Regulatory Impact Analysis:
Control of Emissions of Air Pollution from
Category 3 Marine Diesel Engines
United States
Environmental Protection
Agency
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Regulatory Impact Analysis:
Control of Emissions of Air Pollution from
Category 3 Marine Diesel Engines
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
SER&
United States
Environmental Protection
Agency
EPA-420-R-09-019
December 2009
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Regulatory Impact Analysis
Table of Contents
Executive Summary
Chapter 1: Industry Characterization
1.1 Introduction 1-2
1.2 Marine Transportation Sector 1-2
1.3 Marine Vessels 1-7
1.4 The Marine Transportation Sector 1-10
1.5 Marine Fuels 1-11
Chapter 2: Air Quality and Resulting Health and Welfare Effects
2.1 Background on Pollutants Reduced by this Final Rule 2-2
2.2 Health Effects Associated with Exposure to Pollutants 2-4
2.3 Environmental Impacts Associated with Pollutants 2-22
2.4 Impacts of the Coordinated Strategy on Air Quality 2-63
Chapter 3: Emission Inventory
3.1 Introduction 3-2
3.2 Modeling Domain and Geographic Regions 3-3
3.3 Development of 2002 Baseline Inventory 3-5
3.4 Development of 2020 and 2030 Scenarios 3-99
3.5 Estimated Category 3 Inventory Contribution 3-135
3.6 Projected Emission Reductions 3-140
3.7 Inventories Used for Air Quality Modeling 3-141
Appendix 3A Port Coordinates and Reduced Speed Zone Information 3-143
Appendix 3B Inventory Impacts of Alternative Program 3-150
Chapter 4: Technological Feasibility
4.1 Overview of Emissions Standards and Emission Control Technologies 4-2
4.2 Emission Control Technologies for Tier 2 Standards 4-3
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4.3 Emission Control Technologies for Tier 3 Standards 4-5
4.4 Vessel Technologies for Low Sulfur Fuel Standards 4-11
4.5 Technology for Producing/Distributing Lower Sulfur Fuel 4-25
4.6 Impact on Safety, Noise, and Energy 4-30
Chapter 5: Engineering Cost Estimates
5.1 Components of Coordinated Strategy Included in this Analysis 5-3
5.2 Methodology for Estimating Engine and Equipment Engineering Costs 5-6
5.3 Engineering Costs for Freshly Manufactured Engines 5-15
5.4 Engineering Costs for Existing Engines 5-30
5.5 Engineering Costs for Vessels 5-33
5.6 Operating Costs 5-42
5.7 Summary of Final Program Engineering Costs 5-59
5.8 Cost Effectiveness 5-63
Appendix 5A NOx Monitoring 5-68
Appendix 5B Feasibility and Cost of Testing Engines during Sea Trials 5-70
Appendix SCAnalysis of Gas Turbines 5-74
Chapter 6: Cost-Benefit Analysis
6.1 Overview 6-2
6.2 Quantified Human Health Impacts 6-9
6.3 Monetized Benefits 6-14
6.4 Methodology 6-18
6.5 Methods for Describing Uncertainty 6-31
6.6 Comparison of Costs and Benefits 6-32
Chapter 7: Economic Impact Analysis
7.1 Overview and Results 7-3
7.2 Economic Methodology 7-14
7.3 Estimating Market Impacts on the Marine Transportation Market 7-32
7.4 Sensitivity Analyses 7-42
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Chapter 8: Small Entity Impact Analysis
8.1 Standards 8-2
8.2 Marine Diesel Engine Manufacturers 8-3
8.3 Vessel Manufacturers 8-3
8.4 Fuel Manufacturers and Distributors 8-3
8.5 Vessel Owners and Operators 8-4
Chapter 9: Alternatives
9.1 Mandatory Cold Ironing Requirement 9-2
9.2 Earlier Adoption of CAA Tier 3 Standards 9-3
9.3 Standards for Existing Engines 9-4
in
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List of Acronyms
um Micrometers
bext Light-Extinction Coefficient
ug Microgram
ug/m3 Microgram per Cubic Meter
ABT Average Banking and Trading
ACS American Cancer Society
AE Alaska Southeast Region
AE Auxiliary Engine
AEO Annual Energy Outlook (an EIA publication)
AESS Automatic Engine Stop/Start System
AFC Average Daily Fuel Consumption
AIM Aerosol Inorganics Model
AIRS Aerometric Information Retrieval System
AMVER Automated Mutual-Assistance Vessel Rescue
APHEA Air Pollution and Health: A European Approach
APU Auxiliary Power Unit
AQ Air Quality
AQCD Air Quality Criteria Document
AQMTSD Air Quality Modeling Technical Support Document
ARE Air Resources Board (California)
ASPEN Assessment System for Population Exposure Nationwide
ATAC Average Total Cost
avg Average
AW Alaska West Region
BAF Bunker Adjustment Factor; a surcharge reflecting the fluctuation in fuel cost
BenMAP Benefits Mapping and Analysis Program
bhp Brake Horsepower
BNSF Burlington Northern Santa Fe
BSFC Brake Specific Fuel Consumption
BTS Bureau of Transportation
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)
CAMR Clean Air Mercury Rule
CAND Clean Air Nonroad Diesel rule (69 FR 38957, June 29, 2004)
CARD California Air Resources Board
CASAC Clean Air Scientific Advisory Committee
CAVR Clean Air Visibility Rule
CB Chronic Bronchitis
CCV Closed Crankcase Ventilation
CDC Centers for Disease Control
CDPF Catalyzed Diesel Paniculate Filter
CEA Cost Effective Analysis
CES Constant Elasticity of Substitution
CFR Code of Federal Regulations
CI Compression Ignition (i.e., diesel engines)
CI Confidence Interval
CIMT Carotid Intima-Media Thickness
CITT Chemical Industry Institute of Toxicology
CMAQ Community Multiscale Air Quality
IV
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CMB Chemical Mass Balance
CMV Commercial Marine Vessel
CO Carbon Monoxide
CO2 Carbon Dioxide
COI Cost of Illness
COPD Chronic Obstructive Pulmonary Disease
CPI-U Consumer Price Index - All Urban Consumers
C-R Concentration Response
CSS Coastal Sage Scrub
CUA Cost Utility Analysis
cyl Cylinder
D Demand
DE Diesel Exhaust
DEM Domestic Engine Manufacturer
DDHS Diesel Driven Heating System
diff Difference
disp Displacement
DM Distillate Marine Grade
DOC Diesel Oxidation Catalyst
DOE Department of Energy
DOT Department of Transportation
DPF Diesel Paniculate Filter
DPM Diesel Paniculate Matter
DR Discount Rate
DRIA Draft Regulatory Impact Analysis
DSP Deep Sea Port
DV Design Values
DWT Dead Weight Tonnage
EAC Early Action Component
EC East Coast Region
EC Elemental Carbon
EGA Emission Control Area
EDHS Electric Driven Heating System
EEZ Exclusive Economic Zone
EF Emission Factor
EGR Exhaust Gas Recirculation
EIA Energy Information Administration (part of the U.S. Department of Energy)
EIA Economic Impact Analysis
EDVI Economic Impact Model
EMD Electromotive Diesel
EMS-HAP Emissions Modeling System for Hazardous Air Pollution
EO Executive Order
EPA Environmental Protection Agency
EPAct Energy Policy Act of 2005
ESPN EPA speciation network
F Fahrenheit
FEM Foreign Engine Manufacturer
FEV Functional Expiratory Volume
FR Federal Register
FRM Final Rulemaking
FRP Fiberglass-Reinforced Plastic
g Gram
g/bhp-hr Grams per Brake Horsepower Hour
g/kW-hr Grams per Kilowatt Hour
gal Gallon
GAO Government Accountability Office
v
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GC Gulf Coast Region
GDP Gross Domestic Product
GEOS Goddard Earth Observing System
GETS General Electric Transportation Systems
GI Global Insight
GIS Geographic Information System
GL Great Lakes Region
GRT Gross Registered Tonnage
GT Gas Turbine
H2 Hydrogen Gas
HAD Diesel Health Assessment Document
HAP Hazardous Air Pollutant
HC Hydrocarbon
HD Heavy-Duty
HE Hawaii East Region
HEI Health Effects Institute
HEP Head End Power
HES Health Effects Subcommittee
HFO Heavy Fuel Oil
hp Horsepower
hp-hrs Horsepower Hours
hrs Hours
HW Hawaii West Region
IACS International Association of Classification Societies
IARC International Agency for Research on Cancer
ICD International Classification of Diseases
ICOADS 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
ISCST3 Industrial Source Complex Short Term Model
ISO International Standardization Organization
ISORROPIA Inorganic Aerosol Thermodynamic Model
ITB Integrated Tug Barge
JAMA Journal of the American Medical Association
K Kelvin
k Thousand
km Kilometer
kts Knots
kW Kilowatt
kWH Kilowatt Hour
L Liter
L/cyl Liters Per Cylinder
Ib Pound
LCO Light Cycle Oil
LF Load Factor
LGC Large Gas Carrier
LNG Liquefied Natural Gas
LPG Liquefied Petroleum Gas
LRS Lower Respiratory Symptoms
LSD Low Sulfur Diesel fuel
m3 Cubic Meters
MARAD U.S. Maritime Administration
MARPOL The International Convention for the Prevention of Pollution of Ships
MC Marginal Cost
VI
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MCIP Meteorology-Chemistry Interface Processor
MDO Marine Diesel Oil
ME Main Engine
MECA Manufacturers of Emission Controls Association
mg Milligram
MGO Marine Gas Oil
MDO Marine Diesel Oil
MI Myocardial Infarction
MILY Morbidity Inclusive Life Years
min Minute
MM Million
MM-1 Inverse Megameter
MOBILE6 Vehicle Emission Modeling Software
MRAD Minor Restricted Activity Days
MSAT Mobile Source Air Toxic
MS AT 1 2001 Mobile Source Air Toxics Rule
MSB Major Shipbuilding Base
MSD Medium Speed Diesel
MSDS Material Safety Data Sheet
MVUS Merchant Vessels of the U. S.
MW Megawatt
MW-hrs Megawatt Hours
N Nitrogen
N2 Nitrogen Molecule
NA Not Applicable
NAAQS National Ambient Air Quality Standards
NAICS North American Industry Classification System
NAS National Academy of Sciences
NASA National Aeronautics and Space Administration
NASSCO National Steel and Shipbuilding Company
NATA National Air Toxic Assessment
NBER National Bureau of Economic Research
NCAR National Center for Atmospheric Research
NCDC National Clean Diesel Campaign
NCI National Cancer Institute
NCLAN National Crop Loss Assessment Network
NEI National Emissions Inventory
NESCAUM Northeast States for Coordinated Air Use Management
NESHAP National Emissions Standards for Hazardous Air Pollutants
NH3 Ammonia
NIOSH National Institute of Occupational Safety and Health
NLEV National Low Emission Vehicle
NM Nautical Mile
NMHC Nonmethane Hydrocarbons
NMIM National Mobile Inventory Model (EPA software tool)
NMIM2005 National Mobile Inventory Model Released in 2005
NMMA National Marine Manufacturers Association
NMMAPS National Morbidity, Mortality, and Air Pollution Study
NO Nitrogen Oxide
NOa Nitrogen Dioxide
NOAA National Oceanic and Atmospheric Administration
NONROAD EPA'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
NPRM Notice of Proposed Rulemaking
Vll
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NPV Net Present Value
NRC National Research Council
NRLM Nonroad, Locomotive and Marine diesel fuel
NRT Net Registered Tonnage
NRT4 Nonroad Tier 4 Rule
NSTC National Science and Technology Council
NTE Not To Exceed
NWN National Waterway Network
O&M Operating and maintenance
O3 Ozone
OAQPS Office of Air Quality Planning and Standards
OC Organic Carbon
°CA Degree Crank Angle
OEHHA Office of Environmental Health Hazard Assessment
OEM Original Equipment Manufacturer
OGV Ocean-Going Vessel
OMB Office of Management and Budget
OTAQ Office of Transportation and Air Quality
P Price
PAH Polycyclic Aromatic Hydrocarbons
PCB Fob/chlorinated Biphenyls
PGM Platinum Metals Group
PM Paniculate Matter
PM AQCD EPA Particulate Matter Air Quality Criteria Document
PM/NMHC Particulate Matter to Non-Methane Hydrocarbon Ratio
PM10 Coarse Paniculate Matter (diameter of 10 um or less)
PM2.5 Fine Paniculate Matter (diameter of 2.5 um or less)
PMM Post-Manufacturer Marinizer
PMNAAQS Paniculate Matter National Ambient Air Quality Standards
POM Polycyclic Organic Matter
POLA/LB Ports of Los Angeles, Long Beach
ppb Parts per Billion
PPI Producer Price Index
ppm Parts per Million
psi Pounds per Square Inch
PSR Power Systems Research
Q Quantity
QALY Quality Adjusted Life Years
R&D Research and Development
RfC Reference Concentration
RFA Regulatory Flexibility Analysis
RFS Renewable Fuels Standard
RIA Regulatory Impact Analysis
RM Residual Marine
rpm Revolutions per Minute
RPO Regional Planning Organization
RRF Relative Reduction Factors
RSZ Reduced Speed Zone
RV Revision
RVP Reid Vapor Pressure
S Sulfur
S Supply
SAB Science Advisory Board
SAB-HES Science Advisory Board - Health Effects Subcommittee
S AE Society of Automotive Engineers
SAPS Sulfated-Ash, Phosphorus, and Sulfur Content
Vlll
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SBA Small Business Administration
SBREFA Small Business Regulatory Enforcement Fairness Act
SCC Source Classification Code
SCR Selective Catalyst Reduction
SFC Specific Fuel Consumption
SI Spark Ignition
SIC Standard Industrial Classification
SiC Silicon Carbide
SMAT Speciated Modeled Attainment Test
SO2 Sulfur Dioxide
SOx Oxides of Sulfur
SOA Secondary Organic Carbon Aerosols
SOF Soluble Organic Fraction
SP South Pacific Region
SSD Slow Speed Diesel
ST Steam Turbine
STB Surface Transportation Board
STEEM Waterway Network Ship Traffic, Energy and Environment Model
SVOC Semi-Volatile Organic Compound
SwRI Southwest Research Institute
TEN Total Base Number
TCC Total Compliance Cost
TCM Total Carbon Mass
TDC Top Dead Center
TEU Twenty-foot Equivalent Unit; basic container measurement used in the shipping industry
THC Total Hydrocarbon
TSD Technical Support Document
TVCC Total Variable Compliance Cost
ULCC Ultra Large Crude Carrier
ULSD Ultra Low Sulfur Diesel fuel
URS Upper Respiratory Symptoms
USACE United States Army Corps of Engineers
USDA United States Department of Agriculture
UV Ultraviolet
UV-b Ultraviolet-b
VLCC Very Large Crude Carrier
VLGC Very Large Gas Carrier
VOC Volatile Organic Compound
VOF Volatile Organic Fraction
VOS Voluntary Observing Ships
VSL Value of Statistical Life
WLD Work Loss Days
WTP Willingness-to-Pay
$2,005 U.S. Dollars in calendar year 2005
IX
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x
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Executive Summary
Executive Summary
EPA is finalizing emission standards for new Category 3 marine diesel engines
(engines with per cylinder displacement at or above 30 liters) installed on U.S. vessels. The
standards are part of a coordinated strategy to address emissions from ocean-going vessels
(OGV) A and are an important step in EPA's ongoing National Clean Diesel Campaign
(NCDC).
Emissions from OGV remain at high levels. The Category 3 engines on these vessels
use emission control technology that is comparable to that used by nonroad engines in the
early 1990s, and use fuel that can have a sulfur content of 30,000 ppm or more. As a result,
these engines emit high levels of pollutants that contribute to unhealthy air in many areas of
the U.S. As we look into the future, however, emissions from ocean-going vessels are
expected to become a dominant inventory source. This will be due to both emission
reductions from other mobile sources as new emission controls go into effect and to the
anticipated activity growth for ocean transportation.
Our coordinated strategy to control emissions from ocean-going vessels consists of
actions at both the national and international levels. It includes: (1) the engine and fuel
controls we are finalizing in this action under our Clean Air Act authority; (2) the proposal8
submitted by the United States Government to the International Maritime Organization to
amend MARPOL Annex VI to designate U.S. coasts as an Emission Control Area (ECA)C in
which all vessels, regardless of flag, would be required to meet the most stringent engine and
marine fuel sulfur requirements in Annex VI; and (3) the new engine emission and fuel sulfur
limits contained in the amendments to Annex VI that are applicable to all vessels regardless of
flag and that are implemented in the U.S. through the Act to Prevent Pollution from Ships
(APPS).
A This final rule generally applies to vessels with the largest marine diesel engines, which are called Category 3
engines in our regulations. We often refer to vessels using these engines as Category 3 vessels. In this
preamble, we also refer to them as ocean-going vessels as a descriptive term, since the large majority of these
vessels operate in the oceans, either navigating internationally across oceans or operating extensively in coastal
areas. We do not use the term ocean-going vessels to exclude the few vessels with Category 3 engines that
operate only in fresh-water lakes or rivers, but rather to reflect the way the vessels being regulated are more
commonly known to the general public. Note also that the fuel requirements described in this rule, unless
otherwise specified, generally apply also to fuel used in gas turbines and steam boilers on marine vessels.
B Proposal to Designate an Emission Control Area for Nitrogen Oxides, Sulphur Oxides and F'articulate Matter,
Submitted by the United States and Canada. IMO Document MEPC59/6/5, 27 March, 2009. A copy of this
document can be found at http://www.epa.gov/otaq/regs/nonroad/marine/ci/mepc-59-eca-proposal.pdf
c For the purpose of this rule, the term "EGA" refers to both the EGA and associated internal U.S. waters. Refer
to Section VLB. of the preamble for a discussion of the application of the fuel sulfur and engine emission limits
to U.S. internal waters through APPS.
ES-1
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Regulatory Impact Analysis
We project that by 2030 the coordinated strategy will reduce annual emissions of NOx
and PM by 1.2 million and 143,000 tons, respectively, and the magnitude of these reductions
will continue to grow well beyond 2030.° The estimated annual monetized health benefits of
this coordinated strategy in 2030 are between $110 and $270 billion, assuming a 3 percent
discount rate (or between $99 and $240 billion assuming a 7 percent discount rate). The
estimated annual cost of the overall program in 2030 is significantly less, at approximately
$3.1 billion.
This Regulatory Impact Analysis provides technical, economic, and environmental
analyses of the coordinated strategy. Chapter 1 provides industry characterization for the
marine industry. Chapter 2 presents air quality modeling results and describes the health and
welfare effects associated with NOx, SOx, PM, and ozone. Chapter 3 provides our estimates
of the current emission inventories and the reductions that can be expected from the
coordinated strategy. Chapter 4 contains our technical feasibility justification for the emission
limits, and Chapter 5 contains the estimated costs of complying with those standards. Chapter
6 presents the estimated societal benefits of the coordinated strategy. Chapter 7 contains our
estimates of the market impacts of the coordinated strategy and the distribution of costs
among stakeholders. Chapter 8 provides the results of our small entity screening analysis.
Finally, Chapter 9 contains a summary of our analysis of several programmatic alternatives
we evaluated in our rulemaking.
D These emission inventory reductions include reductions from ships operating within the 24 nautical mile
regulatory zone off the California Coastline, beginning with the effective date of the coordinated strategy
program elements. The California regulation contains a provision that would sunset the requirements of the rule
if the federal program achieves equivalent emission reductions. See
http://www.arb.ca.gov/regact/2008/fuelogv08/frol3.pdfat 13 CCR 2299.2(j)(l).
ES-2
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Executive Summary
1. Coordinated Strategy to Reduce Emissions from Ships
The components of the coordinated strategy are summarized below. Readers should
refer to the preamble for additional information about these provisions.
Clean Air Act Engine and Fuel Standards
We are finalizing new engine standards for Category 3 marine diesel engines under
our Clean Air Act authority. The finalized Tier 2 and Tier 3 NOx limits are set out in Table
ES-1 and will apply to engines with per cylinder displacement at or above 30 liters installed
on U.S. vessels. In addition to the NOX emission limits, we are finalizing standards for
emissions of hydrocarbons (HC) and carbon monoxides (CO) from new Category 3 engines.
We are not setting a standard for PM emissions for Category 3 engines. However, significant
PM emissions benefits will be achieved through the EGA fuel sulfur requirements, described
below, that will apply to ships that operate in areas that affect U.S. air quality. We are also
requiring engine manufacturers to measure and report PM emissions pursuant to our authority
in section 208 of the Act.
Table ES-1 Existing and Proposed NOX Emission Standards for Category 3 Engines (g/kW-hr)
Tier 1
Tier 2
Tier3
2004b
2011
2016
LESS THAN
130 RPM
17.0
14.4
3.4
130-2000
RPMa
45.0.n(-°-20)
44.0-n(-a23)
9.0-n(-a20)
OVER 2000
RPM
9.8
7.7
2.0
Notes:
3 Applicable standards are calculated from n (maximum in-use engine speed in RPM), rounded to one decimal
place.
b Tier 1 NOX standards currently apply for engines originally manufactured after 2004.
With regard to fuels, we are finalizing fuel sulfur limits under section 21 l(c) of the
Clean Air Act that match the limits that apply under Annex VI for EGAs (see below). The
adoption of such standards will: (1) forbid the production and sale of fuel oil above 1,000 ppm
sulfur for use in the waters within the proposed U.S. EGA and associated internal U.S. waters,
unless alternative devices, procedures, or compliance methods are used to achieve equivalent
emissions reductions; and (2) allow for the production and sale of 1,000 ppm sulfur fuel for
use in Category 3 marine vessels.
EC A Designation of U.S. Coasts
To realize the benefits from the MARPOL Annex VI Tier III NOx and fuel sulfur
controls, areas must be designated as Emission Control Areas. On March 27, 2009, the U.S.
and Canadian governments submitted a proposal to amend MARPOL Annex VI to designate
North American coastal waters as an EGA (referred to as the "North American EGA").
France has since joined the EGA proposal on behalf of the Saint Pierre and Miquelon
archipelago. EGA designation would ensure that U.S. and foreign ships that affect U.S. air
quality meet stringent NOx and fuel sulfur requirements while operating within 200 nautical
miles of U.S. coasts. The area of the proposed North American EGA is presented in Figure
ES-3
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Regulatory Impact Analysis
ES-1. The fuel sulfur limits that apply in EGAs pursuant to Annex VI are contained in Table
ES-2. The engine emission limits that apply in EGAs are the MARPOL Annex VI Tier III
limits, which are equivalent to the Tier 3 NOx limits contained in Table ES-1.
Table ES-2 Annex VI Fuel Sulfur Limits
Fuel Sulfur
GLOBAL
2004
2012
2020
45,000 ppma
35,000 ppma
5,000 ppm^
EGA
2005
2010a
2015
1 5,000 ppma
1 0,000 ppma
l,000ppma
Notes:
a Annex VI standards are in terms of percent sulfur. Global sulfur limits are 4.5%; 3.5%; 0.5%. EGA
sulfur limits are 1.5%; 1.0%; 0.1%.
b Subject to a feasibility review in 2018; may be delayed to 2025.
Figure ES-1 Proposed North American Emission Control Area
The EGA stringent international engine NOx standards and fuel sulfur limits will
apply to U.S. and foreign vessels while they operate in the designated area upon adoption of
the proposed amendment to Annex VI. If this proposal is not timely adopted by IMO, we
intend to take supplemental action to control emissions from vessels, including foreign
vessels, that affect U.S. air quality.
MARPOL Annex VI and the Act to Prevention Pollution from Ships
The United States became a party to MARPOL Annex VI by depositing its instrument
of ratification with IMO 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,
ES-4
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Executive Summary
that contains amendments to the Act to Prevent Pollution from Ships (33 USC 1901 et seq.).
These APPS amendments require compliance with Annex VI by all persons subject to the
engine and vessel requirements of Annex VI. The amendments also authorize the United
States Coast Guard and EPA to enforce the provisions of 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. The Final Rule contains regulations to implement several aspects of the Annex
VI engine and fuel regulations, which we are finalizing under that APPS authority.
2. Projected Inventory and Cost Impacts of the Coordinated Strategy
This RIA presents estimated inventory and cost impacts for the entire coordinated
strategy, including the Annex VI Tier II NOx requirements and the EGA controls that will be
mandatory for U.S. and foreign vessels through the Act to Prevent Pollution from Ships (See
Chapter 5 for more details). Specifically, the analysis estimates the costs of the finalized
Clean Air Act (CAA) Tier 2 and Tier 3 emission standards for U.S.-flagged vessels,
operational costs associated with the global Tier II and Tier III standards for foreign-flagged
vessels operating in the EGA, and fuel sulfur requirements. We also include Clean Air Act
compliance costs that will apply only to new U.S. vessels for verification testing after engine
installation (that is, production line testing or PLT). The changes to our fuel regulations are
implementation provisions and do not impose compliance costs, but instead may reduce the
costs for fuel distributors of complying with EPA's distillate diesel standards. Similarly, the
programmatic changes being finalized for Category 1 and 2 engines (see Section VI.C of the
preamble) will not impose compliance costs but instead are intended to facilitate compliance
with both Annex VI and our Clean Air Act requirements for those engines.
Inventory Reductions
A discussion of the current and projected inventories for several key air pollutants are
contained in Chapter 3. Nationally, in 2009, Category 3 vessels will contribute 10 percent of
mobile source NOx emissions, 24 percent of mobile source diesel PM2.5 emissions, and 80
percent of mobile source 862 emissions. In 2030, absent the coordinated strategy, these
vessels would become a larger portion of the total mobile source emissions inventory
constituting 40 percent of mobile source NOx emissions, 75 percent of mobile source diesel
PM2.5 emissions, and 95 percent of mobile source SO2 emissions.
We estimate that the coordinated strategy will reduce annual NOx emissions by 1.2
million tons, PM2.5 emissions by 143,000 tons, and SO2 emissions by 1.3 million tons in 2030.
Engineering Costs
The total engineering costs associated with the coordinated strategy are the summation
of the engine and vessel costs and include both hardware and operating costs. This analysis
can be found in Chapter 5. The cost of the coordinated strategy is estimated to be $1.9 billion
in 2020 and $3.1 billion in 2030; over 98 percent of these costs are attributable to expected
increases in operating costs for U.S. and foreign flag vessels traveling within the U.S. EGA.
These increased operating costs include changes in fuel consumption rates, increases in fuel
ES-5
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Regulatory Impact Analysis
costs, and the use of urea for engines equipped with selective catalytic reduction (SCR). The
total cost of the coordinated strategy based on a 3 percent discount rate from 2010 through
2040 is estimated to be $43 billion and $22 billion at a 7 percent discount rate.
Cost per Ton of Reduced Emissions
Using the inventory and engineering cost information, we can estimate the cost per ton
of pollutant reduced as a result of the more stringent standards. Table ES-3 contains the
estimated cost per ton of pollutant reduced based on the net present value of the engineering
costs and inventory reductions from 2010 through 2040. This estimate captures all of the
engineering costs and emissions reductions associated with the coordinated strategy. When
attributed by pollutant, at a net present value of 3 percent from 2010 through 2040, the NOx
controls are expected to cost about $510 per ton of NOx reduced, SOx controls are expected
to cost about $930 per ton of SOX reduced, and the PM controls are expected to cost about
$7,950 per ton of PM reduced ($500, $920, and $7,850 per ton of NOX, SOX, and PM
respectively, at a net present value of 7 percent over the same period.)
Table ES-3 Program Cost per Ton Estimates
POLLUTANT
NOX
SOX
PM
2010 THRU 2040 DISCOUNTED
LIFETIME COST PER TON AT 3%
$510
$930
$7,950
2010 THRU 2040 DISCOUNTED
LIFETIME COST PER TON AT 7%
$500
$920
$7,850
3. Estimated Benefits and Economic Impacts of the Coordinated Strategy
We estimated benefits for the entire coordinated strategy, including the Annex VI Tier
II NOx requirements and the EGA controls that will be mandatory for U.S. and foreign
vessels through the Act to Prevent Pollution from Ships. Note that the Clean Air Act-specific
portions of the coordinated strategy are compliance measures (PLT, distillate fuel program
changes) and do not impact the estimated benefits. The benefits analysis is presented in
Chapter 6. It uses sophisticated air quality and benefit modeling tools and is based on peer-
reviewed studies of air quality and health and welfare effects associated with improvements in
air quality and peer-reviewed studies of the dollar values of those public health and welfare
effects.
Estimated Benefits
The range of benefits associated with this program are estimated based on the risk of
several sources of PM- and ozone-related mortality effect estimates, along with other PM and
ozone non-mortality related benefits information. These benefits are presented in Table ES-4.
These estimates reflect EPA's most current interpretation of the scientific literature on PM2.5
and mortality, including our updated benefits methodology (i.e., a no-threshold model that
calculates incremental benefits down to the lowest modeled PM2.5 air quality levels)
ES-6
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Executive Summary
compared to estimates in previous RIAs that did not include these changes. Please see
Section 6.4.1.3 of the RIA for more discussion of the treatment of thresholds in this analysis.
We present total benefits based on the PM- and ozone-related premature mortality
function used. The benefits ranges therefore reflect the addition of each estimate of ozone-
related premature mortality (each with its own row in Table ES-4) to estimates of PM-related
premature mortality derived from the epidemiological literature.
Table ES-4 Estimated Monetized PM- and Ozone-Related Health Benefits of Coordinated U.S. Strategy to
Control Ship Emissions
N(
a
2030 TOTAL OZONE AND PM BENEFITS - PM MORTALITY DERIVED FROM
EPIDEMIOLOGY STUDIES3
Premature Ozone Mortality
Function or Assumption
Multi-city
Meta-analysis
Reference
Bell et al., 2004
Huang et al., 2005
Schwartz, 2005
Bell et al., 2005
Ito et al., 2005
Levy etal., 2005
Mean Total Benefits
(Billions, 2006$)c'd
$110 -$260
$110 -$260
$110 -$260
$110 -$260
$110 -$270
$110 -$270
3tes:
developed by adding the estimate from the ozone premature mortality function to the estimate of PM25 -related
premature mortality derived from either the American Cancer Society (ACS) cohort study (Pope et al., 2002) or
the Harvard Six-Cities study (Laden et al., 2006).
Note that total benefits presented here do not include a number of unqualified benefits categories. A detailed
listing of unquantified health and welfare effects is provided in Table 6-2.
c Results reflect the use of a 3 percent discount rate. Using a 7% discount rate, the benefits are approximately
10% less. Monetary results presented in Chapter 6 use both a 3 and 7 percent discount rate, as recommended by
EPA's Guidelines for Preparing Economic Analyses and OMB Circular A-4. Results are rounded to two
significant digits for ease of presentation and computation.
We estimate that by 2030, the annual emission reductions associated with the
coordinated strategy will annually prevent between 12,000 and 30,000 PM-related premature
deaths (based on the American Cancer Society cohort study and the Harvard Six-Cities
study), between 210 and 920 ozone-related premature deaths, 1,400,000 work days lost, and
approximately 9,600,000 minor restricted-activity days.
Benefit-Cost Analysis
We estimate that the monetized benefits of the coordinated strategy in 2030 will range
between approximately $110 and $270 billion, assuming a 3 percent discount rate. The
annual cost of the coordinated strategy in 2030 is estimated to be significantly less, at
approximately $3.1 billion. The 2030 benefits outweigh the costs by at least a factor of 32
and could be as much as a factor of 87. Thus, even taking the most conservative benefits
assumptions, benefits of the coordinated strategy clearly outweigh the costs.
ES-7
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Regulatory Impact Analysis
Economic Impact Analysis
We performed an economic impact analysis to estimate the market-level changes in
prices and outputs for affected markets, the social costs of the coordinated strategy, and the
expected distribution of those costs across stakeholders. This analysis can be found in
Chapter 7. We estimate the social costs of the new program to be approximately $3.1 billion
in 2030.E These costs are expected to be borne by purchasers of marine transportation
services. Because there are no close transportation alternatives for the vast majority of goods
currently moved by ship, these costs are expected to be passed to consumers of marine
transportation in the form of higher freight rates. Ultimately, these costs will be incurred by
the purchasers of goods transported by Category 3 powered vessels in the form of higher
prices for those goods.
With regard to market-level impacts, the equipment costs of the coordinated strategy
are expected to increase the price of a new vessel by 2 percent or less. The impact of the
coordinated strategy, including the increase in operating costs due to fuel standards and
emission requirements, on the price of ocean marine transportation services would vary,
depending on the route and the amount of time spent in the proposed U.S. EGA. For example,
we estimate that the cost of operating a ship in liner service between Singapore, Seattle, and
Los Angeles/Long Beach, which includes about 1,700 nm of operation in the proposed EGA,
would increase by about 3 percent. For a container ship, this represents a price increase of
about $18 per container, assuming the total increase in operating costs is passed on to the
purchaser of marine transportation services. This would be about a 3 percent price increase.
The per passenger price of a seven-day Alaska cruise operating entirely within the EGA is
expected to increase about $7 per day. For ships that spend less time in the EGA, the
expected increase in total operating costs and therefore the impact on freight prices would be
smaller.
4. Alternatives
In the course of designing our rulemaking, we investigated several alternative
approaches to both the engine and fuel programs. The analysis for those alternatives is
contained in Chapter 9 of this RIA.
' All estimates presented in this section are in 2006$.
ES-8
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Executive Summary
This Page Intentionally Left Blank
ES-9
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Regulatory Impact Analysis
CHAPTER 1: Industry Characterization
1.1 Introduction
Marine transportation is a key component of the U.S. national economy, for both our
internal and external trade. According to the U.S. Maritime Administration, the United States
saw about 2.3 billion metric tons of goods shipped via waterborne transportation in 2006, of
which about 1.4 billion, or nearly 65 percent, was foreign trade (imports and exports to and from
the United States).1 This foreign trade, carried primarily by ocean-going vessels powered by
Category 3 marine diesel engines, had a value of about $1.4 trillion.
This chapter provides some basic information about the segment of the marine
transportation sector, ocean-going marine that is affected by today's rule. The material presented
below is a brief synopsis of the unique attributes of the maritime industry, derived from two
detailed reports prepared for this rulemaking.2'3 These reports explore in greater detail the
various aspects of the marine transportation sector and the marine fuel markets. We encourage
readers to review the full reports for further information.
1.2 Marine Transportation Sector
In this report, the marine transportation sector refers to (1) Category 3 marine diesel
engines, (2) the vessels that use those engines, and (3) the transportation services that use those
vessels. EPA defines Category 3 marine engines as compression-ignition engines with a
displacement greater than or equal to 30 liters per cylinder.A Category 3 engines can be
incredibly large and can have anywhere from four to 20 cylinders with displacements ranging
from 30 to 3,000 liters per cylinder. These engines can provide power output from 2,000 kW to
over 100,000 kW. 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, less common are steam or gas turbine
engines. EPA adopted an initial level of emission standards for Category 3 engines on February
28, 2003 (68 FR 9746). This includes all marine diesel engines with per-cylinder displacement
above 30 liters. These initial standards are identical to the standards specified in MARPOL
Annex VI.
The marine transportation industry relies on a variety of large ocean-going commercial
vessel types powered by Category 3 engines to carry goods and passengers around the world.
The EPA typically defines large commercial vessels as vessels engaged in waterborne trade
and/or passenger transport that exceed 400 feet in length and/or weigh more than 2,000 GT.4
A Marine diesel engines with per-cylinder displacement below 30 liters, called Category 1 and Category 2 engines,
became regulated under an initial U. S. Environmental Protection Agency (EPA) rulemaking in 1999 (64 FR 73300,
December 29, 1999). EPA adopted more stringent standards for these engines as part of the Clean Diesel
Locomotive and Marine Rule, which is a three-phased program and will ensure that all locomotives and Category 1
and Category 2 marine diesel engines will produce less pollution (73 FR 37096, June 30, 2008).
1-2
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Chapter 1: Industry Characterization
Marine vessel owners and operators include U.S. and foreign entities that provide ocean marine
transportation services to many industries including: consumer goods, chemical, agricultural,
petroleum, personal transportation, etc. The statistics presented in this report were compiled in
2008 using Lloyd's Register of Ships Sea-Web service.5 Sea-Web provides detailed information
on the vessels that make up the global fleet including details on the installed engines, the vessels
themselves, and the owners and operators of these vessels. Engine details available include:
engine designer, builder, model, type, and propulsion power rating. Vessel details include: ship
type, year built, gross tonnage (GT), flag state, and actual build details (e.g., hull type). The
analyses presented here are based only on vessels built in or after 1990, with at least 5,000 kW,
are at least 2,000 GT, and are in-service; only vessels with complete records were included; for
the purposes of this report these vessels will be referred to as the "global fleet."
Table 1-1 Characteristics of the "Global Fleet"
Auto Carrier
Bulk Cargo
Container
Misc
Passenger
Reefer
RoRo
Tanker
AVERAGE
YEAR
BUILT
2002
2000
2001
2000
1999
1995
2000
2002
AVERAGE
GT
49,000
37,000
34,000
18,000
42,000
9,300
20,000
57,000
NUMBER
OF 2-
STROKES
386
4127
2977
19
7
224
47
3464
NUMBER
OF 4-
STROKES
18
281
492
157
402
21
137
191
NUMBER
OF GAS
TURBINES
0
0
0
0
16
0
8
4
NUMBER
OF
STEAM
TURBINES
0
0
0
2
1
0
0
182
AVERAGE
ENGINE
POWER
(KW)
13000
9400
27000
7500
10000
9700
11000
13000
The coordinated strategy for emission controls of Category 3 marine engines is slightly
different than previous EPA rules in that, in addition to the Clean Air Act (CAA) authority, the
U.S. Government has petitioned the International Maritime Organization (IMO) to create an
Emission Control Area (EGA) around most of the U.S. coastline. The regulations for Category 3
marine diesel engine emissions could directly impact several industries: (1) manufacturers of
marine diesel engines, (2) diesel engine marinizers, (3) marine diesel engine remanufacturers, (4)
boat or vessel builders which install marine diesel engines installed on their vessels, (5) vessel
operators who own existing marine diesel engines with engine displacement at or greater than 30
liters per cylinder (L/cyl), (6) marine fuel manufacturers, (7) marine fuel distributors/brokers,
and (8) U.S. ports.
1.2.1 Engine Types
1.2.1.1 Two-Stroke Engines
Two-stroke engines are usually SSD connected to a direct drive propulsion system.
These engines have large displacements of up to 3,000 L/cylinder. SSD are used for propulsion
on bulk carriers, container ships, larger tankers, general cargo and roll-on/roll-of (RoRo) ships.
They are typically turbo-charged with aftercooling and have four exhaust valves per cylinder.
Scavenge air enters the cylinder through a series of intake ports arranged around the bottom of
the cylinder. Intake is controlled by the piston as it uncovers or covers the intake ports. Fuel
injection is typically mechanical with three injectors per cylinder.
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Regulatory Impact Analysis
The top three two-stroke engine designers of the global fleet on a per-vessel basis are
MAN which represents over 71 percent of that total, Wartsila which produced nearly 18 percent,
and Mitsubishi which captured just over 10 percent. MAN is headquartered in Munich,
Germany and is a supplier of diesel engines, turbo machinery, special gear systems, trucks and
buses. In 2008, MAN employed over 51,000 people and generated revenue of approximately
$23 billion.6 Wartsila is headquartered in Helsinki, Finland and is a provider of ship design,
engines, generator sets, gears and other propulsion equipment. They employ nearly 19,000
people and have locations in close to 70 countries.7 Mitsubishi Power Systems, Inc. (MPS)
headquartered in Lake Mary, FL is a subsidiary company of Mitsubishi Heavy Industries, Ltd.
(MHI) which employs more than 40,000 people worldwide generating more than $25 billion in
annual revenues.8 MPS produces gas and steam turbines in addition to medium speed engines up
to nearly 15,000 kW, and low speed engines over 67,000 kW. MHI also builds and repairs ships,
marine engines and equipment.
Table 1-2 Number of Engines Built per Year by Manufacturer
YEAR
BUILTA
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total
Percent
MAN
170
178
171
193
260
302
352
369
377
368
331
442
474
497
579
703
764
833
673
8036
71%
WARTSILAB
86
91
107
92
108
96
125
147
136
106
155
122
80
92
87
116
115
100
60
2021
18%
MITSUBISHI
41
34
46
55
46
59
67
92
82
69
62
44
53
60
80
81
68
92
59
1190
10%
OTHER
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
3
4
0.04%
TOTAL
297
303
324
340
414
457
544
608
595
543
548
609
607
649
746
900
947
1025
795
11251
Notes:
1 Assumes that the engine was built the same year the vessel was reported as being built.
b Wartsila count includes Sulzer engines.
Wartsila manufactures the world's most powerful diesel engine, the 14-cylinder Wartsila
RT-flex96C marine engine has a maximum continuous power output of 84,000 kW (113,000
bhp) at 102 rpm. This engine is nearly 90 feet long, and over 44 feet tall and weighs over five
million pounds, see Figure l-l.9'10
1-4
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Chapter 1: Industry Characterization
Source:http://www.aucklandshipbrokers.com/index.php?option=com_cont
ent&task=view&id=100&Itemid=68
Figure 1-1 Wartsila RT-flex96C 84,000 kW SSD Engine
1.2.1.2 Four-Stroke Engines
Four-stroke engines are usually MSD engines with significantly smaller cylinder
displacements (30 to 200 L/cylinder) than SSD, and typically have six to 18 cylinders. These
engines are commonly connected to an electric drive propulsion system which is actually a large
generator that can be used to generate auxiliary power as well as drive the propulsion systems.
They are typically used as propulsion engines on smaller tankers, general cargo, RoRo, ferries,
cruise ships, and as auxiliary engines on large ships for power generation or refrigeration. They
are generally turbo-charged and aftercooled, have two intake and two exhaust valves per cylinder
and are mechanically fuel injected with one injector per cylinder.
The top three four-stroke engine designers of the global fleet on a per-vessel basis are
Wartsila which represents over 36 percent of that total, MAN which produced nearly 32 percent,
and MAK which captured approximately 29 percent. MAK is owned by Caterpillar which
1-5
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Regulatory Impact Analysis
produces medium and high speed engines of up to 16,000 kW for main propulsion, and nearly
7,700 kW for marine generator sets and is headquartered in Hamburg, Germany.
11
Table 1-3 Number of Engines Built per Year by Manufacturer
YEAR
BUILTA
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total
WARTSILAB
10
14
12
22
22
30
20
34
51
59
55
49
41
31
36
22
24
51
38
621
MAN0
17
19
21
22
13
19
33
33
35
34
24
12
23
34
12
28
55
60
48
542
MAK
9
4
11
11
10
12
13
9
5
6
21
21
28
43
46
44
57
89
51
490
OTHER
3
1
1
1
1
1
2
2
3
5
3
2
2
2
1
2
3
7
4
46
TOTAL
39
38
45
56
46
62
68
78
94
104
103
84
94
110
95
96
139
207
141
1699
Notes:
a Assumes that the engine was built the same year the vessel was reported as being built.
b Wartsila count includes Sulzer engines.
0 MAN count includes Pielstick engines.
1.2.2 Other Engine Types
Turbine powered vessels accounted for less than two percent of the global fleet, and of
those 13 percent are gas turbines, while the remaining 87 percent are steam turbines. The top
three turbine engine designers include General Electric (GE), Kawasaki, and Mitsubishi and
together account for over 91 percent of installed turbine engines. GE sold gas turbine engines
exclusively to the global fleet representing 11 percent of the turbine powered fleet, while both
Kawasaki and Mitsubishi only have steam turbine engines in the global fleet, accounting for 40
and 39 percent of the turbine powered fleet respectively. Steam turbines have traditionally been
the choice of Liquid Natural Gas carriers primarily because any boil-off gas could be sent
through the turbine and burned.
1-6
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Chapter 1: Industry Characterization
Turbine Engines in the Global Fleet
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Year Built
nGE Marine (Gas) • Kawasaki nMitsubishi nOtherSteam
Figure 1-2 Steam and Gas Turbines in the Current Global Fleet
1.2.2.1 Auxiliary Engines
Category 3 engines can also be used for auxiliary engines as well as Category 2. They
are used to generate electrical power for navigation equipment, maneuvering equipment, and
crew services. The engines used to generate electrical power are typically, however, Category 2
diesel engines. Some vessels, such as refrigerated cargo vessels, may require Category 3 engines
to meet electric power requirements. Cruise ships often employ diesel-electric engines that
provide both propulsion and power generation. In addition to propulsion and electric power
engines, an auxiliary engine is typically installed for emergency use. In 2007, over 10,000
auxiliary engines were ordered, totally 11,600 megawatts.12'13
1.2.2.2 Main Engines in the Global Fleet
Category 3 engines are not typically mass-produced. They are built in different
configurations with varying numbers of cylinders, engine displacement, power output, and
engine speed. Because of the variety of configurations and applications, the selection of the main
engine is a major consideration in the overall design of a vessel. As a result, the engine selected
for a specific vessel is often a unique design or configuration that is built specifically for that
vessel. In many cases, Category 3 engines designed by these manufacturers are built under
license by other companies in Europe and Asia. It can take up to two or three years to receive
delivery of components such as crankshafts and engine blocks, Wartsila notes that it is not
engine assembly that slows production, but delivery of these larger components from sub-
suppliers.14
1.3 Marine Vessels
The marine transport industry relies on a variety of vessel types to carry goods and
passengers around the world. These vessels are typically categorized by the type of cargo the
1-7
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Regulatory Impact Analysis
vessel is designed to transport and by the vessel size, in terms of carrying capacity and hull
dimensions. Table 1-3 outlines the vessel categories that constitute the majority of the current
OGV world fleet.
Table 1-4 Vessel type, category, and size range for the majority of the OGV world fleet.
Vessel Type
Bulk Carrier
Container
Liquid Gas Garner
(Liquid Petroleum Gas
(LPG)/ Liquid Natural
Gas (LNG))
General Cargo
Cruise / Passenger
Refrigerated (Reefer)
Roll-on /Roll-off
(Ro-Ro)
Tanker
Vessel Size
Category
Coastal
Handy
Handymax
Panamax
Capesize
Feeder
Intermediate
Panamax
Post Panamax
Suezmax
Midsize
Large Gas Carrier
(LGC)
Very Large Gas
Carrier (VLGC)
Coastal Small
Coastal Large
Handy
Panamax
All
All
All
Coastal
Handymax
Panamax
AFRAmax
Suezmax
Very Large Crude
Carrier (VLCC)
Ultra Large Crude
Carrier (ULCC)
Average Size Range
(DWT)
1,253 - 9,994 (5,576)
10,095 - 39,990 (27,593)
40,009-54,881(47,616)
55,000-78,932(69,691)
80,000 - 364,767 (157,804)
1,000-13,966 (9,053)
14,003-36,937 (24,775)
37,042-54,700 (45,104)
55,238-84,900 (67,216)
85,250-120,892 (101,099)
1,001-34,800 (7,048)
35,760-59,421 (50,796)
62,510-122,079 (77,898)
1,000-9,999 (3,789)
10,000-24,912 (15,673)
25,082-37,865 (29,869)
41,600-49,370(44,511)
1,000-19,189 (6,010)
1,000-19,126(6,561)
1,000-19,126 (7,819)
1,000-23,853(7,118)
25,000-39,999 (34,422)
40,000-75,992 (52,300)
76,000-117,153(103,112)
121,109-167,294(153,445)
180,377-319,994(294,475)
320,051-441,893 (364,896)
1-8
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Chapter 1: Industry Characterization
1.3.1 Vessel Design and Construction
Ship builders typically design their vessels based on the type of freight they intend to
haul as the type of cargo transported necessitates specific design characteristics, for example,
container vessels require a different structure than a vessel that hauls bulk freight. Six ship
builders are responsible for the majority of commercial vessels constructed in the United States,
including Bath Iron Works, Electric Boat Company, the National Steel and Shipbuilding
Company (NASSCO), Avondale Operations, Ingalls Operations, and Newport News
Shipbuilding. There is a much larger number of ship builders outside the United States. Since
2000, U.S. ship builders have produced 20 to 40 vessels per year, while foreign ship builders
have produced 60 to 120 vessels per year.15
Vessel design is an iterative process that typically includes three stages: concept design,
preliminary design, and contract design. The concept design stage considers the vessel's general
objectives, adjusting key vessel parameters and specifications based on the owner's stated
technical and economic criteria. The preliminary design stage further refines the concept design
by analyzing expected performance and profitability of various alternatives for key design
elements (e.g., proportions, lines, hydrostatics, layout, power). Upon completion, the preliminary
design yields the final vessel attributes, including dimensions, displacement, stability, propulsive
performance, and structural details.12
1.3.2 Vessel Building Classification Societies
Ships must be built in accordance with shipbuilding standards in the country where they
are flagged or in accordance with standards imposed by the International Association of
Classification Societies (IACS). The classification societies implement many of the national or
international requirements that apply to marine vessels, including the various requirements under
MARPOL Annex VI. Classification societies include, among others, American Bureau of
Shipping, Det Norske Veritas, and Germanischer Lloyd. In the United States, the U.S. Coast
Guard works closely with the American Bureau of Shipping to implement and enforce applicable
requirements. It is important to note that EPA implements and enforces requirements related to
exhaust emission standards cooperatively with the U.S. Coast Guard, but without the
involvement of classification societies.
The global shipping industry comprises a large number of diverse firms. Vessel owners
and operators provide marine transportation services in support of international trade and
commodity flows over water. Every ship in the world's shipping fleet is designated by the flag
of registry. The flag of registry is a useful way of characterizing the shipping industry. However,
in many cases, the flag of registry has no correlation with the location of the parent company that
owns/operates a vessel. This confusion results partly because "open registries" allow
owners/operators to register ships in countries outside of their country of domicile
(owner/operator country). The five countries with the most flagged ships in the "Global Fleet" in
order are Singapore, the Marshall Islands, China, Liberia, and Panama. Table 1-5 presents these
values, and shows the ships under the U.S. flag as well.
The U.S. fleet of privately owned ocean-going vessels primarily includes bulk carriers,
containerships, gas carriers, general cargo vessels, passenger vessels, refrigerated container
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Regulatory Impact Analysis
vessels, roll-on/roll-off vessels, and tankers. Containerships comprise the largest number of
vessels in the U.S. commercial fleet with a total of approximately 75 ships (-45% of the total),
while there are around 50 tankers (-33%). The average age of U.S.-flagged commercial ocean-
going vessel is approximately 20 years.
Table 1-5 Ship Type by Country of Flag
SHIP TYPE
Auto Carrier
Bulk Cargo
Container
Misc
Passenger
Reefer
RoRo
Tanker
Grand Total
SINGAPORE
22
161
236
4
0
1
0
279
703
MARSHALL
ISLANDS
1
253
164
4
0
3
1
313
739
CHINA3
2
608
234
12
9
0
2
213
1080
LIBERIA
6
284
676
3
0
67
0
500
1536
PANAMA
173
1337
577
6
32
64
11
528
2728
UNITED
STATES OF
AMERICA
16
11
37
7
2
0
14
32
119
Note:
a This includes the People's Republic of China, Republic of (Taiwan), and Hong Kong.
Section 27 of the Merchant Marine Act of 1920, more commonly known as the Jones
Act, was enacted with the goal of maintaining a domestic merchant fleet of U.S.-owned and
U.S.-crewed vessels that is sufficient to carry the majority of U.S. waterborne commerce and
also to assist the military in times of war. The Jones Act fleet is a subset of the total U.S. fleet
and accounts for 52% of U.S.-flagged ships. The Maritime Administration (MARAD) is the
U.S. Department of Transportation agency responsible for monitoring and maintaining the
domestic merchant fleet, including the Jones Act fleet.
1.4 The Marine Transportation Sector
Over 95 percent of foreign trade was moved by ship in 2006.16 Fifty ports in the U.S.
handle approximately 84 percent of all waterborne domestic and international cargo; ten ports
handle 85 percent of all containerized cargo and have seen a 54 percent increase in container
movements between 2001 and 2006.10 The U.S. ranks second in container traffic after China;
one in nine containers is either bound for or originated from the U.S.17 It is expected that this
trade will continue to grow.
In 2007, the number of vessels calling on U.S. ports increased nearly 13 percent when
looking over the past five years; of these calls 34 percent were tankers, 31 percent
containerships, 17 percent dry-bulk vessels, 10 percent roll-on roll-off, and 6 percent by general
cargo ships.18 The size of vessels visiting U.S. ports has also increased, and in 2007, 54 percent
of the calls to U.S. ports were by vessels less than 10 years old, up 47 percent over the previous
five years.12 Figure 1-3 shows the vessel calls by flag to U.S. Ports in 2007.15
1-10
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Chapter 1: Industry Characterization
U.S.-flag
I2% I ,—-A_7 -Other
0.4%
Source: http://marad.dot.gov/documentsA^essel_Calls_at_US_Ports_Snapshot.pdf
Figure 1-3 2007 Vessel Calls by Flag to U.S. Ports
1.5 Marine Fuels
All marine fuel used today is created from the same basic distillation process that creates
other liquid hydrocarbons such as motor gasoline, heating oil and kerosene. Distillate marine
fuels are comparable to other forms of distillate hydrocarbon liquids, such as nonroad diesel fuel
or No. 2 fuel oil, in that they have similar chemical properties and specification limits. Residual
marine fuels, also called Intermediate Fuel Oils (IFO) or Heavy Fuel Oils (FIFO), are composed
of heavy, residuum hydrocarbons which are created as a by-product during petroleum refining,
and can contain various contaminants such as heavy metals, water, and high sulfur levels. These
contaminants can harm engines and fuel distribution lines and equipment, therefore residual fuel
is typically treated and 'cleaned' of a large amount of these contaminants prior to combustion in
the marine engine.
Both residual and distillate marine fuels are required to meet international fuel
specifications established in the International Organization for Standardization (ISO)
specification 8217 Petroleum products—Fuels (class F)—Specifications of Marine Fuels.19
Each category of fuel is discussed below.
Marine distillate fuel is divided into four distinct fuel types: DMX, DMA, DMB, and
DMC; however, only two of these fuels are commonly used in the marine transportation
industry. DMX is a very low sulfur middle distillate hydrocarbon, and is therefore rather
expensive when compared to other distillate fuels. This distillate type is mainly used onboard
marine vessels for emergencies. The next two types of distillate fuel, DMA & DMB, are also
called Marine Gas Oil (MGO) and Marine Diesel Oil (MDO) respectively. These two distillate
fuels comprise the majority of marine distillate fuels sold. Lastly, DMC, is a higher sulfur fuel
and is normally created by contaminating DMB fuel.
Marine residual fuel is created through traditional petroleum refining as a 'waste' product
of the refining process. Typically, this fuel is rather dense and viscous, and it tends to contain
heavy metals and other contaminants normally contained within crude oil. Residual fuel oil is
categorized by the viscosity of the fuel at a set reference temperature and there are several
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Regulatory Impact Analysis
categories of this fuel type; however, the most commonly used fuel in the marine transportation
industry is Intermediate Fuel Oil (IFO) 180 and 380.
1.5.1 Marine Gas Oil (MGO)
MGO is a light distillate product that is clear and bright, typically amber in color, and can
be manufactured by blending light cycle oil (LCO) with other light distillate oils. MGO is a
relatively light and clean gas oil, compared to other marine fuels. MGO also has a relatively high
cetane value and density, making it a fuel that is best suited for higher rpm engines. Typically,
MGO is used for propulsion in small- to medium-sized marine vessels and for emergency,
maintenance, and auxiliary engines in larger vessels.20
1.5.2 Marine Diesel Oil (MDO)
MDO is a distillate fuel that is a slightly heavier (i.e., higher density) gas oil and has a
lower cetane value than MGO. MDO is designated as distillate marine fuel grade B (DMB)
under ISO standards. Typically, MDO is created when MGO is blended with small amounts of
residual fuel oil, which raises the sulfur content of the fuel beyond the maximum allowable level
for MGO.
1.5.3 Intermediate Fuel Oil (IFO)
Typically, residual fuel oil is not usable as a stand-alone fuel because of purchasers' need
for specific performance characteristics, primarily viscosity. Thus, residual fuel oil normally
requires blending with lighter components to meet specifications for use in marine engines.
Blending with lighter components typically lowers the viscosity of the residual fuel oil to
produce IFO. IFO is the industry colloquial name for the most common fuel blends. These fuels
are categorized by their kinematic viscosity at a set reference temperature. IFO-180 and IFO-380
are the most common fuel grades used in OGV, and these fuels are designated as residual marine
fuel grades RME/F-180 and RMG/H-380 by ISO standard 8217. Additionally, since these fuels
have such a high viscosity, they are normally in a 'solid' state at ambient temperatures and
require constant heating in order to effectively pump and combust it in diesel engines.5
1.5.4 Marine Fuel Supply & Procurement
The actual volume of marine fuels supplied worldwide is the subject of great debate
inside the maritime community. This is because the majority of marine fuel consumed is
composed from residual waste, and other industries (such as power plants, asphalting, and
roofing) use this waste as well. The current estimation is that the world consumes approximately
350 million metric tonnes of marine fuel per year (350 mmt/yr), with about eighty percent
(80%), or 280 mmt/yr, being residual grade fuel.21
Marine fuels are purchased and delivered slightly differently than other fuels (like motor
gasoline or highway diesel). Marine fuels have "brokers" to purchase fuel and arrange delivery.
These broker companies typically never have custody of or title to the bunker fuel, but they
represent ship operators in the solicitation and negotiation of marine fuel purchases, and they
may help coordinate fuel delivery for the operators they represent. Fuel delivery can be achieved
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Chapter 1: Industry Characterization
through several ways; the most widely used method both in the United States and internationally
is delivery by barge. Delivery by barge allows for bunkering of vessels at port berths or at
anchorage within the port boundaries
1.5.5 Fuel Monitoring and Testing
In order to ensure that the fuel delivered is actually the fuel purchased, at least four
marine fuel samples are taken at the time of delivery. One sample is for the vessel (Chief
Engineer), one is for the bunker supplier, one is sent to an independent laboratory for testing
(e.g., DNV Petroleum Services), and one is for the International Maritime Organization (as
required by MARPOL Annex VI). Additionally, there are two other documents that provide
information on the quality of the fuel delivered to the vessel: the material safety data sheet
(MSDS) and the bill of sale or invoice.
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Regulatory Impact Analysis
References
1 U.S Department of Transportation, Maritime Administration (MARAD). (2008). U.S. Water
Transportation Statistical Snapshot. Washington, D.C.: Office of Congressional and Public
Affairs. Retrieved on March 27, 2009 from
http://www.marad.dot.gov/documents/US_Water_Transportation_Stati stical_snapshot.pdf
2 Irvine, S. (2009). Marine Fuel Industry Overview. Ann Arbor, MI: U.S. Environmental
Protection Agency. Docket EPA-HQ-OAR-2007-0121
3 Kopin, Amy (2009). Marine Vessel Industry Overview. Ann Arbor, MI: U.S. Environmental
Protection Agency.
4 U.S. Environmental Protection Agency, "Final Regulatory Support Document: Control of
Emissions from New Marine Compression-Ignition Engines at or Above 30 Liters per Cylinder,"
January 2003. Docket ID EPA420-R-03-004, can be found at:
http://www.epa.gov/otaq/regs/nonroad/marine/ci/r03004.pdf
5 Lloyd's Sea-Web Register of Ships, can be found at: http://www.sea-web.com
6 MAN, 2008 Annual Report, can be found at:
http ://www.mandiesel. com/files/news/filesof5 87/MAN%20Diesel%20 Annual%20Report_08 .pdf
7 Wartsila, 2008 Annual Report, can be found at
http://www.wartsila.com/Wartsila/global/docs/en/press/media_publications/annual_reports/Wart
sila_Annual_Report_2008_EN.pdf
8 http://www.mhi.co.jp/en/index.html
9 Wartsila, "World's Most Powerful Engine Enters Service." September, 2006. Can be found at:
http://www.datahotelli.com/servlet/Piccolo/2006/2006_09_12.html
10 Source: http://www.wartsila.com/,en,press,0,,823457F6-5CFF-4D16-BE26-
A3664B2ClAFD,,,.htm
11 http://www.mak-global.com
12 Diesel & Gas Turbine Worldwide Journal, June 2007 through May 2008.
13 Mercer, Mike. December 2007, "Onward and Upward." Diesel & Gas Turbine Worldwide.
14 Bo Svensson, "Wartsila Expands Thruster Facilities" September, 2008, Diesel & Gas Turbine
Worldwide.
15 Eyres, D.J. 2007. Ship Construction 6th Edition.
16 MARAD, "A Vision for the 21st Century" November 2008, U.S. Department of Maritime
Administration and the U.S. Department of Transportation.
17 Department of Transportation, Bureau of Transportation Statistics, April 2007.
18 MARAD, Vessel Calls at U.S. Ports Snapshot, 2007. Can be found at
http://marad.dot.gov/documents/Vessel_Calls_at_US_Ports_Snapshot.pdf
19
International Standard Organization (ISO). (2008) 8217:2005 Petroleum products — Fuels
(class F) — Specifications of Marine Fuels, http://www.iso.org
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Chapter 1: Industry Characterization
20 Vermerie, M.B. (2008). Everything You Need to Know About Marine Fuels. Ghent, Belgium:
Chevron Global Marine Products. Retrieved on March 27, 2009 from
http://www.fammllc.com/famm/publicati ons/fuels/EverythingAboutFuels_vO 108_LO.pdf.
21 Jameson, N. (2008). Complete Guide to the Bunker Market 2008. Singapore: Petromedial Pte
Ltd.
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CHAPTER 2: Air Quality, Health and Welfare Effects
2.1 Background on Pollutants Reduced by this Final Rule
The coordinated strategy that we are referencing in this final rule will reduce emissions of
PM, SOx and NOx. These emissions are associated with ambient PM, NOx, SOx, and ozone.
Background information on these pollutants is presented in this section.
2.1.1 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. Since 1987, EPA
has delineated that subset of inhalable particles small enough to penetrate to the thoracic region
(including the tracheobronchial and alveolar regions) of the respiratory tract (referred to as
thoracic particles). Current national ambient air quality standards (NAAQS) use PM2.5 as the
indicator for fine particles (with PM2 5 referring to particles with a nominal mean aerodynamic
diameter less than or equal to 2.5 jam), and use PMio as the indicator for purposes of regulating
the coarse fraction of PMi0 (referred to as thoracic coarse particles or coarse-fraction particles;
generally including particles with a nominal mean aerodynamic diameter greater than 2.5 jim
and less than or equal to 10 jam, or PMio-2.s). Ultrafine particles are a subset of fine particles,
generally less than 100 nanometers (0.1 um) in aerodynamic diameter.
Particles span many sizes and shapes and consist of hundreds of different chemicals.
Particles originate from 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 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 pollutants 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 hundreds to thousands of
kilometers.1
2.1.2 Ozone
Ground-level ozone pollution is formed by the reaction of VOCs and NOx in the
atmosphere in the presence of heat and sunlight. These pollutants, often referred to as ozone
precursors, are emitted by many types of pollution sources such as highway vehicles and
nonroad engines (including those subject to this rule), power plants, chemical plants, refineries,
makers of consumer and commercial products, industrial facilities, and smaller area sources.
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Chapter 2: Air Quality, Health and Welfare Effects
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 will occur on a single high-temperature day. Ozone can be
transported hundreds of miles downwind of 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-limited."
Because 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); 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.
2.1.3 Nitrogen Oxides and Sulfur 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 vapor 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. The health effects of ambient PM are discussed in Section 2.2.1.
NOx along with non-methane hydrocarbons (NMHC) are the two major precursors of ozone.
The health effects of ozone are covered in Section 2.2.2.
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2.1.4 Air Toxics - Diesel Exhaust PM
Marine diesel engines emit diesel exhaust (DE), a complex mixture composed 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 particulate matter (DPM) present in diesel exhaust consists of fine
particles (< 2.5|im), including a subgroup with a large number of ultrafine particles (< 0.1 jim).
These particles have a large surface area which makes them an excellent medium for adsorbing
organics, and their small size makes them highly respirable. Many of the organic compounds
present in the gases and on the particles, such as polycyclic organic matter (POM), are
individually known to have mutagenic and carcinogenic properties. 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 DPM (generally much less than one
percent of DPM), 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
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). Also, there are emissions differences
between on-road and nonroad engines because the nonroad engines are generally of older
technology. This is especially true for marine diesel engines.2 After being emitted in the engine
exhaust, 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.3
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.
2.2 Health Effects Associated with Exposure to Pollutants
The coordinated strategy that we are referencing in this final rule will reduce emissions of
PM, SOx and NOx. These emissions are associated with ambient PM, NOx, SOx, and ozone.
Health effects caused from exposure to these pollutants are presented in this section.
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Chapter 2: Air Quality, Health and Welfare Effects
2.2.1 Particulate Matter
This section provides a summary of the health effects associated with exposure to
ambient concentrations of PM.A The information in this section is based on the data and
conclusions in the PM Air Quality Criteria Document (PM AQCD) and PM Staff Paper prepared
by the U.S. Environmental Protection Agency (EPA).8'4'5 We also present additional recent
studies published after the cut-off date for the PM AQCD.6'0 Taken together this information
supports the conclusion that exposure to ambient concentrations of PM are associated with
adverse health effects.
Information specifically related to health effects associated with exposure to diesel
exhaust PM is included in Section 2.2.5.1 of this document.
2.2.1.1 Short-term Exposure Mortality and Morbidity Studies
As discussed in the PM AQCD, short-term exposure to PM2.5 is associated with
premature mortality from cardiopulmonary diseases,7 hospitalization and emergency department
visits for cardiopulmonary diseases,8 increased respiratory symptoms,9 decreased lung function10
and physiological changes or biomarkers for cardiac changes.11'12 In addition, the PM AQCD
described a limited body of new evidence from epidemiologic studies for potential relationships
between short term exposure to PM and health endpoints such as low birth weight, preterm birth,
and neonatal and infant mortality.13
Among the studies of effects associated with short-term exposure to PM2.5, several
specifically address the contribution of mobile sources to short-term PM2.s-related effects on
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 PM NAAQS is currently under review and the EPA is considering all available science on PM health effects,
including information which has been published since 2004, in the development of the upcoming PM Integrated
Science Assessment Document (ISA). A second draft of the PM ISA was completed in July 2009 and was
submitted for review by the Clean Air Scientific Advisory Committee (CASAC) of EPA's Science Advisory Board.
Comments from the general public have also been requested. For more information, see
http ://cfpub .epa.gov/ncea/cfm/recordisplay .cfm?deid=210586.
c These additional studies are included in the 2006 Provisional Assessment of Recent Studies on Health Effects of
Particulate Matter Exposure. The provisional assessment did not and could not (given a very short timeframe)
undergo the extensive critical review by CASAC and the public, as did the PM AQCD. The provisional assessment
found that the "new" studies expand the scientific information and provide important insights on the relationship
between PM exposure and health effects of PM. The provisional assessment also found that "new" studies generally
strengthen the evidence that acute and chronic exposure to fine particles and acute exposure to thoracic coarse
particles are associated with health effects. Further, the provisional science assessment found that the results
reported in the studies did not dramatically diverge from previous findings, and taken in context with the findings of
the AQCD, the new information and findings did not materially change any of the broad scientific conclusions
regarding the health effects of PM exposure made in the AQCD. However, it is important to note that this
assessment was limited to screening, surveying, and preparing a provisional assessment of these studies. For
reasons outlined in Section I.C of the preamble for the final PM NAAQS rulemaking in 2006 (see 71 FR 61148-49,
October 17, 2006), EPA based its NAAQS decision on the science presented in the 2004 AQCD.
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Regulatory Impact Analysis
premature mortality. The results from these studies generally indicated that several combustion-
related fine particle source-types are likely associated with mortality, including motor vehicle
emissions as well as other sources.14 The analyses incorporate source apportionment tools into
short-term exposure studies and are briefly mentioned here. Analyses incorporating source
apportionment by factor analysis with daily time-series studies of daily death rates indicated a
relationship between mobile source PM2 5 and mortality.15'16'17'18 Another recent study in 14 U.S.
cities examined the effect of PMio exposures on daily hospital admissions for cardiovascular
disease. This study found that the effect of PMi0 was significantly greater in areas with a larger
proportion of PMio coming from motor vehicles, indicating that PMio from these sources may
have a greater effect on the toxicity of ambient PMio when compared with other sources.19
These studies provide evidence that PM-related emissions, specifically from mobile sources, are
associated with adverse health effects.
2.2.1.2 Long-term Exposure Mortality and Morbidity Studies
Long-term exposure to ambient PM2 5 is associated with premature mortality from
cardiopulmonary diseases and lung cancer,20 and effects on the respiratory system such as
decreased lung function or the development of chronic respiratory disease.21 Of specific
importance, the PM AQCD also noted that the PM components of gasoline and diesel engine
exhaust represent one class of hypothesized likely important contributors to the observed
ambient PM-related increases in lung cancer incidence and mortality.22
The PM AQCD and PM Staff Paper emphasized the results of two long-term
epidemiologic studies, the Six Cities and American Cancer Society (ACS) prospective cohort
studies, based on several factors - the large air quality data set for PM in the Six Cities Study,
the fact that the study populations were similar to the general population, and the fact that these
studies have undergone extensive reanalysis.23'24'25'2627'28 These studies indicate that there are
positive associations for all-cause, cardiopulmonary, and lung cancer mortality with long-term
exposure to PM2 5. One analysis of a subset of the ACS cohort data, which was published after
the PM AQCD was finalized but in time for the 2006 Provisional Assessment, found a larger
association than had previously been reported between long-term PM2.5 exposure and mortality
from all causes and cardiopulmonary diseases in the Los Angeles area using a new exposure
estimation method that accounted for variations in concentration within the city.29
As discussed in the PM AQCD, the morbidity studies that combine the features of cross-
sectional and cohort studies provide the best evidence for chronic exposure effects. Long-term
studies evaluating the effect of ambient PM on children's development have shown some
evidence indicating effects of PM2 5 and/or PMio on reduced lung function growth.30 In another
recent publication included in the 2006 Provisional Assessment, investigators in southern
California reported the results of a cross-sectional study of outdoor PM2.5 and a measure of
atherosclerosis development in the Los Angeles basin.31 The study found positive associations
between ambient residential PM2 5 and carotid intima-media thickness (CEVIT), an indicator of
subclinical atherosclerosis that is an underlying factor in cardiovascular disease.
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Chapter 2: Air Quality, Health and Welfare Effects
2.2.2 Ozone
Exposure to ambient ozone contributes to a wide range of adverse health effects.0 These
health effects are well documented and are critically assessed in the EPA ozone air quality
criteria document (ozone AQCD) and EPA staff paper.32'33 We are relying on the data and
conclusions in the ozone AQCD and staff paper, regarding the health effects associated with
ozone exposure.
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.34 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.35'36'37'38'39'40
Repeated exposure to ozone can increase susceptibility to respiratory infection and lung
inflammation and can aggravate preexisting respiratory diseases, such as asthma.41'42'43'44'45
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
respiratory illnesses, such as emphysema and chronic bronchitis.46'47'48'49
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.50 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.51 For example, summer camp studies in the Eastern United States and
Southeastern Canada have reported statistically significant reductions in lung function in
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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Regulatory Impact Analysis
children who are active outdoors.52'53'54'55'56'57'58'59 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.60'61'62'63
2.2.3 Sulfur Oxides
This section provides an overview of the health effects associated with SC>2. Additional
information on the health effects of SC>2 can be found in the U.S. Environmental Protection
Agency Integrated Science Assessment for Sulfur Oxides.64 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 SC>2.
The immediate effect of SO2 on the respiratory system in humans is bronchoconstriction. This
response is mediated by chemosensitive receptors in the tracheobronchial tree. These receptors
trigger reflexes at the central nervous system level resulting in bronchoconstriction, mucus
secretion, mucosal vasodilation, cough, and apnea followed by rapid shallow breathing. In some
cases, local nervous system reflexes also may be involved. Asthmatics are more sensitive to the
effects of SC>2 likely resulting from preexisting inflammation associated with this disease. This
inflammation may lead to enhanced release of mediators, alterations in the autonomic nervous
system and/or sensitization of the chemosensitive receptors. These biological processes are
likely to underlie the bronchoconstriction and decreased lung function observed in response to
SC>2 exposure. In laboratory studies involving controlled human exposures to 862, respiratory
effects have consistently been observed following 5-10 min exposures at SC>2 concentrations >
0.2 ppm in asthmatics engaged in moderate to heavy levels of exercise. In these studies, 5-30%
of relatively healthy exercising asthmatics are shown to experience moderate or greater
decrements in lung function (> 100% increase in sRaw (specific airway resistance) or > 15%
decrease in FEVi (forced expiratory volume in 1 second)) with peak exposures to 862
concentrations of 0.2-0.3 ppm. At concentrations > 0.4 ppm, a greater percentage of asthmatics
(20-60%) experience SC>2-induced decrements in lung function, which are frequently
accompanied by respiratory symptoms. A clear concentration-response relationship has been
demonstrated in laboratory studies following exposures to 862 at concentrations between 0.2 and
1.0 ppm, both in terms of increasing severity of effect and 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 SO2 concentrations and respiratory symptoms
in children, particularly those with asthma. Furthermore, limited epidemiologic evidence
indicates that atopic children and adults may be at increased risk for SCVinduced respiratory
symptoms. Generally consistent associations also have been observed between ambient SC>2
concentrations and emergency department visits and hospitalizations for all respiratory causes,
particularly among children and older adults (> 65 years), and for asthma. Intervention studies
provide additional evidence that supports a causal relationship between SC>2 exposure and
respiratory health effects. Two notable studies conducted in several cities in Germany and in
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Chapter 2: Air Quality, Health and Welfare Effects
Hong Kong reported that decreases in 862 concentrations were associated with improvements in
respiratory symptoms, though the possibility remained that these health improvements may be
partially attributable to declining concentrations of air pollutants other than SC>2, most notably
PM or constituents of PM. 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 SC>2 effect
estimates, the effect of SC>2 on respiratory health outcomes appears to be generally robust and
independent of the effects of gaseous and paniculate 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 SC>2 and mortality have been
observed in epidemiologic studies, with larger effect estimates reported for respiratory mortality
than cardiovascular mortality. While this finding is consistent with the demonstrated effects of
SC>2 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 862 and mortality. Significant associations between short-term exposure to 862
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 SO2 exposure and cardiovascular
morbidity.
2.2.4 Nitrogen Oxides
This section provides an overview of the health effects associated with NC>2. Additional
information on the health effects of NC>2 can be found in the U.S. Environmental Protection
Agency Integrated Science Assessment (ISA) for Nitrogen Oxides.65 The U.S. 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.66 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.67 The effect
estimates from U.S. and Canadian studies generally indicate that ambient NC>2 is associated with
a 2-20% increase in risks for emergency department visits and hospital admissions. Risks
associated with respiratory symptoms are generally higher.68 These epidemiologic studies are
supported by evidence from experimental studies, in particular by controlled human exposure
studies that evaluate airway hyperresponsiveness in asthmatic individuals.69 The ISA draws two
broad conclusions regarding airway responsiveness following NC>2 exposure.70 First, the ISA
concludes that NO2 exposure may enhance the sensitivity to allergen-induced decrements in lung
function and increase the allergen-induced airway inflammatory response at exposures as low as
0.26 ppm NC>2 for 30 minutes.71 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.72 In general, small but significant increases in nonspecific airway
responsiveness were observed in the range of 0.2 to 0.3 ppm NC>2 for 30-minute exposures and at
0.1 ppm NC>2 for 60-minute exposures in asthmatics. These conclusions are consistent with
results from animal toxicological studies which have detected 1) increased immune-mediated
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pulmonary inflammation in rats exposed to house dust mite allergen following exposure to 5
ppm NC>2 for 3-hour and 2) increased responsiveness to non-specific challenges following sub-
chronic (6-12 weeks) exposure to 1 to 4 ppm NC>2.73 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.74 Together, the epidemiologic and experimental data sets form a plausible,
consistent, and coherent description of a relationship between NO2 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. For example, results from several large U.S. and European multi-city studies and a
meta-analysis study indicate positive associations between ambient NO2 concentrations and the
risk of all-cause (nonaccidental) mortality, with effect estimates ranging from 0.5 to 3.6% excess
risk in mortality per standardized increment (20 ppb for 24-hour averaging time, 30 ppb for 1-
hour averaging time).75 In general, the NC>2 effect estimates were robust to adjustment for co-
pollutants. In addition, generally positive associations between short-term ambient NO2
concentrations and hospital admissions or emergency department visits for cardiovascular
disease have been reported.76 A number of epidemiologic studies have also examined the effects
of long-term exposure to NC>2 and reported positive associations with decrements in lung
function and partially irreversible decrements in lung function growth.77 Specifically, results
from the California-based Children's Health Study, which evaluated NC>2 exposures in children
over an 8-year period, demonstrated deficits in lung function growth.78 This effect has also been
observed in Mexico City, Mexico79 and in Oslo, Norway,80 with decrements ranging from 1 to
17.5 ml per 20- ppb increase in annual NO2 concentration. Animal toxicological studies may
provide biological plausibility for the chronic effects of NC>2 that have been observed in these
epidemiologic studies.81 The main biochemical targets of NC>2 exposure appear to be
antioxidants, membrane polyunsaturated fatty acids, and thiol groups. NC>2 effects include
changes in oxidant/antioxidant homeostasis and chemical alterations of lipids and proteins.
Lipid peroxidation has been observed at NC>2 exposures as low as 0.04 ppm for 9 months and at
exposures of 1.2 ppm for 1 week, suggesting lower effect thresholds with longer durations of
exposure. Other studies showed decreases in formation of key arachidonic acid metabolites in
mornings following NO2 exposures of 0.5 ppm. NO2 has been shown to increase collagen
synthesis rates at concentrations as low as 0.5 ppm. This could indicate increased total lung
collagen, which is associated with pulmonary fibrosis, or increased collagen turnover, which is
associated with remodeling of lung connective tissue. Morphological effects following chronic
NO2 exposures have been identified in animal studies that link to these increases in collagen
synthesis and may provide plausibility for the deficits in lung function growth described in
epidemiologic studies.82
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2.2.5 Air Toxics
Category 3 vessel emissions 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.83 A number
of these compounds will be impacted by the standards finalized in this rule, including poly cyclic
organic matter (POM) and DPM. These compounds were identified as national or regional risk
drivers in the 2002 National-Scale Air Toxics Assessment (NATA).
According to NATA for 2002, mobile sources were responsible for 47 percent of outdoor
toxic emissions, over 50 percent of the cancer risk, and over 80 percent of the noncancer hazard.
Noncancer health effects can result from chronic,E subchronic,F or acute0 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 2002 NATA, nearly the
entire 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.
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 2002 NATA website.84 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.
2.2.5.1 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.85'86 In accordance with earlier EPA guidelines, exposure to diesel exhaust
£7 88
would similarly be classified as probably carcinogenic to humans (Group B1). ' 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.89' 90'91'92>93 The
E 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).
F Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days,
up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically
used laboratory animal species)..
G Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.
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Health Effects Institute has prepared numerous studies and reports on the potential
carcinogenicity of exposure to diesel exhaust.94'95'96
More specifically, the EPA Diesel HAD states that the conclusions of the document apply
to diesel exhaust in use today including both onroad and nonroad engines. 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 DE [diesel
exhaust] emissions (onroad vehicle emissions) over time, though there is no definitive
information to show that the emission changes portend significant toxicological changes." In
any case, the diesel technology used for marine diesel engines typically lags that used for onroad
engines which have been subject to PM standards since 1998. Thus it is reasonable to assume
that the hazards identified from older technologies may be largely applicable to marine engines.
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.97'98'99
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
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Chapter 2: Air Quality, Health and Welfare Effects
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.
EPA recently assessed air toxic emissions and their associated risk (the National-Scale
Air Toxics Assessment or NAT A for 1996 and 1999), and we concluded that diesel exhaust
ranks with other emissions that the national-scale assessment suggests pose the greatest relative
risk.100'101 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 from marine engines present public health issues of concern to this rule.
2.2.5.2 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.102'103'104'105 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
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Regulatory Impact Analysis
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."106 There is also evidence for an
immunologic effect such as the exacerbation of allergenic responses to known allergens and
asthma-like symptoms.107'108'109
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 2.2.1 of this RIA), 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.
2.2.5.3 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 here using ambient air quality modeling based on DPM emission
inventories.
2.2.5.3.1 Toxics Modeling and Methods
In addition to the general ambient PM modeling conducted for this rulemaking, DPM
concentrations were recently estimated as part of the 2002 National-Scale Air Toxics
Assessment.110 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 2002 NATA. The
median DPM concentration calculated nationwide is 0.91 ug/m3. Table 2-1 below summarizes
the distribution of ambient DPM concentrations at the national scale. Over half of the DPM and
diesel exhaust organic gases can be attributed to nonroad diesels. A map of ambient diesel PM
concentrations is provided in Figure 2-1. Areas with high median concentrations are clustered in
the Northeast, Great Lake States, California, and the Gulf Coast States, and are also distributed
throughout the rest of the U.S.
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2002 NATA
Diesel PM Concentrations (ug/m3)
| 0.25-0.50
| 0.50-0.75
0.75- 1.00
| 1.00-2.00
• 2.00- 15.00
Figure 2-1 Estimated County Ambient Concentration of Diesel Particulate Matter
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Table 2-1 Distribution of Census Tract Ambient Concentrations of DPM at the National Scale in 2002 NATAa
Nationwide (ug/m3)
5th Percentile 0.21
25th Percentile 0.54
Median 0.89
75th Percentile 1.34
95th Percentile 2.63
Onroad Contribution to Median 0.29
Nonroad Contribution to
Median 0.58
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 2002 NATA webpage
(http://www.epa.gov/ttn/atw/nata2002/tables.html).
2.2.5.4 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 paniculate
and exposure levels for diesel particulate is that exposure levels account for a person moving
from location to location, the proximity to the emission source, and whether the exposure occurs
in an enclosed environment.
2.2.5.4.1 Occupational Exposures
Occupational exposures to diesel exhaust from mobile sources, including marine diesel
engines, 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 including marine diesel engines.
2.2.5.4.2 Elevated Concentrations and Ambient Exposures in Mobile Source-Impacted Areas
While occupational studies indicate that those working in closest proximity to diesel
exhaust experience the greatest health effects, recent studies are showing that human populations
living near large diesel emission sources such as major roadways, m rail yards, m and marine
ports113 are also likely to experience greater exposure to PM and other components of diesel
exhaust than the overall population, putting them at a greater health risk.
Regions immediately downwind of marine ports may experience elevated ambient
concentrations of directly-emitted PM2.5 from diesel engines. Due to the nature of marine ports,
emissions from a large number of diesel engines are concentrated in a small area.
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Chapter 2: Air Quality, Health and Welfare Effects
A recent study from the California Air Resources Board (CARB) evaluated air quality
impacts of diesel engine emissions within the Port of Long Beach and Los Angeles in California,
one of the largest ports in the U.S.114 The port study employed the ISCST3 dispersion model.
With local meteorological data used in the modeling, annual average concentrations of DPM
were substantially elevated over an area exceeding 200,000 acres. Because the Ports are located
near heavily-populated areas, the modeling indicated that over 700,000 people lived in areas with
at least 0.3 |ig/m3 of port-related DPM in ambient air, about 360,000 people lived in areas with at
least 0.6 |ig/m3 of DPM, and about 50,000 people lived in areas with at least 1.5 |ig/m3 of
ambient DPM emitted directly from the port. Figure 2-2 provides an aerial shot of the Port of
Long Beach and Los Angeles in California.
y
Figure 2-2 Aerial Shot - Port of LA and Long Beach, California
This port study highlights the substantial contribution these facilities make to ambient
concentrations of DPM in large, densely populated areas.
EPA recently updated its initial screening-level analysis115'116 of selected marine port areas
to better understand the populations, including minority, low-income, and children, that are
exposed to diesel particulate matter (DPM) emissions from these facilities.11 The results of this
study are discussed here and are also available in the public docket.117'118
H This type of screening-level analysis is an inexact tool and not appropriate for regulatory decision-making; it is
useful in beginning to understand potential impacts and for illustrative purposes.
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This screening-level analysis focused on a representative selection of national marine
ports.1 Of the 45 marine ports studied, the results indicate that at least 18 million people,
including a disproportionate number of low-income households, African-Americans, and
Hispanics, live in the vicinity of these facilities and are being exposed to annual average ambient
DPM levels that are 2.0 |ig/m3 and 0.2 |ig/m3 above levels found in areas further from these
facilities. Considering only ocean-going marine engine DPM emissions, the results indicate that
6.5 million people are exposed to annual average ambient DPM levels that are 2.0 |ig/m3 and 0.2
|ig/m3 above levels found in areas further from these facilities. Because those populations exposed
to DPM emissions from marine ports are more likely to be low-income and minority residents,
these populations will benefit from the coordinated strategy. The detailed findings of this study
are available in the public docket for this rulemaking.
With regard to children, this analysis shows that at least four million children live in the
vicinity of the marine ports studied and are also exposed to annual average ambient DPM levels
that are 2.0 |ig/m3 and 0.2 |ig/m3 above levels found in areas further from these facilities. Of the
6.5 million people exposed to DPM emissions from ocean-going vessel emissions, 1.7 million
are children. The age composition of the total affected population in the screening analysis
matches closely with the age composition of the overall U.S. population. However, for some
individual facilities, the young (0-4 years) appear to be over-represented in the affected
population compared to the overall U.S. population. Detailed results for individual harbors are
presented in the Appendices of the memorandum in the docket.
As part of this study, a computer geographic information system was used to identify the
locations and boundaries of the harbor areas, and determine the size and demographic
characteristics of the populations living near these facilities. These facilities are listed in Table
2-2. Figures 2-3 and 2-4 provide examples of digitized footprints of the marine harbor areas
included in this study.
1 The Agency selected a representative sample from the top 150 U.S. ports including coastal, inland, and Great Lake
ports.
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Table 2-2 Marine Harbor Areas
Baltimore, MD
Boston, MA
Charleston, SC
Chicago, IL
Cincinnati, OH
Cleveland, OH
Corpus Christi, Tx
Detroit, MI
Duluth-Superior, MN
Freeport, Tx
Gary, IN
Helena, AR
Houston, Tx
Lake Charles, LA
Long Beach, CA
Los Angeles, CA
Louisville, KY
Miami, FL
Mobile, AL
Mount Vernon, IN
Nashville, TN
New Orleans, LA
New York, NY
Oakland, CA
Panama City, FL
Paulsboro, NJ
Philadelphia, PA
Pittsburgh, PA
Port Arthur, Tx
Port Everglades, FL
Port of Baton Rouge, LA
Port of Plaquemines, LA
Portland, ME
Portland, OR
Richmond, CA
Savannah, GA
Seattle, WA
South Louisiana, LA
St. Louis, MO
Tacoma, WA
Tampa, FL
Texas City, Tx
Tulsa - Port of Catoosa, OK
Two Harbors, MN
Wilmington, NC
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Figure 2-3 Digitized Footprint of New York, NY harbor area.
Figure 2-4 Digitized Footprint of Portland, OR harbor area.
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Chapter 2: Air Quality, Health and Welfare Effects
In order to better understand the populations that live in the vicinity of marine harbor
areas and their potential exposures to ambient DPM, concentration isopleths surrounding the 45
marine port areas were created and digitized for all emission sources at the marine port and for
ocean-going vessel Category 3 engine emissions only. The concentration isopleths of interest
were selected to correspond to two DPM concentrations above urban background, 2.0 |ig/m3 and
0.2 |ig/m3. The isopleths were estimated using the AERMOD air dispersion model. Figures 2-5
and 2-6 provide examples of concentration isopleths surrounding the New York, NY harbor area
for all emission sources and for ocean-going vessel Category 3 only engine emissions,
respectively.
E
Port of New York, NY
Figure 2-5 Concentration Isopleths of New York, NY Harbor Area Resulting from All Emission Sources.
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Regulatory Impact Analysis
N
Port of New York, NY
Figure 2-6 Concentration Isopleths of New York, NY Harbor Area Resulting from Category 3 Sources.
The size and characteristics of populations and households that reside within the area
encompassed by the two DPM concentration isopleths were determined for each isopleth, and the
demographic compositions were assessed, including age, income level, and race/ethnicity.
In summary, the screening-level analysis found that for the 45 U.S. marine ports studied,
al least 18 million people live in the vicinity of these facilities and are exposed to ambient DPM
levels from all port emission sources that are 2.0 |ig/m3 and 0.2 |ig/m3 above those found in areas
further from these facilities. If only Category 3 engine DPM emissions are considered, then the
number of people exposed is 6.5 million.
2.3 Environmental Impacts Associated with Pollutants
The coordinated strategy that we are referencing in this final rule will reduce emissions of
PM, SOx and NOx. These emissions are associated with ambient PM, NOx, SOx, and ozone.
Environmental effects due to these pollutants are presented in this section.
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2.3.1 Environmental Impacts Associated with Deposition of Nitrogen and Sulfur
Large ships release emissions over a wide area, and depending on prevailing winds and
other meteorological conditions, these emissions may be transported hundreds and even
thousands of kilometers across North America. Section 2.4 discusses the results of U.S. air
quality modeling which documents this phenomenon. Overall, these engines emit a large
amount of NOx, SOx and direct PM, which impact not only ambient air concentrations but also
contribute to deposition of nitrogen and sulfur in many sensitive ecological areas throughout the
U.S.
Sulfur in marine fuel is primarily emitted as SO2, with a small fraction (about 2 percent)
being converted to 863.119'120 863 almost immediately forms sulfate and is emitted as primary
PM by the engine and consists of carbonaceous material, sulfuric acid, and ash (trace metals).
The vast majority of the primary PM is less than or equal to 2.5 um in diameter, and accounts for
the majority of the number of particles in exhaust, but only a small fraction of the mass of DPM.
These particles also react in the atmosphere to form secondary PM, which exist there as a carbon
core with a coating of organic carbon compounds, nitrate particles, or as sulfuric acid and ash,
sulfuric acid aerosols, or sulfate particles associated with organic carbon.
At the same time, ships emit large amounts of NO and NO2 (NOx) which are carried into
the atmosphere where they may be chemically altered and transformed into new compounds.
For example, NO2 can be further oxidized to nitric acid (HNO3) and can contribute in that form
to the acidity of clouds, fog, and rain water and can also form ambient paniculate nitrate (pNOs)
which may be deposited either directly onto terrestrial and aquatic ecosystems ("direct
deposition") or deposited onto land surfaces where it subsequently runs off and is transferred into
downstream waters ("indirect deposition").
Deposition of nitrogen and sulfur resulting from ship operations can occur either in a wet
or dry form. Wet deposition includes rain, snow, sleet, hail, clouds, or fog. Dry deposition
includes gases, dust, and minute particulate matters. Wet and dry atmospheric deposition of
PM2.s delivers a complex mixture of metals (such as mercury, zinc, lead, nickel, arsenic,
aluminum, and cadmium), organic compounds (such as polycyclic organic matter, dioxins, and
furans) and inorganic compounds (such as nitrate and sulfate). Together these emissions from
ships are deposited onto terrestrial and aquatic ecosystems across the U.S., contributing to the
problems of acidification and nutrient enrichment.
Deposition of nitrogen and sulfur causes acidification, which alters biogeochemistry and
affects animal and plant life in terrestrial and aquatic ecosystems across the U.S. Major effects
include a decline in sensitive tree species, such as red spruce (Picea rubens) and sugar maple
{Acer saccharum); 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 geological characteristics.
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 the
acid neutralizing capacity and increases in inorganic aluminum concentration contribute to
declines in zooplankton, macro invertebrates, and fish species richness in aquatic ecosystems.
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Across the U.S., ecosystems will continue to be acidified by current NOx and SOx emissions
from stationary sources, area sources, and mobile sources. For example, in the Adirondacks
Mountains of New York State, the current rates of nitrogen and sulfur deposition exceed the
amount that would allow recovery of the most acid sensitive lakes to a sustainable acid
neutralizing capacity (ANC) level.121
Excess nitrogen deposition also leads to nutrient enrichment which can result in
eutrophication of aquatic ecosystems. In terrestrial ecosystems, nitrogen nutrient enrichment can
lead to the loss of sensitive lichen species as they are outcompeted by invasive grasses. Nitrogen
nutrient enrichment can also alter the biodiversity of terrestrial ecosystems, such as forests and
grasslands. Excess nitrogen deposition contributes to eutrophi cation of estuaries and coastal
waters which result in toxic algal blooms and fish kills. For example, the Chesapeake Bay
Estuary is highly eutrophic and 21 - 30% of total nitrogen load comes from atmospheric
deposition.122 Freshwater ecosystems may also be impacted by nitrogen deposition. For
example, high elevation freshwater lakes in the western U.S. experience negative ecological
effects at nitrogen deposition rates as low as 2 kg N/ha/yr.123
There are a number of important quantified relationships between nitrogen deposition
levels and ecological effects. Certain lichen species are the most sensitive terrestrial taxa to
nitrogen with species losses occurring at just 3 kg N/ha/yr in the Pacific Northwest and the
southern portion of the State of California (See Figure 2-9 for the geographic distribution of
these lichens in the continental U.S.). The onset of declining biodiversity was found to occur at
levels of 5 kg N/ha/yr and above within grasslands in Minnesota and in Europe. Altered species
composition of Alpine ecosystems and forest encroachment into temperate grasslands was found
at 10 kg N/ha/yr and above in the U.S.124
The biogeochemical cycle of mercury, a well-known neurotoxin, is closely tied to the
sulfur cycle. Mercury is taken up by living organisms in the methylated form, which is easily
bioaccumulated in the food web. Sulfate-reducing bacteria in wetland and lake sediments play a
key role in mercury methylation. Changes in sulfate deposition have resulted in changes in both
the rate of mercury methylation and the corresponding mercury concentrations in fish. In 2006,
3,080 fish advisories were issued in the U.S. due to the presence of methyl mercury in fish.
Although sulfur deposition is important to mercury methylation, several other interrelated
factors seem to also be related to mercury uptake, including low lake water pH, dissolved
organic carbon, suspended paniculate matter concentrations in the water column, temperature,
and dissolved oxygen. In addition, the proportion of upland to wetland land area within a
watershed, as well as wetland type and annual water yield, appear to be important.
2.3.1.1 Areas Potentially Sensitive to Nitrogen and Sulfur Deposition in the U.S.
The secondary NAAQS for NOx and SOx are currently being reviewed. As part of this
review, ecosystem maps (Figures 2-7 through 2-10)125 for the continental U.S. have been created
that depict areas that are potentially sensitive to aquatic and terrestrial acidification, and aquatic
and terrestrial nutrient enrichment. Taken together, these sensitive ecological areas are of
greatest concern with regard to the deposition of nitrogen and sulfur compounds resulting from
ship emissions. NOx and SOx emissions from ships today and in 2020 will significantly
2-24
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Chapter 2: Air Quality, Health and Welfare Effects
contribute to higher annual total nitrogen and sulfur deposition in all of these potentially
sensitive ecosystems. See Section 2.4.3.2 for a discussion and accompanying maps which
document both the level and geographic impact of ship emissions in 2020 on nitrogen and sulfur
deposition in the U.S.
2.3.1.1.1 TerrestrialAcidification-U.S. Geography
Deposition of total nitrogen (including both oxidized and reduced forms) and sulfur species
contributing to acidification were routinely measured in the U.S. between 2004 and 2006 and those
results are shown in Figures 2-7 and 2-8. Figure 2-7 depicts areas across the U.S. which are
potentially sensitive to terrestrial acidification including forest ecosystems in the Adirondack
Mountains located in the State of New York, the Green Mountains in the State of Vermont, the
White Mountains in the State of New Hampshire, the Allegheny Plateau in the State of
Pennsylvania, in the southeastern part of the U.S., and high-elevation ecosystems in the southern
Appalachians. In addition, areas of the Upper Midwest and parts of the State of Florida are also at
significant risk with regard to terrestrial acidification.
I Area at Higasl Potential Sensitivity
| Top Quartile N
I Top Ouartile S
t.000
:km
Figure 2-7 Areas Potentially Sensitive to Terrestrial Acidification
2.3.1.1.2 Aquatic Acidification- U. S. Geography
A number of national and regional assessments have been conducted to estimate the
distribution and extent of surface water acidity in the U S.126>127>128>129>130>131>132>133 >134 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.
2-25
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Regulatory Impact Analysis
Figure 2-8 illustrates those areas of the U.S. where aquatic ecosystems are at risk from
acidification. These sensitive ecological regions include: portions of the Northeast U.S.,
especially all the New England States, the Adirondacks, and the Catskill Mountains in the State
of New York; the Southeast U.S., including the Appalachian Mountains and the northern section
of the State of Florida; all upper Midwest States; and parts of the western U.S.,135 especially the
Los Angeles Basin and surrounding area and the Sierra Nevada Mountains in the State of
California. Two western mountain ranges with the greatest number of acid sensitive lakes136 are
the Cascade Mountains, stretching from northern California, through the entire States of Oregon
and Washington, and the Sierra Nevada's, found within the State of California. The hydrologic
cycles in these two mountain ranges are dominated by the annual accumulation and melting of a
dilute, mildly acidic snow pack. Finally, also in the western U.S., many Rocky Mountain lakes
in the State of Colorado are also sensitive to acidifying deposition effects.137 However, it does
not appear that chronic acidification has occurred to any significant degree in these lakes,
although episodic acidification has been reported for some.138
H'3h Potential Sensitivity
Acid Sensitive Waters (U5GS)
Figure 2-8 Areas Potentially Sensitive to Aquatic Acidification
2.3.1.1.3 Terrestrial Nutrient Enrichment-U.S. Geography
Nitrogen deposition affects terrestrial ecosystems throughout large areas of the U.S.139
Atmospheric nitrogen deposition is the main source of new nitrogen in many terrestrial
ecosystems throughout the U.S and impacts large numbers of forests, wetlands, freshwater bogs
and salt marshes.140 Figure 2-9 depicts those ecosystems potentially sensitive to terrestrial
nutrient enrichment resulting from nitrogen deposition, including nitrogen deposition from ships.
2-26
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Chapter 2: Air Quality, Health and Welfare Effects
Severe symptoms of nutrient enrichment or nitrogen saturation, have been observed in
forest ecosystems of the State of West Virginia's northern hardwood watersheds;141 in high-
elevation spruce-fir ecosystems in the Appalachian Mountains;142 in spruce-fir ecosystems
throughout the northeastern U.S.;143'144 and in lower-elevation eastern U.S. forests.145'146'147'148
In addition, mixed conifer forests in the Los Angeles Air Basin within the State of California are
also heavily impacted and exhibit the highest stream water nitrate concentrations documented
within wild lands in North America.149'150 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.151
In addition to these forest ecosystems, nitrogen deposition adversely impacts U.S.
grasslands or prairies which are located throughout the U.S.152 The vast majority of these
grasslands are found in the Central Plains regions of the U.S. between the Mississippi River and
the foothills of the Rocky Mountains. However, some native grasslands are scattered throughout
the Midwestern and Southeastern U.S.153 Also considered sensitive to nitrogen nutrient
enrichment effects, and receiving high levels of atmospheric deposition, are some arid and semi-
arid ecosystems and desert ecosystems in the southwestern U.S.154 However, water is generally
more limiting than nitrogen in these areas. The alpine ecosystems in the State of Colorado,
chaparral watersheds of the Sierra Nevada Mountains in the State of California, lichen and
vascular plant communities in the San Bernardino Mountains in California and the entire U.S.
Pacific Northwest, and the Southern California coastal sage scrub community are among the
most sensitive terrestrial ecosystems to nitrogen deposition in the U.S.155>156
Figure 2-9 Areas Potentially Sensitive to Terrestrial Nutrient Enrichment
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Regulatory Impact Analysis
2.3.1.1.4 Aquatic Nutrient Enrichment -V. S. Geography
Aquatic nutrient enrichment impacts a wide range of waters within the U.S. from
wetlands, to streams, rivers, lakes, estuaries and coastal waters. All are vital ecosystems to the
U.S. and all are impacted by ship emissions that contribute to the annual total nitrogen deposition
in the U.S.
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.157
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.158 Freshwater wetlands receive nitrogen mainly from
precipitation, land runoff or ground water. Intertidal wetlands develop on sheltered coasts or in
estuaries where they are periodically inundated by marine water that often carries high nitrogen
loads, in addition to receiving water and nutrient inputs from precipitation and ground/surface
water. Wetlands can be divided into three general categories based on hydrology: (1) Peatlands
and bogs, (2) fens, freshwater marshes, freshwater swamps and (3) intertidal wetlands.
Fens and bogs are the most vulnerable type of wetland ecosystems with regard to nutrient
enrichment effects of nitrogen deposition.159 In the U.S., they are mostly found in the glaciated
northeast and Great Lakes regions and in the State of Alaska, but also in the southeast U.S. along
the Atlantic Coastal Plain stretching from the States of Virginia through North Carolina to
northern Florida.160 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.161
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.162
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.163'164 Elevated
surface water nitrate concentrations due to nitrogen deposition occur in both the eastern and
western U.S., although high concentrations of nitrate in surface waters in the western U.S. are
not as widespread as in the eastern U.S.
High concentrations of lake or stream water nitrate, indicative of ecosystem nitrogen-
saturation, have been found at a variety of locations throughout the U.S. including the San
Bernardino and San Gabriel Mountains within the Los Angeles Air Basin in the State of
California, 165 the Front Range Mountains in the State of Colorado,166'167 the Allegheny
Mountains in the State of West Virginia,168 the Catskill and Adirondack Mountains in the State
of New York,169'170'171'172 ancj the Great Smoky Mountains in the State of Tennessee.
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Chapter 2: Air Quality, Health and Welfare Effects
Nitrogen nutrient enrichment is a major environmental problem facing all U.S. coastal
regions, but especially the Eastern, mid-Atlantic, and Gulf Coast regions, as excess nitrogen
leads to eutrophication. There is broad scientific consensus that nitrogen-driven eutrophication
of shallow estuaries in the U.S. has increased over the past several decades and that
173,174,175
A
environmental degradation of coastal ecosystems is now a widespread occurrence.
recent national assessment of eutrophic conditions in U.S. estuaries found that 65% of the
assessed systems had moderate to high overall eutrophic conditions.176 Estuaries and coastal
waters tend to be nitrogen-limited and are therefore inherently sensitive to increased atmospheric
nitrogen deposition.177 Of 138 estuaries examined in the National Assessment, 44 were
identified as showing symptoms of nutrient enrichment. Of the 23 estuaries examined in the
Northeast U.S., 61% were classified as moderately to severely degraded. Other regions of the
U.S. had mixtures of low, moderate, and high degree of eutrophication.178 The contribution from
atmospheric nitrogen deposition can be greater than 30% of total nitrogen loads in some of the
most highly eutrophic estuaries in the U.S., including the Chesapeake Bay.
I I SIMM
Nutrient Criteria Rivera
Total N Oep Total Sittogen
^^B TQpquarlile I^H 0.12
• 0.32 - 0 .33
•10.38-9.54
IZJOS5-058
Eao.ro-071
[. ID.7J. 076
CD 0.77-088
I I 0.6B • 0 90
IZZl 0.91-2.18
230 603 750
1,000
jkrr
Figure 2-10 Areas Potentially Sensitive to Aquatic Nutrient Enrichment
2-29
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Regulatory Impact Analysis
The most extreme effects of nitrogen deposition on U.S. aquatic ecosystems result in
severe nitrogen-loading to these ecosystems that contribute to hypoxic zones devoid of life.
Three hypoxia zones of special concern in the U.S. are (1) the zone located in the Gulf of Mexico
straddling the States of Louisiana and Texas, (2) The Chesapeake Bay located between the States
of Maryland and Virginia, and (3) Long Island Sound located between the States of New York
and Connecticut. The largest hypoxia zone in the U.S. is in the northern Gulf of Mexico along
the continental shelf. During midsummer, this zone has regularly been larger than 16,000km2.179
Figures 2-11,2-12, and 2-13 depict the location of these three hypoxic zones.
L Pitas *?
' '• ' ' ' ;;• i A H A
3i;^c vec oxygen
E3 ^2-0 rng/L
Sample locaticn
0 15 30 45 60
/\
N
Datisaaice: Li<\KOf),
Figure 2-11 Hypoxia Zone in 2007 for the Gulf of Mexico
<: o M N i <: T I c u I
MniHivtn
A
DM toart*: ComnMsitOfP. 200?
Figure 2-12 Hypoxia Zone in 2007 for Long Island Sound
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Chapter 2: Air Quality, Health and Welfare Effects
^. /*1
,-iV
V arying dis s olve d oxygen levels and overall fish c atch in the Che s ap e ake
Bay through July, 2 003. Source: Virginia Institute, of Marine Science
Figures 2-13 Hypoxia Zone for Chesapeake Bay in 2003
2.3.1.2 Science of 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, nutrient enrichment, and eutrophication.
Ships release emissions over a wide area, and depending on prevailing winds and other
meteorological conditions, these emissions may be transported hundreds and even thousands of
kilometers across North America. Section 2.4 discusses the results of U.S. air quality modeling
which documents this phenomenon. Overall, these engines emit a large amount of NOX, SOX,
and direct PM, which impact not only ambient air concentrations but also contribute to
deposition of nitrogen and sulfur in many sensitive ecological areas throughout the U.S.
Sulfur in marine fuel is primarily emitted as SC>2, with a small fraction (about 2 percent)
being converted to SO3.180 SO3 almost immediately forms sulfate and is emitted as primary PM
by the engine and consists of carbonaceous material, sulfuric acid, and ash (trace metals). The
vast majority of the primary PM is less than or equal to 2.5 um in diameter, and accounts for the
majority of the number of particles in exhaust, but only a small fraction of the mass of DPM.
2-31
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Regulatory Impact Analysis
These particles also react in the atmosphere to form secondary PM, which exist there as a carbon
core with a coating of organic carbon compounds, nitrate particles, or as sulfuric acid and ash,
sulfuric acid aerosols, or sulfate particles associated with organic carbon.
At the same time, ships emit large amounts of NO and NO2 (NOX) emissions which are
carried into the atmosphere where they may be chemically altered and transformed into new
compounds. For example, NO2 can also be further oxidized to nitric acid (HNO3) and can
contribute in that form to the acidity of clouds, fog, and rain water and can also form ambient
particulate nitrate (pNOs) which may be deposited either directly onto terrestrial and aquatic
ecosystems ("direct deposition") or deposited onto land surfaces where it subsequently runs off
and is transferred into downstream waters ("indirect deposition").
Deposition of nitrogen and sulfur resulting from ship operations can occur either in a wet
or dry form. Wet deposition includes rain, snow, sleet, hail, clouds, or fog. Dry deposition
includes gases, dust, and minute particulate matters. Wet and dry atmospheric deposition of
PM2.5 delivers a complex mixture of metals (such as mercury, zinc, lead, nickel, arsenic,
aluminum, and cadmium), organic compounds (such as polycyclic organic matter, dioxins, and
furans) and inorganic compounds (such as nitrate and sulfate). Together these emissions from
ships are deposited onto terrestrial and aquatic ecosystems across the U.S., contributing to the
problems of acidification and nutrient enrichment.
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. The atmospheric deposition of metals and toxic compounds is implicated in severe
ecosystem effects.181
Ships also emit primary PM. In addition, secondary PM is formed from NOX and SOX
gaseous emissions and associated chemical reactions in the atmosphere. The major constituents
of secondary PM are sulfate, nitrate, ammonium, and hydrogen ions. Secondary aerosol
formation depends on numerous factors including the concentrations of precursors; the
concentrations of other gaseous reactive species such as ozone, hydroxyl radical, peroxy radicals,
and hydrogen peroxide; atmospheric conditions, including solar radiation and relative humidity;
and the interactions of precursors and preexisting particles within cloud or fog droplets or on or
in the liquid film on solid particles.182
The lifetimes of particles vary with particle size. Accumulation-mode particles such as
the sulfates and nitrates are kept in suspension by normal air motions and have a lower
deposition velocity than coarse-mode particles; they can be transported thousands of kilometers
and remain in the atmosphere for a number of days. They are removed from the atmosphere
primarily by cloud processes. Dry deposition rates are expressed in terms of deposition velocity
that varies with the particle size, reaching a minimum between 0.1 and 1.0 |j,m Da.183
Particulate matter is a factor in acid deposition. Particles serve as cloud condensation
nuclei and contribute directly to the acidification of rain. In addition, the gas-phase species that
lead to the dry deposition of acidity are also precursors of particles. Therefore, reductions in
2-32
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Chapter 2: Air Quality, Health and Welfare Effects
NOx and 862 emissions will decrease both acid deposition and PM concentrations, but not
necessarily in a linear fashion. Sulfuric acid, ammonium nitrate, and organic particles also are
deposited on surfaces by dry deposition and can contribute to environmental effects.184
2.3.1.3 Computing Atmospheric Nitrogen and Sulfur Deposition to Specific Locations
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.185
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 previous
100 years.186 Direct fluxes of atmospheric nitrogen to ocean and gulf waters along the Northeast
and Southeast U.S. are now roughly equal to or exceed the load of new nitrogen from riverine
inputs at 11, 5.6, and 5.6 kg N/ha for the Northeast Atlantic coast of the U.S., the Southeast
_ 10*7
Atlantic coast of the U.S., and the U.S. Eastern Gulf of Mexico, respectively. Atmospheric
nitrogen is dominated by a number of sources, most importantly transportation sources, including
ships.
Nitrogen deposition takes different forms physically. Physically, deposition can be
direct, with the loads resulting from air pollutants depositing directly to the surface of a body of
water, usually a large body of water like an estuary or lake. In addition, there is an indirect
deposition component derived from deposition of nitrogen or sulfur to the rest of the watershed,
both land and water, of which some fraction is transported through runoff, rivers, streams, and
groundwater to the water body of concern.
Direct and indirect deposition of nitrogen and sulfur to watersheds depend 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
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%, 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 2-14.188 These airsheds extend well into U.S.
coastal waters where ships operate.
2-33
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Regulatory Impact Analysis
Figure 2-14 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).
Nitrogen inputs have been studied in several U.S. Gulf Coast estuaries, as well, owing to
concerns about eutrophication there. Nitrogen from atmospheric deposition in these locations is
estimated to be 10 to 40% of the total input of nitrogen to many of these estuaries, and could be
higher for some. Estimates of total nitrogen loadings to estuaries or to other large-scale elements
in the landscape are then computed using measurements of wet and dry deposition, where these
are available, and interpolated with or without a set of air quality model predictions such as the
Extended Regional Acid Deposition Model (Ext-RADM).189'190'191'192'193
Table 2-3 lists several water bodies for which atmospheric nitrogen inputs have been
computed and the ratio to total nitrogen loads is given. The contribution from the atmosphere
ranges from a low of 2-8% for the Guadalupe Estuary in the southern part of the State of Texas
to highs of-38% in the New York State Bight and the Albemarle-Pamlico Sound in the State of
North Carolina.
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Chapter 2: Air Quality, Health and Welfare Effects
Table 2-3 Atmospheric Nitrogen Loads Relative to Total Nitrogen Loads in Selected U.S. Great
Waters.*
Waterjwtly
Albemarle-Pauilico Sounds
Chesapeake Bay
Delaware Bay
Lous Island Sound
Narrasausett Bay
New York Bight
lot H! N Load
(million kg :\T}
1$
no
5-1
(id
f.
164
Almo$[iLei1rNLo*il
(mill ion kg yr)
9
3.6
&
12
06
62
Percent Load from the
38
:i
i?
10
12
38
Atmosphere
Based on ADN N loads from the watershed only (excluding direct N deposition to the bay surface):
ay, MA 0.022 0.0065 29
Based on ADN directly to the watejtody (excluding ADN loads from the watershed);
Delaware Inland Bays
Flanders Bay, NY
Guadnlupe Estuary, TX
Massachusetts Bays
Nairasansett Bay
Newport River Coastal Water*. NC
Potomac River. MD
Sarasota Bay. EL
Tampa Bay, FL
1.3
0.36
4.2-15.9
22 Ml
9
0.27--0.85
35,5
0.6
3,8
COS 21
0.02'
OJ1 2-8
1.6 6 5 -2"
0.4 4
0.095-0.68 -.^
1-9 5
Oifi 26
1.1 2S
ADN = atmospheric deposition of N
Scwce: ;*Tahiefi'om Deposition of Air Pollutants to the Great Waters-.^rd Report to Cong'ess CERA, 2000)
2.3.1.4 Summary of Ecological Effects Associated with Nitrogen and Sulfur Deposition
Deposition of reduced and oxidized nitrogen and sulfur species cause acidification,
altering biogeochemistry and affecting animal and plant life in terrestrial and aquatic ecosystems
across the U.S. Major effects include a decline in sensitive tree species, such as red spruce and
sugar maple; 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 geological characteristics (bedrock, weathering rates,
etc.).
