Economic Impacts of the
Category 3 Marine Rule
on Great Lakes Shipping
4>EPA
United States
Environmental Protection
Agency
Office of Transportation and Air Quality
EPA-420-R-12-005
April 2012
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Economic Impacts of the
Category 3 Marine Rule
on Great Lakes Shipping
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
&EPA
United States
Environmental Protection
Agency
EPA-420-R-12-005
April 2012
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Table of Contents
EXECUTIVE SUMMARY
CHAPTER 1: THE GREAT LAKES AND EPA'S MARINE EMISSION CONTROL
PROGRAM
1.1 The Great Lakes Transportation System 1-1
1.2 Marine Engines and Their Fuels 1-5
1.3 Emission Control Program for Category 2 and Smaller Marine Diesel Engines and their
Fuels 1-7
1.4 EPA's Coordinated Strategy for Category 3 Marine Diesel Engines and Their Fuels ... 1-8
1.5 The Coordinated Strategy and the Great Lakes 1-15
1.6 Other Studies of the Environmental and Economic Benefits of Marine Transportation in
the United States 1-20
1.7 European Studies of the Potential Impacts of the 2008 Amendments to MARPOL Annex
VI 1-32
CHAPTER 2: TRANSPORTATION SHIFT ANALYSIS
2.1 Summary and Results 2-1
2.2 Scope of Analysis 2-5
2.3 A Route-Based Approach 2-8
2.4 Selection of Origin/Destination Pairs and Shipping Routes 2-9
2.5 Data Inputs 2-15
2.6 Conclusion 2-21
APPENDICES 2-22
CHAPTER 3: POTENTIAL FOR OTHER SHIFTS IN TRANSPORT OF GOODS, AND
EMISSIONS IMPACTS
3.1 Source Shift Analysis: Crushed Stone 3-1
3.2 Production Shift Analysis 3-10
3.3 Emissions Impact Analysis 3-24
CHAPTER 4: EMISSION INVENTORY FOR THE U.S. GREAT LAKES
4.1 Intr eduction 4-1
4.2 Description of Ships Included in the Analysis 4-2
4.3 Inventory Methodology 4-3
4.4 Development of 2002 Emission Inventories 4-5
4.5 Development of 2020 Emission Inventories 4-20
4.6 Adjustment to 2020 Inventories for Jones Act Shipping 4-30
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APPENDICES 4-32
CHAPTER 5: AIR QUALITY, HEALTH AND ENVIRONMENTAL IMPACTS AND
QUANTIFIED BENEFITS OF REDUCED EMISSIONS FROM GREAT LAKE SHIPS
5.1 Types of Pollutants from Great Lakes Ships 5-1
5.2 Human Health Effects Associated with Exposure to Pollutants 5-4
5.3 Environmental Effects Associated with Exposure to Pollutants 5-14
5.4 Contribution of Shipping to Great Lakes Air Quality 5-31
5.5 Quantified and Monetized Health and Environmental Impacts 5-39
APPENDICES 5-50
CHAPTER 6: COSTS OF CONTROLLING EMISSIONS FROM VESSELS ON THE
GREAT LAKES
6.1 Hardware Costs 6-2
6.2 Estimated Fuel Operational Costs 6-9
APPENDICES 6-14
CHAPTER 7: INDUSTRY CHARACTERIZATION
7.1 The Great Lakes Transportation System At-a-Glance 7-1
7.2 Top 10 Great Lakes Ports 7-4
7.3 Primary Cargoes Shipped on the Great Lakes 7-12
7.4 Industries that Use the Cargoes Transported by Great Lakes Shipping 7-15
7.5 Great Lakes Ships 7-24
7.6 Owners Operators of U.S. Category 3 Ships 7-43
APPENDICES 7-47
CHAPTER 8: RESPONSE TO PEER REVIEW COMMENTS
8.1 Overview 8-1
8.2 Comments Not Addressed Specifically 8-1
APPENDICES 8-2
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List of Acronyms
um Micrometers
ug Microgram
ug/m3 Microgram per Cubic Meter
ACE Army Corps of Engineers
AE Auxiliary Engine
AEO Annual Energy Outlook (an EIA publication)
AFC Average Daily Fuel Consumption
AIRS Aerometric Information Retrieval System
AMVER Automated Mutual-Assistance Vessel Rescue
AQ Air Quality
AQCD Air Quality Criteria Document
ARE Air Resources Board (California)
ASPEN Assessment System for Population Exposure Nationwide
ASTM American Society for Testing and Materials
ATB Articulated Tug-Barge
BenMAP Benefits Mapping and Analysis Program
bhp Brake Horsepower
BSFC Brake Specific Fuel Consumption
C Celsius
Cl Category 1; marine diesel engines up to 7 liters per cylinder displacement
C2 Category 2; marine diesel engines 7 to 30 liters per cylinder
C3 Category 3; marine diesel engines at or above 30 liters per cylinder
CA California
CAA Clean Air Act
CAIR Clean Air Interstate Rule (CAIR) (70 FR 25162, May 12, 2005)
CARD California Air Resources Board
CB Chronic Bronchitis
CDC Centers for Disease Control
CFR Code of Federal Regulations
CMAQ Community Multiscale Air Quality
CN Canadian National
CO Carbon Monoxide
CO 2 Carbon Dioxide
COI Cost of Illness
COPD Chronic Obstructive Pulmonary Disease
CPI-U Consumer Price Index - All Urban Consumers
C-R Concentration Response
cyl Cylinder
DE Diesel Exhaust
DM&IR Duluth, Missabe and Iron Range Railway
DMA Distillate Marine Grade A fuel
DMB Distillate Marine Grade B fuel
DMC Distillate Marine Grade C fuel, reclassified as RMA-10
DMX Distillate Marine Grade X fuel; a light distillate used mainly in emergency or Cl engines
DOE Department of Energy
DOT Department of Transportation
DPM Diesel Paniculate Matter
DV Design Values
DWT Dead Weight Tonnage
EC East Coast Region
EC Elemental Carbon
EGA Emission Control Area
EEZ Exclusive Economic Zone
ill
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EF Emission Factor
EIA Energy Information Administration (part of the U.S. Department of Energy)
EPA Environmental Protection Agency
F Fahrenheit
FR Federal Register
FRM Federal Reference Method
g Gram
g/bhp-hr Grams per Brake Horsepower Hour
g/kW-hr Grams per Kilowatt Hour
gal Gallon
GEOS Goddard Earth Observing System
GI Global Insight
GIFT Geospatial Intermodal Freight Transport model (Energy and Environmental Research Associates,
developed with funding from the United States Maritime Administration)
GIS Geographic Information System
GL Great Lakes Region
GLF Great Lakes Fleet
GL/SLS Great Lakes/St. Lawrence Seaway
GRT Gross Registered Tonnage
GT Gas Turbine
HAD Health Assessment Document for Diesel Engine Exhaust
HC Hydrocarbon
HE Hawaii East Region
HEI Health Effects Institute
HES Health Effects Subcommittee
HFO Heavy Fuel Oil
hp Horsepower
hp-hr Horsepower Hour
hrs Hours
HW Hawaii West Region
IARC International Agency for Research on Cancer
ICD International Classification of Diseases
ICO ADS International Comprehensive Ocean-Atmospheric Data Set
IFO Intermediate Fuel Oil
IMO International Maritime Organization
IMPROVE Interagency Monitoring of Protected Visual Environments
IRIS Integrated Risk Information System
ISO International Standardization Organization
ISORROPIA Inorganic Aerosol Thermodynamics Module
JAMA Journal of the American Medical Association
km Kilometer
kt Kiloton (1,000 metric tons)
kts Knots
kW Kilowatt
kWh Kilowatt Hour
L Liter
L/cyl Liters Per Cylinder
LF Load Factor
LGC Large Gas Carrier
LNG Liquefied Natural Gas
LoLo Lift on-Lift off
LPG Liquefied Petroleum Gas
LRS Lower Respiratory Symptoms
LSI Lake Superior and Ishpeming (Railroad)
m3 Cubic Meters
MARAD U.S. Maritime Administration
IV
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MARPOL The International Convention for the Prevention of Pollution of Ships
MCIP Meteorology-Chemistry Interface Processor
MDO Marine Diesel Oil
MGO Marine Gas Oil
MI Myocardial Infarction (in Chapter 5)
mm Millimeter
Mm"1 Inverse Megameter
MOBILE6 Vehicle Emission Modeling Software
MRAD Minor Restricted Activity Days
MSD Medium Speed Diesel (engine)
MW Megawatt
MWh Megawatt Hours
N Nitrogen
N/A Not Applicable
NAAQS National Ambient Air Quality Standards
NAICS North American Industry Classification System
NASA National Aeronautics and Space Administration
NATA National Air Toxic Assessment
NCAR National Center for Atmospheric Research
NCLAN National Crop Loss Assessment Network
NEI National Emissions Inventory
NH3 Ammonia
NIOSH National Institute of Occupational Safety and Health
nm Nautical Mile
NMHC Nonmethane Hydrocarbons
NMIM National Mobile Inventory Model (EPA software tool)
NMMAPS National Morbidity, Mortality, and Air Pollution Study
NO Nitric Oxide
NO2 Nitrogen Dioxide
NOAA National Oceanic and Atmospheric Administration
NONRO AD EP A's Non-road Engine Emission Model
NONROAD2005 EPA's Non-road Engine Emission Model Released in 2005
NOX Oxides of Nitrogen
NP North Pacific Region
NRC National Research Council
NRT Net Registered Tonnage
O/D Origin/Destination
O3 Ozone
OAQPS Office of Air Quality Planning and Standards
OC Organic Carbon
OEHH A Office of Environmental Health Hazard Assessment
OEM Original Equipment Manufacturer
OGV Ocean-Going Vessel
PM Paniculate Matter
PM AQCD EPA Paniculate Matter Air Quality Criteria Document
PM10 Coarse Paniculate Matter (diameter of 10 um or less)
PM2 5 Fine Paniculate Matter (diameter of 2.5 um or less)
PM NAAQS Paniculate Matter National Ambient Air Quality Standards
POM Polycyclic Organic Matter
ppb Parts per Billion
ppm Parts per Million
R&D Research and Development
RfC Reference Concentration
RIA Regulatory Impact Analysis
RM Residual Marine
RMA-10 Residual Marine fuel formerly DMC
v
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rpm Revolutions per Minute
RoPax Roll on-Roll off passenger
RoRo Roll on-Roll off
RSZ Reduced Speed Zone
S Sulfur
SAB Science Advisory Board
SAB-HES Science Advisory Board - Health Effects Subcommittee
SCR Selective Catalyst Reduction
SFC Specific Fuel Consumption
SI Spark Ignition
SLS St. Lawrence Seaway
SMAT Speciated Modeled Attainment Test
SO2 Sulfur Dioxide
SOX Oxides of Sulfur
SOA Secondary Organic Carbon Aerosols
SP South Pacific Region
SSD Slow Speed Diesel (engine)
ST Steam Turbine
STEEM Waterway Network Ship Traffic, Energy and Environment Model
TSD Technical Support Document
ULSD Ultra Low Sulfur Diesel fuel
URS Upper Respiratory Symptoms
USAGE United States Army Corps of Engineers
USDA United States Department of Agriculture
VLCC Very Large Crude Carrier
VLGC Very Large Gas Carrier
VOC Volatile Organic Compound
VOS Voluntary Observing Ships
VSL Value of Statistical Life
WTP Willingness-to-Pay
VI
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Executive Summary
Executive Summary
This report is an analysis of the economic impacts of EPA's Category 3 marine rule on
Great Lakes shipping. Category 3 marine engines are diesel engines with per cylinder
displacement at or above 30 liters. These engines are used for propulsion power on large vessels,
including many Great Lakes cargo vessels, and they emit high levels of pollutants that contribute
to unhealthy air in many areas of the United States.
EPA's final Category 3 marine rule is part of a Coordinated Strategy to reduce emissions
from all Category 3 marine engines that operate in the United States, including those that operate
on the U.S. portions of the Great Lakes and St. Lawrence Seaway (75 FR 22896, April 30,
2010).A The Coordinated Strategy consists of new national and international requirements that
will significantly reduce emissions of particulate matter (PM), sulfur oxides (SOx) and nitrogen
oxides (NOx) from Category 3 marine engines and their fuels. The long-term NOx limits for
new Category 3 engines will require the use of high-efficiency advanced aftertreatment
technology similar to that already required to be used on diesel trucks, locomotives, and smaller
marine engines that are operated in the United States. The long-term fuel sulfur limits are the
international limits that apply in specially designated Emission Control Areas (EGAs), including
the recently-designated North American EGA, and will dramatically reduce PM and SOx
emissions from Category 3 marine engines.
We received many comments from Great Lakes stakeholders about the Coordinated
Strategy during our Category 3 rulemaking process, particularly about the fuel sulfur
requirements. These commenters said that applying stringent EGA fuel sulfur requirements to
Great Lakes Category 3 ships would increase ship fuel costs and could ultimately lead to a
transportation mode shift in the Great Lakes region away from ships and toward less efficient
ground transportation which, in turn, could increase emissions overall. Some commenters also
indicated that increased marine fuel costs could affect the Great Lakes market for crushed stone,
by causing users to change their source of stone from quarries in the upper Great Lakes to
quarries located closer to their facility that would not require marine transportation. In addition,
commenters argued that increased marine fuel costs could lead electricity and steel producers to
shift production out of the Great Lakes region.
We included several compliance flexibility provisions in the final Category 3 marine rule
to address these concerns of Great Lakes stakeholders. In addition, we performed supplemental
analysis to estimate the inventory and cost impacts of applying the EGA fuel sulfur requirements
to the Great Lakes. Finally, we indicated that we would perform an analysis of the economic
impacts of the final rule on Great Lakes shipping. This report contains that analysis.
Great Lakes stakeholder input was essential in the development of this study, and the
industry provided vital assistance with respect to the choice of scenarios studied, the
methodology used, and important data inputs. A key stakeholder contribution was the
identification of Great Lakes shipping routes that industry members believe are at risk of
transportation mode shift as a result of increased costs of EGA fuel. A number of different trade
A For the purpose of this study, "Great Lakes" refers to the five Great Lakes and the St. Lawrence Seaway.
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Executive Summary
routes were submitted by various individuals and companies for EPA's consideration, from
which, with help from the stakeholders, we developed O/D pairs that characterize the 16
scenarios that form the basis of this analysis.6 Great Lakes Stakeholders also provided advice as
we developed our methodology to assess transportation mode shift, and commented on the data
/-i
we used to carry out the analysis.
Consistent with stakeholder comments, this economic impact analysis examines three
potential effects of increased fuel costs associated with the use of reduced sulfur EGA fuel by
Great Lakes shipping: 1) transportation mode shift, 2) source shift, and 3) production shift.
For each of the sixteen at-risk O/D pairs (four each of coal, iron ore, grain, and crushed
stone), the optimal transportation route that contains a marine link was identified, and the
incremental change in fuel costs associated with using EGA-compliant fuel for that route was
estimated.
Transportation mode shift is evaluated for the twelve coal, iron ore, and grain routes by
comparing the EGA-adjusted freight rates for the marine-based routes to freight rates for the next
cheapest means of shipping, the all-rail alternative. This analysis, contained in Chapter 2, shows
that compliance with the EGA fuel sulfur limits is unlikely to lead to transportation mode shift on
these at-risk routes. For ten of the twelve scenarios examined, EGA-adjusted marine freight rates
are expected to remain well below the next least expensive shipping mode, all-rail. For one of
the two remaining scenarios, an All-Rail Alternative route could not be identified, although the
results for a similar case suggest that no transportation mode shift would be indicated. For the
other scenario, the results of the analysis are inconclusive due to mis-specification of the
scenario.
Source shift is evaluated for the four crushed stone routes by examining certain features
of the crushed stone markets for each of the relevant using facilities. This analysis, contained in
Chapter 3, shows that the estimated increase in marine fuel costs is not expected to change the
competitive dynamics of these markets and therefore no source shift is expected.
Finally, production shift is evaluated for electricity and steel markets using a retail
revenue approach. This analysis, also contained in Chapter 3, shows that the estimated increase
in marine fuel costs for transporting coal and iron ore is not expected to shift electrical and steel
production out of the Great Lakes region both because these cost increases are small in
comparison to sector revenues and because the magnitude of the cost increases is well within the
bounds of historic electricity and steel price fluctuations. Chapter 3 also contains a more detail
analysis for steel destined for use in the Detroit, Michigan area.
The analyses contained in Chapters 2 and 3 of this report were peer reviewed pursuant to
EPA's Science Policy Council Peer Review Handbook, 3rd edition (Peer Review Handbook).
The peer review is described in Chapter 8.
B "Origin/destination (O/D) pairs" refers to specific starting and ending points of shipping routes on the Great Lakes.
Section 2.4 describes the selection of the O/D pairs and shipping routes.
c The selection of the 16 routes is briefly described below and in more detail in Chapter 2 of this report. Twelve of
the 16 O/D pairs were identified by stakeholders as being at risk for transportation mode shift. The other four O/D
pairs, for the transportation of crushed stone, were identified as being at risk of source shift to local quarries.
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Executive Summary
The remainder of this Executive Summary provides additional background and a brief
overview of the findings of this study.
The Arthur M. Anderson heads into Port Huron in the early morning fog. Source: Photo taken
by Barant Downs, August 16, 2007.
The Great Lakes and Category 3 Ships
The Great Lakes are an important part of our transportation system, for the region and for
the nation. Today, as illustrated in Figure ES-1, Great Lakes ships, called Lakers, carry bulk raw
materials such as iron ore, coal, grain, and crushed stone from one end of the lakes, where they
are mined or grown, to the other, where they are used in local manufacturing, shipped farther
inland, or shipped to the rest of the world. For the future, the Great Lakes are one of eighteen
marine highway corridors included in the United States Maritime Administration's America's
Marine Highway Program. The goal of this program is "to offer relief to landside corridors that
suffer from traffic congestion, excessive air emissions, or other environmental concerns and
other challenges" particularly through the transport of containerized goods and highway truck
trailers on lift-on/lift-off (LoLo) or roll-on/roll-off (RoRo) vessels. Shifting to marine
transportation is expected to ease rail and highway congestion and reduce energy consumption.
Great Lakes cargo vessels can be as large as or larger than ocean-going vessels,
measuring up to 1,000 ft in length. Similar to ocean-going vessels, many Lakers have Category
3 marine diesel engines (per cylinder displacement at or above 30 liters). Unlike smaller
Category 1 and Category 2 marine engines, these slow speed/high power Category 3 engines use
emission control technology that is comparable to that used by nonroad engines in the early
1990s. In addition, they typically use fuel that is the residue of the refining process. This
residual fuel, also called heavy fuel oil (HFO), has a sulfur content that is significantly higher
than the 15 ppm limit that applies to distillate diesel fuel used in smaller marine engines,
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Executive Summary
highway trucks, nonroad equipment, and locomotives operated in the United States. D According
to the International Maritime Organization, the current global average sulfur content of HFO is
about 23,500 ppm.
As a result, ships with Category 3 engines, including those that operate on the Great
Lakes, emit high levels of pollutants that contribute to unhealthy air in many areas of the
country. Nationally, in 2009, emissions from Category 3 marine engines accounted for about 10
percent of mobile source emissions of nitrogen oxides (NOx), about 24 percent of mobile source
diesel PM2.5 emissions (with PM2.5 referring to particles with a nominal mean aerodynamic
diameter less than or equal to 2.5 jim), and about 80 percent of mobile source emissions of sulfur
oxides (SOx).
Figure ES--1 Great Lakes Docks, Waterways and Railroads
i r
Source: Department of Geography and Planning: Center for Geographic Information Sciences and
Applied Geographies (GISAG), 2007
More than 27 million people live in the U.S. portions of the Great Lakes basin and are
affected by emissions from ships operating on the five lakes, including Category 3 vessels. The
impacted population is even larger considering people living on the Canadian side of the lakes
and along the St. Lawrence Seaway. Several areas, including Chicago, Detroit, Cleveland, and
Buffalo, which each have commercial ports, do not achieve National Ambient Air Quality
Standards for particulate matter, ozone, or both. Ships with Category 3 engines that use heavy
fuel oil contribute to nonattainment in these and other areas on the Great Lakes.
The Coordinated Strategy advanced by the Category 3 marine rule, described below and
in Chapter 1, will significantly reduce NOx, PM and SOx emissions from these engines. We
D EPA's 15 ppm fuel sulfur limit began to apply to land-based nonroad, locomotive, and marine distillate fuel
produced or sold in the United States in 2010 and it will be fully phased-in for these sources by 2014.
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Executive Summary
project that by 2030 this Coordinated Strategy will reduce annual emissions of NOx, sulfur
oxides (SOx), and particulate matter (PM) by 1.2 million, 1.3 million, and 143,000 tons,
respectively, and the magnitude of these reductions would continue to grow well beyond 2030.
These nationwide reductions are estimated to annually prevent between 12,000 and 30,000 PM-
related premature deaths, between 210 and 920 ozone-related premature deaths, 1,400,000 work
days lost, and 9,600,000 minor restricted-activity days. The estimated annual monetized health
benefits of the Coordinated Strategy in 2030 would be between $110 and $270 billion, while the
annual cost of the overall program in 2030 would be significantly less, at approximately $3.1
billion.E
EPA's Coordinated Strategy for Category 3 Engines and Fuels
EPA's Coordinated Strategy addresses emissions from all Category 3 marine engines that
operate in the United States, including those that operate on the U.S. portions of the Great Lakes
and St. Lawrence Seaway (75 FR 22896, April 30, 2010). The combination of this Coordinated
Strategy and EPA's previously adopted standards for smaller marine diesel engines amount to a
comprehensive program to reduce emission from all marine sources.F The overall program is
consistent with the technology forcing goals EPA has applied in all of our other mobile source
regulatory programs and will result in significant human health and welfare benefits.
The Coordinated Strategy for Category 3 engines consists of three parts:
(i) national engine emission standards for Category 3 engines installed on U.S. vessels
and national sulfur limits for fuel produced or sold in the United States, adopted under the
Clean Air Act;
(ii) international engine standards for all marine diesel engines above 130 kW and
international fuel sulfur limits that apply worldwide, contained in the 2008 amendments
to the International Convention for the Prevention of Pollution from Ships, called
MARPOL Annex VI and implemented in the United States through the Act to Prevent
Pollution from Ships (APPS); and
(iii) additional more stringent engine standards and fuel sulfur limits that apply to ships
operating in specially designated emission control areas (EGAs), including the North
American and U.S. Caribbean Sea EGAs, designated by amendment to MARPOL Annex
VI and implemented in the United States through APPS.G'H
E In this report, estimates of monetized benefits and engineering compliance costs are presented in 2006$, consistent
with the Category 3 marine rule analyses.
F New Category 2 and smaller diesel propulsion engines (per cylinder displacement up to 30 liters) installed on U.S.
vessels, including those operating on the Great Lakes, are required to meet stringent national emission limits to
reduce oxides of nitrogen (NOX) and particulate matter (PM) emissions (see 40 CFR 94 and 1043). Our national
fuel program limits the sulfur content of distillate marine diesel fuel produced or sold in the United States to 500
ppm, with an even cleaner 15 ppm sulfur standard phasing in by mid-2014 (see 40 CFR part 84).
G The North American EGA was approved by IMO in July 2009; the amendment to MARPOL Annex VI
designating this EGA was adopted in March 2010. The 10,000 ppm fuel sulfur limit will begin to apply in August
2012; this is reduced to 1,000 ppm beginning January 1, 2015.
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Executive Summary
The engine and fuel requirements of the Coordinated Strategy are applicable to U.S. ships
through EPA's Clean Air Act regulations (contained in 40 CFR 1042), and to all ships while they
are operating in U.S. internal waters and the U.S. portions of the North American EGA,
including the U.S. portions of the Great Lakes and St. Lawrence Seaway, through MARPOL
Annex VI and associated regulations adopted through EPA's authority set out in the Act to
Prevent Pollution from Ships (contained in 40 CFR 1043).u
The designation of the North American EGA through amendment to MARPOL Annex
VI, and its domestic application under the Act to Prevent Pollution from Ships, is an important
part of the Coordinated Strategy. EGA designation ensures that all ships operating within 200
nautical miles from the U.S. coastal baseline (except where limited by the Exclusive Economic
Zones of other countries) use lower sulfur fuel. Beginning August 1, 2012,K the sulfur content of
fuel used onboard vessels operating in the North American EGA cannot exceed 10,000 ppm.
Beginning January 1, 2015, the fuel sulfur limit is reduced to 1,000 ppm. In addition, new
vessels constructed beginning in 2016 will be required to meet stringent NOx emission standards
while they are operating within the EGA region.
The regulatory text included in our Category 3 marine rule made clear that a vessel
operating in U.S. internal waters shoreward of a designated EGA that can be accessed by ocean-
going vessels must meet the Annex VI EGA requirements^ In addition to U.S. coastal ports and
U.S. rivers that are navigable from the EGA (such as the Mississippi River, the Puget Sound, the
Chesapeake Bay), this includes those portions of the Great Lakes and St. Lawrence Seaway in
which the North American EGA is enforceable by the United States.
Great Lakes Provisions in the Final Category 3 Marine Rule
We received many comments from Great Lakes stakeholders during our Category 3
rulemaking process, particularly with respect to the application of the stringent EGA fuel sulfur
limits to Category 3 ships operating on the Great Lakes. Great Lakes shipping industry
stakeholders told EPA that the requirement to use fuel with a sulfur content at or below 1,000
ppm would increase their operating costs and would ultimately lead to a transportation mode
shift in the Great Lakes region away from ships and toward trucks or rail. Such a shift to less
efficient ground transportation, in turn, could increase emissions overall. Some commenters also
indicated that increased operating costs could affect the market for crushed stone, leading users
to change their source of stone from quarries located in the upper Great Lakes to local quarries.
H The U.S. Caribbean Sea ECA was approved by IMO in July 2010; the amendment to MARPOL Annex VI
designating this ECA was adopted in July 2011. The 10,000 ppm fuel sulfur limit will begin to apply in January
2014; this is reduced to 1,000 ppm beginning January 1, 2015.
1 For a full description of the North American ECA, see Section 1.4.3.1 of Chapter 1.
1 Canada is currently developing their program for ships operating on the Canadian portions of the Great Lakes and
the St. Lawrence Seaway.
K Pursuant to Regulation 14.7 of MARPOL Annex VI, "During the first twelve months immediately following an
amendment designating a specific emission control area ... ships operating in that emission control area are exempt
[from the fuel sulfur requirements]." Therefore, while the amendment to Annex VI with respect to the North
American ECA goes into force in August 2011, the fuel requirements are applicable beginning in August 2012.
L In the regulatory text, an internal waterway in which the ECA requirements apply is called an "ECA associated
area."
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Executive Summary
In addition, commenters argued that increased marine fuel costs could lead electricity and steel
producers to shift production out of the Great Lakes region.
To address these stakeholder concerns, and consistent with Congressional
recommendation, we included three Great Lakes-specific provisions in our final Category 3
marine rule. Each of these provisions is available to any ship operating on the U.S. portions of
the Great Lakes, including foreign vessels.
(i) We adopted a steamship exemption: Great Lakes steamships are excluded from the
EGA fuel standards. This provision avoids immediate retirement of steamships, which
may not be able to operate safely on distillate diesel fuel. However, we expect these
vessels will be retired eventually because of their higher fuel usage when compared to
diesel engines (a steam engine can consume up to twice as much fuel as modern diesel
engines).
(ii) We included an economic hardship provision: a Great Lakes ship owner may
petition EPA for a temporary exemption from the long-term (2015) EGA fuel sulfur
requirement. The owner must show that despite taking all reasonable business, technical,
and economic steps to comply with the fuel sulfur requirements, the burden of
compliance costs would create a serious economic hardship for the company. The
Agency will evaluate each application on a case-by-case basis.
(iii) We adopted a fuel availability waiver: a Great Lakes ship may use fuel that exceeds
the 10,000 ppm interim EGA fuel sulfur limit until January 2015 on the condition that the
ship operator purchases fuel with the lowest sulfur content available. This provision
addresses the concern that fuel meeting the interim 10,000 ppm standard may not be
available on the Great Lakes due to the nature of this marine fuel market. There are some
reporting requirements for owners exercising this fuel waiver.
We also performed additional analyses of the inventory and air quality impacts of the
Coordinated Strategy for the Great Lakes region specifically, and estimate the cost of applying
the EGA requirement to Lakers.
Finally, to address concerns that the application of the EGA fuel requirements on the
Great Lakes would result in transportation mode shift, source shift, and/or production shift, we
indicated we would perform a comprehensive study to analyze the potential for these impacts.
This report contains that study.
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Executive Summary
The James R. Barker heading downbound at Mission Point in Sault Ste. Marie, MI - 2008. Source:
Photograph taken by and used with permission from Dick Lund, accessed here:
http://www.dlund.20m. com/images_2008/SOO062908an.JPG.
Scope of this Economic Impact Analysis
This study looks at the impacts of applying the long-term 1,000 ppm EGA fuel sulfur
limit to Great Lakes shipping. The study examines the impacts on only Category 3 ships since
ships powered by Category 2 and smaller engines typically use distillate diesel fuel that is
subject to more stringent fuel sulfur limits (currently 500 ppm in the United States, reduced to 15
ppm by 2014).
The analysis assumes uniform application of the EGA fuel sulfur requirements across the
entire marine Great Lakes/St. Lawrence Seaway system. It should be noted that the Canadian
program to implement the EGA standards is still under development. As a result, this analysis is
conservative in that it applies the more expensive EGA fuel to the entire marine segment.
This study focuses on the long-term EGA fuel requirements, the 1,000 ppm sulfur limit
applicable in 2015. This standard represents by far the most costly part of the fuel sulfur control
program as it is expected to require switching to higher price distillate diesel fuel or the use of an
exhaust gas cleaning system (scrubber). In contrast, the interim 10,000 ppm sulfur limit, which
will apply when the North American EGA goes into effect in August 2012, is expected to be
achievable through the use of lower price reduced sulfur residual fuel and will therefore have a
much smaller impact on operating costs.
This analysis does not consider the impacts of the Coordinated Strategy's engine
requirements. The Tier III standards, which apply to engines installed on ships constructed
beginning in 2016 while they are operating in an EGA, is not included because new ships are
built only rarely for the Great Lakes fleet and therefore it is difficult to anticipate how many, if
any, vessels would be affected in any given year. The Tier II NOx standards, which apply at all
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Executive Summary
times to engines installed on ships constructed beginning in 2011, and the NOx requirements for
existing enginesM are also not included in this analysis because they apply to ships whether or
not they are operated in a designated EGA. Finally, while we present the cost of retrofitting
existing vessels with new engines in our Chapter 6 cost analysis, we do not include the impacts
of engine retrofitting in our economic analysis because there is no requirement to retrofit an
existing vessel with a cleaner, newer engine.
Results of this Economic Impact Study
A detailed description of how the O/D pairs that characterize the sixteen scenarios that
make up this analysis were chosen as well as the results of the transport mode shift, source shift,
and production shift analyses is contained in Chapters 2 and 3 of this report.
Once the sixteen O/D pairs were selected, the optimal transportation route that contains a
marine link was identified for each. These routes were developed by ICF International and its
subcontractor, Energy and Environmental Research Associates (EERA), using the Geospatial
Intermodal Freight Transport (GIFT) model that EERA developed with funding from the United
States Maritime Administration (MARAD). This optimal transportation route is intended to
maximize the use of the Great Lakes across the overall route.
ICF and EERA also estimated a route-based freight rate for each scenario that
incorporates the combined marine and rail segments. This is called the Base Case freight rate.
Then, the incremental change in fuel costs associated with using EGA-compliant fuel was
estimated using an activity-based fuel consumption and cost model that accounts for vessel
operation "at sea" and "in port." This information is used to estimate a revised freight rate for the
route, called the EGA Case freight rate. These freight rates are reported in Table ES-1.
Transportation Mode Shift
The transportation mode shift analysis was carried out on the coal, iron ore, and grain
scenarios. N For this analysis, ICF and EERA developed an all-rail alternative route for each of
the twelve scenarios. While eleven of the twelve O/D pairs can be linked by rail, it was
discovered that the mine and using facility in Scenario 6 cannot: the originating mine has no
access to a national rail line or highway. ICF and EERA estimated an all-rail freight rate for the
remaining eleven scenarios, called the All-Rail Alternative Route freight rate. The EGA Case
freight rate was then compared to the All-Rail Alternative Route freight rate for that scenario to
determine which route has the higher freight rate. If the freight rate for the EGA Case is less
than that of the All-Rail Alternative Route, then no transportation mode shift to rail is indicated
for these at-risk routes.
M The MARPOL Annex VI standards for existing engine apply to marine diesel engines with a power output of
more than 5,000 kW and per cylinder displacement at or above 90 liters installed on a ship constructed on or after 1
January 1990 but prior to 1 January 2000 (Regulation 13.7.1). Note that this requirement depends on the availability
of a certified approved method (i.e., remanufacture system).
N The four crushed stone routes are analyzed separately, as stakeholders indicated that increased marine fuel costs
would lead to source shift (customers would shift their source of crushed stone from quarries located in northern
Michigan, transported in part by ship, to local quarries, transported by truck).
-------
Executive Summary
As shown in Table ES-1, the EGA Case freight rate for the marine transportation mode is
expected to remain well below the next cheapest shipping mode - rail - for ten of the twelve
transportation mode shift scenarios examined, and therefore no transportation mode shift is
indicated. The results for Scenarios 2 and 6 are discussed below.
Table ES-1 Overview of Scenario Resultsa'b
Scenario
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Coal from Montana to
Wisconsin
Coal from Colorado to
Wisconsin
Coal from Montana to
southern Michigan
Coal from Montana to
northern Michigan
Iron Ore from Michigan to
Ontario
Iron Ore from Quebec to
Indiana
Iron Ore from Minnesota to
Indiana
Iron Ore from Minnesota to
Ohio
Grain from Illinois to
Quebec
Grain from Minnesota to
Quebec
Grain from Minnesota to
New York
Grain from Ontario to Ohio
Stone from Michigan to
Ohio
Stone from Michigan to
Ohio
Stone from Michigan to
Minnesota
Stone from Michigan to
Pennsylvania
Base Case Total
Freight Rate
$19.99
C
$21.19
$25.28
$4.12
$16.10
$6.21
$6.83
$22.00
$19.78
$22.43
$9.12
$10.89
$8.91
$12.04
$6.51
ECA Case
Total Freight
Rate
$20.23
C
$22.00
$26.41
$4.47
$18.77
$7.14
$7.73
$24.11
$21.82
$23.93
$9.95
$11.15
$9.14
$12.39
$6.82
Base to ECA
(% Diff)
1.2%
C
3.8%
4.5%
8.5%
16.6%
15.0%
13.2%
9.6%
10.3%
6.7%
9.1%
2.4%
2.6%
2.9%
4.8%
All-Rail
Total Freight
Rate
$21.71
C
$27.44
$28.12
$5.22
d
$11.99
$18.37
$46.75
$59.57
$36.62
$11.80
~
~
~
~
ECA to All-
Rail (%
Diff)
-7.3%
C
-24.7%
-6.5%
-16.8%
d
-67.9%
-137.6%
-93.9%
-173.0%
-53.0%
-18.6%
N/A
N/A
N/A
N/A
" Taken from Table 76 of contractor report, Appendix 2C.
* Modeled baseline freight rates using 2007 fuel prices adjusted for the Great Lakes market, reported in 2008$
c Results are inconclusive due to mis-specification of the scenario. See discussion in text.
d No all-rail alternative exists for this route; results for a partial-rail alternative case would resemble those of
Scenario 9. See discussion in text.
Scenario 2 consists of coal transported from the Elk Creek Mine in Colorado through
South Chicago to the Georgia Pacific paper mill in Green Bay, Wisconsin. The initial results for
this scenario, reported in Appendix C to this chapter, suggest that the route-based freight rate for
10
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Executive Summary
the All-Rail Alternative ($24.43) is less than both the Base Case and the EGA freight rates
($26.03 and $26.64, respectively). This contrary result led EPA to perform additional research
with regard to this facility. The information obtained by EPA indicates that, due to quality
specifications for the coal used by this facility, the western bituminous coal used in this paper
mill is blended with other coal to obtain the product needed. The blended coal is obtained from a
source in South Chicago, where the KCBX Terminal can store up to 1 million net tons of coal on
site and can blend up to three coals for a customer. Consequently, this case was mis-specified.
However, it is unclear whether the transportation costs for this case should be based solely on the
cost of transporting coal from the terminal in Chicago to the facility in Green Bay, or whether
some portion of the transportation cost from the mine head(s) should be included. This question
could be important because this facility also receives coal by ship from Sandusky and Ashtabula,
Ohio, and vessels operating from those facilities are also required to use ECA-compliant fuel.
For these reasons, and because freight rates for a revised scenario are not readily available, it is
not possible to determine the potential for transportation mode shift impacts for this route.
Scenario 6 consists of iron ore transported from Quebec Cartier Mining Co., in Quebec,
to ArcelorMittal, in Burns Harbor, Indiana. Transportation mode shift to rail is impractical for
this scenario because there is no access to a national highway or rail line at the mine in Quebec.
However, this scenario is similar to Scenario 9, which also involves transportation of cargo
(grain) the length of the St. Lawrence Seaway, and the All-Rail Alternative route for that
scenario can be used to estimate the likelihood of transportation mode shift for Scenario 6. As
indicated in Table ES-1, the All-Rail Alternative freight rate for Scenario 9 exceeds the EGA
Case freight rate and no transportation mode shift is indicated. The use of this rail alternative
would likely be even less favorable for Scenario 6 because it would require transportation by
ship to the rail port on the opposite shore of the Gulf of St. Lawrence, with associated cargo
transfers.
Source Shift
The source shift analysis was performed by EPA for the four crushed stone routes
identified by stakeholders as being at risk for source shift to local quarries. The analysis is based
on marine freight rates developed by ICF International and EERA using the same methodology
as in the transportation mode shift analysis described above. We followed the competitive radius
methodology used in the study included in the Canadian Shipowners' Association comments on
the Category 3 marine rule. This methodology examines how an increase in total marine
transportation costs increases the competitive radius around each using facility, potentially
increasing the number of local quarries that could service it and thus changing the competitive
dynamics of that market for crushed stone.
This analysis shows an increase in competitive radius of less than 10 miles for all
scenarios. This small increase in the competitive radius, four percent or less, would not be
expected to result in a change in the competitive structure of the local crushed stone markets for
these four at-risk routes. A geographic examination the increase in competitive radius indicates
that the number of quarries that could service each of the four facilities would not increase
significantly. Therefore, no source shift is indicated for these at-risk routes.
11
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Executive Summary
Production Shift
The production shift analysis was performed by EPA to examine whether higher ship
operating costs associated with the use of EGA-compliant fuel would lead manufacturers to
move the production of steel and electricity out of the Great Lakes region. Based on a retail
revenue analysis, we estimate that the increase in coal and iron ore transportation costs will
amount to less than 0.5 percent of electrical sector revenues and less than 0.1 percent of steel
sector revenues. This small increase in transportation costs is well within historic variations in
electricity and finished steel prices. As a result, the use of EGA-compliant fuel is not expected to
result in movement of production away from the Great Lakes region especially given relocation
costs and, in the steel case, the cost of importing finished steel produced outside the United
States and transporting it to steel users in the Great Lakes area.
Stakeholder Participation
EPA performed the analysis contained in this report in response to comments received
from Great Lakes stakeholders during our Category 3 rulemaking process. As a result, we
solicited industry stakeholder input during all phases of the analysis, especially with respect to
the routes studied, the methodology used, and key data inputs such as cargo types, vessel
characteristics, and cargo transfers. Appendix A to Chapter 2 contains more details about
stakeholder outreach, including a list of workshop attendees and an index of external
correspondence.
EPA engaged with various Great Lakes industry stakeholders throughout the
development of this analysis. Our first outreach with stakeholders was through a presentation to
industry members at Marine Community Day on February 11, 2010. At this conference, EPA
explained to stakeholders that we were developing a research strategy and evaluating existing
modeling tools and various ways to assess the economic impacts of our rule on Great Lakes
Shipping. The goal of the analysis, we noted, would be to see if a transportation cost increase of
the order we expected as a result of applying the EGA fuel requirements to the Great Lakes, in
combination with the dynamics of transportation in the Great Lakes region, would potentially
lead shippers to shift away from marine transportation to one of the land-based alternatives, rail
or truck. We also indicated we were developing ways to engage stakeholders to obtain input on
the methods we would be using and the data we would need to carry out the study.
During the spring of 2010, we evaluated existing models and methodologies that could be
used to perform this analysis. We also engaged a contractor who began to develop the analytic
tools and carry out test modeling for several example cargo/route combinations.
We hosted a workshop in Ann Arbor on June 10, 2010, to present our proposed
transportation mode shift methodology and to solicit data inputs from industry stakeholders.
Under contract with EPA through ICF, Dr. James Winebrake of the University of Rochester and
Dr. James Corbett of the University of Delaware described their Geospatial Intermodal Freight
Transport (GIFT) model and cost function approach. They also presented the results of applying
this methodology to two fairly typical transportation scenarios examining the cost impacts of the
EGA fuel program for two fairly typical transportation scenarios: coal shipped from Montana to
Monroe and St. Glair, Michigan, and iron ore shipped from Minnesota to Gary, Indiana. This
12
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Executive Summary
methodology was well received by the workshop participants. At the close of that workshop we
indicated that the next step in EPA's study would be to define the shipping routes that would be
included in the analysis, and we requested industry assistance identifying those Great Lakes
shipping routes most likely to be at risk for transportation mode shift due to competition from
landside alternatives.
At the request of attendees, EPA followed up on the Ann Arbor workshop with an e-mail,
dated June 16, 2010, that provided additional details about the methodology we intended to use
for the transportation mode shift analysis and contained a list of the data inputs that would be
needed. The e-mail was sent to workshop attendees as well as the two primary trade associations
for Great Lakes carriers: Lake Carriers' Association and the Canadian Shipowners' Association.
In that e-mail, EPA again requested stakeholder assistance in identifying sensitive routes that
might be at risk for transportation mode shift.
We again presented a summary of our analytic approach and results for the two initial
scenarios at the 74th International Joint Conferences of the Canadian Shipowners' Association
and Lake Carriers' Association in Niagara-on-the-Lake, Ontario, on June 21, 2010, and
requested additional stakeholder input.
Several stakeholders responded directly to EPA with confidential information about the
trade routes they believe might be at risk for transportation mode shift as a result of increased
fuel costs. Using this information, EPA prepared a list of 16 routes to be included in the
analysis. After obtaining agreement of those stakeholders who had shared their
recommendations, on July 12, 2010 we forwarded our draft list of at-risk routes to the primary
industry trade organizations for dissemination to their members and requested comments or
revisions. We received no adverse comment on this list of routes. The specific data needed to
perform the analysis for each route were then gathered by EPA's contractor. We forwarded draft
data sheets along with associated route maps to the trade associations on August 13, 2010, again
with a request that they forward the information to their members for review and comment. The
final data inputs used in this analysis are based on the comments we received on these data
sheets.
In addition, EPA exchanged e-mails and had telephone conversations with various
stakeholders with regard to their questions and concerns about the study.
In summary, stakeholder input was solicited during all phases of this project with regard
to the study methodology, the choice of at-risk routes to be analyzed, and the data used to
characterize these routes in the analysis. The assistance provided by stakeholders was highly
valuable and allowed us to focus this analysis on those routes identified by shipping interests as
being most likely to be adversely affected by the application of the EGA fuel requirements to the
Great Lakes.
Organization of this Report
Chapter 1 of this report contains additional information about the Coordinated Strategy
for Category 3 marine diesel engines and their fuels as well as additional background
information about our national marine emission control program for Category 1 and 2 marine
13
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Executive Summary
diesel engines. This chapter also contains a brief review of other studies of the environmental
and economic benefits of marine transportation on the Great Lakes.
Chapter 2 contains our analysis of transportation mode shift. This analysis was
performed by ICF International and its subcontractor, Energy and Environmental Research
Associates (EERA) under contract for EPA.
Chapter 3 contains our analysis of source and production shift, as well as an analysis of
the emission impacts of any possible shifts. These analyses were performed by EPA.
Chapters 4 and 5 contain an emission inventory and air quality analysis of ship emissions
on the Great Lakes. This analysis is derived from the national level analysis performed for our
Category 3 marine rule.
Chapter 6 contains information about the costs of complying with the Coordinated
Strategy requirements for Great Lakes shipping.
Chapter 7 contains a brief industry characterization of those ships on the Great Lakes that
will be subject to the Coordinated Strategy requirements.
Chapter 8 contains documentation of the peer review process, as well as responses to peer
reviewers' comments that are not addressed elsewhere in this report.
14
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
CHAPTER 1: The Great Lakes and EPA's Marine Emission
Control Program
The purpose of the analyses contained in this report is to examine the economic impacts
of EPA's Category 3 marine rule, particularly the fuel sulfur limits, on Great Lakes shipping.
Category 3 marine engines are diesel engines with per cylinder displacement at or above
30 liters that are used for propulsion power on large vessels, including many Great Lakes cargo
vessels. These high horsepower engines typically use heavy fuel oil (HFO, also called residual
fuel). The average sulfur content of this fuel is currently about 23,500 ppm,1 which is many
times higher than the 15 ppm sulfur limit that applies to fuel used in highway trucks, land-based
nonroad equipment, locomotives, and smaller marine diesel engines.A Category 3 engines also
use emission control technology that is comparable to that used by nonroad engines in the early
1990s.
This chapter provides background information with respect to Great Lakes shipping and
describes EPA's three-part Coordinated Strategy to reduce emissions from Category 3 marine
engines and their fuel. We also summarize the concerns of Great Lakes stakeholders with
respect to this Coordinated Strategy, particularly with respect to the application of the North
American Emission Control Area (North American EGA) fuel sulfur requirements to ships
operating on the Great Lakes.0 Finally, we provide a review of several recent studies of the
economic benefits of Great Lakes shipping, the impacts of fuel cost increases on Great Lakes
shipping, and the expected impacts of the Baltic Sea and North Sea EGA fuel sulfur limits on
European marine transportation.
1.1 The Great Lakes Transportation System
The Great Lakes and the St. Lawrence Seaway are an important part of our transportation
system, for the region and the nation. The system is ice-free about nine months of the year, and
during that time a variety of ships carry large quantities of bulk raw materials such as iron ore,
coal, grain, and crushed stone from one end of the lakes, where they are mined or grown, to the
other, where they are used in manufacturing, shipped farther inland, or shipped to the rest of the
world. These materials are important for the production of iron and steel, cement, and
electricity, as well as agricultural exports.
A EPA's 15 ppm fuel sulfur limit began to apply to land-based nonroad, locomotive, and marine distillate fuel
produced or sold in the United States in 2010; it will be fully phased-in for these sources by 2014.
B Chapter 7 describes the Great Lakes shipping sector in greater detail.
c For the purpose of this study, "Great Lakes" refers to the Great Lakes and St. Lawrence Seaway.
1-1
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
ป U '_- - -- \ -TWSWt
IIIHII %
The Maumee passes the Detroit Renaissance Center heading downbound on the Detroit River
in 2008. Source: Photo taken by and used with permission from Blake Kischler.
Historically, producers of steel, iron, cement, and electricity have chosen to locate their
facilities on the Great Lakes because these manufacturers require vast quantities of raw materials
such as coal, iron ore, and stone, and the Great Lakes provides a low-cost way to transport large
shipments of these materials from mines to using plants. The Great Lakes also offer a vast
reservoir of water that is needed for these production processes.2 Today nearly all of the
commodities shipped on the Great Lakes continue to be bulk goods, but there are renewed efforts
to promote the system for transportation of other types of cargo as well. The Great Lakes are
one of eighteen Marine Highway Corridors included in the United States Maritime
Administration's America's Marine Highway Program.3 The goal of this program is "to offer
relief to landside corridors that suffer from traffic congestion, excessive air emissions, or other
environmental concerns and other challenges," particularly through the transport of containerized
goods and highway truck trailers on LoLo vessels (lift-on/lift-off, for containers) or RoRo
vessels (roll-on/roll-off, for trailers). Shifting to marine transportation is expected to ease rail
and highway congestion and reduce energy consumption.D'E
D The Great Lakes are also important for recreational use and fishing. However, those activities are not considered
in this report as those vessels do not use Category 3 marine diesel engines.
E One peer reviewer noted skepticism "that the Great Lakes waterways would be an economically acceptable routing
for intermodal short-sea container shipping" both because ships purpose-built for transporting containers on the
Great Lakes would be small (200 containers) and because there are no container ports (Belzer). Another peer
reviewer explained that short-sea shipping is an important growth industry for the Great Lakes (Hull). See also the
U.S. Maritime Administration Study in sections 1.7.2 and 1.7.3, below.
1-2
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
The interconnectedness of Great Lakes shipping with the area's economy is illustrated in
Figure 1-1. According to Greenwoods Guide to Great Lakes Shipping 2007, there are aboutlSO
commercial ports and docks on the Great Lakes that can handle shipments of coal, iron ore, and
stone; still others handle grain and other bulk goods. These ports and docks range from very
large public commercial facilities like those in Duluth and Superior, Minnesota, to small private
docks that may service one plant. Actual cargo origins and destinations can be located well
inland of the Great Lakes and marine transportation is a link in an intermodal transportation
chain from producer to user. For example, coal can be transported by rail to from coal mines in
Montana to the port at Duluth, Minnesota, and then transported by ship to power plants on the St.
Clair River in Michigan. Similarly, stone can be transported by ship from mines on the shores of
Lake Michigan through Toledo, Ohio, and then by rail to the Ohio River Valley and then by river
barge for use in exhaust cleaning scrubbers at electric power plants located on the river.
Figure 1-1 Great Lakes Maritime Docks, Waterways and Railroads
Source: Department of Geography and Planning: Center for Geographic Information
Sciences and Applied Geographies (GISAG), 2007
The amount of cargo shipped on the Great Lakes is significant. The data in Table 1-1
show that the amount of cargo shipped annually on the five Great Lakes (excluding the St.
Lawrence River system downstream of Buffalo, NY) equals about half of the amount of cargo
shipped annually on the Mississippi River system.
1-3
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Table 1-1 Annual Shipments, Great Lakes and Mississippi River (million short tons)
Mississippi River Total
Great Lakes Dry Bulka'b
2000
327
177
2001
317
166
2002
316
164
2003
308
155
2004
313
170
2005
299
165
2006
314
170
2007
313
157
2008
295
157
Note:
" A majority of the cargo shipped on the Great Lakes is dry bulk (see Chapter 7)
Sources: http://www.lcaships.com/TONPAGE.HTM. http://www.shipowners.ca/index.php?page=annual-report-and-
statistics. http://www. seaway.ca/en/seawav/facts/traffic/index.html
Category 3 marine engines emit high levels of pollutants that contribute to unhealthy air
in many areas of the country. Nationally, in 2009, emissions from all Category 3 marine engines
accounted for about 10 percent of mobile source emissions of nitrogen oxides (NOx), about 24
percent of mobile source diesel PM2.5 emissions (with PM2.5 referring to particles with a nominal
mean aerodynamic diameter less than or equal to 2.5 jim), and about 80 percent of mobile source
emissions of sulfur oxides (SOx). Category 3 ships on the Great Lakes account for about three
percent of Category 3 activity in the United States, as measured by fuel consumption.
More than 27 million people living in the U.S. portions of the Great Lakes basin are
affected by ship emissions from the Great Lakes, including emissions from Category 3 vessels.4'17
The impacted population is even larger considering people living on the Canadian side of the
lakes and along the St. Lawrence Seaway. As shown in Figure 1-2, several areas, including
Chicago, Detroit, Cleveland, and Buffalo, which each have commercial ports, do not achieve
National Ambient Air Quality Standards for particulate matter, ozone, or both. Ships with
Category 3 engines that use HFO contribute to nonattainment in these and other areas on the
Great Lakes.
Interested readers should refer to Chapters 4 and 5 for a more complete description of the inventory contribution,
air quality impacts, and human health and welfare impacts of Category 3 ship emissions in the Great Lakes area.
1-4
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Figure 1-2 Great Lakes Nonattainment Areas (based on data through May 2007)
^Portland
Portsmouth
Boston
rabvidence
'Haven
York/NJ Ports
filadelphi a/Delaware
more
ntington -v Newport News
** .Norfolk Harboi
Ports Q
PM and Oione NonAllalnnwnl 5^^S
Ozone NoiiAttatament
PM2 5 NonAnainment 111 I'll |;||ll
Federal Class, I Areas (Visibility) ^^
Source: EPA
1.2 Marine Engines and Their Fuels
Marine diesel engines range in power from very small engines used to propel sailboats to
huge engines used to power ocean-going ships. To address emissions from such a wide variety
of engines, we created regulatory categories based on size, as measured by displacement in liters
per cylinder (1/cyl). The commercial marine diesel engine categories are set out in Table 1-2.G
For the purposes of this report, Category 3 vessels are vessels with Category 3 main
propulsion engines. Similarly, Category 2 vessels have Category 2 main propulsion engines and
steamships have steam propulsion engines.
Table 1-2 also sets out the types of fuel used by the different categories of marine diesel
engines. Fuel type is important because the sulfur content of the fuel used in an engine has a
direct impact on the engine's particulate emissions, with higher sulfur fuel associated with higher
PM emissions. Marine diesel fuels are either distillate or residual fuels. There are two main
types of distillate marine fuels: marine gas oil (MGO, also known as distillate marine grade A or
DMA), and marine diesel oil (MDO, also known as distillate marine grade B or DMB). These
distillate fuels are similar to distillate diesel fuel used in land-based diesel engines. The current
global average sulfur content of these marine distillate fuels is about 3,900 ppm, which is
comparable to the historic limit for nonroad diesel fuel that was used in the United States in the
early 1990s.5 EPA's fuel program currently limits the sulfur content of marine distillate fuel sold
in the United States to 500 ppm, with a 15 ppm limit phasing in by 2014.
EPA also has standards for recreational marine diesel engines and for gasoline (spark-ignition) marine engines.
These engines are not the subject of this report and therefore their standards are not included in this section.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Residual fuel, also called heavy fuel oil (HFO) is relatively dense ('heavy') and is created
as a refining by-product from typical petroleum distillation (hence the name "residual").
Residual fuels typically are composed of heavy, residuum hydrocarbons and can contain various
contaminants such as heavy metals, water and sulfur compounds. Ships using this fuel must be
equipped with specialized fuel handling equipment such as centrifuges, heaters, and unique
storage tanks. As a result, this fuel is used primarily in larger vessels with Category 3 or steam
propulsion engines. The sulfur content of residual fuel can be as high as 45,000 ppm; however,
the global average is about 23,500 ppm.6 Category 2 and smaller marine diesel engines typically
use distillate fuels, although they can be modified to use HFO when they are used for auxiliary
power on Category 3 vessels or steamships. Auxiliary boilers can be modified to use either
distillate fuel or HFO.
Table 1-2 Types of Commercial Marine Diesel Engines, Their Uses and Fuels Described in EPA Marine
Diesel Engine Rules
ENGINE TYPE
Small marine
diesel engine
Category 1
Category 2
Category 3
Steam Boilers
ENGINE SIZE
Less than 37 kW
Above 37 kW; Per cylinder
displacement less than 5
or 7 liters, depending on
model year
Per cylinder displacement 5
or 7 liters, depending on
model year, to 30 liters
Per cylinder displacement at
or above 30 liters
Up to 50 mW or higher
USE
Propulsion or
Auxiliary on any ship
Propulsion or
Auxiliary on any ship
Propulsion or
Auxiliary on larger ships
Propulsion only
Propulsion or
Auxiliary on larger ships
FUEL
Marine Gas Oil (MGO or DMA)
Marine Diesel Oil (MDO or
DMB)
MGO or MDO
MGO or MDO
Can use Heavy Fuel Oil (HFO) in
some cases
HFO, MGO, MDO
HFO, MGO, MDO
The Great Lakes cargo fleet is different from the cargo fleets that operate in U.S. coastal
ports or on our inland river system. The vast majority of cargo ships that enter our coastal ports
are foreign ocean-going vessels propelled by Category 3 marine engines, while nearly all the
cargo ships on our inland river system are U.S. tug-barge combinations propelled by Category 2
or smaller marine engines. In contrast, the cargo statistics reported in Table 1-3 show that about
two-thirds of the cargo moved on the Great Lakes is carried by U.S. ships, with most of the
remainder carried by Canadian ships. The fleet statistics reported in Table 1-4 show that Great
Lakes ships are propelled by both Category 2 and Category 3 engines.
Table 1-3 Great Lakes Cargo, by Flag, All Ships, 2004-9 (million short tons; all vessel sizes)
Total
U.S.3
Canadian b
Foreign ฐ
2004
170.0
111.3
44.8
13.9
2005
165.4
107.7
42.2
15.5
2006
169.5
109.7
40.4
19.4
2007
157.1
104.0
37.0
16.0
2008
157.1
101.0
38.2
18.0
2009
111.2
66.5
28.7
16.0
Notes:
ahttp://www.lcaships.com/TONPAGE.HTM
ihttp://www.shipowners.ca/index.php?page=annual-report-and-statistics
c http://www.seawav.ca/en/seawav/facts/traffic/index. html
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
The U.S. and Canadian fleets of Category 3 vessels are also different from each other.
Table 1-4 shows that while the Canadian fleet has more Category 3 vessels, the U.S. fleet is
larger with respect to vessel cargo capacity. The average cargo capacity of a U.S. Category 3
iron ore carrier is 59,400 gross tons, compared to 29,700 gross tons for a similar Canadian ship.
The average cargo capacity of a U.S Category 3 coal ship is 47,900 net tons, compared to 27,700
net tons for a similar Canadian ship. Due to their size, many U.S. ships operate only on the
Great Lakes since they are too large to enter the St. Lawrence Seaway due to canal restrictions
(these are called "captive" vessels since they cannot exit the Great Lakes). More information on
the U.S. and Canadian Great Lakes fleets can be found in Chapter 7.
Table 1-4 Distribution of U.S. and Canadian Vessels on the Great Lakes, by Engine Type and Flag (gross
tons)
U.S. Fleet
Canadian Fleet
C3 Vessels
Number of vessels
Total fleet tonnage
Average vessel tonnage
12
295,000
24,600
68
1,054,000
15,500
C2 Vessels
Number of vessels
Total fleet tonnage
Average vessel tonnage
32
402,000
12,600
20
197,000
9,850
Steamships3
Number of vessels
Total fleet tonnage
Average vessel tonnage
13
150,000
11,500
8
116,000
14,500
Note:
" The number of steamships includes both twelve diesel-powered steamships and one coal-fired steamship
currently operating as a car-ferry.
Source: Greenwoods Guide to Great Lakes Shipping 2010. Harbor House Publishing (2010)
1.3 Emission Control Program for Category 2 and Smaller
Marine Diesel Engines, and their Fuels
While EPA's Category 2 marine engine program is not the subject of this analysis, a
description of the emission control program for these engines and fuels is included for
completeness.
The vast majority of vessels with Category 2 or smaller marine propulsion engines
(engines up to 30 liters per cylinder) that operate in U.S. ports and waters, including the inland
waterway system, are flagged in the United States. These vessels include river tugs and
pushboats, port tug and assist vessels, ferries, fishing vessels, offshore supply ships, and some
small cargo vessels. They typically operate on distillate fuel and only rarely use residual fuel.
EPA's program for new Category 2 and smaller marine engines installed on U.S. vessels
consists of several tiers of emission limits adopted under the Clean Air Act (see 40 CFR 94 and
1042). The most recent standards were adopted in 2008 (73 FR 25098, May 6, 2008). These
standards include emission limits for PM and oxides of nitrogen (NOx) that are projected to
require the use of high efficiency advanced aftertreatment technologies similar to that which will
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
be used on new trucks and locomotives. When fully phased in, these standards are expected to
reduce PM emissions by about 90 percent and NOx emissions by about 80 percent, compared to
the current Tier 2 marine standards.7 In 2030 this rule, which also includes standards for
locomotives, is projected to annually prevent up to 1,100 PM-related premature deaths, 120,000
lost work days, and 1.1 million minor restricted activity days. The estimated monetized health
benefits of the rule are estimated to be about $11 billion, compared to estimated costs of about
$74 million.
EPA's Clean Air Act requirements for marine distillate fuel were adopted in our Clean
Air Nonroad Diesel Rule (69 FR 38958, June 29, 2004; see 40 CFR part 84). These standards
limit the sulfur content of marine distillate diesel fuel produced and sold in the United States to
500 ppm beginning in 2007, and an even cleaner 15 ppm standard will be completely phased-in
by mid-2014.H'8 While we did not estimate separate benefits and costs for the marine fuel
requirements, the overall benefits of the rule are estimated to be $80 billion compared to
estimated costs of about $1.7 billion.
Finally, it is worth noting that the fleet of Category 2 cargo vessels that operates on the
Great Lakes is different from the fleet of Category 2 cargo vessels that operates in U.S. coastal
ports and other inland waterways, in two important ways. First, Great Lakes Category 2 ships
can be very large, with cargo capacity of 63,000 tons or more and length up to 1,000 feet. While
ocean vessels of this size typically have Category 3 engines to provide power needed for all
conditions that may arise on the open seas, Lakers have lower power requirements and can be
equipped with smaller Category 2 engines that operate on cleaner burning distillate fuel. As a
result, about 20 percent of the combined U.S. and Canadian Great Lakes diesel fleet are Category
2 ships, representing about 31 percent of total ship tonnage. Second, while most Category 2
cargo ships operating in U.S. coastal ports and inland waterways are flagged in the United States,
a large portion of the Category 2 cargo ships that operate on the Great Lakes are foreign.
Twenty of the 52 Great Lakes Category 2 cargo ships, or about 38 percent, fly a Canadian flag.
This is important because it means that this transportation market is more international, although
due to the Jones Act the ability of foreign vessels to carry cargo between two U.S. ports is
limited.1'9
1.4 EPA's Coordinated Strategy for Category 3 Marine Diesel
Engines and Their Fuels
Category 3 marine engines are used on all types of ocean-going vessels (container ships,
tankers, bulk carriers) as well as on many of the bulk carriers operated on the Great Lakes.
H Fuels covered in this program include any No. 1 and 2 distillate fuels used, intended for use, or made available for
use in nonroad, locomotive, or marine diesel engines. Fuels under this category include those meeting the American
Society for Testing and Materials (ASTM) D 975 or D 396 specifications for grades No. 1-D and No. 2-D. Fuels
meeting ASTM DMX and DMA specifications also would be covered. Distillate fuels with a T-90 distillation point
greater than 700ฐF, when used in Category 2 or 3 marine diesel engines, are not covered by these standards; this
includes Numbers 4, 5, and 6 fuels (e.g., IFO Heavy Fuel Oil Grades 30 and higher), as well as fuels meeting ASTM
specifications DMB, DMC, and RMA-10 and heavier.
1 Jones Act is "[t]he common reference for Section 27 of the Merchant Marine Act of 1920 (41 Stat. 988), which
requires that all water transportation of goods between U.S. ports be on U.S.-built, -owned, -crewed, and -operated
ships. The purpose of the law is to support the U.S. merchant marine industry[.]"
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
EPA's three-part Coordinated Strategy to address emissions from Category 3 engines and their
fuels was proposed in a Notice of Proposed Rulemaking published on August 28, 2009 (74 FR
44442), and adopted in a Final Rule published on April 30, 2010 (75 FR 22896). The
Coordinated Strategy applies to U.S. vessels through the Clean Air Act, and to U.S., Canadian,
and vessels from other countries while they are operating in the U.S. portions of the North
American EGA, including the U.S. portions of the Great Lakes, through MARPOL Annex VI
and the Act to Prevent Pollution from Ships/ The combination of these national and
international measures results in a comprehensive program that covers both U.S. and foreign
vessels, and will achieve significant emission reductions from this sector.K When fully phased
in, the Coordinated Strategy's engine and fuel requirements are expected to reduce NOx
emissions by about 80 percent, PM emission by about 85 percent, and SOx emissions by about
97 percent compared to current standards.
The projected benefits of the Coordinated Strategy are substantial. As detailed in the
Regulatory Impact Analysis for our Category 3 marine rule, we project that by 2030 this
Coordinated Strategy will reduce annual emissions of NOx, SOx, and particulate matter by 1.2
million, 1.3 million, and 143,000 tons, respectively, and the magnitude of these reductions would
continue to grow well beyond 2030.10 These nationwide reductions are estimated to annually
prevent between 12,000 and 30,000 PM-related premature deaths, between 210 and 920 ozone-
related premature deaths, 1,400,000 work days lost, and 9,600,000 minor restricted-activity days.
The estimated annual monetized health benefits of this Coordinated Strategy in 2030 would be
between $110 and $270 billion. L The estimated costs of this Coordinated Strategy are
significantly less, with annual costs of about $3.1 billion in 2030. The transportation market
impacts of the higher fuel cost would be small on a per-unit shipped basis, with an increase of
less than 3 percent per container (about $18), about 1.5 percent per passenger ($6.60/day) for
cruise ships, and about $0.56 per tonne ($0.5 I/ton) for bulk goods.
Our benefit and cost analyses for the Coordinated Strategy were performed on a national
basis. In response to comments on our proposal (see Section 1.5.1), we also performed
additional analyses of the inventory and air quality impacts of the Coordinated Strategy for the
Great Lakes region and estimates of the cost of applying the EGA requirement to Lakers.11 For
the six states bordering the Great Lakes, we estimated the monetized PM2.5 benefits in 2030 to
be between $1.5 and $3.7 billion, compared to total projected costs of about $0.05 billion.
1.4.1 Clean Air Act Standards for Category 3 Marine Engines
The first element of EPA's Coordinated Strategy set out in our Category 3 marine rule is
our Clean Air Act emission control program for Category 3 marine engines and their fuels.
The Clean Air Act engine standards for Category 3 engines apply to new engines
installed on U.S. vessels (40 CFR parts 94 and 1042). Our 2010 Category 3 rule set near-term
1 Canada is currently developing their program for ships operating on the Canadian portions of the Great Lakes and
the St. Lawrence Seaway.
K Interested readers should refer to our Category 3 rulemaking for more information about the compliance and
enforcement of these programs.
L In this report, estimates of monetized benefits and engineering compliance costs are presented in 2006$, consistent
with the Category 3 marine rule analyses.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Tier 2 NOx standards that go into effect in January 2011 and will achieve a 20 percent reduction
from Tier 1 standards that are currently in place. The long-term Tier 3 standards go into effect in
January 2016 and represent an 80 percent reduction from Tier I levels. The Tier 3 NOx
standards are expected to require the use of high efficiency advanced technology emission
controls such as selective catalytic reduction (SCR). These NOx standards, set out in Table 1-5,
are equivalent to the international engine standards described in Section 1.4.2.
Table 1-5 Category 3 Engine Emission NOX Limits
Tier
Tier 1
Tier 2
Tier 2
TierS
Area of Applicability
All U.S. navigable waters and EEZ
All U.S. navigable waters and EEZ
All U.S. navigable waters and EEZ,
excluding ECA and ECA associated areas
ECA and ECA associated areas
Model Year
2004-2010
2011-2015
20 16 and later
20 16 and later
Maximum In-Use Engine Speed
Less than 130
RPM
17.0
14.4
14.4
3.4
130-2,000
RPMa
45.0-n(-a20)
44.0-n(-a23)
44.0-n(-ฐ'23)
9.0-n(-a20)
Note:
a Applicable standards are calculated from n (maximum in-use engine speed, in RPM. There are no Category 3
engines with engine speed >2,000 rpm.
The Clean Air Act marine fuel standards apply to fuels produced and sold in the United
States. Our 2010 Category 3 marine rule included regulations to allow the production and sale of
1,000 ppm sulfur fuel for use in Category 3 marine vessels while they are operating in the North
American ECA (see 40 CFR 80). Without this change, fuel with sulfur content up to 1,000 ppm
would be required to be used in the North American ECA by U.S. Category 3 vessels and all
foreign vessels but fuel production in the United States would be limited to below 500 ppm.
While our national fuel programs allows the production and sale of fuel with sulfur content
above 1,000 ppm (i.e., residual fuel), this fuel can be sold for use only on vessels equipped with
alternative devices, procedures, or compliance methods that achieve equivalent emission control
as operating on 1,000 ppm sulfur fuel (for example, the vessel is equipped with a certified SOx
scrubber), or for use outside the North American ECA.
1.4.2 2008 Amendment to MARPOL Annex VI
The second element of EPA's Coordinated Strategy set out in our Category 3 marine rule
is the 2008 amendments to Annex VI to the International Convention for the Prevention of
Pollution from Ships (called MARPOL Annex VI).
MARPOL Annex VI sets out international emission requirements for ships, including
NOx standards and fuel sulfur limits. The MARPOL Annex VI program is an important part of
our Coordinated Strategy because it extends engine and fuel controls to all ships and is
enforceable by any country that is a Party to the Annex. The United States became a party to
MARPOL Annex VI by depositing its instrument of ratification with International Maritime
Organization (EVIO) on October 8, 2008. This was preceded by the President signing into law
the Maritime Pollution Prevention Act of 2008 (Public Law 110-280) on July 21, 2008, which
contains amendments to the Act to Prevent Pollution from Ships (APPS, 33 USC 1901 et seq.).
The amendments also authorize the U.S. Coast Guard and EPA to enforce the provisions of
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Annex VI against domestic and foreign vessels and to develop implementing regulations, as
necessary. In addition, APPS gives EPA sole authority to certify engines installed on U.S.
vessels to the Annex VI requirements (40 CFR 1043).
The 2008 amendments to MARPOL Annex VI are based on the position advanced by the
19
United States Government as part of the international negotiations. There are two sets of
engine and fuel requirements. The first set is the global engine and fuel requirements. The new
global engine NOx limits consists of Tier II standards that apply to engines installed vessels
constructed beginning in January 2011. These standards will achieve a 20 percent reduction
from the current Tier I levels, and are the same as the EPA Tier 2 and Tier 3 standards set out in
Table 1-5. The new global fuel sulfur limits consist of a near-term limit of 35,000 ppm that
applies beginning in 2012 and a long-term limit of 5,000 ppm that applies beginning in 2020.
The long-term fuel sulfur limit is subject to a fuel availability review to be completed in 2018.
The second set of international standards is the requirements that apply in specially
designated Emission Control Areas (EGAs), described in Section 1.4.3.
1.4.3 Designation of Emission Control Areas
The third element of EPA's Coordinated Strategy for Category 3 engines and their fuels
is designation of Emission Control Areas (EGAs) for the United States.
The EGA approach contained in MARPOL Annex VI was developed as a way to ensure
greater air pollution reductions in specially designated areas while avoiding a requirement to use
high cost emission control equipment and fuels in areas such as the open ocean that are not in
need of that level of environmental protection. The criteria for EGA designation are set out in
Appendix HI to MARPOL Annex VI and require demonstration of a need to prevent, reduce, and
control emissions of SOx, PM, and/or NOx from ships operating in the specified area.
All ships operating in designated EGAs are required to comply with the more stringent
international engine standards and fuel sulfur limits. The EGA NOx standards apply to engines
installed on vessels constructed beginning in 2016: while these vessels operate in a designated
EGA their engines must achieve an 80 percent reduction from the current Tier 1 levels. The
EGA fuel sulfur limit, originally 15,000 ppm, decreases to 10,000 ppm in 2010 and to 1,000 ppm
in 2015.
The EGA standards are applicable to all ships that operate in U.S. designated EGAs
through APPS (see 40 CFR 1043). Currently, the North American EGA has been designated by
amendment to MARPOL Annex VI; the U.S. Caribbean EGA is expected to be adopted in July
2011.
1.4.3.1 North American ECA
The North American ECA, which was proposed jointly by the governments of the United
States, Canada, and France,M was designated through an amendment to MARPOL Annex VI
adopted by the Parties to Annex VI at a meeting held at EVIO on March 26, 2010. This
M The archipelago of Saint Pierre and Miquelon is a French territorial collectivity.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
amendment will enter into force on August 1, 2011, and the fuel sulfur requirements will begin
to apply on August 1, 2012.
As illustrated in Figure 1-3, the North America EGA extends about 200 nautical miles
from the coastal baseline of the United States and Canada except where this distance would enter
the Exclusive Economic Zones (EEZ) of a neighboring country.
Figure 1-3 North American ECA
Source: EPA
On the Pacific Coast, the ECA is bounded in the north such that it includes the
approaches into Anchorage, Alaska, but not the Aleutian Islands or points north.
It continues contiguously to the south including the Pacific coasts of Canada and
the U.S., with its southernmost boundary at the point where California meets the
border with Mexico.
On the Atlantic/Gulf Coast, the ECA is bounded in the west by the border of
Texas with Mexico and continues contiguously to the east around the peninsula of
Florida and north up the Atlantic coasts of the U.S. and Canada to the 60th North
parallel.
The Southeastern Hawaiian Islands are also included: Hawaii, Maui, Oahu,
Molokai, Niihau, Kauai, Lanai, and Kahoolawe.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
The regulatory text included in our 2010 Category 3 Marine rule made clear that a vessel
operating in U.S. internal waters shoreward of a designated ECA that can be accessed by ocean-
going vessels must meet the Annex VI ECA requirements.13 In addition to U.S. coastal ports and
U.S. rivers that are navigable from the ECA (such as the Mississippi River, the Puget Sound, the
Chesapeake Bay), this includes those portions of the Great Lakes and St. Lawrence Seaway in
which the North American ECA is enforceable by the United States. As a result, the North
American ECA requirements are applicable to all vessels operating on the U.S. side of the Great
Lakes and St. Lawrence Seaway, including Canadian and other foreign vessels. U.S. regulations
at 40 CFR 1043 contain provisions that implement the ECA engine standards and fuel sulfur
requirements and set out certain compliance provisions. Canada is currently developing their
national program with respect to implementation of the ECA requirements.
1.4.3.2 U.S. Caribbean Sea ECA
In July 2011, the Marine Environment Protection Committee (MEPC) of the International
Maritime Organization (IMO) adopted an amendment to MARPOL Annex VI designating the
U.S. Caribbean Sea ECA covering the Commonwealth of Puerto Rico and the U.S. Virgin
Islands. This amendment will enter into force on January 1, 2013, and the fuel sulfur
requirements will begin to apply on January 1, 2014. The area covered by this ECA is illustrated
in Figure 1-4.
Figure 1-4 U.S. Caribbean ECA
20'0'O'N-
15WN-
British Virgin
\ Islands
SOWN
-15'0'CTN
65'CWW
Source: EPA
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
The western edge of the proposed area would generally run north-south to the
east of the Mona Passage, 12 or more nautical miles (nm) from the west coast of
the main island of Puerto Rico.
The eastern edge of the proposed area would generally run north-south, but also
extend eastward through the area between the U.S. Virgin Islands and the British
Virgin Islands as well as eastward toward the area between Saint Croix and
Anguilla and Saint Kitts.
The northern edge of the proposed area would extend about 50 nm from the
territorial sea baselines of Puerto Rico and the U.S. Virgin Islands.
The southern edge of the proposed area would extend about 40 nm from the
territorial sea baselines of Puerto Rico and the U.S. Virgin Islands.
1.4.3.3 Additional U.S. ECAs
EPA is continuing its review of the areas of Alaska, Hawaii, and U.S. territories not
already covered by an existing or proposed EGA, with a view to determining if EGA designation
is appropriate.
1.4.4 Summary
Our Coordinated Strategy for Category 3 engines and their fuels is a comprehensive
program that covers marine diesel engines and their fuels on all vessels, U.S. and foreign, which
operate in areas that affect U.S. air quality and will significantly reduce emissions from foreign
and domestic vessels, with significant benefits for human health and welfare throughout the
country.
Finally, it should be noted that, like Category 2 marine engines, the land-based
alternatives to Category 3 vessel transportation on the Great Lakes are also subject to stringent
emission controls. Technology-forcing standards applicable to heavy-duty trucks became
effective in 2007 (particulate matter) and 2010 (NOx), and the diesel fuel used in these engines
has been subject to a 15 ppm sulfur limit since 2006. Technology-forcing standards will begin to
apply to locomotives in 2015; their fuel will be subject to a 15 ppm sulfur limit beginning in
2012.N
N One peer reviewer noted "[i]f ultra-low sulfur fuel requirements are being placed on trucks and locomotives, but
not on [Category 3 Jmarine engines, this would represent an indirect subsidy to marine. While the road to
implementation may be markedly different, the requirements should represent a level playing field to the degree
possible." (Kruse)
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
The Hon. James L. Oberstar (formerly named the Charles M. Beeghly) passes under the Blue
Water Bridge in Port Huron, ML Source: Photo taken by Barant Downs, August 16. 2007.
1.5 The Coordinated Strategy and the Great Lakes
We received comments from nearly 50 persons and organizations regarding the provision
in our Category 3 marine proposal clarifying that the North American EC A, once approved at
EVIO, would also apply to the U.S. portions of the Great Lakes. These commenters represented a
wide spectrum of stakeholders, including companies that own vessels, and their employees;
companies that use the products transported by ship on the Great Lakes, including steel and
utility companies; regional associations; port authorities; fuel providers; and environmental and
governmental groups.14 Their comments and our responses to them are summarized below.
1.5.1 Concerns of Great Lakes Stakeholders
The Great Lakes stakeholder comments on the C3 marine rule are primarily about the
application of the EGA fuel sulfur limits to the Great Lakes.
Great Lakes commenters told EPA that the Great Lakes transportation market is
fundamentally different from the ocean marine transportation market. The ocean market ships
goods between the United States and Europe, Asia, South America, and Africa, and there are no
reasonable alternatives to shipping by vessel for the vast majority of these products. According
to these commenters, the nature of transportation in the Great Lakes region, however, is more
like the Mississippi River system than the international marine system. In the Great Lakes, ship
operators move goods from one area of the country to another and are in competition with rail
and truck transportation modes. These commenters indicated that, for the reasons explained
below, an increase in operating costs associated with the requirement to use EGA-compliant fuel
in the Great Lakes would put marine at a competitive disadvantage in the Great Lakes and cause
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
a transportation mode shift away from ships and toward trucks or rail, which could increase
emissions overall by moving cargo to less efficient ground transportation.
According to these commenters, application of the EGA fuel sulfur requirements on the
Great Lakes would lead to two changes in the Great Lakes shipping conditions, both of which
would result in upward pressure on marine freight rates. First, the application of the EGA fuel
requirements on the Great Lakes would require all vessels that currently use HFO (steamships
and Category 3 vessels) to use higher-price marine distillate oil (MGO or MDO). This would
increase their operating costs beginning January 1, 2015, or even earlier if fuel meeting the ECA
interim fuel sulfur limit of 10,000 ppm is not available on the Great Lakes when the interim fuel
sulfur limit goes into effect in August 2012. While the program would also allow operators to
continue to use lower-price HFO if they install and use an exhaust gas cleaning system
(scrubber) that achieves an equivalent sulfur emission reduction, industry stakeholders told EPA
that scrubber systems that operate in fresh water conditions are currently unavailable and the
ability of these systems to meet washwater discharge requirements is still unclear.
Second, commenters argued that steamships cannot safely use MDO and therefore the
Great Lakes steamship fleet would have to be retired. They indicated that steamships operating
on the Great Lakes were designed and constructed in the 1940s and 1950s and were meant to
operate solely on HFO. Using MDO in these old boilers systems could raise safety concerns due
to a higher risk of explosion because of the different fuel properties of distillate fuel.
Commenters said that it would not be possible to replace U.S. steamships due to the high cost of
building new Jones Act vessels in U.S. shipyards and the long lead time for building new ships.
As a result, the number of cargo ships operating on the Great Lakes would decrease.
The combination of fewer ships in the fleet and higher operating costs for the ships that
remain would put upward pressure on ship freight rates. These increased marine rates would
then make rail and truck transportation more financially attractive, leading to a transportation
mode shift. Since trucks and rail have higher emissions per ton-mile, the net result could be the
opposite of the environmental improvements intended by the requirements.
Commenters were also concerned that the increase in freight rates would affect the
market for crushed stone, leading users to change their source from stone transported from the
upper Great Lakes to local quarries, also resulting in a loss of cargo for Great Lakes carriers.
Finally, some commenters said there could be a production shift for steel manufacturing
and electricity generation as a result of increased transportation costs for iron ore and coal. Such
a production shift would also adversely affect the Great Lakes shipping sector.0
0 One peer reviewer commented that "from the economic perspective, if the higher cost of fuel causes customers to
source their products more nearby, then the products must be close enough substitutes that they should not travel
such distances in the first place. In other words, if close substitutes do not shift closer then society must be
subsidizing excessive freight transport distance, which would be bad public policy because the economics of the
move would not pay the full cost. The researchers find that even those shifts do not occur, so the case is moot.
Especially whether the product is iron ore or Michigan stone that is high in calcium carbonate, the product is
sufficiently unique that it does not provoke a shift." (Belzer)
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
1.5.2 Great Lakes Provisions in the Final Category 3 Marine Rule
Our final Category 3 marine rule contains three regulatory provisions that address the
issues raised by Great Lakes stakeholders described above: a steamship exemption, an economic
hardship provision, and a fuel availability waiver. We also agreed to perform an analysis to
evaluate the economic impacts of the Category 3 rule on Great Lakes shipping.
1.5.2.1 Great Lakes Regulatory Provisions
The Great Lakes EGA regulatory provisions are contained in 40 CFR 1043.95. These
provisions are available to any vessel, including a foreign vessel that operates exclusively on the
Great Lakes, defined as all the streams, rivers, lakes, and other bodies of water that are within the
drainage basin of the St. Lawrence River, west of Anticosti Island. These provisions are
available to foreign as well as U.S. vessels that operate on the U.S. side of the Great Lakes.
First, to address the technical and safety concerns raised by the use of distillate fuel in
steam engines, and consistent with Congressional direction, Great Lakes steamships are excluded
from the EGA fuel standards.15 This provision avoids immediate retirement of steamships,
which may not be able to operate safely on distillate fuel. However, we expect these vessels will
be retired eventually because of their higher fuel usage when compared to diesel engines (they
can consume almost twice as much fuel as modern diesel engines). For the purpose of this
exclusion, a Great Lakes steamship means a vessel operating exclusively on the Great Lakes and
Saint Lawrence Seaway whose primary propulsion is a steam turbine or steam reciprocating
engine. Ships with diesel propulsion engines with auxiliary boilers are not eligible. In addition,
the steamship must have been in service on the Great Lakes prior to October 30, 2009.
Second, the regulations contain a provision that provides for relief in the event of serious
economic hardship. This economic hardship provision allows Great Lakes ship owners to
petition EPA for a temporary exemption from the 2015 fuel sulfur standards. The owner must
show that despite taking all reasonable business, technical, and economic steps to comply with
the fuel sulfur requirements, the burden of compliance costs would create a serious economic
hardship for the company. The Agency will evaluate each application on a case-by-case basis.
Third, the regulations contain a fuel availability waiver, to address the concerns about
availability of 10,000 ppm sulfur fuel on the Great Lakes. This provision is available to
Category 3 Great Lakes vessels that are not covered by the steamship exclusion. The 10,000
ppm EGA fuel sulfur limit applies on the Great Lakes when the North American EGA goes into
effect, in August 2012, and continues until the more stringent 1,000 ppm EGA fuel sulfur limit
goes into effect January 1, 2015. The Great Lakes fuel waiver is available if marine residual fuel
meeting the 10,000 ppm sulfur limit is not available. Under this provision, it will not be a
violation of our standards for a Great Lakes vessel operator to purchase and use marine residual
fuel with sulfur content above 10,000 ppm provided the fuel purchased is the lowest sulfur
marine residual fuel available at the port. There are some reporting requirements for this waiver.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
1.5.2.2 Economic Impact Analysis
As noted above, we performed an extensive economic analysis to examine the inventory
contribution, air quality impacts, benefits, and costs for all vessels covered by the Category 3
marine rule, including Great Lakes Vessels.16 We also performed additional analyses of the
inventory and air quality impacts of the rule for the Great Lakes region and estimates of the cost
of applying the ECA requirement to Lakers.1? That analysis breaks out in greater detail the
inventory and air quality impacts and expected health benefits of applying the ECA requirements
to the Great Lakes region and was based on the national estimates; no new modeling was
performed. According to this analysis, the estimated monetized PM2.5 benefits in 2030 for the
six states bordering the Great Lakes are estimated to be between $1.5 and $3.7 billion. In
comparison, the total projected costs for all Great Lakes vessels in 2030 are significantly less and
estimated at $0.05 billion.
We also performed an initial analysis of the potential for transportation mode shift and
production shift as a result of increased operating costs for Great Lakes vessels.18 We indicated
we would follow this initial analysis with a more detailed study to evaluate the economic impacts
of the Category 3 rule on Great Lakes shipping.
Our initial transportation mode shift analysis was based on a comparison of fuel
consumption rates and transport costs for marine and the land-based alternatives, rail and truck
transportation. The analysis uses the marine price of diesel fuel for all modes and therefore is a
conservative estimate with respect to the rail and truck alternatives, which are or will be required
to use fuel with a maximum sulfur content of 15 ppm that is expected to be more expensive than
1,000 ppm marine fuel. Figure 1-5 presents the results of this analysis, with fuel consumption
and transport costs normalized such that the shipping business as usual (BAU) case is equal to
1.0. This analysis indicates that the ECA fuel requirements are not expected to change the
relative cost advantage of marine over rail or truck transportation with respect to fuel
consumption or transportation costs. Therefore, compliance with the ECA fuel sulfur
requirements by ships operating on the Great Lakes would not be expected to result in significant
mode shifts to other forms of transportation.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Figure 1-5 Relative Cost per Ton-Mile by Transportation Mode
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CJ U
1
1 i i
M
i i
1
Fuel Consumption Trans port Cost
Source: Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at or
above 30 Liters per Cylinder - Information in Support of Applying Emission Control Area (EGA)
Requirements to the Great Lakes Region. EPA-HQ-OAR-2007-0586. December 15, 2009.
The initial source shift analysis was performed for a steel production scenario. The
analysis estimated the additional costs associated with transporting the three primary raw
materials for making steel (iron ore, limestone, and coke) from various locations on the Great
Lakes to Indiana Harbor on ships using EGA compliant fuel and compared this with the
additional costs of transporting imported steel to Detroit, roughly 1,700 miles through the coastal
EGA area, the St. Lawrence Seaway, Lake Ontario, and Lake Erie. p The analysis assumed that
finished steel is transported from Indiana Harbor to Detroit by truck, which would not be
affected by the EGA fuel requirement. This analysis, summarized in Table 1-6, indicates that the
increase in cost for domestic steel is less that the increase in cost for imported steel. The cost
increase is also less than the historical month-to-month fluctuation in steel prices (steel prices
doubled between 2008 and 2009).
p Note that this supplemental steel analysis only considers ship traffic in one direction and assumes that the vessels
will perform useful work on the return voyages (i.e., there is a backhaul). One peer reviewer (Hull) indicated that the
backhaul for steel coils is typically grain. If we were to assume no backhaul for either the domestic or the imported
steel case, this would increase the estimated transportation costs but the increase would apply to both cases
proportionally and therefore no production shift would be expected. If we were to assume a backhaul for the
imported steel but no backhaul for the domestic steel, this would increase the estimated transportation cost for the
domestic case but a production shift would still not be expected. Since the empty backhaul would consume less fuel
(due to the lighter load), the transportation cost increase for the round-trip domestic case would be less than double
the one-way case and therefore the price impacts for the domestic case still would be less than the imported steel
case with a backhaul.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Table 1-6 Impact of Great Lakes ECA on Steel Cost
Increased fuel cost [$/ton-mile]
Shipping distance in ECA [nautical miles]
Increased fuel cost [$/ton of steel]
Price of cold rolled steel (June 2009) [$/ton]a
% cost increase for steel
Domestic Steel
$0.0009
870
$0.90
$525
0.2%
Imported Steel
$0.0009
1,700
$1.75
$525
0.3%
a Source: http://www.steelonthenet.com/prices.html
The remainder of this report contains a more detailed analysis of the economic impacts of
the Category 3 marine rule on the Great Lakes. In Chapter 2 we examine twelve O/D pairsQ that
are at risk for transportation mode shift. For all but one of these scenarios, freight rates for
marine transportation are expected to remain well below the next cheapest shipping mode, rail,
after the application of the ECA fuel sulfur requirements, and therefore no transportation mode
shift is indicated. For the one exception, the initial results suggested the all rail alternative has a
lower route-based freight rate than either the Base Case or ECA Case freight rates. Chapter 2
explains why EPA believes this scenario was mis-specified. In Chapter 3 we look at the
potential for source shift for crushed stone and production shift for electricity and steel. Those
analyses also show that source shift and production shift are not expected. Chapters 4 through 7
contain an expanded discussion of our estimates of the inventory, air quality impacts, health and
environmental benefits, and costs of this program. The analyses contained in Chapters 2 and 3 of
this report were peer reviewed pursuant to EPA's Science Policy Council Peer Review
Handbook, 3rd edition (Peer Review Handbook)^ The peer review is described in Chapter 8.
1.6 Other Studies of the Environmental and Economic Benefits of
Marine Transportation in the United States
In recent years several studies have been performed to examine the environmental and
economic impacts of marine transportation compared to other transportation modes. These
include studies examining the health and human welfare impacts of marine transportation
compared to other modes, the economic benefits of marine transportation, and the impacts of
changing fuel prices. This section briefly describes the methodology and main findings of
several of these studies, many of which were referred to in comments submitted in response to
our Category 3 marine proposal.
Q "Origin/destination (O/D) pairs" refers to specific starting and ending points of shipping routes on the Great Lakes.
Section 2.4 describes the selection of the O/D pairs and shipping routes.
R These guidelines can be found at http://www.epa.gov/peerreview/. Further, the Office of Management and
Budget's (OMB' s) Information Quality Bulletin for Peer Review and Preamble (found in the EPA's Peer Review
Handbook, Appendix B) contains provisions for conducting peer reviews across federal agencies and may serve as
an overview of EPA's peer review process and principles.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
1.6.1 Studies Related to the Health and Human Welfare Benefits of
Marine Transportation
1.6.1.1 Minnesota Department of Transportation Study, 1991.
The study estimates the environmental impacts of an assumed mode shift from marine to
rail or truck transportation for four O/D pairs in Minnesota.19 The purpose of the study was to
evaluate the human health and welfare impacts that may result from policy decisions that reject
developing, maintaining, or improving waterways. The methodology involves estimating annual
increases in air emissions and accidents based on fuel use, tons of cargo transported, and
emission and accident rates.
The authors estimate the increase in fuel use that can be expected to occur if cargo
currently transported by ship were shifted to other modes. They report an increase in annual fuel
use by 826% (shift to trucks) or 331% (shift to rail), an increase in annual exhaust emissions by
709% (shift to trucks) or 470% (shift to rail), and an increase in probable accidents annually by
5,967 accidents (shift to trucks) or 290% (shift to rail).
The results of this study are dated in that it uses fuel efficiencies estimates from a report
published in 1980; EPA emission rates from 1973 and 1989 reports; and accident rates from a
report published in 1986 (trucks), from an analysis of accidents in 1980 (rail), and from 1986-
1990 (marine). In addition, "emissions" are not distinguished by pollutant. As a result, the
impacts cited above are not reflective of the current truck, rail, and marine fleet characteristics,
and the results should be taken as indicators and not as absolute values relevant to the year under
consideration in this study, 2015. Nevertheless, this study is relevant in that it shows the
advantages of marine over rail or truck transportation for the routes considered.
These results also reflect an ongoing disconnect between concerns regarding mode shift
and environmental impacts such as increased CO2 emissions. As we show later in Chapter 2,
fuel costs are 40-50 percent of marine shipping costs. This percentage is lower for trucking.
However, even if the only cost for trucking were fuel costs, trucking rates would be at minimum
four times higher than marine rates. This is because truck fuel consumption is estimated at about
9 times that of marine, per ton of goods moved.
1.6.1.2 Ontario Marine Transportation Study, November 2006.
This is an analysis of the opportunities for the marine transportation mode in Ontario,
Canada.20 The report focuses on container and passenger opportunities, and describes about a
dozen routes on which marine could be an alternative to rail or truck transportation. The report
also quantifies the net benefits of a switch to the marine mode for two routes: Hamilton to
Oswego truck ferry (Can$ 1.7 M annually) and Toronto to Niagara passenger ferry (Can$ 1M
annually), with regard to reductions in air pollution, greenhouse gases, tire disposal, congestion
costs, accidents, and noise and amenity. The report also describes the barriers to realizing these
opportunities, including regulatory and nonregulatory constraints.
Like the Minnesota DOT study and the DOT/MARAD study summarized below, this
study suggests that human health and welfare impacts should be examined in those scenarios
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
where an intermodal shift is indicated to be likely. However, while this study examines the
potential environmental benefits of an intentional shift from truck or rail mode to marine, it does
not contain an analysis of freight rates, operational costs, or the impacts of changes in either the
supply or the demand sides of the market for any of these three sectors. It envisions a wholesale
change of market behavior on certain routes, and does not look at the implications of a change in
operational costs or how transport sectors suppliers or their customers will react to those costs.
Fuel supply and prices are taken as given and are unchanging in this analysis and therefore are
not helpful for a study of impacts of an operational cost increase on marine shipping.
The Canadian-flagged Algowood heads upbound at Mission Point in Sault Ste. Marie, MI. Source: Photo taken
by and used with permission from Dick Lund, available here: http://www.dlund.20m.com/rblla.html.
1.6.1.3 U.S Department of Transportation Maritime Administration Study, December 2007
as amended March 2009.
91
This study is similar to the Minnesota DOT study described above, with updated inputs.
It estimates the impacts of completely closing the Mississippi and Illinois Rivers in St. Louis,
Missouri, and shifting all cargo to truck transportation as a way to quantify the benefits of river
transportation. Two scenarios were modeled, one in which no improvements were made to road
infrastructure to accommodate the increased traffic, and one in which improvements were made.
The impacts after 10 years are estimated to be about a 210 percent increase in the number of
trucks per lane-mile per day; crashes, injuries, and fatalities would increase from 36 percent to
45 percent, depending on the improvements scenario; and emissions would increase 37 percent
to 52 percent, depending on the improvements scenario.
It should be noted that this analysis was for river traffic, characterized by tug-barge
combinations, and emissions are based on fuel usage. Like the Minnesota DOT study, this study
shows the important environmental benefits of marine transportation.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
1.6.2 Studies Related to the Benefits of Short-Sea Shipping
Short sea shipping generally means the transportation of containerized or packaged goods
by ship, either on LoLo (lift-on/lift-off) ships for containers, or RoRo (roll-on/roll-off ships) for
truck trailers. Short-sea shipping takes advantage of the economies of scale of marine
transportation by combining land transportation with a sea link. So, for example instead of
transporting a container from Toronto to Chicago by truck driving around the lakes, the container
would be trucked to a port in Canada and loaded onto a ship for Chicago, where it would be
picked up by a truck for final delivery.
1.6.2.1 Tomchick et al, 2003.
This report was prepared by E. A. Tomchick, et al. of the Pennsylvania Transportation
Institute for Save the River and Great Lakes United.22 The report is an independent examination
of a 2003 study by the Army Corps of Engineers with regard to expansion of the Great Lakes
waterway system that would allow winter navigation. The authors examine various aspects of
the ACE study in the context of a 1979 study of season expansion on the Great Lakes. They also
examine the opportunities for container shipping on the Great Lakes, which would be
encouraged by winter navigation.
The authors question several of the assumptions in a transportation savings analysis of
container traffic on the Great Lakes performed by the Tennessee Valley Authority. First, they
suggest that the use of a 6.25 percent interest rate to estimate the capital costs of in-transit
inventory understates those inventory costs because that 6.25 percent is lower than the current
(2003) cost of capital. Second, they note that the freight rates used in the analysis are based on
ocean liner services; Great Lakes liner services may be higher due to the costs of using the locks
and other system fees. Finally, they note there is a tradeoff between transportation cost savings
and longer transit times. Longer transit times are associated with more uncertainty with regard to
service reliability, which necessitates higher inventories, which leads to higher inventory costs.
Finally, there are shipping chain costs that should be taken into account as well.
The authors also describe several conditions that would encourage container shipping on
the Great Lakes and evaluate whether these conditions are feasible. Ocean port congestion could
lead to the development of container shipping on the Great Lakes, through direct transportation
to consumer areas on the lakes. However, the authors conclude there is no evidence to suggest
that Atlantic ports have significant capacity constraints. They also note that while there is
increasing congestion on highways connecting the Atlantic and Great Lakes areas, rail carriers
have the capacity needed to absorb future traffic growth. With regard to shippers, studies from
the 1970s report that ship operators gave several reasons for not operating on the Great Lakes.
These include items such as "long voyages, averaging 25-30 days; too many ports of call, limits
on ship size, and no commercial interest."23 The authors note that ships coming directly from
Europe would be faced with consolidating Great Lakes cargo in Europe, while shuttle service
from East Coast ports would require consolidation in those ports. Finally, with regard to marine
transportation users, it was stated that "three service criteria were consistently rated most
important: cost of service, transit time, and on-time pickup and delivery." The authors noted
that "a major question is whether container shipping companies ... even with improvements to
the system, can provide the level of service required by shippers."24
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
In conclusion, these authors note that "it is not clear that expanding the [Great Lakes/St.
Lawrence Seaway] would induce container ship operators to offer container service on the
system or what the optimum size vessel would be for offering such service. If the system were
expanded to permit larger vessels ... there might be some improvement in transit time reduction,
but the long transit times and associated transit time unreliability problems would still exist. ...
System expansion will not eliminate the business problems associated with long transit times."25
1.6.2.2 U.S. Department of Transportation Maritime Administration, 2005.
This study is part of the U.S. Department of Transportation's Industry Survey Series and
reports the results of a survey of U.S. carriers operating on the Great Lakes. 26 Seven carriers
responded to the survey, representing 93 percent of Great Lakes domestic traffic in 2004.
While this study does not measure the likelihood of intermodal shift, it examines
operators' opinions on such a shift. When asked how much of their existing cargo could be
captured by rail or truck, all respondents answered less than 10 percent, with the exception of
iron ore for which 4 respondents indicated from 10 to 30 percent could be captured. When asked
how much of existing rail or truck cargo could be captured by marine, more respondents replied
10 to 30 percent for all commodities (iron ore, coal, and limestone).
1.6.2.3 U.S. Department of Transportation Maritime Administration, 2006.
This study was performed by Global Insight in association with Reeve & Associates for
the U.S. Department of Transportation/MARAD.27 It examines the potential for short-sea
shipping to "absorb a significant part of the projected growth in highway and rail freight
9R
traffic." The direction of the freight shift is from highway truck to intermodal truck-ship-truck.
Cargoes examined were containers or truck trailers (RO-RO); bulk cargoes of iron ore, coal,
crude oil, and minerals were not considered in the analysis because they "are not commonly
containerized or carried in highway trailers but [move] by water in large bulk ships or barges."29
The Great Lakes corridor examined is between Milwaukee, WI and Muskegon, MI. The analysis
for this corridor suggests that "the short-sea mode is superior to trucking in terms of both time
and costs."30
The study provides "important information on the perceived criteria for a successful
mode shift from truck to an intermodal truck/ship combination for containerized or trailer cargo."
These include:8'31
The market in a traffic corridor has enough density to enable relatively large
vessels that provide economies of scale in terms of operating and capital cost to
be deployed with high enough service frequency to be competitive with trucking
Vessel capital, crew costs, and marine terminal expenses must be set at "best in
class" levels for U.S. operations for short-sea shipping to be price competitive
with ground transport alternatives on a door-to-door basis
s One peer reviewer notes "... the fact that this shift has not happened, even as fuel price spikes make truck transport
much more disadvantageous, suggests they may still have it wrong." This commenter suggests there will be mode
shift from truck to rail before there is mode shift to ships. (Belzer)
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Short-sea shipping can be particularly competitive for heavy and/or hazardous
shipments currently moving over roads, such as chemicals
When short-sea shipping provides a more direct point-to-point routing and/or
avoids areas of traffic bottlenecks and urban congestion, it can be highly
competitive with ground transportation in terms of both cost and transit time -
such as in the Great Lakes corridor.
With regard to operating costs, survey respondents mentioned labor costs, the Harbor
Maintenance Tax, and new vessel construction costs as constraints for an intermodal approach.
While highway truck fuel costs were one of the costs motivating interest in short-sea shipping,
there was no separate analysis of fuel price impacts on the comparative advantages of short-sea
shipping.
1.6.2.4 Transport Canada, U.S. Army Corps of Engineers, et al, Fall 2007.
The goal of this study was to examine "the current condition of the [Great Lakes/St.
Lawrence Seaway] system, and how best [to] use and maintain the system, in its current physical
configuration, in order to capitalize on the opportunities and face the challenges that will present
themselves in the coming years."32 This study provides background on the geography of the
waterway, its economic significance and environmental conditions. The report also discusses the
current status of the infrastructure and how it should be managed to take full advantage of future
economic opportunities.
The study provides the results of an analysis of the competitiveness of the Great Lakes
compared to other modes of transportation by the Army Corps of Engineers.33 That study
consists of a transportation rate analysis based on a sample of 857 shipping movements in 2002,
covering over 40 commodities and representing about 90 percent of total cargo tonnage shipped
that year on the Great Lakes. The analysis was used to estimate the cost savings associated with
the Great Lakes/St. Lawrence Seaway system in comparison to the next least expensive mode.
The analysis shows that the Great Lakes/St. Lawrence Seaway system "offers shippers an
average savings of $14.80/ton in transportation and handling charges compared to the next-best,
all-land transportation..." The total savings to shippers in 2002 were estimated at "$2.7 billion
in transportation and handling charges that they would otherwise have incurred had they used
other modes of transportation."34 The estimated transportation cost savings of ship
transportation compared to the least cost alternative transportation are presented in Table 1-7.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Table 1-7 Transportation Savings Offered by the Great Lakes/St. Lawrence Seaway by Commodity
Commodity group
Aggregates and Slag
Metallic Minerals and Ores
Coal, Coke, Pet Code
Iron, Steel and Other Metals
Non-metallic Minerals
Wheat
Petroleum Products
Other Grains and Feed Ingredients
Soybeans
Corn
Total
Sample size (tons)
37,813,000
62,395,000
40,784,000
12,872,000
8,884,000
8,046,500
3,932,500
1,819,000
1,692,000
1,169,000
179,407,000
Savings/Ton
$16.03
$9.35
$13.36
$32.49
$19.50
$17.37
$18.60
$28.20
$22.26
$23.61
$14.80
Total Savings"
$605,988,000
$583,464,000
$544,961,000
$418,219,000
$173,224,000
$139,776,000
$73,137,000
$51,330,000
$37,667,000
$27,614,000
$2,665,360,000
" In descending order of total shipper savings, numbers rounded to nearest 1,000
Source: Great Lakes St. Lawrence Seaway Study, Final Report, Fall 2007, available here:
http://www.marad.dot.gov/documents/GLSLs_finalreport_Fall_2007.pdf
EPA's present economic study estimates the EGA fuel price increase at about $193/tonne
of fuel, or $0.48/gallon (see Section 2.5.1.3). Given this relatively small increase, it is unlikely
that compliance with the EGA fuel requirements on the Great Lakes would result in a large
transportation mode shift, especially since rail and truck transportation will be required to use the
more expensive 15 ppm ULSD in the same time frame.
Using the EGA fuel price from EPA's present study and comparing to the 2007 Transport
Canada/ACE study, these fuel impacts reduce the savings per ton reported in Table 1-7 by less
than 15 percent, and by 5 percent or less for the four commodities examined by EPA, for most
scenarios analyzed.1 The range of fuel cost increases reported in Chapter 2 of this EPA report
for the sixteen scenarios examined range from $0.24 and $1.13 per cargo ton for coal, from $0.35
and $2.67 per cargo ton for iron ore, from $0.84 and $2.10 for wheat, and from $0.23 and $0.34
for crushed stone, with the largest cost increases occurring in the scenarios with the longest
marine links.
Coal, iron ore, grain, and crushed stone (see Chapter 2).
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
1.6.3 Studies Related to the Impacts of Fuel Prices on Shipping
1.6.3.1 U.S. Department of Transportation Maritime Administration, 2008.
This study was performed to estimate "the impact of oil prices on markets and their
logistic chains [and] to evaluate the potential of [higher] oil prices on U.S. domestic freight
transportation" as a response to sharp increases in crude oil prices that were experienced in
2008.35 The authors note that the current distribution of cargo between truck, rail, and marine
transportation is largely an artifact of several decades of low fuel prices which allowed trucking
to obtain a large share of the market based on their shipment time advantages. This study
projects future oil prices and "assesses how such prices would impact the transportation logistics
chains and evaluate(s) likely changes." 36 The authors particularly want to explore how short-sea
shipping may benefit from increased fuel prices:
For water, the market position is similar to that of rail as it can provide an alternative to
truck because of water's lower operating costs. The major issue is that because the water
mode is so much slower than truck or rail it has not been able to move into the higher
value container or intermodal business, and has typically only substituted for truck or rail
in bulk and neobulk markets. However, as both truck and rail have capacity problems
while water has considerable capacity, the opportunity may now exist for water to move
up market from bulk traffic, first into neobulks (steel coil) and then into containerized
freight, particularly where market conditions provide additional advantage for water (e.g.,
shorter water distance, easier port transfers, etc.).37
The analysis relies on the GOODS model, which is a generalized cost (GC) model based
on a supply and demand analysis. On the supply side, the GC "incorporates all of the critical
factors that motivate shippers and carriers to use a particular route, mode, and shipment type,"
and is a function of transit time, shipping cost, frequency, and reliability. The generalized cost of
shipping is reported in hours rather than dollars. Generalized costs are developed for each
origin-destination pair in a corridor. The demand side of the model considers the aggregate
impacts of increased oil prices on the economy and what these impacts mean in terms of the
demand for transportation services. The pertinent demand factors are economic growth, induced
demand as a result of increased volumes, and competition effects leading to shifts in demand
from one mode to another based on increased costs. The economic growth projections are based
on the Freight Analysis Framework traffic levels, although the study does not specify what this
growth rate is or how it was estimated.
For a defined set of transportation corridors (West Coast, Gulf Coast, East Coast, Great
Lakes, Mississippi), demand and supply factors are defined. The model is then used to examine
the impacts of increased fuel prices on costs, and whether short-sea shipping can be competitive
with truck or rail service. The analysis was performed for three years (2002, 2005, and 2020),
with three fuel price scenarios for 2020 (low, medium, high).
The results show that "fuel efficient rail and water modes ... are far less affected by fuel
price increases than trucking [and] shippers will be able to realize significant savings by
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
diverting to rail and water." One limiting factor not included in the analysis is drayageu costs,
which may reduce some of the potential intermodal shift. The authors note that "drayage charges
are very high as there is frequently no back haul and trips involve extra time for pickups and
delivery, both at ports and at the customer's loading dock ... [increasing drayage costs] will
encourage firms that make use of intermodal services to locate even closer to ports and rail
terminals to minimize drayage costs."38 It is not clear, however, if such relocation costs are
included in the analysis. The authors also note an additional constraint for rail: capacity
constraints that limit their ability to absorb additional shipping and the relatively long distance
they require to break even on costs because they bear the costs of maintaining the rail system.
The results of this study indicate that as fuel prices increases there is a projected increase
in the number of loaded containers carried on the Great Lakes, with forecast potential traffic
increasing up to 200 percent for a fuel increase from $2 to $7 per gallon. The Mississippi and
Gulf Coast corridors would see similar increases. While there was only a negligible increase in
container traffic for the East and West coasts, there may be a potential for port feeder services
(e.g. transferring containers from large ocean-going ships arriving at coastal ports to smaller
ships for transportation to ports closer to the areas where the goods will be consumed, instead of
transporting those containers by rail or truck). With regard to bulk cargo, "where in recent years,
rail productivity improvement has flattened water traffic growth ... the prospect of rising fuel
prices is likely to shift the cost advantage back to water."39 The results suggest that grain
shipments on the Great Lakes are projected to increase substantially as fuel prices increase,
although petroleum shipments are projected remain about the same.
The significant point to note about this study is that it explores the impact of fuel
increases on the transportation system as a whole, including demand for transportation and the
supply of transportation services (i.e., as fuel prices increases across the economy, what will be
the impacts on the distribution of cargo across different transportation modes). In other words,
there is a synergy in this model between expected economic growth and increases in fuel costs
for the truck, rail, and marine sectors. As fuel price goes up, there is an expected increase in the
cargo volumes handled by ship due to those synergies, and the study concludes an increase in
fuel prices across the economy is expected to lead to more containerized and bulk traffic on the
Great Lakes. However, this study does not provide a tool to analyze the impact of an increase in
fuel costs on the Great Lakes associated with application of EC A fuel requirements, holding all
other aspects of the economy, including all other fuel prices, constant.
1.6.3.2 Canadian Shipowners' Association Study, 2009.
This study was submitted to EPA in support of the Canadian Shipowners' Association
(CSA) comments on EPA's Category 3 marine proposal.40 The study consists of two parts. A
quantitative analysis estimates the impacts of increased fuel costs on freight rates and
transportation mode shift generally, and is performed for the grain and petroleum markets.
These markets appear to have been chosen based on data availability. There is also a qualitative
analysis that considers the impacts of increased fuel costs on a set of specified markets including
the grain, salt, stone, petroleum, and steel markets.
u "Drayage" refers to movement of goods, by land, to and from a port.
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
With regard to the quantitative analysis, the study estimates operating cost increases for
the fleet on average. These costs are used to adjust the freight rates. These adjusted freight rates
are used to estimate potential mode shift using a mode shift factor derived from the 2008
MARAD study described above. The year of analysis is 2012, based on the assumption that
heavy fuels meeting the 10,000 ppm 2012 standard will not be available and all vessels operating
on the Great Lakes will be required to use distillate fuel by that date.v
The fuel prices used in the analysis are the prices reported at Sarnia in Ontario, Canada.
Three price cases are examined: the 2008 average price, the price at June 7, 2008 (reflecting a
peak in fuel prices generally) and the price at July 10, 2009 (current to when the analysis was
performed for the study). The 2008 average prices are $523 for HFO180, $906 for MDO, and
$1,010 so-called premium MDO ($100/MT price premium). Not surprisingly, the choice of fuel
price has an impact on the results. As illustrated in Table 1-8 and Figure 1-6, the oil and fuel
prices for 2008 and early 2009 were particularly high due to various market factors, and they
subsequently fell. In comparison, the prices used in EPA's analysis are $424 for HFO and $848
for MDO, which are the 2007 prices reported by U.S. Energy Information Administration /
Annual Energy Outlook 2010, adjusted by 10% to reflect higher fuel prices on the Great Lakes.
Table 1-8 Europe Bren Spot Price FOB (Dollars per Barrel)
YEAR
2007
2008
2009
JAN
53.68
92.18
43.44
FEE
57.56
94.99
43.32
MAR
62.05
103.64
46.54
APR
67.49
109.07
50.18
MAY
67.21
122.8
57.3
JUN
71.05
132.32
68.61
JUL
76.93
132.72
64.44
AUG
70.76
113.24
72.51
SEP
77.17
97.23
67.65
OCT
82.34
71.58
72.77
NOV
92.41
52.45
76.66
DEC
90.93
39.95
74.46
Source: U.S. Energy Information Administration, available here:
http ://www. eia. sov/dnav/pet/hist/LeafHandler. ashx?n=pet&s=rbrte&f=m
Release Date: 10/27/2010
v It should be noted that EPA's final rule contains a fuel availability waiver if 10,000 ppm fuel is not available on
the lakes that would allow operators to use fuel with a higher sulfur content (see 40 CFR 1043.95).
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Figure 1-6 Weekly Price Comparison No. 2 Diesel vs. FOB Crude
$6.00
$5.00
$4.00
$3.00
$2.00
$1.00
$0.00
Weekly U.S. No 2 Diesel Retail Sales by
All Sellers (Dollars per Gallon)
Weekly All Countries Spot Price FOB
Weighted by Estimated Export Volume
(Dollars per Barrel)
-- $140
-- $120
$160
-$20
$0
Jan 31, Oct 28,
1993 1995
Jul 24,
1998
Apr 19,
2001
Jan 14,
2004
Oct 10,
2006
Jul 06,
2009
Apr 01,
2012
Source: Energy Information Administration
(http://www.eia.gov/dnav/pet/pet pri wco k w.htmX World Crude Oil Prices, Release Date
11/3/2010. Excel file name pet_pri_wco_k_w.xls
Depending on the reference fuel price (2008 average, June 7, 2008, and July 10, 2009)
this study estimates switching to 100 percent MDO would increase fleet fuel costs by 28 to 63
percent in 2012, based on the 2008 average price, and 47 to 76 percent, based on the $100/MT
price premium. It is difficult to evaluate these results because the study does not provide the
underlying data, even for the most basic inputs such as industry fuel volumes by fuel type.w'x
The adjusted freight rates were obtained by "applying the various fuel costs to the 2008
average daily fuel consumption, and using an estimated average daily time charter cost of vessels
with a 10% increment for trade costs."41 The estimated freight rate increases range from 6 to 17
percent, in the base case, and 9 to 21 percent in the premium case. Again, there is not enough
information to evaluate the impact of fuel cost increases on freight rates as freight rata data is not
provided. However, in this analysis fuel costs appear to be about 50 percent of the industry
average freight rates.
To estimate mode shift, the analysis applies a modal shift factor to the fuel cost increase.
The result is an estimate in the percentage of cargo that will shift to a different transportation
mode. The modal shift factor was derived from the MARAD 2008 study described above. This
was done by "scal[ing] from the reported mode-shift plot from grain" and then adjusting this for
energy intensity.42 The estimated modal shift factor is 0.243 for grain traffic and 0.225 for
w "While the consultant has used the data provided to offer some conclusions about the potential consequences of
the proposed fuel regulations the confidentiality agreements precluded disclosing all the calculations by which they
have been developed."
x For example, there appears to be an error in CSA's Table 1, as the proportion of consumption does not add up to
100 percent.
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petroleum traffic, resulting in an estimated mode shift of 7 to 12 percent of cargo for grain and 6
to 14 percent of cargo for petroleum. It is not clear, however, how the mode-shift plot was
scaled, or how it was adjusted, and no details are provided. Without a greater detail of how these
modal shift factors were derived, it is not possible to understand whether they are appropriate.
The derivation of the modal shift factors is important because the CSA factors do not seem to be
consistent with the graphics in the MARAD 2008 study. Specifically, the MARAD 2008 study
shows a negligible positive relationship between fuel price and increased cargo for petroleum.
For grain the relationship is steeper, especially at a price increase of about $2.50 per gallon, but
this may be due to an actual difference in cargo volumes for 2002 and 2005 versus projected
volumes for later years (i.e., there is a kink in the graph that may be due to data differences).
In any case, as noted elsewhere in this section, the MARAD 2008 study was not intended
to evaluate the impacts of a limited price increase on a specific market. It was intended to
examine the impacts of systemic fuel increases across the economy due to rising oil prices. It
uses a generalized cost approach that models the economy as a whole. In the MARAD 2008
study there are at least two sources of mode shift: fuel price increases for competitive modes
(truck, rail, marine) and impacts on the demand for transportation services. In general, as fuel
prices increase for all sources, it becomes more attractive to use intermodal transportation chains
to take advantage of low cost marine services to reduce total transportation costs. Thus, instead
of finding that as marine fuel prices go up demand for marine transportation services goes down,
and the marine transportation market experiences loss of cargo, the MARAD 2008 study finds
that as oil prices go up across the economy the marine transportation market can be expected to
increase cargo carried as it becomes less expensive compared to other transportation options, and
as truck/ship intermodal options become more attractive.
The CSA study also includes a qualitative discussion of the impacts of marine fuel price
increases on specific markets: grain (Thunder Bay to Quebec City and Montreal); salt
(Goderick/Windsor to Toronto); stone/aggregate (Manitoulin to Cleveland); petroleum products;
and steel. The authors specify that iron ore and coal were not examined because for
infrastructure and other reasons they are not vulnerable to shift, although iron ore was examined
in the context of a discussion of potential production shift for steel. These discussions also
include estimates of mode shift in terms of percent of cargo diverted, although these estimate are
not explicitly calculated; instead the discussions extend the results for grain and petroleum
described above.
The discussion of the grain market highlights the features of this market that support the
earlier estimate of a 12 percent mode shift. The discussion of the salt market concludes that
"even with increased EGA costs, rail and truck would not compete for this trade."43 For the
stone market, the CSA study included a competitive radius analysis for stone delivered to
markets in Cleveland and Akron, OH. The study then applied qualitative arguments to conclude
the nature of the market suggests an estimated shift of 20 percent based on a "reasonable"
expectation of a shift twice that of grain. With regard to petroleum the discussion notes that
while the marine mode is expected to recover some of the market from railroads, that recovery
would not occur as a result of increased marine fuel costs; this opportunity cost is estimated to be
about 11.3 percent. With regard to the steel market, the study notes that transportation costs of
iron ore and coal to steel mills are not significant components of the cost of manufacturing steel.
Transportation costs are not large components in the price of either coal or iron ore, and the steel
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mills examined do not have rail alternatives. Nevertheless, the study concludes that a rate
increase of 10 percent or more could lead steel manufacturers to relocate production to a lower
cost facility.44
While this study provides important insight on the questions that should be investigated
with regard to the impacts of increased fuel costs on Great Lakes trade, for the reasons outlined
above, the results should be considered with caution.
1.7 European Studies of the Potential Impacts of the 2008
Amendments to MARPOL Annex VI
Since the 2008 adoption of amendments to MARPOL Annex VI setting more stringent
NOx and fuel sulfur limits, several studies have been performed by government and industry
groups in Europe that examine the impacts of those new standards on their shipping industry.
These studies are briefly described in this section. In addition, two summaries have been
prepared, one by Entec (July 2010), commissioned by the shipowner associations of Belgium,
Finland, Germany, Holland, Sweden and UK45 and one by the European Maritime Safety
Agency (October 2010).46 Note that most of these studies refer to marine diesel fuel meeting the
EGA 1,000 sulfur limit as "MGO."Y
1.7.1 European Cost Studies
1.7.1.1 Ministry of Transport and Communications, Finland Study, 2009.
Each of the studies discussed below contain an analysis of the costs of complying with
the more stringent 2015 EGA fuel sulfur limits, either on a national basis, a European basis, or a
ship basis. The Finnish study is notable because it is the first such study.
Using a range of fuel prices for MGO (0.1% sulfur), this study estimates the maximum
additional cost for ships operating in Finland and Finnish ships, given the difference in price
between MGO and HFO (1.5% sulfur) that is currently used by ships operating in the Baltic and
North Sea EGAs.47 Estimated additional costs are developed by estimating fuel consumption
costs at each of the HFO and MGO prices and calculating the difference between them. This
information is used to create a linear relationship between the price differential and additional
costs, which are then applied to price differentials that may occur in the future. These costs are
then allocated among economic sectors based on the contribution of that sector to Finnish
imports and exports, suggesting that the forest, construction, and chemical industries will be
most affected. While the authors suggest that rising fuel prices will be incorporated into freight
rates over time and that excessively high fuel prices might lead to a modal shift,48 they provide
no analysis to support these outcomes.
Y While there are small differences in the fuel characteristics of MDO and MGO, these are both distillate fuel and
are functionally the same. The price difference between MGO and MDO is small, averaging about +/1 percent.
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1.7.2 European Cost/Benefit Studies
1.7.2.1 UK Maritime and Coastguard Agency and AEA Studies, 2009.
These reports, performed by Entec49 for the UK Maritime and Coastguard Agency and by
AEA50 for the European Commission, are cost and benefit studies that analyze the effects of the
revised MARPOL Annex VI regulations on different parts of Europe. Both of these studies state
that emissions from ships make significant contributions to air pollution, that these emissions are
expected to increase over time, and marine emissions could surpass land-based emission sources
over time if further action is not taken. The main difference between these two reports is that the
UK report estimates the total costs in 2020 are greater than the estimated benefits in 2020, while
the AEA study estimates that the benefits far outweigh the costs in 2015 and 2020. There are a
number of variables that lead to these different results, including geographic area and traffic,
baseline scenario, compliance strategies, models used, monetized benefits included, fuel prices,
and abatement costs.
With respect to geographic area and traffic, the UK study looked at an area 200 nautical
miles from the coastline, extended further East to ensure a more complete coverage of the North
Sea. This study did not look at benefits to any other country, nor did the SOx Emission Control
Area (EGA) change throughout different scenarios as it focused on the North Sea and English
Channel EGAs. The AEA study, on the other hand, looked at most of Europe and presented
different cost and benefit scenarios based on both existing and hypothetical future EGAs. This
study did model benefits to countries other than those adjacent to an EGA. The UK study also
looked at emissions benefits for different groups of vessels including: all vessels traveling within
the study area, vessels within the study area calling at UK ports, and vessels traveling within the
study area with a UK flag. The AEA study did not separate vessels by flag or port, rather it
looked only at all traffic in the study area.
With respect to the scenarios modeled, the UK study presents the cost and benefit
estimates for 2020 for two policy options. The "Do nothing" option represents a business as
usual case that includes the existing MARPOL Annex VI Regulations and the Sulfur Content of
Liquid Fuels Direction (1999/32/EC), which are already in place in the UK. The "Full
implementation" option implements the 2008 Annex VI amendments and focuses on three
different compliance strategies with respect to the portion of the fleet that would use alternative
abatement technologies. The AEA study examined the cost and benefits of a suite of scenarios
reflecting reductions resulting from both the 2008 amendments to Annex VI and the potential
addition of emission control areas. Scenarios were modeled for both 2015 and 2020. Table 1-8
below presents the scenarios analyzed.
A notable difference between the two studies is the baseline that was used to determine
emission reductions and therefore benefits. The UK study baseline is the "Do nothing" scenario
which includes an EGA fuel sulfur limit of 1.5% (i.e. Annex VI requirements prior to the 2008
amendments) the AEA study does not include these EGA fuel sulfur limits from the 1997 EVIO
protocol, nor does it include Tier I or Tier II NOx controls, the latter of which suggests a larger
reduction in emissions than would likely occur.
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The two studies also use different models. The impacts of the revised MARPOL Annex
VI regulations on baseline UK concentrations were estimated using the FRAME model. The
FRAME model was also used to investigate impacts on the ecosystems based on deposition and
critical load modeling. AEA used the LOTOS-EUROS model to estimate atmospheric
dispersion of ship emissions, and their effect on the European distribution of sulfur-and nitrogen
deposition, and on ground-level ozone and particulate matter concentrations. Background
concentrations (from other parts of the world) are provided by a global model, TMf, and
anthropogenic emissions are based on Gains Europe.
The largest difference between the UK and AEA studies are related to which benefits are
monetized in the total benefits estimate. While the AEA study quantifies fifteen different health
impacts, the UK study only looks at three health benefits - which results in substantially lower
monetized benefits presented in the UK study. Although neither study presents monetized
ecosystem impacts, the UK study did monetize benefits from reduced building and material
damage and presented a value of ฃ6.3 million in benefits (ฃ2009 prices and present value). The
AEA study did not expand the analysis to cover building or crop damage.
The two studies also use different fuel prices. The AEA study fuel prices are adapted
from the 2009 Purvin and Gertz study. The UK fuel prices are derived from IEA historic data.
As fuel prices comprise a majority of the cost of compliance with the revised Annex VI, the
larger fuel differential prices used by the UK study could contribute to costs being higher than
benefits.
Finally, each study discusses the estimated costs of abatement technology for both NOx
and SOx. However, the UK study states that "there are currently no defined NOx EGAs and
thus the Tier III standards do not apply. Therefore, end of the pipe technology, such as selective
catalytic reduction, is not considered likely to be necessary unless a NOx EGA is designated."
For this reason, Tier III NOx abatement costs are not discussed in the UK study. Further, the
UK study assumes that Tier I and II technologies are negligible when compared to the costs
associated with complying with the sulfur requirements and these costs are not considered. The
AEA study does present costs for Tier I, Tier II, Tier III, and Tier I retrofit technologies on a per
vessel basis. Both studies present estimated scrubber costs on a per kilowatt basis.
With regard to results, the AEA study presents benefits that exceed the costs in all
scenarios, while the UK study presents costs that exceed the benefits. However, the UK study
presents costs that are annualized (indicating the present value of a stream of costs) while the
benefits are annual. It is not generally considered appropriate to compare annual and annualized
values. This makes it difficult to make a direct comparison of the UK costs and benefits
presented in the study. The total costs and benefits presented in each study are shown in Table
1-9 below.
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Table 1-9 Cost and Benefit Totals Presented in Each Study for 2020
Annualized costs
Annual costs
Annual health benefits
UK - IMPACTS ON
THE UK FROM ALL
VESSELS IN THE
STUDY AREA
(XMILLION)
800 to 3,600
300 to 700
AEA: BALTIC SEA,
NORTH SEA AND
THE ENGLISH
CHANNEL AS SECA
(MILLION)
900 to 4,600
10,000 to 23,000
AEA: INCLUSION OF
MEDITERRANEAN
AND THE BLACK
SEA IN THE SECA
2,000 to 12,000
14,000 to 32,000
The UK study states that it underestimates the benefits, however, review of the study and
the fact that Tier III costs are not presented indicate it likely also understates the costs. However,
the UK study only presents benefits to the UK while the AEA study presents benefits to
numerous countries surrounding the study area. The UK study appears to focus more on the fuel
price impacts of the global standards changing from 0.5% sulfur to 0.1%, while the AEA study is
focused on presenting a complete cost and benefit analysis for most of Europe.
1.7.3 European Modal Shift Studies
The five studies included in this section each examine the impacts of the new 0.1 percent
EGA fuel sulfur requirement on marine transportation in Europe and whether the increase in
costs is likely to result in a transportation mode shift away from marine. Two of the studies were
performed for the European Commission (COMPASS, SKEMA), one was performed by a
government (Swedish Maritime Administration), and two were performed for industry
organizations (ESCA, ISL).
The primary focus of each of these studies is on short-sea shipping, although the Swedish
Maritime Administration Study also includes "other" ships in their analysis.2 Short-sea shipping
refers to transportation by container or truck trailer through a combination of land and marine
transportation links, with the water link on RoRo, LoLo, or container feeder vessels, or ferries.
This is an important distinction because the Great Lakes analysis contained in this report focuses
on bulk shipping: coal, iron ore, grain, crushed stone, which are not as easy to switch to land-
based transportation as are containers or truck trailers. Consequently, the results of these studies
may not be directly transferrable to the Great Lakes situation. In addition, while each of the
European studies examines the impacts of the 0.1% fuel sulfur requirement in the Baltic and
North Sea EGAs, the geographic scope of the studies differs, as do the types of transportation
studied. These differences, along with their use of different methodologies and fuel prices, make
it difficult to compare results across studies and draw any general conclusions.
1.7.3.1 Swedish Maritime Administration Study, 2009.
The Swedish Maritime Administration was charged by the Swedish government to study
the consequence of the Annex VI fuel sulfur limits.57 They prepared this report in consultation
z In contrast to Europe, where as much as 40 percent of all freight moved is through short-sea shipping, the United
States does not have a strong short-sea sector, especially on the Great Lakes (see 1.7.2 for studies of the benefits of
short-sea shipping in the United States).
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with 18 organizations representing other Swedish government agencies and a variety of industry
and public-interest groups.
The transportation mode shift analysis is performed using a freight model developed by
SIKA (Swedish Institute for Transport and Communications Analysis) and the four Swedish
transport administration agencies. The model is a type of geospatial model that "minimizes the
aggregated logistics costs ... for all freight transported during one year" and "focuses solely on
selection of route and transport chain."52 The analysis is performed for freight transported by
ship to and from Sweden, with demand held constant in terms of O/Ds and volumes
transported.53 Baseline fuel prices are the average value of prices during October/November
2008 in Rotterdam ($365 for 1.5% sulfur); fuel prices are weighted by ship category for the
baseline scenario to reflect the range of fuel sulfur limits currently experienced (some vessels use
low sulfur fuel in response to the Swedish Fairway Dues program). The control cases are based
on the October/November 2008 Rotterdam price for 0.1% sulfur fuel (Scenario 1; $662), 75
percent higher (Scenario 2; $1,158) and 150 percent higher (Scenario 3; $1,650).
With regard to results, the analysis suggests that switching to 0.1% sulfur fuel in the
Baltic and North Sea EC As can be expected to decrease ship cargo volumes. The estimated
decrease ranges from 2 percent (Scenario 1) to 10 percent (Scenario 3). The lost marine cargo
volumes are expected to switch to truck or rail transportation.
There are several aspects of this study that suggest the results for Scenarios 2 and 3 may
be overstated. Specifically, while the price of distillate in both of these scenarios is increased to
reflect increases in the prices of a barrel of oil by 75 percent and 150 percent, respectively, the
baseline residual fuel price does not appear to be adjusted. This would result in an exaggerated
price differential between residual and EGA-compliant fuel. In addition, the fuel prices for
trucks and rail are not adjusted, making them relatively less expensive. As stated in the report,
"the price of fuel for trucks has been kept the same in all scenarios." The given reason for doing
this is to avoid price impacts from "increased competition for fuel between truck and shipping,"
but it is not clear how keeping truck fuel prices constant addresses that concern. This would also
tend to increase the potential transportation mode shift impacts in Scenarios 2 and 3 since truck
fuel prices are not adjusted as marine fuel prices are increased.
Finally, the model does not take road and rail infrastructure constraints into account,
particularly with regard to transportation across key bridges, which may make transportation
modal shift to rail and truck less practical ("... a part of the transported freight (e.g. metal
products) is transferred from routes via the Port of Gothenburg to routes via the Oresund Bridge,
which in reality must be seen as less likely since traffic already at present on the bridge is very
significant. As previously mentioned, capacity shortages of the rail network have not been taken
into account in the model." These constraints, however, can affect outcomes in all scenarios,
potentially lessening the likelihood of transportation mode shift.
Scenario 1 is roughly comparable to the study contained in Chapter 2 of this report in that
it is based on current fuel prices for marine and land sources and reflects a $297 price differential
between current EGA fuel and distillate fuel that meets the 1,000 ppm sulfur limit. The results of
Scenario 1 are consistent with the study contained in Chapter 2 of this report, in that a shift to
EGA fuel expected to result in a 2 percent decrease in marine cargo volumes and a 1 percent
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increase in truck cargo volumes; this transportation mode shift in actuality may be offset by
capacity constraints not considered in the Swedish modeling.
The report concludes: "The difference in costs demonstrates the need, at a high level, to
pursue the issue of instituting new control areas outside SEC A and the proposed Emission
Control Areas (EGA) since this is no longer merely an environmental question but a question of
finding a balance between environmental measures and fair competition for Swedish industry
primarily within Europe but also globally." AA'54
1.7.3.2 ESCA Study, 2010.
This study was performed by the Universiteit Antwerpen and Transport & Mobility
Leuven for the European Community Shipowners' Associations (ESCA), which represents
shipowners' associations from twenty-one European countries.55
The study uses a cost approach to evaluate the impact of 0.1% sulfur EGA fuel for
specified O/D pairs. An initial analysis is performed to examine the impacts on ship operating
costs; this is compared to the results of a stated-preference analysis based on a survey of ship
operators. The main focus of the study is a second approach that uses a cost analysis similar to
that presented in Chapter 2 of this report to examine the likelihood of transport mode shift for a
set of thirty O/D pairs. The analysis is performed for several fuel price scenarios, with the price
differential between residual and EGA-compliant fuel ranging from $222 to $444 per ton.
For the low fuel differential case, the study estimates an average increase in total ship
costs of 19.1 percent, on average, leading to an estimated average 11.5 percent increase in freight
rates, across 16 O/D pairs. For the high price scenario, the results are a 30.6 percent in operating
costs and 19.7 percent increase in freight rates.
With regard to transport mode shift, the study examines 30 O/D pairs for four areas
(Germany/Denmark to Sweden; English Channel; West Europe - Baltic States; West Europe -
Scandinavia). There are up to three transportation alternatives for each O/D pair, and all three
fuel price estimates are examined. The analysis compares the adjusted marine freight rates to
land-based freight rates to determine if transport mode shift is likely. The methodology uses a
cost function approach. Cost functions are developed for both marine and road haulage to
estimate freight rates based on distance at various fuel prices (marine) or geographic areas
(road). The estimated freight rates for a given marine fuel price are then compared for each O/D
pair; a transport mode shift is expected if the difference between marine and truck freight rates is
greater than ten percent; between zero and ten percent the market is deemed to be "competitive."
With regard to cost changes, the authors conclude that "the use of MGO is expected to
increase the transport prices particularly on the origin-destination relations with medium or long
short-sea section. Such a price development might eventually trigger a shift from medium and
long short-sea routes to shorter short-sea routes or a "truck only" alternative without any short-
sea section." These results are distance sensitive: the longer the sea link, the larger the impact.
As a result, the impacts of a fuel switch are expected to vary by region. The authors also note
^ A SECA is a Sulfur Emission Control Areas, in which only the more stringent fuel sulfur limits, and not the more
stringent Tier III NOX limits, apply. The Baltic and North Sea areas are SECAs.
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that "the observed shifts in price differences incurred when introducing MGO as a base fuel in
the EGA would undoubtedly lead to changes in the modal split at the expense of short-sea
services" and that '[tjraffic losses for short-sea services force short-sea operators to reduce
capacity, to downsize vessels deployed ... [which could] trigger a vicious cycle of capacity
reduction and lower frequencies ultimately leading to a poorer position for short-sea
services.. ,"56 but the analysis does not support these broad conclusions.
With regard to the specific results of the study, the study does not appear to adjust truck
fuel prices to reflect the higher distillate fuel prices in the medium and high marine fuel price
scenarios. Therefore, the focus here is on the low price scenario, which reflects fuel prices and a
fuel price differential more similar to those used in this study and the Swedish study (HFO 1.5%
$278; MGO 0.1% $500; price differential $222/ton). For this low price scenario, short-sea
shipping is favored to truck transportation or remains competitive for all but two routes. For one
of these, Scenario 3.2, Dieppe-Kaunas, short-sea shipping was not favored in the baseline FIFO
case. For the other, Scenario 3.6 Amsterdam-Kaunas, short-sea shipping changes from being
competitive in the HFO case to favoring truck transportation in the MGO case.
1.7.3.3 SKEMA Study, 2010.
This study was performed by SKEMA for the European Commission, Directorate-
General for Energy and Transport.5 SKEMA is the Sustainable Knowledge Platform for the
European Maritime and Logistics Industry.
This study uses two models, TAP AS (a supply chain model) and NECL (a cost model) to
estimate the impacts of switching from residual to distillate fuel on two type of shipping, LoLo
(for containers) and RoRo (for trailers) shipping. The analysis was performed for four sets of
O/D pairs, with some overlap between the two methodologies.
Both of these models predict a transfer of cargo to land-based transportation. The
TAPAS model, which was used to examine cargo going from Klaipeda to Harwich using five
different routes, predicts that by 2015 most cargo movements will occur on the route through
Rotterdam which has the shortest marine leg (less than 10 percent share of the total route). The
NECL model, which was used to examine cargo going from Gothenburg to Dortmund,
Dortmund to Manchester, and Vilnius to Dortmund as well as Klaipeda to Harwich, also predicts
a loss of cargo to truck transportation; this transportation mode shift would be mitigated if
scrubbers become an alternative. This analysis also examines a scenario in which the EGA fuel
sulfur limit is changed to 0.5 percent, which predicts a much smaller transportation mode shift.
This study is based on the Purvin and Gertz fuel prices (see Section 1.7.4, below).
However, it does not supply much information on the models themselves. Truck fuel prices do
not appear to be adjusted to reflect higher oil prices, again giving truck transportation a cost
advantage over marine freight prices. Trucks are also given an advantage with respect to
capacity (75 percent, as opposed to 50 percent for marine); without a study of the industry, it is
not possible to determine if this difference is reasonable.
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1.7.3.4 COMPASS Study, 2010.
This study was performed for the European Commission DG Environment by Transport
& Mobility Leuven and Nautical Enterprise.58 It examines the impacts of a set of five policy
scenarios to improve environmental performance for European short-sea shipping, on four vessel
types (RoRo, RoPax small, RoPax large, LoLo).BB The policy initiatives include reducing the
sulfur content of fuel used in the European EGAs, the EU eMaritime initiative,cc and greenhouse
gas (GHG) requirements. Impacts are examined by vessel type and length of voyage for
European routes covering the North Sea, Baltic Sea, Atlantic Coast and Mediterranean Sea.
Both trucking and rail are considered as alternatives to marine transportation. The study used the
Purvin & Gertz fuel prices also used in the SKEMA study.
The methodology is based on a business operation model, the goal of which is to
determine the least cost method to ship goods. It is a closed loop model in which demand for
transportation services is not driven by economic activity. Instead, demand is determined
outside the model and is held constant. The model assumes that the amount of resources spent
on transport is fixed and is the same for all policies. In this model, an increase in transportation
costs results in a reduction in transportation services provided given the fixed transportation
services budget.
This study finds that the largest policy impact comes from the EGA 1,000 ppm fuel limit.
This requirement is estimated to increase total costs from 6 percent for RoPax small to 29
percent for LoLos. The resulting decreases in cargo volumes range from 1 percent for RoPax
small to 10 percent for LoLo routes. The results also indicate that cargo volumes for truck
transportation will also decline. The analysis concludes that a combination of all policy options
considered will result in decreases in the modal share of short-sea shipping between 1 percent
and 7 percent. Finally, the results suggest that the decrease in cargo tends to increase as the
distance travelled increases, although this is not true in all cases.
These results of this study should be treated with caution. The impacts of the model may
be overstated due to the closed nature of the model, which artificially restricts spending in the
transportation sector. In fact, the amount of transportation services provided is driven by
demand and not by a fixed transportation budget. In addition, a small increase in transportation
costs may not result in a significant reduction in transportation services. This is because
transportation services are only a small part of the total costs of goods produced, and
manufacturers may be able to pass on a portion or all of an increase in transportation prices.
These impacts cannot be assessed in a closed model such as the one used in this study.
1.7.3.5 ISLStudy, 2010.
The study performed by the Institut fur Seeverkehrswirtschaft and Logistik (ISL) was
originally commissioned by the Federal Ministry of Transport, Building and Urban Development
BB RoPax are RoRo vessels that also transport passengers.
cc According to the study, "the EU eMaritime initiative is aimed at fostering the use of advanced information
technologies for working and doing business in the maritime sector. It is expected that this initiative will reduced
delays in ports through more efficient documentation submission and review processes, and, improved coordination
of inspections by authorities." (p. 13)
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(BMVMS) and the German Shipowners' Association (VDR) and was completed by VDR and
the Association of German Seaport Operators (ZDS). 59 Like the other European study, this
study examines the impact of the EGA 0.1% fuel sulfur requirement on short-sea shipping in the
North Sea and Baltic Sea, focusing on truck trailers transported by RoRo vessels and containers
transported by LoLo vessels.
The analysis is performed separately for RoRo and LoLo markets. For each market, the
main shipping corridors are defined and a set of O/D pairs are specified. Then, for each corridor,
the impacts of higher fuel prices on shipping costs are estimated based on the contribution of fuel
costs to total shipping costs for that corridor. Finally, the risk of transportation mode shifts is
estimated for each corridor using a logit function approach. The analysis is performed for two
sets of future fuel prices representing a high price case (HFO: $709/tonne; MGO $l,182/tonne)
and a low price case (HFO $514/tonne; MGO $773/tonne); current fuel prices are taken as being
$450 and $650/tonne for HFO and MGO, respectively.
With respect to RoRo shipping, the study estimates marine cost increases of 14 to 37
percent in the high fuel price case and 8 to 21 percent in the low fuel price case. The estimated
mode shift risk for these corridors ranges from 14 to 46 percent, with an average of 22 percent
for the high fuel price scenario; no transport mode risk estimates are reported for the low fuel
price alternative. With respect to short-sea container shipping, the study estimates marine cost
increases of 21 to 28 percent in the high fuel price case and 13 to 18 percent in the low fuel price
case. With regard to short-sea shipping, the estimated mode shift risk for these corridors ranges
from 25 to 35 percent with an average of 27 percent in the high fuel price scenario, and from 16
to 23 percent with an average of 17 percent in the low fuel price scenario. Results are also
presented for the feeder ship case.
These results are significantly different from the results of other studies discussed in this
section. However, these results are problematic due to the way in which truck fuel costs were
handled. First, while the authors report that truck fuel prices are adjusted to reflect future fuel
prices, they state that the adjustment was small. They note that "[t]he forecast rise in the market-
dependent proportion of the fuel costs is only slightly above the inflation rate, at least for the
lower limit of the corridor up to 2015. This means that only a small proportion of the rise
remains after discounting to 2010 prices."60 This is surprising given assumed increase in the
price of distillate fuel of 82 percent in the high price case and 19 percent in the low price case.
Alternatively, the authors may be assuming that the price of marine distillate fuel (MGO) is very
different from the price of land distillate fuel; if this is the case, it is not explained. In either
case, the negligible adjustment for truck fuel prices gives road transportation a large advantage
over marine transportation in the analysis. Second, the analysis does not consider that, all things
being equal, higher fuel prices for both modes would result in marine transportation becoming
more advantageous compared to land transportation, all other things remaining equal. This is
because as fuel prices increase, the more efficient mode of transportation on a ton-mile basis
becomes more advantageous, not less.00 However, because results are not provided on a ton-
DD See for example the MARAD report described in Section 1.6.2.2, above. One peer reviewer notes that "the
tradeoff between [marine and land transportation] may not be linear. As the price of oil goes up, the greater
efficiency of using the marine mode might provoke a shift of freight to marine over rail; this would happen at the
extremes of price when the cost of fuel is so great that it begins to trump the cost of intermodal handling needed to
shift as much to marine as possible." (Belzer)
1-40
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
mile basis, it is hard to evaluate the results of this study's methodology with respect to
efficiency.
Finally, the analysis adjusts the percent contribution of fuel costs to total costs, for each
of the future fuel price scenarios, although this is not explained. Nor do the authors explain
whether the assumption that labor costs, capital costs, and other variable and fixed costs will not
change as fuel prices increase by 20 percent to 80 percent is reasonable. By assuming all other
costs are constant, marine transportation is again disadvantaged compared to truck costs with
respect to increasing fuel prices, since it means that marine operating costs are adjusted a
significant amount while truck operating costs are adjusted minimally if at all.
The final section of the report discusses policy options that may reduce the estimated
impacts of the EGA fuel controls. Ship-based measures include the use of scrubbers, measures
to reduce fuel consumption, and the use of alternative fuels. Other measures include increasing
the cost of land transportation and subsidizing sea transportation, and applying the 0.5 percent
2020 global sulfur limit in the Baltic and North Sea EGAs instead of the revised EGA fuel sulfur
limit. According to the results presented in this section, such a change in the fuel sulfur content
would decrease the risk of transport mode shift to 2 percent, on average, for the RoRo markets
and to 3 percent, on average, for the short-sea container markets. This analysis is performed for
2008, however, and may not be comparable to the analysis for 2015 performed for 0.1 percent
fuel sulfur described above. In addition, the analysis relies on a fuel price of about $515/tonne in
the high price case, which is very similar to the HFO price used in the low price analysis for the
1,000 ppm fuel sulfur limit. This price for FIFO suggests that the authors assume fuel meeting
such a limit would be residual fuel. Even assuming that an inexpensive 0.5% sulfur residual fuel
can be produced in the quantities needed for the Baltic and North Sea EGAs, which is by no
means certain, Purvin and Gertz (below) estimate that the cost increase of 0.5% sulfur fuel would
be significantly higher than assumed by ISL. If, alternatively, 0.5 percent sulfur fuel is a
distillate fuel, the advantages of applying the global fuel sulfur limit instead of the new EGA fuel
limits would be reduced.
With regard to the mode shift analysis, it is difficult to evaluate the methodology used
without a more detailed explanation of how these results were obtained. Specifically, it is not
clear how to evaluate the risk of shift without a better understanding of how the logit model was
constructed and the data inputs used to obtain those results, particularly the cost for the truck
alternatives and how the routes were evaluated (on a route basis or some other metric).
