EPA-450/3-75-002
OCTOBER 1974
METHODOLOGY
FOR ESTIMATING EMISSIONS
FROM OFF-HIGHWAY
MOBILE SOURCES
FOR THE RAPS PROGRAM
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-7 5-002
METHODOLOGY
FOR ESTIMATING EMISSIONS
FROM OFF-HIGHWAY
MOBILE SOURCES
FOR THE RAPS PROGRAM
by
Charles T. Hare
- Southwest Research Institute
8500 Culebra Road
San Antonio, Texas 78284
Contract No. 68-02-1397
EPA Project Officer: Charles C. Masser
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park. N. C. 27711
October 1974
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FOREWORD
The work described in this report was performed by Southwest
Research Institute for the U. S. Environmental Protection Agency under
Contract No. 68-02-1397, "Methodology for Estimating Emissions from
Off-Highway Sources for the RAPS Program. " The project grew out of
RFPNo. DU-74-A041 and SwRI's responding Proposal No. 11-9962,
dated January 7, 1974. The project was initiated on March 12, 1974;
and the technical effort was completed on September 30, 1974. It was
identified at SwRI as Project No. 11-3916.
The project leader for SwRI has been Charles T. Hare, Manager,
Advanced Technology, Department of Emissions Research. Overall
supervision has been provided by Karl J. Springer, Director, Depart-
ment of Emissions Research. Project Officer for the Environmental
Protection Agency has been Charles C. Masser, National Air Data
Branch.
111
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ABSTRACT
Emissions, population, and usage data existing in the technical
literature have been collected and organized for the following unregulated
sources: outboard motors, snowmobiles, motorcycles, lawn and garden
equipment, construction equipment, industrial equipment, and farm
equipment. The investigation has been limited to mobile sources utilizing
internal combustion engines and thus has not included plant processes or
stationary engines.
Sources of data for individual counties have been compiled,
mostly items which may have some correlation with equipment popu-
lation, usage, or emissions. Data found in these sources have been
restated only where necessary to other phases of the program.
Methodologies for estimating emissions and fuel consumption
on a county basis have been developed for the sources noted above.
They have been demonstrated for counties in the St. Louis Metropolitan
Air Quality Control Region (AQCR 070), and their strengths and weak-
nesses have been discussed. Methods have also been developed to ap-
portion county emissions estimates to grid elements, but they have not
been demonstrated. The exhaust constituents assessed include hydro-
carbons (HC), carbon monoxide (CO), oxides of nitrogen (NOX), parti-
culate, aldehydes (RCHO), and oxides of sulfur (SOX). For outboard
motors, neither particulate nor aldehyde data were available; but carbon
dioxide (CO?) emissions were included.
IV
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TABLE OF CONTENTS
FOREWORD
ABSTRACT iv
LIST OF TABLES vii
I. INTRODUCTION 1
II. SUMMARY OF NATIONAL AND STATE DATA ON
EQUIPMENT POPULATIONS, USAGE, AND EMISSIONS 3
A. OUTBOARD MOTORS 3
B. SNOWMOBILES 5
C. MOTORCYCLES 6
D. LAWN AND GARDEN EQUIPMENT 10
E. CONSTRUCTION EQUIPMENT 13
F. INDUSTRIAL EQUIPMENT 15
G. FARM EQUIPMENT 16
III. SOURCES OF DATA ON COUNTIES 21
IV. METHODOLOGY FOR COUNTY EMISSIONS ESTIMATES 23
A. OUTBOARD MOTORS 23
B. SNOWMOBILES 25
C. MOTORCYCLES 26
D. LAWN AND GARDEN EQUIPMENT 27
E. CONSTRUCTION EQUIPMENT 28
F. INDUSTRIAL EQUIPMENT 28
G. FARM EQUIPMENT 29
V. DEMONSTRATION OF COUNTY EMISSIONS ESTI-
MATION METHODOLOGIES 31
A. OUTBOARD MOTORS 31
B. SNOWMOBILES 32
C. MOTORCYCLES 34
D. LAWN AND GARDEN EQUIPMENT 34
E. CONSTRUCTION EQUIPMENT 37
F. INDUSTRIAL EQUIPMENT 39
G. FARM EQUIPMENT 42
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TABLE OF CONTESTS (continued)
Page
VI. METHODOLOGY FOR GRID ELEMENT EMISSIONS
ESTIMATES 45
A. OUTBOARDS 47
B. SNOWMOBILES 48
C. MOTORCYCLES 48
D. LAWN AND GARDEN EQUIPMENT 49
E. CONSTRUCTION AND INDUSTRIAL EQUIPMENT 49
F. FARM EQUIPMENT 50
VII. SUMMARY 51
REFERENCES 53
APPENDIXES
A. TABULAR DATA ON POPULATION, USAGE,
AND EMISSIONS OF SELECTED MOBILE SOURCE
CATEGORIES A-l
B. LIST OF COUNTY DATA SOURCES B-l
C. DOCUMENTATION OF COUNTY METHODOLOGY
DEVELOPMENT C-l
D. UTM TO GEOGRAPHIC COORDINATE CONVERSION
PROGRAM D-l
VI
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LIST OF TABLES
Table Page
1 Factors to Correct 1973 State Outboard Boat Regis-
trations for Exemption of Smaller Craft 4
2 Air Pollutant Emission Factors and Fuel Consump-
tion for Outboard Motors 5
3 Emission Factors and Fuel Consumption for Snow-
mobiles with 2-stroke Engines 6
4 Emission Factors and Fuel Consumption for Rotary-
Engine Snowmobiles 7
5 Annual Mileage Data for Motorcycles by Engine Type
and Size 8
6 Mileage Estimates Recommended for Motorcycles
and Population Breakdowns 8
7 Generalized Motorcycle Emission Factors and Fuel
Consumption by Engine Type 9
8 Motorcycle Exhaust Emission Factors and Fuel Con-
sumption per Unit Distance by Engine Type and Size 10
9 Motorcycle Annual Exhaust Emission Factors and
Fuel Consumption by Engine Type and Size 11
10 Assumed Populations of Lawn and Garden Equip-
ment (10/31/74) 11
11 Emission Factors for Lawn and Garden Equipment
by Type of Engine and Source of Information 12
12- Recommended Emission Factors and Fuel Usage
for Lawn and Garden Equipment 13
13 Estimates of Construction Machinery Populations,
Usage, and Rated Horsepower 14
14 Estimates of National Construction Equipment Emis-
sions and Fuel Consumption 14
15 Estimates of Heavy-Duty Industrial Engine Popu-
lation, Rated Power, and Annual Usage 15
VII
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LIST OF TABLES (continued)
Table Pa;
16 Emissions and Fuel Consumption of Industrial
Engines 16
17 Summary of Motorized Farm Equipment Annual
Usage Estimates 17
18 Emission Factors and Fuel Consumption for Farm
Equipment 19
19 Major Sources of Data on Counties 21
20 County Data to be Used in Determining Outboard
Motor Emissions Impact 32
21 Emissions and Fuel Consumption of Outboard
Motors for Counties in AQCR 070 33
22 Snowmobile Emissions and Fuel Consumption,
Counties in AQCR 070 35
23 Computation of Emission Factors and Fuel Con-
sumption for Motorcycles in AQCR 070 34
24 Emissions and Fuel Consumption of Motorcycles,
Counties in AQCR 070 36
25 Lawn and Garden Engine Emissions and Fuel Con-
sumption for Counties in AQCR 070 38
26 Computation of Illinois and Missouri Construction
Equipment Emissions as Percentages of National
Totals 37
27 Construction Equipment Emissions and Fuel Con-
sumption for Counties in AQCR 070 40
28 Computation of Industrial Equipment Population
Percentages for Counties in AQCR 070 39
29 Industrial Engine Emissions and Fuel Consumption
for Counties in AQCR 070 41
30 Farm Equipment Populations for Counties in AQCR 070 42
Vlll
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LIST OF TABLES (continued)
Table Page
31 Farm Equipment Emissions and Fuel Consumption
for Counties in AQCR 070 43
32 Summary of Emissions from Engine Categories
Under Study 44
33 Impact of Off-Highway Sources on Emissions in
AQCR 070 52
IX
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I. INTRODUCTION
This study is an extension of previous work by SwRI on emissions
from uncontrolled mobile sources using internal combustion engines, with
emphasis on estimates for counties and smaller areas. Prior studies
conducted at SwRI under Contract No. EHS 70-108 have been responsible
for the development and/or publication of a substantial fraction of avail-
able data for a number of engine categories. These categories include
locomotives, outboard motors, motorcycles, small utility engines,
farm equipment, construction equipment, industrial equipment, gas
turbine electric utility powerplants, and snowmobiles.
Of the categories noted above, seven were studied during this
project (outboards, snowmobiles, motorcycles, lawn and garden, con-
struction, industrial, and farm). The first objective was to compile and
summarize all available data on emissions, population, and usage of
engines in these categories. Sources consulted were reports for EPA
and other agencies, technical papers, state motor vehicle registration
departments, statistical publications, and others.
Another objective was to compile a list of data sources for coun-
ties and other small areas, and the results of this effort appear as Ap-
pendix B. Although a great deal of direct information on engine emissions,
population, and usage is not available for counties, sufficient data were
uncovered which are relatable to the desired variables to have made the
effort worthwhile. The final objectives of this study were to derive
methodologies for estimating emissions down to the county and grid
element levels,and to demonstrate the county methodologies for AQCR
070 (St. Louis Metropolitan). Even having accomplished these tasks,
the problem remains that no data are available against which the derived
results can be checked.
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II. SUMMARY OF NATIONAL, AND STATE DATA ON
EQUIPMENT POPULATIONS, USAGE, AND EMISSIONS
Engines for which emission estimation methodologies have been
developed under the subject program are used in a wide variety of leisure
and utilitarian applications. They represent all major non-automotive
engine markets up to about the 500 horsepower class» As a consequence
of this diversity in size, type, and field of application, data relating to
population, usage, and emissions of the engines are widely scattered
in the literature. This section of the report will summarize pertinent
data found for each engine category, as a matter of convenience and for
future reference,
A. OUTBOARD MOTORS
Data on the population of outboard motors or outboard boats and
their distribution by state are available through the U0S. Coast Guard^)
and The Boating Industry magazine^). Calendar year 1973 outboard boat
registrations in the 48 contiguous states plus the District of Columbia
totalled 4. 98 million, but some states did not register all outboard boats
operating on their waters. All registration exemptions for small boats
ran out at the end of 1973, however, so the 1974 registration total
(available in 1975) should show a strong increase due to inclusion of a
number of previously unregistered craft,, The 1973 Boating Industry
total for outboard motors in the same states was 1, 51 million, but the
exact basis for this figure is not known.
Breakdowns of the USCC'*' 1973 outboard boat registrations and
the Boating Industry'2) 1973 outboard motor population by state are given
in Appendix A, Tables A-l and A-2, respectively. The reliability of
boat population figures for 14 states will be in doubt until 1974 registra-
tion figures become available, but a correction for unregistered boats
can be estimated using an analysis of the total U.S. outboard motor
population by rated power category'-*'4'. Assuming that boats in the
power categories 0-6. 9 hp and 70 0-19« 9 hp are uniformly distributed
within the categories, the correction factors shown in Table 1 can be
used with corresponding state registrations to come up with more
^Numbers in parentheses indicate list of References at the end of thi-1
report.
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Table 1. FACTORS TO CORRECT 1973 STATE OUTBOARD BOAT
REGISTRATIONS FOR EXEMPTION OF SMALLER CRAFT
Exemption
5 hp or below
7. 5 hp or below
8 hp or below
9. 9 hp or below
10 hp or below
State(s)
TN, WV, WY
MD, MO
MT
ND
AR, FL, GA, LA,
ME, MS, NC
Calculated
% Unregistered
22,5
32.5
33.6
37.6
37.8
Correctioli factor
1.29
1.48
1.51
1.60
1.61
representative values. Performing this correction for all the states
exempting very small craft yields an additional 0.51 million outboard
boats, making the estimated current total about 5. 5 million,,
Relatively little good information is available on usage of out-
board motors or outboard boats, so estimates have been used previously^)
to compute the national impact of outboards. It is expected that climatic
conditions have a strong influence on outboard usage, so the usage aspect
will be handled with the emissions estimation methodology in Section IV.
Several studies have been conducted on outboard motor emissions^""),
but only the first one (References 3 and 4) has been published at this
time. In examining'outboard motor emissions data from all investiga-
tions, attention must be paid to segregating emissions computed or
measured to be ending up in the atmosphere from those ending up in the
water. Depending on the exhaust constituent of interest, fractions going
through the water to the atmosphere range from 40 or 50 to nearly 100 per-
cent. Emission factors for use in making small-scale atmospheric emission
estimates are presented in Table 2, along with fuel consumption factors.
It is anticipated that emission factors in grams per motor hour and fuel
consumption factors in gallons per motor hour will be the most useful
of those given, but factors are also given in other units for convenience.
A number of states keep data on registration of outboard boats
and/or outboard motors by county, but requests for such data were not
sent to all states. In the course of looking for socioeconomic data,
however, a number of state statistical publications were obtained which
contained boat registration data. County registrations were obtained in
this manner for New YorkC7), OhioW, South Carolina(9), and Wiscon-
sin^); but some of these data were out of date by as much as seven
years.
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Table 2. AIR POLLUTANT EMISSION FACTORS AND
FUEL CONSUMPTION FOR OUTBOARD MOTORS
Fuel consumption
Units
g/ rated hp hr
gal/ rated hp hrb
kg /motor hra
gal/motor hra» b
Value
174.
0.0622
4.28
1.53
Atmospheric exhaust emissions
Units
g/ rated hp hr
g/motor hra
g/gal fuelb
HC
31.3
769.
503.
CO
92.7
2,280.
1,490.
C02
1430
3,510.
2,300.
NOX
0. 18
4.5
3.0
SOX
0.18
4.4
2.9
aBased on average motor rated horsepower of 24.6.
bBased on fuel density of 6. 17. lbm/gal = 0.739 g/ml.
B. SNOWMOBILES
Registration of snowmobiles by state is summarized at least
annually by the International Snowmobile Industries Association (ISIA),
and the latest data available are dated March 1, 1974^*). The total of
all U.S. registrations as given in the ISIA data is 1. 71 million, and an
additional 00 86 million are listed for Canada,, Tabulation of all the state
registrations is given in Table A-3 of Appendix A. In addition to the ISIA
data, the only information found on snowmobile population was registra-
tion data by county for New YorkA').
Annual usage of snowmobiles is not a well-defined quantity, and
all values used in the literature to date have been estimated'^-14^ The
estimates used in the referenced publications were 60 hr/yr and 100 hr/
yr, respectively, the former figure being based on qualitative information
from a number of sources. For lack of information to the contrary, the
60 hr/yr estimate will be adopted for the purposes of this report.
Data on exhaust emissions from snowmobile engines are available
from three sources(12-l6)> although information from Reference 12 (and
Reference 13, which is based on Reference 12) is much more comprehen-
sive and complete than that from the others. Reference 16 contains
rudimentary raw data (one speed, several loads and mixtures) on one
engine, and Reference 14 develops an emission factor based on the same
engine. Reference 15 contains basic data (one speed, one load, several
mixtures) on one engine and no real attempt at computing an emission
factor. Reference 12 includes data on four engines (three 2-strokes and
one rotary), each of which was operated at 29 speed/load conditions
using manufacturers' recommended carburetor settings. Where pos-
sible, all these data will be taken into consideration; but it is obvious
that data from Reference 12 will be relied upon most heavily,,
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Emission factors and fuel consumption for 2-stroke snowmobiles
have been computed in several sets of units, and they are presented in
Table 3. The emissions values obtained for a rotary snowmobile engine^2)
Table 3. EMISSION FACTORS AND FUEL, CONSUMPTION
FOR SNOWMOBILES WITH 2-STROKE ENGINES
Units
g/ rated hp hr
g/unit hr
g/gal fuel
kg/unit yr
Emission factors'"-2'
HC
23. 1
630.
