height L.
When the method outlined in this section for estimating ground level
concentrations is used, it is 'also necessary to incorporate point source
emissions into the overall grid model. This can be done by treating
the emissions as volume sources located either in cells downwind of the
point for which the concentration calculation was performed, or in cells
containing and adjacent to the point source. However, one should
exercise care to ensure that emissions are not doubly counted and that
ground level concentrations are not artifica11y elevated in cells where
the volume sources have been located.
2.
Further suggestions for the treatment of large point sources
A better estimate of concentrations resulting from non-reacting
plumes, especially under unsteady conditions, can be obtained by use
of the so-called "puff" mode1.* This model is based on the assumption
of a Gaussian concentration distribution. However, in contrast to the
plume model, this distribution is assumed for all three spatial coordinates, as
applied to an instantaneously released, expanding puff. As each incident
of release may be treated as a separate event, the assumption of. steady
*That'estimates of ground level concentrations obtained from the puff model
are superior to those calculated from plume models has not been conclu-
sively established. However, Roberts, et ai. (1970) report that pre-
dictations based on a puff model (Roberts, et a1. (1969» compare-more
favorably with the Chicago data for which they were validated than do
plume predictions (Turner (1968» for a St. Louis data base. See Roberts'
et ale (1970), p. 17, for further details.
A-69
-------
state is unnecessary,and variations in wind speed, wind direction,
emissions rate, and inversion height with time may be accommodated
in a straightforward (although somewhat involved) manner. The
possibility also exists that this method of analysis may be extended
to account for simple chemical reactions. A description of the
puff model, along with further references, can be found in Roberts,
et ale (1970).
It is not well understood how to model a rea~ting plume. A
possible method of attack might'begin with the estimation of' the
boundaries of the plume using the Gaussian dispersion equation. As
the plume quickly comes to rest relative to the surrounding air (the
plume has no horizontal momentum), this boundary can be considered
a surface in three-dimensional space. The volume contained by this
surface may then be divided into cells by passing planes perpendicular
to the plume axis. Each cell is assumed to be a well-stirred tank,
with transport by convection at the prevailing wind velocity across
the cell interfaces. By applying a reactio~jscheme to this cell model,
the concentrations of any species may be predicted as a function of
time. When a linear dimension of a cell has grown so as to be
comparable to the grid size, the contents of that cell are injected
as a flux into the grid square. Thereafter, point-source emissions
are accounted for by integration of the continuity equations on which
the airshed model is based.
References
Briggs, G. A., "Plume Rise," AEC Critical Review Series (NoveIl'\l)er 1969)
CFSTI No. TID-25075.
HOlland, J. Z., "A Meteorological Survey of the Oak Ridge Area," Atomic
Energy Commission, Report ORO-99, Washington, D.C. (1953).
List, R. J., "Smithsonian Meteorological Tables," 6th Revised Ed.,
Washington, D.C., S,mithsoniai1 Institution (1951).
Roberts, J. J., et al., "An Urban Atmospheric Dispersion Model,"
Proc. Symp. Multiple Source Urban Diffusion Models, Chapel Hill,
N.C. (October 1969) (in press).
Roberts, J. J., et al., "A Multiple Source Urban Atmospheric Dispersion
Model," Argonne National Laboratory, ANL/ES--CC007 -(May 1970).
Strom, G. H., "Atmospheric Dispersion of Stack Effluents," in Air
POllution," (A. Stern, Eq.) Vol. I, Academic Press (1968):--
Turner, D. B., "Relationships
ments and Meteorological
.!!, pp. 483-489 (1961).
Between 24-Hour Mean Air Quality Measure-
Factors in Nashville, Tennessee," JAPCA,
Turner, D. B., "vlorkbook of Atmospheric Dispersion Estimates," U.S.
Department of Health, Education and Welfare, Public Health Service,
pub. No. 999-AP-26 (1969).
A-70
-------
1 ,/~
IV.
FIXED SOURCE EMISSIONS--DISTPJBUTED SOURCES
, .
"
Distributed fixed sources (defined as all fixed sources, ~ith the
exception of power plants and oil refineries) account for approximately
10' of NOx and 26.% of organic gas emissions from all sources in the
Los Angeles Basin. (See Section V.)" These sources will be treated
uniformly as area sources, assignable to a grid node. In this Section
we describe the method of distributing each source in space and time.