1.7.4 Purvin & Gertz Fuel Study, 2009.
Purvin & Gertz (PGI) performed a study for the European Commission on the impacts of
the Annex VI fuel sulfur limits on the European refining industry.61 In determining the refinery
investment and product pricing impacts, this study considered a number of scenarios for
producing 0.5% sulfur fuel to meet the global requirement and 0.1% sulfur fuel to meet the
SEGA requirement in the Baltic and North Sea.
PGI estimates that the price of 0.1% sulfur marine fuel will be in the range of $250 to
$300/tonne more than 1.5% sulfur UFO, which until recently, was used in the Baltic and North
Sea SEC As. PGI presents scenarios where 0.1% sulfur fuel could be produced as a residual or
1-41
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
distillate fuel. PGI states that most cases result in prices similar to MGO (distillate), even when
a 0.1% sulfur HFO is produced.
PGI also estimates that the 0.5% sulfur fuel will be in the range of $120 to $170/tonne
more expensive than heavy fuel oil meeting the global 3.5% fuel sulfur limit. The difference
between 0.5% sulfur fuel and HFO meeting the current 1.0% fuel sulfur limit in SEC As is
estimated to be in the range of $80 to $140/tonne. This range based on scenarios where HFO is
produced that meets the 0.5% sulfur limit. Although one scenario was modeled for the
production of a 0.5% sulfur distillate fuel, this scenario showed higher prices than current MGO
and was not considered in the range presented by PGI.
PGI bases its costs primarily on the desulfurization of residual fuel oil. However, this
report makes no assessment of the availability of low sulfur crude or low sulfur refinery
feedstocks that would be needed for this approach. Note that these crudes and feedstocks are of
high value to modern refineries. PGI's cost assessment assumes that these components are
available at the volumes needed to produce the projected amounts of low sulfur marine fuel.
This cost assessment also assumes that refiners would invest in residual fuel desulfurization
equipment rather than in equipment that would increase the distillate production. Given the
similar capital costs of the associated equipment and the much higher value of distillate products,
it is not clear that this would be the case.
1-42
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
Chapter 1 References
1 Prevention of Air Pollution from Ships, Sulphur Monitoring for 2009, Note by the Secretariat. MEPC 61/4,
February 2010
2 Transport Canada and U.S. Department of Transportation (2007). Great Lakes St. Lawrence Seaway Study, Final
Report, Fall 2007. Chapters.
3 See http ://www. marad. dot, gov/ships shipping landing_page/mhi home/mhi home. htm for more information
about MARAD' s America's Marine Highway Program
4 See the NOAA website "About Our Lakes - Lake by Lake Profile." Available at
http://www.glerl.noaa.gov/pr/ourlakes/lakes.html
5 California Air Resources Board (2008), Initial Statement of Reasons for Proposed Rulemaking: Fuel Sulfur and
Other Operational Requirements for Ocean-Going Vessels Within California Waters and 24 Nautical Miles of the
California Baseline, Appendix F: Evaluation of the Availability of Low Sulfur Marine Distillate Fuel for Ocean-
Going Vessels that Visit California, pg F-18. Note refers to MGO/DMA worldwide samples analyzed in 2006,
reported by Det Norske Veritas in 2007 for California ARE. This document is available at:
http://www.arb.ca.gov/regact/2008/fuelogv08/appffuel.pdf
6 Prevention of Air Pollution from Ships, Sulphur Monitoring for 2009, Note by the Secretariat. MEPC 61/4,
February 2010
7 See 73 FR 25097, May 6, 2008. http://www.epa.gov/fedrgstr/EPA-AIR/2008/Mav/Dav-06/a7999a.htm
8 See 69 FR 38958, June 29, 2004. http://www.epa.gov/fedrgstr/EPA-AIR/2004/June/Dav-29/all293a.pdf
9 Agriculture: A Glossary of Terms, Programs, and Laws, 2005 Edition, updated June 16, 2005. CRS Report for
Congress. Order Code 97-905. This document is available at http://ncseonline.org/nle/crsreports/05jun/97-905.pdf
10 Regulatory Impact Analysis: Control of Emissions of Air Pollution from Category 3 Marine Diesel Engines,
available at http ://www. epa. gov/otaq/regs/nonroad/marine/ci/420r09019 .pdf
11 Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at or above 30 Liters
per Cylinder - Information in Support of Applying Emission Control Area (EGA) Requirements to the Great Lakes
Region. EPA-HQ-OAR-2007-0586. December 15, 2009. See Docket ItemEPA-HQ-OAR-2007-0121-0586(l) at
http://www.regulations.gov.
12 Review of MARPOL Annex VI and the NOx Technical Code, Development of Standards for NOx, PM, and SOx,
Submitted by the United States. BLG 11/5/15, 9 February 2007. This document is available at
http://www.epa.gov/otaq/regs/nonroad/marine/ci/blgll-05-15-nox-pm-sox-united.states.pdf
13 See Summary and Analysis of Comments: Control of Emissions from New Marine Compression-Ignition
Engines at or Above 30 Liters per Cylinder. EPA-420-R-09-015, December 2009, Chapter 5. This document is
available at http ://www. epa. gov/otaq/regs/nonroad/marine/ci/420r09015 .pdf
14 The comments can be found in the docket for the rule (Docket ID No. EPA-HQ-OAR-2007-0121; all documents
in the docket can be found through http://www.regulations.gov). and are discussed in the Summary and Analysis of
Comments that was prepared for the rule (see http://www.epa.gov/otaq/oceanvessels.htm#regs).
15lllth Congress, "Department of the Interior, Environment, and Related Agencies Appropriations Act, 2010" and
associated legislative report, p. 181. "PROHIBITION ON USE OF FUNDS. SEC. 442. None of the funds made
available for the Environmental Protection Agency in this Act may be expended by the Administrator of the
Environmental Protection Agency to issue a final rule that includes fuel sulfur standards applicable to existing
steamships that operate exclusively within the Great Lakes, and their connecting and tributary waters."
16 See Chapters 2, 3, 5, 6, and 7 of the Regulatory Impact Analysis prepared for the rule, available at
http://www.epa.gov/otaq/regs/nonroad/marine/ci/420r09019.pdf
1-43
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
17 Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at or above 30 Liters
per Cylinder - Information in Support of Applying Emission Control Area (EGA) Requirements to the Great Lakes
Region. EPA-HQ-OAR-2007-0586. December 15, 2009. See Docket ItemEPA-HQ-OAR-2007-0121-0586(l) at
http://www.regulations.gov
18 Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at or above 30 Liters
per Cylinder - Information in Support of Applying Emission Control Area (EGA) Requirements to the Great Lakes
Region. EPA-HQ-OAR-2007-0586. December 15, 2009. See Docket ItemEPA-HQ-OAR-2007-0121-0586(l) at
http://www.regulations.gov
19 Environmental Impacts of a Modal Shift. Minnesota Department of Transportation, Ports and Waterways Section.
January, 1991.
20 Marine Transportation Study for the Ontario Marine Transportation Forum and the Ontario Ministry of
Transportation. Pre Summit Draft. November 2006.
21A Modal Comparison of Domestic Freight Transportation Effects on the General Public. Prepared for U.S.
Maritime Administration and National Waterways Foundation by Texas Transportation Institute, C. James Kruse, et
al. December 2007, Updated 2009.
22 Thomchick, Evelyn A., et al. Analysis of the Great Lakes/St. Lawrence River Navigation System's Role in U.S.
Ocean Container Trade. Final Report. Prepared for Save the River and Great Lakes United. August, 2003. See
http://news.smeal.psu.edu/news-release-archives/2003/dec03/report.html
23 Ibid, pg. 50.
24 Ibid, pp. 50 and 51.
25 Ibid, p. 52.
26 Industry Survey Series: Great Lakes Operators. 2005. U.S. Department of Transportation Maritime
Administration. This study can be found at http://www.marad.dot.gov/documents/Great Lakes Operators.pdf.
27 Four Corridor Case Studies of Short-Sea Shipping Services. Short-Sea Shipping Business Case Analysis.
Submitted to U.S. Department of Transportation Office of the Secretary. August 15, 2006. A copy of this report
can be found at http://www.marad.dot.gov/documents/USDOT - Four Corridors Case Study (15-Aug-06).pdf
29
! Ibid, p. 1.
Ibid, pg. 15.
30 Ibid, p. 49.
31 Ibid, pg. 11.
32 Great Lakes St. Lawrence Seaway Study. Final Report. Transport Canada, U.S. Army Corps of Engineers, U.S.
Department of Transportation, The St. Lawrence Seaway Management Corporation, St. Lawrence Seaway
Development Corporation, Environment Canada, and U.S. Fish and Wildlife Service. Fall 2007. A copy of this
study can be found at http://www.marad.dot.gov/documents/GLSLs finalreport Fall 2007.pdf Citation: p. 1.
33 Ibid, pp. 48-52.
34 Ibid, p. 50.
35 Impact of High Oil Prices on Freight Transportation: Modal Shift Potential in Five Corridors. Technical Report.
Prepared for the U.S. Department of Transportation Maritime Administration. October 2008. A copy of this report
can be found at http://www.marad.dot.gov/documents/Modal Shift Study - Technical Report.pdf Citation: p. 1.
36 Ibid, p. 1.
37 Ibid, p. 7.
38 Ibid, p. 33
1-44
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
39
Ibid, p. 48.
English, Gordon, et al. Study of Potential Mode Shift Associated with EGA Regulations in the Great Lakes.
Prepared for the Canadian Shipowners' Association by Research and Traffic Group. August, 2009. Available at
www.regulations.gov under Docket ID No. EPA-HQ-OAR-2007-0121-0027. or at
http://www.shipowners.ca/uploads/Documents/MODE%20SHIFT%20STUDY.pdf
41 Ibid, p. 5.
42 Ibid, pp. 6-7.
43 Ibid, p. 18.
44 Ibid, p. 30.
45 Entek UL Limited. Study to Review Assessment Undertaken of the Revised MARPOL Annex VI Regulations.
Final Report. July, 2010. A copy of this study can be found at
http://www.marisec.org/ICS%20Paper%20MEPC%2061%20-%20Annex%20-
%20MARPOL%20VI%20Final%20Report%20Julv%202010.pdf
46 European Maritime Safety Agency. The 0.1% sulphur in fuel requirement as from 1 January 2015 in SEC As - An
assessment of available impact studies and alternative means of compliance. 22 October 2010. A copy of this
report is available at http://www.marisec.org/ICS%20Paper%20MEPC%2061%20-%20Annex%20-
%20MARPOL%20VI%20Final%20Report%20Julv%202010.pdf
47 Ministry of Transport and Communications Finland. Sulphur content in ships bunker fuel in 2015 - A study on
the impacts of the new IMO regulations on transportation costs. April 2009. A copy of this report can be found at
http://www.jernkontoret.se/energi ochmiljo/transporter/pdf/sulphur content in ships bunker fuel 2015.pdf
48 Ibid, p. 30.
49 Maritime and Coast Guard Agency. Impact Assessment for the revised Annex VI of MARPOL - Final
Supporting Report. July 2009. A copy of this report can be found at:
http://www.marisec.org/ICS%20Paper%20MEPC%2061%20-%20Annex%20-
%20MARPOL%20VI%20Final%20Report%20Julv%202010.pdf
50 AEA. Cost Benefit Analysis to Support the Impact Assessment accompanying the revision of Directive
1999/32/EC on the Sulphur Content of certain Liquid Fuels. Report to the European Commission. December 2009.
A copy of this report can be found at: http://ec.europa.eu/environment/air/transport/pdf/CBA of S.pdf
51 Swedish Maritime Administration. Consequences of the IMO's New Marine Fuel Sulphur Regulations. May
2009. A copy of this report can be found at:
http://anchortime.com/portal/images/stories/PDF/Consequences%20of%20the%20IMOs%20New%20Marine%20Fu
el%20Sulphur%20Regulations.pdf
53 Ibid, p. 34.
54 Ibid, p. 5.
55 European Community Shipowners Associations (ESCA). Analysis of the Consequences of Low Sulphur Fuel
Requirements. January, 2010. A copy of this study can be found at:
http://www.ecsa.be/newsletters/itmmastudv.pdf
56 Ibid, p. 7.
57 SKEMA. Impact Study of the future requirements of Annex VI of the MARPOL Convention on Short-sea
Shippping" Project supported by the European Commission, Directorate- General for Energy and Transportation.
June 2010. A copy of this study can be downloaded from:
http://www.eskema.eu/defaultinfo.aspx?topicid=189&index=l (download document 1)
1-45
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Chapter 1 The Great Lakes and EPA's Marine Emission Control Program
58 Transport & Mobility Leuven and Nautical Enterprise. COMPASS: The COMPetitiveness of EuropeAn Short-
sea freight Shipping compared with road and rail transport, Final Report, prepared for European Commission DG
Environment. August 2010. A copy of this study can be found at:
http://ec.europa.eu/environment/air/transport/pdf/sss report.pdf
59 Institut fur Seeverkehrswirtschaft and Logistic, ISL. Reducing the sulphur content of shipping fuels further to
0.1% in the North Sea and Baltic Sea in 2015: Consequences for shipping in this shipping area. Final Report.
September 2010. A copy of this report can be found at:
http://www.reederverband.de/files/images/GermanISLStudvonSECAimpacts.PDF
60 Ibid, pp. 4-17.
61 Purvin & Gertz, Inc. Impacts on the EU Refining Industry & Markets of IMO Specification Changes & Other
Measures to Reduce the Sulphur Content of Certain Fuels. Prepared for Directorate General Environment. June,
2009. A copy of this report can be found at http://ec.europa.eu/environment/air/transport/pdf/impacts refmeries.pdf
1-46
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Chapter 2 Transportation Shift Analysis
CHAPTER 2: Transportation Shift Analysis
Transportation mode shift refers to users of a particular method of transportation
changing to a different method in response to a change in the market. In the context of the Great
Lakes, industry stakeholders commented that the application to the Great Lakes of certain
provisions of the Category 3 marine rule, and the long-term EGA fuel sulfur limits in
particularly, could lead to higher freight rates, which would make rail transportation more
attractive to shippers.
This chapter examines the impacts of the Category 3 marine rule on Great Lakes shipping
with respect to transportation mode shift. This study was carried out consistent with
Congressional recommendation1 and in response to specific Great Lakes stakeholder concerns.
We engaged with these stakeholders throughout the development of the analysis, particularly
with respect to the choice of scenarios studied, the methodology used, and important data inputs.
Appendix 2A contains a chronology of stakeholder outreach. Appendix 2A also contains
information about EPA's June 10, 2010 stakeholder workshop and a list of stakeholders who
attended the workshop. Appendix 2B contains the presentation used at that workshop.
This analysis is based on modeling performed for EPA by ICF International and its
subcontractor, Energy and Environmental Research Associates (EERA). A This chapter
summarizes the results of that modeling and describes key data inputs. The final contractor
report is contained in Appendix 2C. The analysis shows that compliance with the EGA fuel
sulfur requirements is unlikely to lead to transportation mode shift on the at-risk routes studied.
2.1 Summary and Results
This study examines the economic impacts of applying the Category 3 marine rule to
Great Lakes shipping. Consistent with stakeholder comments, the study focuses on the impacts
of increased fuel costs associated with the use of reduced sulfur EGA fuel. Section 2.2 contains
a description of the scope of the analysis with respect to the standards included, geographic area,
and ship types.
The analysis uses a route-based approach in which the impacts of applying the Category
3 marine program are estimated for a discrete number of trade routes that were identified by
stakeholders as being at-risk for transportation mode shift, source shift, or production shift due to
increases in fuel costs associated with the requirement to use EGA fuel on the Great Lakes. It
should be noted that the results of this analysis are specific to the O/D pairs examined, and are
not estimates of average freight rate increases across the fleet or estimates of average mode shift
impacts. However, if fuel cost increases of the magnitude expected from switching to EGA-
compliant fuel on the Great Lakes do not indicate a transportation mode shift on these at-risk
routes, where the price difference between marine transportation and the all-rail alternative is
close enough to be of concern to stakeholders, then transportation mode shift on other routes
without such price pressures would not likely be indicated. Section 2.3 explains the route-based
A Final Report: Analysis of Impacts of Category 3 Marine Rule on Great Lakes Shipping, September 2010. EPA
Contract No. EP-C-06-094, Work Assignment 3-16. See also Bibliography provided by the contractor, provided in
Appendix D.
2-1
-------
Chapter 2 Transportation Shift Analysis
approach and Section 2.4 describes the sixteen scenarios that form the basis of this analysis and
how they were selected. Finally, Section 2.5 describes key data used in the analysis.
Transportation mode shift analysis was performed for twelve Great Lakes trade routes
identified: four each for coal, iron ore, and grain (the four crushed stone scenarios are the
subject of source shift analysis; see Chapter 3). Transportation mode shift is assessed by
estimating the impacts of an increase in operating costs associated with the marine control
program on a scenario-specific freight rate and comparing the adjusted freight rate to an all-rail
alternative for that scenario. To perform this analysis, the optimal transportation route that
contains a marine link was identified for each scenario. This route is intended to maximize the
use of the Great Lakes across the overall route. It should be noted that nearly all of the Base
Case scenarios contain both a marine and a rail link, since each commodity must be transported
from the origination site to a Great Lakes departure port and from the arrival port to the end user.
Next, the total freight rate was estimated for each scenario that incorporates the combined marine
and rail segments. This freight rate is then adjusted to reflect the increased costs associated with
the control program. An activity-based fuel consumption and cost model is used that accounts
for vessel operation "at sea" and "in port." Then, an All-Rail Alternative route was identified for
each scenario. Next, a route-based freight rate was estimated for each scenario. This Base Case
freight rate incorporates the combined marine and rail segments. To determine if transportation
mode shift is indicated, the Base Case freight rate was then adjusted to reflect the use of EGA-
compliant fuel on the marine link. The incremental change in fuel costs associated with using
EGA-compliant MDO fuel was estimated using an activity-based fuel consumption and cost
model that accounts for vessel operation "at sea" and "in port." This adjusted freight rate is
called the ECA MDO Case freight rate. Finally, the ECA MDO Case freight rate was then
compared to the All-Rail Alternative Route freight rate for that scenario to determine which
route has the higher freight rate. If the freight rate for the ECA MDO Case is less than that of the
All-Rail Alternative Route, then no transportation mode shift to rail is indicated for these at-risk
routes. Appendix 2C contains more information about the transportation mode shift modeling.
The results of the analysis are set out in Table 2-1. In addition to the twelve
transportation mode shift cases, freight rate impacts are also presented for the four gravel cases.
2-2
-------
Chapter 2 Transportation Shift Analysis
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2-3
-------
Chapter 2 Transportation Shift Analysis
With regard to the impacts of the cost of complying with the 1,000 ppm EGA marine fuel
sulfur limit on total route freight rates, these results show an estimated increase in the Base Case
freight rate from about 1.2 percent to 16.6 percent, depending on the route. When considered by
commodity, the estimated freight rate increases reflect, in part, the share of the marine portion to
the total route. The stone and coal cases generally have a shorter marine link, and the estimated
percent increase in the freight rate for these scenarios is less than 5 percent. The coal and iron
ore cases have a longer marine link, with the freight moved by ship from the mine directly to the
using facility, and the estimated percent increase in the freight rate is about 17 percent and 11
percent respectively. In all cases, given that transportation is only one part of the cost of these
raw materials, which are only one input for final goods produced using them, these small freight
rate increases are unlikely to have a significant economic impact overall.6
With regard to transportation mode shift, the results contained in Table 2-1 show that the
EGA Case freight rate for the marine transportation mode is expected to remain well below the
All-Rail Alternative freight rate for ten of the twelve scenarios examined, with the difference
ranging from 6.5 percent to as much as 173 percent. Therefore, no transportation mode shift is
indicated.
Scenario 2 consists of coal transported from the Elk Creek Mine in Colorado through
South Chicago to the Georgia Pacific paper mill in Green Bay, Wisconsin. The initial results for
this scenario, reported in Appendix C to this chapter, suggest that the route-based freight rate for
the All-Rail Alternative ($24.43) is less than both the Base Case and the EGA Case freight rates
($26.03 and $26.64, respectively). This contrary result led EPA to perform additional research
with regard to this facility. The information obtained by EPA indicates that, due to quality
specifications for the coal used by this facility, the western bituminous coal used in this paper
mill is blended with other coal to obtain the product needed.2'3 The blended coal is obtained
from a source in South Chicago, where the KCBX Terminal can store up to 1 million net tons of
coal on site and can blend up to three coals for a customer. Consequently, this case was mis-
specified. However, it is unclear whether the transportation costs for this case should be based
solely on the cost of transporting coal from the terminal in Chicago to the facility in Green Bay,
or whether some portion of the transportation cost from the mine head(s) should be included.
This question could be important because this facility also receives coal by ship from Sandusky
and Ashtabula, Ohio, and vessels operating from those facilities are also required to use ECA-
compliant fuel.4 For these reasons, and because freight rates for a revised scenario are not
readily available, it is not possible to determine the potential for transportation mode shift
impacts for this route.
B One peer reviewer noted "[rjesearchers are correct to conclude that the increment of higher cost due to the fuel
change is so small that it is lost in the noise of price changes. Indeed, the cost of some of these raw materials, most
notably iron ore, coal, and grain, have increased dramatically just in the last year because of global demand for raw
materials such as iron ore and coal, and weather-related pressure on grain prices due to the drought and fires in
Russia in 2010. U.S. public policy that subsidizes corn production for ethanol has driven up grain prices even
further. The additional fraction of a percent of cost for cleaner fuel is a very small increment - one that by itself
would not be noticed in fuel price because other factors, such as the foregoing, put much greater pressure on price.
The recent flooding in Queensland may have a greater impact on commodity prices than the cost of lower sulfur
more refined fuel." (Belzer)
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Chapter 2 Transportation Shift Analysis
Scenario 6 consists of iron ore transported from Quebec Carrier Mining Co., in Quebec,
to ArcelorMittal, in Burns Harbor, Indiana. Transportation mode shift to rail is impractical for
this scenario because there is no access to a national highway or rail line at the mine in Quebec.
However, this scenario is similar to Scenario 9, which also involves transportation of cargo
(grain) the length of the St. Lawrence Seaway, and the All-Rail Alternative route for that
scenario can be used to estimate the likelihood of transportation mode shift for Scenario 6. As
indicated in Table ES-1, the All-Rail Alternative freight rate for Scenario 9 exceeds the EGA
Case freight rate and no transportation mode shift is indicated. The use of this rail alternative
would likely be even less favorable for Scenario 6 because it would require transportation by
ship to the rail port on the opposite shore of the Gulf of St. Lawrence, with associated cargo
transfers.
2.2 Scope of Analysis
This section describes specific characteristics of the Category 3 program and the Great
Lakes shipping industry that are included in the analysis, with respect to the year of analysis, the
geographic scope, the standards modeled, and the vessels included. In general, the application of
the long-term EGA standards to the captive fleet of Great Lakes Category 3 ships operating in to
all areas of the Great Lakes.
2.2.1 Year of Analysis
The long-term international EGA fuel sulfur limits will go into effect in 2015, pursuant to
Regulation 14 of MARPOL Annex VI. As a result, the year of analysis for this study ideally
would be 2015. Using 2015 as the year of analysis, however, would require estimated projected
values of several key inputs, one of the most important of which is estimated freight rates.
Freight rates reflect all costs associated with shipping, including fuel, insurance, repairs and
maintenance, crew, capital, overhead, dock fees and taxes. Because of the lack of publically-
available freight rates, this analysis relies on estimated rates (see below and Chapter 4 of the
study included in Appendix 2C). While it may be possible to project some freight rate inputs
(e.g., projected fuel prices using widely accepted data from a reliable source such as the Energy
Information Agency ), it is not possible to project the future prices of other inputs, such as labor
or capital costs. Similarly, some other costs important to the analyses contained in Chapter 3 are
not easily projected, including the price of crushed stone or electrical generating and steel sector
revenues.
As a result, the year of analysis for this study is 2007. The analysis estimates the impacts
of switching from unregulated fuel to EGA compliant fuel on the Great Lakes based on 2007
freight rates, fuel prices, and other conditions, and assumes the estimated results are indicative of
the expected impacts in 2015, all other conditions not affected by the program held constant.
This approach is appropriate because this is a route-based study that considers the impacts of the
program on freight rates for at-risk routes, as opposed to a longitudinal study like the analysis
performed for our Category 3 rule that compares aggregated estimated compliance costs to
monetized benefits for several future years.
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Chapter 2 Transportation Shift Analysis
2.2.2 Geographic Area
The broad geographic area included in this analysis includes the five Great Lakes and the
St. Lawrence Seaway. It should be noted, however, that the actual area of shipping activity is
scenario specific. In some scenarios activity may be limited to specified portions of one of the
Great Lakes; for others, activity may reach from the western edges of the Great Lakes to the
eastern edge of the St. Lawrence Seaway.
Although the Canadian program to implement the EGA standards is still under
development, this analysis assumes uniform application of the EGA fuel sulfur requirements
across the entire marine leg of each route, on both the U.S. and Canadian portions of the Great
Lakes/St. Lawrence Seaway system. This approach is therefore conservative in that it applies the
higher price EGA fuel to the entire marine segment. Chapter 1 explains the legal application of
the EGA standards to non-U.S. vessels on the U.S. portions of the Great Lakes.
2.2.3 Standards Included in the Analysis
Consistent with the concerns raised by Great Lakes stakeholder commenters on our
Category 3 rule, this analysis examines the impacts of complying with the 1,000 ppm EGA fuel
sulfur limit on the Great Lakes.
We do not consider the international interim 10,000 ppm fuel sulfur limit in this analysis.
That standard began to apply to the European EGAs in July 2010 and that will begin to apply to
the North American EGA in August, 2012. The application of this interim standard is not
expected to have a significant impact on Great Lakes shipping due to inclusion of a fuel
availability waiver provision for that fuel in the Category 3 rule (see Section 1.5.2.1). We also
do not consider the new tiers of global fuel sulfur limits that will apply outside areas that are not
designated EGAs. As noted above, the analysis assumes uniform application of the EGA fuel
sulfur requirements across the Great Lakes and therefore the global fuel sulfur limits are not
relevant.
We also do not consider the impacts of the engine NOx standards contained in EPA's
Category 3 program and in MARPOL Annex VI (see Table 1-5 and associated text). The Tier 3
engine NOx emissions standards apply to a ship operating in a designated EGA only if the ship
was constructed on or after January 1, 2016. Great Lakes vessels operate in fresh water and
therefore they have long service lives; new vessels are only rarely built and no new vessels have
been introduced into the U.S. fleet since the early 1980s. As a result it is difficult to anticipate
how that standard would affect the Great Lakes fleet beginning in 2016. The application of the
Tier 2 engine NOx limits and the standards for certain existing Category 3 engines0 is not
dependent on EGA designation for the Great Lakes and therefore are also not included in the
analysis.
c The MARPOL Annex VI Category 3 existing engine standards apply to marine diesel engines with a power output
of more than 5,000 kW and a per cylinder displacement at or above 90 liters installed on a ship constructed on or
after 1 January 1990 but priorto 1 January 2000 (Regulation 13.7.1). Note that this requirement depends on the
availability of a certified approved method (i.e., remanufacture system).
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Chapter 2 Transportation Shift Analysis
We do not consider the impacts of engine retrofitting in our analysis. Neither the Clean
Air Act requirements nor MARPOL Annex VI contain a mandatory requirement for a ship owner
to retrofit an existing vessel with cleaner, more efficient engines. Retrofitting Great Lakes ships
would be done in response to individual company concerns, for fuel efficiency, maintenance, or
environmental reasons. If a ship owner decides to retrofit, however, the owner may be required
to use an engine that meets the emission standards in effect at that time. We include an estimate
of the cost of engine retrofitting U.S. Category 3 ships in Chapter 7 in response to stakeholder
questions.
2.2.4 Vessels
With regard to the vessels modeled, we consider the impacts of the EGA fuel limits on
only vessels with Category 3 marine diesel engines. Category 3 engines are defined as engines
with a per cylinder displacement at or above 30 liters (40 CFR 94.2; 40 CFR 1042.901). These
are high power, low speed (rpm) engines that are typically designed to use HFO, although they
can be operated on distillate fuel. D Ships with smaller, Category 2, propulsion engines are not
included in this analysis because they do not generally operate on HFO. While these vessels
may often be indistinguishable from and perform the same function as vessels with Category 3
propulsion engines, vessels with Category 2 marine diesel propulsion engines are not typically
equipped with the fuel handling systems and storage tanks that are necessary to use HFO. In the
United States, marine distillate fuel used in vessels with Category 2 and smaller propulsion
engines is already subject to stringent fuel sulfur controls that are unaffected by EGA fuel
controls (see Chapter 1). Steamships that operate on the Great Lakes are also not included in this
analysis. While they also use HFO, they are exempt from the EGA fuel requirements due to
technical and safety issues (40 CFR 1043.95).
The St. Clair, John J. Boland, and the Hon. James L. Oberstar (formerly named the Charles M. Beeghly) in
layupfor the winter of 2002 in Sturgeon Bay. Source: Taken by and used with permission from Dick Lund,
available at: http://www.dlund.20m.com/custom.htmffiA.
D Chapter 6 discusses equipment changes that may be necessary for these vessels to operate on distillate fuel.
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Chapter 2 Transportation Shift Analysis
The analysis focuses on ships that operate solely on the Great Lakes and none of the
scenarios specifically address the impacts on "salties" (ocean-going ships that operate only
sporadically in the Great Lakes). As noted in Chapter 1, salties carry only a small share of cargo
on the Great Lakes, mainly grain for export. These salties will be required to use EGA compliant
fuel while operating within the North American EGA boundaries, the outer boundary of which is
about 200 nautical miles from the U.S. and Canadian coasts. While salties bring containers as
far down the seaway as Montreal we did not think it appropriate to include these ships in this
analysis because the purpose of the analysis is to evaluate the impacts of EPA's Category 3 rule
on Great Lakes shipping. In addition, container shipping has not caught on in the Great Lakes.
While several studies over the past 25 years have investigated the potential for Europe-to-Great
Lakes direct container shipping or feeder shipping links with East Coast Ports,E this market
continues to be undeveloped, in part because infrastructure (port facilities; draft restrictions) and
scheduling constraints make it difficult for short-sea shipping on the Great Lakes to compete
with the preferred rail alternative.17
2.2.5 Flag Neutral
This analysis is flag neutral. It is based on the fuel and vessel characteristics described in
this chapter and not on the characteristics for particular vessels operating under particular flags in
particular ways. As explained in Chapter 1, the application of the EGA fuel requirements on the
U.S. portions of the Great Lakes and St. Lawrence Seaway will apply to all ships, U.S.,
Canadian, and foreign, while operating in the regulated areas.
2.3 A Route-Based Approach
In choosing an analytic methodology used to perform this analysis, EPA considered
several approaches including general equilibrium modeling, a fleet average approach, and a
route-based approach.
The broadest type of economic modeling, general equilibrium modeling, examines the
impact of a program by modeling all of its submarkets simultaneously.0 This type of model can
be used to estimate the impact of a cost change across an entire economic system. However, this
type of broad-based modeling is not appropriate for this study. Available general equilibrium
models typically estimate impacts across an economy as a whole and are not constructed in a
way that would allow analysis of specific transportation links or examination of the extent to
which the raw materials and goods currently transported by one mode (ship) would shift to
E See Chapter 1 for a discussion of a few of these studies.
F While one peer reviewer included detailed comments about the future potential for container shipping on the Great
Lakes (Hull), other comments from industry representatives at a meeting sponsored by the Maritime Administration
in Cleveland, Ohio onFebruary 15, 2011 suggested they do not expect growth in this sector. One industry
representative noted that it is not possible to establish this type of container service without customers but the
customer is reluctant to use ships because there is no service. Lack of port infrastructure for handing containers,
draft restrictions, and ballast water restrictions were also noted as barriers to short-sea shipping. Finally, it was
noted that railroads are not subject to seasonality constraints.
G One peer reviewer noted that "the broadest type of economic model, a macroeconomic model such as that
incorporated in REMI and IMPLAN, would be the best to do a full benefit/cost analysis. This was not required for
this particular study, and thus it was not necessary to incur the additional cost, as mode, production, and source
shifts were in question in this case." (Belzer)
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another (rail or truck). It would also not be feasible to construct a model for the purpose of this
analysis as these models also require a great deal of data and information for potentially
hundreds of submarkets.
Similarly, while a fleet average approach like that used in the 2009 Canadian
Shipowners' Association study (see Section 1.6.3.2) would permit focusing on Great Lakes
transportation and reduces the data needs, it would also require a significant amount of
information, much of it considered to be confidential by the affected industry. Also, this
approach requires creating an average vessel and average route which may not be useful to
model the impacts of a fuel cost increase on a transportation market with as much variation as
the Great Lakes. This approach would also require development of a more robust estimation of a
modal shift factor for each type of cargo, which would still require a more thorough market-
based analysis.
The method used in this analysis is a route-based approach. Developed by ICF
International and their subcontractor, EERA, it is based on combination of geospatial and cost
modeling. In this approach, a shipping route is identified for each O/D pair using the Intermodal
Freight Transport (GIFT) model they developed with funding from the United States Maritime
Administration (MARAD). Then, freight rates are adjusted to account for an increase in fuel
costs and compared with the least cost land-based alternative. A route-based approach allows us
to take advantage of available information while recognizing the complexity of the Great Lakes
transportation system. It also allows us to tailor the research to those routes that are of most
interest to stakeholders: those that are at risk for transportation mode shift. This general
approach was shared with stakeholders at a workshop on June 10, 2010 and received general
support.
2.4 Selection of Origin/Destination Pairs and Shipping Routes
It would not be feasible to look at the impact of the EGA fuel sulfur limits on every
potential O/D pair for Great Lakes cargo using a route-based approach. As illustrated in Figure
2-1, there are thousands of potential combinations and the data requirements and modeling for
such an effort would be enormous, with respect to the types of ships, cargoes carried, and
frequency with which the routes are used. As a result, a more manageable approach was taken
for this study in which analysis is performed for a small number of specified O/D pairs believed
to be most at risk for transportation mode shift. This section describes the selection of O/D pairs
and shipping routes.
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Figure 2-1 Great Lakes Maritime Docks, Waterways and Railroads
Source: Department of Geography and Planning: Center for Geographic Information
Sciences and Applied Geographies (GISAG), 2007
2.4.1 Selection of Origin/Destination Pairs
To ensure that the study responds to the Great Lakes stakeholder concerns, we requested
industry assistance to identify the routes to be examined. Specifically, we asked stakeholders to
identify Great Lakes trade routes they believe are most at risk of transportation mode shift due to
an increase in operating costs (i.e., the price difference between marine transportation and the
all-rail alternative is close enough to be of concern to stakeholders).
Several stakeholders responded to EPA's request, resulting in a list of about fifty at-risk
trade routes for several commodities (e.g., iron ore/Duluth to Conneaut).H EPA selected 16 of
these routes, representing each of the four main cargoes carried on the Great Lakes (coal, iron
ore, grain, and stone)1 and a variety of geographic locations extending from Duluth, Minnesota,
to Baie Comeau, Quebec, to define the sixteen O/D pairs used in this analysis. These sixteen
O/D pairs were selected to include routes that were contained on more than one stakeholder list,
where possible.
We forwarded the 16 O/D pairs to the primary industry trade organizations, asking them
to share the list with their members and to let us know if they would like to replace any of the
H Because the respondents indicated their suggested routes were confidential business information (CBI), the entire
list is not replicated in this report.
1 The importance of grain as a Great Lakes cargo has been declining in recent years; see
http://www.lcaships.com/08SR%20drv-bulk%20commerce%20-%20text.pdf
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Chapter 2 Transportation Shift Analysis
O/D pairs with a different route. This method was chosen to ensure that a maximum of Great
Lakes shipping company representatives, and not simply those that had participated in the EPA
public meeting, had a chance to review the list. We received no adverse comment on this list.
We then proceeded to develop the final list of O/D pairs with respect to actual location of
mines/silo and the production facility that uses the commodity. We did this using information
furnished by stakeholders and public resources. We did not call the production facilities or the
mines for detailed information about their shipments and transportation routes. Instead, we
assume that at least a portion of these routes contains a ship segment, since all O/D pairs were
suggested by Great Lakes stakeholders. Note that we do not assume that all shipments from or to
these facilities are by ship; we only assume that at least some are. The final list of O/D pairs is
set out in Table 2-2.
Table 2-2 Summary of Scenario Routes and Cargo Types
SCENARIO
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
ORIGIN & PORT USED
Rosebud Mine - Superior
Elk Creek Mine - South Chicago
Rosebud Mine - Superior
Rosebud Mine - Superior
Empire and Tilden Mines -
Marquette
Quebec Cartier Mining Co. -
Port Cartier
Hull Rust Mine - Duluth
Northshore Mining - Silver Bay
Lake Calumet Grain Elevators -
Chicago
Duluth Port Grain Elevators
Duluth Port Grain Elevators
Goderich Port Grain Elevators
Port Dolomite
Calcite Quarry and Port
Calcite Quarry and Port
Calcite Quarry and Port
DESTINATION & PORT USED
Bayfront Power Plant - Ashland, WI
GP West Mill - Green Bay
DTE Power Plants - Port Huron
Weadock & Karn Generating Plants -
Essexville
Algoma Steel - Algoma
ArcelorMittal - Chicago/Burns Harbor
U.S. Steel - Gary
Severstal - Ashtabula
Export to Rest of World (RoW) - Baie
Comeau
Export to RoW - Baie Comeau
WNY Ethanol Plant - Buffalo
Nabisco Flour Mill - Toledo
J.M. Stuart Power Plant - Toledo
J.M. Stuart Power Plant - Toledo
American Crystal Sugar Co. - Duluth
Bruce Mansfield Power Station -
Ashtabula
CARGO
TYPE
Coal
Coal
Coal
Coal
Iron Ore
Iron Ore
Iron Ore
Iron Ore
Grain
Grain
Grain
Grain
Stone
Stone
Stone
Stone
It should be emphasized that these 16 O/D pairs were not randomly selected from the
combined list of potential pairs provided by stakeholders, nor was the original list a random
selection of possible Great Lakes shipping routes. As a result, this list of 16 at-risk O/D pairs is
not meant to be representative of all Great Lakes cargo traffic, nor are these meant to be
"typical" routes that could be used to the estimate the economic impacts of the Category 3 rule
on all Great Lakes shipping and a general analysis of transportation mode shift. Instead, the
original set of 50 O/D trade routes was identified by stakeholders as being at risk of
transportation mode shift and the final set of 16 O/D pairs was purposefully selected based on
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cargo type and geographic factors. This is important to keep in mind especially because these at-
risk O/D pairs may not be typical and the amount of cargo shipped to these destinations may be
only a small portion of total Great Lakes cargo in any one year. However, if fuel cost increases
of the magnitude expected from switching to EGA-compliant fuel on the Great Lakes do not
indicate a transportation mode shift on these at-risk routes, where the price difference between
marine transportation and the all-rail alternative is close enough to be of concern to stakeholders,
then transportation mode shift on other routes without such price pressures would not likely be
indicated.
2.4.2 Development of Shipping Routes
Shipping routes were constructed for each of the selected O/D pairs using the Geospatial
Intermodal Freight Transport (GIFT) model developed by EERA with funding from the United
States Maritime Administration. These routes include all transportation links from the source of
the cargo (e.g., mine head, grain silo, and quarry) to the using facility. This is an important
feature of the analysis because it allows consideration of the impacts of the cost of EGA fuel on
the freight rate (in $/ton) for the entire trip and it allows identification of a reasonable all-land
alternative route that would be used if there were transportation mode shift.
The Default Scenario Route for each of the 16 O/D pairs is modeled to represent the
current transportation route between the originating producer of the material being transported
and the using facility. The Default Scenario Route either makes use of the Great Lakes for a
portion of the overall route when the source or destination of the commodity is inland, or
represents a port-to-port route when the source and destination of the commodity are both at a
port. We assume that the marine segment for each of the routes is currently serviced or can be
serviced by Category 3 vessels that would be required to comply with the EGA fuel sulfur limits.
The Default Scenario Route is intended to maximize the use of the Great Lakes across the
overall route, and may include legs of overland travel, where the specified origin and/or
destination of the commodity are inland. In some scenarios (coal and grain, Scenarios 1, 2, 3, 4,
13, 14, 15, 16), there is a large rail component; for the other scenarios (iron ore and stone,
Scenarios 5, 6, 7, 8, 9, 10, 11, 12), the rail component is small or the entire route is by ship.
None of these scenarios includes a highway truck transportation link. This is not surprising as
rail transportation is less expensive that truck transportation, especially for the types of
commodities under consideration.
The Default Scenario Route is used in both the Base Case, which models the use of HFO
for the main engine and MDO for the auxiliary engine of the vessel; and the MDO Case, which
models the use of MDO for both the main and auxiliary engine of the vessel.
1 One peer reviewer considers EPA's selection of the sixteen O/D pairs in detail and concludes that a random
selection among the possible 50 cases would be unlikely to yield much different results given that one third of the
possible cases were used. This peer reviewer also notes that while "[o]ne might also be concerned [ ] that the EPA
selected these cases systematically to identify O/D pairs that would be least likely to trigger the shifts ... it is a thin
reed because the results so strongly refute the contention that transportation mode shift, source shift, and production
shift would occur from the higher fuel cost. (Belzer)
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The All-Rail Alternative Route is modeled to represent an all-rail route from origin to
destination.K An All-Rail Alternative Route was developed for eleven of the twelve iron ore,
coal, and grain scenarios; during this phase of the analysis it was discovered that the mine in
Scenario 6 has no access to a national rail line or highway (see discussion in Section 2.4.2.2
below). No All-Rail Alternative Route was developed for the crushed stone scenarios; instead,
the alternative for these scenarios is to source the crushed stone from a quarry located closer to
the using facility (see Section 2.4.2.4 below; Chapter 3 contains the source shift analysis for
these scenarios).
The method used to create the Default Scenario and All-Rail Alternative routes is
described in Appendix 2C to this chapter, as well as in Appendix 8B. An example transportation
route is illustrated in Figure 2-2, for Scenario 7 (iron ore from Duluth, MN to Gary, IN).
Figure 2-2 Example of Route Mapping, Scenario 7
JjL-E Legend CASE STUDY 7
S OD PAIRS DEFAULT - INTERMODAL ^^ALTERNATIVE-RAIL ONLY
0 125
2.4.2.1 Coal Routes
For each coal O/D pair, this analysis assumes that the coal user purchases the coal from
the originating mine. Therefore, the Default Scenario Route extends from the mine head to the
K An all-rail alternative was identified for eleven scenarios. An all-rail alternative was not identified for Scenario 6,
nor for the four stone scenarios.
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Chapter 2 Transportation Shift Analysis
final user facility. Scenario 1 is coal from Montana, transported through Duluth/Superior to a
power plant in Wisconsin; Scenario 2 is western bituminous coal from Colorado transported
through South Chicago to a paper mill in Green Bay;L Scenario 3 is coal from Montana
transported through Duluth/Superior to a pair of power plants in southern Michigan, and
Scenario 4 is coal from Montana transported through Duluth/Superior to another power plant in
Northern Michigan. These cases all involve an extensive rail link from a mine located fairly far
inland to a Great Lakes port. In each case, the marine link is shorter than the rail link.
2.4.2.2 Iron Ore Routes
For each iron ore O/D pair, the Default Scenario Route also extends from the mine to the
final user, although in these cases the mine is located much closer to the Great Lakes and
therefore the rail segment in the base case is small compared to the marine link. The destination
facilities are all steel mills, in Ontario (Scenario 5), Illinois (Scenario 6), Indiana (Scenario 7),
and Ohio (Scenario 8). Scenario 8 is different from the other three in that the destination is
located inland. This approach is reasonable given the amount of iron ore used by these facilities
and given the fact that there are not many alternative uses for iron ore.M
For Scenario 6 there was no All-Rail Alternative Route identified. Scenario 6 consists of
iron ore transported from Quebec Cartier Mining Co., Quebec, to ArcelorMittal in Burns Harbor,
Indiana. There is no access to a national highway or rail line at the mine in Quebec. Because the
analysis is based on the optimal route between this origin and destination using a ship/rail
transportation mode, a more advantageous ship/rail alternative was not examined (any ship/rail
combination would be less attractive than the all-ship method in the Default Scenario Route).
However, this scenario was retained because it was identified by stakeholders as at-risk for
transportation mode shift, and it is used in the production shift analysis included in Chapter 3.
2.4.2.3 Grain Routes
For each grain O/D pair, the Default Scenario Route extends from a grain silo complex
located at a port to the final user. A silo origin was used for two reasons. First, it would not be
feasible to track the transport of grain from individual farms origin points. Second, silos are
regional gathering points for regional grain shipments for the least-cost land alternative
transportation (rail) as well. In Scenarios 9 and 10, the destination is the export port in Baie
Comeau, where the grain is transferred to ocean vessels. The destination in Scenario 11 is an
ethanol plant in Buffalo, while the destination in Scenario 12 is a food processing plant in
Toledo. All of these facilities are located at or close to port.
L Subsequent to completing the transportation mode shift analysis, EPA learned that while this facility uses Western
bituminous coal, that coal is blended with other coal to meet the quality specifications for the coal used by this
facility. This blending may occur in Chicago. See discussion in Section 2.1, above.
M One peer reviewer noted that in the 2009 Canadian Shipowners' study, the authors state: Marine transportation
costs are a significant but not a majority component of the delivered cost of iron ore. ... Transportation costs while
an important factor in determining ore sourcing are often subordinate to considerations of ore quality, mine
ownership, long term contracts, and overall corporate benefit. With respect to the latter point, the Ontario mills may
at times source from a higher transportation cost origin in order to satisfy an overall corporate contract commitment.
(Kruse)
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Chapter 2 Transportation Shift Analysis
For each of the Default Scenario Routes, because the route begins at a grain silo at the
port, there is no rail component or it is very short. The All-Rail Alternative Route begins at the
same grain silo as the Default Scenario Route.
2.4.2.4 Crushed Stone Routes
For each crushed stone O/D pair, the Default Scenario Route extends from the quarry,
located in Michigan, to the final user facility. The Default Scenario Route was developed in a
similar manner as for the other three commodities. The marine leg was maximized and rail was
presumed to be used for the other cargo-laden leg(s) of the journey. However, instead of
designing an alternate mode route originating at the given quarry in Michigan, the alternate stone
case is one in which a competing quarry provides the stone to the customer. The methodology
for this source shift analysis is described more in Section 3.1.
This different treatment of the stone trade in this study was suggested to EPA by the
stakeholders, who expressed concerns that some other local quarry may offer limestone of
sufficient quality to compete with Michigan quarries for utility customers who have need of lime
for emissions scrubbing. This source-shift rather than mode-shift concept was reinforced when
our contractor ascertained that there is no rail service available at the specified quarries in
Michigan (see Scenarios 13-16, pages 53-59 of Appendix 2C), thus development of an all-rail
mode-shift alternative would not be feasible.
The peer reviewers suggested that EPA evaluate competing routes from specific quarries
that could offer comparable quality stone to that from Michigan. While this study did not attempt
to verify transport routes from specific quarries with confirmed high-calcium scrubber stone
products, we believe there is evidence that some quarries in states including Pennsylvania,
Kentucky, Ohio and Iowa, may offer such products. Given the complexities of this approach,
EPA chose to follow the competitive radius methodology used in the 2009 CSA study (see
Section 1.6.3.2 of Chapter 1). EPA's analysis also assumes, for simplicity, that the stone travels
solely by truck in the alternate case. EPA's research indicates that the American Crystal Sugar
plant in MN (Scenario 15) and the Bruce Mansfield generating station in PA (Scenario 16) both
have rail service, though the JM Stuart generating station in OH (Scenarios 13-14) may not have
rail service.6'7 EPA's research also indicates that both of the power plants in Scenarios 13, 14
and 16 periodically receive their limestone via river barges (See Note 7). Given the variables in
designing a multi-mode route from a competing quarry, such as a rail/truck, truck/barge or
rail/barge route, such an analysis may not provide meaningful results for comparison with the
Default Scenario Route.
2.5 Data Inputs
The data inputs used to carry out the modeling for this analysis are described in detail in
Appendix 2C to this chapter and summarized below. The fuel prices used in the analysis were
supplied to the contractors by EPA and are also described below.
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Chapter 2 Transportation Shift Analysis
2.5.1 Scenario Characteristics - Marine
Many of the data used to represent the marine link in each of the routes included in this
analysis are unique to that Default Scenario Route. These include the length of the route, port
depth restrictions (which have an impact on the amount of cargo carried), and route restrictions
(e.g., locks and canals which may limit the length of vessels that can be used on a route). These
are all described in the report contained in Appendix 2C to this Chapter.
Data describing vessel and engine characteristics are common across groups of scenarios
and are summarized in Table 2-3. It should be noted that these vessel and engine characteristics
are not meant to represent the actual vessels that service these routes. The identities of those
vessels are not easily available and likely to change from shipment to shipment and from year to
year. In addition, there may be times when the route is serviced by a vessel with a Category 2
main propulsion engine. However, based on stakeholder input, we assume that there are
Category 3 vessels that actually service each of these routes at least some of the time. These
assumed characteristics are meant to describe a hypothetical vessel with a Category 3 main
propulsion engine that could service each route given route restrictions (port depth, canal length,
etc.) for that O/D pair.
Table 2-3 General Vessel Characteristics
Scenario
Coal (1,2)
Coal (3,4)
Iron Ore (5, 6)
Iron Ore (7, 8)
Grain (9, 10, 11,12)
Stone (13, 14, 15, 16)
Vessel Length
635ft
1,000 ft
635ft
1,000 ft
635ft
770ft
Maximum
Draft
28ft
29ft
28ft
29ft
28ft
29ft
Cargo Capacity
18, 150 net tons
57,200 net tons*
18, 150 net tons
57,200 net tons
18, 150 net tons
49,300 net tons
Main Engine Power
7,200 hp
16,000 hp
7,200 hp
16,000 hp
7,200 hp
ll,000hp
Operating Speed
12 knots / 14 mph
14 knots / 16 mph
14 knots / 16 mph
14 knots / 16 mph
12 knots / 14 mph
14 knots / 16 mph
*Scenario 3 only; Scenario 4 has a lighter cargo capacity due to port restrictions
Table 2-3 shows that two general vessel types are used for the coal, iron ore, and grain
scenarios. One vessel has a length of 635 ft, main engine power of 7,200 hp, and has a cargo
capacity of 18,150 net tons. This vessel has a draft of 28 ft and travels at 12 knots (14 mph) at
cruise, although the iron ore ships are assumed to travel faster (14 knots or 16 mph). The other is
a longer vessel, at 1,000 ft, powered by a 16,000 hp main engine and has a cargo capacity of
57,200 net tons. It has a draft of 29 feet and travels at 14 knots (16 mph) at cruise. The stone
vessels are assumed to have a length of 770 ft, with main engine power of 11,000 hp and a cargo
capacity of 49,300 net tons. The stone vessels travel at 14 knots (16 mph) and have a draft of 29
feet.
With regard to the main propulsion engine, these are assumed to be operated on HFO in
the Base Case and distillate fuel in the EGA case. The engine specific fuel oil consumption is
196 to 236 g/kW-hr, depending on assumptions about vessel age. Total propulsion power is
assumed to be 7,200 hp, 11,000 hp, or 16,000, depending on cargo (see Table 2-3). The load
factor at sea is dependent on vessel speed; the load factor at port is assumed to be zero (the
engines are assumed to not be operated at port).
2-16
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Chapter 2 Transportation Shift Analysis
With regard to auxiliary engines, these are assumed to be operated on distillate fuel (no
auxiliary boilers). The engine specific fuel oil consumption is 221 g/kW-hr. Total auxiliary
power for each vessel is equivalent to 3 percent of main engine power, and the auxiliary engine
load factor in port and underway is 80 percent.
The analysis includes the fuel costs for a round trip on the marine segment of a scenario
route but assumes that ships have empty backhauls. This approach was used both because not all
routes have backhauls and not all ships on a route with backhauls (e.g., iron ore) will have a
backhaul. As a result, the analysis is conservative because it assumes that no revenue is
generated on the backhaul and all fuel costs are included in the one-way freight rate.
2.5.2 Scenario Characteristics - Rail
The methodology in this analysis included minimizing rail distances between cargo
transfer points. Further information about the design and selection of rail services used in each
scenario may be found in Appendix 2C and Chapter 8. The rail freight rates used in the analysis
reflect a diesel fuel price equivalent to the MDO price described in Section 2.6.3. The analysis
also assumes a rail energy intensity of 328 BTU/ton-mile for all rail links, in accordance with the
national average forecast for 2015, published by the U.S. Energy Information Administration
(EIA), in its Annual Energy Outlook (AEO). See Chapter 3 for a discussion of EPA's analysis
of emissions from locomotives.
2.5.3 Marine Fuel Prices
The fuel prices used in this analysis were provided by EPA to the contractors and are
summarized in Table 2-4.
These fuel prices are different from the fuel prices we used in the analysis supporting our
Category 3 marine rule. The fuel prices used in that earlier economic analysis were projected
fuel prices for 2020 obtained through refinery modeling, based on a price of oil at $52/barrel. In
that analysis, the year 2020 was used instead of the compliance year of 2015 due to constraints
associated with the air quality modeling performed for that rule. The projected fuel prices used
in that rule were $322/MT for HFO and $468/MT for MDO (2006$).
As explained in Section 2.1.1, this analysis uses 2007 as the year of analysis. As a result,
rather than using projected fuel prices the analysis is based on prices reported by the EIA for
2007. This approach responds to the recommendation of Great Lakes stakeholders that EPA
should consider a different approach for estimating fuel prices, one that reflects changes in the
oil market since the Category 3 rule analysis was performed. As a result, the fuel prices used in
this Great Lakes analysis are based on 2007 fuel price for residual diesel fuel reported by the
U.S. EIA in the 2010 AEO: $1.375/gal, or $385/tonne (based on a density of 280 gal/MT;
2008$).N
Stakeholders also informed EPA that fuel prices on the Great Lakes are higher than fuel
prices at coastal ports. An analysis of confidential fuel data provided to EPA by several
N The prices for 2008 were not used due to the perturbations in the global fuel market that occurred in that year, and
data for 2009 were not available.
2-17
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Chapter 2 Transportation Shift Analysis
stakeholders suggests that fuel prices on the Great Lakes are approximately ten percent higher
than fuel prices on the U.S. coasts and in other major global ports (Singapore, and Rotterdam).
Therefore, the 2007 HFO price was adjusted by ten percent, to $424/tonne.
Table 2-4 Fuel Prices Used in the Analysis
(2007 Prices reported by EIA, adjusted for Great Lakes Market; 2008$)
FUEL TYPE
Marine HFO - Great Lakes
Marine MDO - Great Lakes
PRICE: $/MT
$424
$617
PRICE: $/GAL
$1.51
$1.99
To obtain the MDO price used in the analysis, we applied the EIA 2015 projected fuel
price differential for HFO and MDO to the adjusted 2007 HFO fuel price of $424/tonne. This
differential, 45.5%, was calculated and applied as follows.
The 2015 HFO projected price of $2.033 was adjusted by 10 percent to reflect
fuel prices on the Great Lakes, yielding $2.24/gal or $626/MT.
The 2015 MDO price was adjusted to remove the fuel taxes ($0.47) and to reflect
the fuel prices on the Great Lakes, yielding $2.94/gal or $911/MT (based on a
density of 310 gal/MT). Thus the 2015 differential is 1.455 ($911/$626),
meaning MDO is expected to be 45.5 percent more expensive than residual fuel.
When that differential is applied to the 2007 HFO price of $424/MT for the Great
Lakes, this yields an MDO price of $617/MT.
This approach was taken because the price differential in 2007 reported by EIA was
about 100%, meaning the price of distillate was about twice the price of HFO, due to heavy
worldwide demand for distillate fuel at that time. Such a large differential is not representative
of the normal MDO/HFO price differential that has been experienced in past years. During the
development of this transportation mode shift analysis, some Great Lakes industry stakeholders
suggested that the analysis be run using various prices for marine distillate fuel. While this type
of sensitivity analysis could be run, the overall results regarding the occurrence of transportation
mode shift would not change. This is because MDO and distillate fuel used in land-based
transportation (rail and highway truck) are essentially the same fuel and have essentially the
same price, and therefore a price increase in one would be associated with a price increase in the
other.0 While changing the distillate fuel price would affect the absolute value of freight rates
for both marine and the all-rail alternative, the relationship between the two would not change. p
0 Note that the refinery model focuses on fuel cost impacts, where the historic fuel prices can be affected by external
market impacts. An example of external market impacts that can drive pricing was during the tight distillate market
of 2008. During this time period, diesel prices in the U.S. were higher than gasoline prices, even though further
refining (more expensive processing) is necessary to produce gasoline than diesel fuel. This occurred because of
high distillate demand in India and China outstripping existing distillate refining capacity.
p One peer reviewer notes that "though the tradeoffs in fuel prices between marine and land-based distillate probably
would remain constant... the tradeoff between the two might not be linear. As the price of oil goes up, the greater
efficiency of using the marine mode might provoke shift of freight to marine over rail; this would happen at the
extremes of price when the cost of fuel is so great that it begins to trump the cost of intermodal handling needed to
2-18
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Chapter 2 Transportation Shift Analysis
While oil prices are currently increasing, what is important in this analysis is the price
ratio of the price of HFO and MDO and not their absolute prices. This is because as oil prices
increase the prices of both residual fuel and distillate fuel will increase, and distillate fuel prices
will be higher for both marine and for land-based transportation alternatives. The relationship
between the HFO and MDO prices used in this study is consistent with historic prices for HFO
and MDO. Data for Singapore and Fujairah for the years 2000 through 2007, reported in a 2007
Experts Group study prepared for the IMO and reproduced in Table 2-5, show that the price of
HFO ranged between 50 to 72 percent of the price of MDO over that 7-year period.8 For this
analysis, the price of HFO is 69 percent of the price of MDO ($424/$617). The refinery
modeling we performed in support of the North American EGA package and our Category 3 rule
also estimates the price of HFO to be 69 percent of the price of MDO ($322/$468).9
Table 2-5 Price Difference Between HFO and Distillate Fuel, 2000-2007 ($US)
Year
2000
2001
2002
2003
2004
2005
2006
2007
Source:
Average
price
MDO
(USD)
273
202
203
239
343
503
617
655
Averase price
HFO "(USD)
156
127
146
166
176
258
311
365
Annual price
increase decrease
MDO (USD)
-26.1%
0.5%
17.5%
43.8%
46.5%
22.7%
6.2%
Annual price
inc rea se de cr ea se
HFO (USD)
-18,3%
14,8%
13,9%
5,8%
46,4%
20,7%
17,2%
HFOMDO
57%
63%
72%,
70%
51%
51%
50%
56%,
Bu)iker\vor!d (based on prices in Singapore and Fujairah)
2.5.4 Equipment Costs
The EGA-related fuel costs used in this mode shift analysis do not include equipment
costs associated with fuel switching, such as distillate fuel tanks, fuel coolers, pumps, filters, and
piping. These estimated equipment costs are one-time costs and are relatively small, averaging
about $60,000 per vessel, with the costs for no vessel expected to exceed $71,000. Including
these one-time costs would not change the results of the transportation mode shift analysis. A
discussion of the equipment costs is included in Chapter 6.
2.5.5 Freight Rates
The freight rates used in this analysis were obtained by the contractor and are
summarized in Table 2-6. These freight rates were estimated as described in Chapter 4 of the
shift as much to marine as possible. This, however, would not change the conclusions of the analysis because it
would drive freight toward, not away from the marine mode; it would not favor truck or rail." (Belzer) See also
various MARAD reports cited in Chapter 1.
2-19
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Chapter 2 Transportation Shift Analysis
study contained in Appendix 2C of this chapter and are based on the fuel prices described in
Section 2.5.1.3.
Table 2-6 Marine and Rail Freight Rates ($/cargo ton)3
SCENARIO
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
DEFAULT SCENARIO ROUTE
Marine Freight Rate
$1.81
$3.50
$3.02
$7.11
$2.45
$10.98
$3.34
$3.66
$18.50
$16.28
$17.40
$5.52
$4.73
$2.75
$6.15
$3.30
Rail Freight Rate
$16.62
$20.98
$16.62
$16.62
$0.32
$3.76
$1.52
$1.82
N/A
N/A
$1.53
$0.10
$4.96
$4.96
$4.69
$2.01
ALL-RAIL ALTERNATIVE ROUTE
Rail Freight Rate
$20.21
$22.93
$25.94
$26.62
$3.97
N/A
$10.74
$17.12
$43.08
$55.90
$32.95
$8.13
N/A
N/A
N/A
N/A
Freight rates based on 2007 fuel prices, presented in 2008$
The basis for comparison is freight rates in terms of $/cargo ton, not $/ton-mile. In other
words, the analysis estimates how much it would cost to move a ton of cargo (e.g., iron ore) from
Point A (e.g., Hull Rust Mine in Minnesota) to Point B (e.g., U.S. Steel in Gary, Indiana), instead
of estimating a freight rate that could be applied to any route based on distance. While this
approach does not allow for comparisons across scenarios, it does allow comparison of the
marine and all-rail modes for the same cargo tonnage between the same O/D pairs.
With respect to the Default Scenario Route, the total freight rate for each scenario is the
sum of the marine rate, the rail rate, and the cargo transfer costs. This is estimated for both the
Base Case (HFO fuel) and MDO Case (ECA fuel). With respect to the All-Rail Alternative
Route, the total freight rate is the sum of the all-rail route rates and the all-rail route transfer
costs.
A sensitivity analysis was performed to incorporate routing constraints that would
increase the cost of transporting goods by rail for the Default Scenario Route and All-Rail
Alternative Route. In this analysis, rail freight rates increase for all cases except Scenarios 1 and
2. In all cases, no mode shift is indicated.
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Chapter 2 Transportation Shift Analysis
2.6 Conclusion
This transportation mode shift analysis shows that the additional fuel costs associated
with complying with the 1,000 ppm EGA fuel sulfur limit on the Great Lakes are not expected to
result in transportation mode shift. For ten of the twelve scenarios examined, EGA-adjusted
marine freight rates are expected to remain well below the next least expensive shipping mode,
all-rail. For one of the two remaining scenarios, an All-Rail Alternative route could not be
identified, although the results for a similar case suggest that no transportation mode shift would
be indicated. For the other scenario, the results of the analysis are inconclusive due to mis-
specification of the scenario.
These results are specific to the O/D pairs examined. However, the routes studied were
identified by stakeholders as being at-risk of transportation mode shift due to increases in fuel
costs associated with the requirement to use EGA fuel on the Great Lakes. If fuel cost increases
of the magnitude expected from switching to EGA-compliant fuel on the Great Lakes do not
indicate a transportation mode shift on these at-risk routes, where the price difference between
marine transportation and the all-rail alternative is close enough to be of concern to stakeholders,
then transportation mode shift on other routes without such price pressures would not likely be
indicated.
2-21
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Chapter 2 Transportation Shift Analysis
Appendices
Stakeholder Interactions
EPA performed the analysis contained in this report in response to comments received
from Great Lakes stakeholders during our Category 3 rulemaking process. As a result, we
solicited industry stakeholder input during all phases of the analysis, especially with respect to
the routes studied, the study methodology used, and key data inputs such as cargo types, vessel
characteristics, and cargo transfers.
EPA engaged with various Great Lakes industry stakeholders throughout the
development of this analysis. Our first outreach with stakeholders was through a presentation to
industry members at Marine Community Day on February 11, 2010. At this conference, EPA
explained to stakeholders that we were developing a research strategy and evaluating existing
modeling tools and various ways to assess the economic impacts of our rule on Great Lakes
shipping. The goal of the analysis, we noted, would be to see if a transportation cost increase of
the order we expected as a result of applying the EGA fuel requirements to the Great Lakes, in
combination with the dynamics of transportation in the Great Lakes region, would potentially
lead shippers to shift away from marine transportation to one of the land-based alternatives, rail
or truck. We also indicated we were developing ways to engage stakeholders to obtain input on
the methods we would be using and the data we would need to carry out the study.
During the spring of 2010, we evaluated existing models and methodologies that could be
used to perform this analysis. We also engaged a contractor who began to develop the analytic
tools and carry out test modeling for several example cargo/route combinations.
We hosted a workshop in Ann Arbor on June 10, 2010, to present our proposed
transportation mode shift methodology and to solicit data inputs from industry stakeholders. The
invitation to the workshop was sent by email to the full list of stakeholders to whom we had been
making announcements throughout the rulemaking process, including those who had submitted
comments, attended hearings, and those whose interest was made known to us. A remote
attendance option was provided for connecting via phone and web link for those who could not
travel to Ann Arbor on that day. An attempt was made to be inclusive of a wide range of
stakeholders, so that we had the best chance possible of receiving valid data for our study.
Exhibit 1, below, documents EPA's external correspondence during this study. The invitation,
final agenda and attendance list are provided as Exhibits 2, 3, and 4 of this Appendix,
respectively.
At the workshop, EPA's contractors, James Winebrake of the University of Rochester
and James Corbett of the University of Delaware described their Geospatial Intermodal Freight
Transport (GIFT) model they developed with funding from the United States Maritime
Administration (MARAD) and presented the results of draft scenarios examining the cost
impacts of the EGA fuel program for two fairly typical transportation scenarios: coal shipped
from Montana to Monroe and St. Glair, Michigan, and iron ore shipped from Minnesota to Gary,
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Chapter 2 Transportation Shift Analysis
Indiana (slides of the presentation given at this workshop are included as Appendix 2B to this
report). This methodology was well-received by the workshop participants. At the close of that
workshop we indicated that the next step in EPA's study would be to define the shipping
scenarios that would be included in the analysis, and we requested industry input for the
cargo/route combinations that should be included in the analysis. Specifically, we asked the
industry to identify routes most likely to see direct competition leading to a potential mode shift.
We noted it would be helpful if suggested scenarios represented cargo and O/D combinations
that are at risk for transportation mode shift due to competition from landside alternatives.
At the request of attendees, EPA followed up the on Ann Arbor workshop with an e-mail,
dated June 16, 2010, that provided additional details about the methodology we intended to use
for the transportation mode shift analysis and contained a list of the data inputs that would be
needed. The e-mail was sent to workshop attendees as well as the two primary trade associations
for Great Lakes carriers: Lake Carriers' Association and the Canadian Shipowners' Association.
In that e-mail, EPA again requested stakeholders assistance in identifying sensitive routes that
may be at risk for transportation mode shift.
We again presented a summary of our analytic approach and results for the two initial
scenarios at the 74* International Joint Conferences of the Canadian Shipowners' Association
and Lake Carriers' Association in Niagara-on-the-Lake, Ontario, on June 21, 2010, and
requested stakeholder input.
Several stakeholders responded directly to EPA with confidential information about the
trade routes they believe might be at risk for transportation mode shift as a result of increased
fuel costs. Using this information, EPA prepared a list of 16 routes to be included in the
analysis. After obtaining the agreement of those stakeholders who had shared their
recommendations, on July 12, 2010 we forwarded our draft list of at-risk routes to the primary
industry trade organizations for dissemination to their members and requested comments or
revisions. We received no adverse comment on this list of routes. The specific data needed to
perform the analysis for each route were then gathered by EPA's contractor. We forwarded draft
data sheets along with associated route maps to the trade associations on August 13, 2010, again
with a request that they forward the information to their members for review and comment. The
final data inputs used in this analysis are based on the comments we received on these data
sheets.
In addition, EPA exchanged e-mails and had telephone conversations with various
stakeholders with regard to their questions and concerns about the study.
In summary, stakeholder input was solicited during all phases of this project with regard
to the study methodology, the choice of at-risk routes to be analyzed, and the data used to
characterize these routes in the analysis. The assistance provided by stakeholders was highly
valuable and allowed us to focus this analysis on those routes identified by shipping interests as
being most likely to be adversely affected by the application of the EGA fuel requirements to the
Great Lakes
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Chapter 2 Transportation Shift Analysis
Exhibit 2A-1: Index of External Communication
DATE
April 14, 2010
April 30, 2010
May 26, 2010
May 26, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 28, 2010
May 29, 2010
May 3 1,2010
DOCUMENT
TYPE
Log of
telephone call
Log of
telephone call
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Scenario Inputs -
CBI
Scenario
building
Scheduling
public workshop
Scheduling
public workshop
Invitation to
public workshop
Public workshop
Invitation to
public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
DESCRIPTION
Telephone conversation between Jean Marie
Revelt of EPA and Glenn Nekvasil of Lake
Carriers' Association regarding loads of iron ore
to Gary and coal to ports in Michigan
Telephone conversation between JM Revelt of
EPA and Glenn Nekvasil of LCA, regarding
privileged nature of competitive route
information
Email from Byron Bunker of EPA to James
Weakley of LCA, suggesting possible dates for
public workshop
Email from James Weakley of LCA to B Bunker
of EPA, commenting on possible dates for
public workshop
Email from Lauren Steele of EPA to large list of
stakeholders, with invitation to public workshop
Email from Paul Billings of ALA to L Steele of
EPA, commenting on invitation to public
workshop
Email from L Steele of EPA to Julie Gedeon,
with invitation to public workshop
Email from Craig McKim of Testo Ink to L
Steele of EPA, regarding public workshop
Email from G. Bowler of GR Bowler to L Steele
of EPA, regarding public workshop
Email from L Steele of EPA to Craig McKim of
Testo Ink, regarding public workshop
Email from Karl Briers of Herbert Engineering
to L Steele of EPA, regarding public workshop
Email from Gregg Ruhl of Great Lakes Fleet to
L Steele of EPA, regarding public workshop
Email from Craig McKim of Testo Ink to L
Steele of EPA, regarding public workshop
Email from Mark Mather of PM Shipping to L
Steele of EPA, regarding public workshop
Email from Raymond Johnston of CMC to L
Steele of EPA, regarding public workshop
Email from Azin Moradhassel of CSA to L
Steele of EPA, regarding public workshop
2-24
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Chapter 2 Transportation Shift Analysis
DATE
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 1, 2010
June 2, 2010
June 2, 2010
June 2, 2010
June 2, 2010
June 3, 2010
June 3, 2010
June 3, 2010
DOCUMENT
TYPE
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
DESCRIPTION
Email from Daniel Yuska of MARAD to L
Steele of EPA, regarding public workshop
Email from Adrian Mitterhuber of Provmar
Fuels to L Steele of EPA, regarding public
workshop
Email from Chris Tsang of DTE to L Steele of
EPA, regarding public workshop
Email from L Steele of EPA to Adrian
Mitterhuber of Provmar Fuels, regarding public
workshop
Email from Cliff Hill of TOTE to L Steele of
EPA, regarding public workshop
Email from L Steele of EPA to Craig McKim,
regarding public workshop
Email from Brian Harney of Exxonmobile to L
Steele of EPA, regarding public workshop
Email from Caroline Gravel of Shipping
Federation of Canada to L Steele of EPA
regarding public workshop
Email from Gordon Gerber of Caterpillar to L
Steele of EPA regarding public workshop
Email from L Steele of EPA to Lynn Nadon of
Environment Canada, regarding public
workshop
Email from Bill Hart of Toromont to L Steele of
EPA regarding public workshop
Email from L Steele of EPA to 13 stakeholders,
confirming information for public workshop
Email from L Steele of EPA to 2 invitees at
CATF, regarding public workshop
Email from L Steele of EPA to S. Kiser of
ALA, regarding public workshop
Email from Lynn Nadon of Environment
Canada to L Steele of EPA, regarding public
workshop
Email from Mike Elliott of NOVA Chemicals to
L Steele of EPA regarding public workshop
Email from John Kaltenstein of FOE to L Steele
of EPA regarding public workshop
Email from John Kaltenstein of FOE to L Steele
of EPA regarding call-in for public workshop
2-25
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Chapter 2 Transportation Shift Analysis
DATE
June 4, 2010
June 4, 2010
June 4, 2010
June 4, 2010
June 4, 2010
June 4, 2010
June 4, 2010
June 4, 2010
June 4, 2010
June 5, 2010
June 7, 2010
June 7, 2010
June 7, 2010
June 7, 2010
June 7, 2010
June 7, 2010
DOCUMENT
TYPE
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
DESCRIPTION
Email from Adrian Mitterhuber of Provmar
Fuels to L Steele of EPA regarding public
workshop
Email from Ted Thompson of CLIA to L Steele
of EPA regarding public workshop
Email from Patrice Cote of Transport Canada to
L Steele of EPA regarding public workshop
Email from Peter Kelly of Sterling Marine Fuels
to L Steele of EPA regarding public workshop
Email from Nancy Kruger of NACAA to L
Steele of EPA regarding web option for public
workshop
Email from L Steele to Nancy Kruger of
NACAA regarding web option for public
workshop
Email from Paul Topping of Transport Canada
to L Steele of EPA regarding public workshop
Email from Andrew Green of Environment
Canada to L Steele of EPA regarding public
workshop
Email from Daniel Yuska of MARAD to L
Steele of EPA regarding public workshop
Email from David Celebrezze of Ohio
Environmental Council to L Steele of EPA
regarding web option for public workshop
Email from Mike Elliott of NOVA Chemicals to
L Steele of EPA regarding public workshop
Email from Adrian Mitterhuber of Provmar
Fuels to L Steele of EPA regarding web option
for public workshop
Email from Mark Barker of Interlake Steamship
to L Steele of EPA regarding public workshop
Email from L Steele of EPA to Adrian
Mitterhuber of Provmar Fuels regarding web
option for public workshop
Email from L Steele of EPA to 6 stakeholders,
confirming attendance at the public workshop
Email from Adrian Mitterhuber of Provmar
Fuels to L Steele of EPA regarding web option
for public workshop
2-26
-------
Chapter 2 Transportation Shift Analysis
DATE
June 7, 2010
June 7, 2010
June 7, 2010
June 7, 2010
June 7, 2010
June 7, 2010
June 8, 2010
June 8, 2010
June 8, 2010
June 8, 2010
June 8, 2010
June 9, 2010
June 9, 2010
June 9, 2010
June 10, 2010
June 10, 2010
DOCUMENT
TYPE
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
Public workshop
DESCRIPTION
Email from Ted Thompson of CLIA to L Steele
of EPA regarding web option for public
workshop
Email from L Steele of EPA to 12 stakeholders
with invitation to participate via the web option
Email from Mark Mather of PM Shipping to L
Steele of EPA regarding web option for public
workshop
Email from Mike Elliott of NOVA Chemicals to
L Steele of EPA regarding web option for public
workshop
Email from Lawrence Dorr of DTE Energy to L
Steele of EPA regarding public workshop
Email from L Steele of EPA to Lawrence Dorr
of DTE Energy regarding public workshop
Email from Raymond Johnston of CMC to L
Steele of EPA regarding public workshop
Email from Mark Lathrop of American
Steamship to L Steele of EPA regarding public
workshop
Email from L Steele of EPA to S. Bridgewater
of American Iron and Steel Institute inviting to
public workshop
Email from L Steele of EPA to David Knight of
Great Lakes Commission confirming attendance
at public workshop
Email from L Steele of EPA to M. Lathrop and
D Hutchinson of American Steamship
confirming attendance at public workshop
Email from Peter Kelly of Sterling Marine Fuels
to L Steele of EPA regarding web option for
public workshop
Email from Fred Walas of Marathon Oil to L
Steele of EPA regarding public workshop
Email from L Steele of EPA to Fred Walas of
Marathon Oil regarding public workshop
Email from L Steele of EPA to Eric McKenzie
of Seaway Marine Transport regarding public
workshop
Email from Eric McKenzie of Seaway Marine
Transport to L Steele of EPA regarding public
workshop
2-27
-------
Chapter 2 Transportation Shift Analysis
DATE
June 10, 2010
June 10, 2010
June 10, 2010
June 11,2010
June 16, 2010
June 16, 2010
June 17, 2010
June 18,2010
June 18,2010
June 21, 2010
June 25, 2010
June 28, 2010
June 30, 2010
July 12, 2010
DOCUMENT
TYPE
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Public workshop
Applicability
Public
Workshop
Scenario
building
Vessel Info
Study Inputs
Vessel Info
Scenario Inputs
Scenario Inputs
Scenario
building
Scenario inputs
Scenario
building
Scenario
building
Scenario
building
DESCRIPTION
Email from L Steele of EPA to 49 stakeholders
with presentation from public workshop
Email from John Medley of ExxonMobil to L
Steele of EPA regarding applicability of C3 and
IMO standards
Email from Jim Weakley of LCA to L Steele, B
Bunker and JM Revelt of EPA with thanks for
an outstanding workshop
Email from L Steele of EPA to 43 stakeholders
conveying request (given verbally at workshop)
for information on routes to include in the study
Email from JM Revelt of EPA to 43
stakeholders sharing list of C3 vessels to be
included in the study
Email from JM Revelt of EPA to 43
stakeholders sharing description of input data
and assumptions, and reiterating request for
routes to study
Email from Glen Nekvasil of LCA to JM Revelt
of EPA with additions to list of C3 vessels to be
included in the study
Email from Mark Barker of Interlake Steamship
to JM Revelt of EPA, providing CBI on routes
to study
Email from Gregg Ruhl of CN Supply Chain
Solutions to JM Revelt of EPA, providing CBI
on routes to study
Email from William Strauss of the Federal
Reserve Bank of Chicago to JM Revelt of EPA,
providing CBI on rail congestion
Email from Azin Moradhassel of CSA to JM
Revelt of EPA, providing CBI comments on fuel
costs
Email from Mira Hube of Seaway Marine
Transport to JM Revelt of EPA, providing CBI
comments on routes and fuel costs
Email from Azin Moradhassel of CSA to JM
Revelt of EPA, providing CBI comments on
routes and fuel costs
Email from Mark Barker of Interlake Steamship
to JM Revelt of EPA with CBI comments on
routes
2-28
-------
Chapter 2 Transportation Shift Analysis
DATE
July 12, 2010
July 12, 2010
July 12, 2010
July 13, 2010
July 14, 2010
July 19, 2010
July 19, 2010
August 2,
2010
August 10,
2010
August 13,
2010
August 18,
2010
August 18,
2010
DOCUMENT
TYPE
Electronic
mail
Electronic
mail
Facsimile
Electronic
mail
Electronic
mail
Log of
telephone call
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Scenario
building
Public workshop
Public workshop
Scenario
building
Scenario
building
Scenario Inputs
Scenario
building
Scenario Inputs
Scenario Inputs
Scenario Inputs
Scenario Inputs
Scenario Inputs
DESCRIPTION
Email from JM Revelt of EPA to B Bowie of
CSA and J Weakley of LCA sharing 16
suggested O/D pairs to be modeled in the study,
and asking for comment
Email from L Steele of EPA to David Roth of
Holland & Knight with presentation from public
workshop
Fax from L Steele of EPA to David Roth of
Holland & Knight with attendee list from public
workshop
Email from J Weakley of LCA to JM Revelt of
EPA and B Bowie of CSA confirming that
EPA's message of July 12 with 16 O/D pairs
was forwarded to LCA members
Email from Gregg Ruhl of Great Lakes Fleet to
JM Revelt o f EPA, providing comments
including CBI on stone scenario development
Telephone conversation between Jean Marie
Revelt of EPA and Glen Nekvasil of LCA,
regarding final destinations of loads of ore
unloaded at 2 ports in Ohio
Email from Gregg Ruhl of Great Lakes Fleet to
JM Revelt of EPA, providing CBI on fuel costs
Email from L Steele of EPA to B Bowie of CSA
and J Weakley of LCA sharing additional data
inputs and assumptions for the study, plus an
annotated list of the 16 O/D pairs, asking for
comment
Email from Azin Moradhassel of CSA to Lauren
Steele of EPA, providing comments on inputs,
assumptions and O/D pairs
Email from JM Revelt of EPA to LCA, CSA
and other stakeholders, sharing detailed input
data and constraints for each of 16 O/D pairs to
be modeled in the study, and asking for
comment
Email from Dave Anderson of Interlake
Steamship to JM Revelt of EPA, providing
comments including CBI on scenario inputs
Email from Azin Moradhassel of CSA to JM
Revelt of EPA, providing comments including
CBI on scenario inputs
2-29
-------
Chapter 2 Transportation Shift Analysis
DATE
August 20,
2010
August 20,
2010
August 30,
2010
September 2,
2010
DOCUMENT
TYPE
Electronic
mail
Electronic
mail
Electronic
mail
Electronic
mail
SUBJECT
Scenario Inputs
Scenario Inputs
Public workshop
Scenario Inputs
DESCRIPTION
Email from Kate Ferguson of Great Lakes Fleet
to JM Revelt o f EPA, providing comments
including CBI on scenario inputs
Email from Azin Moradhassel of CSA to JM
Revelt of EPA, providing comments including
CBI on scenario inputs for cargo handling
Email from L Steele of EPA to Donald Gregory
of EGCSA with presentation from public
workshop
Email from Wesley Walker of U.S. Army Corps
of Engineers to JM Revelt of EPA, clarifying
role of ACE consultant in scenario development
2-30
-------
Chapter 2 Transportation Shift Analysis
Exhibit 2A-2: Stakeholder Meeting Invitation
Invitation to Participate
Presentation of Methodology for Study of Economic Impacts of Category 3 Marine Diesel Rule
on the Great Lakes Shipping Industry
The United States Environmental Protection Agency (US EPA) is hosting a workshop to discuss
the proposed methodology for studying economic impacts on the Great Lakes shipping industry,
due to the Category 3 Marine Diesel Engine Rule, published April 30, 2010. The workshop will
be held from 9:30 a.m. to 1:00 p.m. on Thursday, June 10, 2010, at the US EPA's National
Vehicle and Fuel Emissions Laboratory, 2000 Traverwood Drive, Ann Arbor, MI 48105, as well
as through a Web conferencing portal for remote participants. A draft agenda is attached below.
US EPA is pleased to invite maritime and transportation experts representing all organizations
interested in this subject, including producers and shippers, to participate in this workshop.
Others are welcome to observe the discussions. Those wishing to connect via the Web
conferencing portal should follow the instructions below.
Results of preliminary trials using the Geographic Intermodal Freight Transportation (GIFT)
model will be presented by experts from Energy and Environmental Research Associates, LLC
(EERA). In addition to the general sharing of information, US EPA and EERA will use these
discussions to consider modifications to the current research plan to study the potential for modal
shift on the Great Lakes due to enactment of stringent marine fuel standards. All attendees are
invited to share technical information they have that may be relevant to the subject of the
meeting. US EPA will use this information to augment its data inputs and improve the modeling
methodology, as it proceeds with its economic study.
We ask that those traveling to Ann Arbor register for this workshop by sending an e-mail to Ms.
Lauren Steele of US EPA at steele.lauren@epa.gov no later than Monday June 7, 2010. Remote
participants will be able to log in 15 minutes prior to the start time.
SEPA
fS Web Conference
Web conference invitation : Great Lakes Workshop
Those wishing to participate in the workshop remotely should go to the URL provided and enter the
conference ID, the conference key, and your name where requested. The dial-in telephone number is
also provided for the audio connection.
http://hawkeye.epa. gov/imtapp/app/prelogin.uix?sitelD=0
2-31
-------
Chapter 2 Transportation Shift Analysis
Conference Title Great Lakes Workshop
Conference ID 84ฃ17
Conference Key 2144788
Date and Time 10 Jun-2010 9:30 AM
Duration 3 Hours, 30 Wins
Timezone (UTC-05:00) US Eastern Time
Dial-In Number 866-299-3188 code 7342144117
2-32
-------
Chapter 2 Transportation Shift Analysis
Exhibit 2A-3: Stakeholder Meeting Final Agenda
Presentation of Methodology for Study of Economic Impacts of Category 3 Marine Diesel
Rule on the Great Lakes Shipping Industry
Public Workshop
EPA National Vehicle and Fuel Emissions Laboratory
Ann Arbor, Michigan
June 10, 2010
9:30 am to 1:00 pm
AGENDA
Welcome and introductions
Opening remarks
Overview of Great Lakes economic study to date
The research question
The modeling framework
Analysis of initial scenarios
Break (15 minutes)
Next steps
Data used in modeling
Additional modeling scenarios
Open discussion
Conclusion
2-33
-------
Chapter 2 Transportation Shift Analysis
Exhibit 2A-4: Stakeholder Meeting Attendance List
Last Name
Barker
Bowie
Bowler
Briers
Browning
Cameron
Celebrezze
Corbett
Cote
Elliott
Gerber
Harkins
Hart
Hill
Hopkins
Kelly
Kelly
Knight
Koman
Kopin
Kubsh
Lathrop
Lewis
Lindhjem
Mather
McKenzie
Medley
Mitterhuber
Moar
Moradhassel
Muehling
Nadon
Nekvasil
First Name
Mark
Bruce
Gary
Karl
Lou
Susan
David
Jim
Patrice
Mike
Gordon
Rick
Bill
Cliff
John
Patrice
Peter
Dave
Irish
Amy
Joseph
Mark
Paula
Chris
Mark
Eric
John
Adrian
Brian
Azin
Brian
Lynn
Glen
Affiliation
Interlake Steamship
Canadian Shipowners
GR Bowler Inc
Herbert Engineering
ICF International, EPA Contractor
Sarasota County, Florida
Ohio Env Council
EERA, EPA Sub Contractor
Transport Canada
NOVA Chemicals
Caterpillar
Keystone Shipping
Toromont Power Systems
Totem Ocean Trailer Express
Interlake Steamship
State of Connecticut
Sterling Fuels
Great Lakes Commission
EPA
EPA
MECA
American Steamship
Lafarge North America
Environ, Inc.
PM Shipping
Seaway Marine Transport
ExxonMobil
Provmar Fuels Inc
Environment Canada
Canadian Shipowners
EPA
Environment Canada
Lake Carriers Association
2-34
-------
Chapter 2 Transportation Shift Analysis
Otterson
Ruhl
Samulski
Sharrow
Thompson
Topping
Trent
Tsang
Walas
Waterhouse
Weakley
Winebrake
Yuska
Brenda
Greg
Mike
James
Ted
Paul
Mireille
Chris
Fred
Alex
Jim
James
Daniel
American Maritime Operators Plans
Great Lakes Fleet
EPA
Duluth Seaway Port Authority
CLIA
Transport Canada
Transport Canada
DTE Energy
Marathon Oil
EPA
Lake Carriers Association
EERA, EPA Sub Contractor
MARAD
2-35
-------
Chapter 2 Transportation Shift Analysis
Economic Impacts of Category 3 Rule on Great Lakes Shipping:
Modeling Fuel Price Impacts on Potential Modal Diversion
Presentation from June 10,2010 Stakeholder Workshop
2-36
-------
Economic Impacts of Cs Rule on
Great Lakes Shipping:
Modeling fuel price impacts on potential modal diversion
U.S. ENVIRONMENTAL PROTECTION AGENCY
STAKEHOLDER MEETING
ANN ARBOR, MICHIGAN
JUNE 10, 2010
JAMES J. CORBETT, PHD, PE
JAMES J. WINEBRAKE, PHD
-------
Overview of Work So Far
The research question
The modeling framework
Analysis of initial scenarios
Discussion
-------
The Research Question
-------
Background
Given the expected increase in fuel prices associated
with the GS Rule, as estimated by EPA:
Q: What is the likelihood of an intermodal shift
from vessel to rail or truck modes?
We use cost functions, scenario data, and modeling
tools to frame and examine this question
-------
Understanding the Question
What is the likelihood of a
typical Great Lakes freight
movement shifting from ship...
to rail or truck modes
.. .in response to increased fuel
I prices for Great Lakes Category 3
^J vessels?
CUH
0 100 200
I ' .' u I
TT
St. Clair Power Plant, Ml
-------
The Modeling Framework
-------
Framing the Question
Understanding impacts of fuel prices on
Great Lakes goods movement requires
estimating:
o Costs involved in Great Lakes shipping
o Cost component due to fuel expenditures
o Anticipated changes in costs due to increased
fuel prices
o Comparison of costs and other factors with
alternative modes of transport
-------
Analytical Approach
Characterize Great Lakes Category 3 vessels
Develop cost functions for Great Lakes shipping
Estimate fuel cost component for vessels and
increased costs due to fuel switching
Estimate freight costs for shipping and alternative
modes (for base fuel price and estimated new price)
Examine scenarios with the increased shipping
freight rates to determine if diversion may occur
-------
Category 3 Great Lakes Vessel Characteristics
USA Flag
Vessel type
(Fuel type)
USA ^^^|
Bulk Carrier
IFO/HFO
IF0280
IF0320
Category 3 Vessels
1
4
3
Canada Flag
Vessel type
IFIIP! tvnp)
CAN
Bulk Carrier
IFO (various)
General Cargo
IFO 180
MDO
Tanker
HFO
IFO (various)
MDO
57
42
12
42
2
1
2
9
1
Data from Greenwood's Guide (2009) and Lloyd's (provided by ICF Consulting).
-------
I
Great Lakes Cs Bulk Vessel Characterization
Averages Horsepower
Average Service Speed (kts)
Average Age (years)
Fuel Type
Coal Cargo Capacity (Net tons)
Fleet Cs US Fla
10,430
13-9
36
IFO (var)
33,310
15,780
14.2
37
IFO (var)
47,900
Iron Ore Capacity (Gross tons)
37,530
59,400
-------
The Modeling Approach
The proposed analysis is comprised of three
components, each of which employ best available
data:
o Great Lakes Shipping Cost model
o Fuel consumption model
o Geospatial Intermodal Freight Transport (GIFT) Model
-------
Great Lakes Shipping Cost Model: Modeling Approach
Purpose:
o Estimate costs of Great Lakes shipping for a range of routes and
vessels and compare estimates with published freight rates for
validation
o Estimate the fraction of costs that are fuel-based
o Estimate the additional shipping costs due to fuel price increase
Approach:
o Identify key variables involved in Great Lakes shipping costs through
cost function analysis
Collect and process data on Great Lakes in order to identify "typical"
vessels and routes
o Conduct case analyses to estimate costs for certain routes
-------
Elements
included in
Great Lakes
Shipping Cost
Model
Voyage costs are the variable costs of a vessel trip:
Fuel costs for main (FM) and auxiliary engine (FA)
Port fees (P)
Canal dues and lock fees (CD)
Tug fees (T)
Operational costs are ongoing costs of vessel operation
Personnel/labor (L)
Repairs (R)
Stores (consumable supplies) (S)
Maintenance (M)
Insurance (I)
Capital costs of financing vessel equipment
Capital payments(CP)
Interest payments (IP)
Cargo handling costs (CS) are charges including:
Cargo loading charges (LC)
Cargo discharge costs (DC)
Cargo claims (CL)
Periodic maintenance (PM) is required every several
years by federal and international regulations
Stopford, M., Maritime Economics: Second Edition. 2009, New York, NY: Routledge, Taylor and Francis Group.
-------
Great Lakes Shipping Cost Model
EERA's Great Lakes Shipping Cost Model also
incorporates:
o Data specific to Great Lakes region
* Lock fees and traversing time
o Montreal-Ontario Locks, Welland Canal, Soo Locks
* Harbor Maintenance Tax
* Port and cargo-handling fees
* Shipping season
o Data representative of Great Lakes Category 3 vessels
ป Engine size, service speed, cargo capacity, age, unloading time
Ability to include/exclude capital costs
-------
Great Lakes Shipping Cost Model: Fuel Consumption
Fuel consumption model incorporates:
Specific fuel oil consumption (g/kWh)
* Main engine and auxiliary engine
* Age
M Engine power and load
M Engine type (SSD, MSB, Steam)
Speed and voyage duration
* Hours at sea and at port
o Cargo moved
* Fuel consumption per ton-mile
Range of fuel prices
* lo-year average
* Individual years 2000 - 2009
* EPA estimates for EGA rule
- Fuel Oil Price Constant 2000S - - Distillate Price Constant 2000 S
-------
Great Lakes Shipping Cost Model Validation: US
ACE Data
US Flag Bulk Vessel Ships (US$ 2002 Prices)
15,000 25,000 35,ooo 40,000 50,000 6o,ooo 80,000 100,000 120,000 130,000
Dead Weight Tonnage (metric tonnes)
Daily Fuel Cost in Port Daily Fuel Cost at Sea Daily Non-Fuel Cost
US Army Corps of Engineers, Economic Guidance Memo #02-06: FY2OO2 Deep Draft Vessel Operating Costs. 2002: Washington, DC.
-------
Great Lakes Shipping Cost Model: Summary
Model cost results appear valid:
Expected differences when cost of capital is included or not
Realistic fractions of cost components (13-18% fuel cost
contributions based on recent fuel prices)
Good agreement with published freight rate data from
current and historic sources
-------
Geospatial Intermodal Freight Transport (GIFT) Model
GIFT is jointly developed by the Rochester Institute of
Technology and the University of Delaware
> Support from US DOT/MARAD, Great Lakes Maritime Research
Institute, ARE and others
GIFT is an ArcGIS based tool that:
> Evaluates the economic, energy, and environmental costs of freight
transport
> Analyzes tradeoffs across multi-modal freight transport routes
> Examines impacts of freight transport policies
GIFT calculates optimal routing of freight between
origin and destination points
> GIFT can solve for least-cost, least-time, least emissions objectives
-------
GIFT Integrates Three Independent Networks
Rail Network
Road Network
Water Network
Hub-and-Spoke Construct
Road
Railroad
Road Node
Rail Node
Transportation Hub (Facility)
-------
GIFT Methodology: Attributes and Evaluators
GIFT includes the time,
distance and costs
associated with each
modal network feature
(water, rail and road
segments)
Time and costs are also
associated with intermodal
transfer facilities to
provide accurate route
optimization for multi-
modal routes
Rail Segment "Costs"
Distance
14.3
Time
Operating
Cost
*
Energy
CO2
NOx
-*-
mi.
Rail Cost Evaluator
Rail NOx Evaluator
Rail-Ship Segment "Costs"
Time
Operating
Cost
*
Energy
CO2
NOx
*
\ I
Rail- Ship_Cost_E valuator
Rail - Ship_N Ox_E valuator
Iship Segment "Costs"
Distance
5. 2 mi.
Time
Operating
Cost
_i
Energy
CO2
NOx
-i.
Ship_Cost_Evaluator
Ship_NOx_Evaluator
-------
Recap/Summary of Methodology
Cost Model Methodology:
o Estimate the portion of total voyage costs devoted to fuel (from
Great Lakes Shipping Cost Model)
o Calculate the impact of new fuel prices on total costs per ton-
mile and per voyage
GIFT Methodology:
o Run a scenario based on published freight rates for ship and
for rail
o Adjust the ship freight rates to include higher fuel costs
o Run a scenario with the new ship freight rate
o Observe whether GIFT assigns a diversion
-------
Initial Scenario Construction
'^^^
O
-------
Selection Criteria for Initial Scenarios
Criteria included identifying routes with
Dominant cargo types in Great Lakes shipping
Large volumes of goods movement
Multimodal opportunities
Commodity-specific origins and destinations
Two that met these criteria were selected
Commodity
Origin-
Destination
Voyage Origin- Dominant Large MultiModal Commodity
Destination Cargo Flow Option O-D
Iron Ore
Coal
Hull Rust, MN Duluth, MN -
to Gary, IN Gary, IN
Rosebud, MT Superior, WI
to Monroe, MI Monroe, MI
X
X
X
X
X
X
X
X
-------
Category 3 Vessels Identified as Traveling Scenario Routes
Coal: Superior, WI to
Monroe, MI
Iron Ore: Duluth, MN to
Gary, IN
HP
Service Speed
(kts)
Build Date
Capacity
Fuel
Average
16,560
13-5
1979^|
64,230
(net tons)
IFO ^H
Scenario
Vessel
16,560
13-5
65,000 (tons)
@ 85% load
(55,250 tons)
HP
Service Speed
(kts)
Build Date
Capacity
Fuel
Average
17,650
14.6
1977
63,870
(gross
tons)
IFO
Note: i net ton = i short ton;
Scenario
Vessel
16,560
13-5
65,000 (tons)@
85% load
(55,250 tons)
i gross ton = 1.12 short tons
-------
Analysis of Initial Scenarios
-------
Scenario Inputs: Coal Shipment Rosebud Mine to Monroe, MI
Scenario 1
Locomotive Inputs
Rail Freight Rates
Rail Fuel Price
Vessel Inputs
Vessel Freight Rate
Vessel Fuel Prices
Cargo Transfer
Inputs
Intermodal Rosebud to Monroe
24,000 Hp Locomotives moving 10,000
tons of coal at 25 mph
Rate: $68.4/ton (industry distance-
adjusted quote} for a distance of 782
miles for rate of 8.77 cents/ton-mile.
Fuel:ULSDat$2.95/gal
Vessel: 16,560 Hp vessel moving 55,250
tons of coal from Superior to Monroe at
15.5 mph.
Rate: $8/ton (industry quote) moving a
distance of 760 miles for rate of 1.05
cents/ton-mile; transfer cost of
$5.00/ton.
Fuel: HFO at $322/mt and MDO at
$444/mt.
Cost of $5.00 per ton to load from rail to
vessel
Unimodal Rosebud to Monroe
2 4,000 Hp Locomotives moving
10,000 tons of coal at 25 mph
Rate: $96. I/ton (industry distance-
adjusted quote} for a distance of 1355
miles for rate of 7.09 cents/ton-mile.
Fuel:ULSDat$2.95/gal.
Not used in an all-rail route
Not used in an all-rail route
Not used in an all-rail route
Not used in an all-rail route
-------
Results for Coal - Rosebud to Monroe MI
HFO
Train: 2 4,000 Hp locomotives moving
10,000 tons of coal from Rosebud to Duluth
at 25 mph.
Rate: $68.4/ton (industry distance-adjusted
quote) for a distance of 782 miles for rate of
8.77 cents/ton-mile.
Fuel:ULSDat$2.95/gal.
Vessel: 16,560 Hp vessel moving
55,250 tons of coal from Superior
to Monroe at 15.5 mph.
Rate: $8/ton (industry quote)
moving a distance of 760 miles for
rate of 1.05 cents/ton-mile; transfer
cost of $5.00/ton.
Fuel:HFOat$322/mt.
Total cost for moving a ton of coal based on
selected route: $80.4/ton
Alternative: Rail move directly from Rosebud
to Monroe would be 7.09 cents/ton-mile for
a distance of 1355 miles, or $96.I/ton.
i 1_^ ^di^JjL_,*_jซSsปปBซ
-------
Alternative Unimodal Rail Route
-------
Results for Coal - Rosebud to Monroe MI
MDO
Train: 2 4,000 Hp locomotives moving
10,000 tons of coal from Rosebud to Duluth
at 25 mph.
Rate: $68.4/ton (industry distance-adjusted
quote) for a distance of 782 miles for rate of
8.77 cents/ton-mile.
Fuel:ULSDat$2.95/gal.
**'-'- 4 '..
Total cost for moving a ton of coal
based on selected route: $82.0/ton
Alternative: Rail move directly from
Rosebud to Monroe would be 7.09
cents/ton-mile fora distance of 1355
miles, or $96.I/ton
Vessel: 16,560 Hp vessel moving
55,250 tons of coal from Duluth to
Monroe at 15.5 mph.
Rate: $8.54/ton (industry quote+
increased fuel costs) moving a
distance of 760 miles for rate of
1.12 cents/ton-mile; transfer cost of
$5.00/ton.
Fuel: MDOat $444/mt.
-------
Data Inputs: Iron Ore Shipment from Hull Rust to Gary, IN
Scenario 2
Locomotive Inputs
Rail Freight Rates
Rail Fuel Price
Vessel Inputs
Vessel Freight Rate
Vessel Fuel Prices
Cargo Transfer
Inputs
Intermodal Hull Rust to Gary
2 4,000 Hp Locomotives moving
10,000 tons of iron ore at 25 mph
Rate: $27.88/ton (industry distance-
adjusted quote} for a distance of 99
miles for rate of 28.16 cents/ton-mile.
Fuel:ULSDat$2.95/gal.
Vessel: 16, 560 Hp vessel moving
55,250tons of iron ore from Duluth to
Gary at 15.5 mph.
Rate: $9.8/ton ($ll/gross ton--
industry quote) moving a distance of
815 miles for rate of 1.21 cents/ton-
mile; transfer cost of $3.50/ton.
Fuel: HFO at $322/mt and MDO at
$444/mt.
Cost of $3.50 per ton to load from rail
to vessel
Unimodal Hull Rust to Gary
2 4,000 Hp Locomotives moving 10,000
tons of iron ore at 25 mph
Rate: $59.9/ton (industry distance-
adjusted quote} for a distance of 550
miles for rate of $10.89 cents/ton-mile.
Fuel:ULSDat$2.95/gal.
Not used in an all-rail route
Not used in an all-rail route
Not used in an all-rail route
Not used in an all-rail route
-------
Results for Iron Ore - Hull Rust Mine to Gary, IN
HFO
Vessel: 16,560 Hp vessel moving
55,250 tons of iron ore from Duluth
to Gary at 15.5 mph.
Rate: $9.8/ton (industry quote)
moving a distance of 815 miles for
rate of 1.21 cents/ton-mile; transfer
cost of $3.50/ton.
Fuel: HFO at $322/mt.
Train: 2 4,000 Hp locomotives moving
10,000 tons of iron ore from Hull Rust
Mine to Duluth at 25 mph.
Rate: $27.88/ton (industry distance-
adjusted quote) for a distance of 99
miles for rate of 28.16 cents/ton-mile.
Fuel: ULSD at $2.95/gal.
Total cost for moving a ton of iron ore
based on selected route: $40.9/ton
Alternative: Rail move directly from
Hull Rust to Gary would be 10.89
cents/ton-mile for a distance of 550
miles, or $59.9/ton
I
-------
Alternative Unimodal Rail Route
-------
Results for Iron Ore - Hull Rust Mine to Gary, IN
MDO
Train: 24,000 Hp locomotives moving
10,000 tons of iron ore from Hull Rust
Mine to Duluth at 25 mph.
Rate: $27.88/ton (industry distance-
adjusted quote) for a distance of 99
miles for rate of 28.16 cents/ton-mile.
Fuel: ULSD at $2.95/gal.
Vessel: 16,560 Hp vessel moving
55,250 tons of iron ore from Duluth
to Gary at 15.5 mph.
Rate: $10.4/ton (industry quote+
increased fuel costs) moving a
distance of 815 miles for rate of
1.28 cents/ton-mile; transfer cost of
$3.50 ton.
Fuel: MDO at $444/mt.
Total cost for moving a ton of iron ore
based on selected route: $41.8/ton
Alternative: Rail move directly from
Hull Rust to Gary would be 10.89
cents/ton-mile for a distance of 550
miles, or $59.9/ton
-------
Initial Scenario Result Summary
Increase in fuel price due to HFO-to-MDO shift
($i22/mt) increases total voyage costs by 6-9%
Increase in fuel price is relatively small fraction of
price differential between vessel and rail freight rates
o Increases vessel costs by less than $i/ton vs. incremental cost
of rail routes of ~$i5/ton
-------
Other Factors to Consider
Additional factors are involved in modal selection that
are not addressed when considering costs of freight
transportation only:
o Infrastructure
* Ports/terminals with required cargo-handling equipment (iron, grain)
* Locations where labor, factory, or other activities may transform these
resources
* Dock accessibility and rail yard capacity
Level of service
o Time
Other performance factors
Capacity of mode
o Value of commodity
o Market characteristics
-------
Break
AFTER BREAK:
OUR PLANNED WORK
OPEN DISCUSSION
-------
Next Steps
INPUT FROM INDUSTRY AND EPA
CONSTRUCTION OF ADDITIONAL SCENARIOS
FOR ANALYSIS
-------
Scenario Construction
Scenario Construction
involves:
Typical trade patterns and routes on
the Great Lakes
Dominant commodities and cargo
Typical origin points for port origin-
destination pairs
Characteristics of vessels identified
as traveling key routes with
examined cargo
Other factors that the industry sees
as important and relevant
Commodity Flows in Great Lakes
Iron ore trade patterns
TiKimire Harbor
Silver Bay
Two Harbors
Dulmh,
Superior
MN
Coal traJe patterns
QC
Santinkv Oซ
IN I OH
-------
Introduction for Discussion
We would like to engage you on these topics:
o Comments and questions on our methods
o Suggestions for improved or substitute data
o Discussion of initial scenario results
o Ideas for additional scenario selection
-------
Discussion Welcome
-------
Chapter 2 Transportation Shift Analysis
Analysis of Impacts of Category 3
Marine Rule on Great Lakes Shipping
Final Report
This Appendix 2C contains the report prepared by EPA's contractor, ICF International
and their subcontractor, Energy and Environmental Research Associates (EERA), documenting
the Base Case conditions for the sixteen trade route scenarios that are the subject of this
economic impact analysis and describing the transport mode shift modeling and results for
twelve of those scenarios. This appendix includes transportation mode shift results for Scenario 2
that suggest that the route-based freight rate for the All-Rail Alternative is less than both the
Base Case and the EGA freight rates. Subsequent to acceptance of this final contractor report,
EPA performed additional research with regard to Scenario 2 that led the Agency to believe this
scenario was mis-specified. Therefore, although the results of the contractor's modeling are
included in the attached report, these results are not included in EPA's summary of the results of
this study (see Section 2.1 and 8A.6) and are not considered to be applicable for the purpose of
this study.
2-37
-------
Analysis of Impacts of Category 3
Marine Rule on Great Lakes Shipping
Final Report
ENERGY AND ENVIRONMENTAL RESEARCH ASSOCIATES, LLC
Bryan Comer
James J. Corbett, Ph.D., P.E.
Erin Green
Chrisman Dager
Jordan Silberman
Karl Korfmacher, Ph.D.
James J. Winebrake, Ph.D.
ICF INTERNATIONAL
Louis Browning, D.Eng.
4/13/2011
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of
Abstract 7
Chapter 1: Introduction 9
Chapter 2: Great Lakes Vessel Fleet Characterization 10
Vessels 10
Fuels 10
Service Speeds 12
Bulk Cargo Capacity 12
Horsepower 13
Value of Goods Transported on the Great Lakes 14
Nature of Backhauls in Great Lakes Freight Transportation 14
Seasonality of Goods Movement 15
Companies Involved in Great Lakes Shipping 16
Chapter 3: Methodology 18
Calculating Default Scenario Route Freight Rates 18
Calculating the Total Route Freight Rate for the All-Rail Alternative Route 21
Chapter 4: Scenario Description and Input Assumptions 22
Description of Input Assumption Sources 23
Origin-Destination Pairs 23
Origin and Destination Ports 23
Vessel Type 23
Cargo Transported 24
Vessel Length 24
Vessel Main Engine Horsepower 25
Vessel Main Engine Specific Fuel Oil Consumption 25
Auxiliary Engine Horsepower and Load Factor 25
Vessel Operating Speed 25
Vessel Cargo Capacity 25
Assumed Cargo Load 26
Vessel Draft at Maximum Cargo Load 26
Vessel Draft at Assumed Cargo Load 26
Port Depth Limit 26
Default Scenario Route Port-to-Port Distance 27
Default Scenario Route Rail Distance 27
All-Rail Alternative Route Distance 27
Marine Vessel Freight Rate 27
Rail Freight Rate 27
Total Cargo Transfer Cost for Default Scenario Route 28
Total Cargo Transfer Cost for All-Rail Alternative Route 28
Scenario 1: Coal from Rosebud Mine, MT to Bayfront Power Plant, Wl 29
Input Assumptions 29
Scenario 2: Coal from Elk Creek Mine, CO to Georgia Pacific West Mill in Green Bay, Wl 31
Input Assumptions 31
Scenario 3: Coal from Rosebud Mine, MT to St. Clair and Monroe Power Plants, Ml 33
Input Assumptions 33
Scenario 4: Coal from Rosebud Mine, MT to Weadock and Karn Generating Plants, Ml 35
Input Assumptions 35
-------
Scenario 5: Iron ore from Empire and Tilden Mines, Ml to Algoma Steel, ON 37
Input Assumptions 37
Scenario 6: Iron ore from Quebec Cartier Mining Company, QCto ArcelorMittal, IL 39
Input Assumptions 39
Scenario 7: Iron ore from the Hull Rust Mine, MN to US Steel, IN 41
Input Assumptions 41
Scenario 8: Iron ore from Northshore Mining, MN to Severstal, OH 43
Input Assumptions 43
Scenario 9: Grain from Lake Calumet Grain Elevators, ILto Baie Comeau, QC 45
Input Assumptions 45
Scenario 10: Grain from Duluth Port Grain Elevators, MN to Baie Comeau, QC 47
Input Assumptions 47
Scenario 11: Grain from Duluth Port Grain Elevators, MN to WNY Ethanol Plant, Medina, NY 49
Input Assumptions 49
Scenario 12: Grain from Goderich Port Grain Elevators, ON to Nabisco Flour Mill, OH 51
Input Assumptions 51
Scenario 13: Stone from Port Dolomite, Ml to the J.M. Stuart Power Plant, OH 53
Input Assumptions 53
Scenario 14: Stone from Calcite Quarry, Ml to the J.M. Stuart Power Plant, OH 55
Input Assumptions 55
Scenario 15: Stone from Calcite Quarry, Ml to American Crystal Sugar Company, MN 57
Input Assumptions 57
Scenario 16: Stone from Calcite Quarry, Ml to Bruce Mansfield Power Station, OH 59
Input Assumptions 59
Chapters: Results 61
Scenario 1: Coal from Rosebud Mine, MTto Bayfront Power Plant, Wl 61
Scenario 2: Coal from Elk Creek Mine, CO to Georgia Pacific West Mill in Green Bay, Wl 63
Scenario 3: Coal from Rosebud Mine, MT to St. Clair and Monroe Power Plants, Ml 65
Scenario 4: Coal from Rosebud Mine, MT to Weadock and Karn Generating Plants, Ml 67
Scenario 5: Iron ore from Empire and Tilden Mines, Ml to Algoma Steel, ON 69
Scenario 6: Iron ore from Quebec Cartier Mining Company, QCto ArcelorMittal, IL 71
Scenario 7: Iron ore from the Hull Rust Mine, MN to US Steel, IN 73
Scenario 8: Iron ore from Northshore Mining, MN to Severstal, OH 75
Scenario 9: Grain from Lake Calumet Grain Elevators, ILto Baie Comeau, QC 77
Scenario 10: Grain from Duluth Port Grain Elevators, MN to Baie Comeau, QC 79
Scenario 11: Grain from Duluth Port Grain Elevators, MN to WNY Ethanol Plant, Medina, NY 81
Scenario 12: Grain from Goderich Port Grain Elevators, ON to Nabisco Flour Mill, OH 83
Scenario 13: Stone from Port Dolomite, Ml to the J.M. Stuart Power Plant, OH 85
Scenario 14: Stone from Calcite Quarry, Ml to the J.M. Stuart Power Plant, OH 87
Scenario 15: Stone from Calcite Quarry, Ml to American Crystal Sugar Company, MN 89
Scenario 16: Stone from Calcite Quarry, Ml to Bruce Mansfield Power Station, OH 91
Chapter 6: Discussion of Results and Sensitivity Analysis 93
Validation of Fuel Costs Compared to Freight Rates 95
Sensitivity of Results to Scenario-Specific Routing Constraints 97
References 99
-------
Table 1: Great Lakes bulk carriers by EPA engine category and flag, 2008 10
Table 2: Marine fuel distribution by type and vessel flag for all engine categories shown as number of
vessels operating on the Great Lakes, 2008 11
Table 3: Residual Fuel Blends vs. MDO fuel distribution by flag for all engine categories shown as number
of vessels operating on the Great Lakes, 2008 11
Table 4: Marine fuel distribution by type and vessel flag for Category 3 engines shown as number of
vessels operating on the Great Lakes, 2008 11
Table 5: Residual Fuel Blends vs. MDO fuel distribution by flag for Category 3 engines shown as number
of vessels operating on the Great Lakes, 2008 12
Table 6: Marine fuel distribution by type and vessel flag for Category 2 engines shown as number of
vessels operating on the Great Lakes, 2008 12
Table 7: Residual Fuel Blends vs. MDO fuel distribution by flag for Category 2 engines shown as number
of vessels operating on the Great Lakes, 2008 12
Table 8: Service speeds by flag and EPA engine category, 2008 12
Table 9: Number of vessels capable of carrying iron ore, coal, and grain by flag and EPA engine category,
2008 13
Table 10: Cargo capacities for iron ore, coal, and grain by flag and EPA engine category, 2008 13
Table 11: Installed horsepower (Hp) by flag and EPA engine category, 2008 13
Table 12: Installed horsepower by commodity, flag, and EPA engine category, 2008 14
Table 13: Quantity and value of iron ore, coal, aggregates, and grain trade on the Great Lakes, 2008.... 14
Table 14: Companies involved in Great Lakes shipping and their annual corporate revenues 17
Table 15: Summary of scenario routes and cargo types 22
Table 16: General inputs for each scenario 23
Table 17: Summary of Scenario 1 inputs 30
Table 18: Summary of Scenario 2 inputs 32
Table 19: Summary of Scenario 3 inputs 34
Table 20: Summary of Scenario 4 inputs 36
Table 21: Summary of Scenario 5 inputs 38
Table 22: Summary of Scenario 6 inputs 40
Table 23: Summary of Scenario 7 inputs 42
Table 24: Summary of Scenario 8 inputs 44
Table 25: Summary of Scenario 9 inputs 46
Table 26: Summary of Scenario 10 inputs 48
Table 27: Summary of Scenario 11 inputs 50
Table 28: Summary of Scenario 12 inputs 52
Table 29: Summary of Scenario 13 inputs 54
Table 30: Summary of Scenario 14 inputs 56
Table 31: Summary of Scenario 15 inputs 58
Table 32: Summary of Scenario 16 inputs 60
Table 33: Scenario 1 Summary Results 61
Table 34: Scenario 1 Default Scenario Route Summary 62
Table 35: Scenario 1 All-Rail Alternative Route Summary 62
Table 36: Scenario 2 Summary Results 63
Table 37: Scenario 2 Default Scenario Route Summary 64
Table 38: Scenario 2 All-Rail Alternative Route Summary 64
Table 39: Scenario 3 Summary Results 65
-------
Table 40: Scenario 3 Default Scenario Route Summary 66
Table 41: Scenario 3 All-Rail Alternative Route Summary 66
Table 42: Scenario 4 Summary Results 67
Table 43: Scenario 4 Default Scenario Route Summary 68
Table 44: Scenario 4 All-Rail Alternative Route Summary 68
Table 45: Scenario 5 Summary Results 69
Table 46: Scenario 5 Default Scenario Route Summary 70
Table 47: Scenario 5 All-Rail Alternative Route Summary 70
Table 48: Scenario 6 Summary Results 71
Table 49: Scenario 6 Default Scenario Route Summary 72
Table 50: Scenario 7 Summary Results 73
Table 51: Scenario 7 Default Scenario Route Summary 74
Table 52: Scenario 7 All-Rail Alternative Route Summary 74
Table 53: Scenario 8 Summary Results 75
Table 54: Scenario 8 Default Scenario Route Summary 76
Table 55: Scenario 8 All-Rail Alternative Route Summary 76
Table 56: Scenario 9 Summary Results 77
Table 57: Scenario 9 Default Scenario Route Summary 78
Table 58: Scenario 9 All-Rail Alternative Route Summary 78
Table 59: Scenario 10 Summary Results 79
Table 60: Scenario 10 Default Scenario Route Summary 80
Table 61: Scenario 10 All-Rail Alternative Route Summary 80
Table 62: Scenario 11 Summary Results 81
Table 63: Scenario 11 Default Scenario Route Summary 82
Table 64: Scenario 11 All-Rail Alternative Route Summary 82
Table 65: Scenario 12 Summary Results 83
Table 66: Scenario 12 Default Scenario Route Summary 84
Table 67: Scenario 12 All-Rail Alternative Route Summary 84
Table 68: Scenario 13 Summary Results 85
Table 69: Scenario 13 Default Scenario Route Summary 86
Table 70: Scenario 14 Summary Results 87
Table 71: Scenario 14 Default Scenario Route Summary 88
Table 72: Scenario 15 Summary Results 89
Table 73: Scenario 15 Default Scenario Route Summary 90
Table 74: Scenario 16 Summary Results 91
Table 75: Scenario 16 Default Scenario Route Summary 92
Table 76: Summary Results of Default Scenario Freight Rates compared to All-Rail Alternative Freight
Rates, if available (all $/cargo ton) 94
Table 77: Summary of impact of fuel price on port-to-port freight rates compared to total route freight
rates 96
Table 78: Sensitivity Results using Route-Specific constraints (all $/cargo ton) 98
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of
Figure 1: Overview map of origin-destination pairs for each scenario 8
Figure 2: U.S. Flagged Dry-Bulk Carriage in the Great Lakes over a Five-Year Period (Five-Year Average of
Monthly Data, 2004-2009) 16
Figure 3: Example of origin and destination port selection 24
Figure 4: Scenario 1 map - Rosebud Mine, MTto Bayfront Power Plant, Ashland, Wl 29
Figure 5: Scenario 2 map - Elk Creek Mine, CO to Georgia Pacific West Mill, Green Bay, Wl 31
Figure 6: Scenario 3 map - Rosebud Mine, MTto St. Clair and Monroe Power Plants, Ml 33
Figure 7: Scenario 4 map - Rosebud Mine, MT to Weadock/Karn Generating Plants, Essexville, Ml 35
Figure 8: Scenario 5 map - Empire and Tilden Mines, Palmer, Ml to Essar Steel Algoma Plant, Sault Ste.
Marie, ON 37
Figure 9: Scenario 6 map - Quebec Cartier Mining Company, Port Cartier, QCto ArcelorMittal, Chicago, IL
39
Figure 10: Scenario 7 map - Hull Rust Mine, Nibbing, MM to US Steel, Gary, IN 41
Figure 11: Scenario 8 map - Northshore Mining, Babbit, MN to Severstal, Warren, OH 43
Figure 12: Scenario 9 map - Lake Calumet Grain Elevators, Chicago, IL to Baie Comeau, QC for export to
the rest of the world 45
Figure 13: Scenario 10 map - Duluth Port Grain Elevators, Duluth, MN to Baie Comeau, QC for export to
the rest of the world 47
Figure 14: Scenario 11 map - Duluth Port Grain Elevators, Duluth, MN to WNY Ethanol Plant, Medina, NY
49
Figure 15: Scenario 12 map - Goderich Port Grain Elevators, Goderich, ON to Nabisco Flour Mill, Toledo,
OH 51
Figure 16: Scenario 13 map - Port Dolomite to J. M. Stuart Power Plant, Aberdeen, OH 53
Figure 17: Scenario 14 map - Calcite Quarry, Ml to J.M. Stuart Power Plant, Aberdeen, OH 55
Figure 18: Scenario 15 map - Calcite Quarry, Ml to American Crystal Sugar Company, Crookston, MN... 57
Figure 19: Scenario 16 map - Calcite Quarry, Ml to Bruce Mansfield Power Station, Shippingport, PA....59
Figure 20: Scenario 1 map - Rosebud Mine, MT to Bayfront Power Plant, Ashland, Wl 61
Figure 21: Scenario 2 map - Elk Creek Mine, CO to Georgia Pacific West Mill, Green Bay, Wl 63
Figure 22: Scenario 3 map - Rosebud Mine, MT to St. Clair and Monroe Power Plants, Ml 65
Figure 23: Scenario 4 map - Rosebud Mine, MT to Weadock/Karn Generating Plants, Essexville, Ml 67
Figure 24: Scenario 5 map - Empire and Tilden Mines, Palmer, Ml to Essar Steel Algoma Plant, Sault Ste.
Marie, ON 69
Figure 25: Scenario 6 map - Quebec Cartier Mining Company, Port Cartier, QCto ArcelorMittal, Chicago,
IL 71
Figure 26: Scenario 7 map - Hull Rust Mine, Hibbing, MN to US Steel, Gary, IN 73
Figure 27: Scenario 8 map - Northshore Mining, Babbit, MN to Severstal, Warren, OH 75
Figure 28: Scenario 9 map - Lake Calumet Grain Elevators, Chicago, IL to Baie Comeau, QC for export to
the rest of the world 77
Figure 29: Scenario 10 map - Duluth Port Grain Elevators, Duluth, MN to Baie Comeau, QC for export to
the rest of the world 79
Figure 30: Scenario 11 map - Duluth Port Grain Elevators, Duluth, MN to WNY Ethanol Plant, Medina, NY
81
Figure 31: Scenario 12 map - Goderich Port Grain Elevators, Goderich, ON to Nabisco Flour Mill, Toledo,
OH 83
Figure 32: Scenario 13 map - Port Dolomite to J. M. Stuart Power Plant, Toledo, OH 85
Figure 33: Scenario 14 map - Calcite Quarry, Ml to J.M. Stuart Power Plant, Aberdeen, OH 87
-------
Figure 34: Scenario 15 map - Calcite Quarry, Ml to American Crystal Sugar Company, Crookston, MN... 89
Figure 35: Scenario 16 map - Calcite Quarry, Ml to Bruce Mansfield Power Station, Shippingport, PA.... 91
-------
Energy and Environmental Research Associates (EERA) performed analysis on the potential for a
modal shift from ship to rail in Great Lakes freight transportation due to a switch from heavy fuel oil
(HFO) to marine diesel oil (MDO) in Category 3 marine diesel engines. The analysis supports the US
Environmental Protection Agency's (EPA) study on the economic impact of the Category 3 Marine Rule
on Great Lakes shipping.
EPA established a set of sixteen (16) scenarios consisting of origin and destination (O/D) pairs
representing the flow of coal, iron ore, grain, and stone in the Great Lakes region. For each Default
Scenario Route, two cases are run. The first case is called the Base Case and models a ship operating on
HFO for the main engine and MDO for the auxiliary engine. The second case is called the MDO Case and
models that same ship operating on MDO for both the main engine and the auxiliary engines. A second
route called the All-Rail Alternative Route was developed which models an all-rail route from origin to
destination, except where no all-rail route could be identified. We were able to identify all-rail
alternative routes for 11 of the 16 scenarios.
Total operating costs for transporting the commodity in the Default Scenario Route using MDO
fuel for both the main and auxiliary engines (the MDO Case) are calculated and compared to the total
operating costs of transporting the same commodity in the All-Rail Alternative Route. The goal of the
analysis was to determine if an increase in fuel prices associated with a switch from HFO to MDO for
main engine fuel-use in Great Lakes marine vessels would result in the potential for a mode shift from
ship to rail for the transportation of bulk commodities.
For 10 of 11 scenarios where an all-rail route was modeled, the All-Rail Alternative Route was
more expensive than the Default Scenario Route's MDO Case. One scenario (Scenario 2) showed that
the All-Rail Route is less expensive than the Base Case route even before adding an additional cost to
the route to account for a switch to MDO fuel use. Figure 1 shows all 16 O/D pairs. The 11 O/D pairs
that are colored yellow represent the routes where an all-rail alternative was confirmed. The five O/D
pairs that are colored gray represent routes where no all-rail alternative was identified.
-------
0 100 200
I i i
400
i
600
i
800 Miles
O= Origin, D = Destination
No All-Rail Alternative
AZ
Figure 1: Overview map of origin-destination pairs for each scenario
-------
1;
Energy and Environmental Research Associates (EERA) performed analysis in support of the US
Environmental Protection Agency's (EPA) study on the economic impact of the Category 3 Marine Rule
on Great Lakes shipping. The analysis evaluated the potential for a modal shift from ships to rail in the
Great Lakes region due to the switch from heavy fuel oil (HFO) to marine diesel oil (MDO) by US-flagged
Category 3 vessels.
The EPA selected a set of sixteen (16) scenarios consisting of origin and destination (O/D) pairs
representing the flow of particular commodities in the Great Lakes region. For this study, "Great Lakes
region" includes all the navigable streams, rivers, lakes, and other bodies of water that are within the
drainage basin of the St. Lawrence River, west of Anticosti Island, including US and Canadian waters.
The commodities represented include: coal, iron ore, grain, and stone.
Each of the 16 scenarios includes a Default Scenario Route that either makes use of the Great
Lakes for a portion of the overall route when the source or destination of the commodity is inland, or
represents a port-to-port route when the source and destination of the commodity are both at the port.
The Default Scenario Route is comprised of: (1) the Base Case which models the use of HFO for the main
engine and MDO for the auxiliary engine of the vessel; and (2) the MDO Case which models the use of
MDO for both the main and auxiliary engines on the vessel. Eleven of the scenarios include a second
route called the All-Rail Alternative Route, representing a confirmed all-rail route from origin to
destination.
In each scenario, the cost of transporting the commodity via the MDO Case of the Default
Scenario Route is compared with the cost of transporting the same commodity via the All-Rail
Alternative Route (where available). We report whether the cost of transporting the commodity is more
expensive in the MDO Case or the All-Rail Alternative Route.
This study uses the Geospatial Intermodal Freight Transport (GIFT) model, discussed in detail in
Winebrake et al. (2008) and Comer et al. (2010), to display maps of the Default Scenario Route and All-
Rail Alternative Route. Additionally, the GIFT model is used to calculate the distance (in miles) from
origin to destination for the All-Rail Alternative Route as well as the distance traveled by rail for the rail
portion of the Default Scenario Route, if any, by solving for the "least-distance" route along active rail
lines. The GIFT model is a GIS-based tool developed by the Rochester Institute of Technology and the
University of Delaware that combines the US and Canadian road, rail, and water transportation
networks through intermodal transfer facilities to create an intermodal network. The GIFT model can
solve a route from origin to destination based on user-defined objectives including least-time, least
distance, least-economic cost, least-energy, and least-emissions (including carbon dioxide [CO2], carbon
monoxide [CO], oxides of nitrogen [NOX], sulfur oxides [SOX], particulate matter [PM10], and volatile
organic compounds [VOCs]). For this study, we utilize GIFT'S visualization and least-distance
optimization capabilities.
This report is comprised of six chapters. Chapter 2 is a characterization of the Great Lakes fleet;
Chapter 3 provides the methodology for the analysis; Chapter 4 describes the inputs used in the analysis
and the sources of those inputs; Chapter 5 summarizes the results of the analysis; and Chapter 6
analyzes the results and includes a sensitivity analysis.
-------
Chapter 2: Great Lakes Vessel Fleet Characterization
Vessels
Great Lakes vessels using diesel marine engines were identified according to EPA engine
category. Category 3 engines have per cylinder displacements equal to or greater than 30 liters;
Category 2 engines have per cylinder displacements between 7 and 30 liters (U.S. Environmental
Protection Agency, 2009). In Great Lakes freight transportation, heavy fuel oil (HFO) is only used by
ships with Category 3 engines or by steam-powered vessels not considered in this study. Category 3
vessels are Great Lakes ships that carry bulk cargo and are typically large in size (dead weight tonnage,
length, and draft). Table 1 shows the distribution of Great Lakes bulk carriers by EPA engine category
and flag. The Great Lakes bulk carrier fleet (US-flag and Canadian-flag combined) is split about 50/50
between Category 3 and other engine sizes. There are a total of 69 Category 3 marine vessels operating
on the Great Lakes; however, only 12 Category 3 marine vessels are US-flag. There are 21 US-flag
Category 2 vessels and 15 US-flag steamships operating on the Great Lakes.
Table 1: Great Lakes bulk carriers by EPA engine category and flag, 2008
EPA engine category
Category 3
Category 2
Steamship
Total
Number of Vessels
(US Flag)
12
21
15
48
Number of Vessels
(Canadian Flag)
57
19
8
84
Total
69
40
22
132
Source: Harbor House Publishers (2009).
Fuels
Marine fuels, or bunkers, can be generally classified into two categories: residual fuels and
distillate fuels. Residual fuels, also known as HFO or intermediate fuel oil (IFO), are a blend of various
oils obtained from the highly viscous residue of distillation or cracking after the lighter (and more
valuable) hydrocarbon fractions have been removed. Since the 1973 fuel crisis, refineries adopted
secondary refining technologies (known as thermal cracking) to extract the maximum quantity of refined
products (distillates) from crude oil. As a consequence, the concentration of contaminants such as
sulfur, ash, asphaltenes, and metals has increased in residual fuels (Corbett & Winebrake, 2008a).
Petroleum fractions of crude oil that are separated in a refinery by a boiling process are known
as distillate fuels. Distillate marine fuels are more similar to nonroad and onroad diesel fuels, except
with differing specification limits for sulfur, viscosity, cetane and other properties. Marine distillate
grade A (Distillate Marine A or DMA) currently has an International Organization for Standardization
(ISO) (2005) specification limit of 1.5% sulfur (15,000 parts per million, or ppm) although the global
average is closer to 3,900 ppm (California Air Resources Board, 2007; Corbett & Winebrake, 2008b); for
US-sold DMA, more than 90% sampled by Det Norske Veritas (DNV) contains less than 500 ppm sulfur
(California Air Resources Board, 2007). Marine distillate grade B (Distillate Marine B or DMB) must meet
ISO specification limits of 2% sulfur, although the global average sulfur content is less than 4,000 ppm
and ~70% of US-sold DMB contains less than 800 ppm sulfur (Corbett & Winebrake, 2008b). The current
IMO Annex VI fuel sulfur standards are 4.5% globally (including the US) and 1% in the North and Baltic
Sea emission control areas (EGAs). Generally, EPA and other environmental regulations have motivated
stricter standards for onroad and nonroad distillate fuels, including requirements that rail locomotives
use an ultra-low-sulfur diesel (ULSD) fuel with less than 15 ppm sulfur (U.S. Environmental Protection
10
-------
Agency, 2010). For this study, marine diesel oils (MDO) represent a range of distillate fuels used by ships
that also meet EPA standards.
While residual fuels can be blended to meet low-sulfur standards, this essentially requires
mixing high-value distillates into low-value residuals. Refinery and market conditions make this less
economically desirable for fuel suppliers than offering marine distillates that immediately comply with
sulfur regulations and are currently fueling ships with Category 2 and Category 1 engines for auxiliary
engines and/or main engines.
The vessels operating on the Great Lakes use a variety of different marine fuel types as indicated
in Table 2. Table 3 shows that the majority of vessels are not using MDO, rather, they are using other
marine fuels. Under the Category 3 Marine Rule, these vessels may eventually have to switch to a
marine fuel oil with a sulfur content of less than 1,000 ppm. Low-sulfur fuel meeting EPA standards is
likely to be a marine distillate fuel, unless a low-sulfur residual fuel is introduced into the Great Lakes
market as a new product; current understanding suggests the demand for such a new product is
insufficient and vessels will comply with a switch to MDO.
Table 2: Marine fuel distribution by type and vessel flag for all engine categories shown as number of vessels operating on
the Great Lakes, 2008
Flag
Canada
United
States
Grand
Total
HFO
9
15
24
IFO/
HFO
0
3
3
IFO
120
2
0
2
IFO
150
2
0
2
IFO
180
33
1
34
IFO
280
0
4
4
IFO
320
0
4
4
IFO
350
2
0
2
IFO
380
6
0
6
IFO
40
4
0
4
IFO
60
4
0
4
IFO
2
0
2
MDO
20
21
41
Table 3: Residual Fuel Blends vs. MDO fuel distribution by flag for all engine categories shown as number of vessels operating
on the Great Lakes, 2008
Flag
Canada
United States
Grand Total
Residual Fuel Blends
64
27
91
MDO Fuel
20
21
41
Table 4 presents the distribution of marine fuel types for Category 3 engines. Most Category 3
engines are operating on IF 180 fuel.
Table 5 shows that the majority of Category 3 engines are using residual fuel blends. Category 2
vessels operating on the Great Lakes mainly use MDO as presented in Table 6 and Table 7.
Table 4: Marine fuel distribution by type and vessel flag for Category 3 engines shown as number of vessels operating on the
Great Lakes, 2008
Flag
Canada
United
States
Grand
Total
HFO
2
0
2
IFO/
HFO
0
3
3
IFO
120
1
0
1
IFO
150
2
0
2
IFO
180
32
1
33
IFO
280
0
4
4
IFO
320
0
4
4
IFO
350
2
0
2
IFO
380
5
0
5
IFO
40
4
0
4
IFO
60
4
0
4
IFO
2
0
2
MDO
3
0
3
11
-------
Table 5: Residual Fuel Blends vs. MDO fuel distribution by flag for Category 3 engines shown as number of vessels operating
on the Great Lakes, 2008
Flag
Canada
United States
Grand Total
Residual Fuel Blends
54
12
66
MDO Fuel
3
0
3
Table 6: Marine fuel distribution by type and vessel flag for Category 2 engines shown as number of vessels operating on the
Great Lakes, 2008
Flag
Canada
United States
Grand Total
IFO 120
1
0
1
IF 180
1
0
1
MDO
17
21
38
Table 7: Residual Fuel Blends vs. MDO fuel distribution by flag for Category 2 engines shown as number of vessels operating
on the Great Lakes, 2008
Flag
Canada
United States
Grand Total
Residual Fuel Blends
2
0
2
MDO Fuel
17
21
38
Service Speeds
Service speeds of Great Lakes bulk carriers range from 9-17 knots (kts) with an average speed of
13.6 kts as presented in Table 8. The average service speed does not vary much among engine
categories.
Table 8: Service speeds by flag and EPA engine category, 2008
Max of Service Speed (kts)
Min of Service Speed (kts)
Average of Service Speed (kts)
Canadian
Cat 2
16.3
9.0
12.7
Cat 3
17.0
10.0
13.7
United States
Cat 2
16.0
10.0
13.8
Cat 3
15.0
13.5
14.2
Bulk Cargo Capacity
Great Lakes vessels carry a variety of different cargoes. Table 9 provides a reference for the
number of vessels capable of carrying iron ore, coal, and grain by flag and EPA engine category.
Relatively few vessels carry grain and all are Canadian-flagged. Typically, vessels can be used to carry
more than one commodity; for example, all of the vessels that carry iron ore can also carry coal and
12
-------
stone, and some grain vessels will backhaul iron ore (currently only Canadian-flagged). Table 10 gives
statistics on the cargo capacities for iron ore, coal, and grain by flag and EPA engine category.
Table 9: Number of vessels capable of carrying iron ore, coal, and grain by flag and EPA engine category, 2008
Commodity
Iron Ore
Coal
Grain
Canadian
Cat 2
11
11
5
Cats
33
33
12
Steamship
8
8
4
United States
Cat 2
21
21
0
Cats
12
12
0
Steamship
13
13
2
Total
98
98
23
Table 10: Cargo capacities for iron ore, coal, and grain by flag and EPA engine category, 2008
Commodity
Iron Ore
(gross tons)*
Coal
(net tons)
Grain
(metric tons)
Capacity
Maximum
Minimum
Average
Maximum
Minimum
Average
Maximum
Minimum
Average
Canadian
Cat 2
32,700
5,880
17,873
31,100
6,880
16,424
26,159
5,974
12,557
Cat3
38,200
4,550
29,699
39,500
5,050
27,695
35,760
4,582
24,766
United States
Cat 2
78,850
14,900
42,908
71,300
7,850
34,636
N/A
N/A
N/A
Cat 3
74,000
12,650
52,395
71,250
12,450
41,807
N/A
N/A
N/A
Note: All analyses in this report use net tons, converting gross or metric as needed, per notes here.
1. Gross ton: 2,240 pounds of a given material. This measure is used mostly for iron ore by mining companies.
Also referred to as a long ton. To convert a gross ton to a net ton, multiply the gross ton total by 1.12.
2. Net ton: 2,000 pounds of a given material. Also referred to as a short ton. To convert a net ton to a gross
ton (see previous entry), multiply the net ton by .89286.
Horsepower
Table 11 gives a summary of the range and average horsepower of Great Lakes bulk carriers by
flag and EPA engine category. Table 12 gives horsepower range and average by commodity carried.
Since the same ships carry both iron ore and coal, the horsepower values are the same.
Table 11: Installed horsepower (Hp) by flag and EPA engine category, 2008
Values
Max of Installed Hp
Min of Installed Hp
Average of Installed Hp
Canadian
Cat 2
9,408
1,880
5,705
Cat 3
12,000
1,120
8,384
United States
Cat 2
14,400
850
8,428
Cat 3
19,500
3,240
13,465
13
-------
Table 12: Installed horsepower by commodity, flag, and EPA engine category, 2008
Flag
Canadian
United
States
Commodity
Iron Ore
(and Stone)
Coal
Grain
Iron Ore
(and Stone)
Coal
Grain
Max Installed Hp
Cat 2
9,378
9,378
8,000
14,400
14,400
N/A
Cats
11,094
11,094
10,881
19,500
19,500
N/A
Min Installed Hp
Cat 2
1,880
1,880
1,880
2,150
2,150
N/A
Cats
1,860
1,860
1,860
3,240
3,240
N/A
Avg. Installed Hp
Cat 2
5,372
5,372
4,642
8,807
8,807
N/A
Cats
8,965
8,965
8,128
13,465
13,465
N/A
Total Average
8,067
8,067
7,102
11,136
11,136
N/A
Value of Goods Transported on the Great Lakes
Many different commodities are transported in the Great Lakes region. The top four bulk
commodities traded on the Great Lakes are iron ore, coal, limestone, and grain (Lake Carriers'
Association, 2007a; U.S. Army Corps of Engineers, 2008). In 2007, iron ore and steel products where
the number one commodity imported to the Great Lakes and grain was the number one commodity
exported from the Great Lakes (U.S. Army Corps of Engineers, 2009). Table 13 presents the value of iron
ore, coal, stone, and grain shipped and received in the Great Lakes. These commodities can be
transported by various modes including ship, rail, and truck. This study models several scenarios for the
transport of the following bulk commodities: coal, iron ore, grain, and stone.
Table 13: Quantity and value of iron ore, coal, aggregates, and grain trade on the Great Lakes, 2008
Commodity
Iron ore/Steel
Products
Coal
Aggregates (including
limestone)
Grain
Thousands of Net Tons
Shipped
541
54
147
2,302
Received
1,184
361
754
22
Within1
58,454
39,157
31,299
2,773
Total
60,179
39,572
32,199
5,097
Value
(Millions of 2007$)
$3,318
$1,553
$2,266
$680
Source: (U.S. Army Corps of Engineers, 2009). Quantity shipped between and within US ports located on waterways on
the Great Lakes system.
Nature of Backhauls in Great Lakes Freight Transportation
Backhaul refers to the practice of carrying cargo on both legs of a round-trip delivery; the
"backhaul" is the cargo carried on the return trip. Owners arrange backhauls to generate revenue on
the return trip to cover labor and other expenses. There are two types of backhauls on the Great Lakes.
The first type of backhaul involves ocean-going vessels ("Salties"). Often, a Salty will unload its iron ore
cargo at its destination within the Great Lakes (e.g., Gary, IN) and take on grain for export out of the
Great Lakes overseas to Europe or Africa (SLSDC & Saint Lawrence Seaway Development Corporation,
2002; Transportation Research Board, 2008). The second type of backhaul involves U.S. and Canadian
vessels operating solely on the Great Lakes. For example, an ore carrier may take iron ore from mines in
14
-------
Quebec to Gary, IN and backhaul grain. In another example, an ore carrier may take iron ore or coal
from the Head of Lakes to Lake Erie destinations and backhaul fluxing stone, sugar stone, or
construction stone from Michigan quarries back to Head of Lakes. There are two important points
about backhauls on the Great Lakes. First, not all trips have backhauls. Second, a backhaul may cover
only a portion of the return trip, and may or may not be a full load. For example, it would be rare that
all trips from Duluth, MN to Ashtabula, OH would be associated with equal return hauls of some other
cargo. More likely the ship would pick up salt in Cleveland and take it to Michigan. Because of the
uncertainty of backhauls, this study estimates fuel costs and freight rates without considering backhaul
in its analysis. It is therefore a conservative analysis because it applies the fuel price increase associated
with a switch from HFO to MDO to the fuel used for a round-trip journey without accounting for
potential backhaul revenue generation.
Seasonality of Goods Movement
The Great Lakes/St. Lawrence Seaway (GLSLS) is typically open for navigation from late March to
late December (SLSMC and SLSDC, St. Lawrence Seaway Management Corp, & St. Lawrence Seaway
Development Corp, 2010). Ice begins forming on the Great Lakes in December and can form up to three
to four feet thick. Slabs of floating ice piled on top of each other, called windrows, can reach 10 to 15
feet thick (Lake Carriers' Association, 2007c).
The U.S. Coast Guard is charged with keeping shipping lanes on the Great Lakes open during ice
season to ensure that industry can continue to operate year round. Approximately 16 percent of
American dry-bulk cargo is transported during periods of ice cover (Lake Carriers' Association, 2007c).
Figure 2 shows the average monthly carriage of dry-bulk cargo on the Great Lakes based on a
five-year average between 2004 and 2009. The shipments of each commodity remain fairly constant
throughout the year but then significantly decrease during the winter months. However, shipments of
various commodities, including iron ore and coal, occur during ice-covered months. Little dry-bulk cargo
is transported on the lakes during January, and less is transported during February.
15
-------
U.S. Flagged Dry-Bulk Carriage in the Great Lakes over a
Five-Year Period
(Five-Year Average of Monthly Data, 2004-2009)
6,000,000
5,000,000
r 4,000,000
-------
14: in
Company
Algoma
Central Corp.
CSL Group Inc.
American
Steamship Co.
Upper Lakes
Group Inc.
Transport
Desgagnes Inc.
Interlake
Steamship Co.
Grand River
Navigation Co.
Lower Lakes
Towing Ltd.
Great Lakes
Fleet Inc.
Central Marine
Logistics
GLF Great
Lakes
Gravel and
Lake Services
Inland Lakes
Transportation
Purvis Marine
Ltd.
Transport
Igloolik Inc.
Vanguard
Shipping
Voyager
Maritime Inc
KK Integrated
Logistics
Flag
CAN
CAN
USA
CAN
CAN
USA
USA
CAN
USA
USA
USA
CAN
USA
CAN
CAN
CAN
CAN
USA
Number
ofC3
Vessels
19
16
1
9
4
5
1
1
3
0
1
0
0
1
0
0
0
1
Number
ofC2
Vessels
3
0
14
2
2
1
4
4
0
1
0
1
1
0
1
1
1
0
C3 + C2
Vessels
22
16
15
11
6
6
4
4
3
1
1
1
1
1
1
1
1
1
Annual
Corp.
Revenue
(if available)
$520M
(2009)1
Unknown
$272M
(2008)2
Unknown
$200M (year
unknown)3
Unknown
$85M
(2009)4
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Company Website
http://www.algonet.com/
http://www.csl.ca/
http://www.americansteamship.com/
http://www.upperlakes.com/
http://www.groupedesgagnes.eom/e
n/home/l.cfm
http://www.interlake-steamship.com/
http://www.randlogisticsinc.com/
http://www.lowerlakes.com/
http://www.randlogisticsinc.com/
N/A
N/A
N/A
N/A
N/A
http://www.purvismarine.com/
N/A
N/A
N/A
http://www.kkil.net
Algoma Central Corporation (2010); 2GATX Corporation (2009); 3Ryan (2010); 4Grand River Navigation Co. and
Lower Lakes Towing Ltd. are owned by Rand Logistics, Inc. The FY 2009 annual revenue for Rand Logistics, Inc. as
a whole was approximately $85M (Rand Logistics Incorporated, 2010)
17
-------
3:
Each scenario includes a Default Scenario Route that either makes use of the Great
Lakes for a portion of the overall route when the source or destination of the commodity is inland, or
represents a port-to-port route when the source and destination of the commodity are both at the port.
Except where no all-rail route could be identified, a second route called the All-Rail Alternative Route is
included and represents an all-rail route from origin to destination.
In the Default Scenario Route, two cases are evaluated. The first case (Base Case) models a ship
operating on HFO for the main engine and MDO for the auxiliary engine. The second case (MDO Case)
models that same ship operating on MDO for both the main engine and the auxiliary engines. An
activity-based fuel cost model is used to calculate the incremental freight rate increase from the Base
Case to the MDO Case due to a switch from HFO to MDO fuel. The MDO Case freight rate increase is the
sum of the Base Case Voyage Rate along with any rail freight rate plus cargo transfer costs accumulated
along the route. Our analysis compares the MDO Case freight rate to the All-Rail Alternative Route
freight rate to determine whether the freight rate increases due to MDO fuel use are sufficiently high to
cause a potential "switchover" to rail. Details of the methodology are presented in the following
sections.
Fuel costs associated with vessel operation for the Default Scenario Routes are calculated using
an activity-based fuel consumption model that accounts for vessel operation "at sea" and "in port."