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 contribute to declines in
zooplankton, macro invertebrates, and fish species richness in aquatic ecosystems. Across the
U.S., ecosystems continue to be acidified by current emissions from both stationary sources, area
sources, and mobile sources. For example, in the Adirondack Mountains of New York State, the
current rates of nitrogen and sulfur deposition exceed the amount that would allow recovery of
the most acid sensitive lakes to a sustainable acid neutralizing capacity (ANC) level.194
2-35
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Regulatory Impact Analysis
In addition to the role nitrogen deposition plays in acidification, nitrogen deposition also
causes ecosystem nutrient enrichment leading to eutrophication that alters biogeochemical
cycles. Excess nitrogen also leads to the loss of nitrogen sensitive lichen species as they are
outcompeted by invasive grasses as well as altering the biodiversity of terrestrial ecosystems,
such as grasslands and meadows. Nitrogen deposition contributes to eutrophi cation of estuaries
and the associated effects including toxic algal blooms and fish kills. For example, the
Chesapeake Bay Estuary is highly eutrophic and 21 - 30% of total nitrogen load comes from
deposition.195 Eutrophication also occurs in freshwater ecosystems. Symptoms, such as altered
algal communities occur in western U.S. high elevation lakes at nitrogen deposition rates a low
as 2 kg/ha/yr.196 Across the U.S., there are many terrestrial and aquatic ecosystems that have
been identified as particularly sensitive to nitrogen deposition.
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
197
ecosystems.
There are a number of important quantified relationships between nitrogen deposition
levels and ecological effects. Certain lichen species are the most sensitive terrestrial taxa to
nitrogen with species losses occurring at just 3 kg N/ha/yr in the U.S. Pacific Northwest and in
the southern portion of the State of California. The onset of declining biodiversity was found to
occur at levels of 5 kg N/ha/yr and above within grasslands in both the State of Minnesota and in
Europe. Altered species composition of Alpine ecosystems and forest encroachment into
temperate grasslands was found at 10 kg N/ha/yr and above in both the U.S. and Canada.198
A United States Forest Service study conducted in areas within the Tongass Forest in
Southeast Alaska found evidence of sulfur emissions impacting lichen communities. The
authors concluded that the main source of sulfur and nitrogen found in lichens from Mt. Roberts
is likely the burning of fossil fuels by cruise ships and other vehicles and equipment in
downtown Juneau.199 According to the Alaska DEC, damage to lichen populations has
widespread effects in Alaskan ecosystems.200
The biogeochemical cycle of mercury, a well-known neurotoxin, is closely tied to the
sulfur cycle. Mercury is taken up by living organisms in the methylated form, which is easily
bioaccumulated in the food web. Sulfate-reducing bacteria in wetland and lake sediments play a
key role in mercury methylation. Changes in sulfate deposition have resulted in changes in both
the rate of mercury methylation and the corresponding mercury concentrations in fish. In 2006,
3,080 fish advisories were issued in the U.S. due to the presence of methyl mercury in fish.
Although sulfur deposition is important to mercury methylation, several other interrelated
factors seem to also be related to mercury uptake, including low lake water pH, dissolved
organic carbon, suspended particulate matter concentrations in the water column, temperature,
and dissolved oxygen. In addition, the proportion of upland to wetland land area within a
watershed, as well as wetland type and annual water yield, appear to be important.
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Chapter 2: Air Quality, Health and Welfare Effects
2.3.1.5 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.201'202203'204 As a consequence, some
native species can be eliminated by nitrogen deposition.205'206207'208'209 Note the terms "low" and
"high" are relative to the amount of bioavailable nitrogen in the ecosystem and the level of
deposition.
Eutrophication effects resulting from excess nitrogen are more widespread than
acidification effects in western North America. Figure 2-15 highlights areas in the Western U.S.
where nitrogen effects have been extensively reported. The discussion of ecological effects of
nutrient enrichment that follows is organized around three types of ecosystem categories which
experience impacts from nutrient enrichment: terrestrial, transitional, and aquatic.
Rwer
Uke
National Fo-otbTU-tonaJ Part
1.2.3
(incipient Mages). 4
Af, ,.)'.-
^»* i '!"•-••- *
avD not txrcn styacd.
iserr.etal
Figure 2-15 Map of the Western U.S. Showing the Primary Geographic Areas where Nitrogen Deposition
Effects have been Reported
2-37
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Regulatory Impact Analysis
2.3.1.5.1 Terrestrial
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.210'211'212 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.213 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 2-9 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.214 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
2-4 provides a brief list of nitrogen deposition levels and associated ecological effects.
Table 2-4 Examples of Quantified Relationship between Nitrogen Deposition Levels and Ecological Effects"
Kg
N/ha/vr
-1.5
3.1
4
3
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 species 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 leaching in Eastern
forests of the U.S.
Multiple effects in tundra, bogs and
freshwater lakes in Europe (critical loads)
Multiple effects in arctic, alpine,
subalpine and scrub habitats in Europe
(critical loads)
Note:
a 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.215 The factors that govern the vulnerability of
terrestrial ecosystems to nutrient enrichment from nitrogen deposition include the degree of
2-38
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Chapter 2: Air Quality, Health and Welfare Effects
nitrogen limitation, rates and form of nitrogen deposition, elevation, species composition, length
of growing season, and soil nitrogen retention capacity.
Regions and ecosystems in the western U.S. where nitrogen nutrient enrichment effects
have been documented in terrestrial ecosystems are shown on Figure 2-15.216 The alpine
ecosystems of the Colorado Front Range, chaparral watersheds of the Sierra Nevada, lichen and
vascular plant communities in the San Bernardino Mountains and the Pacific Northwest, and the
southern California coastal sage scrub community are among the most sensitive terrestrial
ecosystems in the western U.S.
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
surface water. Studies have estimated the number of surface waters at different stages of
saturation across several regions in the eastern U.S.217 Of the 85 northeastern watersheds
examined, 40% were in nitrogen-saturation Stage 0,J 52% in Stage 1, and 8% 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.
2.3.1.5.2 Transitional
About 107.7 million acres of wetlands are widely distributed in the conterminous U.S.,
95% of which are freshwater wetlands and 5% are estuarine or marine wetlands218 (Figure 2-16).
At one end of the spectrum, bogs or peatland are very sensitive to nitrogen deposition because
they receive nutrients exclusively from precipitation, and the species in them are adapted to low
levels of nitrogen.219'220'221 Intertidal wetlands are at the other end of the spectrum; in these
ecosystems, marine/estuarine water sources generally exceed atmospheric inputs by one or two
orders of magnitude.222 Wetlands are widely distributed, including some areas that receive
moderate to high levels of nitrogen deposition.
Nitrogen deposition alters species richness, species composition and biodiversity in U.S.
wetland ecosystems.223 The effect of nitrogen deposition on these ecosystems depends on the
fraction of rainfall in its 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.224'225'226 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
1 In Stage 0, nitrogen inputs are low and there are strong nitrogen limitations on growth. Stage 1 is characterized by
high nitrogen rentention 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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Regulatory Impact Analysis
endangered by eastern U.S. Roundleaf sundew (Drosera rotundifolia) is also susceptible to
elevated atmospheric nitrogen deposition.227 This plant is native to, and broadly distributed
across, the U.S. and is federally listed as endangered in Illinois and Iowa, threatened in
T7S
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.229
Figure 2-16 Location of Wetlands in Continental U.S.
2. J. 1.5. J Freshwater Aquatic
Nitrogen deposition alters species richness, species composition and biodiversity in
freshwater aquatic ecosystems across the U.S.230 Evidence from multiple lines of research and
experimental approaches support this observation, including paleolimnological reconstructions,
bioassays, mesocosm and laboratory experiments. 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. In the
West, a hindcasting exercise determined that the change in Rocky Mountain National Park lake
algae that occurred between 1850 and 1964 was associated with an increase in wet nitrogen
T\ 1
deposition that was only about 1.5 kg N/ha. Similar changes inferred from lake sediment cores
of the Beartooth Mountains of Wyoming also occurred at about 1.5 kg N/ha deposition.232
Some freshwater algae are particularly sensitive to added nutrient nitrogen and
experience shifts in community composition and biodiversity with increased nitrogen deposition.
For example, two species of diatom (a taxanomic group of algae), Asterionella formosa and
Fragilaria crotonensis, now dominate the flora of at least several alpine and montane Rocky
Mountain lakes. Sharp increases have occurred in Lake xahOe.233'234'235'236'237'238 The timing of
this shift has varied, with changes beginning in the 1950s in the southern Rocky Mountains and
in the 1970s or later in the central Rocky Mountains. These species are opportunistic algae that
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Chapter 2: Air Quality, Health and Welfare Effects
have been observed to respond rapidly to disturbance and slight nutrient enrichment in many
parts of the world.
2.3.1.5.4 Estuarine Aquatic
Nitrogen deposition also alters species richness, species composition and biodiversity in
estuarine ecosystems throughout the U.S.239 Nitrogen is an essential nutrient for estuarine and
marine fertility. However, excessive nitrogen contributes to habitat degradation, algal blooms,
toxicity, hypoxia (reduced dissolved oxygen), anoxia (absence of dissolved oxygen), reduction of
sea grass habitats, fish kills, and decrease in biodiversity.240'241'242'243'244245 Each of these
potential impacts carries ecological and economic consequences. Ecosystem services provided
by estuaries include fish and shellfish harvest, waste assimilation, and recreational activities.246
Increased nitrogen deposition can cause shifts in community composition, reduced
hypolimnetic DO, reduced biodiversity, and mortality of submerged aquatic vegetation. The
form of deposited nitrogen can significantly affect phytoplankton community composition in
estuarine and marine environments. Small diatoms are more efficient in using nitrate than NH4+.
Increasing NH4+ deposition relative to nitrate in the eastern U.S. favors small diatoms at the
expense of large diatoms. This alters the foundation of the food web. Submerged aquatic
vegetation is important to the quality of estuarine ecosystem habitats because it provides habitat
for a variety of aquatic organisms, absorbs excess nutrients, and traps sediments. Nutrient
enrichment is the major driving factor contributing to declines in submerged aquatic vegetation
coverage. The Mid-Atlantic region is the most heavily impacted area in terms of moderate or
high loss of submerged aquatic vegetation due to eutrophication.
2.3.1.5.5 Estuarine and Coastal Aquatic
Estuaries and coastal waters tend to be nitrogen-limited and are therefore inherently
sensitive to increased atmospheric nitrogen loading.247'248 The U.S. national estuary condition
assessment completed in 2007249 found that the most impacted estuaries in the U.S. occurred in
the mid- Atlantic region and the estuaries with the lowest symptoms of eutrophication were in
the North Atlantic. Nitrogen nutrient enrichment is a major environmental problem for coastal
regions of the U.S., especially in the eastern and Gulf Coast regions. Of 138 estuaries examined
in the national estuary assessment, 44 were identified as showing symptoms of nutrient over-
enrichment. Estuaries are among the most biologically productive ecosystems on Earth and
provide critical habitat for an enormous diversity of life forms, especially fish. Of the 23
estuaries examined in the national assessment in the Northeast, 61% were classified as
moderately to severely degraded.250 Other regions had mixtures of low, moderate, and high
degree of eutrophication (See Figure 2-17).
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Regulatory Impact Analysis
.-
S
14 IS
ni
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100 "*
,-moJap
' ' Mcd*rBt* h*gft: tyrrpMr-'fj oit'j' letd regtjorty ondwowf
' ' Medprnfer: lyrvtixri* 3i?HF JIB* r^guteity jnd'4ir r»v»i 9 rod i
^^ Mod«raf» h-w: 5'«niplan» occur epiHKKcai/ aiKVoruv
Low: tew ajmptotns O:CTJI at more Ihtm mltwrail levels.
«(U«A#rU uiu Ay in«v*l>
Chang* in
'— ' Wo 4ntnfl4 ln> JyTnpBflU HUM 1 vvv
V Er-nHuni mnHKKl srcc 1909 asdnjur™r(
Figure 2-17 Overall Eutrophication Condition on a National Scale
The national assessment also evaluated the future outlook of the nation's estuaries based
on population growth and future management plans. They predicted that trophic conditions
would worsen in 48 estuaries, stay the same in 11, and improve in only 14 by the year 2020.
Between 1999 and 2007, an equal number of estuary systems have improved their trophic status
as have worsened. The assessed estuarine surface area with high to moderate/high eutrophic
rjsi " OSO
conditions have stayed roughly the same, from 72% in 1999, to 78% in the 2007 assessment. 'L
2.3.1.6 Ecological Effects of Acidification
The U.S. EPA's Integrated Science Assessment for Oxides of Nitrogen and Sulfur-
Ecological Criteria found that the principal factor governing the sensitivity of terrestrial and
aquatic ecosystems to acidification from nitrogen and sulfur deposition is geology (particularly
surficial geology).253 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.254'255'256'257'258 Other factors contribute to the sensitivity of soils and surface
waters to acidifying deposition, including topography, soil chemistry, land use, and hydrologic
flow path.
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Chapter 2: Air Quality, Health and Welfare Effects
2.3.1.6.1 Terrestrial
Acidifying deposition has altered major biogeochemical processes in the U.S. 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.259 These direct effects
can, in turn, 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 disease260 leading to increased mortality of canopy trees. In the U.S., terrestrial effects
of acidification are best described for forested ecosystems (especially red spruce and sugar maple
ecosystems) with additional information on other plant communities, including shrubs and
lichen.261 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.262
2.3.1.6.1.1 Health, Vigor, and Reproduction of Tree Species in Forests
Both coniferous and deciduous forests throughout the eastern U.S. 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. For red spruce,
(Picea rubens) 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.263 Since the 1980s, red spruce growth has increased at both the
higher- and lower-elevation sites corresponding to a decrease in SC>2 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% of
the variability in red spruce tree ring growth between 1940 and 1998, while climatic variability
accounted for about 8% of the growth variation for that period.264 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 10° F.265 More recently, studies
have found a link between availability of soil calcium and winter injury.266 Figure 2-18 shows
the distribution of red spruce (brown) and sugar maple (green) in the eastern U.S.
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Regulatory Impact Analysis
Figure 2-18 Distribution of Red Spruce (pink) and Sugar Maple (green) in the Eastern U.S.
267
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
(Primuspensylvanica), striped maple (Acer pensylvanicum), white ash (Fraxinus americana),
yellow birch (Betula alleghaniensis) and white birch (Betulapapyri/era) in younger stands to
beech (Fagus grandifolid) and red maple (Acer rubrum) in older stands, there is an increase in
sensitivity to acidification.268
Sugar maple (Acer saccharum) is the deciduous tree species of the northeastern U.S. and
central Appalachian Mountain region (See Figure 2-18) that is most commonly associated with
adverse acidification-related effects of nitrogen and sulfur deposition.269 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.270
Loss of calcium ions in the base cations has also been implicated in increased
susceptibility of flowering dogwood (Cornus floridd) to its most destructive disease, dogwood
anthracnose, a mostly fatal disease. Figure 2-19 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). Flowering dogwood is a dominant understory species of hardwood forests in the eastern
U.S.271
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Chapter 2: Air Quality, Health and Welfare Effects
Figure 2-19 Native Range of Flowering Dogwood (dark gray) and the Documented Range of Dogwood
Anthracnose (red)
273
The NOxSOx ISA found limited data on the possible effects of nitrogen and sulfur
deposition on the acid-based characteristics of forests in the U.S., other than spruce-fire and
northern hardwood forests ecosystems as described above.
2.3.1.6.1.2 Health and Biodiversity of Other Plant Communities
Shrubs
The 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. However,
conclusive evidence is generally lacking.
Lichens
The U.S. EPA NOXSOX ISA 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.274 Even in
the Pacific Northwest, which receives uniformly low levels of nitrogen deposition, changes from
acid-sensitive and nitrogen-sensitive to pollution tolerant nitrophillic lichen taxa are occurring in
275
some areas. Lichens remaining in areas affected by acidifying deposition were found to
contain almost exclusively the families Candelariaccae, Physciaceae, and Teloschistaceae.
276
Effects of sulfur dioxide exposure to lichens includes: reduced photosynthesis and
respiration, damage to the algal component of the lichen, leakage of electrolytes, inhibition of
nitrogen fixation, reduced K absorption, and structural changes.277'278 Additional research has
concluded that the sulfur:nitrogen exposure ratio is as important as pH in causing toxic effects on
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Regulatory Impact Analysis
lichens. Thus, it is not clear to what extent acidity may be the principal stressor under high
levels of air pollution exposure. The toxicity of sulfur dioxide to several lichen species is greater
under acidic conditions than under neutral conditions.279'280 The effects of excess nitrogen
deposition to lichen communities are discussed in Section 2.3.1.4.
Arctic and Alpine Tundra
The NOXSOX ISA found that the possible effects of acidifying deposition on arctic and
alpine plant communities are also of concern. Especially important in this regard is the role of
nitrogen deposition in regulating ecosystem nitrogen supply and plant species composition. Soil
acidification and base cation depletion in response to acidifying deposition have not been
documented in arctic or alpine terrestrial ecosystems in the U.S. Such ecosystems are rare and
spatially limited in the eastern U.S., where acidifying deposition levels have been high. These
ecosystems are more widely distributed in the western U.S. and throughout much of Alaska, but
acidifying deposition levels are generally low in these areas. Key concerns are for listed
threatened or endangered species and species diversity.
2.3.1.6.1.3 Aquatic Ecosystems
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.281
Biological effects in aquatic ecosystems can be divided into two major categories: effects on
health, vigor, and reproductive success; and effects on biodiversity.
2.3.1.7 Case Study: Critical Load Modeling in the Adirondack Mountains of New York
State and the Blue Ridge Mountains in the State of Virginia
The Adirondack Mountains of New York and the Blue Ridge Mountains of Virginia have
long been a locus for awareness of the environmental issues related to acidifying deposition.
Soils and water bodies, such as lakes and streams, usually buffer the acidity from natural rain
with "bases," the opposite of acids, from the environment. The poor buffering capability of the
soils in both these regions make the lakes and streams particularly susceptible to acidification
from anthropogenic nitrogen and sulfur atmospheric deposition resulting from nitrogen and
sulfur oxides emissions. Consequently, acidic deposition has affected hundreds of lakes and
thousands of miles of headwater streams in both of these regions. The diversity of life in these
acidic waters has been reduced as a result of acidic deposition.
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Chapter 2: Air Quality, Health and Welfare Effects
The critical load approach provides a quantitative estimate of the exposure to one or more
pollutants below which significant harmful effects on specific sensitive elements of the
environment do not occur according to present knowledge. The critical load for a lake or stream
provides a means to gauge the extent to which a water body has recovered from past acid
deposition, or is potentially at risk due to current deposition levels. Acid neutralizing capacity
(ANC) is an excellent indicator of the health of aquatic organisms such as fish, insects, and
invertebrates.
Figure 2-20 Locations of Lakes and Streams where Critical Loads were Calculated
In this case study, the focus is on the combined load of nitrogen and sulfur deposition
below which the ANC level would still support healthy aquatic ecosystems. Critical loads were
calculated for 169 lakes in the Adirondack region and 60 streams in Virginia (Figure 2-20). The
Steady-State Water Chemistry (SSWC) model was used to calculate the critical load, relying on
water chemistry data from the USEPA Temporal Intergraded Monitoring of Ecosystems (TIME)
and Long-term Monitoring (LTM) programs and model assumptions well supported by the
scientific literature. Research studies have shown that surface water with ANC values greater
than 50 ueq/L tend to protect most fish (i.e., brook trout, others) and other aquatic organisms
(Table 2-5 ). In this case, the critical load represents the combined deposition load of nitrogen
and sulfur to which a lake or stream could be subjected and still have an ANC of 50 ueq/L.
Critical loads of combined total nitrogen and sulfur are expressed in terms of ionic charge
balance as milliequivalent per square meter per year (meq/m2/yr).
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Regulatory Impact Analysis
Table 2-5 Aquatic Status Categories
CATEGORY LABEL ANC LEVELS* EXPECTED ECOLOGICAL EFFECTS
Acute
Concern
<0 micro
equivalent
per Liter
(ueq/L)
Complete loss of fish populations is expected. Planktonic
communities have extremely low diversity and are dominated by
acidophilic forms. The numbers of individuals in plankton species
that are present are greatly reduced.
Severe
Concern
0-20
ueq/L
Highly sensitive to episodic acidification. During episodes of high
acid deposition, brook trout populations may experience lethal
effects. Diversity and distribution of zooplankton communities
decline sharply.
Elevated
Concern
20-50
ueq/L
Fish species richness is greatly reduced (more than half of expected
species are missing). On average, brook trout populations experience
sub-lethal effects, including loss of health and reproduction (fitness).
Diversity and distribution of zooplankton communities also decline.
Moderate
Concern
50 - 100
ueq/L
Fish species richness begins to decline (sensitive species are lost
from lakes). Brook trout populations are sensitive and variable, with
possible sub-lethal effects. Diversity and distribution of zooplankton
communities begin to decline as species that are sensitive to acid
deposition are affected.
Low
Concern
>100 ueq/L
Fish species richness may be unaffected. Reproducing brook trout
populations are expected where habitat is suitable. Zooplankton
communities are unaffected and exhibit expected diversity and
range.
When the critical load is "exceeded," it means that the amount of combined nitrogen and
sulfur atmospheric deposition is greater than the critical load for a particular lake or stream,
preventing the water body from reaching or maintaining an ANC concentration of 50 ueq/L.
Exceedances were calculated from deposition for years 2002 and 2020 with and without
emissions from shipping. In year 2002, there was no difference in the percent of lakes or streams
in both regions that exceeded the critical load for the case with and without ship emissions
(Table 2-6). For the year 2020, when ship emissions are present, 33% of lakes in the Adirondack
Mountains and 52% of streams in the Virginia Blue Ridge Mountains received greater acid
deposition than could be neutralized. When ship emissions were removed from the modeling
domain for the year 2020, 31- and 50% of lakes and streams, respectively, received greater acid
deposition than could be neutralized a 2% improvement.
2.3.1.7.1 Regional Assessment
A regional estimate of the benefits of the reduction in international shipping emissions in
2020 can be derived from scaling up the results from 169 lakes to a larger population of lakes in
the Adirondack Mountains. One hundred fifteen lakes of the 169 lakes modeled for critical loads
are part of a subset of 1,842 lakes in the Adirondacks, which include all lakes from 0.5 to 2,000
ha in size and at least 0.5 meters in depth. Using weighting factors derived from the EMAP
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Chapter 2: Air Quality, Health and Welfare Effects
probability survey and the critical load calculations from the 115 lakes, exceedance estimates
were derived for the entire 1,842 lakes in the Adirondacks. Based on this approach, 66 fewer
lakes in the Adirondack Mountains are predicted to receive nitrogen and sulfur deposition loads
below the critical load and would be protected as a result of removing international shipping
emissions in 2020.
Currently, no probability survey has been completed for the study area in Virginia.
However, the 60 trout streams modeled are characteristic of first and second order streams on
non-limestone bedrock in the Blue Ridge Mountains of Virginia. Because of the strong
relationship between bedrock geology and ANC in this region, it is possible to consider the
results in the context of similar trout streams in the Southern Appalachians that have the same
bedrock geology and size. In addition, the 60 streams are a subset of 344 streams sampled by the
Virginia Trout Stream Sensitivity Study, which can be applied to a population of 304 out of the
original 344 streams. Using the 304 streams to which the analysis applies directly as the total, 6
additional streams in this group would be protected as a result of removing international shipping
emissions in 2020. However, it is likely that many more of the -12,000 trout streams in Virginia
would benefit from reduced international shipping emissions given the extent of similar bedrock
geology outside the study area.
Table 2-6 Percent of Modeled Lakes that Exceed the Critical Load for Years 2002 and 2020 with and without
International Shipping Emissions. "Zero" Indicates without International Shipping Emissions
2002
2002 ZERO
2020
2020 ZERO
Adirondack Mountains
Exceeded Critical Load
(%. Lakes)
Non-Exceeded Critical Load (%. Lakes)
45
55
45
55
33
73
31
71
Virginia Blue Ridge Mountains
Exceeded Critical Load
(%. Lakes)
Non-Exceeded Critical Load (%. Lakes)
82
18
82
18
52
48
50
50
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Regulatory Impact Analysis
2S02 with International
Shipping Emissions
2002 without Inremartiorai
Shipping Emission;
;
* «- • • *J
•ftr %• i-*
i. *
Critical Load £xceed«nc«&
I > ANC of 5ft ueqit)
|
Figure 2-21 a. 2002
2020 with Internaironal
snipping Emisskons
Shipping tin :i-iiir•;
t* "",*;• •*
s"^ ".*«** •*
Ctilic.il Loud Excccdcncts
I > ANC erf SO ucqiLJ
|
Figure 2-21 b. 2020; Critical Load Exceedance for ANC Concentration of 50 jieq/L. Green dots represent
lakes in the Adirondack Mountains where current nitrogen and sulfur deposition is below their critical load
and maintains an ANC concentration of 50 jieq/L. Red dots are lakes where current nitrogen and sulfur
deposition exceeds their limit and the biota are likely impacted.
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Chapter 2: Air Quality, Health and Welfare Effects
2042 with International
Shipping 1 -i i -.,].::-.
JP02 without international
Shipping Emissions
Critical Load Excellences
( > ANC of SO ueqrt.)
| [
Figure 2-22 a. 2002
2020 with International
Shipping Emissions
J02Q w*|M5«t intflrnational
Shipping Emissions
Critical Load Exceedences
( > ANC of 50 ueqrt.)
| |
Figure 2-22 b. 2020; Critical Load Exceedances for ANC Concentration of 50 jieq/L. Green dots represent
streams in the Virginia Blue Ridge Mountains where current nitrogen and sulfur deposition is below their
critical load and maintains an ANC concentration of 50 jieq/L. Red dots are streams where current nitrogen
and sulfur deposition exceeds their limit and the biota are likely impacted.
2.3.2 Environmental Impacts Associated with Deposition of Particulate Matter
Current international shipping emissions of PM2.5 contain small amounts of metals:
nickel, vanadium, cadmium, iron, lead, copper, zinc, aluminum.282'283'284 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
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Regulatory Impact Analysis
vegetation under field conditions.285 While metals typically exhibit low solubility, limiting their
bioavailability and direct toxicity, chemical 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.286 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.287 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.288'289
Ships also emit air toxics, including polycyclic aromatic hydrocarbons (PAHs) — a class
of poly cyclic 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.290'291'292'293'294 Atmospheric deposition of particles is believed to be the major source of
PAHs to the sediments of Lake Michigan in the Great Lakes, Chesapeake Bay which is
surrounded by the States of Maryland and Virginia, Tampa Bay in the central part of the State of
Florida and in other coastal areas of the U.S.295 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.296'297 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.
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Chapter 2: Air Quality, Health and Welfare Effects
2.3.3 Environmental Impacts Associated with Visibility Degradation
International shipping activity contributes to poor visibility in the U.S. through their
primary PM2.5 emissions as well as NOx and SOx emissions (which contribute to the formation
of secondary PM^.s). These airborne particles degrade visibility by scattering and absorbing
light. Good visibility increases the quality of life where individuals live and work, and where
they engage in recreational activities.
2.3.3.1 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 since 1988. The monitoring network was
originally established at 20 sites, but it has now been expanded to 110 sites that represent all but
one of the 156 mandatory class I federal areas across the country (see figure 2-23). 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, with the exception of urban-influenced
sites such as San Gorgonio Wilderness (CA) and Point Reyes National Seashore (CA), which
have annual average levels comparable to certain sites in the Northeast. Regional differences are
illustrated by Figures 4-39a and 4-39b in the Air Quality Criteria Document for Particulate
Matter, which show that, for Class I areas, visibility levels on the 20% haziest days in the West
are about equal to levels on the 20% best days in the East.298
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Regulatory Impact Analysis
Higher visibility impairment levels in the East 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% of the haziness in eastern sites.299 Aerosol light extinction
due to sulfate on the 20% 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).300 With the exception of remote sites in the northwestern U.S., visibility is typically
worse in the summer months. This is particularly true in the Appalachian region, where average
light extinction in the summer exceeds the annual average by 40%.301
2.3.3.2 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
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.K OGVs, powered by Category 3
engines, contribute to visibility concerns in these areas through their primary PM2.5 emissions
and their NOx and SOx emissions, which contribute to the formation of secondary PM2.5.
K 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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Chapter 2: Air Quality, Health and Welfare Effects
Produced by NPS Air Resources Division
* Rainbow Lake, Wl and Bradwell Bay, FL are Class 1 Areas
where uisibility is not an important air quality related ualue
Figure 2-23 Mandatory Class I Areas in the U.S.
2.3.4 Impacts of Ozone on Plants and Ecosystems
There are a number of environmental or public welfare effects associated with the
presence of ozone in the ambient air.302 In this section, we discuss the impact of ozone on plants,
including trees, agronomic crops and urban ornamentals.
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".303 Like carbon dioxide (€62) and other
gaseous substances, ozone enters plant tissues primarily through apertures (stomata) in leaves in
a process called "uptake".304 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.305'306 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,307 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, leading 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
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Regulatory Impact Analysis
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
for transfer from the host to the symbiont.308'309
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). Because ozone damage
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)310'311'312 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.313
Because of 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.
Ozone also has been conclusively shown to cause discernible injury to forest trees.314'315
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.316'317
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.318 In most instances, responses to chronic or
recurrent exposure in forested ecosystems are subtle and not observable for many years. These
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Chapter 2: Air Quality, Health and Welfare Effects
injuries can cause stand-level forest decline in sensitive ecosystems.319'320'321 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."322 In addition, economic studies have shown
reduced economic benefits as a result of predicted reductions in crop yields associated with
observed ozone levels.323'324'325
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.326
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 noteworthy cumulative impacts on forested ecosystems by
affecting regeneration, productivity, and species composition.327 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.328
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
systematic sampling grid, based on a global sampling design.329'330 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 over the last 10 years from monitoring sites in
10 states in 1994 to nearly 1,000 monitoring sites in 41 states in 2002.
2.3.4.1 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 U.S. Department of Agriculture (USDA) Forest Service Forest Inventory and Analysis (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).
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Regulatory Impact Analysis
Sites are selected using a systematic sampling grid, based on a global sampling design.331'332
Because 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 2-24 are based on averages of all observations collected in 2002, the latest year
for which data are 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.333
The highest percentages of observed high and severe foliar injury, those which are most
likely to be associated with tree or ecosystem-level responses, are primarily found in the Mid-
Atlantic and Southeast regions. In EPA Region 3 (which comprises the States of Pennsylvania,
West Virginia, Virginia, Delaware, Maryland and Washington D.C.), 12% of ozone-sensitive
plants showed signs of high or severe foliar damage, and in Regions 2 (States of New York, New
Jersey) and 4 (States of North Carolina, South Carolina, Kentucky, Tennessee, Georgia, Florida,
Alabama, and Mississippi), the values were 10% and 7%, respectively. The sum of high and
severe ozone injury ranged from 2% to 4% in EPA Region 1 (the six New England States),
Region 7 (States of Missouri, Iowa, Nebraska and Kansas), and Region 9 (States of California,
Nevada, Hawaii and Arizona). The percentage of sites showing some ozone damage was about
45% in each of these EPA Regions.
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Chapter 2: Air Quality, Health and Welfare Effects
Degree n( injury:
Nans
Low
Moderns
Higti
Swsra
Percent af monitoring sites in each category:
Region 1
(54 attest
Region 2
[42 sites)
Region 3
(11T sites)
Region 4
[227 sites.}
Region 5
(180 sites)
Region 6
[59 sites'i
Region 7
; 53 sitesi
Region 3
(72 sites)
Region 9
[30 sites'i
Region 10
[57 sites)
68.5
16.7
-1.1
-3.7
51.9
21.4
71
7.1
24
55.9
1B.C1
144
7.2
4.5
75.3
10.1
.5
-4.G
1B.3
5.-
94.3
5.1
S5.7
9.5
TO2
.J-1.fi
100.0
763
12.5
9.8
-1.3
•1.3
100.0
!Cmwrag*: 945 monitoring sites,
located in 41 states.
:'Totflls may rat add to 100% due to
rounding.
0jie source: USDA forest Senior,
2\)K
EPA Ragians
(D
!.
Figure 2-24 Ozone Injury to Forest Plants in U.S. by EPA Regions, 2002a
2. J. 4.1.1 Indicator Limitations
Field and laboratory studies were reviewed to identify the forest plant species in each
region that are highly sensitive to ozone air pollution. Other forest plant species, or even
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Regulatory Impact Analysis
genetic variants of the same species, may not be harmed at ozone levels that cause effects on
the selected ozone-sensitive species.
Because species distributions vary regionally, different ozone-sensitive plant species
were examined in different parts of the country. These target species could vary with respect to
ozone sensitivity, which might account for some of the apparent differences in ozone injury
among regions of the U.S.
Ozone damage to foliage is considerably reduced under conditions of low soil moisture,
but most of the variability in the index (70%) was explained by ozone concentration.334 Ozone
may have other adverse impacts on plants (e.g., reduced productivity) that do not show signs of
visible foliar injury.335
Though FIA has extensive spatial coverage based on a robust sample design, not all
forested areas in the U.S. are monitored for ozone injury. Even though the biosite data have
been collected over multiple years, most biosites were not monitored over the entire period, so
these data cannot provide more than a baseline for future trends.
2.3.4.1.2 Ozone Impacts on Forest Health
Air pollution can impact the environment and affect ecological systems, leading to
changes in the biological community (both in the diversity of species and the health and vigor of
individual species). As an example, many studies have shown that ground-level ozone reduces
the health of plants including many commercial and ecologically important forest tree species
throughout the United States.336
When ozone is present in the air, it can enter the leaves of plants, where it can cause
significant cellular damage. Since photosynthesis occurs in cells within leaves, the ability of the
plant to produce energy by photosynthesis can be compromised if enough damage occurs to
these cells. If enough tissue becomes damaged, it can reduce carbon fixation and increase plant
respiration, leading to reduced growth and/or reproduction in young and mature trees. Ozone
stress also increases the susceptibility of plants to disease, insects, fungus, and other
environmental stressors (e.g., harsh weather). Because ozone damage can consist of visible
injury to leaves, it also reduces the aesthetic value of ornamental vegetation and trees in urban
landscapes, and negatively affects scenic vistas in protected natural areas.
Assessing the impact of ground-level ozone on forests in the eastern United States
involves understanding the risks to sensitive tree species from ambient ozone concentrations and
accounting for the prevalence of those species within the forest. As a way to quantify the risks to
particular plants from ground-level ozone, scientists have developed ozone-exposure/tree-
response functions by exposing tree seedlings to different ozone levels and measuring reductions
in growth as "biomass loss." Typically, seedlings are used because they are easy to manipulate
and measure their growth loss from ozone pollution. The mechanisms of susceptibility to ozone
within the leaves of seedlings and mature trees are identical, though the magnitude of the effect
may be higher or lower depending on the tree species.337
Some of the common tree species in the United States that are sensitive to ozone are
black cherry (Primus serotina), tulip-poplar (Liriodendron tulipifera), eastern white pine (Pinus
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Chapter 2: Air Quality, Health and Welfare Effects
strobus). Ozone-exposure/tree-response functions have been developed for each of these tree
species, as well as for aspen (Populus tremuliodes), and ponderosa pine (Pirntsponderosd).
Other common tree species, such as oak (Quercus spp.j and hickory (Carya spp.), are not nearly
as sensitive to ozone. Consequently, with knowledge of the distribution of sensitive species and
the level of ozone at particular locations, it is possible to estimate a "biomass loss" for each
species across their range.
2.3.4.2 W126 Modeling and Projected Impact of Ship Emissions on U.S. Forests Biomass
To estimate the ozone-related biomass loss across the United States for the tree species
listed above, the biomass loss for each of the five tree species was calculated using the three-
month 12-hour W126 exposure metric at each location and its individual ozone-exposure/tree-
response function. The W126 exposure metric and the individual species ozone-related biomass
loss were calculated using CMAQ model output for AQS air quality monitoring sites and then
interpolated across each of the species' ranges. This analysis was done for 2020 with and
without international shipping emissions to determine the benefit of lowering shipping emissions
on these sensitive tree species in the U.S.
The ozone-related biomass loss in the U.S. attributable to international shipping appears
to range from 0-6.5 % annually, depending on the particular species. The most sensitive species
in the U.S. to ozone-related biomass loss is black cherry; the area of its range with more than
10% biomass loss in 2020 decreased by 8.5% when emissions from ships were removed.
Likewise, Table 2-7 indicates that yellow-poplar, eastern white pine, aspen, and ponderosa pine
saw areas with more than 2% biomass loss reduced by 2.1% to 3.8% in 2020. The 2% level of
biomass loss is important, because a scientific consensus workshop on ozone effects reported
that a 2% annual biomass loss causes long term ecological harm due to the potential for
compounding effects over multiple years as short-term negative effects on seedlings affect long-
term forest health.338'339 Figure 2-25 shows the U.S. geographic areas where the area of each
species' range with more than 2% ozone-related biomass loss in 2020 would decrease if
emissions from ships were removed. Coastal areas and regions along the edges of the areas with
greater than 2% biomass loss for each species show the most improvement.
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Regulatory Impact Analysis
Table 2-7 The Percent Improvement in Area of the Tree Species Range Between the "Base Case" and "Zero
Out" Marine Emissions with Biomass Loss of Greater than 2,4,6, and 10% due to Ozone for Year 2020.
Units are % Improvement of Area of Species Range.
Tree Specie.-'
Perceni of Bioimtss Loss
i 4°* 6*0 10*b
Aspen
Poptifns ftvim/hitlt's
Black Chcrrv
Pnttntsst'nttiiKi
Pondeiosa Puie
Tulip Poplai
Z irioffentiroi i ntfigijfrtt
E Wiiite IPiiie
Pilots strobiis
ILL - Illh l.llilll-a III 111'-1 III ill
II'R— out of riiiiKc
IA
a/a
38
2.1
2.8
14
ll.C..
2,0
0.8
1 I
0.8
2.9
1.5
ll.C.
0.4
n/a
8.5
a/a
na
2020 Base minus Zero C3 Emissions
Figure 2-25 U.S. Geographic Areas where the Area of Each Species' Range with More than 2% Ozone-
Related Biomass Loss in 2020 would Decrease if Emissions from Ships were Removed
2.3.4.2.1 Methodology
Outputs from the CMAQ modeling were used to calculate a cumulative, seasonal ozone
exposure metric known as "W126".340 Previous EPA analyses have concluded that the
cumulative, seasonal W126 index is the most appropriate index for relating vegetation response
to ambient ozone exposures. The metric is a sigmoidally weighted 3-month sum of all hourly
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Chapter 2: Air Quality, Health and Welfare Effects
ozone concentrations observed during the daily 12-hr period between 8 am to 8 pm. The three
months are the maximum consecutive three months during the ozone season, defined for this
modeling as May through September.
As in the ozone and PM2 5 modeling, the CMAQ model was used in a relative sense to
estimate how ambient W126 levels will change as a result of future growth and/or emissions
reductions associated with our coordinated program. The resultant W126 outputs were fed into a
separate model which calculated biomass loss from certain tree species as a result of prolonged
exposure to ozone. The results of that analysis are discussed below. The CMAQ modeling
estimated that ship emissions contributed to high levels of W126 in some coastal areas. This
contribution was estimated to range from as much as 30- to 40% in parts of California and
Florida. The average contribution from all ship emissions was estimated to be 8% nationally.
2.4 Impacts of the Coordinated Strategy on Air Quality
The controls from the coordinated strategy will significantly reduce emissions of NOx,
SOx and PM from Category 3 vessels. Air quality modeling and monitoring data presented in
this section indicate that a large number of people live in counties that are designated as
nonattainment for either or both of the PM2.5 or 8-hour ozone NAAQS. Figures 2-26 and 2-31
illustrate the widespread nature of the ozone and PM2 5 nonattainment areas. Air quality
modeling was performed for the coordinated strategy which illustrates the changes in ambient
concentrations of PM2.s and ozone as well as changes in deposition of nitrogen and sulfur and
levels of visibility which are expected to occur with the emission reductions from the
coordinated strategy.
Emissions and air quality modeling decisions are made early in the analytical process.
For this reason, the emission control scenarios used in the air quality modeling, and the benefits
modeling presented in Chapter 6, are slightly different than the final coordinated strategy
emission control scenarios. For example, the 2020 air quality impacts are based on inventory
estimates that were modeled using incorrect EGA boundary information off of the western coast
of the U.S. A calculation error placed the western 200 nautical mile (nm) EGA boundary
approximately 50 nm closer to shore. Additionally, the 2020 air quality control case does not
reflect emission reductions related to global controls for areas that are beyond 200 nm but within
the CMAQ air quality modeling domain. Finally, the emission control scenarios do not consider
the exemption of Great Lakes steamships from the final fuel sulfur standards. The impact of
these differences is expected to be minimal. In total, while the inventory and air quality
modeling discrepancies are modest, they result in a conservative estimate of the 2020 air quality
impacts that are presented in this chapter. Please refer to Chapter 3 for a comparison of the
inventories used to support the air quality modeling and the inventories of the coordinated
strategy.
2.4.1 Particulate Matter
The emission reductions from the coordinated strategy will assist PM nonattainment
areas in reaching the standard by each area's respective attainment date and assist PM
maintenance areas in maintaining the PM standards in the future. In this section we present
information on current and model-projected future PM levels.
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2.4.1.1 Current Levels of PM2.5
As described in Section 2.2.1, PM causes adverse health effects, and the U.S.
Government has set national standards to protect against those health effects. There are two U.S.
National Ambient Air Quality Standards (NAAQS) for PM2.5: 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 As of July 31, 2009 there are 39 1997 PM2.5 nonattainment areas
composed of 208 full or partial counties with a total population exceeding 88 million.
Nonattainment areas for the 1997 PM2.5 NAAQS are pictured in Figure 2-26. 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). These designations include 31 areas composed of 120 full
or partial counties.
States with PM2.5 nonattainment areas 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 be required to maintain the 1997
PM2.5 NAAQS thereafter.341 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 PM2.5 NAAQS thereafter.342 The IMO, 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, Category 3 vessels are significant contributors to PM2.5
in many areas and states will need additional reductions in a timely manner to help them meet
their air quality goals. The fuel sulfur emission standards will become effective in 2010 and
2015, and the NOx engine emission standards will become effective in 2016. Therefore the fuel
and engine emission reductions associated with the coordinated strategy will assist PM2.5
nonattainment areas in reaching the standard by each area's respective attainment date and/or
assist in maintaining the PM standard in the future.
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.
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Chapter 2: Air Quality, Health and Welfare Effects
PM-2.5 Nonattainment Areas (1997 Standard)
Nonattainment areas are indicated by color.
'When only a portion of a county is shown in color,
it indicates that only that part of the county is within
a nonattainment area boundary.
7/2009
Figure 2-26 1997 Annual PM2.5 Nonattainment Areas
2.4.1.2 Projected Levels of PM2.5
In conjunction with the coordinated strategy, we performed a series of air quality
modeling simulations for the continental U.S. The model simulations were performed for
several emissions scenarios including the following: 2002 baseline projection, 2020 baseline
projection, 2020 baseline projection with Category 3 fuel and engine controls, 2030 baseline
projection, and 2030 baseline projection with Category 3 fuel and engine controls. Information
on the air quality modeling methodology is contained in Section 2.4.5. In the following sections
we describe projected PM2.5 levels in the future, with and without the controls described in this
final rule.
2.4.1.2.1 Projected PM2.s Levels without the Coordinated Strategy
Even with the implementation of all current state and federal regulations, including the
Small SI Engine Rule (73 FR 59034, October 8, 2008), the Locomotive and Marine Rule (73 FR
25098, May 6, 2008), the Clean Air Nonroad Diesel rule (69 FR 38957, June 29, 2004), and the
Heavy Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control
Requirements (66 FR 5002, Jan. 18, 2001), there are projected to be U.S. counties violating the
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Regulatory Impact Analysis
PM2.5 NAAQS well into the future. The model outputs from the 2002, 2020 and 2030 baselines,
combined with current air quality data, were used to identify areas expected to exceed the PM2 5
NAAQS in the future.
The baseline air quality modeling conducted for the coordinated strategy projects that in
2030, with all current controls in effect but excluding the reductions expected to occur as a result
of the coordinated strategy, at least 14 counties, with a projected population of over 30 million
people, may not attain the annual standard of 15 |ig/m3. 11 of these 14 projected nonattainment
areas are in California, which has been shown to be strongly impacted by emissions from
Category 3 vessels. These numbers do not account for those areas that are within 10% of the
PM2 5 standard. These areas, although not violating the standard, will also benefit from the
emissions reductions which will help ensure long term maintenance of the PM2 sNAAQS. For
example, in 2030, an additional 13 million people are projected to live in 12 counties that have
air quality measurements within 10% of the annual PM2.s NAAQS.
In addition, the baseline air quality modeling conducted for the coordinated strategy
projects that in 2030, with all current controls in effect but excluding the reductions expected to
occur as a result of the coordinated strategy, at least 44 counties, with a projected population of
over 59 million people, may not attain the 24-hour standard of 35 |ig/m3. These numbers do not
account for those areas that are within 10% of the 24-hour PM2 5 standard. These areas, although
not violating the standard, will also benefit from the emissions reductions which will help ensure
long term maintenance of the PM25 NAAQS. For example, in 2030, an additional 22 million
people are projected to live in 37 counties that have air quality measurements within 10% of the
24-hour PM2.5 NAAQS.
This modeling supports the conclusion that there are a substantial number of counties
across the U.S. projected to experience PM2.5 concentrations at or above the PM2 5NAAQS into
the future. Emission reductions from Category 3 vessels will be helpful for these counties in
attaining and maintaining the PM25 NAAQS.
2.4.1.2.2 Projected PM2.5 Levels with the Coordinated Strategy
This section summarizes the results of our modeling of PM2.5 air quality impacts in the
future due to the reductions in Category 3 vessel emissions described in this final action.
Specifically, we compare baseline scenarios to scenarios with controls. Our modeling indicates
that the reductions from the coordinated strategy will provide nationwide improvements in
ambient PM2 5 concentrations and minimize the risk of exposures in future years. Since the
emission reductions from this rule 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.
On a population-weighted basis, the average modeled future-year annual PM2.5 design
values will decrease by 0.51 |ig/m3 in 2020 and 0.98 |ig/m3 in 2030 and the average modeled
future-year 24-hour PM2.s design values will decrease by 0.6 |ig/m3 in 2020 and 1.29 |ig/m3 in
2030. In addition, those counties that are projected to be above the PM2 5 standard in 2020 and
2030 will have even larger decreases from the emission controls associated with the coordinated
strategy. On a population-weighted basis, the average modeled future-year annual PM2.5 design
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Chapter 2: Air Quality, Health and Welfare Effects
values for counties whose design values were greater than 15 |ig/m3 will decrease by 1.56 |ig/m3
in 2020 and 2.03 |ig/m3 in 2030. In addition, on a population-weighted basis, the average
modeled future-year 24-hour PM2.5 design values for counties whose design values were greater
than 35 |ig/m3 will decrease by 1.31 |ig/m3 in 2020 and 1.12 |ig/m3 in 2030. Tables 2-8 and 2-9
show the average change in future year PM2.5 design values for: (1) all counties with 2002
baseline design values, (2) counties with baseline design values that exceeded the standard in
2000-2004 ("violating" counties), (3) counties that did not exceed the standard, but were within
10% of it in 2000-2004, (4) counties with future year design values that exceeded the standard,
and (5) counties with future year design values that did not exceed the standard, but were within
10% of it in 2020 and 2030. Counties within 10% of the standard are intended to reflect counties
that meet the standard, but will likely benefit from help in maintaining that status in the face of
growth. All of these metrics show a decrease in 2020 and 2030, indicating in five different ways
the overall improvement in air quality.
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Regulatory Impact Analysis
Table 2-8 Average Change in Projected Future Year Annual PM2.5 Design Value as a Result of the Category 3
Fuel and Engine Controls
Average"
All
All, population-weighted
Counties whose base year is violating the 2006
annual PM2.5 standard
Counties whose base year is violating the 2006
annual PM2.5 standard, population-weighted
Counties whose base year is within 10 percent of
the 2006 annual PM2.5 standard
Counties whose base year is within 10 percent of
the 2006 annual PM2 5 standard, population-
weighted
Counties whose 2020 base year is violating the
2006 annual PM2.5 standard
Counties whose 2020 base year is violating the
2006 annual PM2 5 standard, population-
weighted
Counties whose 2030 base year is violating the
2006 annual PM2.5 standard
Counties whose 2030 base year is violating the
2006 annual PM2 5 standard, population-
weighted
Counties whose 2020 base year is within 10
percent of the 2006 annual PM2.5 standard
Counties whose 2020 base year is within 10
percent of the 2006 annual PM2.5 standard,
population-weighted
Counties whose 2030 base year is within 10
percent of the 2006 annual PM2.5 standard
Counties whose 2030 base year is within 10
percent of the 2006 annual PM2.5 standard,
population-weighted
Number
of US
Counties
556
556
82
82
113
113
13
13
14
14
12
12
12
12
Change in
2020 design
value
(U8/m3)
-0.22
-0.51
-0.28
-0.81
-0.20
-0.36
-0.99
-1.56
-1.06
-1.57
-0.35
-0.30
-0.29
-0.17
Change in
2030 design
value
(U8/m3)
-0.41
-0.98
-0.52
-1.68
-0.34
-0.60
-1.92
-3.27
-2.03
-3.27
-0.62
-0.54
-0.51
-0.30
Note:
a Averages are over counties with 2002 modeled design values
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Chapter 2: Air Quality, Health and Welfare Effects
Table 2-9 Average Change in Projected Future Year 24-hour PM2.5 Design Value as a Result of the Category
3 Fuel and Engine Controls
Average"
All
All, population-weighted
Counties whose base year is violating the 2006
24-hour PM2.5 standard
Counties whose base year is violating the 2006
24-hour PM2.5 standard, population-weighted
Counties whose base year is within 10 percent of
the 2006 24-hour PM2.5 standard
Counties whose base year is within 10 percent of
the 2006 24-hour PM2.5 standard, population-
weighted
Counties whose 2020 base year is violating the
2006 24-hour PM2.5 standard
Counties whose 2020 base year is violating the
2006 24-hour PM2.5 standard, population-
weighted
Counties whose 2030 base year is violating the
2006 24-hour PM2.5 standard
Counties whose 2030 base year is violating the
2006 24-hour PM2.5 standard, population-
weighted
Counties whose 2020 base year is within 10
percent of the 2006 24-hour PM2.5 standard
Counties whose 2020 base year is within 10
percent of the 2006 24-hour PM2.5 standard,
population-weighted
Counties whose 2030 base year is within 10
percent of the 2006 24-hour PM2.5 standard
Counties whose 2030 base year is within 10
percent of the 2006 24-hour PM2.5 standard,
population-weighted
Number
of US
Counties
617
617
115
115
114
114
47
47
44
44
43
43
37
37
Change in
2020 design
value
(U8/m3)
-0.21
-0.60
-0.34
-0.97
-0.17
-0.32
-0.40
-1.31
-0.50
-1.38
-0.32
-0.47
-0.25
-0.33
Change in
2030 design
value
(U8/m3)
-0.39
-1.29
-0.69
-2.31
-0.29
-0.51
-0.93
-3.29
-1.12
-3.38
-0.57
-0.81
-0.44
-0.56
Note:
a Averages are over counties with 2002 modeled design values
Figures 2-27 through 2-30 illustrate the geographic impact of the Category 3 engine and
fuel controls on 24-hour and annual PM2 5 design values in 2020 and 2030. As is expected the
most significant decreases occur along the coastlines. The maximum decrease in a 2030 annual
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Regulatory Impact Analysis
design value is projected to be 6.02 |ig/m3 in Miami, FL and the maximum decrease in a 2030
24-hour design value is projected to be 11.7 |ig/m3 in Los Angeles, CA.
afference in County Annual Average PM2.5 (ua/m3) 2020ce_200nm minus 2020ce
Figure 2-27 Impact of Category 3 Fuel and Engine Controls on Annual PM2.5 Design Values (DV) in 2020
(units are jig/m3)
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Chapter 2: Air Quality, Health and Welfare Effects
Difference in County Annual Average PM2-5 (ug/m3): 2030ce_200glob minus 2030ce
Figure 2-28 Impact of Category 3 Fuel and Engine Controls on Annual PM2.5 Design Values (DV) in 2030
(units are jig/m3)
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Regulatory Impact Analysis
Difference in County 24-hr PM2.5 (ug/m3): 2020ce_200nm minus 2020ce
Figure 2-29 Impact of Category 3 Fuel and Engine Controls on 24-hour PM2.5 Design Values (DV) in
2020 (units are
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Chapter 2: Air Quality, Health and Welfare Effects
Difference in County 24-hr PM2.5 (ug/mS): 2030ce_200glob minus 2030ce
Figure 2-30 Impact of Category 3 Fuel and Engine Controls on Annual PM2.5 Design Values (DV) in 2030
(units are jig/m3)
Table 2-10 lists the counties with projected annual PM2.5 design values that violate or are
within 10% of the annual PM2.5 standard in 2020. Counties are marked with a "V" in the table if
their projected design values are greater than or equal to 15.05 |ig/m3. Counties are marked with
an "X" in the table if their projected annual design values are greater than or equal to 13.55
|ig/m3, but less than 15.05 |ig/m3. 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. The current design values are also presented in Table 2-10. Recall that we project
future design values only for counties that have current design values, so this list is limited to
those counties with ambient monitoring data sufficient to calculate current 3-year design values.
There are three counties whose projected design values go from being above the annual standard
in the base case to being lower than the annual PM2.5 standard with the coordinated strategy
controls.
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Regulatory Impact Analysis
Table 2-10 Counties with 2020 Projected Annual PM2.5 Design Values in Violation or Within 10% of the
Annual PM2.5 Standard in the Base and Control Cases
STATE
Alabama
California
California
California
California
California
California
California
California
California
California
California
California
California
California
Georgia
Illinois
Illinois
Kentucky
Michigan
Montana
New York
Ohio
Pennsylvania
West
Virginia
COUNTY
Jefferson Co
Fresno Co
Imperial Co
Kern Co
Kings Co
Los Angeles Co
Merced Co
Orange Co
Riverside Co
San Bernardino Co
San Diego Co
San Joaquin Co
Stanislaus Co
Tulare Co
Ventura Co
Fulton Co
Cook Co
Madison Co
Jefferson Co
Wayne Co
Lincoln Co
New York Co
Cuyahoga Co
Allegheny Co
Hancock Co
2000-2004
AVERAGE
ANNUAL
PM25DV
(n/3)
18.37
20.03
14.45
21.77
18.77
23.17
16.48
18.27
27.15
24.63
15.65
14.84
16.50
21.33
14.35
18.29
17.07
17.27
16.78
19.32
15.85
17.16
18.37
21.00
17.31
2020
MODELING
PROJECTIONS
OF BASE
ANNUAL PM2 5
DV (ng/rn3)
V
V
X
V
V
V
V
V
V
V
V
X
X
V
X
X
X
X
X
V
X
X
X
V
X
2020
MODELING
PROJECTIONS
OF CONTROL
ANNUAL PM2 5
DV (ng/rn3)
X
V
X
V
V
V
X
V
V
V
X
X
V
X
X
X
X
V
X
X
X
V
2020 PROJECTED
POPULATION343
681,549
1,066,878
161,555
876,131
173,390
10,376,013
277,863
3,900,599
2,252,510
2,424,764
3,863,460
743,469
607,766
477,296
1,023,136
929,278
5,669,479
278,167
726,257
1,908,196
20,147
1,700,384
1,326,680
1,242,587
30,539
2.4.2 Ozone
The emission reductions from the coordinated strategy described in this final rule will
also assist ozone nonattainment areas in reaching the standard by each area's respective
attainment date as well as assist ozone maintenance areas in maintaining the ozone standards in
the future. In this section, we present information on current and model-projected future ozone
levels.
2.4.2.1 Current Levels of Ozone
As described in Section 2.2.2, ozone causes adverse health effects, and the U.S.
Government has set national standards to protect against those health effects. The national
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Chapter 2: Air Quality, Health and Welfare Effects
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 for the 1997 8-
hour ozone NAAQS (69 FR 23858, April 30, 2004).M As of July 31, 2009, there are 54 1997 8-
hour ozone nonattainment areas composed of 282 full or partial counties with a total population
of almost 127 million.344 Nonattainment areas for the 1997 8-hour ozone NAAQS are pictured
in Figure 2-2X. The nonattainment areas associated with the more stringent 2008 8-hour ozone
NAAQS have not yet been designated.N
States with ozone nonattainment areas 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.0 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. Table 2-11
provides an estimate, based on 2005-07 air quality data, of the counties with design values
greater than 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.
M 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.
N 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 August 31, 2010. 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 2010 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 2010, EPA intends to accelerate the designations process to that the designations would be
effective in August 2011.
0 The Los Angeles South Coast Air Basin 8-hour ozone nonattainment area is designated as severe and will have to
attain before June 15, 2021. The South Coast Air Basin has requested to be reclassified as an extreme nonattainment
area which will make their attainment date June 15, 2024. The San Joaquin Valley Air Basin 8-hour ozone
nonattainment area is designated as serious and will have to attain before June 15, 2013. The San Joaquin Valley
Air Basin has requested to be reclassified as an extreme nonattainment area which will make their attainment date
June 15, 2024.
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Regulatory Impact Analysis
Nonattainment and Maintenance Areas in the U.S.
8-hour Ozone (1997 Standard)
NonattainmentAreas (252 entire counties)
Nonattainment Areas (30 partial counties)
Maintenance Areas (152 entire or partial counties)
?.'70C9
Partial counties, those with part of the county designated
nonattainment and part attainment, are shown as full counties on this map.
Figure 2-311997 8-hour Ozone Nonattainment Areas
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Chapter 2: Air Quality, Health and Welfare Effects
Table 2-11 Counties with Design Values Greater Than the 2008 Ozone NAAQS Based on 2005-2007 Air
Quality Data
1997 Ozone Standard: counties within the 54
areas currently designated as nonattainment (as
of 7/3 1/09)
2008 Ozone Standard: additional counties that
would not meet the 2008 NAAQSb
Total
Number of Counties
282
227
509
Population21
126,831,848
41,285,262
168,117,110
Notes:
a Population numbers are from 2000 census data.
b Attainment designations for the 2008 ozone NAAQS have not yet been made. Nonattainment for the 2008 Ozone
NAAQS will be based on three years of air quality data from later years. Also, the county numbers in the table
include only the counties with monitors violating the 2008 Ozone NAAQS. The numbers in this table may be an
underestimate of the number of counties and populations that will eventually be included in areas with multiple
counties designated nonattainment.
2.4.2.2 Projected Levels of Ozone
In conjunction with the coordinated strategy, we performed a series of air quality
modeling simulations for the continental U.S. (described further in Section 3.4.3 of the RIA).
The model simulations were performed for several emissions scenarios including the following:
2002 baseline projection, 2020 baseline projection, 2020 baseline projection with Category 3 fuel
and engine controls, 2030 baseline projection, and 2030 baseline projection with Category 3 fuel
and engine controls. Information on the air quality modeling methodology is contained in
Section 2.4.5. In the following sections, we describe our modeling of 8-hour ozone levels in the
future with and without the controls described in this final action.
2.4.2.2.1 Projected Ozone Levels without the Coordinated Strategy
EPA has already adopted many emission control programs that are expected to reduce
ambient ozone levels. These control programs include the Small SI Engine Rule (73 FR 59034,
October 8, 2008), Locomotive and Marine Rule (73 FR 25098, May 6, 2008), Clean Air
Interstate Rule (70 FR 25162, May 12, 2005), the Clean Air Nonroad Diesel rule (69 FR 38957,
June 29, 2004), and the Heavy Duty Engine and Vehicle Standards and Highway Diesel Fuel
Sulfur Control Requirements (66 FR 5002, Jan. 18, 2001). As a result of these programs, 8-hour
ozone levels are expected to improve in the future.
The baseline air quality modeling conducted for the coordinated strategy projects that in
2030, with all current controls in effect but excluding the reductions achieved through the
coordinated strategy, up to 33 counties, with a population of almost 50 million people, may not
attain the 8-hour standard of 0.075 ppm. These numbers do not account for those areas that are
within 10% of the 2008 ozone standard. These areas, although not violating the standards, will
also benefit from the additional reductions from this rule, ensuring long term maintenance of the
ozone NAAQS. For example, in 2030, an additional 72 million people are projected to live in
105 counties that have air quality measurements within 10% of the 2008 ozone NAAQS. This
modeling supports the conclusion that there are a substantial number of counties across the U.S.
projected to experience 8-hour ozone concentrations at or above the ozone NAAQS into the
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Regulatory Impact Analysis
future. Emission reductions from Category 3 vessels will be helpful for these counties in
attaining and maintaining the ozone NAAQS.
2.4.2.2.2 Projected Ozone Levels with the Coordinated Strategy
This section summarizes the results of our modeling of ozone air quality impacts in the
future due to the reductions in Category 3 vessel emissions finalized in this action. Specifically,
we compare baseline scenarios to scenarios with controls (Section 2.4.2.2 and 3.4.3 of the RIA).
Our modeling indicates that the reductions from this rule will provide nationwide improvements
in ambient ozone concentrations and minimize the risk of exposures in future years. Since some
of the NOx emission reductions from this rule go into effect during the period when some areas
are still working to attain the 8-hour ozone NAAQS, the projected emission reductions will assist
state and local agencies in their effort to attain the 8-hour 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 are not reflected in the modeling shown here.345'346
On a population-weighted basis, the average modeled future-year 8-hour ozone design
values will decrease by 0.30 ppb in 2020 and 0.97 ppb in 2030. In addition, those counties that
are projected to be above the 2008 ozone standard in 2020 and 2030 will have even larger
decreases from the coordinated strategy. On a population-weighted basis, the average modeled
future-year 8-hour ozone design values for counties whose design values were greater than 75
ppb will decrease by 0.46 ppb in 2020 and 1.60 ppb in 2030. Table 2-12 shows the average
change in future year 8-hour ozone design values for: (1) all counties with 2002 baseline design
values, (2) counties with baseline design values that exceeded the standard in 2000-2004
("violating" counties), (3) counties that did not exceed the standard, but were within 10% of it in
2000-2004, (4) counties with future year design values that exceeded the standard, and (5)
counties with future year design values that did not exceed the standard, but were within 10% of
it in 2020 and 2030. Counties within 10% of the standard are intended to reflect counties that
meet the standard, but will likely benefit from help in maintaining that status in the face of
growth. All of these metrics show a decrease in 2020 and 2030, indicating in five different ways
the overall improvement in ozone air quality.
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Chapter 2: Air Quality, Health and Welfare Effects
Table 2-12 Average Change in Projected Future Year 8-hour Ozone Design Value as a Result of the Category
3 Fuel and Engine Controls
Average21
All
All, population-weighted
Counties whose base year is violating the 2008
8 -hour ozone standard
Counties whose base year is violating the 2008
8-hour ozone standard, population-weighted
Counties whose base year is within 10 percent of
the 2008 8-hour ozone standard
Counties whose base year is within 10 percent of
the 2008 8-hour ozone standard, population-
weighted
Counties whose 2020 base year is violating the
2008 8-hour ozone standard
Counties whose 2020 base year is violating the
2008 8-hour ozone standard, population-
weighted
Counties whose 2030 base year is violating the
2008 8-hour ozone standard
Counties whose 2030 base year is violating the
2008 8-hour ozone standard, population-
weighted
Counties whose 2020 base year is within 10
percent of the 2008 8-hour ozone standard
Counties whose 2020 base year is within 10
percent of the 2008 8-hour ozone standard,
population-weighted
Counties whose 2030 base year is within 10
percent of the 2008 8-hour ozone standard
Counties whose 2030 base year is within 10
percent of the 2008 8-hour ozone standard,
population-weighted
Number
of US
Counties
661
661
497
497
99
99
50
50
33
33
135
135
105
105
Change in
2020 design
valueb (ppb)
-0.22
-0.30
-0.21
-0.27
-0.21
-0.29
-0.52
-0.46
-0.61
-0.49
-0.30
-0.24
-0.38
-0.27
Change in
2030 design
valueb (ppb)
-0.68
-0.97
-0.66
-0.87
-0.67
-0.99
-1.65
-1.52
-1.95
-1.60
-0.92
-0.76
-1.16
-0.85
Notes:
a Averages are over counties with 2002 modeled design values
b Ozone design values are reported in parts per million (ppm) as specified in 40 CFR Part 50. Due to the scale of
the design value changes in this action results have been presented in parts per billion (ppb) format.
Figures 2-32 and 2-33 illustrate the geographic impact of the Category 3 engine and fuel
controls on 8-hour ozone design values in 2020 and 2030. The most significant decreases occur
along all of the coastlines with the maximum decrease in a 2030 design value being 5.5 ppb in
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Regulatory Impact Analysis
Bristol, Massachusetts. As can be seen from Table 2-12 and Figures 2-32 and 2-33 the air
quality modeling performed for the coordinated strategy indicates that the Category 3 engine
standards provide improvements in ozone levels for the vast majority of areas. However, there
are two counties in Washington, Clallam County (0.7 ppb) and Clark County (0.2 ppb), and one
county in southern California, Orange County (3.0 ppb), which will experience 8-hour ozone
design value increases in 2030 due to the NOx disbenefits which occur in these VOC-limited
ozone nonattainment areas.
While the impact of the Category 3 engine and fuel controls will reduce ozone levels
generally and provide national ozone-related health benefits, this is not always the case at the
local level. The air quality modeling projects that in a few areas ozone levels will get higher
because of the NOx disbenefit phenomenon. Due to the complex photochemistry of ozone
production, NOX emissions lead to both the formation and destruction of ozone, depending on
the relative quantities of NOx, VOC, and ozone formation catalysts such as the OH and HO2
radicals. In areas dominated by fresh emissions of NOx, ozone catalysts are removed via the
production of nitric acid which slows the ozone formation rate. Because NOx is generally
depleted more rapidly than VOC, this effect is usually short-lived and the emitted NOX can lead
to ozone formation later and further downwind. The terms "NOx disbenefits" or "ozone
disbenefits" refer to the ozone increases that result when reducing NOx emissions in localized
areas. According to the NARSTO Ozone Assessment, disbenefits are generally limited to small
regions within specific urban cores and are surrounded by larger regions in which NOx control is
beneficial.347 It is important to note the following as well: there is a level of NOx control where
enough NOx will have been reduced to result in decreases in ambient ozone concentrations, this
modeling does not include future VOC or NOx controls that local areas are planning, and
reductions in NOX are not only important to help reduce ozone but also to help reduce PM2.5.
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Chapter 2: Air Quality, Health and Welfare Effects
Dfference in County 8-hour Ozone DV (ppb): 202Qce_200nm minus 2020ce
Figure 2-32 Impact of Category 3 Fuel and Engine Controls on 8-hour Ozone Design Values in 2020 (units
are ppb)
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Regulatory Impact Analysis
Difference in County 8-Hour Ozone DV (ppb): 2030ce_200glob minus 2030ce
Figure 2-33 Impact of Category 3 Fuel and Engine Controls on 8-hour Ozone Design Values in 2030 (units
are ppb)
2.4.3 Deposition of Nitrogen and Sulfur
2.4.3.1 Current Levels of Nitrogen and Sulfur Deposition
Over the past two decades, the EPA has undertaken numerous efforts to reduce nitrogen
and sulfur deposition across the U.S. Analyses of long-term monitoring data for the U.S. show
that deposition of both nitrogen and sulfur compounds has decreased over the last 17 years
although many areas continue to be negatively impacted by deposition. Deposition of inorganic
nitrogen and sulfur species routinely measured in the U.S. between 2004 and 2006 were as high
as 9.6 kg N/ha/yr and 21.3 kg S/ha/yr. Figures 2-34 and 2-35 show that annual total deposition
(the sum of wet and dry deposition) decreased between 1989-1999 and 2004-2006 due to sulfur
and NOx controls on power plants, motor vehicles and fuels in the U.S. The data shows that
reductions were more substantial for sulfur compounds than for nitrogen compounds. These
numbers are generated by the U.S. national monitoring network and they likely underestimate
nitrogen deposition because NH3 is not measured. In the eastern U.S., where data are most
abundant, total sulfur deposition decreased by about 36 % between 1990 and 2005 while total
T -JQ
nitrogen deposition decreased by 19% over the same time frame.
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Chapter 2: Air Quality, Health and Welfare Effects
The EPA is concerned that both current ship emissions and projected future ship
emissions will seriously erode environmental improvements that have been achieved in these
ecologically sensitive areas. As the air quality modeling results in Section 2.4.3.2 show, both
nitrogen and sulfur deposition resulting from ship emissions impact a significant portion of
ecologically sensitive areas in the U.S.
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Regulatory Impact Analysis
r
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Figure 2-34 Total Sulfur Deposition in the Contiguous U.S., 1989-1991 and 2004 -2006
2-84
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Chapter 2: Air Quality, Health and Welfare Effects
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nutate Eta! imrajwaspe 51 liar Hx .
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caiars In <*C*H until* mi tire jkcttMi e' -3
Dry nltmgn*fnHan •Wtetnlt'-ogin floras
-'"
OMcnndroninacWMtMUnn it
&ty HMWiportHoii •Dry
pty ntn.' myi«nyi • ws;
« VM ND,'aiposmwi
to
!Cwtrkp: 2;
ara J3 iiariiwing KB in MC4-?3M
Figure 2-35 Total Nitrogen Deposition in the Contiguous U.S., 1989-1991 and 2004-2006
2-85
-------
Regulatory Impact Analysis
2.4.3.2 Projected Levels of Nitrogen and Sulfur Deposition
With the adoption of the coordinated strategy, reductions in nitrogen deposition will
result by 2030, benefiting many sensitive ecological areas throughout the U.S. Areas benefiting
are described in detail in Section 2.3.1.1 and include sensitive forests, wetlands such as
freshwater bogs and marshes, lakes and streams throughout the entire U.S. Figures 2-36 and 2-
37 illustrate the nitrogen deposition reductions that will occur along U.S. coastlines in 2020 and
2030, respectively, as well as reductions occurring within the interior of the U.S. In 2030,
reductions will range from 3% to 23% along the entire Atlantic and Gulf Coasts while along the
Pacific Coast nitrogen deposition reductions will be higher, ranging from 15% to 25%.
Percent Change in Annual Total Nitrogen Deposition
.«? N ^ /
/ / /
-------
Chapter 2: Air Quality, Health and Welfare Effects
Percent Change in Annual Total Nitrogen Deposition
2030ce_2QO_glob minus 2030ce
Figure 2-37 Percent Change in Annual Total Nitrogen over the U.S. Modeling Domain in 2030
With respect to sulfur deposition, adopting the coordinated strategy will result in
reducing sulfur deposition levels; in many regions by more than 25%. Figures 2-38 and 2-39
illustrate the sulfur deposition reductions occurring throughout the U.S. In some individual U.S.
watersheds, consisting of offshore islands or close to coastal areas, sulfur deposition levels will
be reduced by up to 80%. More generally, in 2030 the Northeast Atlantic Coastal region will
experience sulfur deposition reductions from Category 3 vessels ranging from 9% to more than
25% while the Southeast Atlantic Coastal region will experience reductions ranging from 7% to
more than 25%. Sulfur deposition will be reduced in the Gulf Coast region from 5% to more
than 25%. Along the West Coast of the U.S. sulfur deposition reductions exceeding 25% will
occur in the entire Los Angeles Basin in the State of California. The Pacific Northwest will also
see significant sulfur deposition reductions ranging from 17% to more than 25%. As
importantly, sulfur deposition reductions due to the coordinated strategy will also impact the
entire U.S. land mass with even interior sections of the U.S. experiencing reductions of 5%.
Together, these reductions will assist the U.S. in its efforts to reduce acidification impacts
associated with nitrogen and sulfur depositions in both terrestrial and aquatic ecosystems in
coastal areas of the U.S. as well as within the interior of the U.S.
2-87
-------
Regulatory Impact Analysis
Percent Change in Annual Total Sulfur Deposition
2020ce 200nm minus 202Qce
Figure 2-38 Percent Change in Annual Total Sulfur over the U.S. Modeling Domain in 2020
2-5
-------
Chapter 2: Air Quality, Health and Welfare Effects
Percent Change in Annual Total Sulfur Deposition
o,-- cO o,-- o,-- P.- O Q , Q -O Q Q C. -O
^ ^ £ ^ <£> ^ • <$-
2030ce_200_glob minus 2030ce
Figure 2-39 Percent Change in Annual Total Sulfur over the U.S. Modeling Domain in 2030
Appendix 3B presents the range as well as the average total nitrogen and total sulfur
deposition changes in 2020 for CMAQ modeling scenarios over 18 specific U.S. subregions. In
the case of the coordinated strategy, sulfur deposition levels were reduced by on average from 0
to 19% over these large drainage regions. In individual hydrological unit codes (HUCs)
consisting of offshore islands or close to coastal areas, sulfur deposition levels in 2020 were
improved by as much as 78% while nitrogen deposition levels were improved by as much as
13% in some coastal areas.
2.4.4 Visibility Degradation
2.4.4.1 Current Visibility Levels
Recently designated PM2.5 nonattainment areas indicate that, as of July 2009, over 88
million people live in nonattainment areas for the 1997 PM2.5 NAAQS. Thus, at least these
populations would likely be experiencing visibility impairment, as well as many thousands of
individuals who travel to these areas. In addition, while visibility trends have improved in
2-89
-------
Regulatory Impact Analysis
mandatory class I federal areas, the most recent data show that these areas continue to suffer
from visibility impairment. In eastern parks, average visual range has decreased from 90 miles
to 15-25 miles. In the West, visual range has decreased from 140 miles to 35-90 miles. In
summary, visibility impairment is experienced throughout the U.S., in multi-state regions, urban
areas, and remote mandatory class I federal areas.349'350
2.4.4.2 Projected Visibility Levels
Based on modeling for the coordinated strategy, international shipping activities in 2002
contributed to visibility degradation at all 133 mandatory class I federal areas monitored by the
U.S. Government. Absent further emission controls, international shipping activities will have
an even larger impact on visibility impairment in these mandatory class I federal areas by 2030.
The results suggest that controlling emissions from Category 3 vessels will result in improved
visibility in all 133 mandatory class I federal areas in 2020 and 2030, although areas will
continue to have annual average deciview (DV) levels above background in 2020 and 2030.
The results indicate that as a result of the coordinated strategy, reductions in regional
haze will occur in all 133 of the areas analyzed. The model projects that for all mandatory class I
federal areas combined, average visibility on the 20% worst days will improve by 0.22
deciviews,P or 1.4% in 2020 and by 0.43 deciviews or 2.7% in 2030. The greatest improvement
in visibilities will be seen in coastal areas. For instance, the Agua Tibia Wilderness area (near
Los Angeles) will see a 9% improvement (2.17 DV) in 2020 and a 17% improvement (4.6 DV)
in 2030. National parks and national wilderness areas in other parts of the country will also see
improvements as a result of the controls from the coordinated strategy. For example, in 2030 the
Swanquarter National Wildlife Refuge (North Carolina) will see a 5% improvement in visibility
(1.11 DV); and Acadia National Park (Maine) will see a 6% improvement (1.27 DV). Even
inland mandatory class I federal areas are projected to see improvements as a result of the
controls from the coordinated strategy. For example in 2030, the Grand Canyon National Park,
located in the state of Arizona, will see a 4% improvement in visibility (0.42 DV) with the
coordinated strategy. Table 2-13 contains the full visibility results from 2020 and 2030 for the
133 analyzed areas.
p The level of visibility impairment in an area is based on the light-extinction coefficient and a unit less visibility
index, called a "deciview", which is used in the valuation of visibility. The deciview metric provides a scale for
perceived visual changes over the entire range of conditions, from clear to hazy. Under many scenic conditions, the
average person can generally perceive a change of one deciview. The higher the deciview value, the worse the
visibility. Thus, an improvement in visibility is a decrease in deciview value.
2-90
-------
Chapter 2: Air Quality, Health and Welfare Effects
Table 2-13 Visibility Levels in Deciviews for Individual U.S. Class I Areas on the 20% Worst Days for Several
Scenarios
CLASS 1
AREA
(20%
WORST
DAYS)
Sipsey
Wilderness
Caney Creek
Wilderness
Upper Buffalo
Wilderness
Chiricahua NM
Chiricahua
Wilderness
Galiuro
Wilderness
Grand Canyon
NP
Mazatzal
Wilderness
Petrified Forest
NP
Pine Mountain
Wilderness
Saguaro NM
Sierra Ancha
Wilderness
Sycamore
Canyon
Wilderness
Agua Tibia
Wilderness
Caribou
Wilderness
Cucamonga
Wilderness
Desolation
Wilderness
Dome Land
Wilderness
Emigrant
Wilderness
Hoover
Wilderness
Joshua Tree NM
Lassen Volcanic
NP
Lava Beds NM
Mokelumne
Wilderness
STATE
AL
AR
AR
AZ
AZ
AZ
AZ
AZ
AZ
AZ
AZ
AZ
AZ
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
BASE
LINE
VISIB
ILITY
29.03
26.36
26.27
13.43
13.43
13.43
11.66
13.35
13.21
13.35
14.83
13.67
15.25
23.50
14.15
19.94
12.63
19.43
17.63
12.87
19.62
14.15
15.05
12.63
2020
BASE
23.67
22.20
22.25
13.15
13.17
13.18
11.24
12.88
12.88
12.74
14.39
13.33
15.00
22.99
13.73
18.34
12.29
18.59
17.35
12.79
17.95
13.71
14.47
12.40
2020
200NM
CONT-
ROL
23.42
22.01
22.15
13.07
13.09
13.09
11.04
12.73
12.76
12.59
14.31
13.21
14.90
20.82
13.51
17.57
12.11
18.23
17.14
12.68
17.30
13.46
14.32
12.21
2030
BASE
23.59
21.97
21.98
13.25
13.28
13.32
11.42
13.07
12.88
12.94
14.54
13.50
15.13
24.70
13.78
18.69
12.38
18.61
17.45
12.89
18.18
13.78
14.45
12.52
2030
200NM
CONT-
ROL
23.13
21.59
21.79
13.04
13.07
13.07
11.00
12.71
12.61
12.56
14.31
13.18
14.89
20.44
13.37
17.25
12.06
17.95
17.07
12.68
17.08
13.31
14.13
12.18
NATURAL
BACKGROUN
D
10.99
11.58
11.57
7.21
7.21
7.21
7.14
6.68
6.49
6.68
6.46
6.59
6.69
7.64
7.31
7.06
6.12
7.46
7.64
7.91
7.19
7.31
7.86
6.12
2-91
-------
Regulatory Impact Analysis
Pinnacles NM
Point Reyes NS
Redwood NP
San Gabriel
Wilderness
San Gorgonio
Wilderness
San Jacinto
Wilderness
South Warner
Wilderness
Thousand Lakes
Wilderness
Ventana
Wilderness
Yosemite NP
Black Canyon of
the Gunnison
NM
Eagles Nest
Wilderness
Flat Tops
Wilderness
Great Sand
Dunes NM
La Garita
Wilderness
Maroon Bells-
Snowmass
Wilderness
Mesa Verde NP
Mount Zirkel
Wilderness
Rawah
Wilderness
Rocky Mountain
NP
Weminuche
Wilderness
West Elk
Wilderness
Chassahowitzka
Everglades NP
St. Marks
Cohutta
Wilderness
Okefenokee
Wolf Island
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
FL
FL
FL
GA
GA
GA
18.46
22.81
18.45
19.94
22.17
22.17
15.05
14.15
18.46
17.63
10.33
9.61
9.61
12.78
10.33
9.61
13.03
10.52
10.52
13.83
10.33
9.61
26.09
22.30
26.03
30.30
27.13
27.13
17.86
22.38
18.26
17.92
20.66
20.25
14.70
13.68
18.36
17.32
9.77
9.05
9.25
12.41
9.91
9.23
12.42
10.02
10.00
13.09
9.88
9.20
22.37
21.75
22.37
23.29
23.86
23.76
17.11
21.71
17.81
17.12
20.45
19.86
14.57
13.42
17.72
17.13
9.69
9.00
9.20
12.36
9.84
9.19
12.33
9.99
9.97
13.06
9.80
9.15
21.97
21.14
21.96
23.13
23.30
22.97
18.04
22.59
18.55
18.19
20.48
20.27
14.71
13.75
18.55
17.42
9.81
9.08
9.28
12.46
9.97
9.27
12.48
10.03
10.01
13.07
9.94
9.23
21.86
22.81
22.47
22.81
24.28
24.36
16.75
21.45
17.59
16.72
19.98
19.37
14.44
13.26
17.48
17.06
9.62
8.98
9.17
12.35
9.80
9.16
12.28
9.95
9.94
13.01
9.77
9.10
21.01
21.13
21.54
22.49
23.22
23.00
7.99
15.77
13.91
7.06
7.30
7.30
7.86
7.31
7.99
7.64
6.24
6.54
6.54
6.66
6.24
6.54
6.83
6.44
6.44
7.24
6.24
6.54
11.21
12.15
11.53
11.14
11.44
11.44
2-92
-------
Chapter 2: Air Quality, Health and Welfare Effects
Craters of the
Moon NM
Sawtooth
Wilderness
Mammoth Cave
NP
Acadia NP
Moosehorn
Roosevelt
Campobello
International
Park
Isle Royale NP
Seney
Voyageurs NP
Hercules-Glades
Wilderness
Anaconda-
Pintler
Wilderness
Bob Marshall
Wilderness
Cabinet
Mountains
Wilderness
Gates of the
Mountains
Wilderness
Medicine Lake
Mission
Mountains
Wilderness
Scapegoat
Wilderness
Selway-
Bitterroot
Wilderness
UL Bend
Linville Gorge
Wilderness
Swanquarter
Lostwood
Theodore
Roosevelt NP
Great Gulf
Wilderness
Presidential
Range-Dry
River
Wilderness
Brigantine
ID
ID
KY
ME
ME
ME
MI
MI
MN
MO
MT
MT
MT
MT
MT
MT
MT
MT
MT
NC
NC
ND
ND
NH
NH
NJ
14.00
13.78
31.37
22.89
21.72
21.72
20.74
24.16
19.27
26.75
13.41
14.48
14.09
11.29
17.72
14.48
14.48
13.41
15.14
28.77
25.49
19.57
17.74
22.82
22.82
29.01
13.00
13.66
25.43
20.55
19.02
19.25
18.99
21.54
17.55
22.84
13.14
14.13
13.55
10.90
16.20
14.02
14.15
13.08
14.65
22.63
21.79
17.45
16.44
19.53
19.53
25.27
12.97
13.63
25.33
19.79
18.55
18.58
18.84
21.49
17.52
22.74
13.10
14.11
13.50
10.87
16.18
13.99
14.12
13.02
14.63
22.43
21.11
17.43
16.42
19.34
19.33
24.46
12.88
13.67
25.15
20.76
19.16
19.62
18.79
21.32
17.32
22.59
13.14
14.10
13.48
10.86
16.09
13.97
14.12
13.08
14.59
22.18
21.84
17.28
16.26
19.57
19.56
25.37
12.81
13.60
24.98
19.49
18.29
18.27
18.61
21.25
17.27
22.42
13.04
14.03
13.37
10.80
16.04
13.89
14.06
12.94
14.56
21.79
20.73
17.24
16.22
19.24
19.22
24.06
7.53
6.43
11.08
12.43
12.01
12.01
12.37
12.65
12.06
11.30
7.43
7.74
7.53
6.45
7.90
7.74
7.74
7.43
8.16
11.22
11.94
8.00
7.79
11.99
11.99
12.24
2-93
-------
Regulatory Impact Analysis
Bandelier NM
Bosque del
Apache
Gila Wilderness
Pecos
Wilderness
Salt Creek
San Pedro Parks
Wilderness
Wheeler Peak
Wilderness
White Mountain
Wilderness
Jarbidge
Wilderness
Wichita
Mountains
Crater Lake NP
Diamond Peak
Wilderness
Eagle Cap
Wilderness
Gearhart
Mountain
Wilderness
Hells Canyon
Wilderness
Kalmiopsis
Wilderness
Mount Hood
Wilderness
Mount Jefferson
Wilderness
Mount
Washington
Wilderness
Mountain Lakes
Wilderness
Strawberry
Mountain
Wilderness
Three Sisters
Wilderness
Cape Romain
Badlands NP
Wind Cave NP
Great Smoky
Mountains NP
Joyce-Kilmer-
Slickrock
Wilderness
NM
NM
NM
NM
NM
NM
NM
NM
NV
OK
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
sc
SD
SD
TN
TN
12.22
13.80
13.11
10.41
18.03
10.17
10.41
13.70
12.07
23.81
13.74
13.74
18.57
13.74
18.55
15.51
14.86
15.33
15.33
13.74
18.57
15.33
26.48
17.14
15.84
30.28
30.28
11.45
12.93
12.59
10.00
16.70
9.52
9.91
12.87
11.88
20.45
13.33
13.26
17.73
13.41
17.16
15.24
14.30
14.90
14.88
13.28
17.71
14.93
23.51
15.63
14.78
24.01
23.56
11.39
12.89
12.52
9.93
16.66
9.44
9.85
12.82
11.81
20.31
13.20
13.11
17.69
13.30
17.12
14.85
13.93
14.62
14.62
13.14
17.66
14.69
22.35
15.59
14.75
23.81
23.35
11.47
12.85
12.64
10.05
16.63
9.56
9.94
12.84
11.93
20.20
13.36
13.26
17.60
13.43
16.96
15.42
14.44
15.01
14.99
13.32
17.59
15.04
24.16
15.53
14.69
23.64
23.19
11.32
12.76
12.49
9.89
16.54
9.37
9.80
12.73
11.78
19.93
13.09
12.96
17.49
13.20
16.85
14.67
13.63
14.44
14.44
13.03
17.48
14.53
22.29
15.45
14.62
23.25
22.78
6.26
6.73
6.69
6.44
6.81
6.08
6.44
6.86
7.87
7.53
7.84
7.84
8.92
7.84
8.32
9.44
8.44
8.79
8.79
7.84
8.92
8.79
12.12
8.06
7.71
11.24
11.24
2-94
-------
Chapter 2: Air Quality, Health and Welfare Effects
Big Bend NP
Carlsbad
Caverns NP
Guadalupe
Mountains NP
Arches NP
Bryce Canyon
NP
Canyonlands NP
Zion NP
James River
Face Wilderness
Shenandoah NP
Lye Brook
Wilderness
Alpine Lake
Wilderness
Glacier Peak
Wilderness
Goat Rocks
Wilderness
Mount Adams
Wilderness
Mount Rainier
NP
North Cascades
NP
Olympic NP
Pasayten
Wilderness
Dolly Sods
Wilderness
Otter Creek
Wilderness
Bridger
Wilderness
Fitzpatrick
Wilderness
Grand Teton NP
North Absaroka
Wilderness
Red Rock Lakes
Teton
Wilderness
Washakie
Wilderness
Yellowstone NP
Tx
Tx
Tx
UT
UT
UT
UT
VA
VA
VT
WA
WA
WA
WA
WA
WA
WA
WA
WV
WV
WY
WY
WY
WY
WY
WY
WY
WY
17.30
17.19
17.19
11.24
11.65
11.24
13.24
29.12
29.31
24.45
17.84
13.96
12.76
12.76
18.24
13.96
16.74
15.23
29.04
29.04
11.12
11.12
11.76
11.45
11.76
11.76
11.45
11.76
16.25
16.05
16.03
10.94
11.41
10.96
12.91
23.31
22.77
21.02
16.85
13.85
12.23
12.16
17.47
13.85
16.18
14.89
22.46
22.45
10.83
10.87
11.37
11.17
11.45
11.43
11.19
11.40
16.11
15.98
15.95
10.86
11.28
10.90
12.80
23.16
22.61
20.77
16.56
13.53
11.95
11.88
17.02
13.46
15.87
14.82
22.31
22.30
10.78
10.81
11.32
11.14
11.40
11.38
11.16
11.35
16.32
16.03
16.01
11.01
11.51
10.93
12.99
22.86
22.32
20.98
16.97
14.11
12.42
12.32
17.75
14.18
16.47
14.92
22.09
22.10
10.87
10.91
11.37
11.16
11.46
11.43
11.19
11.40
16.02
15.88
15.86
10.83
11.23
10.85
12.71
22.59
22.04
20.56
16.25
13.31
11.77
11.70
16.76
13.19
15.58
14.70
21.83
21.83
10.76
10.79
11.27
11.10
11.36
11.34
11.13
11.31
7.16
6.68
6.68
6.43
6.86
6.43
6.99
11.13
11.35
11.73
8.43
8.01
8.36
8.36
8.55
8.01
8.44
8.26
10.39
10.39
6.58
6.58
6.51
6.86
6.51
6.51
6.86
6.51
2-95
-------
Regulatory Impact Analysis
2.4.5 Air Quality Modeling Methodology
In this section, we present information on the air quality modeling, including the model
domain and modeling inputs. Further discussion of the modeling methodology is included in the
AQM TSD for the coordinated strategy.351
2.4.5.1 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.352'353'354 CMAQ is
a publicly available, peer reviewed,*2 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."355 The CMAQ model is a
well-known and well-respected tool and has been used in numerous national and international
applications.356'357'358
This 2002 multi-pollutant modeling platform used the latest publicly-released CMAQ
version 4.6R 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
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
Q 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 .
R 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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closure scheme); (3) a heterogeneous reaction involving nitrate formation (gas-phase reactions
involving ^Os and H2O); (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.8
2.4.5.2 Model Domain and Configuration
The CMAQ modeling domain encompasses all of the lower 48 States 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 US and a Western US domain), as shown in Figure 2-39. The
modeling domain contains 14 vertical layers with the top of the modeling domain at about
16,200 meters, or 100 millibars (mb).
Figure 2-39 Map of the CMAQ Modeling Domain
s 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.
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2.4.5.3 Model Inputs
The key inputs to the CMAQ model include emissions from anthropogenic and biogenic
sources, meteorological data, and initial and boundary conditions. The CMAQ meteorological
input files were derived from a simulation of the Pennsylvania State University/National Center
for Atmospheric Research Mesoscale Model359 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.360 The meteorology for the national 36 km grid and the 12 km Eastern U.S. grid were
developed by EPA and are described in more detail within the AQM TSD. The meteorology for
the 12 km Western U.S. grid was developed by the Western Regional Air Partnership (WRAP)
Regional Planning Organization. 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.361
The lateral boundary and initial species concentrations are provided by a three-
dimensional global atmospheric chemistry model, the GEOS-CHEM model.362 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 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 future base conditions from the 36 km coarse grid modeling were used
as the initial/boundary state for all subsequent 12 km finer grid modeling.
The emissions inputs used for the 2002 base year and each of the future year base cases
and control scenarios analyzed for the coordinated strategy are summarized in Chapter 3 of this
RIA.
2.4.5.4 CMAQ Evaluation
An operational model performance evaluation for PM2.5 and its related speciated
components (e.g., sulfate, nitrate, elemental carbon, organic carbon, etc.) was conducted using
2002 state/local monitoring data in order to estimate the ability of the CMAQ modeling system
to replicate base year concentrations. In summary, model performance statistics were calculated
for observed/predicted pairs of daily/monthly/seasonal/annual concentrations. Statistics were
generated for the following geographic groupings: domain wide, Eastern vs. Western (divided
along the 100th meridian), and each Regional Planning Organization (RPO) region.1 The
"acceptability" of model performance was judged by comparing our results to those found in
T Regional Planning Organization regions include: Mid-Atlantic/Northeast Visibility Union (MANE-VU), Midwest
Regional Planning Organization - Lake Michigan Air Directors Consortium (MWRPO-LADCO), Visibility
Improvement State and Tribal Association of the Southeast (VISTAS), Central States Regional Air Partnership
(CENRAP), and Western Regional Air Partnership (WRAP).
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recent regional PM2.5 model applications for other, non-EPA studies.u Overall, the performance
for the 2002 modeling platform is within the range or close to that of these other applications.
The performance of the CMAQ modeling was evaluated over a 2002 base case. The model was
able to reproduce historical concentrations of ozone and PM2.5 at land-based monitors with low
amounts of bias and error. While we are not able to evaluate the model's performance over the
ocean due to the absence of surface monitors, there is no evidence to suggest that model
performance is unsatisfactory over the ocean. A more detailed summary of the 2002 CMAQ
model performance evaluation is available within the AQM TSD.
2.4.5.5 Model Simulation Scenarios
As part of our analysis for this rulemaking, 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 projection
2020 base line projection with coordinated strategy emission reductions
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 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 this RIA 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 exemption 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).
u 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.
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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 PM2.5 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)".363 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.364 The projected 8-hour ozone
design values were calculated using the approach identified in EPA's guidance on air quality
modeling attainment demonstrations.365
2.4.5.6 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
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.
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2.4.5.7 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.v
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.366
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
black object against the horizon sky. Visual range (in units of kilometers) can be calculated from
bext using the formula: Visual Range (km) = 3912/bext (bext units are inverse megameters [Mm"1])
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).
v 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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For visibility calculations, we are continuing to use the IMPROVE program species
definitions and visibility formulas which are recommended in the modeling guidance.367 Each
IMPROVE site has measurements of PM2.5 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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116 ICF International. September 28, 2007. Estimation of diesel particulate matter population
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363 U.S. EPA, (2004), Procedures for Estimating Future PM2.5 Values for the CAIR Final Rule
by Application of the (Revised) Speciated Modeled Attainment Test (SMAT)- Updated 11/8/04.
364 U.S. EPA, (2008), Control of Emissions from Nonroad Spark-Ignition Engines and
Equipment, Technical Support Document
365 US EPA (2007). Guidance on the Use of Models and Other Analyses for Demonstrating
Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze. EPA-454/B-07-002.
366 Sisler, J.F. (1996) Spatial and seasonal patterns and long term variability of the composition
of the haze in the United States: an analysis of data from the IMPROVE network. CIRA Report,
ISSN 0737-5352-32, Colorado State University.
367 U.S. EPA (2007) Guidance on the Use of Models and Other Analyses For Demonstrating
Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze; EPA-454/B-07-002;
Research Triangle Park, NC; April 2007.
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CHAPTER 3 Emission Inventory
3.1 Introduction
Ships (i.e., ocean-going vessels) are significant contributors to the total United States
(U.S.) mobile source emission inventory. The U.S. ship inventory reported here focuses on
Category 3 (C3) vessels, which use C3 engines for propulsion. C3 engines are defined as having
displacement above 30 liters per cylinder (L/cyl). The resulting inventory includes emissions
from both propulsion and auxiliary engines used on these vessels, as well as those on gas and
steam turbine vessels.
Most of the vessels operating in U.S. ports that have propulsion engines less than 30
liters per cylinder are domestic and are already subject to strict national standards affecting NOx,
PM, and fuel sulfur content. As such, the inventory does not include any ships, foreign or
domestic, powered by Category 1 or Category 2 (i.e., <30 L/cyl) engines. In addition, as
discussed in Sections 3.3.2.5 and 3.3.3.2, this inventory is primarily based on activity data for
ships that carry foreign cargo. Category 3 vessels carrying domestic cargo that operate only
between U.S. ports are only partially accounted for in this inventory.1 Emissions due to military
vessels are also excluded.
The regional and national inventories for C3 vessels presented in this chapter are sums of
independently constructed port and interport emissions inventories. Port inventories were
developed for 89 deep water and 28 Great Lake ports in the U.S.2 While there are more than 117
ports in the U.S., these are the top U.S. ports in terms of cargo tonnage. Port-specific emissions
were calculated with a "bottom-up" approach, using data for vessel calls, emission factors, and
activity for each port. Interport emissions were obtained using the Waterway Network Ship
Traffic, Energy and Environment Model (STEEM).3'4 STEEM also uses a "bottom-up"
approach, estimating emissions from C3 vessels using historical North American 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 200 nautical miles (nm) of the U.S.
The detailed port inventories were spatially merged into the STEEM gridded inventory to
create a comprehensive inventory for Category 3 vessels. For the 117 ports, this involved
removing the near-port portion of the STEEM inventory and replacing it with the detailed port
inventories. For the remaining U.S. ports for which detailed port inventories are not available,
the near-port portion of the STEEM inventory was simply retained. This was done for a base
year of 2002. Inventories for 2020 were then projected using regional growth rates5'6 and
adjustment factors to account for the International Maritime Organization (IMO) Tier 1 and Tier
2 NOX standards and NOX retrofit program.2 Inventories incorporating additional Tier 3 NOX
and fuel sulfur controls within the proposed Emission Control Area (EGA) were also developed
for 2020 and 2030.
This chapter details the methodologies used to create the baseline and future year
inventories and presents the resulting inventories for the U.S. Section 3.2 describes the modeling
domain and geographic regions used in this analysis. Section 3.3 describes the methodology and
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Chapter 3: Emission Inventory
results for the 2002 base year inventory. Section 3.4 follows with a discussion of the growth
rates and methodology used to create the 2020 and 2030 baseline and control inventories.
Section 3.5 presents the estimated contribution of Category 3 vessels to U.S. national and local
inventories. Section 3.6 follows with estimates of the projected emission reductions due to the
final control program. Section 3.7 concludes the chapter by describing the changes in the
inventories between the baseline scenarios used for the air quality modeling and the updated
baseline scenarios in this final rule.
The inventory estimates reported in this chapter include emissions out to 200 nm from
the U.S. coastline, including Alaska and Hawaii, but not extending into the Exclusive Economic
Zone (EEZ) of neighboring countries. Inventories are presented for the following pollutants:
oxides of nitrogen (NOx), particulate matter (PM2.5 and PMio), sulfur dioxide (862),
hydrocarbons (HC), carbon monoxide (CO), and carbon dioxide (CC^). The PM inventories
include directly emitted PM only, although secondary sulfates are taken into account in the air
quality modeling.
3.2 Modeling Domain and Geographic Regions
The inventories described in this chapter reflect ship operations that occur within the area
that extends 200 nautical miles (nm) from the official U.S. baseline, which 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. This boundary is roughly equivalent to the border of the U.S
Exclusive Economic Zone. The U.S. region was then clipped to the boundaries of the U.S.
Exclusive Economic Zone. The boundary was divided into regions using geographic
information system (GIS) shapefiles obtained from the National Oceanic and Atmospheric
Administration, Office of Coast Survey.7 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.8
The resulting region 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 years 2020 and 2030, as described later in this document.
• 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 46° 15'
North).
• The East Coast and Gulf of Mexico regions were divided along a vertical line roughly
drawn through Key Largo (Longitude 80° 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.
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Regulatory Impact Analysis
• For the Great Lakes domain, a similar approach was used to create shapefiles containing
all the ports and inland waterways in the near 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 Hawaii, Maui, Oahu, Molokai, Niihau, Kauai, 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 3-1. U.S. territories are not included in this analysis.
• 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 3-1 Regional Modeling Domains
3-4
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Chapter 3: Emission Inventory
3.3 Development of 2002 Baseline Inventory
This section describes the methodology and inputs, and presents the resulting inventories
for the 2002 baseline calendar year. The first section describes the general methodology. The
second section describes the methodology, inputs, and results for near port emissions. The third
section describes the methodology and inputs for emissions when operating away from port (also
referred to as "interport" emissions). The fourth section describes the method for merging the
interport and near port portions of the inventory. Resulting total emissions for the U.S., as well
as for nine geographic regions within the U.S., are then presented.
3.3.1 Outline of Methodology
The total inventory was created by summing emissions estimates for ships while at port
(near port inventories) and while underway (interport inventories). Near port inventories for
calendar year 2002 were developed for 117 U.S. commercial ports that engage in foreign trade.
Based on an ICF International analysis,9 these 117 commercial ports encompass nearly all U.S.
C3 vessel calls.10
The outer boundaries of the ports are defined as 25 nm from the terminus of the reduced
speed zone for deep water ports and 7 nm from the terminus of the reduced speed zone for Great
Lake ports. Port emissions are calculated for different modes of operation and then summed.
Emissions for each mode are calculated using port-specific information for vessel calls, vessel
characteristics, and activity, as well as other inputs that vary instead by vessel or engine type
(e.g., emission factors).
The interport inventory was estimated using the Waterway Network Ship Traffic, Energy,
and Environmental Model (STEEM).3'4 The 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.
The 117 near port inventories are an improvement upon STEEM's near 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 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 for the first and last 20
kilometers of each trip when a ship is leaving or entering a 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. Fourth, and finally, the STEEM model does not include the
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Regulatory Impact Analysis
emissions from auxiliary engines during hotelling operations at the port. The near-port
inventories correct these issues.
The regional emission inventories produced by the current STEEM interport model are
most accurate for vessels while cruising in ocean or Great Lakes shipping lanes, and the near
port inventories, which use more detailed local port information, are significantly more accurate
near the ports. Therefore, the inventories in this analysis are derived by merging together: (1)
the near port inventories, which extend 25 nautical miles and 7 nautical miles from the terminus
of the RSZ for deep water ports and Great Lake ports, respectively, and (2) the remaining
interport portion of the STEEM inventory, which extends from the endpoint of the near port
inventories to the 200 nautical mile boundary or international border with Canada, as
appropriate. 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.
3.3.2 Near Port Emissions
Near port inventories for calendar year 2002 were developed for ocean-going vessels at
89 deep water and 28 Great Lake ports in the U.S. The inventories include emissions from both
propulsion and auxiliary engines on these vessels.
This section first describes the selection of the ports for analysis and then provides the
methodology used to develop the near port inventories. This is followed by a description of the
key inputs. Total emissions by port and pollutant for 2002 are then presented. The work
summarized here was conducted by ICF International under contract to EPA.2 The ICF
documentation provides more detailed information.2
3.3.2.1 Selection of Individual Ports to be Analyzed
All 150 deep sea and Great Lake ports in the Principal Ports of the United States dataset11
were used as a starting point. Thirty ports which had no foreign traffic were eliminated because
there is no information in the U.S. Army Corps of Engineers (USAGE) entrances and clearances
data about domestic traffic. (See Section 3.3.2.5 for a further discussion of domestic traffic and
how it is accounted for in this study). In addition, two U.S. Territory ports in Puerto Rico were
removed as these were outside the area of interest for this study. Several California ports were
added to the principle ports list because ARE provided the necessary data and estimates for those
ports. This is discussed in Section 3.3.2.4.1. Also, a conglomerate port in the Puget Sound area
was added as discussed in Section 3.3.2.4.2. The final list of 117 deep sea and Great Lake ports,
along with their coordinates, is given in the Appendix, Table 3-102.
3.3.2.2 Port Methodology
Near port emissions for each port are calculated for four modes of operation: (1)
hotelling, (2) maneuvering, (3) reduced speed zone (RSZ), and (4) cruise. Hotelling, 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
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Chapter 3: Emission Inventory
RSZ would begin and end when the pilots board or disembark, and typically occurs when the
near port shipping lanes reach unconstrained ocean shipping lanes. The cruise mode emissions
in the near ports analysis extend 25 nautical miles beyond the end of the RSZ lanes for deep
water ports and 7 nautical miles for Great Lake ports.
Emissions are calculated separately for propulsion and auxiliary engines. The basic equation
used is as follows:
Equation 3-1
EmissionSl0(le[eng] = (calls) x (P[eng]) x (hrsl callmoj x (LFmode[eng]) x (EF[eng]) x (Adj) x (10^ tonnes/ 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
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 are 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.
3.3.2.2.1 Cruise
Cruise emissions are calculated for both propulsion (main) and auxiliary engines. The
basic equation used to calculate cruise mode emissions for the main engines is:
Equation 3-2
Emission§misimai^ = (calls) x (P[mai^) x (hrsl callcruj x (LFcmisM) x (EF[maili) x (10^ 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
hrs/callcraise = Hours per call for cruise mode
LFcruiSe [main] = Load factor for main engines in cruise mode (unitless)
EFjmain] = 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
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Regulatory Impact Analysis
In addition, the time in cruise is calculated as follows:
Equation 3-3
Hrs I callcruise = Cruise Distance [nmiles] I Cruise Speed [knots] x 2 trips I call
Where:
Cruise distance = one way distance (25 nautical miles for deep sea ports, and 7 nautical miles
for Great Lake ports)
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 3-4
LoadFactorcmi = (Cruise Speed[knots] /Maximum Speed[knots]f
Since cruise speed is estimated at 94 percent of maximum speed12, the load factor for
main engines at cruise is 0.83.
Substituting Equation 3-3 for time in cruise into Equation 3-2, and using the load factor
of 0.83, the equation used to calculate cruise mode emissions for the main engines becomes the
following:
Equation 3-5 Cruise Mode Emissions for Main Engines
Emissionsui^mai^ = (calty x (P[mai^x (CruisDikwcdCruisSpeetyx (Itripkall) x 0.83x (ETj*^) x (10* tonne/kg)
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
Cruise distance = one way distance (25 nautical miles for deep sea ports, and 7 nautical miles
for Great Lake ports)
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)
10"6 = Conversion factor from grams to metric tonnes
The equation used to calculate cruise mode emissions for the auxiliary engines is:
Equation 3-6 Cruise Mode Emissions for Auxiliary Engines
^ = (call:) x (P[auA ) x (CruisDiAwxe/CruisSpee^x (2tripkall) x (LFcmis^ ) x (EF[auA ) x (1 (T6 tonne d g)
3-8
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Chapter 3: Emission Inventory
Where:
EmissionsCruise[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
Cruise distance = one way distance (25 nautical miles for deep sea ports, and 7 nautical miles
for Great Lake ports)
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, as discussed in Section 3.3.2.3.1.1, these inputs were developed by
port for bins that varied by ship type, engine type, and dead weight tonnage (DWT) range.
3.3.2.2.2 Reduced Speed Zone
RSZ emissions are calculated for both propulsion (main) and auxiliary engines. The
basic equation used to calculate RSZ mode emissions for the main engines is:
Equation 3-7
Emissio^maiii = (calfy x (P[maiii) x (hrsl ca^sz) x (LFRS2[maiii) x (EF[maiii) x (Adj) x (10* tonnei 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
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)
10"6 = Conversion factor from grams to metric tonnes
In addition, the time in RSZ mode is calculated as follows:
Equation 3-8
Hrs I call^z = RSZ Distance [nmiles] I RSZ Speed [knots] x 2 trips I call
Load factor during the RSZ mode is calculated as follows:
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Regulatory Impact Analysis
Equation 3-9
LoadFactorRSZ,in. = (RSZ Speed / Maximum Speed}3
In addition:
Equation 3-10
Maximum Speed = Cruise Speed / 0.94
Where:
0.94 = Fraction of cruise speed to maximum speed
Substituting
Equation 3-10 into Equation 3-9, the equation to calculate load factor becomes:
Equation 3-11
LoadFactorRSZ[main, = (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 3-8 for time in mode and Equation 3-11 for load factor into
Equation 3-7 , the expression used to calculate RSZ mode emissions for the main engines
becomes:
Equation 3-12 RSZ Mode Emissions for Main Engines
Emissiong^^ = (caffi)x(P[au4)x(RSZDiiaK(/RSZSpeetf x(2tripdcall)x(RSZSpeed
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Chapter 3: Emission Inventory
adjustment factors were developed and applied when the load falls 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:
Equation 3-13 RSZ Mode Emissions for Auxiliary Engines
= (calls) x (P[awc] ) x (RSZ DiAarre/ RSZ Speed) x (2 tripJcall) x (LF^^ ) x (EF[awc] ) x (1 (T6 tonnes/ 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
RSZ distance = one way distance, in nautical miles (specific to each port)
RSZ speed = speed, in knots (specific to each port)
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, because of the way they are generally operated. When only low loads are needed, 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 vary by port rather than vessel or engine
type. Some RSZ speeds vary by ship type, while others vary by DWT. Mostly, however, RSZ
speed is constant for all ships entering the harbor area. All Great Lake ports have reduced speed
zone distances of three nautical miles occurring at halfway between cruise speed and
maneuvering speed.
3.3.2.2.3 Maneuvering
Maneuvering emissions are calculated for both propulsion (main) and auxiliary engines.
The basic equation used to calculate maneuvering mode emissions for the main engines is:
Equation 3-14
Emission^^ = (call§ x (P[mai^ x (hrs/callmj x (LFmai{maili*)x (EF[maili) x (Adj) x (1 0^ tonne jg)
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
hrs/callman = Hours per call for maneuvering mode
3-11
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Regulatory Impact Analysis
LFman [mam] = 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 3-15
LoadFactorman,main} = (Man Speed[knots]/Maximum Speed[knots]f
In addition:
Equation 3-16
Maximum Speed = Cruise Speed[knots] 10.94
Where:
0.94 = Fraction of cruise speed to maximum speed
Also, the maneuvering speed is 5.8 knots. Substituting Equation 3-16 into Equation 3-15, and
using a maneuvering speed of 5.8 knots, the equation to calculate load factor becomes:
Equation 3-17
LoadFactor , = ($ .45 / Cruise Speed}3
man[mam] \ i /
Load factors below 2 percent were set to 2 percent as a minimum.
Substituting Equation 3-17 for load factor into Equation 3-14, the expression used to
calculate maneuvering mode emissions for the main engines becomes:
Equation 3-18 Maneuvering Mode Emissions for Main Engines
Emission^^ = (calty x (P[maiii) x (hrsl callmm) x (5.457 Cruis&peetf x (EF[maiii) x (Adj) x (1 (T6 tonned 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
hrs/callman = Hours per call for maneuvering mode
Cruise speed = Vessel service speed, in knots
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Chapter 3: Emission Inventory
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 falls below 20 percent, low load
adjustment factors are also applied accordingly. Maneuvering times are not readily available for
all 117 ports. For this analysis, maneuvering times and load factors available for a subset of the
ports were used to calculate maneuvering emissions for the remaining ports. This is discussed in
more detail in Section 3.3.2.3.8.
The equation used to calculate maneuvering mode emissions for the auxiliary engines is:
Equation 3-19 Maneuvering Mode Emissions for Auxiliary Engines
Emissionsma4aux] = (calls') x (P[aux]) x (hrsl callman) x (LFma4aux]) x (EF[aux]) x (1 (T6 tonnes/ 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
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.
3.3.2.2.4 Hotetting
Hotelling emissions are 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:
Equation 3-20 Hotelling Mode Emissions for Auxiliary Engines
Emission^aux] = (calls) x (P[aux]) x (hrsl callhotel) x (LFhotelaux}) x (EF[aux]) x (10^ tonnes/ 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
hrs/callhotei = Hours per call for hotelling mode
i [aux] = Load factor for auxiliary engines in hotelling mode, unitless (these vary by ship
type and activity mode)
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Regulatory Impact Analysis
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 are not readily available for all 117 ports. For this analysis, hotelling
times available for a subset of the ports were used to calculate hotelling emissions for the
remaining ports. This is discussed in more detail in Section 3.3.2.3.8.
3.3.2.3 Inputs for Port Emission Calculations
From a review of the equations described in Section 3.3.2.2, the following inputs are
required to calculate emissions for the four modes of operation (cruise, RSZ, maneuvering, and
hotelling):
• Number of calls
• Main engine power
• Cruise (vessel service) speed
• Cruise distance
• RSZ distance for each port
• RSZ speed for each port
• Auxiliary engine power
• Auxiliary load factors
• Main and auxiliary emission factors
• Low load adjustment factors for main engines
• Maneuvering time-in-mode (hours/call)
• Hotelling time-in-mode (hours/call)
Note that load factors for main engines are not listed explicitly, since they are calculated
as a function of mode and/or cruise speed. This section describes the inputs in more detail, as
well as the sources for each input.
3.3.2.3.1 Calls and Ship Characteristics (Propulsion Engine Power and Cruise Speed)
For this analysis, U.S. Army Corps of Engineers (USAGE) entrance and clearance data
for 2002,13 together with Lloyd's data for ship characteristics,14 were used to calculate 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.
