Regulatory Impact Analysis:
Control of Emissions of Air Pollution
from Locomotive Engines and Marine
Compression Ignition Engines Less than
30 Liters Per Cylinder
United States
Environmental Protection
Agency
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Regulatory Impact Analysis:
Control of Emissions of Air Pollution
from Locomotive Engines and Marine
Compression Ignition Engines Less than
30 Liters Per Cylinder
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
v>EPA
United States EPA420-R-08-001 a
Environmental Protection ..
Agency MaY2008
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Table of Contents
Executive Summary
Chapter 1: Industry Characterization
Chapter 2: Air Quality and Resulting Health and Welfare Effects
Chapter 3: Emission Inventory
Chapter 4: Technological Feasibility
Chapter 5: Engineering Cost Estimates
Chapter 6: Cost-Benefit Analysis
Chapter 7: Economic Impact Analysis
Chapter 8: Alternatives
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List of Acronyms
um Micrometers
bext Light-Extinction Coefficient
ug Microgram
ug/m3 Microgram per Cubic Meter
AAR Association of American Railroads
ABT Average Banking and Trading
ACS American Cancer Society
AEO Annual Energy Outlook (an EIA publication)
AESS Automatic Engine Stop/Start System
AIM Aerosol Inorganics Model
AIRS Aerometric Information Retrieval System
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)
ASLRRA American Short Line and Regional Railroad Association
ASPEN Assessment System for Population Exposure Nationwide
AT AC Average Total Cost
avg Average
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
C2 Category 2
C3 Category 3
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
CMB Chemical Mass Balance
CN Canadian National Railroad
CO Carbon Monoxide
CO2 Carbon Dioxide
ill
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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
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
DV Design Values
EAC Early Action Component
EC Elemental Carbon
EDHS Electric Driven Heating System
EF Emission Factor
EGR Exhaust Gas Recirculation
EIA Energy Information Administration (part of the U.S. Department of Energy)
EIA Economic Impact Analysis
EIM 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
FRA Federal Railroad Administration
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
GDP Gross Domestic Product
GEOS Goddard Earth Observing System
GETS General Electric Transportation Systems
GIS Geographic Information System
H2 Hydrogen Gas
HAD Diesel Health Assessment Document
HAP Hazardous Air Pollutant
HC Hydrocarbon
HD Heavy-Duty
IV
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HEI Health Effects Institute
HEP Head End Power
HES Health Effects Subcommittee
hp Horsepower
hp-hrs Horsepower Hours
hrs Hours
IARC International Agency for Research on Cancer
ICD International Classification of Diseases
IMO International Maritime Organization
IMPROVE Interagency Monitoring of Protected Visual Environments
IRIS Integrated Risk Information System
ISCST3 Industrial Source Complex Short Term Model
ISORROPIA Inorganic Aerosol Thermodynamic Model
JAMA Journal of the American Medical Association
K Kelvin
k Thousand
km Kilometer
kW Kilowatt
kWH Kilowatt Hour
L Liter
Ib Pound
LM Locomotive and Marine
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
MCIP Meteorology-Chemistry Interface Processor
MECA Manufacturers of Emission Controls Association
mg Milligram
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
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
NATA National Air Toxic Assessment
NBER National Bureau of Economic Research
NCDC National Clean Diesel Campaign
NCI National Cancer Institute
NCLAN National Crop Loss Assessment Network
v
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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
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
NO2 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
NPRM Notice of Proposed Rulemaking
NPV Net Present Value
NRC National Research Council
NREC National Railway Equipment Co
NRLM Nonroad, Locomotive and Marine diesel fuel
NRT4 Nonroad Tier 4 Rule
NSTC National Science and Technology Council
NTE Not To Exceed
O&M Operating and maintenance
O3 Ozone
OAQPS Office of Air Quality Planning and Standards
OC Organic Carbon
ฐCA Degree Crank Angle
OEHHA Office of Environmental Health Hazard Assessment
OEM Original Equipment Manufacturer
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 Particulate Matter
PM AQCD EPA Particulate Matter Air Quality Criteria Document
PM/NMHC Paniculate 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
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
VI
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RFS Renewable Fuels Standard
RIA Regulatory Impact Analysis
rpm Revolutions per Minute
RPO Regional Planning Organization
RRF Relative Reduction Factors
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
SBA Small Business Administration
SBREFA Small Business Regulatory Enforcement Fairness Act
SCC Source Classification Code
SCR Selective Catalyst Reduction
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
STB Surface Transportation Board
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
TFM Transportacion Ferroviaria Mexicana
THC Total Hydrocarbon
TSD Technical Support Document
TVCC Total Variable Compliance Cost
ULSD Ultra Low Sulfur Diesel fuel
UP Union Pacific Railroad
URS Upper Respiratory Symptoms
USDA United States Department of Agriculture
UV Ultraviolet
UV-b Ultraviolet-b
VOC Volatile Organic Compound
VOF Volatile Organic Fraction
VSL Value of Statistical Life
WLD Work Loss Days
WTP Willingness-to-Pay
$2,005 U.S. Dollars in calendar year 2005
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Executive Summary
Executive Summary
The Environmental Protection Agency (EPA) is finalizing a comprehensive three-part
program to reduce emissions of particulate matter (PM) and oxides of nitrogen (NOX) from
locomotives and marine diesel engines below 30 liters per cylinder displacement.
Locomotives and marine diesel engines designed to these more stringent standards will
achieve PM reductions of 90 percent and NOX reductions of 80 percent, compared to engines
meeting the current Tier 2 standards. These standards will also yield sizeable reductions in
emissions of nonmethane hydrocarbons (NMHC), carbon monoxide (CO), and hazardous
compounds known as air toxics.
This program is part of EPA's ongoing National Clean Diesel Campaign (NCDC) to
reduce harmful emissions from diesel engines of all types. The anticipated emission
reductions will significantly reduce exposure to harmful pollutants and also provide assistance
to states and regions facing ozone and particulate air quality problems that are causing a range
of adverse health effects, especially in terms of respiratory impairment and related illnesses.
We project that by 2030, this program will reduce annual emissions of NOx and PM
by 800,000 and 27,000 tons, respectively. The annual monetized PM2.5- and ozone-related
health benefits of this rule in 2030 will range from $9.2 billion to $11 billion, assuming a 3
percent discount rate, or between $8.4 billion to $10 billion, assuming a 7% discount rate.
The estimated annual social cost of the program in 2030 is projected to be significantly less, at
$740 million.
This Regulatory Impact Analysis provides technical, economic, and environmental
analyses of the emission standards. Chapter 1 provides industry characterization for both the
locomotive and marine industry. Chapter 2 presents air quality modeling results and
describes the health and welfare effects associated with particulate matter (PM), ozone, and
air toxics. Chapter 3 provides our estimates of the current emission inventories and the
reductions that can be expected from implementation of the more stringent standards.
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 rulemaking. Chapter 7 contains our estimates of the market
impacts of the more stringent standards and the distribution of costs among stakeholders.
Finally, Chapter 8 contains our analysis of several alternative control scenarios we considered
during the development of this rulemaking.
ES-1
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Regulatory Impact Analysis
1. Emission Standards
The program we are finalizing addresses emissions from all types of diesel
locomotives, including line-haul, switch, and passenger rail, and all types of marine diesel
engines below 30 liters per cylinder displacement (collectively called "marine diesel
engines.").A These include marine propulsion engines used on vessels from recreational and
small fishing boats to super-yachts, tugs and Great Lakes freighters, and marine auxiliary
engines ranging from small gensets to large generators on ocean-going vessels. Each of these
markets is described in Chapter 1.
We are finalizing a comprehensive three-part emission control program for
locomotives and for marine diesel engines that will dramatically reduce the emissions from
these sources. The standards and our technical feasibility justification are contained in
Chapter 4.
The first part consists of near-term engine-out emission standards, referred to as Tier 3
standards, for newly-built locomotives and marine diesel engines. These standards reflect the
application of engine-out PM and NOX reduction technologies and begin to phase in starting
in 2009. The second part consists of longer-term standards, referred to as Tier 4 standards, for
newly-built locomotives and over 600 kW marine diesel engines. These standards begin to
take effect in 2015 for locomotives and in 2014 for marine diesel engines. . For most
engines, these standards are similar in stringency to the final standards included in the 2007
highway diesel and Clean Air Nonroad Diesel programs and are expected to require the use of
high-efficiency aftertreatment systems to ensure compliance. These standards will be enabled
by the availability of ultra-low sulfur diesel fuel (ULSD). Third, we are adopting more
stringent emission standards for existing locomotives when they are remanufactured. Also
included in this rulemaking are provisions to eliminate emissions from unnecessary
locomotive idling and standards which apply to existing marine diesel engines over 600 kW
when they are remanufactured.
Locomotive Standards
The standards for newly-built line-haul, passenger, and switch locomotives and for
existing 1973 and later Tier 0, Tier 1, and Tier 2 locomotives are set out in Tables 1 and 2.
With some exceptions, these standards will apply to all locomotives that operate extensively
within the United States. Exceptions include historic steam-powered locomotives and
locomotives powered solely by an external source of electricity.
A In this RIA, Amarine diesel engineฎ refers to compression-ignition marine engines below 30 liters per cylinder
displacement unless otherwise indicated. Engines at or above 30 liters per cylinder are being addressed in
separate EPA actions.
ES-2
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Executive Summary
Table ES-1 - Standards for Line-Haul and Passenger Locomotives (g/bhp-hr)
standards apply
to:
Remanufactured
Tier 0 & 1
Remanufactured
Tier 2
New Tier 3
New Tier 4
take effect in year:
2008 as available,
2010 required
2008 as available,
2013 required
2012
2015
PM
0.22
0.10
0.10
0.03
NOx
7.4ฐ
5.5
5.5
1.3
HC
0.55
0.30
0.30
0.14
For Tier 0 locomotives originally manufactured without a separate loop intake air cooling system, these
standards are 8.0 and 1.00 g/bhp-hr for NOX and HC, respectively.
Table ES-2 - Standards for Switch Locomotives (g/bhp-hr)
standards apply
to:
Remanufactured
TierO
Remanufactured
Tier 1
Remanufactured
Tier 2
New Tier 3
New Tier 4
take effect in year:
2008 as available,
2010 required
2008 as available,
2010 required
2008 as available,
2013 required
2011
2015
PM
0.26
0.26
0.13
0.10
0.03
NOx
11.8
11.0
8.1
5.0
1.3
HC
2.10
1.20
0.60
0.60
0.14
Marine Standards
The standards for newly-built marine diesel engines are set out in Tables 3, 4, 5, and 6.
The Tier 3 standards will apply to all marine diesel engines with per cylinder displacement up
to 30 liters. The Tier 4 standards will apply only to commercial marine diesel engines above
600 kW.
For the purposes of this emission control program, Category 1 marine diesel engines
are those with per cylinder displacement up to 7 liters. Category 2 marine diesel engines are
those with per cylinder displacement from 7 to 30 liters. High power density engines are
those with a power density above 35 kW/liter).
ES-3
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Regulatory Impact Analysis
Table ES-3 - Tier 3 Standards for Marine Diesel Cl Commercial Standard Power Density
MAXIMUM
ENGINE
POWER
<19kW
19to<75kW
75 to 3700
kW
L/CYLINDER
<0.9
<0.9a
<0.9
0.9-<1.2
1.2-<2.5
2.5- <3. 5
3.5-<7.0
PM
g/bhp-hr
(g/kW-hr)
0.30 (0.40)
0.22 (0.30)
0.22 (0.30)b
0.10 (0.14)
0.09 (0.12)
0.08 (0.1 if
0.08 (o.i if
0.08 (0.1 if
NOx+HCrf
g/bhp-hr
(g/kW-hr)
5.6 (7.5)
5.6 (7.5)
3.5 (ฅ.7/
4.0 (5.4)
4.0 (5.4)
4.2 (5.6)
4.2 (5.6)
4.3 (5.6?;
MODEL
YEAR
2009
2009
2014
2012
2013
2014
2013
2012
Notes:
a <75 kW engines at or above 0.9 L/cylinder are subject to the corresponding 75-3700 kW standards.
Option: 0.15 g/bhp-hr (0.20g/kW-hr) PM / 4.3 g/bhp-hr (5.8g/kW-hr) NOx+HC in 2014.
This standard level drops to 0.07 g/bhp-hr (O.lOg/kW-hr) in 2018 for <600 kW engines.
' Tier 3 NOx+HC standards do not apply to 2000-3700 kW engines.
Table ES-4 Tier 3 Standards for Marine Diesel Cl Recreational and Commercial High Power Density
MAXIMUM
ENGINE
POWER
<19kW
19to<75kW
75 to <3700
kW
L/CYLINDER
<0.9
<0.9a
<0.9
0.9-<1.2
1.2-<2.5
2.5- <3. 5
3.5-<7.0
PM
g/bhp-hr
(g/kW-hr)
0.30 (0.40)
0.22 (0.30)
0.22 (0.30)b
0.11 (0.15)
0.10 (0.14)
0.09 (0.12)
0.09 (0.12)
0.08 (0.11)
NOx+HC
g/bhp-hr
(g/kW-hr)
5.6 (7.5)
5.6 (7.5)
3.5 (4.7)b
4.3 (5.8)
4.3 (5.8)
4.3 (5.8)
4.3 (5.8)
4.3 (5.8)
MODEL
YEAR
2009
2009
2014
2012
2013
2014
2013
2012
Notes:
a <75 kW engines at or above 0.9 L/cylinder are subject to the corresponding 75-3700 kW standards.
'Option: 0.15 g/bhp-hr (0.20 g/kW-hr) PM/ 4.3 g/bhp-hr (5.8 g/kW-hr) NOx+HC in 2014.
ES-4
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Executive Summary
Table ES-5 - Tier 3 Standards for Marine Diesel C2
MAXIMUM
ENGINE
POWER
< 3700 kW
L/CYLINDER
7-<15
15-<20
20- <25
25-<30
PM
g/bhp-hr
(g/kW-hr)
0.10 (0.14)
0.20 (0.27)c
0.20 (0.27)
0.20 (0.27;
NOx+HC6
g/bhp-hr
(g/kW-hr)
4.6 (tf.2;
6.5 (8.7)c
7.3 (P.s;
8.2 (77.0;
MODEL
YEAR
2013
2014
2014
2014
Notes:
a See note (c) of Table ES-6 for optional Tier 3/Tier 4 standards.
Tier 3 NOx+HC standards do not apply to 2000-3700 kW engines.
For engines below 3300 kW in this group, the PM Tier 3 standard is 0.25 g/bhp-hr (0.34 g/kW-hr).
Table ES-6 - Tier 4 Standards for Marine Diesel Cl and C2
MAXIMUM
ENGINE POWER
at or above 3700 kW
2000to<3700kW
1400 to <2000 kW
600 to <1400 kW
PM
g/bhp-hr
(g/kW-hr)
0.09 (0.12)"
0.04 (0.06)
0.03 (0.04)
0.03 (0.04)
0.03 (0.04)
NOx+HC
g/bhp-hr
(g/kW-hr)
1.3 (1.8)
1.3 (1.8)
1.3 (1.8)
1.3 (1.8)
1.3 (1.8)
HC
g/bhp-hr
(g/kW-hr)
0.14 (0.19)
0.14 (0.19)
0.14 (0.19)
0.14 (0.19)
0.14 (0.19)
MODEL
YEAR
2014C
2016fe'c
2014c'rf
2016C
20 llb
Notes:
This standard is 0. 19 g/bhp-hr (0.25 g/kW-hr) for engines with 15-30 liter/cylinder displacement.
' Optional compliance start dates can be used within these model years; see discussion below.
? Option for C2: Tier 3 PM / NOx+HC at 0.10 / 5.8 g/bhp-hr (0.14/7.8 g/kW-hr) in 2012, and Tier 4 in 2015.
The Tier 3 PM standards continue to apply for these engines in model years 2014 and 2015 only.
We are also finalizing standards for remanufactured marine diesel engines that will
apply to engines above 600 kW (800 hp). This program requires the use of a certified
remanufacture system when an engine is remanufactured if a certified system is available.
The standard we are finalizing for these systems is a 25 percent reduction in PM emissions,
compared to the engine's baseline emissions level. We expect that this PM reduction will be
met by using incrementally-improved components that are replaced when an engine is
remanufactured. The remanufacture systems sets a cost cap of $45,000 per ton of PM
reduced, based on the incremental cost of the remanufacture system. We intend to assess the
effectiveness of this voluntary program as early as 2012 to ascertain the extent to which
engine manufacturers are providing certified remanufacture systems. If remanufacture system
ES-5
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Regulatory Impact Analysis
are not available or are not in the process of being developed and certified at that time for a
significant number of engines, we may consider changes to the program.
2. Projected Inventory and Cost Impacts
Our analysis of the projected impacts of these standards can be found in Chapter 2 (air
quality impacts), Chapter 3 (inventory impacts) and Chapter 6 (benefits).
Inventory Reductions
A discussion of the estimated current and projected inventories for several key air
pollutants are contained in Chapter 3. Nationally, in 2007 these engines account for about 20
percent of mobile source NOX emissions and 25 percent of mobile source diesel PM2.5
emissions. Absent new emissions standards, we expect overall emissions from these engines
to remain relatively flat over the next 10 to 15 years due to existing regulations such as lower
fuel sulfur requirements and the phase-in of locomotive and marine diesel Tier 1 and Tier 2
engine standards, but starting in about 2025, emissions from these engines would begin to
grow. Without new controls, by 2030, these engines would have become a large portion of
the total mobile source emissions inventory constituting 35 percent of mobile source NOX
emissions and 65 percent of diesel PM emissions.
We estimate that these standards will reduce annual NOX emissions by about 800,000
tons andPM25 and 27,000 tons in 2030. Table 7 shows the emissions reductions associated
with today's rulemaking for selected years, and the cumulative reductions through 2040
discounted at 3 and 7 percent. These reductions in PM and NOX levels will produce
nationwide air quality improvements.
Table ES-7 - Estimated Emissions Reductions Associated with the Locomotive and Marine Standards
(Short tons)
YEAR
2015
2020
2030
2040
PM2.5
7,000
14,000
27,000
37,000
PMio"
7,000
15,000
27,000
38,000
NOx
161,000
371,000
795,000
1,144,000
voc
15,000
28,000
43,000
55,000
Note that, PM2.s is estimated to be 97 percent of the more inclusive PMio emission inventory. In Section II
we generate and present PM2 5 inventories since recent research has determined that these are of greater
health concern. Traditionally, we have used PMio in our cost effectiveness calculations. Since cost
effectiveness is a means of comparing control measures to one another, we use PMio in our cost
effectiveness calculations for comparisons to past control measures.
ES-6
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Executive Summary
Engineering Costs
The engineering cost analysis for these standards can be found in Chapter 5. The total
engineering costs associated with this rulemaking are the summation of the engine and
equipment compliance costs, both fixed and variable, the operating costs, and the costs
associated with the locomotive and marine remanufacturing programs. These costs are
summarized in Table 8.
Table ES-8 - Total Engineering Costs of the Program (SMillions)
YEAR
2011
2012
2015
2020
2030
2040
NPV at 3%
NPV at 7%
ENGINE
COSTS
$138
$80
$123
$82
$99
$98
$1,764
$974
EQUIPMENT
COSTS
$0
$0
$24
$17
$20
$17
$260
$122
OPERATING
COSTS
$0
$0
$30
$187
$535
$806
$5,264
$2,057
COSTS OF
REMANUFACTURING
PROGRAM
$143
$135
$89
$63
$105
$161
$2,120
$1,153
TOTAL
COSTS
$281
$215
$266
$349
$759
$1,082
$9,407
$4,307
These engineering costs are allocated to NOX and PM reductions in Table 9. About
half of the costs of complying with the program are operating costs, with the bulk of those
being reductant-related costs associated with SCR technology. Since SCR is a technique for
reducing NOX emissions, this means that most of the operating costs and, therefore, the
majority of the total engineering costs of the program are associated with NOX control.
Table ES-9 - Total Engineering Costs, Allocated by Pollutant (SMillions)
YEAR
2011
2012
2015
2020
2030
2040
NPV at 3%
NPV at 7%
PM COSTS
$121
$94
$116
$106
$181
$240
$2,680
$1,333
NOx COSTS
$160
$121
$150
$242
$578
$842
$6,727
$2,973
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 10 contains the
estimated cost per ton of pollutant reduced based on the net present value of the engineering
costs and inventory reductions from 2006 through 2040. This estimate captures all of the
engineering costs and emissions reductions including those associated with the locomotive
and marine remanufacturing programs. Table 10 also presents the estimated cost per ton of
pollutant reduced for 2030 using the annual costs and emissions reductions in that year alone.
ES-7
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Regulatory Impact Analysis
That estimates includes engineering costs and emission reductions that will occur from the
new engine standards and locomotive and marine remanufacturing programs in that year.
Table ES-10 - Program Cost per Ton Estimates
POLLUTANT
NOx+NMHC
PM
2006 THRU 2040
DISCOUNTED LIFETIME
COST PER TON AT 3%
$720
$8,440
2006 THRU 2040
DISCOUNTED LIFETIME
COST PER TON AT 7%
$750
$9,620
LONG-TERM
COST PER TON IN
2030
$690
$6,620
3. Estimated Benefits and Economic Impacts
Estimated Benefits
We estimate that the requirements in this rulemaking will result in substantial benefits
to public health and welfare and the environment, as described in Chapter 6. The benefits
analysis performed for this rulemaking 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.
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 all other PM
and ozone non-mortality related benefits information. These benefits are presented in Table
ES-11. The benefits reflect two different sources of information about the impact of
reductions in PM on reduction in the risk of premature death, including estimates of mortality
derived from the epidemiological literature (using both the American Cancer Society (ACS)
cohort study and the Six Cities study) and an expert elicitation study conducted by EPA in
2006. In order to provide an indication of the sensitivity of the benefits estimates to
alternative assumptions, in Chapter 6 of the RIA we present a variety of benefits estimates
based on two epidemiological studies (including the ACS Study and the Six Cities Study) and
the expert elicitation. EPA intends to ask the Science Advisory Board to provide additional
advice as to which scientific studies should be used in future RIAs to estimate the benefits of
reductions in PM.
The range of ozone benefits associated with the final standards is also estimated based
on risk reductions estimated using several sources of ozone-related mortality effect estimates.
There is considerable uncertainty in the magnitude of the association between ozone and
premature mortality. This analysis presents four alternative estimates for the association
based upon different functions reported in the scientific literature. We use the National
Morbidity, Mortality and Air Pollution Study (NMMAPS), which was used as the primary
basis for the risk analysis in the ozone Staff Paper and reviewed by the Clean Air Science
Advisory Committee (CASAC). We also use three studies that synthesize ozone mortality
data across a large number of individual studies. Note that there are uncertainties within each
study that are not fully captured by this range of estimates. Chapter 6 of the RIA presents the
results of each of the ozone mortality studies separately.
ES-8
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Executive Summary
Recognizing that additional research is needed to more fully establish underlying
mechanisms by which such effects occur, we also consider the possibility that the observed
associations between ozone and mortality may not be causal in nature. EPA has requested
advice from the National Academy of Sciences on how best to quantify uncertainty in the
relationship between ozone exposure and premature mortality in the context of quantifying
benefits associated with ozone control strategies.
The range of total ozone- and PM-related benefits associated with the final standards
is presented in Table ES-11. 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-11) to
estimates of PM-related premature mortality, derived from either the epidemiological
literature or the expert elicitation.
Table ES-11- Estimated Monetized PM- and Ozone-Related Health Benefits of the Locomotive and
Marine Engine Standards
2030 Total Ozone and PM Benefits - PM Mortality Derived from Epidemiology Studies"
Premature Ozone Mortality
Function or Assumption
NMMAPS
Meta-analysis
Reference
Bell et al., 2004
Bell et al., 2005
Itoetal.,2005
Levy etal., 2005
Assumption that association is not causal
Mean Total Benefits
(Billions, 2006$)"'''
$9.7 to $20
$11 to $21
$11 to $21
$11 to $22
$9.2 to $20
2030 Total Ozone and PM Benefits - PM Mortality Derived from Expert Elicitation
Premature Ozone Mortality
Function or Assumption
NMMAPS
Meta-analysis
Reference
Bell et al., 2004
Bell et al., 2005
Itoetal.,2005
Levy etal., 2005
Assumption that association is not causal
Mean Total Benefits
(Billions, 2006$)^
$5.2 to $37
$6.2 to $38
$6.7 to $39
$6.7 to $39
$4.7 to $37
Notes:
premature mortality function to both estimates of PM2.5-related premature mortality derived from the ACS
(Pope et al., 2002) and Six-Cities (Laden et al., 2006) studies, respectively.
Total includes ozone and PM2.5 benefits. Range was developed by adding the estimate from the ozone
premature mortality function to both the lower and upper ends of the range of the PM2.5 premature mortality
functions characterized in the expert elicitation. The effect estimates of five of the twelve experts included in the
elicitation panel fall within the empirically-derived range provided by the ACS and Six-Cities studies. One of
the experts fall below this range and six of the experts are above this range. Although the overall range across
experts is summarized in this table, 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.
c 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 VI-5.
Results reflect the use of a 3 percent discount rate. Monetary results presented in Table VI-3 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.
ES-9
-------
Regulatory Impact Analysis
We estimate that by 2030, the annual emission reductions associated with these more
stringent standards will annually prevent 1,100 PM-related premature deaths (based on the
ACS cohort study), between 50 and 250 ozone-related premature deaths (assuming a causal
relationship between ozone and mortality), 120,000 work days lost, and approximately
1,000,000 minor restricted-activity days.
Benefit-Cost Analysis
Using the ACS-based estimate of PM-related premature mortality incidence, we
estimate that the monetized benefits of this rule in 2030 will range between approximately
$9.2 and $11 billion, assuming a 3 percent discount rate. Using the range of results derived
from the expert elicitation, we estimate that the monetized benefits in 2030 will range from
approximately $4.7 billion to $39 billion, assuming a 3 percent discount rate. These estimates
reflect the remanufactured marine engine program that we are finalizing.
The annual cost of the program in 2030 are estimated to be significantly less, at
approximately $740 million.
Economic Impact Analysis
We also performed an economic impact analysis to estimate the market-level changes
in prices and outputs for affected markets, the social costs of the program, 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 $738 million in 2030.B' c
The rail sector is expected to bear about 62.5 percent of the social costs of the program in
2030, and the marine sector is expected to bear about 37.5 percent. In each of these two
sectors, these social costs are expected to be born primarily by producers and users of
locomotive and marine transportation services (62 and 36 percent, respectively). The
remaining 2 percent is expected to be borne by locomotive, marine engine, and marine vessel
manufacturers and fishing and recreational vessel users.
The impact of these costs on society are expected to be minimal, with the prices of rail
and marine transportation services in 2030 estimated to increase by less about 0.6 percent for
locomotive transportation services and about 1.1 percent for marine transportation services.
B All estimates presented in this section are in 2005$.
c The estimated 2030 social welfare cost of $738 million is based on an earlier version of the engineering costs
developed for this rule, which estimated $740 million engineering costs in 2030. The final engineering cost
estimate for 2030 is $760 million.
ES-10
-------
Executive Summary
4. Alternative Program Options
In the course of designing our rulemaking, we investigated several alternative
approaches to both the engine and fuel programs. Chapter 8 contains a description of these
alternatives and an analysis of their potential costs and benefits.
ES-11
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Regulatory Impact Analysis
This Page Intentionally Left Blank
ES-12
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Industry Characterization
CHAPTER 1: INDUSTRY CHARACTERIZATION 2
1.1 Marine 2
1.1.1 Introduction 2
1.1.2 Marine Diesel Engine Manufacturers 6
1.1.3 Marine Vessel Manufacturers 24
1.1.4 Vessel Operators 41
1.2 Locomotive 42
1.2.1 Introduction 42
1.2.2 Current Emission Regulations 43
1.2.3 Supply: Locomotive Manufacturing and Remanufacturing 45
1.2.4 Demand: Railroads 54
1.2.5 Existing Regulations 67
1.2.6 Foreign Railroads in US 69
1-1
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Regulatory Impact Analysis
CHAPTER 1: Industry Characterization
In order to assess the impacts of emission regulations upon the affected industries, it is
important to understand the nature of the industries impacted by the regulations. These
industries include marine diesel engine manufacturers and marinizers, boat or marine vessel
builders which have marine diesel engines installed on them, vessel operators which either
purchase new diesel engines or remanufacture existing engines greater than 600kW, the
manufacturers of locomotives and locomotive engines, the owners and operators of
locomotives (i.e., railroads), and remanufacturers of locomotives and locomotive engines.
This chapter provides market information for each of these affected industries for background
purposes.
1.1 Marine
1.1.1 Introduction
The regulations for marine diesel engines will directly impact five 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, and 5) vessel operators who own existing marine diesel engines greater than 600
kW. Much of this marine industry characterization was taken from a report done for us by
RTI, International.1
1.1.1.1 Marine Diesel Market Overview
Marine diesel engines include both engines used for propulsion on marine vessels, and
those used for marine vessel auxiliary power needs. Diesel marine engines are generally
derived from engines originally designed and manufactured for land-based nonroad
applications. These nonroad engines are then adapted for use in marine applications through
the process of marinization, either by the original engine manufacturer, or by a post-
manufacturer marinizer (PMM). The marinization process is discussed in further detail in
section 1.1.2.2.2.
Propulsion engines can vary dramatically in size and power, from the smallest
engines used in recreational sailboats, to very large engines used in ocean-going commercial
vessels. Similarly, auxiliary engines cover a very broad range of sizes and rated power.
Auxiliary engines can be used for a variety of purposes, including primary or emergency
electrical power generation, and the powering of onboard equipment such as pumps, winches,
cable and pipe laying machinery, and dredging equipment. A description of the various
engine categories used for regulatory purposes is contained in section 1.1.2.1.
As with marine diesel engines, marine vessels include a very broad range of vessel
sizes and types. These include small recreational vessels, as well as commercial vessels such
as tow and tug boats, patrol boats, commercial fishing vessels, research vessels, passenger
vessels (tour boats and ferries), offshore support vessels which service offshore drilling
platforms, and a variety of other specialized commercial vessels.
1-2
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Industry Characterization
Figure 1-1-1 shows the links between the various market segments of the marine
diesel engine industry and the marine vessel industry, as discussed further in the following
sections.
Figure 1-1-1 Marine Diesel Market Segment Flow Chart
Vessel Operators
Marine Diesel Vessel Markets
Recreational Single Engine * Recreational
Twin Engine Tug,'Tow - Ferries Fishing
Coast Guard Cargo Research Offshore
Support- Military
IITS ports
* Recreational
Vessels
Marine Diesel
Engines
Marine Vessel
Manufacturers
Marine Vessel
and Engine
Repair
Businesses
arine Diesel Engine Markets
Small Recreational C1
Commercial C1 - Commercial C2
Marinization
! Performed by
i Engine
1 Manufacturer
.
Propulsion and
Auxiliary Engine
Marinizers
Automotive, Marine, and Generator
Engine Manufacturers
1-3
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Regulatory Impact Analysis
1.1.1.2 Current US Emission Regulations
We adopted Tier 2 emission standards for Category 1 (Cl) marine diesel engines over
37 kW and for category 2 (C2) marine diesel engines in 1999 (64 CFR 73300, December 29,
1999). These standards are shown in Table 1-1.
Table 1-1 Tier 2 Emission Standards for Cl (over 37 kW) and C2 Commercial Marine Diesel Engines
Category
1
2
Displacement
(liters/cylinder)
Power >37 kW, disp.
0.9 < disp. < 1.2
1.2 3300
20.0 < disp. < 25.0
25.0 < disp. < 30.0
Starting
Date
2005
2004
2004
2007
2007
2007
2007
2007
2007
NOX+THC
(g/kW-hr)
7.5
7.2
7.2
7.2
7.8
8.7
9.8
9.8
11.0
PM
(g/kW-hr)
0.40
0.30
0.20
0.20
0.27
0.50
0.50
0.50
0.50
CO
(g/kW-hr)
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
We applied the Tier 2 emission standards for Cl engines shown in Table 1-1 to
recreational marine diesel engines, but with applicable dates two years behind those for the
corresponding commercial marine diesel engines (67 FR 68242, November 8, 2002).
Following the initial adoption of the Tier 2 standards just discussed, we adopted the
Tier 1 emission standards in 2003. These standards became effective with the 2004 model
year (68 FR 9746, February 28, 2003). These NOx-only standards apply to commercial
marine diesel engines with a per-cylinder displacement of greater than 2.5 liters per cylinder.
As shown in Table 1-2 the standards vary depending on the rated speed of the engine.
Table 1-2 Tier 1 Standards for Commercial Marine Diesel Engines over 2.5 Liters per Cylinder
Rated engine speed (rpm)
<130
130-2000
>2000
NOX (g/kW-hr)
17
45 X rpm'0 2
9.8
Prior to today's action, there were no emission regulations specifically for marine
diesel engines less than 37 kW. Rather, these engines were covered by the Tier 2 standards
for nonroad compression ignition (Cl) engines, as shown in Table 1-3 (63 FR 56968, October
23, 1998).
1-4
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Industry Characterization
Table 1-3 Tier 2 Emission Standards for Marine Diesel Engines Below 37 kW
Engine Power
kW<8
8
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Regulatory Impact Analysis
Globally harmonized regulation of ship emissions is generally recognized to be the
preferred approach for addressing air emissions from ocean-going vessels. It reduces costs
for ship owners, since they would not be required to comply with a patchwork of different
standards that could occur if each country was setting its own standards, and it can simplify
environmental protection for port and coastal states.
The significance of international shipping to the United States can be illustrated by
port entrance statistics. In 1999, according to U.S. Maritime Administration (MARAD) data,
about 90 percent of annual entrances to U.S. ports were made by foreign-flagged vessels
(75,700 total entrances; 67,500 entrances by foreign vessels; entrances are for vessels engaged
in foreign trade and do not include Jones Act3 vessels).
The emission control program contained in Annex VI was the first step for the
international control of air pollution from ships. However, as early as the 1997 conference,
many countries "already recognized that the NOx emission limits established in Regulation 13
were very modest when compared with current technology developments."4 Consequently, a
Conference Resolution was adopted at the 1997 conference that invited the Marine
Environment Protection Committee (MEPC) to review the NOx emission limits at a minimum
of five-year intervals after entry into force of the protocol and, if appropriate, amend the NOx
limits to reflect more stringent controls.
The United States began advocating a review of the NOx emission limits in 1999.5
However, MEPC did not formally consider the issue until 2005, after the Annex went into
effect. Negotiations for amendments to the Annex VI standards, including NOx and SOx
emission limits, officially began in April 2006, with the most recent round of negotiations
taking place in April 2007. The United States submitted a paper to that meeting (April 2007
Bulk Liquids and Gases Sub-Committee meeting, referred to as BLG-11) setting out an
approach for new international engine and fuel standards. That approach forms the basis of
the program outlined in the recently published Advance notice of proposed rulemaking for
Control of Emissions from New Marine Compression-Ignition Engines at or Above 30 Liters
per Cylinder.6 Discussions are expected to continue through Summer 2008 and are expected
to conclude at the October 2008 MEPC meeting. We will continue to coordinate our national
rule for Category 3 emission limits with our activities at IMO.
1.1.2 Marine Diesel Engine Manufacturers
Diesel (compression-ignition) engines are designed to be quite robust in order to
withstand the very high temperatures and pressures associated with compression-ignition. As
a result, they tend to be very reliable and have very long service lives. Their energy
efficiency and simple design result in low operating and maintenance costs. As a result,
diesel engines tend to dominate commercial marine applications, where cost and reliability are
key purchase decisions for the vessel operator. Diesel engines account for only a small
portion of the recreational marine market, however, as their initial purchase price is high
relative to gasoline (spark-ignition) engines. The benefits of lower operating costs are not
nearly as important in the recreational market, where engines tend not to get much use as
compared to commercial applications.
1-6
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Industry Characterization
The terms "commercial" and "recreational" are defined in 40 CFR Part 94, Control of
Emissions for Marine Compression-Ignition Engines (Code of Federal Regulations, 2006).
The definitions in section 94.2 state that a commercial engine is an engine installed on a
commercial vessel. Likewise, a recreational engine is an engine installed on a recreational
vessel. As adopted in this final rule in 40 CFR Part 1042, "recreational vessel" is defined as a
vessel that is intended by its manufacturer to be operated primarily for pleasure purposes,
although such a vessel could be chartered, rented or leased. Further, a recreational vessel
includes only those vessels less than 100 gross registered tons carrying six or fewer
passengers, and cannot be used solely for competition.
This industry characterization is concerned with the U.S. market for marine diesel
engines, which encompasses all diesel marine engines installed on marine vessels to be
flagged (registered) in the United States. This includes engines made in the U.S., engines
imported for installation in vessels made in the U.S., and engines included in vessels made
overseas and imported into the U.S. Unless otherwise noted, the production and engine
characteristics data presented in the following sections were obtained from the Power Systems
Research OELink database.7
1.1.2.1 Engine Categories and Characteristics
For the purposes of this industry characterization, we looked at four broad categories
of diesel marine engines, based on the categories that currently exist for emission regulation
purposes. These categories are shown in Table 1-4.
Table 1-4 Diesel Marine Engine Categories and Applications
Category
Small
Recreational
Category 1
Commercial
Category 1
Commercial
Category 2
Commercial
Category 3
Power
<37kW
>37kW
>37kW
>37kW
>37kW
Displacement per
Cylinder
Any
< 5 liters
< 5 liters
> 5 liters and < 30 liters
> 30 liters
Applications
Auxiliary, Recreational Propulsion
Recreational Propulsion
Auxiliary, Commercial Propulsion
Auxiliary, Commercial Propulsion
Commercial Propulsion
Given the broad range of commercial and recreational marine vessels types, it is
difficult to identify typical applications for each engine category. Nonetheless, the following
paragraphs provide an overview of the general characteristics and typical applications of
engines in each category.
Small: Engines in this category range from 4 to 43 horsepower (hp) and are
characterized by low costs and high sales volumes. Most small engines are used for auxiliary
purposes on marine vessels or for propulsion on recreational sailboats. In 2002 they
accounted for approximately 26 percent of the marine diesel engines produced or imported in
1-7
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Regulatory Impact Analysis
the U.S. market. They are typically marinized land-based nonroad diesel engines; we are not
aware of any marine engines of this size made solely for marine application.
Category 1 (Cl) Recreational: Engines in this category range from 52 to 3,155 hp and
are characterized by high power density (power to weight ratio) and low annual hours of
operation relative to commercial engines. Such engines are typically operated no more than
200 to 250 hours per year, and often less. These engines are used for propulsion in
recreational vessels, which are designed for speed and planing operation. In 2002 they
accounted for approximately 34 percent of the marine diesel engines produced or imported in
the U.S. market.
Recreational vessels are designed primarily for speed, and this imposes certain
constraints on the type of engine they can use. For a marine vessel to reach high speeds, it is
necessary to reduce the surface contact between the vessel and the water, and consequently
these vessels typically operate in a planing mode. However, the accompanying high engine
speeds are sustained for only short periods of time compared to the total operation of the
vessel (i.e., long enough for the vessel to get up on plane), and the duty cycle on which these
engines are certified reflects these operations.
Planing imposes two important design requirements. First, the vessel needs to have a
very high power, but lightweight, engine to achieve the speeds necessary to push the vessel
onto the surface of the water. Therefore, recreational engine manufacturers have focused on
achieving higher power output with lighter engines (this is also referred to as high power
density). The tradeoff is less durability, and recreational engines are warranted for fewer
hours of operation than commercial marine engines. The shorter warranty period is not a
great concern, however, since recreational vessels, and therefore their engines, are typically
used for fewer hours per year than commercial engines, and spend much less time operating at
higher engine loads. Second, the vessel needs to be as light as possible, with vertical and
horizontal centers of gravity carefully located to allow the hull of the vessel to be lifted onto
the surface of the water. Therefore, recreational vessel manufacturers have focused on
designing very lightweight hulls. They are typically made out of fiberglass, using precisely
designed molds. The tradeoff is a reduced ability to accommodate any changes to the
standard design. For these reasons, recreational vessels are typically designed around a
specific engine or group of engines, and engines that are heavier or that are physically larger
cannot be used without jeopardizing the vessel's planing abilities or, in many cases, designing
a new fiberglass mold for a modified hull.
Category 1 (Cl) Commercial: Engines in this category are very similar to engines in
the Cl recreational category in displacement, but tend to have lower hp ratings than
recreational marine diesel engines in order to provide increased durability required in
commercial applications. In contrast to Cl recreational engines, Cl commercial engines are
typically used 750 to 4,000 hours per year. They are typically used for propulsion in vessels
with displacement hull designs. They are also used for a wide variety of auxiliary power
needs on marine vessels. In 2002 they accounted for approximately 39 percent of the marine
diesel engines produced or imported in the U.S. market.
1-8
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Industry Characterization
In contrast to recreational marine vessels, commercial vessels are typically larger
displacement hull vessels, and instead of operating on the surface of the water, for speed, they
are pushed through the water. The speed at which a displacement vessel can operate is
limited by its hull design and above that limit, there are quickly diminishing returns on power:
little vessel speed increase is achieved by increasing power. Because vessel speed is limited
by the hull design, there is little incentive to over power the vessel, and engines on these types
of commercial vessels tend to be lower power when compared to recreational vessels of
similar size. Commercial engines operate for long periods at about 80-90% of rated power
and are designed primarily with durability and fuel consumption in mind.
Category 2 (C2): Engines in this category are typically derived from engines
originally designed for use in locomotives or for land-based stationary power generation.
Such engines typically operate 3,000 to 5,000 hours or more per year, and are designed to be
durable and have a very long service life. Under our current program, all C2 marine diesel
engines are handled the same way; there is no distinction between recreational or commercial
engines in this category. In 2002 they accounted for approximately one percent of the marine
diesel engines produced or imported in the U.S. market.
As we were developing this rule, engine manufacturers brought to our attention
another category of marine diesel engines that do not fit neatly in the above scheme. These
are high power-density marine diesel engines used in some commercial vessels, including
certain kinds of crew boats, research vessels, and fishing vessels. Unlike most commercial
vessels, these vessels are built for higher speed, planing operation, which allows them to reach
research fields, oil platforms, or fishing beds more quickly. These engines may have smaller
service lives because of operation at these higher speeds. Our current program does not
distinguish between these commercial engines and those used on displacement vessels with
respect to useful life periods. Further, this industry characterization does not specifically
address these engines as a unique group.
A final category of marine diesel engines, Category 3 (C3) engines, have
displacements of 30 liters per cylinder or greater. Such engines are typically only used in
large ocean-going vessels, and are not considered in this industry characterization; these
engines are not covered by the final rule. Table 1-5 shows a summary of the general
characteristics of engines in each of the four categories considered in this industry
characterization.
1-9
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Regulatory Impact Analysis
Table 1-5 Engine Characteristics for the Considered Engine Categories
Cylinders
Horsepower
Engine Speed (rpm)
Weight (Ibs)
Cycle:
2
4
Configuration:
H-Block
Inline
V-Block
Cooling:
Air
Oil
Water
Small
1-4
4.2-42.4
1,800-3,000
26-246
0.0%
100.0%
8.1%
91.9%
0.0%
5.9%
0.0%
94.1%
Recreational
Category 1
3-16
52-3,155
1,800-3,000
156-7,491
10.2%
89.8%
0.0%
65.3%
34.7%
0.0%
0.0%
100.0%
Commercial
Category 1
3-24
37.5-2,500
1,800-3,000
106-7,900
9.5%
90.5%
0.0%
73.3%
26.7%
0.4%
0.1%
99.5%
Category 2
5-20
300-9, 190a
750-1,500
7,850-35,000
41.0%
59.0%
0.0%
33.7%
66.3%
0.0%
0.0%
100.0%
a While the PSR database shows one C2 engine family with a 300 hp rating, C2 engines are generally over 1000
hp at minimum.
Table 1-6 shows the total number of engines in each category which were sold in the
United States in 2002.
Table 1-6 Marine Diesel Engine Sales by Engine Category in 2002
Application Category
Small
Recreational Cl
Commercial C 1
Commercial C2
Total
Sales in 2002
10,761
13,952
15,826
277
40,816
Percent of Total
26.4%
34.2%
38.8%
0.7%
1.1.2.2 Supply Side
Marine diesel engines are typically derived from land-based nonroad engines. These
engines are adapted for use in the marine environment through a process known as
marinization. In this section we will discuss nonroad engine design, production and costs,
followed by descriptions of the marinization process and the companies engaged in this
activity. Finally we will discuss engine dressing and rebuilding practices for marine diesel
engines.
1-10
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Industry Characterization
1.1.2.2.1 Nonroad Diesel Engine Design and Production
Engine blocks are cast in a foundry, most often from gray iron. Depending on the size
and complexity of the engine, the block may be formed by impression molding or two-piece
sand-casting. Smaller, more complex parts, including cylinder heads, exhaust manifolds, and
cylinder liners, are cast from ductile iron, typically using sand cores to allow formation of the
complicated shapes. All castings must be cleaned and deburred prior to further processing. In
addition, ductile iron parts will also usually be heat treated to relieve stress and harden the
alloys. Table 1-7 lists the materials and primary production processes for various engine
components.8
Table 1-7 Engine Component Materials and Production Processes
Component
Block
Cylinder head
Intake manifold
Connecting rods
Pistons
Crankshaft
Valves
Exhaust systems
Primary Materials
Iron, aluminum
Iron, aluminum
Plastic, aluminum
Powder metal, steel
Aluminum
Iron, steel, powder metal
Steel, magnesium
Stainless steel, aluminum, iron
Primary Process
Casting
Casting, machining
Casting, machining
Molding, forging, machining
Forging, machining
Molding, forging, machining
Stamping, machining
Extruding, stamping
The cast block, cylinder head, and cylinder liners, along with crankshafts, gears,
connecting rods, and other engine parts, are next machined to exact specifications in a
machining center. Holes are drilled, parts reshaped, excess metal removed, and the metal
surfaces polished in the machining area. The operation of the finished engine depends
critically on the precision of the machining work at this stage.
The third major step in engine manufacturing is assembly. This area is usually
physically isolated from the dirty upstream operations so that contaminants are not introduced
into the completed engines, thus affecting their operation or shortening the engine's life. In a
typical plant, subassemblies are first put together on separate lines or in separate bays; then
the subassemblies are brought together for final assembly. The completed engines are
visually inspected and then evaluated on-line on a test bench or in a test cell to ensure their
performance will meet expectations.
1.1.2.2.2 Engine Marinization
Land-based nonroad diesel engines generally need to be modified in some ways to
make them suitable for installation on marine vessels. The process by which this is done is
known as marinization. The marinization process results in changes to the emission
characteristics of the nonroad engine. For this reason, a marinized nonroad engine must be
certified to marine diesel engine emission standards even though the base nonroad engine is
certified to the nonroad diesel engine emission standards. Sometimes, land-based nonroad
diesel engines can be adapted for use in marine applications without changing the emission
characteristics of the engine. This process is called engine dressing, and is discussed in
section 1.1.2.2.5. Marinization typically involves three significant modifications: choosing
1-11
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Regulatory Impact Analysis
and optimizing the fuel management system, configuring a marine cooling system, and
making other peripheral changes. These changes are detailed in the following paragraphs.
Fuel and Air Management: High-performance engines are preferred for most
recreational and some light duty commercial applications. These engines are built to
maximize their power-to-weight ratio (provide more power with less added weight), which is
typically done by increasing power from a given cylinder displacement. This is usually
accomplished by installing a new fuel injection system, which injects more fuel directly into
the cylinder to increase power. This can require changes to the camshaft, cylinder head, and
the injection timing and pressure. Currently, the design limits for increased fuel to the
cylinder are smoke and durability. Modifications made to the cooling system also help
enhance performance. By cooling the charge, more air can be forced into the cylinder. As a
result, more fuel can be injected and burned efficiently because of the increase in available
oxygen. In addition, changes are often made to the pistons, cylinder head components, and
the lubrication system. For example, aluminum piston skirts can be used to reduce the weight
of the pistons. Cylinder head changes include changing valve timing to optimize engine
breathing characteristics. Marinizers do not typically go as far as to physically modify the
cylinder head.
Cooling System: To mitigate performance problems, engine manufacturers
historically used cooling systems that cooled by circulating seawater through the engine that
was pumped from outside the boat. Even though many currently operating marine diesel
engines still use seawater to cool the engine, almost all newly built engines use a closed
cooling system that recirculates coolant through the engine block. These engines still use raw
seawater by using it to draw heat out of the engine coolant. These closed systems help prevent
corrosion and allow the engine to operate at higher temperatures. As part of the cooling
system, water-jacketed exhaust manifolds, pumps, and heat exchangers are added. Marine
diesel engines may also have larger oil pans to help keep oil temperatures down.
Other Additions and Modifications: Marine engines are often installed in engine
compartments without much air flow for cooling, which can result in a number of exposed hot
surfaces (leading to safety concerns) or performance problems from overheating the engine.
To address safety concerns and to comply with U.S. Coast Guard regulations, marine diesel
engines are designed to keep engine and exhaust component (exhaust manifold, turbocharger
and exhaust pipe) temperatures cool. Recreational and light duty commercial engines can
accomplish this by running cool water through a jacket around the exhaust system
components. Larger engines generally use a thick insulation around the exhaust pipes.
Marinization might also include replacing some engine parts with parts made of
materials more durable in a marine environment. These changes include more use of chrome
and brass to prevent corrosion. Because of the unique marine engine designs, marinizers also
add their own front accessory drive assembly. Finally, marine engines must also be coupled
with the lower drive unit to be applicable to a specific vessel.
1-12
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Industry Characterization
1.1.2.2.3 Nonroad Diesel Engine Costs of Production
The U.S. Census Bureau does not differentiate cost of production figures for marine
diesel engines (North American Industry Classification System [NAICS] 333618B106).
However, because small, recreational Cl, commercial Cl, and commercial C2 engines are
derived from nonroad diesel engines, costs of production for nonroad engines could be used to
illustrate costs of production of marine diesel engines (NAICS 3336183). Costs of production
figures are divided into major input categories of labor, materials, and capital expenditures.
Of these categories, purchased materials account for the largest share of total costs. Based on
data from the most recent Economic Census, costs of materials represent about 64 percent of
the value of shipments, followed by labor at about 11 percent and capital expenditures at
about 3 percent. (These numbers correspond with the broader "other engine manufacturing"
category [NAICS 333618].)
Table 1-8 lists the primary materials used in engine components.9 No breakdown of
cost of materials used in production is available from the 2002 Economic Census for the
specific category of marine diesel engines (NAICS 333618B106) nor for nonroad diesel
engines (NAICS 3336183), but based on the broader "other engine manufacturing" category
(NAICS 333618), cost of materials are dominated by cast and formed metal. Iron and steel
accounted for 13 percent of material costs; aluminum accounted for 7 percent; injection fuel
pumps for 5.6 percent; pistons, valves, and piston rings for 3.5 percent; and engine electrical
equipment for 3.5 percent. All other materials and components, parts, containers, and
supplies accounted for 52 percent; no single material accounted for more than 2 percent of
material costs.
Table 1-8 Nonroad and "Other Engine" Costs of Production and Materials Consumed in 2002
NAICS
3336 18 Other engine
equipment manufacturing
3336183 Diesel, semi-
diesel, and dual-fuel
engines (except
automobile, highway
truck, bus, tank)
Materials Consumed by
333618
Iron and steel
Aluminumc
Value of
Shipments
($106)
18,586
2,003
Cost($106)
1,449
770
Labor ($106)a
2,145
11.5%
215
10.7%
Share of Cost
of Materials
13.1%
6.9%
Cost of
Materials
($106)a
11,800
63.5%
1,287
64.3%
Capital
Expenditures
($106f
730
3.9%
59
2.9%
Notes:
NAICS codes 33211101,33151001,33120007, 33120016, 33120033.
1 NAICS codes 33152005, 33152003, 33631100.
1-13
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Regulatory Impact Analysis
1.1.2.2.4 Nonroad Diesel Engine Manufacturers and Marinizers
As was previously discussed, marine diesel engines are typically derived from similar
size land-based diesel engines through the marinization process. Marinization is normally
performed by two types of firms, and has an impact on the engine's emission characteristics.
First, there are large engine manufacturers such as Cummins, Caterpillar, and Deere
that marinize their land-based nonroad engines. They are referred to as domestic engine
manufacturers (DEMs), and they are usually involved in every step of the manufacturing
process of a marine engine. Foreign engine manufacturers (FEMs) are similar to DEM, but
they are owned by foreign parent companies (this also pertains to DDC and EMD, which are
owned by foreign investment companies now). Production of marine engines begins on the
nonroad production line; however, at some stage of the production process, an engine is
moved to a different assembly line or area where production is completed using parts and
processes specifically designed for marine applications.
Second, postmanufacture marinizers (PMMs), or simply marinizers, are smaller
manufacturers that purchase complete or semi-complete land-based engines from engine
manufacturers and complete the marinization process themselves using specially designed
parts, potentially modifying fuel and cooling systems.
Table 1-9 lists DEM, FEM, and PMM companies. Only four U.S.-based engine
manufacturers produce and marinize their marine diesel engines. Cummins is the only
company involved in two types of production. In addition to marinizing their own, Cummins
(through its subsidiary Onan) produces generators using Kubota engines and therefore is
included in both the DEM and postmanufacture marinizers categories.
1-14
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Industry Characterization
Table 1-9 Marine Engine Manufacturers
Domestic Engine
Manufacturers
Caterpillar
Cummins
Deere & Company
General Electric
Foreign Engine Manufacturers
Deutz
EQT (parent to MTU)
Greenbriar Equity, LLC (parent
to EMD)
MAN
Rumo
Volvo
Yanmar
Postmanufacture Marinizers
Bombardier"
Brunswick
Cummins
Daytona Marine"
Fairbanks Morse"
Klassen
Kohler
Marine Corp. of America"
Marine Power
NREC Power Systems
Peninsular Diesel
Reagan Equipment"
Stewart & Stevenson
Sword Marine Technology
Valley Power Systems (parent to
Alaska Diesel)
Westerbeke
These companies' production is not included in the 2004 PSR database.
1.1.2.2.5 Marine Engine Dressing
Marine engine dressing refers to the modifications made to a land-based engine that
enable it to be installed on a marine vessel. Unlike PMMs, however, the changes made by
marine dressers do not affect the emission characteristics of the engine. These modifications
can be made by engine manufacturers or marine dressing firms. Modifications typically
include installing mounting supports and a generator (in the case of an auxiliary engine) or
propeller gears (in the case of propulsion engines). Other modifications consist of adding
adaptors, water-cooled exhaust manifolds, water tanks, electronic instrumentation, and alarm
systems. There are many manufacturers of this type. However, because these companies do
not do anything to the engines to change their emission characteristics, they are exempted
from the regulations. Thus, their coverage will be omitted in this profile.
1.1.2.2.6 Marine Engine Remanufacturing
Marine remanufacturers are engaged in the manufacture or assembly of
remanufactured marine diesel engines. We have identified about 10 U.S. companies
(aftermarket suppliers or aftermarket parts manufacturers and engine manufacturers) that
could potentially remanufacture marine engines. Some of these companies are only involved
in the remanufacture of locomotives. Two companies are both locomotive and marine
remanufacturers that have already certified models.
1-15
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Regulatory Impact Analysis
1.1.2.3 Demand Side
Marine diesel engines can be distinguished according to whether they are used on
commercial or recreational applications. As discussed above, the basic difference derives
from the nature of the requirements on the engine in each application: more power density in
recreational applications and more durability in commercial applications. In this section, we
look at the characteristics of the four key segments of this industry; Recreational marine Cl
and small (at or below 37 kW), Commercial Cl, and C2 diesel engine markets.
Table 1-10 presents the total number of engines produced in and imported to the
United States broken down by application category. According to the data in the PSR
database, the largest single category is marine engines produced for propulsion purposes in
recreational applications (17,954). A slightly smaller number was produced for all auxiliary
functions (16,377) and the rest for propulsion purposes in commercial applications (6,524).
Based on the engine category, the majority of the engines produced or imported were
classified as commercial Cl, followed by recreational Cl and small. Category 2 is the
smallest category with 277 engines produced in 2002.
Table 1-10 Marine Diesel Engine Production by Application and Use Type (2002)
Use Type
Commercial
propulsion
Marine auxiliary
Pleasure
propulsion
Total
Small (<37
kW)
NA
6,798
3,963
10,761
Cl Recreational
NA
NA
13,952
13,952
Cl Commercial
6,389
9,437
NA
15,826
C2
135
142
NA
277
A further look into the characteristics of a commercial fleet was accomplished by
taking a random sample of nearly 400 vessels from the Inland River Record (2006).10 That
sample suggests that the average age of vessels in that fleet is 30 years (with vessels built
between 1944 and 2004), and the average horsepower of these vessels is 840 hp (with a range
of 160-4,400 hp). About 68% of the engines in these vessels were built after 1972, and 31%
were both greater than 800 hp and built after 1972. In addition, about 65% of the engines that
are greater than 800 hp were derived from locomotive engines. Although this sample reflects
only the characteristics of the vessels included in the Inland River Record (primarily tug and
towboats), it provides a detailed look into one database of existing vessels.
1.1.2.3.1 Recreational Applications
Recreational boats (especially the larger ones powered by diesel engines) are generally
considered discretionary goods; demand for them is typically price elastic.
There are several reasons why consumers might choose diesel engines over gasoline
engines for recreational applications. First, diesel engines are more durable and reliable.
Second, diesel engines have better fuel consumption.
1-16
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Industry Characterization
Based on the National Marine Manufacturers Association (NMMA) sales data, there
were approximately 5,760 diesel-powered (out of a total 10,200 diesel and gas-powered
inboard cruiser boats) recreational boats sold in 2002. NMMA also estimated that among
10,200 boats, 92.2 percent had a twin engine.11 Under these ratios, we estimated 11,070
recreational marine diesel engines were sold for propulsion purposes in the United States in
2002. This number differs from 13,952 engines imported or produced in the United States in
2002, as reported in the PSR database. Some of the engines produced are used as the
replacement engines; however, the PSR OELink database is probably not entirely accurate.
Because the NMMA estimate is derived from surveying a large portion of the industry
stakeholders, their consumption estimate seems more reliable.
Not included in that estimate are small marine diesel engines. PSR data indicate that
10,761 small marine diesel engines were produced in 2002, with approximately 64 percent of
those being used for auxiliary purposes and the remainder used as maneuvering engines on
recreational applications and as cruising engines on sailboats.
1.1.2.3.2 Commercial Cl Applications
Engines in this category are inputs into various commercial applications, such as
seasonal and commercial fishing vessels, emergency rescue vessels, ferries, and coastal
freighters.
Commercial vessels are inputs into a wide range of production processes that generate
products and services. As a result, the demand for Cl engines is linked directly to the demand
for boats, and indirectly through the supply chain to the demand for final products and
services produced with commercial ships and boats.
No data are readily available on the volumes of commercial boats produced annually
in the United States. However, based on the 2004 Workboat Construction survey of
approximately 400 commercial boats scheduled to be delivered in 2005, we estimate that 40
percent of them were Cl, 55 percent were C2, and 5 percent were C3 (Workboat, 2005).
Using these estimates, we find that 160 Cl engine-powered commercial vessels were
produced in the United States in 2004. Once again, this number does not correspond with
6,389 engines listed by PSR. More than likely Workboat Construction journal's survey lists
the largest commercial ships and boats, and many smaller commercial boats are unaccounted
for.
1.1.2.3.3 Commercial C2 Applications
Commercial C2 engines might be used on crew and supply boats, trawlers, and tug
and tow boats. Many of the engines are also used as large auxiliary engines on ocean-going
vessels. Based on the Workboat Construction survey estimate, there were 220 C2 engine-
powered commercial vessels built in the United States in 2004.12 This number is lower
compared with 2002 production volume (277 engines) listed by PSR.
Like commercial Cl engines, commercial C2 engines are inputs in vessels, which are
in turn inputs in production processes that generate products and services. Therefore, demand
1-17
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Regulatory Impact Analysis
for commercial C2 engines is linked directly to the demand for commercial C2 vessels and
indirectly to the demand for products and services produced with these vessels.
1.1.2.4 Market Structure
Figure 1-1-2 and Figure 1-1-3 present small and recreational Cl marine diesel engine
market breakdown by the type of a supplier. In 2002, a majority of the small marine diesel
engines (60 percent) were supplied by engine marinizers, with about half of that value
supplied by engine dressers, and only 11 percent by foreign engine manufacturers (FEM) that
oversee the entire production process. No domestic engine manufacturers (DEM) supplied
engines to this market. The situation is opposite for the recreational Cl market, where DEMs
supply 45 percent of engines, and FEMs supply 26 percent. Marinizers accounted for 28
percent, and dressers for less than 1 percent of the recreational Cl market supply.
Table 1-11 details the top three engine manufacturers and marinizers in the small (at
or below 37 kW) and Cl recreational categories. The majority of the engines in the small
category are supplied by U.S.-based marinizer Westerbeke (48 percent). In 2002, Japanese
manufacturer Yanmar and U.S.-based marinizer Kohler both had approximately 10 percent of
the market share. Cummins, a DEM, serves as a marinizer in this market. Kubota engines,
marinized by Cummins, accounted for approximately 3.5 percent of small marine diesel
engine market supply in 2002.
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Industry Characterization
Figure 1-1-2 Small (<37 kW) Marine Diesel Engine Market Supply by Manufacturer Type (2002)
Post-
Manufacturer
Marinizers
61%
Dressers
23%
Foreign Engine
Manufacturers
11%
Figure 1-1-3 Cl Recreational Marine Diesel Engine Market Supply by Manufacturer Type (2002)
Post-Manufacturer
Marinizers
28%
Foreign Engine
Manufacturers
26%
Domestic Engine
Manufacturers
45%
Dressers
1%
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Regulatory Impact Analysis
Table 1-11 Top Three Small and Recreational Cl Marine Diesel Engine Manufacturers and Marinizers
(2002)
Cl
Engine Manufacturers
Caterpillar
Cummins
Yanmar
Top 3 Firms' Production
Engine Marinizers
Westerbeke
Peninsular Diesel
Brunwick Corporation
Top 3 Firms' Production
Total Dressers
Total Cl Market
Small (<37 kW)
Engine Manufacturers
Yanmar
Engine Marinizers
Westerbeke
Valley Power Systems, Inc.
Kohler
Top 3 Firms' Production
Total Dressers
Total Small Market
2002 Production
9,524
2,800
23
13,952
(D)
7,136
2,000-3,000"
10,761
Market Share
68.3%
20.1%
0.2%
(D)
66.3%
25%-30%a
The range is provided to avoid disclosing proprietary information of individual companies.
(D) = Data have been withheld to avoid disclosing proprietary information of individual companies.
1.1.2.4.1 Cl Commercial Applications
The supply structure of the commercial Cl marine diesel engines market resembles
the supply structure of the recreational Cl market, with DEMs and PMMs supplying 76
percent of the engines to the market (Figure 1-1-4). As opposed to the recreational Cl
market, dressers supply a larger portion of the commercial Cl market (19 percent), with
FEMs supplying 5 percent.
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Industry Characterization
Figure 1-1-4 Commercial Cl Marine Diesel Engine Market Supply by Manufacturer Type (2002)
Post-Manufacturer
Marinizers
35%
Foreign Engine
Manufacturers
5%
Domestic Engine
Manufacturers
41%
Dressers
19%
Commercial Cl marine diesel engine market shares are listed by the type of
manufacturer in Table 1-12. DEMs Caterpillar and Deere and engine marinizer Kohler have
approximately equal market shares of 15 percent each. They are followed by U.S.-based
marinizer Westerbeke with an 11 percent market share. Even though engine dressers are not
covered by this rule, it is worth noting that the vast majority of the engines supplied in the
commercial Cl market by these companies are auxiliary engines.