Incremental fuel costs for the voyage can be determined by comparing the Base Case fuel costs (using
HFO prices) with the MDO Case fuel costs (using MDO prices). This incremental fuel cost is then added
to the voyage freight rates to estimate new (MDO Case) freight rates under the Category 3 Rule. The
voyage freight rates were obtained through communication with Chrisman Dager (2010) who provided
EERA with appropriate values on a scenario-by-scenario basis. Key equations for this analysis are shown
below.
ME sea * ^ME + ^MDO * ^AE * ^AE at sea * WAE) * Dptp H- Sa H- 10
where,
VFCseabc = Voyage fuel costs at sea for the Base Case in dollars
PHFO = Price of HFO fuel in dollars per metric ton
CME = Specific Fuel Oil Consumption for the main engine in grams per kilowatt-hour
LMEsea = Main engine load factor at sea as a percent (see Equation 2)
I/I/ME = Rated power of the main engine in kilowatts
PMDO = Price of MDO fuel in dollars per metric ton
CAE = Specific Fuel Oil Consumption for the auxiliary engine in grams per kilowatt-hour
l-AEsea = Auxiliary engine load factor at sea as a percent
WAE = Rated power of the auxiliary engine in kilowatts
Dptp = Port-to-port distance in miles
Sa = Vessel operating speed in miles per hour
Main engine load (LMEsea) can be estimated using the cubic propeller law for fixed-pitched
propellers and displacement hulls as shown in Equation 2.
18
-------
-
MEsea ~
S
a
where,
LMEsea = Main engine load factor at sea as a percent
Sm = The vessel's maximum operating speed in miles per hour
VFCport bc (PHPO * CME * LME port * WME + PMDO * CAE * LAE port * WAE) * Hport : 10
where,
VFCpon be = Voyage fuel costs for the Base Case in port in dollars
PHFO = Price of HFO fuel in dollars per metric ton
CME = Specific Fuel Oil Consumption for the main engine in grams per kilowatt-hour
l-MEpon = Main engine load factor in port as a percent (zero load assumed in port)
I/I/ME = Rated power of the main engine in kilowatts
PMDO = Price of MDO fuel in dollars per metric ton
CAE = Specific Fuel Oil Consumption for the auxiliary engine in grams per kilowatt-hour
l-AEpon = Auxiliary engine load factor in port as a percent
WAE = Rated power of the auxiliary engine in kilowatts
Hport = Hours in port
be sea bc + VFCport bc
where,
VFCtotalbc = Total voyage fuel cost for the Base Case in dollars
eabc = Voyage fuel costs for the Base Case at sea in dollars
ort be = Voyage fuel costs for the Base Case in port in dollars
19
-------
VFCper ton be ~ VFCtotai be + T * 2
where,
VFCper tonbc = Voyage fuel costs for the Base Case in dollars per ton
VFCtotai bc = Total voyage fuel cost for the Base Case in dollars
T = Cargo load in net tons
We multiply by "2" in order to account for fuel costs associated with making an empty return
trip to the port of origin.
The above equations for the Base Case are repeated for the MDO Case, but using MDO fuel
prices specified by EPA. The "incremental fuel cost increase" due to the shift from HFO to MDO fuel is
given as the difference between the VFC for the Base Case and the VFC for the MDO Case. This
incremental cost increase (in $/cargo ton) is added to the freight rate for the vessel leg of each Default
Scenario Route to obtain a vessel freight rate under the MDO Case, as shown in Equation 6.
per ton MDO VFCper ton BC)
where,
FRMDO = the new (calculated) freight rate ($/cargo ton) using MDO
FRBC = the freight rate ($/cargo ton) using HFO
The freight rates for the vessel leg of each Default Scenario Route are added to the rail leg of
each Default Scenario Route (if applicable) to obtain a total freight rate ($/cargo ton). Rail rates (F/?dsrra//)
are calculated by multiplying rates ($/cargo ton-mile) by rail distance as shown below. In addition, any
transfer costs are included ($/cargo ton) to determine an overall (total) freight rate for the origin-
destination pair.
F^dsr rail ~ DTMasr raii * Ddsr raii
where,
FRdsr ran = Rail freight rate in dollars per cargo ton
DTMdsrrail = Rail freight rate in dollars per cargo ton-mile
Ddsr ran = Rail distance in miles
TRCBC FRBC + FRdsr raii + TCasr
where,
TRCBC = Total route freight rate for the Base Case in $/cargo ton
FRBC = Vessel freight rate for the Base Case in $/cargo ton
sr ran = Rail freight rate (used in both the Base Case and the MDO Case) in $/cargo ton
sr = Total transfer costs (used in both the Base Case and the MDO Case) in $/cargo ton
20
-------
TRCMDO FRMDO + FRdsr raii + TCasr
where,
TRCMDO = Total route freight rate for the Base Case in $/cargo ton
FRivioo = Vessel freight rate for the Base Case in $/cargo ton
FRdsr ran = Rail freight rate (used in both the Base Case and the MDO Case) in $/cargo ton
TCdsr = Total transfer costs (used in both the Base Case and the MDO Case) in $/cargo ton
The All-Rail Alternative Route also has an associated freight rate; this is compared to the MDO
Cose freight rate in order compare freight rates between Great Lakes routes and all-rail alternatives.
The equation for calculating the rail freight rate in the All-Rail Alternative Route is shown below, along
with the equation for calculating total freight rates that include any associated transfer costs with the
All-Rail Alternative Route.
where,
FRaiiraii = Rail freight rate in dollars per cargo ton
DTMaiiraii = Rail freight rate in dollars per cargo ton-mile
D an ran = Rail distance in miles
where,
TRCaiira/i = Total route freight rate for the all-rail scenario in dollars per ton
FR aii ran = Rail freight rate used in the all-rail scenario in dollars per ton
TCaiira/i = Total transfer costs used in the all-rail scenario in dollars per ton
21
-------
4;
This chapter provides an overview of each of the scenarios evaluated in the report, as well as
key input assumptions for each of these scenarios. Table 15 summarizes the origin and destination
(O/D) pairs and the cargo transported for the sixteen (16) scenario routes. These scenarios were
provided by EPA and more information is available in Chapter 2 and Section 8A.5 of Chapter 8 in EPA's
Economic Impacts of the Category 3 Marine Rule on Great Lakes Shipping (2011). Table 16 provides a
description of the general inputs used in each scenario.
15: of
Scenario #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Origin (Port Used)
Rosebud Mine, MT
(Port of Superior, Wl)
Elk Creek Mine, CO
(Port of South Chicago, IL)
Rosebud Mine, MT
(Port of Superior, Wl)
Rosebud Mine, MT
(Port of Superior, Wl)
Empire and Tilden Mines, Ml
(Port of Marquette, Ml)
Quebec Cartier Mining Co., QC
(Port Cartier, QC)
Hull Rust Mine, MN
(Port of Duluth, MN)
Northshore Mining, MN
(Port of Silver Bay, MN)
Lake Calumet Grain Elevators, IL
(Port of Chicago, IL)
Duluth Port Grain Elevators, MN
(Port of Duluth, MN)
Duluth Port Grain Elevators, MN
(Port of Duluth, MN)
Goderich Port Grain Elevators, ON
(Port of Goderich, ON)
Port Dolomite, Ml
(Port Dolomite, Ml)
Calcite Quarry, Ml
(Calcite Quarry Port, Ml)
Calcite Quarry, Ml
(Calcite Quarry Port, Ml)
Calcite Quarry, Ml
(Calcite Quarry Port, Ml)
Destination (Port Used)
Bayfront Power Plant, Wl
(Port of Ashland, Wl)
Georgia Pacific West Mill, Wl
(Port of Green Bay, Wl)
St. Clair & Monroe Power Plants, Ml
(St. Clair and Monroe Ports, Ml)
Weadock & Karn Generating Plants, Ml
(Port of Essexville, Ml)
Algoma Steel, ON
(Port of Algoma, Sault Ste. Marie, ON)
ArcelorMittal, IL
(Port of Chicago-Burns Harbor)
U.S. Steel, IN
(Port of Gary, IN)
Severstal, OH
(Port of Ashtabula, OH)
Export to Rest of World (RoW)
(Port of Baie Comeau, QC)
Export to RoW
(Port of Baie Comeau, QC)
WNYEthanol Plant, NY
(Port of Buffalo, NY)
Nabisco Flour Mill, OH
(Port of Toledo, OH)
J.M. Stuart Power Plant, OH
(Port of Toledo, OH)
J.M. Stuart Power Plant, OH
(Port of Toledo, OH)
American Crystal Sugar Co., MN
(Port of Duluth, MN)
Bruce Mansfield Power Station, PA
(Port of Ashtabula, OH)
Cargo
Type
Coal
Coal
Coal
Coal
Iron Ore
Iron Ore
Iron Ore
Iron Ore
Grain
Grain
Grain
Grain
Stone
Stone
Stone
Stone
22
-------
Table 16: General inputs for each scenario
Data description
General or
Scenario-specific
Value
Units
Vessel Fuel Type (defined under baseline and
control conditions)
EPA Specified Fuel Prices
Auxiliary Engine Power1
Auxiliary Engine Specific Fuel Oil Consumption
Auxiliary Engine Load Factor in Port1
Main Engine Load Factor in Port
Rail Fuel Type
Rail Fuel Price
Rail Energy Intensity
General
General
HFOorMDO
$424/MTHFO
$ 617/MT MDO
Varied using Equation 2.
3% of main engine power
Categorical
$/metricton (MT)
Percent of rated
power
kW
General
General
General
General
General
Percent
Percent
Ultra-Low Sulfur Diesel (ULSD) Categorical
328'
BTU/ton-mile
^ee Auxiliary Engine Horsepower and Load Factor section below. 2U.S. Energy Information Administration, Annual
Energy Outlook, Freight Transportation Energy Use. The
average value of 328 Btu/ton-mile is calculated using the 2015 forecasts published in the 2009 and 2010 AEO
reports. See Table 67 of the Supplemental Demand Sector Data Tables, available at
http://www.eia.doe.gov/oiaf/aeo/aeoref tab.html, and
http://www.eia.doe.gov/oiaf/aeo/supplement/stimulus/suparra.htm
Description of Input Assumption Sources
In addition to the general input assumptions above, the analysis requires scenario-specific input
assumptions that relate to the vessels, routes, and port characteristics for each scenario. This section
describes the sources of each scenario-specific input assumption used in the analysis. The following
headings correlate to the rows found in each scenario's input summary table.
Origin-Destination Pairs
The origin-destination pairs for each scenario used in the analysis were specified by the US
Environmental Protection Agency (EPA) following discussions with EERA and after receiving input from
stakeholders.
Origin and Destination Ports
The origin and destination ports are those ports that are used in the Default Scenario Route for
each scenario. The Default Scenario Route either makes use of the Great Lakes for a portion of the
overall route when the source or destination of the commodity is inland, or represents a port-to-port
route when the source and destination of the commodity are both at the port (e.g. Scenarios 9 and 10).
Origin and destination port characteristics were selected based on the characteristics of each scenario
and EPA consultation with stakeholders and EERA discussion with topical experts (Dager, 2010). For
example, Figure 3 shows the origin port selected for Scenario 4 as the Port of Duluth, MN and the
destination port as the Port of Essexville, Ml.
Vessel Type
Each vessel modeled is assumed to be a bulk carrier equipped with a self-unloader. Vessels with
a self-unloader have a conveyor system that allows the vessel to discharge its cargo into a pile on land
after arriving at the dock. Self-unloaders make it possible for a vessel to unload its cargo without shore-
23
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side assistance. Greenwood's Guide to Great Lakes Shipping (2009) indicates that every Category 3
vessel operating on the Great Lakes is equipped with a self-unloader; therefore, bulk carriers with self-
unloaders are modeled for each scenario.
Legend
CASE STUDY 4
OD PAIRS
DEFAULT- INTERMODAL
500
ALTERNATIVE - RAIL ONLY
1,000 Miles
Figure 3: Example of origin and destination port selection.
Cargo Transported
The EPA specified the cargoes that would be modeled for each scenario. The analysis models
the transportation of four bulk commodities: coal, iron ore, grain, and stone. Scenarios 1 through 4
model coal transportation; Scenarios 5 through 8 model iron ore transportation; Scenarios 9 through 12
model grain transportation; and Scenarios 13-16 model stone transportation.
Vessel Length
In choosing vessels to model, the analysis considered scenario characteristics that limit the
length of the vessel. For example, any route that transits the Welland Canal would be limited to a
maximum vessel length of 740 feet. However, in most cases, the limitation on vessel length came from
the length of the dock that the vessel would use at port. Based on length restrictions, the maximum
length vessel that could transit the route completely was chosen. In all, three different vessels are
modeled with lengths of 1,000 feet (Scenarios 3, 4, 7, and 8), 770 feet (Scenarios 13, 14, 15, and 16), and
635 feet (Scenarios 1, 2, 5, 6, 9, 10, 11, and 12). The study applies representative characteristics for
each vessel based on the bulk carriers/self-unloaders found in the Greenwood Great Lakes Shipping
Guide (2009). All vessels are assumed to be Category 3 vessels because the purpose of the study is to
evaluate the economic impacts of the Category 3 Marine Rule. It should be noted that this study does
not model particular vessels; rather we are modeling representative vessels that are the appropriate
24
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length, cargo capacity, and power that could realistically transport the specified commodity along each
route examined in this report.
The main engine horsepower is dependent on the vessel being modeled. Horsepower data
were determined by consulting Greenwood's Great Lakes Shipping Guide (2009) and Lloyds Register
data provided by ICF Consulting (Browning, 2010). The following horsepower (Hp) values are used in
this analysis: 16,000 Hp for 1,000 foot vessels; 11,000 Hp for 770 foot vessels; and 7,200 Hp for 635 foot
vessels. Main engine horsepower values were chosen after analyzing power ratings for Great Lakes
vessels with these lengths and are appropriate according to stakeholder input and expert judgment for
vessels carrying the cargoes (i.e. coal, grain, iron ore, and stone) presented in each scenario.
Data for diesel engine specific fuel oil consumption is included in EPA's Regulatory Impact
Analysis for the Category 3 Marine Rule (2009). The main engine specific fuel oil consumption varies
depending on the age of the vessel's engine being modeled; the newer the engine, the lower the specific
fuel oil consumption. We model three different vessels with lengths of 635, 770, and 1000 feet. We
assumed a fuel oil consumption of 236 grams per kilowatt-hour (g/kWh) for 635 foot vessels (1950 to
1960 engine build date), 196 g/kWh for 770 foot vessels (1980 or 1981 engine build date), and 231
g/kWh for 1000 foot vessels (1961 to 1965 engine build date). These assumptions are reported in best
practices for preparing port emission inventories (Browning & Bailey, 2006) and consistent with bulk
vessel calculations in the Second IMO Greenhouse Gas Study (Buhaug et al., 2009).
As stated in the EPA's Economic Impacts of the Category 3 Marine Rule on Great Lakes
Shipping report (Chapter 4, Section 4.4.1.3) (2011), we do not have data for the number or type of
auxiliary units installed on Great Lakes vessels. Thus, we apply general and uniform assumptions about
the fraction of energy used by auxiliaries at sea and in port. At sea, we assume that the auxiliary engine
represents approximately 3% of main engine horsepower. An assumption that auxiliary engine in-use
power during our scenario analysis is small may be reasonable given that only one (or at most two) of
several auxiliary generator sets are operating at sea. While in port, the auxiliary systems may be
operating with more engines, especially during cargo offloading operations. We acknowledge that
specific auxiliary engine data could be determined in future studies; however, given the focus on main
engine fuel switching, this was out of scope for this work. Similar assumptions to those used here are
reported in best practices for preparing port emission inventories (Browning & Bailey, 2006) and
consistent with bulk vessel calculations in the Second IMO Greenhouse Gas Study (Buhaug et al.,
2009).
The typical maximum operating speed for the vessels modeled was 14 knots (~16 mph) (Harbor
House Publishers, 2009). Through stakeholder input, solicited and distributed to EERA from EPA, the
operating speed on the lakes was adjusted as follows: 12 knots (~14 mph) for Scenarios 1, 2, 9, 10, 11
and 12; and 14 knots (~16 mph) for Scenarios 3, 4, 5, 6, 7, 8, 13, 14, 15, and 16.
The vessel cargo capacity was chosen by examining the Greenwood's Guide to Great Lakes
Shipping (2009) to find appropriate cargo capacities for the modeled vessels. Additionally, EPA solicited
input from stakeholders on this issue. The following vessel cargo capacities were used in the analysis:
25
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57,200 net tons for Scenarios 3, 7, and 8; 49,300 net tons for Scenarios 13, 14, 15, and 16; 47,510 net
tons for Scenario 4; and 18,150 net tons for Scenarios 1, 2, 5, 6, 9, 10, 11, and 12.
Assumed Cargo Load
The assumed cargo load is the amount of the commodity in net tons that is transported along
the route. The analysis assumes that the cargo load is 85% of the vessel cargo capacity provided that
the maximum allowable vessel draft at the loading or unloading dock does not require the load to be
less than 85%. If the load needs to be less than 85% of the vessel cargo capacity, Equation 12 is applied.
Equation 12. Calculating assumed scenario cargo load
Assumed Cargo Load = Cvessel - TL * (Dmax - Dassumed)
where
CVessei = Vessel cargo capacity in net tons, using adjustments described in Table 10
Dmax = Vessel draft at maximum cargo load in feet
Dassumed = Vessel draft considering constrained port or channel conditions in feet
TL = Tons of vessel cargo capacity lost per foot of draft reduction in net tons per foot
The term, tons of vessel cargo capacity lost per foot of draft reduction (TL), is a function of
vessel size and was obtained from the Lake Carriers' Association (2007b). The values for TL are: 1,284 for
Scenarios 1, 2, 5, 9, 11, and 12; and 3,204 for Scenario 4. Scenarios 3, 6, 7, 8, 10, 13, 14, 15, and 16 used
an assumed cargo load of 85% of the vessel cargo capacity because there were no restrictions requiring
a lighter load. Selecting an assumed cargo load of 85% reflects our understanding of actual cargo moves
in the Great Lakes following discussion with experts and also creates a more conservative estimate of
marine vessel freight rates in $/cargo ton for the purposes of this study. The results of our analysis
would not change had we selected an assumed cargo load greater than 85%.
Vessel Draft at Maximum Cargo Load
The vessel draft at maximum cargo load is assumed to be 29 feet for the 1,000 foot and 770 foot
vessels, and 28 feet for the 625 foot vessels modeled. These drafts were chosen after researching the
range of typical drafts for 1,000 foot, 770 foot, and 635 foot vessels (Harbor House Publishers, 2009).
Vessel Draft at Assumed Cargo Load
The default assumption is that the assumed cargo load is 85% of the vessel's cargo capacity.
Using Equation 12, we can solve for Dassumed(which in this case equals the vessel draft at assumed cargo
load) using a tons of vessel cargo capacity lost per foot of draft reduction (TL) value of 1,284 for
Scenarios 6 and 10 (635 foot vessel); 1,524 for Scenarios 13, 14, 15, and 16 (770 foot vessel); and 3,204
for Scenarios 3, 7, and 8 (1000 foot vessel) (Lake Carriers' Association, 2007b). For scenarios that had
port or channel restrictions (Scenarios 1, 2, 4, 5, 9, 11, and 12), the vessel draft at assumed cargo load
was set to equal the "Port Depth Limit" described next.
Port Depth Limit
The port depth limit equals the maximum allowable vessel draft that can be accepted at the
load dock or unload dock at the port (whichever is shallower). This value was obtained by researching
the various dock depth limits at the ports for loading and unloading the commodity being modeled in
each scenario. Dock depth limits for US ports were available from the US Army Corps of Engineers
(USAGE, 2010). These draft limits are modified by observed vessel drafts from the USAGE Waterborne
Commerce Statistical Center 2008 data. Dock depth limits for Canadian ports were obtained from
26
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Greenwood's Guide to Great Lakes Shipping (2009). In some cases, port depth limit actually refers to a
restriction elsewhere along the route, such as a maximum channel depth.
Default Scenario Route Port-to-Port Distance
The Default Scenario Route port-to-port distance refers to the distance traveled by the water-
leg of the Default Scenario Route. This distance was calculated using the Network Analyst extension of
ArcGIS as applied to the US ACE waterway network database. Input was also received from stakeholders
(via EPA) that gave alternate, though similar, port-to-port distances. When the US ACE distance
disagreed with the stakeholder distance, the longer distance was used. A longer port-to-port distance
would result in higher costs for the Default Scenario Route and increase the potential for a mode shift.
Default Scenario Route Rail Distance
The Default Scenario Route rail distance refers to the distance traveled by the rail-leg of the
Default Scenario Route (if applicable). This distance was calculated in the GIFT model (discussed in
Chapter 1) using the Network Analyst extension of ArcGIS as applied to the railway network of the
National Transportation Atlas Database (NTAD).
All-Rail Alternative Route Distance
The All-Rail Alternative Route distance is the total miles traveled by rail along the All-Rail
Alternative Route. This value was calculated in the GIFT model using the Network Analyst extension of
ArcGIS as applied to the railway network of the NTAD. Input from stakeholders was also received (via
EPA) that give alternate all-rail distances for some routes. These alternate distances were very similar to
those calculated in ArcGIS; however, the values presented by stakeholders were chosen when available.
Marine Vessel Freight Rate
The Base Case freight rates for marine vessels used in the analysis were estimated using the
Great Lakes Vessel Costing Model developed by Chrisman Dager while at the Tennessee Valley Authority
and implemented in studies for the Great Lakes for USAGE. The model has been used for rate analysis in
22 USAGE projects since 1999 and uses data collected from 226 Great Lakes dock facilities. The Great
Lakes Vessel Costing Model estimates vessel rates on the Great Lakes by class of vessel using reported
operating costs, depreciated replacement vessel construction costs, return on investment and vessel
operating characteristics such as vessel speed, empty return, and vessel capacity. In addition, the
loading and unloading time is calculated from reported handling speeds at the specific docks, and the
reported draft at the dock or lock is used to develop vessel capacity. For those vessels traversing locks,
the average processing and delay time and tolls (if applicable) are added to the rate estimation. The
marine vessel freight rates are referred to as "Base Case Voyage Rates" in this report. The model
assumed fuel prices of $424/MT of HFO for the main engines and $617/MT of MDO for the auxiliary
engines. The difference in fuel costs in dollars per cargo ton resulting from a switch from HFO to MDO
fuel for main engines is added to the Base Case Voyage Rate to calculate the "MDO Case Voyage Rate."
Rail Freight Rate
The rail freight rates are reported based upon revenue per mile. The source of the railroad data
is the Surface Transportation Board Public Waybill Sample for 2007 (2009). In addition to the Public
Waybill Sample, the Association of American Railroads (AAR) 2007 fourth quarter base, productivity-
adjusted Rail Cost Adjustment Factor (2007) was used to arrive at an index to correct to the second
quarter of 2010. The index indicated that second quarter 2010 rates were 1% greater than the fourth
quarter 2007 rail rates. The attributes used from the AAR to calculate the rail freight rate include
carload revenue, average distance, and average weight per car. The rail freight rate is referred to as the
"Base Case Rail Rate" later in the report.
27
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The total cargo transfer cost for the Default Scenario Routes includes all of the costs associated
with transferring one net ton of cargo from origin to destination for the Default Scenario Route. This
value includes all transfer costs that are not captured in the rail and ship freight rates. Representative
transfer costs were obtained through communication with Chrisman Dager (2010) and derived from
data included in the Great Lakes Vessels Costing model described in the Marine Vessel Freight Rate
section. These rates vary depending on the commodity transferred. The analysis assumes the following
total cargo transfer costs for the Default Scenario Routes: $1.55/cargo ton for coal; $1.35/cargo ton for
iron ore; $3.50/cargo ton for grain; and $1.20/cargo ton for stone. These values include transferring
from rail to ship and unloading from ship to the dock (or into rail cars for further transport if the
destination is not at the dock).
The total cargo transfer cost for the All-Rail Alternative Route includes all of the costs associated
with transferring one net ton of cargo from origin to destination for the All-Rail Alternative Route. This
value includes all transfer costs that are not captured in the rail freight rates. Representative transfer
costs were obtained through communication with Chrisman Dager (2010). These rates vary depending
on the commodity transferred. The analysis assumes the following total cargo transfer costs for the All-
Rail Alternative Routes: $1.50/cargo ton for coal; $1.25/cargo ton for iron ore; $3.67/cargo ton for grain;
and stone is not considered in our All-Rail Alternative Routes. These values include loading the
commodity into rail cars and unloading them at the destination.
28
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Scenario 1: Coal from Rosebud Mine, MT to Bayfront Power Plant, WI
This scenario represents the transport of coal from the Rosebud Mine in Montana to the
Bayfront Power Plant in Ashland, Wisconsin. The Bayfront Power Plant is an end-user. The Bayfront
Power Plant is a 76 megawatt (MW) power plant that burns coal, biomass, and other fuels.
Input Assumptions
The assumptions for this case can be found in Table 17. A 635 foot long vessel is modeled due
to dock restrictions at Ashland which limit vessel draft to 22 feet and length to approximately 700 feet.
Due to draft restrictions, we assume that the vessel will not be fully loaded and apply a loss of 1,284
tons per foot of draft reduction.
Legend
OD PAIRS
250
CASE STUDY 1
DEFAULT - INTERMODAL
500
ALTERNATIVE - RAIL ONLY
DULUTH/SUPERIOR
ASHLAND, WI (BAY-FRONT POWER) *
Figure 4: Scenario 1 map - Rosebud Mine, MTto Bayfront Power Plant, Ashland, WI
29
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Table 17: Summary of Scenario 1 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Rosebud Mine to Bayfront Categorical
Power Plant
Superior, Wl to Ashland, Wl Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route ($/ton)
Total Cargo Transfer Cost for All-Rail Alternative Route ($/ton
1,040
1,260
$1.55
$1.50
feet
miles
miles
miles
$/cargo ton
$/cargo ton
30
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Scenario 2: Coal from Elk Creek Mine, CO to Georgia Pacific West Mill in Green
Bay, WI
This scenario represents the transport of coal from the Elk Creek Mine in Colorado to the
Georgia Pacific West Mill in Green Bay, WI. The Georgia Pacific West Mill is an end-user.
Input Assumptions
The assumptions for this case can be found in Table 18. This scenario is based on a 635 foot
vessel due to vessel length restrictions for vessels traveling under the bridges at the Green Bay port and
draft restriction at the dock in Green Bay (23 feet). Due to the vessel size restrictions, this scenario is
based on a cargo load that assumes a loss of 1,284 tons per foot of draft reduction.
Legend
CASE STUDY 2
OD PAIRS
DEFAULT-INTERMODAL
500
I
ALTERNATIVE - RAIL ONLY
1.000 Miles
I
SOUTH CHICAGO (IROQUIS LANDING)
Figure 5: Scenario 2 map - Elk Creek Mine, CO to Georgia Pacific West Mill, Green Bay, WI
31
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Table 18: Summary of Scenario 2 inputs
Data description
Value
Units
Origin-Destination Pair
Elk Creek Mine, CO to Georgia Pacific
West Mill in Green Bay, Wl
Categorical
Origin and Destination Ports
South Chicago to Green Bay
Categorical
Vessel Type
Cargo Transported
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
Bulk/Self-unloader
Coal
635
7,200
236
12
14
18,150
Categorical
Categorical
M|
Horsepower
g/kWh
knots
mph
Net tons
feet
32
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Scenario 3: Coal from Rosebud Mine, MT to St. Clair and Monroe Power Plants,
MI
This scenario represents the transport of coal from the Rosebud Mine in Montana to the St. Clair
and Monroe Power Plants in Michigan. The power plants are end-users.
Input Assumptions
The assumptions for this case can be found in Table 19. This scenario consists of three port calls
total. It is assumed that a sufficient amount of coal is unloaded at St. Clair in order to reduce the vessel's
draft so that it can unload the remaining coal in Monroe. The Detroit Edison coal dock in Monroe has a
maximum draft limit of 21 feet. Due to the synergies between the two ports, no reduction in vessel
cargo load is assumed due to the restrictions in Monroe.
w
CASE STUDY 3
ALTERNATIVE - RAIL ONLY
ST CLAIR, Ml (WAYPOINT)
MONROE, Ml (DTE POWER)
Figure 6: Scenario 3 map - Rosebud Mine, MTto St. Clair and Monroe Power Plants, Ml
33
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Table 19: Summary of Scenario 3 inputs
Data description
Value
Units
Origin-Destination Pair
Rosebud Mine, MT to St. Clair and
Monroe Power Plants, Ml
Categorical
Origin and Destination Ports
Superior to St. Clair and onto Monroe, Categorical
Ml
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
Bulk/Self-unloader Categorical
Coal Categorical
1,000
16,000 Horsepower
14 knots
57,200 Net tons
48,620 Net tons
29 feet
26.5
Unknown limit at St. Clair but 21 foot feet
limit at the DTE dock in Monroe
1,620
miles
$1.55
$1.50
$/cargo ton
34
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Scenario 4: Coal from Rosebud Mine, MT to Weadock and Karn Generating
Plants, MI
This scenario represents the transport of coal from the Rosebud Mine in Montana to the
Weadock and Karn Generating Plants in Michigan. The generating plants are end-users.
Input Assumptions
The assumptions for this case can be found in Table 20. This scenario is based on two port calls,
with each of two generating plants receiving coal from the port in Essexville, Ml. While this scenario is
based on a large vessel (1,000 foot), there are port draft restrictions at Essexville (23 feet). Due to the
vessel size restrictions, this scenario is based on a cargo load that assumes a loss of 3,204 tons per foot
of draft reduction.
w
CASE STUDY 4
ALTERNATIVE - RAIL ONLY
WEADOCK/KARN GENERATING PLANT. ESSEXVILLE. Ml
Figure 7: Scenario 4 map - Rosebud Mine, MTto Weadock/Karn Generating Plants, Essexville, Ml
35
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Table 20: Summary of Scenario 4 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Rosebud Mine, MT to Weadock and Categorical
Karn Generating Plants, Ml
Superior to Essexville Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
23
620
1,040
1,660
$1.55
Total Cargo Transfer Cost for All-Rail Alternative Route $1.50
($/ton)
feet
miles
miles
miles
$/cargo ton
$/cargo ton
36
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Scenario 5: Iron ore from Empire and Tilden Mines, MI to Algoma Steel, ON
This scenario represents the transport of iron ore from the Empire and Tilden Mines in Michigan
to Algoma Steel in Ontario, Canada. Algoma Steel is an end-user.
Input Assumptions
The assumptions for this case can be found in Table 21. This scenario is based on a 635 foot
vessel due to dock restrictions at the Sault St. Marine, Ontario (Algoma) port which limit vessel draft (23
feet). Due to the vessel size restrictions, this scenario is based on a cargo load that assumes a loss of
1,284 tons per foot of draft reduction.
Legend
CASE STUDY 5
OD PAIRS
DEFAULT- INTERMODAL
ALTERNATIVE- RAIL ONLY
ESSAR STEEL ALGOMA PLANT, SAULT STE. MARIE, ONTARIO. CANADA
EMPIRE'AND TILDEN MINES (PALMER
Figure 8: Scenario 5 map - Empire and Tilden Mines, Palmer, Ml to Essar Steel Algoma Plant, Sault Ste. Marie, ON
37
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Table 21: Summary of Scenario 5 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Empire and Tilden Mines, Ml to Algoma
Steel, ON
Marquette to Algoma
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons) 18,150
Assumed Cargo Load (net tons) 11,730
Vessel Draft at Maximum Cargo Load 28
Vessel Draft at Assumed Cargo Load 23
Port Depth Limit 23
Default Scenario Route Port-to-Port Distance (miles) 170
Default Scenario Route Rail Distance (miles) 20
All-Rail Alternative Route Distance (miles) 210
Total Cargo Transfer Cost for Default Scenario Route $1.35
($/ton)
Bulk/Self-unloader
Iron Ore
635
7,200
236
14
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
$1.25
Categorical
Categorical
feet
Horsepower
g/kWh
knots
mph
Net tons
Net tons
feet
,ซ,
feet
miles
miles
miles
$/cargo ton
$/cargo ton
38
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Scenario 6: Iron ore from Quebec Cartier Mining Company, QC to
ArcelorMittal, IL
This scenario represents the transport of iron ore from the Quebec Cartier Mining Company in
Quebec, Canada to ArcelorMittal in Illinois. ArcelorMittal is an end-user. After reviewing the rail
network in the GIFT model and through discussions with stakeholders and experts, it was determined
that Port Cartier, QC is not serviceable by rail; therefore an All-Rail Alternative Route does not exist.
Input Assumptions
The assumptions for this case can be found in Table 22. This scenario is based on a 635 foot
vessel because this route traverses the Montreal-Lake Ontario Locks and the Welland Canal which has a
maximum allowable draft of 26.5 feet and a maximum vessel length of 740 feet. When the vessel is
loaded at 85% capacity, the resulting draft becomes 26 feet due to a one foot draft reduction per 1,284
net tons of cargo reduction (Lake Carriers' Association, 2007b).
I Legena
-sJfe-E
OD Pairs ^^
Routes
250 500
_i i I
Case Study 6: Ship
1.000 Miles
I
ORT~CARTIER MINING-e
">ORT CARTIER MININiS-GOMPLEX (ARCELOR MITTAL), QUEBEC CANADA^X
CHICAGO/BURNS HARBOR, I
Figure 9: Scenario 6 map - Quebec Cartier Mining Company, Port Cartier, QC to ArcelorMittal, Chicago, IL
39
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Table 22: Summary of Scenario 6 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Quebec Cartier Mining Company, QC to
ArcelorMittal, IL
Port Cartier to Chicago
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Bulk/Self-unloader
Iron Ore
635
7,200
236
14
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
No All-Rail Alternative
Categorical
Categorical
feet
Horsepower
g/kWh
knots
$/cargo ton
40
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Scenario 7: Iron ore from the Hull Rust Mine, MN to US Steel, IN
This scenario represents the transport of iron ore from the Hull Rust Mine in Minnesota to US
Steel in Indiana. US Steel is an end-user.
Input Assumptions
The assumptions for this case can be found in Table 23. This scenario is based on a 1,000 foot
vessel. Despite a port depth limit of 26.5 feet, we assume that the vessel's draft is 26 feet at 85%
capacity due to a loss of one foot per 3,204 net tons of cargo reduction (Lake Carriers' Association,
2007b).
CASE STUDY 7
ALTERNATIVE - RAIL ONLY
Figure 10: Scenario 7 map - Hull Rust Mine, Hibbing, MN to US Steel, Gary, IN
41
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Table 23: Summary of Scenario 7 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Hull Rust Mine, MN to US Steel, IN Categorical
Superior to Gary Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles
Total Cargo Transfer Cost for Default Scenario Route $1.35
($/ton)
Bulk/Self-unloader
Iron Ore
1,000
16,000
231
14
16
57,200
48,620
29
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
$1.25
Categorical
Categorical
feet
Horsepower
g/kWh
knots
mph
Net tons
Net tons
feet
42
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Scenario 8: Iron ore from Northshore Mining, MN to Severstal, OH
This scenario represents the transport of iron ore from Northshore Mining in Minnesota to
Severstal in Ohio. Severstal is an end-user.
Input Assumptions
The assumptions for this case can be found in Table 24. This scenario is based on a 1,000 foot
vessel. Despite a port depth limit of 26.5 feet, we assume that the vessel's draft is 26 feet at 85%
capacity due to a loss of one foot per 3,204 net tons of cargo reduction (Lake Carriers' Association,
2007b).
Legend
CASE STUDY 8
OD PAIRS
DEFAULT- INTERMODAL
ALTERNATIVE - RAIL ONLY
500 Miles
Figure 11: Scenario 8 map - Northshore Mining, Babbit, MN to Severstal, Warren, OH
43
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Table 24: Summary of Scenario 8 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Northshore Mining, MN to Severstal, OH Categorical
Silver Bay to Ashtabula Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
Bulk/Self-unloader
Iron Ore
1,000
16,000
231
14
16
57,200
48,620
29
26
26.5
840
100
900
$1.35
$1.25
Categorical
Categorical
feet
Horsepower
g/kWh
knots
mph
Net tons
Net tons
feet
'"'
feet
miles
miles
miles
$/cargo ton
44
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Scenario 9: Grain from Lake Calumet Grain Elevators, IL to Baie Comeau, QC
This scenario represents the transport of grain from the Lake Calumet Grain Elevators in Illinois
to Baie Comeau in Quebec, Canada. Baie Comeau is a transportation hub.
Input Assumptions
The assumptions for this case can be found in Table 25. This scenario assumes a 635 foot vessel
because this route traverses the Welland Canal. The maximum allowable vessel length for the Welland
Canal is 740 feet and the next smallest vessel that we model is 770 feet long. The Calumet River depth is
the limiting factor for the vessel draft in this scenario. The river can support a draft of 25.5 feet. Due to
the vessel size restrictions, this scenario is based on a cargo load that assumes a loss of 1,284 tons per
foot of draft reduction.
Legend
CASE STUDY 9
OD PAIRS DEFAULT - INTERMODAL
250 500
ALTERNATIVE- RAIL ONLY
1.000 Miles
I
Figure 12: Scenario 9 map - Lake Calumet Grain Elevators, Chicago, IL to Baie Comeau, QC for export to the rest of the world
45
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Table 25: Summary of Scenario 9 inputs
Data description
Value
Units
Origin-Destination Pair
Lake Calumet Grain Elevators, IL to Bale
Comeau, QC for export to the rest of the
world
Categorical
Origin and Destination Ports
Chicago to Baie Comeau
Categorical
Vessel Type
Bulk/Self-unloader
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Grain
635
7,200
Vessel Main Engine Specific Fuel Oil Consumption
236
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
12
14
18,150
14,940
28
Vessel Draft at Assumed Cargo Load
Port Depth Limit
25.5
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
25.5 (Calumet River)
1,720
0
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
Categorical
Categorical
'"'
Horsepower
g/kWh
knots
mph
Net tons
Net tons
feet
feet
46
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Scenario 10: Grain from Duluth Port Grain Elevators, MN to Baie Comeau, QC
This scenario represents the transport of grain from the Duluth Port Grain Elevators in
Minnesota to Baie Comeau in Quebec, Canada. Baie Comeau is a transportation hub.
Input Assumptions
The assumptions for this case can be found in Table 26. This scenario assumes a 635 foot vessel
because this route traverses the Welland Canal. The maximum allowable vessel length for the Welland
Canal is 740 feet and the next smallest vessel that we model is 770 feet long. At an 85% cargo load, the
assumed vessel draft is 26 feet, less than the Seaway limit of 26.5 feet.
Legend
CASE STUDY 10
OD PAIRS
250
DEFAULT - INTERMODAL
500
I
ALTERNATIVE- RAIL ONLY
Figure 13: Scenario 10 map - Duluth Port Grain Elevators, Duluth, MN to Baie Comeau, QC for export to the rest of the world
47
-------
Table 26: Summary of Scenario 10 inputs
Data description
Value
Units
Origin-Destination Pair
Duluth Port Grain Elevators, MN to Bale
Comeau, QC for export to the rest of the
world
Categorical
Origin and Destination Ports
Duluth to Bale Comeau
Categorical
Vessel Type
Bulk/Self-unloader
Categorical
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Grain
635
7,200
Vessel Main Engine Specific Fuel Oil Consumption
236
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
12
14
18,150
15,430
28
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
26
26.5 (St. Lawrence Seaway draft limit)
1,730
0
$3.50
$3.67
Categorical
'"'
Horsepower
g/kWh
knots
mph
Net tons
Net tons
feet
feet
feet
miles
miles
milss
$/cargo ton
$/cargo ton
48
-------
Scenario 11: Grain from Duluth Port Grain Elevators, MN to WNY Ethanol
Plant, Medina, NY
This scenario represents the transport of grain from the Duluth Port Grain Elevators in
Minnesota to the WNY Ethanol Plant in Medina, NY. The WNY Ethanol Plant is an end-user.
Input Assumptions
The assumptions for this case can be found in Table 27. This scenario is based on a 635 foot
vessel because of port draft restrictions in Buffalo (23 feet). Due to the vessel size restrictions, this
scenario is based on a cargo load that assumes a loss of 1,284 tons per foot of draft reduction (Lake
Carriers' Association, 2007b).
CASE STUDY 11
ALTERNATIVE - RAIL ONLY
WESTERN NY ENERGY ETHANOL PLANT, MEDINA, NY
Figure 14: Scenario 11 map - Duluth Port Grain Elevators, Duluth, MN to WNY Ethanol Plant, Medina, NY
49
-------
Table 27: Summary of Scenario 11 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Duluth Port Grain Elevators, MN to WNY Categorical
Ethanol Plant, Medina, NY
Duluth to Buffalo
Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Bulk/Self-unloader
Grain
635
7,200
236
12
18,150
11,730
28
23
23
960
50
970
$3.50
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
$3.67
Categorical
Categorical
feet
Horsepower
g/kWh
knots
mph
Net tons
Net tons
feet
,ซ,
feet
miles
miles
miles
$/cargo ton
$/cargo ton
50
-------
Scenario 12: Grain from Goderich Port Grain Elevators, ON to Nabisco Flour
Mill, OH
This scenario represents the transport of grain from the Goderich Port Grain Elevators in
Ontario, Canada to the Nabisco Flour Mill in Ohio. The Nabisco Flour Mill is an end-user.
Input Assumptions
The assumptions for this case can be found in Table 28. This scenario is based on a 635 foot
vessel because of port draft restrictions at the Nabisco Flour Dock in Toledo (17 feet). Due to the vessel
size restrictions, this scenario is based on a cargo load that assumes a loss of 1,284 tons per foot of draft
reduction (Lake Carriers' Association, 2007b).
w
Legend
CASE STUDY 12
OD PAIRS
62.5
DEFAULT-INTERMODAL
125
i I
ALTERNATIVE - RAIL ONLY
250 Miles
Figure 15: Scenario 12 map - Goderich Port Grain Elevators, Goderich, ON to Nabisco Flour Mill, Toledo, OH
51
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Table 28: Summary of Scenario 12 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Goderich Port Grain Elevators, ON to Categorical
Nabisco Flour Mill, OH
Goderich to Toledo Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Feet
Default Scenario Route Port-to-Port Distance (miles) 185
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles;
Total Cargo Transfer Cost for Default Scenario Route $3.50
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
52
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Scenario 13: Stone from Port Dolomite, MI to the J.M. Stuart Power Plant, OH
This scenario represents the transport of stone from Port Dolomite in Michigan to the J.M.
Stuart Power Plant in Ohio. The power plant is an end-user. After reviewing the rail network in the GIFT
model and through discussions with stakeholders and experts, it was determined that Port Dolomite, Ml
is not serviceable by rail; therefore, an All-Rail Alternative Route does not exist. Additionally, it appears
that there is not a physical rail connection to the J.M. Stuart power plant. If stone were to be
transported from the rail line to the power plant, it would need to be transferred to truck or barge
(likely in Cincinnati). Though we understand that a real-world route would require extra transfer costs
related to the movement of stone to the power plant, this portion of the route is not impacted by the
Category 3 Marine Rule.
Input Assumptions
The assumptions for this case can be found in Table 29. We assume a vessel length of 770 feet
based on stakeholder comment forwarded to EERA from EPA stating that 1,000 foot vessels do not
frequent this route. Stakeholders indicated that vessel lengths are typically 800 feet or less for this
route. At 85% cargo capacity, the vessel draft is assumed to be 24 feet due to a loss of one foot of draft
per 1,524 net tons of cargo reduction (Lake Carriers' Association, 2007b). There is no All-Rail Alternative
Route evaluated for this scenario.
w
Legend
CASE STUDY 13
OD PAIRS
DEFAULT-INTERMODAL
ALTERNATIVE - RAIL ONLY
500 Miles
Figure 16: Scenario 13 map - Port Dolomite to J. M. Stuart Power Plant, Aberdeen, OH
53
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Table 29: Summary of Scenario 13 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Port Dolomite, Ml to J.M. Stuart Power
Plant, OH
Categorical
Port Dolomite to Toledo
Categorical
Vessel Type
Cargo Transported
Bulk/Self-unloader
Stone
Categorical
Categorical
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
54
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Scenario 14: Stone from Calcite Quarry, MI to the J.M. Stuart Power Plant, OH
This scenario represents the transport of stone from Calcite Quarry in Michigan to the J.M.
Stuart Power Plant in Ohio. The power plant is an end-user. After reviewing the rail network in the GIFT
model and through discussions with stakeholders and experts, it was determined that Calcite Quarry
near Rodgers City, Ml is not serviceable by rail; therefore, an All-Rail Alternative Route does not exist. As
stated in the Scenario 13 description, it appears that there is no physical rail connection to the J.M.
Stuart power plant. If stone were to be transported from the rail line to the power plant, it would need
to be transferred to truck or barge (likely in Cincinnati). Though we understand that a real-world route
would require extra transfer costs related to the movement of stone to the power plant, this portion of
the route is not impacted by the Category 3 Marine Rule.
Input Assumptions
The assumptions for this case can be found in Table 30. We assume a vessel length of 770 feet
based on stakeholder comment forwarded to EERA from EPA stating that 1,000 foot vessels do not
frequent this route. Stakeholders indicated that vessel lengths are typically 800 feet or less for this
route. At 85% cargo capacity, the vessel draft is assumed to be 24 feet due to a loss of one foot of draft
per 1,524 net tons of cargo reduction (Lake Carriers' Association, 2007b). There is no All-Rail Alternative
Route evaluated for this scenario.
w
Legend
CASE STUDY 14
OD PAIRS
DEFAULT-INTERMODAL
ALTERNATIVE - RAIL ONLY
500 Miles
CALCITE QUARRY, Ml (NEAR ROGERS'CITY)
^-i f 1* tt U \ fti*
Figure 17: Scenario 14 map - Calcite Quarry, Ml to J.M. Stuart Power Plant, Aberdeen, OH
55
-------
Table 30: Summary of Scenario 14 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Calcite Quarry, Ml to J.M Stuart Power
Plant, OH
Categorical
Calcite Quarry to Toledo
Categorical
Vessel Type
Cargo Transported
Bulk/Self-unloader
Stone
Categorical
Categorical
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
56
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Scenario 15: Stone from Calcite Quarry, MI to American Crystal Sugar
Company, MN
This scenario represents the transport of stone from Calcite Quarry in Michigan to the American
Crystal Sugar Company in Minnesota. The sugar company is an end-user. After reviewing the rail
network in the GIFT model and through discussions with stakeholders and experts, it was determined
that Calcite Quarry near Rodgers City, Ml is not serviceable by rail; therefore, an All-Rail Alternative
Route does not exist.
Input Assumptions
The assumptions for this case can be found in Table 31. We assume a vessel length of 770 feet
based on stakeholder comment forwarded to EERA from EPA stating that 1,000 foot vessels do not
frequent this route. Stakeholders indicated that vessel lengths are typically 800 feet or less for this
route. At 85% cargo capacity, the vessel draft is assumed to be 24 feet due to a loss of one foot of draft
per 1,524 net tons of cargo reduction (Lake Carriers' Association, 2007b). There is no All-Rail Alternative
Route evaluated for this scenario.
w
CASE STUDY 15
ALTERNATIVE- RAIL ONLY
500 Miles
SUGAR STONE, AMERICAN CRYSTAL, CROOKSTON, MN
CALCITE QUARRY, Ml (NEAR ROGERS CITY)
' V
Figure 18: Scenario 15 map - Calcite Quarry, Ml to American Crystal Sugar Company, Crookston, MN.
57
-------
Table 31: Summary of Scenario 15 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Calcite Quarry, Ml to American Crystal Categorical
Sugar Company, MN
Calcite Quarry to Duluth Categorical
Vessel Type
Cargo Transported
Vessel Length (ft.)
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Bulk/Self-unloader
Stone
770
11,000
196
14
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
No All-Rail Alternative
Categorical
Categorical
feet
Horsepower
g/kWh
knots
$/cargo ton
58
-------
Scenario 16: Stone from Calcite Quarry, MI to Bruce Mansfield Power Station,
OH
This scenario represents the transport of stone from Calcite Quarry in Michigan to the Bruce
Mansfield Power Station in Ohio. The power plant is an end-user. After reviewing the rail network in
the GIFT model and through discussions with stakeholders and experts, it was determined that Calcite
Quarry near Rodgers City, Ml is not serviceable by rail; therefore, an All-Rail Alternative Route does not
exist.
Input Assumptions
The assumptions for this case can be found in Table 32. We assume a vessel length of 770 feet
based on stakeholder comment forwarded to EERA from EPA stating that 1,000 foot vessels do not
frequent this route. Stakeholders indicated that vessel lengths are typically 800 feet or less for this
route. At 85% cargo capacity, the vessel draft is assumed to be 24 feet due to a loss of one foot of draft
per 1,524 net tons of cargo reduction (Lake Carriers' Association, 2007b). There is no All-Rail Alternative
Route evaluated for this scenario.
Legend
CASE STUDY 16
OD PAIRS
125
DEFAULT- INTERMODAL
250
I
ALTERNATIVE - RAIL ONLY
500 Miles
BRUCE MANSFIELD POWER STATION, SHIPPINGPORT, PA
CALCITE QUARRY,'Ml (NEAR ROGERS CITY)
> ,*
Figure 19: Scenario 16 map - Calcite Quarry, Ml to Bruce Mansfield Power Station, Shippingport, PA
59
-------
Table 32: Summary of Scenario 16 inputs
Data description
Value
Units
Origin-Destination Pair
Origin and Destination Ports
Calcite Quarry, Ml to Bruce Mansfield
Power Station, OH
Categorical
Calcite Quarry to Ashtabula
Categorical
Vessel Type
Cargo Transported
Bulk/Self-unloader
Stone
Categorical
Categorical
Vessel Main Engine Horsepower (Hp)
Vessel Main Engine Specific Fuel Oil Consumption
Vessel Operating Speed (knots)
Vessel Operating Speed (mph)
Vessel Cargo Capacity (net tons)
Assumed Cargo Load (net tons)
Vessel Draft at Maximum Cargo Load
Vessel Draft at Assumed Cargo Load
Port Depth Limit
Default Scenario Route Port-to-Port Distance (miles)
Default Scenario Route Rail Distance (miles)
All-Rail Alternative Route Distance (miles)
Total Cargo Transfer Cost for Default Scenario Route
($/ton)
Total Cargo Transfer Cost for All-Rail Alternative
Route ($/ton)
60
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Chapter 5: Results
This chapter presents results for each scenario. Results include a map, tables, and a brief
discussion for each scenario.
Scenario 1: Coal from Rosebud Mine, MT to Bayfront Power Plant, WI
Table 33 summarizes the results of Scenario 1. The All-Rail Alternative Route is more expensive
than the Default Scenario Route in dollars per cargo ton. Table 34 presents a summary of the Default
Scenario Route characteristics; Table 35 presents the All-Rail Alternative Route.
Legend
CASE STUDY 1
OD PAIRS
250
DEFAULT- INTERMODAL
ALTERNATIVE- RAIL ONLY
1.000 Miles
DULUTH /SUPERIOR
ASHLAND, WI (BAY-FRONT POWER)
Figure 20: Scenario 1 map - Rosebud Mine, MTto Bayfront Power Plant, Ashland, WI
Table 33: Scenario 1 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$20.23
1,180
All-Rail Alternative Route
(red)
$21.71
1,260
61
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
140
1,040
1,180
10,450
$0.80
$1.04
$0.24
$1.55
$1.81
$16.62
$19.99
$20.23
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
1,260
10,450
$1.50
$20.21
$21.71
62
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Scenario 2: Coal from Elk Creek Mine, CO to Georgia Pacific West Mill in Green
Bay, WI
Table 36 summarizes the results of Scenario 2 and shows that an existing rail-water route may
have higher freight rates under the MDO Case than an All-Rail Alternative. The All-Rail Alternative Route
is less expensive than the Default Scenario Route in dollars per cargo ton. However, in this case, even
the Base Case shows freight rates that are higher than the All-Rail Alternative. Therefore, it is possible
that other factors not considered in this analysis support the movement of this commodity via ship given
prevailing freight rates. Table 37 presents a summary of the Default Scenario Route characteristics;
Table 38 presents the All-Rail Alternative Route.
Legend
CASE STUDY 2
OD PAIRS
250
DEFAULT- INTERMODAL
500
I L
ALTERNATIVE- RAIL ONLY
Figure 21: Scenario 2 map - Elk Creek Mine, CO to Georgia Pacific West Mill, Green Bay, WI
Table 36: Scenario 2 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$26.64
1,700
All-Rail Alternative Route
(red)
$24.43
1,430
63
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
390
1,310
1,700
11,730
$1.64
$2.25
$0.61
$1.55
$3.50
$20.98
$26.03
$26.64
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
1,430
11,730
$1.50
$22.93
$24.43
64
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Scenario 3: Coal from Rosebud Mine, MT to St. Clair and Monroe Power Plants,
MI
Table 39 summarizes the results of Scenario. Table 40 presents a summary of the Default
Scenario Route characteristics; Table 41 presents the All-Rail Alternative Route.
CASE STUDY 3
ALTERNATIVE - RAIL ONLY
ST CLAIR, Ml (WAYPOINT)
MONROE, Ml (DTE POWER)
Figure 22: Scenario 3 map - Rosebud Mine, MTto St. Clair and Monroe Power Plants, Ml
Table 39: Scenario 3 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO(blue)
$22.00
1,800
All-Rail Alternative Route
(red)
$27.44
1,620
65
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
760
1,040
1,800
48,620
$1.97
$2.78
$0.81
$1.55
$3.02
$16.62
$21.19
$22.00
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
1,620
48,620
$1.50
$22.94
$27.44
66
-------
Scenario 4: Coal from Rosebud Mine, MT to Weadock and Karn Generating
Plants, MI
Table 42 summarizes the results of Scenario 4. Table 43 presents a summary of the Default
Scenario Route characteristics; Table 44 presents the All-Rail Alternative Route.
w
Legend
CASE STUDY 4
OD PAIRS
DEFAULT- INTERMODAL
ALTERNATIVE - RAIL ONLY
1,000 Miles
WEADOCK/KARN GENERATING PLANT, ESSEXVILLE, Ml
Figure 23: Scenario 4 map - Rosebud Mine, MTto Weadock/Karn Generating Plants, Essexville, Ml
Table 42: Scenario 4 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO(blue)
$26.41
1,660
All-Rail Alternative Route
(red)
$28.12
1,660
67
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Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
620
1,040
1,660
28,290
$2.78
$3.91
$1.13
$1.55
$7.11
$16.62
$25.28
$26.41
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
1,660
28,290
$1.50
$26.62
$28.12
68
-------
Scenario 5: Iron ore from Empire and Tilden Mines, MI to Algoma Steel, ON
Table 45 summarizes the results of Scenario 5. The All-Rail Alternative Route is less than $1.00
more expensive than the Default Scenario Route in dollars per cargo ton. Table 46 presents a summary
of the Default Scenario Route characteristics; Table 47 presents the All-Rail Alternative Route.
Legend
CASE STUDY 5
OD PAIRS
DEFAULT- INTERMODAL
ALTERNATIVE - RAIL ONLY
ESSAR STEEL ALGOMA PLANT, SAULT STE. MARIE, ONTARIO, CANADA
EMPIRE'AND TILDEN MINES (PALMER
Figure 24: Scenario 5 map - Empire and Tilden Mines, Palmer, Ml to Essar Steel Algoma Plant, Sault Ste. Marie, ON
Table 45: Scenario 5 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$4.47
190
All-Rail Alternative Route
(red)
$5.22
210
69
-------
Table 46: Scenario 5 Default Scenario Route Summary
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
170
20
190
11,730
$1.01
$1.35
$0.35
$1.35
$2.45
$0.32
$4.12
$4.47
Table 47: Scenario 5 All-Rail Alternative Route Summary
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
210
11,730
$1.25
$3.97
$5.22
70
-------
Scenario 6: Iron ore from Quebec Cartier Mining Company, QC to
ArcelorMittal, IL
Table 48 summarizes the results of Scenario 6. It was determined that Port Cartier, QC is not
serviceable by rail. Therefore an All-Rail Alternative Route does not exist. This scenario is useful for
comparing the increase in the total Freight Rate of the Base Case to the MDO Case which can be found
in the last two rows of Table 49.
Legend
OD Pairs ^^ Routes
250
Case Study 6: Ship
500
1,000 Miles
MINING-GOMPLEX (ARCELOR MITTAL), QUEBEC CANADA j^
CHICAGO/BURNS HARBOR.'l
J_
Figure 25: Scenario 6 map - Quebec Cartier Mining Company, Port Cartier, QC to ArcelorMittal, Chicago, IL
Table 48: Scenario 6 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$18.77
1,930
All-Rail Alternative Route
(red)
N/A
N/A
71
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
1730
200
1,930
15,430
$6.27
$8.94
$2.67
$1.35
$10.98
$3.76
$16.10
$18.77
72
-------
Scenario 7: Iron ore from the Hull Rust Mine, MN to US Steel, IN
Table 50 summarizes the results of Scenario 7. Table 51 presents a summary of the Default
Scenario Route characteristics; Table 52 presents the All-Rail Alternative Route.
Legend
CASE STUDY 7
OD PAIRS
DEFAULT- INTERMODAL
ALTERNATIVE - RAIL ONLY
Figure 26: Scenario 7 map - Hull Rust Mine, Hibbing, MN to US Steel, Gary, IN
Table 50: Scenario 7 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$7.14
950
All-Rail Alternative Route
(red)
$11.99
570
73
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
870
80
950
48,620
$2.24
$3.16
$0.93
$1.35
$3.34
$1.52
$6.21
$7.14
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
570
48,620
$1.25
$10.74
$11.99
74
-------
Scenario 8: Iron ore from Northshore Mining, MN to Severstal, OH
Table 53 summarizes the results of Scenario 8. The All-Rail Alternative Route is more than twice
as expensive as the Default Scenario Route in dollars per cargo ton. Table 54 presents a summary of the
Default Scenario Route characteristics; Table 55 presents the All-Rail Alternative Route.
CASE STUDY 8
ALTERNATIVE - RAIL ONLY
Figure 27: Scenario 8 map - Northshore Mining, Babbit, MN to Severstal, Warren, OH
Table 53: Scenarios Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$7.73
940
All-Rail Alternative Route
(red)
$18.37
900
75
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
840
100
940
48,620
$2.16
$3.05
$0.89
$1.35
$3.66
$1.82
$6.83
$7.73
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
900
48,620
$1.25
$17.12
$18.37
76
-------
Scenario 9: Grain from Lake Calumet Grain Elevators, IL to Baie Comeau, QC
Table 56 summarizes the results of Scenario 9. The All-Rail Alternative Route is almost twice as
expensive as the Default Scenario Route in dollars per cargo ton. Table 57 presents a summary of the
Default Scenario Route characteristics; Table 58 presents the All-Rail Alternative Route.
Legend
CASE STUDY 9
OD PAIRS
250
DEFAULT- INTERMODAL
500
I
ALTERNATIVE - RAIL ONLY
1.000 Miles
I
GRAIN ELEVATORS, LAKE CALMUTrCHICAGO, IL
Figure 28: Scenario 9 map - Lake Calumet Grain Elevators, Chicago, IL to Baie Comeau, QC for export to the rest of the world
Table 56: Scenario 9 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$24.11
1,720
All-Rail Alternative Route
(red)
$46.75
1,270
77
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
1,720
0
1,720
14,940
$5.07
$7.17
$2.10
$3.50
$18.50
$22.00
$24.11
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
1,270
14,940
$3.67
$43.08
$46.75
78
-------
Scenario 10: Grain from Duluth Port Grain Elevators, MN to Baie Comeau, QC
Table 59 summarizes the results of Scenario 10. The All-Rail Alternative Route is almost three
times as expensive as the Default Scenario Route in dollars per cargo ton. Table 60 presents a summary
of the Default Scenario Route characteristics; Table 61 presents the All-Rail Alternative Route.
Legend
CASE STUDY 10
OD PAIRS
250
DEFAULT- INTERMODAL
500
I
ALTERNATIVE - RAIL ONLY
1,000 Miles
Figure 29: Scenario 10 map - Duluth Port Grain Elevators, Duluth, MN to Baie Comeau, QC for export to the rest of the world
Table 59: Scenario 10 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$21.82
1,730
All-Rail Alternative Route
(red)
$59.57
1,640
79
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
1,730
0
1,730
15,430
$4.93
$6.97
$2.04
$3.50
$16.28
$19.78
$21.82
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
1,640
15,430
$3.67
$55.90
$59.57
80
-------
Scenario 11: Grain from Duluth Port Grain Elevators, MN to WNY Ethanol
Plant, Medina, NY
Table 62 summarizes the results of Scenario 11. Table 63 presents a summary of the Default
Scenario Route characteristics; Table 64 presents the All-Rail Alternative Route.
CASE STUDY 11
ALTERNATIVE - RAIL ONLY
WESTERN NY ENERGY ETHANOL PLANT, MEDINA, NY
Figure 30: Scenario 11 map - Duluth Port Grain Elevators, Duluth, MN to WNY Ethanol Plant, Medina, NY
Table 62: Scenario 11 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO(blue)
$23.93
1,010
All-Rail Alternative Route
(red)
$36.62
970
81
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
960
50
1,010
11,730
$3.70
$5.20
$1.50
$3.50
$17.40
$1.53
$22.43
$23.93
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
970
11,730
$3.67
$32.95
$36.62
82
-------
Scenario 12: Grain from Goderich Port Grain Elevators, ON to Nabisco Flour
Mill, OH
Table 65 summarizes the results of Scenario 12. Table 66 presents a summary of the Default
Scenario Route characteristics; Table 67 does the same for the All-Rail Alternative Route.
w
Legend
CASE STUDY 12
OD PAIRS
62.5
DEFAULT- INTERMODAL
ALTERNATIVE - RAIL ONLY
Figure 31: Scenario 12 map - Goderich Port Grain Elevators, Goderich, ON to Nabisco Flour Mill, Toledo, OH
Table 65: Scenario 12 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO(blue)
$9.95
190
All-Rail Alternative Route
(red)
$11.80
240
83
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
185
5
190
4,030
$2.58
$3.42
$0.84
$3.50
$5.52
$0.10
$9.12
S9.95
Total Route Distance (miles)
Tons Transported (net ton)
Total Transfer Cost ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo
ton)
Total Freight Rate ($/cargo ton)
All-Rail Alternative Route
240
4,030
$3.67
$8.13
$11.80
84
-------
Scenario 13: Stone from Port Dolomite, MI to the J.M. Stuart Power Plant, OH
Table 68 summarizes the results of Scenario 13. It was determined that Port Dolomite, Ml is not
serviceable by rail. Therefore an All-Rail Alternative Route does not exist. This scenario is useful for
comparing the increase in the total Freight Rate of the Base Case to the MDO Case which can be found
in the last two rows of Table 69.
Legend
CASE STUDY 13
OD PAIRS DEFAULT - INTERMODAL
ALTERNATIVE- RAIL ONLY
500 Miles
Figure 32: Scenario 13 map - Port Dolomite to J. M. Stuart Power Plant, Toledo, OH
Table 68: Scenario 13 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$11.15
620
All-Rail Alternative Route
(red)
N/A
N/A
85
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
360
260
620
41,900
$0.68
$0.94
$0.26
$1.20
$4.73
$4.96
$10.89
$11.15
86
-------
Scenario 14: Stone from Calcite Quarry, MI to the J.M. Stuart Power Plant, OH
Table 70 summarizes the results of Scenario 14. It was determined that Calcite Quarry near
Rodgers City, Ml is not serviceable by rail. Therefore an All-Rail Alternative Route does not exist. This
scenario is useful for comparing the increase in the total Freight Rate of the Base Cose to the MDO Case
which can be found in the last two rows of Table 71.
Legend
CASE STUDY 14
OD PAIRS - DEFAULT - INTERMODAL
ALTERNATIVE- RAIL ONLY
500 Miles
CALCITE QUARRY, Ml (NEAR ROGERS CITY)
"^~ fVtf *S t fti*
Figure 33: Scenario 14 map - Calcite Quarry, Ml to J.M. Stuart Power Plant, Aberdeen, OH
Table 70: Scenario 14 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$9.14
580
All-Rail Alternative Route
(red)
N/A
N/A
87
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
320
260
580
41,900
$0.61
$0.84
$0.23
$1.20
$2.75
$4.96
$8.91
S9.14
88
-------
Scenario 15: Stone from Calcite Quarry, MI to American Crystal Sugar
Company, MN
Table 72 summarizes the results of Scenario 15. It was determined that Calcite Quarry near
Rodgers City, Ml is not serviceable by rail. Therefore an All-Rail Alternative Route does not exist. This
scenario is useful for comparing the increase in the total Freight Rate of the Base Cose to the MDO Case
which can be found in the last two rows of Table 73.
CASE STUDY 15
ALTERNATIVE - RAIL ONLY
SUGAR STONE. AMERICAN CRYSTAL, CROOKSTON, MN
CALCITEflUARRY, Ml (NEAR ROGERS CITY)
Figure 34: Scenario 15 map - Calcite Quarry, Ml to American Crystal Sugar Company, Crookston, MN.
Table 72: Scenario 15 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$12.39
720
All-Rail Alternative Route
(red)
N/A
N/A
89
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
470
250
720
41,900
$0.88
$1.22
$0.34
$1.20
$6.15
$4.69
$12.04
$12.39
90
-------
Scenario 16: Stone from Calcite Quarry, MI to Bruce Mansfield Power Station,
OH
Table 74 summarizes the results of Scenario 16. It was determined that Calcite Quarry near
Rodgers City, Ml is not serviceable by rail. Therefore an All-Rail Alternative Route does not exist. This
scenario is useful for comparing the increase in the total Freight Rate of the Base Cose to the MDO Case
which can be found in the last two rows of Table 75.
Legend
OD PAIRS
125
CASE STUDY 16
DEFAULT- INTERMODAL
250
I
ALTERNATIVE- RAIL ONLY
500 Miles
I
BRUCE MANSFIELD POWER STATION, SHIPPINGPORT, PA
Figure 35: Scenario 16 map - Calcite Quarry, Ml to Bruce Mansfield Power Station, Shippingport, PA
Table 74: Scenario 16 Summary Results
Total Freight Rate ($/cargo ton)
Total Route Distance (miles)
Default Scenario Route
using MDO (blue)
$6.82
540
All-Rail Alternative Route
(red)
N/A
N/A
91
-------
Total Vessel Distance (miles)
Total Rail Distance (miles)
Total Route Distance (miles)
Tons Transported (net ton)
Base Scenario Fuel Costs ($/cargo ton)
MDO Scenario Fuel Costs ($/cargo ton)
Change in Fuel Costs ($/cargo ton)
Total Transfer Cost ($/cargo ton)
Total Vessel Portion of Freight Rate for Base Case ($/cargo ton)
Total Rail Portion of Freight Rate ($/cargo ton)
Total Freight Rate for Base Case ($/cargo ton)
Total Freight Rate for MDO Case ($/cargo ton)
Default Scenario Route
430
110
540
41,900
$0.81
$1.11
$0.31
$1.20
$3.30
$2.01
$6.51
$6.82
92
-------
Chapter 6: Discussion of Results and Sensitivity Analysis
This chapter provides an interpretation of the results presented in Chapter 5 and discusses the
sensitivity of the results. Table 76 presents a summary of each scenario's results. For each scenario,
the All-Rail Alternative Route is more expensive than the MDO Case of the Default Scenario route with
the exception of Scenario 2. For Scenario 2, the cost of the All-Rail Alternate Route is lower than the
Default Scenario Route even before a switch to all-MDO fuel. This route has a couple of unique
characteristics that make it likely to prefer an all-rail route. First, the overall distance for the Default
Scenario Route is approximately 270 miles longer than the All-Rail Alternative Route. Second, the
Default Scenario Route has a relatively short distance traveled by ship (390 miles) compared to the rail
segment (1,310 miles). Therefore, the ship segment of the Default Scenario Route would have to be
very inexpensive to overcome the obstacles of increased route length and costs incurred with an
intermodal transfer from rail to ship (an extra transfer that the All-Rail Alternative Route does not have).
93
-------
Scenario Number, Origin & Port Used,
Destination & Port Used
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Rosebud Mine - Superior to Bayfront Power
Plant - Ashland, Wl
Elk Creek Mine - South Chicago to GP West
Mill -Green Bay
Rosebud Mine - Superior to DTE Power Plants
- Port Huron
Rosebud Mine - Superior to Weadock & Karn
Generating Plants - Essexville
Empire and Tilden Mines- Marquette to
Algoma Steel - Algoma
Quebec Cartier Mining Co. - Port Cartier to
ArcelorMittal - Chicago/ Burns Harbor
Hull Rust Mine - Duluth to U.S. Steel - Gary
Northshore Mining - Silver Bay to Severstal -
Ashtabula
Lake Calumet Grain Elevators - Chicago to
Baie Comeau
Duluth Port Grain Elevators to Baie Comeau
Duluth Port Grain Elevators to WNY Ethanol
Plant- Buffalo
Goderich Port Grain Elevators to Nabisco
Flour Mill -Toledo
Port Dolomite to J.M. Stuart Power Plant -
Toledo
Calcite Quarry and Port to J.M. Stuart Power
Plant -Toledo
Calcite Quarry and Port to American Crystal
Sugar Co. - Duluth
Calcite Quarry and Port to Bruce Mansfield
Power Station - Ashtabula
Cargo
Coal
Coal
Coal
Coal
Iron
Ore
Iron
Ore
Iron
Ore
Iron
Ore
Grain
Grain
Grain
Grain
Stone
Stone
Stone
Stone
Base
Case
Voyage
Rate
$1.81
$3.50
$3.02
$7.11
$2.45
$10.98
$3.34
$3.66
$18.50
$16.28
$17.40
$5.52
$4.73
$2.75
$6.15
$3.30
Base
Case
Transfer
Costs
$1.55
$1.55
$1.55
$1.55
$1.35
$1.35
$1.35
$1.35
$3.50
$3.50
$3.50
$3.50
$1.20
$1.20
$1.20
$1.20
Base Case
Rail Rate
(if used)
$16.62
$20.98
$16.62
$16.62
$0.32
$3.76
$1.52
$1.82
--
--
$1.53
$0.10
$4.96
$4.96
$4.69
$2.01
Base Case
Total Freight
Rate
$19.99
$26.03
$21.19
$25.28
$4.12
$16.10
$6.21
$6.83
$22.00
$19.78
$22.43
$9.12
$10.89
$8.91
$12.04
$6.51
MDO Case
Total Freight
Rate
$20.23
$26.64
$22.00
$26.41
$4.47
$18.77
$7.14
$7.73
$24.11
$21.82
$23.93
$9.95
$11.15
$9.14
$12.39
$6.82
All-Rail
Transfer
Costs
$1.50
$1.50
$1.50
$1.50
$1.25
--
$1.25
$1.25
$3.67
$3.67
$3.67
$3.67
--
--
--
--
All-Rail
Scenario
Rail
Freight
Rate
$20.21
$22.93
$25.94
$26.62
$3.97
--
$10.74
$17.12
$43.08
$55.90
$32.95
$8.13
--
--
--
--
All-Rail
Scenario
Total
Freight
Rate
$21.71
$24.43
$27.44
$28.12
$5.22
$11.99
$18.37
$46.75
$59.57
$36.62
$11.80
BOLD and shaded cells represent highest cost
94
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In order to validate the activity-based fuel consumption and costing model discussed in Chapter
3, a calculation was performed to determine the percentage of vessel-based freight rates that are due to
fuel costs. Results of this validation exercise are shown in Table 77. To determine the percentage of the
port-to-port Base Case freight rate attributable to fuel costs, we divide Column C by Column A and get a
range of 14%-67% (Column E) with eight scenarios above 40%. This is consistent with information
obtained from an EPA stakeholder meeting held in June 2010. Moreover, Column I in the table shows
that waterborne fuel cost as a percentage of origin-destination freight rates for the Base Case may range
from 4% to 12% in Scenarios 1 through 4 and 13 through 16 where a significant rail-connected
movement is included. In Scenarios 5 through 12, where waterborne transport is the dominant service,
fuel accounts for 21% to 67% of the origin-destination freight rate for the Base Case. When a switch to
MDO is considered, the percentage of the port-to-port MDO Cose freight rate attributable to fuel is
determined by dividing Column D by Column B and is found to be between 19%-74% (Column F) with
nine scenarios above 40%. After a switch to MDO, fuel accounts for 5% to 16% of the origin-destination
MDO Case freight rate for Scenarios 1 through 4 and 13 through 16 and 22% to 48% for Scenarios 5
through 12 (Column J).
95
-------
Scenario
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
(A)
Base
Case
Marine
Vessel
Freight
Rate
($/cargo
ton)
$1.81
$3.50
$3.02
$7.11
$2.45
$10.98
$3.34
$3.66
$18.50
$16.28
$17.40
$5.52
$4.73
$2.75
$6.15
$3.30
(B)
MDO
Case
Marine
Vessel
Freight
Rate
($/cargo
ton)
$2.05
$4.11
$3.83
$8.24
$2.79
$13.65
$4.27
$4.55
$20.61
$18.32
$18.90
$6.35
$4.99
$2.98
$6.49
$3.61
Port-to-Port Voyage
Considering both Main Engines and Auxiliaries
(C)
Portion of
Base Case
Freight
Rate
Attributable
to Fuel
($/cargo
ton)
$0.80
$1.64
$1.97
$2.78
$1.01
$6.27
$2.24
$2.16
$5.07
$4.93
$3.70
$2.58
$0.68
$0.61
$0.88
$0.81
(D)
Portion of
MDO Case
Freight
Rate
Attributable
to Fuel
($/cargo
ton)
$1.04
$2.25
$2.78
$3.91
$1.35
$8.94
$3.16
$3.05
$7.17
$6.97
$5.20
$3.42
$0.94
$0.84
$1.22
$1.11
(E)
% of P-to-P
Base Case
Freight
Rate
Attributable
to Fuel
44%
47%
65%
39%
41%
57%
67%
59%
27%
30%
21%
47%
14%
22%
14%
24%
(F)
% of P-to-P
MDO Case
Freight
Rate
Attributable
to Fuel
51%
55%
73%
47%
48%
66%
74%
67%
35%
38%
28%
54%
19%
28%
19%
31%
Scenario Origin to Destination
Considering both Main Engines and Auxiliaries
(G)
Total
Base
Case
Freight
Rate
($/cargo
ton)
$19.99
$26.03
$21.19
$25.28
$4.12
$16.10
$6.21
$6.83
$22.00
$19.78
$22.43
$9.12
$10.89
$8.91
$12.04
$6.51
(H)
Total
MDO
Case
Freight
Rate
($/cargo
ton)
$20.23
$26.64
$22.00
$26.41
$4.47
$18.77
$7.14
$7.73
$24.11
$21.82
$23.93
$9.95
$11.15
$9.14
$12.39
$6.82
(I)
%ofO-D
Base Case
Freight
Rate
Attributable
to Fuel
4%
6%
9%
11%
24%
39%
36%
32%
23%
25%
17%
28%
6%
7%
7%
12%
(J)
% of O-D
MDO Case
Freight
Rate
Attributable
to Fuel
5%
8%
13%
15%
30%
48%
44%
39%
30%
32%
22%
34%
8%
9%
10%
16%
Note: Columns G and H include vessel freight rates, rail freight rates (if used), and transfer costs.
96
-------
Finally, a sensitivity analysis was conducted that explored the use of freight rates that addressed
specific constraints that exist in the Great Lakes transportation system (Dager, 2010). For example,
these constraints can include the necessary use of smaller trains (i.e. less cars) to deliver the commodity
to the destination due to track restrictions or the use of rail ferries across water segments (such as in
Scenarios 9 and 10). These constraints serve to increase the cost of transporting goods by rail for the
Default Scenario Route and All-Rail Alternative Route except for the Base Case and MDO Case in
Scenarios 1 and 2. Table 78 summarizes the results of the analysis assuming scenario-specific routing
constraints. Scenarios 6, 12, 13, 14, 15, and 16 could not be evaluated in the sensitivity analysis, and so
are not included in this table. In discussions with Chrisman Dager (2010), we learned that scenario-
specific routing constraints precluded the use of rail for these routes. Limitations that prevented the
use of rail for these routes included a lack of Class 1 rail lines near the origin or destination. Scenarios
12 through 16 are not included here, because we understand that they use truck rather than rail as part
of intermodal goods movements.
97
-------
Scenario Number, Origin & Port Used,
Destination & Port Used
1
2
3
4
5
7
8
9
10
11
Rosebud Mine -Superior to Bayfront
Power Plant - Ashland, Wl
Elk Creek Mine - South Chicago to GP
West Mill -Green Bay
Rosebud Mine - Superior to DTE
Power Plants - Port Huron
Rosebud Mine - Superior to Weadock
& Karn Generating Plants - Essexville
Empire and Tilden Mines- Marquette
to Algoma Steel - Algoma
Hull Rust Mine - Duluth to U.S. Steel -
Gary
Northshore Mining -Silver Bay to
Severstal - Ashtabula
Lake Calumet Grain Elevators -
Chicago to Baie Comeau
Duluth Port Grain Elevators to Baie
Comeau
Duluth Port Grain Elevators to WNY
Ethanol Plant- Buffalo
Cargo
Coal
Coal
Coal
Coal
Iron Ore
Iron Ore
Iron Ore
Grain
Grain
Grain
Default Scenario Route
Base
Case
Voyage
Rate
$1.81
$3.50
$3.02
$7.11
$2.45
$3.34
$3.66
$18.50
$16.28
$17.40
Base Case
Transfer
Costs
$1.55
$1.55
$1.55
$1.55
$1.35
$1.35
$1.35
$3.50
$3.50
$3.50
Base Case
Rail Rate
(updated)
$17.98
$18.35
$17.98
$20.68
$2.29
$5.69
$5.65
"
$2.27
Base Case
Total Freight
Rate
$21.34
$23.41
$22.55
$29.34
$6.09
$10.38
$10.66
$22.00
$19.78
$23.17
MDO Case
Total Freight
Rate
$21.58
$24.01
$23.36
$30.46
$6.43
$11.31
$11.56
$24.11
$21.82
$24.66
All-Rail Alternative Route
All-Rail
Route
Transfer
Costs
$1.50
$1.50
$1.50
$1.50
$1.25
$1.25
$1.25
$3.67
$3.67
$3.67
All-Rail
Route
Rail
Freight
Rate
$43.49
$36.01
$29.74
$83.53
$11.62
$18.14
$21.71
$46.88
$61.28
$52.15
All-Rail
Route
Total
Freight
Rate
$44.99
$37.51
$31.24
$85.03
$12.87
$19.39
$22.96
$50.55
$64.95
$55.82
98
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adjustment factor.
Buhaug, 0., Corbett, J. J., Endresen, 0., Eyring, V., Faber, J., Hanayama, S., . . . Yoshida, K. (2009). Second
IMO greenhouse gas study. London.
Browning, L (2010). [Personal communication regarding ship specification data from Lloyds Register].
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California Air Resources Board (2007). [Personal communication with Paul Milkey regarding Det Norske
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Corbett, J. J., & Winebrake, J. J. (2008b). Total fuel cycle analysis for alternative marine fuels: Sulfur and
CO2 emissions tradeoffs of California's proposed low-sulfur marine fuel rule. Report to California
Air Resources Board.
Dager, C. (2010). [Personal communication and discussions with tranportation expert regarding Inland
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Exchange Commission.
Harbor House Publishers. (2009). Greenwood's Guide to Great Lakes Shipping.
International Organization for Standardization. (2005). Petroleum products - Fuels (class F) -
Specifications of marine fuels. Geneva, Switzerland.
Lake Carriers' Association. (2007a). 2007 Statistical Annual Report Of Lake Carriers' Association.
Lake Carriers' Association. (2007b). Dredging Great Lakes Ports And Waterways So Shipping Can Meet
The Needs Of Commerce. Cleveland, OH.
Lake Carriers' Association. (2007c). Ensuring the U.S. Coast Guard fleet can meet the needs of Great
Lakes commerce. Cleveland, OH.
Lake Carriers' Association. (2008). 2008 statistical annual report of Lake Carriers' Association.
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Securities and Exchange Commission.
Ryan, L. (2010). Canada's arctic shipping vanguard. Canadian Transportation and Logistics. Retrieved
from http://www.ctl.ca/issues/story.aspx?aid=1000372153&type=Print%20Archives
Saint Lawrence Seaway Development Corporation (SLSDC). (2002). Great Lakes/ St. Lawrence seaway
system: An overview of North America's most dynamic waterway.
Saint Lawrence Seaway Management Corp (SLSMC), & Saint Lawrence Seaway Development Corp
(SLSDC). (2010). Seaway Opening and Closing Information Retrieved March 30, 2010, from
http://www.greatlakes-seawav.com/en/commercial/opening-closing.html
Surface Transportation Board. (2009). 2007 Public use waybill sample. Washington, DC.
-------
Transportation Research Board. (2008). Great Lakes shipping, trade, and aquatic invasive species.
Washington, DC: National Research Council.
U.S. Army Corps of Engineers. (2008). Waterborne commerce of the United States. Alexandria, VA.
U.S. Army Corps of Engineers. (2009). 2008 Great Lakes basin profile. Washington, DC.
U.S. Army Corps of Engineers. (2010). U.S. waterway data: Port and waterway facilities Retrieved
September 2, 2010, from http://www.ndc.iwr.usace.army.mil/db/ports/mdb/
U.S. Environmental Protection Agency. (2009). Regulatory impact analysis: Control of emissions of air
pollution from category 3 marine diesel engines. Washington, DC.
U.S. Environmental Protection Agency. (2010). Regulation of fuels and fuel additives: Subpart I, 40 CFR
80.5.
U.S. Environmental Protection Agency. (2011). Economic Impacts of the Category 3 Marine Rule on
Great Lakes Shipping. Washington, DC.
Winebrake, J.J., Corbett, J.J., Falzarano, A., Hawker, J.S., Korfmacher, K., Ketha, S., & Zilora, S. (2008).
Assessing energy, environmental, and economic tradeoffs in intermodal freight transportation.
Journal of the Air and Waste Management Association, 58, 1004-1013.
100
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Chapter 2 Transportation Shift Analysis
Great Lakes Transportation
Bibliography Provided by Contractor
(April 5, 2010)
1. Adams, T. M., Ebeling, M., Gardner, R., Stewart, R., Hecke, S. V., Vonderembse, M., et al. (2006).
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tariffs-fuel-surcharge.htm?s_icid=home-feature-mdle-fuel-surcharge
3. CN (2010b). Personal communication with CN. In B. Comer (Ed.).
4. Comer, B. (2009). Sustainable Intermodal Freight Transportation: Applying the Geospatial
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7. Dager, C. A. (1997). Great Lakes shipping-pricing behavior of the modes. Middle States
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12. Folga, S., Allison, T., Seda-Sanabria, T., Matheu, E., Milam, T., Ryan, R., et al. (2009). A systems-
level methodology for the analysis of inland waterway infrastructure disruptions. J Transp Secur,
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13. Government Accountabilitiy Office (2006). Freight railroads: Industry health has improved, but
concerns about competition and capacity should be addressed. Washington, DC.
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15. Harkins, R. W. Great Lakes marine air emissions: We're different up here!
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Chapter 2 Transportation Shift Analysis
16. Higginson, J. K. (2007). Great Lakes short-sea shipping and the domestic cargo-carrying fleet.
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Great Lakes commerce. Cleveland, OH.
20. Lake Carriers' Association (2009). Recession trims lakes ore trade by two-thirds in April.
Cleveland, OH.
21. Lake Carriers' Association (2010). Great Lakes iron ore trade skyrockets in January; Shipments
increase 168 persent compared to a year ago. Cleveland, OH.
22. Laurits R. Christensen Associates, I. (2010). An Update to the Study of Competition in the U.S.
Freight Railroad Industry: Final Report. Washington, DC: Prepared for Surface Transportation
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23. Le-Griffin, H. D., & Moore, J. E. (2006). Potential impact of short-sea shipping in the southern
California region. Los Angeles, CA: METRANS Transportation Center.
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25. Millerd, F. (2007). Global climate change and Great Lakes international shipping.
26. NOAA (2009). Distances between United States ports. Washington, DC.
27. Norfolk Southern Corporation (2006). Freight tariff NS 4203-L: Local freight tariff publishing
distance rates on carloads of coal, coke, and iron ore. Roanoke, VA: Coal Business Group.
28. Saint Lawrence Seaway Development Corporation Great Lakes/St. Lawrence seaway system: An
overview of North America's most dynamic waterway.
29. SLSMC (2009). AdaptAbility: 2008/2009 Annual Report. Cornwall, Ontario: The St. Lawrence
Seaway Management Corporation.
30. St. Lawrence Seaway Management Corp (2009). Annual Report. Cornwall, Ontario.
31. St. Lawrence Seaway Management Corp, & St. Lawrence Seaway Development Corp (2010).
Seaway Opening and Closing Information Retrieved March 30, 2010, from
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32. Stewart, R. D. (2006). Great Lakes Marine Transportation System: Upper Midwest Freight
Corridor Study. Madison, Wl.: University of Wisconsin at Madison, Midwest Regional University
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33. Stopford, M. (1997). Maritime Economics: Second Edition. New York, NY: Routledge, Taylor and
Francis Group.
34. Surface Transportation Board (1998). Rail rates continue multi-year decline. Washington, DC:
Office of Economics, Environmental Analysis, and Administration.
35. Surface Transportation Board (2000). Rail rates continue multi-year decline. Washington, DC:
Office of Economics, Environmental Analysis, and Administration.
36. Taylor, J. C, & Roach, J. L. (2009). Ocean shipping in the Great Lakes: An analysis of industry
transportation cost savings. Transportation Journal, 48(1), 53-67.
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Chapter 2 Transportation Shift Analysis
37. Transport Canada, U.S. Army Corps of Engineers, U.S. Department of Transportation, St.
Lawrence Seaway Management Corp, St. Lawrence Seaway Development Corp, Environment
Canada, et al. (2007). Great Lakes St. Lawrence seaway study.
38. Transportation Research Board (2008). Great Lakes shipping, trade, and aquatic invasive species.
Washington, DC: National Research Council.
39. U.S. Army Corps of Engineers (2002a). Deep draft vessel costs.
40. U.S. Army Corps of Engineers (2002b). Reconnaissance report: Great Lakes navigation system
review.
41. U.S. Army Corps of Engineers (2005a). Market adjustments over transportation networks: A time
series analysis of grain movements on the Mississippi inland waterway system.
42. U.S. Army Corps of Engineers (2005b). A survey of the freight transportation demand literature
and a comparison of elasticity estimates.
43. U.S. Army Corps of Engineers (2007). Transportation rate analysis.
44. U.S. Army Corps of Engineers (2008a). Great Lakes and Ohio river navigation systems commerce
report, 2008.
45. U.S. Army Corps of Engineers (2008b). Great Lakes basin profile.
46. U.S. Army Corps of Engineers (2008c). Waterborne commerce of the United States. Alexandria,
VA.
47. U.S. Energy Information Administration (2004). Coal transportation: Rates and trends Retrieved
March 30, 2010, from http://www.eia.doe.gov/cneaf/coal/page/trans/ratesntrends.html
48. Control of emissions from new marine compression-ignition engines at or above 30 litres per
cylinder (2009a).
49. U.S. Environmental Protection Agency (2009b). Regulatory impact analysis: Control of emissions
of air pollution from category 3 marine diesel engines. Washington, DC.
50. U.S. Geological Survey (2010). Mineral commodity summaries: Iron ore.
51. US Army Corps of Engineers (2002). Economic Guidance Memo #02-06: FY2002 Deep Draft
Vessel Operating Costs. Washington, DC.
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and a Comparison of Elasticity Estimates. Alexandria, VA: U.S. Army Corps of Engineers,
Navigation Economic Technologies Program.
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Chapter 2 Transportation Shift Analysis
Chapter 2 References
1 Conference Report 111-316 accompanying HR2996, the Department of Interior, Environment, and Related
Agencies Appropriations Act, 2010.
2 Power Magazine, "Burning PRB Coal," October 2003, explaining why coal blending is necessary for many
existing boilers, available at http://www.prbcoals.com/pdf/PRBCoalInformation/Power-Oct03-PRBCoal.pdf.
3 Telephone call between L. Steele of EPAandK. Graves of Georgia-Pacific, May 12, 2011, concerning coal
sourcing activities.
4 Port of Green Bay, Brown County Port and Solid Waste Department Vessel Log, January 2011, available at
http://www.portofgreenbav.com/uploadedFiles/DeclO.pdf.
5 July 12, 2010 e-mail from Jean Marie Revelt to Bruce Bowie and James H. I. Weakley.
6 Minnesota Pollution Control Agency, Air Emission Permit No. 11900001-004 issued December 15, 2010 to
American Crystal Sugar Company, Crookston, MN. Emission limit of 5 percent opacity from railcar loading and
unloading stations, page A-32.
7 Telephone conversations between L. Steele of EPA and M. Freeman of the Ohio EPA, Portsmouth Local Air
Agency, and R. Begley of the Pennsylvania Department of Environmental Protection, Source Testing Section,
regarding rail access and raw material unloading operations at the J.M. Stuart and Bruce Mansfield electric
generating stations, respectively (January 28, 2011).
8 Note by the Secretariat. Review of MARPOL Annex VI and the NOx Technical Code. Report on the outcome of
the Informal Cross Government/Industry Scientific Group of Experts established to evaluate the effects of the
different fuel options proposed under the revision of MARPOL Annex VI. MEPC 57/4, 20 December 2007.
9 See Summary and Analysis of Comments: Control of Emissions from New Marine Compression-Ignition Engines
at or Above 30 Liters per Cylinder. EPA-420-R-09-015, December 2009. Response 6.2. A copy of this document
is available at www.epa.gov/otaq/oceanvessels.htm
2-41
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
CHAPTER 3: Potential for Other Shifts in Transport of Goods, and
Emissions Impacts
In addition to the transportation mode shift analysis described in Chapter 2, we also
examined the impacts of the application of EGA fuel requirements to Great Lakes shipping with
respect to source shift and production shift. We also estimated the air emissions impacts of
potential transportation mode shift, source shift, and production shift. These analyses are
described in this chapter.
Source shift refers to users of a particular commodity changing to a different supply
network. In the context of the Great Lakes, stakeholders indicated that there is a risk of source
shift with respect to crushed stone markets: the additional fuel costs associated with applying the
EGA fuel requirements to Great Lakes shipping would make stone from local quarries delivered
by truck more cost competitive, leading users to shift their purchases to those local sources. Our
analysis of four O/D pairs at risk for source shift suggests no source shift is indicated for those
scenarios.
Production shift refers to producers of a particular good changing the location of the
production of that good. In the context of the Great Lakes, stakeholders indicated that there is a
risk of production shift with respect to the steel and electrical markets: the additional fuel costs
associated with applying the EGA fuel requirements to Great Lakes shipping would lead
producers to relocate production to facilities outside the region, with presumably lower coal and
iron ore transportation costs. Our analysis of the steel and electric markets in the United States
suggests that no production shift is indicated.
3.1 Source Shift Analysis: Crushed Stone
3.1.1 Background
In the course of developing and carrying out this economic impact analysis, several
stakeholders told EPA that the transportation market for stone is different from that for coal, iron
ore, or grain, and that rather than a transportation mode shift, the likely impact of the application
of EGA fuel requirements on the Great Lakes would be a source shift. Specifically, the increased
costs of transporting stone mined in Michigan to various inland facilities would lead these users
to switch to locally-mined stone. In that case, the stone would be transported from the local
quarries by truck rather than ship, resulting in increased emissions - the opposite of what EPA
intends.
The U.S. Geological Survey (USGS) Crushed Stone Compendium contains a description
of several important features of the crushed stone market.1 Crushed stone is a low value
commodity that is used in large quantities. Production costs are mining-related, dominated by
labor, equipment, energy and water, although safety and environmental regulatory compliance
costs are also relevant. While the price of crushed stone varies based on location, the difficulty
of the deposit and the type of stone being mined, the market price of crushed stone has been
relatively constant. USGC notes that "despite having one of the lowest average-per-ton values of
all mineral commodities, the constant dollar price of crushed stone has changed relatively little"
5-1
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
and notes price fluctuation of only $0.43 during the period!970 to 1990 ($3.48 and $3.91 per
metric ton, in constant 1982 dollars). They note that the stability in prices occurs because cost
increases due to increases in labor, energy, and mining and processing equipment were offset by
productivity increases.
Not surprisingly, "transportation is a major factor in the delivered price of crushed stone"
and that, due to its low price, transportation costs "often equals or exceeds the sale price of the
product at the plant." 2 USGS notes that "because of the high cost of transportation and the large
quantities of bulk material that have to be shipped, crushed stone is usually marketed locally."3
The transportation method is typically by truck; according to the USGS 2008 Minerals
Yearbook, nearly 81 percent of stone mined nationwide is transported from the quarry by truck
and only 5 percent and 3 percent is transported by rail and waterway, respectively; the remainder
is used on site.4
According to the 2008 Minerals Yearbook, an important change in the industry is a
significant increase in the number of sales and distribution yards. Those "located near
metropolitan areas significantly reduce the distance most trucks must travel to pick up and
deliver crushed stone. Therefore, the transportation costs are reduced, as is the impact on heavy
traffic on the infrastructure and the environment."5
Crushed stone from Michigan makes up an important part of stone that is transported
long-distance in the Great Lakes region. According to the Great Lakes Maritime Task Force
(GLMT) comments on the Category 3 marine rule, this stone is attractive to power plants and
manufacturers far inland because it "has the chemical properties ideal for use in scrubbers in coal
fired power plants. Its high calcium carbonate (>97 percent) and low bond work index make it
easier and less expensive to grind in mills. The high CaCOs scrubs more 862 with less stone."
GLMT notes that at least one Great Lakes power company was concerned that the potential
impacts of the EGA fuel requirements on Great Lakes shipping carrying capacity would
adversely affect the ability of this transportation sector to supply Michigan and Ohio power
plants with stone for scrubbers. The annual need of that particular facility is more than 400,000
tons.6
3.1.2 Methodology
To examine the economic impacts of applying the EGA fuel requirements on the stone
sector, EPA chose to follow the competitive radius methodology used in the 2009 Canadian
Shipowners' Association study, which examines stone deliveries to two cities in Ohio (see
Section 1.6.3.2 of Chapter 1). Rather than performing an in-depth study of the nature of local
quarries for a particular stone user and assessing the extent to which such quarries could replace
stone from long-distance sources, both in terms of quality and quantity of stone, the CSA
methodology instead looks at the extent to which higher transportation costs for ship would
increase the competitive radius around purchasing facilities, resulting in an increase in the
number of local quarries that could service the facility and thus a change in the competitive
dynamics of that market.
In the CSA approach, a geographic area is created around a purchasing facility within
which the facility would be indifferent between using stone from a distant quarry transported by
5-2
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
ship or stone from a local quarry transported by truck, given identical stone characteristics. In
other words, the total transportation costs would be the same. This competitive radius is
estimated based on the distance a fleet of trucks can operate from the using facility location
carrying the same quantity of stone for the same total transportation cost as that of the base case
ship/rail scenario. Once the geographic area is identified, it is superimposed on a map identifying
the using facility and the local quarries. The analysis is then repeated using total freight rate for
ship/rail transportation adjusted to account for the EGA fuel costs. This expanded competitive
radius indicates that additional local quarries may become competitive as a result of the increase
in ship operating costs. There are two ways to evaluate the impact of the increase in competitive
radius. The first is to consider the absolute number of additional quarries that are included in the
expanded radius. The second is to consider the size of the increase in radius. If either the
number of additional quarries or the size of the increase in radius is small, then no change in the
competitive structure of the market is indicated and no source shift would be indicated.
Consistent with the methodology used in the CSA study, this analysis does not examine
the reasons why the purchasing facility uses stone originating at a much longer distance,
requiring ship transportation, when stone from local quarries may be available.
The analysis does not assume that substitution of local crushed stone is impossible; that
assumption would be to say that only Michigan crushed stone has the properties required by the
using facility and therefore there would be no source shift. A At the same time, however, the
analysis does not examine the extent to which such additional quarries could supply the
purchasing facility in terms of quantity or quality of stone. Such an analysis would require
detailed information about the using facility and each of the quarries within the competitive
radius of that facility. Instead, the analysis is based on the assumption that the using facility is
making an economically sound decision in purchasing the stone from Michigan and that the
dynamics of the crushed stone market are such that the using facility purchases at least some
stone from Michigan quarries. The analysis examines whether an increase in competitive radius
around the using facilities corresponding to an increase in the freight rate for crushed stone from
Michigan is large enough that it is likely to result in a change in the competitive dynamics of the
crushed stone market for that facility.
3.1.3 Data Inputs
This analysis was performed for Scenarios 13-16, identified in Chapter 2. Table 3-1
repeats the estimated total freight rates for the stone scenarios, for the primary (Base) case and
the EGA (MDO) fuel case, used in this source shift analysis. The increase in freight rates is
estimated using the methodology described in Chapter 2.
A One peer reviewer noted that "if the higher cost of fuel causes customers to source their products more nearby, the
products must be close enough substitutes that they should not travel such distances in the first place. In other
words, if close substitutes do not shift closer then society must be subsidizing excessive freight transport distance ...
Especially whether the product is iron ore or Michigan stone that is high in calcium carbonate, the product is
sufficiently unique that it does not provoke a shift" (Belzer)
3-3
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-1 Estimated Freight Rate Increases Associated with ECA Fuel - Stone Scenarios"
Scenario
13
14
15
16
Base Scenario Route
Stone from Port Dolomite, MI to J.M.
Stuart Power Plant, Aberdeen, OH
Stone from Calcite, MI to J.M. Stuart
Power Plant, Aberdeen, OH
Stone from Calcite, MI to American
Crystal Sugar Co., Crookston, MN
Stone from Quarry at Calcite, MI to
Bruce Mansfield Power Station,
Shippingport, PA
Base Case
Total Freight
Rate
$10.89
$8.91
$12.04
$6.51
ECA (MDO) Case
Total Freight
Rate
$11.15
$9.14
$12.39
$6.82
Base to ECA
(% Diff)
2.4%
2.6%
2.9%
4.8%
"Data from Table 2-1
Consistent with the CSA study, this analysis is based on trucks with a delivery of a load
of 39 metric tonnes (43 short tons) of stone by a tandem tractor and quad dump semi-trailer.8 A
delivery load of this size provides a conservative analysis of the impacts, as a smaller delivery
load would require more trucks to deliver the same amount of crushed stone as one shipload.
Because the CSA study does not give details with respect to truck operation, we assume fuel
consumption to be 5 mpg. This analysis uses the same fuel price, $2.00/gallon, as the
transportation mode shift study in Chapter 2 (see discussion in Section 2.5.1.3)B and assumes the
share of fuel to total operating costs to be about 40.2 percent.9
The analysis uses state-level prices for crushed stone as reported in the USGS 2008
Mineral Yearbook (Table 4; 2007; nominal prices) for Minnesota ($9.68/short ton), Ohio
($5.98/short ton) and Michigan ($4.40/short ton).'"
10
This approach assumes that the freight rate on a dollar per ton basis is the same for trucks
as for the ship/rail case (i.e., stone can be transported from a local quarry to the purchasing
facility at the same price per ton as the ship/rail method). However, anecdotal evidence suggests
that truck rates may be higher, at $20 per short ton or more. In this case, the competitive radius
from the using facility, and the increase in that radius due to the increase in ship fuel costs,
would be smaller.
To simplify the analysis, this approach does not take into account the sometimes spidery
nature of road networks but instead assumes the truck routes are straight lines from the local
quarries to the using facility. As a result, the true competitive radius around a using facility may
be shorter than a simple wheel-and-spokes approach suggests. Therefore, the results of the
analysis are conservative in that the approach maximizes the competitive radius around a using
facility.
B One peer reviewer notes "The current cost of diesel fuel is around SS/gallon. ... as long as fuel prices rise,
systematic shifts likely will favor maritime over rail and rail over truck, so a low price probably leaves a very
conservative result in this case." (Belzer)
5-4
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
This analysis does not consider constraints such as whether the number of trucks needed
to transport the equivalent of a shipload of stone (41,900 short tons, or about 974 truckloads)
would be available, or whether local roads can absorb the additional traffic on a constant basis.
These constraints would ultimately be relevant, however, in terms of environmental and other
social costs associated with the high number of additional trucks on the road in a given area as
well as the ability of localities to absorb the additional traffic due to road capacity and other
infrastructure constraints.
3.1.4 Detailed Results
Table 3-2 presents the results of the competitive distance analysis for Scenarios 13
through 16. We estimated the impacts two ways: one in which using facility is indifferent with
regard to the freight rate (the freight rates are equivalent for trucks and marine/rail intermodal)
and one in which the using facility is indifferent with regard to the total cost of the delivered
stone (freight rate plus cost of stone are equivalent for trucks and marine/rail). From either
perspective, this analysis shows that the increase in fuel costs for Great Lakes ships is expected
to increase the competitive radius around using facilities by only about five to eight miles for the
four stone scenarios analyzed.
Table 3-2 Stone Scenarios Competitive Radius Analysis
SCENARIO
13
14
15
16
EQUAL SHIPPING PRICE PER TON
Base
Competitive
Radius (mi)
235
193
260
141
Control
Competitive
Radius (mi)
241
198
268
147
Increase
Competitive
Radius (mi)
6
5
8
7
EQUAL TOTAL PRICE PER TON
Base
Competitive
Radius (mi)
201
159
146
107
Control
Competitive
Radius (mi)
207
164
154
113
Increase
Competitive
Radius (mi)
6
5
8
7
An increase in competitive radius of this magnitude is not expected to change the nature
of the local stone markets by very much for the four scenarios under consideration with respect
to both the number of additional quarries and the size of the increase in competitive radius.
3.1.4.1 Number of Additional Quarries
With regard to the number of additional facilities, this is illustrated in Figure 3-1, for
Scenarios 13 and 14. Two sets of competitive radii are drawn around the J.M. Stuart power plant
in southern Ohio. The outer set of circles represents the competitive radius for the primary Base
and EGA cases for Scenario 13, while the inner set of circles is for Scenario 14, using the radius
calculated based on equal shipping price per ton. As can be seen, there are many quarries
located within the competitive radii of this facility. While adding 6 or 5 miles to the competitive
radii increases the number of local quarries that could be competitive, the increase is not
substantial compared to the number of quarries already located within the area.
5-5
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Figure 3-1 Competitive Radius Analysis: J.M. Stuart Power Plant0
25 50 7J
Figures 3-2 and 3-3 present similar information for the American Crystal Sugar Co.
located in Crookston, Minnesota (Scenario 15), and the Bruce Mansfield Power Station in
Shippingport, Pennsylvania (Scenario 16). In these cases, the addition of 8 and 7 miles,
respectively, to the competitive radius around the using facility does not bring in a significant
number of quarries and therefore would not be expected to change the competitive dynamics of
these markets.
The concentric circles in Figures 3-1, 3-2 and 3-3 are hand drawn, so the change in potentially competitive
quarries is solely illustrative.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Figure 3-2 Competitive Radius Analysis: American Crystal Sugar Co.
rrultซul.
-------
Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Figure 3-3 Competitive Radius Analysis: Bruce Mansfield Power Station
37- 5S 51
Jvonh
: ru1ion.ll. / ,i*.go\
These above results are somewhat different from the results of the CSA study (see
Section 1.6.3.2), where a $1.00 increase in marine rates was estimated to extend the competitive
radius around Cleveland, Ohio, and Akron, Ohio, by about 13 to 16 km (8 to 10 miles). In the
mode shift analysis described in Chapter 2, the maximum freight rate increase expected is about
31 cents, yielding an increase in competitive radius of up to 8 miles. This difference in the
relation between freight rate increase and competitive radius increase may be due to differences
in the freight rates applied in the two analyses (the CSA study does not provide the freight rates
used).
While both the CSA study and the above analysis conclude that only a small number of
quarries would be added to the stone market around the facilities in Cleveland and Akron, CSA
estimates that this would result in a 20 percent transportation mode shift. This is based on an
assumption that "one might expect that mode shift to truck transportation from local quarries
could be double that of grain and apply to many more movements" (p. 23). However, the CSA
analysis for grain is based on the application of a modal shift factor that is problematic (see
discussion in Section 1.6.3.2). Also, CSA doesn't explain why transportation mode shift to truck
would be double that of grain. In fact, CSA's analysis, as is the case with EPA's analysis, is
simply an analysis of the potential for a change in the competitive dynamics in the crushed stone
market for a given using facility based on an increase in the number of quarries located in an
expanded competitive radius around a facility. Without a detailed analysis of competing freight
rates and the constraints with road transportation to the destination facilities, as well as an
analysis explaining why these facilities currently purchase their stone from quarries located
farther away, it is not possible to speculate on the magnitude of mode shift that may occur if the
-------
Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
competitive radius were significantly expanded. An increase in the number of potentially
competing facilities is not, in itself, an indicator of the amount of mode shift that would be
expected. It is an indicator for the potential for increased competition and therefore downward
price pressures for delivered stone.
3.1.4.2 Additional Distance
The second way to evaluate the impact of an increase in the competitive radius is to
examine increase in the distance from the using facility for a round trip. For all four scenarios,
this increase is very small, 11 miles for Scenario 13, 10 miles for Scenario 14, 15 miles for
Scenario 15, and 13 miles for Scenario 16. In fact, it is possible that quarries located within such
a marginal extra distance can already compete with the quarries within the base case competitive
radius. For example, in Scenario 15 (stone to American Crystal Sugar Company, MN) about 2
additional quarries would be drawn into the market. However, given the increase in round-trip
distance of only 15 miles, those quarries may be considered competitive with the existing
quarries even without the increase in ship freight rates. The additional 15 miles would increase
the fuel costs per trip by about 3 percent, and total operating costs by about 1 percent. Averaged
over miles in the original competitive radius, the increase in fuel costs is about $0.06/gallon/trip,
which is well within the fluctuation of diesel fuel prices. Therefore, including these quarries in
the revised competitive radius does not significantly change the competitive nature of this
market. Table 3-3 contains the results of this analysis for the other three stone scenarios, with
similar results.
Table 3-3 Stone Scenario; Fuel Costs Associated with Increase in Competitive Distance
Transport price 1 truckload
Fuel costs for 1 truckload
Increased mileage round trip
Additional fuel for longer trip (gal)
Increased fuel costs for longer trip
Increased in base fuel costs ($/gal)
% increase in fuel costs for longer trip
% increase in total costs for longer trip
SCENARIO 13
$468
$188
11
2.2
$4.50
$0.05
2.4%
1.0%
SCENARIO 14
$383
$154
10
2.0
$3.98
$0.05
2.6%
1.0%
SCENARIO 15
$518
$208
15
3.0
$6.05
$0.06
2.9%
1.2%
SCENARIO 16
$280
$113
13
2.7
$5.36
$0.10
4.8%
1.9%
3.1.4.3 Sensitivity Analyses
We performed three sensitivity analyses, with respect to the size of the truck load, the
truck freight rate, and the truck route. These results, reported in Table 3-4, show that a smaller
delivery load (20 tons instead of 43 tons per truck) results in a smaller competitive radius for
each scenario. A more expensive truck freight rate ($20/ton) also results in a smaller competitive
radius for each scenario. Finally, to reflect a less direct route between a local quarry and the
using facility, we assumed that a truck would use the same amount of fuel as in the primary case
but diversions along the transport route would be increased by 10 percent. This reduces the
competitive radius as well as the difference in competitive radius caused by the increase in fuel
costs. For each of the sensitivity analyses, the change in competitive radius remains about the
5-9
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
same, less than 10 miles, and is not large enough to change the competitive nature of the relevant
market.
Table 3-4 Stone Scenarios Competitive Radius Analysis - Sensitivity Analyses
SCENARIO 13
SCENARIO 14
SCENARIO 15
SCENARIO 16
Primary Results: Equal Shipping Price/Ton
Baseline Radius (mi)
Control Radius (mi)
Net Increase (mi)
235
241
6
193
198
5
260
268
8
141
147
7
Sensitivity Results: 20 Ton Truck Load; Equal Shipping Price/Ton
Baseline Radius (mi)
Control Radius (mi)
Net Increase (mi)
110
112
o
J
90
92
2
121
125
4
65
69
o
J
Sensitivity Results: Truck Freight Rate $20/ton; Equal Shipping Price/Ton
Baseline Radius (mi)
Control Radius (mi)
Net Increase (mi)
128
131
o
J
86
88
2
157
161
5
46
48
2
Sensitivity Results: Truck Route Not Direct; Equal Shipping Price/Ton
Baseline Radius (mi)
Control Radius (mi)
Net Increase (mi)
212
217
5
173
178
4
234
241
7
127
133
6
3.2 Production Shift Analysis
In addition to transportation mode shift and source shift, several stakeholders told EPA
that an increase in the fuel costs for Great Lakes shipping could lead to a production shift,
particularly for steel production and electrical generation. This section examines these potential
impacts in two ways. First, a retail revenue analysis is used to compare the increase in industry
coal and iron ore transportation costs to total sector revenues. This analysis shows that the
impacts on the prices of electricity and steel are expected to be small, less than 0.5 percent for
electricity, and less than 0.1 percent for steel, and are within historic price variation ranges.
Second, the increased costs for transporting iron ore by Great Lakes ships using EGA fuel is
compared with the costs of transporting steel to the Detroit area from out-of-area producers.
This analysis shows that the costs of transporting out-of-area steel to Detroit would be greater
than the increase in fuel costs to transport iron ore to regional steel mills that currently supply
those using facilities. Both of these analyses show that application of the EGA fuel standards to
the Great Lakes is not likely to result production shift away from the Great Lakes region for
either of these two sectors.
3.2.1 Retail Revenue Analysis
To examine whether increased marine transportation costs on the Great Lakes would
result in shift of steel and electrical production out of the Great Lakes regions, we us a two-part
retail revenue analysis. This involves comparing the increase in transportation costs to revenues
in each sector, and examining how that increase compares to actual price fluctuations
experienced in the sector. If the transportation price increase is small and is within the range of
historic price fluctuations, then we conclude that production is not likely to be shifted out of the
3-10
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
region. This is especially so because moving the location of production could be very costly.
Even if there is excess capacity at other production sites, moving production would require
modifying another facility to accommodate increased production and/or creating new supply,
production and transportation chains, all of which can be very costly. In addition, additional
transportation costs would be incurred to transport the product - finished steel or electricity - to
Great Lakes region users. For steel this would entail truck or rail transportation, which is more
expensive than marine shipping on a ton-mile basis; for electricity it could entail electrical grid
changes.
It should be noted that the impact analysis presented in this section is a sector-level
analysis that is limited to the two specific sectors examined, electricity and steel, and is not for a
specific producer. The actual impacts for a specific facility depend on the individual producer's
cost data, and marginal or incremental cost analysis for that facility.
3.2.1.1 Methodology
In this retail revenue analysis, we estimate the impact of the expected increase in the
transportation cost of coal and iron ore as a percentage of the revenues for the each of the
electricity and steel markets. We then compare the expected percentage increase with historic
price fluctuations on a percentage basis.
For this analysis, the transportation cost increases estimated in Chapter 2 are used. These
cost increases, reproduced in Table 3-5, vary depending on transportation routes and the
commodity shipped. The shipping cost for coal is expected to increase by 1.2 percent to 4.5
percent and the shipping cost for iron ore is expected to increase by 8.5 percent to 16.6 percent,
depending on the scenario. One implication of using the estimated cost increases from Chapter 2
is that those cost increases are facility-specific while, as noted above, this production shift
analysis is intended to represent aggregated sector impacts. As a result, we use the range of
transportation cost increases estimated in Chapter 2. For coal shipped from the Rosebud Mine to
facilities in Wisconsin or Michigan (1.2 percent to 4.5 percent), the range of cost increase is
taken as being representative of the cost increases that would apply to power plants throughout
the Great Lakes region. Because there is variation in the cost estimates (i.e., they are not
homogeneous), the use of this range of cost estimates is reasonable.
3-11
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-5 Estimated Shipping Cost Increases"
Scenario Number, Origin & Port Used, Destination
& Port Used
1
2
O
4
5
6
7
8
Rosebud Mine - Superior to Bayfront Power
Plant - Ashland, WI
Elk Creek Mine - South Chicago to GP West
Mill - Green Bay
Rosebud Mine - Superior to DTE Power Plants
- Port Huron
Rosebud Mine - Superior to Weadock & Kam
Generating Plants - Essexville
Empire and Tilden Mines - Marquette to
Algoma Steel - Algoma
Quebec Carrier Mining Co. - Port Carrier to
ArcelorMittal - Chicago/ Burns Harbor
Hull Rust Mine - Duluth to U.S. Steel - Gary
Northshore Mining - Silver Bay to Severstal -
Ashtabula
Cargo
Coal
Coal
Coal
Coal
Iron ore
Iron ore
Iron ore
Iron ore
Base Case Total
Freight Rate
$19.99
b
$21.19
$25.28
$4.12
$16.10
$6.21
$6.83
MDO Case Total
Freight Rate
$20.23
b
$22.00
$26.41
$4.47
$18.77
$7.14
$7.73
% change
1.2%c
b
3.82%
4.47% d
8.50% c
16.58%d
14.98%
13.18%
Notes:
a Data from Appendix 2C, Table 76. Summary Results of Default Scenario Freight Rates compared to All-Rail
Alternative Freight Rates, if available (all $/cargo ton).
b Results are inconclusive due to mis-specification of the scenario. See discussion in Chapter 2.
0 Percent change represents "the lower bound scenario"
d Percent change represents "the upper bound scenario"
Data on the transportation cost for coal and iron ore, total material cost, and total sales are
obtained from the 2007 Census Bureau, Census Data On Manufacture Industry: iron and steel
industry, NAICS code 331111, for the steel sector, and from the EIA Publication: Electric
Power Monthly, January 2010, DOE/EIA-0226 (2010/01), for the electric sector.
3.2.1.2 Impact on the Great Lakes Electric Sector
To estimate the impact of higher freight rates on the Great Lakes electricity generation
sector, we need to have electricity cost data for the region (East North Central region0). These
data are collected from a recent EIA release. n Two types of data are used in the analysis: (a)
monthly data for October 2009 and October 2008, (b) year-to-date data through October 2009
and October 2008.
This analysis assumes that all coal used for electrical generation in the entire Great Lakes
region is moved by water (not truck and rail). This is certainly not the case and therefore the
results are a conservative estimate of the impacts of the EGA fuel sulfur requirements because
this analysis applies the transportation cost increase to all coal used in electrical generation.
Much of the coal used by power plants in the region is not transported by water, and some
electricity is generated by hydroelectric rather than coal facilities.
D The East North Central region in EIA includes state of Illinois, Indiana, Michigan, Ohio, and Wisconsin.
3-12
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
We use a two-step approach to estimate the revenue impact. The first step is to estimate
the impact of an increased shipping cost on "delivered coal cost" (the cost of coal delivered for
electricity production use). The second step is to estimate the impact of the increased "delivered
coal cost" on electricity revenue.
The EIA regional data for the electricity sector includes only delivered coal cost; it does
not provide separate data for coal cost at the mine and coal shipping cost. Therefore, to perform
this analysis we use EIA reported 2008 U.S. national average coal cost at the mine to
approximate coal cost at the mine for the Great Lakes region. Then, we apply the lower and
upper bound percent increase between the base case freight rate and MDO control case freight
rate (Table 3-5) to the coal cost at the mine to estimate the "delivered coal cost" for the Great
Lake area.
Using this method, shipping costs would be about 39 to 45 percent of "delivered coal
cost," and increasing shipping costs by about 1.2 percent to 4.47 percent would be equivalent to
increasing "delivered coal cost" by about 0.47 percent to 2 percent. It should be noted that this
increase in "delivered coal cost" does not back out the other transportation components such as
the percentage delivered by truck or direct rail since we do not have this information. The
estimated percent increase in "delivered coal cost" as a result of the switch from HFO to MDO is
reported in columns (4) and (6), Table 3-6, for the low and high increase for the marine EGA-
adjusted freight rates, respectively.
In the second step, electricity sales and cost data from EIA publication are used to
estimate the impact of the increase in "delivered coal cost" on electricity revenue. The data used
to perform this analysis are total electricity sales (in MWh) and revenue (in $Million).
The results of this analysis, set out in Table 3-6, indicate that if shipping costs increase by
1.2 percent (the lower bound scenario) due to implementing EPA's fuel requirement, the
increased transportation costs are small compared to electricity retail revenue, about 0.1 percent.
If shipping costs increase 4.5 percent (the upper bound scenario), the comparison of the impact
on shipping costs to electricity retail revenue increases to about 0.5 percent. The results reported
in Table 3-6 also show that the impacts for independent power or public utility companies are
similar. As a result, the increase in transportation costs due to the application of the EGA fuel
requirements to the Great Lakes are not expected to generate a production shift, and are likely to
be smaller than the costs facilities would incur to relocate production out of the region.
3-13
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-6 Production Shift Results - Electrical Sector
Elect. Utility
October 2009
Indep. Power
October 2009
Elect. Utility
Annual 2009
Indep. Power
Annual 2009
Revenue from
retail sales of
electricity
generated with
coal
($ million)
$2,185
$805
$22,460
$8,468
Delivered
Coal Cost
($ million)
$523
$178
$5,324
$1,968
Low cost Case
(Delivered
Coal Cost
increased
1.20%)
$526
$179
$5,348
$1,978
Low cost Case
Increase in
Delivered Coal
costs % of
electricity
revenue
0.11%
0.10%
0.11%
0.11%
High Cost
Case
(Delivered
Coal Cost
increased
4.47%)
$533
$181
$5,430
$2,008
High Cost Case
Increase in
Delivered Coal
costs % of
electricity
revenue
0.48%
0.44%
0.47%
0.46%
Notes:
Coal cost is around 22% to 24% of electricity revenue
For a public utility company, around 55% of electricity revenue is from coal generation and for an independent
power generator, around 24% of revenue is from coal generation
Shipping cost of coal is around 40% of coal cost in this region. In general, national average is about 25%.
Source: Electric Power Monthly, January 2010, DOE/EIA-0226 (2010/01)
http ://www. eia. doe . sov/cneaf/electricitv/epm/epm sum. html
These estimated freight rate increases can be compared to the history of retail prices for
electricity for the Great Lakes states, set out in Table 3-7. The expected freight rate increases of
0.1 and 0.5 percent are small compared to historic electricity price variations.
Table 3-7 Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, By State, Percent
Increase, Year-to-Date July 2009 to July 2010
Middle Atlantic
New Jersey
New York
Pennsylvania
East North Central
Illinois
Indiana
Michigan
Ohio
Wisconsin
Residential
6.0%
-0.3%
5.9%
10.0%
2.6%
-0.6%
-3.0%
6.8%
6.0%
2.8%
Commercial
3.7%
-4.2%
6.8%
6.1%
0.6%
-4.2%
-1.9%
6.8%
1.8%
2.7%
Industrial
2.6%
3.1%
-3.8%
5.7%
-5.2%
-3.8%
-2.1%
-1.1%
-12.2%
-1.5%
Transportation
0.9%
-3.3%
2.0%
-0.3%
-23.3%
-23.5%
-7.3%
-4.3%
-14.8%
N/A
All Sectors
4.6%
-1.6%
5.9%
7.6%
-0.1%
-2.2%
-2.6%
4.5%
-0.3%
1.7%
Source: http://www.eia.doe.sov/electricitv/epm/table5 6 b.html (accessed October 20 10)
This analysis certain limitations due to the assumptions used. For example, we assumed
all the delivered costs in the region are increased by either 1.2 percent or 4.5 percent due to our
fuel requirement. However, not all the coal used to generate power in the Great Lakes areas is
transported by Category 3 vessels, and coal delivered by other modes is not affected. Therefore,
the results of this analysis are likely overstated.
3-14
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
3.2.1.3 Impact on Steel
We used U.S. Census Bureau data for the iron and steel manufacture industry (NAICS
code: 33111) to estimate shipping cost impacts on the steel sector. This analysis uses national-
level data because steel production is a vertically integrated industry. Steel manufacturing
begins with the processing of raw materials such as iron ore and coke, followed by iron and steel
making, and then production of steel scrap, stabs, thin slabs, and many other final steel products.
One company may use several facilities to complete its manufacturing process. Thus, national
data more fully represent this input and output relationship. In 2002, there were 379 facilities
listed under the iron & steel industry by NAICS code 331111 (Census Data, Geographic
Distribution -Iron & Steel MillsE); 194 facilities (51 percent) are located in Great Lakes area or
adjacent states.F With regard to shipments, facilities in the states of Ohio, Pennsylvania,0 New
York, Michigan and Illinois account for 63 percent of the value of U.S. shipments.
The total revenue and cost data of the iron and steel manufacturing industry from the
2007 census are selected to estimate the impacts.H Since Great Lakes coal movements are
almost exclusively destined for power plants and almost no coal is used in steel production, this
analysis considers iron ore as the only major input affected by increased freight rate for steel
manufacturers.1 The results from this approach represent the shipping cost impact on all final
steel products in general.
E Census Bureau Website: http://www.census.gov/econ/census02/data/industry/E331111.HTM, accessed on March
2,2011.
F States of Indiana, Ohio, Pennsylvania, Illinois, Michigan, New York, Minnesota, Wisconsin
G Pennsylvania's shipment value in % of U.S. in 1997 Census data is used because Pennsylvania does not provide
shipment value in 2002 Census
H US Census Bureau, 2007 economic census on the iron and steel industry (NAICS code 331111), (1) Sector 31:
EC073113: Manufacturing Industry Series: Materials Consumed by Kind for the United States: 2007, (2) Sector 00:
EC0700A1: All Sectors: Geographic Area Series: Economic-Wide Key Statistics: 2007. Available at
http://www.census.gov/econ/census07/index.html/
1 One peer reviewer noted that "Great Lakes coal movements are almost exclusively destined for power plants and
almost none is used in steel production (steel companies usually use coke [which] is rail supplied)." This peer
reviewer also noted that "[tjhere are a few exceptions, like the Rouge steel plant in Detroit, which occasionally
receive[s] a shipload of metallurgical coal, but there aren't many. (Hull) EPA confirmed that coal is only used in
facilities that also produce coke. Therefore, EPA removed the coal impacts from the steel analysis included in this
section.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
The American Spirit takes on a load oftaconite at the ore loading facility in Escanaba, MI.
Source: Photograph taken by and used with permission from Dick Lund, accessed here:
http://www.dlund.20m.com/lund2.html
Similar to the two-step approach in the electricity impact analysis, the first step is to
separate "the commodity cost at the mine" and "the shipping cost" in the "delivered commodity
cost" reported in the census data.J Iron ore is assumed to be the only commodity shipped by
water for the steel production. In addition, we assume that 80 percent of the delivered iron ore
cost is "iron ore cost at the mine" and the other 20 percent of the delivered iron ore cost is
"shipping cost." The USGS reports the value at the mine ($/metric ton) of iron ore in the United
States has varied between $37.92 and $70.43 for the years 2004 through 200712. Using our
estimated base case total freight rate, we estimate that shipping costs would vary between about
6 percent and 30 percent of the total price of iron ore. Therefore, 20 percent is a mid-range
value. This is a conservative estimate given the higher value of iron ore at the mine in recent
years. However, the actual ratio between "iron ore cost at the mine" and "shipping cost" varies
depending on many factors, including the price of iron ores in the world, the steel price, and the
shipping cost. After applying the estimated shipping cost increase, "delivered commodity costs"
are estimated. The second step applies these "delivered commodity costs" to steel costs and
revenue data to estimate the impact on steel.
According to census data, total sales for this sector in 2007 were $100.2 billion. Iron ore
inputs were valued at $3 billion, and iron ore transportation cost is valued at $0.6 billion (20
percent of iron ore cost).
The results of this analysis, set out in Table 3-8, indicate that if iron ore shipping costs
increase by 8.5 percent (the lower bound scenario) or 16.6 percent (the higher bound scenario),
due to implementing EPA's fuel requirement, this increase represents about 0.13 percent to 0.17
1 Census Data only provides the delivered commodity (coal and iron ore) cost for the steel industry
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
percent of total materials costs for the iron and steel industry, which represents 0.05 percent
(lower bound scenario) or 0.1 percent (upper bound scenario) of industry revenues. In other
words, while the program is expected to lead to an increase in freight rates of 8.5 percent to 16.6
percent, depending on the scenario, the increase in the transportation freight rate is only part of
the price of iron ore, which is only one input to the production of steel, and therefore the impact
on steel costs is less that 0.2 percent. These impacts are not expected to lead to a production
shift because the cost of relocating production out of the region would almost certainly be more
substantial. Relocation costs would include, among other things, the cost of creating or
modifying steel production facilities in other locations (assuming there is enough excess capacity
available to cover all the steel production in one or all Great Lakes steel mills), the cost of
developing new supply chains and infrastructure, and the cost of transporting steel to
manufacturers in the Great Lakes region who use it as an input.
Table 3-8 Impact on Steel due to Shipping Cost Increase
(1) Total sale revenue
(2) Total materials cost
(3) Baseline case Iron ore input cost
Transp. Cost (%)
Transp. Cost ($)
Transp. Cost as % total materials cost
Transp. Cost as % revenue
(4) Low bound scenario (shipping cost increased by 8.5%
New transp. Cost
Transp. Cost as % total materials cost
Transp. Cost as % revenue
(5) Upper bound scenario (shipping cost increased by 16.6%
New transp. Cost
Transp. Cost as % total materials cost
Transp. Cost as % revenue
(6) Transp. Cost increase impact in the lower bound case as
% total materials/revenue
(7) Transp. Cost increase impact in the upper bound case as
% total materials/revenue
SMillion
$100,240
$56,265
$3,000
20%
$600.05
1.07%
0.60%
$651.1
1.20%
0.65%
$699.6
1.24%
0.70%
0.13%/0.05%
0.17ฐ/o/0.10%
In addition, while steel is used in a large variety of goods, ranging from vehicles to
containers, appliances and electrical goods, and construction, it represents only one input among
many to produce these goods. Therefore, the impact of increased transportation costs due to new
fuel requirements on the steel sector can be expected to have only a negligible impact on the
prices of these finished goods. Figures 3-4 and 3-5 illustrate historic fuel prices and the monthly
price change for the period January 2009 through January 2011. According to steel industry
data, monthly steel price fluctuations have ranged from a decrease of 12 percent to an increase of
14 percent. These steel price fluctuations are larger than the expected impacts on revenues for
this sector.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Figure 3-4 World Steel Prices, 2009-2010 (US$/tonne)
Steel Price Levels by Month - World Carbon Steel Transaction Prices
51.000
$900
5800
$700
$600
$500
$400
$500
$200
$100
Jan-09 Apr-09 ltd -09 Oct-09 lan-10 Apr-10 lul 10 utt-10 Jan-11
-HotRolled Steel Coil
-HotRolled Steel Plate
-Cold Rolled Steel Coil
-Steel WireRod
- Medium Sted Sections
Source: http:/Avww.steelcintJienet com/rmcejnfo html
Figure 3-5 World Steel Prices, 2009-2010 (US$/tonne)
Steel Price Levels Monthly Percent Change 2009 andZOlO - World Carbon Steel Transaction Prices
-HotRolled Steel Coil
- Hot Rolled Steel Plate
Cold Rolled Steel Coil
-Sted WireRod
- M edium Steel Sections
IV
Fel>-09 May-09 Aug-09 Nov-09 Fel)-10
Source: http://www.steelonthenet.com/price_info.html
Mav-10
Aug-]0
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Since we could not obtain region-specific data on the steel industry, this analysis uses the
national level industry data from the Census Bureau. Thus, the analysis assumes that all the
delivered costs for iron ore and coal in the nation are affected by the new fuel regulation, and all
iron ore and coal used for steel making in the nation are delivered on Category 3 ships. To the
extent that these increased costs can be spread across steel production nationally, the results of
this analysis may be overstated.
Finally, it is worth noting that steel production processes are changing and more steel is
being produced from scrap metal. One source estimates that as much as 51 percent of iron used
to make steel now comes from scrap.13 This means that only a portion of steel produced, about
half, will see a production cost increase due to the costs of transporting iron ore by ships using
EGA-compliant fuel. Steel producers may be able to spread this cost increase over all steel
output, thus reducing the impacts of EGA control per unit from both fresh iron ore and from
scrap material.
3.2.2 Detroit Steel Scenario
A second way to explore production shift impacts is to examine a specific scenario.
Commenters on our Category 3 rule were concerned that an increase in transportation costs for
iron ore of the magnitude estimated in this analysis might result in a shift of U.S. steel
production away from the Great Lakes. This section examines this potential shift with respect to
both domestic and foreign steel production.
According to the American Iron and Steel Institute, approximately 40 percent of the steel
produced in the United States during the week ending September 25, 2010, was produced in the
Great Lakes region (Pittsburg/Youngstown, Lake Erie, Detroit, Indiana/Chicago).14 The next
highest producing region was the Southern region, with 33 percent. While production on the
Great Lakes has decreased over time, from 75 percent in the early 1990s to 60 percent in the
early 2000s to 40 percent currently, this region is still the most important in the United States for
steel production.15 The Great Lakes region is favorable for steel production not just due to the
importance of the waterway for transportation of inputs but also because it can supply the large
quantities of water used in steel manufacturing.16
If steel production were shifted out of the Great Lakes region, that steel would need to be
transported to end-use facilities located in the Great Lakes region. This is important because
nearly 60 percent of automobiles and 45 percent of light-duty trucks manufactured in the United
States are produced in the four Great Lakes states of Michigan, Ohio, Indiana, and Illinois.17 The
region also has many producers of other goods that use steel produced in the area. If steel
production were to move out of the Great Lakes region, the transportation costs associated with
bringing that steel back into the region for these manufacturing facilities would be likely to be
higher than the additional costs of transporting the steel inputs to the mills as a result of the EGA
fuel requirements. This is largely due to the longer distances the steel would have to be shipped
(from outside the Great Lakes region) and the higher cost of rail or truck transportation.
Similarly, a production shift to steel mills outside of the United States is not likely to
result in reduced costs. Over the last 15 years, the United States has imported about 20 percent
of its steel.18 The main source countries are Canada and Mexico, which accounted for about 35
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
percent and 13 percent of steel imports, respectively, in 2009 (29 percent and 14 percent,
respectively, in 2007). China, Japan and Korea account for about 18 percent, and Germany and
Italy account for another 7 percent. Altogether, these seven countries account for nearly 60
percent of imported steel in the United States.
It is not clear that shifting more production to these countries would offset the additional
costs associated with complying with EGA fuel requirements for transporting iron ore and coal
on the Great Lakes. Not only is imported steel subject to import taxes, tariffs, and quotas but, in
addition, steel transported from Asia or Europe would have to go through at least one EGA and
potentially two. This is because all U.S. ports in the continental United States are located within
the North American EGA, which extends about 200 nm from U.S. coasts in most cases (see
Figure 1-3). Depending on the route, ships from Asia may spend as many as 1,700 miles in the
North American EGA if they take the North Pacific route to Los Angeles, which is about the
distance of the default route from Baie Comeau to Chicago in Scenario 9 (see Figure 3-5). Ships
coming from Germany to an East Coast port would transit the North Sea EGA as well as the
North American EGA. In addition, the steel would need to be transported by truck or rail from
the coastal port to where it will be used in production facilities. Again, because rail
transportation rates are more costly than ship freight rates, this alternative would result in a
significantly more expensive increase in transportation costs when compared to shipping the raw
material inputs for steel through a Great Lakes EGA. Even if ship owners have discretion in
where they offload their cargo, the steel consumers are unlikely to want to bear the additional rail
cost associated with this option.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Figure 3-6 Examples of Ship Routes: Great Lakes and West Coast
Legend
CASE STUDY 9
OD PAIRS DEFAULT - INTERMODAL ^^ALTERNATIVE - RAIL ONLY
250 yป
Distance on Great
Lakes/Seaway: 1,700 nm
Distance in EGA
1,700 nm
54llgele5 to Singapore: 7,700 nn,
Source: EPA
The additional costs of importing steel can be illustrated by the example of steel that is
manufactured in Indiana Harbor, Indiana, and for use in Detroit, Michigan.19 Steel is made
primarily of three raw materials; iron ore, limestone, and coke. Based on comments from
industry, roughly 1.5 tons of iron ore and 0.7 ton of limestone are shipped on the Great Lakes for
every ton of steel produced. Coke typically arrives by rail, and therefore will not be affected by
a Great Lakes EGA. In addition, steel is typically transported from Indiana Harbor to Detroit by
truck, so this part of the transportation also will not be affected by a Great Lakes EGA.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
There are a number of sources of iron ore and limestone located on the Great Lakes. For
this example, we consider iron ore originating from Two Harbors, Minnesota, Silver Bay,
Minnesota, and Escanaba, Michigan, and limestone originating from Port Inland, Michigan, and
Cedarville, Michigan. Assuming that iron ore comes 50 percent from the Two Harbors/Silver
Bay area and 50 percent Escanaba, the average ton of iron ore travels 460 nm miles to Indiana
Harbor. Splitting the distance between Port Inland and Cedarville, the average ton of limestone
travels roughly 260 nm. Based on these estimates, a total of 2.2 tons of raw material must be
transported by ship to produce one ton of steel. The net is 870 ton-nm (1000 ton-miles) of
transportation on the Great Lakes for each ton of finished steel. Figure 3-7 presents the shipping
routes used in this example.
Figure 3-7 Domestic Steel Shipping Routes
Source: Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines
at or above 30 Liters per Cylinder - Information in Support of Applying Emission Control Area
(ECA) Requirements to the Great Lakes Region. EPA-HQ-OAR-2007-0586. December 15, 2009.
For the imported steel case, the ship needs to pass through roughly 200 nm of the ECA
before reaching the Canadian baseline. The ship then needs to pass through the St. Lawrence
Seaway, Lake Ontario, and Lake Erie on its way to Detroit. The total distance is roughly 1,700
nm (1,960 miles). This shipping route is illustrated in Figure 3-8.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Figure 3-8 Imported Steel Shipping Route
Source: Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at
or above 30 Liters per Cylinder - Information in Support of Applying Emission Control Area (EGA)
Requirements to the Great Lakes Region. EPA-HQ-OAR-2007-0586. December 15, 2009.
Based on this example, imported steel must travel roughly twice the distance through the
EGA as the raw materials needed to produce domestic steel. Even if the domestic steel were
transported from Indiana Harbor to Detroit by ship, this would add only another 550 miles of
shipping in the EGA. As such, the imported steel still requires more shipping, in the EGA, per
ton of finished steel. In either case, the impact of increased shipping costs on a ton of steel is
much less than the historical month-to-month fluctuation in steel prices.
Table 3-9 presents the projected increased transportation costs of a ton of steel that could
result from an EGA. Note that this analysis only considers ship traffic in one direction and
assumes that the vessel will perform useful work on the return voyages (it would have a
backhaul). This assumption is reasonable because it is generally the case that ships that bring
import steel coil to the United States typically carry export grain on the backhaul. If a ship does
not have a backhaul, this would have the effect of roughly doubling the shipping cost per ton of
steel for both the domestic and import cases.
Table 3-9 Imported Steel Shipping Route Costs
Increased fuel cost [$/ton-mile]
Shipping distance in EGA [nautical miles]
Increased fuel cost [$/ton of steel]
Price of cold rolled steel (June 2009) [$/ton]a
Estimated % cost increase for steel
DOMESTIC STEEL
$0.0009
870
$0.90
$525
0.2%
IMPORTED STEEL
$0.0009
1,700
$1.75
$525
0.3%
a See http://www.steelonthenet.com/prices.html
Commenters also suggested that Category 3 ships carrying steel could offload cargo in
New York, or other east coast ports, rather than entering the Great Lakes EGA. In this case, the
ships would pass through roughly 200 nm of the EGA to the port of New York. Finished steel
would then need to be transported over land, presumably by rail, for more than 600 miles to
reach Detroit. Because rail transport rates can be more than three times shipping rates, this
alternative would result in a significantly more expensive increase in transportation costs when
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
compared to shipping through a Great Lakes EGA. The use of an East Coast port would also
affect the ability of these ships to take on a grain backhaul; currently the grain is picked up in
Canadian ports such as Baie Comeau, Quebec.
3.3 Emissions Impact Analysis
Great Lakes commenters on the Category 3 rule expressed concern that a shift away from
ships to land-based transportation would result in an increase in air emissions, the opposite intent
of the program. The analyses presented above and in Chapter 2 show that transportation mode
shift, source shift, and production shift are not expected due to the use of higher cost fuel for the
16 at-risk routes studied. Nevertheless, EPA performed an emissions analysis for each of these
16 scenarios, to examine the emissions difference between ship, rail and truck transportation
modes. EPA estimated the total air emissions of NOx, fine PM and carbon dioxide (CO2) for a
single round trip, for each Base (HFO) Case, MDO (EGA) Case and All-Rail Case (or the
highway truck alternative for the stone scenarios). The sections below present the methodology
employed in this emissions analysis and the inputs used.
This analysis shows that the use of EGA fuel is always better for the environment when
compared to current marine fuel. In addition, with the exception of two grain scenarios
(Scenarios 11 and 12) and the crushed stone scenarios (Scenarios 13-16), marine transportation
using EGA fuel is better for the environment than the alternative transportation mode.
3.3.1 Methodology
EPA estimated the emissions of a single round trip cargo movement scenario by applying
emission factors for each mode of transportation, along with estimates of the efficiency of the
vehicle employed for the various transportation options: Category 3 vessel; line haul
locomotive; and heavy-duty highway truck. These factors were combined with the scenario-
specific parameters defined in Chapter 2 regarding the volume of cargo moved and distances
traveled for each leg of each trip. Thus, for a scenario where the cargo is moved by rail for one
leg of the journey and by water for another, the general format of the emissions equations would
be as follows.
Total Base or ECA Case Route Emissions = Marine Leg Emissions (see Equation 3-1) + Rail Leg Emissions
(see Equation 2)
Scenarios 1-12 Total Alternative Case Route Emissions = Rail Emissions (see Equation 3-2)
Scenarios 13-16 Total Alternative Case Route Emissions = Truck Emissions (see Equation 3-3)
For purposes of the emissions analysis, all distances traveled assume round-trip vehicle
movements, consistent with the mode shift analysis described in Chapter 2, which assumes that
each of the scenarios would include an empty backhaul. Distances were estimated by ICF and its
contractor, EERA, through study of existing transportation networks, and with stakeholder
assistance.
Above in Section 3.1, EPA describes its analysis to assess the possibility that limestone
customers in Scenarios 13 through 16 may choose to obtain stone from local quarries via
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
highway truck rather than from more distant quarries via a water/rail route. One of the outputs of
that analysis is the distance over which a customer may be willing to pay for truck transport of
limestone to his plant. These distances are the same as those estimated in the source shift
analysis presented in Section 3.1 and are presented in Table 3-2. The Control Competitive
Radius distance under the Equal Total Price case estimated in Chapter 3 was employed in this
emissions analysis to estimate emissions from highway trucks.
EPA's emission factors for each transport mode are described below. For each round trip
route, it was assumed that the vessel load as specified for each scenario in Chapter 2 is the cargo
volume moved, regardless of mode. Because the competing modes (locomotive and truck) carry
much smaller volumes per vehicle, EPA normalized the emission estimates by multiplying the
per-vehicle emissions of the competing modes by the number of vehicles that would be needed
to carry a vessel load.
This analysis is solely for the Category 3 propulsion engines, and does not quantify
emissions from auxiliary engines or loading or unloading activities at transfer points.K
Consistent with the methodology of the transportation analyses above, which excluded the costs
of the first loading at the origin and last unloading at the destination, the effects of those initial
and final transfers have been deemed outside the scope of this analysis. EPA has not evaluated
how the emissions profiles of the self-unloading equipment on the vessels differ from the
emissions profiles of the land-based equipment. Furthermore, there are ranges in unloading rates
for both vessels and rail cars. As described below in Chapter 7, the unloading rate of Great
Lakes vessels ranges from approximately 6,000 to 10,000 tons per hour.L Given the variety of
train car unloading systems and the associated unloading rates (from 800 to 20,000 tons/hr), EPA
estimates the difference in duration of material transfer by rail could range from one third to six
90
times the transfer time of a bulk self-unloading vessel. These times exclude maneuvering and
positioning times, which would be expected to increase with the alternate freight modes.
Chapter 8, Section 8A.8 includes an additional discussion of emissions from transfer
equipment.
K Peer reviewer Hull suggested that EPA explain whether a modal shift would result in higher emissions from the
material loading and unloading activities.
L See Sections 7.5.2.1 and 7.5.3.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
The Hon. James L. Oberstar (formerly named the Charles M. Beeghly) unloading at South
Chicago. Source: Gary Clark, Unloading at South Chicago, accessed at: www.boatnerd. com
3.3.2 Data Inputs
3.3.2.1 Marine
Vessel emission factors used in this analysis are EPA's fleet average medium speed
diesel emission factors for Category 3 engines, forecast for 2015. Emission factors for diesel
engines are distinguished by the speed of the engine. The two most common types of Category 3
engines are slow-speed diesel engines (SSD) with engine speeds of 150 rpm or less, and
medium-speed diesel engines (MSD) with engine speeds of approximately 300 to 600 rpm. As
described in Chapter 7, the C3 engines on the Great Lakes vessels are typically medium speed
diesels. The emission factors are presented in Table 3-10. The PM2.5 emission factor shown in
Table 3-10 is based on 1.7 percent sulfur fuel. This PM2.5 emission factor is different from that
used in the full C3 emission inventory (2.7 percent) but is used here to show that even if the
sulfur content of fuel sold on the Great Lakes were less than that used in our inventory, as
suggested by commenters on the Category 3 rule, the emissions benefits of the EGA controls are
nonetheless considerable and are favorable compared to rail or highway truck alternatives for
most scenarios. The PM2.5 emission factor for the control case is based on use of 0.1 percent
sulfur fuel, consistent with the EGA fuel sulfur limit. The emission factors in Table 3-10 were
applied to each scenario using the given vessel horsepower and operating speed values presented
below in Table 3-11.
Although the EGA fuel standards are not set for the purpose of reducing NOx or CO2,
Table 3-10 shows that the control emission factor is slightly less than the baseline emission
factor for those pollutants. This is because there are small NOx and CO2 emission reductions
brought about by switching from residual to distillate fuel. In the case of NOx, this is because
distillate fuel has a lower nitrogen content than residual fuel. In the case of CO2, this is because
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
distillate fuel has higher energy content, on a mass basis, than residual fuel, leading to lower fuel
consumption estimates in the control (EGA) case.
Table 3-10 Category 3 2015 Fleet Average Vessel Emission Factors
POLLUTANT
NOX
PM25
CO2
BASELINE EMISSION
FACTOR (G/kWh)
13.7
1.01
668.4
CONTROL EMISSION
FACTOR (G/kWh)
12.6
0.17
636.6
The following table presents the scenario inputs from Chapter 2. Of note is that the
distances presented in the tables of Appendix 2C represent one-way distances, whereas the
distances in Table 3-11 represent round trip distances. This is only a matter of presentation, not
methodology. This emissions analysis, as well as the above energy and cost analyses, is based
on fuel consumption for the full round trip. This assumes that the vehicle (vessel or other) carried
cargo one way and had an empty backhaul.M For purposes of this simplified analysis, the same
average emission factors are applied regardless of the amount of cargo loading.
Table 3-11 Emissions Scenario Inputs"
Scenario
Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Scenario 6
Scenario 7
Scenario 8
Scenario 9
Scenario 10
Scenario 11
Scenario 12
Scenario 13
Scenario 14
Scenario 15
Scenario 16
Cargo
Load
net short
tons
10,450
11,730
48,620
28,290
11,730
15,430
48,620
48,620
14,940
15,430
11,730
4,030
41,900
41,900
41,900
41,900
Vessel
Power
hp
7,200
7,200
16,000
16,000
7,200
7,200
16,000
16,000
7,200
7,200
7,200
7,200
11,000
11,000
11,000
11,000
Vessel
Speed
mph
14
14
16
16
16
16
16
16
14
14
14
14
16
16
16
16
Round Trip Miles
By Sea (Base
&ECA)
280
780
1,520
1,240
340
3,460
1,740
1,680
3,440
3,460
1,920
370
720
640
940
860
By Rail (Base
&ECA)
2,080
2,620
2,080
2,080
40
400
160
200
-
-
100
10
520
520
500
220
Alternate6
2,520
2,860
3,240
3,320
420
N/A
1,140
1,800
2,540
3,280
1,940
480
482
396
536
294
Notes:
" Data compiled from Appendix 2C, Tables 17 through 32.
