United States Air and Radiation EPA420-R-00-002
Environmental Protection February 2000
Agency
vxEPA Analysis of
Commercial Marine
Vessels Emissions and
Fuel Consumption Data
> Printed on Recycled Paper
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EPA420-R-00-002
February 2000
of
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
Prepared for EPA under contract to
Sierra Research by
Energy and Environmental Analysis, Inc.
EPA Contract No. 68-C7-0051
Work Assignment No. 1-10
NOTICE
This technical report does not necessarily represent final EPA decisions or positions.
It is intended to present technical, analysis of issues using data, which are currently available.
The purpose in the release of such reports is to facilitate the exchange of
technical information and to inform the public of technical developments which
may form the basis for a final EPA decision, position, or regulatory action.
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TABLE OF CONTENTS
Pas
1. INTRODUCTION 1-1
2. REVIEW OF RELEVANT DATA 2-1
2.1 Introduction 2-1
2.2 Findings on Reports Providing Emissions Data 2-1
2.3 Summary of Reports Analyzing Emissions Data 2-3
2.4 Recommendations for Analysis 2-6
3. EMISSION FACTOR DEVELOPMENT 3-1
3.1 Introduction 3-1
3.2 Lloyd's Emission Test Data 3-2
3.3 U.S. Coast Guard Emission Test Data 3-6
3.4 Emissions Data Analysis 3-13
3.5 Emission Factor Development 3-21
4. MARINE VESSEL CLASSIFICATIONS AND POWER RATINGS 4-1
4.1 Classifications Employed in Literature 4-1
4.2 Operating Mode Classifications in Literature 4-4
4.3 Analysis of Ship Type and Weight Categories 4-6
5. EMISSION FACTOR SUMMARY 5-1
6. REFERENCES 6-1
APPENDIX A EMISSION FACTOR REGRESSION SUMMARIES A-l
APPENDIX B SUMMARY OF REPORTS REVIEWED B-l
APPENDIX C ACUREX CLASSIFICATION OF SHIPTYPES C-l
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LIST OF TABLES
Page
Table 2-1. Summary of Emissions Data 2-4
Table 3-1. Overview of the Lloyd's Emission Test Database 3-3
Table 3-2. LIoyd's NO to NOX Ratio for Marine Engines 3-5
Table 3-3. Overview of the USCG Emission Test Database 3-8
Table 3-4. Lloyd's Marine Engine Fuel Specifications 3-10
Table 3-5. Marine Engine Emission Factor Algorithms 3-44
Table 3-6. Marine Gas Turbine Emission Rate Data 3-52
Table 4-1. Booz-Allen Classification of Vessels 4-2
Table 4-2. Engine Loads by Ship Type for Each Operating Mode 4-7
Table 4-3. Results of Regressions between Horsepower and Deadweight Tonnage 4-9
Table 4-4. Regressions of Horsepower vs. Deadweight and Cruise Speed 4-10
Table 4-5. Recommended Ship Types and Regressions of Horsepower
to Deadweight 4-11
Table 4-6. Suggested Loads by Mode 4-13
Table 5-1. Marine Engine Emission Factor and Fuel Consumption Algorithms 5-3
Table 5-2. Suggested Load Factors 5-6
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LIST OF FIGURES
Page
Figure 3-1. Derivation of USCG Fuel H to C Ratio 3-9
Figure 3-2. Implied A/F Ratio 3-14
Figure 3-3. A/F Ratio Comparison - Detailed Carbon Balance 3-17
Figure 3-4. A/F Ratio Comparison - Detailed Oxygen Balance 3-18
Figure 3-5. A/F Ratio Comparison - Excess Air Balance 3-19
Figure 3-6. CO2/O2 Relationship 3-20
Figure 3-7. Consistency of A/F Ratio Estimates 3-22
Figure 3-8. Test Data Load Coverage 3-23
Figure 3-9. Measured CO2 3-25
Figure 3-10. Measured O2 3-26
Figure 3-11. Measured NO 3-27
Figure 3-12. Measured CO 3-28
Figure 3-13. Measured HC 3-29
Figure 3-14. Measured SO2 3-30
Figure 3-15. Measured PM 3-31
Figure 3-16. Fuel Consumption Data by Absolute Load 3-32
Figure 3-17. Fuel Consumption Data by Fractional Load 3-33
Figure 3-18. PM Emission Rate Data 3-35
Figure 3-19. NO Emission Rate Data 3-36
in
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LIST OF FIGURES
(Continued)
Page
Figure 3-20. NOX Emission Rate Data 3-37
Figure 3-21. NC>2 Equivalent NOX Emission Rate Data 3-38
Figure 3-22. SO2 Emission Rate Data 3-39
Figure 3-23. CO Emission Rate Data 3-40
Figure 3-24. CO2 Emission Rate Data 3-41
Figure 3-25. ©2 Emission Rate Data 3-42
Figure 3-26. HC Emission Rate Data 3-43
Figure 3-27. NO Emission Rate Data by Fuel Type 3-49
Figure 3-28. NOX Emission Rate Data by Fuel Type 3-50
Figure 3-29. NO2 Emission Rate Data by Fuel Type 3-51
Figure 3-30. Gas Turbine Emission Rates 3-53
Figure A-l. PM Emission Rate Data by Engine Type A-17
Figure A-2. NO Emission Rate Data by Engine Type A-18
Figure A-3. NOX Emission Rate Data by Engine Type A-19
Figure A-4. NO2 Emission Rate Data by Engine Type A-20
Figure A-5. CO Emission Rate Data by Engine Type A-21
Figure A-6. CO2 Emission Rate Data by Engine Type A-22
Figure A-7. O2 Emission Rate Data by Engine Type A-23
Figure A-8. HC Emission Rate Data by Engine Type A-24
IV
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LIST OF FIGURES
(Continued)
Page
Figure A-9. Dry Exhaust Emission Rate Data by Engine Type A-25
Figure A-10. H^O Emissions Rate Data by Engine Type A-26
Figure A-ll. Wet Exhaust Emission Rate Data by Engine Type A-27
Figure A-12. NO Emission Rate Data by Fuel Type A-28
Figure A-13. NOX Emission Rate Data by Fuel Type A-29
Figure A-14. NO2 Emission Rate Data by Fuel Type A-30
Figure A-15. CO Emission Rate Data by Fuel Type A-31
Figure A-16. CO2 Emission Rate Data by Fuel Type A-32
Figure A-17. ©2 Emission Rate Data by Fuel Type A-33
Figure A-18. HC Emission Rate Data by Fuel Type A-34
Figure A-19. Dry Exhaust Emission Rate Data by Fuel Type A-35
Figure A-20. H2O Emission Rate Data by Fuel Type A-36
Figure A-21. Wet Exhaust Emission Rate Data by Fuel Type A-37
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1. INTRODUCTION
The EPA is initiating a review of its guidance on developing emission inventories for
ocean-going and harbor vessels operating at port areas. The current methodology, as defined in
AP-42, is based on a three step calculation. The first step apportions the time spent by a vessel
in a port area to different operating modes. The second calculates fuel consumption in each
operating mode. The third step calculates emissions using fuel consumption specific emission
factors, which is how marine engine emission factors have been historically specified. All of
these calculations are by vessel type and class, with the type specifying whether the vessel is a
tanker, passenger liner, etc, and the class specifying either the weight or horsepower range.
The time-in-mode is a function of the particular port area geography and is not considered in this
report. The other factors used in the computation are examined, with particular focus on the
emission factor, for all pollutants of concern. One reason for a detailed reconsideration of the
emission factor is that a number of large marine diesels have been tested for emissions and their
tests result have become available in the last few years. In addition, both the EPA and ARB have
recently sponsored studies to calculate marine vessel emissions in the South Coast Air Basin and
in some areas of Region IX, so that there is a body of new research available to update emission
factors. Hence, the use of a larger and newer database on marine vessel emission is expected to
substantially improve the quality of the derived emission factors.
In this work assignment, the EPA did not require a literature review, but instead provided with
nine reports as the basis for this review. Due to the fact that data on emissions from gas turbines
were restricted to two engines, most of the analysis presented in this report pertains only to diesel
powered marine vessels and only an average emission rate for the gas turbines is presented.
Section 2 of this report presents the findings of our literature review of the nine reports provided
by EPA. Section 3 details our analysis of emissions data contained in reports, and the resultant
derivation of emission factors. Section 4 provides an analysis of vessel classifications and
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horsepower to vessel weight relationships. Section 5 summarizes the resultant emission factors
by vessel type, and operating mode.
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2. REVIEW OF RELEVANT DATA
2.1 INTRODUCTION
As noted, the U.S. EPA had identified nine reports in its work assignment for review. All of
these were obtained by EEA from EPA and reviewed to assess the usefulness for this study. The
reports can be classified into two groups of four reports. One group provides detailed tables on
actual emissions data. The second group of four reports are studies that utilize one or more of
the reports in the first group to estimate emission factors, and to estimate emission inventories
for marine vessels operating in a specific region, like the South Coast Air Basin. One report
simply provided data on gas turbines emissions and is not reviewed in this section, but the data is
presented in Section 3.
The reports were reviewed to estimate the applicability of the data or the analysis to the EPA
requirements to calculate emission factors by ship class, type and operating mode. EPA has also
proposed rules for controlling marine engine emissions by defining three engine categories. The
EPA categories are based on individual cylinder displacement and the categories are:
• less than five liters;
• five to 20 liters; and
• greater than 20 liters.
These categories approximately correspond to engines in the high speed, medium speed and slow
speed categories used by IMO and Lloyds in previous analyses. However, the correspondence
may or may not hold true for some specific engine designs.
2.2 FINDINGS ON REPORTS PROVIDING EMISSIONS DATA
The four reports that provide emissions data includes one from British Columbia Ferry
Corporation, one from Environment Canada, one from Lloyd's (in three sections), and one from
the U.S. Coast Guard. Each report is summarized in Appendix B.
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The Lloyd's data1'2'3 is the most detailed although there are some inconsistencies in the data. For
example, the text and table do not agree on the actual number of engines tested, or the type. Data
on engine tests are reported in Appendices, but engine make and displacement are not reported.
In addition, the Lloyd's data also indicated large inconsistencies in the measured output at full
load versus actual engine ratings. Ostensibly, all engines were tested at idle, 25, 50, 75, and 100
percent of full power; yet in a majority of cases, the 100 percent rated power as measured on the
emissions test differs from the engine rated power by as much as ±50 percent. While reductions
in power associated with a service derating is possible and production variations of ±10 percent
may be reasonable, such large differences are cause for concern, especially as they are
unexplained in the text.
However, it should be noted that for most engines, full output corresponded to 83 ±17% of rated
power, while about ten engines have measured power either below 66 percent of rated or over
101 percent of rated power. Results indicate generally well behaved CO emission factors as a
function of percent of rated power but HC and NOX emissions dependence on load varies both in
magnitude and direction across engines as a function of load. In general, absolute emission rates
can vary across engines but the emissions profile for diesel engines as a function of load do not
vary greatly. The variations as plotted in the Lloyds report are so large across engines that it
raises questions on the data and test procedure.
The BC Ferry Test Program report5 appears incomplete and has several inconsistencies that
make the data difficult to use. The main issue is that the test procedure was conducted at two
different, undefined conditions labeled "normal cruise" and "docking operation". Data on eight
engines are presented, (the tables show nine engine tested at normal cruise), but the test
conditions relative to the engine rated power are very inconsistent across engines. Engine data is
inadequate to determine what EPA category they may fall into. Data presented indicates that
five were medium speed diesels, while three are high speed engines (but the data on one high
speed engine shows an improbably high RPM figure for a 4500 kW diesel). Only fuel specific
emission rates are reported for the engines.
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The Environment Canada report6 provides data on 11 engines tested on three modes:
maneuvering, low speed cruise and high speed cruise. The report does not describe how these
modes are defined and whether the relative load on the engine (or load factor) was similar across
the 11 engines. Only fuel specific emission indices are reported, and there are very large
variations across engines in a similar category. Not enough data is provided to determine how
these engines fit into the EPA categories. EEA attempted to obtain more detailed data on the test
procedure and measured emissions from Environment Canada, but could not do so in the time
available.
The tests conducted by the Coast Guard4 were on six ships with two engines each (one ship also
had two gas turbine engines in addition to the diesels). The test procedure was ostensibly
conducted at idle, 25, 50, 75, and 100 percent of maximum power, although here again, there
appear to be large differences in some instances between reported maximum power and engine
ratings. In one instance, the observed power is 85 percent higher than the engine rating
provided. Fuel specifications and engine type information (two-stroke/four-stroke) was not
provided.
Across all of the four reports, emissions data is available on 20 slow speed engine, 51 medium
speed engines and eight high speed engines, plus an additional ten auxiliary engines whose
characteristics are not listed. It is not clear if these have been any QA/QC on the data, since the
data appear to have certain inconsistencies.
Table 2-1 summarizes the data available and the test procedure used, to the extent it is
documented.
2.3 SUMMARY OF REPORTS ANALYZING EMISSIONS DATA
Of the four reports in this category, three were reports that developed marine emissions,
inventories for specific regions. The earliest (1991) report is by Booz-Allen and Hamilton9 for
the ARB that developed inventories for Los Angeles/Long Beach and San Francisco. The report
computed emissions from Ocean-going, harbor, and fishing vessels. Ocean-going and harbor
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TABLE 2-1
SUMMARY OF EMISSIONS DATA
Reference
Vessels
Engines
- Slow speed
- Medium speed
- High speed
- Auxiliary
Test Cycle
Data Reported
Potential
Problems
BC Ferries
8
0
6
3(?)
3
• Normal
cruise
• Docking
• Full Power
for Auxiliary
All except THC
in kg/ton of fuel
Test points
undefined and
varies by engine
Environment
Canada
13
9
1
1
5
• Maneuvering
• Low Speed
• Normal Cruise
• Hoteling for
Auxiliary
engines
All in Kg/ton of
fuel
Test points
undefined. All
engines not tested
at all loads
Lloyds
Register
40
11
36
0
2
• 100% load
• 75% load
• 50% load
• 25% load
• Idle
All except PM,
as raw data
Measured
output at 100%
load unrelated
to rated power
Coast Guard
6
0
8
4
0
• 100% load
• 75% load
• 50% load
• 25% load
• Idle
All in mass per
kW-hr and per
ton of fuel
Measured and
rated power do
not match for
some engines.
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vessels were further divided into four types and five weight or HP classes. Fishing vessels were
subdivided into four HP categories. The operating profile in each port for the three vessel classes
was obtained by surveys. Emissions were calculated using the DOT Port Vessel Emission
Model, that calculates fuel consumption and resulting emissions using existing AP-42 emission
factors. The methodology is relatively simplistic in that emissions are purely a function of fuel
consumption, not load.
A very similar approach was used by Lloyds8 to determine emissions from ferries operated in
Vancouver by the British Columbia Ferry Corporation. The main difference appears to be the
use of engine specific emission factors derived from the Lloyds's test program referenced in the
previous section. The report is not clear how fuel consumption was translated to emissions, i.e.,
by mode or based on aggregate fuel consumption rates.
The two other reports, by Arcadis (previously Acurex), calculate emission inventories for marine
vessels in the South Coast Air Basin. The 1996 report for the South Coast AQMD10 differed
from the 1991 Booz-Allen Report by including Navy and Coast Guard operations. The Acurex
report also used actual data on the HP ratings and fuel consumption (obtained from Lloyds) and
improved the characterization of operations in the South Coast. The Acurex report includes a
very detailed classification of eight ship types, with each ship type subdivided into eight to ten
weight categories. However emissions characterization again appear to be based on calculated
fuel consumption, with the use of emission factors on a unit of fuel consumed as derived by
Lloyds. These emissions appear to have been derived to represent a power setting of about 85
percent of maximum continuous rating (MCR), but there is no documentation of the
methodology used.
The more recent (1999) report by Arcadis (Acurex) for EPA Region IX8 provides an analysis of
marine NOX emissions for the South Coast. The characterization of ship types is quite detailed as
in the 1996 report. This is the only report where emissions in units of work (g/kW-hr) were
derived as a function of percent of MCR. The emission factors on this basis were constructed
from the 'raw' data provided by Lloyds. Surprisingly, the report does not mention the large
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discrepancy between rated and measured power and it is not obvious how the percent of MCR
was derived. Regression analysis of individual data points was utilized to relate NOX emissions
to engine load factor (% of MCR). The regression analysis, however, suggested that NOX
emissions either decline slightly or are independent of MCR. If these results are correct, it would
suggest little or no difference if NOX was treated as a constant or as a function of load.
Nevertheless, the methodology is conceptually superior to using aggregate fuel consumption data
that is multiplied by an emission factor in units of fuel consumption.
2.4 RECOMMENDATIONS FOR ANALYSIS
The review of the emission data available indicated significant inconsistencies in engine power
ratings versus measured power output that are too large to ascribe to engine-to-engine variability,
or a 'service' derating. Moreover, the test procedures used by different organizations are
inconsistent, while the reported results are incompatible with the results from a recommended
EVIO standard test cycles. In most cases, engine displacement is not available, so that the
relationship to EPA engine categories cannot be exactly determined (but could be approximated).
In addition, some reported changes in engine emissions with load are directionally inconsistent
across engines. Hence, the data analysis focused on data cleaning techniques to identify and
correct or reject data that are determined to be in error.
Reports by Booz-Allen, Acurex and Arcadis employ consistent classifications by ship type, but
the Acurex and Arcadis reports have developed more detailed breakouts of each ship type by
weight category. The use of Lloyd's data to determine the engine and auxiliary HP by these
detailed type and weight categories is an improvement over earlier techniques. If engine power
is linearly related to ship characteristics, it is not clear that models require the use of weight
categories for ship types. A linear regression connecting horsepower to ship weight is preferable
relative to analysis by weight categories.
The computation of emissions using fuel consumption as a surrogate load indicator appears to be
both unnecessary and to introduce errors. Indeed, the 1999 Arcadis report has utilized emissions
as a function of engine load factor to directly compute emission at every operating mode that is
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represented in the operating profile. This direct method is preferable to linking emissions to fuel
consumption since the computation of fuel consumption and the translations to emissions
introduce multiplicative errors in emission estimations. EEA suggest a future marine emission
model with four specified modes of operation (e.g., docking, low speed cruise, etc.) where each
type of operation is associated with a single load factor. On the other hand, if emissions in
g/kW-hr are approximately constant with load factors, (as indicated for NOX in the Arcadis
report) different approaches may not lead to significantly different answers.
In addition, time constraints did not allow us to resolve many of the data issues raised. In the
future, EEA recommends that EPA focus on resolving some of the data issues and in expanding
the database.
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3. EMISSION FACTOR DEVELOPMENT
3.1 INTRODUCTION
Ostensibly, six of the reports provided to EEA for review present the results of marine engine
emissions testing.1"6 However, three of these reports do not present the described emissions test
data in sufficient detail to support the fundamental analysis required for the development of
marine engine emission factors.3'5'6 These reports essentially present the results of the author's
emission factor analysis, but not the underlying data that went into the analysis. Without this
underlying data, the utility of these reports is limited for several reasons. First, the presented
emission factors are expressed in units of emission mass per fuel mass consumed, a metric that
for real-world application requires either knowledge or estimation of fuel consumption rates.
However, fuel consumption rates are not usually measured, but rather estimated from engine
design and loading data, where engine loading itself can usually only be estimated. It seems
inappropriate to introduce additional uncertainty into the emissions estimation process through
the use of fuel mass-based emission factors in lieu of emission factors expressed in more
fundamental units of mass per unit engine work. Second, the presented emission factors
represent the aggregation of an unknown number of individual emission tests, such that the
statistical significance of the reported emission factors can be determined. Third, as
demonstrated below, considerable caution must be exercised in converting measured emission
concentrations into valid emission rates. Without access to the underlying test data, it is not
possible to either ensure that adequate caution has been exercised or that the generated emission
rates are comparable to those developed from other test programs.
Attempts were made to contact the authors of the three reports that do not present underlying
emission test data, but these attempts were not successful in the timeframe available to EEA for
analysis. As a result, the emission factors described below were developed through the statistical
analysis of fundamental test data presented in only three of the emission testing reports.1'2'4 Two
of these reports were prepared by Lloyd's Register of Shipping and consider a wide range of
commercial engine sizes and configurations. The third report was prepared for the U.S. Coast
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Guard (USCG) and considers a number of engines that are representative of marine engines in
use in the USCG fleet. As described below, all three datasets required considerable quality
assurance efforts to ensure that emission factors developed from the reported test data were both
reasonable and accurate.
3.2 LLOYD'S EMISSION TEST DATA
Lloyd's Register of Shipping produced two reports that present the results of individual
commercial marine emission tests.1'2 Together, these reports present test data for a total of 46
main propulsion engines and 2 auxiliary engines as summarized in Table 3-1. Emission limits
for marine engines have historically been established by engine size expressed in terms of engine
rated speed, with nearly all commercial marine engines falling into the low and medium speed
categories. The Lloyd's data are quite comprehensive, covering engines in both speed ranges,
and the test program reports provide a listing of nearly all critical test data parameters, including:
• raw concentration-based emission measurements for nitrogen oxide (NO), sulfur dioxide
(802), carbon monoxide (CO), carbon dioxide (CO2), oxygen (©2), and hydrocarbons
(HC),
• test engine load, speed, and volumetric fuel consumption,
• test engine specifications,
• test fuel density and carbon, hydrogen, nitrogen, and sulfur mass fractions, and
• ambient test conditions.
Nevertheless, it is important to recognize that exhaust mass flow rates are not measured, so the
conversion of measured emission concentrations to emissions mass must be based on theoretical
relationships. With the various parameters measured by Lloyd's, it is possible to estimate
emissions mass (and thus mass emission rates) through the determination of the mass of intake
air required to produce the observed (i.e., measured) combustion products. Ignoring the potential
effects of exhaust non-homogeneity and emissions measurement error as well as the unaccounted
influences of non-measured combustion products (e.g., particulate matter (PM) and nitrogen
dioxide (NO2)), there is only one specific mass of intake air that will produce a given quantity of
combustion products for a given fuel. This specific mass can be calculated by chemically mass
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TABLE 3-1
OVERVIEW OF THE LLOYD'S EMISSION TEST DATABASE
Ship Types
Tested
Bulk Carrier
Container
Dredger
Roll-on/Roll-off
Tug
Tanker
Total Tests
Number
of Ships
Tested
6
2
6
9
7*
9
39
No. of
Main
Engines
Tested
6
2
6
16
7
9
46
No. of
Main
Engine
Tests
37
11
32
90
71
58
299
Average
Tests per
Main
Engine
6.2
5.5
5.3
5.6
10.1
6.4
6.5
No. of
Auxiliary
Engines
Tested
0
1
0
1
0
0
2
No. of
Auxiliary
Engine
Tests
0
5
0
5
0
0
10
Average
Tests per
Auxiliary
Engine
0
5.0
0
5.0
0
0
5.0
* For tugs, testing was performed both with (38 tests) and without (33 tests) another vessel being
pushed. However, the net effect of this dual testing simply represents an increase in the number
of engine loading scenarios tested for tugs.
balancing the input fuel characteristics with measured emission products (both of which are
reported by Lloyd's). Such an approach is analogous to the carbon balance technique employed
in motor vehicle emissions testing to estimate dilution air volumes in constant volume sampling
(CVS) systems.
Given a complete and accurate characterization of: (1) emissions, (2) fuel, and (3) intake air,
chemical mass balancing will produce an accurate determination of intake air mass. Ignoring
any measurement error, the Lloyd's database does provide a complete characterization of the
combustion fuel. Characterization of major emission species (i.e., CC>2 and 62) as well as
several minor emission species is also provided. While the widest possible scope of emission
measurements is desirable for increased precision, relatively accurate mass balancing can be
performed using emission measurements for CC>2 and C>2 alone, as these compounds account for
the bulk of exhaust carbon and oxygen. For marine engines for example, emissions of either are
one to two or more orders of magnitude higher than emissions of either CO or HC. However, no
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measurements of intake air characteristics are provided by Lloyd's. Intake air containing
significant concentrations of carbon or hydrogen can significantly influence chemical mass
balance accuracy. In the absence of specific intake air characteristics, it is typical to assume an
"average" air composition of 21 percent oxygen and 79 percent nitrogen (representing nitrogen
plus other minor, relatively inert, air constituents). Such a presumption was employed in all
mass balance analysis performed for this study.
Several additional issues should be considered in interpreting the Lloyd's emissions test data
used in this study. No PM testing was performed and, therefore, the Lloyd's data are of no value
in determining marine PM emission factors. Additionally, HC measurements are missing for 26
of the 309 emission tests performed. In instances where detailed chemical mass balancing, as
described below, included measured HC, a value of zero was assumed for these 26 tests. This
assumption is expected to result in only minor precision losses for calculated intake air mass as
most combustion hydrogen is emitted as water (H^O), not HC (emitted HC is typically two to
three orders of magnitude lower than emitted H2O). However, all 26 tests were excluded from
the statistical analysis underlying the determination of HC emission factors.
Oxides of nitrogen (NOX) emission factors are of particular interest in this study as NOX
represents a major pollutant emission species from diesel engines such as those used for marine
propulsion. However, the Lloyd's database includes only NO measurements, omitting other NOX
components such as NO2. To estimate total NOX emissions from measured NO data, EEA relied
on supplementary data presented in the text portion of the Lloyd's report1 that summarized NO
to NOX ratios for a range of marine engine emission tests conducted prior to those reported.
These tests reportedly cover a diverse range of fuels and test conditions, but the observed NO to
NOX ratio, as presented in Table 3-2, varies over a relatively narrow range of 0.86 to 0.98, with a
mean and standard deviation of 0.94 and 0.03 respectively. Based on this data, EEA assumed for
the purpose of this study, that emitted NOX is equal to measured NO divided by 0.94.