Table 1-12 Top Three Commercial Cl Marine Diesel Engine Manufacturers and Marinizers (2002)
Cl
Engine Manufacturers
Caterpillar
Deere & Company
Cummins
Top 3 Firms' Production
Engine Marinizers
Kohler
Westerbeke
Valley Power Systems, Inc.
Top 3 Firms' Production
Total Dressers
Total Cl Market
2002 Production
6,452
5,690
1,383
15,826
Market Share
40.8%
36.0%
8.7%
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Regulatory Impact Analysis
1.1.2.4.2 Commercial C2 Applications
The commercial C2 marine diesel market is not supplied by dresser companies; most
of the supply comes from marinizers, which supply approximately half of its volume. U.S.-
based companies are dominant in the commercial C2 marine diesel engine market. Among
engine manufacturers, Caterpillar, and among marinizers, General Motors and Stewart and
Stevenson, together compose 78.4 percent of the market. Caterpillar is followed by Japanese
manufacturer Yanmar and German MAN B&W with 11 and 6 percent, respectively (Table
1-13).
Table 1-13 Top Three Commercial C2 Marine Diesel Engine Manufacturers and Marinizers (2002)
C2
Engine Manufacturers
Caterpillar
Greenbriar Equity LLC
Yanmar
Top 3 Firms' Production
Engine Marinizers
Stewart and Stevenson
Total Dressers
Total C2 Market
2002 Production
87
73
31
191
(D)a
277
Market Share
69.0%
(D)
0.0%
(D) = Data have been withheld to avoid disclosing proprietary information of individual companies.
1.1.2.4.3 Pricing Behavior of Marine Diesel Engine Markets
Discussions about market competitiveness usually focus on two types of pricing
behavior: perfect competition (price-taking behavior) and imperfect competition (lack of
price-taking behavior). Under the former scenario, buyers and sellers take (and thus are
"price takers") the market price set in a competitive equilibrium: the market price equals the
value consumers place on the marginal product, as well as the marginal cost to producers.
Under this scenario, firms have some ability to influence the market price of the output they
produce. For example, a firm might produce a commodity with unique qualities that
differentiate its product from its competitors' product. The value consumers place on the
marginal product, the market price, is greater than the cost to producers. Thus, the social
welfare is reduced under this scenario.
As evident from the market share information presented in this report, marine diesel
engine markets are moderately (small and commercial Cl) to highly (recreational Cl and
commercial C2) concentrated and thus have a potential for emergence of imperfect
competition. Nevertheless, our analysis suggests mitigating factors will limit prices from
rising above the marginal cost; therefore, the assumption of perfect competition is justified.
First, the threat of entry encourages price-taking behavior. Industries with high profits
provide incentives to new firms to enter the market and lower the market price to their
competitive levels. In all of the marine diesel markets, domestic and foreign candidates can
enter any of these markets without incurring significant costs.
1-22
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Industry Characterization
Second, the data on capacity utilization rates published by the Federal Reserve (for
machinery, NAICS 333) suggest that excess capacity exists in the broad category that also
includes converted internal combustion engines industry (NAICS 333618B106). February
2006 data present an industry utilization rate of 82.6 percent. If these data do, in fact, indicate
excess capacity in the marine diesel engine industry, then the ability to raise prices is limited
by excess idle capacity.
Third, other theories place less value on market shares as a determinant of pricing
behavior and examine the role of potential competition instead. For instance, three conditions
of perfectly contestable markets demonstrate how potential competition may lead to perfect
competition:13
New firms have access to the same production technology, input prices, products, and
demand information as existing firms
All costs associated with entry can be fully recovered
After learning about new firms' entry, existing firms cannot adjust prices before these
new firms supply the market
Although the extent to which these conditions apply to marine diesel engine markets is
not clear, the theory suggests that market shares alone should not necessarily be considered as
an indicator of imperfect competition in the market.
1.1.2.5 Historical Market Data
1.1.2.5.1 Recreational Applications
The historical market statistics are presented as a means to assess the future of marine
diesel engine production. Information on production trends is presented here.
Historical production volumes for recreational Cl and small marine diesel engine
markets are presented in Table 1-14. The small marine diesel engine market demonstrated
continuous growth in production between 1998 and 2002, growing by 37 percent since 1998.
The recreational Cl market experienced a slight peak in 2000 with 7 percent growth and then
leveled off in 2002 at a slightly higher volume than it was in 1998.
Table 1-14 Historical Market Trends for Small and Recreational Cl Marine Diesel Markets
2002
2001
2000
1999
1998
Percentage Change
Recreational Cl
13,952
13,754
14,408
13,836
13,446
3.8%
Small
10,761
9,833
9,576
7,997
7,853
37.0%
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Regulatory Impact Analysis
1.1.2.5.2 Commercial Cl Applications
The commercial Cl engine market demonstrated a strong steady growth in the past 5
years. Starting at 10,508 engines produced and imported into the United States in 1998, it
grew by more than 50 percent and equaled 15,826 engines in 2002 (Table 1-15).
Table 1-15 Historical Market Trends Commercial Cl Marine Diesel Market
Year
2002
2001
2000
1999
1998
Percent Change
Production
15,826
14,078
12,838
12,178
10,508
50.6%
1.1.2.5.3 Commercial C2 Applications
The commercial C2 market has a relatively small volume of sales compared to the
recreational and commercial Cl markets. Nevertheless, the commercial C2 market
experienced significant growth in the past 5 years. In the period from 1998 to 2002, market
volume more than doubled and equaled 277 engines in 2002 (Table 1-16).
Table 1-16 Historical Market Trends Commercial Cl Marine Diesel Market
Year
2002
2001
2000
1999
1998
Percentage Change
Production
277
231
200
138
134
106.7%
1.1.3 Marine Vessel Manufacturers
Marine vessels include a wide variety of ships and boats. Several alternative
definitions exist to distinguish between ships and boats. For this profile, ships are defined as
those marine vessels exceeding 400 feet in length. They are built to purchasers' specifications
in specialized "Main Shipyard Base" ship yards, and typically powered by Category 3 diesel
engines. Under this definition most of the vessels powered by small, Cl or C2 diesel engines
would be considered boats. In this section, the terms "vessel" and "boat" will be used
interchangeably. Vessels powered by Cl and C2 engines vary widely; they may be made
from fiberglass-reinforced plastic (FRP or fiberglass), aluminum, wood, or steel. Some
vessels are serially produced using assembly line methods; others are individually built to
meet purchasers' specifications in boatyards or in the same yards that build ships. Small
boats may be powered by small spark-ignition (gasoline) engines. Vessels covered by this
profile include a small share of recreational boats: inboard cruisers, especially those over 40
feet in length. In addition the profile covers diesel-powered commercial and governmental
1-24
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Industry Characterization
vessels such as tug/tow boats, fishing vessels, passenger vessels, cargo vessels, offshore
service vessels and crew boats, patrol boats, and assorted other commercial vessels.
The Economic Census includes two industry sectors, NAICS 336611 Ship Building
and Repairing and NAICS 336612 Boat Building, that together cover the marine vessel types
addressed in this profile. Each NAICS includes some vessels not included in this profile.
NAICS 336612 defines boats as "watercraft not built in shipyards and typically of the type
suitable or intended for personal use."; thus, NAICS 336612 includes essentially recreational
vessels; within this NAICS, NAICS 3366123 covers inboard motor boats, including those
powered by diesel engines. Thus, the diesel-powered recreational vessels covered by this
profile represent only a relatively small share of NAICS 336612. NAICS 336611 comprises
establishments primarily engaged in operating a shipyard, fixed facilities with drydocks and
fabrication equipment capable of building a "watercraft typically suitable or intended for
other than personal or recreational use."14 Commercial and governmental vessels powered by
small, Cl and C2 diesel engines are included in NAICS 336611, along with larger ships that
are powered by C3 engines and thus not covered by this profile.
1.1.3.1 Overview of Vessels
This profile covers a wide variety of vessels, including recreational vessels and
smaller commercial, service, and industrial vessels, generally less than 400 feet in length.
Commercial vessels under 400 feet long dominate inland and coastal waters where shallow
drafts restrict access by larger ships. Depending on their mission, Cl- and C2-powered
vessels also may operate in the Great Lakes, coastwise, intercoastal, noncontiguous, and/or
transoceanic environments. The principal commercial boat types are tugboats, towboats,
offshore supply boats, fishing and fisheries vessels, passenger boats, and industrial boats, such
as cable- and pipe-laying boats, oceanographic boats, dredges, and drilling boats. Passenger
boats include crewboats, excursion boats, and smaller ferries.
Most commercial vessels covered by this profile are U.S.-built, U.S.-owned and U.S.-
operated. Under provision of the Jones Act (Section 27, Merchant Marine Act, 1920), vessels
transporting merchandise between U.S. ports must be built in and documented under the laws
of the United States and owned and operated by persons who are citizens of the United States.
Because Cl and C2 diesel engines are frequently used to power vessels that operate in inland
waters or coastwise, they are generally operating between U.S. ports. Thus, many cargo
vessels powered by Cl and C2 diesel engines are required to be U.S.-built, -owned, and -
operated, unless a waiver is granted by the Secretary of the Treasury.
Generally excluded from this profile, because they are powered by C3 engines, are
larger merchant and military vessels, typically exceeding 400 feet in length, that engage in
waterborne trade and/or passenger transport or military operations. Commercial and
government-owned (e.g., military) ships operate in Great Lakes, coastwise, intercoastal,
noncontiguous (between United States mainland and its noncontiguous territories, such as
Alaska, Hawaii, and Puerto Rico), and/or transoceanic routes. The principal commercial ship
types are dry cargo ships, tankers, bulk carriers, and passenger ships. Dry cargo ships include
break bulk, container, and roll-on/roll-off vessels. Passenger ships include cruise ships and
the largest ferries. Military ships include aircraft carriers, battleships, and destroyers. Also
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Regulatory Impact Analysis
excluded from the profile are the smallest recreational, commercial, and government vessels,
which are powered by gasoline outboard, stern-drive, or inboard engines. Figure 1-1-5
illustrates the size of the U.S. commercial fleet over time from 1980 to 2003 and the
distribution between larger and smaller vessels. Compared with smaller commercial vessels,
larger commercial vessels represent a small fraction of the U.S. commercial fleet.
Figure 1-1-5 includes vessels as small as 1,000 gross tons in the ship, rather than boat
population, and omits key categories of boats (smaller vessels), such as supply boats and
fishing boats.15 It is very difficult to develop useful criteria which will allow the separation of
vessel populations into those powered by the various engine categories. Nonetheless, this
analysis provides some insight as to the relative proportion of vessels in the U.S. fleet
powered by C1/C2 engines versus C3 engines.
Figure 1-1-5 U.S. Commercial Fleet (1980 to 2003)
10 poo -,
1930
2003
CS
C1/C2
1.1.3.2 Overview of Vessel Manufacturers
This report classifies vessel manufacturing facilities ("yards"), according to the types
of vessels manufactured. The Economic Census reports on two industry segments that are
related to vessel manufactureshipbuilding and repairing (NAICS 336611) and boatbuilding
(NAICS 336612). Shipbuilding facilities typically have drydocks. NAICS 336612
encompasses facilities that build "watercraft suitable for personal or recreational use," which
corresponds closely to recreational boats, and NAICS 336611 includes facilities that build
larger commercial and government vessels. Both NAICS codes include vessels not covered by
this profile.
NAICS 336611 includes generally one-of-a-kind vessels built in a shipyard with
drydock facilities, including vessels powered by Category 1 and 2 diesel engines, as well as
the larger Category 3 engines. Most vessels manufactured by this NAICS code are for
commercial or governmental applications (e.g., Coast Guard, military, Army Corps of
Engineers, municipal harbor police).
1-26
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Industry Characterization
NAICS 336612 covers generally recreational vessels. These may be built using
repetitive methods, such as an assembly line process or individually; it includes those
powered by gasoline, alcohol, and diesel engines. Within NAICS 336612, only larger (over
40 feet) inboard cruisers are predominantly powered by diesel engines. This segment of
NAICS 336612 (NAICS 3366123 Inboard Motorboats) includes only 82 establishments, less
than 7 percent of the total in the NAICS code. Because most of the smaller inboard
motorboats are Si-powered, the number of facilities manufacturing diesel-powered
recreational vessels is even smaller. The information summarized in Table 1-17 shows
information about establishments and companies in NAICS 336611 and 336612, and indicates
that there are a large number of small establishments in both of these industry segments.16
Most companies in both NAICS codes are single-establishment companies.
Table 1-17 2002 Economic Census Data on Shipbuilding and Boatbuilding Industries
Number of establishments
Number of companies
Establishments with 100+
employees
Establishments with 500+
employees
NAICS 3 3 66 11
(shipbuilding)
639
586
91
21
NAICS 336612
(boatbuilding)
1,123
1,063
134
16
Within NAICS 336611, the U.S. Maritime Administration (MARAD) classifies yards
as either first-tier or second-tier according to building capacity. In the Report on Survey of
U.S. Shipbuilding and Repair Facilities, MARAD (2003) identifies 24 first-tier yards, which
form the "major shipbuilding base" (MSB) in the United States. The 24 MSB yards satisfy
several requirements, including at least one construction position capable of accommodating a
vessel that is 400 feet in length or over and an unobstructed waterway leading to open water
(i.e., locks, bridges) and the channel water must be a minimum of 12 feet deep. While MSB
yards are the only ones to manufacture large ships, many of them also produce smaller
commercial vessels. Second-tier yards do not meet these criteria and include many small- and
medium-sized yards that construct and repair boats.17
1.1.3.3 Recreational Vessels
This section describes the recreational boat manufacturing industry, with special
attention to the segment of the industry using diesel engines.
1.1.3.3.1 Types of Recreational Vessels
U.S. boatbuilders construct a variety of recreational boats, including ski/wakeboard
boats, powerboats, racing boats, sailboats, recreational fishing boats, and yachts. Only a small
segment of recreational boats are powered by diesel engines and thus addressed by this
profile. Diesel-powered types of vessels include inboard cruisers and most of the larger
yachts.
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Regulatory Impact Analysis
1.1.3.3.2 Supply of Recreational Vessels
Boats for personal and recreational use can be manufactured from many different
materials, including fiberglass-reinforced plastic (FRP), aluminum, rotationally molded
(rotomolded) polyethylene or other thermoplastic materials, and wood. Only relatively large
(over 40 foot) inboard cruisers commonly use diesel engines; diesel engines used in
recreational vessels are almost exclusively Cl engines, although C2 engines may be used on
the largest yachts. Among recreational boats, large inboard cruisers are less likely to be
serially produced; because they are quite costly, they tend to be customized to buyers'
specifications. Like smaller serially produced boats, the most common hull material is FRP.
1.1.3.3.3 Production Process
The most common material used in boat manufacturing is FRP. Boats made from FRP
are typically manufactured serially. Using FRP makes it very difficult to incorporate
purchaser preferences into a vessel's design because 1) many features are designed into
fiberglass molds, making customization time consuming and expensive and 2) vessels
constructed from FRP are very sensitive to changes in their vertical or horizontal centers of
gravity, making it difficult to change a particular design. In some cases, boat manufacturers
produce the FRP hulls and decks used in constructing their boats; in other cases the FRP hulls
and decks of boats are manufactured by a contractor for the boat manufacturer.
The process typically used to manufacture these boats is known as open molding. In
this process, separate molds are used for the boat hull, deck, and miscellaneous small FRP
parts such as fuel tanks, seats, storage lockers, and hatches. The parts are built on or inside
the molds using glass roving, cloth, or mat that is saturated with a thermosetting liquid resin
such as unsaturated polyester or vinylester resin. The liquid resin is mixed with a catalyst
before it is applied to the glass. The catalyzed resin hardens to form a rigid shape consisting
of the plastic resin reinforced with glass fibers.
The FRP boat manufacturing process generally follows the following production
steps:
Before each use, the molds are cleaned and polished and then treated with a mold
release agent that prevents the part from sticking to the mold
The open mold is first spray coated with a pigmented polyester resin known as a
gel coat that will become the outer surface of the finished part. The gel coat is
mixed with a catalyst as it is applied so that it will harden
After the gel coat has hardened, the inside of the gel coat is coated with a skin coat
of polyester resin and short glass fibers and then rolled with a metal or plastic
roller to compact the fibers and remove air bubbles. The fibers are applied in the
form of a chopped strand mat or chopped roving from a chopper gun; the skin coat
is about 90 mils (0.09 inches) thick and is intended to prevent distortion of the gel
coat (known as "print through") from the subsequent layers of fiberglass and resin
1-28
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Industry Characterization
After the skin coat has hardened, additional glass reinforcement in the form of
chopped roving, chopped strand mat, woven roving, or woven cloth is applied to
the inside of the mold and saturated with catalyzed polyester resin. The resin is
usually applied with either spray equipment or by hand using a bucket and brush
or paint-type roller. The saturated fabric is then rolled with a metal or plastic
roller to compact the fibers and remove air bubbles
More layers of woven glass or glass mat and resin are applied until the part is the
desired thickness; the part is then allowed to harden while still in the mold. As the
part cures, it generates heat from the exothermic reactions that take place as the
resin hardens; very thick parts may be built in stages to allow this heat to dissipate
to prevent heat damage to the mold
After the resin has cured, the part is removed from the mold and the edges are
trimmed to the final dimensions
The different FRP parts of the boat are assembled using small pieces of woven
glass or glass mat and resin, adhesives, or mechanical fasteners
After the assembly of the hull is complete, the electrical and mechanical systems
and the engine are installed along with carpeting, seat cushions, and other
furnishings and the boat is prepared for shipment
Some manufacturers paint the topsides of their boats to obtain a superior finish; the
larger boats generally also require extensive interior woodwork and cabin
furnishings to be installed
As noted above, only the larger inboard cruisers are likely to have diesel propulsion
engines. Of all inboard cruisers, 56 percent are diesel-powered. For boats less than 40 feet in
length, less than 35 percent are diesel-powered; for those over 40 feet in length, 85 percent are
diesel-powered. Table 1-18 provides estimates of inboard cruiser retail sales by engine type
and length of boat. In 2003, 5,191 diesel-powered inboard cruisers were sold; of these, 3,032
were 41 feet or longer. Another 988 diesel-powered cruisers ranged from 36 to 40 feet in
length. Only 454 were 30 feet long or less.18
Table 1-18 Estimates of Inboard Cruiser Retail Unit Sales by Engine Type and Length of Boat
Boat Length
30' and under
3T-35'
36'-40'
41' and over
Total
1997
Gas
917
1,525
1,048
529
4,019
Diesel
178
309
492
1,302
2,281
1999
Gas
1,064
2,199
1,142
428
4,833
Diesel
435
673
804
2,655
4,567
2001
Gas
1,059
2,458
1,280
420
5,217
Diesel
495
953
991
3,144
5,583
2003
Gas
279
1,294
1,984
572
4,109
Diesel
454
717
988
3,032
5,191
Table 1-19 summarizes the sales data from 1997 through 2003 for recreational boats.
In 2003, an estimated 9,200 inboard cruisers were sold; 97 percent of inboard cruisers over 31
feet long were powered by twin engines. Sales in the United States are expected to continue
1-29
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Regulatory Impact Analysis
to decrease as more and more of the larger recreational boats are being built overseas (e.g.,
19
Taiwan).
Table 1-19 Estimates of Inboard Cruiser Retail Unit Sales by Single vs. Twin Engine and Length of Boat
Boat Length
30' and under
3T-35'
36'-40'
41' and over
Total
1997
Single
789
91
51
30
961
Twin
306
1,742
1,490
1,801
5,339
1999
Single
1,028
97
112
23
1,260
Twin
471
2,775
1,834
3,060
8,140
2001
Single
1,004
155
233
32
1,424
Twin
550
3,256
2,038
3,532
9,376
2003
Single
463
86
136
20
705
Twin
271
1,925
2,815
3,584
8,595
While not all inboard cruisers are diesel-powered, the production costs for inboard
cruisers as a group are likely representative of the relative costs of various inputs used in
producing diesel-powered inboard cruisers. Production costs for builders of inboard cruisers
include the costs of materials, labor, and capital equipment. Materials costs are more than
double the cost of labor for these producers and represent roughly half of the value of
shipments of inboard cruisers (see Table 1-20).20 Because diesel engines are generally more
expensive than gasoline engines, materials may represent an even larger share of diesel-
powered inboard cruiser costs.
Table 1-20 Costs of Production for NAICS 3366123, Inboard Motorboats, Including Commercial and
Military, Except Sailboats and Lifeboats
Establishments
82
Number
13,412
Payroll
($1,000)
427,949
Number
10,457
Hours
(1,000)
20,773
Wages
($1,000)
299,815
Cost of
Materials
($1,000)
1,197,464
Capital
Expenditure
s($ 1,000)
39,900
Value of
Shipments
($1,000)
2,384,478
1.1.3.3.4 Demand for Recreational Vessels
Recreational boats are final consumer goods, and are generally considered
discretionary purchases. Demand for recreational boats is typically characterized by elastic
demand.
1.1.3.3.5 Industrial Organization for Recreational Vessel Manufacturers
Recreational boat builders are located along all coasts and major waterways. Table 1-
21 provides sales and employment information of recreational diesel boat builders.21'22'23 Of
the 36 companies for which data were identified, only 9 employ more than 500 employees.
Two large, multi-facility companies (Genmar and Brunswick) employ 21,000 and 6,000
employees respectively. Companies with fewer than 500 employees would be considered
small businesses under the criteria of the Small Business Administration for NAICS 336612.
Based on that definition, the majority of firms producing recreational diesel boats would thus
be considered small entities.
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Industry Characterization
Table 1-21 Employment Distribution of Companies that Build Recreational Boats
Employment Range
0-100
101-250
251-500
501-1,000
1,000+
Total number of firms
Number of Firms
11
9
7
4
5
36
Revenue Range (SMillions)
1.3-8.5
9.2-45.0
20.2- 101.7
63.2-131.0
45.60-5,229
Although there are a few large companies in the recreational diesel boat building
industry, there are many more small companies. The boat yards are located on water bodies
throughout the country, and many serve somewhat regional markets. Because there are a
relatively large number of suppliers, because there is increasing competition from foreign
suppliers, and because barriers to entry and exit are low, it is reasonable to characterize the
markets for recreational diesel vessels as competitive. As described in section 1.1.2.4.3, the
potential for competition and entry (contestable markets) forces existing producers to behave
in a competitive manner.
1.1.3.3.6 Markets and Trends in the Recreational Vessel Manufacturing Industry
As summarized in Table 1-22, prices for inboard cruisers 41 feet and longer have
displayed no clear trend during the period 2001-2003.24 Prices in most categories dipped in
2003, reaching prices below 2001 levels. This may result from increased competition from
foreign suppliers.
Table 1-22 Estimated Average Retail Selling Price of Recreational Inboard Boats by Length of Boat
Boat Length
41' and over
41M9'
50'-59'
60'-65'
66' and over
1997
$490,409
1998
$475,869
1999
$469,866
2000
$516,146
2001
$449,990
$963,197
$2,166,030
$3,627,189
2002
$419,873
$898,256
$2,280,029
$4,464,111
2003
$384,329
$842,578
$2,220,833
$2,816,731
Information from NMMA indicates that the number of larger recreational boats being
built abroad, in places like Taiwan, has increased significantly in the last few years.25 A
recent NMMA report on recreational boat sales compiled U.S. Department of Commerce
import and export data, as reported in the U.S. International Trade Commission database. The
2003 data confirmed that the trade imbalance continues to grow. Factors affecting this growth
include the rising cost of shipping, trade disputes between the U.S. and Europe, and the
strength of the dollar, which makes it difficult for U.S. boatbuilders to offer competitive
pricing overseas.
Table 1-23 shows that exports of vessels declined from 1997 to 2001, then increased,
posting a substantial increase between 2002 and 2003.26 Imports continue to outpace exports,
with the trade balance deficit roughly tripling between 1997 and 2003. However, because of
the substantial increase in exports, the deficit actually fell between 2002 and 2003.
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Regulatory Impact Analysis
Table 1-23 Value of Imported and Exported Vessels (in SMillions)
Boats export
Boats import
Trade balance
1997
$678.6
$835.0
-$156.40
1998
$674.8
$874.7
-$199.90
1999
$698.5
$984.2
-$285.70
2000
$662.0
$1,074.8
-$412.80
2001
$560.4
$1,113.1
-$552.70
2002
$600.5
$1,157.7
-$557.20
2003
$746.5
$1,207.2
-$460.70
1.1.3.4 Commercial Vessels
This section builds on earlier work by EPA to characterize commercial vessels and
identify how many of each type are powered by Cl and C2 diesel engines. U.S. boat builders
construct a wide variety of commercial vessels. Most of these boat builders are single-
establishment companies and manufacture a limited number of boat designs. A handful of
yards (e.g., Halter Marine) also have the capacity to build ships that would be powered by C3
engines. Most commercial and government boats are manufactured individually or
customized to purchaser's specifications.
U.S. boatyards build boats primarily used on inland and coastal waterways between
U.S. ports. This is because cargo vessels on these routes must satisfy Jones Act requirements
(U.S. Department of Transportation, 1998)(Section 27 of the Merchant Marine Act of 1920)
that any vessel transporting merchandise between U.S. ports be built in the U.S., and be
owned and operated by U.S. citizens. For this reason, the U.S. commercial boatbuilding
industry has a protected local market and does not face the intense foreign competition that
recreational boat builders or shipbuilders constructing large C3 vessels for international trade
do. Clients include waterways operators (e.g., tugboats and pushboats), offshore petroleum
exploration and drilling companies (e.g., liftboats, crewboats, supply boats), fisheries
companies (e.g., fishing and fish processing boats), industrial companies, (e.g., cable-laying
boats), and research organizations (e.g., oceanographic research vessels).
The markets for commercial and governmental vessels can be modeled as if they were
competitive. While the Jones Act prohibits foreign manufacture of cargo vessels trading
between U.S. ports and the Passenger Services Act imposes a fee of $200 per passenger on
carriers transporting passengers between U.S. ports unless the vessels are U.S.-built, -owned,
and -operated, most U.S. markets for commercial vessels have relatively low barriers to entry
and exit. There are a significant number of U.S. firms in each market segment, and they
compete for both government and commercial contracts.
For the commercial boat market, we collected much of the background information in
T7
a separate report. Although the objective of that report was to develop inputs for emissions
inventory modeling, the report provides a general characterization of commercial vessels, and
estimates both Cl and C2 vessel counts for various applications. This report adopts the same
commercial/governmental vessel categories and definitions.
1.1.3.4.1 Tug and Towboats
Towboats, also known as tugboats, include boats with rounded bows used for pulling
(towboats) and boats with square bows for pushing barges, known as pushboats. Towboats
that pull or push barges are referred to as line-haul boats, and are the largest category of
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Industry Characterization
towboats. Specialized towboats may also be used for maneuvering ships in harbors, channel
dredging, and construction activities. Towboats vary widely in size and configuration,
ranging from small harbor tugs less than 30 feet in length to large ocean-going tugs over 100
feet.
Data from WorkBoat Magazine's annual construction survey are shown in Table
1-24.28 Participating in this survey is voluntary, and only 56 of more than 500 companies that
build commercial boats and ships responded. The voluntary nature of the survey may result
in some selection bias such that the respondents are not fully representative of the
nonrespondents. This effect may be relatively stable over time, however, so that trends in the
data may be indicative of trends in the industry as a whole.
Table 1-24 shows that the number of towboats (including towboats, pushboats, tugs,
and AHTS) in production increased from 39 in 2003 to 57 in 2004, and 73 in 2005. The
Category 2 Vessel Census estimated that 3,164 of 4,337 towboats in existing databases had
Cl engines.29 Thus, it is likely that the majority of the newbuilt towboats are also powered by
Cl engines. According to the Vessel Census, the majority of these towboats operate in the
U.S. Gulf and U.S. Inland areas.
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Regulatory Impact Analysis
Table 1-24 U.S. Commercial Boat Orders, 1993,1994,1997 and 2003,2004,2005
Vessel Type
Number of survey respondents
Casino/gaming
Passenger (dive, dinner,
excursion, ferries, sightseeing,
water taxi, charter)
Crew, crew/supply pilot,
personnel launch
Supply/service
Liftboat, utility
Pushboat, towboat, tug
Fire, rescue
Boom, spill response
Small craft (assorted), tender
Patrol (military, nonmilitary)
Other military
Others
Total number of boats
Number of Boats Produced
1993
85
34
102
27"
26b
28
60
44d
99f
26
446
1994
83
27
95
41
5
60
5
33
U4e
89
33
512"
1997
84
6
68
44
81
34
88C
7
38
38
48
79
38
569
2003
40
44
17
37
5
39
2
4
17
74
27
110g
376
2004
46
31
31
25
7
57
12
10
7
69
6
149
405
2005
56
40
18
29
8
73
2
6
14
92
24
155
460
Notes:
a Supply boats were consolidated with crew/supply boats and pilot boats.
General workboats were consolidated with utility boats in the 1993 survey.
c AHTSs were consolidated with pushboats, towboats, and tugs.
Research and survey boats were consolidated with tenders in the. 1993 survey and in the table for 2004 and
2005.
e Research, survey, and utility boats were consolidated with the assorted small craft and tenders in the 1994
survey.
Fireboats were consolidated with the patrol boats in the 1993 survey.
g The total number of "other" boats in included nonself-propelled vessels (2003^2 vessels, 2004-92 vessels,
2005-80 vessels).
The total number of boats in 1994 did not include the 111 RIBS, skiffs, or small utility, or the 26 support,
minehunter, or landing craft reported.
1.1.3.4.1.1 Supply of Tugs and Towboats
The majority of towboats are manufactured individually according to buyer
specifications. Some of the smallest ones may be serially produced. Towboats are durable,
all but the smallest are made of steel, and have relatively large engines for their dimensions.
Commercial shipyards and boatyards building towboats use a variety of manufacturing
processes, including assembly, metal finishing operations, welding, abrasive blasting,
painting, and the use of engines for crane operation and boilers. The typical ship construction
process begins with steel plate material. The steel is formed into shapes, abrasively cleaned
(blasted), and then coated with a preconstruction primer for corrosion protection. This is
usually done indoors at the bigger shipyards and most facilities have automated these steps.
Using the preformed steel plates, small subassemblies are then constructed and again a primer
coat is applied. Larger subassemblies are similarly put together and primed to protect the
1-34
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Industry Characterization
steel substrate material. At some point in the construction, components are moved outdoors
to work areas adjacent to the dry dock. Final assembly and engine installation are done at the
drydock.
Based on statistics for the shipbuilding NAICS code, NAICS 336611, materials
account for more than 50 percent of the production costs, and labor for approximately 40
percent. Energy costs, investment in capital equipment, rental payments, and business
services all account for smaller shares of total value of shipments.
1.1.3.4.1.2 Demand for Tugs and Towboats
Towboats are purchased by towing companies that move cargo on barges on coastal
routes or on the nation's rivers. According to the American Waterways Operators (AWO),
the tugboat, towboat, and barge industry include more than 4000 operating tugs/towboats and
more than 27,000 barges. These vessels move more than 800 million tons of raw materials
and finished goods each year, including more than 20 percent of the nation's coal, more than
60 percent of the nation's grain exports, and most of New England's home heating oil and
gasoline.30 In addition to commodity transportation, tugs are needed within harbors to
maneuver ships to and from their berths, and to assist with bunkering and lightering. The
demand for towboats is thus derived from the demand for commodity transportation services,
which in turn is derived from the demand for the commodities being transported. According
to the AWO, mandated replacement of single hulled barges with double hulled barges in the
oils transportation sector will result in some replacement of the towing vessel fleet as larger
tugs are required to move heavier barges. Further, the harbor tug fleet will continue to be
modernized to include alternatives to conventional tugs for shipdocking and tanker escort
services. In general, the size of the tow and tug fleet is shrinking somewhat, but industry
capacity is increasing as older vessels are being replaced with larger, more powerful vessels.31
1.1.3.4.2 Commercial Fishing Vessels
Commercial fishing vessels are dedicated to procuring fish for market and may be
distinguished by whether they tow nets or are engaged in "hook and line" fishing, or are
multipurpose vessels that support a variety of fishing activities. Fishing vessels vary widely
in size and configuration. Smaller fishing vessels may be serially produced using fiberglass,
similar to recreational boats. Larger fishing vessels are generally built individually to buyer's
specifications. The largest fishing vessels also serve as factory ships with the capacity to sort,
clean, gut, and freeze large quantities offish.
The Vessel Census, based on the Coast Guard's Merchant Vessels of the U. S.
(MVUS) database, estimates that there are more than 30,000 commercial fishing vessels
operating in the U.S., with the largest number being in Alaska, followed by Washington and
Texas. Other states with large numbers of commercial fishing vessels include California,
Florida, Louisiana, and Maine. Of the roughly 30,000 commercial fishing vessels identified,
8,130 are listed as definitely Cl and another 21,300 are characterized by the report's authors
as probably Cl.32 If accurate, this means that all but 700 or so commercial fishing vessels are
powered by Cl engines, and that the remaining 700 are powered by C2 engines. The C2
vessel census suggests that the actual number of C2 powered fishing vessels may be less than
1-35
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Regulatory Impact Analysis
half this number.33 Less than 1 percent of commercial fishing vessels were identified as
gasoline-powered.
Given that the vast majority of commercial fishing vessels are powered by Cl engines,
it seems reasonable to assume that the majority of these vessels are also similar to recreational
vessels in construction. Small commercial fishing vessels must be able to travel rapidly to
and from fishing grounds given that their operations have them going to fishing grounds and
returning to port each day. Thus, many of these vessels have fiberglass hulls and are designed
for planning operation, much like recreational vessels.
1.1.3.4.2.1 Supply of Commercial Fishing Vessels
Smaller commercial fishing vessels are generally produced using fiberglass with a
production method similar to that used for recreational boats. Mid-size fishing boats may be
made of fiberglass, aluminum, or steel, and are likely produced individually to buyers'
specifications. The largest fishing boats, factory ships, are produced individually at shipyards
and a few exceed the 400 foot length that is covered by this profile. Serial and individual
production methods are described above.
1.1.3.4.2.2 Demand for Commercial Fishing Vessels
Commercial fishing boats are inputs into the production offish for sale to consumers,
restaurants, retailers, and processors. Reduced catch in many of the nations' fisheries has
resulted in lower returns for fishermen, and thus in a declining number of commercial
fisherman and declining demand for commercial fishing vessels. This decline is projected to
continue.34 To the extent that governmental efforts to replenish stocks and increase catch are
successful, some increase in the number of commercial fishermen and fishing boats may
occur in the future.
1.1.3.4.3 Patrol Vessels
Patrol boats such as Coast Guard vessels (government, Department of Homeland
Security), include small boats used by harbor police and other law enforcement agency
patrols, as well as larger vessels such as cutters. Small boats used by the Coast Guard include
approximately 1,400 boats ranging from 12 to 64 feet, which operate close to shore. Coast
Guard cutters are at least 65 feet in length, and range up to more than 400 feet in length. The
Vessel Census identified 158 of 235 cutters that were powered by C2 engines.35 The smaller
boats operated by the Coast Guard were determined to be powered by Cl engines. Fast
pursuit boats may be powered by gasoline engines. The majority of patrol boats not operated
by the Coast Guard are relatively small and thus most likely powered by Cl engines, or SI
outboards for the smallest patrol boats.
1.1.3.4.3.1 Supply of Patrol Boats
Patrol boats are generally manufactured from aluminum (two major manufacturers of
patrol boats, Seaark Marine and SAFE Boats, Inc., both manufacture aluminum boats in large
numbers). Other aluminum boatbuilders with government work, including military as well as
state and local agencies, include Kvichak Marine, Northwind Marine, Rozema, All American
1-36
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Industry Characterization
Marine, ACB, Almar, Munson and Workskiff. While their designs can be customized, these
aluminum boats are largely serially produced. Significant inputs include aluminum, engines,
and labor. Some small patrol boats are inflatable, with reinforced rigid hulls made of steel.
Larger patrol boats such as Coast Guard cutters are made of steel.
1.1.3.4.3.2 Demand for Patrol Boats
Government agencies, including the Coast Guard, the Military, the Army Corps of
Engineers, as well as harbor police and municipalities are the major purchasers of patrol
boats. The need to increase vigilance along our coasts and in our harbors since the September
11 attacks has led to a tremendous increase in demand for Coast Guard patrol boats, which is
likely to continue to be strong for several more years as the fleet is built up.36 The Workboat
Construction Survey shows that contracts have risen from 48 in 1997 to 92 in 2005.
1.1.3.4.4 Passenger Vessels
Passenger vessels powered by Cl or C2 diesel engines include ferries, excursion
boats, and water taxis. Ferries are self-propelled vessels that carry passengers from one
location to another, either with or without their automobiles. Ferries may be owned by states
or private companies, and generally operate over set routes according to regular schedules.
Water taxis are generally smaller than ferries and operate on a for-hire basis. The Vessel
Census studied ferries, and identified 106 that were powered by C2 engines and 508 powered
by Cl engines. Water taxis are generally powered by spark-ignition (SI) engines, although
some may be powered by Cl inboard engines. Excursion boats are generally powered by Cl
engines, although some of the larger ones that approach small cruise ships in size, are
powered by C2 engines.
1.1.3.4.4.1 Supply of Passenger Vessels
Passenger vessels may be made of aluminum or steel. For example, Derektor
Shipyards had orders to deliver three aluminum ferries ranging from a 92 foot high speed
catamaran ferry to a passenger/vehicle ferry that was 239 feet long. Two other companies had
orders for large steel ferries, including two 310-foot Staten Island Ferries. Larger ferries and
other passenger vessels are likely powered by C2 engines, while smaller ones are likely Cl or
even SI outboard or sterndrive for the smallest and lightest ones.
1.1.3.4.4.2 Demand for Passenger Vessels
Ferries and water taxis are needed for transportation services, and are generally used
in urban areas. Other types of passenger vessels, including excursion boats, dinner boats, and
floating casinos, are needed for recreational purposes. Some of these, such as whale watching
boats, are very small; others such as floating casinos and some excursion boats may be more
than 100 feet in length. Workboat's 2005 Construction Survey showed orders for 19 dinner,
excursion, or sightseeing boats and also for 19 ferries or water taxis. Both types of passenger
boats are likely to respond to cyclical patterns in the economy, as both commuting and
recreation increase when the economy is strong.
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Regulatory Impact Analysis
1.1.3.4.5 Research Vessels
Research vessels include vessels equipped with scientific monitoring equipment used
to track wildlife, map geological formations, monitor coastal water quality, measure
meteorological conditions, and conduct other scientific investigations. They vary widely in
size and complexity and may be made of aluminum, fiberglass, or steel. They may be
powered by SI outboard engines, Cl, or C2 inboard engines, depending on their size. While
they may be built on a standard hull design, the fittings are highly individualized based on
their task, and may be technically complex. Of 12 research vessels reported in the Workboat
2005 Construction Survey, most are made of aluminum and are less than 80 feet in length.
Two are made of steel and are about 150 to 200 feet in length. Of the purchasers listed, three
of the vessels were ordered by the National Oceanic and Atmospheric Administration
(NOAA) and one by a university. The instruments and other scientific equipment are a
special and potentially expensive cost element for these vessels. Demand for the vessels is a
function of demand for the research products that they support.
1.1.3.4.6 Offshore Support Vessels
Offshore support vessels (OSVs) include a variety of vessels used to construct,
operate, maintain, and service offshore oil platforms. Of the categories listed in Table 1-24,
crew, crew/supply, personnel, supply/service and liftboat/utility vessels are all vessel types
that support the offshore oil industry. This is a diverse category, including a wide range of
sizes, materials, and configurations. Platform supply boats and crew/supply boats tend to be
over 150 feet in length and may be made of steel or aluminum. Lift boats tend to be about
150 feet in length and made of steel. OSVs listed in Workboat's 2005 Construction Survey
range from 145 feet to 280 feet and are made of steel. At the other end of the spectrum are
smaller aluminum crew and utility boats. Most offshore oil activity in the U.S. is in the Gulf
of Mexico; thus, most offshore support vessels operate there.
Demand for offshore support vessels depends largely on the status of the offshore oil
industry. Changes in that industry over the past 15 years have resulted in reduced numbers of
rigs farther from shore. Thus, while fewer support vessels may be needed, they may be
required to be larger and more seaworthy. The Gulf Coast hurricanes of 2005 had a
substantial impact on the offshore oil industry and offshore support vessels. Many platforms
and offshore support vessels suffered damage due to the storms. Demand for offshore support
vessels has increased drastically, and day rates have more than doubled. This will likely
result in an increase in construction of offshore support vessels in the next few years, relative
to recent years.
Table 1-25 gives a summary of the types of boats currently under contract to be built
at U.S. boatyards based on information taken from the Marine Log website and Workboat's
2005 Construction Survey, using the commercial boat categories described above.37
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Industry Characterization
Table 1-25 Boats Under Construction by Type and Client, December 2005 Contracts
Type of Boat
Tow/Tug
Fishing
Coast Guard
Ferry
Cargo
Research
Offshore Support
Great Lake/Others
Military
Total
Commercial Clients
31
0
0
19
75
1
31
3
0
140
Government Clients
7
1
92
2
0
2
0
1
64
169
Total
38
1
92
21
75
3
31
4
64
329
1.1.3.5 Industry Organization
This section examines the organization of the boat building industry, including
characterizing firms in the industry, and examining market structure.
1.1.3.5.1 Location and Number of Vessel Manufacturers
There are several hundred yards that build many different types of boats powered with
small engines (<37 kW) as well as larger Cl and C2 engines. Boat builders are located along
all coasts and major inland waterways of the United States. Figure 1-1-6 shows the
geographic distribution of boat builders in the United States. A majority of them are located
in the Gulf Coast, the Northeast, and the West Coast, and account for approximately 30
percent, 25 percent, and 26 percent of the boatbuilding industry, respectively. Collectively,
these three regions represent 345 boat builders, including 128 builders on the Gulf Coast, 107
in the Northeast and 110 on the West Coast - 80 percent of all companies in the 1998 Boat
builder Database.
Figure 1-1-6 Major Boatbuilding Regions of the United States
Gr-af
uIJi Atlantic '0V.
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Regulatory Impact Analysis
1.1.3.5.2 Firm Characteristics
Table 1-26 summarizes company financial data for companies that produce
commercial vessels powered by Cl and C2 engines.21'22'23 The available data capture total
company employment and sales figures including any subsidiaries and operations including
boat repair that may not be related to boatbuilding. Because many companies may produce
boats powered by both SI and CI engines, or may produce larger vessels powered by C3
engines, not all of the boatbuilding employment and revenues listed in Table 1-26 are
associated with vessels powered by Cl and C2 engines.
Table 1-26 Employment Distribution of Companies that Build Commercial and Government Boats
Employment Range Number of Firms Revenue Range (SMillions)
100 or fewer 29 0.15-7.0
101-250 12 12.0-50.0
251-500 5 11.0-30.9
501-1,000 3 42.0-73.0
1,001 or more 13 82.0-29.9
Total number of firms 62
Almost all companies that produce commercial or governmental vessels powered by
Cl or C2 engines are classified under NAICS 336611. Of an estimated 589 firms in that
NAICS code, company names, employment, and sales data were obtained for only 62. Using
the Small Business Administration's small business criterion for NAICS 336611 (1,000
employees), 49 of the 62 (79 percent) of the companies for which data were obtained would
qualify as small entities.
1.1.3.5.3 Markets and Trends in Commercial Vessel Manufacturing
Markets for commercial and governmental vessels can be modeled as competitive.
While products are differentiated rather than homogeneous, there are many yards that produce
similar types of vessels, and compete for both commercial and governmental contracts.
Barriers to entry and exit are relatively low, at least domestically. For commercial cargo
vessels working between U.S. ports, foreign competition is limited by the Jones Act.
Similarly, passenger vessels plying exclusively domestic routes are constrained by the U.S.
Passenger Services Act. Nevertheless, because the technology and materials for boat building
are widely available, costs of entry into the market are fully recoverable, and barriers to entry
and exit are thus low which results in domestic commercial boat manufacturers facing
markets that are contestable and therefore competitive.
The U.S. boatbuilding industry is currently influenced by several key factors. These
factors suggest a continued increase in the number of commercial boats built in the United
States:
Increasing demand for the T-class vessels. (The U.S. Coast Guard defines T-class
vessels as boats not designed to see the open ocean, such as cruise boats, dinner and
gambling boats, crew boats in the Gulf of Mexico, and off-shore vessels);
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Industry Characterization
Increasing demand for offshore supply vessels to repair and service offshore oil rigs,
including repairing or replacing rigs and OSVs damaged or destroyed by Gulf Coast
hurricanes in 2005;
Increasing demand for oil (e.g., drillships and semisubmersible rigs);
Expansion of demand for casino boats;
Decisions by leading boat builders to reopen facilities and expand their labor forces
provide strong indications that they anticipate continued growth in the market for
commercial and governmental vessels. An increase in demand for new boats will
mean more business for the commercial U.S. boatbuilding industry, as foreign builders
are ineligible to build for segments of this market. Some of the larger boat builders in
the United States also build boats for foreign owners/operators, particularly for foreign
militaries. As noted in the table summarizing current shipyard/boatyard contracts,
there are at least three yards doing work with foreign governments (e.g., Egypt and
Oman)
In summary, U.S. boat builders are cautiously optimistic about the future because
almost every segment of the U.S. flag fleet is facing significant replacement requirements.
The commercial boat builders are expected to continue to be a major consumer of marine
diesel engines.
1.1.4 Vessel Operators
The U.S. Economic Census provides an overview of the Water Transportation
subsector and the subsectors which provide water transporation for passengers and cargo
using water crafts such as ships, barges, and boats. While there is no database that directly
links these firms to type of Commercial Cl and C2 marine diesel engines they use in their
businesses, the survey data does provide a very helpful overview of the industry where these
engines predominate. Information is organized by the North American Industry Classification
System (NAICS) Codes and the data was gathered in 2002 Economic Census.
The Water Transporation Subsector is composed of two industry groups: (1) one for
deep sea, coastal, and Great Lakes- NAICS 4831; and (2) one for inland water transportation-
NAICS 4832. This split typically reflects the difference in equipment used. Scenic and
sightseeing water transportation services are not included in this subsector but rather are taken
account of in subsector 487, Scenic and Sightseeing Transportation. Harbor Tug Services are
included in subsector 488330 and Fishing is captured in subsector 1141. Table 1-27 provides
the breakdown for each of the subsectors.
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Regulatory Impact Analysis
Table 1-27 Industry Subsectors with Employment Level defining Small Business Standards
NAICS
CODE
483111
483112
483113
483114
4832112
4832121
1141
487
488330
Industry
Deep Sea
Freight
Passenger
Coastal & Great
Lakes
Freight
Passenger
Inland
Freight (Towing)
Passenger (Ferry)
Fishing
Scenic &
Sightseeing
Harbor Tugs
Service
TOTAL
Total Firms
235
77
443
124
310
250
2084
1609
657
5789
Approximately 5800 firms are represented in the Water Transporation subsector and
affiliated sectors which purchase and use commercial vessels propelled by either Cl or C2
marine diesel engines. U.S. economic census data reveals that in 2002 about 65 percent of
these firms had annual revenues of less than $1 million while 87 percent had revenues less
than $5 million. In summary, when taking into account all firms in these subsectors about 88
percent of all revenue was generated by 12 percent (-720) of the 5800 firms.
1.2 Locomotive
1.2.1 Introduction
The regulations for locomotives and locomotive engines are expected to directly
impact three industries. These industries are: (1) locomotive and locomotive engine original
equipment manufacturers (OEMs); (2) owners and operators of locomotives (railroads); and
(3) remanufacturers of locomotives and locomotive engines including OEMs, railroads, and
independent remanufacturers. Locomotive manufacturers are companies that make or import
complete "freshly" manufactured locomotives.8 Remanufacturers are companies that certify
kits for remanufactured locomotives.0 A brief overview of these industries follows, along
B Freshly manufactured locomotives are those which are powered by freshly manufactured engines, and contain
fewer than 25 percent previously used parts (weighted by the dollar value of the parts).
c Remanufactured locomotives are locomotives in which all of the power assemblies are replaced with freshly
manufactured (containing no previously used parts) or refurbished power assemblies. Remanufacturing includes
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Industry Characterization
with descriptions of the national economic impact of railroads and current regulations in
effect for railroads.
1.2.2 Current U.S. Emission Regulations
The Agency's 1998 Locomotive Rule (63 FR 18978; April 16, 1998) created a
comprehensive emission control program that subjected manufacturers and railroads
(including all Class I and some small Class II and III railroads) to emission standards, test
procedures and a full compliance program. The unique feature of this program was the
regulation of the engine remanufacturing process, including the remanufacture of locomotives
originally manufactured prior to the effective date of that rulemaking. Regulation of the
remanufacturing process was critical because locomotives are generally remanufactured four
to eight times during their total service lives of approximately 40+ years. Locomotives
powered by an external source of electricity, historic steam-powered locomotives, and
locomotives freshly manufactured prior to 1973 were not covered by the 1998 regulations.
Three separate sets of emission standards (Tiers) were adopted in the 1998
rulemaking, with applicability of the standards dependent on the date a locomotive was
manufactured. The first set of standards (Tier 0) applied to locomotives and locomotive
engines originally manufactured from 1973 through 2001. The second set of standards (Tier
1) applied to locomotives and locomotive engines originally manufactured from 2002 to 2004,
and the final set of standards (Tier 2) applied to locomotives and locomotive engines
originally manufactured in 2005 or later. All of these standards must be met when a
locomotive is "freshly manufactured" and at each subsequent remanufacture. The emission
standards set in 1998 for line-haul and switch duty-cycles are shown in Table 1-28.
Table 1-28 Maximum Permissible NOX, CO, HC, and PM Rates by Tier
(g/bhp/hr)
NOX
CO
HC
PM
Tier 0 Line-
Haul Duty-
Cycle
9.5
5.0
1.00
0.60
TierO
Switch
Duty-Cycle
14.0
8.0
2.10
0.72
Tier 1 Line-
Haul Duty-
Cycle
7.4
2.2
0.55
0.45
Tierl
Switch
Duty-Cycle
11.0
2.5
1.20
0.54
Tier 2 Line-
Haul Duty-
Cycle
5.5
1.5
0.30
0.20
Tier 2 Switch
Duty -Cycle
8.1
2.4
0.60
0.24
In addition to the separate sets of emissions standards established by the 1998
rulemaking, additional requirements for compliance with these emission standards were
promulgated, and are described in 40 CFR Part 92. These provisions apply to manufacturers,
remanufacturers, and owners and operators of locomotives, and locomotive engines
manufactured on or after January 1, 1973. The three most significant requirements for
the following: replacing an engine, upgrading an engine, and converting an engine to enable it to operate using a
fuel other than it was originally manufactured to use.
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Regulatory Impact Analysis
railroads relate to: 1) remanufacture of locomotives 2) maintenance of locomotives, and 3)
testing of locomotives.
The regulations require that post-1972 locomotives be covered by an EPA Certificate
of Conformity when they are remanufactured. (See Applicability of Locomotive Emission
Standards, EPA420-F-99-037, for more information about which locomotives are covered by
these regulations). The certificate certifies that the locomotive was remanufactured in a
specific manner such that it complies with EPA's emission standards. Each certificate covers
a group of similar locomotives that is referred to as an "engine family." A railroad may apply
directly to EPA to obtain a certificate, or may rely on a supplier or remanufacturer that has
obtained a certificate. The company that obtains the certificate is referred to as the certificate
holder, and is responsible for ensuring that the locomotive complies with EPA's emission
standards.
The regulations also require that railroads perform emission-related maintenance on
all regulated locomotives. This requirement is described in 40 CFR 92.1004. Emission-
related maintenance is specified by the certificate holder and approved by EPA at the time of
certification. The certificate holder is required to provide the emission-related maintenance
instructions to the railroads. Emission-related maintenance generally includes regular
replacement of fuel injectors and air filters, as well as the use of fuels and lubricants meeting
the specifications of the certificate holder. In most cases, it will also include frequent
inspection of other emission-related components to ensure that they are functioning properly.
This section of the regulations also prohibits any maintenance that would reasonably be
expected to adversely affect the emission performance of the locomotive.
EPA also established two testing programs to monitor the in-use emissions of
locomotives. The fist program is run by the certificate holders, the second program is run by
the Class I freight railroads and is described in 40 CFR 92.1003. Under this program, which
began on January 1, 2005, each Class I freight railroad is required to test 0.15 percent of its
locomotive fleet each year using the specified EPA test procedure (40 CFR Part 92 Subpart
B). This railroad testing program focuses on the locomotives in the fleet that have exceeded
their useful life values. (Useful life values are defined as the period specified in a certificate
during which the locomotive is designed to comply with the standards; it is generally
equivalent to 750,000 miles or more.)
1.2.2.1 Certification
Locomotive manufacturers must produce compliant locomotives, and they must be
certified. In order for a locomotive to be certified, a company must certify the engine together
with the locomotive. An engine manufacturer can certify, but it must certify the complete
locomotive. Railroads must purchase all new locomotives with a valid certificate of
conformity, and when remanufacturing a locomotive must have a valid certificate of
conformity. However, small railroads are generally provided an exemption for the existing
uncertified locomotives in their fleet, as well as any uncertified locomotives that they may
purchase from other railroads in the future.
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Industry Characterization
1.2.3 Supply: Locomotive Manufacturing and Remanufacturing
1.2.3.1 Locomotive Manufacturing
1.2.3.1.1 Types of Locomotives
Locomotives generally fall into three broad categories based on their intended use:
switcher, passenger, and line-haul locomotives. Switch locomotives, typically 2000 hp or
less, are the least powerful locomotives, and are used in freight yards to assemble and
disassemble trains, or for short hauls of trains that are made up of only a few cars. Some
larger switchers can be rated as high as 2300 hp. Passenger locomotives are powered by
engines of approximately 3000 hp, with high-speed electric passenger locomotives powered
by engines with 6000 hp or more. Freight or line-haul locomotives are used to power freight
train operations over long distances. Older line-haul locomotives are typically powered by
engines with 2000-3000 hp, while newer line-haul locomotives are powered by engines with
3500-5000 hp. In some cases, older line-haul locomotives (especially those with lower
powered engines) are used in switch applications. The development of line-haul locomotives
with even higher horsepower ratings, such as 6000 hp or more continues, but it is not clear if
this will be the future of locomotive engines.
1.2.3.1.2 Type of Propulsion Systems
Locomotives can be subdivided into three general groups on the basis of the source of
energy powering the locomotive: 1) "all-electric" 2) "engine-powered" 3) "hybrid". In the
"all-electric" group, externally generated electrical energy is supplied to the locomotive by
means of overhead lines, a third rail that runs between or alongside the rails, or an onboard
electric storage device such as a battery. Locomotives of this type have existed for over 125
years.38 An example of this type of locomotive is commonly seen on commuter trains.
Emission control requirements for all-electric locomotives would be achieved at the point of
electrical power generation, and thus are not included in this rulemaking.
In the "engine-powered" group of locomotives, fuel (usually diesel in the U.S.,
although natural gas options are also being pursued) is carried on the locomotive. The energy
contained in the fuel is converted to power by burning the fuel in the locomotive engine. A
small portion of the engine output power is normally used directly to drive an air compressor
to provide brakes for the locomotive and the train. However, the vast majority of the output
power from the engine is converted to electrical energy in an alternator or generator which is
directly connected to the engine. This electrical energy is transmitted to electric motors
(traction motors) connected directly to the drive wheels of the locomotive for propulsion, as
well as to motors which drive the cooling fans, pumps, etc., necessary for operation of the
engine and the locomotive.0 In the case of passenger locomotives, electrical energy is also
supplied to the train's coaches to provide heat, air conditioning, lights, etc. (i.e., "hotel
D Essentially all "engine powered" locomotives used in the U.S. employ a diesel engine and the electrical drive
system described above. The term "diesel-electric" has therefore become the most common terminology for
these locomotives.
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Regulatory Impact Analysis
power"). In some passenger trains, electrical energy required for the operation of the
passenger coaches is supplied by an auxiliary engine mounted either on the locomotive or
under the floor of a passenger car.
The third category, "hybrid" is a combination of the "electric" and "engine-powered"
groups, and was first developed and used in the 1920's, although at the time it wasn't very
successful due to a lag in battery technology. Today's hybrid locomotive technology is
considered to be "battery dominant" and uses a small diesel engine and generator to charge a
battery pack; the battery pack then supplies energy on demand to the traction motors.39 The
engine can be 250-640 hp (200-480 kW) and typically operates at a constant speed, which
allows the engine to be optimized for efficiency. Further fuel savings are achieved by running
this engine only during times when it is needed to generate power to keep the batteries at a
certain charge level.40 This technology is currently only available for switcher locomotives,
although it is being developed for use on line-haul locomotives.41
1.2.3.1.3 Locomotive Design Features and Operation
1.2.3.1.3.1 Sizing Constraints
Similar to the variation in horsepower, locomotive size determines the work it may
perform. Switch locomotives tend to be about 40 to 55 feet long, while line-haul locomotives
are typically 60 to 76 feet long. Locomotive length is roughly correlated with engine size,
and thus the difference in length has become more significant as locomotive engines have
become larger and more powerful. Locomotive length is also related to the number of axles
found on a locomotive. In the past, a typical locomotive had four axles (two trucks with two
axles each). While there still are a large number of four-axle locomotives in service, all
newly manufactured line-haul locomotives have six axles (two trucks with three axles each).
There are two primary advantages of having more axles on the locomotive. First, additional
axles allow locomotives to be heavier without increasing the load on each individual axle (and
thus the load on the rail). Second, six-axle locomotives typically have greater tractive power
at low speeds, which can be critical when climbing steep grades. The use of six-axles on a
locomotive does increase its overall length, and continues to lead to the discontinuation of the
practice of converting old line-haul locomotives into switch locomotives, as these larger six-
axle locomotives are too long to be practical in most switch applications.
1.2.3.1.3.2 Operational Characteristics
One unique feature of locomotives that makes them different than other currently
regulated mobile sources is the way power is transferred from the engine to the wheels. Most
mobile sources utilize mechanical means (i.e., a transmission) to transfer energy from the
engine to the wheels (or other point where the power is applied). Because there is a
mechanical connection between the road, vehicle engine and the wheels, the relationship
between engine rotational speed and vehicle speed is mechanically dictated by the gear ratios
in the transmission and final drive (e.g., the differential and rear axle). This results in engine
operation which is very transient in nature, with respect to changes in both speed and load. In
contrast, locomotive engines are typically connected to an electrical alternator or generator to
convert the mechanical energy to electricity. As noted above, this electricity is then used to
1-46
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Industry Characterization
power traction motors which turn the wheels. The effect of this arrangement is that a
locomotive engine can be operated at a desired power output and corresponding engine speed
without being constrained by vehicle speed. The range of possible combinations of
locomotive speed and engine power vary from a locomotive speed approaching zero with the
engine at rated power and speed, to the locomotive at maximum speed and the engine at idle
speed producing no propulsion power. This lack of a direct, mechanical connection between
the engine and the wheels allows the engine to operate in an essentially steady-state mode, in
a number of discrete power settings, or notches. Notches are throttle positions that load the
engine at different power levels. There are typically eight power notches on a locomotive, as
well as idle positions.
Dynamic braking is another unique feature of locomotives setting them apart from
other mobile sources. Dynamic braking is especially important given the traction problems
that locomotives must overcome. Locomotives generate an enormous amount of power that
can be applied to the wheels when they start to roll, however, the use of steel wheels (which
provide less rolling resistance) also make it difficult to start moving a locomotive. On straight
sections of rail, some locomotives have a built-in system that will put sand on the rails in
order to increase traction. The ridges on the sides of the wheels provide traction during
cornering to keep the wheels on the rails, and some locomotives are equipped with an oil
system that puts oil on the sides of the rails to reduce friction on the sides of the wheels during
turns and cornering.
In dynamic braking the traction motors act as generators, where the generated power
is dissipated as heat through an electric resistance grid; this feature decreases overall braking
distance and wear on the wheels. While the engine is not generating motive power (i.e.,
power to propel the locomotive, also known as tractive power) in the dynamic brake mode, it
is generating power to operate resistance grid cooling fans. The power generated from
braking then heats up these resistance grids and is dissipated into the air as heat. As such, the
engine is operating in a power mode that is different than the power notches or idle settings
discussed above. While most diesel-electric locomotives have a dynamic braking mode, some
do not (generally switch locomotives). The potential energy that could be recovered during
dynamic braking and utilized by the locomotive is one area researchers are focusing on to
increase locomotive efficiency. GE noted that "the energy dissipated in braking a 207-ton
locomotive during the course of one year is enough to power 160 households for that year."41
However, it is very difficult to capture and store this energy. The power generated from
dynamic breaking is instantaneous and high enough that it cannot be effectively used by the
locomotive at the time it is generated. If the energy could be stored in batteries, or a
mechanical device such as a flywheel, tremendous fuel savings could be gained, and therefore
development of these types of systems continues.42'43
Hotel power or "Head End Power" (HEP) is power used to operate lighting, heating,
ventilation and air conditioning, and all other electrical needs of the crew and passengers alike
on locomotives equipped with this feature. This power can be provided by the lead
locomotive or by an additional engine, and is distributed to the rest of the cars as needed. The
design of locomotives for use in passenger train service (without additional engines used to
provide HEP) provides for a locomotive to be operated in either of two distinct modes. In one
mode, the locomotive engine provides only propulsion power for the train. In this mode, the
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Regulatory Impact Analysis
engine speed changes with changes in power output, resulting in operation similar to freight
locomotives. In the second mode, the locomotive engine supplies HEP to the passenger cars,
in addition to providing propulsion power for the train. Hotel power provided to the
passenger cars can amount to as much as 800 kW (1,070 hp). In contrast to operation in the
non-hotel power mode, the engine speed remains constant with changes occurring in power
output when operating in hotel power mode. Thus, the two modes of operation utilize
different speed and load points to generate similar propulsion power. These differences in
speed and load points mean that locomotive engines will have different emissions
characteristics when operating in hotel power mode than when operating in non-hotel power
mode.
1.2.3.1.3.3 Design Characteristics
In 1909 Rudolph Diesel helped construct the first diesel locomotive, and in 1918 the
first diesel-electric switch locomotives were put into service.44 By the 1950's diesel-electric
locomotives had replaced steam powered locomotives because they required less fuel,
maintenance, and man-power.45 Locomotives use diesel engines because they are much more
efficient, reliable, and can generate tremendous power. The diesel engine is one of the most
efficient transportation powerplant available today. Thermal efficiency of locomotive diesel
engines is 40% or higher, which results from high power density (via high turbocharger
boost), high turbocharger efficiencies, direct fuel injection with electronic timing control, high
compression ratios, and low thermal and mechanical losses. Many locomotive engines
achieve the equivalent of one million miles before overhaul.43 Durability is critical as a
locomotive breakdown on the tracks can bottleneck the entire system; these failures are very
costly to the railroads because of the importance of timeliness to their customers, and the
difficulty in getting replacement locomotives to the location of the failure. The trend toward
higher power locomotives is naturally resulting in a trend of fewer locomotives per train,
thereby increasing the likelihood that a train would become immobilized by the failure of a
single locomotive.