As mentioned in Section 2.6.1 of Chapter 2, this is a conservative assumption from a freight rate perspective.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Alternate mode is by rail for Scenarios 1-5 and 7-12, and by truck for Scenarios 13-16. No alternate route
was identified for Scenario 6.
When applying the EPA emission factors to each scenario, resulting per-trip vessel
emissions vary due to the range of inputs for the scenarios, engine power, and length of marine
leg. The following equation shows the method used to calculate the emissions from each marine
leg of a journey.
Equation 3-1 Marine Leg Emissions
Tons of Pollutant per Trip = EF x Power x Distance + Speed x CF
Where:
EF = emission factor in g/kW-h
Power = main propulsion engine horsepower
Distance = round trip miles traveled by the vessel
Speed = average vessel service speed in mi/hr
CF = unit conversion factors
Combining the emission factors from Table 3-10 with relevant inputs from Table 3-11,
the per-trip vessel emission rates are estimated on a cargo-related basis, set out in Table 3-12.
These values can be compared with the emissions intensity of locomotive and truck transport,
shown in Tables 3-13 and 3-14, respectively.
Table 3-12 Vessel Emission Intensity (g/100 ton-miles)
Scenario
Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Scenario 6
Scenario 7
Scenario 8
Scenario 9
Scenario 10
Scenario 11
Scenario 12
Scenario 13
Scenario 14
Scenario 15
Scenario 16
Cargo
Load
(tons)
10,450
11,730
48,620
28,290
11,730
15,430
48,620
48,620
14,940
15,430
11,730
4,030
41,900
41,900
41,900
41,900
Base
Vessel
NOX
50
45
21
36
39
30
21
21
35
34
45
130
17
17
17
17
Base
Vessel
PM25
3.7
3.3
1.5
2.7
2.9
2.2
1.5
1.5
2.6
2.5
3.3
9.6
1.2
1.2
1.2
1.2
Base
Vessel
CO2
2,500
2,200
1,000
1,800
1,900
1,500
1,000
1,000
1,700
1,700
2,200
6,400
820
820
820
820
ECA
Vessel
NOX
46
41
19
33
36
27
19
19
32
31
41
120
15
15
15
15
ECA
Vessel
PM25
0.62
0.56
0.26
0.45
0.49
0.37
0.26
0.26
0.44
0.42
0.56
1.6
0.21
0.21
0.21
0.21
ECA
Vessel
CO2
2,300
2,100
1,000
1,700
1,800
1,400
1,000
1,000
1,600
1,600
2,100
6,100
780
780
780
780
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
3.3.2.2 Locomotive
For locomotives, EPA calculated the per-trip emissions from each rail leg of a journey, in
tons, as well as the emissions intensity in grams of pollutant per 100 ton-miles. Locomotive
emission factors used in this analysis are EPA's emission factors for the line-haul fleet average
forecast for the year 2015, as depicted in Table 3-13, in grams of pollutant per gallon of fuel
used.N To apply these factors for CO2, the carbon content of the fuel was taken to be 2,778
g/gal, with 99 percent of the carbon converting to CO2, in accordance with 40 CFR part 600. To
be consistent with the diesel fuel heating value utilized by EERA in their methodology for
locomotives, the energy content of the on-road diesel fuel was taken to be 138,490 Btu/gal, in
accordance with the "low-sulfur diesel" fuel listed in the Department of Energy's GREET model,
version 1.8b.21
Also for consistency with the values used in EERA's analysis, the energy efficiency for
freight transport work for locomotives was taken to be 328 BTU/ton-mile,ฐ This is a top-down
value, derived from national energy consumed, in Btu, by rail freight transport divided by
national cargo delivered, in ton-miles. Although actual energy consumption would vary by cargo
load as well as other trip-specific circumstances such as terrain, the same freight efficiency value
was used for all scenarios in this study.
For each scenario, the number of train cars needed to carry the given cargo load was
calculated, using an assumed train configuration of 100 freight cars carrying 100 tons each. Note
that most Base and EGA case routes include some amount of rail travel. Only Scenarios 9 and 10
are uni-modal in the Base and EGA cases.
To convert the locomotive rate to a cargo-based value in g/ton-mile, the applicable EPA
emission factor was applied to the national average transport efficiency in Btu/ton-mile. These
factors represent our estimate of the emissions intensity for each rail leg of a journey, excluding
transfer points. Based on the above assumptions, the values in the third column of Table 3-13 are
estimated to be the same for all scenarios. Thus, these can be taken as the All-Rail Alternative
route emissions intensity for comparison with the Base Vessel and EGA Vessel emissions
intensity values in Table 3-12, for the sea leg of each journey for each respective pollutant.
Table 3-13 2015 Fleet Average Locomotive Emission Factors
POLLUTANT
NOX
PM2.5
CO2
EPA EMISSION
FACTOR (G/GAL)
129
3.4
10,084
EMISSIONS INTENSITY
(G/100 TON-MILE)
31
0.81
2,400
N US EPA (2009) Emission Factors for Locomotives, EPA-420-F-09-025, available at
www.epa.gov/otaq/locomotives.htm
0 See Table 16 of Appendix 2C, above.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
The following equation shows the method used to calculate the per-trip emissions from
each rail leg of a journey. The resulting emissions estimated from Equation 3-2 are presented in
Tables 3-15, 3-16 and 3-17. For Base and EGA Case Route Emissions, this equation is combined
with Equation 3-1 (Marine Leg Emissions) using Round Trip Miles by Sea and by Rail from
Table 3-11. The Total Alternative Case Route Emissions presented in the three results tables for
Scenarios 1-12 derive from Equation 3-2 using the Alternate distance from Table 3-11.
Equation 3-2 Rail Leg Emissions
Tons of Pollutant per Trip = EF x TE x CL x NT x Distance - EC
Where:
EF = emission factor in g/gallon
TE = average transport efficiency in Btu/ton-mile
CL = cargo load, in tons, of the vessel in the given scenario
NT = Number of trains needed to carry an equivalent vessel load, at 10,000
tons/train
Distance = round trip miles traveled by the locomotive
EC = energy content of ULSD fuel in Btu/gal
3.3.2.3 Gravel Trucks
The emission factors for gravel trucks for the stone scenarios (Scenarios 13-16) used in
this analysis are the highway truck emission rates taken from EPA's MOVES model. A run was
performed for calendar year 2015, to estimate the nationwide fleet average emission rates for
diesel long-haul highway tractor-trailers.1" The resulting emission factors, used in this analysis,
are presented in Table 3-14. As this model produces factors in units of gram of pollutant per
mile driven, no additional adjustments were necessary to apply these rates to the scenarios. The
values in the third column of Table 3-14 are estimated to be the same for all scenarios. Thus,
these can be taken as the Alternative route emissions intensity for Scenarios 13 through 16, for
comparison with the Base Vessel and EGA Vessel emissions intensity values in Table 3-12, for
the sea leg of each journey for each respective pollutant.
For purposes of this study, we only evaluated movement of stone by truck along
distances presented in the source shift analysis in Section 3.1, above. These are radial distances
from the facilities (power plants, sugar processing plant) that are the destinations for Scenarios
13 through 16. As explained in Section 3.2, these are the distances at which a consuming facility
would be indifferent between stone from distant quarries shipped by rail/ship and stone shipped
from local quarries.
p MOVES2010 was run for this analysis. Related software and supporting materials can be found on the Web at
http://www.epa.gov/otaq/models/moves/movesback.htm#moves2010. A newer version, MOVES2010a, is now
available, and can be found at: http://www.epa.gov/otaq/models/moves/index.htm.
3-30
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-14 2015 Fleet Average Truck Emission Factors
POLLUTANT
NOX
PM2.5
CO2
MOVES EMISSION
FACTOR (G/MILE)
9.57
0.247
2,176
EMISSIONS INTENSITY
(G/100 TON-MILE)
22
0.57
5,100
The following equation shows the method used to calculate the per-trip emissions from
each round-trip highway journey. The resulting emissions estimated from Equation 3-3, applying
the Alternate distance from Table 3-11, are presented in Tables 3-19, 3-20 and 3-21, under the
column labeled Truck Emissions from Alternate Quarry. For Base and EGA Case Route Emissions
in those same results tables, Equations 3-1 and 3-2 are combined, as was done with the marine
and locomotive emissions, using Round Trip Miles by Sea and by Rail from Table 3-11.
Equation 3-3 Truck Emissions
Tons of Pollutant per Trip = EF x NT * Distance x CF
Where:
EF = emission factor in g/mile
NT = Number of trucks needed to carry an equivalent vessel load, at 43 tons per
truck
Distance = round trip miles traveled by the truck
CF = conversion factors
3.3.3 Results
This section presents the results of EPA's emissions analysis for each of the 16 scenarios
in this study. First the results for Scenarios 1 through 12 are presented, comparing estimated
emissions for each of the multimodal Base and EGA cases and all-rail cases modeled by EERA
under the mode shift analysis. Following that, the results for Scenarios 13 to 16 are presented,
comparing estimated emissions for the Base and EGA cases modeled by EERA and the
alternative highway truck case from EPA's source shift analysis in Section 3.1.
Since each scenario is designed using different vessels, cargo loadings, and voyage leg
distances, it is not recommended to compare results between scenarios. The per-trip emissions
vary by one to two orders of magnitude between scenarios, depending on the pollutant.
As mentioned above, this emissions analysis presents results using estimated 2015 fleet
average emission rates. The phase-in of current EPA regulations will cause a greater disparity
between ship emissions and those of land-based alternatives farther into the future. The most
stringent tier of EPA's current NOx and PM regulations for locomotives becomes effective in
2015. Therefore, turnover is expected to bring down the fleet average locomotive emissions
rates well beyond 2015. Similarly, EPA's current NOx and PM regulations for highway trucks
beginning in model year 2010 have not penetrated the fleet extensively, thus the truck fleet
3-31
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
average emission rates are also expected to continue to decrease beyond 2015. Both of these
fleets have a faster turnover rate than that of the Great Lakes fleet. Therefore where the results
below indicate emissions increases in the event of mode shift, the magnitude of any such
increase is likely to diminish in the future, and any emissions benefits from a shift would be
likely to improve beyond those shown.
3.3.3.1 Emissions per Ton Mile
As described above and shown in Tables 3-12, 3-13 and 3-14, EPA calculated the
emissions intensity of each transportation mode individually for comparison purposes. Because
we held the characteristics of the land-based transportation modes constant, only the emissions
intensity of the vessels varies across the scenarios. Table 3-15 summarizes the information from
the three previous tables. The values shown are for a single-mode leg of a journey, not a
complete O/D route. From this summary, it can be seen that both the locomotive and truck NOx
emissions intensities fall near the low end of the range of emissions intensities of the modeled
hypothetical ships (See Table 3-11). The estimated CO2 emissions intensities of the land-based
modes fall near the high end of the range of emissions intensities of the ships. The lower bound
of the PM emissions intensity of the Base ship falls above both other modes, while the lower
bound of the PM emissions intensity of the EGA ship falls below both other modes. The high
end of the Base and EGA ship PM emissions intensity falls above that of both other modes.
Therefore, from an emissions perspective, the transport efficiency of a ship compared to land-
based modes depends greatly on the vessel conditions.
Table 3-15 Comparison of Emissions Intensity (g/100 ton-miles)
POLLUTANT
NOX
PM2.5
C02
BASE SHIP
(MIN - MAX)
17- 130
1.2-9.6
820 - 6,400
ECA SHIP
(MIN - MAX)
15- 120
0.21-1.6
780-6,100
LOCOMOTIVE
31
0.81
2,400
TRUCK
22
0.57
5,100
3.3.3.2 Trip Emissions for Coal, Iron Ore and Grain
Estimated emissions of NOx, PM2.5 and CO2 (in short tons) are presented in Table 3-16,
Table 3-17, and Table 3-18, respectively, for a single round trip for each scenario moving coal,
iron ore and grain. In the tables that follow, the last column on the right indicates the percent
change in emissions from the ECA case to the emissions that would occur if the commodity for
that trip were moved only using the rail mode between the specific origin and destination.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-16 NOX Emissions Results for Coal, Iron Ore and Grain (short tons)
Scenario
1
2
3
4
5
6
7
8
9
10
11
12
Cargo
Coal
Iron
Ore
Grain
Number
Trains per
Marine
Trip
1.0
1.2
4.9
2.8
1.2
1.5
4.9
4.9
1.5
1.5
1.2
0.4
Base Case
Total
Emissions
Per Trip
9.3
a
180
70
1.9
21
32
35
20
20
12
2.1
EGA Case
Total
Emissions
Per Trip
9.1
a
180
69
1.8
19
31
33
18
18
11
2.0
All-Rail
Total
Emissions
Per Trip
9.3
a
260
89
1.9
N/A
91
140
19
26
9.0
0.3
Percent
change
from Base
to EGA
-1.4%
a
-0.8%
-1.6%
-7.2%
-6.8%
-4.9%
-4.4%
-8.0%
-8.0%
-7.7%
-8.0%
Percent
change from
EGA to
Alternative
1.4%
a
42%
30%
10%
N/A
190%
330%
4.2%
43%
-16%
-87%
Note:
" Results are inconclusive due to mis-specification of the scenario.
Table 3-17 PM2.5 Emissions Results for Coal, Iron Ore and Grain (short tons)
Scenario
1
2
3
4
5
6
7
8
9
10
11
12
Cargo
Coal
Iron
Ore
Grain
Number
Trains per
Marine
Trip
1.0
1.2
4.9
2.8
1.2
1.5
4.9
4.9
1.5
1.5
1.2
0.4
Base Case
Total
Emissions
Per Trip
0.32
a
5.6
2.5
0.13
1.4
1.8
1.8
1.5
1.5
0.83
0.16
EGA Case
Total
Emissions
Per Trip
0.22
a
4.6
1.7
0.03
0.30
0.58
0.65
0.25
0.25
0.15
0.03
All-Rail
Total
Emissions
Per Trip
0.24
a
6.8
2.4
0.05
N/A
2.4
3.8
0.50
0.69
0.24
0.01
Percent
change
from Base
to EGA
-31%
a
-19%
-34%
-80%
-78%
-67%
-64%
-83%
-83%
-82%
-83%
Percent
change from
EGA to
Alternative
10%
a
49%
43%
95%
N/A
310%
480%
100%
180%
58%
-74%
Note:
" Results are inconclusive due to mis-specification of the scenario.
3-33
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-18 CO2 Emissions Results for Coal, Iron Ore and Grain (short tons)
Scenario
1
2
3
4
5
6
7
8
9
10
11
12
Cargo
Coal
Iron
Ore
Grain
Number
Trains per
Marine
Trip
1.0
1.2
4.9
2.8
1.2
1.5
4.9
4.9
1.5
1.5
1.2
0.4
Base Case
Total
Emissions
Per Trip
680
a
13,800
5,100
100
1,100
2,000
2,200
970
980
580
110
ECA Case
Total
Emissions
Per Trip
670
a
13,700
5,000
90
1,100
1,900
2,100
930
930
550
100
All-Rail
Total
Emissions
Per Trip
720
a
20,200
7,000
150
N/A
7,100
11,200
1,490
2,060
700
20
Percent
change
from Base
to ECA
-0.6%
a
-0.3%
-0.6%
-4.1%
-3.7%
-2.3%
-2.0%
-4.8%
-4.8%
-4.5%
-4.7%
Percent
change from
ECA to
Alternative
7.0%
a
47%
39%
61%
N/A
270%
430%
61%
120%
27%
-79%
Note:
" Results are inconclusive due to mis-specification of the scenario.
As shown in the three tables above, per-trip emissions decrease for each scenario from
the Base to ECA case, ranging from about one to eight percent decrease for NOx, from about 20
to 80 percent for PM2.s, and from less than one to about 5 percent for CO2. This clearly
demonstrates that the use of EGA-compliant fuel on the Great Lakes will provide a dramatic
decrease in emissions from ships. While the decrease for each scenario is calculated through the
use of the vessel emissions factors presented above in Table 3-10, the ranges of expected
emissions decrease reflect the varying amount of rail travel embedded in each scenario's design.
As noted above, Scenarios 9 and 10 are uni-modal in the Base and ECA cases (no rail travel),
and both show the same 4.8 percent decrease from the Base to the ECA case. With respect to the
emissions from the alternative shipping mode - all-rail - the results also indicate that, were mode
shift to occur, some emissions could increase while others could decrease. As shown in Table
3-16, NOx could increase under a shift to all-rail transport for all scenarios except Scenarios 11
and 12. PM2.5 and CO2 would also be likely to increase were a mode shift to rail occur, although
Scenario 12 indicates those emissions could decrease. In Scenario 12 the cargo load is very
small, reducing the marine advantage. No results are presented for Scenario 2; see explanation
in Chapter 2.
Select parameters are presented in Table 3-19 for Scenarios 5 and 12, to help illustrate
why the emissions could increase in Scenario 5 if there were mode shift to rail, but could
improve if there were mode shift in Scenario 12. In Scenario 5, the scenario design stated that
the hypothetical ship is loaded to 65 percent capacity. By contrast, in Scenario 12, the
hypothetical ship is loaded to 22 percent capacity (due to draft restrictions along the route). For
a second point of comparison, the ratio of cargo load to engine power (tons/hp) in Scenario 5 is
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
1.63, while that ratio is 0.56 in Scenario 12. These scenario parameters contribute to the
predicted opposing emissions results if a mode shift were to occur.
Table 3-19 Scenarios 5 and 12 Vessel Characteristics
PARAMTER
Loaded % of Ship's Capacity
Ratio of Cargo Load to Engine Power (tons/hp)
SCENARIO 5
65%
1.63
SCENARIO 12
22%
0.56
3.3.3.3 Trip Emissions for Stone
Estimated emissions of NOx, PM2.s and CC>2 (in short tons) for the four crushed stone
scenarios are presented in Table 3-20, Table 3-21, and Table 3-22, respectively, for a single
round trip. For those Base and EGA cases that include a rail segment, the number of trains
needed to carry the given cargo load was calculated, using an assumed train configuration of 100
freight cars carrying 100 tons each. For the alternate case using trucks, the number of trucks
needed to carry the cargo load was estimated assuming each truck pulled a trailer carrying 43
short tons of stone.
In the tables that follow, the last column on the right indicates the percent change in
emissions from the EGA case to the emissions that would occur if the stone were sourced by an
alternate quarry located at the distance from the customer (route destination) described in Section
3.1.4, above, and presented as a round-trip distance in Table 3-11.
Table 3-20 NOX Emissions Results for Stone (short tons)
Scenario
13
14
15
16
Number
Trains
(Trucks) per
Marine Trip
4.2 (974)
4.2 (974)
4.2 (974)
4.2 (974)
Base Case
Total
Emissions
Per Trip
36.3
35.7
36.8
19.7
EGA Case
Total
Emissions
Per Trip
35.9
35.3
36.3
19.1
Truck
Emissions
from Alternate
Quarry
5.0
4.1
5.5
3.0
Percent
change
from Base
to EGA
-1.2%
-1.1%
-1.6%
-2.7%
Percent
change from
EGA to
Alternative
-86%
-88%
-85%
-84%
Table 3-21 PM25 Emissions Results for Stone (short tons)
Scenario
13
14
15
16
Number
Trains
(Trucks) per
Marine Trip
4.2 (974)
4.2 (974)
4.2 (974)
4.2 (974)
Base Case
Total
Emissions
Per Trip
1.22
1.18
1.32
0.83
EGA Case
Total
Emissions
Per Trip
0.88
0.87
0.87
0.43
Truck
Emissions
from Alternate
Quarry
0.13
0.10
0.14
0.08
Percent
change
from Base
to EGA
-28%
-26%
-34%
-49%
Percent
change from
EGA to
Alternative
-85%
-88%
-84%
-82%
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
Table 3-22 CO2 Emissions Results for Stone (short tons)
Scenario
13
14
15
16
Number
Trains
(Trucks) per
Marine Trip
4.2 (974)
4.2 (974)
4.2 (974)
4.2 (974)
Base Case
Total
Emissions
Per Trip
2,680
2,650
2,670
1,340
EGA Case
Total
Emissions
Per Trip
2,660
2,630
2,650
1,330
Truck
Emissions
from Alternate
Quarry
1,130
930
1,250
690
Percent
change
from Base
to EGA
-0.5%
-0.4%
-0.6%
-1.2%
Percent
change from
EGA to
Alternative
-58%
-65%
-53%
-48%
As shown in these three tables, emissions decrease for each scenario from the Base to
EGA case, ranging from about one to three percent decrease for NOx, from about 25 to 50
percent for PM2.5, and up to about one percent for CC>2. This means that the use of EGA-
compliant fuel is good for the environment, especially for reducing PM emissions. While the
decrease occurs through the use of the vessel emission factors presented above in Table 3-10, the
ranges reflect the varying amount of sea and rail travel embedded in each scenario's design.
The all-truck alternative scenario results shown above indicate that, were a source shift
for these four crushed stone scenarios to occur, trip emissions could decrease. Today's highway
trucks use fuel with 15 ppm sulfur, less than two percent of the sulfur in EGA-compliant fuel.
This enables trucks to have significantly lower PM emissions than ships. As shown above,
estimated per trip NOx and PM2.5 emissions associated with truck transportation of locally-
quarried stone could decrease by nearly 90 percent, and per-trip CO2 could decrease by 50 to 65
percent, compared to stone transported by ship from northern Michigan. It should be noted,
however, that this analysis does not take into account the impacts of potential road congestion in
these areas. Logistically it may be infeasible for local roadways to accommodate the increased
truck traffic. Further, emissions from auxiliary engines and other material handling equipment,
which are also not considered, may be greater for the alternate truck scenario routes than for the
default marine scenario routes.
3.3.4 Key Findings
The analyses presented above and in Chapter 2 show that transportation mode shift,
source shift, and production shift are not expected for the at-risk routes examined. The emission
analysis presented in this section shows that, for the 12 All-Rail Alternative scenarios, the use of
1,000 ppm sulfur fuel on ships is better for the environment than rail transportation for all cases
except Scenario 12 with respect to PM and CO2 and Scenarios 11 and 12 with respect to NOx.
For the four crushed stone scenarios (Scenarios 13-16), while switching to stone produced in
local quarries and transported by truck may reduce direct transportation emissions, other
environmental aspects of such a source shift (e.g., road congestion, mining emissions) are not
evaluated.
3-36
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
1 U.S. Geological Survey Minerals Yearbook, 2008. March 2010. See
http://minerals.usgs.gov/minerals/pubs/commoditv/stone crushed/stat/. accessed September, 2010.
2 U.S. Geological Survey Minerals Yearbook, 2008. March 2010. See
http://minerals.usgs.gov/minerals/pubs/commoditv/stone crushed/stat/. accessed September, 2010.
3 U.S. Geological Survey Minerals Yearbook, 2008. March 2010. See
http://minerals.usgs.gov/minerals/pubs/commoditv/stone crushed/stat/. accessed September, 2010.
4 U.S. Geological Survey Minerals Yearbook, 2008. March 2010. See
http://minerals.usgs.gov/minerals/pubs/commoditv/stone crushed/myb 1-2008-stonc.pdf. accessed September, 2010.
5 U.S. Geological Survey Minerals Yearbook, 2008. March 2010. See
http://minerals.usgs.gov/minerals/pubs/commoditv/stone crushed/myb 1-2008-stonc.pdf. accessed September, 2010.
6 Comments of the Great Lakes Maritime Task Force. EPA-HQ-OAR-2007-0121-0269.
7 English, Gordon, et al. Study of Potential Mode Shift Associated with EGA Regulations in the Great Lakes.
Prepared for the Canadian Shipowners' Association by Research and Traffic Group. August, 2009.
Stone/Aggregate Assessment is Section 7. Available at www.regulations.gov under Docket ID No. EPA-HQ-OAR-
2007-0121-0027. or at http://www.shipowners.ca/uploads/Documents/MODE%20SHIFT%20STUDY.pdf.
8 English, Gordon, et al. Study of Potential Mode Shift Associated with EGA Regulations in the Great Lakes.
Prepared for the Canadian Shipowners' Association by Research and Traffic Group. August, 2009. See OAR-2007-
0121-0027. Page 22.
9 Draft Regulatory Impact Analysis, Proposed Rulemaking to Establish Greenhouse Gas Emissions Standards and
Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, EPA-420-D-10-901, Figure 9-1,
October 2010.
10 U.S. Geological Survey 2008. 2008 Minerals Yearbook, Stone, Crushed (Advanced Release), March 2010. Table
4.
11 EIA, "Electricity Power Monthly," Jan 2010. DOE/EIA-0226 (2010/01).
http://tonto.eia.doe.gov/ftproot/electricity/epm/02261001.pdf & EIA, "Coal Prices and Outlook." 2010.
12 See http://minerals.usgs.gov/minerals/pubs/commodity/iron_ore/mybl-2008-feore.pdf
13 Great Lakes St. Lawrence Seaway Study. Final Report. Transport Canada, U.S. Army Corps of Engineers, U.S.
Department of Transportation, The St. Lawrence Seaway Management Corporation, St. Lawrence Seaway
Development Corporation, Environment Canada, and U.S. Fish and Wildlife Service. Fall 2007, p 39. A copy of
this study can be found at http://www.marad.dot.gov/documents/GLSLs_finalreport_Fall_2007.pdf.
14 See
http://www.steel.org/AM/Template.cfm?Section=Home&TEMPLATE=/CM/HTMLDisplav.cfm&CONTENTID=3
6529. accessed September 28, 2010.
15 See http://www.glc.org/docs/liqasset/liqasset.html. http://www.great-lakes.net/econ/busdev/manf.html. accessed
September 28, 2010.
16 See http://www.glc.org/docs/liqasset/liqasset.html. accessed September 28, 2010.
17 See http://wwwl.eere.energy.gov/vehiclesandfuels/facts/2008_fotw539.html
18 See http://www.ussteel.com/corp/investors/presentations/Morgan-Stanley-presentation-Feb-25-2010.pdf,
accessed September 28, 2010.
19 This discussion is taken from: Memorandum to Docket EPA-HQ-OAR-2007-0121. Control of Emissions from
New Marine Compression-Ignition Engines at or above 30 Liters per Cylinder - Information in Support of Applying
Emission Control Area (EGA) Requirements to the Great Lakes Region. Michael J. Samulski. December 15, 2009.
20 Power Plant Engineering (1995) L.F. Drbal et al, Black & Veatch, Chapter 5: Coal and Limestone Handling.
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Chapter 3 Potential for Other Transportation Shifts and Emissions Impacts
21 U.S. Department of Energy, Argonne National Laboratory, Transportation Technology R & D Center (2008).
Greenhouse gases, Regulated Emissions and Energy use in Transportation (GREET) Model, Version 1.8b, available
a/http://www.transportation.anl.gov/publications/transforum/v8/v8n2/greet_18b.html.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
CHAPTER 4: Emission Inventory for the U.S. Great
Lakes
Like all of EPA's mobile source programs, our Coordinated Strategy for Category 3
marine diesel engines and their fuels applies equally throughout the United States. While we
typically do not estimate the benefits and costs of our mobile source programs on a regional
basis, our final 2010 Category 3 marine rule contained information with respect to the impacts of
emissions from Category 3 vessels on human health and the environment in a number of U.S.
regions, including the Great Lakes region.1 This chapter reproduces and expands on that
information, demonstrating that Category 3 marine diesel engines and their fuels are significant
contributors to air quality in the Great Lakes region. Additionally, in Chapters 5 and 6, we show
that the application of EGA requirements to this area will improve air quality and human health
at a reasonable cost.
4.1 Introduction
This chapter presents our estimated air emission inventories for C3 ships that operate in
the U.S. Great Lakes. This chapter is organized into three parts. First, we describe the domain
of ships included in the analysis. Second, we describe the modeling methodology. Third, we
present the results of this modeling, for the baseline inventory year of 2002 as well as the
baseline and control scenarios for 2020.
The U.S. emissions inventory presented in this section includes marine vessels of all flags
with Category 3 engines. Emissions from both propulsion and auxiliary engines on these vessels
are included, as well as emissions from vessels powered by steam boilers and gas turbine
engines. The emission inventories are a combination of estimates for emissions in port and
underway (or interport). Great Lakes inventories include only emissions from Category 3
vessels operated within the U.S. boundaries of the Great Lakes.
Using the methodology described below, the estimated ship emission inventories in the
Great Lakes for 2020 are as set out in Table 4-1. Inventories for both the reference (baseline)
and the control scenarios are presented. EGA designation is expected to reduce emissions of
NOx, SC>2, and PM by 17 percent, 97 percent, and 87 percent, respectively, in 2020.
Table 4-1 C3 Emission Inventories for the U.S. Great Lakes in 2020
EMISSION TYPE
Reference
Control
Delta Emissions
Delta Emissions (%)
ANNUAL EMISSIONS (METRIC TONNES)a'b
NOX
19,842
16,420
-3, 422
-17%
PM10
1,613
207
-1,406
-87%
PM25C
1,484
190
-1,294
-87%
HC
682
676
0
0%
CO
1,607
1,602
0
0%
SO2
11,993
420
-11,574
-97%
CO2
740,624
704,390
-36,235
-5%
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-2 presents the Great Lakes inventories alongside the national C3 marine emission
inventories.A Roughly 1.5 percent of nationwide emissions of these pollutants occur within the
U.S. portion of the Great Lakes in 2020 and 1.1 percent in 2030. The fuel controls are expected
to reduce PM and SOx emissions by a considerable amount both nationally and on the Great
Lakes, by about 85 percent and 95 percent, respectively. ForNOx, national emissions are
expected to decrease by 30 percent in 2020 and by 57 percent in 2030. Expected NOx emission
reductions are not expected to be as high for the Great Lakes due to differences in the fleet age
distribution and turnover rates. Within the U.S. portion of the Great Lakes, NOx is expected to
be reduced by 17 percent in 2020 and by 27 percent in 2030. The inventory estimates presented
in Table 4-2 were used in the air quality and benefits analysis prepared for the Category 3 rule;
the Great Lakes impacts are presented in Chapter 5. Note that distillate fuel has higher energy
content, on a mass basis, than residual fuel which leads to lower fuel consumption estimates in
the control case.
Table 4-2 U.S. and Great Lakes ECA Emission Inventory [metric tons]
POLLUTANT
[METRIC TONNES]
GREAT
LAKES
2020
GREAT
LAKES
2030
NATIONAL
2020
NATIONAL
2030
NOX
NOX emissions without ECA
NOX emissions with ECA
NOX reductions
19,842
16,420
3,422
22,471
16,369
6,102
1,234,879
863,642
371,237
1,867,484
796,140
1,071,344
Direct PM2 5
PM2 5 emissions without ECA
PM2 5 emissions with ECA
PM25 reductions
1,484
190
1,294
1,757
233
1,524
100,128
14,750
85,378
152,016
22,495
129,521
S02
SO2 emissions without ECA
SO2 emissions with ECA
SO2 reductions
11,993
420
11,574
14,196
501
13,694
841,447
46,168
795,279
1,279,185
70,630
1,208,555
Fuel Consumption
Fuel consumed without ECA
Fuel consumed with ECA
232,681
221,297
275,412
261,933
15,790,179
15,009,910
24,005,856
22,838,278
4.2 Description of Ships Included in the Analysis
The remainder of this chapter describes how the Great Lakes emission inventories were
estimated and provides detailed information for the Great Lakes. The methodology used here is
substantially similar to the methodology used to estimate the national emission inventories.
A The emission inventories set out in Table 4-2 do not include emissions from Jones Act vessels. Section 4.6 of this
chapter describes an adjustment made to estimate the inventories including Great Lakes Jones Act shipping; the
adjusted Great Lakes inventories are about 3 percent of the national inventories for these pollutants. The estimated
inventory reduction as a result of the ECA controls is the same because the adjustment is applied to both the
reference and control inventories.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Readers who are interested in the detailed data inputs for the national inventory should refer to
the analysis performed for our 2010 Category 3 marine rule.B
The ship inventories reported in this chapter are for vessels with Category 3 propulsion
engines. These are the ships that are most likely to be affected by the MARPOL Annex VI fuel
sulfur limits since these vessels tend to use residual fuel. While smaller vessels could be affected
by the EGA fuel requirements, the majority of these smaller vessels are already subject to
comparable U.S. marine diesel engine and fuel requirements under the CAA. Therefore,
switching to a lower sulfur diesel fuel to meet the EGA requirements is not expected to impose a
significant burden on the owners of smaller vessels.
The ship emission inventories are based on the U.S. Army Corps of Engineers (USAGE)
foreign traffic entrances and clearances data set. This data is derived from U.S. Customs Vessels
Entrances and Clearances data, in which the following vessels are required to file a Vessel
Entrance or Clearance Statement.
Any vessel from a foreign port or place;
Any foreign vessel from a domestic port;
Any vessel of the United States arriving from another U.S. port and having
merchandise on board being transported in bond (this does not include bonded
ship's stores or supplies), or transporting unentered foreign merchandise; or
Any vessel, either U.S. or foreign, which has visited a hovering vessel (19 USC
1401(k)), or has delivered or received merchandise or passengers outside of U.S.
waters.
The Entrances and Clearances data sets cover only foreign cargo movements. As a result,
U.S./domestic ships operating solely within the continental United States (i.e., Jones Act ships)
are not included. A portion of the Jones Act traffic is thought to be on ships with Category 2
propulsion engines or tug/barge combination vessels, and these smaller ships are already subject
to U.S. marine diesel engine requirements, and the sulfur content of fuel available in the U.S.
ports in which they operate, is also subject to federal controls. Estimated inventory adjustments
to account for Jones Act shipping by Category 3 vessels are provided in Section 4.6.
4.3 Inventory Methodology
The inventory consists of two parts: port emissions and interport emissions.
Port emissions in the Great Lakes include emissions during maneuvering and
hoteling near the port center, emissions in the Reduced Speed Zone (RSZ) while
nearing the port, and cruise emissions up to a seven mile radius outside of the
RSZ. Port inventories were developed for 28 Great Lakes ports. Port-specific
emissions were estimated using a "bottom-up" approach based on port-specific
vessel calls, emission factors, and activity for each port. For all other ports,
estimates from the STEEM model are used.
B "Regulatory Impact Analysis: Control of Emissions of Air Pollution from Category 3 Marine Diesel Engines,'
EPA-420-R-09-019, December 2009.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Interport emissions consist of emissions that occur outside of the port but within
the inventory domain. These inventories were obtained using the Waterway
Network Ship Traffic, Energy and Environment Model (STEEM). STEEM also
uses a "bottom-up" approach, estimating emissions from C3 vessels using
historical shipping activity, ship characteristics, and activity-based emission
factors. STEEM was used to quantify and geographically (i.e., spatially)
represent interport vessel traffic and emissions for vessels traveling within the
U.S. portion of the Great Lakes.
The regional emission inventories produced by the current STEEM interport model are
most accurate for vessels while cruising in open waters; however, the near port inventories use
more detailed local port information and are significantly more accurate near the ports.
Therefore, to obtain the most accurate inventories, the inventories in this analysis were derived
by merging together: 1) the port inventories, which extend seven nautical miles from the port
entrance, and 2) the remaining interport portion of the STEEM inventory, which extends from
the endpoint of the near port inventories to include the rest of the U.S. portion of the Great
Lakes.
Merging these inventories requires spatially allocating the port emissions, removing the
data for the 28 Great Lakes ports from the STEEM inventory, and replacing it with the detailed
port inventories. The STEEM port data was retained for all other Great Lakes ports. The result
of this process was a complete, spatially allocated inventory covering the entire inventory
domain. Near some ports, a portion of the underlying STEEM emissions were retained if it was
determined that the STEEM emissions included ships traversing the area near a port, but not
actually entering or exiting the port.
The above methodology was used to develop inventories for a base year of 2002. Next,
baseline and control inventories were developed for the entire inventory domain for 2020. The
baseline inventories for 2020 were estimated by applying a growth rate and emission adjustment
factors to the 2002 inventories. The emission adjustment factors account for emission controls
that will be in effect in 2020, including the MARPOL Annex VI Tier I and Tier IINOX
standards for new engines and the Regulation 13 NOx retrofit program. The control inventories
for 2020 were estimated by applying the same growth rate as the 2020 baseline case but a
different set of emission adjustment factors that also account for the EGA engine and fuel sulfur
controls. The result of this process was a complete, spatially allocated inventory for 2020
covering the entire inventory domain, for both the baseline and control scenarios.
Finally, the inventories for the EGA in the 2020 baseline and control scenarios were
developed by totaling the emissions within the EGA boundaries. Inventories are presented for
the following pollutants: NOX, PM2.5, PMio, SO2, HC, CO, and CO2. The PM inventories
include directly emitted PM only.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
4.4 Development of 2002 Emission Inventories
The total inventories for 2002 are the total of port and interport emission inventories
described in this section. The result is a spatially allocated emission inventory for the entire
domain.
4.4.1 Port Emissions
Port emissions are estimated for different modes of operation and then summed.
Emissions for each operating mode are estimated using port-specific information for vessel calls,
vessel characteristics, vessel activity, as well as other inputs that vary by vessel or engine type
(e.g., emission factors). The methodology and port inventory development was conducted under
contract; details of the methodology as applied to the U.S. ports is described in the contractor
report.2
4.4.1.1 Great Lakes Ports Modeled
The 28 port inventories for the Great Lakes are an improvement upon STEEM's port
results in several ways. First, the precision associated with STEEM's use of ship positioning
data may be less accurate in some locations, especially as the shipping lanes approach shorelines
where ships would need to follow more prescribed paths. Second, the STEEM model includes a
maneuvering operational mode (i.e., reduced speed) that is generally assumed to occur within a
20 kilometer radius of each port. In reality, the distance when a ship is traveling at reduced
speeds varies by port. Also, the distance a ship traverses at reduced speeds often consists of two
operational modes: a reduced speed zone (RSZ) as a ship enters or leaves the port area and
actual maneuvering at a very low speed near the dock. Third, the STEEM model assumes that
the maneuvering distance occurs at an engine load of 20 percent, which represents a vessel speed
of approximately 60 percent of cruise speed. This is considerably faster than ships would
maneuver near the docks. The single maneuvering speed assumed by STEEM also does not
reflect the fact that the reduced speed zone, and therefore emissions, may vary by port. Finally,
the STEEM model does not include the emissions from auxiliary engines during hoteling
operations at the port. The new-port inventories correct these issues.
Port emissions were estimated for the Great Lakes ports listed in Table 4-3. The 28 Great
Lakes ports were chosen because of the availability of call data from the USAGE Entrance and
Clearance data.3 The port coordinates are provided in Appendix 4A.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-3 Modeled Ports
GREAT LAKES PORTS
Alpena, MI
Buffalo, NY
Burns Waterway,
Calcite, MI
Cleveland, OH
Dolomite, MI
Erie, PA
Escanaba, MI
Fairport, OH
Gary, IN
Lorain, OH
Marblehead, OH
Milwaukee, WI
Muskegon, MI
IN
Presque Isle, MI
St Clair, MI
Stoneport, MI
Two Harbors, MN
Ashtabula, OH
Chicago, IL
Conneaut, OH
Detroit, MI
Duluth-Superior, MN&WI
Indiana, IN
Inland Harbor, MI
Manistee, MI
Sandusky, OH
Toledo, OH
As stated previously, for all other Great Lakes ports, emissions inventories estimated by
the STEEM model were used.
4.4.1.2 Port Inventory Methodology
Emissions for each port were estimated using a bottom-up approach based on the number
of vessel calls and vessel characteristics. Emissions are estimated for four modes of operation:
Hoteling: Hoteling, or dwelling, occurs while the vessel is docked or anchored
near a dock, and only the auxiliary engine(s) are being used to provide power to
meet the ship's energy needs.
Maneuvering: Maneuvering occurs within a very short distance of the docks.
Reduced speed zone (RSZ): The RSZ varies from port to port, though generally
the RSZ would begin and end when the pilots board or disembark, and typically
occur when the port shipping lanes reach unconstrained shipping lanes. For the
purpose of this inventory, the RSZ is fixed at three nautical miles for each of the
28 Great Lakes ports modeled.
Cruise: The cruise mode emissions in the ports analysis extend seven nautical
miles beyond the end of the RSZ lanes.
Emissions are calculated separately for propulsion and auxiliary engines.
The basic equation used to estimate emissions for an engine at each mode is shown
below.
Equation 4-1
Emissions moAe[eng] = (calls) x (P[eng])x (hrs Icall moj x (LFmode[eng]) x (EF[eng])x (Adj) x (1(T6 tonnes I g)
Where:
- Emissionsmode [eng] = Metric tonnes emitted by mode and engine type
Calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
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Chapter 4 Emission Inventory for the U.S. Great Lakes
P[eng] = Total engine power by engine type, in kilowatts
- hrs/callmode = Hours per call by mode
- LFmode [eng] = Load factor by mode and engine type (unitless)
EF[eng] = Emission factor by engine type for the pollutant of interest, in g/kW-hr
(these vary as a function of engine type and fuel used, rather than activity mode)
- Adj = Low load adjustment factor, unitless (used when the load factor is below
0.20)
10"6 = Conversion factor from grams to metric tonnes
4.4.1.3 Data Inputs for Port Emission Inventories
The following inputs are required to estimate emissions inventories for each vessel at the
four modes of operation (cruise, RSZ, maneuvering, and hoteling); these inputs are described in
more detail below.
Number of calls and ship characteristics (main engine power, cruise speed, and load
factors)
Cruise distance
RSZ distances and speeds for each port
Auxiliary engine power and load factors
Main emission factors
Auxiliary emission factors
Low load adjustment factors for main engines
Maneuvering time-in-mode (hours/call)
Hoteling time-in-mode (hours/call)
Number of Calls and Ship Characteristics (main engine power, cruise speed, and load
factors)
For this analysis, USAGE entrance and clearance data for 2002,4 together with Lloyd's
Register-Fairplay Ltd. data for ship characteristics,5 were used to identify average ship
characteristics and calls by ship type for each port. Information for number of calls, propulsion
engine power, and cruise speed were obtained from these data.
The records from the USAGE Entrances and Clearances database were matched with
Lloyd's data on ship characteristics for each port. Calls by vessels that have either Category 1 or
2 propulsion engines were eliminated from the data set. This was accomplished by matching all
ship calls with information from Lloyd's data. Over 99.9 percent of the calls in the Entrances
and Clearances data were directly matched with Lloyd's data. The remaining 0.1 percent was
estimated based upon ships of similar type and size. Engine category was determined from
engine make and model. Engine bore and stroke were found in the Marine Engine 2005 Guide6
and displacement per cylinder was calculated. Ships with main propulsion engines with per
cylinder displacement less than 30 liters were eliminated from the data set. Passenger ships and
tankers that have either diesel-electric or gas turbine-electric engines used for both propulsion
and auxiliary purposes were retained in the data set as they are subject to the EGA requirements.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
The dataset for vessels with Category 3 propulsion engines was then binned by ship type,
engine type, and dead weight tonnage (DWT) range. The number of entrances and clearances in
each bin were counted, summed together and divided by two to determine the number of calls
(i.e., one entrance and one clearance was considered a call). Propulsion power and vessel cruise
speed are also averaged for each bin.
Main engine load factors were calculated directly from the propeller curve based upon
the cube of actual speed divided by maximum speed (at 100% maximum continuous rating
[MCR]). In addition, cruise mode activity is based on cruise distance and speed inputs.
Appendix 4B provides the specific equations used to calculate propulsion and auxiliary
emissions for each activity mode. Note that load factors for main engines are not listed
explicitly, since they are calculated as a function of mode and/or cruise speed.
Cruise Distance
Cruise mode emissions were calculated for the Great Lakes ports assuming a seven
nautical mile distance into and out of the port outside of the reduced speed and maneuvering
zones.
RSZ Distances and Speeds by Port
The RSZ for each Great Lake port was fixed at three nautical miles. The RSZ speeds for
the Great Lake ports vary by vessel type and are the average of the vessel service speed and the
maneuvering speed.
Auxiliary Engine Power and Load Factors
Hoteling emissions are a significant part of port emission inventories, and it is important
to distinguish propulsion engine emissions from auxiliary engine emissions when estimating ship
emissions. This is because hoteling emissions are generally generated by auxiliary engines.
In the methodology used in this analysis, auxiliary engine maximum continuous rating
power and load factors were calculated separately from propulsion engines and different
emission factors (EFs) applied. All auxiliary engines were treated as Category 2 medium-speed
diesel (MSD) engines for purposes of this analysis.
Auxiliary engine power is not contained in the USAGE database and is only sparsely
populated in the Lloyd's database; as a result, it must be estimated. The approach taken was to
derive ratios of average auxiliary engine power to propulsion power based on survey data. The
California Air Resources Board (ARE) conducted an Oceangoing Ship Survey of 327 ships in
January 2005 that was principally used for this analysis.7 Average auxiliary engine power to
propulsion power ratios were estimated by ship type and are presented in Table 4-4. These ratios
by ship type were applied to the propulsion power data to derive auxiliary power for the ship
types at each port.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-4 Auxiliary Engine Power Ratios (ARE Survey, except as noted)
SHIP TYPE
Auto Carrier
Bulk Carrier
Container Ship
Passenger Ship3
General Cargo
Miscellaneous13
RORO
Reefer
Tanker
AVERAGE
PROPULSION
ENGINE (kW)
10,700
8,000
30,900
39,600
9,300
6,250
11,000
9,600
9,400
Average Auxiliary Engines
NUMBER
2.9
2.9
3.6
4.7
2.9
2.9
2.9
4.0
2.7
POWER
EACH
(kW)
983
612
1,889
2,340
612
580
983
975
735
TOTAL
POWER
(kW)
2,850
1,776
6,800
11,000
1,776
1,680
2,850
3,900
1,985
ENGINE
SPEED
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Medium
AUXILIARY TO
PROPULSION
RATIO
0.266
0.222
0.220
0.278
0.191
0.269
0.259
0.406
0.211
Notes:
a Many passenger ships typically use a different engine configuration known as diesel-electric. These vessels use
large generator sets for both propulsion and ship-board electricity. The figures for passenger ships above are
estimates taken from the Starcrest Vessel Boarding Program.
b Miscellaneous ship types were not provided in the ARE methodology, so values from the Starcrest Vessel
Boarding Program were used.
Auxiliary engine to propulsion engine power ratios vary by ship type and operating mode
from approximately 0.19 to 0.40. Auxiliary load, shown in Table 4-5, is used together with the
total auxiliary engine power to calculate auxiliary engine emissions. Starcrest's Vessel Boarding
Program8 showed that auxiliary engines are on all of the time, except when using shoreside
power during hoteling.
Table 4-5 Auxiliary Engine Load Factor Assumptions
SHIP TYPE
Auto Carrier
Bulk Carrier
Container Ship
Passenger Ship
General Cargo
Miscellaneous
RORO
Reefer
Tanker
CRUISE
0.13
0.17
0.13
0.80
0.17
0.17
0.15
0.20
0.13
RSZ
0.30
0.27
0.25
0.80
0.27
0.27
0.30
0.34
0.27
MANEUVER
0.67
0.45
0.50
0.80
0.45
0.45
0.45
0.67
0.45
HOTEL
0.24
0.22
0.17
0.64
0.22
0.22
0.30
0.34
0.67
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Main Engine Emission Factors
An analysis of emission data was prepared and published in 2002 by Entec.9 The
resulting Entec emission factors include individual values for three speeds of diesel engines
(slow-speed diesel (SSD), medium-speed diesel (MSD), and high-speed diesel (HSD)), steam
turbines/steamships (ST), gas turbines (GT), and for the two types of fuel used, residual marine
(RM) and marine distillate oil (MDO). Table 4-6 lists the propulsion engine emission factors for
NOx and HC that were used in the 2002 port inventory development. The CO, PM, 862 and
CC>2 emission factors shown in the table come from other data sources as explained below.
Since PM and SO2 emission factors are dependent on the fuel sulfur level, the fuel types and fuel
sulfur levels used in this analysis are described at the end of this section.
Table 4-6 Emission Factors for OGV Main Engines using RM, g/kWh
ENGINE
SSD
MSD
ST
GT
NOX
18.1
14.0
2.1
6.1
CO
1.40
1.10
0.20
0.20
HC
0.60
0.50
0.10
0.10
CO2
620.62
668.36
970.71
970.71
PM10
1.4
1.4
1.5
1.5
PM25
1.3
1.3
1.4
1.4
SO 2
10.29
11.09
16.10
16.10
CO emission factors were developed from information provided in the Entec appendices
because they are not explicitly stated in the text. HC and CO emission factors were confirmed
with a recent U.S. Government review.10
11
values were determined based on existing engine test data in consultation with
ARB. GT PMio emission factors were not part of the U.S. Government analysis but assumed
here to be equivalent to ST PMio emission factors. Test data shows PMio emission rates as
dependent upon fuel sulfur levels, with base PMio emission rates of 0.23 g/kW-hr with distillate
fuel (0.24% sulfur) and 1 .35 g/kW-hr with residual fuel (2.46% sulfur). 12 The equation used to
generate emission factors based on sulfur content is shown below. PM2.5 is assumed to be 92
percent of PMio. While the U.S. Government NONROAD model uses 0.97 for such conversion
based upon low sulfur fuels, a reasonable value seems to be closer to 0.92 because higher sulfur
fuels in medium and slow speed engines would tend to produce larger particulates than high
speed engines on low sulfur fuels.
Equation 4-2 Calculation of PM10 Emission Factors Based on Fuel Sulfur Levels
PMEF = PMNom + [(SAct - SNom) x BSFC x FSC x MWR x 0.0001]
where:
= PM emission factor adjusted for fuel sulfur
= PM emission rate at nominal fuel sulfur level
= 0.23 g/kW-hr for distillate fuel, 1.35 g/kW-hr for residual fuel
= Actual fuel sulfur level (weight percent)
= nominal fuel sulfur level (weight percent)
= 0.24 for distillate fuel, 2.46 for residual fuel
PM10 is paniculate matter of aerodynamic diameter 10 micrometers or less.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
BSFC = fuel consumption in g/kW-hr
= 200 g/kW-hr used for this analysis
FSC = percentage of sulfur in fuel that is converted to direct sulfate PM
= 2.247% used for this analysis
MWR = molecular weight ratio of sulfate PM to sulfur
= 224/32 = 7 used for this analysis
SO 2 emission factors were based upon a fuel sulfur to SC>2 conversion formula which
was supplied by ENVIRON.13 Emission factors for SC>2 emissions were calculated using the
formula assuming that 97.753 percent of the fuel sulfur was converted to SC>2.14 The brake
specific fuel consumption (BSFC)D that was used for SSDs was 195 g/kWh, while the BSFC that
was used for MSDs was 210 g/kWh and was based upon Lloyds (1995). The BSFC that was
used for STs and GTs was 305 g/kWh and was based upon Entec.15
Equation 4-3 Calculation of SO2 Emission Factors, g/kWh
SO2 EF = BSFC x 64/32 x 0.97753 x Fuel Sulfur Fraction
C02 emission factors were calculated from the BSFC assuming a fuel carbon content of
86.7 percent by weight15 and a ratio of molecular weights of CO2 and C at 3.667.
Equation 4-4 Calculation of CO 2 Emission Factors, g/kWh
CO2 EF = BSFC x 3.667 x 0.867
Fuel consumption was calculated from CC>2 emissions based on a 1:3.183 ratio.
Approximately 3.183 tons of CC>2 emissions are assumed produced from one metric ton of fuel.
SO2 emission factors were calculated using Equation 4-3 while PM emissions were
determined using Equation 4-2.
Note on Fuel Types and Fuel Sulfur Levels: There are primarily three types of fuel used
by marine engines: residual marine (RM), marine diesel oil (MDO), and marine gas oil (MGO),
with varying levels of fuel sulfur.16 MDO and MGO are generally described as distillate fuels.E
For this analysis, RM and MDO fuels are assumed to be used. Since PM and SO2 emission
factors are dependent on the fuel sulfur level, calculation of port emission inventories requires
information about the fuel sulfur levels associated with each fuel type, as well as which fuel
types are used by propulsion and auxiliary engines.
Table 4-7 sets out the mix of fuel types used for propulsion and auxiliary engines by ship
type in this analysis. The average fuel sulfur level for residual marine was set to 2.7 percent,
which is what was assumed in the North American EGA application for the eastern and gulf
17 1R
coast portions of the U.S. A sulfur content of 1.5 percent was used for MDO. We received
anecdotal data suggesting that the sulfur content of residual fuel sold on the Great Lakes may be
lower than 2.7 percent. However, we retained a sulfur content of 2.7 percent to reflect both the
D Brake specific fuel consumption is sometimes called specific fuel oil consumption (SFOC).
E While there are small differences in the fuel characteristics of MDO and MGO, these are both distillate fuel an
are functionally the same. The price difference between MGO and MDO is small, averaging about +/1 percent.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
higher sulfur content of ocean-going vessels that operate on the Great Lakes and to reflect the
fact that fuel used on steam vessels remains uncontrolled. With regard to distillate fuel, the
sulfur content of marine fuel sold in the United States is about 0.4 percent. However, the 1.5
percent value was retained for this analysis given the higher sulfur content of fuel sold in
Canada. Because of the small proportion of distillate fuel used by ships relative to RM, the
difference should not be significant.
Table 4-7 Estimated Mix of Fuel Types Used by Ships
SHIP TYPE
Passenger
Other
FUEL USED
PROPULSION
100% RM
100% RM
AUXILIARY
92%RM/8%MDO
71%RM/29%MDO
Auxiliary Engine Emission Factors
The most current set of auxiliary engine emission factors also comes from Entec, except
as noted below for PM and SC>2. Table 4-8 provides these auxiliary engine emission factors.
Table 4-8 Auxiliary Engine Emission Factors by Fuel Type, g/kWh
ENGINE
MSD
FUEL
RM
MDO
ALL PORTS
NOX
14.70
13.90
CO
1.10
1.10
HC
0.40
0.40
C02
668.36
668.36
PM10
1.4
0.6
PM25
1.3
0.55
SO 2
11.09
6.16
Auxiliary engine power was estimated from average propulsion power using the ratio of
auxiliary power to propulsion power ratios. Using the ratios of RM versus MDO as given in
Table 4-7 together with the emission factors shown in Table 4-8, the auxiliary engine emission
factor averages by ship type are listed in Table 4-9. Again, as explained above, while this fuel
sulfur level may be higher than the average sulfur level of fuel used on the Great Lakes, we do
not believe this emission factor has a significant effect on the total emission inventory estimates
due to the small portion of fuel used in auxiliary engines as compared to main propulsion
engines.
Table 4-9 Auxiliary Engine Emission Factors by Ship Type, g/kWh
SHIP TYPE
Passenger
Others
ALL PORTS
NOX
14.64
14.47
CO
1.10
1.10
HC
0.40
0.40
C02
668.36
668.36
PM10
1.4
1.2
PM25
1.3
1.1
SO 2
10.70
9.66
Low Load Adjustment Factors for Propulsion Engines
Emission factors are considered to be constant down to about 20 percent load. Below
that threshold, emission factors tend to increase as the load decreases. This trend results because
diesel engines are less efficient at low loads and the brake specific fuel consumption (BSFC)
tends to increase. Thus, while mass emissions (grams per hour) decrease with low loads, the
engine power tends to decrease more quickly, thereby increasing the emission factor (grams per
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Chapter 4 Emission Inventory for the U.S. Great Lakes
engine power) as load decreases. Energy and Environmental Analysis Inc. (EEA) demonstrated
this effect in a study prepared for the U.S. Government in 2000.19 In the EEA report, equations
were developed for the various emissions. The low-load adjustment factors were developed
based upon the concept that the BSFC increases as load decreases below about 20 percent load.
Using these algorithms, fuel consumption and emission factors versus load were
calculated. By normalizing emission factors to 20% load, low-load multiplicative adjustment
factors were calculated for propulsion engines and presented in Table 4-10. Due to their normal
operation, there is no need for a low load adjustment factor for auxiliary engines.
Table 4-10: Calculated Low Load Multiplicative Adjustment Factors
LOAD (%)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
NOX
11.47
4.63
2.92
2.21
1.83
1.60
1.45
1.35
1.27
1.22
1.17
1.14
1.11
1.08
1.06
1.05
1.03
1.02
1.01
1.00
HC
59.28
21.18
11.68
7.71
5.61
4.35
3.52
2.95
2.52
2.20
1.96
1.76
1.60
1.47
1.36
1.26
1.18
1.11
1.05
1.00
CO
19.32
9.68
6.46
4.86
3.89
3.25
2.79
2.45
2.18
1.96
1.79
1.64
1.52
1.41
1.32
1.24
1.17
1.11
1.05
1.00
PM
19.17
7.29
4.33
3.09
2.44
2.04
1.79
1.61
1.48
1.38
1.30
1.24
1.19
1.15
1.11
1.08
1.06
1.04
1.02
1.00
SO 2
5.99
3.36
2.49
2.05
1.79
1.61
1.49
1.39
1.32
1.26
1.21
1.18
1.14
1.11
1.09
1.07
1.05
1.03
1.01
1.00
CO2
5.82
3.28
2.44
2.01
1.76
1.59
1.47
1.38
1.31
1.25
1.21
1.17
1.14
1.11
1.08
1.06
1.04
1.03
1.01
1.00
Maneuvering andHoteling Time-in-Mode
Specific information about the amount of time spent in maneuvering and hoteling modes
was not available for the 28 Great Lakes ports included in the ports inventory. Instead, we used
the approach that was used for the U.S. mainland ports, in which all commercial ports were
mapped to one of a smaller set of "typical ports" and the operating characteristics of the relevant
typical port was applied to the specific matched ports. For this analysis, Cleveland and Duluth-
Superior were selected as the typical ports for the Great Lakes, due to the detailed information
available. Three criteria were used for matching a given port to a typical port: regional
differences, maximum vessel draft, and the ship types that call on a specific port. The Great
Lakes ports were matched to either Cleveland or Duluth-Superior as shown below.
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Table 4-11 Great Lake Match Ports
Port Name
Alpena, MI
Buffalo, NY
Burns Waterway, IN
Calcite, MI
Cleveland, OH
Dolomite, MI
Erie, PA
Escanaba, MI
Fairport, OH
Gary, IN
Lorain, OH
Marblehead, OH
Milwaukee, WI
Muskegon, MI
Presque Isle, MI
St Clair, MI
Stoneport, MI
Two Harbors, MN
Ashtabula, OH
Chicago, IL
Conneaut, OH
Detroit, MI
Duluth-Superior, MN&WI
Indiana, IN
Inland Harbor, MI
Manistee, MI
Sandusky, OH
Toledo, OH
Typical Like Port
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
Duluth-Superior
4.4.1.4 2002 Port Emission Inventories
The resulting 2002 emission inventory for each of the 28 Great Lakes ports is provided in
Table 4-12. These encompass the emissions within the seven nautical mile radius beyond the
end of the RSZ lanes.
Table 4-12 2002 Emissions Summary for Twenty-Eight Great Lake Ports
PORT NAME
Alpena, MI
Buffalo, NY
Burns Waterway, IN
ANNUAL EMISSIONS (METRIC TONNES)
NOX
1.5
2.9
45.5
PM10
0.3
0.3
3.9
PM25
0.2
0.3
3.6
HC
0
0.1
1.5
CO
0.1
0.2
3.7
S02
2.5
2.3
30
C02
156
150
1,982
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PORT NAME
Calcite, MI
Cleveland, OH
Dolomite, MI
Erie, PA
Escanaba, MI
Fairport, OH
Gary, IN
Lorain, OH
Marblehead, OH
Milwaukee, WI
Muskegon, MI
Presque Isle, MI
St Clair, MI
Stoneport, MI
Two Harbors, MN
Ashtabula, OH
Chicago, IL
Conneaut, OH
Detroit, MI
Duluth-Superior, MN&WI
Indiana, IN
Inland Harbor, MI
Manistee, MI
Sandusky, OH
Toledo, OH
Total Emissions
Total Emissions (short tons)
ANNUAL EMISSIONS (METRIC TONNES)
NOX
3.4
32.6
1.9
2.2
3.1
3
3.2
1.5
0.5
26.1
0.9
16.2
4.2
0.7
1.2
36.8
22.1
52.6
51.4
131.8
5.9
1.5
17.8
21
57.9
549
606
PM10
0.3
2.8
0.2
0.2
0.3
0.3
0.3
0.2
0.1
2.3
0.1
1.4
0.4
0.1
0.1
3.4
1.9
5
4.7
12
0.5
0.1
1.5
2
5.1
50
55
PM25
0.3
2.5
0.1
0.2
0.3
0.3
0.3
0.2
0.1
2.1
0.1
1.3
0.4
0.1
0.1
3.1
1.8
4.7
4.4
11.1
0.5
0.1
1.4
1.8
4.7
46
50
HC
0.1
1
0.1
0.1
0.1
0.1
0.1
0.1
0
0.8
0
0.7
0.2
0
0
1.3
0.7
1.9
1.7
4.5
0.2
0.1
0.5
0.8
2
19
21
CO
0.3
2.6
0.2
0.2
0.3
0.3
0.3
0.1
0
2.1
0.1
1.4
0.4
0.1
0.1
3.1
1.8
4.4
4.2
10.7
0.5
0.1
1.4
1.8
4.7
45
50
S02
2.5
21.8
1.1
1.7
2.3
2.5
2.2
1.3
0.5
17.8
0.7
10
o
3
0.4
0.9
26.4
15.3
39.5
37.5
94.5
4.1
1.1
12.2
15.2
39.3
389
429
C02
158
1,448
73
112
146
156
141
84
34
1,177
47
637
193
28
56
1,688
1,003
2,501
2,432
6,130
272
69
827
962
2,550
25,210
27,790
4.4.2 Interport Emission Inventories
The second part of the emissions inventory is emissions from ships traveling outside of
the seven-mile port areas and for ports other than the 28 Great Lakes ports described above.
These emissions were estimated using the Waterway Network Ship Traffic, Energy, and
Environmental Model (STEEM).20'21 This model geographically characterizes emissions from
ships traveling along shipping lanes to and from individual ports, in addition to the emissions
from vessels transiting near the ports. The shipping lanes were identified from actual ship
positioning reports. The model then uses detailed information about ship destinations, ship
attributes (e.g., vessel speed and engine horsepower), and emission factors to produce spatially
allocated (i.e., gridded) emission estimates for ships engaged in foreign commerce.
This modeling was performed to estimate interport emissions from main propulsion and
auxiliary engines used by vessels with Category 3 propulsion engines operating in the modeling
domain consisting of the U.S. portion of the Great Lakes.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
4.4.2.1 Interport Emission Inventory Methodology
STEEM was developed by the University of Delaware as a comprehensive approach to
quantify and geographically represent interport ship traffic, emissions, and energy consumption
from large ocean-going vessels.22'23 The model estimates emissions from main propulsion and
auxiliary marine engines used on Category 3 vessels that engage in foreign commerce17 using
historical shipping activity, ship attributes (i.e., characteristics), and activity-based emission
factor information. These inputs are assembled using a geographic information system (GIS)
platform that also contains an empirically derived network of shipping lanes. It includes the
emissions for all ship operational modes from cruising in unconstrained shipping lanes to
maneuvering in a port. The model, however, excludes hoteling operations while the vessel is
docked or anchored and very low speed maneuvering close to a dock. Due to these exclusions,
STEEM is referred to as an "interport" model.
STEEM begins by building a spatially-defined waterway network based on empirical
shipping location information from two global ship reporting databases. The first is the
International Comprehensive Ocean-Atmosphere Data Set (ICOADS), which contains reports on
marine surface and atmospheric conditions from the Voluntary Observing Ships (VOS) fleet,24
which contains approximately 4,000 vessels worldwide. The ICOADS project is sponsored by
the National Oceanic and Atmospheric Administration (NOAA) and National Science
Foundation's (NSF) National Center for Atmospheric Research (NCAR). The second database is
the Automated Mutual-Assistance Vessel Rescue (AMVER) system.25 The AMVER data set is
based on a ship search and rescue reporting network sponsored by the U.S. Coast Guard. The
AMVER system is also voluntary, but is generally limited to ships over 1,000 gross tons on
voyages of 24 hours or longer. About 8,600 vessels reported to AMVER in 2004.
The latitude and longitude coordinates for the ship reports in the above databases are used
to statistically create and spatially define the direction and width of each shipping lane in the
waterway network. Each statistical lane (route and segment) is given a unique identification
number for computational purposes. For the current analysis, STEEM used 20 years of ICOADS
data (1983-2002) and about one year of AMVER data (part of 2004 and part of 2005). This is
illustrated in Figure 4-1.
F It should be noted that a large portion of activity on the U.S. side of the Great Lakes is by U.S. vessels that are not
included in foreign commerce statistics. See section 4.5.2 for an explanation of how the inventory is adjusted to
include U.S. domestic cargo.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Figure 4-1 AMVER and ICOADS data
Every port is also spatially located in the waterway network using ArcGIS software.
As illustrated in Figure 4-2, the waterway network represented in STEEM resembles a
highway network on land. It is composed of ports, which are origins and destinations of
shipping routes: junctions where shipping routes intersect, and segments that are shipping lanes
between two connected junctions. Each segment can have only two junctions or ports, and ship
traffic flow can enter and leave a segment only through a junction or at a port. Figure 4-2
represents only a sample of the many routes contained in the model.
Figure 4-2 Illustration of STEEM Modeling Domain and Spatial Distribution of Shipping Lanes
: . '<_ '-. : .
The STEEM interport model also employs a number of databases to identify the
movements for each vessel (e.g., trips), individual ship attributes (e.g., vessel size and
horsepower), and related emission factor information (e.g., emission rates) that are subsequently
used in the inventory calculations.
To allocate ships to the statistical lanes, STEEM uses the ArcGIS system Network
Analyst tools along with specific information on each individual ship movement to solve the
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Chapter 4 Emission Inventory for the U.S. Great Lakes
most probable path on the network between each pair of ports (i.e., a trip) for a certain ship size.
This is assumed to represent the least-energy path, which in most cases is the shortest distance
unless prevented by weather or sea conditions, water depth, channel width, navigational
regulations, or other constraints that are beyond the model's capability to forecast.
After identifying the shipping route and resulting distance associated with each unique
trip, the emissions are simply calculated for each operational mode using the following
generalized equation along with information from the ship attributes and emission factor
databases.
Equation 4-5
Emissions per trip = distance (nautical miles) / speed (nautical miles/hour) x horsepower (kW) x
fractional load factor x emission factor (g/kW-hour)
In STEEM, emissions are calculated separately for distances representing cruise and
maneuvering operational modes. Maneuvering occurs at slower speeds and load factors than
during cruise conditions. In STEEM, maneuvering is assumed to occur within a 3 nautical mile
radius of each port when a ship is entering or leaving a port. A ship is assumed to move at
maneuvering speed for an entire trip if the distance is less than 3 nautical miles.
Finally, the emissions along each shipping route (i.e., segment) for all trips are
proportioned among the respective cells that are represented by the gridded modeling domain.
For this work, emissions estimates were produced at a cell resolution of 4 kilometers by 4
kilometers, which is appropriate for most atmospheric air quality models. The results for each
cell are then summed, as appropriate, to produce emission inventories for the various geographic
regions of interest in this analysis.
4.4.2.2 Data Inputs for Interport Emission Inventories
Traffic along each gridded shipping lane is derived from USAGE Entrance and Clearance
a for 2002,26 together with Lloyd's Register
such as propulsion engine power and cruise speed.
call data for 2002,26 together with Lloyd's Register-Fairplay Ltd's data for ship characteristics,
The emission factors and load factors used as inputs to STEEM are very similar to those
used for the ports analysis. Additional adjustments were made to interport emission results for
PMio and 862 in order to reflect recent U.S. Government review of available engine test data
and fuel sulfur levels. Details of the STEEM emission inputs and adjustments are located in
Appendix 4C.
4.4.3 Total Ship Emission Inventory for 2002
The national and regional inventories in this study are a combination of the results from
the ports analysis and the STEEM interport modeling. Therefore, to obtain the total inventory
for 2002 it is necessary to spatially allocate the emissions in a format that is compatible with the
STEEM 4 kilometers by 4 kilometers gridded output. Once that has been accomplished as
described below, the two inventories can be blended together. This work was conducted by
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Chapter 4 Emission Inventory for the U.S. Great Lakes
ENVIRON International as a subcontractor under the U.S. Government contract with ICF
International.
4.4.3.1 Spatial Location of the Port Emission Inventories
The hoteling, maneuvering, RSZ, and cruise emissions from the port emission inventories
were spatially located by their respective latitude and longitude coordinates. For this study,
shapefiles were created that depicted the emission locations as described above. The following
sections provide a more detailed description of how the shapefiles representing the hoteling,
maneuvering, RSZ lanes, and cruise lanes were developed.
Hoteling and Maneuvering emissions
The designated location for hoteling and maneuvering emissions was modeled as a single
latitude/longitude coordinate point using the estimated port center. The hoteling and
maneuvering emissions represented by the latitude/longitude coordinate for each port were
subsequently assigned to a single cell in the gridded inventory where that point was located. It
should be noted that modeling a port as a point will over specify the location of the emissions
associated with that port if it occupies an area greater than one grid cell (4 kilometers by 4
kilometers). The coordinates of the 28 Great Lakes ports used in this work are shown in
Appendix 4A.
RSZ emissions
The RSZ routes associated with each of the 28 Great Lakes ports were modeled as lines.
Each RSZ was assumed to be three nautical miles in length. The RSZ emissions were distributed
evenly along the length of the line. The latitude/longitude coordinates for each point along the
line were subsequently used to assign the emissions to a grid cell based on the proportion of the
line segment that occurred in the respective cell.
Cruise emissions
The cruise mode links that extend seven nautical miles from the end of the RSZ end point
were also modeled with line shapefiles. These links were spatially described for each port
following the direction of the shipping lane evident in the STEEM data. Again, as with RSZ
emissions, the latitude/longitude coordinates for each point along the line were subsequently
used to assign the emissions to a grid cell based on the proportion of the line segment that
occurred in the respective cell.
As the Great Lakes include a large number of ports in a rather small geographical
location, some of the RSZ and cruise mode links overlap. In these cases, the calculated
emissions were allocated to the same links, such that the total emissions allocated to the
overlapping links are the sum of emissions from all of the ports sharing that link.
4.4.3.2 2002 Emission Inventory
After spatially defining the geographic location of the port emissions, but before actually
inserting them into the gridded STEEM inventory, it was necessary to determine if all of the
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Chapter 4 Emission Inventory for the U.S. Great Lakes
STEEM emissions within an affected cell should be replaced, or if some of the emissions should
be retained. In this latter case, ships would be traversing the area near a port, but not actually
entering or exiting the port.
The percentage of STEEM emissions that are attributable to a port, and should be
removed and replaced, was approximated by dividing the STEEM emissions in the isolated
portion of the route that lead only to the port, while the STEEM emissions in the major shipping
lane remained.
The actual merging of the two inventories was performed by creating a number of
databases that identified the fraction of the port inventory for each pollutant species and
operating mode that should be added to the grid cells for each port. A similar database was also
created that identified how much of the original STEEM emissions should be reduced to account
for ship movements associated directly with a port, while preserving those that represented
transient vessel traffic near the port. These databases were subsequently used to calculate the
new emission results for each affected cell in the original STEEM gridded inventory, resulting in
the combined inventory results for this study.
For some ports, the outer edges of the port inventories fell outside the U.S. inventory
domain and those portions outside the domain were removed. As a result, the port totals
presented in the next section are slightly less than those reported in Section 4.4.1.
The total inventory was created by summing emission estimates for ships while at port
and while underway (interport). The total 2002 inventory for the Great Lakes, along with the
relative contributions of the port and interport emissions are presented in Table 4-13.
Table 4-13 2002 Total C3 Inventory for the U.S. Great Lakes Domain
EMISSION TYPE
Port
Interport
Total Emissions
ANNUAL EMISSIONS (METRIC TONNES)3
NOX
491
14,528
15,019
PM10
44
1,135
1,179
PM25
41
1,044
1,085
HC
17
481
498
CO
40
1,134
1,174
S02
346
8,420
8,766
C02
22,476
518,860
541,336
a The port emission totals in this table are slightly less than those in Table 4-12 due to the gridding
process and trimming to include only port emissions that fall within the emission inventory
boundaries.
The interport and port inventories are about 96 percent and 4 percent of the total,
respectively.
4.5 Development of 2020 Emission Inventories
To obtain the 2020 baseline and control inventories for the inventory domain, it is
necessary to adjust the 2002 inventories to account for activity level growth and the emission
reductions that would occur in 2020 absent the EGA controls (baseline case) and with the EGA
controls (control case). This section describes how the adjustment factors were obtained and
presents the inventories for the inventory domain for 2020. The inventories for the EGA are
described in Section 4.6.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
4.5.1 Adjustment Methodology
We used a multi-step approach to adjust the 2002 inventories to estimate the 2020
baseline and control scenarios for the inventory domain. Specifically, we applied a growth factor
adjustment and an emission factor adjustment. The growth factor adjustment was derived from
the growth factors that were estimated for the North American EGA. The emission factor
adjustments were derived by developing a new set of emission factors based on the emission
programs that will be in place in the baseline and control scenarios; the adjustment factor is the
ratio of the 2020 emission factors to the 2002 emission factors.
4.5.1.1 Growth Factors for 2020
The starting point for developing the 2020 inventories was determining the average
annual growth rates from 2002 through 2020. The average annual growth rate for the Great
Lakes is estimated to be 1.7 percent. The methodology used to derive this growth rate is
described in Appendix 4D. The growth rate was then compounded over the inventory projected
time period for 2020 (i.e., 18 years). The growth rate and resulting multiplicative growth factor
for the Great Lakes are provided in Table 4-14.
Table 4-14 Emission Inventory Growth Factors for the Great Lakes in 2020
REGION
Great Lakes
2002-2020 AVERAGE
ANNUALIZED
GROWTH RATE (%)
1.7%
MULTIPLICATIVE
GROWTH FACTOR
RELATIVE TO 2002
1.356
The multiplicative growth factor was applied to each of the pollutant totals for 2002 to
project emissions to 2020. Additional adjustments were required to account for emission
controls, which are described in the following sections.
4.5.1.2 Emission Requirements Included in the Adjustment: Baseline and Control
Application of the EGA requirements to the U.S. portion of the Great Lakes is expected
to begin in August 2012. However, the inventory and air quality analysis performed for the
Coordinated Strategy and this Great Lakes Study is for 2020. The year 2020 was chosen because
it allows the use of detailed emission inventories that were created for other emission sources
(e.g., land-based stationary and mobile sources) as part of wider scale air pollution modelling
efforts. The choice of 2020 is also consistent with the fuel cost analysis. The choice of 2020 is
not expected to affect this analysis, for the reasons discussed below.
With regard to engine controls, by 2020 ships will be required to be in compliance with
the MARPOL Annex VI Tier I NOx standard for marine diesel engines, as well as the Tier II
standard. Also included in the 2020 baseline inventories is the NOx retrofit program for pre-
controlled engines in regulation 13 of MARPOL Annex VI. These requirements are included in
our emissions baseline. Beginning in 2016, new ships constructed on or after January 1, 2016
that operate on the Great Lakes are to be equipped with engines that meet the Tier III NOx
limits. While 2020 will include five years of turnover to the Tier III standards, the long service
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Chapter 4 Emission Inventory for the U.S. Great Lakes
life of Great Lakes vessels means that these impacts will be small and affect less than 25 percent
of the total fleet, assuming an average 20-year service life.
With regard to fuel controls, ships operating on the Great Lakes in 2020 will need to
comply with the EGA fuel requirements and ships will be required to use fuel with a maximum
sulfur content of 0.10 percent. Although the 0.10 percent fuel sulfur requirement goes into place
for all vessels operating in EGAs beginning in 2015, the use of 2020 as the analytic year will still
provide a representative scenario for the impact of the 0.10 percent fuel sulfur requirement on
human health and the environment. This is because the fuel requirements of the EGA go into
effect all at once with no phase-in. In addition, the Great Lakes fuel availability waiver for
10,000 ppm fuel will no longer apply in 2020. As a result, the impacts of the 1,000 ppm fuel
sulphur requirement on the Great Lakes in 2020 are expected to be the same as in 2015, with a
small increase due to growth.
While the use of 2020 is not expected to affect the outcome of our inventory and air
quality analyses, there are two other implications for the inventory analysis. First, with regard to
the impacts of the EGA fuel sulphur requirements, the choice of 2020 slightly over-estimates the
immediate benefits of the program in 2015. Therefore, the use of 2020 as the analytic year will
provide a representative scenario for the impact of the 0.1 percent fuel sulphur requirement on
human health and the environment. Second, with regard to the NOx impacts, the use of 2020
includes only five years of turnover since the Tier III standards were implemented. Due to the
long service lives of engines on ocean-going vessels, this means that the fleet will not be fully
turned over for some time and the full benefits of the EGA NOx controls will not be reflected in
this analysis. The choice of 2020 as the analytic year provides a balance between modelling a
year prior to full Tier III NOx standard fleet implementation and modelling a future year where
there may be more uncertainty associated with projecting emissions. It should be noted that,
although the 0.5 percent global fuel sulphur standard goes into effect in 2020, we did not include
the global standard in the 2020 analysis, as the sulphur content of the fuel used in the Great
Lakes at that time would be lower than the 0.5 percent global standard.
The effects of these controls are reflected in the 2020 emission inventories by applying
appropriate adjustment factors that reflect the percentage of the vessel fleet in those years that
are estimated to comply with the controls. Adjustment factors are ratios of 2020 to 2002
calendar year (CY) emission factors (EFs). Adjustment factors are derived separately by engine
type for propulsion and auxiliary engines. The adjustment factors for propulsion engines are
applied to the propulsion portion of the port inventory and the interport portion of the inventory.
The adjustment factors for auxiliary engines are applied to the auxiliary portion of the port
inventory.
4.5.1.3 Emission Factors for 2020 Emission Inventory Adjustments
The emission factors for the 2020 emission inventory adjustments reflect the application
of the engine controls described above. Note that the NOx engine standards apply only to diesel
reciprocating engines; gas and steam turbine engines are not subject to any of the NOx
standards.
4-22
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
For the NOx limits, the current Tier I controls, which are modeled as achieving an 11
percent reduction from Tier 0, apply to the 2000 through 2010 model year (MY) engines. In
2011 thru 2015, Tier II controls are applied. Tier II controls are modeled as a 2.5 g/kW-hr
reduction from Tier I. In the EGA area only, for 2016 MY engines and beyond, Tier III controls
are applied. Tier III controls are modeled as achieving an 80 percent reduction from Tier I
levels. The NOx retrofit program for Tier 0 (pre-control) engines was modeled as 11 percent
control from Tier 0 for 80 percent of 1990 thru 1999 MY engines greater than 90 liters per
cylinder (1/cyl) starting in 2011. The retrofit program was also modeled with a five year phase-
in. Control of fuel sulfur content within the EGA area to 0.10 percent affects both SC>2 and PM
emissions.
The NOx emission factors (EFs) by engine/ship type and Tier are provided in Table 4-15.
Tier 0 refers to pre-control. There are separate entries for Tier 0/1/2 base and Tier 0/1/2 control,
since the control engines would be using distillate fuel, and there are small NOx emission
reductions assumed when switching from residual to distillate fuel.27 The NOx control EFs by
Tier were derived using the assumptions described above.
Table 4-15 Modeled NOX Emission Factors by Tier
ENGINE/
SHIP
TYPE
Mainb
SSD
MSD
ST
GT
Aux
Pass
Other
NOX EF (g/kW-hr)
BASELINE
TIERO
18.1
14
2.1
n/a
14.6
14.5
TIERO
RETROFIT
16.1
12.5
n/a
n/a
n/aa
n/aa
TIER
I
16.1
12.5
n/a
n/a
13.0
12.9
TIER
II
13.6
10.0
n/a
n/a
10.5
10.4
CONTROL AREAS
TIERO
17
13.2
2
n/a
14.6
14.5
TIERO
RETROFIT
15.1
11.7
n/a
n/a
n/aa
n/aa
TIER
I
15.1
11.7
n/a
n/a
13.0
12.9
TIER
n
12.6
9.2
n/a
n/a
10.5
10.4
TIER
III
3
2.3
n/a
n/a
2.6
2.6
Notes:
a The retrofit program applies to engines over 90 1/cyl; auxiliary engines are smaller than this cutpoint and would
therefore not be subject to the program.
b SSD is slow speed diesel, MSD is medium speed diesel, ST is steam turbine, GT is gas turbine, Pass is passenger.
Because this program phases in over time, it is necessary to estimate the adjustment
factor for each year to obtain the appropriate adjustment factor for 2020. This is done by using
vessel age distributions (Table 4-16) to generate calendar year NOx EFs by engine/ship type for
the base and control areas included in the scenarios. The adjustment factors for 2020 for the
baseline and control scenarios are presented in Table 4-17.
4-23
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-16 Vessel Age Distribution for Great Lake Ports by Engine Type
AGE
GROUP
(years old)
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35+
PROPULSION ENGINE TYPE
(Fraction of Total)
MSB SSD ST
0.01610
0.02097
0.01370
0.02695
0.01571
0.04584
0.01494
0.01327
0.00099
0.00027
0.01085
0.00553
0.00739
0.02289
0.00000
0.00275
0.00069
0.00000
0.00342
0.00219
0.00867
0.00000
0.03375
0.04270
0.08161
0.02935
0.18511
0.01870
0.13815
0.05487
0.00000
0.03986
0.03654
0.03358
0.00295
0.06974
0.03913
0.03489
0.04644
0.03040
0.04547
0.01498
0.02180
0.01857
0.04842
0.03376
0.01177
0.01183
0.00546
0.02557
0.00286
0.00510
0.00073
0.00104
0.01967
0.01220
0.06140
0.05638
0.02108
0.02051
0.01010
0.05217
0.00522
0.00389
0.01438
0.01160
0.00114
0.00000
0.00282
0.00000
0.00123
0.30796
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
1.00000
ALL
AUXILIARY
ENGINES
0.02399
0.02243
0.02544
0.02511
0.02497
0.02442
0.01528
0.01391
0.02107
0.01454
0.01076
0.00782
0.00626
0.02242
0.00121
0.00361
0.00078
0.00041
0.01059
0.00645
0.03034
0.02503
0.02279
0.02606
0.03744
0.03480
0.07701
0.01083
0.06181
0.02697
0.00047
0.01611
0.01631
0.01358
0.00165
0.31734
4-24
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-17 Modeled NOX Emission Factors by Calendar Year and Control Type
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
CYNOxEF(g/kW-hr)
2002
18.1
14
2.1
n/a
14.6
14.5
2020 BASE
17.12
13.64
2.1
n/a
14.13
13.97
2020 ECA
CONTROL
13.07
11.79
2.0
n/a
11.99
11.99
The PM and SC>2 EFs are a function of fuel sulfur level. For the baseline portions of the
inventory, the residual fuel sulfur level modeled is 27,000 ppm (see Fuel Sulfur Level discussion
on page 4-12). The baseline distillate fuel sulfur level assumed for all areas is 15,000 ppm. As
discussed previously, for the baseline, main engines use residual fuel and auxiliary engines use a
mix of residual and distillate fuel. For the control areas, there is one level of distillate fuel sulfur
assumed to be used by all engines: 1,000 ppm for the ECA control areas.
Table 4-18 provides the PMio EFs by engine/ship type and fuel sulfur level. For
modeling purposes, PM2.5 is assumed to be 92 percent of PMio. The PM EFs are adjusted to
reflect the appropriate fuel sulfur levels using Equation 4-2.
Table 4-18 Modeled PM10 Emission Factors
ENGINE/ SHIP
TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
PM10EF(g/kW-hr)
BASELINE
27,000 ppm S
1.40
1.40
1.50
n/a
1.40
1.20
CONTROL AREAS
ECA 1,000 ppm S
0.19
0.19
0.17
n/a
0.19
0.19
Table 4-19 provides the modeled 862 EFs. 862 emission reductions are directly
proportional to reductions in fuel sulfur content.
4-25
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-19 Modeled SO, Emission Factors
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
SO2 EF (g/kW-hr)
BASELINE
27,000 ppm S
10.29
11.09
16.10
n/a
10.70
9.66
CONTROL AREAS
ECA
1,000 ppm S
0.36
0.39
0.57
n/a
0.39
0.39
For the CO 2 emission factors, CC>2 is directly proportional to fuel consumed. Table 4-20
provides the modeled CC>2 and BSFC EFs. Due to the higher energy content of distillate fuel on
a mass basis, the switch to distillate fuel for the control areas results in a small reduction to
BSFC and, correspondingly, CC>2 emissions.28
Table 4-20 Modeled Fuel Consumption and CO2 Emission Factors
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
EF (g/kW-hr)
BASELINE
BSFC
195
210
305
n/a
210
210
C02
621
668
970
n/a
668
668
CONTROL
AREAS
BSFC
185
200
290
n/a
200
200
C02
589
637
923
n/a
636
636
The HC and CO emission factors are assumed to remain unchanged from the 2002
scenario, since there are no emission standards or requirements for those pollutants. The ECA
NOx and fuel sulfur requirements are anticipated to reduce the NOx, 862 and PM emission
factors. The switch to lower sulfur distillate fuel use is also expected to lower CO2 emissions
slightly.
4.5.1.4 Port Emission Adjustment Factors
The EF adjustment factors are a ratio of the control EF to the 2002 EF. Table 4-21
through Table 4-25 provides the EF adjustment factors for each pollutant for the 2020 baseline
and control scenarios.
4-26
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-21 NOX EF Adjustment Factors by Engine/Ship Type and Control Type3
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
2020
BASE
0.9459
0.9744
1.0000
n/a
0.9657
0.9657
2020 ECA
CONTROL
0.7219
0.8423
0.9524
n/a
0.8196
0.8295
3 NOX adjustment factors are a ratio of future base or control EFs to
2002 EFs
Table 4-22 PM10 EF Adjustment Factors by Engine/Ship Type and Control Type3
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
2020
BASE
1.0000
1.0000
1.0000
n/a
1.0000
1.0000
2020 ECA
CONTROL
0.1352
0.1328
0.1108
n/a
0.1328
0.1550
PM10 adjustment factors are a ratio of the control EFs to the 2002
EFs. PM is not adjusted for the future baseline because fuel sulfur
levels are only assumed to change within the ECA.
Table 4-23 PM2.S EF Adjustment Factors by Engine/Ship Type and Control Type3
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
2020
BASE
1.0000
1.0000
1.0000
n/a
1.0000
1.0000
2020 ECA
CONTROL
0.1339
0.1316
0.1092
n/a
0.1316
0.1555
3 PM25 adjustment factors are a ratio of the control EFs to the 2002
EFs. PM is not adjusted for the future baseline because fuel sulfur
levels are only assumed to change within the ECA. The PM2 5
adjustment factors are slightly different from those for PM10 due to
rounding.
4-27
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-24 SO2 EF Adjustment Factors by Engine/Ship Type and Control Type"
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
2020
BASE
1.0000
1.0000
1.0000
n/a
1.0000
1.0000
2020 ECA
CONTROL
0.0351
0.0353
0.0352
n/a
0.0365
0.0405
a SO2 adjustment factors are a ratio of the control EFs to the
2002 EFs. SO2 is not adjusted for the future baseline because
fuel sulfur levels are only assumed to change within the ECA.
Table 4-25 CO2 EF Adjustment Factors by Engine/Ship Type and Control Type3
ENGINE/
SHIP TYPE
Main
SSD
MSD
ST
GT
Aux
Pass
Other
2020
BASE
1.0000
1.0000
1.0000
n/a
1.0000
1.0000
2020 ECA
CONTROL
0.9488
0.9531
0.9509
n/a
0.9525
0.9525
a CO2 adjustment factors are a ratio of the control EFs to the
2002 EFs. CO2 is not adjusted for the future baseline because
fuel consumption (BSFC) is only assumed to change within the
ECA.
4.5.1.5 Interport Emission Inventory Adjustment Factors
Since the interport portion of the inventory is not segregated by engine or ship type, it
was necessary to develop a different set of emission adjustment factors for these emissions. This
was done based on the assumed mix of main (propulsion) engine types in the Great Lakes. This
is appropriate because the majority of emissions while underway are from propulsion, not
auxiliary, engines. Using the ship call and power data, the mix of main engine types for the
Great Lakes is 44 percent SSD, 48 percent MSD and 8 percent ST.
The EF adjustment factors by main engine type from the port calculations were used with
a mix of main engine types to develop the Great Lakes interport EF adjustment factors. The
resulting EF adjustment factors applied to the 2002 interport portion of the emission inventory
are provided in Table 4-26.
4-28
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-26 EF Adjustment Factors for 2020 Scenarios3
POLLUTANT
NOX
PM10
PM25
S02
CO2
2002
1.0000
1.0000
1.0000
1.0000
1.0000
2020
BASE
0.9641
1.0000
1.0000
1.0000
1.0000
ECA CONTROL
0.7989
0.1320
0.1307
0.0352
0.9510
a Adjustment factors are ratios of future base or control EFs to 2002 EFs.
These adjustment factors are used to adjust the interport portion of the 2002
inventory.
4.5.2 2020 Port and Interport Emission Inventories
The 2020 port and interport inventories were developed by applying the growth factors
and emission factor adjustments to the 2002 inventories. These inventories were then combined
to obtain the 2020 total inventories, for the baseline and control cases. The port inventories were
created by applying the growth and emission adjustment factors to the 2002 port inventories.
The port inventories were then converted into a gridded format using the same approach as for
the 2002 inventory. Using this grid, STEEM values were removed from port cells and port
emissions were used as replacement values. In cases where the emissions near ports were only
partially attributable to port traffic, the STEEM inventory was reduced rather than removed. The
interport inventories were scaled by a growth factor to 2020, as previously described, and the
emission adjustment factors were applied.
Port and interport emissions were then aggregated to form regional totals. The resulting
baseline (reference) and control inventories for 2020 are presented in Table 4-27. Also presented
are the tonnes reduced and the percent reductions for each pollutant. The inventories include all
emissions within the U.S. portion of the Great Lakes.
Table 4-27 Category 3 Vessel Inventories in the U.S. Great Lakes for 2020 Scenarios3
SCENARIO
Reference
Control
Delta Emissions
Delta Emissions (%)
ANNUAL EMISSIONS (METRIC TONNES)
NOX
19,842
16,420
-3, 422
-17%
PM10
1,613
207
-1,406
-87%
PM25
1,484
190
-1,294
-87%
HC
682
676
-6
0%
CO
1,607
1,602
-5
0%
SO2
11,993
420
-11,574
-97%
CO2
740,624
704,390
-36,235
-5%
a These inventories include all emissions within the U.S. Great Lakes.
The fuel consumption by fuel type in the baseline and ECA cases is presented in Table
4-28.
4-29
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4-28 Fuel Consumption by Category 3 Vessels for 2020 Scenarios3
SCENARIO
Reference
Control
METRIC TONNES FUEL
DISTILLATE
1,719
221,297
RESIDUAL
230,962
0
TOTAL
232,681
221,297
3 These inventories include all emissions within the U.S. Great Lakes.
4.6 Adjustment to 2020 Inventories for Jones Act Shipping
Domestic traffic, i.e., U.S. ships delivering cargo from one U.S. port to another U.S. port,
is covered under the Jones Act, and is not accounted for in the above inventories. For the final
Category 3 rule, the contribution of Jones Act traffic by Category 3 vessels was estimated based
on an analysis by ICF International, under contract to EPA.29 For the Great Lakes, the ratio of
estimated total installed power with Jones Act traffic to the actual installed power included in the
emission inventory is 1.97. Installed power is used as a surrogate for emissions.
This ratio is applied to the C3 inventories in the previous section to obtain the adjusted
Great Lakes 2020 inventories in Table 4-29. Since the adjustments are applied to both the
reference and control emission inventories, the percent reductions are unchanged.
Table 4-29 Adjusted Category 3 Vessel Emission Inventories in the U.S. Great Lakes for 2020 Scenarios3
SCENARIO
Reference
Control
Delta Emissions
Delta Emissions
(%)
ANNUAL EMISSIONS (METRIC TONNES)
NOX
39,089
32,347
6,741
-17%
PM10
3,178
407.79
2,770
-87%
PM25
2,923
374.3
2,549
-87%
HC
1343.54
1331.72
11.82
-0%
CO
3,166
3,156
9.85
0%
S02
23,626
827.4
22, 799
-96%
C02
1,459,029
1,387,648
71,381
-5%
3 These inventories include all emissions within the U.S. Great Lakes, with an adjustment to account for Jones
Act traffic.
This ratio can also be applied to estimated fuel consumption for the 2020 scenarios; the
results are provided in Table 4-30.
Table 4-30 Adjusted Fuel Consumption by Category 3 Vessels for 2020 Scenarios3
SCENARIO
Reference
Control
METRIC TONNES FUEL
DISTILLATE
2,500
435,955
RESIDUAL
455,882
0
TOTAL
458,382
435,955
3 These inventories include all emissions within the U.S. Great Lakes, with an
adjustment to account for Jones Act traffic.
It should be noted that the application of this adjustment factor to the control inventories and the
fuel consumption estimates does not take into account the exclusion of steamships operating on
the Great Lakes from the EGA fuel control requirements, as provided in the Category 3 marine
4-30
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
final rule. As a result, both the inventory reductions and the increase in distillate fuel use for the
control program are over-estimated. The size of this discrepancy depends on how many
steamships continue to be in service in 2020, and the degree to which they are used. There are
currently 13 steamships in the U.S. fleet, built between 1942 and 1953, with one each built in
1959 and 1960 (this number includes both 12 diesel-powered steamships and one coal-fired
steamship). The Canadian fleet consists of 8 steamships built between 1952 and 1963, with one
built in 1906 and one built in 1967. Due to their age, these vessels are more likely to be retired
or repowered (i.e., new diesel engines installed for propulsion) by 2020.
4-31
-------
Chapter 4 Emission Inventory for the U.S. Great Lakes
Appendices
4 A
Port Coordinates
Table 4A-1 Port Coordinates
Port Name
Alpena, Ml
Ashtabula, OH
Buffalo, NY
Burns Waterway Harbor, IN
Calcite, Ml
Chicago, IL
Cleveland, OH
Conneaut, OH
Detroit, Ml
Duluth-Superior, MN and Wl
Erie, PA
Escanaba, Ml
Fairport Harbor, OH
Gary, IN
Indiana Harbor, IN
Lorain, OH
Manistee, Ml
Marblehead, OH
Milwaukee, Wl
Muskegon, Ml
Port Dolomite, Ml
Port Inland, Ml
Presque Isle, Ml
Sandusky, OH
St. Clair, Ml
Stoneport, Ml
Toledo, OH
Two Harbors, MN
U.S. ACE
CODE
L3617
L3219
L3230
L3739
L3620
L3749
L3217
L3220
L3321
L3924
L3221
L3795
L3218
L3736
L3738
L3216
L3720
L3212
L3756
L3725
L3627
L3803
L3845
L3213
L3509
L3619
L3204
L3926
PORT COORDINATES3
Longitude
-83.4223
-80.7917
-78.8953
-87.1552
-83.7756
-87.638
-81.6719
-80.5486
-83.1096
-92.0964
-80.0679
-87.025
-81.2941
-87.3251
-87.4455
-82.1951
-86.3443
-82.7091
-87.8997
-86.3501
-84.3128
-85.8628
-87.3852
-82.7123
-82.4941
-83.4703
-83.5075
-91.6626
Latitude
45.0556
41.91873
42.8783
41.64325
45.39293
41.88662
41.47852
41.96671
42.26909
46.77836
42.15154
45.73351
41.76666
41.61202
41.67586
41.48248
44.25082
41.52962
42.98824
43.19492
45.99139
45.95508
46.57737
41.47022
42.82663
45.28073
41.66294
47.00428
1 U.S. Army Corps of Engineers (USAGE) data from http://www.iwr.usace.army.mil/ndc/db/pport/dbf/
4-32
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Port Methodology and Equations
Emissions for each port were calculated for four modes of operation: 1) hoteling, 2)
maneuvering, 3) reduced speed zone (RSZ), and 4) cruise. Hoteling, or dwelling, occurs while
the vessel is docked or anchored near a dock, and only the auxiliary engine(s) are being used to
provide power to meet the ship's energy needs. Maneuvering occurs within a very short distance
of the docks. The RSZ varies from port to port, though generally the RSZ would begin and end
when the pilots board or disembark, and typically occurs when the port shipping lanes reach
unconstrained shipping lanes. The cruise mode emissions in the ports analysis extend seven
nautical miles beyond the end of the RSZ lanes for the Great Lake ports.
Emissions were calculated separately for propulsion and auxiliary engines. The basic
equation used is as follows.
Equation 4B-1
\ \y I MT^CI / ,
"g]'
Emissions model] = (calls) x (P ) x (hrs I callmode) x (LFmode, ,) x (EF, ,) x (Adj) x (1(T6 tonnes I g)
Where:
Emissionsmode [eng] = Metric tonnes emitted by mode and engine type
Calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[eng] = Total engine power by engine type, in kilowatts (kW)
hrs/callmode = Hours per call by mode
LFmode [eng] = Load factor by mode and engine type (unitless)
EF[eng] = Emission factor by engine type for the pollutant of interest, in g/kW-hr
(these vary as a function of engine type and fuel used, rather than activity mode)
Adj = Low load adjustment factor, unitless (used when the load factor is below 0.20)
10"6 = Conversion factor from grams to metric tonnes
Main engine load factors were calculated directly from the propeller curve based upon
the cube of actual speed divided by maximum speed (at 100% maximum continuous rating
[MCR]). In addition, cruise mode activity is based on cruise distance and speed inputs. The
following sections provide the specific equations used to calculate propulsion and auxiliary
emissions for each activity mode.
Cruise
Cruise emissions were calculated for both propulsion (main) and auxiliary engines. The
basic equation used to calculate cruise mode emissions for the main engines is below.
Equation 4B-2
Emissions crmse[mam] = (calls) x (P[mam]) x (hrs I callcrmse) x (LFcrmse[mam]) x (EF[mam]) x (1 (T6 tonnes I g)
4-33
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Where:
Emissionscruise [main] = Metric tonnes emitted from main engines in cruise mode
Calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[main] = Total main engine power, in kilowatts (kW)
hrs/callCruiSe = Hours per call for cruise mode
LFcruise [main] = Load factor for main engines in cruise mode (unitless)
EF[main] = Emission factor for main engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
10~6 = Conversion factor from grams to metric tonnes
In addition, the time in cruise is calculated as follows.
Equation 4B-3
Hrs I callcruise = Cruise Distance [nmiles] I Cruise Speed [knots] x 2 trips I call
Where:
Cruise distance = one way distance (7 nautical miles)
Cruise speed = vessel service speed, in knots
2 trips/call = Used to calculate round trip cruise distance
Main engine load factors are calculated directly from the propeller curve based upon the
cube of actual speed divided by maximum speed (at 100% maximum continuous rating [MCR]).
Equation 4B-4
LoadFactor cruisetmain-\= (CruiseSpeed[knots]/ MaximumSpeed[knots]f
Since cruise speed is estimated at 94 percent of maximum speed30, the load factor for
main engines at cruise is 0.83.
Substituting Equation 4B-3 for time in cruise into Equation 4B-2, and using the load
factor of 0.83, the equation used to calculate cruise mode emissions for the main engines
becomes the following.
Equation 4B-5 Cruise Mode Emissions for Main Engines
Emissions cmise[mam] = (calls) x (P[mam]) x (CruiseDistance/Cruise Speed) x (2 trips/call) x 0.83 x (EF[mam]) x (10~6 tonnes/g)
Where:
Emissionscruise [main] = Metric tonnes emitted from main engines in cruise mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[main] = Total main engine power, in kilowatts (kW)
Cruise distance = one way distance (7 nautical miles)
Cruise speed = vessel service speed, in knots
2 trips/call = Used to calculate round trip cruise distance
0.83 = Load factor for main engines in cruise mode, unitless
EF [main] = Emission factor for main engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
4-34
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Chapter 4 Emission Inventory for the U.S. Great Lakes
10~6 = Conversion factor from grams to metric tonnes
The equation used to calculate cruise mode emissions for the auxiliary engines is below.
Equation 4B-6 Cruise Mode Emissions for Auxiliary Engines
Emissions cruiselaux] = (calls) x (Plaux]) x (Cruise Distance/Cruise Speed) x (2trips/call) x (LFcruiselaux])x (EEaux])x (1(T6 tonnes I g)
Where:
Emissionscraise[aux] = Metric tonnes emitted from auxiliary engines in cruise mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[aux] = Total auxiliary engine power, in kilowatts (kW)
Cruise distance = one way distance (7 nautical miles)
Cruise speed = vessel service speed, in knots
2 trips/call = Used to calculate round trip cruise distance
LFcruise [aux] = Load factor for auxiliary engines in cruise mode, unitless (these vary by ship
type and activity mode)
EF[aux] = Emission factor for auxiliary engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
10~6 = Conversion factor from grams to metric tonnes
The inputs of calls, cruise distance, and vessel speed are the same for main and auxiliary
engines. Relative to the main engines, auxiliary engines have separate inputs for engine power,
load factor, and emission factors. The activity-related inputs, such as engine power, vessel
speed, and calls, can be unique to each ship calling on a port, if ship-specific information is
available. For this analysis, these inputs were developed by port for bins that varied by ship
type, engine type, and dead weight tonnage (DWT) range.
Reduced Speed Zone
RSZ emissions were calculated for both propulsion (main) and auxiliary engines. The
basic equation used to calculate RSZ mode emissions for the main engines is below.
Equation 4B-7
EmissionsRSZ[mam] = (calls) x (P[mam]) x (hrs I callRSZ) x (LFRSZ[mam]) x (EF[mam]) x (Adj) x (10"6 tonnes I g)
Where:
EmissionsRsz[main] = Metric tonnes emitted from main engines in RSZ mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[main] = Total main engine power, in kilowatts (kW)
hrs/callRsz = Hours per call for RSZ mode
LFRSZ [main] = Load factor for main engines in RSZ mode, unitless
EF[main] = Emission factor for main engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
Adj = Low load adjustment factor, unitless (used when the load factor is below 0.20)
4-35
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Chapter 4 Emission Inventory for the U.S. Great Lakes
10~6 = Conversion factor from grams to metric tonnes
In addition, the time in RSZ mode was calculated as follows.
Equation 4B-8
Hrs I callRSZ = RSZ Distance [nmiles] I RSZ Speed [knots] x 2 trips I call
Load factor during the RSZ mode was calculated as follows.
Equation 4B-9
LoadFactorRSZ,in-, = (RSZ Speed IMaximum Speed)3
In addition,
Equation 4B-10
Maximum Speed = Cruise Speed 10.94
Where:
0.94 = Fraction of cruise speed to maximum speed
Substituting Equation 4B-10 into Equation 4B-9, the equation to calculate load factor becomes
Equation 4B-11
LoadFactorRSZ,in. = (RSZ Speed x 0.94 / Cruise Speed )
Where:
0.94 = Fraction of cruise speed to maximum speed
Load factors below 2 percent were set to 2 percent as a minimum.
Substituting Equation 4B-8 for time in mode and Equation 4B-11 for load factor into
Equation 4B-7, the expression used to calculate RSZ mode emissions for the main engines
becomes
Equation 4B-12 RSZ Mode Emissions for Main Engines
EmissionsRSZ[aux] = (calls) x (P[aux^) x (RSZ Distance/ RSZ Speed) x (2 trips/call)
x (RSZ Speed x 0.94 / Cruise Speed)3 x (EF[aux]) x (Adj) x (10~6 tonnes I g)
Where:
EmissionsRsz[main] = Metric tonnes emitted from main engines in RSZ mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[main] = Total main engine power, in kilowatts (kW)
RSZ distance = one way distance, in nautical miles (3 nm for all Great Lake ports)
RSZ speed = speed, in knots
2 trips/call = Used to calculate round trip RSZ distance
Cruise speed = vessel service speed, in knots
4-36
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Chapter 4 Emission Inventory for the U.S. Great Lakes
= Emission factor for main engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
Adj = Low load adjustment factor, unitless (used when the load factor is below 0.20)
10"6 = Conversion factor from grams to tons
0.94 = Fraction of cruise speed to maximum speed
Emission factors are considered to be relatively constant down to about 20 percent load.
Below that threshold, emission factors tend to increase significantly as the load decreases.
During the RSZ mode, load factors can fall below 20 percent. Low load multiplicative
adjustment factors were developed and applied when the load fell below 20 percent (0.20). If the
load factor is 0.20 or greater, the low load adjustment factor is set to 1.0.
The equation used to calculate RSZ mode emissions for the auxiliary engines is below.
Equation 4B-13 RSZ Mode Emissions for Auxiliary Engines
EmissionsRSZ[aux] = (calls) x (P[aux]) x (RSZ Distance/ RSZ Speed) x (2 trips/call) x (LFRSZ[aux]) x (EF[aux]) x (10 tonnes I g)
Where:
EmissionsRsz[aux] = Metric tonnes emitted from auxiliary engines in RSZ mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[aux] = Total auxiliary engine power, in kilowatts (kW)
RSZ distance = one way distance, in nautical miles (3 nm for all Great Lake ports)
RSZ speed = speed, in knots
2 trips/call = Used to calculate round trip cruise distance
LFRSZ [aux] = Load factor for auxiliary engines in RSZ mode, unitless (these vary by ship type
and activity mode)
EF[aux] = Emission factor for auxiliary engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
10"6 = Conversion factor from grams to metric tonnes
Unlike main engines, there is no need for a low load adjustment factor for auxiliary
engines, due to their normal operation. When low loads are needed for an auxiliary engine, one
or more engines are shut off, allowing the remaining engines to maintain operation at a more
efficient level.
The inputs of calls, RSZ distance, and RSZ speed are the same for main and auxiliary
engines. Relative to the main engines, auxiliary engines have separate inputs for engine power,
load factor, and emission factors. The RSZ distances are assumed to be 3 nm for all Great Lake
ports.
Maneuvering
Maneuvering emissions were calculated for both propulsion (main) and auxiliary engines.
The basic equation used to calculate maneuvering mode emissions for the main engines is below.
4-37
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Equation 4B-14
Emissions man[mam] = (calls} x (P[mam]) x (hrs I callman) x (LFman[mam]) x (EF[mam]) x (Adj) x (1(T6 to/roes / g)
Where:
Emissionsman[main] = Metric tonnes emitted from main engines in maneuvering mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[main] = Total main engine power, in kilowatts (kW)
hrs/callman = Hours per call for maneuvering mode
LFman [main] = Load factor for main engines in maneuvering mode, unitless
EF[main] = Emission factor for main engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
Adj = Low load adjustment factor, unitless (used when the load factor is below 0.20)
10"6 = Conversion factor from grams to metric tonnes
Maneuvering time-in-mode is estimated based on the distance a ship travels from the
breakwater or port entrance to the pier/wharf/dock (PWD). Maneuvering times also include
shifts from one PWD to another or from one port within a greater port area to another. Average
maneuvering speeds vary from 3 to 8 knots depending on direction and ship type. For
consistency, maneuvering speeds were assumed to be the dead slow setting of approximately 5.8
knots.
Load factor during maneuvering is calculated as follows.
Equation 4B-15
LoadFactorman,ai, = (Man Speed[knots] / Maximum Speed[knots])3
In addition,
Equation 4B-16
Maximum Speed = Cruise Speed[knots]/0.94
Where:
0.94 = Fraction of cruise speed to maximum speed
Substituting Equation 4B-16 into Equation 4B-15 and using a maneuvering speed of 5.8 knots,
the equation to calculate load factor becomes
Equation 4B-17
LoadFactor , ,= (5.45 / Cruise Speed}3
man[mam] \ + /
Load factors below 2 percent were set to 2 percent as a minimum.
Substituting Equation 4B-17 for load factor into Equation 4B-14, the expression used to
calculate maneuvering mode emissions for the main engines becomes
4-38
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Equation 4B-18 Maneuvering Mode Emissions for Main Engines
Emissionsman[mam] = (calls') x (P[mam]) x (hrs I callman) x (5.45 / Cruise Speed)3 x (EF[mam]) x (Ad)} x (1(T6 tonnes I g)
Where:
Emissionsman[main] = Metric tonnes emitted from main engines in maneuvering mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[main] = Total main engine power, in kilowatts (kW)
hrs/callman = Hours per call for maneuvering mode
Cruise speed = Vessel service speed, in knots
EF[ma;n] = Emission factor for main engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
Adj = Low load adjustment factor, unitless (used when the load factor is below 0.20)
10"6 = Conversion factor from grams to metric tonnes
Since the load factor during maneuvering usually fell below 20 percent, low load
adjustment factors were also applied accordingly. Maneuvering times were not readily available
for all 28 Great Lakes ports. For this analysis, maneuvering times and load factors available for
either Cleveland or Duluth-Superior were used to calculate maneuvering emissions for the Great
Lake ports.
below.
The equation used to calculate maneuvering mode emissions for the auxiliary engines is
Equation 4B-19 Maneuvering Mode Emissions for Auxiliary Engines
Emissionsman[aux] = (calls) x (P[aux]) x (hrs I callman) x (LFman[aux]) x (EF[aux]) x (1 (T6 tonnes I g)
Where:
Emissionsman[aux] = Metric tonnes emitted from auxiliary engines in maneuvering mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[aux] = Total auxiliary engine power, in kilowatts (kW)
hrs/callman = Hours per call for maneuvering mode
LFman [aux] = Load factor for auxiliary engines in maneuvering mode, unitless (these vary by
ship type and activity mode)
EF[aux] = Emission factor for auxiliary engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
10"6 = Conversion factor from grams to metric tonnes
Low load adjustment factors are not applied for auxiliary engines.
Hotelling
Hotelling emissions were calculated for auxiliary engines only, as main engines are not
operational during this mode. The equation used to calculate hotelling mode emissions for the
auxiliary engines is below.
4-39
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Equation 4B-20 Retelling Mode Emissions for Auxiliary Engines
Emissionshotel[aux] = (calls) x (P[aux]) x (hrs I callhotel) x (LFhotel[aux]) x (EF[aux]) x (1 (T6 tonnes I g)
Where:
Emissionshotei[aux] = Metric tonnes emitted from auxiliary engines in hotelling mode
calls = Round-trip visits (i.e., one entrance and one clearance is considered a call)
P[aux] = Total auxiliary engine power, in kilowatts (kW)
hrs/call hotel = Hours per call for hotelling mode
LFhotel [aux] = Load factor for auxiliary engines in hotelling mode, unitless (these vary by ship
type and activity mode)
EF[aux] = Emission factor for auxiliary engines for the pollutant of interest, in g/kW-hr (these
vary as a function of engine type and fuel used, rather than activity mode)
10~6 = Conversion factor from grams to metric tonnes
Hotelling times were not readily available for the 28 Great Lakes ports. For this analysis,
hotelling times available for either Cleveland or Duluth-Superior were used to calculate hotelling
emissions for the Great Lake ports.
4-40
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Emission Inputs to STEEM
The STEEM waterway network model relies on a number of databases to identify the
movements for each vessel, individual ship attributes, and related emission factor information.
Each of these databases is described separately below.
Shipping Movements
The shipping activity and routes database provides information on vessel movements or
trips. It is developed using port entrance and clearance information from the USAGE report for
the U.S. and the Lloyd's Maritime Intelligence Unit (LMIU) for Canada and Mexico.31 These
sources contain information for each vessel carrying foreign cargo at each major port or
waterway that, most importantly for this analysis, includes vessel name and last port of call
(entrance record) or next port of call (clearance record). The database then establishes unique
identification numbers for each ship, each port pair, and each resulting trip.
Ship Attributes
The ship attributes data set contains the important characteristics of each ship that are
necessary for the STEEM interport model to calculate the emissions associated with each trip.
The information in this data set is matched to each previously assigned ship identification
number. The following information comes from the USAGE Entrances and Clearances report
for each ship identification number.
Ship type
Gross registered tonnage (GRT)
Net registered tonnage (NRT)
The ship attributes data set contains the following information from Lloyd's Register-
Fairplay for each ship identification number.
Main propulsion engine installed power (horsepower)
Service speed (cruise speed)
Ship size (length, width, and draft)
Sometimes data was lacking from the above references for ship speed. In these instances,
the missing information was developed for each of the nine common vessel types and the
appropriate value was applied to each individual ship of that type. Specifically, the missing ship
speeds for each ship category were obtained from the average speeds used in a Lloyd's Register
study of the Baltic Sea and from an Entec UK Limited study for the European Commission.32'33
The resulting vessel cruise speeds for ships with missing data are shown in Table 4C-1.
4-41
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4C-1 Average Vessel Cruise Speed by Ship Typeฃ
AVERAGE CRUISE
SHIP TYPE SPEED (knots)
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Refrigerated
Cargo (Reefer)
Roll On-Roll Off
(RORO)
Tanker
Fishing
Miscellaneous
14.1
19.9
12.3
22.4
16.4
16.9
13.2
11.7
12.7
a Used only when ship specific data were missing from the
commercial database references.
The average speed during maneuvering is approximately 60 percent of a ship's cruise
speed based on using the propeller law described earlier and the engine load factor for
maneuvering that is presented later in this section.
As with vessel cruise speed, main engine installed power was sometimes lacking in the
Lloyd's Register-Fairplay data set. Here again, the missing information was developed for nine
common vessel types and the appropriate value was applied to each individual ship of that type
when the data were lacking. In this case, the missing main engine horsepower was estimated by
regressing the relationships between GRT and NRT, and between installed power and GRT for
each vessel. This operation was performed internally in the model and the result was applied to
each individual ship, as appropriate.
The ship attributes database also contains information on the installed power of engines
used for auxiliary purposes. However, this information is usually lacking in the Lloyds data set,
so an alternative technique was employed to estimate the required values. In short, the STEEM
model uses a ratio of main engine horsepower to auxiliary engine horsepower that was
determined for eight different vessel types using information primarily from ICF International.34
(The ICF report attributed these power values to a study for the Port of Los Angeles by Starcrest
Consulting.30) The auxiliary engine power for each individual vessel of a given ship type was
then estimated by multiplying the appropriate main power to auxiliary power ratio and the main
engine horsepower rating for that individual ship. The main and auxiliary power values and the
resulting auxiliary engine to main engine ratios are shown in Table 4C-2.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4C-2 Auxiliary Engine Power Ratios
VESSEL TYPE
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Reefer
RORO
Tanker
Miscellaneous
AVERAGE
MAIN ENGINE
POWER (kW)
7,954
30,885
9,331
39,563
9,567
10,696 c
9,409
6,252
AVERAGE
AUXILIARY ENGINE
POWER (kW)
1,169
5,746
1,777
39,563 a
3,900 b
2,156C
1,985
1,680
AUXILIARY TO
MAIN ENGINE
POWER RATIO
0.147
0.186
0.190
1.000
0.136
0.202
0.211
0.269
a The ICF reference reported a value of 11,000 for auxiliary engines used on passenger vessels.
b The STEEM used auxiliary engine power as reported in the ARE methodology document.
0 The STEEM purportedly used values for RORO main and auxiliary engines that represent a trip
weighted average of the auto carrier and cruise ship power values from the ICF reference.
Finally, the ship attributes database provides information on the load factors for main
engines during cruise and maneuvering operations in addition to load factors for auxiliary marine
engines. Main engine load factors for cruise operations were taken from a study of international
shipping for all ship types, except passenger vessels.35 For this analysis, the STEEM model used
a propulsion engine load factor for passenger ship engines at cruise speed of 55 percent of the
total installed power. This is based on engine manufacturer data contained in two global
shipping studies.35'36 During maneuvering, it was assumed that all main engines, including those
for passenger ships, operate at 20 percent of the installed power. This is consistent with a study
done by Entec UK for the European Commission. The main engine load factors at cruise speed
by ship type are shown in Table 4C-3.
Auxiliary engine load factors, except for passenger ships, were obtained from the ICF
International study referenced above. These values are also shown in Table 4C-3. For cruise
mode, neither port nor interport portions of the inventory were adjusted for low load operation,
as the low load adjustments are only applied to propulsion engines with load factors below 20
percent.
Table 4C-3 Main and Auxiliary Engine Load Factors at Cruise Speed by Ship Type
SHIP TYPE
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Reefer
RORO
Tanker
Miscellaneous
AVERAGE MAIN
ENGINE LOAD
FACTOR (%)
75
80
80
55
80
80
75
70
AVERAGE AUXILIARY
ENGINE LOAD
FACTOR (%)
17
13
17
25
20
15
13
17
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Emission Factor Information
The emission factor data set contains emission rates for the various pollutants in terms of
grams of pollutant per kilowatt-hour (g/kW-hr). The main engine emission factors are shown in
Table 4C-4. The speed specific factors for NOx, HC, and 862 were taken from several recent
analyses of ship emissions in the U.S., Canada, and Europe.37'38'39'40 The PM factor was based
on discussions with the California Air Resources Board (ARB) staff. The fuel specific CO
emission factor was taken from a report by ENVIRON International.41 The STEEM model used
the composite emission factors shown in the table because the voyage data used in the model do
not explicitly identify main engine speed ratings, i.e., slow or medium, or the auxiliary engine
fuel type, i.e., marine distillate or residual marine. The composite factor for each pollutant is
determined by weighting individual emission factors by vessel engine population data from a
2005 survey of ocean-going vessels that was performed by ARB.42
Table 4C-4 Main Engine Emission Factors by Ship and Fuel Type
ENGINE
TYPE
Slow Speed
Medium Speed
Composite EF
MAIN ENGINE EMISSION FACTORS (g/kW-hr)
FUEL TYPE
Residual
Marine
Residual
Marine
Residual
Marine
NOX
18.1
14
17.9
PM10
1.5
1.5
1.5
PM25a
1.4
1.4
1.4
HC
0.6
0.5
0.6
CO
1.4
1.1
1.4
S02
10.5
11.5
10.6
a Estimated from PM10 using a multiplicative adjustment factor of 0.92.
The emission factors for auxiliary engines are shown in Table 4C-5. The fuel specific
main emission factors for NOx and HC were taken from several recent analyses of ship
emissions in the U.S., Canada, and Europe, as referenced above for the main engine load factors.
The PM factor for marine distillate was taken from a report by ENVIRON International, which
was also referenced above. The PM factor for residual marine was based on discussions with the
California Air Resources Board (ARB) staff. The CO factors are from the Starcrest Consulting
study of the Port of Los Angeles.30 For SO2, the fuel specific emission factors were obtained
from Entec and Corbett and Koehler.'35 The composite emission factors displayed in the table
are discussed below.
Table 4C-5 Auxiliary Engine Emission Factors by Ship and Fuel Type
ENGINE TYPE
Medium Speed
Medium Speed
Composite EF
AUXILIARY ENGINE EMISSION FACTORS (g/kW-hr)
FUEL TYPE
Marine
Distillate
Residual
Marine
Residual
Marine
NOX
13.9
14.7
14.5
PM10
0.3
1.5
1.2
PM25a
0.3
1.4
1.1
HC
0.4
0.4
0.4
CO
1.1
1.1
1.1
S02
4.3
12.3
**
Estimated from PM10 using a multiplicative adjustment factor of 0.92.
See Table 4C-6 for composite SO2 emission factors by vessel type.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
As for main engines, the STEEM model used the composite emission factors for auxiliary
engines. For all pollutants other than 862, underlying data used in the model do not explicitly
identify auxiliary engine voyages by fuel type, i.e., marine distillate or residual marine. Again,
the composite factor for those pollutants was determined by weighting individual emission
factors by vessel engine population data from a 2005 survey of ocean-going vessels that was
performed by ARB.43
For SC>2, composite emission factors for auxiliary engines were calculated for each vessel
type. These composite factors were determined by taking the fuel specific emission factors from
Table 4C-5 and weighting them with an estimate of the amount of marine distillate and residual
marine that is used by these engines. The relative amount of each fuel type consumed was taken
from the 2005 ARB survey. The relative amounts of each fuel type for each vessel type and the
resulting SC>2 emission factors are shown in Table 4C-6.
Table 4C-6 Auxiliary Engine SO 2 Composite Emission Factors by Vessel Type
VESSEL TYPE
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Reefer
RORO
Tanker
Miscellaneous
RESIDUAL
MARINE
(%)
71
71
71
92
71
71
71
0
MARINE
DISTILLATE
(%)
29
29
29
8
29
29
29
100
COMPOSITE
EMISSION FACTOR
(g/kW-hr)
9.98
9.98
9.98
11.66
9.98
9.98
9.98
4.3
Adjustments to STEEM PM and SO2 Emission Inventories
The interport emission inventories contained in this study for PMio and 862 were taken
from the STEEM inventories and then adjusted to reflect the U.S. Government's recent review of
available engine test data and fuel sulfur levels for the port analysis. In the ports work, a PM
emission factor of 1.4 g/kW-hr was used for most main engines, e.g., slow speed diesel and
medium speed diesel engines, all of which are assumed to use residual marine. A slightly higher
value was used for steam turbine and gas turbine engines, and a slightly lower value was used for
most auxiliary engines. However, these engines represent only a small fraction of the total
emissions inventory. The STEEM model used an emission factor of 1.5 g/kW-hr for all main
engines and a slightly lower value for auxiliary engines. Here again, the auxiliary engines
comprise only a small fraction of the total emissions from these ships. Therefore, for simplicity,
the interport PM inventories were adjusted by multiplying the STEEM results by the ratio of the
two primary emission factors, i.e., 1.4/1.5 or 0.933, to approximate the difference in fuel effects.
4-45
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Growth Factor Development
This appendix describes the development of growth factors for the Great Lakes and other
U.S. Regions that were used as the basis for the Great Lakes growth rate.
Geographic Regions
The geographic area reflects ship operations that occur within 200 nautical miles (nm)
from the official U.S. baseline but excludes operations in Exclusive Economic Zones of other
countries. The official U.S. baseline is recognized as the low-water line along the coast as
marked on the official U.S. nautical charts in accordance with the articles of the Law of the Sea.
The boundary was mapped using geographic information system (GIS) shapefiles obtained from
the NOAA's Office of Coast Survey. 4 The accuracy of the NOAA shapefiles was verified with
images obtained from the U.S. Geological Survey. The confirmed NOAA shapefiles were then
combined with a shapefile of the U.S. international border from the National Atlas.45 The
resulting U.S. area was further subdivided for this analysis to create regions that were compatible
with the geographic scope of the regional growth rates, which are used to project emission
inventories for the year 2020.
The Pacific Coast region was split into separate North Pacific and South Pacific regions
along a horizontal line originating from the Washington/Oregon border (Latitude 46ฐ 15'
North).
The East Coast and Gulf of Mexico regions were divided along a vertical line roughly
drawn through Key Largo, FL (Longitude 80ฐ 26' West).
The Alaska region was divided into separate Alaska Southeast and Alaska West regions
along a straight line intersecting the cities of Naknek and Kodiak. The Alaska Southeast
region includes most of the State's population, and the Alaska West region includes the
emissions from ships on a great circle route along the Aleutian Islands between Asia and
the U.S. West Coast.
For the Great Lakes domain, shapefiles were created containing all the ports and inland
waterways in the port inventory and extending out into the lakes to the international
border with Canada. The modeling domain spanned from Lake Superior on the west to
the point eastward in the State of New York where the St. Lawrence River parts from
U.S. soil.
The Hawaiian domain was subdivided so that a distance of 200 nm beyond the
southeastern islands of Hawai'i, Maui, O'ahu, Moloka'i, Ni'ihau, Kaua'i, Lanai, and
Kahoolawe was contained in Hawaii East. The remainder of the Hawaiian Region was
then designated Hawaii West.
This methodology resulted in nine separate regional modeling domains that are identified
below and shown in Figure 4D-1. U.S. territories are not included in this analysis.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
South Pacific (SP)
North Pacific (NP)
East Coast (EC)
Gulf Coast (GC)
Alaska Southeast (AE)
Alaska West (AW)
Hawaii East (HE)
Hawaii West (HW)
Great Lakes (GL)
Figure 4D-1 Regional Modeling Domains
ซ=^-=
Growth Factors by Geographic Region
The growth factors that are used to estimate future year emission inventories are based on
the expected demand for marine bunker fuels that is associated with shipping goods, i.e.,
commodities, into and out of the U.S. This section describes the growth factors that are used to
project the emissions to 2020 for each of the nine geographic regions evaluated in this analysis.
The use of bunker fuel as a surrogate for estimating future emissions is appropriate because the
quantity of fuel consumed by C3 engines is highly correlated with the amount of combustion
products, i.e., pollutants, that are emitted from those vessels. The term bunker fuel in this report
also includes marine distillate oil and marine gas oil that are used in some auxiliary power
engines.
The remainder of this section first summarizes the development of growth rates by RTI
International (RTI) for five geographic regions of the U.S., as performed under contract to the
U.S. Government.46'47 This is followed by the derivation of the growth factors for the nine
geographic regions of interest.
Summary of Regional Growth Rate Development
RTI developed fuel consumption growth rates for five geographic regions of the U.S.
These regions are the East Coast, Gulf Coast, North Pacific, South Pacific, and Great Lakes. The
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Chapter 4 Emission Inventory for the U.S. Great Lakes
amount of bunker fuel required in any region and year is based on the demand for transporting
various types of cargo by Category 3 vessels. This transportation demand is in turn driven by the
demand for commodities that are produced in one location and consumed in another, as predicted
by an econometric model. The flow of commodities is matched with typical vessels for trade
routes (characterized according to cargo capacity, engine horsepower, age, specific fuel
consumption, and engine load factors). Typical voyage parameters are then assigned to the trade
routes that include average ship speed, round trip mileage, tons of cargo shipped, and days in
port. Fuel consumption for each trade route and commodity type thus depends on commodity
projections, ship characteristics, and voyage characteristics. Figure 4D-2 illustrates the approach
to developing baseline projections of marine fuel consumption.
As a means of comparison, the EVIO Secretary General's Informal Cross
Government/Industry Scientific Group of Experts presented a growth rate that ranged from 3.3
AR
percent to 3.7 percent. RTFs overall U.S. growth rate was projected at 3.4 percent, which is
consistent with the FMO range.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Figure 4D-2 Illustration of Method for Estimating Bunker Fuel Demand
Ship Analysis: by Vessel Type and Size Category
Inputs
Outputs
Deadweight for all Vessels of
Given Type & Size3
Horsepower, Year of Build
for all Vessels of Given
Type & Size3
Specific Fuel Consumption
(g/SHP-HR) by Year of Build6
Engine Load Factors0
Average Daily Fuel
Consumption (Tons/Day)
- Main, Aux. Engine at Sea
- Aux. Engine in Port
Trade Analysis: by Commodity and Trade Route
Inputs
Outputs
Average Ship Speed0
Round Trip Mileage1
Tons of Cargo Shipped8
Average Cargo Carried
per Ship Voyage
Total Estimated Bunker Fuel Demand
Average Daily Fuel Consumption
(Tons/Day)
- Main, Aux. Engine at Sea
- Aux. Engine in Port
Total Days at Sea
and in Port
Bunker Fuel
Demand
Driven by changes in engine efficiency.
Driven by growth in
commodity flows.
Trade Analysis
Trade flows between geographic regions of the world, as illustrated by the middle portion
of Figure 4D-2, were defined for the following eight general types of commodities.
liquid bulk - crude oil
liquid bulk - refined petroleum products
liquid bulk - residual petroleum products
liquid bulk - chemicals (organic and inorganic)
liquid bulk -gas (including LNG and LPG)
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Chapter 4 Emission Inventory for the U.S. Great Lakes
dry bulk (e.g., grain, coal, steel, ores, and scrap)
general cargo (e.g., lumber/forest products)
containerized cargo
The analysis specifically evaluated trade flows between 21 regions of the world. Table
4D-1 shows the countries associated with each region.
Table 4D-1 Aggregate Regions and Associated Countries
AGGREGATE
REGIONS
U.S. Atlantic Coast
U.S. Great Lakes
U.S. Gulf Coast
E. Canada3
W. Canada3
U.S. Pacific North
U.S. Pacific South
Greater Caribbean
South America
Africa - West
Africa-North/East-
Mediterranean
Africa-East/South
Europe-North
Europe-South
Europe-East
Caspian Region
Russia/FSU
Middle East Gulf
Australia/NZ
Japan
Pacific-High Growth
China
Rest of Asia
BASE COUNTRIES / REGIONS
U.S. Atlantic Coast
U.S. Great Lakes
U.S. Gulf Coast
Canada3
Canada3
U.S. Pacific North
U.S. Pacific South
Colombia, Mexico, Venezuela, Caribbean Basin, Central America
Argentina, Brazil, Chile, Peru, Other East Coast of S. America, Other West
Coast of S. America
Western Africa
Mediterranean Northern Africa, Egypt, Israel,
Kenya, Other Eastern Africa, South Africa, Other Southern Africa
Austria, Belgium, Denmark, Finland, France, Germany, Ireland,
Netherlands, Norway, Sweden, Switzerland, United Kingdom
Greece, Italy, Portugal, Spain, Turkey, Other Europe
Bulgaria, Czech Republic, Hungary, Poland, Romania, Slovak Republic
Southeast CIS
The Baltic States, Russia Federation, Other Western CIS
Jordan, Saudi Arabia, UAE, Other Persian Gulf
Australia, New Zealand
Japan
Hong Kong S.A.R., Indonesia, Malaysia, Philippines, Singapore, South
Korea, Taiwan, Thailand
China
Viet Nam, India, Pakistan, Other Indian Subcontinent
3 Canada is treated as a single destination in the GI model. Shares of Canadian imports from and exports
to regions of the world in 2004 are used to divide Canada trade into shipments to/from Eastern Canada
ports and shipments to/from Western Canada ports.49
The overall forecast of demand for shipping services and bunker fuel was determined for
each of the areas using information on commodity flows from Global Insight's (GI) World Trade
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Service. Specifically, GI provided a specialized forecast that reports the flow of each commodity
type for the period 1995-2024, based on a proprietary econometric model. The general structure
of the GI model for calculating trade flow assumes a country's imports are driven by the
importing country's demand forces (given that the exporting country possesses enough supply
capacity), and are affected by exporting the country's export price and importing the country's
import cost for the commodity. The model then estimates demand forces, country-specific
exporting capacities, export prices, and import costs.
The salty Milo is led through the Soo Locks by the Tug Missouri - the Milo frequently carries wheat
from the U.S. to Italy. Source: Photograph taken by and used with permission from Dick Lund,
available here: http://dlund.20m.com/
The GI model includes detailed annual region-to-region trade flows for eight composite
commodities from 1995 to 2024, in addition to the total trade represented by the commodities.
Table 4D-2 illustrates the projections for 2012 and 2020, along with baseline data for 2005. In
2005, dry bulk accounted for 41 percent of the total trade volume, crude oil accounted for 28
percent, and containers accounted for 12 percent. Dry bulk and crude oil shipments are expected
to grow more slowly over the forecast period than container shipments. By 2020, dry bulk
represents 39 percent of the total trade volume, crude oil is 26 percent, and containers rise to 17
percent.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4D-2 Illustration of World Trade Estimates for Composite Commodities, 2005,2012, and 2020
COMMODITY TYPE
Dry Bulk
Grade Oil
Container
Refined Petroleum
General Cargo
Residual Petroleum and Other Liquids
Chemicals
Natural Gas
Total International Cargo Demand
CARGO (millions of tons)
2005
2,473
1,703
714
416
281
190
122
79
5,979
2012
3,051
2,011
1,048
471
363
213
175
91
7,426
2020
3,453
2,243
1,517
510
452
223
228
105
8,737
Ship Analysis by Vessel Type and Size
Different types of vessels are required to transport the different commodities to the
various regions of the world. Profiles of these ships were developed to identify the various
vessel types and size categories that are assigned to transport commodities of each type along
each route. These profiles include attributes such as ship size, engine horsepower, engine load
factors, age, and engine fuel efficiency. This information was subsequently used to estimate
average daily fuel consumption for each typical ship type and size category.
The eight GI commodity categories were mapped to the appropriate vessel type using
information from Clarkson's Shipping Database.50 These assignments are shown in Table 4D-3
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4D-3 Assignment of Commodities to Vessel Types
COMMODITY SHIP CATEGORY VESSEL TYPE
Liquid bulk - crude oil
Liquid bulk - refined
petroleum products
Liquid bulk - residual
petroleum products
Liquid bulk - chemicals
(organic and inorganic)
Liquid bulk - natural gas
(including LNG and LPG)
Dry bulk (e.g. grain, coal,
steel, ores, and scrap)
General cargo (including
neobulk, lumber/forest
products)
Containerizable cargo
Crude Oil Tankers
Product Tankers
Product Tankers
Chemical Tankers
Gas Carriers
Dry Bulk Carriers
General Cargo
Container Ships
Tanker
Product Carrier
Product Carrier
Chemical & Oil Carrier
LNG Carrier, LPG Carrier, Chemical & LPG Carrier,
Ethylene/LPG, Ethylene/LPG/Chemical,
LNG/Ethylene/LPG, LNG/Regasification, LPG/Chemical,
LPG/Oil, Oil & Liquid Gas Carrier
Bulk Carrier
General Cargo Liner, Reefer, General Cargo Tramp, Reefer
Fish Carrier, Ro-Ro, Reefer/Container, Ro-Ro
Freight/Passenger, Reefer/Fleet Replen., Ro-Ro/Container,
Reefer/General Cargo, Ro-Ro/Lo-Lo, Reefer/Pallets
Carrier, Reefer/Pass./Ro-Ro, Reefer/Ro-Ro Cargo
Fully Cellular Container
Each of the vessel types were classified by their cargo carrying capacity or deadweight
tons (DWT). The size categories were identified based on both industry definitions and natural
size breaks within the data. Table 4D-4 summarizes the size categories that were used in the
analysis and provides other information on the general attributes of the vessels from Clarkson's
Shipping Database. The vessel size descriptions are also used to define shipping routes based on
physical limitations that are represented by canals or straits through which ships can pass.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4D-4 Fleet Characteristics
SHIP
TYPE
Container
General
Cargo
Dry Bulk
Crude Oil
Tanker
Chemical
Tanker
Petroleum
Product
Tanker
Natural
Gas
Carrier
Other
Total
SIZE BY
DWT
Suezmax
PostPanamax
Panamax
Intermediate
Feeder
All
Capesize
Panamax
Handymax
Handy
VLCC
Suezmax
AFRAmax
Panamax
Handymax
Coastal
All
AFRAmax
Panamax
Handy
Coastal
VLGC
LGC
Midsize
All
-
MINIMUM
SIZE
(DWT)
83,000
56,500
42,100
14,000
0
MAXIMUM
SIZE
(DWT)
140,000
83,000
56,500
42,100
14,000
All
79,000
54,000
40,000
0
180,000
120,000
75,000
43,000
27,000
0
0
79,000
54,000
40,000
0
180,000
120,000
75,000
43,000
27,000
All
68,000
40,000
27,000
0
60,000
35,000
0
0
68,000
40,000
27,000
0
60,000
35,000
All
-
-
NUMBER
OF SHIPS
101
465
375
1,507
1,100
3,214
715
1,287
991
2,155
470
268
511
164
100
377
2,391
226
352
236
349
157
140
863
7,675
26,189
TOTAL
DWT
(millions)
9.83
30.96
18.04
39.8
8.84
26.65
114.22
90.17
46.5
58.09
136.75
40.63
51.83
10.32
3.45
3.85
38.8
19.94
16.92
7.9
3.15
11.57
6.88
4.79
88.51
888.4
TOTAL
HORSE-
POWER
(millions)
8.56
29.3
15.04
32.38
7.91
27.07
13.81
16.71
10.69
19.58
15.29
5.82
8.58
2.17
1.13
1.98
15.54
3.6
4.19
2.56
1.54
5.63
2.55
3.74
53.6
308.96
TOTAL
KILO-
WATTS
(millions)
6.38
21.85
11.21
24.14
5.90
20.18
10.30
12.46
7.97
14.60
11.40
4.34
6.40
1.62
0.84
1.48
11.59
2.68
3.12
1.91
1.15
4.20
1.90
2.79
39.96
230.36
The average fuel consumption for each vessel type and size category was estimated in a
multi-step process using individual vessel data on engine characteristics. Clarkson's Shipping
Database Register provides each ship's total installed horsepower (HP), type of propulsion
(diesel or steam), and year of build. These characteristics are then matched to information on
typical specific fuel consumption (SFC), which is expressed in terms of grams of bunker fuel
burned per horsepower-hour (g/HP-hr), which is equivalent to 1.341 g/kW-hr.
The SFC values are based on historical data from Wartsila Sulzer, a popular manufacturer
of diesel engines for marine vessels. RTI added an additional 10 percent to the reported
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Chapter 4 Emission Inventory for the U.S. Great Lakes
historical number, (i.e.,"test bed" or "catalogue") to account for the guaranteed tolerance level
and an in-service SFC differential. Overall, the 10 percent estimate is consistent with other
analyses that show some variation between the "test bed" SFC values reported in the
manufacturer product catalogues and those observed in actual service. This difference is
explained by the fact that old engines tend to consume more fuel than brand new engines and in-
service fuels may be different than the test bed fuels.51
Figure 4D-3 shows SFC values that were used in the model regarding the evolution of
specific fuel oil consumption rates for diesel engines over time. Engine efficiency in terms of
SFC has improved over time, most noticeably in the early 1980s in response to rising fuel prices.
However, there is a tradeoff between improving fuel efficiency and reducing emissions.
Conversations with engine manufacturers indicate that it is reasonable to assume SFC will
remain constant for the projection period of this study, particularly as they focus on meeting
NOx emission standards as required by MARPOL Annex VI, or other potential pollution control
requirements. Post-2000 SFC values are constant at approximately 135 g/hp-hr (180 g/kW-hr),
for diesel engines. However, RTI assumed a fixed SFC of 220 g/HP-hr (295 g/kW-hr) for steam
engines operating on bunker fuel.
Figure 4D--3 Diesel Engine Specific Fuel Consumption
200
180
120
B 100
80
60
40
20
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
Using the above information, the average daily fuel consumption (AFC), expressed in
metric tons of fuel at full engine load, for each vessel type and size category is found using the
following equation.
Equation 4D-1
Fleet AFCV_, =
SFCVS x HPVS x 1 0~6 tonnes I g]
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Where:
- Fleet AFC = Average daily fuel consumption in metric tonnes at full engine load
- v = Vessel type
s = Vessel size category
N = Number of vessels in the fleet
SFC = Specific fuel consumption in grams of bunker fuel burned per horsepower-
hour in use(g/FIP-hr)
FTP = Total installed engine power, in horsepower (FTP)
106 tonnes/g = Conversion from grams to metric tonnes
As previously noted, AFC values calculated in the above equation are based on total
horsepower; therefore, they must be scaled down to reflect typical operation using less than 100
percent of the horsepower rating, i.e., actual engine load. Table 4D-5 shows the engine load
factors that were used to estimate the typical average daily fuel consumption (tonnes/day) for the
main propulsion engine and the auxiliary engines when operated at sea and in port.52
Table 4D-5 Main and Auxiliary Engine Load Factors
VESSEL TYPE
Container Vessels
General Cargo Carriers
Dry Bulk Carriers
Crude Oil Tankers
Chemical Tankers
Petroleum Product Tankers
Natural Gas Carrier
Other
MAIN
ENGINE
LOAD
FACTOR
(%)
80
80
75
75
75
75
75
70
AUXILIARY
ENGINE AS % OF
MAIN ENGINE
22.0
19.1
22.2
21.1
21.1
21.1
21.1
20.0
AUXILIARY
ENGINE AS % OF
MAIN ENGINE
AT SEA
11.0
9.5
11.1
10.6
10.6
10.6
10.6
10.0
The RTI analysis also assumes that the shipping fleet changes over time as older vessels
are scrapped and replaced with newer ships. Specifically, vessels over 25 years of age are retired
and replaced by new ships of the most up-to-date configuration. This assumption leads to the
following change in fleet characteristics over the projection period.
New ships have engines rated at the current SFC, so even though there are no further
improvements in specific fuel consumption, the fuel efficiency of the fleet as a whole
will improve over time through retirement and replacement.
Due to modern building materials and designs, new ships will weigh as much as the
average ship built in 2005, so the total cargo capacity of the fleet will increase over
time as smaller ships retire and are replaced.
Container ships will increase in size over time on the trade routes between Asia to
either North America or Europe due to new designs.
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Trade Analysis by Commodity Type and Trade Route
Determining the total number of days at sea and in port requires information on the
relative amount of each commodity that is carried by the different ship type size categories on
each of the trade routes. For example, to serve the large crude oil trade from the Middle East
Gulf region to the Gulf Coast of the U.S., 98 percent of the deadweight tonnage is carried on
very large oil tankers, while the remaining 2 percent is carried on smaller Suezmax vessels.
After the vessel type size distribution was found, voyage parameters were estimated.
Specifically, these are days at sea and in port for each voyage (based on ports called, distance
between ports, and ship speed), and the number of voyages (based on cargo volume projected by
GI and the DTW from Clarkson's Shipping Database). The length of each voyage and number
of voyages were used to estimate the total number of days at sea and at port, which is a
parameter used later to calculate total fuel consumption for each vessel type and size category
over each route and for each commodity type. (More information on determining the round trip
distance for each voyage that is associated with cargo demand for the U.S. is provided in the next
section.)
The days at sea were calculated by dividing the round trip distance by the average vessel
speed.
Equation 4D-2
round trip distance route
DaysatSeaPerVoyageVVOMte =
speedv s x 24 hrs
Where:
v = Vessel type
s = Vessel size category
route = Unique trip itinerary
round trip route distance = Trip length in nautical miles
speed = Vessel speed in knots or nautical miles per hour
24 hrs = Number of hours in one day
CO
Table 4D-6 presents the speeds by vessel type that were used in the analysis. These
values are the same for all size categories, and are assumed to remain constant over the forecast
period.
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Table 4D-6 Vessel Speed by Type
VESSEL TYPE
Grade Oil Tankers
Petroleum Product Tankers
Chemical Tankers
Natural Gas Carriers
Dry Bulk Carriers
General Cargo Vessels
Container Vessels
Other
SPEED (knots)
13.2
13.2
13.2
13.2
14.1
12.3
19.9
12.7
The number of voyages along each trade route was estimated for each vessel type, v, and
size category, s, serving a given route by dividing the tonnes of cargo moved by the amount of
cargo (DTW) per voyage.
Number of Voyagesv>,>rwafe =
Equation 4D-3
total metric tonnes of cargo moved
fleet average DWTV s x utilization rate
Where:
tons
v = Vessel type
s = Vessel size category
trade = Commodity type
Fleet average DWT = Median dead weight tonnage carrying capacity in metric
Utilization rate = Fraction of total ship DWT capacity used
The cargo per voyage is based on the fleet average ship size from the vessel profile
analysis. For most cargo, a utilization rate of 0.9 is assumed to be constant throughout the
forecast period. Lowering this factor would increase the estimated number of voyages required
to move the forecasted cargo volumes, which would lead to an increase in estimated fuel
demand.
In addition to calculating the average days at sea per voyage, the average days in port per
voyage was also determined by estimating that most types of cargo vessels spend four days in
port per voyage (two loading and two unloading). RTI notes, however, that this can vary
somewhat by commodity and port.
Worldwide Estimates of Fuel Demand
This section describes how the information from the vessel and trade analyses were used
to calculate the total annual fuel demand associated with international cargo trade. Specifically,
for each year, y, of the analysis, the total bunker fuel demand is the sum of the fuel consumed on
each route for each commodity type (trade). The fuel consumed on each route for each trade is
the sum of the fuel consumed for each route and trade for that year by the main engines and
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auxiliary engines when operated at sea and in port. These summations are illustrated by the
following equations.