3.3.2.3.1.1 Bins by Ship Type, Engine Type, and DWT Range
The records from the USAGE entrances and clearances data base 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. The data was then binned by ship type,
engine type and dead weight tonnage (DWT) range. The number of entrances and clearances in
each bin are counted, summed together and divided by two to determine the number of calls (i.e.,
one entrance and one clearance was considered a call). For Great Lake ports, there is a larger
frequency of ships either entering the port loaded and leaving unloaded (light) or entering the
3-14
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Chapter 3: Emission Inventory
port light and leaving loaded. In these cases, there would only be one record (the loaded trip into
or out of the port) that would be present in the data. For Great Lake ports, clearances were
matched with entrances by ship name. If there was not a reasonable match, the orphan entrance
or clearance was treated as a call.
Propulsion power and vessel cruise speed are also averaged for each bin. While each port
is analyzed separately, the various bins and national average ship characteristics are given in
Table 3-1 for deep sea ports and Table 3-2 for Great Lake ports. Auxiliary engine power was
computed from the average propulsion power using the auxiliary power to propulsion power
ratios discussed in Section 3.3.2.3.4.
Table 3-1 Bins and Average Ship Characteristics for Deep Sea Ports
Ship Type
AUTO CARRIER
Main
Engine a
MSB
DWT Range
< 10,000
10,000-20,000
20,000 - 30,000
MSB Total
SSB
<10,000
10,000-20,000
20,000 - 30,000
SSB Total
AUTO CARRIER Total
BARGE CARRIER
MSB
< 25,000
MSB Total
SSB
< 25,000
35,000-45,000
45,000 - 90,000
SSB Total
ST
35,000-45,000
ST Total
BARGE CARRIER Total
BULK CARRIER
MSB
< 25,000
25,000 - 35,000
35,000-45,000
45,000 - 90,000
> 90,000
MSB Total
Calls
35
224
28
286
84
2,316
621
3,020
3,306
1
1
1
20
19
40
5
5
45
213
6
44
51
1
314
Engine Power (kW)
Main
6,527
10,499
6,620
9,640
7,927
10,899
13,239
11,298
11,155
4,461
4,461
3,916
19,463
25,041
21,724
24,196
24,196
21,779
4,867
8,948
9,148
9,705
16,109
6,360
Auxiliary
1,736
2,793
1,761
2,564
2,109
2,899
3,522
3,005
2,967
1,200
1,200
1,053
5,236
6,736
5,844
6,509
6,509
5,859
1,080
1,986
2,031
2,155
3,576
1,412
Cruise
Speed
(kts)
16.0
18.2
13.0
17.4
17.7
18.7
19.5
18.8
18.7
13.3
13.3
14.0
18.0
20.0
18.9
21.7
21.7
19.1
14.0
14.0
15.2
14.3
15.8
14.2
DWT
6,211
13,003
22,268
13,063
8,845
14,959
24,860
16,826
16,500
4,393
4,393
11,783
44,799
48,093
45,538
41,294
41,294
44,657
15,819
29,984
39,128
71,242
105,550
28,621
3-15
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Regulatory Impact Analysis
Table 3-1 Bins and Average Ship Characteristics for Deep Sea Ports (continued)
Ship Type
BULK CARRIER
Main
Engine a
SSD
DWT Range
< 25,000
25,000 - 35,000
35,000-45,000
45,000 - 90,000
> 90,000
SSD Total
ST
< 25,000
25,000 - 35,000
ST Total
BULK CARRIER Total
CONTAINER SHIP
MSB
< 25,000
25,000 - 35,000
35,000-45,000
45,000 - 90,000
MSB Total
SSB
< 25,000
25,000 - 35,000
35,000-45,000
45,000 - 90,000
> 90,000
SSB Total
ST
< 25,000
25,000 - 35,000
35,000-45,000
ST Total
CONTAINER SHIP Total
GENERAL CARGO
MSB
< 25,000
25,000 - 35,000
35,000-45,000
45,000 - 90,000
MSB Total
SSB
< 25,000
25,000 - 35,000
35,000-45,000
45,000 - 90,000
> 90,000
SSB Total
ST
< 25,000
ST Total
GENERAL CARGO Total
Calls
1,194
2,192
1,742
3,733
352
9,212
72
3
75
9,600
1,005
53
59
248
1,365
2,054
2,360
2,443
6,209
98
13,163
46
89
41
176
14,703
2,937
38
1
9
2,984
2,357
500
1,122
405
6
4,389
18
18
7,391
Engine Power (kW)
Main
5,650
7,191
8,515
9,484
14,071
8,434
6,290
8,948
6,379
8,350
6,846
22,304
26,102
37,650
13,878
12,381
19,247
24,755
36,151
57,325
27,454
20,396
21,066
23,562
21,472
26,122
5,080
9,458
13,728
11,932
5,159
6,726
7,575
9,269
9,336
10,628
7,718
17,897
17,897
6,709
Auxiliary
1,254
1,596
1,890
2,105
3,124
1,872
1,396
1,986
1,416
1,854
1,506
4,907
5,742
8,283
3,053
2,724
4,234
5,446
7,953
12,612
6,040
4,487
4,635
5,184
4,724
5,747
1,316
2,450
3,556
3,090
1,336
1,742
1,962
2,401
2,418
2,753
1,999
4,635
4,635
1,738
Cruise
Speed
(kts)
14.2
14.6
14.7
14.4
14.5
14.5
15.0
15.0
15.0
14.5
17.2
20.6
22.3
24.0
18.8
19.1
20.5
21.8
23.3
25.0
21.9
20.8
21.0
21.0
21.0
21.6
15.1
15.4
14.3
16.0
15.1
15.4
14.9
15.2
15.1
14.5
15.3
21.0
21.0
15.2
DWT
19,913
29,323
39,875
62,573
112,396
46,746
18,314
33,373
18,819
45,936
8,638
28,500
39,932
56,264
19,419
18,776
31,205
40,765
58,604
105,231
44,513
19,963
30,804
40,949
30,334
42,014
8,268
30,746
40,910
50,250
8,688
14,409
29,713
41,568
47,712
134,981
26,326
22,548
22,548
19,196
3-16
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Chapter 3: Emission Inventory
Table 3-1 Bins and Average Ship Characteristics for Deep Sea Ports (continued)
Ship Type
MISCELLANEOUS
Main
Engine a
MSB
DWT Range
All
MSB Total
MSB-EB
All
MSB-EB Total
SSB
All
SSB Total
ST
All
ST Total
MISCELLANEOUS Total
PASSENGER
MSB
<10,000
10,000-20,000
MSB Total
MSB-EB
<10,000
10,000-20,000
MSB-EB Total
SSB
<10,000
SSB Total
GT-EB
10,000-20,000
GT-EB Total
ST
<10,000
10,000-20,000
ST Total
PASSENGER Total
REEFER
MSB
<10,000
10,000-20,000
MSB Total
SSB
<10,000
10,000-20,000
SSB Total
REEFER Total
RORO
MSB
<10,000
10,000-20,000
> 30,000
MSB Total
SSB
<10,000
10,000-20,000
20,000 - 30,000
> 30,000
SSB Total
GT
> 30,000
GT Total
ST
10,000-20,000
20,000 - 30,000
ST Total
RORO Total
Calls
51
51
6
6
7
7
1
1
64
1,011
24
1,035
1,964
228
2,192
189
189
143
143
13
52
65
3,623
122
60
182
464
801
1,265
1,447
892
286
31
1,208
132
208
31
555
925
1
1
2
1
3
2,137
Engine Power (kW)
Main
9,405
9,405
16,968
16,968
4,659
4,659
12,871
12,871
9,564
22,024
96,945
23,762
39,095
53,236
40,566
23,595
23,595
44,428
44,428
16,858
29,982
27,357
34,800
4,829
12,506
7,360
6,539
12,711
10,449
10,060
7,840
9,312
22,386
8,561
7,240
9,062
12,781
20,362
15,702
47,076
47,076
22,373
22,373
22,373
11,687
Auxiliary
2,530
2,530
4,565
4,565
1,253
1,253
3,462
3,462
2,573
6,123
26,951
6,606
10,868
14,800
11,277
6,559
6,559
12,351
12,351
4,687
8,335
7,605
9,674
1,961
5,077
2,988
2,655
5,161
4,242
4,084
2,031
2,412
5,798
2,217
1,875
2,347
3,310
5,274
4,067
12,193
12,193
5,795
5,795
5,795
3,027
Cruise
Speed
(kts)
12.7
12.7
12.7
12.7
14.2
14.2
21.0
21.0
13.0
20.2
28.5
20.4
20.9
22.0
21.1
20.1
20.1
24.0
24.0
21.2
18.0
18.6
20.9
16.3
20.0
17.5
18.0
20.8
19.7
19.5
15.5
17.0
21.0
16.0
15.0
16.9
18.9
18.9
17.9
24.0
24.0
25.0
25.0
25.0
16.8
DWT
6,083
6,083
15,795
15,795
8,840
8,840
16,605
16,605
7,311
5,976
15,521
6,197
7,345
10,924
7,717
6,235
6,235
11,511
11,511
6,981
13,960
12,564
7,443
5,646
11,632
7,619
7,267
13,138
10,986
10,562
6,641
11,338
31,508
8,389
4,695
14,293
22,146
42,867
30,321
36,827
36,827
16,144
22,501
18,687
17,910
3-17
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Regulatory Impact Analysis
Table 3-1 Bins and Average Ship Characteristics for Deep Sea Ports (continued)
Ship Type
TANKER
Main
Engine a
MSB
DWT Range
<30,000
30,000 - 60,000
60,000 - 90,000
90,000 - 120,000
MSB Total
SSB
<30,000
30,000 - 60,000
60,000 - 90,000
90,000 - 120,000
120,000-150,000
> 150,000
SSB Total
GT-EB
30,000 - 60,000
GT-EB Total
ST
< 30,000
30,000 - 60,000
60,000 - 90,000
90,000 - 120,000
120,000-150,000
> 150,000
ST Total
TANKER Total
TUG
MSB
All
MSB Total
TUG Total
Grand Total
Calls
650
181
148
3
981
3,050
3,752
1,766
2,835
258
487
12,147
13
13
2
87
73
4
3
2
170
13,310
48
48
48
55,672
Engine Power (kW)
Main
4,888
10,533
9,782
15,139
6,697
6,303
9,021
10,310
12,318
15,840
16,888
9,755
7,592
7,592
13,534
15,818
26,848
17,660
19,125
20,785
20,678
9,667
7,579
7,579
7,579
15,212
Auxiliary
1,031
2,222
2,064
3,194
1,413
1,330
1,903
2,175
2,599
3,342
3,563
2,058
1,602
1,602
2,856
3,338
5,665
3,726
4,035
4,386
4,363
2,040
2,039
2,039
2,039
3,593
Cruise
Speed
(kts)
14.3
15.3
14.7
14.1
14.6
14.6
14.9
14.6
14.6
14.7
15.2
14.7
14.5
14.5
18.0
17.9
18.9
16.3
16.0
14.3
18.2
14.8
14.5
14.5
14.5
17.4
DWT
11,415
42,153
74,245
113,957
26,847
17,145
41,677
74,595
101,116
144,405
166,394
61,353
39,839
39,839
27,235
43,982
70,108
91,868
122,409
190,111
58,616
58,754
626
626
626
38,083
Note:
a Engine Types: MSB = medium speed engine; SSB = slow speed engine; ST = steam turbine; GT = gas turbine
3-18
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Chapter 3: Emission Inventory
Table 3-2 Bins and Average Ship Characteristics for Great Lake Ports
Ship Type
BULK CARRIER
Main
Engine"
MSD
DWT Range
10,000-20,000
20,000 - 30,000
30,000 - 40,000
MSD Total
SSD
10,000-20,000
20,000 - 30,000
30,000 - 40,000
SSD Total
ST
20,000 - 30,000
ST Total
BULK CARRIER Total
SELF UNLOADING
BULK CARRIER
MSD
10,000 - 20,000
20,000 - 30,000
30,000 - 40,000
> 40,000
MSD Total
SSD
20,000 - 30,000
30,000 - 40,000
SSD Total
ST
< 10,000
10,000-20,000
20,000 - 30,000
ST Total
SELF UNLOADING BULK CARRIER Total
GENERAL CARGO
MSD
< 10,000
10,000 - 20,000
MSD Total
SSD
< 10,000
10,000 - 20,000
20,000 - 30,000
30,000 - 40,000
SSD Total
GENERAL CARGO Total
INTEGRATED
TUG-BARGE
MSD
All
MSD Total
INTEGRATED TUG-BARGE Total
TANKER
MSD
10,000-20,000
MSD Total
SSD
10,000-20,000
SSD Total
TANKER Total
Grand Total
Calls
9
4
11
24
18
208
223
449
23
23
496
5
12
771
67
855
275
122
397
26
93
79
198
1,450
87
6
93
3
7
1
6
17
110
24
24
24
42
42
5
5
47
2,127
Engine Power (kW)
Main
4,413
8,826
6,001
5,876
4,844
6,995
8,284
7,549
6,910
6,910
7,438
3,114
6,436
6,881
12,140
7,265
6,659
7,574
6,940
3,236
4,750
6,679
5,321
6,910
4,436
5,939
4,533
4,763
6,280
7,099
8,827
6,959
4,908
5,364
5,364
5,364
3,972
3,972
5,160
5,160
4,098
6,850
Auxiliary
980
1,959
1,332
1,305
1,075
1,553
1,839
1,676
1,534
1,534
1,651
691
1,429
1,528
2,695
1,613
1,478
1,681
1,541
718
1,055
1,483
1,181
1,534
847
1,134
866
910
1,199
1,356
1,686
1,329
937
1,443
1,443
1,443
838
838
1,089
1,089
865
1,515
Cruise
Speed
(kts)
15.3
14.0
13.5
14.2
13.6
14.6
14.1
14.3
15.5
15.5
14.4
10.5
15.0
13.2
13.5
13.3
15.0
14.9
14.9
12.3
13.6
16.6
14.6
13.9
15.1
16.5
15.2
16.4
14.1
16.0
15.0
14.9
15.1
13.8
13.8
13.8
13.5
13.5
14.3
14.3
13.6
14.1
DWT
11,693
28,481
32,713
24,125
14,392
27,486
34,172
30,282
26,513
26,513
29,809
12,513
28,591
33,531
65,089
35,812
26,504
34,476
28,954
4,538
16,830
28,847
20,011
31,776
6,755
12,497
7,125
6,708
16,993
24,432
30,900
20,524
9,196
672
672
672
10,475
10,475
13,735
13,735
10,822
29,336
Note:
a Engine Types: MSD = medium speed engine; SSD = slow speed engine; ST = steam turbine
3-19
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Regulatory Impact Analysis
3.3.2.3.1.2 Removal of Category 1 and 2 Ships
Since these inventories were intended to cover ships with Category 3 propulsion engines
only, the ships with Category 1 and 2 propulsion engines were eliminated. This was
accomplished by matching all ship calls with information from Lloyd's Data, which is produced
by Lloyd's Register-F airplay Ltd.14 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 Guide15 and displacement per cylinder was calculated.
Ships with Category 1 or 2 propulsion engines were eliminated from the data.
Many passenger ships and tankers have either diesel-electric or gas turbine-electric
engines that are used for both propulsion and auxiliary purposes. Both were included in the
current inventory.
3.3.2.3.1.3 Treatment of Electric-Drive Ships
Many passenger ships and tankers have either diesel-electric or gas turbine-electric
engines that are used for both propulsion and auxiliary purposes. Both were included in the
current inventory.
Lloyds clearly calls out these types of engines in their database and that information was
used to distinguish them from direct and geared drive systems. Generally the power Lloyds lists
is the total power. To separate out propulsion from auxiliary power for purposes of calculating
emissions, the total power listed in the Lloyds data was divided by 1 plus the ratio of auxiliary to
propulsion power (given in Table 3-3) to obtain the propulsion power portion of the total. The
remaining portion was considered auxiliary engine power. In addition, no low load adjustment
factor was applied to diesel and gas turbine electric engines for loads below 20 percent MCR
because several engines are used to generate power, and some can be shut down to allow others
to operate at a more efficient setting.
3.3.2.3.2 Cruise Distance
Cruise mode emissions are calculated assuming a 25 nautical mile distance into and out
of the port for deep sea ports and 7 nautical miles into and out of the port for Great Lake ports
outside of the reduced speed and maneuvering zones.
3.3.2.3.3 RSZ Distances and Speeds by Port
Reduced speed zone (RSZ) distance and speed were determined for each port. For deep
sea ports, the RSZ distances were developed from shipping lane information contained in the
U.S. Army Corps of Engineers National Waterway Network.16 The NWN is a geographic
database of navigable waterways in and around the U.S. The database defines waterways as
links or line segments that, for the purposes of this study, represent actual shipping lanes (i.e.,
channels, intracoastal waterways, sea lanes, and rivers). The geographic locations of the
waterways that were directly associated with each of the 117 ports were viewed using geographic
3-20
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Chapter 3: Emission Inventory
information system computer software. The sea-side endpoint for the RSZ was selected as the
point along the line segment that was judged to be far enough into the ocean where ship
movements were unconstrained by the coastline or other vessel traffic. These RSZ sea-side
endpoints typically coincided with estimates provided by the pilots for the major ports as
reported in earlier work. The resulting RSZ distance was then measured for each deep sea port.
The final RSZ distances and endpoints for each port are listed in the Appendix, Table 3-103.
The RSZ for each Great Lake port was fixed at three nautical miles, as previously discussed in
Section 3.3.2.2.2.
The RSZ speeds were primarily taken from previous studies by ICF17'18 or from an
ENVIRON report19 based upon discussions with pilots. A few of the RSZ speeds were also
modified based upon newer information obtained from conversations with pilots. The final RSZ
speeds for each port are listed in the Appendix, Table 3-103. 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.
3.3.2.3.4 Auxiliary Engine Power and Load Factors
Since hotelling emissions are a large part of port inventories, it is important to distinguish
propulsion engine emissions from auxiliary engine emissions. 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.20 Average auxiliary engine power to
propulsion power ratios were estimated by ship type and are presented in Table 3-3. These ratios
by ship type were applied to the propulsion power data to derive auxiliary power for the ship
types at each port.
3-21
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Regulatory Impact Analysis
Table 3-3 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.
Load factors for auxiliary engines vary by ship type and operating mode. It was
previously thought that power generation was provided by propulsion engines in all modes but
hotelling. Starcrest's Vessel Boarding Program12 showed that auxiliary engines are on all of the
time, except when using shoreside power during hotelling. Table 3-4 shows the auxiliary engine
load factors by ship type determined by Starcrest, through interviews conducted with ship
captains, chief engineers, and pilots during its vessel boarding programs. Auxiliary load factors
were used in conjunction with total auxiliary power. Auxiliary load factors listed in Table 3-4
are used together with the total auxiliary engine power (determined from total propulsion power
and the ratios from Table 3-3) to calculate auxiliary engine emissions.
3-22
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Chapter 3: Emission Inventory
Table 3-4 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
3.3.2.3.5 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.5 MDO
and MGO are generally described as distillate fuels. 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 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.
An ARB survey20 found that almost all ships used RM in their main propulsion engines,
and that only 29 percent of all ships (except passenger ships) used distillate in their auxiliary
engines, with the remaining 71 percent using RM. However, only 8 percent of passenger ships
used distillate in their auxiliary engines, while the other 92 percent used RM. We used the
results of this survey as reasonable approximations for calculations of emission factors.
However, their accuracy for years other than those of the ARB survey may be affected by fuel
prices, since as fuel prices increase, more ships will use RM in their auxiliary engines.
Based on the ARB survey, average fuel sulfur level for residual marine was set to 2.5
percent for the west coast and 2.7 percent for the rest of the country. A sulfur content of 1.5
percent was used for MDO.21 While a more realistic value for MDO used in the U.S. appears to
be 0.4 percent, given the small proportion of distillate fuel used by ships relative to RM, the
difference should not be significant. Sulfur levels in other areas of the world can be significantly
higher for RM. Table 3-5 provides the assumed mix of fuel types used for propulsion and
auxiliary engines by ship type.
3-23
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Regulatory Impact Analysis
Table 3-5 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
3.3.2.3.6 Propulsion and Auxiliary Engine Emission Factors
21
An analysis of emission data was prepared and published in 2002 by Entec. The
resulting Entec emission factors include individual factors for three speeds of diesel engines
(slow-speed diesel (SSD), medium-speed diesel (MSD), and high-speed diesel (HSD)), steam
turbines (ST), gas turbines (GT), and two types of fuel used here (RM and MDO). Table 3-6
lists the propulsion engine emission factors for NOx and HC that were used for the 2002 port
inventory development. The CO, PM, SO2 and CO2 emission factors shown in the table come
from other data sources as explained below.
Table 3-6 Emission Factors for OGV Main Engines using RM, g/kWh
Engine
SSD
MSD
ST
GT
All Ports
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
C02
620.62
668.36
970.71
970.71
West Coast Ports
PM10
1.4
1.4
1.4
1.4
PM25
1.3
1.3
1.3
1.3
S02
9.53
10.26
14.91
14.91
Other Ports
PM10
1.4
1.4
1.5
1.5
PM25
1.3
1.3
1.4
1.4
S02
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 EPA review.
22
values were determined by EPA based on existing engine test data in consultation
with ARB.23 GT PMio emission factors were not part of the EPA 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).24 The equation used to generate
emission factors based on sulfur content is shown below.
Equation 3-21 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
3-24
-------
Chapter 3: Emission Inventory
= 0.23 g/kW-hr for distillate fuel, 1.35 g/kW-hr for residual fuel
SACI= Actual fuel sulfur level (weight percent)
SNom= nominal fuel sulfur level (weight percent)
= 0.24 for distillate fuel, 2.46 for residual fuel
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
The PMio to PM2.5 conversion factor used here is 0.92. While the 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.
SC>2 emission factors were based upon a fuel sulfur to SC>2 conversion formula which was
supplied by ENVIRON.25 Emission factors for SC>2 emissions were calculated using the formula
assuming that 97.753 percent of the fuel sulfur was converted to 862.26 The brake specific fuel
consumption (BSFC)A that was used for SSDs was 195 g/kWh, while the BSFC that was used
for MSDs was 210 g/kWh based upon Lloyds 1995. The BSFC that was used for STs and GTs
was 305 g/kWh based upon Entec.21
Equation 3-22 Calculation of SO2 Emission Factors, g/kWh
SO2 EF = BSFC x 2 x 0.97753 x Fuel Sulfur Fraction
CC>2 emission factors were calculated from the BSFC assuming a fuel carbon content of
86.7 percent by weight21 and a ratio of molecular weights of CO2 and C at 3.667.
Equation 3-23 Calculation of CO2 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. 3.183
tons of CC>2 emissions are assumed produced from one metric ton of fuel.
The most current set of auxiliary engine emission factors comes from Entec except as
noted below. Table 3-7 provides these auxiliary engine emission factors.
Table 3-7 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
CO2
668.36
668.36
West Coast Ports
PM10
1.4
0.6
PM25
1.3
0.55
SO2
10.26
6.16
Other Ports
PM10
1.4
0.6
PM25
1.3
0.55
SO2
11.09
6.16
1 Brake specific fuel consumption is sometimes called specific fuel oil consumption (SFOC).
3-25
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Regulatory Impact Analysis
It should be noted that Entec used 2.7 percent fuel sulfur content for RM, and 1.0 percent
for MDO which is consistent with the RM assumptions made in this analysis for other than West
Coast ports. For MDO, there is a slight discrepancy between the 1.0 percent used by Entec
versus the 1.5 percent estimate used for this analysis. SC>2 emission factors were calculated
based upon the assumed sulfur levels and the methodology suggested by ENVIRON25 while PM
emissions were determined by EPA based on existing engine test data in consultation with
ARE.
23
20
Using the ratios of RM versus MDO use determined by the ARB study " as given in
Table 3-5 together with the emission factors shown in Table 3-7, the auxiliary engine emission
factor averages by ship type are listed in Table 3-8. As discussed above, this fuel sulfur level
may be too high for the U.S. However, we do not believe this emission factor has a significant
effect on the total emission inventory estimates.
If the fuel sulfur level for MDO is correctly adjusted from 1.5 percent to 1.0 percent, the
effect on SO2 emissions is still less than 7 percent, due to the high percentage of RM fuel used in
auxiliary engines. The difference for PM is within the round off error of the emission factor.
Table 3-8 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
CO2
668.36
668.36
West Coast Ports
PM10
1.3
1.1
PM25
1.2
1.0
SO2
9.93
9.07
Other Ports
PM10
1.4
1.2
PM25
1.3
1.1
SO2
10.70
9.66
3.3.2.3.7 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 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 engine power) as load decreases.
Energy and Environmental Analysis Inc. (EEA) demonstrated this effect in a study prepared for
EPA in 2000.27 In the EEA report, various equations have been developed for the various
emissions. The low-load emission factor adjustment factors were developed based upon the
concept that the BSFC increases as load decreases below about 20 percent load. For fuel
consumption, EEA developed the following equation:
Equation 3-24
Fuel Consumption (g/kWh) = 14.1205 (I/Fractional Load)
205.7169
In addition, based upon test data, they developed algorithms to calculate emission factors
at reduced load. These equations are noted below:
3-26
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Chapter 3: Emission Inventory
Equation 3-25
Emission Rate (g/kWh) = a (Fractional Load)"x + b
For SO2 emissions, however, EEA developed a slightly different equation:
Equation 3-26
Emission Rate (g/kWh) = a (Fuel Consumption x Fuel Sulfur Fraction) + b
The coefficients for the above equations are given in Table 3-9 below.
Table 3-9 Emission Factor Algorithm Coefficients for OGV Main Engines using RM
Coefficient
a
X
b
NOX
0.1255
1.5
10.4496
HC
0.0667
1.5
0.3859
CO
0.8378
1.0
0.1548
PM
0.0059
1.5
0.2551
S02
2.3735
n/a
-0.4792
C02
44.1
1.0
648.6
The underlying database used to calculate these coefficients includes primarily tests on
engines rated below 10,000 kW, using diesel fuel. This introduces uncertainty regarding the use
of these coefficients for Category 3 engines using residual fuel; however, these are the best
estimates currently available.
Using these algorithms, fuel consumption and emission factors versus load were
calculated. By normalizing these emission factors to 20% load, the low-load multiplicative
adjustment factors presented in Table 3-10 are calculated. 862 adjustment factors were
calculated using 2.7% sulfur. The SC>2 multiplicative adjustment factors at 2.5 percent sulfur are
not significantly different.
3-27
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Regulatory Impact Analysis
Table 3-10 Calculated Low Load Multiplicative Adjustment Factors
Load (%)
1
2
o
5
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
S02
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
C02
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
There is no need for a low load adjustment factor for auxiliary engines, because they are
generally operated in banks. When only low loads are needed, one or more engines are shut off,
allowing the remaining engines to operate at an efficient level.
3.3.2.3.8 Use of Detailed Typical Port Data for Other Inputs
There is currently not enough information to readily calculate time-in-mode (hours/call)
for all 117 ports during the maneuvering and hotelling modes of operation. As a result, it was
necessary to review and select available detailed emission inventories that have been estimated
for selected ports to date. These ports are referred to as typical ports. The typical port
information for maneuvering and hotelling time-in-mode (as well as maneuvering load factors
for the propulsion engines) was then used for the typical ports and also assigned to the other
modeled ports. A modeled port is the port in which emissions are to be estimated. The
methodology that was used to select the typical ports and match these ports to the other modeled
ports is briefly described in this section, and more fully described in the ICF documentation.2
3.3.2.3.8.1 Selection of Typical Ports
In 1999, EPA published two guidance documents17'18 to calculate marine vessel activity
at ports. These documents contained detailed port inventories of eight deep sea ports, two Great
3-28
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Chapter 3: Emission Inventory
Lake ports and two inland river ports. The detailed inventories were developed by obtaining ship
call data from Marine Exchanges/Port Authorities (MEPA) at the various ports for 1996 and
matching the various ship calls to data from Lloyds Maritime Information Services to provide
ship characteristics. The ports for which detailed inventories were developed are shown in Table
3-11 for deep sea ports and Table 3-12 for Great Lake ports along with the level of detail of
shifts for each port. Most ports provided the ship name, Lloyd's number, the vessel type, the
date and time the vessel entered and left the port, and the vessel flag. Inland river ports were
developed from U.S. Army Corps of Engineers (USAGE) Waterborne Commerce Statistics
Center data.
Table 3-11 Deep Sea MEPA Vessel Movement and Shifting Details
MEPA Area and Ports
Lower Mississippi River
including the ports of New
Orleans, South Louisiana,
Plaquemines, and Baton Rouge
Consolidated Port of New York
and New Jersey and other ports
on the Hudson and Elizabeth
Rivers
Delaware River Ports including
the ports of Philadelphia,
Camden, Wilmington and others
Puget Sound Area Ports including
the ports of Seattle, Tacoma,
Olympia, Bellingham, Anacortes,
and Grays Harbor
The Port of Corpus Christi, TX
The Port of Coos Bay, OR
Patapsco River Ports including
the port of Baltimore Harbor, MD
The Port of Tampa, FL
MEPA Data Includes
Information on the first and last pier/wharf/dock (PWD) for the
vessel (gives information for at most one shift per vessel). No
information on intermediate PWDs, the time of arrival at the first
destination PWD, or the time of departure from the River.
All PWDs or anchorages for shifting are named. Shifting arrival
and departure times are not given. Hotelling time is based upon the
entrance and clearance times and dates, subtracting out
maneuvering times. Maneuvering times were calculated based
upon the distance the ship traveled at a given maneuvering speed.
All PWDs or anchorages for shifting are named. Shifting arrival
and departure times are not given. Hotelling time is based upon the
entrance and clearance times and dates, subtracting out
maneuvering times. Maneuvering times were calculated based
upon the distance the ship traveled at a given maneuvering speed.
All PWDs or anchorages for shifting are named. Arrival and
departure dates and times are noted for all movements, allowing
calculation of maneuvering and hotelling both for individual shifts
and the overall call on port.
Only has information on destination PWD and date and time in
and out of the port area. No shifting details.
Only has information on destination PWD and date and time in
and out of the port area. No shifting details.
All PWDs or anchorages for shifting are named. Shifting arrival
and departure times are not given. Hotelling time is based upon the
entrance and clearance times and dates, subtracting out
maneuvering times. Maneuvering times were calculated based
upon the distance the ship traveled at a given maneuvering speed.
All PWDs or anchorages for shifting are named. Arrival and
departure dates and times are noted for all movements, allowing
calculation of maneuvering and hotelling both for individual shifts
and the overall call.
3-29
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Regulatory Impact Analysis
Table 3-12 Great Lake MEPA movements and shifts
MEPA Area and Ports
Port of Cleveland, OH
Port of Burns Harbor, IN
MEPA Data Includes
Information on the first and last PWD for the vessel (gives
information for at most one shift per vessel). No information on
intermediate PWDs..
No shifting details, No PWDs listed..
Since 1999, several new detailed emissions inventories have been developed and were
reviewed for use as additional or replacement typical ports: These included:
• Port of Los Angeles12'28
• Puget Sound Ports29
• Port of New York/New Jersey30
• Port ofHouston/Galveston31
• Port of Beaumont/Port Arthur32
• Port of Corpus Christi33
• Port of Portland34
• Ports of Cleveland, OH and Duluth-Superior, MN&WI35
Based on the review of these newer studies, some of the previous typical ports were
replaced with newer data and an additional typical port was added. Data developed for
Cleveland and Duluth-Superior for LADCO was used in lieu of the previous typical port data for
Cleveland and Burns Harbor because it provided more detailed information and better engine
category definitions. The Port ofHouston/Galveston inventory provided enough data to add an
additional typical port. All three port inventories were adjusted to reflect the current
methodology used in this study.
The information provided in the current inventory for Puget Sound Ports29 was used to
calculate RSZ speeds, load factors, and times for all Puget Sound ports. As described in Section
3.3.2.4.2, an additional modeled port was also added to account for the considerable amount of
Jones Act tanker ship activity in the Puget Sound area that is not contained in the original
inventory.
The newer Port of New York/New Jersey inventory provided a check against estimates
made using the 1996 data. All other new inventory information was found to lack sufficient
detail to prepare the detailed typical port inventories needed for this project.
The final list of nine deep sea and two Great Lake typical ports used in this analysis and
their data year is as follows:
3-30
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Chapter 3: Emission Inventory
• Lower Mississippi River Ports [1996]
• Consolidated Ports of New York and New Jersey and Hudson River [1996]
• Delaware River Ports [1996]
• Puget Sound Area Ports [1996]
• Corpus Christi, TX [1996]
• Houston/Galveston Area Ports [1997]
• Ports on the Patapsco River [1996]
• Port of Coos Bay, OR [1996]
• Port of Tampa, FL [ 1996]
• Port of Cleveland, OH on Lake Erie [2005]
• Duluth-Superior, MN & WI on Lake Michigan [2005]
The maneuvering and hotelling time-in-modes, as well as the maneuvering load factors
for these typical ports, were binned by ship type, engine type, and DWT type, using the same
bins described in Section 3.3.2.3.1.1.
3.3.2.3.8.2 Matching Typical Ports to Modeled Ports
The next step in the process was to match the ports to be modeled with the typical port
which was most like it. Three criteria were used for matching a given port to a typical port:
regional differences,8 maximum vessel draft, and the ship types that call on a specific port. One
container port, for instance, may have much smaller bulk cargo and reefer ships number of calls
on that port than another. Using these three criteria and the eleven typical ports that are suitable
for port matching, the 89 deep sea ports and 28 Great Lake ports were matched to the typical
ports. For a typical port, the modeled and typical port is the same (i.e., the port simply represents
itself). For California ports, we used data provided by ARB as discussed in Section 3.3.2.4. The
matched ports for the deep sea ports are provided in Table 3-13.
Table 3-13 Matched Ports for the Deep Sea Ports
Modeled Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Typical Like Port
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
B The region in which a port was located was used to group top ports as it was considered a primary influence on the
characteristics (size and installed power) of the vessels calling at those ports.
3-31
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Regulatory Impact Analysis
Modeled Port Name
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Typical Like Port
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Coos Bay
Coos Bay
Coos Bay
Coos Bay
Coos Bay
Coos Bay
Houston
Houston
Houston
Houston
Houston
Houston
Corpus Christi
Corpus Christi
Corpus Christi
Tampa
Tampa
Tampa
Tampa
Tampa
Tampa
Tampa
Tampa
Tampa
Lower Mississippi
Lower Mississippi
Lower Mississippi
Lower Mississippi
New York/New Jersey
New York/New Jersey
New York/New Jersey
Delaware River
Delaware River
3-32
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Chapter 3: Emission Inventory
Modeled Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Typical Like Port
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Delaware River
Patapsco River
Patapsco River
Patapsco River
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
ARE Supplied
3-33
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Regulatory Impact Analysis
Great Lake ports were matched to either Cleveland or Duluth as shown in Table 3-14.
Table 3-14 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
Once a modeled port was matched to a typical port, the maneuvering and hotelling time-
in-mode values, as well as the maneuvering load factors by bin for the typical ports, were used
directly for the modeled ports, with no adjustments. The other inputs used for both the typical
and modeled ports are as described in Section 3.3.2.3.
3-34
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Chapter 3: Emission Inventory
3.3.2.3.8.3 Bin Mismatches
In some cases, the specific DWT range bin at the modeled port was not in the typical like
port data. In those cases, the next nearest DWT range bin was used for the calculations. In a few
cases, the engine type for a given ship type might not be in the typical like port data. In these
cases, the closest engine type at the typical like port was used. Also in a few cases, a specific
ship type in the modeled port data was not in the typical like port data. In this case, the nearest
like ship type at the typical port was chosen to calculate emissions at the modeled port.
3.3.2.4 Stand Alone Ports
In a few cases, the USAGE entrances and clearances data was not used to calculate
emissions at the modeled port. These include the California ports for which we received data
from ARB, the Port of Valdez, Alaska, and a conglomerate port within the Puget Sound area, as
described below.
3.3.2.4.1 California Ports
The California Air Resources Board (ARB) supplied inventories for 14 California ports
for 2002. The data received from ARB for the California ports were modified to provide
consistent PM and SC>2 emissions to those calculated in this report. In addition, cruise and RSZ
emissions were calculated directly based upon average ship power provided in the ARB
methodology document36 and number of calls, because ARB did not calculate cruise emissions,
and transit (RSZ) emissions were allocated to counties instead of ports. ARB provided transit
distances for each port to calculate the RSZ emissions. Ship propulsion and auxiliary engine
power were calculated based upon the methodology in Section 3.3.2.3.1.3 for use in computing
cruise and RSZ emissions. For maneuvering and hotelling emissions, the ARB values were used
and adjusted as discussed below. The data supplied by ARB included domestic traffic as well as
foreign cargo traffic.
For PM emission calculations, ARB used an emission factor of 1.5 g/kWh to calculate
total PM emissions and factors of 0.96 and 0.937 to convert total PM to PMio and PM2.5
respectively. Since an emission factor of 1.4 g/kWh was used in our calculations for PMio and
an emission factor of 1.3 g/kWh for PM2.5, ARB PMio and PM2.5 emissions were multiplied by
factors of 0.972 and 0.925, respectively to get consistent PMio and PM2.s emissions for
propulsion engines.
For auxiliary engines, ARB used the same emission factors as above, while we used
PMio and PM2.s emission factors of 1.3 and 1.2 g/kWh, respectively for passenger ships and 1.1
and 1.0 g/kWh, respectively for all other ships. In the ARB inventory, all passenger ships are
treated as electric drive and all emissions are allocated to auxiliary engines. ARB auxiliary
engine emissions were thus multiplied by factors of 0.903 and 0.854 respectively for passenger
ships and 0.764 and 0.711 respectively for other ships to provide consistent PM emission
calculations.
3-35
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Regulatory Impact Analysis
SO2 emissions were also different between the ARB and these analyses. ARB used a
composite0 propulsion engine SC>2 emission factor of 10.55 g/kWh while we used a composite
SC>2 emission factor of 9.57 g/kWh. Thus, ARB SC>2 propulsion emissions were multiplied by a
factor of 0.907 to be consistent with our emission calculations. For auxiliary engines, ARB used
SC>2 emission factors of 11.48 and 9.34 g/kWh, respectively for passenger and other ships, while
we use emission factors of 9.93 and 9.07 g/kWh, respectively. Thus, ARB auxiliary SC>2
emissions were multiplied by factors of 0.865 and 0.971, respectively for passenger and other
ships to provide consistent SC>2 emissions.
3.3.2.4.2 Port in Puget Sound
In the newest Puget Sound inventory29, it was found that a considerable amount of tanker
ships stop at Cherry Point, Ferndale, March Point and other areas which are not within the top 89
U.S. deep sea ports analyzed in this analysis. In addition, since they are ships carrying U.S.
cargo (oil from Alaska) from one U.S. port to another, they are not documented in the USAGE
entrances and clearances data. To compensate for this anomaly, an additional port was added
which encompassed these tanker ships stopping within the Puget Sound area but not at one of the
Puget Sound ports analyzed in this analysis. Ship calls in the 1996 typical port data to ports
other than those in the top 89 U.S. deep sea ports were analyzed separately. There were 363 ship
calls by tankers to those areas in 1996. In the inventory report for 2005, there were 468 calls.
For 2002, it was estimated there were 432 calls. The same ship types and ship characteristics
were used as in the 1996 data, but the number of calls was proportionally increased to 432 calls
to represent these ships. The location of the "Other Puget Sound" port was approximately at
Cherry Point near Aberdeen.
3.3.2.4.3 PortofValdez
In a recent Alaska port inventory,37 it was found that significant Category 3 domestic
tanker traffic enters and leaves the Port of Valdez on destination to West Coast ports. Since the
USAGE entrances and clearances data did not contain any tanker calls at Valdez in 2002, the
recent Alaska inventory data was used to calculate emissions at that port. In this case, the
number of calls and ship characteristics for 2002 were taken directly from the Alaska inventory
and used in determining emissions for the modeled port with the Puget Sound area typical port
being used as the like port.
3.3.2.5 Domestic Traffic
One of the concerns with using USAGE entrances and clearances data is that it only
contains foreign cargo movements moved by either a foreign flag vessel or a U.S. flag vessel.
The Maritime Administration (MARAD) maintains the Foreign Traffic Vessel Entrances and
Clearances database, which contains statistics on U.S. foreign maritime trade. Data are compiled
during the regular processing of statistics on foreign imports and exports. The database contains
information on the type of vessel, commodities, weight, customs districts and ports, and origins
and destinations of goods. Thus domestic traffic, i.e., U.S. ships delivering cargo from one U.S.
c Based upon ARB assuming 95 percent of the engines were SSD and 5 percent were MSD. The composite SO2 EF
of 9.57 g/kW-hr was calculated using this weighting, along with the SSD and MSD SO2 EFs for the West Coast
ports reported in Table 3-6.
3-36
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Chapter 3: Emission Inventory
port to another U.S. port, is covered under the Jones Act and is not accounted for in the database.
However, U.S. flagged ships carrying cargo from a foreign port to a U.S. port or from a U.S. port
to a foreign port are accounted for in the USAGE entrances and clearances database, as these are
considered foreign cargo movements.
Under the Jones Act, domestic cargo movements from one U.S. port to another U.S. port
must be carried by a U.S. flag ship. The Jones Act also requires ships traveling between United
States ports to be constructed by United States companies and owned by a United States
company or citizen. Members of the ships' crews must be United States citizens or legal aliens.
Because of the use of USAGE data, in the present baseline and future year inventories, only
limited Jones Act ships were counted. These ships included those servicing California ports,
those serving the Port of Valdez and those serving other Puget Sound ports. At all other ports,
Jones Act ships were not counted.
ICF conducted an analysis to estimate the amount of Category 3 Jones Act ships calling
at the 117 U.S. ports. This was done by analyzing marine exchange data obtained from port
authorities for eleven typical ports and using this information to estimate the Jones Act ship
contribution for the remaining ports. Based on this limited analysis, Jones Act ships are
estimated to account for 9.2% of the total installed power calling on U.S. ports. Approximately
30% of these ships, largely in the Alaska and Pacific regions, have been included in the 2002
baseline inventory. Based on this analysis, Jones Act ships excluded from this inventory
constitute roughly 6.5% of total installed power.38 This results in an underestimation of the port
ship inventory and therefore the benefits of the coordinated program reported in this chapter are
also underestimated.
3.3.2.6 2002 Near Port Inventories
This section presents a summary of the baseline near port inventories for 2002.
Individual port inventories are presented separately for deep sea ports and Great Lake ports
because of the difference in ship types between the two. This is followed by totals for the
summed port inventories, provided by engine type (propulsion and auxiliary), mode of operation,
and ship type.
3.3.2.6.1 Deep Sea Ports
Emission inventories for the 89 deep sea ports are presented here. Total emissions
(propulsion and auxiliary) by ports are given in Table 3-15. Auxiliary only emissions by ports
are given in Table 3-16. Emissions by mode are given in Table 3-17 for cruise, Table 3-18 for
reduced speed zone, Table 3-19 for maneuvering, and Table 3-20 for hotelling. Emissions by
ship type by port are given in Table 3-21 through Table 3-31. Ports that are missing from those
lists had no emissions related to that ship type during 2002.
For deep sea ports, auxiliary emissions are responsible for roughly 47% of the NOx and
PM emissions, primarily due to emissions during the hotelling mode. Container and Tanker
ships combined are responsible for approximately half the total emissions, followed by
Passenger ships and Bulk Carrier ships.
3-37
-------
Regulatory Impact Analysis
3.3.2.6.2 Great Lake Ports
Emissions inventories for 28 Great Lake ports were developed and are presented here.
Great Lake ships include self-unloading bulk carriers (Bulk Carrier, SU) which tend to operate
within the Great Lakes only. Other ships travel down the St. Lawrence River from the open
ocean. Integrated tug-barges (ITB) are also used on the Great Lakes.
Total emissions by port for Great Lakes Ports are shown in Table 3-32. Auxiliary engine
emissions for Great Lake ports are shown in Table 3-33. Emissions by mode for Great Lake
ports are shown in Table 3-34 for cruise, Table 3-35 for reduced speed zone, Table 3-36 for
maneuvering, and Table 3-37 for hotelling. Emissions by ship type are shown in Table 3-38
through Table 3-42.
3-38
-------
Chapter 3: Emission Inventory
Table 3-15 Total Emissions by Deep Sea Port in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez,AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Installed
Power
(MW)
545
472
186
360
8,037
1,190
1,619
97
556
11,198
26,292
19,130
1,946
6,676
5,678
537
399
4,514
2,323
591
1,110
12,699
7,411
6,572
47,147
3,531
7,382
11,452
6,382
8,200
1,213
3,556
2,903
2,504
662
3,566
351
10,941
38,304
27,575
4,627
18,366
4,230
396
86,980
3,968
609
185
Metric Tonnes
NOX
403
122
82
50
1,268
359
413
56
151
2,307
6,669
5,742
446
343
2,111
221
46
929
474
122
270
2,106
714
1,014
4,625
436
970
1,758
850
1,144
175
607
667
389
70
518
40
1,507
4,287
6,603
1,985
6,428
1,045
103
7,364
722
89
45
PM10
32
10
7
4
116
30
34
4
13
206
573
477
37
37
219
18
4
77
39
10
26
261
92
118
546
52
127
143
80
95
14
51
56
32
6
44
3
129
402
556
160
519
85
9
622
60
7
4
PM2.5
29
9
6
4
102
26
30
4
11
182
513
428
33
33
197
16
3
70
35
9
24
240
85
102
491
47
117
132
74
88
13
46
49
28
5
40
3
109
372
513
148
479
78
8
575
55
7
3
HC
14
4
3
2
47
13
15
2
5
117
265
217
17
11
71
7
2
27
14
4
8
91
25
35
158
17
33
59
35
39
6
20
22
14
2
17
1
50
134
221
63
203
33
4
274
23
3
2
CO
32
10
7
4
102
30
35
4
12
223
551
464
39
27
169
17
4
72
37
9
21
189
54
69
347
37
74
401
239
303
14
48
53
33
6
42
3
121
334
536
155
502
82
9
621
57
7
4
SO2
225
71
46
30
800
210
239
31
89
1,320
3,789
3,211
259
299
1,745
133
27
626
312
83
209
1,972
716
873
4,136
388
986
1,090
594
724
108
414
450
239
44
344
27
988
3,123
4,245
1,223
3,976
658
65
4,620
466
152
211
CO2
15,462
5,034
3,125
2,066
54,385
14,555
16,495
2,047
6,042
90,558
253,190
215,754
17,821
20,789
118,629
8,236
1,810
44,368
22,094
5,884
13,794
83,736
28,422
43,643
183,952
17,342
38,575
70,240
38,409
46,155
7,057
26,382
28,904
15,827
2,789
22,223
1,726
63,033
198,127
272,794
78,568
257,346
43,258
4,167
296,780
30,836
3,668
1,764
3-39
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Regulatory Impact Analysis
Table 3-15 Total Emissions by Deep Sea Port in 2002 (continued)
Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Port Emissions
Total Port Emissions (short
tons)
Installed
Power
(MW)
2,754
967
3,272
1,467
290
765
721
1,097
5,184
17,801
46,233
1,801
2,277
1,452
4,209
7,644
4,444
4,888
596
13,908
57,415
543
13,290
181
25,197
5,529
37,523
928
3,442
1,685
409
3,334
56,935
50,489
48,762
456
3,956
455
8,255
6,260
1,210
863,191
Metric Tonnes
NOx
965
121
668
196
35
199
174
198
670
3,060
3,809
287
219
247
994
1,684
627
641
86
1,507
7,155
110
1,647
39
6,412
505
3,594
78
537
192
82
319
5,303
4,793
3,022
107
484
138
840
684
332
121,606
134,047
PM10
79
10
55
16
3
16
14
16
54
281
311
23
19
20
82
140
52
53
7
125
650
9
146
3
519
41
289
7
39
14
6
22
389
352
222
8
35
10
68
53
24
10,530
11,608
PM2.5
73
9
50
15
3
15
13
15
50
261
288
22
18
19
76
129
48
49
7
116
602
8
135
3
481
38
267
7
36
13
5
21
357
324
205
7
33
9
63
49
22
9,631
10,616
HC
30
4
22
7
1
6
6
6
22
89
133
9
7
8
34
55
23
22
3
51
218
3
53
1
212
17
126
2
17
6
2
10
166
150
100
3
15
4
25
21
10
4,148
4,572
CO
76
10
54
16
3
16
14
16
53
233
310
22
17
19
83
140
54
52
8
122
551
9
131
3
502
41
291
6
42
15
6
280
417
378
239
8
37
11
65
53
26
10,635
11,723
S02
2,462
94
2,103
411
52
394
656
334
1,297
2,279
4,519
207
162
164
1,625
3,363
1,011
956
206
1,652
5,340
124
1,572
33
3,918
316
2,174
53
309
108
51
190
3,141
2,839
1,638
64
211
81
536
419
192
93,908
103,515
C02
40,563
5,196
26,676
7,648
1,748
8,257
6,878
8,222
26,273
139,768
150,424
12,116
9,869
10,692
41,540
70,523
25,319
26,264
3,333
62,457
322,880
4,769
74,625
1,700
244,560
19,760
137,046
3,639
20,535
7,095
3,486
12,820
213,005
192,430
110,003
4,317
18,361
5,417
36,609
28,356
12,830
4,995,871
5,507,005
3-40
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Chapter 3: Emission Inventory
Table 3-16 Auxiliary Engine Emissions by Deep Sea Port in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Installed
Power
(MW)
115
101
40
73
2,043
260
346
21
111
2,560
5,947
4,305
427
1,411
1,198
158
78
1,251
642
164
235
2,415
1,342
1,645
8,410
640
1,414
2,486
1,347
1,816
260
878
902
535
130
795
87
2,639
9,813
6,376
988
3,988
919
85
20,036
883
129
40
Metric Tonnes
NOX
147
77
21
25
793
172
183
9
42
924
1,472
1,279
182
256
951
99
21
815
412
108
132
873
321
674
1,827
173
418
770
457
423
84
415
491
202
28
277
20
777
3,032
3,426
813
2,969
607
46
3,467
477
42
16
PM10
11
6
2
2
67
13
14
1
3
70
116
97
14
20
72
8
2
64
32
8
10
149
58
89
305
29
78
64
38
35
7
34
41
17
2
23
2
67
277
295
67
246
50
4
294
40
3
1
PM2.5
10
5
1
2
61
12
13
1
3
64
106
88
13
18
66
7
2
58
29
8
9
135
53
75
268
25
71
59
35
32
6
30
35
14
2
20
1
51
256
271
62
226
46
3
270
37
3
1
HC
4
2
1
1
22
5
5
0
1
26
41
35
5
7
26
3
1
23
12
3
4
31
11
24
64
6
15
21
13
12
2
11
13
6
1
8
1
21
84
95
22
82
17
1
96
13
1
0
CO
11
6
2
2
60
13
14
1
3
70
112
97
14
19
72
8
2
64
32
8
10
63
24
42
129
12
31
59
35
32
6
31
37
15
2
21
1
59
230
260
62
226
46
3
263
36
3
1
SO2
92
48
13
16
522
108
115
6
26
580
939
802
114
161
596
63
14
529
267
70
83
1,188
461
660
2,352
220
626
514
305
282
56
292
343
131
19
187
14
534
2,158
2,343
543
1,982
406
31
2,343
320
28
11
C02
6,798
3,568
977
1,176
36,366
7,930
8,445
410
1,922
42,675
67,795
59,093
8,402
11,836
43,927
3,683
949
38,048
19,178
5,023
5,623
40,334
14,819
31,135
84,373
8,002
19,301
35,563
21,105
19,529
3,899
19,017
22,448
9,318
1,315
12,772
906
35,735
140,039
158,234
37,544
137,151
28,058
2,111
159,839
22,034
1,960
757
3-41
-------
Regulatory Impact Analysis
Table 3-16 Auxiliary Engine Emissions by Deep Sea Port in 2002 (continued)
Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Auxiliary Emissions
Total Auxiliary Emissions
(short tons)
Installed
Power
(MW)
583
203
701
318
61
164
159
236
1,302
4,916
10,277
379
506
522
1,286
1,803
1,155
1,045
130
3,242
14,504
116
3,100
53
5,924
1,216
8,297
257
772
355
88
1,010
13,007
11,535
10,759
101
866
95
2,164
1,480
259
197,430
Metric Tonnes
NOx
617
74
294
63
17
120
69
118
263
2,486
1,630
188
132
187
579
976
303
333
26
776
5,171
73
1,105
28
1,632
170
1,035
45
193
47
59
177
2,632
2,356
860
59
164
61
483
345
125
57,317
63,181
PM10
51
6
25
5
2
10
6
10
22
225
136
16
11
15
48
81
25
28
2
64
462
6
94
2
137
14
83
4
13
3
4
11
178
160
57
4
11
4
37
25
8
5,052
5,569
PM2.5
47
6
23
5
2
9
5
9
20
209
124
14
10
14
44
74
23
25
2
59
428
6
87
2
126
13
76
4
11
3
4
10
162
145
52
3
10
4
34
23
7
4,597
5,067
HC
17
2
8
2
1
3
2
3
7
68
45
5
4
5
16
27
8
9
1
21
142
2
30
1
45
5
29
1
5
1
2
5
72
65
24
2
5
2
13
9
3
1,615
1,781
CO
47
6
22
5
2
9
5
9
20
187
124
14
10
14
44
74
23
25
2
59
389
6
84
2
52
13
79
3
15
4
5
47
205
184
67
5
13
5
37
27
10
4,306
4,746
S02
412
49
198
42
15
80
46
79
176
1,804
1,093
125
89
125
387
652
202
223
18
516
3,711
49
759
19
1,111
122
691
28
128
32
38
115
1,704
1,525
551
39
109
40
311
224
82
41,232
45,450
C02
28,518
3,421
13,584
2,897
1,035
5,532
3,204
5,436
12,160
113,582
75,271
8,664
6,082
8,625
26,754
45,081
13,982
15,397
1,216
35,693
236,659
3,380
50,846
1,280
75,309
8,063
47,804
2,043
8,706
2,117
2,661
7,955
119,333
106,855
39,102
2,665
7,403
2,754
21,942
15,630
5,673
2,635,436
2,905,071
3-42
-------
Chapter 3: Emission Inventory
Table 3-17 Cruise Emissions by Deep Sea Port in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Installed
Power
(MW)
545
472
186
360
8,037
1,190
1,619
97
556
11,198
26,292
19,130
1,946
6,676
5,678
537
399
4,514
2,323
591
1,110
12,699
7,411
6,572
47,147
3,531
7,382
11,452
6,382
8,200
1,213
3,556
2,903
2,504
662
3,566
351
10,941
38,304
27,575
4,627
18,366
4,230
396
86,980
3,968
609
185
Metric Tonnes
NOX
50
28
9
15
300
72
89
5
27
424
775
622
88
45
197
22
21
108
58
14
32
665
362
283
2,180
184
386
584
266
402
69
148
132
143
35
181
16
539
1,348
1,249
238
961
221
20
3,266
195
31
10
PM10
4
2
1
1
28
6
8
0
2
40
74
59
8
8
24
2
2
14
7
2
4
52
28
23
173
15
30
46
25
33
5
13
11
11
3
15
1
45
131
102
19
75
17
2
261
16
3
1
PM2.5
4
2
1
1
26
6
7
0
2
37
69
55
7
8
22
2
2
13
6
2
4
48
26
22
161
13
28
43
23
30
5
12
10
10
3
14
1
42
121
94
17
70
16
2
242
15
2
1
HC
2
1
0
1
10
2
3
0
1
15
27
22
3
2
7
1
1
4
2
1
1
22
12
9
72
6
13
19
9
13
2
5
4
5
1
6
1
18
45
41
8
32
7
1
108
6
1
0
CO
4
2
1
1
23
6
7
0
2
33
59
49
7
4
15
2
2
9
5
1
3
51
28
22
169
14
30
45
21
31
5
12
10
11
3
15
1
42
104
97
18
74
17
2
253
15
2
1
S02
29
16
6
10
206
45
55
3
17
291
544
428
56
75
202
14
12
109
51
15
34
384
209
175
1,290
108
224
341
195
247
40
95
82
83
20
118
10
341
1,038
761
139
557
128
12
1,940
118
19
6
CO2
1,871
1,039
385
627
13,469
2,949
3,597
184
1,134
19,040
35,599
28,010
3,650
4,904
13,218
934
758
7,278
3,382
984
2,220
23,253
12,624
10,741
78,115
6,521
13,579
20,702
11,811
14,961
2,453
5,765
4,991
5,021
1,240
7,155
635
20,705
62,951
46,164
8,439
33,789
7,766
734
117,641
7,131
1,153
356
3-43
-------
Regulatory Impact Analysis
Table 3-17 Cruise Emissions by Deep Sea Port in 2002 (continued)
Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Cruise Emissions
Toted Cruise Emissions (short
tons)
Installed
Power
(MW)
2,754
967
3,272
1,467
290
765
721
1,097
5,184
17,801
46,233
1,801
2,277
1,452
4,209
7,644
4,444
4,888
596
13,908
57,415
543
13,290
181
25,197
5,529
37,523
928
3,442
1,685
409
3,334
56,935
50,489
48,762
456
3,956
455
8,255
6,260
1,210
863,191
Metric Tonnes
NOx
143
44
166
63
13
41
38
58
222
665
1,702
92
83
58
191
326
178
213
25
571
2,068
27
465
8
1,013
214
1,400
36
171
87
19
137
2,093
1,856
1,676
24
197
23
336
273
63
34,193
37,691
PM10
11
4
13
5
1
3
3
4
17
54
133
7
8
4
15
26
14
17
2
46
173
2
41
1
81
17
110
4
13
7
2
11
168
149
131
2
15
2
30
23
5
2,826
3,115
PM2.5
10
3
12
5
1
3
3
4
16
50
123
7
7
4
14
24
13
16
2
43
161
2
38
1
75
16
102
3
12
6
1
10
156
138
122
2
14
2
28
21
5
2,623
2,891
HC
5
1
5
2
0
1
1
2
7
22
56
3
3
2
6
11
6
7
1
19
70
1
16
0
34
7
46
1
6
3
1
5
69
62
55
1
7
1
11
9
2
1,141
1,258
CO
11
3
13
5
1
3
3
4
17
52
132
7
6
5
15
25
14
16
2
44
161
2
36
1
78
17
108
3
13
7
1
11
162
144
130
2
15
2
26
21
5
2,651
2,922
S02
82
28
97
37
9
23
22
33
129
501
986
54
60
34
113
194
104
125
15
349
1,497
17
340
5
600
125
815
26
92
47
11
74
1,165
1,033
900
13
106
13
217
162
34
21,186
23,353
C02
4,974
1,687
5,887
2,261
540
1,415
1,351
2,007
7,816
30,423
59,738
3,259
3,623
2,073
6,874
11,761
6,283
7,597
891
21,139
90,831
1,018
20,603
331
36,410
7,560
49,371
1,700
6,025
3,068
699
4,862
76,254
67,622
58,866
851
6,936
821
14,243
10,632
2,216
1,314,146
1,448,598
3-44
-------
Chapter 3: Emission Inventory
Table 3-18 Reduced Speed Zone Emissions by Deep Sea Port in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Installed
Power
(MW)
545
472
186
360
8,037
1,190
1,619
97
556
11,198
26,292
19,130
1,946
6,676
5,678
537
399
4,514
2,323
591
1,110
12,699
7,411
6,572
47,147
3,531
7,382
11,452
6,382
8,200
1,213
3,556
2,903
2,504
662
3,566
351
10,941
38,304
27,575
4,627
18,366
4,230
396
86,980
3,968
609
185
Metric Tonnes
NOx
191
3
49
3
75
101
125
43
77
969
4,289
3,685
175
33
963
121
5
27
14
4
117
771
28
101
656
97
181
419
175
352
23
50
78
55
7
68
5
329
71
2,670
1,091
2,897
244
48
881
48
16
22
PM10
15
0
4
0
7
8
10
3
6
86
349
290
14
5
112
10
0
2
1
0
12
81
2
10
57
10
16
33
20
29
2
4
7
5
1
6
0
29
7
224
87
229
19
4
83
4
1
2
PM2.5
14
0
4
0
6
7
9
3
6
79
323
269
13
5
104
9
0
2
1
0
12
75
2
9
53
9
14
31
19
27
1
3
4
3
0
5
0
16
7
208
80
212
18
4
76
4
1
2
HC
6
0
2
0
3
4
5
1
3
58
151
121
7
1
32
4
0
1
0
0
4
45
1
4
22
6
6
14
13
12
1
2
3
3
0
2
0
12
3
98
36
95
8
2
54
2
1
1
CO
15
0
4
0
6
9
11
3
6
108
347
285
16
3
75
10
1
2
1
0
9
88
2
8
50
11
14
293
185
239
2
5
7
6
1
6
0
28
7
227
85
225
19
5
105
4
1
2
S02
103
2
27
2
48
57
70
23
45
539
2,402
2,023
100
46
942
71
3
18
9
2
99
574
18
73
429
71
117
250
124
219
12
27
36
27
4
40
3
159
52
1,678
648
1,712
144
30
547
30
105
196
CO2
6,773
125
1,785
109
3,223
3,800
4,645
1,509
2,924
36,288
157,988
133,271
6,661
3,044
61,929
3,721
123
339
156
47
5,979
29,868
1,016
3,958
24,233
3,760
6,581
15,432
7,805
13,537
879
2,070
3,183
2,117
263
2,788
225
13,321
3,225
103,988
40,082
105,846
8,910
1,845
34,706
1,839
615
781
3-45
-------
Regulatory Impact Analysis
Table 3-18 Reduced Speed Zone Emissions by Deep Sea Port in 2002(continued)
Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total RSZ Emissions
Total RSZ Emissions (short
tons)
Installed
Power
(MW)
2,754
967
3,272
1,467
290
765
721
1,097
5,184
17,801
46,233
1,801
2,277
1,452
4,209
7,644
4,444
4,888
596
13,908
57,415
543
13,290
181
25,197
5,529
37,523
928
3,442
1,685
409
3,334
56,935
50,489
48,762
456
3,956
455
8,255
6,260
1,210
863,191
Metric Tonnes
NOX
245
2
254
86
5
45
82
26
215
73
539
4
5
2
346
505
206
110
44
206
182
11
135
4
4,325
131
1,333
11
183
58
4
8
748
755
524
25
123
58
98
101
156
34,427
3 7,949
PM10
20
0
21
7
0
4
7
2
17
7
44
0
0
0
29
43
17
9
4
17
17
1
13
0
347
11
107
1
14
5
0
1
62
63
43
2
10
5
9
8
12
2,887
3,182
PM2.5
18
0
19
7
0
3
6
2
16
7
41
0
0
0
27
40
16
9
3
16
16
1
12
0
321
10
99
1
13
4
0
1
58
58
40
2
9
4
8
8
11
2,657
2,929
HC
9
0
9
3
0
1
3
1
7
2
22
0
0
0
14
19
10
5
2
8
6
0
6
0
142
5
46
0
6
2
0
0
30
30
23
1
4
2
3
3
5
1,280
1,410
CO
20
0
21
8
0
4
7
2
17
6
50
0
0
0
32
48
20
10
4
19
15
1
13
0
336
11
110
1
14
5
0
256
69
69
53
2
10
4
8
8
12
3,804
4,193
S02
1,996
16
1,841
343
29
295
598
225
1,015
94
2,504
27
14
6
1,208
2,603
747
620
180
820
331
59
514
10
2,596
86
802
8
100
32
2
5
436
440
272
14
67
32
63
61
85
35,148
38,744
C02
9,058
75
9,527
3,292
231
1,671
3,045
971
7,867
3,316
20,265
146
235
98
13,693
19,709
7,996
4,169
1,688
8,030
8,194
442
6,009
158
159,626
4,998
49,492
523
6,591
2,093
165
251
29,056
29,305
18,380
905
4,427
2,088
4,198
4,015
5,586
1,318,897
1,453,835
3-46
-------
Chapter 3: Emission Inventory
Table 3-19 Maneuvering Emissions by Deep Sea Port in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Installed
Power
(MW)
545
472
186
360
8,037
1,190
1,619
97
556
11,198
26,292
19,130
1,946
6,676
5,678
537
399
4,514
2,323
591
1,110
12,699
7,411
6,572
47,147
3,531
7,382
11,452
6,382
8,200
1,213
3,556
2,903
2,504
662
3,566
351
10,941
38,304
27,575
4,627
18,366
4,230
396
86,980
3,968
609
185
Metric Tonnes
NOX
50
25
9
12
360
63
72
3
19
501
980
810
75
55
252
1
1
12
6
1
2
49
23
40
169
17
28
112
54
70
8
27
33
16
4
20
2
66
233
192
35
143
33
3
455
37
3
1
PM10
5
2
1
1
36
6
7
0
2
49
100
81
7
8
29
0
0
1
1
0
0
14
7
12
47
5
8
11
6
7
1
3
3
2
0
2
0
7
24
19
3
14
3
0
46
4
0
0
PM2.5
3
2
1
1
28
4
5
0
1
37
76
62
5
6
22
0
0
1
1
0
0
12
6
5
31
3
7
10
5
6
1
2
3
1
0
2
0
6
23
17
3
12
3
0
42
3
0
0
HC
3
1
1
1
19
4
4
0
1
33
70
57
4
3
13
0
0
1
0
0
0
2
1
1
6
1
1
8
4
5
1
2
2
1
0
1
0
4
12
13
2
10
2
0
36
2
0
0
CO
5
2
1
1
32
6
7
0
2
50
98
82
8
5
25
0
0
1
1
0
0
4
2
3
13
1
2
14
6
8
1
3
4
2
0
2
0
8
23
22
4
18
4
0
54
4
0
0
S02
23
12
4
6
194
31
35
2
10
232
445
368
37
46
163
1
0
8
4
1
1
95
45
38
255
25
59
68
38
44
7
20
25
13
3
18
2
95
163
118
21
87
20
2
265
23
2
1
CO2
1,610
806
301
412
13,248
2,122
2,411
109
666
16,173
30,829
25,644
2,538
3,156
11,182
54
26
557
283
73
90
1,909
898
1,676
6,754
683
1,063
4,385
2,414
2,835
323
1,025
1,301
609
144
829
68
2,637
10,273
7,540
1,371
5,606
1,297
120
17,069
1,472
126
39
3-47
-------
Regulatory Impact Analysis
Table 3-19 Maneuvering Emissions by Deep Sea Port in 2002 (continued)
Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Maneuver Emissions
Total Maneuver Emissions
(short tons)
Installed
Power
(MW)
2,754
967
3,272
1,467
290
765
721
1,097
5,184
17,801
46,233
1,801
2,277
1,452
4,209
7,644
4,444
4,888
596
13,908
57,415
543
13,290
181
25,197
5,529
37,523
928
3,442
1,685
409
3,334
56,935
50,489
48,762
456
3,956
455
8,255
6,260
1,210
863,191
Metric Tonnes
NOx
22
5
24
5
1
5
4
7
25
70
199
11
9
10
27
46
22
24
2
66
241
4
65
1
130
25
164
10
23
9
4
9
272
242
241
3
26
3
80
54
7
7,383
8,138
PM10
2
0
2
1
0
0
0
1
2
7
20
1
1
1
3
4
2
2
0
6
25
0
7
0
13
3
17
1
1
1
0
0
15
13
10
0
2
0
6
4
0
758
835
PM2.5
2
0
2
1
0
0
0
1
2
6
19
1
1
1
2
4
2
2
0
6
23
0
6
0
12
2
15
1
1
1
0
0
13
12
9
0
1
0
6
4
0
625
689
HC
2
0
2
0
0
0
0
0
2
3
17
1
1
1
2
3
2
2
0
5
14
0
4
0
10
2
14
0
1
0
0
0
6
5
5
0
1
0
2
1
0
440
485
CO
3
1
3
1
0
1
0
1
3
6
24
1
1
1
3
6
3
3
0
8
24
0
7
0
15
3
20
1
1
1
0
1
15
13
11
0
2
0
6
4
0
724
799
S02
14
3
15
3
1
3
2
4
15
50
112
7
6
6
17
28
13
14
1
40
164
2
44
1
76
14
91
6
11
4
2
4
120
106
89
1
12
1
46
29
3
4,356
4,802
C02
874
204
953
204
60
196
159
269
974
3,118
7,263
435
388
419
1,090
1,790
861
922
79
2,587
10,379
147
2,812
52
4,931
929
5,936
455
740
287
133
294
8,669
7,687
6,472
83
838
84
3,409
2,105
220
266,262
293,504
3-48
-------
Chapter 3: Emission Inventory
Table 3-20 Hotelling Emissions by Deep Sea Port in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Installed
Power
(MW)
545
472
186
360
8,037
1,190
1,619
97
556
11,198
26,292
19,130
1,946
6,676
5,678
537
399
4,514
2,323
591
1,110
12,699
7,411
6,572
47,147
3,531
7,382
11,452
6,382
8,200
1,213
3,556
2,903
2,504
662
3,566
351
10,941
38,304
27,575
4,627
18,366
4,230
396
86,980
3,968
609
185
Metric Tonnes
NOX
113
66
14
20
533
123
126
5
29
413
625
624
108
210
699
76
20
784
396
103
119
622
301
590
1,621
138
376
643
355
321
74
382
425
175
25
248
17
573
2,634
2,492
621
2,427
547
32
2,762
442
38
13
PM10
9
5
1
2
45
9
10
0
2
31
49
47
8
16
53
6
1
60
30
8
9
114
55
73
269
23
73
53
29
27
6
31
35
15
2
21
1
49
240
211
51
201
45
3
234
37
3
1
PM2.5
8
5
1
1
41
9
9
0
2
29
45
43
7
15
48
5
1
54
27
7
8
105
51
67
246
21
67
49
27
24
6
29
32
13
2
19
1
45
222
194
47
185
42
2
215
34
3
1
HC
3
2
0
1
15
3
3
0
1
11
17
17
3
6
19
2
1
22
11
3
3
22
11
21
57
5
13
18
10
9
2
10
12
5
1
7
0
16
73
69
17
67
15
1
76
12
1
0
CO
9
5
1
2
40
9
10
0
2
31
47
47
8
16
53
6
1
60
30
8
9
46
22
36
115
10
28
49
27
24
6
29
32
13
2
19
1
43
200
189
47
185
42
2
210
34
3
1
S02
71
42
9
12
352
77
79
3
18
259
399
391
67
132
438
47
12
491
248
65
75
919
445
587
2,162
184
585
430
237
214
49
272
307
117
16
168
12
392
1,870
1,688
414
1,620
365
21
1,867
296
26
9
CO2
5,207
3,064
653
918
24,445
5,684
5,842
245
1,319
19,057
28,774
28,829
4,972
9,685
32,299
3,527
903
36,194
18,273
4,780
5,505
28,707
13,884
27,267
74,850
6,379
17,352
29,720
16,379
14,822
3,402
17,521
19,428
8,080
1,141
11,451
797
26,370
121,678
115,102
28,676
112,104
25,286
1,467
127,364
20,394
1,773
589
3-49
-------
Regulatory Impact Analysis
Table 3-20 Hotelling Emissions by Deep Sea Port in 2002 (continued)
Port Name
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Hotel Emissions
Toted Hotel Emissions (short
tons)
Installed
Power
(MW)
2,754
967
3,272
1,467
290
765
721
1,097
5,184
17,801
46,233
1,801
2,277
1,452
4,209
7,644
4,444
4,888
596
13,908
57,415
543
13,290
181
25,197
5,529
37,523
928
3,442
1,685
409
3,334
56,935
50,489
48,762
456
3,956
455
8,255
6,260
1,210
863,191
Metric Tonnes
NOx
555
70
223
41
15
108
50
108
208
2,252
1,368
179
122
175
430
807
220
294
15
665
4,665
68
982
25
944
136
698
21
159
37
55
164
2,189
1,941
581
55
137
54
326
257
107
45,603
50,268
PM10
46
6
19
3
2
9
4
9
17
213
114
15
10
15
36
67
18
24
1
55
434
6
85
2
79
11
55
2
10
2
4
11
144
127
37
4
9
3
23
18
7
4,060
4,475
PM2.5
42
5
17
3
2
8
4
8
16
198
105
14
9
13
33
61
17
22
1
51
402
5
78
2
73
10
50
2
9
2
3
10
130
116
34
3
8
3
21
16
6
3,726
4,107
HC
15
2
6
1
1
3
1
3
6
62
38
5
3
5
12
22
6
8
0
18
128
2
27
1
26
4
19
1
4
1
2
5
60
53
16
2
4
1
9
7
3
1,287
1,419
CO
42
5
17
3
2
8
4
8
16
169
104
14
9
13
33
61
17
22
1
51
351
5
74
2
72
10
53
2
13
3
4
13
172
152
46
4
11
4
25
20
8
3,456
3,809
S02
371
47
150
27
13
72
34
72
139
1,634
917
120
82
117
287
539
147
196
10
444
3,348
46
673
17
646
91
466
13
107
25
36
107
1,420
1,259
376
36
92
35
209
167
70
33,218
36,617
C02
25,657
3,230
10,309
1,891
918
4,975
2,323
4,975
9,616
102,912
63,159
8,276
5,623
8,102
19,882
37,262
10,180
13,576
675
30,702
213,476
3,163
45,202
1,160
43,593
6,274
32,248
961
7,178
1,646
2,489
7,413
99,027
87,816
26,285
2,479
6,160
2,424
14,758
11,604
4,808
2,096,566
2,311,068
3-50
-------
Chapter 3: Emission Inventory
Table 3-21 Auto Carrier Deep Sea Port Emissions in 2002
Port Name
Honolulu, HI
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Beaumont, TX
Galveston, TX
Houston, TX
Mobile, AL
Manatee, FL
Matagorda Ship
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
South Louisiana, LA
New York/New Jersey
Morehead City, NC
Chester, PA
Brunswick, GA
Canaveral, FL
Charleston, SC
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Jacksonville, FL
Miami, FL
Boston, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Carquinez, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Richmond, CA
San Diego, CA
San Francisco, CA
Total Auto Carrier
Total Auto Carrier (short tons)
Installed
Power
(MW)
539
6
2,331
9
2,123
278
31
560
1,141
692
4
16
169
284
136
225
16
4,588
35
9
3,350
53
1,922
40
0
111
1,012
4,420
131
744
5,458
270
644
682
2,036
1,068
947
10
468
1,374
20
37,954
Metric Tonnes
NOX
59
1
416
3
733
48
4
59
122
72
0
1
13
24
22
50
3
361
3
2
368
4
182
3
0
16
126
389
10
62
1,290
27
76
84
125
96
87
1
51
131
2
5,125
5,649
PM10
5
0
38
0
61
4
1
6
12
6
0
0
1
2
2
4
0
30
0
0
30
0
15
0
0
1
10
32
1
5
103
2
6
6
9
7
6
0
4
9
0
421
464
PM2.5
5
0
33
0
55
4
1
5
11
6
0
0
1
2
2
4
0
28
0
0
28
0
14
0
0
1
10
29
1
5
95
2
6
6
8
6
6
0
3
9
0
384
424
HC
3
0
21
0
27
2
0
2
4
2
0
0
0
1
1
2
0
15
0
0
12
0
6
0
0
1
5
14
0
2
43
1
3
3
4
3
3
0
2
4
0
185
204
CO
5
0
42
0
59
5
0
4
8
16
0
0
1
2
2
4
0
32
0
0
29
0
14
0
0
1
11
32
1
5
101
2
6
6
157
7
7
0
4
10
0
577
636
S02
35
1
246
2
414
28
4
43
92
47
0
1
8
15
14
32
2
218
2
4
499
3
169
2
0
27
180
362
7
54
768
20
46
49
71
55
50
1
30
77
1
3,676
4,052
CO2
2,397
47
16,911
109
27,690
1,946
195
2,372
5,019
2,993
14
48
520
994
938
2,089
129
13,923
102
65
14,351
153
7,234
133
0
604
5,014
15,430
395
2,495
48,152
1,127
2,898
3,246
4,650
3,681
3,339
42
1,986
5,123
81
198,637
218,960
3-51
-------
Regulatory Impact Analysis
Table 3-22 Barge Carrier Deep Sea Port Emissions in 2002
Port Name
Mobile, AL
New Orleans, LA
Morehead City, NC
Charleston, SC
Total Barge Carrier
Total Barge Carrier (short
tons)
Installed
Power
(MW)
2
472
73
420
967
Metric Tonnes
NOX
0
87
6
55
148
163
PM10
0
8
1
4
13
14
PM2.5
0
7
1
4
12
13
HC
0
3
0
2
5
6
CO
0
8
0
4
12
14
S02
0
57
5
78
141
156
C02
17
3,738
330
2,279
6,364
7,015
3-52
-------
Chapter 3: Emission Inventory
Table 3-23 Bulk Carrier Deep Sea Port Emissions in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Installed
Power
(MW)
67
82
71
140
158
1,007
1,142
73
72
2,351
523
872
1,003
7
52
87
31
34
246
1,055
392
1,063
5,996
890
481
3,359
1,116
2,752
685
120
322
586
79
586
25
3,380
626
8,311
Metric Tonnes
NOX
28
14
33
24
29
233
265
45
22
633
244
445
256
1
22
10
3
4
74
185
35
114
655
106
60
460
147
401
106
21
60
118
13
116
4
604
109
2,511
PM10
2
1
3
2
2
19
22
4
2
51
19
35
21
0
2
1
0
0
6
19
4
11
66
11
6
37
13
32
9
2
5
10
1
9
0
49
9
202
PM2.5
2
1
2
2
2
17
19
3
2
46
18
32
19
0
2
1
0
0
5
16
3
9
54
9
5
34
12
30
8
2
4
9
1
8
0
43
8
187
HC
1
1
1
1
1
8
10
2
1
23
8
15
9
0
1
0
0
0
2
9
1
4
22
4
2
16
6
14
3
1
2
4
0
4
0
20
3
79
CO
2
1
3
2
2
20
22
4
2
53
19
35
22
0
2
1
0
0
6
18
3
8
48
9
4
121
46
115
8
2
5
10
1
9
0
48
9
196
S02
15
9
18
14
17
136
154
24
12
364
135
247
147
1
12
6
2
2
41
129
25
78
446
74
40
278
91
241
65
13
36
71
8
70
3
365
70
1,550
CO2
1,033
599
1,206
974
1,188
9,408
10,659
1,628
848
25,061
9,103
16,617
10,127
59
763
389
125
145
2,609
6,998
1,347
4,285
24,640
4,025
2,221
17,665
5,870
15,258
4,234
834
2,364
4,713
515
4,586
178
23,968
4,652
100,577
3-53
-------
Regulatory Impact Analysis
Table 3-23 Bulk Carrier Deep Sea Port Emissions in 2002 (continued)
Port Name
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Georgetown, SC
Hopewell, VA
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Fall River, MA
New Castle, DE
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Carquinez, CA
Eureka, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Bulk Carrier
Total Bulk Carrier (short tons)
Installed
Power
(MW)
1,668
11,606
2,714
280
3,168
470
408
127
243
130
168
35
127
240
659
511
370
464
1,589
424
83
98
775
473
345
422
11
1,394
122
37
450
2,851
692
1,474
717
114
2,297
2,037
280
437
385
218
350
498
638
82,437
Metric Tonnes
NOX
722
4,014
665
79
482
62
63
30
54
17
38
7
13
51
161
78
75
59
238
55
11
13
176
105
66
68
3
203
16
6
59
1,273
118
334
172
28
468
423
40
103
82
72
64
101
198
19,373
21,355
PM10
58
323
54
6
41
5
5
2
4
1
3
1
2
4
13
6
6
5
19
4
1
1
14
8
5
5
0
17
1
0
5
102
10
27
12
2
33
29
3
7
6
5
4
7
14
1,570
1,731
PM2.5
53
298
50
6
37
5
5
2
4
1
3
1
1
4
12
6
6
4
18
4
1
1
13
8
5
5
0
15
1
0
5
95
9
25
11
2
30
27
3
7
5
5
4
6
13
1,431
7,577
HC
23
127
21
3
16
2
2
1
2
1
1
0
1
2
5
3
2
2
8
2
0
0
6
3
2
2
0
6
1
0
2
41
4
11
5
1
14
13
1
3
2
2
2
3
6
633
697
CO
56
313
52
7
39
5
5
2
4
1
3
1
1
4
13
6
6
5
19
4
1
1
14
8
5
5
0
16
1
0
5
99
9
26
13
2
36
33
3
8
6
6
5
8
15
1,732
1,909
S02
439
2,470
417
49
317
38
116
144
192
13
57
26
30
37
637
154
276
54
449
43
9
10
714
296
215
160
18
337
17
9
90
773
78
205
103
18
283
255
23
61
50
42
39
61
116
14,945
16,474
C02
28,070
159,561
27,385
3,152
20,791
2,458
2,606
1,167
2,146
692
1,522
289
792
2,080
6,326
3,157
2,934
2,453
9,729
2,282
442
547
6,918
4,161
2,611
2,718
117
8,436
653
227
2,652
48,126
4,815
13,237
6,934
1,201
19,185
17,295
1,568
4,155
3,371
2,842
2,638
4,139
7,780
767,825
846,382
3-54
-------
Chapter 3: Emission Inventory
Table 3-24 Container Ship Deep Sea Port Emissions in 2002
Port Name
Everett, WA
Honolulu, HI
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Freeport, TX
Galveston, TX
Houston, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Gulfport, MS
Everglades, FL
New Orleans, LA
South Louisiana, LA
Plaquemines, LA
New York/New Jersey
Morehead City, NC
Chester, PA
Charleston, SC
New Haven, CT
Palm Beach, FL
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Boston, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Carquinez, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Richmond, CA
San Diego, CA
San Francisco, CA
Total Container Ship
Total Container Ship (short
tons)
Installed
Power
(MW)
24
2,190
14
5,227
21,749
15,446
7
1,575
427
13,441
24
36
39
1,538
7,732
5,756
36
12
56,253
24
1,140
37,982
14
752
2,696
1,999
1,779
539
3,997
20,834
5,016
9,224
3,797
28,209
27
55
82
42,292
37,505
47,109
165
385
1,209
378,355
Metric Tonnes
NOx
6
308
2
879
5,230
3,109
4
74
22
698
2
4
4
181
658
788
5
1
3,246
2
139
2,691
1
44
306
197
130
74
279
1,310
325
1,411
251
2,088
3
6
6
3,434
3,097
2,833
15
30
102
33,990
3 7,468
PM10
0
30
0
85
445
264
0
6
2
59
0
0
0
15
56
65
0
0
268
0
11
219
0
4
25
16
11
6
24
107
27
112
20
168
0
0
0
244
221
208
1
2
7
2,733
3,012
PM2.5
0
25
0
74
396
236
0
6
2
55
0
0
0
14
52
60
0
0
248
0
10
202
0
4
23
15
10
6
22
99
25
104
19
156
0
0
0
225
203
192
1
2
7
2,494
2,749
HC
0
15
0
59
218
124
0
2
1
23
0
0
0
7
23
35
0
0
130
0
5
97
0
2
13
8
5
3
11
46
13
49
9
77
0
0
0
109
99
94
0
1
3
1,282
1,413
CO
0
27
0
96
441
253
0
6
2
53
0
1
1
15
53
76
1
0
281
0
11
222
0
3
28
18
12
7
24
105
28
113
20
173
0
0
6
272
247
224
1
2
8
2,833
3,123
S02
3
181
1
486
2,857
1,741
2
46
14
446
1
2
2
110
426
482
3
1
1,934
1
306
3,001
1
32
671
379
162
182
279
961
305
828
148
1,230
2
4
4
1,986
1,791
1,532
8
17
59
22,628
24,944
CO2
210
12,403
78
33,142
191,094
116,552
143
2,679
792
25,617
84
135
155
7,411
27,826
30,940
197
41
122,010
58
5,313
103,968
34
1,861
11,715
7,555
5,115
2,807
11,419
51,282
12,667
51,462
9,311
76,805
105
245
250
134,894
121,601
102,880
571
1,168
4,003
1,288,596
1,420,434
3-55
-------
Regulatory Impact Analysis
Table 3-25 General Cargo Ship Deep Sea Port Emissions in 2002
Port Name
Anacortes, WA
Everett, WA
Grays Harbor, WA
Honolulu, HI
Kalama, WA
Longview, WA
Olympia, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Anchorage, AK
Coos Bay, OR
Hilo, HI
Kahului, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Gulfport, MS
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Georgetown, SC
Hopewell, VA
Marcus Hook, PA
Morehead City, NC
Paulsboro, NJ
Chester, PA
Installed
Power
(MW)
23
58
220
43
116
441
24
390
771
841
264
514
6
4
312
5
7
24
744
238
111
5,806
890
46
188
670
2,529
206
496
301
27
545
466
71
986
1,813
2,925
356
810
178
83
1,841
202
44
39
387
22
237
Metric Tonnes
NOX
5
19
26
6
15
61
11
90
123
261
105
73
1
1
36
1
1
7
113
22
12
560
100
6
20
71
297
23
51
36
2
52
45
7
118
197
601
111
216
29
15
153
26
12
7
40
3
40
PM10
0
2
2
1
1
5
1
7
11
21
9
6
0
0
3
0
0
1
12
2
1
59
11
1
2
7
25
2
4
3
0
4
4
1
10
18
50
10
18
2
1
13
2
1
1
3
0
3
PM2.5
0
1
2
1
1
5
1
7
9
19
8
6
0
0
3
0
0
0
12
2
1
52
9
1
2
6
23
2
4
3
0
4
4
1
9
16
46
9
16
2
1
12
2
1
1
3
0
3
HC
0
1
1
0
1
2
0
3
5
9
4
3
0
0
1
0
0
0
5
1
0
19
4
0
1
3
10
1
2
1
0
2
2
0
4
6
20
4
7
1
1
6
1
0
0
1
0
1
CO
0
1
2
1
1
5
1
7
11
21
8
7
0
0
3
0
0
1
11
2
1
42
9
0
5
22
85
2
4
3
0
4
4
1
9
16
48
9
17
2
1
13
2
1
1
3
0
3
S02
3
11
16
4
8
35
6
49
71
145
61
43
1
1
21
0
0
4
89
16
9
439
77
4
14
49
190
15
32
22
2
33
30
5
75
138
384
73
134
19
10
95
35
42
16
30
2
71
C02
218
764
1,093
294
568
2,376
419
3,291
4,812
9,653
4,096
2,924
39
48
1,421
21
29
247
4,691
845
486
23,458
4,085
232
876
3,150
11,928
949
2,048
1,430
104
2,070
1,915
287
4,784
9,057
24,538
4,624
8,502
1,192
639
5,957
1,062
444
299
1,684
145
1,679
3-56
-------
Chapter 3: Emission Inventory
Table 3-25 General Cargo Ship Deep Sea Port Emissions in 2002 (continued)
Port Name
Fall River, MA
Perm Manor, PA
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Carquinez, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Oakland, CA
Redwood City, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total General Cargo
Toted General Cargo (short
tons)
Installed
Power
(MW)
139
56
32
1,066
549
1,814
382
722
974
960
185
1,178
38
1,419
2,941
3
122
2,275
568
2,521
39
183
77
996
883
462
19
67
202
867
453
202
49,711
Metric Tonnes
NOX
17
12
4
168
61
223
43
76
180
164
28
155
7
152
354
0
14
673
74
415
8
42
7
158
143
43
4
13
58
144
82
55
7,402
8,159
PM10
2
1
0
14
5
18
4
7
15
14
2
13
1
13
31
0
1
56
6
34
1
3
0
11
10
3
0
1
4
10
6
4
630
694
PM2.5
1
1
0
12
5
17
3
6
14
13
2
12
1
12
29
0
1
52
6
32
1
3
0
10
9
3
0
1
4
9
5
4
576
635
HC
1
0
0
6
2
7
1
2
6
6
1
5
0
5
11
0
0
22
2
14
0
1
0
5
4
1
0
0
2
4
2
2
251
277
CO
1
1
0
14
5
18
3
6
15
14
2
12
1
12
28
0
1
52
6
32
1
3
10
12
11
3
0
1
5
11
6
4
684
754
S02
16
18
7
475
52
343
30
54
349
315
43
237
5
160
272
1
13
430
47
261
5
26
4
94
85
23
2
8
34
87
50
32
6,208
6,843
CO2
774
500
158
6,535
2,509
9,045
1,791
3,524
7,471
6,907
1,165
6,288
322
6,422
16,024
17
606
26,796
3,033
16,543
331
1,750
262
6,364
5,742
1,579
163
530
2,292
5,901
3,375
2,147
302,338
333,270
3-57
-------
Regulatory Impact Analysis
Table 3-26 Miscellaneous Ship Deep Sea Port Emissions in 2002
Port Name
Honolulu, HI
Portland, OR
Seattle, WA
Anchorage, AK
Kahului, HI
Houston, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Pensacola, FL
New Orleans, LA
New York/New Jersey
Baltimore, MD
Newport News, VA
Total Miscellaneous
Total Miscellaneous (short
tons)
Installed
Power
(MW)
16
21
9
58
1
13
119
3
604
65
12
26
23
6
976
Metric Tonnes
NOX
4
7
5
22
0
1
16
0
83
11
7
7
14
2
179
797
PM10
0
1
0
2
0
0
2
0
8
1
1
1
1
0
16
18
PM2.5
0
0
0
2
0
0
1
0
7
1
1
1
1
0
15
17
HC
0
0
0
1
0
0
1
0
3
0
0
0
0
0
6
7
CO
0
0
0
2
0
0
5
0
24
1
1
1
1
0
35
39
SO2
2
4
3
15
0
1
12
0
62
8
4
5
10
2
128
141
CO2
149
269
180
992
11
49
759
18
3,903
497
281
325
674
103
8,209
9,049
3-58
-------
Chapter 3: Emission Inventory
Table 3-27 Passenger Ship Deep Sea Port Emissions in 2002
Port Name
Honolulu, HI
Portland, OR
Seattle, WA
Valdez, AK
Anchorage, AK
Hilo, HI
Kahului, HI
Nawiliwili, HI
Galveston, TX
Houston, TX
Corpus Christi, TX
Mobile, AL
Manatee, FL
Tampa, FL
Everglades, FL
New Orleans, LA
New York/New Jersey
Portland, ME
Paulsboro, NJ
Fall River, MA
Canaveral, FL
Charleston, SC
Palm Beach, FL
Philadelphia, PA
Miami, FL
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Savannah, GA
Catalina, CA
Eureka, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
San Diego, CA
San Francisco, CA
Total Passenger
Total Passenger (short tons)
Installed
Power
(MW)
4,359
60
3,017
31
200
4,467
2,256
583
3,248
751
113
330
634
3,599
22,083
5,401
6,841
380
126
11
15,756
758
146
44
28,808
2,878
16
1,058
16
919
57
29
5,756
5,105
5,172
2,241
127,251
Metric Tonnes
NOX
637
12
739
2
66
923
466
120
644
143
21
80
66
352
2,447
1,133
745
31
30
1
2,758
101
15
11
4,919
431
2
427
5
78
6
2
567
516
456
214
19,165
21,126
PM10
58
1
72
0
5
76
38
10
76
19
2
7
7
34
244
110
74
3
3
0
256
9
1
1
463
41
0
42
1
7
1
0
52
47
42
19
1,819
2,005
PM2.5
53
1
66
0
5
70
35
9
64
15
2
6
5
25
227
102
68
3
3
0
238
9
1
1
430
38
0
39
0
7
1
0
48
43
38
18
1,668
1,838
HC
19
1
23
0
2
27
14
4
23
5
1
2
2
12
73
37
25
1
1
0
80
3
0
0
142
13
0
13
0
2
0
0
17
16
14
7
578
638
CO
48
1
54
0
5
72
36
9
42
9
3
11
5
28
187
91
59
2
2
0
209
8
1
1
373
33
0
33
0
6
0
4
43
40
35
16
1,470
1,620
SO2
427
8
540
2
43
622
307
82
559
131
14
52
52
271
1,897
835
551
25
23
1
2,044
75
11
8
3,712
327
2
320
4
53
4
1
382
348
307
144
14,184
15,635
C02
28,546
558
35,669
110
2,495
44,123
21,755
5,810
28,782
6,539
954
3,538
3,064
16,166
117,326
51,550
34,382
1,523
1,395
63
126,856
4,652
684
508
230,290
20,219
94
19,829
243
3,608
290
100
26,353
23,970
21,178
9,935
893,157
984,538
3-59
-------
Regulatory Impact Analysis
Table 3-28 Refrigerated Cargo Ship Deep Sea Port Emissions in 2002
Port Name
Honolulu, HI
Port Angeles, WA
Seattle, WA
Anchorage, AK
Galveston, TX
Houston, TX
Corpus Christi, TX
Mobile, AL
Gulfport, MS
Manatee, FL
Pascagoula, MS
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
New York/New Jersey
Morehead City, NC
Paulsboro, NJ
Brunswick, GA
Canaveral, FL
Charleston, SC
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Jacksonville, FL
Miami, FL
Searsport, ME
New Bedford/Fairhaven, MA
Baltimore, MD
Hueneme, CA
Long Beach, CA
Los Angeles, CA
San Diego, CA
Total Reefer
Total Reefer (short tons)
Installed
Power
(MW)
6
3
55
140
532
78
97
22
374
1,277
232
2
245
116
163
1,575
6
4
158
525
82
1,086
2,088
833
733
173
742
5
69
45
963
662
587
48
13,724
Metric Tonnes
NOX
3
1
30
62
87
13
21
5
56
453
54
0
38
71
109
195
1
1
32
96
16
188
531
206
171
34
130
1
15
58
161
94
84
9
3,027
3,337
PM10
0
0
2
5
9
1
2
0
5
37
5
0
3
6
9
16
0
0
3
8
1
15
44
17
14
3
11
0
1
5
11
6
6
1
247
273
PM2.5
0
0
2
4
8
1
2
0
4
33
4
0
3
5
8
15
0
0
2
7
1
14
41
16
13
3
10
0
1
4
10
6
5
1
226
249
HC
0
0
1
2
3
0
1
0
2
14
2
0
1
2
3
7
0
0
1
3
0
6
19
7
6
1
4
0
0
2
5
3
2
0
98
108
CO
0
0
2
5
6
1
3
1
4
36
4
0
3
5
9
16
0
0
2
7
1
15
45
18
14
3
10
0
1
4
81
7
7
1
313
345
SO2
2
1
17
36
70
11
13
3
37
307
38
0
25
47
72
123
1
1
20
63
10
121
341
132
110
22
84
1
10
38
99
56
51
5
1,968
2,170
CO2
113
57
1,203
2,256
3,724
563
897
209
2,320
19,845
2,387
13
1,599
3,223
4,907
8,151
56
53
1,373
4,212
684
8,196
22,716
8,874
7,319
1,483
5,666
44
682
2,641
6,839
3,884
3,494
378
130,060
143,367
3-60
-------
Chapter 3: Emission Inventory
Table 3-29 Roll-On/Roll-Off Ship Deep Sea Port Emissions in 2002
Port Name
Barbers Point, HI
Everett, WA
Honolulu, HI
Longview, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Anchorage, AK
Beaumont, TX
Galveston, TX
Houston, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Gulfport, MS
Manatee, FL
Pensacola, FL
Tampa, FL
Everglades, FL
New Orleans, LA
South Louisiana, LA
Albany, NY
New York/New Jersey
Portland, ME
Morehead City, NC
Chester, PA
Perm Manor, PA
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Richmond, VA
Jacksonville, FL
Miami, FL
Boston, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Hueneme, CA
Long Beach, CA
Installed
Power
(MW)
4
27
39
5
110
11
148
11
5
62
59
810
6
6
69
1,028
3
18
166
3,734
783
4
6
3,323
305
27
47
6
219
75
455
32
423
23
22
175
10
342
8
855
3,646
301
3,284
77
2,578
52
483
Metric Tonnes
NOx
0
2
3
1
8
4
45
2
2
13
7
99
1
1
11
299
1
5
48
285
132
1
1
290
28
2
8
1
23
9
43
3
49
3
4
31
1
35
2
102
380
37
841
12
281
5
67
PM10
0
0
0
0
1
0
4
0
0
1
1
10
0
0
1
26
0
0
4
27
11
0
0
24
3
0
1
0
2
1
4
0
4
0
0
3
0
3
0
9
33
3
65
1
22
0
5
PM2.5
0
0
0
0
1
0
3
0
0
1
1
9
0
0
1
23
0
0
4
25
10
0
0
22
2
0
1
0
2
1
3
0
4
0
0
3
0
3
0
8
30
3
60
1
20
0
4
HC
0
0
0
0
0
0
2
0
0
1
0
3
0
0
0
9
0
0
1
10
5
0
0
11
1
0
0
0
1
0
1
0
2
0
0
1
0
1
0
3
12
1
28
0
9
0
2
CO
0
0
0
0
1
0
4
0
0
1
0
7
0
0
2
23
0
0
4
23
12
0
0
25
2
0
1
0
2
1
3
0
4
0
0
3
0
3
0
8
30
3
65
1
22
8
5
SO2
0
1
2
1
5
2
25
1
1
9
5
75
1
1
7
222
1
4
36
209
81
1
1
176
20
2
5
1
14
6
28
2
35
2
3
22
1
22
1
71
258
26
495
8
169
3
39
C02
3
64
129
39
325
150
1,654
81
75
521
290
4,089
33
33
454
13,769
36
231
2,230
13,387
5,237
34
50
11,292
1,316
104
302
53
880
418
1,777
163
2,302
110
178
1,456
48
1,390
87
4,617
16,915
1,734
30,930
532
10,774
173
2,617
3-61
-------
Regulatory Impact Analysis
Table 3-29 Roll-On/Roll-Off Ship Deep Sea Port Emissions in 2002 (Continued)
Port Name
Los Angeles, CA
Oakland, CA
Total RoRo
Total RoRo (short tons)
Installed
Power
(MW)
428
901
25,210
Metric Tonnes
NOX
61
104
3,391
3,738
PM10
4
8
281
310
PM2.5
4
7
259
286
HC
2
3
113
725
CO
5
8
278
306
SO2
36
59
2,193
2,418
CO2
2,379
3,935
139,396
153,658
3-62
-------
Chapter 3: Emission Inventory
Table 3-30 Tanker Ship Deep Sea Port Emissions in 2002
Port Name
Anacortes, WA
Barbers Point, HI
Everett, WA
Honolulu, HI
Kalama, WA
Longview, WA
Port Angeles, WA
Portland, OR
Seattle, WA
Tacoma, WA
Vancouver, WA
Valdez, AK
Other Puget Sound
Anchorage, AK
Hilo, HI
Kahului, HI
Nawiliwili, HI
Nikishka, AK
Beaumont, TX
Freeport, TX
Galveston, TX
Houston, TX
Port Arthur, TX
Texas City, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Manatee, FL
Matagorda Ship
Panama City, FL
Pascagoula, MS
Tampa, FL
Everglades, FL
New Orleans, LA
Baton Rouge, LA
South Louisiana, LA
Plaquemines, LA
Albany, NY
New York/New Jersey
Portland, ME
Hopewell, VA
Marcus Hook, PA
Installed
Power
(MW)
455
387
6
687
67
30
72
309
74
111
133
6,632
5,678
78
11
9
8
840
10,807
5,206
552
19,096
1,751
6,856
7,498
4,544
1,114
320
355
1,875
38
2,275
2,282
2,036
3,506
2,603
5,886
1,322
28
9,361
2,813
14
2,472
Metric Tonnes
NOX
370
108
23
221
112
86
34
222
152
1,306
64
338
2,111
45
2
2
2
189
1,791
584
68
2,334
230
905
1,213
627
187
45
51
268
5
301
323
495
1,181
1,153
2,187
349
8
1,885
601
4
904
PM10
29
9
2
18
9
7
3
19
12
104
5
36
219
4
0
0
0
19
228
80
12
319
31
121
99
60
15
4
4
22
0
26
27
41
96
93
177
28
1
157
49
0
74
PM2.5
26
8
2
16
8
6
3
17
11
94
5
32
197
3
0
0
0
18
210
74
11
294
28
111
91
55
14
3
4
20
0
24
24
37
89
86
164
26
1
144
45
0
68
HC
13
4
1
8
4
3
1
8
5
45
2
11
71
2
0
0
0
6
76
20
2
80
9
31
40
26
6
1
2
9
0
10
11
15
37
36
68
11
0
65
19
0
28
CO
29
9
2
18
9
7
3
18
12
105
5
27
169
4
0
0
0
15
159
45
5
178
19
69
263
168
46
4
4
22
0
25
26
39
92
90
170
27
1
156
47
0
71
SO2
207
62
13
130
66
49
25
133
87
723
37
296
1,745
25
1
1
1
165
1,742
630
93
2,494
237
942
752
450
115
28
32
166
3
205
202
320
744
711
1,365
221
5
1,202
383
25
2,255
C02
14,211
4,432
881
9,165
4,579
3,421
1,721
9,246
5,952
49,146
2,600
20,581
118,629
1,608
99
77
74
10,938
71,331
23,551
2,832
93,908
9,232
36,122
48,747
29,166
7,432
1,859
2,101
10,961
204
13,293
13,293
21,592
48,739
45,874
88,846
14,598
326
79,931
25,538
153
38,119
3-63
-------
Regulatory Impact Analysis
Table 3-30 Tanker Ship Deep Sea Port Emissions in 2002 (continued)
Port Name
Morehead City, NC
Paulsboro, NJ
Fall River, MA
New Castle, DE
Providence, RI
Brunswick, GA
Canaveral, FL
Charleston, SC
New Haven, CT
Palm Beach, FL
Bridgeport, CT
Camden, NJ
Philadelphia, PA
Wilmington, DE
Wilmington, NC
Jacksonville, FL
Miami, FL
Searsport, ME
Boston, MA
New Bedford/Fairhaven, MA
Baltimore, MD
Newport News, VA
Savannah, GA
Catalina, CA
Carquinez, CA
El Segundo, CA
Hueneme, CA
Long Beach, CA
Los Angeles, CA
Richmond, CA
Sacramento, CA
San Diego, CA
San Francisco, CA
Stockton, CA
Total Tanker
Total Tanker (short tons)
Installed
Power
(MW)
286
2,952
13
524
554
21
351
1,213
951
124
206
349
2,352
159
1,167
1,633
161
498
3,775
96
979
118
2,083
9
1,977
1,685
95
3,380
2,998
2,871
34
60
1,839
370
146,245
Metric Tonnes
NOX
51
595
3
147
116
5
71
260
184
22
40
103
845
38
253
346
33
103
719
22
424
21
395
1
270
192
13
419
383
323
8
6
184
79
29,758
32,802
PM10
4
48
0
12
10
0
6
21
15
2
3
8
70
3
21
28
3
9
64
2
33
2
31
0
20
14
1
31
28
24
1
0
14
6
2,796
3,082
PM2.5
4
45
0
11
9
0
5
20
14
2
3
8
64
3
19
26
3
8
59
2
31
1
29
0
19
13
1
28
26
22
1
0
13
6
2,562
2,824
HC
2
20
0
5
4
0
2
8
6
1
1
3
24
1
8
11
1
3
22
1
14
1
13
0
9
6
0
13
12
10
0
0
6
3
994.23952
1,096
CO
4
48
0
12
9
0
6
20
14
2
3
8
67
3
20
27
3
8
56
2
33
2
31
0
21
15
14
33
30
25
1
0
14
6
2,695
2,977
S02
41
2,021
5
357
173
13
55
366
131
19
29
218
1,891
83
375
419
26
114
757
22
256
13
258
0
151
108
8
245
223
181
4
3
104
44
27,802
30,646
C02
2,169
23,560
120
6,177
4,907
200
3,032
11,054
7,846
923
1,705
4,257
36,299
1,606
10,753
14,554
1,502
4,482
34,227
924
15,951
840
16,547
31
9,920
7,095
547
16,028
14,610
11,904
282
224
6,823
2,903
1,259,107
1,387,928
3-64
-------
Chapter 3: Emission Inventory
Table 3-31 Ocean Going Tug Deep Sea Port Emissions in 2002
Port Name
Portland, OR
Seattle, WA
Kahului, HI
Galveston, TX
Houston, TX
Corpus Christi, TX
Lake Charles, LA
Mobile, AL
Brownsville, TX
Manatee, FL
Pascagoula, MS
Everglades, FL
New Orleans, LA
South Louisiana, LA
Plaquemines, LA
New York/New Jersey
Canaveral, FL
Palm Beach, FL
Jacksonville, FL
Miami, FL
Boston, MA
Total Ocean Going Tug
Total Ocean Going Tug (short
tons)
Installed
Power
(MW)
18
4
16
19
16
47
7
46
3
7
7
28
21
7
4
3
28
28
17
31
4
361
Metric Tonnes
NOX
6
2
2
2
1
5
1
6
0
1
1
3
4
2
1
0
3
3
2
3
1
48
53
PM10
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
5
5
PM2.5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
4
HC
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
CO
0
0
0
0
0
1
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
6
6
S02
3
1
1
1
1
4
1
4
0
1
1
2
3
1
1
0
2
2
2
2
0
34
37
CO2
234
78
77
80
70
226
37
269
16
49
42
126
198
77
43
18
135
133
97
152
24
2,182
2,405
3-65
-------
Regulatory Impact Analysis
Table 3-32 Total Emissions by Great Lake Port in 2002
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
Total Emissions
Toted Emissions (short tons)
Installed
Power
(MW)
89
84
819
126
560
67
55
118
114
84
64
26
495
37
562
156
22
48
1,179
492
1,863
1,359
3,441
140
56
164
742
1,517
14,476
Metric Tonnes
NOx
1.5
2.9
45.5
3.4
32.6
1.9
2.2
3.1
3.0
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
21.0
57.9
549
606
PM10
0.3
0.3
3.9
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
5.0
4.7
12.0
0.5
0.1
1.5
2.0
5.1
50
55
PM2.5
0.2
0.3
3.6
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
0.0
0.1
1.5
0.1
1.0
0.1
0.1
0.1
0.1
0.1
0.1
0.0
0.8
0.0
0.7
0.2
0.0
0.0
1.3
0.7
1.9
1.7
4.5
0.2
0.1
0.5
0.8
2.0
19
21
CO
0.1
0.2
3.7
0.3
2.6
0.2
0.2
0.3
0.3
0.3
0.1
0.0
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
2.3
30.0
2.5
21.8
1.1
1.7
2.3
2.5
2.2
1.3
0.5
17.8
0.7
10.0
3.0
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
156
150
1,982
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
3-66
-------
Chapter 3: Emission Inventory
Table 3-33 Auxiliary Engine Emissions by Great Lake Port in 2002
Port Name
Alpena, MI
Buffalo, NY
Bums 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
Total Auxiliary Emissions
Total Auxiliary Emissions
(short tons)
Installed
Power
(MW)
20
19
181
28
122
15
12
26
25
18
14
6
109
8
125
35
5
11
262
108
414
303
760
31
12
35
165
336
3,202
Metric Tonnes
NOX
1.2
1.5
29.6
1.4
22.5
0.6
1.5
1.2
1.3
1.5
0.7
0.3
17.5
0.4
5.6
1.6
0.2
0.5
16.3
13.7
20.9
29.6
74.0
3.7
0.6
15.1
8.1
30.9
302
333
PM10
0.1
0.1
2.5
0.1
1.9
0.1
0.1
0.1
0.1
0.1
0.1
0.0
1.4
0.0
0.5
0.1
0.0
0.0
1.3
1.1
1.7
2.5
6.1
0.3
0.0
1.3
0.7
2.6
25
28
PM2.5
0.1
0.1
2.2
0.1
1.7
0.0
0.1
0.1
0.1
0.1
0.1
0.0
1.3
0.0
0.4
0.1
0.0
0.0
1.2
1.0
1.6
2.2
5.6
0.3
0.0
1.2
0.6
2.3
23
25
HC
0.0
0.0
0.8
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.2
0.0
0.0
0.0
0.4
0.4
0.6
0.8
2.0
0.1
0.0
0.4
0.2
0.9
8
9
CO
0.1
0.1
2.2
0.1
1.7
0.0
0.1
0.1
0.1
0.1
0.1
0.0
1.3
0.0
0.4
0.1
0.0
0.0
1.2
1.0
1.6
2.2
5.6
0.3
0.0
1.2
0.6
2.3
23
25
S02
0.8
1.0
19.7
0.9
15.0
0.4
1.0
0.8
0.9
1.0
0.5
0.2
11.7
0.3
3.7
1.1
0.2
0.3
10.9
9.1
13.9
19.8
49.4
2.5
0.4
10.1
5.4
20.6
202
222
CO2
57
71
1,366
63
1,039
30
68
56
60
70
32
12
806
18
257
76
11
21
752
633
964
1,367
3,418
170
27
699
376
1,426
13,944
15,370
3-67
-------
Regulatory Impact Analysis
Table 3-34 Cruise Emissions by Great Lake Port in 2002
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
Total Cruise Emissions
Total Cruise Emissions (short
tons)
Installed
Power
(MW)
89
84
819
126
560
67
55
118
114
84
64
26
495
37
562
156
22
48
1,179
492
1,863
1,359
3,441
140
56
164
742
1,517
14,476
Metric Tonnes
NOx
0.3
0.9
11.7
1.4
7.7
0.8
0.6
1.5
1.2
1.1
0.6
0.1
6.4
0.4
7.3
1.7
0.3
0.6
15.1
6.4
23.1
16.5
43.3
1.7
0.7
2.0
9.4
20.2
183
202
PM10
0.1
0.1
1.0
0.1
0.7
0.1
0.1
0.1
0.1
0.1
0.1
0.0
0.6
0.0
0.6
0.2
0.0
0.1
1.4
0.6
2.3
1.6
4.2
0.2
0.1
0.2
0.9
1.8
17
19
PM2.5
0.1
0.1
0.9
0.1
0.6
0.1
0.1
0.1
0.1
0.1
0.1
0.0
0.5
0.0
0.5
0.2
0.0
0.0
1.3
0.5
2.1
1.5
3.9
0.2
0.1
0.2
0.8
1.7
16
IS
HC
0.0
0.0
0.4
0.0
0.3
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.2
0.1
0.0
0.0
0.5
0.2
0.8
0.6
1.5
0.1
0.0
0.1
0.3
0.7
6
7
CO
0.0
0.1
0.9
0.1
0.6
0.1
0.0
0.1
0.1
0.1
0.0
0.0
0.5
0.0
0.6
0.1
0.0
0.0
1.2
0.5
1.8
1.3
3.4
0.1
0.1
0.2
0.7
1.6
14
16
S02
1.2
0.9
7.5
1.1
5.2
0.5
0.5
1.2
1.1
0.8
0.6
0.3
4.5
0.3
4.4
1.4
0.2
0.4
11.3
4.6
18.4
13.1
33.3
1.3
0.5
1.6
7.1
14.0
137
151
C02
75
55
453
66
314
30
33
71
66
48
37
16
275
21
265
82
12
26
684
281
1,113
793
2,019
78
31
97
428
846
8,313
9,164
3-68
-------
Chapter 3: Emission Inventory
Table 3-35 Reduced Speed Zone Emissions by Great Lake Port in 2002
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
Total RSZ Emissions
Toted RSZ Emissions (short
tons)
Installed
Power
(MW)
89
84
819
126
560
67
55
118
114
84
64
26
495
37
562
156
22
48
1,179
492
1,863
1,359
3,441
140
56
164
742
1,517
14,476
Metric Tonnes
NOx
0.1
0.2
2.8
0.3
1.9
0.2
0.1
0.4
0.3
0.3
0.1
0.0
1.6
0.1
1.7
0.4
0.1
0.1
3.7
1.5
5.8
4.1
10.8
0.4
0.2
0.5
2.3
4.9
45
50
PM10
0.0
0.0
0.2
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.3
0.1
0.6
0.4
1.0
0.0
0.0
0.0
0.2
0.4
4
5
PM2.5
0.0
0.0
0.2
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.3
0.1
0.5
0.4
0.9
0.0
0.0
0.0
0.2
0.4
4
4
HC
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.1
0.1
0.2
0.1
0.4
0.0
0.0
0.0
0.1
0.2
2
2
CO
0.0
0.0
0.2
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.3
0.1
0.5
0.3
0.8
0.0
0.0
0.0
0.2
0.4
4
4
S02
0.3
0.2
1.8
0.3
1.3
0.1
0.1
0.3
0.3
0.2
0.1
0.1
1.1
0.1
1.0
0.3
0.0
0.1
2.8
1.1
4.5
3.1
8.1
0.3
0.1
0.4
1.7
3.4
33
37
CO2
19
14
112
16
78
7
8
18
16
12
9
4
67
5
65
20
3
6
170
69
277
193
502
19
7
24
106
208
2,052
2,262
3-69
-------
Regulatory Impact Analysis
Table 3-36 Maneuvering Emissions by Great Lake Port in 2002
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
Total Maneuver Emissions
Total Maneuver Emissions
(short tons)
Installed
Power
(MW)
89
84
819
126
560
67
55
118
114
84
64
26
495
37
562
156
22
48
1,179
492
1,863
1,359
3,441
140
56
164
742
1,517
14,476
Metric Tonnes
NOx
0.2
0.6
4.4
0.9
2.0
0.5
0.2
0.3
0.8
0.7
0.4
0.1
2.3
0.2
4.2
1.1
0.2
0.2
6.0
2.0
9.7
5.7
15.2
0.5
0.3
0.6
3.8
6.6
70
77
PM10
0.0
0.1
0.4
0.1
0.2
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.2
0.0
0.4
0.1
0.0
0.0
0.6
0.2
1.0
0.6
1.6
0.1
0.0
0.1
0.4
0.7
7
8
PM2.5
0.0
0.1
0.4
0.1
0.2
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.2
0.0
0.4
0.1
0.0
0.0
0.6
0.2
0.9
0.6
1.5
0.0
0.0
0.1
0.4
0.6
7
7
HC
0.0
0.0
0.3
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.3
0.1
0.0
0.0
0.3
0.1
0.6
0.3
0.9
0.0
0.0
0.0
0.2
0.4
4
5
CO
0.0
0.1
0.5
0.1
0.2
0.1
0.0
0.0
0.1
0.1
0.0
0.0
0.3
0.0
0.5
0.1
0.0
0.0
0.7
0.2
1.1
0.6
1.7
0.1
0.0
0.1
0.4
0.8
8
9
S02
0.3
0.4
3.0
0.6
1.4
0.3
0.2
0.2
0.6
0.5
0.3
0.1
1.6
0.2
2.6
0.7
0.1
0.2
4.4
1.4
7.3
4.5
11.3
0.4
0.2
0.4
2.7
4.6
50
56
C02
17
28
190
41
89
19
11
15
38
32
18
6
105
11
167
47
7
10
111
87
466
284
718
24
13
27
174
291
3,213
3,542
3-70
-------
Chapter 3: Emission Inventory
Table 3-37 Hotelling Emissions by Great Lake Port in 2002
Port Name
Alpena, MI
Buffalo, NY
Bums 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
Total Hotel Emissions
Toted Hotel Emissions (short
tons)
Installed
Power
(MW)
89
84
819
126
560
67
55
118
114
84
64
26
495
37
562
156
22
48
1,179
492
1,863
1,359
3,441
140
56
164
742
1,517
14,476
Metric Tonnes
NOX
1.0
1.2
26.6
0.8
20.9
0.4
1.3
0.9
0.8
1.1
0.4
0.2
15.8
0.2
3.0
1.0
0.1
0.3
12.1
12.2
14.0
25.1
62.6
3.3
0.4
14.7
5.5
26.1
252
278
PM10
0.1
0.1
2.2
0.1
1.7
0.0
0.1
0.1
0.1
0.1
0.0
0.0
1.3
0.0
0.3
0.1
0.0
0.0
1.0
1.0
1.2
2.1
5.2
0.3
0.0
1.2
0.5
2.2
21
23
PM2.5
0.1
0.1
2.0
0.1
1.6
0.0
0.1
0.1
0.1
0.1
0.0
0.0
1.2
0.0
0.2
0.1
0.0
0.0
0.9
0.9
1.1
1.9
4.8
0.2
0.0
1.1
0.4
2.0
19
21
HC
0.0
0.0
0.7
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.1
0.0
0.0
0.0
0.3
0.3
0.4
0.7
1.7
0.1
0.0
0.4
0.2
0.7
7
8
CO
0.1
0.1
2.0
0.1
1.6
0.0
0.1
0.1
0.1
0.1
0.0
0.0
1.2
0.0
0.2
0.1
0.0
0.0
0.9
0.9
1.1
1.9
4.8
0.2
0.0
1.1
0.4
2.0
19
21
S02
0.7
0.8
17.7
0.5
14.0
0.2
0.9
0.6
0.5
0.7
0.3
0.1
10.5
0.2
2.0
0.6
0.1
0.2
8.0
8.2
9.3
16.8
41.8
2.2
0.3
9.8
3.7
17.4
168
185
CO2
46
53
1,227
36
967
16
60
42
36
49
20
8
730
11
140
44
6
13
557
565
645
1,162
2,891
152
18
679
254
1,205
11,631
12,821
3-71
-------
Regulatory Impact Analysis
Table 3-38 Self-Unloading Bulk Carrier Emissions by Great Lake Port in 2002
Port Name
Alpena, MI
Buffalo, NY
Bums 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
Total SU Bulk Carrier
Total SU Bulk Carrier (short
tons)
Installed
Power
(MW)
89
71
236
126
75
67
27
118
114
71
64
26
169
37
562
156
22
48
1,047
208
1,843
802
2,201
52
56
9
735
987
10,015
Metric Tonnes
NOX
1.5
2.0
7.6
3.4
1.3
1.9
0.5
3.1
3.0
2.3
1.5
0.5
4.3
0.9
16.2
4.2
0.7
1.2
29.2
5.5
51.3
20.3
61.8
1.3
1.5
0.2
20.6
28.1
276
304
PM10
0.3
0.2
0.7
0.3
0.2
0.2
0.1
0.3
0.3
0.2
0.2
0.1
0.5
0.1
1.4
0.4
0.1
0.1
2.8
0.5
4.9
2.1
6.0
0.1
0.1
0.0
1.9
2.5
27
29
PM2.5
0.2
0.2
0.7
0.3
0.2
0.1
0.1
0.3
0.3
0.2
0.2
0.1
0.4
0.1
1.3
0.4
0.1
0.1
2.6
0.5
4.6
2.0
5.6
0.1
0.1
0.0
1.8
2.3
25
27
HC
0.0
0.1
0.3
0.1
0.0
0.1
0.0
0.1
0.1
0.1
0.1
0.0
0.2
0.0
0.7
0.2
0.0
0.0
1.1
0.2
1.9
0.7
2.3
0.0
0.1
0.0
0.8
1.0
10
11
CO
0.1
0.2
0.7
0.3
0.1
0.2
0.0
0.3
0.3
0.2
0.1
0.0
0.4
0.1
1.4
0.4
0.1
0.1
2.5
0.5
4.3
1.7
5.2
0.1
0.1
0.0
1.7
2.4
23
26
S02
2.5
1.8
5.7
2.5
1.7
1.1
0.6
2.3
2.5
1.6
1.3
0.5
3.8
0.7
10.0
3.0
0.4
0.9
21.6
4.4
38.7
17.5
47.9
1.1
1.1
0.2
14.8
19.3
210
231
C02
156
112
362
158
109
73
37
146
156
104
84
34
238
47
637
193
28
56
1,363
282
2,449
1,106
3,034
68
69
11
935
1,226
13,273
14,631
3-72
-------
Chapter 3: Emission Inventory
Table 3-39 Bulk Carrier Emissions by Great Lake Port in 2002
Port Name
Buffalo, NY
Burns Waterway, IN
Cleveland, OH
Erie, PA
Gary, IN
Milwaukee, WI
Ashtabula, OH
Chicago, IL
Conneaut, OH
Detroit, MI
Duluth-Superior, MN&WI
Indiana, IN
Sandusky, OH
Toledo, OH
Total Bulk Carrier
Total Bulk Carrier (short tons)
Installed
Power
(MW)
13
562
427
17
7
292
126
219
20
458
1,032
88
7
421
3,689
Metric Tonnes
NOX
0.9
36.8
27.7
1.1
0.5
19.9
7.4
12.8
1.2
27.2
61.1
4.6
0.4
25.1
227
250
PM10
0.1
3.0
2.3
0.1
0.0
1.6
0.6
1.1
0.1
2.2
5.2
0.4
0.0
2.1
19
21
PM2.5
0.1
2.8
2.1
0.1
0.0
1.5
0.6
1.0
0.1
2.1
4.7
0.4
0.0
2.0
17
19
HC
0.0
1.1
0.9
0.0
0.0
0.6
0.2
0.4
0.0
0.9
1.9
0.1
0.0
0.8
7
8
CO
0.1
2.9
2.2
0.1
0.0
1.6
0.6
1.0
0.1
2.2
4.8
0.4
0.0
2.0
18
20
S02
0.6
23.5
17.7
0.7
0.3
12.7
4.7
8.3
0.8
17.3
40.5
3.1
0.4
16.8
147
162
CO2
38
1,567
1,179
46
22
852
313
550
52
1,149
2,692
203
27
1,116
9,807
10,811
Table 3-40 General Cargo Ship Emissions by Great Lake Port in 2002
Port Name
Burns Waterway, IN
Cleveland, OH
Erie, PA
Milwaukee, WI
Ashtabula, OH
Chicago, IL
Detroit, MI
Duluth-Superior, MN&WI
Toledo, OH
Total General Cargo
Total General Cargo (short
tons)
Installed
Power
(MW)
21
58
11
34
6
44
44
167
77
462
Metric Tonnes
NOx
1.2
3.5
0.6
1.9
0.2
1.9
2.0
6.7
3.5
22
24
PM10
0.1
0.3
0.1
0.2
0.0
0.2
0.2
0.6
0.3
2
2
PM2.5
0.1
0.3
0.1
0.2
0.0
0.2
0.2
0.5
0.3
2
2
HC
0.0
0.1
0.0
0.1
0.0
0.1
0.1
0.2
0.1
1
1
CO
0.1
0.3
0.0
0.2
0.0
0.2
0.2
0.5
0.3
2
2
S02
0.8
2.4
0.4
1.3
0.2
1.3
1.3
4.7
2.3
15
16
C02
53
160
29
87
12
84
88
305
152
969
1,068
Table 3-41 Tanker Ship Emissions by Great Lake Port in 2002
Port Name
Chicago, IL
Detroit, MI
Duluth-Superior, MN&WI
Manistee, MI
Toledo, OH
Total Tanker
Total Tanker (short tons)
Installed
Power
(MW)
15
6
12
155
5
193
Metric Tonnes
NOx
1.8
0.7
1.4
17.6
0.5
22
24
PM10
0.1
0.1
0.1
1.5
0.0
2
2
PM2.5
0.1
0.1
0.1
1.4
0.0
2
2
HC
0.1
0.0
0.0
0.5
0.0
1
1
CO
0.1
0.1
0.1
1.4
0.0
2
2
SO2
1.2
0.4
0.9
12.1
0.3
15
16
CO2
80
30
63
816
24
1,012
1,116
3-73
-------
Regulatory Impact Analysis
Table 3-42 Integrated Tug-Barge Emissions by Great Lake Port in 2002
Port Name
Gary, IN
Chicago, IL
Detroit, MI
Duluth-Superior, MN&WI
Toledo, OH
Total ITB
Total ITB (short tons)
Installed
Power
(MW)
6
6
49
29
27
117
Metric Tonnes
NOx
0.3
0.1
1.2
0.7
0.7
3
3
PM10
0.0
0.0
0.1
0.1
0.1
0
0
PM2.5
0.0
0.0
0.1
0.1
0.1
0
0
HC
0.0
0.0
0.0
0.0
0.0
0
0
CO
0.0
0.0
0.1
0.1
0.1
0
0
S02
0.2
0.1
0.9
0.6
0.5
2
3
C02
15
7
59
35
32
149
164
For Great Lake ports, auxiliary emissions are responsible for roughly 50% of the NOx
and PM emissions, primarily due to emissions during the hotelling mode. Bulk Carrier ships are
responsible for the vast majority of the emissions.