Another unique design feature of locomotives is the design of the engine cooling
system and procedures used to control engine coolant temperature. Normal practice in
locomotive design has been to mount the radiator on the roof of the locomotive and not to use
a thermostat. Control of coolant temperature is achieved by controlling the heat rejection rate
at the radiator. The rate of heat rejection at the radiator can be controlled by means such as
turning fans on and off or employing a variable speed fan drive, or by controlling the amount
of coolant flow to the radiator (using non-thermostat controls). A related point of difference
between road vehicle and locomotive engine cooling systems is that antifreeze is not generally
used in locomotives. Locomotives use water, not antifreeze to cool their engines because
water is much more efficient at removing heat. Using antifreeze would require a cooling
system approximately 20% larger than the current design (which holds approximately 450
gallons of water).46 The size of a locomotive is limited by the existing track and tunnel
infrastructure which restricts the height, width, and length of a locomotive. Locomotives
usually run in consists (groups) which means that any locomotive following the lead
locomotive will not have the same effective cooling as the one in front because the air it
encounters will be warmer. The practice of "following" creates additional cooling problems,
especially in tunnels which call for special design considerations.
1-48
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Industry Characterization
The final unique design feature noted here is the manner in which new designs and
design changes are developed. The initial design of any new locomotive model and the
production of prototype models are done in much the same manner as is the case with other
mobile sources. Locomotive manufacturers have indicated that this process can be expected
to require from 12 to 24 months for significant changes such as those required to comply with
Tier 0 standards. Unlike most other mobile sources, prototype locomotives are typically sold
or leased to their customers (the railroads) for extended field reliability testing. Only after
this testing is completed is the new design/design change certified and placed into normal
production.
1.2.3.2 Line-Haul Manufacturing
1.2.3.2.1 Manufacturers
Locomotives used in the United States are primarily produced by two manufacturers:
Electromotive Diesel (EMD) and General Electric Transportations Systems (GETS). EMD
manufactures its locomotives primarily in London, Ontario and their engines in La Grange,
Illinois. The GETS locomotive manufacturing facilities are located in Erie, Pennsylvania,
while their engine manufacturing facilities are located in Grove City, Pennsylvania. These
manufacturers produce both the locomotive chassis and propulsion engines; they also
remanufacture engines. MotivePower's Wabtec division, headquartered in Wilmerding,
Pennsylvania, has produced some mid-horsepower locomotives suited for commuter or long-
distance service using engines manufactured by Caterpillar, Inc.47 They also manufacture a
switcher locomotive that runs on liquefied natural gas. The Cummins Engine Company, Inc.,
headquartered in Columbus, Indiana, produces V12 and V16 diesel engines for use in
locomotives.48 The EPA has identified four diesel locomotive manufacturers, one of which
can be considered a small business according to SB A guidelines.49 There are also a few
companies such as Steward and Stevenson or Brookville Mining Equipment that manufacture
small switch locomotives (under 700 bhp and not covered by this rulemaking) for use in
mines or other specialized purposes.50
EMD was founded in 1922 and acquired by General Motors in 1930 and subsequently
sold by General Motors in 2005 to the Greenbriar Equity Group and Berkshire Partners, and is
now called Electro-Motive Diesel, Inc. While they primarily manufacture a 2-stroke diesel
locomotive engine, they began manufacturing a 4-stroke engine in 1997. They currently
produce five national models ranging from 3000-6000hp, and offer international models as
well as custom built locomotives. EMD employs approximately 2,600 people and designs,
manufactures, market, sells, and services freight and passenger diesel-electric locomotives
worldwide.51 GE was formed by Thomas Edison who developed his first experimental
electrical locomotive in 1880, GE also built and put into the service the world's first diesel-
electric switcher locomotive in 1924 that remained in service until 1957. GE currently
produces at least five national models, two international models, passenger locomotives, and
is developing a hybrid locomotive. GE's Transportation division employs approximately
8,000 people and also engineers, manufactures, markets and services their diesel locomotive
products worldwide.52
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Regulatory Impact Analysis
1.2.3.2.2 Production
Due to the long total life span of locomotives and their engines, annual replacement
rates of existing locomotives with freshly-manufactured units are very low. Table 1-29
illustrates the historical replacement rates for locomotives in the Class I railroad industry.
Sales of new locomotives have averaged approximately 780 units per year over the last ten
years. This replacement rate indicates a fleet turnover time of about 30 years for Class I
railroads. Fleet turnover is the time required for the locomotive fleet to be entirely composed
of locomotives that were not in service in the applicable base year. Class II and III railroads
generally buy used locomotives from Class I railroads, although occasionally purchase new
switchers or line-haul locomotives.
Table 1-29 Class I New Locomotive Turnover Rates53
Year
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Number of New
Locomotives Installed
928
761
743
889
709
640
710
745
587
1,121
Total Number of
Locomotives in Service
18,812
19,269
19,684
20,261
20,256
20,028
19,745
20,506
20,774
22,015
Percent Turnover
of New
4.9%
3.9%
3.8%
4.4%
3.5%
3.2%
3.6%
3.6%
2.8%
5.1%
1.2.3.2.3 Cost
The cost of a locomotive can vary between $1.5 million to $2.2 million, depending on
the configuration and options installed. Figure 1-1-7 shows data from the AAR's Railroad
Ten-Year Trends 1995-2004 publication. Some of the variation from year to year can be
attributed to differences in features, but it appears the overall trend in the price of AC
locomotives is downward, while DC locomotive pricing remains steady.
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Industry Characterization
Figure 1-1-7 Cost of New Locomotives5
Cost of Diesel-Electric Locomotives
2500000 -,
2000000 -
1500000 -
1000000
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
-de-traction
-ac-traction
1.2.3.3 Switcher Manufacturing
1.2.3.3.1 Manufacturers
The majority of switchers in operation today are former line-haul locomotives that
have been assigned to a yard, and they are usually quite old. This trend will most likely abate
over time because the size and power of most new locomotives can make them unsuitable for
switching operations. While EMD does offer a traditional new switch locomotive, other
companies are offering switchers with alternative power plants (such as hybrid or gen-set
locomotives) that are usually built off of an old switcher platform.
Motive Power, headquartered in Wilmerding, PA offers a switching locomotive fueled
by liquefied natural gas, which they build on cores supplied by a railroad. A core is a
locomotive that is no longer in service which will be completely torn-down and reconfigured
reusing any of its own salvageable parts as well as new parts. Motive Power is a large
company with nearly 5,000 employees; they service other industries such as marine, transit
and power generation. National Railway Equipment Co. (NREC) based in Houma, Louisiana
with facilities also in Illinois manufactures a "gen-set" switcher locomotive (powered by
multiple smaller diesel engines) that is built from the ground up. They employ approximately
150 employees.54 RailPower Technologies is headquartered in Brossard, Quebec but also has
an American office in Erie, Pennsylvania. They employ approximately 100 people, and
manufacture the GreenGoat hybrid yard switcher and are developing a natural gas switcher
locomotive as well. Railpower also uses an old switcher locomotive core to build their
platform on.55
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Regulatory Impact Analysis
1.2.3.3.2 Production
The existing fleet of retired line-haul switcher locomotives turns over very slowly.
However, production of alternative technology switchers is beginning to increase. NREC is
working with Union Pacific Railroad (UP) to build sixty 2,100 hp GS21B gensets equipped
with three four-cycle, six-cylinder, 700hp Cummins QSK-19 engines.56 These switchers are
believed to reduce NOX and PM by 80% and to reduce fuel consumption by up to 16% as
compared to a conventional switcher. UP is also evaluating the GreenGoat hybrid switcher,
which is also expected to reduce fuel consumption by up to 16% and NOX and PM emissions
by 80%. Norfolk Southern has recently ordered two gen-set switchers from from RailPower
in the form of retrofit kits where their own maintenance staff will install this triple-engine
system during a switcher rebuild.57 While new switchers can cost upwards of $1.5 million
dollars, the GreenGoat hybrid switcher can cost as little as $700,000 if a customer supplies a
completely reconditioned GP-9 locomotive.58 Note that the price of these and other switchers
depends on whether or not a core is supplied and what features it will be built with.
1.2.3.3.3 Trends
Remote control locomotives (RCL) have been used in Canada and the U.S. for many
years; however, Class I railroads have recently begun to implement this technology on a wider
scale according to the Federal Railroad Administration (FRA).59 Although RCL technology
is mainly used in switch yards, this type of operation may be applied on line-hauls in the
future. RCL requirements may affect cab design and require that special equipment is built
into future switchers. Another growing trend is the retrofit and use of idle reduction
technology on locomotives to decrease fuel consumption and increase the railroads efficiency,
especially as the cost of fuel continues to increase.60
1.2.3.4 Remanufactured Locomotives
Since most locomotive engines are designed to be remanufactured a number of times,
they generally have extremely durable engine blocks and internal parts. Parts or systems that
experience inherently high wear rates (irrespective of design and materials used) are designed
to be easily replaced so as to limit the time that the unit is out of service for repair or
remanufacture. The prime example of a part that is designed to be readily replaceable on
locomotive engines is the power assembly, which is composed of: pistons, piston rings,
cylinder liners, fuel injectors and controls, fuel injection pump(s) and controls, and valves.
Within the power assemblies, parts such as the cylinder head generally do not experience high
wear rates, and may be reused after being inspected and requalified (i.e. determined to be
within manufacturers specifications). The power assemblies can be remanufactured to bring
them back to as-new condition, or they can be upgraded to incorporate the latest design
configuration for that engine. In addition to the power assemblies, there are numerous other
parts or systems that are also designed to be easily replaced on locomotives.E Engine
E Bottom end components, such as crankshafts and bearings, are often remanufactured only during every other
remanufacture event. Remanufacture events that do not include these bottom end components are sometimes
referred to as "partial remanufactures"
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Industry Characterization
remanufacturing may be performed by the railroad that owns the locomotive, or by the
original manufacturer of the locomotive. Remanufacturing is also performed by companies
that specialize in performing this work.
During its forty-plus year total life span, a locomotive engine could be remanufactured
as many as ten times (although this would not be considered the norm). Locomotive engine
remanufacturing events are thus routine, and are usually part of scheduled maintenance. It is
standard practice for the Class I railroads to remanufacture a line-haul locomotive engine
every four to eight years. Typically newer locomotives, which have very high usage rates, are
remanufactured every four years. Older locomotives are usually remanufactured less
frequently because they are used less within each year. Such remanufacturing is necessary to
ensure the continued proper functioning of the engine. Remanufacturing is performed to
correct losses in power or fuel economy, and to prevent catastrophic failures, which may
cause a railroad line to be blocked by an immobile train.
When a locomotive engine is remanufactured, it receives replacement parts which are
either freshly-manufactured or remanufactured to as-new condition (in terms of their
operation and durability).F This includes the emission-related parts which, if not part of the
basic engine design, are also generally designed to be periodically replaced. The replacement
parts are often updated designs, which are designed to either restore or improve the original
performance of the engine in terms of durability, fuel economy and emissions. Because of a
locomotive engine's long life, a significant overall improvement in the original design of the
parts, and therefore of the engine, is possible over the total life of the unit. Since these
improvements in design usually occur in the power assemblies (i.e., the components where
fuel is burned and where emissions originate), remanufacturing of the engine essentially also
makes the locomotive or locomotive engine a new system in terms of emission performance.
A remanufactured locomotive would therefore be like-new in terms of emissions generation
and control.
While Class I locomotives are remanufactured on a relatively frequent and scheduled
basis of 4 to 8 years, Class II and III locomotives may be remanufactured on a longer
schedule or may not be remanufactured at all. The typical service life of a locomotive (40
years) is often exceeded by small railroads that continue to use older locomotives. It is
important to note that there is no inherent limit on how many times a locomotive can be
remanufactured, or how long it can last, rather, the service life of a locomotive or locomotive
engine is limited by economics. For example, in cases, where it is economical to cut out
damaged sections of a frame, and weld in new metal, an old locomotive may be salvaged
instead of being scrapped. Remanufacturers can also replace other major components, such as
trucks or traction motors, to allow an older locomotive to stay in service. However, at some
point, most railroads decide that the improved efficiency of newer technologies justifies the
additional cost, and thus scrap the entire locomotive. Nevertheless, many smaller railroads,
F In some cases, some components are remanufactured by welding in new metal and remachining the component
to the original specifications.
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Regulatory Impact Analysis
especially switching and terminal railroads, are still using locomotives that were originally
manufactured in the 1940s.
1.2.3.4.1 Remanufacturers
While the original manufacturers provide much of the remanufacturing services to
their customers, there are several smaller entities that also provide remanufacturing services
for locomotive engines. These businesses can be rebuilders licensed by the OEMs, in
addition to the OEMs themselves. Moreover, some of the Class I and II railroads
remanufacture locomotive engines for their own units and on a contractual basis for other
railroads. EPA has been able to identify nine independent locomotive remanufacturers, four
of which are small business entities. Many of these businesses are full service operations that
remanufacture locomotive assemblies (such as trucks or air brake systems), sell new and used
parts, repair wrecked locomotives or provide routine maintenance. A few of these operations
remanufacture locomotives primarily for resale or lease, while others remanufacture engines
for operating railroads or industrial customers. A few also offer contract maintenance; this
may be tied to a locomotive lease, or may be offered separately to owners of locomotives. The
size of these companies can vary tremendously. Some have as few as two employees, while
others can have as many as 5,000 employees. The cost of a remanufacturing kit can vary
depending on the model of locomotive and year of manufacture; an estimated range is
$15,000-$30,000 per kit.
1.2.4 Demand: Railroads
Railroads are said to transport freight more efficiently than other modes of surface
transportation because they require less energy and emit fewer pollutants.43 The 2006
Transportation Energy Data Book shows that rail transportation used approximately 7% of all
diesel fuel used in transportation to move nearly 40% of all freight ton-miles (miles one ton of
freight is moved). It is important to recognize, however, that this 7% represents the total
amount of fuel used in all rail sectors including: line-haul, switcher, Amtrak, commuter rail,
and transit rail, as shown in Figure 1-1-8.
1-54
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Industry Characterization
Figure 1-1-8 Rail Energy Use
Rail Energy Use
(Total is 605 trillion BTU)
D Line-haul
Switcher
DAmtrak
~i Commuter rail
D Transit
Source: Linda Gains, "Reduction of Impacts from Locomotive Idling", Argonne National Laboratory, 2003
There are many other unique characteristics of the railroad industry, such as: track
sharing, locomotive sharing, and fleet age. Track sharing is when a locomotive owned by one
company travels over track that belongs to another company. This is not an inherent right and
must be negotiated between the railroads. Locomotive sharing occurs when locomotives
owned by different companies form one consist that hauls a train. This enables a company's
locomotives to be fully utilized. Unlike most other methods of shipping, railroads are
responsible for maintaining their own infrastructure such as tracks, and bridges, which is a
very expansive network. The Class I railroads spent more than $320 billion or approximately
44% of their operating revenue between 1980-2003 to maintain and improve their
infrastructure and equipment.61 As locomotives grow larger and heavier, and as cars are
designed to hold more weight, track is required that can handle this increased load. To date,
of the 549 short line and regional railroads in existence, 333 have track that cannot handle
f-rj
these increased loads.
1.2.4.1 Railroad Classification System (Class I, II and III)
In the United States, freight railroads are subdivided into three classes based on annual
revenue by the federal government's Surface Transportation Board (STB) (STB regulations
for the classification of railroads are contained in 49 CFR Chapter X). The STB regulations
divide the railroads into three classes based on their annual carrier operating revenue.63 As of
2005, Class I railroads had annual carrier operating revenues of at least $319 million, Class II
railroads had annual carrier operating revenues between $40-$319 million, and Class III
railroads had operating revenues of $40 million or less. The AAR further subdivides Class II
and III railroads into regional and local railroads based on the miles of track over which they
operate, in addition to their revenue. A regional railroad is a line-haul railroad that operates
on at least 350 miles of track and/or earns revenue between $40 million and the Class I
revenue threshold. A local railroad is a line-haul railroad which operates over less than 350
miles of track and has revenues less than $40 million. Class III also includes switching and
terminal railroads. These types of railroads usually belong to the American Short Line and
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Regulatory Impact Analysis
Regional Railroad Association (ASLRRA). Figure 1-9 shows the differences in fuel
consumption, number of railroads and the amount of track miles traveled for these different
categories of railroads.
Figure 1-1-9 Freight Rail Industry Overview
100% n
90%
80%
70%
60%
50%
40%
30%
20%
10%
0% -
1%
(
70%
95%
Freight Rail Industry Overvie
(% of Industry Totals in 2003)
(Source: Assoc. of American Railroads. Overview of U.S. Freight Railroads
56%
11%
6% | 1
37%
1 1
14%
1.70%
I I 1
-
w
Feb.2005)
5%
^1 .70%
1 1
Dlass Regional Local Linehaul Switching & Terminal
D Number of Railroads Track Miles Operated n Fuel Consumptio
-\
1.2.4.2 Class I Characteristics
Current railroad networks (rail lines) are geographically widespread across the United
States, serving every major city in the country. Approximately one-sixth of the freight hauled
in the United States is hauled by train.64 There are few industries or citizens in the country
who are not ultimate consumers of services provided by American railroad companies.
According to statistics compiled by AAR, Class I rail revenue accounted for 0.36 percent of
the Gross National Product in 2004. Combined with the value of the freight they haul (which
is nearly 40% of all freight as measured in ton-miles), it is obvious that efficient train
transportation is a vital factor in the strength of the U.S. economy.
In order for Class I railroads to operate nationally, they need unhindered rail access
across all state boundaries. If different states regulated locomotives differently, a railroad
could conceivably be forced to change locomotives at state boundaries, and/or have
state-specific locomotive fleets. Currently, facilities for such changes do not exist, and even if
switching areas were available at state boundaries, it would be a costly and time consuming
disruption of interstate commerce. A disruption in the efficient interstate movement of trains
throughout the U.S. could have an impact on the health and well-being of not only the rail
industry, but the entire U.S. economy as well.
Class I railroads are nationwide, long-distance, line-haul railroads which carry the
bulk of the railroad commerce. There are currently 7 Class I freight railroads operating in the
1-56
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Industry Characterization
country, two of which are Canadian owned.65 Class I railroads operated approximately
22,400 locomotives in the U.S., over 97,662 miles0 of track, accounted for approximately 90
percent of the ton-miles of freight hauled by rail annually, and consumed 4.1 billion gallons of
diesel fuel in 2004.66'64 Of these, the two largest Class I railroads, Burlington Northern and
Santa Fe (BNSF), and UP, accounted for the vast majority (63%) of the Class I locomotives in
service in the U.S as of the end of 2004.67 According to the 2004 AAR "Analysis of Class I
Railroads," Class I railroads paid on average over $1.06 for a gallon of fuel in 2004 for a total
expenditure of $4.2 billion which was 11% of their operating revenue. U.S. Class I railroads
employ approximately 177,000 people, the vast majority of who are unionized, and as of 2004
received an average compensation of $65,000.
The Bureau of Transportation Statistics 2006 report shows that in terms of ton-miles
of freight, railroads haul 36.8% of total ton-miles, followed by trucking (29%), pipline
(19.9%), river/canal/barge (13.9%), and air (0.3%), also shown in Figure 1-1-10 . Rail is a
primary means of transport for many bulk commodities, according to AAR, 65% of all coal
produced in the U.S., 33% of all grain harvested in the U.S. and 75% of all new automobiles
manufactured in the U.S. were transported by rail. As a primary mode of transportion for
these items, the railroad industry normally sets the industry standard price ($/ton-mile). Rail
transport is typically more fuel efficient and less expensive than other land-based sources of
transport. In terms of BTUs of energy expended per ton-mile of freight hauled, Department
of Energy statistics indicate that rail transport can be as much as three to four times more
efficient than truck transport. The AAR has asserted that one double-stack train can carry the
equivalent of 280 truckloads of freight.68'69
Figure 1-1-10 U.S. Freight Transportation Share by Mode
Pipeline, 19.9%
Air, 0.3%
V\feter, 13.9%
Truck, 29.0%
Railroad, 36.8%
G This is the road length of track or the aggregate length of track excluding sidings and parallel tracks, actual
track miles are 167,312.
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Regulatory Impact Analysis
Figure 1-12 and Table 1-30 show the long term growth trends in the amount of freight
carried by Class I railroads and the amount of fuel consumed in carrying that freight.66 Note
that the ton miles of freight carried have almost tripled, while total fuel consumption has risen
only 10-20%, showing an approximate 250% improvement in freight hauling efficiency since
1960. Efficiency increases have occurred for a number of reasons including: locomotive
manufacturers have made continual progress in improving the fuel efficiency of their engines
and the electrical efficiency of their alternators and motors, and railroads have made
significant improvements to their operational efficiency. Fuel efficiency of the railroad
industry overall has improved 16% over the last decade.43 It is reasonable to project that the
growth in the amount of freight hauled will continue in the future. It is less certain, however,
whether fuel consumption will increase significantly in the near future.
Table 1-30 Annual Fuel Consumption and Revenue Freight For Class I Railroads
Annual Fuel Consumption and Revenue Freight
For Class I Railroads
Year
1960
1970
1980
1990
1995
2000
2001
2002
2003
2004
Revenue Freight
(Million Ton-Miles)
572,000
765,000
919,000
1,030,000
1,300,000
1,460,000
1,500,000
1,510,000
1,550,000
1,660,000
Fuel Consumption
(Million Gallons)
3,500
3,500
3,900
3,100
3,400
3,700
3,700
3,700
3,800
4,100
Ton-Miles of Freight
moved per gallon of fuel
160
220
240
330
380
390
410
410
410
410
Figure 1-1-11 Fuel Consumption and Revenue Ton-Miles for Class I Railroads
2000
1500 -
53 1000 -
500 -
i
e
1955 1960 1965 1970 1975 1930 1985 1990 1995 2000 2004
-Ton-Miles
Fuel
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Industry Characterization
1.2.4.2.1 Class I Market Share
UP operates over the most miles of track (32,616), has the largest number of
employees (49,511), the greatest operating revenue ($12,180 million), but is surpassed in
revenue ton-miles by BNSF (569 billion).H UP owns more miles of track than any other
Class I (27,123), and operates the most locomotives (7,680), as shown in Table 1-31.
Table 1-31 Class I Railroads - Number of Locomotives
Class I Railroads - Number of Locomotives
(2003 Data)
(Source: https://www.aar.org/AboutThelndustry/RailroadProfiles.asp)
8000
7000
6000
5000
4000
3000
2000
1000
Union Pacific Burlington CSX Norfolk
Railroad Northern and Transportation Southern
Company Santa Fe Combined
Railway Railroad
Company Subsidiaries
Candian Kansas City Canadian
National Southern Pacific Railway
Railway
Company
1.2.4.2.2 Locomotive Fleet
Historically, Class I railroads have purchased virtually all of the freshly-manufactured
locomotives sold. As the Class I railroads replace their equipment with freshly-manufactured
units, the older units are either sold by the Class I railroads to smaller railroads, are scrapped,
or are purchased for remanufacture and ultimate resale (or leasing) by companies specializing
in this work. The industry-wide replacement rate for locomotives is therefore actually lower
than those indicated for the Class I railroads only. This would mean that the time required for
the total locomotive fleet to turn over is longer.
Additionally, independent of cyclic changes in the industry, future locomotive
replacement rates may actually decrease as higher powered locomotives pull longer trains
leading to fewer locomotives in a consist. Locomotive manufacturers are now producing
locomotives that have significantly more horsepower than older locomotives. Railroads have
requested this change so that fewer locomotives are needed to pull a train. Placing more
horsepower on a locomotive chassis increases overall train fuel efficiency. For example, it is
H A revenue ton-mile is calculated by dividing freight revenue by total freight ton-miles, it is a measure of the
level of revenue received by a railroad for hauling weight over distance. (AAR Railroad Facts, 2006)
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Regulatory Impact Analysis
more fuel-efficient to use two 6000 hp locomotives, rather than three 4000 hp locomotives, to
pull the same size train, because the weight of an entire locomotive can be eliminated. Thus,
while three old locomotives may be scrapped, only two new locomotives need to be
purchased as replacements.
On the other hand, the business outlook for the railroad industry has been improving in
the last few years. As railroads have become increasingly cost-competitive with other
shipping methods like trucking, they are attracting more business. This in turn increases
demand for locomotive power to move the additional freight. Thus, while purchases of new
locomotives may increase in the next few years, these locomotives will likely supplement,
rather than replace, existing locomotives. Moreover, if freight demands continue to increase,
it may become cost-effective to operate locomotives for longer periods than are estimated
here.
1.2.4.2.3 Operation Profile
1.2.4.2.3.1 Fuel consumption70
Class I railroads consumed over 531 trillion BTUs in 2003. Locomotives traveled
1,538 million unit-miles in 2004, and averaged 69,900 miles per locomotive in 2004. The
Surface Transportation Board reported that Class I railroads consumed 4.1 billion gallons of
diesel fuel in 2004, for an average mile traveled per gallon of 0.13. The 4.1 billion gallons of
diesel fuel used by the Class I railroads is 96% of all locomotive fuel used in the U.S. and
7.4% of all diesel fuel used for transportation in the United States. Class I railroads spent
$4.2 billion which is nearly 11% of total operating expenses on fuel in 2004. Railroads are
continually trying to reduce their fuel consumption through efforts such as idle reduction, and
other operational improvements.71 In a study done by the Department of Energy, the
aerodynamic drag of coal cars has been shown to account for 15% of total round-trip fuel
consumption on a coal train; intermodal cars that are double stacked also carry an
aerodynamic fuel consumption penalty of approximately 30% due to drag. Experiments have
been done to develop equipment such as fairings and foil that can reduce this drag loss on coal
cars by up to 5% which would save 75 million gallons or 2% of total Class I fuel consumption
in 2002.43
1.2.4.2.3.2 Maintenance Practices
Locomotive maintenance practices also present some unique features. As is the case
with other mobile sources, locomotive maintenance activities can be broken down into a
number of subcategories including: routine servicing, scheduled maintenance, and breakdown
maintenance. Routine servicing consists of providing the fuel, oil, water, sand (which is
applied to the rails for added traction), and other expendables necessary for day-to-day
operation. Scheduled maintenance can be classified as light (e.g., inspection and cleaning of
fuel injectors) or heavy, which can range from repair or replacement of major engine
components (such as power assemblies) to a complete an engine remanufacture. Wherever
possible, scheduled maintenance (particularly the lighter maintenance) is timed to coincide
with periodic federally-required safety inspections, which normally occur at 92-day intervals.
Breakdown maintenance, which may be required to be done in the field, consists of the
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Industry Characterization
actions necessary to get a locomotive back into service. Because of the high cost of a
breakdown in terms of lost revenue that could result from a stalled train or blocked track,
every effort is made to minimize the need for this type of maintenance. In general, railroads
strive to maintain a high degree of reliability, which results in more rigorous maintenance
practices than would be expected for most other mobile sources. However, the competitive
nature of the business also results in close scrutiny of costs to achieve the most cost-effective
approach to achieving the necessary reliability. This has resulted in a variety of approaches to
providing maintenance.
Maintenance functions were initially the purview of the individual railroads. Some
major railroads with extensive facilities have turned to providing this service for other
railroads. A few of the smaller railroads have also done the same, in particular for other small
railroads. However, the tendency in recent years has been toward a diversification of
maintenance providers. A number of independent companies have come into existence to
provide many of the necessary, often specialized services involved in locomotive repair (e.g.,
turbocharger repair or remanufacture). The trend toward outside maintenance has also been
accelerated by the policies of some of the larger railroads to divest themselves of not only
maintenance activities, but ownership of locomotives as well. The logical culmination of this
trend is the "power by the mile" concept, whereby a railroad can lease a locomotive with all
the necessary attendant services for an agreed-upon rate.
1.2.4.2.4 Leasing
Locomotives are available for lease from OEMs, remanufacturers, and a small number
of specialized leasing companies formed for that purpose. Leasing practices appear to be
fairly standardized throughout the industry. Although lease contracts can be tailored on an
individual basis, most leases seem to incorporate standard boilerplate language, terms and
conditions. Under a typical lease, the lessee takes on the responsibility for safety certification
and maintenance (parts and scheduled service) of the locomotive (including the engine),
although these could be made a part of the lease package if desired. The lease duration ranges
between 30 days and 5 years, with the average being 3 years Figure 1-12 shows that leasing
has been a continuing trend among Class I railroads, with almost two-thirds of the
locomotives placed into service in 2004 leased locomotives. Leasing among Class II and III
railroads is not nearly as widespread.
1-61
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Regulatory Impact Analysis
Figure 1-1-12 Source: AAR Railroad Ten-year Trends 1995-2004: Number of Purchased and Leased Class
I Locomotives
1200
1000
800
600
400
200
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
1.2.4.2.5 Traffic10
The value of goods transported by all modes of transportation between 1993 and 2003
increased by 43.6% to $8,397.2 billion, and the ton miles increased over that period by 29.6%
to 3,138 billion ton-miles. The railroads share of the value market increased during that time
by 25.7%, and the percent increase in their ton-miles shipped over that time was 33.8%. Ton-
miles shipped using multiple modes of transportation also increased over this period such as
Truck and Rail (20.8%), and Rail and Water (63.8%).
Figure 1-1-13 shows that the overall Class I traffic volumes are still increasing, and as
the car miles and train miles converge, this means they are optimizing the number of cars a
locomotive can carry most likely by using fewer more powerful locomotives to haul more
cars.64 The average length of a haul for Class I railroads has generally increased every year,
and has almost doubled since 1960 when 461 miles was the average haul as compared to 2004
when 862 miles was the average haul length. Commuter rail has generally not increased its
average haul length over this same time period. Class I train-miles, (a train-mile is the
movement of a train, which can consist of multiple cars, the distance of one mile) were 535
million in 2004, Class I car-miles (a car-mile measures the distance traveled by every car in a
train) were 37,071 million miles in 2004.72
1-62
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Industry Characterization
Figure 1-1-13 Class I Train Miles and Car Miles Source: AAR Ten Year Trends 1995-2004
38000 -,
36000 -
34000 -
32000 -
30000 -
28000 -
26000 -
24000 -
22000 -
20000 -
-r 550
-- 500
-- 450
-- 400
-- 350
300
&'
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Regulatory Impact Analysis
Figure 1-1-14 Class I Intermodal Traffic
Intermodal Traffic (AAR Railroad Facts 2006)
12000000 -,
5 10000000 -
c
a
o 8000000
o
6000000 -
4000000 -
2000000 -
1980
1985
1990 1995
year
2000
2004
1.2.4.4 Track Statistics52
As of 2004, Class I owned 97,662 miles of trackage. Since 1980, capital expenditures
on trackage and other structures has increased 88% from $2.6 billion in 1990 to $4.9 billion in
2004 as railroad tracks have been upgraded to 130 pound per yard weighted rail to
accommodate heavier loads being hauled per car. Class I railroads have increased their traffic
(ton-miles) by approximately 81%, while they have decreased the miles of track they own by
41%. This has increased traffic density, and although double-stacking containers has helped
to reduce traffic to some degree, this is still a concern due to the continual growth in ton-
miles.
73
1.2.4.5 Class II & III Characteristics74 75
In the 1970's, deregulation allowed the Class I railroads to stop operating many
smaller lines that were unprofitable. This allowed many small independent railroads to take
over that portion of the line and run it more efficiently and sometimes at a lower cost due to
their enhanced flexibility as a small business. In 2004 there were 549 Class II and Class III
railroads. In many cases, these smaller railroads are also able to receive financial assistance
from local governments or associations of customers to help them upgrade their infrastructure
(in many cases, the tracks are quite old and are not rated for the loads that today's cars
typically carry).
In 2004, short lines originated or terminated one out of every four carloads moved by
the domestic rail industry, and operated over 50,000 miles of track, which is nearly 29% of all
U.S. rail mileage. They had over 19,000 employees and served over 11,700 customers and
facilities. Of the track they operate, only 43% is capable of handling the heavier 286,000 ton
axle weight cars. The total revenue for the Class II and III railroads in 2004 was almost $3
billion, while they spent nearly $433 million on capital expenditures, $397 million on
maintenance of equipment, road and structures, and $221 million on fuel. More than half of
1-64
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Industry Characterization
the short line and regional railroads connect to two or more other railroads, and over 80%
operate in only one state.
Statistics compiled by the ASLRRA in 2004 show that there are approximately 549
Class II and III railroads (not including commuter or insular railroads that serve a track within
a factory). A more detailed breakdown of these small railroads can be found in Table 1-32.
They consist primarily of regional and local line-haul and switching railroads, which operate
in a much more confined environment than do the Class I railroads.1 Class II and III railroads
operated approximately 3,777 locomotives in 2004, and in survey taken in 2004 by the
ASLRRA, locomotive fleet age data shows that over 92% of the locomotives owned by the
Class II and III railroads are over twenty years old, slightly over 5% are 10-19 years old, and
2% are newer than 10 years old. Class II and III railroads used 552 million gallons of fuel in
2004, which is about 13% of the amount of diesel fuel used by Class I locomotives, in 2004.
Employment has declined for all railroads including Class I railroads substantially since the
1990's, but nearly all railroads are predicting growth in hiring.
Table 1-32 Profile of Railroad Industry -200453
Type of Railroad
Class I Freight Railroad
National Passenger
Railroads
Regional Railroads
Local/Line-Haul Railroads
Switching and Terminal
Class I Subsidiaries
Commuter Railroads
Shipper-Owned Railroads
Government Owned
Railroads
Number of Railroads
7
1
31
314
204
102
21
68
28
Number of Employees
157699
18,909
7422
5349
6429
3687
25,29676
NA
NA
Some of the smaller railroads are owned and operated by Class I railroads, many of
which are operated as formal subsidiaries for financial purposes, but are run as standalone
entities. In 2004, there were 31 regional railroads, 314 local line-haul railroads and 204
switching and terminal railroads, including subsidiaries (regional and local railroads may also
have subsidiaries). A few of these are publicly held railroads and some are shipper-owned.
Insular (in-plant) railroads are not included in this total. ASLRRA estimated that there are
probably about 1,000 insular railroads in the U.S. These railroads are not common carriers,
but rather are dedicated to in-plant use. They typically operate a single switch locomotive
powered by an engine with less than 1000 hp. Finally, there are a handful of very small
passenger railroads that are primarily operated for tours. These tourist railroads are included
within the Class II and III railroads.
1 "Regional railroad" and "local railroad" are terms used by AAR that are similar, but not identical, to "Class II"
and "Class III", respectively.
1-65
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Regulatory Impact Analysis
1.2.4.6 Passenger Rail
1.2.4.6.1 Amtrak
Amtrak was formed in 1971 by Congress through the Rail Passenger Service Act of
1970 (P.L. 91-518, 84 Stat.1327) to relieve the railroads of the financial burden of providing
passenger railway service. In return for government permission to leave the passenger rail
business and avoid continued losses, many of the freight railroads donated equipment to
Amtrak as well as $200 million in startup capital.61 Amtrak is operated by the National
Railroad Passenger Corporation of Washington, D.C. The U.S. Secretary of Transportation
has the authority to designate Amtrak's destinations, which as of 2004 included 527 cities;
other transit rail serve 2,909 destinations, some of which may be shared with Amtrak.70
Amtrak traveled over 37 million train miles in 2004, and served on average, 777,000 people
each day that depend on commuter rail services operated under contract by Amtrak, or that
use Amtrak-owned infrastructure, shared operations and dispatching. On average, 69,000
people ride on up to 300 Amtrak trains each day77. Amtrak relies on receiving federal
subsidies in order to operate, although it continually works to become independent and
profitable.
Although Amtrak's rates are not regulated, it does depend on the amount of subsidies
received from the Federal government; this is not unlike most other forms of passenger rail in
the U.S that receive federal, state, or local subsidies. Amtrak competes with other modes of
transportation, and this also affects its ability to charge higher rates. Fuel costs can
dramatically affect rates and Amtrak's need for subsidies. Between 2004 and 2005, Amtrak's
fuel costs increased 149% or by $43 million, and continue to increase substantially, despite
efforts for improved fuel conservation methods that reduced its fuel consumption by nearly
10% during that same period.78
Amtrak is the sole large-scale provider of inter-city passenger transport. Its fleet
includes 436 locomotives, 360 of which are diesel locomotives that used a reported 69.9
million of gallons of fuel in 2005. It also owns 76 electric locomotives. Recently, the FRA
provided Amtrak with funding to purchase Acela locomotives, which are 4,000 horsepower
gas turbine locomotives. These locomotives consume about the same amount of fuel as a
diesel locomotive but produce about 1/1 Oth of the NOX.
Amtrak offers service to 46 states on 21,000 miles of routes, only 745 miles of which
are actually owned by Amtrak and are located primarily in Michigan, and between Boston and
Washington DCError! Bฐฐkrkปฐtdefld- Based on gross revenue, Amtrak is classified as a
Class I railroad by the STB. However, unlike the Class I freight railroads Amtrak's current
operating expenses exceed its gross revenue.
The average age of a passenger train from Amtrak is quite young; in fact, since 1980 it
has remained under 14.5 years old. Amtrak was on-time 74% of the time in 2003, and 65% of
that delay was caused by a host railroad. A host railroad is a freight or commuter railroad over
which track Amtrak operates on for all or part of a trip, and delays can include signal delays,
train interference, routing delays or power outages. Amtrak must pay these host railroads for
use of this track and any other resources. In 2005, those payments were based on more than
1-66
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Industry Characterization
25 million train miles (one train-mile is a mile of track usage by each train) which totaled
more than $92 million.
The average Amtrak city-to-city fare was $55.15, with an average trip of 231 miles,
and average revenue per passenger-mile is $0.251 for Amtrak.70 In 2006, Amtrak was able to
obtain an additional subsidy in order to remain operational in 2006, in the amount of $1.1
billion.79 The future of Amtrak is uncertain, and may change if the Passenger Rail Reform
Act is passed. This bill is currently in the House Subcommittee on Railroads, and would split
Amtrak up into three different entities, two privately owned and one government owned
corporation.
1.2.4.6.2 Commuter^
There are also 21 independent commuter rail systems operating in sixteen U.S. cities,
consuming 72 million gallons of diesel fuel annually, operating over 6,785 miles of track.
They employed approximately 25,000 employees in 2004. Many of these commuter railroads
rely on Federal subsidies to improve their infrastructure, in some cases they also rely on state
and local government subsidies to support their operations.
The average commuter fare in 2004 was $3.90, for an average trip length of 23.5
miles, with average revenue per passenger-mile of $0.154. An estimated 414 million people
use commuter rail each year to result in over 9.7 billion passenger-miles. Like Amtrak,
commuter rail operations also maintain a young fleet that has remained younger than 17 years
old since 1985.
1.2.5 Existing Regulations
1.2.5.1 Safety
Achieving and maintaining the safe operation of commercial (common carrier)
railroads in the U.S. falls under the jurisdiction of the Federal Railroad Administration (FRA),
which is a part of the Department of Transportation. The FRA was created in 1966 to
perform a number of disparate functions, including rehabilitating the Northeast Corridor rail
passenger service, supporting research and development for rail transportation, and promoting
and enforcing safety regulations throughout the railway system.
FRA safety regulations apply to railroads on a nationwide basis. In 49 CFR section
229 the regulations require safety inspections of each locomotive used in commercial
operations: daily, every 92 days (i.e. the periodic inspection), annually, and biennial. Each
subsequent inspection increases in complexity. The inspections are usually performed by the
railroad which owns or leases the locomotive. FRA personnel review the findings of these
inspections and any corrective actions identified and taken. Since each locomotive is required
to be out of revenue service for inspection every 92 days, railroads commonly schedule their
performance of preventive maintenance during these times. It appears likely that each
locomotive is out of service for 12 to 24 hours during each FRA safety inspection and
1-67
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Regulatory Impact Analysis
preventative maintenance period/ To limit the time that locomotives are out of service for
these safety inspections and preventive maintenance, railroads maintain suitable facilities
distributed across the nation. Thus, it appears that the railroads have had a long history of
compliance with federal regulations, and have developed strategies to live within the
regulations and to minimize any adverse business impacts that may have resulted.
1.2.5.2 Federal81
In 1980 Congress passed the Staggers Act (USCA 49 ง 10101) which laid out the
government's statutory objectives for the railroad industry which are to balance the efficiency
and viability of the industry with the need for: reasonable rates, fair wages, public health and
safety, and energy conservation. The railroads are governed by two separate federal agencies
directly, both under the Department of Transportation, a cabinet-level department. The
Federal Railroad Administration (FRA) regulates safety issues. The FRA sets safety
standards for rail equipment and operation, and also investigates accidents on rail lines and at
rail crossings. The FRA also plays a role in labor disputes to a small degree, by monitoring
the progress of negotiations, projecting the economic impact of a strike and assisting the
Secretary in briefing Congress if necessary. The STB is an adjudicatory body that was
formed in 1966 to settle disputes and regulate the various modes of surface transportation
within the U.S. Organizationally, the STB is part of the Department of Transportation (DOT),
the STB deals with railway rate and service issues, railway restructuring and various other
issues, including classification of railroads. The Surface Transportation Board (STB)
regulates economic issues such as rates. The STB can also mandate access to locations in
order to maintain competition in areas where mergers reduced the number of available carriers
1.2.5.3 Rates
Rail transportation accounts for 8.7% of all for-hire transportation services that are a
measured in the GDP. The average freight revenue per ton-mile for Class I rail in 2004 was
$0.0235, with average operating revenue of $40.5 billion. Freight rates, when adjusted for
inflation have declined by an average of 1.1% a year between 1990 and 2004, due in large
part to the passage of the Staggers Act, as shown in Figure 1-1-15.82
If a shipper believes a rate is unreasonable (only if that shipper does not have access to
another railroad, and waterway or highway modes are not feasible), they can complain to the
STB, which has a stand-alone rate standard. This means that they determine what a
hypothetical new carrier to serve that shipper would need to charge to cover all of its costs
including capital and construction. If this hypothetical rate is less than what the shipper is
being charged, that charged rate is considered to be "unreasonably high" and the railroad can
be ordered to reduce the challenged rate and pay reparations to the shipper. Complaints such
as these are typically made by bulk shippers, such as coal or chemicals, who cannot use other
modes of transportation such as highway or can't access other railroads.
1 Values are an approximate estimate by FRA personnel.
1-68
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Industry Characterization
Figure 1-1-15 Railroad Rate Trends Before and After Staggers Act of 19808
Railroad Rates After Inflation
1972=100
1-fU
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Ij?
i ^n
IjU
i >ฃ
iz?
1 1fl
1ZU
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1 1 ft
11U
i c\z
1U?
100
9C
?
on
yu
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on
, X
/ ^N.
/ \
/ "v
/ s.
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^ "%
,- / ^ ^
/ ^/ -"-- -
V V V V
V V
V V
Year
Sources: U.S. Dept. of Labor, Bureau of Labor Statistics, Producer Price Index of Line-
Haul Operating Railroads; U.S. Dept. of Commerce, Bureau of Economic Analysis, Implicit
Price Deflator for Gross Domestic Product
1.2.6 Foreign Railroads in US
Locomotives that operate extensively within the U.S. are subject to the existing
provisions of 40 CFR Part 92.
1.2.6.1 Mexico
In 2004, the Bureau of Transportation Statistics (BTS) says there were a total of
675,305 US/Mexico railcar crossings, that's an average of almost 1900 crossings a day, or one
every minute. The Mexican Railroads and their 16,415 miles of track have been privately
owned since a Constitutional amendment was passed in 1995 (see FRA "Border Issues").
They primarily haul NAFTA generated goods, such as cars, automobile parts, and other
manufactured products. Mexico has two railroads, Ferrocarril Mexicano, which has a joint
venture with UP, and Transportacion Ferroviaria Mexicana (TFM) of which Kansas City
Southern has controlling interest.83
1.2.6.2 Canada
In 2004, the BTS says there were 1,950,909 border crossings into Canada by railcars.
Canada is also home to two Class I railroads that operate extensively in the U.S., Grand Trunk
Corporation which includes almost all of Canadian National's (CN) U.S. operations, and
Canadian Pacific Railway which operates its Soo Line primarily in the U.S.
1-69
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Regulatory Impact Analysis
References
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Vessels," Final Report, May 2006. Prepared for U.S Environmental Protection Agency, Office of Transportation
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2 See www.imo.org Go to Conventions, Status of Conventions - Summary.
3 46 USCS Appx ง 688
4 Proposal to Initiate a Revision Process, Submitted by Finland, Germany, Italy, the Netherlands, Norway,
Sweden and the United Kingdom. MEPC 53/4/4, 15 April 2005. Marine Environment Protection Committee,
53rd Session, Agenda Item 4.
5 Revision of the NOx Technical Code, Tier 2 Emission Limits for Diesel Marine Engines At or Above 130 kW,
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7 Power Systems Research (PSR). 2004. OELink. .
8 U.S. Environmental Protection Agency (EPA). 1995. EPA Office of Compliance Sector Notebook Project:
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9 U.S. Census Bureau. 2004. Economic Manufacturing Industry Series: 2002. EC02-311-333618. Washington,
DC: U.S. Census Bureau. Tables 1, 5, and 7.
10 Docket ID# EPA-HQ-OAR-2003-0190-0847
11 National Marine Manufacturers' Association (NMMA). January 12, 2006. Facsimile from John McKnight
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12 Workboat. January 2005. Workboat Construction Survey. Last obtained March 15, 2006.
(http ://www. workboat. com/pdfs/WB_2004const_survey .pdf)
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MA: D.C. Heath and Co.
14 U.S. Census Bureau. 2004. Economic Manufacturing Industry Series: 2002. EC02-31I-333618. Washington,
DC: U.S. EPA.
15 U.S. Department of Transportation. 1998 and 2006. National Transportation Statistics 1997 and 2005.
Washington, DC: U.S Department of Transportation.
16 U.S. Bureau of the Census. 2002 Economic Census, http://www.census.gov/prod/ec02/ec0231i336611.pdfand
http://www.census.gov/prod/ec02/ec0231i336612.pdf.
17 U.S. Maritim Administration (MARAD). 2003. Report on the survey of U.S. Shipbuilding and Repair
Facilities. U.S. Department of Transportation, Maritime Administration.
18 National Marine Manufacturers Association (NMMA). 2004. 2004 Recreational Boating Statistical Abstract.
Chicago, IL.
19 National Marine Manufacturers Association (NMMA). 2004. 2004 Recreational Boating Statistical Abstract.
Chicago, IL.
20 U.S. Bureau of the Census. 2002 Economic Census, http://www.census.gov/prod/ec02/ec0231i336612.pdf.
21 Hoover's Online. 2006. Online company database, .
22 Dun & Bradstreet. 2006a. D&B Million Dollar Directory. Bethlehem, Pennsylvania: Dun & Bradstreet, Inc.
23 Dun & Bradstreet. 2006b. Small Business Database, .
24 National Marine Manufacturers Association (NMMA). 2004. 2004 Recreational Boating Statistical Abstract.
Chicago, IL.
25 National Marine Manufacturers Association (NMMA). 2004. 2004 Recreational Boating Statistical Abstract.
Chicago, IL.
26 National Marine Manufacturers Association (NMMA). 2004. 2004 Recreational Boating Statistical Abstract.
Chicago, IL.
27 Eastern Research Group, Inc. (ERG). "Category 2 Vessel Census, Activity, and Spacial Allocation Assessment
and Category 1 and Category 2 In-port/At-sea Splits," Final Report, Feb. 16, 2007. Prepared for U.S
Environmental Protection Agency, Office of Transportation and Air Quality.
1-70
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Industry Characterization
28 WorkBoat. Annual Construction Survey. January/February 1992, January /February 1994, January/February
1995, January 1998, and January 2004. Portland, ME: Workboat.
29 Eastern Research Group, Inc. (ERG). "Category 2 Vessel Census, Activity, and Spacial Allocation Assessment
and Category 1 and Category 2 In-port/At-sea Splits," Final Report, Feb. 16, 2007. Prepared for U.S
Environmental Protection Agency, Office of Transportation and Air Quality.
30 American Waterways Operators (A WO). 2006. Facts About the American Tugboat, Towboat, and Barge
Industry, http://www.americanwaterwavs.com/. Arlington, VA.
31 Letter from Jennifer Carpenter, Senior Vice President of Government Affairs and Policy Analysis, American
Waterways Operators, to EPA Docket EPA-HQ-OAR-2003-0190, July 2, 2007.
32 Eastern Research Group, Inc. (ERG). "Category 2 Vessel Census, Activity, and Spacial Allocation Assessment
and Category 1 and Category 2 In-port/At-sea Splits," Final Report, Feb. 16, 2007. Prepared for U.S
Environmental Protection Agency, Office of Transportation and Air Quality.
33 Eastern Research Group, Inc. (ERG). "Category 2 Vessel Census, Activity, and Spacial Allocation Assessment
and Category 1 and Category 2 In-port/At-sea Splits," Final Report, Feb. 16, 2007. Prepared for U.S
Environmental Protection Agency, Office of Transportation and Air Quality.
34 U.S. Department of Labor Statistics. 2006. Occupational Outlook Handbook.
http://www.bls.gov/oco/ocosl77.htm.
35 Eastern Research Group, Inc. (ERG). "Category 2 Vessel Census, Activity, and Spacial Allocation Assessment
and Category 1 and Category 2 In-port/At-sea Splits," Final Report, Feb. 16, 2007. Prepared for U.S
Environmental Protection Agency, Office of Transportation and Air Quality.
36 WorkBoat.com. February 2006. 2005 Construction Survey.
37 WorkBoat.com. February 2006. 2005 Construction Survey.
38 "Locomotive Facts & History" GE Transportation, www.getransportation.com/na/en/locofacts.html
39 Frank W. Donnelly, Raymond L. Cousineau, R. Nigel M. Horsley, "Hybrid Technology for the Rail Industry"
ASME/IEEE Document RTD2004-66041, April 2004.
40 www.railpower.com/products_hl_howitworks.html
41 https://www.getransportation.com/general/locomotives/hybrid/hybrid_default.asp
42 "Prospects for Dynamic Brake Energy Recovery on North American Freight Locomotives"
"Railroad and Locomotive Technology Roadmap" Argonne National Laboratory, December 2002
44 "American Diesel-Electric Locomotives" www.nps.gov/history/history/online_books/steamtown/shs5.htm
45 www.uprr.com/aboutup/history/loco/locohs03 . shtml
46 Steven Fritz, "On Track Toward Cleaner Large Engines: New emissions reduction strategies focus on
locomotives and ferry boats" Southwest Research Technology Today. Spring 2004.
47 http://www.wabtec.com/corp/fast_facts.asp
48 http://www.everytime.cummins.com/every/applications/rail.jsp
49 Docket ID# EPA-HQ-OAR-2003-0190-0367[1]
50 www.stewartand Stevenson.com, http://brookvilleequipment.com/
51 http://www.emdiesels.com/lms/en/company/history
52 www.getransportation.com/general/freight_rail/models
53 Association of American Railroads (AAR) Railroad Ten- Year Trends 1995-2004
54 http://www.nationalrailway.com/
55 http://www.railpower.com/products_td.html
56 "New Ultra-Low Emission Locomotive Goes to Work in Union Pacific's Los Angeles Basin Rail Yards"
http://www.uprr.eom/newsinfo/releases/environment/2007/0 13 l_ultralow. shtml
57
William C. Vantuono, "New power plays to watch" Railway Age, August 2006, www.nyab.com/news/NYAB-
RA-10-06-Power%20Plays.pdf
58 "Green $ave$ Green" http://www.railpower.com/dl/greensavesgreen.pdf
59 http://www.fra.dot.gov/us/printcontent/94
60 "Stop Your Engines" http://www.roadstartonline.com/2004/ll/026a0411.asp
61 "Overview of U.S. Freight Railroads" nationalatlas.gov/articles/transportation/a_freightrr.html
1-71
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Regulatory Impact Analysis
62 American Short Line and Regional Railroad Association 2005 Facts and Figures.
63 STB Railroad Revenue Deflator Formula: Current Year's Revenues x (1991 Average Index/Current Year's
Average Index)
64 Transportation Energy Data Book, Edition 25, 2006
65 The five U.S. Class I Railroads are: Burlington Northern and Santa Fe (BNSF), CSX Transportation, Kansas
City Southern Railway Company, Norfolk Southern Railway (and subsidiaries), Union Pacific Railroad
Company (UP). The two Canadian owned Class I Railroads are: Grand Trunk Corporation and the Soo Line
Railroad Company
66 Association of American Railroads (AAR) Railroad Facts 2005
67 Based on 2005 Railroad Annual Reports filed with STB.
es "Q>R showcases success in greenhouse gas reductions" http:www.prnewswire.com
69 Quoted from May 15, 1997 testimony by Bruce Wilson representing AAR. Docket item #A-94-3 l-IV-D-7.
70 National Transportation Statistics 2006, Bureau of Transportation
71 "Fuel Savings Solutions" www.getransportation.com/na/en/docs/806349 Fuel Savings Broch-L.pdf
72 Table 4-17: Class I Rail Freight Fuel Consumption and Travel
http://www.bts.gov/publications/national_transportation_statistics/2006/csv/table_04_17.csv
73 "Freight Railroads: Industry Health Has Improved, but Concerns about Competition and Capacity Should be
Addressed" GAO Report to Congressional Requesters, October, 2006.
74 Short Line and Regional Railroad Facts and Figures, 2005 Edition
75 "An Industry in Uncertain Territory" Presentation by Richard F. Timmons, President of the Transportation
Research Forum, www.aslrra.org/images/news_file/Transportation_Research.Forum_October_6_2006.pdf
76 "Commuter Rail National Totals, Fiscal Year 2004" http://www.apta.com/research/stats/rail/crsum.cfm
77 "Amtrak National Fact Sheet" Amtrak Media Relations: July, 2006.
78 "Amtrak: Energy Efficient Travel" Amtrak Media Reltaions: June, 2006.
79 Andrew Taylor, "Amtrak Supporters Aim to Ease Budget Cuts" 06/14/06, Associated Press.
80 "2006 Transit Fact Book", American Public Transportation Association.
81 http://www.fra.dot.gov/us/printcontent/955
82 "Freight Railroads Background" Federal Railroad Administration, 2003:
www.fra.dot.gov/downloads/policv/freight2003.pdf
83 "Competition Agencies Clear the Way for Kansas City Southern's NAFTA Railway" The Transportation
Antitrust Update, Winter 2005 - Issue No. 14
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Air Quality and Resulting Health and Welfare Effects
CHAPTER 2: Air Quality and Resulting Health and Welfare Effects of Air Pollution from
Mobile Sources 2-2
2.1 Particulate Matter 2-4
2.1.1 Science of PM Formation 2-4
2.1.2 Health Effects of PM Pollution 2-11
2.1.3 Current PM2.5 Levels 2-14
2.1.4 Projected PM2.5 Levels 2-15
2.1.5 Environmental Effects of PM Pollution 2-19
2.2 Ozone 2-28
2.2.1 Science of Ozone Formation 2-28
2.2.2 Health Effects of Ozone Pollution 2-29
2.2.3 Current 8-Hour Ozone Levels 2-30
2.2.4 Projected 8-Hour Ozone Levels 2-32
2.2.5 Environmental Effects of Ozone Pollution 2-40
2.3 Air Quality Modeling Methodology 2-42
2.3.1 Air Quality Modeling Overview 2-42
2.3.2 Model Domain and Configuration 2-43
2.3.3 Model Inputs 2-44
2.3.4 CMAQ Evaluation 2-45
2.3.5 Model Simulation Scenarios 2-45
2.3.6 Visibility Modeling Methodology 2-46
2.4 Air Toxics 2-48
2.4.1 Diesel Exhaust PM 2-48
2.4.2 Other Air Toxicsbenzene, 1,3-butadiene, formaldehyde, acetaldehyde,
acrolein, POM, naphthalene 2-65
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Regulatory Impact Analysis
CHAPTER 2: Air Quality and Resulting Health and Welfare
Effects of Air Pollution from Mobile Sources
The locomotive and marine diesel engines subject to this rulemaking generate
significant emissions of particulate matter (PM) and nitrogen oxides (NOX) that contribute to
nonattainment of the National Ambient Air Quality Standards (NAAQS) for PM2.5 and ozone.
These engines also emit hazardous air pollutants, or air toxics, that are associated with serious
adverse health effects. Emissions from locomotive and marine diesel engines also cause harm
to public welfare by contributing to visibility impairment and other harmful environmental
impacts across the U.S. Therefore, EPA is adopting new standards to control these emissions.
The health and environmental effects associated with these emissions are a classic
example of a negative externality (an activity that imposes uncompensated costs on others).
With a negative externality, an activity's social cost (the cost borne to society imposed as a
result of the activity taking place) exceeds its private cost (the cost to those directly engaged
in the activity). In this case, as described in this chapter, emissions from locomotives and
marine diesel engines and vessels impose public health and environmental costs on society.
However, these added costs to society are not reflected in the costs of those using these
engines and equipment. The current market and regulatory scheme do not correct this
externality because firms in the market are rewarded for minimizing their production costs,
including the costs of pollution control, and do not benefit from reductions in emissions. In
addition, firms that may take steps to use equipment that reduces air pollution may find
themselves at a competitive disadvantage compared to firms that do not. The emission
standards EPA is finalizing help address this market failure and reduce the negative
externality from these emissions by providing a regulatory incentive for engine and
locomotive manufacturers to produce engines and locomotives that emit fewer harmful
pollutants and for railroads and vessel builders and owners to use those cleaner engines.
Today millions of Americans continue to live in areas with air quality that may
endanger public health and welfare (i.e., levels not requisite to protect the public health with
an adequate margin of safety). As of October 10, 2007 there are 88 million people living in
39 areas (which include all or part of 208 counties) that either do not meet the PM2.5 NAAQS
or contribute to violations in other counties. These numbers do not include the people living
in areas where there is a significant future risk of failing to maintain or achieve the current or
future PM2.5 NAAQS. Currently, ozone concentrations exceeding the level of the 8-hour
ozone NAAQS occur over wide geographic areas, including most of the nation's major
population centers. As of October 10, 2007 there are approximately 144 million people living
in 81 areas (which include all or part of 366 counties) designated as not in attainment with the
8-hour ozone NAAQS. These numbers do not include the people living in areas where there
is a future risk of failing to attain or maintain the 8-hour ozone NAAQS. Figure 2-1 presents
the counties currently designated as nonattainment for the PM2.5 or 8-hour ozone NAAQS as
well as mandatory class I federal areas for visibility. This figure illustrates the widespread
nature of these air quality problems.
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Air Quality and Resulting Health and Welfare Effects
* The nonattainment areas are current as of October 2007.
Nonattainment areas include whole and partial counties.
, ^ป
PM and Ozone NonAtlainment
Ozone NonAttainment
PM2.5 NonAttainment
Federal Class I Areas (Visibility)
Figure 2-1 Air Quality Problems are Widespread
Emissions from locomotive and marine diesel engines account for substantial portions
of today's ambient PM2.5 and NOX levels (20 percent of total mobile source NOX emissions
and 25 percent of total mobile source diesel PM 2.5 emissions). Unless EPA takes action to
reduce their pollution levels, the relative contribution of these engines to air quality problems
will increase over time. By 2030 locomotive and marine diesel engines could constitute more
than 65 percent of mobile source diesel PM2.5 emissions and 35 percent of mobile source NOX
emissions.
Under the emission standards finalized in this action, in 2030 annual NOX emissions
will be reduced by about 800,000 tons and annual PM2.5 emissions by about 27,000 tons. We
estimate that the reduction in PM2.5 will produce nationwide air quality improvements.
According to air quality modeling performed in conjunction with this rule, all current PM2 5
nonattainment areas will experience a resulting decrease in their 2030 annual PM2 5 design
values (DV). In addition, all 133 modeled mandatory class I federal areas will experience
improved visibility. For the current 39 PM2.5 nonattainment areas (annual DVs greater than
15|ig/m3) the average population-weighted modeled future-year annual PM2.s DVs will on
average decrease by 0.16 |ig/m3 in 2030. The maximum decrease for future-year annual
PM2.5 DVs over the U.S. will be 0.81 |ig/m3 in 2030.
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Regulatory Impact Analysis
According to air quality modeling performed for this rulemaking, the locomotive and
marine diesel engine emissions controls are expected to provide nationwide improvements in
ozone levels. On a population-weighted basis, the average modeled future-year 8-hour ozone
design values will decrease by 0.85 ppb in 2030. Within projected ozone nonattainment
areas, the average decrease will be 0.62 ppb in 2030. The maximum decrease for future-year
8-hour ozone DVs over the U.S. will be 4.6 ppb in 2030.
While EPA has already adopted many emission control programs that are expected to
reduce both ambient ozone and PM levels over the next two decades, including the Clean Air
Interstate Rule (CAIR) (70 FR 25162, May 12, 2005) and the Clean Air Nonroad Diesel rule
(69 FR 38957, June 29, 2004), the additional PM2.5 and NOX emissions reductions from this
rule will be important to a number of states efforts to attain and maintain the ozone and PM2.5
NAAQS near term and in the decades to come.
2.1 Particulate Matter
In this section we review the health and welfare effects of PM2.5. We also describe air
quality monitoring and modeling data that indicate many areas across the country continue to
be exposed to high levels of ambient PM2.5. Emissions of hydrocarbons (HCs) and NOX from
the engines subject to this rule contribute to these PM concentrations. Information on air
quality was gathered from a variety of sources, including monitored PM concentrations, air
quality modeling done for this rulemaking as well as state and local air quality information.
2.1.1 Science of PM Formation
Particulate matter (PM) represents 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. PMio refers to particles
generally less than or equal to 10 micrometers (|im) in diameter. PM2.5 refers to fine particles,
generally less than or equal to 2.5 jim in diameter. Inhalable (or "thoracic") coarse particles
refer to those particles generally greater than 2.5 jim but less than or equal to 10 jim in
diameter. Ultrafine PM refers to particles less than 100 nanometers (0.1 |im) in diameter.
Larger particles tend to be removed by the respiratory clearance mechanisms, whereas smaller
particles are deposited deeper in the lungs.
Particles span many sizes and shapes and consist of hundreds of different chemicals.
Particles are emitted directly 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.
Particles are made up of different chemical components. The major chemical
components include carbonaceous materials (carbon soot and organic compounds), inorganic
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Air Quality and Resulting Health and Welfare Effects
compounds (including, sulfate and nitrate compounds that usually include ammonium) and a
mix of substances often apportioned to crustal materials such as soil and ash (Figure 2-2).
The different components that make up particle pollution come from specific sources and are
often formed in the atmosphere. As mentioned above, particulate matter includes both
"primary" PM, which is directly emitted into the air, and "secondary" PM. Primary PM
consists of carbonaceous materials emitted from cars, trucks, heavy equipment, forest fires,
some industrial processes and burning waste. It also includes both combustion and process-
related fine metals and larger crustal material from unpaved roads, stone crushing,
construction sites, and metallurgical operations. Secondary PM forms in the atmosphere from
gases. Some of these reactions require sunlight and/or water vapor. Secondary PM includes:
sulfates formed from sulfur dioxide emissions from power plants and industrial facilities;
nitrates formed from nitrogen oxide emissions from cars, trucks, industrial facilities, and
power plants; and organic carbon formed from reactive organic gas emissions from cars,
trucks, industrial facilities, forest fires, and biogenic sources such as trees.