Equation 4D-4
T^/~I y1 y1 T7/^
y trade, route, year
trade route
= E E [ AFCtade)route!yatsea x Days at Sea^^ + AFCtrade!route)yatport x Days at Porttrade>route)y
trade route
Where:
FC = Fuel consumed in metric tonnes
y = calendar year
trade = Commodity type
route = Unique trip itinerary
AFC = Average daily fuel consumption in metric tonnes
yatsea = Calendar year main and auxiliary engines are operated at sea
yatport = Calendar year main and auxiliary engines are operated in port
Equations 4D-5
AFCtrade,route,yatsea = v ฃ ^ (Percent of trade along toute)^ [Fleet AFCV s x (MELF+AE at sea LF)]
AFCtrade,route,yatPort = v ฃ r (Percent of trade along route)v s [Fleet AFCV s x AE import LF]
DaysatSeatad t = S (Percent of trade along route) [Days at sea per voyage x Number of voyages 1
v,s,t,r ' L_ ' ' -I
Days at Porttade route y = S (Percent of trade along route)v s [Days at port per voyage x Number of voyages]
Where:
AFC = Average daily fuel consumption in metric tones
trade = Commodity type
route = Unique trip itinerary
- yatsea = Calendar year main and auxiliary engines are operated at sea
- yatport = Calendar year main and auxiliary engines are operated in port
- y = calendar year
- v = Vessel type
s = Vessel size category
t = Trade
- r = Route
- Fleet AFC = Average daily fuel consumption in metric tonnes at full engine load
MELF = main engine load factor, unitless
AE at sea LF = auxiliary engine at-sea load factor, unitless
- AE in port LF = auxiliary engine in-port load factor, unitless
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Chapter 4 Emission Inventory for the U.S. Great Lakes
The inputs for these last four equations were all derived from the vessel analysis and the
trade analysis previously described.
Worldwide Bunker Fuel Consumption
Based on the methodology outlined above, estimates of global fuel consumption over
time were computed, and growth rates were determined from these projections.
Figure 4D-4 Worldwide Bunker Fuel Consumption
B Container IB General Cargo D Dry Bulk H Crude Oil
DChemicals DPetroleum Natural Gas DOther
Fishing Vessels Passenger Ships D Military Vessels
Figure 4D-4 shows estimated world-wide bunker fuel consumption by vessel type.
Figure 4D-5 shows the annual growth rates by vessel-type/cargo that are used in the projections
shown in Figure 4D-4. Total annual growth is generally between 2.5 percent and 3.5 percent
over the time period between 2006 and 2020 and generally declines over time, resulting in an
average annual growth rate of around 2.6 percent.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Figure 4D-5 Annual Growth Rate in World-Wide Bunker Fuel Use by Commodity Type
10%
-O- Total -9- Container General Cargo * Dry Bulk
-A- Crude Oil -K- Chemicals -*- Petroleum -- Natural Gas
~~ Other Fishing Vessels Passenger Ships Military Vessels
Fuel Demand Used to Import and Export Cargo for the United States
The methodology described previously provides an estimate of fuel consumption for
international cargo worldwide. RTI also estimates the subset of fuel demand for cargo imported
to and exported from five regions of the U.S. These five regions are North Pacific, South
Pacific, Gulf Coast, East Coast, and the Great Lakes. For this analysis, the same equations as
earlier were used, but were limited to routes that carried cargo between specific cities in Asia,
Europe, and the Middle East to the various ports in the specific regions of the U.S.
The trip distances for non-container vessel types were developed from information
provided by the Worldscale Association and Maritime Chain.53 The data from Worldscale is
considered to be the industry standard for measuring port-to-port distances, particularly for
tanker traffic. The reported distances account for common routes through channels, canals, or
straits. This distance information was supplemented by data from Maritime Chain, a web service
that provides port-to-port distances along with some information about which channels, canals,
or straits must be entered on the voyage.
Voyage distances for container vessels are based on information from the
Containerization International Yearbook (CIY)54 and calculations by RTI. CIY provides voyage
information for all major container services. Based on the frequency of the service, number of
vessels assigned to that service, and the number of days in operation per year, RTI estimated the
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average length of voyages for the particular bilateral trade routes in the Global Insights trade
forecasts.
The distance information developed above was combined with the vessel speeds
previously shown in Table 4D-6 to find the length of a voyage in days. Table 4D-7 presents the
day lengths for non-containerized vessel types and Table 4D-8 shows the day lengths for
container vessels.
Table 4D-7 Day Length for Voyages for Non-Container Cargo Ship (approximate average)
GLOBAL INSIGHTS TRADE
REGIONS
Africa East-South
Africa North-Mediterranean
Africa West
Australia-New Zealand
Canada East
Canada West
Caspian Region
China
Europe Eastern
Europe Western-North
Europe Western-South
Greater Caribbean
Japan
Middle East Gulf
Pacific High Growth
Rest of Asia
Russia-FSU
Rest of South America
DAYS PER VOYAGE
U.S. South
Pacific
68
49
56
48
37
11
95
41
61
53
54
26
35
77
52
68
64
51
U.S. North
Pacific
75
56
63
47
46
5
89
36
68
60
61
33
31
72
48
64
71
30
U.S. East
Coast
57
37
36
65
7
40
41
73
38
24
30
16
65
56
67
66
38
41
U.S. Great
Lakes
62
43
46
81
18
58
46
87
45
32
37
29
81
65
76
64
46
46
U.S. Gulf
54
47
43
63
19
39
48
69
46
34
37
17
62
83
88
73
48
44
Table 4D-8 Day Length for Voyages for Container-Ship Trade Routes
ORIGIN - DESTINATION REGIONS
Asia - North America (Pacific)
Europe - North America (Atlantic)
Mediterranean - North America
Australia/New Zealand - North America
South America - North America
Africa South - North America (Atlantic)
Africa West - North America (Atlantic)
Asia - North America (Atlantic)
DAYS PER
VOYAGE
37
37
41
61
48
54
43
68
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Chapter 4 Emission Inventory for the U.S. Great Lakes
ORIGIN - DESTINATION REGIONS
Europe - North America (Pacific)
Africa South - North America (Pacific)
Africa West - North America (Pacific)
Caspian Region - North America (Atlantic)
Caspian Region - North America (Pacific)
Middle East/Gulf Region - North America (Atlantic)
Middle East/Gulf Region - North America (Pacific)
DAYS PER
VOYAGE
64
68
38
42
38
63
80
Bunker Fuel Consumption for the United States
Figure 4D-6 and Figure 4D-7 present the estimates of fuel use for delivering trade goods
to and from the U.S. The results in Figure 4D-6 show an estimated historical bunker fuel use in
year 2001 of around 47 million tonnes (note: while this fuel is used to carry trade goods to and
from the U.S., it is not necessarily all purchased in the U.S. and is not all burned in U.S. waters).
This amount is estimated to grow to over 90 million tonnes by 2020 with the most growth
occurring on trade routes from the East Coast and the South Pacific region of the West Coast.
Figure 4D-6 Bunker Fuel Used to Import and Export Cargo by Region of the United States
100
a
ffl
s
o
H
a
o
10
S US North Pacific D US Great Lakes D US Gulf d US East Coast @ US South Pacific
Figure 4D-7 shows the estimated annual growth rates for the fuel consumption which
were used in the projections shown in Figure 4D-6. Overall, the average annual growth rate in
marine bunkers associated with future U.S. trade is 3.4 percent between 2005 and 2020.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Figure 4D-7 Annual Growth Rates for Bunker Fuel Used to Import and Export Cargo by Region of the
United States
10%
1 United States
1 US Great Lakes
US South Pacific
US Gulf
1 US North Pacific
US East Coast
2020 Growth Factors for Nine Geographic Regions
The results of the RTI analysis described above were used to develop the growth factors
that were necessary to project the 2002 base year emissions inventory out to 2020. The next two
sections describe how the five U.S. regions RTI examined were associated with the nine U.S.
regions analyzed in this report, and how the specific growth rates for each of the nine U.S.
regions were developed.
Mapping the RTI Regional Results to the Nine Region Analysis
The nine U.S. geographic regions analyzed in this study were designed to be consistent
with the five RTI U.S. regional modeling domains. More specifically, four of the nine U.S.
geographic areas in this study, i.e., Alaska East, Alaska West, Hawaii East, and Hawaii West are
actually subsets of the two broader regional areas that were analyzed by RTI, i.e., the North
Pacific for both Alaska regions and the South Pacific for Hawaii. Therefore, the growth rate
information from the broader region was assumed to be representative for the smaller subset
regions.
The nine U.S. geographic regions represented in the emission inventory study are
presented in Figure 2-1. The association of the RTI U.S. regions to the emission inventory
regions is shown in Table 4D-9.
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Table 4D-9 Association of the RTI U.S. Regions to the Nine Emission Inventory Regions
CONSUMPTION REGION
North Pacific
North Pacific
North Pacific
South Pacific
South Pacific
South Pacific
Gulf
East Coast
Great Lakes
CORRESPONDING
EMISSION INVENTORY
REGION
North Pacific (NP)
Alaska East (AE)
Alaska West (AW)
South Pacific (SP)
Hawaii East (HE)
Hawaii West (HW)
Gulf Coast (GC)
East Coast (EC)
Great Lakes (GL)
Growth Factors for the Emission Inventory Analysis
Emission inventories for 2020 are estimated by multiplying the 2002 baseline inventory
for each region by a corresponding growth factor that was developed from the RTI U.S. regional
results. Specifically, the average annual growth rate from 2002-2020 was calculated for each of
the five U.S. regions. Each regional growth rate was then compounded over the inventory
projection time period for 2020, i.e., 18 years. The resulting multiplicative growth factors for
each emission inventory region and the associated RTI average annual growth rates are presented
in Table 4D-10 for 2020.
Table 4D-10 Regional Emission Inventory Growth Rate Factors for 2020
EMISSION
INVENTORY
REGION
Alaska East (AE)
Alaska West (AW)
East Coast (EC)
Gulf Coast (GC)
Hawaii East (HE)
Hawaii West (HW)
North Pacific (NP)
South Pacific (SP)
Great Lakes (GL)
2002-2020 AVERAGE
ANNUALIZED GROWTH
RATE (%)
o o
J.J
1 1
J.J
4.5
2.9
5.0
5.0
o o
J.J
5.0
1.7
MULTIPLICATIVE
GROWTH RATE
FACTOR RELATIVE
TO 2002
1.79
1.79
2.21
1.67
2.41
2.41
1.79
2.41
1.35
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Chapter 4 Emission Inventory for the U.S. Great Lakes
Chapter 4 References
1 See in particular Memorandum to Docket EPA-HQ-OAR-2007-0121, Control of Emissions from New Marine
Compression-Ignition Engines at or above 30 Liters per Cylinder - Information in Support of Applying Emission
Control Area (EGA) Requirements to the Great Lakes Region. Michael J. Samulski, December 15, 2009.
2ICF International (October 2007). Commercial Marine Port Inventory Development, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA-420-R-07-012c, Docket ID EPA-HQ-OAR-2007-
0121-0063.1.
3 U.S. Army Corps of Engineers Navigation Data Center, Vessel Entrances and Clearances, 2002, available at
http://www.iwr.usace.army.mil/ndc/db/entclrn/data/entrclrn02/
4 U.S. Army Corps of Engineers Navigation Data Center, Vessel Entrances and Clearances, 2002, available at
http://www.iwr.usace.army.mil/ndc/db/entclrn/data/entrclrn02/
5 ICF International (October 2007). Commercial Marine Port Inventory Development, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA-420-R-07-012c, Docket ID EPA-HQ-OAR-2007-
0121-0063.1.
6 Nexus Media Communications, The Motor Ship's Guide to Marine Diesel Engines 2005, available at
http://www.motorship.com/
7 California Air Resources Board (September 2005). 2005 Oceangoing Ship Survey, Summary of Results.
8 Starcrest Consulting Group (June 2004). Port-Wide Baseline Air Emissions Inventory, prepared for the Port of Los
Angeles
9 Entec UK Limited (2002). Quantification of Emissions from Ships Associated with Ship Movements between
Ports in the European Community, prepared for the European Commission, Docket ID EPA-HQ-OAR-2007-0121-
0059.
10 U.S. Environmental Protection Agency (January 2009). Main Engine CO and HC Emission Factors in C3 Model
and Current Literature, Memorandum from Ari Kahan to Docket EPA-HQ-OAR-2007-0121.
11 U.S. Environmental Protection Agency (September 2007). Estimation of Paniculate Matter Emission Factors for
Diesel Engines on Ocean-Going Vessels, Memorandum from Mike Samulski to Docket EPA-HQ-OAR-2007-0121,
Docket ID EPA-HQ-OAR-2007-0121-0060.
12 U.S. Environmental Protection Agency (September 2007). Estimation of Particulate Matter Emission Factors for
Diesel Engines on Ocean-Going Vessels, Memorandum from Mike Samulski to Docket EPA-HQ-OAR-2007-0121,
Docket ID EPA-HQ-OAR-2007-0121-0060.
13 Memo from Chris Lindhjem of ENVIRON, PM Emission Factors, December 5, 2005.
14 U.S. Environmental Protection Agency, Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling -
Compression Ignition (April 2004). Appendix C, EPA- 420-P-04-009, available online at
http://www.epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf. Docket ID EPA-HQ-OAR-2003-0190-
0411.
15 Entec UK Limited (2002). Quantification of Emissions from Ships Associated with Ship Movements between
Ports in the European Community, prepared for the European Commission, Docket ID EPA-HQ-OAR-2007-0121-
0059.
16 RTI International (December 2006). Global Trade and Fuels Assessment - Future Trends and Effects of
Designation Requiring Clean Fuels in the Marine Sector: Task Order No. 1, Draft Report, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA420-D-07-006, Docket ID EPA-HQ-OAR-2007-0121-
0063.3.
17 This value is based on California Air Resources Board (September 2005). 2005 Oceangoing Ship Survey,
Summary of Results.
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18 Entec UK Limited (2002). Quantification of Emissions from Ships Associated with Ship Movements between
Ports in the European Community, prepared for the European Commission, Docket ID EPA-HQ-OAR-2007-0121-
0059.
19 Energy and Environmental Analysis Inc. (February 2000). Analysis of Commercial Marine Vessels Emissions and
Fuel Consumption Data, EPA420-R-00-002, available online at http://www.epa.gov/otaq/models/nonrdmdl/c-
marine/r00002.pdf.
20 Corbett, J. et al. (April 2007). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Final Report, prepared by University of Delaware for the California Air Resource Board, Contract
Number 04-346, and the Commission for Environmental Cooperation in North America, Contract Number 113.111,
Docket ID EPA-HQ-OAR-2007-0121-0063.2.
21 Corbett, J. et al. (May 2006). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Tasks 1 and 2: Baseline Inventory and Ports Comparison, Final Report, prepared by University of
Delaware for the California Air Resource Board, Contract Number 04-346, and the Commission for Environmental
Cooperation in North America, Contract Number 113.Ill, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
22 Corbett, J. et al. (April 2007). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Final Report, prepared by University of Delaware for the California Air Resource Board, Contract
Number 04-346, and the Commission for Environmental Cooperation in North America, Contract Number 113.111,
Docket ID EPA-HQ-OAR-2007-0121-0063.2.
23 Corbett, J. et al. (May 2006). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Tasks 1 and 2: Baseline Inventory and Ports Comparison, Final Report, prepared by University of
Delaware for the California Air Resource Board, Contract Number 04-346, and the Commission for Environmental
Cooperation in North America, Contract Number 113.Ill, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
24 Corbett, J. et al. (May 2006). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Tasks 1 and 2: Baseline Inventory and Ports Comparison, Final Report, prepared by University of
Delaware for the California Air Resource Board, Contract Number 04-346, and the Commission for Environmental
Cooperation in North America, Contract Number 113.Ill, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
25 Corbett, J. et al. (May 2006). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Tasks 1 and 2: Baseline Inventory and Ports Comparison, Final Report, prepared by University of
Delaware for the California Air Resource Board, Contract Number 04-346, and the Commission for Environmental
Cooperation in North America, Contract Number 113.Ill, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
26 U.S. Army Corps of Engineers Navigation Data Center (2002), Vessel Entrances and Clearances available at
http://www.iwr.usace.army.mil/ndc/db/entclrn/data/entrclrn02/
27 Entec UK Limited (2002). Quantification of Emissions from Ships Associated with Ship Movements between
Ports in the European Community, prepared for the European Commission, Docket ID EPA-HQ-OAR-2007-0121-
0059.
28 Entec UK Limited (2002). Quantification of Emissions from Ships Associated with Ship Movements between
Ports in the European Community, prepared for the European Commission, Docket ID EPA-HQ-OAR-2007-0121-
0059.
29ICF International (March 2009). Inventory Contribution of U.S. Flagged Vessels, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA-420-R-09-005, Docket ID EPA-HQ-OAR-2007-0121-
0154.
30 Starcrest Consulting Group (June 2004). Port-Wide Baseline Air Emissions Inventory, prepared for the Port of
Los Angeles
31 Corbett, J. et al. (May 2006). Estimation, Validation and Forecasts of Regional Commercial Marine Vessel
Inventories, Tasks 1 and 2: Baseline Inventory and Ports Comparison, Final Report, prepared by University of
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Delaware for the California Air Resource Board, Contract Number 04-346, and the Commission for Environmental
Cooperation in North America, Contract Number 113.Ill, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
32 Lloyd's Register and International Maritime Organization, Marine Exhaust Emission Quantification Study -
Baltic Sea, inMEPC 45/INF.7. 1998.
33 Entec UK Limited (2002). Quantification of Emissions from Ships Associated with Ship Movements between
Ports in the European Community, prepared for the European Commission, Docket ID EPA-HQ-OAR-2007-0121-
0059.
34ICF International (January 5, 2006). Current Methodologies and Best Practices in Preparing Port Emission
Inventories, Final Report, prepared for the U.S. Environmental Protection Agency, available online at
http://www.epa.gov/sectors/ports/bp_portemissionsfinal.pdf.
35 Corbett, JJ. and H. W. Koehler (2003). Updated Emissions from Ocean Shipping, Journal of Geophysical
Research, 108(D20); p. 4650.
36 Corbett, JJ. and H.W. Koehler (2004). Considering Alternative Input Parameters in an Activity-Based Ship Fuel
Consumption and Emissions Model: Reply to Comment by Oyvind Endresen et al. on "Updated Emissions from
Ocean Shipping," Journal of Geophysical Research. 109(D23303).
37 Levelton Consultants Ltd. (2006). Marine Emission Inventory Study Eastern Canada and Great Lakes - Interim
Report 4: Gridding Results, prepared for Transportation Development Centre, Transport Canada.
38 California Air Resources Board (October 2005). Emissions Estimation Methodology for Ocean-Going Vessels.
39 ICF International (January 5, 2006). Current Methodologies and Best Practices in Preparing Port Emission
Inventories, Final Report, prepared for the U.S. Environmental Protection Agency, available online at
http://www.epa.gov/sectors/ports/bp-portemissionsfinal.pdf.
40 Corbett, JJ. and H. W. Koehler (2003). Updated Emissions from Ocean Shipping, Journal of Geophysical
Research, 108 (D20); p. 4650.
41 ENVIRON International Corporation (2002). Commercial Marine Emission Inventory Development, prepared for
the U.S. Environmental Protection Agency, EPA Report Number: EPA420-R-02-019.
42 California Air Resources Board (September 2005). 2005 Oceangoing Ship Survey, Summary of Results.
43 California Air Resources Board (September 2005). 2005 Oceangoing Ship Survey, Summary of Results.
44 National Oceanic and Atmospheric Administration, Exclusive Economic Zone, Available online at
http://nauticalcharts.noaa.gov/csdl/eez.htm.
45 U.S. Department of Interior, North American Atlas - Political Boundaries, Available online at
http://www.nationalatlas.gov/mld/boundOm.html.
46 RTI International (December 2006). Global Trade and Fuels Assessment - Future Trends and Effects of
Designation Requiring Clean Fuels in the Marine Sector: Task Order No. 1, Draft Report, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA420-D-07-006, Docket ID EPA-HQ-OAR-2007-0121-
0063.3.
47 RTI International (April 24, 2006). RTI Estimates of Growth in Bunker Fuel Consumption, Memorandum with
spreadsheet from Michael Gallaher and Martin Ross, RTI, to Barry Garelick and Russ Smith, U.S. Environmental
Protection Agency.
48IMO. Revision of MARPOL Annex VI and the NOX technical code. Input from the four subgroups and
individual experts to the final report of the Informal Cross Government/Industry Scientific Group of Experts.
BLG/TNF. 10 12/28/2007
49 Transport Canada; Transportation in Canada Annual Report 2004. 2004. (Tables 3-26 and 8-27).
http://www.tc.gc.ca/pol/en/report/anre2004/8F_e.htm.
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50 RTI International (December 2006). Global Trade and Fuels Assessment - Future Trends and Effects of
Designation Requiring Clean Fuels in the Marine Sector: Task Order No. 1, Draft Report, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA420-D-07-006, Docket ID EPA-HQ-OAR-2007-0121-
0063.3.
51 RTI International (December 2006). Global Trade and Fuels Assessment - Future Trends and Effects of
Designation Requiring Clean Fuels in the Marine Sector: Task Order No. 1, Draft Report, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA420-D-07-006, Docket ID EPA-HQ-OAR-2007-0121-
0063.3.
52 Corbett, James and Chengfeng Wang (October 26, 2005). Emission Inventory Review SECA Inventory Progress
Discussion, p 11, memorandum to California Air Resources Board.
53 RTI International (December 2006). Global Trade and Fuels Assessment - Future Trends and Effects of
Designation Requiring Clean Fuels in the Marine Sector: Task Order No. 1, Draft Report, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA420-D-07-006, Docket ID EPA-HQ-OAR-2007-0121-
0063.3.
54 RTI International (December 2006). Global Trade and Fuels Assessment - Future Trends and Effects of
Designation Requiring Clean Fuels in the Marine Sector: Task Order No. 1, Draft Report, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA420-D-07-006, Docket ID EPA-HQ-OAR-2007-0121-
0063.3.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
CHAPTER 5: Air Quality, Health and Environmental
Impacts and Quantified Benefits of
Reduced Emissions from Great Lake Ships
The air quality and benefits modeling we performed in support of our 2010 Category 3
marine rule is a national-level analysis, reflecting the fact that our Coordinated Strategy is a
national program that applies equally throughout the United States.1 In response to stakeholder
comments during the regulatory process, we also prepared a Memorandum to the Docket in
which we broke out information with respect to air quality impacts, costs, and benefits associated
with applying the engine and fuel EGA requirements to the Great Lakes.2 This chapter expands
on the air quality impacts and human health and welfare benefits discussion contained in that
memorandum.
This chapter consists of four parts. First, we describe the air pollutants from Category 3
engines and their fuels that will be reduced by the Coordinated Strategy. Then we describe the
human health and environmental effects associated with exposure to these pollutants. This is
followed by a description of the air quality impacts of these pollutants and how these are
expected to be reduced in the Great Lakes region as a result of the application of the EGA fuel
and engine requirements. Finally, we discuss the human health and welfare benefits of these air
quality improvements. While the focus of this study is on the EGA fuel sulfur limits, which will
reduce PM emissions, this chapter includes information on the other benefits of the application
of the Coordinated Strategy on the Great Lakes.
Because it is not possible to isolate the potential impacts of the inventory reductions
occurring in the Northeast Atlantic portion of the North American EGA, estimated air quality
improvements are presented only for the Great Lakes states west of Pennsylvania. In addition,
because no new modeling was performed for this analysis, the estimates presented below do not
take into account the Great Lakes inventory adjustments described in Chapter 4. While the
impact of those adjustments on the air quality estimates presented below is unknown without
additional modeling, the vessel inventory reductions of 87 and 96 percent for PM and SOx,
respectively, will undoubtedly assist Great Lakes states' efforts to achieve and maintain National
Ambient Air Quality Standards (NAAQS) and help provide cleaner air throughout the region.
5.1 Types of Pollutants from Great Lakes Ships
The emissions that will be reduced from Great Lakes ships and their fuels include PM,
SOx and NOx. These emissions contribute to air pollution in the form of elevated ambient
levels of PM, ozone, NOx, and SOx, as well as air toxics. Each of these pollutants is presented
in this section; their health and environmental effects are described in Section 5.2.
5.1.1 Particulate Matter
Particulate matter (PM) is a generic term for a broad class of chemically and physically
diverse substances. It can be principally characterized as discrete particles that exist in the
condensed (liquid or solid) phase spanning several orders of magnitude in size.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Particles span many sizes and shapes and consist of numerous different chemicals.
Current NAAQS use PM2.s as the indicator for fine particles (with PM2.s referring to particles
with a nominal mean aerodynamic diameter less than or equal to 2.5 jim). The NAAQS use
PMio as the indicator for purposes of controlling the coarse fraction of PM, referred to as
thoracic coarse particles or coarse-fraction particles. This category generally includes particles
with a nominal mean aerodynamic diameter greater than 2.5 jim and less than or equal to 10 |im,
or PM 10-2.5). A third category of PM, ultrafme particles (UFPs), is a subset of fine particles,
generally less than 100 nanometers (0.1 um) in aerodynamic diameter.
Particles originate from various stationary and mobile sources and are also formed
through atmospheric chemical reactions. The former are often referred to as "primary" particles,
and the latter as "secondary" particles. In addition, there are also physical, non-chemical
reaction mechanisms that contribute to secondary particles. Particle pollution also varies by time
of year and location, and is affected by several weather-related factors, such as temperature,
clouds, humidity, and wind. A further layer of complexity comes from a particle's ability to shift
between solid, liquid, and gaseous phases, which is influenced by concentration, meteorology,
and temperature.
Fine particles are produced primarily by combustion processes and by transformations of
gaseous emissions (e.g., SOx, NOx and volatile organic compounds (VOCs)) in the atmosphere.
The chemical and physical properties of PM2.5 may vary greatly with time, region, meteorology
and source category. Thus, PM2.5 may include a complex mixture of different chemicals
including sulfates, nitrates, organic compounds, elemental carbon and metal compounds. These
particles can remain in the atmosphere for days to weeks and travel through the atmosphere up to
hundreds or even thousands of kilometers.3
5.1.2 Ozone
Ground-level ozone pollution is typically formed by the reaction of VOCs and NOx in
the lower atmosphere in the presence of sunlight. These pollutants, often referred to as ozone
precursors, are emitted by many types of pollution sources such as highway and nonroad motor
vehicles and engines, power plants, chemical plants, refineries, makers of consumer and
commercial products, industrial facilities, and smaller area sources.
The science of ozone formation, transport, and accumulation is complex. Ground-level
ozone is produced and destroyed in a cyclical set of chemical reactions, many of which are
sensitive to temperature and sunlight. When ambient temperatures and sunlight levels remain
high for several days and the air is relatively stagnant, ozone and its precursors can build up and
result in more ozone than typically occurs on a single high-temperature day. Ozone can be
transported hundreds of miles downwind from precursor emissions, resulting in elevated ozone
levels even in areas with low VOC or NOx emissions.
The highest levels of ozone are produced when both VOC and NOx emissions are
present in significant quantities on clear summer days. Relatively small amounts of NOx enable
ozone to form rapidly when VOC levels are relatively high, but ozone production is quickly
limited by removal of the NOx. Under these conditions NOx reductions are highly effective in
reducing ozone while VOC reductions have little effect. Such conditions are called "NOx-
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
limited." Since the contribution of VOC emissions from biogenic (natural) sources to local
ambient ozone concentrations can be significant, even some areas where man-made VOC
emissions are relatively low can be NOx-limited.
Ozone concentrations in an area also can be lowered by the reaction of nitric oxide (NO)
with ozone, forming nitrogen dioxide (NO2); however as the air moves downwind and the cycle
continues, the NO2 forms additional ozone. The importance of this reaction depends, in part, on
the relative concentrations of NOx, VOC, and ozone, all of which change with time and location.
When NOx levels are relatively high and VOC levels relatively low, NOx forms inorganic
nitrates (i.e., particles) but relatively little ozone. Such conditions are called "VOC-limited."
Under these conditions, VOC reductions are effective in reducing ozone, but NOx reductions can
actually increase local ozone under certain circumstances. Even in VOC-limited urban areas,
NOx reductions are not expected to increase ozone levels if the NOx reductions are sufficiently
large. Rural areas are usually NOx-limited, due to the relatively large amounts of biogenic VOC
emissions in such areas. Urban areas can be either VOC- or NOx-limited, or a mixture of both,
in which ozone levels exhibit moderate sensitivity to changes in either pollutant.
5.1.3 Sulfur Oxides and Nitrogen Oxides
Sulfur dioxide (802), a member of the sulfur oxide (SOx) family of gases, is formed
from burning fuels containing sulfur (e.g., coal or oil), extracting gasoline from oil, or extracting
metals from ore. Nitrogen dioxide (NO2) is a member of the nitrogen oxide (NOx) family of
gases. Most NO2 is formed in the air through the oxidation of nitric oxide (NO) emitted when
fuel is burned at a high temperature. SO2 andNO2 can dissolve in water droplets and further
oxidize to form sulfuric and nitric acid which react with ammonia to form sulfates and nitrates,
both of which are important components of ambient PM. NOx along with non-methane
hydrocarbons (NMHC) are the two major precursors of ozone.
5.1.4 Air Toxics
Marine diesel engines emit diesel exhaust (DE), a complex mixture comprised of carbon
dioxide, oxygen, nitrogen, water vapor, carbon monoxide, nitrogen compounds, sulfur
compounds and numerous low-molecular-weight hydrocarbons. A number of these gaseous
hydrocarbon components are individually known to be toxic including aldehydes, benzene and
1,3-butadiene. The diesel paniculate matter (DPM) present in diesel exhaust consists of fine
particles (< 2.5|im), including a subgroup with a large number of ultrafme particles (< 0.1 jim).
These particles have large surface areas which make them an excellent medium for adsorbing
organics, and their small size makes them highly respirable and able to deposit deep in the lung.
Diesel PM contains small quantities of numerous mutagenic and carcinogenic compounds
associated with the particles (and also organic gases). In addition, while toxic trace metals
emitted by marine diesel engines represent a very small portion of the national emissions of
metals (less than one percent) and are a small portion of diesel PM (generally much less than one
percent of diesel PM), we note that several trace metals of potential toxicological significance
and persistence in the environment are emitted by diesel engines. These trace metals include
chromium, manganese, mercury, and nickel. In addition, small amounts of dioxins have been
measured in highway engine diesel exhaust, some of which may partition into the particulate
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
phase. Dioxins are a major health concern but diesel engines are a minor contributor to overall
dioxin emissions.
Diesel exhaust varies significantly in chemical composition and particle sizes between
different engine types (heavy-duty, light-duty), engine operating conditions (idle, accelerate,
decelerate), and fuel formulations (high/low sulfur fuel). 4 Also, there are emission differences
between on-road and nonroad engines since the nonroad engines are generally of older
technology. After being emitted, diesel exhaust undergoes dilution as well as chemical and
physical changes in the atmosphere. The lifetime for some of the compounds present in diesel
exhaust ranges from hours to days.
A number of health studies have been conducted regarding diesel exhaust. These include
epidemiologic studies of lung cancer in groups of workers and animal studies focusing on non-
cancer effects specific to diesel exhaust exposure. Diesel exhaust PM (including the associated
organic compounds which are generally high molecular weight hydrocarbon types but not the
more volatile gaseous hydrocarbon compounds) is generally used as a surrogate measure for
diesel exhaust.
5.2 Human Health Effects Associated with Exposure to Pollutants
Ambient levels of PM, ozone, SOx, NOx, and air toxics contribute to serious human
health and environmental concerns. The human health impacts are described in this section;
environmental impacts are described in Section 5.3.
5.2.1 Particulate Matter
The summary of the health effects associated with exposureA to ambient concentrations
of PM presented in this section is based on the information and conclusions in the Integrated
Science Assessment (ISA) for Particulate Matter (December 2009) prepared by EPA's Office of
Research and Development (ORD).5B Interested readers should refer to that document for more
detailed information.
The ISA concludes that ambient concentrations of PM are associated with a number of
adverse health effects.0 The ISA characterizes the weight of evidence for different health effects
associated with three PM size ranges: PM2.5, PMio-2.s, and UFPs. The discussion below
highlights the ISA's conclusions pertaining to these three size fractions of PM, considering
variations in both short-term and long-term exposure periods.
With respect to effects associated with short-term exposure to PM2.5, the ISA concludes
that cardiovascular effects and all-cause cardiovascular- and respiratory-related mortality are
A Personal exposure includes contributions from many different types of particles, from many sources, and in many
different environments. Total personal exposure to PM includes both ambient and nonambient components; and
both components may contribute to adverse health effects.
B The ISA is available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546
c The ISA evaluates the health evidence associated with different health effects, assigning one of five "weight of
evidence" determinations: causal relationship, likely to be a causal relationship, suggestive of a causal relationship,
inadequate to infer a causal relationship, and not likely to be a causal relationship. For definitions of these levels of
evidence, please refer to Section 1.5 of the ISA.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
causally associated with short-term exposure to PM2.5.6 It also concludes that respiratory effects
are likely to be causally associated with short-term exposure to PM2.s, including respiratory
emergency department (ED) visits and hospital admissions for chronic obstructive pulmonary
disease (COPD), respiratory infections, and asthma; and exacerbation of respiratory symptoms in
asthmatic children.
With respect to effects associated with long-term exposure to PM2.s, the ISA concludes
that there are causal associations between long-term exposure to PM2.5 and cardiovascular
effects, such as the development/progression of cardiovascular disease (CVD), and premature
mortality, particularly from cardiopulmonary causes.7 It also concludes that long-term exposure
to PM2.5 is likely to be causally associated with respiratory effects, such as reduced lung function
growth, increased respiratory symptoms, and asthma development. The ISA characterizes the
evidence as suggestive of a causal relationship for associations between long-term PM2.5
exposure and reproductive and developmental outcomes, such as low birth weight and infant
mortality. It also characterizes the evidence as suggestive of a causal relationship between PM2.5
and cancer incidence, mutagenicity, and genotoxicity.
With respect to effects associated with PMio-2.5, the ISA summarizes evidence related to
short-term exposure to PMio-2.5. PMio-2.5 is the fraction of PMio particles that is larger than
PM2.5.8 The ISA concludes that available evidence is suggestive of a causal relationship
between short-term exposures to PM 10-2.5 and cardiovascular effects, such as hospitalizations for
ischemic heart disease. It also concludes that the available evidence is suggestive of a causal
relationship between short-term exposures to PM 10-2.5 and respiratory effects, including
respiratory-related ED visits and hospitalizations and pulmonary inflammation. The ISA also
concludes that the available literature suggests a causal relationship between short-term
exposures to PM 10-2.5 and mortality. Data are inadequate to draw conclusions regarding health
effects associated with long-term exposure to PMio-2.5.9
Finally, with respect to effects associated with ultrafine particles, the ISA concludes that
the evidence is suggestive of a causal relationship between short-term exposures to UFPs and
cardiovascular effects, including changes in heart rhythm and vasomotor function (the ability of
blood vessels to expand and contract).10 The ISA also concludes that there is suggestive
evidence of a causal relationship between short-term UFP exposure and respiratory effects. The
types of respiratory effects examined in epidemiologic studies include respiratory symptoms and
asthma hospital admissions, the results of which are not entirely consistent. There is evidence
from toxicological and controlled human exposure studies that exposure to UFPs may increase
lung inflammation and produce small asymptomatic changes in lung function. Data are
inadequate to draw conclusions regarding health effects associated with long-term exposure to
UFPs"
5.2.2 Ozone
are to ambient <
health effects are well documented and are critically assessed in the EPA ozone air quality
Exposure to ambient ozone contributes to a wide range of adverse health effects.0 These
D Human exposure to ozone varies over time due to changes in ambient ozone concentration and because people
move between locations which have notable different ozone concentrations. Also, the amount of ozone delivered to
the lung is not only influenced by the ambient concentrations but also by the individuals breathing route and rate.
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1 O 1 Q
criteria document (ozone AQCD) and EPA staff paper. ' This summary is based on the data
and conclusions in the ozone AQCD and staff paper, regarding the health effects associated with
ozone exposure. Interested readers should refer to that document for more detailed information.
Ozone-related health effects include lung function decrements, respiratory symptoms,
aggravation of asthma, increased hospital and emergency room visits, increased asthma
medication usage, and a variety of other respiratory effects. Cellular-level effects, such as
inflammation of lungs, have been documented as well. In addition, there is suggestive evidence
of a contribution of ozone to cardiovascular-related morbidity and highly suggestive evidence
that short-term ozone exposure directly or indirectly contributes to non-accidental and
cardiopulmonary-related mortality, but additional research is needed to clarify the underlying
mechanisms causing these effects. In a recent report on the estimation of ozone-related
premature mortality published by the National Research Council (NRC), a panel of experts and
reviewers concluded that short-term exposure to ambient ozone is likely to contribute to
premature deaths and that ozone-related mortality should be included in estimates of the health
benefits of reducing ozone exposure.14 People who appear to be more susceptible to effects
associated with exposure to ozone include children, asthmatics and the elderly. Those with
greater exposures to ozone, for instance due to time spent outdoors (e.g., children and outdoor
workers), are also of concern.
Based on a large number of scientific studies, EPA has identified several key health
effects associated with exposure to levels of ozone found today in many areas of the country.
Short-term (1 to 3 hours) and prolonged exposures (6 to 8 hours) to ambient ozone
concentrations have been linked to lung function decrements, respiratory symptoms, increased
hospital admissions and emergency room visits for respiratory problems.15'16'17'18'19'20
Repeated exposure to ozone can increase susceptibility to respiratory infection and lung
91 99 9^ 9/1 9S
inflammation and can aggravate preexisting respiratory diseases, such as asthma. ' ' ' '
Repeated exposure to sufficient concentrations of ozone can also cause inflammation of the lung,
impairment of lung defense mechanisms, and possibly irreversible changes in lung structure,
which over time could affect premature aging of the lungs and/or the development of chronic
r\r r\-j fjc, /JQ
respiratory illnesses, such as emphysema and chronic bronchitis. ' ' '
Children and adults who are outdoors and active during the summer months, such as
construction workers, are among those most at risk of elevated ozone exposures.30 Children and
outdoor workers tend to have higher ozone exposure because they typically are active outside,
working, playing and exercising, during times of day and seasons (e.g., the summer) when ozone
levels are highest.31 For example, summer camp studies in the Eastern United States and
Southeastern Canada have reported statistically significant reductions in lung function in
children who are active outdoors.32'33'34'35'36' 7'3 '39 Further, children are more at risk of
experiencing health effects from ozone exposure than adults because their respiratory systems
are still developing. These individuals (as well as people with respiratory illnesses, such as
asthma, especially asthmatic children) can experience reduced lung function and increased
respiratory symptoms, such as chest pain and cough, when exposed to relatively low ozone levels
during prolonged periods of moderate exertion.40'41'42'43
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5.2.3 Nitrogen Oxides
Information on the health effects of NC>2 can be found in the EPA Integrated Science
ment (ISA) for Nitn
more detailed information.
Assessment (ISA) for Nitrogen Oxides.44 Interested readers should refer to that document for
The EPA has concluded that the findings of epidemiologic, controlled human exposure,
and animal toxicological studies provide evidence that is sufficient to infer a likely causal
relationship between respiratory effects and short-term NC>2 exposure. The ISA concludes that
the strongest evidence for such a relationship comes from epidemiologic studies of respiratory
effects including symptoms, emergency department visits, and hospital admissions. The ISA
also draws two broad conclusions regarding airway responsiveness following NC>2 exposure.
First, the ISA concludes thatNC^ exposure may enhance the sensitivity to allergen-induced
decrements in lung function and increase the allergen-induced airway inflammatory response
following 30-minute exposures of asthmatics to NC>2 concentrations as low as 0.26 ppm. In
addition, small but significant increases in non-specific airway hyperresponsiveness were
reported following 1-hour exposures of asthmatics to 0.1 ppm NC>2. Second, exposure to NC>2
has been found to enhance the inherent responsiveness of the airway to subsequent nonspecific
challenges in controlled human exposure studies of asthmatic subjects. Enhanced airway
responsiveness could have important clinical implications for asthmatics since transient increases
in airway responsiveness following NC>2 exposure have the potential to increase symptoms and
worsen asthma control. Together, the epidemiologic and experimental data sets form a plausible,
consistent, and coherent description of a relationship between NC>2 exposures and an array of
adverse health effects that range from the onset of respiratory symptoms to hospital admission.
Although the weight of evidence supporting a causal relationship is somewhat less certain
than that associated with respiratory morbidity, NC>2 has also been linked to other health
endpoints. These include all-cause (nonaccidental) mortality, hospital admissions or emergency
department visits for cardiovascular disease, and decrements in lung function growth associated
with chronic exposure.
5.2.4 Sulfur Oxides
This section provides an overview of the health effects associated with 862. Additional
information on the health effects of SC>2 can be found in the EPA Integrated Science Assessment
for Sulfur Oxides.45 Interested readers should refer to that document for more detailed
information.
Following an extensive evaluation of health evidence from epidemiologic and laboratory
studies, the U.S. EPA has concluded that there is a causal relationship between respiratory health
effects and short-term exposure to SO2. The immediate effect of SO2 on the respiratory system
in humans is bronchoconstriction. Asthmatics are more sensitive to the effects of SO2 likely
resulting from preexisting inflammation associated with this disease. In laboratory studies
involving controlled human exposures to 862, respiratory effects have consistently been
observed following 5-10 min exposures at SC>2 concentrations > 0.4 ppm in asthmatics engaged
in moderate to heavy levels of exercise, with more limited evidence of respiratory effects among
exercising asthmatics exposed to concentrations as low as 0.2-0.3 ppm. A clear concentration-
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response relationship has been demonstrated in these studies following exposures to SO2 at
concentrations between 0.2 and 1.0 ppm, both in terms of increasing severity of respiratory
symptoms and decrements in lung function, as well as the percentage of asthmatics adversely
affected.
In epidemiologic studies, respiratory effects have been observed in areas where the mean
24-hour SC>2 levels range from 1 to 30 ppb, with maximum 1 to 24-hour average 862 values
ranging from 12 to 75 ppb. Important new multicity studies and several other studies have found
an association between 24-hour average ambient SC>2 concentrations and respiratory symptoms
in children, particularly those with asthma. Generally consistent associations also have been
observed between ambient 862 concentrations and emergency department visits and
hospitalizations for all respiratory causes, particularly among children and older adults (> 65
years), and for asthma. A limited subset of epidemiologic studies have examined potential
confounding by copollutants using multipollutant regression models. These analyses indicate
that although copollutant adjustment has varying degrees of influence on the 862 effect
estimates, the effect of 862 on respiratory health outcomes appears to be generally robust and
independent of the effects of gaseous and particulate copollutants, suggesting that the observed
effects of SC>2 on respiratory endpoints occur independent of the effects of other ambient air
pollutants.
Consistent associations between short-term exposure to 862 and mortality have been
observed in epidemiologic studies, with larger effect estimates reported for respiratory mortality
than for cardiovascular mortality. While this finding is consistent with the demonstrated effects
of 862 on respiratory morbidity, uncertainty remains with respect to the interpretation of these
associations due to potential confounding by various copollutants. The U.S. EPA has therefore
concluded that the overall evidence is suggestive of a causal relationship between short-term
exposure to SO2 and mortality. Significant associations between short-term exposure to SO2 and
emergency department visits and hospital admissions for cardiovascular diseases have also been
reported. However, these findings have been inconsistent across studies and do not provide
adequate evidence to infer a causal relationship between SC>2 exposure and cardiovascular
morbidity.
5.2.5 Air Toxics
Motor vehicle emissions, including emissions from Great Lakes vessels, contribute to
ambient levels of air toxics known or suspected as human or animal carcinogens, or that have
noncancer health effects.
The population experiences an elevated risk of cancer and other noncancer health effects
from exposure to air toxics.46 These compounds include, but are not limited to, benzene, 1,3-
butadiene, formaldehyde, acetaldehyde, acrolein, diesel particulate matter and exhaust organic
gases, polycyclic organic matter (POM), and naphthalene. All of these air toxics are present in
emissions from diesel engines.
These compounds were identified as national or regional risk drivers or contributors in
the 2005 National-scale Air Toxics Assessment (NATA) and have significant inventory
contributions from mobile sources. Although the 2005 NATA did not quantify cancer risks
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
associated with exposure to diesel exhaust, EPA has concluded that diesel exhaust ranks with the
other emissions that the 2005 NATA suggests pose the greatest relative risk. According to
NATA for 2005, mobile sources were responsible for 43 percent of outdoor toxic emissions and
over 50 percent of the cancer risk and noncancer hazard attributable to direct emissions from
mobile and stationary sources.E
Noncancer health effects can result from chronic,F subchronic,G or acuteH inhalation
exposures to air toxics, and include neurological, cardiovascular, liver, kidney, and respiratory
effects as well as effects on the immune and reproductive systems. According to the 2005
NATA, about three-fourths of the U.S. population was exposed to an average concentration of
air toxics that has the potential for adverse noncancer respiratory health effects. This will
continue to be the case in 2030, even though toxics concentrations will be lower.47
The NATA modeling framework has a number of limitations which prevent its use as the
sole basis for setting regulatory standards. These limitations and uncertainties are discussed on
the 2005 NATA website.48 Even so, this modeling framework is very useful in identifying air
toxic pollutants and sources of greatest concern, setting regulatory priorities, and informing the
decision making process.
5.2.5.1 Potential Cancer Effects of Exposure to Diesel Exhaust
Exposure to diesel exhaust is of specific concern because it has been judged by EPA to
pose a lung cancer hazard for humans at environmental levels of exposure.
EPA's 2002 final "Health Assessment Document for Diesel Engine Exhaust" (the EPA
Diesel HAD) classified exposure to diesel exhaust as likely to be carcinogenic to humans by
inhalation at environmental exposures, in accordance with the revised draft 1996/1999 EPA
cancer guidelines.49'50 In accordance with earlier EPA guidelines, exposure to diesel exhaust
would similarly be classified as probably carcinogenic to humans (Group Bl).51'52 A number of
other agencies (National Institute for Occupational Safety and Health, the International Agency
for Research on Cancer, the World Health Organization, California EPA, and the U.S.
Department of Health and Human Services) have made similar classifications.53' 54>55>56'57 The
Health Effects Institute has prepared numerous studies and reports on the potential
carcinogenicity of exposure to diesel exhaust.58'59'60
More specifically, the EPA Diesel HAD states that the conclusions of the document apply
to diesel exhaust in use today including both on-road and nonroad engines, such as those in Great
E NATA also includes estimates of risk attributable to background concentrations, which includes contributions
from long-range transport, persistent air toxics, and natural sources; as well as secondary concentrations, where
toxics are formed via secondary formation. Mobile sources substantially contribute to long-range transport and
secondarily formed air toxics.
F Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database
(http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than approximately
10% of the life span in humans (more than approximately 90 days to 2 years in typically used laboratory animal
species).
G Defined in the IRIS database as exposure to a substance spanning approximately 10% of the lifetime of an
organism.
H Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.
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Lakes vessels. The EPA Diesel HAD acknowledges that the studies were done on engines with
generally older technologies and that "there have been changes in the physical and chemical
composition of some diesel exhaust emissions (onroad vehicle emissions) overtime, though
there is no definitive information to show that the emission changes portend significant
toxicological changes."
For the Diesel HAD, EPA reviewed 22 epidemiologic studies on the subject of the
carcinogenicity of exposure to diesel exhaust in various occupations, finding increased lung
cancer risk, although not always statistically significant, in 8 out of 10 cohort studies and 10 out
of 12 case-control studies which covered several industries. Relative risk for lung cancer,
associated with exposure, ranged from 1.2 to 1.5, although a few studies show relative risks as
high as 2.6. Additionally, the Diesel HAD also relied on two independent meta-analyses, which
examined 23 and 30 occupational studies respectively, and found statistically significant
increases of 1.33 to 1.47 in smoking-adjusted relative lung cancer risk associated with diesel
exhaust. These meta-analyses demonstrate the effect of pooling many studies and in this case
show the positive relationship between diesel exhaust exposure and lung cancer across a variety
of diesel exhaust-exposed occupations.61'62'63
EPA generally derives cancer unit risk estimates to calculate population risk more
precisely from exposure to carcinogens. In the simplest terms, the cancer unit risk is the
increased risk associated with average lifetime exposure of 1 |ig/m3. EPA concluded in the
Diesel HAD that it is not currently possible to calculate a cancer unit risk for diesel exhaust due
to a variety of factors that limit the current studies, such as a lack of standard exposure metric for
diesel exhaust and the absence of quantitative exposure characterization in retrospective studies.
In the absence of a cancer unit risk, the Diesel HAD sought to provide additional insight
into the significance of the diesel exhaust-cancer hazard by estimating possible ranges of risk
that might be present in the population. An exploratory analysis was used to characterize a
possible risk range by comparing a typical environmental exposure level for highway diesel
sources to a selected range of occupational exposure levels. The occupationally observed risks
were then proportionally scaled according to the exposure ratios to obtain an estimate of the
possible environmental risk. If the occupational and environmental exposures are similar, the
environmental risk would approach the risk seen in the occupational studies whereas a much
higher occupational exposure indicates that the environmental risk is lower than the occupational
risk. A comparison of environmental and occupational exposures showed that for certain
occupations the exposures are similar to environmental exposures while, for others, they differ
by a factor of about 200 or more.
A number of calculations are involved in the exploratory analysis of a possible risk range,
and these can be seen in the EPA Diesel HAD. The outcome was that environmental risks from
diesel exhaust exposure could range from a low of 10"4 to 10"5 to as high as 10"3, reflecting the
range of occupational exposures that could be associated with the relative and absolute risk
levels observed in the occupational studies. Because of uncertainties, the analysis acknowledged
that the risks could be lower than 10"4 or 10"5, and a zero risk from diesel exhaust exposure was
not ruled out.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
EPA recently assessed air toxic emissions and their associated risk (the 2005 NATA), and
we concluded that diesel exhaust ranks with other emissions that the national-scale assessment
suggests pose the greatest relative risk.64 This national assessment estimates average population
inhalation exposures to DPM for nonroad as well as on-highway sources. These are the sum of
ambient levels in various locations weighted by the amount of time people spend in each of the
locations.
In summary, even though EPA does not have a specific carcinogenic potency with which
to accurately estimate the carcinogenic impact of exposure to diesel exhaust, the likely hazard to
humans together with the potential for significant environmental risks leads us to conclude that
diesel exhaust emissions present public health issues of concern.
5.2.5.2 Other Health Effects of Exposure to Diesel Exhaust
Noncancer health effects of acute and chronic exposure to diesel exhaust emissions are
also of concern to the EPA. The Diesel HAD established an inhalation Reference Concentration
(RfC) specifically based on animal studies of diesel exhaust exposure. An RfC is defined by
EPA as "an estimate of a continuous inhalation exposure to the human population, including
sensitive subgroups, with uncertainty spanning perhaps an order of magnitude, which is likely to
be without appreciable risks of deleterious noncancer effects during a lifetime." EPA derived the
RfC from consideration of four well-conducted chronic rat inhalation studies showing adverse
pulmonary effects.65'66'67'68 The diesel RfC is based on a "no observable adverse effect" level of
144 |ig/m3 that is further reduced by applying uncertainty factors of 3 for interspecies
extrapolation and 10 for human variations in sensitivity. The resulting RfC derived in the Diesel
HAD is 5 |ig/m3 for diesel exhaust as measured by DPM. This RfC does not consider allergenic
effects such as those associated with asthma or immunologic effects. There is growing evidence
that exposure to diesel exhaust can exacerbate these effects, but the exposure-response data is
presently lacking to derive an RfC. The EPA Diesel HAD states, "With DPM [diesel particulate
matter] being a ubiquitous component of ambient PM, there is an uncertainty about the adequacy
of the existing DE [diesel exhaust] noncancer database to identify all of the pertinent DE-caused
noncancer health hazards."
While there have been relatively few human studies associated specifically with the
noncancer impact of exposure to DPM alone, DPM is a component of the ambient particles
studied in numerous epidemiologic studies. The conclusion that health effects associated with
ambient PM in general are relevant to DPM is supported by studies that specifically associate
observable human noncancer health effects with exposure to DPM. As described in the Diesel
HAD, these studies identified some of the same health effects reported for ambient PM, such as
respiratory symptoms (cough, labored breathing, chest tightness, wheezing), and chronic
respiratory disease (cough, phlegm, chronic bronchitis and suggestive evidence for decreases in
pulmonary function). Symptoms of immunological effects such as wheezing and increased
allergenicity are also seen. Studies in rodents, especially rats, show the potential for human
inflammatory effects in the lung and consequential lung tissue damage from chronic diesel
exhaust inhalation exposure. The Diesel HAD concludes "that acute exposure to DE [diesel
exhaust] has been associated with irritation of the eye, nose, and throat, respiratory symptoms
(cough and phlegm), and neurophysiological symptoms such as headache, lightheadedness,
nausea, vomiting, and numbness or tingling of the extremities."69 There is also evidence for an
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immunologic effect such as the exacerbation of allergenic responses to known allergens and
asthma-like symptoms.70'71'72
The Diesel HAD briefly summarizes health effects associated with ambient PM and
discusses the PM2.5 NAAQS. There is a much more extensive body of human data, which is also
mentioned earlier in the health effects discussion for PM2.5 (Section 5.2.1 of this document),
showing a wide spectrum of adverse health effects associated with exposure to ambient PM, of
which diesel exhaust is an important component. The PM2.5 NAAQS is designed to provide
protection from the non-cancer and premature mortality effects of PM2.5 as a whole.
5.2.5.3 Ambient Levels of Diesel Exhaust PM
Because DPM is part of overall ambient PM and cannot be easily distinguished from
overall PM, we do not have direct measurements of DPM in the ambient air. DPM
concentrations are estimated using ambient air quality modeling based on DPM emission
inventories. DPM concentrations were recently estimated as part of the 2005 NATA.73 Ambient
impacts of mobile source emissions were predicted using the Assessment System for Population
Exposure Nationwide (ASPEN) dispersion model.
Concentrations of DPM were calculated at the census tract level in the 2005 NATA.
Table 5-1 below summarizes the distribution of ambient DPM concentrations at the national
scale. The median DPM concentration calculated nationwide is 0.53 ug/m3. A map of ambient
diesel PM concentrations is provided in Figure 5-1. The Great Lakes region contains areas with
high median concentrations.
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Figure 5-1 Estimated Ambient Concentration of Diesel Participate Matter
2005 NATA Estimated Tract Level Total Diesel PM Concentration
Table 5-1 Distribution of Census Tract Ambient Concentrations of DPM at the National Scale in 2005 NATAa
5m Percentile
25th Percentile
Median
75th Percentile
95th Percentile
NATIONWIDE (MG/MJ)
0.03
0.17
0.53
1.22
2.91
Note:
a This table is generated from data contained in the diesel paniculate matter Microsoft Access
database file found in the Tract-Level Ambient Concentration Summaries section of the 2005
NATA webpage (http://www.epa.gov/ttn/atw/nata2005/tables.html).
5.2.5.4 Exposure to Diesel Exhaust PM
Exposure of people to diesel exhaust depends on their various activities, the time spent in
those activities, the locations where these activities occur, and the levels of diesel exhaust
pollutants in those locations. The major difference between ambient levels of diesel particulate
and exposure levels for diesel particulate is that exposure levels account for a person moving
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from location to location, the proximity to the emission source, and whether the exposure occurs
in an enclosed environment.
Occupational exposures to diesel exhaust from mobile sources can be several orders of
magnitude greater than typical exposures in the non-occupationally exposed population. Over
the years, diesel particulate exposures have been measured for a number of occupational groups
resulting in a wide range of exposures from 2 to 1280 |ig/m3 for a variety of occupations. As
discussed in the Diesel HAD, the National Institute of Occupational Safety and Health (NIOSH)
has estimated a total of 1,400,000 workers are occupationally exposed to diesel exhaust from on-
road and nonroad vehicles.
In addition, due to the nature of marine ports, emissions from a large number of diesel
engines are concentrated in a small area. As a result, regions immediately downwind of marine
ports may experience elevated ambient concentrations of directly-emitted PM2.5 from diesel
engines.
5.3 Environmental Effects Associated with Exposure to Pollutants
In addition to their impacts on human health, ambient levels of PM, NOx, SOx, and
ozone can also contribute to serious environmental impacts. These environmental impacts are
summarized in this section, including impacts that are specific to the Great Lakes region.
5.3.1 Atmospheric Deposition of Contaminants
Ship engines emit large amounts of NOx, SOx and direct PM over a wide area.
Depending on prevailing winds and other meteorological conditions, these emissions may be
transported hundreds and even thousands of kilometers across the Great Lakes region and impact
not only ambient air concentrations but also contribute to deposition in many sensitive ecological
areas. The large surface area of the Great Lakes makes them particularly vulnerable to
atmospheric deposition of contaminants.74
Deposition can occur either in a wet or dry form. Wet deposition includes rain, snow,
sleet, hail, clouds, or fog. Dry deposition includes gases and dust. The chemical form of
deposition is determined by ambient conditions (e.g., temperature, humidity, oxidant levels) and
the pollutant source. Chemical and physical transformations of ambient particles occur in the
atmosphere and in the media (terrestrial or aquatic) on which they deposit. These
transformations influence the fate, bioavailability and potential toxicity of these compounds.
Ships operating on high sulfur fuel emit both SO2 and sulfate PM. The sulfur in marine
fuel is primarily emitted as sulfur dioxide (802), with a small fraction (about two percent) being
converted to sulfur trioxide (SOs).75 SOs almost immediately forms sulfate, which is emitted as
primary PM by the engine, and consists of carbonaceous material, sulfuric acid, and ash (trace
metals). These particles also react in the atmosphere to form secondary PM, such as sulfuric acid
aerosols or sulfate particles.
Ships also emit large amounts of nitric oxide (NO) and nitrogen dioxide (NO2) which are
carried into the atmosphere where they may be chemically altered and transformed into new
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compounds. For example, NO2 can be further oxidized to nitric acid (HNOs) and can also form
ambient particulate nitrate
5.3.2 Nitrogen and Sulfur Deposition
Nitrogen and sulfur interactions in the environment are highly complex. Both are
essential, and sometimes limiting, nutrients needed for growth and productivity. Excess of
nitrogen or sulfur can lead to acidification and nutrient enrichment, which can have significant
ecological impacts. These ecological impacts are described in this section.
5.3.2.1 Acidification and Nutrient Enrichment
Deposition of nitrogen and sulfur species causes acidification, which alters
biogeochemistry and affects animal and plant life in terrestrial and aquatic ecosystems across the
Great Lakes region. Major effects include a decline in sensitive tree species and a loss of
biodiversity of fishes, zooplankton, and macro invertebrates. The sensitivity of terrestrial and
aquatic ecosystems to acidification from nitrogen and sulfur deposition is predominantly
governed by the earth's geology.
Biological effects of acidification in terrestrial ecosystems are generally linked to
aluminum toxicity and decreased ability of plant roots to take up base cations. Decreases in acid
neutralizing capacity and increases in inorganic aluminum concentration also contribute to
declines in zooplankton, macro invertebrates, and fish species richness in aquatic ecosystems.
Across the Great Lakes, ecosystems continue to be acidified by NOx and SOx emissions,
including those from vessels in the Great Lakes.
In addition to the role nitrogen deposition plays in acidification, it also causes ecosystem
nutrient enrichment and eutrophi cation. Nutrient enrichment alters biogeochemical cycles and
harms animal and plant life and alters biodiversity of terrestrial ecosystems, such as forests and
grasslands. Eutrophi cation of estuaries and waterbodies result in toxic algal blooms and fish
kills.
The addition of nitrogen to most ecosystems causes changes in primary productivity and
growth of plants and algae, which can alter competitive interactions among species. Some
species grow more than others, leading to shifts in population dynamics, species composition,
and community structure. The most extreme effects of nitrogen deposition include a shift of
ecosystem types in terrestrial ecosystems, and hypoxic zones that are devoid of life in aquatic
ecosystems.7 Inputs of new nitrogen, i.e., non-recycled mostly anthropogenic in origin, are often
key factors controlling primary productivity in nitrogen-sensitive estuarine and coastal waters.77
Increasing trends in urbanization, agricultural intensity, and industrial expansion have led to
increases in nitrogen deposited from the atmosphere on the order of a factor of 10 in the past 100
years.78 Atmospheric nitrogen is dominated by a number of sources, most importantly
transportation sources, including ships.
Direct and indirect deposition of nitrogen and sulfur to watersheds depends on air
pollutant concentrations in the airshed above the watershed. The shape and extent of the airshed
is quite different from that of the watershed. In a watershed, everything that falls in its area, by
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definition, flows into a single body of water. An airshed, by contrast, is a theoretical concept
that defines the source area containing the emissions contributing a given level, often 75 percent,
to the deposition in a particular watershed or to a given water body. Hence, airsheds are
modeled domains containing the sources estimated to contribute a given level of deposition from
each pollutant of concern. The principal NOx airsheds and corresponding watersheds for several
regions in the eastern U.S. are shown in Figure 5-2.79 These airsheds include much of the Great
Lakes. In addition, airsheds for other regions in the U.S., which would include the rest of the
Great Lakes, are not shown on this figure.
Figure 5-2 Principal Airsheds and Watersheds for Oxides of Nitrogen for Estuaries. Hudson/Raritan Bay;
Chesapeake Bay; Pamlico Sound; and Altamaha Sound (listed from north to south)
5.3.2.2 Ecological Effects of Acidification
The principal factor governing the sensitivity of terrestrial and aquatic ecosystems to
acidification from nitrogen and sulfur deposition is geology (particularly surficial geology).80
Geologic formations having low base cation supply generally underlie the watersheds of acid-
sensitive lakes and streams. Bedrock geology has been used in numerous acidification
studies.81'82'83'84'85 Other factors contributing to the sensitivity of soils and surface waters to
acidifying deposition, include: topography, soil chemistry, land use, and hydrologic flow path.
5.3.2.2.1 Terrestrial Ecosystems
Figure 5-3 depicts areas across the U.S. that are potentially sensitive to terrestrial
acidification. Many areas adjacent and nearby to the Great Lakes are in the top quartile for N or S
sensitivity or have been labeled as areas of highest potential sensitivity.
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Figure 5-3 Areas Potentially Sensitive to Terrestrial Acidification
| Area of Higes! Potential Sensitivity
| Top Quartilt N
I Top Quattila S
1.000
D kirt
Acidifying deposition has altered major biogeochemical processes in the U.S., including
the Great Lakes, by increasing the nitrogen and sulfur content of soils, accelerating nitrate and
sulfate leaching from soil to drainage waters, depleting base cations (especially calcium and
magnesium) from soils, and increasing the mobility of aluminum. Inorganic aluminum is toxic
to some tree roots. Plants affected by high levels of aluminum from the soil often have reduced
root growth, which restricts the ability of the plant to take up water and nutrients, especially
calcium.86 These direct effects can influence the response of these plants to climatic stresses
such as droughts and cold temperatures. They can also influence the sensitivity of plants to other
stresses, including insect pests and disease87 leading to increased mortality of canopy trees.
Terrestrial effects of acidification are best described for forested ecosystems (especially red
spruce and sugar maple ecosystems) with additional information on other plant communities,
oo
including shrubs and lichen. There are several indicators of stress to terrestrial vegetation
including percent dieback of canopy trees, dead tree basal area (as a percent), crown vigor index
and fine twig dieback.89
5.3.2.2.2 Health, Vigor, and Reproduction of Tree Species in Forests
Both coniferous and deciduous forests throughout the eastern U.S., including the Great
Lakes region, are experiencing gradual losses of base cation nutrients from the soil due to
accelerated leaching for acidifying deposition. This change in nutrient availability may reduce
the quality of forest nutrition over the long term. Evidence suggests that red spruce and sugar
maple in some areas in the eastern U.S. have experienced declining health as a consequence of
this deposition. Figure 5-4 shows the distribution of red spruce (brown) and sugar maple (green)
in the eastern U.S. For red spruce, dieback or decline has been observed across high elevation
landscapes of the northeastern U.S., and to a lesser extent, the southeastern U.S. Acidifying
deposition has been implicated as a causal factor.90 Since the 1980s, red spruce growth has
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
increased at both the higher- and lower-elevation sites corresponding to a decrease in SO2
emissions in the U.S. (to about 20 million tons/year by 2000), while NOx emissions held fairly
steady (at about 25 million tons/year). Research indicates that annual emissions of sulfur plus
NOx explained about 43 percent of the variability in red spruce tree ring growth between 1940
and 1998, while climatic variability accounted for about 8 percent of the growth variation for that
period.91 The observed dieback in red spruce has been linked, in part, to reduced cold tolerance
of the spruce needles, caused by acidifying deposition. Results of controlled exposure studies
showed that acidic mist or cloud water reduced the cold tolerance of current-year needles by 3 to
Q9
10ฐ F. More recently, studies have found a link between availability of soil calcium and winter
93
injury.
Figure 5-4 Distribution of Red Spruce (pink) and Sugar Maple (green) in the Eastern U.S.
94
Sugar maple is the deciduous tree species, whose range includes the Great Lakes region
(See Figure 5-4), that is most commonly associated with adverse acidification-related effects of
nitrogen and sulfur deposition.95 In general, evidence indicates that acidifying deposition in
combination with other stressors is a likely contributor to the decline of sugar maple trees that
occur at higher elevation, on geologies dominated by sandstone or other base-poor substrate, and
that have base-poor soils having high percentages of rock fragments.96
In hardwood forests, species nutrient needs, soil conditions, and additional stressors work
together to determine sensitivity to acidifying deposition. Stand age and successional stage also
can affect the susceptibility of hardwood forests to acidification effects. In northeastern
hardwood forests, older stands exhibit greater potential for calcium depletion in response to
acidifying deposition than younger stands. Thus, with the successional change from pin cherry,
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
striped maple, white ash, yellow birch and white birch in younger stands to beech and red maple
in older stands, there is an increase in sensitivity to acidification.97
Loss of calcium ions in the base cations has also been implicated in increased
susceptibility of flowering dogwood to its most destructive disease, dogwood anthracnose, a
mostly fatal disease. Figure 5-5 shows the native range of flowering dogwood in the U.S. (dark
gray) as well as the range of the anthracnose disease as of 2002 in the eastern U.S. (red). The
ranges for the tree species and the disease are within the Great Lakes region. Flowering
dogwood is a dominant understory species of hardwood forests in the eastern U.S.
98
Figure 5-5 Native Range of Flowering Dogwood (dark gray) and the Documented Range of Dogwood
Anthracnose (red)99
5.3.2.2.3 Health and Biodiversity of Other Plant Communities
The U.S. EPA NOXSOX ISA found that available data suggest that it is likely that a
variety of shrub and herbaceous species are sensitive to base cation depletion and/or aluminum
toxicity. The U.S. EPA NOxSOx ISA also found that lichens and bryophytes are among the first
components of the terrestrial ecosystem to be affected by acidifying deposition. Vulnerability of
lichens to increased nitrogen input is generally greater than that of vascular plants.100 Even in
the Pacific Northwest, which receives uniformly low levels of nitrogen deposition - generally
lower than the levels in the Great Lakes - changes from acid-sensitive and nitrogen-sensitive to
pollution tolerant nitrophillic lichen taxa are occurring in some areas.101'102 Lichens remaining in
areas affected by acidifying deposition were found to contain almost exclusively the families
Candelariaccae, Physciaceae, and Teloschistaceae, which are pollution tolerant species.103
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5.3.2.2.4 Aquatic Ecosystems
A number of national and regional assessments have been conducted to estimate the
distribution and extent of surface water acidity in the us.104'105'106'107'108'109'110'111 >112 As a result,
several regions of the U.S. have been identified as containing a large number of lakes and
streams which are seriously impacted by acidification. Figure 5-6 illustrates those areas of the
U.S. where aquatic ecosystems are at risk from acidification. These sensitive ecological regions
include portions of the northwest Great Lakes and areas nearby or adjacent to the eastern Great
Lakes.
Figure 5-6 Areas Potentially Sensitive to Aquatic Acidification
^H H'3h Potential Senwivity
Acid Sensitive Waters : USCS >
_l States
1.000
i -in-
Aquatic effects of acidification have been well studied in the U.S. and elsewhere at
various trophic levels. These studies indicate that aquatic biota have been affected by
acidification at virtually all levels of the food web in acid sensitive aquatic ecosystems. Effects
have been most clearly documented for fish, aquatic insects, other invertebrates, and algae.
Biological effects are primarily attributable to a combination of low pH and high
inorganic aluminum concentrations. Such conditions occur more frequently during rainfall and
snowmelt that cause high flows of water and less commonly during low-flow conditions, except
where chronic acidity conditions are severe. Biological effects of episodes include reduced fish
condition factor, changes in species composition and declines in aquatic species richness across
multiple taxa, ecosystems and regions. These conditions may also result in direct mortality.113
Biological effects in aquatic ecosystems can be divided into two major categories: effects on
health, vigor, and reproductive success; and effects on biodiversity.
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5.3.2.3 Ecological Effects of Nutrient Enrichment
In general, ecosystems that are most responsive to nutrient enrichment from atmospheric
nitrogen deposition are those that receive high levels of nitrogen loading, are nitrogen-limited, or
contain species that have evolved in nutrient-poor environments. Species that are adapted to low
nitrogen supply will often be more readily outcompeted by species that have higher nitrogen
demands when the availability of nitrogen is increased.114'115'116'117 As a consequence, some
native species can be eliminated by nitrogen deposition.118'119'120'121 Note the terms "low" and
"high" are relative to the amount of bioavailable nitrogen in the ecosystem and the level of
deposition.
5.3.2.3.1 Terrestrial Ecosystems
Nitrogen deposition affects terrestrial ecosystems throughout large areas of the U.S.,
including in the Great Lakes region.122 Atmospheric nitrogen deposition is the main source of
new nitrogen in many terrestrial ecosystems throughout the U.S. 23 Figure 5-7 depicts those
ecosystems potentially sensitive to terrestrial nutrient enrichment resulting from nitrogen
deposition, including nitrogen deposition from ships.
Severe symptoms of nutrient enrichment or nitrogen saturation, have been observed in
areas adjacent to and nearby the Great Lakes including in high-elevation spruce-fir ecosystems in
the Appalachian Mountains;124 in spruce-fir ecosystems throughout the northeastern U.S.;125'126
and in lower-elevation eastern U.S. forests.127'128'129'130 In general, it is believed that deciduous
forest stands in the eastern U.S. have not progressed toward nitrogen saturation as rapidly or as
far as coniferous stands in the eastern U.S.131
Figure 5-7 Areas Potentially Sensitive to Terrestrial Nutrient Enrichment
| High Potential
Aodoprtylic Lehen
25D SOO 750 I.OIOkm
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Ecological effects of nitrogen deposition occur in a variety of taxa and ecosystem types
including: forests, grasslands, arid and semi-arid areas, deserts, lichens, alpine, and mycorrhizae.
Atmospheric inputs of nitrogen can alleviate deficiencies and increase growth of some plants at
the expense of others. Nitrogen deposition alters the competitive relationships among terrestrial
plant species and therefore alters species composition and diversity.132'133'134 Wholesale shifts in
species composition are easier to detect in short-lived terrestrial ecosystems such as annual
grasslands, in the forest understory, or mycorrhizal associations, than for long-lived forest trees
where changes are evident on a decade or longer time scale. Note species shifts and ecosystem
changes can occur even if the ecosystem does not exhibit signs of nitrogen saturation.
There are a number of important quantified relationships between nitrogen deposition
levels and ecological effects.135 Certain lichen species are the most sensitive terrestrial taxa to
nitrogen in the U.S. with clear adverse effects occurring at just 3 kg N/ha/yr. Figure 5-7 shows
the geographic distribution of lichens in the U.S. Among the most sensitive U.S. ecosystems are
Alpine ecosystems where alteration of plant covers of an individual species (Carex rupestris)
was estimated to occur at deposition levels near 4 kg N/ha/yr and modeling indicates that
deposition levels near 10 kg/N/ha/yr alter plant community assemblages.136 Within grasslands,
the onset of declining biodiversity was found to occur at levels of 5 kg N/ha/yr. Forest
encroachment into temperate grasslands was found at 10 kg N/ha/yr and above in the U.S. Table
5-2 provides a brief list of nitrogen deposition levels and associated ecological effects.
Table 5-2 Examples of Quantified Relationship between Nitrogen Deposition Levels and Ecological Effects
Kg
N.ha/vr
-1.5
3.1
4
5
5.6 - 10
5-10
5-15
Ecological effect
Altered diatom communities in high
elevation freshwater lakes and elevated
nitrogen in tree leaf tissue high elevation
forests in the U.S.
Decline of some lichen specie; in the
Western U.S. (critical load)
Altered growth and coverage of alpine
plant species in U.S.
Onset of decline of species richness in
grasslands of the U.S. and U.K.
Onset of nitrate leadline in Eastern
forests of the U.S.
Multiple effects in tundra, boss and
freshwater lakes in Europe (critical loads)
Multiple effects in arctic, alpine.
subalpine and scrub habitats in Europe
(critical loads)
Source: EPA, Integrated Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological criteria
Most terrestrial ecosystems are nitrogen-limited, therefore they are sensitive to
perturbation caused by nitrogen additions.137 The factors that govern the vulnerability of
terrestrial ecosystems to nutrient enrichment from nitrogen deposition include the degree of
nitrogen limitation, rates and form of nitrogen deposition, elevation, species composition, length
of growing season, and soil nitrogen retention capacity.
In the eastern U.S., the degree of nitrogen saturation of the terrestrial ecosystem is often
assessed in terms of the degree of nitrate leaching from watershed soils into ground water or
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surface water. Studies have estimated the number of surface waters at different stages of
1 Q Q
saturation across several regions in the eastern U.S. Of the 85 northeastern watersheds
examined, 40 percent were in nitrogen-saturation Stage O,1 52 percent in Stage 1, and 8 percent
in Stage 2. Of the northeastern sites for which adequate data were available for assessment,
those in Stage 1 or 2 were most prevalent in the Adirondack and Catskill Mountains in the State
of New York.
5.3.2.3.2 Aquatic Ecosystems
Aquatic nutrient enrichment impacts a wide range of waters within the U.S., and within
the Great Lakes region, from wetlands, to streams, rivers, and lakes. All are vital ecosystems
and all are impacted by ship emissions that contribute to the annual total nitrogen deposition.
Nitrogen deposition is the main source of nitrogen for many surface waters in the U.S. including
headwater streams, lower order streams, and high elevation lakes.139'140 Nitrogen deposition
alters species richness, species composition and biodiversity in freshwater aquatic ecosystems.141
Increased nitrogen deposition can cause a shift in community composition and reduce
algal biodiversity. Elevated nitrogen deposition results in changes in algal species composition,
especially in sensitive oligotrophic lakes. There are oligotrophic lakes in the Great Lakes region,
including Lake Superior.
Wetlands are found throughout the U.S. and support over 4200 native plant species, of
which 121 have been designated by the U.S. Government as threatened or endangered.142
Freshwater wetlands are particularly sensitive to nutrient enrichment resulting from nitrogen
deposition since they contain a disproportionately high number of rare plant species that have
evolved under nitrogen-limited conditions.143 Freshwater wetlands receive nitrogen mainly from
precipitation, land runoff or ground water.
Fens and bogs are the most vulnerable type of wetland ecosystems with regard to nutrient
enrichment effects of nitrogen deposition.144 In the U.S., they are mostly found in the glaciated
northeast and Great Lakes regions and in the State of Alaska.145 Like bogs, fens are mostly a
northern hemisphere phenomenon, occurring in the northeastern United States, the Great Lakes
region, western Rocky Mountains, and much of Canada, and are generally associated with low
temperatures and short growing seasons where ample precipitation and high humidity cause
excessive moisture to accumulate.146
The third type of wetlands sensitive to nitrogen deposition are marshes, characterized by
emergent soft-stemmed vegetation adapted to saturated soil conditions. There are many different
kinds of marshes in the U.S., ranging from the prairie potholes in the interior of the U.S. to the
Everglades found in the extreme southern portion of the State of Florida. U.S. fresh water
marshes are important for recharging groundwater supplies, and moderating stream flow by
providing water to streams and as habitats for many wildlife species.147
1 In Stage 0, nitrogen inputs are low and there are strong nitrogen limitations on growth. Stage 1 is characterized by
high nitrogen retention and fertilization effect of added nitrogen on tree growth. Stage 2 includes the induction of
nitrification and some nitrate leaching, though growth may still be high. In Stage 3 tree growth declines,
nitrification and nitrate loss continue to increase, but nitrogen mineralization rates begin to decline.
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About 107.7 million acres of wetlands are widely distributed in the conterminous U.S.,
including throughout the Great Lakes region (Figure 5-8). The effect of nitrogen deposition on
these ecosystems depends on the fraction of rainfall in the areas total water budget. Excess
nitrogen deposition can cause shifts in wetland community composition by altering competitive
relationships among species, which potentially leads to effects such as decreasing biodiversity,
increasing non-native species establishment, and increasing the risk of extinction for sensitive
and rare species.
U.S. wetlands contain a high number of rare plant species.148'149' 15ฐ High levels of
atmospheric nitrogen deposition increase the risk of decline and extinction of these species that
are adapted to low nitrogen conditions. In general, these include the genus Isoetes sp., of which
three species are federally endangered; insectivorous plants like the endangered green pitcher
Sarracenia oreophila; and the genus Sphagnum, of which there are 15 species listed as
endangered by eastern U.S. Roundleaf sundew (Drosera rotundifolia) is also susceptible to
elevated atmospheric nitrogen deposition.151 This plant is native to, and broadly distributed
across, the U.S. and is federally listed as endangered in Illinois and Iowa, threatened in
1 S9
Tennessee, and vulnerable in New York. In the U.S., Sarraceniapurpurea can be used as a
biological indicator of local nitrogen deposition in some locations.15
Figure 5-8 Location of Wetlands in Continental U.S.
:'ฃV
5.3.3 Particulate Matter Deposition
Ships emit small amounts of metals and air toxics. The atmospheric deposition of metals
and toxic compounds is implicated in severe ecosystem effects.154 Shipping emissions of PM2.5
contain small amounts of metals: nickel, vanadium, cadmium, iron, lead, copper, zinc, and
aluminum.155'156'157 Investigations of trace metals near roadways and industrial facilities indicate
that a substantial burden of heavy metals can accumulate on vegetative surfaces. Copper, zinc,
and nickel are shown to be directly toxic to vegetation under field conditions.158 While metals
typically exhibit low solubility, limiting their bioavailability and direct toxicity, chemical
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transformations of metal compounds occur in the environment, particularly in the presence of
acidic or other oxidizing species. These chemical changes influence the mobility and toxicity of
metals in the environment. Once taken up into plant tissue, a metal compound can undergo
chemical changes, accumulate and be passed along to herbivores or can re-enter the soil and
further cycle in the environment.
Although there has been no direct evidence of a physiological association between tree
injury and heavy metal exposures, heavy metals have been implicated because of similarities
between metal deposition patterns and forest decline.159 This hypothesized correlation was
further explored in high elevation forests in the northeastern U.S. These studies measured levels
of a group of intracellular compounds found in plants that bind with metals and are produced by
plants as a response to sublethal concentrations of heavy metals. These studies indicated a
systematic and significant increase in concentrations of these compounds associated with the
extent of tree injury. These data strongly imply that metal stress causes tree injury and
contributes to forest decline in Northeast U.S.160 Contamination of plant leaves by heavy metals
can lead to elevated concentrations in the soil. Trace metals absorbed into the plant, frequently
bind to the leaf tissue, and then are lost when the leaf drops. As the fallen leaves decompose, the
heavy metals are transferred into the soil.161'162
Ships also emit air toxics, including polycyclic aromatic hydrocarbons (PAHs) - a class
of polycyclic organic matter (POM) that contain compounds which are known or suspected
carcinogens. Since the majority of PAHs are adsorbed onto particles less than 1.0 um in
diameter, long range transport is possible. Particles of this size can remain airborne for days or
even months and travel distances up to 10,000 km before being deposited on terrestrial or aquatic
surfaces.163'164'165'166'167 Atmospheric deposition of particles is believed to be the major source of
PAHs to the sediments of Lake Michigan in the Great Lakes.168 PAHs tend to accumulate in
sediments and reach high enough concentrations in some coastal environments to pose an
environmental health threat that includes cancer in fish populations, toxicity to organisms living
in the sediment and risks to those (e.g., migratory birds) that consume these organisms.169'170
PAHs tend to accumulate in sediments and bioaccumulate in freshwater, flora and fauna.
The effects of the deposition of atmospheric pollution, including ambient PM, on
materials are related to both physical damage and impaired aesthetic qualities. The deposition of
PM (especially sulfates and nitrates) can physically affect materials, adding to the effects of
natural weathering processes, by potentially promoting or accelerating the corrosion of metals,
by degrading paints, and by deteriorating building materials such as concrete and limestone.
Only chemically active fine particles or hygroscopic coarse particles contribute to these physical
effects. In addition, the deposition of ambient PM can reduce the aesthetic appeal of buildings
and culturally important articles through soiling. Particles consisting primarily of carbonaceous
compounds cause soiling of commonly used building materials and culturally important items
such as statues and works of art.
5.3.4 Impacts of Particles on Visibility
Shipping activity, including that within the Great Lakes, contributes to poor visibility
through their primary PM2.5 emissions as well as NOx and SOx emissions (which contribute to
the formation of secondary PM2.s).171 These airborne particles degrade visibility by scattering
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and absorbing light. Good visibility increases the quality of life where individuals live and work,
and where they engage in recreational activities.
5.3.4.1.1 Visibility Monitoring
In conjunction with the U.S. National Park Service, the U.S. Forest Service, other Federal
land managers, and State organizations in the U.S., the U.S. EPA has supported visibility
monitoring in national parks and wilderness areas, including 3 mandatory class I federal areas
located on the shores of the Great Lakes, since 1988. This long-term visibility monitoring
network is known as IMPROVE (Interagency Monitoring of Protected Visual Environments).
IMPROVE provides direct measurement of fine particles that contribute to visibility
impairment. The IMPROVE network employs aerosol measurements at all sites, and optical and
scene measurements at some of the sites. Aerosol measurements are taken for PMio and PM2.5
mass, and for key constituents of PM2.5, such as sulfate, nitrate, organic and elemental carbon,
soil dust, and several other elements. Measurements for specific aerosol constituents are used to
calculate "reconstructed" aerosol light extinction by multiplying the mass for each constituent by
its empirically-derived scattering and/or absorption efficiency, with adjustment for the relative
humidity. Knowledge of the main constituents of a site's light extinction "budget" is critical for
source apportionment and control strategy development. Optical measurements are used to
directly measure light extinction or its components. Such measurements are taken principally
with either a transmissometer, which measures total light extinction, or a nephelometer, which
measures particle scattering (the largest human-caused component of total extinction). Scene
characteristics are typically recorded three times daily with 35 millimeter photography and are
used to determine the quality of visibility conditions (such as effects on color and contrast)
associated with specific levels of light extinction as measured under both direct and aerosol-
related methods. Directly measured light extinction is used under the IMPROVE protocol to
cross check that the aerosol-derived light extinction levels are reasonable in establishing current
visibility conditions. Aerosol-derived light extinction is used to document spatial and temporal
trends and to determine how proposed changes in atmospheric constituents would affect future
visibility conditions.
Annual average visibility conditions (reflecting light extinction due to both anthropogenic
and non-anthropogenic sources) vary regionally across the U.S. The rural East generally has
higher levels of impairment than remote sites in the West. Higher visibility impairment levels in
the East, including the Great Lakes region, are due to generally higher concentrations of
anthropogenic fine particles, particularly sulfates, and higher average relative humidity levels. In
fact, sulfates account for 60-86 percent of the haziness in eastern sites.172 Aerosol light
extinction due to sulfate on the 20 percent haziest days is significantly larger in eastern class I
areas as compared to western areas (Figures 4-40a and 4-40b in the Air Quality Criteria
Document for Particulate Matter).173
5.3.4.1.2 Addressing Visibility in the U.S.
The U.S. EPA is pursuing a two-part strategy to address visibility. First, EPA has set
secondary PM2.5 standards which act in conjunction with the establishment of a regional haze
program. In setting the secondary PM2.5 standard, EPA concluded that PM2.5 causes adverse
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effects on visibility in various locations, depending on PM concentrations and factors such as
chemical composition and average relative humidity. Second, section 169 of the Clean Air Act
provides additional authority to address existing visibility impairment and prevent future
visibility impairment in the 156 mandatory class I federal areas (62 FR 38680-81, July 18, 1997).
In July 1999, the regional haze rule (64 FR 35714) was put in place to protect the visibility in
mandatory class I federal areas. Visibility can be said to be impaired in both PM2.5
nonattainment areas and mandatory class I federal areas/
5.3.5 Environmental Effects Associated with Ozone
There are a number of environmental or public welfare effects associated with the
presence of ozone in the ambient air.174 Great Lakes vessels emit NOx, which is a precursor to
ozone. In this section, we discuss the impact of ozone on plants, including trees, agronomic
crops and urban ornamentals.
5.3.5.1.1 Impacts of Ozone on Plants and Ecosystems
The Air Quality Criteria Document for Ozone and related Photochemical Oxidants notes
that, "ozone affects vegetation throughout the United States, impairing crops, native vegetation,
and ecosystems more than any other air pollutant".175 Like carbon dioxide (CO2) and other
gaseous substances, ozone enters plant tissues primarily through apertures (stomata) in leaves in
a process called "uptake".176 Once sufficient levels of ozone (a highly reactive substance), or its
reaction products, reaches the interior of plant cells, it can inhibit or damage essential cellular
components and functions, including enzyme activities, lipids, and cellular membranes,
disrupting the plant's osmotic (i.e., water) balance and energy utilization patterns.177'178 If
enough tissue becomes damaged from these effects, a plant's capacity to fix carbon to form
carbohydrates, which are the primary form of energy used by plants is reduced,179 while plant
respiration increases. With fewer resources available, the plant reallocates existing resources
away from root growth and storage, above ground growth or yield, and reproductive processes,
toward leaf repair and maintenance, which leads to reduced growth and/or reproduction. Studies
have shown that plants stressed in these ways may exhibit a general loss of vigor, which can lead
to secondary impacts that modify plants' responses to other environmental factors. Specifically,
plants may become more sensitive to other air pollutants, more susceptible to disease, insect
attack, harsh weather (e.g., drought, frost) and other environmental stresses. Furthermore, there
is evidence that ozone can interfere with the formation of mycorrhiza, essential symbiotic fungi
associated with the roots of most terrestrial plants, by reducing the amount of carbon available
1 Rn 1 & 1
for transfer from the host to the symbiont. '
This ozone damage may or may not be accompanied by visible injury on leaves, and
likewise, visible foliar injury may or may not be a symptom of the other types of plant damage
described above. When visible injury is present, it is commonly manifested as chlorotic or
necrotic spots, and/or increased leaf senescence (accelerated leaf aging). Since ozone damage
1 As mentioned above, the EPA recently amended the PM NAAQS, making the secondary NAAQS equal, in all
respects, to the primary standards for both PM2 5 and PM10, (71 FR 61144, Oct. 17, 2006). In February 2009, the
D.C. Circuit Court remanded the secondary standards for fine particles, based on EPA's failure to adequately
explain why setting the secondary PM2 5 NAAQS equivalent to the primary standards provided the required
protection for public welfare including protection from visibility impairment.
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can consist of visible injury to leaves, it can also reduce the aesthetic value of ornamental
vegetation and trees in urban landscapes, and negatively affect scenic vistas in protected natural
areas.
Ozone can produce both acute and chronic injury in sensitive species depending on the
concentration level and the duration of the exposure. Ozone effects also tend to accumulate over
the growing season of the plant, so that even lower concentrations experienced for a longer
duration have the potential to create chronic stress on sensitive vegetation. Not all plants,
however, are equally sensitive to ozone. Much of the variation in sensitivity between individual
plants or whole species is related to the plant's ability to regulate the extent of gas exchange via
leaf stomata (e.g., avoidance of ozone uptake through closure of stomata)182'183'184 Other
resistance mechanisms may involve the intercellular production of detoxifying substances.
Several biochemical substances capable of detoxifying ozone have been reported to occur in
plants, including the antioxidants ascorbate and glutathione. After injuries have occurred, plants
may be capable of repairing the damage to a limited extent.185
Due to the differing sensitivities among plants to ozone, ozone pollution can also exert a
selective pressure that leads to changes in plant community composition. Given the range of
plant sensitivities and the fact that numerous other environmental factors modify plant uptake
and response to ozone, it is not possible to identify threshold values above which ozone is
consistently toxic for all plants. The next few paragraphs present additional information on
ozone damage to trees, ecosystems, agronomic crops and urban ornamentals.
1 %.f\ 1 R7
Ozone also has been conclusively shown to cause discernible injury to forest trees. '
In terms of forest productivity and ecosystem diversity, ozone may be the pollutant with the
greatest potential for regional-scale forest impacts. Studies have demonstrated repeatedly that
ozone concentrations commonly observed in polluted areas can have substantial impacts on plant
function.188'189
Because plants are at the base of the food web in many ecosystems, changes to the plant
community can affect associated organisms and ecosystems (including the suitability of habitats
that support threatened or endangered species and below ground organisms living in the root
zone). Ozone impacts at the community and ecosystem level vary widely depending upon
numerous factors, including concentration and temporal variation of tropospheric ozone, species
composition, soil properties and climatic factors.190 In most instances, responses to chronic or
recurrent exposure in forested ecosystems are subtle and not observable for many years. These
injuries can cause stand-level forest decline in sensitive ecosystems.191'192'193 It is not yet
possible to predict ecosystem responses to ozone with much certainty; however, considerable
knowledge of potential ecosystem responses has been acquired through long-term observations
in highly damaged forests in the United States.
Laboratory and field experiments have also shown reductions in yields for agronomic
crops exposed to ozone, including vegetables (e.g., lettuce) and field crops (e.g., cotton and
wheat). The most extensive field experiments, conducted under the National Crop Loss
Assessment Network (NCLAN), examined 15 species and numerous cultivars. The NCLAN
results show that "several economically important crop species are sensitive to ozone levels
typical of those found in the United States."194 In addition, economic studies have shown
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
reduced economic benefits as a result of predicted reductions in crop yields associated with
observed ozone levels.195'196'197
Urban ornamentals represent an additional vegetation category likely to experience some
degree of negative effects associated with exposure to ambient ozone levels. It is estimated that
more than $20 billion (1990 dollars) are spent annually on landscaping using ornamentals, both
by private property owners/tenants and by governmental units responsible for public areas.198
This is therefore a potentially costly environmental effect. However, in the absence of adequate
exposure-response functions and economic damage functions for the potential range of effects
relevant to these types of vegetation, no direct quantitative analysis has been conducted.
Air pollution can have cumulative impacts on forested ecosystems by affecting
regeneration, productivity, and species composition.199 In the U.S., ozone in the lower
atmosphere is one of the pollutants of primary concern. Ozone injury to forest plants can be
diagnosed by examination of plant leaves. Foliar injury is usually the first visible sign of injury
to plants from ozone exposure and indicates impaired physiological processes in the leaves. ฐฐ
In the U.S. this indicator is based on data from the U.S. Department of Agriculture
(USDA) Forest Service Forest Inventory and Analysis (FIA) program. As part of its Phase 3
program, formerly known as Forest Health Monitoring, FIA examines ozone injury to ozone-
sensitive plant species at ground monitoring sites in forest land across the country. For this
indicator, forest land does not include woodlots and urban trees. Sites are selected using a
901 909
systematic sampling grid, based on a global sampling design. ' At each site that has at least
30 individual plants of at least three ozone-sensitive species and enough open space to ensure
that sensitive plants are not protected from ozone exposure by the forest canopy, FIA looks for
damage on the foliage of ozone-sensitive forest plant species. Monitoring of ozone injury to
plants by the USD A Forest Service has expanded from monitoring sites in 10 states in 1994 to
nearly 1,000 monitoring sites in 41 states in 2002.
5.3.5.1.2 Recent Ozone Effects Data for the U.S.
There is considerable regional variation in ozone-related visible foliar injury to sensitive
plants in the U.S. The U.S. EPA has developed an environmental indicator based on data from
the USDA FIA program which examines ozone injury to ozone-sensitive plant species at ground
monitoring sites in forest land across the country (this indicator does not include woodlots and
urban trees). Sites are selected using a systematic sampling grid, based on a global sampling
design.203' ฐ4 Since ozone injury is cumulative over the course of the growing season,
examinations are conducted in July and August, when ozone injury is typically highest. The data
underlying the indictor in Figure 5-9 are based on averages of all observations collected in 2002,
the latest year for which data were publicly available at the time the study was conducted, and
are broken down by U.S. EPA Regions. Ozone damage to forest plants is classified using a
subjective five-category biosite index based on expert opinion, but designed to be equivalent
from site to site. Ranges of biosite values translate to no injury, low or moderate foliar injury
(visible foliar injury to highly sensitive or moderately sensitive plants, respectively), and high or
severe foliar injury, which would be expected to result in tree-level or ecosystem-level
responses, respectively.205
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
As mentioned above, Figure 5-9 presents the ozone injury to forest plants by EPA
Regions. Region 5, which includes the Great Lakes, has 18 percent of monitoring sites with low
ozone injury and 6 percent of sites with moderate ozone injury. The Coordinated Strategy
emissions reductions will reduce ozone injury to forest plants in the Great Lakes region.
Figure 5-9 Ozone Injury to Forest Plants in U.S. by EPA Regions, 2002ab
Region 1
!5-i sites)
Region 1
\A2 sites)
Region 3
[11tates.}
Region 4
(227 sites}
Region 5
|1 80 sites)
Region 6
(59 sites)
Region 7
(63 sites)
Region '-
(72 sites'!
Region 9
(90 sites)
Region 10
{57 sites)
Coverage:
beared in A
:Totals may
raunditxj
Data jflii.re
2m
)egree al injury:
None Low Modems High Severs
3Brcsrrt at monitoring sites in each category:
68.5 16.7 71.1 -
61J 21.4 71 7.1
S5.9 110 144 7.2
75.3 10.17:"
755 1BJ 5.'
94.9
85.7 9.5 "
100.0
753 12,5 3.8 |
100,0
?45 monitoring sites, EPA Re-giora
1 states.
not add to 100% due to
n- I'tCm fciracf Ccn^^c.
9. uoun ruvoSi jerVTOff, ^tt\
3.7
2.4
4.5
3.5
4.0
5.1
32
1.6
-1.3
-1.3
f ฐ
-P% ^ fc
5-30
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5.4 Contribution of Shipping to Great Lakes Air Quality
The preceding sections describe the human health and environmental impacts of exposure
to particulate matter, ozone, NOx, SOx, and air toxics. In this section, we describe the
contribution of ships to levels of particulate matter, ozone, NOx and SOx in the Great Lakes and
the air quality impacts of the Coordinated Strategy in the Great Lakes region. This analysis
shows that application of the EGA requirements to the Great Lakes is expected to result in
important air quality benefits for the Great Lakes, reducing ambient levels of both PM and
ozone.
The air quality and benefits modeling we performed in support of our 2010 Category 3
marine rule is a national-level analysis, reflecting the fact that our Coordinated Strategy is a
national program that applies equally throughout the United States (see the RIA for the final
Category 3 marine rulemaking and the Appendix to this chapter for a description of the
methodology used for that modeling). 206 While emissions from ships operating on the Pacific or
Gulf coasts are not likely to affect the Great Lakes, some portion of emissions from ships
operating in the Saint Lawrence Seaway or Northern Atlantic states may have an impact.
Because it is not possible to isolate the potential impacts of the inventory reductions occurring in
the Northeast Atlantic portion of the North American EGA, estimated air quality improvements
are presented only for the Great Lakes states west of Pennsylvania: Minnesota, Wisconsin,
Illinois, Indiana, Ohio and Michigan.
In addition, because no new modeling was performed for this analysis, the estimates
presented below do not take into account the Great Lakes inventory adjustments described in
Chapter 4. While the impact of those adjustments on the air quality estimates presented below is
unknown without additional modeling, the estimated vessel inventory reductions of 87 and 96
percent for PM and SOx, respectively, will assist Great Lakes states' efforts to achieve and
maintain National Ambient Air Quality Standards and help provide cleaner air throughout the
region.
Finally, the estimated air quality improvements presented below do not include
improvements in air quality that would occur in Canada as a result of reduced emissions from
ships operating in the U.S. portion of the Great Lakes.
5.4.1 PM and Ozone Nonattainment in the Great Lakes
Over 27 million people live in the Great Lakes basin and are affected by ship emissions
from the Great Lakes.20 Many counties in the Great Lakes area are in nonattainment for the
National Ambient Air Quality Standards for PM2.5 and ozone, and ships are contributors to those
ozone and PM levels. Figure 5-10 presents ports along with these nonattainment areas.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Figure 5-10 Great Lakes Nonattainment Areas (based on data through May 2007)
\ ^*rsr*
Two Harbors
t9
Duluth-Supenor"' -,- Presque Isle
r
<3 Portland
OPortsmouth
-. Boston
.ftPibvidence
,Mew Haven
.Jridgcport
lew York/NJ Ports
iiladelphia/Delaware
-Baltimore
intington .ป.. Newport News
* .Norfolk Harboi
Rons
PM and Ozone NonAllainmenl
Ozone NonAtlalnment
PM2 5 NonAiialnmom
Federal Class I Areas (Visibility)
5.4.2 Impacts of the Coordinated Strategy at the National Level
The air quality modeling we performed in support of the Coordinated Strategy and our
Category 3 marine rule indicates that a significant portion of the country, including areas located
well inland, are expected to experience air quality improvements as a result of the Coordinated
Strategy. With respect to PM2.s, the modeling shows that in 2020 and 2030 all of the modeled
counties will experience decreases in their annual and 24-hour PM2.5 design values. For areas
with annual PM2.5 design values greater than 15|ig/m3, the modeled future-year, population-
weighted annual PM2.5 design values are expected to decrease on average by 0.8 |ig/m3 in 2020
and by 1.7 |ig/m3 in 2030. For areas with 24-hour PM2.5 design values greater than 35|ig/m3, the
modeled future-year, population-weighted annual PM2.5 design values are expected to decrease
on average by 1.3 |ig/m in 2020 and by 3.4 |ig/m3 in 2030. With respect to ozone, the air
quality modeling results also indicate that emission reductions achieved through the Coordinated
Strategy will improve both the average and population-weighted average ozone design value
concentrations nationwide in 2020 and 2030. In projected nonattainment counties, on a
population-weighted basis, the 8-hour ozone design value will on average decrease by 0.5 ppb in
2020andl.6ppbin2030.K
K It should be noted that even though our air quality modeling predicts important reductions in nationwide ozone
levels, three counties (of 661 that were part of the analysis) are expected to experience an increase in their ozone
design values in 2030. There are two counties in Washington, Clallam County and Clark County, and Orange
County CA, which will experience 8-hour ozone design value increases due to the NOX disbenefits which occur in
these VOC-limited ozone nonattainment areas. Briefly, NOX reductions at certain times and in some areas can lead
to increased ozone levels. We do not see any ozone increases in the Great Lakes region.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5.4.3 Projected Particulate Matter Air Quality Impacts in the Great
Lakes Region
The analysis described in this section shows the projected PM2.5 air quality
improvements in the Great Lakes region due to the Coordinated Strategy emissions reductions.
Our analysis indicates that the reductions from the Coordinated Strategy will provide Great
Lakes-wide improvements in ambient PM2.5 concentrations and minimize the risk of exposures
in future years. In addition, since the emission reductions from the Coordinated Strategy go into
effect during the period when some areas are still working to attain the PM2.5 NAAQS, the
projected emission reductions will assist state and local agencies in their effort to attain the
PM2.5 standard and help others maintain the standard.
EPA has issued two NAAQS for PM^.s: an annual standard (15 ug/m3) and a 24-hour
standard (35 ug/m3). The most recent revisions to these standards were in 1997 and 2006. In
2005, the U.S. EPA designated nonattainment areas for the 1997 PM2.5 NAAQS (70 FR 19844,
April 14, 2005).L On October 8, 2009, the EPA issued final nonattainment area designations for
the 2006 24-hour PM2.5 NAAQS (74 FR 58688, November 13, 2009).
Great Lakes states with PM2.5 nonattainment areas, including Michigan, Wisconsin,
Indiana, Illinois and Ohio, will be required to take action to bring those areas into compliance in
the future. Most 1997 PM2.5 nonattainment areas are required to attain the 1997 PM2.5 NAAQS
in the 2010 to 2015 time frame and then required to maintain the 1997 PM2.5 NAAQS
90R90Q
thereafter. The 2006 24-hour PM2.5 nonattainment areas will be required to attain the 2006
24-hour PM2.5 NAAQS in the 2014 to 2019 time frame and then be required to maintain the
2006 24-hour PM2.s NAAQS thereafter.210 The U.S. Government and individual states and local
areas have already put in place many PM2.5 and PM2.5 precursor emission reduction programs.
However, we expect many of the PM2.5 nonattainment areas will need to adopt additional
emissions reduction programs to attain and maintain the PM2.s NAAQS. In the Great Lakes
Category 3 vessels are contributors to PM2.5 and reductions from this source in a timely manner
will help the states to meet their air quality goals. The Coordinated Strategy for Category 3
marine engines and their fuels will provide additional needed inventory reductions to the Great
Lakes and will assist PM2.s nonattainment areas in reaching the standard by each area's
respective attainment date and/or assist attainment areas in maintaining the PM2.5 standard in the
future.
Figure 5-11 presents the projected annual PM2.5 improvements in 2020 from the
Coordinated Strategy for the Great Lakes region.M Based on the air quality modeling performed
for the Coordinated Strategy, we project that most of the eastern portion of this region, including
the metropolitan areas of Cleveland and Detroit, will see improvements of between 0.03 and 0.05
ug/m3.
L A nonattainment area is defined in the Clean Air Act (CAA) as an area that is violating an ambient standard or is
contributing to a nearby area that is violating the standard.
M Maps for improvements in 24-hour PM2 5 were not created because the mapping methodology was being finalized
at the time the Coordinated Strategy modeling occurred.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Figure 5-11 Improvement in Annual Average PM2.g Concentrations in 2020 from the Coordinated Strategy
<= 0.01 ug/m3
>0.01 to <= 0.03
>0.03to<=0.05
> 0.05 to <= 0.10
> 0.1 to <= 0.25
One way to estimate the air quality impacts from the Great Lakes Fleet is to consider only
the 6 mid-western states that border the Great Lakes (IL, IN, MI, MN, OH, and WI). This
method minimizes the impact that East Coast emissions reductions may be having in the eastern
Great Lakes states like New York and Pennsylvania. Within the 6 mid-western states that border
the Great Lakes, the average modeled future-year annual PM2.5 design values will decrease by
0.03 |ig/m3 in 2020 and the average modeled future-year 24-hour PM2.5 design values will also
decrease by 0.03 |ig/m3 in 2020. These design value decreases indicate the overall improvement
in air quality in the Great Lakes region due to the emissions reductions in Great Lakes vessels
from the Coordinated Strategy.
Table 5-3 and Table 5-4 list the counties on the shores of the Great Lakes with projected
annual and/or 24-hour PM2.5 design values that violate or are within 10 percent of the PM2.5
standard in 2020. Counties marked with a "V" in the table have projected design values greater
than or equal to the standard. Counties marked with an "X" in the table have projected design
values within 10 percent below the standard. The counties marked "X" are not projected to
violate the standard, but to be close to it, so the rule will help assure that these counties continue
to meet the standard. Reducing emissions from Great Lakes vessels will help assure that these
counties attain or maintain the standard.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Table 5-3 Great Lakes Counties with 2020 Projected PM2.S Design Values in Violation or Within 10 percent
of the Annual PM2.5 Standard in the Base and Control Cases
State
IL
MI
OH
County
Cook Co
Wayne Co
Cuyahoga Co
2000-2004
Average
annual
PM25DV
(n/3)
17.07
19.32
18.37
2020 modeling
projections of
Base annual
PM2 5 DV
(uG/M3)
X
V
X
2020 modeling
projections of
Control annual
PM25 DV
(uG/M3)
X
V
X
2020
Projected
Population"
5,669,479
1,908,196
1,326,680
a Woods & Poole Economics Inc. 2001. Population by Single Year of Age CD. Woods & Poole
Economics, Inc.
Table 5-4 Great Lakes Counties with 2020 Projected PM2.5 Design Values in Violation or Within 10 percent
of the 24-hour PM2.5 Standard in the Base and Control Cases
State
IL
MI
OH
IN
County
Cook Co
Wayne Co
Cuyahoga Co
Lake Co
2000-2004
Average 24-
hour PM25
DV (u/3)
43.3
42.9
44.0
43.8
2020 modeling
projections of
Base 24-Hour
PM25DV
(uG/M3)
V
V
V
V
2020 modeling
projections of
Control 24-
hour PM2 5 DV
(uG/M3)
V
V
V
V
2020
Projected
Population"
5,669,479
1,908,196
1,326,680
509,293
a Woods & Poole Economics Inc. 2001. Population by Single Year of Age CD. Woods & Poole
Economics, Inc.
5.4.4 Projected Ozone Air Quality Impacts in the Great Lakes Region
The analysis described in this section shows the projected ozone air quality impacts in the
Great Lakes region in the future due to the Coordinated Strategy emissions reductions. Our
analysis indicates that the reductions from the Coordinated Strategy will provide Great Lakes-
wide improvements in ambient ozone concentrations and minimize the risk of exposures in
future years. In addition, since the emission reductions from the Coordinated Strategy go into
effect during the period when some areas are still working to attain the ozone NAAQS, the
projected emission reductions will assist state and local agencies in their effort to attain the
ozone standard and help others maintain the standard. Emissions reductions from this rule will
also help to counter potential ozone increases due to climate change, which are expected in many
urban areas in the United States, but were not reflected in the Coordinated Strategy
modeling.
211,212
EPA's national ambient air quality standard (NAAQS) for ozone is an 8-hour standard set
at 0.075 ppm. The most recent revision to this standard was in 2008, the previous 8-hour ozone
standard, set in 1997, had been 0.08 ppm. In 2004, the U.S. EPA designated nonattainment areas
5-35
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
for the 1997 8-hour ozone NAAQS (69 FR 23858, April 30, 2004).N The nonattainment areas
associated with the more stringent 2008 8-hour ozone NAAQS have not yet been designated.0
Great Lakes states with ozone nonattainment areas, including Michigan, Wisconsin,
Indiana, Illinois and New York, are required to take action to bring those areas into compliance
in the future. The attainment date assigned to an ozone nonattainment area is based on the area's
classification. Most ozone nonattainment areas are required to attain the 1997 8-hour ozone
NAAQS in the 2007 to 2013 time frame and then be required to maintain it thereafter. In
addition, there will be attainment dates associated with the designation of nonattainment areas as
a result of the reconsideration of the 2008 ozone NAAQS. We expect many of the ozone
nonattainment areas will need to adopt additional emissions reduction programs to attain and
maintain the ozone NAAQS. The expected NOx reductions from the Coordinated Strategy will
be useful to states as they seek to either attain or maintain the ozone NAAQS.
Figure 5-12 presents the projected ozone improvements in 2020 from the Coordinated
Strategy. Most of the eastern Great Lakes region, including the metropolitan areas of Cleveland
and Detroit, are projected to see improvements of between 0.05 and 0.1 ppb.
Figure 5-12 Improvement in Summertime Maximum 8-hour Average Ozone Concentrations in 2020 from the
Coordinated Strategy
N A nonattainment area is defined in the Clean Air Act (CAA) as an area that is violating an ambient standard or is
contributing to a nearby area that is violating the standard.
0 On September 16, 2009, the Administrator announced that the EPA is reconsidering the 2008 ozone standards to
determine whether they adequately protect public health and the environment. She also announced that the Agency
will propose to temporarily stay the 2008 standards for the purpose of attainment and nonattainment area
designations. Under the stay, all activities to designate areas for the 2008 ozone standards would be suspended for
the duration of the reconsideration period. EPA intends to complete the reconsideration by July 31,2011. If, as a
result of the reconsideration, EPA determines that the 2008 ozone standards are not supported by the scientific
record and promulgates different ozone standards, the new 2011 ozone standards would replace the 2008 ozone
standards and the requirement to designate areas for the 2008 standards would no longer apply. If EPA promulgates
new ozone standards in 2011, the designations would likely be effective in 2013.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
As mentioned above, one way to estimate the air quality impacts from the Great Lakes
Fleet is to consider only the 6 mid-western states that border the Great Lakes (IL, IN, MI, MN,
OH, and WI). Within the 6 mid-western states that border the Great Lakes the average modeled
future-year ozone design values will decrease by 0.03 ppb in 2020. These design value
decreases indicate the overall improvement in air quality in the Great Lakes region due to the
emissions reductions in Great Lakes vessels from the Coordinated Strategy.
Table 5-5 lists the counties on the shores of the Great Lakes with projected 8-hour ozone
design values that violate or are within 10 percent of the 2008 8-hour ozone standard in 2020.
Counties marked with a "V" in the table have projected design values greater than or equal to the
standard. Counties marked with an "X" in the table have projected design values within 10
percent below the standard. The counties marked "X" are not projected to violate the standard,
but to be close to it, so the rule will help assure that these counties continue to meet the standard.
Reducing emissions from Great Lakes vessels will help assure that these counties attain or
maintain the standard.
Table 5-5 Great Lakes Counties with 2020 Projected 8-hour Ozone Design Values in Violation or Within 10%
of the Standard in the Base and Control Cases
State
Wisconsin
Wisconsin
Ohio
Indiana
Wisconsin
Wisconsin
Michigan
Michigan
Wisconsin
Indiana
Indiana
Wisconsin
Illinois
Ohio
Michigan
Ohio
Michigan
Michigan
Michigan
Wisconsin
Illinois
Wisconsin
Ohio
Ohio
County
Kenosha
Sheboygan
Ashtabula
Lake
Ozaukee
Racine
Allegan
Macomb
Milwaukee
La Porte
Porter
Door
Cook
Lake
Muskegon
Lucas
Berrien
Wayne
St Clair
Kewaunee
Lake
Manitowoc
Lorain
Cuyahoga
2000-2004
Average 8-hour
Ozone DV (u/3)
98.3
97.0
95.7
88.3
93.0
91.7
94.0
92.3
91.0
90.3
86.3
91.0
85.3
92.7
90.0
90.0
88.0
86.0
88.0
89.3
84.7
87.0
87.0
88.0
2020 modeling projections
of Base 8-hour Ozone DV
(uG/M3)
V
V
V
V
V
V
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2020 modeling projections
of Control 8-hour Ozone
DV (uC/M3)
V
V
V
V
V
V
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2020
Projected
Population3
184,825
128,777
108,355
509,293
110,294
212,351
141,851
894,095
927,845
114,207
188,604
34,106
5,669,479
250,353
183,444
445,152
169,437
1,908,196
194,501
21,040
861,958
85,187
309,007
1,326,680
a Woods & Poole Economics Inc. 2001. Population by Single Year of Age CD. Woods & Poole Economics, Inc.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5.4.5 Projected Nitrogen and Sulfur Deposition Air Quality Impacts in
the Great Lakes Region
The emissions reductions from the Coordinated Strategy will also reduce nitrogen and
sulfur deposition levels for the Great Lakes region in 2020. Our analysis shows that sulfur
deposition would be reduced from 1 percent to 3 percent and nitrogen deposition would be
reduced from between 0 to 1 percent. Figure 5-13 illustrates the sulfur deposition reductions that
will occur in the Great Lakes region. Many of the areas that will see the reductions in sulfur
deposition are the same areas that have aquatic ecosystems which are particularly sensitive to
acidifying deposition (see Figure 5-6). These projected nitrogen and sulfur deposition reductions
will assist the U.S. in its efforts to reduce acidification impacts in both terrestrial and aquatic
ecosystems in the Great Lakes.
Figure 5-13 Percent Change in Annual Total Sulfur Deposition in 2020 from the Coordinated Strategy
The modeling provides estimates of the amount of nitrogen and sulfur deposition in the
Great Lakes region. Additionally, we conducted analyses using a separate methodology in
which the model outputs were used to estimate the impacts on deposition levels by creating wet
deposition relative reduction factors, more detail is available in Section 2.4.5.6 of the RIA for the
final Category 3 marine rulemaking. This analysis was completed for each individual 8-digit
hydrological unit code (HUC) within the U.S. modeling domain. Table 5-6 presents the results
of this analysis for the Great Lakes. This assessment corroborated the deposition modeling
results. Both analyses indicate that the Coordinated Strategy will help reduce nitrogen and sulfur
deposition within the Great Lakes region.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Table 5-6 Percent reduction in Nitrogen (N) and Sulfur (S) deposition averaged over the Great Lakes HUC
sub region. The reductions are shown in parentheses.
HUC SUB REGION
GREAT LAKES
Great Lakes (4)
POLLUTANT
Nitrogen
Sulfur
COORDINATED STRATEGY
PERCENT REDUCTION
0.2%
(0.1 to 0.5%)
1.0%
(0.5 to 2.7%)
5.4.6 Projected Visibility Impacts in the Great Lakes Region
As discussed in Section 5.3.4, visibility impairment is experienced throughout the U.S.,
in multi-state regions, urban areas, and remote mandatory class I federal areas, including those
91 ^ 91 A
within the Great Lakes. ' The CMAQ model was also used to estimate visibility impacts
based on the projected improvement in annual average visibility at mandatory federal class I
federal areas. The mandatory class I federal areas are required to achieve natural background
visibility levels by 2064 under the Regional Haze Rule.
Table 5-7 presents the CMAQ visibility results from the 2020 Coordinated Strategy
scenario for the 3 mandatory class I federal areas on the shores of the Great Lakes. The results
indicate that although the areas would continue to have annual average deciview levels above
background in 2020, reductions in regional haze would occur in all of the areas as a result of the
emissions reductions in the Coordinated Strategy.
Table 5-7 Visibility Levels in Deciviews for Great Lakes Mandatory Class 1 Federal Areas on the 20 percent
Worst Days
CLASS 1 AREA
(20% WORST DAYS)
Isle Royale NP
Seney
Voyageurs NP
STATE
MI
MI
MN
BASELINE
VISIBILITY
20.74
24.16
19.27
2020
BASE
18.99
21.54
17.55
ECA
18.84
21.49
17.52
NATURAL
BACKGROUND
12.37
12.65
12.06
5.5 Quantified and Monetized Health and Environmental Impacts
EPA's Coordinated Strategy to control emissions from ships will result in a substantial
improvement in air quality and related human health and environmental impacts throughout the
r\ -I c
United States, including the Great Lakes region. We have estimated the human health benefits
associated with the air quality improvements projected for the U.S. portion of the Great Lakes
region. These benefits are derived from the modeling that was performed in support of our
Coordinated Strategy and are based on the national inventories developed for those actions (see
Chapter 4 for more information about our estimated marine inventory). No new air quality
modeling or benefits analysis was performed specifically for this Great Lakes study.
This section describes the methods and assumptions used to estimate the air quality-
related benefits in the Great Lakes region associated with EPA's Coordinated Strategy to control
emissions from ships and describes in more detail the related methods and assumptions that
underpin the benefits presented in the final RIA for the Coordinated Strategy.216 Using these
methods, we project monetized health benefits for 2030 associated with the application of the
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
EGA controls on the Great Lakes to be between $1.5 and $3.7 billion for the six western states
bordering the Great Lakes.
5.5.1 Estimated Benefits of the Coordinated Strategy on the National
Level
Benefits modeling begins with estimates of the air quality impacts of a program. EPA
used the CMAQ model described in Appendix 5 A to model the national-level ozone and PM air
quality impacts of total shipping emissions, as well as the air quality improvements associated
with EPA's Coordinated Strategy to control emissions from ships. That modeled ambient air
quality data serves as an input to the Environmental Benefits Mapping and Analysis Program
(BenMAP).p BenMAP is a computer program developed by the EPA that integrates a number of
the modeling elements used in previous EPA analyses (e.g., interpolation functions, population
projections, health impact functions, valuation functions, analysis and pooling methods) to
translate modeled air concentration estimates into health effect incidence estimates. EPA then
monetized health impacts related to the implementation of the Coordinated Strategy based on
well established methods. These methods are described in Appendix 5B.
EPA estimates that by 2020, implementation of the Coordinated Strategy is expected to
result in the reduction of a significant number of PM2.s-related health impacts, including 5,300 to
14,000 fewer premature mortalities, the reduction of 3,900 hospital admissions (related to both
cardiovascular and respiratory causes), 720,000 days of work lost avoided, 8,800 fewer non-fatal
heart attacks, and the reduction of 4.3 million days of restricted physical activity.
EPA also estimates that by 2030, implementation of the Coordinated Strategy is expected
to result in an even larger reduction of PM2.5-related health impacts, including 12,000 to 30,000
fewer premature mortalities, the reduction of 9,300 hospital admissions (related to both
cardiovascular and respiratory causes), 1,400,000 days of work lost avoided, 20,000 fewer non-
fatal heart attacks, and the reduction of 8.5 million days of restricted physical activity.
5.5.2 Benefits Analysis for Great Lakes
Similar to the air quality analyses above, this benefits analysis considers only the 6 mid-
western states that border the Great Lakes (IL, IN, MI, MN, OH, and WI). For this analysis, we
disaggregated the PM2.5-related benefits that accrue to these states from the nationally
aggregated PM2.s benefits totals presented in the rulemaking support documentation that
accompanied the Coordinated Strategy to control ship emissions.02 Table 5-8 presents both the
disaggregated quantified and monetized PM2.5-related health impacts estimated for the 6 Great
Lakes states as well as the benefits associated with the national program.
p Information on BenMAP, including downloads of the software, can be found at http://www.epa.gov/ttn/ecas/
benmodels.html.
Q For national-level benefits analyses, such as EPA's Coordinated Strategy to control ship emissions, we typically
present total benefits for the nation as a whole. For this analysis, however, we utilized BenMAP to sum and report
those benefits that accrue to the six "Great Lakes" states (IL, IN, MI, MN, OH, and WI) under the Coordinated
Strategy.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Based on the estimated improvements in concentrations of ambient PM2.5 presented in
the previous section, EPA estimates that by 2020, implementation of the Coordinated Strategy in
the Great Lakes is expected to result in 87 - 230 fewer PM-related premature deaths, the
reduction of 70 hospital admissions (related to both cardiovascular and respiratory causes),
11,000 days of work lost avoided, 160 fewer non-fatal heart attacks, and the reduction of 63,000
days of restricted physical activity. By 2030, PM-related health impacts improve even more,
with 170 - 430 fewer PM-related premature deaths, the reduction 140 hospital admissions
(related to both cardiovascular and respiratory causes), 18,000 days of lost work avoided, 310
fewer non-fatal heart attacks, and the reduction of 110,000 days of restricted physical activity.
Table 5-8 shows that the monetized PM-related benefits in the 6 Great Lakes states range
from $0.8 to $1.9 billion in 2020 and from $1.5 to $3.7 billion in 2030. This represents between
1.4 and 1.7 percent of the nationally-aggregated monetized benefits.
Table 5-8 Selected PM2S-related Health Benefits of Ships Operating in the U.S. Portion of the North
American ECA
Health Impact
Premature Mortality51
Chronic Bronchitis
Non-Fatal Heart Attacks
Hospital Admissions11
Acute Bronchitis
Acute Respiratory Symptoms
Avoided Work Loss Days
Total Monetized PM2.5
Benefits [billions, 2006$]c
Great Lakes
2020
87-230
64
160
70
140
63,000
11,000
$0.8 -$1.9
Great Lakes
2030
170-430
110
310
140
250
110,000
18,000
$1.5 - $3.7
National 2020
5,300-14,000
3,800
8,800
3,900
8,500
4,300,000
720,000
$46 -$110
National 2030
12,000-30,000
8,100
20,000
9,300
17,000
8,500,000
1,400,000
$110 -$270
Notes:
" Includes only PM25-related estimates of premature mortality. The range is based on the high- and low-end
estimate of incidence derived from two alternative studies used to estimate PM25-related premature mortality in
the U.S. (Pope et al, 2002 and Laden et al., 2006).
* Includes estimates of both cardiovascular- and respiratory-related hospital admissions.
c Only PM benefits are included here which are monetized at a discount rate of 3 percent and presented in year 2006
dollars. The range is based on the high- and low-end estimate of incidence derived from two alternative studies
used to estimate PM25-related premature mortality in the U.S. (Pope et. al. and Laden et. al.)
The national-level benefits, and those specific to the Great Lakes states, presented in
Table 5-8 omit a number of benefits categories, including human health and environmental
benefits from reductions in ozone formation, air toxics, and other PM-related impacts that we do
not quantify or monetize. These benefit categories remain unquantified because of current
limitations in methods or available data and are listed in Table 5-9. As a result, the quantified
health and environmental benefits, both nationally and in the Great Lakes region, are likely
underestimates of the total benefits attributable to the implementation of the Coordinated
Strategy.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Table 5-9 Unqualified and Non-Monetized Potential Effects of a Coordinated U.S. Strategy to Control Ship
Emissions
Pollutant/ Effects
Ozone Healtha
Ozone Welfare
PM Health0
PM Welfare
Nitrogen and Sulfate
Deposition Welfare
CO Health
HC/Toxics Health
HC/Toxics Welfare
Effects Not Included in Analysis - Changes in:
Premature mortality - short term exposures
Hospital admissions - respiratory causes
Emergency room visits - asthma
Minor restricted activity days
School absence days
Chronic respiratory damageb
Premature aging of the lungsb
Non-asthma respiratory emergency room visits
Exposure to UVb (+/-)e
Yields for
-commercial forests
-some fruits and vegetables
-non-commercial crops
Damage to urban ornamental plants
Impacts on recreational demand from damaged forest aesthetics
Ecosystem functions
Exposure to UVb (+/-)e
Premature mortality - short term exposures
Low birth weight
Pulmonary function
Chronic respiratory diseases other than chronic bronchitis
Non-asthma respiratory emergency room visits
Exposure to UVb (+/-)e
Residential and recreational visibility in non-Class I areas
Soiling and materials damage
Damage to ecosystem functions
Exposure to UVb (+/-)e
Commercial forests due to acidic sulfate and nitrate deposition
Commercial freshwater fishing due to acidic deposition
Recreation in terrestrial ecosystems due to acidic deposition
Existence values for currently healthy ecosystems
Commercial fishing, agriculture, and forests due to nitrogen deposition
Recreation in estuarine ecosystems due to nitrogen deposition
Ecosystem functions
Passive fertilization
Behavioral effects
Cancer (benzene, 1,3 -butadiene, formaldehyde, acetaldehyde)
Anemia (benzene)
Disruption of production of blood components (benzene)
Reduction in the number of blood platelets (benzene)
Excessive bone marrow formation (benzene)
Depression of lymphocyte counts (benzene)
Reproductive and developmental effects (1,3 -butadiene)
Irritation of eyes and mucus membranes (formaldehyde)
Respiratory irritation (formaldehyde)
Asthma attacks in asthmatics (formaldehyde)
Asthma-like symptoms in non-asthmatics (formaldehyde)
Irritation of the eyes, skin, and respiratory tract (acetaldehyde)
Upper respiratory tract irritation and congestion (acrolein)
Direct toxic effects to animals
Bioaccumulation in the food chain
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Pollutant/ Effects
Effects Not Included in Analysis
- Changes in:
Damage to ecosystem function
Odor
Notes:
a The public health impact of biological responses such as increased airway responsiveness to stimuli, inflammation
in the lung, acute inflammation and respiratory cell damage, and increased susceptibility to respiratory infection are
likely partially represented by our quantified endpoints.
b The public health impact of effects such as chronic respiratory damage and premature aging of the lungs may be
partially represented by quantified endpoints such as hospital admissions or premature mortality, but a number of
other related health impacts, such as doctor visits and decreased athletic performance, remain unqualified.
0 In addition to primary economic endpoints, there are a number of biological responses that have been associated
with PM health effects including morphological changes and altered host defense mechanisms. The public health
impact of these biological responses may be partly represented by our quantified endpoints.
d While some of the effects of short-term exposures are likely to be captured in the estimates, there may be
premature mortality due to short-term exposure to PM not captured in the cohort studies used in this analysis.
e May result in benefits or disbenefits.
5.5.3 Economic Values for Health Outcomes
Reductions in ambient concentrations of air pollution generally lower the risk of future
adverse health effects for a large population. Therefore, the appropriate economic measure is
willingness-to-pay (WTP) for changes in risk of a health effect rather than WTP for a health
effect that would occur with certainty (Freeman, 1993). Epidemiological studies generally
provide estimates of the relative risks of a particular health effect that is avoided because of a
reduction in air pollution. We converted those to units of avoided statistical incidence for ease of
presentation. We calculated the value of avoided statistical incidences by dividing individual
WTP for a risk reduction by the related observed change in risk. For example, suppose a
pollution-reduction regulation is able to reduce the risk of premature mortality from 2 in 10,000
to 1 in 10,000 (a reduction of 1 in 10,000). If individual WTP for this risk reduction is $100, then
the WTP for an avoided statistical premature death is $1 million ($100/0.0001 change in risk).
WTP estimates generally are not available for some health effects, such as hospital
admissions. In these cases, we used the cost of treating or mitigating the effect as a primary
estimate. These cost-of-illness (COI) estimates generally understate the true value of reducing
the risk of a health effect, because they reflect the direct expenditures related to treatment, but
not the value of avoided pain and suffering (Harrington and Portney, 1987; Berger, 1987). We
provide unit values for health endpoints (along with information on the distribution of the unit
value) in Table 5-10. All values are in constant year 2000 dollars, adjusted for growth in real
income out to 2020 and 2030 using projections provided by Standard and Poor's. Economic
theory argues that WTP for most goods (such as environmental protection) will increase if real
income increases. Many of the valuation studies used in this analysis were conducted in the late
1980s and early 1990s. Because real income has grown since the studies were conducted,
people's willingness to pay for reductions in the risk of premature death and disease likely has
grown as well. We did not adjust cost of illness-based values because they are based on current
costs. Similarly, we did not adjust the value of school absences, because that value is based on
current wage rates. For details on valuation estimates for PM-related endpoints, see the 2006
PM NAAQS RIA. For details on valuation estimates for ozone-related endpoints, see the 2008
Ozone NAAQS RIA.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5.5.4 Methods for Describing Uncertainty
917
The National Research Council (NRC) highlighted the need for EPA to conduct
rigorous quantitative analysis of uncertainty in its benefits estimates and to present these
estimates to decision makers in ways that foster an appropriate appreciation of their inherent
uncertainty. In response to these comments, EPA's Office of Air and Radiation (OAR) is
developing a comprehensive strategy for characterizing the aggregate impact of uncertainty in
key modeling elements on both health incidence and benefits estimates. Components of that
process include emissions modeling, air quality modeling, health effects incidence estimation,
and valuation.
In benefit analyses of air pollution regulations conducted to date, the estimated impact of
reductions in premature mortality has accounted for 85 percent to 95 percent of total benefits.
Therefore, it is particularly important to characterize the uncertainties associated with reductions
in premature mortality. The health impact functions used to estimate avoided premature deaths
associated with reductions in ozone have associated standard errors that represent the statistical
errors around the effect estimates in the underlying epidemiological studies.R In our results, we
report credible intervals based on these standard errors, reflecting the uncertainty in the estimated
change in incidence of avoided premature deaths. We also provide multiple estimates, to reflect
model uncertainty between alternative study designs.
For premature mortality associated with exposure to PM, we follow the same approach
that has been used in several recent RIAs.218'219'220 First, we use Monte Carlo methods for
estimating random sampling error associated with the concentration response functions from
epidemiological studies and economic valuation functions. Monte Carlo simulation uses random
sampling from distributions of parameters to characterize the effects of uncertainty on output
variables, such as incidence of premature mortality. Specifically, we used Monte Carlo methods
to generate confidence intervals around the estimated health impact and dollar benefits.
Distributions for individual effect estimates are based on the reported standard errors in the
epidemiological studies. Distributions for unit values are described in Table 5-10.
Second, as a sensitivity analysis, we use the results of our expert elicitation of the
concentration response function describing the relationship between premature mortality and
Q O9 1
ambient PM2.5 concentration. ' Incorporating only the uncertainty from random sampling
error omits important sources of uncertainty (e.g., in the functional form of the model; whether
or not a threshold may exist). This second approach attempts to incorporate these other sources
of uncertainty.
Use of the expert elicitation and incorporation of the standard errors approaches provide
insights into the likelihood of different outcomes and about the state of knowledge regarding the
benefits estimates. Both approaches have different strengths and weaknesses, which are fully
described in Chapter 5 of the PM NAAQS RIA.
R Health impact functions measure the change in a health endpoint of interest, such as hospital admissions, for a
given change in ambient ozone or PM concentration.
s Expert elicitation is a formal, highly structured and well documented process whereby expert judgments, usually of
multiple experts, are obtained (Ayyb, 2002).
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
These multiple characterizations, including confidence intervals, omit the contribution to
overall uncertainty of uncertainty in air quality changes, baseline incidence rates, populations
exposed and transferability of the effect estimate to diverse locations. Furthermore, the approach
presented here does not yet include methods for addressing correlation between input parameters
and the identification of reasonable upper and lower bounds for input distributions characterizing
uncertainty in additional model elements. As a result, the reported confidence intervals and
range of estimates give an incomplete picture about the overall uncertainty in the estimates. This
information should be interpreted within the context of the larger uncertainty surrounding the
entire analysis.
As mentioned above, total benefits are driven primarily by the reduction in PM2.5 -related
premature mortalities each year. Some key assumptions underlying the premature mortality
estimates include the following, which may also contribute to uncertainty:
Inhalation of fine particles is causally associated with premature death at
concentrations near those experienced by most Americans on a daily basis.
Although biological mechanisms for this effect have not yet been completely
established, the weight of the available epidemiological, lexicological, and
experimental evidence supports an assumption of causality. The impacts of
including a probabilistic representation of causality were explored in the expert
elicitation-based results of the PM NAAQS RIA.
All fine particles, regardless of their chemical composition, are equally potent in
causing premature mortality. This is an important assumption, because PM
produced via transported precursors emitted from engines may differ significantly
from PM precursors released from electric generating units and other industrial
sources. However, no clear scientific grounds exist for supporting differential
effects estimates by particle type.
The C-R function for fine particles is approximately linear within the range of
ambient concentrations under consideration. Thus, the estimates include health
benefits from reducing fine particles in areas with varied concentrations of PM,
including both regions that may be in attainment with PM2.s standards and those
that are at risk of not meeting the standards.
There is uncertainty in the magnitude of the association between ozone and
premature mortality. The range of ozone impacts associated with the final rule is
estimated based on the risk of several sources of ozone-related mortality effect
estimates. In a recent report on the estimation of ozone-related premature
mortality published by the National Research Council, a panel of experts and
reviewers concluded that short-term exposure to ambient ozone is likely to
contribute to premature deaths and that ozone-related mortality should be
999
included in estimates of the health benefits of reducing ozone exposure. EPA
has requested advice from the National Academy of Sciences on how best to
quantify uncertainty in the relationship between ozone exposure and premature
mortality in the context of quantifying benefits.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Acknowledging omissions and uncertainties, we present a best estimate of the total
benefits based on our interpretation of the best available scientific literature and methods
supported by EPA's technical peer review panel, the Science Advisory Board's Health Effects
Subcommittee (SAB-HES). The National Academies of Science (NRC, 2002) has also reviewed
EPA's methodology for analyzing the health benefits of measures taken to reduce air pollution.
EPA addressed many of these comments in the analysis of the final PM NAAQS.223'2 4 This
analysis incorporates this most recent work to the extent possible.
Table 5-10 Unit Values Used for Economic Valuation of Health Endpoints (2000$)a
Health Endpoint
Premature Mortality
(Value of a Statistical
Life): PM2.5- and Ozone-
related
Chronic Bronchitis (CB)
Nonfatal Myocardial
Infarction (MI) (heart
attack)
3% discount rate
Age 0-24
Age 25-44
Age 45-54
Age 55-65
Age 66 and over
7% discount rate
Age 0-24
Age 25-44
Age 45-54
Age 55-65
o
Age 66 and over
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
$6,320,000
$340,000
$66,902
$74,676
$78,834
$140,649
$66,902
$65,293
$73,149
$76,871
$132,214
$65,293
2020
Income
T 1b
Level
$7,590,000
$420,000
$66,902
$74,676
$78,834
$140,649
$66,902
$65,293
$73,149
$76,871
$132,214
$65,293
2030
Income
T 1b
Level
$7,800,000
$430,000
$66,902
$74,676
$78,834
$140,649
$66,902
$65,293
$73,149
$76,871
$132,214
$65,293
Derivation of Estimates
EPA currently recommends a default central Value
of a Statistical Life (VSL) of $6.3 million based on a
Weibull distribution fitted to twenty -six published
VSL estimates (5 contingent valuation and 21 labor
market studies). The underlying studies, the
distribution parameters, and other useful information
are available in Appendix B of EPA's current
Guidelines for Preparing Economic Analyses. The
guidelines can be accessed at:
http://yosemite.epa.gOv/ee/epa/eermfile.nsf/vwAN/E
E-05 16-0 1 .pdf/$File/EE-05 16-0 1 .pdf
Point estimate is the mean of a generated distribution
of WTP to avoid a case of pollution-related CB.
WTP to avoid a case of pollution-related CB is
derived by adjusting WTP (as described in Viscusi et
al., 1991225) to avoid a severe case of CB for the
difference in severity and taking into account the
elasticity of WTP with respect to severity of CB.
Age-specific cost-of-illness values reflect lost
earnings and direct medical costs over a 5-year
period following a nonfatal MI. Lost earnings
estimates are based on Cropper and Krupnick
(1990). Direct medical costs are based on simple
227
average of estimates from Russell et al. (1998)
990
and Wittelsetal. (1990).
Lost earnings:
Cropper and Krupnick (1990). Present discounted
value of 5 years of lost earnings:
age of onset: at 3% at 7%
25-44 $8,774 $7,855
45-54 $12,932 $11,578
55-65 $74,746 $66,920
Direct medical expenses: An average of:
1. Wittels et al. (1990) ($102,658 no discounting)
2. Russell et al. (1998), 5-year period ($22,33 1 at
3% discount rate; $21,113 at 7% discount rate)
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Health Endpoint
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
2020
Income
T 1b
Level
2030
Income
T 1b
Level
Derivation of Estimates
Hospital Admissions
Chronic Obstructive
Pulmonary Disease
(COPD)
(ICD codes 490-492, 494-
496)
$12,378
$12,378
$12,378
The COI estimates (lost earnings plus direct medical
costs) are based on ICD-9 code-level information
(e.g., average hospital care costs, average length of
hospital stay, and weighted share of total COPD
category illnesses) reported in Agency for Healthcare
229
Research and Quality (2000) (www.ahrq.gov).
Pneumonia
(ICD codes 480-487)
$14,693
$14,693
$14,693
The COI estimates (lost earnings plus direct medical
costs) are based on ICD-9 code-level information
(e.g., average hospital care costs, average length of
hospital stay, and weighted share of total pneumonia
category illnesses) reported in Agency for Healthcare
Research and Quality (2000) (www.ahrq.gov).
Asthma Admissions
5,634
5,634
5,634
The COI estimates (lost earnings plus direct medical
costs) are based on ICD-9 code-level information
(e.g., average hospital care costs, average length of
hospital stay, and weighted share of total asthma
category illnesses) reported in Agency for Healthcare
Research and Quality (2000) (www.ahrq.gov).
All Cardiovascular
(ICD codes 390-429)
$18,387
$18,387
$18,387
The COI estimates (lost earnings plus direct medical
costs) are based on ICD-9 code-level information
(e.g., average hospital care costs, average length of
hospital stay, and weighted share of total
cardiovascular category illnesses) reported in Agency
for Healthcare Research and Quality (2000)
(www.ahrq.gov).
Emergency Room Visits
for Asthma
$286
$286
$286
Simple average of two unit COI values:
(1) $311.55, from Smith et al. (1997)230 and
(2) $260.67, from Stanford et al. (1999).231
Respiratory Ailments Not Requiring Hospitalization
Upper Respiratory
Symptoms (URS)
$25
$27
$27
Combinations of the three symptoms for which WTP
estimates are available that closely match those listed
by Pope et al. result in seven different "symptom
clusters," each describing a "type" of URS. A dollar
value was derived for each type of URS, using mid-
232
range estimates of WTP (lEc, 1994) to avoid each
symptom in the cluster and assuming additivity of
WTPs. The dollar value for URS is the average of
the dollar values for the seven different types of
URS.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Health Endpoint
Lower Respiratory
Symptoms (LRS)
Asthma Exacerbations
Acute Bronchitis
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
$16
$42
$360
2020
Income
T 1b
Level
$17
$45
$380
2030
Income
T 1b
Level
$17
$45
$390
Derivation of Estimates
Combinations of the four symptoms for which WTP
estimates are available that closely match those listed
by Schwartz et al. result in 1 1 different "symptom
clusters," each describing a "type" of LRS. A dollar
value was derived for each type of LRS, using mid-
range estimates of WTP (lEc, 1994) to avoid each
symptom in the cluster and assuming additivity of
WTPs. The dollar value for LRS is the average of
the dollar values for the 1 1 different types of LRS.
Asthma exacerbations are valued at $42 per
incidence, based on the mean of average WTP
estimates for the four severity definitions of a "bad
asthma day," described in Rowe and Chestnut
233
(1986). This study surveyed asthmatics to
estimate WTP for avoidance of a "bad asthma day,"
as defined by the subjects. For purposes of
valuation, an asthma attack is assumed to be
equivalent to a day in which asthma is moderate or
worse as reported in the Rowe and Chestnut (1986)
study.
Assumes a 6-day episode, with daily value equal to
the average of low and high values for related
respiratory symptoms recommended in Neumann et
al. (1994).234
Restricted Activity and Work/School Loss Days
Work Loss Days (WLDs)
School Absence Days
Variable
(national
median = )
$75
$75
$75
County-specific median annual wages divided by 50
(assuming 2 weeks of vacation) and then by 5 to
get median daily wage. U.S. Year 2000 Census,
compiled by Geolytics, Inc.
Based on expected lost wages from parent staying
home with child. Estimated daily lost wage (if a
mother must stay at home with a sick child) is based
on the median weekly wage among women age 25
and older in 2000 (U.S. Census Bureau, Statistical
Abstract of the United States: 2001, Section 12:
Labor Force, Employment, and Earnings, Table No.
621). This median wage is $551. Dividing by 5
gives an estimated median daily wage of $103.
The expected loss in wages due to a day of school
absence in which the mother would have to stay
home with her child is estimated as the probability
that the mother is in the workforce times the daily
wage she would lose if she missed a day = 72.85%
of $103, or $75.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Health Endpoint
Worker Productivity
Minor Restricted Activity
Days (MRADs)
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
$0.95 per
worker per
10% change
in ozone per
day
$51
2020
Income
T 1b
Level
$0.95 per
worker per
10% change
in ozone per
day
$54
2030
Income
T 1b
Level
$0.95 per
worker per
10%
change in
ozone per
day
$55
Derivation of Estimates
Based on $68 - median daily earnings of workers in
farming, forestry and fishing - from Table 621,
Statistical Abstract of the United States ("Full -Time
Wage and Salary Workers - Number and Earnings:
1985 to 2000") (Source of data in table: U.S. Bureau
of Labor Statistics, Bulletin 2307 and Employment
and Earnings, monthly).
Median WTP estimate to avoid one MRAD from
9^S
Tolleyetal. (1986).
All monetized annual benefit estimates are presented in year 2000 dollars. We use the Consumer Price Indexes to
adjust both WTP- and COI-based benefits estimates to 2007 dollars from 2000 dollars.236 For WTP-based
estimates, we use an inflation factor of 1.20 based on the CPI-U for "all items." For COI-based estimates, we use an
inflation factor of 1.35 based on the CPI-U for medical care.
Our analysis accounts for expected growth in real income over time. Economic theory argues that WTP for most
goods (such as environmental protection) will increase if real incomes increase. Benefits are therefore adjusted by
multiplying the unadjusted benefits by the appropriate adjustment factor to account for income growth over time.
For a complete discussion of how these adjustment factors were derived, we refer the reader to the PM NAAQS
regulatory impact analysis. Note that similar adjustments do not exist for cost-of-illness-based unit values. For
these, we apply the same unit value regardless of the future year of analysis.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Appendices
Air Quality Modeling Methodology
This Appendix presents information on the air quality modeling for the Coordinated
Strategy, including the model domain and modeling inputs.
Air Quality Modeling Overview
A national scale air quality modeling analysis was performed to estimate future year
annual PM2.5 concentrations, 8-hour ozone concentrations, nitrogen and sulfur deposition, and
visibility levels. The 2002-based CMAQ modeling platform was used as the tool for the air
quality modeling of future baseline emissions and control scenarios for the Coordinated Strategy.
This platform represents a structured system of connected modeling-related tools and data that
provide a consistent and transparent basis for assessing the air quality response to changes in
emissions, meteorology, and/or model formulation. The base year of data used to construct this
platform includes emissions and meteorology for 2002. The platform was developed by the U.S.
EPA's Office of Air Quality Planning and Standards in collaboration with the Office of Research
and Development and is intended to support a variety of regulatory and research model
applications and analyses.
The CMAQ modeling system is a non-proprietary comprehensive three-dimensional,
grid-based Eulerian air quality model designed to estimate the formation and fate of oxidant
precursors, primary and secondary PM concentrations and deposition, over regional and urban
spatial scales for given input sets of meteorological conditions and emissions. 37'238'239 CMAQ is
a publicly available, peer reviewed,1 state-of-the-science model consisting of a number of
science attributes that are critical for simulating the oxidant precursors and non-linear organic
and inorganic chemical relationships associated with the formation of sulfate, nitrate, and organic
aerosols. CMAQ also simulates the transport and removal of directly emitted particles which are
speciated as elemental carbon, crustal material, nitrate, sulfate, and organic aerosols. The
CMAQ model version 4.6 was most recently peer-reviewed in February of 2007 for the U.S.
EPA as reported in the "Third Peer Review of the CMAQ Model."240 The CMAQ model is a
well-known and well-respected tool and has been used in numerous national and international
applications.241'242'243
This 2002 multi-pollutant modeling platform used the latest publicly-released CMAQ
version 4.6U with a few minor changes and new features made internally by the U.S. EPA
CMAQ model developers, all of which reflects updates to earlier versions in a number of areas to
improve the underlying science. The model enhancements in CMAQ v4.6.1 include: (1) an in-
cloud sulfate chemistry module that accounts for the nonlinear sensitivity of sulfate formation to
T Community Modeling & Analysis System (CMAS) - Reports from the CMAQ Review Process can be found at:
http://www.cmascenter.org/r_and_d/cmaq_review_process.cfm?temp_id=99999.
u CMAQ version 4.6 was released on September 30, 2006. It is available from the Community Modeling and
Analysis System (CMAS) as well as previous peer-review reports at: http://www.cmascenter.org.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
varying pH; (2) an improved vertical asymmetric convective mixing module (ACM2) that allows
in-cloud transport from a source layer to all other-in cloud layers (combined non-local and local
closure scheme); (3) a heterogeneous reaction involving nitrate formation (gas-phase reactions
involving ^Os and H^O); (4) the heterogeneous ^Os reaction probability is now temperature-
and humidity-dependent, (5) an updated version of the ISORROPIA aerosol thermodynamics
module including improved representation of aerosol liquid water content and correction in
activity coefficients for temperature other than 298K, and (6) an updated gas-phase chemistry
mechanism, Carbon Bond 05 (CB05) and associated Euler Backward Iterative (EBI) solver, with
extensions to model explicit concentrations of air toxic species.v
Model Domain and Configuration
The CMAQ modeling domain encompasses all of the lower 48 States (including the
Great Lakes region) and portions of Canada and Mexico. The modeling domain is made up of a
large continental U.S. 36 km grid and two 12 km grids (an Eastern U.S. and a Western U.S.
domain), as shown in Figure 5A-1.W'X The modeling domain contains 14 vertical layers with the
top of the modeling domain at about 16,200 meters, or 100 millibars (mb). Air quality
conditions at the outer boundary of the 36 km domain were taken from the global GEOS-Chem
model and did not change over the simulated scenarios. The 36 km grid was only used to
establish the incoming air quality concentrations along the boundaries of the 12 km grids. All of
the modeling results assessing the air quality impacts of emissions reductions from the
application of EGA controls were taken from the 12 km grids. Table 5A-1 provides some basic
geographic information regarding the CMAQ domains. Table 5A-2 provides information on the
vertical structure of the CMAQ modeling as well as the model which provided meteorological
inputs. Table 5A-3 indicates which CMAQ configuration options were chosen for this analysis.
v An updated version of CMAQ, version 4.7, has recently been released. Version 4.7 includes updates to the
organic aerosol module and is available at: www.cmaq-model.org.
w
data for locations like Alaska and Hawaii.
x In the overlapping portion of the two fine grids we used the WUS results for the States of MT, WY, CO, and MM,
We were unable to consider effects beyond the 48-State area due to the unavailability of gridded meteorological
ita for locations like Alaska and Hawaii.