3.3.2.6.3 Summary
This section provides a summary of the total port emissions for 2002. Table 3-43 and
Table 3-44 provide a breakout of the total port emissions by auxiliary and propulsion engines, in
units of metric tonnes and short tons, respectively. Table 3-45 and Table 3-46 provide the
breakout by mode of operation, while Table 3-47 and Table 3-48 provide a summary of port
emissions by ship type.
Auxiliary emissions at ports are responsible for 39-48% of the total inventory, depending
on the pollutant. Hotelling, cruise, and RSZ modes of operation are all important contributors to
emissions. Container and Tanker ships are the largest contributors to port emissions.
Table 3-43 2002 Port Emissions Summary by Engine and Port Type (metric tonnes)
Engine Type
Propulsion
Auxiliary
All
Port Type
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Grand Total
Metric Tonnes
NOx
64,288
248
64,536
57,317
302
57,619
121,606
549
122,155
PM10
5,478
25
5,503
5,052
25
5,077
10,530
50
10,580
PM2.5
5,034
23
5,057
4,597
23
4,620
9,631
46
9,677
HC
2,532
11
2,543
1,615
8
1,624
4,148
19
4,167
CO
6,329
22
6,351
4,306
23
4,328
10,635
45
10,680
S02
52,676
187
52,863
41,232
202
41,433
93,908
389
94,297
C02
2,360,435
11,267
2,371,702
2,635,436
13,944
2,649,380
4,995,871
25,210
5,021,082
3-74
-------
Chapter 3: Emission Inventory
Table 3-44 2002 Port Emissions Summary by Engine and Port Type (short tons)
Engine Type
Propulsion
Auxiliary
All
Port Type
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Grand Total
Short Tons
NOx
70,866
273
71,139
63,181
333
63,514
134,047
606
134,653
PM10
6,039
27
6,066
5,569
28
5,597
11,608
55
11,662
PM2.5
5,549
25
5,575
5,067
25
5,092
10,616
50
10,667
HC
2,792
12
2,803
1,781
9
1,790
4,572
21
4,593
CO
6,977
24
7,001
4,746
25
4,771
11,723
50
11,772
S02
58,065
207
58,272
45,450
222
45,672
103,515
429
103,944
C02
2,601,934
12,419
2,614,353
2,905,071
15,370
2,920,442
5,507,005
27,790
5,534,795
Table 3-45 2002 Port Emissions Summary by Mode and Port Type (metric tonnes)
Mode
Cruise
RSZ
Maneuvering
Hotelling
All
Port Type
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Grand Total
Metric Tonnes
NOx
34,193
183
34,376
34,427
45
34,472
7,383
70
7,452
45,603
252
45,855
121,606
549
122,155
PM10
2,826
17
2,843
2,887
4
2,891
758
7
765
4,060
21
4,081
10,530
50
10,580
PM2.5
2,623
16
2,639
2,657
4
2,661
625
7
632
3,726
19
3,745
9,631
46
9,677
HC
1,141
6
1,148
1,280
2
1,281
440
4
444
1,287
7
1,294
4,148
19
4,167
CO
2,651
14
2,665
3,804
4
3,808
724
8
732
3,456
19
3,475
10,635
45
10,680
SO2
21,186
137
21,323
35,148
33
35,181
4,356
50
4,406
33,218
168
33,386
93,908
389
94,297
CO2
1,314,146
8,313
1,322,459
1,318,897
2,052
1,320,950
266,262
3,213
269,476
2,096,566
11,631
2,108,197
4,995,871
25,210
5,021,082
3-75
-------
Regulatory Impact Analysis
Table 3-46 2002 Port Emissions Summary by Mode and Port Type (short tons)
Mode
Cruise
RSZ
Maneuvering
Hotelling
All
Port Type
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Grand Total
Short Tons
NOx
37,691
202
37,893
37,949
50
37,999
8,138
77
8,215
50,268
278
50,546
134,047
606
134,653
PM10
3,115
19
3,134
3,182
5
3,187
835
8
843
4,475
23
4,498
11,608
55
11,662
PM2.5
2,891
18
2,909
2,929
4
2,934
689
7
696
4,107
21
4,128
10,616
50
10,667
HC
1,258
7
1,265
1,410
2
1,412
485
5
490
1,419
8
1,426
4,572
21
4,593
CO
2,922
16
2,938
4,193
4
4,197
799
9
807
3,809
21
3,830
11,723
50
11,772
SO2
23,353
151
23,504
38,744
37
38,781
4,802
56
4,857
36,617
185
36,802
103,515
429
103,944
CO2
1,448,598
9,164
1,457,762
1,453,835
2,262
1,456,098
293,504
3,542
297,046
2,311,068
12,821
2,323,889
5,507,005
27,790
5,534,795
3-76
-------
Chapter 3: Emission Inventory
Table 3-47 2002 Port Emissions Summary by Ship Type and Port Type (metric tonnes)
Ship Type
Auto Carrier
Barge Carrier
Self-Unloading
Bulk Carrier
Other Bulk
Carrier
Container
General Cargo
Miscellaneous
Passenger
Refrigerated
Cargo
Roll-On/Roll-
Off
Tanker
Ocean Going
Tug
Integrated Tug-
Barge
All
Port Type
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Grand Total
Metric Tonnes
NOx
5,125
0
5,125
148
0
148
0
276
276
19,373
227
19,600
33,990
0
33,990
7,402
22
7,424
179
0
179
19,165
0
19,165
3,027
0
3,027
3,391
0
3,391
29,758
22
29,780
48
0
48
0
3
3
121,606
549
122,155
PM10
421
0
421
13
0
13
0
27
27
1,570
19
1,589
2,733
0
2,733
630
2
631
16
0
16
1,819
0
1,819
247
0
247
281
0
281
2,796
2
2,798
5
0
5
0
0
0
10,530
50
10,580
PM2.5
384
0
384
12
0
12
0
25
25
1,431
17
1,448
2,494
0
2,494
576
2
578
15
0
15
1,668
0
1,668
226
0
226
259
0
259
2,562
2
2,564
4
0
4
0
0
0
9,631
46
9,677
HC
185
0
185
5
0
5
0
10
10
633
7
640
1,282
0
1,282
251
1
252
6
0
6
578
0
578
98
0
98
113
0
113
994
1
995
2
0
2
0
0
0
4,148
19
4,167
CO
577
0
577
12
0
12
0
23
23
1,732
18
1,750
2,833
0
2,833
684
2
686
35
0
35
1,470
0
1,470
313
0
313
278
0
278
2,695
2
2,697
6
0
6
0
0
0
10,635
45
10,680
S02
3,676
0
3,676
141
0
141
0
210
210
14,945
147
15,092
22,628
0
22,628
6,208
15
6,223
128
0
128
14,184
0
14,184
1,968
0
1,968
2,193
0
2,193
27,802
15
27,817
34
0
34
0
2
2
93,908
389
94,297
C02
198,637
0
198,637
6,364
0
6,364
0
13,273
13,273
767,825
9,807
777,632
1,288,596
0
1,288,596
302,338
969
303,307
8,209
0
8,209
893,157
0
893,157
130,060
0
130,060
139,396
0
139,396
1,259,107
1,012
1,260,119
2,182
0
2,182
0
149
149
4,995,871
25,210
5,021,082
3-77
-------
Regulatory Impact Analysis
Table 3-48 2002 Port Emissions Summary by Ship Type and Port Type (short tons)
Ship Type
Auto Carrier
Barge Carrier
Self-Unloading
Bulk Carrier
Other Bulk
Carrier
Container
General Cargo
Miscellaneous
Passenger
Refrigerated
Cargo
Roll-On/Roll-
Off
Tanker
Ocean Going
Tug
Integrated Tug-
Barge
All
Port Type
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Total
Deep Sea
Great Lakes
Grand Total
Short Tons
NOX
5,649
0
5,649
163
0
163
0
304
304
21,355
250
21,605
37,468
0
37,468
8,159
24
8,183
197
0
197
21,126
0
21,126
3,337
0
3,337
3,738
0
3,738
32,802
24
32,826
53
0
53
0
3
3
134,047
606
134,653
PM10
464
0
464
14
0
14
0
29
29
1,731
21
1,752
3,012
0
3,012
694
2
696
18
0
18
2,005
0
2,005
273
0
273
310
0
310
3,082
2
3,084
5
0
5
0
0
0
11,608
55
11,662
PM2.5
424
0
424
13
0
13
0
27
27
1,577
19
1,597
2,749
0
2,749
635
2
637
17
0
17
1,838
0
1,838
249
0
249
286
0
286
2,824
2
2,826
4
0
4
0
0
0
10,616
50
10,667
HC
204
0
204
6
0
6
0
11
11
697
8
705
1,413
0
1,413
277
1
278
7
0
7
638
0
638
108
0
108
125
0
125
1,096
1
1,097
2
0
2
0
0
0
4,572
21
4,593
CO
636
0
636
14
0
14
0
26
26
1,909
20
1,929
3,123
0
3,123
754
2
756
39
0
39
1,620
0
1,620
345
0
345
306
0
306
2,971
2
2,973
6
0
6
0
0
0
11,723
50
11,772
SO2
4,052
0
4,052
156
0
156
0
231
231
16,474
162
16,636
24,944
0
24,944
6,843
16
6,860
141
0
141
15,635
0
15,635
2,170
0
2,170
2,418
0
2,418
30,646
16
30,663
37
0
37
0
3
3
103,515
429
103,944
CO2
218,960
0
218,960
7,015
0
7,015
0
14,631
14,631
846,382
10,811
857,193
1,420,434
0
1,420,434
333,270
1,068
334,338
9,049
0
9,049
984,538
0
984,538
143,367
0
143,367
153,658
0
153,658
1,387,928
1,116
1,389,044
2,405
0
2,405
0
164
164
5,507,005
27,790
5,534,795
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Chapter 3: Emission Inventory
3.3.3 Interport Emissions
This section presents our nationwide analysis of the methodology and inputs used to
estimate interport emissions from main propulsion and auxiliary engines used by Category 3
ocean-going vessels for the 2002 calendar year. The modeling domain for vessels operating in
the ocean extends from the U.S. coastline to a 200 nautical mile boundary. For ships operating
in the Great Lakes, it extends out to the international boundary with Canada. The emission
results are divided into nine geographic regions of the U.S. (including Alaska and Hawaii), and
then totaled to provide a national inventory.
The interport emissions described in this section represent total interport emissions prior
to any adjustments made to incorporate near-port inventories. The approach used to replace the
near-port portion of the interport emissions is provided in Section 3.3.3.3. The final adjusted
interport emissions are provided in Section 3.3.4.
3.3.3.1 Methodology
The interport emissions were estimated using the Waterway Network Ship Traffic,
Energy, and Environmental Model (STEEM).3'4 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 vessels calling on U.S. ports or transiting
the U.S. coastline to other destinations, and shipping activity in Canada and Mexico. The model
estimates emissions from main propulsion and auxiliary marine engines used on Category 3
vessels that engage in foreign commerce using historical North American 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 cruise in unconstrained shipping lanes to maneuvering in a port. The model,
however, excludes hotelling operations while the vessel is docked or anchored, and very low
speed maneuvering close to a dock. For that reason, STEEM is referred to as an "interport"
model, to easily distinguish it from the near ports analysis.
STEEM uses advanced ArcGIS tools and develops emission inventories in the following
way.39 The model 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.
There are approximately 4,000 vessels worldwide in the VOS system. The ICOADS project is
sponsored by the National Oceanic and Atmospheric Administration and National Science
Foundation's National Center for Atmospheric Research (NCAR). The second database is the
Automated Mutual-Assistance Vessel Rescue (AMVER) system. 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.
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Regulatory Impact Analysis
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) (Figure
3-2).
Nautical Miles
Figure 3-2 AMVER and ICOADS data
Every major ocean and Great Lake port is also spatially located in the waterway network
using ArcGIS software. For the U.S., the latitude and longitude for each port is taken from the
USAGE report on vessel entrances and clearances.13 There are 251 U.S. ports in the USAGE
entrances and clearances report. Each port also has a unique identification number for
computational purposes.
As illustrated in Figure 3-3, the waterway network represented by 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. The figure
represents only a sample of the many routes contained in the model.
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Chapter 3: Emission Inventory
C02(kg/16sqr. km)
| ] 0-5.000
Figure 3-3 Illustration of STEEM Modeling Domain and Spatial Distribution of Shipping Lanes
Every major ocean and Great Lake port is also spatially located in the waterway network
using ArcGIS software. For the U.S., the latitude and longitude for each port is taken from the
U.S. Army Corps of Engineers report on vessel entrances and clearances (subsequently referred
to as USAGE).13 There are 251 U.S. ports in the entrances and clearances report. Each port also
has a unique identification number for computational purposes.
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.
Once the waterway network and various databases are constructed, STEEM uses ArcGIS
Network Analyst tools along with specific information on each individual ship movement to
solve the 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:
Emissions per trip = distance (nautical miles) / speed (nautical miles/hour) x
horsepower (kW) x fractional load factor x emission
factor (g/kW-hour)
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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 for the first and last 20
kilometers of each trip 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 20 kilometers.
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.
3.3.3.1.1 Emission Inputs
The STEEM waterway network model relies on a number of inputs to identify the
movements for each vessel, individual ship attributes, and related emission factor information.
Each of these databases is described separately below.
3.3.3.1.1.1 Shipping Movements
The shipping activity and routes database provides information on vessel movements or
trips. It is developed using port entrances and clearances information from the USAGE report
for the U.S. and the Lloyd's Maritime Intelligence Unit (LMIU) for Canada and Mexico.40
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
• 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.
3.3.3.1.1.2 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)
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Chapter 3: Emission Inventory
The ship attributes data set contains the following information from Lloyd's Register-
Fairplay for each ship identification number.
14
• Main propulsion engine installed power (horsepower)
• Service speed (cruise speed)
• Ship size (length, wide, and draft)
Sometimes data was lacking from the above references for ship speed. In these instances,
the missing information was developed for each of nine 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.41'21 The
resulting vessel cruise speeds for ships with missing data are shown in Table 3-49.
Table 3-49 Average Vessel Cruise Speed by Ship Type"
Ship Type Average Cruise Speed (knots)
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Refrigerated Cargo
Roll On-Roll Off
Tanker
Fishing
Miscellaneous
14.1
19.9
12.3
22.4
16.4
16.9
13.2
11.7
12.7
Note:
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 in Section 3.3.2 above 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
different 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 category. This operation is performed internally in the model and the result 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.42
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Regulatory Impact Analysis
(The ICF report attributed these power values to a study for the Port of Los Angeles by Starcrest
Consulting.12) The auxiliary engine power for each individual vessel of a given ship type is 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 3-50.
Table 3-50 Auxiliary Engine Power Ratios
Vessel Type
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Refrigerated Cargo
Roll On-Roll Off
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
42
Notes:
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 Roll On-Roll Off 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 operation, in addition to load factors for auxiliary marine
engines. Main engine load factors for cruise operation were taken from a study of international
shipping for all ship types, except passenger vessels.43 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.43'44 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.21 The main engine load factors at cruise
speed by ship type are shown in Table 3-51.
Auxiliary engine load factors, except for passenger ships, were obtained from the ICF
International study referenced above. These values are also shown in Table 3-51. 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%.
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Chapter 3: Emission Inventory
Table 3-51 Main and Auxiliary Engine Load Factors at Cruise Speed by Ship Type
Ship Type
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Refrigerated Cargo
Roll On-Roll Off
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
3.3.3.1.1.3 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 3-52 . The speed specific factors for NOx, HC, and SC>2 were taken from several recent
analyses of ship emissions in the U.S., Canada, and Europe. 21>36>42'43'45 The PM factor was
based on discussions with the California Air Resources Board (ARE) staff. The fuel specific CO
emission factor was taken from a report by ENVIRON International.19 The STEEM study 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.20 Fuel consumption was
calculated from CO2 emissions using the same ratio (1:3.183) as used in the near-port analysis.
Table 3-52 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
Note:
a Estimated from PM10 using a multiplicative adjustment factor of 0.92.
The emission factors for auxiliary engines are shown in Table 3-53. 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
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Regulatory Impact Analysis
was also referenced above. The PM factor for residual marine was based on discussions with the
California Air Resources Board (ARE) staff. The CO factors are from the Starcrest Consulting
study of the Port of Los Angeles.12 For SC>2, the fuel specific emission factors were obtained
from Entec and Corbett and Koehler.
21,43
The composite emission factors displayed in the table are discussed below.
Table 3-53 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
SO2
4.3
12.3
**
Note:
a Estimated from PM10 using a multiplicative adjustment factor of 0.92.
b See Table 3-54 for composite SO2 emission factors by vessel type.
As for main engines, the STEEM study used the composite emission factors for auxiliary
engines. For all pollutants other than SC>2, 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.20
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 3-53 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 3-54.
Table 3-54 Auxiliary Engine SO2 Composite Emission Factors by Vessel Type
Vessel Type
Bulk Carrier
Container Ship
General Cargo
Passenger Ship
Refrigerated Cargo
Roll On-Roll Off
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
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Chapter 3: Emission Inventory
3.3.3.1.1.4 EPA Adjustments to STEEM PM and SO2 Emission Inventories
The interport emission results contained in this study for PMio and 862 were taken from
the STEEM inventories and then adjusted to reflect EPA's recent review of available engine test
data and fuel sulfur levels as described Section 3.3.2.3 for the near port analysis. In the near
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. As shown in Section 3.3.3.1.1.3, the STEEM study
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, EPA adjusted the interport PM inventories
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.
The STEEM SC>2 emission inventories were similarly adjusted using SC>2 emission
factors from the interport analysis (Section 3.3.3.1.1.3) and the near ports analysis (Section
3.3.2.3). This information is displayed in Table 3-55. The composite values in the table are
calculated by mathematically weighting the slow speed and medium speed emission factors from
each study by their individual population fraction from the 2005 ARB shipping survey, i.e., 95
percent and 5 percent, respectively.20 Therefore, the interport 862 inventories that appear in this
report are the result of multiplying the STEEM inventories by the ratio of the two composite
g/kW-hr emission factors shown in table, i.e., 10.33 /10.6 or 0.975.
Table 3-55 SO2 Emission Factors Used to Adjust STEEM Emission Inventories
Engine Type
Slow Speed
Medium Speed
Composite
Fuel Type
Residual
Marine
Residual
Marine
Residual
Marine
STEEM
(g/kW-hr)
10.50
11.50
10.6 a
Near Ports
(g/kW-hr)
10.29
11.09
10.33 a
Composite
(g/ kW -hr)
n/a
n/a
0.975
Note:
a Weighted by ship populations from 2005 ARB survey: 95 percent slow speed and 5 percent
medium speed.
3.3.3.2 Interport Domestic Traffic
As previously noted, STEEM includes the emissions associated with ships that are
engaged in foreign commerce. As a result, U.S.-flagged vessels carrying domestic cargo (Jones
Act ships) are not included. The STEEM interport analysis also roughly estimated the emissions
associated with these ships that are engaged solely in domestic commerce.1'4 Specifically, the
interport analysis estimated that the large ocean-going vessels carrying only domestic cargo
excluded from STEEM represent approximately 2-3 percent of the total U.S. emissions.
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Regulatory Impact Analysis
In Section 3.3.2.5, in the estimation of port inventories, the estimate of excluded installed
power was roughly 6.5 percent. It is not inconsistent that the STEEM estimate of excluded
emissions is lower than the excluded power estimated from calls to U.S. ports, since the STEEM
model includes ships that are transiting without stopping at U.S. ports. Since most of the Jones
Act ships tend to travel closer along the coast line, most of the Jones Act ship traffic is expected
to fall within the proposed EGA. Therefore, the results presented in this chapter are expected to
underpredict the benefits of the proposed EGA.
3.3.3.3 Combining the Near Port and Interport Inventories
The national and regional inventories in this study are a combination of the results from
the near ports analysis described in Section 3.3.2 and the STEEM interport modeling described
in this section. The two inventories are quite different in form. As previously presented in
Figure 3-1, the STEEM modeling domain spans the Atlantic and Pacific Oceans in the northern
hemisphere. The model characterizes emissions from vessels while traveling between ports.
That includes when a vessel is maneuvering a distance of 20 kilometers to enter or exist a port,
cruising near a port as it traverses the area, or moving in a shipping lane across the open sea. For
the U.S., STEEM includes the emissions associated with 251 ports. The results are spatially
reported in a gridded format that is resolved to a cell dimension of 4 kilometers by 4 kilometers.
The near port results, however, are much more geographically limited and are not
reported in a gridded format. The analysis includes the emissions associated with ship
movements when entering or exiting each of 117 major U.S. ports. For deep sea ports that
includes when a vessel is hotelling and maneuvering in the port, operating in the RSZ that varies
in length for each port, and cruising 25 nautical miles between the end of the RSZ and an
unconstrained shipping lane. For Great Lakes ports that includes hotelling and maneuvering,
three nautical miles of RSZ operation, and cruising 7 nautical miles between the end of the RSZ
and open water. The results are reported for each port and mode of operation.
To precisely replace only the portion of the STEEM interport inventory that is
represented in the near port inventory results, 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, the two inventories can be blended together. Both of these
processes are described below. This work was conducted by ENVIRON International as a
subcontractor under the EPA contract with IGF.2
3.3.3.3.1 Spatial Location of the Near Port Inventories
The hotelling, maneuvering, RSZ, and cruise emissions from the near port inventories
were spatially located by their respective latitude and longitude coordinates using ArcGIS
software. For this study, shapefiles were created that depicted the emission locations as
described above. Additional shapefiles were also obtained to locate other geographic features
such as the coastline and rivers of the U.S. These shapefiles and the STEEM output can be
layered upon each other, viewed in ArcMap, and analyzed together. The following sections
provide a more detailed description of how the shapefiles representing the ports, RSZ lanes, and
cruise lanes were developed.
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Chapter 3: Emission Inventory
3.3.3.3.1.1 Ports
Each port, and thus the designated location for hotelling and maneuvering emissions, is
modeled as a single latitude/longitude coordinate point using the port center as defined by the
Army Corp of Engineers in the Principal Ports of the United States dataset.11 One additional
port, "Other Puget Sound," which was specially created in the near ports analysis, was added to
the list of ports. Some port locations were inspected by consulting Google Earth satellite images
to ensure that the point that defined the port's location was physically reasonable for the
purposes of this analysis. This resulted in slightly modifying the locations of five ports: Gray's
Harbor, Washington; Freeport and Houston, Texas; Jacksonville, Florida; and Moreshead City,
North Carolina. In all five cases the change was very small. The hotelling 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, or 4 kilometers by 4 kilometers.
The coordinates of all of the 117 ports used in this work are shown in the Appendix, Table
3-102.
3.3.3.3.1.2 Reduced Speed Zone Operation
The RSZ routes associated with each of the 117 ports were modeled as lines. Line
shapefiles were constructed using the RSZ distance information described in Section 3.3.2 and
the Army Corp of Engineers National Waterway Network (NWN) geographic database of
navigable waterways in and around the U.S.16 The coordinates of RSZ endpoints for all of the
117 ports used in this work are shown in the Appendix, Table 3-103.
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. Figure 3-4 illustrates how the length of the RSZ line can vary in any grid cell.
In several instances the NWN links and STEEM data indicated there were two RSZs.
These ports are: Honolulu, Hawaii; Los Angeles, Long Beach and El Segundo, California;
Brunswick, Georgia; and Baton Rouge, New Orleans, Port of South Louisiana, and Plaquemines,
Louisiana. The lengths of the two lines were similar in every case, so the RSZ emissions from
the near ports analysis were divided equally between both branches. Figure 3-5 shows an
example of a port with multiple RSZs.
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Regulatory Impact Analysis
Figure 3-4 Example of Gridded RSZ Lane (Hopewell, Virginia)
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Chapter 3: Emission Inventory
Figure 3-5 Example of Multiple RSZ Lanes (Brunswick, Georgia)
3.3.3.3.1.3 Cruise Operations
The cruise mode links that extend 25 nautical miles for deep sea ports or 7 nautical miles
for Great Lake ports 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.
The STEEM data sometimes indicated there were two or three cruise mode links
associated with a port. In these cases, the underlying STEEM ship movement data was evaluated
to determine whether any particular route should be assigned larger emissions than the others.
That information was judged to be inadequate to justify such differential treatment, so the near
port cruise emissions for ports with multiple cruise lanes were assigned equally to each link.
Figure 3-6 provides an example of multiple cruise lanes.
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Figure 3-6 Example of Multiple Cruise Lanes
(Tampa and Port Manatee, Florida)
3.3.3.3.2 Combining the Near Port and STEEM Emission Inventories
After spatially defining the geographic location of the near port emissions, but before
actually inserting them into the gridded STEEM inventory, it was necessary to determine if all of
the 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.
This evaluation was performed for each port by first overlaying the RSZ and cruise
shapefiles on the STEEM gridded inventory, and then using ArcGIS tools to create a series of
circular buffers with a radius of 25 nautical miles around each of the points that represented an
RSZ line. A single elongated buffer was then made from the intersection or outer boundaries of
all the individual circular buffers. As illustrated in Figure 3-6, the resulting RSZ buffer encloses
the port, RSZ links and cruise mode links. The STEEM emissions underneath the buffer were
then evaluated. In cases where the STEEM data showed that ships were routed directly to an
isolated port, the STEEM emissions were completely replaced by near port emissions (Figure
3-7). Conversely, when the examination revealed that the underlying STEEM emissions
included some ship passages that were simply traversing near the port, the emissions associated
with those vessel movements were retained, i.e., not completely replaced with the near port
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Chapter 3: Emission Inventory
emission results (Figure 3-8). The methodology for determining the emissions from transient
ship operation is described below.
Figure 3-7 Example of Complete Replacement of STEEM Emissions
(Panama City, Florida)
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Figure 3-8 Example of Partial Replacement of STEEM Emissions
(Coos Bay, Oregon)
The percentage of STEEM emissions that are attributable to a port, and should be
replaced, were approximated by dividing the STEEM emissions in the isolated portion of the
route that lead only to the port, with the STEEM emissions in the major shipping lane. As an
example, the STEEM emissions in the portion of the buffer in Figure 3-8 that only went to the
port were approximately 347 kg/cell/year. The emissions within the buffer for just the major
shipping lane were 6996 kg/cell/year. Therefore, the emissions in the grid cells that comprised
the portion of the buffer overlaying the major shipping lane were reduced by the fraction
347/6996, or 5 percent before the near port emissions were added to the gridded inventory.
The actual merging of the two inventories was performed by creating a number of
databases that identified the fraction of the near 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. 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.
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Chapter 3: Emission Inventory
Figure 3-9 provides side-by-side comparisons of the original STEEM emissions
inventory and the new merged inventory. The results indicate that the spatial allocation of the
near port emissions conducted in this study provides a more precise assessment of vessel travel
near a port than the STEEM methodology. As previously described, the near port ship emissions
may be over specified, but this approach generally provides a more reasonable placement of
emissions near the coastline than the wide shipping lanes in the STEEM model, which in some
cases show shipping emissions over land.
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Original
Gecrgetom, SC
New
Figure 3-9 Spatial Comparison of the Original STEEM and New Combined Gridded Inventories
Southeast United States
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Chapter 3: Emission Inventory
3.3.4 2002 Baseline Emission Inventories
The modeling domain of the new combined emission inventory described above is the
same as the original STEEM domain, i.e., the Atlantic and Pacific Oceans, the Gulf of Mexico,
the Great Lakes, Alaska and Hawaii. Inventories for the nine geographic regions of the U.S.
specified in Section 3.2 were created using ArcGIS software to intersect the regional shapefiles
with the 4 kilometers by 4 kilometers gridded domain. Any grid cell split by a regional boundary
was considered to be within a region if over 50 percent of its area was within the region. The
emissions in each of the cells defined within a region were then summed. The final emission
inventories for 2002 are shown in Table 3-56 for each of the nine geographic regions and the
nation. The geographic scope of these regions was previously displayed in Figure 3-1. The fuel
consumption by fuel type associated with each region is also provided in Table 3-57.
Table 3-56 2002 Regional and National Emissions from Category 3 Vessel Main and Auxiliary Engines
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)
Total Metric Tonnes
Total Short Tons b
Metric Tonnes
NOX
18,051
60,019
219,560
172,897
22,600
31,799
26,037
104,155
15,019
670,137
738,700
PM10
1,425
4,689
17,501
14,043
1,775
2,498
2,154
8,094
1,179
53,358
58,817
PM25a
1,311
4,313
16,101
12,920
1,633
2,297
1,982
7,447
1,085
49,089
54,112
HC
597
1,989
7,277
5,757
749
1,053
938
3,464
498
22,322
24,606
CO
1,410
4,685
17,231
14,169
1,765
2,484
2,090
8,437
1,174
53,445
58,913
S02
10,618
34,786
145,024
104,852
13,182
18,546
15,295
60,443
8,766
411,512
453,614
C02
657,647
2,143,720
8,131,553
6,342,139
818,571
1,151,725
990,342
3,796,572
541,336
24,573,605
27,087,763
Notes:
a Estimated from PM10 using a
b Converted from metric tonnes
multiplicative adjustment factor of 0.92.
using a multiplicative conversion factor of 1.102 short tons per metric tonne.
Table 3-57 2002 Regional and National Fuel Consumption
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)
Total Metric Tonnes
Total Short Tons0
Metric Tonnes Fuel
Distillate
1,887
0
91,529
63,876
4,375
0
15,905
35,052
1,270
213,894
235,778
Residual
204,725
673,490
2,463,153
1,928,628
252,794
361,836
295,230
1,157,714
168,801
7,506,371
8,274,358
Total
206,612
673,490
2,554,682
1,992,504
257,170
361,836
311,135
1,192,765
170,071
7,720,265
8,510,136
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As previously noted, the inventories in the above table reflect the emissions associated
with Category 3 ocean-going vessels that are engaged in foreign commerce. The STEEM
interport analysis also roughly estimated the emissions associated with these ships that are
engaged solely in domestic commerce.1'4 These vessels are sometimes referred to as Jones Act
ships, as explained in Section 3.3.2.5. Specifically, the interport analysis estimated that the
emissions from large ocean-going vessels carrying only domestic cargo represent approximately
2-3 percent of the total values presented in Table 3-56. This is less than the 6.5 percent estimate
based on calls to U.S. ports, since the interport traffic includes transiting traffic in U.S. waters.
The relative contributions of the near port and interport emission inventories to the total
U.S. emissions are presented in Table 3-58 and Table 3-59. As expected, based on the
geographic scope of the two types of inventories, the interport and near port inventories are about
80 percent and 20 percent of the total, respectively. The deep sea ports are about 97 to nearly
100 percent and the Great Lake ports are about 3 to almost zero percent of the total inventories,
depending on the port region. This result is also expected given the small number of Great Lake
ports and more limited geographic area of the modeling domain.
Table 3-58 2002 Contribution of Near Ports and Interport Emissions to the Total C3 Inventory
Region and
Port Type
Interport
Deep Sea
Great Lakes
Near Port
Deep Sea
Great Lakes
All Regions
Deep Sea
Great Lakes
All Region
Short Tons b
Metric Tonnes
NOX
Total
549,852
535,325
14,528
120,285
119,793
491
670,137
655,118
15,019
738,700
%
Region
82.1
—
~
17.9
—
~
100
—
~
%
Type
100
97.4
2.6
100
99.6
0.4
~
97.8
2.2
PM10
Total
42,945
41,811
1,135
10,413
10,368
44
53,358
52,179
1,179
58,817
%
Region
80.5
—
~
19.5
—
~
100
—
~
%
Type
100
97.4
2.6
100
99.6
0.4
~
97.8
2.2
PM25a
Total
39,510
38,465
1,044
9,580
9,539
41
49,089
48,004
1,085
54,112
%
Region
80.5
—
~
19.5
—
~
100
—
~
%
Type
100
97.4
2.6
100
99.6
0.4
~
97.8
2.2
Notes:
a Estimated from PM10 using a multiplicative adjustment factor of 0.92.
b Converted from metric tonnes using a multiplicative adjustment factor of 1.102 short tons per metric tonne.
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Chapter 3: Emission Inventory
Table 3-59 2002 Contribution of Near Ports and Interport Emissions to the Total C3 Inventory (Cont'd)
Region and
Port Type
Interport
Deep Sea
Great Lakes
Near Port
Deep Sea
Great Lakes
All Regions
Deep Sea
Great Lakes
All Region Short
Tonsa
Metric Tonnes
HC
Total
18,219
17,738
481
4,103
4,086
17
22,322
21,824
498
24,606
%
Region
81.6
—
~
18.4
—
~
100
—
~
%
Type
100
97.4
2.6
100
99.6
0.4
~
97.8
2.2
CO
Total
42,912
41,778
1,134
10,533
10,493
40
53,445
52,271
1,174
58,913
%
Region
80.3
—
~
19.7
—
~
100
—
~
%
Type
100
97.4
2.6
100
99.6
0.4
~
97.8
2.2
S02
Total
318,450
310,030
8,420
93,062
92,716
346
411,512
402,746
8,766
453,614
%
Region
77.4
—
~
22.6
—
~
100
—
~
%
Type
100
97.4
2.6
100
99.6
0.4
—
97.9
2.1
Note:
a Converted from metric tonnes using a multiplicative adjustment factor of 1.102 short tons per metric tonne.
3.4 Development of 2020 and 2030 Scenarios
3.4.1 Outline of Methodology
The emissions from Category 3 ocean-going and Great Lakes vessels (main propulsion
and auxiliary engines) are projected to 2020 and 2030 by applying certain adjustment factors to
the 2002 emission inventories to account for the change in ship traffic over these time periods,
i.e., growth, and the effect of the current controls and the NOx and fuel controls described in the
final rule.
The following sections describe the derivation of the growth adjustment factors for each
of the modeling regions described in Section 3.2, the emission adjustment factors, and the
resulting 2020 and 2030 emission inventories.
The final section describes the baseline and control emission inventories that were
developed for calendar years 2020 and 2030. The 2030 inventories were used for air quality
modeling, although the 2020 control inventories reported here have been updated relative to
those used for the air quality modeling. A comparison of the 2020 control case inventories
reported here with those used for the air quality modeling is provided in Section 3.7.
3.4.2 Growth Factors by Geographic Region
This section describes the growth factors that are used to project the emissions to 2020
and 2030 for each of the nine geographic regions evaluated in this analysis. These factors 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. 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
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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 EPA
(Section 3.4.2.1).5'6 This is followed by the derivation of the growth factors that are used in this
study for the nine geographic regions of interest (Section 3.4.2.9).
3.4.2.1 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
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 3-10 from RTI illustrates the
approach to developing baseline projections of marine fuel consumption.
As a means of comparison, the IMO Secretary General's Informal Cross
Government/Industry Scientific Group of Experts presented a growth rate that ranged from 3.3%
to 3.7%.46 RTFs overall U.S. growth rate was projected at 3.4%, which is consistent with that
range.
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Chapter 3: Emission Inventory
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 Buildb
Engine Load Factors0
Average Cargo /T\
Carried (Tons) \^J
Average Daily Fuel
> Consumption
(Tons/Day)
Average Daily Fuel
Consumption (Tons/Day) *fo\
- Main, Aux. Engine at Sea *V_V
-Aux. Engine in Port
Trade Analysis: by Commodity and Trade Route
Inputs
Average Ship Speed0
Round Trip Mileage"
Tons of Cargo Shipped*5
Average Cargo Carried/' N
per Ship Voyage \^
Outputs
Days at Sea and in
, Port, per Voyage
Total Days at J^c\
, '' Sea and in Port \^J
>• Number of Voyages
Total Estimated Bunker Fuel Demand
/• N
Average Daily Fuel Consumption
(Tons/Day) Total Days at Sea Bunker Fuel
- Main, Aux. Engine at Sea (^T\ and in Port f^\ Demand
- Aux. Engine in Port \^_^ \^_^
\^ J
Driven by changes in engine efficiency. Driven ^ f ™th in
commodity flows.
a - Clarksons Ship Register Database
b - Engine Manufacturers' Data, Technical Papers
c - Corbett and Wang (2005) "Emission Inventory Review: SECA Inventory Progress Discussion"
d - Combined trade routes and heavy leg analysis
e - Global Insight Inc. (Gil) Trade Flow Projections
Figure 3-10 Illustration of Method for Estimating Bunker Fuel Demand
3.4.2.2 Trade Analysis
The trade flows between geographic regions of the world, as illustrated by the middle
portion of Figure 3-10, were defined for the following eight general types of commodities:
- liquid bulk - crude oil
liquid bulk - refined petroleum products
liquid bulk - residual petroleum products
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- liquid bulk - chemicals (organic and inorganic)
liquid bulk -gas (including LNG and LPG)
- 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
3-60 shows the countries associated with each region.
Table 3-60 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
Note:
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.47
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Chapter 3: Emission Inventory
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
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 flows assumes a country's imports from another country are
driven by the importing country's demand forces (given that the exporting country possesses
enough supply capacity), and affected by exporting the country's export price and importing
country's import cost for the commodity. The model then estimates demand forces, country-
specific exporting capacities, export prices, and import costs.
The GI model included 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 3-61 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, crude oil is 26 percent, and containers rise to 17 percent.
Table 3-61 Illustration of World Trade Estimates for Composite Commodities, 2005,2012, and 2020
Commodity Type
Diy 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
3.4.2.3 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. As shown at the top of Figure 3-10, 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.
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The eight GI commodity categories were mapped to the type of vessel that would be used
to transport that type of cargo using information from Clarksons Shipping Database.
assignments are shown in Table 3-62.
48
These
Table 3-62 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 3-63 summarizes the size categories that were used in the
analysis and provides other information on the general attributes of the vessels from Clarksons
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. Very
large crude oil tankers are the largest by DWT rating, and the biggest container ships (Suezmax)
are also very large.
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Chapter 3: Emission Inventory
Table 3-63 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
39.80
8.84
26.65
114.22
90.17
46.50
58.09
136.75
40.63
51.83
10.32
3.45
3.85
38.80
19.94
16.92
7.90
3.15
11.57
6.88
4.79
88.51
888.40
Total
Horse
Power
(millions)
8.56
29.30
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
3.60
4.19
2.56
1.54
5.63
2.55
3.74
53.60
308.96
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. Clarksons' 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).
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The specific 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 "test bed" or "catalogue" numbers 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,
used engines consume more fuel than brand new engines and in-service fuels may be different
than the test bed fuels.
49
Figure 3-11 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 standard as required by MARPOL Annex VI, or other potential pollution control
requirements.
200
180
160
140
120
100
80
60
40
20
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
Figure 3-11 Diesel Engine Specific Fuel Consumption
RTI assumed a fixed SFC of 220 g/HP-hr for steam engines operating on bunker fuel.
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:
3-106
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Chapter 3: Emission Inventory
Equation 3-27
Fleet AFCV_, =— £ [SFC^, x HPVS x 1 0~6 tonnes I g]
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/HP-hr)
HP = Total installed engine power, in horsepower (HP)
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 3-64 shows the engine load
factors that were used to estimate the typical average daily fuel consumption (tons/day) for the
main propulsion engine and the auxiliary engines when operated at sea and in port.50
Table 3-64 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
Percent of Main
Engine
22.0
19.1
22.2
21.1
21.1
21.1
21.1
20.0
Auxiliary Engine as
Percent 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 assumed 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.
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Regulatory Impact Analysis
• 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.
3.4.2.4 Trade Analysis by Commodity Type and Trade Route
Determining the total number of days at sea and in port, as shown in the middle portion
of Figure 3-10, 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 Clarksons 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 Section 3.4.2.5.)
The days at sea were calculated by dividing the round trip distance by the average vessel
speed:
Days at Sea Per Voyage
Equation 3-28
_ round trip distance route
speed vs x24hrs
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
Table 3-65 presents the speeds by vessel type that were used in the analysis.50 These
values are the same for all size categories, and are assumed to remain constant over the forecast
period.
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Chapter 3: Emission Inventory
Table 3-65 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 route for each trade was estimated for each vessel
type v and size category s serving a given route by dividing the tons of cargo moved by the
amount of cargo (DTW) per voyage:
Number of Voyagesv
s,trade
Equation 3-29
total metric tonnes of cargo moved
fleet average DWTV s x utilization rate
Where:
v = Vessel type
s = Vessel size category
trade = Commodity type
Fleet average DWT = Median dead weight tonnage carrying capacity in metric tons
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 estimated by assuming that most types of cargo vessels spend four days in port
per voyage. RTI notes, however, that this can vary somewhat by commodity and port.
3.4.2.5 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^ of the analysis, the total bunker fuel demand is the sum of the fuel consumed on
each route of each trade (commodity). The fuel consumed on each route of each trade is in turn
the sum of the fuel consumed for each route and trade for that year by propulsion main engines
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Regulatory Impact Analysis
and auxiliary engines when operated at sea and in port. These steps are illustrated by the
following equations:
Equation 3-30
y1 y1 T7/"1
trade, route, year
trade route
Z Z [ AFCtade)route>yatsea x Days at Seatade_routeiy + AFC^^^ x Days at PorttadeiIDUtejy ]
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 3-31
2 (Percent of trade along route)v s [Fleet AFCV s x (MELF+AE at sea LF)]
= v £ ^ (Percent of trade along route)v s [Fleet AFCV_, xAEimportLF]
Days at Seatade route = 2 (Percent of trade along route)v s [Days at sea per voyagev s x Number of voyagesv s
DaysatPort^^ = 2 (Percentof tradealongroute)vs[Daysatportpervoyage xNumberof voyages]
v,s,t,r
Where:
AFC = Average daily fuel consumption in metric tonnes
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
The inputs for these last four equations are all derived from the vessel analysis in Section 3.4.2.3
and the trade analysis in Section 3.4.2.2.
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Chapter 3: Emission Inventory
3.4.2.6 Worldwide Bunker Fuel Consumption
Based on the methodology outlined above, estimates of global fuel consumption over
time were computed, and growth rates determined from these projections. Figure 3-12 shows
estimated world-wide bunker fuel consumption by vessel type.
H Container ID General Cargo D Dry Bulk 0 Crude Oil
D Chemicals D Petroleum • Natural Gas D Other
• Fishing Vessels • Passenger Ships D Military Vessels
Figure 3-12 Worldwide Bunker Fuel Consumption
Figure 3-13 shows the annual growth rates by vessel-type/cargo that are used in the
projections shown in Figure 3-12. 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 of around 2.6 percent.
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Regulatory Impact Analysis
10%
a
3
pa
Oil
a
cs
JS
U
s.
01
OH
-O- Total
-A-Crude Oil
Other
• Container —•— General Cargo -•- Dry Bulk
Chemicals HK- Petroleum -•- Natural Gas
Fishing Vessels Passenger Ships Military Vessels
Figure 3-13 Annual Growth Rate in World-Wide Bunker Fuel Use by Commodity Type
3.4.2.7 Fuel Demand Used to Import and Export Cargo for the United States
The methodology described above provides an estimate of fuel consumption for
international cargo worldwide. RTI also estimated the subset of fuel demand for cargo imported
to and exported from five regions of the U.S. The five regions are:
• North Pacific
• South Pacific
• Gulf
• East Coast
• Great Lakes
For this analysis, the same equations were used, but were limited to routes that carried
cargo between specific cities in Asia, Europe and 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 from
Worldscale Association and Maritime Chain.51 The data from Worldscale is considered to be the
3-112
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Chapter 3: Emission Inventory
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
passed on the voyage.
Voyage distances for container vessels are based on information from Containerization
International Yearbook (CIY) and calculations by RTI. That reference 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
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 3-65 to find the length of a voyage in days. Table 3-66 presents the
day lengths for non-containerized vessel types and Table 3-67 shows the same information for
container vessels.
Table 3-66 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
US South
Pacific
68
49
56
48
37
11
95
41
61
53
54
26
35
77
52
68
64
51
US North
Pacific
75
56
63
47
46
5
89
36
68
60
61
33
31
72
48
64
71
30
US East
Coast
57
37
36
65
7
40
41
73
38
24
30
16
65
56
67
66
38
41
US Great
Lakes
62
43
46
81
18
58
46
87
45
32
37
29
81
65
76
64
46
46
US Gulf
54
47
43
63
19
39
48
69
46
34
37
17
62
83
88
73
48
44
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Regulatory Impact Analysis
Table 3-67 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)
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
37
37
41
61
48
54
43
68
64
68
38
42
38
63
80
3.4.2.8 Bunker Fuel Consumption for the United States
Figure 3-14 and Figure 3-15 present the estimates of fuel use for delivering trade goods
to and from the U.S. The results in Figure 3-14 show estimated historical bunker fuel use in year
2001 of around 47 million tons (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 grows to over 90 million tons by 2020 with the most growth occurring on trade routes
from the East Coast and the "South Pacific" region of the West Coast.
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Chapter 3: Emission Inventory
B US North Pacific ffi US Great Lakes D US Gulf 8 US East Coast 1 US South Pacific
Figure 3-14 Bunker Fuel Used to Import and Export Cargo by Region of the United States
Figure 3-15 shows the estimated annual growth rates for the fuel consumption that are
used in the projections shown in Figure 3-14. Overall, the average annual growth rate in marine
bunkers associated with future U.S. trade flows is 3.4 percent between 2005 and 2020.
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Regulatory Impact Analysis
10%
8%
6%
a
o
"a
-o-United States
•*• US Great Lakes
• US South Pacific
• US Gulf
•US North Pacific
• US East Coast
Figure 3-15 Annual Growth Rates for Bunker Fuel Used to Import and Export Cargo by Region of the
United States
3.4.2.9 2020 and 2030 Growth Factors for Nine Geographic Regions
The results of the RTI analysis described above are used to develop the growth factors
that are necessary to project the 2002 base year emissions inventory to 2020 and 2030. The next
two sections describe how the five RTI regions were associated with the nine regions analyzed in
this report, and how the specific growth rates for each of the nine regions were developed.
3.4.2.9.1 Mapping the RTI Regional Results to the Nine Region Analysis
As described in Section 3.3.4, the nine geographic regions analyzed in this study were
designed to be consistent with the five RTI regional modeling domains. More specifically, four
of the nine geographic areas in this study, i.e., Alaska East, Alaska West, Hawaii East, and
Hawaii West are actually subsets of two broader regional areas that were analyzed by RTI, i.e.,
the North Pacific for both Alaska regions and South Pacific for Hawaii. Therefore, the growth
rate information from the related larger region was assumed to be representative for that state.
The nine geographic regions represented in the emission inventory study are presented in
Figure 3-1. The association of the RTI regions to the emission inventory regions is shown in
Table 3-68.
5-116
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Chapter 3: Emission Inventory
Table 3-68 Association of the RTI 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)
3.4.2.9.2 Growth Factors for the Emission Inventory Analysis
Emission inventories for 2020 and 2030 are estimated in Section 3.4.5 by multiplying the
2002 baseline inventory for each region by a corresponding growth factor that was developed
from the RTI regional results. Specifically, the average annual growth rate from 2002-2020 was
calculated for each of the five regions. Each regional growth rate was then compounded over the
inventory projection time period for 2020 and 2030, i.e., 18 and 28 years, respectively. The
resulting multiplicative growth factors for each emission inventory region and the associated RTI
average annual growth rate are presented in Table 3-69 for each projection year.
Table 3-69 Regional Emission Inventory Growth Factors for 2020 and 2030
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
Annuali/ed
Growth Rate
(%)
3.3
3.3
4.5
2.9
5.0
5.0
3.3
5.0
1.7
Multiplicative Growth
Factor Relative to 2002
2020
1.79
1.79
2.21
1.67
2.41
2.41
1.79
2.41
1.35
2030
2.48
2.48
3.43
2.23
3.92
3.92
2.48
3.92
1.60
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Regulatory Impact Analysis
3.4.3 Emission Controls in Baseline and Control Scenarios
This section describes the control programs present in the baseline and control scenarios,
as well as the resulting emission factors.
The baseline scenario includes the International Marine Organization's (IMO) Tier 1
NOx standard for marine diesel engines that became effective in 2000. The control scenario
applies global controls as well as additional EGA controls within the EGA boundaries
The global NOx controls include a retrofit program for Tier 0 (pre-control) engines,
which was modeled as 11 percent control from Tier 0 for 80 percent of 1990 thru 1999 model
year (MY) engines greater than 90 liters per cylinder (L/cyl) starting in 2011. The retrofit
program was also modeled with a five year phase-in. The current Tier 1 controls, which also are
modeled as achieving an 11 percent reduction from Tier 0, apply to the 2000 thru 2010 MY
engines. In 2011 thru 2015, Tier 2 controls are applied. Tier 2 controls are modeled as a 2.5
g/kW-hr reduction from Tier 1. Fuel sulfur content for the global control area is assumed to be
controlled to 5,000 ppm. No controls are assumed for HC or CO.
Within the EGA areas, additional Tier 3 NOx controls are applied for 2016 MY engines
and beyond. Tier 3 controls are modeled as achieving an 80 percent reduction from Tier 1
levels. Note that gas and steam turbine engines are not subject to any of the NOx standards;
however, these engines are not a large part of the inventory. Note also that the emission control
scenarios described in this chapter do not consider the exemption of Great Lakes steamships
from the final fuel sulfur standards. This change to the program is also not expected to have a
significant impact on national inventory estimates. We intend to follow up with a more detailed
study of the impacts of the emission control program on Great Lakes carriers which may provide
information that will help us refine our Great Lakes emission inventories.
Fuel sulfur content is also assumed to be controlled to 1,000 ppm, for all vessels, within
the EGA in 2020 and 2030. Fuel sulfur content affects SO2 and PM emissions.
Within the control scenario, global controls are applied for the Alaska West and Hawaii
West regions. Global controls are also applied beyond 200 nm from shore for the 48 contiguous
states, Alaska East, and Hawaii East. The EGA controls are applied within 200 nm from shore
for the 48 contiguous states as well as the Alaska East and Hawaii East regions.
3.4.3.1 2020 and 2030 Emission Factors
The baseline scenario described in the previous section includes Tier 1 NOx control. The
control scenario includes additional NOX controls and fuel sulfur controls, the latter affecting PM
and SO2 emissions. The switch to lower sulfur distillate fuel use is also assumed to lower CO2
emissions slightly. HC and CO are assumed to remain unchanged.
The NOX emission factors (EFs) by engine/ship type and tier are provided in Table 3-70.
Tier 0 refers to pre-control. There are separate entries for Tier 0/1 base and Tier 0/1 control,
since the Tier 0/1 control engines would be using distillate fuel, and there are small NOx
3-118
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Chapter 3: Emission Inventory
emission reductions assumed when switching from residual to distillate fuel.
EFs by tier were derived using the assumptions described in Section 3.4.3.
21
The NOX control
Table 3-70 Modeled NOX Emission Factors by Tier
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
NOX EF (g/kW-hr)
Baseline
TierO
18.1
14
2.1
6.1
14.6
14.5
Tierl
16.1
12.5
n/a
n/a
13.0
12.9
Control Areas
TierO
17
13.2
2
5.7
14.6
14.5
TO
retrofit a
15.1
11.7
n/a
n/a
n/a*
n/a*
Tierl
15.1
11.7
n/a
n/a
13
12.9
Tier 2
12.6
9.2
n/a
n/a
10.5
10.4
Tier 3
3
2.3
n/a
n/a
2.6
2.6
Note:
a The retrofit program applies to engines over 90 L/cyl; auxiliary engines are smaller than this
outpoint and would therefore not be subject to the program.
The NOx EFs by tier were then used with the age distributions in Table 3-71 and Table
3-72 below to generate calendar year NOx EFs by engine/ship type for the base and control areas
included in the scenarios. These calendar year NOx EFs are provided in Table 3-73. Since the
age distributions are different for vessels in the Great Lakes, NOx EFs were determined
separately for the Great Lakes.
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Regulatory Impact Analysis
Table 3-71 Vessel Age Distribution for Deep Sea 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
0.00570
0.07693
0.10202
0.08456
0.08590
0.06427
0.06024
0.07867
0.06730
0.04181
0.04106
0.03100
0.04527
0.03583
0.03519
0.02921
0.00089
0.01326
0.00847
0.00805
0.00566
0.00495
0.00503
0.00676
0.00539
0.01175
0.00803
0.00522
0.00294
0.00285
0.00254
0.00084
0.00023
0.00117
0.00132
0.01967
SSD
0.02667
0.07741
0.07512
0.07195
0.05504
0.05563
0.04042
0.07266
0.05763
0.04871
0.04777
0.03828
0.03888
0.02787
0.02824
0.01466
0.01660
0.01582
0.02414
0.01982
0.02258
0.02945
0.01883
0.01080
0.01091
0.01099
0.01045
0.00835
0.00788
0.00370
0.00106
0.00113
0.00367
0.00582
0.00092
0.00013
GT
0.00000
0.07189
0.14045
0.05608
0.67963
0.04165
0.00000
0.00626
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
0.00034
0.00370
0.00000
0.00000
0.00000
0.00000
0.00000
ST
0.00447
0.12194
0.16464
0.05321
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.04873
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00875
0.00883
0.00883
0.18029
0.11065
0.01395
0.08657
0.02907
0.05126
0.00605
0.07105
0.00000
0.00000
0.03172
All
Auxiliary
Engines
0.01958
0.07670
0.08426
0.07489
0.07831
0.05685
0.04455
0.07150
0.05764
0.04475
0.04364
0.03538
0.04160
0.02909
0.02935
0.01869
0.01189
0.01462
0.01966
0.01550
0.01756
0.02260
0.01467
0.00943
0.00900
0.01224
0.01130
0.00738
0.00659
0.00349
0.00193
0.00096
0.00322
0.00419
0.00098
0.00598
Note:
a MSD is medium speed diesel, SSD is slow speed diesel, GT is gas turbine, ST is steam turbine.
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Chapter 3: Emission Inventory
Table 3-72 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
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
SSD
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
ST
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
Notes:
a MSD is medium speed diesel, SSD is slow speed diesel, GT is gas turbine, ST is steam
turbine.
b Fleet average weighted by installed power (ship port calls x main propulsion engine power).
5-121
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Regulatory Impact Analysis
Table 3-73 Modeled NOX Emission Factors by Calendar Year and Control Type
Engine/
Ship
Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
CY NOX EF (g/kW-hr)
2002
18.1
14
2.1
6.1
14.6
14.5
2020 Base
DSPa
16.36
12.58
2.1
6.1
13.21
13.06
GLb
17.12
13.64
2.1
n/ac
14.13
13.97
2020 ECA
Control
DSP
10.80
7.72
2.0
5.7
8.59
8.59
GL
13.07
11.79
2.0
n/a
11.99
11.99
2020 Global
Control
DSP
13.74
10.17
2.0
5.7
n/a
n/a
GL
14.95
12.44
2.0
n/a
n/a
n/a
2030 Base
DSP
16.13
12.50
2.1
6.1
13.05
12.90
GL
16.73
12.74
2.1
n/a
13.61
13.46
2030 ECA
Control
DSP
5.68
3.58
2.0
5.7
4.39
4.39
GL
10.44
9.95
2.0
n/a
10.30
10.30
2030 Global
Control
DSP
13.00
9.49
2.0
5.7
n/a
n/a
GL
14.20
11.44
2.0
n/a
n/a
n/a
Notes:
a DSP = Deep sea ports and areas other than the Great Lakes
b GL = Great Lakes
0 n/a = not applicable. There are no GT engines assumed to be operating in the Great Lakes. Auxiliary engines are assumed to be
operating in ports and therefore not subject to global controls.
For PM and SO2, there are no proposed standards; however, the control of fuel sulfur
affects these pollutants. Therefore, the PM and SO2 EFs are strictly a function of fuel sulfur
level. For the baseline portions of the inventory, there are two residual fuel sulfur levels
modeled: 25,000 ppm for the West Coast and 27,000 ppm for the rest of the U.S. The baseline
distillate fuel sulfur level assumed for all areas is 15,000 ppm. As discussed in Section 3.3.2.3.5,
for the baseline, main engines use residual fuel and auxiliary engines use a mix of residual and
distillate fuel. For the control areas, there are two levels of distillate fuel sulfur assumed to be
used by all engines: 5,000 ppm for the global control areas and 1,000 ppm for the ECA control
areas.
Table 3-74 provides the PMio EFs by engine/ship type and fuel sulfur level. For
modeling purposes, PM2 5 is assumed to be 92 percent of PMi0. The PM EFs are adjusted to
reflect the appropriate fuel sulfur levels using the equation described in Section 3.3.2.3.6.
Table 3-75 provides the modeled SO2 EFs. SO2 emission reductions are directly
proportional to reductions in fuel sulfur content.
CO2 is directly proportional to fuel consumed. Table 3-76 provides the modeled CO2 and
brake specific fuel consumption (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, CO2 emissions.21
3-122
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Chapter 3: Emission Inventory
Table 3-74 Modeled PM,0 Emission Factors*
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
PM10 EF (g/kW-hr)
Baseline
Other than
West Coast
27,000 ppm S
1.40
1.40
1.50
1.50
1.40
1.20
West Coast3
25,000 ppm S
1.40
1.40
1.40
1.40
1.30
1.10
Control Areas
ECA
5,000 ppm S
0.31
0.31
0.35
0.35
0.31
0.31
Global Control
1,000 ppm S
0.19
0.19
0.17
0.17
0.19
0.19
Note:
aFor the base cases, the West Coast fuel is assumed to be used in the following
regions: Alaska East (AE), Alaska West (AW), Hawaii East (HE), Hawaii West
(HW), North Pacific (NP), and South Pacific (SP).
Table 3-75 Modeled SO2 Emission Factors*
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
SO2 EF (g/kW-hr)
Baseline
Other than
West Coast
27,000 ppm S
10.29
11.09
16.10
16.10
10.70
9.66
West Coast3
25,000 ppm S
9.53
10.26
14.91
14.91
9.93
9.07
Control Areas
ECA
5,000 ppm S
1.81
1.96
2.83
2.83
1.96
1.96
Global
Control
1,000 ppm S
0.36
0.39
0.57
0.57
0.39
0.39
Note:
aFor the base cases, the West Coast fuel is assumed to be used in the following
regions: Alaska East (AE), Alaska West (AW), Hawaii East (HE), Hawaii West
(HW), North Pacific (NP), and South Pacific (SP).
5-123
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Regulatory Impact Analysis
Table 3-76 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
305
210
210
C02
620.62
668.36
970.71
970.71
668.36
668.36
Control Areas
BSFC
185
200
290
290
200
200
C02
588.86
637.05
923.07
923.07
636.60
636.60
3.4.4 Calculation of Near Port and Interport Inventories
Based on the emission factors described in Section 3.4.3.1, appropriate growth factors
and emission adjustment factors were applied to the 2002 baseline inventory to obtain the NOx,
PM (PMio and PM2.5), SO2, and CO2 inventory of each 2020 and 2030 scenario. Adjustment
factors are ratios of the 2020 or 2030 calendar year EFs to the 2002 calendar year 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. This section describes the development
and application of the adjustment factors to the port and interport inventories, and the
methodology for combining the port and interport portions.
3.4.4.1 Port Methodology
3.4.4.1.1 Non-California Ports
For the non-California ports, 2002 emissions for each port are summed by engine/ship
type. Propulsion and auxiliary emissions are summed separately, since the EF adjustment factors
differ. The appropriate regional growth factor, as provided in Table 3-69, is then applied, along
with EF adjustment factors by engine/ship type. The EF adjustment factors are a ratio of the
control EF to the 2002 EF. Table 3-77 thru Table 3-81 provide the EF adjustment factors for
each pollutant and control area. The ports will be subject to EGA controls in the control
scenarios. These tables are also used as input for the California ports and interport control
inventory development, discussed in subsequent sections. Since the control scenario assumes a
portion of the inventory is subject to global controls, the adjustment factors for the 2020 and
2030 global controls are also provided. The baseline adjustment factors are also provided.
3-124
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Chapter 3: Emission Inventory
Table 3-77 NOX EF Adjustment Factors by Engine/Ship Type and Control Type3
Engine/
Ship
Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
2020 Base
DSPb
0.9037
0.8987
1.0000
1.0000
0.9025
0.9025
GLC
0.9459
0.9744
1.0000
n/a
0.9657
0.9657
2020 ECA
Control
DSP
0.5967
0.5515
0.9524
0.9344
0.5869
0.5940
GL
0.7219
0.8423
0.9524
n/a
0.8196
0.8295
2020 Global
Control
DSP
0.7592
0.7265
0.9524
0.9344
n/a
n/a
GL
0.8261
0.8883
0.9524
n/a
n/a
n/a
2030 Base
DSP
0.8913
0.8926
1.0000
1.0000
0.8917
0.8917
GL
0.9243
0.9101
1.0000
n/a
0.9301
0.9301
2030 ECA
Control
DSP
0.3138
0.2559
0.9524
0.9344
0.3003
0.3039
GL
0.5771
0.7109
0.9524
n/a
0.7042
0.7127
2030 Global
Control
DSP
0.7183
0.6776
0.9524
0.9344
n/a
n/a
GL
0.7847
0.8170
0.9524
n/a
n/a
n/a
Notes:
a NOX adjustment factors are a ratio of future base or control EFs to 2002 EFs
b DSP = deep sea ports and areas other than the Great Lakes
c GL = Great Lakes
Table 3-78 PM10 EF Adjustment Factors by Engine/Ship Type and Control Type
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
Base
Otherb
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
wcc
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
ECA Control
Other
0.1352
0.1328
0.1108
0.1108
0.1328
0.1550
we
0.1352
0.1328
0.1187
0.1187
0.1430
0.1691
Global Control
Other
0.2183
0.2227
0.2324
0.2324
0.2227
0.2598
we
0.2183
0.2227
0.2490
0.2490
0.2398
0.2834
Notes:
a PM10 adjustment factors are a ratio of the control EFs to the baseline EFs. PM is not
adjusted for the future baselines because fuel sulfur levels are only assumed to
change within the ECA and global control areas.
b Other = Other than West Coast
0 WC = Ports/areas within the West Coast. This includes the regions of Alaska,
Hawaii, North Pacific, and South Pacific.
5-125
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Regulatory Impact Analysis
Table 3-79 PM2.S EF Adjustment Factors by Engine/Ship Type and Control Type"
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
Base
Otherb
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
wcc
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
ECA Control
Other
0.1339
0.1316
0.1092
0.1092
0.1316
0.1555
we
0.1339
0.1316
0.1176
0.1176
0.1426
0.1711
Global Control
Other
0.2163
0.2207
0.2291
0.2291
0.2207
0.2608
we
0.2163
0.2207
0.2467
0.2467
0.2390
0.2868
Notes:
a PM2.5 adjustment factors are a ratio of the control EFs to the baseline EFs. PM is
not adjusted for the future baselines because fuel sulfur levels are only assumed to
change within the ECA and global control areas. The PM2 5 adjustment factors are
slightly different from those for PM10 due to rounding.
b Other = Other than West Coast
0 WC = Ports/areas within the West Coast. This includes the regions of Alaska,
Hawaii, North Pacific, and South Pacific.
Table 3-80 SO2 EF Adjustment Factors by Engine/Ship Type and Control Type3
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
Base
Otherb
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
wcc
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
ECA Control
Other
0.0351
0.0353
0.0352
0.0352
0.0365
0.0405
WC
0.0380
0.0381
0.0380
0.0380
0.0394
0.0431
Global Control
Other
0.1757
0.1764
0.1761
0.1761
0.1827
0.2024
WC
0.1898
0.1907
0.1901
0.1901
0.1969
0.2156
Notes:
a SO2 adjustment factors are a ratio of the control EFs to the baseline EFs. SO2 is
not adjusted for the future baselines because fuel sulfur levels are only assumed to
change within the ECA and global control areas.
b Other = Other than West Coast
0 WC = Ports/areas within the West Coast. This includes the regions of Alaska,
Hawaii, North Pacific, and South Pacific.
3-126
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Chapter 3: Emission Inventory
Table 3-81 CO2 EF Adjustment Factors by Engine/Ship Type and Control Type
Engine/
Ship Type
Main
SSD
MSD
ST
GT
Aux
Pass
Other
Base
Otherb
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
wcc
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
ECA Control
Other
0.9488
0.9531
0.9509
0.9509
0.9525
0.9525
we
0.9488
0.9531
0.9509
0.9509
0.9593
0.9683
Global Control
Other
0.9488
0.9531
0.9509
0.9509
0.9525
0.9525
we
0.9488
0.9531
0.9509
0.9509
0.9593
0.9683
Notes:
a CO2 adjustment factors are a ratio of the control EFs to the baseline EFs. CO2 is not
adjusted for the future baselines because fuel consumption (BSFC) is only assumed
to change within the ECA and global control areas.
b Other = Other than West Coast
0 WC = Ports/areas within the West Coast. This includes the regions of Alaska,
Hawaii, North Pacific, and South Pacific.
3.4.4.1.2 California Ports
For the California ports, 2002 emissions for each port are summed by ship type.
Propulsion and auxiliary emissions are summed separately, since the EF adjustment factors
differ. The EF adjustment factors by engine/ship type, provided in the previous section, are
consolidated by ship type, using the CARB assumption that engines on all ships except
passenger ships are 95 percent slow speed diesel (SSD) engines and 5 percent medium speed
diesel engines (MSD) based upon a 2005 ARB survey.52 All passenger ships were assumed to be
medium speed diesel engines with electric drive propulsion (MSD-ED). Steam turbines (ST) and
gas-turbines (GT) are not included in the CARB inventory. The EF adjustment factors by ship
type are then applied, along with ship-specific growth factors supplied by CARB. The ship-
specific growth factors relative to 2002 are provided in Table 3-82 below.
Table 3-82 Growth Factors by Ship Type for California Ports Relative to 2002
Ship Type
Auto
Bulk
Container
General
Passenger
Reefer
RoRo
Tanker
Calendar Year
2002
.0000
.0000
.0000
.0000
.0000
.0000
.0000
1.0000
2020
1.5010
0.2918
2.5861
0.7331
7.5764
1.0339
1.5010
2.0979
2030
1.8478
0.1428
4.2828
0.5985
26.4448
1.0532
1.8478
3.0806
5-127
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Regulatory Impact Analysis
3.4.4.2 Interport Methodology
The interport portion of the inventory is not segregated by engine or ship type. As a
result, regional EF adjustment factors were developed based on the assumed mix of main
(propulsion) engine types in each region. The mix of main engine types by region was
developed using the ship call and power data and is presented in Table 3-83 and Figure 3-16.
Main engines are considered a good surrogate for interport emissions, since the majority of
emissions while underway are due to the main engines. The EF adjustment factors by main
engine type in Section 3.4.4.1.1 were used together with the mix of main engine types by region
to develop the EF regional adjustment factors for each control area. The resulting EF regional
adjustment factors for each pollutant and control area are provided in Table 3-84 thru Table 3-88
below. These EF regional adjustment factors, together with the regional growth factors in Table
3-69, were applied to calculate the future inventories for each control area.
Table 3-83 Installed Power by Main Engine Type for Deep Sea Portsa
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)
2020 Installed Power (%)
MSB
19.1%
19.1%
25.6%
13.7%
66.2%
66.2%
5.1%
29.2%
SSD
18.4%
18.4%
72.5%
85.5%
18.5%
18.5%
83.5%
70.8%
GT
0.3%
0.3%
0.9%
0.0%
7.4%
7.4%
1.6%
0.0%
ST
62.2%
62.2%
1.0%
0.8%
8.0%
8.0%
9.7%
0.0%
Total
0.8%
0.8%
45.4%
16.8%
2.0%
2.0%
5.0%
30.0%
2030 Installed Power (%)
MSB
19.1%
19.1%
25.6%
13.7%
66.2%
66.2%
5.1%
45.5%
SSD
18.4%
18.4%
72.5%
85.5%
18.5%
18.5%
83.5%
54.5%
GT
0.3%
0.3%
0.9%
0.0%
7.4%
7.4%
1.6%
0.0%
ST
62.2%
62.2%
1.0%
0.8%
8.0%
8.0%
9.7%
0.0%
Total
0.6%
0.6%
42.3%
13.4%
2.0%
2.0%
4.1%
37.6%
Note:
a Installed power is main propulsion engine power (kW) multiplied by
medium speed diesel, SSD is slow speed diesel, GT is gas turbine, ST
ship port calls by engine type. MSD
is steam turbine.
is
MSD
48%
Figure 3-16 Installed Power by Main Engine Type for Great Lake Ports
Installed power is main propulsion engine power (kW) multiplied by ship port calls by engine type. MSD is
medium speed diesel, SSD is slow speed diesel, GT is gas turbine, ST is steam turbine.
3-128
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Chapter 3: Emission Inventory
Table 3-84 NOX EF Adjustment Factors by Region and Control Type
U.S. 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)
OutofRegionb
2002
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2020
Base
0.9629
0.9629
0.9042
0.9038
0.9152
0.9152
0.9143
0.9022
0.9641
0.8942
ECA
Control
0.8104
n/a
0.5917
0.5935
0.6201
n/a
0.6343
0.5837
0.7989
n/a
Global
Control
n/a
0.8737
n/a
n/a
n/a
0.7659
n/a
n/a
n/a
0.7557
2030
Base
0.9595
0.9595
0.8937
0.8924
0.9088
0.9088
0.9036
0.8919
0.9238
0.8940
ECA
Control
0.7019
n/a
0.3110
0.3113
0.3723
n/a
0.3828
0.2877
0.6726
n/a
Global
Control
n/a
0.8568
n/a
n/a
n/a
0.7260
n/a
n/a
n/a
0.7103
Notes:
a NOX adjustment factors are a ratio of future base or control EFs to 2002 EFs. These regional adjustment
factors are used to adjust the interport portion of the 2002 inventory.
b Out of Region refers to areas outside 200nm, but within the air quality modeling domain. The out of
region adjustment factors are derived by weighting the regional adjustment factors by the main propulsion
power in each region. ECA control is only assumed within 200nm.
Table 3-85 PM10 EF Adjustment Factors by Region and Control Type"
U.S. 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)
OutofRegionb
2002
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2020
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
ECA
Control
0.1244
n/a
0.1341
0.1347
0.1311
n/a
0.1332
0.1345
0.1320
n/a
Global
Control
n/a
0.2280
n/a
n/a
n/a
0.2246
n/a
n/a
n/a
0.2198
2030
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
ECA
Control
0.1244
n/a
0.1341
0.1347
0.1311
n/a
0.1332
0.1341
0.1320
n/a
Global
Control
n/a
0.2280
n/a
n/a
n/a
0.2246
n/a
n/a
n/a
0.2200
Notes:
a PM10 adjustment factors are a ratio of future base or control EFs to 2002 EFs. These regional adjustment
factors are used to adjust the interport portion of the 2002 inventory.
b Out of Region refers to areas outside 200nm, but within the air quality modeling domain. The out of
region adjustment factors are derived by weighting the regional adjustment factors by the main propulsion
power in each region. ECA control is only assumed within 200nm.
5-129
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Regulatory Impact Analysis
Table 3-86 PM2 s EF Adjustment Factors by Region and Control Type"
U.S. 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)
OutofRegionb
2002
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2020
ECA
Control
0.1233
n/a
0.1329
0.1334
0.1299
n/a
0.1320
0.1332
0.1307
n/a
Global
Control
n/a
0.2252
n/a
n/a
n/a
0.2225
n/a
n/a
n/a
0.2177
Base
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
2030
ECA
Control
0.1233
n/a
0.1329
0.1334
0.1299
n/a
0.1320
0.1329
0.1307
n/a
Global
Control
n/a
0.2252
n/a
n/a
n/a
0.2225
n/a
n/a
n/a
0.2180
Notes:
a PM2 5 adjustment factors are a ratio of future base or control EFs to 2002 EFs. These regional adjustment
factors are used to adjust the interport portion of the 2002 inventory.
b Out of Region refers to areas outside 200nm, but within the air quality modeling domain. The out of
region adjustment factors are derived by weighting the regional adjustment factors by the main propulsion
power in each region. ECA control is only assumed within 200nm.
Table 3-87 SO2 EF Adjustment Factors by Region and Control Type"
U.S. 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)
OutofRegionb
2002
1.0000
1.0000
1.0000
1.0000
.0000
.0000
.0000
.0000
.0000
1.0000
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2020
ECA
Control
0.0380
n/a
0.0352
0.0352
0.0381
n/a
0.0380
0.0380
0.0352
n/a
Global
Control
n/a
0.1814
n/a
n/a
n/a
0.1893
n/a
n/a
n/a
0.1811
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2030
ECA
Control
0.0380
n/a
0.0352
0.0352
0.0381
n/a
0.0380
0.0380
0.0352
n/a
Global
Control
n/a
0.1814
n/a
n/a
n/a
0.1893
n/a
n/a
n/a
0.1821
Notes:
a SO2 adjustment factors are a ratio of future base or control EFs to 2002 EFs. These regional adjustment
factors are used to adjust the interport portion of the 2002 inventory.
b Out of Region refers to areas outside the 200nm, but within the air quality modeling domain. The out of
region adjustment factors are derived by weighting the regional adjustment factors by the main propulsion
power in each region. ECA control is only assumed within 200nm.
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Chapter 3: Emission Inventory
Table 3-88 CO2 EF Adjustment Factors by Region and Control Type
U.S. 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)
OutofRegionb
2002
1.0000
1.0000
1.0000
1.0000
.0000
.0000
.0000
.0000
.0000
1.0000
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2020
ECA
Control
0.9509
n/a
0.9499
0.9494
0.9519
n/a
0.9493
0.9501
0.9510
n/a
Global
Control
n/a
0.9509
n/a
n/a
n/a
0.9519
n/a
n/a
n/a
0.9499
Base
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
2030
ECA
Control
0.9509
n/a
0.9499
0.9494
0.9519
n/a
0.9493
0.9507
0.9510
n/a
Global
Control
n/a
0.9509
n/a
n/a
n/a
0.9519
n/a
n/a
n/a
0.9502
Notes:
a CO2 adjustment factors are a ratio of future base or control EFs to 2002 EFs. These regional adjustment
factors are used to adjust the interport portion of the 2002 inventory.
b Out of Region refers to areas outside 200nm, but within the air quality modeling domain. The out of
region adjustment factors are derived by weighting the regional adjustment factors by the main propulsion
power in each region. ECA control is only assumed within 200nm.
3.4.4.3 Estimating and Combining the Near Port and Interport Inventories
To produce future year control scenarios, the interport inventories were scaled by a
growth factor to 2020 and 2030, as previously described. An ECA boundary line was drawn so
that each point on it was at a 200 nm distance from the nearest point on land. Adjustment
factors, as described in Section 3.4.3.1, were then applied to interport emissions within the ECA
boundary.
To create control scenarios in the near port inventories, growth and control factors were
applied to the 2002 near port inventories (described in Sections 3.4.2 and 3.4.3.1). The near port
inventories were then converted into a gridded format (Section 3.3.3.3). Using this grid, STEEM
values were removed from near port cells and near 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.
Interport and near port emissions were then aggregated to form regional totals.
3.4.5 2020 and 2030 Baseline Inventories
The resulting 2020 and 2030 estimated emission inventories by region and the nation are
shown in Table 3-89 and Table 3-90. These baseline inventories account for growth as well as
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Regulatory Impact Analysis
implementation of the Tier 1 NOx standard. Estimated fuel consumption for the baseline
inventories by region and fuel type is given in Table 3-91.
Table 3-89 2020 Baseline Emissions Inventory
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons0
Metric Tonnes per Year
NOX
29,242
93,685
439,604
259,295
48,026
67,573
42,644
234,968
19,842
1,234,879
1,361,221
PM10
2,561
8,118
39,003
23,403
4,185
5,888
3,916
20,148
1,613
108,835
119,970
PM25a
2,356
7,469
35,882
21,531
3,850
5,417
3,603
18,536
1,484
100,128
110,372
HC
1,073
3,444
16,216
9,590
1,765
2,483
1,706
8,585
681.914
45,544
50,204
CO
2,534
8,112
38,382
23,628
4,161
5,855
3,799
20,686
1,607
108,762
119,890
S02
19,084
60,227
323,038
174,751
31,075
43,722
27,807
149,751
11,993
841,447
927,537
C02
1,182,047
3,711,596
18,121,202
10,567,512
1,930,172
2,715,741
1,800,743
9,490,502
740,624
50,260,140
55,402,321
Notes:
a Estimated from PM10 using a multiplicative conversion factor of 0.92.
b Converted from metric tonnes using a multiplicative conversion factor of 1.102 short tons per metric tonne.
Table 3-90 2030 Baseline Emissions Inventory
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons0
Metric Tonnes per Year
NOX
42,930
137,951
679,271
341,903
78,806
110,880
58,937
394,335
22,471
1,867,484
2,058,549
PM10
3,544
11,232
60,615
31,142
6,818
9,593
5,433
34,948
1,910
165,235
182,140
PM25a
3,260
10,333
55,766
28,651
6,273
8,825
4,999
32,152
1,757
152,016
167,569
HC
1,485
4,765
25,207
12,761
2,875
4,045
2,372
14,635
807
68,951
76,006
CO
3,505
11,223
59,678
31,427
6,780
9,539
5,278
35,208
1,902
164,539
181,373
S02
26,404
83,329
502,305
232,547
50,630
71,237
38,556
259,982
14,196
1,279,185
1,410,061
C02
1,635,479
5,135,278
28,163,780
14,062,207
3,144,932
4,424,900
2,497,078
16,470,350
876,636
76,410,639
84,228,311
Notes:
a Estimated from PM10 using a multiplicative conversion factor of 0.92.
b Converted from metric tonnes using a multiplicative conversion factor of 1.102 short tons per metric tonne.
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Chapter 3: Emission Inventory
Table 3-91 Fuel Consumption by Category 3 Vessels in Baseline Scenarios
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons
Metric Tonnes Fuel
2020 Baseline
Distillate
3,386
0
202,139
96,428
10,529
0
28,532
83,576
1,269
425,860
469,431
Residual
367,977
1,166,068
5,490,981
3,223,557
595,871
853,202
537,206
2,898,045
231,412
15,364,319
16,936,262
Total
371,363
1,166,068
5,693,120
3,319,985
606,400
853,202
565,738
2,981,622
232,681
15,790,179
17,405,693
2030 Baseline
Distillate
4,685
0
313,916
128,338
17,151
0
39,476
157,878
2,037
663,482
731,364
Residual
509,132
1,613,345
8,534,271
4,289,571
970,889
1,390,166
745,028
5,016,595
273,375
23,342,374
25,730,563
Total
513,817
1,613,345
8,848,187
4,417,910
988,040
1,390,166
784,505
5,174,474
275,412
24,005,856
26,461,926
3.4.6 2020 and 2030 Control Inventories
For the control scenario, the inventories for each of the nine geographic regions, the U.S.
total, and the 48-state total are presented in Table 3-92 and Table 3-93. The regional and total
inventories include all emissions within 200nm of shore. For the purposes of this analysis, EGA
controls are assumed to apply to all regions, except Alaska West and Hawaii West. For the
Alaska West and Hawaii West regions, global controls apply. Estimated fuel consumption for
the control inventories by region and fuel type is given in Table 3-94.
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Regulatory Impact Analysis
Table 3-92 Category 3 Vessel Inventories for 2020 Control Case"
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons
Metric Tonnes per Year
NOX
25,978
90,787
289,671
170,861
32,952
57,406
29,105
150,461
16,420
863,642
952,002
PM10
322
1,851
5,286
3,201
551
1,323
539
2,753
207
16,032
77,67.3
PM25a
296
1,703
4,863
2,945
507
1,217
496
2,533
190
14,750
16,259
HC
1,072
3,444
16,231
9,581
1,764
2,483
1,709
8,546
676
45,507
50,163
CO
2,534
8,112
38,421
23,615
4,162
5,855
3,803
20,585
1,602
108,688
119,808
S02
728
10,927
11,514
6,255
1,187
8,277
1,076
5,786
420
46,168
50,892
C02
1,124,652
3,529,505
17,233,800
10,034,946
1,838,832
2,585,222
1,715,210
9,009,986
704,390
47,776,542
52,664,623
Note:
a This scenario assumes EGA controls apply within 200 nautical miles of all U.S. regions except Alaska West
and Hawaii West, with global controls applied in all other areas. Corrected boundaries are used.
Table 3-93 Category 3 Vessel Inventories for 2030 Control Case
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons
Metric Tonnes per Year
NOX
30,722
123,187
235,378
118,930
31,992
88,502
22,758
128,302
16,369
796,140
877,594
PM10
445
2,677
8,221
4,261
899
2,175
751
4,769
253
24,451
26,953
PM25a
410
2,463
7,563
3,920
827
2,001
691
4,388
233
22,495
24, 797
HC
1,485
4,765
25,207
12,761
2,875
4,045
2,372
14,635
807
68,951
76,006
CO
3,505
11,223
59,678
31,426
6,780
9,539
5,278
35,202
1,902
164,539
181,373
SO2
1,008
15,847
17,896
8,325
1,933
13,596
1,494
10,030
501
70,630
77,856
CO2
1,556,045
4,883,341
26,763,558
13,355,741
2,995,263
4,214,197
2,378,683
15,713,679
833,733
72,694,239
80,131,682
Note:
a This scenario assumes EGA controls apply within 200 nautical miles of all U.S. regions, except Alaska
West and Hawaii West, with global controls elsewhere. Corrected boundaries are used.
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Chapter 3: Emission Inventory
Table 3-94 Fuel Consumption by Category 3 Vessels in Control Scenarios
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons
Metric Tonnes Fuel
2020 Control
Distillate
353,331
1,108,861
5,414,326
3,152,669
577,704
812,197
538,866
2,830,658
221,297
15,009,910
16,545,593
Residual
0
0
0
0
0
0
0
0
0
0
0
Total
353,331
1,108,861
5,414,326
3,152,669
577,704
812,197
538,866
2,830,658
221,297
15,009,910
16,545,593
2030 Control
Distillate
488,861
1,534,194
8,408,281
4,195,960
941,019
1,323,970
747,309
4,936,751
261,933
22,838,278
25,174,892
Residual
0
0
0
0
0
0
0
0
0
0
0
Total
488,861
1,534,194
8,408,281
4,195,960
941,019
1,323,970
747,309
4,936,751
261,933
22,838,278
25,174,892
3.5 Estimated Category 3 Inventory Contribution
This section describes the contribution of Category 3 marine engines to national and
selected local emission inventories in 2002, 2020, and 2030. The pollutants analyzed are NOx,
directly emitted PM2.5, and SO2. All weight units in the following tables are short tons.
3.5.1 Baseline Contribution of C3 Vessels to National Level Inventory
Category 3 marine engines contribute to the formation of ground level ozone and
concentrations of fine particles in the ambient atmosphere. Based on our current emission
inventory analysis, we estimate that these engines contributed nearly 6 percent of mobile source
NOX, over 10 percent of mobile source PM2.5, and about 40 percent of mobile source SO2 in
2002. We estimate that their contribution will increase to about 40 percent of mobile source
NOx, 48 percent of mobile source PM2 5, and 95 percent of mobile source SO2 by 2030 without
further controls on these engines. Our current estimates for NOx, PM2 5, and SO2 inventories are
set out in the following tables. Inventory projections for 2020 and 2030 include the effect of
existing emission mobile source and stationary source control programs previously adopted by
EPA.
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Regulatory Impact Analysis
Table 3-95 50 State Annual NOX Baseline Emission Levels for Mobile and Other Source Categories
Category
Commercial Marine (C3)
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Small Nonroad SI
Recreational Marine SI
SI Recreational Vehicles
Large Nonroad SI (>25hp)
Aircraft
Total Off Highway
Highway Diesel
Highway non-diesel
Total Highway
Total Mobile Sources
Stationary Point & Area
Sources
Total Man-Made Sources
2002
short tons
738,700
1,118,786
40,437
834,025
1,555,812
119,833
49,902
10,614
336,292
103,591
4,907,990
3,529,046
4,293,733
7,822,779
12,730,769
8,613,718
21,344,488
%of
mobile
source
5.8
8.8
0.3
6.6
12.2
0.9
0.4
0.1
2.6
0.8
38.6
27.7
33.7
61.4
100.0
-
%of
total
3.5
5.2
0.2
3.9
7.3
0.6
0.2
0.0
1.6
0.5
23.0
16.5
20.1
36.7
59.6
40.4
100
2020
short tons
1,361,221
669,405
43,579
499,798
683,481
80,901
87,709
30,108
48,270
132,278
3,636,750
681,142
1,270,269
1,951,411
5,588,160
5,773,927
11,362,088
%of
mobile
source
24.4
12.0
0.8
8.9
12.2
1.4
1.6
0.5
0.9
2.4
65.1
12.2
111
34.9
100.0
-
%of
total
12.0
5.9
0.4
4.4
6.0
0.7
0.8
0.3
0.4
1.2
32.0
6.0
11.2
17.2
49.2
50.8
100
2030
short tons
2,058,549
437,245
43,665
308,614
435,774
91,913
73,961
34,318
47,766
143,986
3,675,790
355,817
1,144,199
1,500,016
5,175,806
5,773,927
10,949,734
%of
mobile
source
39.8
8.4
0.8
6.0
8.4
1.8
1.4
0.7
0.9
2.8
71.0
6.9
22.1
29.0
100.0
-
%of
total
18.8
4.0
0.4
2.8
4.0
0.8
0.7
0.3
0.4
1.3
33.6
3.2
10.4
13.7
47.3
52.7
100
3-136
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Chapter 3: Emission Inventory
Table 3-96 50 State Annual PM2.5 Baseline Emission Levels for Mobile and Other Source Categories
Category
Commercial Marine (C3)
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Small Nonroad SI
Recreational Marine SI
SI Recreational Vehicles
Large Nonroad SI (>25hp)
Aircraft
Total Off Highway
Highway Diesel
Highway non-diesel
Total Highway
Total Mobile Sources
Stationary Point & Area Sources
Total Man-Made Sources
2002
short tons
54,112
29,660
1,096
28,730
159,111
25,700
16,262
13,710
1,652
17,979
348,013
94,982
51,694
146,676
494,690
3,025,244
3,519,933
%of
diesel
mobile
14.7
8.1
0.3
7.8
43.3
25.8
%of
total
1.5
0.8
0.0
0.8
4.5
0.7
0.5
0.4
0.0
0.5
9.9
2.7
1.5
4.2
14.1
85.9
100
2020
short tons
110,372
15,145
973
15,787
46,056
31,981
2,845
11,901
2,421
22,176
259,656
20,145
45,329
65,474
325,131
3,047,714
3,372,845
%of
diesel
mobile
52.9
7.3
0.5
7.6
22.1
9.7
%of
total
3.3
0.4
0.0
0.5
1.4
0.9
0.1
0.4
0.1
0.7
7.7
0.6
1.3
1.9
9.6
90.4
100
2030
short tons
167,569
8,584
1,053
10,017
17,902
36,795
1,225
10,090
2,844
24,058
280,136
18,802
51,621
70,423
350,559
3,047,714
3,398,274
%of
diesel
mobile
74.8
3.8
0.5
4.5
8.0
8.4
%of
total
4.9
0.3
0.0
0.3
0.5
1.1
0.0
0.3
0.1
0.7
8.2
0.6
1.5
2.1
10.3
89.7
100
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Regulatory Impact Analysis
Table 3-97 50 State Annual SO2 Baseline Emission Levels for Mobile and Other Source Categories
Category
Commercial Marine (C3)
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Small Nonroad SI
Recreational Marine SI
SI Recreational Vehicles
Large Nonroad SI (>25hp)
Aircraft
Total Off Highway
Highway Diesel
Highway non-diesel
Total Highway
Total Mobile Sources
Stationary Point & Area
Sources
Total Man-Made Sources
2002
short tons
453,614
75,385
5,145
80,353
172,304
6,742
2,755
1,530
933
8,701
807,463
71,147
171,866
243,013
1,050,475
13,897,968
14,948,443
%of
mobile
source
43.2
7.2
0.5
7.6
16.4
0.6
0.3
0.1
0.1
0.8
76.9
6.8
16.4
23.1
100.0
-
%of
total
3.0
0.5
0.0
0.5
1.2
0.0
0.0
0.0
0.0
0.1
5.4
0.5
1.1
1.6
7.0
93.0
100
2020
short tons
927,537
396
162
2,961
999
8,870
2,995
2,862
905
11,171
958,857
4,218
30,922
35,140
993,998
7,864,681
8,858,678
%of
mobile
source
93.3
0.0
0.0
0.3
0.1
0.9
0.3
0.3
0.1
1.1
96.5
0.4
3.1
3.5
100.0
-
%of
total
10.5
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
10.8
0.0
0.3
0.4
11.2
88.8
100
2030
short tons
1,410,061
464
192
3,002
1,079
10,282
3,184
3,019
1,020
12,197
1,444,498
5,478
36,011
41,489
1,485,986
7,864,681
9,350,667
%of
mobile
source
94.9
0.0
0.0
0.2
0.1
0.7
0.2
0.2
0.1
0.8
97.2
0.4
2.4
2.8
100.0
-
%of
total
15.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
15.4
0.1
0.4
0.4
15.9
84.1
100
3-138
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Chapter 3: Emission Inventory
3.5.2 Contribution to Mobile Source Inventories for Selected Cities
Commercial marine vessels, powered by Category 3 marine engines, contribute
significantly to the emissions inventory for many U.S. ports. This is illustrated in Table 3-98,
which presents the mobile source inventory contributions of these vessels for several ports. The
ports in this table were selected to present a sampling over a wide geographic area along the U.S.
coasts. In 2005, these twenty ports received approximately 60 percent of the vessel calls to the
U.S. from ships of 10,000 dead weight tons (DWT) or greater.
53
Table 3-98 Contribution of Commercial Marine Vessels to Mobile Source Inventories
for Selected Ports in 2002a
Port Area
Valdez, AK
Seattle, WA
Tacoma, WA
San Francisco, CA
Oakland, CA
LA/Long Beach, CA
Beaumont, TX
Galveston, TX
Houston, TX
New Orleans, LA
South Louisiana, LA
Miami, FL
Port Everglades, FL
Jacksonville, FL
Savannah, GA
Charleston, SC
Wilmington, NC
Baltimore, MD
New York/New Jersey
Boston, MA
% of total
NOX
4
10
20
1
8
5
6
5
3
14
12
13
9
5
24
22
7
12
4
4
% of total
PM25
10
20
38
1
14
10
20
12
10
24
24
25
20
11
39
33
16
27
9
5
% of total
S02
43
56
74
31
80
71
55
47
41
59
58
66
56
52
80
87
73
69
39
30
Note:
a This category includes emissions from Category 3 (C3) propulsion engines and
C2/3 auxiliary engines used on ocean-going vessels.
Currently, more than 40 major U.S. deep sea ports are located in areas that are designated
as being in nonattainment for either or both the 8-hour ozone NAAQS and PM2.5 NAAQS.
Many ports are located in areas rated as class I federal areas for visibility impairment and
regional haze. It should be noted that emissions from ocean-going vessels are not simply a
localized problem related only to cities that have commercial ports. Virtually all U.S. coastal
areas are affected by emissions from ships that transit between those ports, using shipping lanes
that are close to land. Many of these coastal areas also have high population densities. For
example, Santa Barbara, which has no commercial port, estimates that engines on ocean-going
marine vessels currently contribute about 37 percent of total NOx in their area.54 These
3-139
-------
Regulatory Impact Analysis
emissions are from ships that transit the area, and "are comparable to (even slightly larger than)
the amount of NOx produced onshore by cars and truck." By 2015 these emissions are expected
to increase 67 percent, contributing 61 percent of Santa Barbara's total NOx emissions. This mix
of emission sources led Santa Barbara to point out that they will be unable to meet air quality
standards for ozone without significant emission reductions from these vessels, even if they
completely eliminate all other sources of pollution. Interport emissions from OGV also
contribute to other environmental problems, affecting sensitive marine and land ecosystems.
3.6 Projected Emission Reductions
The projected tons reductions for each of the 2020 control cases relative to the 2020
baseline, as well as the tons reductions for the 2030 control case relative to the 2030 baseline, are
presented in Table 3-99 thru Table 3-100. Reductions by region, for the total U.S., and for the
total 48-states, are provided by pollutant in each table.
Table 3-99 Reductions for 2020 Control Case
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons
Metric Tonnes f
NOX
3,264
2,897
149,933
88,434
15,074
10,166
13,539
84,507
3,422
371,237
409,219
PM10
2,239
6,267
33,717
20,202
3,634
4,565
3,377
17,395
1,406
92,803
102,297
PM25a
2,060
5,766
31,020
18,586
3,343
4,200
3,107
16,003
1,294
85,378
94,114
HC
0
0
0
0
0
0
0
0
0
0
0
>er Year
CO
0
0
0
0
0
0
0
0
0
0
0
S02
18,356
49,300
311,523
168,496
29,888
35,445
26,731
143,965
11,574
795,279
876,645
C02
57,395
182,091
887,402
532,567
91,340
130,519
85,533
480,516
36,235
2,483,598
2,737,698
Note:
a The emission reductions are relative to the 2020 baseline.
3-140
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Chapter 3: Emission Inventory
Table 3-100 Reductions for 2030 Control Case
U.S. 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)
Total U.S. Metric
Tonnes
Total U.S. Short Tons
Metric Tonnes per Year
NOX
12,208
14,764
443,893
222,973
46,814
22,377
36,179
266,033
6,102
1,071,344
1,180,955
PM10
3,099
8,555
52,394
26,881
5,919
7,417
4,683
30,179
1,657
140,783
155,187
PM25a
2,851
7,870
48,203
24,731
5,446
6,824
4,308
27,764
1,524
129,521
142,772
HC
0
0
0
0
0
0
0
0
0
0
0
CO
0
0
0
0
0
0
0
6
0
0
0
SO2
25,397
67,482
484,409
224,221
48,698
57,641
37,062
249,952
13,694
1,208,555
1,332,204
CO2
79,434
251,937
1,400,222
706,466
149,669
210,703
118,395
756,671
42,904
3,716,400
4,096,630
Note:
a The emission reductions are relative to the 2030 baseline.
3.7 Inventories Used for Air Quality Modeling
The emission inventories for 2020 presented in this chapter are slightly different from the
emissions inventories used in the air quality modeling presented in Chapter 2. Specifically, the
2020 inventories used in the air quality modeling reflect a slightly different boundary for the
proposed EGA that was based on a measurement error. Due to the nature of the measurement
error, the corrections to the EGA boundaries are not uniform, but are different by coastal area.
The measurement error affects only those portions that are farthest from shore. The 2030
inventories are not affected by this error.
A comparison of the air quality and final inventories by region for the 2020 baseline
scenario is provided in Table 3-101. Results are provided only for NOx, PM2.5, and 862, since
the air quality modeling is focused on ozone and PM2.5. In addition, Alaska and Hawaii are not
included, since the air quality modeling domain does not include these states. As seen in Table
3-101, the changes due to the boundary error are not expected to have a significant impact on the
results of our analysis.
3-141
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Regulatory Impact Analysis
Table 3-101 Comparison of Air Quality versus Final Inventories for 2020 Baseline Case
U.S. Region
East Coast (EC)
Gulf Coast (GC)
North Pacific
(NP)
South Pacific
(SP)
Great Lakes (GL)
Total 48-State
Metric Tonnes per Year
NOX
AQ
439,713
261,024
42,291
216,849
19,842
979,719
Final
439,604
259,295
42,644
234,968
19,842
996,353
%
Diff
0%
1%
-1%
-8%
0%
-2%
PM25
AQ
35,891
21,669
3,575
17,092
1,484
79,711
Final
35,882
21,531
3,603
18,536
1,484
81,036
%
Diff
0%
1%
-1%
-8%
0%
-2%
S02
AQ
323,108
175,862
27,580
138,102
11,993
676,645
Final
323,038
174,751
27,807
149,751
11,993
687,340
%
Diff
0%
1%
-1%
-8%
0%
-2%
The 2020 control inventories are also subject to the boundary error. In addition, the 2020
air quality control case does not include global controls for areas that are beyond 200 nm but
within the air quality modeling domain. The impact of this latter difference is expected to be
minimal.
The modeling for 2030 for the NPRM was based on inventories that reflected an EGA
distance closer to shore than what we are finalizing. The air quality modeling and related
estimates of benefits in the NPRM, therefore reflect the impacts associated with approximately
80% of the emission reductions achieved by the coordinated strategy. For the final RIA, we
modeled the 2030 coordinated strategy with a 200 nm boundary and global controls beyond. As
a result, the 2030 air quality impacts and health benefits presented in Chapters 2 and 6,
respectively, reflect this updated 2030 control case.