Figure 2-2 Common Sources Contributing to Fine Particle Levels
Cars, trucks, industrial
combustion and
processes, heavy
equipment, wildfires,
wood/waste burning,
Cars, trucks,
industrial combustion, and
power generation
Suspended soils, industrial
metallurgical operations
Mobile power generation,
industrial combustion and
processes
Source: The Particulate Matter Report, USEPA 454-R-04-002, Fall 2004. Carbon reflects both organic
carbon and elemental carbon. Organic carbon accounts for emissions from a wide range of sources including
locomotive and marine diesel engines as well as automobiles, biogenic, gas-powered off-road vehicles, and
wildfires. Elemental carbon is formed from both diesel and gasoline powered sources.
2.1.1.1 Composition of PMi.s in Selected Urban Areas
Note that fine particles can be transported long distances by wind and weather and can
be found in the air thousands of miles from where they formed. The relative contribution of
various chemical components to PM2.5 varies by region of the country, as illustrated in Figure
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Regulatory Impact Analysis
2-3. Data on PM2.5 composition are available from the EPA Speciation Trends Network and
the IMPROVE Network, covering both urban and rural locations across the U.S.
These data show that carbonaceous PM2.5 makes up the major component for PM2.5 in
both urban and rural areas in the Western U.S. Carbonaceous PM2.5 includes both elemental
and organic carbon. Nitrates formed from NOX also play a major role in the western U.S.,
especially in the California area where nitrates are responsible for about a quarter of the
ambient PM2.5 concentrations. Sulfate plays a lesser role in these regions by mass, but it
remains important to visibility impairment. Data for the Eastern and Central U.S. show that
both sulfates and carbonaceous PM2.5 are major contributors to ambient PM2.5 in urban and
rural areas. In some eastern areas, carbonaceous PM2 5 is responsible for up to half of ambient
PM2.s concentrations. Sulfate is also a major contributor to ambient PM2 5 in the Eastern U.S.
and in some areas sulfate makes greater contribution than carbonaceous PM2.5.
Figure 2-3 Average PM2.5 Composition in Urban areas by Region, 2003
WEST
EAST
Northwest
Upper
Midwest
s
Southern
California
s
Southwest
Industrial
Midwest
ฉ
Southeast
e
Northeast
ฉ
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Air Quality and Resulting Health and Welfare Effects
contributions to fine particles are likely dominated by directly emitted particulate matter from
sources such as gasoline and diesel mobile sources, including locomotive and marine diesel
enginesA, industrial facilities (e.g., iron and steel manufacturing, coke ovens, or pulp mills),
and residential wood and waste burning.
Development of effective and efficient emission control strategies to lower PM2.5
ambient concentrations can be aided by determining the relationship between the various
types of emissions sources and elevated levels of PM2.5 at ambient monitoring sites. Source
apportionment analyses such as receptor modeling are useful in this regard by estimating
potential fine particulate regional and local source impacts on a receptor's ambient
concentrations. The goal is to apportion the mass concentrations into components attributable
to the most significant source categories. Receptor modeling techniques are observation-
based models which utilize measured ambient concentrations of PM2.5 species to quantify the
contribution that regional and local sources have at a given receptor which, in this case, is an
ambient monitoring location.8 These techniques may be useful in helping to characterize fine
particulate source contributions to ambient PM2.5 levels; however, there are inherent
limitations including but not limited to the adequacy (e.g., vintage and representativeness) of
existing source profiles in identifying source groups or specific sources, availability,
completeness and representativeness of ambient datasets to fully inform these techniques, and
current scientific understanding and measured data to relate tracer elements to specific
sources, production processes, or activities. Additionally, commingling of similar species
from different sources in one "factor" can make it difficult to relate the "factor" to a particular
source. Furthermore, long-range transport of particles may alter the chemical composition of
specific source emissions, making it more difficult to differentiate sources.1
A literature compilation summarizing source apportionment studies was conducted as
part of a research and preparation program for the CAIR, which was focused on PM2.5
transport.2 Literature selected in this compilation represented key source apportionment
research, focusing primarily on recent individual source apportionment studies in the eastern
U.S. The sources identified are grouped into seven categories: secondary sulfates, mobile,
secondary nitrates, biomass burning, industrial, crustal and salt, and other/not identified.
Some of these studies are based on older ambient databases and more recent ambient data
have shown improvement and reduced levels of ambient PM2.5 concentrations across the U.S.,
especially in the East, which affects the quantitative conclusions one may draw from these
studies. Notably, the relative fraction of sulfates has continued to decrease with the
implementation of the acid rain program and removal of sulfur from motor vehicle fuels.
More routine monitoring for specific tracer compounds that are unique to individual sources
or more time-resolved measurements can lead to better separation of blended "factors" such
A Note that while we believe that the mobile source sector is a substantial contributor to total PM2 5 mass; our
current mobile source inventory is likely underestimated and information on control measures is incomplete.
B Currently, three established receptor models are widely used for source apportionment studies: the Chemical
Mass Balance (CMB) model, UNMIX and Positive Matrix Factorization (PMF). The CMB receptor model relies
on measured source profiles as well as ambient species measurements to produce a source contribution estimate
at the receptor location, while the PMF and UNMIX techniques decompose the ambient measurement data
matrix into source profiles and contributions by utilizing the underlying relationship (i.e., correlations) between
the individually measured species.
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Regulatory Impact Analysis
as secondary commingled sulfates and organic aerosols, the latter which are more attributed to
emissions from vehicles and vegetation. Western studies have focused on sources impacting
both high population areas such as Seattle, Denver, the San Joaquin Valley, Los Angeles, San
Francisco as well as national parks.3'4'5'6'7'8'9'10'11'12
As mentioned previously, the sources of PM2.5 can be categorized as either direct
emissions or contributing to secondary formation. The results of the studies showed that
approximately 20 to 60% of the fine particle mass comes from secondarily formed inorganic
nitrates and sulfates depending on the area of the country, with nitrates predominantly
affecting the West, sulfates in the East and a mixture of the two in the Industrial Midwest.
The precursors of secondary inorganic particles are generally gaseous pollutants such
as sulfur dioxide or oxides of nitrogen, which react with ammonia in the atmosphere to form
ammonium salts. Dominant sources of SO2 include power generation facilities, which are
also sources of NOX, of which mobile sources including locomotive and marine diesel engines
are also major sources. The result of recent and future reductions in precursor emissions from
electrical generation utilities and mobile sources, however, will lead to a reduction in
precursor contributions which would aid in limiting the production of secondary sulfates and
nitrates. Also, reductions in gasoline and diesel fuel sulfur will reduce mobile source SO2
emissions.
In addition, secondary organic carbon aerosols (SOA) also make a large contribution
to the overall total PM2.5 concentration in both the Eastern and Western United States. For
many of the receptor modeling studies, the majority of organic carbon is attributed to mobile
source emissions (including both gasoline and diesel). While vehicles emit organic carbon
particulate, the various organic gases also emitted by these sources react in the atmosphere to
form SOA which shows a correlation to the other secondarily formed aerosols due to common
atmospheric reactions. As Section 2.1.1.4 of this RIA discusses, based on current data,
locomotives and larger marine diesel engines which have similar engine characterizations
emit a relatively large amount of organic PM. Other common sources of the organic gases
which form SOA include vegetation, vehicles, and industrial volatile organic compound
(VOC) and semi-volatile organic compound (SVOC) emissions. However, due to some limits
on data and a lack of specific molecular markers, current receptor modeling techniques have
some difficulty attributing mass to SOA. Therefore, currently available source apportionment
studies may be attributing an unknown amount of SOA in ambient PM to direct emissions of
mobile sources; concurrently, some secondary organic aerosol found in ambient samples may,
as mentioned above, be coming from mobile sources and not be fully reflected in these
assessments. Research is underway to improve estimates of the contribution of SOA to total
fine particulate mass.
While gaseous precursors of PM2.5 are important contributors, urban primary sources
still influence peak local concentrations that exceed the NAAQS, even if their overall
contributions are smaller. The mixture of industrial source contributions to mass vary across
the nation and include emissions from heavy manufacturing such as metal processing (e.g.,
steel production, coke ovens, foundries), petroleum refining, and cement manufacturing,
among others. Mobile source contributions from facilities like ports, rail yards, truck stops,
and heavily-trafficked roads can also have strong, localized air quality impacts. Other sources
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Air Quality and Resulting Health and Welfare Effects
of primary PM2.5 are more seasonal in nature. One such source is biomass burning, which
usually contributes more during the winter months when households burn wood for heat, but
also contributes episodically during summer as a result of forest fires. Other seasonal sources
of primary PM include soil, sea salt and road salting operations that occur in winter months.
The extent of these primary source contributions to local PM2.5 problems varies across the
U.S. and can even vary within an urban area.
2.1.1.3 Regional and Local Source Contributions to Formation of PM2.s
Both local and regional sources contribute to particle pollution. Figure 2-4 shows how
much of the PM2.5 mass can be attributed to local versus regional sources for 13 selected
urban areas. The "urban excess" is estimated by subtracting the measured PM2 5 species at a
regional monitor location c (assumed to be representative of regional background) from those
measured at an urban location.
As shown in Figure 2-4, total carbon mass is the main contributor to urban excess
concentrations in all regions, with Fresno, CA and Birmingham, AL having the largest
observed measures. Larger urban excess of nitrates is seen in the western U.S. and northern
tier cities with Fresno, CA and Salt Lake City, UT having values significantly higher than all
other areas across the nation. These results indicate that local sources of these pollutants are
indeed contributing to the PM2 5 air quality problem in these areas.
Urban and nearby rural PM2 5 concentrations suggest substantial regional contributions
to fine particles in the East.
c Regional concentrations are derived from the rural IMPROVE monitoring network Interagency Monitoring of
Protected Visual Environments. See http://vista.cira.colostate.edu/improve.
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Regulatory Impact Analysis
Figure 2-4. Estimated "Urban Excess" of 13 Urban Areas by PM2.5 Species Component
nJLL q
Baltimore
nchmond
Note: Total Carbon Mass (TCM) is the sum of Organic Carbon (OC) and Elemental Carbon (EC). In
this graph, the light grey is OC and the dark grey is EC. See: Turpin, B. and H-J, Lim, 2001: Species
contributions to PM25 mass concentrations: Revisiting common assumptions for estimating organic mass,
Atmospheric Environment, 35, 602-610.
Regional pollution contributes more than half of total PM25 concentrations. As
expected for a predominately regional pollutant, only a modest urban excess is observed for
sulfates. Rural background PM2.5 concentrations are high in the East and are somewhat
uniform over large geographic areas. These regional concentrations come from emission
sources such as power plants, natural sources, and urban pollution and can be transported
hundreds of miles and reflect to some extent the denser clustering of urban areas in the East as
compared to the West. The local and regional contributions for the major chemical
components that make up urban PM2.5 are sulfates, carbon, and nitrates.
2.1.1.4 Composition of PMi.s from Locomotive and Marine Diesel Engines
Locomotive and Marine Diesel engines contribute significantly to ambient PM2 5
levels, largely through emissions of carbonaceous PM2.5. As discussed in the previous
section, carbonaceous PM2.5 is a major portion of ambient PM2.5, especially in populous urban
areas. For the medium speed diesel engine commonly used in locomotive and Category 2
marine applications, the majority of the total carbon PM is organic carbon. Locomotive and
marine diesels also emit high levels of NOX which react in the atmosphere to form secondary
PM2.s (namely ammonium nitrate). Locomotive and marine diesel engines also emit SO2 and
HC which form secondary PM2 5 (namely sulfates and organic carbonaceous PM2 5). Figure
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Air Quality and Resulting Health and Welfare Effects
2-5 shows the relative contribution of elemental and organic carbon to PM emissions for
seven Tier 0, Tier 1, and Tier 2 locomotives (four locomotive engines were 2-stroke while 3
locomotive engines were 4- stroke). This recent data, while limited to seven locomotives,
suggest that locomotives, regardless of when they were built, tend to emit a very high level of
organic carbon PM, precisely the type of carbon that appears to be responsible for a high
percentage of the urban excess PM2 5 species across the US.
Figure 2-5: PM emissions for 7 locomotives tested using 2800 ppm sulfur nonroad diesel fuel.
2006 AAR Data
0.600
0.550
0.500
0.<
0.400
0.350
0.300
0.250
0.200
0.150
0.100
0.050
0.000
0.60 g/bhp-hr (Tier 0 PM Standard)
'o
DSulfate PM (mostly sulfuric acid+associated water)
D Organic PM (mostly lube oil)
D Elemental Carbon PM (soot)
0.45 g/bhp-hr (Tier 1 PM Standard)
2.1.2 Health Effects of PM Pollution
As stated in EPA's Particulate Matter Air Quality Criteria Document (PM AQCD),
available scientific findings "demonstrate well that human health outcomes are associated
with ambient PM."D We are relying on the data and conclusions in the PM AQCD and PM
Staff Paper, which reflects EPA's analysis of policy-relevant science from the PM AQCD,
regarding the health effects associated with particulate matter.13'14 We also present additional
recent studies published after the cut-off date for the PM AQCD.E15 Taken together this
D 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.
E 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 EPA, 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
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Regulatory Impact Analysis
information supports the conclusion that PM-related emissions such as those controlled in this
action are associated with adverse health effects. Information on PM-related mortality and
morbidity is presented first, followed by information on near-roadway exposure studies,
marine ports and rail yard exposure studies.
2.1.2.1 Short-term Exposure Mortality and Morbidity Studies
As discussed in the PM AQCD, short-term exposure to PM2 5 is associated with
mortality from cardiopulmonary diseases (PM AQCD, p. 8-305), hospitalization and
emergency department visits for cardiopulmonary diseases (PM AQCD, p. 9-93), increased
respiratory symptoms (PM AQCD, p. 9-46), decreased lung function (PM AQCD Table 8-34)
and physiological changes or biomarkers for cardiac changes (PM AQCD, Section 8.3.1.3.4).
In addition, the PM AQCD describes 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. (PM AQCD,
Section 8.3.4).
Among the studies of effects from short-term exposure to PM2.5, several specifically
address the contribution of mobile sources to short-term PM2.s effects on daily mortality.
These studies indicate that there are statistically significant associations between mortality
and PM related to mobile source emissions (PM AQCD, p.8-85). The analyses incorporate
source apportionment tools into daily mortality studies and are briefly mentioned here.
Analyses incorporating source apportionment by factor analysis with daily time-series studies
of daily death indicated a relationship between mobile source PM2.5 and mortality.16'17
Another recent study in 14 U.S. cities examined the effect of PMi0 exposures on daily hospital
admissions for cardiovascular disease. This study found that the effect of PMio 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.18 These studies provide evidence that PM-related
emissions, specifically from mobile sources, are associated with adverse health effects.
2.1.2.2 Long-term Exposure Mortality and Morbidity Studies
Long-term exposure to elevated ambient PM2.5 is associated with mortality from
cardiopulmonary diseases and lung cancer (PM AQCD, p. 8-307), and effects on the
respiratory system such as decreased lung function or the development of chronic respiratory
disease (PM AQCD, pp. 8-313, 8-314). Of specific importance to this rulemaking, the PM
AQCD also notes 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 (PM AQCD, p. 8-318).
The PM AQCD and PM Staff Paper emphasize the results of two long-term studies,
the Six Cities and American Cancer Society (ACS) prospective cohort studies, based on
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.
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Air Quality and Resulting Health and Welfare Effects
several factors - the inclusion of measured PM data, the fact that the study populations were
similar to the general population, and the fact that these studies have undergone extensive
reanalysis (PM AQCD, p. 8-306, Staff Paper, p.3-18).19'20'21 These studies indicate that there
are significant 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 in the Los Angeles area using a new exposure estimation method that
accounted for variations in concentration within the city.22
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 (PM AQCD, Section 8.3.3.2.3). In another recent publication included in the 2006
Provisional Assessment, investigators in southern California reported the results of a cross-
sectional study of outdoor PM25 and measures of atherosclerosis in the Los Angeles basin.23
The study found significant associations between ambient residential PM2.5 and carotid
intima-media thickness (CIMT), an indicator of subclinical atherosclerosis, an underlying
factor in cardiovascular disease.
2.1.2.3 Roadway-Related Exposure and Health Studies
A recent body of studies reinforces the findings of these PM morbidity and mortality
effects by looking at traffic-related exposures, PM measured along roadways, or time spent in
traffic and adverse health effects. While many of these studies did not measure PM
specifically, they include potential exhaust exposures which include mobile source PM
because they employ indices such as roadway proximity or traffic volumes. One study with
specific relevance to PM2 5 health effects is a study that was done in North Carolina looking at
concentrations of PM2 5 inside police cars and corresponding physiological changes in the
police personnel driving the cars. The authors report significant elevations in markers of
cardiac risk associated with concentrations of PM2.5 inside police cars on North Carolina state
highways.24 A number of studies of traffic-related pollution have shown associations between
fine particles and adverse respiratory outcomes in children who live near major
roadways.25'26'27
2.1.2.4 Marine Ports and Rail Yard Studies
Recently, new studies from the State of California provide evidence that PM2 5
emissions within marine ports and rail yards can contribute significantly to elevated ambient
concentrations near these sources28'29 and that a substantial number of people experience
exposure to fresh locomotive and marine diesel engine emissions, raising potential health
concerns. Additional information on marine port and rail yard emissions and potential health
effects can be found in Section 2.4 of this RIA.
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Regulatory Impact Analysis
2.1.3 Current PM2.5 Levels
EPA has recently amended the NAAQS for PM2.5 (71 FR 61144, October 17, 2006).
The final PM NAAQS rule addressed revisions to the primary and secondary NAAQS for
PM2.5 to provide increased protection of public health and welfare, respectively. The primary
PM2.5 NAAQS includes a short-term (24-hour) and a long-term (annual) standard. The level
of the 24-hour PM2.5 NAAQS has been revised from 65 ug/m3to 35 ug/m3 to provide
increased protection against health effects associated with short-term exposures to fine
particles. The current form of the 24-hour PM2.5 standard was retained (e.g., based on the
98th percentile concentration averaged over three years). The level of the annual PM2.5
NAAQS was retained at 15ug/m3, continuing protection against health effects associated with
long-term exposures. The current form of the annual PM2.5 standard was retained as an
annual arithmetic mean averaged over three years, however, the following two aspects of the
spatial averaging criteria were narrowed: (1) the annual mean concentration at each site will
now be within 10 percent of the spatially averaged annual mean, and (2) the daily values for
each monitoring site pair will now yield a correlation coefficient of at least 0.9 for each
calendar quarter.
With regard to the secondary standards for PM2.5, EPA has revised these standards to
be identical in all respects to the revised primary standards. Specifically, EPA has revised the
current 24-hour PM2.5 secondary standard by making it identical to the revised 24-hour PM2.5
primary standard and retained the annual PM2.5 secondary standard. This suite of secondary
PM2.5 standards is intended to provide protection against PM-related public welfare effects,
including visibility impairment, effects on vegetation and ecosystems, and material damage
and soiling.
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.
In 2005, EPA designated 39 nonattainment areas for the 1997 PM2.5 NAAQS based on air
quality design values and a number of other factors (70 FR 943, January 5, 2005; 70 FR
19844, April 14, 2005).F These areas are comprised of 208 full or partial counties with a total
population exceeding 88 million. The 1997 PM2.5 nonattainment counties, areas and
populations, as of October 2007, are listed in Appendix 2A to this RIA. The 1997 PM2.5
NAAQS was recently revised and the 2006 PM2.5 NAAQS became effective on December 18,
2006. Nonattainment areas will be designated with respect to the 2006 PM2.5 NAAQS in
early 2010. Table 2-1 provides an estimate, based on 2003-05 air quality data, of the counties
violating the 2006 PM2.5 NAAQS.
F The full details involved in calculating a PM2 5 design value are given in Appendix N of 40 CFR Part 50.
2-14
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Air Quality and Resulting Health and Welfare Effects
Table 2-1 Counties violating the 2006 PM2.S NAAQS based on 2003-2005 Air Quality Data
Fine Particle Standards:
Current Nonattainment Areas and Other Violated Counties
1997 PM2.5
designated
2006 PM2.5
monitors6
Standards: 39 areas currently
Standards: Counties with violating
Total
Number of Counties
208
49
257
Population"
88,394,000
18,198,676
106,592,676
Notes:
The areas designated as nonattainment for the 2006 PM2 5 NAAQS will be based on three years of air quality
data. Also, the county numbers in the summary table include only the counties with monitors violating the 2006
PM2 5 NAAQS. The monitored county violations may be an underestimate of the number of counties and
populations that will eventually be included in areas with multiple counties designated nonattainment.
As can be seen in Figure 2-1 ambient PM2 5 levels exceeding the 1997 PM2 5 NAAQS
are widespread throughout the country. States with PM2 5 nonattainment areas will be
required to take action to bring those areas into compliance in the future. Most PM2.5
nonattainment areas will be 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.0 The
attainment dates associated with the potential nonattainment areas based on the 2006 PM2 5
NAAQS would likely be in the 2015 to 2020 timeframe. The emission standards being
finalized in this action become effective between 2008 and 2015. Therefore, the PM2.s and
PM2 5 precursor inventory reductions in this action will be useful for states to attain or
maintain the PM2.5 NAAQS.
2.1.4 Projected PM2.5 Levels
In conjunction with this rulemaking, we performed a series of PM2 5 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 locomotive/marine diesel engine controls, 2030
baseline projection, and 2030 baseline projection with locomotive/marine diesel engine
controls. Information on the air quality modeling methodology is contained in Section 2.3 as
well as the air quality modeling technical support document (AQ TSD). In the following
sections we describe projected PM2 5 levels in the future with and without the controls being
finalized in this action.
2.1.4.1 Projected PMi.s Levels without this Rulemaking
Even with the implementation of all current state and federal regulations, including the
CAIR Rule, the NOX SIP call, nonroad and on-road diesel rules and the Tier 2 rule, there are
The EPA finalized PM25 attainment and nonattainment areas in April 2005. The EPA finalized the PM
Implementation rule in November 2005 (70 FR 65984, Nov. 5, 2005).
2-15
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Regulatory Impact Analysis
projected to be U.S. counties violating the 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 this final rule projects that in 2020,
with all current controls in effect, up to 11 counties, with a population of 24 million people,
may not attain the annual standard of 15 |ig/m3. This does not account for additional areas
that have air quality measurements within 10 percent of the PM2.5 standard. These areas,
although not violating the standard, will also benefit from the emissions reductions, ensuring
long term maintenance of the PM NAAQS. For example, in 2020, an additional 16 million
people are projected to live in 13 counties that have air quality measurements within 10
percent of the 2006 PM NAAQS. This modeling supports the conclusion that there are a
substantial number of counties across the US projected to experience PM2.5 concentrations at
or above the PM2.5 NAAQS into the future. A number of state governments and state
organizations have told EPA that they need the reductions from this rule in order to be able to
attain or maintain the 1997 PM2.5 standards as well as to attain the 2006 PM2.5NAAQS.30
Emission reductions from locomotive and marine diesel engines will be helpful for these
counties in attaining and maintaining the PM2.5 NAAQS.
2.1.4.2 Projected PM2.5 Levels With this Rulemaking
The impacts of the locomotive/marine diesel engine controls were determined by
comparing the model results in the future year control runs against the baseline simulations of
the same year. According to air quality modeling performed for this rulemaking, the
locomotive and marine diesel engine standards are expected to provide nationwide
improvements in PM2 5 levels. On a population-weighted basis, the average modeled future-
year annual PM2.5 design value (DV) for all counties is expected to decrease by 0.06 |ig/m3 in
2020 and 0.12 |ig/m3 in 2030. In counties predicted to have annual PM2 5 design values
greater than 15 |ig/m3 the average decrease will be somewhat higher: 0.11 |ig/m3in 2020 and
0.21 |ig/m3 in 2030. In addition, those counties that are within 10 percent of the annual PM2 5
design value will see their average DV decrease by 0.09 |ig/m3 in 2020 and 0.18 |ig/m3 in
2030. The maximum decrease for future-year annual PM2.5 design values will be 0.38 |ig/m3
in 2020 and 0.81 |ig/m3 in 2030. Note that for the current 39 PM2.5 nonattainment areas the
average population weighted future-year annual PM2 5 design value will on average decrease
by 0.08 |ig/m3 in 2020 and by 0.16 |ig/m3 in 2030.
Figure 2-6 illustrates the geographic impact of the locomotive and marine diesel
engine controls on annual PM2 5 design values in 2030. The greatest PM2 5 reductions are
projected to occur in the gulf coast region where in 2030 four counties will experience
reductions in their annual PM2.5 design values of 0.50 to 1.00 |ig/m3. The twenty counties
experiencing PM2.5 reductions between 0.25 and 0.49 |ig/m3 are geographically dispersed
along the midwest, the pacific northwest, the gulf coast and southern California An
additional 143 counties spread across the US will see a decrease in their projected annual
PM2.s DV ranging from 0.10 to 0.24 |ig/m3. A complete set of maps illustrating the
geographic impact of various alternatives explored as part of this rulemaking are available in
the Air Quality Modeling TSD for this rulemaking.
2-16
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Air Quality and Resulting Health and Welfare Effects
Legend
Number of Counties
| |-1.00 to-0.50 4
Q^ -0.49 to -0.25 20
|-0.24 to-0.10 143
$$Jti\ -ฐ-09 to -ฐ-05 193
| -0.04 to 0.00 196
> 0.00 0
Differences due to scenario 2030cc Locomarine
Figure 2-6 Impact of Locomotive/Marine controls on annual PM2.5 Design Values (DV) in 2030
2-17
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Regulatory Impact Analysis
Table 2-2 lists the counties with projected annual PM2.5 design values that violate or
are within 10 percent 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 2-2.
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.
Table 2-2 Counties with 2020 Projected Annual PM2.5Design Values in Violation or within 10 percent of
the Annual PM2.5 Standard
State
Alabama
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
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
PM2.5
DV
(ug/m3)
18.36
20.02
14.44
21.77
18.77
23.16
16.47
18.27
27.15
24.63
15.65
14.84
16.49
21.33
18.29
17.06
17.27
16.58
19.32
15.85
17.16
18.36
20.99
17.30
2020 modeling
projections of
annual PM25DV
(ug/m3)
base
V
X
V
X
X
X
X
X
X
X
V
V
V
X
V
V
V
V
X
V
V
V
X
V
control
V
X
V
X
X
X
X
X
X
X
V
V
V
X
V
V
V
V
X
V
V
V
X
V
2020
Population
673,910
1,012,929
183,835
851,948
172,415
10,067,663
263,184
3,690,329
2,173,672
2,302,697
3,715,268
711,938
579,349
464,651
898,342
5,369,914
276,838
717,730
1,879,876
20,078
1,560,060
1,305,880
1,234,865
30,461
2-18
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Air Quality and Resulting Health and Welfare Effects
2.1.5 Environmental Effects of PM Pollution
In this section we discuss public welfare effects of PM and its precursors including
visibility impairment, atmospheric deposition, and materials damage and soiling.
2.1.5.1 Visibility Impairment
Visibility can be defined as the degree to which the atmosphere is transparent to
visible light.31 Visibility impairment manifests in two principal ways: as local visibility
impairment and as regional haze.32 Local visibility impairment may take the form of a
localized plume, a band or layer of discoloration appearing well above the terrain as a result
of complex local meteorological conditions. Alternatively, local visibility impairment may
manifest as an urban haze, sometimes referred to as a "brown cloud." This urban haze is
largely caused by emissions from multiple sources in the urban area and is not typically
attributable to only one nearby source or to long-range transport. The second type of
visibility impairment, regional haze, usually results from multiple pollution sources spread
over a large geographic region. Regional haze can impair visibility over large regions and
across states.
Visibility is important because it has direct significance to people's enjoyment of daily
activities in all parts of the country. Individuals value good visibility for the well-being it
provides them directly, where they live and work and in places where they enjoy recreational
opportunities. Visibility is also highly valued in significant natural areas such as national
parks and wilderness areas, and special emphasis is given to protecting visibility in these
areas.
Fine particles are the major cause of reduced visibility in parts of the United States.
To address the welfare effects of PM on visibility, EPA sets secondary PM2.5 standards which
work in conjunction with the regional haze program. The secondary (welfare-based) PM2.5
NAAQS is equal to the suite of primary (health-based) PM2.5 NAAQS. The regional haze
rule (64 FR 35714, July 1999) was put in place to protect the visibility in mandatory class I
federal areas. These areas are defined in Section 162 of the Act as those national parks
exceeding 6,000 acres, wilderness areas and memorial parks exceeding 5,000 acres, and all
international parks which were in existence on August 7, 1977. A list of the mandatory class I
federal areas is included in Appendix 2D. Visibility is impaired in both PM2.5 nonattainment
areas and mandatory class I federal areas.
Control of locomotive and marine diesel engine emissions will improve visibility
across the nation. The locomotive and marine diesel engines subject to this rule either
directly emit PM2.5 or emit PM precursors which contribute to the formation of secondary
PM2.5 and thus contribute to visibility impairment. In the next sections we present current
information and projected estimates about visibility impairment related to ambient PM2.5
levels across the country and visibility impairment in mandatory class I federal areas. We
conclude that visibility will continue to be impaired in the future and the emission reductions
from this rule will help improve visibility conditions across the country and in mandatory
class I federal areas. For more information on visibility see the PM AQCD as well as the
2005 PM Staff Paper.33'34
2-19
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Regulatory Impact Analysis
2.1.5.1.1 Current Visibility Impairment in PM2.s Nonattainment Areas
As mentioned above, the secondary PM2 5 standards were set as equal to the suite of
primary PM2.5 standards. Almost 90 million people live in the 208 counties that are in
nonattainment for the 1997 PM2 5 NAAQS, (see Appendix 2A for the complete list of current
nonattainment areas). These populations, as well as large numbers of individuals who travel
to these areas can experience visibility impairment.
2.1.5.1.2 Current Visibility Impairment at Mandatory Class I Federal Areas
Detailed information about current and historical visibility conditions in mandatory
class I federal areas is summarized in the EPA Report to Congress and the 2002 EPA Trends
Report.35'36 The conclusions draw upon the Interagency Monitoring of Protected Visual
Environments (IMPROVE) network data. One of the objectives of the IMPROVE monitoring
network program is to provide regional haze monitoring representing all mandatory class I
federal areas where practical. The National Park Service report also describes the state of
national park visibility conditions and discusses the need for improvement.37
The regional haze rule requires states to establish goals for each affected mandatory
class I federal area that 1) improves visibility on the haziest days (20% most impaired days),
2) ensures no degradation occurs on the cleanest days (20% least impaired days), and 3)
achieves natural background visibility levels by 2064. Although there have been general
trends toward improved visibility, progress is still needed on the haziest days. Specifically, as
discussed in the 2002 EPA Trends Report, without the effects of pollution a natural visual
range in the United States is approximately 75 to 150 km in the East and 200 to 300 km in the
West. In 2001, the mean visual range for the worst days was 29 km in the East and 98 km in
the West.38
2.1.5.1.3 Future Visibility Impairment
Additional emission reductions will be needed from a broad set of sources, including
those in this action, as part of the overall strategy to achieve the visibility goals of the Act and
the regional haze program.
Modeling was used to project visibility conditions in 133 mandatory class I federal
areas across the US in 2020 and 2030 as a result of the locomotive and marine diesel engine
standards. The AQ modeling TSD and Section 2.3 of this RIA provide information on the
modeling methodology. The results indicate that improvements in visibility will occur in all
133 mandatory class I federal areas, although these areas will continue to have annual average
deciview levels above background. Table 2-3 below indicates the current monitored deciview
values, the natural background levels each area is attempting to reach, and also the projected
deciview values in 2020 and 2030 with and without the standards. In 2030, the greatest
visibility improvement due to this rule will occur at San Gorgonio (0.24 deciview) located in
San Bernadino County, California.
2-20
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Air Quality and Resulting Health and Welfare Effects
Table 2-3 Current (2002) and Future (2020 and 2030) Projected Visibility Conditions With and Without
Locomotive and Marine Diesel Rule in Mandatory Class I Federal Areas (20% Worst Days)
Mandatory Class 1
Federal Area Name
Acadia NP
Agua Tibia Wilderness
Alpine Lake Wilderness
Anaconda-Pintler
Wilderness
Arches NP
Badlands NP
Bandelier NM
Big Bend NP
Black Canyon of the
Gunnison NM
Bosque del Apache
Bob Marshall
Wilderness
Bryce Canyon NP
Bridger Wilderness
Brigantine
Cabinet Mountains
Wilderness
Caney Creek
Wilderness
Canyonlands NP
Caribou Wilderness
Carlsbad Caverns NP
Chassahowitzka
Chiricahua NM
Chiricahua Wilderness
Cohutta Wilderness
Crater Lake NP
Craters of the Moon NM
Cucamonga Wilderness
Desolation Wilderness
Diamond Peak
Wilderness
Dome Land Wilderness
Dolly Sods Wilderness
Eagle Cap Wilderness
Eagles Nest Wilderness
Emigrant Wilderness
Everglades NP
Fitzpatrick Wilderness
Flat Tops Wilderness
Galiuro Wilderness
State
ME
CA
WA
MT
UT
SD
NM
TX
CO
NM
MT
UT
WY
NJ
MT
AR
UT
CA
TX
FL
AZ
AZ
GA
OR
ID
CA
CA
OR
CA
WV
OR
CO
CA
FL
WY
CO
AZ
2002
Baseline
Visibility
(dv)a
22.89
23.50
17.84
13.41
11.24
17.14
12.22
17.30
10.33
13.80
14.48
11.65
11.12
29.01
14.09
26.36
11.24
14.15
17.19
26.09
13.43
13.43
30.30
13.74
14.00
19.94
12.63
13.74
19.43
29.04
18.57
9.61
17.63
22.30
11.12
9.61
13.43
2020
Base
Case
(dv)
19.79
21.23
16.77
13.15
11.14
15.87
11.43
16.15
9.80
12.96
14.14
11.36
10.81
24.88
13.57
22.11
10.84
13.62
15.93
21.96
13.09
13.09
23.36
13.29
13.00
17.42
12.15
13.25
18.37
22.38
17.86
9.05
17.22
19.75
10.86
9.31
13.08
2020
Control
Case
(dv)
19.77
21.14
16.71
13.14
11.11
15.84
11.41
16.13
9.79
12.90
14.13
11.34
10.81
24.85
13.54
22.05
10.81
13.60
15.92
21.94
13.09
13.09
23.33
13.27
12.97
17.36
12.13
13.20
18.34
22.35
17.83
9.03
17.21
19.77
10.85
9.31
13.07
2030
Base
Case
(dv)
19.86
21.16
16.72
13.13
11.05
15.80
11.38
16.18
9.79
12.94
14.11
11.34
10.80
24.99
13.52
22.06
10.83
13.55
15.92
21.96
13.10
13.10
23.34
13.26
12.90
17.14
12.15
13.22
18.20
22.38
17.79
8.99
17.24
19.97
10.86
9.32
13.11
2030
Control
Case
(dv)
19.81
20.94
16.60
13.11
11.03
15.75
11.34
16.15
9.77
12.81
14.08
11.31
10.80
24.91
13.46
21.92
10.82
13.51
15.90
21.91
13.09
13.09
23.28
13.20
12.82
17.10
12.12
13.12
18.11
22.33
17.71
8.96
17.19
19.94
10.84
9.31
13.09
Natural
Bckgrnd
(dv)
12.43
7.64
8.43
7.43
6.43
8.06
6.26
7.16
6.24
6.73
7.74
6.86
6.58
12.24
7.53
11.58
6.43
7.31
6.68
11.21
7.21
7.21
11.14
7.84
7.53
7.06
6.12
7.84
7.46
10.39
8.92
6.54
7.64
12.15
6.58
6.54
7.21
2-21
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Regulatory Impact Analysis
Mandatory Class 1
Federal Area Name
Gates of the Mountains
Wilderness
Gearhart Mountain
Wilderness
Gila Wilderness
Glacier Peak
Wilderness
Goat Rocks Wilderness
Grand Canyon NP
Great Gulf Wilderness
Great Sand Dunes NM
Great Smoky Mountains
NP
Grand Teton NP
Guadalupe Mountains
NP
Hells Canyon
Wilderness
Hercules-Glades
Wilderness
Hoover Wilderness
Isle Royale NP
Jarbidge Wilderness
James River Face
Wilderness
Joshua Tree NM
Joyce-Kilmer-Slickrock
Wilderness
Kalmiopsis Wilderness
Lava Beds NM
La Garita Wilderness
Lassen Volcanic NP
Linville Gorge
Wilderness
Lostwood
Lye Brook Wilderness
Maroon Bells-
Snowmass Wilderness
Mammoth Cave NP
Mazatzal Wilderness
Medicine Lake
Mesa Verde NP
Mission Mountains
Wilderness
Mount Hood Wilderness
Mount Jefferson
Wilderness
State
MT
OR
NM
WA
WA
AZ
NH
CO
TN
WY
TX
OR
MO
CA
Ml
NV
VA
CA
TN
OR
CA
CO
CA
NC
ND
VT
CO
KY
AZ
MT
CO
MT
OR
OR
2002
Baseline
Visibility
(dv)a
11.29
13.74
13.11
13.96
12.76
11.66
22.82
12.78
30.28
11.76
17.19
18.55
26.75
12.87
20.74
12.07
29.12
19.62
30.28
15.51
15.05
10.33
14.15
28.77
19.57
24.45
9.61
31.37
13.35
17.72
13.03
14.48
14.86
15.33
2020
Base
Case
(dv)
10.92
13.39
12.55
13.62
12.06
11.13
19.48
12.36
23.96
11.36
15.89
17.26
23.00
12.73
19.15
11.86
23.43
17.95
23.46
15.00
14.45
9.90
13.56
22.48
17.73
21.10
9.24
25.53
12.74
16.25
12.40
14.06
14.19
14.80
2020
Control
Case
(dv)
10.91
13.37
12.54
13.60
12.05
11.09
19.45
12.36
23.93
11.35
15.88
17.20
22.93
12.72
19.10
11.86
23.34
17.93
23.43
14.98
14.42
9.89
13.54
22.45
17.70
21.08
9.24
25.48
12.72
16.22
12.39
14.04
14.13
14.77
2030
Base
Case
(dv)
10.89
13.36
12.55
13.69
12.07
11.15
19.50
12.37
23.93
11.33
15.89
17.18
22.96
12.75
19.16
11.86
23.43
17.85
23.43
14.97
14.40
9.89
13.48
22.47
17.67
21.17
9.24
25.54
12.77
16.18
12.40
14.02
14.28
14.82
2030
Control
Case
(dv)
10.87
13.33
12.54
13.67
12.03
11.08
19.46
12.36
23.86
11.31
15.86
17.04
22.81
12.74
19.04
11.85
23.26
17.71
23.37
14.93
14.32
9.88
13.43
22.41
17.60
21.11
9.24
25.44
12.73
16.12
12.37
13.99
14.14
14.76
Natural
Bckgrnd
(dv)
6.45
7.84
6.69
8.01
8.36
7.14
11.99
6.66
11.24
6.51
6.68
8.32
11.30
7.91
12.37
7.87
11.13
7.19
11.24
9.44
7.86
6.24
7.31
11.22
8.00
11.73
6.54
11.08
6.68
7.90
6.83
7.74
8.44
8.79
2-22
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Air Quality and Resulting Health and Welfare Effects
Mandatory Class 1
Federal Area Name
Mokelumne Wilderness
Mountain Lakes
Wilderness
Moosehorn
Mount Rainier NP
Mount Washington
Wilderness
Mount Zirkel Wilderness
North Absaroka
Wilderness
North Cascades NP
Okefenokee
Olympic NP
Otter Creek Wilderness
Pasayten Wilderness
Pecos Wilderness
Petrified Forest NP
Pine Mountain
Wilderness
Pinnacles NM
Point Reyes NS
Presidential Range-Dry
River Wilderness
Rawah Wilderness
Red Rock Lakes
Redwood NP
Roosevelt Campobello
International Park
Cape Romain
Rocky Mountain NP
Salt Creek
San Gabriel Wilderness
San Gorgonio
Wilderness
Saguaro NM
San Jacinto Wilderness
St. Marks
San Pedro Parks
Wilderness
Sawtooth Wilderness
Scapegoat Wilderness
Selway-Bitterroot
Wilderness
Seney
Shenandoah NP
Sierra Ancha
State
CA
OR
ME
WA
OR
CO
WY
WA
GA
WA
WV
WA
NM
AZ
AZ
CA
CA
NH
CO
WY
CA
ME
SC
CO
NM
CA
CA
AZ
CA
FL
NM
ID
MT
MT
Ml
VA
AZ
2002
Baseline
Visibility
(dv)a
12.63
13.74
21.72
18.24
15.33
10.52
11.45
13.96
27.13
16.74
29.04
15.23
10.41
13.21
13.35
18.46
22.81
22.82
10.52
11.76
18.45
21.72
26.48
13.83
18.03
19.94
22.17
14.83
22.17
26.03
10.17
13.78
14.48
13.41
24.16
29.31
13.67
2020
Base
Case
(dv)
12.32
13.26
18.65
17.27
14.77
10.06
11.17
13.58
23.46
15.85
22.31
14.85
10.01
12.90
12.59
17.37
22.01
19.48
10.04
11.44
17.89
18.47
22.77
13.10
16.61
17.30
20.28
14.50
19.92
21.84
9.53
13.64
14.17
13.06
21.77
22.83
13.22
2020
Control
Case
(dv)
12.30
13.24
18.63
17.24
14.75
10.05
11.16
13.57
23.42
15.82
22.29
14.84
10.00
12.83
12.58
17.36
21.99
19.45
10.04
11.43
17.86
18.45
22.74
13.08
16.59
17.25
20.22
14.47
19.87
21.82
9.52
13.63
14.16
13.04
21.72
22.80
13.20
2030
Base
Case
(dv)
12.34
13.23
18.68
17.27
14.78
10.07
11.15
13.68
23.50
15.95
22.32
14.83
10.02
12.87
12.59
17.16
21.87
19.50
10.06
11.42
17.86
18.51
22.77
13.06
16.58
17.01
19.94
14.49
19.61
21.88
9.53
13.64
14.14
13.02
21.78
22.83
13.18
2030
Control
Case
(dv)
12.31
13.17
18.64
17.21
14.72
10.04
11.13
13.67
23.40
15.89
22.27
14.81
10.01
12.75
12.54
17.09
21.79
19.46
10.04
11.39
17.79
18.47
22.71
13.01
16.52
16.93
19.70
14.44
19.55
21.83
9.52
13.63
14.12
12.99
21.66
22.76
13.15
Natural
Bckgrnd
(dv)
6.12
7.84
12.01
8.55
8.79
6.44
6.86
8.01
11.44
8.44
10.39
8.26
6.44
6.49
6.68
7.99
15.77
11.99
6.44
6.51
13.91
12.01
12.12
7.24
6.81
7.06
7.30
6.46
7.30
11.53
6.08
6.43
7.74
7.43
12.65
11.35
6.59
2-23
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Regulatory Impact Analysis
Mandatory Class 1
Federal Area Name
Wilderness
Sipsey Wilderness
South Warner
Wilderness
Strawberry Mountain
Wilderness
Swanquarter
Sycamore Canyon
Wilderness
Teton Wilderness
Three Sisters
Wilderness
Thousand Lakes
Wilderness
Theodore Roosevelt NP
UL Bend
Upper Buffalo
Wilderness
Ventana Wilderness
Voyageurs NP
Washakie Wilderness
West Elk Wilderness
Weminuche Wilderness
White Mountain
Wilderness
Mount Adams
Wilderness
Wheeler Peak
Wilderness
Wind Cave NP
Wichita Mountains
Wolf Island
Yellowstone NP
Yosemite NP
Zion NP
State
AL
CA
OR
NC
AZ
WY
OR
CA
ND
MT
AR
CA
MN
WY
CO
CO
NM
WA
NM
SD
OK
GA
WY
CA
UT
2002
Baseline
Visibility
(dv)a
29.03
15.05
18.57
25.49
15.25
11.76
15.33
14.15
17.74
15.14
26.27
18.46
19.27
11.45
9.61
10.33
13.70
12.76
10.41
15.84
23.81
27.13
11.76
17.63
13.24
2020
Base
Case
(dv)
23.78
14.61
17.77
21.17
14.96
11.41
14.84
13.54
16.65
14.66
22.41
17.67
17.62
11.18
9.24
9.86
13.07
12.03
9.96
14.94
20.67
23.40
11.39
17.16
12.96
2020
Control
Case
(dv)
23.73
14.59
17.73
21.15
14.94
11.40
14.82
13.52
16.54
14.64
22.35
17.64
17.58
11.17
9.24
9.86
13.05
12.01
9.95
14.91
20.62
23.37
11.38
17.14
12.92
2030
Base
Case
(dv)
23.77
14.57
17.69
21.20
14.98
11.39
14.84
13.46
16.61
14.62
22.34
17.67
17.53
11.16
9.24
9.86
13.07
12.02
9.97
14.94
20.68
23.40
11.36
17.15
12.89
2030
Control
Case
(dv)
23.66
14.52
17.60
21.15
14.93
11.36
14.79
13.41
16.42
14.58
22.19
17.62
17.43
11.14
9.23
9.86
13.04
11.97
9.96
14.87
20.55
23.32
11.34
17.11
12.81
Natural
Bckgrnd
(dv)
10.99
7.86
8.92
11.94
6.69
6.51
8.79
7.31
7.79
8.16
11.57
7.99
12.06
6.86
6.54
6.24
6.86
8.36
6.44
7.71
7.53
11.44
6.51
7.64
6.99
The level of visibility impairment in an area is based on the light-extinction coefficient and a unitless 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.
2.1.5.2 Particulate Matter Deposition
Paniculate matter contributes to adverse effects on vegetation and ecosystems, and to
soiling and materials damage. These welfare effects result predominately from exposure to
excess amounts of specific chemical species, regardless of their source or predominant form
2-24
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Air Quality and Resulting Health and Welfare Effects
(particle, gas or liquid). Reflecting this fact, the PM AQCD concludes that regardless of size
fractions, particles containing nitrates and sulfates have the greatest potential for widespread
environmental significance, while effects are also related to other chemical constituents found
in ambient PM, such as trace metals and organics. The following characterizations of the
nature of these welfare effects are based on the information contained in the PM AQCD and
PM Staff Paper.
2.1.5.2.1 Deposition of Nitrates and Sulfates
At current ambient levels, risks to vegetation from short-term exposures to dry
deposited particulate nitrate or sulfate are low. However, when found in acid or acidifying
deposition, such particles do have the potential to cause direct leaf injury. Specifically, the
responses of forest trees to acid precipitation (rain, snow) include accelerated weathering of
leaf cuticular surfaces, increased permeability of leaf surfaces to toxic materials, water, and
disease agents; increased leaching of nutrients from foliage; and altered reproductive
processesall which serve to weaken trees so that they are more susceptible to other stresses
(e.g., extreme weather, pests, pathogens). Acid deposition with levels of acidity associated
with the leaf effects described above are currently found in some locations in the eastern
U.S.39 Even higher concentrations of acidity can be present in occult depositions (e.g., fog,
mist or clouds) which more frequently impacts higher elevations. Thus, the risk of leaf injury
occurring from acid deposition in some areas of the eastern U.S. is high. Nitrogen deposition
has also been shown to impact ecosystems in the western U.S. A study conducted in the
Columbia River Gorge National Scenic Area (CRGNSA), located along a portion of the
Oregon/Washington border, indicates that lichen communities in the CRGNSA have shifted
to a higher proportion of nitrophilous species and the nitrogen content of lichen tissue is
elevated.40 Lichens are sensitive indicators of nitrogen deposition effects to terrestrial
ecosystems and the lichen studies in the Columbia River Gorge clearly show that ecological
effects from air pollution are occurring.
Some of the most significant detrimental effects associated with excess reactive
nitrogen deposition are those associated with a syndrome known as nitrogen saturation.
These effects include: (1) decreased productivity, increased mortality, and/or shifts in plant
community composition, often leading to decreased biodiversity in many natural habitats
wherever atmospheric reactive nitrogen deposition increases significantly and critical
thresholds are exceeded; (2) leaching of excess nitrate and associated base cations from soils
into streams, lakes, and rivers, and mobilization of soil aluminum; and (3) fluctuationof
ecosystem processes such as nutrient and energy cycles through changes in the functioning
and species composition of beneficial soil organisms.41
In the U.S. numerous forests now show severe symptoms of nitrogen saturation.
These forests include: the northern hardwoods and mixed conifer forests in the Adirondack
and Catskill Mountains of New York; the red spruce forests at Whitetop Mountain, Virginia,
and Great Smoky Mountains National Park, North Carolina; mixed hardwood watersheds at
Fernow Experimental Forest in West Virginia; American beech forests in Great Smoky
Mountains National Park, Tennessee; mixed conifer forests and chaparral watersheds in
southern California and the southwestern Sierra Nevada in Central California; the alpine
2-25
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Regulatory Impact Analysis
tundra/subalpine conifer forests of the Colorado Front Range; and red alder forests in the
Cascade Mountains in Washington.
Excess nutrient inputs into aquatic ecosystems (i.e. streams, rivers, lakes, estuaries or
oceans) either from direct atmospheric deposition, surface runoff, or leaching from nitrogen
saturated soils into ground or surface waters can contribute to conditions of severe water
oxygen depletion; eutrophication and algae blooms; altered fish distributions, catches, and
physiological states; loss of biodiversity; habitat degradation; and increases in the incidence
of disease.
Severe and persistent eutrophi cation often directly impacts human activities. For
example, losses in the nation's fishery resources may be directly caused by fish kills
associated with low dissolved oxygen and toxic blooms. Declines in tourism occur when low
dissolved oxygen causes noxious smells and floating mats of algal blooms create unfavorable
aesthetic conditions. Risks to human health increase when the toxins from algal blooms
accumulate in edible fish and shellfish, and when toxins become airborne, causing respiratory
problems due to inhalation. According to a NOAA report, more than half of the nation's
estuaries have moderate to high expressions of at least one of these symptoms - an indication
that eutrophi cation is well developed in more than half of U.S. estuaries. 42
2.1.5.2.2 Deposition of Heavy Metals
Heavy metals, including cadmium, copper, lead, chromium, mercury, nickel and zinc,
have the greatest potential for influencing forest growth (PM AQCD, p. 4-87).43 Investigation
of trace metals near roadways and industrial facilities indicate that a substantial load of heavy
metals can accumulate on vegetative surfaces. Copper, zinc, and nickel have been
documented to cause direct toxicity to vegetation under field conditions (PM AQCD, p. 4-75).
Little research has been conducted on the effects associated with mixtures of contaminants
found in ambient PM. 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 (PM AQCD, p. 4-76). This hypothesized
relationship/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 the northeastern United
States (PM AQCD 4-76,77).44 Contamination of plant leaves by heavy metals can lead to
elevated soil levels. Trace metals absorbed into the plant frequently bind to the leaf tissue,
and then are lost when the leaf drops (PM AQCD, p. 4-75). As the fallen leaves decompose,
the heavy metals are transferred into the soil.45'46
2-26
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Air Quality and Resulting Health and Welfare Effects
The environmental sources and cycling of mercury are currently of particular concern
due to the bioaccumulation and biomagnification of this metal in aquatic ecosystems and the
potent toxic nature of mercury in the forms in which is it ingested by people and other
animals. Mercury is unusual compared with other metals in that it largely partitions into the
gas phase (in elemental form), and therefore has a longer residence time in the atmosphere
than a metal found predominantly in the particle phase. This property enables mercury to
travel far from the primary source before being deposited and accumulating in the aquatic
ecosystem. The major source of mercury in the Great Lakes is from atmospheric deposition,
accounting for approximately eighty percent of the mercury in Lake Michigan.47'48 Over fifty
percent of the mercury in the Chesapeake Bay has been attributed to atmospheric
deposition.49 Overall, the National Science and Technology Council identifies atmospheric
deposition as the primary source of mercury to aquatic systems.50 Forty-four states have
issued health advisories for the consumption offish contaminated by mercury; however, most
of these advisories are issued in areas without a mercury point source.
Elevated levels of zinc and lead have been identified in streambed sediments, and
these elevated levels have been correlated with population density and motor vehicle use.51'52
Zinc and nickel have also been identified in urban water and soils. In addition, platinum,
palladium, and rhodium, metals found in the catalysts of modern motor vehicles, have been
measured at elevated levels along roadsides.53 Plant uptake of platinum has been observed at
these locations.
2.1.5.2.3 Deposition ofPolycyclic Organic Matter
Poly cyclic organic matter (POM) is a byproduct of incomplete combustion and
consists of organic compounds with more than one benzene ring and a boiling point greater
than or equal to 100 degrees centigrade.54 Poly cyclic aromatic hydrocarbons (PAHs) are a
class of POM that contains compounds which are known or suspected carcinogens.
Major sources of PAHs include mobile sources. PAHs in the environment may be
present as a gas or adsorbed onto airborne parti culate matter. Since the majority of PAHs are
adsorbed onto particles less than 1.0 jim in diameter, long range transport is possible.
However, studies have shown that PAH compounds adsorbed onto diesel exhaust particulate
and exposed to ozone have half lives of 0.5 to 1.0 hours.55
Since PAHs are insoluble, the compounds generally are particle reactive and
accumulate in sediments. Atmospheric deposition of particles is believed to be the major
source of PAHs to the sediments of Lake Michigan.56'57 Analyses of PAH deposition in
Chesapeake and Galveston Bay indicate that dry deposition and gas exchange from the
atmosphere to the surface water predominate.58'59 Sediment concentrations of PAHs are high
enough in some segments of Tampa Bay to pose an environmental health threat. EPA funded
a study to better characterize the sources and loading rates for PAHs into Tampa Bay.60
PAHs that enter a water body through gas exchange likely partition into organic rich particles
and can be biologically recycled, while dry deposition of aerosols containing PAHs tend to be
more resistant to biological recycling.61 Thus, dry deposition is likely the main pathway for
PAH concentrations in sediments while gas/water exchange at the surface may lead to PAH
distribution into the food web, leading to increased health risk concerns.
2-27
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Regulatory Impact Analysis
Trends in PAH deposition levels are difficult to discern because of highly variable
ambient air concentrations, lack of consistency in monitoring methods, and the significant
influence of local sources on deposition levels.62 Van Metre et al. noted PAH concentrations
in urban reservoir sediments have increased by 200-300% over the last forty years and
correlate with increases in automobile use.63
Cousins et al. estimate that more than ninety percent of semi-volatile organic
compound (SVOC) emissions in the United Kingdom deposit on soil.64 An analysis of PAH
concentrations near a Czechoslovakian roadway indicated that concentrations were thirty
times greater than background.65
2.1.5.2.4 Materials Damage and Soiling
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.
2.2 Ozone
In this section we review the health and welfare effects of ozone. We also describe the
air quality monitoring and modeling data which indicate that people in many areas across the
country continue to be exposed to high levels of ambient ozone and will continue to be into
the future. Emissions of nitrogen oxides (NOX) and VOCs, of which HC are the major subset,
from the locomotive and marine diesel engines subject to this rule have been shown to
contribute to these ozone concentrations. Information on air quality was gathered from a
variety of sources, including monitored ozone concentrations, air quality modeling forecasts
conducted for this rulemaking, and other state and local air quality information.
The emission reductions from this rule will assist 8-hour ozone nonattainment and
maintenance areas in reaching the standard by each area's respective attainment date, and
maintaining the 8-hour ozone standard in the future. The emission reductions will also help
continue to lower ambient ozone levels and reduce health impacts.
2.2.1 Science of Ozone Formation
Ground-level ozone pollution is formed by the reaction of VOCs and nitrogen oxides
(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, power plants, chemical plants, refineries, makers of consumer
and commercial products, and smaller area sources.
2-28
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Air Quality and Resulting Health and Welfare Effects
The science of ozone formation, transport, and accumulation is complex.66 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 would occur on a single high-temperature
day. Ozone also can be transported into an area from pollution sources found hundreds of
miles upwind, 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 can be lowered by the reaction of nitric oxide 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 are 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 would not be 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 many rural 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.
2.2.2 Health Effects of Ozone Pollution
Exposure to ambient ozone contributes to a wide range of adverse health effects11.
These health effects are well documented and are critically assessed in the EPA ozone air
quality criteria document (ozone AQCD) and EPA staff paper.67'68 We are relying on the data
and conclusions in the ozone AQCD and staff paper, regarding the health effects associated
with ozone exposure.
H 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 concentration but also by the individuals breathing
route and rate.
2-29
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Regulatory Impact Analysis
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. Cell-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. 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 higher ambient ozone
concentrations have been linked to lung function decrements, respiratory symptoms, increased
hospital admissions and emergency room visits for respiratory problems.69' 70'71' 72' 73' 74
Repeated exposure to ozone can increase susceptibility to respiratory infection and lung
inflammation and can aggravate preexisting respiratory diseases, such as asthma.75'76'77'78'79
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 lead to premature aging of the lungs and/or chronic
respiratory illnesses, such as emphysema and chronic bronchitis.80'81'82'83
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.84 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.85 For example, summer camp studies in the Eastern United
States and Southeastern Canada have reported significant reductions in lung function in
children who are active outdoors.86'87'88'89' 90'91' 92' 93 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.94'95'96'97
2.2.3 Current 8-Hour Ozone Levels
The locomotive and marine engine emission reductions will assist 8-hour ozone
nonattainment areas in reaching the standard by each area's respective attainment date and/or
assist in maintaining the 8-hour ozone standard in the future. The current ozone National
Ambient Air Quality Standard (NAAQS) has an 8-hour averaging time.1 The 8-hour ozone
1 EPA's review of the ozone NAAQS is underway, the proposal was published in June 2007 and the final rule is
scheduled for March 2008.
2-30
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Air Quality and Resulting Health and Welfare Effects
NAAQS is met at an ambient air quality monitoring site when the average of the annual
fourth-highest daily maximum 8-hour average ozone concentration over three years is less
than or equal to 0.08 ppm. In the following section we present information on current and
model-projected future 8-hour ozone levels.
A nonattainment area is defined in the CAA as an area that is violating a NAAQS or is
contributing to a nearby area that is violating the NAAQS. EPA designated nonattainment
areas for the 8-hour ozone NAAQS in June 2004. The final rule on Air Quality Designations
and Classifications for the 8-hour Ozone NAAQS (69 FR 23858, April 30, 2004) identifies
the criteria that EPA considered in making the 8-hour ozone nonattainment designations,
including 2001-2003 measured data, air quality in adjacent areas, and other factors/
As of October 10, 2007 there are approximately 144 million people living in 81 areas
designated as nonattainment with the 8-hour ozone NAAQS. There are 366 full or partial
counties that make up the 8-hour ozone nonattainment areas. These numbers do not include
the people living in areas where there is a future risk of failing to maintain or attain the 8-hour
ozone NAAQS. The current 8-hour ozone nonattainment areas, nonattainment counties, and
populations are listed in Appendix 2C to this RIA.
States with 8-hour ozone nonattainment areas are required to take action to bring those
areas into compliance in the future. The maximum attainment date assigned to an ozone
nonattainment area is based on the area's classification. Most 8-hour ozone nonattainment
areas will be required to attain the 8-hour ozone NAAQS in the 2007 to 2013 time frame and
then be required to maintain the 8-hour ozone NAAQS thereafter.K We expect many of the 8-
hour ozone nonattainment areas will need to adopt additional emissions reduction programs to
attain and maintain the 8-hour ozone NAAQS. The expected NOX and VOC reductions from
these standards, which take effect between 2008 and 2017, will be useful to states as they seek
to either attain or maintain the 8-hour ozone NAAQS.
EPA's review of the ozone NAAQS is currently underway, the proposal was published
in June 2007 (72 FR 37818, July 11, 2007) and the final rule is scheduled for March 2008. If
the ozone NAAQS is revised then new nonattainment areas could be designated. While EPA
1 An ozone design value is the concentration that determines whether a monitoring site meets the NAAQS for
ozone. Because of the way they are defined, design values are determined based on three consecutive-year
monitoring periods. For example, an 8-hour ozone design value is the fourth highest daily maximum 8-hour
average ozone concentration measured over a three-year period at a given monitor. The full details of these
determinations (including accounting for missing values and other complexities) are given in Appendices H and
I of 40 CFR Part 50. Due to the precision with which the standards are expressed (0.08 parts per million (ppm)
for the 8-hour), a violation of the 8-hour standard is defined as a design value greater than or equal to 0.085 ppm
or 85 parts per billion (ppb). For a county, the design value is the highest design value from among all the
monitors with valid design values within that county. If a county does not contain an ozone monitor, it does not
have a design value. However, readers should note that ozone design values generally represent air quality
across a broad area and that absence of a design value does not imply that the county is in compliance with the
ozone NAAQS.
K 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 recently applied to be redesignated as an extreme
nonattainment area which will make their attainment date June 15, 2024.
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Regulatory Impact Analysis
is not relying on it for purposes of justifying this rule, the emission reductions from this
rulemaking will also be helpful to states if EPA revises the ozone NAAQS to be more
stringent.
2.2.4 Projected 8-Hour Ozone Levels
In the following sections we describe our modeling of 8-hour ozone levels in the
future with and without the controls being finalized in this action.
2.2.4.1 Projected 8-Hour Ozone Levels without this Rulemaking
EPA has already adopted many emission control programs that are expected to reduce
ambient ozone levels. These control programs include the 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, the number of
areas that continue to violate the 8-hour ozone NAAQS in the future is expected to decrease.
The baseline air quality modeling completed for this rule predicts that without
additional local, regional or national controls there will continue to be a need for reductions in
8-hour ozone concentrations in some areas in the future. The determination that an area is at
risk of exceeding the 8-hour ozone standard in the future was made for all areas with current
design values greater than or equal to 85 ppb (or within a 10 percent margin) and with
modeling evidence that concentrations at and above these levels will persist into the future.L
Those interested in greater detail should review the air quality modeling TSD.
The baseline inventories that underlie the modeling conducted for this rulemaking
include emission reductions from existing federal, state and local controls. There was no
attempt to examine the prospects of areas attaining or maintaining the standard with future
possible controls. The results should therefore be interpreted as indicating what counties are
at risk for violating the ozone NAAQS in the future without additional federal, state or local
measures that may implemented after this rulemaking is finalized. We expect many of the
areas to adopt additional emission reduction programs, but we are unable to quantify or rely
upon future reductions from additional programs since they have not yet been promulgated.
With reductions from programs already in place (but excluding the emission
reductions from this rule), the number of counties with projected 8-hour ozone design values
at or above 85 ppb in 2020 is expected to be 9 counties where 22.5 million people are
projected to live. In addition, in 2020, 39 counties where 28.6 million people are projected to
live, will be within 10 percent of violating the 8-hour ozone NAAQS.
As discussed in the next section, the air quality modeling conducted for this rule
indicates that the almost 300,000 tons of annual NOX reductions in 2020 will be important for
ensuring that air quality in these areas meets the 8-hour ozone standard.
L 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.
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Air Quality and Resulting Health and Welfare Effects
2.2.4.2 Projected 8-Hour Ozone Levels with this Rulemaking
This section summarizes the results of our modeling of ozone air quality impacts in
the future due to the reductions in locomotive and marine diesel emissions finalized in this
action. Specifically, we compare baseline scenarios to scenarios with controls. Our modeling
indicates that the reductions from this rule will contribute to reducing ambient ozone
concentrations and minimizing the risk of exposures in future years. Since some of the VOC
and 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.98
According to air quality modeling performed for this rulemaking, the locomotive and
marine diesel engine standards provide improvements in ozone levels for the vast majority of
areas. There are three nonattainment areas in southern California, the Los Angeles-South
Coast Air Basin nonattainment area, the Riverside Co. (Coachella Valley) nonattainment area
and the Los Angeles-San Bernardino (W. Mojave) nonattainment area, which will experience
8-hour ozone design value increases due to the NOX disbenefits which occur in these VOC-
limited ozone nonattainment areas. Briefly NOX reductions can at certain times and in some
areas cause ozone levels to increase slightly. Section 2.2.4.2.1 provides additional detail
about NOX disbenefits.