In the overlapping portion of the two fine grids we used the WUS re
and the BUS results for ND, MN, SD, IA, ME, MO, KS, OK, and TX.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Figure 5A-1 Map of the CMAQ Modeling Domain
at nWMi iO MtoCIMMF
origin -2412000. -972000
col 213 row 192
".:
12hm Eastern Dwnasn
Table 5A-1 Geographic Elements of Domains Used in the EGA Modeling
CMAQ MODELING CONFIGURATION
Map Projection
Grid Resolution
Coordinate Center
True Latitudes
Dimensions
Vertical extent
National Grid
Western U.S. Fine Grid
Eastern U.S. Fine Grid
Lambert Conformal Projection
36km
12km
12km
97degW,40degN
33 deg N and 45 deg N
148x112x14
213x192x14
279 x 240 x 14
14 Layers: Surface to 100 millibar level (see Table 5A-2)
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Table 5A-2 Vertical Layer Structure for MM5 and CMAQ (heights are layer top)
CMAQ
LAYERS
0
1
2
o
J
4
5
6
7
8
9
10
11
12
13
14
MM5 LAYERS
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
SIGMA P
1.000
0.995
0.990
0.985
0.980
0.970
0.960
0.950
0.940
0.930
0.920
0.910
0.900
0.880
0.860
0.840
0.820
0.800
0.770
0.740
0.700
0.650
0.600
0.550
0.500
0.450
0.400
0.350
0.300
0.250
0.200
0.150
0.100
0.050
0.000
APPROXIMATE
HEIGHT (M)
0
38
77
115
154
232
310
389
469
550
631
712
794
961
1,130
1,303
1,478
1,657
1,930
2,212
2,600
3,108
3,644
4,212
4,816
5,461
6,153
6,903
7,720
8,621
9,625
10,764
12,085
13,670
15,674
APPROXIMATE
PRESSURE (MB)
1000
995
991
987
982
973
964
955
946
937
928
919
910
892
874
856
838
820
793
766
730
685
640
595
550
505
460
415
370
325
280
235
190
145
100
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Table 5A-3 Additional Details Regarding the CMAQ Model Configuration
GAS-PHASE CHEMICAL
MECHANISMKRER
Gas-Phase Chemical Solver
PM Module
Inorganic PM module
Organic PM module
Advection Scheme
(vertical and horizontal)
Planetary Boundary Layer
Scheme
Dry Deposition
Aqueous Chemistry
Cloud Scheme
Vertical Coordinate
CB05
Euler Backward Iterative (EBI) scheme
AERO4 aerosol module which contains mechanisms
dealing with sea salt emissions. Three-mode approach:
One coarse mode, two fine modes with variable standard
deviations.
ISORROPIA
Updated SOA module based on Odum/Griffin et al.,
(1997, 1999)
Piecewise Parabolic Method (PPM)
Asymmetric Convective Mixing module (ACM2) scheme
which permits gradual layer-by-layer downward mixing
through compensatory subsidence
M3DRY module modified RADM scheme
RADM Bulk scheme
RADM Cloud scheme
Terrain-following Sigma coordinate
The 36 km and both 12 km CMAQ modeling domains were modeled for the entire year
of 2002. We also modeled ten days at the end of December 2001 as a model "ramp up" period.
These days are used to minimize the effects of initial conditions and are not considered as part of
the output analyses. All 365 model days were used in the calculations of the EGA impacts on
annual average levels of PM2.5. For the 8-hour ozone results, we only used the modeling results
from the period between May 1 and September 30, 2002. This 153-day period generally
conforms to the ozone season across most parts of the U.S. and contains the majority of days
with observed high ozone concentrations in 2002.
Model Inputs
The key inputs to the CMAQ model include emissions from anthropogenic and biogenic
sources, meteorological data, and initial and boundary conditions.
Meteorological Data Inputs
The CMAQ meteorological input files were derived from a simulation of the
Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model'
for the entire year of 2002. This model, commonly referred to as MM5, is a limited-area,
nonhydrostatic, terrain-following system that solves for the full set of physical and
thermodynamic equations which govern atmospheric motions.
'.44
245
Meteorological model input fields were prepared separately for each of the domains
shown in Figure 5A-1 above. The 36 km national domain was modeled using MM5 v.3.6.0 and
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
the 12 km Eastern U.S grid was modeled with MM5 v3.7.2. Both of these two sets of
meteorological inputs were developed by the U.S. EPA. For the 12 km western U.S. grid, we
utilized existing MM5 meteorological model data prepared by the Western Regional Air
Partnership.246 All three sets of MM5 model runs were conducted in 5.5 day segments with 12
hours of overlap for spin-up purposes. Additionally, all three domains contained 34 vertical
layers with an approximately 38m deep surface layer and a 100 millibar top. The MM5 and
CMAQ vertical structures are shown in Table 5A-2 and do not vary by horizontal grid resolution.
The meteorological outputs from MM5 were processed to create model-ready inputs for
CMAQ using the Meteorology-Chemistry Interface Processor (MCIP) version 3.1 to derive the
specific inputs to CMAQ, for example: horizontal wind components (i.e., speed and direction),
temperature, moisture, vertical diffusion rates, and rainfall rates for each grid cell in each vertical
layer. Before initiating the air quality simulations, an evaluation was conducted to identify the
biases and errors associated with the meteorological modeling inputs. The U.S. EPA 2002 MM5
model performance evaluations used an approach which included a combination of qualitative
and quantitative analyses to assess the adequacy of the MM5 simulated fields. More detail on
the meteorological modeling evaluations can be found in the following references.247'248 The
general conclusion of each of these meteorological evaluations was that the simulated
meteorology reproduced the actual meteorology with sufficient accuracy for them to be used in
subsequent air quality analyses.
Initial and Boundary Conditions Data Inputs
The lateral boundary and initial species concentrations are provided by a three-
dimensional global atmospheric chemistry model, the GEOS-CHEM model.249 The global
GEOS-CHEM model simulates atmospheric chemical and physical processes driven by
assimilated meteorological observations from the NASA's Goddard Earth Observing System
(GEOS). This model was run for 2002 with a grid resolution of 2.0 degree x 2.5 degree
(latitude-longitude) and 20 vertical layers. The predictions were used to provide one-way
dynamic boundary conditions at three-hour intervals and an initial concentration field for the 36
km CMAQ simulations. The 36 km coarse grid modeling was used as the initial/boundary
conditions for the 12 km EUS and WUS finer grid modeling. More information is available
about the GEOS-CHEM model and other applications using this tool at: http://www-
as. harvard. edu/chemi stry/trop/geos.
Emissions Inventory Data Inputs
With the exception of the marine emissions discussed in Chapter 4 of this document and
Chapter 3 of the C3 RIA, the CMAQ gridded 2002 emissions input data were based on emissions
from the 2002 National Emissions Inventory (NET) version 3.0. This inventory includes
emissions of criteria pollutantsY from point, stationary area, and mobile source categories. With
^
the exception of California , monthly onroad and nonroad emissions were generated from the
National Mobile Inventory Model (NMEVI) using versions of MOBILE6.0 and NONROAD2005
Y Criteria pollutant emissions include sulfur dioxide, oxides of nitrogen, carbon monoxide, volatile organic
compounds, ammonia, and fine particles.
z The California Air Resources Board submitted annual emissions for California. These were allocated to monthly
resolution prior to emissions modeling using data from the National Mobile Inventory Model (NMIM).
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
consistent with recent national rule analyses. AA'BB The 2002-based platform and its associated
chemical mechanism (CB05) employs updated speciation profiles using data included in the
SPECIATE4.0 database.cc The 2002-based platform also incorporates several temporal profile
updates for both mobile and stationary sources.
The 2002-based platform includes emissions for a 2002 base year model evaluation case,
a 2002 base case and a 2020 future base case. The model evaluation case uses prescribed
burning and wildfire emissions specific to 2002, which were developed and modeled as day-
specific, location-specific emissions using an updated version of Sparse Matrix Operator Kernel
Emissions (SMOKE) system, version 2.3, which computes plume rise and vertically allocates the
fire emissions. SMOKE also provides mobile, area, and point source emissions as gridded,
temporalized, and speciated data inputs to CMAQ (Houyoux and Vukovich, 1999).250 The 2002
evaluation case also includes continuous emissions monitoring (CEM) data for 2002 for electric
generating units (EGUs) with CEMs. The 2002 and projection year baselines include multi-year
averages for the fire sector and EGU emissions that are temporally allocated based on a
combination of multi-year average and 2002 temporal profiles. Projections from 2002 were
developed to account for the expected impact of national regulations, consent decrees or
settlements, known plant closures, and, for some sectors, activity growth. Biogenic emissions
were processed using the Biogenic Emissions Inventory System (BEIS) version 3.13.
CMAQ Evaluation
An operational model performance evaluation for ozone and PM2.5 and its related
speciated components was conducted using 2002 State/local monitoring data in order to estimate
the ability of the CMAQ modeling system to replicate the base year concentrations for the 12-km
EUS and WUS grids. This evaluation principally comprises statistical assessments of model
versus observed pairs that were paired in space and time on a daily or weekly basis, depending
on the sampling frequency of each monitoring network. For any time periods with missing
ozone and PM2.s observations we excluded the CMAQ predictions from those time periods in
our calculations. It should be noted when pairing model and observed data that each CMAQ
concentration represents a grid-cell volume-averaged value, while the ambient network
measurements are made at specific locations. In conjunction with the model performance
statistics, we also provide spatial plots for individual monitors of the calculated bias and error
statistics (defined below). Statistics were generated for the 12-km EUS and WUS grids and five
large subregions.DD The Atmospheric Model Evaluation Tool (AMET) was used to conduct the
evaluation described in this document.251
^ MOBILE6 version was used in the Mobile Source Air Toxics Rule: Regulatory Impact Analysis for Final Rule:
Control of Hazardous Air Pollutants from Mobile Sources, U.S. Environmental Protection Agency, Office of
Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI 48105, EPA420-R-07-002,
February 2007.
BB NONROAD2005 version was used in the proposed rule for small spark ignition (SI) and marine SI rule: Draft
Regulatory Impact Analysis: Control of Emissions from Marine SI and Small SI Engines, Vessels, and Equipment,
U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Office of Transportation and Air
Quality, Assessment and Standards Division, Ann Arbor, MI, EPA420-D-07-004, April 2007.
cc See http://www.epa.gov/ttn/chief/software/speciate/index.html for more details.
DD The subregions are defined by States where: Midwest is IL, IN, MI, OH, and WI; Northeast is CT, DE,MA, MD,
ME, NH, NJ, NY, PA, RI, and VT; Southeast is AL, FL, GA, KY, MS, NC, SC, TN, VA, and WV; Central is AR,
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
The ozone evaluation primarily focused on observed hourly ozone concentrations and
eight-hour daily maximum ozone concentrations above a threshold of 40 ppb. The ozone model
performance evaluation was limited to the ozone season modeled for the EGA: May, June, July,
August, and September. Ozone ambient measurements for 2002 were obtained from the Air
Quality System (AQS) Aerometric Information Retrieval System (AIRS). A total of 1178 ozone
measurement sites were included for evaluation. The ozone data were measured and reported on
an hourly basis.
The PM2.5 evaluation focuses on PM2.5 total mass and its components including sulfate
(SO4), nitrate (NO3), total nitrate (TNO3=NO3+HNO3), ammonium (NH4), elemental carbon
(EC), and organic carbon (OC). The PM2.5 performance statistics were calculated for each
month and season individually and for the entire year, as a whole. Seasons were defined as:
winter (December-January-February), spring (March-April-May), summer (June-July-August),
and fall (September-October-November). PM2.5 ambient measurements for 2002 were obtained
from the following networks for model evaluation: Speciation Trends Network (STN, total of
199 sites), Interagency Monitoring of Protected Visual Environments (IMPROVE, total of 150),
and Clean Air Status and Trends Network (CASTNet, total of 83). The pollutant species
included in the evaluation for each network are listed in Table 5A-4. For PM2.5 species that are
measured by more than one network, we calculated separate sets of statistics for each network.
Table 5A-4 PM2.S Monitoring Networks and Pollutants Species Included in the CMAQ Performance
Evaluation
AMBIENT
MONITORING
NETWORKS
IMPROVE
CASTNet
STN
PARTICULATE SPECIES
PM25
Mass
X
X
S04
X
X
X
NO3
X
X
TNO3
X
NH4
X
X
X
EC
X
X
OC
X
X
Note that TNO3 = (NO3 + HNO3)
There are various statistical metrics available and used by the science community for
model performance evaluation. The four evaluation statistics used to evaluate CMAQ
performance were two bias metrics, normalized mean bias and fractional bias; and two error
metrics, normalized mean error and fractional error.
The "acceptability" of model performance was judged by comparing our CMAQ 2002
performance results to the range of performance found in recent regional ozone and PM2.5 model
applications. These other modeling studies represent a wide range of modeling analyses which
cover various models, model configurations, domains, years and/or episodes, chemical
mechanisms, and aerosol modules. Overall, the statistical calculations of model bias and error
indicate that the CMAQ predicted ozone and PM2.5 concentrations for 2002 are within the range
or close to that found in recent U.S. EPA applications.252 Figure 5A-2, Figure 5A-3, Figure 5A-4
IA, KS, LA, MN, MO, ME, OK, and TX; West is AK, CA, OR, WA, AZ, MM, CO, UT, WY, SD, ND, MT, ID, and
NV.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
and Figure 5 A-5 show the seasonal aggregate normalized mean bias for 8-hourly ozone and
PM2.5 over the two 12-km grids. The CMAQ model performance results give us confidence that
our applications of CMAQ using this 2002 modeling platform provide a scientifically credible
approach for the impacts of EGA controls on ozone and PM2.5 concentrations, visibility levels,
and acid deposition amounts.
Figure 5A-2 Normalized Mean Bias (%) of hourly ozone (40 ppb threshold) by monitor for 12-km Eastern
U.S. domain, seasonal aggregate
O3 NMB (%| lot tun ZQJZae 1SMH EU5 laf 2CQg(H01 to 2002093?
i -3 ..'-
Cl RCLE-AQS_Bhrmax;
Figure 5A-3 Normalized Mean Bias (%) of hourly ozone (40 ppb threshold) by monitor for 12-km Western
U.S. domain, seasonal aggregate
03 MMB |>| Inr run Kปiac_iakin_WUS lor 20020501 to 2ซttW3l
."..>t,'T =,.>,.;
CIRCLE=AQS Shrmax;
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Figure 5A-4 Normalized Mean Bias (%) of annual PM2.g by monitor for 12-km Eastern U.S. domain, 2002
PMM Hue -V tf nป MM*. 1*01 EUS rer Jmtti ID PซCM>bปf
OftCLE-IMPflOvE: TflMNGLE-STN:
Figure 5A-5 Normalized Mean Bias (%) of annual PM2.S by monitor for 12-km Western U.S. domain, 2002
dftCLE-MPROVE. tfltANGLE-STN
Model Simulation Scenarios
As part of our analysis for the Coordinated Strategy, the CMAQ modeling system was
used to calculate annual PM2.5 concentrations, 8-hour ozone concentrations, nitrogen and sulfur
deposition levels and visibility estimates for each of the following emissions scenarios:
2002 base year
2020 base line project!on
2020 base line projection with Coordinated Strategy emission reductions
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
2030 base line projection
2030 base line projection with Coordinated Strategy emission reductions
It should be noted that the emission control scenarios used in the air quality and benefits
modeling are slightly different than in the Coordinated Strategy. The differences reflect further
refinements of the regulatory program since we performed the air quality modeling for this rule.
Chapter 3 of the RIA for the final Category 3 marine rule describes the changes in the inputs and
resulting emission inventories between the preliminary assumptions used for the air quality
modeling and the final regulatory scenario. Additionally, the emission control scenarios do not
consider the exclusion of Great Lakes steamships from the final fuel sulfur standards. These
refinements to the program would not significantly change the results summarized here or our
conclusions drawn from this analysis.
We use the predictions from the model in a relative sense by combining the 2002 base-
year predictions with predictions from each future-year scenario and applying these modeled
ratios to ambient air quality observations to estimate annual PM2.5 concentrations, 8-hour ozone
concentrations, nitrogen and sulfur deposition levels, and visibility levels for each of the 2020
and 2030 scenarios. The ambient air quality observations are average conditions, on a site by
site basis, for a period centered around the model base year (i.e., 2000-2004).
The projected annual PM2.5 design values were calculated using the Speciated Modeled
Attainment Test (SMAT) approach. The SMAT uses an Federal Reference Method FRM mass
construction methodology that results in reduced nitrates (relative to the amount measured by
routine speciation networks), higher mass associated with sulfates (reflecting water included in
FRM measurements), and a measure of organic carbonaceous mass that is derived from the
difference between measured PM2.5 and its non-carbon components. This characterization of
PM2.5 mass also reflects crustal material and other minor constituents. The resulting
characterization provides a complete mass balance. It does not have any unknown mass that is
sometimes presented as the difference between measured PM2.s mass and the characterized
chemical components derived from routine speciation measurements. However, the assumption
that all mass difference is organic carbon has not been validated in many areas of the U.S. The
SMAT methodology uses the following PM2.5 species components: sulfates, nitrates,
ammonium, organic carbon mass, elemental carbon, crustal, water, and blank mass (a fixed value
of 0.5 |ig/m3). More complete details of the SMAT procedures can be found in the report
"Procedures for Estimating Future PM2.5 Values for the CAIR Final Rule by Application of the
(Revised) Speciated Modeled Attainment Test (SMAT)."253 For this latest analysis, several
datasets and techniques were updated. These changes are fully described within the technical
support document for the Small SI Engine Rule modeling AQM TSD.254 The projected 8-hour
ozone design values were calculated using the approach identified in EPA's guidance on air
quality modeling attainment demonstrations.255
Deposition Modeling Methodology
The CMAQ model provides estimates of the amount of nitrogen and sulfur deposition in
each of the simulated scenarios. Additionally, we conducted analyses using a separate
methodology in which the CMAQ outputs were used to estimate the impacts on deposition levels
in a manner similar to how the model is used for ozone and fine particulate matter. In this
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methodology, CMAQ outputs of annual wet deposition from the 2002 base year model run are
used in conjunction with annual wet deposition predictions from the control or future case
scenarios to calculate relative reduction factors (RRFs) for wet deposition. Separate wet
deposition RRFs are calculated for reduced nitrogen, oxidized nitrogen, and sulfur. These RRFs
are multiplied by the corresponding measured annual wet deposition of reduced nitrogen,
oxidized nitrogen, and sulfur from the National Atmospheric Deposition Program (NADP)
network. The result is a projection of the NADP wet deposition for the control or future case
scenarios. The projected wet deposition for each of the three species is added to the CMAQ-
predicted dry deposition for each of these species to produce total reduced nitrogen, total
oxidized nitrogen, and total sulfur deposition for the control/future case scenario. The reduced
and oxidized nitrogen depositions are summed to calculate total nitrogen deposition.
This analysis was completed for each individual 8-digit hydrological unit code (HUC)
within the U.S. modeling domain. Each 8-digit HUC represents a local drainage basin. There
were 2,108 8-digit HUCs considered as part of this analysis. This assessment corroborated the
absolute deposition modeling results.
Visibility Modeling Methodology
The modeling platform described in this section was also used to project changes in
visibility. The estimate of visibility benefits was based on the projected improvement in annual
average visibility at mandatory class I federal areas. There are 156 mandatory class I federal
areas which, under the Regional Haze Rule, are required to achieve natural background visibility
levels by 2064. These mandatory class I federal areas are mostly national parks, national
monuments, and wilderness areas. There are currently 116 Interagency Monitoring of Protected
Visual Environments (IMPROVE) monitoring sites (representing all 156 mandatory class I
federal areas) collecting ambient PM2.5 data at mandatory class I federal areas, but not all of
these sites have complete data for 2002. For this analysis, we quantified visibility improvement
at the 133 mandatory class I federal areas which have complete IMPROVE ambient data for
2002 or are represented by IMPROVE monitors with complete data.EE
Visibility impairment is quantified in extinction units. Visibility degradation is directly
proportional to decreases in light transmittal in the atmosphere. Scattering and absorption by
both gases and particles decrease light transmittance. To quantify changes in visibility, our
analysis computes a light-extinction coefficient (bext) and visual range. The light extinction
coefficient is based on the work of Sisler, which shows the total fraction of light that is decreased
per unit distance. This coefficient accounts for the scattering and absorption of light by both
particles and gases and accounts for the higher extinction efficiency of fine particles compared to
coarse particles. Fine particles with significant light-extinction efficiencies include sulfates,
nitrates, organic carbon, elemental carbon, and soil.256
Visual range is a measure of visibility that is inversely related to the extinction
coefficient. Visual range can be defined as the maximum distance at which one can identify a
EE There are 100 IMPROVE sites with complete data for 2002. Many of these sites collect data that is
"representative" of other nearby unmonitored mandatory class I federal areas. There are a total of 133 mandatory
class I federal areas that are represented by the 100 sites. The matching of sites to monitors is taken from "Guidance
for Tracking Progress Under the Regional Haze Rule".
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
black object against the horizon sky. Visual range (in units of kilometers) can be calculated from
bgxt using the formula: Visual Range (km) = 3912/bext (bext units are inverse megameters [Mm"
The future year visibility impairment was calculated using a methodology which applies
modeling results in a relative sense similar to the Speciated Modeled Attainment Test (SMAT).
In calculating visibility impairment, the extinction coefficient is made up of individual
component species (sulfate, nitrate, organics, etc). The predicted change in visibility is
calculated as the percent change in the extinction coefficient for each of the PM species (on a
daily average basis). The individual daily species extinction coefficients are summed to get a
daily total extinction value. The daily extinction coefficients are converted to visual range and
then averaged across all days. In this way, we can calculate annual average extinction and visual
range at each IMPROVE site. Subtracting the annual average control case visual range from the
base case visual range gives a projected improvement in visual range (in km) at each mandatory
class I federal area. This serves as the visibility input for the benefits analysis (See Chapter 6 of
this RIA).
For visibility calculations, we are continuing to use the IMPROVE program species
definitions and visibility formulas which are recommended in the modeling guidance.257 Each
IMPROVE site has measurements of PM2.s species and therefore we do not need to estimate the
species fractions in the same way that we did for FRM sites (using interpolation techniques and
other assumptions concerning volatilization of species).
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
5B
Benefits Methodology
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
This Appendix provides details about the benefits methods applied in the estimation of
benefits for the Category 3 marine final rulemaking, from which the estimate of Great Lakes-
related benefits were derived.
Human Health Impact Functions
Health impact functions measure the change in a health endpoint of interest, such as
hospital admissions, for a given change in ambient ozone or PM concentration. Health impact
functions are derived from primary epidemiology studies, meta-analyses of multiple
epidemiology studies, or expert elicitations. A standard health impact function has four
components: (1) an effect estimate from a particular study; (2) a baseline incidence rate for the
health effect (obtained from either the epidemiology study or a source of public health statistics
such as the Centers for Disease Control); (3) the size of the potentially affected population; and
(4) the estimated change in the relevant ozone or PM summary measures.
A typical health impact function might look like:
where yo is the baseline incidence (the product of the baseline incidence rate times the
potentially affected population), p is the effect estimate, and Ax is the estimated change in the
summary pollutant measure. There are other functional forms, but the basic elements remain the
same. The following subsections describe the sources for each of the first three elements: size
of the potentially affected populations; PM2.5 and ozone effect estimates; and baseline incidence
rates. We also describe the treatment of potential thresholds in PM-related health impact
functions. Section 7.2 describes the ozone and PM air quality inputs to the health impact
functions.
Potentially Affected Populations
The starting point for estimating the size of potentially affected populations is the 2000
U.S. Census block level dataset.258 Benefits Modeling and Analysis Program (BenMAP)
incorporates 250 age/gender/race categories to match specific populations potentially affected by
ozone and other air pollutants. The software constructs specific populations matching the
populations in each epidemiological study by accessing the appropriate age-specific populations
from the overall population database. BenMAP projects populations to 2030 using growth
9SQ
factors based on economic projections.
Effect Estimate Sources
The most significant quantifiable benefits of reducing ambient concentrations of ozone
and PM are attributable to reductions in human health risks. EPA's Ozone and PM Criteria
Documents260'261 and the World Health Organization's 2003 and 2004262'263 reports outline
numerous human health effects known or suspected to be linked to exposure to ambient ozone
and PM. EPA recently evaluated the ozone and PM literature for use in the benefits analysis for
the final 2008 Ozone NAAQS and final 2006 PM NAAQS analyses. We use the same literature
in this analysis; for more information on the studies that underlie the health impacts quantified in
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
this RIA, please refer to those documents.
It is important to note that we are unable to separately quantify all of the possible PM and
ozone health effects that have been reported in the literature for three reasons: (1) the possibility
of double counting (such as hospital admissions for specific respiratory diseases versus hospital
admissions for all or a sub-set of respiratory diseases); (2) uncertainties in applying effect
relationships that are based on clinical studies to the potentially affected population; or (3) the
lack of an established concentration-response (CR) relationship. Table 5B-1 lists the health
endpoints included in this analysis.
Table 5B-1 Health Impact Functions Used in BenMAP to Estimate Impacts of PM25 and Ozone Reductions
ENDPOINT
Premature Mortality
Premature mortality -
daily time series
Premature mortality
cohort study, all-cause
Premature mortality,
total exposures
Premature mortality
all-cause
Chronic Illness
Chrome bronchitis
Nonfatal heart attacks
Hospital Admissions
Respiratory
POLLUTANT
03
PM25
PM25
PM25
PM25
PM25
03
PM25
STUDY
Multi-city
Bell et al (2004) (NMMAPS study)264 - Non-
accidental
Huang et al (2005)265 - Cardiopulmonary
Schwartz (2005)266 - Non-accidental
Meta-analvses:
Bell et al (2005)267 - All cause
Ito et al (2005)268 - Non-accidental
Levy et al (2005)269 - All cause
Popeetal. (2002)2/u
Laden et al. (2006)271
Expert Elicitation (lEc, 2006)272
Woodruff etal. (1997)273
Abbey etal. (1995)274
Peters etal. (200 1)275
Pooled estimate:
Schwartz (1995) - ICD 460-519 (all resp)276
Schwartz (1994a; 1994b) - ICD 480-486
(pneumonia)277'278
Moolgavkar et al. (1997) - ICD 480-487
(pneumonia)279
Schwartz (1994b) - ICD 491-492, 494-496
(COPD)
Moolgavkar et al. (1997) - ICD 490-496
(COPD)
Burnett etal. (200 1)280
Pooled estimate:
Moolgavkar (2003) ICD 490-496 (COPD)281
Ito (2003) ICD 490-496 (COPD)282
STUDY
POPULATION
All ages
>29 years
>25 years
>24 years
Infant (<1 year)
>26 years
Adults (>18 years)
>64 years
<2 years
>64 years
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
ENDPOINT
Cardiovascular
Asthma-related ER
visits
Asthma-related ER
visits (con't)
POLLUTANT
PM25
PM25
PM25
PM25
PM25
03
PM25
STUDY
Moolgavkar (2000) ICD 490-496
(COPD)283
Ito (2003) ICD 480-486 (pneumonia)
Sheppard (2003) ICD 493 (asthma)284
Pooled estimate:
Moolgavkar (2003) ICD 390-429 (all
cardiovascular)
Ito (2003) ICD 410-414, 427-428 (ischemic
heart disease, dysrhythmia, heart failure)
Moolgavkar (2000) ICD 390-429 (all
cardiovascular)
Pooled estimate:
Jaffe et al (2003)285
Peel et al (2005)286
Wilson et al (2005)287
Norrisetal. (1999)288
STUDY
POPULATION
20-64 years
>64 years
<65 years
>64 years
20-64 years
5-34 years
All ages
All ages
0-18 years
Other Health Endpoints
Acute bronchitis
Upper respiratory
symptoms
Lower respiratory
symptoms
Asthma exacerbations
Work loss days
School absence days
Minor Restricted
Activity Days
(MRADs)
PM25
PM25
PM25
PM25
PM25
03
03
PM25
Dockeryetal. (1996)289
Popeetal. (1991)290
Schwartz and Neas (2000)291
Pooled estimate:
Ostro et al. (200 1)292 (cough, wheeze and
shortness of breath)
Vedal et al. (1998)293 (cough)
Ostro (1987)294
Pooled estimate:
Gilliland et al. (2001)295
Chenetal. (2000)296
Ostro and Rothschild (1989)297
Ostro and Rothschild (1989)
8-12 years
Asthmatics, 9-11
years
7-14 years
6-18 years3
18-65 years
5-17 years'3
18-65 years
18-65 years
Notes:
a The original study populations were 8 to 13 for the Ostro et al. (2001) study and 6 to 13 for the Vedal et al. (1998)
study. Based on advice from the Science Advisory Board Health Effects Subcommittee (SAB-HES), we extended
the applied population to 6 to 18, reflecting the common biological basis for the effect in children in the broader age
group. See: U.S. Science Advisory Board. 2004. Advisory Plans for Health Effects Analysis in the Analytical Plan
for EPA's Second Prospective Analysis -Benefits and Costs of the Clean Air Act, 19902020. EPA-SAB-
COUNCIL-ADV-04-004. See also National Research Council (NRC). 2002. Estimating the Public Health Benefits
of Proposed Air Pollution Regulations. Washington, DC: The National Academies Press.
b Gilliland et al. (2001) studied children aged 9 and 10. Chen et al. (2000) studied children 6 to 11. Based on recent
advice from the National Research Council and the EPA SAB-HES, we have calculated reductions in school
absences for all school-aged children based on the biological similarity between children aged 5 to 17.
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
In selecting epidemiological studies as sources of effect estimates, we applied several
criteria to develop a set of studies that is likely to provide the best estimates of impacts in the
U.S. To account for the potential impacts of different health care systems or underlying health
status of populations, we give preference to U.S. studies over non-U.S. studies. In addition, due
to the potential for confounding by co-pollutants, we give preference to effect estimates from
models including both ozone and PM over effect estimates from single-pollutant models.298'299
Baseline Incidence Rates
Epidemiological studies of the association between pollution levels and adverse health
effects generally provide a direct estimate of the relationship of air quality changes to the relative
risk of a health effect, rather than estimating the absolute number of avoided cases. For example,
a typical result might be that a 100 ppb decrease in daily ozone levels might, in turn, decrease
hospital admissions by 3 percent. The baseline incidence of the health effect is necessary to
convert this relative change into a number of cases. A baseline incidence rate is the estimate of
the number of cases of the health effect per year in the assessment location, as it corresponds to
baseline pollutant levels in that location. To derive the total baseline incidence per year, this rate
must be multiplied by the corresponding population number. For example, if the baseline
incidence rate is the number of cases per year per 100,000 people, that number must be
multiplied by the number of 100,000s in the population.
Tables 5B-2 summarizes the sources of baseline incidence rates and provides average
incidence rates for the endpoints included in the analysis. For both baseline incidence and
prevalence data, we used age-specific rates where available. We applied concentration-response
functions to individual age groups and then summed over the relevant age range to provide an
estimate of total population benefits. In most cases, we used a single national incidence rate, due
to a lack of more spatially disaggregated data. Whenever possible, the national rates used are
national averages, because these data are most applicable to a national assessment of benefits.
For some studies, however, the only available incidence information comes from the studies
themselves; in these cases, incidence in the study population is assumed to represent typical
incidence at the national level. Regional incidence rates are available for hospital admissions,
and county-level data are available for premature mortality. We have projected mortality rates
such that future mortality rates are consistent with our projections of population growth. ฐฐ
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
Table 5B-2a National Average Baseline Incidence Rates"
ENDPOINT
Mortality
Respiratory
Hospital
Admissions
Asthma ER
visits
Minor
Restricted
Activity Days
(MRADs)
School Loss
Days
SOURCE
CDC Compressed Mortality
File, accessed through CDC
Wonder (1996-1998)
1999 NHDS public use data
files'3
2000 NHAMCS public use
data files'; 1999 NHDS public
use data files'3
Ostro and Rothschild
(1989, p. 243)
National Center for Education
Statistics (1996) and 1996 HIS
(Adams etal., 1999, Table
47); estimate of 180 school
days per year
NOTES
non-
accidental
incidence
incidence
incidence
all-cause
RATE PER 100 PEOPLE PER YEARd BY AGE
GROUP
<18
0.025
0.043
1.011
990.0
18-24
0.022
0.084
1.087
780
25-34
0.057
0.206
0.751
780
35-44
0.150
0.678
0.438
780
45-54
0.383
1.926
0.352
780
55-64
1.006
4.389
0.425
780
65+
4.937
11.62
0.232
Notes:
a The following abbreviations are used to describe the national surveys conducted by the National Center for Health
Statistics: HIS refers to the National Health Interview Survey; NHDS - National Hospital Discharge Survey;
NHAMCS - National Hospital Ambulatory Medical Care Survey.
b See ftp://ftp.cdc.gov/pub/Health Statistics/NCHS/Datasets/NHDS/
c See ftp://ftp.cdc.gov/pub/Health Statistics/NCHS/Datasets/NHAMCS/
d All of the rates reported here are population-weighted incidence rates per 100 people per year. Additional details
on the incidence and prevalence rates, as well as the sources for these rates are available upon request.
Table 5B-2b National Average Baseline Incidence Rates
ENDPOINT
Asthma Exacerbations
SOURCE
Ostro etal. (2001)
Vedal etal. (1998)
NOTES
Incidence (and
prevalence) among
asthmatic African-
American children
Incidence (and
prevalence) among
asthmatic children
Daily wheeze
Daily cough
Daily dyspnea
Daily wheeze
Daily cough
Daily dyspnea
RATE PER 100 PEOPLE
PER YEAR
0.076(0.173)
0.067(0.145)
0.037 (0.074)
0.038
0.086
0.045
5-68
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Chapter 5 Air Quality, Health and Environmental Impacts and Benefits
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266 Schwartz, J. (2005) How sensitive is the association between ozone and daily deaths to control for temperature?
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283 Moolgavkar, S.H. (2000). Air Pollution and Hospital Admissions for Diseases of the Circulatory System in
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284 Sheppard, L. (2003). Ambient Air Pollution and Nonelderly Asthma Hospital Admissions in Seattle,
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300 Abt Associates, Inc. October 2005. Methodology for County-level Mortality Rate Projections. Memorandum to
BryanHubbell and Zachary Pekar, U.S. EPA.
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Chapter 6 Costs of Controlling Emissions
CHAPTER 6: Costs of Controlling Emissions from
Vessels on the Great Lakes
This chapter presents our estimate of the costs that are expected to be incurred by
operators of U.S.-flagged vessels as a result of the application of the EGA requirements on the
Great Lakes. We provide estimates of hardware and operating costs associated with the use of
EGA-compliant distillate fuel as well as costs associated with repowering a vessel with Tier 2 or
Tier 3 compliant engines; we do not include new vessel cost impacts because Great Lakes
vessels have very long service lives and are more likely to be repowered than replaced. As there
are thousand-footer vessels powered by either a single Category 3 engine, or multiple Category 2
engines, it is conceivable that a Category 3 vessel could be repowered with Category 2 engines;
however, these costs are not presented here.A While there is no requirement that a vessel must
be repowered, if a vessel is repowered, under most circumstances, the new engine must meet
current NOx standards, therefore, we are presenting these engine costs for the sake of
completeness. The cost estimates presented here are based on the cost analysis we performed for
our Coordinated Strategy as announced in our 2010 Category 3 rulemaking, the fuel prices
described in Chapter 2 of this report and the individual characteristics of the Category 3 vessels
of the U.S. Great Lakes fleet to provide cost estimates on a per-vessel basis.1'6 Costs to
comparable Canadian or other foreign vessels operating on the Great Lakes would be similar to
the costs presented here for U.S. vessels.
This cost analysis considers the compliance costs for existing vessels only. Because
Great Lakes vessels operate in fresh water, they have a very long service life; in fact, the last new
Category 3 vessel to enter the U.S. Great Lakes fleet was built in 1981. As a result, it is more
likely that an existing vessel would be upgraded or repowered than a new vessel would be built
for this fleet. However, we estimated the new vessel costs of our Coordinated Strategy; these
costs are presented in the Economic Impact Analysis of the 2010 Category 3 rulemaking. While
these costs are for ocean-going vessels, they provide an indicator of the likely costs for newly
constructed Great Lakes vessels.2
We estimate the hardware costs of complying with the EGA fuel requirement for vessels
operating on the Great Lakes to be between $42,000 to $71,000 per vessel depending on the size
and power of the vessel. This is a one-time cost to accommodate the change from a residual fuel
system to a distillate fuel system. With regard to operating costs we examined two ships for each
of two routes. The estimated increase in fuel costs associated with the use of EGA-compliant
distillate fuel for a 1,000-foot vessel traveling one-way from the port of Duluth-Superior, MN to
Gary, IN (about 870 miles) is between $24,000 and $30,000, depending on the size and power of
the vessel; this is an approximate 39 percent increase in the one-way voyage fuel costs for this
route. The estimated increase in fuel costs for a smaller vessel (600 to 800 foot) traveling one-
way from the port of Roger City, MI to Ashtabula, OH (about 430 miles) can range from $2,100
A Standards and estimated costs for Category 2 engines were presented in 2008 rulemaking "Control of Emissions of
Air Pollution From Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Liters per
Cylindef available here: http://www.epa.gov/otaq/marine.htm
B Consistent with the 2010 Category 3 Marine Final Rulemaking, hardware costs are presented in U.S. $2006. Fuel
operational costs are consistent with Chapter 2 of this report and are presented in U.S. $2008.
6-1
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Chapter 6 Costs of Controlling Emissions
to over $5,000, depending on the vessel. This is an approximate 39 percent increase in the one-
way voyage fuel costs.
6.1 Hardware Costs
This section presents estimated hardware costs associated with modifying a Great Lakes
ship to accommodate the use of EGA compliant fuel. We also present estimated hardware costs
for repowering a vessel. It should be noted that our program does not require vessel repowering;
these estimated costs are presented for informational purposes only.
Because only twelve Great Lakes vessels have Category 3 marine diesel engines that use
residual fuel and thus are affected by the fuel requirements, we can provide hardware cost
estimates for each of these vessels. After identifying each of these ships, this report presents
estimates of fuel system hardware costs and engine repowering costs for each ship. Note that
while these are EPA's best estimates, actual estimates prepared by a shipyard for each vessel
may be different.
6.1.1 Great Lakes Vessels Included in this Cost Analysis
There are 57 U.S.-flagged freighters, tug-barge combinations, and ferries working on the
Great Lakes today that are over 2,000 GRT. According to the 2010 Greenwood's Guide to Great
Lakes Shipping, Lloyd's Sea-Web database, and comments we received on our 2010 Category 3
marine rule, twelve of these are Category 3 ships that use residual fuel.3'4'5 These twelve vessels
are listed in Table 6-1. The other large U.S. freighters include 32 U.S.-flagged Category 2
powered large freighters, as well as numerous small vessels, under 2,000 GRT, such as ferries
that work on the Great Lakes and are powered by either Category 1 or Category 2 engines that
are subject to a different regulatory framework and therefore are not included in this analysis.
Steamships operating on the Great Lakes are also not included in the analysis because they are
excluded from the EGA fuel sulfur standards and are not covered by the engine NOx limits (see
Chapter 1). Finally, this analysis estimates costs for U.S. vessels only. While non-Canadian
foreign vessels are also required to comply with the EGA fuel sulfur limits when operating on the
U.S. side of the Great Lakes, they are assumed to have installed the relevant fuel hardware in
response to compliance with the North American EGA and not for the Great Lakes specifically.
Hardware costs for Canadian ships operating on the Great Lakes are also not presented in this
analysis. The costs for comparable Canadian vessels would be similar to the costs estimated
here, but are assumed to be incurred as a result of a Canadian national program and not as a
result of this program.
Table 6-1 Category 3 U.S. -Flagged Great Lakes Vessels
Ship Name
American Spirit
Hon. James L. Oberstar
Edgar B. Speer
Edwin H. Gott
James R. Barker
Lee A. Tregurtha
Maumee
Engine Manufacturer
Pielstick
Rolls-Royce Bergen
Pielstick
Enterprise
Pielstick
Rolls-Royce Bergen
Nordberg
6-2
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Chapter 6 Costs of Controlling Emissions
Ship Name
Mesabi Miner
Paul R. Tregurtha
Presque Isle
Roger Blough
Victory
Engine Manufacturer
Pielstick
MaK
Mirrlees Blackstone
Pielstick
Krupp - MAK
The fleet of twelve U.S.-flagged Category 3 vessels that ply the Great Lakes is diverse in
terms of age, size, and engine power. This fleet includes ten self-unloading bulk freighters as
well as two tugboats. Table 6-3 lists the detailed specifications for each of the 12 ships included
in this analysis.
The average age of these twelve vessels is just over 41 years old, and no vessel was built
after 1981. The oldest vessel is the Maumee, operated by the Grand River Navigation Company.
She was launched in 1929 and was initially a steam powered vessel; she was repowered with
diesel engines in 1964 and is pictured in Figure 6-1.
Figure 6-1 The Maumee Unloads Coal in Menominee, MI, August 1,2007
Source: Photo taken by and used with permission from Dick Lund, available here:
http://dlund.20m.com
With respect to size, the gross registered tonnage of these twelve vessels ranges from 950
to 36,400 tons, with an average of nearly 25,000 tons, compared to the 16,000 GRT average size
of all 57 U.S. freighters, large tugs, and ferries working on the Great Lakes. It should be noted
that there are six 1,000 foot U.S. freighters with Category 2 propulsion engines that operate on
the same routes as these twelve Category 3 ships.
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Chapter 6 Costs of Controlling Emissions
The main engine power of the U.S. Category 3 Great Lakes fleet ranges from 2,400 kW
to 14,500 kW, with an average of approximately 10,000 kW, compared to an average of 6,200
kW for all 57 U.S. ships in the fleet. All of the twelve U.S.-flagged Category 3 vessels currently
operate on residual fuel oil.
Table 6-2 Characteristics of the U.S.-Flagged Category 3 Powered Fleet
SHIP NAME
American Spirit
Hon. James L. Oberstar
Edgar B. Speer
Edwin H. Gott
James R. Barker
Lee A. Tregurtha
Maumee
Mesabi Miner
Paul R. Tregurtha
Presque Isle
Roger Blough
Victory
GROSS
REGISTERED
TONS
34,600
16,300
34,600
36,000
34,700
14,700
8,200
34,700
36,400
22,600
22,000
950
YEAR
BUILT
1978
1959
1980
1978
1976
1942
1929
1977
1981
1973
1972
1981
SHIP TYPE
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Tugboat
Self-Unloader
Tugboat
POWER
(kW)
11,900
6,300
14,400
14,500
11,900
6,000
2,400
11,900
12,000
11,200
11,900
5,900
OVERALL
LENGTH
1004'0"
806'0"
1004'0"
1004'0"
1004'0"
826'0"
604'9"
1004'0"
1013'6"
144'4"
858"
140'0"
YEAR
REPOWERED
2009
2006
1964
2010
ORE
CAPACITY
(gross tons)
62,400
31,000
73,700
74,100
63,300
29,300
12,650
63,300
68,000
57,500
43,900
NA
The two Category 3 powered tugboats are both articulated tug/barge combinations.
These two tugboats are each over 140 feet long and, according to Greenwood's 2010 Guide to
Shipping, both use residual fuel.3 While the use of residual fuel oil in a tugboat requires a
substantial amount of space for heating, centrifuging, filtering and otherwise conditioning the
fuel for use, very large tugboats such as the Victory and the Presque Isle have the space
necessary for this equipment.6 Each of these tugs is mated to a particular barge that she was
designed to work with: the Victory is paired with the barge James L. Kuber while the Presque
Isle is paired with the barge Presque Isle; both of these barges are self-unloading. Great Lakes
barges are often made out of older freighters and can be up to 740 feet long. For example, the
steamship Reserve was converted into the barge James L. Kuber.
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Chapter 6 Costs of Controlling Emissions
The Lee A. Tregurtha unloading. Source: Interlake Steamship Company Photo Gallery,
available here: http://www.interlake-steamship.com
6.1.2 Engineering Cost Methodology
This analysis is based on the cost analysis performed for the Coordinated Strategy as
announced in the 2010 Category 3 Rule and uses the same methodology. In the Coordinated
Strategy, the estimated hardware costs associated with fuel system and engine upgrades needed
to comply with the Coordinated Strategy are presented for a number of different vessel types and
sizes. To develop these cost estimates, the EPA contracted with ICF International (ICF) to
conduct a cost study of the various compliance strategies expected to be used to meet the new
fuel and engine requirements.7 A series of both slow-speed and medium-speed engine
configurations were selected and used to provide an understanding of the costs to apply emission
control technologies associated with fuel system upgrades and new engine emission standards.
Table 6-3 lists the engine configurations used in the Coordinated Strategy analysis. The engine
configurations were selected based on a review of 2005 U.S. Army Corps of Engineers
'Entrances and Clearances' data which was used to determine the characteristics of engines on
those vessels that call on U.S. ports most frequently. This data represents a broad range of
propulsion power for each engine type (slow and medium speed engines). The costs developed
for these engine configurations were used to develop a relationship between costs and engine
size ($/kW) that could be applied to estimate the compliance costs for any slow or medium speed
engine to obtain a hardware cost estimate for that engine.
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Chapter 6 Costs of Controlling Emissions
Table 6-3 Engine Configurations Used in the 2010 Category 3 Rulemaking Cost Analyses
ENGINE TYPE
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
BSFC (g/kWh)
MEDIUM-SPEED
4,500
9
35
650
9,500
12
65
550
18,000
16
95
500
210
LOW-SPEED
8,500
6
380
130
15,000
8
650
110
48,000
12
1400
100
195
For the cost analysis associated with the Coordinated Strategy, engine speed information
was not explicitly available, therefore, 2-stroke engines were assumed to be slow speed engines
(SSD), and 4-stroke engines were assumed to be medium speed engines (MSD); the same
assumption is used for this Great Lakes cost analysis. All twelve of the Category 3 Great Lakes
vessels discussed in this chapter were confirmed to be either medium-speed or powered by 4-
stroke engines, therefore, all twelve were assumed to be medium-speed engines.
After ICF developed their initial cost estimates, they provided surveys to several engine
and emission control technology manufacturers to determine the reasonableness of their
approach and cost estimates. Input received from those surveyed was incorporated into the final
cost estimates discussed in the 2010 analysis of the Coordinated Strategy. The resulting cost
estimates were used to determine a $/kW equation which could be scaled according to engine
type and size to arrive at a per vessel cost. These equations were presented in the 2010
Coordinated Strategy and are also presented in the Appendix to this chapter. In this analysis for
Great Lakes vessels, these equations are used along with the engine characteristics for each of
the twelve Category 3 Great Lakes vessels to estimate the cost per vessel for complying with the
EGA requirements on the Great Lakes.
The hardware cost estimates include variable costs for components, assembly, and
associated markup and fixed costs for tooling, research and development, redesign efforts, and
certification. For technologies sold by a supplier to an engine manufacturer, cost estimates are
based on a direct cost to manufacture the system components plus a 29 percent markup to
account for the supplier's overhead and profit.7 Variable costs also include a 29 percent markup
to account for both manufacturer and dealer overhead and carrying costs. We believe the
hardware costs from our Coordinated Strategy are applicable to this analysis as the engine and
hardware manufacturers available for repowering Great Lakes vessels are the same as those that
provide power for ocean-going vessels and produce engines that power similar sized vessels used
in other applications. Further details on these costs can be found in the Appendix to this chapter.
6.1.3 Estimates for Equipment to Accommodate the Use of Lower
Sulfur Fuel
There are different technologies that may be available to meet the EGA standards on the
Great Lakes, and we expect that each manufacturer or vessel owner/operator will evaluate all
possible technological avenues to determine how to minimize the cost of compliance. This cost
analysis, however, does make certain assumptions regarding compliance with the fuel sulfur
standards. In particular, this analysis assumes that the EGA fuel standards will be met through
the use of lower sulfur fuel. Alternative control strategies that provide equivalent reductions,
6-6
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Chapter 6 Costs of Controlling Emissions
such as scrubbers, can be used to meet the fuel standards; however, this section does not provide
cost estimates for this technology. Vessel owners would presumably use scrubbers only if this
were a lower-cost option.
This section presents the cost estimates for each of the twelve U.S.-flagged vessels to
install equipment to accommodate the use of lower sulfur fuel. Note that while these are EPA's
best estimates, actual estimates prepared by a shipyard for each vessel may be different.
Estimated costs to install this equipment include both fixed costs, generally for engineering and
tooling and variable costs generally for hardware and labor. As part of the effort to prepare an
analysis of the Coordinated Strategy, ICF developed cost estimates for installing equipment to
accommodate the use of lower sulfur fuel on existing vessels. This included separate estimates
for three low-speed engines and three medium-speed engines representing a range of power
ratings. The cost estimate was based on installing a new distillate fuel system to operate in
tandem with the original residual fuel system. The new hardware installed included new
distillate fuel tanks, fuel coolers, pumps, filters, and piping. It also included at least 480 hours of
labor to install the new equipment. Applying a curve fit to the cost data allowed us to develop an
equation for estimating the cost of compliance as a function of power rating for low-speed and
medium-speed engines. Using these equations, we estimated the compliance cost for modifying
each of the twelve U.S.-flagged Category 3 vessels to accommodate the use of lower sulfur fuel
based on the power rating of the installed main engine(s). In the case of Great Lakes vessels,
these figures may overestimate the actual cost; for example, it may be possible to convert the
original fuel tanks to hold distillate fuel instead of residual fuel, and it may be possible to remove
the fuel heating system. Appendix 6A of this document contains the details of the estimated fuel
system costs and the curve-fit equation.
Table 6-4 presents the estimated cost for each of the twelve Category 3 vessels operating
on the Great Lakes to modify their fuel system to accommodate the use of lower sulfur fuel. It is
estimated that the cost to install this hardware ranges from $42,000 to $71,000 per vessel.
Table 6-4 Estimated Hardware Costs for Equipment to Accommodate the Use of Lower Sulfur Fuel
SHIP NAME
American Spirit
Hon. James L. Oberstar
Edgar B. Speer
Edwin H. Gott
James R. Barker
Lee A. Tregurtha
Maumee
Mesabi Miner
Paul R. Tregurtha
Presque Isle
Roger Blough
Victory
ENGINE
POWER (kW)
11,900
6,000
14,400
14,500
11,900
6,000
2,400
11,900
12,800
11,200
11,200
5,900
EXISTING VESSEL
HARDWARE COSTS
$65,000
$51,000
$71 ,000
$71,000
$65,000
$51,000
$42,000
$65,000
$65,000
$63,000
$61 ,000
$50,000
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Chapter 6 Costs of Controlling Emissions
6.1.4 Estimated Costs of Repowering
Because Great Lakes vessels operate in fresh water, they have a very long service life; in
fact, the last new Category 3 vessel to enter the U.S. Great Lakes fleet was built in 1981. This
section, therefore, only presents the costs for modifications that would be made to existing
vessels as it is more likely that an existing vessel would be upgraded or repowered than it would
be for a new vessel to enter the fleet.
Category 3 vessels in the Great Lakes fleet are not expected to incur costs associated with
the engine standards, as the Tier 2 and Tier 3 standards for Category 3 engines apply only to new
engines. The cost to new vessels is presented in the Economic Impact Analysis of the 2010
Coordinated Strategy, which considered ocean-going vessels as well.8 Due to the longevity of
vessels that trade on the fresh-water Great Lakes, in many cases the hulls long outlive their
original power plants, and investments are made that increase the fuel efficiency of these vessels
by repowering them with new engines.9
While Great Lakes vessels can be repowered, this would be done in response to
individual company concerns and not to comply with a mandatory regulatory requirement as
there is no obligation for ships to repower. However, if they do repower there are requirements
the new engine must meet under Regulation 13 of Annex VI and the Clean Air Act. For
example, if a ship is repowered in 2016 the installer must look at using a Tier 3 engine, however,
if it is not possible for a Tier 3 engine to fit there are exemptions that can be granted to allow the
use of a Tier 2 engine in existing vessels. Therefore, this section will also report the estimated
additional costs to repower each of the twelve vessels with Tier 2 or Tier 3 compliant engines;
this section assumes a Category 3 vessel would be repowered with a Category 3 engine. The
appendix to this chapter shows how the Tier 2 and Tier 3 costs are estimated; more information
is contained in the analysis provided in the 2010 Category 3 rulemaking. Note that while these
are EPA's best estimates, actual estimates prepared by a shipyard for each vessel may be
different.
The estimated repowering costs presented below in Table 6-5 reflect the incremental cost
above the cost of the new engine that would be incurred as a result of purchasing a new engine
that is either Tier 2 or Tier 3 compliant. We estimate that the incremental cost of purchasing a
Tier 2 engine for the twelve Category 3 vessels would range from $53,000 to $111,000. This is
the incremental cost over that of a Tier 1 engine and assumes that the new engine would have the
same power rating as the existing engine. The estimated cost to repower with a Tier 3 compliant
engine includes the cost of an SCR system and ranges from $385,000 to $641,000. As stated
above, there is no obligation for a ship to repower; we are providing these incremental engine
costs for the sake of completeness. These costs include the cost of adding emission control
equipment that may be required to make the engine compliant with current standards; these costs
do not include the base engine costs, labor to install the engine, or any modifications to the
vessel that may be done during the repower; while the incremental engine costs presented here
would apply to any new engine, additional costs of installation may vary depending on a vessel's
existing powerplant and would likely be different for compression-ignition powered vessels than
for steamships.
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Chapter 6 Costs of Controlling Emissions
Table 6-5 Incremental Cost of Tier 2 and Tier 3 Compliant Engines
SHIP NAME
American Spirit
Hon. James L. Oberstar
Edgar B. Speer
Edwin H. Gott
James R. Barker
Lee A. Tregurtha
Maumee
Mesabi Miner
Paul R. Tregurtha
Presque Isle
Roger Blough
Victory
MAIN ENGINE
POWER (kW)
11,900
6000
14,400
14,500
11,900
6,000
2,400
11,900
12,800
11,200
11,200
5,900
TIER 2 ENGINE
COSTS (variable
and fixed costs)3
$104,000
$83,000
$110,000
$111,000
$104,000
$83,000
$53,000
$104,000
$105,000
$102,000
$101,000
$82,000
TIER 3 ENGINE AND
SCR COSTS (variable
and fixed costs)
$640,000
$488,000
$700,000
$710,000
$640,000
$488,000
$385,000
$640,000
$641,000
$617,000
$605,000
$478,000
a Tier 2 costs assume that all vessels had mechanical fuel injection and were upgraded to common rail for
Tier 2.
6.2 Estimated Fuel Operational Costs
Chapter 2 of this report presents the estimated increase in fuel operational costs
associated with the use of ECA-compliant fuel for certain routes along the Great Lakes including
both rail and ship activity. The same fuel prices were used in this chapter as were used in
Chapter 2 and are presented in U.S. $2008. This section will present the estimated increase in
vessel fuel costs for two of these routes and for four U.S.-flagged Category 3 vessels currently in
the Great Lakes fleet. These estimates are provided as an example of the costs a vessel owner
might see and are not meant to represent the typical or average costs for these routes for
Category 3 vessels. The methodology used here is intended to be consistent with the information
provided for these routes in Chapter 2 and uses the same assumptions for distance traveled, main
engine specific fuel oil consumption, and operating speed. Actual fuel operational costs for these
routes would vary with a number of factors, for example: maneuvering time, speed restrictions in
certain areas, actual specific fuel consumption of each vessel, and the installed engine power.
This section does not present a yearly fuel operational cost estimate for each vessel or for
the fleet as it is unknown what routes each vessel travels and how often, nor is it clear what layup
costs are or how these costs might be passed on to customers. This section also does not provide
an estimate of the annualized Great Lakes Category 3 fuel related operational costs associated
with the EGA. While we could use the CO2 numbers provided by the inventory to estimate the
total increase in fuel costs for all vessels operating within the Great Lakes inventory domain, we
only have an emissions inventory available for the U.S. side of the Great Lakes, and we do not
have a way to determine what percentage of this fuel is used by U.S.-flagged, Canadian-flagged,
or foreign-flagged vessels. In addition, we cannot distinguish how much of this fuel is used by
steamships as the usage patterns for U.S.-flagged steamships are unknown, and while the
percentage of steamships in the national inventory is small, estimated to be 3 percent of the
North American EGA, in terms of number of vessels, they make up a large portion of the U.S.-
flagged Great Lakes fleet, made up of thirteen U.S.-flagged steamships (this number includes
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Chapter 6 Costs of Controlling Emissions
both 12 diesel-powered steamships and one coal-fired steamship) compared to twelve U.S.-
flagged Category 3 vessels.
This section will present the estimated increase in fuel costs to a Category 3 vessel that
would be incurred during a one-way trip for two specific routes on the Great Lakes, due to a
switch from residual fuel to distillate fuel. This section uses vessel characteristic data published
in the 2010 Greenwood's Guide to Shipping and contained in Lloyd's Sea-web database.3'4
6.2.1 Estimated Trip Cost: Duluth-Superior, Minnesota to Gary,
Indiana
This analysis uses Scenario 7 presented in Chapter 2 to estimate the increase in fuel costs
a vessel would see when traveling along the water portion of this trip which starts at the port of
Duluth-Superior, Minnesota, and ends at Gary, Indiana, as shown in Figure 6-2 (it does not
include the land-based portion of this route from Hibbing, Minnesota to Duluth-Superior,
Minnesota). This scenario was based on a 1,000 foot vessel, therefore, the cost estimates for this
route could be applicable to the American Spirit and the Edwin H. Gott, both of which are over
1,000 feet long. The scenario also assumes that over 48,000 net tons of iron ore would be
hauled. Both the American Spirit and the Edwin H. Gott are capable of carrying this much ore,
and are representative of ships that could carry iron ore along this route.
Figure 6-2 Scenario 7: Iron Ore from the Duluth-Superior, Minnesota to Gary, Indiana
CASE STUDY 7
Legend
OD PAIRS
12!
DEFAULT - INTERMODAL
250
ALTERNATIVE - RAIL ONLY
500 Miles
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Chapter 6 Costs of Controlling Emissions
The actual main engine power for each vessel (11,900 kW and 14,500 kW respectively)
is used in this analysis with the main engine fuel consumption value of 231 g/kWh presented in
Chapter 2. The fuel consumption numbers were adjusted for the difference in energy density
between residual and distillate fuel as shown in Equation 6-2. Finally, the operating speed was
assumed to be 14 knots for the entire trip, consistent with Scenario 7. These values were input
into Equation 6-1 and Equation 6-2 to estimate the amount of fuel used by each vessel per one-
way trip for both distillate and residual fuel. The fuel prices used to estimate the increase in cost
per trip are the same as those presented in Chapter 2, $424 per tonne for residual fuel and $617
per tonne for distillate fuel. This results in an estimated increase in cost of approximately
$24,000 for the American Spirit and $30,000 for the Edwin H. Gott, as shown in Table 6-6
below.
Equation 6-1 Tonnes of Fuel Used per Trip per Vessel - Residual Fuel
~~ speed(knots) kWh
30000 Itom
g
'IC
Equation 6-2 Tonnes of Fuel Used per Trip per Vessel - Distillate Fuel
distance _(nm) *
1
speed(knots}
*BSFC
g
kWh
* power(kW) *
0
00000 \tonne
g
Table 6-6 Estimated Increased Fuel Costs per Vessel per One-Way Trip for Duluth-Superior to Gary, IN
VESSEL
NAME
American Spirit
Edwin H. Gott
MAIN
ENGINE
POWER
(kW)
11,900
14,500
VESSEL
SPECIFIC
RESIDUAL
FUEL
CONSUMPTION
(g/kWh)
231
231
OPERATING
SPEED
(knots)
14
14
COST PER
TRIP-
RESIDUAL
FUEL
$62,900
$76,700
COST PER
TRIP-
DISTILLATE
FUEL
$87,200
$106,300
ESTIMATED
INCREASE IN
FUEL COST
PER TRIP
$24,300
$29,600
6.2.2 Estimated Trip Cost: Stone from Calcite Quarry, MI to Bruce
Mansfield Power Station, OH
This analysis uses Scenario 16 presented in Chapter 2 to estimate the increase in fuel
costs an actual vessel may experience when traveling along the water portion of this trip from the
port of Roger City, MI to Ashtabula, OH, as shown in Figure 6-3. The two vessels used in the
analysis in this section are the 605 foot-long Maumee and the 806 foot-long Hon. James L.
Oberstar, both carry stone according to Lloyd's Sea-web database. The analysis in this section
estimates the one-way fuel operational cost increase of this vessel route. It should be noted that
this analysis is not intended to duplicate the cost analysis contained in the transportation mode
shift analysis reported in Chapter 2, which reflects operating costs for a composite vessel as
defined in that chapter.
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Chapter 6 Costs of Controlling Emissions
Figure 6-3 Scenario 16: Stone from the Calcite Quarry, MI to Bruce Mansfield Power Station, OH
Legend
CASE STUDY 16
OD PAIRS
125
DEFAULT INTERMODAL
250
ALTERNATIVE- RAIL ONLY
BRUCE MANSFIELD POWER STATION, SHIPPINGPORT. PA
The actual main engine power installed in the Maumee is just over 2,400 kW while the
Hon. James L. Oberstar has over 6,000 kW; the main engine fuel consumption value of 196
g/kWh that was used in Chapter 2 is also used here; as with the previous analysis, the fuel
consumption value was adjusted for the difference in energy density associated with the use of
distillate fuel. Finally, the operating speed was assumed to be 14 knots for the entire trip also
consistent with Scenario 16. These values were input into Equation 6-1 and Equation 6-2 to
estimate the amount of fuel used per vessel per one-way trip. Using the same fuel prices as those
presented in Chapter 2 ($424 per tonne for residual fuel and $617 per tonne for distillate fuel) we
estimate an increase in cost of approximately $2,100 for the Maumee and over $5,100 for the
Hon. James L. Oberstar, as shown in below in Table 6-7.
Table 6-7 Estimated Increased Fuel Costs per Vessel per Trip for Rogers City, MI to Ashtabula, OH
Vessel Name
The Maumee
Hon. James L.
Oberstar
Main Engine
Power (KW)
2,416
5,995
Vessel Specific
Residual Fuel
Consumption
(G/KWH)
196
196
Operating
Speed
(KNOTS)
14
14
Cost per trip
(Residual
Fuel)
$5,400
$13,300
Cost per trip
(Distillate
Fuel)
$7,800
$18,400
Estimated
Increase in Fuel
Cost per Trip
$2,400
$5,100
6-12
-------
Chapter 6 Costs of Controlling Emissions
6.2.3 Conclusion
The above analysis shows that fuel operating costs on the marine leg of the routes for
these scenarios are expected to increase by about 39 percent, which is consistent with the
expected increase in price per tonne of fuel.
6-13
-------
Chapter 6 Costs of Controlling Emissions
Al Engineering Costs for Existing Vessels to Accommodate the Use of Lower
Sulfur Fuel
A 1.1 Variable Costs to Existing Vessels to Accommodate the Use of Lower
Sulfur Fuel
All vessels including both new and existing vessels are required to meet the EGA lower
sulfur fuel (LFO) standards beginning in 2015 (with the exception of steamships). This section
discusses the vessel costs associated with the EGA standards that may be incurred if additional
hardware is required to accommodate the use of lower sulfur fuel in place of heavy-fuel oil
(HFO). Costs may include additional distillate fuel storage tanks, an LFO fuel separator, an
FTFO/LFO blending unit, a 3-way valve, an LFO cooler, filters, a viscosity meter, and various
pumps and piping depending on the configuration of the vessel undergoing a retrofit, these costs
are presented in Table 6-8.
Table 6-8 Variable Costs Associated with the use of Lower Sulfur Fuel - Existing Vessels
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
MEDIUM
9,500
12
65
550
Hardware Cost to Supplier
MEDIUM
18,000
16
95
500
LOW
8,500
6
380
130
LOW
15,000
8
650
110
LOW
48,000
12
1400
100
Component Costs
Additional Tanks
LFO Separator
HFO/LFO Blending
Unit
3 -Way Valve
LFO Cooler
Filters
Viscosity Meter
Piping/Pumps
Total Component Cost
$3,400
$2,800
$4,200
$950
$2,400
$950
$1,400
$2,000
$18,100
$5,500
$3,300
$4,700
$1,400
$2,800
$950
$1,400
$2,000
$22,100
$8,300
$3,800
$5,600
$1,900
$3,300
$950
$1,400
$2,000
$27,300
$4,600
$3,800
$4,700
$1,400
$2,800
$950
$1,400
$2,000
$21,600
$6,500
$4,200
$5,600
$1,900
$3,800
$950
$1,400
$2,000
$26,400
$13,700
$4,700
$6,600
$2,800
$4,700
$950
$1,400
$2,000
$36,900
Assembly
Labor (hours)
Cost($23.85/hr)
Overhead @40%
Total Assembly Cost
Total Variable Cost
Markupฎ 29%
Total Hardware RPE
480
$11,400
$4,600
$16,000
$34,100
$9,900
$44,000
640
$15,300
$6,100
$21,400
$43,400
$12,600
$55,000
960
$22,900
$9,200
$32,100
$59,300
$17,200
$76,500
640
$15,300
$6,100
$21,400
$43,000
$12,500
$55,500
960
$22,900
$9,200
$32,100
$58,400
$17,000
$75,400
1200
$28,600
$11,400
$40,000
$77,000
$22,300
$99,300
The estimated cost of new fuel tanks is presented here for informational purposes as it is
assumed that the Category 3 vessels operating on the Great Lakes would convert their existing
heavy-fuel oil tanks over to carry distillate. New distillate tanks are assumed to be constructed
6-14
-------
Chapter 6 Costs of Controlling Emissions
of cold rolled steel one mm thick, double walled, and are estimated to carry capacity sufficient
for 250 hours of propulsion and auxiliary engine operation. The tank size is based on 250 hours
of operation and when estimated to provide fuel for the six different engine configurations used
in this analysis tank sizes range from 240 m3 to nearly 2,000 m3, these costs are presented in
Table 6-9.
Table 6-9 Variable Cost to Associated with Fuel Switching - Extra Tankage
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
MEDIUM
9,500
12
65
550
MEDIUM
18,000
16
95
500
LOW
8,500
6
380
130
LOW
15,000
8
650
110
LOW
48,000
12
1400
100
Propulsion
BSFC (g/kWh)
Load factor
Auxiliary
Power (kW)
BSFC (g/kWh)
Load factor
210
73%
1,000
227
31%
210
73%
2,200
227
31%
210
73%
4,100
227
31%
195
73%
1,900
227
31%
195
73%
3,400
227
31%
195
73%
10,900
227
31%
Combined
Fuel Amount (kg)
Density (kg/mA3)
Tank Size (mA3)
Tank Material (mA3)
Tank Material Cost ($)
190,000
960
238
0.46
$2,500
401,000
960
501
0.75
$4,100
760,000
960
950
1.15
$6,200
336,000
960
350
0.59
$3,200
592,000
960
617
0.87
$4,700
1,896,000
960
1,975
1.88
$10,100
Assembly
Labor (hours)
Cost($23.85/hr)
Overhead@40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
5
$119
$48
$167
$2,600
$800
$3,400
6
$143
$57
$200
$4,300
$1,200
$5,500
7
$167
$67
$234
$6,500
$1,900
$8,400
10
$238
$95
$334
$3,500
$1,000
$4,500
12
$286
$114
$401
$5,100
$1,500
$6,600
15
$358
$143
$501
$10,600
$3,100
$13,700
The costs were developed for each of the six different engine sizes and types used in this
analysis. These values were used to develop a curve fit, as presented in Figure 6-4, used to
estimate a $/kW equation applicable to other engine sizes and types. As all twelve of the
Category 3 Great Lakes vessels are assumed to be powered with medium-speed diesels, the
medium speed cost equation was used to project the cost to each vessel.
6-15
-------
Chapter 6 Costs of Controlling Emissions
Figure 6-4 Variable Cost Curve Fit for Fuel Switching Vessels Costs to Existing Vessels
Fuel Switching Hardware Costs - Existing Vessels
* Slow Speed Fuel Switching -New Vessels
Medium Speed Fuel Switching -New Vessels
$120,000
$100,000
$80,000 -
$60,000 -
$40,000 -
$20,000 -
$0
y=24,600Ln(x)-164,700
15,000, $75,400
48,000, $99,300
8,500, $55,40
I
^9,500, $56,000
4,500, $44,000 y = 2.409x + 33,200
10,000
20,000 (kW) 30,000
40,000
50,000
60,000
A 1.2 Fixed Engineering Costs to Accommodate the Use of Lower Sulfur Fuel
The fixed costs associated with existing vessels switching to the use of lower sulfur fuel
are shown in Table 6-10 and are similar to the costs estimated for new vessels; however,
additional research and development is provided to test systems on existing ships.
Table 6-10 Fixed Costs for Fuel Switching Hardware Costs on Existing Vessels
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
MEDIUM
9,500
12
65
550
MEDIUM
18,000
16
95
500
LOW
8,500
6
380
130
LOW
15,000
8
650
110
LOW
48,000
12
1400
100
Fixed Costs
R&D Costs (0.33 year
R&D)
Marine Society Approval
Engines/yr.
Years to recover
Fixed cost/engine
$227,040
$5,000
40
5
$1,160
$227,040
$5,000
40
5
$1,160
$227,040
$5,000
40
5
$1,160
$227,040
$5,000
40
5
$1,160
$227,040
$5,000
40
5
$1,160
$227,040
$5,000
40
5
$1,160
6-16
-------
Chapter 6 Costs of Controlling Emissions
A2 Engineering Costs for Freshly Manufactured Engines
This section describes the projected variable and fixed costs to new engines that may be
incurred if a vessel operating on the Great Lakes is repowered with a new Category 3 Tier 2 or
Tier 3 engine sometime in the future. The component, tooling, labor and overhead costs are
presented here separately for Tier 2 and Tier 3.
A2.2 Engineering Costs for Tier 2 Engines
Tier 2 NOx standards are roughly 20 percent lower than the existing Tier 1 NOx
standards. To meet these standards, in-cylinder emission control approaches such as
electronically controlled high pressure common rail fuel systems, turbocharger optimization,
compression ratio changes and electronically controlled exhaust valves could be used.
A 2.2.1 Tier 2 Variable Costs
There are no variable costs associated with the Tier 2 engine modifications (such as
injection timing and valve timing adjustments, increased compression ratio, and nozzle
optimization) as the changes are not expected to require any additional hardware.10 However,
the migration of some engines from mechanical fuel injection (MFI) to common rail fuel systems
will require additional hardware including a control unit, common rail accumulators, low and
high pressure pumps, injectors and wiring harnesses and we will consider the variable costs
associated with these changes as part of the Tier 2 total costs. The cost of the Tier 2 technology
presented here was developed using Tier 1 technology as the baseline and assumes that all Great
Lakes vessels use mechanical fuel injection. Table 6-11 shows the per engine variable cost
estimates for the six engine configurations used in this analysis, and Figure 6-5 shows the cost
curve developed from these data points to determine a $/kW equation applicable to other engine
sizes.
Table 6-11 Variable Costs for Going from Mechanical Fuel Injection Systems to Common Rail
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
MEDIUM
9,500
12
65
550
MEDIUM
18,000
16
95
500
LOW
8,500
6
380
130
LOW
15,000
8
650
110
LOW
48,000
12
1400
100
Hardware Cost to Engine Manufacturer
Component Costs:
Electronic Control Unit
Common Rail Accumulators (each)
Number of Accumulators
Low Pressure Pump
High Pressure Pump
Modified injectors (each)
Number of injectors
Wiring Harness
Total Component Cost
$3,500
$2,000
3
$2,000
$3,500
$2,500
9
$2,500
$40,000
$3,500
$2,000
6
$3,000
$4,500
$2,500
12
$2,500
$55,500
$3,500
$2,000
8
$4,000
$6,000
$2,500
16
$2,500
$72,000
$5,000
$2,000
9
$2,500
$4,500
$3,500
18
$3,000
$96,000
$5,000
$2,000
12
$3,500
$6,000
$3,500
24
$3,000
$125,500
$5,000
$2,000
18
$4,500
$8,000
$3,500
36
$3,000
$182,500
6-17
-------
Chapter 6 Costs of Controlling Emissions
SPEED
MEDIUM
MEDIUM
MEDIUM
LOW
LOW
LOW
Assembly
Labor (hours)
Cost($23.85/hr)
Overhead @40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
120
$2,900
$1,100
$4,000
$44,000
$12,800
$56,800
160
$3,800
$1,500
$5,300
$60,800
$17,700
$78,500
200
$4,800
$1,900
$6,700
$78,700
$22,800
$101,500
200
$4,800
$1,900
$6,700
$102,700
$29,800
$132,500
250
$5,900
$2,400
$8,300
$133,800
$38,800
$172,600
300
$7,100
$2,900
$10,000
$192,500
$55,800
$248,300
Figure 6-5 Variable Cost Curve-Fit for Mechanically Controlled MFI to Common Rail Fuel Injection
Systems
Costs of Migrating from Mechanical Fuel Injection
to Common Rail
$300,000 i
$250,000 -
$200,000 -
ป $150,000 -
$100,000 -
$50,000 -
$0
ป"Slow Speed - Mechanical Injection"
Medium Speed Mechanical Injection
48,000, $248,000
y=67,OOOI_n(x)- 470,000
15,000, $173,OC
8,500, $132,000
18,000, $101,000
3,500, $78,000
4,500, $57,000
y = 32,OOOLn(x) - 215,000
10,000
20,000 (kW) 30,000
40,000
50,000
60,000
A 2.2.2 Tier 2 Fixed Costs
Tier 2 fixed costs are comprised of those costs associated with engine modifications
shown in Table 6-12, and those associated with the migration from mechanical fuel injection to
common rail shown in Table 6-13. The engine modification fixed cost estimates include
modification of fuel injection timing, increasing the compression ratio, fuel injection nozzle
optimization and Miller cycle effects. Retooling cost estimates include cylinder head and piston
rod shim modifications to increase compression ratios as well as to accommodate different
injection nozzles. Differential costs for new common rail fuel injection systems that replace
mechanical fuel injection systems include research and development, and retooling costs include
modification of the cylinder head to accommodate the common rail fuel injection systems.
6-18
-------
Chapter 6 Costs of Controlling Emissions
Table 6-12 Fixed Costs Estimated for Tier 2 Engine Modifications
ENGINE SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
Fixed Costs
R&D Costs (1 yearR&D)
Retooling Costs
Marine Society Approval
Engines/yr.
Years to recover
Fixed cost/engine
MEDIUM
4,500
9
35
650
$688,000
$750,000
$5,000
40
5
$7,200
MEDIUM
9,500
12
65
550
$688,000
$750,000
$5,000
40
5
$7,200
MEDIUM
18,000
16
95
500
$688,000
$750,000
$5,000
40
5
$7,200
LOW
8,500
6
380
130
$688,000
$1,000,000
$5,000
40
5
$8,500
LOW
15,000
8
650
110
$688,000
$1,000,000
$5,000
40
5
$8,500
LOW
48,000
12
1400
100
$688,000
$1,000,000
$5,000
40
5
$8,500
Table 6-13 Fixed Costs for Mechanical Fuel Injection to Common Rail Fuel Injection
ENGINE SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed
(rpm)
MEDIUM
4,500
9
35
650
Fixed Costs
R&D Costs (1 year
R&D)
Retooling Costs
Marine Society
Approval
Engines/yr.
Years to recover
Fixed cost/engine
$688,000
$1,000,000
$5,000
40
5
$8,500
MEDIUM
9,500
12
65
550
$688,000
$1,000,000
$5,000
40
5
$8,500
MEDIUM
18,000
16
95
500
$688,000
$1,000,000
$5,000
40
5
$8,500
LOW
8,500
6
380
130
$688,000
$1,000,000
$5,000
40
5
$8,500
LOW
15,000
8
650
110
$688,000
$1,000,000
$5,000
40
5
$8,500
LOW
48,000
12
1400
100
$688,000
$1,000,000
$5,000
40
5
$8,500
A2.3 Engineering Costs Associated with Tier 3
Tier 3 NOx standards are approximately 80 percent lower than the existing Tier 1 NOx
standards. To meet these standards, it is expected that selective catalytic reduction (SCR) will be
used along with engine modifications. A cost estimate is presented for each of the six engine
configurations used in this analysis.
A2.3.1 Tier 3 Variable Costs
The variable costs associated with the use of engine modifications for Tier 3 include the
use of two stage turbochargers and electronic valve actuation, and are shown in Table 6-14,
Figure 6-6 shows the cost curve used to determine a $/kW equation applicable to other engine
sizes and types. The methodology used here to estimate the capacity of the SCR systems is
6-19
-------
Chapter 6 Costs of Controlling Emissions
based on the power rating of the propulsion engines only. Auxiliary engine power represents
about 20 percent of the total installed power on a vessel; however, it would be unusual to operate
both propulsion and auxiliary engines at 100 percent load. Typically, ships operate under full
propulsion power only while at sea when the SCR is not operating; when nearing ports the
auxiliary engine is operating at high loads while the propulsion engine is operating at very low
loads.
Table 6-14 Variable Costs for Engine Modifications Associated with Tier 3
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
MEDIUM
9,500
12
65
550
MEDIUM
18,000
16
95
500
LOW
8,500
6
380
130
LOW
15,000
8
650
110
LOW
48,000
12
1400
100
Hardware Costs to the Manufacturer
Component Costs
2 Stage Turbochargers
(Incremental)
Electronic Intake Valves (each)
Intake Valves per Cylinder
Electronic Exhaust Valves
(each)
Exhaust Valves per Cylinder
Controller
Wiring
Total Component Cost
Markup @ 29%
Total Hardware RPE
$16,250
$285
2
$285
2
$3,750
$2,800
$33,000
$10,000
$43,000
$20,900
$285
2
$285
2
$3,750
$2,800
$41,000
$12,000
$53,000
$46,750
$285
2
$285
2
$3,750
$2,800
$72,000
$21,000
$93,000
$28,000
$425
4
$3,750
$2,800
$45,000
$13,000
$58,000
$42,000
$425
4
$3,750
$2,800
$62,000
$18,000
$80,000
$61,000
$425
4
$3,750
$2,800
$88,000
$25,000
$113,000
6-20
-------
Chapter 6 Costs of Controlling Emissions
Figure 6-6 Variable Cost Curve-Fit for Engine Modifications Associated with Tier 3
Estimated Costs for Tier 3 Engine Modifications
$140,000
Slow Speed - Engine Modifications
Medium Speed Engine Modifications
$20,000 -
$o
$120,000 -
$100,000
$80,000 -
$60,0008>500> $57,72
$40,000
y = 31661 Ln(x) - 226946 48,ooo, $113,456
18,000, $92,287
15,000, $80,
9,500, $53,058
4,500, $42,647
y=3.7768x +22378
10,000
20,000 (kW) 30,000
40,000
50,000
60,000
Table 6-15 shows the variable costs associated with the use of SCR, these costs include
the urea tank, the reactor, dosage pump, urea injectors, piping, bypass valve, the acoustic horn, a
cleaning probe and the control unit and wiring. Detailed costs for the urea tank are shown in
Table 6-16 and are based on the storage of urea sufficient for up to 250 hours of normal
operation of the SCR. It is envisioned that the urea tank is constructed of 304 stainless steel one
mm thick due to the corrosive nature of urea, at a cost of approximately $2,700 per metric ton
(tonne).11
Figure 6-7 shows the cost curve used to determine a $/kW equation applicable to other
engine types and sizes. The total variable hardware costs of Tier 3 estimated here include the
fuel injection changes, engine modifications, SCR, and the costs associated with the requirement
to test each production engine (ง1042.302). We estimate that, on average, this requirement
would add a one-time cost of $10,000 for each new engine.
Table 6-15 Variable Costs Associated with the Use of SCR
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
MEDIUM
9,500
12
65
550
MEDIUM
18,000
16
95
500
LOW
8,500
6
380
130
LOW
15,000
8
650
110
LOW
48,000
12
1400
100
Hardware Costs to the Supplier
6-21
-------
Chapter 6 Costs of Controlling Emissions
Component Costs
Aqueous Urea Tank
Reactor
Dosage Pump
Urea Injectors (each)
Number of Urea
Injectors
Piping
Bypass Valve
Acoustic Horn
Cleaning Probe
Control Unit/Wiring
Total Component Cost
Assembly
Labor (hours)
Cost ($23.85/hr)
Overhead @40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
$1,200
$200,000
$9,500
$2,400
3
$4,700
$4,700
$9,500
$575
$14,000
$251,000
1000
$23,900
$9,500
$33,400
$284,800
$82,600
$367,400
$1,900
$295,000
$11,300
$2,400
6
$5,600
$5,600
$11,300
$575
$14,000
$360,000
1200
$28,600
$11,400
$40,000
$399,700
$115,900
$515,600
$2,800
$400,000
$13,000
$2,400
8
$6,600
$6,600
$13,000
$575
$14,000
$476,000
1500
$35,800
$14,300
$50,100
$525,800
$152,500
$678,300
$1,700
$345,000
$11,300
$2,400
12
$5,600
$5,600
$11,700
$700
$19,000
$429,000
1200
$28,600
$11,400
$40,000
$469,400
$136,100
$605,500
$2,400
$560,000
$13,000
$2,400
16
$7,500
$6,600
$14,000
$700
$19,000
$662,000
1600
$38,200
$15,300
$53,500
$715,000
$207,300
$922,300
$4,600
$1,400,000
$15,000
$2,400
24
$9,500
$7,500
$16,400
$700
$19,000
$1,530,000
2000
$47,700
$19,100
$66,800
$1,597,100
$463,200
$2,060,300
Figure 6-7 Variable Cost Curve-Fit for SCR Systems
Estimated Tier 3 Selective Catalytic Reduction
Costs
$2,500,000
$2,000,000
$1,500,000
Slow Speed -SCR Medium Speed SCR
$1,000,000
$500,000
$0
y = -0.0004X2 + 57.2x + 145,000
48,000, $2,100,00]
15,000, $922,000
8,5 )0, $606,000
18,000, $678,000
3^00, $516,000
4,500, $367,00
y=22.6x +279,000
10,000
20,000 (kW) 30,000
40,000
50,000
60,000
6-22
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Chapter 6 Costs of Controlling Emissions
Table 6-16 Variable Costs Associated with the Urea Tanks for use with SCR Systems
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
Urea Tank Costs
Urea Amount (kg)
Density (kg/mA3)
Tank Size (mA3)
Tank Material (mA3)
Tank Material Cost ($)
Assembly
Labor (hours)
Cost ($23.85/hr)
Overhead @40%
Total Assembly Cost
Total Variable Cost
Markupฎ 29%
Total Hardware RPE
MEDIUM
4,500
9
35
650
12,910
1,090
14
0.04
$758
5
$119
$48
$167
$925
$268
$1,194
MEDIUM
9,500
12
65
550
27,255
1,090
30
0.06
$1,248
6
$143
$57
$200
$1,448
$420
$1,868
MEDIUM
18,000
16
95
500
51,642
1,090
57
0.09
$1,909
7
$167
$67
$234
$2,143
$621
$2,765
LOW
8,500
6
380
130
22,645
1,090
21
0.05
$977
10
$238
$95
$334
$1,310
$380
$1,690
LOW
15,000
8
650
110
39,961
1,090
37
0.07
$1,426
12
$286
$114
$401
$1,826
$530
$2,356
LOW
48,000
12
1400
100
127,875
1,090
117
0.14
$3,093
15
$358
$143
$501
$3,594
$1,042
$4,636
A 2.3.2 Tier 3 Fixed Costs
The Tier 3 fixed costs presented here include those associated with the use of SCR,
including research and development costs, marine society approval, and retooling for the
redesign of the exhaust system to accommodate the SCR unit; the costs are shown in Table 6-17.
The migration to common rail from Tier 3 is primarily from electronic fuel injection which
includes modification of the cylinder head to accommodate common rail fuel injection systems,
these costs are shows in Table 6-18. The fixed costs associated with the migration from
mechanical fuel injection to common rail are shown above in Table 6-13. Finally, Tier 3 also
includes the fixed costs associated with the engine modifications which include the use of two
stage turbochargers and electronic valve actuation; the retooling costs represent turbocharger
redesign and valve actuation modifications as shown in Table 6-19.
Table 6-17 Fixed Costs Associated with the use of SCR for Tier 3
ENGINE SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
Fixed Costs
R&D Costs (1 year
R&D)
Retooling Costs
Marine Society
Approval
$1,376,000
$2,000,000
$5,000
MEDIUM
9,500
12
65
550
$1,376,000
$2,000,000
$5,000
MEDIUM
18,000
16
95
500
$1,376,000
$2,000,000
$5,000
LOW
8,500
6
380
130
$1,376,000
$2,000,000
$5,000
LOW
15,000
8
650
110
$1,376,000
$2,000,000
$5,000
LOW
48,000
12
1400
100
$1,376,000
$2,000,000
$5,000
6-23
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Chapter 6 Costs of Controlling Emissions
Engines/yr.
Years to recover
Fixed cost/engine
40
5
$16,900
40
5
$16,900
40
5
$16,900
40
5
$16,900
40
5
$16,900
40
5
$16,900
Table 6-18 Fixed Costs Associated with the Migration of Electronic Fuel Injection to Common Rail
ENGINE SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
Fixed Costs
R&D Costs (0.5 year
R&D)
Retooling Costs
Marine Society Approval
Engines/yr.
Years to recover
Fixed cost/engine
$344,000
$500,000
$5,000
40
5
$4,200
MEDIUM
9,500
12
65
550
$344,000
$500,000
$5,000
40
5
$4,200
MEDIUM
18,000
16
95
500
$344,000
$500,000
$5,000
40
5
$4,200
LOW
8,500
6
380
130
$344,000
$500,000
$5,000
40
5
$4,200
LOW
15,000
8
650
110
$344,000
$500,000
$5,000
40
5
$4,200
LOW
48,000
12
1400
100
$344,000
$500,000
$5,000
40
5
$4,200
Table 6-19 Fixed Costs Associated with Engine Modifications Used for Tier 3
ENGINE SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
Fixed Costs
R&D Costs (1 year
R&D)
Retooling Costs
Marine Society
Approval
Engines/yr.
Years to recover
Fixed cost/engine
$688,000
$1,000,000
$5,000
40
5
$8,500
MEDIUM
9,500
12
65
550
$688,000
$1,000,000
$5,000
40
5
$8,500
MEDIUM
18,000
16
95
500
$688,000
$1,000,000
$5,000
40
5
$8,500
LOW
8,500
6
380
130
$688,000
$1,320,000
$5,000
40
5
$10,000
LOW
15,000
8
650
110
$688,000
$1,320,000
$5,000
40
5
$10,000
LOW
48,000
12
1400
100
$688,000
$1,320,000
$5,000
40
5
$10,000
6-24
-------
Chapter 6 Costs of Controlling Emissions
Chapter 6 References
1 U.S. EPA, April 30, 2010, Final Rule: Control of Emissions of Air Pollution from New Marine Compression-
Ignition Engines at or Above 30 Liters per Cylinder. Available at: http://www.epa.gov/otaq/oceanvessels.htm
2 See Tables 7-2 and 7-3 of Chapter 7 of the Category 3 Regulatory Impact Analysis that can be accessed here:
http ://www. epa. gov/otaq/regs/nonroad/420r09019-chp07 .pdf
3 2010 Greenwood's Guide to Great Lakes Shipping. Harbor House Publishers, Inc., Boyne City, Michigan.
4 Lloyd's Sea-Web database of ships, accessed August, 2010 from www.sea-web.com
5 See comments of the Great Lakes Maritime Task Force, Docket Item EPA-HQ-OAR-2007-0121-0269 at
http://www.regulations.gov
6 Walsh, Gregory M, April, 2008, "Economical heavy fuel oil finding its way into the tugboat industry." Published
in issue #112 of the Professional Mariner, available here:
http://www.professiomlmariner.com/ME2/dirmod.asp?sid=420C4D38DC9C4E3A903315CDDC65AD72&nm=Arc
hives&type=Publishing&mod=Publications%3A%3AArticle&mid=8F3A7027421841978F18BE895F87F791&tier=
4&id=FlDFA02472A643369559CCF5F5AC618F
7ICF International, "Costs of Emission Reduction Technologies for Category 3 Marine Engines," prepared for the
U.S. Environmental Protection Agency, December 2008. EPA Report Number : EPA-420-R-09-008.
8 See Tables 7-2 and 7-3 of Chapter 7 of the Category 3 Regulatory Impact Analysis that can be accessed here:
http ://www. epa. gov/otaq/regs/nonroad/420r09019-chp07 .pdf
9 Marine Log, July, 2010, Rand Logistics to Repower Lakes steamship. Available here:
http://www.marinelog.com/DOCS/NEWSMMIX/2010jul00271 .html
10 MAN Diesel, "Exhaust Gas Emission Control Today and Tomorrow, August 19, 2008," available at
http://www.manbw.com/article 009187.html
11 See http://www.metalprices.com/FreeSite/metals/stainless_product/product.asp#Tables for 2006.
6-25
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Chapter 7: Industry Characterization
CHAPTER 7: Industry Characterization
This chapter provides a description of the Great Lakes shipping sector, specifically the
ships that are affected by the engine and fuel standards recently finalized in our Category 3
marine rule (75 FR 22896, April 30, 2010). We briefly describe the Great Lakes marine
transportation system, the ships operating within that system, the cargoes they carry, and where
they take those cargoes.
The primary purpose of this industry characterization is to provide information with
respect to those ships on the Great Lakes that will be subject to the Coordinated Strategies. With
respect to fuel production and availability, the Great Lakes were included in the fuel sector
analysis prepared for the North American EGA application. That analysis can be found on our
website, www.epa.gov/otaq/oceanvessels.htm. Additional information on many aspects of the
Great Lakes Transportation System can be found in Appendix A to this chapter.
7.1 The Great Lakes Transportation System At-a-Glance
The Great Lakes are an important part of our national and regional transportation system
carrying large quantities of raw materials such as iron ore, coal, grain, and crushed stone from
the northern and western part of the lakes to places where these resources are used locally,
shipped farther inland, or shipped to the rest of the world. Ships are one part of the system, and
primarily carry bulk cargo port-to-port. Some of those materials are used at the point of
discharge, while others are shipped inland, primarily by rail. Figure 7-1 illustrates the
interconnectedness of ship and rail links and shows how Great Lakes shipping is integrated into
the region's transportation system.
7-1
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Chapter 7: Industry Characterization
Figure 7-1 Great Lakes Maritime Information Delivery System - Docks, Waterways and Railroads
Source: Department of Geography and Planning: Center for Geographic Information Sciences and
Applied Geographies (GISAG), 2007
According to Greenwoods Guide to Great Lakes Shipping 2010, there are about 130
commercial ports and docks on the Great Lakes that can handle shipments of coal, iron ore, and
stone; still others handle grain and other bulk goods (the main Great Lakes ports are illustrated in
Figure 7-2). These ports and docks range from very large facilities like those in Superior,
Wisconsin and Duluth, Minnesota to small docks that may service one plant. In addition to these
ports and docks, actual cargo origins and destinations can be located well inland of the Great
Lakes. For example, coal can be shipped by rail from Montana to Duluth on Lake Superior and
then be transported to power plants on the St. Clair River in Michigan. Similarly, stone can be
shipped from mines on the shores of Lake Michigan through Toledo, Ohio, and then shipped by
rail to the Ohio River Valley for use in power plant scrubbers.
The amount of cargo annually shipped on the Great Lakes is significant. The data in
Table 7-1 show that cargo carried annually on the five Great Lakes themselves, excluding the St.
Lawrence River system downstream of Buffalo, amounts to over half of the annual cargo
shipments on the Mississippi River system.
Table 7-1 Annual Shipments, Great Lakes and Mississippi River (million short tons)
Mississippi River Total
Great Lakes Dry Bulk
2000
327
177
2001
317
166
2002
316
164
2003
308
155
2004
313
170
2005
299
165
2006
314
170
2007
313
157
2008
295
157
" A majority of the cargo shipped on the Great Lakes is dry bulk.
Sources: http://www.lcaships.com/TONPAGE.HTM. http://www.shipowners.ca/index.php?page=annual-report-and-
statistics. http://www. seaway.ca/en/seawav/facts/traffic/index.html
7-2
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Chapter 7: Industry Characterization
Figure 7-2 Great Lakes Ports
ASHLAND*..
ซ..
MARQUETTE '
"*-. GLADSTONE
-'.
ESCANABA
MUNIS1NG
PORT INLAND
MENOM1NEE ,'f,f
MARiNETTEal
I
MUWUAKEE
WAUKEGAN
GO*
INDIANA HARBOR
Source: www.portofmonroe.com/
BENTON HARBOR
RIVER ROUGE
PCORSFm
OGDENSBURG
OSWEGO
BUFFtNGTON GARY
HARBOR
7-3
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Chapter 7: Industry Characterization
7.2 Top 10 Great Lakes Ports
The Army Corps of Engineers keeps track of the amount and type of freight delivered
and shipped for 83 ports along the Great Lakes.1 Of these 83 ports, 12 did not receive any cargo
in 2008, and little to no cargo from 2004 through 2007. Of the other 71 ports, Duluth-Superior
(Duluth MN, Superior, WI) had the largest quantity of shipments in 2008, more than twice the
tonnage of the second largest port, Chicago, IL. All but one of the top ten Great Lakes ports
handle primarily coal and iron ore. The exception is Chicago, which handles a wider variety of
cargo. The top ten U.S. ports on the Great Lakes in terms of tonnage handled in 2008 are listed
Table 7-2, along with their 2008 cargo figures and primary commodity.
Table 7-2 Ten Largest Ports in terms of Tonnage in 2008
PORT
Duluth, Mi-
Superior, WI
Chicago, IL
Detroit Harbor,
MI
Indiana Harbor,
IN
Two Harbors,
MN
Toledo, OH
Cleveland, OH
Gary, IN
Presque Isle, MI
St. Clair, MI
PORT DESCRIPTION
Superior Bay and its tributaries, St.
Louis Bay and St. Louis River, and
Allouez Bay.
Chicago Harbor, Chicago River,
Chicago Sanitary and Ship Canal, Lake
Calumet, IL, Calumet Harbor and
River, IL and IN.
U.S. bank of Detroit River from Lake
St. Clair to western extreme of Zug
Island.
Entire Harbor, Indiana Harbor Canal,
including the Calumet River Branch to
Columbus Drive Bridge and the Lake
George Branch.
Entire Harbor
Channel in Lake Erie and 7 miles in
lower Maumee River.
Outer Harbor, Old River and Cuyahoga
River from mouth to and including
Upper Republic Steel Corp. Dock,
Entire harbor.
Entire harbor.
West bank of St. Clair River at St.
Clair, MI
2008 TOTAL
TONNAGE
RECEIVED
AND
SHIPPED
(SHORT
TONS)
45,341,000
22,659,000
17,752,000
15,380,000
13,433,000
10,955,000
10,637,000
9,030,000
8,808,000
7,880,000
PRINCIPAL
COMMODITY
HANDLED IN
TERMS OF
TONNAGE
Coal
Coal
Iron ore
Iron ore
Iron ore
Iron ore
Iron ore
Iron ore
Iron ore
Coal
% OF TOTAL
TONNAGE
HANDLED
BY
PRINCIPAL
COMMODITY
48%
22%
46%
76%
100%
42%
49%
94%
73%
100%
Figure 7-3 shows the tonnages moved by the ten busiest Great Lakes ports from 2004
through 2008. Four of the ten ports have seen declines in tonnage handled since 2004, including
the ports of: Detroit, MI; Indiana Harbor; Cleveland, OH; and Presque Isle, MI. All four of these
ports handle iron ore as their primary cargo. Overall, the graph shows relatively steady traffic
since 2004.
7-4
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Chapter 7: Industry Characterization
Figure 7-3 Tonnages Moved by the Ten Busiest Great Lakes Ports 2004-2008
V)
I
t
O
20
10
Duluth-Superior
Chicago, IL
Detroit Harbor, Ml
Indiana Harbor, IN
Two Harbors, MN
Toledo, OH
Cleveland, OH
Gary, IN
Presque Isle, Ml
St. Clair, Ml
2004
2005
2006
2007
2008
7.2.1 Duluth, MN - Superior, WI
The "Twin Ports" of Duluth-Superior combine to represent the largest volume port in the
Great Lakes/St. Lawrence Seaway system, it is the second largest dry-bulk port in the U.S., and
one of the top 20 ports in the U.S. overall.2 Duluth-Superior is a multi-modal hub for both
domestic and international cargo; industries accommodated at this port include: agriculture,
forestry, mining, manufacturing, construction, power generation, and passenger cruising.
Located at the head of the Great Lakes, Duluth-Superior functions primarily as a loading port for
iron ore mined and processed into taconite from northern Minnesota's Missabe Range, for grain
produced in Minnesota and North and South Dakota, and for coal transported via rail from mines
in the Powder River Basin of Wyoming and Montana.
The port of Duluth-Superior handles an average of 46 million short tons of cargo and
over 1,100 vessel visits each year along its 49 miles of waterfront, supporting about 2,000 local
jobs. This port has been designated as Foreign Trade Zone which provides incentives for
international shippers as the port looks for opportunities to handle containers in the future.
Currently, iron ore and coal account nearly evenly for about 80 percent of the port's total
tonnage; nearly 20 million tons of low-sulfur coal from Montana and Wyoming are transferred
here for delivery via marine transport to utility and manufacturing plants on the lower Great
Lakes. Outbound shipments of grain harvested in the Midwest headed for Europe and Africa
account for five to ten percent of the Port's annual tonnage. Inbound shipments of other bulk
commodities such as limestone, salt, and cement account for another ten percent. Table 7-3 lists
the ten commodities handled most often in the port of Duluth-Superior in 2008; these ten
commodities represent over 99 percent of all commodities handled at this port.
7-5
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Chapter 7: Industry Characterization
Table 7-3 Port of Duluth-Superior: Top Commodities Handled in 2008 (short tons)
COMMODITY
Coal & Lignite
Iron Ore
Limestone
Wheat
Cement & Concrete
Non-Metallic Mineral NEC (ex. Common Salt)
Animal Feed, Prepared
Oats
Slag
Clay & Other Refractory Minerals
All Commodities
TONNAGE
(short tons)
21,740,637
18,760,970
2,913,831
635,286
291,797
227,580
188,639
175,759
153,740
99,635
PERCENTAGE OF
ALL TONNAGE
47.9%
41.4%
6.4%
1.4%
0.6%
0.5%
0.4%
0.4%
0.3%
0.2%
45,341,808
7.2.2 Chicago, IL
The Port of Chicago is an intermodal facility that also connects barge traffic traveling up
from the Gulf of Mexico via the Mississippi River to the Great Lakes.3 It is the leading 'general
cargo' port on the Great Lakes, and moves an average of over 26 million tons of natural
resources and other goods. The Port of Chicago is near five federal highways and six major
railroads as well as a large airport. Facilities include the Iroquois Landing Lakefront Terminus
which specializes in intermodal container services and is on a 100-acre parcel with 3,000 linear
feet of ship and barge berthing space and a navigational depth of 27 feet. There are also two
storage facilities with well over 100,000 sq ft and direct access to rail and truck services. Lake
Calumet, part of the Port of Chicago also offers terminals approximately 6 miles inland from
Lake Michigan; in addition, Lake Calumet offers 3,000 linear feet of ship and barge berthings
and over 315,000 sq ft of shed storage.
The Port of Chicago also includes a Foreign Trade Zone which comprises a 60-mile
radius from the city limits of Chicago. It includes 400,000 sq ft of warehouse space and 20 acres
of developable land for the storage, handling, processing, manufacturing, and/or assembling of
foreign goods. Finally, the Port of Chicago also offers grain and bulk liquid storage capable of
holding 14 million bushels and 800,000 barrels respectively. The Port handles a wide variety of
goods including: steel, scrap metals, cement, coke, stone, ore, vegetable oil, sugar, and many
others, and provides over 3,300 jobs directly related to the Port. Table 7-4 shows the top ten
commodities handled by the Port of Chicago in 2008. These ten commodities represent over 79
percent of all tonnage handled at this port.
7-6
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Chapter 7: Industry Characterization
Table 7-4 Port of Chicago: Top Commodities Handled in 2008 (short tons)
COMMODITY
Coal & Lignite
Sand & Gravel
Non-Metallic Mineral NEC (ex. Common Salt)
Petroleum Coke
Cement & Concrete
Limestone
Iron & Steel Scrap
Distillate Fuel Oil
Iron Ore
Pig Iron
All Commodities
TONNAGE
(short tons)
4,872,272
2,940,254
2,335,214
2,331,050
1,326,982
1,101,997
864,939
799,123
784,146
649,484
PERCENTAGE OF
ALL TONNAGE
22%
13%
10%
10%
5.9%
4.9%
3.8%
3.5%
3.5%
2.9%
22,659,554
7.2.3 Detroit Harbor, MI
The Port of Detroit services southeast Michigan's busy manufacturing sector, which is
still heavily dominated by the automotive industry.4 The Port also offers rail and trucking
services. There are two main companies that depend on this port: Thyssen Krupp and Corus
(formerly British Steel). Nearly one-third of the cargo that is handled by the Port is imported by
Thyssen for their fabrication plant in Southwest Detroit that serves the automotive industry. The
Port is near three main highways and the Ambassador Bridge that crosses to Canada. The Port
covers approximately 35 acres with docks over 2,100 feet in length and a depth of 27 feet, and
offers 128,000 sq ft of covered storage. The Port supported over 5,800 jobs directly as of 2005,
as well as generated over $201 million in tax revenue and over $164 million in business revenue.
Table 7-5 shows the top ten commodities handled by the Port of Detroit Harbor in 2008, these
ten commodities represent over 96 percent of all tonnage handled at this port.
Table 7-5 Port of Detroit Harbor: Top Commodities Handled in 2008 (short tons)
COMMODITY
Iron Ore
Limestone
Coal & Lignite
Cement & Concrete
Non-Metallic Mineral NEC (ex. Common Salt)
Asphalt, Tar & Pitch
Petroleum Coke
Slag
Sand & Gravel
Coal Coke
All Commodities
TONNAGE
(short tons)
5,363,333
1,964,950
1,844,784
946,072
837,382
400,951
379,380
270,649
193,829
159,308
PERCENTAGE OF
ALL TONNAGE
42%
15%
14%
7.4%
6.5%
3.1%
3.0%
2.1%
1.5%
1.2%
12,836,319
7-7
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Chapter 7: Industry Characterization
7.2.4 Indiana Harbor, IN
The Port of Indiana Harbor, shown in Figure 7-4, is on the southwestern shore of Lake
Michigan, in East Chicago, Indiana.5 It is an artificial waterway that connects the Grand
Calumet River to Lake Michigan and is made up of two canals: the two kilometer Lake George
Branch and the three-kilometer Grand Calumet River Branch. The Port supports a number of
companies including ArcelorMittal, and handles cargo such as: iron ore, limestone, coke, steel,
gypsum, cement, concrete, and petroleum products as BP has a refinery near this port. Indiana
Harbor primarily carries iron ore (over 76 percent), although it handled over one million short
tons of limestone in 2008. Table 7-6 shows the top ten commodities, in tons, handled by the Port
of Indiana Harbor in 2008. These commodities represent over 98 percent of the total tonnage
handled that year.
Figure 7-4 Indiana Harbor, IN
Source: U.S. Army Corps of Engineers
Table 7-6 Port of Indiana Harbor: Top Commodities Handled in 2008 (short tons)
COMMODITY
Iron Ore
Limestone
Slag
Coal Coke
Distillate Fuel Oil
Asphalt, Tar & Pitch
Iron & Steel Plates & Sheets
Gasoline
Petroleum Coke
Aluminum Ore
All Commodities
TONNAGE
(short tons)
11,738,007
1,241,768
595,043
341,815
290,778
280,244
198,297
142,337
142,186
111,369
PERCENTAGE OF ALL
TONNAGE
76%
8.1%
3.9%
2.2%
1.9%
1.8%
1.3%
0.9%
0.9%
0.7%
15,380,630
7-S
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Chapter 7: Industry Characterization
7.2.5 Two Harbors, MN
Two Harbors is primarily engaged in loading iron ore and has been doing so for over one
hundred and twenty-five years as the first ship to leave this port loaded with iron ore did so in
1884.6 This Port is located on the north shore of Lake Superior, approximately 27 miles
northeast of Duluth, MN.7 U.S. Steel and Canadian National companies are major stakeholders
for this Port. The bulk commodities which pass through this harbor generate over $120 million
annually and directly support 2,400 jobs. Since 2004, Two Harbors has handled iron ore almost
exclusively as it has made up over 99 percent of the tonnage handled by this port each year. In
2008, Two Harbors only handled two different types of cargo, over 13 million tons of iron ore
(short tons) and nearly 60,000 tons of limestone.
7.2.6 Toledo, OH
The Lake Erie port of Toledo, Ohio is a multi-modal transportation hub with heavy rail,
highway and air cargo activity as well as its waterborne traffic.8 Waterborne cargo movement
through Toledo involves the U.S.-Canadian interlake trades, coastal trades and the overseas St.
Lawrence Seaway trades. Three commodities - coal, iron ore and grain - account for almost 90
percent of the tonnage moved through the port. This Port also has a Foreign Trade Zone and
handles over 12 million tons of cargo and 700 vessel calls each year. The Toledo Shipyard is
home to one of the only U.S. full service shipyards with graving docks on the lower lakes.
Recent property acquisitions by the Port have allowed it to become the largest land mass seaport
on the Great Lakes. This port is located at a national crossroads of four railroads including:
Norfolk Southern, CSX, Canadian National, and Wheeling & Lake Erie, as well as two
transcontinental highways. The Port of Toledo offers four grain terminals with a combined 22
million bushel storage capacity. Table 7-7 shows the top ten commodities in terms of tonnages
handled by the Port of Toledo, which represent over 92 percent of the total tonnage handled by
this port in 2008.
Table 7-7 Port of Toledo: Top Commodities Handled in 2008 (short tons)
COMMODITY
Iron Ore
Coal & Lignite
Limestone
Non-Metallic Mineral NEC
Sand & Gravel
Soybeans
Coal Coke
Cement & Concrete
Gasoline
Corn
All Commodities
TONNAGE
(short tons)
4,574,172
3,031,652
564,091
368,531
363,964
276,681
271,964
257,454
251,595
191,822
10,954,686
PERCENTAGE OF
ALL TONNAGE
42%
28%
5.1%
3.4%
3.3%
2.5%
2.5%
2.4%
2.3%
1.8%
7-9
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Chapter 7: Industry Characterization
7.2.7 Cleveland, OH
The Port of Cleveland handles about 12 million to 16 million metric tons annually of
international and interlake cargos with eight international cargo docks and 110 acres of land
situated along Lake Erie as well as the 44 acre site of the Cleveland Bulk Terminal facility.9 It is
also home to a number of Great Lakes fleet offices and to the Lake Carriers' Association, which
represents the U.S.-flag vessel operators on the Great Lakes. Primary cargoes handled include
inbound and outbound steel and heavy machinery. The Cleveland Bulk Terminal features an
automated iron ore loader that can move ore at a rate of 5,200 tons per hour. This port supports
the Cleveland-Cliffs iron ore pellet supplier, Mittal Steel's mills, and Oglebay Norton Co. that
utilize and transport these materials. The Port of Cleveland offers nine berths, 6,500 linear feet of
dock space with a depth of 27 feet; in addition they also offered over 300,000 square feet of
storage. Table 7-8 shows the top ten commodities in terms of tonnages handled by the Port of
Cleveland, which represent over 97 percent of the total tonnage handled by this port in 2008.
Table 7-8 Port of Cleveland: Top Commodities Handled in 2008 (short tons)
COMMODITY
Iron Ore
Limestone
Non-Metallic Mineral NEC
Cement & Concrete
Sand & Gravel
Iron & Steel Primary Forms
Slag
Asphalt, Tar & Pitch
Iron & Steel Plates & Sheets
Residual Fuel Oil
All Commodities
TONNAGE
(short tons)
5,159,314
2,995,005
700,104
527,842
364,565
168,094
132,633
125,147
107,136
73,904
PERCENTAGE OF
ALL TONNAGE
49%
28%
6.6%
5.0%
3.4%
1.6%
1.2%
1.2%
1.0%
0.7%
10,637,330
7.2.8 Gary, IN
The Port of Gary is operated by the U.S. Steel Corporation where the Gary Works, U.S.
Steel's largest manufacturing plant is located on the south shore of Lake Michigan.10 This port
handles commodities such as: coal and petroleum coke, limestone, iron ore, iron and steel scrap,
non-ferrous scrap and ores, clay and refractory materials, slag, and iron and steel plates and
sheets. In Gary, U.S. Steel makes 7.5 million net tons of raw steel, and also operates three coke
batteries with annual production capability of 1.3 million net tons. Table 7-9 shows the top ten
commodities in terms of tonnages handled by the Port of Gary, which represent over 99 percent
of the total tonnage handled by this port in 2008.
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Chapter 7: Industry Characterization
Table 7-9 Port of Gary: Top Commodities Handled in 2008 (short tons)
COMMODITY
Iron Ore
Limestone
Iron & Steel Plates & Sheets
Slag
Non-Ferrous Scrap
Clay & Refractory Materials
Petroleum Coke
Iron & Steel Scrap
Coal Coke
Primary Iron & Steel
All Commodities
TONNAGE
(short tons)
8,486,695
209,603
119,525
68,942
49,172
31,221
31,191
10,673
10,277
8,537
PERCENTAGE OF
ALL TONNAGE
94%
2.3%
1.3%
0.8%
0.5%
0.3%
0.3%
0.1%
0.1%
0.1%
9,030,152
7.2.9 Presque Isle, MI
The Port of Presque Isle, located in Marquette, MI, was built in 1941 and primarily
receives two types of cargo, iron ore and coal; small amounts of limestone are also delivered
occasionally.11 Nearly 73 percent of the Port's cargo is iron ore delivered via railcar from the
Upper Peninsula of Michigan. The majority of this iron ore is sent to Algoma Steel in Sault Ste.
Marie, Ontario. Table 7-10 shows the three commodities in terms of tonnages handled by the
Port of Presque Isle in 2008.
Table 7-10 P ort of Presque Isle: Top Commodities Handled in 2008 (short tons)
COMMODITY
Iron Ore
Coal & Lignite
Limestone
All Commodities
TONNAGE (short
tons)
6,399,079
2,240,725
167,805
PERCENTAGE OF ALL
TONNAGE
73%
25%
2%
8,807,609
7.2.10 St. Clair, MI
Almost the entire cargo unloaded in St. Clair is coal intended for the Detroit Edison's
(DTE) Belle River power plant located on the bank of the St. Clair River on a 2,200 acre site.12
The Belle River plant produces 1,350 megawatts of power, and is the second largest DTE owned
plant. Table 7-11 shows the tonnages by cargo type unloaded in St. Clair in 2008.
Table 7-11 P ort of St. Clair: Top Commodities Handled in 2008 (short tons)
COMMODITY
Coal & Lignite
Distillate Fuel Oil
All Commodities
TONNAGE (short
tons)
7,880,089
294
PERCENTAGE OF ALL
TONNAGE
99%
ซ1%
7,880,383
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Chapter 7: Industry Characterization
7.3 Primary Cargoes Shipped on the Great Lakes
According to the Lake Carriers' Association, the main commodities shipped on the Great
Lakes are iron ore, coal, and limestone. These accounted for 38, 25, and 21 percent,
respectively, of the dry-bulk commerce on the Great Lakes in 2008.
Table 7-12 Great Lakes Dry-Bulk Commerce, Calendar Years 2004-2008 and 5-year Average (net tons)
Iron Ore
Coal
Limestone
Salt
Cement
Grain
Total
2004
62,614,611
39,936,860
40,222,052
9,239,658
6,345,674
11,667,639
170,026,494
2005
58,187,548
42,706,688
37,725,377
9,255,371
6,154,834
11,377,508
165,407,326
2006
59,878,098
41,878,453
38,977,721
9,726,206
6,047,303
13,027,677
1 69,535,458
2007
58,099,138
39,260,538
34,001,466
8,892,084
5,671,762
11,135,605
157,060,593
2008
59,242,954
39,790,490
32,367,513
11,425,851
5,036,915
9,284,286
157,148,009
5-Year
Average
59,604,467
40,696,404
36,658,825
9,707,834
5,851,297
11,298,941
163,817,768
Source: Lake Carriers' Association (http://www.lcaships.com/SR09-Dry-Bulk%20Commerce%20-%20Text.pdf)
7.3.1 Coal
As shown in Table 7-12, there were 39,790,490 tons of coal shipped on the Great Lakes
in 2008. This figure was slightly down from the five preceding years' average of 40,770,723
tons.13 This coal goes primarily to power generating plants, steel mills, and paper mills along the
coast of the Great Lakes. The paper mills include Cellu Tissue in Menominee, MI;14 Neenah
Paper in Munising, MI;15 and Georgia-Pacific in Green Bay, WI.16 In paper mills, coal is used to
power boilers. In the paper production process, boilers produce steam both for a turbine and to
power steam drives, a substitute for electric motors.17 Coal is primarily used to power the blast
furnace in steel mills, along with being used in the smelting of iron. It also serves as a source of
electricity for the steelmaking process and as a source of carbon, which can be used as an energy
source and a method of decreasing iron oxide levels during the steelmaking process.18 The
largest use of coal in the Great Lakes region is in power plants to generate electricity. Burning
coal heats water until it evaporates into steam. High pressure steam then is routed to spin a
turbine attached by a shaft to a generator. The spinning generator then produces electricity.19
The great majority of this coal comes from two sources: the Powder River Basin, Montana from
the west and the Appalachian region from the east. After being mined, the coal is then
transported by rail to ports on the Great Lakes; coal from the Powder River Basin is railed to
Lake Superior while coal from Appalachia is transported by rail to Lake Erie.20 From these ports
the coal is transported by vessel to lakeside power plants or ports to transfer the cargo. Power
plants that aren't located on the water or have a lakeside unloading station will receive their
shipments from either truck or rail.
7.3.2 Iron Ore
Iron ore is the most transported commodity on the Great Lakes, the Hon. James L.
Oberstar, shown in Figure 7-5 is an example of a ship that carries iron ore. The year 2008 saw
59,242,954 tons of iron ore shipped on the Great Lakes.21 The final destination of the almost 60
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Chapter 7: Industry Characterization
million tons are steel mills. Iron ore is used in the steelmaking process, primarily in the blast
furnace to create molten iron, an early step in the production of steel.22 The iron ore transported
on the Great Lakes mainly comes from two iron ranges in the U.S.: the Mesabi Iron Range in the
Arrowhead Region of Minnesota, and the Marquette Iron Range in the northern Upper Peninsula
90 ' * "'
of Michigan. Eastern Canada is also a source of iron ore with large mines such as the Wabush
Mine in Wabush and other deposits in Newfoundland and Labrador.23 The Mont-Wright Mining
Complex and Fire Lake Mine are located in northeastern Quebec and are owned by
ArcelorMittal. As they are about 35 miles away from each other, ore mined at the Fire Lake
Mine is transported to the Mont-Wright Mining Complex where the iron ore mined at both
facilities are transported by rail to Port-Cartier, Quebec to be shipped to their final destinations.
24'25 The Carol Project, outside of Labrador City in Newfoundland and Labrador, Canada, is an
iron ore mining operation just beyond the Quebec border. After it is mined and processed, the
iron ore is transported via rail to a year-round port in Sept-Des, Quebec for shipping.26
Figure 7-5 The Hon. James L. Oberstar Heads Downbound at Sault Ste. Marie, MI in July of 2007
Source: Photo taken by and used with permission from Blake Kishler
7.3.3 Stone
There are several different types of stone transported on the Great Lakes, but the
dominant type is crushed limestone, 32,367,513 tons of which was transported on the Great
Lakes in 2008.2? Another heavily shipped material is cement with 4,188,457 tons shipped on the
Great Lakes in 2008.28 Other stone-like aggregate products shipped include sand and gravel,
with 3,984,434 tons shipped in 2008, and gypsum, with 422,431 tons shipped in 2008 Despite
these different types of stone, there are only a few types of companies interested in obtaining it.
Limestone can be utilized by cement manufacturers and construction companies as an aggregate
along with sand and gravel.27'29 Cement is also largely used by the construction industry.28 In
addition, limestone is used in the steelmaking process as a filtering material in the blast furnace,
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Chapter 7: Industry Characterization
specifically for removing sulfur.30 The power generation industry has found use for limestone's
property of reducing sulfur as well. Coal-fired power plants use limestone to control sulfur
emissions to comply with environmental standards.29 Limestone transported in the Great Lakes
region is primarily quarried in northeastern Michigan, both in the Lower Peninsula and the
Upper Peninsula.20 Cement is not a raw material and thus not found naturally, but instead
produced in plants. It is made from mainly limestone and clay. The two materials are ground,
mixed, superheated, and cooled. Then gypsum and other materials are added depending on the
type of cement being made.31 Michigan is the top cement-producing state in the Great Lakes
region.32
7.3.4 Grain
The lowest quantity of grain transported over the Great Lakes in the last ten years
occurred in 2008 reflecting a 31% decrease from the year before as only 7,744,592 tons of grain
were transported on the Great Lakes. Part of the reason for this decline is that Canada is shifting
its grain trade to the West Coast.33 From 1998 to 2009, grain shipments from Thunder Bay fell
by 47% from 2,059 thousand metric tons to 1,093 thousand metric tons while grain shipments
from Canada's Pacific coast rose by over 20% from 15,420 thousand metric tons to 18,716
thousand metric tons.34'35 This trend in Canadian shipping is attributable to the shift of Canadian
grain sales to Asian countries, making shipping from the Pacific coast the most economic
option.36 The companies involved in the grain trade are typically food companies who process
and distribute grain and grain products. A large portion of the grain shipments originating in the
Great Lakes are exported, with Canada, Western Europe, and Eastern Asia being the main
"*H ^R
destinations. ' The main domestic targets for grain transported on the Great Lakes are New
York and Ohio.37
7.3.5 Other Cargoes
The Great Lakes are also used for the transportation of salt, petroleum, vehicles, and
people. Salt makes up about 4% of all cargo transported on the Great Lakes. It is mined in
Canada and Ohio and shipped mostly to Michigan, Wisconsin, and Illinois. Salt is sold as table
salt, used in deicing during the winter, or as a component in other products.39 Petroleum tankers
and barges are an economically efficient way to deliver fuel to some areas on the Great Lakes
that need it, since some cities aren't connected to pipelines while others need to supplement their
pipeline supply. The use of petroleum tankers is also an effective method to transport fuels that
can't be sent through a pipeline due to their makeup.40 The Great Lakes has eighteen self-
powered tankers and twenty-six tanker barges.41 These forty-four vessels are responsible for all
petroleum transportation between the U.S. and Canada.
There are almost fifty car ferries on the Great Lakes, the S.S. Badger based in the Port of
Ludington, MI and the M.S. Chi-Cheemaun of Tobermory, Ontario are the two largest ferries
operating on the Great Lakes. They are the only ferries on the lakes that have a capacity of over
one hundred cars, with capacities of 180 and 138 respectively.41 The S.S. Badger makes a four-
hour trip across Lake Michigan between Ludington, Michigan and Manitowoc, Wisconsin and
can carry passenger cars as well as semi trucks and trailers.42 She serves as a link between the
two sections of U.S. Highway 10 on either side of Lake Michigan.43 The carferries also carry
passengers across the Great Lakes.41
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Chapter 7: Industry Characterization
7.3.6 Short-sea Shipping
There has been more emphasis in recent years on promoting short-sea shipping on the
Great Lakes as a way of relieving rail and highway congestion and reduce energy consumption.
Short-sea shipping generally involves moving containers and truck trailers (RO-RO) away from
highway transportation and toward an intermodal truck-ship-truck route. For example, goods
that arrive in east coast ports from all parts of the world would be loaded on smaller container
ships and shipped down the St. Lawrence Seaway to Great Lakes ports for distribution in the
region.44 In another example, truck trailers are shipped from Michigan to Wisconsin, across
Lake Michigan, to avoid road congestion around Chicago; one study estimates savings on
shipping costs of up to 18 percent.45 In a third example, a study of cargo shipped from Montreal
to Cleveland estimates reduced CC>2 emissions and operating costs for truck/ship and truck/rail
alternatives to truck only transportation.46 While short-sea shipping has not yet been
implemented on the Great Lakes, this may become a more attractive transportation solution as a
result of increasing fuel prices.
7.4 Industries that Use the Cargoes Transported by Great Lakes
Shipping
Numerous companies depend on marine transportation to deliver raw materials to their
facilities. These industries are crucial for our society, and provide basic products that are used
every day. Historically, producers of steel, iron, cement, and electricity located their plants on
the Great Lakes because these plants require large amounts of raw materials and water. The
Great Lakes provide a low-cost way to transport large quantities of raw materials.47 Power
generation plants, usually need to be located on water and often have coal delivered by water
right to the plant. Steel mills have been built on the waterway because it made the transportation
of iron ore and other materials needed for steel production easier. Construction is a service
performed all over, and the Great Lakes facilitate the movement of aggregate materials that are
needed by this industry. The grain industry, utilizes the Great Lakes as the first leg of sending
their product overseas. Marine transportation is engrained in each of these industries.
7.4.1 Steel Industry
There are over a dozen steel mills along the coast of the Great Lakes. The steel giants
ArcelorMittal and U.S. Steel own eleven such mills between them, with the other mills being
owned by AK Steel, Essar Steel, and Severstal.48'49'50'51'52 ArcelorMittal's four steel mills on the
Great Lakes include plants in Burns Harbor, Indiana; Cleveland, Ohio; Indiana Harbor,
Indiana;48 and a Dofasco mill in Hamilton, Ontario.53 The facilities on the Great Lakes
belonging to U.S. Steel include: Mon Valley Works outside of Pittsburgh, Pennsylvania; Gary
Works in Gary, Indiana; Midwest Plant in Portage, Indiana; Great Lakes Works just outside of
Detroit, Michigan; Lorain Tubular Operations in Lorain, Ohio; Hamilton Works in Hamilton,
Ontario; and Lake Erie Works in Nanticoke, Ontario.49 AK Steel owns a steel mill in
Middletown, Ohio.50 The facility owned by Essar Steel is in Sault St. Marie, Ontario.51
Severstal owns three mills serviced by the Great Lakes located in Dearborn, Michigan; Warren,
Ohio; and Follansbee, West Virginia.54'55 There is also a facility in Lorain, Ohio owned by
Republic Engineered Products.5
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Chapter 7: Industry Characterization
These integrated steel mills produce several different types of steel products. The major
differences between steel bars, strip, plate, and sheet are width and thickness. Sheet steel is thin
and flat-rolled. Plate steel is sheet that is wider than eight inches and between a quarter of an
inch to over a foot thick. Both plate and sheet steel are produced by further processing slab, the
primary type of semi-finished steel. Strip is similar to sheet steel, but often is narrower and of a
more uniform thickness.57 Bars are long pieces of steel rolled from the semi-finished billets.
Differing from slabs, billets typically have square width and thickness, whereas slabs vary from
being thirty to eighty inches wide and two to ten inches thick.58 While hot-rolling is the typical
method to produce sheet and strip steel, cold-rolling is a method that is also used.57 Cold-rolled
steel is stronger than hot-rolled and is therefore more valuable.58 Galvanized steel is coated with
a layer of zinc.59 As with all types of coated steel, the zinc acts as an anti-corrosive.58 Tin mill
products are composed of steel with a thin tin layer, used primarily in making cans.57
ArcelorMittal's Burns Harbor mill, with about 4,000 employees, produced 1,779 metric
kilotons (kt) of hot-rolled steel, 941 metric kt of cold-rolled steel, 358 metric kt of coated-sheet
steel, and 442 metric kt of steel plate for a total of 3,520 metric kt in 2009.60 This same year,
ArcelorMittal's plant in Cleveland produced 466 metric kt of hot-rolled steel, 150 metric kt of
cold-rolled steel, 142 metric kt of galvanized sheet steel, and 614 metric kt of steel slabs, totaling
1,372 metric kt of steel produced.61 As of 2009, the facility had between 700 and 850
employees.62 By comparison, ArcelorMittal's largest American plant in Indiana Harbor had
5,500 employees.63 In 2009, this plant produced 3,568 metric kt of hot-rolled steel, 1,202 metric
kt of cold-rolled steel, 417 metric kt of galvanized steel, and 3,902 metric kt of steel slabs, for a
total of 9,143 metric kt.61 As the national production of steel in the United States in 2009 was 56
million metric tons, ArcelorMittal's Burns Harbor mill was responsible for 6.3 percent of the
national output, Cleveland for 1.45 percent, and Indiana Harbor for 16.3 percent.64
ArcelorMittal's Canadian Dofasco plant had 5,000 employees in 2009 and produced 3,074
metric tons of hot-rolled steel, 2,088 metric kt of cold-rolled steel, 986 metric kt of galvanized
steel, and 2,686 kt of steel slabs for a total of about 5, 763,074 metric tons of steel.65'61 Canada's
total steel production was 9,245,310 metric tons, ArcelorMittal's Dofasco mill produced 62.3
percent of Canada's 2009 output.66
U.S. Steel's Mon Valley Works just outside of Pittsburgh employs 1,245 people.67 The
Edgar Thomson Plant is the basic steel producer at the Mon Valley Works which employs
roughly 643 people.68'67 Its slab production is the base of the annual steel production of the Mon
Valley Works of 2,460 kt.68'69 In 2009, of about 56 million metric tons of steel produced in the
United States, the Mon Valley Works production made up about 4 percent of the national output.
In 2009, Gary Works produced 5,379 kt of slabs, sheets, tin mill, and strip mill plate at their
facility with about 4,690 employees.69'67 Gary Works accounted for about 8.7 percent of the
national production. At their facility with 2,070 employees, Great Lakes Works produced 473 kt
of slabs and sheets in 2009, making up 0.76 percent of the national output.67'69 For U.S. Steel's
Canadian operations in 2009, Hamilton Works, with an employment of about 1,400,67 produced
564 kt of slabs, sheets, and bars and their Lake Erie Works produced 356 kt of slabs and sheets at
a facility with almost 1,100 employees.69'67 Each of these mills is serviced by a port owned by
U.S. Steel except Mon Valley Works.41
AK Steel, Essar Steel, Severstal, and Republic Engineered Products own six steel
facilities serviced by the Great Lakes between them. AK Steel's mill in Middletown, Ohio
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Chapter 7: Industry Characterization
produces hot-rolled, cold-rolled, enameled, galvanized, aluminized carbon, and stainless steel.50
In 2008, Canada's Essar Steel Algoma plant produced 2,121 metric kt of sheet, 594 metric kt of
plate, and 17 metric kt of slab, for a total of 2,732 metric kt in that year.70 Canada's national
production in 2008 was 14,845,117 metric tons, meaning that Essar Steel Algoma produced
about 18.4 percent of Canada's steel output.66 Severstal has three plants serviced by the Great
Lakes iron ore trade: Severstal Dearborn, Michigan; Severstal Warren, Ohio; and Severstal
Wheeling, West Virginia. The Dearborn plant produces hot-rolled, cold-rolled, and galvanized
steel71 while the Warren plant produced hot-rolled and galvanized steel.72 Essar Steel Algoma
and Severstal Dearborn are the only facilities in this group that own their own port.41
ArcelorMittal's plant at Burns Harbor receives shipments of ore, coal, and limestone by
both rail and lake vessel.73 Besides being serviced by the Burns Harbor port, the plant also
receives ore from the Indiana Harbor Belt Railroad and the Gary Railroad Company via
Canadian National Rail (CN).74'75 In Cleveland, ArcelorMittal is located down the Cuyahoga
River, past the section navigable by the large lake vessels. To get the ore to the plant, the cargo
is often transferred at the Cleveland Bulk Terminal to a smaller ship, able to navigate the river
when it gets narrower.76 ArcelorMittal's Indiana Harbor plant is also serviced by the Indiana
Harbor Belt Railroad.74
By and large, U.S. Steel's mills are serviced either by ports directly or short line rail lines
that are operated by Transtar, a subsidiary of U.S. Steel.77 For instance, Mon Valley Works is
serviced by the Union Railroad Company.78 In Gary, Indiana, iron ore is received at the west
dock. Transtar owns Gary Railway Company, which operates on 63 miles of track, allowing
trains to pick up ore shipments at the dock and bring them to the U.S. Steel Gary Works.79
Similarly to the Gary Railway Company in Gary, Delay Connecting Railroad Company brings
iron ore from U.S. Steel's USX dock on the Detroit River to the various facilities in the U.S.
Steel Great Lakes Works. It also receives coke shipments from CN and CSX to use in the blast
Q(-\
furnaces.
A major source of the iron ore used for steelmaking in the Great Lakes region comes
from the Mesabi Range in Minnesota. U.S. Steel, ArcelorMittal, and Essar all have mining
01 oa
operations in the Mesabi Range, ' and therefore have control over how the iron ore gets from
the mine to their various mills and production facilities. The Range is serviced by the Duluth,
Missabe and Iron Range Railway (DM&IR), which is controlled by CN, which also has tracks
that service Chicago, northern Indiana, and the Detroit area.83 The current state of operations is
that the DM&IR brings the iron ore to ports in Duluth and Two Harbors, MN to be shipped to
their final destination.84
In the winter, Great Lakes navigation is officially out of season from January 15 to March
21. During this time, the Soo Locks, which allow vessels to travel from Lake Superior to the
o c
lower Great Lakes, are closed. Because of lock closure, shipments made out of the Duluth,
Two Harbors, and Marquette ports cannot make it to the steel mills in the lower Great Lakes
region. Instead, iron ore is brought to Escanaba, MI by rail to be shipped to the mills in the
lower Great Lakes.86 This allows the steel mills to continue operating without the need to
stockpile large amounts of ore.
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Chapter 7: Industry Characterization
Figure 7-6 Map of Steel Industry on Great Lakes
Tacordte Haib or
S ilver Bay t, - '
Two Harbors
Duiith ~y
Y**
.Supeiior inr^
I <
,'
" fc. -.feuHiS n<
Gaiy ;,^f; --r:^-^
f TTHTlJlTTi '-t.^^1'
Harbor
. Toledo Cf>iiป
'-JL' J1*- " .
Loraiii Cleveland
Integrated StedMifl
Iron One Mine
Source: http://outreach.lrh.usace.army.mil/Industries/Iron%20Ore/Iron%20Ore%20GL.htm
7.4.2 Power Generation Industry
Many power plants are located near a body of water, often used as a cooling agent in
steam-based electricity generation. As a result of that location, coal is delivered either directly to
a power plant or near to it, allowing easy transportation. In the Great Lakes region, DTE and
Consumers Energy Company own the big power plants, accounting for about 75% of the
electricity generated by power plants serviced by coal-bearing lake vessels. DTE has five plants
serviced by the Great Lakes vessel system: Belle River, St. Clair, Harbor Beach, Marysville, and
Monroe, all in Michigan. In terms of power generation, Belle River has a capacity of 1,270 MW,
St. Clair has a capacity of 1,400 MW, Harbor Beach has a capacity of 103 MW, Marysville has a
capacity of 166 MW, and Monroe has a capacity of 3,110 MW.87 In 2008, the net summer
capacity of electricity for the state of Michigan was 30,419 MW: Belle River made up 4.2 % of
the state's capacity, St. Clair was 4.6%, Harbor Beach had 0.3%, Marysville accounted for 0.5%,
and Monroe 10.2% of Michigan's capacity.88
Consumers Energy Company has three power plants on the Great Lakes: the D.E. Karn -
J.C. Weadock Complex in Essexville, Michigan;89 the B.C. Cobb Plant in Muskegon,
Michigan;90 and the J.H. Campbell Complex in Holland, Michigan.19 The D.E. Karn - J.C.
Weadock Complex, with 370 employees has a capacity of 2,101 MW, accounting for 6.9% of
Michigan's capacity. However, only four units at the plant are powered by coal, totaling 821
MW or 2.7% of the state's capacity. The other units are powered by natural gas.89 The B.C.
Cobb Plant has a 500 MW capacity, maintaining 1.6% of Michigan's 2008 capacity with 122
employees. This plant has two active coal units and three units powered by natural gas. The two
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Chapter 7: Industry Characterization
coal units at the B.C. Cobb plant, however, have a capacity of 320 MW, or 1.0% of the state's
capacity.90 The J.H. Campbell Complex, with 310 employees, has a 1,440 MW generating
capacity and is responsible for 4.7% of the state's capacity.19
NRG Energy has two locations serviced by the Great Lakes, both in the State of New
York. They own and operate both the Dunkirk Generating Station in Dunkirk and the Huntley
Generating Station in Tonawanda. In 2008, New York had a 38,720 MW capacity of
electricity.88 The Dunkirk plant has 530 MW or 1.4% of the state's capacity and the Huntley
plant generates 380 MW, or 1.0% of the state's capacity.91 WE-Energies also has two locations
Q9
on the Great Lakes: the Presque Isle Power Plant in Marquette, Michigan which has a
generating capacity of 431 MW,92 or 1.4% of Michigan's capacity, and the Valley Power Plant in
Milwaukee, Wisconsin93 which has a generating capacity of 280 MW,93 or 1.6% of Wisconsin's
capacity. These two companies total 1,621 MW of generating capacity.
The other coal-fired power plants on the American side of the Great Lakes are smaller
operations. Almost all of them are either owned by a municipal government or a local business.
Upper Peninsula Power Company operates Escanaba Generating Station, which is owned by the
City of Escanaba, Michigan. Its capacity is 26.3 MW,94 meaning that it contributes 0.09% of the
state's electric capacity. T.E.S. Filer City Station is in Filer City, Michigan and has an output of
60 MW,95 accounting for 0.20% of the state's capacity. The J.B. Sims Generating Station is
owned by the Board of Light and Power, Grand Haven, Michigan. It has a capacity of 65 MW96
and is therefore responsible for 0.21% of the state's electricity capacity. J.P. Pulliam Station in
Green Bay, Wisconsin is operated by the Wisconsin Public Service Corp and generates 397
MW,97 accounting for 2.3% of the annual capacity of Wisconsin. The James De Young
Generating Station is owned by the Holland Board of Public Works in Holland, Michigan and is
capable of generating 60 MW of electricity,98 which is roughly 0.20% of the state's capacity.
The Manitowoc Public Utilities Power Plant in Manitowoc, Wisconsin has a 79 MW capacity,99
making up 0.45% of the state's capacity. White Pine Power Plant is a power plant in White Pine,
Michigan, outside of Ontonagon. It has a generating capacity of 40 MW100 which allows it to
produce 0.13% of the state's capacity. Minnesota Power's Taconite Harbor Energy Center has a
capacity of 200 MW.101 As Minnesota had a capacity of 14,237 MW of electricity in 2008,88 the
Taconite Harbor Energy Center accounted for about 1.4% of Minnesota's capacity. Also, the
Wyandotte Municipal Power Plant in Wyandotte, Michigan has a capacity of 70 MW,102 0.23%
of the state's capacity. These smaller operations total a capacity of 997.3 MW, less than most of
the plants owned by DTE and Consumers Energy Company.
On the Canadian side of the Great Lakes, the two energy companies serviced by Great
Lakes transportation industry are New Brunswick Power and Ontario Power Generation. New
Brunswick Power's plant in Belledune has a capacity 458 MW.103 Canada's total electricity
capacity in 2007 was 124,720 MW.104 Using the same principle as the American power plants,
the Belledune power plant generates about 0.37% of its nation's annual electricity capacity.
Ontario Power Generation has three facilities on the Great Lakes: Lambton Generating Station,
Nanticoke Generating Station, and Thunder Bay Generating Station. Thunder Bay Generating
Station has 145 employees and can produce 306 MW of electricity,105 which translates to 0.25%
of Canada's annual capacity. The other two stations in Lambton and Nanticoke are each shutting
down two generating units in 2010 in an effort to reduce CO2 emissions and save money.
Ontario Power Generation projects a lower demand for electricity and maintains that closing the
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units will not affect their energy reliability or adequacy. The unit closures will result in a
reduction of about 1000 MW generated at each station.106 Prior to this switch, Lambton's
generating capacity was 1,920 MW107 and Nanticoke's was 3,640 MW.108 As a result, their new
capacities will be about 920 MW (0.7%) and 2,640 MW (2.1%), respectively.
7.4.3 Transportation of Coal to the Power Generation Industry on the
Great Lakes
The transportation of coal is quite active on the Great Lakes. Coal is brought to the
power plants from two main regions: the Powder River Basin and the Northern Appalachian
region. Markets in southern Michigan could be reached by train without having to take a longer
trip to get around the Great Lakes. However, markets in Wisconsin, Minnesota, northern
Michigan, and Canada would be more difficult to reach with solely rail due to required
navigation around the lakes. However, due to emissions regulations, much of the coal used by
power plants is at least in some part from the west. Low-sulfur western coal, coming from the
Powder River Basin, has seen increased use in recent years.109 Wisconsin, being the largest
shipper of coal in the Great Lakes, ships western coal out of the Superior Midwest Energy
Terminal. DTE has an ownership interest in the terminal, which serves DTE and Consumers
Energy Company, as well as other power plants. As mentioned previously, those two companies
generate about 75% of the electricity generated by the power plants serviced by the Great Lakes.
Figure 7-7 maps the major coal port facilities and locations of shore-side power plants in the
Great Lakes area.
Figure 7-7 Major Great Lakes Area Coal Port Facilities and U.S. Waterside Power Plants
Power P ants and Coal Faculties
Source: http://outreach.lrh.usace.army.mil/Industries/Coal/graphics/Great%20Lakes%20Coal%20Ports.bmp
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According to the U.S. Army Corps of Engineers, of the 36,471,098 tons of coal
transported over the Great Lakes in 2008, 13,960,329 tons of it went to Canada.110 That's about
37% of the coal transported on the Great Lakes. In an attempt to reduce harmful emissions,
Canada is phasing out 33 coal-fired power plants that are considered at the end of their economic
lives by 2025, planning to replace them with plants the run on natural gas.111 As Canada uses
less coal, a large piece of the Great Lakes market for coal transportation will decrease.
Depending on which plants are closed, coal traffic on the Great Lakes could drop by up to one
third.
The Maumee unloads coal at the Menominee Paper Company in Menominee, MI. Source: Taken by
and used with permission from Dick Lund, available here:
http://www.dlund.20m.com/DMen2008.html
Wisconsin is the state that ships the largest amount of coal on the Great Lakes. This coal
HIT
112
comes largely from the Powder River Basin, located in Wyoming and Montana. '" The sole
coal loading port in Wisconsin is the Superior Midwest Energy Terminal,41 an operation
commissioned by DTE to facilitate the transport of low-sulfur coal from the Powder River Basin
to the lower Great Lakes.113 Some of the Superior Midwest Energy Terminal customers include:
Consumers Energy Company, DTE, Marquette Board of Light and Power, Minnesota Power,
New Brunswick Power, Ontario Power Generation, and WE-Energies.114
Of the above power plants, there are several that don't own their own ports. Upper
Peninsula Power Company, J.H. Campbell Complex of Consumers Energy Company, J. P.
Pulliam Generating Station, Manitowoc Public Utilities Power Plant, and White Pine Power
Plant all receive their coal from a dock that they don't own.41 Consumers Energy Company's
D.E. Karn - J.C. Weadock Complex uses about three million tons of coal every year. The coal
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they use is a blend of eastern coal from West Virginia, Pennsylvania, and Kentucky, and low-
sulfur western coal from Wyoming and Montana.89 Their B.C. Cobb Plant, burning a similar
blend, goes through about a million tons of coal annually.90 The J.H. Campbell Complex, also
owned by Consumers Energy Company, has a unit that uses only western coal. The other two
units burn a mix of coal from the east and west. In all, the complex burns about five million tons
of coal every year.19 Grand Haven's J.B. Sims Generating Station's source of coal is delivered
in twelve shipments by lake vessels every shipping season. The plant uses about 550 tons of coal
every day.96 The J.P. Pulliam Generating Station in Green Bay uses 1.5 million tons of pure
western coal every year.115 Coal is brought to the power plant in Manitowoc usually by lake
vessel or rail, although truck is occasionally the mode of transport.99 WE-Energies has a number
of plants including the Presque Isle Power Plant which uses 1.6 million tons of western coal
annually, delivered by lake9 , and the Valley Power Plant which uses 2,200 tons of coal every
day, also delivered on the lake.93
During the winter, additional power is sometimes needed in the Great Lakes region. The
power plants that receive shipments of coal can't discontinue running because the lakes freeze.
To facilitate the transportation of coal and other commodities on the Great Lakes, the U.S. Coast
Guard has several ice breakers they use during the winter. These ice breakers allow the power
plants to continue to receive the coal they need to keep running.116 Of course, plants also
stockpile coal for the winter. For example, DTE's St. Clair Power Plant maintains a stockpile of
two million tons of coal for the winter. 1? With a combination of increasing storage and
continued shipments, power plants are able to continue their production during the winter.
7.4.4 Construction Industry
The construction industry is unique in many ways. It is seasonal, with most construction
taking place in the summer months, usually beginning in the spring and ending in the fall. Also,
construction can take place wherever there are roads, making numerous cities and townships
potential locations. This is a reason why there are so many ports on the Great Lakes that service
construction aggregate. Demand is everywhere for construction companies, so there are
numerous companies in the region. Delivering materials closest to the project is ideal,
minimizing transportation costs. The large number of ports allow for drop-off close to a
particular construction project. Construction's seasonal nature also means there isn't much
demand for it during the winter months when the lakes are closed. As no construction aggregate
is needed, no alternative transportation is required for the Great Lakes.
In general, limestone is a difficult material to transport. Due to its weight, transportation
can be costly when using most forms of freight transportation. When moving large amounts of
heavy stones such as limestone, it is usually most economic to transport them to a facility close
to the quarry or to use a form of transportation capable of carrying extremely large loads, such as
lake vessels.118 In Michigan, the largest shipper of limestone and other aggregate in the Great
Lakes region,29 there are three active quarries in a region where there used to be over thirty. The
area, near the Great Lake coast, includes a quarry at Port Calcite and Presque Isle, the largest
limestone quarry in the world.118 As a result of the costliness of land transportation and location
of the quarries, shipping limestone with lake vessels is a commonly preferred method for
transporting a widely-used commodity out of such a concentrated area.
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The limestone quarries in the northern lower peninsula of Michigan serve as the source of
most of the Great Lakes region's limestone. The concentration of these quarries, all near
shipping ports, means an effective mode of transportation is important, especially since
limestone is such a widely-used commodity. It is also an especially heavy cargo and must be
transported in smaller volumes. As a result, a large cargo capacity is ideal in order to carry as
much as possible in a single load. Lake vessels can widely distribute such a heavy, commonly
used commodity from quarries that are near ports.
The Great Lakes shipping industry services almost forty companies involved in
construction or other stone aggregate services. The main companies that drive the industry are:
Carmeuse, Essroc, Holcim, Lafarge, Levy, Southwestern Sales Corporation, and St. Marys
Cement. Carmeuse has ten locations, focused on limestone and other forms of lime: Buffington,
Indiana; Burns Harbor, Indiana; Calcite, Michigan; Chicago, Illinois; Cleveland, Ohio; Detroit,
Michigan; Erie, Pennsylvania; Fairport Harbor, Ohio; Port Dolomite, Michigan; and Port Inland,
Michigan.119 Essroc's cement and concrete facilities120 include Cleveland, Ohio; Essexville,
Michigan; Oswego, New York; Picton, Ontario; Rochester, New York; Toronto, Ontario; and
Windsor, Ontario.41 Holcim has a several different types of facilities on the Great Lakes. In
Canada, Holcim has an aggregate production plant in Colborne and a concrete plant in
Mississauga.121 In the U.S., Holcim has cement plants in Buffalo, New York and Duluth,
Minnesota,122 and an aggregate facility in Dundee, Michigan.123 Lafarge, the world leader in
cement sales,124 has nearly thirty terminals on the Great Lakes.41 Lafarge's largest cement
operation in North America is located in Alpena, Michigan. The facility has over 250 employees
and produces 2.7 million tons of cement annually.125 As annual cement production in the United
States is just over 100 million tons,32 this facility accounts for about 2.5% of the national output.