Some of the emissions from distributed fixed sources are spread
over highly populated areas, and for this reaSon it was necessary to
divide the modeling area into regions of high and low population density.
The areas of low population density are shown in Figure A-1S, and the
total number of squa~es in each category are tabulated in Table A-24.
The emissions figures contained in this Section are obtained from:
u
(1)
(2)
"Profile of Air Pollution Control in Los Angeles County,"
Los Angeles County Air Pollution Control District, January
1969, hereafter referred to as "LACAPCD."
"Emissiops Inventory--1969," County of Orange Air Pollution
Control District, August 1970.
A.
Oxides of Nitrogen
1.
Los Angeles County
PetroZeum marketing, domestic, ship and raiZroad emissions
contribute 46 tons/day.
In order to distribute nitrogen oxide emissions, the following
.assumptions were made:
(1)
Half of the total daily domestictemissions (17.5 tons)
occur between 6 a.m. and 6 p.m. PST.
(2)
The total daily emissions attributable to petroleum
marketing operations (10 tons) occur between 6 a.m. and
6 p.m. PST.
(3)
Half of the daily ship and railroad emissions (1/2 ton)
occur at the Port of Los Angeles.
(4)
The emissions cited in (1) and (2) above, plus an
additional 1/2 ton due to ships and railroads (i.e., a
total of 28 tons), are distributed uniformly over the 262
high-population squares of Los Angeles County.
(5)
All emissions rates, whether assignable to a twelve
or twenty-four hour period, are uniform between 6 a.m.
and 6 p.m. PST.
*Domestic, commercial and industrial facilities on firm natural
gas schedules.
A-71
Figure A-IS
and Table A-24 £0110\'1
-------
"
Figure A-lB.
Population Density Distribution of the Los Angeles Basin
(Areas of low population density are cross-hatched.)
A-72
-------
Table A-24. Grid Square Classification
by Population Density
Nmnber
.J
Population of
Densi ty Squares
Los Ange 2es Coun ty
High 262
Low 101
Total 363
Orange Co un ty
High 68
Low 28
Total 96
-
Total over land 459
Total OVer ocean 166
-
TarAL 625
A-73
-------
Based on these assumptions, NOx emissions between 6 a.m. and 6 p.m.
PST over the highly populated areas of Los Angeles County are:
28. x 2000 x 454 ~ 10~3 = 81 kilograms/hour/square
12 x 262
Incineration contributes 1 ton/day. To operate incinerating equip-
ment it is necessary to obtain a permit from the Los Angeles County Air
Pollution Control District. Thus far there have been 1283 permit
units issued for this purpose in the County.
Assumptions made in apportioningNOi emissions due to incineration
are:
(1)
Th~ total daily emissions occur between 6 a.m. and 6 p.m.,
PST,
(2)
Emission rates are constant, and..i
(3)
Emissions assignable to a grid square are proportional to
the number of permit units issued for the five-mile square
area containing that grid square.
The distribution of permit units is shown on page 17, "LACAPCD."
Mineral, processing pZants contribute 6 tons/day, mainly
from concrete batch plants. These emissions are apportioned
in the same manner as incineration emissions. The distribution of
concrete batch plant perndt units is shown on page 19, "LACAPCD."
Metallurgical plants contribute 3 tons/day. These emissions are
apportioned in the same manner as incineration emissions. The
distribution of metal melting equipment permit units is shown on
page 18, "LACAPCD."
Petroleum Production contributes 10 tons/day. These emissions
are apportioned in the same manner as incineration emissions, but
spread uniformly over 24 hours. The distribution of petroleum
processing equipment permit units is shown on page 20, "LACAPCD."
"Other Industries" contribute 25 tons/day, which are distributed
uniformly between 6 a.m. and 6 p.m., PST, mainly over the southern
central portions of Los Angeles County, with smaller amounts in the
San Fernando and San Gabriel Valleys.
The total hourly NOx emissions from all the above sources are
shown in Figure A-l9.**
*Domestic, commercial and industrial facilities on firm natural gas
schedules.
**The emissions rates shown in Figures A-19, A-20, and A-2l were computed
.for the hours 6 a.m. to 6 p.m. PST, and are assumed to be uniform ~er
this time interval. Other rates would apply for hours outside this range.
