United States
Environmental Protection
Agency
Office of Mobile Source Air Pollution Control
Emission Control Technology Division
2565 Plymouth Road
Ann Arbor, Michigan 48105
EPA 460/3-83-007
August 1983
xvEPA
Air
Petroleum Versus Alternate-Source
Fuel Effects on Light-Duty Diesel
Emissions
-------
EPA 460/3-83-007
Petroleum Versus Alternate-Source Fuel
Effects on Light-Duty Diesel Emissions
by
Bruce B. Bykowski
Southwest Research Institute
6220 Culebra Road
San Antonio, Texas 78284
Contract No. 68-03-3073
Work Assignment 5
EPA Project Officer: Robert J. Garbe
Branch Technical Representative: Thomas M. Baines
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Mobile Source Air Pollution Control
Emission Control Technology Division
2565 Plymouth Road
Ann Arbor, Michigan 48105
August 1983
Agency
ฃ30 S. Dear :v-,vr, . ;;, t, _.,j;n 1670
Chicago, iL 60604-
-------
This report is issued by the Environmental Protection Agency to report
technical data of interest to a limited number of readers. Copies are
available free of charge to Federal employees, current contractors and
grantees, and nonprofit organizations - in limited quantities - from
the Library Services Office, 2565 Plymouth Road, Ann Arbor, Michigan
48105.
This report was furnished to the Environmental Protection Agency by
Southwest Research Institute, 6220 Culebra Road, San Antonio, Texas,
in fulfillment of Work Assignment 5 of Contract 68-03-3073. The
contents of this report are produced herein as received from Southwest
Research Institute. The opinions, findings, and conclusions expressed
are those of the author and not necessarily those of the Environmental
Protection Agency. Mention of company or product names is not to be
considered as an endorsement by the Environmental Protection Agency.
Publication No. EPA 460/3-83-007
11
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FOREWORD
This project was conducted for the U.S. Environmental Protection Agency
by the Department of Emissions Research/ Southwest Research Institute. The
laboratory testing phase of the project began in June 1982, and was completed
in January 1983. The work was performed under EPA Contract No. 68-03-3073/
Work Assignment No. 5, and was identified within Southwest Research Institute
as Project 05-6619-005. The scope of work defined by the EPA is located in
Appendix A of this report. The EPA Project Officer was Mr. Robert J. Garbe,
and the Branch Technical Representative was Mr. Thomas M. Baines, both of the
Characterization and Technical Applications Branch, Emission Control Tech-
nology Division, Environmental Protection Agency, 2565 Plymouth Road, Ann
Arbor, Michigan. The Southwest Research Institute Project Manager was
Charles T. Hare, and the Project Leader and Principal Investigator was
Bruce B. Bykowski.
111
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ABSTRACT
This report describes laboratory emissions evaluation of several alternate-
source diesel fuels in a 1980 Volkswagen Rabbit. These evaluations are essen-
tially a continuation of a previous study of several alternate-source fuels
under EPA Contract 68-03-2884, Task Specification No. 3. The complete fuel
matrix consisted of a No. 2 petroleum diesel fuel as base, mixtures of base
fuel plus coal-derived liquids, shale oil diesel fuel, shale jet fuel, and
a blend of petroleum stocks with coal and shale liquids. Two of the eleven
fuels were evaluated during this latest project.
Vehicle operating procedures used for test purposes included those
specified in Federal Regulations (FTP)(D* and several steady-state modes.
Both regulated and unregulated gaseous and particulate emissions were measured
using a CVS-PDP and dilution tunnel operating on the entire exhaust stream of
the engine. DOAS odor analysis was performed on raw exhaust samples during
steady-state operation. Biological response evaluations, BaP measurement, and
HPLC fractionation were conducted on the organic soluble portion of the parti-
culate. The majority of the sampling and analytical procedures used were
developed during earlier EPA Contracts 68-02-2494(2>, 68-03-2707(3>,
68-02-1230<4'5'), and 68-03-2440.<6)
After laboratory emission evaluations of the fuels were completed, the
resulting data base, representing alternate-source fuels,was analyzed statis-
tically along with data available in the literature representing petroleum-
based fuels. Regression analysis was used to determine whether alternate-
source materials affected exhaust emissions more strongly, less strongly, or
to about the same extent as petroleum-based fuels.
*Numbers in parentheses designate references at the end of the report.
iv
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TABLE OF CONTENTS
Page
FOREWORD iii
ABSTRACT iv
LIST OF FIGURES vii
LIST OF TABLES ix
I. INTRODUCTION 1
II. SUMMARY AND CONSLUSIONS 3
III. TEST VEHICLE AND FUELS 5
A. Test Vehicle 5
B. Test Fuels 6
IV. INSTRUMENTATION AND ANALYTICAL PROCEDURES 9
A. Vehicle Operation and Smoke Measurements 9
B. Regulated and Unregulated Gaseous Emissions 9
C. Particulate Collection, Mass Rate, and Aerodynamic Sizing 10
D. Analysis of Particulate Composition 12
E. Analysis of the Soluble Fraction of Particulate Matter 12
V. TEST PLANS AND OPERATING SCHEDULE 15
A. Vehicle Test Plan 15
B. Quality Assurance Project Plan 15
C. Statistical Analysis Test Plan 18
VI. GASEOUS AND PARTICULATE EMISSION RESULTS 19
A. Regulated Gaseous and Particulate Emissions Results 19
B. Aldehyde and Phenol Results 20
C. Results of Odor Analysis 21
D. Visible Smoke Emissions 21
E. Particulate Size Distribution 24
F. Analysis of Particulate Composition 24
G. Composition of Organic Solubles in Particulate Matter 25
H. Gas Chromatograph "Boiling Range" Analysis of Organic
Solubles 26
I. Fractionation by Relative Polarity 27
J. Benzo(a)pyrene (BaP) in Organic Solubles 30
K. Mutagenic Activity by Ames Testing 31
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TABLE OF CONTENTS (Cont'd)
VII. STATISTICAL ANALYSIS OF FUEL AND EMISSIONS DATA
A. Statistical Methodology 33
B. Raw Data Acquisition 38
C. Selection of Variables and Study Identification 38
D. Data Normalization 39
E. Scattergrams of Select Variables 46
F. Additional Comments 68
REFERENCES 77
APPENDICES
A. Scope of Work, Work Assignment No. 5, Contract 68-03-3073
B. Test Vehicle Baseline Check
C. Gaseous and Particulate Emission Results
D. Statistical Analysis Results
E. Scattergrams
VI
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LIST OF FIGURES
Figure Page
1 Schematic Diagram of Exhaust Dilution Tunnel 11
2 HPLC Response to BaP and 9-Fluorenone 28
3 HPLC Response to Extract Generated from Base DF-2 28
4 HPLC Response to Extract Generated from SASOL Middle 29
Distillate
5 HPLC Response to Extract Generated from 25% H-Coal 29
6 Normalized HC versus Cetane 49
7 Normalized HC versus Cetane by Individual Study 50
8 Normalized HC versus Aromatics 52
9 Normalized HC versus Density 53
10 Normalized HC versus 10% Boiling Point 54
11 Normalized HC versus 90% Boiling point 55
12 Normalized CO versus Cetane 57
13 Normalized CO versus Aromatics 58
14 Normalized CO versus Nitrogen 59
15 Normalized NOX versus Aromatics 61
16 Normalized NOX versus Density 62
17 Normalized NOX versus 10% Boiling Point 63
18 Normalized Particulate versus Aromatics 64
19 Normalized Particulate versus 90% Boiling Point 65
20 Normalized Particulate versus Density 66
21 Normalized Particulate versus 10% Boiling Point 67
22 Normalized Fuel versus Olefins 69
23 Normalized Fuel versus Density 70
vii
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LIST OF FIGURES (Cont'd)
Figure Page
24 Normalized BaP versus Nitrogen 71
25 Normalized BaP versus Aromatics 72
26 Normalized Aldehyde versus Aromatics 73
27 Normalized Solubles versus Cetane 74
28 Normalized Solubles versus Nitrogen 75
Vlll
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LIST OF TABLES
Tables Page
1 Description of Test Vehicle 5
2 Comparative Emissions Data, Two Studies 6
3 Fuel Properties and Composition 1
4 Outline of Chemical and Physical Exhaust Evaluations 16
5 Test Plan for Each Fuel 17
6 Average Regulated Gaseous Emissions Data 19
7 Average Particulate Mass Emissions Data 20
8 FTP Aldehyde Emissions Data 22
9 FTP Phenol Emissions Data 22
10 HFET Phenol and Aldehyde Emissions Data 23
11 Results of Odor Analysis at Steady States 23
12 Summary of Visible Smoke Data 23
13 Particulate Size Distribution 24
14 Carbon and Hydrogen in Exhaust Particulate Matter 24
15 Percent Trace Elements in Particulate Matter 25
16 Composition of the Organic Soluble Portion of the
Particulate
26
17 Chromatograph Analysis of Organic Solubles in Particulate
Matter 27
18 BaP Present in Organic Solubles During FTPC + FTPft 30
19 Particulate Emissions Versus Fuel Aromatic Content,
Mock Data 36
20 Number of Pearson Correlation Coefficients Greater than
0.700 for Fuel Properties vs. Emissions 40
21 Number of Pearson Correlation Coefficients Greater than
0.700 for Fuel Properties vs. Fuel Properties 41
ix
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LIST OF TABLES (Cont'd)
Table Page
22 Number of Pearson Correlation Coefficients Greater than
0.700 for Emissions vs. Emissions 42
23 Fuel Property - Exhaust Emission Correlation for the
Alternate-Source Fuel Study 43
24 Selected Fuel Property-Exhaust Emission Data Pairs 43
25 Pearson's Correlation coefficients for Select Fuel
Property - Exhaust Emission Data Pairs 44
26 Analyses of Phillips 2D Diesel Fuel Lots 45
27 Emission Normalization Factors for Select Fuel Property -
Exhaust Emission Data Pairs 47
28 Comparison of Observed versus Predicted Hydrocarbons 51
as a Function of Fuel Cetane using Petroleum-Based Fuel
Study Equation and Alternate-Source Fuel Data 51
29 Hydrocarbon Data Pairs Good-of-Fit 56
30 CO Data Pairs Goodness-of-Fit 56
31 NOX Data Pairs Goodness-of-Fit 60
32 Particulate Data Pairs Goodness-of-Fit 60
33 Unregulated Emission Data Pairs Goodness-of-Fit 68
x
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I. INTRODUCTION
The world's supply of crude oil is being depleted, creating incentives
for discovery and utilization of alternate sources of fuels. Although
interest has waned somewhat due to the current oil glut, it is considered
important to continue research and development in preparation for the time
when alternate-source fuels become a viable alternative. This study was
designed to determine if alternate-source fuels, as currently available, will
disproportionately affect exhaust emissions as compared to petroleum-based
fuels. A light-duty diesel vehicle was used for test purposes. Diesel
engines offer more sensitive evaluation of alternate fuel effects than gasoline
cars do. No exhaust aftertreatment system has to be used on diesel automobiles
to meet HC and CO standards for 1983, but a catalytic converter system is
used on gasoline-fueled vehicles. Changes in diesel exhaust emissions due
to alternate fuels thus affect the atmosphere and the recipient directly,
but the catalyst on a gasoline vehicle tends to reduce the impact of changes
in emissions seen in the raw exhaust.
This study continued the work performed under EPA Contract 68-03-2884,
Task Specification No. 3. As discussed in that report^7), alternate fuel
utilization and long-term research are basically still in their infancy due
to the absence of large-volume production. Pilot plant yields are small, and
the cost for pilot plant production of quantities suitable for testing in
this program was prohibitive. Materials available in test quantities mostly
represent first-generation alternate source materials. "First generation"
refers to materials derived from alternate sources with little or no after-
treatment, such as hydrogenation or catalytic cracking. In most cases,
these currently available liquids did not have the specifications to run
"as is." These liquids were blended with a petroleum base fuel to permit
observation of any changes in emissions.
Selection of compounds used in both studies was made on the basis of
availability, variety, and anticipation of second-generation compositions.
Substances investigated include coal-derived liquids from the Solvent Refined
Coal (SRC-II), Exxon Donor Solvent (EDS), and the Hydrocarbon Research
(H-Coal) processes, shale oil products, a broadcut fuel containing n-butane
among other stocks, and a mixture of coal, shale, and petroleum products.
A literature search was conducted to obtain published reports of
technical papers presenting data on petroleum fuel effects on light-
duty diesel emissions. The data from these studies and the data generated
from the alternate source studies were normalized and statistically analyzed
to present data in such a manner that a determination might be made as to
the effects of alternate-source fuels on emissions as compared to petroleum
fuels.
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II. SUMMARY AND CONCLUSIONS
The major objective of this project was to determine if the effects
of property variation in alternate-source fuels on exhaust emissions were the
same, less pronounced, or more pronounced than the effects of property variation
in petroleum fuels. This study generated exhaust emissions data using several
alternate-source diesel fuels in a 1980 Volkswagen Rabbit. The same vehicle
was used in an earlier study(7) to evaluate several other alternate-source
fuels. Data from this study and the previous studyf) were combined to repre-
sent alternate-source fuel effects on light-duty diesel exhaust emissions.
Data regarding petroleum fuel effects on light-duty diesel emissions were
obtained by reviewing available studies found in a library literature search.
One of the major challenges in performing this work was to formulate a
statistical analysis test plan which would strengthen the statistical arguments,
while minimizing the number of assumptions and maximizing the applications of
the conclusions. The data base available had some severe limitations which
restricted the application of more advanced statistical concepts. These
limitations were that experiments were performed at differing times, under
differing test conditions, and with differing objectives. Due to these con-
ditions, it was expected that only general trend information would be available
at the conclusion of this project. Decisions on whether petroleum fuels and
alternate-source fuels affected exhaust emissions similarly or differently
were based on calculated chi-square values or goodness-of-fit statistics.
The most important observations and conclusions reached as a result of
this project (not necessarily in order) are as follows:
1. SASOL middle distillate fuel was associated with exhaust emissions
similar to those observed while evaluating a shale diesel marine fuel.
In general, the SASOL fuel was associated with the same or slightly
lower emission levels as compared to the base fuel.
2. The 25 percent H-Coal blend has properties and emission results
similar to the 25 percent EDS blend (both coal-derived liquids). Both
fuel blends were associated with increases in emissions.
3. It appears that further treatment of "first generation" coal liquids
by hydrogenation or catalytic cracking would result in "second
generation" materials which do not increase exhaust emissions. This
conclusion is based on comparing results of "first generation"
liquids (SRC-II, EDS, H-Coal) and "second generation" materials
(shale diesel marine, Paraho JP-5, SASOL).
4. Review of various studies obtained by the library literature search
indicated a wide variety of conclusions concerning fuel effects on
exhaust emissions. In most cases, the primary conclusion appeared
to be that the vehicle/engine type, followed by driving cycles, affected
exhaust emissions on a g/km basis more than changes in fuel properties.
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5. Bivariate correlation coefficients indicated that the various studies
reviewed were associated with differing types of fuel property-
exhaust emission relationships. For a particular fuel property-
exhaust emission data pair, it was not uncommon for the correlation
coefficients to range from -0.166 to 0.908. Some of these data
having poor correlations yielded linear regression equations whose
slope was opposite that observed with other studies.
6. For each fuel property-exhaust emission data pair, data from the
petroleum-based fuel studies were used to generate prediction
equations. The alternate-source fuel properties were inserted into
the equations to yield predicted emissions. The observed and pre-
dicted emissions were used to determine goodness-of-fit of the
models. Based on these calculations, the effects of alternate-source
fuels on exhaust emissions are statistically indistinguishable from
those associated with petroleum fuels.
7. It is not recommended to use detailed statistical analysis to evaluate
the effects of alternate-source fuels versus petroleum fuels on
exhaust emissions using the currently available data. Reasons include
lack of good data bases, poor correlation within available bases, and
the apparent stronger effects of engine displacement and driving cycle on
exhaust emissions. Comparisons between alternate-source and petroleum
fuels should be performed with the raw data, unless an adequate
statistical experimental design was formulated prior to program initiation.
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III. TEST VEHICLE AND FUELS
The test vehicle used was the identical vehicle previously employed
to evaluate other alternate-source fuels in a previous study (?), continuity
being the primary concern. Fuel selection was directed principally by
availability of alternate-source (non-petroleum) materials not evaluated
under the previous alternate-source study. Alternate-source materials were
analyzed thoroughly to establish the properties of each fuel in detail.
A. Test Vehicle
The test vehicle was 1980 Volkswagen Rabbit diesel. A description of
the vehicle is provided in Table 1, and it was supplied to the Contractor
by EPA for test purposes.
TABLE 1. DESCRIPTION OF TEST VEHICLE
Vehicle Model
Engine Model
Model Year
V.I.N.
Engine No.
Body Type
Inertia equivalent, kg (lbm)
Transmission
Displacement &(in )
Cylinders
Power, kW (hp) @ rpm
Injection System
Combustion Chamber
Compression Ratio
Distance on Vehicle, km
Volkswagen Rabbit
Family D
1980
17A0926720
CK591126
2-Door Hatchback
1021 (2250)
5-speed manual
1.47 (90)
4
(48) @ 5000
Bosch
Swirl Chamber
23:1
2806a, 4980b
a C
at project initiation
at project completion
Initially, the vehicle was driven 220 km for conditioning using the base
fuel. Emission tests were conducted to determine whether or not any shifts
had occurred in the baseline emissions observed during the previous study.f)
The test results are summarized in Table 2. Complete test results can be
found in Appendix B, pages B-2 and B-3. The variability was considered
satisfactory for the purpose of continuing evaluation of alternate-source fuels.
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TABLE 2. COMPARATIVE EMISSIONS DATA, TWO STUDIES
Average FTP Emissions
Earlier Study Current Study
HC, gAm 0.31 0.29
CO, g/km 0.96 0.99
NOX, g/km 0.66 0.70
Particulate, g/km 0.25 0.27
Fuel, H/100 km 6.37 6.40
B. Test Fuels
Most of the available alternate-source fuels were previously evaluated
under another project.^7^ Two additional fuels evaluated during this project
were a SASOL coal-derived middle distillate, and a blend of 25 percent H-Coal
in base fuel (DF-2). Due to the good ignition characteristics of the SASOL
fuel (reflected in its cetane number), it was run "as-is." The H-Coal
material required blending with the base fuel to permit reasonable vehicle
operation. A 25 percent blend was chosen to be consistent with the other
two coal-derived blends previously tested (SRC-II and EDS). Complete fuel
characterization was a part of this sutdy. Properties of all the alternate-
source fuels tested in both the current and previous projects are listed in
Table 3.
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TABLE 3. FUEL PROPERTIES AND COMPOSITION.
Description
Fuel Code (EM-
Cetane No. (D613)
Cetane Index (D976)
Gravity, "API @ 60ฐF
Density, g/mS, @ 60ฐF
Carbon, wt. %
Hydrogen, wt. %
Nitrogen, ppm (oxid. pyrolysis)
Sulfur ( 1 amp) , %
Calculated H/C, numeric
Carbon No. range (.G.C.)
Aromatics, vol. %
Olefins, vol. %
Paraffins, vol. %
Viscosity, cs @ 100ฐF (D445)
Gum, mg/100 mS, (D481)
Total solids, mg/S,
Metals in fuel, x-ray
Boiling Range, ฐC (IBP-EP,D86)
10% point
20% point
30% point
40% point
50% point
60% point
70% point
80% point
90% point
95% point
Residue, wt. % (D86)
Base
DF-2
329-F
50
50
37.5
0.837
85.8
13.0
48
0.24
1.81
8-24
21.3
1.7
77.0
2.36
14.3
7.4
Oa
191-340
219
231
242
251
260
269
278
290
307
323
1.3
Shale Diesel
Marine
453-F
49
52
37.9
0.835
86.3
13.4
5
<0.005
1.85
9-20
28.5
2.1
69.4
2.61
0.3
0.3
Oa
207-317
236
246
252
259
266
272
278
286
295
302
1.0
Paraho
JP-5
473-F
45
42
43.6
0.808
85.9
13.7
<1
0.005
1.90
10-15
22.
2.
76.
1.38
1.4
0
179-248
189
192
196
198
202
206
211
218
228
237
1.5
Coal Case
5A
474-F
42
41
31.1
0.870
86.5
12.4
1600
0.100
1.71
9-24
34.9
1.4
63.7
3.08
38.8
0
192-366
234
244
253
259
267
276
277
292
330
353
1.5
35%
SRC-II
475-F
31
32
28.2
0.886
86.2
11.8
3400
0.31
1.52
8-20
47.0
0.6
52.4
2.53
89. 7b
13.1
0
171-328
207
215
225
234
243
252
263
274
292
309
1.0
Broadcut
Mid-Continent
476-F
35
49
44.1
0.806
86.1
13.2
1000
0.17
1.83
3-24
16.2
0.0
83.8
1.53
23.8
0
21-354
53
121
151
178
216
239
255
270
303
327
1.0
25%
SRC-II
478-F
38
38
31.7
0.867
86.4
12.3
2000
0.23
1.70
8-20
39.9
1.2
58.9
2.45
30.1
7.2
9ppm Fe
178-327
209
220
231
240
250
259
270
281
303
319
1.0
25%
EDS
482-F
44
42
33.8
0.856
86.5
12.7
267
0.16
1.75
8-20
36.4
0.0
63.6
2.37
60.0
3.1
0
179-353
207
218
227
239
251
263
276
293
316
336
1.5
25% EDS
Naphtha
485-F
45
45
38.3
0.833
86.3
13.3
142
0.28
1.84
7-20
25.5
0.5
74.0
1.76
13.1
1.2
0
108-334
157
182
203
223
238
254
267
281
302
319
1.5
25%
H-Coal
526-F
42
46
32.8
0.861
86.8
12.5
980
0.21
1.72
9-20
37.2
1.2
61.6
2.31
54.6
16.3
c
182-331
212
223
231
239
247
256
267
279
299
316
1.0
SASOL
Mid. Dist.
527-F
50
52
44.5
0.804
85.7
14.0
<1
<0.01
1.96
10-24
24.0
0.0
76.0
2.14
24.4
0.8
0
190-404
200
206
210
217
223
233
249
278
339
392
1.0
<10 ppm of Cr, Fe, No, Cu, Zn, and Mg; <70 ppm Pb; <100 ppm Al and Si
cSample not dry after 1 hr. in steam lit block
38 ppm Fe, 14 ppm Cu, 21 ppm Cr, <60 ppm Pb
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TABLE 3 (CONT'D). FUEL PROPERTIES AND COMPOSITION.
Substance
Fuel Code (EM-
Boiling Range, ฐC (IBP-EP,D2887)
10% point
20% point
30% point
40% point
50% point
60% point
70% point
80% point
90% point
95% point
Residue, wt. % (D2887)
Composition, Volume %
Kerosene
Petroleum
JP-5
JP-8
Diesel
Petroleum
Shale DFM
Coal
Light Cycle Oil
LSR Naphtha
HSR Petroleum
Shale
Coal (Simulated)
N-Butane
Base
DF-2
329-F
104-387
197
220
239
256
268
280
292
307
330
347
0.0
0.0
0.0
0.0
100.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Shale Diesel
Marine
453-F
118-341
216
237
254
265
274
285
297
307
319
325
0.0
0.0
0.0
0.0
0.0
100.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Paraho
JP-5
473-F
157-286
175
187
195
201
210
216
224
234
244
254
0.0
0.0
100.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Coal Case
5A
474-F
140-416
217
238
254
264
271
284
299
315
344
367
0.0
17.3
0.0
0.0
66.7
0.0
16.0
0.0
0.0
0.0
0.0
0.0
0.0
35%
SRC-II
475-F
0.0
0.0
0.0
65.0
0.0
35.0
0.0
0.0
0.0
0.0
0.0
0.0
Boradcut
Mid-Continent
476-F
24-399
68
123
155
196
233
251
262
280
314
342
0.0
22.0
0.0
0.0
23.0
0.0
6.2
5.2
7.4
4.8
20.9
0.0
10.5
25%
SRC-II
478-F
129-508
193
214
232
248
259
271
285
302
321
345
0.0
0.0
0.0
0.0
75.0
0.0
25.0
0.0
0.0
0.0
0.0
0.0
0.0
25%
EDS
482-F
128-419
192
210
228
243
257
273
289
305
332
356
0.0
0.0
0.0
0.0
75.0
0.0
25.0
0.0
0.0
0.0
0.0
0.0
0.0
25% EDS
Naphtha
485-F
72-455
139
174
197
225
249
264
279
298
314
336
0.0
0.0
0.0
0.0
75.0
0.0
25.0
0.0
0.0
0.0
0.0
0.0
0.0
25%
H-Coal
526-F
122-382
196
214
230
241
254
266
278
294
316
335
0.0
0.0
0.0
0.0
75.0
0.0
25.0
0.0
0.0
0.0
0.0
0.0
0.0
SASOL
Mid. Dist.
527-F
161-487
188
198
208
216
228
241
261
292
358
410
0.0
0.0
0.0
0.0
0.0
0.0
100.0
0.0
0.0
0.0
0.0
0.0
0.0
00
<10 ppm of Cr, Fe, NI, Cu, Zn, and Mg; <70 ppm Pb; <100 ppm Al and Si
-------
IV. INSTRUMENTATION AND ANALYTICAL PROCEDURES
Analytical procedures and equipment used to measure regulated and unreg-
ulated emissions are described briefly in this section. These procedures were
used in earlier EPA Contracts(2,3,6,7)f an(j are routinely used in present-day
emission testing.
A. Vehicle Operation and Smoke Measurements
The VW Rabbit was operated to simulate road experience on a 2-roll Model
ECE-50 Clayton light-duty chassis dynamometer, of the type qualified for
Federal light-duty certificaiton.(Q) Inertia and power absorption settings
used for all test work on this dynamometer were set to simulate operations of
an earlier model VW Rabbit tested in a previous study. '''
Care was taken to insure that the vehicle's fuel system was purged properly
before testing of each fuel. All test fuels were withdrawn from individual
19 liter cans. Prior to test, a 2 liter sample of test fuel was used to run
the vehicle, with the return line routed to a container subsequently dis-
carded. After this purge, the vehicle was operated for approximately 30
minutes, followed by FTP and HFET driving cycles, to remove any residuals
from other fuels, and to insure that the vehicle fuel system contained only
the fuel to be tested.
Exhaust smoke measurements were made using an optical light-extinction
smokemeter, of the type specified in Federal regulations for heavy-duty
diesel engine smoke certification.^ The smokemeter was mounted on a 51 mm
(2 in.) O.D. tailpipe extension when in use. The control/readout unit for the
smokemeter was mounted remote from the vehicle under test, and continuous
recordings of smoke opacity were made concurrently with vehicle speed traces.