There's also a cement plant in Bath, Ontario that has over 110 employees and produces about
19^
3,300 metric tons of cement every day. They also operate a plant in South Chicago that grinds
slag, a byproduct of the steelmaking process, into a cement-like substance.127 Levy has five
locations on the Great Lakes, focusing on slag, aggregate, asphalt, and other construction
materials: Burns Harbor, Indiana; Detroit, Michigan; Gary, Indiana; Indiana Harbor, Indiana; and
1 9R
Saginaw, Michigan. Southwestern Sales Corporation has docks in five locations in Ontario:
Kingsville, Sarnia, Sombra, Tecumseh, and Windsor. They provide limestone-based
construction materials to Essex, Lambton, and Chatham-Kent.129 St. Marys Cement has many
terminal locations on the Great Lakes, including: Buffalo, New York; Chicago, Illinois;
Cleveland, Ohio; Ferrysburg, Michigan; Green Bay, Wisconsin; Manitowoc, Wisconsin;
Milwaukee, Wisconsin; Toledo, Ohio; and Waukegan, Illinois. Its plants on the Great Lakes are
in Algoma, Ontario; Bowmanville, Ontario; Charlevoix, Michigan; Detroit, Michigan;
Milwaukee, Wisconsin, and Nanticoke, Ontario.130 Most docks servicing the above facilities are
owned by St. Mary's Cement, except for the following plants: Lafarge in Thunder Bay, Ontario;
St. Marys Cement in Chicago; Carmeuse in Cleveland, Erie, and Port Dolomite; Essroc in
Cleveland; Levy in Gary; Holcim in Mississauga; and Southwestern Sales Corp. in Sombra.41
7.4.5 Grain/Agriculture Industry
The Great Lakes are a valuable mode of transportation for the grain industry because of
the large portion of exports by the grain industry. In 2008, almost 70% of all grain transported
over the Great Lakes was headed for non-U.S. destinations, with about one third of all grain
1"7
being sent overseas. The Great Lakes and St. Lawrence Seaway provide a convenient avenue
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for this grain to be taken overseas. Much of the grain is brought from U.S. and Canadian farms
by rail to Superior, Wisconsin; Duluth, Minnesota; and Thunder Bay, Ontario for transportation
over the Great Lakes. Over 70% of the grain transported over the Great Lakes was shipped from
Wisconsin, Minnesota, or Canada.37
Domestic grain transport on the Great Lakes is delivered in a different fashion than the
grain exported overseas, and is delivered in small amounts, with one vessel often making several
smaller stops on the way to a larger unloading point, sometimes a transshipment point for grain
being sent overseas.131 A combination of the large proportion of grain being exported and the
practice of dropping off smaller cargoes on the way to a transshipment point leads to a
continuation of current practices. Grain cannot be shipped overseas by rail or truck, thus water-
based transport remains the most viable option. Lake vessels bringing grain east for
transshipment make their trips more efficient by making stops to drop off cargo at grain elevators
on the way. As transshipment continues, it makes sense for the domestic cargo deliveries to
continue as well.
7.5 Great Lakes Ships
7.5.1 General Characteristics
According to Greenwood's 2010 Guide to Great Lakes Shipping (GWG) there are at least
57 U.S.-flagged freighters, tug-barge combinations, and ferries and 98 Canadian-flagged
freighters, tug-barge combinations, and ferries operating on the Great Lakes.132 These vessels
range from small tugboats to ore carriers over 1,000 feet long, and are powered by a wide range
of engines ranging from low horse power/high speed Category 1 marine diesel engines to high
horsepower/low speed Category 3 marine diesel engines. These ships are flagged in the United
States, Canada, and other countries. In addition, there are hundreds of small vessels, ranging
from fishing and recreational vessels to dredgers and harborcraft.
One important characteristic of Great Lakes vessels is that they tend to be older than
vessels that operate on the oceans. This is because the fresh water of the Great Lakes is not as
corrosive as ocean salt water. Several tugboats built in the late 1880s are still in operation on the
Great Lakes, although they have been repowered with newer engines. Figure 7-8 shows the
oldest Great Lakes freighter in operation, the St. Mary's Challenger, built in 1906, being assisted
to port by one of the oldest operating tugboats, the John M. Selvick, built in 1898 and owned by
Calumet River Fleeting.
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Figure 7-8 The St. Mary's Challenger Arrives at Sturgeon Bay and is Assisted to Port by the John M. Selvick
Source: Photo taken by and used with permission from Blake D. Kishler, taken March 27, 2009 accessed at:
www.boatnerd.com
Ships in the Great Lakes fleet are also distinguished by whether they are "salties" or
"captive" vessels. Some ships operating on the Great Lakes can navigate the St. Lawrence
Seaway and on to the Atlantic Ocean and throughout the world. Vessels that visit the Great
Lakes that can also operate on the ocean are called "salties;" these ships typically use residual
fuel and will be affected by the application of the EGA fuel requirements to the Great Lakes.
Other ships can operate solely on the Great Lakes, and are called "captive" vessels. They are
captive due to size restrictions based on their length, width, and draft (i.e. the depth a vessel
reaches in the water) that can prevent them from passing through locks in the Great Lakes. For
example, for a ship to be able to pass through the St. Lawrence Seaway, it must be no more than
740 feet long, 78 feet wide, while the draft can change yearly depending on water levels. In
2010, for example, the canal opened on March 25, 2010 with a draft of 26 feet 3 inches.133 The
Poe lock in Sault Ste. Marie, is 1,200 feet long and can handle vessels as long as the Paul R.
Tregurtha which is 1013.5 feet long, currently the longest vessel operating on the Great Lakes,
and therefore titled the "Queen of the Lakes" (see Figure 7-9). Vessels that are built to travel
through the Poe lock are considered to be part of the 'captured fleet' of boats on the Great Lakes
as they cannot travel through the St. Lawrence Seaway and into the Atlantic Ocean. All foreign
vessels that visit the Great Lakes, must be smaller than these thousand foot vessels, known as
' 1,000-footers' in order to travel through the St. Lawrence Seaway and into the Great Lakes. Of
the twelve U.S. flagged C3 vessels, all are captured vessels except for three, the Maumee, the
Tug Presque Isle, and the Tug Victory.
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Figure 7-9 The "Queen of the Lakes" the Paul R Tregurtha Heading Downbound at Mission Point
Source: Photograph taken by and used with permission from Dick Lund, available here:
http ://dlund. 20m.com/rbl2 .html
7.5.2 Types of Vessels that Operate on the Great Lakes
7.5.2.1 Bulk Freighters
The C3 vessels discussed in this report are bulk freighters, or "lakers." These vessels can
carry cargoes such as iron ore, coal, stone, and grain. These vessels are either "self-unloaders"
or straight-deck vessels. Straight-deck vessels, such as the Edward L. Ryerson shown below in
Figure 7-10, are vessels whose cargo must be removed by cranes or other methods which can
take numerous hours to unload. The Edward L. Ryerson is one of only two remaining straight-
deck U.S. flagged vessels, and the only one who has operated recently. The other straight decker
is the John Sherwin, she is currently out of service pending possible repowering while the
Ryerson still uses her original steam engine. The Edward L. Ryerson is the only vessel built in
her configuration with a rounded bow, streamlined stainless steel stack, and rounded tapered
stern and as such is adored by boat watching fans throughout the Great Lakes and beyond.
While the Edward L. Ryerson has not sailed since 2008, she is still considered part of the fleet
having received her last 5-year survey in 2006.A The straight-deck vessel has not entirely
disappeared from Canadian ships and there are still a number of Canadian vessels that are not
self-unloaders.
' George Wharton, "Great Lakes Fleet Page Vessel Feature - Edward L. Ryerson", accessed at www.boatnerd.com
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Figure 7-10 The Edward L. Ryerson on the St. Clair River
Source: Roger LeLievre, on the St. Clair River, accessed at www.boatnerd.com
Most Great Lakes freighters were converted to self-unloaders as early as 1952 as the
supply of higher grade iron ore became depleted and steel production turned to the use of
taconite pellets. The conversion of straight deckers to self-unloaders continued throughout the
early 1980's with conveyor systems that can unload cargo at even an unimproved dock without
the assistance of shore-side equipment. Self-unloading systems can transport most free-flowing
dry-bulk commodities including: iron ore, coal, limestone, sand, gypsum and grain at rates of up
to 10,000 tons per hour.B These ships can typically carry up to 70,000 tons of cargo, and have a
pivoting boom of up to 280 feet to discharge their cargo to its final destination. Ten of the
twelve C3 Lakers are self-unloading (the remaining two vessels are tugboats.)
Ten of the twelve C3 vessels are bulk carriers of two distinct styles based on the location
of the pilothouse. Older vessels, such as the Edward L. Ryerson were built with the pilothouse in
the front of the ship for better visibility; later ships were built with the pilothouse on the rear to
reduce costs and complexity. The difference between the two vessel types can affect the
propulsion and drive system designs of these vessels. The use of either a forward or rear
pilothouse can affect on the cost to repower and modify a vessel, Figure 7-11 demonstrates the
difference between pilothouse locations. The St. Mary's Challenger was built with a forward
pilothouse (she is the smaller vessel on the right in the photograph) and the American Century
was built with a rearward pilothouse.
; See http://www.americansteamship.com/self-unloading-technology.php
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Figure 7-11 The St. Mary's Challenger (Built with a Forward Pilothouse and Pictured on the Right) Spends
the Winter in Sturgeon Bay next to the American Century (Equipped with a Rear Pilothouse)
Source: Photograph taken by and used with permission from Dick Lund, available here:
http://www.dlund.20m.com/aa_slideshows/SB_040909/sb040909n.html
7.5.2.2 Ferries
Not all freight moving on the Great Lakes consists of raw materials, grain, or finished
steel products. While the days of passenger vessels taking travelers on day trips throughout the
Great Lakes came to an end in the middle of the twentieth century, there are still passenger and
car ferries moving people and freight across the Great Lakes or to various islands. According to
the GWG, there are 47 car ferries operating on the Great Lakes, of these, 31 are U.S. flagged,
while 16 are Canadian. In general, these ferries range from 13 to 6,991 Gross Registered
Tonnage (GRT) and can carry anywhere from 25 to 600 passengers and up to 180 vehicles. The
S.S. Badger is the largest U.S. flagged ferry at 4,244 GRT and she is one of two remaining U.S.
vessels powered by a Skinner Unaflow four-cylinder steam engine; she was built in 1952 and
looks much the same today, as shown in Figure 7-12.
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Figure 7-12 The S.S. Badger - Yesterday and Today
Source: www.ssbadger.com/home.aspx
The S.S. Badger is designated as a mechanical engineering landmark by the American
Society of Mechanical Engineers, and burns coal to power her steam engines.1 4 The S.S.
Badger can carry 600 passengers, the most of any ferry on the Great Lakes, as well as 180
automobiles, or tour buses, RVs, motorcycles, and commercial trucks; she also has the most
vehicle capacity of any ferry on the Great Lakes. She travels between Ludington, MI and
Manitowoc, WI nearly 500 times during her short-season that begins at the end of May and ends
the first week of October. Recently, the Badger has assisted in the cause of renewable energy by
carrying wind turbine parts across Lake Michigan as they make their way to Altoona, PA to be
installed in a new windfarm and become the tallest windmills in the U.S.135 The smallest ferry
working on the Great Lakes, at just 13 GRT, is the Canadian Howe Islander; she can carry 6 cars
and up to 25 passengers. With the exception of the Badger, the rest of the ferries working on the
Great Lakes are powered by Cl or C2 engines. There are no C3 powered car or passenger ferries
working on the Great Lakes.
7.5.2.3 Other Vessels
Other vessels that work on the Great Lakes assist freighters with navigation including: ice
breakers, harbor tugs, buoy tenders, and crane barges.
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Ice Breakers The U.S. Coast Guard also provides services to the fleet of Great Lakes
vessels to increase the length of their work season through the use of ice-breakers. Since, 1944
the icebreaker Mackinaw (WAGE 83) was a familiar winter sight on the Great Lakes. She could
break up to 32 inches of ice continuously at 3 knots and break ice up to 11 feet thick by backing
and ramming; she was replaced in 2006.136 The new Mackinaw (WLBB-30) can break up to 30
inches of ice continuously or up to 10 feet of ice. The new Mackinaw also features a 20 ton
crane that can assist with the placement and removal of buoys that aid in navigation. She is
equipped with two ABB Azipods with electric propulsion drive systems where the propulsion
motor is installed inside a pod and coupled directly to a very short propeller shaft to increase
maneuverability; the new Mackinaw is powered by two C2 Caterpillar 3612 engines.137'138
Tugs and Barges There are a large number of tugboats and barges operating on the Great
Lakes, the Presque Isle shown in 7-13 is an example of a C3 tug-barge combination. According
to GWG, there are 178 U.S. and 122 Canadian tow and tugboats performing towing and salvage
on the Great Lakes. These vessels can range in GRT from 10 to 1,361 tons and are powered by
engines ranging in horsepower from 120 hp to 10,200 hp. Of the U.S. flagged tugboats, two are
powered by C3 engines, while the remainder are powered by Cl or C2 engines and are not
covered here in this report. These vessels can be found pushing or towing one of the 41 U.S. or
over 100 Canadian barges in addition to assisting large vessels maneuver into or out of port.
7-13 The Tug-Barge Combination the Presque Isle Clears the Blue Water Bridge in Port Huron, MI
Source: Photo taken by Barant Downs, May 7, 2005.
Barges can carry bulk cargo, be equipped with cranes or excavators, be self-unloaders,
floating dry-docks, or serve a number of other purposes. The U.S. barge fleet includes barges
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that are up to 460 feet long and in some cases, are made out of the former freighters. For
example, the barge Lewis J. Kuber began life as the S.S Sparrow Point, a 626 foot steamship
launched in 1952, later converted to a self-unloader; renamed the Buckeye, she hauled her last
load of coal in December of 2004.c In 2006, her rear accommodations, engine room, forward
accommodations and wheelhouse were removed and she emerged as a notched, articulated barge,
the Lewis J. Kuber, shown whole as the Buckeye, and as the resulting barge being pushed by the
tug Olive Moore in Figure 7-14.
Figure 7-14 Example of a Former Freighter Turned Barge: The Lewis J. Kuber Pushed by the Olive Moore
Source: John Meyland, on the St. Cl air River, accessedatwww.boatnerd.com
Dredgers
Source: Todd Ehorkey, on the Saginaw River, Sept. 21, 2006 accessed atwww.boatnerd.com
As all Federal harbors on the Great Lakes are located at the mouth of a river or along a
coastline using natural or dredged navigation channels, lake and river currents transport sand and
silt that can be deposited into the navigation channels making them less deep.139 The U.S. Army
Corps of Engineers is responsible for the construction, maintenance, and operation of Federal
river and harbor projects. The Corps of Engineers has regulatory authority for work on
structures in navigable waterways under Section 10 of the Rivers and Harbors Acts of 1899 and
regulatory authority over the discharge of dredged or fill material into "waters of the United
States" a term, which includes wetlands and other valuable aquatic areas.140 The U.S. Army
Corps of Engineers operates crane barges, derrick barges, tugs, and tenders to help maintain
waterways; these vessels are all Cl and C2 vessels.
Recreational and Fishing Vessels
While commercial fishing has diminished on the Great Lakes over the past few decades,
sport fishing and recreational boating has increased. Nearly five million American and Canadian
anglers fish on the Great Lakes each year. The commercial and sport fishing industry on the
Great Lakes is collectively valued at more than $4 billion annually and is a blend of native and
introduced species.141 In 2008, the Army Corps of Engineers reported that there were 911,000
recreational boaters on the Great Lakes.142 Most fishing boats and recreational boats are less
KK Integrated Logistics "Lewis J. Kuber/Olive Moore" accessed at: http://www.kkil.net/lkuber.html
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than 100 feet long and are powered by Category 1, Category 2 or gasoline engines and are not
covered in this report.
7.5.3 U.S. Category 3 Vessels
This section provides information for only those vessels that are affected by the
application of the EGA fuel sulfur requirements to the Great Lakes: vessels with Category 3
main propulsion engines. While other vessels may share the same characteristics as the affected
Category 3 vessels, they are not included in this report because they are not affected by the
Category 3 rule. For example, some bulk carriers may be propelled by smaller Category 2
marine diesel engines. While these may appear to be identical to other bulk carriers that have
Category 3 engines, the Category 2 vessels are already required to use low-sulfur fuel (the
marine distillate fuel sulfur limit is currently 500 ppm; the phase-in to 15 ppm fuel will be
completed in 2014). Similarly, while steamships are an important part of the Great Lakes fleet,
they are not included in this report because they are excluded from the EGA fuel sulfur
requirements. The St. Mary's Challenger, owned by Port City Tug, hauls cement for the
LaFarge Group and is an example of one of the remaining steamships still operating on the Great
Lakes. She is one of eight steamships in the Canadian fleet. The U.S. has 13 steamships
operating on the Great Lakes.143'144' The twelve U.S. Category 3 ships that operate on the Great
Lakes are listed in Table 7-13.
Table 7-13 Twelve Category 3 Vessels Discussed in this Industry Characterization
SHIP NAME
American Spirit
Hon. James L. Oberstar
Edgar B. Speer
Edwin H. Gott
James R. Barker
Lee A. Tregurtha
Maumee
Mesabi Miner
Paul R. Tregurtha
Presque Isle
Roger Blough
Victory
OWNER
American Steamship Company
Interlake Steamship Company
Great Lakes Fleet, Inc.
Great Lakes Fleet, Inc.
Interlake Steamship Company
Lakes Shipping Company
Grand River Navigation
Interlake Steamship Company
Interlake Steamship Company
Great Lakes Fleet, Inc.
Great Lakes Fleet, Inc.
KK Integrated Logistics LLC
This fleet of ships is somewhat different than the fleet described in the report contained in
Appendix 2C to Chapter 2 of this report, prepared by ICF and EERA. ICF/EERA reports that
there are 12 Category 3 (C3) vessels, 21 Category 2 (C2) vessels, and 15 steamships while the
EPA reports that there are 32 C2 vessels and 13 steamships in the U.S. fleet. The fleet numbers
presented here are used only in the industry characterization and were not used in Chapter 2
which is route based.
The fleet data is taken from the 2010 Greenwood's Guide and was cross-checked by the
EPA with the Lloyd's Sea-web database and shipping company websites wherever possible.145
D The total of thirteen steamships includes twelve diesel-powered steamships and one coal-fired steamship car ferry.
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Further, the EPA did not base the distinction between engine categories on Gross Registered
Tons (GRT) or any other similar metric, rather, we checked the bore and stroke of every engine
model currently installed in the ships listed in the Greenwood's Guide to determine the category
associated with each vessel's main propulsion engine(s). With regard to steamships, the EPA
relied on the number of vessels supplied by the Lake Carriers' Association comments submitted
in 2009 in response to the C3 Notice of Proposed Rulemaking.146 While there are other
steamships listed in the Greenwood's Guide, some of these do not operate under their own
propulsion anymore and are in long-term layup or are used for other purposes. For example, the
J.B. Ford owned by Inland Lakes Management is used as a cement silo for excess capacity; we
did not include vessels used for storage or in lay-up in our count.
The fleet of twelve U.S.-flagged C3 vessels that ply the Great Lakes is diverse in terms of
age, size, and engine power and includes ten self-unloading bulk freighters as well as two
tugboats; all twelve vessels are operated on residual fuel. Based on moving cargoes of 70,000
net tons, these vessels can reduce both rail and truck traffic by hauling in one trip, cargoes
equivalent to 2,800 trucks, or 700 railcars which would combine to form a train stretching nearly
7 miles.147 The average age of these twelve vessels is just over 41 years old with no vessels
being built after 1981. The oldest vessel is the Maumee, operated by the Grand River Navigation
Company. She was launched in 1929 and was initially a steam powered vessel, but was
repowered with a Nordberg diesel engine in 1964; she has the lowest installed power of the
twelve C3 vessels at just over 2,400 kW. The youngest laker is the Paul R. Tregurtha, she was
built in 1981 in Lorain, OH and can carry 68,000 gross tons of taconite pellets, or 71,000 net tons
of coal and unloads her cargo with a 260 foot boom in about eight hours; she is owned by the
Interlake Steamship Company.148 The Paul R. Tregurtha was repowered in 2010 with two
medium-speed 6-cylinder MAK model 6M43C diesel engines producing approximately 12,000
kW.149
The average main engine power of the U.S. C3 fleet is approximately 10,000 kW ranging
from the smallest installed power of the Maumee at just over 2,400 kW, to the largest and most
powerful U.S.-flagged vessel working on the Great Lakes, the Edwin H. Gott, with just over
14,500 kW. The Edwin H. Gott is owned by Great Lakes Fleet Inc. and was launched in 1978
and carried taconite exclusively from 1979 -1995; she has the largest ore capacity of the C3 fleet,
at 74,100 gross tons and has the longest unloading boom at 280 feet.150
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7-15 The Edwin H. Gott Travels Through the Poe Lock on Engineer's Day in Sault Ste. Marie, MI in June of
2010
Source: Photo taken by and used with permission from Dick Lund, available at:
http://www.dlund.20m.com/rbl2.html#Eng
The Edwin Gott is powered by the only Enterprise engines in the C3 Great Lakes fleet;
Enterprise was an engine manufacturer that dated back to the late 1800's and was sold to
DeLaval in the 1960's. Production of Enterprise diesel engines appears to have stopped in the
late 1980's although these engines are still supported by Cameron Compression Systems which
owns and operates the Enterprise OEM aftermarket business.151'152 The Edwin H. Gott is also
the only 1,000-footer that was not built by the American Shipbuilding Company in Ohio, rather
she was built by Bay Shipbuilding of Sturgeon Bay, WI; they are still in business, but are now a
part of the Fincantieri group, headquartered in Italy. The tug-barge Presque Isle, also owned by
Great Lakes Fleet Inc. is the only C3 vessel powered by two Mirrlees Blackstone diesel engines
producing over 11,000 kW. The Mirrlees Blackstone Company was formed in 1969, was taken
over by MAN, and is no longer producing engines. MAN, however, still does provide engine
overhaul, refurbishment, and OEM parts for Mirrlees Blackstone engines.153'154 Table 6-1 lists
the propulsion engine manufacturer for each of the twelve C3 Great Lakes vessels.
The average GRT of the twelve C3 vessels is nearly 25,000 tons compared to a less than
16,000 GRT average size for all 55 U.S. flagged freighters and large tugs working on the Great
Lakes. The largest vessel in terms of GRT is the Paul R. Tregurtha, while the smallest is the tug
Victory. The Victory (see Figure 7-16) with 947 GRT was launched in 1981 for Texaco Marine
Services and was purchased by KK Integrated Shipping in 2006 and paired with the barge James
L. Kuber, which was made into an articulated barge from the steamship Reserve (launched in
1953); the barge was completed in 2008.
engines that produce nearly 6,000 kW.
155
The Victory is powered by 2 Krupp-MAK diesel
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Figure 7-16 The Tug Victory - One of Two Category 3 Powered Tugs
Source: Photo taken by and used with permission from Dick Lund April 10, 2008, available here:
http://www.dlund.20m.com/index.html
Due to the longevity of vessels working on fresh-water, the hull can outlast the original
power-plant and a vessel may be repowered. Of the 57 large U.S.-flagged vessels on the Great
Lakes, eight have been repowered since 2000; three of these were repowers to Category 3
vessels. For example, in 2006, the Lee A. Tregurtha, owned by the Lakes Shipping Co. Inc., was
repowered with two Rolls Royce Bergen medium-speed diesel engines producing over 6,000
kW. The Lee A. Tregurtha, shown in Figure 7-17, has a long and distinguished career that began
with her construction as a World War II tanker in 1942. She served as a tanker in the Atlantic
and Pacific oceans including during the invasion of France. She was awarded six campaign
medals and two battle stars for her service that are now painted on her pilot house as colored
ribbons (see Figure 7-17).
In addition to being repowered, a laker's longevity is increased by the modifications they
receive over the years to increase their capabilities, and no finer example of this exists than with
the Lee A. Tregurtha.156 After the war, she was decommissioned and sat idle until the winter of
1959. She was then substantially modified for work on the Great Lakes and changes were made
to her structure that include: a 510 foot mid-body cargo section was added and the hull was
widened by 7 feet and deepened by 2 feet in 1960, her original midship pilot house and living
quarters were moved forward, she received a bow-thruster in 1966, was lengthened another 96
feet in 1976, she was converted to a self-unloader in 1978, received a stern thruster in 1982, and
her original steam plant was replaced with a modern diesel plant and she received a controllable
pitch propeller system in 2006.
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Chapter 7: Industry Characterization
Figure 7-17 The Lee Tregurtha: As She Looks Today, as a World War II Tanker, and Her Campaign Medals
b
a Source: wv.vv.mterlake-iteamship.com
b Source: U.S. Navy, accessed at: http: J'Avw.navsoujce.org archives 09 19 1906S.htm
c Source: Chns \Vmters.The Tregurtha's campaign ribbons. Accessed at Tvww.b oatnerd.com
The Hon. James L. Oberstar (shown in Figure 7-5) was also repowered when her original
steam plant was removed and replaced with two Rolls Royce Bergen diesels engine in 2009
producing approximately 6,300 kW; she is also the fastest C3 laker with a service speed of 15.5
knots. The Hon. James L. Oberstar was built in 1959 by the American Shipbuilding Company
and was then one of the longest vessels on the lakes at 710 feet. She also went through
numerous changes including being lengthened 96 feet in 1972 and converted into a self-unloader
in 1981; she can discharge her 31,000 gross tons of cargo at a rate of 6,000 tons per hour.
Table 6-2 shows the characteristics of all twelve U.S.-flagged C3 vessels.
Table 7-14 Characteristics of the U.S.-Flagged Category 3 Powered Fleet
157
SHIP NAME
American Spirit
Hon. James L. Oberstar
Edgar B. Speer
Edwin H. Gott
James R. Barker
Lee A. Tregurtha
Maumee
Mesabi Miner
Paul R. Tregurtha
Presque Isle
Roger Blough
Victory
CRT
34,600
16,300
34,600
36,000
34,700
14,700
8,200
34,700
36,400
22,600
22,000
950
BUILT
1978
1959
1980
1978
1976
1942
1929
1977
1981
1973
1972
1981
SHIP TYPE
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Self-Unloader
Tugboat
Self-Unloader
Tugboat
POWER
(KW)
11,900
6,300
14,400
14,500
11,900
6,000
2,400
11,900
12,000
11,200
11,900
5,900
OVERALL
LENGTH
1004'0"
806'0"
1004'0"
1004'0"
1004'0"
826'0"
604'9"
1004'0"
1013'6"
1000'0"
858"
140'0"
YEAR
REPOWERED
2009
2006
1964
2010
ORE
CAPACITY
(GROSS
TONS)
62,400
31,000
73,700
74,100
63,300
29,300
12,650
63,300
68,000
57,500
43,900
NA
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Some vessels, such as the American Spirit, either came equipped with or were later
modified to include bow thrusters that improve maneuverability and reduce docking times by
eliminating the need for tug-assistance to port. The American Spirit was launched in 1978 in
Lorain, OH, by the American Shipbuilding Company and is powered by 2 Pielstick engines that
produce approximately 12,000 kW combined. She is a self-unloader owned by the American
Steamship Company and is primarily used for long-haul transport of iron ore pellets.15
The James R. Barker, built in 1976 was the first 1,000-foot class vessel constructed
entirely on the Great Lakes, where she was built in Lorain, OH by the American Ship Building
Company.159 She is named for the President and Chairman of the Board of the Interlake
Steamship Company and is shown in Figure 7-18. The James R. Barker can carry over 63,000
gross tons which is enough material to produce the steel for 16,000 automobiles.160 She is
powered by 2 Pielstick diesel engines that produce approximately 12,000 kW of power.
Figure 7-18 The James R Barker Heads Downbound at West Pier in the Upper St. Mary's River June 29,
2008
Source: Photo taken by and used with permission from Dick Lund, available here:
http://www.dlund.20m.com/images_2008/SOO062908ai.JPG
In addition to carrying products associated with the production of steel, five C3 vessels
also carry sand or stone according to Lloyds Sea-web database, including the Roger Blough (see
Figure 7-11).161 The Roger Blough was launched in 1972 by the American Shipbuilding
Company, and is the longest traditional (forward pilot house) vessel still working on the Great
Lakes. She is powered by 2 Pielstick diesel engines that produce approximately 12,000 kW of
power. The Blough has a unique self unloader that is located in the stern section of her hull and
can be moved out from either side of the stern, it is 54 feet long and was made to unload directly
into a hopper at the ports of Gary, IN, South Chicago, IL, and Conneaut, OH, when steel mills in
these areas were flourishing. Today, this special unloading system restricts her ability to unload
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at other ports, and she was laid up for several years in the 1980's because of this limited
capability.162 Today, however, she is kept busy by the increasing amount of pellets that travel to
Duluth via train.
Lloyd's Sea-web database also lists grain capacity for four lakers, indicating that these
vessels are capable of carrying grain, including: the Hon. James L. Oberstar, American Spirit,
James R. Barker, and the Mesabi Miner. However, there are no available sources indicating any
of these vessels have carried grain recently, although the Lake Carrier's Association does note
the movement of some grain by U.S. carriers recently, it is unclear which vessels actually move
this grain. The Mesabi Miner, like nearly every other 1,000-footer, was built by the American
Shipbuilding Company and was launched in 1977, see Figure 7-19. Unlike most other vessels,
however, she was not named for a prominent business man; rather she was named in honor of the
men and women of Minnesota's Mesabi Iron Range.163 The Mesabi Miner is powered by two
Pielstick diesel engines that produce nearly 12,000 kW of power and can carry over 63,000 gross
tons of ore and over 57,000 net tons of coal.
Figure 7-19 The Mesabi Miner Arrives in Marquette, MI in December, 2005.
Source: The Mesabi Miner - Taken by Lee Rowe, Arriving Marquette, MI, Dec, 2005.
Of the twelve C3 vessels and tug-barge combinations, ten have self-unloading booms that
are at least 250 feet long, the two ships that do not are the Roger Blough and the Edgar B. Speer,
the latter of which has the shortest boom at 52 feet. Similar to the Roger Blough, the Edgar B.
Speer's boom is mounted on her stern and restricts her cargo to taconite pellets that can only be
unloaded in Gary, IN and Conneaut, IN where the boom can feed directly into a specially
designed hopper. The Edgar B. Speer, shown in Figure 7-20, was built by the American
Shipbuilding Company in Ohio, and was launched in 1980. She has twenty hatches that lead to
five cargo holds and can carry the second largest amount of ore on the Great Lakes at nearly
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74,000 gross tons and over 50,000 net tons of coal. The Edgar B. Speer is powered by 2
Pielstick diesel engines that produce the second most power of any C3 U.S.-flagged vessel in the
Great Lakes fleet, slightly less than 14,400 kW.
Figure 7-20 The Edgar B. Speer Working in the Winter
Source: http://www.duluthboats.com/shippages/shippic37.html
7.5.4 Canadian Category 3 Vessels
In order to determine how many Canadian vessels are Category 3 vessels, we used the
same methodology as for our U.S. study. First, we reviewed the GWG to find the vessels in the
fleet, and then researched the bore and stroke for each individual vessel to determine the cylinder
displacement, and subsequently what category engine is installed in each ship. We found that
there are 68 C3 Canadian-flagged vessels (consistent with the number reported in their
comments on the Category 3 rule164), 20 C2 vessels, and 8 steamships.E
The average age of the 68 Canadian C3 vessels is approximately 30 years, with the
newest vessel being built in 2009, compared to the newest U.S.-flagged vessel having been built
in 1981. Canada recently restructured its tariff system such that there is no longer a 25 percent
tariff on ships over 129 meters long built in foreign countries and imported into Canada, and as a
result a number of new ships are being built in China for the Canadian side of the Great Lakes.F
There are a number of different types of vessels in the Canadian C3 fleet including: 26 self-
unloaders, 24 bulk freighters, 15 tankers, and 3 cargo vessels. The size of these vessels ranges
from over 5,700 GRT to nearly 24,000 GRT with an average of just over 15,000 GRT. The
E Note that these fleet numbers are different from those reported by ICF/EERA in their report contained in Appendix
2C to Chapter 2 (57 C3 and 19 C2 vessels). This discrepancy is not important to this report as these fleet numbers
are provided for completeness for this industry characterization. No fleet-wide cost estimates are developed in the
analyses contained in this report.
F See http://www.fm.gc.ca/nlO/10-089-eng.asp
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reported power of these vessels ranges from just under 2,800 kW to over 11,500 kW with an
average power of nearly 6,600 kW. Based on available data, four of the 68 vessels have been
repowered, one in 1974, and the other three after 2008.
The St. Lawrence Seaway limits the length of ships to 740 feet, and there are no
Canadian ships that are longer than this restricted length in the fleet of 68 vessels; nearly 56
percent of the vessels in this fleet are 740 feet long. The ore capacity ranges from nearly 8,400
gross tons to nearly 38,000 gross tons for the ore-carrying vessels in this fleet. The coal carrying
capacity ranges from 8,700 net tons to over 40,000 net tons for those vessels that carry coal. As
would be expected, the shorter overall length mandates that these vessels carry less cargo than
the U.S. flag ore and coal carriers. Nearly 37 percent of the Canadian C3 vessels carry wheat,
sand or stone, corn and rye, barley or oats with capacities ranging from over 7,000 metric tons to
over 37,000 metric tons of these commodities.
7.5.5 Salties
There are a number of vessels from countries all over the world that travel across the
Atlantic and through the St. Lawrence Seaway to visit the Great Lakes and have done so since
the locks opened in 1959. These vessels travel through the 5 Canadian and 2 U.S. locks to reach
Lake Ontario, and may continue through another 8 Canadian locks of the Welland Canal to enter
Lake Erie and continue on from there to other Great Lakes ports. Since 1959, more than 2.5
billion tonnes of cargo worth an estimated $375 billion have moved to and from Canada, the
U.S. and nearly fifty other nations.165 Nearly 25 percent of the traffic through the Seaway travels
to and from overseas ports, especially from Europe, the Middle East, and Africa. Vessels
visiting from foreign ports must be small enough to pass through the smaller locks (e.g. no more
than 740 feet long) and can therefore easily pass through the Poe Lock in Sault Ste. Marie.
The data presented here on foreign-flagged vessels visiting the Great Lakes comes from
the 2009 Seaway Ships.166 In 2009, 189 different ships visited the Great Lakes from foreign
ports, of these most were bulk carriers (39%) followed by general cargo vessels (37%), chemical
tankers (23%), and one tanker. The majority of these vessels, (14%) were flying the flag of the
Netherlands, Antigua & Barbuda (13%), and Cyprus (11%); while vessels from more than 25
countries visited the Great Lakes. The average GRT of these ships is approximately 12,800,
which is less than the U.S. Great Lakes fleet of 16,000 GRT and the Canadian Great Lakes fleet
at 15,000 GRT. The smallest ship that visited in terms of length and GRT, the Thor Athos, is
less than 291 feet long with a GRT of just over 3,100. The Thor Athos, shown in Figure 7-21, is
a general cargo vessel built in 1987 flagged from the Isle of Man; she delivered her cargo to
Hamilton, ON during her one visit here in 2009.
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Figure 7-21 The Thor Athos. The Smallest Foreign-Flagged Vessel to Visit the Great Lakes in 2009
Source: www.sav-service.com.ua/
The largest vessel in terms of GRT to visit the Great Lakes in 2009 was the Antigua &
Barbuda flagged Bluebill. Rated over 37,000 GRT, the Bluebill is owned and managed by
Navarone SA; and visited the Great Lakes once in 2009, delivering her cargo to Toronto, ON.
The longest foreign-flagged vessel to visit the Great Lakes, the Saguenay, is nearly 730 feet long
with just over 22,700 GRT; she is flagged in the Marshall Islands and visited the lakes four
times, three months in a row starting in June and one more time in November. The Saguenay is
owned by the Canadian Steamship Lines and is one of their straight-deck bulk freighters.
The fleet of foreign-flagged vessels that visited the Great Lakes in 2009 is quite young at
an average age often years in comparison to both the U.S. and Canadian fleets that are on
average 41 and 30 years old respectively. The oldest ship that visited was built in 1980, while
over 6 percent of these vessels were sailing their first season in 2009.
More than 70 percent of the vessels visited the Great Lakes only one time in 2009, just
over 18 percent visited twice and the rest visited no more than four times. In most cases, vessels
that visit multiple times visit the same port each time. Some vessels visit multiple ports during
each visit, for example heading to Ashtabula, OH, then Duluth-Superior, MN. Figure 7-22 and
Figure 7-23 plot the number of times each port was visited by a foreign-flagged ship in 2009.
The port of Duluth-Superior, MN was visited most frequently by foreign-flagged vessels.
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Figure 7-22 Number of Visits by Foreign-Flagged Ships to Ports on Lakes: Superior, Michigan, Huron and
Erie
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Chapter 7: Industry Characterization
Figure 7-23 Number of Visits by Foreign-Flagged Ships to Ports on Lake Ontario and the St. Lawrence
Seaway
In all, there were nearly 400 port visits in the Great Lakes in 2009 to both U.S. and
Canadian ports, of these over 65 percent of these visits were to Canadian ports, nearly 20 percent
of these visits were to Hamilton, ON. The visits to U.S. ports were primarily to Lake Superior,
nearly 37 percent of all foreign-flagged visits to Great Lakes ports were to Duluth, MN.
7.6 Owners Operators of U.S. Category 3 Ships
There are numerous companies that own and operate vessels that work on the Great
Lakes, including small businesses that may operate one tugboat, to large companies that send
ocean-going vessels to Great Lakes ports. Of these, there are five companies that own and
operate the twelve C3 vessels in the U.S. flagged Great Lakes fleet: The American Steamship
Company, The Interlake Steamship Company, Great Lakes Fleet, Inc., Grand River Navigation,
and KK Integrated Logistics LLC. This section provides a brief overview of these five
companies.
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7.6.1 The American Steamship Company
The American Steamship Company (ASC) was founded in Buffalo, NY in 1907, and is
headquartered today in Williamsville, NY.167'168 In 1917, ASC vessels were the first on the
Great Lakes to be equipped with radio telegraph sets removed from Navy vessels at the end of
World War I. In the 1930's, ASC was the first company on the Great Lakes to convert their bulk
freighters into self-unloading vessels. In 1973, ASC was acquired by the General American
Transportation Corporation, known as the GATX Corporation of Chicago, and added a number
of new vessels to their fleet throughout the 1970's. In 1996, the American Republic, a Category
2 Great Lakes vessel belonging to ASC made history by carrying the Olympic flame on her deck
with a specially-built cauldron on her bow; she carried the torch from Detroit, MI to Cleveland,
OH on its way to the Olympic Games in Atlanta, GA. In 2002, ASC pooled operations with
Oglebay Norton Marine Services under the name of the United Shipping Alliance, however, they
terminated this relationship in 2006 and ASC purchased six vessels increasing their fleet to 18
vessels. This fleet of 18 vessels is all self-unloading and ranges in length from 635 feet to 1,000
feet, with carrying capacities ranging from nearly 24,000 to over 80,000 gross tons which can be
unloaded at speeds from 7,000 to 10,000 net tons per hour. In 2009, ASC vessels could carry 39
percent of the total industry annual capacity on the Great Lakes, and primarily served electric
utilities, followed by the steel industry and construction. In 2009, ASC moved 21 million net
tons of cargo which was comprised of 48 percent coal, 39 percent iron ore, 10 percent limestone
aggregates, and 3 percent other. Of their 18 vessels, three are steamships and six are thousand-
footers.
GATX, ASC's parent company was founded in 1898 as a railcar lessor and today still
specializes in railcar leases serving both the North American and European markets with 162,000
train cars; 83 percent of their assets are involved with the rail industry. They also own a fleet of
approximately 600 locomotives, and lease these as well as provide maintenance services,
engineering, and training to the rail industry, in addition to owning and leasing marine vessels,
and other industrial equipment. GATX reaches beyond the Great Lakes and has invested in
ocean-going vessels as well and are a part of five joint ventures that involve over 30 of these
vessels including: bulk carriers, chemical tankers, LPG carriers, and multi-gas carriers. Their
industrial equipment portfolio serves the transportation, mining, and automotive industries. In
2009, GATX had a gross income of $1.15 billion, with assets worth $6.2 billion, while ASC had
a gross income of $132.7 million in 2009 down from $271.5 million in 2008.169
7.6.2 Interlake Steamship Company, and the Lakes Shipping Company
The Interlake Steamship Company was founded in 1913 through a consolidation of all
the vessels formerly managed by Pickands Mather & Company founded in 1883.170 The
Pickands Mather & Company began as a start-up company with an interest in an Upper
Michigan iron range land, and a 13/20 interest in a 1,700 ton capacity wooden steamer; their
company grew along with the demand for steel during the turn of the century and in 1913, their
fleet numbered 39 vessels. In 1927, they commissioned the Str. Harry Coulby which was larger
than any other vessel on the Great Lakes at 631 feet long; she was the first to carry more than
16,000 tons of cargo. Over the years, Interlake continued to modernize its fleet adding some
newly constructed ships, lengthening, converting and acquiring others. In 1975, the Str. Herbert
C. Jackson was the first of three Interlake straight-deck vessels to be converted to self-unloaders.
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Between 1976 and 1981, Interlake added three vessels to their fleet: the James R. Barker, Mesabi
Miner, and Paul R. Tregurtha which together added 194,600 gross tons to Interlake's total
capacity. In 1987, Interlake became a privately held company. In 1989, the three boats left in
the Rouge Steel fleet were purchased and organized as the Lakes Shipping Company under the
management of the Interlake Shipping Company; these three vessels include: the Lee A.
Tregurtha, Str. Kaye E. Barker, and the Str. John Sherwin.
Today, Interlake is headquartered in Richfield, OH. They own and operate nine vessels
over 2,000 GRT on the Great Lakes including: three steamships, five vessels powered by C3
engines, and one powered by a C2 engine. In 2010, Interlake was awarded the Midwest Clean
Diesel Initiative Leadership Award for repowering three of their vessels with new diesel engines.
7.6.3 Great Lakes Fleet, Inc.
Great Lakes Fleet (GLF) is owned by Canadian National (CN) and operated by the
Keystone Shipping Co., based in Duluth, MN.171 GLF owns a fleet of eight vessels including
four steamships and four C3 powered vessels; seven of the vessels are self-unloaders while the
eighth is an integrated tug-barge combination, the Presque Isle, which is also self-unloading.
The Great Lakes Fleet vessels came from U.S. Steel's Great Lakes fleet which was sold in 2001
to Great Lakes Transportation LLC, a conglomerate of other transportation companies. Great
Lakes Transportation was then sold to CN Railway in 2004. In 2009, CN had revenues of over
$7.3 billion and employed nearly 22,000 people.1 2
GLF transports dry bulk cargoes, primarily for the U.S. steel industry; their fleet serves
both U.S. and Canadian ports. Their ships range from 767 feet to 1,004 feet in length with
carrying capacities of 28,400 to 74,500 net tons. Products handled include taconite and natural
iron ore mined in the Upper Peninsula of Michigan along the western edge of Lake Superior and
shipped to Detroit, Erie, and the lower end of Lake Michigan. They also ship limestone mined
along northern Lake Huron and shipped throughout the Great Lakes, coal, petroleum coke, slag,
mill scale, taconite pellet screenings, and sand. Great Lakes Fleet vessels have a very distinctive
paint scheme, as shown below on the Arthur M. Anderson in Figure 7-24.
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Figure 7-24 The Arthur M. Anderson Visiting Duluth, MI in November, 2009
f
y
Taken by and used with permission from Andrew Tubesing. Source:
http ://www. ee. nmt. edu/~tubesing/personal/boats/boatwatcher. htm
7.6.4 Grand River Navigation
Grand River Navigation (GRN) was acquired by Rand Logistics in 2005 along with
Lower Lakes Towing Ltd.173 GRN is headquartered in Avon Lake, OH with offices in Traverse
City, MI, Rand Logistics is headquartered in New York, NY. The Rand fleet is made up of the
Lower Lakes fleet of eight Canadian vessels, and the GRN fleet of six vessels which includes 4
self-unloading vessels, and one articulated tug-barge combination that is also a self unloader.
These vessels range in length from just over 609 feet to 630 feet with capacities of 12,650 to
nearly 20,000 tons. In July, 2010 Rand announced it would repower its last steamship, the S.S.
Michipicoten to diesel power during the winter of 2010, similar to the repowering of the Saginaw
that they completed in 2008 for an estimated cost of $15 million.174 For the fiscal year of 2010,
Rand announced marine freight revenues (excluding fuel and other surcharges, and outside of
charter revenue) was $85.1 million with total sail-days equal to 3,143, down 5 days from
2009.175
7.6.5 KK Integrated Logistics LLC
KK Integrated Logistics operates two articulated tug-barge combinations, with one tug,
the Victory, powered by a C3 engine. They are headquartered in Menominee, MI with offices in
Marinette, Manitowoc, and Green Bay Wisconsin.176 They offer warehousing, stevedoring,
shipping, and trucking. KK Integrated Logistics has two privately owned ports in Menominee,
MI and Green Bay, WI with two loading docks at each port and on-site rail access. The port in
Menominee was built to serve the wind industry and can store over 13 shipments of windmill
towers. Their two articulated tug-barge (ATB) combinations were both purchased as steamships
and converted to ATBs in 2006 and 2007 and are both self-unloaders.
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Appendices
Additional Features of the
Great Lakes Transportation System
This Appendix describes several features of the Great Lakes Transportation network,
including seasonal operation constraints, the interface with rail, the impact of cabotage laws, the
amount of cargo shipped on the Great Lakes, and Great Lakes waterway routes, including the
canal system.
Seasonal Constraints
During the winter, the Great Lakes often experience widespread ice cover typically
beginning in mid-December and ending in mid-April, as a result, navigation is restricted. For
instance, every year the Soo Locks close from January 15 to March 25.177 This severely restricts
shipping in the Great Lakes as the Soo Locks provide the only point of access from Lake
Superior to both Lake Michigan and Lake Huron. The U.S. Coast Guard operates the icebreaker
Mackinaw on the Great Lakes to enable ships to pass through the ice while the Locks are open;
however, cargoes are not shipped during the month of February and in some cases during the
month of January.178
Interface with Other Modes of Transportation
The Great Lakes serve as an effective and convenient mode of transportation, especially
for raw commodities. However, the origins and destinations of these materials are not always
located directly on the lakes. As a result, the method to get these materials from their source to
their endpoint is often intermodal transportation. For example, much of the coal transported on
the Great Lakes comes from either the Powder River Basin in Montana or the Appalachian
region. Neither of these coal deposits is adjacent to the Great Lakes and therefore neither has a
mine on the shores of the Great Lakes. While power plants are often located near water in order
to maintain a steady stream of cold water for their power generation, steel mills don't have the
same requirement. Coal that goes to steel mills, along with iron ore and limestone, usually must
travel by rail to get to the final destination. Both the origins and destinations of iron ore, stone,
and grain aren't always on the shores of the Great Lakes and therefore require more than one
mode of transportation to get to the endpoint. For example, the Mesabi Iron Range serves as the
main source of iron ore for Great Lakes industry. Canadian National (CN) owns Duluth,
Missabe, & Iron Range line, which services the iron range.179 This line also runs to Duluth,
Minnesota, where CN owns the ore loading dock.180'41 The ore would then be loaded on a lake
vessel for transport to any number of steel mills on the Great Lakes, most of which have ore
docks at their facilities.
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Chapter 7: Industry Characterization
Cabotage Laws (U.S., Canada)
Domestic waterborne transportation is safe, reliable, efficient and an established mainstay
of America's national transport system. The domestic shipping operations of the American
merchant marines provide essential services to 41 states reaching 90 percent of the national
population. This form of surface transportation handles a combined total of over 1.1 billion short
tons of cargo, which is about 23 percent of the ton-miles of all domestic surface transportation
traffic. Domestic waterborne transportation contributes $7.7 billion to the gross domestic product
annually in the form of freight revenue.
To encourage a strong U.S. merchant marine for both national defense and economic
security, the nation's domestic waterborne commerce is reserved for vessels built in the United
101
States, owned and crewed by American citizens, and registered under the American flag. ' U.S.
laws governing the domestic transportation of passengers and cargo by water are generally
known as the Jones Act, named after Senator Wesley Jones (R-WA), the sponsor of the
Merchant Marine Act of 1920. The Jones Act continues to be the foundation for America's
domestic shipping policy.
The Jones Act (46 U.S.C. 883, 19CFR 4.80 and 4.80b) requires that merchandise being
transported by water between U.S. points must travel in U.S.-built and U.S.-citizen owned
vessels that are documented by the U.S. Coast Guard for such carriage. The U.S. Customs
Service has direct responsibility for enforcing the provisions of the Jones Act and is statutorily
limited to granting waivers from the Act only in the interest of national defense or for a vessel in
distress.
The Canadian equivalent of the Jones Act that establishes laws regarding domestic
commercial marine activity is known as the "Coasting Trade Act." It includes the transportation
of goods and passengers between Canadian points as well as any other commercial marine
activity in Canadian waters. The Coasting Trade Act supports domestic marine interests in a
similar manner as the U.S. Jones Act by reserving the coastal trade of Canada to Canadian-
1 $T")
flagged ships, with some exemptions.
Foreign-flagged vessels entering the Great Lakes through the St. Lawrence Seaway can
deliver and take out cargoes at any port for export. The Jones Act, for example, only prevents
these ships from picking up and subsequently delivering cargo within the U.S.
How Much Cargo is Moved on the Great Lakes
The Lake Carriers' Association (LCA) represents eighteen operators of U.S.-flagged
vessels that operate on the Great Lakes. Similarly, the Canadian Shipowners' Association (CSA)
represents owners and operators of Canadian-flagged vessels in Canada. These two associations
report the tonnages moved by their respective members each year. In 2009, LCA reported that
their members moved over 111 million net tons of dry bulk tonnage; while CSA reported that
their members moved over 51 million net tons.G Figure 7A-1 shows the dry-bulk tonnages
G The LCA only reports tonnages for dry bulk cargoes including: iron ore, coal, limestone, salt, cement, and grain
while the CSA reports dry bulk tonnages for the following cargos: coke, general cargo, gypsum, misc. bulk, and
potash. In addition, the CSA also reports tanker cargos. In order to compare the dry bulk results here, the remaining
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Chapter 7: Industry Characterization
moved by type of cargo reported moved by the LCA and the CSA in 2009. The difference in the
amount of cargo between U.S. and Canadian vessels in part can be explained by the length and
capacity of the vessels operating on the lakes.
Figure 7A-1 U.S. and Canadian Dry Bulk Tonnage in 2009 from LCA and CSA
40
I Lake Carriers Association (net tons)
I Canadian Shipowners Association
In terms of what type of dry-bulk tonnage makes up the majority of this category of
cargo, both the LCA and the CSA report that ships mainly move iron ore, although the CSA
reports that their vessels move more salt then coal, while the LCA reports that coal is the second-
most moved cargo in 2009. The total amount of coal moved on the Great Lakes as reported by
LCA or nearly 30 million net tons, or approximately 3.4 percent of the amount of coal moved by
rail in the U.S. which according to the American Association of Railroads (AAR) was over 878
1 R'?
million tons in 2009. Coal is the most frequently moved cargo by railroads comprising over
45 of all moved tonnage in 2009. In terms of metallic ores, LCA reports that U.S.-flagged
vessels moved approximately 32 million tons of iron ore in 2009, while the AAR reports that in
2009 nearly 60 million tons of metallic ores were moved by rail. Figure 7A-2 highlights how
important the iron ore, coal, and limestone cargos are to the Great Lakes fleet of vessels, both in
the U.S. and in Canada.
categories of CSA cargos were totaled as "Other" and are included in the dry bulk totals presented in this analysis.
Note that the 51.4 million net tons reported moved in 2009 by CSA also includes 6.6 million tons of tanker products.
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Chapter 7: Industry Characterization
Figure 7A-2 Dry-Bulk Tonnages Moved on the Great Lakes in 2009
Lake Carrier Association - U.S.-Flagged Dry Bulk
Tonnage
Canadian Shipowners Association - Canadian-
Flagged Dry BulkTonnage
11%
2 IK
27=.;
14%
27%
19":
iron ore
Coal
Limestone
Salt
Grain
cerrent
other
14 %
Great Lakes Shipping Routes
Shipping routes on the Great Lakes are dictated by the nature of the cargo and backhaul
being carried by each vessel. More specifically, the location of iron ore, coal mines, and stone
quarries dictated, in the late 1800's, where ports would be built and what they would handle.
These old ports are still in use today, and the characteristics of these ports continue to set limits
on the size and type of vessel that can be used on a route (draft limitations; loading and
unloading equipment).
For example, iron ore is the most common cargo shipped across the Great Lakes due to
the fact that major iron ore mines are located close to Lake Superior and the lower St. Lawrence
1 ฐ.zl
River. Vessels collect ore at these locations and deliver them to the steel mills located
primarily at the southern ends of Lakes Michigan and Erie. In this case, mining in the Mesabi
IOC
Range led to the establishment of the ports of Duluth-Superior as early as 1892, and steel mills
were located in Illinois, Indiana, and Ohio to take advantage of ship transportation and abundant
supplies of water. Similarly, coal traffic through Lakes Superior, Michigan, Huron, and Erie has
largely been driven by the availability of low sulfur coal from the Powder River Basin.
Limestone has seen an increase in demand as it aids in the reduction of sulfur emissions through
the use of scrubbers from coal-burning industries.
Figure 7A-3 shows the origins of the main commodities shipped on the Great Lakes and
the routes they typically operate.
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Chapter 7: Industry Characterization
Figure 7A-3 Shipping Routes Along the Great Lakes by Commodity
GREAT LAKES SHIPPING
0 100 rmlw
0 100 ttonnwtt
Mining Shipping
<^~ (ron ore
Coal
Limestone
Grain
I Steel center
In Manufacturing center
SuMTtOC *_!ป*,
* * AiMind ^TTlro
MD.
1X6
Source: Army Corps of Engineers, "Great Lakes Navigation System Five-Year Development Plan."
Waterways
There are a number of lakes, rivers, and locks that make up the navigable waterways of
the Great Lakes region which empties into the Atlantic Ocean.187 The Great Lakes include: Lake
Huron, Lake Ontario, Lake Michigan, Lake Erie, and Lake Superior; they are connected by three
main rivers: the St. Clair River, St. Mary's River, Detroit River, and are connected to the
Atlantic Ocean via the St. Lawrence River. The lakes are the largest system of fresh, surface
1 R R
water on earth, containing nearly 21 percent of the world supply. ฐ They contain approximately
1 QQ
5,500 cubic miles of water and cover an area of nearly 94,000 square miles. Ships travelling
from the Atlantic Ocean can reach the western edge of Lake Superior in 8.5 sailing days.
Despite their large size, however, the Great Lakes are sensitive to the effects of a wide range of
pollutants. The sources of pollution include the runoff of soils and farm chemicals from
agricultural lands, the waste from cities, discharges from industrial activity such as ship
emissions and leachate from disposal sites. The large surface area of the lakes also makes them
vulnerable to direct atmospheric pollutants that fall with rain or snow and as dust on the lake
surface.190 Outflows from the Great Lakes are relatively small (less than 1 percent per year) in
comparison with the total volume of water. Pollutants that enter the lakes - whether by direct
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Chapter 7: Industry Characterization
discharge along the shores, through tributaries, from land use or from the atmosphere - are
retained in the system and become more concentrated with time. Also, pollutants remain in the
system because of resuspension (or mixing back into the water) of sediment and cycling through
biological food chains.
Figure 7A-4 The Great Lakes Waterways
Lake Superior is the coldest, deepest, and largest of all the Great Lakes; it is 350 miles
long and 160 miles wide and in terms of volume could hold all of the other Great Lakes and
three more Lake Erie's combined; the average depth is 483 feet with a maximum depth of 1,330
feet. Due to its large size and small outflow, it has a retention time of 191 years.191 Lake
Superior is an estimated 183.5 meters above sea level, while both Lake Huron and Lake
Michigan are 176.3 meters above sea level. The Soo Locks lead vessels from Lake Superior to
the St. Mary's River on their way to Lake Huron and Lake Michigan. Lake Huron is the widest
lake of the five at 183 miles wide and is 206 miles in length; it also offers the most shoreline of
the lakes at over 3,800 miles. Lake Michigan and Lake Huron are connected directly at the
Straits of Mackinac. Lake Michigan is the second largest Great Lake in terms of volume, and the
second longest after Superior at 307 miles and is 118 miles wide; it is the only lake that lies
entirely within the U.S. border. The southern shore of Lake Michigan is one of the most heavily
urbanized areas of all the lakes, and includes Milwaukee, WI, and Chicago, IL.
Vessels traveling to Cleveland, OH, for example, from Chicago would go through the
Straits of Mackinac and under the Mackinac Bridge and into Lake Huron, and then into the St.
Clair River through Lake St. Clair and through the Detroit River to arrive in Lake Erie. Lake
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Chapter 7: Industry Characterization
Erie is slightly lower than Lake Huron, at 174.3 m above sea level, and is the most biologically
productive of the Great Lakes.192 Lake Erie is also the smallest of the lakes by volume it is 241
miles long and 57 miles wide and is the shallowest of all the lakes with an average depth of 62
feet. From Lake Erie, vessels must go through the Welland Canal to pass through the nearly 100
meter drop between these two bodies of water. Lake Ontario is approximately 75 m above sea
level, and although slightly smaller than Lake Erie in terms of area, Lake Ontario is much deeper
with an average depth of 283 feet and a maximum depth of 802 feet. Lake Ontario is 193 miles
long and 53 miles wide. The U.S. shoreline is less urbanized than the Canadian side of Lake
Ontario which includes the industrial areas of Toronto and Hamilton. Finally, vessels heading to
the Atlantic Ocean will have to pass through the Montreal/Lake Ontario sections of locks and the
St. Lawrence Seaway which is nearly 2,340 miles long.193
The Soo Locks
Located on the St. Mary's River in Sault Ste. Marie, MI the Soo Locks connect Lake
Superior to the lower lakes. The Soo Locks consist of two canals and four locks. The Poe Lock
is the newest lock, built in 1968, and is 110 feet wide and 1200 feet long. The MacArthur Lock
was built in 1943 and is 80 feet wide and 800 feet long. The remaining two locks, the Davis and
the Sabine were built prior to 1920 and are currently closed. In 2008, over 72 million tons of
cargo valued at over $3.2 billion passed through the Soo Locks, 62 percent of which was iron
ore. The Army Corps of Engineers maintains and operates the locks, and is evaluating the
replacement of the Davis and Sabine locks with a single lock that would be 110 feet wide and
1,200 feet long. Congress authorized the replacement of this lock in the Water Resource
Development Act of 1986, and groundbreaking ceremonies have occurred, however, whether or
not there will be funding for the entire project is not clear.194
7A -5 The Edgar B. Speer Travels Through the Poe Lock in Sault Ste. Marie with Approximately 30" of
Clearance per Side.
Source: Photo taken by and used with permission from Dick Lund, available here:
http://www.dlund.20m.com/custom5.html
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Chapter 7: Industry Characterization
Welland Canal
The Welland Canal consists of a series of eight locks that provide over 326 feet of lift and
leads ships through 27 miles of channels and locks.195 The locks limit the size of ships that can
pass through the entire Seaway and enter the Great Lakes; ships must be no more than 740 feet
long, 78 feet wide, the draft can change yearly depending on water levels. In 2010, the canal
opened on March 25, 2010 with a draft of 26 feet 3 inches.196 Vessels transiting through this
waterway are typically either freighters or tug/barge combinations that travel exclusively on the
Great Lakes, or are ocean-going vessels. The large Great Lakes freighters typically carry iron
ore from the Quebec Labrador mining area to the steel mills that are located in the Great Lakes.
These same vessels may also carry grain to ports along the lower St. Lawrence River that will be
loaded aboard ocean-going vessels for shipment overseas.
Figure 7A--6 Locks 4,5, and 6 of the Welland Canal
Source: St. Lawrence Seaway Management Corporation
The development, operation, and maintenance of the Seaway are under the joint control
of the St. Lawrence Development Corporation, a corporate agency of the U.S., and the St.
Lawrence Seaway Management Corporation of Canada (SLSMC). The U.S. Corporation
headquarters is in Washington, D.C., and the operational field headquarters is in Massena, N.Y.
The Canadian Corporation headquarters is in Cornwall, Ont, with field offices in Cornwall, St.
Lambert, and St. Catherines. The SLSMC operates and manages the assets of the St. Lawrence
Seaway for the Canadian Government under a long-term agreement with Transport Canada. The
SLSMC oversees the transit of over 4,000 vessels each year through the Seaway during their
season that typically goes from late March to late December.
Ships up to 78 feet wide enter the 80 foot wide lock, remain under their own power, and
are tied up as large steel gates close and the lock either fills or empties via gravity flow. The
amount of water used to fill a lock can vary, depending on the size of the lock, but is generally
upwards of 15 million gallons which can flow in and fill the lock in approximately 15 minutes.
Typically, the total lock transit time can be at least 30 minutes, which includes the vessel
approach, mooring, etc. The total estimated time it takes to travel through the entire Welland
Canal is 8-12 hours depending on traffic.
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Chapter 7: Industry Characterization
Figure 7A-7 The Edward L. Ryerson Passing Through Lock 2 of the Welland canal
Source: St. Lawrence Seaway Management Corporation
The Lake Ontario/Montreal Canal System of the St. Lawrence Seaway
The St. Lawrence Seaway is a nearly 2,340 mile stretch of navigable waters and locks
connecting the Atlantic Ocean to the Great Lakes and in addition to the Welland Canal, it also
includes the Montreal/Lake Ontario section that is comprised of a series of seven locks.197 The
Montreal/Lake Ontario section of the St. Lawrence Seaway allows vessels to navigate between
Lake Ontario and the lower St. Lawrence River. Dominant commodities moved in this waterway
are: iron ore, coal, limestone, grain, cement, and general cargo such as iron products and heavy
machinery. The first set of locks heading from the Great Lakes to the Atlantic Ocean is the
Iroquois lock that provides between 0.6 and 1.8 m of lift, depending on the water height of Lake
Ontario. The other locks include: two U.S. locks the Snell and Eisenhower, the Lower and
Upper Beauharnois, Cote Ste. Catherine, and the: St. Lambert locks. Figure 7A-8 shows the
major ports along the Great Lakes and the St. Lawrence Seaway. It is estimated to take
seventeen hours to travel through the locks of the upper St. Lawrence Seaway.
Figure 7A-8 Ports of the Great Lakes and the St. Lawrence Seaway
Sept-Iles
Port-Ca
Baie Co
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Chapter 7: Industry Characterization
In 2009, the Seaway celebrated its 50* year of operation while the current Welland Canal
is approaching its 80th year in operation. Tonnage in 2009 dropped to levels not seen since the
early 1960s, and was down nearly 25 percent from 2008 levels or 30.7 million tonnes, with more
tonnage passing through the Welland Canal than the Montreal/Lake Ontario section.198 The drop
in production in the steel industry had a significant effect on the decrease in tonnage in the
2009/2010 season, with shipments of iron ore falling nearly 58 percent to just over 5 million
tonnes through the Montreal/Lake Ontario section and a drop of over 34 percent to 2.7 million
tonnes through the Welland Canal.
Figure 7A-9 Tonnage of Freight by Type Moved Through the St. Lawrence Seaway
TRAFFIC RESULTS: COMBINED
(Total cargo in millions of tonnes)
B
Gram
Iron Ore
2005
To,: Other Bulk
2006 p5 2007
Se-ecs
2QOS
2003
Source: 2009/2010 Seaway Annual Report
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Chapter 7: Industry Characterization
Chapter 7 References
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7 See http://www.lre.usace.army.mil/ETSpubs/HFS/Two%20Harbors.pdf. accessed 9/2/2010.
8 See http://www.toledoseaport.org/. accessed 9/1/2010.
9 See http://www.portofcleveland.com/site.cfm/Maritime.cfm. accessed 9/1/2010.
10 See www.ussteel.com. accessed 8/4/2010.
11 See http://www.associatedcontent.com/article/2505655/the_presque isle iron ore dock.html?cat=8. accessed
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12 See http://dteenergv.mediaroom.com/index.php?s=43&item=551. accessed 9/3/2010.
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14 Cellu Tissue Holdings, Inc. (2009). Locations [Map]. Retrieved August 2, 2010, from
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19 Consumers Energy. (2010). J. H. Campbell generating complex. Retrieved July 23, 2010, from
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26 Ironore Company of Canada. (2009). About IOC. Retrieved July 8, 2010, from
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27
Lake Carriers' Association. (2008). 2008 statistical annual report of Lake Carriers' Association: 2008 limestone
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31 Hoclim. (n.d.). Cement production [Interactive process map]. Retrieved August 3, 2010, from
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32 van Oss, H. G. (2010, January). Domestic Production and Use. In Cement. Retrieved July 9, 2010, from U.S.
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33 Lake Carriers' Association. (2008). 2008 statistical annual report of Lake Carriers' Association: 2008 grain
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34 Canadian Grain Commission. (1998). Exports by clearance sector. Canadian grain exports. Retrieved from
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42 Lake Michigan Carfeny. (2010). S.S. Badger: A little history, a lot of fun! Retrieved August 4, 2010, from
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43 Manning, J. R. (2009, February 27). Lake Michigan car ferry service. In SS Badger, Lake Michigan carferry
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44 Great Lakes St. Lawrence Seaway Study. Final Report. Transport Canada, U.S. Army Corps of Engineers, U.S.
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Development Corporation, Environment Canada, and U.S. Fish and Wildlife Service. Fall 2007. A copy of this
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45 Four Corridor Case Studies of Short-Sea Shipping Services. Short-Sea Shipping Business Case Analysis.
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46 Winebrake, James J. et al. Intermodal Freight Transport in the Great Lakes: Development and Application of a
Great Lakes Geographic Intermodal Freight Transport Model, Final Report. October 31, 2008. A copy of this
report can be found at http://www.glmri.org/downloads/winebrake08a.pdf. See also
http://www.glmri.org/do wnloads/2009Reports/affiliatesMtg/Winebrake&Hawker.pdf
47 Transport Canada and U.S. Department of Transportation (2007). Great Lakes St. Lawrence Seaway Study, Final
Report, Fall 2007. Chapters.
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51 Essar Steel Algoma. (2008, June 23). Company. Retrieved July 13, 2010, from http://www.algoma.com/company/
52 Severstal. (2006). Severstal Dearborn, Inc. In North American operations. Retrieved July 13, 2010, from
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53 ArcelorMittal. (n.d.). Hamilton Operations. Retrieved July 14, 2010, from ArcelorMittal Dofasco website:
http://www.dofasco.ca/bins/content_page.asp?cid=339-342
54 Severstal. (2006). In North American operations. Retrieved July 13, 2010, from
http://www.severstalna.com/about-us/north-american-operations.html
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Chapter 8: Peer Review
CHAPTER 8: Response to Peer Review Comments
This EPA report has undergone peer review pursuant to EPA's Science Policy Council
Peer Review Handbook, 3rd edition (Peer Review Handbook).^ The peer review was facilitated
by RTI International. The three reviewers were Dr. Michael Belzer of Wayne State University,
Dr. Bradley Hull of John Carroll University, and Mr. James Kruse of the Texas Transportation
Institute.
Appendix 8A to this chapter contains peer review comments and responses that are not
addressed in the above chapters of this document, and is included here for completeness
purposes; it was not part of the draft document that underwent peer review. In addition to
writing our responses, EPA retained the original contractor who conducted the mode shift study,
EERA, to prepare responses to certain of the comments pertaining to their contractor report,
contained in Chapter 2, Appendix 2C. While most mode-shift related comments have been
addressed directly in Appendix 2C, EERA also produced a separate document for addressing
certain comments, and this is attached as Appendix 8B.
Finally, the documentation of the peer review process and summary of its findings are
found in the technical memorandum titled "Peer Review of EPA's 'Economic Impacts of the
Category 3 Marine Rule on Great Lakes Shipping' Study," included as Appendix 8C.
8.1 Overview
The reviewers were charged to review and provide comments on: 1) the clarity of the
presentation; 2) the overall approach and methodology; 3) the appropriateness of the datasets and
other inputs; 4) the data analyses conducted; and 5) appropriateness of the conclusions. The
reviewers were asked to focus their review on the first three chapters of this report.
All three reviewers provided supportive comments as well as suggestions for
improvements. The reviewers generally found the EPA report to be comprehensive and well
written. Overall, reviewers concurred with the selected methodology.
8.2 Comments Not Addressed Specifically
Where practical, responses to comments from peer reviewers have been incorporated into
the body of this report, in the sections to which the comments were directed. Reviewers also
made several suggestions for straightforward editorial revisions, such as use of unit labels for
numbers and consistent use of terms. Unless noted otherwise, these were all accepted and
resulted in changes to the report that may not be highlighted within the context of the narrative.
In addition, some substantive comments warrant responses that don't fit into the
narrative. These have been collected and are presented with their responses in Appendix 8A.
A These guidelines can be found at http://www.epa.gov/peerreview/. Further, the Office of Management and
Budget's (OMB' s) Information Quality Bulletin for Peer Review and Preamble (found in the EPA's Peer Review
Handbook, Appendix B) contains provisions for conducting peer reviews across federal agencies and may serve as
an overview of EPA's peer review process and principles.
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Appendices
EPA Responses to Peer Review Comments on 'Economic Impacts of
the Category 3 Marine Rule on Great Lakes Shipping'
In this appendix, EPA provides responses to the substantive comments offered by
reviewers that did not fit easily into the narrative of the report, and that are not addressed by the
EERA work in Appendices 2C or 8B.
8A.1. Ships' Contribution to Air Pollution 8-3
8A.2. Scope of Analysis; U.S. Jurisdiction 8-4
8A.3. Steamship Applicability 8-6
8A.4. Fuel Availability and Fuel Price 8-7
8A.5. Scenario Selection 8-9
8A.6. Transportation Mode Shift - Methodology; Validation 8-10
8A.7. Source Shift Analysis: Stone Scenarios 8-11
8.A.7.1 Qualitative Comparisons 8-12
8.A.7.2 Data Assumptions 8-13
8A.8. Air Emissions Comments 8-14
8A.9. Production Shift: Electricity and Steel 8-16
8.A.9.1 Cost of Production 8-16
8.A.9.2 Coal Movements for Electric Sector / Revenues 8-16
8.A.9.3 Coal Transport Costs 8-17
8.A.9.4 Elasticity 8-17
8.A.9.5 Coal Movements for Steel 8-18
8.A.9.6 Steel Raw Material Costs 8-18
8A.10. Production Shift: Supplemental Steel Analysis 8-19
8A.10.1 Quotas 8-19
8A.10.2 Linear Flow Model 8-19
8A.10.3 Consideration of Steel Coil/Grain Movements 8-20
8A. 10.4 Trans-Pacific Routes 8-23
8A.10.5 Steel Costs 8-24
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8A.11. Impacts of Fuel Sulfur Controls on Emerging Markets - Containers 8-24
8A.12. Other Comments 8-27
8A.12.1 Grain Exports 8-27
8A. 12.2 Retrofitting 8-28
8A.12.3 Stakeholder Participation 8-28
8A.1. Ships' Contribution to Air Pollution
Commenter
Comment
Hull
Demonstrate that ships are a major contributor to sulfur problems in the Great Lakes/St.
Lawrence region. Your study hasn't done that in a convincing way. Convince the
audience. Provide a chart that shows ship emissions versus sulfur emissions from all the
other polluters: trucks, railroads, automobiles, and manufacturers in the Great Lakes
area. Convince the audience that adopting MDO will have a significant positive impact on
the Great Lakes environment. Demonstrate that despite the fact that a large percentage
of ship emissions occur in unpopulated areas, ships are major polluters in populated areas
compared with shore based emissions sources.
Hull
At the beginning of Chapter 1, make the case that marine emissions are a big problem in
the Great Lakes and St. Lawrence. This is the reason for having a C3 ruling in the first
place. Present statistics showing that the Great Lakes are a non-attainment region and
establish that marine emissions are a considerable percentage of those emissions. Add a
table comparing the emissions from ships, trucks, railroads, automobiles, and factories
showing the relative contribution of each to our densely populated region.
Hull
Page 1-4: Please document the degree to which ships contribute to the air quality in the
region, compared with other emissions sources. From a novice's point of view, the
Midwest economy is depressed, and shipping is considerably off, so with few ships there
will be few air emissions. Also, I would imagine that trucks, rail, and factories contribute a
much greater share than do ships. If possible it would be useful to document this.
EPA Response:
EPA performed an extensive analysis of the environmental need for the new Category 3 engine
standards and fuel sulfur limits as part of our Category 3 rule.
We estimate that in 2009 Category 3 engines contributed about 10 percent of national mobile
source emissions of nitrogen oxides (NOx), about 24 percent of national mobile source diesel
PM2.5 emissions (with PM2.5 referring to particles with a nominal mean aerodynamic diameter
less than or equal to 2.5 |im), and about 80 percent of national mobile source emissions of sulfur
oxides (SOx). Without new controls, we anticipate the contribution of Category 3 engines to
national emission inventories to increase to about 24 percent, 34 percent, and 93 percent of
mobile source NOx, PM2.5, and SOx emissions, respectively in 2020, growing to 40 percent, 48
percent, and 95 percent respectively in 2030.
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The inventory, air quality and benefits analyses developed for our for Category 3 rule were
developed on a national basis. In response to comments on our Category 3 rule proposal (see
Section 1.5.1), we also prepared a memorandum to the docket discussing the inventory impacts
and the benefits and costs of the applying the Coordinated Strategy to the Great Lakes region in
response to comments on our proposal.1 Chapters 4, 5 and 6 of this report expand on that
analysis.
We estimate that Great Lakes vessels will account for about 1.5 percent of uncontrolled national
emissions of Category 3 marine for each of NOx, PM2.5 and SOx emissions in 2020.B If
Category 3 engines on the Great Lakes were to remain uncontrolled after the Category 3
requirements for engines and fuels go into place, these percentages would increase to 2.3
percent, 10 percent, and 26 percent for NOx, PM2.5, and SOx emissions, respectively.
With regard to human health and welfare impacts, we are able to use the air quality modeling
performed for the national rule to estimate air quality and benefits impacts of the application of
the EGA fuel sulfur requirements for the six states bordering the Great Lakes: IL, IN, MI, MN,
OH, and WI. The results of the disaggregation of national to regional benefits are contained in
Section 5.5 of this report. This analysis shows that the monetized PM2.5 human health and
welfare benefits that would accrue to these six Great Lakes states in 2030 from applying the
EGA fuel controls in the Great Lakes are expected to be between $1.5 and $3.7 billion, compared
to total projected costs of about $0.05 billion.
8A.2. Scope of Analysis; U.S. Jurisdiction
Commenter
Comment
Hull
Page 1-8: North American EGA: Ships transiting the Seaway will travel many more miles
with the North American EGA than will ships travelling from, say, Europe to an East Coast
port. Thus the ruling will fall more heavily on Seaway transits than any other part of the
North American EGA - true or false? If true, then the main cost increases will be the ships
that are either captive to the Great Lakes or FF ships that transit the Seaway. Thus, both
types of ships should be reviewed.
Hull
Clarify whether the Seaway between Montreal and the mouth of the mouth of the St
Lawrence River (a 500 mile long leg which exclusively runs through Canada), will require
100% MDO. I assume that this section of the River will continue to use HFO. Here is why:
Montreal aggressively competes with US East Coast Ports to handle imports/exports for
the US Midwest. Since the St Lawrence River downstream of Montreal runs exclusively
through Canada, the many miles of using 100% MDO would negatively impact Montreal's
competitive position - an undesirable result from a Canadian point of view. I encourage
you to address the issue and state what you feel is the most likely assumption, so that
readers can better understand the areas of impact of the C3 Ruling. (As a parenthetical
comment, both the Montreal and US East Coast port routes to Midwestern cities involve
overland, high emissions truck/rail legs. The lowest emission route is all-water through
the Seaway and the Great Lakes to Midwestern cities. Thus, it is important to protect the
all-water route).
B The emission inventories for Great Lakes Category 3 vessels are set out in Table 4-2 of Chapter 4. As explained in
Section 4.6, the estimated inventories do not include emissions from Jones Act vessels; when the inventories are
adjusted, Great Lakes inventories are about 3 percent of the national inventories for these pollutants.
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Commenter
Hull
Hull
Hull
Hull
Comment
Please state the jurisdiction of the C3 Rule more clearly. 1 assume that the C3 Rule legally
covers all ships travelling through or loading/unloading in US waters. If so, please state
that. Due to the more-than-a-dozen border crossings, 1 assume that it de facto covers all
ships travelling through Canadian waters in the Great Lakes as well. If so, please state
that too.
Explain how the US EPA standards can apply to the Canadian Great Lakes ships of Table 1-
3. 1 think that EPA standards would apply to US waters, and that EPA standards would be
applied to Canadian ships because of the many boundary crossings they must make.
Are the sulfur limits imposed on the Great Lakes/Seaway by EPA any stricter than those
planned by the Canadians, or those planned for the US East Coast ports? Do the sulfur
limits apply downstream of Montreal? What parts of the Lakes and St. Lawrence River are
impacted?
With only 8 Category Three US Flagged Vessels, 57 Category Three Canadian Flagged
Vessels, and numerous Category Three Foreign Flagged Vessels, the impact of the EPA
ruling will fall mainly on Canadian and Foreign Flagged ships. Will the Canadian and
Foreign Flagged ships require engine modifications too?
EPA Response:
The broad geographic area included in this study includes the five Great Lakes and the St.
Lawrence Seaway. As explained elsewhere in this report, the transportation mode shift analysis,
and therefore the actual area of shipping activity studied, is scenario specific. Sixteen O/D pairs
were selected; vessel operating costs were estimated based on currently-used HFO and EGA-
compliant distillate fuel. Then, freight rates were adjusted to reflect the increase in fuel
operating costs. Operating costs were estimated for the entire trip, and are based on the
assumption that the EGA fuel requirements are applied uniformly on the U.S. and Canadian sides
of the Great Lakes.
As a result, in some scenarios activity may be limited to a small portion of one of the Great
Lakes; for others, activity may reach from the western edges of the Great Lakes to the eastern
limit of the St. Lawrence Seaway. There are 3 scenarios that include extensive operation on the
St. Lawrence Seaway: Scenarios 6, 9, and 10. In addition, the supplemental analysis for the
steel sector contained in Section 3.2.4 of Chapter 3 discusses the impacts on a foreign vessel
transiting both the coastal and the Great Lakes St. Lawrence Seaway portions of the North
American EGA.
Pursuant to MARPOL Annex VI, the EGA fuel sulfur limits apply to any ship, regardless of flag
operating in a designated EGA. We clarify that these requirements apply to vessels operating in
U.S. internal waters, including the U.S. portions of the Great Lakes, through our recent
rulemaking under the Act to Prevent Pollution from Ships (see 40 CFR 1043). Therefore, the
EGA fuel requirements apply on all U.S. portions of the Great Lakes and St. Lawrence Seaway.
The Canadian program to implement the North American EGA is still under development. To
simplify the analysis, we apply the fuel operating costs associated with the EGA controls to the
Canadian side of the lakes for those scenarios that contain operation in areas under Canadian
jurisdiction. As a result, this approach is conservative. To the extent that Canada adopts a
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different approach with respect to the application of the EGA requirements to the Great Lakes,
ship owners may have more flexibility in their compliance strategies. They may be able to use a
combination of strategies that provide least-cost compliance with the fuel requirements on the
relevant parts of the Great Lakes St. Lawrence System. For example, if a ship installs an exhaust
gas cleaning system (scrubber) it may be possible to run it at different intensities on the U.S. and
Canadian sides of the lakes. Note that such an option may not be available for ships operating on
the St. Clair and Detroit Rivers between Lake Erie and Lake Huron due to the narrow shipping
channel on these rivers and the frequent cross-overs between U.S. and Canada. This would
require ships either to use compliant fuel for the entire length of that journey or leave any on/off
technology "on."
It is difficult to say whether the fuel sulfur requirements will fall mainly on Canadian and foreign
vessels. As explained in Chapter 1, while the Canadian fleet may be larger numerically than the
U.S. fleet, the U.S. fleet is larger in terms of total tonnage and it carries more cargo.
8A.3. Steamship Applicability
Commenter
Hull
Hull
Hull
Comment
With steam engines being excluded from the ruling, is it likely that they will be more
heavily used by ship owners so that they can avoid retrofitting Category Three vessels?
Please confirm that steamships are PERMANENTLY excluded from the ruling or list any
conditions attached.
Page 1-11:
Please reconcile the following two seemingly contradictory sentences:
1) "...we excluded Great lakes steamships from the EGA fuel sulfur requirements."
2) "..allows Great Lakes shippers to petition EPA for a temporary exemption from the
2015 fuel standards, which can encourage repowering steam engines to "
Are steamships excluded permanently from the sulfur standards, or only until 2015?
1 thought that steamships were permanently exempted from the ruling. The text indicates
that a fuel waiver is available only until January 2015. Which is true? Please clarify.
EPA Response:
These comments refer to different parts of our compliance program with respect to internal
waters (see 40 CFR 1043.95).
The special Great Lakes provisions contained in our Category 3 rule consists of three provisions:
the exclusion of Great Lakes steamships from the EGA fuel standards; a general fuel availability
waiver for to the 10,000 ppm fuel sulfur limit that is available for non-steamship Great Lakes
Category 3 ships, and an economic hardship waiver.
With regard to the steamship provision, Great Lakes steamships are excluded from the EGA fuel
standards. This exclusion is available for vessels propelled by steam turbine engines or
reciprocating steam engines, provided they were operated within the Great Lakes before October
30, 2009 and continue to operate exclusively within the Great Lakes. This exclusion does not
expire.
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Chapter 8: Peer Review
The fuel availability waiver applies to fuel meeting the 10,000 ppm fuel sulfur limit and is
available to Category 3 Great Lakes vessels that are not covered by the steamship exclusion.
The 10,000 ppm EGA fuel sulfur limit begins to apply on the Great Lakes when the North
American EGA goes into effect, in August 2012, and continues until the more stringent 1,000
ppm EGA fuel sulfur limit goes into effect January 1, 2015. The Great Lakes fuel waiver is
available if marine residual fuel meeting the 10,000 ppm sulfur limit is not available. Under this
provision, it will not be a violation of our standards for a Great Lakes vessel operator to purchase
and use marine residual fuel with sulfur content above 10,000 ppm provided the fuel purchased
is the lowest sulfur marine residual fuel available at the port. There are some reporting
requirements for this waiver.
With regard to the economic hardship waiver, this provision was included in the program to
provide Great Lakes shippers a temporary exemption from the 2015 fuel sulfur standards. This
waiver is not automatic; the ship owner must apply to EPA. As part of that application, the ship
owner must show that despite taking all reasonable business, technical, and economic steps to
comply with the fuel sulfur requirements, the burden of compliance costs would create a serious
economic hardship for the company. The Agency will evaluate each application on a case-by-
case basis, which must be submitted by January 1, 2014.
Finally, the ability of fleet owners to favor steamships over diesel ships depends mostly on how
steamships are currently used and whether they can be used more intensely. The impact of such
a change on freight rates, which is the focus of this study, is unclear. However, given the higher
fuel costs of steamships and their small share of Great Lakes cargo capacity (15 percent of the
number of vessels, 12.5 percent of tonnage; see Table 1-4 in Chapter 1) it is reasonable to ignore
these potential effects in this study.
8A.4. Fuel Availability and Fuel Price
Commenter
Comment
Hull
Do sufficient quantities of MDO exist to support the C3 ruling? I assume so, but did not
see this question addressed or analyzed in detail. This point should be cleared up to
further establish the feasibility of the C3 Rule.
Hull
Page 2-15: You quote that MDO is expected to be 45.5% more expensive than HFO. Is that
figure in $/ton for both MDO and HFO? How does the btu content of MDO compare with
HFO? What is the comparison in $/BTU? I would think that the cost per BTU would be a
more valid comparison of MDO and HFO.
Belzer
2-14: I wonder if they aren't using a per-barrel oil price that is too low to be "normal"?
Using the 2007 price has the disadvantage of capturing a non-random point in time rather
than a trend, and I would suggest an averaging or trend-based method across ten years or
so.
Kruse
I don't see where the document addresses the concern the shareholders expressed
regarding a potential spike in the price of the 0.1% sulfur fuel if there is a limited supply in
the Great Lakes region when implementation begins.
EPA Response:
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The availability of EGA-compliant marine fuel was discussed extensively in our Category 3
rulemaking and is not the subject of this study. See C3 Marine Diesel Rule, Final Regulatory
Impact Analysis, Chapter 5, Engineering Cost Estimates, Section 5.6.4.3.4 Overall Increases Due
to Fuel Switching and Desulfurization. See also the Summary and Analysis of Comments on the
C3 rule, Section 4.5, Fuel Availability.
The fuel prices used in this study are described in Section 2.5.3.1 and are based on 2007 fuel
prices reported by the U.S. Energy Information Administration (EIA) in the Annual Energy
Outlook (AE) for 2010. Fuel prices for 2007 are used rather than projected fuel prices because
freight rates are based in part on current fuel prices, not projected fuel prices for many years in
the future.0 These fuel prices are adjusted for the Great Lakes market (10 percent adjustment;
see Section 2.6.3). Using a price based on a trend (e.g., 2000-2007), as suggested by the peer
reviewer, would result in a lower price given the historic low price of UFO ($150-$175/ton for
2000-2005).
While fuel prices have increased over the last month or so due to instability in the Middle East,
these price increases are not incorporated in the study. This is because it is not possible to
anticipate any long-term market impacts particularly with regard to prices in 2015. In addition,
oil price increase will affect the price of MDO for both marine and the land-based alternative,
and therefore an increase in market prices is not expected to substantially affect the overall
findings of this study. The analysis is based on the price differential between HFO and MDO,
and historic price data suggest that the long-term differential between these fuels has been fairly
constant outside periods of market adjustment. Finally, as noted by Belzer, "As the price of oil
goes up, the greater efficiency of using the marine mode might provoke shift of freight to marine
over rail; this would happen at the extremes of price when the cost of fuel is so great that it
begins to trump the cost of intermodal handling needed to shift as much to marine as possible.
This, however, would not change the conclusions of the analysis because it would drive freight
toward, not away from the marine mode; it would not favor truck or even rail." In addition,
Belzer notes "as long as fuel prices rise, systematic shifts likely will favor maritime over rail and
rail over truck, so a low price probably leaves a very conservative result in this case."
c The prices for 2008 were not used due to the perturbations in the global fuel market that occurred in that year, and
data for 2009 were not available.
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8A.5. Scenario Selection
Commenter
Comment
Hull
Page 2-7: How did the EPA identify the stakeholders who provided the 50 O/D pairs? Who
were the stakeholders? How did you winnow the list down to the 16 winners? Please
provide a list of stakeholders either in the text or in an appendix. If the stakeholder list is
confidential, please characterize them to the extent reasonable. The readers would like to
know who was involved.
Belzer
2-7: As discussed above, this report does not clearly specify the basis on which the EPA
chose the sixteen routes among the fifty routes provided to them by stakeholders. Except
generally for an attempt to incorporate all four broad commodity groups, the basis for the
selection of these particular sixteen O/D pairs is never explained. The choices are not
random, which normally would be preferred.
EPA Response:
Section 2.4 of Chapter 2 of this report contains an expanded description of the method we used
to select the 16 O/D pairs included in the study. As noted in that section, we solicited input from
industry stakeholders both directly and through the primary trade organizations with respect to
shipping routes that are at risk for transportation mode shift as a result of the fuel requirements
contained in our Category 3 rule. We received suggestions for about 50 O/D pairs; we selected
16 and shared them with stakeholders asking them if they would like to replace any of the O/D
pairs with a different route. We received no adverse comments on our selection.
Chapter 2, Appendix 2B has been modified to include the list of stakeholders who attended the
June 10, 2010 EPA workshop. The invitation to that workshop was sent to a broad group
including environmental organizations, a variety of industry stakeholders, states and port
authorities, and individual citizens who had participated in our C3 rulemaking process. That list
is not confidential but is too lengthy to repeat here. However, all comments made on the C3 rule
are publically available at www.regulations.gov under Docket ID number EPA-HQ-OAR-2007-
0121.
These 16 O/D pairs are not a random selection of possible Great Lakes shipping routes or of the
50 suggested O/D pairs. They were selected from the set of about fifty at-risk routes based on
cargo type and geographic factors. As a result, these at-risk O/D pairs may not be typical and the
amount of cargo shipped to these destinations may be only a small portion of total Great Lakes
cargo in any one year. However, if fuel price increases of the magnitude expected from
switching to EGA-compliant fuel on the Great Lakes do not indicate a transportation mode shift
on these at-risk routes, where the price difference between the marine and the all-rail alternative
is close enough to be of concern to stakeholders, then transportation mode shift on other routes
without such price pressures would not likely be indicated. In his comments, Dr. Belzer notes
that "EPA selected these cases systematically in an attempt to fairly represent a cross-section of
trips about which the private sector was concerned. One might also be concerned, however, that
the EPA selected these cases systematically to identify O/D pairs that would least likely to
trigger the shifts. While the critique can be made, it is a thin reed because the results so strongly
refute the contention that transportation mode shift, source shift, and production shift would
occur from the higher fuel cost. The only case studied that might support this contention is the
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odd case in which coal travels almost as far on rail in the rail diversion case as in the default
case, and unique circumstances must allow this route choice in the first place."
8A.6. Transportation Mode Shift - Methodology; Validation
Commenter
Comment
Hull
If you proceed with this analysis I urge you to add a validation step in which you select
some of the sixteen origin/destination pairs, meet with the relevant stakeholder, and
delve into details of the actual movements.
Hull
Since the EERA model is theoretical and actual routes and rates may differ, I would
encourage a final validation of the model by selecting a subset of the sixteen scenarios
and interviewing shippers/carriers for their input and perspective.
Hull
In Scenario 2, were the mine and paper mill stakeholders approached to try to better
understand the situation? I think this might be a valuable way of validating the modeling
approach, since the modeling approach did not seem to work. I recommend that you get
into the details of Scenario 2 and talk with the shippers and carriers to find an
explanation. Without such explanation, the result casts doubt on the results of the other
Scenarios.
Hull
Scenario 2's Base Case looks crazy. I recommend that it be researched further. Why
would anyone use a ship in this case? Does the base case reflect an actual movement? Is
it possible that Georgia Pacific cant unload rail cars? Is the actual rail route the same as
the one that the model chose? Is there an equity ownership involved?
EPA Response:
EPA validated the scenarios by sharing all of the data inputs used in the transportation mode shift
analysis with stakeholders prior to performing the analysis described in Chapter 2. This includes
the description of the transportation routes for the ship route and the all-rail alternative; the
characteristics of the vessel carrying the cargo, and cargo transfer costs. All comments received
were used to adjust the scenarios. While EPA solicited input on actual industry freight rates,
stakeholders were unwilling to share this information with us as this is confidential business
information and because these rates may vary not only by route but by freight customer.
Therefore, while a validation exercise with actual using facilities might be interesting, the main
result of such a step would be simply to revise the characteristics of the scenarios.
The comments with respect to Scenario 2 are in reference to the results for that scenario as
reported in the contractor report contained in Appendix 2C, which suggest that the route-based
freight rate for the all rail alternative is less than both the Base Case or EGA Case freight rates.
The trade route that makes up Scenario 2 was recommended by a stakeholder who described it as
coal from South Chicago to Green Bay that originates as western bituminous coal from, for
example, Colorado. This stakeholder further specified that the coal is delivered to a paper mill in
Green Bay. At the time the scenario was defined, we did not have details about the specific
characteristics of the facility and we designed the route to be consistent with the other scenarios:
transportation of coal from the mine head to the using facility. The scenario as specified was
shared with all stakeholders and we received no adverse comment on its particulars.
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The contrary modeling results for this scenario reported in Appendix 2C led EPA to perform
additional research with regard to this facility. The information obtained by EPA indicates that,
due to quality specifications for the coal used by this facility, the western bituminous coal used
in this paper mill is blended with other coal to obtain the product needed.2'3 The blended coal is
frequently obtained from a source in South Chicago, where the KCBX Terminal can store up to
one million net tons of coal on site and can blend up to three coals for a customer.
Consequently, EPA believes this case was mis-specified.
We did not remodel this scenario based on a new definition of the route. We do not have the
information needed to remodel, particularly with regard to the relevant freight rates for the
Baseline Case and for the All-Rail Alternative. For example, Dr. Belzer noted that "[i]t is also
possible that the route through South Chicago is inexpensive because trains handle so much
volume from Elk Creek to South Chicago that the ton-mile cost is lower via that combined
rail/marine route than via the direct rail route." In addition, it is unclear how the scenario should
be modeled, to ensure consistency with the other scenarios. To be consistent, it would be
necessary to include transportation costs from the coal mine; however, it is not clear how this
could be done, particularly with respect to the cost of transporting coal from the terminal in
Chicago to the facility in Green Bay. Specifically, we do not have a mechanism to allocate the
transportation cost from the mine head(s) to the total route scenario. This question could be
important because this facility also receives coal by ship from Sandusky and Ashtabula, Ohio,
and vessels operating from those facilities are also required to use ECA-compliant fuel. For the
reasons stated here and in Chapter 2, it is not possible for this study to assess the potential for
transportation mode shift impacts for this route.
8A.7. Source Shift Analysis: Stone Scenarios
Commenter
Comment
Kruse
I have strong concerns about the methodology used for crushed stone. On page 3-3, the
next-to-last paragraph states "It also does not examine the reason why the purchasing
facility uses stone originating at a much longer distance, requiring ship transportation,
when stone from local quarries may be available." The existence of this situation in the
"real world" invalidates the methodology used in the document. Users are importing
stone from great distances for a reason. To simply expand the "competitive radius" as the
basis of the analysis ignores this consideration. If the stone is being imported from a
specific quarry, then the inclusion of quarries producing similar quality/grade stone needs
to be evaluated rather than just looking at quarries generically.
EPA Response:
EPA used the methodology used by the Canadian Shipowners' Association in their 2009 study
(see Section 1.6.3.2 in Chapter 1), which also does not consider the grade of stone at the different
quarries. See response under 8A.7.2 for more about stone quality.
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8.A.7.1 Qualitative Comparisons
Commenter Comment
Kruse
The conclusions were appropriate and justified, taking into account the data sources and
inputs employed for the analysis. There were just two instances, where I felt the
conclusions needed to be shored up. On pages 3-5 and 3-6 statements are made to the
effect that "the increase is not substantial compared to the number of quarries already
located within the radius." This is a subjective statement that needs to be validated with
numbers/data.
EPA Response:
The analysis is based on the change in the competitive radius around the stone using facility, and
considers the number of quarries within the original radius and a revised radius that reflects the
increase in ship transportation costs. There are two ways to evaluate the impacts of an increase
in the competitive radius. The first is to consider the number of additional quarries that are
included in the expanded radius. Referring to the maps in Chapter 3, it is clear that for Scenarios
13, 14, and 16, the number is small when compared to the number of quarries within the
distance. A count of the quarries for Scenario 15 reveals that approximately 2 more quarries are
added to the competitive radius, which is an addition of about 22 percent.
The second way to evaluate the impact of an increase in the competitive radius is to examine
increase in the distance from the using facility. We performed this analysis for the four stone
scenarios and added it to Chapter 3. For all four scenarios, this increase is very small, 11 miles
for Scenario 13, 10 miles for Scenario 14, 15 miles for Scenario 15, and 13 miles for Scenario
16. In fact, it is possible that quarries located within such a marginal extra distance can already
compete with the quarries within the base case competitive radius. For example, in Scenario 15
(stone to American Crystal Sugar Company, MN) about 2 additional quarries would be drawn
into the market. However, given the increase in round-trip distance of only 15 miles, those
quarries may be considered competitive with the existing quarries even without the increase in
ship freight rates. The additional 15 miles would increase the fuel costs per trip by about 3
percent, and total operating costs by about 1 percent. Averaged over miles in the original
competitive radius, the increase in fuel costs is about $0.06/gallon/trip, which is well within the
fluctuation of diesel fuel prices. Therefore, including these quarries in the revised competitive
radius does not significantly change the competitive nature of this market. Table 8A-1 presents
the results of this analysis for the other three stone scenarios, with similar results.
Table 8A-1 Stone Scenario; Fuel Costs Associated with Increase in Competitive Distance
Transport price 1 truckload
Fuel costs for 1 truckload
Increased mileage round trip
Additional fuel for longer trip (gal)
Increased fuel costs for longer trip
Increased in base fuel costs ($/gal)
% increase in fuel costs for longer trip
% increase in total costs for longer trip
Scenario 13
$468
$188
11
2.2
$4.50
$0.05
2.4%
1.0%
Scenario 14
$383
$154
10
2.0
$3.98
$0.05
2.6%
1.0%
Scenario 15
$518
$208
15
3.0
$6.05
$0.06
2.9%
1.2%
Scenario 16
$280
$113
13
2.7
$5.36
$0.10
4.8%
1.9%
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8.A.7.2 Data Assumptions
Commenter
Comment
Kruse
In Chapter 3, is the assumption of a truck load of 43 short tons valid if the quarry is
located in the United States?
Kruse
I have strong concerns about the methodology used for crushed stone. On page 3-3, the
next-to-last paragraph states "It also does not examine the reason why the purchasing
facility uses stone originating at a much longer distance, requiring ship transportation,
when stone from local quarries may be available." The existence of this situation in the
"real world" invalidates the methodology used in the document. Users are importing
stone from great distances for a reason. To simply expand the "competitive radius" as the
basis of the analysis ignores this consideration. If the stone is being imported from a
specific quarry, then the inclusion of quarries producing similar quality/grade stone needs
to be evaluated rather than just looking at quarries generically.
Hull
I felt the crushed stone analysis was quite good though it needs a review of its underlying
data sources.
Hull
Section 3.1: Source Shift (Crushed Stone): I assume that power plants run a combination
of trucked and ship/railed stone? Michigan's high calcium carbonate and low bond work
index seems to be valuable because of its chemical properties for use in scrubbers.
Further I assume that a ton of Michigan stone, because of its unique chemical properties,
must replace more than one ton of locally quarried stone. If this is true then we would
want to encourage the use of long distance Michigan stone to reduce the number of
truckloads of lower grade local stone.
Hull
Stone shift analysis is stated as problematic, even by the authors, due to factors not
included in the analysis. I happen to like the analysis a lot, but it makes several simplifying
assumptions which need to be examined and validated, such as the use of theoretical
transport costs from origin to destination, the assumption that highways are "straight
line", that Michigan specialty stone replaces local quarry stone on a ton for ton basis, and
that heavy trucks are allowed on US highways. These assumptions need to be reviewed,
but found the analysis otherwise very interesting.
Hull
The study states that the analysis is problematic because of factors not included, as listed
in the last paragraph on Page 3-8. Still further, the shift analysis hinges on theoretical
rail/water cost figures. Despite all that I think this is a very interesting approach.
EPA Response:
The discussion in the last paragraph on page 3-8 is a discussion of the Canadian Shipowners'
Study, not the EPA study. We corrected the text to clarify this.
We performed an analysis of the emissions impacts of the shift; see Section 3.3 of Chapter 3.
Dr. Hull is correct that the analysis relies on the rail/water freight rates reported in Chapter 2.
This is appropriate as the intent of the study was to estimate the impact on freight rates of an
increase in fuel costs associated with the application of the EGA on the Great Lakes.
To respond to the comments about truck size and distance to the quarry, we performed three
sensitivity analyses, with respect to the size of the truck load, the truck freight rate, and the truck
route. These results are reported in Table 3-4 of Chapter 3. This analysis shows that a smaller
delivery load (20 tons instead of 43 tons per truck), a more expensive truck freight rate ($20/ton),
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or a less direct route between a local quarry and the using facility (represented by an increase of
diversions along the truck route by 10 percent) all reduce the competitive radius around the using
facility. However, for each of the sensitivity analyses, the change in competitive radius remains
about the same, less than 10 miles, and is not large enough to change the competitive nature of
the relevant market.
EPA received comments during our rulemaking process that the quality of Michigan stone makes
it "attractive to power plants and manufacturers far inland as it contains a high percentage of
calcium carbonate (over 97 percent) that scrubs more SC>2 with less stone."0 However, we did
not conduct a sensitivity analysis with regard to additional tons needed to compensate for the
quality of stone, because the amount of additional tonnage is not known and may vary by
facility. It is possible that some power plants have choices in the quality of scrubber stone used
to achieve the required sulfur dioxide emissions limits. Customers choose stone based on many
factors, including the power demands on the pumping system of circulating the reagent slurry in
the correct ratio to the flue gas flow (need more power for higher liquid to gas ratio with lower
calcium content), as well as tolerances for variations in pH to minimize unacceptable scaling or
corrosion.
EPA assumed that all identified quarries within the selected competitive radius are potentially
equally competitive. The effect of considering only those quarries that can provide stone with a
given calcium content, for example, would be a decrease in the total number of truly competitive
quarries. It is beyond the scope of this analysis to investigate the tolerances of the using facilities
or the quality of limestone at each mapped quarry. Qualitatively, if the total number of truly
competitive quarries were reduced, then the number of additional quarries becoming competitive
due to the EGA fuel prices could be a higher proportion of the total.
8A.8. Air Emissions Comments
Commenter
Comment
Hull
Further, if a shift from rail/water to truck occurs, the emissions consequences of this shift
should be calculated and be included in the analysis.
Hull
If the Bruce Mansfield Power Station is expected to see a partial modal shift, we should
find out if the increased emissions of the additional trucks offset the emissions savings of
the C3 ruling. Also, if the Power Station is outfitted to unload cars with few emissions, a
conversion to truck may increase them. It wouldn't hurt to talk directly with the Station
about their supply sources to validate your analysis.
Hull
In the scenarios, does a switch from the Base Case Route to an All Rail route involve more
emissions at destination? That is, for example, does a power plant emit more when it
unloads rail cars or a ship? If this is true, is this factored in anywhere?
EPA Response:
EPA has estimated the emissions consequences of both a shift from the base water/rail route to
an all-truck route (Scenarios 13-16) and a shift to an all-rail route (Scenarios 1-5, 7-12).
Although the transportation analyses indicate that neither type of shift is likely, the potential
D See comments of the Great Lakes Maritime Task Force. EPA-HQ-OAR-2007-0121-0269. See also discussion in
Chapter 7 of this report, page 7-56.
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emissions impacts are described in Section 3.3 of the report. Further, Section 3.3 has been
revised to incorporate responses to the above comments.
As explained in Section 3.3, the emissions analysis does not include emissions from loading and
unloading operations. We focused on the transportation emissions from the main propulsion
engines. Consistent with the methodology of the transportation analyses, which excluded the
costs of the first loading at the origin and final unloading at the destination, the effects of those
initial and final transfers have been deemed outside the scope of this analysis.
To include all transfer emissions would entail quantifying not only the emissions from material
handling equipment operated at origin and destination, but also emissions at the intermediate
transfer points, the additional engine idling emissions as well as the fugitive dust PM emissions
during cargo transfer.
Looking at the scenarios, there were seven where the alternate case assumed the same mode as
the base case at the origin (first leg of journey was by rail for both cases); four scenarios where
the final leg of the journey used the same mode under the alternate case as the base case (product
delivered to end user by rail for both cases), and three scenarios where the intermediate number
of transfer points along the journey did not change with mode (uni-modal under base and
alternate cases).
As noted in Section 3.3.1, EPA does not have specific information indicating whether the land-
based material transfer emissions rates are greater or less than the vessel-based
loading/unloading emissions rates. For the scenarios where there is either a higher number of
intermediate transfer points under the base case, or an increase in use of land-based transfer
equipment as well as engine idling at either the origin or destination, or both, the total trip-based
emissions could either be greater or less when including all material handling emissions. If these
all-inclusive trip-based emissions were less under the alternate case, then this analysis may
understate the emissions benefits of any possible mode shift. If they were greater, then the
adverse emissions impacts of any mode shift, should it occur, may be underestimated.
One could also imagine that any increased truck or rail traffic could lead to more congestion-
related vehicle emissions, and that both a rail and a truck alternative could have the effect of
shifting the source of the emissions closer to some population centers.
Section 2.4.2.4 describes how we validated the stone scenario routes. Our sources indicate that
the sugar factory and one of the two power plants have rail access, and both power plants can
receive stone from river barges.
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8A.9. Production Shift: Electricity and Steel
8.A.9.1 Cost of Production
Commenter
Comment
Hull
Section 3.2: Production shift (Steel and Electric): Low cost steel and electricity producers
typically run at capacity, while high cost producers expand or contract their production to
meet the ups and downs of demand. By increasing the transportation cost of the inputs,
we put the Great Lakes producers into the higher cost category, and as such they may
lose production at times to the lower cost producers. This is probably a difficult concept
to quantify. The classic example of such a potential shift is the new Thyssen-Krupp steel
mill in Mobile. Thyssen has water access to the Midwest for its steel through the
Tennessee-Tombigbee Waterway, and would like compete with the Midwest producers.
As a new state of the art facility, they are high volume, low cost producer. Thus, perhaps
the Great Lakes producer does not go out of business, but he will likely lose some
business at the edge of his/her marketing area to companies such as Thyssen-Krupp
EPA Response:
As Dr. Hull notes, it would be difficult to quantify whether the additional transportation costs
would place Great Lakes steel producers into the higher cost category. This would likely require
an in-depth analysis of steel producing facilities near the Ohio and Mississippi rivers and
southern Ontario and Quebec. Nevertheless, it is unlikely that a production cost increase of the
magnitude expected by the application of the EGA requirement to the Great Lakes would put
Great Lakes steel producers in the high cost category. Although the freight rate in terms of cost
per cargo-ton is estimated to increase by up to 16.6 percent, it should be remembered that the
transportation of iron ore is only one input to the cost of making steel, and the impacts of the
increase in transportation costs in terms of steel industry revenues is estimated to be about 0.10
percent. As illustrated in Figure 3-4 of Chapter 3, steel price fluctuations have been larger than
the estimated increase for iron ore transportation costs.
8.A.9.2 Coal Movements for Electric Sector / Revenues
Commenter
Comment
Hull
Section 3.2.2: Impact on Great Lakes Sector: The Rosebud Mine is used for the lower and
upper bound scenario and applied to electrical generation for the entire Lakes region. This
is certainly a conservative assumption, since lots of the coal used does not even move by
water, and some electricity is not generated by hydroelectric rather than coal. You might
mention this in the text. Further in your analysis, you relate the transport cost increase to
reduced electricity revenues. How do you calculate this inverse relationship? Is it a price
elasticity argument?
EPA Response:
We made the notation in the text with respect to coal movement by rail and hydroelectric
generation.
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The analysis is not related to reduced electricity revenues. Rather, we attempt to put the increase
in transportation costs in context by comparing them to revenues in this sector. The increase in
freight rates for coal transportation is estimated to be about 0.5 percent, which is less than the
fluctuation in retail prices for electricity for the Great Lakes region, as illustrated in Table 3-5 of
Chapter 3.
8.A.9.3 Coal Transport Costs
Commenter
Comment
Hull
Your argument in the last paragraph of Page 3-10 is difficult to follow. Please explain more
fully how you separate the transport cost from the EIA figures. My understanding is that
you use average figure for mine costs in East North Central, and subtract it from the
"delivered coal cost." Also, once you have subtracted the transport component, you must
have to back out the percentage trucked and direct railed. Finally in using your baseline
case freight rate, you are using the Rosebud Mine as indicative of the Midwest industry. I
somehow am not understanding your argument or I am overthinking it. Please clarify for
me and for others. It would be helpful if you would add some columns to Table 3-4 so that
one could more easily follow your argument. Also, in the table you distinguish between
public utilities versus independent power generators - but you don't distinguish between
them in the text. Please expand this section
EPA Response:
We included additional explanatory text in Chapter 3 and revised Table 3-4.
The EIA regional data for the electricity sector reports only delivered coal cost; it does not
provide separate data for coal cost at the mine and coal shipping cost. Therefore, to perform this
analysis we used EIA reported 2008 U.S. national average coal cost at the mine to approximate
coal cost at the mine for the Great Lakes region. Using this method, shipping costs would be
about 39 percent to 45 percent of "delivered coal cost," and increasing in shipping costs by about
1.2 percent to 4.47 percent would be equivalent to increasing "delivered coal cost" by about 0.47
percent to 2 percent. It should be noted that this increase in "delivered coal cost" does not back
out the other transport component such as the percentage trucked and direct railed, since we do
not have this information.
8.A.9.4 Elasticity
Commenter
Comment
Hull
The argument is compelling but not complete in that you show that the MDO cost
increase is a small percentage of revenues. However, as a percent of transport cost it can
be between 8.5-16.6% for iron ore and 1.2-4.5% for coal. A company is quite capable of
changing their shipping decisions based on such percentage increases in cost (especially
for the iron ore percentages). A company's shipping decisions are typically designed
around minimizing manufacturing and transport costs. Revenues are calculated
separately. If a steel company has no choice it may have to pay the difference, but the
steel manufacturing decision may result in producing a bit less at the now-higher-cost
Great Lakes plant and more at another plant.
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EPA Response:
It is difficult to predict what a particular company would do in response to a freight rate increase
for iron ore or coal of the magnitude estimated by this study. As we illustrated in Chapter 3, the
impacts are expected to be small both in terms of industry revenues and historic price variations
for electricity and steel. In addition, while it may be the case that a company may change
shipping decisions based on increases in freight rates of this magnitude, there may also be many
reasons why such a change may not be feasible, including the use of established supply chains
and infrastructure, making it more reasonable for the company to pass on the costs instead of
incurring the costs associated with changing these established ways of doing business.
In addition, Dr. Belzer notes that "the small increased price for steel would be absorbed in down-
market competition, so you are correct to conclude that it's negligible. Commenting also on the
table, and repeating what has been said above, for all these commodities except perhaps stone,
the marginal increase in cost for the transportation service will be swamped by the rising costs of
the commodity globally."
8.A.9.5 Coal Movements for Steel
Commenter
Comment
Hull
My understanding is that Great Lakes coal movements are almost exclusively destined for
power plants and almost none is used in steel production (steel companies usually use
coke with is rail supplied). There are a few exceptions, like the Rouge steel plant in Detroit
which occasionally received a shipload of metallurgical coal, but there aren't many. Your
table in this section seems to indicate that Great Lakes ships DO consume coal delivered
by Great Lakes ships. This should be changed.
EPA Response:
We removed coal from the steel analysis.
8.A.9.6 Steel Raw Material Costs
Commenter
Kruse
Comment
What is the basis for the assumption that 80% of the delivered
ore cost at the mine"?
iron ore cost is the "iron
EPA Response:
Without having specific freight rate and cargo data from stakeholders it is difficult to say with
certainty what portion of the price of delivered ore is the cost of iron ore at the mine. However,
the USGS reports the value at the mine ($/metric ton) of iron ore in the United States has varied
between $37.92 and $70.43 for the years 2004 through 20074. Using our estimated base case
total freight rate, we estimate that shipping costs would vary between about 6 percent and 30
percent of the total price of iron ore. Therefore, 20 percent is a mid-range value. This is a
conservative estimate given the higher value of iron ore at the mine in recent years.
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8A.10. Production Shift: Supplemental Steel Analysis
8A.10.1 Quotas
Commenter
Kruse
Comment
Would steel import quotas
have an effect on this analysis?
If so, that should be analyzed.
EPA Response:
To the extent steel quotas keep steel prices - and therefore steel revenues - high, then the impact
of steel quotas on the analysis would result in the fuel cost increase being relatively smaller than
for a market with competitive steel prices. It should be noted, however, that the analysis takes
the market as given and does not try to separate out the impacts of steel quotas on the results.
8A. 10.2 Linear Flow Model
Commenter
Comment
Hull
I encourage the EPA to consider the following approach to the steel industry analysis:
develop a linear program that models the mills on the Great Lakes and elsewhere and
optimizes flows from mills to market. Next, perform a sensitivity analysis on the water
transport costs to determine the extent to which MDO usage shifts steel manufacturing
away from the Great Lakes to other steel centers. I am concerned that increased MDO
costs might result in global steel companies shifting production (to greater or lesser
degree) from Great Lakes mills to their other mills. With the depressed state of the "rust
belt" we don't want to lose any more jobs.
EPA Response:
This study was performed in response to comments on our Category 3 marine rule. As
summarized in Chapter 1 of this study and in the Summary and Analysis of Comments document
prepared for our final rule5, Great Lakes stakeholders expressed concern that the application of
the EGA fuel requirements to the Great Lakes would lead to transportation mode shift and result
in increased emissions in the Great Lakes region. Stakeholders were also concerned that an
increase in transportation costs would result in steel and electrical production moving out of the
Great Lakes region.
In support of our final rule we performed an analysis of the impact of increased transportation
costs associated with the EGA for steel that is manufactured in Indiana Harbor (IN) and for use
in Detroit (MI).6 With respect to steel, the increased cost for transporting iron ore and limestone
to Indiana Harbor was compared to steel imported from Europe. The analysis showed that the
additional fuel costs associated with using EGA-compliant fuel are smaller than the cost of
importing steel to Detroit, either through the St. Lawrence Seaway or by rail from an East Coast
port. Chapter 3 of this study expands on that analysis and shows the impact of higher fuel
operating costs associated with transporting iron ore in the Great Lakes using EGA compliant
fuel is small, about 0.1 percent of sector revenues. This is less than the annual fluctuation in
steel prices.
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We did not use a general equilibrium model in this analysis, or a linear flow mode. Available
general equilibrium models typically estimate impacts across an economy as a whole and are not
constructed in a way that would allow analysis of specific transportation links or examination of
the extent to which the raw materials and goods currently transported by one mode (ship) would
shift to another (rail or truck). It would also not be feasible to construct a model for the purpose
of this study as these models also require a great deal of data and information for potentially
hundreds of submarkets.
While a linear flow model would be more targeted to the steel industry, it would also require a
great deal of information about steel production and use through the Great Lakes region, the
relationship between producers of raw material inputs, steel producers, and steel user for the
entire country, as well as detailed information on exports and imports. However, given that
transportation costs for iron ore are only one part of the cost of iron ore, which is only one input
into the steel making process, we determined that developing a full-scale model of this economic
sector was not necessary, particularly given the small estimated impact on iron ore freight rates
(8.5% to 16.7%, depending on the scenario). This increase on its own is unlikely to cause steel
production to shift out of the Great Lakes region, especially given the cost of creating or
modifying steel production facilities in other locations (assuming there is enough excess capacity
available to cover all the steel production in one or all Great Lakes steel mills), the cost of
developing new supply chains and infrastructure, and the cost of transporting steel to
manufacturers in the Great Lakes region who use it as an input.
8A. 10.3 Consideration of Steel Coil/Grain Movements
Commenter
Comment
Hull
A further factor to include in your steel industry analysis: Steel imports from Northern
Europe to the Midwest are highly dependent on grain backhauls (steel ships need a grain
backhaul to justify the inbound steel movement). To the extent that MDO usage reduces
the availability of grain backhauls while simultaneously increasing the cost of steel
fronthauls, steel movements into the Great Lakes become less economic. Eliminating the
steel coil imports weakens the steel industry, because the European made steel coils are
purchased for specialty uses.
Hull
6. Impact of global marketplace is not included in the study, but should be included
because it is the "growth business" of the Seaway. The Great Lakes has a significant
quantity of captive business with iron ore, limestone, crushed stone, coal, and internal
grain movement. However, these businesses have been on the decline since before 1990,
and any growth for the Great Lakes/Seaway will necessarily come from increased
import/export. Currently grain is exported (significant quantities this fall!), and steel
coils/slabs have been imported for the past 50 years (using FedNav, Polsteam, and
Wagenborg - none of whom is included in the study). Further, moves are afoot to deliver
international containers to the Great Lakes (the Ports of Cleveland, Toledo,
Erie/Conneaut, Ashtabula are all studying this, and Great Lakes Feeder Lines, McKeil
Marine, and Wagenborg are interested carriers). Since this would create a significant
number of jobs in the depressed "rust belt" and since this business would take trucks off
the road, I believe that it should be included in the study. Here are three components that
should be included:
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Commenter
Comment
a. Grain from the Midwest is shipped abroad via three main routes - by ship through the
Great Lakes/St Lawrence, by rail to the US West Coast for loading to China, and by river
barge down the Mississippi for export from New Orleans. My understanding is that the
route chosen is highly dependent on transport rates, and small rate changes can have a
major impact on choice of route. Would a requirement to burn MDO both ways on the
2000+ mile journey have a significant negative impact on the amount of grain routed
through the Great Lakes? Page 7-26 of the study states that 70% of grain on the Great
Lakes is destined for export, so this is an important case to be considered in the body of
the report. Grain is an important export and should be explicitly analyzed.
b. Steel coils are imported into the Great Lakes in the following manner. A breakbulk ship
(typically FedNav, Polsteam, or Wagenborg) loads steel coils in Northern Europe for a
variety of Great Lakes customers. The ship then crosses the Atlantic and transits the
Seaway to discharge partial cargos at Cleveland, Detroit, and Burns Harbor. When
finished discharging, the ship picks up a grain backhaul and returns to Europe. Two issues
need to be addressed: i. If use of 100% MDO on the entire Great Lakes/Seaway route has
a significant negative impact on availability of grain backhauls, will steel coil imports
become uneconomic? ii. If the use of 100% MDO makes the (fronthaul) delivery of steel
coils through the Seaway less economic, steel coils will likely be diverted to the East Coast
ports for an overland rail/truck leg to Midwestern customers, (this is an alternative
Midwestern route used by steel companies) In this case, the system generates more
emissions from rail/truck. This alternate route is also considerably more expensive (that's
why the all-water route to the Midwest is preferred) which then reduces the viability of
the existing Midwestern steel companies.
Hull
I believe that you should include a category for imported steel coils/slabs in addition to
coal, iron ore, crushed rock, and grain, because there are an appreciable number of steel
coils imported into the Midwest from Northern Europe by ship. This would involve a
breakbulk ship delivering steel coils from Northern Europe to the steel companies in
Cleveland/Detroit/Burns Harbor, typically using a three port discharge, with a grain
backhaul. This breakbulk ship voyage should be compared with another similar voyage to
the East Coast for delivery to the same destinations by rail. Midwestern steel companies
use both routes. I am concerned that the need to utilize MDO for the entire Seaway
voyage will eliminate the Seaway route in favor of the water/rail route (which increases
emissions and cost).
Hull
I think the steel issue is one of extent, rather than one of relocating. A large, global steel
company faces a worldwide demand and meets it with least cost. Thus if one of the steel
mills owned by the global company experiences an increase in its transport cost to
market, that mill will manufacture less, and another lower cost steel mill located
elsewhere will manufacture more. Thus, a GL transport price increase would likely reduce
the shipments "somewhat" rather than result in an immediate relocation. The amount of
the reduction is often measured by a linear program.
Hull
FedNav (Canadian flag and FF ship operator), Polsteam (Polish flag), and Wagenborg
(Dutch flag) are breakbulk operators who operate a significant number of vessels between
the Great Lakes and abroad. FedNav also operates within the Great Lakes. FedNav, in
particular is a major ship operator headquartered in Montreal. They should be included
in Table 14 and in the analysis. These are "salties" that bring steel coils into the Seaway
and export grain.
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EPA Response:
This report was not intended to look at the impact of the application of the EGA program to the
steel industry; it was intended to look at the impacts of the program on Great Lakes shipping.
We looked at the four main cargoes transported on the Great Lakes: Iron ore, coal, crushed
stone, and grain.
We did not look at the impacts of this program on specific industrial sectors in the Great Lakes
region. Our analysis of production shift was intended to examine the fuel cost increase expected
from the application of the EGA to Great Lakes Shipping in comparison with total revenues for
specific sectors to explore whether these freight rate increases are large enough to have a
significant impact on the industrial sector, as measured by revenues. That analysis shows that
the expected transportation cost increase as a percent of sector revenues is within historic price
variations and therefore no production shift is indicated.
We also included a supplemental analysis with respect to imported steel because stakeholders
were concerned that the additional transportation costs on the Great Lakes would shift steel
production offshore. Our analysis shows this is unlikely because the increase in transportation
costs for steel inputs on the Great Lakes is less than the increase for transporting a ton of steel
through the North American EGA and Great Lakes St. Lawrence Seaway (see Table 3-7 of
Chapter 3).
This supplemental steel analysis only considers ship traffic in one direction and assumes that the
vessels will perform useful work on the return voyages (i.e., there is a backhaul; one peer
reviewer (Hull) indicated that the backhaul for steel coils is typically grain. If we were to
assume no backhaul for either the domestic or the imported steel case, this would increase the
estimated transportation costs but the increase would apply to both cases proportionally and
therefore no production shift would be expected. If we were to assume a backhaul for the
imported steel but no backhaul for the domestic steel, this would increase the estimated
transportation cost for the domestic case but a production shift would still not be expected. Since
the empty backhaul would consume less fuel (due to the lighter load), the transportation cost
increase for the round-trip domestic case would be less than double the one-way case and
therefore the price impacts for the domestic case still would be less than the imported steel case
with a backhaul.
While the analysis was not intended to examine the imported steel coil market specifically, it
suggests that even if the fuel costs for the entire EGA trip, inbound and outbound, were placed
on the imported steel, this would represent an increase of approximately 0.6 percent in the cost of
a ton of steel. This increase is still low compared to price fluctuations for the entire steel
industry. Also, because steel transportation costs are only one element of total input costs for
goods produced using steel, this is not likely to have a large impact on steel consumers,
especially those that use higher-priced specialty steel.
Finally, grain backhauls on these routes between North America and Europe are a discount on
shipping costs in that they allow the ship owner to generate revenue on the return voyage. These
grains backhauls to Europe are not expected to cease because these backhauls reduce the costs of
the return trip in that they generate revenue that an empty backhaul would not.
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8A. 10.4 Trans-Pacific Routes
Commenter
Comment
Hull
Page 3-15: The statement is made that a trip from Asia to LA can involve 1700 miles of
North American EGA transit. How can that be? I thought that the NA EGA extended to 200
miles offshore only. If such a route exists, is it likely that that captain would take it when
he can burn HFO for only 200 miles?
EPA Response:
While the Pacific region of the North American EGA is not the subject of this study, Figure 8A-1
illustrates the distance between Asia and Los Angeles through the EGA. Our Category 3 rule
contains a discussion of the routes taken by ships in this area, based on ship traffic densities (see
Chapter 3 of the RIA, Figure 3-3 and associated text).
Figure 8A-1 North American ECA Pacific Route
Source: EPA
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8A.10.5 Steel Costs
Commenter Comment
Hull
Page 3-17: Please check the fuel cost increased for the imported steel case. It seems to
me that if imported steel moves through the North American EGA, all the way (1500 miles
or so) down the St Lawrence and into the Great Lakes, that utilizing MDO at a 40% or so
premium above HFO would significantly increase the transport cost. However, the figures
on Table 3-7 do not reflect this, if true.
EPA Response:
The calculations contained in Table 3-7 are based on the fuel prices in the Category 3 rule RIA
(not the newer adjusted Great Lakes fuel prices) and are based on the following logic. The Great
Lakes Maritime Task Force indicates that a ship can move 607 ton miles per gallon of fuel.
Based on a density of 270 gallons per metric ton, this yields about 164,000 ton miles per metric
tonne of fuel. At a price increase of $322 per metric tonne, we get a baseline fuel cost of roughly
$0.0020 per ton-mile. A 40% increase on this is $0.0008 per ton-mile, which compares well with
$0.0009 per ton-mile contained in Table 3-7.
This calculation does not take into account differences in density and energy content of the two
fuels. When these are considered, the estimate decreases to about $0.0007 per ton-mile.
When the analysis is performed with the adjusted fuel prices for the Great Lakes ($424/tonne for
HFO and $617/tonne for distillate), this results in an estimated increase of $0.0010 per ton-mile.
In summary, the estimated cost increase in Table 3-7 is a little overstated because it did not
account for the differences in energy content between HFO and distillate fuel. However, using
the updated Great Lakes fuel costs, the estimated cost per ton-mile increases slightly compared
to what was reported in Table 3-7.
8A.11. Impacts of Fuel Sulfur Controls on Emerging Markets -
Containers
Commenter
Comment
Hull
In addition to the two pronged approach described above, I feel strongly that the EPA
should add a third prong: the impact of MDO usage on the potential all-water imports and
exports through the Great Lakes/St Lawrence - this is potentially a significant growth
industry for the Great Lakes.
Here is the business opportunity for Midwestern cities located near the Great Lakes: The
St Lawrence Seaway lies geographically on a straight line between the Midwest (large
consuming population and industrial heartland), and Rotterdam/Antwerp (two of the
largest world ports). This route has been cost effectively used by the steel industry for the
past 50 years for importing steel coils from Northern Europe, but it is rarely used for
general merchandise. (I will discuss the reasons with you if you wish) Based on the
minimum mileage character of this straight line and the low cost of all-water transport,
this route could benefit a host of imports/exports. As such, it is widely recognized as a
potential growth business. Great Lakes ports, shippers, and carriers are studying ways to
initiate service.
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Chapter 8: Peer Review
Commenter
Comment
This is a MAJOR OPPORTUNITY for the EPA to reduce emissions in the Midwest
and East Coast: As a large manufacturing and consuming region, the Midwest imports and
exports considerable quantities between Midwestern cities and Europe. The routes
currently used, though, require an overland leg by rail or truck (generating major
emissions) between the Midwest and either Montreal or US East Coast ports, and then a
waterborne leg between Montreal or East Coast ports and Rotterdam/Antwerp/Europe. If
imports/exports were channeled through the all-water route, we would reduce emissions
in the Midwest and East Coast, save transport costs, and take trucks off the roads. This
would have a significant positive impact both to the Great Lakes as well as the East Coast
environment. The Rhine River is an excellent example of such a working system, because
the Rhine handles much of Europe's commerce, reducing overland journeys through
Europe by truck and rail, and significantly reducing emissions throughout Europe.
Relevance to the current EPA study: Montreal successfully competes with the US East
Coast ports for deliveries to the Midwest, and approximately half of Montreal's imports
are destined for the US Midwest. Many Great Lakes ports, shippers and water carriers are
evaluating the all water service to Europe described above, (few such services exist and I
would be happy to discuss this further with you). Will the higher cost of MDO discourage
the development of these many opportunities, giving further advantage to the high
emissions overland routes to East Coast ports and Montreal?
In summary, with the internal Great Lakes industries in decline, we should encourage
growth of new business opportunities, such as import/export - especially since this
growth simultaneously cleans up the environment. The C3 study should address this topic.
Hull
The EERA study addresses the impact of 100% MDO on internal Great Lake
movements. With the Great Lakes industries on the decline, the study needs to
consider the global marketplace and present and potential import/export
opportunities, which is, after all the growth opportunity for Great Lakes as well as the rest
of the economy.
Hull
6. Impact of global marketplace is not included in the study, but should be included
because it is the "growth business" of the Seaway. The Great Lakes has a significant
quantity of captive business with iron ore, limestone, crushed stone, coal, and internal
grain movement. However, these businesses have been on the decline since before 1990,
and any growth for the Great Lakes/Seaway will necessarily come from increased
import/export. Currently grain is exported (significant quantities this fall!), and steel
coils/slabs have been imported for the past 50 years (using FedNav, Polsteam, and
Wagenborg - none of whom is included in the study). Further, moves are afoot to deliver
international containers to the Great Lakes (the Ports of Cleveland, Toledo,
Erie/Conneaut, Ashtabula are all studying this, and Great Lakes Feeder Lines, McKeil
Marine, and Wagenborg are interested carriers). Since this would create a significant
number of jobs in the depressed "rust belt" and since this business would take trucks off
the road, I believe that it should be included in the study. Here are three components that
should be included:
[Grain and steel coils; see response to Production Shift: Supplemental Analysis, above]
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Chapter 8: Peer Review
Commenter
Comment
c. Containers: Containerships transit the Seaway as far as Montreal. At that point, the
containers are transloaded to truck and rail for delivery to Canadian and US customers.
The truck/rail movements generate high emissions. My understanding is that
approximately half of the containers are delivered to the US. At present there are several
moves afoot to extend container deliveries into the Great Lakes by water, possibly directly
from Europe or by transloading containers to feeder ships or barges in Montreal or Halifax
(the Ports of Cleveland, Toledo, Erie/Conneaut, and Oswego are the interested ports and
Wagenborg, Great Lakes Feeder Lines, and McKeil Marine are interested carriers). Such a
service would reduce SOX, NOX, and particulate emissions because it would replace rail
and truck deliveries from Montreal and the East Coast. Would the 100% MDO ruling make
this opportunity uneconomic?
Belzer
1-4: I am skeptical that the Great Lakes waterways would be an economically acceptable
routing for intermodal short-sea container shipping. No container ships have been built
for the Great Lakes and they probably could not hold more than two hundred containers,
so this would only work for bulk shipments by container. No container ports exist on the
Great Lakes. Containers more likely will travel by rail.
Hull
I would like to ask the author a further question ... to deliver breakbulk material such as
steel (but of any type), what will be the increased cost of Seaway transit to cities such as
Cleveland, Toledo, Detroit, and Burns Harbor. I believe that this question is quite
important, specifically because there are many attempts to deliver international
containers directly into the Great Lakes ports from Europe, rather than delivering them
through New York/Phila/Baltimore with an overland freight leg. I am concerned that a
large marine fuel cost increase on the Seaway might delay this shift to waterborne
deliveries, and would like to understand the potential incremental cost per ton of cargo.
Hull
The study only includes the 16 identified captive Great Lakes cases, but does not include
import/export along the Seaway.
EPA Response:
Two peer reviewers, Hull and Belzer, commented on the impacts of the EGA fuel controls on the
emerging market of container shipping on the Great Lakes. Dr. Hull raises concerns about the
impact of the EGA fuel sulfur limits on the potential for container shipping in the Great Lakes
region. He notes that not only will this emerging market provide important economic
opportunities for the region, but it will also help reduce air emissions by using more efficient
ship transportation. Dr. Belzer, on the other hand, is less optimistic about the future for container
shipping on the Great Lakes. He is skeptical, he notes, because "no container ships have been
built for the Great Lakes and they probably could not hold more than two hundred containers, so this
would only work for bulk shipments by container. No container ports exist on the Great Lakes.
Containers more likely will travel by rail."
Taken together, these two comments illustrate why it would not be possible for EPA to perform
analysis on this market sector that does not currently exist.
The Great Lakes container market, both direct container shipments from Europe and short-sea
container shipments from East Coast ports, has been the subject of analysis since the 1970s.
While there had been container traffic on the Great Lakes in the earlier part of the 1970s,
changes in container ship sizes subsequently made them unable to access the Great Lakes. As a
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Chapter 8: Peer Review
result, containers enter the United States through East Coast ports and are transported to the
Great Lakes region via rail.
More recent analysis of the container market suggests that there are important constraints that
would need to be resolved for the Great Lakes container market to resume. Constraints raised
most recently by stakeholders at a meeting held by MARAD in the context of their Ship
Revitalization StudyE include the seasonality limits of Great Lakes shipping, lack of port
infrastructure, ship loading restrictions due to lack of dredging in key areas, bottlenecks at locks
and rivers, lack of attention to the shipping transportation network by state transportation boards,
and the competitive advantage given to railroads through various subsidies. These are all serious
infrastructure limitations that are unaffected by ship fuel costs. Other stakeholders noted that it
is quicker to transport containers by rail from East Coast ports than it would be for containers to
go through the St. Lawrence Seaway to the Great Lake ports and therefore the Great Lakes St.
Lawrence Seaway route may be efficient only to the extent that there are bottlenecks at East
Coast ports or for containers that are oversized or overweight.
In summary, there are serious infrastructure constraints for container shipping on the Great
Lakes, and it is unlikely that applying the EGA fuel sulfur limits to the Great Lakes will affect
the impacts of those constraints.
Finally, it should be noted that the fuel sulfur limit for distillate fuel sold for use in locomotive
engines and in marine engines with per cylinder displacement less than 30 liters was reduced to
500 ppm in 2007, with a further reduction to 15 ppm to be phased in by 2014. Thus, these
alternative transportation modes must use fuel that is much more environmentally protective than
the fuel used by Category 3 vessels.
8A.12. Other Comments
8A.12.1 Grain Exports
Commenter Comment
Hull
70% of grain on the Great Lakes is destined for export, so this is an important case to be
considered in the body of the report
Grain exports: Grain from the Midwest gets exported either through the Great Lakes, the
Mississippi River, or the West Coast depending on market prices and transport cost.
Adding cost to Great Lakes route will tilt the flow toward the other two routes to a
degree. Can you quantify this? How much additional cost will be added and/or how
much MDO versus HFO will be burned on the inbound and outbound voyages? (with 70%
of grain on the Great Lakes destined for export, this is an important case)
EPA Response:
As noted in our response for the supplemental steel analysis, this report was not intended to look
at the impact of the application of the EGA program to the grain industry, including exports. It
E Meeting held in Cleveland, Ohio, on February 15, 2011. More information about the MARAD Ship Revitalization
Study can be found at http://gcaptain.com/great-lakes-shipping-revitalization719640.
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Chapter 8: Peer Review
was intended to look at the impacts of the program on Great Lakes shipping. We looked at the
four main cargoes transported on the Great Lakes: Iron ore, coal, crushed stone, and grain. With
respect to grain, we considered grain transported from western locations on the Great Lakes to
users on the Great Lakes (Scenarios 11 and 12), and to Baie Comeau where it is stored in silos
awaiting export.
Our response for the supplemental steel analysis discusses the implications of the program for
grain backhauls associated with steel coil imports. See response in section 8A.10.3, above.
8A.12.2 Retrofitting
Commenter
Comment
Hull
With Category Three US Flagged Vessels using HFO, all will require retrofitting. Is the
technology available currently to allow a changeover? The information on Page 13
indicates that the US Flagged vessels are quite large, so can the changeover present a
problem?
In the majority of vessels which operate on residual fuel, marine distillate fuel is still used for
operation during routine maintenance, prior to and immediately after engine shut-down, or in
emergencies. Certain changes will need to be made to the engine's fuel system with respect to
injectors, fuel pumps, and fuel lines. Chapter 4 of Regulatory Impact Analysis prepared for our
Category 3 marine diesel rule contains a discussion of the changes that may be needed.
8A.12.3 Stakeholder Participation
Commenter
Hull
Comment
Algoma Central and CSL Group are the Canadian Flag operators who have the lions share
of Category Three ships. Have they issued a position to the study?
EPA Response:
All stakeholders were invited to participate in the development of this study. The Canadian
Shipowners' Association was involved in all steps of this study. However, neither Algoma
Central nor CSL Group commented directly on our Category 3 marine rule or directly
participated in this analysis.
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Chapter 8: Peer Review
Chapter 8 References
1 Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at or above 30 Liters
per Cylinder - Information in Support of Applying Emission Control Area (EGA) Requirements to the Great Lakes
Region. EPA-HQ-OAR-2007-0586. December 15, 2009.
2 Power Magazine, "Burning PRB Coal," October 2003, explaining why coal blending is necessary for many
existing boilers, available at http://www.prbcoals.com/pdf/PRBCoalInformation/Power-Oct03-PRBCoal.pdf.
3 Telephone call between L. Steele of EPAandK. Graves of Georgia-Pacific, May 12, 2011, concerning coal
sourcing activities.
4 See http://minerals.usgs.gov/minerals/pubs/commodity/iron_ore/myb 1 -2008-feore.pdf
5 EPA (December, 2009) Summary and Analysis of Comments: Control of Emissions from New Marine
Compression-Ignition Engines at or Above 30 Liters per Cylinder. Chapter 10. EPA420-R-01-019 A copy of this
document can be found at http://www.epa.gov/otaq/regs/nonroad/marine/ci/420r09015.pdf
6 Samulski, Michael. Control of Emissions from New Marine Compression-Ignition Engines at or above 30 Liters
per Cylinder - Information in Support of Applying Emission Control Area (EGA) Requirements to the Great Lakes
Region. EPA-HQ-OAR-2007-0586. December 15, 2009.
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EERA Responses to Peer Review Comments on 'Economic Impacts of
the Category 3 Marine Rule on Great Lakes Shipping'
In this appendix, EPA's contractor, Energy and Environmental Research Associates,
LLC, provides responses to the substantive comments offered by reviewers. In addition, their
final contract report, included as Appendix 2C to this report, has been revised in response to
comments.
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EERA's Response to Reviewers' Comments on Appendix 2A: Analysis of Impacts of
Category 3 Marine Rule on Great Lakes Shipping
6 April 2011
Comment 1
Summarized Comment:
In four scenarios, there is no all-rail alternative considered, but the document does not explain why at
this point. In the results section, the document states, "It was determined that xxxx is not serviceable by
rail. Therefore an All-Rail Alternative Route does not exist". The justification needs to be included on
pages 53, 55, 57, and 59 as well. (Kruse)
Contractor Response:
Language indicating why a no-rail alternative exists for Scenarios 6, 13, 14, 15, and 16 has been added to
the appropriate sections under Chapter 4: Scenario Description and Input Assumptions. Generally, the
language states that, "After reviewing the rail network in the GIFT model and through discussions with
stakeholders and experts, it was determined that no rail service exists at [appropriate origin of the
route]; therefore, no All Rail Alternative Route exists."
Comment 2
Summarized Comment:
How did EPA (or its contractor) derive the assumed propulsion powers? (Kruse)
Contractor Response:
We have added language under Vessel Main Engine Horsepower to reinforce that our choices for main
engine horsepower values were made after considering hp values for actual Great Lakes ships of 1000,
770, and 625 foot vessels carrying coal, iron ore, grain, and stone.
Comment 3
Summarized Comment:
What is the basis or source for the statement on engine specific fuel oil consumption?(Kruse)
How were fuel consumption rates calculated for the ships? (Hull 18)
Contractor Response:
We added language under Vessel Main Engine Specific Fuel Oil Consumption in order to clarify how main
engine specific fuel oil consumption was chosen for each vessel modeled.
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Comment 4
Summarized Comment:
The current Great Lakes basin profile is for 2008. Table 13 should be updated. (Kruse 25)
Contractor Response:
We have updated Table 13 to reflect the 2008 Great Lakes Basin Profile. We found that only Iron
ore/Steel Products changed substantially. Coal had no change.
Comment 5
Summarized Comment:
The sources should be stated for the following assumptions used to develop Table 16: Auxiliary Engine
power, Auxiliary Engine Load Factor in Port, and Rail Energy Intensity. (Kruse 25)
Contractor Response:
We have included Footnote F from page 3-22 of the main EPA report as a note under Table 16 to
indicate the source of the rail energy intensity variable. We have also added the Auxiliary Engine
Horsepower and Load Factor section under Description of Input Assumption Sources to address auxiliary
engine power and auxiliary engine load factor in port.
Comment 6
Summarized Comment:
Why is it assumed that the vessel will be loaded to 85% of its capacity? Since this assumption directly
affects the unit freight cost, it is important to justify it. (Kruse)
Contractor Response:
We have added language to the Assumed Cargo Load section of the report expanding our explanation of
why we chose a maximum assumed cargo load of 85%.
Comment 7
Summarized Comment:
The Corps' Port and Waterway Facilities data were used to obtain the depth of each port. I don't know
about the Great Lakes, but for the Inland Waterway System, these data are highly unreliable. Again,
since available depth directly affects the unit freight cost, I would suggest some kind of "truthing" of
these depths. (Kruse)
Contractor Response:
We added language under Port Depth Limit to clarify that the USAGE data is modified by observed vessel
drafts and therefore are "ground-truthed."
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Comments
Summarized Comment:
According to what the document says on 2A-16 and what the carriers state, vessels that carry iron ore
can also carry grain. (Kruse)
Contractor Response:
We have added language to Bulk Cargo Capacity and Nature of Backhauls in Great Lakes Freight
Transportation to clarify that the Canadian-flagged grain vessels sometimes backhaul iron ore.
Comment 9
Summarized Comment:
In the body of the text please distinguish between "rates" and "costs." (Hull)
Contractor Response:
We took care to standardize our terminology and edited the Calculating the Total Route Costs for the
All-Rail Alternative Route to read Calculating the Total Route Freight Rate for the All-Rail Alternative
Route. We similarly edited the title and variable descriptions of Equation 11 and changed one column in
Table 76 and Table 78 from "All-Rail Scenario Rail Rate" to "All-Rail Scenario Rail Freight Rate." Lastly,
the column headings and title of Table 77 have been completely re-worked for consistency.
Comment 10
Summarized Comment:
Are the underlying rates/costs provided by Dager rates or are they costs? Please explain what you mean
by freight rates. I think that you are building up the ship, rail and handling costs and adding some
percentage of profit. Is this true? If the analysis is based on value of service, how is this estimated (rail
and ship rates are contractual and not published) and what is the information source? Railroads set their
rates based on negotiations, using "differential pricing" or a "value of service approach." Their freight
rates often differ widely from their costs. Rates would be more accurate but extremely difficult to
accomplish with accuracy. Much better definition of his data set is required. Your analysis expects the
reader to accept the rail rates you are publishing - so you need to provide backup as to how you arrived
at them. (Hull)
Contractor Response:
In order to clarify that the freight rates used in the report for rail and ship are indeed rates and not
costs, we have added two new sections (Marine Vessel Freight Rate and Rail Freight Rate) to the report
under Description of Input Assumptions Sources. These sections describe in detail how marine vessel
and rail freight rates were estimated. We also added language to Total Transfer Costs for Default
Scenario Route to better explain how intermodal transfer costs were estimated.
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Comment 11
Summarized Comment:
Other parts of the report state that there are 12 Category Three US Flag Ships, as opposed to the 8
referred to on this page. My understanding is that there are 12. (Hull)
Contractor Response:
We have confirmed that there are indeed 12 US-flag C3 vessels operating on the Great Lakes. We found
that two steamships and one C2 vessel were repowered with C3 engines. Also, one C3 US-flag vessel
and one US-flag steamship were previously unreported. We have updated Chapter 2: Great Lakes Vessel
Fleet Characterization and Table 1 to reflect this change as shown below. We have also edited Tables 2,
3, 4, 5, 6, 7, 9, 10, 12, and 14 since they are affected by changes in the number of Category 3 and
Category 2 US-flag vessels.
Comment 12
Summarized Comment:
The study refers to cost function modeling (which is cost-of-service, as opposed to value-of-service).
Does the analysis strictly compare costs of two alternatives or does it compare rates? If the analysis is
cost of service, what component costs are included and what was the source of the information? All
cost components should be explicitly enumerated in the text. For Great Lakes ships, if the study includes
cost-of-service, it should include the cost of laying the ships up during winter, which will increase their
costs. It must also include factors such as tug costs which will be required to position ships alongside
docks, lock fees, pilotage fees which can be quite high, etc. (Hull)
Contractor Response:
The cost-function that is referred to in the report is an activity-based fuel cost model that we use to
calculate the incremental freight rate increase from the Base Case to the MDO case due to the use of
EGA-compliant fuel (i.e. MDO). Our analysis compares the total freight rates of the MDO Case to those
of the All-Rail Alternative Route. These rates include marine vessel freight rates, cargo transfer costs,
and rail freight rates as discussed in our response to Comment 10. A complete description of how we
calculate MDO Case freight rate is presented in Chapter 3: Methodology in Appendix 2A of the EPA
report.
Comment 13
Summarized Comment:
The reference in Chapter 2 to the assumption of no backhauls in the study is not prominent enough. The
commenters were unclear about this assumption. (Hull & Belzer)
Contractor Response:
We have added language under Nature of Backhauls in Great Lakes Freight Transportation to address
this comment and clarify why we chose to assume no backhauls.
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Comment 14
Summarized Comment:
Most of the cases modeled involve US Port/US Port movement. These require US Flagged vessels which
are large. Does the ship analysis in this study account for this fact, or is it using generic Category Three
ship figures? (Hull)
Contractor Response:
We want to clarify that the vessels used in the analysis are based upon the characteristics of the Great
Lakes Vessel fleet but do not represent a particular vessel. Rather, the vessels modeled are considered
to be a representative vessel of a length, cargo capacity, and power that could transport the specified
commodity along each route examined in the report. We have added language to Vessel Length in order
to address this comment.