3-142
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Chapter 3: Emission Inventory
APPENDIX 3A
Port Coordinates and Reduced Speed Zone Information
-------
Regulatory Impact Analysis
Table 3-102 Port Coordinates
Port Name
Albany, NY
Alpena, Ml
Anacortes, WA
Anchorage, AK
Ashtabula, OH
Baltimore, MD
Barbers Point, Oahu, HI
Baton Rouge, LA
Beaumont, TX
Boston, MA
Bridgeport, CT
Brownsville, TX
Brunswick, GA
Buffalo, NY
Burns Waterway Harbor, IN
Calcite, Ml
Camden-Gloucester, NJ
Carquinez, CA
Catalina, CA
Charleston, SC
Chester, PA
Chicago, IL
Cleveland, OH
Conneaut, OH
Coos Bay, OR
Corpus Christi, TX
Detroit, Ml
Duluth-Superior, MN and
Wl
El Segundo, CA
Erie, PA
Escanaba, Ml
Eureka, CA
Everett, WA
Fairport Harbor, OH
Fall River, MA
Freeport, TX
Galveston, TX
Gary, IN
Georgetown, SC
Grays Harbor, WA
Gulfport, MS
Hilo, HI
Honolulu, HI
Hopewell, VA
USAGE
Code
C0505
L3617
C4730
C4820
L3219
C0700
C4458
C2252
C2395
C0149
C0311
C2420
C0780
L3230
L3739
L3620
C0551
CCA01
CCA02
C0773
C0297
L3749
L3217
L3220
C4660
C2423
L3321
L3924
CCA03
L3221
L3795
CCA04
C4725
L3218
C0189
C2408
C2417
L3736
C0772
C4702
C2083
C4400
C4420
C0738
Port Coordinates
Longitude
-73.7482
-83.4223
-122.6
-149.895
-80.7917
-76.5171
-158.109
-91.1993
-94.0881
-71.0523
-73.1789
-97.3981
-81.4999
-78.8953
-87.1552
-83.7756
-75.1043
-122.123
-118.496
-79.9216
-75.3222
-87.638
-81.6719
-80.5486
-124.21
-97.3979
-83.1096
-92.0964
-118.425
-80.0679
-87.025
-124.186
-122.229
-81.2941
-71.1588
-95.3304
-94.8127
-87.3251
-79.2896
-124.122
-89.0853
-155.076
-157.872
-77.2763
Latitude
42.64271
45.0556
48.49617
61.23778
41.91873
39.20899
21.29723
30.42292
30.08716
42.35094
41.172
25.9522
31.15856
42.8783
41.64325
45.39293
39.94305
38.03556
33.43943
32.78878
39.85423
41.88662
41.47852
41.96671
43.36351
27.81277
42.26909
46.77836
33.91354
42.15154
45.73351
40.79528
47.98476
41.76666
41.72166
28.9384
29.31049
41.61202
33.36682
46.91167
30.35216
19.72861
21.31111
37.32231
3-144
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Chapter 3: Emission Inventory
Port Name
Houston, TX
Indiana Harbor, IN
Jacksonville, FL
Kahului, Maui, HI
Kalama, WA
Lake Charles, LA
Long Beach, CA
Longview, WA
Lorain, OH
Los Angeles, CA
Manistee, Ml
Marblehead, OH
Marcus Hook, PA
Matagorda Ship Channel,
TX
Miami, FL
Milwaukee, Wl
Mobile, AL
Morehead City, NC
Muskegon, Ml
Nawiliwili, Kauai, HI
New Bedford, MA
New Castle, DE
New Haven, CT
New Orleans, LA
New York, NY and NJ
Newport News, VA
Nikishka, AK
Oakland, CA
Olympia, WA
Other Puget Sound, WA
Palm Beach, FL
Panama City, FL
Pascagoula, MS
Paulsboro, NJ
Penn Manor, PA
Pensacola, FL
Philadelphia, PA
Plaquemines, LA, Port of
Port Angeles, WA
Port Arthur, TX
Port Canaveral, FL
Port Dolomite, Ml
Port Everglades, FL
Port Hueneme, CA
Port Inland, Ml
USAGE
Code
C2012
L3738
C2017
C4410
C4626
C2254
C4110
C4622
L3216
C4120
L3720
L3212
C5251
C2410
C2164
L3756
C2005
C0764
L3725
C4430
C0187
C0299
C1507
C2251
C0398
C0736
C4831
C4345
C4718
C4754
C2162
C2016
C2004
C5252
C0298
C2007
C0552
C2255
C4708
C2416
C2160
L3627
C2163
C4150
L3803
Port Coordinates
Longitude
-95.2677
-87.4455
-81.6201
-156.473
-122.863
-93.2221
-118.21
-122.914
-82.1951
-118.241
-86.3443
-82.7091
-75.4042
-96.5641
-80.1832
-87.8997
-88.0411
-76.6947
-86.3501
-159.353
-70.9162
-75.5616
-72.9047
-90.0853
-74.0384
-76.4582
-151.314
-122.308
-122.909
-122.72
-80.0527
-84.1993
-88.5588
-75.2266
-74.7408
-87.2579
-75.2022
-89.6875
-123.453
-93.9607
-80.6082
-84.3128
-80.1178
-119.208
-85.8628
Latitude
29.72538
41.67586
30.34804
20.89861
46.02048
30.22358
33.73957
46.14222
41.48248
33.77728
44.25082
41.52962
39.81544
28.5954
25.78354
42.98824
30.72527
34.71669
43.19492
21.96111
41.63641
39.65668
41.29883
29.91414
40.67395
36.98522
60.74793
37.82152
47.06827
48.84099
26.76904
30.19009
30.34802
39.82689
40.13598
30.40785
39.91882
29.48
48.1305
29.83142
28.41409
45.99139
26.09339
34.14824
45.95508
5-145
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Regulatory Impact Analysis
Port Name
Port Manatee, FL
Portland, ME
Portland, OR
Presque Isle, Ml
Providence, Rl
Redwood City, CA
Richmond, CA
Richmond, VA
Sacramento, CA
San Diego, CA
San Francisco, CA
Sandusky, OH
Savannah, GA
Searsport, ME
Seattle, WA
South Louisiana, LA, Port
of
St. Clair, Ml
Stockton, CA
Stoneport, Ml
Tacoma, WA
Tampa, FL
Texas City, TX
Toledo, OH
Two Harbors, MN
Valdez, AK
Vancouver, WA
Wilmington, DE
Wilmington, NC
USAGE
Code
C2023
C0128
C4644
L3845
C0191
CCA05
C4350
C0737
CCA06
C4100
C4335
L3213
C0776
C0112
C4722
C2253
L3509
C4270
L3619
C4720
C2021
C2404
L3204
L3926
C4816
C4636
C0554
C0766
Port Coordinates
Longitude
-82.5613
-70.2513
-122.665
-87.3852
-71.3984
-122.21
-122.374
-77.4194
-121.544
-117.178
-122.399
-82.7123
-81.0954
-68.925
-122.359
-90.6179
-82.4941
-121.316
-83.4703
-122.452
-82.5224
-94.9181
-83.5075
-91.6626
-146.346
-122.681
-75.507
-77.954
Latitude
27.63376
43.64951
45.47881
46.57737
41.81178
37.51306
37.92424
37.45701
38.56167
32.70821
37.80667
41.47022
32.08471
44.45285
47.58771
30.03345
42.82663
37.9527
45.28073
47.28966
27.78534
29.36307
41.66294
47.00428
61.12473
45.62244
39.71589
34.23928
3-146
-------
Chapter 3: Emission Inventory
Table 3-103 Port RSZ Information
Port Name
Albany, NY
Alpena, Ml
Anacortes, WA
Anchorage, AK
Ashtabula, OH
Baltimore, MD
Barbers Point, Oahu, HI
Baton Rouge, LA
Beaumont, TX
Boston, MA
Bridgeport, CT
Brownsville, TX
Brunswick, GA
Buffalo, NY
Burns Waterway Harbor, IN
Calcite, Ml
Camden-Gloucester, NJ
Carquinez, CA
Catalina, CA
Charleston, SC
Chester, PA
Chicago, IL
Cleveland, OH
Conneaut, OH
Coos Bay, OR
Corpus Christi, TX
Detroit, Ml
Duluth-Superior, MN and
Wl
El Segundo, CA
Erie, PA
Escanaba, Ml
Eureka, CA
Everett, WA
Fairport Harbor, OH
Fall River, MA
Freeport, TX
Galveston, TX
Gary, IN
Georgetown, SC
RSZ
Speed
(knts)
c
e
a
14.5
e
c
10
10
7
10
10
8.8
13
e
e
e
c
12
12
12
c
e
e
e
6.5
d
e
e
12
e
e
12
a
e
9
c
c
e
12
RSZ
distance
(naut mi)
142.5
3
108.3
143.6
3
157.1
5.1
219.8
53.5
14.3
2
18.7
38.8
3
3
3
94
39
11.9
17.3
78.2
3
3
3
13
30.1
3
3
23.3
3
3
9
123.3
3
22.7
2.6
9.3
3
17.6
Final RSZ End Point(s)
Longitude
-73.8929
-83.2037
-124.771
-152.309
-80.8097
-75.8067
-158.132
-89.4248
-89.137
-93.7552
-70.7832
-73.1863
-97.0921
-80.9345
-81.1357
-79.0996
-87.1032
-83.5383
-75.0095
-122.632
-118.465
-79.6452
-75.0095
-87.4141
-81.765
-80.5639
-124.359
-96.8753
-83.1384
-91.8536
-118.926
-118.465
-80.115
-86.9224
-124.347
-124.771
-81.3917
-71.3334
-95.2949
-94.6611
-87.2824
-79.0779
Latitude
40.47993
44.99298
48.49074
59.5608
42.08549
36.8468
21.21756
28.91161
28.98883
29.55417
42.37881
41.13906
26.06129
31.29955
30.68935
42.81683
41.80625
45.39496
38.79004
37.76094
33.63641
32.62557
38.79004
41.86971
41.63079
42.13361
43.35977
27.74433
42.10308
46.78916
33.91252
33.63641
42.3151
45.58297
40.75925
48.49074
41.91401
41.41708
28.93323
29.3247
41.77658
33.1924
5-147
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Regulatory Impact Analysis
Port Name
Grays Harbor, WA
Gulfport, MS
Hilo, HI
Honolulu, HI
Hopewell, VA
Houston, TX
Indiana Harbor, IN
Jacksonville, FL
Kahului, Maui, HI
Kalama, WA
Lake Charles, LA
Long Beach, CA
Long view, WA
Lorain, OH
Los Angeles, CA
Manistee, Ml
Marblehead, OH
Marcus Hook, PA
Matagorda Ship Channel, TX
Miami, FL
Milwaukee, Wl
Mobile, AL
Morehead City, NC
Muskegon, Ml
Nawiliwili, Kauai, HI
New Bedford, MA
New Castle, DE
New Haven, CT
New Orleans, LA
New York, NY and NJ
Newport News, VA
Nikishka, AK
Oakland, CA
Olympia, WA
Other Puget Sound, WA
Palm Beach, FL
Panama City, FL
Pascagoula, MS
Paulsboro, NJ
Penn Manor, PA
Pensacola, FL
RSZ
Speed
(knts)
a
10
10
10
10
c
e
10
10
b
6
12
b
e
12
e
e
c
7.3
12
e
11
10
e
10
9
c
10
10
c
14
14.5
12
a
a
3
10
10
c
c
12
RSZ
distance
(naut mi)
4.9
17.4
7.1
10
91.8
49.6
3
18.6
7.5
68.2
38
18.1
67.3
3
20.6
3
3
94.7
24
3.8
3
36.1
2.2
3
7.3
22.4
60.5
2.1
104.2
15.7
24.3
90.7
18.4
185.9
106
3.1
10
17.5
83.5
114.5
12.7
Final RSZ End Point(s)
Longitude
-124.24
-88.9263
-154.985
-157.956
-157.785
-75.8067
-94.6611
-87.4007
-81.3649
-156.44
-124.137
-93.3389
-118.465
-118.13
-124.137
-82.2701
-118.465
-118.13
-86.3819
-82.7293
-75.0095
-96.2287
-80.1201
-87.6718
-88.0644
-76.6679
-86.5377
-159.266
-71.1013
-75.0095
-72.9121
-89.4248
-89.137
-73.8929
-75.8067
-152.309
-122.632
-124.771
-124.771
-79.9973
-84.1797
-88.4804
-75.0095
-75.0095
-87.298
Latitude
46.89509
30.11401
19.76978
21.17658
21.23827
36.8468
29.3247
41.8401
30.39769
21.01066
46.22011
29.73094
33.63641
33.45211
46.22011
41.64023
33.63641
33.45211
44.41573
41.69638
38.79004
28.33472
25.75787
42.97343
30.1457
34.68999
43.29151
21.87705
41.38499
38.79004
41.26588
28.91161
28.98883
40.47993
36.8468
59.5608
37.76094
48.49074
48.49074
26.77129
30.0818
30.09597
38.79004
38.79004
30.27777
3-148
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Chapter 3: Emission Inventory
Port Name
Philadelphia, PA
Plaquemines, LA, Port of
Port Angeles, WA
Port Arthur, TX
Port Canaveral, FL
Port Dolomite, Ml
Port Everglades, FL
Port Hueneme, CA
Port Inland, Ml
Port Manatee, FL
Portland, ME
Portland, OR
Presque Isle, Ml
Providence, Rl
Redwood City, CA
Richmond, CA
Richmond, VA
Sacramento, CA
San Diego, CA
San Francisco, CA
Sandusky, OH
Savannah, GA
Searsport, ME
Seattle, WA
South Louisiana, LA, Port
of
St. Clair, Ml
Stockton, CA
Stoneport, Ml
Tacoma, WA
Tampa, FL
Texas City, TX
Toledo, OH
Two Harbors, MN
Valdez, AK
Vancouver, WA
Wilmington, DE
Wilmington, NC
RSZ
Speed
(knts)
c
10
a
7
10
e
7.5
12
e
9
10
b
e
9
12
12
10
12
12
12
e
13
9
a
10
e
12
e
a
9
c
e
e
10
b
c
10
RSZ
distance
(naut mi)
88.1
52.4
65
21
4.4
3
2.1
2.8
3
27.4
11.4
105.1
3
24.9
36
22.6
106.4
90.5
11.7
14.4
3
45.5
22.2
133.3
142.8
3
86.9
3
150.5
30
15.1
3
3
27.2
95.7
65.3
27.6
Final RSZ End Point(s)
Longitude
-75.0095
-89.4248
-89.137
-124.771
-93.7552
-80.5328
-84.2445
-80.082
-119.238
-85.6524
-83.0364
-70.1077
-124.137
-87.082
-71.3334
-122.632
-122.632
-75.8067
-122.632
-117.315
-122.632
-82.5251
-78.0498
-68.7645
-124.771
-89.4248
-89.137
-82.5838
-122.632
-83.2355
-124.771
-83.0364
-94.6611
-83.3034
-91.4414
-146.881
-124.137
-75.0095
-80.325
Latitude
38.79004
28.91161
28.98883
48.49074
29.55417
28.41439
45.83181
26.08627
34.10859
45.87553
27.59078
43.54224
46.22011
46.5804
41.41708
37.76094
37.76094
36.8468
37.76094
32.62184
37.76094
41.56193
33.83598
44.1179
48.49074
28.91161
28.98883
42.55923
37.76094
45.25919
48.49074
27.59078
29.3247
41.7323
46.93391
60.86513
46.22011
38.79004
31.84669
a Cruise speed through Strait of Juan de Fuca, then varies by ship type for remaining journey
b Inbound on Columbia River at 6.5 knots, outbound at 12 knots
0 Speed varies by ship type similar to typical like port
d Speed varies by ship DWTs
e All Great Lake ports have reduced speed zone distances of 3 nautical miles with
speeds halfway between service speed and maneuvering speed.
5-149
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Regulatory Impact Analysis
APPENDIX 3B
Inventory Impacts of Alternative Program
The final program represents a comprehensive approach to reduce emissions from
Category 3 marine diesel engines. As we developed this proposal, we evaluated an alternative,
which considers the possibility of pulling ahead the CAA Tier 3 NOx standard from 2016 to
2014. NOx emissions were calculated for the year 2023 under three scenarios: Tier 1 only NOx
standards (the base case), the coordinated strategy as presented in the final rule which includes
the 2016 NOx standards in effect 2016 (the primary case), and NOx standards for U.S.-vessels
only pulled ahead to 2014 (the alternative case). This appendix describes the methodology that
was used to estimate the NOx inventories for the final and alternative program scenarios in 2023.
The inventories described in this chapter are for calendar years 2002, 2020, and 2030. To
calculate inventories for 2023, a spreadsheet model was developed and used. For both the final
and alternative scenarios, it was assumed that the proposed EGA controls apply within 200
nautical miles for all 48 contiguous states. The only difference modeled was the different start
dates for Tier 3. Note that only emissions from U.S. vessels are impacted by the alternative.
Under the base scenario, 48-state NOx emissions in 2023 are 10,494,636 short tons.
With the coordinated strategy in effect (the primary case), 48-state NOx emissions in 2023 are
7,515,389 short tons, a 28.4 % reduction from Tier 1 only standards. Under the alternative
scenario, 48-state NOX emissions in 2023 are 7,444,866 short tons, a difference of 0.9 percent
from the primary case (Figure 3B-1).
TO
0)
>>
I
to
c
o
r
o
r-
to
to
c
0
'to
to
'E
LU
X
o
i,uuu,uuu -
900,000
800,000
700,000
600,000
500,000
400,000
300,000
200,000
100,000
n
Tier 3 in 2016
— 'Tier 3 in 2014 for U.S. ships
!••• ^B ^
^^^^-^ - -.^^
2014 2015 2016 2017 2018 2019 2020 2021
Calendar Year
2022 2023
Figure 3B-1 NOX Emissions with the Primary Case (Tier 3 in 2016) versus the Alternative Case (Tier 3 in
2014 for U.S. vessels only)
3-150
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Chapter 3: Emission Inventory
References
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Regulatory Impact Analysis
12 Starcrest Consulting Group (June 2004). Port-Wide Baseline Air Emissions Inventory,
prepared for the Port of Los Angeles, Docket ID EPA-HQ-OAR-2007-0121-0171.
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Clearances available at http://www.iwr.usace.army.mil/ndc/db/entclrn/data/entrclrn02/, Docket
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16 U.S. Army Corps of Engineers (2006). National Waterway Network, Available online at
http://www.iwr.usace.army.mil/ndc/data/datanwn.htm, Downloaded April 2006, Docket ID
EPA-HQ-OAR-2007-0121-0193.1.
17 ARCADIS Geraghty & Miller, Inc. (September 1999). Commercial Marine Activity for Deep
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Lake and Inland River Ports in the United States, prepared for the U.S. Environmental Protection
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EPA420-R-02-019, Docket ID EPA-HQ-OAR-2007-0121-0144.
20 California Air Resources Board (2005), 2005 Oceangoing Ship Survey, Summary of Results,
Docket ID EPA-HQ-OAR-2007-0121-0149.
21 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.
22 U.S. Environmental Protection Agency (January 2009). Category 3 Marine Engine CO and HC
Emission Factors, Memorandum from Ari Kahan to Docket EPA-HQ-OAR-2007-0121, Docket
ID EPA-HQ-OAR-2007-0121-0173.
23 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.
24 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.
5-152
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Chapter 3: Emission Inventory
25 Memo from Chris Lindhjem of ENVIRON (2005). PM Emission Factors, December 15, 2005,
Docket ID EPA-HQ-OAR-2007-0121-0162.
26 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.
27 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, Docket ID EPA-HQ-OAR-
2007-0121-0146.
28 Starcrest Consulting Group (January 2007). Draft Port of Los Angeles Air Emissions
Inventory for Calendar Year 2005, Docket ID EPA-HQ-OAR-2007-0121-0145.
29 Starcrest Consulting Group (April 2007). Puget Sound Maritime Air Forum Maritime Air
Emissions Inventory, Docket ID EPA-HQ-OAR-2007-0121-0166.
30 Starcrest Consulting Group, LLC (April 2003). The New York, Northern New Jersey, Long
Island Nonattainment Area Commercial Marine Vessel Emission Inventory, Vol 1 - Report,
Prepared for the Port Authority of New York & New Jersey, United States and the Army Corps
of Engineers, New York District, Docket ID EPA-HQ-OAR-2007-0121-0152.
31 Starcrest Consulting Group, LLC (November 2000). Houston-Galveston Area Vessel
Emissions Inventory, Prepared for the Port of Houston Authority and the Texas Natural Resource
Conservation Commission, Docket ID EPA-HQ-OAR-2007-0121-0147.
32 Eastern Research Group and Starcrest Consulting Group, LLC (January 2004). Update To The
Commercial Marine Inventory For Texas To Review Emissions Factors, Consider A Ton-Mile
El Method, And Revise Emissions For The Beaumont-Port Arthur Non-Attainment Area Final
Report, Submitted to the Houston Advanced Research Center, Docket ID EPA-HQ-OAR-2007-
0121-0153.
33 Zuber M. Farooqui and Kuruvilla John (June 2004). Refinement of the Marine Emissions
Inventory for the Corpus Christi Urban Airshed, Department of Environmental Engineering,
Texas A&M University - Kingsville, Proceedings of the 97th Annual A&WMA Conf. &
Exhibition, Docket ID EPA-HQ-OAR-2007-0121-0160.
34 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,
October 2007, Docket ID EPA-HQ-OAR-2007-0121-0063.1.
35 ENVIRON International Corporation (March 2007). LADCO 2005 Commercial Marine
Emissions, Docket ID EPA-HQ-OAR-2007-0121-0158.
36 California Air Resources Board (October 2005). Emissions Estimation Methodology for
Ocean-Going Vessels, Docket ID EPA-HQ-OAR-2007-0121-0164.
37 E.H. Pechan & Associates Inc. (June 2005), Commercial Marine Inventories for Select
Alaskan Ports, Final Report, Prepared for the Alaska Department of Conservation, Docket ID
EPA-HQ-OAR-2007-0121-0165.
3-153
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Regulatory Impact Analysis
38ICF 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-O AR-2007-0121-0154.
39 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 113.111, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
40 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 113.111, May 2006, Docket ID EPA-HQ-OAR-2007-0121-0013.
41 Lloyd's Register and International Maritime Organization, Marine Exhaust Emission
Quantification Study - Baltic Sea, in MEPC 45/INF.7. 1998, Docket ID EPA-HQ-OAR-2007-
0121-0389.
42 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, Docket ID EPA-
HQ-OAR-2007-0121-0148.
43 Corbett, JJ. and H.W. Koehler (2003). Updated Emissions from Ocean Shipping, Journal of
Geophysical Research, 108(D20); p. 4650, Docket ID EPA-HQ-O AR-2007-0121-0176.
44 Corbett, J. J. 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), Docket ID EPA-HQ-OAR-2007-0121-0159.
45 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, Docket ID EPA-HQ-OAR-2007-0121-0161.
46 IMO. 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/INF.10 12/28/2007, Docket ID EPA-HQ-OAR-2007-0121-
0118.
47 Transport Canada (2004). Transportation in Canada Annual Report 2004. (Tables 3-26 and 8-
27). http://www.tc.gc.ca/pol/en/report/anre2004/8F_e.htm, Docket ID EPA-HQ-O AR-2007-
0121-0169.
48 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-O AR-2007-0121-0063.3.
49 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
3-154
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Chapter 3: Emission Inventory
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.
50 Corbett, James and Chengfeng Wang (October 26, 2005). Emission Inventory Review SECA
Inventory Progress Discussion, p 11, memorandum to California Air Resources Board, Docket
ID EPA-HQ-OAR-2007-0121-0168.
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 California Air Resources Board ( September 2005). 2005 Oceangoing Ship Survey, Summary
of Results, Docket ID EPA-HQ-OAR-2007-0121-0149.
53 U.S. Maritime Administration, Office of Statistical and Economic Analysis (April 2006).
Vessel Calls at U.S. & World Ports, 2005, Docket ID EPA-HQ-OAR-2007-0121-0040.
54 Santa Barbara County Air Quality News, Issue 62, July-August 2001, Docket ID EPA-HQ-
OAR-2007-0121-0167.
5-155
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Regulatory Impact Analysis
CHAPTER 4: Technological Feasibility
In this chapter, we describe in detail the analysis of emission control technologies we
used to develop the new standards. Section 4.1 presents an overview of the standards and the
emission control technologies we expect will be used in meeting these standards. Section 4.2
describes the in-cylinder, or engine design-based, emission control technologies that can be used
to meet the Tier 2 standards. Section 4.3 describes the exhaust aftertreatment and water-based
emission control technologies that can be used to meet the Tier 3 standards. Section 4.4
describes technologies associated with switching to low sulfur distillate fuel or, alternatively,
using exhaust gas cleaning devices to remove sulfur from the exhaust. Section 4.5 presents
technology that can be used to produce and distribute additional low sulfur distillate fuel.
Section 4.6 discusses the potential impact of the standards on safety, noise, and energy.
4.1 Overview of Emissions Standards and Emission Control Technologies
Our current emission standards for Category 3 marine engines are equivalent to the NOx
limits in Annex VI to the Convention for the Prevention of Pollution from Ships (MARPOL).
These standards, referred to as "Tier 1", were adopted by the EPA in 2003 and went into effect in
2004. Globally, these standards went into effect 2003 and became retroactive for vessels built
from 2000 to 2002. The Tier 1 standards rely on engine-based technologies to reduce emissions.
The International Maritime Organization recently amended Annex VI to include new tiers of
NOx standards for new engines that reflect the use of advanced emission control technologies,
including exhaust aftertreatment; these Tier 2 and Tier 3 standards will go into effect in 2011 and
2016, respectively. The Annex VI amendments also include limits on the sulfur content of fuel
that will reduce SOx and PM emissions, and NOx limits for existing engines that will take effect
as soon as certified Approved Methods are available.
To meet the Tier 2 standards (which require approximately 15 to 21% reductions in NOx
relative to Tier 1, depending on rated engine speed), advanced, engine-based improvements will
be needed. These engine-based approaches for Tier 2 can include changes and/or advancements
to turbocharger, valve timing, compression ratio, combustion chamber, and common-rail fuel
injection system designs. The extent to which any or all of these engine-based improvements are
used is dependent upon the level of emission reduction needed for a given engine. The fuel
injection approaches to reducing engine-out NOx emissions are described in detail in Section 4.2.
To meet the Tier 3 standards (which require an 80% reduction in NOx, relative to Tier 1),
further engine-based approaches, such as Exhaust Gas Recirculation (EGR), direct water
injection, fuel-water emulsifi cation, and intake air humidification are under development. We
anticipate that exhaust aftertreatment approaches, such as Selective Catalytic Reduction (SCR),
will used, in many cases, to achieve the necessary NOx reductions. SCR is a common catalytic
exhaust emission control used for meeting more stringent NOx emissions standards in worldwide
diesel applications. Stationary, coal-fired power plants have used SCR for three decades as a
means of controlling NOx emissions, and currently, U.S. and European heavy-duty truck
manufacturers are using this technology to meet the more-stringent NOx limits. In the Category
2 and Category 3 marine sector, at least 300 vessels are currently equipped with SCR systems to
control NOX emissions. Our analysis, described in detail in Section 4.3, projects that SCR will
4-2
-------
Chapter 4: Technological Feasibility
be a viable technology available to Category 3 engine manufacturers to meet the Tier 3 NOx
standard.
4.2 Emission Control Technologies for Tier 2 Standards
4.2.1 In-Cylinder NOX Controls
The engine-out, or in-cylinder, NOx emissions of a diesel engine can be controlled by
utilizing engine design and calibration parameters (e.g. fuel delivery and valve timing) to limit
the formation of NOx. The formation rate of NOx has a strong exponential relationship to
combustion temperature; high combustion temperatures result in high NOx formation rates.1'2
Any changes to the engine design or combustion process which can lower the peak temperature
will reduce NOx emissions. Most of the engine-out NOx emission control technologies
discussed in the following in this Section reduce NOx emissions by reducing the level and
duration peak combustion temperatures, while balancing the impact on PM emissions, fuel
consumption, and torque output.
Control of diesel emissions by modifying the combustion processes is often characterized
by trade-offs in NOx emission control versus other parameters such as PM emissions, and fuel
consumption. For example, lower oxygen content (through exhaust gas recirculation, or EGR)
lowers NOx formation but may increase PM formation. Advanced (earlier) injection timing
reduces PM emissions but increases NOx formation, while retarded (later) injection timing
reduces NOx formation but increases PM formation, increases fuel consumption, and at high
torque output levels, can increase soot accumulation within the lubricating oil. During engine
development, these trade-offs are balanced against each other in order to obtain effective NOx
and PM control while maintaining acceptable power output, fuel efficiency, and engine
durability. The introduction of more-advanced electronic fuel injection systems and the
flexibility these systems provide in terms of injection timing, fuel delivery rate, number of
injection events per combustion cycle can improve these tradeoffs, allowing for reduced
emissions of both NOx and PM, while minimizing the impact on fuel efficiency.
Electronic control of injection timing has been used by highway, nonroad, locomotive,
and marine diesel engine manufacturers to balance NOx emissions, PM emissions, fuel
efficiency, engine performance and engine durability. While in-line, unit-injector, and common-
rail injection systems can all benefit from electronic controls, it is the common-rail system which
provides the greatest flexibility of controlling the injection timing, pressure, flow rate, as well as
the number of injection events for each combustion cycle. Engine manufactures, such as MAN
B&W and Wartsila, have already incorporated common rail systems into their Tier 1 engine
designs, and we expect that manufacturers will continue to improve these systems to further
reduce NOx emissions while minimizing the effect on PM emissions and fuel consumption.
4.2.1.1 Fuel Injection Pressure and Timing
Delaying the start of fuel injection, and thus the start of combustion, can significantly
reduce NOx emissions from a diesel engine. The effect of injection timing on emissions and
performance is well established.3'4'5'6 Delaying the start of combustion by retarding injection
timing aligns the heat release from the fuel combustion with the portion of the power (or
4-3
-------
Regulatory Impact Analysis
combustion) stroke of the engine cycle after the piston has begun to move down. This means
that the cylinder volume is increasing and that work (and therefore heat) is being extracted from
the hot gases. The removal of this heat through expansion lowers the temperature in the
combustion gases. NOX is reduced because the premixed burning phase is shortened and
because cylinder temperature and pressure are lowered.
Injection timing retard typically reduces NOx while increasing HC, CO, PM, and fuel
consumption because the end of injection comes later in the combustion stroke, where the time
for extracting energy from fuel combustion is shortened and the cylinder temperature and
pressure are too low for more complete oxidation of PM. The increases in HC, CO, and PM can
be offset by increasing injection pressure, allowing an earlier end of injection at the same torque
output (i.e., shorter injection duration for the same quantity of fuel injected), and by using
multiple injection events following the primary combustion event to enhance soot oxidation.
While injection timing retard can achieve the 20% reduction in NOx required for Tier 2, and HC,
CO, and PM increases can be eliminated, or minimized, through optimization for the injection
strategy.
We expect that electronic control of the fuel injection timing and pressure will be used by
manufacturers of Tier 2 and Tier 3 engines to reduce engine-out NOx emissions.
4.2.1.2 Common Rail Fuel Injection Systems
The most recent advances in fuel injection technology for marine use are high-pressure
common rail injection systems with the ability to use multiple injections and rate shaping (i.e.,
adjusting the flow rate of fuel delivered throughout the injection event as a function of crank
angle) to control the timing and quantity of fuel delivered to the engine over the course of a
single combustion event. Common rail systems can provide both NOx and PM reductions and
are in widespread use in heavy-duty on-highway diesel engines, and are also used in many
current nonroad diesel engines. These common rail systems provide precise control of the fuel
injection event, allowing it to be broken up into discrete, multiple phases. Injecting a small
quantity of fuel early in the compression stroke (or well before the piston reaches top-dead-
center) is known as "pilot" injection. The ignition of this smaller quantity of fuel limits the rapid
increase in pressure and temperature (and the associated NOx formation) which is characteristic
of premixed diesel combustion. Injecting the remainder of the fuel quantity into the established
flame resulting from the pilot injection then allows for a steady burn which limits the combustion
temperature, and hence NOx emissions. Rate shaping of the fuel injection event can be done
either mechanically or electronically, and has been shown to reduce NOx emissions by up to 20
percent diesel engines.7
A further splitting of the injection event, using a late cycle, or post-main, injection pulse
has been shown to significantly reduce particulate emissions, most notably in cases where
retarded injection timing, or a combination of injection timing retard and EGR, is used to control
NOx.8'9'10'11 With this approach, the typical diffusion-burn combustion event is broken up into
two events; a main injection which is terminated, followed by a short dwell period with no
injection, and a short, post-main injection event, see Figure 4-1. The second pulse of injected
fuel induces late-combustion turbulent mixing. The splitting of the injection event into two
4-4
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Chapter 4: Technological Feasibility
events aids in breaking up and entraining the "soot cloud" formed from the first injection event
into the bulk cylinder contents, allowing further combustion of the soot can occur.
o>
1
CD
£ 0
-10 0 10 20 30 40
(TDC) °Crank Ang|e
Figure 4-1 An Example of Using Multiple Fuel Injection Events to Induce Late-Combustion Mixing and
Increase Soot Oxidation for PM Control (adapted from Pierpont, Montgomery, and Rietz, 1995)
By utilizing a fuel delivery strategy which incorporates retarded injection timing (for
reduced NOx emissions), multiple injections (to reduce the PM which would typically increase
with retarded injection timing), and rate shaping (to control the level and duration of peak
combustion temperatures), an engine can be operated in a manner which balances NOx
emissions, PM emissions, and fuel consumption under all operating conditions. As in the case of
Tier 1 engines, the application of common-rail technology (which allows a broad range of
control over the fuel injection and combustion process) can reduce fuel consumption, but the
ultimate fuel saving potential is limited by the NOx standard that the engine must comply with;
the lower the NOx standard, the less potential there is to reduce fuel consumption through
control of the fuel injection and combustion parameters.12 We project that fuel delivery
strategies which result in decreases in peak cylinder temperature and pressure to meet the Tier 2
NOx standard may increase fuel consumption by as much as 2%. However, engine
manufacturers may be able to reduce NOx emissions and reduce fuel consumption if the
compression ratio is increased while simultaneously reducing the excess air ratio (to maintain an
equivalent 'effective' compression ratio).13 In addition, Miller-cycle supercharging (in which
higher intake charge pressures and early closing of the intake valve can result in lower
combustion temperatures) can be used to reduce NOx emissions without increasing fuel
consumption.14
4.3 Emission Control Technologies for Tier 3 Standards
In this section we describe the emission control technologies that we believe will be used
to meet the Tier 3 standards. In general, these technologies involve the use of SCR exhaust
aftertreatment, water-based approaches (e.g., fuel-water emulsification, intake air humidification,
and direct water injection), and EGR to reduce NOx emissions. These technologies may be used
individually, or in combination with other technologies, to achieve the level of NOx reduction a
given manufacturer or engine design requires. SCR is a commonly-used aftertreatment
technology for diesel engines that can achieve a 90 to 95% reduction in NOx emissions in marine
applications.15 Light-duty, heavy-duty (both highway and nonroad), and marine diesel
applications have already begun using SCR technology to meet more stringent, aftertreatment-
4-5
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Regulatory Impact Analysis
forcing NOx standards and water-based technologies have been demonstrated in Category 3
marine applications. Given the preponderance of studies and data and our analysis summarized
in this section, we believe that these technologies are appropriate for Category 3 marine
applications.
4.3.1 Selective Catalytic Reduction
NOx emissions can be reduced substantially using SCR, a commonly-used technology
used to comply with NOx emissions standards in diesel applications worldwide. An SCR
catalyst reduces nitrogen oxides to N2 and water by using ammonia (NHa) as the reducing agent.
The most-common method for supplying ammonia to the SCR catalyst is to inject an aqueous
urea- water solution into the exhaust stream. In the presence of high-temperature exhaust gas
(greater than 250 °C), the urea hydrolyzes to form NH3 and CO2; the NH3 is stored on the surface
of the SCR catalyst where it is used to complete the NOx-reduction reaction. In theory, it is
possible to achieve 100% NOx conversion if the NHa-to-NOx ratio (a) is 1 : 1 and the space
velocity within the catalyst is not excessive (i.e., there is ample time for the reactions to occur).
The urea dosing strategy and the desired a are dependent on the conditions present in the
exhaust; namely gas temperature and the quantity of NOx present (which can be determined by
engine mapping, temperature sensors, and NOx sensors). However, given the space limitations
in packaging exhaust aftertreatment devices mobile and marine applications, an a of 0.85-1.0 is
often used to balance the need for high NOx conversion rates against the potential for NH3 slip
(where NHs passes through the catalyst unreacted).
Stationary power plants fueled with coal, diesel, and natural gas have used SCR for three
decades as a means of controlling NOx emissions. European heavy-duty truck manufacturers are
using this technology to meet Euro 5 emissions limits and several heavy-duty truck engine
manufacturers have indicated that they will use SCR technology to meet stringent U.S. NOx
limits beginning in 2010. Studies have shown that a selective catalytic reduction (SCR) system
is capable of providing well in excess of 80% NOx reduction efficiency in high-power, heavy-
duty diesel applications.16'17'18 SCR has also been demonstrated for use with marine diesel
engines. To date, more than 300 SCR systems, developed by Argillon, Wartsila, Munters, and
other companies, have been installed on marine vessels. Some of which have been in operation
for more than 10 years and have accumulated 80,000 hours of operation.19'20'21'22 These systems
are used in a wide range of ship types including ferries, supply ships, RoRos (roll-on roll-off),
tankers, container ships, icebreakers, cargo ships, workboats, cruise ships, and foreign navy
vessels for both propulsion and auxiliary engines. These SCR units are being used successfully
on low- and medium-speed Category 3 propulsion engines and on Category 2 propulsion and
auxiliary engines. The fuel used on ships with SCR systems ranges from low sulfur distillate
fuel to high sulfur residual fuel. In marine applications, SCR is capable of reducing NOx
01 0 A OS 0^
emissions more than 90 percent. ' ' ' An example of the performance capability of SCR in a
medium-speed diesel marine application is the Staten Island Ferry Alice Austen. This
demonstration project reports that 90 to 95% NOx reduction is possible under steady-state
conditions where the exhaust gas temperature is above 270 °C.27
Marine engine manufacturers report that the minimum exhaust temperature for SCR
operation ranges from 250 to 300°C, depending on the catalyst system design and fuel sulfur
level.28'29'30 Below this temperature, the SCR catalyst unit would not be hot enough to efficiently
4-6
-------
Chapter 4: Technological Feasibility
reduce NOx. An example of the effect of exhaust gas temperature on the NOx conversion
efficiency of an SCR catalyst is shown in Figure 4-3. If the engine is able to use fuel with very
low sulfur levels, a highly reactive oxidation catalyst can be used upstream of the SCR unit to
convert NO to NO2, improving the low temperature efficiency of the SCR. NO2 reacts in the
SCR catalyst at lower temperatures than NO and therefore, use of an oxidation catalyst can lower
the exhaust temperature at which an SCR unit is effective. However, as the sulfur concentration
in the fuel increases, a less reactive oxidation catalyst must be used to prevent excessive
formation of sulfates and poisoning of the oxidation catalyst. When operating on marine
distillate fuel with a sulfur level of 1,000 ppm, the minimum exhaust temperature for effective
reductions through a current SCR system would be on the order of 270°C. On typical heavy fuel
oils, which have sulfur concentrations on the order of 2.5 percent, the exhaust temperature would
need to be about 300°C due to high sulfur concentrations. Sea trial test data from a vessel
equipped with a 55 MW, low-speed main engine indicates that turbine inlet exhaust gas
temperatures, illustrated in Figure 4-2, will be near, or above, the minimum level needed to
achieve greater than 80% NOx reduction for all operating loads of the E3 test cycle (which
includes power levels from 25 to 100%).31
400
350 --
300
250
200
150
100
50
-Turbine Inlet
-Turbine Outlet
10 20 30 40 50 60
Engine Load (% of rated power)
70
90
Figure 4-2 Example of Exhaust Gas Temperature as a Function of Engine Load on a 55 MW, 2-stroke, Low-
Speed Main Propulsion Engine31
As shown in Figure 4-3, the NOx conversion efficiency of an SCR catalyst can be greater
than 90% (for the 'turbine inlet' exhaust gas temperatures observed in the sea trial data shown in
Figure 4-2). And even at the relatively cooler turbine temperatures, it is possible to achieve NOX
4-7
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Regulatory Impact Analysis
conversion efficiencies greater than 80%. We believe that modern SCR systems will be able to
achieve the NOx reduction levels sufficient to meet or exceed the Tier 3 standard.
100
Example of
pre-turbo
exhaust gas
temperature
range for low-
speed main
engine (@ 25-
to-85% load)
200
250 300 350
Exhaust Gas Temperature @ Catalyst Inlet (°C)
400
450
Figure 4-3 SCR NOX Conversion Efficiency versus Exhaust Temperature Using an Ammonia-to-NOx Ratio of
1:132
In determining the stringency of the Tier 3 standards, we considered important issues
related to in-use compliance throughout the useful life across the duty cycle. To comply with the
Tier 3 standards manufacturers will need to design the SCR system to achieve greater than 80
percent reductions at higher power modes to offset lower efficiency at the 25 percent power
mode. They will also need to include a compliance margin to address in-use deterioration and
production variability. The final standards are consistent with the statutory direction to set
standards requiring the greatest degree of emission reduction that is achievable in the given time
frame.
In cases such as low power operation (less than 25% engine load), where exhaust
temperatures could fall below the minimum required to ensure proper SCR functioning, we
believe there are several approaches to ensure that exhaust temperatures remain high. An
example of such approach, proposed by Munters, is to position the SCR system ahead of the
turbocharger inlet.33 On turbocharged engines, the exhaust gas temperature is always higher at
the inlet (or before the turbine stage) than at the outlet. When exhaust gasses pass through the
turbine stage, heat energy from the exhaust gas is converted into shaft work, where it is then used
to compress the intake air. By positioning the SCR before the turbocharger inlet, where exhaust
gas temperatures are higher, the engine load range over which the SCR can operate is extended.
4-8
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Chapter 4: Technological Feasibility
For example, during sea trials on a 55 MW low-speed main engine, the exhaust gas temperature
conditions at the turbine inlet would allow SCR operation at 12% engine load, whereas the
turbine outlet temperature conditions would only SCR operation over a narrower much narrower
load range (approximately 15 to 50% engine load), unless other measures are taken to increase
exhaust heat. Such measures to increase exhaust heat may include reducing the level of charge
air cooling or modifying the injection timing. Another approach to increase the exhaust
temperature would be to use burner systems during low power operation. The "pre-
turbocharger" SCR approach has been used on vessels equipped with slow-speed engines which
require NOx control when operating at low loads near a coastal areas.34 In one case, SCR was
used on a short passenger car ferry which originally had exhaust temperatures below 200°C
when the engine was operated at low load.35 When the SCR unit was installed, controls were
placed on the intercooler in the air intake system. By reducing the amount of cooling on the
intake air, the exhaust temperature was increased to be within the operating range of the SCR
unit, even during low power operation. On a ship using multiple propulsion engines, one or
more engines could be shut down such that the remaining engine (or engines) operating at higher
power. Whichever approach is used, we believe that engine manufacturers will be able to
design systems which allow the SCR to function at engine loads below 25%, yet still remain
below the upper temperature limit (500 °C) of the SCR unit during high-load operation.
The onboard storage of the aqueous urea solution on marine vessels can be accomplished
through segmenting of the existing fuel tanks or the fitment of a separate stainless steel or plastic
urea tank. To assure consistent SCR operation between refueling stops, the volume of urea-
water solution carried onboard will need to be sufficient; the amount of solution required is
dependent on the expected NHa-to-NOx ratio (a) of the engine under the normal operating
conditions. At the appropriate intervals, the vessel operator will need to refill the urea tank. The
distribution and dispensing of urea is already established for on-road sectors, and is being
developed for the nonroad, railroad, and marine sectors as well. We expect that the distribution
and dispensing of urea for Category 3 marine vessels will benefit from any solutions put in place
by these other sectors, and should be in place well in advance of the Tier 3 regulations.
SCR- or emissions-grade urea is a widely used industrial chemical around the world.
Although an infrastructure for widespread transportation, storage, and dispensing of SCR-grade
urea does not currently exist in most shipping ports, we believe that it will develop as-needed,
based on market forces. Concerning urea production capacity, the U.S. has more than sufficient
capacity to meet the additional needs of the marine sector. Currently, the U.S. consumes 14.7
million tons of ammonia resources per year, and relies on imports for 41 percent of that total (of
which, urea is the principal derivative). In 2005, domestic ammonia producers operated their
plants at 66 percent of rated capacity, which provides 4.5 million tons of reserve production
capacity.36 Thus we do not project that urea cost, supply, or infrastructure will be an issue in the
2016 timeframe for implementation of the Tier 3 standards.
4.3.2 Water-Based Technologies
In this Section we describe the "water-based" technologies which can be used to reduce
NOX emissions. All of these approaches to reducing engine-out NOX are based on limiting the
formation of NOx by limiting the peak combustion temperature. It is the heat capacity of water,
its ability to absorb combustion energy, which limits the peak combustion temperature, and
4-9
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Regulatory Impact Analysis
hence NOx formation. Whether this water is emulsified with fuel, injected directly into the
combustion chamber, or in the form of humidity within the intake air, its purpose is to limit the
peak combustion temperature. These water-based approaches to controlling NOx emissions,
when used in combination with the engine design-based approaches, such as fuel injection
controls, EGR, and variable valve timing, are also capable of providing significant (up to 60%)
NOx reductions.13 Whichever approach or combination of approaches is employed by engine
manufacturers reduce Tier 2 and Tier 3 NOx emissions, we believe that these water-based
technologies are feasible and can be implemented within the timeframe of this rule.
4.3.2.1 Fuel-Water Emulsions
Fuel-water emulsions for marine engines can be either diesel fuel-water mixtures, with
emulsifying and/or stabilizing agents added, or a heavy fuel oil-water mixtures. When a fuel-
water mixture is injected into the combustion chamber, vaporization of water within the mixture
injection increases fuel dispersion (making the combustion of fuel more efficient) and absorbs
combustion heat, which limits the formation of NOx. For each 0.7 to 1% of water added to the
fuel, a 1% reduction in NOx emissions can be realized.35'37 Engine manufacturers have
demonstrated NOX reductions of up to 50% through the use of fuel-water emulsions alone.38'39
In many existing engine designs, the limiting factor for fuel-water emulsions is the delivery
capacity of the fuel injection system; to maintain the same power level (i.e., keep the quantity of
fuel injected constant), the injection system must have enough volume capacity to deliver the
quantity of fuel normally injected, plus an additional volume of water emulsified within the fuel.
We believe that future injection systems which utilize fuel-water emulsions will be designed to
accommodate the amount of water in the fuel necessary to meet the applicable NOx standard
while maintaining engine power at the same level observed when running on 100% fuel.
4.3.2.2 Direct Water Injection
Direct water injection (DWI) technology involves introducing water into the combustion
chamber during the combustion process. The injection of water, whether directing into the
combustion chamber or into the intake manifold, can be controlled electronically, allowing
precise calibration and control of the water-to-fuel ratio. In the case where water is injected
directly into the combustion chamber (and separate from the fuel), electronic control also allows
precise control over timing and quantity of water injected as well. This approach allows water to
be injected at a point in the combustion process where it will provide the optimum NOx
reduction while minimizing the impact on other criteria pollutants (e.g. HC, CO, and PM) and
fuel consumption.40 Engine manufacturers have reported that DWI, when using a water-to-fuel
ratio of 40 to 70%, is capable of reducing NOx emissions by 50 to 60%, without affecting engine
power.24'35
4.3.2.3 Intake Air Humidification
Similar to fuel-water emulsions and direct water injection, increasing the humidity of the
intake air on a diesel engine reduces the peak temperature of combustion, and hence, reduces the
formation of NOx. One approach to introducing water into the combustion process is to increase
the humidity (water content) of the intake air through evaporation of a water mist, which is
injected to the intake air as it exits the compressor stage of the turbocharger. As intake air is
4-10
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Chapter 4: Technological Feasibility
compressed by the turbocharger, its temperature increases, and it is this temperature increase
which facilitates the evaporation of the injected water mist. To achieve a 50% reduction in NOx
emissions, the quantity of water that must be added to the intake air is roughly twice the quantity
of fuel consumed by the engine (or double the amount of water consumed in fuel-water emulsion
or DWI approaches for a similar NOx reduction).26
4.3.2.4 Exhaust Gas Recirculation
Exhaust gas recirculation (EGR) is a strategy which reduces peak combustion
temperature (and hence NOX formation, similar to water-based approaches) in which a non-
combustible gas is added to the combustion process. In this strategy, exhaust gas is typically
routed from the exhaust system and mixed with the incoming combustion air. The recycled
exhaust gas has lower oxygen content and also absorbs some of the heat energy during
combustion, both of which reduce the peak temperatures. MAN B&W has demonstrated that up
to 70% NOx reduction can be achieved when using EGR in combination with intake air
humidification.39 An alternative to routing/mixing exhaust gas with the incoming fresh air
charge is use "internal" EGR, where early closing of the exhaust valve is used to trap a portion of
the exhaust gas from the previous combustion event within the cylinder.41
4.4 Vessel Technologies for Low Sulfur Fuel Standards
The MARPOL Annex VI fuel sulfur limit for ships operating in an EGA is 1.5% today
and reduces to 1.0% in July 2010 and further to 0.1% in 2015. We anticipate that the 0.1% fuel
sulfur limit, beginning in 2015, will likely result in the use of distillate fuel for operation in
EGAs. This would require the vessel to switch from a higher sulfur fuel to 0.1% S fuel before
entering the EGA. The practical implications of fuel switching are discussed below. As an
alternative to operating on low sulfur fuel, an exhaust gas cleaning device may be used to
remove sulfur from the exhaust. These devices, which are colloquially known as SOx scrubbers,
are also discussed below.
4.4.1 Fuel Switching on Vessels
4.4.1.1 Impact of fuel switching on emissions
Currently, the majority of ocean-going vessels use residual fuel (also called 'Heavy Fuel
Oil (HFO) or 'Intermediate Fuel Oil' (IFO)) in their main propulsion engines, as this fuel is
relatively inexpensive and has a good energy density. This fuel is relatively dense ('heavy') and
is created as a refining by-product from typical petroleum distillation. Residual fuels typically
are composed of heavy, residuum hydrocarbons and can contain various contaminants such as
heavy metals, water and sulfur compounds. The current global average sulfur for residual
marine fuel is approximately 2.7%.42 It is these sulfur compounds that cause the SOx emissions
when the fuel is combusted.
Switching from operating marine engines on residual fuel to distillate fuel can reduce
exhaust PM emissions, both on a mass basis and on a particle basis. The sulfur in marine fuel is
primarily emitted as SO2; however, a small fraction (about 2 percent) is converted to SOs.
almost immediately forms sulfate and is emitted as direct PM by the engine. Consequently,
4-11
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Regulatory Impact Analysis
emissions of SC>2 and sulfate PM are very high for engines operating on residual fuel. Switching
from high sulfur residual fuel to low sulfur distillate fuel results in large reductions in SC>2 and
sulfate PM emissions.
In addition to high sulfur levels, residual fuel contains relatively high concentrations of
low volatility, high molecular weight organic compounds and metals. Organic compounds that
contribute to PM can be present either as a nucleation aerosol or as a material adsorbed on the
surfaces of agglomerated elemental carbon soot particles and metallic ash particles. The sulfuric
acid aerosol in the exhaust provides a nucleus for agglomeration of organic compounds.
Operation on higher volatility distillate fuel reduces both nucleation and adsorption of organic
compounds into particulate matter. Therefore, in addition to direct sulfate PM reductions,
switching from residual fuel to distillate fuel reduces organic PM and metallic ash particles in the
exhaust.
The impact of switching from high-sulfur residual fuel to lower sulfur distillate fuel on
PM levels has been investigated in a number of test programs.43'44'45'46'47 On a mass basis, PM
from marine engines has been shown to be reduced by 60 to 90 percent when switching from
residual to distillate fuel. Figure 4-4 presents the impact of fuel switching on direct PM
emissions for testing performed on one slow-speed two-stroke marine engine and four medium-
speed four-stroke marine engines.
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Figure 4-4 Effect of Fuel Switching on PM Emissions from Marine Engines
The PM emissions reductions presented above were primarily due to reductions in direct
sulfate PM. However, fuel switching also led to measured reductions in non-sulfate PM for
these engines. Specifically, significant reductions were observed in the soluble organic fraction
of the PM as well as metallic ash. This is demonstrated in the following charts, excerpted from
three of the papers referenced above, which present speciated PM reductions due to fuel
switching.
4-12
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Chapter 4: Technological Feasibility
1% Load; MOO
1% Load; HFO
100% Load; MOO
100% Load; HFO
Figure 4-5 Speciated PM from 2-Stroke Slow-Speed Engine (Kasper et al, 2007)
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Figure 4-6 Soluble Organic Fraction of PM from 4-Stroke Medium-Speed Engine (Nakajima et al, 2000)
Typical PM emission with HFO
Medium speed marine 4-stroke
Typical PM emission with MGO
Medium speed marine 4-stroke
Figure 4-7 Speciated PM from 4-Stroke Medium-Speed Engine (MAN, 2007)
4-13
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Regulatory Impact Analysis
Operating on distillate fuel also reduces the particle count in the exhaust. Lowering the
sulfur in the fuel reduces the relative fuel contribution to ultrafme nucleation aerosols by
reducing nucleation sites for organic PM. These nucleation particles are the largest contributor
to particle number, since the fine particle number count is approximately 1.5 times higher for
operation on residual fuel than for operation on distillate fuel. This effect is shown in Figure
4-g.48'49
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Figure 4-8 Exhaust Particle Concentration for Two Ships
4.4.1.2 Fuel Switching Procedures
Marine distillate fuels are similar in composition and structure to other petroleum based
middle distillate fuels such as diesel and No. 2 heating oil, but they have a much lower allowable
sulfur content than residual fuels.50 This lower sulfur content means that by combusting marine
distillate fuel in their propulsion engines, vessels operating within the EGA would meet the
stricter SOX requirements. However, sulfur content is not the only difference between the
marine residual and distillate fuels; they also have different densities, viscosities, and aromatic
contents.
In the majority of vessels today, marine distillate fuel is used for operation during routine
maintenance, prior to and immediately after engine shut-down, or in emergencies. Standard
procedures today have been established to ensure that this operational fuel switchover is
performed safely and efficiently. Mainly, in order for the vessel to completely switch from one
type of fuel to another, the fuel pumps and wetted lines will need to be completely purged by the
new fuel to ensure that the ship is burning the correct fuel for the area. This purging will vary
from ship to ship due to engine capacity, design, operation, and efficiency. Provided the ship has
separate service tanks for distillate and residual fuel (most, if not all, vessels do), fuel switching
time should be limited only by maximum allowable rate of fuel temperature change, typically not
4-14
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Chapter 4: Technological Feasibility
more than 2°C change per minute. Figure 4-9 presents three common fuel system configurations
recommended by a Category 3 engine manufacturer to facilitate fuel switching.
A.
B.
4-15
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Regulatory Impact Analysis
Figure 4-9 Common Fuel Tank Layouts. A. One MDO and one HFO settling tank, B. One MDO and two
HFO settling tanks, C. One MDO settling tank and two sets of HFO settling and service tanks (Courtesy of
MAN B&W)
This slow temperature increase will ensure that the fuel's viscosity does not drastically
change prior to injection and therefore protects the fuel injection equipment. If the fuel viscosity
or temperature is increased too quickly, some of the fuel handling components, such as the fuel
valves, pump plungers, or fuel suction valves, could become damaged or 'sticky' and not
function correctly. One way to ensure that the fuels are changed out accordingly is to install an
automatic system for handling the changeover of different viscosity fuels, as shown in Figure 4-
10 from MAN B&W.34
4-16
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Chapter 4: Technological Feasibility
Figure 4-10 Automatic System for Changeover between Fuels of Different Viscosity
The maritime industry has analyzed the differences between the residual and distillate
fuel compositions to address any potential issues that could arise from switching operation of a
Category 3 engine from residual fuel to distillate fuel. The results from this research has evolved
into routine operational switching procedures that ensure a safe and efficient way for the
Category 3 engines to switch operation between the residual and distillate fuels. Engine
manufacturers, fuel suppliers, and the U.S. Coast Guard have provided guidance on fuel
switching procedures.51'52'53'54'55 A brief summary of the fuel differences, as well as any potential
issues and their usual solutions are below.
4.4.1.2.1 Fuel Density
Due to its chemical composition, residual fuel has a slightly higher density than marine
distillates. Using a less dense fuel could affect the ballast of a ship at sea and would have to
require compensation. Therefore, when beginning to operate on the distillate fuel, the vessel
operator would have to pay attention to the vessel's ballast and may have to compensate for any
changes that may occur. We anticipate that these procedures would be similar to operating the
vessel with partially-full fuel tanks.
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Regulatory Impact Analysis
Another consideration when switching to a lower density fuel is the change in volumetric
energy content. Distillate fuel has a lower energy density content on a per gallon basis when
compared to the residual fuel; however, per ton, distillate fuel's energy density is larger than the
residual fuel. This means that when switching from residual fuel to distillate fuel, if the vessel's
tanks are volumetrically limited (i.e., the tanks can only hold a set quantity of fuel gallons), the
distance a vessel can travel on the distillate fuel may be slightly shorter than the distance the
vessel could travel on the residual fuel due to the lower volumetric energy content of distillate
fuel, which could require compensation. This distance reduction would be approximately 5%
and would only be of concern while the vessel was operating on the distillate fuel (i.e., while in
the U.S. EGA) as the majority of the time the vessel will be operating on the residual fuel.
However, if the vessel is limited by weight (draft), the higher energy content per ton of fuel
would provide an operational advantage.
4.4.1.2.2 Kinematic Viscosity
Residual fuel's kinematic viscosity is much higher than marine distillate fuel's viscosity.
Viscosity is the 'thickness' of the fuel. If this parameter is lowered from the typical value used
within a pump, some issues could arise. If a distillate fuel with a lower viscosity is used in a
system that typically operates on residual fuel, the decrease in viscosity could quickly cause
problems with high-pressure fuel injection pumps; whereas older, lower-pressure pumps can
develop troubles over a period of time, especially if the pump in question has large clearances
and cannot make up the pressure to pump the fuel through with the thinner fuel due to the
increased potential for internal leakage of the thinner fuel through the clearances in the pumping
elements. Internal leakage is part of the design of a fuel pump and is used in part to lubricate the
pumping elements. However, if this leakage rate is too high, the fuel pump could produce less
than optimal fuel injection pressures. If the distillate fuel's lower viscosity becomes an issue, it
is possible to cool the fuel and increase the viscosity above 2 centistokes, which is how most
vessels operate today during routine fuel switchovers as was discussed above.56'57
4.4.1.2.3 Flash Point
Flash point is the temperature at which the vapors off the fuel ignite with an outside
ignition source. This can be a safety concern if the owner/operator uses an onroad diesel fuel
rather than a designated 'marine distillate' fuel for operation because marine fuels have a
specified minimum flash point of 60°F to ensure onboard safety, whereas onroad diesel has a
minimum specified flash point of 52°F.58'59 However, since most distillate fuels are created in
the same fashion, typical flash points of onroad diesel are above 60°F and would meet the marine
fuel specification for this property. Bunker suppliers ensure that marine fuels meet a minimum
flash point of 60°C (140°F) through fuel testing as designated on the bunker delivery note.
4.4.1.2.4 Lubricity
Lubricity is the ability of the fuel to lubricate the engine/pump during operation. If the
distillate is more 'harsh' (from severely reduced sulfur content or removal of certain chemical
structures) than the residual fuel typically used, there can be added friction to the engine/pump
which could cause malfunctions and/or failures of equipment. Fuels with higher viscosity and
high sulfur content tend to have very good lubricity without the use of specific lubricity
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Chapter 4: Technological Feasibility
improving additives. Refining processes that lower fuel sulfur levels and their viscosities can
also remove some of the naturally-occurring lubricating compounds. Severe hydrotreating of fuel
to obtain ultra-low sulfur levels can result in poor fuel lubricity. Therefore, refineries commonly
add lubricity improvers to ultra low sulfur diesel. This will most likely become a concern when
very low levels of sulfur are present in the fuel and/or the fuel has been hydrotreated to reduce
sulfur, e.g., if ultra-low sulfur highway diesel (ULSD) is used in the engine. 60 Several groups
have conducted studies on this subject, and for some systems where fuel lubricity has become an
issue, lubricity additives can be utilized or the owner/operator can install a lubricating system for
the fuel pump.
4.4.1.2.5 Lube Oil
Diesel engines require lubrication in order to operate efficiently, and these lubricating
oils need to be compatible with the fuel used in the engine. Lube oil base numbers help to
achieve a compatible lubricant between the fuel and the oil. If the lube oil base is too lubricating
for the fuel, calcium and other deposits can develop on the surfaces. If the lube base oil is too
little of a lubricant for use with the fuel, the fuel's acidity can increase causing additional wear
on parts as well as creating problems combusting the fuel. Lube oils are used to neutralize acids
formed in combustion, most commonly sulfuric acids created from sulfur in the fuel. The
quantity of acid neutralizing additives in lube oil should match the total sulfur content of the fuel.
If excessive amounts of these additives are used, they may create deposits on engine
components. Marine engine manufacturers have recommended that lube oil only needs to be
adjusted if the fuel is switched for more than one week, but the oil feed rate may need to be
reduced as well as engine operating power. Additional research has been conducted in this area
and several oil companies have been working to create a lubricating oil that would be compatible
with several different types of fuel.61
4.4.1.2.6 Asphaltenes
Asphaltenes are heavy, non-volatile, aromatic compounds which are contained naturally
in some types of crude oil. Asphaltenes may precipitate out of the fuel solution when a fuel rich
in carbon disulfide, such as residual fuel, is mixed with a lighter hydrocarbon fuel, such as n-
pentane or n-heptane found in some distillate fuels.62 When these heavy aromatic compounds
fall out of the fuel solution, they can clog filters, create deposition along the fuel
lines/combustion chamber, seize the fuel injection pump, or cause other system troubles. This
risk can be minimized through onboard test kits and by purchasing distillate and residual fuel
from the same refiner. However, according to the California Air Resources Board, the formation
of asphaltenes is not seen as an issue based on data from previous maritime rules.63
As can be seen, if vessel operators choose to operate on marine distillate fuel while in the
EGA, some prudence is required. However, as described above, any issues that could arise with
switching between residual and distillate fuel are addressed through changes to operating
procedures. To conduct a successful switchover between the residual and marine distillate fuels,
vessel operators will need to keep the above issues in mind and follow the engine manufacturer's
standard fuel switching procedure.
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Regulatory Impact Analysis
4.4.1.2.7 Boilers
Steamships operate through the use of steam produced by boilers. In addition, boilers are
often used on diesel-propelled ships for auxiliary power. Auxiliary boilers may be used to heat
residual fuel, viscous cargo, water, and passenger spaces. In addition the boilers may be used to
distill fresh water, drive steam-turbine pumps, or provide power at port when the main engine is
turned off. Most marine boilers are primarily operated on heavy fuel oil. However, modern
boilers can generally operate on distillate fuel as well with minor adjustments. More significant
modifications are likely necessary for older boilers.64
To operate on residual fuel, the fuel must be heated to reduce its viscosity so that it can
be pumped to the boiler. In addition, the burners must be optimized for heavy fuel oil so that it
can be properly atomized for combustion. There are three common types of burners used;
pressure jet, rotary cup, and steam atomizing.65 Pressure jet burners are typically used in smaller
boilers and can run on both residual and distillate fuels. When distillate fuel is used, higher
amounts of fuel input may result in a risk of increased smoke if the burner and fuel control
system is not properly optimized. Rotary cup burners, especially in larger boilers, may need to
be modified to prevent coking when operating on lighter fuels. In addition, due to the easier
evaporation of lighter fuels, the control system for the main burner should be adjusted to prevent
an accidental ignition in case of a flameout. Steam atomizing burners are typically used on
larger boilers and can run on residual or distillate fuel. When distillate fuel is used, either the
lance must be replaced, or compressed air should be used as the atomizing medium, rather than
air to prevent over fueling.
Lloyd's Register published a list of recommendations for vessel operators to consider if
switching from residual fuel to distillate fuel with a marine boiler.66 These recommendations are
listed below:
• Boiler and fuel system manufacturers should be consulted for fuel switching guidance
and to confirm that the boiler, combustion control systems and associated fuel system
components, such as pumps, are suitable for the intended types of fuel.
• The furnace purge process must be functioning correctly. It is essential that the whole of
the furnace space is fully purged before re-lighting any fires.
• Burners, in general, and tips, in particular, must be appropriate to each type of fuel to be
used.
• The spark igniters (or equivalent) must be correctly functioning and positioned so as to
readily ignite the fuel spray on start up.
• All boiler flame detection and related safety systems must be operating correctly. In the
case of flame detectors, they must be correctly positioned to pick out the particular flame
pattern which is encountered with the types of fuel to be used.
• Manual and automated combustion control system functions should be checked as
necessary to ensure they are operating correctly and reliably.
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• Due to their searching nature, the use of gas oil fuels in systems which have generally
previously operated with HFO can result in seepage of fuel from pipe flanges, equipment
seams and other fittings.
• To ensure the minimum quantity of carbon deposition material within the combustion
and uptake spaces, soot blowers should be operated at the latest possible opportunity
before entry into coastal and port waters.
• The boilers, burner and fuel oil system, including the relevant automatic controls,
should be reviewed by means of a HAZOP workshop, through which the action points for
the operators and manufacturers can be identified.
• Oil fuel burning arrangements must be in accordance with the Rules of the relevant
classification society.
The American Bureau of Shipping also provides suggestions for the use of marine gas oil
as a fuel for boilers.67 These recommendations are generally similar to those provided by
Lloyd's; however, more detail is provided. For systems modified for use on distillate fuel, ABS
requires its members to submit a risk analysis and notes that the modifications are subject to
ABS review and approval, for both the design assessment and survey.
4.4.2 Exhaust Gas Cleaning Systems
Annex VI allows for alternative compliance strategies in including the use of exhaust gas
cleaning systems (EGCS). EGCS systems used today for sulfur control are commonly known as
SOx scrubbers.
4.4.2.1 SOX Scrubber
SOx scrubbers are capable of removing up to 95 percent of SOx from ship exhaust using
the ability of seawater to absorb SOx. SOx scrubbers have been widely used in stationary source
applications, where they are a well established SOx reduction technology. In these applications,
lime or caustic soda are typically used to neutralize the sulfuric acid in the washwater. While
SOx scrubbers are not widely used on ocean going vessels, there have been prototype
installations to demonstrate their viability in this application such as the Krystallon systems
installed on the P&O ferry Pride of Kent and the Holland America Line cruise ship the ms
Zaandam.68'69 These demonstrations have shown scrubbers can replace and fit into the space
occupied by the exhaust silencer units and can work well in marine applications.
There are two main scrubber technologies. The first is an open-loop design which uses
seawater as exhaust washwater and discharges the treated washwater back to the sea. Such open
loop designs, such as those used on the Pride of Kent and ms Zaandam, discussed above, are also
referred to as seawater scrubbers. In a seawater scrubber, the exhaust gases are brought into
contact with seawater, either through spraying seawater into the exhaust stream or routing the
exhaust gases through a water bath. The SO2 in the exhaust reacts with oxygen to produce sulfur
trioxide which then reacts with water to form sulfuric acid. The sulfuric acid in the water then
reacts with carbonate and other salts in the seawater to form sulfates which may be removed
from the exhaust. The washwater is then treated to remove solids and raise the pH prior to
discharge back to the sea. The solids are collected as sludge and held for proper disposal ashore.
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Regulatory Impact Analysis
A second type of SOx scrubber, using a closed loop design, is also feasible for use on
marine vessels.70'71 In a closed loop system, fresh water is used as washwater, and caustic soda
is injected into the washwater to neutralize the sulfur in the exhaust. A small portion of the
washwater is bled off and treated to remove sludge, which is held and disposed of at port, as with
the open loop design. The treated effluent is held onboard or discharged at open sea. Additional
fresh water is added to the system as needed. While this design is not completely closed loop,
strictly speaking, it can be operated in zero discharge mode for periods of time.
Exhaust gas scrubbers can achieve reductions in particulate matter as well. By removing
sulfur from the exhaust, the scrubber removes most of the direct sulfate PM. Sulfates are a large
portion of the PM from ships operating on high sulfur fuels. By reducing the SOx emissions, the
scrubber will also control much of the secondary PM formed in the atmosphere from SOx
emissions. However, simply mixing alkaline water in the exhaust does not necessarily remove
much of the carbonaceous PM, ash, or metals in the exhaust. While SO2 associates with the
wash water, particles can only be washed out of the exhaust through direct contact with the
water. In simple scrubber designs, much of the mass of particles can hide in gas bubbles and
escape out the exhaust.
Manufacturers have been improving their scrubber designs to address carbonaceous soot
and other fine particles. Finer water sprays, longer mixing times, and turbulent action would be
expected to directionally reduce PM emissions through contact impactions. One scrubber design
uses an electric charge on the water to attract particles in the exhaust to the water.72'73 In this
design, the exhaust gas is first passed through a preconditioning chamber where a coarse water
spray cools the exhaust, removes particles larger than 10 microns and causes very small particles
to agglomerate into larger particles. The exhaust gas then moves successively through one or
two cloud generation chambers, where highly charged water droplets form a cloud. These
droplets serve to attract the particles, and as each water droplet has collected enough tiny
particles and thus has its charge neutralized, it coagulates with other droplets and falls to a sump.
This liquid is then re-circulated back to the cloud generator and used to form new charged
droplets. Finally, the cleaned exhaust passes from the cloud chamber through a mist eliminator
to remove excess moisture and out through the exhaust stack. In the dual cloud chamber design,
the first chamber contains positively charged water droplets which collect neutral and negatively
charged particles. Conversely, the second chamber contains negatively charged water droplets
which collect positively charged and remaining neutral particles. Since most particles are
neutral, this second chamber would only be utilized in designs requiring very high particle
removal efficiency.
In another design, demisters are used that help effectively wash out PM from the exhaust
stream.74 In this design, the exhaust gases are compressed and then expanded in a saturated
environment. The expansion process in the supersaturated environment results in condensation
and agglomeration of fine parti culate, which is then washed from the exhaust stream using a
water spray. In either of these PM control system designs, however, the systems would be
effective at removing SO2 from the exhaust even if the additional hardware needed for non-
sulfate PM reduction were not used.
Water-soluble components of the exhaust gas such as SO2, SOs, and NO2 form sulfates
and nitrates that are dissolved into the discharge water. Scrubber wash water also includes
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suspended solids, heavy metals, hydrocarbons and polycyclic aromatic hydrocarbons (PAHs).
Before the scrubber water is discharged, it may be processed to remove solid particles through
several approaches. Heavier particles may be trapped in a settling or sludge tank for disposal.
The removal process may include cyclone technology similar to that used to separate water from
residual fuel prior to delivery to the engine. However, depending on particle size distribution
and particle density, settling tanks and hydrodynamic separation may not effectively remove all
suspended solids. Other approaches include filtration and flocculation techniques. Flocculation,
which is used in many waste water treatment plants, refers to adding a chemical agent to the
water that will cause the fine particles to aggregate so that they may be filtered out. Sludge
separated from the scrubber water would be stored on board until it is disposed of at proper
facilities.
The International Maritime Organization (IMO) has developed guidance criteria for the
use of exhaust gas cleaning devices, such as SOx scrubbers, as alternative to operating on low
sulfur fuel. This guidance, includes monitoring and water discharge practices.75 The washwater
should be continuously monitored for pH, PAH and turbidity. Further, the IMO guidance
include specifications for these same items, as well as nitrate content when washwater is
discharged in ports, harbors or estuaries. Finally, the IMO guidance recommends that washwater
residue (sludge) be delivered ashore to adequate reception facilities, and not discharged to the
sea or burned on board.
Another technology, which is currently under investigation, is the use of an exhaust gas
cleaning unit (EGCS) to reduce NOx emissions. One significant technological issue that must be
addressed is the prevention of nitrates from being introduced into the water. In a typical diesel
exhaust gas mixture, NOx is composed of roughly 5-10% NO2, with the majority of the
remainder in the form of NO. NO2 is soluble in water, and therefore may be removed by the
water in the scrubber. It is possible to treat the exhaust upstream of the scrubber to convert more
of the NOx to NO2, thereby facilitating the use of a scrubber to remove NO2.76 However, we are
concerned that this would add to nitrogen loading of the water in which the ship is operating. As
discussed in Section 2.3.1, nitrogen loading can lead to serious water quality impacts. This issue
addressed in the IMO EGCS guidelines by limiting the amount of nitrates that may be removed
by the scrubber, and washed overboard. However, a scrubber design may be acceptable if it
removes nitrates from the wash water, which in turn are disposed of properly, or prevents nitrates
from forming in the wash water.
One manufacturer has stated that their unique EGCS design converts NOx to nitrogen
(N2), rather than nitrates.77 In addition, to SOx, PM, and NOx, this system is designed to remove
CO2 from the exhaust. This system uses ultra-low frequency treatment and electrolysis to raise
the alkalinity of the seawater injected into the scrubber. The intent is to convert CO2 into
bicarbonates in the water.
4.4.2.2 Equivalence to Fuel Switching
MARPOL Annex VI does not present specific exhaust gas limits that are deemed to be
equivalent to the primary standard of operating on low sulfur fuel. Prior to the recent
amendments to Annex VI, regulation 13 included a limit of 6 g/kW-hr SO2 as an alternative to
the 1.5% sulfur limit for sulfur emission control areas. Under the amended requirements, the
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Regulatory Impact Analysis
specific SC>2 limit was removed and more general language on alternative approaches was
included. Specifically, regulation 4 of MARPOL Annex VI now states "The Administration of a
Party may allow any fitting, material, appliance or apparatus to be fitted in a ship or other
procedures, alternative fuel oils, or compliance methods used as a alternative to that required by
this Annex if such fitting, material, appliance or apparatus or other procedures, alternative fuel
oils, or compliance methods are at least as effective in terms of emissions reductions as that
required by this Annex, including any of the standards set forth in regulations 13 and 14."
Based on the methodology that was used to determine the SO2 limit of 6.0 g/kW hr for
existing EGAs, the corresponding limit, which is presented in the ECGS guidelines, would be 0.4
g/kW-hr SC>2 for a 0.1% fuel S limit. This limit is based on an assumed fuel consumption rate of
200 g/kW-hr and the assumption that all sulfur in the fuel is converted to SC>2 in the exhaust.
This calculation is presented in the following equation:
SO2 [g/kW-hr] = BSFC x fuel S x conversion x MWRs02/s
= 200 x 0.1% x 100% x 64/32
= 0.4 g/kW-hr, where:
BSFC = brake specific fuel consumption = 200 g/kW-hr
fuel S = fuel sulfur level (weight percent) = 0.1%
conversion = percentage of sulfur in fuel that is converted to SC>2 = 100%
MWRSo2/s = molecular weight ratio of SO2 to sulfur = 64/32
The IMO EGCS guidelines also use an approach of basing the limit on a ratio of 862 to
CC>2. This has the advantage of being easier to measure during in-use monitoring. In addition,
this ratio holds more constant at lower loads than a brake-specific limit, which would approach
infinity as power approaches zero. For the 1.5% fuel sulfur limit, a SO2 (ppm)/CO2(%) limit of
65 was developed.78 As with the equation above, the simplifying assumption is made that all
fuel sulfur is converted to SC>2 and all carbon is converted to CC>2. The equivalent limit for 0.1%
fuel sulfur presented in the ECGS guidelines is 4.0 SC>2 (ppm)/CO2(%).
SO2/CO2 [ppm/%] = (fuel S / fuel C) x 10,000 x MWRc/s
= (0.1% / 86.3%) x 10,000 x 12/32
= 4.0 ppm/%, where:
fuel C = fuel carbon level (weight percent) for distillate fuel
= (100% - 0.1%S - 0.03% other) x (MWH x H/C)/(MWC + MWH x H/C) A
= 86.3%
10,000 = conversion from percent to ppm
MWRc/s = molecular weight ratio of carbon to sulfur = 12/32
A Fuel properties are based on properties in the IMO NOX monitoring guidelines, MEPC. 103(49) which includes a
hydrogen to carbon (H/C) ratio for distillate fuel of 1.88 mol/mol. In addition, fuel is assumed to be composed of
carbon, hydrogen, sulfur, and other, where other is assumed to be 0.03 weight % for distillate fuel. (MWH =1.008,
MWC= 12.01)
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Chapter 4: Technological Feasibility
Scrubbers are effective at reducing 862 emissions and sulfate PM emissions from the
exhaust. However, as discussed above, the effectiveness of the scrubber at removing PM
emissions, other than sulfates, is dependent on the scrubber design. In addition to sulfate PM
reductions, switching from residual fuel to distillate fuel results in reductions in organic PM and
metallic ash particles in the exhaust. Clearly, scrubbers can be designed to provide similar
reductions in such non-sulfate PM emissions if need be to provide equivalent reductions
compared to fuel switching.
4.5 Technology for Producing/Distributing Lower Sulfur Fuel
4.5.1 Production of Lower Sulfur Marine Fuel
We project that the 1,000 ppm fuel sulfur limit, beginning in 2015, will likely result in
the increased use of distillate fuel for operation in EGAs. As such, additional distillate fuel will
likely be necessary to replace the residual fuel that would have been used without an EGA.
Some engines already operate on distillate fuel; however, this distillate fuel may need to be
further refined to meet the 1,000 ppm S limit.
4.5.1.1 Processing of Residual Stocks
IFO bunker grades are primarily comprised of residual stocks, such as Vacuum
Residuals, Atmospheric Residuals, Visbreaker Residuals, and Fluidized Catalytic Cracking
(FCC) clarified oil. These fuels also contain distillates that are added as cutter stocks, such as
Light Cycle Oil (LCO), Vacuum Gas Oils (VGO), and kerosenes. As such, only the residual fuel
blendstocks in IFO bunkers would need to be replaced or converted into distillate volumes to
provide for additional lower sulfur distillate marine fuel. For converting residuals to distillates,
refiners use two process technologies: Coking Units (Cokers) and Residual Hydrocrackers.
Coking units are used to convert the poorer quality residual feedstocks in IFO bunkers,
such as vacuum residuals. The coking units crack these resids into distillates, using heat and
residence time to make the conversion. The process produces petroleum coke and off gas as
byproducts. Residual hydrocrackers are used to convert low and medium sulfur residual streams
into distillates. Residual hydrocracking uses fluidized catalyst, heat and hydrogen to
catalytically convert residual feedstocks into distillates and other light fuel products. The
hydrocracking process upgrades low value residual stocks into high value distillate transportation
fuels consuming large amounts of hydrogen.
For processing of residual blendstocks, vacuum tower distillation capacity is added to
extract gas oils blendstocks that exist in residuals fuels used in current IFO bunker grades. The
extracted gas oils are further processed in either distillate hydrotreaters or gas oil hydrocrackers
to produce a distillate fuel that would meet a 1,000 ppm fuel sulfur limit. The use of additional
vacuum towers capacity minimizes the volume of residual stocks which lowers processing costs,
as less volume of fuel is processed in high cost residual coking and residual hydrocracker
processes.
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Regulatory Impact Analysis
4.5.1.2 Distillate Stocks Processing
Conventional distillate hydrotreating technology is used to lower the sulfur levels of high
sulfur distillate stocks. This technology removes sulfur compounds from distillate stocks using
catalyst, heat and hydrogen. Since the EGA sulfur standard is 1,000 ppm, conventional distillate
hydrotreating would likely be the technology chosen by refiners to make this distillate, rather
than the ultra low sulfur technology that is used to remove sulfur to levels below 15 ppm.
Conventional distillate hydrotreating refers to the design and conditions in the process, such as
catalyst type, catalyst volume, reactor pressure, feed and reactor flow scheme used to lower
sulfur levels to 500 ppm or higher.
Although the cutter stocks in IFO bunkers are distillate fuels, they would need to be
desulfurized because the 1,000 ppm sulfur limit for the EGA is lower than the nominal sulfur
levels for these blendstocks under the "business as usual" projections. The sulfur levels of
distillate used directly as bunker fuel (MDO and MGO), are greater than 1,000 ppm, and thus
would also need to be treated. Therefore, in addition to converting residuals to distillate fuels,
existing distillates used as bunker fuel in MDO, MGO and IFO would also need to be
hydrotreated. More distillate hydrotreating capacity would be required to lower the sulfur
content of incremental distillate produced from cokers and residual hydrocrackers that do not
meet low sulfur marine fuel standards.
For distillate stocks that are highly aromatic and high in sulfur, the use of technology for
hydrocracking low sulfur gas oil is used to convert these blendstocks into No 2. grade diesel
streams. Gas oil hydrocracking is a high volume gain process which produces diesel blendstocks
that typically meet EGA sulfur standards, eliminating the need for further processing in
hydrotreaters.
4.5.1.3 Supportive Processes
The increase in hydrotreating and hydrocracking requires new hydrogen and sulfur plant
capacity. Extra hydrogen is required to react with and remove sulfur compounds in refinery
hydrotreating processes. It is also needed to improve the hydrogen to carbon ratio of products
made from converting IFO blend components to distillates, via processing in cokers and
hydrocrackers.
4.5.2 Fuel Distribution Considerations
The existing nonroad, locomotive, and marine (NRLM) diesel fuel program requires that
all marine diesel fuel meet a 15 ppm sulfur standard by June 1, 2014 except fuel produced by
transmix processors which is allowed to meet a 500 ppm sulfur standard indefinitely, and fuel
with a T90 distillation point greater than 700 °F when used in Category 2 or 3 marine diesel
engines to which no EPA sulfur standard currently applies. The provisions in today's rule
would generally adopt a 1,000 ppm sulfur standard for fuel sold for use in an emission control
area (EGA) as defined by the International Maritime Organization under MARPOL Annex VI.
Alternatively, vessels could use higher sulfur fuel if in conjunction with an approach, such as
using a SOx scrubber, that achieves equivalent emission reductions. The U.S. Government has
proposed an amendment to MARPOL Annex VI to establish an EGA that would include the
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majority of U.S. coastal waters. Assuming the adoption of an amendment to MARPOL Annex
VI establishing a U.S. EGA, the 1,000 ppm marine sulfur standard would become effective
January 1,2015.
Due to the nature of the refinery options to reduce the sulfur content of fuel used in
Category 3 engines, we believe that the fuel manufactured to meet a 1,000 ppm sulfur
specification would likely have a T90 below 700 °F, and thus would be subject to the
requirements under the existing NRLM diesel program. Therefore, changes are needed to
existing NRLM diesel program to facilitate the adoption of a 1,000 ppm sulfur standard for
Category 3 marine under MARPOL Annex VI. Without such changes, the implementation of a
1,000 ppm Category 3 diesel sulfur standard would actually result in the requirement for the use
of 15 ppm diesel fuel in Category 3 marine engines.
The current provisions that allow transmix processors to continue to produce 500 ppm
locomotive and marine (LM) diesel fuel after June 1, 2014 were put in place to allow an outlet
for >15 ppm sulfur diesel fuel produced at transmix processors other than heating oil. These
special provisions were deemed to be necessary due to challenges associated with desulfurizing
diesel fuel produced at transmix processing facilities to a 15 ppm sulfur standard and the
geographically limited and seasonal nature of the heating oil market. Transmix processing
facilities consist of a simple distillation column with no other facilities for modifying the
resulting gasoline and diesel fractions such as a hydrotreater to remove sulfur.8 The small
throughput of transmix processing facilities is not sufficient to justify the installation of current
sulfur removal units (such as a hydrotreater).
In the process of shipping products by pipeline, mixing takes place between batches of
gasoline and distillate products that abut each other in the pipeline. This material (referred to as
transmix) must be re-processed to make it suitable for use. The vast majority of transmix
volume originates from pipeline shipments, although some is also generated during other fuel
distribution activities such as when the same fuel handling and storage equipment is alternatively
used for gasoline and distillate fuels. Transmix volumes typically gather towards the end of
pipeline systems which are commonly distant from refineries. Transmix processors are typically
located at these downstream pipeline locations to provide a means of coping with transmix
volumes that would otherwise present logistical difficulties to return to refineries for
reprocessing. Although transmix that is generated near refineries is sometimes returned to the
refinery for reprocessing, introducing large volumes of transmix into the distillation column at a
refinery can cause problems in the management of the output from this unit.0 Hence, refiners
would face difficulties in absorbing all of the transmix generated in the distribution system even
absent the logistical hurdles.
B High octane gasoline blendstocks are sometimes blended into the gasoline fraction produced at a transmix
processor to restore it to a marketable octane level. This is sometimes necessary because the heavier ends that
normally exist in gasoline (which are high in octane) are typically cut into the distillate fraction during transmix
distillation.
c Distillation columns at refineries are tuned to handle crude oil that has a much broader boiling range than
transmix.
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Regulatory Impact Analysis
The use of 500 ppm LM diesel fuel was limited to outside of the Northeast Mid-Atlantic
(NE/MA) and Alaska area after 2014 because it was concluded that heating oil provided a
sufficient outlet for >15 ppm diesel fuel from transmix processors within the NE/MA area and
Alaska. To support the continued use 500 ppm LM diesel fuel outside the NE/MA area and AK,
additional requirements were put in place to prevent distillate initially produced as heating oil to
be inappropriately shifted into the 500 ppm LM diesel pool during distribution. Specifically,
heating oil and 500 ppm LM diesel are required to be designated and tracked (D&T) throughout
the distribution system up to the point where the fuel leaves the terminal. Handlers of these fuels
in the distribution chain are further required to file a report with EPA on an annual basis to
demonstrate that heating oil was not inappropriately shifted into the 500 ppm LM diesel pool.
These requirements continue indefinitely after 2014 for all parties in the distribution chain that
handle heating oil and/or 500 ppm LM diesel fuel. We estimated that a many as 1,000 parties in
the distribution system may be affected by these recordkeeping and reporting requirements at an
annual cost of approximately $2.6 million.79
Before heating oil leaves the terminal, the solvent yellow 124 (SY-124) marker is
required to be added in order to continue to prevent its introduction in the 500 ppm LM diesel
pool given that the D&T and reporting requirements were not practical to implement
downstream of the terminal level. Given that most heating oil use takes place in the NE/MA area
and AK, the exclusion of 500 ppm LM diesel fuel from the NE/MA and AK after June 1, 2014
and the accompanying exemption from heating oil marker requirement in these areas
substantially limited the amount of heating oil that would need to be marked. This substantially
limited the costs associated with installing equipment to store/inject the marker at the terminal
and the cost of the marker itself. We estimated that 1.4 billion gallons of heating oil would need
to be marked each year at an annual cost of $425 thousand.80
The accommodation of 1,000 ppm Category 3 diesel fuel within the framework of the
NRLM program affords an opportunity to potentially simplify the requirements under the NRLM
program. We believe that the creation of a 1,000 ppm Category 3 marine diesel grade in
combination with the continued demand for heating oil may provide a sufficient outlet for >15
ppm diesel fuel produced by transmix processors. Today's action eliminates the allowance for
the continued production of 500 ppm LM diesel fuel by transmix processors. This would allow
the tracking, reporting, and marker requirements for heating oil to be eliminated after June 1,
2014, which would result in a significant reduction in the cost of compliance for a number of
parties in the fuel distribution system. Since there would be no limitation on the amount of 1,000
ppm Category 3 diesel that could be produced, and given the absence of a limited 500 ppm LM
diesel pool, the sulfur content alone would be sufficient to differentiate 1,000 Category 3 diesel
fuel from other distillate fuels (in order to facilitate compliance oversight by EPA).D
Removing the potential outlet to the locomotive and Category 2 marine markets, while
opening a new outlet to the Category 3 marine market would affect the distribution pathways for
>15 ppm diesel fuel produced at transmix processors. We believe that transmix generated near
the coasts would have ready access to marine applications, and transmix generated in the mid-
D Internal Revenue Service (IRS) red dye requirements to differentiate non-taxed diesel fuel will continue to apply.
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Chapter 4: Technological Feasibility
continent could be shipped via rail, pipeline, or other means to Category 3 marine and heating oil
markets on the coasts.
We contacted several transmix processors and organizations that represent transmix
processors prior to the publication of the proposed rule to solicit their input regarding the
potential impacts on their operations from the introduction of a 1,000 ppm Category 3 marine
fuel grade and the elimination of the 500 ppm transmix processor LM diesel provisions.
Transmix processors located the farthest away from potential 1,000 ppm Category 3 marine fuel
marine markets related that they planned to evaluate the potential impacts on their operations
from these changes and may be providing comments on the proposed rule based on their
evaluation. No comments on the proposed changes were received from transmix processors.
There may be some increase in the cost of distributing some portion of the >15 ppm
diesel fuel produced by transmix processors while in other cases there may be decrease in
distribution costs. It is useful to compare the potential savings from the elimination of the D&T
requirements needed to support the 500 ppm LM transmix provisions to the potential increase in
distribution cost for such fuel if the outlet to the LM diesel fuel market was eliminated. To
facilitate this comparison, we assumed that 430 million gallons a year of transmix generated 500
ppm diesel fuel would be used in LM applications. This is 40% of the total annual transmix
volume. The remaining transmix is assumed to be consumed in the heating oil market or
returned to a refinery for reprocessing. Dividing the annual potential savings (~$3 million) by
the annual volume of transmix-generated 500 ppm distillate estimated to be used in LM results in
approximately 1 cent per gallon. Thus, if the distribution costs for 500 ppm diesel fuel produced
at transmix processors increased by 1 cent per gallon as a result of the amendments, the overall
net cost would be neutral. We believe that the overall impact to the distribution costs for 500
ppm transmix-generated diesel fuel would be less than 1 cent per gallon.
We anticipate that the introduction of a 1,000 ppm Category 3 marine fuel grade would
not cause the need for a significant number of additional storage tanks or transport vessels (rail
cars, tank trucks, and barges). Downstream of the producer, we expect the same distribution
equipment would be used. In certain instances where the distribution pathway may need to be
altered to accommodate a switch from the locomotive and Category 2 marine market to the
Category 3 marine market, it may be necessary to introduce an additional trans-loading step from
rail car to tank truck. However, we believe that such trans-loading could be accomplished at
existing trans-loading facilities at rail yards. The improved flow-ability of 1,000 ppm diesel fuel
over current Category 3 marine fuels (which sometimes requires heating to maintain flow-
ability), may simplify the handling of Category 3 marine fuels. The likely fungibility of 1,000
ppm Category 3 marine fuels with heating oil may also facilitate its distribution in areas where
heating oil is shipped in bulk (primarily the Northeast). Based on the above discussion, we
expect that the introduction of a 1,000 ppm Category 3 marine fuel grade and the elimination of
500 ppm transmix processor LM diesel fuel post 2014 with the associated streamlining of the
diesel program compliance requirements would result in a reduced costs to the industry as a
whole.
We do not anticipate that the lack of access to 500 ppm LM diesel fuel produced at
transmix processors would pose a difficulty to locomotive and Category 2 marine end users
given the widespread availability of 15 ppm diesel fuel. Instead of being the consumers of fuel
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Regulatory Impact Analysis
produced at transmix processors, locomotive and Category 2 marine operators would likely be an
important means of bringing such fuel to the Category 3 market.
4.6 Impact on Safety, Noise, and Energy
We do not anticipate any impact on vessel safety or noise due to the engine-based
emission control technologies which we anticipate manufacturers will use to meet the Tier 2 and
Tier 3 standards. Some of these technologies are incremental improvements to existing engine
components, and many of these improvements have already been applied to similar engines.
Based on numerous data from automotive, truck, and marine industries, we do not anticipate that
SCR technology will impact vessel safety or noise.
No new impacts are anticipated on the energy supply due to this rule. We anticipate that
the Tier II NOx standards required by Annex VI of the International Convention for the
Prevention of Pollution from ships will result engine modifications which may result in
approximately a 2 percent fuel penalty. The 2020 increase in fuel consumption (in U.S.
inventory domain) due to 2 percent Tier II penalty is roughly 1,700 barrels per day (BPD) (250
BPD from U.S. vessels). The use of SCR to meet Tier III NOX standards may provide the
opportunity to offset this fuel penalty when vessels are operating in an EGA by recalibrating the
engine when the SCR is operating and relying on the SCR unit to achieve the full NOx reduction.
Because we are not finalizing requirements that would necessitate further engine or vessel
modifications beyond what is anticipated to meet the Annex VI requirements, this rule would not
significantly affect the energy use, production, or distribution beyond what is required by Annex
VI.
Similarly, we are not establishing new fuel sulfur standards beyond what is necessary
under the Annex VI requirements for marine fuels in this action; therefore no increase in energy
use during fuel refining is anticipated. However, under the coordinated strategy, increased
demand for distillate fuel in the EGA would increase the volume of crude oil needed in global
refinery processes. This is discussed in Chapter 5. As shown in Table 5-36, the total refinery
crude throughput in 2020 would increase by nearly 0.1 million BPD, leading to a corresponding
increase in crude oil supply.
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Chapter 4: Technological Feasibility
References
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2 Heywood, John B., "Internal Combustion Engine Fundamentals", McGraw-Hill, 1988.
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5 Durnholz, M., G. Eifler, and H. Endres, "Exhaust-Gas Recirculation - A Measure to Reduce
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7 Ghaffarpour, M. and R. Baranescu, "NOX Reduction Using Injection Rate Shaping and
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in Diesel Engines", SAE 960833, 1996.
11 Mather, D.K. and R.D. Reitz, "Modeling the Influence of Fuel Injection Parameters on Diesel
Engine Emissions," SAE 980789, 1998.
12 "Experience with Sulzer Common-Rail Engines," Wartsila,
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_papers
13 Geist, M. A. R. Holtbecker, and S. Chung, "Marine Diesel NOX Reduction - A New Sulzer
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14 Goldsworthy, L., "Design of Ship Engines for Reduced Emissions of Oxides of Nitrogen,"
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15 MAN B&W, "Exhaust Gas Emission Control Today and Tomorrow - Applications on MAN
B&W Two-Stroke Marine Diesel Engines," September 19, 2008,
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16 Walker, A.P. et al., "The Development and In-Field Demonstration of Highly Durable SCR
Catalyst Systems," SAE 2004-01-1289.
17 Conway, R. et al., "Combined SCR and DPF Technology for Heavy Duty Diesel Retrofit,"
SAE 2005-01-1862, 2005.
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Regulatory Impact Analysis
18 "The Development and On-Road Performance and Durability of the Four-Way Emission
Control SCRT® System," presented by Andy Walker, 9th DEER Conference, August, 2003.
19 "DEC SCR Converter System," Muenters, May 1, 2006, Docket ID EPA-HQ-OAR-2007-
0121-0013.
20 Hagstrom, U., "Humid Air Motor (HAM) and Selective Catalytic Reduction (SCR)," Viking
Line, presented at Air Pollution from Ships, May 24-26, 2005, Docket ID EPA-HQ-OAR-2007-
0121-0027.
21 "Reference List - SI NOX ® Systems," Argillon, December 2006, Docket ID EPA-HQ-OAR-
2007-0121-0035.
22 "Reference List January 2005 Marine Applications," Hug Engineering, January 2005, Docket
ID EPA-HQ-OAR-2007-0121-0036.
23 Heim, K., "Future Emission Legislation and Reduction Possibilities," Wartsila, presented at
CIMAC Circle 2006, September 28, 2006, Docket ID EPA-HQ-OAR-2007-0121-0017.
24 Argillon, "Exhaust Gas Aftertreatment Systems; SCR - The Most Effective Technology for
NOX Reduction," presented at Motor Ship Marine Propulsion Conference, May 7-8, 2003,
Docket ID EPA-HQ-OAR-2007-0121-0010.
25 Holmstrom, Per, "Selective Catalytic Reduction," presentation by Munters at Clean Ships:
Advanced Technology for Clean Air, February 7-9, 2007, Docket ID EPA-HQ-OAR-2007-0121-
0013.
26 Wartsila, "2005 Annual Report,"
http://www.euroland.com/arinhtml/sf_wrt/2005/B Y_ENG_2005.pdf.
27 M.J. Bradley & Associates, "Alice Austen Vessel SCR Demonstration Project - Final Report,"
August 2006, http://www.mjbradley.com/documents/Austen_Alice_Report_Final_3 lAug06.pdf.
28 Rasmussen, K., Ellegasrd, L., Hanafusa, M., Shimada, K., "Large Scale SCR Application on
Diesel Power Plant," CIMAC paper number 179, presented at International Council on
Combustion Engines Congress, 2004, Docket ID EPA-HQ-OAR-2007-0121-0007.
29 "Munters SCR Converter™ System," downloaded from www.munters.com, November 21,
2006, Docket ID EPA-HQ-OAR-2007-0121-0023.
30 Argillon, "Exhaust Gas Aftertreatment Systems; SCR - The Most Effective Technology for
NOx Reduction," presented at Motor Ship Marine Propulsion Conference, May 7-8, 2003,
Docket ID EPA-HQ-OAR-2007-0121-0010.
31 From emission test results provided to EPA from sea trials on a Tier I, 55 MW, low-speed
engine, Docket ID EPA-HQ-OAR-2007-0121-XXXX.
32
Johnson Matthey, "SCRT Technology for Retrofit of Heavy Duty Diesel Applications,"
,th
33
34
presented by Ray Conway, 11 DEER Conference, August, 2005.
Munters, "Selective Catalytic Reduction," presented at Clean Ships Conference, San Diego,
CA, February 7, 2007.
MANB&W, "Emission Control Two-Stroke Low-Speed Diesel Engines," December 1996,
Docket ID EPA-HQ-OAR-2007-0121-0020.
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Chapter 4: Technological Feasibility
35 "NOX Emissions from M/V Hamlet," Data provided to W. Charmley, U.S. EPA. by P.
Holmstrom, DEC Marine, February 5, 2007, Docket ID EPA-HQ-OAR-2007-0121-0015.
36
U.S. Department of the Interior, "Mineral Commodity Summaries 2006," page 118, U.S.
Geological Survey, January 13, 2006, Docket ID EPA-HQ-OAR-2007-0121-0022.
37
Hountalas, D.T., "Use of Water Emulsion and Intake Water Injection as NOx Reduction
Techniques for Heavy Duty Diesel Engines," SAE 2006-01-1414, 2006.
38
MAN B&W, "Emission Control: Two-Stroke Low-Speed Diesel Engines," 1999,
http://www.manbw.com/files/news/filesofl417/19993701.pdf.
39
MAN B&W, "Emission Control: MAN B&W Two-Stroke Diesel Engines," 2004,
http://www.manbw.com/files/news/filesof4458/p9000.pdf
40 Wartsila, "Marine Technologies for Reduced Emissions," presented by Heinrich Schmid and
German Weisser, 2nd Annual Conference on Green Ship Technology, Amsterdam, Netherlands,
April 13-14th, 2005.
41 Weisser, G., "Emission Reduction Solutions for Marine Vessels - Wartsila Perspective"
presentation by Wartsila at the Clean Ships: Advanced Technology for Clean Air Conference,
February 8, 2007, Docket ID EPA-HQ-OAR-2007-0121-0032.
42 International Maritime Organization, "Input from the four subgroups and individual experts to
the final report of the Informal Cross Government/Industry Scientific Group of Experts,"
Subcommittee on Bulk Liquids and Gases, 12th session, Agenda item 6, BLG12/INF.10,
December 28, 2007.
43 Kasper, A., Aufdenblatten, S., Forss, A., Mohr, M. and Burtscher, H., "Particulate Emissions
from a Low-Speed Marine Diesel Engine," Aerosol Science and Technology, 41:1, 24 - 32, 2007
44
Nakajima et al, "Measurement and Analysis of Particulate Matter (PM) from Marine Diesel
Engines," Proceedings of the 6th International Symposium on Marine Engineering, October,
2000.
45 Email from Fritz Fleischer, MAN to Bryan Wood-Thomas, EPA, "Particulates," October 02,
2007.
46 Agrawal, H., et al., "In-Use Gaseous and Particulate Matter Emissions from a Modern Ocean
Going Container Vessel," Atmospheric Environment, doi:10.1016/j.atmosenv.2008.02.053, 2008.
47
Maeda et al, "Measurement of PM Emission from Marine Diesel Engines," International
Council on Combustion Engines, CEVIAC Paper 107, 2004.
48 Janhall, S., "Particle Emissions from Ships," Goteborg University, The Alliance for Global
Sustainability, ISBN: 978-91-976534-3-5, 2007.
49 Sinha et al., "Emissions of Trace Gases and Particles from Two Ships in the Southern Atlantic
Ocean," Atmospheric Environment 37 (2003) 2139-2148, 2003.
50 International Standard Organization (ISO) "8217 Petroleum products — Fuels (class F) —
Specifications of Marine Fuels," Edition: 3 | Stage: 90.92 | TC 28/SC 4, ICS: 75.160.20,
http://www.iso.org
51 MAN B&W Diesel, "Operation on Low-Sulphur Fuels; Two-Stroke Engines," 2004.
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Regulatory Impact Analysis
52 Wartsila, "Low Sulphur Guidelines," January 9, 2006.
53 American Petroleum Institute, "Technical Considerations of Fuel Switching Practices," API
Technical Issues Workgroup, June 3, 2009.
54 American Bureau of Shipping, "ABS Notes: Use of Low-Sulphur Marine Fuel for Main and
Auxiliary Diesel Engines," Fuel Oil Piping, EWZ-001-02-P04-W007, Attachment G - Revision
1.
55 United States Coast Guard, "Avoiding Propulsion Loss from Fuel Switching: American
Petroleum Institute, Technical Considerations," Marine Safety Alert 03-09, June 16, 2009.
56 Wartsila, "CARB Workshop Switching Fuel," presented by Leo Schnellmann, California
Maritime Technical Working Group, Sacramento, CA, July 24, 2007,
http://www.arb.ca.gov/ports/marinevess/presentations/072407/072407warpres.pdf
57 Herbert Engineering Corp., "California Maritime Technical Working Group Focus on Fuel
Switching Fuel Oil Systems," prepared by Herbert Engineering Corp., California Maritime
Technical Working Group, Sacramento, CA, July 24, 2007,
http://www.arb.ca.gov/ports/marinevess/presentations/072407/072407herpres.pdf
58 International Standard Organization (ISO) "8217 Petroleum products - Fuels (class F) —
Specifications of Marine Fuels," Edition: 3 | Stage: 90.92 | TC 28/SC 4, ICS: 75.160.20,
http://www.iso.org
59 ASTM International, "ASTM D975 - 09 Standard Specification for Diesel Fuel Oils,"
Developed by Subcommittee: D02.E0.02 (Book of Standards Volume: 05.01,
http://www.astm.org
60 ExxonMobil Marine Lubricants, "Low Sulfur Fuel: Impacts on the Marine Industry,"
http://www.exxonmobil.com/lubes/exxonmobil/marine/files/LSF_Bulletin.pdf
61 Total Petrochemicals USA, Inc., Lubmarine, Talusia Universal,
http://www.lubmarine.com/lub/content/NTOOOF9DB2.pdf
62 Lloydminster Oilfield Technical Society (OTS), "OTS Heavy Oil Science Center, What are
Asphaltenes?," Lloydminster, Saskatchewan/Alberta, Canada,
http://www.lloydminsterheavyoil.com/asphaltenes.htm
63 California Air Resources Board, "Commercial Marine Vessels," Sacramento, CA,
http://www.arb.ca.gov/ports/marinevess/marinevess.htm
64 California Air Resources Board, "Evaluation of Ship Auxiliary Boilers for Inclusion in the
Proposed Regulation for Ship Main Engines," September 24, 2007.
65 Aalborg Industries, "Changing from HFO to MDO or MGO," Aalborg Solutions, No. 12,
January 2009.
66 Lloyd's Register, "Maintaining boiler safety and availability when using low-sulphur fuels,"
Classification News, No.24/2009, August 14, 2009
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Chapter 4: Technological Feasibility
67 American Bureau of Shipping, "ABS Notes: Use of Marine Gas Oil (MGO) as Fuel for
Boilers," Gas Fuel Burner System, EWZ-001-02-P04-W031, Attachment B - Revision 1.
68 "Holland America Line Krystation Sea Water Scrubber Technology Demonstration Project,"
July 23-25, 2008
69 Hufnagl, M., et al (2005 March). Effects of Sea Water Scrubbing - Final Report. BP Marine.
70 Heim, Klaus M. (2008 September 25). Engines and SOx Scrubber Technologies to Meet IMO
Fuel Quality Requirements on Sulphur and SOX Paper presented at the CIMAC Circle SMM
2008.
71 Henriksson, T. (2007 September 28). SO x Scrubbing of Marine Exhaust Gases. Retrieved
August 12, 2008 from http://www.shipgaz.eom/magazine/issues/2007/l8/1807_articlel.php.
72 Tri-Mer Corporation (2005, April 14). Cloud Chamber Scrubber Performance Results for
Diesel Exhaust.
73 Tri-Mer Corporation. Cloud Chamber Scrubbers Product Bulletin. Retrieved April 9, 2009
from http://www.tri-mer.com/pdf-files/Tri-Mer-CCS-Brochure-03-09.pdf
74 Dupont/Belco. Belco Technologies Corporation. Presentation on emission control
technologies from Dupont/Belco receieved August 21, 2008.
75 International Maritime Organization, "2009 Guidelines for Exhaust Gas Cleaning Systems,"
Resolution MEPC. 184(59), Adopted on 17 July 2009, MEPC 59/24/Add.l/Annex 9.
76 Cooper, J.R. et. al. "The e-SCRUB machine: An 800 kV, 500 kW average power pulsed
electron beam generator for flue-gas scrubbing, Sceince Applications International Corporation,
SPIE Vol. 2374/147.
77
78
EcoSpec, "CSNOx," presentation at MEPC 59, July 16, 2009.
International Maritime Organization (2005 July 22). Guidelines for On-Board Exhaust Gas-
SOx Cleaning Systems; Annex 12, Resolution MEPC. 130(53). MEPC 53/24/Add.l.
79 Supporting Statement for the Information Collection Request, Recordkeeping and Reporting
Requirements for Motor Vehicle and Non-Road Diesel Fuel, EPA ICR 1718.08, January 2008.
80 Section 7.4.4 "Fuel Marker Costs", Final Regulation Analysis, Control of Emissions from
Nonroad Engines, May 2004, EPA420-R-04-007, http://www.epa.gov/nonroad-
diesel/2004fr/420r04007.pdf
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CHAPTER 5: Engineering Cost Estimates
In this chapter, we present the projected cost impacts associated with the coordinated
emission control strategy for Category 3 vessels including the engine and fuel standards
described in this action and those that would apply in the U.S. ECA.A
We estimate the costs of the coordinated strategy to be approximately $1.85 billion in
2020, increasing to $3.11 billion in 2030B Of the 2020 costs, nearly 89 percent or $1.64 billion
are attributable to the fuel sulfur provisions which include the costs incurred by both U.S. and
foreign-flagged vessels. The total operational costs are estimated to be $1.82 billion in 2020,
which include fuel sulfur controls, a two percent fuel consumption penalty associated with Tier 2
and global Tier IINOX standards, and the use of urea on vessels equipped with selective catalytic
reduction (SCR) to meet Tier 3 and global Tier III NOx standards. The costs to apply engine
controls to U.S.-flagged vessels are expected to be $31.9 million in 2020, increasing to $47.4
million in 2030 as more ships are built to comply with Clean Air Act (CAA) Tier 3 NOx limits.
When attributed by pollutant, at a discount rate of 3 percent from 2010 through 2040, the
NOx controls are expected to cost about $510 per ton of NOx reduced, SOx controls are
expected to cost about $930 per ton of SOx reduced, and the PM controls are expected to cost
about $7,950 per ton of PM reduced ($500, $920, and $7,850 per ton of NOX, SOX, and PM
respectively, at a net present value of 7 percent over the same period.) These costs are
comparable to our other recently-adopted mobile source programs, and are one of the most cost
effective programs in terms of NOx and PM when compared to recent mobile and stationary
programs. The coordinated strategy also provides very cost effective SOx reductions comparable
to the Heavy-Duty Nonroad diesel rulemaking.
The estimated costs presented in this chapter are for the entire coordinated strategy,
including those requirements that are the subject of this action and those that are associated with
the proposed EGA designation. The costs of the coordinated strategy consist of the costs
associated with the MARPOL Annex VI global standards that are operational through APPS,
some of which we are also adding to our CAA emission control program for U.S. vessels (Tier 2
and Tier 3 NOx emission control hardware for U.S. vessels; operating costs for the Tier 2 NOx
requirements; controls for existing vessels; certain compliance requirements). Also included are
the costs associated with EGA standards in U.S. waters (Tier 3 operating costs; fuel sulfur
hardware and operating costs).
The regulatory changes for Category 1 and 2 engines are not included in this cost analysis
as they are intended to be compliance flexibilities and not result in increased compliance costs.
A We use the term "engineering costs" to differentiate from "social costs." Social costs are discussed in Chapter 7 of
this RIA. For simplicity, the terms "cost" and "costs" throughout the discussion in this Chapter 5 should be taken as
referring to "engineering costs."
B The costs totals reported in this FRM are slightly different than those reported in the EGA proposal. This is
because the EGA proposal did not include costs associated with the Annex VI existing engine program, Tier II, or
the costs associated with existing vessel modifications that may be required to accommodate the use of lower sulfur
fuel. Further, the cost totals presented in the EGA package included Canadian cost estimates.
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Chapter 5: Engineering Cost Estimates
Similarly, the technical amendments for other engines, would not have significant economic
impacts and are therefore not addressed here. Finally, to provide for a representative comparison
between costs and benefits of the program, the cost analysis presented here assumes that all
vessels currently using residual fuel will operate on distillate fuel in an EGA, including Great
Lakes steamships. As noted in earlier chapters, Great Lakes steamships have been excluded from
the final fuel sulfur standards. This change is not expected to have a significant impact on the
estimated costs or benefits of the rule as those vessels are not a large part of the national
inventory.
A more detailed description of the components of the coordinated strategy that are
included in this cost analysis is presented in Section 5.1 of this chapter. Section 5.2 describes the
methodology used to estimate the hardware and operating costs, including the development of a
representative future fleet and predicted sales volumes to which these hardware and operating
costs are applied. Sections 5.3 and 5.4 present the estimated hardware costs of the individual
engine technologies we expect manufacturers to use to comply with the emissions standards for
new and existing engines, along with a discussion of the associated fixed costs of these
technologies such as research and development, tooling, and certification. Section 5.5 describes
vessel hardware and fixed costs that may be incurred by some vessels to accommodate the use of
lower sulfur fuel. Section 5.6 presents our estimate of changes in vessel operating costs that
may result from the coordinated strategy, including estimated fuel production costs. Section 5.7
presents the total estimated cost of the coordinated strategy to U.S.- and foreign-flagged vessels,
and finally Section 5.8 presents the cost effectiveness of this program. All costs presented in this
chapter are in 2006 dollars. See Appendices 5A through 5C for additional information regarding
NOX monitoring, testing during sea trials, and gas turbines, respectively.
5.1 Components of Coordinated Strategy Included in this Analysis
This analysis estimates the costs associated with all components of the coordinated
strategy. These include the costs of the CAA Tier 2 and Tier 3 emission standards for U.S.-
flagged vessels, operational costs associated with the global Tier II and Tier III standards for
foreign-flagged vessels operating in the EGA, and the EGA fuel sulfur requirements. We also
include Clean Air Act compliance costs that will apply only to new U.S. vessels for verification
testing after engine installation (PLT). The fuel program changes are implementation provisions
and do not impose compliance costs but, instead, may reduce the costs for fuel distributors of
complying with EPA's distillate diesel standards.
While there is significant overlap between the coordinated strategy and our proposal for
EGA designation, the total costs associated with these two programs are not identical. The
differences between the two programs are set out in Table 5-1. The estimated costs for the
coordinated strategy include hardware costs for new U.S.-flagged vessels to comply with the
CAA Tier 2 and Tier 3 engine standards, and for existing U.S.-flagged vessels to comply with
the MARPOL Annex VI existing engine requirements. Costs are also included for hardware
changes associated with switching to 1,000 ppm sulfur fuel for certain new and existing U.S.-
flagged vessels. The cost analysis includes all of these hardware costs even though some of the
benefits from using these emission control systems will occur outside the United States.
Conversely, we do not include any new vessel Tier 3 or fuel hardware costs for foreign vessels
that operate in U.S. waters even though a significant share of the benefits of the coordinated
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Regulatory Impact Analysis
strategy will arise from foreign vessels that comply with the EGA engine and fuel sulfur limits
while operating within the U.S. EGA.
The estimated costs for the coordinated strategy also include operating costs for U.S. and
foreign vessels while operating in the inventory modeling domain, which includes the proposed
EGA. These increased operating costs include changes in fuel consumption rates, the differential
increase in fuel costs, and the use of urea for engines equipped with SCR. There are also Clean
Air Act compliance costs that will apply only to new U.S. vessels for verification testing after
engine installation (PLT). The fuel program changes are implementation provisions and do not
impose compliance costs but, instead, may reduce the costs for fuel distributors of complying
with EPA's distillate diesel standards.
Estimated costs for the proposed EGA designation, on the other hand, include hardware
costs for both U.S. and foreign vessels to meet the EGA Tier III NOX and fuel sulfur limits and
operating costs associated with using those systems within the EGA domain. Although we
included the entire hardware cost for all vessels, these vessels will likely operate in other existing
or yet-to-be-designated EGAs in Europe or Asia, and therefore it may have been more
appropriate to allocate only a portion of those hardware costs.
5-4
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Chapter 5: Engineering Cost Estimates
Table 5-1 Costs Associated with the Coordinated Strategy and U.S./Canadian Proposal to IMO for ECA
Designation
PROGRAM ELEMENT
Hardware - T2
(variable costs; fixed costs
applied in 2010)
Hardware - T3
(variable costs; fixed costs
recovered in the year in which
they occur: 2011-15)
Hardware - Fuel
Operating - T2
(inside full inventory
modeling domain)
Operating - T3
(inside relevant part of
affected waterays)
Operating - Fuel
(inside relevant part of
affected waterways)
Existing vessels - engine costs
(all US vessels 1990-99
retrofit during first 5 years of
program, 20 1 1 - 1 5 )
Existing vessels - vessel fuel
switching costs
(all US vessels 1999-90
retrofit during first 5 years of
program, 2011-15)
US vessels
Foreign Vessels
US vessels
(variable costs; fixed costs
recovered in the year in which
they occur: 2011-15)
Foreign vessels: 30% of vessels
making 75% of entrances to US
ports
Foreign vessels: 70% of vessels
making 25% of entrances to US
ports
US vessels
(new vessel costs)
Foreign vessels
(new vessel costs)
US vessels
Foreign vessels
US vessels
Foreign vessels
US vessels
Foreign vessels
US vessels
Foreign vessels
US vessels
Foreign vessels
U.S. COORDINATED
STRATEGY
$3,310,000
N/A - global std
$28,700,000
$296,700,000
$692,200,000
$804,000
$23,600,000
$5,630,000
$32,900,000
$15,800,000
$127,000,000
$210,000,000
$1,430,000,000
$0
N/A - global std
$0
$0
CANADIAN ECA
NA- not part of ECA
NA- not part of ECA
$100,000,000
$10,000,000
NA- not part of ECA
NA- not part of ECA
$30,000,000
$260,000,000
NA- not part of ECA
NA- not part of ECA
Canada did not provide
Canada did not provide
The CAA Tier 2 and Tier 3 NOx standards will not result in costs to U.S. vessels above
or beyond those costs that will already be experienced through compliance with the Tier II and
Tier III NOx standards contained in Annex VI. In addition, we are not requiring NOx standards
for foreign-flagged vessels, nor are we requiring requirements for the use of lower sulfur fuel.
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Regulatory Impact Analysis
However, the U.S. Government was a key participant in the development of the new Annex VI
NOx emission standards and fuel sulfur limits. As such, we are interested in quantifying the
costs and benefits associated with the coordinated strategy.