Smoke measurements were made over the first 505 seconds of the cold-start FTP
cycle, while the vehicle was operated on the chassis dynamometer. This pro-
cedure was developed for research purposes on an earlier EPA Contract,
No. 68-03-2417.(1Q)
B. Regulated and Unregulated Gaseous Emissions
Regulated gaseous emissions of hydrocarbons (HC), carbon monoxide (CO),
and oxides of nitrogen (NOX) were collected and analyzed using procedures
and equipment described in the Federal Register.(8) r^e method of hydrocarbon
analysis was an updated version of that proposed, and eventually adopted for,
the 1980 Federal Register.^
The unregulated gaseous emissions measured were aldehydes, phenols, and
odor. Aldehydes were measured using the 2,4-dinitrophenylhydrazine (DNPH)
method.(2) The method consists of withdrawing a continuous sample of dilute
exhaust at a rate of 0.24 m3/hr, and bubbling the sample through glass
impingers containing DNPH in hydrochloric acid. This process forms the
aldehydes, phenylhydrazone derivatives, which are eventually injected into a
gas chromatograph equipped with a flame ionization detector for separation
and identification.
9
-------
Phenols were measured using the ether extraction procedure.^ The first
step was to collect dilute exhaust in impingers containing aqueous potassium
hydroxide, at a rate of 1.02 m3/hr. The contents of the impingers are acidified
and extracted with ethyl ether, and are eventually injected into a gas chroma-
tograph equipped with a flame ionization detector.
Exhaust odor was evaluated using the A. D. Little "Diesel Odorant
Analytical System" (DOAS). The procedure used in this study was the same as
used in previous studies(5,10), and described in detail in the final report
on another study.dl) The vehicle was operated at 3 steady-state modes; idle,
50 kph, and 85 kph. Raw exhaust samples were taken for a specified time so
that the required amount of exhaust would pass through the Chromosorb 102
traps. TIA (total intensity of aroma) values are defined by either:
TIA = 1 + log (LCO, ug/ฃ)
or
TIA = 0.4 + 0.7 log, (LCA, yg/Ji) ,
whichever generates the highest value. "LCO" represents liquid column
oxygenates, and "LCA" represents liquid column aromatics.
C. Particulate Collection, Mass Rate, and Aerodynamic Sizing
Particulate collection for this project was performed using a 457 mm
(18 inch) diameter by 5m (16 feet) long dilution tunnel operating on total
vehicle exhaust. Other associated equipment includes probes, pumps, and
filter holders to withdraw and collect the particulate on filters, and a
balance to determine the mass of particulate collected.
The dilution tunnel is identical to that used in a previous study.(7)
A 114 mm (4.5 inch) probe was located at the downstream end of the tunnel.
This large probe was used to withdraw a dilute exhaust sample at a rate of
3.4 m3/min (120 SCFM) through a 500 x 500 mm (20 x 20 inch) Pallflex filter
(Pall Corporation). The dilution tunnel used is shown schematically in
Figure 1. Some of the equipment necessary for collecting particulate and
relating it to undiluted vehicle emissions is not shown in the schematic.
It includes a constant volume sampler (CVS) operating at a nominal capacity of
12.6 m3/min (450 CFM) to withdraw and measure unsampled air/exhaust mixture,
and the positive-displacement pump (capacity 3.4 m3/min) used for the 500 x 500 mm
filter system.
Particle sizing was accomplished using a radial-slot impactor. The
impactor system contained stainless steel stages on which particulate matter
was supposedly fractionated by size, and a final Pallflex backup filter.
The impactor was locatd at the downstream end of dilution tunnel. In operation,
each stage was placed on a plate such that the slots in each stage decreased
in width from sample entrance down to the filter. Each stage was rotated 45
degrees so the particulate matter passing through the slots impacted on a solid
portion of the following plate. Particle retention characteristics were
10
-------
610mm
(24in)
610mm
(24in)
4.88m (16ft)
840mm (33in)
450mm
(17.7in)
DILUTION AIR
FILTER ENCLOSURE
76mm (Sin) RAW
EXHAUST TRANSFER TUBE
230mm (Sin)
MIXING ORIFICE
TO CVS
114mm
(4-1/2in)DIA
r
700mm (27.5in)
SAMPLE
AIR+"
EXH,
r
4EA1/2inlD
SAMPLING PROBE
114mm
(4-1/2in)DIA
Figure 1. Schematic diagram of exhaust dilution tunnel.
500 x 500mm
(20in x 20in)
FILTER HOLDER
-------
related to the slot size and flowrate through the impactor. The flowrate was
controlled using a metal bellows vacuum pump, pressure gauge, and flowmeter.
The flowrate was maintained at 2.8 H/mฑn (0.1 CFM) to achieve particle sizing
down to 0.1 micrometer.
The mass of particulate matter collected on sample filters and impactor
discs was determined on a microbalance. This balance is enclosed in a
vibration-resistant, temperature- and humidity-controlled chamber to minimize
outside interferences. Filters and other materials for weighing were allowed
to stabilize in the chamber for a minimum of 12 hours before they were weighed.
The sensitivity of the balance is 1 yg. Air to the chamber flows at about
17 m3/hr on a one-pass basis, and keeps the chamber pressure at about 2.5 kPa
above atmospheric. The control system keeps chamber conditions at 22.2 ฑ
0.6ฐC and 63 ฑ 2 percent relative humidity, and air entering the chamber is
filtered through a 99.99 percent DOP-efficient filter.
D. Analysis of Particulate Composition
Particulate samples were acquired by several methods for various analyses.
After determining particulate matter weights, the samples were subjected to
analysis for major elements and trace elements. Some particulate samples
were collected in order to obtain the soluble fraction of particulate matter.
Analysis of the soluble fraction is discussed in the next section.
1. Trace Elements
Analysis for trace elements (metals and sulfur) in the particulate
matter was performed on 47 mm Fluoropore filter samples. As provided in the
contract agreement, these determinations were made at EPA's Research Triangle
Park laboratories as part of the EPA in-house measurement program. The in-
strumentation used for these analyses was a Siemens MRS-3 x-ray fluorescence
spectrometer.
2. Major Elements
Samples collected on 47 mm glass fiber filters were sent to Galbraith
Laboratories and analyzed for carbon and hydrogen content by combustion and
subsequent gas analysis. The equipment used was a Perkin-Elmer Model 240B
automated thermal conductivity CHN analyzer. Results of this analysis were
reported in percent of submitted mass and calculated weight of element detected
on the filter. These results make the filter weighing accuracy very important.
E. Analysis of the Soluble Fraction of Particulate Matter
The soluble fraction of particulate matter was obtained by extraction
from the 500 x 500 mm (20x20 inch) Pallflex filters. This large filter
enabled enough soluble material to be extracted so that the total amount could
be divided into smaller aliquots, then analyzed for a variety of constituents.
12
-------
1. Total Soluble Organics
The 500 x 500 mm filters were weighed before and after test to determine
the weight of particulate matter. Each filter was extracted using methylene
chloride in a Soxhlet apparatus. The solvent volume was reduced at low
temperature and under vacuum. The remaining solvent/solubles were transferred
to a preweighed container, and the solvent was evaporated by nitrogen purging.
The total mass of solubles was determined gravimetrically, and the percent
of solubles in the particulate matter calculated.
2. Major Elements
One aliquot of the dried, weighed soluble extract was submitted to
Galbraith Laboratories and analyzed for carbon, hydrogen, oxygen, and sulfur
by the technique and instrumentation described in Section IV, D.2 (Perkin-
Elmer 240B). An additional aliquot of soluble extract was submitted to SwRI's
U.S. Army Fuels and Lubricants Research Laboratory for nitrogen analysis by
oxidative pyrolysis and chemiluminescence.
3. Solubles Boiling Range and Individual n-Paraffin Analysis
Another aliquot of soluble extract was submitted to SwRI's U.S. Army
Fuels and Lubricants Research Laboratory for determination of the boiling
range and reference to normal paraffins. The procedure is a high-temperature
variation of ASTM D2887-73. Each aliquot was dissolved in carbon disulfide,
and an internal standard (Cg and C^i compounds) was added to quantitate
results. The maximum temperature that this column reached was 450ฐC, eluting
compounds boiling up to 650ฐC.
4. Benzo(a)pyrene (BaP) and Ames Bioassay
An additional 500 x 500 mm (20x20 inch) filter was extracted, and the
extract was divided into eleven aliquots. One aliquot was used to determine
the BaP content of the soluble extract. This analysis was performed by
SwRI's Department of Emissions Research. The procedure, developed by others
is based on high-performance liquid chromatography to separate BaP from other
organic solubles in particulate matter; and it incorporated fluorescence
detection to measure BaP. The instrument used was Perkin-Elmer 3B liquid
chromatograph equipped with a MPF-33 fluorescence spectrophotometer. Excita-
tion was at a wavelength of 383 nm, and emission was read at 430 nm. The
remaining ten aliquots were shipped on dry ice to EG&G for Ames bioassay
testing. The Ames test refers to a bacterial mutagenesis plate assay with
Salmonella typhimurium, according to the method of Ames.d3)
5. Fractionation by Relative Polarity
The composition of the organic soluble portion of the particulate
matter is complex, and its separation into individual compounds is very dif-
ficult. Fractionation of the solubles by high performance liquid chromato-
graphy (HPLC) separates the sample into a series of fractions of increasing
molecular polarity. This procedure is discussed in detail in a CRC report.
13
-------
Briefly, an organic solubles sample is initially carried in a solvent composed
of 95 percent hexane and 5 percent methylene chloride, a relatively non-polar
mixture. After a period of time, the ratio of methylene chloride to hexane,
and therefore solvent polarity, is increased to a rate of 5 percent methylene
chloride per minute. At 100 percent methylene chloride, the carrier solvent
is moderately polar. A fluorescence detector is used at an excitation wave-
length of 330 nm and an emission wavelength of 418 nm. A UV detector is
used at wavelength of 254 nm. At these wavelengths fluorescence and UV
responses of compounds are mapped as a function of column elution time,
reflecting polarity.
14
-------
V. TEST PLANS AND OPERATING SCHEDULE
The following section describes the vehicle operating schedules, exhaust
analysis test plan, Quality Assurance Project Plan, and statistical analysis
test plan. A summary of the exhaust constituents evaluated is given in
Table 4. Discussion of the analytical techniques is presented in Section
IV of this report.
A. Vehicle Test Plan
The vehicle followed two transient cycles, FTP and HFET, during most
sample collection and measurement runs. These cycles are routinely used in
emission testing and are well documented in other works.(1*3,6,10) Smoke
evaluation was performed separately during the cold transient portion of the
FTP (first 505 seconds). The cold transient portion incorporates all of the
most interesting modes from a smoke standpoint, including cold engine start,
first idle, first acceleration, second idle, and second acceleration. Steady-
state modes at idle, 50 kph, and 85 kph were used to obtain raw exhaust
samples for odor analysis. Vehicle running time on the steady-state modes
was governed by the sample volume requirements of the odor measurement pro-
cedure (DOAS).
The test plan incorporating the cycles and evaluations for each test
fuel is given in Table 5. Samples taken over each 2-bag FTP were defined as
a "cold FTP" or a "hot FTP." Testing for each fuel required a minimum of
three days. After the first day of testing, as many of the results as
possible were reviewed to determine whether or not replicate analysis would
be required on the second day of testing. It was important to determine the
validity of the tests as early as possible, to avoid costly reruns and de-
pletion of limited test fuel quantities by repurging the fuel system.
Procedure for fuel system purging between test fuels is discussed in Section
IV. Duplicate filter samples were collected on Day 2, and retained for
possible replicate analyses. In some cases, samples were stored in their
most stable form, then submitted for analysis as a group (rather than in-
dividually) to minimize the effects of day-to-day variability in an analytical
procedure.
B. Quality Assurance Project Plan
A Quality Assurance Project Plan was prepared following EPA QAMS-005/80,
entitled, "Guidelines and Specifications for Preparing Quality Assurance
Project Plans," December, 1980. This project plan(15) was forwarded to the
EPA in June 1982, prior to initiation of technical efforts.
A substantial portion of the program expenditures was made to prepare
the Quality Assurance Project Plan. Costs for this effort were not originally
included in the Work Plan. Therefore, some technical efforts originally
planned were reduced to compensate for the Quality Assurance Project Plan
efforts.
15
-------
TABLE 4. OUTLINE OF CHEMICAL AND PHYSICAL EXHAUST EVALUATIONS
Exhaust Component
under Study
Constituent(s) analyzed for
Collection
Method
Analysis technique(s)
Smoke
smoke (visible
EPA smokemeter (continuous)
gases
HC, CO, CO2, NOX
aldehydes
odor
phenols
sample bag
wet impinger
DOAS traps
wet impinger
constant volume sampler
DNPH
DOAS sampler
extraction, GC
particulate
total mass
size distribution
sulfur & trace elements
carbon, hydrogen in
particulate
organic extractable substances
BaP in organic solubles
molecular weight range of
organic solubles
carbon, hydrogen in solubles
biological response of
solubles
polarity profile of solubles
Pallflex filters
impactor-filter
filter, 47 mm
Fluoropore
filter, 47 mm
glass fiber
"20x20" filter
gravimetric
gravimetric
x-ray fluorescence
combustion (commercial)
soxhlet extraction
LC, fluorescence detection
GC
combustion (commercial)
Ames bioassay
HPLC
-------
TABLE 5. TEST PLAN FOR EACH FUEL
Analysis or Sample
gaseous HC, CO, NOX, CO2
sulfur & trace elements
particle size distribution
organic extractables
total particulate mass
C & H in particulate
odor
aldehydes
phenols
BaP and Ames bioassay
smoke
Day 1
Cold FTP
X
X
X
X
X
-
-
-
-
-
Hot FTP
C
X
X
X
X
X
-
-
-
-
-
HFET
X
X
X
X
X
-
-
-
-
-
Day 2
Cold FTP
X
-
X
-
-
X
X
X
-
Hot FTP
X
-
X
-
-
X
X
X
-
HFET
X
-
X
-
-
X
X
-
-
Idle
X
-
X
-
X
-
-
-
-
50 kph
X
-
X
-
X
-
-
-
-
85 kph
X
-
X
-
X
-
-
-
-
Day 3
cold transient
(505 seconds)
-
-
-
-
-
-
-
-
X
Repeat samples optional
One sample collected for entire 4-bag FTP
COrganic extractables divided into aliquots for HPLC, carbon & hydrogen, and boiling range
analysis
-------
C. Statistical Anaylsis Test Plan
The principal objective of this study was to determine the degree to
which alternate-source fuels affect exhaust emissions as compared to petroleum
fuels. Several statistical approaches were available to meet this objective.
Attempts were made to strengthen the statistical arguments while minimizing
the number of assumptions and maximizing the applicability of the conclusions.
It was not within the scope of the project to perform a detailed statistical
analysis. However, the data were collected and treated in such a way that
future efforts could continue with such analysis.
A literature search was conducted to obtain studies dealing with petroleum
fuel property effects on exhaust emissions. Due to the wide variety of vehicles,
fuels, test cycles, and measurement techniques used in previous studies, a
method to relate all these studies in terms of general trends was developed.
The data from all studies, on both petroleum and alternate-source fuels, were
normalized to a selected fuel property level. Regression analysis was per-
formed on each study's normalized data to yield linear equations for each
selected (fuel property-exhaust emission) data pair. Analysis of the
resulting line plots yielded general observations of trends for petroleum
fuels versus alternate-source fuels. Bivariate correlation coefficients
for each selected fuel property-exhaust emission data pair were also deter-
mined on each study. Goodness-of-fit was calculated by inserting the alternate-
source fuel properties into the petroleum fuel exhaust emission prediction
equations. These goodness-of-fit results were used to determine whether
or not emission effects observed with property variation in petroleum fuels
and alternate-source fuels differed statistically.
18
-------
VI. GASEOUS AND PARTICULATE EMISSION RESULTS
This report section includes results and discussion on regulated gaseous
emissions, aldehydes, phenols, exhaust odor, visible smoke, total particulate
mass emissions, particle size distribution, and particulate matter elemental
analysis. In addition, it includes information on organic solubles in parti-
culate matter, elemental analysis of the solubles, BaP in solubles, boiling
range of organic solubles by gas chromatograph analysis, polarity profile of
the solubles, and bioassay analysis. Confidence limits could not be calcu-
lated due to an insufficient number of data points. Emission repeatability
was good, with replicate results on the same fuel deviating five percent or
less from the results of the first run. Exhaust emission results from the
alternate-source fuels tested in the earlier study(7) are not reiterated in
this section. Some of those results are presented with the data from
petroleum fuel studies in Section VII.
A. Regulated Gaseous and Particulate Emission Results
Data on regulated gaseous emissions, including CO2 and fuel consumption,
were obtained by analysis of bag samples collected from the CVS-diluted
exhaust. Particulate results were obtained concurrently by filtration of
diluted exhaust. These results are summarized in Tables 6 and 7. They are
reported for each individual bag, a calculated 3-bag FTP, and a calculated
4-bag FTP. The computer printouts for all the tests are located in Appendix
C, pages C-2 through C-15.
TABLE 6. AVERAGE REGULATED GASEOUS EMISSIONS DATA
Fuel
Base
EM-329-F
SASOL
EM-527-F
25%
H-Coal
EM-526-F
Item
HC
CO
C0?
NOX
Fuel
HC
CO
C02
NOX
Fuel
HC
CO
C02
NOX
Fuel
Emissions (g/km) a
FTP Bag Number
1
0.40
1.23
179.
0.67
6.94
0.51
1.43
174.
0.64
7.05
0.50
1.33
184.
0.72
6.88
2
0.26
0.82
164.
0.67
6.33
0.21
0.88
156.
0.65
6.24
0.31
0.97
164.
0.72
6.07
3
0.33
1.03
156.
0.64
5.95
0.39
1.21
150.
0.62
6.05
0.35
0.97
158.
0.70
5.89
4
0.25
0.80
163.
0.66
6.32
0.18
0.82
152.
0.66
6.08
0.22
1.06
160.
0.71
5.91
nd Fuel Usage (5./100 km) by Driving Schedule
(Calculated)
3-bag FTP
0.31
0.96
165.
0.66
6.37
0.32
1.08
158.
0.64
6.35
0.36
1.12
166.
0.71
6.18
(Calculated)
4-bag FTP
0.31
0.95
165.
0.66
6.36
0.31
1.07
157.
0.64
6.30
0.33
1.15
165.
0.71
6.14
HFET
0.35
1.04
133.
0.61
5.17
0.23
1.25
132.
0.60
5.35
0.39
1.28
143.
0.74
5.34
Steady-State
Idle3
2.13
9.30
1136.
5.78
0.44
1.56
7.95
1125.
5.52
0.45
10.74
24.69
1067.
5.31
0.42
50 kph
0.17
0.54
124.
0.53
4.77
0.14
0.54
116.
0.52
4.66
0.38
0.79
119.
0.53
4.42
85 kph
0. 39
1.20
134.
0.67
5.22
0.24
1.38
129.
0.60
5.24
0.35
1.12
143.
0.73
5.33
Emission in g/h instead of g/km, fuel in i/h instead of Si/100 km
The SASOL middle distillate fuel yielded gaseous and particulate
emission results similar to the base fuel, EM-329-F, during the FTP. Fuel
consumption was also unaffected. During the HFET, the SASOL fuel was
19
-------
TABLE 7. AVERAGE PARTICULATE MASS EMISSIONS DATA
Fuel Code
EM- 329 -F
EM-527-F
EM-526-F
Fuel Type
Base DF-2
SASOL
25% H-Coal
Grains Particulate per Kilometer
Calculated
1981 FTP
0.25
0.23
0.28
HFET
0.25
0.25
0.33
Steady-State
Idlea
0.71
0.42
1.11
50 kph
0.17
0.14
0.18
85 kph
0.28
0.27
0.31
Emissions in g/h instead of g/km
associated with a 34 percent reduction in HC, but a 20 percent increase in
CO. A slight increase in fuel consumption was observed during the HFET.
NOX and particulate were essentially unaffected. The steady-state driving
modes indicated that the SASOL fuel was generally associated with the same
or slightly lower emission levels as compared to the base fuel. During the
idle condition, particulate emissions with the SASOL fuel were about 41 percent
lower.
Results with the H-Coal fuel blend, EM-526-F, indicated general increases
in emissions and slight decreases in fuel consumption over both the transient
cycles and all steady-states, as compared to the base fuel. The previous
study(7) indicated similar results while testing a 25 percent EDS fuel blend.
The EDS (Exxon Donor Solvent) material is a "first generation" coal-derived
liquid produced by a process somewhat similar to the H-Coal process. Therefore,
these results are not unexpected.
Of some interest is that data from the previous study^7^ and this one
have both shown that the "first generation" coal-derived materials tend to
increase emissions. It was speculated in the earlier report that "second
generation" materials would yield lower emissions than their "first generation"
counterparts. The SASOL material, although not extracted from coal in the same
way as the other coal liquids investigated, is an upgraded or "second generation"
coal-derived fuel. This "second generation" material was associated with
emissions similar to the base fuel. In the previous study, the upgraded
shale oil liquids tested also yielded results similar to the base fuel. It
is probable that further treatment of "first generation" coal-derived liquids'
by hydrogenation and catalytic cracking would result in "second generation"
liquids which might not affect exhaust emissions adversely. This projection
depends strongly on the degree of hydrotreatment used, and the desired quality
of the end product.
B. Aldehyde and Phenol Results
Concentrations of several individual low-molecular weight aldehydes
were determined in CVS-diluted exhaust. The results for each aldehyde species
20
-------
and their sums during the FTP are presented in Table 8. "Total" aldehydes
refers to the sum of the individual aldehydes determined using the procedure
discussed in Section IV. Table 9 represents the phenol results for the fuels
tested. HFET results for both aldehydes and phenols are presented in Table
10. Aldehyde and phenol emissions for both alternate-source fuels were lower
than those observed for the base fuel, regardless of driving cycle. These
results were unexpected, and investigation into the analyses did not un-
cover any errors.
C. Results of Odor Analysis
This subsection contains results from instrumental odor evaluations
(DOAS). The chromatographic procedure separates an oxygenate fraction
(liquid column oxygenates, LCD) and an aromatic fraction (liquid column
aromatics, LCA). Studies(Hป16) have been made in an attempt to correlate
instrumental analysis to a panel of trained human evaluators. One study1
indicated that TIA (LCO-based) of less than 1.0 would be rated by a trained
panel at less than "D"-l. A perceived odor intensity of "D"-l by the Turk
method is considered a light (barely perceptible) odor. It should be noted
that since the TIA (total intensity of aroma) is calculated using a logarithmic
equation, each increase of one unit in the TIA value relates to a concentration
increase by a factor of ten.
Results of the odorant analysis are listed in Table 11. The TIA
values (LCO-based) indicate that the SASOL fuel exhibited lower exhaust
odorant levels than the base fuel. The 25 percent H-Coal blend, EM-526-F,
was associated with higher exhaust odorant levels during the idle and 50 kph
steady-state, but lower levels during the 85 kph steady-state condition.
Similar results were reported in the earlier study(7) with the 25 percent
EDS blend. In that study, the shale diesel marine resulted in lower odor
levels than the base fuel.
D. Visible Smoke Emissions
Visible smoke was measured using an EPA-type smokemeter over the first
505 seconds (the "cold transient phase") of the FTP. Data taken on a 2-pen
strip chart recorder consisted of vehicle speed and smoke opacity versus
time. The traces, which were analyzed manually, are located in Appendix C,
pages C-16 and C-17. The results, along with previously-run base fuel
results, are summarized in Table 12.
These data show a marked increase of smoke during vehicle operation with
the 25 percent H-Coal blend. Similar results were previously reported in the
earlier study(7> with other coal-derived liquids. The SASOL fuel followed
the trends reported with use of the Shale Diesel Marine fuel. During the
cold-start and first acceleration, both fuels were associated with high
smoke opacities as compared to the base fuel. During the second acceler-
tion at 164 seconds, both fuels yielded lower smoke levels compared to the
base fuel. Apparently, the Shale Diesel Marine and the SASOL combustion
characteristics improve after vehicle warmup.
21
-------
TABLE 8. FTP ALDEHYDE EMISSIONS DATA
Operating
Schedule
Cold FTP
Hot FTP
Calculated
1981 FTP
Compound (s)
Formaldehyde
Acetaldehyde
Acetone3
Hexanaldehyde
Benzaldehyde
"Total"
Formaldehyde
Acetaldehyde
Acetone3
Hexanaldehyde
Benzaldehyde
"Total"
Formaldehyde
Acetaldehyde
Acetone3
Hexanaldehyde
Benzaldehyde
"Total"
Concentration (mq/km) by Fuel Tested
Base
EM-329-F
7.
2.
2.
0.0
0.0
11.
10.
2.
3.
0.0
0.0
15.
9.
2.
3.
0.0
0.0
14.
SASOL
EM-527-F
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.
4.
0.0
0.0
0.0
0.0
2.
2.
25% H-Coal
Ell- 5 26 -F
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Includes acrolein and proponol
TABLE 9. FTP PHENOL EMISSIONS DATA
Operating
Schedule
Cold FTP
Hot FTP
Calculated
1981 FTP
Compound(s)
Phenol
Salicylaldehyde
m-Cresol + p-Cresol
Group 5a
2, 3,5-trimethylphenol
2,3,5, 6-tetramethylphenol
2-n-propylphenol
"Total"
Phenol
Salicylaldehyde
m-Cresol + p-Cresol
Group 5a
2,3, 5-trimethylphenol
2,3,5 , 6-tetramethylphenol
2-n-propylphenol
"Total"
Phenol
Salicylaldehyde
m-Cresol + p-Cresol
Group 5a
2 , 3,5-trimethylphenol
2,3,5, 6-tetramethylphenol
2-n-propylphenol
"Total"
Concentration (mq/km) bv Fuel Tested
Base
EM-329-F
0.0
0.0
1.
4.
0.4
0.3
7.
13.
0.0
0.0
0.1
2.
0.1
0.2
8.
10.
0.0
0.0
0.7
3.
0.3
0.3
8.
12.
SASOL
EM-527-F
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25% H-Coal
EM-526-F
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Group 5 consists of p-ethylphenol, 2-isopropylphenol,
3,5-xylenol, 2,4,6-trimethylphenol
22
2,3-xylenol,
-------
TABLE 10. HFET PHENOL AND ALDEHYDE EMISSIONS DATA
Fuel Type
Fuel Code
Phenols
Phenol
Salicylaldehyde
m-Cresol + p-Cresol
Group 5a
2, 3,5-trimethylphenol
2, 3, 5, 6-tetramethy Iphenol
2-n-propy Iphenol
"Total"
Aldehydes
Formaldehyde
Acetaldehyde
Acetone'3
Hexanaldehyde
Benzaldehyde
"Total"
Concentration (mg/km) by Fuel Tested
Base
EM-329-F
0.0
0.0
1.