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TABLE 3-2
LLOYD'S NO TO NOX RATIO FOR MARINE ENGINES
Engine
Type
Propeller
Law
Constant
Speed
Test
Fuel
Fuel 1
Fuel 2
Fuel3
FueU
Fuel 1
Fuel 2
Fuel3
FueU
Idle
0.93
0.96
0.91
0.86
25%
Load
0.93
0.89
0.91
0.87
0.97
0.92
0.96
0.95
50%
Load
0.95
0.91
0.92
0.89
0.98
0.93
0.94
0.94
75%
Load
0.96
0.93
0.92
0.92
0.97
0.92
0.97
0.94
Rated
Load
0.96
0.93
0.96
0.94
0.96
0.93
0.96
0.94
Overall Average = 0.94, Standard Deviation = 0.03
Even though Lloyd's reported ambient temperature, pressure, and humidity data, no ambient
corrections have been applied to any of the emission estimates presented in this study. The
decision to ignore ambient corrections was based on the fact that: (1) no generally accepted
correction algorithms have been developed for marine engines, (2) ambient data is not available
for the USCG data that were combined with the Lloyd's data to generate emission factors (see
Section 3.3 below), and (3) the magnitude of ambient corrections are expected to be minor
relative to the overall variability of the emissions data.
All emissions data for one of the tankers tested by Lloyd's (designated as ship TK7) have been
excluded from statistical emission factor analysis because exhaust O2 measurements are not
reported. Unlike HC, O2 is a major exhaust constituent and no reliable assumptions can be made
regarding intake air mass (and thus exhaust and emissions mass) in the absence of reliable 62
data. As a result, the seven emission tests conducted on tanker TK7 were excluded from the
analysis database.
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All Lloyd's test data not otherwise excluded as described above have been treated with equal
weight in the emission factor analysis conducted for this study. This may result in some bias of
analysis results toward engines with an above average number of associated emission tests, but
there is no obvious means of weighting the data that would ensure less bias than simply treating
all data with equal weight. Lloyd's stated test program design criteria was to conduct testing at
idle and 25, 50, 75, and 100 percent of rated engine output. Therefore, ideally, each engine
would be tested five times at five distinct operating modes. However, as indicated in Table 3-1,
the number of actual tests per engine ranged from five to ten, with tug testing representing the
upper bound due to testing in both "pushing" and "non-pushing" modes.
Because all testing was performed at variable load conditions, applying a weighting factor to all
the test data for a given engine to equate that engine's overall statistical influence to that of a
"five test" engine can result in an unintended bias at specific loads where the weighted engine's
test data carries less influence than data from another engine, even though both represent equally
valid test measurements at the given load. An alternative approach of simply discarding all but
five test data points across the load range for any given test engine is less problematic, but
requires some methodology to select those data points to either retain or exclude. Given the
considerable variability in observed test data, it was concluded that the overall bias induced by
simply retaining all data points was likely to be minor and thus no specific data weighting or
selection/exclusion scheme was employed in this analysis. Follow-up analysis to quantify the
potential magnitude of any bias can be conducted, but is beyond the scope of this analysis.
3.3 U.S. COAST GUARD EMISSION TEST DATA
Environmental Transportation Consultants produced a report for the Volpe National
Transportation Systems Center and the USCG that presents the results of marine engine emission
tests on six USCG vessels.4 In total, the report presents comprehensive test data for 12 main
diesel propulsion engines as summarized in Table 3-3. Summary data are also presented for two
additional gas turbine propulsion engines, but supporting detailed test data are omitted from the
report necessitating the exclusion of detailed gas turbine engine analysis from this study. In
3-6
-------
general, the USCG data are less detailed that the Lloyd's data described in Section 3.2 above, but
reported test data parameters include:
• raw concentration-based emission measurements for NOX, 862, CO, CC>2, 62, and HC,
• raw mass-based emission measurements for PM,
• test engine load, speed, and volumetric fuel consumption, and
• test engine specifications.
Data on fuel specifications, density, and composition was not included, representing the most
critical omission for purposes of this study. Data on ambient test conditions was also omitted,
but this omission is a lesser concern as any ambient adjustments to emissions are expected to be
minor relative to overall data variability.
As described in Section 3.2, fuel characteristics are a necessary element in constructing an
accurate chemical mass balance as required to estimate intake air mass and subsequently exhaust
and emissions mass. Unfortunately, the USCG test data report only describes the combustion
fuel as "diesel" and presents no supporting test data. Therefore, EEA undertook an alternative
analysis approach in an attempt to estimate the characteristics of the unknown USCG diesel
"fuel" as follows.0
Using reported 62 and CC>2 emission concentrations, the stoichiometric CC>2 concentration for
the USCG fuel was derived through regression analysis as summarized in Figure 3-1. The
derived stoichiometric CC>2 concentration (15.2 percent at zero percent 62) can readily be
translated through chemical mass balance to an implied fuel hydrogen to fuel carbon (H to C)
ratio of 1.9127. Such a ratio is not typical for a diesel fuel, instead being more reflective of a
lighter fuel such as gasoline and implying a bias toward a slight under-measurement of CC>2, 62,
or both. Although diesel fuels with H to C ratios above 1.9 have been reported, they generally
represent upper bound H to C fuels and would be quite uncommon as an average fuel
Certainly USCG test fuel specifications varied across test engines. However, fuel specifications can only be
inferred from the aggregate USCG data and, therefore, derived specifications represent average, rather than
specific fuel characteristics.
3-7
-------
TABLE 3-3
OVERVIEW OF THE USCG EMISSION TEST DATABASE
Ship Types
Tested
High Endurance Cutter (WHEC)
Medium Endurance Cutter (WHEC)
Patrol Boat (WPB)
Utility Boat (UTB)
Total Tests
Number
of Ships
Tested
1
2
2
1
6
No. of
Main
Engines
Tested
2*
4
4
2
12*
No. of
Main
Engine
Tests
30
60
52
30
172
Average
Tests per
Main
Engine
15.0
15.0
13.0
15.0
14.3
No. of
Auxiliary
Engines
Tested
0
0
0
0
0
* The report actually presents summary results for 2 WHEC diesel propulsion engines and 2
WHEC gas turbine propulsion engines, but only includes detailed test data for the two diesel
engines. This "missing" data required that the two gas turbine engines be excluded from
detailed statistical emission factor analysis in this study.
characteristic over the entire USCG emissions testing program. As a result, EEA elected to
utilize the average fuel specifications for the various "diesel" fuels included in the Lloyd's
marine engine test program as a better means of approximating the average unknown fuel
characteristics associated with the USCG data. Table 3-4 presents the statistical specifications of
the various Lloyd's test fuels. The average "all fuels" specifications were used for all USCG
chemical mass balance analysis in this study.
Like the Lloyd's data, several additional assumptions are required in processing the USCG
database. In general, however, required assumptions for the USCG data are more extensive than
those associated with processing the Lloyd's database, but inclusion of the USCG data in this
study is considered to be critical for two primary reasons. First, the USCG data serves as the
only independent means of validating the basic trends observed through the Lloyd's test data.
Second, the USCG database is the only database provided to EEA for review that includes PM
3-8
-------
Derivation of USCG Fuel H to C Ratio
0)
a
0)
a
25
20
15
10
0
0
O2 = 20.956- 1.375(CO2)
(t=353) (t=-135)
r2 = 0.99, F = 18264, Obs = 142
Stoichiometric CO2= 15.242%
Implied Fuel H to C Ratio = 1.9128
6 8 10 12
CO2 (percent dry)
14
16
18
FIGURE 3-1
-------
TABLE 3-4
LLOYD'S MARINE ENGINE FUEL SPECIFICATIONS
Parameter
Number of Observations
Density
Carbon Content
Hydrogen Content
Nitrogen Content
Sulfur Content
H to C Ratio
N to C Ratio
S to C Ratio
Average
Standard Deviation
Average
Standard Deviation
Average
Standard Deviation
Average
Standard Deviation
Average
Standard Deviation
Average
Standard Deviation
Average
Standard Deviation
Average
Standard Deviation
Gas Oil
25
0.8553
0.0056
0.8651
0.0032
0.1293
0.0030
0.0020
0.0021
0.0036
0.0021
1.7812
0.0468
0.0020
0.0020
0.0016
0.0009
Heavy
Fuel Oil
9
0.9816
0.0055
0.8606
0.0078
0.1080
0.0024
0.0040
0.0024
0.0274
0.0077
1.4954
0.0338
0.0040
0.0024
0.0120
0.0034
Intermediate
Fuel Oil
2
0.9900
0.0000
0.8580
0.0004
0.1042
0.0001
0.0019
0.0003
0.0358
0.0002
1.4477
0.0010
0.0019
0.0003
0.0156
0.0001
Light
Fuel Oil
19
0.9539
0.0297
0.8601
0.0047
0.1150
0.0075
0.0033
0.0005
0.0215
0.0094
1.5937
0.1029
0.0033
0.0005
0.0094
0.0041
All Fuels
55
0.9149
0.0587
0.8624
0.0052
0.1200
0.0103
0.0028
0.0019
0.0149
0.0125
1.6576
0.1385
0.0028
0.0019
0.0065
0.0055
data. Nevertheless, the following issues should be considered in evaluating the USCG marine
emissions data analysis.
Many of the HC measurements included in the USCG database are questionable and five of the
172 tests are missing HC measurements altogether. Additionally, about 17 percent of the
reported HC measurements indicate concentrations below 0.001 ppmC, while nearly all of the
remaining 83 percent exhibit concentrations over four orders of magnitude higher (often for the
same engine at the same test conditions). For purposes of this analysis, these concentrations
were assumed to equal 0.001 ppmC, but more in depth follow-up analysis beyond the scope of
3-10
-------
this study may yield sufficient information to exclude these data as erroneous. As was the case
with the Lloyd's data, in instances where detailed chemical mass balancing, as described below,
included measured HC, a value of zero was assumed for all five tests where HC was unreported.
This assumption will result in only minor precision losses for calculated intake air mass as most
combustion hydrogen is emitted as H2O, not HC. As with the Lloyd's data, all five tests were
excluded from the statistical analysis underlying the determination of HC emission factors. At
the same time, all HC measurements reported as being below 0.001 ppmC were retained
throughout the entire analysis and could serve as a downward bias on estimated HC emission
factors should such measurements ultimately be identified as erroneous.
USCG HC measurements were assumed to be reported as dry since they were based on bag
sampling at a point apparently downstream of a sample line water trap. Since Lloyd's HC
measurements are report as wet, a conversion factor was applied to the USCG HC data to
convert the reported data to a wet measurement equivalent. This conversion factor was derived
from analysis of the Lloyd's test data, through which it was determined that the average wet to
dry exhaust concentration ratio was 0.9658, with a standard deviation of 0.0158 (based on 1215
data points associated with 302 individual test records evaluated over four mass balance
techniques plus 7 individual test records evaluated over a single mass balance technique).
In an analogous fashion, the USCG data reports NOX while the Lloyd's data reports NO as a NOX
surrogate. As described in Section 3.2, Lloyd's claims an average NO to NOX ratio of 0.94, a
factor used by EEA to convert Lloyd's NO data to a NOX equivalent. This same factor was also
used to convert USCG reported NOX data to an NO equivalent.
Unlike the Lloyd's data, which was treated without weighting individual data points, the USCG
data was aggregated before statistical processing. This aggregation was necessary to address the
fact that USCG data was reported individually for each of up to three tests performed on the
same engine at the same load conditions. In effect, multiple data points were reported for
identical test conditions, creating an inherent weighting factor of up to three for the USCG data
versus the Lloyd's data. To reduce the weight of the USCG data to unity, all data points
3-11
-------
applying to identical test conditions were collapsed into a single data point representative of the
average reported test results for the component data.
Such an approach is generally consistent with the "average" test results for each unique set of
test conditions as reported in the USCG test document.4 Nevertheless, the USCG reported
average test results will vary in some circumstances from those used in this study. This results
from the fact that the average test results presented in the USCG report include the effects of
partial tests, whereas those used in this study do not. For example, in the USCG report, results
for three tests, two of which include measurement of HC, CO, NOX, SC>2, 62, CC>2, and PM and
one of which only includes measurement of HC are averaged over two tests for CO, NOX, SO2,
O2, CO2, and PM and over three tests for HC. In this study, all species are averaged over only
the two comprehensive tests and the third, HC-only test is ignored. This is deemed a more
appropriate aggregation methodology since there is no way of knowing how unmeasured
emission species will have varied over the third test in accordance within any observed variation
in HC. In addition, any individual tests for which inconsistent air/fuel ratios were calculated
across the differing estimation methodologies described in Section 3.4 below, were also excluded
from the aggregation process.
Finally, the USCG report also included specific fuel consumption estimates only for the average
engine speed and output calculated for each unique set of test conditions. Since individual test
results were re-aggregated for this study in accordance with the modified "acceptance" criteria
described above, it was necessary to estimate fuel consumption for each individual test, instead
of simply knowing the aggregate test average. In the absence of specific engine maps, EEA
employed a simplifying assumption that fuel consumption varies linearly with engine speed for
outputs "near" the specific engine output for which the USCG reported fuel consumption.
Observed engine speed variations ranged from only -3 to +4 percent of reported average engine
speed so that calculated fuel consumption adjustments averaged only 0.01 percent, with a
maximum adjustment of 1.1 percent.
3-12
-------
3.4 EMISSIONS DATA ANALYSIS
As described above, exhaust mass is not a measured component of either the Lloyd's or USCG
databases. Nevertheless, an estimate of exhaust mass is necessary to covert concentration-based
emission measurements into mass-based equivalents. To estimate exhaust flow for each
emissions test included in the combined Lloyd's/USCG database, a chemical mass balance was
employed using intake fuel characteristics and measured exhaust components to estimate the
effective combustion air/fuel (A/F) ratio. This A/F ratio estimate can then be combined with fuel
flow measurements reported for each emissions test to derive an estimate for intake air mass, that
when added to intake fuel mass results in the required estimate of exhaust mass. In referring to
intake air, it is worth noting that this includes both intake and scavenge air (as applicable,
typically for two stroke engines) and that the estimated A/F ratio is the effective mass ratio of all
air (regardless of the timing or location of its injection into the flow stream) to combustion fuel.
While it is not possible to separate actual intake air from scavenge air based on exhaust
measurements alone, such a separation is not required to estimate total exhaust mass, which is
the critical analysis parameter for this study.
Figure 3-2 presents a summary of the A/F ratios calculated on the basis of Lloyd's and USCG
reported exhaust components. Based on the calculated ratios, EEA has some concern over the
integrity of the reported emissions data. This concern stems primarily from the magnitudes of
the calculated A/F ratios over the entire engine load range, defined by EEA as the "fractional
load" or the ratio of the reported engine output during the emissions test to the reported rated
engine output. Even at 100 percent rated load, the Lloyd's database generally implies A/F ratios
between 30:1 and 40:1. This is substantially higher than the 20:1 or so A/F ratios that would be
expected from previous experience with on-road diesel engines. Moreover, while calculated A/F
ratios approaching 80:1 are not unexpected at low load ranges, values of 1000:1 or, in one case,
4000:1 are certainly cause for concern. As noted above, scavenge airflow for two stroke engines
could explain some of the excessive A/F ratios, but the generally apparent over-prediction is
observed for both two and four stroke engines. Since EEA has no information on the number of
engines employing secondary air scavenging or the mass of air flow associated with such
3-13
-------
Implied A/F Ratio
Simple Carbon Balance
A/F
^
0
0
O
^
0
O
10
O Lloyds (Consistent A/F)
4 USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
A A
0%
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-2
-------
systems on marine engines, it is not possible to elaborate further (for this study) as to the role
that secondary scavenging systems may have on apparent A/F ratio over-prediction.
In an attempt to isolate those data that are most highly suspect, EEA undertook a series of
alternative chemical mass balance approaches to estimating effective A/F ratio. The first
approach, designated for this study as the simple carbon balance approach, estimates A/F ratio on
the basis of fuel H to C ratio and exhaust C>2 to CC>2 ratio alone. Without presenting the detailed
mass balance derivation here, this method presumes that all intake fuel and air is fully
represented in the exhaust as CC>2, H^O, and unreacted air (represented as 21 percent C>2 and 79
percent molecular nitrogen (N2)). Furthermore, this method represents a commonly employed
mass balance approach in that it accounts for major exhaust constituents, providing a reasonably
reliable A/F ratio estimate. However, in instances where exhaust constituents may not be
measured accurately, there are more detailed alternative chemical mass balance methods that can
be employed for validation purposes.
A more detailed carbon balance approach considers all measured exhaust constituents that
contain either carbon or hydrogen (HC, CO, and CC>2 in the database available for this study).
This approach can provide a considerably more accurate A/F ratio estimate when significant
concentrations of either CO or HC are measured. A third A/F ratio estimation approach
employing a detailed oxygen (rather than carbon) balance considers all measured oxygen,
nitrogen, and hydrogen containing exhaust species (CO, CO2, 62, NO, SO2, and HC in the
database available for this study). Finally, a fourth A/F ratio estimation approach based solely
on the amount of intake air required to completely combust the intake fuel and provide the
measured quantity of "excess air" in the exhaust was also employed. This excess air approach
uses only measured exhaust oxygen and measured fuel characteristics to satisfy the required
chemical mass balance criteria.
Figures 3-3 through 3-5 present the results of the alternative A/F ratio evaluations. The three
figures each present a plot of the estimated A/F ratio for one of the three alternative mass balance
methods employed in this study versus the A/F ratio estimated using the simple carbon balance
3-15
-------
approach. The considerable variation between three of the four approaches is easily observed.
As might be expected, the simple carbon balance and detailed carbon balance approaches
produce similar A/F estimates since both principally rely on a balance of intake and exhaust
carbon. The excess air approach, which relies on the major exhaust oxygen containing
component (i.e., air) as its primary mass balance criteria indicates significant deviation from the
carbon-based approaches, but the greatest deviation is observed for the detailed oxygen balance,
which relies on all exhaust oxygen containing compounds as its mass balance criteria.
Moreover, the disagreement between the four approaches gets more pronounced as the estimated
A/F ratio increases, with the oxygen-based approaches generally estimating lower A/F ratios
than the carbon-based approaches. Given that exhaust mass and thus emissions mass are directly
dependent on A/F ratio, there are clear concerns associated with the raw exhaust measurements
reported in the marine engine database employed in this study.
Further evidence of the potential problems with the marine engine emissions databases can be
observed by comparing measured CO2 and O2 concentrations. Figure 3-6 presents such a
comparison, where the dashed lines represent the theoretical relationship between measured CO2
and O2 as implied by the measured characteristics of the Lloyd's test fuels. Deviations from
these theoretical relationships are indicative of instances in which measurement error for either
CC>2, O2, or both are likely. Clearly, such deviations are quite common at low CO2
concentrations, which correspond to high O2 and thus high A/F ratios. More troubling, however,
is the fact that significant deviations are observed across the full measured CO2 spectrum.
Given the concerns associated with the reported exhaust emissions data, it would be
advantageous to perform a more in depth analysis of the test programs underlying the reported
data. However, such an analysis is beyond the scope of this study. As an alternative, EEA
quantified the magnitude of the variation between the alternative A/F ratio estimation
methodologies and retained for statistical analysis, only those tests for which consistent A/F
ratios were observed across the alternative estimation approaches. For this study, consistent A/F
ratios were defined as instances in which: (1) three of the four employed A/F ratio estimation
3-16
-------
A/F Ratio Comparison
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-------
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FIGURE 3-4
-------
A/F Ratio Comparison
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A/F - Simple Carbon Balance
10000
FIGURE 3-5
-------
CO2 / O2 Relationship
O Lloyds (Consistent A/F)
*USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
0
4
6 8 10 12
Measured CO2 (percent dry)
14
16
18
FIGURE 3-6
-------
methodologies produced cumulative absolute estimate deviations of no more than 15 percent
relative to the estimate produced by the simple carbon balance approach and (2) none of the three
otherwise consistent A/F ratio estimates varied by more than 10 percent from the estimate
produced by the simple carbon balance approach. The choice of these retention criteria are
somewhat arbitrary, but deviations of this magnitude yield reasonably consistent mass emissions
estimates, well within the overall uncertainty of the underlying test programs.
All figures presented in this section allow inspection of both consistent and inconsistent A/F ratio
test data. Mass emission estimates presented in these figures and used for subsequent emission
factor analysis represent the arithmetic average of the mass emission rates associated with the
three most consistent A/F ratio estimation methodologies: the simple carbon balance, the detailed
carbon balance, and the excess air approaches. Figure 3-7 presents a distribution of the
cumulative absolute deviations associated with these same three A/F ratio estimation approaches
for the combined Lloyd's and USCG database. As can be noted, approximately 18 percent of all
reported emission tests do not meet the consistent A/F ratio criteria. Such records are excluded
from all emission factor analysis in this study but have been included on all figures to allow the
reader to evaluate the potential impact associated with this exclusion.
3.5 EMISSION FACTOR DEVELOPMENT
Based on the database development and acceptance criteria presented in the preceding sections,
EEA compiled an overall emission factor analysis database consisting of 291 "consistent A/F
ratio" emission tests spanning the full range of engine operating loads (i.e., from idle to 100
percent rated output). Figure 3-8 summarizes the overall test engine and operating loads
represented in this database. As indicated, the bulk of the large engines tested by Lloyd's fail to
meet the A/F ratio acceptance criteria, so that the overall database includes only a modest
number of tests on engines rated above 10,000 kilowatts (kW). Given the under-representation
of large marine engines in this database, further investigation of large engine performance
relative to both emissions measurement accuracy and consistency with the emission factor
algorithms presented below is recommended.
3-21
-------
Consistency of A/F Ratio Estimates
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FIGURE 3-7
-------
Test Data Load Coverage
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5000
10000 15000
Test Load (kW)
20000
25000
FIGURE 3-8
-------
Figures 3-9 through 3-15 present measured (i.e., concentration-based) emissions by fractional
engine load for each of the emission species represented in the analysis database. Although
overall measurements for most species span several orders of magnitude, clear trends are
observable for all species except CO, HC, and 862. The lack of a distinguishable trend in the
raw CO and HC data is likely the result of the relatively low production of both species across
the entire load range of diesel engines. The lack of a load-based trend for SO2 is due to the direct
relationship of SO2 emissions to fuel sulfur content, which varies considerably across the
emission test database.
Figures 3-16 and 3-17 present reported fuel consumption by absolute and fractional test load
respectively. As indicated, the distribution of reported fuel consumption over fractional load
space is quite "well behaved." Regression analysis indicates that fuel consumption is inversely
related to fractional engine load as follows:
Fuel Consumption (g/kW-hr) = 14.1205 (I/Fractional Load) + 205.7169
(t = 22.75) (t = 32.88)
[r2 = 0.64, F = 518, Observations = 291]
Based on this behavior, along with the previously illustrated (see Figure 3-2) well defined
behavior of A/F ratio (and thus exhaust mass) with fractional load, statistical regression
structures based on emissions mass by fractional load were investigated as the most promising
basis for emission factor algorithms. It is worth noting that previous studies have investigated
emission mass in terms of fuel consumption alone and while such an approach may yield
reasonable emission estimates, fuel consumption is itself dependent on fractional load as
illustrated in Figure 3-17 and, therefore, is not an appropriate independent regression parameter
in instances where fuel consumption is not measured directly (with the exception of SO2
emissions, which are directly dependent on highly variable fuel sulfur content). While a two step
conversion from fractional load to fuel consumption to emissions mass is certainly feasible, the
combined uncertainty associated with such a process is surely larger than the single step
estimation of emissions mass from a given fractional load.
3-24
-------
Measured CO2
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FIGURE 3-9
-------
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100%
120%
FIGURE 3-10
-------
10000
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1000
100 -
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0%
O Lloyds (Consistent A/F)
4 USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-11
-------
Measured CO
10000
-I \J\J\J\J
1000 -
^
>
a 10° -
c.
o
u
10 -
1
O Lloyds (Consistent A/F) 4 USCG (Consistent A/F)
----------- (- ------- A Lioyos ^rconsistent t\/r) w UoULr ^inconasuenL i\/r)
v °
__ V/: ______ V_ _____ y_ _______ JF-^ ------------ O -------------- -^ ----------
AAp-t U ___ ^-^ ^* O _<_k _^
4fUQ O O O • w W OQ On
JLPo_v ^OA^ J5 rf> ilft^o « o
™C^^«_v*^2) _*° oQ ^ oUo o ST ° «Cb 9p
^S^^w-^oSS^XTOy-^Q^?0 ^^ V°qi .SoQcP cfi°q> ^ o
**^20 O OOA ^O WOf ^ rv ^C?3:"AQQ °°
£_. /^ • v xi «VA ^>a \/\ jncJJ\Ti fR^Tn
i^ S_r__?i_iOOO ° n 0 O ^ o Lfl OrL *rn O rt
A°ry* 2r rv A -»o r» rP ^o ^L ° n
j& O rrt^v" O o ° CT^" ^^ Q rvn r\ °
. _|\A -** - ' -\JJ A" --------------- •»*- » - - ^j( ------------------»« y- u - -y ..........
A MA A /"\ O
y»- O__ __ W
OA A /"«
t_ ------------------ £±- - - - \J
! A ! A
Af\- ' A
_._._._._._._._._._._._._._._._._._ y. ___________ _^ __________________
III
O,
_____________________________________________________________
1 1 1 1 1 1
0% 20% 40% 60% 80% 100% 120%
Fractional Load
FIGURE 3-12
-------
Measured HC
1 000 0 *
100.0 -
u
I 10.0
u
ffi
1.0
n 1
_ -ta . _-_-_ -\s- -------------------------
^A _w~v f^
J*M ^ Q (0 Q "•*
QflHyP Q) jCto Av. Cj> CO O O C5
A^rf*3 OJ^K&cP °ff~ °(icft OK® o ° «n~ « ®
^> ^
J \ ^^ ^? A 3a ^^^^fl? ^"^ ^^/ ff^C^
/vk ^5 Jrt ^% ^*^^J N^^ ^J^'
«y QJ . Q» .»
o»*o" "
»(P^&Qg^ ^g.
OO ^) **^3 ?v Oo^ O
._ A O Q ^"^ O O
*_ O ia
u A **
\j
n\ O & O
• * *A * *
^ ____ _^ _____________
• A
^
"""Vv ,.....,..
•
0% 20% 40% 60%
Fractional
* *
>----------------------------
•
* :
• ^
O Lloyds (Consistent A/F)
* USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
I I
80% 100%
Load
120%
FIGURE 3-13
-------
10000
1 \J\J\J\J
1000
E
a 100-
0
C/5
10
1
Measured SO2
O Lloyds (Consistent A/F) 4 USCG (Consistent A/F)
A Lloyds (Inconsistent A/F) • USCG (Inconsistent A/F)
n ^ r» O
^v ^5 13- \rt ^^ ^^ ~ ^^i j*. C7*' v^^", x^t. jc it *K ^1^-fc.