Despite these areas which experience ozone increases, the overall effect of this rule is
positive with 573 counties (of 579 that have monitored data) experiencing at least a 0.1 ppb
decrease in their 2030 ozone design values. On a population-weighted basis, the average
modeled future-year 8-hour ozone design values over these counties will decrease by 0.30 ppb
in 2020 and 0.85 ppb in 2030. Within areas with the highest projected 8-hour ozone design
values, greater than 85 ppb, the average decrease will be 0.13 ppb in 2020 and 0.62 ppb in
2030. The maximum decrease for future-year design values will be 1.8 ppb in 2020 and 4.6
ppb in 2030.
Table 2-4 identifies the full list of counties projected to have design values at or above
85 ppb as well as the counties within 10 percent of violating the 8-hour ozone NAAQS in
2020. The design value for Kenosha, WI goes from being above the standard in the base case
to being lower than the 8-hour ozone NAAQS with the controls being finalized in this
rulemaking.
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Regulatory Impact Analysis
Table 2-4 Counties with 2020 8-hour Ozone Design Values in Violation or within 10 percent of the Ozone
Standard in the Base and Control Cases
State
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CT
CT
IN
LA
MD
Ml
Ml
NJ
NJ
NJ
NJ
NY
NY
NY
OH
OH
PA
PA
TX
County
Calaveras
El Dorado
Fresno
Kern
Kings
Los Angeles
Madera
Merced
Nevada
Orange
Placer
Riverside
Sacramento
San Bernardino
San Diego
Stanislaus
Tula re
Tuolumne
Ventura
Fairfield
New Haven
Lake
East Baton Rouge
Harford
Allegan
Macomb
Camden
Gloucester
Mercer
Ocean
Erie
Niagara
Suffolk
Ashtabula
Geauga
Bucks
Philadelphia
Brazoria
2000-2004
Average 8-Hour
Ozone DV
(ppb)a
91.0
105.0
110.0
114.3
95.7
121.3
91.0
101.7
97.7
85.3
98.3
115.0
99.0
128.7
92.3
95.0
105.7
91.0
94.7
98.3
98.3
88.3
87.0
100.3
94.0
92.3
99.7
98.0
97.7
105.7
95.7
91.7
97.0
95.7
99.0
99.0
96.7
94.0
2020 modeling projections of
8-Hour Ozone DV (ppb)
base
V
X
X
X
V
X
V
V
V
V
V
X
V
X
V
V
X
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
control
V
X
X
X
V
X
V
V
V
V
V
X
V
X
V
V
X
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
2020
Population
58,261
236,310
1,066,878
876,131
173,390
10,376,013
173,940
277,863
131,831
3,900,599
451 ,620
2,252,510
1,640,590
2,424,764
3,863,460
607,766
477,296
70,570
1,023,136
962,824
898,415
509,293
522,399
317,847
141,851
894,095
547,817
304,105
392,236
644,323
959,145
220,989
1,598,742
108,355
114,438
711,275
1,394,176
322,385
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Air Quality and Resulting Health and Welfare Effects
State
TX
TX
TX
TX
TX
Wl
Wl
Wl
Wl
Wl
County
Galveston
Harris
Jefferson
Montgomery
Tarrant
Kenosha
Milwaukee
Ozaukee
Racine
Sheboygan
2000-2004
Average 8-Hour
Ozone DV
(ppb)a
89.7
102.0
91.0
88.3
98.7
98.3
91.0
93.0
91.7
97.0
2020 modeling projections of
8-Hour Ozone DV (ppb)
V
X
V
V
V
X
V
V
V
V
V
X
V
V
V
V
V
V
V
V
2020
Population
318,966
4,588,812
272,075
526,335
2,137,957
184,825
927,845
110,294
212,351
128,777
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.
Table 2-5 shows the average change in future year eight-hour ozone design values.
Average changes are shown for: (1) all counties with 2002 baseline design values, (2)
counties with baseline design values that exceeded the standard in 2000-2004 ("violating"
counties), and (3) counties that did not exceed the standard, but were within 10 percent of it in
2000-2004. This last category is 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 a larger decrease in 2030, indicating in three different ways the
overall improvement in ozone air quality.
Table 2-5 Average change in projected future year 8-hour ozone design value as a result of the
locomotive and marine diesel controls
Average"
All
All, population-weighted
Violating countiesc
Violating counties^ population-weighted
Counties within 10 percent of the standard''
Counties within 10 percent of the standard^,
population-weighted
Number of US
Counties
579
579
261
261
477
477
Change in 2020
design value6 (ppb)
-0.45
-0.30
-0.45
-0.27
-0.46
-0.31
Change in 2030
design value6 (ppb)
-1.15
-0.85
-1.18
-0.78
-1.18
-0.86
Notes:
averages are over counties with 2002 modeled design values
design value changes in this action results have been presented in parts per billion (ppb) format.
counties whose 2002 baseline design values exceeded the 8-hour ozone standard (>= 85 ppb)
counties whose 2002 baseline values were less than but within 10 percent of the 8-hour ozone standard.
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Regulatory Impact Analysis
Figure 2.7 shows those US counties in 2030 which experience a change in their ozone
design values as a result of this rule. Some of the most significant decreases will occur in the
following counties: St. Mary (3.1 ppb) and Lafayette (2.6 ppb) Counties in Louisiana;
Brazoria (2.9 ppb) and Jefferson (3.0 ppb) Counties in Texas; Warren County (3.2 ppb) in
Mississippi; and Santa Barbara County (4.6 ppb) in California. 338 counties will see 8-hour
ozone design value reductions from between 1.0 to 1.9 ppb while an estimated 190 additional
counties will see design value reductions from 0.5 to 0.9 ppb. Note that 5 counties, Cook
County (0.2 ppb) in Illinois; Lake County (0.1 ppb) in Indiana; and San Bernardino (0.1 ppb),
Riverside (0.5 ppb) and Orange (5.5 ppb) counties in California are projected to experience
increases in their ozone design values because of the NOx disbenefit that occurs in these
VOC-limited areas.
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Air Quality and Resulting Health and Welfare Effects
Legend Number of Counties
^B <= -2-0
^^ >-2.0to<=-1.0
^^ >-1.0to<=-0.5
fejSjฃ| > -0.5 to <= -0.1
^^ =0.0
27
338
190
18
1
4
1
Effect of Locomarine in 2030
Figure 2-7 Impact of Locomotive/Marine controls on Ozone Design Values in 2030
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Regulatory Impact Analysis
2.2.4.2.1 Potentially Counterproductive Impacts on Ozone Concentrations from NOx
Emissions Reductions
While this rule reduces ozone levels generally and provides national ozone-related
health benefits, this is not always the case at the local level. 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 HC>2 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 Ox 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."
EPA believes that the best available approach for determining the value of a particular
national emission reduction strategy is the net air quality change projected to result from a
rule, evaluated on a nationwide basis for all pollutants of concern. The primary tool for
assessing the net health and welfare impacts at this time is the Community Multiscale Air
Quality (CMAQ) model. Model scenarios for 2020 and 2030 with and without the emission
control strategies from this rule were compared to determine the expected changes in future
pollutant levels resulting from this rule. A wide variety of ozone metrics were considered in
assessing emissions reductions. Three of the most important are: 1) the effect of the rule on
projected future-year ozone design values, 2) the effect of the rule in assisting local areas in
attainment and maintenance of the NAAQS, and 3) an economic assessment of the rule
benefits based on existing health studies.
When considering NOx disbenefit results for these local areas several factors related
to both the model inputs and the air quality modeling should be considered. First, our future
year modeling does not contain any local governmental actions which have not already been
promulgated in a finalized State SIP. The inability to account for future local controls is a
function of the SIP development process. EPA typically does not include local plans to
reduce ozone precursors in our future baseline projections until those reductions are part of a
fully promulgated State or local regulation. However, significant local controls of VOC
and/or NOX that are not reflected in the air quality modeling for this rule could modify the
conclusions regarding ozone changes in some areas.
Second, due to the ozone disbenefit chemistry described above, modeling only the
final rule-related NOx reductions in an area that is VOC-limited can give an inaccurate
representation of future air quality. In an area such as this, marginal NOx reductions modeled
independently will likely lead to ozone disbenefits. However, there is a level of NOx
reduction, even in VOC-limited areas, where enough NOx will have been controlled to result
in NOx-limited conditions and as a result ambient ozone concentrations will decrease.
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Air Quality and Resulting Health and Welfare Effects
The majority of the projected NOx disbenefits from this rule occur in Southern
California, specifically Orange, Riverside and San Bernardino counties. California's South
Coast Air Quality Management District (SCAQMD) includes the southern two-thirds of Los
Angeles County, all of Orange County, and the western, urbanized portions of Riverside and
San Bernardino counties. The SCAQMD has recently completed an air quality modeling
exercise as part of their ozone attainment demonstration. This modeling indicates that with
substantial NOx and VOC reductions (-90% and -45% respectively), the entire south coast
basin will be in attainment for the 8-hour ozone NAAQS by 2024.M
The SCAQMD attainment demonstrations for both PM2 5 and 8-hour ozone were
conducted using photochemical dispersion and meteorological modeling tools developed in
response to U.S EPA modeling guidelines100, and recommendations from air quality modeling
experts. The air quality modeling has undergone scientific peer review and was made
available for public review. Air Resources Board (ARB) and South Coast District staffs
worked together on the modeling, including development of a gridded modeling inventory
and meteorological and geological data inputs, model performance analysis, and validation of
the attainment demonstrations.
It is important to note that the NOx emission reductions associated with this final
locomotive and marine rule play an important role in the South Coast's demonstration of
future-year ozone attainment. The SCAQMD modeling projections are based on emissions
reductions from many different state and local programs, the majority of which are not yet
finalized. The results of the SCAQMD attainment demonstration modeling illustrate the fact
that with additional NOx and VOC controls, beyond those being finalized in this rule, ambient
ozone would be reduced in Southern California.
Finally, although a VOC-heavy control strategy can be an effective means to reduce
NOx disbenefits, there are reasons why NOx reductions can still be the preferred route to
reducing ozone in local areas. One reason is because NOx is not only an ozone precursor but
a PM precursor. Based on modeling and cost/benefit analyses completed by SCAQMD they
have concluded that due to the magnitude of emissions reductions needed for ozone and PM
attainment, as well as the readiness of NOx control technologies, a NOx-heavy control
approach provides the most efficient path to attainment for both pollutants in California's
south coast..
Historically, NOX reductions have been very successful at reducing regional/national
ozone levels. Consistent with that fact, the photochemical modeling completed for this rule
indicates that the emission reductions resulting from the locomotive and marine engine rule
assist in the attainment and maintenance of the ozone NAAQS at the national level.
Furthermore, NOX reductions also result in reductions in PM and its associated health and
welfare effects. This rule is one important element of the overall emission reductions that
States, local governments, and Tribes need to reach their clean air goals. It is expected that
future local and national controls that decrease VOC, CO, and regional ozone will mitigate
M Note that the NOx reductions modeled in the south coast attainment demonstration include NOx reductions
that are projected to occur due to new technology that does not currently exist.
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Regulatory Impact Analysis
localized disbenefit. EPA continues to rely on local attainment measures to ensure no future
violations of the NAAQS. Many states and environmental organizations with an interest in
improved air quality have urged EPA to finalize this rule because of the significant NOX
reductions that will reduce both ozone and PM.101 EPA believes that a balanced air quality
management approach, which includes NOX reductions from locomotive and marine engines,
is needed as part of the Nation's progress toward clean air.
Another effect of ozone reduction strategies is the potential impact these reductions
may have on the shielding provided by ozone from ultraviolet radiation (UV-B) derived from
the sun. The majority of this shielding results from naturally occurring ozone in the
stratosphere, but a variable portion of this tropospheric fraction of UV-B shielding is derived
from ground level ozone. Therefore, strategies that reduce ground level ozone could, in some
small measure, increase exposure to UV-B from the sun, thus potentially increasing skin
cancer.
While it is possible to provide quantitative estimates of benefits associated with
globally based strategies to restore the far larger and more spatially uniform stratospheric
ozone layer, the changes in UV-B exposures associated with ground level ozone reduction
strategies are much more complicated and uncertain. Comparatively smaller changes in
ground-level ozone (compared to the total ozone in the troposphere) and UV-B are not likely
to measurably change long-term risks of adverse effects.
2.2.5 Environmental Effects of Ozone Pollution
There are a number of public welfare effects associated with the presence of ozone in
the ambient air.102 In this section we discuss the impact of ozone on plants, including trees,
agronomic crops and urban ornamentals.
2.2.5.1 Impacts on Vegetation
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. Like carbon dioxide (CC^) and
other gaseous substances, ozone enters plant tissues primarily through apertures (stomata) in
leaves in a process called "uptake".103 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.104'105 This damage is commonly manifested as visible foliar injury such as chlorotic
or necrotic spots, increased leaf senescence (accelerated leaf aging) and/or reduced
photosynthesis. All these effects reduce a plant's capacity to form carbohydrates, which are
the primary form of energy used by plants.106 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. Studies have shown
that plants stressed in these ways may exhibit a general loss of vigor, which can lead to
secondary impacts that modify plants' responses to other environmental factors. Specifically,
plants may become more sensitive to other air pollutants, more susceptible to disease, insect
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Air Quality and Resulting Health and Welfare Effects
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.107'108
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 Oj uptake through closure of stomata). 109'110>ni
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.112
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.113'114 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.115'116
Because plants are at the center 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.117 In most instances, responses to
chronic or recurrent exposure in forested ecosystems are subtle and not observable for many
years. These injuries can cause stand-level forest decline in sensitive ecosystems.118'119'120 It
is not yet possible to predict ecosystem responses to ozone with much certainly; 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
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Regulatory Impact Analysis
typical of those found in the Unites States."121 In addition, economic studies have shown
reduced economic benefits as a result of predicted reductions in crop yields associated with
observed ozone levels.122'123'124
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.125 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.
2.3 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, including
evaluations of model performance, is included in the Air Quality Modeling Technical Support
Document (AQM TSD).126
2.3.1 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 and visibility levels. These
projections were used as inputs to the calculation of expected benefits from the locomotive
and marine emissions controls considered in this assessment. The 2002-based CMAQ
modeling platform was used as the tool for the air quality modeling of future baseline
emissions and control scenarios. It should be noted that the 2002-based modeling platform
has recently been finalized and the 2001-based modeling platform was used as the tool for the
air quality modeling performed for the proposal. In the next paragraph we discuss some of
the differences between the 2001-based platform used for the proposal and the 2002-based
platform used for this final rule.
The 2002-based modeling platform includes a number of updates and improvements to
data and tools compared to the 2001-based platform that was used for the proposal modeling.
For the final rule modeling we used the new 2002 National Emissions Inventory along with
updated versions of the models used to project future emissions from electric generating units
(EGUs) and onroad and nonroad vehicles. The proposal modeling was based on the 2001
National Emissions Inventory. The new platform also includes 2002 meteorology and more
recent ambient design values which were used as the starting point for projecting future air
quality. For proposal, we used meteorology for 2001 for modeling the East and 2002 for
modeling the West. The updates to CMAQ between proposal and final include (1) an in-
cloud sulfate chemistry module that accounts for the nonlinear sensitivity of sulfate formation
to varying pH; (2) improved vertical convective mixing; (3) heterogeneous reaction involving
nitrate formation; (4) an updated gas-phase chemistry mechanism, Carbon Bond 2005
(CB05); and (5) an aqueous chemistry mechanism that provides a comprehensive simulation
of aerosol precursor oxidants.
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Air Quality and Resulting Health and Welfare Effects
The CMAQ model is a three-dimensional grid-based Eulerian air quality model
designed to estimate the formation and fate of oxidant precursors, primary and secondary
particulate matter concentrations and deposition over regional and urban spatial scales (e.g.,
1 T7 1 0ฃ 10Q
over the contiguous U.S.). ' ' Consideration of the different processes that affect
primary (directly emitted) and secondary (formed by atmospheric processes) PM at the
regional scale in different locations is fundamental to understanding and assessing the effects
of pollution control measures that affect PM, ozone and deposition of pollutants to the
surface. In addition to the CMAQ model, the modeling platform includes the emissions,
meteorology, and initial/boundary condition data which are inputs to this model.
The CMAQ model was peer-reviewed in 2003 for EPA as reported in "Peer Review of
CMAQ Model". 13ฐ The latest version of CMAQ (Version 4.6.1) was employed for this
modeling analysis. This version reflects updates, as mentioned above, in a number of areas to
improve the underlying science which include (1) use of a state-of-the science inorganic and
organic aerosol module, (2) an in-cloud sulfate chemistry module that accounts for the
nonlinear sensitivity of sulfate formation to varying pH, (3) improved vertical convective
mixing, (4) heterogeneous reaction involving nitrate formation and (5) an updated Carbon
Bond 05 (CB05) gas-phase chemistry mechanism and aqueous chemistry mechanism that
provides a comprehensive simulation of aerosol precursor oxidants.
2.3.2 Model Domain and Configuration
As shown in Figure 2-8 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 2-8. The modeling domain contains 14 vertical layers with the top of the
modeling domain at about 16,200 meters, or 100 millibars (mb).
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Regulatory Impact Analysis
Figure 2-8. Map of the CMAQ modeling domain.
2.3.3 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 Model131 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. 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.132
The lateral boundary and initial species concentrations are provided by a three-
dimensional global atmospheric chemistry model, the GEOS-CHEM model.133 The global
GEOS-CHEM model simulates atmospheric chemical and physical processes driven by
assimilated meteorological observations from the NASA's Goddard Earth Observing System
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Air Quality and Resulting Health and Welfare Effects
(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 are summarized in Chapter 3 of this RIA.
2.3.4 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
the 2002 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.134 The
"acceptability" of model performance was judged by comparing our results to those found in
recent regional PM2.5 model applications for other, non-EPA studies135. Overall, the
performance for the 2002 modeling platform is within the range of these other applications.
A detailed summary of the 2002 CMAQ model performance evaluation is available within the
AQM TSD.
2.3.5 Model Simulation Scenarios
As part of our analysis for this rulemaking the CMAQ modeling system was used to
calculate annual PM2.s concentrations, 8-hour ozone concentrations and visibility estimates
for each of the following emissions scenarios:
2002 base year
2020 base line projection
2020 base line projection with diesel marine only controls
2020 base line projection with locomotive and diesel marine controls
2030 base line projection
2030 base line projection with diesel marine only controls
2030 base line projection with locomotive and diesel marine controls
It should be noted that the emission control scenarios used in the air quality and
benefits modeling are slightly different than the emission control program being finalized.
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
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inputs and resulting emission inventories between the preliminary assumptions used for
the air quality modeling and the final regulatory scenario. 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, 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). After completing this process, we then
calculated the effect of changes in PM, ozone and visibility air quality metrics resulting from
this rulemaking on the health and welfare impact functions of the benefits analysis
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 US. The SMAT methodology uses the following PM25 species components: sulfates,
nitrates, ammonium, organic carbon mass, elemental carbon, crustal, water, and blank mass (a
fixed value of 0.5 jig/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)".136 For this latest
analysis, several datasets and techniques were updated. These changes are fully described
within the AQM TSD. The projected 8-hour ozone design values were calculated using the
approach identified in EPA's guidance on air quality modeling attainment demonstrations.
2.3.6 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 Federally
mandated Class I 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
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Air Quality and Resulting Health and Welfare Effects
which have complete IMPROVE ambient data for 2002 or are represented by IMPROVE
monitors with complete data.N
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.137
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).
For visibility calculations, we are continuing to use the IMPROVE program species
definitions and visibility formulas which are recommended in the draft modeling guidance.
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).
N 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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Regulatory Impact Analysis
2.4 Air Toxics
People experience elevated risk of cancer and other noncancer health effects from
exposure to air toxics. Mobile sources are responsible for a significant portion of this risk.
According to the National Air Toxic Assessment (NATA) for 1999, mobile sources were
responsible for 44 percent of outdoor toxic emissions and almost 50 percent of the cancer risk.
Benzene is the largest contributor to cancer risk of all 133 pollutants quantitatively assessed in
the 1999 NATA and mobile sources were responsible for 68 percent of benzene emissions in
1999. In response, EPA has recently finalized mobile source and fuel controls that address
this public health risk.0 Although the 1999 NATA did not quantify cancer risks associated
with exposure to diesel exhaust, EPA has concluded that diesel exhaust ranks with the other
emissions that the 1999 NATA suggests pose the greatest relative risk.
According to the 1999 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. Mobile sources were responsible for 74 percent of the noncancer (respiratory)
risk from outdoor air toxics in 1999. The majority of this risk was from exposure to acrolein.
The confidence in the RfC for acrolein is medium and confidence in NATA estimates of
population noncancer hazard from ambient exposure to this pollutant is low.138>139
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 1999 NATA website. 14ฐ 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.
The following section provides an overview of air toxics which are associated with
nonroad engines, including locomotive and marine diesel engines, and provides a discussion
of the health risks associated with each air toxic.
2.4.1 Diesel Exhaust PM
Locomotive and marine diesel engines emit diesel exhaust (DE), a complex mixture
comprised of carbon dioxide, oxygen, nitrogen, water vapor, carbon monoxide, nitrogen
compounds, sulfur compounds and numerous low-molecular-weight hydrocarbons. A number
of these gaseous hydrocarbon components are individually known to be toxic including
aldehydes, benzene and 1,3-butadiene. The diesel particulate matter (DPM) present in diesel
exhaust consists of fine particles (< 2.5|im), including a subgroup with a large number of
ultrafme particles (< 0.1 jim). These particles have large surface areas which make them an
excellent medium for adsorbing organics, and their small size makes them highly respirable
and able to deposit deep in the lung. Diesel PM contains small quantities of numerous
mutagenic and carcinogenic compounds associated with the particles (and also organic gases).
In addition, while toxic trace metals emitted by locomotive and marine diesel engines
0 U.S. EPA (2006) Control of Hazardous Air Pollutants from Mobile Sources. 71 FR 15804; March 29, 2006.
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Air Quality and Resulting Health and Welfare Effects
represent a very small portion of the national emissions of metals (less than one percent) and
are a small portion of diesel PM (generally much less than one percent of diesel PM), we note
that several trace metals of potential toxicological significance and persistence in the
environment are emitted by diesel engines. These trace metals include chromium,
manganese, mercury and nickel. In addition, small amounts of dioxins have been measured in
highway engine diesel exhaust, some of which may partition into the particulate 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).141 Also, there are emission
differences between on-road and nonroad engines because the nonroad engines are generally
of older technology. After being emitted diesel exhaust undergoes dilution as well as
chemical and physical changes in the atmosphere. The lifetime for some of the compounds
present in diesel exhaust ranges from hours to days.
A number of health studies have been conducted regarding diesel exhaust. These
include epidemiologic studies of lung cancer in groups of workers and animal studies
focusing on non-cancer effects specific to diesel exhaust exposure. Diesel exhaust PM
(including the associated organic compounds which are generally high molecular weight
hydrocarbon types but not the more volatile gaseous hydrocarbon compounds) is generally
used as a surrogate measure for diesel exhaust.
2.4.1.1 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.142>143 In accordance with earlier EPA guidelines, exposure
to diesel exhaust would similarly be classified as probably carcinogenic to humans (Group
Bl).144'145 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 US Department of Health and Human Services) have made similar
classifications.146' 147>148>149>150 xhe Health Effects Institute has prepared numerous studies and
reports on the potential carcinogenicity of exposure to diesel exhaust.151'152'153 In addition
many animal and bioassay/genotoxic tests have been done on diesel exhaust154'155 and case-
control and cohort studies have been conducted on railroad worker exposures to diesel
exhaust from railroad engines156'157'158 in addition to studies on truck workers.159'160'161'162
Also, there are numerous other epidemiologic studies including some studying mine workers
and fire fighters.163'164
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
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Regulatory Impact Analysis
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 locomotive and 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 locomotive and 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, including railroad workers.
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.165'166'167
Retrospective health studies of railroad workers have played an important part in
finding that exposure to diesel exhaust is a likely to be carcinogenic to humans by inhalation
at environmental levels of exposure. Key evidence of the diesel exhaust exposure linkage to
lung cancer comes from two retrospective case-control studies of railroad workers. The
Garshick railroad study168 looked at more than 55,000 railroad workers post-1959 which
coincided with the widespread dieselization of the railroads. The study found that the risk of
lung cancer increased with increasing duration of employment, and that the youngest workers
had the highest risk of dying. The second railroad study, authored by Swanson et al.169, found
statistically significant excess risks, when adjusted for age, smoking, and race, among railroad
workers employed for more than 10 years and heavy truck drivers employed for more than 20
years. In addition, a 1988 industrial hygiene study documented the increased lung cancer
risks associated with different railroad worker job classifications.170 Thirty-nine job titles
were originally identified and were then collapsed, for statistical analyses, into 5 categories
including clerks, signal maintainers, engineers/firers, brakers/conductors/hostlers, and shop
workers. The study documented that those in closest contact with diesel exhaust exhibited the
highest level of lung cancer risk. Train workers (engineers/firers etc.) had the highest risk,
shop workers an intermediate level, and clerks the lowest lung cancer risk.
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.
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Air Quality and Resulting Health and Welfare Effects
In the absence of a cancer unit risk, the Diesel HAD sought to provide additional
insight into the significance of the diesel exhaust-cancer hazard by estimating possible ranges
of risk that might be present in the population. An exploratory analysis was used to
characterize a possible risk range by comparing a typical environmental exposure level for
highway diesel sources to a selected range of occupational exposure levels. The
occupationally observed risks were then proportionally scaled according to the exposure ratios
to obtain an estimate of the possible environmental risk. If the occupational and
environmental exposures are similar, the environmental risk would approach the risk seen in
the occupational studies whereas a much higher occupational exposure indicates that the
environmental risk is lower than the occupational risk. A comparison of environmental and
occupational exposures showed that for certain occupations the exposures are similar to
environmental exposures while, for others, they differ by a factor of about 200 or more.
A number of calculations are involved in the exploratory analysis of a possible risk
range, and these can be seen in the EPA Diesel HAD. The outcome was that environmental
risks from diesel exhaust exposure could range from a low of 10"4 to 10"5 to as high as 10"3,
reflecting the range of occupational exposures that could be associated with the relative and
absolute risk levels observed in the occupational studies. Because of uncertainties, the
analysis acknowledged that the risks could be lower than 10"4 or 10"5, and a zero risk from
diesel exhaust exposure was not ruled out.
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.171'172 This national assessment estimates average population inhalation
exposures to diesel PM 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 locomotive and marine engines present public
health issues of concern to this rule.
2.4.1.2 Other Health Effects of 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.173'174'175'176 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
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Regulatory Impact Analysis
sensitivity. The resulting RfC derived in the Diesel HAD is 5 |ig/m3 for diesel exhaust as
measured by diesel PM. 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 paniculate
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" (p. 9-19).
While there have been relatively few human studies associated specifically with the
noncancer impact of exposure to diesel PM alone, diesel PM 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 diesel PM is supported by studies that
specifically associate observable human noncancer health effects with exposure to diesel PM.
As described in the Diesel HAD, these studies identified some of the same health effects
reported for ambient PM, such as respiratory symptoms (cough, labored breathing, chest
tightness, wheezing), and chronic respiratory disease (cough, phlegm, chronic bronchitis and
suggestive evidence for decreases in pulmonary function). Symptoms of immunological
effects such as wheezing and increased allergenicity are also seen. Studies in rodents,
especially rats, show the potential for human inflammatory effects in the lung and
consequential lung tissue damage from chronic diesel exhaust inhalation exposure. The
Diesel HAD concludes "that acute exposure to DE [diesel exhaust] has been associated with
irritation of the eye, nose, and throat, respiratory symptoms (cough and phlegm), and
neurophysiological symptoms such as headache, lightheadedness, nausea, vomiting, and
numbness or tingling of the extremities."177 There is also evidence for an immunologic effect
such as the exacerbation of allergenic responses to known allergens and asthma-like
symptoms.178'179'180
Exposure to diesel exhaust has been shown to cause serious noncancer effects in
occupational exposure studies. One recent study181 of a small group of railroad workers and
electricians found that exposure to diesel exhaust resulted in neurobehavioral impairments in
one or more areas including reaction time, balance, blink reflex latency, verbal recall, and
color vision confusion indices. Pulmonary function tests also showed that 10 of the 16
workers studied had airway obstruction and another group of 10 of 16 workers had chronic
bronchitis, chest pain, tightness, and hyperactive airways. Finally, a variety of studies have
been published subsequent to the completion of the Diesel HAD. One study, published in
2006182 found that railroad engineers and conductors with diesel exhaust exposure from
operating trains had an increased incidence of chronic obstructive pulmonary disease (COPD)
mortality. The odds of COPD mortality increased with years on the job so that those who had
worked more than 16 years as an engineer or conductor after 1959 had an increased risk of
1.61 (95% confidence interval, 1.12 - 2.30). EPA is assessing the significance of this study
within the context of the broader literature.
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 2.1.2 of this RIA),
showing a wide spectrum of adverse health effects associated with exposure to ambient PM,
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Air Quality and Resulting Health and Welfare Effects
of which diesel exhaust is an important component. The PM^.sNAAQS is designed to
provide protection from the non-cancer and premature mortality effects of PM2 5 as a whole.
A number of recent studies have associated living near roadways with adverse health
effects. A Dutch study of a population of people 55-69 years old found that there was an
elevated risk of heart and lung related mortality among populations living near high traffic
roads.183 In a review of studies of the respiratory health of people living near roadways,
another publication indicated that the risk of asthma and related respiratory disease appeared
elevated in people living near heavy traffic.184 These studies offer evidence that people
exposed most directly to emissions from mobile sources, including diesels, face an elevated
risk of illness or death.
2.4.1.3 Ambient Levels of Diesel Exhaust PM
Because diesel PM is part of overall ambient PM and cannot be easily distinguished
from overall PM, we do not have direct measurements of diesel PM in the ambient air. Diesel
PM concentrations are estimated here using ambient air quality modeling based on diesel PM
emission inventories.
2.4.1.3.1 Toxics Modeling and Methods
In addition to the general ambient PM modeling conducted for this rulemaking, diesel
PM concentrations were recently estimated as part of the 1999 National-Scale Air Toxics
Assessment.185 Ambient impacts of mobile source emissions were predicted using the
Assessment System for Population Exposure Nationwide (ASPEN) dispersion model.
Concentrations of diesel PM were calculated at the census tract level in the 1999
NATA. The median diesel PM concentration calculated nationwide is 0.91 ug/m3 with levels
of 1.06 ug/m3 in urban counties and 0.43 ug/m3 in rural counties. Table 2-6 below
summarizes the distribution of ambient diesel PM concentrations at the national scale. Over
half of the diesel PM and diesel exhaust organic gases can be attributed to nonroad diesels. A
map of median ambient concentrations is provided in Figure 2-9. 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 Assessment of the U.S.
Table 2-6 Distribution of Census Tract Ambient Concentrations of Diesel PM at the National Scale in 1999 NATA"
5th Percentile
25thPercentile
Median
75th Percentile
95th Percentile
Onroad Contribution to Mean
Nonroad Contribution to Mean
Nationwide (ug/m3)
0.22
0.54
0.91
1.41
2.91
0.43
0.78
Urban (ug/m3)
0.33
0.70
1.06
1.56
3.21
0.49
0.90
Rural (ug/m3)
0.08
0.28
0.43
0.62
0.96
0.20
0.28
This table is generated from data contained in the diesel particulate matter Microsoft Access database file found in the
County-Level Ambient Concentration Summaries section of the 1999 NATA webpage
(http://www.epa.gov/ttn/atw/natal999/tables.html).
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Regulatory Impact Analysis
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Air Quality and Resulting Health and Welfare Effects
2.4.1.4 Exposure to Diesel Exhaust PM
Exposure of people to diesel exhaust depends on their various activities, the time spent
in those activities, the locations where these activities occur, and the levels of diesel exhaust
pollutants in those locations. The major difference between ambient levels of diesel
particulate and exposure levels for diesel particulate is that exposure levels account for a
person moving from location to location, the proximity to the emission source, and whether
the exposure occurs in an enclosed environment.
2.4.1.4.1 Occupational Exposures
Occupational exposures to diesel exhaust from mobile sources, including locomotive
engines and 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. Studies have shown that miners and railroad workers typically have higher
diesel exposure levels than other occupational groups studied, including firefighters, truck
dock workers, and truck drivers (both short and long haul).186 A 1988 study187 estimated that
U.S. railroad workers received an estimated occupational exposure/concentration of between
39 -191 |ig/m3 (measured as smoking adjusted respirable particles) which resulted in an
equivalent environmental exposure of 8-40 |ig/m3. 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 locomotive and marine diesel engines.
2.4.1.4.2 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, 188 rail yards,
189 and marine ports190 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 rail yards and marine ports may experience
elevated ambient concentrations of directly-emitted PM2.5 from diesel engines. Due to the
unique nature of rail yards and marine ports, emissions from a large number of diesel engines
are concentrated in a small area. Furthermore, emissions occur at or near ground level,
allowing emissions of diesel engines to reach nearby receptors without fully mixing with
background air.
A study conducted by the California Air Resources Board (CARB) in 2004 examined
the air quality impacts of railroad operations at the J.R. Davis Rail Yard, the largest service
and maintenance rail facility in the western United States.191 The yard occupies 950 acres
along a one-quarter mile wide and four mile long section of land in Roseville, CA. The study
developed an emissions inventory for the facility for the year 2000 and modeled ambient
2-55
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Regulatory Impact Analysis
concentrations of diesel PM using the ISCST3 dispersion model. The study found
substantially elevated concentrations in an area 5,000 meters from the facility, with higher
concentrations closer to the rail yard. Using local meteorological data, annual average
contributions from the rail yard to ambient diesel PM concentrations under prevailing wind
conditions were 1.74, 1.18, 0.80, and 0.25 |ig/m3 at receptors located 200, 500, 1000, and
5000 meters from the yard, respectively. Several tens of thousands of people live within the
area experiencing substantial increases in annual average ambient PM2.5 as a result of
emissions from the yard. As part of an agreement between CARB and the Union Pacific
Railroad and BNSF Railway, similar assessments are being prepared for 16 other large
railyards. The details and results of these additional assessments can be found in their
192
respective reports. '
Another study from 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.193 Like the earlier rail yard study, the port study employed the ISCST3 dispersion
model. Also using local meteorological data, annual average concentrations of diesel PM
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 diesel PM in ambient air, about 360,000 people
lived in areas with at least 0.6 |ig/m3 of diesel PM, and about 50,000 people lived in areas
with at least 1.5 |ig/m3 of ambient diesel PM emitted directly from the port. Figure 2-10
provides an aerial shot of the Port of Long Beach and Los Angeles in California.
Figure 2-10 Aerial Shot - Port of LA and Long Beach, California
Together these railyard and port studies highlight the substantial contribution these
facilities make to ambient concentrations of diesel PM in large, densely populated areas.
2-56
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Air Quality and Resulting Health and Welfare Effects
The US EPA recently conducted a screening-level analysis to better understand the
populations including minority, low-income, and children that are exposed to diesel particulate
matter (DPM) from these facilities. The results of this studyp are discussed here and are also
available in the public docket.194'195 In the proposal, EPA committed to finalize this study as
part of an ongoing obligation to children's health and environmental justice (EJ).
This screening-level analysis focused on a representative selection of national marine
ports and rail yards.Q Of the 47 marine ports and 37 rail yards selected, the results indicate
that at least 13 million people, including a disproportionate number of low-income
households, African-Americans, and Hispanics, living in the vicinity of these facilities, are
being exposed to 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 and rail yards are more likely to be low-income and minority residents,
these populations will receive a significant benefit from this rule.
With regard to children, this analysis shows that of the 13 million people living in the
vicinity of the marine ports and rail yards 3.5 million are children. The age composition of the
total affected population in the screening analysis matches closely with the age composition
of the overall US population. However, for some individual facilities the young (0-4 years)
appear to be over-represented in the affected population compared to the overall US
population. Detailed results for individual harbors and rail yards 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 a sampling of 47 US harbor areas and 37 US rail yards and
terminals, and determined the size and demographic characteristics of the populations living
near these facilities. These facilities are listed in Tables 2-7 and 2-8 for harbor areas and rail
yards, respectively. Figures 2-11 to 2-14 provide examples of digitized footprints of the rail
yards and marine harbor areas included in this study.
p 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. Additionally, the emissions
inventories used as inputs for the analyses are not official estimates and likely underestimate overall emissions
because they are not inclusive of all emission sources at the individual ports in the sample. For example, most
inventories did include emissions from ocean-going vessels (powered by Category 3 engines), as well as some
commercial vessel categories, including harbor crafts, (powered by Category land 2 engines), cargo handling
equipment, locomotives, and heavy-duty vehicles. This final rule will not address emissions from ocean-going
vessels, cargo handling equipment, or heavy-duty vehicles.
Q The Agency selected a representative sample of the top 150 U.S. ports including coastal, inland, and Great
Lake ports. In selecting a sample of rail yards the Agency identified a subset from the hundreds of rail yards
operated by Class I Railroads.
2-57
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Regulatory Impact Analysis
Table 2-7 Marine Harbor Areas
Harbor Location
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
Jacksonville, FL
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
Norfolk Harbor, VA
Oakland, CA
Panama City, FL
Paulsboro, NJ
Philadelphia, PA
Pittsburgh, PA
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Air Quality and Resulting Health and Welfare Effects
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
Table 2-8 Rail Yards and Terminals
Yard Name
Argentine
Avon Yard
Bailey Yard
Barr Yard
Barstow Yard
Bellevue Yard
Bensenville Yard
Blue Island Yard
Boyles Yard
Buckeye Yard
Clearing Yard
Conway Yard
Location
Kansas City, KS
Indianapolis, IN
North Platte, NE
Chicago, IL
Barstow, CA
Bellevue, OH
Bensenville, IL
Blue Island, IL
Birmingham, AL
Columbus, OH
Chicago, IL
Conway, PA
Railroad
BNSF
CSXT
UP
CSXT
BNSF
NS
CP
1KB
CSXT
CSXT
BRC
NS
2-59
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Regulatory Impact Analysis
Corwith Yard
DeButts Yard
Frontier Yard
Frontier Yard Intermodal Terminal
Galesburg
Hinkle
Inman Yard
J.R. Davis Yard
Jenks Shop
Locomotive Maintenance Facility
Locomotive Repair Facility
Madison Yard
Moncrief Yard
Philadelphia PA Railyard
Pig's Eye Yard
Proviso Yard
Queensgate Yard
Radnor Yard
Rice Yard
Schiller Park
Selkirk Yard
Shaffers Crossing
Spencer Yard
Stanley/Walbridge Yard
West Colton Yard
Chicago, IL
Chattanooga, TN
Buffalo, NY
Buffalo, NY
Galesburg, IL
Hermiston, OR
Atlanta, GA
Roseville, CA
North Little Rock, AR
Alliance, NE
Topeka, KS
East St. Louis, MO
Jacksonville, FL
Philadelphia, PA
Minneapolis, MN
Chicago, IL
Cincinnati, OH
Nashville, TN
Waycross, GA
Schiller Park, IL
Selkirk, NY
Roanoke, VA
Linwood, NC
Toledo, OH
West Colton, CA
BNSF
NS
CSXT
CSXT
BNSF
UP
NS
UP
UP
BNSF
BNSF
TRRA
CSXT
CSXT
CP
UP
CSXT
CSXT
CSXT
CP
CSXT
NS
NS
CSXT
UP
2-60
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Air Quality and Resulting Health and Welfare Effects
Figure 2-11 Digitized footprint of New York, NY harbor area.
Figure 2-12 Digitized footprint of Portland, OR harbor area.
2-61
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Regulatory Impact Analysis
Figure 2-13 Digitized footprint of Argentine Rail Yard, Kansas City, Kansas.
Figure 2-14. Digitized footprint of DeButts Rail Yard, Chattanooga, Tennessee.
In order to better understand the populations that are living in the vicinity of rail yards
and marine harbor areas and their potential exposures to DPM, DPM concentration isopleths
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Air Quality and Resulting Health and Welfare Effects
surrounding the facilities were identified and digitized. 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. For marine harbor areas, the isopleths were estimated using the AERMOD air
dispersion model. For rail yards and terminals, the isopleths were estimated using a process
for scaling from published rail yard modeling reports. Both estimation methods are subject to
important uncertainties that are discussed in the memorandum. Figures 2-15 to 2-16 provide
examples of concentration isopleths surrounding the New York, NY harbor area and DeButts
Rail Yard in Chattanooga, TN.
Figure 2-15 Concentration isopleths of New York, NY harbor area.
Port of New York, NY
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Regulatory Impact Analysis
Figure 2-16. Concentration isopleths of DeButts Rail Yard, Chattanooga, Tennessee.
DeButts Yard
Chattanooga, TN
Maximum
The size and characteristics of populations and households that reside within the area
encompassed by the two DPM concentration isopleths were determined. In addition to the
total population and number of households residing within each isopleth, the demographic
compositions were assessed, including age, income level, and race/ethnicity.
In summary, the population analysis suggests that for the 47 US marine ports and 37
US rail yards analyzed, at least 13 million people living in the vicinity of these facilities are
being exposed to ambient DPM levels that are 2.0 |ig/m3 and 0.2 |ig/m3 above those found in
areas further from these facilities.
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Air Quality and Resulting Health and Welfare Effects
2.4.2 Other Air Toxicsbenzene, 1,3-butadiene, formaldehyde, acetaldehyde,
acrolein, POM, naphthalene
Locomotive and marine diesel engine emissions contribute to ambient levels of other
air toxics known or suspected as human or animal carcinogens, or that have non-cancer health
T?^ Q T
effects. Noncancer health effects can result from chronic , subchronic , or acute inhalation
exposures, and include neurological, cardiovascular, liver, kidney, and respiratory effects as
well as effects on the immune and reproductive systems.
These other compounds include, but are not limited to, benzene, 1,3-butadiene,
formaldehyde, acetaldehyde, acrolein, polycyclic organic matter (POM), and naphthalene.
These compounds, except acetaldehyde, were identified as national or regional risk drivers in
the 1999 National-Scale Air Toxics Assessment (NAT A) and have significant inventory
contributions from mobile sources. Table 2-9 provides the mobile source inventory
contributions associated with these compounds.196 The reductions in locomotive and marine
diesel engine emissions in this rulemaking will help reduce exposure to these harmful
substances.
Table 2-9 Mobile Source Inventory Contribution to 1999 Emissions of NATA Risk Drivers"
1999 NATA Risk Driver
Benzene
1,3-Butadiene
Formaldehyde
Acrolein
Polycyclic organic matter (POM)
Naphthalene
Diesel PM and Diesel exhaust
organic gases
Percent of Emissions
Attributable to All
Mobile Sources
68%
58%
47%
25%
5%
27%
100%
Percent of Emissions
Attributable to Non-
road Sources
19%
17%
20%
11%
2%
6%
62%
This table is generated from data contained in the pollutant specific Microsoft Access database files found in
the County-Level Emission Summaries section of the 1999 NATA webpage
(http://www.epa.gov/ttn/atw/natal999/tables.html).
This POM inventory includes the 15 POM compounds: benzo[b]fluoranthene, benz[a]anthracene, indeno(l,2,3-
c,d)pyrene, benzo[k]fluoranthene, chrysene, benzo[a]pyrene, dibenz(a,h)anthracene, anthracene, pyrene,
benzo(g,h,i)perylene, fluoranthene, acenaphthylene, phenanthrene, fluorine, and acenaphthene.
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 laboratory
animal species).
s Defined in the IRIS database as exposure to a substance spanning approximately 10 of the lifetime of an
organism.
T Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.
2-65
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Regulatory Impact Analysis
Benzene: The EPA's IRIS database lists benzene as a known human carcinogen
(causing leukemia) by all routes of exposure, and that exposure is associated with additional
health effects, including genetic changes in both humans and animals and increased
proliferation of bone marrow cells in mice. 197'198>199 EPA states in its IRIS database that data
indicate a causal relationship between benzene exposure and acute lymphocytic leukemia and
suggests a relationship between benzene exposure and chronic non-lymphocytic leukemia and
chronic lymphocytic leukemia. A number of adverse noncancer health effects including
blood disorders, such as preleukemia and aplastic anemia, have also been associated with
long-term exposure to benzene.200'201 The most sensitive noncancer effect observed in
humans, based on current data, is the depression of the absolute lymphocyte count in
blood.202'203 In addition, recent work, including studies sponsored by the Health Effects
Institute (HEI), provides evidence that biochemical responses are occurring at lower levels
of benzene exposure than previously known.204'205' 206'207 EPA's IRIS program has not yet
evaluated these new data.
1,3-Butadiene: EPA has characterized 1,3-butadiene as carcinogenic to humans by
inhalation.208'209 There are numerous studies consistently demonstrating that 1,3-butadiene is
metabolized into genotoxic metabolites by experimental animals and humans. The specific
mechanisms of 1,3-butadiene-induced carcinogenesis are unknown; however, the scientific
evidence strongly suggests that the carcinogenic effects are mediated by genotoxic
metabolites. Animal data suggest that females may be more sensitive than males for cancer
effects; while there are insufficient data in humans from which to draw conclusions about
sensitive subpopulations. 1,3-Butadiene also causes a variety of reproductive and
developmental effects in mice; no human data on these effects are available. The most
sensitive effect was ovarian atrophy observed in a lifetime bioassay of female mice.210
Formaldehyde: Since 1987, EPA has classified formaldehyde as a probable human
carcinogen based on evidence in humans and in rats, mice, hamsters, and monkeys.211 EPA is
currently reviewing recently published epidemiological data. For instance, research
conducted by the National Cancer Institute (NCI) found an increased risk of nasopharyngeal
cancer and lymphohematopoietic malignancies such as leukemia among workers exposed to
formaldehyde.212'213 NCI is currently performing an update of these studies. A recent
National Institute of Occupational Safety and Health (NIOSH) study of garment workers also
found increased risk of death due to leukemia among workers exposed to formaldehyde.214
Extended follow-up of a cohort of British chemical workers did not find evidence of an
increase in nasopharyngeal or lymphohematopoeitic cancers, but a continuing statistically
significant excess in lung cancers was reported.215
In the past 15 years there has been substantial research on the inhalation dosimetry for
formaldehyde in rodents and primates by the CUT Centers for Health Research (formerly the
Chemical Industry Institute of Toxicology), with a focus on use of rodent data for refinement
of the quantitative cancer dose-response assessment.216'217'218 CIIT's risk assessment of
formaldehyde incorporated mechanistic and dosimetric information on formaldehyde.
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Air Quality and Resulting Health and Welfare Effects
Based on the developments of the last decade, in 2004, the working group of the
International Agency for Research on Cancer (IARC) concluded that formaldehyde is
carcinogenic to humans (Group 1), on the basis of sufficient evidence in humans and
sufficient evidence in experimental animals - a higher classification than previous IARC
evaluations. After reviewing the currently available epidemiological evidence, the IARC
(2006) characterized the human evidence for formaldehyde carcinogenicity as "sufficient,"
based upon the data on nasopharyngeal cancers; the epidemiologic evidence on leukemia was
characterized as "strong".219 EPA is reviewing the recent work cited above from the NCI and
NIOSH, as well as the analysis by the CUT Centers for Health Research and other studies, as
part of a reassessment of the human hazard and dose-response associated with formaldehyde.
Formaldehyde exposure also causes a range of noncancer health effects, including
irritation of the eyes (tearing of the eyes and increased blinking) and mucous membranes.
Acetaldehyde: Acetaldehyde is classified in EPA's IRIS database as a probable
human carcinogen, based on nasal tumors in rats, and is considered toxic by the inhalation,
oral, and intravenous routes.220 The primary noncancer effects of exposure to acetaldehyde
vapors include irritation of the eyes, skin, and respiratory tract.221 Some asthmatics have been
shown to be a sensitive subpopulation to decrements in functional expiratory volume (FEV1
test) and bronchoconstriction upon acetaldehyde inhalation.222
In short-term (4 week) rat studies, degeneration of olfactory epithelium was observed
T)1 T? A
at various concentration levels of acetaldehyde exposure. ' Data from these studies were
used by EPA to develop an inhalation reference concentration. The agency is currently
conducting a reassessment of the health hazards from inhalation exposure to acetaldehyde.
Acrolein: EPA determined in 2003 that the human carcinogenic potential of acrolein
could not be determined because the available data were inadequate. No information was
available on the carcinogenic effects of acrolein in humans and the animal data provided
inadequate evidence of carcinogenicity.225
Acrolein is extremely acrid and irritating to humans when inhaled, with acute
exposure resulting in upper respiratory tract irritation, mucus hypersecretion and congestion.
Levels considerably lower than 1 ppm (2.3 mg/m3) elicit subjective complaints of eye and
nasal irritation and a decrease in the respiratory rate.226'227 Lesions to the lungs and upper
respiratory tract of rats, rabbits, and hamsters have been observed after subchronic exposure
to acrolein. Based on animal data, individuals with compromised respiratory function (e.g.,
emphysema, asthma) are expected to be at increased risk of developing adverse responses to
strong respiratory irritants such as acrolein. This was demonstrated in mice with allergic
airway-disease by comparison to non-diseased in a study of the acute respiratory irritant
effects of acrolein.228
The Agency is currently in the process of conducting an assessment of acute exposure
effects for acrolein. The intense irritancy of this carbonyl has been demonstrated during
controlled tests in human subjects who suffer intolerable eye and nasal mucosal sensory
reactions within minutes of exposure.229
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Regulatory Impact Analysis
Polycyclic Organic Matter (POM): POM is generally defined as a large class of
organic compounds which have multiple benzene rings and a boiling point greater than 100
degrees Celsius. Many of the compounds included in the class of compounds known as POM
are classified by EPA as probable human carcinogens based on animal data. One of these
compounds, naphthalene, is discussed separately below. Recent studies have found that
maternal exposures to PAHs ( a subclass of POM), in a population of pregnant women, were
associated with several adverse birth outcomes, including low birth weight and reduced length
at birth as well as impaired cognitive development at age three.230'231 EPA has not yet
evaluated these recent studies.
Naphthalene: Naphthalene is found in small quantities in gasoline and diesel fuels but
is primarily a product of combustion. Naphthalene emissions have been measured in larger
quantities in both gasoline and diesel exhaust and evaporative emissions from mobile sources.
EPA recently released an external review draft of a reassessment of the inhalation
fy^fy
carcinogenicity of naphthalene based on a number of recent animal carcinogenicity studies.
The draft reassessment recently completed external peer review.233 Based on external peer
review comments received to date, additional analyses are being undertaken. This external
review draft does not represent official agency opinion and was released solely for the
purposes of external peer review and public comment. Once EPA evaluates public and peer
reviewer comments, the document will be revised. The National Toxicology Program listed
naphthalene as "reasonably anticipated to be a human carcinogen" in 2004 on the basis of
bioassays reporting clear evidence of carcinogenicity in rats and some evidence of
carcinogenicity in mice.234 California EPA has released a new risk assessment for
naphthalene, and the IARC has reevaluated naphthalene and re-classified it as Group 2B:
possibly carcinogenic to humans.235 Naphthalene also causes a number of chronic non-cancer
effects in animals, including abnormal cell changes and growth in respiratory and nasal
tissues.236
In addition to reducing substantial amounts of NOX and PM2.5 emissions from
locomotive and marine diesel engines the standards being finalized today will also reduce air
toxics emitted from these engines thereby helping to mitigate some of the adverse health
effects associated with operation of these engines.
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Air Quality and Resulting Health and Welfare Effects
Appendix 2A - PM2.5 Nonattainment
Table 2A 1997 PM2.5 Nonattainment Areas and Populations (Data is current through October 2007 and
Population Numbers are from 2000 Census Data)
County
Area Name
County
NAWhole/Part
Design Value
(|lg/m3)
Pop (2000)
ALABAMA
Jackson Co
Jefferson Co
Shelby Co
Walker Co
Chattanooga, AL-TN-GA
Birmingham, AL
Birmingham, AL
Birmingham, AL
Part
Whole
Whole
Part
16.1
17.3
17.3
17.3
1,578
662,047
143,293
2,272
CALIFORNIA
Fresno Co
Kern Co
Kings Co
Los Angeles Co
Madera Co
Merced Co
Orange Co
Riverside Co
San Bernardino Co
San Joaquin Co
Stanislaus Co
Tulare Co
San Joaquin Valley, CA
San Joaquin Valley, CA
San Joaquin Valley, CA
Los Angeles-South Coast Air
Basin, CA
San Joaquin Valley, CA
San Joaquin Valley, CA
Los Angeles-South Coast Air
Basin, CA
Los Angeles-South Coast Air
Basin, CA
Los Angeles-South Coast Air
Basin, CA
San Joaquin Valley, CA
San Joaquin Valley, CA
San Joaquin Valley, CA
Whole
Part
Whole
Part
Whole
Whole
Whole
Part
Part
Whole
Whole
Whole
21.8
21.8
21.8
27.8
21.8
21.8
27.8
27.8
27.8
21.8
21.8
21.8
799,407
550,220
129,461
9,222,280
123,109
210,554
2,846,289
1,194,859
1,330,159
563,598
446,997
368,021
CONNECTICUT
Fairfield Co
New Haven Co
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
Whole
Whole
17.7
17.7
882,567
824,008
DELAWARE
New Castle Co
Philadelphia- Wilmington, PA-
NJ-DE
Whole
16.2
500,265
DISTRICT OF COLUMBIA
Entire District
Washington, DC-MD-VA
Whole
15.8
572,059
GEORGIA
Barrow Co
Bartow Co
Bibb Co
Carroll Co
Catoosa Co
Cherokee Co
Atlanta, GA
Atlanta, GA
Macon, GA
Atlanta, GA
Chattanooga, AL-TN-GA
Atlanta, GA
Whole
Whole
Whole
Whole
Whole
Whole
18
18
15.2
18
16.1
18
46,144
76,019
153,887
87,268
53,282
141,903
A2-1
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Regulatory Impact Analysis
County
Clayton Co
Cobb Co
Coweta Co
De Kalb Co
Douglas Co
Fayette Co
Floyd Co
Forsyth Co
Fulton Co
Gwinnett Co
Hall Co
Heard Co
Henry Co
Monroe Co
Newton Co
Paulding Co
Putnam Co
Rockdale Co
Spalding Co
Walker Co
Walton Co
Area Name
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Rome, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Macon, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Chattanooga, AL-TN-GA
Atlanta, GA
County
NAWhole/Part
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Part
Whole
Part
Whole
Whole
Part
Whole
Whole
Whole
Whole
Design Value
(llg/m3)
18
18
18
18
18
18
15.6
18
18
18
18
18
18
15.2
18
18
18
18
18
16.1
18
Pop (2000)
236,517
607,751
89,215
665,865
92,174
91,263
90,565
98,407
816,006
588,448
139,277
170
119,341
950
62,001
81,678
3,088
70,111
58,417
61,053
60,687
ILLINOIS
Cook Co
DuPage Co
Grundy Co
Kane Co
Kendall Co
Lake Co
Madison Co
Me Henry Co
Monroe Co
Randolph Co
St Clair Co
Will Co
Chicago-Gary-Lake County,
IL-IN
Chicago-Gary-Lake County,
IL-IN
Chicago-Gary-Lake County,
IL-IN
Chicago-Gary-Lake County,
IL-IN
Chicago-Gary-Lake County,
IL-IN
Chicago-Gary-Lake County,
IL-IN
St. Louis, MO-IL
Chicago-Gary-Lake County,
IL-IN
St. Louis, MO-IL
St. Louis, MO-IL
St. Louis, MO-IL
Chicago-Gary-Lake County,
IL-IN
Whole
Whole
Part
Whole
Part
Whole
Whole
Whole
Whole
Part
Whole
Whole
17.7
17.7
17.7
17.7
17.7
17.7
17.5
17.7
17.5
17.5
17.5
17.7
5,376,741
904,161
6,309
404,119
28,417
644,356
258,941
260,077
27,619
3,627
256,082
502,266
INDIANA
A2-2
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Air Quality and Resulting Health and Welfare Effects
County
Clark Co
Dearborn Co
Dubois Co
Floyd Co
Gibson Co
Hamilton Co
Hendricks Co
Jefferson Co
Johnson Co
Lake Co
Marion Co
Morgan Co
Pike Co
Porter Co
Spencer Co
Vanderburgh Co
Warrick Co
Area Name
Louisville, KY-IN
Cincinnati-Hamilton, OH-KY-
IN
Evansville, IN
Louisville, KY-IN
Evansville, IN
Indianapolis, IN
Indianapolis, IN
Louisville, KY-IN
Indianapolis, IN
Chicago-Gary-Lake County,
IL-IN
Indianapolis, IN
Indianapolis, IN
Evansville, IN
Chicago-Gary-Lake County,
IL-IN
Evansville, IN
Evansville, IN
Evansville, IN
County
NAWhole/Part
Whole
Part
Whole
Whole
Part
Whole
Whole
Part
Whole
Whole
Whole
Whole
Part
Whole
Part
Whole
Whole
Design Value
(llg/m3)
16.9
17.8
16.2
16.9
16.2
16.7
16.7
16.9
16.7
17.7
16.7
16.7
16.2
17.7
16.2
16.2
16.2
Pop (2000)
96,472
10,434
39,674
70,823
3,698
182,740
104,093
16,770
115,209
484,564
860,454
66,689
4,633
146,798
5,092
171,922
52,383
KENTUCKY
Boone Co
Boyd Co
Bullitt Co
Campbell Co
Jefferson Co
Kenton Co
Lawrence Co
Cincinnati-Hamilton, OH-KY-
IN
Huntington-Ashland, WV-KY-
OH
Louisville, KY-IN
Cincinnati-Hamilton, OH-KY-
IN
Louisville, KY-IN
Cincinnati-Hamilton, OH-KY-
IN
Huntington-Ashland, WV-KY-
OH
Whole
Whole
Whole
Whole
Whole
Whole
Part
17.8
17.2
16.9
17.8
16.9
17.8
17.2
85,991
49,752
61,236
88,616
693,604
151,464
1,050
MARYLAND
Anne Arundel Co
Baltimore (City)
Baltimore Co
Carroll Co
Charles Co
Frederick Co
Harford Co
Howard Co
Montgomery Co
Baltimore, MD
Baltimore, MD
Baltimore, MD
Baltimore, MD
Washington, DC-MD-VA
Washington, DC-MD-VA
Baltimore, MD
Baltimore, MD
Washington, DC-MD-VA
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
16.6
16.6
16.6
16.6
15.8
15.8
16.6
16.6
15.8
489,656
651,154
754,292
150,897
120,546
195,277
218,590
247,842
873,341
A2-3
-------
Regulatory Impact Analysis
County
Prince George's Co
Washington Co
Area Name
Washington, DC-MD-VA
Martinsburg, WV-Hagerstown,
MD
County
NAWhole/Part
Whole
Whole
Design Value
(llg/m3)
15.8
16.3
Pop (2000)
801,515
131,923
MICHIGAN
Livingston Co
Macomb Co
Monroe Co
Oakland Co
St Clair Co
Washtenaw Co
Wayne Co
Detroit- Ann Arbor, MI
Detroit- Ann Arbor, MI
Detroit- Ann Arbor, MI
Detroit- Ann Arbor, MI
Detroit- Ann Arbor, MI
Detroit- Ann Arbor, MI
Detroit- Ann Arbor, MI
Whole
Whole
Whole
Whole
Whole
Whole
Whole
19.5
19.5
19.5
19.5
19.5
19.5
19.5
156,951
788,149
145,945
1,194,156
164,235
322,895
2,061,162
MISSOURI
Franklin Co
Jefferson Co
St Charles Co
St Louis
St Louis Co
St. Louis, MO-IL
St. Louis, MO-IL
St. Louis, MO-IL
St. Louis, MO-IL
St. Louis, MO-IL
Whole
Whole
Whole
Whole
Whole
17.5
17.5
17.5
17.5
17.5
93,807
198,099
283,883
348,189
1,016,315
MONTANA
Lincoln Co
Libby, MT
Part
16.2
2,626
NEW JERSEY
Bergen Co
Burlington Co
Camden Co
Essex Co
Gloucester Co
Hudson Co
Mercer Co
Middlesex Co
Monmouth Co
Morris Co
Passaic Co
Somerset Co
Union Co
New York-N. New Jersey-
Long Island, NY-NJ-CT
Philadelphia- Wilmington, PA-
NJ-DE
Philadelphia- Wilmington, PA-
NJ-DE
New York-N. New Jersey-
Long Island, NY-NJ-CT
Philadelphia- Wilmington, PA-
NJ-DE
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
17.7
16.2
16.2
17.7
16.2
17.7
17.7
17.7
17.7
17.7
17.7
17.7
17.7
884,118
423,394
508,932
793,633
254,673
608,975
350,761
750,162
615,301
470,212
489,049
297,490
522,541
A2-4
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Air Quality and Resulting Health and Welfare Effects
County
Area Name
Long Island, NY-NJ-CT
County
NAWhole/Part
Design Value
(llg/m3)
Pop (2000)
New York
Bronx Co
Kings Co
Nassau Co
New York Co
Orange Co
Queens Co
Richmond Co
Rockland Co
Suffolk Co
Westchester Co
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
New York-N. New Jersey-
Long Island, NY-NJ-CT
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
17.7
17.7
17.7
17.7
17.7
17.7
17.7
17.7
17.7
17.7
1,332,650
2,465,326
1,334,544
1,537,195
341,367
2,229,379
443,728
286,753
1,419,369
923,459
NORTH CAROLINA
Catawba Co
Davidson Co
Guilford Co
Hickory, NC
Greensboro-Winston Salem-
High Point, NC
Greensboro-Winston Salem-
High Point, NC
Whole
Whole
Whole
15.5
15.8
15.8
141,685
147,246
421,048
OHIO
Adams Co
Ashtabula Co
Belmont Co
Butler Co
Clark Co
Clermont Co
Coshocton Co
Cuyahoga Co
Delaware Co
Fairfield Co
Franklin Co
Gallia Co
Greene Co
Hamilton Co
Huntington-Ashland, WV-KY-
OH
Cleveland-Akron-Lorain, OH
Wheeling, WV-OH
Cincinnati-Hamilton, OH-KY-
IN
Dayton-Springfield, OH
Cincinnati-Hamilton, OH-KY-
IN
Columbus, OH
Cleveland-Akron-Lorain, OH
Columbus, OH
Columbus, OH
Columbus, OH
Huntington-Ashland, WV-KY-
OH
Dayton-Springfield, OH
Cincinnati-Hamilton, OH-KY-
Part
Part
Whole
Whole
Whole
Whole
Part
Whole
Whole
Whole
Whole
Part
Whole
Whole
17.2
18.3
15.7
17.8
15.2
17.8
16.7
18.3
16.7
16.7
16.7
17.2
15.2
17.8
2,374
23,239
70,226
332,807
144,742
177,977
1,286
1,393,978
109,989
122,759
1,068,978
3,625
147,886
845,303
A2-5
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Regulatory Impact Analysis
County
Jefferson Co
Lake Co
Lawrence Co
Licking Co
Lorain Co
Medina Co
Montgomery Co
Portage Co
Scioto Co
Stark Co
Summit Co
Warren Co
Washington Co
Area Name
IN
Steubenville-Weirton, OH-WV
Cleveland-Akron-Lorain, OH
Huntington-Ashland, WV-KY-
OH
Columbus, OH
Cleveland-Akron-Lorain, OH
Cleveland-Akron-Lorain, OH
Dayton-Springfield, OH
Cleveland-Akron-Lorain, OH
Huntington-Ashland, WV-KY-
OH
Canton-Massillon, OH
Cleveland-Akron-Lorain, OH
Cincinnati-Hamilton, OH-KY-
IN
Parkersburg-Marietta, WV-OH
County
NAWhole/Part
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Design Value
(llg/m3)
17.8
18.3
17.2
16.7
18.3
18.3
15.2
18.3
17.2
17.3
18.3
17.8
16
Pop (2000)
73,894
227,511
62,319
145,491
284,664
151,095
559,062
152,061
79,195
378,098
542,899
158,383
63,251
PENNSYLVANIA
Allegheny Co
Allegheny Co
Armstrong Co
Beaver Co
Berks Co
Bucks Co
Butler Co
Cambria Co
Chester Co
Cumberland Co
Dauphin Co
Delaware Co
Greene Co
Indiana Co
Lancaster Co
Lawrence Co
Lebanon Co
Montgomery Co
Philadelphia Co
Liberty-Clairton, PA
Pittsburgh-Beaver Valley, PA
Pittsburgh-Beaver Valley, PA
Pittsburgh-Beaver Valley, PA
Reading, PA
Philadelphia- Wilmington, PA-
NJ-DE
Pittsburgh-Beaver Valley, PA
Johnstown, PA
Philadelphia- Wilmington, PA-
NJ-DE
Harrisburg-Lebanon-Carlisle,
PA
Harrisburg-Lebanon-Carlisle,
PA
Philadelphia- Wilmington, PA-
NJ-DE
Pittsburgh-Beaver Valley, PA
Johnstown, PA
Lancaster, PA
Pittsburgh-Beaver Valley, PA
Harrisburg-Lebanon-Carlisle,
PA
Philadelphia- Wilmington, PA-
NJ-DE
Philadelphia- Wilmington, PA-
Part
Part
Part
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Part
Part
Whole
Part
Whole
Whole
Whole
21.2
16.9
16.9
16.9
16.4
16.2
16.9
15.8
16.2
15.7
15.7
16.2
16.9
15.8
17
16.9
15.7
16.2
16.2
21,600
1,260,066
3,691
181,412
373,638
597,635
174,083
152,598
433,501
213,674
251,798
550,864
1,714
11,833
470,658
1,198
120,327
750,097
1,517,550
A2-6
-------
Air Quality and Resulting Health and Welfare Effects
County
Washington Co
Westmoreland Co
York Co
Area Name
NJ-DE
Pittsburgh-Beaver Valley, PA
Pittsburgh-Beaver Valley, PA
York, PA
County
NAWhole/Part
Whole
Whole
Whole
Design Value
(llg/m3)
16.9
16.9
17
Pop (2000)
202,897
369,993
381,751
TENNESSEE
Anderson Co
Blount Co
Hamilton Co
Knox Co
Loudon Co
Roane Co
Knoxville, TN
Knoxville, TN
Chattanooga, AL-TN-GA
Knoxville, TN
Knoxville, TN
Knoxville, TN
Whole
Whole
Whole
Whole
Whole
Part
16.4
16.4
16.1
16.4
16.4
16.4
71,330
105,823
307,896
382,032
39,086
737
VIRGINIA
Alexandria
Arlington Co
Fairfax
Fairfax Co
Falls Church
Loudoun Co
Manassas
Manassas Park
Prince William Co
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Washington, DC-MD-VA
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
Whole
15.8
15.8
15.8
15.8
15.8
15.8
15.8
15.8
15.8
128,283
189,453
21,498
969,749
10,377
169,599
35,135
10,290
280,813
WEST VIRGINIA
Berkeley Co
Brooke Co
Cabell Co
Hancock Co
Kanawha Co
Marshall Co
Mason Co
Ohio Co
Pleasants Co
Putnam Co
Wayne Co
Wood Co
TOTAL
Martinsburg, WV-Hagerstown,
MD
Steubenville-Weirton, OH-WV
Huntington-Ashland, WV-KY-
OH
Steubenville-Weirton, OH-WV
Charleston, WV
Wheeling, WV-OH
Huntington-Ashland, WV-KY-
OH
Wheeling, WV-OH
Parkersburg-Marietta, WV-OH
Charleston, WV
Huntington-Ashland, WV-KY-
OH
Parkersburg-Marietta, WV-OH
208 Counties
Whole
Whole
Whole
Whole
Whole
Whole
Part
Whole
Part
Whole
Whole
Whole
16.3
17.8
17.2
17.8
17.1
15.7
17.2
15.7
16
17.1
17.2
16
75,905
25,447
96,784
32,667
200,073
35,519
2,774
47,427
1,675
51,589
42,903
87,986
88,394,361
A2-7
-------
Regulatory Impact Analysis
Appendix 2B - Current 8-Hour Ozone Nonattainment Areas
Table 2B 1997 8-Hour Ozone Nonattainment Areas and Populations (Data is current through October
2007 and Population Numbers are from 2000 Census Data)
Area Name Category/ 2000 Pop
Class
Albany-Schenectady-Troy, NY
Allegan Co, Ml
Allentown-Bethlehem-Easton, PA
Amadorand Calaveras Cos (Central Mtn), CA
Atlanta, GA
Baltimore, MD
Baton Rouge, LA
Beaumont-Port Arthur, TX
Berkeley and Jefferson Counties, WV
Boston-Lawrence-Worcester (E. MA), MA
Boston-Manchester-Portsmouth(SE),NH
Buffalo-Niagara Falls, NY
Charlotte-Gastonia-Rock Hill, NC-SC
Chattanooga, TN-GA
Chicago-Gary-Lake County, IL-IN
Chico, CA
Cincinnati-Hamilton, OH-KY-IN
Clearfield and Indiana Cos, PA
Cleveland-Akron-Lorain, OH
Columbia, SC
Columbus, OH
Dallas-Fort Wo rth, TX
Denver-Boulder-Greeley-Ft Collins-Love., CO
Detroit-Ann Arbor, Ml
Door Co, Wl
Erie, PA
Essex Co (Whiteface Mtn), NY
Fayetteville, NC
Frederick Co, VA
Greater Connecticut, CT
Greene Co, PA
Greensboro-Winston Salem-High Point, NC
Greenville-Spartanburg-Anderson, SC
Haywood and Swain Cos (Great Smoky NP), NC
Hickory-Morganton-Lenoir, NC
Houston-Galveston-Brazoria, TX
Imperial Co, CA
Indianapolis, IN
Jamestown, NY
Jefferson Co, NY
Johnson City-Kingsport-Bristol, TN
Kern Co (Eastern Kern), CA
Kewaunee Co, Wl
Knoxville, TN
Las Vegas, NV
Los Angeles-San Bernardino Cos(W Mojave),CA
Subpart 1
Subpart 1
Subpart 1
Subpart 1
Marginal
Moderate
Marginal
Marginal
Subpart 1 EAC
Moderate
Moderate
Subpart 1
Moderate
Subpart 1 EAC
Moderate
Subpart 1
Subpart 1
Subpart 1
Moderate
Subpart 1 EAC
Subpart 1
Moderate
Subpart 1 EAC
Marginal
Subpart 1
Subpart 1
Subpart 1
Subpart 1 EAC
Subpart 1 EAC
Moderate
Subpart 1
Marginal EAC
Subpart 1 EAC
Subpart 1
Subpart 1 EAC
Moderate
Marginal
Subpart 1
Subpart 1
Moderate
Subpart 1 EAC
Subpart 1
Subpart 1
Subpart 1
Subpart 1
Moderate
923,778
105,665
637,958
75,654
4,228,492
2,512,431
636,214
385,090
118,095
5,534,130
696,713
1,170,111
1,476,564
372,264
8,757,808
203,171
1,891,518
172,987
2,945,831
494,518
1,541,930
5,030,828
2,811,580
4,932,383
27,961
280,843
1,000
302,963
82,794
1,543,919
40,672
1,285,879
799,147
288
309,512
4,669,571
142,361
1,607,486
139,750
111,738
206,611
99,251
20,187
713,755
1,348,864
656,408
A2-8
-------
Air Quality and Resulting Health and Welfare Effects
Area Name Category/ 2000 Pop
Class
Los Angeles South Coast Air Basin, CA
Macon, GA
Manitowoc Co, Wl
Mariposa and Tuolumne Cos (Southern Mtn),CA
Memphis, TN-AR
Milwaukee-Racine, Wl
Murray Co (Chattahoochee Nat Forest), GA
Nashville, TN
Nevada Co. (Western Part), CA
NewYork-N. New Jersey-Long Island, NY-NJ-CT
Philadelphia-Wilmin-AtlanticCi,PA-NJ-MD-DE
Phoenix-Mesa, AZ
Pittsburgh-Beaver Valley, PA
Poughkeepsie, NY
Providence (All Rl), Rl
Raleigh-Durham-Chapel Hill, NC
Riverside Co, (Coachella Valley), CA
Roanoke, VA
Rochester, NY
Sacramento Metro, CA
San Antonio, TX
San Diego, CA
San Francisco Bay Area, CA
San Joaquin Valley, CA
Scranton-Wilkes-Barre, PA
Sheboygan, Wl
Springfield (Western MA), MA
St Louis, MO-IL
State College, PA
Sutter Co (Sutter Buttes), CA
Ventura Co, CA
Washington, DC-MD-VA
Washington Co (Hagerstown), MD
York, PA
Youngstown-Warren-Sharon, OH-PA (PA Portion)
Total (81 areas)
Severe 17
Subpart 1
Subpart 1
Subpart 1
Marginal
Moderate
Subpart 1
Subpart 1 EAC
Subpart 1
Moderate
Moderate
Subpart 1
Subpart 1
Moderate
Moderate
Subpart 1
Serious
Subpart 1 EAC
Subpart 1
Serious
Subpart 1 EAC
Subpart 1
Marginal
Serious
Subpart 1
Moderate
Moderate
Moderate
Subpart 1
Subpart 1
Moderate
Moderate
Subpart 1 EAC
Subpart 1
Subpart 1
14,593,587
153,937
82,887
71,631
948,338
1,839,149
1,000
1,097,810
77,735
19,634,122
7,333,475
3,086,045
2,431,087
717,262
1,048,319
1,244,053
324,750
235,932
1,098,201
1,978,348
1,559,975
2,813,431
6,541,828
3,191,367
699,312
112,646
814,967
2,504,603
135,758
1
753,197
4,452,498
131,923
473,043
120,293
144,349,183
A2-9
-------
Regulatory Impact Analysis
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electronically at:
ftp://ftp.arb.ca.gov/carbis/msprog/offroad/marinevess/documents/portstudy0406.pdf
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30 For example, see letter dated September 23, 2006 from Northeast States for Coordinated Air
Use Management to Administrator Stephen L. Johnson; September 7, 2006 letter from
Executive Officer of the California Air Resources Board to Acting Assistant Administrator
William L. Wehrum; August 9, 2006 letter from State and Territorial Air Pollution Program
Administrators and Association of Local Air Pollution Control Officials (and other
organizations) to Administrator Stephen L. Johnson; January 20, 2006 letter from Executive
Director, Puget Sound Clean Air Agency to Administrator Stephen L. Johnson; June 30,
2005 letter from Western Regional Air Partnership to Administrator Stephen L. Johnson.