2.
0.03
0.6
4.
7.
9.
1.
5.
0.0
0.0
15.
SASOL
EM-527-F
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.
0.0
0.0
0.0
0.4
1.
25% H-Coal
EM-526-F
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Group 5 consists of p-ethyIphenol, 2-isopropyIphenol, 2,3-xylenol,
3,5-xylenol, 2,4,6-trimethyphenol
Includes acrolein and propanol
TABLE 11. RESULTS OF ODOR ANALYSIS AT STEADY STATES
Date
12/12/80
11/9/82
11/12/82
Fuel Code
EM-329-F
EM-527-F
EM-526-F
Fuel Type
Base DF-2
SASOL
25% H-Coal
Condition
Idle
50 kph
85 kph
Idle
50 kph
85 kph
Idle
50 kph
85 kph
LCA, Ug/S,
55.
110.
400.
7.4
30.
28.
47.
41.
81.
LCO, Ug/S,
3.7
7.5
21.
1.5
1.4
4.8
5.9
17.
7.3
TIA
LCA
1.6
1.8
2.2
1.0
1.4
1.4
1.6
1.5
1.7
LCO
1.6
1.9
2.3
1.2
1.1
1.7
1.8
2.2
1.9
TABLE 12. SUMMARY OF VISIBLE SMOKE DATA
Condition
Cold Start Peak
Cold Idle, avg.
(after start)
1st Accel. Peak
Idle at 125 sees. ,
Avg.
Accel, at 164 sees..
Peak
Smoke Opacity, %, by Fuel
329
21.2
0.2
28.2
0.7
37.5
527
54.0
0.7
39.0
0.1
24.5
526
61.0
0.5
54.5
0.5
56.2
23
-------
E. Particulate Size Distribution
Data from impactor runs were analyzed, and are presented as percentage
of the total particulate mass by stage in Table 13. These data show that,
as observed earlier(7) , over half the particulate mass was composed of
particles smaller than 0.2 ym. In the case of the SASOL fuel, almost 75
percent of the particulate mass was under 0.2 ym.
TABLE 13. PARTICULATE SIZE DISTRIBUTION
Run
No.
1
2
1
1
Fuel Code
EM-329-F
EM-329-F
EM-527-F
EM-526-F
Fuel
Description
Base DF-2
Base DF-2
SASOL
25% H-Coal
Stage 3
9.5 Uma
4.9
6.8
5.8
2.5
Stage 4
5.8 yma
2.7
6.3
2.3
3.8
Percent of Total Particulate
Stage 5
3.7 yma
6.3
2.0
1.4
3.9
Stage 6
2.1 Uma
4.4
2.3
5.9
6.8
Stage 7
1.2 yma
8.2
5.7
2.3
4.8
Stage 8
0.8 yma
5.0
2.3
3.2
3.2
Stage 9
0.5 l_ima
6.1
2.7
3.2
5.1
Stage 10
0.2 uma
7.9
6.7
1.3
5.2
Filter
55.
65.
74.
65.
Vehicle
Total
Particulate
g/cyclea
5.81
6.05
5.13
7.21
Based on 47 mm Pallflex for 4-bag FTP
F. Analysis of Particulate Composition
This subsection includes data on major elements and trace elements.
Carbon and hydrogen analyses were performed on particulate collected using
47 mm glass fiber filters. Particulate collected on 47 mm Fluoropore filters
was analyzed for trace elements.
Carbon and hydrogen data are listed in Table 14. As seen in earlier
studies(3/7)^ the data show fairly high carbon and low hydrogen content,
indicative of "dry" or soot-like particulate material. The analyses on the
SASOL and 25 percent H-Coal blend were performed approximately a year later
TABLE 14. CARBON AND HYDROGEN IN EXHAUST PARTICULATE MATTER
Fuel
Code
EM-329-F
EM-527-F
EH-526-F
Fuel Description
Base DF-2
SASOL
25% H-Coal
Cycle
FTPC
FTPh
HFET
FTPC
FTPh
HFET
FTPC
FTPh
HFET
Weight Percent
Carbon
81.6
80.3
83.6
92.8
93.1
91.4
91.1
92.5
84.0
Hydrogen
2.8
2.7
2.9
2.7
3.1
2.9
3.0
3.1
2.6
24
-------
than those reported in the earlier study.> Results from both studies do
not indicate any trends. As stated in other studies (3,6,7)f the technique
used to analyze carbon and hydrogen content of particulate collected on
glass fiber filters appears somewhat questionable. A new procedure is needed
to insure correct and accurate analysis of particulate collected on glass
fiber filters.
Date on trace elements are given in Table 15. As a whole, these
elements made up 0.3 to 2.1 percent of the particulate mass. The trace
TABLE 15. PERCENT TRACE ELEMENTS IN PARTICULATE MATTER
Elements
Mg
Al
Si
P
S
Cl
Ca
Ti
Fe
Zn
Sn
Ba
Cr
Pb
Mn
Br
Cd
K
Cu
Ni
V
Sb
Mo
Total Percentage
of Particulate
Weight Percentage of Particulate Matter by Fuel and Cycle
EM-329-F Base
FTPC
0.018
0.025
0.048
0.039
0.741
0.003
0.082
0.005
0.388
0.051
0.008
0.004
0.000
0.000
0.000
0.000
0
0.009
0
0.096
0.000
0.000
0
1.517
FTPh
0.011
0.009
0.022
0.029
0.427
0.005
0.035
0.000
0.145
0.040
0.003
0.000
0.008
0.000
0.000
0.017
0
0.003
0
0.016
0.000
0.000
0
0.770
FET
0.004
0.003
0.005
0.009
0.254
0.001
0.007
0.001
0.029
0.009
0.000
0.000
0.000
0.000
0.000
0.000
0
0.001
0
0.005
0.001
0.000
0
0.329
EM-527-F SASOL
FTPC
0.016
0.012
0.006
0.017
0.176
0.003
0.020
0.000
0.448
0.029
0.000
0.002
0.020
0.088
0.006
0.044
0
0.000
0
0.092
0.008
0.000
0
1.410
FTPh
0.007
0.005
0.000
0.008
0.051
0.000
0.013
0.000
0.154
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0
0.000
0
0.000
0.000
0.000
0
0.643
FET
0.013
0.005
0.000
0.014
0.071
0.006
0.012
0.000
0.150
0.032
0.000
0.000
0.000
0.000
0.000
0.000
0
0.000
0
0.020
0.008
0.000
0
1.012
EM-526-F 25% H-Coal
FTPC
0.016
0.014
0.015
0.038
0.727
0.000
0.028
0.003
0.688
0.051
0.000
0.000
0.000
0.000
0.000
0.000
0
0.000
0
0.058
0.000
0.000
0
2.152
FTPh
0.013
0.004
0.007
0.023
0.527
0.000
0.016
0.003
0.387
0.033
0.000
0.000
0.000
0.000
0.000
0.000
0
0.000
0
0.019
0.008
0.000
0
1.557
HFET
0.010
0.005
0.000
0.033
0.849
0.000
0.015
0.003
0.437
0.051
0.002
0.000
0.000
0.000
0.000
0.000
0
0.000
0
0.021
0.006
0.000
0
1.838
elements found most commonly in the particulate matter were sulfur, iron,
nickel, calcium, and zinc. Possible sources of iron and nickel are wear
products from the engine and exhaust system. Suflur, calcium, and zinc
can probably be attributed to fuel sulfur and lubricating oil additives.
Of some interest was the presence of a measureable amount of lead when the
SASOL fuel was used during the cold-start FTP. The earlier study^7) reported
lead only with the 25 percent SRC-II blend (a non-upgraded coal-derived
liquid).
G. Composition of Organic Solubles in Particulate Hatter
The organic soluble portion of the particulate was obtained from parti-
culate samples collected on 20x20 inch Pallflex filters, using a Soxhlet
25
-------
extraction procedure (methylene chloride as solvent). A portion of the
organic soluble material was analyzed for carbon and hydrogen. The results
are given in Table 16. All of the elemental data for the FTP are indicative
of hydrocarbon-like materials (numeric H/C ratio approximately 1.80). The
TABLE 16. COMPOSITION OF THE ORGANIC SOLUBLE PORTION OF THE PARTICULATE
Fuel
Code
EM-329-F
EM-527-F
EM-526-F
Fuel Description
Base DF - 2
SASOL
25% H-Coal
Cyclea
FTP
HFET
FTP
HFET
FTP
HFET
Weight Percent
Carbon
85.2
85.5
84.3
80.9
82.8
81.9
Hydrogen
12.9
12.9
12.0
7.7
11.0
8.2
"4-bag" FTP's
SASOL and 25 percent H-Coal solubles yielded a numeric H/C ratio of about
1.5 during the HFET. This ratio is somewhat lower than reported in other
studies.(3,6,7) since extractions are performed with a relatively non-polar
solvent (methylene chloride), the material extracted should be hydrocarbon-
like. A pure hydrocarbon yielding a numeric H/C ratio of 1.15 would be made
up of approximately 91 percent carbon and 9 percent hydrogen,with an emperical
formula similar to benzene. The sum of carbon and hydrogen for the HFET's
is approximately 88 percent. The remaining 12 percent could be speculated
to be oxygen, but the aldehydes, phenols, and the analysis of the total
particulate do not support this speculation.
H. Gas Chromatograph "Boiling Range" Analysis of Organic Solubles
The organic soluble portion of particulate matter resembles a very
heavy oil or a varnish. A high-temperature GC-simulated boiling point
distribution, with an internal standard, was run on organic soluble material
from particulate generated with each fuel. Table 17 summarizes the results
for samples generated during both the FTP and HFET. The chromatograms for
all of the samples summarized in Table 17 are located in Appendix C, Figures
C-3 through C-6.
Both FTP and HFET results show that solubles from tests on the SASOL
and 25 percent H-Coal test fuels show slightly lower boiling ranges as
compared to the base fuel. The SASOL fuel gave a boiling range similar to
that observed with the Broadcut fuel tested in the earlier study.(7)
26
-------
TABLE 17. CHROMATOGRAPH ANALYSIS OF ORGANIC SOLUBLES IN PARTICULATE MATTER
Fuel Description
Fuel Code
IBP
10% point
20% point
30% point
40% point
50% point
60% point
70% point
80% point
90% point
Er
% Recovery @ 640ฐC
Fuel Code
IBP
10% point
20% point
30% point
40% point
50% point
60% point
70% point
80% point
90% point
EP
%Recovery @ 640 ฐC
Boiling Temperature, ฐC, at Distillation Point
by Fuel during 4-Baq FTP
Base DF-2
EM-329-F
318
365
388
416
451
494
537
605
_
_
-
70.0
SASOL
EM-527-F
253
342
377
406
428
452
479
512
564
_
-
83.8
25% H-Coal
EM-526-F
269
337
353
395
420
449
482
522
603
_
-
79.6
Boiling Temperature, ฐC, at Distillation Point
by Fuel during HFET
EM-329-F
325
374
400
429
462
492
526
582
-
-
-
71.7
EM-527-F
278
353
396
418
438
460
482
510
555
-
-
84.5
EM-526-F
262
341
376
410
437
464
493
530
603
_
-
80.3
I. Fraction by Relative Polarity
Composition of the soluble organic fraction of the particulate is com-
plex, and its separation into individual compounds is very difficult.
Fractionation of the organic solubles by high performance liquid chromato-
graphy (HPLC) separates the soluble portion into a series of fractions of
increasing molecular polarity. This procedure^ ' is not quantitative, but
provides a method to collect fractions with generally different polarities.
All samples were analyzed at the same ratio of organic extract and carrier
solvent. Therefore, the results can be compared to one another on a relative
basis to estimate increases or decreases of compound classes which differ from
each other by molecular polarity. Figures 2 through 5 show the HPLC chromato-
graphic outputs for direct comparison of the relative response of increasingly
polar compounds at the wavelengths discussed in Section IV, Part E-5 of the
report.
Each figure contains three traces, one representing the carrier solvent
composition, a second representing the ultraviolet detector response, and the
27
-------
_: l-i-slr *-:':'-
70
60
50
40 30
Time,minutes
Figure 2. HPLC response to BaP and 9-fluorenone
tE ULTRAVIOLET
= EE FLUORESCENCE -
50 40 30 20
Time, minutes
Figure 3. HPLC response to extract generated from base DF-2
28
10
-------
ฃj SOLVENT V -^t-.-^"!:- t-
^ POLARITY V:-<';rJ,""7:J!'vff
-i^. x_X_.::: i '
f"."---..: r FLUORESCENCE . ฃ H ! ' :
40 40
Time, minutes
Figure 4. HPLC response to extract generated from SASOL middle distillate
SOLVENT
POLARITY
ULTRAVIOLET rlri..:H.-:-n"tn
- FLUORESCENCE ill! ii'Lll'-Ll
70
60
50
40 30
Time, minutes
20
10
Figure 5. HPLC response to extract generated from 25% H-Coal
29
-------
third representing the fluorescence detector response. Figure 2 shows the
response of BaP and 9-fluorenone. BaP and similar compounds elute in this
non-polar region. Near the end of the transition period (i.e., solvent
polarity now polar), 9-fluorenone elutes. With 100 percent methylene chloride,
even more polar compounds elute. For example, acridine elutes during this
polar period (at about 70 minutes).
A CRC study^ ' indicated that compounds which fluoresce in the tran-
sition fraction (at 20 to 30 minutes elution time, a fraction of intermediate
polarity) yielded the highest Ames response (i.e., mutagenic activity).
During this period, 20.9 percent of the Ames activity was associated with
2.5 weight percent of the organic soluble material. The greatest fluorescence
response in this fraction (20 to 30 minutes elution time) was associated with
the SASOL fuel. In the earlier study(7), the Paraho JP-5 (a shale oil fuel)
yielded the highest fluorescence response. The H-Coal response was similar
to the SRC-II blend reported earlier.(7) In summary, based on the results of
the aforementioned CRC data and this study's fluorescence data, increases
in Ames activity as compared to the base fuel might be projected for both
the SASOL and the 25 percent H-Coal blend.
J. Benzo(a)pyrene (BaP) in Organic Solubles
BaP results are presented in Table 18 along with percentage of organic
solubles in particulate matter. The BaP present in the organic soluble
portion of the particulate for the fuels tested is substantially higher
TABLE 18.
BaP PRESENT IN ORGANIC SOLUBLES DURING FTPQ + FTPh
Fuel Code
EM-329-F
EM-527-F
EM-526-F
Fuel
Description
Base DF-2
SASOL
25% H-Coal
Filter No.
P20-82,83
P20-9,10
P20-18,19
Particulate
g/kma
0.25
0.23
0.28
Percentage
Extractables
14.6
15.3
16.9
% BaP
in Extract
0.042
0.057
0.039
BaP
yg/km
14.9
19.6
19.0
based on 47 mm Pallflex
(about a factor of 10) than that found in other studies. (3'5'17) These
results are consistent with those observed in the earlier study^ ' using
the same vehicle.
The BaP emissions for both the SASOL and 25 percent H-Coal blend were
about 30 percent higher than those observed with base fuel. BaP emissions
for most of the other alternate-source fuels tested earlier^7^ were generally
twice to three times the baseline levels.
30
-------
K. Mutagenic Activity by Ames Testing
An additional amount of organic solubles representing each fuel tested
was reserved for Ames bioassay analysis. The Ames test refers to a bacterial
mutagenesis plate assay with Salmonella typhimurium according to the method
of Ames.(**) The original test plan called for the Ames analysis to be
performed by an outside laboratory under a separate EPA contract. Funding
for this analysis was not included under Contract 68-03-3073, so it can not
be performed at this time. It is anticipated that a new contract will be
issued to complete these analyses, but it has not yet been finalized at this
writing.
31
-------
VII. STATISTICAL ANALYSIS OF FUEL AND EMISSIONS DATA
This report section discusses the application of several statistical
computer programs to fuel and emissions variables. The principal goal was
to determine, in a broad sense, the degree to which variation in alternate-
source fuels affects exhaust emissions as compared to variation in petroleum
fuels.
A. Statistical Methodology
Several approaches were developed to analyze data taken in the study
and the data available in the literature. Alternate-source data from an
earlier EPA study(7)f this study, data available in previous EPA fuel variables
work, and published literature were normalized to evaluate whether or not
changes in emissions are affected by the source of the fuel (coal, shale,
petroleum, etc.).
Originally, the prediction equations developed under EPA Contract
68-03-2707(3) were to be used in conjunction with the properties of the
alternate-source fuels to yield predicted emissions, as if the alternate-
source fuels were petroleum fuels. This study(3) used a Mercedes Benz 240D
to evaluate petroleum fuel variation effects on exhaust emissions. The data
from that study were subjected to multiple linear regression analysis to yield
exhaust emission prediction equations as functions of fuel properties.
Requests to insert alternate-source fuel properties into petroleum
fuel regression equations developed under Contract No. 68-03-2707 could not
be answered straightforwardly without several critical assumptions. Due to
the test designs of the two studies, they are essentially unrelated to each
other because of vehicle differences (VW vs. Mercedes). Normalization of
the Mercedes prediction equations would have involved a third study, in which
both a Mercedes and a Volkswagen Rabbit were tested on the same fuels. This
third study could have been used to determine the relationship between the
two vehicles by determining a vehicle response factor, or equation which,
when applied to Mercedes petroleum fuel prediction equations, would have
resulted in petroleum fuel prediction equations for the VW. Insertion of
alternate-source fuel properties into the VW equations would have yielded
predicted emissions as if the fuels were petroleum-based. Comparison
between these predicted values and the actual observed values using alternate-
source fuels would have been used to determine if alternate-source fuel
property variations were responsible for greater, lesser, or similar
changes in emissions as compared to petroleum fuel property variations.
Determination of a vehicle response factor would have been difficult.
In order to minimize the cumulative errors that would have occurred, the stuty
conducted should have contained as many similarities as possible in terms of
engine size, inertia settings, sample acquisition, analytical techniques, etc.,
to both the study which developed the Mercedes prediction equations and this
current study. One study, performed at SwRI under Contract No. 68-03-2440^),
incorporated the identical Mercedes 240D used to develop prediction equations.
The VW used in Contract No. 68-03-2440 was a different vehicle model year,
33
-------
although the engine displacement/ inertia, horsepower setting, and transmission
shift points were identical. Comparison of FTP emissions from the two VW
Rabbits, both operated on "National Average" No. 2 diesel fuel (but different
lots), showed that the vehicles did not respond similarly. If an assumption
were made that the response difference was due to different diesel fuel lots,
and that both VW's would respond identically if the exact same fuel were used,
then the VW used in Contract No. 68-03-2440 could be used to determine a
relationship between the Mercedes (petroleum-based prediction equation study)
and the VW used in the alternate-source study.
Several other more critical assumptions would have been necessary. A
vehicle response factor for each emission concerned would have been developed.
The study under Contract No. 68-03-2440 did not result in prediction equations
for most of the emissions with which we are concerned. At a minimum, the data
in Contract No. 68-03-2440 would have been utilized again to establish some
relationship between fuel properties and exhaust emissions for the Mercedes
and VW Rabbit. If the relationships yielded equations containing the same
fuel properties as variables, high R-squares, and low standard deviations,
then the two vehicles could have been linked by some factor. If the resulting
regression equations for the two vehicles were parallel, then a single vehicle
response factor would have resulted. If the regression equations yielded
non-parallel lines, then the vehicle response factor itself would have been
in the form of another equation. Without this exercise to determine regression
equations, a vehicle response factor for a particular point (i.e., one fuel
property value) would have resulted. This resulting factor would have only
been applicable to one point of the alternate-source fuel data, and general
trends could not have been determined. Even if regression equations for both
vehicles could have been determined, any error associated with each equation
would have been cumulative, and would have eventually affected the final
calculated VW prediction equations.
Assuming success to this point, two approaches existed. First, the
vehicle response factor would have been applied to the Mercedes prediction
equations determined in Contract No. 68-03-2707 to yield VW prediction
equations. The accuracy of the Mercedes equations themselves would have to
be verified first. Brief evaluation of the Mercedes prediction equations
had shown poor prediction capabilities, however, due to a lack of population
dispersion for fuels in that study. (*>) Using these equations would have
introduced additional error. The second approach involved using the pre-
diction equations generated from the Mercedes/VW study (Contract No.
68-03-2440) ^, assuming that prediction equations were obtainable and that
the 1977 model VW generated emission trends identical to the 1980 model VW,
and inserting alternate-source properties into these equations to yield
emissions as if the fuels were petroleum-based. This approach would have
avoided probable errors that would have been introduced if vehicle factors
had to be determined and then applied to the questionable Mercedes prediction
equations. In any case, the procedures thus far discussed make many assumptions
and introduce errors that may be large enough to invalidate any conclusions
reached.
34
-------
An alternate approach was reviewed to satisfy the objective of
determining whether or not alternate-source materials affect exhaust emissions
in the same way as petroleum fuels. This approach involved reviewing data
available in previous EPA fuel variables work and other published literature
to select studies that had some common element between the alternate-source
study and petroleum studies. For example, studies chosen would incorporate
a "base" fuel that is similar in properties. This criterion would reduce the
number of studies to a workable matrix. The data from selected studies
(about 12 were anticipated) would be grouped according to similar fuel
property/exhaust emission interactions. For example, those studies which
have shown a relationship between fuel aromatics and particuate emissions
would be grouped together. Studies which resulted in a viscosity/particulate
relationship would be in another group.
Each group would be treated separately. The data from each study within
a particular group would be normalized to the "base" fuel for that study.
The resulting normalization would express the various emissions data in
terms of percent change from baseline data. The alternate-source study
data would be treated similarly to determine if comparable changes in fuel
properties would affect exhaust emisisons more, less, or the same as the
results seen in studies dealing with petroleum base stocks.
In order to better visualize this approach, Table 19 presents mock data
from studies reviewed and the alternate-source study. The following dis-
cussion is an example of what the table may be describing.
"Table 19 shows the results of fuel aromatic content on particulate
emissions. It should be noted that although an attempt was made to
choose studies that began with a base fuel of similar properties,
this was not the case.for study D's aromatic content (study D was
chosen for another fuel property matrix). Due to the apparent sensi-
tivity of additional aromatics after a critical level, study D's
results are not considered representative and comparable to the
other petroleum fuel studies. Its data were therefore not included
in averaging."
"Another point to consider is that only study B incorporated a VW
Rabbit. The other studies used different vehicles. The average,
therefore, is affected by a variation in vehicle combustion
characteristics- Direct comparison between the average data
from the alternate-source study with a VW Rabbit and the petro-
leum fuel study (study B) with a VW Rabbit showed that aromatic
increases in the alternate-source materials did not affect parti-
culate emissions."
The advantages of this approach would have been that no prediction
equations were used directly (avoiding potentially high errors), vehicle
response factors were not required, few assumptions were necessary, and a
greater number of outside studies could have been used. Some disadvantages
would have been that studies chosen may have had diverse base fuels which
were not similar in properties. This situation would not have been apparent
35
-------
TABLE 19. PARTICULATE EMISSIONS VERSUS FUEL
AROMATIC CONTENT, MOCK DATA
Aromatic Content
% A from Base
1-25
26-50
51-75
76-100
101-150
151-200
Average
Particulate Emissions % A from Baseline Study
Alternate Mercedes
Source VW 240D
0.1 0
0.9
4.
8. 20.
50.
12.6
ABC
0.5
-1.0 5.
-7
/ ซ *-""
10. 10. 10.
20. 30. 25.
40. 70.
- 12. 5C -
_a b
D Average
10. 0.25
2.
40. 7.
12.5
25.
55.
15. 4ฐ
Study D base fuel's aromatic content was twice that of other studies
^Study D is not included in the average
"Average does not include 101-150% A aromatic content
"Conclusions:"
3.
At each range of A aromatic content, the alternate-source materials
were associated with a smaller increase in particulate emissions as
compared to the average results of petroleum based fuel studies.
On the average throughout the aromatic content range, the alternate-
source fuels were associated with about 18% less particulate emissions
as compared to the average of all the petroleum-based fuel studies.
Comparing the alternate-source study (VW) with study B (VW) shows
that the alternate-source fuels did not affect particulate
emissions.
Study D exhibited the greatest increase of particulate emissions with
minimal change in aromatic content. Probable cause was the initially
high aromatic levels of that study's base fuel.
36
-------
when reviewing the table. Other parameters such as engine displacment and
driving schedules would also have been "buried" in the table. The range of
a particular fuel property may not have been evenly spaced to cover each
study properly. These potential inconsistencies may have resulted in a table
which contained only a few elements, and in any case, would have not shown
any type of population dispersion.
A third approach, which incorporated some of the techniques of the two
aforementioned approaches, involved both a visual representation and a pre-
diction equation. Due to the wide variety of vehicles, fuels, test cycles,
and measurement techniques used in previous studies, a method to relate all
these studies in terms of general trends was adopted. This method involved
reviewing each study dealing with petroleum fuels for emission trends. Those
studies which indicated similar fuel property-exhaust emission relationships
(primarily one-to-one relationships) were grouped together. The data from
each study were normalized to a predetermined fuel property level (similar
to National Average No. 2D). The normalized data set for each study was
plotted on a common graph. The resulting graph showed emission trends as a
function of petroleum fuel property with a variety of vehicles, base fuels,
and driving cycles. A band encompassing the plotted data represented a
population dispersion of petroleum-based fuel effects studies. Data from the
alternate-source fuel study were also normalized and plotted on the same
graph. Where the alternate-source study's line fell in relation to the
petroleum-based fuel's band described the comparative effects of using
alternate-source fuels.
Data from the petroleum-based fuel studies' band were subjected to linear
regression analysis to determine an equation which represented all of the
studies evaluated. This equation was used in conjunction with the alternate-
source fuel study's fuel properties to yield predicted emissions based on
petroleum fuel trends. Comparisons between predicted emissions and observed
emissions from the alternate-source study were analyzed using chi-square
test for goodness-of-fit, and conclusions were reached about alternate-
source fuel effects on emissions as compared to average trends seen in
petroleum-based fuel studies.
Other options may have existed to satisfy the objectives of this project.
It was our opinion, however, that the third approach satisfied the objectives
without involving too many assumptions or possible misrepresentation of the
data. In. addition, the third approach allowed for inclusion of as many
studies as desired without their having to meet restrictive criteria. During
a November 2, 1982 meeting at SwRI, the Branch Technical Representative
approved the third approach. Past studies have shown that fuel property-
exhaust emission relationships are not simple one-to-one correlations.
Unless a test plan has been designed essentially without compromise,
statistical analysis should not be overly complex, but should only be used
in general terms to describe trends.
At the request of the Branch Technical Representative, an expanded dis-
cussion of the third approach to the statistical analysis (from a statistician's
perspective) was written. Dr. Robert L. Mason of SwRI's Department of Fuels
37
-------
and Lubricants Technology assisted in the expansion and discussion of the
third approach. His discussion is located in Appendix D, pages D-2 through
D-5, for reference.