^^ ^* ^^ ' ^^ »lrft f\ /
V 3 °g^?d cbo
Q.jA"^ Q O
L c«o *3 w&sf^ cp ^«»c^^ o ft n a"33 n rO
v O
^ ^^
» ' ^^ ' ^^
^h i ^V i ^k i ^p
™ ^ i ^ i
A
4 ; ;
0% 20%
ii
40% 60% 80% 100%
Fractional Load
120%
FIGURE 3-14
-------
Measured PM
1 n n
1U.U
=
o
I 1.0
s
PH
n 1
---------- O Lloyds (Consistent A/F)
~_ ~_ ~* ~_ ~_ ~_ ~_ ~_ ~_ *USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
* ;
i !•
,
^ A
* A
• 4
• • ^ *
A
t
» * *
0% 20% 40% 60% 80% 100% 120%
Fractional Load
FIGURE 3-15
-------
Fuel Consumption Data by Absolute Load
10000
*
1000
to
E
B
5C
o
u
100
10
O Lloyds (Consistent A/F)
* USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
10
100
1000
Test Load (kW)
10000
100000
FIGURE 3-16
-------
Fuel Consumption Data by Fractional Load
10000
1000 -
E
B
5C
=
O
U
13
B
100 -
10
0%
20%
O Lloyds (Consistent A/F)
* USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
Consistent Data Regression Line
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-17
-------
Figures 3-18 through 3-26 summarize work-specific mass emission rates by species based on the
chemical mass balance of parameters reported in the combined Lloyd's and USCG database. In
general, all species display an inverse exponential distribution with fractional load. Although the
behavior of the work-specific emission rate data is at least as good as expected given the wide
range of engines tested, an expected upturn in the work-specific emission rate for NOX at high
fractional loads is not readily apparent. Nevertheless, to check for the potential existence of such
a trend, both full and partial load range regression structures were evaluated.
To confirm the validity of an inverse exponential relationship between mass emissions and
fractional load as opposed to a simple linear relation, EEA regressed the emissions/load data
over both linear and inverse exponential structures. In all cases, excepting 862 as discussed
below, the inverse exponential relations exhibited substantially better statistics (i.e., higher
correlation coefficients and more significant regression parameter statistics). Restricted load
range regressions evaluated to determine whether the inverse exponential relations were most
appropriate over the entire fractional load range or whether specific fractional load ranges were
better represented with alternative linear algorithms, revealed similar results. Specifically,
separate regressions over the 0-20 percent and 20-100 percent fractional load ranges were
constructed to determine if a better inverse exponential fit over the lower load range or an
alternative linear fit over the upper load range might be more appropriate than an inverse
exponential fit over the full fractional load range. For all emission species (again excepting
862), it was evident that the best statistical fit of the reported emissions data was obtained with
the inverse exponential relations over the full fractional load range. In no case did any linear
relation over the full or upper load range (20-100 percent) yield better statistics. After
determining the superiority of the inverse exponential approach, the most appropriate values for
the fractional load exponents were evaluated, although all regressions yielded surprisingly good
fits for an initially evaluated exponent of negative unity. Alternative exponent value regressions
were selected as the basis for the best fit regression only in cases where such values produced
significantly improved statistics relative to a unity exponent. Table 3-5 presents the results of
this regression analysis for each emission species evaluated.
3-34
-------
PM Emission Rate Data
100.0
10.0
O Lloyds (Consistent A/F)
« USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
Consistent Data Regression Line
1.0 -
0.1
0%
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-18
-------
NO Emission Rate Data
1000
100
I
10
O Lloyds (Consistent A/F)
)
___________
AA
L«Zl
\£~
\rtfA
war A
*Y?fe> r^O
4 USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
Consistent Data Regression Line
0%
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-19
-------
N(X Emission Rate Data
1000
100 -
O Lloyds (Consistent A/F)
* USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
Consistent Data Regression Line
10
0%
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-20
-------
NO2 Equivalent NOX Emission Rate Data
1000
100
Lloyds (Consistent A/F)
USCG (Consistent A/F)
Lloyds (Inconsistent A/F)
USCG (Inconsistent A/F)
Consistent Data Regression Line
I
10
0%
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-21
-------
SO2 Emission Rate Data
I
Q 30
O Lloyds (Consistent A/F)
A Lloyds (Inconsistent A/F)
Consistent Data Regression Line
0
0
10 15 20
Fuel Sulfur Flow (g/kW-hr)
25
30
FIGURE 3-22
-------
CO Emission Rate Data
1000.0
100.0 -
£ 10.0 H
o
u
1.0 -
0.1
O Lloyds (Consistent A/F)
4 USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
Consistent Data Regression Line
-------
CO2 Emission Rate Data
10000
o
u
1000 -
Lloyds (Consistent A/F)
USCG (Consistent A/F)
Lloyds (Inconsistent A/F)
USCG (Inconsistent A/F)
Consistent Data Regression Line
100
0%
20%
40% 60% 80%
Fractional Load
100% 120%
FIGURE 3-24
-------
O2 Emission Rate Data
1000000
100000
I 10000
1000
100
Lloyds (Consistent A/F)
USCG (Consistent A/F)
Lloyds (Inconsistent A/F)
USCG (Inconsistent A/F)
Consistent Data Regression Line
0%
20%
40% 60% 80%
Fractional Load
100% 120%
FIGURE 3-25
-------
HC Emission Rate Data
1000.000
'-
Bt
100.000 -
10.000 -
1.000
0.100
0.010 -
0.001
O Lloyds (Consistent A/F)
* USCG (Consistent A/F)
A Lloyds (Inconsistent A/F)
• USCG (Inconsistent A/F)
Consistent Data Regression Line
0%
20%
40% 60% 80%
Fractional Load
100% 120%
FIGURE 3-26
-------
TABLE 3-5
MARINE ENGINE EMISSION FACTOR ALGORITHMS
Statistical Parameter
Exponent (x)
Intercept (b)
Intercept t-stat
Significant intercept t?
Coefficient (a)
Coefficient t-stat
Significant coefficient t?
o
F-stat
Significant F-stat?
Observations
PM
1.5
0.2551
7.780
Yes
0.0059
23.143
Yes
.95
536
Yes
31
NO
1.5
9.5181
24.154
Yes
0.1146
19.391
Yes
.57
376
Yes
291
NOX
1.5
10.4496
24.154
Yes
0.1255
19.391
Yes
.57
376
Yes
291
NO2
1.5
15.5247
24.154
Yes
0.1865
19.391
Yes
.57
376
Yes
291
SO2
n/a
-0.4792
-1.124
No
2.3735
28.924
Yes
.78
837
Yes
239
CO
1
0.1548
0.323
No
0.8378
17.700
Yes
.52
313
Yes
291
CO2
1
648.6
33.957
Yes
44.1
23.374
Yes
.65
546
Yes
291
O2
1.5
1298.1
4.101
Yes
107.9
22.769
Yes
.64
512
Yes
291
HC
1.5
0.3859
1.429
No
0.0667
17.064
Yes
.52
291
Yes
271
Dry
Exhaust
1.5
8982
6.390
Yes
489
23.239
Yes
.65
540
Yes
291
H2O
1
220.09
29.806
Yes
15.92
21.839
Yes
.62
477
Yes
291
Wet
Exhaust
1.5
9243
6.557
Yes
491
23.271
Yes
.65
541
Yes
291
1. All regressions but SO2 are in the form of: Emission Rate (g/kW-hr) = a (Fractional Load)"x + b
2. Fractional load is equal to actual engine output divided by rated engine output.
3. The SO2 regression is in the form of: Emission Rate (g/kW-hr) = a (Fuel Sulfur Flow in g/kW-hr) + b
-------
SC>2, due to its obvious dependence on fuel sulfur content, is treated in a different fashion than
the remainder of the emission species. Theoretically, work-specific 862 emissions should
approach two times work-specific fuel sulfur consumption (i.e., the ratio of the molecular weight
of SC>2 to elemental sulfur is 64.0628/32.064, or 1.998), depending on the relative insignificance
of other sulfur sources (e.g., sulfur compounds in intake air) and sinks (e.g., sulfate emissions).
Since a direct linear relationship (with a zero intercept and a coefficient of about two) should be
evidenced, such a regression structure was evaluated for SC>2 in lieu of the load-based regression
structures described above for other emission species.
The resulting regression statistics are presented in Table 3-5, where it is evident that the proper
zero intercept was derived, but that the derived fuel sulfur coefficient (2.37) is about 20 percent
too high. While this lends further support to an overestimation bias in the implied effective A/F
ratio of the underlying emission test data (i.e., A/F overestimation implies exhaust mass
overestimation, thereby implying emission species overestimation) and further investigation into
this phenomenon is recommended, it is not possible within the time or resource constraints of
this study to elaborate further. Certainly, a 20 percent error in emissions estimates in not
unreasonable given the overall variability of emission rates across engines. Nevertheless, the
apparent overestimation of 862 implies a directional bias that should be addressed. In the
interim, EEA recommends using the theoretical coefficient for SC>2 production (i.e., 1.998) in
place of that presented in Table 3-5.
It is also important to note that statistics presented for NC>2 do not represent direct nitrogen
dioxide emissions, but rather the NC>2 equivalent mass of emitted NOX. In effect, NC>2 emission
rates reflect the net emission rate of NOX assuming all NOX is converted to NC>2 (through
oxidation from a source not accounted for in the intake/exhaust stream, such as post-exhaust
atmospheric oxidation). This emission rate was produced as requested by the EPA, but should
be recognized as the maximum potential post-exhaust contribution to atmospheric NC>2 and not
Of course, carbon containing emission species are equally dependent on fuel carbon content. However, while total
fuel consumption is an acceptable surrogate for fuel carbon consumption due to the fact that carbon comprises the
bulk of the total fuel, the considerable variability of sulfur content across fuels makes SO2 emissions dependent
not on just fuel consumption per se (and thus co-dependent on load), but on fuel sulfur consumption in particular.
3-45
-------
an indication of directly emitted NC>2.
Statistics associated with each of the various regression structures evaluated by EEA are
presented in Appendix A. This includes both the full and partial load range regression structures
evaluated as well as separate regressions for: (1) all database records and (2) only those database
records satisfying the A/F ratio acceptance criteria discussed above. The improvement in
regression statistics for consistent A/F ratio records (designated in Appendix A as the "Yes Data"
regressions under the column labeled "A/F Criteria") relative to those of the "All Data"
regressions across emission species is obvious and further illustrates the need to address any
remaining uncertainty in A/F ratios (and thus exhaust and emission species mass) to minimize
emission factor uncertainty.
The regression statistics presented in Table 3-5 apply to the aggregate emissions test database
and do not distinguish between the various engine types (e.g., two stroke versus four stoke) or
diesel fuels (e.g., distillate, light residual, etc.) encountered in marine vessel operations. Study
time and resource constraints as well as underlying test program structure prohibit an in-depth
evaluation of whether a finer resolution of marine vessel emission rates is appropriate. For
example, more two stroke engine data for which consistent A/F ratio estimates can be developed,
more larger engine emission data in general, more data using less common fuels, and data
collected from the same engine while operating on different fuels is critical to isolating and
quantifying distinctions between any or all of these elements. Given the current size and
construction of the underlying emissions test database, it is not possible to separate simple
engine-to-engine variability from potential engine or fuel type influences.
Nevertheless, to investigate the potential for such distinctions and provide an indication of the
need for further database enhancement, regression statistics for both two versus four stroke
engines and the various fuel types identified in the Lloyd's database were generated. Regression
statistics for these various data sets are included in Appendix A. Figures A-l through A-l 1 plot
all consistent A/F ratio test data by engine type and emission species, while Figures A-12
3-46
-------
through A-21 plot the same data by test fuel type.
A review of Figures A-l through A-21 and the regression statistics presented in Appendix A
reveals that it is certainly possible that both engine configuration and fuel type could be
significant influences on marine engine emission rates for one or more emission species.
Unfortunately, it is not possible given existing database structure and available time and resource
constraints to determine whether the apparent influences are attributable to simple variability
across engines or to specific engine or fuel characteristics. However, it is also apparent that the
scatter for most, if not all, of the separated engine type and fuel specific data is sufficiently wide
to support the general usage of the regression statistics presented in Table 3-5 until such time as
supplemental test data can be collected and supporting analysis performed. Nevertheless, EEA
certainly recommends that such evaluation be performed as soon as possible to validate the
general applicability of the presented regressions.
An initial investigation of the dependence of exhaust NOX on fuel nitrogen content was also
conducted. As shown in Figures 3-27 through 3-29, the scatter of estimated NOX emissions at
any given fuel nitrogen content is considerably wider than any trend in NOX with increasing fuel
nitrogen content. In fact, the only trend across fuel nitrogen content appears to be flat. Given
the overwhelming significance of intake air nitrogen on overall NOX formation, such a trend is
not surprising.
Lastly, all presented emission factors and emission factor analysis in this study apply solely to
marine internal combustion engines operating on diesel fuel (either distillate or residual).
Moreover, no distinction has been made between main propulsion engines and auxiliary engines.
This lack of distinction is based on two major factors, one technical and one logistical.
Technically, no significant differences are expected between the emission profiles of marine
engines used for propulsion versus auxiliary operations as the same engine makes and models are
The USCG database does not identify the two versus four stroke configuration of several of its component test
engines and does not distinguish the various test fuels employed during testing, except to indicate that all fuels
were "diesel." Therefore, all engine type statistics for "not indicated" engines and "diesel" fuel are based on
USCG data only. Conversely, all statistics for specific types of diesel fuel are based on Lloyd's data only.
3-47
-------
used to satisfy both applications. Logistically, the entire marine engine database used for this
study contains test data for only two auxiliary engines, prohibiting any detailed independent
assessment of auxiliary engines alone. Similarly, no emissions data for steam engines was
provided to EEA for review. For gas turbines, EPA provided a summary data sheet for only a
single oil tanker engine tested at two loads,11 while the USCG report4 cites summary test results
for two additional gas turbines, but provides no supporting data such as that included for all
diesel engines tested. Therefore, the ability to develop detailed emission factors for gas turbines
is also quite limited.
Table 3-6 and Figure 3-30 summarize the available gas turbine emissions data and present
several arithmetic averages of reported mass emission rate data. Regressions were not performed
over the full load range of these turbines as no emissions rate data was provided at loads below
about 50 percent of rated output. While both NOX and CO may exhibit trends (NOX increasing
with load, CO decreasing with load), there simply is no data available to indicate whether these
trends hold true over the lower load ranges and, if so, what the general shape of the emissions
curve might be. Therefore, at this time, the use of simple arithmetic averages over the entire
range of test data or at each individual test data load point (50, 75, and 100 percent of rated
output) represents the only viable emission factor estimation technique. The resulting emission
factors for either approach are presented in Table 3-6. With appropriate qualifications given the
gas turbine database size, gas turbine emissions would, in general, appear to be about half those
of diesel marine engines for NOX and similar to diesel marine engine emissions for HC, CO, and
PM.
3-48
-------
NO Emission Rate Data
1000
100
10
1
0.00%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
O
0
0.20%
0.40% 0.60% 0.80%
Fuel Nitrogen Content
1.00%
1.20%
FIGURE 3-27
-------
N(X Emission Rate Data
1000
100
10
1
0.00%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
0.20%
0.40% 0.60% 0.80%
Fuel Nitrogen Content
1.00%
1.20%
FIGURE 3-28
-------
NO2 Emission Rate Data
1000
100
10
1
0.00%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
4 Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
0.20% 0.40% 0.60% 0.80% 1.00%
Fuel Nitrogen Content
1.20%
FIGURE 3-29
-------
TABLE 3-6
MARINE GAS TURBINE EMISSION RATE DATA
Parameter
Test Load (mW)
Rated Load (mW)
Fractional Load
Chevron
"Louisiana"
6.30
8.05
0.78
4.60
8.05
0.57
USCG "Sherman"
Starboard
13.42
13.42
1.00
9.84
13.42
0.73
6.71
13.42
0.50
Port
13.42
13.42
1.00
9.84
13.42
0.73
6.71
13.42
0.50
Reported Emission Rate (pounds per hour)
PM
SO2
NOX
CO
HC
2.21
12.35
62.50
-1.17
4.31
12.64
33.60
0.31
10.50
177.00
2.98
2.67
3.87
80.40
27.40
16.00
4.10
50.60
39.50
3.41
8.54
205.00
31.60
0.50
2.89
87.10
26.90
7.23
3.68
53.60
43.50
1.47
Reported Emission Rate (g/kW-hr)
PM
SO2
NOX
CO
HC
0.16
0.89
4.50
-0.08
0.42
1.25
3.31
0.03
0.35
5.98
0.10
0.09
0.18
3.71
1.26
0.74
0.28
3.42
2.67
0.23
0.29
6.93
1.07
0.02
0.13
4.01
1.24
0.33
0.25
3.62
2.94
0.10
Overall
Average
50% Load
Average
75% Load
Average
Full Load
Average
0.29
0.45
4.44
1.15
0.25
0.42
0.59
3.45
1.88
0.16
0.16
0.40
4.07
0.81
0.54
0.32
6.45
0.58
0.05
to
-------
Gas Turbine Emission Rates
-1
0%
8
7 * PM • SO2 A NOx • CO x HC
Solid markers are Chevron data,
s- ^ open markers are USCG data.
Chevron does not report HC.
USCG does not report PM.
4 \ A
*-
& A A
3 : ; o
e o
o
I 2
E
^ 1
0
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE 3-30
-------
-------
4. MARINE VESSEL CLASSIFICATIONS AND POWER RATINGS
4.1 CLASSIFICATIONS EMPLOYED IN LITERATURE
Three of the reports provided by EPA had utilized specific classifications of marine vessels that
varied both in detail and grouping, and these groupings are reviewed below.
The 1991 report by Booz-Allen9 categorizes oceangoing vessels into four types:
• container ships;
• tankers and bulk carriers;
• general cargo/vehicle carriers/RORO/and ocean-going tugs; and
• passenger liners and cruise ships.
Each particular category is then divided into weight classes in 25,000 ton deadweight ton (DWT)
steps (0 to 25, 25 to 50, etc) and an average horsepower is associated with each weight class for
every ship type. However, the horsepower data is identical across all ship types, except for
tankers and bulk carriers. The report also identifies horsepower for tankers and bulk carriers as
being higher than the horsepower (see Table 4-1) for other types within each weight class. The
Booz-Allen data is potentially incorrect, since tankers and bulk carriers cruise relatively slowly
(their cargo is not perishable or high cost), and typically have the lowest horsepower for a given
deadweight.
The Acurex report10 for SCAQMD also has a categorization scheme by deadweight and ship
type. The analysis relied on data from Lloyds, from the ships visiting San Pedro Bay. Acurex
classified ships by type and 'design category' where:
Design Category = (DWT)0'667 * (Service Speed)3/!O4
4-1
-------
TABLE 4-1
BOOZ-ALLEN CLASSIFICATION OF VESSELS
Type
(1) Tankers & Bulk Carriers
(2) All Others*
DWT (xlOOO) Range
0-25
25-50
50-75
75-100
100+
0-25
25-50
50-75
75-100
100+
Horsepower
16862
35742
59342
80582
104182
8560
11920
16120
19900
24100
* Booz-Allen has three categories for vessels: (a) container ships, (b) general cargo/vehicle carriers/RORO/
ocean-going tugs, and (c) passenger and cruise ships. However, all use the same HP to DWT relationship.
4-2
-------
This equation is based on the well-known relationship between power to overcome drag, which
varies as the surface area in the water and the cube of speed. From the Lloyds registration data,
Acurex developed eight ship type categories namely:
• auto carriers;
• bulk carriers;
• container ships;
• general cargo ships;
• passenger ships;
• refrigerated cargo (reefer) ships;
• 'roll-on, roll-off,' or RORO; and
• tankers.
Each of the eight ship types is then further subdivided into design categories (up to eight) in step
of 200. These classifications are provided in Appendix C. However, it is not clear how many
ships were available in the sample for each combination of design category and ship type. An
examination of the data suggests significant sample variation since, in several instances,
horsepower declines with increasing design category range. The Acurex analysis showed that
the design category approach reduced the dispersion in horsepower within a ship type, but also
showed the dispersion reduction relative to using deadweight as an indicator was not large. In
addition, these are large variations in the percentage increase in horsepower for every 200 step in
design category range, indicating significant unexplained variation in horsepower.
o
The Arcadis (1999) report for the EPA utilizes the same ship types as the Acurex study cited
above, but also provided cruise speeds by ship type. Bulk carriers, tankers and general cargo
ships had cruise speeds in the range of 15 to 16 knots, while reefers, RORO and container ships
had speeds of 20 to 22 knots. Auto carriers had an average speed of 18.3 knots while passenger
liner had an average speed of 19.9 knots. These estimates appear reasonable except for
passenger liners, where the relatively low average speed may have been influenced by the
sample selected; many passenger liners have speeds of 30 knots or higher. In addition, the
Arcadis report stated that there was considerable dispersion of speeds within ship type, but a
4-3
-------
majority of ships were within ± 2 knots of the averages cited. This would suggest that bulk
carriers and tankers would have similar relationships between deadweight and horsepower, while
reefers, container ships and RORO may also have similar relationships.
Non-oceangoing vessels are typically more simply classified by type and horsepower. The
Booz-Allen report classifies these vessels into the following:
• fishing vessels;
• tugs;
• passenger ferries;
• dredging and construction ships;
• work/crew boats.
The Acurex report uses a virtually identical classification for non-oceangoing vessels as the
Booz-Allen classification, but further groups all vessels except for tugs and fishing vessels into a
single category called 'other' for emission estimation.
4.2 OPERATING MODE CLASSIFICATIONS IN LITERATURE
In general, ocean-going ships approach a port area at cruise speed, but reduce speed when they
are positioned within a few miles of the port (known as a precautionary area) to a speed of about
10 to 12 knots. Much closer to the docking area (about one mile), the ships slow to about five
knots and, assisted by tugboats, maneuver into the harbor and dock at the pier. Once at the pier,
only the auxiliary engines are used to provide electrical and accessory power, in a mode called
"hoteling." The literature reviewed uniformly cites these four modes, through not all four modes
are used in all reports reviewed.
The Booz-Allen report cites these four modes, called full, half, slow and moored. The power
ratings, as a function of rated maximum power are 80, 40, 10, and zero for the four modes
respectively with regard to main engines. It was also assumed that for all ocean-going vessels,
the auxiliary power engines were operated at 500 kW. For harbor and fishing vessels, three
modes are utilized: full at 80 percent power, cruise at 50 percent power and slow at 20 percent
4-4
-------
power. No hoteling emissions appear to be included from these classes of vessels.
The Acurex report assumed that at cruise, engines are operated at 80 percent of the maximum
continuous rating (MCR). Slow cruise was estimated as 12 knots, and the percent of power
required was calculated based on the cube of the ratio of 12 knots to actual cruise speed. Hence,
the percent of power used varies according to ship type, since for example, RORO and container
ship cruse much faster than bulk carriers and tankers. As a result, the percent of power used
varies from a little as 14 percent of MCR for container ships to 40 percent of MCR for bulk
carriers. For maneuvering, container ships were estimated to use only 10 percent of MCR, while
at the other extreme, bulk carriers were assumed to use 20 percent of MCR, based on
' engineering j udgement."
The Acurex report also attempted to estimate auxiliary power loads under all modes including
hoteling. A survey based method was used, but no good relationships were found between
auxiliary loads and ship size or weight. Acurex recommend the following auxiliary power loads
independent of ship type (except for passenger ships) or weight:
• slow/fast cruise - 750 kW
• maneuvering - 1250 kW
• hoteling - lOOOkW
For passenger ships only, auxiliary power loads of 5000 kW were estimated under all conditions.
Acurex did not develop mode specific emission rates for harbor and fishing vessels, but simply
used annual fuel consumption average per horsepower to estimate emissions for tugs. Harbor
vessel activity was characterized at three modes representing 80, 50, and 20 percent of MCR.
Fishing vessel activity was characterized at 80 and 25 percent of MCR and at idle. (Fishing
vessels do not have large "hoteling" loads).
4-5
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The newer Arcadis report does not vary significantly in its assessment of loads and operating
modes relative to the Acurex report. Table 4-2 shows the loads by vessel type and mode for
ocean going vessels, as provided in this report.
The Environment Canada report6 also cites four modes, but does not have specific values for
percent of power used by ship type on these modes.
4.3 ANALYSIS OF SHIP TYPE AND WEIGHT CATEGORIES
Under this work assignment, EPA provided a data base on ships operating at the West Coast that
contained information on ship type, weight, cruise speed and engine horsepower, obtained from
Lloyds. The database was similar in content to the one used by Arcadis in earlier analyses, and
has been provided to Arcadis for some current (ongoing) analyses.
While the date base contained about 5000 records, it included some data with incomplete records
for ship horsepower, type or weight. It also included data on non-oceangoing vessels such as
tugs, construction vessels and fishing vessels. Oceangoing vessels were classified in the scheme
cited in the Acurex report and included eight broad classifications by ship type as listed in
Section 4-1. The total sample of oceangoing ships with all necessary data was about 4100
vessels.
Ideally, rated horsepower would be more closely related to the maximum loaded weight of the
ship (i.e., empty weight + payload) but data on empty weight was not available for a large
fraction of the data records, and only deadweight (DWT) data is constantly available. EEA
attempted two sets of regressions that link horsepower to ship characteristics. The first is
between horsepower and DWT by ship type for each of the eight types. The second has
horsepower as the independent variable and uses (DWT)0'667 and (speed)3 as the independent
variables. In addition, a regression across all ship types was performed using both regression
specifications.
4-6
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TABLE 4-2
ENGINE LOADS BY SHIP TYPE FOR EACH OPERATING MODE
Ship Type
Auto Carrier
Bulk Carrier
Container
General Cargo
Passenger
Reefer
RORO
Tanker
Cruise
80
80
80
80
80
80
80
80
Slow Cruise
20
40
10
35
20
20
15
40
Maneuvering
15
20
10
20
15
15
10
20
Source: Reference 8.
4-7
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Table 4-3 shows the regressions for the eight types and across all ship types using (DWT) as the
independent variable. The regression has poor explanatory power when all ship types are
combined, but has reasonable explanatory power when each ship type is considered separately.
Most of the regressions by ship type have r2 values in excess of 0.55.