670.
3708
CO
35.9
978.
1000.
58. 7
NOX
0.367
10.0
ii.
0.60
Part.
1.02
27.9
30.
1.67
RCHO
0.34
9.2
9.8
0.55
sox
0.031
0.85
0.90
0.05
Emission factors' '
HC
29.
580.
58.
CO
105.
2100.
210.
NOX
0.32
6.40
0.64
Fuel consumption
(12)
Units
g/ rated hp hr
gal/ rated hp hr
kg /unit hr
gal/unit hr
kg /unit yr
gal/unit yr
Value
97.
0.035
2.6
0.94
160.
56.
Notes:
average rated hp = 20(14) or 27. 22<12)
annual usage = 100 hr(14) or 60 hr(12)
average load factor = 0. 5o(14) or 0. 210(12)
fuel density =6.2 lbm/gal = 0. 743 g/ml
are not included in Table 3, because they were different than 2-stroke
levels in several cases. It should be noted that the values are based on
tests of only one engine, a 35 hp unit, and that care must be exercised
in choice of scaling factors when the data are used to represent other
rotaries. Emission factors and fuel consumption for rotary-engined
snowmobiles are given in Table 4 in several sets of units. Factors from
both Tables 3 and 4 can be used for snowmobile populations where the
fraction of each type in the population is known or can be estimated. The
OMC rotaries have been on the market less than three seasons as of now
(10/74); so if the population breakdown is not available, only small
errors would be introduced by assuming that the population is all of the
2-stroke type and using factors from Table 3.
C. MOTORCYCLES
Motorcycle registrations by state are compiled by the U. S.
Department of Transportation, Federal Highway Administration. These
data are published annually in Statistical Abstract of the United StatesU?),
Highway Statistics^22'. and elsewhere. Another source for reasonably
accurate i .ate registration data is Automotive Industries(^S) magazine,
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Table 4. EMISSION FACTORS AND FUEL CONSUMPTION
FOR ROTARY-ENGINE SNOWMOBILES^2)
Fuel consumption
Units
g/ rated hp hr
gal/ rated hp hr
kg /unit hr
gal/unit hr
kg /unit yr
gal/unit yr
Value
124.
0.044
4.3
1.54
260.
92.
Emission factors
Units
g/ rated hp hr
g/unit hr
g/gal fuel
kg /unit yr
HC
4. 14
145.
94.
8.70
CO
71.7
25100
1600.
151.
NOX
0061
21.2
14.
1.27
Part.
0029
10.2
6.6
0.61
SOX
0.052
1.81
1.2
0.11
Notes: rated hp = 35
annual usage = 60 hr
average load factor = 0. 217
fuel density =6.2 Ibm/gal = 0. 743 g/ml
and this source has a shorter time lag than the official government pub-
M n\
Iications0 The latest registration data available now are for 1973^ ',
indicating total U. S. registered motorcycles to be about 4.36 million.
A recent national survey(19) indicates that 21 percent of all motorcycles
may be unregistered, bringing the estimated national total to 5.52 million
units. The 1973 registrations by state mentioned above are tabulated in
Table A-4 of Appendix A.
A great deal of information is available now regarding motorcycle
usage, but none of it is without flaws. The most comprehensive sources
are two statistical surveys^-*-?' 20) conducted quite recently by a marketing
research firm. The major problems with these data are: (1) that all
survey participants were city residents, and (2) that the researchers used
a "median average" rather than the arithmetic mean for expressing yearly
mileage to compensate for what they felt to be respondent or interviewer
errors resulting in high mileage figures. The influence of sampling
only in cities cannot be estimated quantitatively, but a recent publication
on fuel usage estimation by county(^l) indicates annual light-duty vehicle
mileage in rural areas may be significantly greater than that in urban
areaso How well this directional generality would work for motorcycles
is not known.
Annual mileage data in terms of medians and means from the two
surveys\19, 20) are shown in Table 5 as functions of engine size and type.
Most of the trends from the two surveys compare rather well, but the
median average mileages are grossly different. This result is difficult
to explain in view of the very good agreement of the overall mean averages;
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Table 5. ANNUAL MILEAGE DATA* FOR MOTORCYCLES
BY ENGINE TYPE AND SIZE
Engine size
90cc or less
91-190cc
191-290cc
over 290cc
All
Annual mileage by type(19)
2 -stroke
828
1,644
1,968
2,796
1,896
4-stroke
1,560
1,980
3,000
4,464
3,456
Mean average
All
1, 152
1,764
2,232
3,948
2,280
3, 276
Annual mileage by type(20)
2 -stroke
620
1, 170
1,630
2,420
1,420
4-stroke
480
1,240
1,300
2,740
1,870
Mean average
All
560
1, 170
1,570
2,580
1,590
3,460
a"Median average" mileages except where otherwise noted.
and in combination with other mathematical and logical errors in the survey
analyses, the disagreement makes strong confidence in the overall survey
results impossible.
Other mileage estimates for motorcycles'22, 23) nave been largely
a matter of speculation, except one set of figures released in 1973 by the
Motorcycle Industry Council (MIC)'24)j These estimates were 1900 miles
per year for machines under lOOcc, 2500 miles per year for 100-199cc
units, 3000 miles per year for bikes in the 200-299cc class, and 4500
miles per year for units 300cc or larger. Even with all the information
available, there is not a clear-cut choice of existing mileage data which is
obviously accurate. Consequently, the estimates in Table 6 are recom-
mended in lieu of more reliable information. The population percentages
Table 6. MILEAGE ESTIMATES RECOMMENDED FOR
MOTORCYCLES AND POPULATION BREAKDOWNS
Engine size
90cc or less
91- 90cc
191-290cc
over 290cc
Annual mileage
750
1400
2100
3000
National mean 1996
% of populationU9)
21
27
11
41
Overall
% of population (^9)
2-stroke
11
19
8
13
51
4-stroke
9
8
3
29
49
aComputed using population percentages from Reference 19.
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by engine size in Table 6 can be used for the nation as a whole, but more
accurate regional size breakdowns'19) are given in Appendix A, Table
A-5. The breakdown by engine type in Table 6 can be used for all areas.
It should be noted that where parts of an Air Quality Control Region (AQCR)
fall into two or more motorcycle "regions", it would probably be logical
to use compromise population percentages by engine size for the entire
area rather than use different ones on either side of a boundary.
Data on emissions from motorcycles are available from several
S-Z?)^ j-,^ those given in Reference 25 (and refined in Reference
26, a paper based on Reference 25) are by far the most comprehensive.
Emissions data given in the Olson report'2**) are not useful in computing
emission factors due to the inaccuracy of the old procedures used.
Factors listed by AESi in its report to the California Air Resources
Board(27) are essentially equal to those developed by SwRI in its report
to the Environmental Protection Agency'25) and almost equal to the
refined factors(26)t
If a simplified calculation of motorcycle emissions is desired,
data from Table 6 can be used in conjunction with emission factors from
Table 7. A more detailed analysis can be performed (by "region", as
Table 7. GENERALIZED MOTORCYCLE EMISSION FACTORS
AND FUEL CONSUMPTION BY ENGINE TYPE
Application
on- road
off -road
Engine
type
2-s
4-8
2-s
4-s
Data
ref.
25
26
27
25
26
27
27
27
Emissions in grams per mile
HCa
16.
17.
16.
3.5
3.6
3.5
24.
4.0
CO
27.
30.
27.
33.
34.
33.
3204
39.6
N0xb
0.12
0.11
0. 12
0.24
0,23
0.24
0.06
0,36
Part.
0.33
Oo36
0.33
0.046
0.048
0.04
0.33
0.04
RCHO
0. 11
0. 12
0.047
0.050
-
sox
0.038
0.040
0.022
0.023
-
Fuel,
mi/gal
41
44
-
alncludes an allowance for evaporative emissions.
"Does not reflect correction to new driving schedule for testing
smaller (under 170cc) motorcycles'29).
defined in Table A-5) by using emission factors from Table 8 and population
breakdowns from Table 6. These factors can be expressed in other units
when the annual mileage estimate from Table 6 is used, and the results
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Table 8. MOTORCYCLE EXHAUST EMISSION FACTORS
AND FUEL, CONSUMPTION PER UNIT DISTANCE
BY ENGINE TYPE AND SIZE
Engine size
90cc or lessa
91-190cca
191-290cc
over 290cc
Emissions from 2- stroke motorcycles
in grams per mile
HC
6
10
18
25
CO
6
12
30
50
NOX
0.11
0.10
0.04
0.04
Part.
0. 14
0.19
0.35
0.55
RCHO
0.10
0. 11
0. 13
0. 14
SOX
00021
0.025
0.043
0.057
Fuel usage,
mi /gal
80
69
40
30
Engine size
90cc or lessa
91-190cca
191-290cc
over 290cc
Emissions from 4-stroke motorcycles
in grams per mile
HC
2.2
2.6
3.4
4.8
CO
20
24
32
46
NOX
0.22
0.20
0. 17
Oo 11
Part.
0.022
0.030
0.045
0.070
RCHO
Oo018
0.026
0.044
0.079
sox
0.014
0.017
0.022
0.031
Fuel usage,
mi /gal
88
74
56
40
aOnly the NOX values have been corrected to reflect the new smaller-
bike (under 170cc) cycle(29)f
are given in Table 9. Note that all the factors developed thus far except
those given in Table 7 include no evaporative emissions. The data and
method required to estimate evaporative emissions will be presented with
the county motorcycle emissions estimation methodology in Section IV.
D. LAWN AND GARDEN EQUIPMENT
In estimating the number of small utility engines used nationwide
in lawn and garden equipment, there are no registration statistics and
very few reliable data on sales or production. The best estimates available
at present are summarized in Table A-6 of Appendix A(^> 30, 31)^ an(j tney
are discussed and evaluated in a previous report to the Environmental
Protection Agency^32) and a technical publication based on that report^33).
In attempting to account for utility engines used for lawn and garden appli-
cations, a major supposition is that the equipment should be distributed
more or less in proportion to the number of single-unit housing structures.
It has also been assumed that a rough balance should occur between extra
units operated on commercial or public property and homes which have no
engine-powered equipment. A good check on these assumptions is to note
10
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Table 9. MOTORCYCLE ANNUAL EXHAUST EMISSION FACTORS
AND FUEL CONSUMPTION BY ENGINE TYPE AND SIZE
Engine size
90cc or less
91-190cca
191-290cc
over 290 cc
Emissions from 2 -stroke motorcycles
in kg per year
HC
4.5
14.
38.
750
CO
4.5
17.
63.
150.
NOX
0.082
0. 14
0.08
0. 12
Part.
0. 10
0.27
0.74
1.65
RCHO
0.075
0.15
0.27
0.42
S°x
0.016
0.035
0.090
0. 17
Fuel usage,
gal/yr
9.4
20.
52.
100.
Engine size
90cc or lessa
91-190cca
191-290cc
over 290 ccc
Emissions from 4-stroke motorcycles
in kg per year
HC
1.6
3.6
7.1
14.
CO
15.
34.
67.
140.
NOX
0. 16
0.28
0.36
0.33
Part.
0.016
0.042
0.094
0.21
RCHO
0.014
0.036
0.092
0.24
SOX
0.010
0.024
0.046
0.093
Fuel usage,
gal/yr
8.5
19.
38.
75.
aOnly the NOX values have been corrected to reflect the new smaller-
bike (under 170cc) cycle
(29)
that the 1970 census' ' showed 46.8 million single-unit housing structures
(49.6 million projected to the present), while the population of lawnmowers
(alone) projects to about 45. 6 million at present. This sort of agreement
is quite reasonable and tends to support the overall assumptions.
Based on data from Table A-6 and assuming a growth rate of 6
percent per year for the population of lawn and garden equipment since
1968, the equipment populations basic to this estimation methodology
are presented in Table 10. Usage of lawn and garden equipment undoubtedly
Table 10. ASSUMED POPULATIONS OF LAWN
AND GARDEN EQUIPMENT (10/31/74)
Engine type
4-stroke
2-stroke
Snowthrowers
Other equipment
Total
Typical rated hp
3.5
3.0
3. 5 (approx. )
3. 5 (approx. )
Engines in service
50.9 x 106
3.5 x 106
1 . 5 x 1 06
52.9 x 106
54.4 x 10&
11
-------
varies with climate, but a well-founded overall estimate of average
usage is 50 hours per year(^^', A method has been developed to cor-
rect individual county emissions for climate utilizing mean frost-free
days per year as basis, and it will be discussed in Section IV as the
methodologies are outlined.
Data on emissions from small utility engines are available in
several References^ ' ' ' ' ' representing the results of three
independent studies. The study reported on in References 14 and 16 was
a limited laboratory investigation of 36 engines, with 29 4-stroke engines
and seven 2-stroke engines in the sample. Reference 27 reports on a
study in which eleven machines (eight 4-stroke and three 2-stroke) were
operated through their normal tasks (cutting grass, tilling, etc.) while
their exhausts were collected via a large bag or a constant-volume sam-
pler. These data may be closer to real-life emissions than any other
information available at this time. The work reported on in References
32 and 33 was an intensive laboratory study of five engines, with one 2-
stroke engine and four 4-strokes in the group investigated. Some degree
of effort was expended by the original researchers or by others on develop-
ment of emission factors and emissions impact using each of the three
studies as basis.
Hourly mass emissions and fuel consumption for the lawn and
garden applications of small utility engines are given in Table 11 as
Table 11. EMISSION FACTORS FOR LAWN AND GARDEN EQUIPMENT
BY TYPE OF ENGINE AND SOURCE OF INFORMATION
Engine type
4-stroke
2-stroke
Data from
reference
16
27
32
16
27
32
Emissions in grams per hour
HC
19.
40.
34.
170.
280.
300.
CO
333.
380.
380.
418.
650.
670.
NOX
5.2
4.0
4.3
1.2
2.0
2.2
Particulate
0.7a
0.6
10. a
9.4
RCHO
0.7
2.8
SOX
0.5
0.8
Fuel usage,
gal/hr
0.177
0.21
0.400
0.41
Adopted from Reference 32 by author of Reference 27.
estimated according to each of the major studies conducted. Data from
studies described in References 27 and 32 are considered to be most
representative, so a compromise set of emission factors has been drawn
up using these references as basis and is presented as Table 12. These
factors can be used with the methodology as outlined in Section IV to
estimate emissions on a county basis.
12
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Table 12. RECOMMENDED EMISSION FACTORS AND FUEL, USAGE
FOR LAWN AND GARDEN EQUIPMENT
Units of
factor
g/hr
kg/yra
Engine or
equipment
4-s (all)
2-s snow-
thrower
Other 2-s
4-s snow-
thrower
2-s snow-
thrower
Other 4-s
Other 2-s
Emission factors
HC
37.
350.
300.
0.19
1.9
1.8
15.
CO
380.
770.
660.
2.0
4.1
19.
33.
NOX
4.2
2.4
2.1
0.02
0.01
0.21
0.01
Part.
0.6
11.
9.4
0.00
0.06
0.03
0.47
RCHO
0.7
3.3
2.8
0.00
0.02
0.04
0.14
sox
0.5
0.9
0.8
0.00
0.00
0.02
0.04
Fuel usage
Value
0.20
0.47
0.40
1.1
2.5
10.
20.
Units
gal/hr
gal/hr
gal/hr
gal/hr
gal/hr
gal/hr
gal/hr
Assuming 40 inches snowfall for snowthrowers and a 213 day season for other
equipment.
E. CONSTRUCTION EQUIPMENT
Although the project considered construction and industrial
equipment as a single category, it now seems more reasonable to con-
sider them separately and thereby reduce the risk of logical errors. In
conjunction with efforts toward developing emission factors, a number
/?7 *^4— ^ ft ^
of sources* '» ~ ' provide estimates of construction equipment popu-
lations. In two of these References'-^, 38), ^e scope was limited to a
single state; so populations estimated therein are not general enough
for present purposes. Another study*") made no distinction between
construction and industrial equipment usage, so its population figures
cannot be used here. Two more References*'-35' ^6) ^o not make use of
explicit equipment populations, but rather a total horsepower-hour figure,
in estimating emissions impact. By elimination, Reference 34 is the only
usable source of population data on construction equipment. Table 13
summarizes these estimates by equipment category, along with data
from several sources on typical machine horsepower and-annual usage.