B. Raw Data Acquisition
Raw data representing the alternate-source fuels were obtained by
combining results generated in this study with results reported in the
earlier study. *'> Raw data representing petroleum fuels were obtained
by performing a library literature search dealing with diesel fuel effects
on emissions from light-duty vehicles. The initial search resulted in a
listing of 37 references. These references were reviewed along with other
available materials to determine which studies met basic criteria. Criteria
for selection were: more than one petroleum-based fuel evaluated, adequate
fuel analysis, exhaust emissions measurements, and use of a light-duty
4-stroke engine (<7 liters displacement). For example, studies dealing
with the effects of methanol were not useful in satisfying the objective
of this study. After review, a total of 9 references met the criteria. In
those nine, a total of 15 test cases were available (some studies used
multiple vehicles, and each vehicle was considered a test case). Studies
used are listed as references 3, 6, and 18 through 24.
The statistical packages used for analysis of the data were SPSS (Statis-
tical Package for the Social Sciences) '^5) an(j BMDP (Biomedical Computer
( f)ฃ\\
Programs).VZD; Selected programs for each of these packages were used to
evaluate the data.
C. Selection of Variables and Study Identification
The total number of fuel property and exhaust emission variables was too
large to form a reasonable test matrix. During the November 2, 1982 meeting
at SwRI, the Branch Technical Representative approved 8 fuel properties and
9 exhaust emission variables for further consideraiton. Fuel properties
chosen were: density, aromatics, olefins, cetane number, gum, nitrogen content,
90 percent boiling point, and 10 percent boiling point. Exhaust emissions
selected were: HC, CO, NOX, particulate, fuel consumption, organic solubles,
aldehydes, phenols, and BaP. Gum was later deleted from further consideration
because only one study reported gum values for the fuels tested. This matrix
was filled by data from the fuel studies selected.
In the nine petroleum-fuel studies, there were a total of fifteen cases
of fuel property effects on exhaust emissions. The raw data for the studies
available are listed in Appendix D, pages D-6 through D-8. At the request
of its author, the raw data for Study H were not published; however, the
normalized data were approved for publication. Each case was identified
as a "Study ID" number. Cases conducted under the same study were identi-
fied by "Study Info". For example, Bl and B2 are both from the same study,
but represent two different vehicle types, and therefore, two separate
cases. Study Kl consists of data representing the alternate-source fuels.
38
-------
The raw data from the petroleum fuels studied in each case were subjected
to a bivariate correlation procedure to generate Pearson's correlation
coefficients. Coefficients were determiend for "fuel property-fuel property",
"emission-emission," and "fuel property-emission" relationships. All the
coefficients were reviewed to determine trends depicted in all the test
cases. Coefficients less than 0.700 were not considered as representing a
usable correlation. A summary of the occurrence of coefficients greater than
0.700 is listed in Tables 20 through 22. The complete computer printout is
too voluminous to include in this report.
Primary interest was in the fuel property-exhaust emission relationships.
Another bivariate correlation procedure was performed on the alternate-source
data. Raw data for this study are located in Appendix D, page D-8, as
Study K. The fuel property-emission matrices for this study are shown as
Table 23. Criteria for selecting fuel property-emission data pairs for further
analysis were as follows:
1. Alternate-source study's data pairs which yielded
coefficients greater than 0.700.
2. Data pairs in Table 20 which contained a large number
of studies.
3. Data pairs which intuitively may have been related, but
did not yield high coefficients.
Based on the above criteria, the fuel property-exhaust emission data pairs
are shown in Table 24. The combination of data pairs covers most of the
original fuel properties and exhaust emissions originally selected. Phenols
were not analyzed further because only one petroleum study contained phenol
analysis. Table 25 lists the Pearson correlation coefficients of the data
pairs in Table 24 for all the studies.
D. Data Normalization
In order to account for the wide variety of vehicles, fuels, test cycles,
and measurement techniques used in the various test cases, a method to relate
all these cases in terms of general trends was developed. The exhaust emission
data from all test cases were normalized to each of the selected fuel properties.
The fuel property level was based on an average of several Phillips 2D Emissions
Grade control fuel lot analyses. Averages were rounded for ease of insertion
into calculations and data discussion. Fuel property analyses of the Phillips
control fuel are listed in Table 26.
None of the test cases evaluated a fuel with the exact fuel property
levels listed in Table 26. Therefore, linear regression analysis was performed
on each of the selected fuel property-exhaust emission data pairs for each
study case. The resulting equations were used in conjunction with the appro-
priate fuel properties from Table 26 to yield prediction of emissions. The
prediction for each data pair and case was used to normalize (by division)
the corresponding raw emissions data. This process could have resulted in
39
-------
TABLE 20. NUMBER OF PEARSON CORRELATION COEFFICIENTS GREATER THAN
0.700 FOR FUEL PROPERTIES VS. EMISSIONS
Cetane(ll)a
Density (11)
Nitrogen (3)
Aromatics ( 11)
Olefins (7)
BP 10% (11)
BP 90% (11)
Number of Studies Where Coefficients wei^ >0. 9 (1st digit), 0.9-0.8(2r.d digit), 0.8-0.7 (3rd digit)
HC(9)a
2,3,1
1,1,2
1,0,0
2,0,1
1,0,2
1,0,1
1,0,2
COO)
3,2,1
1,0,2
1,0,1
3,1,0
1,1,2
0,2,1
0,1,1
NOX(9)
2,0,0
1,0,5
0,0,1
2,0,0
0,1,2
1,0,3
2,0,1
Part. (9)
1,0,1
2,4,1
1,0,0
1,5,2
1,0,1
0,1,0
0,0,1
Fuel (9)
1,0,1
0,1,1
1,0,1
1,0,1
1,0,2
0,0,2
0,1,1
BaP(4)
0,1,1
0,0,1
1,0,1
0,1,1
0, 0,0
0,0,0
0,0,0
Aldehydes (5)
1,0, 1
1,1,0
1,1,0
1,1,2
0,1,0
1,1,0
1,1,0
Phenols (1)
0,0,0
0,0,0
0,0,0
0,0,0
0,0,0
0,0,0
0,0,0
Solubles (7)
0,1,0
0,2,0
1,1,0
0,0,1
0,0,1
0,0,0
0,0,0
ifc.
o
Number in parentheses is number of studies containing particular fuel property or emission
-------
TABLE 21. NUMBER OF PEARSON CORRELATION COEFFICIENTS GREATER THAN
0.700 FOR FUEL PROPERTIES VS. FUEL PROPERTIES
Cetane(ll)a
Density (11)
Nitrogen (3)
Aromatic s (11)
Olefins (7)
BP 10% (11)
BP 90% (11)
Number of Studies Where Coefficients were >0.9(lst digit), 0.9-0.8(2nd digit), 0.8-0.7(3rd digit)
Cetane(ll)a
_b
0, 1, 3
0,2,1
1, 2,0
1, 1,0
0, 1,0
0,1, 0
Density (11)
b
b
0,0,0
4,7,0
1,0,2
2,2,0
3,0,4
Nitrogen ( 3)
___b
b
b
0, 0, 0
0, 0, 0
0, 0, 0
0, 0, 0
Aromatics (11)
b
b
b
b
0,0, 2
1,0,1
2,0, 1
Olefins (7)
b
b
b
b
_b
5,0,0
3, 0, 0
BP 10% (11)
b
b
b
b
b
b
4, 0, 2
BP 90% (11)
___b
b
_b
b
b
b
b
Number in parentheses is number of studies containing particular property
Redundant values omitted
-------
TABLE 22. NUMBER OF PEARSON CORRELATION COEFFICIENTS GREATER THAN
0.700 FOR EMISSIONS VS. EMISSIONS
HC(9)a
CO (9)
NOX(9)
Part. (9)
Fuel (9)
BaP ( 4 )
Aldehydes (5)
Phenols (1)
Solubles (7)
Number of Studies Where Coefficients were >0.9(lst digit), 0.9-0.8(2nd digit), 0.8-0.7(3rd digit)
HC ( 9 ) a
b
5,4,0
2,1,0
1,0,1
0,2,1
1,1,0
3,0,0
0,0,0
1,0,1
CO(9)
b
b
2,2,2
2,0,0
2,2,0
1,0,0
1,1,1
0,0,0
1,0,1
NOX(9)
b
b
b
0,1,3
3,1,1
0,0,0
2,0,1
0,0,0
0,0,0
Part. (9)
b
b
b
b
1,1,1
1,0,1
1,0,1
0,0,0
2,0,1
Fuel (9)
b
b
b
b
b
0,1,0
1,1,0
0, 0,0
1,1,0
BaP (4)
b
b
b
b
b
b
1,0,1
0, 0, 0
1,0,0
Aldehydes (5)
b
b
b
b
b
b
b
0, 0, 0
0,1,0
Phenols (1)
b
b
b
b
b
___b
b
b
0, 0, 0
Solubles (7)
b
b
b
b
b
b
b
b
b
Number in parentheses is number of studies containing particulate emissions
Redundant values omitted
-------
TABLE 23. FUEL PROPERTY - EXHAUST EMISSION CORRELATION FOR THE
ALTERNATE-SOURCE FUEL STUDY
Cetane
Density
Nitrogen
Aromatic
Olefins
BP 10%
BP 90%
Pearson Correlation Coefficients
HC
-0.8873
-0.0563
0.6696
-0.0864
-0.2625
-0.6800
-0.1407
CO
-0.9221
-0.0123
0.6556
0.0404
-0.3172
-0.6387
-0.1980
NOX
-0.3262
0.7390
0.5871
0.6483
0.1202
0.3149
-0.0795
Part.
-0.2938
0.8059
0.6672
0.8030
0.2565
0.4490
-0.0875
Fuel
-0.0669
-0.6205
-0.2254
-0.6387
0.2369
-0.4838
-0.4892
BaP
-0.0800
-0.0365
0.0681
-0.0806
0.2607
0.0583
-0.1264
Aldehyde
0.1104
-0.4577
-0.3332
-0.7479
0.4099
-0.3021
-0.5701
Solubles
-0.5069
0.4921
0.8149
0.4817
0.0320
0.0368
0.1157
TABLE 24. SELECTED FUEL PROPERTY-EXHAUST EMISSION DATA PAIRS
Fuel Property
Cetane
Cetane
Cetane
Density
Density
Density
Density
.Nitrogen
Nitrogen
Nitrogen
Aromatics
Aromatics
Aromatics
Aromatics
Aromatics
Aromatics
Olefins
10% B.P.
10% B.P.
10% B.P.
90% B.P.
90% B.P.
Exhaust Emission
HC
CO
Solubles
HC
NO
X
Particulate
Fuel
CO
BaP
Solubles
HC
CO
NO
X
Particulate
BaP
Aldehydes
Fuel
HC
NO
X
Particulate
HC
Particulate
43
-------
TABLE 25. iEARSON'S CORRELATION COEFFICIENTS FOR SELECT FUEL PROPERTY - EXHAUST EMISSION DATA PAIRS
Fuel
Property
Cetane
Cetane
Cetane
Density
Density
Density
Density
Nitrogen
Nitrogen
Nitrogen
Aromatics
Aromat ics
Aromatics
Aromatics
Aromatics
Aromatics
Olefins
10% B.P.
10% B.P.
10% B.P.
90% B.P.
90% B.P.
Exhaust
Emission
HC
CO
Solubles
HC
NOX
Particulate
Fuel
CO
BaP
Solubles
HC
CO
NOX
Particulate
Aldehydes
BaP
Fuel
HC
NOX
Particulate
HC
Particulate
Al
-0.7618
-0.5405
-0.2560
0.7524
0.7217
0.8888
-0.0878
0.0605
-0.0313
-0.3506
0.7965
0.9131
0.6955
0.8740
-0.3742
0.1493
0.6246
-0.4500
-0.0354
0.0735
0.0005
0.0817
Bl
-0.6425
-0.6213
0.5026
0.8307
0.7273
0.9870
0.3993
0.7342
0.7269
-0.3042
0.6360
0.2347
0.4237
0.8939
0.7120
0.8568
-0.5565
0.6997
0.7283
0.8218
0.4973
0.7273
B2
-0.8297
-0.8848
-0.8766
0.6675
0.1886
0.8011
0.4891
0.9846
0.9744
0.9819
0.6914
0.5854
0.2745
0.8315
0.8413
0.7085
-0.2942
0.3464
0.5578
0.4826
0.1829
0.3294
Cl
0.9864
0.9806
1.0000
0.6990
0.7780
0.5553
0.9513
0.2487
0.2739
0.2608
0.9084
0.3866
1.0000
-0.9698
0.7088
0.7962
0.5275
0.7481
0.5626
Study Identification
Dl
-0.6934
-0.8660
-0.9265
0.9449
-0.0751
0.4740
-0.9993
-0.9494
0.9999
-0.4102
0.9349
-0.9999
-0.9707
0.9820
-0.2168
-0.9794
-0.2550
Fl
-0.9623
-0.9632
0.7473
-0.2080
-0.8665
0.9599
0.9195
-0.6170
-0.7033
-0.6874
0.7225
0.7400
F2
1.0000
1.0000
0.2842
0.7125
0.6533
-0.2402
0.3542
0.9696
-0.5684
1.0000
-0.4617
-0.1043
Gl
-0.2962
-0.4325
-0.1599
0.2028
-0.0262
0.0221
-0.2198
0.3877
0.8321
-0.4444
-0.1657
-0.4152
0.4864
0.0880
0.4744
-0.2186
G2
0.8014
0.7337
0.1557
-0.6027
-0.0387
0.8915
-0.0766
I
-0.5090
-0.3510
-0.0711
0.7432
0.1499
-0.0489
0.3823
-0.0734
0.4946
HI
-0.3599
-0.2926
-0.2295
-0.0974
0.4711
0.2362
-0.1339
0.2317
0.3697
0.2792
-0.3230
-0.2956
0.4420
-0.1842
0.4070
11
-0.1807
0.9233
;;
0.8875
0.2617
0.5768
12
-0.2153
0.7349
0.7058
0.1076
0.4331
Jl
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
J2
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
J3
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
Kl
-0.8873
-0.9221
-0.8873
-0.0563
0.7390
0.8059
-0.6205
0.6556
0.0681
0.8149
-0.0864
0.0404
0.6483
0.8030
-0.7479
-0.0806
0.2369
-0.6800
0.3149
0.4490
-0.1407
-0.0875
-------
TABLE 26. ANALYSES OF PHILLIPS 2D DIESEL FUEL LOTS
Property
Cetane No.
Distillation Range
IBP, ฐC
10% point, ฐC
50% point, ฐC
90% point, ฐC
End point, ฐC
Gravity, "API
Density, g/mฃ
Sulfur, %
Hydrocarbon Composition
Paraffins, vol. %
Olefins, vol. %
Aromatics, vol. %
Flash Point, ฐC min
Viscosity, cs, 40ฐC
Nitrogen, ppm
EPA
Specification
42-50
171-204
204-238
243-282
288-321
304-249
33-37
0.2-0.5
27 min
54.4
2.0-3.2
Phillips Lot No.
C-345
47.8
196
223
264
299
315
34.8
0.8509
0.30
65.
5.
30.0
79.4
2.56
C-504
46.3
200
224
257
296
323
35.7
0.8463
0.25
69.0
1.2
29.8
75.0
2.44
80
C-747
47.5
197
221
263
302
321
35.8
0.8458
0.20
29.1
69.4
2.50
Average
47.2
198
223
262
299
319
35.4
0.8478
0.25
67.3
3.1
29.6
74.4
2.50
80
Rounded
47.
200
220
260
300
320
35.0
0.8500
0.25
68.
2.
30.
74.
2.50
80
45
-------
a total of 352 normalization factors (16 cases, (15 petroleum + 1 alternate-
source) x 22 selected fuel property-exhaust emission pairs). However, some
studies did not report some of the selected fuel properties or exhaust emissions,
so the actual total of normalization factors was 262. The normalization factors
are listed in Table 27.
Application of the normalization factors to each raw data set (about two
thousand simple divisions, plus re-establishment and storage of data files)
was performed by a computer program written specifically for that purpose.
The normalized exhaust emission data for each selected fuel property are listed
in Appendix D, pages D-9 through D-29.
E. Scattergrams of Select Variables
The normalized data from each study were plotted on a common graph showing
the emission of interest versus a specific fuel property. The petroleum-
based fuel study data were plotted using the plot symbol "A", and the alternate-
source study data used "B". A linear regression analysis was performed on the
petroleum-based fuel data from all the studies to yield a single equation.
This equation was used to superimpose a line on the common plot, representing
the relationship between a particular petroleum-based fuel property and one
exhaust emission variable. Similarly, a line representing the alternate-
source fuels was also drawn on the plot. In addition, each plot contained
a horizontal line representing a normalized emission value of 1.0, along
with a vertical line representing the fuel property level to which the
data were normalized. The effects of using alternate-source fuels were
determined by observing where the alternate-source fuel line fell relative to
the petroleum-based fuel line.
In addition, the normalized emissions data from each individual study
were fitted with a least squares regression line using a specified fuel pro-
perty as the independent variable. An equation was used similarly to fit
the alternate fuel data. These lines were plotted on a common graph. The
lines from the petroleum fuel data formed a region representing the dispersion
for such studies. The effects of using alternate-source fuels were determined
by observing where the alternate-source fuel line fell relative to the pet-
roleum-based fuel band defined by the individual-study lines.
In all cases, the regression equation representing all the petroleum-
based fuel data points was used (with the fuel property data from the
alternate-source study) to obtain predicted emission values for comparison
to the observed emission data from the alternate-source study. This com-
parison was accomplished using a goodness-of-fit statistic, defined as:
n o
2 _ ~ (Observed - Predicted)z
. , Predicted
i=l
Although "x^" (as used here) is not a true chi-square statistic (as would
occur in a single experiment with random observations), it is similar to the
46
-------
TABLE 27. EMISSION NORMALIZATION FACTORS FOR SELECT FUEL PROPERTY - EXHAUST EMISSION DATA PAIRS
Fuel
Property
Cetane
Cetane
Cetane
Density
Density
Density
Density
Nitrogen
Nitrogen
Nitrogen
Aromatics
Aromatics
Armoatics
Aromatics
Aromatics
Aromatics
Olefins
10% B.P.
10% B.P.
10% B.P.
90% B.P.
90% B.P.
Exhaust
Emissions
HC
CO
Solubles
HC
NOX
Particulate
Fuel
CO
BaP
Solubles
HC
CO
NOX
Particulate
BaP
Aldehydes
Fuel
HC
NOX
Particulate
HC
Particulate
Study Identification
Al
0.124
0.576
27.811
0.151
1.053
0.311
9.560
0.521
0.480
26.753
0.123
0.608
0.938
0.235
0.523
0.974
9.592
0.085
0.854
0.188
0.101
0.209
Bl
0.148
0.639
29.807
0.169
0.833
0.342
8.985
0.625
0.383
30.321
0.168
0.645
0.826
0.347
0.503
19.794
8.757
0.171
0.840
0.345
0.149
0.319
B2
0.318
0.592
34.614
0.388
0.608
0.277
5.883
0.550
1.454
30.155
0.418
0.637
0.597
0.289
2.278
35.948
5.787
0.357
0.619
0.268
0.300
0.245
Cl
0.200
0.790
71.600
0.288
1.536
0.300
8.958
--
--
--
0.264
0.860
1.412
0.323
0.985
33.247
8.426
0.288
1.533
0.299
0.270
0.291
r>i
0.240
0.880
--
0.169 ,
0.844
0.179
7.917
0.197
0.782
0.834
0.179
28.621
7.563
0.178
0.840
0.178
0.249
0.181
Fl
0.875
1.022
--
1.722
0.411
4.918
1.094
1.168
0.409
4.150
0.240
0.492
0.785
F2
0.479
1.213
0.434
1.099
12.877
0.367
1.170
1.047
10.738
0.648
0.936
0.372
Gl
0.101
0.418
26.086
0.130
0.963
0.117
10.125
0.125
0.505
0.946
0.116
0.080
1.054
0.118
0.130
0.115
G2
0.260
0.762
39.439
0.033
0.818
0.176
11.552
0.098
0.644
0.818
0.158
0.269
0.816
0.160
0.198
0.153
HI
0.771
--
37.27
0.428
2.019
13.233
128.30
0.660
2.145
12.982
124.69
0.209
1.939
13.176
0.638
12.878
11
181.473
0.563
0.595
0.522
0.436
12
68.590
0.255
*~
0.264
0.226
0.220
Jl
0.369
1.251
163.619
0.353
0.873
0.282
8.596
0.330
1.103
0.844
0.267
1.560
11.462
8.494
0.309
0.821
0.254
0.345
0.276
J2
0.329
1.047
101.976
0.305
1.259
0.209
10.219
~~
0.269
0.909
1.265
0.183
2.224
7.296
10.409
0.240
1.271
0.163
0.292
0.199
J3
0.135
0.709
41.338
0.131
0.651
0.276
10.636
"
0.125
0.670
0.645
0.254
0.398
0.307
10.709
>.119
0.539
0.236
0.127
0.769
Kl
0. 333
1.095
45.244
0.398
0.732
0.299
6. 357
1.106
2 3 095
38. 934
0.400
1.163
0.718
0.285
23.480
6.494
6.474
0.356
0.721
0.292
0.405
0.278
-------
chi-square; and the chi-square table was used to provide guidelines for
determining whether or not the observed and the predicted values differed.
A percentile value of X2ig5, based on 9 degrees of freedom, was chosen
from tables of the chi-square distribution to serve as a guideline value.
If these had been true random observations, from a normal distribution,
this value (16.9) would mean that decisions on whether petroleum-based fuel
and alternate-source fuel effects were statistically different would have
a 5 percent error rate.
As stated in the Work Plan for this Assignment, the extent of statistical
analysis possible depended on the funding available at the initiation of
the data analysis portion of the work. As the analysis task began, it was
apparent that a detailed statistical analysis was not possible due to efforts
expended on the Q/A Project Plan and on attempts to formulate statistical
approaches to analyze a greater number of fuel property/exhaust emission data
pairs than originally anticipated. All the aforementioned analyses and data
are included in this report as Appendix E. A detailed discussion of all the
selected fuel property/exhaust emission data pairs was not feasible. Dis-
cussion on the regulated emissions (HC, CO, NOX, and particulate) along with
a few of the more interesting other results are presented using the goodness-
of-fit technique to determine whether or not alternate-source fuels 'are
different in affecting exhaust emissions as compared to petroleum-based fuels.
1. Hydrocarbons
Figure 6 shows the normalized data for both the petroleum-based fuels
(A) and the alternate-source fuels (B) plotted in a common frame. The slopes
of both lines are very similar, indicating that hydrocarbons respond to fuel
cetane number independent of the type of fuel. The low correlation coefficient
of the petroleum-based fuel- data reflects variation by the individual study
line plots among the petroleum-based fuel studies used; and this variation is
further illustrated in Figure 7. These lines show that the alternate-source
study Kl (dashed line) fell within the spread of the various petroleum-based
studies.
Figure 6 includes the linear regression equation which represents
data points from all the petroleum-based fuel studies. Using this equation
and data froir, che alternate-source study, predicted emission values were
calculated and compared to the observed emission data from the alternate-
source study. Table 28 presents these results. The calculated "chi-square"
(or goodness-of-fit, in this case) was 0.2376. The percentile value for a
chi-square distribution with 9 degrees of freedom (number of data points - 1)
for X2>95 is 16.9. Since 0.2376 is much smaller than 16.9, the "fit" of the
data is very good, and therefore the observed values and predicted values do
not appear to be different.
Figures 8 through 11 show the hydrocarbon data as a function of aro-
matics, density, 10 percent boiling point, and 90 percent boiling point, res-
pectively. The line plots of the individual studies (similar to Figure 7)
are located in Appendix E. Table 29 presents the goodness-of-fit (chi-square)
48
-------
**..***...+x...ปป...+***.ป...ปปป...+....+*...+....+...**-....+.... + .
3.2
2.8 +
2.4
Petroleum
Solid Line
H 2.0
C
1.6
& 1,2
.80 +
.40 +
A A
...+.. "'""''. + ....+.... + ...X+....+....+....T....T. ...+ซซ
28 36 44 52 60 68
32 40 48 56 64 72
CETANE
f
ft
A Y
ป*^***ซ*^*a
76
80
N= 85
COR=-.276
MEAN ST.DEV. REGRESSION LINE R|S.MS.
47.424 8.3294 X=-1.1745*Y+ 48.644 \*-*ฐ2
1.0390 1.9545 Y=-.06467*X+ 4.1058 3.5724
N= 10
COR=-.887
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 44.000 4.9889 X=-11.360*Y+ 57.713 5.9547
Y 1.2072 .38969 Y=-.06931*X+ 4.2568 .03633
Figure 6. Normalized HC versus cetane.
-------
OH
/I
3NV130
9S
Ofr
zs
o
LO
-------
TABLE 28. COMPARISON OF OBSERVED VERSUS PREDICTED HYDROCARBONS AS A
FUNCTION OF FUEL CETANE USING PETROLEUM-BASED FUEL STUDY
EQUATION AND ALTERNATE-SOURCE FUEL DATA
"K"
"J" (Observed-
Cetane No. Observed HC Predicted HC Predicted) "K"/"J"
50
49
45
42
35
38
44
45
50
42
0.9309
0.9309
1.1411
1.1712
2.0402
1.8018
0.9910
1.0210
0.9610
1.0811
0.8723
0.9730
1.1957
1.3897
1.8424
1.6483
1.2603
1.1957
0.8723
1.3897
0.0034
0.0003
0.0030
0.0477
0.0399
0.0235
0.0725
0.0305
0.0079
0.0952
0.0039
0.0003
0.0025
0.0343
0.0217
0.0143
0.0575
0.0255
0.0091
0.0685
o II v11
X = Z = 0.2376
51
-------
* ป J. * # ป* J. # *** j. y ***4. 4. * * J. J. * 4. j. j.
. . ..T. .. . .T. . ...T....A." **++ T. . .. + ....+,
3.2
2.8
2.4
N= 33
COR= .141
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 21.430 11.289 X= 2.7817*Y+ 18.968 126.46
Y .88527 .57197 Y= .00714*X+ .73224 .32461
H 2.0 +
C
A A
1.6 +
1.2 +
.80 +
.40 +
ซ " "" ปA', ''* ซ' *1*ป '' *' * "ป" * ซ * ^* * "t"* *^ซ
5. 15 25 35 45 55 65
0. 10 20 30 40 50 60 70
AROMATIC
N= 10
COR=-.086
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES. MS.
X 28.590 8.0524 X=-2. 1452*Y+ 30.746 72.401
Y 1.0050 .32442 Y=-.00348*X+ 1.1046 .11752
Figure 8. Normalized HC versus aromatics.