Table 4-4 shows the regressions for the same ship types when (DWT)0'667 and (speed)3 are the
independent variables. These regressions have better explanatory power than the regressions
using DWT alone, but the improvements are not very large, except for the case when all ship
types are considered as one group. This is consistent with the observation that cruise speeds
within a ship type do not vary much, but vary significantly across ship types.
Our contacts with a few ports established that its is easier to obtain information on a ship's
deadweight tonnage that to obtain cruise speed or horsepower (which would require purchase of
Lloyd's data). Hence, the use of the (DWT) based regressions may be preferable to determine
horsepower. In examining the regression and the related scatter plots (not included in this
report), it was obvious that certain ship type categories could be combined
The regression coefficient for bulk carriers and tankers are very similar, and Arcadis also reports
a very similar top speed, so that combining these categories is appropriate. In addition, Table
4-4 also shows that the DWT coefficient for auto carriers, RORO, container ship and reefers are
quite similar (between 15 and 20) and could be combined. Plots of horsepower against (DWT)
for these ship types show that RORO reefers and auto carriers are distributed in the 5000 to
20,000 ton DWT range while most of the container ships are the 20,000 to 70,000 ton DWT
range. Because of their relatively high horsepower to weight ratio in comparison to general
cargo ships and tankers, and because of the fact that the sample size for these ship types was
(individually) only about 100 to 160, they were combined with container ships. Regression
coefficients for the combined categories are shown in Table 4-5.
4-8
-------
TABLE 4-3
RESULTS OF REGRESSIONS BETWEEN HORSEPOWER
AND DEADWEIGHT TONNAGE
SHIP TYPE
ALL
(N=4103)
AUTO CARRIER
(N= 157)
BULK CARRIER
(N= 1644)
CONTAINER
(N=489)
GENERAL CARGO
(N=641)
PASSENGER
(N= 40)
REEFER
(N=160)
RORO
(N= 110)
TANKER
(N=861)
INTERCEPT
9070
(42.05 )
7602
(7.33)
6726
(54.54)
-749.4
(-0.61)
3046
(15.67)
-4877
(-1.24)
1364
(2.23)
4358
(6.70)
6579
(34.61)
DWT COEFF
0.1097
(26.01)
0.4172
(5.75)
0.0985
(26.01)
0.800
(26.29)
0.288
(28.43)
6.81
(9.97)
1.007
(14.93)
0.5364
(18.34)
0.1083
(41.16)
R-SQUARE
0.14
0.176
0.55
0.59
0.56
0.72
0.58
0.76
0.66
T-statistics in parentheses under coefficients.
4-9
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TABLE 4-4
REGRESSIONS OF HORSE POWER vs DEADWEIGHT AND CRUISE SPEED
SHIP TYPE
ALL
(N=4103)
AUTOCARRIER
(N=157)
BULK CARRIER
(N=1644)
CONTAINER
( N=489)
GENERAL
CARGO (N=839)
PASSENGER
( N= 40)
REEFER
(N=160)
RORO
(N=110)
TANKER
(N=861)
INTERCEPT
-4585
(23.18)
2956
(1.947)
1586
(6.514)
-13924
(-10.36)
-1307
(-7.73)
-25305
(-4.43)
-2357
(-3.68)
-3664
(-5.02)
156.6
(0.544)
DWT COEFF
6.711
(51.95)
14.41
(5.788)
5.901
(48.55)
20.06
(12.60)
8.819
(34.94)
118.45
(5.228)
17.00
(8.749)
16.18
(15.68)
6.271
(49.32)
SPEED COEFF
2.662
(92.66)
0.381
(3.38)
0.791
(13.11)
2.342
(16.63)
1.202
(34.84)
2,612
(3.498)
0.861
(10.98)
1.386
(9.040)
1.291
(16.40)
R-SQUARED
0.73
0.25
0.61
0.73
0.80
0.73
0.77
0.88
0.78
T-statistics in parentheses. Equation uses (DWT) and (SPEED) as independent variables.
4-10
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TABLE 4-5
RECCOMENDED SHIP TYPES AND REGRESSIONS
OF HORESEPOWER TO DEADWEIGHT
SHIP TYPE
BULK CARRIERS +T ANKERS
(N=2505)
PASSENGER
(N=40)
GENERAL CARGO
(N= 641)
CONTAINER/RORO
AUTO CARRIER/REEFER
(N= 917)
INTERCEPT
9070
(48.52)
-4877
(-1.24)
3046
(15.67)
2581
(5.50)
DWT COEFF.
0.101
(49.55)
6.81
(9.97)
0.288
(28.43)
0.719
(47.27)
R-SQUARE
0.67
0.72
0.56
0.71
T-statistics in parentheses under coefficients.
4-11
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Passenger ships posed a dilemma since there are only 40 ships in the database. The regression
show extremely high horsepower per DWT, and it implies that a 15,000 DWT ship would have
engines whose output is about 100,000 HP. In contrast, the Arcadis report estimates a similar
ship would have engines rated at 33,000 HP. It should be noted that the passenger ships in the
Arcadis report had relatively low top speeds of about 20 knots. If typical speeds are closer to 30
knots, the cubic relationship with speed would explain the differences in horsepower, since
(30/20)3 is 3.375, i.e., passenger ships capable of 30 knots cruise would require 3.375 times the
power of ships capable of 20 knot cruise. Nevertheless, the regressions should be treated with
caution because of the very small sample.
No independent data on the possible modes of operation and load factors was received. The
Arcadis report utilizing estimates of load factor derived from speeds appears more defensible
than using constant load factors across ship types for each mode. However, the load factor for
slow cruise (in the precautionary area) derived by Arcadis is based on an assumption that all
ships slow to 12 knots. It is entirely possible that larger ships such as bulk carriers and tankers
may operate slower as they cannot be maneuvered or stopped as easily as small ships, so that
using 12 knots for all ships may be incorrect. Due to the cubic relationship of power to speed,
slowing to ten knots would imply a load factor almost half that of slowing to 12 knots. The
cubic relationship also assumes that propeller and drivetrain efficiency remains constant over the
speed range which is likely incorrect. Due to the grouping of vessel types, and due to modest
changes to speed assumptions, EEA suggests load factors that are slightly different from the
Arcadis factors by mode, and these are listed in Table 4-6.
No alternatives to hoteling loads other than Arcadis survey based data are available. Hence, we
suggest these be utilized until more extensive survey based data becomes available.
4-12
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TABLE 4-6
SUGGESTED LOADS BY MODE
(as percent of maximum continuous rating)
Bulk Carrier & Tankers
General Cargo
Passenger*
Container/RORO/Reefer/Auto Carrier
Cruise
80
80
80
80
Slow Cruise
40
35
20
30
Maneuvering
20
20
10
15
Auxiliary Loads in kW
Passenger Ships
All Others
Fast/Slow Cruise Maneuvering
5000 5000
750 1250
Hoteling
5000
1000
* All values except main engine load categories marked are from Reference 8.
4-13
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Data on the horsepower and operating modes of all non-oceangoing hips is much more sparse.
Based on the data provided by EPA, EEA calculated the following average rated horsepower by
vessel type:
• Fishing Vessels - 1106
• Tug - 4268
• Ferries - 2415
• Yachts - 1863
• Harbor Operations - 5046
No data is available to compare these estimates, but these estimates are based on samples of
about 100 vessels in each class.
Operating mode data on non-oceangoing vessels is not easy to characterize. Typical estimates
have been based on power factors of 80 percent, 40 percent, 20 percent and idle, for cruise, slow
cruise, maneuvering, and trawling or waiting. No estimates of auxiliary loads for such vessels
are available.
The operating mode data on both oceangoing and non-oceangoing vessels appears to be derived
from numerous assumptions that have not been subjected to any validation by EEA. However,
this is the best available data within the time and resource constraints of this project.
4-14
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5. EMISSION FACTOR SUMMARY
The analysis presented in this report derives new emission factors for marine vessels, based on
data from the Lloyds Marine Exhaust Emissions Research Program, and the Coast Guard Test
Program. Unlike marine emission factors that were historically specified in units of fuel
consumption, the emission factors are specified in units of work (kW-hr) and are dependent on
engine load factor, which is the ratio of actual output to rated output based on the maximum
continuous rating.
The computation of emissions (and fuel consumption, if required) can be performed by ship type
for a given port and requires the following inputs:
• The number of calls to the port by vessel class and deadweight tonnage.
• The time spent, by ship type, in each of four operating modes defined as: normal cruise,
slow cruise, maneuvering and hoteling.
Alternatively, if ship horsepower is directly available for each ship, classification by deadweight
tonnage is not required. In addition, the user may define alternative modes of operation and
typical engine load factors by mode.
The basic equations used for the calculation are:
TIMEvcC, DWT, MODE = CALLSycC, DWT X LENGTHycC,DWT X %TIMEvcC, DWT, MODE/100
EMIS SIGNSVCC,DWT,MODE = (EF)(LFMODE) x (HP)(DWT) x LFMODE x TIMEycc, DWT, MODE
where:
VCC is the vessel class (tanker, RORO, etc.)
DWT is the deadweight tons
EF is the emissions factor
LF is the mode specific load factor
5-1
-------
For the calculation, the TIME equation requires port specific inputs, while this report provides
the EF and FTP relationships.
The emission factors and fuel consumption rates are derived from substantially more data than
earlier emission factors, and represent an improvement over the current fuel based emission
factors. However, the emission factors derived are subject to the following cautions:
• A significant portion of the database had measurements that yielded inconsistent values
of air-fuel ratio depending on the calculation methodology employed. These records
were excluded from the analysis, but the remaining database was still adequate for
analysis.
• Some of the data reported suspiciously low values of HC concentrations (below one ppb),
but these data were retained in the analysis. However, the number of records with low
HC values is small.
• There are concerns regarding the determination of output power at each test mode, for
about ten percent of the records.
• Most of the data analyzed is on engines rated at less than 8000 kW. Most of the data
points eliminated from analysis due to errors are from higher output engines, which are
mostly two-stroke engines. Hence, the applicability of the derived emission factors to all
engine sizes is not firmly established.
The emissions factor algorithms derived are of the form:
E (g/kW-hr) = a (Fractional Load)x + b
where E is the emissions rate per unit of work. The data analysis showed no statistically
significant differences in emissions rates by engine size or output range, or by
two-stroke/four-stoke, subject to the caveats detailed above. Emissions rates for 862 are based
on (fuel consumption x sulfur content of fuel) since all 862 emissions are fuel derived. Table 5-1
provides a summary of HC, CO, NOX, NC>2, PM, CC>2, and 862 emission factors and fuel
consumption as a function of load. The fuel consumption factor algorithm (derived from the
same database as the emission factors) is also in the same equation form as emission factor
algorithms. These emissions factor and fuel consumption rate algorithms are applicable to all
engine sizes since the emissions data showed no statistically significant difference across engine
sizes. In all cases (including fuel consumption), the algorithms provide the rates per unit of work,
i.e. per kW-hr. In order to obtain the absolute emission or fuel consumption level in grams, it is
5-2
-------
TABLE 5-1
MARINE ENGINE EMISSION FACTOR
AND FUEL CONSUMPTION ALGORITHMS
(in g/kW-hr, for all marine engines)
Pollutant
PM
NOX
NO2
S02
CO
HC
C02
Exponent (x)
1.5
1.5
1.5
n/a
1
1.5
1
Intercept (b)
0.2551
10.4496
15.5247
n/s
n/s
n/s
648.6
Coefficient (a)
0.0059
0.1255
0.18865
2.3735
0.8378
0.0667
44.1
1. All regressions but SO2 are in the form of:
Emissions Rate (g/kW-hr) = a (Fractional Load)"x + b
2. Fractional load is equal to actual engine output divided by rated engine output.
3. The SO2 regression is the form of:
Emissions Rate (g/kW-hr) = a (Fuel Sulfur Flow in g/kW-hr) + b
4 Fuel Consumption (g/kW-hr) = 14.12/(Fractional Load) + 205.717
5. n/a is not applicable, n/s is not statistically significant.
5-3
-------
necessary to multiply the rates per unit of work by the work in kilowatts and the time in hours, as
indicated by the equation listed on page 5-1 for emissions.
While the rederivation of emission factors and fuel consumption rate are central to this report,
the relationship of engine rated horsepower to ship type and deadweight tonnage was also
investigated. Oceangoing ships were classified into four types and their horsepower was related
to deadweight (DWT) using linear regressions. The results are:
(1) Bulk Carriers and Tankers: HP = 9070 + 0.101 (DWT)
(2) General Cargo Ships: HP = 3046 + 0.288 (DWT)
(3) Container/RORO/Auto Carriers/Refrigerated Ships: HP = 2581 + 0.719 (DWT)
(4) Passenger Ships: HP = -4877 + 6.81 (DWT)
The relationship for the passenger ship category is the most uncertain since the sample of ships
in this category was very small (40).
For all non-ocean going vessels, the empty weight or deadweight is generally not available in the
Lloyd's registration data, so that for these classes of vessels, only an average horsepower across
the class was computed. The values are based on a sample of about 100 vessels in each category
and the results are:
• fishing vessels - 1106 HP;
• tugs - 4268 HP;
• ferries - 2415 HP;
• yachts - 1863 HP;
• harbor operations - 5046 HP;
The values could be used as default values in the absence of actual HP data on the vessels
operating at a specific port.
5-4
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Operating modes were divided into four types:
• normal cruise;
• slow cruise;
• maneuvering;
• docking (hoteling).
No independent data analysis was performed on the load factors for the engines (main and
auxiliary) at these operating modes. Results from literature are summarized, and the best source
of load factor data is from a recent report by Arcadis. Nevertheless, this data relies on a number
of assumptions that may not be true, especially for a specific port. The auxiliary engine loads (in
absolute kilowatts) may be the most arbitrary as they are specified independent of ship size or
weight.
Computation of emissions from auxiliary engines require the use of the same emission factors
specified in Table 5-1, and are evaluated at a load factor equal to one (i.e., at full load). Hence,
the equation for emission from auxiliary engines is given by
Emissions = (EF)(LF=1) x Auxiliary Power (kW) x Timevcc,Dwr,HOTEL
Table 5-2 shows the suggested load factors for both ocean-going vessels and non-ocean-going
vessels. While these values could be reasonable default values, the use of port specific load
factors is preferable, if available.
5-5
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TABLE 5-2
SUGGESTED LOAD FACTORS
(as percent of maximum continuous rating)
Vessel Type
Bulk Carriers & Tankers
General Cargo
Passenger
Container/RORO/Reefer/Auto Carrier
All non-oceangoing
Cruise
80
80
80
80
80
Slow Cruise
40
35
20
30
40
Maneuvering
20
20
10
15
20
SUGGESTED AUXILIARY LOADS IN KW
(ocean-going vessels only)*
Passenger Ships
All others
Slow Cruise
5000
750
Maneuvering
5000
1250
Hoteling
5000
1000
* Non-oceangoing vessels do not have separate auxiliary loads of significance.
5-6
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6. REFERENCES
1. Marine Exhaust Emissions Research Programme: Steady State Operation, Lloyd's Register
of Shipping, London, United Kingdom, 1990.
2. Marine Exhaust Emissions Research Programme: Steady State Operation, Slow Speed
Addendum, Lloyd's Register of Shipping, London, United Kingdom, 1991.
3. Marine Exhaust Emissions Research Programme, Lloyd's Register of Shipping, London,
United Kingdom, 1995.
4. Shipboard Marine Engines Emission Testing for the United States Coast Guard, Delivery
Order Number 31, Final Report, prepared by Environmental Transportation Consultants for
the Volpe National Transportation Systems Center and the United States Coast Guard
Headquarters Naval Engineering Division, undated (emissions testing conducted in 1995).
5. BC Ferries Emissions Test Program, Report for the BC Ferry Corporation, ERMD
#98-26711, Environment Canada, Ottawa, Ontario, Canada, 1998
6. Port of Vancouver Marine Vessel Emissions Test Project, Final Report, ERMD #97-04,
Environment Canada, Ottawa, Ontario, Canada, 1997
7. Marine Emissions Quantification - BCFC Ferries operating in Greater Vancouver Regional
District Airshed, 97/EE/7002, Final Report, prepared by Lloyd's Register of Shipping for the
British Columbia Ferry Corporation, London, United Kingdom, 1997.
8. Analysis of Marine Emissions in the South Coast Air Basin, Draft Report, EPA Contract
Number 68-C6-0068, Work Assignment Number 0-02, prepared by Acurex Environmental
Corporation for the U.S. Environmental Protection Agency, 1999.
9. Inventory of Air Pollutant Emissions from Marine Vessels, Final Report, prepared by
Booz-Allen & Hamilton for the California Air Resources Board, Revised March 1991
10. Marine Vessel Emission Inventory and Control Strategies, Final Report, prepared by Acurex
Environmental Corp., for the South Coast Air Quality Management District, 1996
11. Facsimile transmittal on gas turbine emission rates from the Chevron "Louisiana," Brian
Shafritz of the Santa Barbara County (California) Air Pollution Control District to Gregg
Jansen [sic] of the U.S. Environmental Protection Agency, June 1, 1999.
6-1
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-------
APPENDIX A
EMISSION FACTOR REGRESSION SUMMARIES
-------
KEY TO APPENDIX TERMS:
1. All regressions are of the form:
Emission rate (g/kW-hr) = (Coefficient x Independent Variable) + Intercept
where: Coefficient = Value in column labeled "Coeff,"
Intercept = Value in column labeled "Intercept," and
Independent Variable = Parameter indicated in column labeled "Param" as follows:
"FL" = Fractional Load,
"l/(FLAe)" = Fractional Load to the negative "e" power, and
"Fuel S" = Fuel sulfur flow in g/kW-hr.
2. Where applicable, the exponent "e" is indicated in the upper center of each regression
summary.
3. Entries in the column labeled "A/F Criteria" have the following meanings:
"All Data" indicates that no data was excluded from the regression
analysis due to inconsistencies in estimated A/F ratio.
"Yes Data" indicates that only data meeting the consistent A/F ratio
criteria described in Section 3 is included in the regression analysis.
4. Entries in the column labeled "Loads Covered" have the following meanings:
"FL ge 0" means all data with an indicated fractional load greater than
or equal to zero.
"FL ge 20" means all data with an indicated fractional load greater than
or equal to 20 percent.
"FL It 20" means all data with an indicated fractional load of less than
20 percent.
A-2
-------
KEY TO APPENDIX TERMS
(Continued)
5. Entries in the column labeled "Cycles Covered" have the following meanings:
"All" means all reported engine types are included in the regression
analysis.
"2 Stroke" means only data for reported two stroke engines are included
in the regression analysis.
"4 Stroke" means only data for reported four stroke engines are
included in the regression analysis.
"Not Ind." (not indicated) means only data for USCG engines not
reported as either two or four stroke are included in the regression
analysis.
6. Entries in the column labeled "Fuels Covered" have the following meanings:
"All" means all reported fuel types are included in the regression
analysis.
"Diesel" means only USCG fuel types (all identified simply as "diesel")
are included in the regression analysis.
"Gas Oil" means only data for reported gas oil fuel are included in the
regression analysis.
"Gas Oil" means only data for reported gas oil fuel are included in the
regression analysis.
"Hvy FO" means only data for reported heavy fuel oil fuel are included
in the regression analysis.
"Int FO" means only data for reported intermediate fuel oil fuel are
included in the regression analysis.
"Light FO" means only data for reported light fuel oil fuel are included
in the regression analysis.
A-3
-------
KEY TO APPENDIX TERMS
(Continued)
7. Entries in the columns labeled "Int-T" and Coeff-T" indicate the regression t statistics for
the intercept and coefficient respectively.
8. Entries in the column labeled "r2" indicate the regression correlation coefficient.
9. Entries in the column labeled "F" indicate the regression model variance F statistic.
10. Entries in the three columns labeled "Sig?" indicate, from left to right, whether ("Yes") or
not ("No") the indicated intercept t statistic, coefficient t statistic, and variance F statistic are
significant at the 99 percent confidence level.
11. Entries in the column labeled "Obs" indicate the number of observations used in the
regression analysis.