31 National Research Council, 1993. Protecting Visibility in National Parks and Wilderness
Areas. National Academy of Sciences Committee on Haze in National Parks and Wilderness
Areas. National Academy Press, Washington, DC. This book is available electronically at
http://www.nap.edu/books/0309048443/html/ and is available in Docket EPA-HQ-OAR-
2004-0008.
32U.S. EPA , National Ambient Air Quality Standards for Particulate Matter; Proposed Rule;
January 17, 2006, Vol71 p 2676. This information is available electronically at:
http://epa.gov/fedrgstr/EPA-AIR/2006/January/Day-17/al 77.pdf
33 U.S. EPA (2004) Air Quality Criteria for Particulate Matter (Oct 2004), Volume I
Document No. EPA600/P-99/002aF and Volume II Document No. EPA600/P-99/002bF.
This document is available in Docket EPA-HQ-OAR-2004-0008.
34 U.S. EPA (2005) Review of the National Ambient Air Quality Standard for Particulate
Matter: Policy Assessment of Scientific and Technical Information, OAQPS Staff Paper.
EPA-452/R-05-005. This document is available in Docket EPA-HQ-OAR-2004-0008.
35 U.S. EPA. 1993. Effects of the 1990 Clean Air Act Amendments on Visibility in Class I
Areas: An EPA Report to Congress. EPA452-R-93-014.
36U.S. EPA (2002) Latest Findings on National Air Quality - 2002 Status and Trends. EPA
454/K-03-001.
37National Park Service. Air Quality in the National Parks, Second edition. NFS, Air
Resources Division. D 2266. September 2002.
38U.S. EPA (2002) Latest Findings on National Air Quality - 2002 Status and Trends. EPA
454/K-03-001.
39 Environmental Protection Agency (2003). Response Of Surface Water Chemistry to the
Clean Air Act Amendments of 1990. National Health and Environmental Effects Research
Laboratory, Office of Research and Development, U.S. Environmental Protection Agency.
Research Triangle Park, NC. EPA 620/R-03/001.
40 Fenn, M.E. and Blubaugh, T. J. (2005) Winter Deposition of Nitrogen and Sulfur in the
Eastern Columbia River Gorge National Scenic Area, USDA Forest Service.
41 Galloway, J. N.; Cowling, E. B. (2002). Reactive nitrogen and the world: 200 years of
change. Ambio 31: 64-71.
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Air Quality and Resulting Health and Welfare Effects
42 Bricker, Suzanne B., et al., National Estuarine Eutrophication Assessment, Effects of
Nutrient Enrichment in the Nation's Estuaries, National Ocean Service, National Oceanic and
Atmospheric Administration, September, 1999.
43 Smith, W.H. 1991. "Air pollution and Forest Damage." Chemical Engineering News,
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44Gawel, I.E.; Ahner, B.A.; Friedland, A.J.; and Morel, F.M.M. 1996. "Role for heavy metals
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45 Cotrufo, M.F.; DeSanto, A.V.; Alfani, A.; et al. 1995. "Effects of urban heavy metal
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46Niklinska, M.; Laskowski, R.; Maryanski, M. 1998. "Effect of heavy metals and storage
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47 Mason, R.P. and Sullivan, K.A. 1997. "Mercury in Lake Michigan." Environmental Science
& Technology, 31: 942-947. (from Delta Report "Atmospheric deposition of toxics to the
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48Landis, M.S. and Keeler, GJ. 2002. "Atmospheric mercury deposition to Lake Michigan
during the Lake Michigan Mass Balance Study." Environmental Science & Technology, 21:
4518-24.
49U.S. EPA. 2000. EPA453/R-00-005, "Deposition of Air Pollutants to the Great Waters:
Third Report to Congress," Office of Air Quality Planning and Standards, Research Triangle
Park, North Carolina.
50 NSTC 1999
51 Callender, E. and Rice, K.C. 2000. "The Urban Environmental Gradient: Anthropogenic
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52 Rice, K.C. 1999. "Trace Element Concentrations in Streambed Sediment Across the
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53 Ely, JC; Neal, CR; Kulpa, CF; et al. 2001. "Implications of Platinum-Group Element
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35:3816-3822.
54U.S. EPA. 1998. EPA454/R-98-014, "Locating and Estimating Air Emissions from Sources
of Poly cyclic Organic Matter," Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina.
55 U.S. EPA. 1998. EPA454/R-98-014, "Locating and Estimating Air Emissions from Sources
of Poly cyclic Organic Matter," Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina.
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56 Simcik, M.F.; Eisenreich, S.J.; Golden, K.A.; et al. 1996. "Atmospheric Loading of
Polycyclic Aromatic Hydrocarbons to Lake Michigan as Recorded in the Sediments."
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57 Simcik, M.F.; Eisenreich, S.J.; and Lioy, PJ. 1999. "Source apportionment and source/sink
relationship of PAHs in the coastal atmosphere of Chicago and Lake Michigan." Atmospheric
Environment, 33: 5071-5079.
58 Arzayus, K.M.; Dickhut, R.M.; and Canuel, E.A. 2001. "Fate of Atmospherically Deposited
Polycyclic Aromatic Hydrocarbons (PAHs) in Chesapeake Bay." Environmental Science &
Technology, 35, 2178-2183.
59Park, J.S.; Wade, T.L.; and Sweet, S. 2001. "Atmospheric distribution of polycyclic
aromatic hydrocarbons and deposition to Galveston Bay, Texas, USA." Atmospheric
Environment, 35: 3241-3249.
60Poor, N.; Tremblay, R.; Kay, H.; et al. 2002. "Atmospheric concentrations and dry
deposition rates of polycyclic aromatic hydrocarbons (PAHs) for Tampa Bay, Florida, USA."
Atmospheric Environment 38: 6005-6015.
61 Arzayus, K.M.; Dickhut, R.M.; and Canuel, E.A. 2001. "Fate of Atmospherically Deposited
Polycyclic Aromatic Hydrocarbons (PAHs) in Chesapeake Bay." Environmental Science &
Technology, 35, 2178-2183.
62 U.S. EPA. 2000. EPA453/R-00-005, "Deposition of Air Pollutants to the Great Waters:
Third Report to Congress," Office of Air Quality Planning and Standards, Research Triangle
Park, North Carolina.
63 Van Metre, P.C.; Mahler, B.J.; and Furlong, E.T. 2000. "Urban Sprawl Leaves its PAH
Signature." Environmental Science & Technology, 34: 4064-4070.
64 Cousins, IT.; Beck, A.J.; and Jones, K.C. 1999. "A review of the processes involved in the
exchange of semi-volatile organic compounds across the air-soil interface." The Science of
the Total Environment, 228: 5-24.
65 Tuhackova, J. et al. (2001) Hydrocarbon deposition and soil microflora as affected by
highway traffic. Environmental Pollution, 113: 255-262.
66U.S. EPA. 1996. Air Quality Criteria for Ozone and Related Photochemical Oxidants,
EPA600-P-93-004aF.
67U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S.
EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.
68 U.S. EPA, Review of the National Ambient Air Quality Standards for Ozone: Policy
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69 Bates, D.V.; Baker-Anderson, M.; Sizto, R. (1990) Asthma attack periodicity: a study of
hospital emergency visits in Vancouver. Environ. Res. 51: 51-70.
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Air Quality and Resulting Health and Welfare Effects
70 Thurston, G.D.; Ito, K.; Kinney, P.L.; Lippmann, M. (1992) A multi-year study of air
pollution and respiratory hospital admissions in three New York State metropolitan areas:
results for 1988 and 1989 summers. J. Exposure Anal. Environ. Epidemiol. 2:429-450.
71 Thurston, G.D.; Ito, K.; Hayes, C.G.; Bates, D.V.; Lippmann, M. (1994) Respiratory
hospital admissions and summertime haze air pollution in Toronto, Ontario: consideration of
the role of acid aerosols. Environ. Res. 65: 271-290.
72 Lipfert, F.W.; Hammerstrom, T. (1992) Temporal patterns in air pollution and hospital
admissions. Environ. Res. 59: 374-399.
73 Burnett, R.T.; Dales, R.E.; Raizenne, M.E.; Krewski, D.; Summers, P.W.; Roberts, G.R.;
Raad-Young, M.; Dann,T.; Brook, J. (1994) Effects of low ambient levels of ozone and
sulfates on the frequency of respiratory admissions to Ontario hospitals. Environ. Res. 65:
172-194"
74 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S.
EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.
75 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S.
EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.
76 Devlin, R. B.; McDonnell, W. F.; Mann, R.; Becker, S.; House, D. E.; Schreinemachers, D.;
Koren, H. S. (1991) Exposure of humans to ambient levels of ozone for 6.6 hours causes
cellullar and biochemical changes in the lung. Am. J. Respir. Cell Mol. Biol. 4: 72-81.
77 Koren, H. S.; Devlin, R. B.; Becker, S.; Perez, R.; McDonnell, W. F. (1991) Time-
dependent changes of markers associated with inflammation in the lungs of humans exposed
to ambient levels of ozone. Toxicol. Pathol. 19: 406-411.
78 Koren, H. S.; Devlin, R. B.; Graham, D. E.; Mann, R.; McGee, M. P.; Horstman, D. H.;
Kozumbo, W. J.; Becker, S.; House, D. E.; McDonnell, W. F.; Bromberg, P. A. (1989a)
Ozone-induced inflammation in the lower airways of human subjects. Am. Rev. Respir. Dis.
139:407-415.
79 Schelegle, E.S.; Siefkin, A.D.; McDonald, RJ. (1991) Time course of ozone-induced
neutrophilia in normal humans. Am. Rev. Respir. Dis. 143:1353-1358.
80 U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,
EPA600-P-93-004aF; (See page 7-171).
81 Hodgkin, I.E.; Abbey, D.E.; Euler, G.L.; Magie, A.R. (1984) COPD prevalence in
nonsmokers in high and low photochemical air pollution areas. Chest 86: 830-838.
82 Euler, G.L.; Abbey, D.E.; Hodgkin, I.E.; Magie, A.R. (1988) Chronic obstructive
pulmonary disease symptom effects of long-term cumulative exposure to ambient levels of
total oxidants and nitrogen dioxide in California Seventh-day Adventist residents. Arch.
Environ. Health 43: 279-285.
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Regulatory Impact Analysis
83 Abbey, D.E.; Petersen, F.; Mills, P.K.; Beeson, W.L. (1993) Long-term ambient
concentrations of total suspended particulates, ozone, and sulfur dioxide and respiratory
symptoms in a nonsmoking population. Arch. Environ. Health 48: 33-46.
84 U.S. EPA, Review of the National Ambient Air Quality Standards for Ozone: Policy
Assessment of Scientific and Technical Information, OAQPS Staff Paper, Washington, DC,
EPA-452/R-07-003, January 2007.
85 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S.
EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.
86U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S.
EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.
87 Avol, E. L.; Trim, S. C.; Little, D. E.; Spier, C. E.; Smith, M. N.; Peng, R.-C.; Linn, W. S.;
Hackney, J. D.; Gross, K. B.; D'Arcy, J. B.; Gibbons, D.; Higgins, I. T. T. (1990) Ozone
exposure and lung function in children attending a southern California summer camp.
Presented at: 83rd annual meeting and exhibition of the Air & Waste Management
Association; June; Pittsburgh, PA. Pittsburgh, PA: Air & Waste Management Association;
paper no. 90-150.3.
88Higgins, I. T. T.; D'Arcy, J. B.; Gibbons, D. L; Avol, E. L.; Gross, K. B. (1990) Effect of
exposures to ambient ozone on ventilatory lung function in children. Am. Rev. Respir. Dis.
141: 1136-1146.
89Raizenne, M. E.; Burnett, R. T.; Stern, B.; Franklin, C. A.; Spengler, J. D. (1989) Acute
lung function responses to ambient acid aerosol exposures in children. Environ. Health
Perspect. 79: 179-185.
90Raizenne, M.; Stern, B.; Burnett, R.; Spengler, J. (1987) Acute respiratory function and
transported air pollutants: observational studies. Presented at: 80th annual meeting of the Air
Pollution Control Association; June; New York, NY. Pittsburgh, PA: Air Pollution Control
Association; paper no. 87-32.6.
91 Spektor, D. M.; Lippmann, M. (1991) Health effects of ambient ozone on healthy children
at a summer camp. In: Berglund, R. L.; Lawson, D. R.; McKee, D. J., eds. Tropospheric
ozone and the environment: papers from an international conference; March 1990; Los
Angeles, CA. Pittsburgh, PA: Air & Waste Management Association; pp. 83-89. (A&WMA
transaction series no. TR-19).
92 Spektor, D. M.; Thurston, G. D.; Mao, J.; He, D.; Hayes, C.; Lippmann, M. (1991) Effects
of single- and multiday ozone exposures on respiratory function in active normal children.
Environ. Res. 55: 107-122.
93 Spektor, D. M.; Lippman, M.; Lioy, P. J.; Thurston, G. D.; Citak, K.; James, D. J.; Bock,
N.; Speizer, F. E.; Hayes, C. (1988a) Effects of ambient ozone on respiratory function in
active, normal children. Am. Rev. Respir. Dis. 137: 313-320.
94U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S.
EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.
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95 Hazucha, M. J.; Folinsbee, L. J.; Seal, E., Jr. (1992) Effects of steady-state and variable
ozone concentration profiles on pulmonary function. Am. Rev. Respir. Dis. 146: 1487-1493.
96 Horstman, D.H.; Ball, B.A.; Folinsbee, L.J.; Brown, J.; Gerrity, T. (1995) Comparison of
pulmonary responses of asthmatic and nonasthmatic subjects performing light exercise while
exposed to a low level of ozone. Toxicol. Ind. Health.
97 Horstman, D.H.; Folinsbee, L.J.; Ives, P.J.; Abdul-Salaam, S.; McDonnell, W.F. (1990)
Ozone concentration and pulmonary response relationships for 6.6-hour exposures with five
hours of moderate exercise to 0.08, 0.10, and 0.12 ppm. Am. Rev. Respir. Dis. 142: 1158-
1163.
98 Intergovernmental Panel on Climate Change (2007). Fourth Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge University Press, NY.
"NARSTO Synthesis Team (2000). An Assessment of Tropospheric Ozone Pollution: A
North American Perspective.
100 Attainment demonstration modeling guidelines
101 For example, see letters in the Air Docket for this rule from American Lung Association,
Clean Air Trust, California Environmental Protection Agency, New York State Department of
Environmental Conservation, Texas Commission on Environmental Quality (TCEQ, formerly
Texas Natural Resources Conservation Commission), State and Territorial Air Pollution
Program Administrators and the Association of Local Air Pollution Control Officials
(STAPPA/ALAPCO), Natural Resources Defense Council, Sierra Club, and Union of
Concerned Scientists.).
102 U.S. EPA. 1999. The Benefits and Costs of the Clean Air Act, 1990-2010. Prepared for
U.S. Congress by U.S. EPA, Office of Air and Radiation, Office of Policy Analysis and
Review, Washington, DC, November; EPA report no. EPA410-R-99-001.
103 Winner, W.E., and CJ. Atkinson. 1986. "Absorption of air pollution by plants, and
consequences for growth." Trends in Ecology and Evolution 1:15-18.
104U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.This document is available in
Docket EPA-HQ-OAR-2005-0036.
105 Tingey, D.T., and Taylor, G.E. 1982. "Variation in plant response to ozone: a conceptual
model of physiological events." In: Effects of Gaseous Air Pollution in Agriculture and
Horticulture (Unsworth, M.H., Omrod, D.P., eds.) London, UK: Butterworth Scientific,
pp.113-138.
106 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006.This document is available in
Docket EPA-HQ-OAR-2005-0036.
107U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
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108U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
109 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
110 Ollinger, S.V., J.D. Aber and P.B. Reich. 1997. "Simulating ozone effects on forest
productivity: interactions between leaf canopy and stand level processes." Ecological
Applications 7:1237-1251.
111 Winner, W.E., 1994. "Mechanistic analysis of plant responses to air pollution." Ecological
Applications, 4(4):651-661.
112U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
113 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
114 Fox, S., and R. A. Mickler, eds. 1996. Impact of Air Pollutants on Southern Pine Forests.
Springer-Verlag, NY, Ecol. Studies, Vol. 118, 513 pp.
115 De Steiguer, I, J. Pye, C. Love. 1990. "Air Pollution Damage to U.S. Forests." Journal of
Forestry, Vol 88 (8) pp. 17-22.
116 Pye, J.M. 1988. "Impact of ozone on the growth and yield of trees: A review." Journal of
Environmental Quality 17 pp.347-360.
117U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
118 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
119McBride, J.R., P.R. Miller, and R.D. Laven. 1985. "Effects of oxidant air pollutants on
forest succession in the mixed conifer forest type of southern California." In: Air Pollutants
Effects On Forest Ecosystems, Symposium Proceedings, St. P, 1985, p. 157-167.
120 Miller, P.R., O.C. Taylor, R.G. Wilhour. 1982. Oxidant air pollution effects on a western
coniferous forest ecosystem. Corvallis, OR: U.S. Environmental Protection Agency,
Environmental Research Laboratory (EPA600-D-82-276).
121 U.S. EPA. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final).
U.S. EPA, Washington, DC, EPA/600/R-05/004aF-cF, 2006. This document is available in
Docket EPA-HQ-OAR-2005-0036.
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122Kopp, R. J.; Vaughn, W. J.; Hazilla, M.; Carson, R. 1985. "Implications of environmental
policy for U.S. agriculture: the case of ambient ozone standards." J. Environ. Manage.
20:321-331.
123 Adams, R. M.; Hamilton, S. A.; McCarl, B. A. 1986. "The benefits of pollution control:
the case of ozone and U.S. agriculture." Am. J. Agric. Econ. 34: 3-19.
124 Adams, R. M.; Glyer, J. D.; Johnson, S. L.; McCarl, B. A. 1989. "A reassessment of the
economic effects of ozone on U.S. agriculture." JAPCA 39:960-968.
125 Abt Associates, Inc. 1995. Urban ornamental plants: sensitivity to ozone and potential
economic losses. U.S. EPA, Office of Air Quality Planning and Standards, Research Triangle
Park. Under contract to RADIAN Corporation, contract no. 68-D3-0033, WA no. 6. pp. 9-
10.
126 U.S. EPA, Technical Support Document for the Final Locomotive/Marine Rule: Air
Quality Modeling, Research Triangle Park, NC, EPA 454 R-07-XXX.
127U.S. EPA, Byun, D.W., and Ching, J.K.S., Eds, 1999. Science algorithms of EPAModels-
3 Community Multiscale Air Quality (CMAQ modeling system, EPA/600/R-99/030, Office
of Research and Development).
128 Byun, D.W., and Schere, K.L., 2006. Review of the Governing Equations, Computational
Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality
(CMAQ) Modeling System, J. Applied Mechanics Reviews, 59 (2), 51-77.
129Dennis, R.L., Byun, D.W., Novak, J.H., Galluppi, K.J., Coats, C.J., and Vouk, M.A., 1996.
The next generation of integrated air quality modeling: EPA's Models-3, Atmospheric
Environment, 30, 1925-1938.
130 Amar, P., Bornstein, R., Feldman, H., Jeffries, H., Steyn, D., Yamartino, R., Zhang, Y.,
2004. Final Report Summary: December 2003 Peer Review of the CMAQ Model, p. 7.
131 Grell, G., J. Dudhia, and D. Stauffer, 1994: A Description of the Fifth-Generation Penn
State/NCARMesoscale Model (MM5), NCAR/TN-398+STR., 138 pp, National Center for
Atmospheric Research, Boulder CO.
132U.S. Environmental Protection Agency, Byun, D.W., and Ching, J.K.S., Eds, 1999.
Science algorithms of EPA Models-3 Community Multiscale Air Quality (CMAQ modeling
system, EPA/600/R-99/030, Office of Research and Development). Please also see:
http ://www. cmascenter. org/
133 Yantosca, B., 2004. GEOS-CHEMv7-01-02 User's Guide, Atmospheric Chemistry
Modeling Group, Harvard University, Cambridge, MA, October 15, 2004.
134 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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135 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.
136 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".
137 Sisler 1996
138 U.S. EPA (2003) Integrated Risk Information System File of Acrolein. National Center
for Environmental Assessment, Office of Research and Development, Washington, D.C.
2003. This material is available electronically at http://www.epa.gov/iris/subst/0364.htm.
139 U.S. EPA (2006) National-Scale Air Toxics Assessment for 1999. This material is
available electronically at http://www.epa.gov/ttn/atw/natal999/risksum.html.
140 U.S. EPA (2006) National-Scale Air Toxics Assessment for 1999.
http://www.epa.gov/ttn/atw/natal999.
141 U.S. EPA (2002) Health Assessment Document for Diesel Engine Exhaust. EPA/600/8-
90/057F Office of Research and Development, Washington DC. Ppl-1 1-2. This document is
available electronically at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=29060.
142 U.S. EPA (2002) Health Assessment Document for Diesel Engine Exhaust. EPA/600/8-
90/057F Office of Research and Development, Washington DC. This document is available
electronically at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=29060.
143 U.S. EPA. (1999). Guidelines for Carcinogen Risk Assessment. Review Draft. NCEA-F-
0644, July. Risk Assessment Forum, Washington, DC.
http://www.epa.gov/ncea/raf/cancer.htm.
144
U.S. EPA. (1986) .Guidelines for carcinogen risk assessment. Federal Register
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145 National Institute for Occupational Safety and Health (NIOSH). (1988). Carcinogenic
effects of exposure to diesel exhaust. NIOSH Current Intelligence Bulletin 50. DHHS
(NIOSH) Publication No. 88-116. Atlanta, GA: Centers for Disease Control.
146 International Agency for Research on Cancer - IARC. (1997). Monographs on the
evaluation of carcinogenic risks to humans. Vol. 68. Silica, some silicates, coal dust and
para-aramid fibrils. Lyon, France: IARC, pp. 362-375.
147National Institute for Occupational Safety and Health (NIOSH). (1988). Carcinogenic
effects of exposure to diesel exhaust.. NIOSH Current Intelligence Bulletin 50. DHHS
(NIOSH) Publication No. 88-116. Atlanta, GA: Centers for Disease Control.
148 World Health Organization International Program on Chemical Safety (1996).
Environmental Health Criteria 171. Diesel fuel and exhaust emissions. Geneva: World Health
Organization, pp. 172-176.
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149 California Environmental Protection Agency. (Cal EPA, OEHHA) (1998). Health risk
assessment for diesel exhaust. Public and Scientific Review Draft.
150 National Toxicology Program (NTP). (2000). 9th report on carcinogens. Public Health
Service, U.S. Department of Health and Human Services, Research Triangle Park, NC.
Available from: http://ntp-server.niehs.nih.gov.
151 Health Effects Institute (HEI). (1995). Diesel exhaust: a critical analysis of emissions,
exposure, and health effects. Cambridge, MA.
152 Health Effects Institute (HEI) (1999). Diesel emissions and lung cancer: epidemiology
and quantitative risk assessment. A special report of the Institute's Diesel Epidemiology
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153 Health Effects Institute (HEI). (2002). Research directions to improve estimates of human
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164 Saverin, R. (1999). German potash miners: cancer mortality. Health Effects Institute
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165
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179 Attfield, MD. (1978) The effect of exposure to silica and diesel exhaust in underground
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180 Wade, JF, III; Newman, LS. (1993) Diesel asthma: reactive airways disease following
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181 Kilburn (2000) See HAD Chapter 5-7.
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184 R. Delfino
185 U.S. EPA (2006), National-Scale Air Toxics Assessment for 1999. This material is
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186 Diesel HAD Page 2-110, 8-12; Woskie, SR; Smith, TJ; Hammond, SK: et al. (1988a)
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187 Woskie, SR; Smith, TJ; Hammond, SK: et al. (1988a) Estimation of the DE exposures of
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188 Mobile Source Air Toxics Rule (Control of Hazardous Air Pollutants from Mobile
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and Resulting Health and Welfare Effects of Air Pollution from Mobile Sources." This
document is available electronically at: http://www.epa.gov/otaq/regs/toxics/420r07002.pdf
189 Sate of California Air Resources Board. Rail Yard Health Risk Assessments and
Mitigation Measures. This material is available electronically at:
http://www.arb.ca.gov/railyard/hra/hra.htm.
190 State of California Air Resources Board. Diesel Paniculate Matter Exposure Assessment
Study for the Ports of Los Angeles and Long Beach, April 2006. This document is available
electronically at: http://www.arb.ca.gov/regact/marine2005/portstudy0406.pdf
191 Hand, R.; Pingkuan, D.; Servin, A.; Hunsaker, L.; Suer, C. (2004) Roseville rail yard
study. California Air Resources Board. This document is available electronically at:
http://www.arb. ca. gov/diesel/documents/rrstudy .htm
192 Sate of California Air Resources Board. Rail Yard Health Risk Assessments and
Mitigation Measures. This material is available electronically at:
http://www.arb.ca.gov/railyard/hra/hra.htm.
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193 Di, P.; Servin, A.; Rosenkranz, K.; Schwehr, B.; Tran, H. (2006) Diesel particulate matter
exposure assessment study for the Ports of Los Angeles and Long Beach. California Air
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http://www.arb.ca.gov/msprog/offroad/marinevess/marinevess.htm.
194 ICF International. September 28, 2007. Estimation of diesel particulate matter
concentration isopleths for marine harbor areas and rail yards. Memorandum to EPA under
Work Assignment Number 0-3, Contract Number EP-C-06-094. This memo is available in
Docket EPA-HQ-OAR-2003-0190.
195 ICF International. September 28, 2007. Estimation of diesel particulate matter population
exposure near selected harbor areas and rail yards. Memorandum to EPA under Work
Assignment Number 0-3, Contract Number EP-C-06-094. This memo is available in Docket
EPA-HQ-O AR-2003 -0190.
196 http://www.epa.gov/ttn/atw/natal999/tables.html
197U.S. EPA. 2000. Integrated Risk Information System File for Benzene. This material is
available electronically at: http://www.epa.gov/iris/subst/0276.htm.
198 International Agency for Research on Cancer, IARC monographs on the evaluation of
carcinogenic risk of chemicals to humans, Volume 29, Some industrial chemicals and
dyestuffs, International Agency for Research on Cancer, World Health Organization, Lyon,
France, p. 345-389, 1982.
199Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. (1992) Synergistic action of
the benzene metabolite hydroquinone on myelopoietic stimulating activity of
granulocyte/macrophage colony-stimulating factor in vitro, Proc. Natl. Acad. Sci. 89:3691-
3695.
200Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health
Perspect. 82: 193-197.
201 Goldstein, B.D. (1988). Benzene toxi city. Occupational medicine. State of the Art
Reviews. 3: 541-554.
202Rothman, N., G.L. Li, M. Dosemeci, W.E. Bechtold, G.E. Marti, Y.Z. Wang, M. Linet,
L.Q. Xi, W. Lu, M.T. Smith, N. Titenko-Holland, L.P. Zhang, W. Blot, S.N. Yin, and R.B.
Hayes (1996) Hematotoxi city among Chinese workers heavily exposed to benzene. Am. J.
Ind. Med. 29: 236-246.
203 U.S. EPA 2002 Toxicological Review of Benzene (Noncancer Effects). Environmental
Protection Agency, Integrated Risk Information System (IRIS), Research and Development,
National Center for Environmental Assessment, Washington DC. This material is available
electronically at http://www.epa.gov/iris/subst/0276.htm.
204Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.; Melikian, A.; Eastmond, D.;
Rappaport, S.; Li, H.; Rupa, D.; Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.;
Winnik, M.; Kwok, E.; Li, Y.; Mu, R.; Xu, B.; Zhang, X.; Li, K. (2003). HEI Report 115,
Validation & Evaluation of Biomarkers in Workers Exposed to Benzene in China.
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205 Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et al. (2002). Hematological changes
among Chinese workers with a broad range of benzene exposures. Am. J. Industr. Med. 42:
275-285.
206 Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al. (2004). Hematotoxically in Workers
Exposed to Low Levels of Benzene. Science 306: 1774-1776.
207 Turtletaub, K.W. and Mani, C. (2003). Benzene metabolism in rodents at doses relevant to
human exposure from Urban Air. Research Reports Health Effect Inst. Report No. 113.
208U.S. EPA. 2002. Health Assessment of 1,3-Butadiene. Office of Research and
Development, National Center for Environmental Assessment, Washington Office,
Washington, DC. Report No. EPA600-P-98-001F. This document is available electronically
at http://www.epa.gov/iris/supdocs/buta-sup.pdf.
209U.S. EPA. 2002 "Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0)"
Environmental Protection Agency, Integrated Risk Information System (IRIS), Research and
Development, National Center for Environmental Assessment, Washington, DC
http://www.epa.gov/iris/subst/0139.htm.
210Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996) Subchronic toxicity of 4-
vinylcyclohexene in rats and mice by inhalation. Fundam. Appl. Toxicol. 32:1-10.
211 U.S. EPA. 1987. Assessment of Health Risks to Garment Workers and Certain Home
Residents from Exposure to Formaldehyde, Office of Pesticides and Toxic Substances, April
1987.
212Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality
from lymphohematopoetic malignancies among workers in formaldehyde industries. Journal
of the National Cancer Institute 95: 1615-1623.
213 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality
from solid cancers among workers in formaldehyde industries. American Journal of
Epidemiology 159: 1117-1130.
214
Pinkerton, L. E. 2004. Mortality among a cohort of garment workers exposed to
formaldehyde: an update. Occup. Environ. Med. 61: 193-200.
215
Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of
British chemical workers exposed to formaldehyde. J National Cancer Inst. 95:1608-1615.
216 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller.
2003. Biologically motivated computational modeling of formaldehyde carcinogenicity in the
F344 rat. Tox Sci 75: 432-447.
217 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller.
2004. Human respiratory tract cancer risks of inhaled formaldehyde: Dose-response
predictions derived from biologically-motivated computational modeling of a combined
rodent and human dataset. Tox Sci 82: 279-296.
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218 Chemical Industry Institute of Toxicology (CUT). 1999. Formaldehyde: Hazard
characterization and dose-response assessment for carcinogenicity by the route of inhalation.
CUT, September 28, 1999. Research Triangle Park, NC.
219 International Agency for Research on Cancer (2006) Formaldehyde, 2-Butoxyethanol and
l-tert-Butoxypropan-2-ol. Monographs Volume 88. World Health Organization, Lyon,
France.
220U.S. EPA (1988). Integrated Risk Information System File of Acetaldehyde. Research and
Development, National Center for Environmental Assessment, Washington, DC. This
material is available electronically at http://www.epa.gov/iris/subst/0290.htm.
221 U.S. EPA (1988). Integrated Risk Information System File of Acetaldehyde. This
material is available electronically at http://www.epa.gov/iris/subst/0290.htm.
222 Myou, S.; Fujimura, M.; Nishi K.; Ohka, T.; and Matsuda, T. (1993) Aerosolized
acetaldehyde induces histamine-mediated bronchoconstriction in asthmatics. Am. Rev.
Respir.Dis.U8(4Pt 1): 940-943.
223 U.S. EPA. 2003. Integrated Risk Information System File of Acrolein. Research and
Development, National Center for Environmental Assessment, Washington, DC. This
material is available electronically at http://www.epa.gov/iris/subst/0364.htm.
224 Appleman, L.M., R.A. Woutersen, and VJ. Feron. (1982). Inhalation toxicity of
acetaldehyde in rats. I. Acute and subacute studies. Toxicology. 23: 293-297.
225 Integrated Risk Information System File of Acrolein. Research and Development, National
Center for Environmental Assessment, Washington, DC. This material is available at
http://www.epa.gov/iris/subst/0364.htm
226 Weber-Tschopp, A; Fischer, T; Gierer, R; et al. (1977) Experimentelle reizwirkungen von
Acrolein auf den Menschen. Int Arch Occup Environ Hlth 40(2): 117-130. In German
227 Sim, VM; Pattle, RE. (1957) Effect of possible smog irritants on human subjects. J Am
Med Assoc 165(15):1908-1913.
228 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immediate sensory nerve-mediated
respiratory responses to irritants in healthy and allergic airway-diseased mice. J Appl Physiol
94(4):1563-1571.
229 Sim VM, Pattle RE. Effect of possible smog irritants on human subjects JAMA165: 1980-
2010, 1957.
230 Perera, F.P.; Rauh, V.; Tsai, W-Y.; et al. (2002) Effect of transplacental exposure to
environmental pollutants on birth outcomes in a multiethnic population. Environ Health
Perspect. 111:201-205.
231 Perera, F.P.; Rauh, V.; Whyatt, R.M.; Tsai, W.Y.; Tang, D.; Diaz, D.; Hoepner, L.; Barr,
D.; Tu, Y.H.; Camann, D.; Kinney, P. (2006) Effect of prenatal exposure to airborne
poly cyclic aromatic hydrocarbons on neurodevelopment in the first 3 years of life among
inner-city children. Environ Health Perspect 114: 1287-1292.
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232 U. S. EPA. 2004. Toxicological Review of Naphthalene (Reassessment of the Inhalation
Cancer Risk), Environmental Protection Agency, Integrated Risk Information System,
Research and Development, National Center for Environmental Assessment, Washington,
DC. This material is available electronically at http://www.epa.gov/iris/subst/0436.htm.
233 Oak Ridge Institute for Science and Education. (2004). External Peer Review for the IRIS
Reassessment of the Inhalation Carcinogenicity of Naphthalene. August 2004.
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=84403
234 National Toxicology Program (NTP). (2004). 11th Report on Carcinogens. Public Health
Service, U.S. Department of Health and Human Services, Research Triangle Park, NC.
Available from: http://ntp-server.niehs.nih.gov.
235 International Agency for Research on Cancer (IARC). (2002). Monographs on the
Evaluation of the Carcinogenic Risk of Chemicals for Humans. Vol. 82. Lyon, France.
236 U. S. EPA. 1998. Toxicological Review of Naphthalene, Environmental Protection
Agency, Integrated Risk Information System, Research and Development, National Center for
Environmental Assessment, Washington, DC. This material is available electronically at
http://www.epa.gov/iris/subst/0436.htm
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This Page Intentionally Left Blank
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Emission Inventory
CHAPTER 3: Emission Inventory 3-2
3.1 Commercial Marine Diesel Engines 3-2
3.1.1 General Methodology 3-3
3.1.2 Baseline (Pre-Control) Inventory Development 3-7
3.1.3 Control Inventory Development 3-34
3.1.4 Projected Commercial Marine Emission Reductions of Final Rule 3-57
3.2 Recreational Marine Diesel Engines 3-61
3.2.1 General Methodology 3-61
3.2.2 Baseline (Pre-Control) Inventory Development 3-63
3.2.3 Control Inventory Development 3-68
3.2.4 Projected Recreational Marine Emission Reductions of Final Rule 3-71
3.3 Locomotives 3-73
3.3.1 General Methodology 3-73
3.3.2 Baseline (Pre-Control) Inventory Development 3-77
3.3.3 Control Inventory Development 3-88
3.3.4 Projected Locomotive Emission Reductions from the Final Rule ... 3-95
3.4 Projected Total Emission Reductions from the Final Rule 3-99
3.5 Contribution of Marine Diesel Engines and Locomotives to Baseline
National Emission Inventories 3-105
3.5.1 Categories and Sources of Data 3-105
3.5.2 PM2.s Contributions to Baseline 3-106
3.5.3 NOX Contributions to Baseline 3-106
3.5.4 VOC Contributions to Baseline 3-106
3.5.5 CO Contributions to Baseline 3-106
3.5.6 SOi Contributions to Baseline 3-107
3.6 Contribution of Marine Diesel Engines and Locomotives to Non-
Attainment Area Emission Inventories 3-112
3.7 Emission Inventories Used for Air Quality Modeling 3-115
3.7.1 Comparison of Air Quality and Final Rule Inventories 3-115
3.7.2 Locomotive Inventory Changes 3-116
3.7.3 Marine Diesel Inventory Changes 3-116
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Regulatory Impact Analysis
CHAPTER 3: Emission Inventory
This chapter presents our analysis of the emission impact of the final rule for the three
source categories affected: commercial marine diesel engines, recreational marine diesel
engines, and locomotives. The final control requirements include NOX, HC, and PMA
emission standards for Category 1 and Category 2 commercial marine diesel engines (both
above and below 37 kilowatts [kW]). New NOX, HC, and PM emission standards would also
apply to all recreational marine diesel engines and locomotives. There are no new standards
for CO. In addition, there is a remanufacturing program requirement for locomotives and for
selected Category 1 and Category 2 engines.
Section 3.1 describes the methodology and presents the resulting baseline and
controlled inventories for commercial marine diesel engines, including the projected emission
reductions from the final rule. Sections 3.2 and 3.3 present similar information for
recreational marine diesel engines and locomotives, respectively. The baseline inventories
represent current and future emissions with only the existing standards. The controlled
inventories incorporate the new standards in the final rule. Section 3.4 follows with the total
projected emission reductions from all three affected source categories. Section 3.5 and
section 3.6 then describe the contribution of these source categories to national and selected
local inventories, respectively. Section 3.7 concludes the chapter by describing the changes in
the inputs and resulting emission inventories between the baseline and control scenarios used
for the air quality modeling and the updated baseline and control scenarios in this final rule.
The inventory estimates reported in this chapter are for the 50-state geographic area.
Inventories are presented for the following pollutants: paniculate matter (PM2.5 and PMi0),
oxides of nitrogen (NOX), sulfur dioxide (862), volatile organic compounds (VOC), carbon
monoxide (CO), and mobile source air toxics. The specific air toxics are benzene,
formaldehyde, acetaldehyde, 1,3-butadiene, acrolein, napthalene, and 15 other compounds
grouped together as polycyclic organic matter (POM). The PM inventories include directly
emitted PM only, although secondary sulfates are taken into account in the air quality
modeling. Inventories are provided for calendar years 2002 through 2040.
3.1 Commercial Marine Diesel Engines
This section describes the methodology and presents the resulting baseline and
controlled inventories for commercial marine diesel engines, including the projected emission
reductions from the final rule. Separate inventories were developed for the following
commercial marine diesel engine categories: Category 1 commercial propulsion, Category 1
marine auxiliary, Category 2 commercial propulsion, less than (<) 37kW commercial
propulsion, and <37kW marine auxiliary. Category 1 and 2 only include engines greater than
or equal to (>) 37kW, so it was necessary to include separate categories for those engines less
than 37kW. Note that the auxiliary categories include engines used on either commercial or
recreational vessels; however, given the expected small number of recreational auxiliary
1 PM in this document refers to PMi0, which are particles less than 10 microns in diameter.
o o
3-2
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Emission Inventory
engines in comparison to commercial auxiliary engines, and our inability to separate the
auxiliary categories by end use, the auxiliary categories have been included in the broader
commercial marine category. Category 2 marine auxiliary engines are not included here,
since they are used on Category 3 ocean-going vessels that are primarily foreign-flagged and
not subject to U.S. regulations. Emissions from Category 2 auxiliary engines are therefore
part of the Category 3 inventories.
3.1.1 General Methodology
For the Category 1 and Category 2 commercial marine categories, inventories are
estimated using spreadsheet models. Since the less than 37kW commercial marine engines
are subject to existing EPA nonroad diesel regulations, emissions were estimated for this
category using a special version of the NONROAD2005 model, with Source Classification
Codes (SCCs) and associated inputs added for both the commercial and auxiliary engines.
The general methodology for calculating commercial marine diesel engine inventories
for HC, CO, NOX, and PM is first described. This is followed by the methodologies used to
calculate fuel consumption, 862, VOC, PM2.5, and air toxic inventories.
Commercial marine diesel engine inventories for HC, CO, NOX, and PM are estimated
using the equation:
Equation 3-1 / = (#) x (?) x (z) x (A) x (Ep)
where each term is defined as follows:
I = the emission inventory (gram/year)
N = engine population (units)
P = average rated power (kW)
L = load factor (average fraction of rated power used during operation; unitless)
A = engine activity (operating hours/year)
EF = emission factor (gram/kW-hr)
Emissions are then converted and reported as short tons/year.
The average rated power, load factor, and activity inputs remain constant across all
simulation years. However, populations and emission factors vary by year and age.
Populations for a given base calendar year are first calculated, along with the corresponding
age distribution, and then projected from that base year into the future. For most of the
commercial marine diesel categories, the base year is 2002. The pollutant emission factors
vary by age to account for the current and final regulations, as well as emissions deterioration.
PM emission factors also have an additional adjustment to account for the in-use fuel sulfur
level, which is described in more detail below.
Three variables are used to project emissions over time: the annual population growth
rate, the engine median life/scrappage, and the relative deterioration rate. Collectively, these
variables represent population growth, changes in the population age distribution, and
emission deterioration.
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Regulatory Impact Analysis
Annual Population Growth Rate (percent/year). The population growth rate
represents the percentage increase in the total calendar year engine population from year (n)
toyear(n+l). It is a compound growth rate. These growth rates vary by category. The
compound growth rates are used for Category 1 and 2 engines. Since the NONROAD model
uses linear growth inputs, the compound growth rates are converted to a form consistent with
the NONROAD model for the less than 37kW commercial marine engines.
Engine Median Life (years) and Scrappage. The engine median life defines the
length of time engines remain in service. Engines persist in the population over two median
lives; during the first median life, 50 percent of the engines are scrapped, and over the second,
the remaining 50 percent of the engines are scrapped. Engine median lives also vary by
category. The age distribution is defined by the median life and the scrappage algorithm. For
commercial marine diesel engines, the scrappage algorithm in the NONROAD model was
used for all categories.1
Relative Deterioration Rate (percent increase in emission factor/percent median life
expended). A deterioration factor can be applied to the emission factor to account for in-use
deterioration. The deterioration factor varies by age and is calculated as:
Equation 3-2 DF = 1 + A x
ML
where each term is defined as follows:
DF = the deterioration factor for a given pollutant at a given age
A = the relative deterioration rate for a given pollutant (percent increase in emission
factor/percent useful life expended)
age = the age of a specific model year group of engines in the simulation year (years)
ML = the median life of the given model year cohort (years)
A given model year cohort is represented as a fraction of the entire population. The
deterioration factor adjusts the emission factor for engines in a given model year cohort in
relation to the proportion of median life expended. Deterioration is linear over one median
life. Following the first median life, the deteriorated emission factor is held constant over the
remaining life for engines in the cohort. This is consistent with the diesel deterioration
applied in the NONROAD model.2
Sulfur Adjustment for PM Emissions. For Tier 2 and prior engines, a sulfate
adjustment is added to the PM emissions to account for differences in fuel sulfur content
between the certification fuel and the episodic (calendar year) fuel, using the following
equation from the NONROAD model:
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Emission Inventory
Equation 3-3 SPM d. = (PC] x (?. l) x (0.0224?) x x (soxdsl - soxbas] x
PMadj \ ! \ ! \ ) ^ 32 J V /
where each term is defined as follows:
SPM adj = PM sulfate adjustment (tons)
FC = fuel consumption (gallons)
7.1 = fuel density (Ib/gal)
0.02247 = fraction of fuel sulfur converted to sulfate
224/32 = grams PM sulfate/grams PM sulfur
soxdsl = episodic fuel sulfur weight fraction (varies by calendar year)
soxbas = certification fuel sulfur weight fraction
2000 = conversion from Ib to ton
The certification fuel sulfur term is the fuel sulfur level associated with a base
emission factor in the model. If the episodic fuel sulfur level is less than the certification fuel
sulfur level, the PM adjustment is negative and PM emissions will decrease.
For engines prior to Tier 2 the base fuel sulfur (soxbas) is assumed to be 3300 ppm.
For Tier 2 engines less than or equal to 50 hp (37 kW) it is set at 2000 ppm, as described in
the Clean Air Nonroad Diesel Rule3, since these smaller engines are subject to the same
standards as land-based diesel engines. For Tier 2 engines greater than 50 hp (37 kW) it is set
at 350 ppm, based on the most recent certification data for these engines. For Tier 3 and later
engines, no sulfur adjustment is applied. These engines will be certified to a fuel sulfur level
at or lower than the episodic fuel sulfur levels expected when these engines are introduced.
The fraction of fuel sulfur converted to sulfate is based on an analysis of nonroad
engine data conducted at various fuel sulfur levels. The derivation is described in the
NONROAD documentation.4
Estimation of fuel consumption. Annual fuel consumption is estimated using the
following equation:
^ (BSFC xNxPxLxA)
Equation 3-4 FC = -, 7 -
(7.1x454)
where each term is defined as follows:
FC = fuel consumption (gallons)
BSFC = brake specific fuel consumption (g/kW-hr)
N = engine population (units)
P = average rated power (kW)
L = load factor (average fraction of rated power used during operation; unitless)
A = engine activity (operating hours/year)
7.1 = fuel density (Ib/gal)
454 = conversion from Ib to g
Estimation ofSOi emissions. Annual SO2 inventories are estimated using the
following equation:
3-5
-------
Regulatory Impact Analysis
Equation 3-5 SO7 = (FC} x (?. l) x (l - 0.0224?) x I x (soxdsl)
2 V ' V ' V ' V '
2000
where each term is defined as follows:
SC>2 = sulfur dioxide inventory (tons)
FC = fuel consumption (gallons)
7.1 = fuel density (Ib/gal)
(1-0.02247) = fraction of fuel sulfur converted to SO2
64/32 = grams SCVgrams sulfur
soxdsl = episodic fuel sulfur weight fraction (varies by calendar year)
2000 = conversion from Ib to ton
The calendar year fuel sulfur levels (soxdsl) were taken from the Clean Air Nonroad
Diesel Rule and are reproduced in Table 3-1 below.5
Table 3-1 Modeled 50-State In-Use Diesel Fuel Sulfur Content for Marine Engines
Calendar
Year(s)
Through 2000
2001
2002-2005
2006
2007
2008-2009
2010
2011
2012
2013
2014
2015-2017
2018-2040
Modeled In-Use Fuel
Sulfur Content, ppm
2640
2635
2637
2588
1332
435
319
236
124
44
52
56
55
Estimation of VOC andPM25 emissions. To estimate VOC emissions, an adjustment
factor of 1.053 is applied to the HC output. Similarly, to estimate PM2.5 emissions, an
adjustment factor of 0.97 is applied to the PMi0 output. These adjustment factors are
consistent with those used in the NONROAD model6'7 and the Clean Air Nonroad Diesel
Rule.8
Estimation of air toxic emissions. The air toxic baseline emission inventories for this
rule are based on information developed for EPA's Mobile Source Air Toxics (MSAT) final
rulemaking.9 That rule calculated air toxic emission inventories for all nonroad engines. The
gaseous air toxics are correlated to VOC emissions, while POM is correlated to PMi0
emissions. To calculate the air toxics emission inventories and reductions for this rule, the
percent reductions in VOC and PMi0 emissions will be applied to the baseline gaseous and
POM air toxic inventories, respectively.
3-6
-------
Emission Inventory
3.1.2 Baseline (Pre-Control) Inventory Development
This section describes the inputs and provides the resulting baseline inventories for
commercial marine engines.
3.1.2.1 Category 1 Propulsion
The inventory inputs of base year population, average power, load factor, and activity
for Category 1 commercial propulsion engines are given in Table 3-2 and Table 3-3. These
inventory inputs are used to develop both baseline and control inventories. As a result, there
are displacement, power density, and kilowatt subcategories, which are required to model
both the current and final standards in this rule.
The current emission standards vary only by displacement (disp) category, which is
expressed as liters per cylinder (L/cyl). There are four displacement categories for Category 1
engines: 1) less than 0.9 L/cyl (and power greater than or equal to 37kW), 2) greater than or
equal to 0.9 L/cyl and less than 1.2 L/cyl, 3) greater than or equal to 1.2 L/cyl and less than
2.5 L/cyl, and 4) greater than or equal to 2.5 L/cyl and less than 5 L/cyl. For simplification,
these will be referred to as 1) disp <0.9, 2) 0.9< disp <1.2, 3) 1.2< disp <2.5, and 4) 2.5< disp
In order to model the final Tier 3 standards, the 2.5< disp <5 category is further
broken out into 2.5< disp <3.5 and 3.5< disp <5 categories. The Tier 3 standards also have
cut points at 75kW and 3700kW, so it was necessary to break out the disp<0.9 category into
3775kW categories. Since there are no Category 1 engines greater than
3700kW, this cut point was not necessary to include. Finally, there are different Tier 3
standards for standard power density and high power density engines. Standard power
density engines are less than 35 kW per liter (kW/L), and the high power density engines are
greater than or equal to 35 kW/L. The inputs for the standard power density engines are given
in Table 3-2 and the inputs for the high power density engines in Table 3-3.
The final Tier 4 standards that apply to Category 1 engines vary by the following kW
categories: <600kW, 6003700kW. As a result, these power categories were also added, with the exception of the
>2000kW categories, since there are no Category 1 engines in this power range.
The base year populations by displacement category are generated using historical
sales estimates in conjunction with the scrappage algorithm described above. Other inventory
inputs that affect scrappage are load factor, activity, and median life. The historical sales
estimates for calendar years 1973-2002 were obtained from Power Systems Research (PSR).
These populations by displacement category were further broken out into power density and
kilowatt categories using the 2002 population and engine data from PSR.
The average power estimates were population-weighted, using the 2002 engine and
population data from PSR. The load factor and activity estimates were 0.45 and 943 hours
per year, respectively for engines <560 kW (750 hp). These are the estimates for commercial
marine propulsion engines provided by PSR. For engines >560 kW, the load factor and
3-7
-------
Regulatory Impact Analysis
activity estimates used were 0.79 and 4,503 hours per year. These latter estimates were taken
from the 1999 Marine Diesel FRM.10 Higher load factors and activities were assigned to
these larger engines based on information provided by the manufacturers for the previous
rule, and supported by more recent discussions with the American Waterways Operators
about how these larger engines typically operate.u This power break point is not related to
the kW categories in the final standards.
Load factors for each subcategory were developed by first identifying the engines in
the PSR population dataset corresponding to each subcategory. Load factors for each engine
in a subcategory were assigned based on the criteria above. An average load factor for each
subcategory was then obtained by weighting the individual engine load factors by population
and power. A similar approach was followed to obtain activity estimates for each
subcategory, with the exception that the weightings were population, power, and load factor.
The average power, load factors and activities needed to be estimated using these weightings
to ensure that the total inventory from this source category is correctly calculated. Note that
the load factor and hours of use only varied for Cl engines in the <600 kW and
1.2<=disp<2.5 standard power density category.
The median life for all Cl propulsion engines used is 13 years, which is the estimate
provided by PSR. The annual population growth rate is 1.009, which is the estimate from the
Energy and Information Administration (EIA) for domestic shipping.12
-------
Emission Inventory
Table 3-2 Inventory Inputs for Cl Propulsion Standard Power Density Engines
DISPLACEMENT CATEGORY
DISP0.9 AND 3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
<35 W/L
<=600KW
2002
POPULATION
1,665
1,102
19,255
23,561
5,898
205
51,687
AVG
KW
43
154
128
294
397
404
LOAD
FACTOR
0.45
0.45
0.45
0.51
0.45
0.45
ACTIVITY,
HOURS
943
943
943
1,905
943
943
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
<35 KW/L
10001400KWa
2002
POPULATION
0
0
0
0
0
1,264
1,264
AVG
KW
1,492
LOAD
FACTOR
0.79
ACTIVITY,
HOURS
4,503
TOTAL
POPULATION
0
0
0
1,013
186
1,476
2,675
Grand Total
56,139
53,098
3,041
No populations >2000 kW
5-9
-------
Regulatory Impact Analysis
Table 3-3 Inventory Inputs for Cl Propulsion High Power Density Engines
DISPLACEMENT CATEGORY
DISP0.9 AND 3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
>35 KW/L
<=600KW
2002
POPULATION
0
3,151
21
1,338
0
0
4,510
AVG
KW
165
313
341
LOAD
FACTOR
0.45
0.45
0.45
ACTIVITY,
HOURS
943
943
943
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
>35 KW/L
10001400KWa
2002
POPULATION
0
0
0
0
0
361
361
AVG
KW
1,765
LOAD
FACTOR
0.79
ACTIVITY,
HOURS
4,503
TOTAL
POPULATION
0
0
0
0
0
575
575
Grand Total
5,187
4,724
463
No populations >2000 kW
3-10
-------
Emission Inventory
The baseline emission factors are given in Table 3-4 and Table 3-5. The emission
factors are provided for three technology types: Base, Tier 1, and Tier 2. The base
technology type includes all pre-control engines. Tier 1 refers to the first round of existing
standards for NOX only that began in 2000. Tier 2 refers to the second round of existing
standards for HC+NOX and PM that began in 2004 to 2007, depending on the displacement
category.