-------
+....+..*.+..ซ.+....+.ซ.ปป. * *X*ปป+ป*. ปซ.ป..*..*.+ +....+
H
C
en
CO
21)
Af.786,404)
A(.759,32.52)
3.2
2.8
2.4
2.0
1.6
1.2 .-___
.80
.40
HC = 1.0
^630 !e90 [756 Isio Is76 [936 !99o'
.600 .660 .720 .780 .840 .900 .960
DENSITY
Petroleum
Solid Line
N= 86
COR=-.220
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .81541 .03993 X=-.00209*Y+ .81939 .00154
Y 1.9074 4.2128 Y=-23.261*X+ 20.875 17.085
N= 10
COR=-.056
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .83770 .02546 X=-.00440*Y+ .84214 727E-6
Y 1.0100 .32604 Y=-.72142*X+ 1.6144 .11921
Figure 9. Normalized HC versus density.
-------
....* + *... 4-*... 4-..*. 4-*.. ***... 4-... X+. ****.ป*.**.*.+...*ป*.*.+ +.*..+.
3.2
2.8
2.4 +
AA
N= 76
COR=-.077
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 200.24 41.010 X=-5.5852*Y+ 206.08 1694.5
Y 1.0470 .56361 Y=-. 00105*X4- 1.2583 .32005
"*" "*" **"* T" "*" ' *^ ซ "" * T , ซ "*", ป"'", ปT. , ป *
60. 100 140 180 220 260 300
80. 120 160 200 240 280 320
BPTEN
Alternate
COR=-.'6ฐ80
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 191.60 53.707 X=-100.19*Y+ 304.74 1744.6
Y 1.1292 .36451 Y = -. 00462*X4- 2.0135 .08036
Figure 10. Normalized HC versus 10% boiling point.
-------
V .
>:*
-------
values for all the hydrocarbons-fuel property data pairs. The calculated
"chi-square" values were compared to the X2_g5 percentile value to determine
TABLE 29. HYDROCARBON DATA PAIRS GOODNESS-OF-FIT
Calculated Petroleum vs. Alternate
Data Pair "Chi-Square" Statistically Different
HC - Cetane 0.238 No
HC - Aromatics 1.19 No
HC - Density 3.53 No
HC - 10% Boiling Point 0.920 No
HC - 90% Boiling Point 1.63 No
if substitution of alternate source fuel properties into petroleum-based fuel
prediction equations yielded statistically different results than emissions
observed while using alternate-soruce fuels.
In summary, the effects of fuel aromatic content, cetane number,
density and 90 percent boiling point on hydrocarbon emissions were about
the same, independent of the source (petroleum-based or alternate-source).
Although goodness-of-fit indicated that the 10 percent boiling point affected
HC regardless of the source, the plot of the individual study lines showed
a wide variation of HC response to petroleum-based fuels. This wide
variation does not allow for a clear trend to be interpreted. Figure 9
shows the petroleum-base fuel line forced to reach a few points off-scale.
It appears that without these points, the petroleum-based fuel line would
be similar to that of the alternate-source line.
2. Carbon Monoxide
Figures 12 through 14 present the carbon monoxide data as functions
of cetane number, aromatics, and nitrogen. The individual line plots for
each study (in common frame) are located in Appendix E. Table 30 presents
the goodness-of-fit values for each of the CO-fuel property data pairs.
As before, the "chi-square" values were compared in the X2 gs percentile to
TABLE 30. CO DATA PAIRS GOODNESS-OF-FIT
Petroleum vs. Alternate
Data Pair Calculated "Chi-Square" Statistically Different
CO - Cetane 0.116 No
CO - Aromatics 0.117 No
CO - Nitrogen 0.061 No
determine if statistical similarities existed. All the scattergrams and
goodness-cf-fit calculations indicate that the effects of fuel cetane number,
aromatic content, and nitrogen content on CO emissions are similar regardless
56
-------
ปป* *** * *** ซ**ป*ป*ซ* ปซ**
.+*...+....+...ป+.
3.2 X
2.8 +
2.4
N= 54
COR=-.200
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 48.815 7.1153 X=-7.4838*Y+ 56.042 49.541
Y .96567 .18998 Y=-.00534*X+ 1.2261 .03532
C 2.0 +
0
1.6
1.2
.80
N= 10
COR.922
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 44.000 4.9889 X=-41,380*Y+ 87.911 4.1923
Y 1.0612 .11117 Y=-.02055*X+ 1.9653 .00208
.40
28 36 44 52 60 68 76
32 40 48 56 64 72 80
CETANE
Figure 12. Normalized CO versus cetane.
-------
***+** *****+##***#+ * 4- **** * It** 4. 4. * Y -4- 4.
' * ' T ** *' "''
3.2
2.8
2.4 +
N= 56
COR= .272
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 21.979 10.717 X= 14.688*Y+ 7.9194 108.34
Y .95719 .19825 Y= .00503*X+ .84671 .03708
C 2.0 +
0
.A
Cn
CO
1.6
1.2 -f
N= 10
COR= .040
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 28.590 8.0524 X= 3.0995*Y-t- 25.493 72.828
Y .99913 .10467 Y= 524E-6*X+ .98416 .01230
.40
"" * A . * T0 m
5.
10
15
"*"ซ <* ซ "'"
25
20 30
35
40
AROMATIC
45
50
55
** *' "*"
65
60 70
Fiugre 13. Normalized CO versus aromatics.
-------
*""*"'*' "TV '*' '*"'*'
+
3.2
2.8
2.4
Petroluem
Solid Line
N = 21
COR= .138
MEAN
X 171.00
Y 1.0164
ST.DEV.
263.07
.14813
REGRESSION LINE RES.MS.
X= 245. 1 5*Y-78. 175 71458.
Y= 777E-7*X+ 1.0031 .02266
C 2.0 +
0
1.6
1.2
.A
.80 X
.40
_A A
CO = 1.0-
X
A .
Y
A *
*
*"*"''" ^ "*""*' + + + ++++ +
17.50 52.50 87.50 122.5 157.5 192.5 227.5
0.000 35.00 70.00 105.0 140.0 175.0 210.0 245.0
NITROGEN
COR
Alternate
10 Dashed Line
.656
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 604.40 742.46 X= 4422.9*Y-4042.4 353645
Y 1.0506 .11004 Y= 972E-7*X+ .99189 .00777
Figure 14. Normalized CO versus nitrogen.
-------
of the fuel source.
3. Oxides of Nitrogen
The NO data as functions of aromatics, density, and 10 percent
boiling point are shown in Figures 15 through 17. Appendix E contains the
same data plotted as individual lines representing each study. Table 31
lists the goodness-of-fit values for each of the NOX data pairs. Comparing
TABLE 31. NO DATA PAIRS GOODNESS-OF-FIT
x
Petroleum vs. Alternate
Data Pair Calculated "Chi-Square" Statistically Different
NOX - Aromatics 0.045 No
NOX - Density 0.062 No
NOX - 10% Boiling Point 0.640 No
the "chi-sguare" values in Table 31 to X2_95 (16.9) indicates that the
effects of fuel aromatics, density, and 10 percent boiling point on NOX
emissions are similar regardless of the fuel source. Figure 16 shows a
sharper slope for the alternate-source data than the petroleum data. This
slope can be misleading in that the alternate-source data points do not
exhibit a wide population dispersion and are located quite near the fuel
density value to which the NOX data were normalized.
4. Particulate
Figures 18 through'21 present particulate data as a function of fuel
aromatics, 90 percent boiling point, density, and 10 percent boiling point.
Individual regression lines representing each study, in common graphs, are
located in Appendix E. Table 32 gives the goodness-of-fit values for each
of the particulate-fuel property data pairs. Calculated "chi-squares"
TABLE 32. PARTICULATE DATA PAIRS GOODNESS-OF-FIT
Calculated Petroleum vs. Alternate
Data Pair _ "Chi-Square" Statistically Different
Particulate - Aromatics 0.133 No
Particulate - 10% Boiling Point 0.421 No
Particulate - Density 0.127 No
Particulate - 90% Boiling Point 1.713 No
indicate that fuel aromatics, 90 percent boiling point, density, and 10 percent
boiling point affect particulate emissions similarly for both petroleum-based
fuels and alternate-source fuels. Although the calculated "chi-square" value
for the 10 percent boiling point is the highest of all the particulate-fuel
property data pairs (1.713), the slopes of the alternate-source study and the
60
-------
.*.*..+....*.**.+.*..**...+....+.***+....+....*.*..+....+..*.+.
3.2
2.8
2.4 +
N= 87
COR= .256
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 20.895 11.396 X= 21.231*Y+ .21010 122.79
Y .97428 .13739 Y= .00309*X+ .90980 .01785
N 2.0 +
0
CTi
1.6
.80
.40
. A
Alternate
N= jo Dashed Line
COR" .648
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 28.590 8.0524 X= 62.390*Y-33.192 42.279
Y .99025 .08368 Y= .00674*X+ .79760 .00457
ป"^ซ ^^ป *ซ^ซ '*"*"'" ^*ซ ปปT, ปป+, m ป+, +, ซ ซ ซ ^ * * ^ ป ^ป *"
5. 15 25 35 45 55 65
0. 10 20 30 40 50 60 70
AROMATIC
Figure 15. Normalized NOX versus aromatics.
-------
.+...**ป.ซ.*..*.-MX. **.*..*..ป.+ + +
3.2
2.8
2.4
N= 87
COR= .043
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .81523 .03974 X= ,00988*Y+ .80542 .00159
Y .99281 .17358 Y= . 18852*X + .83913 .03043
N 2.0 +
0
X
1.6 +
1.2
.80 +
.40
ABB
AAA A A A
A A A /
NO
= 1.0-
COR =
10
.739
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .83770 .02546 X= .22911*Y+ .61516 331E-6
Y .97132 .08210 Y= 2.3831*X-1.0250 .00344
....
.630 .690 .750 .810 .870 .930 .990
.600 .660 .720 .780 .840 .900 .960
DENSITY
Figure 16. Normalized NOX versus density.
-------
+....+....+..*.+....+.... + ... *+.***+.**.*..
3.2
2.8
2.4
Petroleum
Solid Line
N= 87
COR=-.246
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 189.66 51.422 X=-80.717*Y+ 270.78 2513.6
Y 1.0050 .15664 Y=-749E-6*X+ 1.1471 .02332
N 2.0 +
0
X
cn
1.6
A
A A
N =
COR =
10
.315
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 191.60 53.707 X= 203.01*Y-8.5940 2923.1
Y .98614 .08333 Y= 489E-6*X+ .89250 .00704
#"*" ' "*" "** "*' "" ** *' T, 'T* ซ ^Xซซ + v m *^*ซ "^"*
60. 100 140 180 220 260 300
80. 120 160 200 240 280 320
BPTEN
Figure 17. Normalized NOV versus 10% boiling point.
-------
K 4- 4- * 4- * #4- *4- 4- 4- # 4- 4- 4- 4- 4- 4- 4-
Tซป T T Tซซซซ'ซปปปTซ ^'''^^**
3.2 +
2.8
2.4 +
N= 1 12
COR= .701
MEAN
X 21.012
Y .90169
Petroleum
Solid Line
ST.DEV. REGRESSION LINE RES.MS
14.112 X= 38.669*Y-13.856 102.3
.25567 Y= .01269*X+ .63500 .0335'
P
A
R
T
N =
COR =
10
.803
MEAN
X 28.590
Y .97509
Alternate
Dashed Line
ST.DEV. REGRESSION LINE RES.MS.
8.0524 X= 34.579*Y-5.1281 25.902
.18701 Y= ,01865*X+ .44188 .01397
ป^ป * ป ^ " ปT^ ซ ** "'' T , ซ* ^''ซ "* 9 9 9' * 999^9 999^9
5. 15 25 35 45 55 65
0. 10 20 30 40 50 60 70
AROMATIC
Figure 18. Normalized particulate versus aromatics.
-------
"*"'""*''*" '^ป '' * "'*''**"
3.2
Ui
2.8 +
2.4
P 2.0
A
R
T
1.6
1.2 +
.80
.40
A
A
A
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES. MS.
X 276.96 61.310 X= 82.100*Y+ 195.17 3086.3
Y .99628 .32235 Y= .00227ซX+ .36770 .08532
NB 10
COR=-.087
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X, 308.70 39.936 X=-18.213*Y+ 326.91 1780.5
Y .99965 .19170 Y=-420E-6*X+ 1.1292 .04103
* * "*" " "** **+ปปปป+. *TV 'T, ซ *** ** ป' *
75. 125 175 225 275 325 375
100 150 200 250 300 350 400
BPNINETY
Figure 19. Normalized particulate versus 90% boiling point.
-------
3.2 +
* "*' "^"^ซ ""*
2.8 +
2.4
N= 112
COR= .565
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .82167 .04249 X= .08736*Y+ .74464 .00124
Y .88174 .27503 Y= 3.6602*X-2.1258 .05192
P 2.0 +
A
R
T
1.6
1.2 +
.80 +
.40
'* **" * "*" "*" #''' X ซ T , ^ "*", #ป **<" ' "*" ป" ป ป *^* ป ' ป
.630 .690 .750 .810 .870 .930 .990
.600 .660 .720 .780 .840 .900 .960
DENSITY
Alternate
Dashed Line
N= 10
COR= .806
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .83770 .02546 X= .11511*Y+ .73072 256E-6
Y .92943 .17823 Y= 5.6425*X-3.7973 .01253
Figure 20. Normalized particulate versus density.
-------
P
A
R
T
3.2
2.8
2.4
2.0
1.6
1.2
.80
.40
+
+
A
A
Yss-B"**"^
! A A
+
'
X
*
*
A
A
A A
A +
A
A A A
* A
A
A AA M A A A +
A AA AAAAAB A fl TT
A B A AAA A, ^ ^^'^r'PTl 0 '
A A , ~A^+tagr*~ , [/\ B *
A A BA A AAA '
^sfc A AAAA/ A +
"" A A BA A A
A A AAA A
A A A A
A
A +
A
*
* * ' *" ^ t * ' ป ^ ^ ^ ** ^ซ ^
60. 100 140 180 220 260 300
80. 120 160 200 240 280 320
BPTEN
COR=%3
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 203.20 52.199 X= 50.185*Y+ 154.81 2544.8
Y .96412 .28379 Y= .00148*X+ .66271 .07522
NS )Q
COR- .449
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 191.60 53.707 X- 132.13*Y+ 65.847 2590.7
Y .95171 .18252 Y= .00153*X+ .65934 .02992
Fiugre 21. Normalized particulate versus 10% boiling point.
-------
petroleum-based studies are almost identical (Figure 21). This apparent
anomally is due to the poor fit of the regression lines caused by scattered
data. The data was scattered similarly in both cases to yield similar slopes.
5. Unregulated Emissions
The remaining selected fuel property-exhaust emission data pairs
are shown in Figures 22 through 28. Again, the individual regression lines
representing each study in a common frame (for each fuel property-emission
variable pair) are located in Appendix E. Table 33 shows the goodness-of-fit
for each fuel property-exhaust emission data pair. Calculated "chi-square"
TABLE 33. UNREGULATED EMISSION DATA PAIRS GOODNESS-OF-FIT
Calculated Petroleum vs. Alternate
Data Pair "Chi-Square" Statistically Different
Fuel Consumption - Olefins 0.033 No
Fuel.Consumption - Density 0.012 No
BaP - Nitrogen 1.96 No
BaP - Aromatics 2.25 No
Aldehyde - Aromatics 3.65 No
Solubles - Cetane 1.45 No
Solubles - Nitrogen 0.482 No
values do not indicate any statistically different between petroleum-based
and alternate-source fuel effects on the exhaust emissions listed in Table 33.
F. Additional Comments
In many cases, the scattergrams of the fuel property-exhaust emission data
pairs did not visually support the trends determined by goodness-of-fit
calculations. It should be noted that all the scattergrams contained regression
lines representing both petroleum-based fuels and alternate-source fuels,
regardless of the bivariate correlation coefficient values. Bivariate
correlation coefficients less than 0.7 are not considered to represent a
good fit of the data. In most cases, the coefficients were <0.7. Therefore,
the lines themselves may be misleading. A detailed statistical analysis would
have included an error band to show the range within which the lines could
have fallen. As used in this study, goodness-of-fit does not imply good linear
fit of the ata. In the case of this study, the goodness-of-fit shows that
petroleum-based fuel data yield prediction equations which, when used in
conjunction with alternate-soruce data, results in a scatter of predicted
results that are statistically similar to the scattered results observed.
68
-------
* "*" + . , ซ ซ T. ซซ.+.
*^ป "*"
3.2
2.8
2.4
Petroleum
69 Solid Line
COR=-.238
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 1.8116 1.1309 X=-3.5767*Y+ 5.4825 1.2244
Y 1 0263 .07529 Y=-.01585*X+ 1.0551 .00543
F 2.0 +
U
E
L
X
1.6 +
A AA-B~BA7\* A A
Fuel =1.0-1
Alternate
N= 10 Dashed Line
COR= .237
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 1.0100 .82926 X= 6.3767*Y-5.3105 -730ฐ5
Y 99119 .03086 Y= ,00883*X+ .98227 .00101
.40
'*''''"''ซ'*'..'''.. ^'. .'''..'''....'''..'''. .X. + .... + ..
.40 1.2 2.0 2.8 3.6 4.4 5.2
0.0 .80 1.6 2.4 3.2 4.0 4.8
OLEFINS
5.6
Figure 22. Normalized fuel versus olefins.
-------
..+....+....+....+....+....+...***.*.*..*.+*ป.**.*..*..*.+....+....+
3.2
2.8
2.4 4-
N= 85
COR= .195
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .81565 .04006 X= .15468*Y+ .66181 .00156
Y .99455 .05062 Y= .24700*X+ .79309 .00249
F 2.0 4-
U
E
L
1.6 4-
1.2 -f __ __
.80
.40
Fuel= 1.0-
****** "ซ*X *?* ' *rป T ^ ''"' ' ^''ซ * *^ป
.630 .690 .750 .810 .870 .930 .990
.600 .660 .720 .780 .840 .900 .960
DENSITY
N= 10
COR=-.621
Alternate
Dashed Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X .83770 .02546 X=-.50251*Y+ 1.3450 448E-6
Y 1.0094 .03144 Y=-.76657*X+ 1.6516 684E-6
Figure 23. Normalized fuel versus density.
-------
^"ป "*""*" * ^* '*'*'*' *
,,+, ซ ซ "^"
3.2
2.8
2.4
A .
N =
COR=
21
.077
MEAN
X 171.00
Y 1.0448
Petroleum
Solid Line
ST.DEV. REGRESSION LINE RES.MS.
263.07 X= 40.591*Y+ 128.59 72410.
.50174 Y= 148E-6*X+ 1.0195 .26341
B 2.0 +
A
P
1.6 +
- :"=
.8
1.2 +A
Y*
.80 + A
A Y
A
A A
BAP = 1.0I
N =
COR
X
Y
10
= .068
MEAN
604.40
1.0236
Alternate
Dashed Line
ST.DEV. REGF
742.46 X= 10:
.49078 Y= 45(
REGRESSION LINE RES.MS.
103.02*Y+ 498.95 617273
r*X+ .99640 .26972
.40 +A
* ซ"*"ป "** ** "'" *"*" *T* tป*rซ "** ''' *^*ป "** ^ซ ^* "*"*
17.50 52.50 87.50 122.5 157.5 192.5 227.5
0.000 35.00 70.00 105.0 140.0 175.0 210.0 245.0
NITROGEN
Figure 24. Normalized BaP versus nitrogen.
-------
* ** +** **ปปป+ * **ป***+ #**+ ป*** * ซy *** 4- + * -(- + +
* ' ' * ' " '* **''
3.2 +
2.8 +
2.4 +
N= 29
COR= .327
MEAN
X 20.162
Y .88624
ST.DEV.
12.020
.38263
Petroleum
Solid Line
REGRESSION LINE RES.MS.
X= 10.271*Y+ 11.060 133.83
Y= ,01041#X+ .67642 .13560
B 2.0 +
A
P . A
1.6 +
1.2
.80 + A
.40 +
N= 10
COR=-.081
MEAN
X 28.590
Y 1.0068
ST.DEV.
8.0524
.48273
Alternate
Dashed Line
REGRESSION LINE RES.MS.
X=-1.3445*Y+ 29.944 72.472
Y=-.00483*X+ 1.1450 .26045
*#* "*" '*# * ป "^ ป **' ' *" " * T" m "*" * * '"
5. 15 25 35 45 55 65
0. 10 20 30 40 50 60 70
AROMATIC
Figure 25. Normalized BaP versus aromatics.
-------
!x A(6.6,15.61) !
T O AN 1 \ ,
** + v A(5.1, 9.07) +
\
: \ \ ซ :
2.8 + \ \ +
\ \
\ \
2.4 1 \ \ I
; \ \
A 2.0 + \ \ B +
D B \ \ !
E \\
H \
Y 1.6 + \\ +
^ ฐ \\
E \\ A
A \\B
A A Y
1.2 + \\ ป +
A Vi A
A A \ \
.80 + A AA A ^ -f
A \\ A
Y A \\ A
\ 0
.40 i A y\ +
A A B \ B
\ \
+ A A AA B \ \ +
5. 15 25 35 45 55 65
0. 10 20 30 40 50 60 70
Petroleum
Solid Line
N= 34
COR=-.398
MEAN ST.DEV. REGRESSION LINE RES. MS.
X 21.176 11.500 X=-1.4345*Y+ 23.795 114.73
Y 1.8256 3.1943 Y=-. 11068*X+ 4. 1694 8.8519
Alternate
Dashed Line
N= 9
COR=-.748
MEAN ST.DEV. REGRESSION LINE RES. MS.
X 28.933 8.4629 X=-7.6660*Y+ 37.197 36.067
Y 1.0779 .82565 Y=-.07297ปX+ 3.1891 .34329
AROMATIC
Figure 26. Normalized aldehyde versus aromatics.
-------
... + .... + .X..*..,. + ,,.*+**,***.*. + . .,.*.... + *... + .... + ....-*.... + ....-I-.*.
3.2
2.8
2.4 +
N= 105
COR=-.219
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 46.810 9.8833 X=-5.0690*Y+ 51.851 93.911
Y .99450 .42644 Y=-.00944*X+ 1.4362 .17483
.40
* "*" * *** Tซ "*" ""* *"** * A "*" *** * "*" * * ^ %" * ^*
28 36 44 52 60 68 76
32 40 48 56 64 72 80
CETANE
Alternate
N_ g Dashed Line
COR=-.507
MEAN ST.DEV. REGRESSION LINE RES.MS.
X 43.889 5.2784 X=-5.9836*Y+ 50.672 23.658
Y 1.1336 .44719 Y=-.04295*X-t- 3.0186 .16982
Figure 27. Normalized solubles versus cetane.
-------
.*+
3.2
2.8
2.4
S 2.0
0
L
U
B
L 1.6
^ E
1.2
.80
.40
+
+
+
*
+
+
. B
+ A
!AA A rri
.A "~~ A i
+B A
X
+
^ซ **"***''
X
+
A .
Y
Solubles 1 ^ *
*
*
.
" ป T. ...T. ...+.. ซ.T....*r....T.
'* '' ' '*' ''* ''' ' ซ <
17.50 52.50 87.50 122.5 157.5 192.5 227.5
0.000 35.00 70.00 105.0 140.0 175.0 210.0 245.0
N= 17
COR= .492
Petroleum
Solid Line
MEAN ST.DEV. REGRESSION LINE RES. MS.
X 57.118 74.904 X= 144 ,73*Y-91 .980 4538.4
Y 1.0302 .25442 Y= .00167*X+ .93482 .05236
Alternate
N= 9 Dashed Line
COR= .815
MEAN ST.OEV. REGRESS JON LINE R|S.MS.
X 655 78 768.41 X= 1205.0*Y-931.56 226"1
Y 1 3173 51968 Y= 551E-6*X+ .95590 .10367
NITROGEN
Figure 28. Normalized solubles versus nitrogen.
-------
REFERENCES
1. Federal Register, Vol. 44, No. 23, Part IV, Thursday, February 1, 1979.
2. Smith, L.R., Parness, M.A., Fanick, E.R., and Dietzmann, H.E., "Analytical
Procedures for Characterizing Unregulated Emissions from Vehicles Using
Middle-Distillate Fuels." Interim Report, Contract 68-02-2497, U.S.
Environmental Protection Agency, Office of Research and Development,
April 1980.
3. Bykowski, B.B., "Characterization of Diesel Emissions as a Function of
Fuel Variables." Final Report, Contract 68-03-2707, U.S. Environmental
Protection Agency, Office of Mobile Source Air Pollution Control, April
1981.
4. Hare, C.T., "Methodology for Determining Fuel Effects on Diesel Particulate
Emissions." EPA 650/2-75-056. U.S. Environmental Protection Agency,
. Office of Research and Development, March 1975.
5. Hare, C.T., Springer, K.J., and Bradow, R.L., "Fuel and Additive Effects
on Diesel Particulate-Development and Demonstration of Methodology."
SAE Paper 760130, Detroit, Michigan, February 1976.
6. Hare, C.T., "Characterization of Gaseous and Particulate Emissions from
Light-Duty Diesels Operated on Various Fuels." Final Report Contract
68-03-2440, U.S. Environmental Protection Agency, July 1979.
7. Bykowski, B.B., "Characterization of Diesel Emissions from Operation of a
Light-Duty Diesel Vehicle on Alternate Source Diesel Fuels." Final Report,
Contract 68-03-2884, U.S. Environmental Protection Agency, Office of Mobile
Source Air Pollution Control, November 1981.
8. Federal Register, Vol. 42, No. 124, Tuesday, June 28, 1977.
9. Federal Register, Vol. 45, No. 45, Wednesday, March 5, 1980.
10. Springer, K.J., and Baines, T.M., "Emissions from Diesel Versions of
Production Passenger Cars." SAE Paper 770818, Detroit, Michigan,
September 1977.
11. Levins, P.L., and Kendall, D.A., "Application of Odor Technology to
Mobile Source Emission Instrumentation." CRC Project CAPE 7-68 under
Contract No. 68-03-0561, September 1973.
12. Swarin, S.J., and Williams, R.L., "Liquid Chromatographic Determination
of Benzo(a)pyrene in Diesel Exhaust Particulate: Verification of the
Collection and Analytical Methods," Research Publication GMR-3127,
General Motors Research Laboratories, Warren, Michigan, October 23, 1979.
77
-------
REFERENCES (Conf'd)
13. Ames, B., McCann, J., Yamasaki, E., "Methods for Detecting Carcinogens
and Mutagens with Samonella Mammalian-Microsome Mutagenicity Test."
Mutation Research, 31, pp. 347-364, 1975.