A-4
-------
REGRESSION SUMMARY FOR:
PM
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
2.4352
0.8332
0.3344
4.5556
1.8897
0.9289
0.2551
0.3344
2.4562
0.1797
0.9533
0.0000
0.4088
0.2558
0.0000
0.1828
0.9289
0.0000
0.0000
0.0000
0.0000
0.2551
0.0000
0.0000
0.0000
0.0000
0.9533
0.0000
0.0000
0.0000
0.0000
0.4088
0.0000
0.0000
0.2558
0.0000
0.0000
0.0000
0.0000
0.1828
0.0000
0.0000
2.981
1.430
2.696
2.245
1.272
4.369
7.780
2.696
6.000
3.921
3.927
0.000
4.140
6.235
0.000
2.955
4.369
0.000
0.000
0.000
0.000
7.780
0.000
0.000
0.000
0.000
3.927
0.000
0.000
0.000
0.000
4.140
0.000
0.000
6.235
0.000
0.000
0.000
0.000
2.955
0.000
0.000
Yes
No
No
No
No
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
-3.6383
0.0066
-0.0482
-25.4900
0.0035
-1.1052
0.0059
-0.0482
-15.5027
0.0061
-1.1154
0.0000
-0.2656
0.0059
0.0000
0.0274
-1.1052
0.0000
0.0000
0.0000
0.0000
0.0059
0.0000
0.0000
0.0000
0.0000
-1.1154
0.0000
0.0000
0.0000
0.0000
-0.2656
0.0000
0.0000
0.0059
0.0000
0.0000
0.0000
0.0000
0.0274
0.0000
0.0000
-1.892
1.593
-0.221
-1.300
0.486
-2.346
23.143
-0.221
-4.426
27.472
-1.967
0.000
-1.443
20.590
0.000
1.602
-2.346
0.000
0.000
0.000
0.000
23.143
0.000
0.000
0.000
0.000
-1.967
0.000
0.000
0.000
0.000
-1.443
0.000
0.000
20.590
0.000
0.000
0.000
0.000
1.602
0.000
0.000
No
No
No
No
No
No
Yes
No
No
Yes
No
No
Yes
No
No
Yes
No
No
Yes
No
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/CFL'V)
FL
FL
l/CFL'V)
FL
FL
FL
l/CFI/X)
l/CFL'V)
1/(FIAO
FL
FL
FL
FL
FL
l/CFL^e)
l/(FLAe)
1/(FIA:)
1/(FIA:)
l/CFL'V)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIA:)
1/(FIAO
l/CFL'V)
1/(FIAO
1/CFIA:)
1/(FIA:)
1/(FIAO
1/(FIAO
0.10
0.07
0.00
0.11
0.02
0.16
0.95
0.00
0.66
0.99
0.14
0.00
0.34
0.95
0.00
0.39
0.16
0.00
0.00
0.00
0.00
0.95
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
0.34
0.00
0.00
0.95
0.00
0.00
0.00
0.00
0.39
0.00
0.00
3.58
2.54
0.05
1.69
0.24
5.50
535.58
0.05
19.59
754.73
3.87
0.00
2.08
423.95
0.00
2.57
5.50
0.00
0.00
0.00
0.00
535.58
0.00
0.00
0.00
0.00
3.87
0.00
0.00
0.00
0.00
2.08
0.00
0.00
423.95
0.00
0.00
0.00
0.00
2.57
0.00
0.00
No
No
No
No
No
No
Yes
No
Yes
Yes
No
No
Yes
No
No
Yes
No
No
Yes
No
35
35
19
16
16
31
31
19
12
12
25
0
6
25
0
6
31
0
0
0
0
31
0
0
0
0
25
0
0
0
0
6
0
0
25
0
0
0
0
6
0
0
2.435
0.929
0.784
2.456
0.726
0.953
0.409
0.785
0.929
0.784
0.953
0.409
0.785
2.435
0.929
0.442
2.456
0.373
0.953
0.409
0.443
0.929
0.442
0.953
0.409
0.443
2.435
0.929
0.279
2.456
0.204
0.953
0.409
0.279
0.929
0.279
0.953
0.409
0.279
2.435
0.929
0.263
2.456
0.188
0.953
0.409
0.264
0.929
0.263
0.953
0.409
0.264
2.435
0.929
0.261
2.456
0.186
0.953
0.409
0.262
0.929
0.261
0.953
0.409
0.262
-------
REGRESSION SUMMARY FOR:
NO
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
20.0268
10.4583
10.7756
36.0476
14.1805
16.9497
9.5181
10.3842
33.9582
11.4486
18.6862
9.5052
17.7374
10.8992
11.5228
8.7618
13.8772
20.6879
10.7749
14.3115
14.9135
8.9596
8.5884
12.5316
16.4739
8.8753
18.6862
5.7116
9.3553
10.7749
14.3115
10.3081
21.2210
14.9135
10.8992
6.2249
6.3121
12.5316
16.4739
8.4415
8.7582
8.8753
19.658
18.481
22.772
11.209
7.215
17.580
24.154
21.257
8.753
7.186
11.938
6.425
14.654
17.308
15.199
24.437
11.302
9.899
4.684
3.934
14.592
13.947
13.755
11.263
8.921
23.720
11.938
39.867
3.353
4.684
3.934
4.813
9.822
14.592
17.308
74.161
6.932
11.263
8.921
3.834
13.922
23.720
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
-14.9792
0.1110
-1.7939
-158.9668
0.0939
-10.8279
0.1143
-1.6405
-144.4380
0.1070
-14.8995
3.3223
-12.2715
0.0461
-0.0331
0.1701
-7.2368
-18.7851
2.3879
0.8539
-7.4032
0.0466
0.1679
-0.0974
-0.2364
0.1754
-14.8995
0.8915
-3.7954
2.3879
0.8539
-2.9725
-19.4814
-7.4032
0.0461
-0.0058
0.0575
-0.0974
-0.2364
-0.0495
0.1695
0.1754
-7.862
14.647
-2.449
-5.124
6.270
-6.407
19.391
-2.207
-4.358
8.884
-4.426
1.239
-5.936
10.252
-1.394
27.588
-3.571
-4.675
0.616
0.128
-4.384
7.634
20.753
-0.611
-1.546
13.124
-4.426
3.117
-0.572
0.616
0.128
-1.180
-4.720
-4.384
10.252
-4.130
3.339
-0.611
-1.546
-0.096
20.995
13.124
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
No
Yes
No
No
No
No
No
Yes
Yes
No
No
Yes
No
No
No
No
No
No
No
No
Yes
No
No
No
No
No
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
lAEL^e)
l/CFL'V)
1/(FIAO
FL
FL
FL
FL
FL
1/(FIA:)
l/(FLAe)
l/CFIA:)
l/(FLAe)
l/(FL"e)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIAO
l/CFIA:)
l/CFL^e)
1/(FIAO
l/(FLAe)
1/(FIA:)
1/(FIAO
1/(FIA:)
0.15
0.38
0.02
0.19
0.26
0.12
0.57
0.02
0.21
0.52
0.45
0.03
0.14
0.81
0.04
0.78
0.21
0.16
0.02
0.00
0.17
0.55
0.79
0.02
0.23
0.65
0.45
0.58
0.14
0.02
0.00
0.10
0.17
0.17
0.81
0.71
0.85
0.02
0.23
0.00
0.80
0.65
61.81
214.54
6.00
26.25
39.31
41.06
376.02
4.87
18.99
78.93
19.59
1.54
35.23
105.10
1.94
761.12
12.76
21.86
0.38
0.02
19.22
58.29
430.69
0.37
2.39
172.25
19.59
9.72
0.33
0.38
0.02
1.39
22.28
19.22
105.10
17.06
11.15
0.37
2.39
0.01
440.78
172.25
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
Yes
No
No
No
No
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
20.027
20.386
10.776
36.048
22.577
16.950
19.746
10.384
33.958
21.015
18.686
9.505
17.737
15.022
11.523
23.980
13.877
20.688
10.775
14.311
14.913
13.129
23.604
12.532
16.474
24.562
18.686
5.712
10.775
14.311
10.308
21.221
14.913
15.022
6.225
12.532
16.474
8.441
23.917
24.562
20.027
13.968
10.776
36.048
17.149
16.950
13.134
10.384
33.958
14.831
18.686
9.505
17.737
12.357
11.523
14.142
13.877
20.688
10.775
14.311
14.913
10.434
13.897
12.532
16.474
14.421
18.686
5.712
10.775
14.311
10.308
21.221
14.913
12.357
6.225
12.532
16.474
8.441
14.118
14.421
20.027
10.897
10.776
36.048
14.552
16.950
9.970
10.384
33.958
11.871
18.686
9.505
17.737
11.081
11.523
9.434
13.877
20.688
10.775
14.311
14.913
9.144
9.252
12.532
16.474
9.569
18.686
5.712
10.775
14.311
10.308
21.221
14.913
11.081
6.225
12.532
16.474
8.441
9.428
9.569
20.027
10.613
10.776
36.048
14.312
16.950
9.678
10.384
33.958
11.598
18.686
9.505
17.737
10.964
11.523
9.000
13.877
20.688
10.775
14.311
14.913
9.025
8.823
12.532
16.474
9.120
18.686
5.712
10.775
14.311
10.308
21.221
14.913
10.964
6.225
12.532
16.474
8.441
8.995
9.120
20.027
10.569
10.776
36.048
14.274
16.950
9.632
10.384
33.958
11.556
18.686
9.505
17.737
10.945
11.523
8.932
13.877
20.688
10.775
14.311
14.913
9.006
8.756
12.532
16.474
9.051
18.686
5.712
10.775
14.311
10.308
21.221
14.913
10.945
6.225
12.532
16.474
8.441
8.928
9.051
-------
REGRESSION SUMMARY FOR:
NOx
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
21.9867
11.4817
11.8301
39.5753
15.5683
18.6084
10.4496
11.4004
37.2814
12.5690
20.5149
10.4352
19.4732
11.9658
12.6504
9.6193
15.2353
22.7124
11.8293
15.7119
16.3730
9.8363
9.4289
13.7580
18.0862
9.7439
20.5149
6.2705
10.2705
11.8293
15.7119
11.3168
23.2977
16.3730
11.9658
6.8337
6.9302
13.7580
18.0862
9.2673
9.6153
9.7439
19.658
18.481
22.772
11.209
7.215
17.580
24.154
21.257
8.753
7.186
11.938
6.425
14.654
17.308
15.198
24.437
11.302
9.899
4.684
3.934
14.592
13.947
13.755
11.263
8.921
23.720
11.938
39.887
3.354
4.684
3.934
4.813
9.822
14.592
17.308
74.147
6.932
11.263
8.921
3.834
13.922
23.720
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
-16.4451
0.1219
-1.9694
-174.5233
0.1031
-11.8876
0.1255
-1.8011
-158.5718
0.1174
-16.3577
3.6475
-13.4724
0.0506
-0.0363
0.1868
-7.9452
-20.6235
2.6216
0.9377
-8.1277
0.0512
0.1843
-0.1069
-0.2595
0.1925
-16.3577
0.9784
-4.1654
2.6216
0.9377
-3.2635
-21.3880
-8.1277
0.0506
-0.0064
0.0631
-0.1069
-0.2595
-0.0543
0.1861
0.1925
-7.862
14.647
-2.449
-5.124
6.270
-6.407
19.391
-2.207
-4.358
8.884
-4.426
1.239
-5.936
10.252
-1.394
27.588
-3.572
-4.675
0.616
0.128
-4.384
7.634
20.753
-0.611
-1.546
13.124
-4.426
3.118
-0.572
0.616
0.128
-1.180
-4.720
-4.384
10.252
-4.127
3.339
-0.611
-1.546
-0.096
20.995
13.124
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
No
Yes
No
No
No
No
No
Yes
Yes
No
No
Yes
No
No
No
No
No
No
No
No
Yes
No
No
No
No
No
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
lAEL^e)
l/CFL'V)
1/(FIAO
FL
FL
FL
FL
FL
l/CFL^e)
l/(FLAe)
l/CFIA:)
l/(FLAe)
l/(FL"e)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIAO
l/CFIA:)
l/CFL^e)
1/(FIAO
l/(FLAe)
1/(FIA:)
1/(FIAO
1/(FIA:)
0.15
0.38
0.02
0.19
0.26
0.12
0.57
0.02
0.21
0.52
0.45
0.03
0.14
0.81
0.04
0.78
0.21
0.16
0.02
0.00
0.17
0.55
0.79
0.02
0.23
0.65
0.45
0.58
0.14
0.02
0.00
0.10
0.17
0.17
0.81
0.71
0.85
0.02
0.23
0.00
0.80
0.65
61.81
214.54
6.00
26.25
39.31
41.06
376.02
4.87
18.99
78.93
19.59
1.54
35.23
105.10
1.94
761.12
12.76
21.86
0.38
0.02
19.22
58.28
430.69
0.37
2.39
172.24
19.59
9.72
0.33
0.38
0.02
1.39
22.28
19.22
105.10
17.03
11.15
0.37
2.39
0.01
440.78
172.24
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
Yes
No
No
No
No
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
21.987
22.381
11.830
39.575
24.787
18.608
21.678
11.400
37.281
23.071
20.515
10.435
19.473
16.492
12.650
26.327
15.235
22.712
11.829
15.712
16.373
14.413
25.913
13.758
18.086
26.966
20.515
6.270
11.829
15.712
11.317
23.298
16.373
16.492
6.834
13.758
18.086
9.267
26.257
26.966
21.987
15.335
11.830
39.575
18.828
18.608
14.419
11.400
37.281
16.282
20.515
10.435
19.473
13.566
12.650
15.526
15.235
22.712
11.829
15.712
16.373
11.454
15.257
13.758
18.086
15.833
20.515
6.270
11.829
15.712
11.317
23.298
16.373
13.566
6.834
13.758
18.086
9.267
15.499
15.833
21.987
11.963
11.830
39.575
15.976
18.608
10.946
11.400
37.281
13.033
20.515
10.435
19.473
12.166
12.650
10.358
15.235
22.712
11.829
15.712
16.373
10.039
10.157
13.758
18.086
10.505
20.515
6.270
11.829
15.712
11.317
23.298
16.373
12.166
6.834
13.758
18.086
9.267
10.351
10.505
21.987
11.652
11.830
39.575
15.712
18.608
10.625
11.400
37.281
12.733
20.515
10.435
19.473
12.037
12.650
9.880
15.235
22.712
11.829
15.712
16.373
9.908
9.686
13.758
18.086
10.013
20.515
6.270
11.829
15.712
11.317
23.298
16.373
12.037
6.834
13.758
18.086
9.267
9.875
10.013
21.987
11.604
11.830
39.575
15.671
18.608
10.575
11.400
37.281
12.686
20.515
10.435
19.473
12.016
12.650
9.806
15.235
22.712
11.829
15.712
16.373
9.887
9.613
13.758
18.086
9.936
20.515
6.270
11.829
15.712
11.317
23.298
16.373
12.016
6.834
13.758
18.086
9.267
9.801
9.936
-------
REGRESSION SUMMARY FOR:
NO2 Equivalent NOx
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
32.6651
17.0581
17.5759
58.7960
23.1294
27.6461
15.5247
16.9374
55.3881
18.6734
30.4786
15.5034
28.9309
17.7773
18.7945
14.2911
22.6347
33.7434
17.5747
23.3426
24.3249
14.6136
14.0083
20.4401
26.8702
14.4763
30.4786
9.3158
15.2591
17.5747
23.3426
16.8134
34.6129
24.3249
17.7773
10.1530
10.2959
20.4401
26.8702
13.7683
14.2852
14.4763
19.659
18.481
22.772
11.209
7.215
17.580
24.154
21.257
8.753
7.186
11.938
6.425
14.654
17.308
15.199
24.437
11.302
9.899
4.684
3.934
14.592
13.947
13.755
11.263
8.922
23.720
11.938
39.863
3.353
4.684
3.934
4.813
9.822
14.592
17.308
74.148
6.932
11.263
8.922
3.834
13.922
23.720
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
-24.4322
0.1810
-2.9262
-259.2844
0.1531
-17.6612
0.1865
-2.6760
-235.5868
0.1744
-24.3023
5.4192
-20.0158
0.0752
-0.0539
0.2775
-11.8040
-30.6400
3.8949
1.3935
-12.0752
0.0760
0.2738
-0.1589
-0.3856
0.2861
-24.3023
1.4542
-6.1893
3.8949
1.3935
-4.8488
-31.7759
-12.0752
0.0752
-0.0094
0.0937
-0.1589
-0.3856
-0.0807
0.2764
0.2861
-7.862
14.647
-2.449
-5.124
6.270
-6.408
19.391
-2.207
-4.358
8.884
-4.426
1.239
-5.936
10.252
-1.394
27.588
-3.572
-4.675
0.616
0.128
-4.384
7.634
20.753
-0.611
-1.546
13.124
-4.426
3.117
-0.572
0.616
0.128
-1.180
-4.720
-4.384
10.252
-4.129
3.339
-0.611
-1.546
-0.096
20.995
13.124
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
No
Yes
No
No
No
No
No
Yes
Yes
No
No
Yes
No
No
No
No
No
No
No
No
Yes
No
No
No
No
No
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
lAEL^e)
l/CFL'V)
l/(FL''-e)
FL
FL
FL
FL
FL
l/(FLAe)
1/(FIA:)
l/(FL^e)
l/(FLAe)
l/(FL"e)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIAO
1/(FIA:)
l/CFL^e)
l/(FLAe)
l/(FLAe)
l/(FLAe)
l/(FL''-e)
1/(FIA:)
0.15
0.38
0.02
0.19
0.26
0.12
0.57
0.02
0.21
0.52
0.45
0.03
0.14
0.81
0.04
0.78
0.21
0.16
0.02
0.00
0.17
0.55
0.79
0.02
0.23
0.65
0.45
0.58
0.14
0.02
0.00
0.10
0.17
0.17
0.81
0.71
0.85
0.02
0.23
0.00
0.80
0.65
61.81
214.54
6.00
26.25
39.31
41.06
376.02
4.87
18.99
78.93
19.59
1.54
35.23
105.10
1.94
761.12
12.76
21.86
0.38
0.02
19.22
58.28
430.69
0.37
2.39
172.24
19.59
9.72
0.33
0.38
0.02
1.39
22.28
19.22
105.10
17.05
11.15
0.37
2.39
0.01
440.78
172.24
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
Yes
No
No
No
No
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
32.665
33.250
17.576
58.796
36.825
27.646
32.207
16.937
55.388
34.277
30.479
15.503
28.931
24.502
18.794
39.113
22.635
33.743
17.575
23.343
24.325
21.414
38.499
20.440
26.870
40.062
30.479
9.316
17.575
23.343
16.813
34.613
24.325
24.502
10.153
20.440
26.870
13.768
39.010
40.062
32.665
22.783
17.576
58.796
27.972
27.646
21.423
16.937
55.388
24.190
30.479
15.503
28.931
20.155
18.794
23.067
22.635
33.743
17.575
23.343
24.325
17.018
22.667
20.440
26.870
23.522
30.479
9.316
17.575
23.343
16.813
34.613
24.325
20.155
10.153
20.440
26.870
13.768
23.027
23.522
32.665
17.774
17.576
58.796
23.735
27.646
16.262
16.937
55.388
19.363
30.479
15.503
28.931
18.074
18.794
15.388
22.635
33.743
17.575
23.343
24.325
14.914
15.091
20.440
26.870
15.607
30.479
9.316
17.575
23.343
16.813
34.613
24.325
18.074
10.153
20.440
26.870
13.768
15.378
15.607
32.665
17.311
17.576
58.796
23.343
27.646
15.785
16.937
55.388
18.917
30.479
15.503
28.931
17.882
18.794
14.679
22.635
33.743
17.575
23.343
24.325
14.720
14.391
20.440
26.870
14.876
30.479
9.316
17.575
23.343
16.813
34.613
24.325
17.882
10.153
20.440
26.870
13.768
14.672
14.876
32.665
17.239
17.576
58.796
23.283
27.646
15.711
16.937
55.388
18.848
30.479
15.503
28.931
17.852
18.794
14.569
22.635
33.743
17.575
23.343
24.325
14.690
14.282
20.440
26.870
14.762
30.479
9.316
17.575
23.343
16.813
34.613
24.325
17.852
10.153
20.440
26.870
13.768
14.562
14.762
-------
REGRESSION SUMMARY FOR:
CO
Exponent= 1
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
17.9327
-0.7044
2.8330
47.6066
-0.8009
9.9821
0.1548
2.7465
30.8036
-0.5190
7.1043
10.0714
10.4487
1.2052
-0.0311
-0.8389
4.9827
12.3421
2.2926
-0.0250
12.9905
1.1761
-1.5152
3.1895
1.1732
-0.6867
7.1043
1.6026
56.3283
2.2926
-0.0250
3.6282
10.3567
12.9905
1.2052
0.7511
-2.3730
3.1895
1.1732
1.7660
-1.7160
-0.6867
11.404
-0.757
12.807
9.888
-0.203
9.983
0.323
12.135
7.784
-0.218
4.138
2.787
9.169
2.717
-0.016
-1.956
5.218
5.885
1.739
-0.338
8.795
3.294
-1.755
3.905
9.474
-1.058
4.138
3.847
2.555
1.739
-0.338
5.165
5.510
8.795
2.717
4.762
-1.597
3.905
9.474
1.824
-2.700
-1.058
Yes
No
Yes
Yes
No
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
No
No
Yes
Yes
No
No
Yes
Yes
No
Yes
Yes
No
Yes
Yes
No
No
No
Yes
Yes
Yes
No
Yes
No
Yes
Yes
No
No
No
-23.1061
1.2802
-1.4384
-299.4701
1.2891
-11.4844
0.8378
-1.3058
-179.5074
0.8653
-7.1069
-12.2131
-12.0126
0.3414
1.0290
1.1081
-3.4791
-16.0776
0.7222
1.6230
-15.6928
0.3111
1.1578
-0.2032
-0.1249
1.3344
-7.1069
-0.8657
-89.1275
0.7222
1.6230
-1.5295
-13.1566
-15.6928
0.3414
0.0725
3.6561
-0.2032
-0.1249
0.3854
1.0740
1.3344
-7.856
16.633
-4.200
-6.447
6.867
-6.553
17.700
-3.791
-5.309
7.175
-1.925
-1.865
-6.172
14.485
3.637
23.705
-2.208
-3.988
0.325
11.935
-6.429
12.743
15.205
-0.755
-4.351
13.786
-1.925
-1.041
-1.701
0.325
11.935
-1.851
-3.664
-6.429
14.485
5.278
28.520
-0.755
-4.351
0.954
19.151
13.786
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
Yes
No
Yes
Yes
No
No
Yes
No
No
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
1/(FIAO
l/CFL'V)
1/(FIAO
FL
FL
FL
FL
FL
l/CFL^e)
1/(FIAO
1/CFIA:)
1/(FIA:)
l/(FL"e)
FL
FL
FL
FL
FL
FL
FL
FL
1/CFIA:)
1/(FIA:)
l/CFL'V)
1/(FIAO
1/CFIA:)
1/(FIA:)
1/(FIAO
1/(FIAO
0.15
0.44
0.07
0.27
0.29
0.13
0.52
0.06
0.28
0.42
0.13
0.07
0.15
0.90
0.24
0.72
0.09
0.12
0.01
0.95
0.31
0.78
0.67
0.03
0.70
0.67
0.13
0.13
0.59
0.01
0.95
0.22
0.11
0.31
0.90
0.80
1.00
0.03
0.70
0.07
0.77
0.67
61.72
276.67
17.64
41.57
47.15
42.94
313.29
14.38
28.19
51.48
3.71
3.48
38.09
209.81
13.23
561.94
4.88
15.90
0.11
142.44
41.34
162.38
231.19
0.57
18.93
190.05
3.71
1.08
2.89
0.11
142.44
3.43
13.42
41.34
209.81
27.86
813.41
0.57
18.93
0.91
366.75
190.05
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
Yes
No
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
No
No
No
No
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
No
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
17.933
25.603
2.833
47.607
25.782
9.982
16.756
2.746
30.804
17.306
7.104
10.071
10.449
6.828
20.580
22.161
4.983
12.342
0.081
12.991
7.398
23.156
3.189
1.173
26.687
7.104
1.603
0.081
3.628
10.357
12.991
6.828
2.201
73.122
3.189
1.173
21.480
26.687
17.933
12.802
2.833
47.607
12.891
9.982
8.378
2.746
30.804
8.653
7.104
10.071
10.449
3.414
10.290
11.081
4.983
12.342
0.162
12.991
4.287
11.578
3.189
1.173
13.344
7.104
1.603
0.162
3.628
10.357
12.991
3.414
1.476
36.561
3.189
1.173
10.740
13.344
17.933
3.200
2.833
47.607
3.223
9.982
2.094
2.746
30.804
2.163
7.104
10.071
10.449
0.853
2.572
2.770
4.983
12.342
0.649
12.991
1.954
2.894
3.189
1.173
3.336
7.104
1.603
0.649
3.628
10.357
12.991
0.853
0.932
9.140
3.189
1.173
2.685
3.336
17.933
1.600
2.833
47.607
1.611
9.982
1.047
2.746
30.804
1.082
7.104
10.071
10.449
0.427
1.286
1.385
4.983
12.342
1.298
12.991
1.565
1.447
3.189
1.173
1.668
7.104
1.603
1.298
3.628
10.357
12.991
0.427
0.842
4.570
3.189
1.173
1.343
1.668
17.933
1.280
2.833
47.607
1.289
9.982
0.838
2.746
30.804
0.865
7.104
10.071
10.449
0.341
1.029
1.108
4.983
12.342
1.623
12.991
1.487
1.158
3.189
1.173
1.334
7.104
1.603
1.623
3.628
10.357
12.991
0.341
0.824
3.656
3.189
1.173
1.074
1.334
-------
REGRESSION SUMMARY FOR:
CO2
Exponent= 1
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
1361.0
653.1
807.0
2361.5
731.2
1186.3
648.6
819.5
2207.6
639.4
1228.3
1045.2
1202.2
742.8
667.1
606.0
1060.2
1355.3
939.8
680.3
1142.9
721.3
574.8
670.6
820.3
634.8
1228.3
733.4
2407.9
939.8
680.3
982.6
1308.4
1142.9
742.8
710.3
395.8
670.6
820.3
586.2
573.7
634.8
24.928
20.189
64.326
14.126
5.373
26.161
33.957
66.563
12.978
6.831
11.111
8.284
22.388
36.310
9.719
32.861
16.674
13.847
23.391
3.872
22.495
28.580
15.544
31.198
7.151
46.184
11.111
73.288
2.562
23.391
3.872
22.744
13.646
22.495
36.310
143.907
3.159
31.198
7.151
7.950
16.696
46.184
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
-911.9
46.5
-120.6
-10017.0
43.8
-647.5
44.1
-132.5
8823.5
44.5
-684.5
-479.9
-662.2
24.5
35.8
55.8
-389.8
-986.7
-302.1
72.7
-556.0
22.5
59.5
41.8
-31.8
53.0
-684.5
-28.2
2852.9
-302.1
72.7
-273.4
-915.1
-556.0
24.5
1.7
133.6
41.8
-31.8
98.9
57.1
53.0
-8.931
17.363
-6.210
-6.211
6.749
-8.148
23.374
-7.072
-6.072
9.365
-2.879
-2.099
-7.220
22.528
3.571
27.754
-3.715
-5.244
-4.464
0.225
-6.622
13.065
18.240
5.900
-1.197
25.879
-2.879
-1.413
-1.277
-4.464
0.225
-5.378
-4.995
-6.622
22.528
3.983
12.357
5.900
-1.197
3.215
18.836
25.879
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
l/CFL7^)
l/(FL"e)
1/(FIAO
FL
FL
FL
FL
FL
l/(FLAe)
1/(FIAO
1/(FIAO
1/(FIA:)
l/(FL"e)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIAO
1/(FIA:)
l/(FL"e)
1/(FIAO
1/CFIA:)
l/(FL"e)
1/(FIAO
1/(FIAO
0.18
0.46
0.14
0.25
0.29
0.19
0.65
0.19
0.34
0.55
0.26
0.09
0.19
0.95
0.23
0.78
0.23
0.20
0.50
0.01
0.32
0.78
0.75
0.64
0.15
0.88
0.26
0.22
0.45
0.50
0.01
0.71
0.19
0.32
0.95
0.69
0.99
0.64
0.15
0.46
0.77
0.88
79.76
301.48
38.56
38.57
45.55
66.38
546.34
50.02
36.86
87.71
8.29
4.40
52.13
507.49
12.75
770.29
13.80
27.50
19.93
0.05
43.85
170.71
332.68
34.81
1.43
669.74
8.29
2.00
1.63
19.93
0.05
28.92
24.95
43.85
507.49
15.86
152.70
34.81
1.43
10.34
354.79
669.74
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
No
No
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
1361.0
1582.8
807.0
2361.5
1606.9
1186.3
1530.3
819.5
2207.6
1529.4
1228.3
1045.2
1202.2
1232.4
1382.6
1721.6
1060.2
1355.3
939.8
680.3
1142.9
1172.3
1764.2
1506.5
820.3
1695.4
1228.3
733.4
939.8
680.3
982.6
1308.4
1142.9
1232.4
744.5
2671.0
1506.5
820.3
2565.0
1715.9
1695.4
1361.0
1117.9
807.0
2361.5
1169.0