Since the result required from this section for input to the county
construction equipment methodology is total national construction equip-
ment emissions, only three References*'34' 35' 36) can be used for finai
comparison. Emission factors developed in some of the other studies,
however, are useful for indicating the range of estimates available; and
all the factors available are included in Table A-7 of Appendix A. Values
for national construction equipment emissions are given in Table 14, in-
cluding amounts estimated for earthmov4ng equipment as well as all
13
-------
equipment categories. Agreement between estimates for earthmoving
equipment is reasonably good, although entirely different assumptions
were made for the estimate in Reference 34 as compared to the other
two.
Table 13. ESTIMATES OF CONSTRUCTION MACHINERY
POPULATIONS, USAGE, AND RATED HORSEPOWER
Equipment category
Tracklaying tractors
Tracklaying loaders
Motor graders
Scrapers
Off-highway trucks
Wheel loaders
Wheel tractors
Rollers
Wheel dozers
General purpose
Estimated
/34\
population^ '
197, 000
86,000
95,300
27,000
20,800
134,000
437,000
81,600
2,700
100,000
Est. usage, hr/yr
Ref.
27a
1350
1700
2000
1000
2400
1400
900
700
1800
600
Ref.
34
1050
1100
830
2000b
1
2000°
1140
740
740
2000
1000
Ref.
36
1500
2000
1200
2000
2200
2000
Estimated
power, hp
Ref.
27a
140
240
105
475
420
140
82
78
330
115
Ref.
34
120
65
90
475
400
130
75
75
300
120
aThese estimates are not considered entirely independent of those in
Reference 34 and are intended for California only.
These estimates are not independent of those in Reference 36.
Table 14. ESTIMATES OF NATIONAL CONSTRUCTION
EQUIPMENT EMISSIONS AND FUEL CONSUMPTION
Equipment
categories
All const.
Earth-
moving
Fuel
Diesel
Gasol.
Diesel
Diesel
Diesel
Ref.
34
34
35*
36b
34
Emissions in kg/yr x 10
HC
72.
56.
55.3
39.9
57.4
CO
220.
1100.
164.
202.
160.
NCV
820.
36.
376.
567.
529.
Part.
63.
2.2
— _ _
18.1
34.8
RCHO
17.
1.
_ __
10.
sox
65.
1.6
_ - - _
97.0
42.3
Fuel, 106
gal/yr
4615.
602.
3609.°
3874. c
3368.
""Estimate for 1969 made in 1970.
Estimate for 1969 made in 1972.
GAssuming a BSFC of 0.44 lbm/hp hr = 200 g/hp hr,
fuel density = 0. 86 g/ml.
14
-------
F. INDUSTRIAL EQUIPMENT
This category of engines includes a relatively large number of
small utility engines similar to those used in lawn and garden equipment
and a much smaller number of more durable, more expensive engines
of the heavy-duty type. Treating the heavy-duty class first, it includes
items such as fork lift engines, auxiliary engines used on mobile equip-
ment, engines used in the mineral industries, and pump and generator
engines used by airports and utilities. The major source of information
on this class of equipment is a previous report to the Environmental
Protection Agency* ', in which engine populations and size distributions
were estimated on the basis of engine shipments and their value. These
estimates are presented in Table 15 along with assumptions on annual
Table 15. ESTIMATES OF HEAVY-DUTY INDUSTRIAL ENGINE
POPULATION, RATED POWER, AND ANNUAL USAGE*34)
Engine type
Diesel
Gasoline
Typical rated hp
125
55
Annual usage, hr/yr
600
300
Population
417, 000
990,000
engine usage which are about one-half the numbers of hours estimated
earlier for comparably-sized construction equipment.
The light-duty gasoline engines used in industry are assumed to
be the relatively inexpensive air-cooled type. The population of these
engines can be estimated by extending the method used in Reference 34
and by assuming that: (1) useful life of these engines averages 600 hours
and (Z) annual usage averages 100 hours. The resulting population esti-
mate for light-duty industrial gasoline engines is 5.8 million units, and
average rated horsepower is estimated at 3.86* '.
Information on emissions from one or more types of industrial
engines is found in several of the same sources already utilized(27, 33,
34, 37)^ Reference 37 is limited in scope to industrial tractors only,
but the specific emissions data are useful for comparison. Reference 27
contains original emissions data only on light duty gasoline engines.
Emissions data from these sources are summarized in Table 16 along
with fuel consumption estimates and a compromise figure is given for
emissions from the light-duty class of industrial engines. The total of
estimated annual emissions can be used with the methodologies developed
in Section IV to estimate county and grid emissions totals.
15
-------
Table 16. EMISSIONS AND FUEL CONSUMPTION
OF INDUSTRIAL ENGINES
Engine type
Heavy-duty
diesel
Heavy-duty
gasoline
Light-duty
gasoline
Ref.
34
37a
34
34
37a
34
27b
33
c
c
Units
g/hp hr
g/hp hr
106 kg/yr
g/hp hr
g/hp hr
10b kg/yr
g/hr
g/hr
g/m
10b kg/yr
Emissions
HC
1. 12
2.7
18.2
6.68
2.8
86. 5
50.0
29.2
32.
19.
CO
3.03
6.5
49.3
199.
163.
1690.
600.
386.
400.
230.
NOX
14.0
8.3
228.
5. 16
7.8
43. 8
10.0
7.68
7.3
4.2
Part.
1.00
-
16.2
0.327
-
2.8
0.7
0.68
0.68
0.39
RCHO
0.21
-
3.4
0.22
-
1.9
_
0. 72
0. 72
0.42
SOX
0.931
-
15.1
0.268
-
2.3
_
0.60
0.60
0.35
Engine type
Heavy-duty
diesel
Heavy-duty
gasoline
Light-duty
gasoline
Ref.
34
37a
34
34
37a
34
27b
33
c
c
Fuel
Units
g/hp hr
g/hp hr
106 gal/yr
g/hp hr
g/hp hr
106 gal/yr
gal/hr
gal/hr
gal/hr
106 gal/yr
Value
211.
193.
1067.
312.
243.
941.
0.300
0.25
0.23
133.
Industrial wheel tractors only.
^Category called "home utility" in reference.
cCompromise between estimates given in
References 27 and 33, based on 3.86 average engine hp .
G. FARM EQUIPMENT
The population of farm equipment is quite well defined down to the
county level due to the availability of the Census of Agriculture^^), This
reference can be considerably out of date, since it is published at five-
year intervals, but the equipment populations change slowly enough so that
16
-------
most of the data remain reasonably accurate. The edition used in pre-
paring this report was for 1969, and a new one (dated 1974) should be out
in 1976. Data given in this reference are much too voluminous to be
included here, but copies of the whole document are available in most
libraries.
Farm equipment usage information is available in the form of
estimates from several sources(33, 34, 37, 3>8)> but accurate survey data
are not available. The estimates are summarized in Table 17, along with
Table 17. SUMMARY OF MOTORIZED FARM
EQUIPMENT ANNUAL USAGE ESTIMATES
Type of equipment
Diesel tractor
Gasoline tractor
Self-propelled combine
Pull combine
Balers
Forage harvesters
Miscellaneous heavy-duty
Miscellaneous light- duty
Ref.
34
37
38b
34
37
38b
34
38b
34
38b
34
38b
34
38b
34
38b
34
Estimated annual
usage, hours
490
432
600
291
282
500
73
100
52
100
24
60
120
100
50
50
50
Typical
power, hp
80. 2a
78. 4a
80.4
40. 9a
39. 7a
50.5
110.
120/105°
25.
120/105°
40.
70/50C
140.
150/110°
30.
60/30°
3.5
Typical
load
factor
0.57
0.43
0.57
0.57
0.36
0.57
0.52
0.52
0.52
0.52
0.52
0.52
0.52
0.50
0.52
0.50
0.40
aFlywheel hp
"-"California only
cEstimates for diesel/gasoline equipment.
17
-------
values for the typical horsepower and load factor of each category of
equipment. Estimates given in References 34 and 37 for tractors are
in very good agreement, but those in Reference 38 show much higher
usage. It should also be noted that tractor horsepower estimates in
Reference 38 apparently do not include a correction for power train
losses. It is recommended that the values of usage and horsepower
from Reference 34 be used when computing emissions from a given area
due to their consistent availability, but estimates for tractors could be
made using Reference 37 with little change in overall values. Usage of
estimates from Reference 38 should at least be restricted to California,
and the power loss correction noted above should be made for any cal-
culation involving tractors.
In order to be usable in the emissions estimation methodology
without modification, farm equipment emission factors should be ex-
pressed in kg/hr. This step is presented as Table 18 for data from
several references, along with information on fuel consumption. Hourly
emission factors from all the sources are in reasonably good agreement
for diesel tractors, and the disagreements for gasoline tractors stem
primarily from the variation in load factors shown by Table 17 (these
comments also apply to fuel consumption). Since the emission factors
from Reference 38 are derived mainly from those in Reference 34, the
more complete documentation of Reference 34 makes it the logical choice
over Reference 38 for all categories. Making a choice between References
34 and 37 in the gasoline tractor category, however, is a more difficult
problem. For hydrocarbons, the choice would have to be Reference 34
due to the greater accuracy of the analytical method used (FID rather
than NDIR). A compromise between values given in References 34 and
37 for CO, NO , and fuel consumption would probably be most appro-
priate, resulting in factors of 2.86, 0.134, and 5.08 kg/hr, respectively.
18
-------
Table 18. EMISSION FACTORS AND FUEL CONSUMPTION
FOR FARM EQUIPMENT
Equipment
type
Diesel
tractor
Gasoline
tractor
Self-propelled
combine
Pull combine
Baler
Forage
harvester
Miscellaneous
heavy-duty
Miscellaneous
light -duty
Ref.
34
37
38
34
37
38
34
38
34
34
38
34
38
34
38
c
Emission factors, kg/hr
HC
0.078
0.092
0.063
0. 208
0.041b
0.197
0. 300
0.259
0.116
0.183
0. 179
0.122
0.171
0.082
.0.079
0. 029
CO
0. 154
0.221
0.139
3.34
2.38
4.11
6.37
6. 50
2. 83
4.53
5.33
0..297
2.25
1.73
1. 70
0.363
NOX
0.429
0. 282
0.426
0. 155
0. 113
0. 190
0.408
0.417
0.068
0.109
0. 148
0.657
0.612
0.112
0.175
0.007
Part.
0.059
0.050
0.008
0.010
0.054
0.055
0.005
0.008
0.012
0.110
0.098
0.015
0.025
0.001
RCHO
0.016
0.007
0.015
0.003
0.005
0.022
0.004
0.001
S0:.
0.040
0.040
0.006
0.007
0.034
0.033
0.004
0.006
0.007
0.067
0.060
0.009
0.015
0.001
Fuel*,
r - / hr
9.06
8.06
8.23
6.30
3.86
6.94
15.3
12.6
4.25
6.80
6.34
15.2
14.3
4.17
4. 71
0.58
aWhere necessary, densities assumed were 0. 731 g/ml for gasoline and
6.851 g/ml for diesel fuel.
bBased on NDIR data.
°Based on factors for light-duty industrial engines, Table 16.
19
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III. SOURCES OF DATA ON COUNTIES
Amid all the information available in the literature on subjects
which bear on this study, very little is available for the county level.
The major sources of county data utilized are given in Table 19, along
Table 19. MAJOR SOURCES OF DATA ON COUNTIES
Source
Type of data contributed
County and City Data Book
1969 Census of Agriculture
^40^
Area Measurement Reports' '
New York State Statistical
Yearbook -
Statistical Abstract of Ohio -
1969(8)
South Carolina Statistical
Abstract - 1973(9)
Wisconsin Statistical Abstract -
Third Edition - June 1974(10)
Secretary of State, State of
Illinois*42)*
Missouri Department of
(43)
Revenue '
Demographic, business, agricultural
Agricultural equipment populations
(1969)
Land and water areas (I960)
Outboard and snowmobile registration
data
Outboard registration data
Outboard registration data
Outboard registration data
Motorcycle registration data
Motorcycle and outboard registration
data
Two examples of sources for motorcycle registration data - the other
states were not contacted.
21
-------
with descriptions of the types of data obtained. In some cases, of
course, the data contributed by a given source to this project cons-
titute only a small portion of the data available from that source; and
there may be a great many more sources (e.g., state motor vehicle
departments) which provide equally useful data.
A number of other sources contain a lesser amount of data for
counties, and these sources are listed (along with those given in Table
19) in Appendix B. Another source of county data useful to this effort
has been county maps of the type prepared and distributed by state high-
way departments. These maps normally include not only roads but also
bodies of water, boundaries and populations of incorporated places, rural
dwellings, and many other features. The maps used during this project
were on a scale of one-half inch equals one mile (1:126, 720), but larger-
scale maps are usually available and should be used for any serious ef-
fort at making county and grid emissions estimates.
22
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IV. METHODOLOGY FOR COUNTY EMISSIONS ESTIMATES
Availability of data and the applicability of specific items and
techniques varies among the emissions sources being considered here,
so each source will be considered in a separate subsection. Before ar-
riving at the methodologies presented, experimentation was conducted
with a number of alternatives for some of the source categories. Docu-
mentation of this research is provided in Appendix C, although the
methods presented in the text are recommended as preferable overall.
A. OUTBOARD MOTORS
As a consequence of the Federal Safety Act of 1971, most states
are currently registering all power boats operating within their borders;
but a few states still exempt very small craft (common exemption limit
is under 10 horsepower). Statistics for 1974 (available in 1975) should
have registrations fo'r all power boats, since the exemptions are no
longer approved by the Coast Guard after calendar year 1973. A number
of states tabulate boat registrations by county as well as total for the
state, but county tabulations are not required for Coast Guard approval.
For the states in which boat registrations are available by county,
the county boat population will be assumed to equal registrations plus
any applicable correction for boats not registered. It would be worth
expending considerable effort to find boat registrations by county or to
extract such values from available data, because registrations by county
are not easily projected from other generally-available county data.
Data from four states (New York^7), Ohio^8), South Carolina^9),
and Wisconsin* ) confirm that boat registrations correlate strongly
with population on a county basis. Simple regression analysis shows
correlation coefficients r^ from 0. 70 to 0. 99 for individual states,and
around 0. 75 for the four states taken together. New York data' '' also
show that, except for inland counties having no surface water usable
for boating ("dry" counties), boats used correlate strongly with boats
registered (r^ over 0. 9). To be recorded by the Bureau of the Census'"*^',
ponds mut'"•. be at least 40 acres (0. 16 km ) in area and streams must be
23
-------
at least 1/8 mile (0. 20 km) wide. The best estimate of boats used in a
county, therefore, is to apportion total state boat registrations (corrected
for boats not registered, if any) by population. Adjustments for individual
inland counties can be made if no inland water usable for boating exists
by simply neglecting outboard emissions. Care should be exercised,
however, to make certain that a given county really has no water usable
for boating; because many reservoirs have been constructed since these
area measurements were made (I960 or earlier). A correction for dis-
proportionately low registrations and usage in densely populated counties
can also be made according to the empirical relationship (based on four-
state dataC7'10)
percent of state boat total used in county =
31.6 (population density, inhabitants/mi )~ * x
(percent of state population in county)
for counties having population densities over 1000 inhabit ants/ mi .
The general equation to be used for outboard emissions is
county emissions (kg/yr) = (boats used in county) x
(emission factor, kg/unit year).
The emission factor is a function of the mixture of boats in the boat
population (sizes and types) as well as annual operating time. Although
it would be desirable to use a specific mixture of boat sizes and types
for each county, such data are not available; so it will be necessary to
assume a "typical" mixture'^' in order to proceed with calculations.