14. Perez, J.M., et al, "Information Report of the Measurement and Charac-
terization of Diesel Exhuast Emissions." CRC-APRAC Project No. CAPI-1-64,
Coordinating Research Council, Inc. Atlanta, Georgia, December 1980.
15. Montalvo, D.A., Bykowski, B.B., "Quality Assurance Project Plan for
Vehicle Emissions from Alternate Diesel Fuels." Work Assignment No. 5
of Contract 68-03-3073, prepared for U.S. Environmental Protection
Agency, June 1982.
16. Springer, K.J., "Investigation of Diesel-Powered Vehicle Emissions VII."
Interim Report, Contract 68-03-2116, U.S. Environmental Protection Agency,
- Office of Mobile Source Air Pollution Control, February 1977.
17. Williams, R.L., and Swarin, S.J., "Benzo(a)pyrene Emissions from Gasoline
and Diesel Automobiles." SAE Paper 790419, Detroit, Michigan, March 1979.
18. Braddock, J.N., and Gabele, P.A., "Emission Patterns of Diesel-Powered
Passenger Cars - Part II, SAE Paper 770168, Cobo Hall, Detroit,
February 28-March 4, 1977.
19. Braddock, J.N., and Bradow, R.L., "Emissions Patterns of Diesel-Powered
Passenger Cars," SAE Paper 750682, Houston, Texas, June 3-5, 1975.
20. Currie, T., and Whyte, R.B., "Broad Cut Fuels for Automotive Diesels."
SAE Paper 811182, Tulsa, Oklahoma, October 19-22, 1981.
21. Seizinger, D.E., Naman, T.M., Marshall, W.F., Clark, C.R. and McClellan, R.O.,
"Diesel Particulates and Bioassay Effect of Fuels, Vehicles, and Ambient
Temperature." SAE Paper 820813, Troy, Michigan, June 7-10, 1982
22. Burley, H.A., and Rosebrock, T.L., "Automotive Diesel Engines-Fuel Com-
position vs Particulates", SAE Paper 790923, Houston, Texas, Oct. 1-4,1979.
23. Bouffard, R.A., and Beltzer, M., "Light-Duty Diesel Particulate Emissions -
Fuel and Vehicle Effects", SAE Paper 811191, Tulsa, OK, Oct. 19-22, 1981.
24. Montalvo, D.A., Hare, C.T., "Characterization of Emissions from Advanced
Automotive Power Plant Concepts." Draft Final Report, Contract 68-02-2703,
U.S. Environmental Protection Agency, Mobile Source Emissions Research
Branch, Submitted July 19, 1982.
25. Nie, Norman, H., Hull, C. Hadlai, Jenkins, Jean G., Steinbrenner, Karin,
and Bent, Dale H., "SPSS", McGraw-Hill, New York, New York, 1975.
26. Health Sciences Computing Facility, "BMDP Biomedical Computer Programs,
P-Series 1979", University of California Press, Los Angeles, CA, 1979.
78
-------
APPENDIX A
SCOPE OF WORK
WORK ASSIGNMENT NO. 5
CONTRACT 68-03-3073
-------
WORK ASSIGNMENT NO. 5
VEHICLE EMISSIONS FROM ALTERNATE DIESEL FUELS
Scope of Work
Objective: The area of transportation fuels is currently a very dynamic
area. There are some problems with the long term outlook for conventional
petroleum supplies and for this reason alternate sources of transportation
fuels are actively being sought. However, most research into this area is
being done in the area of processes and not in end-use emissions.
It is therefore one objective of this work to operate a light duty vehicle
on three alternate source fuels and analyze its emissions for a variety of
pollutants. The vehicle to be used will be the same Volkswagen previously
tested on which a complete baseline exists.
The second and most important objective of this work is to analyze statisti-
cally the fuels data obtained. The data derived from the first part of this
task will be combined with that derived previously from the use of different
alternate source fuels in the same vehicle (the VW). The combined data will
then be statistically analyzed to detect trends in emissions as a function
of fuel properties. The data will be compared to data taken from vehicles
operated on petroleum based fuels.- This comparison will be made to see if
the changes observed in the emissions from the vehicle operated with
alternate source fuels are significantly different from the changes one
would expect based on the knowledge derived from this previous work on
petroleum fuels.
Task I - Obtain Representative Fuels
The contractor shall obtain test quantities of up to three suitable fuels in
accordance with the Project Officers technical direction. It is expected
that EPA shall do much of the initial work to locate suitable fuels, but the
contractor should be prepared to follow-up the acquisition efforts with re-
gards to shipping and receiving the candidate fuels. Also, the contractor
should be prepared to expend effort toward contacting potential sources of
alternate fuels upon the direction of the Project Officer.
A-2
-------
APPENDIX B
TEST VEHICLE BASELINE CHECK
-------
CFTP - VEHICLE EMISSIONS RESULTS -VW CHECKOUT
PROJECT 05-6619-005
TEST NO. 329X01 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 746.25 MM HG(29.38 IN HG)
RELATIVE HUMIDITY 54. PCT
BAG RESULTS
BAG NUMBER
DESCRIPTION
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. CCDEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC 8CKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
tfl
I
M
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
THC
CO
CO 2
NOX
GRAMS/KM
GRAMS/KM
GRAMS/KM
GRAMS/KM
FUEL CONSUMPTION BY CB L/1OOKM
RUN TIME SECONDS
MEASURED DISTANCE KM
SCF, DRY
DFC, WET (DRY)
TOT VOL (SCM) / SAM BLR (SCM)
KM (MEASURED)
FUEL CONSUMPTION L/1OOKM
COMPOSITE RESULTS
TEST NUMBER 329X01
BAROMETER MM HG 746.3
HUMIDITY G/KG 9.5
TEMPERATURE DEG C 22.8
VEHICLE N0.1
DATE 1 I/ 3/82
BAG CART NO. 1 / CVS NO.
DYNO NO. 2
17
TEST WEIGHT 1021
ACTUAL ROAD LOAD
DIESEL EM-329-F
ODOMETER 4535. KM(
KG(
5.4
2250. LBS)
KW( 7.3 HP)
2818. MILES)
DRY BULB TEMP. 22.8 DEG CC73.0 DEG F)
ABS. HUMIDITY 9.5 GM/KG
NOX HUMIDITY CORRECTION FACTOR .96
1
OLD TRANSIENT
914.4 (36.0)
889.0 (35.0)
40.6 (105.0)
4989.
147.0 ( 5192.)
31.4/11/ 31.
3.0/ I/ 3.
49. 4/1 3/ 47.
.9/13/ 1.
59.4/1 I/ .4888
7.3/1 I/ .0437
15. I/ 2/ 15.1
.4/ 2/ .4
26.33
29.
45.
.4467
14.7
3.700 (99.)
2.44
7.62
1202.6
3.98
2.53
.42
1.32
208.6
.69
8.06
505.
5.77
.978
2
STABILIZED
914.4 (36.0)
889.0 (35.0)
45.0 (113.0)
8574.
250.1 ( 8833.)
11.4/11/ 11.
2.9/ I/ 3.
20.3/13/ 18.
1.2/13/ 1.
63.1/12/ .2567
11.8/12/ .0400
10. 2/ 2/ 10.2
.4/ 2/ .4
50.35
9.
17.
.2174
9.8
1.997 (96.)
1.24
4.96
995.8
4.51
1.33
.20
.80
160.0
.72
6.15
867.
6.22
.979 .980
.973( .957)
397.
1
2/ 78.15
1.99
7.07
CARBON
3
HOT TRANSIENT
914.4 (36.0)
889.0 (35.0)
38.3 (101.0)
4987.
147.8 ( 5218.)
26. 3/1 I/ 26.
2.9/ I/ 3.
43.6/13/ 41.
.4/13/ 0.
82.9/12/ .3611
11.9/12/ .0404
14. 4/ 2/ 14.4
.4/ 2/ .4
35.54
23.
39.
.3219
14.0
2.786 (98.)
2.02
6.78
871.1
3.81
1.89
.35
1.17
150.1
.66
5.82
504.
5.80
.979 .980
.977( .
4
STABILIZED
914.4 (36.0)
889.0 (35.0)
37.8 (100.0)
8574.
254.4 ( 8984.)
11.7/11/ 12.
2.8/ I/ 3.
20.9/13/ 19.
.6/13/ 1.
61. 4/1 2/ .2483
11.5/12/ .0389
10. I/ 2/ 10.1
.3/ 2/ .3
52.00
9.
18.
.2101
9.8
1.911 (97.)
1.33
5.36
978.9
4.59
1.32
.21
.85
155.8
.73
6.00
867.
6.28
.980
961)
402. 2/ 78.12
12.09
5.91
DIOXIDE G/KM
FUEL CONSUMPTION L/1 OOKM
HYDROCARBONS (THC) G/KM
CARBON
OXIDES
MONOXIDE G/KM
OF NITROGEN G/KM
PARTI CULATES G/KM
3-BAG (4-BAG)
167.3 ( 166.1)
6.45 ( 6.41)
.29 ( .29)
1.01 ( 1.02)
.70 ( .70)
.291 ( .290)
-------
C505 - VEHICLE EMISSIONS RESULTS *VW CHECKOUT
PROJECT 35-66}9-005
TEST NO. 329X02 RUN 2
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 752.60 MM HG(29.63
RELATIVE HUMIDITY 82. PCT
BAG RESULTS
TEST CYCLE
IN HG)
ro
i
U)
BLOWER DIF P MM. H20UN. H20)
3LOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, OEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
VEHICLE N0.1
DATE 11/ 4/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 23.3 DEG CC74.0 DEG F)
ABS. HUMIDITY 15.0 GM/KG
C505
914.4 (36.0)
389.0 (35.0)
39.4 (103.0)
4994.
150.0 ( 5295.)
25.9/1 I/ 26.
4.1/ I/ 4.
46.9/13/ 44.
5.9/13/ 5.
90.9/12/ .4082
12.8/12/ .0436
15.9/ 2/ 15.9
.7/ 2/ .7
31.49
22.
38.
.3660
15.2
2.906 (98.)
1.92
6.55
1004.9
5.08
1.92
505.
.968 ( .943)
1.000 ( .969)
150.0
29.94
5.75
329X02
752.6
15.0
23.3
174.8
6.75
.33
1.14
.88
.334
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EMi329iF
ODOMETER 4561. KM( 2834. MILES)
NOX HUMIDITY CORRECTION FACTOR 1.16
-------
APPENDIX C
GASEOUS AND PARTICULATE EMISSION RESULTS
-------
TEST NO. 527F01 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 745.74 MM HGC29.36 IN HG)
RELATIVE HUMIDITY 59. PCT
BAG RESULTS
BAG NUMBER
DESCRIPTION
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DlLUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
O
I
K>
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
THC GRAMS/KM
CO GRAMS/KM
CO2 GRAMS/KM
NOX GRAMS/KM
FUEL CONSUMPTION BY CB L/100KM
RUN TIME SECONDS
MEASURED DISTANCE KM
SCF, DRY
DFC, WET (DRY)
TOT VOL (SCM) / SAM BLR (SCM)
KM (MEASURE?)
FUEL CONSUMPTION L/100KM
COMPOSITE RESULTS
TEST NUMBER 527F01
BAROMETER MM HG 745.7
HUMIDITY G/KG 11.6
TEMPERATURE DEG C 24.4
FTP - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 1 I/ 9/82
BAG CART NO. 1 / CVS NO. 17
DYNO NO. 2
DRY BULB TEMP. 24.4 DEG C(76.0 DEG F)
ABS. HUMIDITY 11.6 GM/KG
1
lOLD TRANSIENT
914.4 (36.0)
889.0 (35.0)
34.4 ( 94.0)
4992.
149.6 ( 5282.)
36.1/11/ 36.
6.0/ I/ 6.
51.5/13/ 49.
2.5/13/ 2.
91.3/12/ .4106
12.9/12/ .0439
14. O/ 2/ 14.0
1.3/ 2/ 1.3
31.10
30.
45.
.3681
12.7
2.611 (98.)
2.64
7.88
1008.2
3.75
'.81
.46
1.36
174.6
.65
7.06
505.
5.77
2
STABILIZED
914.4 (36.0)
889.0 (35.0)
35.0 ( 95.0)
8572.
256.5 ( 9053.)
14.1/11/ 14.
5.8/ I/ 6.
22.7/13/ 21.
2.3/13/ 2.
62.3/12/ .2527
13.0/12/ .0443
9.0/ 2/ 9.0
.9/ 2/ .9
50.87
8.
18.
.2093
8.1
1.578 (99.)
1.26
5.44
983.0
4.10
1.06
.20
.87
156.6
.65
6.28
868.
6.28
.977 .978 .978
.976(
406. I/
12.
6.
.957)
78.17
05
66
TEST WEIGHT 1021. KG ( 2250. LBS}
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-527-F
ODOMETER 4625. KM( 2874. MILES)
NOX HUMIDITY CORRECTION FACTOR 1.03
HOT TRANSIENT
914.4 (36.0)
8'89.0 (35.0)
36.1 ( 97.0)
4990.
148.9 ( 5258.)
31.9/11/ 32.
5.8/ I/ 6.
45.8/13/ 43.
1.8/13/ 2.
82.8/12/ .3606
13.0/12/ .0443
13.I/ 2/ 13.1
.7/ 2/ .7
35.41
26.
40.
.3175
12.4
1.988 (99.)
2.28
6.98
865.8
3.64
1.35
.39
1.21
149.8
.63
6.06
STABILIZED
914.4 (36.0)
889.0 (35.0)
37.2 ( 99.0)
8576.
255.3 ( 9013.)
13.4/11/ 13.
5.4/ I/ 5.
21.5/13/ 20.
2.3/13/ 2.
61.1/12/ .2469
12.9/12/ .0439
9.0/ 2/ 9.0
.It 2/ .7
52.09
8.
17.
.2038
8.3
1.470 (97.)
1.21
5.09
952.3
4.18
.98
.19
.82
152.5
.67
6.12
505. 868.
5.78 6.24
.977 .978 .978
.977( .959)
404.2/ 78.14
12.03
6.09
CARBON DIOXIDE G/KM
FUEL CONSUMPTION L/100KM
HYDROCARBONS (THC) G/KM
CARBON MONOXIDE G/KM
OXIDES OF NITROGEN G/KM
PARTICULATES G/KM
3-BAG
158.5
6.38
.31
1.06
.65
.216
(4-BAG)
( 157.2)
( 6.33)
( .30)
( 1.05)
( .65)
( .213)
-------
TEST NO. 527H02 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 745.49 MM HG(29.35 IN HG)
RELATIVE HUMIDITY 56. PCT
BAG RESULTS
TEST CYCLE
BLOWER OIF P MM. H20UN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DE6. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METKES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY. %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
O
I
LO
TEST NUMBER,
BAROMETER,
HUMIDITY,
TEMPERATURE,
CARBON DIOXIDE,
FUEL CONSUMPTION,
MM HG
G/KG
DEC C
G/KM
L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
HFET - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 1 I/ 9/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.0 DEC C(77.0 DEG F)
ABS. HUMIDITY 11.3 GM/KG
HFET
927.1 (36.5)
889.0 (35.0)
38.3 (101.0)
7560.
223.6 ( 7895.)
34.0/11/ 34.
5.2/ I/ 5.
83.0/13/ 83.
1.6/13/ 1.
66.7/1 I/ .5724
7.4/1 I/ .0444
23.3/ 2/ 23.3
.?/ 2/ .7
22.32
29.
79.
.5300
22.6
5.691 (99.)
3.78
20.50
2169.8
9.88
4.07
765.
.955 ( .938)
1.000 ( .976)
223.6
42.73
16.39
527H02
745.5
11.3
25.0
132.4
5.35
.23
1.25
.60
.248
TEST WEIGHT 1021.
ACTUAL ROAD LOAD
DIESEL EM-527-F
ODOMETER 4649. KM(
KG(
5.4
2250. LBS)
KW( 7.3 HP)
2889. MILES)
NOX HUMIDITY CORRECTION FACTOR 1.02
-------
n
i
TEST NO. 527103 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 745.49 MM HG(29.35 IN HG)
RELATIVE HUMIDITY 53. PCT
BAG RESULTS
TEST CYCLE
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PI'M
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEG C
CARBON DI OX IDF, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
IDLE - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 1 I/ 9/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.6 DEG C(78.0 DEG F)
ABS. HUMIDITY 11.1 GM/KG
IDLE
927.1 (36.5)
889.0 (35.0)
37.8 (100.0)
1 1864.
351.3 (12405.)
7.6/11/ 8.
5.I/ I/ 5.
8.4/13/ 8.
1.1/13/ 1.
50.8/13/ .1003
22.9/13/ .0423
3.4/ 2/ 3.4
.7/ 2/ .7
127.94
3.
6.
.0583
2.7
.175 (85.)
.52
2.65
375. 1
1.84
.14
1201.
.992 ( .975)
1.000 ( .982)
351.3
66.81
527 I 03
745.5
11.1
25.6
TEST WEIGHT 1021.
ACTUAL ROAD LOAD
DIESEL EM-527-F
ODOMETER 4667. KM(
KG(
5.4
2250. LBS)
KW( 7.3 HP)
2900. MILES)
NOX HUMIDITY CORRECTION FACTOR 1.01
-------
TEST NO. 527504 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSI ON M4
BAROMETER 744.73 MM HG(29.32 IN HG)
RELATIVE HUMIDITY 52. PCT
BAG RESULTS
TEST CYCLE
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
n
i
Ln
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
50 KM - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 1t/ 9/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.0 DEG C(77.0 DEG F)
ABS. HUMIDITY 10.6 GM/KG
50 KM
927.1 (36.5)
889.0 (35.0)
36.7 ( 98.0)
5939.
175.9 ( 6210.)
16.1/11/ 16.
5.0/ I/ 5.
25.7/13/ 24.
1.1/13/ 1.
79.8/12/ .3438
12.9/12/ .0439
13.6/ 2/ 13.6
.6/ 2/ .6
37.48
1 1.
22.
.3010
13.0
1.714 (97.)
1. 16
4.51
969.2
4.37
1.16
601.
.973 ( .957)
1.000 ( .980)
175.9
33.27
8.33
527504
744.7
10.6
25.0
1 16.3
4.66
.14
.54
.52
.139
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-527-F
ODOMETER 4667. KM( 2900. MILES)
NOX HUMIDITY CORRECTION FACTOR 1.00
-------
TEST NO. 527805 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 741.93 MM HG(29.21 IN HG)
RELATIVE HUMIDITY 50. PCT
BAG RESULTS
TEST CYCLE
BLOWER OIF P MM. H20CIN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEC. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
n
i
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
85 KM - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/ 9/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.6 DEG C(78.0 DEG F)
ABS. HUMIDITY 10.4 GM/KG
85 KM
927.1 (36.5)
889.0 (35.0)
41.7 (107.0)
5933.
172.9 ( 6104.)
38.0/1 I/ 38.
4.9/ I/ 5.
99.3/13/ 101.
.6/13/ 1.
70.9/11/ .6234
7.3/1 I/ .0437
26.6/ 2/ 26.6
,6/ 2/ .6
20.45
33.
98.
.5818
26.0
4.313 (99.)
3.36
19.71
1841.5
8.53
3.80
600.
.951 ( .936)
1.000 ( .978)
172.9
33.00
14.24
TEST WEIGHT 1021.
ACTUAL ROAD LOAD
DIESEL EM-527-F
ODOMETER 4677. KM(
KG (
5.4
2250. LBS )
KW( 7.3 HP)
2906. MILES)
NOX HUMIDITY CORRECTION FACTOR
.99
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
527805
741.9
10.4
25.6
129.3
5.24
.24
1.38
.60
.267
-------
FTP - VEHICLE EMISSIONS RESULTS
PROJECT 05-6619-005
TEST NO. 527F06 RUN 2
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 746.25 MM HG(29.38 IN HG)
RELATIVE HUMIDITY 60. PCT
BAG RESULTS
BAG NUMBER
DESCRIPTION
BLOWER OIF P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
O THC CONCENTRATION PPM
^, CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
THC
CO
CO 2
NOX
GRAMS/KM
GRAMS/KM
GRAMS/KM
GRAMS/KM
FUEL CONSUMPTION BY CB L/100KM
RUN TIME SECONDS
MEASURED DISTANCE KM
SCF, DRY
DFC, WET (DRY)
TOT VOL (SCM) / SAM BLR (SCM)
KM (MEASURED)
FUEL CONSUMPTION L/100KM
COMPOSITE RESULTS
TEST NUMBER 527F06
BAROMETER MM HG 746.3
HUMIDITY G/KG 12.1
TEMPERATURE DEG C 25.0
VEHICLE N0.1
DATE 11/10/82
BAG CART NO. 1 / CVS NO.
DYNO NO. 2
17
DRY BULB TEMP. 25.0 DEG C(77.0 DEG F)
ABS. HUMIDITY 12.1 GM/KG
1
COLD TRANSIENT
914.4 (36.0)
889.0 (35.0)
38.3 (101.0)
4991.
148.2 ( 5232.)
21.7/12/ 43.
6.0/ I/ 6.
55.5/13/ 53.
1.5/13/ 1.
91.6/12/ .4125
13.2/12/ .0450
12.8/ 2/ 12.8
.5/ 2/ .5
30.88
38.
50.
.3689
12.3
2.983 (99.)
3.25
8.64
1000.8
3.65
1.99
.56
1.50
173.3
.63
7.03
505.
5.78
.977 .978
.976( .
402.1/ 78.05
12.07
6.60
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-527-F
ODOMETER 4688. KM( 2913. MILES)
NOX HUMIDITY CORRECTION FACTOR 1.05
2
STABILIZED
914.4 (36.0)
889.0 (35.0)
39.4 (103.0)
8576.
253.9 ( 8966.)
7.4/12/ 15.
5.8/ I/ 6.
22.7/13/ 21.
1.8/13/ 2.
62.3/12/ .2527
13.0/12/ .0443
8.4/ 2/ 8.4
.5/ 2/ .5
50.85
9.
19.
.2093
7.9
1.632 (98.)
1.34
5.51
973.1
4.02
1.08
.21
.88
154.5
.64
6.20
868.
6.30
.978
3
HOT TRANSIENT
914.4 (36.0)
889.0 (35.0)
41.7 (107.0)
4993.
147.0 ( 5192.)
15.8/12/ 32.
5.8/ I/ 6.
45.4/13/ 43.
1.0/13/ 1.
83.3/12/ .3634
13.1/12/ .0446
12. 3/ 2/ 12.3
.5/ 2/ .5
35.15
26.
41.
.3201
11.8
2.059 (98.)
2.22
6.94
861.6
3.48
1.37
.38
1.20
149.2
.60
6.03
505.
5.78
.977 .978
4
STABILIZED
914.4 (36.0)
889.0 (35.0)
40.0 ( 104.0)
8579.
253.7 ( 8957.)
6.2/12/ 12.
5.4/ I/ 5.
21.0/13/ 19.
1.4/13/ 1.
61.2/12/ .2474
13.2/12/ .0450
8.4/ 2/ 8.4
.5/ 2/ .5
52.03
7.
17.
.2032
7.9
1.469 (97.)
1.04
5.15
943.8
4.02
.98
.17
.82
150.4
.64
6.03
868.
6.27
.978
>7) .977( .959)
05
CARBON
400. 7/ 78
12.05
6.03
DIOXIDE G/KM
FUEL CONSUMPTION L/100KM
HYDROCARBONS (THC) G/KM
CARBON
OXIDES
MONOXIDE G/KM
OF NITROGEN G/KM
PARTICULATES G/KM
.05
3-BAG (4-BAG)
156.9 ( 155.7)
6.32 ( 6.27)
.33 ( .32)
1.09 ( 1.08)
.63 ( .63)
.225 { .220)
-------
TEST NO. 527H07 RUN 2
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 745.49 MM H6(29.35 IN HG)
RELATIVE HUMIDITY 55. PCT
BAG RESULTS
TEST CYCLE
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C
-------
TEST NO. 526F01 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 747.78 MM H6(29.44 IN HG)
RELATIVE HUMIDITY 25. PCT
BAG RESULTS
BAG NUMBER
DESCRIPTION
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
O
I
TriC GRAMS/KM
CO GRAMS/KM
C02 GRAMS/KM
NOX GRAMS/KM
FUEL CONSUMPTION BY CB L/100KM
RUN TIME SECONDS
MEASURED DISTANCE KM
SCF, DRY
DFC, WET (DRY)
TOT VOL (SCM) / SAM BLR (SCM)
KM (MEASURED)
FUEL CONSUMPTION L/100KM
COMPOSITE RESULTS
TEST NUMBER 526F01
BAROMETER MM HG 747.8
HUMIDITY G/KG 4.6
TEMPERATURE DEG C 23.9
FTP - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/12/82
BAG CART NO. 1 / CVS NO. 17
DYNO NO. 2
DRY BULB TEMP.
ABS. HUMIDITY
23.9 DEG C(75.0 DEG F)
4.6 GM/KG
1
OLD TRANSIENT
939.8 (37.0)
914.4 (36.0)
35.0 ( 95.0)
4982.
148.9 ( 5258.)
16.7/12/ 33.
3.0/ I/ 3.
48.8/13/ 46.
1.2/13/ 1.
94.7/12/ .4318
12.3/12/ .0418
18. 5/ 2/ 18.5
.6/ 2/ .6
30.67
31.
44.
.3914
17.9
4.005 (99.)
2.62
7.66
1067.0
4.25
2.78
.45
1.32
183.4
.73
6.83
504.
5.82
2
STABILIZED
927.1 (36.5)
889.0 (35.0)
36.1 ( 97.0)
8566.
256.2 ( 9045.)
9.7/12/ 19.
3.0/ I/ 3.
23.8/13/ 22.
1.2/13/ 1.
63.8/12/ .2601
12.3/12/ .0418
12. O/ 2/ 12.0
.7/ 2/ .7
51.04
16.
20.
.2191
11.3
2.278 (97.)
2.43
6.08
1027.8
4.62
1.59
.38
.96
161.7
.73
6.00
867.
6.36
.988 .989 .990
.976(
405. I/
12.
6.
.968)
78.27
17
40
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-526-F
ODOMETER 4801. KM( 2983. MILES)
NOX HUMIDITY CORRECTION FACTOR
.83
HOT TRANSIENT
927.1 (36.5)
889.0 (35.0)
36.1 ( 97.0)
4988.
149.2 ( 5267.)
13.7/12/ 27.
3.0/ 1/ 3.
46.6/13/ 44.
1.4/13/ 1.
84.9/12/ .3726
11.9/12/ .0404
17.7/ 2/ 17.7
.5/ 2/ .5
35.52
24.
42.
.3334
17.2
2.693 (99.)
2.10
7.27
910.4
4.09
1.87
.36
1.25
157.0
.71
5.85
STABILIZED
927.1 (36.5)
889.0 (35.0)
36.7 ( 98.0)
8570.