1186.3
1089.4
819.5
2207.6
1084.4
1228.3
1045.2
1202.2
987.6
1024.8
1163.8
1060.2
1355.3
939.8
680.3
1142.9
946.8
1169.5
1088.6
820.3
1165.1
1228.3
733.4
939.8
680.3
982.6
1308.4
1142.9
987.6
727.4
1335.5
1088.6
820.3
1575.6
1144.8
1165.1
1361.0
769.3
807.0
2361.5
840.6
1186.3
758.8
819.5
2207.6
750.7
1228.3
1045.2
1202.2
804.0
756.5
745.5
1060.2
1355.3
939.8
680.3
1142.9
777.7
723.5
775.1
820.3
767.3
1228.3
733.4
939.8
680.3
982.6
1308.4
1142.9
804.0
714.5
333.9
775.1
820.3
833.6
716.5
767.3
1361.0
711.2
807.0
2361.5
785.9
1186.3
703.7
819.5
2207.6
695.0
1228.3
1045.2
1202.2
773.4
711.8
675.7
1060.2
1355.3
939.8
680.3
1142.9
749.5
649.1
722.9
820.3
701.1
1228.3
733.4
939.8
680.3
982.6
1308.4
1142.9
773.4
712.4
166.9
722.9
820.3
709.9
645.1
701.1
1361.0
699.5
807.0
2361.5
775.0
1186.3
692.7
819.5
2207.6
683.9
1228.3
1045.2
1202.2
767.2
702.9
661.8
1060.2
1355.3
939.8
680.3
1142.9
743.9
634.3
712.4
820.3
687.8
1228.3
733.4
939.8
680.3
982.6
1308.4
1142.9
767.2
712.0
133.6
712.4
820.3
685.2
630.8
687.8
-------
REGRESSION SUMMARY FOR:
O2
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
17437.0
3007.9
2378.7
47341.0
9630.8
7798.3
1298.1
2130.4
25276.0
2076.7
7018.9
4761.9
8415.0
1038.3
1999.4
877.2
4711.8
10081.0
4830.9
4385.2
7885.8
968.0
580.4
1578.6
2385.1
1016.8
7018.9
4082.7
6724.9
4830.9
4385.2
1329.9
10238.0
7885.8
1038.3
1132.5
1194.0
1578.6
2385.1
312.8
615.3
1016.8
6.247
1.720
21.528
4.810
1.513
9.080
4.101
22.334
7.256
1.484
4.036
9.196
7.630
5.831
9.461
2.897
4.819
5.295
7.861
4.346
7.613
9.310
1.196
6.138
3.481
2.438
4.036
3.220
2.253
7.861
4.346
4.721
5.173
7.613
5.831
41.841
10.283
6.138
3.481
1.501
1.236
2.438
Yes
No
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
No
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
-22996.0
161.2
1375.3
-302256.0
130.8
9141.2
107.9
1137.9
-152436.0
104.8
9675.1
4395.3
9864.1
47.2
51.3
155.1
4607.4
-13574.0
4262.3
3544.2
8944.3
47.4
152.5
199.7
38.0
177.4
9675.1
4183.2
8951.3
4262.3
3544.2
-579.7
-13783.0
8944.3
47.2
46.4
82.9
199.7
38.0
182.5
153.4
177.4
-4.405
6.886
-8.040
-3.183
2.698
-6.072
22.769
-7.839
-5.122
9.917
-2.587
-4.683
-5.236
37.143
7.767
29.779
-2.856
-3.709
-4.118
-1.915
-5.225
48.006
24.247
5.418
0.670
11.914
-2.587
-1.653
-1.262
-4.118
-1.915
-1.749
-3.645
-5.225
37.143
102.674
37.767
5.418
0.670
3.752
24.010
11.914
No
Yes
No
No
No
No
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
FL
1/(FIA:)
FL
FL
1/(FIAO
FL
l/(FLAe)
FL
FL
l/CFL^e)
FL
FL
FL
1/(FIAO
l/(FL"e)
1/(FIAO
FL
FL
FL
FL
FL
1/(FIA:)
1/(FIAO
l/(FL^e)
1/(FIA:)
l/CFL^e)
FL
FL
FL
FL
FL
FL
FL
FL
l/(FL^e)
l/CFL^)
l/(FL"e)
1/(FIAO
1/CFIA:)
l/(FL"e)
1/(FIAO
1/(FIAO
0.05
0.12
0.21
0.08
0.06
0.11
0.64
0.22
0.27
0.58
0.22
0.34
0.11
0.98
0.58
0.80
0.15
0.11
0.46
0.31
0.23
0.98
0.84
0.59
0.05
0.60
0.22
0.28
0.44
0.46
0.31
0.20
0.11
0.23
0.98
1.00
1.00
0.59
0.05
0.54
0.84
0.60
19.40
47.41
64.64
10.13
7.28
36.87
518.42
61.45
26.24
98.34
6.69
21.93
27.42
1379.57
60.33
886.80
8.16
13.76
16.96
3.67
27.31
2304.57
587.90
29.36
0.45
141.94
6.69
2.73
1.59
16.96
3.67
3.06
13.29
27.31
1379.57
10542.03
1426.33
29.36
0.45
14.08
576.47
141.94
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
No
No
No
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
17437.0
14421.9
2378.7
47341.0
7798.3
10945.2
2130.4
25276.0
9377.5
7018.9
4761.9
8415.0
5262.3
6591.4
14749.4
4711.8
10081.0
4830.9
4385.2
7885.8
5211.2
13638.7
19441.7
15869.4
7018.9
4830.9
4385.2
1329.9
10238.0
7885.8
5262.3
5283.6
8608.3
19441.7
16320.5
13720.3
15869.4
17437.0
5098.9
2378.7
47341.0
7798.3
4708.8
2130.4
25276.0
3315.5
7018.9
4761.9
8415.0
2531.7
3622.9
5781.8
4711.8
10081.0
4830.9
4385.2
7885.8
2468.2
4822.0
7894.2
5610.7
7018.9
4830.9
4385.2
1329.9
10238.0
7885.8
2531.7
2600.2
3815.4
7894.2
5770.2
4850.9
5610.7
17437.0
637.4
2378.7
47341.0
7798.3
1724.4
2130.4
25276.0
414.4
7018.9
4761.9
8415.0
1225.0
2202.3
1490.3
4711.8
10081.0
4830.9
4385.2
7885.8
1155.6
602.7
2368.0
701.3
7018.9
4830.9
4385.2
1329.9
10238.0
7885.8
1225.0
1316.0
1521.7
2368.0
721.3
606.4
701.3
17437.0
225.3
2378.7
47341.0
7798.3
1448.8
2130.4
25276.0
146.5
7018.9
4761.9
8415.0
1104.3
2071.1
1094.0
4711.8
10081.0
4830.9
4385.2
7885.8
1034.3
213.1
1857.7
248.0
7018.9
4830.9
4385.2
1329.9
10238.0
7885.8
1104.3
1197.4
1309.9
1857.7
255.0
214.4
248.0
17437.0
161.2
2378.7
47341.0
7798.3
1405.9
2130.4
25276.0
104.8
7018.9
4761.9
8415.0
1085.5
2050.7
1032.3
4711.8
10081.0
4830.9
4385.2
7885.8
1015.5
152.5
1778.3
177.4
7018.9
4830.9
4385.2
1329.9
10238.0
7885.8
1085.5
1179.0
1276.9
1778.3
182.5
153.4
177.4
-------
REGRESSION SUMMARY FOR:
HC
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
8.3003
1.1654
0.9744
22.1000
3.8756
4.1802
0.3859
0.8851
14.0632
0.3131
1.7494
0.7667
5.1403
0.1789
0.5473
0.1150
0.9475
6.0535
1.0406
0.1605
4.7410
0.0657
-0.0980
0.5361
1.0607
0.4183
1.7494
0.2060
2.2633
1.0406
0.1605
0.0218
6.2336
4.7410
0.1789
0.0999
0.2000
0.5361
1.0607
0.0235
-0.0432
0.4183
8.497
2.036
12.004
6.861
1.846
6.502
1.429
11.272
5.101
0.265
3.541
3.957
6.175
1.807
5.503
0.543
3.450
4.370
4.630
0.575
6.578
0.969
-0.301
4.376
6.147
1.347
3.541
3.164
2.224
4.630
0.575
2.350
4.330
6.578
1.807
3.036
2.820
4.376
6.147
2.608
-0.132
1.347
Yes
No
Yes
Yes
No
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
Yes
No
Yes
Yes
Yes
No
Yes
No
No
Yes
Yes
No
Yes
No
No
Yes
No
No
Yes
Yes
No
No
No
Yes
Yes
No
No
No
-10.9026
0.0810
-0.5558
-141.1223
0.0691
-5.0538
0.0667
-0.4455
-86.3093
0.0670
-2.6120
-0.3210
-6.1653
0.0113
0.0052
0.1106
-0.9892
-8.1345
-0.7845
1.3609
-5.6510
0.0110
0.1102
0.0167
-0.0325
0.1051
-2.6120
-0.1509
-3.4396
-0.7845
1.3609
0.0059
-8.3627
-5.6510
0.0113
0.0017
0.0299
0.0167
-0.0325
0.0009
0.1113
0.1051
-6.050
11.057
-4.478
-4.437
4.530
-4.513
17.064
-3.762
-3.656
7.710
-2.321
-0.904
-4.388
17.361
1.705
31.223
-2.214
-3.055
-2.046
2.658
-4.871
18.455
26.184
0.995
-2.273
9.612
-2.321
-1.162
-1.422
-2.046
2.658
0.589
-3.041
-4.871
17.361
3.023
22.278
0.995
-2.273
0.370
26.559
9.612
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
No
Yes
No
No
No
No
No
Yes
Yes
No
No
Yes
No
No
No
No
No
No
No
No
Yes
No
Yes
No
No
No
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
1/(FIAO
l/CFL'V)
1/(FIAO
FL
FL
FL
FL
FL
l/CFL^e)
1/(FIAO
1/CFIA:)
1/(FIA:)
l/CFL'V)
FL
FL
FL
FL
FL
FL
FL
FL
1/CFIA:)
1/(FIA:)
l/(FL"e)
1/(FIAO
1/CFIA:)
1/(FIA:)
1/(FIAO
1/(FIAO
0.10
0.28
0.09
0.16
0.17
0.07
0.52
0.07
0.16
0.47
0.21
0.02
0.09
0.94
0.07
0.83
0.11
0.08
0.19
0.47
0.22
0.89
0.86
0.05
0.39
0.53
0.21
0.16
0.50
0.19
0.47
0.04
0.08
0.22
0.94
0.57
1.00
0.05
0.39
0.02
0.87
0.53
36.60
122.26
20.06
19.69
20.52
20.37
291.17
14.16
13.37
59.45
5.39
0.82
19.25
301.40
2.91
974.85
4.90
9.33
4.19
7.06
23.73
340.58
685.59
0.99
5.17
92.40
5.39
1.35
2.02
4.19
7.06
0.35
9.25
23.73
301.40
9.14
496.29
0.99
5.17
0.14
705.36
92.40
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
No
Yes
No
Yes
No
No
Yes
Yes
Yes
No
No
Yes
No
No
No
No
No
No
Yes
Yes
Yes
No
Yes
No
No
No
Yes
Yes
321
321
218
103
103
271
271
201
70
70
22
43
206
22
43
206
42
114
20
10
85
42
114
20
10
85
22
9
4
20
10
11
110
85
22
9
4
20
10
11
110
85
8.300
7.249
0.974
22.100
6.178
4.180
5.970
0.885
14.063
5.995
1.749
0.767
5.140
1.010
0.547
9.890
0.947
6.054
1.041
4.741
0.985
9.860
0.536
1.061
9.404
1.749
1.041
6.234
4.741
1.010
2.672
0.536
1.061
9.956
9.404
8.300
2.563
0.974
22.100
2.184
4.180
2.111
0.885
14.063
2.120
1.749
0.767
5.140
0.357
0.547
3.497
0.947
6.054
1.041
4.741
0.348
3.486
0.536
1.061
3.325
1.749
1.041
6.234
4.741
0.357
0.945
0.536
1.061
3.520
3.325
8.300
0.320
0.974
22.100
0.273
4.180
0.264
0.885
14.063
0.265
1.749
0.767
5.140
0.045
0.547
0.437
0.947
6.054
1.041
4.741
0.044
0.436
0.536
1.061
0.416
1.749
1.041
6.234
4.741
0.045
0.118
0.536
1.061
0.440
0.416
8.300
0.113
0.974
22.100
0.097
4.180
0.093
0.885
14.063
0.094
1.749
0.767
5.140
0.016
0.547
0.155
0.947
6.054
1.041
4.741
0.015
0.154
0.536
1.061
0.147
1.749
1.041
6.234
4.741
0.016
0.042
0.536
1.061
0.156
0.147
8.300
0.081
0.974
22.100
0.069
4.180
0.067
0.885
14.063
0.067
1.749
0.767
5.140
0.011
0.547
0.111
0.947
6.054
1.041
4.741
0.011
0.110
0.536
1.061
0.105
1.749
1.041
6.234
4.741
0.011
0.030
0.536
1.061
0.111
0.105
-------
REGRESSION SUMMARY FOR:
Dry Exhaust Mass
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05 | 0.10 | 0.40 | 0.80 | 1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
81773
16654
13974
215837
46871
38787
8982
12856
118345
13054
35710
25164
41490
8207
11780
7100
25056
49392
24582
21717
38883
7715
5900
9835
13652
7526
35710
20751
40881
24582
21717
10269
49800
38883
8207
8199
8215
9835
13652
4285
5980
7526
6.739
2.196
29.048
5.064
1.699
10.070
6.390
30.853
7.628
2.103
4.504
9.547
8.401
10.211
10.838
5.325
5.642
5.783
9.202
4.339
8.479
15.764
2.745
8.921
4.138
4.210
4.504
3.847
2.327
9.202
4.339
7.703
5.609
8.479
10.211
67.122
13.124
8.921
4.138
4.130
2.699
4.210
Yes
No
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
-103985
725
6660
-1354570
586
-42156
489
5551
-693710
473
-44675
-21223
-45285
216
252
700
-21595
-62686
-19331
-14896
-40817
216
688
905
114
811
-44675
-17801
-52924
-19331
-14896
3880
-63187
-40817
216
197
489
905
114
979
691
811
-4.582
7.136
-8.942
-3.294
2.788
-6.244
23.239
-8.754
-5.234
10.086
-2.620
-4.442
-5.368
37.625
7.401
30.514
-2.946
-3.818
-4.297
-1.623
-5.386
46.522
24.725
5.729
0.416
12.697
-2.620
-1.653
-1.268
-4.297
-1.623
-2.474
-3.725
-5.386
37.625
96.782
41.328
5.729
0.416
4.044
24.304
12.697
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
FL
1/CFIA:)
FL
FL
1/(FIAO
FL
l/CFL^e)
FL
FL
1/(FIAO
FL
FL
FL
l/CFL'V)
l/CFIA:)
1/(FIAO
FL
FL
FL
FL
FL
l/CFL'V)
1/(FIAO
l/CFL'V)
l/(FI/e)
1/(FIA:)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIAO
l/CFL'V)
l/CFIA:)
l/(FLAe)
l/CFIA:)
1/(FIA:)
1/(FIA:)
l/(FL^e)
0.06
0.13
0.25
0.09
0.06
0.12
0.65
0.26
0.28
0.59
0.22
0.31
0.12
0.98
0.56
0.81
0.16
0.12
0.48
0.25
0.24
0.98
0.85
0.62
0.02
0.63
0.22
0.28
0.45
0.48
0.25
0.34
0.11
0.24
0.98
1.00
1.00
0.62
0.02
0.58
0.85
0.63
21.00
50.92
79.96
10.85
7.77
38.99
540.03
76.63
27.39
101.73
6.86
19.73
28.82
1415.64
54.77
931.13
8.68
14.57
18.47
2.63
29.01
2164.33
611.34
32.82
0.17
161.23
6.86
2.73
1.61
18.47
2.63
6.12
13.88
29.01
1415.64
9366.66
1707.97
32.82
0.17
16.36
590.69
161.23
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
No
No
No
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
81773.0
64821.6
13974.0
215837.0
52414.7
38787.0
52701.8
12856.0
118345.0
42309.6
35710.0
25164.0
41490.0
27522.5
34284.1
69690.4
25056.0
49392.0
24582.0
21717.0
38883.0
27070.0
61579.4
90791.8
13652.0
80024.7
35710.0
20751.0
24582.0
21717.0
10269.0
49800.0
38883.0
27522.5
25857.0
51952.0
90791.8
13652.0
91857.6
61811.2
80024.7
81773.0
22917.9
13974.0
215837.0
18531.4
38787.0
24439.3
12856.0
118345.0
14958.7
35710.0
25164.0
41490.0
15036.4
19736.4
29229.0
25056.0
49392.0
24582.0
21717.0
38883.0
14558.1
21771.6
38457.2
13652.0
33158.1
35710.0
20751.0
24582.0
21717.0
10269.0
49800.0
38883.0
15036.4
14442.2
23678.6
38457.2
13652.0
35246.4
21853.6
33158.1
81773.0
2864.7
13974.0
215837.0
2316.4
38787.0
10914.2
12856.0
118345.0
1869.8
35710.0
25164.0
41490.0
9061.1
12774.5
9866.1
25056.0
49392.0
24582.0
21717.0
38883.0
8570.5
2721.5
13412.3
13652.0
10729.9
35710.0
20751.0
24582.0
21717.0
10269.0
49800.0
38883.0
9061.1
8979.6
10148.3
13412.3
13652.0
8154.9
2731.7
10729.9
81773.0
1012.8
13974.0
215837.0
819.0
38787.0
9665.2
12856.0
118345.0
661.1
35710.0
25164.0
41490.0
8509.3
12131.6
8078.0
25056.0
49392.0
24582.0
21717.0
38883.0
8017.5
962.2
11099.5
13652.0
8658.6
35710.0
20751.0
24582.0
21717.0
10269.0
49800.0
38883.0
8509.3
8475.1
8898.7
11099.5
13652.0
5653.0
965.8
8658.6
81773.0
724.7
13974.0
215837.0
586.0
38787.0
9470.9
12856.0
118345.0
473.0
35710.0
25164.0
41490.0
8423.4
12031.6
7799.8
25056.0
49392.0
24582.0
21717.0
38883.0
7931.5
688.5
10739.6
13652.0
8336.4
35710.0
20751.0
24582.0
21717.0
10269.0
49800.0
38883.0
8423.4
8396.6
8704.3
10739.6
13652.0
5263.8
691.1
8336.4
-------
REGRESSION SUMMARY FOR:
H2O
Exponent= 1
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05
0.10 | 0.40
0.80
1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
477.17
222.44
280.42
825.06
259.05
416.44
220.09
284.37
782.36
220.34
423.18
366.65
424.42
257.01
198.53
208.46
366.09
498.35
275.59
200.29
380.12
249.71
212.09
205.72
242.25
209.17
423.18
248.95
1003.21
275.59
200.29
343.21
475.58
380.12
257.01
248.92
156.49
205.72
242.25
197.86
210.71
209.17
29.543
25.956
57.875
18.584
7.286
24.781
29.806
56.590
12.204
6.104
11.379
6.640
21.963
38.289
6.678
30.979
17.044
13.593
23.913
3.937
23.514
28.157
14.629
32.352
7.336
48.104
11.379
415.284
2.547
23.913
3.937
24.260
13.613
23.514
38.289
529.531
3.046
32.352
7.336
7.716
16.687
48.104
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
-331.90
16.49
-51.20
3478.26
15.20
-238.44
15.92
-53.02
3163.97
15.94
-236.35
-210.79
-241.36
8.30
16.22
20.06
-136.04
-362.12
-78.35
21.87
-190.68
7.61
21.80
10.86
-9.52
17.37
-236.35
0.06
1202.47
-78.35
21.87
-100.48
-328.57
-190.68
8.30
0.01
56.12
10.86
-9.52
36.20
20.68
17.37
-10.987
23.250
-6.824
-8.121
8.966
-8.095
21.839
-6.933
-5.777
8.698
-2.955
-2.106
-7.312
23.289
3.739
27.350
-3.838
-5.138
-4.037
0.234
-7.138
12.542
17.051
5.181
-1.244
26.800
-2.955
0.053
-1.285
-4.037
0.234
-6.036
-4.923
-7.138
23.289
0.196
12.662
5.181
-1.244
3.383
18.560
26.800
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
Yes
No
Yes
Yes
No
Yes
Yes
Yes
FL
1/(FIAO
FL
FL
1/(FIAO
FL
l/(FL"e)
FL
FL
l/CFL'V)
FL
FL
FL
l/CFL7^)
l/CFL'V)
1/(FIAO
FL
FL
FL
FL
FL
1/(FIA:)
1/(FIAO
1/CFIA:)
l/(FLAe)
l/(FI/e)
FL
FL
FL
FL
FL
FL
FL
FL
l/(FL^e)
1/(FIA:)
l/(FL"e)
1/(FIAO
1/CFIA:)
1/(FIA:)
l/(FL^e)
1/(FIA:)
0.25
0.60
0.16
0.37
0.42
0.18
0.62
0.18
0.32
0.51
0.27
0.09
0.20
0.96
0.25
0.77
0.24
0.19
0.45
0.01
0.35
0.77
0.72
0.57
0.16
0.88
0.27
0.00
0.45
0.45
0.01
0.75
0.18
0.35
0.96
0.01
0.99
0.57
0.16
0.49
0.76
0.88
120.72
540.55
46.57
65.94
80.40
65.53
476.93
48.07
33.38
75.65
8.73
4.44
53.47
542.37
13.98
748.01
14.73
26.40
16.30
0.06
50.95
157.31
290.73
26.84
1.55
718.24
8.73
0.00
1.65
16.30
0.06
36.44
24.23
50.95
542.37
0.04
160.34
26.84
1.55
11.44
344.46
718.24
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
No
No
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
477.17
552.25
280.42
825.06
563.00
416.44
538.52
284.37
782.36
539.05
423.18
366.65
424.42
423.10
522.93
609.57
366.09
498.35
275.59
200.29
380.12
401.83
648.02
422.87
242.25
556.66
423.18
248.95
275.59
200.29
343.21
475.58
380.12
423.10
248.92
1122.49
422.87
242.25
921.87
624.33
556.66
477.17
387.35
280.42
825.06
411.03
416.44
379.31
284.37
782.36
379.69
423.18
366.65
424.42
340.05
360.73
409.02
366.09
498.35
275.59
200.29
380.12
325.77
430.06
314.30
242.25
382.92
423.18
248.95
275.59
200.29
343.21
475.58
380.12
340.05
248.92
561.24
314.30
242.25
559.86
417.52
382.92
477.17
263.67
280.42
825.06
297.04
416.44
259.89
284.37
782.36
260.18
423.18
366.65
424.42
277.77
239.08
258.60
366.09
498.35
275.59
200.29
380.12
268.72
266.58
232.86
242.25
252.60
423.18
248.95
275.59
200.29
343.21
475.58
380.12
277.77
248.92
140.31
232.86
242.25
288.36
262.42
252.60
477.17
243.05
280.42
825.06
278.05
416.44
239.99
284.37
782.36
240.26
423.18
366.65
424.42
267.39
218.81
233.53
366.09
498.35
275.59
200.29
380.12
259.21
239.34
219.29
242.25
230.88
423.18
248.95
275.59
200.29
343.21
475.58
380.12
267.39
248.92
70.16
219.29
242.25
243.11
236.56
230.88
477.17
238.93
280.42
825.06
274.25
416.44
236.01
284.37
782.36
236.27
423.18
366.65
424.42
265.31
214.75
228.52
366.09
498.35
275.59
200.29
380.12
257.31
233.89
216.58
242.25
226.54
423.18
248.95
275.59
200.29
343.21
475.58
380.12
265.31
248.92
56.12
216.58
242.25
234.06
231.39
226.54
-------
REGRESSION SUMMARY FOR:
Wet Exhaust Mass
Exponent = 1.5
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fractional Load . . .
0.05 | 0.10 | 0.40 | 0.80 | 1.00
All Data
All Data
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FL ge 20
FL It 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
4 Stroke
Not Ind.
2 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
82250
16926
14254
216662
47241
39204
9243
13140
119128
13376
36133
25531
41914
8491
12009
7358
25422
49890
24858
21917
39264
7985
6175
10050
13888
7760
36133
21000
41885
24858
21917
10612
50276
39264
8491
8448
8479
10050
13888
4511
6250
7760
6.775
2.231
29.641
5.082
1.712
10.141
6.557
31.522
7.655
2.149
4.536
9.545
8.457
10.529
10.877
5.506
5.699
5.820
9.288
4.337
8.541
16.194
2.865
9.107
4.177
4.340
4.536
3.894
2.332
9.288
4.337
7.901
5.643
8.541
10.529
69.083
13.329
9.107
4.177
4.293
2.812
4.340
Yes
No
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
-104317
111
6711
-1358048
588
-42395
491
5604
-696874
475
-44911
-21433
-45527
217
254
703
-21731
-63048
-19409
-14874
-41008
217
691
909
110
814
-44911
-17801
-54126
-19409
-14874
3980
-63516
-41008
217
197
500
909
110
993
694
814
-4.594
7.155
-9.014
-3.302
2.796
-6.257
23.271
-8.834
-5.242
10.097
-2.622
-4.421
-5.378
37.678
7.368
30.568
-2.952
-3.826
-4.306
-1.605
-5.398
46.390
24.758
5.745
0.400
12.752
-2.622
-1.653
-1.268
-4.306
-1.605
-2.519
-3.731
-5.398
37.678
96.674
41.585
5.745
0.400
4.049
24.324
12.752
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
Yes
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
FL
1/CFIA:)
FL
FL
1/(FIAO
FL
1/(FIA:)
FL
FL
1/(FIAO
FL
FL
FL
l/CFL'V)
l/CFIA:)
1/(FIAO
FL
FL
FL
FL
FL
l/CFL'V)
1/(FIAO
l/CFL^e)
l/(FI/e)
1/(FIA:)
FL
FL
FL
FL
FL
FL
FL
FL
1/(FIAO
l/CFL'V)
l/CFIA:)
1/(FIA:)
l/CFIA:)
1/(FIA:)
1/(FIAO
1/(FL^)
0.06
0.13
0.25
0.09
0.06
0.12
0.65
0.27
0.28
0.59
0.22
0.31
0.12
0.98
0.56
0.81
0.16
0.12
0.48
0.24
0.24
0.98
0.85
0.62
0.02
0.63
0.22
0.28
0.45
0.48
0.24
0.35
0.11
0.24
0.98
1.00
1.00
0.62
0.02
0.58
0.85
0.63
21.11
51.20
81.25
10.90
7.82
39.15
541.52
78.04
27.47
101.95
6.87
19.54
28.93
1419.65
54.29
934.41
8.72
14.64
18.54
2.58
29.14
2152.06
612.94
33.01
0.16
162.62
6.87
2.73
1.61
18.54
2.58
6.34
13.92
29.14
1419.65
9345.81
1729.27
33.01
0.16
16.40
591.66
162.62
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
No
No
No
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
356
356
241
115
115
291
291
217
74
74
26
45
220
26
45
220
49
114
22
10
96
49
114
22
10
96
26
9
4
22
10
14
110
96
26
9
4
22
10
14
110
96
82250.0
65019.9
14254.0
216662.0
52572.6
39204.0
53151.2
13140.0
119128.0
42476.7
36133.0
25531.0
41914.0
27898.3
34767.4
70198.2
25422.0
49890.0
24858.0
21917.0
39264.0
27428.6
68005.0
91334.5
13888.0
80592.1
36133.0
21000.0
24858.0
21917.0
10612.0
50276.0
39264.0
27898.3
26106.0
53202.0
91334.5
13888.0
93343.6
68301.0
80592.1
82250.0
22988.0
14254.0
216662.0
18587.2
39204.0
24767.0
13140.0
119128.0
15017.8
36133.0
25531.0
41914.0
15352.7
20055.3
29575.1
25422.0
49890.0
24858.0
21917.0
39264.0
14859.1
28035.5
38788.4
13888.0
33510.2
36133.0
21000.0
24858.0
21917.0
10612.0
50276.0
39264.0
15352.7
14691.2
24290.9
38788.4
13888.0
35918.3
28188.1
33510.2
82250.0
2873.5
14254.0
216662.0
2323.4
39204.0
11183.6
13140.0
119128.0
1877.2
36133.0
25531.0
41914.0
9349.0
13014.8
10134.7
25422.0
49890.0
24858.0
21917.0
39264.0
8844.0
8908.0
13642.3
13888.0
10979.0
36133.0
21000.0
24858.0
21917.0
10612.0
50276.0
39264.0
9349.0
9228.6
10455.4
13642.3
13888.0
8437.2
8991.9
10979.0
82250.0
1015.9
14254.0
216662.0
821.4
39204.0
9929.2
13140.0
119128.0
663.7
36133.0
25531.0
41914.0
8794.5
12364.6
8339.4
25422.0
49890.0
24858.0
21917.0
39264.0
8288.5
7141.5
11320.1
13888.0
8898.3
36133.0
21000.0
24858.0
21917.0
10612.0
50276.0
39264.0
8794.5
8724.1
9177.7
11320.1
13888.0
5899.3
7219.1
8898.3
82250.0
726.9
14254.0
216662.0
587.8
39204.0
9734.0
13140.0
119128.0
474.9
36133.0
25531.0
41914.0
8708.3
12263.4
8060.1
25422.0
49890.0
24858.0
21917.0
39264.0
8202.0
6866.7
10958.8
13888.0
8574.5
36133.0
21000.0
24858.0
21917.0
10612.0
50276.0
39264.0
8708.3
8645.6
8978.9
10958.8
13888.0
5504.5
6943.4
8574.5
-------
REGRESSION SUMMARY FOR:
SO2
A/F
Criteria
Loads
Covered
Cycles
Covered
Fuels
Covered
Intercept
Int-T
Sig?