Annual boat usage has been estimated to average 75 hours nation-
wide^ ', but usage undoubtedly varies with climatic conditions. For the
purposes of this methodology, annual usage will be estimated by the
equation
annual boat usage (hr) = 10C2J
where Q-^ ~ number of months during which "monthly normal" temperature
exceeds:
45° F for counties in the north region (43°N latitude
and northward)
48° F for counties in the central region (37°N latitude
to 43°N latitude)
55°F for counties in the south region (south of 37°N
latitude).
24
-------
The temperatures were computed by assuming that the annual
period of usage averages six months in the north region, seven months
in the central region, and eight months in the south region. "Monthly
normal" temperatures are averages of daytime highs and lows averaged
over each month of the year for a long period of time (typically 30 years
or more). Such data are usually compiled for all weather stations, and
data for the nearest weather station can be used. The expression for
the yearly average emission factor thus becomes
emissions in kg/unit yr = 0.01 G£ (emissions in g/unit hr).
It is understood that the emissions under consideration are air pollutants
only, so the factors should not include pollutants expected to remain in
the water phase.
B. SNOWMOBILES
Snowmobiles are used mainly in the north central and northeast
states, and good state registration data are available' '. Registrations
by county, however, were found only for New YorkA ''; and they correlate
very well with snowmobiles used in each county (r^ over 0. 99). In order
to predict usage of snowmobiles by county where county data are not
available, urban and non-urban counties should be separated. For non-
urban counties in New York (population density under 1000 inhabitants
per square mile), multiple regression analysis yielded the following
relationship (r^ = 0.66):
percent of state snowmobiles used in county = -2.345 +
1.560 (percent of state population in county) +
0.0325 (percent snowfall at state geographic center).
Other variables with which experimentation was conducted, such as num-
ber of developed trails and number of large farms, exhibited very weak
correlation with snowmobile usage. The percentages resulting from the
equation above can be used with state snowmobile registrations to com-
pute the number of snowmobiles operating in each county.
For urban areas where population density is 1000 inhabitants per
square mile or more, snowmobile usage decreases as a function of popu-
lation density. It appears that usage drops to zero when population den-
sity reaches about 3000 per square mile, so it will be assumed that usage
in urban areas follows the relationship
percent of state snowmobiles used in county =
C^ I 1.5-0. 0005 (county population density, inhabitant s/ mi ) x
(percent of state population in county),
25
-------
where C^ = 1 for densities from 1000 to 3000 per square mile and C^. =
0 for densities above 3000 per square mile.
The general equation used to estimate snowmobile emissions on
a county basis is
county emissions (kg/yr) =
(snowmobiles operating in county)
(total national emissions, kg/yr) (national snowmobile registrations).
C. MOTORCYCLES
The methodology for motorcycles is one of the least complicated
of those under consideration, because registration data for motorcycles
are available by county. Registrations only tell part of the story, how-
ever, since some motorcycles are always unregistered in each part of
the country. The general relationship to be used for motorcycle emis-
sions is
county emissions (kg/yr) = (county registrations) /
(1 - fraction units unregistered) x (emission factor, kg/unit yr).
J
The county registration data are available from individual state motor
vehicle departments, and the fraction of units unregistered is available
on both national and regional bases from a recent statistical survey' ''.
The emission factor for the population of motorcycles under consideration
is computed for each pollutant by
m \
factor, kg/unit yr = (0.001) £, Fi (emissions, g/mi x r 1 +
i=i I
C, (riding season, days) [tank volume, ji ) (—% - '- - °- - ]
A \ / \ / \/ tank volume dayy .,
where i = individual motorcycle type/ size (e.g., 2- stroke, 91-190
displacement)
F^ = fraction of motorcycle population under consideration which
is classified in category i
C± =1.0 for hydrocarbons, 0.0 for other pollutants.
The factors F^ and distances travelled annually are available from the
same statistical survey mentioned above' '' on both national and re-
gional bases. Length of the riding season in days is available as a na-
tional average from another survey(2°), and a method has been devised
to correct the riding season for specific locations by making use of
monthly normal temperatures for U.S. Cities' '. This correction
26
-------
simply involves counting the number of months during which monthly
normal temperature was 38°F or higher for the location of interest
and converting those months to days. Fuel tank volumes can be esti-
mated at 2.0 gallons (7.6j?) for bikes of 90 cc or less, 2.5 gallons (9.5^)
for those in the 91-190 cc range, 3.0 gallons (11.4,0 for those in the
191-290 cc range, and 3.5 gallons (15. 2 X) for those over 290 cc.
D. LAWN AND GARDEN EQUIPMENT
Emissions from individual small utility engines of the types
used in lawn and garden equipment have been studied thoroughly^ ' ',
and estimates of national emissions have been made using these emis-
sions results as basis' ' '. To allocate emissions from lawn and
garden equipment by county, however, consideration will be given to
areas where these machines are used and to seasonal factors. Lawn
and garden equipment is used predominantly around homes, so it seems
reasonable that equipment population should correlate well with number
of one-unit housing structures'^). This data item will be the basic cri-
terion by which emissions from lawn and garden engines are allocated to
counties.
An additional factor for lawn and garden equipment is the highly
seasonal nature of its use. Data on occurrence of freezing conditions' ''
can be used to predict the length of season for use of mowers, edgers,
and tillers. Usage of snowthrowers is predominantly limited to relatively
few states, where snowfalls of one inch or more are recorded 10 or 15
times per year (or more frequently). This usage can be evaluated by
assuming that no snowthrowers are in service where annual snowfall is
under 30 inches and that each snowthrower operates eight minutes for
each inch of snowfall. These assumptions are based on a "typical" snow-
fall of 2. 5 inches and a typical usage time of 20 minutes per snowfall.
The criterion of 30 inches annual snowfall leads to an (approximate) di-
viding line of 40°N latitude separating the region of snowthrower operation
from generally warmer climates. The distribution of snowthrowers will
be assumed to follow the distribution of population in those areas where
they are likely to be in service.
The general relationship for lawn and garden equipment emissions is
county emissions (kg/yr) = (nat'l emissions except snowthrowers, kg/yr) x
/average operating year\ /county mean freeze-free days\
\ 213 days /\ year /x
one-unit housing structures \ , / county population \
one-unit housing structures^ $\ heavy snow zone population/
/one hour operation \
(national snowthrower population) ^ 5 incheg snOwfallJ x
(county snowfall, in/yr) (emission factor, kg/hr);
27
/ county
V national
-------
where Co = 0 for counties having less than 30 inches annual snowfall,and
Co = 1 for counties having 30 inches annual snowfall or more.
The "heavy snow zone population" is the sum of populations of 19 states
plus half the populations of three additional states, totalling 83. 98 mil-
lion (1970 census). County snowfall can be assumed equal to that re-
corded at the nearest reporting station, either inside or outside the
county.
E. CONSTRUCTION EQUIPMENT
Nationwide emissions from construction equipment have been
estimated by several individual efforts' ' ' ', and there is reason-
ably good agreement on the totals. Allocation of these emissions will
be made first to the states, based on construction dollar volume' '.
Allocation to counties will then be made by population.
The construction volume data to be used are available at intervals
of six months in the open literature and probably at smaller intervals by
consulting directly with the source. The data are broken into three
major categories: heavy construction, highways and bridges, and building
construction (not including ho me building). The first two categories
make use of more engine-powered equipment per dollar of construction
performed than building construction does, so construction dollars in
the first two categories will be weighted by a factor of 3 as compared to
those spent in building construction. The relationship used to calculate
county emissions from construction equipment (based on the above con-
siderations) is
county emissions (kg/yr) =
. . . (state const, volume) (county population)
(national emissions, kg/yr) -. —r\ • : , *—*—*—: :—.
to ' (nat 1 const, volume) (state population)
Emissions due to homebuilding and other light construction are consi-
dered negligible compared to emissions from larger (contracted) cons-
truction jobs.
F. INDUSTRIAL EQUIPMENT
Based on rather minimal information, emissions from industrial
engines have been estimated on a national basis'^'. This category in-
cludes engine applications such as: fork-lifts, generators, pumps, and
other machinery used by manufacturing concerns; refrigeration units,
auxiliary engines, and material-handling machinery used in wholesale
trade; and machinery used in mining and quarrying. The method used
in this case will be to apportion emissions to counties directly from
national estimates by the relationship
28
-------
county emissions(kg/yr) =
, .. , . . i / \ county (A + B + C)
(national emissions kg/yr) — - - ' \ ' ;
national (A + B + C)
where A = value added by manufacturing establishments,
B = sales of wholesale trade establishments, and
C = value of shipments and receipts of mineral industries.
In some cases it will be necessary to estimate these quantities by ap-
portioning state data according to number of establishments of each type
in the county. Such estimation will be necessary to a greater extent for
item "C" than for the others, but it is (for most counties) a relatively
small contributor to the sum of A, B, and C.
G. FARM EQUIPMENT
Emissions from motorized farm equipment can be estimated quite
accurately due to availability of good data on machine populations' ' and
well- documented estimates of annual machine usage'1"* ' » ->°> ^^>. Popu-
lation data are available for farm tractors, garden tractors used on
farms, combines, motorized balers, and motorized forage harvesters.
Population estimates for large miscellaneous engines (mostly used in
irrigation), small utility engines, and small utility engines used speci-
fically on lawn and garden equipment can also be made.
The large (mpstly water-cooled) general purpose engines in ser-
vice nationwide number about 27 percent of the tractor population*
It will be assumed that these engines number 5 percent of the tractor
population in non-irrigated areas and 30 percent in irrigated areas.
General-purpose small utility engines (used on augers, sprayers, etc.)
will be assumed to number 1.5 per farm (class 1-5 farms only). These
assumptions are based on the ratio of engines in service in agriculture
nationwide to total number of farms and consideration of typical farm
requirements. Annual usage of all these items of equipment and appli-
cable emission factors have been developed sufficiently for use in this
methodology.
The basic relationship for calculating emissions from farm
equipment is
county emissions (kg/yr) = ^(equipment population) x
(annual usage) (emission factor, kg/hr),
where the summation is taken over the types of equipment used.
The number of class 1-5 farms in each county is also available from the
Census of Agriculture^ ', along with specific data on machinery populations,
29
-------
V. DEMONSTRATION OF COUNTY EMISSIONS
ESTIMATION METHODOLOGIES
The methodologies presented in Section IV are demonstrated
in this section for the 12 counties in the St. Louis Metropolitan Air
Quality Control Region (AQCR 070). While most aspects of the method-
ologies can be demonstrated well for these particular counties, special
situations restricting applicability or accuracy -will be identified. It
should be noted, however, that unforeseen circumstances are very
likely to occur if the methodologies are applied widely in the field,
creating a need for sound judgment and good knowledge of the area
under study.
A. OUTBOARD MOTORS
Referring back to Section IV. A. , certain data are needed for
each county to compute the emissions impact of outboard motors. These
data are summarized in Table 20 for the counties in AQCR 070. Before
the Missouri outboard registration data can be used, they must be mul-
tiplied by the appropriate correction factor from Table 1 (1.48) to ac-
.count for unregistered small craft. To convey an idea of the accuracy
of the registration data under discussion, the Missouri total (corrected
for unregistered units) is 227,450 motors as determined by the Depart-
ment of Revenue, while other sources show 196, 000 motors^2)
and 105, 013 outboard boats^3). It is likely that the last figure is low
due to non-inclusion of small boats (it would correct to 155, 419), but
there is still a considerable amount of disagreement. The figure con-
sidered most reasonable for outboard boats in Illinois is listed in Table
A-l of Appendix A, and for the end of 1973 this figure is 182, 120.
The value of C2 listed in Table 20 is seven (months), so annual
boat usage for AQCR 070 is estimated at 10C2 = 70 hours. The formula
for annual emissions becomes
emissions in kg/unit yr = 0.07 (emissions in g/unit hr).
31
-------
Table 20. COUNTY DATA TO BE USED IN DETERMINING OUTBOARD
MOTOR EMISSIONS IMPACT
State
Missouri
County
°n
Monroe
Randolph
c<- flair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Outboard
regist.
a
2, 536b
5,108b
4, 468b
23, 488b
12,121b
% state
popul.
0 1 ?6
0 255
2 26
0.170
0.282
7 57
0.124
1.18
2.25
1.99
20.3
13.3
Population
density,
inhab. / rra~
,
•24.7
49
53
4?4
24
59
158
169
1,907
10,201
Inland
water,
'
!*-..-}
9.1
12.2
7 7
0.6
8.3
3.4
35.0
17.6
3.8
C2
7
7
7
7
7
7
7
7
7
7
7
7
aNot available for Illinois.
Includes only boats with motors of 7. 5 hp or more.
CShown on county road map -0.0 mi^ in I960 tabulation' '.
"Shown on county road map - only 0. 1 mi^ in I960 tabulation' '.
Based on 1973 Illinois total boat registrations apportioned according to
population and corrected Missouri registrations by county, Table 21
shows county emissions and fuel consumption of outboard motors using
factors from Table 2. These values will be combined later with emis-
sions from the other categories of interest to determine totals for counties
and AQCR 070. In terms of season, the outboard emissions are expected
to occur during the months of April through October, inclusive.
B. SNOWMOBILES
As shown by data in Table A-3 of Appendix A, no snowmobiles
are registered in Missouri; and 34, 500 are registered in Illinois. Using
the method developed in Section IV. B. for apportioning the snowmobile
population to counties, the equation for Illinois counties becomes
snowmobiles in county = -809. + 538. (% of state popul. in county)
+ 11.1 (77.7)
= 53 + 538 (% of state popul. in county)
assuming that average snowfall at the state geographic center is 22.0
inches per year. All emissions from snowmobiles, of course, would
32
-------
Table 21. EMISSIONS AND FUEL CONSUMPTION OF OUTBOARD MOTORS
FOR COUNTIES IN AQCR 070
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Outboard
boats used
229
464
4, 116
310
514
4,680
226
3, 753
7, 560
6,613
34, 762
17,939
81,166
Emissions, 103 kg/yr
HC
12.3
25.0
222.
16.7
27. 7
252.
12. 2
12.2
407.
356.
1,870.
966.
4,370.
CO
36.5
74.1
657.
49.5
82.0
747.
36.1
36.1
1,210.
1,060.
5,550.
2, 860.
13, 000.
co2
56.3
114.
1,010.
76.2
126.
1,150.
55.5
55.5
1,860.
1,620.
8,540.
4,410.
19,900.
NOX
0.072
0. 146
1.30
0.098
0.162
1.47
0.071
0.071
2.38
2. 08
11.0
5.65
25.6
SOx
0.071
0.143
1.27
0.096
0.158
1.44
0.070
0.070
2.33
2.04
10.7
5.53
25.0
Fuel used,
103 gal/yr
24.5
49.7
441.
33.2
55.0
501.
24.2
402.
810.
708.
3,720.
1,920.
8,690.
(jo
-------
occur in the winter months (December through March, in this case).
Snowmobile populations, emissions, and fuel consumption are sum-
marized in Table 22 for the counties of AQCR 070 where they are
computed to occur. It is probable that the error of estimate in this
case makes these values higher than actual, due to the rather minimal
snowfall in the area for lengthy snowmobile operation.
C. MOTORCYCLES
Emissions from motorcycles are estimated using the method
in Section IV. C. and data from Section II. C. The breakdown according
to engine size and type is taken from Table 6, and the riding season is
computed to be nine months (March through November) or 275 days.
The computation of emission factors (in kg/unit year) and fuel consump-
tion is outlined in Table 23, with the results for AQCR 070 appearing
as "weighted composites" at the bottom of the table.
Table 23. COMPUTATION OF EMISSION FACTORS AND FUEL
CONSUMPTION FOR MOTORCYCLES IN AQCR 070
Motorcycle
size
4-s/0-90cc
4-s/91-190cc
4-s/191-290cc
4-s/over 290cc
2-s/0-90cc
2-s/91-190cc
2-s/191-290cc
2-s/over 290cc
i
1
2
3
4
5
6
7
8
Fi
0.109
0.127
0.058
0.231
0.098
0.115
0.053
0.208
Weighted composite
Emissions in kg/unit year
HC
2.7
5.0
8.8
16.