5.2 Methodology for Estimating Engine and Equipment Engineering Costs
To estimate the cost of the coordinated strategy for ensuring that all ships that affect U.S.
air quality will be required to meet stringent NOx and fuel sulfur requirements, we estimated the
hardware and operational costs to both U.S.- and affected foreign-flagged ships separately. The
hardware costs are only applied to U.S.-flagged vessels, and include those associated with the
Annex VI existing engine program, Tier 2, Tier 3, and the use of lower sulfur fuel. For the sake
of completeness, however, estimated hardware costs for foreign-flagged vessels associated with
global Annex VI Tier III standards and additional hardware that may be required to
accommodate the use of lower sulfur fuel are presented here as a separate analysis. Tier 2
hardware costs are expected to consist of changes to the engine block and the migration from
mechanical fuel injection to common rail fuel injection systems. Tier 3 hardware costs include
engine modifications, the migration from mechanical fuel injection to common rail fuel injection
systems, and the installation of SCR. Hardware costs associated with the use of lower sulfur fuel
are a result of applying additional tanks and equipment to enable a vessel to switch from residual
fuel to lower sulfur fuel. These equipment costs were applied to those new vessels that may
require such additional hardware, and also include the estimated cost of retrofitting the portion of
the fleet that may require additional hardware to accommodate the use of lower sulfur fuel in
2015, when the fuel sulfur standards take effect. The total hardware costs also include a per
engine cost of $10,000 associated with the requirement to test each production engine
(§1042.302).
The operational costs were applied to both U.S.- and foreign-flagged vessels and include
additional operational costs associated with the applicable NOx limits, and the use of lower
sulfur fuel. The operational costs for NOx controls consist of the additional fuel required due to
an estimated two percent fuel penalty associated with the use of technology to meet Tier 2
standards for U.S.-flagged vessels and global Annex VI Tier II standards for foreign-flagged
vessels, and the use of urea for ships equipped with an SCR unit. The operational costs
associated with the use of lower sulfur fuel include both the differential cost of using lower
sulfur fuel that meets EGA standards instead of using marine distillate fuel, and the differential
cost of using lower sulfur fuel that meets EGA standards instead of using residual fuel.
To assess these potential cost impacts we must understand: the makeup of the fleet of
ships expected to visit the U.S. when these requirements go into effect, the emission reduction
technologies expected to be used, and the cost of these technologies. The total engine and vessel
costs associated with the coordinated strategy are based on a cost per unit value applied to the
number of affected vessels. Operational costs are based on fuel consumption values determined
in the inventory analysis (Chapter 3). This section discusses an overview of the methodology
used to develop the hardware and operational costs. This section also presents the methodology
used to develop a fleet of future vessels necessary to determine how to apply these hardware and
engineering costs.
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Chapter 5: Engineering Cost Estimates
5.2.1 Engineering Cost Methodology
To determine the cost of applying emission reduction technology on a per vessel basis,
ICF International (ICF) was contracted by the U.S. EPA to conduct a cost study of the various
compliance strategies expected to be used to meet the new requirements. The resulting cost
estimates were used to determine a $/kW equation which could be scaled according to engine
speed and power to arrive at a per vessel cost. The per vessel hardware costs were then applied
to the number of applicable new vessels estimated to be built in each year after the standards take
effect.
5.2.1.1 Overview
There are a number of technologies available or expected to be available to meet CAA
Tier 2 and Tier 3, global Tier II and Tier III, and Annex VI Existing Engine NOx standards, and
to accommodate the use of lower sulfur fuel. We expect that each manufacturer will evaluate all
possible technology avenues to determine how to best balance costs while ensuring compliance,
however, this analysis makes certain assumptions regarding how manufacturers will comply with
the new emission and fuel standards. First, Tier 2 assumes that compliance is met through a
combination of fuel injection system changes for some engines and the use of engine
modifications for all engines. These engine modifications do not require additional hardware
and therefore do not have any related variable costs associated with them. The fuel injection
change (the migration from mechanical fuel injection to common rail fuel injection systems) is
expected to apply to a certain fraction of engines for Tier 2, and an additional fraction for Tier 3.
Tier 3 NOx standards are projected to be met through the use of SCR systems. The fuel
standards are assumed to be met through the use of lower sulfur fuel. An analysis was performed
on the current global operating fleet to estimate the percentage of the fleet that may require
additional hardware to accommodate the use of lower sulfur fuel, as some ships either already
have or are expected to be built with the equipment necessary to accommodate the use of lower
sulfur fuel.
Through our background work for this rulemaking and for the EGA application, we
sought input from the regulated community regarding the expected future costs of applying the
emission control technologies associated with the coordinated strategy. EPA contracted with
ICF to research the fixed and variable costs associated with the technologies expected to be used
to meet engine and fuel sulfur requirements, as applied to different engine types and sizes. 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 the
coordinated strategy. 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 $/kW
value that could be applied to any slow or medium speed engine. Using the average propulsion
power by ship type presented in the inventory analysis (Chapter 3), the per vessel hardware costs
were then applied to the estimated number of applicable vessels built after the standards take
effect, Table 5-2 lists these engine configurations. After ICF developed their initial cost
estimates, they provided surveys to several engine and emission control technology
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Regulatory Impact Analysis
manufacturers to determine the reasonableness of their approach and cost estimates. Input
received from those surveyed was incorporated into the final cost estimates used in this analysis.
Table 5-2 Engine Configurations Used in the 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
5.2.1.2 Hardware Costs
The hardware cost estimates include variable costs (components, assembly, and
associated markup) and fixed costs (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.1 Variable costs also include a 29 percent markup
to account for both manufacturer and dealer overhead and carrying costs. Fixed costs are
estimated to be incurred over a five-year period preceding the introduction of the standard.
Hardware costs associated with EVIO's existing engine standards were applied to the
portion of the existing U.S.-flagged fleet built between 1990 and 1999 expected to be subject to
these standards in 2011 when the standards go into effect. These costs were taken over a five-
year period beginning in 2011 where 20 percent of the subject fleet was estimated to undergo a
rebuild event in each respective year. The existing engine program fixed costs were phased in
over a five year period beginning in 2010 and applied on a per vessel basis using the estimated
applicable fleet in each respective sales year.
Hardware costs associated with the CAA Tier 2 program were applied to all new U.S.-
flagged vessels beginning in the year 2011 when the standards take effect. The fixed costs
associated with Tier 2 standards are expected to be incurred over a five year period, however, as
the Tier 2 standards take effect in 2011, it is assumed that manufacturers are nearing the end of
their research and development efforts. To capture all of these costs, the fixed costs that would
have been incurred during that five year phase-in period were all taken in the year 2010 and
applied on a per vessel basis using the applicable future fleet of new U.S.-flagged vessels in
2010.
Hardware costs associated with Tier 3 are estimated for U.S. vessels and are applied as of
2016. Because of the global scope of the Tier III standards, and the fact that other EGAs exist
today and more may exist in the future, we do not include hardware costs for Tier III emission
controls on foreign-flagged vessels. However, for completeness, Section 5.2 presents these
hardware cost estimates separately. The fixed costs associated with Tier 3 were phased in over a
five year period beginning in 2011. Hardware costs associated with the use of lower sulfur fuel
are estimated separately for both new and existing vessels that may require additional hardware
to accommodate the use of lower sulfur fuel. The fuel sulfur control related hardware costs for
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Chapter 5: Engineering Cost Estimates
new vessels begin to apply in 2015, while all retrofit costs are expected to be incurred by 2015.
The fixed costs for both new and existing vessels that may require additional hardware to
accommodate the use of lower sulfur fuel are applied on a per vessel basis and are phased in over
a five year period beginning as of 2010.
5.2.1.3 Operational Costs
The operational costs estimated here are comprised of three parts, (1) the estimated 2
percent increase in fuel consumption (see Chapter 4) expected to occur with the use of Tier 2 and
global Tier II technologies on U.S.- and foreign-flagged vessels, (2) the differential cost of using
lower sulfur, and (3) the use of urea with SCR as a Tier 3 and global Tier III NOx emission
reduction technology on both U.S.- and foreign-flagged vessels. The fuel consumption values
were determined in the inventory analysis (see Chapter 3). The two percent fuel penalty estimate
is based on the use of modifications to the fuel delivery system to achieve Tier IINOX
reductions, and does not reflect the possibility that there may be other technologies available to
manufacturers that could offset this fuel penalty. Additionally, Tier III will provide the
opportunity to re-optimize engines for fuel economy when using aftertreatment, such as SCR, to
provide NOX reductions similar to the compliance strategy for some heavy-duty truck
manufacturers using urea SCR to meet our 2010 truck standard. The differential cost of using
lower sulfur fuel is discussed in Section 5.5.4. The estimated costs of using of urea associated
with Tier III NOx standards are derived from a urea dosage rate that is 7.5 percent of the fuel
consumption rate.
Operating costs per vessel vary depending on what year the vessel was built, for example,
vessels built as of 2016 will incur operating costs associated with the use of urea necessary when
using SCR as a Tier 3 and global Tier III NOx emission control technology. Vessels built prior
to 2016 will not incur the cost of using urea, but will incur operating costs associated with the
differential cost of using lower sulfur fuel. Further, we have assumed that vessels built as of
2011 that meet Tier 2 and global Tier II standards will incur a 2 percent fuel consumption
penalty. Therefore, an estimated fleet had to be developed over a range of years, and provide a
breakout of ships by age in each year. We use the fuel consumption rates from the inventory
analysis in Chapter 3 as the basis for estimating additional operating costs incurred prior to 2016
and for ships traveling in non-EC A areas within the U.S. after 2016
5.2.2 Development of 2010-2040 Fleets
To project future costs, we needed to first develop estimates of the number of ships that
may visit U.S. ports in a baseline year. This baseline fleet was grown using the growth rates
described in Chapter 3 to estimate an approximation of the fleet of ships by age and engine type
that may visit U.S. ports in the future.
5.2.2.1 Baseline Fleet
To characterize the fleet of ships visiting U.S. ports we used U.S. port call data collected
in 2002 for the inventory port analysis (see Chapter 3 of the draft RIA) which included only
vessels with Category 3 engines where the engine size and type was identified. We used this
data with the growth rates developed in the inventory analysis to estimate how many ships by
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Regulatory Impact Analysis
ship type and engine type would visit U.S. ports in future years. Due to the long life of these
vessels, and the fact that there has been no significant event that would have changed the
composition of the world fleet since this baseline data was taken, it is reasonable to use 2002
data as the basis for modeling the future fleet upon which to base hardware cost estimates. An
analysis is presented in Section 5.1.2.2 which confirms the reasonableness of this assumption
using 2007 MARAD data. The ships that called on the U.S. in 2002 were cross referenced with
Lloyd's database using each ship's EVIO number to determine the actual propulsion power,
engine type, and ship type information for each ship. This allowed for ships without Category 3
engines to be removed from the analysis. To separate slow speed engines from medium speed
engines where that information was not explicitly available, 2-stroke engines were assumed to be
slow speed engines (SSD), and 4-stroke engines were assumed to be medium speed engines
(MSD). The research performed for this cost analysis differentiated between SSD and MSD
engines, and separate $/kW values were developed for each engine type. The separation by
engine type was also necessary to allow for the use of the age distribution formula developed in
the inventory analysis (Chapter 3) which provided a method to estimate how many vessels the
hardware costs are applicable to in each year.
The ship type information gathered from this baseline data, for the purposes of both this
analysis and the inventory, was categorized into one of the following ship types: Auto Carrier,
Bulk Carrier, Container, General Cargo, Miscellaneous, Passenger, Refrigerated Cargo (Reefer),
Roll-On Roll-Off (RoRo), and Tankers. The 2002 baseline fleet was also used to develop
average ship characteristics shown in Table 5-3, these values were used to represent the
characteristics of new (and future existing) vessels included in this cost analysis.
The 2002 port call data were sorted by EVIO number to determine the total number of
unique ships that visited all included U.S. ports in 2002. Table 5-4 shows the breakout by ship
type of these approximately 6,700 ships. Next, to be consistent with the inventory analysis
which provides different regional growth rates, the original port call data were separated into the
same regions used by the inventory (South Pacific (SP), North Pacific (NP), East Coast (EC),
Gulf Coast (GC), Great Lakes (GL), Alaska East (AE), Alaska West (AW), Hawaii East (HE),
and West Hawaii (HW)). This was done by matching each port-of-call entry in the original port
call data file with the corresponding region containing that port as per the inventory analysis.2
This resulted in a fleet of ships for each region, each with a unique IMO number.
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Chapter 5: Engineering Cost Estimates
Table 5-3 Average Ship Characteristics
SHIP TYPE
Auto Carrier
Bulk Carrier
Container
General
Cargo
Passenger
Reefer
RoRo
Tanker
Misc.
ENGINE
SPEED
Slow Speed
Medium
Speed
Slow Speed
Medium
Speed
Steam Turbine
Slow Speed
Medium
Speed
Steam Turbine
Slow Speed
Medium
Speed
Steam Turbine
Slow Speed
Medium
Speed
Steam Turbine
Gas Turbine
Slow Speed
Medium
Speed
Slow Speed
Medium
Speed
Gas Turbine
Steam Turbine
Slow Speed
Medium
Speed
Gas Turbine
Steam Turbine
Slow Speed
Medium
Speed
Steam Turbine
AVERAGE
PROPULSION
POWER (KW)
11,000
9,600
8,400
6,300
6,400
27,000
14,000
21,000
7,700
5,200
18,000
24,000
24,000
27,000
44,000
10,000
7,400
16,000
8,600
47,000
22,000
9,800
6,700
7,600
21,000
4,700
9,400
13,000
AVERAGE
AUXILIARY
POWER
(KW)
3,000
2,600
1,900
1,400
1,400
6,000
3,000
4,700
2,000
1,300
4,600
6,600
6,600
7,600
12,000
4,200
3,000
4,000
2,200
12,000
5,800
2,100
1,400
1,600
4,400
1,300
2,500
3,500
SERVICE
SPEED
(KNOTS)
19
17
15
14
15
22
19
21
15
15
21
210
20
19
24
20
18
18
16
24
25
15
15
15
18
14
13
21
AVERAGE
DWT
17,000
13,000
47,000
27,000
19,000
45,000
19,000
30,000
26,000
8,700
23,000
6,200
6,200
13,000
12,000
11,000
7,600
30,000
8,400
37,000
19,000
61,000
27,000
40,000
59,000
8,800
6,000
17,000
Some ships may have visited ports in more than one region which could result in an
overestimate of the hardware costs that are applied to each unique vessel as required. To prevent
over-counting of vessels visiting the U.S., a factor was developed (see Equation 5-1) to account
for this overlap. The number of unique ships in each region (identified by unique IMO numbers)
was summed together to produce a total number of "unique" ships visiting all regions, this value
was then reduced by the total number of unique ships that had visited U.S. ports in 2002 (from
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Regulatory Impact Analysis
the original baseline data) to eliminate the over-counting of ships that had visited multiple
regions.
Equation 5-1 Regional Fleet Overlap Reduction Factor
#Unique Auto Carriers in Total Port Call Data ,, . , TT „ , , ,-,
—= = =—= = = % _ Actual _ Unique _ Re gionai _ Auto _ Carriers
2_^ Unique _ Auto _ Carriers _ by _ Re gion
For example, a total of 300 unique auto carriers visited all included U.S. ports in 2002,
yet when looking at unique ships on a regional basis and totaling all regions, 650 auto carriers
appeared to visit. This implies that only 46 percent of auto carriers were "unique" and the
additional 350 auto carriers were actually ships that had visited multiple regions. Therefore, only
46 percent of the auto carriers in each regional fleet were assumed to be "unique." The growth
rates were only applied to the corrected count of "unique" ships in each region to estimate the
regional fleet makeup in future years.
Table 5-4 2002 Baseline Fleet of Ships and Regional Overlap Factor
SHIP TYPE
Auto Carrier
Bulk
Container
Gen. Cargo
Misc
Pass
Reefer
RoRo
Tanker
Total
TOTAL UNIQUE
SHIP VISITS TO
U.S. PORTS IN 2020
300
2,500
1,000
980
24
110
280
120
1,400
6,700
UNIQUE REGIONAL
VISITING U.S.
PORTS IN 2020
650
3,600
1,600
1,700
50
200
400
200
2,700
1 1 ,000
REGIONAL
OVERLAP FACTOR
46%
68%
63%
57%
49%
57%
71%
58%
52%
62%
5.2.2.2 Projected Fleet
Within each region, the ship types were further broken down by engine type. The unique
ship fleet within each region was then grown by ship type and engine type using the appropriate
growth rate (Chapter 3) to estimate the makeup of the future fleet. To be consistent with the
inventory, we used the same flag fractions to estimate how many of these vessels were U.S.-
flagged and how many were foreign-flagged.3 However, the flag fractions developed by the
inventory are based on installed power, while the cost estimate is based on the number of vessels
that called U.S. ports. According to MARAD, U.S.-flagged ships averaged 36 calls per vessel
per year while foreign-flagged ships averaged only eight calls per vessel per year.4 To eliminate
the potential over-counting of the actual number of U.S.-flagged ships using the installed power
method, which does not account for the disparity in the number of visits per year by ship, the
U.S.-flagged vessel fraction presented in the inventory was reduced by 75 percent for this cost
analysis and was applied to estimate the number of U.S. vessels in the future fleet. This resulted
in a more representative estimated fleet in 2007 of 265 existing and 22 new U.S.-flagged vessels.
According to MARAD, at the end of 2007 there were 189 U.S.-flagged vessels and another 25
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Chapter 5: Engineering Cost Estimates
on order that were over 10,000 deadweight tons.5'0 Table 5-5 shows the estimated 2020 fleet of
ships expected to visit U.S. ports.
Table 5-5 Baseline 2002 and Estimated 2020 Fleet by Ship Type and Engine Type
SHIP TYPE
Auto
Carrier
Auto
Carrier
Bulk Carrier
Bulk Carrier
Bulk Carrier
Container
Container
Container
General
Cargo
General
Cargo
General
Cargo
Passenger
Passenger
Passenger
Passenger
Reefer
Reefer
RoRo
RoRo
RoRo
RoRo
Tanker
Tanker
Tanker
Tanker
Misc.
Misc.
Misc.
ENGINE
SPEED
SSD
MSD
SSD
MSD
ST
SSD
MSD
ST
SSD
MSD
ST
SSD
MSD
ST
GT
SSD
MSD
SSD
MSD
GT
ST
SSD
MSD
GT
ST
SSD
MSD
ST
Total:
US
FLAG
FOREIGN
FLAG
TOTAL
2002
8
1
70
20
8
30
3
2
20
3
1
2
1
1
0
5
2
2
1
0
0
30
10
1
5
0
0
0
220
220
50
2,300
300
60
890
120
30
630
120
20
70
30
5
2
120
60
60
30
1
2
1,000
300
20
50
7
4
1
6,500
228
51
2,370
320
68
920
123
32
650
123
21
72
31
6
3
195
62
62
31
1
3
1,030
340
21
55
8
4
2
6,730
US
FLAG
FOREIGN
FLAG
TOTAL
2020
20
4
150
30
15
70
7
4
40
8
3
4
2
1
0
10
5
4
2
0
0
60
20
1
7
1
1
1
470
510
120
4,900
660
120
2,100
290
70
1,400
300
40
150
80
10
5
130
130
140
60
2
5
2,200
800
50
110
15
10
3
14,410
530
124
5,050
690
135
2,170
298
74
1,440
308
43
154
82
11
5
140
135
144
62
2
5
2,260
820
51
117
16
10
3
14,880
c Note that the number reported by MARAD includes only vessels greater than 10,000 DWT while the average
vessel characteristics developed from the baseline fleet of ships visiting U.S. ports in 2002, and reported in
Table 5-3, include some vessels less than 10,000 DWT assumed to have Category 3 propulsion engines, and are
considered in this analysis.
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Regulatory Impact Analysis
5.2.2.3 Current Distillate Carrying Capacity of the Existing Global Fleet
Although most ships primarily operate on residual fuel, they typically carry some amount
of distillate fuel as well. Switching to the use of lower sulfur distillate fuel is the compliance
strategy assumed here to be used by both new and existing ships in 2015 when the new lower
sulfur fuel standards go into effect. To estimate the potential cost of this compliance, we first
evaluated the distillate storage capacity of the current existing fleet to estimate how many ships
may require additional hardware to accommodate the use of lower sulfur fuel. We performed
this analysis on the entire global fleet listed in Lloyd's database as of 2008.6 Of the nearly
43,000 vessels listed, approximately 20,000 vessels had provided Lloyd's with fuel tankage
information, cruise speed, and propulsion engine power data. Using this information, we were
able to estimate how far each individual vessel could travel on its existing distillate carrying
capacity.
The cruise speed provided by Lloyd's was used to determine the vessel's maximum
speed using Equation 5-2 while transit speed was assumed to be 12 knots, and maneuver speed
5.8 knots.7 The load factor used at cruise speed was 83 percent, while both the transit and
maneuver load factors were estimated by cubing the ratio their respective speeds to the ship's
maximum speed. The same low load factors used in the inventory (for loads less than 20
percent) were used here to adjust the brake specific fuel consumption (BSFC) because diesel
engines are less efficient at low loads and the BSFC tends to increase. It was also assumed that
ships spend a total of four hours per call in both transit and maneuver speeds. The BSFC values
used here are the same as reported in the inventory section, 195 g/kWh for SSDs, 210 g/kWh for
MSDs, and 305 g/kW for steam and gas turbines. The fuel consumed by auxiliary engines was
also taken into account and the same ratios used in the inventory section (Chapter 3) of auxiliary
power by ship type were used here to estimate the total installed auxiliary engine power and load
factors at cruise, transit, and maneuver speeds for each ship.
Equation 5-2: Maximum Speed
Lloyds _ speed
0.94
* 0.83 = max imum _ speed
To determine if the current distillate capacity of a particular ship was sufficient to call on
the U.S. EGA without requiring additional hardware, we evaluated whether or not each ship
could travel 1,140 nm, or the distance between the Port of Los Angeles and the Port of Tacoma.
This distance was selected because it represents one of the longer trips a ship could travel
without stopping at another port, and should overestimate the number of vessels that would
require such a modification. The amount of fuel a ship will consume calling on a port and
travelling a total distance of 1,140 nm was determined using the methodology described above.
The total fuel used in each mode (cruise, transit and maneuver) by both main and auxiliary
engines was summed and compared to the total amount of distillate fuel carried onboard. This
provided an estimate of the number of ships that had sufficient distillate capacity onboard, and
the number that did not, shown in Table 5-6. The resulting percentages of ships that were
estimated to require a retrofit were then applied to the number of existing ships in the 2015 fleet
to estimate the total cost of this compliance strategy for existing ships built prior to 2015. The
same percentages were also applied to all new ships built as of 2015 to determine the number of
5-14
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Chapter 5: Engineering Cost Estimates
ships that may require additional hardware, beyond that of comparable new ships, to estimate the
cost of this compliance strategy for new vessels.
Table 5-6 Ships that Can Travel 1,140 nm on Existing Distillate Carrying Capacity
SHIP TYPE
General Cargo
Tanker
Container
Bulk Cargo
RoRo
Auto Carrier
Misc.
Passenger
Reefer
TOTAL
#
SHIPS
4,600
5,900
1,900
3,600
510
360
1,600
710
530
TOTAL #
SHIPS THAT
ONLY
CARRY
DISTILLATE
1,900
740
45
230
70
20
1,100
170
60
DISTILLATE
ONLY SHIPS
THAT MAY
NEED A
MODIFICATION
#
9
60
1
7
1
0
4
10
0
%
0.5%
8.7%
2.2%
3.1%
1.4%
0.0%
0.4%
6.0%
0.0%
TOTAL #
SHIPS THAT
CARRY
DISTILLATE
+ ANOTHER
FUEL
2,300
4,900
1,700
3,000
380
310
210
460
440
SHIPS THAT
CARRY
DISTILLATE +
ANOTHER
FUEL THAT
MAY NEED A
MODIFICATION
#
200
1,600
910
1,600
30
20
70
270
20
%
8.9%
33%
53%
53%
7.6%
7.1%
34%
59%
4.1%
TOTAL #
SHIPS THAT
CARRY NO
DISTILLATE
370
280
140
400
60
40
210
85
25
%NO
DISTILLATE
8.2%
4.7%
7.3%
11%
12%
10%
14%
12%
4.8%
TOTAL OF ALL
SHIPS THAT
MAY NEED A
MODIFICATION
#
580
1,900
1000
2,000
90
60
280
360
40
%
13%
33%
55%
55%
18%
16%
18%
51%
8.2%
5.3 Engineering Costs for Freshly Manufactured Engines
This section describes the projected variable and fixed costs to new engines. The
component, tooling, labor and overhead costs are presented here separately for Tier 2 and Tier 3.
First, the costs are presented as estimated for the six engine configurations described in Table
5-2. Those values were then plotted by engine type and the resulting curve fit and $/kW
equation is presented next. Finally, the stream of costs from 2010 through the year 2040 are
presented with a three and seven percent discount rate.
5.3.1 Tier 2 Variable Hardware Costs
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. There are
no variable costs associated with the 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.0 However, the migration of some engines from
mechanically controlled 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. The cost of the Tier 2 technology presented here
was developed using Tier 1 technology as the baseline. Table 5-7 shows the per engine variable
cost estimates for the six engine configurations used in this analysis, Figure 5-1 shows the cost
D MAN Diesel, "Exhaust Gas Emission Control Today and Tomorrow, August 19, 2008," available at
http://www.manbw.com/article_009187. html
5-15
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Regulatory Impact Analysis
curve developed from these data points to determine a $/kW equation applicable to other engine
sizes.
Table 5-7 Variable Costs for Going to Common Rail from Mechanical Fuel Injection Systems
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
Assembly
Labor (hours)
Cost($23.85/hr)
Overhead @40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
$3,500
$2,000
3
$2,000
$3,500
$2,500
9
$2,500
$40,000
120
$2,900
$1,100
$4,000
$44,000
$12,800
$56,800
$3,500
$2,000
6
$3,000
$4,500
$2,500
12
$2,500
$55,500
160
$3,800
$1,500
$5,300
$60,800
$17,700
$78,500
$3,500
$2,000
8
$4,000
$6,000
$2,500
16
$2,500
$72,000
200
$4,800
$1,900
$6,700
$78,700
$22,800
$101,500
$5,000
$2,000
9
$2,500
$4,500
$3,500
18
$3,000
$96,000
200
$4,800
$1,900
$6,700
$102,700
$29,800
$132,500
$5,000
$2,000
12
$3,500
$6,000
$3,500
24
$3,000
$125,500
250
$5,900
$2,400
$8,300
$133,800
$38,800
$172,600
$5,000
$2,000
18
$4,500
$8,000
$3,500
36
$3,000
$182,500
300
$7,100
$2,900
$10,000
$192,500
$55,800
$248,300
5-16
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Chapter 5: Engineering Cost Estimates
Costs of Migrating from Mechanical Fuel Injection
to Common Rail
$300,000
$250,000 -
$200,000 -
S? $150,000 -
$100,000 -
$50,000 -
»"Slow Speed - Mechanical Injection"
• Medium Speed Mechanical Injection
48,000, $248,000
y=67,OOOLn(x)- 470,000
15,000,$173,0
8,500,$132,000
18,000,$101,000
5^00, $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
Figure 5-1 Variable Cost Curve-Fit for Mechanically Controlled MFI to Common Rail Fuel Injection
Systems
It is estimated that approximately 20 percent of SSD and 60 percent of MSD will remain
mechanically injected under the Tier 2 standards. We estimate that 5 percent of all SSD and 10
percent of MSD are already equipped with common rail fuel systems.E Table 5-8 shows the
expected migration from MFI to common rail for Tier 2 and Tier 3 NOx standards. Table 5-9
shows the total cost estimate of the Tier 2 program per year from 2010 through 2040, these costs
are included in the total cost of the coordinated strategy. Also included here are the costs
associated with the requirement to test each production engine (§1042.302). We estimate that,
on average, this requirement would add a one-time cost of $10,000 for each new engine.
Table 5-8 Mechanical Injection to Common Rail Technology Mix for Tier 2 and Tier 3
TECHNOLOGY
MIX
Tier 2
(Tier 1 is baseline)
TierS
ENGINE
SPEED
SSD
MSD
SSD
MSD
PERCENT
COMMON
RAIL IN TIER 1
5
10
80
40
PERCENT
MECHANICAL MFI
TO COMMON RAIL
75
30
5
10
PERCENT ELECTRICAL
MFI TO COMMON RAIL
0
0
15
30
TOTAL
PERCENT
COMMON RAIL
80
40
100
80
' Conversations between Lou Browing of ICF and Amy Kopinof the U.S. EPA on 3/1/09.
5-17
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Regulatory Impact Analysis
Table 5-9 Estimated Tier 2 Variable Costs to U.S.-Flagged Vessels 2010-2040
TOTAL US FLAG - TIER 2 COSTS
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
SSD
Variable
$0
$2,410,000
$2,510,000
$2,610,000
$2,710,000
$2,810,000
$2,700,000
$2,800,000
$2,910,000
$3,030,000
$3,150,000
$3,270,000
$3,400,000
$3,540,000
$3,680,000
$3,820,000
$3,980,000
$4,130,000
$4,300,000
$4,470,000
$4,650,000
$4,840,000
$5,040,000
$5,240,000
$5,460,000
$5,680,000
$5,910,000
$6,150,000
$6,400,000
$6,670,000
$6,940,000
$75,400,000
$43,200,000
MSD
Variable
$0
$164,000
$170,000
$176,000
$183,000
$190,000
$139,000
$1 44,000
$150,000
$155,000
$161,000
$167,000
$174,000
$181,000
$188,000
$195,000
$203,000
$21 1 ,000
$219,000
$227,000
$236,000
$246,000
$256,000
$266,000
$277,000
$288,000
$299,000
$31 1 ,000
$324,000
$337,000
$351 ,000
$4,040,000
$2,380,000
Total
$0
$2,570,000
$2,680,000
$2,790,000
$2,890,000
$3,000,000
$2,840,000
$2,940,000
$3,060,000
$3,190,000
$3,310,000
$3,440,000
$3,570,000
$3,720,000
$3,870,000
$4,020,000
$4,180,000
$4,340,000
$4,520,000
$4,700,000
$4,890,000
$5,090,000
$5,300,000
$5,510,000
$5,740,000
$5,970,000
$6,210,000
$6,460,000
$6,720,000
$7,010,000
$7,290,000
$79,400,000
$45,600,000
5.3.2 Tier 2 Fixed Costs
Tier 2 fixed costs are comprised of those associated with engine modifications shown in
Table 5-10, and those associated with the migration from MFI to common rail shown in Table
5-11. 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
5-18
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Chapter 5: Engineering Cost Estimates
compression ratios as well as to accommodate different injection nozzles. Differential costs for
new common rail fuel injection systems that replace MFI systems include research and
development, and retooling costs include modification of the cylinder head to accommodate the
common rail fuel injection systems. The fixed costs associated with common rail are applied on
a per vessel basis only to those engines expected to receive this technology; the fixed costs
associated with the engine modifications are applied to all vessels. These costs are included in
the total estimated cost of the coordinated strategy.
Table 5-10 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 5-11 Fixed Costs for Mechanical 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 (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
5.3.3 Tier 3 Variable Hardware Costs
Tier 3 NOx standards are approximately 80 percent lower than the existing Tier 1 NOx
standards. To meet these standards, it is expected that SCR will be used along with the
additional migration from mechanical injection systems to common rail, and engine
modifications. The variable costs associated with Tier 3 include the continued migration to
5-19
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Regulatory Impact Analysis
common rail (see Table 5-8 for the expected percentages migrating for Tier 3). Table 5-7 shows
these variable costs. Table 5-12 shows the variable costs associated with the migration from
electronically controlled mechanical fuel injection (EFI) to common rail. A cost estimate is
presented for each of the six engine configurations used in this analysis. Figure 5-2 shows the
cost curve developed from these data points to determine a $/kW equation applicable to other
engine sizes and types.
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 5-13,
Figure 5-3 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
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 5-14 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 5-15 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).F
In this analysis, we estimated the average number of hours a ship may spend to call on a
U.S. port: if the call was straight in and straight out at a distance of 200 nm, the average time
spent was slightly over 35 hours. If the distance travelled was substantial, such as from the Port
of Los Angeles to the Port of Tacoma, or 1140 nm, the average time spent travelling was
approximately 75 hours. Therefore, the size of the tanks and corresponding $/kW value
estimated here to carry enough urea for 250 hours of continuous operation may be an
overestimate, and some owners may choose a smaller tank and to refill more often. Based on
250 hours of operation, a range of urea tank sizes from 20 m3 to approximately 256 m3 was
estimated for the six different engine configurations used in this analysis.
To understand what impacts this may have on the cargo hauling capacity of the ship, we
looked at the ISO standard containers used today. Currently, over two-thirds of the containers in
use today are 40 feet long, total slightly over 77m3 and are the equivalent of two TEU.G The
urea tank size range estimates provided here reflect a cargo equivalence of 0.5-2 TEUs, based on
a capacity sufficient for 250 hours of operation. The TEU capacity of container ships, for
example, continues to increase and can be as high as 13,000 TEUs; while not all ports are
equipped to handle ships of this size, feeder ships (ships that carry containers to ocean-going
F http://www.metalprices.com/FreeSite/metals/stainlessj)roduct/product.asp#Tables for 2006.
G www.iicl.org, Institute of International Container Lessors
5-20
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Chapter 5: Engineering Cost Estimates
vessels in smaller ports) have also increased in size to carry as much as 2,000 TEUs.H Based on
a rate of approximately $1,300 per TEU to ship a container from Asia to the US,!a net profit
margin of 10%, and an average of 16 trips per year, the estimated cost due to displaced cargo to
call on a U.S.-Canada EGA may be $2,100.J'K'L The cost analysis presented here does not
include displaced cargo costs due to the variability of tank sizes owners choose to install.
The cost of Tier 3 technology as presented here was developed using Tier 2 as a baseline.
Figure 5-4 shows the 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 (§1042.302). We estimate that, on average, this requirement
would add a one-time cost of $10,000 for each new engine. Table 5-16 shows the total variable
hardware costs estimated from 2010 through 2040 of Tier 3 for U.S.-flagged vessels, and Table
5-17 shows the total variable hardware costs estimated from 2010 through 2040 of Tier 3 for
foreign-flagged vessels.
H Kristensen, Hans Otto Holmegaard, "Preliminary Ship Design of Container Ships, Bulk Carriers, Tankers, and
Ro-Ro Ships. Assessment of Environmental Impact from Sea-Borne Transport Compared with Landbased
Transport," March, 2008.
1 http://people.hofstra.edu/geotrans/eng/ch2en/conc2en/maritimefreightrates.html
Jhttp://moneycentral.msn.com/investor/invsub/results/hilite.asp?Symbol=SSW
Khttp://moneycentral.msn.com/investor/invsub/results/hilite.asp?Symbol=SSW
L Based on a container ship carrying nearly 9,000 TEUs traveling from Hong Kong to the Port of Los Angeles
(approximately 6,400 nm) with a cruise speed of 25 nm/hr, the round trip time is nearly 21 days and this trip could
be made roughly 16 times per year.
5-21
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Regulatory Impact Analysis
Table 5-12 Variable Costs for EFI 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 Costs to the 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
Assembly
Labor (hours)
Cost($23.85/hr)
Overhead @ 40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
$500
$2,000
3
$1,000
$1,500
$500
9
$500
$14,000
40
$950
$380
$1,330
$15,300
$4,400
$19,700
$500
$2,000
6
$1,000
$1,500
$500
12
$500
$21,500
60
$1,430
$570
$2,000
$23,500
$6,800
$30,300
$500
$2,000
8
$1,000
$1,500
$500
16
$500
$27,500
80
$1,910
$760
$2,670
$30,200
$8,800
$39,000
$500
$2,000
9
$1,500
$2,000
$750
18
$650
$36,150
40
$950
$380
$1,330
$37,500
$10,900
$48,400
$500
$2,000
12
$1,500
$2,000
$750
24
$650
$46,650
60
$1,430
$570
$2,000
$48,700
$14,100
$62,800
$500
$2,000
18
$1,500
$2,000
$750
36
$650
$67,650
80
$1,910
$760
$2,670
$70,300
$20,400
$90,700
5-22
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Chapter 5: Engineering Cost Estimates
$100,000
$90,000 -
$80,000 -
$70,000 -
$60,000 -
$50,000 -
$40,000 -
$30,000 -
$20,000 -
$10,000 -
Costs of Migrating from Electronic Fuel Injection to
Common Rail
"Slow Speed - Electronic Injection"
Medium Speed_Electronic Injection
15,000,$63,000
Ln(x)-170,000
48,000, $91,000
18,000,$39,000
*~~~
r, $30,000
,500, $20,000 y = 14,000*Ln(x) - 96,000
10,000
20,000 (kW) 30,000
40,000
50,000
60,000
Figure 5-2 Variable Cost Curve-Fit for Electronically Controlled MFI to Common Rail Fuel Injection
Systems
Table 5-13 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
5-23
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Regulatory Impact Analysis
Estimated Costs for Tier 3 Engine Modifications
$140,000
»Slow Speed - Engine Modifications
• Medium Speed Engine Modifications
$120,000 -
$100,000 -
$80,000 -
$60,0008-
$40,000 -
$20,000 -
y= 31661Ln(x)-226946 48,ooo, $113,456
18,000,$92,287
15,000,$80,1
500, $57,728^
' 9,500, $53,058
4,50"0, $42,647
y= 3.7768x+ 22378
10,000
20,000
(kW)
30,000
40,000
50,000
60,000
Figure 5-3 Variable Cost Curve-Fit for Engine Modifications Associated with Tier 3
5-24
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Chapter 5: Engineering Cost Estimates
Table 5-14 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
Component Costs
Aqueous Urea Tank
Reactor
Dosage Pump
Urea Injectors (each)
Number of Urea
Injectors
Piping
Bypass Valve
Acoustic Horn
Cleaning Probe
Control UnitAA/iring
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
5-25
-------
Regulatory Impact Analysis
Estimated Tier 3 Selective Catalytic Reduction
Costs
$2,500,000
• Slow Speed-SCR • Medium Speed SCR
$2,000,000 -
$1,500,000 -
$1,000,000 -
8,5
$500,000 -
y= -0.0004X2 + 57.2x + 145,000
48,000,$2,100,00)
15,000, $922,000
DO, $606,000
4,500, $367,00
18,000,$678,000
D,$516,000
y= 22.6x +279,000
10,000
20,000
(kW)
30,000
40,000
50,000
60,000
Figure 5-4 Variable Cost Curve-Fit for SCR Systems
Table 5-15 Variable Costs Associated with the Urea Tanks for use with SCR Systems
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
Urea Tank Costs
Urea Amount (kg)
Density (kg/mA3)
Tank Size (mA3)
Tank Material (mA3)
Tank Material Cost ($)
Assembly
Labor (hours)
Cost ($23.85/hr)
Overhead @ 40%
Total Assembly Cost
Total Variable Cost
Markup @ 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
5-26
-------
Chapter 5: Engineering Cost Estimates
Table 5-16 Estimated Tier 3 Costs to U.S.-Flagged Vessels 2010-2040 (SMillions)
TOTAL ESTIMATED US FLAG TIER 3 COSTS
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
SSD
Variable
$0.00
$0.00
$0.00
$0.00
$0.00
$0.00
$21.5
$22.4
$23.3
$24.2
$25.2
$26.2
$27.2
$28.3
$29.5
$30.6
$31.9
$33.2
$34.5
$35.9
$37.4
$38.9
$40.5
$42.2
$43.9
$45.7
$47.6
$49.6
$51.6
$53.8
$56.0
$509
$261
MSD
Variable
$0.00
$0.00
$0.00
$0.00
$0.00
$0.00
$2.98
$3.09
$3.21
$3.33
$3.46
$3.59
$3.73
$3.87
$4.02
$4.18
$4.35
$4.52
$4.69
$4.88
$5.07
$5.28
$5.49
$5.71
$5.94
$6.18
$6.43
$6.69
$6.96
$7.25
$7.54
$69.3
$35.6
Total
$0.00
$0.00
$0.00
$0.00
$0.00
$0.00
$24.5
$25.5
$26.5
$27.5
$28.6
$29.8
$31.0
$32.2
$33.5
$34.8
$36.2
$37.7
$39.2
$40.8
$42.5
$44.2
$46.0
$47.9
$49.8
$51.9
$54.0
$56.3
$58.6
$61.0
$63.5
$579
$297
5-27
-------
Regulatory Impact Analysis
Table 5-17 Estimated Tier 3 Costs to Foreign Flagged Vessels 2010-2040 (SMillions)
TOTAL FOREIGN FLAG
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV @ 3%
NPV@7%
SSD
Variable
$0
$0
$0
$0
$0
$0
$754
$784
$817
$850
$885
$922
$960
$1,000
$1 ,040
$1,080
$1,130
$1,180
$1,230
$1,280
$1,330
$1,390
$1,450
$1,510
$1,570
$1,640
$1,710
$1,780
$1,850
$1 ,930
$2,020
$18,100
$9,260
MSD
Variable
$0
$0
$0
$0
$0
$0
$89
$93
$97
$101
$105
$110
$115
$120
$125
$130
$136
$142
$148
$154
$161
$168
$175
$183
$191
$199
$208
$217
$227
$237
$247
$2,180
$1,110
Total
$0
$0
$0
$0
$0
$0
$843
$877
$914
$951
$991
$1,032
$1,075
$1,119
$1,165
$1,210
$1 ,266
$1 ,322
$1 ,378
$1 ,434
$1 ,491
$1 ,558
$1 ,625
$1 ,693
$1,761
$1 ,839
$1,918
$1 ,997
$2,077
$2,167
$2,267
$20,280
$10,370
5.3.4 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, and are shown in Table 5-18. The
migration to common rail from for Tier 3 is primarily from EFI which includes modification of
the cylinder head to accommodate common rail fuel injection systems, these costs are shows in
5-28
-------
Chapter 5: Engineering Cost Estimates
Table 5-18. The fixed costs associated with the migration from MFI to common rail are shown
above in Table 5-11. 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. These
costs are applied to U.S.-flagged vessels and are included in the total cost estimate of the
coordinated strategy.
Table 5-18 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
Engines/yr.
Years to recover
Fixed cost/engine
$1,376,000
$2,000,000
$5,000
40
5
$16,900
MEDIUM
9,500
12
65
550
$1,376,000
$2,000,000
$5,000
40
5
$16,900
MEDIUM
18,000
16
95
500
$1,376,000
$2,000,000
$5,000
40
5
$16,900
LOW
8,500
6
380
130
$1,376,000
$2,000,000
$5,000
40
5
$16,900
LOW
15,000
8
650
110
$1,376,000
$2,000,000
$5,000
40
5
$16,900
LOW
48,000
12
1400
100
$1,376,000
$2,000,000
$5,000
40
5
$16,900
Table 5-19 Fixed Costs Associated with the Migration of EFI 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
5-29
-------
Regulatory Impact Analysis
Table 5-20 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
5.4 Engineering Costs for Existing Engines
The October 2008 amendments to MARPOL Annex VI include NOx standards that apply
to existing engines on ships constructed on or after January 1, 1990 but prior to January 1, 2000
for marine diesel engines with a per cylinder displacement of at least 90 liters and a power output
of over 5,000 kW. Subject engines must be retrofit with components that reduce NOx
approximately 20 percent and be certified to confirm the engine meets Tier I standards.
5.4.1 Variable Costs for the Annex VI Existing Engine Program
Most manufacturers will comply with the existing engine standard by providing retrofit
kits which contain modified fuel injectors and possibly modified injection timing. The costs for
the retrofit kit include new fuel injectors plus three months of research and development to
modify the timing, and consist only of the incremental cost associated with the required emission
reductions. A Marine Society approval certificate is also estimated to be included. As part of
the JJVIO regulations, the retrofit kit cannot exceed $375 Special Drawing Rights (SDR)/metric
ton of NOx reduced. The currency value of the SDR is determined by summing the values in
U.S. dollars, based on market exchange rates, of a basket of major currencies (the U.S. dollar,
Euro, Japanese yen, and pound sterling). The SDR currency value is calculated daily and the
valuation basket is reviewed and adjusted every five years, the conversion rate used in this
analysis is $1.49 per SDR. Table 5-21 presents the estimated variable costs associated with the
existing engine program. The costs are presented only for the engine configurations used in this
analysis that are subject to the program.
5-30
-------
Chapter 5: Engineering Cost Estimates
Table 5-21 Variable Costs Associated with the Existing Engine Program
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
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
Number of Injectors
Improved Fuel Valves
(each)
Total Component Cost
Assembly
Labor (hours)
Cost ($23.85/hr)
Overhead @40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
16
$235
$3,760
120
$2,860
$1,150
$4,010
$7,770
$2,250
$10,020
18
$235
$4,230
168
$4,010
$1,600
$5,610
$9,840
$2,850
$12,690
24
$375
$9,000
216
$5,150
$2,060
$7,210
$16,210
$4,700
$20,910
36
$470
$16,920
312
$7,440
$2,980
$10,420
$27,340
$7,930
$35,270
$40,000
$35,000
$30,000
$25,000
$20,000
$15,000
$10,000
$5,000
$0
Existing Engine Program Costs
Slow Speed
Medium Speed
48,000, $35,300
y=13,000*l_n(x)-104,000
15,000, $20,900
8,500, $12,700
18,000, $10,000
10,000
20,000
(kW)
30,000
40,000
50,000
60,000
Figure 5-5 Variable Cost Curve Fit for Existing Engine Program
5-31
-------
Regulatory Impact Analysis
5.4.2 Fixed Costs for the Annex VI Existing Engine Program
The fixed costs associated with the existing engine program are presented below in Table
5-22 and include the costs for research and development and marine society approval. These
costs as applied to U.S.-flagged vessels are included in the total cost estimate of the coordinated
strategy.
Table 5-22 Fixed Costs Associated with the Existing Engine Program
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
18,000
16
95
500
Fixed Costs
R&D Costs (0.25 year R&D)
Marine Society Approval
Engines/yr.
Years to recover
Fixed cost/engine
$172,000
$5,000
40
5
$880
LOW
8,500
6
380
130
$172,000
$5,000
40
5
$880
LOW
15,000
8
650
110
$172,000
$5,000
40
5
$880
LOW
48,000
12
1400
100
$172,000
$5,000
40
5
$880
5.4.3 Total Estimated Costs of the Annex VI Existing Engine Program
The costs for the existing engine program for Tier 0 (pre-control) engines were developed
in the same manner modeled in the inventory (Chapter 3) as being applicable to 80 percent of
1990 through 1999 model year engines greater than 90 liters per cylinder (L/cyl) and 5,000 kW
starting in 2011, with a five year phase-in. In this cost analysis, the research and development
fixed costs were phased in from 2010-2014, while the certification fixed costs were applied in
2010. To estimate the cost of the existing engine program to U.S.-flagged vessels, we had to
determine how many ships built between 1990-1999 there would be in each year from 2011
through 2015 using the age distribution analysis from the inventory. The $/kW values were then
applied to the portion of the fleet each year between 2011 and 2015 expected to be subject to
these standards. Table 5-23 presents the total estimated costs of the existing engine program to
U.S.-flagged vessels; these costs are included in the total cost estimate of the coordinated
strategy.
Table 5-23 Total Estimated Costs of the Existing Engine Program to U.S.-Flagged Vessels
TOTAL US FLAG
Year
2010
2011
2012
2013
2014
2015
2016
SSD
$0
$145,000
$139,000
$132,000
$126,000
$128,000
$0
MSD
$0
$6,800
$5,500
$4,600
$3,600
$3,000
$0
Total
$0
$152,000
$1 44,000
$137,000
$129,000
$131,000
$0
5-32
-------
Chapter 5: Engineering Cost Estimates
5.5 Engineering Costs for Vessels
5.5.1 Freshly Manufactured Vessels
5.5.1.1 Variable Costs
The vessel costs associated with the coordinated strategy are those that may be incurred if
additional hardware is required to accommodate the use of lower sulfur fuel. This section
discusses the costs that may be incurred by some newly built ships if additional fuel tank
equipment, beyond that installed on comparable new ships, is required to meet lower sulfur fuel
standards in the EGA. Based on existing vessel fleet data, we estimate that nearly one-third of
new vessels may need additional equipment installed to accommodate additional lower sulfur
fuel storage capacity. The size of the tank is dependent on the frequency with which the
individual ship owner prefers to fill the lower sulfur fuel tank.
Costs include additional distillate fuel storage tanks, an LFO fuel separator, an HFO/LFO
blending unit, a 3-way valve, an LFO cooler, filters, a viscosity meter, and various pumps and
piping, these costs are shown in Table 5-24. The estimates of the additional tank costs are shown
in Table 5-25. Distillate tanks are assumed to be constructed of cold rolled steel one mm thick,
double walled, and estimated to carry capacity sufficient for 250 hours of propulsion and
auxiliary engine operation. Similar to the urea tank size estimation presented in this analysis,
this is most likely an overestimate of the amount of lower sulfur fuel a ship owner would need to
carry, resulting in an overestimate of the total cost to existing and new vessels. The tank size
based on 250 hours of operation and based on the six different engine configuration used in this
analysis ranges from 240 m3 to nearly 2,000 m3 This would be the equivalent of 6-50 TEUs.
This cost analysis does not reflect the costs of displaced cargo as there are other design options
such as partitioning of a residual fuel tank to allow for lower sulfur fuel capacity which would
reduce the amount of additional space required, nor does this analysis reflect the possibility that
some ships may have already been designed to carry smaller amounts of distillate fuel in separate
tanks for purposes other than continuous propulsion.
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, Figure 5-6, used to determine a $/kW
equation applicable to other engine sizes and types. Table 5-27 presents the total estimated
variable hardware costs for U.S.-flagged vessels associated with the installation of additional
equipment to enable the use of lower sulfur fuel, these costs are included in the total estimated
cost of the coordinated strategy. While the estimated costs to new foreign-flagged vessels are
presented here in Table 5-28, they are not included as a part of the total cost of the coordinated
strategy as this technology will be used globally and will result in emissions reductions in many
other countries.
5-33
-------
Regulatory Impact Analysis
Table 5-24 Variable Costs Associated with the use of Lower Sulfur Fuel - New 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
Hardware Cost to Supplier
Component Costs
Additional Tanks
LFO Separator
HFO/LFO Blending Unit
3-Way Valve
LFO Cooler
Filters
Viscosity Meter
Piping/Pumps
Total Component Cost
Assembly
Labor (hours)
Cost($23.85/hr)
Overhead @ 40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
$3,400
$2,800
$4,200
$950
$2,400
$950
$1,400
$2,000
$18,100
240
$5,700
$2,300
$8,000
$26,100
$7,600
$33,700
$5,500
$3,300
$4,700
$1,400
$2,800
$950
$1,400
$2,000
$22,100
320
$7,600
$3,100
$10,700
$32,700
$9,500
$42,200
$8,300
$3,800
$5,600
$1,900
$3,300
$950
$1,400
$2,000
$27,300
480
$11,400
$4,600
$16,000
$43,300
$12,600
$55,900
$4,600
$3,800
$4,700
$1,400
$2,800
$950
$1,400
$2,000
$21,600
320
$7,600
$3,100
$10,700
$32,300
$9,400
$41,700
$6,500
$4,200
$5,600
$1,900
$3,800
$950
$1,400
$2,000
$26,400
480
$11,400
$4,600
$16,000
$42,400
$12,300
$54,700
$13,700
$4,700
$6,600
$2,800
$4,700
$950
$1,400
$2,000
$36,900
600
$14,300
$5,700
$20,000
$56,900
$16,500
$73,400
5-34
-------
Chapter 5: Engineering Cost Estimates
Fuel Switching Hardware Costs - New Vessels
»Slow Speed - Fuel Switching Hardware Costs Existing Vessels
• Medium Speed Fuel Switching Costs-Existing Vessels
1,000
$70,000 -
$60,000 -
$50,000 -
$40,000 -
$30,000 -
$20,000 -
$10,000 -
y= 18,OOOLn(x)-120,000
48,000, $73,000
8,500, $42,000
4,500, $34,000
9,500, $42,000
y= 1.64x + 26,000
10,000
20,000 (kW) 30,000
40,000
50,000
60,000
Figure 5-6 Variable Cost Curve Fit for Fuel Switching Vessels Costs to New Vessels
5-35
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Regulatory Impact Analysis
Table 5-25 Variable Cost to New Vessels Associated with Fuel Switching - Extra Tankage
SPEED
Engine Power
(kW)
Cylinders
Liters/cylinder
Engine Speed
(rpm)
MEDIUM
4,500
9
35
650
Propulsion
BSFC (g/kWh)
Load factor
Auxiliary
Power (kW)
BSFC (g/kWh)
Load factor
210
73%
1,000
227
31%
Combined
Fuel Amount (kg)
Density (kg/mA3)
Tank Size (mA3)
Tank Material
(mA3)
Tank Material Cost
($)
Assembly
Labor (hours)
Cost ($23.85/hr)
Overhead@40%
Total Assembly
Cost
Total Variable
Cost
Markup @ 29%
Total Hardware
RPE
190,000
960
238
0.46
$2,500
5
$119
$48
$167
$2,600
$800
$3,400
MEDIUM
9,500
12
65
550
210
73%
2,200
227
31%
401,000
960
501
0.75
$4,100
6
$143
$57
$200
$4,300
$1,200
$5,500
MEDIUM
18,000
16
95
500
210
73%
4,100
227
31%
760,000
960
950
1.15
$6,200
7
$167
$67
$234
$6,500
$1,900
$8,400
LOW
8,500
6
380
130
195
73%
1,900
227
31%
336,000
960
350
0.59
$3,200
10
$238
$95
$334
$3,500
$1,000
$4,500
LOW
15,000
8
650
110
195
73%
3,400
227
31%
592,000
960
617
0.87
$4,700
12
$286
$114
$401
$5,100
$1,500
$6,600
LOW
48,000
12
1400
100
195
73%
10,900
227
31%
1,896,000
960
1,975
1.88
$10,100
15
$358
$143
$501
$10,600
$3,100
$13,700
5.5.1.2 Fixed Engineering Costs
The fixed vessel costs associated with the use of switching to lower sulfur fuel are shown
in Table 5-26. These costs include research and development, and marine society approval; it is
assumed that there would not be any new retooling costs incurred. These costs, as applied to
U.S.-flagged vessels, are included in the total estimated cost of the coordinated strategy.
5-36
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Chapter 5: Engineering Cost Estimates
Table 5-26 Fixed Costs for Fuel Switching Hardware Costs on New Vessels
SPEED
Engine Power (kW)
Cylinders
Liters/cylinder
Engine Speed (rpm)
MEDIUM
4,500
9
35
650
Fixed Costs
R&D Costs (0.25 year
R&D)
Marine Society Approval
Engines/yr.
Years to recover
Fixed cost/engine
$172,000
$5,000
40
5
$880
MEDIUM
9,500
12
65
550
$172,000
$5,000
40
5
$880
MEDIUM
18,000
16
95
500
$172,000
$5,000
40
5
$880
LOW
8,500
6
380
130
$172,000
$5,000
40
5
$880
LOW
15,000
8
650
110
$172,000
$5,000
40
5
$880
LOW
48,000
12
1400
100
$172,000
$5,000
40
5
$880
5.5.1.3 Total Cost to New Vessels
Total vessel hardware cost estimates associated with the coordinated strategy were
developed from the number of new ships expected to require additional hardware to
accommodate the use of lower sulfur fuel (approximately one-third as discussed in Section
5.2.2.3). All new vessels were considered to have the average characteristics (including
propulsion power) shown in Table5-3. The variable and fixed cost estimates developed for the
six engine configurations shown above were used to develop $/kW equations that were applied
to the number of new ships, by ship and engine type, expected to require this additional
hardware. The total estimated hardware costs to new U.S.-flagged vessels are shown below in
Table5-27, these costs are included in the total cost associated with the coordinated strategy.
The total estimated hardware costs to foreign-flagged vessels are shown in Table 5-27, however,
these costs are only shown here for the sake of completeness and are not included in the total
cost estimate of the coordinated strategy.
5-37
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Regulatory Impact Analysis
Table 5-27 Total Estimated New Vessel Hardware Costs - U.S.-Flagged
TOTAL US FLAG
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
SSD
$0
$0
$0
$0
$0
$499,000
$518,000
$539,000
$560,000
$582,000
$605,000
$628,000
$653,000
$679,000
$706,000
$734,000
$764,000
$794,000
$826,000
$859,000
$894,000
$930,000
$968,000
$1,010,000
$1,050,000
$1 ,090,000
$1,140,000
$1,180,000
$1 ,230,000
$1 ,280,000
$1 ,330,000
$12,600,000
$6,610,000
MSD
$0
$0
$0
$0
$0
$38,100
$39,500
$41 ,000
$42,500
$44,100
$45,800
$47,500
$49,300
$51 ,200
$53,100
$55,200
$57,300
$59,500
$61 ,800
$64,200
$66,700
$69,300
$72,100
$74,900
$77,900
$81 ,000
$84,200
$87,600
$91,100
$94,800
$98,600
$946,000
$497,000
Gas Turbine
$0
$0
$0
$0
$0
$3,900
$4,100
$4,300
$4,500
$4,700
$4,900
$5,200
$5,400
$5,700
$5,900
$6,200
$6,500
$6,800
$7,200
$7,500
$7,900
$8,200
$8,600
$9,000
$9,500
$9,900
$10,400
$10,900
$1 1 ,400
$12,000
$12,600
$109,000
$56,000
Steam Turbine
$0
$0
$0
$0
$0
$125,000
$129,000
$133,000
$138,000
$143,000
$148,000
$153,000
$158,000
$163,000
$169,000
$175,000
$181,000
$187,000
$194,000
$200,000
$207,000
$215,000
$222,000
$230,000
$238,000
$246,000
$255,000
$264,000
$274,000
$283,000
$293,000
$2,960,000
$1,570,000
Total
$0
$0
$0
$0
$0
$666,000
$691 ,000
$717,000
$745,000
$774,000
$804,000
$834,000
$866,000
$899,000
$934,000
$970,000
$1,010,000
$1 ,050,000
$1 ,090,000
$1,130,000
$1,180,000
$1 ,220,000
$1 ,270,000
$1 ,320,000
$1 ,380,000
$1 ,430,000
$1 ,490,000
$1 ,540,000
$1,610,000
$1 ,670,000
$1 ,730,000
$16,600,000
$8,730,000
5-38
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Chapter 5: Engineering Cost Estimates
Table 5-28 Total Estimated New Vessel Hardware Costs - Foreign Flagged
TOTAL FOREIGN FLAG
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
SSD
$0
$0
$0
$0
$0
$16,500,000
$17,200,000
$17,800,000
$18,600,000
$19,300,000
$20,100,000
$20,900,000
$21 ,800,000
$22,700,000
$23,600,000
$24,600,000
$25,600,000
$26,600,000
$27,700,000
$28,900,000
$30,100,000
$31 ,300,000
$32,600,000
$34,000,000
$35,400,000
$36,900,000
$38,500,000
$40,100,000
$41 ,800,000
$43,500,000
$45,400,000
$424,000,000
$221,000,000
MSD
$0
$0
$0
$0
$0
$1 ,090,000
$1,140,000
$1,190,000
$1 ,240,000
$1,290,000
$1,350,000
$1,410,000
$1,470,000
$1,530,000
$1,600,000
$1,670,000
$1,740,000
$1,820,000
$1,890,000
$1,980,000
$2,060,000
$2,160,000
$2,250,000
$2,350,000
$2,450,000
$2,560,000
$2,670,000
$2,790,000
$2,920,000
$3,050,000
$3,180,000
$28,900,000
$15,000,000
Gas Turbine
$0
$0
$0
$0
$0
$127,000
$133,000
$140,000
$147,000
$154,000
$161,000
$169,000
$177,000
$186,000
$194,000
$204,000
$214,000
$224,000
$235,000
$246,000
$258,000
$271 ,000
$284,000
$298,000
$312,000
$327,000
$343,000
$360,000
$377,000
$395,000
$41 4,000
$3,590,000
$1,850,000
Steam Turbine
$0
$0
$0
$0
$0
$1,630,000
$1,690,000
$1,760,000
$1,830,000
$1,900,000
$1,970,000
$2,050,000
$2,130,000
$2,220,000
$2,310,000
$2,400,000
$2,490,000
$2,590,000
$2,700,000
$2,810,000
$2,920,000
$3,040,000
$3,160,000
$3,290,000
$3,420,000
$3,560,000
$3,710,000
$3,860,000
$4,010,000
$4,180,000
$4,350,000
$41 ,200,000
$21 ,600,000
Total
$0
$0
$0
$0
$0
$19,300,000
$20,200,000
$20,900,000
$21 ,800,000
$22,600,000
$23,600,000
$24,500,000
$25,600,000
$26,600,000
$27,700,000
$28,900,000
$30,000,000
$31 ,200,000
$32,500,000
$33,900,000
$35,300,000
$36,800,000
$38,300,000
$39,900,000
$41 ,600,000
$43,300,000
$45,200,000
$47,100,000
$49,100,000
$51,100,000
$53,300,000
$497,000,000
$260,000,000
5.5.2 Existing Vessels Hardware Costs
5.5.2.1 Existing Vessel Variable Costs
Existing vessels are required to meet the EGA lower sulfur fuel standards beginning in
2015. The existing vessel hardware costs associated with the coordinated strategy are those that
may be incurred if additional hardware is required to accommodate the use of lower sulfur.
Based on the methodology described above in Section 5.1.2.2, it is estimated that over two-thirds
of vessels would not require additional hardware. For the remaining vessels, the hardware
requirements would be similar to those discussed in Section 5.4.1, and would most likely include
5-39
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Regulatory Impact Analysis
additional distillate fuel storage tanks, an LFO fuel separator, an HFO/LFO blending unit, a 3-
way valve, an LFO cooler, filters, a viscosity meter, and various pumps and piping. This cost
analysis does not reflect other design options such as partitioning of a residual fuel tank to allow
for lower sulfur fuel capacity which would reduce the amount of additional space required, nor
does this analysis reflect the possibility that some ships may have already been designed to carry
smaller amounts of distillate fuel in separate tanks for purposes other than continuous propulsion.
Similar to the costs to new vessels, the existing vessel hardware cost analysis assumes
sufficient capacity for 250 hours of main and auxiliary engine operation, which may be an
overestimate of the amount of fuel necessary to call on U.S. ports. The variable costs associated
with existing vessels are shown in Table 5-29. Retrofitting a vessel is expected to require more
effort than making upgrades during new vessel construction, to address this, additional labor is
allocated for installing equipment to accommodate the use of lower sulfur fuel on existing ships.
The cost of the extra tanks is assumed to be the same as that for new vessels, shown in Table -24.
The costs were developed for each of the six different engine sizes and types used in this
analysis, and are shown plotted in Figure 5-7 from which a curve fit was developed to obtain an
equation for the $/kW cost of this technology that could be applied to other engine types and
sizes.
Table 5-29 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
Component Costs
Additional Tanks
LFO Separator
HFO/LFO Blending
Unit
3-Way Valve
LFO Cooler
Filters
Viscosity Meter
Piping/Pumps
Total Component
Cost
Assembly
Labor (hours)
Cost ($23.85/hr)
Overhead @ 40%
Total Assembly Cost
Total Variable Cost
Markup @ 29%
Total Hardware RPE
$3,400
$2,800
$4,200
$950
$2,400
$950
$1,400
$2,000
$18,100
480
$11,400
$4,600
$16,000
$34,100
$9,900
$44,000
$5,500
$3,300
$4,700
$1,400
$2,800
$950
$1,400
$2,000
$22,100
640
$15,300
$6,100
$21,400
$43,400
$12,600
$55,000
MEDIUM
18,000
16
95
500
$8,300
$3,800
$5,600
$1,900
$3,300
$950
$1,400
$2,000
$27,300
960
$22,900
$9,200
$32,100
$59,300
$17,200
$76,500
LOW
8,500
6
380
130
$4,600
$3,800
$4,700
$1,400
$2,800
$950
$1,400
$2,000
$21,600
640
$15,300
$6,100
$21,400
$43,000
$12,500
$55,500
LOW
15,000
8
650
110
$6,500
$4,200
$5,600
$1,900
$3,800
$950
$1,400
$2,000
$26,400
960
$22,900
$9,200
$32,100
$58,400
$17,000
$75,400
LOW
48,000
12
1400
100
$13,700
$4,700
$6,600
$2,800
$4,700
$950
$1,400
$2,000
$36,900
1200
$28,600
$11,400
$40,000
$77,000
$22,300
$99,300
5-40
-------
Chapter 5: Engineering Cost Estimates
Fuel Switching Hardware Costs - Existing Vessels
»Slow Speed Fuel Switching -New Vessels
• Medium Speed Fuel Switching -New Vessels
$120,000
$100,000 -
1,000 -
$60,000 -
$40,000 -
$20,000 -
y= 24,600Ln(x)-164,700
15,000, $75,400
8,500, $55,400,
r9,500, $56,000
4,500, $44,000 y= 2.409x +33,200
48,000, $99,300
10,000
20,000
(kW)
30,000
40,000
50,000
60,000
Figure 5-7 Variable Cost Curve Fit for Fuel Switching Vessels Costs to Existing Vessels
5.5.2.2 Fixed Engineering Costs
The fixed costs associated with the use of switching to lower sulfur fuel for existing
vessels are shown in Table 5-30, and are similar to the cost for new vessels; however, additional
research and development is provided to test systems on existing ships. The fixed costs are
applied to U.S.-flagged vessels and are included in the total estimated cost of the coordinated
strategy.
Table 5-30 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
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
MEDIUM
9,500
12
65
550
$227,040
$5,000
40
5
$1,160
MEDIUM
18,000
16
95
500
$227,040
$5,000
40
5
$1,160
LOW
8,500
6
380
130
$227,040
$5,000
40
5
$1,160
LOW
15,000
8
650
110
$227,040
$5,000
40
5
$1,160
LOW
48,000
12
1400
100
$227,040
$5,000
40
5
$1,160
5-41
-------
Regulatory Impact Analysis
5.5.2.3 Total Costs to Existing Vessels
The total estimated cost to existing vessels includes both variable and fixed costs.
Analysis of these costs to both U.S.-flagged and foreign-flagged vessels that affect U.S.
emissions was completed and while U.S.-flagged costs are included in the total estimated cost of
the coordinated strategy, foreign-flagged costs are presented only for the benefit of ship owners.
The fuel sulfur standards take effect in 2015, and for the purposes of simplification all vessels
were assumed to be modified by 2015 therefore all hardware costs were applied in 2015. The
cost to existing U.S.-flagged vessels is estimated to be $10.4 million in 2015. The cost to
foreign-flagged vessels in 2015 is estimated to be $317 million. Table 5-31 shows the estimated
costs to U.S- and foreign-flagged vessels through 2015 included all fixed and variable costs.
Table 5-31 Estimated Costs to Existing Vessels - U.S. and Foreign Flagged
TOTAL US FLAG
Year
2010
2011
2012
2013
2014
2015
Fixed
$155,700
$161,500
$167,600
$173,800
$180,300
$0
Variable
$0
$0
$0
$0
$0
$10,400,000
Total
$155,700
$161,500
$167,600
$173,800
$180,300
$10,400,000
TOTAL FOREIGN FLAG
Year
2010
2011
2012
2013
2014
2015
Fixed
$4,671,000
$4,855,000
$5,048,000
$5,249,000
$5,458,000
$0
Variable
$0
$0
$0
$0
$0
$316,900,000
Total
$4,671,000
$4,855,000
$5,048,000
$5,249,000
$5,458,000
$316,900,000
5.6 Operating Costs
5.6.1 Tier II Fuel Consumption Impacts
We estimate a two percent fuel consumption penalty associated with the engine
modifications made to comply with Tier II standards. The two percent fuel penalty estimate is
based on the use of modifications to the fuel delivery system to achieve Tier II NOx reductions,
and does not reflect the possibility that there may be other technologies available to
manufacturers that could offset this fuel penalty (see Chapter 4 for more details). Additionally,
Tier III will provide an opportunity to re-optimize engines for fuel economy when using
aftertreatment such as SCR to provide NOx reductions. To estimate the cost of this fuel penalty,
we applied the two percent to the total fuel consumed presented in the inventory (Chapter 3) and
the fuel prices described in Section 5.5.4. The engines must continue to meet Tier II standards
globally after 2015; therefore, this fuel penalty is projected even for Tier III engines. However,
for engines equipped with SCR, we assume that the fuel penalty will not be incurred when the
engine is operating in the EGA where Tier III standards apply because the use of SCR
5-42
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Chapter 5: Engineering Cost Estimates
aftertreatment affords the opportunity to advance the fuel injection timing for fuel efficiency
while using the exhaust aftertreatment technology to achieve Tier III NOx levels. These
operational costs were applied to both U.S.- and foreign-flagged vessel operations estimated in
the inventory analysis and are shown in Table 5-32 below, these costs are included in the total
estimated cost of the coordinated strategy.
Table 5-32 Operational Costs Associated with Tier II
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
U.S. FLAG
Residual
Fuel
(Tonnes)
0
516
2,519
4,873
7,184
2,127
2,604
3,055
3,706
4,307
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
26,400
21,800
Distillate
Fuel
(Tonnes)
0
14
63
118
174
7,172
8,302
7,890
7,971
7,897
12,035
12,454
12,905
12,739
12,578
12,779
12,564
12,264
11,918
12,100
12,173
12,802
13,980
14,711
14,967
15,412
15,844
16,128
16,367
17,026
17,320
193,000
103,000
FOREIGN FLAG
Residual
Fuel
(Tonnes)
0
3,361
16,596
31,985
47,257
3,709
4,591
5,468
6,692
7,862
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
113,000
97,100
Distillate
Fuel
(Tonnes)
0
107
515
983
1,449
57,335
66,590
63,265
64,206
63,702
70,273
71,154
72,466
67,999
63,722
62,561
58,117
53,759
48,529
47,729
45,646
47,703
54,026
56,740
55,524
55,390
55,446
52,665
51,713
52,845
52,368
944,000
549,000
TOTAL
Residual
Fuel
(Tonnes)
0
3,878
19,115
36,858
54,441
5,836
7,196
8,523
10,399
12,169
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
139,000
119,000
Distillate
Fuel
(Tonnes)
0
121
577
1,101
1,623
64,507
74,892
71,155
72,176
71,599
82,309
83,608
85,371
80,739
76,301
75,340
70,681
66,022
60,447
59,829
57,819
60,505
68,006
71 ,451
70,491
70,802
71 ,290
68,793
68,080
69,871
69,688
1,140,000
653,000
C02
Emissions
(Tonnes)
0
12,729
62,682
120,825
178,450
223,903
261 ,286
253,615
262,837
266,634
261,988
266,125
271,737
256,991
242,865
239,807
224,979
210,149
192,404
190,436
184,039
192,586
216,464
227,429
224,371
225,362
226,916
218,969
216,698
222,401
221,816
4,060,000
2,460,000
Distillate and
Residual Fuel
Costs3
$0
$1,306,556
$6,431 ,250
$13,249,217
$19,567,804
$32,201 ,585
$37,530,731
$36,240,842
$37,367,120
$37,708,847
$38,513,853
$39,121,913
$39,946,889
$37,779,189
$35,702,589
$35,253,126
$33,073,186
$30,893,155
$28,284,583
$27,995,257
$27,054,822
$28,311,283
$31,821,543
$33,433,355
$32,983,936
$33,129,589
$33,358,073
$32,189,713
$31 ,855,940
$32,694,254
$32,608,299
$580,000,000
$346,000,000
Note:
aThese fuel costs were estimated using $462/tonne of distillate through 2014, $468/tonne of distillate as of
2015, $322/tonne for residual through 2012, and $346/tonne for residual fuel as of 2013.
The impacts of this estimated increase in fuel consumption on U.S. energy security are
small. U.S. energy security is broadly defined as protecting the U.S. economy against
circumstances that threaten significant short- and long-term increases in energy costs. Most
5-43
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Regulatory Impact Analysis
discussion of U.S. energy security revolves around the topic of the economic costs of the U.S.
dependence on oil imports. The Tier 2 standards modestly increase consumption of petroleum in
ocean-going vessels. This increase in petroleum consumption increases both financial and
strategic risks associated with a potential disruption in supply or a spike in cost of oil. As a
result, the Tier 2 standards have a modest adverse impact on U.S. energy security. In the recent
RFS2 proposal, EPA estimated that the macroeconomic disruption component for energy
security at $4.74 per barrel or oil, or alternatively, $0.1 I/gallon. In the case of ocean-going
vessels, there is no energy security-related monopsony component since the oil consumed in the
vessels in purchased outside the U.S.
Table 5-32 above presents potential CC>2 increases associated with the estimated fuel
penalty for Tier II engines. If we consider that interim social costs of carbon have been
estimated at between $8/ton and $83/ton in 2020,M we can monetize the estimated CO2
disbenefit. For 2020, which is one of the years with the most significant impact, we estimate the
net effect to be a disbenefit in the range of 2-24 million dollars (2007$). Note that this is less
then one tenth of one percent of the total benefits associated with the coordinated strategy in
2020.
5.6.2 Tier III Urea Consumption
In addition to the SCR hardware costs discussed above in Section 5.2.4, ships built as of
2016 would also incur operating costs associated with SCR's use of urea. The urea costs are
based on a price of $1.52 per gallon with a density of 1.09 g/cc. The cost per gallon was derived
for a 32.5 percent urea solution delivered in bulk to the ship through research completed by ICF
combined with historical urea price information.8'9'10'11 This cost analysis uses a urea dosing rate
that is 7.5 percent of the BSFC to estimate how much urea would be used by different engine
types and sizes. These operational costs were applied to both U.S. and foreign-flagged vessels,
and are shown in Table 5-33 below. These costs are included in the total estimated cost of the
coordinated strategy.
M The social cost of carbon estimates are being used on an interim basis while analysis is conducted to generate new
estimates. For more detail about the interim estimates, see Environmental Protection Agency and Department of
Transportation, "Proposed Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and
Corporate Average Fuel Economy Standards; Proposed Rule," 74 FR 49454, Table III.H.6-3, p. 49617, September
28, 2009. Note that the table is in 2007 dollars while the benefits analyses in this rule are presented in 2006 dollars.
5-44
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Chapter 5: Engineering Cost Estimates
Table 5-33 Operation Costs Associated with the use of Urea with SCR for Tier 3 -U.S.- and Foreign-Flagged
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV @ 3%
NPV @ 7%
U.S. -FLAG
$0
$0
$0
$0
$0
$0
$934,000
$4,320,000
$8,220,000
$12,100,000
$15,800,000
$19,500,000
$22,700,000
$27,700,000
$32,300,000
$36,500,000
$40,800,000
$44,900,000
$49,500,000
$53,900,000
$58,500,000
$62,300,000
$66,000,000
$70,100,000
$74,900,000
$79,700,000
$85,100,000
$91 ,300,000
$97,100,000
$103,000,000
$109,000,000
$660,000,000
$299,000,000
FOREIGN-FLAG
$0
$0
$0
$0
$0
$0
$7,110,000
$34,500,000
$66,100,000
$97,500,000
$127,000,000
$157,000,000
$183,000,000
$225,000,000
$263,000,000
$297,000,000
$333,000,000
$367,000,000
$406,000,000
$441 ,000,000
$480,000,000
$512,000,000
$543,000,000
$577,000,000
$618,000,000
$658,000,000
$702,000,000
$753,000,000
$801 ,000,000
$847,000,000
$896,000,000
$5,410,000,000
$2,450,000,000
TOTAL
$0
$0
$0
$0
$0
$0
$8,040,000
$38,800,000
$74,300,000
$110,000,000
$143,000,000
$177,000,000
$206,000,000
$253,000,000
$295,000,000
$334,000,000
$374,000,000
$412,000,000
$456,000,000
$495,000,000
$539,000,000
$574,000,000
$609,000,000
$647,000,000
$693,000,000
$738,000,000
$787,000,000
$844,000,000
$898,000,000
$950,000,000
$1,010,000,000
$6,070,000,000
$2,750,000,000
5.6.3 Operation on Lower-Sulfur Fuel
The increased operating costs associated with the use of lower sulfur fuel, as discussed in
Section 5.5.4, were applied to the fuel consumption values presented in the inventory. The costs
in 2014 and 2015 represent operation on 1.0 percent sulfur residual fuel in regulated U.S.
waterways. Costs for 2015 and later represent operation on 0.1 percent sulfur distillate fuel in
regulated U.S. waterways. These costs were applied to both U.S.- and foreign-flagged vessels
and are presented in the Table 5-34 below, and are included in the total estimated cost of the
coordinated strategy.
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Regulatory Impact Analysis
Table 5-34 Operational Costs Associated with the use of Lower Sulfur Fuel (in Sthousands)
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
US FLAG
$0
$0
$0
$30,700
$31 ,800
$176,000
$180,000
$190,000
$200,000
$200,000
$210,000
$220,000
$230,000
$240,000
$250,000
$260,000
$270,000
$280,000
$290,000
$300,000
$310,000
$330,000
$340,000
$350,000
$370,000
$380,000
$400,000
$420,000
$440,000
$450,000
$470,000
$4,500,000
$2,370,000
FOREIGN FLAG
$0
$0
$0
$201 ,000
$209,000
$1,160,000
$1,210,000
$1 ,260,000
$1,310,000
$1 ,370,000
$1 ,430,000
$1 ,490,000
$1 ,550,000
$1 ,620,000
$1 ,690,000
$1 ,760,000
$1 ,840,000
$1 ,920,000
$2,000,000
$2,090,000
$2,180,000
$2,280,000
$2,380,000
$2,480,000
$2,600,000
$2,710,000
$2,830,000
$2,960,000
$3,100,000
$3,240,000
$3,390,000
$31 ,000,000
$16,300,000
TOTAL
$0
$0
$0
$232,000
$241 ,000
$1 ,340,000
$1 ,390,000
$1 ,450,000
$1,510,000
$1,570,000
$1,640,000
$1,710,000
$1,780,000
$1,860,000
$1,940,000
$2,020,000
$2,110,000
$2,200,000
$2,290,000
$2,390,000
$2,500,000
$2,600,000
$2,720,000
$2,840,000
$2,960,000
$3,100,000
$3,240,000
$3,380,000
$3,540,000
$3,700,000
$3,870,000
$35,500,000
$18,600,000
5.6.4 Projected Fuel Costs
This section presents our analysis of the impact of the proposed EGA on marine fuel
costs. Distillate fuel will likely be used to meet the 1,000 ppm fuel sulfur limit, beginning in
2015. As such, the primary cost of the fuel sulfur limit for ship owners will be that associated
with switching from heavy fuel oil to higher-cost distillate fuel. Some engines already operate
on distillate fuel and would not be affected by fuel switching costs. On the other hand, distillate
fuel costs may be affected by the need to further refine the distillate fuel to meet the 1,000 ppm S
limit. To investigate these effects, studies were performed on the impact of a North American
EGA on global fuel production and costs. These studies, which are summarized below, include
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Chapter 5: Engineering Cost Estimates
economic modeling to project bunker fuel demand and refinery modeling to assess the impact of
a North American EGA on fuel costs. Detailed documentation of these studies may be found in
the docket.
5.6.4.1 Bunker Fuel Demand Modeling
To assess the affect of an EGA on the refining industry, we needed to first understand and
characterize the fuels market and more specifically the demand for the affected marine fuels both
currently and in the future. Research Triangle Institute (RTI) was contracted to conduct a fuels
study using an activity-based economic approach.12 The RTI study established baseline bunker
fuel demand, projected a growth rate for bunker fuel demand, and established future bunker fuel
demand volumes. The basis for this work was the Global Insights economic model which
projects international trade for different categories of commodities. Demand for marine fuels
was derived from the demand of transportation of various types of cargoes by ship, which, in
turn, was derived from the demand for commodities produced in one region of the world and
consumed in another. The flow of commodities was matched with typical vessels for that trade
(characterized according to size, engine power, age, specific fuel consumption, and engine load
factors). Typical voyage parameters were assigned, including average ship speed, round trip
mileage, tons of cargo shipped, and days in port. Fuel consumption for each trade route and
commodity type was thus a function of commodity projections, ship characteristics, and voyage
characteristics.
The bunker demand model included operation off the coasts of the contiguous United
States and southeastern Alaska. The bunker demand volumes for this modeling in the Canadian
portion of the North American EGA was based on fuel consumed by ships en route to and from
Canadian ports based on estimates from Environment Canada.
The affected fuel volumes used in the WORLD model are slightly higher than what we
now estimate for the proposed EGA. This difference is because the RTI evaluation of affected
fuel volumes was performed before the EGA was defined and was performed independently of
the emission inventory modeling described in Chapter 3. However, we believe it is reasonable to
use the fuel cost increases, on a per-tonne basis, from the WORLD modeling to estimate the
impact of the proposed EGA. In earlier work,13 EnSys modeled a number of fuel control
scenarios where the volume of affected fuel was adjusted to represent (1) different EGAs or (2)
various penetration scenarios of exhaust gas scrubbers (as an alternative to fuel switching). This
work suggests that the differences in fuel volume between these scenarios have only a small
effect on fuel cost. Although this earlier work was based on the older crude oil and refinery
costs used in the expert group study, it is sufficient for observing the sensitivity of fuel cost
increases to small changes (on a global scale) in affected fuel volume. In addition, the larger
affected fuel volume, used in the WORLD modeling, direct!onally increases the projected fuel
cost increases, and therefore allows for a conservative analysis.
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Regulatory Impact Analysis
5.6.4.2 Bunker Fuel Cost Modeling
5.6.4.2.1 Methodology
To assess the impacts of the proposed EGA on fuel costs, the World Oil Refining
Logistics and Demand (WORLD) model was run by Ensys Energy & Systems, the owner and
developer of the refinery model. The WORLD model is the only such model currently
developed for this purpose, and was developed by a team of international petroleum consultants.
It has been widely used by industries, government agencies, and OPEC over the past 13 years,
including the 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.14 The
model incorporates crude sources, global regions, refinery operations, and world economics.
The results of the WORLD model have been shown to be comparable to other independent
predictions of global fuel, air pollutant emissions and economic predictions.
WORLD is a comprehensive, bottom-up model of the global oil downstream that
includes crude and noncrude supplies; refining operations and investments; crude, products, and
intermediates trading and transport; and product blending/quality and demand. Its detailed
simulations are capable of estimating how the global system can be expected to operate under a
wide range of different circumstances, generating model outputs such as price effects and
projections of refinery operations and investments.
5.6.4.2.2 Assessment of the Impact of Marine Fuel Standards
During the development of the amendments to MARPOL Annex VI, a Cross
Government/Industry Scientific Group of Experts was established, by IMO, to evaluate the
effects of the different fuel options that were under consideration at the time. This expert group
engaged the services of EnSys to assess the impact of these fuel options using the WORLD
model. The final report from this study presents great detail on the capabilities of the WORLD
model and provides support for why the WORLD model was chosen as the appropriate tool for
modeling the economic impacts of the different fuel options.15 The following description of the
WORLD model is taken from the expert group study:
WORLD is a linear programming model that simulates the activities and economics of
the world regional petroleum industry against short, medium or long term horizons. It models
and captures the interactions between:
• crude supply;
• non-crudes supply: Natural gas Liquids (NGLs), merchant MTBE, biofuels,
petrochemical returns, Gas To Liquid fuels (GTLs), Coal to Liquid fuels (CTLs);
• refining operations;
• refining investment;
• transportation of crudes, products and intermediates;
• product blending/quality;
• product demand; and
• market economics and pricing.
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Chapter 5: Engineering Cost Estimates
The model includes a database representing over 180 world crude oils and holds detailed,
tested, state-of-the-art representation of fifty-plus refinery processes. These representations
include energy requirements based on today's construction standards for new refinery units. It
allows for advanced representation of processes for reformulated, ultra-lower sulfur/aromatics
fuels and was extended for detailed modeling of marine fuels for the aforementioned EPA and
API studies. The model contains detailed representations of the blending and key quality
specifications for over 50 different products spread across the product spectrum and including
multiple grades of gasolines, diesel fuels/gasoils (marine and non-marine) and residual fuels
(marine and non-marine).
The refining industry is a co-product industry. This means that changes in production of
one product also affect production volume and/or production costs of other products. As
necessary, the model will adjust refinery throughputs and operations, crude and product trade
patterns to ensure that a specified product demand slate is met, without surplus or deficit of any
product.
To evaluate the impact of changes to marine fuels specifications as a result of any of the
options under consideration, the model is run with a future demand scenario for all products. The
first run, the base case, assumes marine fuels in line the current Annex VI regulation. The second
run is done with marine fuel specifications in line with the option under consideration. Both runs
are optimized independently. Since the only thing that is altered between the cases is the change
in the projected marine fuels regulation, the difference between both cases is therefore a true
assessment of the actual cost and other implications of the change to the marine fuels
requirements under consideration. Thus, the incremental refining investment costs, incremental
marine fuel costs and incremental refinery/net CCh emissions are all directly attributable to, and
must be allocated to, the change in regulation.
Prior to the expert group study, EnSys made updates to the WORLD model to be able to
perform the analysis of the impacts of different marine fuel options. As part of this effort, the
refinery data, capacity additions, technology assumptions, and costs were reviewed. EnSys
reviewed relevant regulations to ensure that the WORLD model was correctly positioned to
undertake future analyses of marine fuels EGAs. In developing these updates, a number of
issues had to be considered:
• the costs of refining, including the capital expenditures required to reduce bunker fuel
sulfur content and the potential for process technology improvements;
• likely market reactions to increased bunker fuel costs, such as fuel grade availability,
impacts on the overall transportation fuels balance, and competition with land-based
diesel and residual fuels for feedstocks that can upgrade fuels;
• the effects of emissions trading; and
• the potential for low- and high-sulfur grade bunker sources and consumption to
partially shift location depending on supply volume, potential, and economics.
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Regulatory Impact Analysis
The analytical system thus had to be set up to allow for alternative compliance scenarios,
particularly with regard to (a) adequately differentiating bunker fuel grades; (b) allowing for
differing degrees to which the EGA or other standards in a region were presumed to be met by
bunker fuel sulfur reductions, rather than by other means such as scrubbing or emissions trading;
and (c) allowing for all residual fuel bunker demand to be reallocated to marine diesel. Beyond
any international specifications, the analytical system needed to be able to accommodate future
consideration of regional, national, and local specifications.
The primary approach taken to manage these issues was to
• expand the number of bunker grades in the model to three distillates and four residual
grades,N
• allow for variation where necessary in (regional) sulfur standards on specific bunker
grades, and
• enable residual bunker demand to be switched to marine diesel.
Other updates to the WORLD model included product transportation matrices covering
tanker, interregional pipeline, and minor modes were expanded to embody the additional
distillate and residual bunker grades, adjustments to the yield patterns of the residuum
desulfurization, and blocking of paraffin!c streams from residual fuel blends. The details of
compliance in any particular region must be estimated external to the main WORLD model. As
discussed above, we provided our estimates of affected fuel volumes to Ensys.
5.6.4.2.3 Updates for EC A A nalysis
To determine the impact of a North American EGA, the WORLD model was employed
using the same basic approach as for the IMO expert group study. Modeling was performed for
2020 in which the control case included a fuel sulfur level of 1,000 ppm in the U.S. and
Canadian EEZs.16 The baseline case was modeled as "business as usual" in which ships continue
to use the same fuel as today. This approach was used for two primary reasons. First, significant
emission benefits are expected in an EGA, beginning in 2015, due to the use of 1,000 ppm S fuel.
These benefits, and costs, would be much higher in the early years of the program before the
5,000 ppm S global standard goes into effect. By modeling this scenario, we are able to observe
the impact of the proposed EGA in these early years. Second, there is no guarantee that the
global 5,000 ppm S fuel sulfur standards will begin in 2020. The global standard may be
delayed until 2025, subject to a fuel availability review in 2018. In addition, the 35,000 ppm S
global standard, which begins in 2012, is higher than the current residual fuel sulfur average of
27,000 ppm S.
N Specifically, the following seven grades were implemented: MGO, plus distinct high- and low-sulfur blends for
MDO and the main residual bunker grades IFO 180 and IFO 380. The latest international specifications applying to
these fuels were used, as were tighter sulfur standards for the low-sulfur grades applicable in SECAs.
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Chapter 5: Engineering Cost Estimates
In the modeling for the expert group study, crude oil prices were based on projections
released by the U.S. Energy Information Administration (EIA) in 2006.17 Since that time, oil
prices have fluctuated greatly. Using new information, EIA has updated its projections of oil
price for 2020.18'19 In response to this real-world effect, the EGA modeling was conducted using
the updated oil price estimates. Specifically, we used a crude oil price of $51.55 for the reference
case, and $88.14/bbl for the high price case, both expressed in real (2006) dollars. These crude
oil prices were input to the WORLD model which then computed residual and distillate marine
oil prices for 2020. The net refinery capital impacts are imputed based on the differences in the
costs to the refining industry that occur between the Base Cases and EGA cases in 2020. The
incremental global refining investment over the Base Case is projected to cost an additional
$3.83 billion, with $1.48 billion being used for debottlenecking projects and $1.96 billion used
for new units. For the high priced crude case, the incremental capital investments for an EGA
is $3.44 billion over the base case, with new units accounting for $2.49 billion while
debottlenecking costs are $0.72 billion. For both of the crude oil price cases, refinery
investments represent a marginal increase of about 2% over the corresponding total base case
investments required in 2020. Additionally, the majority of these EGA investments occur in the
U.S./Canada refining regions, though smaller amounts also occur in other world regions. In
addition to increased oil price estimates, the updated model accounts for increases in natural gas
costs, capital costs for refinery upgrades, and product distribution costs.
5.6.4.3 Results of Fuel Cost Study
5.6.4.3.1 Incremental Refinery Capital Investments Associated with Desulfurlzatlon
The primary refining cost of desulfurization is associated with converting IFO bunker oil
into a distillate fuel with a DMA specification. The other significant refining costs are those
related to desulfurizing distillate stocks. The bulk of the refinery investments occur in regions
located outside of the U.S. and Canada, because capital investments in these regions are
approximately 9 and 23 percent of the overall capital for the reference and high priced crude
cases, respectively. Table 5-35 summarizes the overall capital investments made for both
conversion of IFO bunker oil into distillate as well as desulfurization in refineries in the various
U.S. regions (East Coast, West Coast and Gulf Coast) and overseas. These cost estimates are
based on the WORLD modeling results.
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Regulatory Impact Analysis
Table 5-35 Incremental Refinery Capital Investment Made in 2020 (2006 dollars)
USEC
USGCCE
USWCCW
Refinery
Investments Total
USA+Canada
Refinery
Investments Total
Other Regions
Total World
REFINERY INVESTMENTS ($ BILLION)
Base
Case
$52/bbl
Crude
1.4
14.5
1.4
17.3
85.2
102.5
NAECA
$52/bbl
Crude
1.2
14.8
1.6
17.6
88.1
105.7
Delta
-0.2
0.3
0.2
0.3
2.9
3.2
Base Case
$88/bbl
Crude
1.0
26.2
1.4
28.6
110.5
139.1
NAECA
$88/bbl
Crude
0.9
27.3
1.5
29.8
115.0
144.8
Delta
-0.1
1.2
0.2
1.3
4.4
5.7
Type of Modification
Debottleneck
Major New Units
Total World
0.7
97.8
102.5
0.7
100.8
105.7
0.0
3.0
3.2
1.4
132.1
139.1
1.4
138.0
144.8
0.0
6.0
5.7
Notes:
USEC is United States East Coast, USGCCE is United States Gulf Coast and Eastern Canada,
USWCCW is United States West Coast and Western Canada, $Bn is Billion U.S. Dollars. The
results presented are investments made in 2020 to add new refinery processing capacity to what
exists in the 2008 base case plus known projects.
Refinery investments in North America, Greater Caribbean and South American regions
account for greater than half of all investments for the reference case, while investments made in
China and Middle Eastern Gulf regions account for close to 40 percent of remaining investments.
This accounts for greater than 90 percent of investments for the reference case. For the high
price case, investments in the U.S., Canada, Greater Caribbean and South American refiner
regions again account for greater than half of all investments made, while European north and
China regions account for greater than 44 percent of the remaining investments. Table 5-36
summarizes overall incremental investments made in all world refining regions for the reference
and high price case.
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Chapter 5: Engineering Cost Estimates
Table 5-36 World Region Refining Investments for ECA Made in 2020
USEC
USGICE
USWCCW
GrtCAR
SthAM
AfWest
AfN-EM
Af-E-S
EUR-No
EUR-So
EUR-Ea
CaspRg
RusFSU
MEGulf
Paclnd
PacHi
China
RoAsia
Total
REFERENCE CASE
Capital, $
Billion
-0.167
0.277
0.176
0.253
0.810
0.004
0.143
0.007
0.011
-0.006
0.021
0.157
0.185
0.754
-0.115
0.177
0.490
0.018
3.20
% of Capital
-5.2%
8.7%
5.5%
7.9%
25.4%
0.1%
4.5%
0.2%
0.4%
-0.2%
0.7%
4.9%
5.8%
23.6%
-3.6%
5.5%
15.3%
0.6%
100.0%
HIGH PRICED CASE
Capital, $ Billion
-0.095
1.159
0.224
0.828
0.870
0.002
-0.006
0.006
1.239
-0.035
-0.014
-0.001
0.036
0.119
0.069
0.000
1.305
-0.002
5.70
% of Capital
-1.7%
20.3%
3.9%
14.5%
15.3%
0.0%
-0.1%
0.1%
21.7%
-0.6%
-0.2%
0.0%
0.6%
2.1%
1.2%
0.0%
22.9%
0.0%
100.0%
Notes:
USEC = US East Coast, USGICE= US Gulf Coast, Interior & Canada East, USWCCW= US West
Coast & Canada West, GrtCAR= Greater Caribbean, SthAM= South America, AfWest=African
West, AFN- EM= North Africa/Eastern Mediterranean, AF-E-S=Africa East and South, Eur-
No=Europe North, EUR-So= Europe South, EUR-EA= Europe East, CaspRg= Caspian Region,
RusFSU= Russia & Other Former Soviet Union, MEGulf= Middle East Gulf, Pac Ind= Pacific
Industrialized, PacHi= Pacific High Growth / Industrializing, RoAsia= Rest of Asia
5.6.4.3.2 Capacity and Throughput Changes for the Reference Case
The WORLD model used a total of 140 thousand barrels per stream day (KBPSD) of
coking capacity to convert residual stocks to distillates. Of this amount, 110 KBPSD is existing
spare or "slack" capacity available in U.S. and Canada refiner regions. This capacity is available
based on projections that refiners add excess coking capacity in the base case. The remaining
balance of coking capacity, or 30 KBPSD, is new capacity added to refiner regions outside of
United States and Canada, equivalent to one additional coker. In addition to utilizing more
coking capacity, the WORLD model also increased residual hydrocracking capacity by 50
KBPSD to convert residual stocks into distillates. These one to two additional hydrocrackers
were added to refiner regions located outside of United States and Canada. Overall, considering
the use of cokers and residual hydrocrackers, the total refiner process capacity is 190 KBPSD for
residual stocks processing, mirroring the amount needed to process the residual volumes
contained in IFO180 and IFO 380 bunker grades. To remove any gas oils in residual blendstocks
5-53
-------
Regulatory Impact Analysis
such as atmospheric and vacuum tower residuals, the model utilized 60 KBPSD of existing
vacuum tower capacity, 50 KBPSD in U.S. and Canada and 10 KBPSD in other refiner regions.
Crude throughput is increased by 54 KBPSD, primarily to account for increased energy
usage in refinery processes such as hydro crackers and hydrotreaters. Crude throughput is also
increased to offset liquid volume loss from residual stocks that are converted to petroleum coke
in coking units. Table 5-37 summarizes overall crude and non crude throughputs for the base
and EGA cases.
Table 5-37 Refiner Crude and Non Crude Throughputs
Grade Throughput
Non Grade Supply
NGL ETHANE
NGLs C3+
PETCHEM RETURNS
BIOMASS
METHANOL (EXNGS)
GTL LIQUIDS (EXNGS)
CTL LIQUIDS (EX COAL)
HYDROGEN (EXNGS)
Total Non Grade Supply
TOTAL Supply
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
MMBPD
REFERENCE
BASE CASE
86.7
1.7
6.3
1.0
1.5
0.1
0.3
0.5
1.0
12.3
99.3
REFERENCE
ECA
CASE
86.7
1.7
6.3
1.0
1.5
0.1
0.3
0.5
1.0
12.3
99.4
DELTA
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
HIGH
BASE
CASE
75.6
1.7
6.1
0.8
3.0
0.1
0.6
0.8
0.8
14.0
90.2
HIGH
ECA
CASE
75.6
1.7
6.1
0.8
3.0
0.1
0.6
0.8
0.9
14.0
90.3
DELTA
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
The model added 70 KBPSD of new ultra lower sulfur gas oil hydrocracking capacity in
refiner regions outside of the U.S. and Canada. The distillate produced from these units has a sulfur
content low enough to meet ECA standards and therefore does not require further processing in
hydrotreaters. The model also reduced throughput by 40 KBPSD in existing base case capacity for
Conventional Gas Oil Hydrocrackers located in U.S. and Canada refiner regions.
The model added 160 KBPSD of new conventional distillate hydrotreating capacity, 140
KBPSD to U.S. and Canada refiner regions and 20 KBPSD in refining regions in other areas of the
world. In addition to new units, the model used 150 KBPSD of "slack" distillate conventional
hydrotreating capacity, 90 KBPSD of this located in U.S. and Canada and 60 KBPSD in other world
refiner regions. Considering this, the total net use of conventional distillate hydrotreating for the
reference case is 310 KBPSD above the base case, mirroring incremental demand of lower sulfur
distillate for ECA. The model used 70 KBPSD of slack capacity for vacuum gas oil/residual
hydrotreating in addition to distillate hydrotreating. Of this amount, 40 KBPSD is in U.S. and
Canada and 30 KBPSD in other world refiner regions.
The increased hydrotreating and hydrocracking capacity requires new hydrogen and sulfur
plant capacity and was added to refiner regions that use more distillate hydrotreating and
5-54
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Chapter 5: Engineering Cost Estimates
hydrocracking. Other minor refinery process modifications were required by the model in 2020,
although these were not substantial (see Table 5-38).
Table 5-38 Refinery Secondary Processing Capacity Additions in 2020 Reference Case (Million barrels per
stream day)
Total Additions
Over Base
Total Crude
Capacity Used
2020
Vacuum
Distillation
Coking
Catalytic
Cracking
Hydro-Cracking
(TOTAL)
- Gasoil
Conventional
- Gasoil ULS
- Resid LS
- Resid MS
Catalytic
Reforming with
Revamp
Hydrotreating
(Total)
- Gasoline - ULS
Distillate
-New Conv/LS
- VGO/Resid
Hydrogen,
(MMSCFD)
Sulfur Plant,
(TPD)
USE OF BASE CAPACITY
US/CAN
0.00
0.02
0.05
0.11
(0.07)
(0.04)
(0.04)
0.00
0.00
0.00
0.01
0.13
0.00
0.09
0.04
0
500
Rest of
World
0.05
0.04
0.01
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.08
(0.00)
0.06
0.03
70
500
Total
0.05
0.05
0.06
0.12
(0.06)
(0.04)
(0.04)
0.00
0.00
0.00
0.02
0.21
(0.00)
0.15
0.06
70
1000
NEW CAPACITY
US/CAN
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
(0.03)
0.14
0.00
8
10
Rest of
World
0.05
0.04
(0.02)
0.02
(0.01)
0.12
0.00
0.07
0.01
0.04
0.07
0.05
0.03
0.02
0.00
211
130
Total
0.05
0.05
(0.02)
0.02
(0.01)
0.12
0.00
0.07
0.01
0.04
0.07
0.17
(0.00)
0.16
0.00
218
140
BASE PLUS NEW CAPACITY
US/CAN
0.00
0.017
0.05
0.11
(0.07)
(0.04)
(0.04)
0.00
0.00
0.00
0.01
0.24
(0.03)
0.23
0.04
8
510
Rest of
World
0.05
0.037
(0.01)
0.03
0.00
0.12
0.00
0.07
0.01
0.04
0.07
0.14
0.02
0.08
0.03
280
630
Total
0.05
0.054
0.04
0.14
(0.07)
0.08
(0.04)
0.07
0.01
0.04
0.08
0.37
(0.01)
0.31
0.07
288
1140
While coking and hydrocracking (residual and gas oil) processes primarily produce
distillates, to a lesser extent, some low octane gasoline blendstocks are also manufactured, requiring
refiners to install additional catalytic reforming unit capacity. As such, in the U.S. and Canada
regions approximately 10 KPBSD of existing spare CCR capacity is used while approximately 70
BPSD of new CCR capacity is added to other WORLD refiner regions that added cokers and
hydrocrackers.
5.6.4.3.3 Capacity and Throughput Changes for the High Price Crude Oil Case
For the high priced case, the high cost of crude and high capital costs for processing units
push the model to reduce installation of new processing units. The price of natural gas is also
reduced relative to the price of crude which induces the model to use more natural gas and
reduce the use of crude. Under these conditions, the model uses less crude, more natural gas and
installs less capital for refinery processing units. As a result, the model favors the use of more
5-55
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Regulatory Impact Analysis
hydrocracking processing which adds hydrogen (made from natural gas) to residual and gas oils,
producing lower sulfur distillates stocks that do not require further processing in hydrotreaters.
The model also uses more synthetic crudes and less heavy sour crudes, which reduce the
amounts of residual stocks that need upgrading.
Crude throughput is increased by 29 KBPSD, which is less than the reference case, as the
model preferentially uses natural gas over crude and reduces the use of cokers and hydrotreating.
Table 5-39 shows crude and non crude inputs for the high priced case.
The WORLD model used a total of 80 KBPSD of "slack" coking capacity to convert residual
stocks to distillates. Of this amount, 70 KBPSD was used in the U.S. and Canada regions and 10
KBPSD in regions in other areas of the world. The model also added 80 KBPSD of new low and
medium sulfur residual hydrocracking capacity to convert residual stocks into distillates—20 KBPSD
in the U.S. and Canada and 60 KBPSD in other world refiner regions. Overall, considering the use
of cokers and residual hydrocrackers, the total refiner process capacity for residual stocks processing
for use in the EGA is 160 KBPSD for the high priced case.
To extract gas oils from residual blendstocks, the model utilized 90 KBPSD of existing
vacuum tower capacity—80 KBPSD in the U.S. and Canada and 10 KBPSD on other refiner regions.
In addition, the model added 120 KBPSD of new ultra lower sulfur gas oil hydrocracking capacity in
refiner regions outside of the U.S. and Canada. The distillate fuel produced from these units meet
EGA sulfur standards. The model also used 30 KBPSD of slack capacity in the U.S. and Canada
refiner regions for hydrocracking of conventional gas oil.
The model added 40 KBPSD of new conventional distillate hydrotreating capacity to the U.S.
and Canada refiner regions and 20 KBPSD of new capacity to refining regions in other areas of the
world. While the model also used 40 KBPSD of "slack" conventional distillate hydrotreating
capacity in the U.S. and Canada, other world refiner regions decreased use of base case or slack
capacity by 80 KBPSD. Considering the use of the new and slack capacity, a total net use of
capacity is 20 KBPSD of conventional distillate hydrotreating capacity. The model also used 60
KBPSD of existing slack capacity for vacuum gas oil/residual distillate hydrotreaters, with 20
KBPSD used in the U.S. and Canada refiner regions and 40 KBPSD in other world refining regions.
The use of additional hydrocracking and hydrotreater capacity requires installation of new
hydrogen plant capacity. New sulfur plant capacity is required in refiner regions to process the
offgas produced from incremental use of hydro cracking and hydrotreating (see Table 5-39 below).
5-56
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Chapter 5: Engineering Cost Estimates
Table 5-39 Refinery Secondary Processing Capacity Additions in 2020 High Priced Case (Million barrels per
stream day)
Total Additions
Over Base Case
Total Crude
Capacity Used in
2020
Vacuum Distillation
Coking
Catalytic Cracking
Hydro-Cracking
(Total)
- Gasoil
Conventional
- Gasoil ULS
- Resid LS
- Resid MS
Catalytic Reforming
with Revamp
Hydro treating
(Total)
- Gasoline - ULS
Distillate
-New Conv/LS
- VGO/Resid
Hydrogen,
(MMSCFD)
Sulfur Plant, (TPD)
USE OF BASE CAPACITY
US/CAN
0.00
0.05
0.08
0.07
(0.03)
0.03
0.03
0.00
0.00
0.00
0.00
0.06
0.00
0.04
0.02
0
580
Rest of
World
(0.05)
(0.02)
0.10
0.01
(0.05)
0.00
0.00
0.00
0.00
0.00
0.02
(0.04)
0.00
(0.08)
0.03
0
300
Total
(0.05)
0.03
0.18
0.08
(0.09)
0.03
0.03
0.00
0.00
0.00
0.02
0.02
0.00
(0.03)
0.05
0
880
NEW CAPACITY
US/CAN
0.00
0.05
0.00
0.00
0.00
0.02
0.00
0.00
0.02
0.00
(0.05)
0.04
0.00
0.04
0.00
243
0
Rest of
World
(0.05)
(0.02)
0.00
(0.00)
0.00
0.18
0.00
0.12
0.03
0.03
0.02
0.02
(0.01)
0.02
0.00
325
120
Total
(0.05)
0.03
0.00
(0.00)
0.00
0.20
0.00
0.12
0.05
0.03
(0.03)
0.06
(0.01)
0.06
0.00
568
120
BASE PLUS NEW CAPACITY
US/CAN
0.00
0.054
0.08
0.07
(0.03)
0.05
0.03
0.00
0.02
0.00
(0.05)
0.11
0.00
0.08
0.02
243
580
Rest of
World
(0.05)
(0.024)
0.10
0.00
(0.05)
0.18
0.00
0.12
0.03
0.03
0.04
(0.03)
(0.01)
(0.06)
0.04
325
420
Total
(0.05)
0.029
0.18
0.08
(0.09)
0.22
0.03
0.12
0.05
0.03
(0.00)
0.08
(0.01)
0.02
0.06
568
1000
5.6.4.3.4 Overall Increases Due to Fuel Switching and Desulfurization
Global fuel use in 2020 by international shipping is projected to be 500 million metric
tonnes per year (tonnes/yr). The main energy content effects of bunker grade shifts were
captured in the WORLD modeling by altering the volume demand and, at the same time,
consistency was maintained between the bunker demand figures in tonnes and in barrels. The
result was that partial or total conversion of IFO to distillate was projected to lead to a reduction
in the total global tonnes of bunker fuel required but also led to a projected increase in the barrels
required. These effects are evident in the WORLD case results. Because only a small portion of
global marine fuel is consumed in the EGA, the overall impact on global fuel production is small.
Global fuel use in 2020 by ships is projected to be 500 million metric tonnes/yr. Of this amount,
90 million metric tonnes of fuel is used for U.S./Canadian trade, or about 18 percent of total
global fuel use. In the proposed EGA, less than 20 million metric tonnes of fuel will be
consumed in 2020, which is less than 4 percent of total global marine fuel use. Of the amount of
fuel to be consumed in the proposed EGA in 2020, about 4 million metric tonnes of distillate will
be consumed in the Business as Usual (BAU) case, which is about 20 percent of the amount of
5-57
-------
Regulatory Impact Analysis
total fuel to be consumed in the proposed ECA.° As would be expected, since the shift in fuel
volumes on a world scale is relatively small, the WORLD model predicts the overall global
impact of an EGA to also be small.
There are two main components to projected increased marine fuel cost associated with
an EGA. The first component results from the shifting of operation on residual fuel to operation
on higher cost distillate fuel. This is the dominant cost component. The WORLD model
computed costs based on a split between the costs of residual and distillate fuels. However, there
is a small cost associated with desulfurizing the distillate to meet the 1,000 ppm S standard.
Based on the WORLD modeling, the average increase in costs associated with switching from
marine residual to distillate will be $145 per tonne.p This is the cost increase that will be borne
by the shipping companies purchasing the fuel. Of this amount, $6 per tonne is the cost increase
associated with distillate desulfurization. In other words, we estimate a cost increase of $6/tonne
for distillate fuel used in an EGA.
The above cost estimates are based on EIA's "reference case" projections for crude oil
price in 2020. We also performed a sensitivity analysis using EIA's "high price" scenario.
Under this scenario, the increase in fuel costs for switching from residual to distillate fuel is $237
per tonne. The associated increase in distillate fuel cost is $7 per tonne.
Table 5-40 summarizes the reference and high price fuel cost estimates with and without
an EGA. In the baseline case, fuel volumes for operation are 18% marine gas oil (MGO), 7%
marine diesel oil (MDO), and 75% IFO. In the EGA, all fuel volumes are modeled as MGO.
Table 5-40 Estimated Marine Fuel Costs
FUEL
MGO
MDO
IFO
UNITS
$/bbl
$/tonne
$/bbl
$/tonne
$/bbl
$/tonne
REFERENCE CASE
Baseline
$ 61.75
$ 464
$ 61.89
$ 458
$ 49.87
$ 322
ECA
$ 62.23
$ 468
$ 62.95
$ 466
$ 49.63
$ 321
HIGH PRICE CASE
Baseline
$ 102.70
$ 772
$ 102.38
$ 757
$ 83.14
$ 538
ECA
$ 103.03
$ 775
$ 103.70
$ 767
$ 82.52
$ 534
For this analysis, the U.S. included the lower contiguous states and southeastern Alaska.
p Note that distillate fuel has a higher energy content, on a per tonne basis, than residual fuel. As such, there is an
offsetting cost savings, on a per tonne basis, for switching to distillate fuel. Based on a 5 percent higher energy
content for distillate, the net equivalent cost increase is estimated as $123 for each tonne of residual fuel that is being
replaced by distillate fuel ($200/tonne for the high price case).
5-58
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Chapter 5: Engineering Cost Estimates
5.7 Summary of Final Program Engineering Costs
5.7.1 Engineering Costs for Freshly Manufactured Engines
The total engine costs presented here include the fixed and variable costs of CAA Tier 2
and Tier 3 technologies to U.S.-flagged vessels, and are included in the total estimated cost of
the coordinated strategy. The costs associated with the existing engine program are not included
here but are presented in Section 5.3.1. The engine related costs to new U.S.-flagged vessels
through 2040 at a 3 percent discount rate is estimated to be $0.66 billion, and $0.35 billion at a 7
percent discount rate.
Table 5-41 Total U.S.-Flagged Engine Costs for Freshly Manufactured Engines
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
FIXED
$309,000
$837,000
$869,000
$902,000
$936,000
$972,000
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$4,440,000
$3,990,000
VARIABLE
$0
$2,580,000
$2,680,000
$2,780,000
$2,890,000
$3,000,000
$27,400,000
$28,400,000
$29,600,000
$30,700,000
$31 ,900,000
$33,200,000
$34,500,000
$35,900,000
$37,400,000
$38,800,000
$40,400,000
$42,000,000
$43,700,000
$45,500,000
$47,400,000
$49,300,000
$51 ,300,000
$53,400,000
$55,600,000
$57,900,000
$60,200,000
$62,700,000
$65,300,000
$68,000,000
$70,800,000
$658,000,000
$342,000,000
TOTAL
$309,000
$3,420,000
$3,550,000
$3,680,000
$3,830,000
$3,970,000
$27,400,000
$28,400,000
$29,600,000
$30,700,000
$31 ,900,000
$33,200,000
$34,500,000
$35,900,000
$37,400,000
$38,800,000
$40,400,000
$42,000,000
$43,700,000
$45,500,000
$47,400,000
$49,300,000
$51 ,300,000
$53,400,000
$55,600,000
$57,900,000
$60,200,000
$62,700,000
$65,300,000
$68,000,000
$70,800,000
$663,000,000
$346,000,000
5-59
-------
Regulatory Impact Analysis
5.7.2 Engineering Costs for Vessels
The vessel costs presented here are associated with the use of lower sulfur fuel to meet
the 2015 fuel sulfur standards for U.S.-flagged vessels. The costs here include additional
equipment that may be required to accommodate the use of lower sulfur fuel on both new and
existing vessels. The total cost to U.S.-flagged ships through 2040 at a 3 percent discount rate is
$0.26 billion, or $0.17 billion at a seven percent discount rate.