A-74
Figure A-l9 follows
-------
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~~ ~ H- --:-r ;-;:~~ t;: - -~ ;;:- ;. - -;:[:i-;; ; - --; f -;1 -: ;-1-:-; 1- -: --;1-: i-: ::
23 8 1'9 -;1-1:-t~ ~ ;; 1:- I-~- '-~T-~'I-~-r-;t-~--.~.t._~ ;--0 ...~.-t -~-'--J'-O..-~t-~'r'~ 23
21 . I' I~t-~~-;; -;-;t,:-r-;~-r-;-[- .:-;,-;- -;r;;- ;'-;l-.---;t-; --;:-:1--. 21
11 -~.~ '-" --;;-; -;!-;~;,~ i-;:-;)-;t;; ~;t;-,~;L;;:~;--J;-:'7~ .,
~:~ , ~Ff-:- -:i-~ -;:-h:-l~~-' ~:--~'~'h~+~*~:'-' ~- '-'~':+~~i'~: .~~~- -~~.L~;'!-i-~~'-': ::
IS' i. -;l~--1--~;; or;; -I-;;:~;-I;;- -;;-I;;t ;-'T~~ ;; - ;; j -;; :-;;t~;;--d ~t- ;j--J;. /8
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. IS '+-I-J -- t- ~J:.:~_~1_t.~~-I-1:.. :.0.j-~_+~:~~1- -~-~-1' ,1:.i- 51.3_.~_!- _.! ~"_.!.L~~. ° IS"
'41"1 ' : : 13 I 25 I 25 i 22 ~ 20 20 l Jl I Jl I 26: 22 22 22) - ~~.I 7 ; ° ° ° ° I ° ° If
::I~~=r+T- ~ -1~~+:~j:~i~ - ~J,~f~gl::--=t~~~~f~.. :: ,: --~:- -:::
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'. -H-+---- -- .'-~ L" - j~' - '.'. : "- i '~-j "~'~" J ,,- L~' - ': - ".-"'~-I'-';-~- _.~ 10
<; ~tltJ=~~-~-! :_~ -~.l~~l~~:-: ~H~itiJ;~~ ~;-1i ::~j-i:- i~ f.= i~ _:~ ~i~~- =: : .
1~-:---lmi---;--.11.. 4- 18 -~-+~~-~.' -. .'--.'- .1~'i'~~ .;..11. 1!.. ?_~- ..~- _1_~.. .!.:.I~~-' .-°17
(. I '! . 4! 6 ! 20 2! I j.. 11 111 11 11 11 11 11 0 0 l.
Si -J--. '-~.!._._.~._..--I-L- ---..-..-.. --1---: .-_.. -0. --_..-... !~__1_1...~_1.~.. _.~_l- --~- ---~ ...0. --~IS
" .--.1-.-. .., ..~-_.t-- -;.t ---- __L__-J-"- ~- -': :~ -'- --~--' ~
. : S-j- [ - --+-- --- -- -f- - ml- - +-,-- ~- " -~: -:~- : -:- u: :
r 1 -', I -- .-- -- --- ----- ._--~ .,.- ."-' _.. ..-O..-t-- .--- -.; ._--.~- ~- -; I
I ' .....i I I
'.. I 2. 3 ~ 5 . E. 7 8 q' 70 II ~3'";';;"'-'" ,,-' 17 ir "iT" 10 z., 2.-2 2.3 U ~5
'.
Figure A-l9. NOx Emissions (kilograms/hour) From Petroleum
Marketing, Domestic, Ships and Railroads, Incinerators,
Minerals, Metals, Petroleum Production, and "Other Industries"
A-75
-------
2.
Orange County
As the spatial distribution of industrial plants in Orange County
is unknown, the follmdng assumptions were made in distributing nitrogen
oxide emissions from fixed sources:
(1)
Half of the total daily domestic emissions (3 tons) occur between
6 a.m. and 6 p.m. PST.
(2)
The total daily emissions due to mineral processing equipment,
incineration, "other industries," and ships and railroads,
a total of 6.5 tons, occur between 6 a.m. and 6 p.m. PST.
(3)
Enussions from all sources listed under (1) and (2) are
released in the 68 highly populated squares of Orange County.
(4)
Emissions rates are constant.
,J
Hence, NOx emissions rates over the highly populated areas of Orange
County, between 6 a.m. and 6 p.m. PST, are:
9.5 x 2000 x 454 x 10-3 = 10.6 kilogramsjhour/square
12 x 68
These emissions are included in Figure A-19.