5.6
15.
40.
77.
26.
CO
15.
34.
67.
140.
4.5
17.
63.
150.
79.
NOX
0.16
0.28
0.36
0.33
0.082
0.14
0.08
0.12
0.20
Part.
0.016
0.042
0.094
0.21
0.10
0.27
0.74
1.65
0.50
RCHO
0.014
0.036
0.092
0. 24
0.075
0.15
0.27
0.42
0.19
S0x
0.010
0.024
0.046
0.093
0.016
0.035
0.090
0.17
0.074
Fuel
usage,
gal/yr
8.5
19.
38.
75.
9.4
20.
52.
100.
50.
Calculation of emissions by county requires registration data,
which are available' ' '»and an assumption of the percentage of un-
registered motorcycles in the total population (15 percent for AQCR
070)^ "'. Emissions and fuel consumption for counties are shown in
Table 24, as well as a total for AQCR 070. As already mentioned, these
emissions would occur during the March through November period; and
they appear to be concentrated in the more urban counties.
D. LAWN AND GARDEN EQUIPMENT
This category is divided into two classes, namely snowthrowers
and other equipment. According to criteria suggested in Section IV. D. ,
34
-------
Table 22. SNOWMOBILE EMISSIONS AND FUEL CONSUMPTION,
COUNTIES IN AQCR 070
State
Illinois
County
Bond
Clinton
Madison
Monroe
Randolph
St. Glair
Washington
Total AQCR 070
Snowmobiles
in use
121
190
1269
144
205
1436
120
3485
Emissions, 10 kg/yr
HC
4.57
7. 18
48.0
5.44
7.75
54.3
4.54
132.
CO
7.10
11.2
74.5
8.45
12.0
84.3
7.04
205.
NOX
0.073
0.114
0.761
0. 086
0.123
0.862
0.072
2.09
Part.
0.202
0.317
2.12
0. 240
0.342
2.40
0.200
1.9
RCHO
0.067
0.10
0. 70
0.079
0.11
0.79
- 0.066
5. 82
S0x
0.006
0.010
0.065
0.007
0.010
0.073
0.006
0.178
Fuel used,
103 gal/yr
6. 78
10.6
71.1
8.06
11.5
80.4
6. 72
195.
-------
Table 24. EMISSIONS AND FUEL CONSUMPTION OF MOTORCYCLES,
COUNTIES IN AQCR 070
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Motorcyclesa
in use
555
713
6,080
500
1,012
4,969
295
1,608
3,320
3,492
14,392
10,084
47, 020
Emissions, 10 kg/yr
HC
14.
19
160
13
26
130
8
42
86
91
370
260
1, 200
CO
44
56
480
40
80
390
23
130
260
280
1, 100
800
3, 700
NOX
0. 11
0. 14
1.2
0. 10
0.20
0.99
0.06
0.32
0.66
0.70
2.9
2.0
9.4
Part.
0.28
0. 36
3.0
0. 25
0. 51
2.5
0. 15
0. 80
1.7
1.7
7.2
5.0
24.
RCHO
0. 11
0. 14
1.2
0. 10
0. 19
0.94
0. 06
0.31
0. 63
0. 66
2.7
1.9
8.9
S0x
0. 04
0.05
0.45
0.04
0. 07
0.37
0.02
0. 12
0.25
0.26
1. 1
0.75
3.5
Fuel used,
103 gal/yr
28.
36.
300.
25.
51.
250.
15.
80.
170.
170.
720.
500.
2,400.
UJ
Assuming 15 percent of motorcycles unregistered' ''
-------
only an insignificant number of snowthrowers should be operating in the
St. Louis area; so they will be omitted from this analysis. National
.emissions and fuel consumption of equipment other than snowthrowers
are computed using data from Tables 10 and 12, assuming 2. 7 million
2-stroke engines and 50. 2 million 4-stroke engines. The other data
required for this computation are the mean freeze-free days per year
(205)'*^' and the numbers of one-unit housing structures in the indivi-
dual counties and the nation^ '. The number of one-unit housing struc-
tures in the nation is approximately 46. 8 million, and emissions appor-
tioned to counties using this variable are shown in Table 25 along with
fuel consumption and calculated county engine populations. Emissions
from lawn and garden equipment occurring in AQCR 070 are about 1
percent of the national total emissions from this engine category.
E. CONSTRUCTION EQUIPMENT
Emissions from construction equipment are given in Table 14
(along with fuel consumption) as national totals, and the construction
dollar volume data required for apportioning the national totals to states
can be obtained from Reference 29 (August 1974 issue in this case). Com-
putation of the percentage of national construction equipment emissions
allocated to the two states within which AQCR 070 falls (Illinois and Mis-
souri) is presented in Table 26. These percentages are equal to the
weighted averages of construction dollar percentages given in the last
column of Table 26.
Table 26. COMPUTATION OF ILLINOIS AND MISSOURI
CONSTRUCTION EQUIPMENT EMISSIONS AS PERCENTAGES
OF NATIONAL TOTALS
Area or
state
U.S.C
Illinois
Missouri
Heavy const.
10° dol.
11,140
395
214
%
100
3.55
1.92
Highway const.
10° dol.
4,385
297
148
%
100
6.77
3.38
Building const.
106 dol.
13,097
834
348 '
%
100
6.37
2.66
Avg.b
%
100
5.33
2.65
aExcluding ho me building.
Weighted using method in Section IV. E.
cExcluding Alaska and Hawaii.
The state percentages can be divided further to make county esti-
mates by apportioning according to population. Percentages of state
populations for each county in AQCR 070 were given in Table 20, and
they are used with percentages from Table 26 and national totals from
37
-------
Table 25. LAWN AND GARDEN ENGINE EMISSIONS AND
FUEL CONSUMPTION FOR COUNTIES IN AQCR 070
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
One-unit
housing
structures
4,490
7,788
65,533
5,383
8,624
68,769
4,848
15,882
27,593
21,631
235,303
81,784
547, 628
Computed engine
populations
4- stroke
4,820
8,350
70,300
5,770
9,250
73,800
5, 200
17,000
29,600
23,200
252, 000
87,700
587, 000
2- stroke
259
449
3,780
311
498
3,970
280
916
1,590
1, 250
13, 600
4, 720
31, 600
Fuel used
103 gal/yr
53.4
92.5
779.
63.9
102.
817.
57. 6
188.
328.
257.
2790.
971.
11,750.
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
Randolph
St. Charles
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Emissions, 10^ kg/yr
HC
12.6
21.8
183.
15. 1
24. 1
192.
13.6
44.4
77. 1
60.5
658.
229.
1,530.
CO
100.
174.
1,460.
120.
192.
1,530.
108.
354.
615.
482.
5,240.
1, 820.
12,200.
NOX
1.01
1.76
14. 8
1.22
1.95
15.5
1.09
3.59
6.23
4.88
53. 1
18.5
124.
Part.
0. 27
0.46
3.89
0.32
0.51
4.08
0.29
0.94
1. 64
1. 28
14. 0
4.85
32.5
RCHO
0.23
0.40
3.3
0.27
0.44
3.5
0.25
0.81
1.4
1.1
12.
4.2
28.
SOX
0. 11
0. 19
1.56
0. 13
0. 20
1. 63
0. 12
0.38
0. 66
0.51
5.59
1. 94
13.0
38
-------
Table 14 to compute county emissions as shown in Table 27. As ex-
pected, this category has a much larger fuel consumption and loading
of NO emissions than any of the others examined thus far.
2t
F. INDUSTRIAL EQUIPMENT
Fuel consumption and emissions of industrial engines are given
in Table 16 as national totals, and information required to apportion
emissions according to the method outlined in Section IV. F. is presented
in Reference 39. These latter data are summarized in Table 28 for the
counties in AQCR 070, indicating that a range from about 0.002 percent
to 0.8 percent of national industrial engine emissions occur within indi-
vidual counties. Using national emissions and fuel consumption data
from Table 16 in conjunction with percentage distributions from Table
28, industrial engine emissions by county for AQCR 070 have been
Table 28. COMPUTATION OF INDUSTRIAL EQUIPMENT
POPULATION PERCENTAGES FOR COUNTIES IN AQCR 070
Area or
state
U.S.
Illinois
Missouri
County
All
Bond
Clinton
Madison
Monroe
Randolph
St. Glair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Millions of dollars
A = value
added
261,983.8
13.2
17.1
645.2
0.9
30.3
267.3
2.3
56.0
66.4
44.8
1, 285.8
1,793.5
4, 222.8
B = whole-
sale sales
459,475.967
14.583
17.391
229.629
12.829
14.394
519.297
15.643
25.699
17.333
33.644
3, 065.356
4,518.156
8, 483.954
C = min-
erals
25,848.7
a
a
2.8
a
18.4
_a
2.8
a
3.0
a
9.8
0.-7
37.5
/County A +B+C\
\ U.S. A+B+C )
1.0
3.72xlO-5
4.62xlO"5
1.17xlO"3
1.84xlO-5
8. 44x1 0"5
l.OSxlQ-3
2.78xlO"5
3.44xlO~5
1.1 2x1 0~4
l.OSxlO-4
5.84xlO'3
8.45xlO"3
1. 71xlO"2
aNegligible
calculated and appear as Table 29. The population of industrial engines
is more heavily weighted toward gasoline-fueled units than the population
of construction equipment, so it produces more HC and CO and less NOX
than does construction equipment on a soecific basis.
39
-------
Table 27. CONSTRUCTION EQUIPMENT EMISSIONS AND FUEL CONSUMPTION
FOR COUNTIES IN AQCR 070
State County
Illinois
Missouri
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
% national
emissions
0.00672
0.0136
0.120
0.00906
0.0150
0.137
0.00661
0.0313
0.0596
0.0527
0.538
0.352
1.342
•2
Emissions, 10 kg/yr
HC
8.60
17.4
154. •
11.6
19.2
175.
8.46
40.1
76.3
67.5
689.
451.
1,720.
CO
88. 7
180.
1, 580.
120.
198.
1, 810.
87.3
413.
787.
696.
7,100.
4,650.
17, 700.
NOX
57.5
116.
1,030.
77.6
128.
1, 170.
56.6
268.
510.
451.
4,610.
3,010.
11, 500.
Part.
4.38
8.87
78.2
5.91
9. 78
89.3
4.31
20.4
38.9
34.4
351.
230.
875.
RCHO
1.2
2.4
22.
1.6
2.7
25.
1.2
5.6
11.
9.5
97.
63.
240.
sox
4.48
9.06
79.9
6.03
9.99
91.2
4.40
20.8
39.7
35. 1
358.
234.
894.
Fuel used,
103gal/yra
351.
710.
6, 260.
473.
783.
7, 150.
345.
1,630.
3, 110.
2, 750.
28, 100.
18, 400.
70,000.
88.5 percent of gallons are diesel fuel, 11.5 percent gasoline.
-------
Table 29. INDUSTRIAL ENGINE EMISSIONS AND FUEL CONSUMPTION
FOR COUNTIES IN AQCR 070
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Emissions, 10^ kg/yr
HC
4. 60
5.71
145.
2. 28
10.4
130.
3.44
4. 26
13.9
13.0
722.
1, 050.
2, 120.
CO
73.3
. 91.0
2,300.
36.2
166.
2, 070.
54. 7
67.7
221.
207.
11,500.
16, 600.
33, 700.
NOX
10. 3
12.8
323.
5. 1
23. 3
290.
7.7
9.5
30.9
30.0
1,610.
2,330.
4,720.
Part.
0.72
0.90
22. 7
0. 36
1. 64
20.4
0.54
0. 67
2. 17
2.04
113.
164.
332.
RCHO
0.2
0.3
6.7
0. 1
0.5
6..0
0.2
0.2
0.6
0. 6
33.
48.
96.
s°x
0.66
0.82
20.8
0.33
1. 50
18. 6
0.49
0. 61
1.99
1.86
104.
150.
304.
Fuel used,
103 gal/yra
79.6
98.9
2, 504.
39.4
181.
2, 250.
59.5
73.7
240.
225.
12, 500.
18, 100.
36, 600.
149.8 percent of gallons are diesel fuel, 50.2 percent gasoline.
-------
G. FARM EQUIPMENT
To compute emissions and fuel consumption of farm equipment
by county, data from Reference 40 on equipment populations are used
with information from Tables 17 and 18 on annual equipment usage and
emission rates. To simplify the calculations, composite emission and
fuel consumption factors can be used for all tractors (both gasoline and
diesel). These factors (in kg/hr) are 0. 153 HC, 1. 71 CO, 0. 259 NOX,
0.030 Particulate, 0.011 RCHO, 0.020 SOX, and 6.77 fuel. In addition,
the composite annual tractor usage is 352 hours and fuel used in tractors
is 53.1 percent diesel fuel by volume. A similar analysis for combines
yields factors (in kg/hr) of 0.281 HC, 6.00 CO, 0.372NOX, 0.049 Parti-
culate, 0.014 RCHO, 0.031 SOX, and 14.1 fuel. Composite annual
combine usage is 70 hours, and fuel used in combines is 34. 2 percent
diesel fuel by volume. Looking at the other farm application made up
of both diesel and gasoline engines, fuel used in miscellaneous heavy-
duty engines is 35.4 percent diesel fuel by volume.
Equipment populations for the counties in AQCR 070 (1969) are
listed in Table 30 along with totals for the region. These data can be
Table 30. FARM EQUIPMENT POPULATIONS FOR COUNTIES
IN AQCR 070<4°)
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
Randolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Population by type of equipment (1969)
Trac-
tors
1,967
2,946
4,513
2, 244
2,948
3, 746
2,980
3, 128
1,312
2,700
1,179
29,663
Com-
bines
379
527
782
454
484
785
674
190
91
472
154
4,992
Bal-
ers
291
586
751
256
537
478
509
726
382
358
125
4,999
For-
age
harv.
104
303
157
72
151
141
185
149
49
93
16
1,420
Misc.
heavy
duty
98
147
226
112
147
187
149
156
66
135
59
1,482
Misc.
light
duty
1,140
1,602
2,234
1,068
1,480
1,878
1,580
1,400
514
1, 242
554
12,692
used with emission and fuel consumption factors given above in the text
and in Tab?e 18 to calculate total emissions by county. To avoid
42
-------
Table 31. FARM EQUIPMENT EMISSIONS AND FUEL CONSUMPTION
FOR COUNTIES IN AQCR 070
State
Illinois
Missouri
County
Bond
Clinton
Madison
Monroe
R andolph
St. Clair
Washington
Franklin
Jefferson
St. Charles
St. Louis
St. Louis City
Total AQCR 070
Emissions, 103 kg/yr
HC
118.
179.
268.
134.
175.
225.
181.
180.
75.8
160.
68.3
1,760.
CO
1,410.
2, 110.
3, 190.
1, 600.
2, 080.
2, 690.
2, 180.
2, 080.
885.
1,900.
803.
20,900.
NOX
199.
309.
448.
224.
296.
376.
306.
305.
127.
268.
114.
2,970.
Part.
23.7
37. 3
53.0
26.5
35.2
44. 6
36.6
36. 1
15.0
31. 7
13.3
353.
RCHO
8.4
13.
19.
9.5
12.
16. .
13.
13.
5.4
11.
4.8
120.
sox
15. 6
24.5
35. 0
17. 5
23.2
29.4
24. 1
23. 8
9.9
20.9
8.8
233.
Fuel useda
103 gal/yr
1,770.
2,730.
3,980.
1,990.
2, 620.
3,350.
2, 730.
2,690.
1, 130.
2,380.
1,010.
26,400.
L52. 5 percent of gallons are diesel fuel, 47. 5 percent gasoline.
-------
unnecessary complication, the results of this calculation are given in
Table 31 as totals for all the farm equipment in each county rather
than as totals for each type of equipment. In the computations for farm
equipment emissions and fuel consumption, it is necessary to assume
that the diesel and gasoline population fractions are the same as for the
national population. Although this assumption may be somewhat in error
for specific counties, no data are available at the county level which
would permit a more refined analysis.