Coeff
Coeff-T
Sig?
Param
r2
F
Sig?
Obs
Prediction at Fuel Sulfur Flow (g/kW-hr) . . .
0.05
1.00 | 5.00
25.00
75.00
All Data
All Data
All Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
Yes Data
FLgeO
FL ge 20
FL It 20
FLgeO
FL ge 20
FL It 20
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
FLgeO
All
All
All
All
All
All
2 Stroke
4 Stroke
All
All
All
All
All
Not Ind.
2 Stroke
2 Stroke
2 Stroke
2 Stroke
4 Stroke
4 Stroke
4 Stroke
All
All
All
All
All
All
All
All
Diesel
Gas Oil
HvyFO
IntFO
Light FO
Diesel
Diesel
Gas Oil
HvyFO
IntFO
Diesel
Gas Oil
Light FO
-0.7670
0.0724
0.0202
-0.4792
0.2349
-0.2861
-2.0526
-0.4113
-1.0787
0.2231
-2.0296
-0.6356
-3.4758
-0.5717
14.7217
0.2575
-2.0296
-0.6356
-1.1326
-0.0069
-3.4758
-1.669
0.239
0.016
-1.124
0.730
-0.215
-3.454
-0.877
-3.670
0.228
-2.124
-0.518
-7.517
-2.039
1.918
4.072
-2.124
-0.518
-1.275
-0.007
-7.517
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
2.4938
2.0971
2.6144
2.3735
2.0600
2.6365
2.4836
2.4005
0.6258
2.6522
2.4103
2.4319
2.7430
0.5481
-4.2272
0.9920
2.4103
2.4319
0.7276
3.0026
2.7430
33.454
33.125
17.230
28.924
29.266
13.595
28.628
24.802
9.525
3.218
16.769
16.579
41.171
9.863
-1.899
31.242
16.769
16.579
3.179
3.340
41.171
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
FuelS
0.79
0.84
0.77
0.78
0.83
0.77
0.96
0.75
0.66
0.09
0.93
0.97
0.95
0.80
0.34
1.00
0.93
0.97
0.46
0.10
0.95
1119.20
1097.25
296.87
836.57
856.49
184.83
819.59
615.13
90.72
10.35
281.20
274.85
1695.06
97.28
3.61
976.09
281.20
274.85
10.11
11.16
1695.06
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
298
207
91
239
183
56
36
203
49
111
22
10
96
26
9
4
22
10
14
107
96
0.125
0.105
0.131
0.119
0.103
0.132
0.124
0.120
0.031
0.133
0.121
0.122
0.137
0.027
0.050
0.121
0.122
0.036
0.150
0.137
2.494
2.097
2.614
2.374
2.060
2.636
2.484
2.401
0.626
2.652
2.410
2.432
2.743
0.548
0.992
2.410
2.432
0.728
3.003
2.743
12.469
10.486
13.072
11.868
10.300
13.182
12.418
12.003
3.129
13.261
12.052
12.160
13.715
2.740
4.960
12.052
12.160
3.638
15.013
13.715
62.345
52.429
65.360
59.338
51.499
65.912
62.089
60.013
15.646
66.306
60.258
60.798
68.574
13.702
24.801
60.258
60.798
18.189
75.065
68.574
187.035
157.286
196.081
178.013
154.497
197.737
186.266
180.038
46.938
198.917
180.774
182.394
205.722
41.106
74.402
180.774
182.394
54.568
225.196
205.722
>
-------
PM Emission Rate Data
10.0
1.0
0.1
0%
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
20%
40% 60% 80%
Fractional Load
100% 120%
FIGURE A-1
-------
NO Emission Rate Data
1 nnn
1UUU
1
0
z 10 -
1
o
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
o
rfP
°8o ~M
°«^8&S ftS" &°sJ>* % «^£>fe<
b ^^^°^y fi Ro^^^^K «^
O A A o A ^^ V^™ JA ^^ Qo ^^ JO Cf*^CF^^
A ^ ^ ^ ^^ Q f\ Cf f* A Q
A A A
^ tl **
• « '
° 8
fl^^) odoQ__Q 60
O AfV ^QC^ tr
O"
o
A
1 1 1 1 1 1
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-2
-------
NOX Emission Rate Data
innn
1UUU
^ 100 -
1
M
O
fc 10 -
1
o
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
o
o^
rfr
8& <&• ; : • :
°-^'o^ycMl&^^
OA A A O A 'Ct 4* I-L ^^ OT M\ O
-^ - - v — • o^ o O " °
^
^^H ^^
J^^Jj ^-^-^-^^?S__«->*» f\ ^r ^^
jfc^' * ^^ntXJ ri
U Q ^* ^^
o
: A ; A ; A : :
• A
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-3
-------
NO2 Emission Rate Data
innn
1UUU
^ 100 -
1
O
fc 10 -
1
o
-Q --------------------------------------------
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
Q/ i i i i
ffy i i i i i
o^&\
Jg&
-------
CO Emission Rate Data
1000 0
1 \J\J\J. \J
100.0
=* 10.0
o
u
1.0
n 1
^^ '
JyJ i i i 1
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
o
AV?
***£& *
°8^> o
- ^^t^^rt^ " " f\ " ^k i ----------- -i ----------- ^ ----------- i- ----------- i ------------
f\ ^j Eff ^^ ^b
V^ j»x ^^ 'C^^ ' ' ^* ^^ '
o 5N? »j^ ^^^ ^ f^ firt o A ^p I
A /O On^^ ®Oo£j-*r\ -ft A ^
°O ^P^^i^^a ^)^C®CT OrO° ®i
A n
0
Qj^
° *c?0<^ o 0<^^ llrLg o ^os^^^0 *^A ° o°
^^ ^^^ ^^j ^^ i ^^ ^^ i l^l ^^^
^0 0 ou * o o
• * ; o
^* f\ ^k ^^ ^^ '
^^ ^»i 0&^ ^^ /^
i O ,**. i /^
_ ,_ . - . - . - . v/- Q - -QP - - -
• i j i
- - - - -----------------------------------------------------------
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-5
-------
CO2 Emission Rate Data
i nnnn
1UUUU
i
Ib 100°
O
u
i nn
o
•
0°
«o£
,_ vQn£4^ j ^^s f\ Q /-k ' Ott
O /% ~/-\"*ilV'tor>l> ^-§LjOD 'r-u ^O nSji? r^ ^L^\ ^v-A o
-* ^o*> Co^o^^^^Pyc^yS Qtro^Sy^P^
1 '
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
o
flDrn JfrjT'Qx^rflDn o^
•Bo
-------
O2 Emission Rate Data
1 000000
-I \J\J\J\J\J\J
100000 -
id
| 10000
o
1000
i nn
o
O-i
o
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
CQ
O ! ! ! !
"*^^D^i ---------------------------------------------------------------
CD ^*^1^ JE ^^
^? /*^ ^k ^/ ' '
*Jp JT^ O --
^CnjppD ^)^B A
O ^VfS&fSP^&t Q> • ^A, ^ flJ* •
• O^^0^®^^^^^^)^
i ^^ i ^^ %x ^^ i ^j • • ^%
.A -**
«V rO ®
^^^^ ^^- \J i ^^
, , ^^~
0
A "^
A ^ /ft
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-7
-------
HC Emission Rate Data
100 000 -r~
10.000
* 1.000
1
u o.ioo -
ffi
0.010 -
n nm
w -------------------------------------------
A>
\J -LJB^J- ---------------------------------------
^f^f V^
*^
Mi__P ;
00 ^jjLrh'dk ^J&^fL^ °0 * ^
oft "b% S^JPd Q_J?§S>Q?r^ °^ cP^ct^S
A ^^ ^B ^^ •• n^^ ^^ ^^^t j ^^ ^""^ i^i ^)^^ri^ C? *•% 11 rii
^r 0 O _. O A«^ D ^^r^fcOO O^
o o ^ *o w ^
A o o ° o
A A m
A
A A ... ...... .A A
A A "
A
A- - - -
A
_-_-_-_-_-_-_-_-_._
O Lloyds (4 Stroke)
• 1 1 /~v\7/Hc 1 / ^1"f"/~\K £* 1
I ji\^i\ VJ.o 1 ^ O LI WJvC )
A USCG (2 Stroke)
rv O
^ 6
On
^^^fc ^^ tJ"
^oo^^^ogo
•
:;::: A; :::»:::::::::
___________________
,
o
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-8
-------
Dry Exhaust Emission Rate Data
i nnnnnn
1UUUUUU
£ 100000
3
w 10000 -
fc*
Q
innn
o
eft
0 Lloyds (4 Stroke)
• Lloyds (2 Stroke)
A USCG (4 Stroke)
A USCG (2 Stroke)
- -\0- -------,-----------,-----------------------,----------- T -----------
o
A.
A.^8ST
8 v*> • •
*^__o
^ $8S£w^aS&«« v
^ ^^^ ^^ ^5 0" ^^jl^ rQ_ C^?^ C*~^ llQOr"^ ^^
™ O ^u t» D Ofu& G^^
A A /& *Sr
fk o
OttP o^croSP^ 80
: : :
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-9
-------
H2O Emission Rate Data
10000
1000 -
0
100
10
0% 20%
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
40% 60% 80% 100% 120%
Fractional Load
FIGURE A-10
-------
Wet Exhaust Emission Rate Data
i nnnnnn
1UUUUUU
£ 100000 -
=
e*
S 10000 -
innn
o
O Lloyds (4 Stroke)
• Lloyds (2 Stroke)
AUSCG(4Stroke)
AUSCG(2Stroke)
o
A.
1 T
fOD ....
A jfT !
t3 c*> o •
^ft? o
^iS^AA^sS-ssMt:
_ ^^* o O OF ^^^ ff oi. ftf ^L^vSBP^ AA
^ * ^ riO 'J 15 OXJQ O^^
A o
07 ^P Avv»<)9f>vv-rS
qjp ^^^°O^JPM go
O
A A fli **^
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-11
-------
NO Emission Rate Data
1000
100
10
0%
20%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
40% 60% 80%
Fractional Load
100% 120%
FIGURE A-12
-------
NO Emission Rate Data
1000
100
10
0%
20%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
40% 60% 80%
Fractional Load
100%
120%
FIGURE A-13
-------
NO2 Emission Rate Data
1000
100 -
10
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
0%
20%
40% 60% 80%
Fractional Load
100% 120%
FIGURE A-14
-------
CO Emission Rate Data
1000 0
-1 \J\J\J. \J
100.0
=* 10.0
•32
o
u
1.0 -
n 1
A
>A
-Q --------- :- -----------------------------
A
A Lloyds (light fuel oil)
4 Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
°^$ O
°A6A A
MJV *» /v n • B
V^ ^^ ^^ ' A^ ' ' ^^ ^| '
A 7? A T^ -A A A A ^P
X) Or%^^ OA^ B. ^^
°O jP^Qll^^ ^9L^»(^ Ar»AA ° A
° ^? ":* 0 °^^ ln?jft &|" # ^
^^rt» ^» A iO
~ ^^ O
* O
• n
fi
f& x A o
A Aj . X O
^\ O A » ^ A
Tf -w A. . ^^ a . . .
A A A A
" A «»
•
: H
0% 20% 40% 60% 80% 100%
Fractional Load
120%
FIGURE A-15
-------
CO2 Emission Rate Data
10000
I
1000
O
u
100
O Lloyds (gas oil)
A Lloyds (light fuel oil)
4 Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
o o
0%
20%
40% 60% 80%
Fractional Load
100% 120%
FIGURE A-16
-------
O2 Emission Rate Data
1000000
100000 -
10000
1000 -
100
o
A
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
0%
20%
40% 60% 80%
Fractional Load
100%
120%
FIGURE A-17
-------
HC Emission Rate Data
100.00
10.00
*
1.00
u
ffi
0.10
0.01
o
A
o
56
0%
20%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
4 Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
40% 60% 80%
Fractional Load
100% 120%
FIGURE A-18
-------
Dry Exhaust Emission Rate Data
1000000
I
100000 -
5C
B
10000
1000
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
0%
20%
40% 60% 80% 100%
Fractional Load
120%
FIGURE A-19
-------
H2O Emission Rate Data
10000
1000 -
o
n
ffi
100
10
0%
20%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
* Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
40% 60% 80%
Fractional Load
100%
120%
FIGURE A-20
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Wet Exhaust Emission Rate Data
1000000
100000
B
e*
10000 -
1000
o
A
0%
20%
O Lloyds (gas oil)
A Lloyds (light fuel oil)
4 Lloyds (intermediate fuel oil)
• Lloyds (heavy fuel oil)
40% 60% 80%
Fractional Load
100%
120%
FIGURE A-21
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APPENDIX B
SUMMARY OF REPORTS REVIEWED
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"Marine Exhaust Emissions Research Programme"
By Lloyd's Register
Summary
The Marine Exhaust Emissions Research Programme tested the emissions of nitric oxide
(NO), carbon monoxide (CO), hydrocarbons (HC), carbon dioxide (CO2), and sulfur
dioxide (SO2) from marine vessels. Emissions were tested on a total of 48 engines
installed on 39 vessels, representing a cross section of marine vessels and included bulk
carriers, container ships, dredgers, ferries, tankers, and tugs. Phase I quantified the
exhaust emissions from marine diesel engines operating under steady state conditions,
which is summarized here. The summary is broken into two parts: medium speed
engines, slow speed engines.
Of the total vessels tested, 37 engines in 31 vessels were reportedly medium speed
engines. Examination of the data revealed that of these 37 engines, 36 were medium
speed and one was a high speed engine. The vessels were monitored under steady state
operation over a range of load conditions from idle through full power. Each ship was
tested for emissions between 4 to 6 different engine loads. Exhaust gases were sampled at
the point of discharge into the atmosphere. Non-dispersive infrared (NDIR) analyzers
monitored NO, SO2, CO, and CO2. Samples of the fuel and lubricating oil in use at the
time of trial were also evaluated. Exhaust emission factors were then calculated in terms
of kg pollutant per ton of fuel.
Detailed data on each engine revealed very large differences in measured power at 100%
load relative to the engine rated power, with measured power being anywhere from 50 to
130% of rated power. No explanation of these differences were provided in the text. In
addition, only raw emission concentration data was provided for each engine so that
engine brake specific emissions at each test point could not be easily determined. Engine
specifications other than rated power were not disclosed.
The following emission factors were derived from the medium speed engines tested:
• NOx 59 kg/ton fuel
• CO 8 kg/ton fuel
• HC 2.7 kg/ton fuel
• CO2 3250 kg/ton fuel
• SO2 (2l.OxS)-2.1 kg/ton fuel
Where S = sulfur content of fuel (% by weight)
There is no detailed explanation in the text as to how the emission factors were derived,
but the factors appear to be for a 85% engine load.
Emissions were tested on 11 slow speed engines installed on 9 vessels. One of these
vessels had also been included in the medium speed sample. The following emission
factors in kg pollutant per ton of fuel were calculated from the slow speed engine
measurement program:
-------
• NOx 84 kg/ton fuel
• CO 9 kg/ton fuel
• HC 2.5 kg/ton fuel
• CO2 3165 kg/ton fuel
• SO2 (21.0xS)where
Where S = sulfur content of fuel (% by weight)
In a related series of tests, Lloyds examined the implications of transient operation during
port arrival and departure stages. Emissions on a fuel specific basis for HC and CO were
significantly different from emissions measured at steady state, with HC emissions higher
by 50% and CO higher by 280%. NOx emissions were about 10% lower.
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"Port of Vancouver Marine Vessel Emissions Test Project - Final Report"
By Environment Canada
Summary
The objective of this study was to perform a detailed study of the emission contribution from
marine shipping activities within selected Canadian regions/ports to the local ambient air quality.
In order to accomplish this the ERMD measured exhaust emissions from a selected sample of
large marine vessels operating in the waters in and around the Port of Vancouver. The selected
sample of marine vessels included low speed diesel cargo and container vessels, medium speed
diesel ferry and cruise ships, and a high speed diesel work boat (tug) with emphasis placed on the
cargo and container vessels The engine test sample included nine loe speed diesels, one medium
speed and one high speed diesel, as well as five auxiliary engines.. These vessels were examined
in four operating modes: maneuvering, low-speed cruise, normal cruise, and hotel power while at
berth.
The report describes the four operating modes in very general terms and there is no information
on what the engine load factor was during these conditions, or the degree of transient operation,
although it can be inferred that maneuvering could consist of a higher degree of transient
operation. The auxiliary engines were tested only at the hoteling mode. Not all engines were
tested at all modes. Detailed engine specifications were not provided although the engine make
and model were identified.
To measure the exhaust emissions on the vessels while in operation, the sampling and analysis
system had to be portable rugged, and easily assembled, as well as provide meaningful data
comparable to a more permanent installation of analyzers. Both main engines and auxiliary
engines were tested. Main engines were tested in three different operational modes:
maneuvering, low cruise, and normal cruise. Eleven main engines were tested, however one
engine was tested only in the normal cruise operational mode. A table summarizing the results is
presented below:
Maneuvering
Low Cruise
Normal Cruise
Auxiliary
High
Low
High
Low
High
Low
High
Low
NOX
184.74
35.48
172.65
39.36
178.86
48.58
86.22
24.44
THC
1.33
0.37
22.9
0.22
1.19
0.15
3.78
0.93
CO
61.1
3.29
21.11
0
9.7
0
7.64
2.75
C02
3357
2787
3362
3212
3393
2818
3457
2855
PM
13.39
1.47
12.4
1.78
16.32
1.04
9.97
0.65
Fuel samples were taken to analyze the sulfur content. The calculated SO2 emissions varied from
4.7 kg/tonne to 63.8 kg/tonne.
11
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The study results were compared to the IMO emission limits and to the Lloyds Marine Exhaust
Emissions Research Programme. The spread in emission rates from the vessels is evenly
distributed around the IMO limit. The emissions factors were claimed to show reasonable
agreement between this study and the Lloyds study, even though there are significant differences
between the test procedures and analytical instrumentation.
12
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"BC Ferries Emissions Test Program Report for BC Ferry Corporation"
by Environment Canada
Summary
The objective of this study was to quantify the emissions from a cross section of ferries
from the British Columbia fleet. Eight vessels in the British Columbia Ferry Corporation
(BCFC) fleet, were tested for the emission rates of oxides of nitrogen (NOx), carbon
monoxide (CO), carbon dioxide (CO2), hydrocarbons, and particulate matter (PM). One
engine from each of the vessels was tested except for the vessel named Quinsam where
two engines were tested at cruise.
This study utilized a portable commercial continuous emission monitor (ECOM-AC) for
the measurement of CO, CO2, NO, NO2, and O2 and a stainless steel mini dilution
system for the collection of particulate sample filters. A fuel sample was collected and
analyzed at a commercial laboratory to determine the sulfur content. The sampling
system was connected to the exhaust ducting of the ship's propulsion or auxiliary engine.
Emissions were tested from a main propulsion engine while the vessel was underway at
normal cruising speed, as well as when the vessel was at dock. The emission calculations
are based upon those outlined in ISO 8178-1, which are based on a carbon balance
between the fuel and exhaust.
The details of the test cycle used are described only in very general terms. Tests were
conducted conditions described only as 'cruise' and 'docking' and there is reference to
the fact the main engines were operating at about 85% of maximum rated power at cruise
and at 15% during 'docking'. However, the data presented in the tables together with the
data on rated power (which must be inferred from a chart) do not support these
statements. No data on the engine specifications are provided, and in one instance, the
cruise RPM stated in the table appears very unlikely to be correct.
The emission rates of the eight vessels analyzed are comparable at cruise were claimed to
Lloyds factors generated from research conducted by Lloyds Registry and reported in
Marine Exhaust Emissions Research Programme. Below are the average emission rates
from main engines during cruise (kg/tonne fuel) in comparison to the Lloyds results.
Pollutant
NOX
CO
C02
PM
BCFC Factors
68.7
4.9
3150
2.0
Lloyds Emission
Factors
75
3
3190
1-1.5
The table below shows the average emission rates from main engines while docked in
comparison to the emission factors developed by Lloyds Register.
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Pollutant
NOX
CO
CO2
PM
BCFC Factors
72.1
8.2
3043
3.7
Lloyds Emission
Factors
58
45
3190
6-8
The emission factors observed varied greatly between engines at the same test condition
(by as much as a factor of three), but the averages appear invariant by mode.
Three auxiliary engines were also tested, at full load and rated speed. Observed emissions
on a fuel specific basis varied by a factor of 4 for NOx and PM emissions
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"Shipboard Marine Engine Emission Testing for the United States Coast Guard"
By Volpe National Transportation Systems Center and U.S. Coast Guard Headquarters
Naval Engineering Division
Summary
The objective of this study was to quantify the emissions for nitrogen oxides (NOJ, sulfur
dioxide (SO2), carbon monoxide (CO), unbumed hydrocarbons (UHC), and particulate matter
(PM) of a selected number of vessels of the United States Coast Guard (USCG) fleet. CO2 and
O2 levels in exhaust gas were monitored and smoke opacity determined. This study also sought
to update the emission inventory for USCG vessels in area under California Air Resources Board
(CARB) jurisdiction using emission data obtained from this study, as well as update emission
reduction strategies based on the results. The USCG selected six vessels for source testing which
would give emission data for a cross section of engine types operating at different load
conditions. Only ship board engines used for propulsion were tested. Each vessel had two
engines for a total of 12 engines tested, of which 8 were medium speed and 4 were high speed
diesels. One vessel also had 2 gas turbine engines which were tested.
To determine the NOX, CO, and SO2 emissions, continuous emission monitoring (CEM) was
used following EPA methods. An analysis of batch samples provided the UHC estimates and
PM estimates were acquired using a novel, micro dilution method. Opacities were estimated for
three vessels which were equipped with vertical stacks and exhaust plumes could be observed.
The test procedure employed was a steady-state cycle at idle, 25%,50%, 75% and 100% of the
maximum rated power. The description is not completely clear about how power was
determined, and the reported power data do not agree very well with the rated power of the
engines. In one case, the measured power at the 100% load point differed from the rated power
by 85 percent. In one case, no full power data was measured.
Below are tables summarizing the estimates for diesel engine emissions.
Power
100%
75%
50%
25%
Idle
Starboard
Port
Starboard
Port
Starboard
Port
Starboard
Port
Starboard
Port
NO, (g/kWh)
High
18.7
14.7
16.9
15.2
20.9
21.1
23.8
23.2
47.9
49.5
Low
6.85
6.3
8.7
6.41
8.94
8.14
6
4.22
8.76
9.67
CO (g/kWh)
High
1.38
1.24
3.27
2.98
4.01
2.61
6.1
4.91
89
118
Low
0.83
0.55
1.21
0.87
0.89
0.83
0.74
0.98
3.67
3.95
SO7 (g/kWh)
High
1.66
1.56
1.9
2.04
2.65
2.98
2.51
2.69
5.77
5.1
Low
0.12
0.1
0.11
0.09
0.1
0.09
0.1
0.09
0.48
0.42
15
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Power
100%
75%
50%
25%
Idle
Starboard
Port
Starboard
Port
Starboard
Port
Starboard
Port
Starboard
Port
UHC (g/kWh)
High
0.59
0.42
0.53
0.37
0.84
0.6
3
2.05
6.86
5.69
Low
0.02
0.01
< 0.001
0.02
0.01
0.04
0.03
< 0.001
0.42
0.71
PM (g/kWh)
High
0.81
0.23
0.44
0.69
0.46
0.52
0.8
0.81
3.22
3.26
Low
0.14
0.13
0.18
0.15
0.19
0.19
0.17
0.27
3.08
2.22
Power
100%
75%
50%
25%
Idle
Starboard
Port
Starboard
Port
Starboard
Port
Starboard
Port
Starboard
Port
0, (%)
High
13.1
13.3
13.2
13.3
15.8
14.9
18.9
18.3
19.4
19.7
Low
10.7
10.4
9.88
9.02
8.08
7.77
7.79
7.06
18.7
18.8
CO, (%)
High
8.28
8.27
8.29
8.31
9.43
9.45
9.46
9.57
1.61
1.51
Low
5.46
5.52
5.66
5.66
3.91
4.25
1.99
1.84
1.03
1.18
Opacity (%)
High
10
9
15
16
15
15
19
19
10
10
Low
5
5
5
5
9
9
8
8
5
5
For one vessel, 378-ft WHEC Sherman, both the diesel engines and gas turbines were source
tested. Below is a table summarizing the gas turbine emissions data.
16
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Pollutant
NO,
CO
SO,
UHC
0,
CO,
g/kWh
g/kWh
g/kWh
g/kWh
%
%
1 00% Power
Starboard
5.98
0.1
0.35
0.1
17
2.73
Port
6.94
1.07
0.29
0.02
17.4
2.79
75% Power
Starboard
3.7
1.26
0.18
0.74
17.8
2.38
Port
4.01
1.24
0.13
0.33
18
2.56
50% Power
Starboard
3.42
2.67
0.28
0.23
18.1
2.05
Port
3.63
2.94
0.25
0.1
18.4
2.28
From the source testing results, an emission inventory for NOx, CO, UHC, PM, and SO2 was
estimated for each of the selected classes of USCG vessels. The table below shows the range of
emission rates for each pollutant.
Pollutant
NO,
CO
UHC
PM
SO,
High
727.8
73.3
13.2
98.7
9.2
Low
54.6
8.1
0.1
1.0
2.3
This study concludes by discussing emission control options that may be available for marine
diesel engines. These include engine modifications, exhaust after treatment, and fuel selection.
17
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"Analysis of Marine Emissions in the South Coast Air Basin" by Acurex
Summary
This study analyzes the NOx reductions expected from International Maritime
Organization (IMO) emission standards, national emission standards and reduction of
ship cruising speeds in the South Coast. Oceangoing vessels would be affected by the
IMO standards and harbor vessels would be regulated under national emissions standards,
while all vessels would be affected by speed reductions in the South Coast Air Basin.