B.
Organic Gases
1.
Los Angeles County
Petroleum marketing~ dry cleaning~ degreasing and "other" organic
solvent users contribute 105 tons/day of high reactivity and 275 tons/day
of low reactivity organic gases.* These sources are assumed to be
uniformly distributed over the 262 highly populated squares between
the hours of 6 a.m. and 6 p.m. PST, thus,. .
105 x 2000 x 454 = 30 kilograms/hour/square
262 x 12 x 103 high reactivity organic gases
and
275 x 2000 x 454 c 79 kilograms/hour/square
262 x 12 x 103
low reactivity organic gases.
Surface painting and coating operations contribute 45 tons/day
of high reactivity and 185 tons/day of low reactivity organic gases,
*The division of organic gas emissions into high and low reactivity
was made by the Los Angeles County APCO, using a reaction scale
similar to that shottTn in Table A-IO. .
A-76
-------
mainly from paint bake ovens. These emissions are distributed uniformly
between 6 a.m. and 6 p.m. PST in proportion to the number of paint
bake oven permits in each square, as shown on page 16 IILACAPCD.II
Petroleum produation contributes 60 tons/day of low reactivity
organic gases. These emissions are spread uniformly over 24 hours
and in propo~tion to the number of petroleum processin~ equipment permit
uni ts in each square, as shO\om on page 20 of II LACAPCD. II
Inaineration~ mineral proaessing plants, pOlt'er pl.ants, and "other
industries" contribute 1, 1, 4 and 1 tons/day respectively. As these
amounts are small, they were not considered here.
The total hourly emissions of organic gases from all the above
sources are shown in Figures A-20 and A-21.
2.
Orange County
Petroleum marketing, organia solvent users, and "other industries"
contribute 9.7. tons/day of high reactivity and 39.1 tons/day of low
reactivity organic gases. These emissions are distributed uniformly
between 6 a.m. and 6 p.m. PST over the 68 highly populated squares,
thus,
9.7 x 2000 x 454 x 10-3 = 11 kilograms/hour/square
12 x 68 high reactivity organic gases
and
39.1 x 2000 x 454 x 10-3 = 44 kilograrns/hour/square
12 x 68 low reactivity organic gases
These emissions are included in Figures A-20 and A-2l.
C.
carbon Monoxide
The total fixed source emissions of CO comprise approximately 0.5%
of all CO emissions in the modeling area ,and thus were considered
negligible.
A-77
Figures A-20 and A-2l follow
-------
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Figure A-20. High P2activity Organic Gas Emissions
(kilograms/hour) From Petroleum Marketing and
Organic Solvent Users
A-7S
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. I T~r~Lr? ,_.b-T7u1-~-'r~"l!'o..- -.Il'T!J:'r.!~-r'-~-r:f .L6_f~'['~-r.~ I 2'- ~T--R'j ,~ f'''-
~: .~:-._;--
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V.
CONTAHINANT EMISSIONS INVENTORY OF THE LOS ANGELES BASIN
The purpose of this Section is to show the approximate magnitudes
and relative contributions of the different emissions sources in the
Los Angeles Basin. Average daily emissions rates of NOx, organic
gases and CO into the, atmosphere of the Los Angeles Basin are shown
in Tables A-25 to A-30. These data, with the exception of automotive
emissions, were obtained from the appropriate County Air Pollution
Control District.* Automotive emissions were computed from the product
of the vehicle mileage in the parts of each county within the modeling
area and the average emissions rate per vehicle (see section I).
*The power plant data shown are total figures obtained from the counties
and were not used in the model. They are included only for comparison.
The power.plant data used in the model and reported in section IV are
much more detailed.
Tables A-25 to A-30 follow
A-SO
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Table A-25.
Zmissions of Nitrogen Oxides in Los Angeles countyl
Quanti ty
Emission Source (tons/day) , of Total
Motor Vehicles2 . ~66 60.4
Aircraft 15 1..9
Petroleum
Refining 25 3.2
Production 10 1.3
Marketing 10 1..3
Power Plants 135 17.5
Oil Refineries 40 5.2
Other Industries 25 3.2
Domestic3 3S 4.5
Incineration l ' 0.1
Ships and Railroads 1 0.1
Metals 3 0.4
Minerals 6 0.8
-
772 99.9
lpixed sourc~ and aircraft emissions ta.1(en fran: "Profile of Air
Pollution control in Los Angeles CoUnty," Los Angeles County
Air Pollution Control District, January 1969.