Having calculated emissions and fuel consumption for the seven
categories of internal combustion engines under study, it is now possible
to construct a summary which can be compared to the NEDS (National
Emissions Data System) survey data for AQCR 070. This summary is
presented in Table 32 with the NEDS data for off-highway gasoline- and
diesel-powered vehicles and a total for the AQCR.
Table 32. SUMMARY OF EMISSIONS FROM ENGINE
CATEGORIES UNDER STUDY
Category
Outboard motors
Snowmobiles
Motor cycle sa
Lawn and garden
Construction
Industrial
Farm
. Total
NEDS gasoline^
NEDS dieselb
NEDS totalb
HC
4 370
132.
1,200.
1,530.
1,720.
2,120.
1,760.
12, 800.
4, 050
337
4. 390.
CO
13 000
205.
3,700.
12,200.
17, 700.
33,700.
20,900.
101,000.
22 200
2 050
24. 200
Emissions
NOX
25 6
2.1
9.4
124.
11,500.
4,720.
2,970.
19,400.
1 290
3 370
4. 6AO
, 103 kg/
Part.
5.8
24.
32.5
875.
332.
353.
1,620.
59
1 1 8
1 77
yr
RCHO
1.9
8.9
28.
240.
96.
120.
490.
SOX
0.2
3.5
13.0
849.
304.
233.
1,430.
246*
78?
a25 percent of this total estimated off-highway.
Off-highway I.C. engine area sources.
44
-------
VI. METHODOLOGY FOR GRID ELEMENT EMISSIONS ESTIMATES
The intrinsic properties of grid elements which can be helpful
in making emissions estimates for them include:
1. area (1, 4, 25, or 100 km^) - some portion of area may not
be in county for a given element
2. highway mileage by type of highway in rural areas (street
details not given on maps)
3. presence and amount of surface water suitable for boating
4. area in open land suitable for farming
5. area in towns, cities, and incorporated places
6. number of dwellings (some counties) in rural areas
To indicate typical detail given on a county highway map (scale is 1/2
inch = 1 mile or 1:126, 720), a section of the map for St. Louis County,
Missouri is included as Figure 1. Several of the grid elements have
been laid out on this map section to document their appearance, the
larger ones being 5 km square and the smaller ones 2 km square. The
computer program (a copy of which is in Appendix D) prints geographical
coordinates to the nearest 0. 01 second of angle, which represents the
nearest 8 x lO"-' inch for longitude and the nearest 1 x 10 inch for
latitude on the maps. It is obvious that the grids cannot be plotted with
this kind of accuracy, and a reasonable estimate of accuracy is ±0.02
inches on the map or an actual error of ±65 m on the ground.
The distributions of several engine categories under investi-
gation in this methodology development program are probably related
more strongly to population than to any other single variable. Popu-
lation data by grid element, however, are not available from any known
source. It seems desirable to have a system for allocating population
to grid elements; so this problem will be analyzed here before addressing
specific methodologies for engine categories. Neglecting population den-
sity variations within incorporated places (incorporated places are out-
lined on county highway maps), grid element population can be estimated
by
45
-------
TAR.TIAL OMER.LAY OF
ON
MAP OF VT,
Figure 1. Sample layout of grid elements on a county highway map
46
-------
/privately-owned grid land area\
grid element population ^ area Q£ incorporated place ) x
(population of incorporated place).
Grid element area is given by definition, and both the other variables
can be obtained from Appendix B, Table B-2 of the County and City
Data Book' ' for places having a population of 2500 or more. Places
having fewer than 2500 people are outlined on county highway maps, and
their populations are given; so both variables can still be obtained (area
to be measured by geometric sections or polar planimeter). For a
serious effort directed at grid element estimates, larger-scale maps
than the ones obtained for reference during this project should be avail-
able and are highly recommended for use.
Population estimates for grid elements not in incorporated areas
are not as simple as those for incorporated areas. In this case, the
best which can be done is to allocate (by area) the county's rural popu-
lation to land remaining after all incorporated areas have been sub-
tracted. This process takes the form
/privately-owned grid land area\
grid element population ={ : ——3 )x
6 c c \ county unincorporated area /
(county farm population + county rural nonfarm population),
where "county unincorporated area" can be determined by subtracting
areas of incorporated places from total county area. An easier but
somewhat less rigorous estimate could be made by assuming that
"county unincorporated area" is equal to county area in farms'-'"',
with small probable errors in most parts of the country.
Although not mentioned specifically thus far, grid elements which
contain parts of two incorporated places, and/or two counties, and/or
both incorporated and unincorporated places will have to be treated in
separate parts. After the parts have been analyzed, the grid total popu-
lation estimate can be summed.
A. OUTBOARDS
The major variable by which boating can be allocated to grids
is availability of surface water of a suitable nature. The relationship
proposed for outboard emission estimates is
grid element emissions (kg/yr) = (county emissions, kg/yr) x
grid surface water area \
^county surface water area/ '
47
-------
The equation should be satisfactory where all county surface water is
suitable for boating, but the accepted total county figure' ' should
probably be revised if some water geometrically OK for boating is
heavily polluted, moving very swiftly, or otherwise unfit for use by
small boats. The degree of care exercised on this point depends on the
desired accuracy of the estimate and the amount of detailed data avail-
able for the area under stud". Surface water areas for grid elements
can be determined by measurement (e.g. , by polar planimeter) using
maps of the largest practically available scale. On a map such as the
segment shown in Figure 1, minimum-size features used as input to
tabular data'^' are represented by ponds 0.14 inch in diameter and
rivers 0. 062 inch wide. This reporting guideline does not necessarily
reflect a typical minimum water area for outboard operation, but it
would be an involved matter to form a new criterion since re-measure-
ment of all the county's inland water area would be involved. In all
cases, county surface water area from Reference 41 should be checked
(at least roughly) against the county map, because many reservoirs have
been built since I960.
B. SNOWMOBILES
Emissions from snowmobiles will be allocated on an area basis,
since urban and non-urban ownership and usage patterns have already
been accounted for in the county methodology. The relationship which
follows is
/grid element land area\
grid element emissions (kg/yr) =^ county land area /x
(county emissions, kg/yr).
This estimate could be modified by adding lakes which might be frozen
during the snowmobile season to the area terms, but such a modification
could hardly be justified by the accuracy of the overall estimate in most
cases. In the same way, uniform subtractions of areas in which snow-
mobiles do not run can probably not be justified.
C. MOTORCYCLES
Although some other variables may be significant, motorcycles
in service and their usage are probably related strongly to distribution
of population within the county. It is proposed, therefore, that the grid
element estimates for motorcycles be determined by the relationship
grid element emissions (kg/yr) = (county emissions, kg/yr) x
fgrid population estimateN .
county population /'
48
-------
where the grid population estimate is made as described above.
D. LAWN AND GARDEN EQUIPMENT
Following the same general method used in allocating emissions
from lawn and garden equipment to counties, it will still be attempted
to apportion these emissions to grids according to location of one-unit
housing structures. Using the technique developed earlier for estimating
grid element population, the relationships which result are
(grid one-unit structures \
county one-unit structures,/x
(county emissions, kg/yr)
and
'area one-unit structures\
/.
grid one-unit structures = (grid population) f -
area population /
The last term in the second equation is available for cities of 25, 000 or
more in tabular form* '. In all other privately-owned areas, the value
of that term will be assumed as 0. Z30, which is the national average^ ''.
E. CONSTRUCTION AND INDUSTRIAL EQUIPMENT
It is doubtful that any of the intrinsic properties of grid elements
correlate directly with construction equipment usage. While major con-
struction projects such as highways, sewer systems, and large buildings
are built to serve people's needs, they are often built on the periphery of
the densely-populated areas. Industrial areas are also often located
near, but not in, the most heavily-populated areas. These industrial
areas can be pinpointed, however, by examining zoning maps for the
area of interest if extreme accuracy is desired.
Having noted the shortcomings of the method, it is still necessary
(due to lack of other data) to allocate construction and industrial engine
emissions by population. The method derived earlier for grid population
estimates can be used in the relationship
. , , . , /estimated grid element population\
grid element emissions (kg/yr) =1 a ^Hr: )x
0 & ' \ county population /
(county emissions, kg/yr).
A more refined technique, using zoning laws, can be applied to industrial
engine emissions in areas of industrial zoning. This technique results
in the equation
49
-------
grid element area in industrial/
. , , . ,, / . i commercial zones \
grid element emissions (kg/yr) = —— — x
l county area zoned industrial/ '
commercial
(county emissions, kg/yr),
and this second technique is considered highly preferable to the popu-
lation-based method where the necessary information is available.
F. FARM EQUIPMENT
It will be assumed that, emissions from farm equipment correlate
well with area (acreage) in farms, leading to the relation
'privately-owned unincorpo->
grid element emissions (kg/yr) = [ rated grid area | x
county area in farms
(county emissions, kg/yr).
Depending on the desired level of accuracy, the term in the denominator
could be checked against the county sum of privately-owned unincorpo-
rated area, which it is assumed to equal. If the two are not equal, then
"county area in farms" could be replaced by "county privately-owned
unincorporated area" to make the sum of the grid/county ratios equal
1.0.
50
-------
VII. SUMMARY
All the phases of this study have been completed, but it should
not be assumed that the results are a completely authoritative and cor-
rect analysis of emissions and fuel consumption on a county basis.
Throughout the narrative, it has been stressed that achieving the
project's objectives has often required usage of data which are really
insufficient for the task. The results must be used only with full
knowledge of their limitations, most of which were known even before
the study began.
Most of the basic emissions data on which county methodologies
(and hence grid methodologies) were derived are probably quite accurate;
but even from the points at which modal data were combined to yield
composite data or individual vehicle/engine data were combined to
produce category data, errors have certainly occurred. In all cases,
however, so many variables are missing that the errors cannot be
estimated statistically. Proper use of the study's results, then,
requires the knowledge that they are limited to estimates of an accuracy
commensurate with' the time and effort which went into the project. In
other words, the estimates are reasonably good but in no way rigorous.
A number of good sources of emissions, population, and usage
data were found; and these sources are essentially the composition of
the List of References. A few References (e. g., 7-10, 39, 41, and
perhaps others) are primarily sources of county data relatable to
vehicle or engine population or usage, and a more complete list of
these documents is found in Table 19. Secondary sources of
county/small area data are listed in Appendix B, but they were not
used much in preparation of this report.
The county and grid element methodologies themselves have
been structured as much as possible to permit "plugging in" values
with little or no prior computation involved. In some cases, values
will have to be processed before use, such as those for percentages
of state population in a given county. It is simply not practical here to
convert all data to be used in the methodologies to compatible terms,
especially since the methodologies may not be used for all areas at
any foreseeable time.
51
-------
Due to the length of equations and explanations used in the
methodologies, it is not considered practical to reiterate them all in
this section. It is in order, however, to give an assessment of the
estimated relative accuracy of the methodologies. A rank-ordering
from most accurate to least accurate is as follows:
1.
2.
3.
4.
5.
farm equipment
motorcycles
construction equipment
lawn and garden,and outboards (tie)
industrial equipment and
snowmobiles (tie)
This assessment is based first on availability of county population data,
then on accuracy of emissions data, and finally on availability of usage
information.
As shown in Table 32, total emissions from sources under study
in this project exceed by considerable margins those estimated for
off-highway internal combustion engine sources by the NEDS system.
The basis for the NEDS estimates is not known at this time. To further
compare emissions estimated by the methodologies developed herein to
NEDS figures, Table 33 is presented to illustrate the impact of off-
highway source emissions on totals for AQCR 070. This comparison
shows estimated emissions of HC, CO, and NOX from uncontrolled
engines to be small but significant contributors to air pollution around
St. Louis. It likewise shows that these engines do not contribute
significantly to total particulate or SOX emissions in that area.
Table 33. IMPACT OF OFF-HIGHWAY SOURCES
ON EMISSIONS IN AQCR 070
Source categories
NEDS area sources
NEDS point sources
NEDS all sources
NEDS gasoline
off-highway
NEDS dies el off -highway
NEDS all off- highway
Off-highway (this report)
- as % NEDS total
Emissions, 10^ kg/yr
HC
196,541
71, 194
295, 123
4,050
337
4,390
12,800
4.34
CO
922, 148
2,573, 063
3,495, 211
22, 200
2,050
24, 200
101, 000
2.89
NOX
111, 181
282, 132
393,314
1,290
3,370
4, 660
19,400
4.93
Part.
34, 043
287,709
321, 752
59
118
177
1, 620
0.504
SOX
42, 730
1,077, 113
1, 119, 843
36
246
282
1,430
0. 128
52
-------
REFERENCES
1. State Boat Registration. MAREX Marketing Committee .
2. The Boating Business - 1973. The Boating Industry.
3. Hare, C. T. and K. J. Springer. Exhaust Emissions From
Uncontrolled Vehicles and Related Equipment Using Internal
Combustion Engines - Part 2, Outboard Motors. Environ-
mental Protection Agency. Contract EHS 70-108. January
1973.
4. Hare, C. T. and K. J.% Springer. Exhaust Emissions from
2-Stroke Outboard Motors and Their Impact. Society of
Automotive Engineers. Paper No. 740737. September 1974.
5. Analysis of Pollution from Marine Engines and Effects on the
Environment. Environmental Protection Agency and Boating
Industries Association. Joint study number 30843.
6. Joint study funded by Environmental Protection Agency and
Departmentof Transportation on emissions from outboard
motors.
7. New York State Statistical Yearbook - 1973. New York State
Division of the Budget/Office of Statistical Coordination.
8. Statistical Abstract of Ohio - 1969. Economic Research
Division Development Department.
9. South Carolina Statistical Abstract - 1973. South Carolina
Budget and Control Board, South Carolina Division of Research
and Statistical Services. July 1973.
10. Wisconsin Statistical Abstract - Third Edition. Departmentof
Administration, State Bureau of Planning and Budget, Infor-
mation Systems Unit. June 1974.
11. Data on snowmobile registrations as of March 1, 1974 submitted
to C. T. Hare of SwRI by letter from John F. Nesbitt. May 22,
1974.
12. Hare, C. T. and K. J. Springer. Exhaust Emissions from
Uncontrolled Vehicles and Related Equipment Using Internal
Combustion Engines - Part 7, Snowmobiles. Environmental
Protection Agency. Contract EHS 70-108. April 1974.
53
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13. Hare, C. T. , K. J. Springer, and T. A. Hula. Snowmobile
Engine Emissions and Their Impact. Society of Automotive
Engineers. Paper No. 740735. September 1974.
14. Donahue, J. A., et al. Small Engine Exhaust Emissions and
Air Quality in the United States. Society of Automotive Engineers.
Paper No. 720198. January 1972.
15. Kollman, R. E. , S. S. Lestz, and W. E. Meyer. Exhaust
Emission Characteristics of a Small 2-Stroke Cycle Spark
Ignition Engine. Society of Automotive Engineers. Paper No.
730159. January 1973.
16. Eccleston, B. H. and R. W. Hum. Exhaust Emissions From
Small, Utility, Internal Combustion Engines. Society of
Automotive Engineers. Paper No. 720197. January 1972.
17. Statistical Abstract of the United States - 1973. U. S. Depart-
ment of Commerce.
18. Automotive Industries 1974 Statistical Issue. April 1, 1974.
19. March 1974 Motorcycle Usage and Owner Profile Study.
Hendrix, Tucker & Walker, Inc.
20. Motorcycle Usage Study. Hendrix, Tucker & Walker, Inc.
Prepared for Motorcycle Industry Council. August 1973.
21. Goldish, J. C. , et al. Development of a Methodology to
Allocate Liquid Fossil Fuel Consumption by Country.
Environmental Protection Agency. Publication No. EPA-
450/3-74-021. March 1974.
22. Highway Statistics 1972. U. S. Department of Transportation,
Bureau of Public Roads. Tables VM-1 and VM-2.
23. Raney, J. L. and G. D. Kittredge. Measurement and Control
of Air Pollution from Aircraft and Other Off-Highway Propulsion
Systems. Prepared for International Clean Air Congress.