Table 5-42 U.S.-Flagged Vessel Engineering Costs
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
FIXED
$166,000
$172,000
$179,000
$185,000
$192,000
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$842,000
$781 ,000
VARIABLE
$0
$0
$0
$0
$0
$11,100,000
$691 ,000
$717,000
$745,000
$773,000
$803,000
$834,000
$866,000
$899,000
$934,000
$970,000
$1,010,000
$1 ,050,000
$1 ,090,000
$1,130,000
$1,180,000
$1 ,220,000
$1 ,270,000
$1 ,320,000
$1 ,370,000
$1 ,430,000
$1 ,490,000
$1 ,540,000
$1,610,000
$1 ,670,000
$1 ,740,000
$25,600,000
$16,200,000
TOTAL
$166,000
$172,000
$179,000
$185,000
$192,000
$11,100,000
$691 ,000
$717,000
$745,000
$773,000
$803,000
$834,000
$866,000
$899,000
$934,000
$970,000
$1,010,000
$1 ,050,000
$1 ,090,000
$1,130,000
$1,180,000
$1 ,220,000
$1 ,270,000
$1 ,320,000
$1 ,370,000
$1 ,430,000
$1 ,490,000
$1 ,540,000
$1,610,000
$1 ,670,000
$1 ,740,000
$26,500,000
$16,900,000
5-60
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Chapter 5: Engineering Cost Estimates
5.7.3 Total Increased Operating Costs
The total increase operating costs associated with the coordinated strategy are $42 billion
at a 7 percent discount rate in 2040, and $22 billion at a 3 percent discount rate. The operational
costs include Tier 2 and global Tier II fuel consumption increases, the use of urea with SCR for
Tier 3 and Tier III equipped vessels, and the increased costs associated with the use of lower
sulfur fuel. Table 5-43 presents the operating costs for both U.S.- and foreign-flagged vessels,
and the total for the coordinated strategy.
Table 5-43 Total Operational Costs (SThousands)
TOTAL OPERATING COSTS
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
U.S.-Flag
$0
$0
$1,000
$32,000
$34,000
$180,000
$189,000
$199,000
$210,000
$221 ,000
$233,000
$246,000
$258,000
$272,000
$286,000
$300,000
$315,000
$330,000
$345,000
$362,000
$378,000
$395,000
$413,000
$431 ,000
$451 ,000
$471 ,000
$494,000
$517,000
$541 ,000
$566,000
$591 ,000
$5,260,000
$2,730,000
Foreign Flag
$0
$1,000
$6,000
$213,000
$226,000
$1,188,000
$1,250,000
$1,326,000
$1,409,000
$1,500,000
$1,590,000
$1,680,000
$1,767,000
$1,877,000
$1,983,000
$2,086,000
$2,200,000
$2,312,000
$2,429,000
$2,553,000
$2,681 ,000
$2,814,000
$2,948,000
$3,084,000
$3,244,000
$3,394,000
$3,558,000
$3,738,000
$3,925,000
$4,112,000
$4,311,000
$36,900,000
$19,000,000
Total
$0
$1 ,000
$7,000
$245,000
$260,000
$1,368,000
$1,439,000
$1,525,000
$1,619,000
$1,721,000
$1,823,000
$1,926,000
$2,025,000
$2,149,000
$2,269,000
$2,386,000
$2,515,000
$2,642,000
$2,774,000
$2,915,000
$3,059,000
$3,209,000
$3,361,000
$3,515,000
$3,695,000
$3,865,000
$4,052,000
$4,255,000
$4,466,000
$4,678,000
$4,902,000
$42,200,000
$21 ,700,000
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Regulatory Impact Analysis
5.7.4 Total Engineering and Operating Costs Associated with the Final Program
The total engineering hardware and operational costs associated with the coordinated
strategy and included in the total cost of the coordinated strategy are described in Table 5-44 and
presented in Table 5-45. The total cost of the program through 2040 at a 3 percent discount rate
is $43 billion, or $22 billion at a 7 percent discount rate.
Table 5-44 U.S.- and Foreign-Flagged Costs Included in Total
COSTS INCLUDED IN THE TOTAL COORDINATED STRATEGY COST ESTIMATE*
U.S.-Flagged Vessels
Annex VI Existing Engine Program Hardware Costs
(No Estimated Fuel Consumption Penalty)
Tier 2 Hardware Costs
Tier 2 Operational Costs
(based on an estimated 2 percent fuel consumption penalty)
Tier 3 Hardware Costs
Tier 3 Operational Costs
(based on the use of urea with SCR)
Lower Sulfur Fuel Hardware Costs
(New and Existing Vessels)
Lower Sulfur Fuel Operational Costs
(based on the differential price of lower sulfur fuel)
Foreign-Flagged Vessels
Not Included
Not Included
Tier 2 Operational
(based on an estimated 2 percent fuel consumption penalty)
Not Included
(Presented as a separate analysis, not included in total cost)
TierS Operational
(based on the use of urea with SCR)
Not Included
(Presented as a separate analysis, not included in total cost)
Lower Sulfur Fuel Operational Costs
(based on the differential price of lower sulfur fuel)
Notes:
A The cost totals reported in this FRM are slightly different than those reported in the EGA proposal, because the EGA proposal did not include
costs associated with the Annex VI existing engine program, Tier II, or the costs associated with existing vessel modifications that may be
required to accommodate the use of lower sulfur fuel. Further, the cost totals presented in the EGA package included Canadian cost estimates.
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Chapter 5: Engineering Cost Estimates
Table 5-45 Total Costs Associated with the Coordinated Strategy (SThousands)
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV@3%
NPV@7%
FIXED
$485
$1,020
$1,060
$1,100
$1,140
$972
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,320
$4,800
VARIABLE
$0
$2,730
$2,820
$2,920
$3,020
$14,200
$28,100
$29,200
$30,300
$31 ,500
$32,700
$34,000
$35,400
$36,800
$38,300
$39,800
$41 ,400
$43,100
$44,800
$46,600
$48,500
$50,500
$52,600
$54,700
$56,900
$59,300
$61 ,700
$64,300
$66,900
$69,700
$72,600
$685,000
$359,000
OPERATIONAL
$0
$1,310
$6,430
$245,000
$261 ,000
$1 ,370,000
$1 ,440,000
$1 ,530,000
$1,620,000
$1,720,000
$1,820,000
$1,930,000
$2,030,000
$2,150,000
$2,270,000
$2,390,000
$2,510,000
$2,640,000
$2,770,000
$2,910,000
$3,060,000
$3,210,000
$3,360,000
$3,520,000
$3,690,000
$3,870,000
$4,060,000
$4,260,000
$4,470,000
$4,680,000
$4,910,000
$42,200,000
$21 ,700,000
TOTAL
$485
$5,060
$10,300
$249,000
$265,000
$1 ,380,000
$1 ,470,000
$1 ,550,000
$1 ,650,000
$1 ,750,000
$1 ,850,000
$1 ,960,000
$2,060,000
$2,180,000
$2,310,000
$2,430,000
$2,550,000
$2,680,000
$2,820,000
$2,960,000
$3,110,000
$3,260,000
$3,410,000
$3,570,000
$3,750,000
$3,930,000
$4,120,000
$4,320,000
$4,530,000
$4,750,000
$4,980,000
$42,900,000
$22,100,000
5.8 Cost Effectiveness
One tool that can be used to assess the value of the coordinated strategy is the measure of
cost effectiveness; a ratio of engineering costs incurred per ton of emissions reduced. This
analysis involves a comparison of our final program to other measures that have been or could be
implemented. As summarized in this section, the coordinated strategy represents a highly cost
effective mobile source control program for reducing NOx, PM and SOx emissions.
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Regulatory Impact Analysis
We have estimated the cost per ton based on the net present value of 3 percent and 7
percent of all hardware costs incurred by U.S.-flagged vessels, and all operational costs incurred
by both U.S.- and foreign-flagged vessels, and all emission reductions generated from the year
2010 through the year 2040. The baseline case for these estimated reductions is the existing set
of engine standards for Category 3 marine diesel engines and existing fuel sulfur limits. Note
that PM2 5 is estimated to be 92 percent of the more inclusive PMi0 emission inventory for
marine vessels. In Chapter 3, we generate and present PM2.5 inventories since recent research
has determined that these are of greater health concern. Traditionally, we have used PMi0 in our
cost effectiveness calculations. Since cost effectiveness is a means of comparing control
measures to one another, we use PMi0 in our cost effectiveness calculations for comparisons to
past control measures, Table5-46 shows the annual emissions reductions associated with the
coordinated strategy, these annual tons are undiscounted. A description of the methodology used
to estimate these annual reductions can be found in Chapter 3 of the RIA.
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Chapter 5: Engineering Cost Estimates
Table 5-46 Estimated Emissions Reductions Associated with the Coordinated Strategy (Short tons)
CALENDAR
YEAR
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV at 3%
NPV at 7%
REDUCTIONS (TONS)
NOX
47,000
54,000
70,000
88,000
105,000
123,000
150,000
209,000
279,000
349,000
409,000
488,000
547,000
634,000
714,000
790,000
866,000
938,000
1,020,000
1,100,000
1,180,000
1,260,000
1,330,000
1,410,000
1,500,000
1,590,000
1,690,000
1,810,000
1,920,000
2,020,000
2,130,000
14,400,000
6,920,000
SOX
0
0
0
390,000
406,000
641,000
668,000
695,000
724,000
755,000
877,000
916,000
954,000
995,000
1,040,000
1,080,000
1,130,000
1,170,000
1,220,000
1,280,000
1,330,000
1,390,000
1,450,000
1,510,000
1,580,000
1,650,000
1,720,000
1,800,000
1,880,000
1,970,000
2,050,000
19,100,000
10,100,000
PM
0
0
0
48,400
50,400
68,000
70,800
73,700
76,800
80,000
94,100
98,200
102,000
107,000
111,000
116,000
121,000
126,000
131,000
137,000
143,000
149,000
155,000
162,000
169,000
177,000
184,000
193,000
201,000
210,000
220,000
2,100,000
1,090,000
C02a
0)
(14,031)
(69,095)
(133,186)
(196,707)
(246,811)
(288,018)
(279,562)
(289,728)
(293,913)
(288,793)
(293,352)
(299,538)
(283,284)
(267,713)
(264,342)
(247,996)
(231,650)
(212,089)
(209,920)
(202,868)
(212,290)
(238,611)
(250,697)
(247,327)
(248,419)
(250,133)
(241,372)
(238,869)
(245,155)
(244,510)
(4,475,384)
(2,711,686)
represents CO2 increase associated with estimated fuel penalty for Tier IINOX standard
The net estimated reductions by pollutant, using a net present value of 3 percent from
2010 through 2040 are 14.4 million tons of NOX, 19.1 million tons of SOX, and 2.1 million tons
of PM (6.9 million, 10.1 million, and 1.1 million tons of NOx, SOx, and PM, respectively, at a
net present value of 7 percent over the same period.)
Using the above cost and emission reduction estimates, we estimated the lifetime (2010
through 2040) cost per ton of pollutant reduced. For this analysis, all of the hardware costs
associated with the Annex VI existing engine program, and Tier 2 and Tier 3 NOx standards as
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Regulatory Impact Analysis
well as the operational costs associated with the CAA Tier 2 and Tier 3, and global Tier II and
Tier III NOx standards were attributed to NOx reductions. The costs associated with lower
sulfur fuel operational costs as applied to all vessels visiting U.S. ports and the hardware costs
associated with accommodating the use of lower sulfur fuel on U.S.-flagged vessels were
associated with SOx and PM reductions. In this analysis, we have allocated half of the costs
associated with the use of lower sulfur fuel to PM and half to SOx, because the costs incurred to
reduce SOx emissions directly reduce emissions of PM as well. Using this allocation of costs
and the emission reductions shown in Table 5-46, we can estimate the lifetime cost per ton
reduced associated with each pollutant. The resultant estimated cost effectiveness numbers are
shown in Table 5-47. Using a net present value of 3 percent, the discounted lifetime cost per ton
of pollutant reduced is $510 for NOX, $930 for SOX, and $7,950 for PM ($500, $920, and $7,850
per ton of NOX, SOX, and PM, respectively, at a net present value of 7 percent.) As shown in
Table 5-47, these estimated discounted lifetime costs are similar to the annual long-term (2030)
cost per ton of pollutant reduced.
Table 5-47 Coordinated Strategy Estiamted Aggregate Discounted Cost per Ton and Long-Term Annual
Cost per Ton3'b
POLLUTANT
NOX
SOX
PM
2010 THRU 2040 DISCOUNTED
LIFETIME COST PER TON AT
3%
$510
$930
$7,950
2010 THRU 2040 DISCOUNTED
LIFETIME COST PER TON AT
7%
$500
$920
$7,850
LONG-TERM
COST PER TON
(FOR 2030)
$520
$940
$8,060
Notes:
"These costs are in2006 U.S. dollars.
b The $/ton numbers presented here vary from those presented in the EGA proposal due to the net present value of
the annualized reductions being applied from 2015-2020, and the use of tonnes rather than of short tons.
These results for the coordinated strategy compare favorably to other air emission control
programs. Table 5-48 compares the coordinated strategy to other air programs. This comparison
shows that the coordinated strategy will provide a cost-effective strategy for generating
substantial NOx, SOx, and PM reductions from ocean-going vessels. The results presented in
Table 5-48 are lifetime costs per ton discounted at a net present value of 3 percent, with the
exception of the stationary source program and locomotive/marine retrofits, for which annualized
costs are presented. While results at a net present value of 7 percent are not presented, the results
would be similar. Specifically, the coordinated strategy falls within the range of values for other
recent programs.
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Chapter 5: Engineering Cost Estimates
Table 5-48 Estimated $/ton for the Coordinated Strategy Compared to Previous Mobile Source Programs for
NOX, SOX, and PM10
SOURCE CATEGORY20'*
Category 3 Compression Ignition Engine
Coordinated Strategy FRM, 2009
Nonroad Small Spark-Ignition Engines
73 Fed Reg 59034, October 8, 2008
Stationary Diesel (CI) Engines
71 Fed Reg 39154, July 11,2006
Locomotives and Category I/Category 2
(Both New and Retrofits) °
73 Fed Reg 25097, May 6, 2008
Heavy Duty Nonroad Diesel Engines0 69
Fed Reg 38957, June 29, 2004
Heavy Duty Onroad Diesel Engines °
66 Fed Reg 5001, January 18, 2001
IMPLEMENTATION
DATE
2011
2010
2006
2015
2015
2010
NOX
COST/TONNE
510
330-1200b'c
580-20,000
730b
l,100b
2,200b
SOX
COST/TONNE
930
-
-
-
780
5,800
PM10
COST/TONNE
7,950
-
3,500-42,000
8,400 (New)
45,000 (Retrofit)1"
13,000
14,000
Notes:
a Table presents aggregate program-wide cost/ton over 30 years, discounted at a 3 percent NPV, except for
stationary CI Engines and LocoMarine retrofits, for which annualized costs of control for individual sources are
presented. All figures are in 2006 U.S. dollars per short ton.
b Includes NOX plus non-methane hydrocarbons (NMHC). NMHC are also ozone precursors, thus some rules set
combined NOX +NMHC emissions standards. NMHC are a small fraction of NOX so aggregate cost/ton
comparisons are still reasonable.
0 Low end of range represents costs for marine engines with credit for fuel savings, high end of range represents
costs for other nonroad SI engines without credit for fuel savings.
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Regulatory Impact Analysis
APPENDIX 5A
NOx Monitoring
EPA is adopting provisions that will require the monitoring of NOx emissions in certain
circumstances and require measurement of NOx emission rates (g/kW-hr) in other
circumstances. Section 1042.110 requires the measurement of exhaust NOx concentrations
(ppm) for new engines using SCR or other on-off NOx controls. This provision will require a
permanent NOx monitor. Section 1042.302 requires measurement of NOx emission rates (g/kW-
hr) during the sea trial of a new vessel. The provisions of §1042.302 can be also met with a NOx
monitoring system. This appendix summarizes the feasibility and costs of two different types of
NOX monitoring systems. See Appendix 5C for a more complete discussion of measurement of
NOx emission rates (g/kW-hr) during the sea trial of a new vessel.
5A.1 Simple NOx Sensor Systems
The requirements of §1042.110 can be met using a very simple system that consists
primarily of a zirconia NOX sensor. Such sensors are currently being used in highway vehicles
to monitor NOx and ammonia concentrations downstream of SCR systems.
For engines that will sometimes operate on fuels with very high sulfur levels,
manufacturers may choose to include a sampling system that would allow the sensor to be
isolated from the exhaust when running on high sulfur fuels. Such a sampling system could be
as simple as a sample probe in the exhaust stream connected to a pump that can supply a sample
of exhaust to the NOx sensor when measurement is required. It could also include valves to
further isolate the sensor from exhaust gases when not being used. As summarized in the
following table, we believe that such a system could be produced for less than $4,000. Such a
system would work for any size engine.
COMPONENT
Zirconia NOx Sensor
Sample Pump
Tubing, Valves, and Fittings
Total Cost
ESTIMATED COST
$2,000
$1,000
<$1,000
<$4,000
5A.2 Complete Monitoring Systems
Appendix 8 to the NOx Technical Code specifies a method for measuring emissions from
ships. Under our regulations, manufacturers could also choose to purchase a complete
monitoring system that complies with these requirements. This method, which is referred to as
the Direct Measurement and Monitoring (DMM) method, provides a continuous monitoring
option to ensure that engines with adjustable parameters stay in compliance with Regulation 13
of MARPOL Annex VI. Under this approach, emissions of regulated pollutants are measured
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Chapter 5: Engineering Cost Estimates
when the engine is operating at or near the certification speed and load points. The DMM
method also describes analyzer, calibration gas, and sample handling system requirements.
One supplier commented that a complete DMM system for continuous monitoring that
was fully integrated into the vessel would cost approximately $100,000. However, only a small
part of this cost would be attributable to our requirement, since these systems have other benefits
for the vessel operator. These systems are advertised as reducing fuel and maintenance costs in
addition to simplifying compliance with Annex VI regulations.
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Regulatory Impact Analysis
APPENDIX 5B
Feasibility and Cost of Testing Engines during Sea Trials
5B.1 Requirement
A new §1042.302 requires that all Category 3 engines be tested for NOx emissions
during the sea trial of the vessel or within the first 300 hours of operation, whichever occurs first.
This provision requires that the engine be tested at the test points for the specified duty cycle, or
at similar test points consistent with the specifications of section 6 of Appendix 8 to the NOx
Technical Code. The engines must comply with the alternate installed-engine standard of
§1042.104(g), which is ten percent higher than the certification standard. Manufacturers must
obtain EPA approval of their test procedures prior to testing the engine. This provision allows
measurement of NOx emissions according to the Direct Measurement and Monitoring method
specified in section 6.4 of the NOx Technical Code. Measurement of HC, CO and PM is not
required.
It is important to also note that the costs presented here should be compared to the cost of
performing a full certification test with an installed catalyst system. One of the reasons why we
determined that this sea-trial testing was necessary was that manufacturers convinced us that,
given the very low sales volumes, it would be impractical and expensive to perform a standard
certification test for catalyst-equipped engines. For all other engine sectors, manufacturers can
spread the cost of a prototype catalyst system for certification testing other many production
engines. If we had not finalized this requirement for sea-trial testing, we would have required
full certification testing with a prototype catalyst system.
5B.2 Test Procedures
Manufacturers can use variations of two test procedures. The first is the field testing
procedures of 40 CFR part 1065. The second is the Direct Measurement and Monitoring (DMM)
method specified in section 6.4 of the NOx Technical Code.
While measuring emission rates from installed marine engines is very similar to other
testing, there are challenges specific to Category 3 engine testing. First, care must be taken in
determining how to collect a representative sample of the exhaust. Good engineering judgment
would generally require locating the sample port at least several pipe diameters downstream of
any flow disturbance. This can be challenging given the diameter of a typical Category 3
exhaust system. Nevertheless, this can be readily achieved, especially with proper consideration
during the design phase of a vessel.
The second challenge is that it can be difficult to replicate the certification test points,
especially the 100% load point. Most engines are not capable of running continuously at 100%
load due to physical limitations on engine and drive train components. It can be difficult to
target other certification speed and load points during the Sea Trial. However, these issues have
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Chapter 5: Engineering Cost Estimates
been addressed in the NOx Technical Code. This approach is described in the later discussion of
direct measurement and monitoring.
5B.2.1 1065 Testing With PEMS
The test procedures of 40 CFR part 1065 are designed to be adaptable to both laboratory
and field testing. Subpart J of part 1065 describes how to apply these procedures for measuring
emissions from installed engines.
Part 1065 contains provisions for portable emission measurement systems (PEMS). In
recent years, several companies have developed portable systems for measuring gaseous and
particulate emission rates from installed engines. These systems have been tested in a variety of
environments. EPA has recently participated in a test program to measure gaseous emissions
from Category 3 marine engines installed on ocean going vessels. While the results of the test
program have not been finalized, preliminary indications are that PEMS can be used to
accurately measure emissions from installed engines in-use. Further, the certification speed and
load points were achievable during testing with the exception of the 100% load point, which
shows the feasibility of using part 1065.
5B.2.2 Direct Measurement and Monitoring
Appendix 8 to the NOx Technical Code specifies a method for measuring emissions from
ships. This DMM method provides a continuous monitoring option to ensure that engines with
adjustable parameters stay in compliance with Regulation 13 of MARPOL Annex VI. Under
this method, emissions of regulated pollutants are measured when the engine is operating at or
near the certification speed and load points. The DMM method also describes analyzer,
calibration gas, and sample handling system requirements.
An important part of the method is its specification for how to test engines when it is not
possible to run at all of the certification load points in-use. The DMM method provides
equations to determine alternate weighting factors for determination of cycle-specific emissions.
It does this by determining a new weighting factor for a given load point based on that point's
certification weighting factor and the combined weighting factors of the other test points to be
included in the composite calculation. Provisions for power stability over the duration in which
data is collected for a given point are also provided.
5B.3 Costs
There are three types of expenses to consider for testing: equipment, engineering, and
operating. The actual cost to comply with this requirement will depend on how the
manufacturers choose to comply, how efficiently they run the test, and the number of engines
over which the equipment costs can be amortized.
We are including in this appendix a worst-case analysis, assuming manufacturers do not
fully optimize the testing to minimize costs. However, we expect that classification societies
will ultimately develop the ability to integrate emission testing into the sea trials for much less
than the worst-case costs presented here.
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Regulatory Impact Analysis
5B.3.1 Equipment Costs
Equipment costs will differ depending on whether the manufacturer chooses to do 1065
PEMS testing or DMM testing. We estimate that PEMS equipment will cost about $100,000
when the testing is required. The per-test cost would be dependent on how this cost would be
spread over multiple tests and other purposes. Manufacturers purchasing a PEMS unit would
likely use it for many other purposes such as during its development work, and could spread the
cost over both the compliance tests and the development work. Classification societies
purchasing PEMS units would likely use them only for testing, but would perform more tests
with them. Thus, we estimate that a cost of $2,000 to $10,000 should be assigned for testing a
given installation.
The other option for a manufacturer would be to incorporate a DMM continuous
monitoring system. One supplier commented that a complete DMM system for continuous
monitoring would cost approximately $100,000. This cost would apply to each vessel.
However, this approach has other benefits for the vessel operator. These systems are advertised
as reducing fuel and maintenance costs, as well as simplifying compliance with Annex VI
regulations. It also would meet the requirements for monitoring on-off emission systems. Thus
the true cost attributable to sea-trial emission testing would be less than $100,000. Since it is
reasonable to expect that manufacturers would choose this option only if these other benefits
were worth more to them than the additional cost over performing PEMS testing, the cost
assignable to testing should be the same as for PEMS.
5B.3.2 Engineering Costs
Whether a manufacturer chooses 1065 PEMS system or a DMM system, we estimate that
there would be a cost for one or more engineers to maintain, set up, and run the emission testing
equipment. However, both types of equipment are designed to be relatively user-friendly and
easy to operate. As is true for the equipment costs, we believe not all of these costs should be
assigned to the testing required by EPA (they could also be spread over both the compliance tests
and the development work). We estimate that the amount that should be assigned to compliance
testing would be a few thousand dollars, but would not exceed $5,000 per test (equivalent to 50
hours at $100 per hour).
5B.3.3 Operating Costs
Euromot commented that performing an onboard emission test would add one full day to
the sea trial at an expense of 200,000 Euro (approximately $300,000). We do not have
information to dispute Euromot's claim that sea trials cost $300,000 per full day. However, we
disagree that the required emission test would add one full day to the sea trial. First, we believe
that measuring emissions at four test points could easily be done within two hours. Since setup
for the testing could be done with the engine in port, these few hours would be the only testing-
related time burden while the vessel is at sea. More importantly, it would be possible to
simultaneously perform other non-emission testing and evaluation while measuring emissions.
With proper planning, we would not expect emission testing to add to the overall length of a sea
trial. Even without fully harmonizing the testing in the sea trial, the most that emission testing
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Chapter 5: Engineering Cost Estimates
would add to the cost would be $50,000 (one-sixth of day using Euromot's cost estimate).
However, we estimate that a properly optimized test would cost only $10,000.
5B.4 Conclusion
The requirement to measure NOX emissions during the sea trial will be an important part
of our compliance efforts. Unlike many smaller nonroad sources, we cannot bring in
representative engines from the field to test them ourselves. In addition, §1042.655 allows
manufacturers to certify engines without testing a fully assembled engine and catalyst system.
Thus, the required testing will provide test data that would not otherwise be available to us.
Since we recognize that requiring full certification testing of a fully assembled production engine
(which we require for many other nonroad sectors) could be prohibitively expensive for
Category 3 engines, we have made many allowances to minimize the costs.
We estimate that the long-term average cost for the requirement to measure NOX
emission during the sea trial would be $10,000 per test, provided the manufacturers and/or class
societies integrate it into the trial. However, other approaches, such as hiring a third party to run
a stand-alone emission test, could be much more expensive.
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Regulatory Impact Analysis
APPENDIX 5C
Analysis of Gas Turbines
We are finalizing provisions to apply our emission standards to gas turbine engines,
beginning in the Tier 4 timeframe. These provisions will apply the same standards as will apply
for our Category 1 and Category 2 engines. See §1042.670 of the regulations for a complete
description of these new requirements.
5C.1 Background
Gas turbine engines are internal combustion engines that can operate using a variety of
fuels (such as diesel fuel or natural gas) but do not operate on a compression-ignition diesel cycle
or other reciprocating engine cycle. Power is extracted from the combustion gas using a rotating
turbine rather than reciprocating pistons. Just like diesel engines, gas turbines can operate over
wide ranges of air/fuel ratios. The most significant effects of changing air/fuel ratios are changes
to thermal efficiency, exhaust gas temperatures, and exhaust flow rates.
The primary type of U.S.-flagged vessels that use gas turbine engines are naval combat
ships. While a small number of gas turbine engines have been used in commercial ships, we are
not aware of any current sales for commercial applications. They can range in size from those
equivalent in power to mid-size Category 1 engines to those that produce the same power as
many Category 3 engines. While these engines are subject to the Clean Air Act as nonroad
engines, we have until now deferred setting standards for marine gas turbine engines. We
originally raised the issue of regulating marine gas turbine engines in 1998, but decided not to
finalize any requirements, as described in the 1999 Summary and Analysis of Comments
document for that rule. These engines have not been previously subject to our marine standards
because the regulations apply them only to compression-ignition and spark-ignition marine
engines. This rule amends the regulations in part 1042 to apply the emission standards to other
engines including gas turbines.
5C.2 Feasibility
The section discusses the technological feasibility of certifying gas turbine engines to our
Tier 4 standards. It is important to note that, irrespective of this analysis, this requirement can be
considered to be feasible based solely on the fact that vessel manufacturers do not need to use
turbine engines in commercial applications. Commenters did not dispute our assertion that the
only circumstance in which a vessel would actually need a gas turbine engine would be for
military purposes and it is entirely feasible for all other vessels to be powered by a diesel engine
(as is being done today).
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5C.2.1 NOX Standards
Gas turbine engines tend to have relatively low engine-out emissions of NOx. For this
analysis, we are assuming them to be approximately 5.0 g/kW-hr, which is about half the
emissions from a Category 2 engine meeting Tier 2 emission standards. To the extent this
assumed emission rate is incorrect, estimates of total costs would be different than those
estimated here. However, estimated cost-effectiveness would be less sensitive to such changes.
We are confident that gas turbine engines could use the same type of NOx aftertreatment
as is projected for diesel engines. The basic reactions through which SCR reduces NOX
emissions can occur under a wide range of conditions, and exhaust from gas turbine engines is
fundamentally similar to exhaust from diesel engines. SCR effectiveness is dependent on
exhaust temperature, especially at lower temperatures. This would not be a problem for gas
turbine engines since they tend to have higher exhaust temperatures. Commenters raised
concerns about higher exhaust flow rates and back pressure limitations. These concerns can be
addressed by making the catalyst system larger and more open.
5C.2.2 HC, CO, and PM standards
Given their high air/fuel ratios, gas turbine engines tend to have relatively low engine-out
emissions of HC, CO, and PM. To the extent that these engine-out levels exceed the standards,
they can be reduced with catalytic aftertreatment to further oxidize these pollutants. We do not
expect this to be necessary.
5C.3 Costs and Cost-Effectiveness
5C.3.1 Comparison to Diesel Engine Costs
Compliance cost for gas turbine engines meeting the Tier 4 standards should be similar to
those of Category 2 diesel engines. However, there would likely be some differences. First,
exhaust catalyst systems may need to be larger and more open to handle higher exhaust flow
rates. However, the lower engine-out NOx emissions may allow them to be more lightly loaded
than they will be for diesel engines. For this analysis, we are assuming that SCR catalyst cost
will scale with exhaust flow rate, and that gas turbine engines will have flow rates 30 percent
higher than diesel engines producing the same power.
Second, since gas turbine engines have lower engine-out NOx emissions, they would
need less urea to meet the standard on a brake-specific basis. Urea cost would be proportional to
the difference between engine-out NOx and the standard.
Third, if gas turbine engines have lower sales volumes, the fixed costs could be higher on
a per-engine basis. However, it is important to note that many marine diesel engine families are
also small. Per-engine fixed costs for gas turbine engines should be similar to those for small
diesel engine families.
Finally, we expect that gas turbine engines will not need catalytic aftertreatment to reduce
HC, CO, or PM. This would reduce aftertreatment cost by about half from what would apply for
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diesel engines since they are expected to need catalytic PM traps to meet the Tier 4 PM
standards.
5C.3.2 Cost-Effectiveness of NOX Standards
This section compares the cost-effectiveness of our Tier 4 NOX standards for a typical
Category 2 diesel engine and gas turbine engine with the same rated power. We are not
estimating cost-effectiveness for the HC, CO, or PM standards because we do expect there to be
significant compliance costs for these standards for gas turbine engines. To the extent that this is
incorrect, costs should still be much lower than for diesel engines. Consistent with this
assumption, all fixed costs are assigned to NOx control.
It is important to note that this analysis, which is summarized in Table 5C-1, is somewhat
simplistic and is intended to represent a worst-case comparison. Given how low the estimated
cost per ton is, a more sophisticated analysis is not necessary. In general, the inputs to the
analysis for diesel engines are the equivalent to those used for the 2008 final rule setting
emission standards for Category 2 marine diesel engines. The fixed costs for diesel and turbine
families are assumed be the same, so the per-engine costs are dependent on the number of
engines in the families. The critical assumptions in this analysis are those related to:
Engine family size
Engine emission rates
Hardware costs
Urea cost
The assumptions of the numbers of engines in engine families represent the combined
number of engines in applicable family over multiple model years (assuming carryover
certification). For example, the assumption of 100 engines in the diesel engine family could be a
family produced for five years with 20 engines per year. The assumed engine-out emission rates
affect the emission reductions and the urea cost. For example, assuming engine-out emissions
from gas turbines were 3.4 g/kW-hr would have cut both the tons of NOx reduced and the urea
costs in half. In addition, if engine out emission were this low, manufacturers may also be able
to reduce the hardware costs as well, or avoid using SCR altogether.
Hardware costs were estimated from the equations summarized in Table 5-27 of this
chapter for the 2008 final rule, adjusted to 2006 dollars. Hardware costs for turbines were
assumed to be 30 percent higher due a 30 percent higher exhaust flow rate. Urea is assumed to
cost $1.52 per gallon.
Costs and benefits were calculated for the useful life period. This represents a worst-case
cost effectiveness since most engines will be rebuilt and operate beyond the useful life. The
emission controls should continue to achieve very similar emission reductions after the rebuild
but compliance costs would be limited primarily to the operating costs.
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Table 5C-1 Simplified Cost-Effectiveness Analysis of NOX Standards
ASSUMPTIONS
Displacement (1/eng)
Rated kW
Engines per Family
Engine-out NOx (g/kW-hr)
Standard (g/kW-hr)
Reduction (g/kW-hr)
R&D ($/eng)
Tooling ($/eng)
Certification ($/eng)
Hardware Costs ($/eng)
Urea Rate (gal/gal fuel)
Urea Cost ($/gal)
Fuel Consumption(gal/hr)
Useful Life (hrs)
Urea Cost ($/UL)
Total Cost ($/UL)
Load Factor
Reductions (ton/UL)
$/ton
DIESEL
300
4500
100
9.8
1.8
8
$4,120
$1,360
$556
$71,051
0.04
$1.52
280
20,000
$340,480
$417,567
0.7
504
$829
GAS TURBINE
-
4500
10
5
1.8
3.2
$41,200
$13,596
$5,562
$92,367
0.016
$1.52
280
20,000
$136,192
$288,917
0.7
201.6
$1,433
5C.4 Conclusion
Gas turbine engines can meet the Tier 4 emission standards using the same emission
controls as will be used for diesel engines. While hardware cost may be higher, overall
compliance costs for gas turbines should be less than for diesel engines due to lower engine-out
emission rates. The standards will be very cost-effective for gas turbines, although the calculated
cost per ton is somewhat higher than for diesel engines because the standards will achieve lower
NOx reductions from turbines engines.
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References
1ICF 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.
2 "Matched Typical Ports to Modeled Ports" Table 2-33 of Section 2.5.2 of "The Commercial
Marine Port Inventory Development, 2002 and 2005 Draft Inventories" report to EPA from ICF
International, September 2007.
3 ICF International, Inventory Contribution of U.S. Flagged Vessels, prepared for the U.S.
Environmental Protection Agency, EPA Report Number EPA-420-R-09-005, March 2009.
4http://www.marad.dot.gov/documents/Vessel_Calls_at_US_Ports_Snapshot.pdf
5 http://www.marad.dot.gov/documents/us-flag_fleet_l0000_dwt_and_above.xls
6 Lloyd's Register of Ships, can be found at www.sea-web.com
7 ICF International, "Commercial Marine Port Inventory Development 2002 and 2005 Draft
Inventories" prepared by the U.S. Environmental Protection Agency, September 2007.
8 "Nonroad SCR-Urea Study Final Report" July 29, 2007 TIAX for Engine Manufacturers
Association (EMA) can be found
at:http://www.enginemanufacturers.org/admin/content/upload/l 98.pdf
9 http://www.adblueonline.co.uk/air_l/bulk_delivery
10 http://www.factsaboutscr.com/documents/IntegerResearch-Ureapricesbackto20051evels.pdf
11 http://www.fertilizerworks.com/fertreport/index.html
12 Research Triangle Institute, 2008. "Global Trade and Fuels Assessment—Future Trends and
Effects of Designating Requiring Clean Fuels in the Marine Sector"; Research Triangle Park,
NC; EPA420-R-08-021; November.
13 Research Triangle Institute, 2008. "Global Trade and Fuels Assessment—Future Trends and
Effects of Designating Requiring Clean Fuels in the Marine Sector"; Research Triangle Park,
NC; EPA420-R-08-021; November.
14 International Maritime Organization, Note by the Secretariat, "Revision of MARPOL Annex
VI and 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," Subcommittee
on Bulk Liquids and Gases, 12th Session, Agenda Item 6, BLG 12/INF. 10, December 28, 2007.
15 International Maritime Organization, Note by the Secretariat, "Revision of MARPOL Annex
VI and 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," Subcommittee
on Bulk Liquids and Gases, 12th Session, Agenda Item 6, BLG 12/INF. 10, December 28, 2007.
16 EnSys Energy & Systems, Inc. and RTI International 2009. Global Trade and Fuels
Assessment—Additional EGA Modeling Scenarios, prepared for the U.S. Environmental
Protection Agency.
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Chapter 5: Engineering Cost Estimates
17 Energy Information Administration, 2006. "Annual Energy Outlook 2006" (DOE/EIA-
0383(2006)); Washington, DC. (Available at: http://www.eia.doe.gov/oiaf/aeo/archive.html)
18 Energy Information Administration, 2008a. "Annual Energy Outlook 2008" (DOE/EIA-
0383(2008)); Washington, DC. (Available at: http://www.eia.doe.gov/oiaf/aeo/)
19 Energy Information Administration, 2008b. "International Energy Outlook 2008" (DOE/EIA-
0484(2008)); Washington, DC. (Available at: http://www.eia.doe.gov/oiaf/ieo/)
20 Regulation of Fuels and Fuel Additives: Fuel Quality Regulations for Highway Diesel Fuel
Sold in 1993 and Later Calendar Years, 55 Fed Reg 34120, August 21, 1990.
Standards of Performance for Stationary Compression Ignition Internal Combustion Engines,
71 Fed Reg 39154, July 11, 2006.
Control of Emissions of Air Pollution from Locomotives and Marine Compression-Ignition
Engines Less Than 30 Liters per Cylinder, 73 Fed Reg 25097, May 6, 2008.
Control of Emissions of Air Pollution From Nonroad Diesel Engines and Fuel 69 Fed Reg
38957, June 29, 2004.
Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine and Vehicle Standards
and Highway Diesel Fuel Sulfur Control Requirements 66 Fed Reg 5001, January 18, 2001.
Control of Air Pollution From New Motor Vehicles: Tier 2 Motor Vehicle Emissions Standards
and Gasoline Sulfur Control Requirements 65 Fed Reg 6697, February 10, 2000.
Acid Rain Program; General Provisions and Permits, Allowance System, Continuous
Emissions Monitoring, Excess Emissions and Administrative Appeals, 58 Fed Reg 3590,
January 11, 1993; Finding of Significant Contribution and Rulemaking for Certain States in
the Ozone Transport Assessment Group Region for Purposes of Reducing Regional Transport
of Ozone, 63 Fed Reg 57356, October 27, 1998.
Prevention of Significant Deterioration (PSD) and Nonattainment New Source Review (NSR):
Baseline Emissions Determination, Actual-to-Future-Actual Methodology, Plantwide
Applicability Limitations, Clean Units, Pollution Control Projects, 67 Fed Reg 80186,
December 31,2002
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CHAPTER 6: Cost-Benefit Analysis
6.1 Overview
This chapter presents our analysis of the health and environmental benefits that will occur
as a result of EPA's coordinated strategy to address emissions from Category 3 engines and
ocean-going vessels throughout the period from initial implementation through 2030. We
provide estimated costs for the entire coordinated strategy, including the Annex VI Tier II NOx
requirements and the EGA controls that will be mandatory for U.S. and foreign vessels through
the Act to Prevent Pollution from Ships. However, unlike the cost analysis, this benefits analysis
does not allocate benefits between the components of the program (the requirements in this rule
and the requirements that would apply through MARPOL Annex VI and EGA implementation).
This is because the benefits of the coordinated strategy will be fully realized only when the U.S.
EGA is in place and both U.S. and foreign vessels are required to use lower sulfur fuel and
operate their Tier 3 NOx controls while in the designated area, and therefore it makes more sense
to consider the benefits of the coordinated strategy as a whole.
The components of the coordinated strategy will apply stringent NOx and SOx standards
to virtually all vessels that affect U.S. air quality, and impacts on human health and welfare will
be substantial. As presented in Chapter 2, the coordinated strategy for controlling emissions
from Category 3 engines and ocean-going vessels is expected to provide very large reductions in
NOx (a precursor to ozone formation and secondarily-formed PM2.5), SOx (a precursor to
secondarily-formed PM^.s) and directly-emitted PM2.5. These pollutants contribute to on-land
concentrations of PM2.5 and ozone that cause harm to human health and the environment. This
chapter presents the reductions in adverse health impacts that can be expected to occur from the
adoption of a coordinated strategy to control ship emissions that includes implementation of the
proposed CAA standards and the EGA designation described in this RIA.
Exposure to ozone and PM2.5 is linked to adverse human health impacts such as
premature deaths as well as other important public health and environmental effects. The most
conservative premature mortality estimates (Pope et al., 2002 for PM2 5 and Bell et al., 2004 for
ozone)1'2 suggest that implementation of the coordinated strategy will reduce approximately
12,000 premature mortalities in 2030 and yield approximately $110 billion in total benefits. The
upper end of the premature mortality estimates (Laden et al., 2006 for PM2.5 and Levy et al.,
2005 for ozone)3'4 suggest that implementation of the coordinated strategy will increase the
estimate of avoided premature mortalities to approximately 31,000 in 2030 and yield
approximately $270 billion in total benefits.A Thus, even taking the most conservative premature
mortality assumptions, the health impacts of the coordinated strategy are clearly substantial.
The health impacts modeling presented in this chapter is based on peer-reviewed studies
of air quality and health and welfare effects associated with improvements in air quality. The
health impact estimates for the coordinated strategy are based on an analytical structure and
sequence consistent with health impacts analyses performed by the United States Environmental
A These benefits use a 3% discount rate. Using a 7% discount rate, the benefits are approximately 10% less.
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Chapter 6: Cost-Benefit Analysis
Protection Agency (EPA) for its recent analyses in support of the final Ozone National Ambient
Air Quality Standard (NAAQS) and the final PM NAAQS as well as all of its recent mobile
source emission control programs.5'6 For a more detailed discussion of the principles of health
impacts analysis used here, we refer the reader to those NAAQS documents.
To model the ozone and PM air quality impacts of the coordinated strategy, we used the
Community Multiscale Air Quality (CMAQ) model (see Chapter 2). The modeled ambient air
quality data serves as an input to the Environmental Benefits Mapping and Analysis Program
(BenMAP).B BenMAP is a computer program developed by the EPA that integrates a number of
the modeling elements used in previous analyses (e.g., interpolation functions, population
projections, health impact functions, valuation functions, analysis and pooling methods) to
translate modeled air concentration estimates into health effects incidence estimates and
monetized benefits estimates.
The range of total ozone- and PM-related benefits associated with the coordinated
strategy to control ship emissions is presented in Table 6-1. We present total benefits based on
the PM- and ozone-related premature mortality function used. The benefits ranges therefore
reflect the addition of each estimate of ozone-related premature mortality (each with its own row
in Table 6-1) to estimates of PM-related premature mortality. These estimates represent EPA's
preferred approach to characterizing the best estimate of benefits associated with the coordinated
strategy. As is the nature of Regulatory Impact Analyses (RIAs), the assumptions and methods
used to estimate air quality benefits evolve to reflect the Agency's most current interpretation of
the scientific and economic literature. This analysis, therefore, incorporates five important
changes from recent RIAs released by the Office of Transportation and Air Quality (OTAQ):
• The 2030 air quality modeling of the final coordinated strategy reflects air quality impacts
associated with an EGA boundary distance of 200 nm with global controls (set through IMO)
beyond the EGA boundary. For the proposal, however, the air quality modeling reflected
impacts associated with an EGA boundary distance of 100 nm with global controls beyond.
To estimate the 2030 benefits associated with a 200 nm EGA boundary in the proposal, we
transferred the relationship between modeled impacts between 100 nm and 200 nm EGA
boundaries observed in 2020. For each health endpoint and associated valuation, we
calculated a ratio based on the national-level estimate for the 200 nm and 100 nm scenario
and applied that to the related 2030 100 nm estimate. For the final RIA, we estimated
benefits based on the actual 2030 200 nm air quality modeling results. The net effect of this
change results in a small decrease in 2030 benefits compared to the proposal.
• For a period of time (2004-2008), the Office of Air and Radiation (OAR) valued mortality
risk reductions using a value of statistical life (VSL) estimate derived from a limited analysis
of some of the available studies. OAR arrived at a VSL using a range of $1 million to $10
million (2000$) consistent with two meta-analyses of the wage-risk literature. The $1
million value represented the lower end of the interquartile range from the Mrozek and
B Information on BenMAP, including downloads of the software, can be found at http://www.epa.gov/ttn/ecas/
benmodels.html.
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Regulatory Impact Analysis
Taylor (2002)7 meta-analysis of 33 studies and $10 million represented the upper end of the
interquartile range from the Viscusi and Aldy (2003)8 meta-analysis of 46 studies. The mean
estimate of $5.5 million (2000$)° was also consistent with the mean VSL of $5.4 million
estimated in the Kochi et al. (2006)9 meta-analysis. However, the Agency neither changed
its official guidance on the use of VSL in rule-makings nor subjected the interim estimate to
a scientific peer-review process through the Science Advisory Board (SAB) or other peer-
review group.
During this time, the Agency continued work to update its guidance on valuing mortality risk
reductions, including commissioning a report from meta-analytic experts to evaluate
methodological questions raised by EPA and the SAB on combining estimates from the
various data sources. In addition, the Agency consulted several times with the Science
Advisory Board Environmental Economics Advisory Committee (SAB-EEAC) on the issue.
With input from the meta-analytic experts, the SAB-EEAC advised the Agency to update its
guidance using specific, appropriate meta-analytic techniques to combine estimates from
unique data sources and different studies, including those using different methodologies (i.e.,
wage-risk and stated preference) (U.S. EPA-SAB, 2007).10
Until updated guidance is available, the Agency determined that a single, peer-reviewed
estimate applied consistently best reflects the SAB-EEAC advice it has received. Therefore,
the Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the
Guidelines for Preparing Economic Analyses (U.S. EPA, 2000) while the Agency continues
its efforts to update its guidance on this issue.0 This approach calculates a mean value across
VSL estimates derived from 26 labor market and contingent valuation studies published
between 1974 and 1991. The mean VSL across these studies is $6.3 million (2000$).E
The Agency is committed to using scientifically sound, appropriately reviewed evidence in
valuing mortality risk reductions and has made significant progress in responding to the
SAB-EEAC's specific recommendations. The Agency anticipates presenting results from
this effort to the SAB-EEAC in Winter 2009/2010 and that draft guidance will be available
shortly thereafter.
In recent analyses, OTAQ has estimated PM2 5-related benefits assuming that a threshold
exists in the PM-related concentration-response functions (at 10 |ig/m3) below which there
c In this analysis, we adjust the VSL to account for a different currency year (2006$) and to account for income
growth to 2020 and 2030. After applying these adjustments to the $5.5 million value, the VSL is $7.7m in 2020 and
$7.9 in 2030.
D In the (draft) update of the Economic Guidelines, EPA retained the VSL endorsed by the SAB with the
understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future.
Therefore, this report does not represent final agency policy. The 2000 guidelines can be downloaded here:
http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html, and the draft updated version (2008) of the
guidelines can be downloaded here: http://yosemite.epa.gov/ee/epa/eerm.nsf/vwRepNumLookup/EE-
0516?OpenDocument
E In this analysis, we adjust the VSL to account for a different currency year (2006$) and to account for income
growth to 2020 and 2030. After applying these adjustments to the $6.3 million value, the VSL is $8.9m in 2020 and
$9.1m in 2030.
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Chapter 6: Cost-Benefit Analysis
are no associations between exposure to PM2.5 and health impacts. For the benefits analysis
of the coordinated strategy, however, we have revised this assumption. EPA strives to use
the best available science to support our benefits analyses, and we recognize that
interpretation of the science regarding air pollution and health is dynamic and evolving.
Based on our review of the body of scientific literature, EPA applied the no-threshold model
in this analysis. EPA's draft Integrated Science Assessment/'0 which was recently reviewed
by EPA's Clean Air Scientific Advisory Committee,11'1 concluded that the scientific literature
consistently finds that a no-threshold log-linear model most adequately portrays the PM-
mortality concentration-response relationship while recognizing potential uncertainty about
the exact shape of the concentration-response function/ Although this document does not
represent final agency policy that has undergone the full agency scientific review process, it
provides a basis for reconsidering the application of thresholds in PM2.5 concentration-
response functions used in EPA's RIAs.K It is important to note that while CAS AC provides
advice regarding the science associated with setting the National Ambient Air Quality
Standards, typically other scientific advisory bodies provide specific advice regarding
benefits analysis.L Please see Section 6.4.1.3 of the RIA for more discussion of the treatment
of thresholds in this analysis.
F U.S. Environmental Protection Agency (U.S. EPA). Integrated Science Assessment for Paniculate Matter
(External Review Draft). National Center for Environmental Assessment, Research Triangle Park, NC.
EPA/600/R-08/139. December. Available on the Internet at
.
G U.S. Environmental Protection Agency (U.S. EPA). Integrated Science Assessment for Paniculate Matter (Second
External Review Draft). National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-
08/139B. July. Available on the Internet at .
H U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). Review of EPA's Integrated
Science Assessment for Paniculate Matter (First External Review Draft, December 2008). EPA-COUNCIL-09-008.
May. Available on the Internet at
.
1 U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). Consultation on EPA's
Paniculate Matter National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and Exposure
Assessment. EPA-COUNCIL-09-009. May. Available on the Internet at
.
1 It is important to note that uncertainty regarding the shape of the concentration-response function is conceptually
distinct from an assumed threshold. An assumed threshold (below which there are no health effects) is a
discontinuity, which is a specific example of non-linearity.
K The final PM ISA, which will have undergone the full agency scientific review process, is scheduled to be
completed in late December 2009.
L In the proposed Portland Cement RIA, EPA solicited comment on the use of the no-threshold model for benefits
analysis within the preamble of that proposed rule. The comment period for the Portland Cement proposed
NESHAP closed on September 4, 2009 (Docket ID No. EPA-HQ-OAR-2002-0051 available at
http://www.regulations.gov). EPA is currently reviewing those comments. U.S. Environmental Protection Agency.
(2009). Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants from the Portland
Cement Manufacturing Industry. Office of Air and Radiation. Retrieved on May 4, 2009, from
http://www.epa. gov/ttn/ecas/regdata/RIAs/portlandcementria_4-20-09.pdf
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Regulatory Impact Analysis
• For the coordinated strategy, we rely on two empirical (epidemiological) studies of the
relationship between ambient PM2.5 and premature mortality (the extended analyses of the
Harvard Six Cities study by Laden et al (2006) and the American Cancer Society (ACS)
cohort by Pope et al (2002)) to anchor our benefits analysis, though we also present the
PM2 s-related premature mortality benefits associated with the estimates supplied by the
expert elicitation as a sensitivity analysis. This approach was recently adopted in the
Portland Cement MACT RIA. Since 2006, EPA has calculated benefits based on these two
empirical studies and derived the range of benefits, including the minimum and maximum
results, from an expert elicitation of the relationship between exposure to PM2 5 and
premature mortality (Roman et al., 2008).u Using alternate relationships between PM2.5 and
premature mortality supplied by experts, higher and lower benefits estimates are plausible,
but most of the expert-based estimates have fallen between the two epidemiology-based
estimates (Roman et al., 2008). Assuming no threshold in the empirically-derived premature
mortality concentration response functions used in the analysis of the coordinated strategy,
only one expert falls below the empirically-derived range while two of the experts are above
this range (see Tables 6-5 and 6-6). Please refer to the Portland Cement MACT RIA for more
information about the preferred approach and the evolution of the treatment of threshold
assumptions within EPA's regulatory analyses.
• The range of ozone benefits associated with the coordinated strategy is estimated based on
risk reductions derived from several sources of ozone-related mortality effect estimates. This
analysis presents six alternative estimates for the association based upon different functions
reported in the scientific literature. We use three multi-city studies,12'13'14 including the Bell,
2004 National Morbidity, Mortality, and Air Pollution Study (NMMAPS) that was used as
the primary basis for the risk analysis in the ozone Staff Paper15 and reviewed by the Clean
Air Science Advisory Committee (CASAC).16 We also use three studies that synthesize
ozone mortality data across a large number of individual studies.17'18'19 This approach is
consistent with recommendations provided by the NRC in their ozone mortality report (NRC,
2008),20 "The committee recommends that the greatest emphasis be placed on estimates from
new systematic multicity analyses that use national databases of air pollution and mortality,
such as in the NMMAPS, without excluding consideration of meta-analyses of previously
published studies." The NRC goes on to note that there are uncertainties within each study
that are not fully captured by this range of estimates.
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Chapter 6: Cost-Benefit Analysis
Table 6-1 Estimated 2030 Monetized PM-and Ozone-Related Health Benefits of a Coordinated U.S. Strategy
to Control Ship Emissions"
2030 TOTAL OZONE AND PM BENEFITS - PM MORTALITY DERIVED FROM AMERICAN
CANCER SOCIETY ANALYSIS AND SIX-CITIES ANALYSISA
Premature Ozone
Mortality Function
Multi-city analyses
Meta-analyses
Reference
Bell etal, 2004
Huang et al., 2005
Schwartz, 2005
Bell etal., 2005
Ito et al., 2005
Levy et al., 2005
Total Benefits
(Billions, 2006$, 3%
Discount Rate)b'c
$110 -$260
$110 -$260
$110 -$260
$110 -$260
$110 -$270
$110 -$270
Total Benefits
(Billions, 2006$, 7%
Discount Rate) b'c
$99 - $240
$100 -$240
$100 - $240
$100 - $240
$110 -$240
$110 -$240
Notes:
"Total includes premature mortality-related and morbidity-related ozone and PM25 benefits. Range was
developed by adding the estimate from the ozone premature mortality function to the estimate of PM25-related
premature mortality derived from either the ACS study (Pope et al., 2002) or the Six-Cities study (Laden et al.,
2006).
b Note that total benefits presented here do not include a number of unqualified benefits categories. A detailed
listing of unqualified health and welfare effects is provided in Table 6-2.
0 Results reflect the use of both a 3 and 7 percent discount rate, as recommended by EPA's Guidelines for
Preparing Economic Analyses and OMB Circular A-4. Results are rounded to two significant digits for ease of
presentation and computation.
The benefits in Table 6-1 include all of the human health impacts we are able to quantify
and monetize at this time. However, the full complement of human health and welfare effects
associated with PM and ozone remain unquantified because of current limitations in methods or
available data. We have not quantified a number of known or suspected health effects linked
with ozone and PM for which appropriate health impact functions are not available or which do
not provide easily interpretable outcomes (i.e., changes in heart rate variability). Additionally,
we are unable to quantify a number of known welfare effects, including reduced acid and
particulate deposition damage to cultural monuments and other materials, and environmental
benefits due to reductions of impacts of eutrophication in coastal areas. These are listed in Table
6-2. As a result, the health benefits quantified in this chapter are likely underestimates of the
total benefits attributable to the implementation of the coordinated strategy to control ship
emissions.
6-7
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Regulatory Impact Analysis
Table 6-2 Unqualified and Non-Monetized Potential Effects of a Coordinated U.S. Strategy to Control Ship
Emissions
POLLUTANT/
EFFECTS
EFFECTS NOT INCLUDED IN ANALYSIS - CHANGES IN:
Ozone Health
Chronic respiratory damage
Premature aging of the lungsb
Non-asthma respiratory emergency room visits
Exposure to UVb (+/-)e
Ozone Welfare
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
PM Health0
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
PM Welfare
Residential and recreational visibility in non-Class I areas
Soiling and materials damage
Damage to ecosystem functions
Exposure to UVb (+/-)e
Nitrogen and Sulfate
Deposition Welfare
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
CO Health
Behavioral effects
HC/Toxics Health
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)
6-8
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Chapter 6: Cost-Benefit Analysis
HC/Toxics Welfare
Direct toxic effects to animals
Bioaccumulation in the food chain
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.
However, the PM mortality results derived from the expert elicitation do take into account premature mortality
effects of short term exposures.
e May result in benefits or disbenefits.
f Many of the key hydrocarbons related to this rule are also hazardous air pollutants listed in the Clean Air Act.
6.2 Quantified Human Health Impacts
Tables 6-3 and 6-4 present the annual PM2.5 and ozone health impacts in the 48
contiguous U.S. states associated with the coordinated strategy for both 2020 and 2030. For each
endpoint presented in Tables 6-3 and 6-4, we provide both the mean estimate and the 90%
confidence interval.
Using EPA's preferred estimates, based on the ACS and Six-Cities studies and no
threshold assumption in the model of mortality, we estimate that the coordinated strategy will
result in between 5,300 and 14,000 cases of avoided PM2.s-related premature deaths annually in
2020 and between 12,000 and 30,000 avoided premature deaths annually in 2030. As a
sensitivity analysis, when the range of expert opinion is used, we estimate between 1,900 and
18,000 fewer premature mortalities in 2020 and between 4,300 and 40,000 fewer premature
mortalities in 2030.
The range of ozone benefits associated with the coordinated strategy is based on risk
reductions estimated using several sources of ozone-related mortality effect estimates. This
analysis presents six alternative estimates for the association based upon different functions
reported in the scientific literature, derived from both the National Morbidity, Mortality, and Air
Pollution Study (NMMAPS) (Bell et al., 2004) and from a series of recent meta-analyses (Bell et
al., 2005, Ito et al., 2005, and Levy et al., 2005). This approach is not inconsistent with
recommendations provided by the NRC in their recent report (NRC, 2008) on the estimation of
ozone-related mortality risk reductions, "The committee recommends that the greatest emphasis
be placed on estimates from new systematic multicity analyses that use national databases of air
pollution and mortality, such as in the NMMAPS, without excluding consideration of meta-
analyses of previously published studies."
6-9
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Regulatory Impact Analysis
For ozone-related premature mortality, we estimate a range of between 61 to 280 fewer
premature mortalities as a result of the coordinated strategy in 2020 and between 210 to 920 in
2030. The increase in annual benefits from 2020 to 2030 reflects additional emission reductions
from coordinated strategy, as well as increases in total population and the average age (and thus
baseline mortality risk) of the population.
Following these tables, we also provide a more comprehensive presentation of the
distributions of incidence generated using the available information from empirical studies and
expert elicitation. Tables 6-5 and 6-6 present the distributions of the reduction in PM2.5-related
premature mortality based on the C-R distributions provided by each expert, as well as that from
the data-derived health impact functions, based on the statistical error associated with the ACS
study (Pope et al., 2002) and the Six-cities study (Laden et al., 2006). The 90% confidence
interval for each separate estimate of PM-related mortality is also provided.
In 2020, the effect estimates of nine of the twelve experts included in the elicitation panel
fall within the empirically-derived range provided by the ACS and Six-Cities studies. Only one
expert falls below this range, while two of the experts are above this range. This same
relationship occurs in 2030, as well. Although the overall range across experts is summarized in
these tables, the full uncertainty in the estimates is reflected by the results for the full set of 12
experts. The twelve experts' judgments as to the likely mean effect estimate are not evenly
distributed across the range illustrated by arraying the highest and lowest expert means.
6-10
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Chapter 6: Cost-Benefit Analysis
Table 6-3 Estimated PM2.5-Related Health Impacts Associated with a Coordinated U.S. Strategy to Control
Ship Emissions"
Health Effect
Premature Mortality - Derived from Epidemiology
Literature13
Adult, age 30+, ACS Cohort Study (Pope et al., 2002)
Adult, age 25+, Six-Cities Study (Laden et al., 2006)
Infant, age <1 year (Woodruff et al., 1997)
Chronic bronchitis (adult, age 26 and over)
Non-fatal myocardial infarction (adult, age 18 and
over)
Hospital admissions - respiratory (all ages)0
Hospital admissions - cardiovascular (adults, age >18)d
Emergency room visits for asthma (age 18 years and
younger)
Acute bronchitis, (children, age 8-12)
Lower respiratory symptoms (children, age 7-14)
Upper respiratory symptoms (asthmatic children, age
9-18)
Asthma exacerbation (asthmatic children, age 6-18)
Work loss days
Minor restricted activity days (adults age 18-65)
2020 Annual Reduction in
Ship-Related Incidence
(5*% - 95th%ile)
5,300
(2,100-8,500)
14,000
(7,400 - 20,000)
20
(0-55)
3,800
(700 - 6,900)
8,800
(3,200 - 14,000)
1,200
(590 - 1,800)
2,700
(2,000 - 3,200)
3,500
(2,000 - 4,900)
8,500
(0 - 17,000)
100,000
(49,000 - 150,000)
77,000
(24,000 - 130,000)
95,000
(10,000-260,000)
720,000
(630,000-810,000)
4,300,000
(3,600,000-4,900,000)
2030 Annual Reduction in
Ship-Related Incidence
(5tho/o . 95tho/oile)
12,000
(4,700 - 19,000)
30,000
(17,000-44,000)
34
(0-93)
8,100
(1,500 - 14,000)
20,000
(7,600 - 33,000)
2,700
1,300-4,000)
6,600
(4,700 - 7,700)
7,300
(4,300 - 10,000)
17,000
(0 - 35,000)
210,000
(100,000-310,000)
160,000
(50,000 - 270,000)
200,000
(22,000 - 550,000)
1,400,000
(1,300,000 - 1,600,000)
8,500,000
(7,200,000 - 9,800,000)
Notes:
a Incidence is rounded to two significant digits. Estimates represent incidence within the 48 contiguous United States.
b PM-related adult mortality based upon the American Cancer Society (ACS) Cohort Study (Pope et al., 2002) and the Six-Cities
Study (Laden et al., 2006). Note that these are two alternative estimates of adult mortality and should not be summed. PM-
related infant mortality based upon a study by Woodruff, Grillo, and Schoendorf, (1997).
0 Respiratory hospital admissions for PM include admissions for chronic obstructive pulmonary disease (COPD), pneumonia and
asthma.
d Cardiovascular hospital admissions for PM include total cardiovascular and subcategories for ischemic heart disease,
dysrhythmias, and heart failure.
6-11
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Regulatory Impact Analysis
Table 6-4 Estimated Ozone-Related Health Impacts Associated with a Coordinated U.S. Strategy to Control
Ship Emissions"
Health Effect
Premature Mortality, All agesb
Multi-City Analyses
Bell et al. (2004) - Non-accidental
Huang et al. (2005) - Cardiopulmonary
Schwartz (2005) - Non-accidental
Meta-analyses:
Bell et al. (2005) - All cause
Ito et al. (2005) - Non-accidental
Levy et al. (2005) - All cause
Hospital admissions- respiratory causes (adult,
65 and older)0
Hospital admissions -respiratory causes
(children, under 2)
Emergency room visit for asthma (all ages)
Minor restricted activity days (adults, age 18-
65)
School absence days
2020 Annual Reduction in Ship-
Related Incidence
(5*% - 95th%ile)
61
(23 - 98)
100
(43 - 160)
93
(34 - 150)
200
(100-290)
270
(170-370)
280
(200 - 360)
470
(46 - 830)
380
(180-590)
210
(0 - 550)
360,000
(160,000 - 570,000)
130,000
(51,000-190,000)
2030 Annual Reduction in Ship-
Related Incidence
(5tho/o . 95tho/oile)
210
(70 - 340)
350
(130-570)
320
(100-530)
660
(320 - 1,000)
920
(560 - 1,300)
920
(640 - 1,200)
1,900
(120-3,300)
1,200
(490 - 1,900)
690
(0 - 1,800)
1,100,000
(430,000 - 1,700,000)
420,000
(150,000-630,000)
Notes:
a Incidence is rounded to two significant digits. Estimates represent incidence within the 48 contiguous United States.
b Estimates of ozone-related premature mortality are based upon incidence estimates derived from several alternative studies: Bell
et al. (2004); Huang et al. (2005); Schwartz (2005); Bell et al. (2005); Ito et al. (2005); Levy et al. (2005). Lhe estimates of
ozone-related premature mortality should therefore not be summed.
0 Respiratory hospital admissions for ozone include admissions for all respiratory causes and subcategories for COPD and
pneumonia.
6-12
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Chapter 6: Cost-Benefit Analysis
Table 6-5 Results of Application of Expert Elicitation: Annual Reductions in Premature Mortality in
2020 Associated with a Coordinated U.S. Strategy to Control Ship Emissions
Source of Mortality
Estimate
Pope et al. (2002)
Laden et al. (2006)
Expert A
Expert B
Expert C
Expert D
Expert E
Expert F
Expert G
Expert H
Expert I
Expert J
Expert K
Expert L
2020 Primary Option
5th Percentile
2,100
7,400
2,600
1,400
2,000
1,600
9,000
6,800
0
30
1,700
2,600
0
1,100
Mean
5,300
14,000
14,000
11,000
11,000
7,600
18,000
9,800
6,300
8,100
11,000
8,700
1,900
7,500
95th Percentile
8,500
20,000
26,000
23,000
23,000
12,000
27,000
14,000
12,000
18,000
19,000
19,000
8,800
15,000
Table 6-6 Results of Application of Expert Elicitation: Annual Reductions in Premature Mortality in
2030 Associated with a Coordinated U.S. Strategy to Control Ship Emissions
Source of Mortality
Estimate
Pope et al. (2002)
Laden et al. (2006)
Expert A
Expert B
Expert C
Expert D
Expert E
Expert F
Expert G
Expert H
Expert I
Expert J
Expert K
Expert L
2030 Primary Option
5th Percentile
4,700
17,000
6,000
3,200
4,400
3,600
20,000
16,000
0
67
3,900
5,900
0
2,500
Mean
12,000
30,000
32,000
24,000
24,000
17,000
40,000
22,000
14,000
18,000
24,000
20,000
4,300
17,000
95th Percentile
19,000
44,000
58,000
52,000
52,000
28,000
60,000
32,000
26,000
41,000
43,000
43,000
20,000
33,000
6-13
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Regulatory Impact Analysis
6.3 Monetized Benefits
Monetized values for each quantified health endpoint are presented in Table 6-7. For
each endpoint presented in Table 6-7, we provide both the mean estimate and the 90%
confidence interval. Total aggregate monetized benefits are presented in Tables 6-8 and 6-9
using either a 3 percent or 7 percent discount rate, respectively. All of the monetary benefits are
in constant-year 2006 dollars.
In addition to omitted benefits categories such as air toxics and various welfare effects,
not all known PM2 5- and ozone-related health and welfare effects could be quantified or
monetized. The estimate of total monetized health benefits of the coordinated strategy is thus
equal to the subset of monetized PM2.s- and ozone-related health benefits we are able to quantify
plus the sum of the nonmonetized health and welfare benefits. We believe the total benefits are
therefore likely underestimated.
Our estimate of total monetized benefits in 2020 for the coordinated strategy, using the
ACS and Six-Cities PM mortality studies and the range of ozone mortality assumptions, is
between $47 billion and $110 billion, assuming a 3 percent discount rate, or between $42 billion
and $100 billion, assuming a 7 percent discount rate. In 2030, we estimate the monetized
benefits to be between $110 billion and $270 billion, assuming a 3 percent discount rate, or
between $99 billion and $240 billion, assuming a 7 percent discount rate. The monetized benefit
associated with reductions in the risk of both ozone- and PM2.5-related premature mortality
ranges between 90 to 98 percent of total monetized health benefits, in part because we are unable
to quantify a number of benefits categories (see Table 6-2). These unquantified benefits may be
substantial, although their magnitude is highly uncertain.
The next largest benefit is for reductions in chronic illness (chronic bronchitis and
nonfatal heart attacks), although this value is more than an order of magnitude lower than for
premature mortality. Hospital admissions for respiratory and cardiovascular causes, minor
restricted activity days, and work loss days account for the majority of the remaining benefits.
The remaining categories each account for a small percentage of total benefit; however, they
represent a large number of avoided incidences affecting many individuals. A comparison of the
incidence table to the monetary benefits table reveals that there is not always a close
correspondence between the number of incidences avoided for a given endpoint and the
monetary value associated with that endpoint. For example, there are over 100 times more work
loss days than PM-related premature mortalities (based on the ACS study), yet work loss days
account for only a very small fraction of total monetized benefits. This reflects the fact that
many of the less severe health effects, while more common, are valued at a lower level than the
more severe health effects. Also, some effects, such as hospital admissions, are valued using a
proxy measure of willingness-to-pay (e.g., cost-of-illness). As such, the true value of these
effects may be higher than that reported here.
6-14
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Chapter 6: Cost-Benefit Analysis
Table 6-7 Estimated Monetary Value in Reductions in Incidence of Health and Welfare Effects (in millions of
2006$) a'b
PM2 s-Related Health Effect
Premature Mortality
Epidemiology
Studies0'4
Adult, age 30+ - ACS study
(Pope etal., 2002)
3% discount rate
7% discount rate
Adult, age 25+ - Six-cities study
(Laden et al., 2006)
3% discount rate
7% discount rate
Infant Mortality, <1 year -
(Woodruff etal. 1997)
Chronic bronchitis (adults, 26 and over)
Non-fatal acute myocardial infarctions
3% discount rate
7% discount rate
Hospital admissions for respiratory causes
Hospital admissions for cardiovascular causes
Emergency room visits for asthma
Acute bronchitis (children, age 8-12)
Lower respiratory symptoms (children, 7-14)
Upper respiratory symptoms (asthma, 9-11)
Asthma exacerbations
Work loss days
Minor restricted-activity days (MRADs)
2020
2030
Estimated Mean Value of Reductions
(5th and 95th %ile)
$43,000
($5,000 -$110,000)
$38,000
($4,500 -$100,000)
$110,000
($14,000 -$270,000)
$98,000
($13,000 -$250,000)
$180
($0 - $670)
$1,900
($140 -$6,500)
$960
($170 -$2,300)
$930
($160 -$2,300)
$17
($8.4 - $25)
$76
($48 -$110)
$1.3
($0.70 -$1.9)
$0.63
($0 - $1.6)
$2.0
($0.75 -$3.7)
$2.4
($0.65 - $5.3)
$5.1
($0.51 -$15)
$110
($94 -$120)
$270
($150 -$390)
$99,000
($12,000 -$260,000)
$89,000
($11,000 -$230,000)
$250,000
($33,000 - $630,000)
$230,000
($30,000 - $570,000)
$310
($0-$ 1,200)
$4,100
($320 -$14,000)
$2,700
($460 - $6,700)
$2,600
($430 - $6,600)
$39
($19 - $57)
$180
($120 - $250)
$2.7
($1.5 -$4.1)
$1.3
($0-$3.2)
$4.1
($1.6 - $7.6)
$5.0
($1.4 -$11)
$11
($1.1 -$32)
$220
($190 - $250)
$540
($3 10 -$780)
Ozone-related Health Effect
Premature Mortality, All ages -
Derived from Multi-city
analyses
Premature Mortality, All ages -
Derived from Meta-analyses
Bell et al., 2004
Huang et al., 2005
Schwartz, 2005
Bell etal., 2005
$540
($63 -$1,400)
$910
($110 -$2,300)
$830
($94 - $2,200)
$1,700
($220 - $4,400)
$1,800
($2 10 -$4,900)
$3,100
($360 - $8,200)
$2,800
($3 10 -$7,600)
$5,800
($740 -$15,000)
6-15
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Regulatory Impact Analysis
Ito et al., 2005
Levy etal., 2005
Hospital admissions- respiratory causes (adult, 65 and
older)
Hospital admissions- respiratory causes (children, under
2)
Emergency room visit for asthma
(all ages)
Minor restricted activity days (adults, age 18-65)
School absence days
$2,400
($330 - $5,900)
$2,400
($340 - $5,900)
$11
($1.1 -$20)
$3.8
($1.8 -$5.9)
$0.08
($0.03 - $0.20)
$23
($9.8 -$41)
$12
($4.6 -$17)
$8,200
($1,100 - $20,000)
$8,200
($1,100 - $20,000)
$45
($2.8 - $79)
$12
($4.9 -$19)
$0.25
($0 - $0.63)
$69
($25 - $120)
$37
($13 - $57)
Notes:
a Monetary benefits are rounded to two significant digits for ease of presentation and computation. PM and ozone
benefits are nationwide.
b Monetary benefits adjusted to account for growth in real GDP per capita between 1990 and the analysis year (2020
or 2030)
0 Valuation assumes discounting over the SAB recommended 20 year segmented lag structure. Results reflect the
use of 3 percent and 7 percent discount rates consistent with EPA and OMB guidelines for preparing economic
analyses (EPA, 2000; OMB, 2003).
d The valuation of adult premature mortality derived from the epidemiology literature is not additive. Rather, the
valuations represent a range of possible mortality benefits.
6-16
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Chapter 6: Cost-Benefit Analysis
Table 6-8 Total Monetized Benefits Associated with a Coordinated U.S. Strategy to Control Ship Emissions
3% Discount Rate
Total Ozone and PM Benefits (billions, 2006$) -
PM Mortality Derived from the ACS and Six Cities Studies
2020
Ozone
Mortality
Function
Multi-city
Meta-analysis
PM
Reference
Bell et al,
2004
Huang et al.,
2005
Schwartz,
2005
Bell et al.,
2005
Ito et al., 2005
Levy etal.,
2005
Total
Mean Total
Benefits
$47 -$110
$47 -$110
$47 -$110
$48 -$110
$48 -$110
$48 -$110
2030
Ozone
Mortality
Function
Multi-city
Meta-analysis
Ozone and PM Benefits (billions,
Reference
Bell et al.,
2004
Huang et al.,
2005
Schwartz,
2005
Bell et al.,
2005
Ito et al., 2005
Levy etal.,
2005
2006$) -
Mean Total
Benefits
$110 -$260
$110 -$260
$110 -$260
$110 -$260
$110 -$270
$110 -$270
Mortality Derived from Expert Elicitation (Lowest and Highest Estimate)
2020
Ozone
Mortality
Function
Multi-city
Meta-analysis
Reference
Bell etal.,
2004
Huang et al.,
2005
Schwartz,
2005
Bell etal.,
2005
Ito et al., 2005
Levy etal.,
2005
Mean Total
Benefits
$19 -$150
$19 -$150
$19 -$150
$20 - $150
$21 -$150
$21 -$150
2030
Ozone
Mortality
Function
Multi-city
Meta-analysis
Reference
Bell et al.,
2004
Huang et al.,
2005
Schwartz,
2005
Bell et al.,
2005
Ito et al., 2005
Levy etal.,
2005
Mean Total
Benefits
$45 . $340
$47 . $340
$46 - $340
$49 - $340
$52 - $350
$52 - $350
6-17
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Regulatory Impact Analysis
Table 6-9 Total Monetized Benefits Associated with a Coordinated U.S. Strategy to Control Ship Emissions
7% Discount Rate
Total Ozone and PM Benefits (billions, 2006$) -
PM Mortality Derived from the ACS and Six Cities Studies
2020
Ozone
Mortality
Function
Multi-city
Meta-analysis
PM
Reference
Bell et al,
2004
Huang et al.,
2005
Schwartz,
2005
Bell et al.,
2005
Ito et al., 2005
Levy etal.,
2005
Total
Mean Total
Benefits
$42 - $100
$43 - $100
$43 - $100
$44 - $100
$44 - $100
$44 - $100
2030
Ozone
Mortality
Function
Multi-city
Meta-analysis
Ozone and PM Benefits (billions,
Reference
Bell et al.,
2004
Huang et al.,
2005
Schwartz,
2005
Bell et al.,
2005
Ito et al., 2005
Levy etal.,
2005
2006$) -
Mean Total
Benefits
$99 - $240
$100 -$240
$100 -$240
$100 -$240
$110 -$240
$110 -$240
Mortality Derived from Expert Elicitation (Lowest and Highest Estimate)
2020
Ozone
Mortality
Function
Multi-city
Meta-analysis
Reference
Bell etal.,
2004
Huang et al.,
2005
Schwartz,
2005
Bell etal.,
2005
Ito et al., 2005
Levy etal.,
2005
Mean Total
Benefits
$18 -$130
$18 -$130
$18 -$130
$19 -$130
$19 -$140
$19 -$140
2030
Ozone
Mortality
Function
Multi-city
Meta-analysis
Reference
Bell et al.,
2004
Huang et al.,
2005
Schwartz,
2005
Bell et al.,
2005
Ito et al., 2005
Levy etal.,
2005
Mean Total
Benefits
$42 -$310
$43 -$310
$43 -$310
$46 -$310
$48 -$310
$48 -$310
6.4 Methodology
6.4.1 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.
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Chapter 6: Cost-Benefit Analysis
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.
Section 4.2.2 describes the ozone and PM air quality inputs to the health impact functions.
6.4.1.1 Potentially Affected Populations
The starting point for estimating the size of potentially affected populations is the 2000
U.S. Census block level dataset.21 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 2020 using growth
factors based on economic projections.22
6.4.1.2 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
Documents23'24 and the World Health Organization's 2003 and 200425'26 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
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 6-10 lists the health
endpoints included in this analysis.
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Regulatory Impact Analysis
Table 6-10 Ozone- and PM-Related Health Endpoints
ENDPOINT
POLLUTANT
STUDY
STUDY POPULATION
Premature Mortality
Premature mortality -
daily time series
Premature mortality
— cohort study, all-
cause
Premature mortality,
total exposures
Premature mortality
— all-cause
03
PM25
PM25
PM25
Multi-city
Bell et al (2004) (NMMAPS study)27 - Non-
accidental
Huang et al (2005)28 - Cardiopulmonary
Schwartz (2005)29 - Non-accidental
Meta-analyses:
Bell et al (2005)30 - All cause
Ito et al (2005)31 - Non-accidental
Levy et al (2005)32 - All cause
Pope et al. (2002)33
Laden et al. (2006)34
Expert Elicitation (lEc, 2006)35
Woodruff etal. (1997)36
All ages
>29 years
>25 years
>24 years
Infant (<1 year)
Chronic Illness
Chronic bronchitis
Nonfatal heart attacks
PM25
PM25
Abbey etal. (1995)37
Peters etal. (200 1)38
>26 years
Adults (>1 8 years)
Hospital Admissions
Respiratory
Cardiovascular
03
PM25
PM25
PM25
PM25
PM25
PM25
Pooled estimate:
Schwartz (1995) - ICD 460-519 (all resp)39
Schwartz (1994a; 1994b) - ICD 480-486
(pneumonia)40'41
Moolgavkar et al. (1997) - ICD 480-487
(pneumonia)42
Schwartz (1994b) - ICD 491-492, 494-496
(COPD)
Moolgavkar et al. (1997) - ICD 490-496
(COPD)
Burnett etal. (200 1)43
Pooled estimate:
Moolgavkar (2003)— ICD 490-496 (COPD)44
Ito (2003)— ICD 490-496 (COPD)45
Moolgavkar (2000)— ICD 490-496 (COPD)46
Ito (2003)— ICD 480-486 (pneumonia)
Sheppard (2003)— ICD 493 (asthma)47
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)
>64 years
<2 years
>64 years
20-64 years
>64 years
<65 years
>64 years
20-64 years
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Chapter 6: Cost-Benefit Analysis
Asthma-related ER
visits
Asthma-related ER
visits (con't)
03
PM25
Pooled estimate:
Jaffe et al (2003)48
Peel et al (2005)49
Wilson et al (2005)50
Norrisetal. (1999)51
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)52
Popeetal. (199 1)53
Schwartz and Neas (2000)54
Pooled estimate:
Ostro et al. (200 1)55 (cough, wheeze and
shortness of breath)
Vedal et al. (1998) (cough)
Ostro (1987)57
Pooled estimate:
Gilliland et al. (200 1)58
Chenetal. (2000)59
Ostro and Rothschild (1989)60
Ostro and Rothschild (1989)
8-12 years
Asthmatics, 9-11
years
7-14 years
6-18 years3
18-65 years
5-17 yearsb
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, 1990—2020. 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.
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.61'62
6.4.1.3 Treatment of Potential Thresholds in PM2.5-Related Health Impact Functions
In recent analyses, OTAQ has estimated PM2.s-related benefits assuming that a threshold
exists in the PM-related concentration-response functions (at 10 |ig/m3) below which there are no
associations between exposure to PM2.5 and health impacts. For the benefits analysis of the
coordinated strategy, however, we have revised this assumption. As explained in the recently
published Portland Cement MACT RIA, EPA's preferred benefits estimation approach assumes
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Regulatory Impact Analysis
a no-threshold model that calculates incremental benefits down to the lowest modeled PM2.5 air
quality levels.
EPA strives to use the best available science to support our benefits analyses, and we
recognize that interpretation of the science regarding air pollution and health is dynamic and
evolving. Based on our review of the body of scientific literature, EPA applied the no-threshold
model in this analysis. EPA's draft Integrated Science Assessment,M'N which was recently
reviewed by EPA's Clean Air Scientific Advisory Committee,0'1" concluded that the scientific
literature consistently finds that a no-threshold log-linear model most adequately portrays the
PM-mortality concentration-response relationship while recognizing potential uncertainty about
the exact shape of the concentration-response function.*2 Although this document does not
represent final agency policy that has undergone the full agency scientific review process, it
provides a basis for reconsidering the application of thresholds in PM2.5 concentration-response
functions used in EPA's RIAs.R It is important to note that while CAS AC provides advice
regarding the science associated with setting the National Ambient Air Quality Standards,
typically other scientific advisory bodies provide specific advice regarding benefits analysis.8
This approach reflects EPA's most current interpretation of the scientific literature on PM2.5 and
mortality. Please refer to the proposed Portland Cement MACT RIA for a description of the
history of the treatment of thresholds in our analyses.63
M U.S. Environmental Protection Agency (U.S. EPA). Integrated Science Assessment for Paniculate Matter
(External Review Draft). National Center for Environmental Assessment, Research Triangle Park, NC.
EPA/600/R-08/139. December. Available on the Internet at
.
N U.S. Environmental Protection Agency (U.S. EPA). Integrated Science Assessment for Paniculate Matter (Second
External Review Draft). National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-
08/139B. July. Available on the Internet at .
0 U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). Review of EPA's Integrated
Science Assessment for Paniculate Matter (First External Review Draft, December 2008). EPA-COUNCIL-09-008.
May. Available on the Internet at
.
p U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). Consultation on EPA's
Paniculate Matter National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and Exposure
Assessment. EPA-COUNCIL-09-009. May. Available on the Internet at
.
Q It is important to note that uncertainty regarding the shape of the concentration-response function is conceptually
distinct from an assumed threshold. An assumed threshold (below which there are no health effects) is a
discontinuity, which is a specific example of non-linearity.
R The final PM ISA, which will have undergone the full agency scientific review process, is scheduled to be
completed in late December 2009.
s In the proposed Portland Cement RIA, EPA solicited comment on the use of the no-threshold model for benefits
analysis within the preamble of that proposed rule. The comment period for the Portland Cement proposed
NESHAP closed on September 4, 2009 (Docket ID No. EPA-HQ-OAR-2002-0051 available at
http://www.regulations.gov). EPA is currently reviewing those comments. U.S. Environmental Protection Agency.
(2009). Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants from the Portland
Cement Manufacturing Industry. Office of Air and Radiation. Retrieved on May 4, 2009, from
http://www.epa. gov/ttn/ecas/regdata/RIAs/portlandcementria_4-20-09.pdf
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Chapter 6: Cost-Benefit Analysis
As can be seen in Table 6-11, we conducted a sensitivity analysis for premature
mortality, with alternative thresholds at 3 |ig/m3 (the "background," or no-threshold,
assumption), 7.5 |ig/m3, 10 |ig/m3,12 |ig/m3, and 14 |ig/m3. By replacing the no-threshold
assumption in the ACS premature mortality function with a 10 |ig/m3 threshold model, the
number of avoided incidences of premature mortality would decrease by approximately 40
percent.
Table 6-11 PM-Related Mortality Benefits Associated with a Coordinated U.S. Strategy to Control Ship
Emissions: Threshold Sensitivity Analysis Using the ACS Study (Pope et al., 2002)a
Level of
Assumed
Threshold
14 ug/m3
12 ug/m3
10 ug/m3 c
7.5 ug/m3
3 ug/m3 e
PM Mortality Incidence
2020
1,800
2,100
3,400
4,500
5,300
2030
4,600
5,000
7,500
10,000
12,000
Notes:
a Note that this table only presents the effects of a threshold on PM-
related mortality incidence based on the ACS study.
b Alternative annual PM NAAQS.
0 Previous threshold assumption
d SAB-HES (2004)86
e NAS (2002)87
6.4.2 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 ($100/0.0001 change in risk).
WTP estimates generally are not available for some health effects, such as hospital
admissions. In these cases, we used the cost of treating or mitigating the effect as a primary
estimate. These cost-of-illness (COI) estimates generally understate the true value of reducing
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Regulatory Impact Analysis
the risk of a health effect, because they reflect the direct expenditures related to treatment, but
not the value of avoided pain and suffering (Harrington and Portney, 1987; Berger, 1987). We
provide unit values for health endpoints (along with information on the distribution of the unit
value) in Table 6-12. All values are in constant year 2006 dollars, adjusted for growth in real
income out to 2020 and 2030 using projections provided by Standard and Poor's. Economic
theory argues that WTP for most goods (such as environmental protection) will increase if real
income increases. Many of the valuation studies used in this analysis were conducted in the late
1980s and early 1990s. Because real income has grown since the studies were conducted,
people's willingness to pay for reductions in the risk of premature death and disease likely has
grown as well. We did not adjust cost of illness-based values because they are based on current
costs. Similarly, we did not adjust the value of school absences, because that value is based on
current wage rates. For details on valuation estimates for PM-related endpoints, see the 2006
PM NAAQS RIA. For details on valuation estimates for ozone-related endpoints, see the 2008
Ozone NAAQS RIA.
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Chapter 6: Cost-Benefit Analysis
Table 6-12 Unit Values Used for Economic Valuation of Health Endpoints (2000$)a
Health Endpoint
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
2020 Income
Levelb
2030 Income
Levelb
Derivation of Estimates
Premature Mortality (Value of a
Statistical Life): PM25- and
Ozone-related
$6,320,000
$7,590,000
$7,800,000
EPA currently recommends a default central VSL of $6.3 million
based on a Weibull distribution fitted to twenty-six published VSL
estimates (5 contingent valuation and 21 labor market studies). The
underlying studies, the distribution parameters, and other useful
information are available in Appendix B of EPA's current Guidelines
for Preparing Economic Analyses. The guidelines can be accessed
at: http://yosemite.epa.gov/ee/epa/eermfile.nsf/vwAN/EE-0516-
01 .pdf/$File/EE-0516-01 .pdf
Chronic Bronchitis (CB)
$340,000
$420,000
$430,000
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., [1991] ) 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.
Nonfatal Myocardial Infarction
(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
Age 66 and over
$66,902
$74,676
$78,834
$140,649
$66,902
$65,293
$73,149
$76,871
$132,214
$65,293
$66,902
$74,676
$78,834
$140,649
$66,902
$65,293
$73,149
$76,871
$132,214
$65,293
$66,902
$74,676
$78,834
$140,649
$66,902
$65,293
$73,149
$76,871
$132,214
$65,293
Age-specific cost-of-illness values reflect lost earnings and direct
medical costs over a 5-year period following a nonfatal MI. L0<;t
earnings estimates are based on Cropper and Krupnick (1990).
Direct medical costs are based on simple average of estimates from
Russell et al. (1998)66 and Wittels et al. (1990).67
Lost earnings:
Cropper and Krupnick (1990). Present discounted value of 5 years
of lost earnings:
age of onset: , -,0/ at 7%
25-44 $8f774 $7,855
45-54 $12,932 $H,578
55-65 $74j46 $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 ($22,331 at 3% discount rate;
$21,113 at 7% discount rate)
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Regulatory Impact Analysis
Table 6-12 Unit Values Used for Economic Valuation of Health Endpoints (2006$)a (continued)
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)
Pneumonia
(ICD codes 480-487)
Asthma Admissions
All Cardiovascular
(ICD codes 390-429)
Emergency Room Visits for
Asthma
$12,378
$14,693
$6,634
$18,387
$286
$12,378
$14,693
$6,634
$18,387
$286
$12,378
$14,693
$6,634
$18,387
$286
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 Research and
Quality (2000)68 (www.ahrq.gov).
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).
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).
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).
Simple average of two unit COI values:
(1) $311.55, from Smith etal. (1997)69 and
(2) $260.67, from Stanford et al. (1999).70
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Chapter 6: Cost-Benefit Analysis
Table 6-12 Unit Values Used for Economic Valuation of Health Endpoints (2006$)a (continued)
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
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-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.
Lower Respiratory Symptoms
(LRS)
$16
$17
$17
Combinations of the four symptoms for which WTP estimates are
available that closely match those listed by Schwartz et al. result in
11 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 11 different types of LRS.
Asthma Exacerbations
$42
$45
$45
Asthma exacerbations are valued at $42 per incidence, based on the
mean of average WTP estimates for the four severity definitions of a
72
"bad asthma day," described in Rowe and Chestnut (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.
Acute Bronchitis
$360
$380
$390
Assumes a 6-day episode, with daily value equal to the average of
low and high values for related respiratory symptoms recommended
in Neumann et al. (1994).
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Regulatory Impact Analysis
Table 6-12 Unit Values Used for Economic Valuation of Health Endpoints (2006$)a (continued)
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
Restricted Activity and Work/School Loss Days
Work Loss Days (WLDs)
School Absence Days
Worker Productivity
Minor Restricted Activity Days
(MRADs)
Variable
(national
median = )
$75
$0.95 per
worker per
10% change in
ozone per day
$51
$75
$0.95 per
worker per
10% change
in ozone per
day
$54
$75
$0.95 per
worker per
10% change in
ozone per day
$55
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.
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).
74
Median WTP estimate to avoid one MRAD from Tolley et al. (1986).
All monetized annual benefit estimates associated with the coordinated strategy have been inflated to reflect values in year 2006 dollars. We use the Consumer
Price Indexes to adjust both WTP- and COI-based benefits estimates to 2006 dollars from 2000 dollars. For WTP-based estimates, we use an inflation factor of
1.17 based on the CPI-U for "all items." For COI-based estimates, we use an inflation factor of 1.29 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 6: Cost-Benefit Analysis
6.4.3 Manipulating Air Quality Modeling Data for Health Impacts Analysis
In Chapter 2, we summarized the methods for and results of estimating air quality for the
coordinated strategy. These air quality results are in turn associated with human populations to
estimate changes in health effects. For the purposes of this analysis, we focus on the health
effects that have been linked to ambient changes in ozone and PM2.5 related to emission
reductions estimated to occur due to the implementation of the coordinated strategy. We
estimate ambient PM2.5 and ozone concentrations using the Community Multiscale Air Quality
model (CMAQ). This section describes how we converted the CMAQ modeling output into full-
season profiles suitable for the health impacts analysis.
6.4.3.1 General Methodology
First, we extracted hourly, surface-layer PM and ozone concentrations for each grid cell
from the standard CMAQ output files. For ozone, these model predictions are used in
conjunction with the observed concentrations obtained from the Aerometric Information
Retrieval System (AIRS) to generate ozone concentrations for the entire ozone season.T'u The
predicted changes in ozone concentrations from the future-year base case to future-year control
scenario serve as inputs to the health and welfare impact functions of the benefits analysis (i.e.,
BenMAP).
To estimate ozone-related health effects for the contiguous United States, full-season
ozone data are required for every BenMAP grid-cell. Given available ozone monitoring data, we
generated full-season ozone profiles for each location in two steps: (1) we combined monitored
observations and modeled ozone predictions to interpolate hourly ozone concentrations to a grid
of 12-km by 12-km population grid cells for the contiguous 48 states, and (2) we converted these
full-season hourly ozone profiles to an ozone measure of interest, such as the daily 8-hour
maximum.v'w
For PM2.5, we also use the model predictions in conjunction with observed monitor data.
CMAQ generates predictions of hourly PM species concentrations for every grid. The species
include a primary coarse fraction (corresponding to PM in the 2.5 to 10 micron size range), a
primary fine fraction (corresponding to PM less than 2.5 microns in diameter), and several
secondary particles (e.g., sulfates, nitrates, and organics). PM2.5 is calculated as the sum of the
primary fine fraction and all of the secondarily formed particles. Future-year estimates of PM2.5
were calculated using relative reduction factors (RRFs) applied to 2002 ambient PM2.5 and PM2.5
species concentrations. A gridded field of PM2.s concentrations was created by interpolating
Federal Reference Monitor ambient data and IMPROVE ambient data. Gridded fields of PM2 5
T The ozone season for this analysis is defined as the 5-month period from May to September.
u Based on AIRS, there were 961 ozone monitors with sufficient data (i.e., 50 percent or more days reporting at least
nine hourly observations per day [8 am to 8 pm] during the ozone season).
v The 12-km grid squares contain the population data used in the health benefits analysis model, BenMAP.
w This approach is a generalization of planar interpolation that is technically referred to as enhanced Voronoi
Neighbor Averaging (EVNA) spatial interpolation. See the BenMAP manual for technical details, available for
download at http://www.epa.gov/ai^enmap.
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Regulatory Impact Analysis
species concentrations were created by interpolating EPA speciation network (ESPN) ambient
data and IMPROVE data. The ambient data were interpolated to the CMAQ 12 km grid.
The procedures for determining the RRFs are similar to those in EPA's draft guidance for
modeling the PM2 5 standard (EPA, 1999). The guidance recommends that model predictions be
used in a relative sense to estimate changes expected to occur in each major PM2.5 species. The
procedure for calculating future-year PM2 5 design values is called the "Speciated Modeled
Attainment Test (SMAT)." EPA used this procedure to estimate the ambient impacts of the
coordinated strategy to control ship emissions.
Table 6-13 provides those ozone and PM2 5 metrics for grid cells in the modeled domain
that enter the health impact functions for health benefits endpoints. The population-weighted
average reflects the baseline levels and predicted changes for more populated areas of the nation.
This measure better reflects the potential benefits through exposure changes to these populations.
Table 6-13. Summary of CMAQ-Derived Population-Weighted Ozone and PM2 5 Air Quality Metrics for
Health Benefits Endpoints Associated with a Coordinated U.S. Strategy to Control Ship Emissions
Statistic3
2020
Baseline
Changeb
2030
Baseline
Changeb
Ozone Metric: National Population- Weighted Average (ppb)°
Daily Maximum 8-Hour Average
Concentration
44.60
0.21
44.33
0.60
PM2 5 Metric: National Population- Weighted Average (ug/m3)
Annual Average Concentration
10.24
0.35
10.40
0.69
Notes:
a Ozone and PM2 5 metrics are calculated at the CMAQ grid-cell level for use in health effects estimates.
Ozone metrics are calculated over relevant time periods during the daylight hours of the "ozone season"
(i.e., May through September).
b The change is defined as the base-case value minus the control-case value.
0 Calculated by summing the product of the projected CMAQ grid-cell population and the estimated
CMAQ grid cell seasonal ozone concentration and then dividing by the total population.
Emissions and air quality modeling decisions are made early in the analytical process.
For this reason, the emission control scenarios used in the air quality and benefits modeling are
slightly different than the coordinated strategy. The discrepancies impact the benefits analysis in
two ways:
• The air quality modeling used for the 2020 scenario is based on inventory estimates that were
modeled using incorrect boundary information. We believe the impact of this difference,
while modest, likely leads to a small underestimate of the benefits that are presented in this
section. The correct boundary information was used for the 2030 scenario. Please refer to
the Chapter 3 of the RIA for more information on the emissions excluded from the health
impacts analysis.
• The 2020 air quality modeling scenarios do not include emission reductions associated with
the implementation of global controls (set through IMO) beyond the assumed EGA boundary
of 200 nautical miles (nm). Again, while we expect the impact of this difference is modest,
the omission of these additional emission reductions likely leads to a small underestimate of
the 2020 benefits presented in this section. The 2030 air quality modeling scenario did
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Chapter 6: Cost-Benefit Analysis
include emission reductions associated with global controls beyond the assumed EGA
boundary of 200 nm.
6.5 Methods for Describing Uncertainty
The National Research Council (NRC)76 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% to 95% 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.x 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.77'78'79 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 6-11.
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
ambient PM2.5 concentration/'80 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.
x 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.
Y 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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Regulatory Impact Analysis
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.
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.
6.6 Comparison of Costs and Benefits
This section presents the cost-benefit comparison related to the expected impacts of our
coordinated strategy for ocean-going vessels. In estimating the net benefits of the coordinated
strategy, the appropriate cost measure is 'social costs.' Social costs represent the welfare costs
of a rule to society and do not consider transfer payments (such as taxes) that are simply
redistributions of wealth. For this analysis, we estimate that the social costs of the coordinated
program are equivalent to the estimated compliance costs of the program. While vessel owners
and operators will see their costs increase by the amount of those compliance costs, they are
expected to pass them on in their entirely to consumers of marine transportation services in the
form of increased freight rates. Ultimately, these costs will be borne by the final consumers of
goods transported by ocean-going vessels in the form of higher prices for those goods. The
social benefits of the coordinated strategy are represented by the monetized value of health and
welfare improvements experienced by the U.S. population. Table 6-14 contains the estimated
social costs and the estimated monetized benefits of the coordinated strategy.
As discussed in earlier chapters, although the Great Lake steamships are excluded from
the final fuel sulfur standards, our analyses include costs and benefits that would be associated
with fuel sulfur standards for these vessels. This is because the air quality modeling was
performed before the decision to exclude these vessels was made. Because of the relatively
small contribution of Great Lakes steamships to the Category 3 vessel emission inventory, this
has little effect on the cost benefit analysis. We intend to follow up with a more detailed
investigation of the impacts of this final rule on Great Lakes carriers.
The results in Table 6-14 suggest that the 2020 monetized benefits of the coordinated
strategy are greater than the expected costs. Specifically, the annual benefits of the total program
will range between $47 to $110 billion annually in 2020 using a three percent discount rate, or
between $42 to $100 billion assuming a 7 percent discount rate, compared to estimated social
costs of approximately $1.9 billion in that same year. These benefits are expected to increase to
between $110 and $270 billion annually in 2030 using a three percent discount rate, or between
$99 and $240 billion assuming a 7 percent discount rate, while the social costs are estimated to
be approximately $3.1 billion. Though there are a number of health and environmental effects
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Chapter 6: Cost-Benefit Analysis
associated with the coordinated strategy that we are unable to quantify or monetize (see Table 6-
2), the benefits of the coordinated strategy far outweigh the projected costs.
Using a conservative benefits estimate, the 2020 benefits outweigh the costs by a factor
of 22. Using the upper end of the benefits range, the benefits could outweigh the costs by a
factor of 58. Likewise, in 2030 benefits outweigh the costs by at least a factor of 32 and could be
as much as a factor of 87. Thus, even taking the most conservative benefits assumptions,
benefits of the coordinated strategy clearly outweigh the costs.
Table 6-14 Summary of Annual Benefits and Costs Associated with a Coordinated U.S. Strategy to Control
Ship Emissions a
(Millions of 2006 dollars)
Description
Total Estimated Costs
Total Estimated Health Benefitsc'd'e't
3 percent discount rate
7 percent discount rate
Annual Net Benefits (Total Benefits - Total Costs)
3 percent discount rate
7 percent discount rate
2020
$1,900
$47,000 to $110,000
$42,000 to $100,000
$45,000 to $110,000
$40,000 to $98,000
2030
$3,100
$110,000 to $270,000
$99,000 to $240,000
$110,000 to $270,000
$96,000 to $240,000
Notes:
a All estimates represent annual benefits and costs anticipated for the years 2020 and 2030. Totals are rounded to
two significant digits and may not sum due to rounding.
b The calculation of annual costs does not require amortization of costs over time. Therefore, the estimates of annual
cost do not include a discount rate or rate of return assumption (see Chapter 7 of the RIA). In Chapter 7, however,
we use both a 3 percent and 7 percent social discount rate to calculate the net present value of total social costs
consistent with EPA and OMB guidelines for preparing economic analyses.
0 Total includes ozone and PM2 5 benefits. Range was developed by adding the estimate from the Bell et al., 2005
ozone premature mortality function to PM2 5-related premature mortality derived from the ACS (Pope et al., 2002)
and Six-Cities (Laden et al., 2006) studies.
d Annual benefits analysis results reflect the use of a 3 percent and 7 percent discount rate in the valuation of
premature mortality and nonfatal myocardial infarctions, consistent with EPA and OMB guidelines for preparing
economic analyses.
e Valuation of premature mortality based on long-term PM exposure assumes discounting over the SAB
recommended 20-year segmented lag structure described in the Regulatory Impact Analysis for the Final Clean Air
Interstate Rule (March, 2005).
f Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit categories
that have not been quantified and monetized are listed in Table 6-2.
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Regulatory Impact Analysis
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CHAPTER 7: Economic Impact Analysis
This chapter contains our analysis of the expected economic impacts of our coordinated
strategy on the markets for Category 3 marine diesel engines, ocean-going vessels, and the
marine transportation service sector. We examine the impacts of all components of the
coordinated strategy on the markets for Category 3 marine diesel engines, ocean-going vessels,
marine fuels, and international marine transportation services. This includes the cost of the
Clean Air Act emission control program for Category 3 marine diesel engines for U.S. vessel
owners and the costs of complying with the emission and fuel sulfur controls for all ships
operating in the area proposed by the U.S. Government to be designated as an Emission Control
Area (EGA) under MARPOL Annex VI. We look at two aspects of the economic impacts:
estimated social costs and how they are shared across stakeholders, and estimated market
impacts in terms of changes in prices and quantities produced for directly affected markets.
This economic impact analysis uses a competitive model approach for all affected
markets. The competitive market assumption is discussed in section 7.1.2, below.
The total estimated social costs of the coordinated strategy in 2030 are equivalent to the
estimated engineering compliance costs of the program, at approximately $3.1 billion.A'B As
explained below, these costs are expected to accrue initially to the owners and operators of
affected vessels when they purchase engines, vessels, and fuel. These owners and operators are
expected to pass their increased costs on to the entities that purchase international marine
transportation services, in the form of higher freight rates. Ultimately, these social costs are
expected to be borne by the final consumers of goods transported by affected vessels in the form
of slightly higher prices for those goods.
With regard to market-level impacts, we estimate that compliance with the coordinated
strategy would increase the price of a new vessel by 0.5 to 2 percent, depending on the vessel
type. The price impact of the coordinated strategy on the marine transportation services sector
would vary, depending on the route and the amount of time spent in waterways covered by the
engine and fuel controls (the U.S. EGA and U.S. internal waters covered by the coordinated
strategy). For example, we estimate that the cost of operating a ship in liner service between
Singapore, Seattle, and Los Angeles/Long Beach, which includes about 1,700 nm of operation in
waterways covered by the coordinated strategy, would increase by about 3 percent. For a
container ship, this represents a price increase of about $18 per container (3 percent price
increase), assuming the total increase in operating costs is passed on to the purchaser of marine
transportation services. The per passenger price of a seven-day Alaska cruise on a vessel
operating entirely within waterways covered by the coordinated strategy is expected to increase
about $7 per day, again assuming that the total increase in operating costs is passed on to the
passengers of the vessel. Ships that spend less time in covered areas would experience relatively
A All estimates presented in this section are in 2006 dollars.
B The costs totals reported in this FRM are slightly different than those reported in the EGA proposal. This is
because the EGA proposal did not include costs associated with the Annex VI existing engine program, Tier II, or
the costs associated with existing vessel modifications that may be required to accommodate the use of lower sulfur
fuel. Further, the cost totals presented in the EGA package included Canadian cost estimates.
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Chapter 7: Economic Impact Analysis
smaller increases in their operating costs and the impact on freight prices is expected to be
smaller.
7.1 Overview and Results
7.1.1 What is an Economic Impact Analysis?
In general, the purpose of an Economic Impact Analysis (EIA) is to provide information
about the potential economic consequences of a regulatory action, such as the coordinated
strategy to reduce emissions from Category 3 vessels. Such an analysis consists of estimating
the social costs of a regulatory program and the distribution of these costs across stakeholders.
The estimated social costs can then be compared with estimated social benefits as presented in
Chapter 6.
In an economic impact analysis, social costs are the value of the goods and services lost
by society resulting from (a) the use of resources to comply with and implement a regulation and
(b) reductions in output. There are two parts to the analysis. In the market analysis, we estimate
how prices and quantities of goods directly affected by the emission control program can be
expected to change once the program goes into effect. In the economic welfare analysis, we look
at the total social costs associated with the program and their distribution across key
stakeholders.1
7.1.2 What Methodology Did EPA Use in This Economic Impact Analysis?
Our analysis of the economic impacts of the coordinated strategy is based on the
application of basic microeconomic theory. Our methodology and the key assumptions are
described in Section 7.2 below.
We use a competitive market model approach in which the interaction between supply
and demand determines equilibrium market prices and quantities. Specifically, we use the
relationships between supply and demand to simulate how markets can be expected to respond to
increases in production costs that occur as a result of the new emission control program. Using
that information, we can estimate the social costs of the program and identify how those costs
will be shared across the markets and, thus, across stakeholders.
This analysis assumes that the structure of the Category 3 engine market is competitive,
despite there being two primary engine manufacturers that account for the majority of sales.
Some commenters suggested that this market is an oligopoly and should be modeled accordingly.
This assumption is discussed in more detail in Section 7.2.1.3.3.
In addition, our analysis assumes that the demand for marine transportation services is
nearly perfectly inelastic. As explained in Section 7.2.1.1, this assumption is reasonable because
there are no reasonable alternatives to transportation by ship for most goods. The assumption of
nearly perfectly inelastic demand has three consequences for the analysis. First, with respect to
market impacts, it means that equilibrium quantity in the affected markets will not change
relative to the baseline, no-control scenario, and that the equilibrium prices for marine engines,
vessels, and transportation services will increase by the amount of the compliance costs. This is
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Regulatory Impact Analysis
explained more fully in Section 7.2.2. Second, it means that virtually all of the compliance costs
will be borne by the users of marine transportation services. These costs are expected to be
passed on to consumers of goods transported by sea in the form of higher prices. Third, it means
that it is not necessary to estimate the price elasticity of supply for the affected markets. As long
as the supply curves can be assumed to be upward-sloping, the degree of the slope will not affect
the estimated market impacts or social welfare impacts described below. We received comments
that suggested that demand in the cruise industry should not be treated as nearly perfectly
inelastic, and we discuss the implications of this assumption for the cruise ship industry in
Section 7.2.1.1.
With regard to the fuels markets, the impacts of the coordinated strategy on fuel costs
were assessed using the World Oil Refining Logistics and Demand (WORLD) model, as run by
Ensys Energy & Systems, the owner and developer of the refinery model. That model is
described in Chapter 5 of the RIA and incorporates assumptions about the character of the
affected fuels markets and how they respond to regulatory programs.
It should be noted that this economic analysis holds all other aspects of the market
constant except for elements of the coordinated strategy. It does not attempt to predict the future
market equilibrium conditions, particularly with respect to how excess capacity in today's
market due to the current economic downturn will be absorbed. This approach is appropriate
because the goal of an economic impact analysis is to explore the impacts of a specific program;
allowing changes in other market conditions would confuse the impacts due to the regulatory
program.
This analysis of the economic impacts of the coordinated strategy relies on the estimated
engineering compliance costs for engines and fuels described in Chapter 5. These costs include
hardware costs for new U.S. vessels, to comply with the Tier 2 and Tier 3 engine standards, and
for existing U.S. vessels to comply with the MARPOL Annex VI requirements for existing
engines. There are also hardware costs for fuel switching equipment on new and existing U.S.
vessels to comply with the 1,000 ppm fuel sulfur limit; the cost analysis assumes that 32 percent
of all vessels require fuel switching equipment to be added (new vessels) or retrofit (existing
vessels). Also included are expected increases in operating costs for U.S. and foreign vessels
operating in the inventory modeling domain (the waterways covered by the engine and fuel
controls, i.e., the U.S. EGA and U.S. internal waters covered by the coordinated strategy).0
These increased operating costs include changes in fuel consumption rates, increases in fuel
costs, and the use of urea for engines equipped with SCR, as well as a small increase in operating
costs for operation outside the waterways covered by the coordinated strategy due to the fuel
price impacts of the program.
c The MARPOL amendments include Tier II and Tier III NOX standards that apply to all vessels, including foreign
vessels. While the analysis does not include hardware costs for the MARPOL Tier II and Tier III standards for
foreign vessels because foreign vessels operate anywhere in the world, it is appropriate to include the operating costs
for these foreign vessels while they are operating in our inventory modeling domain. This is because foreign vessels
complying with the Tier II and Tier III standards will have a direct beneficial impact on U.S. air quality, and if we
consider the benefits of these standards we should also consider their costs.
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Chapter 7: Economic Impact Analysis
7.1.3 What Economic Sectors are Included in This Economic Impact Analysis?
The coordinated strategy consists of two parts: engine standards that apply to Category 3
marine diesel engines and fuel sulfur requirements for vessels operating waterways affected by
the coordinated strategy. The characteristics of the engine, vessel, and marine transportation
service markets analyzed that are relevant to this economic analysis are summarized in Table 7-
1, and described in more detail in Section 7.3.
With respect to the fuels market, the market impacts were estimated through the cost
analysis described in Chapter 5, using the WORLD model. As described in Chapter 5, WORLD
is a comprehensive, bottom-up model of the global oil downstream that includes crude and
noncrude supplies; refining operations and investments; crude, products, and intermediates
trading and transport; and product blending/quality and demand. Its detailed simulations are
capable of estimating how the global system can be expected to operate under a wide range of
different circumstances, generating model outputs such as price effects and projections of
refinery operations and investments.
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Regulatory Impact Analysis
Table 7-1 Summary of Markets in Economic Impact Model
Description of Markets: Supply
C3 Marine Diesel Engines :
• slow-speed diesel (SSD)
• medium-speed diesel (MSD)
Ocean Marine Vessels: 9 types of vessel
• Auto Carrier
Bulk Carrier
• Container
General Cargo
• Passenger
Reefer
RoRo
• Tanker
Misc.
Marine Transportation Services: U.S. and foreign entities that provide ocean marine
transportation services that operate with waters covered by the coordinated strategy
using affected engines and fuels
All supply curves upward sloping (price increase leads to increase in amount
produced)
Description of Markets: Demand
C3 Marine Engines: Vessel manufacturers
Ocean Marine Vessels: Marine vessel users (owners of all types of ocean vessels)
Marine Transportation Services: Entities that use marine transportation services
(consumer goods, chemical, agricultural, oil companies; personal transportation; etc.)
Demand for marine transportation services assumed to be nearly perfectly inelastic;
demand for other markets derived from demand for marine transportation services
Geographic Scope
50 states
Note: only some portions of the waterways of Alaska and Hawaii are included in the
coordinated strategy for purposes of Tier 3 engine and fuel sulfur controls
Market Structure
Competitive Market
7.1.4 Summary of Results
7.1.4.1 Market Impacts: Engine and Vessel Markets
The estimated market impacts for engines and vessels are based on the variable costs
associated with the engine and vessel compliance programs; fixed costs are not included in the
market analysis. This is appropriate because in a competitive market the industry supply curve is
generally based on the market's marginal cost curve; fixed costs do not influence production
decisions at the margin. Therefore, the market analysis for a competitive market is based on
variable costs only.
The assumption of nearly perfectly inelastic demand for marine transportation services
means that the quantity of these services purchased is not expected to change as a result of costs
of complying with the coordinated strategy. As a result, the demand for vessels and engines
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Chapter 7: Economic Impact Analysis
would also not change compared to the no-control scenario, and the quantities produced would
remain the same.
The assumption of nearly perfectly inelastic demand for marine transportation services
also means the price impacts of the coordinated strategy on new engines and vessels would be
equivalent to the variable engineering compliance costs. Estimated price impacts for a sample of
engine-vessel combinations are set out in Table 7-2, for medium speed engines, and Table 7-3,
for slow speed engines. These are the estimated price impacts associated with the Tier 3 engine
standards on a vessel that will switch fuels to comply with the fuel sulfur requirements while
operating in the waterways covered by the engine and fuel controls. Because there is no phase-in
for the standards, the estimated price impacts are the same for all years, beginning in 2016.
Table 7-2 Summary of Estimated Market Impacts -Medium Speed Tier 3 Engines and Vessels
($2006)''
SHIP TYPE
Auto Carrier
Bulk Carrier
Container
General Cargo
Passenger
Reefer
RoRo
Tanker
Misc.