255.9 ( 9037.)
7.5/12/ 15.
2.8/ 2/ 6.
26.0/13/ 24.
1.4/13/ 1.
62.9/12/ .2557
12.3/12/ .0418
11.8/ 2/ 11.8
.6/ 2/ .6
51.96
10.
22.
.2147
11.2
1.687 (96.)
1.40
6.63
1005.9
4.57
1.17
.22
1.04
157.1
.71
5.82
505. 867.
5.80 6.40
.989 .989 .990
.977( .970)
405.1/ 78.30
12.20
5.83
CARBON DIOXIDE G/KM
FUEL CONSUMPTION L/100KM
HYDROCARBONS (THC) G/KM
CARBON MONOXIDE G/KM
OXIDES OF NITROGEN G/KM
PART ICULATES G/KM
3-BAG
164.9
6.13
.39
1.11
.72
.316
(4-BAG)
( 163.5)
( 6.08)
( .34)
( 1.13)
( .72)
( .296)
-------
TEST NO. 526H02 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 747.78 MM HGC29.44 IN HG)
RELATIVE HUMIDITY 24. PCT
BAG RESULTS
TEST CYCLE
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. CCDEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
o
I
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
HFET - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/12/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.0 DEG C(77.0 DEG F)
ABS. HUMIDITY 4.8 GM/KG
HFET
965.2 (38.0)
939.8 (37.0)
36.7 ( 98.0)
7565.
223.8 ( 7902.)
26.0/12/ 52.
3.0/ 1/ 3.
81.3/13/ 81.
.2/13/ 0.
70.2/11/ .6148
6.8/1 I/ .0406
36.2/ 2/ 36.2
1.9/ 2/ 1.9
21.48
49.
79.
.5761
34.4
7.071 (99.)
6.33
20.55
2360.2
12.30
5.19
766.
.953 ( .946)
1.000 ( .987)
223.8
42.94
16.55
526H02
747.8
4.8
25.0
142.6
5.32
.38
1.24
.74
.314
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-526-F
ODOMETER 4826. KM( 2999. MILES)
NOX HUMIDITY CORRECTION FACTOR
.84
-------
TEST NO. 526103 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CIO) L-4
TRANSMISSION M4
BAROMETER 748.03 MM HG(29.45 IN HG)
RELATIVE HUMIDITY 26. PCT
BAG RESULTS
TEST CYCLE
BLOWER OIF P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
O
I
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
IDLE - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/12/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 24.4 DEG C(76.0 DEG F)
ABS. HUMIDITY 5.0 GM/KG
IDLE
927.1 (36.5)
889.0 (35.0)
36.1 ( 97.0)
11864.
354.1 (12502.)
20.7/11/ 21.
3.2/ 1/ 3.
22.6/13/ 21.
.5/13/ 0.
47.1/13/ .0924
20.6/13/ .0378
4.8/ 2/ 4.8
1.7/ 2/ 1.7
139.69
18.
20.
.0549
3.1
.445 (83.)
3.58
8.23
355.9
1.77
.37
1200.
.993 ( .985)
1.000 ( .991)
354.1
67.29
5.00
526103
748.0
5.0
24.4
71.2
2.78
.72
1.65
.35
.074
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-526-F
ODOMETER 4844. KM( 3010. MILES)
NOX HUMIDITY CORRECTION FACTOR .84
-------
TEST NO. 526504 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 748.28 MM H6(29.46 IN HG)
RELATIVE HUMIDITY 27. PCT
BAG RESULTS
TEST CYCLE
BLOWER OIF P MM. H20(IN. H20)
BLOWER INLET P MM. H20CIN. H20)
BLOWER INLET TEMP. DEC. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RAN6E/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
O
I
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEC C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
50 KPH- VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/12/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.0 DEG C(77.0 DEG F)
ABS. HUMIDITY 5.3 GM/KG
50 KPH
927.1 (36.5)
889.0 (35.0)
36.7 ( 98.0)
5934.
176.8 ( 6242.)
16.9/12/ 34.
3.0/ 1/ 3.
35.1/13/ 32.
.1/13/ 0.
80.1/12/ .3454
11.8/12/ .0400
16.9/ 2/ 16.9
1.4/ 2/ 1.4
38.31
31.
32.
.3065
15.5
2.178 (96.)
3.14
6.56
991.8
4.46
1.50
600.
.974 ( .965)
1.000 ( .988)
176.8
33.92
8.35
526504
748.3
5.3
25.0
1 18.7
4.42
.38
.79
.53
.179
TEST WEIGHT 1021. KG ( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-526-F
ODOMETER 4844. KM( 3010. MILES)
NOX HUMIDITY CORRECTION FACTOR .85
-------
TEST NO. 526805 RUN 1
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 748.54 MM HG(29.47 IN HG)
RELATIVE HUMIDITY 24. PCT
BAG RESULTS
TEST CYCLE
BLOWER OIF P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEC. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
n
i
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
TEST NUMBER,
BAROMETER, MM HG
HUMIDITY, G/KG
TEMPERATURE, DEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
85 KPH- VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/12/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 25.0 DEG C(77.0 DEG F)
ABS. HUMIDITY 4.7 GM/KG
85 KPH
927.1 (36.5)
889.0 (35.0)
39.4 (103.0)
5933.
175.5 ( 6197.)
26.2/12/ 52.
3.0/ 1/ 3.
81.1/13/ 80.
.5/13/ 0.
74.8/11/ .6729
6.9/11/ .0412
38.4/ 2/ 38.4
1.4/ 2/ 1.4
19.66
50.
78.
.6338
37.1
5.845 (99.)
5.00
16.00
2036.3
10.40
4.41
600.
.949 ( .942)
1.000 ( .986)
175.5
33.81
14.24
526805
748.5
4.7
25.0
143.0
5.33
.35
1.12
.73
.309
TEST WEIGHT 1021.
ACTUAL ROAD LOAD
DIESEL EM-526-F
ODOMETER 4854. KM(
KG(
5.4
2250. LBS)
KW( 7.3 HP)
3016. MILES)
NOX HUMIDITY CORRECTION FACTOR .84
-------
TEST NO. 526F06 RUN 2
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CIO) L-4
TRANSMISSION M4
BAROMETER 753.87 MM HGC29.68 IN HG)
RELATIVE HUMIDITY 16. PCT
BAG RESULTS
BAG NUMBER
DESCRIPTION
BLOWER 01F P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEG. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, *)
THC MASS GRAMS
n
i
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
THC
CO
CO 2
NOX
GRAMS/KM
GRAMS/KM
GRAMS/KM
GRAMS/KM
FUEL CONSUMPTION BY CB L/100KM
RUN TIME SECONDS
MEASURED DISTANCE KM
SCF, DRY
DFC, WET (DRY)
TOT VOL (SCM) / SAM BLR (SCM)
KM (MEASURED)
FUEL CONSUMPTION L/100KM
COMPOSITE RESULTS
TEST NUMBER 526F06
BAROMETER MM HG 753.9
HUMIDITY G/KG 2.9
TEMPERATURE DEG C 23.9
FTP - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/15/82
BAG CART NO. 1 / CVS NO. 17
DYNO NO. 2
DRY BULB TEMP. 23.9 DEG C(75.0 DEG F)
ABS. HUMIDITY 2.9 GM/KG
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-526-F
ODOMETER 4881. KM( 3033. MILES)
NOX HUMIDITY CORRECTION FACTOR .80
1
:OLD TRANSIENT
927.1 (36.5)
914.4 (36.0)
42.8 (109.0)
4989.
148.3 ( 5237.)
20.1/12/ 40.
4.0/ I/ 4.
48.8/13/ 46.
1.2/13/ 1.
94.7/12/ .4318
12.3/12/ .0418
18. 5/ 2/ 18.5
.6/ 2/ .6
30.62
36.
44.
.3914
17.9
3.597 (99.)
3.10
7.65
1062.6
4.04
2.39
.54
1.33
184.7
.70
6.88
505.
5.75
2
STABILIZED
939.8 (37.0)
927.1 (36.5)
36.7 ( 98.0)
8576.
258.2 ( 9118.)
7.9/12/ 16.
6.0/ 1/ 6.
23.8/13/ 22.
1.2/13/ 1.
63.8/12/ .2601
12.3/12/ .0418
12. O/ 2/ 12.0
.7/ 2/ .7
51.11
10.
20.
.2191
11.3
1.741 (97.)
1.48
6.15
1036.0
4.45
1.21
.24
.98
165.8
.71
6.14
867.
6.25
.991 .992 .993
.976(
406. 5/
12.
6.
.971)
80.25
00
50
CARBON
3
HOT TRANSIENT
927.1 (36.5)
914.4 (36.0)
36.1 ( 97.0)
4991.
150.7 ( 5322.)
14.0/12/ 28.
6.0/ 1/ 6.
46.6/13/ 44.
1.4/13/ 1.
84.9/12/ .3726
11.9/12/ .0404
17. 7/ 2/ 17.7
.5/ 2/ .5
35.51
22.
42.
.3334
17.2
1.906 (97.)
1.92
7.37
920.0
3.95
1.30
.33
1.27
159.1
.68
5.92
505.
5.78
4
STABILIZED
927.1 (36.5)
914.4 (36.0)
36.1 ( 97.0)
8576.
259.0 ( 9146.)
7.3/12/ 15.
6.0/ 1/ 6.
26.0/13/ 24.
1.4/13/ 1.
62.9/12/ .2557
12.3/12/ .0418
11. 8/ 2/ 1 1.8
.6/ 2/ .6
51.97
9.
22.
.2147
11.2
2.867 (98.)
1.31
6.73
1018.1
4.42
1.99
.21
1.07
161.8
.70
5.99
868.
6.29
.992 .992 .993
.977(
409. 7/
12.
5.
DIOXIDE G/KM
FUEL CONSUMPTION L/100KM
HYDROCARBONS (THC) G/KM
CARBON
OXIDES
MONOXIDE G/KM
OF NITROGEN G/KM
PARTICULATES G/KM
.973)
80.19
08
96
3-BAG (4-BAG)
167.8 ( 166.7)
6.23 ( 6.19)
.32 ( .32)
1.13 ( 1.16)
.70 { .70)
.248 ( .284)
-------
TEST NO. 526H07 RUN 2
VEHICLE MODEL 80 VW RABBIT
ENGINE 1.5 L( 90. CID) L-4
TRANSMISSION M4
BAROMETER 752.60 MM HGC29.63 IN HG)
RELATIVE HUMIDITY 19. PCT
BAG RESULTS
TEST CYCLE
BLOWER DIP P MM. H20(IN. H20)
BLOWER INLET P MM. H20(IN. H20)
BLOWER INLET TEMP. DEC. C(DEG. F)
BLOWER REVOLUTIONS
TOT FLOW STD. CU. METRES(SCF)
THC SAMPLE METER/RANGE/PPM
THC BCKGRD METER/RANGE/PPM
CO SAMPLE METER/RANGE/PPM
CO BCKGRD METER/RANGE/PPM
C02 SAMPLE METER/RANGE/PCT
C02 BCKGRD METER/RANGE/PCT
NOX SAMPLE METER/RANGE/PPM
NOX BCKGRD METER/RANGE/PPM
DILUTION FACTOR
THC CONCENTRATION PPM
CO CONCENTRATION PPM
C02 CONCENTRATION PCT
NOX CONCENTRATION PPM
FILTER WT. MG (EFFICIENCY, %)
THC MASS GRAMS
CO MASS GRAMS
C02 MASS GRAMS
NOX MASS GRAMS
PARTICULATE MASS GRAMS
RUN TIME SECONDS
DFC, WET (DRY)
SCF, WET (DRY)
VOL (SCM)
SAM BLR (SCM)
KM (MEASURED)
o
I
TEST NUMBER,
BAROMETER, MM HG
HUMIOITY, G/KG
TEMPERATURE, DEG C
CARBON DIOXIDE, G/KM
FUEL CONSUMPTION, L/100KM
HYDROCARBONS, (THC) G/KM
CARBON MONOXIDE, G/KM
OXIDES OF NITROGEN, G/KM
PARTICULATES, G/KM
HFET - VEHICLE EMISSIONS RESULTS -
PROJECT 05-6619-005
VEHICLE N0.1
DATE 11/15/82
BAG CART NO. 1
DYNO NO. 2
CVS NO. 17
DRY BULB TEMP. 23.9 DEG C(75.0 DEG F)
ABS. HUMIDITY 3.5 GM/KG
HFET
927.1 (36.5)
889.0 (35.0)
37.2 ( 99.0)
7565.
227.0 ( 8014.)
28.2/12/ 56.
7.0/ 1/ 7.
85.0/13/ 85.
1.8/13/ 2.
69.8/11/ .6099
7.0/11/ .0419
34.7/ 2/ 34.7
.5/ 2/ .5
21.62
50.
82.
.5699
34.2
7.761*(99.)
6.48
21.61
2368.3
1 1.99
5.65
765.
.954 ( .948)
1.000 ( .988)
227.0
43.48
16.54
526H07
752.6
3.5
23.9
143.2
5.35
.39
1.31
.73
.342
TEST WEIGHT 1021. KG( 2250. LBS)
ACTUAL ROAD LOAD 5.4 KW( 7.3 HP)
DIESEL EM-526-F
ODOMETER 4907. KM( 3049. MILES)
NOX HUMIDITY CORRECTION FACTOR .81
-------
o
(
CTi
H
O
g
50
40
30
20
10
Start
0 Sec. ->
End
505 Sec.
10
20
30
40
50
60
VI
0
tn
0)
rH
H
a
<1)
0)
ft
Figure C-l. Smoke opacity and vehicle speed vs. time for the first 505 seconds
of a cold-start FTP, VW Rabbit Diesel, EM-527-F, SASOL, 11/11/82.
-------
o
I
o
(0
0
G
to
505 sec
Figure C-2- Smoke opacity and vehicle speed vs time for the first 505 seconds
of a cold-start FTP, VW Rabbit Diesel, EM-478-F, 25% SRC-II, 7/21/81
The trace is similar to what was observed using EM-526, 25% H-Coal.
-------
4G300 j-
I
40800 r
LD
CM
X
n Jฑ[
i , ~i
oo I-
I
320UO (-
I A
RT in min
15
IB
21
24
SRMPLE: S-263 INJECTED flT 12:23:23 OH DEC 27, 1932
Method: SB/OIL Raw: S263BB Proc : *PRC65
Figure C-3. Chromatogram of organic solubles from particulate matter,
vehicle operated on EM-527-F fuel during FTP.
-------
in
LD
4260U r
39980
cr 24000
RT in
1
_i_
12
SfiMPLE: S'
15
IS 21
INJECTED flT
24
OH DEC
27
Hethod: SB/OIL Raw: S269BB Proc : *PRC05
38
Figure C-4. Chromatogram of organic solubles from particulate matter,
vehicle operated on EM-527-P fuel during HFET.
-------
LJ)
111
I/I
n
B
42900 r
cr 24000-
RT in min.
1
SflMPLE: S-265 INJECTED fiT 13:34:44 OH DEC 27, 1932
Method: SD/OIL Raw: S265BB Proc : *PRCQ5
Figure C-5. Chromatogram of organic solubles from particulate matter,
vehicle operated on EM-526-F fuel during FTP.
-------
111
I/I
260013
U'J
C'J
LJ
a
r
RT in min
1
1!
18
:i
24
ฃ. I
SflMPLE: S-267 INJECTED RT 14:48:23 ON EEC 27, 1982
Method: SB/OIL Raw: S267BB Proc : *PRC05
Figure C-6. Chromatogram of organic solubles from particulate matter,
vehicle operated on EM-526-F fuel during HFET.
-------
APPENDIX D
STATISTICAL ANALYSIS RESULTS
-------
SOUTHWEST RESEARCH INSTITUTE
INTER-DEPARTMENTAL MEMORANDUM
October 4, 1982
Bruce Bykowski
FROM: R.L. Mason
SUBJECT: Response to 05-6619-005 Task Order
The analysis approach proposed for meeting the objectives of the
current task order is discussed in the following paragraphs. Attempts
have been made to strengthen the statistical arguments while
minimizing the number of assumptions and maximizing the application of
the conclusions.
Experiments involving the study of the relationships between
exhaust emissions and fuel properties are known to depend on several
factors. These include, as a minimum, the vehicle on which the tests
are run, the type of fuel, the test cycle, and the measurement
techniques. Further, it is well known that the quantity of a given
exhaust emission depends on a variety of fuel properties and that this
type of an association precludes simple one-to-one relationships
between a given emission and a specific fuel property.
The above facts have an important effect in any effort aimed at
combining various studies on emissions. First, these studies most
probably will have varying experimental conditions resulting in
experiments utilizing different vehicles, fuels, test cycles and
measurement techniques. Second, each experiment may yield differing
prediction equations relating emissions to fuel properties. These
equations will be based on different sample sizes as well as
experimental conditions. Third, the experimental results will have
wide variation as a result of the many sources of variation. This
will result in differing levels of fit with some prediction equations
yielding large correlation coefficients while others yield moderate-
to-low correlations.
Any analysis plan devised for combining the data from many
studies on petroleum-based fuels will be, at best, descriptive in
nature as a result of the previous arguments. Nevertheless, it is
possible to obtain some helpful information by the usage of both
graphical displays of the data as well as some simple statistical
techniques. The proposed method involves reviewing each study
concerned with predicting emission trends from petroleum-based fuels
and determining which indicate similar relationships.
D-2
-------
Due to the difficulties involved in displaying and comparing
multiple-variable equations, the primary effort in this task will be
devoted to studying one-to-one relationships between exhaust emissions
and fuel properties. However, if enough data are available, some
effort may be given to expanding the analysis plan to consider multi-
variable relationships.
Since each experiment may be using different data ranges for the
fuel properties (e.g., due to differing fuel types or test vehicles),
the data from each study as well as from the alternate-source fuel
study must be normalized to a common point. This will yield more
meaningful comparisons. Hence, the data from each study will be
normalized to a predetermined fuel property level (e.g., 30%
aromatics).
Three procedures will be used to analyze the normalized data.
These include the following:
1. Graphical Comparison
The normalized data from each study will be plotted on a graph of
the emission of interest versus a specific fuel property. In this
manner a region of interest will be established within which will lie
the data from all petroleum-based studies. The normalized data from
the alternate-source fuel will be plotted on the same graph to
determine if the data fall inside or outside the region of interest.
2. Curve-Fitting Comparison
The normalized emissions data from each study will be fitted with
a least squares regression line using a specified fuel property as the
predictor variable. Similarly an equation will be used to fit the
alternate-fuel data. These lines will be plotted on a graph similar
to the one given as an example in Figure 1. The lines from the
petroleum-fuel data will form a region representing the dispersion for
such studies. The effects of using alternate-source fuels can be
determined by observing where the alternate-source fuel line falls
relative to the petroleum-based fuel band.
3. Average Comparison
Although the prediction equations obtained in step 2 will be
based on varying experimental conditions and sample sizes, and will
have differing degrees of fit (i.e., correlation coefficients), an
attempt will be made to fit all the petroleum-based fuel data using a
single regression line. This combined equation then could be used as
a comparison for the alternate-source fuel fit. One means of
accomplishing this analysis is to form an "average" line whose
intercept and slope are the average of the intercepts and slopes,
respectively, of the individual lines. Another approach might be to
fit all the petroleum-data to a single line; however, this method
D-3
SOUTHWEST RESEARCH INSTITUTE
-------
would give undue emphasis to studies with better fits and more data.
The resulting "average" fit could be used with the fuel property data
from the alternate-source study to obtain predicted emission values
that could be compared to the observed emission data from the
alternate-source study.
This comparison would be accomplished using a goodness-of-f it
statistic such as
9 n (Observed - Predicted)2
X = ฃ Predicted
While X is not a chi-square statistic (as would occur in a single
experiment with random observations) it is similar to it and the chi-
square table can be used to provide guidelines for determining whether
the observed and predicted values differ.
A brief example of a typical plot of the data resulting from the
above study is shown in Figure 1.
It shows that the alternate-source study's effect of aromatics is
greater than the average of all petroleum-based studies reviewed. The
alternate-source study's fuel aromatic contents could be inserted into
the linear equation for the average of studies A, B, C, D to yield
particulate emissions as if the alternate fuels were petroleum-based
fuels. The predicted particulate values could be compared to actual
observed particulate emissions. Where appropriate, additional
comparisons would be made between the alternate-source study and
individual studies. For example, if study "A" represented results
from a petroleum-based study which incorporated the same vehicle type
and driving cycle as the alternate-source study, then the results
would indicate that the alternate-source fuels exhibit less of a
particulate emission increase as compared with the petroleum-based
fuels.
The previous discussions describe the statistical approach for
combining the data from the various studies and the expected output
from the analysis. In summary, descriptive statistical techniques
based on plotting the data and fitting curves to the data will be
utilized in order to compare the effects of petroleum-based fuels on
exhaust emissions to those of alternate-source fuels on emissions.
The proposed methodology has some severe limitations which
restrict the application of more advanced statistical concepts. These
include the usage of experiments performed at differing times under
differing test conditions and with differing objectives. Due to these
facets, it is expected that only some general trend information will
be available at the conclusion of this project.
D-4
SOUTHWEST RESEARCH INSTITUTE
-------
d
0)
N
tO
o
c
0)
4J
ft
o
H
4J
M
RJ
1.5-
1.0-
0.5 -
A,B,C/D = petroleum studies
alternate-source study
B
^. ^A,B,C,D average
C
D-
i i i r t
0 10 20 30 40 50 60
% Aromatics
Figure 1. Particulate index vs. percent aromatics
D-5
-------
a
STUDY
INFO ID
Al
Al
Al
Al
At
Al
Al
Al
Al
A 1
Al
Bl
Bl
Bt
Bt
Bl
82
B2
B2
B2
B2
Cl
Cl
Cl
Cl
01
01
01
F 1
F 1
Fl
Fl
F2
F2
F2
61
61
61
Gl
61
61
61
Gl
Gl
62
62
62
62
62
62
62
62
62
HI
HI
HI
HI
HI
HI
HI
2!
2.
2.
2.
2.
3.
3.
3.
3.
3.
4.
4.
4.
4.
5.
5.
5.
6.
6.
6.
6.
7.
7.
7.
8.
8.
8.
8.
8.
8.
8.
8.
8.
9.
9.
9.
9.
9.
9.
9.
9.
9.
10.
10.
10.
10.
10.
10.
10.
FUEL
CODE
395.
401.
404.
405.
430.
434.
438.
448.
460.
461.
463.
238.
239
240.
241.
242.
238.
239.
240.
241.
242.
1.
2.
3.
4.
20.
2.
1.
1.
4.
5.
6.
1.
5.
6.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
2.
3.
6.
7.
9.
11.
13.
CETANE
NO.
62.
55.
62.
61.
63.
44.
64.
56.
46.
68.
60.
53.
47.
47.
41.
50.
53.
47.
47.
41.
50.
47.
47.
49.
49.
50.
47.
48.
48.4
50.0
43.5
48.4
43.5
61.0
45.7
47.7
44.9
41.2
41. 1
44.2
39.8
37.0
61.0
45.7
47.7
44.9
41.2
41.4
44.2
39.8
37.0
27.
45.
28.
47.
28.
49.
39.
DENSITY N
G/ML PPM
0.793
0.800
0.794
0.795
0.796
0.825
0.793
0.783
0.815
0.791
0.826
0.845
0.844
0.806
0.861
0.831
0.845
0.844
0.806
0.861
0.831
0.806
0.832
0.844
0.843
0.850
0.847
0.835
0.829
0.809
0.840
0.800
0.829
0.840
0.800
0.784
0.810
0.820
0.811
0.823
0.819
0.852
0.835
0.830
0.784
0.810
0.820
0.811
0.823
0.819
0.852
0.835
0.830
0.707
0.707
0.678
0.678
0.723
0.817
0.789
1 .
1 .
479.
930.
493.
5.
1.
1 .
t.
1.
718.
50.
50.
60.
240.
80.
50.
50.
60.
240.
80.
ARO.
VOL %
5.8
2.7
6. 1
6.6
8.8
31.5
6.8
4.9
32. 1
5. 1
30.8
29.8
21.6
13.0
34.6
12.4
29.8
21.6
13.0
34.6
12.4
13.0
27.0
21.6
26.5
35.1
28.8
22.8
23.7
19.2
36.9
19.2
23.7
36.9
19.2
0.0
13.0
13.0
17.0
20.0
20.0
32.0
32.0
34.0
0.0
13.0
13.0
17.0
20.0
20.0
32.0
32.0
34.0
7.0
7.0
3.0
3.0
6.0
17.0
13.0
OLE.
VOL %
1.5
1.9
1.5
1.5
1.8
2.9
6.6
1.8
1 .0
1.0
1.2
1.6
0.8
3.4
1.0
0.8
1.6
0.8
3.4
1.0
0.8
3.4
1.8
0.8
0.9
0.0
1.4
1. 1
0.96
0.70
0.72
0.72
0.96
0.72
0.72
4.0
4.0
3.0
3.0
1.0
4.0
2.0
IO*PT
DEG C
21 1.
206.
21 1.
210.
210.
206.
210.
189.
209.
216.
206.
213.
216.
181.
216.
213.
213.
216.
181.
216.
213.
181.
204.
216.
214.
223.
217.
205.
197.
151.
139.
136.
197.
139.
136.
209.
206.
213.
188.
203.
201.
214.
199.
199.
209.
206.
213.
188.
203.
201.
214.
199.
199.
54.
54.
63.
63.
79.
201.
165.
90JJPT
OEG C
224.
239.
224.
224.
228.
234.
224.
223.
224.
251.
234.
313.
303.
238.
301.
310.
313.
303.
238.
301.
310.
238.
280.
303.
306.
316.
309.
297.
290.
303.
308.
279.
290.
308.
279..
247.
226.
309.
244.
249.
227.
306.
312.
251.
247.
226.
309.
244.
249.
227.
306.
312.
251.
130.
130.
92.
92.
122.
255.
186.
HC
6/KM
0.09
0. 1 1
0.08
0.08
0.09
0. 12
0.09
0.1 1
0.13
0.08
0. 13
0. 12
0. 19
0.09
0.20
0.12
0. 18
0.20
0.17
0.71
0.20
0.21
0.19
0.29
0.30
0.15
0.21
0.26
0.31
0.37
1.74
0.55
0.30
0.29
0. 1
0. 1
0.1
O.I
0.2
0.1
0.7
0.1
0. 1
0.2
0. 1
O.I
0.2
0.2
0.2
CO
G/KM
0.52
0.50
0.47
0.46
0.52
0.59
0.48
0.48
0.60
0.47
0.66
0.57
0.64
0.57
0.71
0.68
0.49
0.51
0.55
0.81
0.52
0.80
0.78
0.88
0.90
0.68
0.84
0.88
0.71
0.74
1.50
0.87
1.23
1.17
1.08
0.4
0.4
0.4
0.5
0.6
0.5
1.2
0.5
0.6
0.7
0.6
0.6
0.9
0.6
0.7
NOX
G/KM
0.75
0.85
0.76
0.89
0.84
0.88
0.85
0.82
0.92
0.86
1.04
0.78
0.79
0.73
0.88
0.85
0.59
0.65
0.57
0.58
0.63
1.12
1.14
1.64
1.43
0.85
0.83
0.81
0.46
0.46
0.38
0.40
0.96
1.12
0.96
1.0
1.1
0.9
1.0
0.9
0.9
0.9
0.7
0.8
0.9
0.8
0.8
0.9
0.8
0.8
PART.