2Computed,from the product of our estimated figure of 4.4 g~ams
of NOx per vehicle mile and 96,358,000 vehicle 'miles per day"
this being the vehicle mileage driven per day in Los Angeles
County within the modeling area.
3Domestic, commercial and,industria1 facilities on firm natural
gas schedules.
A-81
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Table A-26.
Emissions of Nitrogen Oxides in Orange Countyl
Quantity
Emission Source (tons/day) , of Total
Motor Vehicles2 88.0 74.1
Aircraft 3.9 3.3
Minerals 0.3 - 0.3
Incineration 0.2 0.2
Power Plant
(S.C .E. at Huntington Beach),- 14.3 12.1
Other Industries 4.0 3.4
Domestic3 6.0 5.1
Ships and Railroads 2.0 1.7
118.7 100.2
1
Fixed source and aircraft emissions taken from:
Inventory--1969," County of Orange Air Pollution
District, August 1970.
"Emissions
Control.
2computed frnm: 4.4 grams/vehicle mile x 19,101,000 vehicle
miles per day, this being the vehicle mileage driven per day in
Orange County within the modeling area.
3
Domestic, commercial and industrial facilities on firm natural
gas schedules. ,-
A-82
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Table A-27.
Emissions of Organic Gases in
Los Ange1~s County1
Emission Source"
High Reactivity Gases
(tons(day:)
1037
Motor Vehic1es2
Aircraft
Petroleum
Refining
Marketing
Production
Orgariic Solvent Users
Surface coating
Dry cleaning
Degreaslng
Other
Incineration
Minerals
Power Plants
Oil Refineries
Other Industries
. ."
1see Ref. 1, cited in Table A-25.
45
5
50
o
45
5
20
30
o
o
o
o
o
-
1237
Low Reactivity Gases
" (tons/day)
183
45
45
60
60
185
20
7S
120
1
1
4
4
1
-
804
2 " "
Computed from the product of our estimated figure of 9.0 grams of hYdrocarbon/
vehicle mile and "96,358,000 vehicle miles per daY1 plus evaporation losses equal
to 72 grams/vehicle/day x 3,338,000 vehicles. AS before, an 85~15 split between
reactive and unreactive species is assumed.
A-83
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Table A-28.
Emissions of Organic Gases in
Orange countyl
High Reactivity Gases Low Reactivity Gases
Emission Source Ctons (day > (tons/day)
Motor Vehicles2. 206.6 36.5
Aircraft 3.6 l.~ 3.7
Petroleum Marketing 5.0 . 7.0
Organic Solvent Users
Surface coating 2.0 8.0
.Dry cleaning 0 2.5
Degreasing 2.3 . 0.4
Other 0.3 20.0
Other Industries 0.1 1.2
219.9 79.3
.1 . f
See Re . .1, dited in Table A-26.
2. ...
Co~uted from: ~.O grams/vehicle mile x 18,101,000 vehicle miles per day,
evaporation losses equal to 72 grams/vehicle/day x 797,000 vehicles, and an
85,15 split between reactive and unreactive hydrocarbon species.
A-84
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Table A-29.. Carbon Monoxide Emissions in
Los Angeles count11
Quantity
Emission Source (tons/day) , of Total
Motor Vehicles2 6781 96.8
Petroleum P~fining 30 0.4
Incineration 1 0.0
Metals 3 0.0
Aircraft 190 2.7
Oil Refineries 1 0.0
-.
7006 99.9
!gee Ref. 1, cited in Table A-25.
2
Computed from the product of
63.9 grams of CO/vehicle mile
miles per day.
our estimated figure of
and 96,358,000 vehicle
A-as
-------
Table A-30. Carbon Monoxide Emissions
in Orange C0W1ty1
Quantity
Emission Source (tons/day> , of Total
Motor Vehicles2 1274 97.4
Incineration 0 0.0
Aircraft 30 2.3
Ships and Railroads 4 0.3
1308 100.0
lsee Ref. 1, cited in Table A-26.
2Conputed from:
miles per day.
63,9 grams/vehicle mile x 18,101,000 vehicle
A-86
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