AVERAGE
PROPULSION
POWER
9,600
6,400
13,900
5,200
23,800
7,400
8,600
6,700
9,400
NEW VESSEL
ENGINE PRICE
IMPACT (NEW
TIER 3 ENGINE
PRICE IMPACT)b
$573,200
$483,500
$687,800
$450,300
$952,500
$511,000
$543,800
$492,800
$566,800
NEW VESSEL
FUEL SWITCHING
EQUIPMENT
PRICE IMPACT"
$42,300
$36,900
$49,200
$34,900
$65,400
$38,500
$40,500
$37,400
$41,900
NEW VESSEL
TOTAL PRICE
IMPACT
$615,500
$520,400
$736,000
$475,200
$1,107,900
$549,500
$584,300
$530,200
$608,700
Notes:
a The new vessel engine price impacts listed here do not include a per engine cost of $10,000 for engines
installed on U.S. vessels to comply with the production testing requirement (§1042.302)
b Medium speed engine price impacts are estimated from the cost information presented in Chapter 5 using the
following formula: (10%*($/SHIP_MECH^CR)>f(30%*($/SHIP_ELEC^CR)>f(T3 ENGINE MODS)+(T3SCR))
0 Assumes 32 percent of new vessels would require the fuel switching equipment.
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Regulatory Impact Analysis
Table 7-3 Summary of Estimated Market Impacts - Slow Speed Tier 3 Engines and Vessels ($2006)a
SHIP TYPE
Auto Carrier
Bulk Carrier
Container
General Cargo
Passenger
Reefer
RoRo
Tanker
Misc.
AVERAGE
PROPULSION
POWER
11,300
8,400
27,500
7,700
23,600
10,400
15,700
9,800
4,700
NEW VESSEL
ENGINE PRICE
IMPACT (NEW
TIER 3 ENGINE
PRICE IMPACT)b
$825,000
$672,600
$1,533,100
$632,900
$1,385,300
$781,000
$1,042,100
$744,200
$453,600
NEW VESSEL
FUEL SWITCHING
EQUIPMENT
PRICE IMPACT"
$48,000
$42,700
$63,900
$41,000
$61,200
$46,500
$53,900
$45,300
$32,000
NEW VESSEL
TOTAL PRICE
IMPACT
$873,000
$715,300
$1,597,000
$673,900
$1,446,500
$827,500
$1,096,000
$789,500
$485,600
Notes:
a The new vessel engine price impacts listed here do not include a per engine cost of $10,000 for engines
installed on U.S. vessels to comply with the production testing requirement (§1042.302)
b slow speed engine price impacts are estimated from the cost information presented in Chapter 5 using the
following formula: (5%*($/SfflPJMECH^CR))f(15%*($/SfflP_ELEC->CR))f(T3 ENGINE MODS)^(T3 SCR))
0 Assumes 32 percent of new vessels would require the fuel switching equipment.
The estimated price impacts for Tier 2 vessels would be substantially lower, given the
technology that will be used to meet the Tier 2 standards is much less expensive. The cost of
complying with the Tier 2 standards ranges from about $56,000 to $100,000 for a medium speed
engine, and from about $130,000 to $250,000 for a slow speed engine. Again, because the
standards do not phase in, the estimated price impacts are the same for all years the Tier 2
standards are required, 2011 through 2015.
These estimated price impacts for Tier 2 and Tier 3 vessels are small when compared to
the price of a new vessel. A selection of new vessel prices is provided in Table 7-4; these range
from about $40 million to $480 million. The program price increases range from about $600,000
to $1.5 million. A price increase of $600,000 to comply with the Tier 3 standards and fuel
switching requirements would be an increase of approximately 2 percent for a $40 million
vessel. The largest vessel price increase noted above, for a Tier 3 passenger vessel, is about $1.5
million; this is a price increase of less than 1 percent for a $478 million passenger vessel.
Independent of the nearly perfectly inelasticity of demand, price increases of this magnitude
would be expected to have little, if any, effect on the sales of new vessels, all other economic
conditions held constant.
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Chapter 7: Economic Impact Analysis
Table 7-4 Newbuild Vessel Price by Ship Type and Size, Selected Vessels (Millions, $2008)
Vessel Type
Bulk Carrier
Container
Gas carrier
General
cargo
Passenger
Reefer
Ro-Ro
Tanker
Vessel Size
Category
Handy
Handymax
Panamax
Capesize
Feeder
Intermediate
Panamax
Post Panamax
Midsize
LGC
VLGC
Coastal Small
Coastal Large
Handy
Panamax
All
All
All
Coastal
Handymax
Panamax
AFRAmax
Suezmax
VLCC
Size Range (Mean) (DWT)
10,095 - 39,990 (27,593)
40,009-54,881(47,616)
55,000-78,932(69,691)
80,000 - 364,767 (157,804)
1,000-13,966 (9,053)
14,003-36,937 (24,775)
37,042-54,700 (45,104)
55,238-84,900 (67,216)
1,001-34,800 (7,048)
35,760-59,421 (50,796)
62,510-122,079(77,898)
1,000-9,999 (3,789)
10,000-24,912 (15,673)
25,082-37,865 (29,869)
41,600-49,370(44,511)
1,000-19,189 (6,010)
1,000-19,126 (6,561)
1,000-19,126 (7,819)
1,000-23,853(7,118)
25,000-39,999 (34,422)
40,000-75,992 (52,300)
76,000-117,153(103,112)
121,109-167,294 (153,445)
180,377-319,994(294,475)
Newbuild
$56.00
$79.00
$97.00
$175.00
$38.00
$70.00
$130.00
$165.00
$79.70
$37.50
$207.70
$33.00
$43.00
$52.00
$58.00
$478.40
$17.30
$41.20
$20.80
$59.00
$63.00
$77.00
$95.00
$154.00
Sources: Lloyd's Shipping Economist (2008), Informa (2008), Lloyd's Sea-Web (2008)
7.1.4.2 Market Impacts: Fuel Market
The market impacts for the fuel markets were estimated through the modeling performed
to estimate the fuel compliance costs for the coordinated strategy. As described in Chapter 5, the
WORLD model is the only such model currently developed for this purpose, and was developed
by a team of international petroleum consultants. It has been widely used by industries,
government agencies, and OPEC over the past 13 years, including the 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. The model
incorporates crude sources, global regions, refinery operations, and world economics, as well as
assumptions about how these markets respond to regulatory programs. The results of the
WORLD model have been shown to be comparable to other independent predictions of global
fuel, air pollutant emissions and economic predictions.
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Regulatory Impact Analysis
WORLD is a comprehensive, bottom-up model of the global oil downstream that
includes crude and noncrude supplies; refining operations and investments; crude, products, and
intermediates trading and transport; and product blending/quality and demand. Its detailed
simulations are capable of estimating how the global system can be expected to operate under a
wide range of different circumstances, generating model outputs such as price effects and
projections of refinery operations and investments.
In the WORLD model, the total quantity of fuel used is held constant, which is consistent
with the assumption that the demand for international shipping transportation would not be
expected to change due to the lack of transportation alternatives.
The expected price impacts of the coordinated strategy are set out in Table 7-5. Note that
on a mass basis, less distillate than residual fuel is needed to go the same distance (5 percent
less). The prices in Table 7-5 are adjusted for this impact. Table 7-5 shows that the coordinated
strategy is expected to result in a small increase in the price of marine distillate fuel, about 1.3
percent. The price of residual fuel is expected to decrease slightly, by less than one percent, due
to a reduction in demand for that fuel.
Table 7-5 Summary of Estimated Market Impacts - Fuel Markets
FUEL
Distillate
Residual
Fuel
Switching
UNITS
$/tonne
$/tonne
$/tonne
BASELINE
PRICE
$462
$322
$322
CONTROL
PRICE
$468
$321
$468
ADJUSTED FOR
ENERGY
DENSITY
N/A
N/A
$444
% CHANGE
+1.3%
-0.3%
+38.9% a
Notes:
a Energy adjusted value
Because of the need to shift from residual fuel to distillate for ships while operating in the
waterways covered by the engine and fuel controls (the U.S. EGA and U.S. internal waters
covered by the coordinated strategy), ship owners are expected to see an increase in their total
cost of fuel. This increase is because distillate fuel is more expensive than residual fuel.
Factoring in the higher energy content of distillate fuel relative to residual fuel, the fuel cost
increase would be about 39 percent.
7.1.4.3 Market Impacts: Marine Transportation Services Market
We used the above estimates of engine, vessel, and fuel price impacts to estimate the
impacts on the prices of marine transportation services. This analysis, presented in Section 7.3,
below, is limited to the impacts of increases in operating costs due to the fuel and emission
requirements of the coordinated strategy. Operating costs would increase due to the increase in
the price of fuel, the need to switch to fuel with a sulfur content not to exceed 1,000 ppm while
operating in the waterways covered by the engine and fuel controls, and due to the need to dose
the aftertreatment system with urea to meet the Tier 3 standards. Table 7-6 summarizes these
price impacts for selected transportation markets. Table 7-6 also lists the vessel and engine
parameters that were used in the calculations.
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Chapter 7: Economic Impact Analysis
Table 7-6 Summary of Impacts of Operational Fuel/Urea Cost Increases
VESSEL TYPE
Container
North Pacific Circle Route
Bulk Carrier
North Pacific Circle Route
Cruise Liner
(Alaska)
VESSEL AND
ENGINE
PARAMETERS
36,540 kW
50,814 DWT
3,825 kW
16,600 DWT
3 1,500 kW
226,000 DWT
1,886 passengers
OPERATIONAL PRICE
INCREASES
$17.53/TEU
$0.56/tonne
$6.60/per passenger per day
This information suggests that the increase in marine transportation service prices would
be small, both absolutely and when compared to the price charged by the ship owner per unit
transported, and are estimated to be about $18 per TEU on the North Pacific Circle Route and
$0.56 per tonne for bulk cargo on the North Pacific Circle Route. Stopford notes that the price of
transporting a 20 foot container between the UK and Canada is estimated to be about $1,500; of
that, $700 is the cost of the ocean freight; the rest is for port, terminal, and other charges.2 Thus,
a price increase of about $18 represents an increase of less than 3 percent of ocean freight cost,
and about one percent of transportation cost. Similarly, the price of a 7-day Alaska cruise varies
from $100 to $400 per night or more. In that case, a price increase of about $7 per night would
be a 1.5 percent to about 6 percent increase.
Our analysis also suggests that increases in operational costs of the magnitude expected
to occur for vessels operating in the area covered by the coordinated strategy are within the range
of historic price variations for bunker fuel. This is illustrated in Figure 7-1. This figure is based
on variation in fuel price among the ports of Singapore, Houston, Rotterdam, and Fujairah.
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Regulatory Impact Analysis
$675
$575
$475
$375
$275
$175
•Baseline Value (Cheapest)
•Most Expensive Fuel
3% Increase due to EGA
Date
Figure 7-1 Range of Bunker Fuel Prices
This graph illustrates the price differential between these ports, comparing the estimated
3% EGA increase to the cheapest fuel for each month. We then plotted these calculated EGA
increases (the 3% increases), the cheapest fuel (as a baseline) and the most expensive fuel for the
same six month period. As can be observed from the previous calculations and the trends in
Figure 7-1, there are both spatial and temporal price fluctuations in fuel prices. During this
period (granted, a period of above-average fluctuations), the price of fuel varied both spatially
and temporally. The variation over time is higher than the variation over ports; however, by
either form of variation, the 3% increase in bunker fuel price due to the requirements of the
coordinated strategy is smaller than the normal price variation of the fuel.
7.1.4.4 Social Welfare Impacts and Their Distribution across Stakeholders
The total social costs of the coordinated strategy are based on both fixed and variable
costs. Fixed costs are a cost to society: they displace other product development activities that
may improve the quality or performance of engines and vessels. In this economic impact
analysis, fixed costs are accounted for in the year in which they occur, with the fixed costs
associated with the Tier 2 engine standards accounted for in 2010 and the fixed costs associated
with the Tier 3 engine standards and the fuel sulfur controls for vessels operating on the
waterways covered by the coordinated strategy are accounted for in the five-year period
beginning prior to their effective dates.
These estimated social costs of the coordinated strategy for all years are presented in
Table 5-44, copied below for convenience. For 2030, the social costs are estimated to be about
$3.1 billion. Due to the nearly perfectly inelastic demand for marine transportation services,
these costs are expected to be borne fully by consumers of marine transportation services.
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Chapter 7: Economic Impact Analysis
Table 7-7 Total Costs Associated with the Coordinated Strategy
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPV @ 3%
NPV @ 7%
Fixed
$477,020
$1,018,766
$1,056,245
$1,095,347
$1,136,035
$972,037
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,311,963
$4,805,557
Variable
$0
$2,497,657
$2,580,365
$2,667,173
$2,757,514
$13,954,191
$28,052,583
$29,154,639
$30,302,933
$31 ,499,499
$32,746,463
$34,046,049
$35,400,583
$36,812,494
$38,284,325
$39,818,735
$41,418,504
$43,086,539
$44,825,880
$46,639,709
$48,531 ,352
$50,504,289
$52,562,159
$54,708,770
$56,948,104
$59,284,330
$61,721,806
$64,265,093
$66,918,964
$69,688,411
$72,578,659
$683,356,096
$358,019,816
Operational
$0
$1,306,556
$6,431 ,250
$244,951 ,550
$260,810,043
$1,369,402,786
$1,438,235,966
$1,525,633,990
$1,622,800,854
$1,721,756,141
$1,820,614,217
$1,925,263,118
$2,028,002,568
$2,147,543,473
$2,266,962,666
$2,387,551 ,773
$2,512,510,228
$2,638,815,284
$2,774,457,455
$2,913,118,509
$3,063,782,201
$3,205,898,377
$3,358,465,311
$3,519,017,395
$3,689,819,658
$3,867,580,840
$4,056,506,472
$4,258,730,159
$4,465,788,635
$4,680,205,640
$4,905,310,074
$42,179,757,713
$21,724,932,914
Total
$477,020
$4,822,979
$10,067,860
$248,714,070
$264,703,592
$1,384,329,013
$1 ,466,288,549
$1,554,788,630
$1,653,103,787
$1,753,255,640
$1,853,360,680
$1,959,309,168
$2,063,403,150
$2,184,355,967
$2,305,246,991
$2,427,370,508
$2,553,928,732
$2,681,901,822
$2,819,283,335
$2,959,758,218
$3,112,313,554
$3,256,402,666
$3,411,027,470
$3,573,726,165
$3,746,767,762
$3,926,865,170
$4,118,228,278
$4,322,995,252
$4,532,707,599
$4,749,894,051
$4,977,888,733
$42,868,425,773
$22,087,758,287
These social costs are small when compared to the total value of U.S. waterborne foreign
trade. In 2007, waterborne trade for government and non-government shipments by vessel into
and out of U.S. foreign trade zones, the 50 states, the District of Columbia, and Puerto Rico was
about $1.4 trillion. Of that, about $1 trillion was for imports.3
If only U.S. vessels are considered, the social costs of the coordinated strategy in 2030
would be about $427.5 million. Again, these social costs are small when compared to the annual
revenue for this sector. In 2002, the annual revenue for this sector was about $19.8.4
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Regulatory Impact Analysis
While users of marine transportation services are expected to bear the entire compliance
costs of the program, these costs are expected to be passed on to consumers in the form of higher
prices for the goods transported by sea. When these costs are spread across these goods, their
impacts are expected to be very small. For example, an increase of $18 to transport a container
from Singapore to Los Angeles would result in an increase of about one cent for a pair of shoes.
In general, transportation costs are only a small portion of the costs of goods and materials.
According to UNCTAD, freight costs in 2001 were only about 5.1 percent of import value in
2001, for developed countries.5
7.2 Economic Methodology
The methodology used in this Economic Impact Analysis (EIA) is rooted in applied
microeconomic theory and was developed following U.S. EPA's recommendations.6 This
section describes the economic theory underlying the analysis and how it was applied to the
problem of estimating the economic impacts of the U.S. coordinated strategy on shipping
engaged in international trade.
7.2.1 What Is the Economic Theory Used to Estimate Economic Impacts?
The approach used to estimate the economic impacts of the coordinated strategy relies on
the basic relationships between production and consumption in competitive markets.
7.2.1.1 Behavioral Model
This economic impact analysis uses a behavioral approach in that it builds on the
engineering cost analysis by incorporating economic theory related to producer and consumer
behavior to estimate changes in market conditions. As Bingham and Fox7 note, this framework
provides "a richer story" of the expected distribution of economic welfare changes across
producers and consumers. In behavioral models, manufacturers of goods affected by a
regulation are economic agents who can make adjustments, such as changing production rates or
altering input mixes, which will generally affect the market environment in which they operate.
Before the implementation of a control program, a competitive market is assumed to be
in equilibrium, with producers producing the amount of a good that consumers desire to purchase
at the market price. The implementation of a control program results in an increase in
production costs by the amount of the compliance costs. This generates a "shock" to existing
equilibrium market conditions (a change in supply). Producers of affected products will try to
pass some or all of the increased production costs on to the consumers of these goods through
price increases, without changing the quantity produced. In response to the price increases,
consumers will decrease the quantity they buy of the affected good (a change in the quantity
demanded). This creates surplus production at the new price. Producers will react to the
decrease in quantity demanded by reducing the quantity they produce, and they will be willing to
sell the remaining production at a lower price that does not cover the full amount of the
compliance costs. Consumers will then react to this new price. These interactions continue until
the surplus production is removed and a new market equilibrium price and quantity combination
is achieved.
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Chapter 7: Economic Impact Analysis
The amount of the compliance costs that will be borne by stakeholders is ultimately
limited by the price sensitivity of consumers and producers in the relevant markets, represented
by the price elasticities of demand and supply for each market. An "inelastic" price elasticity
(less than one) means that supply or demand is not very responsive to price changes (a one
percent change in price leads to less than one percent change in quantity). An "elastic" price
elasticity (more than one) means that supply or demand is sensitive to price changes (a one
percent change in price leads to more than one percent change in quantity). A price elasticity of
one is unit elastic, meaning there is a one-to-one correspondence between a percent change in
price and percent change in quantity.
On the production side, price elasticity of supply depends on the time available to adjust
production in response to a change in price, how easy it is to store goods, and the cost of
increasing (or decreasing) output. In this analysis, we assume the supply for engines, vessels,
and marine transportation services is elastic: an increase in the market price of an engine, vessel
or freight rates will lead producers to want to produce more, while a decrease will lead them to
produce less (this is the classic upward-sloping supply curve).
It would be difficult to estimate the slope of the supply curve for each of these markets
given the global nature of the sector and, as explained below, it is not necessary to have
estimated supply elasticities for this analysis due to the assumption of nearly perfectly inelastic
demand for the marine transportation sector. However, we can make some observations about
the supply elasticities based on the nature of each sector. For the marine transportation sector, it
is reasonable to assume a supply elasticity equal to or because the amount of transportation
services provided can easily be adjusted due to a change in price in most cases (e.g., move more
or fewer containers or passengers) especially if the market can carry a certain amount of excess
capacity. For the new Category 3 engine market, the supply elasticity is also likely to be greater
than one. These engines are often used in other land-based industries, notably in power plants,
which provides a market to accommodate production fluctuations as manufacturers adjust their
output for the marine market. The supply elasticity for the vessel construction market, on the
other hand, is upward sloping but this slope (supply elasticity) may be less than or equal to one.
This would be expected since it may be harder to adjust production and/or store output if the
price drops, or rapidly increase production if the price increases. Because of the nature of this
industry, it may not be possible to easily switch production to other goods, or to stop or start
production of new vessels.
On the consumption side, we assume that the demand for engines is a function of the
demand for vessels, which is a function of the demand for international shipping (demand for
engines and vessels is derived from the demand for marine transportation services). This makes
intuitive sense: Category 3 engine and ocean-going vessel manufacturers would not be expected
to build an engine or vessel unless there is a purchaser, and purchasers will want a new
vessel/engine only if there is a need for one to supply marine transportation services. Deriving
the price elasticity of demand for the vessel and engine markets from the international shipping
market is an important feature of this analysis because it provides a link between the product
markets.
In this analysis, the price elasticity of demand for marine transportation services, and
therefore fore vessels and Category 3 engines, is assumed to be nearly perfectly inelastic (the
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Regulatory Impact Analysis
demand for marine transportation services will remain the same for all price changes). This
stems from the fact that, for most goods, there are no reasonable alternatives to shipping by
vessel for the vast majority of products transported by sea to the United States and Canada. It is
impossible to ship goods between these countries and Asia, Africa, or Europe by rail or highway.
Transportation of goods between these countries and Central and South America by rail or
highway would be inefficient due to the time and costs involved. While aviation may be an
alternative for some goods, it is impossible for goods shipped in bulk or goods shipped in large
quantities. There are also capacity constraints associated with trans-continental aviation
transportation, and the costs are higher on a per tonne basis. As a result, approximately 90
percent of world trade by tonnage is moved by ship, and ships provide the most efficient method
to transport these goods on a tonne-mile basis.8 Stopford notes that "shippers need the cargo
and, until they have time to make alternative arrangements, must ship it regardless of cost... The
fact that freight generally accounts for only a small portion of material costs reinforces this
argument."9 A nearly perfectly inelastic price elasticity of demand for marine transportation
services means that virtually all of the compliance costs can be expected to be passed on to the
consumers of marine transportation services, with no change in output for engine producers, ship
builders, or owners and operators of ships engaged in international trade. Section 7.4, below,
provides a discussion of the impact of relaxing the of nearly perfectly demand elasticity for
marine transportation services in general, and for the cruise industry specifically. Relaxing this
assumption is not expected to change the estimated total social costs of the program, which are
limited by the engineering compliance costs. However, it would change the way those costs are
shared among stakeholders.
Representatives of the cruise industry commented that, unlike the other transportation
services affected by the coordinated strategy, the demand for cruises is not nearly perfectly
inelastic. These commenters noted that cruises are a recreational activity and consumers are
more sensitive to price changes than consumers of transportations services for containers or bulk
goods. They contend that if the price of a cruise increases, consumers will choose to spend their
recreational budgets on other activities. We acknowledge that, as a recreational service, demand
for cruises is expected to be more elastic that demand for other transportation services.
However, an elastic demand for cruises means that the compliance costs associated with the
coordinated strategy will be shared among the cruise providers and their customers, rather than
being passed on completely to the passengers through higher prices. While this distribution of
the compliance burden may offset at least partially a decline in demand for cruises through
smaller price increases, it also means that cruise ship companies will bear at least part of the
compliance costs of the program. Nevertheless, these compliance costs are still expected to be
small compared to the daily costs of a cruise. While the cruise sector may be in difficulty due to
current economic conditions, it is not possible to predict what the conditions will be when the
coordinated strategy goes into effecting 2016 for Tier 3 engines and 2020 for 1,000 ppm sulfur
fuel. All things considered equal, this analysis suggests that the impacts on the cruise industry
will be small. A brief discussion of the results of relaxing the assumption of perfectly inelastic
demand elasticity is presented in Section 7.4, below.
7.2.1.2 Multi-Market, Partial-Equilibrium Approach
This is also a multi-market, partial equilibrium approach. It is a multi-market approach
in that more than one market is examined: the markets for marine engines, vessels, and
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international shipping transportation services. It is a partial-equilibrium approach in that rather
than explicitly modeling all of the interactions in the global economy that are affected by
international shipping, the individual markets that are directly affected by the rule requirements
are modeled in isolation. This technique has been referred to in the literature as "partial
equilibrium analysis of multiple markets."10
This EIA does not examine the economic impact of the U.S. coordinated strategy on
finished goods that use ocean transportation services as inputs. This is because international
shipping transportation services are only a small part of the total inputs of the final goods and
services produced using the materials shipped. A change in the price of marine transportation
services on the order anticipated by this program would not be expected to significantly affect
the markets for the finished goods. So, for example, while we look at the impacts of the program
on ocean transportation costs, we do not look at the impacts of the controls on gasoline produced
using crude oil transported by ship, or on manufactured products that use petroleum products as
inputs.
It should also be noted that this EIA estimates the aggregate economic impacts of the
control program at the market level. This is not intended to be a firm-level analysis; therefore
compliance costs facing any particular ship operator may be different from the market average,
and the impacts of the program on particular firms can vary significantly. The difference can be
important, particularly where the rule affects different firms' costs over different activity rates.
7.2.1.3 Competitive Market Structure
The methodology used in this EIA relies on the assumption that the relevant markets have
a competitive market structure. This means that consumers and firms are price takers and do not
have the ability to influence market prices. Competitive market structure is a widely accepted
assumption for this type of analysis and only in rare cases are other approaches used.11
Stopford's description of the shipping market and how prices are set in this market supports this
assumption.12
In a competitive market at equilibrium with no externalities, the market price equals the
value society (consumers) places on the marginal product, as well as the marginal cost to society
(producers). Producers are price takers, in that they respond to the value that consumers put on
the product. It should be noted that the assumption of competitive market structure is not
primarily about the number of firms in a market. It is about how the market operates: whether or
not individual firms have sufficient market power to influence the market price. Indicators that
allow us to assume a competitive market structure include absence of barriers to entry, absence
of strategic behavior among firms in the market, and product differentiation.0'13 Finally,
according to contestable market theory, oligopolies and even monopolies will behave very much
like firms in a competitive market if it is possible to enter particular markets costlessly (i.e., there
are no sunk costs associated with market entry or exit). This would be the case, for example,
when products are substantially similar (e.g., a recreational vessel and a commercial vessel).
D The number of firms in a market is not a necessary condition for a competitive market. See Robert H. Frank,
Microeconomics and Behavior, 1991, McGraw-Hill, Inc., p 333.
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7.2.1.3.1 Competition in the Marine Transportation Services Market
Ships that service the marine transportation services market are either tramp vessels or
liner vessels. As explained below, both of these sectors can reasonably be modeled as
competitive markets.
Tramp vessels "carry bulk and general cargoes not catered for by the liner industry."14
These vessels have no fixed route or ports of call, or published freight rates. Instead, they
arrange to carry loads on a per voyage basis and operate on the spot market. According to a
survey performed for the World Trade Organization in 1998 (37 member countries, counting the
EU as one, and representing nearly half of the tonnage of the world fleet), bulk traffic accounted
for about 65 percent of the volume of trade in that sample.15 That report notes that "contracts are
allocated on an extremely competitive basis; business is won on the basis of freight rates a few
cents per ton lower than the competition. Stopford notes that this sector has expanded greatly
since the 1970s, benefiting from advances in communication that facilitated information flows.
The result, he notes, is "the highly efficient transport system for bulk cargoes we have today."16
Consequently, it is reasonable to assume a competitive market structure.
Liner vessels, in contrast, operate on fixed routes and schedules with published rates.
The liner sector is specifically exempt from antitrust legislation, and so-called conference
agreements set rates and conditions of service for the scheduled routes. However, this sector can
also be assumed to operate competitively. This is because the Ocean Shipping Reform Act of
1998 allows the use of "service contracts," which are private contracts that do not have to
comply with the conference rates. These open conferences exist only on the U.S. routes. The
amount of freight shipped in liners using service contracts instead of published rates has grown
tremendously since 1998; it has been estimated that 80% of cargo transported on routes between
U.S. ports and other countries carried by conference members uses service contracts.17 This
availability of service contracts appears to have increased substantially the competitiveness of
liner shipping in the U.S. In addition, the World Trade Organization survey suggests that "the
share of traffic held by the conferences has been eroded as new state trading and South East
Asian operators have emerged and become powerful enough to offer on their own services
equivalent to those of the conferences."18
It should be noted that contracts for liner shipping typically include a bunker fuel
adjustment factor (BAF) in addition to the shipping rate. The BAF is used to adjust shipping
costs in response to unexpected fuel cost variation after shipping rates are set.19 The BAF is
determined by individual line shipping company and allows ship owners to adjust their rates by
these increases in operating costs, thereby passing increases in operating costs to the entities that
purchase their transportation services.
In sum, tramp shipping appears to be a competitive market. Liner shipping, although
exempt from antitrust laws, nevertheless is much less able than in the past to enforce its
noncompetitively set published rates, and it faces some degree of competition from tramp
shipping and from liners that are not members of the established conferences.
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7.2.1.3.2 Competition in the Vessel Building Market
With regard to the vessel building market, there are short- and medium-term barriers to
trade that could impede competition. Specifically, the shipping industry is characterized by high
fixed costs (building a vessel). High entry costs can serve as a temporary barrier to entry in an
industry: since existing shippers in the industry have already incurred those costs, they can
operate at costs low enough to deter entry. However, this condition is offset by the excess
capacity that appears to exist at many shipyards.20 An industry with excess capacity faces strong
competition, as shipyards are likely to compete with each other for any new business. As a
result, shipyards are likely to operate with margins small enough that they must pass along any
increases in costs. Any requirements that affect the costs of a new vessel are likely to be
included in the cost of a new vessel. Finally, while vessel building is concentrated in a few
countries (South Korea, China, Japan, Germany), the purchaser of a new vessel has many
shipyards available since most countries maintain at least some vessel building capacity.
7.2.1.3.3 Competition in the Engine Manufacturing Market
In recent years, the Category 3 marine diesel engine industry has become more
consolidated. In 1998, there were 19 Category 3 engine manufacturers, with four sharing 80
percent of the market.21 Since that time, Wartsila purchased Sulzer, and Caterpillar purchased
MaK. Currently, these companies along with MAN B&W and Mitsubishi account for the vast
majority of the Category 3 engine market. This small number of companies suggests that these
manufacturers may have certain market power. However, an important characteristic of the
market suggests this market may nevertheless be competitive. Specifically while the primary
engine companies design and patent Category 3 marine diesel engines, they manufacture only
key components and not the actual engine itself. Engines are manufactured through licensing
agreements with shipyards or other companies. Licensees pay a fixed cost to the primary engine
manufacturers for using their designs and brands. Engine prices are then set by the licensees,
sometimes as part of the price of a completed vessel, and there is competition among these firms
to manufacturer engines and vessels.
Nevertheless, to estimate the maximum economic impact of the program , we can
examine how the results of this economic impact analysis would change if we assumed an
imperfectly competitive market structure. In markets with a small number of producers, it is not
uncommon for manufacturers to exercise market power to obtain prices above their costs,
thereby securing greater profits. In this case, market prices would be expected to increase by
more than the compliance costs of the regulatory program, although the magnitude of the
increase would be limited by the existing dynamics of the market (i.e., the current difference
between the actual market price and the competitive market price). This impact is discussed in
more detail in Section 7.4, below. The higher price impact from imperfect competition would be
transmitted to the vessel and marine transportation markets. However, even in this case, the
price impacts of this rule on the Category 3 engine market are not expected to be large given the
price increases estimated for the competitive case, described below. This is because the
compliance costs for engine program are relatively small compared to the price of a vessel.
Finally, the existence of only a small number of firms in a market does not mean that the
firms act non-competitively. According to the Bertrand competition model, price competition in
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Regulatory Impact Analysis
an oligopoly achieves the similar results as a perfectly competitive market.22 In this case, each
firm chooses its price to compete with the other firms. Varian describes this as a model of
competitive bidding: "Suppose that one firm 'bids' for the consumers' business by quoting a
price above marginal cost. Then the other firm can always make a profit by undercutting this
price by a lower price."23 In the Bertrand model, price competition under constant returns to
scale yields a price equal to the constant marginal cost. In other words, the price bidding prices
leads to perfectly competitive results.
The theoretical conditions for Bertrand competition are: there are at least two firms
producing homogeneous products; firms do not cooperate; firms have the same marginal cost
(MC); marginal cost is constant; demand is linear; firms compete in price, and choose their
respective prices simultaneously; there is strategic behavior by both firms; both firms compete
solely on price and then supply the quantity demanded; and consumers buy everything from the
cheaper firm or half at each, if the price is equal.24 In an oligopoly market, price competition
may be softened when the manufacturers face sharply rising marginal costs, when they compete
repeatedly, or when their products are differentiated.
In this case, the two primarily engine producers compete against each other and against
the smaller producers in the market. While their products are differentiated, the choice of engine
and the ship's design interact so purchasers can choose among engine manufacturers and models.
Engine manufacturers also compete to sell the same or similar engines in the land-based
electrical power generating market, where they face many more competitors. In addition, the
Category 3 engine market is a mature industry and pricing power in mature markets is typically
limited.
To respond to comments about the market structure for the Category 3 engine market,
Section 7.4 provides a discussion of relaxing the competitive market assumption for that market
and describes how it would affect the results of this economic impact analysis.
7.2.1.4 Intermediate-Run Impacts
This EIA explores economic impacts on affected markets in the intermediate run. In the
intermediate run, some factors of production are fixed and some are variable. A short-run
analysis, in contrast, imposes all compliance costs on producers, while a long-run analysis
imposes all costs on consumers. The use of the intermediate run means that some factors of
production are fixed and some are variable, and illustrates how costs will be shared between
producers and consumers as the markets adjust to the new compliance program. The use of the
intermediate time frame is consistent with economic practices for this type of analysis.
7.2.1.4.1 Short-Run Analysis
In the very short run, all factors of production are assumed to be fixed, leaving producers
with no means to respond to the increased costs associated with the regulation (e.g., they cannot
adjust labor or capital inputs). Within a very short time horizon, regulated producers are
constrained in their ability to adjust inputs or outputs due to contractual, institutional, or other
factors and can be represented by a vertical supply curve, as shown in Figure 7-2. Under this
time horizon, the impacts of the regulation fall entirely on the regulated entity. Producers incur
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Chapter 7: Economic Impact Analysis
the entire regulatory burden as a one-to-one reduction in their profit. This is referred to as the
"full-cost absorption" scenario and is equivalent to the engineering cost estimates. Although
there is no hard and fast rule for determining what length of time constitutes the very short run, it
is inappropriate to use this time horizon for this type of analysis because it assumes economic
entities have no flexibility to adjust factors of production. Note that the BAF is a way to avoid
this scenario. Additionally, the fact that liner price schedules are renegotiated at least annually,
and that individual service contracts may be negotiated more frequently, suggests that a very
short-run analysis would not be suitable.
Price
Q Output
Figure 7-2 Short-Run: All Costs Borne by Producers
7.2.1.4.2 Long-Run Analysis
In the long run, all factors of production are variable, and producers can be expected to
adjust production plans in response to cost changes imposed by a regulation (e.g., using a
different labor/capital mix). Figure 7-3 illustrates a typical, if somewhat simplified, long-run
industry supply function. The supply function is horizontal, indicating that the marginal and
average costs of production are constant with respect to output. This horizontal slope reflects
the fact that, under long-run constant returns to scale, technology and input prices ultimately
determine the market price, not the level of output in the market.
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Regulatory Impact Analysis
$ d
Price
Increase
Sr With Regulation
Unit Cost Increase
S0: Without Regulation
Q1 Q0
Figure 7-3 Long-Run: Full Cost Pass-Through
Output
Market demand is represented by the standard downward-sloping curve. The market is
assumed here to be competitive; equilibrium is determined by the intersection of the supply and
demand curves. In this case, the upward shift in the market supply curve represents the
regulation's effect on production costs and is illustrated in Figure 7-3. The shift causes the
market price to increase by the full amount of the per-unit control cost (i.e., from P0 to PI). With
the quantity demanded sensitive to price, the increase in market price leads to a reduction in
output in the new with-regulation equilibrium (i.e., Qo to Qi). As a result, consumers incur the
entire regulatory burden as represented by the loss in consumer surplus (i.e., the area Poac PI). In
the nomenclature of EIAs, this long-run scenario is typically referred to as "full-cost pass-
through."
Taken together, impacts modeled under the long-run/full-cost-pass-through scenario
reveal an important point: under fairly general economic conditions, a regulation's impact on
producers is transitory. Ultimately, the costs are passed on to consumers in the form of higher
prices. However, this does not mean that the impacts of a regulation will have no impact on
producers of goods and services affected by a regulation. For example, the long run may cover
the time taken to retire today's entire capital equipment, which could take decades. Therefore,
transitory impacts could be protracted and could dominate long-run impacts in terms of present
value. In addition, to evaluate impacts on current producers, the long-run approach is not
appropriate. Consequently a time horizon that falls between the very short-run/full-cost-
absorption case and the long-run/full-cost-pass-through case is most appropriate for this EIA.
7.2.1.4.3 Intermediate Run Analysis
The intermediate run time frame allows examination of impacts of a regulatory program
during the transition between the very short run and the long run. In the intermediate run, there
is some resource immobility which may cause producers to suffer producer surplus losses.
Specifically, producers may be able to adjust some, but not all, factors of production, and they
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Chapter 7: Economic Impact Analysis
therefore will bear some portion of the costs of the regulatory program. The existence of fixed
production factors generally leads to diminishing returns to those fixed factors. This typically
manifests itself in the form of a marginal cost (supply) function that rises with the output rate, as
shown in Figure 7-4.
Price
Increase
81: With Regulation
Unit Cost Increase
b ^^ S0 : Without Regulation
Qo
Figure 7-4 Intermediate-Run: Partial-Cost Pass-Through
Output
Again, the regulation causes an upward shift in the supply function. The lack of resource
mobility may cause producers to suffer profit (producer surplus) losses in the face of regulation;
however, producers are able to pass through some of the associated costs to consumers, to the
extent the market will allow. As shown, in this case, the market-clearing process generates an
increase in price (from PO to PI) that is less than the per-unit increase in costs, so that the
regulatory burden is shared by producers (net reduction in profits) and consumers (rise in price).
In other words, there is a loss of both producer and consumer surplus.
7.2.1.5 Economic Impacts of a Control Program - Single Market
A graphical representation of a general economic competitive model of price formation,
as shown in Figure 7-5(a), posits that market prices and quantities are determined by the
intersection of the market supply and market demand curves. Under the baseline scenario, a
market price and quantity (p,Q) are determined by the intersection of the downward-sloping
market demand curve (DM) and the upward-sloping market supply curve (SM). The market
supply curve reflects the sum of the domestic (Sd) and import (Sf) supply curves.
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Regulatory Impact Analysis
= P
Domestic Supply
Foreign Supply
a) Baseline Equilibrium
Q
Market
P'
P
S',
P'
P
q'd qd
Domestic Supply
Foreign Supply
b) With-Regulation Equilibrium
Q' Q
Market
Figure 7-5 Market Equilibrium Without and With Regulation
With the regulation, the costs of production increase for suppliers. The imposition of
these regulatory control costs is represented as an upward shift in the supply curve for domestic
and import supply by the estimated compliance costs. As a result of the upward shift in the
supply curve, the market supply curve will also shift upward as shown in Figure 7-5(b) to reflect
the increased costs of production.
At baseline without the new standards, the industry produces total output, Q, at price, p,
with domestic producers supplying the amount qd and imports accounting for Q minus qd, or qf.
With the regulation, the market price increases from p to p', and market output (as determined
from the market demand curve) decreases from Q to Q'. This reduction in market output is the
net result of reductions in domestic and import supply.
As indicated in Figure 7-5, when the new standards are applied the supply curve will shift
upward by the amount of the estimated compliance costs. The demand curve, however, does not
shift in this analysis. This is explained by the dynamics underlying the demand curve. The
demand curve represents the relationship between prices and quantity demanded. Changes in
prices lead to changes in the quantity demanded and are illustrated by movements along a
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Chapter 7: Economic Impact Analysis
constant demand curve. In contrast, changes in consumer tastes, income, prices of related goods,
or population would lead to change in demand and are illustrated as shifts in the position of the
demand curve.E'25 For example, an increase in the number of consumers in a market would
cause the demand curve to shift outward because there are more individuals willing to buy the
good at every price. Similarly, an exogenous increase in average income would also lead the
demand curve to shift outward or inward, depending on whether people choose to buy more or
less of a good at a given price.
7.2.1.6 Economic Impacts of a Control Program - Multiple Markets
The above description is typical of the expected market effects for a single product
market considered in isolation (for example, the ocean transportation service market). However,
the markets considered in this EIA are more complicated because they are linked: the market for
engines is affected by the market for vessels, which is affected by the market for international
marine transportation services. In particular, it is reasonable to assume that the input-output
relationship between the marine diesel engines and vessels is strictly fixed and that the demand
for engines varies directly with the demand for vessels. Similarly, the demand for vessels varies
directly with the demand for marine transportation services. A demand curve specified in terms
of its downstream consumption is referred to as a derived demand curve. Figure 7-6 illustrates
how a derived demand curve is identified.
Price
Equipment
($/Q)
APE
Q .Equipment
Price
Engines
($/Q)
APei
nit Cost Increase
Derived
Demand
AQeng
AQE = AQei
Q - Engines
Figure 7-6 Derived-Demand Curve for Engines
E An accessible detailed discussion of these concepts can be found in Chapters 5-7 of Nicholson's (1998)
intermediate microeconomics textbook.
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Regulatory Impact Analysis
Consider an event in the engine market, such as a new technology requirement, that
causes the price of an engine to increase by APeng. This increase in the price of an engine will
cause the supply curve in the engine market to shift up, leading to a decreased quantity (AQeng).
The change in engine production leads to a decrease in the demand for equipment (AQE). The
difference between the supply curves in the equipment market, S'E - SE, is the difference in price
in the engine market, APeng, at each quantity. Note that the supply and demand curves in the
equipment market are needed to identify the derived demand in the engine market.
In the market for vessels and engines, the derived demand curves are expected to be
vertical. The full costs of the engines will be passed into the cost of vessels, and the cost of
vessels will be passed into the cost of ocean transportation.
7.2.1.7 Using Economic Theory to Estimate the Social Costs of a Control Program
The economic welfare implications of the market price and output changes with the
regulation can be examined by calculating consumer and producer net "surplus" changes
associated with these adjustments. This is a measure of the negative impact of an environmental
policy change and is commonly referred to as the "social cost" of a regulation. It is important to
emphasize that this measure does not include the benefits that occur outside of the market, that
is, the value of the reduced levels of air pollution with the regulation. Including this benefit will
reduce the net cost of the regulation and even make it positive.
The demand and supply curves that are used to project market price and quantity impacts
can be used to estimate the change in consumer, producer, and total surplus or social cost of the
regulation (see Figure 7-7).
7-26
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Chapter 7: Economic Impact Analysis
$/Q
Q2 Q,
(a) Change in Consumer Surplus with
Regulation
Q/t
$/Q
Q/t
(b) Change in Producer Surplus with
Regulation
$/Q
Q2 Q,
(c) Net Change in Economic Welfare with
Regulation
Q/t
Figure 7-7 Economic Welfare Calculations: Changes in Consumer, Producer, and Total Surplus
The difference between the maximum price consumers are willing to pay for a good and
the price they actually pay is referred to as "consumer surplus." Consumer surplus is measured
as the area under the demand curve and above the price of the product. Similarly, the difference
between the minimum price producers are willing to accept for a good and the price they actually
receive is referred to as "producer surplus." Producer surplus is measured as the area above the
supply curve and below the price of the product. These areas can be thought of as consumers'
net benefits of consumption and producers' net benefits of production, respectively.
7-27
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Regulatory Impact Analysis
In Figure 7-7, baseline equilibrium occurs at the intersection of the demand curve, D, and
supply curve, S. Price is PI with quantity Qi. The increased cost of production with the
regulation will cause the market supply curve to shift upward to S'. The new equilibrium price
of the product is ?2. With a higher price for the product there is less consumer welfare, all else
being unchanged. In Figure 7-7(a), area A represents the dollar value of the annual net loss in
consumer welfare associated with the increased price. The rectangular portion represents the
loss in consumer surplus on the quantity still consumed due to the price increase, Ch, while the
triangular area represents the foregone surplus resulting from the reduced quantity consumed, Qi
-Q2.
In addition to the changes in consumers' welfare, there are also changes in producers'
welfare with the regulatory action. With the increase in market price, producers receive higher
revenues on the quantity still purchased, Ch. In Figure 7-7(b), area B represents the increase in
revenues due to this increase in price. The difference in the area under the supply curve up to the
original market price, area C, measures the loss in producer surplus, which includes the loss
associated with the quantity no longer produced. The net change in producers' welfare is
represented by area B - C.
The change in economic welfare attributable to the compliance costs of the regulations is
the sum of consumer and producer surplus changes, that is, -(A) + (B-C). Figure 7-7(c) shows
the net (negative) change in economic welfare associated with the regulation as area D.
7.2.1.8 Fixed and Variable Costs in a Competitive Market
The estimated engineering compliance costs, consisting of fixed costs (R&D
capital/tooling, certification costs), variable costs, and operational costs, provide an initial
measure of total annual compliance costs without accounting for behavioral responses. The
starting point for assessing the social costs and market impacts of a regulatory action is to
incorporate the regulatory compliance costs into the production decision of the firm.
7-28
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Chapter 7: Economic Impact Analysis
$/q
MC'
P _
Figure 7-8 Modeling Fixed Regulatory Costs
In general, shifting the supply curve by the total cost per unit implies that both capital and
operating costs vary with output levels. At least in the case of capital, this raises some questions.
In the long run, all inputs (and their costs) can be expected to vary with output. But a short(er)-
run analysis typically holds some capital factors fixed. For instance, to the extent that a market
supply function is tied to existing facilities, there is an element of fixed capital (or one-time
R&D). As indicated above, the current market supply function might reflect these fixed factors
with an upward slope. As shown in Figure 7-8, the marginal cost (MC) curve will only be
affected, or shift upwards, by the per-unit variable compliance costs (ci=TVCC/q), while the
average total cost (ATAC) curve will shift up by the per-unit total compliance costs (c2=TCC/q).
Thus, the variable costs will directly affect the production decision (optimal output rate), and the
fixed costs will affect the closure decision by establishing a new higher reservation price for the
firm (i.e., pm'). In other words, the fixed costs are important in determining whether the firm will
stay in this line of business (i.e., produce anything at all), and the variable costs determine the
level (quantity) of production.
Depending on the industry type, fixed costs associated with complying with a new
regulation are generally treated differently in an analysis of market impacts. In a competitive
market, the industry supply curve is generally based on the market's marginal cost curve; fixed
costs do not influence production decisions at the margin. Therefore, the market analysis for a
competitive market is based on variable costs only.
7-29
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Regulatory Impact Analysis
Implicit in this approach is the assumption that manufacturers do not recover their
production fixed costs by passing all or part of them to consumers through new price increases.
Yet, production fixed costs must be recovered; otherwise, manufacturers would go out of
business. Manufacturers in any industry are likely to have ongoing product development
programs the costs of which are included in the current market price structure. It is expected that
the resources for those programs would be re-oriented toward compliance with the regulatory
program until those costs are recovered for each manufacturer. If this is the case, then the rule
would have the effect of shifting product development resources to regulatory compliance from
other market-based investment decisions. Thus, fixed costs are a cost to society because they
displace other product development activities that may improve the quality or performance of
engines and equipment. In this EIA, fixed costs are included in the total social costs in the year
in which they occur.
7.2.2 How Is This Economic Theory Applied In This EIA?
In the above explanation of how to estimate the market and social welfare impacts of a
control action, the price elasticities of supply and demand were nonzero. This was reflected in
the upward-slope of the supply curve and the downward slope of the demand curve. In the
derived demand analysis, a nonzero price elasticity of demand in the vessel market yielded a
nonzero price elasticity of demand in the engine market.
However, the price elasticity of demand in the international shipping market is expected
to be nearly perfectly inelastic (demand curve with near-infinite slope - a vertical demand
curve). This is not to say that an increase in price has no impact on quantity demanded; rather, it
means that the price increase would have to be very large before there is a noticeable change in
quantity demanded.
A nearly perfectly inelastic price elasticity of demand simplifies the analysis described
above. Figure 7-9 reproduces the relationships in a multi-level market but this time with a nearly
perfectly inelastic demand curve in the international shipping market. The relationships between
this market and the markets for vessels and engines means that the derived demand curves for
engines and vessels are also expected to be nearly perfectly inelastic. Specifically, if demand for
transportation services is not expected to be affected by a change in price, then the demand for
vessels will also remain constant, as will the demand for engines.
7-30
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Chapter 7: Economic Impact Analysis
*-^0,trans
(a) The vertical demand curve for
ocean transportation market
..---""
'J-^^
S1,ship
--'' c;
.---"" ^Z.ship
^^-
(b) The vertical demand curve for
ocean vessel market
Q0,eng
(c) The vertical demand curve for
C-3 engine market
Figure 7-9 Market Impacts in Markets with Nearly Perfectly Inelastic Demand
As indicated in Figure 7-9, a change in unit production costs due to compliance with the
engine emission and fuel sulfur requirements of the coordinated strategy shifts the supply curves
for engines, vessels, and ocean transportation services. The cost increase causes the market price
to increase by the full amount of per unit control cost (i.e. from P0 to PI) while the quantity
demanded for engines, vessels, and transportation services remains constant. Thus, engine
manufacturers are expected to be able to pass on the full cost of producing Tier III compliant
engines to the vessel builders, who are expected to be able to pass the full cost of installing the
engines and fuel switching equipment on to the vessel owners. The vessel owners, in turn, are
expected to be able to pass on these cost increases, as well as the additional operating costs they
incur for the use of SCR reductant (urea) and low sulfur fuel while operating in the waterways
covered by the coordinated strategy.
7-31
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Regulatory Impact Analysis
Note that the fuel and urea costs affect the ocean transportation services market directly,
but affect the vessel and engine markets only through the derived demand curves. That is, the
equilibrium prices and quantities for vessels and engines will change only if the quantity of
ocean transportation services demanded changes due to fuel and urea costs. Because the changes
in fuel and urea prices are expected to be too small to affect the quantity of ocean transportation
services demanded, the markets for vessels and engines are not expected to be affected by fuel
changes.
7.3 Estimating Market Impacts on the Marine Transportation Market
To characterize the increase in vessel operating costs due to the coordinated strategy,
calculations were performed for three types of ocean going vessels, container, bulk carrier, and
cruise liner. Our estimates were developed using typical vessel characteristics, projected fuel
and urea costs, and worst case sea-route data. This section presents the methodology used for
these calculations.
7.3.1 Container Vessel
A typical container vessel was derived using data obtained from the Lloyd's of London
Sea-Web Database26. This data base includes information on actual vessel size (Dead Weight
Tonnes (DWT)) and engine power (kilowatt - hour (kW-hr)) for a wide range of vessel types.
Operating costs included those associated with switching from residual fuel to 0.1%
sulfur distillate fuel and urea consumption for vessels equipped with selective catalytic reduction
(SCR). The fuel and urea costs are based on projections that are presented in the EGA proposal.
These fuel costs estimates are $322/tonne for residual fuel and $468/tonne for 0.1% sulfur
distillate fuel. We use a urea consumption rate of 7.5% of fuel consumption, at $1.52/gallon.
rrAnge.es to Singapore: 7,700 nm
Figure 7-10 Example Sea Route
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Chapter 7: Economic Impact Analysis
To develop a representative sea-route for our price estimations, we created a 'circle route'
for a theoretical trip. Since the Port of Los Angeles27, one of the largest ports in the U.S., lists
the majority of its cargo as traveling from South Asia, our route had a vessel hypothetically
travel from Singapore to the Port of Seattle, then down the West Coast of the United States
(U.S.) to the Port of Los Angeles, then back to Singapore. To map this route, we divided it into
three "legs." The first leg has the vessel traveling from Singapore to the Port of Seattle; the
second part travels down the West Coast of the U.S. to the Port of Los Angeles/Long Beach
(POLA/LB); the third leg continues from Los Angeles to Singapore. This trip is illustrated in
Figure 7-10. The total distance for this route was determined from http://nauticaldistance.com/,
and is described below.
We understand that it will take some additional time and distance to switch vessel
operations from one fuel to another. Additionally, we acknowledge that vessels may enter the
EGA at an angle relative to the port in question, and would be operating in the EGA for a slightly
longer distance than the 200 nautical miles of the EGA. Therefore, to make our fuel usage
estimates as accurate as possible, we included some additional EGA traversing distances in our
circle route calculations, adding 183 nm to the distance for reaching the Port of Seattle, and 35
nm to the distance from POLA/LB.
7.3.1.1 Baseline Operating Costs
In order to begin our estimated fuel cost increases, we needed to establish the fuel usage
and prices for our baseline route (i.e., the price of the route operating on residual fuel). We
determined average operational values for our hypothetical vessel by selecting the mid-point of
the operational ranges used today by OGV. Therefore, our baseline estimations for the fuel
usage for the first leg were determined by multiplying the engine power for the average sized
containership (in kilowatts (kW)) by the average estimated engine efficiency (80 percent) as well
as the average residual fuel consumption (195 grams fuel per kilowatt hour (g/kW-hr)).
(Equation 7-1) This value was then multiplied by the nautical miles (nm) for the first leg of the
trip (the distance from Singapore to Seattle (7,064 nm)), and divided by the average engine speed
(16 knots). To obtain the correct units for the calculation, a unit conversion was also included.
(Equation 7-2) As average values are represented here, it is possible that these values could
fluctuate slightly depending on the vessel's speed, engine efficiency, and specific fuel
consumption, but we believe that these estimates provide a reasonable forecast for the majority
of container vessels in operation today.
7-33
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Regulatory Impact Analysis
Equation 7-1
36,540Wx 0.8x195^™ dw , = 5,700,240^™ d
-hr ' ' /hr
Equation 7-2
5,700,240 ^res% x7,Q64nm
- -
l,000,000g
= 2,5 17 tonne resid
The same determinations were conducted for the second leg of the trip (1,143 nm,
Equation 7-3) and the third leg (7,669 nm, Equation 7-4).
Equation 7-3
5,700,240^^. xl,143iwi tonne
/-nL = 407tonne
16 knots/ l,000,000g
Equation 7-4
5,700,240 gresid/ x7,669nm tonne
, , x = 2J32tonne
16 knots/ l,000,000g
resid
resjd
Total fuel usage for each leg of the trip was multiplied by the price of the fuel (2006 U.S.
dollars per tonne ($/tonne) which provided the baseline cost of fuel for each leg. These costs
were then summed to produce an aggregate estimation of fuel cost for the entire circle trip
(Equation 7-5). This calculation provides the baseline cost of about $1.8M for an average sized
container ship to traverse the theoretical circle route.
Equation 7-5
(2,5\7tonneresid+4Q7tonneresid+2,732tonneresid)x $322.48/tonneresid = $1,823,947
7.3.1.2 Operating Costs with an ECA
Operating cost increases due to an ECA are due to increased fuel costs and urea
consumption within the ECA. Operating costs are assumed to remain unchanged outside the
ECA. In addition, the ECA is assumed to have no impact on the route travelled.
7.3.1.2.1 Increased Fuel Costs
To determine the fuel usage and price increase caused by the ECA on our vessel traveling
our theoretical circle route, we conducted the same analysis as our baseline using the appropriate
distillate fuel properties. Since the distillate fuel will most likely only be used in the ECA, the
7-34
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Chapter 7: Economic Impact Analysis
remainder of the trip will continue operating on residual fuel. Therefore, we adjusted our trip
section distances accordingly, using residual fuel over the first leg for 6,679 nm and over 7,434
nm for the third leg, while the remainder of the trip was determined using a distillate fuel.
Equation 7-6 provides the approximation for engine power and fuel consumption using distillate
fuel and Equation 7-7, 8, and 9 calculate the corresponding trip segment fuel usages. Due to the
chemical properties of the two marine fuels, there is approximately a five percent (5%) increase
in energy, on a mass basis, when operating on the distillate fuel instead of the residual fuel, and
this increase is accounted for in Equation 7-6.
Equation 7-6
J9 5 Sdistil/ ,
36,540kW x 0.8 x /kW-hr = 5 428,800g<*«"/
1 + 0.05 ' ' /hr
Equation 7-7a Residual Fuel Estimation
5,700,240*™^. x 6,679nm tonm
= 2,379tonneresid
, /
16 knots/ 1,000,000 g
/hr
Equation 7-7b Distillate Fuel Estimation
5,428,800 ***i x385nm tonne
? /
I6knots/ l,000,000g
Equation 7-8
5,428,800 *^ x l,143n/» tonm
, / x = 388tonnedlstil
I6knots/ l,000,000g
Equation 7-9a Residual Fuel Estimation
5,700,240^-^' x7,434knots tonne
/ / x = 2,648tonneresjd
I6knots/ l,000,000g
7-35
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Regulatory Impact Analysis
Equation 7-9b Distillate Fuel Estimation
5,428,800-^% x 23 5nm tonm
, / x = monnedlstll
I6knots/ l,000,000g
7.3.1.2.2 Urea Costs
Switching to a distillate marine fuel will achieve reductions only in sulfur and particulate
emissions. In order to meet the required nitrogen oxides (NOx) emission reductions, vessel
owners/operators would need to install a Selective Catalytic Reduction (SCR) device, or similar
technologies, on new vessels built in 2016 and later. Using an SCR requires dosing exhaust
gases with urea to aid with the emission reductions, which adds some additional costs to the
operation of the vessel. In an SCR on a marine engine, the average dosage of urea is seven and a
half percent (7.5%) per gallon of distillate fuel used. Subsequently, to estimate the volume of
urea required for our circle route, we multiplied the distillate quantity determined above by this
urea percentage (Equation 7-10). As we expect these costs to be incurred several years in the
future, we used the analysis preformed for the EPA by EnSys28 which predicted that in 2020,
33.2% of the fuel used in EGAs will be on vessels equipped SCR. The urea costs below are
adjusted to reflect this prediction.
Equation 7-10
599tonnesdlstil x —^ x —^ x 264'llSal x0.075 = 14,185ga/_ x0.332 = 4,709ga/_
O.OOltonne &36.6kgdistil m
To determine the additional price of our vessel's operation through the EGA, we then
multiplied the fuel and urea quantities by their corresponding prices ($322.48/tonne for residual,
$467.92/tonne for distillate, and $1.52/gal for the urea). We then summed these values to
determine the aggregate price for fuel and urea required for our container vessel to travel our
circle route with the proposed EGA in place (Equation 7-11).
Equation 7-11
[(2,379tonneresid + 2,648tonneresid)x $322.48 / tonneresid ] +
[(13 \tonne dism + 388tonnedistil + monnedistil) x $467.92 / tonne ^ ] +
(4,709galurea x $l.52/galurj = $1,908,549^
The total estimated price for an average sized containership traversing the circle with the
EGA in place is just over $1.9M. The cost increase of this trip caused by the fuel and urea prices
used in the EGA came from subtracting the baseline (residual fuel) trip price from the EGA price
(Equation 7-12). The price differential between the baseline trip and the EGA trip is
demonstrated in Equation 7-13 and takes into consideration the fuel cost portion of the
operational cost for a vessel, which is typically around 60 percent of the total. As can be seen,
by operating in the EGA for our theoretical circle route it is estimated that the operational costs
due to the distillate fuel is approximately three percent (3%).
7-36
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Chapter 7: Economic Impact Analysis
Equation 7-12
$1,908,549^ -$1,823,947^ = $84,602
Equation 7-13
$1 908 549 - $1 823 947
0 60 x * I>™*>^ECA » 1,*<",W lhaseime x ! op = 2 8%
947
yt/
To put this price increase in some perspective, we assumed our average sized
containership was hauling goods, such Twenty-foot Equivalent Units (TEU), and estimated the
increase per each TEU. Estimating these prices required the cargo weight of the vessel.
Literature shows that approximately 93-97% of a container vessel's DWT is used for hauling
cargo, with the remaining weight composing the crew, vessel engines and hull, and fuel.29
Equation 7-14 shows the calculation used to convert the vessel's DWT to cargo weight using the
middle value of 95%.
Equation 7-14
50,814DffT x 0.95 = 48,273cargo_ tonnes
Dividing the difference between the baseline fuel price and the EGA fuel price we
calculated previously by the cargo tonnes as established in Equation 7-14 provided the price
increase per tonne of good shipped for the entire route (Equation 7-15).
Equation 7-15
($1 908 549 -$1823947 ">
A*™ = $l-75/cargo_to^nOT
48,273c argo _ tonnes
Using this value and the weight of a full TEU (10 metric tonnes)30, we determined the
cost increase for shipping a fully loaded TEU across our circle route (Equation 7-16).
Equation 7-16
$1.75 Wtonnes
cargo _tonnemcrease full _TEU
7.3.2 Bulk Carrier
= $l7.53/full_TEUmcrease
Since the majority of goods transported to the U.S. are brought by bulk carriers as well as
container vessels, and bulk carriers are of a different construction than container vessels, we also
conducted estimations as to what the price increase per tonne of bulk cargo would be due to the
EGA. For a comparison, we calculated what the price increase would be for a tonne of bulk
cargo carried on a vessel traversing the same theoretical circle route as the containership.
7-37
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Regulatory Impact Analysis
Equation 7-17 shows the same calculations as performed above for the containership
using the average engine power for a bulk carrier (3,825 kW) and the total trip distance (15,876
nm)
Equation 7-17
««•<*/__- . v,^,™™ towwg
x = 592tonne.d
l,000,000e
/V
This determination was also conducted for the EGA, using the appropriate values for the
distillate part of the circle route (1,763 nm) and the residual fuel part of the route (14,113 nm)
(Equation 7-18 and 19 respectively). Equation 7-20 determines the urea required for use in the
EGA (as was established in Equation 7-10), and Equation 7-21 estimates the overall price
increase for the bulk carrier if it was to operate on the theoretical circle route through the EGA.
Equation 7-18
IQS^ resid/ -\ ^/-^ ^
/ 7 T/T/" 1 \ I f~\ i ^7777 IftWTlf*
3,825kW x 0.8 x / KW - nr x , x = $i£tonne
1 + 0.05 i6knots/ 1,000,0002-
/hr
Equation 7-19
3,825Wx 0.8 x 195s™d/,w _h xl4,113w»i tonne
1 ~^- X = 526toWWere«d
I6knots/ l,000,000g
Equation 7-20
62.6tonnesdlsta x—-^ x-—^ x 264'llSal x0.075 = l,4*3galma x0.332 = 492galurea
O.OOltonne 836.6kg distil m
Equation 7-21
[(62.6tonnedlsa x $467.927tonnedlstil) + (526tonneresid x $322.487tonneresid) + (492galurea x $1.52/galurea)]
- [592tonneresid x $322.48 / tonneresid ] = $8,756mcr_
To establish this price increase in terms of bulk cargo shipped, the value from Equation
7-21 was divided by the available cargo weight for the bulk carrier which was determined from
the actual vessel weight (16,600 tonnes) as was performed in Equation 7-14 (Equation 7-22).
7-38
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Chapter 7: Economic Impact Analysis
Equation 7-22
= $0.567 bulk _ c arg o _ tonne inc
(16,6QQbulk_cargo_ tonnes x 0.95)
As can be seen, for an average bulk carrier that would travel from Singapore to Seattle,
POLA/LB, and then back out to Singapore, the price increase caused by operation in the EGA
would be around $0.56 per tonne of good shipped. As with the other vessels, this price would
fluctuate depending on the distance traveled within the EGA, the vessel's speed, and the engine
power used.
7.3.3 Cruise Ship
We also conducted an analysis on a typical Alaskan cruise liner. These vessels tend to
operate close to shore and would be within the EGA for the majority of their routes. As such,
this analysis presents worst case cost impacts for this type of vessel.
To conduct this analysis, a series of average vessel characteristics were chosen along with
a typical 7 day (168 hours) Alaskan cruise route. The characteristics used below are the main
engine power (31,500 kW), auxiliary engine power (18,680 kW), base specific residual fuel
consumption (178 gfuei/kW-hr for main engines, 188 gfuei/kW-hr for auxiliary engines), distance
between voyage destinations (5 destinations with a distance ranging between 230 to 700 nm
(shown in Table 7-8)), maximum vessel speed (21.5 knots), and the average number of
passengers on-board the vessel (1,886 people). Additionally, the arrival and departure times at
the various ports of call along the cruise route were used to calculate the average speed travelled
between each destination (shown in Table 7-8). The required power for a given journey segment
was calculated using the relationship shown in Equation 7-23. This relationship was developed
for the "2005-2006 BC Ocean-Going Vessel Emissions Inventory,"31 which was conducted by
the Chamber of Shipping of British Columbia, Canada.
Equation 7-23
Required engine power = 0.8199 x (avg speed/max speed)3 - 0.0191 x (avg speed/max speed)2
+ 0.0297 x (avg speed/max speed) + 0.1682
This relationship was developed to approximate effective power given cruise ships'
diesel-electric operation. The auxiliary engines reported within the Lloyd's of London 'Seaweb'
database32, and are presumably operated independently of the vessels main diesel-electric power
generation, as well as assumed to operate at an average of 50% power for the entire voyage.
To demonstrate the price increase for the cruise liner that would operate within the
waterways covered by the coordinated strategy, calculations for one leg of the Alaskan voyage
are shown in Equation 7-24 to 27, the entire trip operational cost increase per person in Equation
7-28, and with Table 7-8 depicting the total increases over the entire trip broken out by
destination.
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Regulatory Impact Analysis
Equation 7-24
11 UK ,. , hr tonne
3l,500kWx 0.5683 x ^Lx704nmx x = l34tonne
kW-hr I6.76knots l,000,000g
Equation 7-25
\34tonneresid $322.48 „„ _. ,
—— ^ x = $22.89 /person^
~esid
tonne
esid
Equation 7-26
3 l,500kW x 0.5683 x ^ x 704nm x — x -
(l.05)kW-hr I6.76knots l,000,000g
Equation 7-27
= 127tonnedlstl
•a
\21tonnedlM $467.92 „.-„,
^- x = $31.62 / person
l,**6people tonnedlsttl
distil
Equation 7-28
$31.62-$22.89 = W.73/perSonmam_mcrease
Table 7-8 Alaskan Cruise Liner Destinations and the Corresponding Operational Price Increases
Destination
Origin
Vancouver
Sitka
Hubbard Glacier
Juneau
Ketchilkan
Destination
Conclusion
Sitka
Hubbard Glacier
Juneau
Ketchilkan
Vancouver
Distance
Between
Locations (nm)
704
253
246
237
534
Average Speed
Traveled Between
Ports (knots)
16.76
16.32
14.47
13.17
15.48
Calculated
Engine Load
(Equation 7-23)
0.5683
0.5385
0.4295
0.3675
0.4856
Total
Estimated Price
Increase / Person ($)
$8.73
$3.06
$2.67
$2.42
$6.13
$2j.02main increase
Additionally, the operational cost increases for the auxiliary engines were estimated.
Equation 7-29 to 33), as well as the cost increases caused by dosing the engine exhaust with urea
(Equation 7-34 & 35), and the total price increase for the cruise (Equation 7-36) divided by the
length of the cruise (Equation 7-37).
7-40
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Chapter 7: Economic Impact Analysis
Equation 7-29
18,680W x 0.50 x ^^ x 168/zrs x = 295tonne ,
kW-hr l,000,000g
295tonneresid $322.48
Equation 7-30
= $50.44 / person resid
l,886people tonneresid
Equation 7-31
18,680W x 0.50 x ^ x 168hrs x — = 281tonnedlM
(1.05)kW-hr l,000,000g
Equation 7-32
28ltonnedlsttl $467.92
, _. .Ill per son dlM
In c\ .r- / , -i ulSlli
,886 people tonne disttl
Equation 7 33
$69.71 - $50.44 = $19.27/^r50«_ _„_
Equation 7-34
6\6.75tonneSdlstil x —-^ x —^ x ^ilZ^. x 0.075 = 14,606ga/urea x 0.332 = 4,849ga/urea
O.OOltonne 836.6kgdistil m
Equation 7-35
Equation 7-36
$23.02 _„___ +$19.27__mcr_ +$3.91arefl_mcr_ = $46.201 persontotal_jmase
Equation 7-37
$46.201 perSontotal mc
= $6.60 / person I day
e _ length
To put this price increase in perspective of the additional cost for a typical seven-day
Alaskan cruise, we also determined the % increase for the various stateroom types available on
the vessel. These values were established as shown in Equation 7-38 and Table 7-9 lists the four
main stateroom types used on a typical Alaskan cruise liner. It should be noted that these
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Regulatory Impact Analysis
estimates are provided for illustration only; cruise ship lines may choose some other method to
allocate the increase in operating costs among passengers.
Equation 7-38
$46.20
Stateroom _ price($599)
x 100 = 7.7%
Table 7-9 Representative Alaskan Cruise Liner Stateroom Price Increases
Stateroom Type
Interior
Ocean View
Balcony
Suite
Original Average Price Per
Night ($)
$100
$200
$300
$400
Percentage
Increase
6.6%
3.3%
2.2%
1.7%
As can be seen from all the above price increase estimations, the additional costs of the
distillate fuel and the urea required to operate in the waterways covered by the coordinated
strategy is not expected to be a significant increase to the overall cost to operate a the vessel,
regardless of vessel type.
7.4 Sensitivity Analyses
This section provides a discussion of the implications of relaxing two assumptions used
in this economic impact analysis: nearly perfectly inelastic demand for marine transportation
services in general and the cruise industry specifically, and the use of a competitive market
structure for the Category 3 marine diesel engine market.
7.4.1 Nearly Perfectly Inelastic Demand - Marine Transportation Services Market
This economic impact analysis is based on the assumption of near-perfectly inelastic
demand for ocean marine transportation services. In this section, we examine the implications of
relaxing this assumption to consider the impacts of the coordinated strategy if consumers of
marine transportation services were able to react to an increase in prices by reducing their
demand for these services.
The marine transportation services market is a global market, which makes it complicated
to estimate the price sensitivity of demand. In addition, that sensitivity would likely vary
depending on the types of goods transported and the type of vessel used. For example, the
demand elasticity for bulk cargo transportation services would likely vary depending on the type
of bulk (e.g., food, oil, electronic goods) and the type of vessel (bulk/tramp or liner). Instead of
estimating these price elasticities, this alternative analysis relies on the price elasticities we
developed for our 2008 rulemaking that set technology-forcing standards for Category 1 and
Category 2 engines (73 FR 25098, May 6, 2008). Although these price elasticities of demand
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and supply were developed using data for United States markets only, they reflect behavioral
reactions to price changes if alternative modes of transportation were available. The values used
for the behavioral parameters for the Category 1 and 2 markets are provided in Table 7-10
Table 7-10: Behavioral Parameters Used in Locomotive/Marine Economic Impact Model
Sector Market Demand Source Supply Source
Elasticity Elasticity
Marine
Marine
Transportation
Services
Commercial Vessels3
Engines
-0.5 (inelastic)
Derived
Derived
Literature
Estimate
N/A
N/A
0.6 (inelastic)
2.3 (elastic)
3.8 (elastic)
Literature
Estimate
Econometric
Estimate
Econometric
Estimate
Notes:
a Commercial vessels include tug/tow/pushboats, ferries, cargo vessels, crew/supply boats, and other commercial
vessels.
The alternative price elasticity of demand for marine transportation services is inelastic,
at -0.5. This means a one percent increase in price will result in a 0.5 percent decrease in
demand. This inelastic demand elasticity will yield inelastic demand elasticities for both engines
and vessels. The estimates of the price elasticity of supply are elastic, consistent with the
primary analysis described above.
Rather than create a computer model to estimate the economic impacts of the coordinated
strategy using this revised set of assumptions, we examine their impact qualitatively. In general,
relaxing the condition of nearly perfectly inelastic demand elasticity would result in the
compliance costs of the coordinated strategy being shared by consumers and suppliers. In the
engine and vessel markets, the share borne by producers would nevertheless be expected to be
small, given the elastic supply elasticity compared to the inelastic demand elasticity. Because
suppliers would bear part of the compliance costs, the price increase for engines and vessels
would be smaller than the per-unit engineering compliance costs. In the marine transportation
market, the price impacts would be shared more equally between producers (vessel owners) and
consumers (firms that purchase marine transportation services), due to the nearly identical price
elasticity of supply (0.6) and demand (-0.5). However, given the relatively small per unit
engineering costs, the total impacts on prices and quantities in these markets would still be
expected to be modest.
In addition, there would be a small change in demand since consumers would react to an
increase in price by reducing their consumption of marine transportation services. Again,
because the relative price impact is small, the impact on quantity would also be small.
The distribution of compliance costs from our earlier rule are presented in Table 7-11.
While the emission control requirements and the compliance cost structure of the coordinated
strategy are somewhat different, these results give an idea of how costs would be shared if the
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assumption of nearly perfectly inelastic price elasticity of demand for the transportation services
market in the ocean-going marine sector were relaxed.
Table 7-11: Distribution of Social Costs among Stakeholder Groups - Category 1 and Category 2 Engine
Program
Stakeholder Group 2020 2030
Marine engine producers
Marine vessel producers
Recreational and fishing vessel consumers
Marine transportation service providers
Marine transportation service consumers
Total
0.8%
10.7%
8.4%
36.4%
43.8%
100.0%
0.5%
3.8%
4.1%
41.5%
50.0%
100.0%
7.4.2 Nearly Perfectly Inelastic Demand - Cruise Market
Representatives of the cruise industry commented that, unlike the other transportation
services affected by the coordinated strategy, the demand for cruises is not nearly perfectly
inelastic. These commenters noted that cruises are a recreational activity and consumers are
more sensitive to price changes than consumers of transportations services for containers or bulk
goods. They contend that if the price of a cruise increases, consumers will choose to spend their
recreational budgets on other activities.
Clearly, the consumers in that market, tourists and holiday-makers, have alternatives
available for their recreational activities. In the case of a cost increase from a proposed
regulatory program, if the cost of a cruise increases too much, they may decide to spend their
vacation in other activities closer to home, or may elect to fly somewhere instead. To reflect
these conditions, it would be necessary to use a more elastic demand elasticity for cruises, one
larger than -0.5. As illustrated in Table 7-10, an elastic demand for marine transportation
services means that the compliance costs associated with the coordinated strategy will be shared
among the cruise providers and their customers, rather than being passed on completely to the
passengers through higher prices. While this distribution of the compliance burden may offset at
least partially a decline in demand for cruises through smaller price increases, it also means that
cruise ship companies will bear at least part of the compliance costs of the program.
The share of the compliance costs that will be borne by the cruise industry suppliers will
depend on the magnitude of the demand elasticity. If the price elasticity of demand is larger (in
absolute value) than the price elasticity of supply, ship owners will bear a larger share of the
costs of the program; if the price elasticity of demand is smaller (in absolute value) than the price
elasticity of supply, consumers will bear a larger share of the program. Similarly, the vessel
builders and engine manufacturers will also bear a portion of the costs. If the quantity demanded
for cruises decreases, the derived quantity demanded for vessels will decrease, as will the derived
quantity demanded for engines. If the supply curves for these industries are not perfectly elastic
(i.e., horizontal), then the downward-sloping derived demand curves will lead to shared impacts
among all of the affected sectors.
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In our recreational vehicle rule we estimated the demand elasticity for inboard cruisers to
be about -1.4 and the supply elasticity to be about 1.6.33 Using these values as a proxy for cruise
ship demand and supply, this suggests that the compliance costs will be share among passengers
and operators roughly evenly
As described in Section 7.3 of this chapter, the compliance costs associated with the
coordinated strategy are expected to be small compared to the daily costs of a cruise, at about $7
per night. Overall, total engine and vessel costs are expected to increase about one percent and
operating costs increasing between 1.5 and 6 percent. These increases are within the range of
historic variations in bunker fuel prices. So, although relaxing the assumption of nearly perfectly
elastic demand elasticity for cruises means the burden of the coordinated strategy would be
shared between cruise ship operators and cruise ship passengers, those costs, and therefore the
expected price increases, are expected to be small compared to the price of a cruise.
It is worth repeating that this economic analysis holds all other aspects of the market
constant except for the elements of the coordinated strategy. It does not attempt to predict future
market equilibrium conditions, the cruise market will recover from the current economic
downturn. While the cruise sector may be in difficulty due to current economic conditions,
independent of implementation of MARPOL Annex VI or the coordinated strategy, it is not
possible to predict what the conditions will be when the coordinated strategy goes into effecting
2016 for Tier 3 engines and 2020 for 1,000 ppm sulfur fuel or whether the impact of the program
will be more serious for these operators.
Finally, depending on the nature of the demand for cruises, it may be possible for cruise
ship operators to offset some of these increased costs by advertising the environmental benefits
of using engines and fuels that comply with the requirements of the coordinated strategy. Many
cruise passengers enjoy this form of recreational because it allows them a personal-level
experience with the marine environment, and they may be willing to pay an increased fee to
protect that nature. If people prefer more environmentally friendly cruises, then the demand
curve for these cruises will shift up. Consumers will be willing to bear more of the costs of the
changes. If the demand shift for environmentally friendly cruises is large enough, both the
equilibrium price and quantity of cruises might increase.
7.4.3 Engine Market Structure
This Economic Impact Analysis assumes that the market structure for the Category 3
marine diesel engine market is competitive. As explained in section 7.2.1.3.3, this is a
reasonable assumption given the level of competition among the two primary manufacturers, the
maturity of the market, and the similarity of their products. This section discusses the impacts of
relaxing that assumption.
Nevertheless, we can examine whether assuming an oglipolistic market structure will
have an impact on the results of this EIA.
In an oligopolistic market, producers are able to set the market price at a level higher than
the competitive market clearing price. They can do this by creating a cartel, by making
assumptions about their competitors output and making their own production decisions
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accordingly (Cournot or conjectural models), or by engaging in price leadership (setting a price
and seeing the response of the other firm). Alternatively, firms can compete through product
differentiation or advertising.
In each case, the result is a market price set above cost and firms are able to capture a
markup in profits.
If this is currently the case in the Category 3 marine engine market, engine prices already
reflect this oligopoly premium. This rule will not affect whether or not market prices are already
higher than would be the case under competition. Those oligopoly prices would already be
reflected through the associated vessel and marine transportation service markets.
However, if the engine market is indeed an oligopoly, it means that the price increases
expected for the engine market would be more than the engineering costs, to reflect the oligopoly
premium. Therefore, instead of an increase of approximately $700,000 for a container ship with
a 13,900 kW engine, the price increase would be higher. This higher price would affect the
vessel and marine transportation markets. While engine and vessel manufacturers would pay a
higher price for the engines, this additional cost would be passed to the users of the vessel
transportation services due to the assumption of nearly perfectly inelastic demand for those
services. As a result, the additional cost due to a functioning oligopoly would be borne by the
consumers of transportation services, and ultimately by the consumers of goods transported
using those services. In other words, there would be a transfer of wealth from consumers to
Category 3 engine manufacturers.
The makeup of the price over marginal cost is an important concept in both industrial
organization and macroeconomics due to the implications it has for market competition, and for
determining the extent to which excess capacity exists in an industry. However, since the
marginal cost is not directly observable, the markup is not straightforward to estimate from data.
For many years, the markup was computed using an approach that focused on estimating
the slope of the demand schedule (for survey of this work see Bresnahan.34 However, Hall's
methodology then displaced this as the most popular framework, which remains as the
foundation of the majority of papers that are written even today.35 Hall's framework tries to
estimate marginal cost as the observed change in cost as output changes from one year to the
next. This methodology is then applied to US manufacturing data, which allows Hall to derive
estimates of the markup. In his 1988 paper, Hall addressed the markup behavior of firms in a
number of industries and comes to the conclusion that markups exist and are large. According to
Hall, manufacturing firm's prices exceed the costs of added inputs by approximately 63%. Hall
also suggested, however, that profitability implied by these markups may be counteracted by
excess capacity or returns to scale.36
Many papers have since been written which also estimate the markup, most of which are
based on Hall's methodology, or often some extension of it. Some studies examine markup over
marginal cost by modifying the production function that Hall used. Some studies extend Hall's
analysis by including intermediate inputs (materials), and by allowing the markup over time. For
example, Morrison [1988] modified Hall' study, and addressed a production theory-based model
of firm's markup behavior, in a short run econometric approach. The estimation was carried out
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using manufacturing data from the U.S. and Japan from 1960 through 1981.37 The capacity
utilization, return to scale, and demand and supply shock directly affect the markup (statistically
significant). The average markup is from 11% to 23% for the US manufacture and from 7% to
48% for the Japan manufacture.
The most recent study was done by Mazumder.38 Mazumder extended Hall's framework
by developing a new measure of marginal cost. Instead of estimating the absolute levels of the
markup, He estimated the change in the trends over time and its movement over the business
cycle. The study used the Census Bureau data for 13 surveys between 1954 and 2007. Results
indicated that the new markup index for the US manufacturing sector was decreasing in size
from 1960s to 2007 on the order of 20%, which indicated that, the degree of market power
prevalent in the manufacturing industry has been reduced by a sizable margin in this time period.
The results suggested that foreign competition-as measured by the share of manufactured goods
that were imported- was the main determinant for the decline in the manufacturing markup.
Domestic competition also played an important role, although to a much lesser extent than
foreign competition.
If we assume a noncompetitive structure for the Category 3 marine diesel engine market,
using a 20 percent markup, this means that the portion of the engine costs passed on to vessel
manufacturers and vessel purchasers would be 20 percent higher. However, given the relatively
small engine compliance costs associated with this rule, such a markup is not expected to
significantly change the results of the analysis, especially given the nearly perfectly competitive
market assumption for the vessel and marine transportation markets.
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Reference
1 U.S. EPA. (2000). EPA Guidelines for Preparing Economic Analyses. EPA 240-R-00-003. A
copy of this document can be found at
http://yosemite.epa.gov/ee/epa/eed.nsf/webpates/guidelines.html
2 Stopford, M. (2009). Maritime Economics, 3rd Edition. Routledge, Page 519. See also, World
Trade Organization, World Trade Report 2004: Exploring the linkage between the domestic
policy environment and international trade. Page 117, Taboel 1 IB.4 Sea freight rates on the
three major liner trade routes, 2000-2004.
3 Census Bureau's Foreign Trade Division, U.S. Waterborne Foreign Trade by U.S. Custom
Districts., as reported by the Maritime Administration at
http://www.marad.dot.gov/library _landing_page/data_and_statistics/Data_and_Stati sties.htm,
accessed April 9, 2009.
4 U.S. Census Bureau, Industry Statistics Sampler, NAICS 48311, Deep sea, coastal, and Great
Lakes transportation, at http://www.census.gov/econ/census02/data/industry/E48311 .HTM,
assessed on April 9, 2009.
5 UNCTAD, Review of Marine Transportation (2003), as cited in World Trade Organization,
World Trade Report 2004: Exploring the linkage between the domestic policy environment and
international trade, http://www.wto.org/english/res_e^ooksp_e/anrep_e/world_trade_report04_e.pdf assessed
on April 9, 2009.
6 U.S. EPA. "OAQPS Economic Analysis Resource Document." Research Triangle Park, NC:
EPA 1999. A copy of this document can be found at
http://www.epa.gov/ttn/ecas/econdata/6807-305.pdf; U.S. EPA "EPA Guidelines for Preparing
Economic Analyses." EPA 240-R-00-003. September 2000. A copy of this document can be
found at http://yosemite.epa.gov/ee/epa/eed.nsf/webpates/guidelines.html
7 Bingham, T.H., and T. J. Fox. "Model Complexity and Scope for Policy Analysis." Public
Administration Quarterly, 23(3), 1999.
8 Harrould-Koleib, Ellycia. Shipping Impacts on Climate: A Source with Solutions. Oceana,
July 2008. A copy of this report can be found at
http://www.oceana.org/fileadmin/oceana/uploads/Climate_Change/Oceana_Shipping_Report.pdf
9 Stopford, Martin. Maritime Economics, 3rd Edition. Routledge, 2009. p. 163.
10 Berck, P., and S. Hoffman. "Assessing the Employment Impacts." Environmental and
Resource Economics 22:13 3 -15 6. 2002.
11 U.S. EPA "EPA Guidelines for Preparing Economic Analyses." EPA 240-R-00-003.
September 2000, p. 113. A copy of this document can be found at
http://yosemite.epa.gov/ee/epa/eed.nsf/webpates/guidelines.html
12
Stopford, Martin. Maritime Economics, 3rd Edition. Routledge, 2009. See Chapter 4.
13 Frank, Robert H. Microeconomics and Behavior, 1991, McGraw-Hill, Inc., p 333.
14 Stopford, Martin, Maritime Economics, 3rd Edition. Routledge, 2009, page 32.
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Chapter 7: Economic Impact Analysis
15 World Trade Organization, Council for Trade in Services. Maritime Transport Services:
Background Note by the Secretariat. S/C/W/62, 16 November 1998, p. 2. This document can be
found at www.wto.org/English/Tratop_E/serv_e/w62.doc
16 Stopford, Martin, Maritime Economics., 3rd Edition. Routledge, 2009, p. 41.
17 Sagers, Chris, "The Demise of Regulation in Ocean Shipping: A Study in the Evolution of
Competition Policy and the Predictive Power of Microeconomics," Vanderbilt Journal of
Transnational Law 39 (May 2006), pp. 792-3.
18 World Trade Organization, Council for Trade in Services. Maritime Transport Services:
Background Note by the Secretariat. S/CW/62, 16 November 1998. This document can be
found at: http://www.wto.org/English/Tratop_E/serv_e/w62.doc
19 Stopford, Martin, Maritime Economics, 3rd Edition. Routledge, 2009.
20 Shipbuilders Association of Japan. (2008). Global Shipbuilding Supply and Demand Outlook.
Presented at Shipbuilding Workshop with non-OECD economies and industry, Paris, France,
December 4-5, 2008; http://www.oecd.org/dataoecd/61/41/41812839.pdf, accessed March 5,
2009.
21 US EPA (2003) Final Regulatory Support Document: Control of Emissions from New
Marine Compression-Ignition Engines at or Above 30 Liters per Cylinder. EPA420-R-03-004,
January 2003.
22 Tirole, Jean. The Theory of Industrial Organization (1989). MIT Press. See pages 223-224.
23 Varian, Hal. R. (1993). Intermediate Economics: A Modern Approach, 3rd Edition. Norton.
P.462.
24 http://en.wikipedia.Org/wiki/B ertrand_competition
25 Nicholson, W., Microeconomic Theory: Basic Principles and Extensions, 1998, The Dryden
Press, Harcourt Brace College Publishers.
26 Lloyd's of London Sea-Web Database, Ocean going vessel statistical queries, Retrieved
Autumn 2008, from http://www.sea-web.com/seaweb_welcome.aspx
27 Port of Los Angeles Website, Facts and Figures, Retrieved Spring 2009, from:
http://www.portoflosangeles.org/newsroom/press_kit/facts.asp
28 EnSys Navigistics. (2007). Analysis of Impacts on Global Refining & CO2 Emissions of
Potential MARPOL Regulations for International Marine Bunker Fuels. Final Report for the
U.S. Environmental Protection Agency, 26 September 2007.
29 Wellmer, F.W., Dalheimer, M., Wagner, M. 2008. Economic Evaluations in Exploration. New
York, NY: Springer-Verlag Berlin Heidelberg
30 International Maritime Organization (IMO), (2005), Interim Guidelines for Voluntary Ship
CO 2 Emission Index for use in Trials, MEPC/Circ. 471, 29, Retrieved Spring 2009, from:
http://www.imo.org/includes/blastDataOnly.asp/data_id%3D12740/471.pdf
31 The Chamber of Shipping of British Columbia, Canada, (2007, January 25), 2005-2006 BC
Ocean-Going Vessel Emissions Inventory, Retrieved Spring 2009, from:
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http://www.cosbc.ca/index.php?option=com_docman&task=doc_view&gid=3&tmpl=component
&format=raw&Itemid=53
32 Lloyd's of London Sea-Web Database, Ocean going vessel statistical queries, Retrieved
Autumn 2008, from http://www.sea-web.com/seaweb_welcome.aspx
33 EPA420-02-022, Final Regulatory Support Document: Control of Emissions from
Unregulated Nonroad Engines, Chapter 9. This document is available at
http://www.epa.gov/otaq/regs/nonroad/2002/r02022j.pdf
34Bresnahan, T.F., [1989] "Empirical Studies of Industrial with Market Power", in Schmalensee,
R.., Willing, R. (Ed.), Handbook of Industrial Organization, page 1011-1057. Elsevier.
35 Hall, Robert R. [1988a], "The Relation between Price and Marginal Cost in U.S. Industry",
Journal of Political Economy, Vol. 96, No. 5, October, pp. 921-947.
36 Hall, Robert R. [1988a], "The Relation between Price and Marginal Cost in U.S. Industry",
Journal of Political Economy, Vol. 96, No. 5, October, pp. 921-947; Hall, Robert B. [1988b],
"Increasing Returns: Theory and Measurement with Industry Data", manuscript, presented at the
N.B.E.R. Conference on Economic Fluctuations, Cambridge, Massachusetts, October.
37 Morrison, J. Catherine [1988], "Markup in U.S. and Japan Manufacturing: a Short Run
Econometric Analysis", NEBR Working Paper Series, Working Paper No. 2799.
38 Mazumder, Sandeep [September, 2009], "The Price-Marginal Cost Markup and Determinants
in U.S. Manufacturing", MPRA Paper 17260, University Library of Munich, Germany.
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CHAPTER 8: Small Entity Impact Analysis
This chapter contains the results of our small entity screening analysis for the finalized
rule regarding emissions from Category 3 marine diesel engines (i.e., those marine diesel engines
with per cylinder displacement at or above 30 liters). This analysis is required under the
provisions of the Regulatory Flexibility Act as amended by the Small Business Regulatory
Enforcement Fairness Act (RFA/SBREFA). As described below, our analysis shows that very
few small entities that will be impacted by the final rule. We have determined that there are no
companies with estimated compliance costs exceeding three percent of their revenue. Consistent
with EPA's RFA/SBREFA guidelines, the Administrator is therefore certifying that this rule will
not have a significant economic impact on a substantial number of small entities.
For purposes of assessing the impacts of this rule on small entities, small entity is defined
as: (1) a small business that is primarily engaged in manufacture of large diesel marine engines
as defined by NAICS code 333618 with 1,000 or fewer employees (based on Small Business
Administration size standards) or a small business primarily engaged in the shipbuilding and
repairing as defined by NAICS code 336611 with 1,000 or fewer employees (based on Small
Business Administration size standards); (2) a small business that is primarily engaged in freight
or passenger transportation, either on the Great Lakes or in coastal areas as defined by NAICS
codes 483113 and 483114 with 500 or fewer employees (based on Small Business
Administration size standards); (3) a small governmental jurisdiction that is a government of a
city, county, town, school district or special district with a population of less than 50,000; and (4)
a small organization that is any not-for-profit enterprise which is independently owned and
operated and is not dominant in its field.
This chapter provides some background information on the finalized rule and describes
the outcome of our screening analysis. Section 8.1 describes the engine and fuel standards we
are finalizing. Sections 8.2 and 8.3 provide small business information for the diesel marine
engine program. Section 8.4 provides small business information for the diesel fuel program and
Section 8.5 describes how the rule will impact owners and operators of vessels that operate in
our internal waters.
8.1 Standards
In October 2008, negotiations were successfully concluded for amendments to Annex VI
to the International Convention for the Prevention of Pollution from Ships (MARPOL Annex
VI). These amendments, which are based on the proposal submitted to IMO by the United States
Government in February 2007, set additional tiers of standards for marine diesel engine oxides of
nitrogen (NOx) emissions and the sulfur content of fuel.
Our Category 3 rule will add the Annex VI NOx limits to our Clean Air Act marine
diesel engine requirements for Category 3 engines, and create an allowance for the production of
diesel fuel specifically for these engines. Specifically, we are adopting two additional tiers of
NOx limits for Category 3 engines. The Tier 2 standards will result in a 20 percent reduction in
NOx in 2011 as compared to the existing Tier 1 standards, based largely on in-cylinder control
technologies. The Tier 3 standards, taking effect in 2016, will rely upon high-efficiency exhaust
aftertreatment technology such as selective catalytic reduction (SCR) and will result in an 80
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Chapter 8: Small Entity Impact Analysis
percent reduction in NOx. We are also modifying our diesel fuel program to allow the
manufacture and sale of marine diesel fuel with a sulfur content up to 1,000 parts per millions
(ppm) for use in engines with a displacement of more than 30 liters per cylinder.
As explained below, this rule is not expected to have a significant impact on a substantial
number of small businesses.
8.2 Marine Diesel Engine Manufacturers
The responsibility for meeting the new engine standards will fall on the engine
manufacturers. Such manufacturers are those primarily engaged in manufacture of large diesel
marine engines as defined by North American Industry Classification System (NAICS) code
333618. There are no U.S. companies that manufacture Category 3 marine diesel engines in the
U.S.
While there is one U.S. company that is a parent company to a foreign Category 3 engine
manufacturing company, this company is not a small business (using the Small Business
Administration definition of companies with less than or equal to 1,000 employees), and the
engine manufacturing does not occur in the U.S. We are unaware of any foreign manufacturers
of such engines with a U.S-based facility that qualify as a small business.
For these reasons, we conclude that the finalized engine regulations will not place a
substantial burden on any small U.S. engine manufacturers.
8.3 Vessel Manufacturers
While the primary responsibility for meeting the new engine standards lies with the
engine manufacturers, the vessel manufacturers are potentially affected as well in the case of the
Tier 3 standards. Such manufacturers are those primarily engaged in the shipbuilding and
repairing as defined by NAICS code 336611. Vessel manufacturers will have to accommodate
the addition of exhaust aftertreatment hardware in their design and manufacturing processes.
We have identified 6 shipyards in the U.S. capable of producing Category 3 vessels. Of
those, most build primarily military vessels. One of these shipyards is owned by a foreign
company, and none of these shipyards is a small business that would meet the Small Business
Administration definition of 1,000 or fewer employees.
For these reasons, we conclude that the finalized regulations will not place a substantial
burden on any small U.S. vessel manufacturers.
8.4 Fuel Manufacturers and Distributors
We are revising our diesel fuel program to allow the manufacture and sale of marine
diesel fuel with a sulfur content up to 1,000 ppm for use in Category 3 engines. This will allow
our regulations to be consistent with the new sulfur limits that will become applicable in 2015
under IMO regulations in Emission Control Areas. Our current diesel fuel program sets a sulfur
limit of 15 ppm that is fully phased in by December 1, 2014 for the production of diesel fuel
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designated for use in Category 1 and Category 2 marine applications (DMX and DMA). Without
this change to our diesel fuel regulations, while fuel with a sulfur content of up to 1,000 ppm
could be used on Category 3 applications, it would be unlawful to produce, distribute or sell it
within the United States.
This revision to our diesel fuel program will not require any person to manufacture,
distribute or sell 1,000 ppm sulfur fuel. It simply allows for its production and sale, which is
precluded under our current diesel fuel regulations.
This allowance for 1,000 ppm sulfur fuel will be a benefit to those fuel producers,
distributors or marketers who choose to produce or sell it, as it allows for higher sulfur content
than diesel fuels allowed under current EPA regulations. Since we are not mandating production
of this fuel, fuel manufacturers, distributors and marketers can opt out of producing, distributing
or selling it. Thus, allowing this fuel will not require a mandatory change in any company's
business situation. Those companies that would find it beneficial to produce, distribute or sell
this fuel would do so. Conversely, those companies that would not find it beneficial would
simply continue to operate the way they otherwise would in the absence of this new allowance.
For the reasons just outlined, the allowance we are finalizing for 1,000 ppm sulfur marine
diesel fuel will not place a substantial burden on any small U.S. refiners, pipeline operators, fuel
terminal operators, or fuel marketers.
8.5 Vessel Owners and Operators
Our small business analysis for the proposed rule did not include a separate assessment of
compliance costs for companies that own or operate vessels. Our general approach was to
consider that the Annex VI fuel requirements apply independent of this rulemaking. The global
cap on sulfur standards applies internationally without further action by the United States or any
other government. We expect the EGA standards to eventually apply based on the procedures
spelled out by the International Maritime Organization under Annex VI. Implementing the EGA
standards will involve active participation on the part of the U.S. Government, but this
rulemaking is separate from those EGA fuel requirements that will apply under the provisions of
Annex VI.
Some commenters pointed out that we were proposing to apply the EGA fuel standards to
our internal waters and therefore needed to evaluate the costs of compliance for affected vessel
owners and operators. We agree with this and have performed this analysis.
The most substantial part of the impact of applying the EGA fuel requirements to internal
waters is for the Great Lakes. There are a dozen or more small U.S. businesses operating ships
for freight transportation on the Great Lakes.A However, not all of these companies will face
A These companies operate under NAICS code 483113. The Small Business Administration considers these
companies to qualify as small businesses if they have 500 or fewer employees.
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Chapter 8: Small Entity Impact Analysis
compliance burdens under this rule. Companies would face no new obligations under this rule
for steamships or vessels with Category 1 and Category 2 engines. There will be a cost to
comply with this final rule only for Category 3 engines that currently burn residual fuel. We
adopted fuel-related requirements for Category 1 and Category 2 engines in an earlier
rulemaking (69 FR 38958, June 29, 2004). In a departure from the proposed rule, we are not
applying the fuel-related requirements for the captive fleet of existing steamships on the Great
Lakes. The rule applies no new requirements for Category 3 engines that already operate on
distillate fuel.
We have identified four U.S. companies that are operating Category 3 engines that
currently burn residual fuel, and have estimated the compliance burden for each of these four
companies to comply with the requirements of this final rule based on available information
about the companies and their vessels. Our analysis indicates that three companies will have an
estimated compliance burden representing less than 1 percent of their operating revenues, and
one company will have an estimated compliance burden representing between 1 and 3 percent of
their operating revenues. This analysis also does not include cost savings from increased
durability and reliability or decreased maintenance that occurs when using distillate fuel instead
of residual fuel. Our estimated burden for these companies therefore overestimates the costs
these companies will actually face when complying with the rule. Our analysis indicates that two
companies will have an estimated compliance burden representing less than 1 percent of their
operating revenues, one company will have an estimated compliance burden representing
between 1 and 3 percent of their operating revenues, and one company will have an estimated
compliance burden representing slightly over 6 percent of their operating revenues.
Additionally, in some areas, we consider port areas to be internal waters even though they
are directly accessed by vessels that operate in coastal and international service on the oceans
(such as Puget Sound). We believe it would not be realistic to expect companies operating such
vessels to use distillate fuel as they approach U.S. ports and then convert the engines to operate
on residual fuel for that portion of their operation that is considered internal waters. Since it
would take about an hour of operation to transition back to the residual fuel, we believe this
would not be commonly practiced whether or not fuel requirements apply in internal waters.
Nevertheless, we have analyzed this scenario for potential small business impacts. We found
that one U.S. small business with coastal operations would be affected by this rule, but that they
will have costs representing less than one percent of their revenues. As a result, we have
concluded that all small businesses that own or operate these coastal vessels will see no
significant economic impact in complying with this rule.
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Regulatory Impact Analysis
CHAPTER 9: Alternative Program Options
EPA's coordinated strategy to control emissions from ocean-going vessels consists of a
number of components including Clean Air Act standards for Category 3 engines and
designation of an EGA for U.S. coasts through amendment to MARPOL Annex VI. The
coordinated strategy will ensure that all ships operating within 200 nautical miles of U.S. coasts
meet the most stringent NOx standards and fuel sulfur limits by 2015 (fuel sulfur) and 2016
(engine NOx).
The air quality and benefits analysis we performed for the coordinated strategy suggests
that substantial human health and environmental benefits can be obtained from additional
reductions in emissions from ocean-going vessels, and many stakeholders have expressed a
desire for additional NOx reductions from OGV in earlier years, prior to the effective dates for
the Tier 2 and Tier 3 NOx limits. As described in Section I of the preamble, EPA has a number
of port initiatives under our National Clean Diesel Campaign to reduce emissions from this
sector. These include recognition for efforts by port authorities and their customers to reduce
emissions from OGV through a variety of efforts, grants under the Energy Policy Act of 2005
Diesel Emissions Reduction Program to electrify piers and repower Cl and C2 marine vessels,
and grants under the Clean Air Act to demonstrate sea water scrubbers and to provide incentives
to ship operators to use lower sulfur fuels.A EPA has also sponsored a number of workshops and
conferences focused on exchanging technical information about emissions reduction techniques
for ships (Clean Ships Conference in San Diego in 2007, Faster Freight meetings on East and
West coasts, and up-coming workshop with MARAD).
In addition, we evaluated several programmatic alternatives including mandating the use
of shoreside power in our CAA program, pulling the effective date of the CAA Tier 3 standards
ahead, and various options for addressing emissions from existing engines. We also considered
action under the Clean Air Act to apply the Tier 3 standards to foreign vessels that operate in the
United States. However, as explained in more detail in the preamble, foreign vessels will be
required to comply with the Annex VI NOx and fuel sulfur limits through U.S. EGA designation
and therefore it is unnecessary to take action under the Act at this time.
This chapter presents a summary of our analysis of these alternative control scenarios.
9.1 Mandatory Cold Ironing Requirement
To provide earlier air quality benefits, some have suggested requiring the use of shoreside
power while ships are at dock (called "cold-ironing"). Shoreside power is an effective way to
reduce emissions from ships while they are at berth. The U.S. Navy is a pioneer and has used
cold-ironing successfully for many years. However, to be successful, this strategy requires
changes to both the ship and the port. First, the ship must be equipped to use shore power
through changes to its equipment and electrical systems. The EVIO, working with the
International Organization for Standardization (ISO), is currently developing harmonized
A Clean Ports USA (see www.epa.gov/cleandiesel/ports for further information).
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Chapter 9: Alternative Program Options
requirements for these systems, and we believe it would be more effective for EPA to consider
requiring such systems once the technology is better defined.A Second, the port terminal must
ensure that the electricity is available at the berths. This is a significant barrier to the adoption of
shoreside power on a national basis. However, some port authorities already require cold-
ironing for frequent-calling vessels and are pursuing additional reductions from shoreside port
equipment. The Ports of Los Angeles, Long Beach, Seattle, and Tacoma are among those with
cold-ironing programs. EPA is working with East Coast ports to develop plans for shoreside
power as part of port development plans.
9.2 Earlier Adoption of CAA Tier 3 Standards
We considered a programmatic alternative that would pull ahead the CAA Tier 3 NOx
standard from 2016 to 2014. This would require engine manufacturers to apply SCR two years
earlier than they would be required to under the MARPOL Annex VI program.
This option presents serious technical feasibility challenges. Beginning in 2011,
manufacturers will be introducing new engine-based technologies to meet the Tier 2 standards.
We believe that these new NOx-reducing technologies and emission control approaches will also
be the basis for Tier 3 engine designs. It will be necessary for manufacturers to design, develop,
and validate these engine-based technologies before they can be used in conjunction with
exhaust aftertreatment or additional engine-based technologies required to meet Tier 3 standards.
Once these Tier 2 technologies are mature and well-under stood, they can be further refined and
developed for use with the additional NOx control technologies. The original five-year period
between Tier 2 and Tier 3 was deemed challenging but feasible for engine manufacturers to
design the Tier 3 engines and incorporate those engines into new vessel designs. For this reason,
we do not believe it is technically feasible to advance the Tier 3 standards for new engines
earlier.
Nevertheless, if such an alternative were feasible, we can estimate the inventory benefits
associated with those earlier NOx reductions. Cumulative NOx emission reductions for the
period 2014 to 2023 as a result of the coordinated strategy are estimated to be 3 million short
tons NOx reduction beyond the Tier 1 standards (Table 9-1). Introducing the CAA Tier 3
standards two years earlier would affect only U.S. vessels and would reduce an additional 0.07
million short tons of reduction of NOx beyond our coordinated strategy through 2023. The
method we used to estimate these inventory impacts are presented in Appendix 3B.
A See MEPC 59/4/3 (9 April 2009), Response to IMO Secretariat's invitation to ISO to make recommendations
regarding fuel characteristics and parameters addressing air quality, ship safety, engine performance and crew
health, Submitted by the International Organization for Standardization (ISO).
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Regulatory Impact Analysis
Table 9-1 Comparison of NOX Reductions through 2023 with Adoption of CAA Tier 3 in 2016 versus 2014
SCENARIO
Base Case
(Tier 1 only NOx standards)
Primary Case
(20 16 NOX standards)
Alternative 1
(2014 NOX standards for U.S. Vessels)
NOX EMISSIONS THROUGH 2023
(SHORT TONS)
10,494,636
7,515,389
7,444,866
Due to the technical concerns described above, our review of this alternative leads us to
conclude that advancing the introduction of the Tier 3 NOx standards is not a feasible way to
improve 2023 NOx reductions and could create significant problems for implementation of the
overall coordinated strategy.
9.3 Standards for Existing Engines
We examined a third programmatic alternative, including improvements in NOx
emissions from pre-2016 engines. A control program for existing engines would help many
areas, notably the South Coast of California, to achieve their ozone and PM NAAQS goals
through Category 3 engine NOx reductions sooner than fleet turnover would allow. In this
section we describe several methods to control emissions from existing engines.
9.3.1 Clean Air Act Remanufacturing Program
Our recently-finalized emission control program for marine diesel engines up to 30 liters
per cylinder displacement includes standards that will apply to existing engines at the time they
are remanufactured (73 FR 25098, May 6, 2008, at 25130). In that program, we define "new
marine engine" to include an engine that has been remanufactured, which is defined as
replacement of all cylinder liners, either in one event or over a five-year period. Vessel
owners/operators and engine rebuilders who remanufacture those engines would be required to
use a certified remanufacture system when an engine is remanufactured if such a certified system
is available; if there is no certified kit, there is no requirement until the time of the next
remanufacture event. The program applies to engines with maximum engine power greater than
600 kW and manufactured in 1973 or later, through Tier 2 (2012-14, depending on engine size).
A certified marine remanufacture system must achieve a 25 percent reduction in PM emissions
compared to the engine's measured baseline emissions level without increasing NOx emissions.
The program, which is similar to the locomotive remanufacture program, was possible to
adopt under the Clean Air Act because many commercial Category 1 and 2 engines undergo
periodic full like-new rebuilds to ensure their dependability by returning the engine to as-new
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Chapter 9: Alternative Program Options
condition. Many manufacturers provide guidance for a full rebuild to as-new condition, which
might include replacing piston rings, heads, bearings, and gear train/camshaft as well as piston
liners. Based on discussions with engine manufacturers, we determined that replacing all
cylinder liners is a simple and clear indicator that the servicing being done is extensive enough
for the engine to be considered functionally equivalent to a freshly manufactured engine, both
mechanically and in terms of how it is used. Therefore, we defined remanufacture as the
removal and replacement of all cylinder liners, either during a single maintenance event or over a
five-year period. Marine diesel engines are not considered to be remanufactured if the rebuilding
process falls short of this definition (i.e., the cylinder liners are removed and replaced over more
than a five-year period).
We do not think it is possible to adopt a similar program for Category 3 engines at this
time. Even though Category 3 engines may remain in the fleet for several decades, they are not
maintained in the same way as Category 1 or Category 2 engines. Category 3 engines are very
large, with cylinder sizes of 90 liters not uncommon. Maintenance for these engines is very
different than that for Category 1 or Category 2 engines. Specifically, piston liners, as well as
other engine components, are not replaced unless there is a catastrophic failure. Our analysis of
available information suggests that cylinder liners for engines this large are inspected based on
hours of operation, with the standard interval being about 6,000 to 12,000 hours for engines
operating on residual fuel and up to 25,000 hours for engines operating on distillate fuel. Engine
manufacturers specify how this inspection is to be performed. Typically, the liner is inspected,
measured, dressed, honed or replaced if beyond specifications. As each cylinder has individual
wear characteristics, the complete engine liner replacement is not normally done on all cylinders
at one time, since this would be much more expensive than the maintenance according to the
manufacturer specifications. If there is an extended dry dock, it is possible that a ship owner may
take advantage of this time to inspect and work on several or all cylinders, but it is doubtful that
a complete cylinder liner replacement would be done due to the expense. These engines are an
integral part of the vessel design, and it would be difficult to replace the cylinder liners if it is not
absolutely necessary.
Other maintenance occurs on a cylinder-specific basis and is not comprehensive enough
to return the engine to as-new condition. Finally, engine manufacturers have informed us that
these engines are built to last, with most vessels being scrapped before the engine is worn out.
Operating at lower speeds (130 rpm) also reduces wear on the cylinders.
Based on the above information and because there is no specific maintenance action
common to all Category 3 engines that (1) would return an engine to as-new condition and (2)
could be used to identify engines as being remanufactured and therefore "new," we conclude it is
not possible to extend the marine remanufacture program to Category 3 engines at this time.
9.3.2 MARPOL Annex VI Existing Engine Program
MARPOL Annex VI has two sets of NOx provisions that apply to existing engines.
These requirements will apply to engines on U.S. vessels through the Act to Prevent Pollution
from Ships and are briefly described in this section. In addition to these NOx requirements,
MARPOL Annex VI will provide significant PM reductions from existing vessels through its
fuel sulfur requirements, particularly in a U.S. EGA.
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Regulatory Impact Analysis
First, Annex VI requires any engine above 130 kW that undergoes a major conversion to
comply with the standards that are in effect at the time that major conversion takes place. Major
conversion means the engine is replaced by a non-identical engine, an engine is added to the
vessel, the engine's maximum continuous rating is increased by more than 10 percent, or the
engine undergoes any modification that would increase its emissions.
Second, the recent amendments to Annex VI add a provision that requires all engines at
or above 90 liters per cylinder displacement and above 5,000 kW that were built between 1990
through 1999 to comply with the Tier I NOx limits if there is a certified Approved Method
(remanufacture system) for that engine. This kit-based approach is similar to our domestic
program except it is triggered solely by the existence of a certified remanufacture system and
does not also require a specific remanufacture event (i.e., replacing all cylinder liners either all at
once or within a period of five years). The Tier 1 NOX limits are appropriate for this group of
engines because they often are based on the same or a similar engine platform as the Tier 1
engines and the emission control techniques that apply to Tier 1 engines should also be
applicable to many of the pre-Tier 1 engines. Pre-1990 engines were excluded from this
program because their base engine platforms can be very different from Tier 1 engines; because
many of the original engine manufacturers of these engines are no longer in business; and
because the population of these engines is expected to be too small in 2010 to warrant emission
controls. Engine manufacturers are expected to begin certifying Approved Methods when the
Annex amendments go into force in July 2010; owners will be required to install the kits at the
time of the first renewal survey that occurs 12 months after the kit is certified.
The combination of the Annex VI existing engine program to reduce NOx emissions
from very large Category 3 engines and the Annex VI fuel sulfur program will significantly
reduce NOX and PM emissions from existing vessels. Because these requirements will apply to
Category 3 engines on U.S. and foreign vessels through APPS, it is not necessary to adopt these
same requirements under our Clean Air Act authority to protect U.S. air quality or to implement
Annex VI.
9.3.3 Voluntary Marine Verification Program
We considered a programmatic alternative to encourage additional NOx reductions from
Category 3 engines on ocean-going vessels. In combination with state or local incentives, this
program would provide incentives for owners to achieve, on a voluntary basis, greater emission
reductions earlier than required for new Category 3 engines, and to retrofit existing Category 3
engines with more advanced NOx emission control technologies.
In this approach, States, localities, and ports would encourage vessel owners to
participate in this program through specially-designed incentive plans. This would allow States,
localities, and ports the flexibility to tailor use of the program to their specific needs.
We received comments supporting such a program. However, since it would be
voluntary, we do not believe it is necessary to finalize any regulatory provisions, especially at
this time. Nevertheless, we will continue to evaluate this approach, and will adopt regulatory
provisions if we determine they are necessary.
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Chapter 9: Alternative Program Options
To facilitate such state or local programs, EPA would set up a voluntary Marine
Verification Program as an extension of our current diesel retrofit program. Under this program,
we would provide a verification, based on simplified emission testing, for any vessel owner who
provides data to show that the Category 3 propulsion engines on the relevant vessel achieve a
more stringent tier of NOx limits, Tier 2 or Tier 3, than otherwise applies to those engines.
While verification would not be equivalent to EPA certification (the base engine certification
would remain the same), it would provide assurance to the states and localities that adopt such
programs that the emission reductions are occurring. The test methods used to make this
demonstration would be the same as those that would be used to comply with the production
testing requirements for new engines. The verification could be periodically reviewed to ensure
the engine continues to meet the verified emission levels. This could occur at the time of the
vessel certification surveys required by MARPOL Annex VI, either the intermediate survey
(every two and a half years) or the renewal survey (every five years).
The voluntary Marine Verification Program would be available to Category 3 propulsion
engines on new or existing vessels, and would be based on achieving the Tier 2 or Tier 3 NOx
limits and not on a percent reduction from a baseline. Owners could achieve these NOX limits by
adjusting the engine, retrofitting engine components, or retrofitting with an aftertreatment device.
However, we would not consider an exhaust gas scrubber to be an acceptable control strategy for
reducing NOx emissions.
Unlike a remanufacture program, which relies on the certification of remanufacture
systems that would apply to all specified engines, the Marine Verification Program would apply
to Category 3 propulsion engines on a vessel-specific basis. It would be up to the individual
vessel owner to determine how to reduce the NOx emissions from the engines on a vessel, and to
demonstrate, per the testing protocols outlined above, that the relevant engines achieve the more
stringent NOx limit. Note that an engine verification would not create the presumption that a
verified retrofit constitutes a remanufacture system or Certified Approved Method that must be
applied to all engines of the same model. However, we seek comment on whether there are ways
to approve groups of engine in a verification to reduce the cost of the program by spreading
design costs over more engines.
Participation in the Marine Verification Program would be completely voluntary: no
state, locality, or port authority would be required to adopt this program, and no vessel owner
would be required to retrofit a NOx emission control technology.
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