G/KM
0. 171
0. 151
0. 162
0. 162
0. 180
0.212
0. 155
0.142
0.219
0. 159
0.287
0.329
0.314
0.235
0.380
0.292
0.225
0.218
0. 177
0.375
0.194
0.231
0.308
0.247
0.316
0.172
0.187
0. 178
0. 1 1
0.14
0. 11
0.12
0.11
0. 11
0.10
0.14
0.15
0.12
0.13
0. 14
0.19
0.14
0.16
FUEL BAP
L/IOOKM UG/KM
9.46
9.55
9.50
9.59
9.76
9.52
9.84
9.51
9.56
9.63
9.62
8.48
8.60
8.51
9.38
9.38
5.71
5.60
5.71
6. 17
5.89
7.99
8.34
8.87
8.89
8.06
7.71
7.79
5 05
10.7
11.2
9.8
10.2
10.2
9.8
11.2
11.8
11.
13. 1
11.8
11.2
11.2
0.59
0.42
0.25
0.35
0.96
0.37
0.21
0.51
0.73
0.43
0.43
0.39
0.46
0.32
0.62
0.23
1. 13
1.33
1. 18
3.64
1.05
0.96
0.98
ALDE.
MG/KM
0.31
4.89
0.30
15.2
0.00
2.80
0.00
8. 18
0.00
8.83
0.00
16.9
15.9
16.0
23.9
16.9
28.7
12.6
18.0
52.5
13.4
22.6
34.7
29.6
23.0
PHEN.
MG/KM
1.69
0.00
4.33
29.4
128.
0.66
0. 17
0.21
1.30
0.55
0. 18
SOLUBLE
MG/KM
27.0
23.7
21.7
17.0
22.9
27.6
28.4
26.7
30.2
26.2
34.7
36.7
30.6
28.3
28.7
26.1
24.4
28.8
26.6
58.4
26.4
71.6
74.0
19.3
31.7
25.5
39.8
19.3
31.7
39.8
41.0
44.7
31.1
32.9
57.2
40.4
29.8
34.2
61.4
30.3
48.9
24.8
45.5
20.1
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STUDY
INFO ID
J3
J3
K 1
Kl
K1
Kl
Kt
K 1
K 1
K 1
K 1
K 1
15.
15.
16.
16.
16.
16.
16.
16.
16.
16 .
16.
16.
FUEL CETANE
CODE NO.
329.
469.
329.
453.
473.
474.
476.
478.
482.
485 .
527.'
526.
50.1
48.0
50.
49.
45.
42.
35.
38.
44.
4 5.
50!
42.
DENSITY N
6 /ML PPM
0.837
0.849
0.837
0.835
0.808
0.870
0.806
0.867
0.856
0.833
0.804
0.861
48.
48.
5.
1.
1600.
1000.
2000.
267.
1 42 .
l!
980.
ARO.
VOL %
21.3
39.1
21.3
28.5
22.0
34.9
16.2
39.9
36.4
25.5
24.0
37.2
OLE.
VOL %
1.7
0.9
1.7
2. 1
2.0
1.4
0.0
1.2
0.0
0 5
o!o
1.2
10JSPT
DE6 C
219.
307.
219.
236.
189.
234.
53.
209.
207.
1 57
200]
212.
90*PT
OEG C
219.
315.
302.
295.
228.
330.
303.
303.
316.
302
392!
316.
HC CO
G/KM G/KM
0.12 0.65
0.13 0.69
0.31 0.96
0.31 1.06
0.38 1.20
0.39
0.68
0.60
0.33
0.34
0^32
0.36
.21
.38
.31
. 14
.16
!08
. 12
NOX
G/KM
0.64
0.65
0.66
0.67
0.70
0.83
0.65
0.76
0.73
0 76
o!e4
0.71
PART.
G/KM
0.236
0.273
0.249
0.274
0.250
0.321
0.208
0.394
0.281
0 299
o!22t
0.282
FUEL BAP
L/100KM US/KM
10.69
10.64
6.37
6.63
6.62
6.23
6.64
6.45
6. 1 1
6. 59
e!35
6. 18
0.3
0.5
14.9
34.0
31.6
44. 1
30.2
10.0
24.3
8 7
19.6
19.0
ALOE.
MG/KM
1. 1
0.5
14.
9.
13.
8.
12.
2.
3.
2.
0.0
PHEN.
MG/KM
8.5
9.7
12.
1 1.
0.5
14.
2.
12.
24.
0.0
0.0
SOLUBLE
MG/KM
28.2
37.1
44.8
48.6
30.4
56.6
52.4
101.
36.7
43.3
47.8
-------
D
I
IQ
STUDY
1 NFO 1 D
Al
Al
Al
Al
A 1
Al
Al
A 1
Al
A 1
Al
Bl
81
Bl
Bl
Bl
82
82
B2
B2
82
Ct
Cl
Cl
Cl
01
Dl
01
F 1
F 1
F1
F 1
F2
F2
F2
61
61
61
61
61
61
61
61
61
62
62
62
62
62
62
62
62
62
.
.
.
.
.
.
.
.
.
.
.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
4.
4.
4.
4.
5.
5.
5,
6.
6.
6.
6.
7.
7.
7.
8.
8.
8.
8.
8.
8.
8.
8.
8.
9.
9.
9.
9.
9.
9.
9.
9.
9.
FUEL
CODE
395.
401.
404.
405.
430.
434.
438.
448.
460.
461.
463.
238.
2390.
240.
241.
242.
238.
239.
240.
241 .
242.
1.
2.
3.
4.
20.
2.
1.
1.
4.
5.
6.
1.
5.
6.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
DENSITY
6/ML
.793
.800
.794
.795
.796
.825
.793
.783
.815
.791
.826
.845
.844
.806
.861
.831
.845
.844
.806
.861
.831
.806
.832
.844
.843
.850
.847
.835
.829
.809
.840
.800
.829
.840
.800
, 784
.810
.820
.81 1
.823
.819
.852
.835
.830
.784
.810
.820
.811
.823
.819
.852
.835
.830
HC
NORM
1
1
1
1
1
1
1
1
1
1
21
3
3
6
3
3
6
6
6
.5960
.7285
.5298
.5298
.5960
.7947
.5960
.7285
.8609
.5298
.8609
.7101
.1243
.5325
. 1834
.7101
.4639
.5155
.4381
.8299
.5155
.7292
.6597
.0069
.041 7
.8876
.2426
.5385
.1800
.2149
.0105
.2673
.6912
.6682
.7692
.7692
.7692
.7692
.5385
.7692
.2121
.0303
.0303
.0606
.0303
.0303
.0606
.0606
.0606
NOX
NORM
.7123
.8072
.7217
.8452
.7977
.8357
.8072
.7787
.8737
.8167
.9877
1.2601
1.2763
1. 1793
1.4216
1.3732
.9704
1.0691
.9375
.9539
1.0362
.7292
.7422
1.0677
.9310
1.0071
.9834
.9597
1. 1192
1.1192
.9246
.9732
.8735
1.0191
.8735
1.0384
1.1423
.9346
1.0384
.9346
.9346
1.1002
.8557
.9780
1.1002
.9780
.9780
1. 1002
.9780
.9780
PART.
NORM
.5498
.4855
.5209
.5209
.5788
.6817
.4984
.4566
.7042
.5113
.9228
.9620
.9181
.6871
1.1111
.8538
.8123
.7870
.6390
1.3538
.7004
.7700
1.0267
.8233
1.0533
.9609
1.0447
.9944
.9402
1.1966
.9402
1.0256
.9402
.9402
.5682
.7955
.8523
.6818
.7386
.7955
1 .0795
.7955
.9091
FUEL
NORM
.9895
.9990
.9937
1.0031
1.0209
.9958
1.0293
.9948
1.0000
1 .0073
1.0063
.9438
.9572
.9471
1 .0440
1.0440
.9706
.9519
.9706
1.0488
1.0012
.8919
.9310
.9902
.9924
1.0181
.9739
.9840
1.0106
1.0492
1.0268
1.0756
.9567
1.0088
.9614
1.0568
1.1062
.9679
1.0074
1.0074
.9679
.9695
1.0215
.9695
1. 1340
1.0215
.9695
.9695
-------
D
I-1
O
STUDY FUEL
NFO ID CODE
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
Ht
Ht
HI
HI
HI
10.
10.
10.
10.
to.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
to.
10.
to.
10.
to.
10.
10.
10.
10.
10.
10.
10.
10.
10.
11.
11.
11.
11.
It.
11.
II.
11.
11.
It.
11.
It.
11.
11.
11.
2.
3.
6.
7.
9.
1 1.
13.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
30.
31.
32.
33.
34.
35.
36.
40.
43.
46.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
DENSITY
6/ML
.707
.707
.678
.678
.723
.817
.789
.786
.826
.879
.816
.834
.845
.851
.845
.851
.848
.840
.813
.754
.843
.759
.776
.864
.832
.759
.789
.737
.780
.849
.840
.809
.851
.864
.883
.871
.899
.843
.918
.775
.872
.782
.829
.795
.808
.872
HC
NORM
4.7196
2. 1729
4.5561
1.9626
1. 1682
. 1636
. 1636
4.0421
1.0981
.8879
2.8037
1. 1682
2.5935
1.7290
1.1916
.3738
.4206
.2804
.1168
.2804
.3505
32.5234
.7944
.3037
.3972
.5140
.3972
.8178
.1168
.6776
.2336
_-__
'
NOX
NORM
1.4413
1.0401
.9609
.9014
1. 1194
.8370
.7033
.9212
1.2729
1.3422
1.0253
1.0599
1. 1441
1.0599
1.0203
1. 1095
.9559
1.0599
.9856
.8470
.9312
1.4859
1.2729
.8321
1.0550
1.0797
1.0451
1.0896
.5002
.6835
.8123
_
PART.
NORM
.5592
.9174
.5894
.8365
.9129
t. 1048
1.0172
.6250
.9371
1. 1502
1. 1093
.9378
.8826
.9892
.7481
.9091
.8698
.8501
.8932
.8600
1.1955
.6499
.9537
1.0874
1.0149
1.1124
1. 1486
1.0058
.7617
t.1683
.8683
.5293
.7726
1.1279
1.4689
1 . 1 26 1
1.6234
.6963
1 . 7 54 9
.5187
1.6234
.3428
.6181
.4636
.5417
1.0053
FUEL
NORM
.9782
.9852
.9961
.9571
.9439
.9727
.9127
.9883
.9922
1.0078
1.0023
1. 1403
.9758
.9260
.9712
.9673
.9478
.9906
.9049
.8527
1.0585
1.1052
.9556
.9860
.9587
.9657
.9704
.9509
.9790
1. 1582
1.0663
--__
.__.
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M
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STUDY
INFO ID
At
A1
Al
A1
Al
Al
Al
Al
Al
Al
Al
Bl
B1
8t
Bl
Bl
B2
82
82
82
B2
Cl
Cl
CI
Cl
01
Dl
D1
Fl
Fl
Fl
F 1
F2
F2
F2
61
61
61
61
61
61
61
61
61
62
62
62
62
62
62
62
62
62
.
a
.
.
.
f
.
f
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
4.
4.
4.
4.
5.
5.
5.
6.
6.
6.
6.
7.
7.
7.
8.
8.
8.
8.
8.
8.
8.
8.
8.
9.
9.
9.
9.
9.
9.
9.
9.
9.
FUEL
CODE
395.
401.
404.
405.
430.
434.
438.
448.
460.
461.
465.
238.
2390.
240.
241 .
242.
238.
239.
240.
241.
242.
1 .
2.
3.
4.
20.
2.
1 .
1.
4.
5.
6.
1.
5.
6.
7812.
7938.
7941 .
8017.
7939.
7942.
7926.
7943.
7940.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
CETANE
NO.
62.0
55.0
62.0
61.0
63.0
44.0
64.0
56.0
46.0
68.0
60.0
53.0
47.0
47.0
41.0
50.0
53.0
47.0
47.0
41.0
50.0
47.0
47.0
49.0
49.0
50.0
47.0
48.0
48.4
50.0
43.5
48.4
43.5
.
61.0
45.7
47.7
44.9
41.2
41.1
44.2
39.8
37.0
61.0
45.7
47.7
44.9
41.2
41.4
44.2
39.8
37.0
HC
NORM
.7258
.8871
.6452
.6452
.7258
.9677
.7258
.8871
1.0484
.6452
1.0484
.8108
1.2838
.6081
1.3514
.8108
.5660
.6289
.5346
2.2327
.6289
1.0500
.9500
1.4500
1.5000
.6250
.8750
1.0833
.3543
.4229
1.9886
1.1482
.6263
.6054
.9901
_
.9901
.9901
.9901
1.9802
.9901
2.6923
.3846
.3846
.7692
.3846
.3846
.7692
.7692
.7692
CO
NORM
.9028
.8681
.8160
.7986
.9028
1.0243
.8333
.8333
1.0417
.8160
1. 1458
.8920
1.0016
.8920
1. Ill 1
1.0642
.8277
.8615
.9291
1.3682
.8784
1.0127
.9873
1.1 139
1.1392
.7727
.9545
1.0000
.6947
.7241
1.4677
.8513
1.0140
.9646
.8904
.9569
.9569
.9569
1.1962
1.4354
1.1962
1.5748
.6562
.7874
.9186
.7874
.7874
1. 1811
.7874
.9186
SOLUBLE
NORM
.9708
.8522
.7803
.6113
.8234
.9924
1.0212
.9601
1.0859
.9421
1.2477
1.2313
1.0266
.9494
.9629
.8756
.7049
.8320
.7685
1.6872
.7627
1.0000
ป-~
1,0335
-r-~
_
.7399
____
1.2152
.9775
1.5257
.7399
.2152
.0092
.0396
.1334
.7886
.8342
.4503
.0244
.7556
.8672
-------
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STUDY
INFO ID
Al
Al
Al
Al
A 1
Al
Al
Al
Al
Al
Al
Bl
Bl
Bl
Bl
81
B2
B2
B2
B2
B2
C 1
Cl
C 1
Cl
Dl
01
01
F 1
F 1
Fl
Fl
F2
F2
F2
Gl
61
Gl
61
Gl
61
Gl
Gl
Gl
62
62
62
G2
62
G2
62
62
62
2!
2.
2.
2.
2.
3.
3.
3.
3.
3.
4.
4.
4.
4.
5.
5.
5.
6.
6.
6.
6.
7.
7.
7.
8.
8.
8.
8.
8.
8.
8.
8.
8.
9.
9.
9.
9.
9.
9.
9.
9.
9.
FUEL
CODE
395.
401.
404.
405.
'430.
434.
438.
448.
460.
461.
463.
238.
2390.
240.
241.
242.
238.
239.
240.
241.
242.
1.
2.
3.
4.
20.
2.
1.
1.
4.
5.
6.
1.
5.
6.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
7812.
7938.
7941.
801 7.
7939.
7942.
7926.
7943.
7940.
N
PPM
1.
1 .
479.
930.
493.
5.
1.
1.
1.
1.
718.
50.
50.
60.
240.
80.
50.
50.
60.
240.
80.
_
_
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CO
NORM
i!
r.
ii
i.
i .
i.
i.
i.
i
_
9981
9597
9021
8829
9981
1324
9213
9213
1516
9021
2668
9120
0240
9120
1360
0880
8909
9273
0000
4727
9455
III
BAP
NORM
2.
i!
i.
i!
i.
i.
2'.
_
2292
8750
5208
7292
0000
7708
4375
0625
5208
8958
8958
0183
2010
8355
6188
6005
7772
9147
81 16
5034
7221
SOLUBLE
NORM
1.
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i.
i!
i!
i.
i.
il
~
I
0092
8859
8111
6354
8560
0317
0616
9980
1288
9793
2971
2104
0092
9333
9465
8608
8092
9551
8821
9367
8755
III
-------
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I i i i I I i I I I
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i i t t i
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i i i i i i
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D-16
-------
o
I
STUDY
INFO ID
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
J 1
J 1
J2
J2
J3
J3
K 1
K 1
K 1
K 1
K 1
K 1
K 1
K 1
K 1
K 1
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
13.
13.
14.
14.
15.
15.
16.
16.
16.
16.
16.
16.
16.
16.
16.
16.
FUEL
CODE
1.
2.
4.
7.
1 1.
13.
1.
2.
8.
1 1.
12.
15.
1.
2.
4.
1 1.
12.
329.
469.
329.
469.
329.
469.
329.
453.
473.
474.
476.
478.
482.
485.
527.
526.
N
PPM
48.
48.
48.
48.
5.
1.
1600.
1000.
2000.
267.
142.
1.
980.
CO
NORM
.8680
.9584
.0850
.0940
.2477
.1844
.0307
.0488
.9765
1.0127
BAP
NORM
.6452
1.4722
1.3683
1.9095
1.3076
.4330
1.0522
.3767
.8487
.8227
SOLUBLE
NORM
1.1507
1.2483
.7808
1.4537
1.3459
2.5941
.9426
1.1 121
1.2277
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-------
D
I
NJ
o
STUDY
INFO ID
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Jl
J1
J2
J2
J3
J3
Kl
Kl
K 1
Kl
Kl
Kl
Kl
Kl
Kl
Kl
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
12.
13.
13.
H.
14.
15.
15.
16.
'6.
16.
16.
16.
16.
16.
16.
16.
16.
FUEL
CODE
1.
2.
4.
7.
1 1.
13.
1.
2.
8.
1 1.
12.
15.
1.
2.
4.
1 1.
12.
329.
469.
329.
469.
329.
469.
329.
453.
473.
474.
476.
478.
482.
485.
527.
526.
ARO.
VOL *
19.
32.
33.
9.
1.
0.
19.
32.
57.
1.
*
45.
19.
32.
33.
1.
2l!
39.
21.
39.
21.
39.
21.
28.
22.
34.
16.
39.
36.
25.
24.
37.
9
7
7
7
7
0
9
7
7
7
3
1
9
7
7
7
3
3
1
3
1
3
1
3
5
0
9
2
9
4
5
0
2
HC
NORM
.9394
1 .0606
.8922
1.1 152
.9600
1.0400
.7750
.7750
.9500
.9750
1.7000
1.5000
.8250
.8500
.8000
.9000
CO
NORM
.9338
1.0698
.9241
1.0781
.9701
1.0299
.8255
.91 14
1.0318
1.0404
1.1866
1.1264
.9802
.9974
.9286
.9630
NOX
NORM
.9716
1.0308
1.0040
.9960
.9922
1.0078
.9192
.9331
.9749
1.1560
.9053
1.0585
1.0167
1.0585
.8914
.9889
PART.
NORM
.9167
1. 1780
1.6023
.9167
.5871
.6591
.5417
.6818
1.2462
.3068
.4470
.8485
1.0114
1.2235
1.2462
.6591
.6591
.9551
1.0487
.8852
1 . 1 202
.9291
1.0748
.8737
.9614
.8772
1.1263
.7298
1.3825
.9860
1.0491
.7754
.9895
BAP
NORM
1.2821
.7051
.4946
1.5288
.7538
1.2563
.6346
1.4480
1.3458
1.8782
1.2862
.4259
1.0349
.3705
.8348
.8092
ALDE.
NORM
1
1
2
1
2
1
1
0
.0469
.9510
.2747
.7127
.3631
.6196
.1558
.3859
.0018
.2319
.8479
.3080
.4620
.3080
.0000
-------
D
to
STUDY
INFO ID
At
A1
A 1
A1
Al
A 1
Al
Al
Al
Al
Al
Bl
B1
Bl
Bl
81
B2
B2
B2
B2
B2
Cl
Cl
Cl
Cl
01
01
Dl
F1
F1
Fl
Fl
F2
F2
F2
Gl
G1
Gl
Gl
Gl
Gl
Gl
Gl
Gl
62
G2
62
62
G2
62
62
62
G2
1.
t.
1.
1.
1.
1.
1.
1.
1.
1.
1.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
4.
4.
4.
4.
5.
5.
5.
6.
6.
f>.
6.
7.
7.
7.
8.
8.
8.
8.
8.
8.
8.
8.
8.
9.
9.
9.
9.
9.
9.
9.
9.
9.
FUEL
CODE
395.
40).
404.
405.
430.
434.
438.
448.
460.
461.
463.
238.
2390.
240.
241.
242.
238.
239.
240.
241.
242.
1.
2.
3.
4.
20.
2.
1.
1 .
4.
5.
6.
1.
5.
6.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
7812.
7938.
7941.
8017.
7939.
7942.
7926.
7943.
7940.
OLE.
VOL %
1.
1.
1.
1.
1.
2.
6.
50
90
50
50
80
90
60
1.80
1.
1.
1.
1.
t
3l
1.
f
1.
w
00
00
20
60
80
40
00
80
60
80
3.40
1.
.
3.
1.
f
u
o'.
1.
1.
.
^
.
f
B
f
f
_
_.
__-..
_--_
00
80
40
80
80
90
00
40
10
96
70
72
72
96
72
72
FUEL
NORM
.9862
.9956
.9904
.9998
.0175
.9925
.0259
.9915
.9967
.0040
.0029
.9684
.9821
.9718
.0711
.0711
.9867
.9677
.9867
.0662
.0178
.9483
.9898
.0527
.0551
.0657
.0194
.0300
.1976
.2434
.2169
.2747
. 1473
.2097
. 1529
--.._
-_-_
---_
..
-------
D
I
to
to
STUDY FUEL
INFO ID CODE
HI
HI
HI
HI
H1
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
H1
HI
HI
HI
HI
HI
HI
HI
HI
HI
H1
HI
HI
10.
10.
10.
10.
10.
to.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
10.
1 1.
11.
11.
11.
11.
11.
11.
11.
11.
11.
1 1.
11.
1 1.
1 1.
11.
2.
3.
6.
7.
9.
1 1.
13.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
30.
31.
32.
33.
34.
35.
36.
40.
43.
46.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
1 1.
12.
13.
14.
15.
OLE.
VOL %
4.00
4.00
3.00
3.00
1.00
4.00
2.00
1.00
2.00
1.00
2.00
4.00
3.00
2.00
3.00
5.00
3.00
3.00
3.00
0.00
4.00
1.00
1.00
3.00
3.00
1.00
2.00
1.00
2.00
~-_
--__
___
^
____
_-.~-.
,_
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._-._
FUEL
NORM
1.0065
1.0137
1.0249
.9848
.9712
1.0009
.9391
1.0169
1.0209
1.0370
1.0314
1.1733
1.0041
.9528
.9993
.9953
.9752
1.0193
.9311
.8774
1.0891
1.1372
.9832
1.0145
.9864
.9937
.9985
.9784
1.0073
ซ_.._
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12
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12
12
12
12
12
12
12
12
12
12
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J 1
J 1
J2
J2
J3
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12.
12.
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12.
12.
12.
13.
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15.
15.
16.
16.
16.
16.
16.
16.
16.
16.
16.
16.
FUEL
CODE
1.
2.
4.
7.
1 1.
13.
1.
2.
8.
11.
12.
15.
1.
2.
4.
1 1.
12.
329.
469.
329.
469.
329.
469.
329.
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474.
476.
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482.
485.
527.
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197.
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271.
258.
211.
221.
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254.
211.
309.
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197.
209.
271.
211.
309.
219.
307.
219.
307.
219.
307.
219.
236.
189.
234.
53.
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207.
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NORM
.
_
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.1327
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.0084
.0924
.8708
.8708
1.0674
1.0955
1.9101
1.6854
.9270
.9551
.8989
1.0112
NOX
NORM
.9988
1.0597
.9992
.9913
1.0016
1.0172
.9154
.9293
.9709
1.1512
.9015
1.0541
1.0125
1.0541
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PART.
NORM
1.0708
1.3761
1.8717
1.0708
.6858
.7699
.6327
.7965
1.4558
.3584
.5221
.9912
1.1814
1.4292
1.4558
.7699
.7699
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.9939
.2577
.0000
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.8527
.9384
.8562
1.0993
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1.3493
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1.0240
.7568
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APPENDIX E
SCATTERGRAMS
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70
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125 175 225
100 150 200 250
375 H1
350 400
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H
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.600 .660 .720 .780 .840 .900 .960
DENSITY
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w
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60. 100 140 180 220 260 300
80. 120 160 200 240 280 320
BPTEM
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+ซซ+ซ
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to
to
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2.8
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"17.56" "52.56" "87.50" "\22\5" "l57!s" "l92l5" "227\5*'
0.000 35.00 70.00 105.0 140.0 175.0 210.0 245.0
NITROGEN
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing}
1. REPORT NO.
EPA - 460/3-83-007
2.
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Petroleum Versus Alternate Source Fuel Effects on
Light-Duty Diesel Emissions
5. REPORT DATE
August 1983
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Bruce B. Bykowski
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORG-\NIZATION NAME AND ADDRESS
Southwest Research Institute
2565 Plymouth Road
Ann Arbor, MI. 48105
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-03-3073
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Protection Agency
2565 Plymouth Road
Ann Arobr, MI. 48105
13. TYPE OF REPORT AND PERIOD COVERED
Final Report (6-82/1-83)
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
This project was conducted for the U.S. Environmental Protection Agency
by the Department of Emissions Research, Southwest Research Institute. The
laboratory testing phase of the project began in June 1982, and was completed
in January 1983. The work was performed under EPA Contract No. 68-03-3073,
Work Assignment No. 5, and was identified within Southwest Research Institute
as Project 05-6619-005. The scope of work defined by the EPA is located in
Appendix A of this report. The EPA Project Officer was Mr. Robert J. Garbe,
and the Branch Technical Representative was Mr. Thomas M. Baines, both of the
Characterization and Technical Applications Branch, Emission Control Tech-
nology Division, Environmental Protection Agency, 2565 Plymouth Road, Ann
Arbor, Michigan. The Southwest Research Institute Project Manager was
Charles T. Hare, and the Project Leader and Principal Investigator was
Bruce B. Bykowski.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Held/Group
Exhaust Emissions Diesel Engines
Diesel Engines
Diesel Fuels
Alternate Fuels
Statistics
Fuel Effects
Statistical Analysis
Alternate Fuel Charac-
terization
Emission Characterization
13. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
164
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
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