Comment 15
Summarized Comment:
It would be wise to verify that the Algoma facility included in the analysis does have the facility to
receive iron ore by rail. Regarding the CSA study, "The authors specify that iron ore and coal were not
examined because for infrastructure and other reasons they are not vulnerable.. . the steel mills
examined do not have rail alternatives." (report p 1-22/1-23) (Kruse)
Contractor Response:
The Geospatial Intermodal Freight Transport (GIFT) model was used in our analysis. This model uses
geographic information system (GIS) data from Transport Canada for the location of Canadian rail lines.
The geospatial location of the Algoma facility suggests that there is a possibility for a rail connection.
Additionally, we verified the existence of rail lines in close proximity to the Algoma facility using Google
Earth. Therefore, Scenario 5 in the analysis provides a comparison of the total freight rate comparison
between the Default Scenario Route and an All-Rail Alternative Route that we believe is plausible.
Comment 16
Summarized Comment:
Please confirm that there is a rail ferry across the St. Lawrence River to Baie Comeau, QC. I have never
heard of such! What are the sensitivities considered? (Hull)
Contractor Response:
There is a rail ferry that links Baie Comeau, QC to Matane, QC across the St. Lawrence River. The ferry
has a capacity of twenty-six 50 foot rail cars. The name of the ferry is the Georges-Alexandre-Lebel Rail
Ferry. The source of these data is the City of Baie Comeau, QC website available at:
http://www.ville.baie-comeau.qc.ca/en/investing/services/rail-port complex/
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Comment 17
Summarized Comment:
Please check the rail routes for feasibility: are they heavily travelled trunkline routes, and do they
involve multiple railroads? Railroads often don't use the shortest route. Railroads try to shift traffic to
their most heavily used lines for economies of scale, density, and service. The rate and route also
depends on how many railroads are involved and their individual routes - railroads all want to achieve
long haul economics and may avoid a least cost routing that might extend over multiple railroads. A
route with more than two carriers is rare. (Hull)
Contractor Response:
The GIFT model is a GIS-based tool developed by the Rochester Institute of Technology and the
University of Delaware that combines the US and Canadian road, rail, and water transportation
networks to create an intermodal network. GIFT is an optimization model and can solve a route from
origin to destination based on user-defined objectives including least-time, least distance, least-
economic cost, least-CO2, least PM10, etc. For the all-rail alternative routes, we solved for the "least-
distance" while staying on active rail lines (mainly Class I rail lines). In our analysis, we calculated the all-
rail alternative route freight rate by multiplying the total distance (in miles) by the per-mile freight rate
($/mi). Our analysis cannot ensure that only one rail company was used. However, our analysis gives
the least possible distance from origin to destination along active rail lines. For our purposes, the least-
distance all-rail route is also the least expensive. If we had focused on using only one or two rail
companies, the route may have been longer, resulting in an increased total freight rate.
To address Dr. Hull's comment directly, the question about heavily travelled trunkline routes is
interesting but was (a) not contained within the scope of our study and (b) not necessary in the analysis
of the least-distance route. We did not come across data about travel frequency along these trunkline
routes. We are aware that the Class I railroads have shared agreements for segments of the national
railway network and we understand that Class I rail operators may dominantly operate its own
equipment on other sections of the network; there may be a number of rail line owners represented
along our route.
Additional EPA Comment
Please provide a description of the GIFT model to be included in Chapter 2 of the EPA report and
Appendix 2A.
Contractor Response:
We provide the following description of the GIFT model and how it is used in the report and have
included it in the Introduction section of Appendix 2A of the EPA report:
This study uses the Geospatial Intermodal Freight Transport (GIFT) model, discussed in detail in
Winebrake et al. (2008) and Comer et al. (2010), to display maps of the Default Scenario Route and All-
Rail Alternative Route. Additionally, the GIFT model is used to calculate the distance (in miles) from
origin to destination for the All-Rail Alternative Route as well as the distance traveled by rail for the rail
portion of the Default Scenario Route, if any, by solving for the "least-distance" route along active rail
lines. The GIFT model is a GIS-based tool developed by the Rochester Institute of Technology and the
University of Delaware that combines the US and Canadian road, rail, and water transportation
networks through intermodal transfer facilities to create an intermodal network. The GIFT model can
solve a route from origin to destination based on user-defined objectives including least-time, least
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distance, least-economic cost, least-energy, and least-emissions (including carbon dioxide [CO2], carbon
monoxide [CO], oxides of nitrogen [NOX], sulfur oxides [SOX], particulate matter [PM10], and volatile
organic compounds [VOCs]). For this study, we utilize GIFT'S visualization and least-distance
optimization capabilities.
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Peer Review of EPA's 'Economic Impacts of the Category 3 Marine
Rule on Great Lakes Shipping' Study
8-31
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Peer Review of EPA's "Economic
Impacts of the Category 3 Marine
Rule on Great Lakes Shipping" Study
Work Assignment 3-05
(RTI 005)
Technical Memorandum
Prepared for
Lauren Steele
U.S. Environmental Protection Agency
Office of Transportation and Air Quality
2000 Traverwood Dr.
Ann Arbor, Ml 48105
Prepared by
Alex Rogozhin
RTI International
3040 Cornwallis Road
Research Triangle Park, NC 27709
EPA Contract Number EP-C-08-008
RTI Project Number 0211577.004.005
January 2011
-------
Technical Memorandum on Peer Review of EPA's "Economic
Impacts of the Category 3 Marine Rule on Great Lakes
Shipping" Study
Table of Contents
Contents Page
Background 1
Description of the Peer-Review Process 2-3
Summary of the Peer-Review Comments 3-10
Appendix A: Resumes of Selected Reviewers A1-A16
Appendix B: Charge Questions B1-B2
Appendix C: Questions and Answers Provided During the Review Process... C1-C6
Appendix D: Cover Letters D1-D4
Appendix E: Review Reports E1-E28
Appendix F: Additional Documents Provided to the Reviewers F1-F20
-------
RTI
INTERNATIONAL
Memorandum
TO: Lauren Steele, (Environmental Engineer) U.S. Environmental Protection Agency,
Office of Transportation and Air Quality (OTAQ)
FROM: Alex Rogozhin, RTI International.
DATE: January 28, 2011.
SUBJECT: Peer-Review of EPA's "Economic Impacts of the Category 3 Marine Rule on
Great Lakes Shipping" Study
1. Background
The U.S. Environmental Protection Agency's (EPA's) Office of Transportation and Air
Quality recently finalized regulations addressing emissions from Category 3 marine diesel
engines and their fuels (the C3 Marine Rule, 83 FR 22896, April 30, 2010). That rule contains
EPA's coordinated strategy to address these emissions through a combination of national and
international actions. As EPA developed the C3 Marine Rule, stakeholders from the Great Lakes
shipping industry expressed their concerns that the proposed program, particularly the fuel sulfur
limits, would lead to higher operating costs for ships operating on the Great Lakes. They further
commented that this would lead to a transportation mode shift away from ships and toward
trucks or rail, with concerns that the result could actually be an increase in emissionsthe
opposite of what EPA sought to accomplish. They also indicated that the increased operating
costs could lead to a source shift for the crushed stone market and a production shift for steel
manufacturing, which would also adversely affect Great Lakes shipping.
EPA did not change its final rule with regard to applying the C3 marine engine standards
and fuel sulfur limits to the Great Lakes. In response to the comments, EPA performed an
analysis of the economic impact of the C3 Marine Rule on Great Lakes shipping ("Economic
Impacts of the Category 3 Marine Rule on Great Lakes Shipping," called "the EPA Report").
The EPA Report includes an analysis of transportation mode shift analysis, performed by ICF
International and Energy and Environmental Research Associates, LLC (EERA), and source
shift and production shift analyses performed by EPA. EPA submitted the Report for peer
review, seeking the reviewers' expert opinion on the methodologies employed and analyses
presented in the report and whether the impacts and effects described reflect a solid
understanding of the effects of the C3 Marine Rule on Great Lakes shipping. RTI International
facilitated this peer review, and this memorandum contains a summary of the peer review results
as well as documentation of the peer-review process.
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2. Description of the Peer-Review Process
EPA's Office of Transportation and Air Quality contacted RTI in October 2010 to
facilitate the peer review of the EPA Report titled "Economic Impacts of the Category 3 Marine
Rule on Great Lakes Shipping." EPA provided RTI a non-comprehensive list of subject matter
experts from academia and the public sector (Appendix A of the performance work statement,
WA 2-05), and this served as a starting point from which RTI assembled the list of subject matter
experts. Even though EPA provided a non-comprehensive list of subject matter experts, the final
list of 16 potential reviewers was compiled by RTI without consultation with EPA. To ensure
that the work would be completed in a timely manner, RTI contacted the potential reviewers
within a week of submitting the work plan and determined whether each expert would be able to
review the study during the period of performance. RTI selected three independent (as defined
in Sections 1.2.6 and 1.2.7 of EPA's Peer Review Handbook) subject matter experts based on the
following criteria in order of importance: 1) expertise in subject matter, 2) diversity of
backgrounds of the reviewers as a group, and 3) availability to perform the review in the
stipulated time frame. When one of the initially selected reviewers later declined to participate,
RTI selected an alternate reviewer from the list of 16 potential subject matter experts. To make
the review process as credible as possible, RTI did not consult EPA in selecting the final
reviewers.
The selected reviewers possess a range of expertise in maritime operations, transportation
planning and logistics, economic analysis, environmental issues, and the effect of transportation
on economic development. Appendix A of this technical memorandum provides the resumes
obtained from the selected reviewers. The selected reviewers have sufficient knowledge in: 1)
economics, 2) water transportation, 3) transportation logistics, and 4) regulation analysis to
evaluate the three methodologies (mode-shift analysis, source shift analysis, and production shift
analysis) used in the EPA Report.
RTI provided each of the reviewers with a copy of the EPA Report. The reviewers were
also given a set of charge questions prepared by the EPA as well as several supporting
documents (the list of additional documents provided to the reviewers is available in Appendix
F). The note along with the set of charge questions sent from RTI to the reviewers is included in
Appendix B of this memorandum.
After 3 weeks of the review process, a telephone conference call was organized between
EPA, the reviewers, and RTI. The purpose of the telephone conference was to provide an
opportunity for the reviewers to discuss any questions or concerns regarding the review material
and the expected deliverables. Some of the questions addressed in this process are included in
Appendix C of this memorandum. Additionally, one of the reviewers had further questions
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regarding the study. A second telephone conference was held between EPA, the reviewer, and
RTI with the purpose to address those questions. The telephone conference was documented,
and the log of the conference was later shared with the other reviewers. The log of the second
conference call is included in Appendix C.
RTI received the review reports from the reviewers and forwarded the reports to EPA by
the requested date. The review reports included the responses to the charge questions and any
additional comments or recommendations. From each reviewer, RTI obtained a cover letter that
stated the reviewer's name, the name and address of his/her organization, the documents that
were received and reviewed by the reviewer, and a statement of any real or perceived conflict(s)
of interest. These cover letters and the review reports are included in Appendices D and E of this
memorandum.
3. Summary of the Peer-Review Comments
The EPA Report consists of seven chapters and various appendices. The reviewers were
asked to comment on the report as a whole but to focus on Chapters 2, 3, and the Appendices to
those chapters. Chapter 2 contains the analysis of the potential for transportation mode shift on
the Great Lakes as a result of compliance with the Category 3 rule. Chapter 3 contains the
analysis of the potential for source shift and production shifts, as well as the emission impacts of
transportation mode shift, were it to occur. The remainder of the EPA Report consists of general
information about EPA's marine emissions control program (Chapter 1) as well as information
specific to the Great Lakes with regard to estimated emission inventories (Chapter 4), estimated
air quality impacts and human health and welfare benefits associated with the Category 3 rule
(Chapter 5), estimated compliance costs for Category 3 ships on the Great Lakes (Chapter 6),
and an industry characterization (Chapter 7).
With regard to Chapters 2 and 3, the reviewers were asked to focus their reviews
primarily on the following issues raised by charge questions: 1) clarity of the presentation, 2) the
overall approach and methodology, 3) appropriateness of the datasets and other inputs, 4) the
data analyses conducted, and 5) appropriateness of the conclusions. Reviewers organized their
review reports by first addressing each of the five issues mentioned above, and then providing a
list of page-by-page comments. This memorandum provides a summary of the comments
received from the three reviewers: Dr. Michael Belzer (Wayne State University), Dr. Bradley
Hull (John Carroll University), and Mr. James Kruse (Texas Transportation Institute).
This memorandum is structured as follows: Section 3.1 provides an overview of all the
peer-review reports, Section 3.2 summarizes comments on clarity and presentation of the EPA
Report, Section 3.3 summarizes comments on the overall approach and methodology, Section 3.4
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summarizes comments on the appropriateness of the datasets and other inputs, Section 3.5
summarizes comments on the data analyses conducted, Section 3.6 summarizes comments on
appropriateness of the conclusions, and Section 3.7 summarizes any other comments provided by
reviewers. Interested readers should refer to Appendix E for the full text of the comments.
3.1 Overview of the Reviewers' Comments
The reviewers found the EPA Report to be comprehensive and well substantiated. With
respect to clarity of presentation, the reviewers generally noted that the EPA Report is well
written and easy to follow.
With respect to methodology, the reviewers commented that the methodology chosen is
appropriate but had some suggestions about some of the methodology assumptions. One of the
reviewers suggested improving mode shift analysis by addressing the impacts of a global trade
on three commodities (grain, steel coils, and containers). Another reviewer suggested that a
cost-benefit analysis would have been sufficient to justify environmental action.
Reviewers' most substantive critique was of the inputs to the analysis. All reviewers
emphasized the need for better documentation of some of the inputs and further explanation of
how several other inputs were derived.
While the reviewers commented that the conclusions drawn from the study were
appropriate, they suggested providing further evidence and explanation for some of them. One
reviewer suggested validating the applicability of the assumptions in the real world by discussing
inputs, analysis, and conclusions of a subset of 16 selected scenarios with the stakeholders.
3.2 Clarity of the Presentation
The reviewers generally noted that the EPA Report is well written and easy to follow.
The reviewers provided suggestions to improve overall readability and clarity to a general
audience. Some of their suggestions are summarized in this section.
Dr. Belzer suggested changing wording and clarifying several passages in Chapter 3. For
example, he suggested attributing the argument about a negligible increase in price of
commodities (except stone) to "down-market competition" in the last paragraph on page 3-13.
He also recommended providing a reference for an assumption that "marine carriers have empty
backhauls" in the first paragraph on page 3-20. Finally, Dr. Belzer suggested portraying marine
emissions in Table 3-9 on page 3-20 in the manner similar to locomotive emissions in Table 3-11
on page 3-22. He explained that it seems that locomotive and marine emission calculations are in
different denominations, and that makes it hard for a reader to compare the two.
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Dr. Hull suggested stating clearly early in the EPA Report that the study addresses sulfur
limits only, because readers might question why only sulfur limits are addressed in the EPA
Report, while the report also includes details on NOX and particulate matter. He proposed
clarifying the jurisdiction of the C3 Marine Rule, and suggested adding a convincing argument
that ships are among the major contributors to sulfur pollution in the Great Lakes/St. Lawrence
region (he suggested providing a table that lists sulfur emissions from ships, trucks, railroads,
automobiles, and manufacturers in the Great Lakes). He added that readers need to be convinced
that even though a majority of marine emissions take place in unpopulated areas, populated areas
are affected as well.
Dr. Hull also suggested clarifying "whether the Seaway between Montreal and the mouth
of the St. Lawrence River will require 100% MDO" and requested to perform a due diligence
analysis to determine whether sufficient quantities of MDO exist to support the C3 Marine Rule.
Finally, he suggested distinguishing clearly between the terms "rates" and "costs" throughout the
entire report.
Mr. Kruse mentioned that it would be helpful to standardize the units of measures for
tons, as terms such as "tonnes," "tons," "metric tons," and "short tons" are used throughout the
report. He suggested spelling out acronyms when they are introduced in the report for the first
time, such as "BAU" on page 1-12. He recommended providing explanation for the statement
"the analysis does not consider the transportation of the grain from the farm to the silo" on page
2-9. Mr. Kruse also suggested stating the fact that in some cases the origin/destination points are
not serviceable by rail in the beginning Appendix A to Chapter 2 versus, as it stands now, at the
end of the report in the results section. Mr. Kruse commented that the following two statements
were important and suggested adding them to the executive summary: 1) "The purpose of this
study is to examine whether an increase in fuel costs for Great Lakes shipping could lead to
transportation mode shift" on page 2-6, and 2) an explanation of how the freight comparison was
conducted on page 2-16.
3.3 Overall Approach and Methodology
Overall reviewers concurred with the selected methodology. With respect to the
origin/destination pairs, Dr. Belzer raised a concern that the 16 routes that were used in the
analysis were not randomly selected from about 50 cases suggested by the industry. He
mentioned that one potentially could assume that EPA selected "the cases with [the] least
likelihood of modal shift." However, Dr. Belzer argued that since 50 cases were proposed by the
industry that in general objects to the C3 Marine Rule, all 50 cases were likely to "support [the]
contention that these shifts would occur." Dr. Belzer commented that "due to overwhelming
evidence, repudiating the notion that modal shift would occur, it is unlikely that random selection
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would have yielded much different results;" and he further mentioned that if there is any bias, it
is likely to be on the conservative (higher cost) side. Dr. Belzer stated that it appears that EPA
"selected these cases systematically in an attempt to fairly represent a cross-section of trips about
which the private sector was concerned."
The other two reviewers suggested that clarifications are necessary for some of the
methodology assumptions. Dr. Hull suggested a clarification on whether the rail routes used in
the analysis are "heavily traveled trunk-line routes" and whether they involve multiple railroads.
He explained that though the shortest routes are appealing, railroads might choose longer, even
circuitous routes to preserve the long haul to gain the economies of scale and to not have to share
the revenue with another railroad by having to use another railroad for part of the way. Dr. Hull
further suggested explaining whether the routes were calculated based on "cost of service" or
"value of service" and specifying which components were included or providing a clear
definition of the calculation method. In his review report, Dr. Hull described both approaches,
and noted that in real life railroads use a "value of service" rather than "cost of service"
approach.
Mr. Kruse commented that "the approach of looking at origin/destination pairs that
stakeholders thought might be affected was excellent." He also mentioned that based on
historical cargo flows, the "commodities that were chosen were appropriate," and "the
involvement of stakeholders was accurate and meaningful." The fact that backhauls were
considered to be empty, in Mr. Kruse's opinion, was an assumption on the conservative (higher
cost) side. Finally, Mr. Kruse commented, the analysis followed "an appropriate trade-off
between accuracy and the level of effort."
With regard to stone shipments, two reviewers suggested that some additional
clarification is needed. Mr. Kruse recommended further studying and providing an explanation
as to why some facilities used stone originating at a much longer distance, requiring ship
transportation, when stone from local quarries may be available. Dr. Belzer noted that "if the
higher cost of fuel causes customers to source their products more nearby, then the products must
be close enough substitutes that they should not travel such distances in the first place. In other
words, if close substitutes do not shift closer then society must be subsidizing excessive freight
transport distance, which would be a bad public policy because the economics of the move
would not pay the full cost." Dr. Belzer also suggested EPA to consider quantitatively validating
the otherwise subjective statement about the stone analysis, that "the increase in number of
quarries is not substantial compared to the number of quarries already located within this radius"
on pages 3-5 and 3-6.
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3.4 Appropriateness of Databases and Other Inputs
All three reviewers agreed on the need to explain how certain inputs for the analysis were
derived. Some of the key suggestions are presented in this section.
Dr. Belzer commented that datasets appear to be acceptable by both EPA and the
industry, and seem as most appropriate for this analysis. Dr. Belzer suggested using an average
(or trend) price of marine fuel rather than single year price, because "using the 2007 price has a
disadvantage of capturing non-random point in time, rather than a trend." He also made a similar
comment about diesel fuel price for trucks and suggested using a long-term trend price.
However, he noted that using a lower price results in a "very conservative" estimate in the
analysis.
Dr. Belzer also mentioned that it would be helpful to study a coal-supply route from the
paper mill in Green Bay, Wisconsin (mentioned in Chapter 2); he suspected that the transfer cost
would not make viable a long part-rail/part-marine route. However, the route through South
Chicago might be inexpensive because of volume of cargo handled thus making the ton-mile cost
lower for a combined rail/marine route versus an all-rail route.
Dr. Hull sought clarifications on the rate/cost inputs provided for the analysis by
Chrisman Dager. He reiterated that it should be stated clearly whether these inputs are in terms
of "cost of service" or "value of service." If the inputs are in terms of cost of service, it should be
explicitly noted what components were included and what the source of the information was. If
the inputs are in terms of value of service, it should be noted how they were estimated and what
the source of the information was.
Mr. Kruse suggested providing a source for the specific engine marine fuel oil
consumption, and how the assumed propulsion power was derived. He also suggested the
following:
updating the Great Lakes basin profile with more recent data (if available) in Chapter
2, Appendix A, Table 13;
stating the sources for following variables: Auxiliary Engine Power, Auxiliary Engine
Load Factor in Port, and Rail Energy Intensity in Chapter 2, Appendix A, Table 16;
- justifying the assumption that a vessel would be loaded to 85% of its capacity (this
assumption directly affects unit freight costs) in Appendix A;
verifying the depth of ports located on the Great Lakes (this assumption also directly
affects unit freight costs); in Mr. Kruse's experience, the Corps of Engineers' Port
and Waterway Facilities data are not reliable for an inland waterway system;
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verifying the truck load assumption of 43 short tons, if the quarry is located in the
United States; and
verifying the assumption that the Algoma facility included in the analysis does have
the ability to receive iron ore by rail, and providing the source of the assumption that
"80% of the delivered iron ore costs, is the iron ore cost at the mine."
3.5 Data Analysis Conducted
In general, all reviewers agreed that transportation mode shift, source shift, and
production shift analyses performed were straightforward, appropriate, and adequate. Dr. Belzer
commented that the mode, shift, and production analyses were appropriate. Dr. Hull commented
that the analysis was straightforward and particularly the crushed stone analysis was "quite good,
though it would still benefit from a review of the underlying data sources." Dr. Hull commented
that the coal analysis could have been more thorough and the steel and supplementary analyses
should be revised to incorporate a global perspective.
More specifically, Dr. Hull made the following comments with regard to stone, coal,
steel, and supplementary portions of the mode shift analysis:
- Stone: Several simplifying assumptions were made and need to be validated. These
assumptions include the use of theoretical transportation cost from origin to
destination, the assumption that highways were a "straight line," the fact that
Michigan specialty stone replaces local quarry stone ton for ton, and the fact that
heavy trucks are allowed on highways.
Coal: The explanation of this portion of the analysis was rather confusing, and could
benefit from further explanation in simpler terms.
- Steel: Since steel is a vital industry in the Midwest, it can benefit from an expanded
analysis. One of the assumptions made in the analysis is that coal supplied to Great
Lakes by marine route is used in steel production, while in reality it is almost always
used by power plants.
Supplementary: This portion of the analysis is generally compelling, but requires
adding grain backhauls and a wider (worldwide) marketplace.
Mr. Kruse thought the analysis was "appropriate and adequate" with the exception of
concern why some facilities do not use stone from local quarries (See Section 3.3, above).
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3.6 Appropriateness of the Conclusion
In general, the reviewers commented that the conclusions drawn in the EPA Report were
appropriate. Dr. Belzer commented that conclusions were adequate based on the information that
was analyzed, and that cost increases due to a fuel change would be lost in the noise of price
changes and would not cause the shifts in question.
Dr. Hull suggested that EPA expand on the report, commenting that "with the Great
Lakes industries on the decline, the study needs to consider the global marketplace and present
potential import/export opportunities." Also, since the EERA model is theoretical, and the
assumptions may differ from the actual routes and rates, Dr. Hull encouraged a final validation
of the model by gaining stakeholders' input and perspective about a subset of 16 selected
origin/destination routes. Dr. Hull also noted that in reality the railroads and marine operators
price their services based on value of service, and even though the analysis shows that no modal
shift will occur, the higher priced marine fuel can result in "less business overall, as
manufacturers shift production away from the Great Lakes toward lower cost supply sources."
Mr. Kruse thought the conclusions were appropriate and justified given the data sources
and inputs used in the analysis.
3.7 Other Comments
In addition to the comments on the charge questions, the reviewers also provided other
suggestions and comments, which are summarized in this section.
Dr. Belzer commented that even though transportation mode shift, source shift, and
production shift analyses are of a concern in the EPA Report, from an economic and
environmental standpoint "these shifts would be entirely acceptable and in many cases more
efficient," especially considering that the societal benefits in this case exceed costs by anywhere
between 30:1 and 100:1. Dr. Belzer suggested that these impacts can be examined through the
use of a broad type of macroeconomic model, such as that incorporated in REMI and IMPLAN
would be adequate to perform a full cost-benefit analysis. Dr. Belzer also commented that truck
and locomotive industries already endure the costs of switching to low-sulfur fuel that resulted
from higher fuel prices and restrictions. He argued that actions to preserve air quality should
affect all transportation modes. Thus, if maritime sector were not required to comply with
cleaner fuel regulations, the society "risks subsidizing marine sector over others, contributing to
economic inefficiency and social inequity."
Dr. Hull urged EPA to include in the analysis the impact of the global marketplace on
three commodities in the Great Lakes region:
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Grain: Grain from the Midwest is shipped via three main routes: by ship through the
Great Lakes/St. Lawrence, by rail to the U.S. West Coast for loading on ships to
China, and by river barge down the Mississippi River for export from New Orleans.
These routes likely depend on transportation rates, and small rate changes might have
major impacts on the choice of route. As stated on p.7-26, almost 70% of grain
shipments on the Great Lakes are destined for export, so this might be a commodity
that should be analyzed explicitly.
Steel Coils: Break-bulk ships (typically operated by FedNav, Polstream, and
Wagenborg) export steel coils from Northern Europe by crossing the Atlantic,
transiting the Seaway, and discharging partial cargos at Cleveland, Detroit, and Burns
Harbor. These ships are then loaded with grain on the backhaul trip to Europe. Thus,
it is important to address whether requiring a use of low-sulfur fuel would: 1) make
deliveries of steel coils on their way to the Unites States through the Seaway less
economically attractive, shifting it to East Coast ports for an overland rail/truck route,
and potentially causing more emissions from rail/trucks and 2) make backhaul
deliveries of grain less available, thus making delivery of steel coils less
economically attractive, and causing the routes to shift inland, causing higher
emissions from rail/trucks.
- Containers: Containerships transit the Seaway as far as Montreal and then are loaded
on trucks and rail for delivery, with approximately half of the containers going to
Canada and half going to the United States. Currently, plans are underway to extend
container deliveries into the Great Lakes by water, directly through Europe or by
loading containers on feeder ships or barges in Montreal or Halifax (the ports of
Cleveland, Toledo, Erie/Conneaut, and Oswego are the interested ports and
Wagenborg, Great Lakes Feeder Lines, and McKeil Marine are the interested
carriers). If realized, these plans would lower SOX, NOX, and particulate emissions by
replacing rail and truck deliveries from Montreal and the East Coast. It is important to
study whether requiring use of low-sulfur fuel would make these plans less
economically attractive.
Mr. Kruse mentioned that one facet that is missing from the analysis is the concept of
equity, i.e. placing low-sulfur fuel requirements on the truck and locomotive industries but not
on the marine would represent an indirect subsidy to the marine industry.
10
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Appendix A: Resumes of Selected Reviewers
Resume of Reviewer Page
1. Dr. Michael Belzer A1-A2
2. Dr. Bradley Hull A3-A6
3. Mr. James Kruse A7-A11
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MICHAEL H. BELZER, PhD
Wayne State University
College of Liberal Arts and Sciences
656 W Kirby, 2074 Faculty/Administration Bldg.
Detroit, MI 48202
(313)577-3345
michael.h.belzer@wayne.edu
BIOGRAPHICAL SUMMARY:
Michael H. Belzer is Associate Professor in the Department of Economics of the College of
Liberal Arts and Sciences at Wayne State University. He also is Associate Director of the Alfred
P. Sloan Foundation's Trucking Industry Program, one of more than twenty Sloan Industry
Centers. The Trucking Industry Program focuses on trucking industry operations, regulation,
industrial organization, and industrial relations, and Dr. Belzer directs its Trucking Industry
Benchmarking Program. He serves as Chair of the Transportation Research Board Committee on
Trucking Industry Research, as a member of the Freight Systems Executive Board, and as a
member of the Committee on Freight Economics and Regulation as well as a member of the
Truck and Bus Safety Committee. Additional current interests include labor policy, industrial
organization, and the role of transportation in economic development.
DEPARTMENT/COLLEGE:
Department of Economics, College of Liberal Arts and Sciences
Departmental web page: http://www.clas.wayne.edu/unit-faculty-detail.asp?FacultyID=595
PRESENT RANK & DATE OF RANK:
Associate Professor, since September 1, 2000.
WSU APPOINTMENT HISTORY:
Year Appointed/Rank: September 1, 2000, as Associate Professor
Tenured in 2004 as Associate Professor of Urban and Labor Studies in the College of Urban,
Labor, and Metropolitan Affairs (CULMA)
With closure of CULMA on September 30, 2005, tenure granted in Department of
Interdisciplinary Studies, College of Liberal Arts and Sciences
With dissolution of the Department of Interdisciplinary Studies on September 30, 2007,
tenure granted in Department of Economics, College of Liberal Arts and Sciences
Academic Director, Master of Arts in Industrial Relations Program
September 1, 2000 - October 15, 2003
A-l
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EDUCATION:
Baccalaureate: A.B. College of Arts and Sciences, Cornell University, 1972
Graduate: M.S. Graduate School, Cornell University, 1990 (Ithaca, NY)
Ph.D. Graduate School, Cornell University, 1993 (Ithaca, NY)
(Studied at New York State School of Industrial and Labor Relations)
Major: Collective Bargaining, Labor Law, and Labor History
Minors: City and Regional Planning/ Human Resource Studies/ Research Methods
SELECTED PUBLICATIONS:
Book Chapters:
1. "Labor and Human Resources in the Freight Industry." A chapter in Intermodal Freight
Transportation, Lester Hoel, Genevieve Giuliano, and Michael Meyer, editors. Publisher:
Eno Transportation Foundation, Inc. Forthcoming.
2. "The Next Move: Metropolitan Regions and the Transformation of the Freight Transport
and Distribution System." With Susan Christopherson. In Urban and Regional Policy and
Its Effects, edited by Nancy Pindus, Howard Wial, and Harold Wolman. Brookings
Institution Press. 2009.
3. "The Effects of Trucking Firm Financial Performance on Safety Outcomes." With Marta
S. Rocha and Daniel A. Rodriguez. In Transportation Labor Issues and Regulatory
Reform. James H. Peoples and Wayne K. Talley eds. Research in Transportation
Economic Series. Rotterdam, The Netherlands: Elsevier Science Publishers, 2004, pp.
35-55.
Peer-Reviewed Journal Articles Published:
1. "Environmental determinants of obesity-associated morbidity risks for truckers." International
Journal of Workplace Health Management. With Yorghos Apostolopoulos, Sevil Sonmez, and
Mona M Shattell, In press.
2. "Worksite-Induced Morbidities Among Truck Drivers in North America: A Comprehensive
Literature Review." With Yorghos Apostolopoulos, Sevil Sonmez, and Mona M. Shattell.
American Association of Occupational Health Nurses [AAOHN] Journal. Vol. 58, No. 7, 2010:
pp. 285-96.
3. "Empirical Evidence of Toll Road Traffic Diversion and Implications for Highway Infrastructure
Privatization." With Peter F. Swan. Public Works Management & Policy, Vol. 14, No. 4 (April
2010): pp 351-73.
A-2
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BRADLEY HULL, PhD
Associate Professor and Reid Chair
Department of Management, Marketing, and Logistics
John Carroll University
University Heights OH 44118
(216)397-4182
bzhull@jcu.edu
LOGISTICS MANAGEMENT EXPERT with well-developed management skills and proven
ability to control costs, maximize service levels and build profitable national and international
logistics operations.
Recognized as a leader in oil/chemical industry logistics and strategic planning issues.
Creative problem solver, known for ability to creatively overcome obstacles and
develop innovative solutions for difficult logistics problems.
Highly effective in utilizing logistics to enhance marketability of company assets.
Broad base of industry contacts and an up-to-date knowledge of market conditions.
Core Competencies:
Supply Chain Management Operations Management Operations Planning
Distribution Management Operations Research Carrier Selection / Negotiation
Emergency /Haz-Mat Response Fleet Management Total Quality Management
Inventory Management Customer Service Warehouse Management
BIOGRAPHICAL SUMMARY
1. Previously employed by British Petroleum for 28 years in a wide variety of logistics and
supply chain positions. In these positions I stored and delivered chemicals, petroleum, and
petroleum products, both domestically and internationally by rail, truck, barge, pipe, and ship.
2. For the past 11 years I have been a professor at John Carroll University where I research
transportation topics and teach courses in logistics and operations management. More recently, I
also worked on a part-time basis for the Port of Cleveland developing new business. In addition,
I was hired by NEOTEC (Northeast Ohio Trade and Economic Consortium) to perform the
"Northeast Ohio Logistics Infrastructure Study" which can be found at
www.neohiotransportationupdate.com or www.neotec.org.
3.1 hosted three seminars on campus in the past year. Each was attended by more than 250
business people. The first was titled "The Great Lakes/St Lawrence Marine Highway, Fitting the
Pieces Together," and the second was titled "Northeast Ohio Logistics Infrastructure." The
recent August 30th seminar is the second annual "Fitting the Pieces Together" seminar. These
seminars have led directly to decisions to 1) expand rail access to the Port of Cleveland, 2)
reexamine the feasibility of a cross lake ferry, and 3) reexamine the feasibility of a
Cleveland/Montreal scheduled waterborne service.
4. Through my efforts, John Carroll University has been accepted a member of the Great Lakes
Maritime Research Institute and the Great Lakes Coalition.
A-3
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Professional Profile
Education
University of Pennsylvania, BS in Mathematics
Stanford University, MS in Operations Research
Case Western Reserve University, PhD in Operations Research
Experience
JOHN CARROLL UNIVERSITY - Cleveland, Ohio
Associate Professor of Management (2007-present)
Teach undergraduate and MBA courses in Logistics, Transportation, Operations
Management, MIS
Assistant Professor of Management Information Systems (1999-2007)
Teach undergraduate and MBA courses in MIS, ERP Systems, Operations Management,
and Logistics
BP OIL COMPANY - Cleveland, Ohio
Logistics Expert (1997-1999)
Functioned as logistics expert, supporting operations such as Refinery Supply, Alaskan
Trading, International Oil Trading, Exploration, Terminals and Chemicals. Develop
flexible, cost-effective distribution channels for BP's business units.
Developed new crude oil and finished product supply routes, when BP sold one
refinery and greatly modified another. Logistics expenditures exceed $150,000,000
per year.
Persuaded BP to spend $1 million to improve a terminal, resulting in $2million/year
savings, and a partnering offer, due to its newfound logistics potential. Completed
similar projects at other terminals.
Identified and resolved a persistent crude oil contamination problem. $2 million
annual savings.
Avoided a "last minute" sale of $9 million worth of crude oil (in transit to one of our
refineries during a fire). Identified unique method of supplying the burned refinery
with intermediate feedstocks.
Published monthly "Pipeline News " newsletter for three years.
Provided consulting services to the Canadian government.
Alaskan Oil Logistics Mgr. - Lower 48 and Panama (1988-1997)
Managed $100,000,000-S300,000,000 in annual logistics expenditures. Managed the
flow of Alaskan Oil to mid-continent markets along a 12,000 mile long supply chain (via
crude oil tanker deliveries through Panama and four cross country pipeline networks).
Responsibilities included: tanker and pipeline scheduling, inventory management,
customer service, new account development, and quality control. Managed BP's
operations at four crude oil terminals.
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Increased customer base by 25%, cut inventories by 25%, and cut transportation costs
by 20%.
Customer deliveries 99% on time and within specification.
Developed 10-15 new customers for Alaskan crude in the mid-continent.
Extended our marketing area by utilizing uniques modes of transportation.
Successfully avoided many "last minute" sales of crude oil, during multiple logistics
disruptions
Increased BP's market share by helping competitors find low cost routes to other
markets.
BP OIL COMPANY AND BP PIPE LINE COMPANY - Cleveland, Ohio
Logistics Consultant / Mgr. Computer Resources (1986-1988)
Provided logistics consulting services; developed multiple crude supply routes for BP's
five refineries.
Resolved a 10-year raw materials bottleneck at BP's New Orleans refinery.
Developed access routes from BP's Los Angeles supply hub to four independent LA
refiners.
Developed the first use of laptop computers for pipelines (software was sold to
Exxon).
BP CHEMICALS - Lima and Cleveland, Ohio
Director of Logistics (1978-1985)
Managed $100,000,000 in annual logistics expenditures. Coordinated the distribution of
20 product lines. Assumed responsibility for planning and day-to-day operations (i.e.,
transportation, storage, fleet management, private trucking, emergency response, export
and hazardous materials regulation). Utilized multiple transportation modes, including
rail, truck, barge, pipeline and ship. Directed activities of more than 100 trucking
companies, a fleet of 1000 rail cars, 15 tractor-trailers, and 30 storage facilities.
Supervised and directed a staff of 30, and managed a $12,000,000 budget.
Coordinated daily shipping operations (from order entry through physical delivery),
and achieved a 99% on-time performance; additionally responsible for emergency
response to hazardous situations.
Managed a 1000 rail car fleet in the U.S. and a 30-car rail fleet in Europe.
Planned and negotiated rates and service commitments with tank car suppliers,
railroads, trucking companies, barge lines and ocean carriers.
Negotiated warehousing facilities for chemicals in the U.S. and Europe.
Successfully implemented logistics innovations that improved system performance.
SOHIO - Cleveland, Ohio
Management Science Specialist (1973-1977)
Developed linear programs and computer simulations for a wide variety of logistics
issues critical to the company's growth and success. Served as member of six-person
team ($500,000,000 project) that selected a crude oil tanker fleet, developed supertanker
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port, and identified market for Alaskan oil following development of the Alaskan oil
field.
OTHER EXPERIENCE (1986-1999)
Lecturer - John Carroll and other local Universities. Teach evening MBA courses in
Operations Research and Operations Management (part-time)
Selected Publications
Hull, B., "Supply Chain Mythology", submitted to the Decision Sciences Journal
Hull, B., "Northeast Ohio Logistics Infrastructure Study." Sponsored by NEOTEC, January
2010, www.neohiotransportationupdate.com.
Hull, B., "Frankincense and Myrrh - the Oldest Global Supply Chain?" Journal of
Macromarketing, Vol. 28, No. 3, 2008, pp. 275-289.
Hull, B., "Have Supply (Driven) Chains Been Forgotten?," International Journal of Logistics
Management, 16.2 (2005): 218-36.
Hull, B., "Oil Pipeline Markets and Operations," Journal of the Transportation Research Forum,
44.2 (2005): 111-25. [2] (Fall Issue).
Hull, B., "The Role of Elasticity in Supply Chain Performance", InternationalJournal of
Production Economics, Vol. 98, Issue 3, Dec. 2005, pp. 301-314
Grenci, R. and B. Hull, "New Dog, Old Tricks: ERP and the Systems Development Life Cycle",
Journal of Information Systems Education, Vol. 15, No. 3, (Fall 2004), pp. 277-287.
Hull, B. "A Structure for Supply Chain Information Flows and its Application to the Alaskan
Crude Oil Supply Chain", Logistics Information Management, 15,1,2002.
Ten editions of Pipeline News, a pipeline industry newsletter, which I wrote and distributed to
100+ colleagues and customers.
Hull, B., "How to Make a Logistics Partnership Work", Transportation and Distribution, June
1989.
Hull, B., TE Moroni, DL West, "Automating Liquid Line Shipping Documentation." Pipeline
Industry, May 1987.
Hull, B., TE Moroni, GE Shetler, DL West, "Automating Flow of Pipeline Shipments
Documentation," Proceedings of the American Petroleum Institute Conference, April 1986.
Hull, B., TE Moroni, DL West, "Adapting Small Computers to Pipelines," PipelineDigest,
October 1986.
Hull, B., "Two Algorithms for Matroids", Discrete Mathematics, Vol. 13, No 2, October 1975.
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C. JAMES KRUSE
Director, Center for Ports & Waterways
Texas Transportation Institute
701 North Post Oak, Suite 430
Houston, TX 77024
Phone: (713) 686-2971
Fax: (713) 686-5396
j-kruse@ttimail.tamu.edu
BIOGRAPHICAL SUMMARY
Mr. Kruse is the Director of the Center for Ports and Waterways at the Texas
Transportation Institute (TTI). He is responsible for identifying research and extension needs in
the port community and mobilizing resources to meet those needs.
He served in a senior executive capacity for nine years at the Port of Brownsville (1988-
1997), Texas (eight years as port director), where he led a successful effort to acquire a
Presidential Permit for an international bridge. Following his service at the Port of Brownsville,
Mr. Kruse worked as a Regional Program Manager for Foster Wheeler Environmental's Ports
Harbors & Waterways Program and assisted on port-related projects around the country.
Mr. Kruse has acquired a strong transportation planning background, having served on
numerous local, state, and national boards and task forces. He was an active participant in the
development of long range plans for a seaport and airport in South Texas, he has worked on
statewide issues in Texas, he has participated in border transportation organizations, and he has
assisted ports from Corpus Christi to New York with planning and environmental issues. Mr.
Kruse is bilingual (Spanish/English) and has worked on a number of projects in the Latin
American region.
EDUCATION
MS, International Business and Human Resources, Houston Baptist University, 2000.
MBA, Accounting and Finance, University of Kansas, 1977.
B.A., Business Administration, Mid-America Nazarene University, 1975.
RELEVANT EXPERIENCE
Texas Transportation Institute, Center for Ports & Waterways (2002 - Present). Director, Center
for Ports and Waterways
As Director of the Center for Ports & Waterways, primary focus is on acquiring research
contracts for the organization and directing that research.
Technical Analyst: Provided technical assistance to Puerto Rico Sea Grant Program in
evaluating issues raised by the Environmental Impact Statement for the proposed Port of the
Americas
Technical Analyst: Prepared comments for Port of Chicago regarding land use options
Organizer: Organized the 2004, 2006, and 2008 Texas Ports and Waterways Conference co-
hosted by Sea Grant and the Center for Ports and Waterways
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Research Analyst: Gathered information on Liquefied Natural Gas import terminals and
presented to Sea Grant agents and state legislators from various states
Investigator: Panama Canal Dry-Bulk Market Segment Peer Review (Research funded by
Panama Canal Authority, 2003)
Principal Investigator: Analysis of Start-up Cross-Gulf Shipping Activities with Mexico Since
1990: Problems and Opportunities (Research funded by Southwest Region University
Transportation Center, 2004)
Principal Investigator: Effect of Security Requirements on Port Infrastructure Development
and Funding (Research funded by Southwest Region University Transportation Center,
2005)
Principal Investigator: Analysis OfU.S.-Mexico Border Trade Targets For Short Sea
Shipping (Research funded by Gulf Ports Association of the Americas, 2006)
Principal Investigator: Container on Barge Market Analysis - Task 1 (Research funded by
private industry, 2006)
Principal Investigator: Environmental Impacts of Modal Transportation Study-Phase /,
(Research funded by Maritime Administration, 2006)
Principal Investigator: The Value of Texas Seaports in an Environment of Increasing Global
Trade (Research funded by Texas Department of Transportation) - (Research funded by
Texas Department of Transportation, 2007)
Principal Investigator: A Modal Comparison of Domestic Freight Transportation Effects on
the General Public (Research funded by US Maritime Administration and National
Waterways Foundation, 2007)
Principal Investigator: Short Sea Shipping Initiatives and the Impacts on the Texas
Transportation System (Research funded by Texas Department of Transportation, 2007)
Investigator: Study for the Development of a National Competitiveness Pact (Research
funded by Secretariat of Communications and Transportation, Mexico, 2008)
Principal Investigator: An Analysis of Harbor Master Positions in Cargo Ports (Research
funded by Port of Houston Authority, 2008)
Principal Investigator: Lock And Dam Non-Navigation Beneficiary Study (Research funded
by National Waterways Foundation, 2008)
Principal Investigator: Development of Potential Policies and Incentives to Encourage
Movement of Containerized Freight on Texas Inland Waterways (Research funded by Texas
Department of Transportation, 2008)
Investigator: Emerging Trade Corridors and Texas Transportation Planning (Research
funded by Texas Department of Transportation, 2009)
Investigator: Protecting Waterways from Encroachment (Research funded by Texas
Department of Transportation, 2010)
Principal Investigator: North American Marine Highway Operations (Research funded by
National Cooperative Freight Research Program, Transportation Research Board, 2010)
Principal Investigator: Transportation Rate Analysis For The Gulf Intracoastal Waterway -
West (Research funded by the US Army Corps of Engineers, 2010)
Principal Investigator: Modal Comparison of Greenhouse Gas Emissions (Research funded
by the National Waterways Foundation, 2009)
Principal Investigator: Metropolitan Planning Organization (MPO) Maritime Information
Needs Study, (Research funded by Marine Highways Cooperative Program, 2010)
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Principal Investigator: Analysis of the Effects of Lack of Channel Maintenance Dredging
(Research funded by Port of Houston Authority ,2010)
Principal Investigator: Update to "A Modal Comparison of Domestic Freight Transportation
Effects on the General Public" (Research funded by National Waterways Foundation
Research in Progress)
Principal Investigator: Transportation Rates & Closure Response Research - Calcasieu Lock
(Research funded the U.S. Army Corps of EngineersResearch in Progress)
Active Memberships:
1. Transportation Research Board Committee on Ports and Channels
2. Transportation Research Board Committee on Marine Environment
3. Transportation Research Board Committee on Inland Waterways
4. Harbors, Navigation and Environment Committee, American Association of Port
Authorities
5. Texas Ports Association
6. Houston-Galveston Area Maritime Security Committee
Foster Wheeler Environmental Corporation, (19972002). Regional Program Manager,
Ports, Harbors & Waterways Program
Project Manager- Gulf Intracoastal Canal Association, Verification Analysis of Economic Impact
of Lower LagunaMadre Reach ofGlWW, 2002.
Project Manager- BP Refinery (Amoco Oil) Navigation Project Permit and Development
Assistance (Texas City), 2001-2002.
Business Development Lead & Project Team Member- Maine Department of Transportation
Dredging Management Action Plan, 2001.
Project Manager- Port of Texas City Disposal Area Management Plan, Phase II, 2001.
Task Manager- Port Authority of New York & New Jersey, Analysis of Opportunities and
Issues for Near shore Fills for Terminal Expansion, 2000.
Project Manager- Port of Houston Authority, Administrative and Oversight Assistance with
Alexander Island Spill Cleanup, 1999-2000.
Project Manager- Port of Texas City Disposal Area Management Plan, Phase I, 1999.
Project Manager- Port of Corpus Christi, Assumption of Maintenance Analysis, Rincon
Canal System, 1998.
Project Manager- Port ofPascagoula (MS), Project Management for Dredging and
Infrastructure Improvements, 1997-1999.
In addition to his project activities, Mr. Kruse was the regional Business Development Manager
for Ports, Harbors, & Waterways opportunities, and assisted on many proposals both nationwide
and in foreign countries.
Port of Brownsville, TX, (1988 -1997). General Manager & Port Director
As Port Director, served in a wide variety of functional areas:
Was appointed by Gov. Ann Richards to Texas/Mexico Authority
Supervised planning, design, and implementation of $100 million in improvements to the
Port facilities
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Engaged in extensive public relations efforts including newspapers, radio, TV, magazines,
seminars, speaking engagements, and special campaigns
Re-evaluated and redesigned organizational structure, producing new job descriptions,
procedures, and policies
Wrote the Port's long range plan
Worked extensively with business leaders and State and Federal Government officials in U.S.
and Mexico on legislative and economic development matters
Major project activities included:
Project Manager- Permitting and Project Development for New International Bridge
Crossing between Brownsville, TXandMatamoros, Tamaulipas, Mexico, 1990-1997.
Project Coordinator- Channel Deepening Project, Brownsville, TX, 1989-1995.
Project Coordinator- Mexico Intracoastal Waterway, Analysis and Relations with Mexican
Government, 1993-1997.
Project Manager- Acquisition and Installation ofDrydock for Port of Brownsville, TX, 1994-
1996.
Project Over sight- Provided project oversight for railroad relocation, new dock construction,
and rehabilitation and reconstruction of docks and roads for the shrimping industry.
Legislative: Testified before a number of U.S. Congressional Committees and Texas
legislative committees on a variety of issues.
During tenure at Port of Brownsville, served on the following Boards/Committees:
Texas Border Transportation Technical Advisory Committee (TxDOT)
Economic Development Subcommittee of the Statewide Transportation Plan Committee for
development of the 1994 Texas Transportation Plan (Texas Department of Transportation)
American Association of Port Authorities, Board of Directors
Gulf Ports Association of the Americas
Long Range Plan Committee for Brownsville/South Padre Island International Airport
Long Range Plan Committee for Brownsville Navigation District
Arthur Andersen & Co., (1977-1980), Senior Analyst, Management Information Consulting
Division
Designed, installed, and revised several accounting systems for use in oil and gas industry in Texas and
Mexico. Worked one and one-half years in Mexico City (1978-1980) on project for Petroleos Mexicanos
(PEMEX).
SELECTED PUBLICATIONS
J. Mileski, R. Thrailkill, K. Haupt, J.J. Lane, W.T. McMullen, J. Gunn, CJ. Kruse, D.H.
Bierling, L.E. Olson, J. Huang, P.-. Lorente. Protecting Waterways from Encroachment. 0-6225-
S. Texas Transportation Institute, College Station, TX. 2010.
J. Mileski, W.T. McMullen, R. Thrailkill, J. Gunn, K. Haupt, CJ. Kruse, J.J. Lane, D.H.
Bierling. Recommendations and Guidelines on Shoreline Development and Hazards to
Navigation. 0-6225-P1. Texas Transportation Institute, College Station, TX. December 2010.
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J. Mileski, R. Thrailkill, K. Haupt, J.J. Lane, W.T. McMullen, J. Gunn, CJ. Kruse, D.H.
Bierling, L.E. Olson, J. Huang, P.-. Lorente. Analysis and Recommendations on Protecting
Waterways from Encroachment. 0-6225-1. Texas Transportation Institute, College Station, TX.
August 2010.
C. J. Kruse, C. A. Morgan, N. Hutson. Potential Policies and Incentives to Encourage Movement
of Containerized Freight on Texas Inland Waterways. 0-5937-1. Texas Transportation Institute,
College Station, TX. March 2009.
CJ. Kruse, N. Hutson, C.A. Morgan. Guidebook: Potential Policies and Incentives to Encourage
Movement of Containerized Freight on Texas Waterways. 0-5937-P1. Texas Transportation
Institute, College Station, TX. February 2009.
CJ. Kruse, J.C. Villa, D.H. Bierling, M.S. Terra, N. Hutson. Short Sea Shipping Initiatives and
the Impacts on the Texas Transportation System. PSR. 0-5695-S. Texas Transportation Institute,
College Station, TX. 2007.
CJ. Kruse, J.C. Villa, D.H. Bierling, M.S. Terra, N. Hutson. Short Sea Shipping Initiatives and
the Impacts on the Texas Transportation System: Technical Report. SWUTC. 0-5695-1.
Southwest Region University Transportation Center, Texas Transportation Institute. December
2007.
C J. Kruse, A. A. Protopapa, L.E. Olson, D.H. Bierling. A Modal Comparison of Domestic
Freight Transportation Effects on General Public: Final Report. TTI-2007-5. Texas
Transportation Institute, College Station, TX. December 2007.
C J. Kruse, J.C. Villa, D.H. Bierling, J.M. Solari-Terra, P.-. Lorente. Container on Barge Market
Analysis - Task 1. April 2006.
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Appendix B: Charge Questions
Particulars Page
i Letter to the reviewers with charge , _
1. . r> 1 -r>2
questions
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RTI
INTERNATIONAL
Memorandum
TO: Michael H. Belzer, PhD (Wayne State University)
Bradley Hull, PhD (John Carroll University)
James Kruse (Texas A&M University)
FROM: Alex V. Rogozhin (RTI)
CC: Dileep K. Birur (RTI); Michael P. Gallaher (RTI); Lauren Steele (EPA)
DATE: Decemb er 1, 2010
SUBJECT: Charge Questions for Peer Review of Economic Impacts of the Category 3
Marine Rule on Great Lakes Shipping.
Thank you for agreeing to review the enclosed report, "Economic Impacts of the
Category 3 Marine Rule on Great Lakes Shipping."
EPA's Office of Transportation and Air Quality recently finalized regulations addressing
emissions from Category 3 marine diesel engines and their fuels (the C3 Marine Rule, 83 FR
22896, April 30, 2010). This rule contains EPA's coordinated strategy to address these emissions
through a combination of national and international actions. As EPA developed the C3 Marine
Rule, stakeholders from the Great Lakes shipping industry expressed their concerns that the
proposed program, particularly the fuel sulfur limits, would lead to higher operating costs for
ships operating on the Great Lakes. They indicated that this would lead to a transportation mode
shift away from ships and toward trucks or rail, which could increase emissions overall by
moving to less efficient ground transportation. . They also indicated that the increased operating
costs could affect the market for crushed stone, leading users to change their source from stone
transported from the upper Great Lakes to local quarries. In addition, there was concern about a
possible production shift for steel manufacturing and electricity generation, which would also
adversely affect the Great Lakes shipping sector. Although EPA did not change its final rule
with regard to applying the engine standards and fuel sulfur limits to the Great Lakes, EPA
included several provisions to address these concerns and indicated that it would perform an
economic impact analysis of the rule on Great Lakes shipping. The attached report contains that
analysis. We are submitting this document to you for a peer review of the methodology, and the
validity of the data and assumptions that go into it.
EPA has provided direction and charge questions for this review and these are included
below. A teleconference call will also be arranged so that EPA can respond to questions from
individual reviewers on the material that was provided for review. The completed review reports
are to be furnished to RTI by January 12, 2011.
Elements to be addressed in the Charge to the Reviewers of the Report on "Economic
Impacts of the Category 3 Marine Rule on Great Lakes Shipping."
The report looks at three aspects of EPA's recent Category 3 marine rule raised by
stakeholders with respect to the application of stringent fuel sulfur limits to ships that operate on
the Great Lakes. Specifically, the report examines whether higher fuel costs associated with
switching from heavy-fuel oil to distillate fuel will result in transportation mode shift, source
shift, or production shift.
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Three separate methodologies are used for the analyses. The transportation mode shift
was performed by ICF Int'l. with EERA, and uses a route-based approach. The source shift
analysis was performed by EPA and uses a competitive radius approach. Finally, the production
shift was performed by EPA and uses a retail revenue approach.
The report also contains information on EPA's estimated emission inventories (Chapter
4), air quality impacts and human health and welfare benefits (Chapter 5), costs (Chapter 6), and
industry characterization (Chapter 7). However, these chapters are included in the report for
information purposes only and we are not asking you to review them.
We request that your review primarily focus on: 1) clarity of the presentation, 2) the
overall approach and methodology, 3) appropriateness of the datasets and other inputs, 4) the
data analyses conducted, and 5) appropriateness of the conclusions. For this review, no
independent data analysis is required, nor is it required that you duplicate the results. The
appendices to several chapters of the report contain detailed information about the analysis,
including contractor reports where relevant. You may need to review and comment on these
appendices as part of the peer review of the report, especially Appendix 2A, which is the final
project report from EERA and ICF.
In your comments, you should distinguish between recommendations for clearly defined
improvements that can be readily made based on data reasonably available to EPA, versus
improvements that are more exploratory or dependent on data not available to EPA. The
comments should be sufficiently detailed to allow a thorough understanding by EPA or other
parties familiar with the work.
Your comments should be provided as an enclosure to a cover letter that clearly states
your name, the name and address of your organization, what material was reviewed, a summary
of your expertise and qualifications, and a statement that you have no real or perceived conflicts
of interest. Please also enclose an email with your comments in MS Word, or a format that can
be imported into MS Word. The comments should be sent in care of Alex Rogozhin to the E-
mail: avr@rti.org.
This study is in response to an EPA rulemaking on this subject. Therefore, EPA will
make the report and your comments available in the Public Docket for the rule.
We would appreciate your not providing the peer review materials or your comments to
anyone else until EPA makes them public. We would also like to receive the results of this
review in the shortest time frame possible, preferably within four weeks of your receipt of this
request. If you have any questions about what is required in order to complete this review, or if
you find you need additional background material, please contact Alex Rogozhin by phone (919-
541-6335) or e-mail ravr@rti.org1. If you have any questions about the EPA peer review process
itself, please direct them to Ms. Ruth Schenk of EPA by phone (734-214-4017) or e-mail
rschenk.ruth@epa.gov1
You will be paid a flat fee of $5,000 for this peer review. This fee was calculated based
on an estimated 50 hours of review time at a rate of $100 per hour. In your cover letter please
indicate the number of hours spent on the review; spending fewer or more hours than our
estimate will not affect the fee paid for this work, but will help us improve our future budget
estimates.
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Appendix C: Questions and Answers Provided During
the Review Process
Particulars Page
Questions provided by reviewers for
conference call #1
Log of questions and answers during
conference call # 2
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Conference Call # 1:
Reviewers provided EPA with a list of questions that directed EPA's presentation, and were
addressed on the conference call. Reviewers were given an opportunity to ask additional
questions during the conference call.
Participants:
Reviewers: Michael H. Belzer, PhD (Wayne State University); Bradley Hull, PhD (John
Carroll University); James Kruse (Texas A&M University)
EPA: Lauren Steele, Jean-Marie Revelt
RTI: Alex Rogozhin
Questions from Dr. Brad Hull
General Questions:
1. In the Great Lakes area, what percent of the emissions are caused by ships? I ask this
because, being a depressed economy, there doesn't seem to be much Great Lakes
shipping.
2. Please confirm that the EPA C3 requirements are the same as those stated in the last
paragraph on page 12 of the executive summary. Why didn't EPA make its ruling
directly rather than through an amendment to MARPOL Annex VI?
3. How do the MARPOL Annex VI limits compare with those proposed for the North
American EGA? Are they more stringent for the Great Lakes?
4. Canada must have emissions limits for Canadian Flag vessels. How do their limits
compare with the existing US requirements and proposed EPA C3 requirements?
5. Does the technology presently exist to achieve these proposed standards?
6. Could I read some of the stakeholder comments, such as Lake Carriers and Canadian
Shipowners? I would like to understand their viewpoint as I review the EPA study.
7. The foreign flag shipping industry does not have an organization like Lake Carriers or
Canadian Shipowners. How will the C3 requirements impact international movements of
foreign flag ships?
Comparison of the Great Lakes versus other US waterways:
1. How do the EPA C3 requirements compare with those required on the
Mississippi/Dlinois/Ohio river system? Do the vessels on those rivers utilize C2 or C3
engines?
2. Are the same EPA C3 requirements being applied to domestic US Flag shipping
requirements on the East, West, and Gulf Coasts of the US?
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Who uses C3 engines? :
My understanding is that the Great Lakes freighters that stay within the Great Lakes
operate with C3 engines.
1. Do Great Lakes barge operators use C3 engines - or do they use C2?
2. Do Great Lakes towing companies use C3 engines - or do they use C2?
3. Do the cross-lake ferries use C3 engines? (I assume that Badger does, but is it the only
one?)
4. Do oceangoing vessels that transit the Seaway/Great Lakes have C3 engines - or do they
use C2? Here I am referring to Seawaymax or smaller vessels that carry steel slabs and
coils from Europe to the Great Lakes, grain ships, and breakbulk ships that move project
cargo.
Understanding the EPA C3 requirements from a vessel perspective:
1. Do the EPA C3 requirements apply only to US Flag ships? Do Canadian and foreign flag
vessels fall under these requirements?
2. Will the EPA C3 requirements be enforced on Canadian and/or foreign flag ships in US
Great Lakes waters or US Great Lakes ports?
3. Are the EPA C3 requirements more or less stringent than Canadian requirements? What
are the Canadian requirements?
4. The Canadian Shipowners Association is listed as a stakeholder. Why is this, if the EPA
ruling only pertains to US Flag ships? What is the expected impact on Canadian ship-
owners?
Economic Arguments:
1. What is the expected percentage wise increase that C3 requirements will add to shipping
costs?
2. The executive summary concludes that reducing C3 emissions should not impact
volumes moving on the Great Lakes, and should not displace them to rail or truck (which
would cause more emissions). However, by paying higher fuel costs will the crushed
stone (and the other Great Lakes products) less profitable the increased fuel costs to their
customers. That is, in economic terms, how much will demand for Great Lakes products
be reduced when the fuel price increases? Is this a major or minor point?
My understanding is that for commodities like crushed stone, potash, etc, that
transportation costs are a significant percentage of the sales price. In particular, years
ago, when I used to move potash from Saskatchewan to the Midwest by rail, that the rail
rates were 40% of the sales price of the potash! If this is the case with crushed stone,
coal, and the other Great Lakes commodities, might not this phenomenon reduce the
overall demand for the product?
3. Could the new C3 standards result in a shift to Canadian sources for crushed stone or
coal? After all, US shipping prices would increase relative to Canadian?
4. Any impact on steel movements? Or other breakbulk movements?
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5. Why does the list of 16 at risk moves include some cross-lake movements. (Cross-lake
movements can utilize foreign flag ships). Might not a cross-lake movement presently
being made by a US Flag ship, switch to a Canadian flag ship?
Questions from Mr. James Kruse
General Questions:
1. Does an analysis of the economic dampening effect of an increase in cost without an
increase in productivity or service levels need to be performed?
2. A parallel question: There may not be a mode shift, but will businesses continue to
consume the same amount of product if the cost rises? In other words, instead of a shift,
what if there is a reduction in economic activity?
3. How were individual vessel fuel consumption patterns determined?
4. Chapter 6 seems to indicate that we are only talking about modifying 12 ships. Is that
correct?
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Conference Call # 2:
Log of January 7, 2011 telephone conversation between RTI (Alex Rogozhin), EPA (Lauren
Steele, Jean-Marie Revelt), and Dr. Bradley Hull
1) Q: Are steamships excluded? Do they run on heavy fuel? Can they run on residual fuel?
Are there any that run on coal?
A: Steamships are exempt from EGA fuel sulfur requirements on the Great Lakes. There
are no freighters with steam power from coal operating on the Great Lakes.1 Steamships
on the Great Lakes do run on heavy fuel (aka residual). Steamships were exempted from
the EGA fuel requirements after the industry raised safety concerns that may arise from
the use of distillate fuel in these boilers, which were designed to use residual fuel.
2) Q: Are steamships used on the same trade routes on Great Lakes as diesel ships?
A: Yes, steamships operate on the same trade routes on the Great Lakes as diesel ships.
3) Q: Are steamships more expensive to operate on Great Lakes?
A: EPA did not attempt to study the operating costs of steamships operating on the Great
Lakes because they are exempt from the EGA fuel sulfur requirements on the Great
Lakes.
4) Q: Are C2/C3 diesel ships required to comply with regulation if retrofitted, are
steamships required to comply if retrofitted?
A: EPA does not require any vessel, including steamships, to be repowered. However, if
an owner decides to repower a steamship, the replacement diesel engines would be
required to comply with EPA's replacement engine requirements (have to meet current
tier standards or demonstrate why this is not possible).
5) Q: Are steamships exempt from EGA sulfur requirements until 2015 (or 2014) or
indefinitely?
A: Existing steamships that operate on the Great Lakes are exempt from the EGA fuel
sulfur requirements indefinitely.
6) Q: I recall seeing different numbers of US flagged ships mentioned in the report (some
parts 8, some parts 12), what is the correct number of US flagged ships operating in Great
Lakes?
1 It was not mentioned on the Jan 7 call but there is a steam-powered car ferry that burns coal, the S.S. Badger, operating on the
Lakes.
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A: To our understanding, the correct number is 12. Different parts of the report were
written by different authors and contractors, and some might have reviewed outdated
literature. Please flag the discrepancies if you see them.
7) Q: Did the study considered US flagged vessels only?
A: The Study was meant to be "flag neutral," in that the analysis looks at the impact of an
increase in fuel costs for a type of vessel operating on a particular route. The flag of the
ship was not taken into consideration. The EGA fuel sulfur requirements are expected to
have similar impacts on similar vessels regardless of flag. Canadian flagship operators
were a part of EPA's outreach process to stakeholders.
8) Q: Study only considers sulfur standards, the NOX standards would be affected by
retrofitting, correct?
A: Yes, the study considers only the impacts of the EGA fuel requirements on the Great
Lakes. The study does not consider the EGA NOX requirements because new ships are
added to the Great Lakes fleet only rarely.
9) Q: What is meant by "BAU" on page 1-12 of the report.
A: BAU stands for "Business as Usual."
10) Q: Sulfur limits are only supposed to be imposed in US waters (NA EGA), are some of
Canadian waters considered NA EGA?
A: NA EGA are defined in an amendment to ANNEX VI, which defines the outer limit of
the area. In the C3 rule, EPA clarified that the EGA applies to US internal waters,
including waters adjacent or emptying into the EGA and the U.S. portion of the Great
Lakes. EPA's study assumes vessels use EGA fuel on the entirety of the Great Lakes.
However, it is up to the Canadian Government to determine how the EGA requirements
will apply on their side of the Great Lakes.
11) Q: In what part of Chapter 2 does EPA identify stakeholders?
A: Stakeholders are identified in an Appendix to Chapter 2. EPA invited a wide group of
stakeholders to a workshop on the Great Lakes study, consisting of all those individuals
and groups that were on EPA's public outreach list from the Category 3 marine diesel
engine rule, the loco/marine rule, and other marine-related actions. Only a small subset
of that invitational list participated in the workshop, however. Nevertheless, the main
marine trade associations participated, as well as many ship owners and purchasers of
marine transportation services. EPA will provide Appendix 2B and the workshop
attendee list to RTI for sharing with the peer reviewers.
12) Q: How was the rail-route chosen in a GIFT model?
A: Rail-route was chosen based on shortest distance between the origin and destination
points.
C-5
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13) Q: How were the GIFT model input costs (such as freight rates) calculated?
A: Key inputs, such as freight rates, transfer costs and port conditions, were obtained by
contractors who performed the analysis, Corbett and Winebrake, from Chrisman Dager, a
transportation expert consulted during the study. Fuel prices were EPA-specified.
14) Q: How were the routes for Great Lakes study developed?
A: The selection of baseline routes is described in Section 2.4 of the Study. Stakeholders
identified origin/destination pairs for at-risk routes. EPA selected 16 O/D pairs and
provided additional details with respect to actual sites. After sharing this final list with
stakeholders, EPA provided this list to the Contractor, who developed the exact routes
using the GIFT model, by maximizing the use of the Great Lakes over the route. The
alternative all-rail route was determined by minimizing the distance between the origin
and destination. Corbett and Winebrake performed due diligence, such as making sure
that rails exist and operational for the routes identified for rail transportation scenarios.
15) Q: There is a route, originating in Europe, shipping steel coils, which are later dropped
off at Cleveland and Detroit. The ships then get loaded with grain, and head back to
Europe. The shipping is done by FedNav located in Canada. This route can be alternated
by shipping cargo to NYC, and then distributing to mainland by rail. Is there a specific
reason this route is not added?
A: No, this route was not identified to EPA by the stakeholders through the process
described above in Q14 and Section 2.4. The reviewer should feel free to add this to his
comments.
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Appendix D: Cover Letters
Particulars Page
I Cover letter from Dr. Michael Belzer Dl
2 Cover letter from Dr. Bradley Hull D2
3 Cover letter from Mr. James Kruse D3
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SOUND SCIENCE
Sound Science, Inc.
2281 TraverRoad
Ann Arbor, MI 48105
Sound.Science@me.com
Lauren Steel e
U.S. Environmental Protection Agency
Office of Transportation and Air Quality
2000 Traverwood Dr.
Ann Arbor, MI 48105
January 12, 2011
Greetings:
The documents that I received from EPA (or RTI International) were a letter containing the
charge questions and the study report by ICF International and Energy and Environmental
Research Associates, LLC.
I reviewed all of the documents that I received in developing my expert opinion as contained in
the "Peer Review, Economic Impacts of the Category 3 Marine Rule on Great Lakes Shipping"
submitted on December 1, 2010.
I have provided a brief bio along with this report, as requested in the Charge Letter.
I declare that there are no real or perceived conflicts of interest concerning my involvement in
this review for the U.S. Environmental Protection Agency.
I have worked approximately 50 hours on this report.
Best regards,
Reviewer Michael H. Belzer
D-l
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Bradley Z Hull PhD
Associate Professor and Reid Chair
Department of Management, Marketing, and Logistics
John Carroll University
20700 North Park Blvd
University Heights, OH 44118
bzhull@jcu.edu
office: 216-397-4182 cell: 216-973-4118
Peer Review of "ECONOMIC IMPACTS OF THE CATEGORY 3 MARINE RULE ON
GREAT LAKES SHIPPING," Assessment and Standards Division, Office of Transportation
and Air Quality, US Environmental Protection Agency
Bradley Hull's background for this peer review process:
1. Professor at John Carroll University for the past 12 years, teaching/researching logistics
and supply chain courses/issues.
2. University of Pennsylvania (BA in Mathematics), Stanford University (MS in Operations
Research), and Case Western Reserve University (PhD in Operations Research)
3. During a previous career at British Petroleum, I developed mathematical models of
logistics systems. These models included linear programming models for oil and
chemicals movements, mixed integer programming models for ship and pipeline
scheduling, and several computer simulations of the Alaskan crude oil supply chain.
4. At British Petroleum, I was a logistics/supply chain manager (in a variety of positions)
during most of my 28 year tenure. For BP Chemicals, I managed freight expenditures of
$200 million per year and for BP Oil I managed freight expenditures that were greater. I
have managed rail and truck movements, a fleet of 2000 rail tank cars, operated tows on
the Mississippi and the Gulf Coast, shipped potash on the Great Lakes, moved a lot of
Alaskan and other crude oils by ship and pipeline both internationally and in the US,
stored and moved chemicals through Europe and Asia as well as domestically, and started
a private trucking company. I have extensive experience both operating logistics systems
and negotiating rates with carriers.
5. I have a strong interest in the transportation infrastructure of the Great Lakes/St
Lawrence, and completed a year-long project "Northeast Ohio Logistics Infrastructure"
in late 2009 for NEOTEC (Northeast Ohio Trade and Economic Consortium).
6. I consulted for the Port of Cleveland for over a year to help them develop new
waterborne business on the Great Lakes.
7. I have hosted three conferences on the John Carroll University campus in the past two
years - two of which were titled "Great Lakes St Lawrence Marine Highway - Fitting the
Pieces Together" (which had a water focus) and one titled "Northeast Ohio Transport
Infrastructure Study" (which had a rail focus). The conferences brought together many
stakeholders (shippers, carriers, ports, and government officials) of the Great Lakes and
Northeast Ohio to generate business opportunities.
I have no real or perceived conflicts of Interest. I grew up on the Great Lakes and I just want the
best of all things for the Great Lakes and our environment. I sincerely thank you for the
opportunity to comment. I spent approximately 150 hours to prepare this review.
D-2
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To: Lauren Steele
U.S. Environmental Protection Agency
Office of Transportation and Air Quality
2000 Traverwood Dr.
Ann Arbor, MI 48105
From: C. James Kruse
Texas Transportation Institute
Texas A&M University System
701 N. Post Oak, Suite 430
Houston, TX 77024
Email: j-kruse@ttimail. tamu. edu
January 12,2011
Dear Ms. Steele:
The documents that I received from EPA (via RTI International) were a letter containing the
charge questions and the study report by ICF International and Energy and Environmental
Research Associates, LLC. I reviewed all of the documents that I received in developing my
expert opinion as contained in the "Peer Review, Economic Impacts of the Category 3 Marine
Rule on Great Lakes Shipping" submitted on December 1, 2010.
I declare that there are no real or perceived conflicts of interest concerning my involvement in
this review for the U.S. Environmental Protection Agency.
I spent approximately 40 hours while performing this review.
Best regards,
C. James Kruse
Director, Center for Ports & Waterways
Texas Transportation Institute
D-3
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Appendix E: Review Reports
Particulars Page
I Review Report from Dr. Michael Belzer E1-E5
2 Review Report from Dr. Bradley Hull E6-E22
3. Review Report from Mr. James Kruse E23-E28
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Review-1 by: Dr. Michael Belzer.
Peer Review, Economic Impacts of the Category 3 Marine Rule on Great Lakes Shipping
Dr. Michael H. Belzer
Wayne State University and Sound Science, Inc.
January 5, 2011
My overall impression of the assessment is that it is comprehensive and exhaustive and generally
very well executed. From an economic perspective, it should not even be necessary to prove that
transportation mode shift, source shift, and production shift would not occur. That is, a
benefit/cost analysis would seek to demonstrate that the policy has a net benefit to society and
this report shows that it achieves this benefit.2 For the purpose required in this evaluation - to
determine whether transportation mode shift, source shift, and production shift would occur - it
meets the standard quite clearly. According to the text on page 1-7, the benefits exceed the costs
by between 30:1 and 100:1.
To be very specific, benefit/cost analysis would determine whether the full benefit of the policy
would exceed the full cost. If the higher cost of fuel resulted in a net cost that exceeded the
health and climatological benefit of reduced environmental pollution, then there might be an
issue. However, I have been informed by the EPA that the health effects of higher pollution due
to lower grade fuels, and the costs of those effects, are not contested; that is, the amount of health
risk and the cost of that risk is not in dispute. I do not see reference to climate-change issues in
the chapters under review: Executive Summary and Chapters 1 through 3, inclusive.
With respect to mode, source, and production shifts, from the economic perspective, if the higher
cost of fuel causes customers to source their products more nearby, then the products must be
close enough substitutes that they should not travel such distances in the first place. In other
words, if close substitutes do not shift closer then society must be subsidizing excessive freight
transport distance, which would be bad public policy because the economics of the move would
not pay the full cost. The researchers find that even those shifts do not occur, so the case is moot.
Especially whether the product is iron ore or Michigan stone that is high in calcium carbonate,
the product is sufficiently unique that it does not provoke a shift.
Incidentally, the paper makes reference to a possible disintermediation between raw iron ore and
scrap steel. From my understanding of the steel industry, steel mills that use iron ore generally do
not use scrap, and vice versa. That is, scrap mills generally do not require the resources that
basic steel requires so they can be built farther from iron ore sources anyway. I do not believe
that basic steel uses scrap either, so their incentives to relocate are even smaller than the report
suggests.
See Committee for Study of Public Policy for Surface Freight Transportation. 1996. Paying Our Way: Estimating Marginal Social Costs
of Freight Transportation. Washington, DC: Transportation Research Board of the National Research Council; National Academies
Press.
E-l
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1) Clarity of the presentation
The executive summary and introductory chapter lay out the problem clearly. Chapters 2 and 3
get more complex, but it still is clearly written with few exceptions. For those who wish to get
into the underlying methodology, which was not required for this review, the extensive appendix,
which is the report written by the EERA consultants, amply documents the processes.
2) The overall approach and methodology
One might quibble with the sampling design for the sixteen cases because they were not drawn at
random from among the possible cases, but these cases were selected from among the 50 cases
suggested by those who had objected to the rule and who were concerned that these shifts would
occur, so the selection process was biased conservatively at the outset. That is, since the cases
were provide by the stakeholder community as possible instances in which these shifts would
occur, we would expect that evidence would tend to support the contention that shifts would
occur. They did not.
These cases had been recommended by the private sector objectors because it would have been
impossible for the EPA to identify the population of all possible routings. However, at least one
and perhaps two of the cases chosen were not apropos of the study because either alternative
routes just did not exist or the short route leg on the Great Lakes suggested something else was
going on. This could suggest that perhaps the EPA should have selected the sixteen cases they
chose at random from the 50 cases available to them, but the chance of having been chosen
would have been one in three, reducing the likely validity from the random draw. With the
results so strongly repudiating the notion that the shifts would occur, it is unlikely that the
selection used would have yielded much different results from a random draw.
It appears that the EPA selected these cases systematically in an attempt to fairly represent a
cross-section of trips about which the private sector was concerned. One might also be
concerned, however, that the EPA selected these cases systematically to identify O/D pairs that
would least likely to trigger the shifts. While the critique can be made, it is a thin reed because
the results so strongly refute the contention that transportation mode shift, source shift, and
production shift would occur from the higher fuel cost. The only case studied that might support
this contention is the odd case in which coal travels almost as far on rail in the rail diversion case
as in the default case, and unique circumstances must allow this route choice in the first place. I
discuss this below.
3) Appropriateness of the datasets and other inputs
The datasets used appear to be accepted by both the EPA and the shipping community. They
appear to be the most appropriate ones for this situation. The data and methods appear to have
consensual agreement.
4) The data analyses conducted
The first analysis determined whether mode shifts would occur. There is no evidence to support
this contention. Researchers are correct to conclude that the increment of higher cost due to the
fuel change is so small that it is lost in the noise of price changes. Indeed, the cost of some of
these raw materials, most notably iron ore, coal, and grain, have increased dramatically just in
the last year because of global demand for raw materials such as iron ore and coal, and weather-
related pressure on grain prices due to the drought and fires in Russia in 2010. US public policy
E-2
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that subsidizes corn production for ethanol has driven up grain prices even further. The
additional fraction of a percent of cost for cleaner fuel is a very small increment - one that by
itself would not be noticed in final price because other factors, such as the foregoing, put much
greater pressure on price. The recent flooding in Queensland may have a greater impact on
commodity prices than the cost of lower sulfur more refined fuel.
5) Appropriateness of the conclusions.
The conclusions drawn are appropriate based on the information analyzed. There is no question
that cost increases due to this fuel will not cause the feared shifts.
Detailed comments, by page and section.
1-4:1 am skeptical that the Great Lakes waterways would be an economically acceptable routing
for intermodal short-sea container shipping. No container ships have been built for the Great
Lakes and they probably could not hold more than two hundred containers, so this would only
work for bulk shipments by container. No container ports exist on the Great Lakes. Containers
more likely will travel by rail.3
On pages 1-14 through 1-25 the authors present an annotated literature review. The review is
critical and evaluates the relevant previous studies. However, they uncritically report in section
1.7.1.1 theMNDot 1991 study having a purpose to "demonstrate"... that policy decisions ...can
have important human health and welfare impacts". That study should have been "evaluation",
not "demonstration", but that's not the problem of the authors of the present study.
On page 1-16 they review the MARAD 2006 study that evaluates short-sea shipping on the Great
Lakes. This evaluation is sketchy and the fact that this shift has not happened, even as fuel price
spikes made truck transport much more disadvantageous, suggests they may still have it wrong.
I would suggest that the shift will be from truck to rail before it ever gets to short-sea shipping.
The cost of time is significant and rail is much faster. I do not know if this study reviewed the
Thorn chick et al. study cited here.
1-24: In paragraphs 2 and 3 on this page, the report repeatedly refers to "realistic" and "normal"
prices for fuel. I think it is difficult to forecast pricing and define normality in fuel pricing. Yes,
fuel prices jumped far out of the norm by the summer of 2008, but the high fuel prices were
speculatively driven and contributed to the ensuing recession. Fuel prices may have been
unrealistically low before that point and may be starting to approach those 2008 levels as
developing countries' demand for fuel continues to rise in spite of the recession in the
industrially developed countries.4 I would suggest using an objective standard based on a trend
analysis of real historical prices and live with the consequences.
Thomchick, Evelyn A., Gary L. Gittings, John C. Spychalski, and Christopher M. Cassano. 2003. Analysis of the Great
Lakes/St. Lawrence River Navigation System's Role in U.S. Ocean Container Trade: Pennsylvania Transportation Institute.
www.mautc.psu.edu/docs/PSU-2002-04.pdf
4 SeePfeifer, Sylvia. "Oil price 'enters danger zone'". Financial Times USA. Wednesday, January 5,2011, page 1. This story
highlights the fact that crude oil at this time is nearing SlOO/barrel, even during a time of great global economic uncertainty.
E-3
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1-25: The authors are correct to argue that "monetized health benefits are most likely
significantly underestimated." This is the hardest measure to develop. However, it is important
also to emphasize that fuel prices and restrictions affecting air quality affects all modes,
including truck and rail, which already have borne the cost of shifting to low-sulfur fuel. If the
maritime sector were not required to use clean fuel, we might risk subsidizing that sector over
the others, contributing to economic inefficiency and social inequity.
2-2: It would have been helpful if the researchers had attempted to find out the coal-supply route
from the paper mill in Green Bay. Perhaps this was not within their scope or authority, but I
suspect that the transfer costs in time and money would not make it worthwhile to make the long
part-rail/part-ship route. It also is possible that the route through South Chicago is inexpensive
because trains handle so much volume from Elk Creek to South Chicago that the ton-mile cost is
lower via that combined rail/marine route than via the direct rail route.
2-6: The broadest type of economic model, a macroeconomic model such as that incorporated in
REMI and IMPLAN, would be the best to do a full benefit/cost analysis. This was not required
for this particular study and thus it was not necessary to incur the additional cost, as mode,
production, and source shifts were in question in this case.
2-7: As discussed above, this report does not clearly specify the basis on which the EPA chose
the sixteen routes among the fifty routes provided to them by stakeholders. Except generally for
an attempt to incorporate all four broad commodity groups, the basis for the selection of these
particular sixteen O/D pairs is never explained. The choices are not random, which normally
would be preferred.
2-8: Did the EPA try to determine the specifics underlying the O/D pairs as discussed in Table 2-
2? It would take some digging and investigation, along with cooperation, to determine what is
going on for each case.
2-14: I wonder if they aren't using a per-barrel oil price that is too low to be "normal"? Using
the 2007 price has the disadvantage of capturing a non-random point in time rather than a trend,
and I would suggest an averaging or trend-based method across ten years or so.
2-15: With respect to last full paragraph in 2.6.3,1 think that though the tradeoffs in fuel prices
between marine and land-based distillate probably would remain constant, as stated in this
section, but the tradeoff between the two might not be linear. As the price of oil goes up, the
greater efficiency of using the marine mode might provoke shift of freight to marine over rail;
this would happen at the extremes of price when the cost of fuel is so great that it begins to trump
the cost of intermodal handling needed to shift as much to marine as possible. This, however,
would not change the conclusions of the analysis because it would drive freight toward, not away
from the marine mode; it would not favor truck or even rail.
While developed countries continue to have stagnant growth, many developing countries, especially in Asia, are experiencing
rapid growth in demand for oil.
E-4
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3-1: While I understand that mode, source, and production shift is the issue to be addressed here,
from the economics and environmental perspective, these shifts are entirely acceptable and in
many cases more efficient. In fact, if for some commodities the price of movement may be too
great to support the move, and the sale and movement of the commodity would be foregone.
From an economic perspective, this is an appropriate outcome. No matter what moon rocks are
worth, the cost of obtaining them is prohibitively high for commercial purposes.
3-4: The current cost of diesel fuel is around $3/gallon, plus taxes, and as noted above, many
analysts anticipate it will continue to rise even in the short term despite global economic
uncertainty.5 This just emphasizes the value of using a long-term price trend on which to base
estimates. However, as long as fuel prices rise, systematic shifts likely will favor maritime over
rail and rail over truck, so a low price probably leaves a very conservative result in this case.
3-13: Very technical clarification in first full paragraph. I would say "iron and steel sector"
instead of "this sector". Last full paragraph comment: the small increased price for steel would
be absorbed in down-market competition, so you are correct to conclude that it's negligible.
Commenting also on the table, and repeating what has been said above, for all these commodities
except perhaps stone, the marginal increase in cost for the transportation service will be
swamped by the rising costs of the commodity globally.
3-18: Regarding the first paragraph and repeating what I discussed above, the markets for iron-
ore-based production and scrap-based production are different. I am pretty certain that the
crossover is negligible.
3-20: Top of page, last sentence in paragraph, refers to assumption that marine carriers have
empty backhauls. I haven't seen a reference to this before. Is this verifiable?
3-22, Table 3-11: It would be helpful if vessel emissions could be portrayed and measured the
same way as this. Seems like the calculations are in different denominators and a translation
must exist for this. It is hard for a reader to make the judgment without it.
Pfeifer, Sylvia. 2011. "Oil price 'enters danger zone'". Financial Times (USA), Wednesday, January 05, 1.
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Review-2 by: Dr. Bradley Hull.
Bradley Z Hull PhD
Associate Professor and Reid Chair
Department of Management, Marketing, and Logistics
John Carroll University
Peer Review of "ECONOMIC IMPACTS OF THE CATEGORY 3 MARINE RULE ON
GREAT LAKES SHIPPING," Assessment and Standards Division, Office of Transportation
and Air Quality, US Environmental Protection Agency
GENERAL COMMENTS ON THE STRUCTURE OF THE ANALYSIS
The study takes a two pronged approach to the HFO/MDO issue. First, it develops a cost
comparison of all-rail versus rail/water routes for sixteen origin destination pairs. The goal is to
establish that a switch from FIFO to MDO will not result in a significant modal shift to rail.
While the results of the analysis strongly suggests this result, it is not conclusive. A stronger
argument is required. Here is why: The study utilizes a shortest route all-rail route for the
origin/destination pairs, and also utilizes a cost based (I think) approach to compare the all-rail
versus rail/water alternatives. In reality, railroads often don't use the shortest route, and don't
use cost based methods to calculate their rates. Rather, they calculate their freight rates based on
"differential pricing" methods (charging what the market will bear). In fact, railroads are
famously known for using differential pricing to compete for waterborne traffic. Thus, though
the analysis strongly indicates minimal modal shift to rail, the reality could be different. If you
proceed with this analysis I urge you to add a validation step in which you select some of the
sixteen origin/destination pairs, meet with the relevant stakeholder, and delve into details of the
actual movements.
The second prong of this two pronged approach is important and necessary because it addresses
the wider issue of industry competition - taking the study beyond the bounds of strictly modal
competition. It takes a Great Lakes perspective of the steel, stone, coal, and power generation
industries and evaluates the impact of the higher priced MDO on the ability of these industries to
compete. Overall, I feel that each of the industry analyses can be improved (later in the
document you will see detailed comments on each), and that more work needs to be done. The
analysis should further include a look beyond the Great Lakes especially for the steel industry,
due to its global nature.
I encourage the EPA to consider the following approach to the steel industry analysis: develop a
linear program that models the mills on the Great Lakes and elsewhere and optimizes flows from
mills to market. Next, perform a sensitivity analysis on the water transport costs to determine the
extent to which MDO usage shifts steel manufacturing away from the Great Lakes to other steel
centers. (The petroleum industry uses similar models to direct flows of crude oil from multiple
origins through multiple waterborne and pipeline routes, to multiple refineries. It uses similar
models to optimally route refined products from refineries to markets -1 developed and worked
with several of these models at BP). I am concerned that increased MDO costs might result in
E-6
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global steel companies shifting production (to greater or lesser degree) from Great Lakes mills to
their other mills. With the depressed state of the "rust belt" we don't want to lose any more jobs.
A further factor to include in your steel industry analysis: Steel imports from Northern Europe to
the Midwest are highly dependent on grain backhauls (steel ships need a grain backhaul to justify
the inbound steel movement). To the extent that MDO usage reduces the availability of grain
backhauls while simultaneously increasing the cost of steel fronthauls, steel movements into the
Great Lakes become less economic. Eliminating the steel coil imports weakens the steel
industry, because the European made steel coils are purchased for specialty uses.
In addition to the two pronged approach described above, I feel strongly that the EPA should add
a third prong: the impact of MDO usage on the potential all-water imports and exports through
the Great Lakes/St Lawrence - this is potentially a significant growth industry for the Great
Lakes.
Here is the business opportunity for Midwestern cities located near the Great
Lakes: The St Lawrence Seaway lies geographically on a straight line between the Midwest
(large consuming population and industrial heartland), and Rotterdam/Antwerp (two of the
largest world ports). This route has been cost effectively used by the steel industry for the past
50 years for importing steel coils from Northern Europe, but it is rarely used for general
merchandise. (I will discuss the reasons with you if you wish) Based on the minimum mileage
character of this straight line and the low cost of all-water transport, this route could benefit a
host of imports/exports. As such, it is widely recognized as a potential growth business. Great
Lakes ports, shippers, and carriers are studying ways to initiate service.
This is a MAJOR OPPORTUNITY for the EPA to reduce emissions in the Midwest
and East Coast: As a large manufacturing and consuming region, the Midwest imports and
exports considerable quantities between Midwestern cities and Europe. The routes currently
used, though, require an overland leg by rail or truck (generating major emissions) between the
Midwest and either Montreal or US East Coast ports, and then a waterborne leg between
Montreal or East Coast ports and Rotterdam/Antwerp/Europe. If imports/exports were
channeled through the all-water route, we would reduce emissions in the Midwest and East
Coast, save transport costs, and take trucks off the roads. This would have a significant positive
impact both to the Great Lakes as well as the East Coast environment. The Rhine River is an
excellent example of such a working system, because the Rhine handles much of Europe's
commerce, reducing overland journeys through Europe by truck and rail, and significantly
reducing emissions throughout Europe.
Relevance to the current EPA study: Montreal successfully competes with the US East
Coast ports for deliveries to the Midwest, and approximately half of Montreal's imports are
destined for the US Midwest. Many Great Lakes ports, shippers and water carriers are
evaluating the all water service to Europe described above, (few such services exist and I would
be happy to discuss this further with you). Will the higher cost of MDO discourage the
development of these many opportunities, giving further advantage to the high emissions
overland routes to East Coast ports and Montreal?
In summary, with the internal Great Lakes industries in decline, we should encourage
growth of new business opportunities, such as import/export - especially since this growth
simultaneously cleans up the environment. The C3 study should address this topic.
RESPONSES TO THE CHARGE QUESTIONS PLUS ONE MORE
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1. Clarity of the Presentation: The study is well written, but I have a few suggestions for
"framing the problem," especially in the opening pages, to enhance its clarity for a
general audience.
a. State clearly that the study addresses Sulfur limits. In reading the study it took me
awhile to understand this, because the study includes details on NOX and
Particulates. My understanding now is that NOX and Particulates standards were
previously justified and ruling has been made - they are secondary to Sulfur for
this study. In my initial reading, I had felt that the NOX and Particulate limits
were a subject of the analysis as well, and I wondered why the analysis was on
sulfur only.
b. Demonstrate that ships are a major contributor to sulfur problems in the Great
Lakes/St. Lawrence region. Your study hasn't done that in a convincing way.
Convince the audience. Provide a chart that shows ship emissions versus sulfur
emissions from all the other polluters: trucks, railroads, automobiles, and
manufacturers in the Great Lakes area. Convince the audience that adopting
MDO will have a significant positive impact on the Great Lakes environment.
Demonstrate that despite the fact that a large percentage of ship emissions occur
in unpopulated areas, ships are major polluters in populated areas compared with
shore based emissions sources.
c. Clarify whether the Seaway between Montreal and the mouth of the mouth of the
St Lawrence River (a 500 mile long leg which exclusively runs through Canada),
will require 100% MDO. I assume that this section of the River will continue to
use HFO. Here is why: Montreal aggressively competes with US East Coast
Ports to handle imports/exports for the US Midwest. Since the St Lawrence River
downstream of Montreal runs exclusively through Canada, the many miles of
using 100% MDO would negatively impact Montreal's competitive position - an
undesirable result from a Canadian point of view. I encourage you to address the
issue and state what you feel is the most likely assumption, so that readers can
better understand the areas of impact of the C3 Ruling. (As a parenthetical
comment, both the Montreal and US East Coast port routes to Midwestern cities
involve overland, high emissions truck/rail legs. The lowest emission route is all-
water through the Seaway and the Great Lakes to Midwestern cities. Thus, it is
important to protect the all-water route)
d. Please state the jurisdiction of the C3 Rule more clearly. I assume that the C3
Rule legally covers all ships travelling through or loading/unloading in US waters.
If so, please state that. Due to the more-than-a-dozen border crossings, I assume
that it de facto covers all ships travelling through Canadian waters in the Great
Lakes as well. If so, please state that too.
e. Do sufficient quantities of MDO exist to support the C3 ruling? I assume so, but
did not see this question addressed or analyzed in detail. This point should be
cleared up to further establish the feasibility of the C3 Rule (and having worked in
the petroleum industry I can offer some suggestions if you wish).
f. In the body of the text please distinguish between "rates" and "costs." Your use
of these terms was confusing at times and they seem to be used interchangeably. I
am fairly certain that your analysis compares the costs of all-rail, versus the costs
of rail/water transport. Unless you are adding a profit margin to these figures,
please continue to refer to them as costs rather than as rates. This confused me
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since railroads set their rates based on negotiations, using "differential pricing" or
a "value of service approach." (in fact, this is the method by which they famously
compete with water transport) Their freight rates can and often differ widely from
their costs.
More clearly defining the scope of the issues and the jurisdiction of the C3 Rule on the
first pages adds clarity to the remainder of the presentation. Also, clarity is enhanced in
the body of the text through items e and f above.
2. The overall approach and methodology need further clarification:
a. The EERA approach compares a minimum distance all-rail route with a minimum
distance rail/water route. The rail routes are calculated using a model of existing
rail tracks. Please check these routes for feasibility: are they heavily travelled
trunkline routes, and do they involve multiple railroads? This is important since
the routes are theoretically calculated rather than based on knowledge of actual
routes being used.
While the shortest route is appealing, railroads often don't use the shortest
route. Railroads want a long haul to gain economies of scale, and the long haul
may not be the shortest, and may even be circuitous. In fact I have seen railroads
utilize extremely circuitous routes just so they can preserve the long haul instead
of having to share revenues by incorporating a second railroad. Also, railroads try
to shift traffic to their most heavily used lines for economies of scale, density, and
service. These heavily used lines may detract from the shortest route approach
as well.
b. Are the routes from "item a" above evaluated on a "cost of service" or "value of
service" basis? (I think that you are using "cost of service" but please clarify) A
more clear definition of the calculation method and components is required.
"Cost of service" builds up costs from the component operating costs of railroads
and ships. It would include such factors as cost of cost of the train operating
costs, winter layup for ships, tugs, lock fees, and pilot fees in calculating an
overall voyage cost. Value of service would compare existing freight rates
(which are very difficult to find due to their proprietary nature), and competitive
positions of the railroads. Cost of service seems more appropriate for
theoretically calculated routes. The EERA study uses rate/cost information from
Chrisman Dager. It is important to understand the source of his information and
whether it is cost or rate based. See references to Dager in part 3 below and on
my comments about the EERA report. Further documentation of Dager's
technique and information source is needed. It would be good if his input figures
could be included in an appendix.
c. Railroads use "value of service" or "differential pricing" to value their services.
In fact, on the Great Lakes and Mississippi River systems, they are known for
drastically reducing their rates to attract business away from the water. This issue
should also be addressed in the analysis, and it puts the entire concept of "cost of
service "pricing in question for this analysis.
3. Appropriateness of the of the datasets and other inputs:
a. Dager provided many of the underlying rates/costs for the analysis. Are they rates
or are they costs? If the analysis is cost of service, what component costs are
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included and what was the source of the information? There are many such costs
for both railroads and ships. For ships on the Great Lakes, costs include, US Flag
hire cost, US crew cost, pilot fees, tug charges, lock delays on the Seaway,
wintertime layup costs, and many more. Costs should be explicitly enumerated in
the text. Similarly, if the analysis is based on value of service, how is this
estimated (rail and ship rates are contractual and not published) and what is the
information source (actual rates are very difficult to find)? Much better definition
of his data set is required.
4. The data analyses conducted:
a. The EERA study provides a straightforward analysis of the Dager information.
b. Regarding the stone, coal, and steel analyses of Chapter 3,1 would like a more
thorough analysis done for coal, I felt the crushed stone analysis was quite good
though it needs a review of its underlying data sources, and that the steel analysis
and supplementary analysis needs to be revised to incorporate a more global
perspective.
5. Appropriateness of the conclusions:
a. The EERA study addresses the impact of 100% MDO on internal Great Lake
movements. With the Great Lakes industries on the decline, the study needs to
consider the global marketplace and present and potential import/export
opportunities, which is, after all the growth opportunity for Great Lakes as well as
the rest of the economy.
b. Since the EERA model is theoretical and actual routes and rates may differ, I
would encourage a final validation of the model by selecting a subset of the
sixteen scenarios and interviewing shippers/carriers for their input and
perspective.
c. The EERA study is suggestive but not conclusive. First the all-rail versus
rail/water comparison is based on a cost model that may or may not be followed
in the real world. Railroads and ship price their services on value of service
instead of cost of service. This is especially true when they compete for
waterborne business. Regardless of the fact that the EERA cases show that Great
Lakes ships can absorb the increased cost of MDO without significant modal
shift, the higher priced MDO can still result in less business overall, as
manufacturers shift production away from the Great Lakes toward lower cost
supply sources.
d. The stone, coal, and steel analyses of Chapter 3 are also not conclusive.
i. Stone shift analysis is stated as problematic, even by the authors, due to
factors not included in the analysis. I happen to like the analysis a lot, but
it makes several simplifying assumptions which need to be examined and
validated, such as the use of theoretical transport costs from origin to
destination, the assumption that highways are "straight line", that
Michigan specialty stone replaces local quarry stone on a ton for ton basis,
and that heavy trucks are allowed on US highways. These assumptions
need to be reviewed, but found the analysis otherwise very interesting.
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ii. Coal power is explained in a confusing way and the argument needs to be
expanded. I spent a lot of time reading it, and would like the work done
more explained further in more simple terms.
iii. I would like to see an expanded analysis of the steel industry since steel is
so vital to the Midwest. The first discussion of steel assumes that water
supplied coal is used in steel production, when in reality, the coal
delivered by Great Lakes ships almost always goes to power plants. The
supplementary analysis is more compelling but needs to factor in the need
for grain backhauls and a wider marketplace. Also with the additional
MDO costs added to limestone and iron ore movements along with
additional MDO costs for steel imports and grain backhauls, it seems
conceptually that the combined effect would be a significant negative for
the competitiveness of the steel industry, vis a vis the steel industry
elsewhere.
Impact of global marketplace is not included in the study, but should be included because
it is the "growth business" of the Seaway. The Great Lakes has a significant quantity of
captive business with iron ore, limestone, crushed stone, coal, and internal grain
movement. However, these businesses have been on the decline since before 1990, and
any growth for the Great Lakes/Seaway will necessarily come from increased
import/export. Currently grain is exported (significant quantities this fall!), and steel
coils/slabs have been imported for the past 50 years (using FedNav, Polsteam, and
Wagenborg - none of whom is included in the study). Further, moves are afoot to deliver
international containers to the Great Lakes (the Ports of Cleveland, Toledo,
Erie/Conneaut, Ashtabula are all studying this, and Great Lakes Feeder Lines, McKeil
Marine, and Wagenborg are interested carriers). Since this would create a significant
number of jobs in the depressed "rust belt" and since this business would take trucks off
the road, I believe that it should be included in the study. Here are three components that
should be included:
a. Grain: Grain from the Midwest is shipped abroad via three main routes - by ship
through the Great Lakes/St Lawrence, by rail to the US West Coast for loading to
China, and by river barge down the Mississippi for export from New Orleans. My
understanding is that the route chosen is highly dependent on transport rates, and
small rate changes can have a major impact on choice of route. Would a
requirement to burn MDO both ways on the 2000+ mile journey have a
significant negative impact on the amount of grain routed through the Great
Lakes? Page 7-26 of the study states that 70% of grain on the Great Lakes is
destined for export, so this is an important case to be considered in the body of the
report. Grain is an important export and should be explicitly analyzed.
b. Steel Coils: Steel coils are imported into the Great Lakes in the following
manner. A breakbulk ship (typically FedNav, Polsteam, or Wagenborg) loads
steel coils in Northern Europe for a variety of Great Lakes customers. The ship
then crosses the Atlantic and transits the Seaway to discharge partial cargos at
Cleveland, Detroit, and Burns Harbor. When finished discharging, the ship picks
up a grain backhaul and returns to Europe. Two issues need to be addressed:
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i. If use of 100% MDO on the entire Great Lakes/Seaway route has a
significant negative impact on availability of grain backhauls, will steel
coil imports become uneconomic?
ii. If the use of 100% MDO makes the (fronthaul) delivery of steel coils
through the Seaway less economic, steel coils will likely be diverted to the
East Coast ports for an overland rail/truck leg to Midwestern customers.
(this is an alternative Midwestern route used by steel companies) In this
case, the system generates more emissions from rail/truck. This alternate
route is also considerably more expensive (that's why the all-water route
to the Midwest is preferred) which then reduces the viability of the
existing Midwestern steel companies.
Containers: Containerships transit the Seaway as far as Montreal. At that point,
the containers are transloaded to truck and rail for delivery to Canadian and US
customers. The truck/rail movements generate high emissions. My
understanding is that approximately half of the containers are delivered to the US.
At present there are several moves afoot to extend container deliveries into the
Great Lakes by water, possibly directly from Europe or by transloading containers
to feeder ships or barges in Montreal or Halifax (the Ports of Cleveland, Toledo,
Erie/Conneaut, and Oswego are the interested ports and Wagenborg, Great Lakes
Feeder Lines, and McKeil Marine are interested carriers). Such a service would
reduce SOX, NOX, and particulate emissions because it would replace rail and
truck deliveries from Montreal and the East Coast. Would the 100% MDO ruling
make this opportunity uneconomic?
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DETAILED COMMENTS
The numerous comments below are listed page by page. I boldfaced some of the more important
comments for emphasis.
Executive Summary
Page 10: Define "Category 3" engines in the text, rather than in a footnote, since the study
is about them.
Page 13: I thought that steamships were permanently exempted from the ruling. The text
indicates that a fuel waiver is available only until January 2015. Which is true? Please clarify.
Page 16: Provide more information on which stakeholders were consulted. Stakeholder
buy-in is critical. This section only lists Lake Carriers Assn. and Canadian Shipowners Assn.
That isn't a lot of stakeholders. A full list should be included in the body of the study or in an
Appendix. If the full list is confidential, you should try to characterize the list as best you can.
Chapter 1
At the beginning of Chapter 1, make the case that marine emissions are a big problem in the
Great Lakes and St. Lawrence. This is the reason for having a C3 ruling in the first place.
Present statistics showing that the Great Lakes are a non-attainment region and establish that
marine emissions are a considerable percentage of those emissions. Add a table comparing the
emissions from ships, trucks, railroads, automobiles, and factories showing the relative
contribution of each to our densely populated region.
Page 1-4: Please document the degree to which ships contribute to the air quality in the
region, compared with other emissions sources. From a novice's point of view, the Midwest
economy is depressed, and shipping is considerably off, so with few ships there will be few air
emissions. Also, I would imagine that trucks, rail, and factories contribute a much greater share
than do ships. If possible it would be useful to document this.
Page 1-5: Explain how the US EPA standards can apply to the Canadian Great Lakes ships
of Table 1 -3. I think that EPA standards would apply to US waters, and that EPA standards
would be applied to Canadian ships because of the many boundary crossings they must make.
Page 1-5: The study looks only at sulfur standards in fuel and yet engine changes must be
made to accommodate reductions in particulates and NOX. Please explain the relevance of NOX
and particulates to this particular study, and explain why the cost of engine changes is not
incorporated in the analysis.
Page 1-6: Ocean going salties "carry only a small share of cargo on the Great Lakes." They
are very important though because they represent the growth business for the Seaway, so it is
important to consider them in the analysis. Elsewhere in this document I am recommending that
you evaluate the steel movements of salties. Also there are a considerable number of "salties"
that bring containers as far down the Seaway as Montreal and there are studies that show that
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extending their reach to the Great Lakes is economic. Thus, it is important to determine whether
this ruling will have a significant negative impact on these growth opportunities for the Seaway.
Page 1-7: With steam engines being excluded from the ruling, is it likely that they will be
more heavily used by ship owners so that they can avoid retrofitting Category Three vessels?
Page 1-7: Please confirm that steamships are PERMANENTLY excluded from the ruling or
list any conditions attached.
Page 1-8: North American EGA: Ships transiting the Seaway will travel many more miles
with the North American EGA than will ships travelling from, say, Europe to an East Coast port.
Thus the ruling will fall more heavily on Seaway transits than any other part of the North
American EGA - true or false?
If true, then the main cost increases will be the ships that are either captive to the Great Lakes or
FF ships that transit the Seaway. Thus, both types of ships should be reviewed.
Page 1-9: Add a bullet point describing the Seaway and Great Lakes components of the
North American EGA. (you have bullet points for the other NA EGA components).
Page 1-9: In the summary, or earlier in the text, please be sure to explain how a US EPA
ruling becomes incumbent on Canadian and Foreign Flag carriers. Are they included due to the
fact that they travel through US waters? Are they included only if they unload at a US port? Are
they included because it would be too complicated to track all the boundary crossings?
Page 1-11: Please reconcile the following two seemingly contradictory sentences:
1) "... we excluded Great lakes steamships from the EGA fuel sulfur
requirements."
2) "..allows Great Lakes shippers to petition EPA for a temporary exemption
from the 2015 fuel standards, which can encourage repowering steam engines
to "
Are steamships excluded permanently from the sulfur standards, or only until
2015?
Page 1-12: Please define "BAU" (business as usual) for the general audience.
The remaining pages of the chapter are quite interesting summaries of other studies. I think this
is good to put your study in context, and very useful. I only have one comment on them below:
Page 1-22/23: I think the steel issue is one of extent, rather than one of relocating. A large,
global steel company faces a worldwide demand and meets it with least cost. Thus if one of the
steel mills owned by the global company experiences an increase in its transport cost to market,
that mill will manufacture less, and another lower cost steel mill located elsewhere will
manufacture more. Thus, a GL transport price increase would likely reduce the shipments
"somewhat" rather than result in an immediate relocation. The amount of the reduction is often
measured by a linear program.
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Chapter 2 General (and important) Comment on Chapter 2: I believe that you should include a
category for imported steel coils/slabs in addition to coal, iron ore, crushed rock, and grain,
because there are an appreciable number of steel coils imported into the Midwest from Northern
Europe by ship. (I can fill you in on more details). This would involve a breakbulk ship
delivering steel coils from Northern Europe to the steel companies in Cleveland/Detroit/Burns
Harbor, typically using a three port discharge, with a grain backhaul. This breakbulk ship
voyage should be compared with another similar voyage to the East Coast for delivery to the
same destinations by rail. Midwestern steel companies use both routes. I am concerned that the
need to utilize MDO for the entire Seaway voyage will eliminate the Seaway route in favor of
the water/rail route (which increases emissions and cost).
Page 2-2: Category Three ships must undergo modifications as well as fuel change. I
believe the modification costs were not included in the analysis. What would be the impact if
these were included?
Page 2-2: In Scenario 2, were the mine and paper mill stakeholders approached to try to
better understand the situation? I think this might be a valuable way of validating the modeling
approach, since the modeling approach did not seem to work. I recommend that you get into the
details of Scenario 2 and talk with the shippers and carriers to find an explanation. Without such
explanation, the result casts doubt on the results of the other Scenarios.
Page 2-5: Are the sulfur limits imposed on the Great Lakes/Seaway by EPA any stricter
than those planned by the Canadians, or those planned for the US East Coast ports? Do the
sulfur limits apply downstream of Montreal? What parts of the Lakes and St. Lawrence River
are impacted?
Page 2-6: (IMPORTANT) Since the conversion to run MDO instead of HFO in
Category Three ships is inexpensive, these costs can be effectively ignored. You should
make this point in the analysis, as well as document it, because as you discuss modal shift, I
kept wondering why you did not include the fixed costs of conversion
Page 2-6: By "flag neutral" I assume that the EPA requirements will be required of all US,
Canadian, and Foreign Flag ships operating in US waters in the Great Lakes St Lawrence
Seaway System. Correct?
Page 2-7: How did the EPA identify the stakeholders who provided the 50 O/D pairs? Who
were the stakeholders? How did you winnow the list down to the 16 winners? Please provide a
list of stakeholders either in the text or in an appendix. If the stakeholder list is confidential,
please characterize them to the extent reasonable. The readers would like to know who was
involved.
Page 2-10: I am concerned at the use of the GIFT model to calculate an optimal all rail route.
This is because railroads negotiate rates based on "value of service approach" or "differential
pricing." This is charging what the market will bear, rather than a straight mileage times dollars
per mile calculation. The rate and route also depends on how many railroads are involved and
their individual routes - railroads all want to achieve long haul economics and as such may avoid
a least cost routing that might extend over multiple railroads.
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Page 2-13: The study refers to cost function modeling (which is cost-of-service, as opposed
to value-of-service). Does the analysis strictly compare costs of two alternatives or does it
compare rates? Rates would be more accurate but extremely difficult to accomplish with
accuracy.
Page 2-14: I disagree with Section 2.6.2. I think that since the rail routes used are calculated
a model, that we can't provide detail about the specific types of services. These calculated rail
rates are critical to the results of the analysis. You should expand this one paragraph section to
describ how you calculate the rail rates. Your analysis expects the reader to accept the rail rates
you are publishing - so you need to provide backup as to how you arrived at them.
Page 2-14: For Great Lakes ships, if the study includes cost-of-service, it should include the
cost of laying the ships up during winter, which will increase their costs. It must also include
factors such as tug costs which will be required to position ships alongside docks, lock fees,
pilotage fees which can be quite high, etc.
Page 2-15: You quote that MDO is expected to be 45.5% more expensive than HFO. Is that
figure in $/ton for both MDO and HFO? How does the btu content of MDO compare with HFO?
What is the comparison in $/BTU? I would think that the cost per BTU would be a more valid
comparison of MDO and HFO.
Page 2-15: Please explain what you mean by freight rates. I think that you are building up
the ship, rail and handling costs and adding some percentage of profit. Is this true?
Page 2-15: If this is a buildup of costs, then please provide a list of the component costs. For
ships there are some costs unique to the Great Lakes that need to be included, such as winter
layup cost, tug costs, pilot costs (which can be quite expensive), the high US Flag costs for
maintenance and ops, and tolls - along with the more usual costs. Were these costs included?
Chapter 2, Appendix A
Overall Comment: Chrisman Dager's input is crucial to the analysis, and also undocumented.
Please document his input and how he arrived at it.
Page 7: The study only includes the 16 identified captive Great Lakes cases, but does not
include import/export along the Seaway. Also, no cost of converting engines to handle MDO is
included. If the conversion cost is high it should be included in the analysis, otherwise the
authors should establish that they are too small to bother with (as I think is the case).
Page 10: Other parts of the report state that there are 12 Category Three US Flag Ships, as
opposed to the 8 referred to on this page. My understanding is that there are 12. With only 8
Category Three US Flagged Vessels, 57 Category Three Canadian Flagged Vessels, and
numerous Category Three Foreign Flagged Vessels, the impact of the EPA ruling will fall
mainly on Canadian and Foreign Flagged ships. Will the Canadian and Foreign Flagged ships
require engine modifications too?
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Page 12: With Category Three US Flagged Vessels using HFO, all will require retrofitting. Is
the technology available currently to allow a changeover? The information on Page 13 indicates
that the US Flagged vessels are quite large, so can the changeover present a problem?
Page 16: The no backhaul assumption can make shipping more expensive than the reality with
backhauls.
Page 17: FedNav (Canadian flag and FF ship operator), Polsteam (Polish flag), and
Wagenborg (Dutch flag) are breakbulk operators who operate a significant number of
vessels between the Great Lakes and abroad. FedNav also operates within the Great
Lakes. FedNav, in particular is a major ship operator headquartered in Montreal. They
should be included in Table 14 and in the analysis. These are "salties" that bring steel coils
into the Seaway and export grain.
Page 17: Algoma Central and CSL Group are the Canadian Flag operators who have the lions
share of Category Three ships. Have they issued a position to the study?
Page 18: Most of the cases modeled involve US Port/US Port movement. These require one of
the 8 (US Flagged vessels above, and the study indicates, these vessels are large. Does the ship
analysis in this study account for this fact, or is it using generic Category Three ship figures?
Also, with steamships being exempted, one might expect a shift from using US Flag Category
Three ships to more fully utilizing steamships,
Page 19: Who is Chrisman Dager? He is providing the rail rates for the analysis and we don't
know how he gets them? Does he build them up on a cost plus basis, or does he use knowledge
of the existing rate structure, or some other method?
Pages 19-22: I believe that Chrisman Dager provided figures for
FRBC DTMdsrrcal TCdsr and DTMallrml. These figures are critical to the results of the
analysis and their source and values should be documented.
Pages 19-22: In calculating the at-sea fuel cost, what size ship is used? More generally, the rail
freight is calculated as a $/ton figure times miles travelled, and the ship freight rates were
provided by Chrisman Dager. Who provided the rail costs and how were these rail/ship freight
figures estimated? If the ship rates were calculated on a cost of service basis, how were the old
US Flag ships valued?
Sailing on the Seaway/Great Lakes differs from East Coast sailing, in that the speed limits are
lower, there are several lock fees, wintertime layup costs, costs of US crews and ships, tug fees,
and pilotage fees are an issue. I understand that pilotage fees can cost $10,000 per day for
foreign flag ships. Are these factors included in the analysis? If so, then they are factored in
through the Dager analysis.
For the base case rail route in the scenarios, how do the routes chosen by the model compare
with those actually used?
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Page 23: Of the 16 cases, 12 require a US Flag ship. Are these ship moves presently being made
by a steamship (exempted from the study) or one of the US Flagged Category Three ships? If
the moves are steamship moves, shouldn't they be removed from the study? Are the remaining 4
cases handled by a Canadian Flag ship?
Page 26: How were fuel consumption rates calculated for the ships?
Page 26-29: It is nice to see that careful thought was put into the ship selection for each
Origin/Destination pair.
Pages 24-29: in the Description of Input Assumption Sources please add a paragraph on how
rail rates were calculate and another paragraph for ship rates.
Page 27-28: Rail distances. Railroads prefer one-line-hauls. If the movement is from a mine
served b a single railroad, the origin carrier will want the long haul to achieve economies of
scale. For this reason, rail movements are not necessarily the shortest distance route (and can be
quite circuitous), especially if the shortest route involves two or more railroads. I would be
curious to know if the model used selected a route with three or more railroads - since a route
with more than two carriers is rare.
Pages 29-94
In the scenarios, I assume that the Base Case Route is the one that is actually used. Is this true,
or are either the rail or ship portion generated by the Hawker model?
In the scenarios, does a switch from the Base Case Route to an All Rail route involve more
emissions at destination? That is, for example, does a power plant emit more when it unloads
rail cars or a ship? If this is true, is this factored in anywhere?
Scenario 2's Base Case looks crazy. I recommend that it be researched further. Why would
anyone use a ship in this case? Does the base case reflect an actual movement? Is it possible
that Georgia Pacific cant unload rail cars? Is the actual rail route the same as the one that the
model chose? Is there an equity ownership involved?
Page 97: Please confirm that there is a rail ferry across the St. Lawrence River to Baie Comeau,
QC. I have never heard of such! What are the sensitivities considered?
Chapter 2, Appendix B
Stakeholders were approached at Marine Community Day, an Ann Arbor workshop, the
Canadian Shipowner's Association, and Lake Carrier's Association. These were likely
representatives of the water carriers as opposed to representatives of the coal, stone, iron ore, and
grain industries. Were stakeholders from these industries also included in the analysis? Please
describe the stakeholders in the study.
Chapter 3
Section 3.1: Source Shift (Crushed Stone): I assume that power plants run a combination of
trucked and ship/railed stone? Michigan's high calcium carbonate and low bond work index
seems to be valuable because of its chemical properties for use in scrubbers.
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Further I assume that a ton of Michigan stone, because of its unique chemical properties, must
replace more than one ton of locally quarried stone. If this is true then we would want to
encourage the use of long distance Michigan stone to reduce the number of truckloads of lower
grade local stone. I suggest that someone from the stone industry (or one of the power plants
under discussion) answer this question.
Section 3.1.2: Based on the reading and a subsequent phone call with the EPA here is my
understanding of the method utilized: I believe that we start with the EERA model-calculated
water/rail cost from the Michigan origin to a power plant, and then for this cost we draw a circle
around the power plant to represent a competitive truck radius. This identifies the truck
completion. We then look at expanding the truck radius by the extra ship MDO expenditure. As
a result, the analysis is strongly dependent on the initial rail and ship cost figures provided by
Dager (see my Chapter 2 remarks). The source of Dager's figures needs to be documented.
Water/rail deliveries versus truck deliveries of crushed stone:
1. On Page 3-4, the analysis assumes oversized trucks with 43 ton cargos, rather than
the 20 ton cargos allowed on Ohio's and Pennsylvania's roads (Pennsylvania's
weight limit may even be lower than 20 tons). Is this a valid assumption?
2. The study indicates that "anecdotal evidence suggests that truck rates may be higher, at
$20 per short ton more" than their analysis uses. This large discrepancy should be
reconciled.
If the Bruce Mansfield Power Station is expected to see a partial modal shift, we should find out
if the increased emissions of the additional trucks offset the emissions savings of the C3 ruling.
Also, if the Power Station is outfitted to unload cars with few emissions, a conversion to truck
may increase them. It wouldn't hurt to talk directly with the Station about their supply sources to
validate your analysis.
The study states that the analysis is problematic because of factors not included, as listed in the
last paragraph on Page 3-8. Further, if a shift from rail/water to truck occurs, the emissions
consequences of this shift should be calculated and be included in the analysis. Still further, the
shift analysis hinges on theoretical rail/water cost figures. Despite all that I think this is a very
interesting approach.
Section 3.2: Production shift (Steel and Electric): Low cost steel and electricity
producers typically run at capacity, while high cost producers expand or contract their
production to meet the ups and downs of demand. By increasing the transportation cost of
the inputs, we put the Great Lakes producers into the higher cost category, and as such
they may lose production at times to the lower cost producers. This is probably a difficult
concept to quantify. The classic example of such a potential shift is the new Thyssen-
Krupp steel mill in Mobile. Thyssen has water access to the Midwest for its steel through
the Tennessee-Tombigbee Waterway, and would like compete with the Midwest producers.
As a new state of the art facility, they are high volume, low cost producer. Thus, perhaps
the Great Lakes producer does not go out of business, but he will likely lose some business
at the edge of his/her marketing area to companies such as Thyssen-Krupp.
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Section 3.2.2: Impact on Great Lakes Sector: The Rosebud Mine is used for the lower and
upper bound scenario and applied to electrical generation for the entire Lakes region. This is
certainly a conservative assumption, since lots of the coal used does not even move by water, and
some electricity is not generated by hydroelectric rather than coal. You might mention this in the
text. Further in your analysis, you relate the transport cost increase to reduced electricity
revenues. How do you calculate this inverse relationship? Is it a price elasticity argument?
Your argument in the last paragraph of Page 3-10 is difficult to follow. Please explain more
fully how you separate the transport cost from the EIA figures. My understanding is that you use
average figure for mine costs in East North Central, and subtract it from the "delivered coal
cost." Also, once you have subtracted the transport component, you must have to back out the
percentage trucked and direct railed. Finally in using your baseline case freight rate, you are
using the Rosebud Mine as indicative of the Midwest industry. I somehow am not understanding
your argument or I am overthinking it. Please clarify for me and for others. It would be helpful
if you would add some columns to Table 3-4 so that one could more easily follow your
argument. Also, in the table you distinguish between public utilities versus independent power
generators - but you don't distinguish between them in the text. Please expand this section.
Section 3.2.3: Impact on Steel: I encourage you to add another row in Table 3-6 immediately
above "transp cost increase % revenue" with the $100.2 billion steel revenue figure. This would
add clarity for people like me who like to reproduce the answers.
The argument is compelling but not complete in that you show that the MDO cost increase is a
small percentage of revenues. However, as a percent of transport cost it can be between 8.5-
16.6% for iron ore and 1.2-4.5% for coal. A company is quite capable of changing their shipping
decisions based on such percentage increases in cost (especially for the iron ore percentages). A
company's shipping decisions are typically designed around minimizing manufacturing and
transport costs. Revenues are calculated separately. If a steel company has no choice it may
have to pay the difference, but the steel manufacturing decision may result in producing a bit less
at the now-higher-cost Great Lakes plant and more at another plant.
My understanding is that Great Lakes coal movements are almost exclusively destined for
power plants and almost none is used in steel production (steel companies usually use coke
with is rail supplied). There are a few exceptions, like the Rouge steel plant in Detroit
which occasionally received a shipload of metallurgical coal, but there aren't many. Your
table in this section seems to indicate that Great Lakes ships DO consume coal delivered by
Great Lakes ships. This should be changed.
Section 3.2.4 Steel Production Shift: A Supplemental Analysis: The analysis in this section is
both thought provoking and well done. I would like to ask the author a further question: An
appreciable quantity of imported steel coils enters the Great Lakes from Europe. The steel coils
are typically carried by FedNav, Polsteam, or Wagenborg. When these ships arrive in the Great
Lakes, they discharge partial cargos at Cleveland, Detroit and Burns Harbor. After this, they
pick up a grain backhaul and return to Europe (typically). This is a very cost effective movement
that has been popular for the past 50 years! Competing for this business is a second movement
from Europe. This second movement involves the same ships (or larger ships due to Seaway
E-20
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limitations) delivering coils to the Philadelphia/New York area, where they are offloaded and
shipped into the Ohio/Pennsylvania area by rail.
The question for the author is: to deliver breakbulk material such as steel (but of any type), what
will be the increased cost of Seaway transit to cities such as Cleveland, Toledo, Detroit, and
Burns Harbor. I believe that this question is quite important, specifically because there are many
attempts to deliver international containers directly into the Great Lakes ports from Europe,
rather than delivering them through New York/Phila/Baltimore with an overland freight leg. I
am concerned that a large marine fuel cost increase on the Seaway might delay this shift to
waterborne deliveries, and would like to understand the potential incremental cost per ton of
cargo.
Page 3-15: The statement is made that a trip from Asia to to LA can involve 1700 miles of
North American EGA transit. How can that be? I thought that the NA EGA extended to 200
miles offshore only. If such a route exists, is it likely that that captain would take it when he can
burn HFO for only 200 miles?
Page 3-17: Please check the fuel cost increased for the imported steel case. It seems to me
that if imported steel moves through the North American EGA, all the way (1500 miles or so)
down the St Lawrence and into the Great Lakes, that utilizing MDO at a 40% or so premium
above HFO would significantly increase the transport cost. However, the figures on Table 3-7
do not reflect this, if true.
Page 3-17: Truth is stranger than fiction. Steel does move by water to East coast ports and
then by rail to the Midwest. Norfolk Southern RR has a yard in Philadelphia dedicated to such
moves.
Chapter 6
Page 6-1: Is it possible that we would refit a Category Three ship with a Tier 2 OR a Tier 3
engine?
Page 6-2: hardware costs of fuel switch are $42k-$71k!!! So little!! Say this at the
beginning of the study, so that a reader does not feel that you overlooked what they may think of
as a major fixed investment cost!
Page 6-8: Category Three ships do not need to be repowered under the ruling - only for
company reasons, such as the existing power unit outliving the hull of the ship. This comment is
important and should be more prominent in the beginning of the study.
Page 6-8: The repowering costs mentioned above are up to $600,000 in addition to an
engine replacement. Thus, they are extremely high. Does this pertain to steamships too, and will
this contribute to them being retired?
Page 6-9: Seasonal layups are not included in the freight costs, but would likely be included
in the actual freight rates charged to customers.
E-21
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Page 6-11: PLEASE EXPLAIN THIS PAGE - WHERE DO THE STATS COME FROM?
Page 6-12: IN THE TABLE, ARE THE COLUMNS DIFFERENT SHIPS?
Chapter 7
Page 7-26: 70% of grain on the Great Lakes is destined for export, so this is an important
case to be considered in the body of the report
Grain exports: Grain from the Midwest gets exported either through the Great Lakes, the
Mississippi River, or the West Coast depending on market prices and transport cost. Adding cost
to Great Lakes route will tilt the flow toward the other two routes to a degree. Can you quantify
this? How much additional cost will be added and/or how much MDO versus HFO will be
burned on the inbound and outbound voyages? (with 70% of grain on the Great Lakes destined
for export, this is an important case)
Page 7-54: Please site the specific document from which you obtained Figure 7A-3.
E-22
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Review-3 by: Mr. James Kruse.
PEER REVIEW
ECONOMIC IMPACTS OF THE CATEGORY 3 MARINE RULE
ON GREAT LAKES SHIPPING
Reviewer: C. James Kruse, Texas Transportation Institute
In preparing these comments, I reviewed four documents:
Economic Impacts of the Category 3 Marine Rule on Great Lakes Shipping, Chapters 1,
2, and 3
Comment Letter from Canadian Shipowners Association, dated September 25, 2009
Study of Potential Mode Shift Associated with EGA Regulations In the Great Lakes,
August 2009
EPA's Emission Control Program: Great Lakes Shipping, PowerPoint presentation dated
February 11,2010
I also participated in a conference call on December 21, 2010, that included a representative of
RTI International, several representatives of the Environmental Protection Agency (EPA), and
the other peer reviewers.
In reviewing the document, I focused on methodology, assumptions, and data sources. I did not
attempt to do any grammatical or editing reviews, nor did I attempt to verify that computations
were correct or that stated values were accurately imported from their sources.
For the most part, I found the document to be comprehensive and well-substantiated. Exceptions
are noted in the attached comments. One facet of the analysis that is missing is the concept of
equity. If ultra-low sulfur fuel requirements are being placed on trucks and locomotives, but not
on marine engines, this would represent an indirect subsidy to marine. While the road to
implementation may be markedly different, the requirements should represent a level playing
field to the degree possible.
The charge letter requested that peer reviewers focus on 5 issues. These are addressed in the
following paragraphs.
1. Clarity of presentation
By and large, the presentation is fairly easy to follow. There are a few things that could
be done to improve clarity and readability:
It would be helpful to standardize the units of measures for tons. Specifically, the
document uses "tonnes", "tons", "metric tons", and short "tons" (to name a few).
Either the same "type" of ton should be used throughout the document or the unit
of measure should be explicit each time any variant of "ton" is used.
There are a lot of missing words and extraneous words. Correcting these editorial
problems will help.
E-23
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On page 1-7, paragraph 5, the reference to "Section 1.1.4 below" doesn't make
sense. This is already section 1.4.2.
On page 1-8, the document says "the level of fuels used in an EGA will decrease
from 15,000 ppm to 10,000 in 2010". We are already past 2010. Should it say
"decreased" instead of "will decrease"?
On page 1-9, the document states that France was instrumental in getting the
North American EGA approved. Should it be Mexico? Omitted?
Acronyms need to be spelled out at first usage. For example, on page 1-12,
paragraph 1, what does "BAU" stand for?
On page 1-22, paragraph 1, "go does" should be "goes down".
On page 2-6, the document states that "The purpose of this study is to examine
whether an increase in fuel costs for Great Lakes shipping could lead to
transportation mode shift". This is extremely important in evaluating the analysis.
I think this should be highlighted in the Executive Summary and at several points
throughout the document.
On page 2-9, the document states that "the analysis does not consider the
transportation of the grain from the farm to the silo", but does not state why.
Although the reason may seem obvious, some explanation should be given.
There are two issues with paragraph 1 on page 2-14: (1) The term "net tons"
needs to be explicitly defined. (2) In three instances in this paragraph, the
document states that the vessel weighs a certain amount. This is not true. It
appears that the author intends to refer to "deadweight tonnage", which is the
weight of cargo, fuel, stores, and crews that the vessel can accommodate at its
maximum load linenot the weight of the vessel. This needs to be clarified.
On page 2-16, there is an excellent description of how the freight comparison was
conducted. It might be useful to mention this in a couple of other places (e.g.,
executive summary), but not critical.
In four scenarios shown in Chapter 2, Appendix A, there is no all-rail alternative
considered, but the document does not explain why at this point. In the results
section, the document states, "It was determined that xxxx is not serviceable by
rail. Therefore an All-Rail Alternative Route does not exist". The justification
needs to be included on pages 53, 55, 57, and 59 as well.
What is the unit of measure for costs In Table 3-6? Is it millions of dollars?
2. The overall approach and methodology
The approach of looking at origin/destination pairs that stakeholders thought might be
affected is excellent. Given historical cargo flows, it also appears that the commodities
that were chosen were appropriate. The involvement of stakeholders seems to be
adequate and meaningful. Finally, there was an appropriate trade-off between accuracy
and level of effort. My specific concerns about methodology are the following;
In the CSA study dated August 2009, the authors state that "Transportation costs
while an important factor in determining ore sourcing are often subordinate to
considerations of ore quality, mine ownership, long-term contracts, and overall
corporate benefit". This should be noted in EPA's analysis of the iron ore trade.
In the document I reviewed, the analysis assumes that each voyage will have a
revenue-generating backhaul. I have received a notice that backhauls were
E-24
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considered to be empty in the analysis. If so, I do not have a problem with
backhauls, as empty backhauls will state the worst expected case.
I agree that focusing on the 2015 sulfur limit is the way to go.
I have strong concerns about the methodology used for crushed stone. On page 3-
3, the next-to-last paragraph states "It also does not examine the reason why the
purchasing facility uses stone originating at a much longer distance, requiring ship
transportation, when stone from local quarries may be available." The existence
of this situation in the "real world" invalidates the methodology used in the
document. Users are importing stone from great distances for a reason. To
simply expand the "competitive radius" as the basis of the analysis ignores this
consideration. If the stone is being imported from a specific quarry, then the
inclusion of quarries producing similar quality/grade stone needs to be evaluated
rather than just looking at quarries generically.
Would steel import quotas have an effect on this analysis? If so, that should be
analyzed.
I don't see where the document addresses the concern the shareholders expressed
regarding a potential spike in the price of the 0.1% sulfur fuel if there is a limited
supply in the Great Lakes region when implementation begins.
3. Appropriateness of the datasets and other inputs
In the CSA study, it was noted that neither Ontario steel mill has the facility to
receive coal by rail. It would be wise to verify that the Algoma facility included
in the analysis does have the facility to receive iron ore by rail.
What is the basis or source for the statement on engine specific fuel oil
consumption? How did EPA (or its contractor) derive the assumed propulsion
powers?
The source for the assumption on rail energy intensity needs to be stated.
The current Great Lakes basin profile is for 2008. Table 13 in Appendix A should
be updated.
The sources should be stated for the following assumptions used to develop Table
16 in Appendix A: Auxiliary Engine power, Auxiliary Engine Load Factor in
Port, and Rail Energy Intensity.
In Appendix A, why is it assumed that the vessel will be loaded to 85% of its
capacity? Since this assumption directly affects the unit freight cost, it is
important to justify it.
The Corps' Port and Waterway Facilities data were used to obtain the depth of
each port. I don't know about the Great Lakes, but for the Inland Waterway
System, these data are highly unreliable. Again, since available depth directly
affects the unit freight cost, I would suggest some kind of "truthing" of these
depths.
In Chapter 3, is the assumption of a truck load of 43 short tons valid if the quarry
is located in the United States?
What is the basis for the assumption that 80% of the delivered iron ore cost is the
"iron ore cost at the mine"?
E-25
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4. Data analyses conducted
With the exception of the concern regarding stone quarry analysis noted above, I found
the analyses to be appropriate and adequate. I have no further items of concern in this
area.
5. Appropriateness of the conclusions
The conclusions were appropriate and justified, taking into account the data sources and
inputs employed for the analysis. There were just two instances, where I felt the
conclusions needed to be shored up. On pages 3-5 and 3-6 statements are made to the
effect that "the increase is not substantial compared to the number of quarries already
located within the radius." This is a subjective statement that needs to be validated with
numbers/data.
My comments are attached in tabular format. They are arranged in the order in which the
underlying paragraphs in the document are presentednot in order of importance. The items I
consider to be of greater importance have an asterisk ("*") below the page number.
LISTING OF COMMENTS REGARDING
ECONOMIC IMPACTS OF THE CATEGORY 3 MARINE RULE
ON GREAT LAKES SHIPPING
Page Paragraph Comment
General
General
General
General
General
General
1-7
1-8
5
2
It would be helpful to standardize the units of measures for tons.
Specifically, the document uses "tonnes", "tons", "metric tons", and
short "tons" (to name a few). Either the same "type" of ton should be
used throughout the document or the unit of measure should be explicit
each time any variant of "ton" is used.
There are a lot of missing words and extraneous words.
The involvement of stakeholders seems to be adequate and meaningful.
I don't see where the document addresses the concern the shareholders
expressed regarding a potential spike in the price of the 0. 1% sulfur fuel
if there is a limited supply in the Great Lakes region when
implementation begins.
In the CSA study dated August 2009, the authors state that
"Transportation costs while an important factor in determining ore
sourcing are often subordinate to considerations of ore quality, mine
ownership, long-term contracts, and overall corporate benefit". This
should be noted in EPA's analysis of the iron ore trade.
In the same CSA study, it was noted that neither Ontario steel mill has
the facility to receive coal by rail. It would be wise to verify that it does
have the facility to receive iron ore by rail.
The reference to "Section 1.1.4 below" doesn't make sense. This is
already section 1.4.2.
The document says "the level of fuels used in an EGA will decrease from
15,000 ppm to 10,000 in 2010". We are already past 2010. Should it say
"decreased" instead of "will decrease"?
E-26
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Page Paragraph Comment
1-9
1-12
1-12
1-22
2-5
2-6
*
2-9
*
2-14
2-14
*
2-14
*
2-16
2 A- 13
2 A- 15
2A-24
*
2A-26
*
2A-26
*
0
0
1
1
2
3
1
1
2&3
4
1
1
Table 13
Table 16
2
5
The document states that France was instrumental in getting the North
American EGA approved. Should it be Mexico? Omitted?
At the end of the paragraph, should probably use "metric ton" instead of
"tonne". (See general comments).
What does "BAU" stand for? Please write it out.
"go does" should be "goes down".
I agree that focusing on the 2015 sulfur limit is the way to go.
The document states that "The purpose of this study is to examine
whether an increase in fuel costs for Great Lakes shipping could lead to
transportation mode shift". This is extremely important in evaluating the
analysis. I think this should be highlighted in the Executive Summary
and at several points throughout the document.
The document states that "the analysis does not consider the
transportation of the grain from the farm to the silo", but does not state
why. Although it may seem obvious why, some explanation should be
given.
There are two issues with this paragraph: (1) The term "net tons" needs
to be explicitly defined. (2) In three instances in this paragraph, the
document states that the vessel weighs a certain amount. This is not true.
It appears that the author intends to refer to "deadweight tonnage", which
is the weight of cargo, fuel, stores, and crews that the vessel can
accommodate at its maximum load line not the weight of the vessel.
This needs to be clarified.
What is the basis or source for the statement on engine specific fuel oil
consumption? How did EPA (or its contractor) derive the assumed
propulsion powers?
The source for the assumption on rail energy intensity needs to be stated.
This is an excellent description of how the freight comparison was
conducted. It might be useful to mention this in a couple of other places
(e.g., executive summary), but not critical.
According to what the document says on 2 A- 16 and what the carriers
state, vessels that carry iron ore can also carry grain.
The current Great Lakes basin profile is for 2008. The table should be
updated.
The sources should be stated for the following assumptions: Auxiliary
Engine power, Auxiliary Engine Load Factor in Port, and Rail Energy
Intensity.
Source for specific fuel oil consumption parameters?
Why is it assumed that the vessel will be loaded to 85% of its capacity?
Since this assumption directly affects the unit freight cost, it is important
to justify it.
E-27
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Page Paragraph Comment
2A-27
*
2A-53,
55, 57,
&59
3-2 ff
**
3-4
3-5
3-6
3-9
3-12
3-13
4
2
2
1
3
4
Table 3-6
The Corps' Port and Waterway Facilities data were used to obtain the
depth of each port. I don't know about the Great Lakes, but for the
Inland Waterway System, these data are highly unreliable. Again, since
available depth directly affects the unit freight cost, I would suggest
some kind of "truthing" of these depths.
In four scenarios, there is no all-rail alternative considered, but the
document does not explain why at this point. In the results section, the
document states, "It was determined that xxxx is not serviceable by rail.
Therefore an All-Rail Alternative Route does not exist". The
justification needs to be included on pages 53, 55, 57, and 59 as well.
I have strong concerns about the methodology used for crushed stone.
On page 3-3, the next-to-last paragraph states "It also does not examine
the reason why the purchasing facility uses stone originating at a much
longer distance, requiring ship transportation, when stone from local
quarries may be available." The existence of this situation in the "real
world" invalidates the methodology used in the document. Users are
importing stone from great distances for a reason. To simply expand the
"competitive radius" as the basis of the analysis ignores this
consideration. If the stone is being imported from a specific quarry, then
the inclusion of quarries producing similar quality /grade stone needs to
be evaluated rather than just looking at quarries generically.
Is the assumption of a load of 43 short tons valid if the quarry is located
in the United States?
The last sentence states, ". . .the increase is not substantial compared to
the number of quarries already located within the radius." "Not
substantial" is subjective. I suggest including some numbers here.
See previous comment.
Would steel import quotas have an effect on this analysis? If so, that
should be examined here.
What is the basis for the assumption that 80% of the delivered iron ore
cost is the "iron ore cost at the mine"?
What is the unit of measure for costs? Is it millions of dollars?
E-28
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Appendix F: Additional Documents Provided to the
Reviewers
Particulars Page
1 List of additional documents provided ^.
to the reviewers
_ Document "Marine Community Day _-
Presentation" by Byron Bunker
-------
List of Additional Documents Provided to the Reviewers
1) U.S. EPA Appendix 2B "Stakeholder Interactions" to Chapter 2 of the EPA "Economic
Impacts of the Category 3 Marine Rule on Great Lakes Shipping" (June 10, 2010);
2) Stakeholder "Attendee List" (June 10, 2010);
3) U.S. EPA Marine Control Program: "Marine Community Day Presentation" (February
11, 2010) [Available in Appendix F of this memorandum];
4) "Comments of the Canadian Shipowners Association on the United States Environmental
Protection Agency's proposed rulemaking entitled "Control of Emissions from New
Marine Compression-Ignition Engines at or above 30 Liters per Cylinder" (September 25,
2010 EPA-HQ-OAR-2007-0121);
5) Research and Traffic Group "Study of Potential Mode Shift Associated with EGA
Regulations In the Great Lakes" (August, 2009);
6) U.S. EPA "Control of Emissions from New Marine Compression-Ignition Engines at or
above 30 Liters per Cylinder - Information in Support of Applying Emission Control
Area (ECA) Requirements to the Great Lakes Region" (December 15, 2009 EPA-HQ-
OAR-2007-0121-0586);
7) U.S. EPA "Summary and Analysis of Comments: Control of Emissions from New
Marine Compression-Ignition Engines at or Above 30 Liters per Cylinder" (December,
2009 EPA-420-R-09-015).
F-l
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EPA's Emission Control Program:
Great Lakes Shipping
Marine Community Day
February 11, 2010
Byron Bunker
U.S. Environmental
Protection Agency
F-2
-------
Overview
<> Summary of Marine Engine, Fuel
Programs
<> Congressional Direction
ฎ Great Lakes Provisions
<*> Great Lakes Study
F-3
-------
EPA's Marine Program
<> Comprehensive program
and fuels
- marine engines
U.S. Domestic
Rulemaking
North American
J Annex VI
Standards
_^ . wonn ซme
ฎ Coordinated strategy ECA?^
Clean Air Act
MARPOL Annex VI
Emission Control Area Designation
EGA designation expected to be adopted at IMO March
2010
F-4
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Marine Diesel Engines
ฎ2008 Loco/Marine Rule
ฎNew Category 1 and 2 engines
ฎ Reman Category 2 engines
ฎ2009 Rule/MARPOL Annex VI Amendments
ฎNew engines >130 kW
ฉExisting Category 3 engines
F-5
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Marine Fuels
<> Sulfur and PM
ฎ Fuels produced, distributed in US (CAA program)
15 ppm distillate by 2014
2004 Clean Air Nonroad Diesel Rule
1,000 ppm EGA fuel by 2015
2009 Category 3 Marine Rule
ฎ Fuels used in North American EGA (EGA program)
10,000 ppm by 2012
1,000 ppm by 2015
F-6
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United Slates (48 states)
F-7
-------
Result: Reduced ShiD Emissions
~ 80% NOx reduction new
vessels (2016)
ฎPM and SOx Controls
-95% SOx reduction
-85% PM reduction
Shipping will be efficient and clean!
F-S
-------
Human Health & Welfare Benefits:
Category 3 Rule
<ง> 2030 estimated benefits are between $110
and $280 billion
<*> By 2030, program expected to prevent:
Between 13,000 and 32,000 PM-related premature
deaths
Between 220 and 980 ozone-related premature deaths
Up to 1,500,000 work days lost
Up to 10,000,000 minor restricted-activity days
<ป> Estimated annual costs are much smaller:
$3.1 billion
F-9
-------
Human Health & Welfare Benefits:
2008 Loco/Marine Rule
ฎ 2030 estimated benefits are between $9 an*
$ 11 billion
ฎ By 2030, program expected to prevent:
1,100 PM-related premature deaths
280 ozone-related premature deaths
* 120,000 work days lost
* 1,100,000 minor restricted-activity days
ฎ Estimated costs are much smaller: $740
million
F-10
-------
Great Lakes Shipping
U.S. ship owners and G;
Lakes industry associatio
contributed to our marine
actions
2003 Tier 1 Rule
2004 Locomotive and Marine Rule
2007 Ship AOTRM
<ง> Environment Canada, Transport Canada,
and Canadian ship owners also participated
F-ll
-------
Great Lakes Vessels
the Great Lakes will -
Put steamships out of use -distillate fuel causes
safety concerns
* Increase operating costs, leading to significant
modal shifts to rail or truck
Result will be emissions increase, from
rail and truck
F-12
-------
Direction from Congress
ฎ 2010 Appropriations Bill (HR9226, the
Department of Interior, Environment, and
Related Agencies Appropriates Act, 2010)
ฎ EPA directed to exclude Great Lakes
steamships from fuel sulfur standards
<ง> Bill Report: EPA should include 2 waivers
(fuel availability, economic hardship), do
study)
F-13
-------
FRM Provisions for Lakers
<> 40 CFR 1043.95
ฎ Steamships excluded from fuel requirements
ฎ Diesel ships: compliance waived for 10,000 ppm
fuel if that fuel is not available - but owner must
purchase the next cleanest fuel available
<> Serious economic hardship provision
ฎ Canadian vessels are also eligible - Annex VI
Compliance on the Lakes
F-14
-------
Great Lakes Economic Study
ฎ What are the impacts of fuel sulfur
requirements on Great Lakes
shipping?
ฎ How do we evaluate this question?
Methodology
Data needs
ฎ Developing stakeholder process to
carry out this study
ฎ Assessing existing methodologies
F-15
-------
Additional Information
ฎ 2009 Category 3 Marine Rule and North
American EGA
ป www.epa.gov/otaq/oceanvessels.htm
ฎ 2008 Loco/Marine Rule
* www.eDa.aov/otaa/marine.htm
General Marine Program Contact
Jean-Marie Revelt
U.S. Environmental Protection Agency
Revelt.Jean-Marie@epa.gov
(734)214-4822
F-16
-------
Appendix
Impacts of
Great Lakes Vessels
on U.S. Air Quality
F-17
-------
Great Lakes Ports and
Nonattainment Areas
emissions and fuel consumption in the U.S.,
but their impacts are localized on the Lakes
T\
Two HartDors
f&
Duluth-Superw^ Presque Isle
7 .
i'
Milwaukee =^eirort
*-' Bums
C
D "
PM and Oioiw NonAitainnwmi
FedMSI CIBJS I Areas (Visubllitv)
F-18
-------
Great Lake Vessel Contribution
ฎ About 1.7% of the PM benefits of Category 3
engine and fuel controls in the U.S. are achieved
in 6 Great Lake states (IN, IL, MI, MN, OH, WI)
PA and NY not included because they also border Atlantic
Ocean
(> Estimated benefits of controls on Lakers is -
$ 1.5-3.7 billion in benefits v. $0.05 billion in costs
In comparison, the total benefit of Category 3 marine rule
in 2030, for the full U.S. EGA, is $110-$260 billion, with $3.1
billion in costs, for similar benefit-to-cost ratio
F-19
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>OOStO<*0 t
>0Mo<-025
>05to<= 10
> 1 0 to <= 2 0
> 2 0 to<= 4 1
F-20
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