24. Motorcycle Mileage Data agreed upon by manufacturer members
of MIC Statistical Committee, July 1973. Submitted to C. T.
Hare of SwRI by Leo Lake of Yamaha Intl. Corp.
54
-------
25. Hare, C. T. and K. J. Springer. Exhaust Emissions From
Uncontrolled Vehicles and Related Equipment Using Internal
Combustion Engines - Part 3, Motorcycles. Environmental
Protection Agency. Contract EHS 70-108. March 1973.
26. Hare, C. T. and K. J. Springer. Motorcycle Emissions, Their
Impact, and Possible Control Techniques. Society of Automotive
Engineers. Paper No. 740627. August 1974.
27. Uncontrolled Vehicle Emission Study. State of California Air
Resources Board. October 30, 1973.
28. Wimette, H. J. and R. T. Van Derveer. Report on the Deter-
mination of Mass Emissions from Two-Cycle Engine Operated
Vehicles. Environmental Protection Agency. Contract CPA-
22-60-91. January 1970.
29. Draft Emission Regulations for New Motorcycles. Environmental
Protection Agency, Emission Control Technology Division
January 17, 1974.
30. Press releases from Outdoor Power Equipment Institutes, Inc.,
11/28/72, 12/1/71, 12/22/70, 1/12/70, 12/6/68. 734 15th
Street Northwest, Washington, D. C. 20005.
31. Implement & Tractor magazine, issues of 1/7/73, 4/7/72,
1,21/71, 5/21/70, 8/21/69, and others.
32. Hare, C. T. and K. J. Springer. Exhaust Emissions From
Uncontrolled Vehicles and Related Equipment Using Internal
Combustion Engines - Part 4, Small Air-Cooled Spark Ignition
Utility Engines. Environmental Protection Agency. Contract
EHS 70-108. May 1973.
33. Hare, C. T. and K. J. Springer. Small Engine Emissions and
Their Impact. Society of Automotive Engineers. Paper No.
730859. September 1973.
34. Hare, C. T. and K. J. Springer. Exhaust Emissions From
Uncontrolled Vehicles and Related Equipment Using Internal
Combustion Engines - Part 5, Farm, Construction, and
Industrial Engines. Environmental Protection Agency.
Contract EHS 70-108. October 1973.
35. Henderson, R. D. Air Pollution and Construction Equipment.
Society of Automotive Engineers. Paper No. 700551. 1970.
55
-------
36. Henderson, R. D. Digging Into Air Pollution Problems—An
Earthmover's Viewpoint. Society of Automotive Engineers.
Paper No. 720609 1972.
37. Hardwick, G. C. and C. R. Hudson. Farm and Industrial
Tractors - Emission Trends and Their Impact. Society of
Automotive Engineers. Paper No. 730829. September 1973.
38. Van Loan, M. and L. Resnick. Impact of Emissions from Farm
Equipment and Off-Road Heavy Duty Equipment on Air Pollution
in California. Society of Automotive Engineers. Paper No.
730830. September 1973.
39. County and City Data Book, A Statistical Abstract Supplement.
U. S. Department of Commerce. 1972.
40. 1969 Census of Agriculture, Volume I - Area Reports. U. S.
Department of Commerce, Bureau of the Census.
41. Area Measurement Reports. U. S. Department of Commerce/
Bureau of the Census. Publication GE-20, No. 1. May 1970.
42. Motor Vehicle Units Registered for the Year 1973. State of
Illinois. Accounting Revenue Division.
43. 1973 County Audit Report. Missouri Department of Revenue.
44. Climatological Data,National Summary. Department of Commerce.
Volume 15, No. 1. 1964.
45. Data on Contracting Bid Volume from several issues of
Construction Machinery and Equipment (periodical).
46. Current Industrial Reports, Internal Combustion Engines 1971
(and Prior Years to 1964), Series MA-35L(71)-1. U. S.
Department of Commerce, Bureau of the Census.
56
-------
APPENDIX A
TABULAR DATA ON POPULATION, USAGE, AND EMISSIONS
OF SELECTED MOBILE SOURCE CATEGORIES
-------
Table A-l. 1973 BOAT REGISTRATIONS AS COMPILED
BY THE U. S. COAST GUARD*1)
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Dist. of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Outboard boats
131,933
11,642
41,706
67, 201
264,085
29,027
54, 159
17,027
2,349
219,433
53,414 .
8, 185
36,541
182, 120
- 91,264
100,009
61, 100
82,586
102,868
29,441
57,579
103, 823
512,302
306, 165
37,545
105,013
13,299
State
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Guam
Puerto Rico
Virgin Islands
Total including 48 states and D. C.
Outboard boats
31,266
14, 170
6,844
93,746
22, 141
295, 171
87, 716
12,085
127,509
125,686
85,337
119,872
10,483
119,206
18,049
161, 136
385, 196
19,264
21,369
96,407
78, 110
11,971
331,980
7,362
437
7,200
2,802
4,984,065
A-2
-------
Table A-2.
OUTBOARD MOTORS, DECEMBER 31, 1973
ESTIMATED STATE DISTRIBUTION OF
(2)
State
Alabama
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Dist. of Columbia
Florida
Georgia
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Motors
150,000
44,000
121,000
385,000
38,000
92,000
23,000
26,000
527,000
152,000
43,000
312,000
201,000
103,000
71,000
99, 000
292,000
86,000
131,000
177,000
482,000
380, 000
68,000
196,000
20,000
State
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Penn sylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Total
Motors
38,000
16,000
43, 000
185, 000
19,000
534, 000
134, 000
24,000
293,000
114,000
114, 000
195,000
28,000
129,000
20,000
167,000
470,000
35,000
23,000
120, 000
185, 000
27, 000
370,000
8, 000
7, 510, 000
A-3
-------
Table A-3. U. S. SNOWMOBILE REGISTRATIONS
AS OF MARCH 1, 1974(n)
State
Alaska
Arizona
California
Colorado
Connecticut
Idaho
Illinois
Iowa
Maine
Massachusetts
Michigan
Minnesota
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Dakota
Ohio
Oregon
Pennsylvania
Rhode Island
South Dakota
Utah
Vermont
Washington
Wisconsin
Wyoming
Total U. S.
Snowmobiles
20, 100
1,000
15,000
23,000
15,300
32,000
34,500
26,000
75,260
71,900
400,000
290,400
30,000
400
3,000
49, 000
12,000
2, 100
172,776
37,751
12,500
10,600
60,000
1,050
25,077
13,500
13,013
10,500
233,569
12,000
1,714,796
A-4
-------
Table A-4. 1973 MOTORCYCLE REGISTRATIONS BY STATERS)
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Dist. of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Motorcycles
65,560
15, 143
62,768
34,036
631,961
81,871
51,440
6,050
4,045
142,478
90,454
12,000
45, 936
177,487
99,000
118,545
99,399
49, 112
40,000
20,713
44,000
67,000
269, 185
119,277
130,000
95,263
State
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Total
Motorcycles
37, 133
45,000
15,434
20, 544
69,208
30,799
91,575
95,435
18,738
179,359
94, 156
100, 203
231,475
15, 190
33,232
19,785
74,000
257,400
51,375
8,981
69,000
91, 184
48, 703
77,080
14,893
4,362,605
A-5
-------
Table A-5. MOTORCYCLE BREAKDOWNS BY SIZE
FOR REGIONS OF THE UNITED STATES(19)
"Region" of the U.S.
New England
Middle Atlantic
East North Central
West North Central'
South Atlantic
Motorcycle size distribution
Displacement, cc
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
% of population
9
20
9
59
3
20
22
12
46
0
23
22
11
42
2
18
26
11
45
0
22
25
10
40
3
States included
in "region"
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
New Jersey
New York
P enn s yl vani a
Illinois
Indiana
Michigan
Ohio
Wisconsin
Iowa
Kansas
Minnesota
Missouri
Nebraska
North Dakota
South Dakota
Delaware
Dist. of
Columbia
Florida
Georgia
Maryland
North Carolina
South Carolina
Virginia
West Virginia
table continued next page
A-6
-------
Table A-5 (continued). MOTORCYCLE BREAKDOWNS BY SIZE
FOR REGIONS OF THE UNITED STATESf1?)
"Region" of the U.S.
East South Central
West South Central
Mountain
Pacific
Motorcycle size distribution
Displacement, cc
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
90 and less
91-190
191-290
291 and over
Unclassified
% of population
24
27
3
40
6
21
33
7
36
3
28
32
10
22
8
20
27
16
35
2
States included
in "region"
Alabama
Kentucky
Mississippi
Tennessee
Arkansas
Louisiana
Oklahoma
Texas
Arizona
Colorado
Idaho
Montana
Nevada
New Mexico
Utah
Wyoming
Alaska
California
Hawaii
Oregon
Washington
A-7
-------
Table A-6. SALES, PRODUCTION, AND POPULATION ESTIMATES
FOR LAWN AND GARDEN EQUIPMENT
Previous Population Estimate for Small Utility Engines (1968-A11)(14)
Engine type
Lawn and garden 4- stroke
Lawn and garden 2- stroke
Miscellaneous 4- stroke
Average rated hp
3.43
3.43
3.86
Total
Engines in service
36, 200, 000
2, 500,000
5, 550,000
44, 250,000
Outdoor Equipment Sales and Population Estimates(30)
Type of equipment
Walking mowers
Lawn tractors and
riding mowers
parden tractors
Total lawn and garden
Estimated total in use
Motor tillers
Snow throwers
Sales or population for sales year, millions
ai973
5.45
0.74
0.26
6.45
—
0.43
0.33
1972
5.2
0.68
0. 25
6. 13
43.
0.43
0.32
1971
4.7
0.88
b
5.58
38.
0.36
0.26
LJ970
4.7
0.95
b
5. 65
37.
0.36
0. 24
1969
4.7
1.0
b
5.7
36.
0.38
0.26
1968
4. 56
0.93
b
5.49
—
0.38
0.26
1967
4.9
0.25
b
5. 15
--
0.35
0. 18
aPrediction
Included with lawn tractors and riding mowers.
Breakdown of 1966-1970 Small Engine Production by Application^ 1)
Application
Riding mower
Walking mower
Garden tractor
Motor tiller
Snow thrower
Other lawn and garden
Total lawn and garden
Recreation
Industrial
Agriculture
Miscellaneous
Total
Production (millions)
2.84
23.67
1.19
1.70
1. 18
1.31
31.89
1. 10
2.65
0.97
3.27
39.88
% of total
7. 1
59.4
3.0
4.3
3.0
3.3
80.0
2.8
6.6
2.4
8.2
100.0
A-8
-------
Table A-7. EMISSION FACTORS AND FUEL CONSUMPTION FOR
CONSTRUCTION EQUIPMENT BY CATEGORY AND REFERENCE
Equipment
category
Tracklaying
tractors
Tracklaying
loaders
Motor
graders
Scrapers
Off- highway
Wheel
loaders
Wheel
tractors
Rollers
Diesel or
gasoline
Diesel
Diesel
Diesel
Gasoline
Both
Diesel
Diesel
Diesel
Gasoline
Both
Diesel
Gasoline
Both
Diesel
Gasoline
Both
Ref.
38*
34
SB3"
34
38a
34
38a
34
34
38a
34
38a
34
38a
34
38a
34
34
38a
34
38a
34
34
38a
34
38a
34
34
Brake specific emissions, g/hp hr
HC
0.69
0.685
0.36
0.362
1.68
0.532
7. 18b
8.62°
0.936
1. 22
1.22
0.85
0.853
1.70
0.948
6.86b
7.35C
1.97
1.70
1.39,
6. 86b
7.41C
1.99
1.68
0 -777
7. 18b
12. Oc
6.71
CO
2.39
2.39
1.80
1.80
4.08
2. 15
218.
187.
11.4
2.84
2. 84
2. 62
2.62
3.34
2.63
143.
163.
28.3
3.34
4.40
143.
142.
18. 1
4.08
3.64
218.
202.
193.
NOX
9.08
9.08
6.56
6.56
9.03
10.6
5. 24
4.92
10.3
12. 1
12.1
14.9
14.9
9.39
11.2
6.62
5.41
10.3
9.39
9.34
6.62
6.37
9.05
9.03
15.8
5.24
5.47
8. 57
Part.
0.69
0.692
0.66
0.655
1.51
0.613
0. 37
0.320
0.598
0.79
0.789
0. 50
0.502
1.28
0.810
0.37
0.312
0.730
1. 28
1.27
0.35
0.360
1. 18
1.51
0. 777
0.37
0.394
0.506
RCHO
«
0. 17
_
0. 10
^
0. 12
-
0.30
0. 13
w
0.28
_
0.22
_
0.20
_
0.22
0.20
.
0.28
M
0.26
0.28
—
0.20
—
0.25
0. 24
S0x
0.85
0.851
0.85
0.853
0.92
0.874
0.22
0.26
0.844
0.90
0.901
0.89
0.887
0.87
0.857
0. 23
0.244
0.759
0.87
0.851
0.23
0. 230
0.789
0.92
1.00
0.23
0.279
0.495
BSFC
g/hp hr
—
193.
_
194.
—
199.
_
295.
-
—
205.
_
201.
_
195.
276.
-
.
193.
269.
-
.
228.
325.
-
table continued next page
A-9
-------
Table A-7 (continued). EMISSION FACTORS AND FUEL CONSUMPTION
FOR CONSTRUCTION EQUIPMENT BY CATEGORY AND REFERENCE
Equipment
category
Wheel
dozers
General
purpose
All equip' t.
Earth -
movers
only
Diesel or
gasoline
Diesel
Diesel
Gasoline
Both
Both
Diesel
Ref.
38a
34
38a
34
38a
34
34
34
35*
36e
34
Brake specific emissions, g/hp hr
HC
0.58
0.576
1.68
1.03
7.18*
8.3f
1.85
1.45
0.958
0.630
1.04
CO
1.83
1.83
4.08
2.82
218.
198.
32. 1
14.9
2. 84
3. 19
2.90
NOX
12.5
12.5
9.03
14.8
5. 24
4.79
13.3
9.61
6.53
8.94
9. 62
Part.
0.41
0.411
1.51
0.907
0.37
0.300
0. 816
0.731
M
0.29
0. 633
RCHO
—
0. 16
—
0.20
-
0.23
0.21
0.20
—
.
sox
0.87
0.867
0.92
0.933
0. 23
0.273
0.834
0.752
—
1.53
0.769
BSFC
g/hp hr
—
197.
—
212.
•*
308.
-
-
—
-
-
aAll Reference 38 values based on Reference 34.
b
25 percent allowance included for evaporative and crankcase emissions.
'•Allowance included for evaporative and crankcase emissions (variable).
dEstimate for 1969 made in 1970.
eEstimate for 1969 made in 1972.
A-10
-------
APPENDIX B
LIST OF COUNTY DATA SOURCES
-------
PRIMARY SOURCES
1. County and City Data Book, A Statistical Abstract Supplement.
U. S. Department of Commerce. 1972.
2. 1969 Census of Agriculture, Volume I - Area Reports. U. S.
Department of Commerce, Bureau of the Census.
3. Area Measurement Reports. U. S. Department of Commerce/
Bureau of the Census. Publication GE-20, No. 1. May 1970.
4. New York State Statistical Yearbook - 1973. New York State
Division of the Budget/Office of Statistical Coordination.
5. Statistical Abstract of Ohio - 1969. Economic Research
Division Development Department.
6. South Carolina Statistical Abstract - 1973. South Carolina
Budget and Control Board, South Carolina Division of Research
and Statistical Services. July 1973.
7. Wisconsin Statistical Abstract - Third Edition. Department of
Administration, State Bureau of Planning and Budget, Infor-
mation Systems Unit. June 1974.
8. Motor Vehicle Units Registered for the Year 1973. State of
Illinois. Accounting Revenue Division.
9. 1973 County Audit Report. Missouri Department of Motor
Vehicles.