Table 3-4 Baseline PM10 and NOX Emission Factors for Cl Propulsion Engines
DISPLACEMENT
CATEGORY
DISPO.9
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
PMio G/KW-HR
BASE
0.54
0.47
0.34
0.30
0.30
TIER1
0.54
0.47
0.34
0.30
0.30
TIER 2
0.23
0.12
0.13
0.13
0.13
NOX G/KW-HR
BASE
10
10
10
10
11
TIER1
9.8
9.8
9.8
9.1
9.2
TIER 2
5.7
6.1
6.0
6.0
6.0
Deterioration is applied to the PM emission factors (EFs); see text for details. The NOX EFs are not subject to
deterioration.
Table 3-5 Baseline HC and CO Emission Factors for Cl Propulsion Engines
DISPLACEMENT
CATEGORY
DISPO.9
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
HC G/KW-HR
BASE
0.41
0.32
0.27
0.27
0.27
TIER1
0.41
0.32
0.27
0.27
0.27
TIER 2
0.41
0.32
0.19
0.19
0.19
CO G/KW-HR
BASE
1.6
1.6
1.6
1.6
1.8
TIER1
1.6
1.6
1.6
1.6
1.8
TIER 2
1.6
0.9
1.1
1.1
1.1
The HC and CO emission factors (EFs) are not subject to deterioration.
The base emission factors were taken from the 1999 Marine Diesel rulemaking, and
are based on emission data for uncontrolled engines.13 For Tier 1, the NOX emission factors
were estimated using 2006 certification data. The certification data for engines using the E3
cycle8 were sales-weighted to obtain Tier 1 NOX emission factors for each displacement
category. Since the Tier 1 standards only affect NOX, the Tier 1 emission factors for the other
pollutants are equal to the base emission factors. For Tier 2, the same 2006 certification data
were used to estimate PM, NOX, and HC emission factors.
' The E3 duty cycle is designated for propulsion marine diesel engines.
5-11
-------
Regulatory Impact Analysis
For Cl engines, PM is the only pollutant for which deterioration factors are applied.
The relative deterioration rate (A) is 0.473, which is used for both pre-control and all
regulatory tiers. As a result, the maximum PM deterioration factor is 1.473. This is
consistent with the diesel deterioration assumed in the NONROAD model.14 Not enough
information is available at this time to develop deterioration factors for the other pollutants.
The certification fuel sulfur levels, which are used to estimate the PM sulfate
adjustments, are 3300ppm for the Base (pre-control) technology type, and 350ppm for Tier 1
and Tier 2. The Base level was taken from the NONROAD model.2 The Tier 1 and Tier 2
levels were estimated from reviewing the marine certification data and fuel requirements.
For calculating fuel consumption, estimates of brake specific fuel consumption
(BSFC) are also required. For this analysis, a value of 213 g/kW-hr was used. This value is
consistent with published estimates of BSFC and those for heavy-duty diesel engines.15
The resulting baseline 50-state emission inventories for Category 1 propulsion engines
are given in Table 3-6.
5-12
-------
Emission Inventory
Table 3-6 Baseline (50-State) Emissions for Cl Propulsion Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
13,328
13,690
13,807
13,873
13,872
12,230
10,961
10,710
10,304
9,916
9,471
9,003
8,587
8,155
7,718
7,346
7,058
6,805
6,632
6,538
6,470
6,422
6,388
6,368
6,359
6,363
6,381
6,410
6,451
6,499
6,552
6,611
6,671
6,731
6,791
6,852
6,914
6,976
7,039
PM2.5
12,928
13,279
13,393
13,457
13,456
11,863
10,632
10,388
9,995
9,619
9,187
8,733
8,330
7,910
7,487
7,126
6,846
6,601
6,433
6,342
6,276
6,229
6,197
6,177
6,168
6,173
6,190
6,218
6,258
6,304
6,356
6,413
6,471
6,529
6,588
6,647
6,707
6,767
6,828
NOX
335,561
336,369
332,798
328,810
324,900
316,663
308,524
300,509
292,651
284,979
277,551
270,764
264,634
258,879
253,538
249,327
246,339
243,964
242,764
242,677
242,990
243,640
244,563
245,736
247,141
248,720
250,474
252,384
254,450
256,608
258,851
261,181
263,532
265,903
268,297
270,711
273,148
275,606
278,086
voc
9,488
9,573
9,561
9,550
9,540
9,415
9,291
9,170
9,051
8,934
8,821
8,711
8,606
8,507
8,415
8,347
8,304
8,272
8,269
8,293
8,326
8,367
8,414
8,466
8,523
8,584
8,649
8,719
8,792
8,868
8,946
9,026
9,107
9,189
9,272
9,356
9,440
9,525
9,610
HC
9,010
9,091
9,080
9,069
9,060
8,941
8,824
8,708
8,595
8,484
8,377
8,273
8,173
8,079
7,992
7,927
7,886
7,855
7,852
7,876
7,907
7,946
7,990
8,040
8,094
8,152
8,214
8,280
8,349
8,421
8,495
8,572
8,649
8,727
8,805
8,885
8,965
9,045
9,127
CO
55,303
55,801
55,722
55,582
55,450
54,423
53,405
52,401
51,414
50,445
49,497
48,574
47,680
46,827
46,023
45,368
44,879
44,482
44,301
44,329
44,423
44,571
44,760
44,987
45,248
45,539
45,861
46,209
46,583
46,975
47,385
47,811
48,241
48,675
49,114
49,556
50,002
50,452
50,906
SO2
36,201
36,528
36,862
37,192
36,827
19,121
6,299
6,355
4,705
3,513
1,862
664
799
857
865
872
879
886
893
900
907
915
923
931
939
946
954
962
970
978
986
995
1,006
1,015
1,023
1,032
1,040
1,050
1,059
5-13
-------
Regulatory Impact Analysis
3.1.2.2 Category 1 Auxiliary
The methodology and data sources for Category 1 marine auxiliary engines are
essentially the same as those for Category 1 propulsion engines. For this source category,
however, the PSR data for marine auxiliary engines and the certification data with the D2
auxiliary cycle0 were used instead. Weighted load factor and activity values were calculated,
although the load factor and hours of use only varied in the <600 kW and 1.2<=disp<2.5
standard power density category. The inventory inputs of base year population, average
power, load factor, and activity for Cl auxiliary engines are given in Table 3-7 and Table 3-8.
The baseline emission factors are given in Table 3-9 and Table 3-10.
For auxiliary engines, the load factor and activity estimates are 0.56 and 724 hours per
year, respectively, for engines <560kW. These are the estimates for auxiliary marine engines
provided by PSR. For engines >560kW, the load factor and activity estimates used are 0.65
and 2,500 hours per year, taken from the 1999 FRM.10 The cut point of 560kW is that used
for propulsion engines and is not related to the kW categories in the final standards.
The median life for all Cl auxiliary engines is 17 years, which is the estimate provided
by PSR. Estimates for the annual growth rate, PM deterioration factor, certification fuel
sulfur levels, and BSFC are assumed to be the same as those for Cl propulsion engines.
The resulting baseline 50-state emission inventories for Category 1 auxiliary engines
are given in Table 3-11.
The D2 steady-state duty cycle is designated for constant-speed engines.
3-14
-------
Emission Inventory
Table 3-7 Inventory Inputs for Cl Auxiliary Standard Power Density Engines
DISPLACEMENT CATEGORY
DISP0.9 AND 3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
<35 KW/L
<=600KW
2002
POPULATION
9,786
1,251
11,933
14,119
785
347
38,221
AVG
KW
44
83
109
324
332
356
LOAD
FACTOR
0.56
0.56
0.56
0.57
0.56
0.56
ACTIVITY,
HOURS
724
724
724
925
724
724
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
<35 KW/L
10001400KW"
2002
POPULATION
0
0
0
0
0
96
96
AVG
KW
1,527
LOAD
FACTOR
0.65
ACTIVITY,
HOURS
2,500
TOTAL
POPULATION
0
0
0
0
14
364
378
Grand Total
38,503
1,090
39,593
' No populations >2000KW
3-15
-------
Regulatory Impact Analysis
Table 3-8 Inventory Inputs for Cl Auxiliary High Power Density Engines
DISPLACEMENT CATEGORY
DISP0.9 AND 3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
>35 KW/L
<=600KW
2002
POPULATION
215
218
0
0
0
0
433
AVG
KW
75
141
LOAD
FACTOR
0.56
0.56
ACTIVITY,
HOURS
724
724
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
TOTAL
>35 KW/L
10001400KWa
2002
POPULATION
0
0
0
39
0
0
39
AVG
KW
1,531
LOAD
FACTOR
0.65
ACTIVITY,
HOURS
2,500
TOTAL
POPULATION
0
0
11
39
0
0
50
Grand Total
444
39
483
' No populations >2000KW
3-16
-------
Emission Inventory
Table 3-9 Baseline PMi0 and NOX Emission Factors for Cl Auxiliary Engines
DISPLACEMENT
CATEGORY
DISPO.9
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
PMio G/KW-HR
BASE
0.84
0.53
0.34
0.32
0.30
TIER1
0.84
0.53
0.34
0.32
0.30
TIER 2
0.23
0.21
0.15
0.15
0.15
NOX G/KW-HR
BASE
11
10
10
10
11
TIER1
9.8
9.8
9.8
9.1
9.2
TIER 2
5.7
5.4
6.1
6.1
6.1
Deterioration is applied to the PM emission factors (EFs); see text for details. The NOX EFs are not subject to
deterioration.
Table 3-10 Baseline HC and CO Emission Factors for Cl Auxiliary Engines
DISPLACEMENT
CATEGORY
DISPO.9
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
HC G/KW-HR
BASE
0.41
0.32
0.27
0.27
0.27
TIER1
0.41
0.32
0.27
0.27
0.27
TIER 2
0.41
0.32
0.21
0.21
0.21
CO G/KW-HR
BASE
2.0
1.7
1.5
1.5
1.8
TIER1
2.0
1.7
1.5
1.5
1.8
TIER 2
1.6
0.8
0.9
0.9
0.9
The HC and CO emission factors (EFs) are not subject to deterioration.
17
-------
Regulatory Impact Analysis
Table 3-11 Baseline (50-State) Emissions for Cl Auxiliary Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
2,714
2,773
2,791
2,786
2,769
2,482
2,263
2,230
2,170
2,115
2,052
,993
,952
,907
,860
,806
,746
,685
,625
,576
,543
,520
,504
,495
,489
,486
,484
,484
,486
,489
,493
,499
,506
,514
,524
,535
,547
,561
,574
PM2.5
2,632
2,690
2,708
2,703
2,686
2,407
2,195
2,163
2,105
2,052
,990
,933
,893
,850
,805
,752
,693
,634
,576
,528
,497
,474
,459
,451
,445
,441
,440
,440
,441
,444
,448
,454
,461
,469
,478
,489
,501
,514
,527
NOX
60,641
60,959
60,482
59,774
59,073
58,048
57,030
56,020
55,022
54,038
53,069
52,118
51,185
50,277
49,399
48,589
47,849
47,160
46,531
46,079
45,840
45,706
45,683
45,756
45,875
46,035
46,228
46,452
46,703
46,980
47,283
47,611
47,962
48,332
48,721
49,126
49,553
49,991
50,436
voc
1,767
1,783
1,785
1,788
1,791
1,787
1,783
1,779
1,776
1,773
1,770
1,767
1,765
1,763
1,761
1,760
1,759
1,759
1,760
1,764
1,771
1,778
1,788
1,799
1,811
1,824
1,837
1,851
1,865
1,880
1,895
1,911
1,927
1,943
1,960
1,977
1,995
2,013
2,031
HC
,678
,693
,696
,698
,700
,697
,693
,690
,686
,684
,681
,678
,676
,674
,673
,672
,671
,671
,672
,675
,681
,689
,698
,709
,720
,732
,745
,758
,771
,785
,800
,815
,830
,845
,861
,878
,894
,911
,928
CO
9,624
9,710
9,668
9,585
9,503
9,331
9,160
8,989
8,820
8,654
8,489
8,327
8,167
8,010
7,857
7,708
7,563
7,426
7,298
7,198
7,134
7,088
7,066
7,067
7,077
7,094
7,117
7,145
7,178
7,215
7,257
7,303
7,353
7,407
7,464
7,524
7,588
7,654
7,721
SO2
6,553
6,613
6,673
6,733
6,667
3,461
1,140
1,150
852
636
337
120
145
155
157
158
159
160
162
163
164
166
167
169
170
171
173
174
176
177
179
180
182
184
185
187
188
190
192
18
-------
Emission Inventory
3.1.2.3 Category 2 Propulsion
The methodology used for C2 propulsion engines is the same as that used for Cl
propulsion engines, as described in section 3.1.1. For activity however, separate estimates
were made for underway and idling activity, using the following equations:
Equation 3-6 Underway kW-hr = (Likely kW) x (Total Engines) x (Likely Annual Transit Days) x (Likely
Load Factor) x (24 hours/day)
Equation 3-7 Idling kW-hr = (Likely kW) x (Total Engines) x (Likely Annual Idling Days) x (Minimum
Load Factor) x (24 hours/day)
The Category 2 activity inputs for U.S. flag vessels by vessel type are provided in
Table 3-12. These inputs were largely developed by Eastern Research Group, Inc. (ERG),
under contract to EPA, with the exception of ferry vessels.16 For ferries, a diesel fuel
consumption estimate of 35,120,000 gallons for fiscal year 2004 published by the American
Public Transportation Association was used, since a published value was deemed more
reliable.17 The diesel fuel gallons consumed by ferries were then converted to kW-hr using a
fuel density of 7.1 Ib/gallon and a brake specific fuel consumption estimate of 0.35 Ib/hp-hr.
As part of its comment submittal to EPA, the American Waterways Operators (AWO)
provided propulsion engine population data for towboats that can be directly compared with
the estimates in this rule.18 Table 3-13 below provides a comparison of the data submitted by
AWO to that developed by ERG for towboats. The AWO data represent current populations,
although the reference year was not provided. For this rule, population data for 2004 were
used.
19
-------
Regulatory Impact Analysis
Table 3-12 Category 2 U.S. Flag Engine Activity Inputs
Vessel Type
Deep Water Cargo
Tow Boats
Ferries
Commercial Fishing
Great Lake
Coast Guard
Offshore
Research
Total
Total C2
Engines
92
2,071
218
403
272
320
1,339
70
4,785
Utilization
Rate
100%
74%
85%
85%
85%
100%
97%
100%
Equivalent
C2
. a
Engines
92
1,533
185
342
232
320
1,303
70
4,076
Horsepower
Min
1,860
900
865
1,000
518
1,250
740
600
Likely
3,603
2,207
2,412
1,924
2,505
2,289
2,016
1,622
Max
7,200
7,420
4,400
4,313
3,600
3,650
7,502
3,750
Total
329,920
3,382,781
446,529
658,293
579,847
732,734
2,626,265
113,717
8,870,086
Annual Transit Days
Min
152
250
29
280
711
Likely
219
219
174
271
136
88
299
220
1,625
Max
243
292
157
317
1,009
Annual
Idling Days
Likely
0
0
0
81
0
18
66
88
253
Load Factor
Min
10%
10%
53%
27%
53%
10%
10%
10%
Likely
80%
85%
68%
70%
84%
80%
85%
85%
Max
90%
90%
80%
80%
84%
90%
87%
90%
Vessel Type
Deep Water Cargo
Tow Boats
Ferries
Commercial Fishing
Great Lake
Coast Guard
Offshore
Research
Total
Activity (HP-HR)
Underway
1,387,249,658
15,112,911,191
1,267,998,585
2,995,235,100
1,588,928,635
1,238,027,096
15,992,380,323
510,360,006
40,093,090,594
Idling
0
0
0
346,591,490
0
94,962,306
413,920,432
24,016,941
879,491,169
Total HP-HR
1,387,249,658
15,112,911,191
1,267,998,585
3,341,826,590
1,588,928,635
1,332,989,402
16,406,300,754
534,376,948
40,972,581,763
Chosen Activity
Total HP-HR
1,387,249,658
15,112,911,191
712,434,286
3,341,826,590
1,588,928,635
1,332,989,402
16,406,300,754
534,376,948
40,417,017,464
Reference
Year(s)
2004
2002-2004
2000-2004
2000-2004
2004
2004
2005
2004
Chosen
Reference
Year
2004
2004
2004
2004
2004
2004
2005
2004
Total U.S. Flag Activity Adjusted for
2002 Base Year
Total HP-HR
1,362,612,266
14,844,507,648
699,781,536
3,282,476,139
1,560,709,448
1,309,315,665
15,971,186,089
524,886,475
39,555,475,265
Total KW-HR
1,016,099,966
11,069,549,353
521,827,091
2,447,742,457
1,163,821,035
976,356,691
11,909,713,466
391,407,845
29,496,517,905
Equivalent C2 Engines = (Total C2 Engines) x (Utilization Rate).
Different activity used for ferries; see text.
20
-------
Emission Inventory
Table 3-13 Comparison of Towboat Propulsion Engine Populations
Vessel Type
Inland Towing
Coastal Towing
Total
Total Propulsion Engines
ERG
6,091
2,181
8,272
AWO
5,228
2,582
7,810
Category 2 Proi
ERG
1,356
715
2,071
julsion Engines
AWO
1,516
904
2,420
AWO estimates that 31 percent of the towboat propulsion engines are Category 2,
based on the assumption that inland towing vessels greater than 2,000 hp and coastal towing
vessels greater than 3,000 hp are generally equipped with C2 engines. For the ERG analysis,
a percentage of 25 percent was applied, using both vessel horsepower and hull displacement
as category indicators. Applying both percentages to the AWO engine total of 7,810 engines,
the range of Category 2 towboat propulsion engines is 1,952 to 2,420 engines. Since the ERG
estimate falls within this range, it was retained for the final rule.
Since the reference years for the data collection varied by vessel type, it was necessary
to adjust the activity estimates to the 2002 calendar year, which is the base year for this
analysis. This was done by backcasting the Category 2 growth rate. The underway and idling
kW-hr estimates for all vessel types were then consolidated into a single term for total kW-
hr/year. For U.S. flag vessels, the total activity estimate in 2002 is 29,496,517,905 kW-hr.
The foreign-flag inputs are given in Table 3-14. All foreign-flag activity is assumed to
come from off-shore vessels. These estimates were also generated by ERG. The total activity
estimate is then multiplied by 0.15 to account for the fraction of time these vessels are spent
in U.S. waters. The resulting foreign-flag activity in U.S. waters is estimated to be
750,291,634 kW-hr.
Table 3-14 Category 2 Foreign Flag Engine Activity Inputs
Vessel Type
Deep Water
Cargo Foreign
Total
Engines
508
Horsepower
Likely
2,576
Total
1,308,465
Annual
Transit
Days
267
Annual
Idling
Days
0
Load
Factor
80%
Total Activity
Total HP-HR
6,707,716,548
Total KW-HR
5,001,994,230
Time spent in U.S. waters:
Total activity in U.S. waters:
0.15
750,291,634 kW-hr
The total kW-hr values for U.S. flag and foreign flag vessels were then allocated to the
necessary displacement and horsepower categories, using the PSR engine data. The
allocation fractions are provided in Table 3-15. For U.S. vessels, inventories were then
developed by applying current and future emission factors, whereas only base (non-
controlled) emission factors are used for foreign flag vessels. The same growth rate is used
for each.
5-21
-------
Regulatory Impact Analysis
Table 3-15 Category 2 Activity Allocation Fractions by Displacement and Power
Displacement/kW Category
5.0<=disp<15 and <600kW
5.0<=disp<15 and 600<=kW<1000
5.0<=disp<15 and 1000<=kW<1400
5.0<=disp<15 and 1400<=kW<2000
5.0<=disp<15 and 2000<=kW<3700
5.0<=disp<15 and >=3700kW
15.0<=disp<20.0 and <600kW
15.0<=disp<20.0 and 600<=kW<1000
15.0<=disp<20.0 and 1000<=kW<1400
15.0<=disp<20.0 and 1400<=kW<2000
15.0<=disp<20.0 and 2000<=kW<3300
15.0<=disp<20.0 and 3300<=kW<3700
15.0<=disp<20.0 and >=3700kW
Fraction of
Total Activity
0.0066
0.0046
0.0191
0.0881
0.2021
0.2049
0.0000
0.0000
0.0000
0.0284
0.1229
0.0000
0.3234
The activity estimates in Table 3-12 were based on estimates provided by ERG prior
to release of the latest version of the report. The estimates in the latest version contain some
revised inputs for deep water cargo and research vessels. Incorporating these revisions would
change the total U.S. flag activity from 29,496,517,905 kW-hr to 25,665,967,253 kW-hr.
ERG also provides a total activity estimate of 34,869,677,700 kW-hr, using a Monte Carlo
analysis. Since the activity estimates in Table 3-12 fall between these two updated estimates,
the decision was made to retain the previous activity estimates used for the NPRM.
19
The median life for all C2 propulsion engines is 23 years. The emission factors used
for all C2 propulsion engines are largely those we used for the original commercial marine
rulemaking analysis.20 The one exception to this is for Tier 1 NOx, which was updated based
on an analysis of 2006 certification data. The C2 emission factors are shown in Table 3-16.
Estimates for the annual growth rate, PM deterioration factor, and certification fuel sulfur
levels are assumed to be the same as those for Cl propulsion engines.
Table 3-16 Baseline Emission Factors for C2 Engines (g/kW-hr)a
Tier
BASE
TIER1
TIER 2
PMio
0.32
0.32
0.32
NOX
13.36
10.55
8.33
HC
0.134
0.134
0.134
CO
2.48
2.48
2.00
Deterioration is applied to the PM emission factors (EFs); see text for details. The NOx, HC and CO EFs are
not subject to deterioration.
The resulting baseline 50-state emission inventories for Category 2 propulsion engines are
given in Table 3-17..
5-22
-------
Emission Inventory
Table 3-17 Baseline (50-State) Emissions for C2 Propulsion Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
12,850
13,112
13,376
13,641
13,907
14,174
14,436
14,706
14,975
15,245
15,515
15,727
14,475
13,635
13,883
13,986
14,127
14,228
14,365
14,613
14,850
15,059
15,243
15,423
15,599
15,772
15,943
16,114
16,283
16,451
16,618
16,786
16,952
17,119
17,286
17,453
17,620
17,787
17,954
PM2.5
12,464
12,719
12,975
13,232
13,490
13,748
14,003
14,264
14,525
14,787
15,050
15,255
14,041
13,226
13,466
13,566
13,703
13,801
13,934
14,175
14,405
14,607
14,786
14,960
15,131
15,299
15,465
15,630
15,794
15,957
16,120
16,282
16,444
16,605
16,767
16,929
17,091
17,253
17,416
NOX
432,306
431,973
431,683
431,417
431,195
427,380
423,601
419,857
416,169
412,537
408,943
405,428
401,970
398,593
395,295
392,101
388,988
386,000
383,155
380,458
377,990
376,313
375,430
374,784
374,343
374,086
374,039
374,219
375,126
376,727
378,567
380,573
382,749
385,076
387,519
390,097
392,794
395,609
398,527
voc
4,701
4,743
4,786
4,829
4,872
4,916
4,960
5,005
5,050
5,096
5,141
5,188
5,234
5,281
5,329
5,377
5,425
5,474
5,523
5,573
5,623
5,674
5,725
5,777
5,829
5,881
5,934
5,987
6,041
6,096
6,150
6,206
6,262
6,318
6,375
6,432
6,490
6,549
6,607
HC
4,464
4,504
4,545
4,586
4,627
4,669
4,711
4,753
4,796
4,839
4,883
4,927
4,971
5,016
5,061
5,106
5,152
5,199
5,245
5,293
5,340
5,388
5,437
5,486
5,535
5,585
5,635
5,686
5,737
5,789
5,841
5,893
5,946
6,000
6,054
6,108
6,163
6,219
6,275
CO
82,621
83,364
84,115
84,872
85,635
85,621
85,611
85,605
85,609
85,621
85,639
85,665
85,701
85,746
85,800
85,864
85,937
86,020
86,116
86,222
86,341
86,475
86,626
86,790
86,974
87,178
87,406
87,672
88,078
88,623
89,207
89,820
90,457
91,119
91,799
92,500
93,219
93,956
94,707
SO2
36,868
37,193
37,528
37,866
38,207
38,550
38,837
39,204
39,559
39,920
40,278
39,905
21,334
7,888
7,958
6,238
4,998
3,277
2,031
2,185
2,258
2,279
2,299
2,319
2,339
2,359
2,379
2,399
2,421
2,442
2,463
2,485
2,507
2,529
2,551
2,573
2,595
2,618
2,641
5-23
-------
Regulatory Impact Analysis
3.1.2.4 Under 37 kW Propulsion and Auxiliary
Category 1 commercial marine engines are defined as being greater than or equal to
(>) 37kW and less than (<) 5.0 liters/cylinder; however, there are commercial marine engines
<37kW. The majority of these small power engines are used as auxiliary engines, although
there are some propulsion engines that fall into this category. Commercial marine engines
<37kW are covered under this proposal; therefore, inventories have been estimated.
Emissions were estimated using a special version of the NONROAD2005 model, with
Source Classification Codes (SCCs) and associated inputs added for both the commercial and
auxiliary engines. An SCC of 2280002030 was assigned to the <37kW propulsion engines,
with an SCC of 2280002040 assigned to the <37kW auxiliary engines.
The inventory inputs of base year population, average power, load factor, activity, and
median life are given in Table 3-18 below. These inputs were generated using the same
methodology and data sources as the Cl propulsion and Cl auxiliary categories. Horsepower
(hp) is used as the unit for power in the NONROAD model, so the inputs for power and
emission factors are hp and g/hp-hr, respectively. The 2002 base year populations are
assigned to one or more of the following hp categories in NONROAD: 0-11, 11-16, 16-25,
25-40, and 40-50. The propulsion engines all fall within the 25-40hp category, whereas there
are auxiliary engines in each hp category. The average power values in the table below are
population-weighted estimates.
Table 3-18 Inventory Inputs for <37kW Commercial Marine Diesel Engines
INPUTS
2002
POPULATION
AVGHP
LOAD
FACTOR
ACTIVITY,
HOURS
MEDIAN
LIFE, YEARS
PROPULSION
1,232
34.8
0.45
943
13
AUXILIARY
67,708
24.9
0.56
724
17
The baseline emission factors are given in Table 3-19 and Table 3-20. These engines
are subject to EPA nonroad diesel regulations that have established two tiers of emission
standards.21 Tier 1 phased in from 1999-2000, depending on the horsepower category, with
Tier 2 phased in from 2004-2005. The "Base" entries in the tables refer to emissions from
pre-controlled engines. These emission factors are used for both propulsion and auxiliary
engines.
5-24
-------
Emission Inventory
Table 3-19 Baseline PM10 and NOX Emission Factors and Deterioration Factors for <37kW Commercial
Marine Diesel Engines
HP
RANGE
0-11
11-16
16-25
25-50
DF ("A")
PMio G/HP-HR
BASE
1.00
0.90
0.90
0.80
0.473
TIER1
0.45
0.27
0.27
0.34
0.473
TIER 2
0.38
0.19
0.19
0.23
0.473
NOX G/HP-HR
BASE
10.00
8.50
8.50
6.90
0.024
TTER1
5.23
4.44
4.44
4.73
0.024
TIER 2
4.39
3.63
3.63
3.71
0.009
Table 3-20 Baseline HC and CO Emission Factors and Deterioration Factors for <37kW Commercial
Marine Diesel Engines
HP
RANGE
0-11
11-16
16-25
25-50
DF ("A")
HC G/HP-HR
BASE
1.50
1.70
1.70
1.80
0.047
TIER1
0.76
0.44
0.44
0.28
0.036
TIER 2
0.68
0.21
0.21
0.54
0.034
CO G/HP-HR
BASE
5.00
5.00
5.00
5.00
0.185
TIER1
4.11
2.16
2.16
1.53
0.101
TIER 2
4.11
2.16
2.16
1.53
0.101
The emission factors for the base and Tier 1 technology types are consistent with those
used in the NONROAD model.22 Tier 2 emission factors were estimated using nonroad
engine certification data. The deterioration factors by pollutant and technology type are also
given in the tables above. The deterioration factors are those used for diesel engines in the
NONROAD model.
23
The certification fuel sulfur levels are 3300ppm for the base and Tier 1 technology
type and 350ppm for Tier 2. Brake specific fuel consumption (BSFC) values were taken from
the NONROAD model and are 0.408 Ib/hp-hr for all hp categories.24 The compound
population growth rate is 1.009, which is the growth rate used for all commercial diesel
engines. Since the NONROAD model uses linear growth inputs, the compound growth rates
are converted to a form consistent with the NONROAD model for this category.
The resulting baseline 50-state emission inventories for <37kW commercial marine
engines (propulsion and auxiliary combined) are given in Table 3-21.
5-25
-------
Regulatory Impact Analysis
Table 3-21 Baseline (50-State) Emissions for <37kW Commercial Marine Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
728
710
692
671
648
596
551
526
499
472
444
417
392
368
348
332
320
310
301
294
288
284
280
278
276
275
275
275
275
276
278
279
282
284
286
289
291
294
296
PM2.5
706
689
671
651
629
578
534
511
484
458
431
404
381
357
337
322
311
301
292
285
279
275
272
269
268
267
267
267
267
268
269
271
273
275
278
280
282
285
287
NOX
5,517
5,448
5,350
5,229
5,101
4,973
4,846
4,719
4,594
4,472
4,351
4,234
4,120
4,011
3,917
3,846
3,790
3,744
3,704
3,675
3,659
3,654
3,654
3,658
3,670
3,685
3,703
3,723
3,746
3,771
3,798
3,828
3,859
3,891
3,924
3,958
3,992
4,026
4,061
voc
1,273
1,222
1,179
1,128
1,075
1,022
969
916
864
813
763
715
668
624
588
564
546
531
519
507
497
491
485
481
479
478
478
478
479
481
484
488
492
496
500
504
509
513
517
HC
,209
,161
,120
,071
,021
970
920
870
821
772
725
679
634
592
559
535
518
504
493
482
472
466
461
457
455
454
454
454
455
457
460
463
467
471
475
479
483
487
491
CO
3,783
3,680
3,576
3,460
3,339
3,216
3,093
2,970
2,846
2,724
2,603
2,484
2,369
2,259
2,170
2,109
2,063
2,027
,997
,972
,952
,940
,932
,926
,926
,929
,934
,942
,952
,963
,977
,992
2,009
2,026
2,044
2,061
2,079
2,097
2,115
SO2
731
738
745
752
745
387
128
129
95
71
38
14
16
18
18
18
18
18
18
18
18
19
19
19
19
19
19
20
20
20
20
20
21
21
21
21
21
21
22
5-26
-------
Emission Inventory
3.1.2.5 Commercial Marine Diesel Baseline Inventory Summary
3.1.2.5.1 PMio, PM25, NOX, VOC, CO, and SO2 Emissions
Table 3-22 thru Table 3-27 present the resulting 50-state consolidated commercial
marine baseline inventories by pollutant and category, for calendar years 2002-2040.
3.1.2.5.2 Air Toxics Emissions
The baseline air toxics inventories for the consolidated commercial marine diesel
engines were taken from the Mobile Source Air Toxics Rule (MSAT)25 and are provided in
Table 3-28. Inventories are provided for calendar years 1999, 2010, 2015, 2020, and 2030.
The air toxics inventories were developed independently and prior to this final rule
development. The purpose of presenting these inventories is to show the incidental hazardous
air pollutant (HAP) reductions from this rule.
5-27
-------
Regulatory Impact Analysis
Table 3-22 Baseline (50-State) PM10 Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
13,328
13,690
13,807
13,873
13,872
12,230
10,961
10,710
10,304
9,916
9,471
9,003
8,587
8,155
7,718
7,346
7,058
6,805
6,632
6,538
6,470
6,422
6,388
6,368
6,359
6,363
6,381
6,410
6,451
6,499
6,552
6,611
6,671
6,731
6,791
6,852
6,914
6,976
7,039
Cl
AUXILIARY
2,714
2,773
2,791
2,786
2,769
2,482
2,263
2,230
2,170
2,115
2,052
,993
,952
,907
,860
,806
,746
,685
,625
,576
,543
,520
,504
,495
,489
,486
,484
,484
,486
,489
,493
,499
,506
,514
,524
,535
,547
,561
,574
Cl
TOTAL
16,041
16,463
16,598
16,659
16,641
14,712
13,224
12,940
12,474
12,031
11,522
10,996
10,539
10,062
9,579
9,152
8,804
8,490
8,257
8,114
8,013
7,942
7,893
7,864
7,849
7,849
7,865
7,895
7,937
7,988
8,045
8,110
8,177
8,245
8,315
8,387
8,461
8,537
8,613
C2
PROPULSION
12,850
13,112
13,376
13,641
13,907
14,174
14,436
14,706
14,975
15,245
15,515
15,727
14,475
13,635
13,883
13,986
14,127
14,228
14,365
14,613
14,850
15,059
15,243
15,423
15,599
15,772
15,943
16,114
16,283
16,451
16,618
16,786
16,952
17,119
17,286
17,453
17,620
17,787
17,954
<37KW
728
710
692
671
648
596
551
526
499
472
444
417
392
368
348
332
320
310
301
294
288
284
280
278
276
275
275
275
275
276
278
279
282
284
286
289
291
294
296
TOTAL
29,619
30,285
30,666
30,972
31,196
29,481
28,211
28,172
27,948
27,748
27,482
27,140
25,406
24,066
23,809
23,470
23,250
23,028
22,923
23,021
23,151
23,284
23,416
23,564
23,724
23,897
24,083
24,283
24,495
24,715
24,941
25,175
25,411
25,648
25,887
26,129
26,372
26,617
26,864
5-28
-------
Emission Inventory
Table 3-23 Baseline (50-State) PM2.5 Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
12,928
13,279
13,393
13,457
13,456
11,863
10,632
10,388
9,995
9,619
9,187
8,733
8,330
7,910
7,487
7,126
6,846
6,601
6,433
6,342
6,276
6,229
6,197
6,177
6,168
6,173
6,190
6,218
6,258
6,304
6,356
6,413
6,471
6,529
6,588
6,647
6,707
6,767
6,828
Cl
AUXILIARY
2,632
2,690
2,708
2,703
2,686
2,407
2,195
2,163
2,105
2,052
,990
,933
,893
,850
,805
,752
,693
,634
,576
,528
,497
,474
,459
,451
,445
,441
,440
,440
,441
,444
,448
,454
,461
,469
,478
,489
,501
,514
,527
Cl
TOTAL
15,560
15,969
16,100
16,159
16,142
14,270
12,827
12,552
12,100
11,670
11,177
10,666
10,223
9,760
9,291
8,878
8,539
8,235
8,009
7,871
7,773
7,703
7,656
7,628
7,613
7,614
7,629
7,658
7,699
7,748
7,804
7,867
7,932
7,998
8,066
8,136
8,207
8,281
8,355
C2
PROPULSION
12,464
12,719
12,975
13,232
13,490
13,748
14,003
14,264
14,525
14,787
15,050
15,255
14,041
13,226
13,466
13,566
13,703
13,801
13,934
14,175
14,405
14,607
14,786
14,960
15,131
15,299
15,465
15,630
15,794
15,957
16,120
16,282
16,444
16,605
16,767
16,929
17,091
17,253
17,416
<37KW
706
689
671
651
629
578
534
511
484
458
431
404
381
357
337
322
311
301
292
285
279
275
272
269
268
267
267
267
267
268
269
271
273
275
278
280
282
285
287
TOTAL
28,730
29,377
29,746
30,042
30,260
28,596
27,364
27,327
27,109
26,916
26,657
26,326
24,644
23,344
23,095
22,766
22,553
22,337
22,236
22,330
22,457
22,585
22,714
22,857
23,012
23,180
23,361
23,555
23,760
23,973
24,193
24,420
24,648
24,879
25,111
25,345
25,581
25,819
26,058
5-29
-------
Regulatory Impact Analysis
Table 3-24 Baseline (50-State) NOX Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
335,561
336,369
332,798
328,810
324,900
316,663
308,524
300,509
292,651
284,979
277,551
270,764
264,634
258,879
253,538
249,327
246,339
243,964
242,764
242,677
242,990
243,640
244,563
245,736
247,141
248,720
250,474
252,384
254,450
256,608
258,851
261,181
263,532
265,903
268,297
270,711
273,148
275,606
278,086
Cl
AUXILIARY
60,641
60,959
60,482
59,774
59,073
58,048
57,030
56,020
55,022
54,038
53,069
52,118
51,185
50,277
49,399
48,589
47,849
47,160
46,531
46,079
45,840
45,706
45,683
45,756
45,875
46,035
46,228
46,452
46,703
46,980
47,283
47,611
47,962
48,332
48,721
49,126
49,553
49,991
50,436
Cl
TOTAL
396,202
397,328
393,280
388,583
383,973
374,710
365,554
356,529
347,673
339,017
330,621
322,882
315,819
309,156
302,937
297,916
294,188
291,123
289,295
288,756
288,831
289,346
290,245
291,492
293,016
294,755
296,703
298,836
301,153
303,588
306,134
308,792
311,494
314,236
317,017
319,838
322,701
325,597
328,522
C2
PROPULSION
432,306
431,973
431,683
431,417
431,195
427,380
423,601
419,857
416,169
412,537
408,943
405,428
401,970
398,593
395,295
392,101
388,988
386,000
383,155
380,458
377,990
376,313
375,430
374,784
374,343
374,086
374,039
374,219
375,126
376,727
378,567
380,573
382,749
385,076
387,519
390,097
392,794
395,609
398,527
<37KW
5,517
5,448
5,350
5,229
5,101
4,973
4,846
4,719
4,594
4,472
4,351
4,234
4,120
4,011
3,917
3,846
3,790
3,744
3,704
3,675
3,659
3,654
3,654
3,658
3,670
3,685
3,703
3,723
3,746
3,771
3,798
3,828
3,859
3,891
3,924
3,958
3,992
4,026
4,061
TOTAL
834,025
834,749
830,313
825,229
820,269
807,063
794,001
781,105
768,436
756,026
743,915
732,544
721,910
711,760
702,150
693,862
686,966
680,867
676,154
672,889
670,480
669,313
669,329
669,934
671,029
672,525
674,445
676,778
680,025
684,087
688,500
693,193
698,103
703,203
708,460
713,892
719,486
725,233
731,111
-------
Emission Inventory
Table 3-25 Baseline (50-State) VOC Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
9,488
9,573
9,561
9,550
9,540
9,415
9,291
9,170
9,051
8,934
8,821
8,711
8,606
8,507
8,415
8,347
8,304
8,272
8,269
8,293
8,326
8,367
8,414
8,466
8,523
8,584
8,649
8,719
8,792
8,868
8,946
9,026
9,107
9,189
9,272
9,356
9,440
9,525
9,610
Cl
AUXILIARY
,767
,783
,785
,788
,791
,787
,783
,779
,776
,773
,770
,767
,765
,763
,761
,760
,759
,759
,760
,764
,771
,778
,788
,799
,811
,824
,837
,851
,865
,880
,895
,911
,927
,943
,960
,977
,995
2,013
2,031
Cl
TOTAL
11,255
11,356
11,346
11,338
11,331
11,202
11,074
10,949
10,826
10,707
10,591
10,479
10,371
10,270
10,176
10,107
10,063
10,031
10,029
10,057
10,097
10,145
10,202
10,265
10,334
10,408
10,487
10,570
10,657
10,748
10,841
10,937
11,034
11,133
11,232
11,333
11,435
11,537
11,641
C2
PROPULSION
4,701
4,743
4,786
4,829
4,872
4,916
4,960
5,005
5,050
5,096
5,141
5,188
5,234
5,281
5,329
5,377
5,425
5,474
5,523
5,573
5,623
5,674
5,725
5,777
5,829
5,881
5,934
5,987
6,041
6,096
6,150
6,206
6,262
6,318
6,375
6,432
6,490
6,549
6,607
<37KW
,273
,222
,179
,128
,075
,022
969
916
864
813
763
715
668
624
588
564
546
531
519
507
497
491
485
481
479
478
478
478
479
481
484
488
492
496
500
504
509
513
517
TOTAL
17,229
17,321
17,311
17,295
17,278
17,140
17,003
16,870
16,741
16,615
16,495
16,381
16,273
16,175
16,094
16,048
16,034
16,036
16,071
16,137
16,218
16,310
16,412
16,523
16,642
16,767
16,898
17,035
17,178
17,325
17,476
17,631
17,788
17,947
18,107
18,269
18,433
18,599
18,766
-------
Regulatory Impact Analysis
Table 3-26 Baseline (50-State) CO Emissions for Commercial Marine Diesel Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
55,303
55,801
55,722
55,582
55,450
54,423
53,405
52,401
51,414
50,445
49,497
48,574
47,680
46,827
46,023
45,368
44,879
44,482
44,301
44,329
44,423
44,571
44,760
44,987
45,248
45,539
45,861
46,209
46,583
46,975
47,385
47,811
48,241
48,675
49,114
49,556
50,002
50,452
50,906
Cl
AUXILIARY
9,624
9,710
9,668
9,585
9,503
9,331
9,160
8,989
8,820
8,654
8,489
8,327
8,167
8,010
7,857
7,708
7,563
7,426
7,298
7,198
7,134
7,088
7,066
7,067
7,077
7,094
7,117
7,145
7,178
7,215
7,257
7,303
7,353
7,407
7,464
7,524
7,588
7,654
7,721
Cl
TOTAL
64,927
65,511
65,390
65,167
64,954
63,754
62,565
61,391
60,235
59,099
57,986
56,901
55,847
54,837
53,880
53,076
52,443
51,908
51,599
51,527
51,557
51,659
51,827
52,054
52,325
52,633
52,978
53,354
53,761
54,191
54,642
55,114
55,595
56,082
56,577
57,079
57,589
58,105
58,627
C2
PROPULSION
82,621
83,364
84,115
84,872
85,635
85,621
85,611
85,605
85,609
85,621
85,639
85,665
85,701
85,746
85,800
85,864
85,937
86,020
86,116
86,222
86,341
86,475
86,626
86,790
86,974
87,178
87,406
87,672
88,078
88,623
89,207
89,820
90,457
91,119
91,799
92,500
93,219
93,956
94,707
<37KW
3,783
3,680
3,576
3,460
3,339
3,216
3,093
2,970
2,846
2,724
2,603
2,484
2,369
2,259
2,170
2,109
2,063
2,027
,997
,972
,952
,940
,932
,926
,926
,929
,934
,942
,952
,963
,977
,992
2,009
2,026
2,044
2,061
2,079
2,097
2,115
TOTAL
151,331
152,556
153,080
153,499
153,928
152,591
151,269
149,966
148,690
147,444
146,227
145,050
143,917
142,842
141,851
141,049
140,443
139,954
139,712
139,720
139,851
140,073
140,384
140,771
141,226
141,740
142,318
142,968
143,791
144,776
145,825
146,926
148,060
149,227
150,419
151,640
152,887
154,158
155,449
-------
Emission Inventory
Table 3-27 Baseline (50-State) SO2 Emissions for Commercial Marine Diesel Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
36,201
36,528
36,862
37,192
36,827
19,121
6,299
6,355
4,705
3,513
1,862
664
799
857
865
872
879
886
893
900
907
915
923
931
939
946
954
962
970
978
986
995
1,006
1,015
1,023
1,032
1,040
1,050
1,059
Cl
AUXILIARY
6,553
6,613
6,673
6,733
6,667
3,461
1,140
1,150
852
636
337
120
145
155
157
158
159
160
162
163
164
166
167
169
170
171
173
174
176
177
179
180
182
184
185
187
188
190
192
Cl
TOTAL
42,754
43,141
43,535
43,925
43,493
22,583
7,440
7,506
5,557
4,148
2,199
784
943
,012
,021
,030
,038
,046
,055
,063
,072
,081
,090
,099
,109
,118
,127
,136
,146
,155
,165
,175
,188
,198
,208
,218
,228
,240
,251
C2
PROPULSION
36,868
37,193
37,528
37,866
38,207
38,550
38,837
39,204
39,559
39,920
40,278
39,905
21,334
7,888
7,958
6,238
4,998
3,277
2,031
2,185
2,258
2,279
2,299
2,319
2,339
2,359
2,379
2,399
2,421
2,442
2,463
2,485
2,507
2,529
2,551
2,573
2,595
2,618
2,641
<37KW
731
738
745
752
745
387
128
129
95
71
38
14
16
18
18
18
18
18
18
18
18
19
19
19
19
19
19
20
20
20
20
20
21
21
21
21
21
21
22
TOTAL
80,353
81,073
81,808
82,543
82,445
61,520
46,404
46,838
45,212
44,139
42,515
40,702
22,293
8,917
8,997
7,286
6,054
4,342
3,104
3,267
3,348
3,378
3,408
3,437
3,466
3,496
3,526
3,555
3,586
3,617
3,649
3,680
3,716
3,748
3,780
3,812
3,845
3,880
3,913
-------
Regulatory Impact Analysis
Table 3-28 Air Toxics Emissions for Commercial Marine Diesel Engines (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3 -BUTADIENE
ACROLEIN
NAPHTHALENE
POM
1999
530
3,897
1,937
6
75
43
11
2010
556
4,091
2,033
6
79
39
10
2015
559
4,112
2,044
6
79
37
9
2020
572
4,208
2,091
6
81
36
9
2030
624
4,587
2,280
7
89
40
10
3.1.3 Control Inventory Development
This section describes how the control emission inventories were developed for the
commercial marine diesel categories: Category 1 propulsion, Category 1 auxiliary, Category 2
propulsion, and less than (<) 37kW. This section will only describe the modifications to the
emission factors, since the other inventory inputs are unchanged.
3.1.3.1 Control Scenario(s) Modeled
For commercial marine diesel engines, there are two tiers of final PM standards and
either combined HC+NOX or NOX and HC only standards for the control scenario that were
modeled.
The final emission standards for Category 1 engines are summarized in Table 3-29 and
Table 3-30. These standards apply to both propulsion and auxiliary engines. There are
separate emission levels for standard and high power density engines. Standard power
density engines are less than 35 kW per liter (kW/L), and the high power density engines are
greater than or equal to 35 kW/L. Within these power density categories, there are also
separate standards that vary by power and displacement. There are no Tier 4 standards for
engines less than 600 kW. Standards are not shown in cases where there is zero engine
population.
The final emission standards for Category 2 engines are summarized in Table 3-31.
The standards vary by displacement and power. All Category 2 engines are considered to be
standard power density engines. These engines are subject to both Tier 3 and Tier 4 emission
standards.
The final emission standards for <37kW propulsion and auxilliary engines are given in
Table 3-32. This category is subject to Tier 3 standards which begin in 2009.
> O A
5-34
-------
Emission Inventory
Table 3-29 Final Standards (g/kW-hr) for Cl Standard Power Density Engines
DISPLACEMENT
CATEGORY
DISP0.9 AND
3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
<35 KW/L
<=600KW
YEAR
2009
2014
2012
2013
2014
2018
2013
2018
2012
2018
TIERS
NOx+HC
7.5
4.7
5.4
5.4
5.6
5.6
5.8
PM
0.30
0.13
0.12
0.11
0.09
0.11
0.09
0.11
0.09
YEAR
NO TIER
TIER 4
HC
NOX
PM
4 STANDARDS
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
<35 KW/L
1000
-------
Regulatory Impact Analysis
Table 3-30 Final Standards (g/kW-hr) for Cl High Power Density Engines
DISPLACEMENT
CATEGORY
DISP0.9 AND
3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
>35 KW/L
<=600KW
YEAR
2009
2014
2012
2013
2014
TIER 3
NOx+HC
7.5
4.7
5.8
5.8
5.8
PM
0.30
0.15
0.13
0.12
NO ENGINES
YEAR
TIER 4
HC
NOX
PM
NO TIER 4 STANDARDS
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
>35 KW/L
1000
-------
Emission Inventory
Table 3-31 Final Standards (g/kW-hr) for C2 Engines
DISPLACEMENT CATEGORY
5.0<=DISP<15 AND <600KW
5.0<=DISP<15 AND 60077nrปTf w
15.0<=DISP<20.0 AND <1400KW
15.0<=DISP<20.0 AND 1400 onnn^T^w^'jnn
15.0<=DISP<20.0 AND 3300 ^"rnm^w
20.0<=DISP<30.0
YEAR
2013
2013
2013
2013
2013
TIER 3
NOx+HC
6.2
6.2
6.2
6.2
PM
0.13
0.13
0.13
0.13
0.13
YEAR
2018
2017
2016
2014
2016
2014
2017
TIER 4
HC
0.19
0.19
0.19
0.19
0.19
NOX
1.7
1.7
1.7
1.7
1.7
PM
0.04
0.04
0.04
0.04
0.12
0.05
NO ENGINES IN THIS CATEGORY
2014
2014
7.0
0.34
0.34
2016
2014
2016
0.19
0.19
1.7
1.7
0.04
0.04
NO ENGINES IN THIS CATEGORY
2014
2017
0.19
1.7
0.25
0.05
NO ENGINES IN THIS CATEGORY
Table 3-32 Final Standards (g/hp-hr) for <37kW Commercial Marine Diesel Engines
HP
RANGE
0-25
25-50
YEAR
2009
2009
2014
TIERS
NOx+HC
5.6
5.6
3.5
PM
0.30
0.22
0.22
In addition to the new emission standards, Category 1 and Category 2 engines larger
than 600 kW and newly manufactured after January 1, 1973 are subject to a remanufacturing
program. A description of the remanufacturing program modeled is provided in Table 3-33.
The remanufacturing program affects PM emissions from Category 1 engines and both NOx
and PM emissions from Category 2 engines. The remanufacturing program exempts those
vessel owners who earn less than $5 million per year in gross annual revenues.
Table 3-33 Description of Remanufacturing Program Modeled
Category
Category 1
Category 2
Power
Cutoff
>600 kW
>600 kW
Calendar
Year Start
2012
2008
Model
Years
1972+
1972+
Engine Model Series
Cat 3500
DOC/MTU 149
Cummins KTA 38
EMD645
EMD710
GE (all models)
Tiers
Tiers 0/1/2
Tiers 0/1 for NOx
Tiers 0/1/2 for PM
Percent
Reduction
NOx
None
30%
PM
25%
25%
-------
Regulatory Impact Analysis
3.1.3.2 Category 1 Propulsion
The modeled Tier 3 and Tier 4 emission factors corresponding to the emission
standards are shown in Table 3-34 and Table 3-35. These emission factors are derived by
applying the appropriate relative reductions from the Tier 2 standard to the Tier 2 emission
factors, using the following equations:
Equation 3-8 Tier 3 EF = (Tier 3 std/Tier 2 std) x Tier 2 EF
Equation 3-9 Tier 4 EF = (Tier 4 std/Tier 2 std) x Tier 2 EF
For NOX, the standards used in the above equations are the combined HC+NOX
standards. For HC and PM, the PM standards are used.
Once inventories were estimated using the control emission factors, the additional
NOx emissions reductions of the remanufacturing program were calculated. The total NOx
inventories were first separated by tier and by power category. The NOx emissions from Tier
0, Tier 1, and Tier 2 engines greater than 600 kW that are subject to the remanufacturing
program were then summed for each calendar year. The following equation was then applied
to those affected tons to calculate the reduced tons under the remanufacturing program:
Equation 3-10 Remfr TonsCY = [Frac ct!CY x (1-Red) + (1-Frac ct!CY)] x TonsCY
Where:
Remfr Tonscy = Tons for >600kW pre-Tier 3 engines with remanufacturing program,
by calendar year
Fract ctlcY = Fraction of the fleet >600kW subject to the remanufacturing program, by
calendar year (from Table 3-36)
Red = Fractional reduction (0.25 from Table 3-33)
Tons = Tons for >600kW pre-Tier 3 engines, by calendar year
The fraction of the fleet subject to the remanufacturing program was estimated based
on an evaluation of a random sample of inland river vessels.26 A seven year phase-in was
allowed to account for the typical rebuild cycle for these engines. The resulting fleet fractions
by calendar year are provided in Table 3-36.
The remanufacture tons (Remfr Tons) was then subtracted from the Tons value to
obtain the delta tons for the remanufacturing program for each calendar year. The resulting
delta tons value was decreased by 12 percent to account for the small business exemption.
This delta tons value was then subtracted from the total Category 1 propulsion inventory for
each calendar year to obtain the resulting tons for the combined emission standard and marine
remanufacturing control program.
The resulting control case 50-state emission inventories for Category 1 propulsion
engines are given in Table 3-37.
J-J
-------
Emission Inventory
Table 3-34 Control PM10, NOx, and HC Emission Factors (g/kW-hr) for Cl Propulsion Standard Power Density Engines
DISPLACEMENT
CATEGORY
DISPO.9 AND
3775KW
0.9<=DISP<1.2
i i75KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
<35 KW/L
10001400KW
,TAr TIERS ,TAF TIER 4
HC NOX PM ^ HC NOX PM
NO ENGINES IN THESE CATEGORIES
2012 0.10 4.81 0.07 2016 0.04 1.3 0.03
3-39
-------
Regulatory Impact Analysis
Table 3-35 Control PM10, NOx, and HC Emission Factors (g/kW-hr) for Cl Propulsion High Power Density Engines
DISPLACEMENT
CATEGORY
DISP0.9 AND
3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
>35 KW/L
<=600KW
YEAR
TIERS
HC
NOX
PM
NO ENGINES
2012
2013
2014
0.15
0.14
0.11
4.38
4.89
4.81
0.08
0.05
0.08
NO ENGINES
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
>35 KW/L
10001400KW
TIER 3 TIER 4
lL^ HC NOX PM HC NOX PM
NO ENGINES IN THESE CATEGORIES
2012 0.10 4.81 0.07 2016 0.04 1.3 0.03
3-40
-------
Emission Inventory
Table 3-36 Percent of Fleet Subject to Remanufacturing Standards*
Calendar Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018+
Category 1
0.0%
0.0%
0.0%
0.0%
8.5%
16.9%
25.4%
33.9%
42.3%
50.8%
59.3%
Category 2
8.8%
17.6%
26.4%
35.2%
44.0%
52.8%
61.6%
61.6%
61.6%
61.6%
61.6%
* Note that these percentages were based on an earlier draft analysis of Inland River Record samples.
The percentages in the final analysis differ by less than two percent from those in this table.
5-41
-------
Regulatory Impact Analysis
Table 3-37 Control Case (50-State) Emissions for Cl Propulsion Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
13,328
13,690
13,807
13,873
13,872
12,230
10,961
10,709
10,304
9,916
9,274
8,610
7,949
7,288
6,608
5,981
5,422
4,970
4,582
4,259
3,956
3,668
3,393
3,143
2,922
2,739
2,591
2,471
2,387
2,330
2,295
2,273
2,258
2,249
2,246
2,249
2,256
2,268
2,282
PM2.5
12,928
13,279
13,393
13,457
13,456
11,863
10,632
10,388
9,995
9,618
8,996
8,351
7,710
7,070
6,410
5,802
5,259
4,821
4,445
4,132
3,837
3,558
3,292
3,048
2,834
2,657
2,513
2,397
2,315
2,260
2,226
2,205
2,190
2,182
2,179
2,181
2,188
2,200
2,214
NOX
335,561
336,369
332,798
328,810
324,900
316,663
308,524
300,509
292,651
284,979
276,209
267,453
257,691
248,317
236,292
223,265
209,717
196,847
185,242
174,843
164,971
155,589
146,696
138,521
131,195
124,763
119,185
114,708
111,660
109,766
108,624
107,896
107,443
107,233
107,236
107,444
107,834
108,376
109,054
voc
9,488
9,573
9,561
9,550
9,540
9,415
9,291
9,169
9,050
8,933
8,708
8,433
8,042
7,658
7,228
6,784
6,334
5,898
5,496
5,126
4,772
4,433
4,111
3,826
3,589
3,400
3,252
3,134
3,049
2,991
2,953
2,927
2,911
2,902
2,901
2,906
2,919
2,936
2,957
HC
9,010
9,091
9,080
9,069
9,060
8,941
8,824
8,708
8,594
8,483
8,270
8,008
7,637
7,273
6,864
6,443
6,015
5,601
5,219
4,868
4,532
4,210
3,904
3,634
3,408
3,229
3,089
2,976
2,896
2,841
2,804
2,780
2,764
2,756
2,755
2,760
2,772
2,788
2,808
CO
55,303
55,801
55,722
55,582
55,450
54,423
53,405
52,401
51,414
50,445
49,497
48,574
47,680
46,827
46,023
45,368
44,879
44,482
44,301
44,329
44,423
44,571
44,760
44,987
45,248
45,539
45,861
46,209
46,583
46,975
47,385
47,811
48,241
48,675
49,114
49,556
50,002
50,452
50,906
S02
36,201
36,528
36,862
37,192
36,827
19,121
6,299
6,355
4,705
3,513
1,862
664
799
857
865
872
879
886
893
900
907
915
923
931
939
946
954
962
970
978
986
995
1,006
1,015
1,023
1,032
1,040
1,050
1,059
5-42
-------
Emission Inventory
3.1.3.3 Category 1 Auxiliary
The modeled Tier 3 and Tier 4 emission factors for Category 1 auxiliary engines are
shown in Table 3-38 and Table 3-39. The methodology described above for Category 1
propulsion engines was used to derive these emission factors and calculate the emissions
impact of the remanufacturing program.
The resulting control case 50-state emission inventories for Category 1 auxiliary
engines are given in Table 3-40.
5-43
-------
Regulatory Impact Analysis
Table 3-38 Control PM10, NOx, and HC Emission Factors (g/kW-hr) for Cl Auxiliary Standard Power Density Engines
DISPLACEMENT
CATEGORY
DISPO.9 AND
3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
<35 KW/L
<600KW
YEAR
2009
2014
2012
2013
2014
2018
2013
2018
2012
2018
TIERS
HC
0.30
0.14
0.13
0.11
0.11
0.11
NOX
5.70
3.56
4.08
4.02
4.77
4.77
4.89
PM
0.17
0.08
0.08
0.08
0.070
0.08
0.070
0.08
0.070
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
<35 KW/L
10001400KW
TIER 3 TIER 4
HC NOX PM HC NOX PM
NO ENGINES IN THESE CATEGORIES
2012 0.11 4.89 0.08 2016 0.04 1.3 0.03
3-44
-------
Emission Inventory
Table 3-39 Control PM10, NOx, and HC Emission Factors (g/kW-hr) for Cl Auxiliary High Power Density Engines
DISPLACEMENT
CATEGORY
DISPO.9 AND
3775KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
>35 KW/L
<600KW
YEAR
2009
2014
2012
TIER 3
HC
0.30
0.15
NOX
5.70
3.56
4.38
PM
0.17
0.08
NO ENGINES IN THESE
CATEGORIES
60075KW
0.9<=DISP<1.2
1.2<=DISP<2.5
2.5<=DISP<3.5
3.5<=DISP<5.0
>35 KW/L
10001400KW
,TAr TIERS ,TAF TIER 4
HC NOX PM ^ HC NOX PM
NO ENGINES IN THESE CATEGORIES
2014 0.11 4.77 0.08 2016 0.04 1.3 0.03
NO ENGINES IN THESE CATEGORIES
3-45
-------
Regulatory Impact Analysis
Table 3-40 Control Case (50-State) Emissions for Cl Auxiliary Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
2,714
2,773
2,791
2,786
2,769
2,482
2,263
2,229
2,169
2,113
2,028
,943
,862
,778
,691
,597
,490
,393
,296
,210
,138
,075
1,019
968
919
873
829
788
752
723
700
680
664
652
644
638
635
634
634
PM2.5
2,632
2,690
2,708
2,703
2,686
2,407
2,195
2,162
2,104
2,049
,967
,884
,806
,725
,641
,549
,445
,351
,258
,173
,104
,043
988
939
892
847
804
765
730
702
679
660
644
632
625
619
616
615
615
NOX
60,641
60,959
60,482
59,774
59,073
58,048
57,030
56,020
55,022
54,038
52,949
51,796
50,317
48,863
47,349
45,754
43,895
42,089
40,347
38,787
37,444
36,210
35,096
34,089
33,138
32,243
31,399
30,630
29,948
29,388
28,939
28,572
28,303
28,159
28,117
28,123
28,176
28,259
28,367
voc
1,767
1,783
1,785
1,788
1,791
1,787
1,783
1,778
1,773
1,768
1,753
1,727
1,677
1,628
1,577
1,523
1,463
1,403
1,345
1,290
1,239
1,188
1,141
1,095
1,052
1,010
970
935
905
882
866
853
843
836
832
830
829
829
831
HC
,678
,693
,696
,698
,700
,697
,693
,688
,684
,679
,664
,640
,593
,546
,497
,446
,389
,333
,278
,225
,176
,129
,083
,040
999
959
921
888
859
838
823
810
801
794
790
788
787
788
789
CO
9,624
9,710
9,668
9,585
9,503
9,331
9,160
8,989
8,820
8,654
8,489
8,327
8,167
8,010
7,857
7,708
7,563
7,426
7,298
7,198
7,134
7,088
7,066
7,067
7,077
7,094
7,117
7,145
7,178
7,215
7,257
7,303
7,353
7,407
7,464
7,524
7,588
7,654
7,721
S02
6,553
6,613
6,673
6,733
6,667
3,461
1,140
1,150
852
636
337
120
145
155
157
158
159
160
162
163
164
166
167
169
170
171
173
174
176
177
179
180
182
184
185
187
188
190
192
5-46
-------
Emission Inventory
3.1.3.4 Category 2 Propulsion
The modeled Tier 3 and Tier 4 emission factors for Category 2 propulsion engines are
shown in Table 3-41. The methodology described above for Category 1 propulsion engines
was used to derive these emission factors. The emissions impact of the remanufacturing
program was calculated using Equation 3-10 and the inputs provided in Table 3-33 and Table
3-36. Similarly to Category 1, the emissions benefit of the remanufacturing program was
reduced by 12 percent to account for the small business exemption.
The resulting control case 50-state emission inventories for Category 2 propulsion
engines are given in Table 3-42.