The report utilizes a detailed classification of vessels by 8 ship types, with detailed
records on ship activity by type obtained from the 1996 Acurex report on the Marine
vessel inventory for the South Coast. To assess the expected reductions from and IMO
emissions standard, NOx emissions from main and auxiliary engines need to be
examined. Reductions in main engine emissions are estimated by first developing NOx
emission rates (in g/kWh) using test data from Lloyd's Marine Exhaust Emissions
Research Programme. The report, however, did not appear to address the issue of the
poor match between engine rated power versus observed power at the full power
emissions measurement setting. Emissions calculations were performed in accordance
with the NOx Technical Code using a carbon balance methodology, which yielded NOx
emission rates for several engine loads for each engine tested. However, some curve-
fitting was necessary to fill in the gaps where Lloyd's data was lacking. Two curve-
fitting methods were used: engine specific, combined.
In the engine specific method, first two sets of emission factors in grams of NOx per kWh
were developed, one for uncontrolled engines and one for IMO-controlled engines. Next,
calendar year specific factors were developed, which reflected the mix of ships in
operation in the South Coast built before and after January 1,2000 and was based on the
age profile developed in the inventory study. Then, slow speed and medium speed engine
emission factors, both uncontrolled and calendar year IMO factors were averaged to
calculate load specific factors for the fleet under the two scenarios: uncontrolled and
calendar year controlled operation. These load-specific factors were then weighted by the
total energy spent by each ship speed type at each engine load to calculate energy-
weighted average NOx emission factors in g/kWh. The energy-weighted average NOx
uncontrolled emission factors were then compared with IMO-controlled results for each
calendar year to calculate a percentage NOx reduction associated with the introduction of
the IMO NOx emission limit. This percentage reduction was then applied to the relevant
portion of the NOx inventory from the inventory study, to give an estimated reduction in
tons of NOx per year.
However, because the data are limited, a reasonable use of the data is to combine all of
the results for all of the engines tested (still treating medium speed and slow speed
separately) into a single scatter plot and apply a linear fit to the data. This study chose to
use the curves fit to the data for 10 percent MCR and higher to estimate emissions
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reductions. To determine the effect of IMO standards, the linear fit curve was moved
down until the E2/E3 cycle results would equal the IMO standard. Two equations (slow
and medium speed) were developed to calculate uncontrolled emissions and two
equations (slow and medium speed) to calculate full IMO-controlled emissions. The
uncontrolled and full-IMO controlled factors were then weighted to produce calendar
year-specific factors as in the engine specific methodology. As also in the engine specific
method, the calendar year-specific factors were weighted for medium speed versus slow
speed operation and energy-weighted based on annual energy consumption by
approximate engine load. An ultimate reduction in 2010 of 0.8 NOx tpd is projected
from main engines which call at the San Pedro Bay Ports. The IMO standards will also
reduce emissions from oceangoing vessels that pass through South Coast waters without
calling on the Ports. Comparison of uncontrolled NOx rates at 80 percent MCR and the
2010-controlled NOx rates at 80 percent MCR (energy-weighted average of medium and
slow speed factors) of these transiting vessels shows that for the engine-specific method a
4 percent NOx reduction is expected from the main engines of transiting vessels or 0.3
tpd.
A methodology similar to above was used to estimate NOx reductions from auxiliary
engines. Emissions factors for uncontrolled engines came from data prepared by TRC
Environmental Consultants. The arithmetic average of the emission rates (in g/kWh) for
the engines tested is used to represent the uncontrolled emissions rates of all auxiliary
engines operating in the South Coast waters in a year. The IMO-controlled emissions
were developed assuming that all of these engines would emit at their IMO standard.
Calendar year-specific NOx emission rates for auxiliary engines are calculated from an
age profile. The age profile of the auxiliary engines is assumed as the same as the age
profile of the ships themselves since auxiliary engines are not typically replaced. A
percentage reduction was then calculated by dividing the calendar year-specific NOx
factors by the uncontrolled NOx factor. By 2010, it is expected that NOx emissions from
these auxiliary engines would decline by 1.2 tpd.
This study also estimates the NOx reductions that would be created from harbor and
fishing vessels assuming that EPA adopts the Tier 2 standards from 1600+ rpm engines
and that IMO standards will apply to engines of less than 1600 rpnii To estimate the
NOx reductions, the propulsion engines within each category type were categorized based
on engine rated power and speed (rpm) and the applicable NOx standard identified, as
well as the applicable uncontrolled NOx emission rate. Then calculating an energy-
weighted average controlled and uncontrolled NOx rate in 2010. The two energy-
weighted averages were then compared to calculate the NOx reductions expected in 2010
from IMO and national standards. From these calculations, it is expected that NOx
emissions from harbor and fishing vessels would be reduced by 0.8 tpd if the above
standards were adopted.
Speed reduction is one of the most promising operational modifications for reducing ship
emissions. Eight speed reduction scenarios were analyzed. Each scenario specifies the
distance from the start of the reduced speed zone to the precautionary area, the maximum
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speed allowed, and whether or not the speed limit is applied to all vessels. For each
scenario, distances by operational mode (mil cruise and reduced speed zone cruise - all
other modes unaffected) were recalculated. These distances were then used to calculate
revised hours by operating mode and shiptype. Using scenario speeds and speed power
curves provided by the Navy and their consultant, John J. McMullen (JJMA), engine load
by operating mode and shiptype were estimated. The revised hours and engine loads
were then used to calculate energy consumption (total annual energy consumption and
energy consumption by energy profile loads). Next, the IMO-controlled NOx emission
rates determined above and the revised energy consumption were used to calculate
normalized emissions in 2010, with IMO and speed reduction compared with baseline
operation. Total increased time spent cruising due to speed reduction was calculated and
compared to baseline operation to calculate the associated increased emissions from
auxiliary engines. The net NOx reductions attributable to speed reduction in 2010 were
then calculated. For the scenarios analyzed the 2010 NOx reductions from speed
reduction alone range from 1.6 tpd to 5.2 tpd.
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"Inventory of Air Pollutant Emissions From Marine Vessels"
By Booz-Allen & Hamilton, Inc.
Summary
This study estimates the amount of air pollution generated by commercial marine vessels along
the coastline of California. A three-step process, assessing in sequence vessel population,
activity, and emissions, was used to calculate the tons of emissions of the following pollutants:
oxides of nitrogen (NOJ, hydrocarbons (HC), carbon monoxide (CO), oxides of sulfur (SOX),
and particulate matter (PM).
Population assessments of ocean-going commercial vessels were determined based on
information obtained from the marine exchanges of the San Francisco Bay area and ports of Los
Angeles and Long Beach and the local port authorities and bar pilot associations for the smaller
ports. Vessel populations were assessed in the following classifications: ocean-going, harbor, and
fishing vessels. The main classifications were then further broken down by vessel type, size,
mode of propulsion, and horsepower. For ocean-going population, the population is expressed in
units of individual vessel port calls per year by port. An average duration of call for each vessel
category was calculated for a sample population of vessel calls at the ports in San Francisco Bay
Area and of Los Angeles and Long Beach. The population of harbor vessels was extracted from
the U.S. Army Corps. Of Engineers report Waterborne Transportation Lines of the United States.
1988. while the population of fishing vessels was taken from the 1990 roster of vessels registered
as commercial fishermen with the California Department of Fish and Game.
The levels and types of activity associated with the vessels in each of these classifications were
defined in terms of calculated annual fuel consumption. Equations for fuel consumption rates
published by the U.S. Department of Transportation, Maritime Administration Port Vessel
Emissions Model were used to calculate fuel consumption rates for each type and size of ocean
going vessels. These equations use vessel deadweight tonnage, horsepower, and throttle setting
as a proportion of full power to calculate fuel consumption in gallons per hour. To determine an
average vessel size in deadweight tons and rated shaft horsepower, a sample population of vessel
movements in February, May, August, and November of 1989 was used. The sample vessels
were categorized according the population classifications and for each category of vessel, an
average vessel size in deadweight tons and rated shaft horsepower were calculated. These
averages were then applied to all vessels falling into that category. Then for an entire year, each
vessel call in at each port was recorded as a tally in the appropriate category of vessel type,
propulsion mode, and deadweight tonnage range.
A distinction was then made between energy consumption in-port (either underway or moored)
versus at-sea. In-port activity in the underway mode at each port is characterized by a unique
series of speed and distance vectors for each port destination. The total fuel consumed by each
vessel type, for each propulsion type, and in each weight class is calculated by adding the fuel
consumed over the series of vectors for the port, doubling that figure to account for arrival and
departure, and multiplying by the total number of annual vessel calls. Fuel consumption of
vessels while moored is directly determined by the amount of time spent moored. The time spent
moored is calculated by subtracting out the time spent underway from the total time of each
18
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vessel call. For each classification of vessels, the average number of hours spent moored was
then derived. The total amount of fuel consumed by each vessel classification moored in each
port during one year was calculated by multiplying the average number of hours spent moored by
the number of port calls by that classification of vessel, the full-power fuel consumption rate and
the percentage of full-power fuel consumption associated with the mooring activity for each
vessel classification.
At-sea vessel movements are defined by vectors which represent transit distances between ports
in the basins and the California coastal water boundaries. At-sea fuel consumption is calculated
by first determining the total miles traveled at sea in the basin. The total miles are calculated by
multiplying the number of vessels in each classification by the above vectors lengths. The total
miles are divided by the average at-sea operating speed for each of the vessel classifications and
then multiplied by the full power fuel consumption rate and a factor of 0.8 (which represents the
typical at-sea throttle setting). The final result is the total amount of fuel consumed in the basin
during at-sea operation.
Rates of fuel consumption for harbor and fishing vessels were calculated in much the same
manner as above. The operating profile of each type of vessel was characterized by the
proportion of total operating time that is spent at 20%, 50%, and 80% of full rated power output.
The amount of operating time for each type of vessel per year is characterized as the number of
hours of operation on an operating day and the number of days of operation per year. From this
the average rates of fuel consumption were calculated for each classification of vessel.
Emissions generated by each classification of vessels were calculated based on the amount and
type of fuel consumed and the applicable emission factors. This study uses emission factors
drawn from the 1985 U.S. Environmental Protection Agency report (AP-42) Compilation of Air
Pollutant Emission Factors and the U.S. Maritime Administration's 1986 Port Vessel Emissions
Model. AP-42 contains emission factors for diesel propulsion and auxiliary engines of less than
2,500 horsepower while the Port Vessel Emissions Model provides emission factors for diesel
propulsion plants in excess of 2,500 horsepower. For ocean-going commercial vessels, emission
factors have been applied to the annual fuel consumption figures derived for each port and at-sea
basin.
In-port emissions for underway and mooring operations were calculated separately. The rate at
which a vessel emits pollutants for underway operations varies according to the proportion of full
power at given throttle settings defined as 80%, 50%, and 20% of rated horsepower. For
motorships, a single emission factor is used for all underway modes while emission from
steamships is calculated using two sets of emission factors, one for full power and one for
maneuvering. The following equation for underway emissions from motorships was used:
1000
where: TE = Total annual emissions of specific pollutant (pounds per year)
FC = Total annual amount of fuel consumed underway in 'port' water
19
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(gallons per year)
EF = Emission factor for specific pollutant (pounds per 1 ,000 gallons of
fuel)
For steamship operations the emission calculation is expanded to:
) + (•** ^HALF + ^ ^SLOW )(^ 'MANEUVERING )
1000
where: FCMODE = Total annual amount of fuel consumed in underway
operating mode (gallons per year)
EFMODE = Emission factor for specific pollutant at operating mode
(pounds per 1,000 gallons of fuel)
The calculations for emissions associated with mooring activity are similar to those for underway
operations. For all classes of large ocean-going motorships, emission factors for 500KW
auxiliary generators were assumed and for steam vessels, hotelling emissions were calculated
using the factors prescribed for plants using residual bunker fuel for ship's service power.
Annual emissions for all vessel classifications were summarized as an annual total for each port.
To calculate at-sea emissions, a single set of emission factors were applied for steamships and
another for motorships since the study assumes that all of the coastal traffic operates at full
throttle setting while in transit. The full-power operation emission factor for steamships was
applied to the total amount of fuel consumed by each classification to obtain annual emissions
while the emission factors for all operating modes was used for motorships. The resultant annual
emissions for all vessel classifications were finally totaled for each basin.
The calculation of total emissions for harbor and fishing vessels involves using emission factors
from AP-42, however where factors were omitted iri.this EPA report emission factors from Port
Vessel Emissions Model were used. As in the case of ocean-going commercial vessels, the
emissions from harbor and fishing vessels were calculated on the basis of operating mode,
expressed as a percentage of rated shaft horsepower so the following equation is used to calculate
emissions:
TE =
where: FC = Total annual amount of fuel consumed (gallons per year)
OPpowER = Percentage of operating time spent at each operating mode
EFMODE = Emission factor for specific pollutant at each operating mode
(pounds per 1,000 gallons of fuel)
The following table shows the total statewide emissions for each pollutant:
20
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Pollutant
NO,
HC
CO
so,
PM
Emissions
(tons of pollutant per day)
412.29
28.67
57.53
226.25
27.60
21
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"Marine Emissions Quantification - BCFC Ferries Operating in Greater Vancouver
Regional District Air Shed"
By Lloyd's Register
Summary
At the request of British Columbia Ferry Corporation (BCFC), Lloyd's Register (LR) conducted
a desk based air emissions quantification exercise on all BCFC vessels operating in the Greater
Vancouver Regional District (GVRD) Airshed. The basis for this emission quantification study
were modified fuel consumption data models provided by BCFC. These models were for all
classes of vessels operating on each of the five routes which pass, either entirely or partly,
through the GVRD Airshed. The models include details of route description, vessel class details,
voyage profiles, lay-up fuel consumption, and fuel details.
To estimate the emissions from oxides of nitrogen (NOX), carbon monoxide (CO), carbon dioxide
(CO2), hydrocarbons (HC), sulfur dioxide (SO2), and particulate matter (PM), first data relating
to the whole route was input into the model. The data entered into the model included:
• brake specific fuel consumption (bsfc) figures for the main propulsion engines
• bsfc figures for the generators of all the vessels and for the main engines of the Route
8 vessels
• the duration of each crossing
• the average loads and bsfc for each generator
The following items were calculated:
• volume of fuel consumed by each vessel's main engines whilst on a crossing
• fuel consumed by each vessel's generator whilst in service
Based on the above information the total route fuel consumption figure was derived from the
model. The model derived fuel consumption total was then compared with the actual known
quantity of fuel consumed. Next, the percentage loading of the main engine whilst vessels were
operating along that route were adjusted in order to match these two fuel consumption numbers.
Fuel specific emission factors were then developed for each of the main engine and generator
types from data generated by Lloyds and used to estimate the emissions per vessel per route.
The results show that the BCFC vessels contribute less than 4 percent of total SO2 emissions by
marine vessels. However, these vessels do emit 15 to 16 percent of NOX emissions from all
marine vessels into the airshed. Below is a table summarizing the results by showing an annual
total emission estimate for each of the pollutants tested:
22
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Pollutant
NO,
CO
CO,
so,
PM
hydrocarbons
BCFC Totals
Kg/year
1,565,658
129,162
74,300,883
67,935
36,898
60,874
Note: Sulfur dioxide estimates in this study were presented for three
different sulfur contents of fuels (0.03%, 0.05%, 0.27%).
The total emission of each sulfur dioxide estimates were combined
to calculate the final SO2 estimate.
23
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"Marine Vessel Emissions Inventory and Control Strategies" by Acurex
Summary
This study develops an inventory for marine vessel emissions that contribute to the air quality
problem in the South Coast Air Basin and sets out to resolve any discrepancies from earlier
inventory reports and marine vessel inventories. The inventory assessment includes a baseline
inventory for 1993, a "backcast" to 1990, and a forecast of the 2000 and 2010 inventories for five
pollutants which include: nitrogen oxides (NOx), sulfur oxides (SOx), hydrocarbons (HC),
carbon monoxide (CO), and particulate (PM). Inventories for several categories of ships that
travel through the waters of the South Coast Air Basin are presented in this report and
appendices. The ship categories include: ocean going vessels, tugboats and other harbor vessels,
fishing vessels, U.S. Navy vessels, U.S. Coast Guard vessels.
Ocean going vessels include those vessels calling on the San Pedro Bay Ports and the Chevron
offshore facility at El Segundo, as well as those transiting through the area without calling into
the ports. Ocean going vessels were first grouped in by shiptype. They were further broken
down by propulsion type (motorships or steamships) and then categorized by size and speed
using a "design category" parameter. For each category, fuel consumption at cruise speeds are
calculated by combining route-weighted average distance with average service speed for each
shiptype. Fuel consumption in reduced speed modes (within the precautionary area and
maneuvering in the harbor) are also calculated. Fuel consumption within the precautionary area
is calculated using the assumption that power varies as ship speed cubed. Fuel consumption
while maneuvering in the harbor is estimated based on test data from Lloyds Marine Exhaust
Research Programme and on engineering judgement. Emissions were then calculated using
emission factors in pounds of pollutants per thousand gallons of fuel consumed.
The emissions of the ocean going vessels are calculated using emission factors (pounds of
pollutant per thousand gallons of fuel consumed). For the vessels calling at El Segundo,
adjustments were made to the cruising emissions to avoid double counting. The emissions in the
forecasted years are based on cargo and fleet forecasts for the San Pedro Bay Ports.
Emissions calculations were made for mooring tugboats, non-mooring tugboats and ocean going
tugs. This study chose to simplify by using annual fuel consumption data to estimate annual
consumption. Emission factors in pounds per thousand gallons of fuel consumed for medium
speed diesel engines were used to calculate total emissions. The number of tugs and horsepower
ratings are assumed to remain the same through 2010 so the emissions results are the same since
they are ultimately calculated based on the amount of fuel used.
For fishing vessels, fuel consumption based on four modes of operation and emission factors in
pounds per 1000 gallons of fuel consumed for medium speed diesel engines, taken from the
Lloyd's Marine Exhaust Emissions Research Programme, were used to calculate total emissions
for each of the five pollutants. Since there was no data to support a projection of South Coast
fishing activity, a "no growth" scenario was the most reasonable assumption. Based on
information from the Navy, U.S. Navy vessel emissions were calculated using emission factors
in grams of pollutant per horsepower-hour of shaft power output. _A Coast Guard report in
27
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which emissions test results are presented for several Coast Guard vessels is the basis for
emissions from these vessels^.
Based on the above calculations, marine vessels generate significant quantities of NOX, SOX, HC,
CO, and PM. Overall, the ocean-going vessels calling in at the San Pedro Bay Ports emit the
most tons per day of all five pollutants in 1990 and 1993, as well as in 2000 and 2010. Fishing
vessels emit the next largest amounts in all pollutants except particulate. Emissions of all
pollutants decline from 1990 to 1993 but are expected to increase from 1993 to 2010. Reducing
emissions from marine vessels is important for improving air quality in the South Coast Air
Basin and three types of measures are contained in the South Coast Air Quality Management
District's Air Quality Management Plan and in the California State Implementation Plan for
Ozone. They include: applying emissions standards uniformly worldwide and, for non-ocean-
going vessels nationwide; reducing emissions occurring in the South Coast Air Basin with in-
basin operational modifications such as speed reductions or shipping lane relocation; developing
special (voluntary) projects that reduce emissions locally.
28
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APPENDIX C
ACUREX CLASSIFICATION OF SHIPTYPES
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W1S4, Page 1
MARINE EMISSIONS INVENTORY
Ocean-going VesselsCalling on SPB Ports: Average Rated Power and Fuel consumption in Cruise Mode
Shiptype
Auto Carrier
design
categories
Motorships 0-200
200-400
400-600
>600*
corresponding
dwt categories
0 - 5,800
5,800 - 16,500
16.500 - 30,300
30,300 +
Avg. LMIS bhp
for category
-
13,552
16,003
18,000
BSFC
gram/bhp-hr
100
100
100
cruise fuel consumption
for category (gal/hour)
328
387
435
design
Shiptype categories
Bulk Carrier Motorships 0-200
200-400
400-600
600-800
800-1000
>1000
Steamships 600-800
800-1000
1000-1200
corresponding Avg. LMIS bhp
dwt categories
0
14,100 -
40,000 -
73,600 -
113,300 -
758/400 +
73,600 -
773,300 -
758,400 -
14,100
40,000
73,600
113,300
158,400
758,4^0
208,200
for category
8,143
10,103
12,508
15,626
23,763
31,200
16,500
24,000
27,500
BSFC cruise fuel consumption
gram/bhp-hr for category (gal/hour)
100
100
100
100
100
100
250
250
250 •
197
244
302
378
575
755
918
1,335
1,530
MARMODRV.10
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W1S4, Page 2
j ~~~~ " design
Shiptype categories
Container Ship Motorships 0-200
200-400
400-600
600-800
800-1000
1000-1200
1200-1400
1400-1600
1600-1800
1800-2000
2000-2200
>2200
Steamships 600-800
800-1000
1000-1200
1200-1400
1400-1600
1600-1800
1800-2000
2000-2200
design
Shiptype categories
General Cargo Motorships 0-200
200-400
400-600
600-800
800-1000
>1000*
corresponding
dwt categories
0 - 1,900
1,900 - 5,500
5,500 •
10,200 -
15,700 -
21,900 -
28,800 -
36,300 -
44,400 -
53,000 -
62,100 -
71,600 +
10,200 -
15,700 -
21,900 -
28,800 -
36,300 -
44,400 -
53,000 -
62,100 -
10,200
15,700
21,900
28,800
36,300
44,400
53,000
62,100
71,600
15,700
21,900
28,800
36,300
44,400
53,000
62,100
71,600
corresponding
dwt categories
0 - 11,600
11.600 - 32,900
32,900 -
60,500 -
93,100 -
130,200 +
60,500
93,100
130,200
Avg. LMIS bhp
for category
8,000
15,044
15,364
19,234
25,499
26,117
30,116
38,739
42,533
47,651
53,207
67,080
32,000
31,238
38,000
0
0
69,833
0
36,000
Avg. LMIS bhp
for category
2,598
10,179
12,988
16,870
35,008
26,000
BSFC
gram/bhp-hr
100
100
100
100
100
100
100
100
100
100
100
100
250
250
250
250
250
250
250
250
- BSFC
gram/bhp-hr
100
100
100
100
100
100
cruise fuel consumption
for category (gal/hour)
193
364
372
465
617
632 •
728
937
1,029
1,152
1,287
1,622
1,780
1,737
2,114
0
0
3,884
0
2,002
cruise fuel consumption
for category (gal/hour)
63
246
314
408
847
629
MARMODRV.10
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W1S4, PageS
design
Jhiptype categories
'assengerShp Motorships 0-100
100-200
200-300
300-400
400-500*
500-600
600-700
700-800*
Steamships 0-100
100-200
200-300
300-400
400-500
500-600
corresponding
dwt categories
0 - 1.400
1,400 - 4,000
4,000 - 7,400
7,400 - 11,500
11,500 - 16,000
16,000 - 21,100
21,100 - 26,600
26,600 - 32,500
0 - 1,400
1,400 - 4,000
4,000 - 7,400
7,400 - 11,500
11,500 - 16,000
16,000 • 21,100
21,100 +
Avg. LMIS bhp
for category
13,943
20,544
26,103
28,859
33,831
-
-
48,747
-
-
24,500
30,220
-
44,000
BSFC
gram/bhp-hr
100
100
100
100
100
100
100
100
250
250
250
250
250
250
cruise fuel consumption
for category (gal/hour)
337
497
631
698
818
-
-
1,179
-
-
1,363
1,681
-
2,447
design
:hiptype categories
eefer Motorships 0-100
100-200
200-300
300-400
400-500
500-600
600-700
700-800
>800*
corresponding
dwt categories^
0 - 1,500\
1,500 - 4,200
4,200 - 7,800
7,800 - 12,100
12,100 - 16,900
16,900 - 22,200
22,200 - 28,000
28,000 - 34.200
34,200 +
Avg. LMIS bhp
for category
5,134
\ 6,530
8,989
12,846
12,385
16,609
20,797
' 23,200
25,500
BSFC
gram/bhp-hr
100
100
100
100
100
100
100
100
100
cruise fuel consumption
for category (gal/hour)
124
158
217
311
300
402
503
561
617
MARMODRV.10
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\N\S4, Page 4
1 "" design
1 Shiptype categories
1 RORO Motorships 0-200
| ; 200-400
I"; i 400-600
ij i 600-800
| * 800-1000
| I 1000-1200
I j
| J Steamships 600-800*
^} 800-1000*
If 1000-1200
|; >1200*
S*
jL_ —
-I design
: Shiptype categories
Tanker Motorships 0-200
200-400
400-600
600-800
800-1000
1000-1200
1200-1400
>1400*
Steamships 0-200
200-400
400-600
600-800
800-1000
1000-1200
1200-1400
1400-1600
1600-1800
corresponding
dwt categories
0 • 2,500
2,500 - 7,200
7,200 - 13,300
13,300 - 20,500
20,500 • 28,700
28,700 - 37,700
13,300 - 20,500
20,500 - 28,700
28,700 - 37,700
37,700 +
corresponding
dwt categories
0 - 12,800
12,800 - 36,300
36,300 - 66,700
66,700 - 102,800
102,800 - 143,600
143,600 - 188,800
188,800 - 238.000
238,000 +
0 - 12,800
12,800 - 36,300
36,300 - 66,700
66,700 - 102,800
102,800 - 143,600
143,600 - 188,800
188,800 - 238,000
238,000 - 290,800
.290,800 +
Avg. LMIS bhp
for category
-
16,683
19,085
27,900
30,150
34,987
32,000
31,000
30,000
32,000
Avg. LMIS bhp
for category
5,894
11,840
15,252
16,251
19,130
24,726
22,690
35,000
7,000
12,333
15,587
20,000
24,457
26,667
28,350
33,600
32,000
BSFC
gram/bhp-hr
100
100
100
100
100
250
250
250
250
BSFC
gram/bhp-hr
100
100
100
100
100
100
100
100
250
250
250
250
250
250
250
250
250
cruise fuel consumption
for category (gal/hour)
403
462
675
729
846
1,780
1,724
1,669
1.780
cruise fuel consumption
for category (gal/hour)
143
286
369
393
463
598
549
846
389
686
867
1.112
1,360
1,483
1,577
1,869
1,780
Notes
1. Calculation of cruise fuel consumption assumes cruise at 80% MCR and assumes a fuel density of 0.95 kg/I
2. BSFC is estimated based fuel consumption estimates for 1983 and newer ships from Reference 18
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