B-2
-------
SECONDARY SOURCES
10. Economic Abstract of Alabama 1972. Center for Business and
Economic Research, Graduate School of Business, The Univer-
sity of Alabama, University, Alabama, December 1972.
11. Arizona Statistical Review. Phoenix, Arizona, Economic Re-
search Department, September 1973.
12. The Arkansas Almanac 1972. Little Rock, Arkansas, Arkansas
Alamanca, Incorporated.
13. California Statistical Abstract 1973. Sacramento, California, 1973.
14. Delaware Statistical Abstract 1974. Social and Economic Analysis
Section, Delaware, State Planning Office, Dover, Delaware.
15. Florida Statistical Abstract 1973. Gainsville, Florida, University
of Florida Press, August 1973.
16. Norman Nybroten. Idaho/1971 Statistical Abstract, Moscow, Idaho,
University of Idaho, August 1971.
17. 1972 Edition Illinois State and Regional Economic Data Book. State
of Illinois Department of Business and Economic Development.
18. 1972 Statistical Profile of Iowa. Des Moines, Iowa, The Iowa
Development Commission.
19. Kansas Statistical Abstract 1973. Institute for Social and Environ-
mental Studies, The University of Kansas, Lawrence, Kansas.
20. Statistical Abstract of Louisiana. Division of Business and Econo-
mic Research, College of Business Administration, Louisiana State
University in New Orleans. Fourth Edition 1971.
21. 1973 Maryland Statistical Abstract. Department of Economic and
Community Development, State of Maryland, Annapolis, Maryland.
22. Michigan Statistical Abstract, Tenth Edition 1974. East Lansing,
Michigan, Michigan State University.
23. Minnesota Statistical Abstract 1973, Vols. land 2. St. Paul, Min-
nesota, Minnesota State Planning Agency.
B-3
-------
24. Mississippi Statistical Abstract 1973. Mississippi State,
Mississippi, Division of Research, College of Business and
Industry, Mississippi State University, May 1973.
25. Data for Missouri Counties. Columbia, Missouri, University
of Missouri.
26. Montana Data Book. Helena, Montana, Department of Planning
and Economic Development, State of Montana, 1970.
27. Nebraska Statistical Handbook, 1974-1975. Lincoln, Nebraska,
The Nebraska Department of Economic Development.
28. New Mexico Statistical Abstract 1972. Albuquerque, New Mexico,
The University of New Mexico.
29. North Carolina State Government Statistical Abstract, Second Edition
1973. Statistical Services Section, Office of State Budget, Depart-
ment of Administration.
30. Statistical Abstract of Oklahoma 1972. Norman, Oklahoma, Bureau
for Business and Economic Research, University of Oklahoma, May
1973.
31. Pennsylvania Abstract 1973. Harrisburg, Pennsylvania, Department
of Commerce.
32. Tennessee Statistical Abstract 1 971. Knoxville, Tennessee, Center
for Business and Economic Reasearch, The University of Tennessee.
33. Texas Almanac and State Industrial Guide 1972-1973. A. H. Belo
Corporation.
34. Statistical Abstract of Utah 1973. Bureau of Economic and Business
Research, Center for Economic and Community Development, Uni-
versity of Utah.
35. Vermont Facts and Figures 1973. Montpelier, Vermont, Vermont
Department of Budget and Management, March 1973.
36. Statistical Abstract of Virginia 1966, Vol. I and 1970, Vol. II.
Charlottsville, Virginia, University of Virginia.
37. The Research Council's Handbook, Fourth Edition. Olympia, Wash-
inton, Washington State Research Council.
38. The 1973 Statistical Handbook. Charleston, West Virginia, West
Virginia Research League, Inc.
B-4
-------
39. Wyoming Data Book 1972. Laramie, Wyoming, Division of
Business and Economic Research, University of Wyoming.
B-5
-------
APPENDIX C
DOCUMENTATION OF COUNTY METHODOLOGY DEVELOPMENT
-------
DOCUMENTATION OF COUNTY METHODOLOGY DEVELOPMENT
The purpose of this Appendix is to present procedures utilized
in arriving at two of the county methodologies described in Section IV,
including several methods which proved unsuccessful. The categories
for which this presentation will be made are outboard motors and snow-
mobiles. Methodologies for the other categories were developed in a
more straightforward way because either (1) ample information was
available on which to base a logical method or (2) insufficient information
was available to check on the method developed. In the first case, the
methodologies will yield emissions data having good accuracy. In the
second case, the accuracy of calculated values simply cannot be assessed;
so they must be accepted as gross estimates. The categories for which
good data are available are motorcycles and farm equipment. Those
for which few data are available are lawn and garden equipment, cons-
truction equipment, and farm equipment.
1. Outboard Motors
A number of general regression analyses were attempted; and to
show the results concisely, the following terms are defined:
fl = percent of state boat registrations in county
f2 = percent of state boat usage in county
f3 = percent of state population in county
f5 = percent of state inland water area in county.
Data were obtained on fl, f3, and f5 for New York('), Ohio* ', South
Carolina''', and Wisconsin'* '. Data on f2 were obtained only for New
York. Regressions were calculated for all the data together, and also
for individual states, urban and rural areas, and coastal and inland
areas. The results of these regression analyses are shown in Table
C-l, and none of the general ones is very promising.
Another approach tried was to characterize the outboard popu-
lation in terms of generalities and then to fit a mathematical model to
these generalities once complete. The observations and calculated data
were the following:
(a) Boat registrations are basically proportional to population
in each state.
(b) Except for inland counties having no surface water usable
for boating ("dry" counties), boats used correlate strongly
with boat registrations (r over 0.9). To be recorded, ponds
must have areas of 40 acres (0. 16 km^) or more and streams
must be at least 1/8 mile (0. 20 km) wide.
C-2
-------
Table C-l. REGRESSION ANALYSES ATTEMPTED
ON OUTBOARD MOTOR DATA
Dependent
variable
f2
fl
fl
fl
fl
fl
fl
fl
fl
fl
fl
fl
fl
fl
Independent
variable(s)
fl
£3
f3
£3
£3
£3
£3
£3
£3
£3
£3
£3. £5
£3
£3
Data utilized
All NY
All coastal
All inland
NY coastal
Ohio coastal
SC coastal
Wise, coastal
NY inland
Ohio inland
SC inland
Wise, inland
All NY
All urban
All non-urban
Coefficients )
a
0.0431
1.103
0.255
0.616
0.781
0.503
0.545
0.150
0.172
0.0874
0.340
0.0627
3.97
0.222
b
0.905
0.672
0.885
1.195
0.591
1.075
0.532
1.42
0.880
0.910
0.873
1.257
0.420
0.927
c
0.146
r2
0.892
0.694
0.809
0.686
0.958
0.985
0.991
0.752
0.836
0.813
0.766
0.795
0.372
0.806
(c) As an average, 9 percent more boats are used in coastal
counties than are registered in those counties' '. This gen-
eralization includes counties bordering the great lakes as
well as the oceans.
(d) Congested urban areas generally show fewer outboards re-
gistered than would be projected solely on a population basis.
The following terms were also defined:
^ = county population density (inhabitants/mi ), {^ 1000 is cri-
terion for urban county;
', ", '" as superscripts indicate values after first, second, and
third corrections (coastal-inland correction, dry-wet correction,
and urban—non-urban correction, respectively);
c, i, d, w, u, and n as second subscripts mean "coastal", "in-
land", "dry", "wet", "urban", and "non-urban", respectively.
The estimation procedure was as follows:
(a) Assume f2 = £3 (f3, f5, and ^ , and an indicator of coastal ar
inland status should be tabulated by county for the state)
C-3
-------
(b) Make the "coastal-inland" correction by calculating:
1-0.09 \ ; and tabulating
(c) Make the "dry-wet" correction by calculating:
/ V '
" n i / ),£ 2d
f2d = 0; £2w = £2w { 1 + - — j; and tabulating by county.
(d) Make the "urban-rural" correction by calculating:
II r-» i
- Lf2U
0.53 ; f2n = f2nl V " V "' /: and tabu-
lating by county.
to
The values f2 were the final results for all the counties on a. per-
centage basis and could be multiplied by the state boat population to yield
the actual number of boats used in each county. While the method guaran-
iii ' HI °
tees that the sum of the f2 equals 100 percent, the individual f did not
agree very well with the individual f2 for New York (r^ = 0.35).
2. Snowmo biles
The only county snowmobile registration data located were for
New York' ', and a number of approaches were attempted before a
usable relationship was found. The following terms are defined for
convenience:
gl = percent of state snowmobile registrations in county
g2 = percent of state snowmobile usage in county
g3 = percent of state population in county
g4 = snowfall, in/yr
g5 = development index = (number of snowmobile developments
in county)"- .
The regression analyses attempted are described in Table C-2,
verifying that snowmobile usage correlates well with registration.
Table C-2 also shows that separating urban and rural areas enhances
the accuracy of the estimate for rural areas and that the "development
index" is only a marginal contributor to variability in usage. The ex-
pression second from the bottom of Table C-2 was the one modified
for use in the methodology, along with an empirical correction to re-
flect low registrations and usage in congested urban areas. The modi-
fication consisted of normalizing the snowfall term to a percentage of
snowfall at the state's geographical center, making the coefficient c -
take on the new value 0. 0321.
C-4
-------
Table C-2. REGRESSION ANALYSES ATTEMPTED
ON NEW YORK SNOWMOBILE DATA
Dependent
variable
g2
g2
g2
g2
g2
g2
g2
g2
g2
g2
g2
Independent
variable(s)
gl
gl, g5, g3, g4
gli g5, g3, g4
gl, g3, g5, g4
g3
g4
(g5)2
g3,g4
g3,g5,g4
g3» g4
g3, g4, g5
Data utilized
All
All
Non-urban
Urban
All
All
All
All
All
Non-urban
Non-urban
Coefficient(s)
a
0.0392
-2. .224
-2.418
0.119
1.702
-1.020
1.306
-2.125
-2.229
-2.345
-2.424
b
0.977
-0. 00294
-0. 00175
0.981
-0.0092
0.0400
0.111
0. 250
0.273
1.560
1.579
c
0. 234
0.143
-0.00272
0. 0521
0. 236
0.0458
0.0432
d
0.272
1.576
0.0945
0.0476
0.145
e
0.0478
0.0433
-0.00660
r2
0.994
0.425
0.665
0.999
0.00016
0.317
0.0633
0.408
0.424
0.657
0.665
o
Un
-------
APPENDIX D
UTM TO GEOGRAPHIC COORDINATE CONVERSION PROGRAM
-------
000003
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000033
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000055
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000070
000073
000075
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000077
000100
000100
000102
00010H
OOOlOb
000107
000110
000111
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000131
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oooite
OOOlbb
c
c
PROGRAM UTMGEOCINPUT,OUTPUT)
DIMENSION YNORTHJH ) , XE A ST ( H ) * I I_D ( H ) , ILM ( H ) , SL A ( H )
DIMENSION IGP{H),IGMCO,SNGCO
(DEGREES) PROGRAM TRANSFORMS UTM TO GEOGRAPHIC
COORDINATES (TBM-lfa-JAN-73)
SCALE = .
ENSNS = ENU * SECRD
EPCS = EPSO * CCSO
CPCSQ = 1. t EPCS
QSO = 0*0
QCU = OSCi * 0
QFR = QCU * Q
QFV = OFR * 0
OSX = QFV * Q
SCLAT = 1./CSLAT
ENSN& = ENU**'t * ENSNS
SVN = (((TNLAT/(2.*ENU*ENSNS))*F.PCS03/(SCALE*SCALF)3*lO.Eil
EG=5.+3.*TNSQ+SEPO*CCCSQ-SNSQ)-(3.*EPSQ**2*CCSO)*(CCSO+3.
1*SNSQ)
EGH = TNLAT/(2H.*ENU**3*ENSNS)
EGHT = (EGH*EG/SCALE**f)*10.E+23
D-2
-------
000172 Dblsfal,+(H5.*TNSQ)*(2,+TNSl3-EP8Q*SNSQ)+EPSQ*(J07,*CCSn
l«lb2.*SNSU)
00020B Db2=TNLAT/(?20,*ENU**5*ENSNS)
000213 Ob s (QSX*Db2*Dbl/SCALE**b)*10Ef35
OUC220 ANINE = (SCLAT/ENSNS)/SCA|.£*1U,E5
000223 TEN = (SCLAT/Cb.*ENU**2*ENSN3)>*(1.+2.*TNSQ+EPCS)
1/SCALE**3*10,E17
00023fa ES = G)FV*(SCLAT/(iaO,*ENiSN5))*(5, + (H,*TNSQ)*(7f'»-bt*TNSQ)
IfC2,*EPSQ)*(3.*CCSQ+H.*SNSa))/SCALE**5*10.E2R
0002bH XLAT = PHIS-SVN*QSQ + EGHT*GFR - Dfa
000272 OLAM a ANINE*Q - TEN*QCU +E5
000300 7"fO CONTINUE
000300 XLONCJ s CM + OLAM
000302 YLONG = -XlONG/3bDO,
000301 YLAT = XLAT/3bOO,
OOOSOb 101 s YUAT
0130310 REM s (YLAT-IDl) * 3bOO.
000313 IM1 = REM/faO,
000315 31 = REM - (IMl*bO,)
000320 ID2 a YLONG
000322 REM = (YLONG - 102) * 3bOOt
000325 IM2 s REM/bO.
000327 32 s REM-CIM2*bOf)
000332 ILDCDsIOl
OU0335 ILMCDsIMl
OOQ33b SLACI)=S1
OQ03tO IGO(I)=ID5
0003^1 IGM(I)elM2
000343 SNG(I)=S2
0003HH 200 CONTINUE
0003tb IFCLCT .LT, 58) GO TO HO
000350 PRINT 104,IPAGE
00035b 10H FORHAT(*l*»15Xr*ST LOUlS AQCR GRID SQUARE COORDINATES*/* PAGE*,I3/
1 * ID 1 2 3 H*
2 /10X, *OEG MIN SEC DEC MIN SEC UEG MIN SEC DEG MIN SE
3C*)
00035b LCT=t
000357 IPAGE sIPAGE+J
0003bl HO PRINT 102,ID,(ILO(I),ILM(I),SLA(I),1=1,H),
1 (160(1),lGM(I)r3N6(I),Ial,f)
OOOH13 LCTsLCT+3
OOOH15 101 FOHMAT(IH,1X,-3P8F5,1)
OUOH15 102 FORMAT(*U*,IH,* LAT*,H(I'»,I3,Fb,2)/5X,* LONG*,H(IH,I3,Fb,2))
OOOH15 GO TO 32
OOOH15 W STOP
00OH!7 END
D-3
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
2.
3. RECIPIENT'S ACCESSION-NO.
4, TITLE AND SUBTITLE
Methodology for Estimating Emissions from Off-Highway
Mobile Sources for the RAPS
5. REPORT DATE
10-30-74
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO,
Charles T. Hare
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Southwest Research Institute
8500 Culebra Road
San Antonio, Texas 78284
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-02-1397
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final Report 3/74-9/74
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Emissions, population, and usage data existing in the technical literature have
been collected and organized for the following unregulated sources: outboard motors,
snowmobiles, motorcycles, lawn and garden equipment, construction equipment, in-
dustrial equipment, and farm equipment.
Methodologies for estimating emissions and fuel consumption on a county basis
have been developed for the sources noted above. They have been demonstrated for
counties in the St. Louis Metropolitan Air Quality Control Region (AQCR 070), and
their strengths and weaknesses have been discussed. Methods have also been de-
veloped to apportion county emissions estimates to grid elements, but they have not
been demonstrated. The exhaust constituents assessed include hydrocarbons (HC),
carbon monoxide (CO), oxides of nitrogen (NO ), particulate, aldehydes (RCHO), and
oxides of sulfur (SO ). For outboard motors, neither particulate nor aldehyde data
were available; but Carbon dioxide (C02) emissions were included.
7.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
Mobile Source Emissions
Apportion Emissions
3. DISTRIBUTION STATEMEN1
Release Unlimited
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
86
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
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