Table 3-41 Control PM10, NOx, and HC Emission Factors (g/kW-hr) for C2 Engines
DISPLACEMENT CATEGORY
5.0<=DISP<15 AND <600KW
5.0<=DISP<15 AND 600 onnn^T^w^'5'7nn
5.0<=DISP<15 AND >3700KW
15.0<=DISP<20.0 AND 1400 onnn^vw^'snn
15.0<=DISP<20.0 AND >3700KW
YEAR
2013
2013
2013
2013
2013
TIER 3
HC
0.07
0.07
0.07
0.07
NOX
5.97
5.97
5.97
5.97
PM
0.11
0.11
0.11
0.11
0.11
2014
2014
0.09
6.77
0.30
0.30
YEAR
2018
2017
2016
2014
2016
2014
2017
2016
2014
2016
2014
2017
TIER 4
HC
0.02
0.02
0.02
0.02
0.06
0.03
0.01
0.01
0.07
0.01
NOX
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
1.3
PM
0.03
0.03
0.03
0.03
0.10
0.04
0.04
0.04
0.23
0.05
5-47
-------
Regulatory Impact Analysis
Table 3-42 Control Case (50-State) Emissions for C2 Propulsion Engines
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PM10
12,850
13,112
13,376
13,641
13,907
14,174
14,164
14,151
14,127
14,094
14,051
13,813
12,231
11,378
11,293
10,973
10,680
10,361
10,067
9,831
9,580
9,298
8,990
8,670
8,340
8,001
7,653
7,301
6,943
6,581
6,216
5,852
5,488
5,128
4,795
4,504
4,244
4,022
3,864
PM25
12,464
12,719
12,975
13,232
13,490
13,748
13,739
13,726
13,703
13,671
13,630
13,399
11,864
11,037
10,954
10,644
10,360
10,051
9,765
9,536
9,293
9,019
8,720
8,410
8,090
7,761
7,424
7,082
6,735
6,383
6,030
5,676
5,323
4,974
4,651
4,369
4,116
3,902
3,748
NOX
432,306
431,973
431,683
431,417
431,195
427,380
414,725
402,915
391,965
381,869
372,614
363,742
345,213
333,586
320,992
308,346
295,746
283,222
270,832
258,585
246,543
235,176
224,475
213,984
203,629
193,441
183,404
173,555
164,024
154,845
145,870
137,176
128,777
120,726
113,237
107,705
104,042
101,058
98,614
VOC
4,701
4,743
4,786
4,829
4,872
4,916
4,960
5,005
5,050
5,096
5,141
5,174
5,069
4,964
4,846
4,680
4,514
4,348
4,182
4,018
3,855
3,692
3,530
3,369
3,209
3,050
2,891
2,734
2,579
2,427
2,276
2,129
1,986
1,848
1,718
1,616
1,539
1,472
1,420
HC
4,464
4,504
4,545
4,586
4,627
4,669
4,711
4,753
4,796
4,839
4,883
4,914
4,814
4,714
4,602
4,445
4,287
4,129
3,972
3,816
3,661
3,506
3,352
3,200
3,047
2,896
2,746
2,597
2,450
2,305
2,162
2,022
,886
,755
,632
,535
,462
,398
,349
CO
82,621
83,364
84,115
84,872
85,635
85,621
85,611
85,605
85,609
85,621
85,639
85,665
85,701
85,746
85,800
85,864
85,937
86,020
86,116
86,222
86,341
86,475
86,626
86,790
86,974
87,178
87,406
87,672
88,078
88,623
89,207
89,820
90,457
91,119
91,799
92,500
93,219
93,956
94,707
S02
36,868
37,193
37,528
37,866
38,207
38,550
38,837
39,204
39,559
39,920
40,278
39,905
21,334
7,888
7,817
5,901
4,574
2,963
1,888
1,976
1,995
1,975
1,954
1,934
1,913
1,894
1,874
1,855
1,836
1,818
1,800
1,783
1,766
1,750
1,735
1,721
1,709
1,700
1,699
5-48
-------
Emission Inventory
3.1.3.5 Less than 37 kW Propulsion and Auxiliary
The modeled Tier 3 emission factors for less than (<) 37kW commercial marine diesel
engines are given in Table 3-43. These emission factors apply to both propulsion and
auxiliary engines. For HC, the methodology described for Category 1 propulsion engines was
used. For PM, a 20 percent compliance margin was applied to the Tier 3 standard; however,
if the resulting emission factor was greater than the corresponding Tier 2 emission factor, the
Tier 2 value was used for Tier 3. Since the final rule does not result in NOX control for this
category, the Tier 3 NOX emission factors were set equal to Tier 2.
Table 3-43 Control PM10, NOX, and HC Emission Factors (g/hp-hr) for <37kW Commercial Marine Diesel
Engines
HP
RANGE
0-11
11-16
16-25
25-50
YEAR
2009
2009
2014
2009
2014
2009
2014
TIER 3
HC
0.43
0.21
0.21
0.21
0.21
0.41
0.41
NOX
4.39
3.63
2.32
3.63
2.32
3.71
2.32
PM
0.24
0.19
0.19
0.19
0.19
0.18
0.18
The resulting control case 50-state emission inventories for <37kW propulsion and
auxiliary engines are given in Table 3-44.
3.1.3.6 Commercial Marine Diesel Control Inventory Summary
3.1.3.6.1 PMio, PM25, NOX, VOC, CO, andSO2 Emissions
Table 3-45 thru Table 3-50 present the resulting 50-state consolidated commercial
marine control case inventories for each pollutant and category, for calendar years 2002-2040.
3.1.3.6.2 Air Toxics Emissions
The control case air toxics inventories for commercial marine diesel engines are
provided in Table 3-51. The gaseous air toxics are assumed to be controlled proportionately
to VOC, whereas POM is controlled proportionately to PM.
5-49
-------
Regulatory Impact Analysis
Table 3-44 Control Case (50-State) Emissions for <37kW Commercial Marine Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
728
710
692
671
648
596
551
524
495
466
437
409
383
357
334
317
303
291
280
271
263
257
252
248
244
242
241
240
240
240
241
242
244
245
247
249
251
253
255
PM2.5
706
689
671
651
629
578
534
509
480
452
424
397
371
346
324
308
294
282
272
263
255
249
244
240
237
235
234
233
233
233
234
235
236
238
240
242
244
246
248
NOX
5,517
5,448
5,350
5,229
5,101
4,973
4,846
4,719
4,594
4,472
4,351
4,234
4,073
3,917
3,777
3,658
3,556
3,462
3,377
3,301
3,240
3,188
3,144
3,103
3,070
3,042
3,018
2,998
2,982
2,978
2,983
2,993
3,007
3,022
3,040
3,058
3,079
3,100
3,123
voc
1,273
1,222
1,179
1,128
1,075
1,022
969
911
853
797
741
688
636
586
545
515
492
472
454
438
423
411
401
393
387
383
381
379
378
378
380
381
384
387
389
392
395
398
402
HC
1,209
1,161
1,120
1,071
1,021
970
920
865
810
757
704
653
604
556
518
489
467
448
432
416
402
390
381
373
368
364
361
360
359
359
360
362
365
367
370
372
375
378
381
CO
3,783
3,680
3,576
3,460
3,339
3,216
3,093
2,970
2,846
2,724
2,603
2,484
2,369
2,259
2,170
2,109
2,063
2,027
,997
,972
,952
,940
,932
,926
,926
,929
,934
,942
,952
,963
,977
,992
2,009
2,026
2,044
2,061
2,079
2,097
2,115
S02
731
738
745
752
745
387
128
129
95
71
38
14
16
18
18
18
18
18
18
18
18
19
19
19
19
19
19
20
20
20
20
20
21
21
21
21
21
21
22
5-50
-------
Emission Inventory
Table 3-45 Control Case (50-State) PM10 Emissions for Commercial Marine Diesel Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
13,328
13,690
13,807
13,873
13,872
12,230
10,961
10,709
10,304
9,916
9,290
8,640
7,990
7,338
6,663
6,039
5,480
5,020
4,625
4,296
3,986
3,692
3,412
3,157
2,933
2,747
2,597
2,476
2,390
2,333
2,297
2,274
2,259
2,250
2,246
2,249
2,256
2,268
2,282
Cl
AUXILIARY
2,714
2,773
2,791
2,786
2,769
2,482
2,263
2,229
2,169
2,113
2,029
1,946
1,866
1,784
1,699
1,605
1,499
1,401
1,303
1,216
1,144
1,080
1,023
971
922
876
831
790
754
725
701
681
665
652
644
639
636
634
634
Cl
TOTAL
16,041
16,463
16,598
16,659
16,641
14,712
13,224
12,939
12,472
12,029
11,320
10,586
9,856
9,122
8,362
7,644
6,979
6,421
5,928
5,512
5,130
4,772
4,435
4,128
3,855
3,623
3,428
3,266
3,144
3,057
2,998
2,955
2,923
2,902
2,891
2,887
2,892
2,902
2,916
C2
PROPULSION
12,850
13,112
13,376
13,641
13,907
14,174
14,164
14,151
14,127
14,094
14,051
13,813
12,231
11,378
11,293
10,973
10,680
10,361
10,067
9,831
9,580
9,298
8,990
8,670
8,340
8,001
7,653
7,301
6,943
6,581
6,216
5,852
5,488
5,128
4,795
4,504
4,244
4,022
3,864
<37KW
728
710
692
671
648
596
551
524
495
466
437
409
383
357
334
317
303
291
280
271
263
257
252
248
244
242
241
240
240
240
241
242
244
245
247
249
251
253
255
TOTAL
29,619
30,285
30,666
30,972
31,196
29,481
27,938
27,614
27,095
26,589
25,808
24,808
22,470
20,857
19,989
18,934
17,962
17,073
16,275
15,614
14,973
14,328
13,677
13,046
12,440
11,866
11,323
10,807
10,327
9,878
9,455
9,049
8,655
8,276
7,933
7,641
7,387
7,177
7,035
5-51
-------
Regulatory Impact Analysis
Table 3-46 Control Case (50-State) PM2.5 Emissions for Commercial Marine Diesel Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
12,928
13,279
13,393
13,457
13,456
11,863
10,632
10,388
9,995
9,618
9,012
8,380
7,750
7,118
6,463
5,858
5,316
4,869
4,486
4,167
3,867
3,582
3,310
3,062
2,845
2,665
2,519
2,402
2,318
2,263
2,228
2,206
2,191
2,182
2,179
2,181
2,188
2,200
2,214
Cl
AUXILIARY
2,632
2,690
2,708
2,703
2,686
2,407
2,195
2,162
2,104
2,049
1,968
1,888
1,810
1,731
1,648
1,557
1,454
1,359
1,264
1,179
1,109
1,048
992
942
895
850
806
767
731
703
680
661
645
633
625
619
616
615
615
Cl
TOTAL
15,560
15,969
16,100
16,159
16,142
14,270
12,827
12,551
12,098
11,668
10,980
10,268
9,561
8,848
8,111
7,414
6,770
6,228
5,750
5,346
4,976
4,629
4,302
4,005
3,740
3,514
3,325
3,168
3,050
2,966
2,908
2,867
2,836
2,815
2,804
2,801
2,805
2,815
2,828
C2
PROPULSION
12,464
12,719
12,975
13,232
13,490
13,748
13,739
13,726
13,703
13,671
13,630
13,399
11,864
11,037
10,954
10,644
10,360
10,051
9,765
9,536
9,293
9,019
8,720
8,410
8,090
7,761
7,424
7,082
6,735
6,383
6,030
5,676
5,323
4,974
4,651
4,369
4,116
3,902
3,748
<37KW
706
689
671
651
629
578
534
509
480
452
424
397
371
346
324
308
294
282
272
263
255
249
244
240
237
235
234
233
233
233
234
235
236
238
240
242
244
246
248
TOTAL
28,730
29,377
29,746
30,042
30,260
28,596
27,100
26,785
26,282
25,792
25,034
24,064
21,796
20,231
19,389
18,366
17,423
16,561
15,787
15,145
14,524
13,898
13,266
12,654
12,067
11,510
10,983
10,483
10,017
9,582
9,171
8,778
8,395
8,028
7,695
7,411
7,165
6,962
6,824
5-52
-------
Emission Inventory
Table 3-47 Control Case (50-State) NOX Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
335,561
336,369
332,798
328,810
324,900
316,663
308,524
300,509
292,651
284,979
276,209
267,453
257,691
248,317
236,292
223,265
209,717
196,847
185,242
174,843
164,971
155,589
146,696
138,521
131,195
124,763
119,185
114,708
111,660
109,766
108,624
107,896
107,443
107,233
107,236
107,444
107,834
108,376
109,054
Cl
AUXILIARY
60,641
60,959
60,482
59,774
59,073
58,048
57,030
56,020
55,022
54,038
52,949
51,796
50,317
48,863
47,349
45,754
43,895
42,089
40,347
38,787
37,444
36,210
35,096
34,089
33,138
32,243
31,399
30,630
29,948
29,388
28,939
28,572
28,303
28,159
28,117
28,123
28,176
28,259
28,367
Cl
TOTAL
396,202
397,328
393,280
388,583
383,973
374,710
365,554
356,529
347,673
339,017
329,158
319,249
308,007
297,181
283,640
269,020
253,612
238,936
225,589
213,630
202,415
191,800
181,792
172,610
164,333
157,006
150,584
145,338
141,608
139,154
137,563
136,468
135,746
135,392
135,352
135,566
136,009
136,635
137,421
C2
PROPULSION
432,306
431,973
431,683
431,417
431,195
427,380
414,725
402,915
391,965
381,869
372,614
363,742
345,213
333,586
320,992
308,346
295,746
283,222
270,832
258,585
246,543
235,176
224,475
213,984
203,629
193,441
183,404
173,555
164,024
154,845
145,870
137,176
128,777
120,726
113,237
107,705
104,042
101,058
98,614
<37KW
5,517
5,448
5,350
5,229
5,101
4,973
4,846
4,719
4,594
4,472
4,351
4,234
4,073
3,917
3,777
3,658
3,556
3,462
3,377
3,301
3,240
3,188
3,144
3,103
3,070
3,042
3,018
2,998
2,982
2,978
2,983
2,993
3,007
3,022
3,040
3,058
3,079
3,100
3,123
TOTAL
834,025
834,749
830,313
825,229
820,269
807,063
785,125
764,163
744,232
725,358
706,123
687,225
657,294
634,684
608,409
581,023
552,914
525,620
499,798
475,517
452,197
430,164
409,411
389,698
371,033
353,489
337,006
321,891
308,614
296,977
286,416
276,637
267,530
259,140
251,629
246,330
243,131
240,793
239,157
5-53
-------
Regulatory Impact Analysis
Table 3-48 Control Case (50-State) VOC Emissions for Commercial Marine Diesel Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
9,488
9,573
9,561
9,550
9,540
9,415
9,291
9,169
9,050
8,933
8,708
8,433
8,042
7,658
7,228
6,784
6,334
5,898
5,496
5,126
4,772
4,433
4,111
3,826
3,589
3,400
3,252
3,134
3,049
2,991
2,953
2,927
2,911
2,902
2,901
2,906
2,919
2,936
2,957
Cl
AUXILIARY
,767
,783
,785
,788
,791
,787
,783
,778
,773
,768
,753
,727
,677
,628
,577
,523
,463
,403
,345
,290
,239
,188
,141
,095
,052
,010
970
935
905
882
866
853
843
836
832
830
829
829
831
Cl
TOTAL
11,255
11,356
11,346
11,338
11,331
11,202
11,074
10,947
10,823
10,701
10,461
10,160
9,719
9,286
8,805
8,307
7,796
7,302
6,841
6,416
6,010
5,621
5,252
4,922
4,640
4,410
4,223
4,068
3,953
3,874
3,819
3,781
3,754
3,738
3,733
3,736
3,748
3,765
3,787
C2
PROPULSION
4,701
4,743
4,786
4,829
4,872
4,916
4,960
5,005
5,050
5,096
5,141
5,174
5,069
4,964
4,846
4,680
4,514
4,348
4,182
4,018
3,855
3,692
3,530
3,369
3,209
3,050
2,891
2,734
2,579
2,427
2,276
2,129
,986
,848
,718
,616
,539
,472
,420
<37KW
,273
,222
,179
,128
,075
,022
969
911
853
797
741
688
636
586
545
515
492
472
454
438
423
411
401
393
387
383
381
379
378
378
380
381
384
387
389
392
395
398
402
TOTAL
17,229
17,321
17,311
17,295
17,278
17,140
17,003
16,863
16,726
16,594
16,344
16,022
15,424
14,836
14,196
13,502
12,802
12,121
11,478
10,872
10,288
9,724
9,183
8,684
8,236
7,843
7,494
7,182
6,911
6,679
6,475
6,291
6,124
5,973
5,841
5,744
5,682
5,636
5,609
5-54
-------
Emission Inventory
Table 3-49 Control Case (50-State) CO Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
55,303
55,801
55,722
55,582
55,450
54,423
53,405
52,401
51,414
50,445
49,497
48,574
47,680
46,827
46,023
45,368
44,879
44,482
44,301
44,329
44,423
44,571
44,760
44,987
45,248
45,539
45,861
46,209
46,583
46,975
47,385
47,811
48,241
48,675
49,114
49,556
50,002
50,452
50,906
Cl
AUXILIARY
9,624
9,710
9,668
9,585
9,503
9,331
9,160
8,989
8,820
8,654
8,489
8,327
8,167
8,010
7,857
7,708
7,563
7,426
7,298
7,198
7,134
7,088
7,066
7,067
7,077
7,094
7,117
7,145
7,178
7,215
7,257
7,303
7,353
7,407
7,464
7,524
7,588
7,654
7,721
Cl
TOTAL
64,927
65,511
65,390
65,167
64,954
63,754
62,565
61,391
60,235
59,099
57,986
56,901
55,847
54,837
53,880
53,076
52,443
51,908
51,599
51,527
51,557
51,659
51,827
52,054
52,325
52,633
52,978
53,354
53,761
54,191
54,642
55,114
55,595
56,082
56,577
57,079
57,589
58,105
58,627
C2
PROPULSION
82,621
83,364
84,115
84,872
85,635
85,621
85,611
85,605
85,609
85,621
85,639
85,665
85,701
85,746
85,800
85,864
85,937
86,020
86,116
86,222
86,341
86,475
86,626
86,790
86,974
87,178
87,406
87,672
88,078
88,623
89,207
89,820
90,457
91,119
91,799
92,500
93,219
93,956
94,707
<37KW
3,783
3,680
3,576
3,460
3,339
3,216
3,093
2,970
2,846
2,724
2,603
2,484
2,369
2,259
2,170
2,109
2,063
2,027
1,997
1,972
1,952
1,940
1,932
1,926
1,926
1,929
1,934
1,942
1,952
1,963
1,977
1,992
2,009
2,026
2,044
2,061
2,079
2,097
2,115
TOTAL
151,331
152,556
153,080
153,499
153,928
152,591
151,269
149,966
148,690
147,444
146,227
145,050
143,917
142,842
141,851
141,049
140,443
139,954
139,712
139,720
139,851
140,073
140,384
140,771
141,226
141,740
142,318
142,968
143,791
144,776
145,825
146,926
148,060
149,227
150,419
151,640
152,887
154,158
155,449
5-55
-------
Regulatory Impact Analysis
Table 3-50 Control Case (50-State) SO2 Emissions for Commercial Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
Cl
PROPULSION
36,201
36,528
36,862
37,192
36,827
19,121
6,299
6,355
4,705
3,513
1,862
664
799
857
865
872
879
886
893
900
907
915
923
931
939
946
954
962
970
978
986
995
1,006
1,015
1,023
1,032
1,040
1,050
1,059
Cl
AUXILIARY
6,553
6,613
6,673
6,733
6,667
3,461
1,140
1,150
852
636
337
120
145
155
157
158
159
160
162
163
164
166
167
169
170
171
173
174
176
177
179
180
182
184
185
187
188
190
192
Cl
TOTAL
42,754
43,141
43,535
43,925
43,493
22,583
7,440
7,506
5,557
4,148
2,199
784
943
,012
,021
,030
,038
,046
,055
,063
,072
,081
,090
,099
,109
,118
,127
,136
,146
,155
,165
,175
,188
,198
,208
,218
,228
,240
,251
C2
PROPULSION
36,868
37,193
37,528
37,866
38,207
38,550
38,837
39,204
39,559
39,920
40,278
39,905
21,334
7,888
7,817
5,901
4,574
2,963
,888
,976
,995
,975
,954
,934
,913
,894
,874
,855
,836
,818
,800
,783
,766
,750
,735
,721
,709
,700
,699
<37KW
731
738
745
752
745
387
128
129
95
71
38
14
16
18
18
18
18
18
18
18
18
19
19
19
19
19
19
20
20
20
20
20
21
21
21
21
21
21
22
TOTAL
80,353
81,073
81,808
82,543
82,445
61,520
46,404
46,839
45,212
44,139
42,515
40,702
22,293
8,917
8,855
6,949
5,630
4,028
2,961
3,058
3,085
3,074
3,063
3,052
3,041
3,031
3,020
3,010
3,002
2,993
2,985
2,978
2,975
2,969
2,964
2,961
2,958
2,962
2,971
5-56
-------
Emission Inventory
Table 3-51 Control Case (50-State) Air Toxic Emissions for Commercial Marine Diesel Engines (short
tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
556
4,088
2,032
6
79
38
9
2015
513
3,772
1,875
5
73
34
8
2020
409
3,005
1,494
4
58
26
6
2030
251
1,846
917
3
36
16
4
3.1.4 Projected Commercial Marine Emission Reductions of Final Rule
The PM2.5, NOX, and VOC emission reductions for each category and calendar year
are presented in Table 3-52 thru Table 3-54. The air toxic emission reductions by pollutant
and calendar year are given in Table 3-55.
5-57
-------
Regulatory Impact Analysis
Table 3-52 Projected Commercial Marine PM2.5 Emission Reductions (short tons)
YEAR
2008
2009
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
Cl
PROPULSION
0
0
0
0
175
353
580
792
1,023
1,268
1,530
1,732
1,947
2,175
2,409
2,647
2,887
3,115
3,323
3,508
3,671
3,816
3,939
4,041
4,128
4,207
4,280
4,347
4,409
4,466
4,518
4,568
4,614
Cl
AUXILIARY
0
1
2
2
22
45
83
120
157
196
240
275
312
349
387
427
467
508
550
592
633
673
710
741
768
793
816
836
853
869
884
899
912
Cl
TOTAL
0
1
2
3
197
398
662
912
1,180
1,463
1,770
2,007
2,259
2,524
2,797
3,074
3,354
3,623
3,873
4,099
4,304
4,489
4,649
4,782
4,896
5,000
5,096
5,183
5,262
5,335
5,402
5,466
5,526
C2
PROPULSION
264
538
822
1,116
1,420
1,856
2,177
2,189
2,512
2,922
3,343
3,750
4,170
4,639
5,112
5,587
6,066
6,550
7,041
7,538
8,041
8,549
9,059
9,574
10,090
10,606
11,121
11,631
12,116
12,560
12,975
13,352
13,667
<37KW
0
2
4
5
6
8
9
11
13
15
16
18
20
22
24
26
28
29
31
32
33
33
34
35
35
36
37
37
38
38
39
39
40
TOTAL
264
541
828
1,124
1,623
2,262
2,848
3,112
3,706
4,400
5,130
5,776
6,448
7,185
7,933
8,687
9,447
10,203
10,945
11,670
12,378
13,072
13,743
14,391
15,022
15,642
16,253
16,851
17,416
17,933
18,416
18,857
19,233
5-58
-------
Emission Inventory
Table 3-53 Projected Commercial Marine NOX Emission Reductions (short tons)
YEAR
2008
2009
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
Cl
PROPULSION
0
0
0
0
1,342
3,311
6,944
10,562
17,246
26,061
36,621
47,117
57,522
67,833
78,019
88,051
97,867
107,215
115,946
123,957
131,290
137,676
142,790
146,842
150,228
153,285
156,089
158,671
161,061
163,268
165,314
167,230
169,033
Cl
AUXILIARY
0
0
0
0
121
322
868
1,414
2,051
2,835
3,954
5,071
6,184
7,292
8,397
9,495
10,586
11,667
12,737
13,792
14,829
15,822
16,755
17,592
18,343
19,039
19,659
20,173
20,604
21,004
21,377
21,732
22,069
Cl
TOTAL
0
0
0
0
1,463
3,633
7,812
11,976
19,297
28,896
40,576
52,187
63,705
75,126
86,416
97,546
108,453
118,882
128,683
137,749
146,119
153,498
159,545
164,434
168,571
172,324
175,748
178,844
181,665
184,271
186,692
188,962
191,102
C2
PROPULSION
8,876
16,942
24,204
30,668
36,330
41,685
56,757
65,007
74,303
83,755
93,242
102,778
112,324
121,873
131,448
141,137
150,954
160,800
170,714
180,644
190,636
200,664
211,102
221,882
232,697
243,398
253,972
264,350
274,282
282,393
288,751
294,551
299,914
<37KW
0
0
0
0
0
0
47
94
141
188
235
281
328
374
420
465
510
555
599
643
685
726
764
794
815
835
852
869
884
899
913
926
938
TOTAL
8,876
16,942
24,204
30,668
37,792
45,319
64,616
77,077
93,741
112,839
134,052
155,247
176,357
197,373
218,283
239,149
259,918
280,237
299,996
319,036
337,439
354,888
371,411
387,110
402,084
416,556
430,573
444,063
456,832
467,563
476,356
484,440
491,954
5-59
-------
Regulatory Impact Analysis
Table 3-54 Projected Commercial Marine VOC Emission Reductions (short tons)
YEAR
2008
2009
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
Cl
PROPULSION
0
0
1
1
113
279
564
849
1,187
1,563
1,970
2,374
2,773
3,167
3,555
3,934
4,303
4,639
4,934
5,184
5,397
5,585
5,743
5,876
5,993
6,099
6,197
6,287
6,371
6,449
6,521
6,589
6,654
Cl
AUXILIARY
0
2
3
5
17
40
88
135
185
237
297
356
415
474
532
590
647
704
760
814
867
917
961
998
,029
,058
,084
,107
,128
,147
,166
,183
,200
Cl
TOTAL
0
2
4
6
130
319
652
984
1,372
1,800
2,267
2,730
3,188
3,640
4,087
4,524
4,950
5,343
5,694
5,998
6,264
6,501
6,704
6,874
7,022
7,157
7,281
7,394
7,499
7,596
7,687
7,772
7,854
C2
PROPULSION
0
0
0
0
0
14
166
318
483
697
912
,127
,341
,555
,769
,982
2,195
2,407
2,620
2,831
3,043
3,253
3,462
3,669
3,874
4,076
4,275
4,470
4,657
4,816
4,951
5,076
5,187
<37KW
0
5
11
16
22
27
32
38
43
49
54
59
64
70
75
79
84
89
92
95
97
99
101
103
105
106
108
109
111
112
114
115
116
TOTAL
0
7
14
22
152
359
850
1,339
1,897
2,546
3,232
3,915
4,593
5,265
5,930
6,586
7,229
7,839
8,405
8,924
9,404
9,854
10,267
10,646
11,001
11,339
11,664
11,974
12,267
12,525
12,751
12,963
13,157
5-60
-------
Emission Inventory
Table 3-55 Projected Commercial Marine Air Toxic Emission Reductions (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
0
4
2
0
0
0
0
2015
46
341
169
0
7
O
1
2020
164
1,203
598
2
23
10
3
2030
373
2,742
1,363
4
53
24
6
3.2 Recreational Marine Diesel Engines
This section describes the methodology and presents the resulting baseline and
controlled inventories for recreational marine (pleasure craft) diesel propulsion engines,
including the projected emission reductions from the final rule. These engines are already
subject to existing emission control standards, so the baseline inventories presented here
account for those existing standards. Emissions from any diesel auxiliary engines used on
recreational marine vessels are covered above in the section on engines less than 37 kW or the
section on Category 1 engines, if they are over 37 kW.
3.2.1 General Methodology
The general methodology for calculating recreational marine diesel engine inventories
for HC, CO, NOX, PMio, SO2, VOC, PM2.5, and fuel consumption uses the EPA
NONROAD2005 model with inputs modified to reflect the final standards as well as updated
baseline data.27 Air toxic inventories are not generated by the NONROAD model, so those
are calculated separately. NONROAD separates recreational diesel engines into two basic
categories: inboard and outboard engines. NONROAD also subdivides these by power
range. There are relatively few outboard diesels, and they are all in the 25 - 40 hp range.
The actual calculation methodology used by the NONROAD model is the same as
described above in section 3.1.1 for all other marine diesel engines. Following is a summary
of that.
Equation 3-11 / = (#) x (?) x (l) x (A) x (EF)
where each term is defined as follows:
I = the emission inventory (gram/year)
N = engine population (units)
P = average rated power (kW)
L = load factor (average fraction of rated power used during operation; unitless)
A = engine activity (operating hours/year)
EF = emission factor (gram/kW-hr)
5-61
-------
Regulatory Impact Analysis
Emissions are then converted and reported as short tons/year. In NONROAD the
inputs are expressed in terms of horsepower (hp) instead of kW, and gram/bhp-hr instead of
gram/kW-hr.
Three variables are used to project emissions over time: the engine population growth,
the engine median life/scrappage, and the relative emissions deterioration rate.
Engine Population Growth. Unlike the commercial marine methodology which uses
a compound population growth rate, the NONROAD model uses a linear growth assumption
for recreational diesel engines, which is represented by a set of growth indexes that provide a
ratio of estimation year population relative to the base year population. 28 The growth used
for recreational diesel engines is 3.3 percent per year relative to a 1996 base year; i.e., each
year the population grows by the same number of engines, and that number is 3.3 percent of
the 1996 population.
Engine Median Life (years) and Scrappage. The engine median life defines the
length of time engines remain in service. Engines persist in the population over two median
lives; during the first median life, 50 percent of the engines are scrapped, and over the second,
the remaining 50 percent of the engines are scrapped. Engine median lives also vary by
category. The median life of both inboard and outboard engines is assumed to be 20 years,
but due to the different activities used for these two categories (200 and 150 hours/year,
respectively), the corresponding median life inputs for the model are 1400 and 1050 hours at
full load. The age distribution is defined by the median life and the scrappage algorithm. The
same basic scrappage algorithm is used for recreational and commercial marine diesel
engines.29
Relative Deterioration Rate (percent increase in emission factor/percent median life
expended). A deterioration factor can be applied to the emission factor to account for in-use
deterioration. The deterioration factor varies by age and is calculated as:
Equation 3-12 DF = 1 + A x
ML
where each term is defined as follows:
DF = the deterioration factor for a given pollutant at a given age
A = the relative deterioration rate for a given pollutant (percent increase in emission
factor/percent useful life expended)
age = the age of a specific model year group of engines in the simulation year (years)
ML = the median life of the given model year cohort (years)
A given model year cohort is represented as a fraction of the entire population. In the
NONROAD model the deterioration factor adjusts the emission factor for engines in a given
model year cohort in relation to the proportion of median life expended.30 Deterioration is
linear over one median life. Following the first median life, the deteriorated emission factor is
held constant over the remaining life for engines in the cohort.
5-62
-------
Emission Inventory
Sulfur Adjustment for PM Emissions. For Tier 2 and prior engines, a sulfate
adjustment is added to the PM emissions to account for differences in fuel sulfur content
between the certification fuel and the episodic (calendar year) fuel, using the following
equation:
Equation 3-13 SPM d- = (PC] x (?. l) x (0.0224?) x - x (soxdsl - soxbas] x
PMadj \ ! \ ! \ ) V /
PM d-
PMadj
where each term is defined as follows:
SPM adj = PM sulfate adjustment (tons)
FC = fuel consumption (gallons)
7.1 = fuel density (Ib/gal)
0.02247 = fraction of fuel sulfur converted to sulfate
224/32 = grams PM sulfate/grams PM sulfur
soxdsl = episodic fuel sulfur weight fraction (varies by calendar year)
soxbas = certification fuel sulfur weight fraction
2000 = conversion from Ib to ton
For engines prior to Tier 2 the base fuel sulfur (soxbas) is assumed to be 3300 ppm.
For Tier 2 engines less than or equal to 50 hp (37 kW) it is set at 2000 ppm, as described in
the Clean Air Nonroad Diesel Rule31, since these smaller engines are subject to the same
standards as land-based diesel engines. For Tier 2 engines greater than 50 hp (37 kW) it is set
at 350 ppm, based on the most recent certification data for these engines. For Tier 3 and later
engines, no sulfur adjustment is applied. These engines will be certified to a fuel sulfur level
at or lower than the episodic fuel sulfur levels expected when these engines are introduced.
The calendar year fuel sulfur levels (soxdsl) were taken from the Clean Air Nonroad
Diesel Rule and are provided in Table 3-1.
32
Estimation of air toxic emissions. The air toxic baseline emission inventories for this
proposal are based on information developed for EPA's Mobile Source Air Toxics (MSAT)
final rulemaking.33 That rule calculated air toxic emission inventories for all nonroad
engines. The gaseous air toxics are correlated to VOC emissions, while POM is correlated to
PMio emissions. To calculate the air toxics emission inventories and reductions for this
proposal, the percent reductions in VOC and PMio emissions will be applied to the baseline
gaseous and POM air toxic inventories, respectively.
3.2.2 Baseline (Pre-Control) Inventory Development
3.2.2.1 Baseline Inventory Inputs
This section describes the NONROAD model inputs that were used to generate the
baseline emission inventories for recreational marine diesel engines.
Table 3-56 and Table 3-57 list the base engine populations, average hp by power
range, annual activity, load factor, and median life. These also apply to the control case, and
are unchanged from the default inputs in the NONROAD model.
5-63
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Regulatory Impact Analysis
Table 3-56 Recreational Marine Diesel Modeling Inputs
NONROAD MODEL INPUT
POPULATION (year 2000)
HP AVERAGE
ACTIVITY HRS/YEAR
LOAD FACTOR
MEDIAN LIFE (hrs at full load)
MEDIAN LIFE (years)
RECREATIONAL MARINE DIESEL
INBOARD
291,387*
*
200
0.35
1400
20
OUTBOARD
9,819
32.25
150
0.35
1050
20
* See TABLE 3-57 for breakout by individual power ranges.
Table 3-57 Recreational Marine Inboard Diesel Population
POWER RANGE
MIN < HP <= MAX
0-11
11-16
16-25
25-40
40-50
50-75
75 - 100
100- 175
175-300
300 - 600
600 - 750
750 - 1000
1000 - 1200
1200 - 2000
2000 - 3000
TOTAL
DIESEL REC MARINE INBOARD
HPAVG
9.736
14.92
21.41
31.2
42.4
56.19
94.22
144.9
223.1
387.1
677
876.5
1154
1369
2294
POPULATION
9,126
4,478
9,908
5,421
1,002
8,784
7,397
60,632
99,703
73,546
2,902
5,502
448
1,573
964
291,387
The baseline emission factors are given in Table 3-58 and Table 3-59. "Zero Hour"
emission factors represent the emissions from new engines that have been broken in, but
before any significant deterioration occurs. The Deterioration Factor is used to calculate how
emissions change as the engine and emission control system deteriorate over time, as
explained above in Equation 3-2. Engines under 50 hp are subject to EPA nonroad diesel
regulations that have established two tiers of emission standards.34 Tier 1 phased in from
1999-2000, depending on the hp category, and Tier 2 phased in from 2004-2005. Engines
above 50 hp are subject to separate standards (shown in the Tier 2 column) that take effect in
5-64
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Emission Inventory
2008-2012, depending on hp category. The "Base" entries in the tables refer to emissions
from pre-controlled engines. All these emission factors are used for both inboard and
outboard diesel engines, although the outboards are all under 50 hp.
The emission factors for the base and Tier 1 technology types are unchanged from
what has been in the NONROAD model.35 Tier 2 emission factors were updated from those
in the NONROAD model using all the nonroad engine certification data available in mid-
2006. The deterioration factors by pollutant and technology type are also given in the tables
above, and they are unchanged from what has been in the NONROAD model.36
The certification fuel sulfur levels are 3300ppm for the base and Tier 1 technology
type and 350ppm for Tier 2. Brake Specific Fuel Consumption (BSFC) values in the
NONROAD model are 0.408 Ib/hp-hr for all hp categories.37
Table 3-58 Baseline PM10 and NOX Zero Hour Emission Factors and Deterioration Factors for
Recreational Marine Diesel Engines
HP
RANGE
0-11
11-16
16-25
25-50
50-75
75-100
100-175
175-300
300-600
600-750
750-1200
>1200
DF ("A")
PMio G/HP-HR
BASE
1.00
0.90
0.90
0.80
0.16
0.16
0.16
0.16
0.16
0.16
0.16
0.16
0.473
TIER1
0.45
0.27
0.27
0.34
0.16
0.16
0.16
0.16
0.16
0.16
0.16
0.16
0.473
TIER2
0.38
0.19
0.19
0.23
0.13
0.13
0.13
0.090
0.082
0.082
0.082
0.082
0.473
NOX G/HP-HR
BASE
10.00
8.50
8.50
6.90
6.67
6.67
6.67
6.67
6.67
6.67
6.67
6.67
0.024
TIER1
5.23
4.44
4.44
4.73
6.67
6.67
6.67
6.67
6.67
6.67
6.67
6.67
0.024
TIER2
4.39
3.63
3.63
3.71
3.82
3.82
3.82
4.46
4.42
4.42
4.42
4.42
0.009
5-65
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Regulatory Impact Analysis
Table 3-59 Baseline HC and CO Zero Hour Emission Factors and Deterioration Factors for Recreational
Marine Diesel Engines
HP
RANGE
0-11
11-16
16-25
25-50
50-75
75-100
100-175
175-300
300-600
600-750
750-1200
>1200
DF ("A")
HC G/HP-HR
BASE
1.50
1.70
1.70
1.80
0.22
0.22
0.22
0.22
0.22
0.22
0.22
0.22
0.047
TIER1
0.76
0.44
0.44
0.28
0.22
0.22
0.22
0.22
0.22
0.22
0.22
0.22
0.047
TIER2
0.68
0.21
0.21
0.54
0.20
0.20
0.20
0.25
0.33
0.33
0.33
0.33
0.034
CO G/HP-HR
BASE
5.00
5.00
5.00
5.00
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.185
TIER1
4.11
2.16
2.16
1.53
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.101
TIER2
4.11
2.16
2.16
1.53
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.101
3.2.2.2 Recreational Marine Diesel Baseline Inventory
3.2.2.2.1 PMio, PM25, NOX, VOC, CO, andSO2 Emissions
Table 3-60 shows the baseline 50-state emission inventories for recreational marine
diesel engines (inboard and outboard combined) resulting from the baseline model inputs
presented above.
3.2.2.2.2 Air Toxics Emissions
The baseline air toxics inventories for recreational marine diesel engines were taken
from the final MSAT rule38 and are summarized in Table 3-61. Inventories are provided for
calendar year 1999, and are projected for 2010, 2015, 2020, and 2030.
5-66
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Emission Inventory
Table 3-60 Baseline (50-State) Emissions for Recreational Marine Diesel Engines (short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
,130
,161
,192
,223
,247
,054
915
937
935
938
934
935
952
969
984
998
1,011
1,024
,037
,050
,063
,075
,087
1,099
1,112
1,127
1,143
1,159
1,175
1,192
1,208
1,226
1,243
1,260
1,278
1,295
1,313
1,331
1,349
PM2.5
,096
,126
,156
,186
,210
,023
888
909
907
910
906
907
924
940
954
968
981
994
,006
,019
,031
,043
,054
,066
,079
,093
,108
,124
,140
,156
,172
,189
,205
,222
,239
,256
,274
,291
,308
NOX
40,437
41,572
42,704
43,835
44,089
44,307
44,513
44,648
44,772
44,880
44,977
45,064
45,139
45,208
45,270
45,327
45,378
45,427
45,477
45,531
45,586
45,649
45,729
45,842
46,114
46,549
47,030
47,551
48,102
48,671
49,257
49,861
50,477
51,106
51,748
52,399
53,062
53,735
54,417
voc
1,540
1,578
1,618
1,656
1,720
1,783
1,846
1,912
1,979
2,045
2,112
2,179
2,246
2,313
2,380
2,448
2,516
2,584
2,653
2,723
2,793
2,862
2,932
3,000
3,064
3,124
3,184
3,242
3,299
3,356
3,412
3,468
3,524
3,579
3,634
3,689
3,744
3,798
3,852
HC
,462
,499
,536
,573
,633
,693
,753
,816
,879
,942
2,006
2,069
2,133
2,196
2,260
2,325
2,389
2,454
2,520
2,586
2,652
2,718
2,784
2,849
2,910
2,967
3,023
3,079
3,133
3,187
3,240
3,294
3,346
3,399
3,451
3,503
3,555
3,607
3,659
CO
6,467
6,642
6,816
6,989
7,161
7,331
7,499
7,665
7,829
7,991
8,150
8,308
8,464
8,618
8,771
8,922
9,073
9,223
9,374
9,525
9,675
9,825
9,975
10,124
10,279
10,439
10,601
10,765
10,930
11,095
11,262
11,429
11,596
11,765
11,933
12,102
12,272
12,442
12,613
S02
5,145
5,290
5,436
5,582
5,621
2,967
993
1,017
764
578
311
113
136
150
153
156
156
159
162
165
168
171
174
177
180
183
186
189
192
195
199
202
205
208
211
214
217
220
223
5-67
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Regulatory Impact Analysis
Table 3-61 Baseline Air Toxics Emissions for Recreational Marine Diesel Engines (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
1999
30
176
79
3
5
0
1
2010
34
199
89
3
5
0
0
2015
34
197
88
3
5
0
0
2020
34
195
87
3
5
0
0
2030
35
201
90
3
5
0
0
3.2.3 Control Inventory Development
3.2.3.1 Control Scenario(s) Modeled
Table 3-62 shows the control case exhaust emission standards that were modeled for
recreational marine diesel engines.
Table 3-62 Modeled Standards (g/hp-hr) for Recreational Marine Diesel Engines
HP
RANGE
0-25
25-100
100-175
175-300
300-750
750-1200
>1200
TIER 3
YEAR
2009
2009
2014
2012
2013
2014
2013
2012
NOx+HC
5.6
5.6
3.5
4.3
4.3
4.3
4.3
4.3
PM
0.30
0.22
0.22
0.11
0.10
0.09
0.09
0.08
3.2.3.2 Control Inventory Inputs
Table 3-63 shows the NONROAD model emission factor inputs that were used to
generate the control case emission inventories for recreational marine diesel engines. These
emission factors were applied to engines beginning with the model years shown in Table
3-62. No sulfur adjustment is applied to the Tier 3 PM calculations, since these engines will
be certified to a fuel sulfur level at or lower than the episodic fuel sulfur levels expected when
these engines are introduced
All other modeling inputs are the same as shown above for the base case inventory
development. Table 3-56 and Table 3-57 list the base engine populations, average hp by
5-68
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Emission Inventory
power range, annual activity, load factor, and median life. These are unchanged from the
default inputs in the NONROAD model.
Table 3-63 Control Emission Factors for Recreational Marine Diesel Engines
HP RANGE
0-11
11-16
16-25
25-50
50-75
75-100
100-175
175-300
300-600
600-750
750-1200
>1200
DF ("A")
TIER 3 EMISSION FACTORS
G/HP-HR
PMio
0.24
0.19
0.19
0.18
0.18
0.13
0.13
0.13
0.13
0.088
0.08
0.072
0.072
0.072
0.064
0.473
NOX
4.39
3.63
3.63
3.71
2.32
3.82
2.39
3.82
2.39
3.34
3.9
3.98
3.98
3.98
3.98
0.009
HC
0.43
0.21
0.21
0.41
0.41
0.2
0.2
0.2
0.2
0.13
0.22
0.29
0.29
0.29
0.29
0.034
CO
4.11
2.16
2.16
1.53
1.53
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.95
0.101
3.2.3.3 Recreational Marine Diesel Control Inventory
3.2.3.3.1 PMio, PM25, NOX, VOC, CO, andSO2 Emissions
The control case 50-state emission inventories for recreational marine diesel engines
(inboard and outboard combined) resulting from the control case model inputs presented
above are shown in Table 3-64.
3.2.3.3.2 Air Toxics Emissions
The control case air toxics inventories for recreational marine diesel engines are
provided in Table 3-65. Gaseous air toxics and POM are reduced proportionately to VOC and
PM2.5, respectively.
5-69
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Regulatory Impact Analysis
Table 3-64 Control Case (50-State) Emissions for Recreational Marine Diesel Engines
(short tons)
YEAR
2002
2003
2004
2005
2006
2007
2008
2009
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
PMio
,130
,161
,192
,223
,247
,054
915
937
935
938
931
929
943
956
966
976
986
994
1,003
1,011
1,018
1,025
1,032
1,038
1,046
1,056
1,065
1,075
1,086
1,097
1,108
1,121
1,135
1,149
1,163
1,178
1,193
1,208
1,223
PM2.5
,096
,126
,156
,186
,210
,023
888
909
907
910
903
901
915
927
937
947
956
965
973
981
988
995
,001
,007
,015
,024
,033
,043
,053
,064
,075
,088
,101
,114
,128
,143
,157
,172
,187
NOX
40,437
41,572
42,704
43,835
44,089
44,307
44,513
44,649
44,772
44,880
44,938
44,889
44,724
44,551
44,368
44,178
43,982
43,780
43,579
43,380
43,181
42,989
42,814
42,672
42,688
42,868
43,096
43,364
43,665
43,989
44,343
44,741
45,189
45,672
46,177
46,697
47,234
47,785
48,347
voc
1,540
1,578
1,618
1,656
1,720
1,783
1,846
1,912
1,978
2,044
2,104
2,159
2,206
2,252
2,298
2,345
2,391
2,438
2,486
2,534
2,582
2,629
2,676
2,723
2,765
2,803
2,840
2,877
2,913
2,948
2,985
3,024
3,065
3,108
3,151
3,195
3,239
3,282
3,326
HC
,462
,499
,536
,573
,633
,693
,753
,816
,878
,941
,998
2,051
2,095
2,139
2,183
2,227
2,271
2,316
2,361
2,406
2,452
2,497
2,542
2,586
2,626
2,662
2,697
2,732
2,766
2,800
2,835
2,872
2,911
2,952
2,993
3,034
3,076
3,117
3,159
CO
6,467
6,642
6,816
6,989
7,161
7,331
7,499
7,665
7,829
7,991
8,150
8,308
8,464
8,618
8,771
8,922
9,073
9,223
9,374
9,525
9,675
9,825
9,975
10,124
10,279
10,439
10,601
10,765
10,930
11,095
11,262
11,429
11,596
11,765
11,933
12,102
12,272
12,442
12,613
S02
5,145
5,290
5,436
5,582
5,621
2,967
993
1,017
764
578
311
113
136
150
153
156
156
159
162
165
168
171
174
177
180
183
186
189
192
196
199
202
205
208
211
214
217
220
223
5-70
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Emission Inventory
Table 3-65 Control Case Air Toxic Emissions for Recreational Marine Diesel Engines
(short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
34
198
89
3
5
0
0
2015
33
192
86
3
5
0
0
2020
31
182
82
3
5
0
0
2030
31
178
80
3
5
0
0
3.2.4 Projected Recreational Marine Emission Reductions of Final Rule
The PM2.5, NOX, and VOC emission reductions by calendar year are shown in Table
3-66. The air toxic emission reductions by pollutant and calendar year are given in Table
3-67.
5-71
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Regulatory Impact Analysis
Table 3-66 Projected Recreational Marine Emission Reductions (short tons)
YEAR
2008
2009
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
PM2.5
0
0
0
1
3
5
9
13
17
21
25
29
34
38
43
48
53
59
64
70
75
81
86
92
97
101
105
108
111
114
116
119
122
NOX
0
0
0
0
39
174
415
657
902
1,148
1,397
1,647
1,898
2,151
2,405
2,659
2,915
3,171
3,426
3,681
3,935
4,187
4,437
4,682
4,915
5,120
5,288
5,434
5,570
5,702
5,828
5,951
6,070
voc
0
1
1
2
8
20
40
61
82
103
124
146
167
189
211
233
255
277
299
321
343
365
386
407
427
444
459
471
483
494
505
516
526
5-72
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Emission Inventory
Table 3-67 Projected Air Toxic Reductions from Recreational Marine Diesel Engines (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
0
0
0
0
0
0
0
2015
1
5
2
0
0
0
0
2020
2
12
6
0
0
0
0
2030
4
24
11
0
1
0
0
3.3 Locomotives
3.3.1 General Methodology
Given the quality of the data available, it was possible to develop more detailed
estimates of fleet composition and emission rates. As described in this chapter, detailed data
on fuel consumption, fleet size, and fleet composition were available from industry sources.
Load factors and emission factors were developed in the previous rulemaking. However,
usage and scrappage rates had to be assumed based on less detailed information. These
assumptions were made available to the railroads and the rest of the public in the NPRM, and
we received no information to contradict them. It is important to note that the overall analysis
is much less sensitive to these assumptions than to the estimates of fuel consumption and
emission factors.
Locomotive emissions were calculated based on estimated current and projected fuel
consumption rates. Emissions were calculated separately for the following locomotive
categories:
Large Railroad Line-Haul Locomotives
Large Railroad Switching (including Class III Switch railroads owned by Class I
railroads)
Other Line-Haul Locomotives (such as local railroads)
Other Switch/Terminal Locomotives
Passenger/Commuter Locomotives
We used the following approach for all categories, except for the small railroads (see
3.3.2.3). For each calendar year, locomotives were tracked separately by model year and then
the activity was summed (in terms of work, fuel, and emissions) for all model years in the
fleet. Seven basic steps were used to determine emissions in any calendar year:
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1. Start with the fleet from the previous calendar year.
2. Determine which model years would be due to be remanufactured or scrapped.
3. Update the fleet to remove locomotives that would be scrapped.
4. Determine the amount of work that would be done by the remaining locomotives from the
previous year's fleet.
5. Determine the number of freshly manufactured (i.e., brand new) locomotives that would
be purchased, and add them to the fleet.
6. Determine the total amount of work that would be done by all the locomotives in the fleet.
7. Determine total emissions from the work and brake-specific emission factors.
3.3.1.1 Base Fleet
As is described later, the base fleet was estimated for 2005 from a variety of industry
sources. A new base fleet is calculated for each subsequent calendar year based on the
scrappage rates and sales. The base fleet is a sum of multiple model years that are described
by the number of locomotives in the fleet, the average work that has been accumulated since
the last time it was remanufactured (in megawatt-hours or MW-hr), the average horsepower,
and the Tier of standards to which they are certified.
3.3.1.2 Useful Life
In this analysis, all locomotives are assumed to be either remanufactured or scrapped
when they reach or exceed their useful life. The useful life in MW-hrs is set equal to the rated
horsepower of the locomotive multiplied by 7.5. Thus a 4000 horsepower locomotive would
have a useful life of 30,000 MW-hrs. Annual accumulation of MW-hrs is projected based on
the assumed rated horsepower of the locomotive and the relative use rate (which is a function
of locomotive age). At the end of this second step, the projected fleet is adjusted to reflect a
year's worth of use beyond the previous base fleet.
3.3.1.3 Scrappage
For each future calendar year, there will generally be some locomotive model years
that will be projected to have reached the end of their current useful life. For example, we
estimate that there will be 243 line-haul freight locomotives in use in 2010 that:
Were originally manufactured in model year 1986.
Will be accumulating about 2000 MW-hrs per year.
Will reach the end of their useful lives during 2011.
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According to our scrappage curve, we estimate that 15 of these locomotives will be
scrapped in 2011. The remaining 228 are projected to be remanufactured. We perform this
analysis for each model year, then update that fleet to remove locomotives that would be
scrapped and change the emission levels for locomotives that are remanufactured to new
standards.
3.3.1.4 Work Done by Old Fleet
Once the existing fleet is adjusted for each new calendar year, we determine the
amount of work that would be done by the remaining locomotives from the previous year's
fleet. First we calculate the amount of work done by each model year's fleet as follows:
Equation3-14 Wt = (ff)x (LF)x (#.)x (Pt.)x (RUFJ )
W; = Combined annual work output for all locomotives remaining in the fleet that
were originally manufactured in model year i.
H = Number of hours per year that a newly manufactured locomotive is projected to
be used (approximately 4000 to 5000 hrs/yr).
L = Typical average load factor.
N; = Number of locomotives remaining in the fleet that were originally manufactured
in model year i.
P;= Average rated power of locomotives remaining in the fleet that were originally
manufactured in model year i.
RUF; = Relative use factor for locomotives remaining in the fleet that were originally
manufactured in model year i.
The total work done by the remaining fleet (Wr) is calculated by summing the work
done by each model year (W).
3.3.1.5 New Sales
Sales of freshly manufactured locomotives are projected for each calendar year after
the remaining fleet has been analyzed. These newly manufactured locomotives are added to
the remaining locomotives to comprise a new total fleet. The number is calculated based on
the amount of fuel that is projected to be used in that calendar year:
Equation 3-15 New Sales = (Total Fuel IBSFC - Wr) / HI LF IP
Where BSFC is the estimated brake specific fuel consumption rate (Gal/MW-hr)
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3.3.1.6 Total Work
The total amount of work that would be done by all the locomotives in the fleet is
calculated for each calendar year by summing the work projected to be done by the newly
manufactured locomotives and the work projected to be done by the remaining locomotives.
The total work is calculated separately for each tier of locomotives.
3.3.1.7 Emissions
Emissions are determined from the work calculated in section 3.3.1.6 (converted to
hp-hrs) and brake-specific emission factors:
Equation 3-16 Total Emissions = (Total Work} x (Emission Factor}
The emission factors used are the estimated average in-use emissions for each tier of
standards, which are shown in Table 3-68 and Table 3-69. They take into account
deterioration of emissions throughout the useful life, production variations, and the
compliance margins that manufacturers incorporate into their designs. For this analysis, we
are generally assuming that average in-use emission levels will be 10 percent below the
applicable standards.
Table 3-68 Baseline Line-Haul Emission Factors (g/bhp-hr)
UNCONTROLLED
TIERO
TIER1
TIER2
PMio
0.32
0.32
0.32
0.18
HC
0.48
0.48
0.47
0.26
NOX
13.0
8.60
6.70
4.95
CO
1.28
1.28
1.28
1.28
Table 3-69 Baseline Switch Emission Factors (g/bhp-hr)
UNCONTROLLED
TIERO
TIER1
TIER 2
PM10
0.44
0.44
0.43
0.19
HC
1.01
1.01
1.01
0.51
NOX
17.4
12.6
9.9
7.3
CO
1.83
1.83
1.83
1.83
These PMio emission factors reflect the emission rates expected from locomotives
operating on current in-use fuel with sulfur levels at 3000 ppm. The emission inventories
described in this chapter, however, account for the reductions in sulfate particulate expected
to result from using lower sulfur fuels after 2007. We estimate that the PMio emission rate for
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locomotives operating on nominally 500 ppm sulfur fuel will be 0.05 g/bhp-hr lower than the
PMio emission rate for locomotives operating on 3000 ppm sulfur fuel. Similarly we estimate
that the PMio emission rate for locomotives operating on nominally 15 ppm sulfur fuel will be
0.06 g/bhp-hr lower than the PMio emission rate for locomotives operating on 3000 ppm
sulfur fuel. This is higher than the estimates used for the NPRM because they are based on
newer data.
To estimate VOC emissions, an adjustment factor of 1.053 is applied to the HC
output.39 Similarly, to estimate PM2.5 emissions, an adjustment factor of 0.97 is applied to the
PMio output.40 These adjustment factors are the same as those used for marine engines.
3.3.2 Baseline (Pre-Control) Inventory Development
In developing the baseline inventory, we collected fuel consumption estimates from
the regulated industries, including publicly available estimates for Class I and commuter
railroads. We used the same estimated average in-use emission factors and load factors as we
used in the previous rulemaking.
We are using a projection by the Energy Information Administration (EIA) that
locomotive fuel consumption will grow 1.6 percent annually.41 We are assuming that this
fuel growth applies equally across all categories of locomotives and is directly proportional to
engine work performed by the fleet.
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Table 3-70 Summary of Locomotive Emission Analysis Inputs
2005 FUEL
CONSUMPTION
(GAL/YR)
HOURS USED PER
YEAR WHEN NEW
YEARS AFTER
WHICH USAGE
BEGINS TO
DECLINE
HOURS PER YEAR
AT END OF LIFE
AGE AFTER WHICH
SCRAPPAGE
BEGINS
AGE AFTER WHICH
NO LOCOMOTIVES
REMAIN IN FLEET
LOAD FACTOR
(AVG HP/RATED
HP)
AVG HP-HR/GAL
Large
Line-Haul
3.981
BILLION
4350
8
1740 @ 40
YRS
20
40
0.275
20.8
Large
Switch
315
MILLION
4450
50
3115@70
YRS
50
70
0.100
15.2
Small
Line-Haul
34
MILLION
NA
NA
NA
NA
NA
0.275
18.2
Small
Switch
34
MILLION
NA
NA
NA
NA
NA
0.100
15.2
Passenger/
Commuter
142
MILLION
3900
20
2340@30YRS
20
30
0.275
20.8
3.3.2.1 Large Line-Haul
The large line-haul category includes line-haul freight locomotives that are fully
subject to the standards being final. Class III locomotives that are owned and operated by
railroads that qualify as small businesses are addressed separately, as described in 3.3.2.3.
The large line-haul analysis is based primarily on data collected for Class I and Class II
railroads. However, as described in 3.3.2.3, the total fuel includes one-third of the estimated
Class III fuel use to account for those Class III railroads that do not qualify as small
businesses. The estimate of current Class I total fuel use came from the AAR Railroad Facts
booklet. The estimate of Class II railroad fuel consumption is based on the survey
information provided by the American Shortline Railroad Association for Class II and Class
III railroads. These results had to be adjusted upward to correct for a response rate of
approximately 85 percent. The combined total for Class I and Class II railroads was reduced
by 7 percent to reflect fuel used in switching rather than line-haul operation.
42
The fleet composition for all large railroads was estimated based on a contractor
analysis. The contractor estimated that this fleet included 19,757 locomotives with more than
2500 hp. (Locomotives with 2500 hp or less were assumed to be used primarily in switching
operations.) To be precise, this estimate was intended to reflect the locomotives that were
subject to the Part 92 regulations and thus excluded Class II locomotives owned by small
businesses. An additional 878 locomotives were added to account for the previously excluded
Class II locomotives. Usage and scrappage patterns were developed to fit the fuel use and
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fleet composition data. The average in-use load factor was assumed to be the same as the
load factor for a typical line-haul duty cycle test.
3.3.2.2 Large Switch
We generally used the same approach to calculate switch emissions as we used to
calculate line-haul emissions, but we used different inputs. We also made one change to the
analysis of future sales. We assumed that the majority of growth in switching activity will be
achieved by using switch locomotives more rather than by adding new switch locomotives to
the fleet. More specifically, we assumed that 1.2 percent of the annual 1.6 percent growth in
activity will be achieved by using the existing switchers more, while only 0.4 percent of the
growth will be achieved by increasing the number of switchers in the fleet.
As shown in Table 3-70, we believe that switch locomotives tend to last longer in the
fleet and have a lower in-use load factor than line-haul locomotives. Thus the average age of
switch locomotives is much older than for line-haul. We also estimate that switching
operation will use approximately 7 percent of total large railroad fuel, and will grow at the
same rate as line-haul operation. The switch fleet composition for all large railroads was
estimated based on the same contractor analysis used for the line-haul fleet. The contractor
estimated that this fleet included 5206 locomotives with 2500 hp or less. This included 1645
locomotives with 2250 to 2500 hp. While we recognize that some of these locomotives will
be used in branch service0, for this analysis they are assumed to be used primarily in
switching operations. The FRM analysis includes an additional 66 switch locomotives owned
by previously excluded Class II railroads.
3.3.2.3 Small Railroads
We used a simplified approach for small railroads (that is, railroads that are not
required to retrofit their locomotive with new emission controls because they qualify as
"small railroads" under the regulatory definition). We assume that these small railroads are
unlike the larger railroads in the following ways:
They do not purchase newly manufactured locomotives.
They use their locomotives at a constant rate.
They replace their existing locomotives at a constant rate of 3 percent per year.
Brake-specific PM emissions are 0.03 g/bhp-hr higher for locomotives owned by
small railroads (relative to Class I/II locomotives) because of their higher fuel
consumption rates.
D Branch service includes short-haul operations that would be considered intermediate to intercity line-haul
service and switch service.
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For this analysis, we considered small railroad activity in the same two categories as
the larger railroads: line-haul and switch. For small line-haul operations, we are projecting
that railroads will scrap and replace their oldest locomotives with 25 year-old locomotives
purchased from the larger railroads. Thus, the inventory analysis has these railroads obtaining
Tier 1 locomotives starting in 2026, and Tier 2 locomotives in 2030. For small switch
operations, the railroads are projected to replace their scrapped locomotives with only
uncontrolled or Tier 0 locomotives purchased from the larger railroads. This analysis runs
through 2040 and we consider it unlikely that any significant number of Tier 1 or later switch
locomotives will be available for small railroads before 2040.
The analysis of small railroads is based on the survey information provided by the
American Shortline Railroad Association for Class III railroads. These results had to be
adjusted upward to correct for a response rate of approximately 85 percent. We also had to
adjust these estimates because not all Class III railroads qualify as small railroads under the
regulations. We estimate that one-third of these railroads are owned by Class I railroads or
other large businesses. Finally, we estimated that Class III railroads use 50 percent of their
fuel in switching service. We thus estimate that small Class III railroads used a total of 34
million gallons of diesel fuel in line-haul service in 2005, and 34 million gallons of diesel fuel
in switching service, as shown in Table 3-64.
3.3.2.4 Passenger/Commuter
We used the same approach to calculate passenger and commuter emissions as we
used to calculate large line-haul emissions, but we used different inputs. As shown in Table
3-1, we believe that passenger/commuter locomotives tend to have an average age that is
slightly newer than for line-haul. We used estimates from AMTRAK and APT A for current
fuel consumption rates, and project that these will grow at the same rate as line-haul
operation.
3.3.2.5 Locomotive Baseline Inventory Summary
The baseline locomotive inventory is shown separately for PMio, PM2.5, NOX, VOC,
HC, CO, and SO2 in Table 3-71 through Table 3-77.
The baseline air toxics inventories for locomotives were taken from the MSAT rule
and are provided in Table 3-78. Inventories are provided for calendar years 1999, 2010, 2015,
2020, and 2030.
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Emission Inventory
Table 3-71 Baseline (50-State) PM10 Emissions for Locomotives (short tons)
Calendar
Year
2006
2007
2008
2009
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
Large Line-
haul
28,477
28,401
23,293
23,152
22,989
22,815
22,635
21,759
21,582
21,394
21,193
20,990
20,792
20,593
20,388
20,178
19,964
19,748
19,542
19,332
19,151
18,996
18,868
18,768
18,692
18,645
18,625
18,629
18,662
18,727
18,827
18,953
19,105
19,287
19,497
Large Switch
2,304
2,329
2,071
2,093
2,115
2,137
2,159
2,141
2,163
2,185
2,208
2,231
2,254
2,277
2,301
2,324
2,348
2,353
2,350
2,342
2,329
2,310
2,286
2,260
2,227
2,188
2,143
2,097
2,046
,996
,945
,909
,879
,850
,819
Small
Railroads
492
500
442
449
456
464
471
469
477
484
491
498
505
513
520
528
535
543
551
559
567
575
584
592
597
601
606
610
615
620
624
629
633
638
642
Passenger/
Commuter
1,023
1,011
822
807
793
778
762
723
708
692
676
660
644
628
612
596
581
565
549
533
520
510
501
496
492
489
489
490
493
497
501
505
509
513
517
Total
32,296
32,241
26,629
26,502
26,353
26,193
26,028
25,093
24,930
24,755
24,567
24,379
24,195
24,010
23,821
23,626
23,428
23,209
22,992
22,766
22,567
22,391
22,239
22,115
22,007
21,923
21,863
21,827
21,816
21,840
21,898
21,996
22,127
22,287
22,476
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Regulatory Impact Analysis
Table 3-72 Baseline (50-State) PM2.5 Emissions for Locomotives (short tons)
Calendar
Year
2006
2007
2008
2009
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
Large Line-
haul
27,622
27,549
22,595
22,458
22,300
22,130
21,956
21,107
20,935
20,752
20,557
20,361
20,168
19,975
19,776
19,572
19,365
19,156
18,955
18,752
18,576
18,426
18,302
18,205
18,131
18,086
18,066
18,070
18,102
18,166
18,262
18,384
18,532
18,708
18,913
Large Switch
2,235
2,259
2,009
2,030
2,051
2,073
2,094
2,077
2,098
2,120
2,142
2,164
2,186
2,209
2,232
2,255
2,278
2,282
2,280
2,271
2,259
2,241
2,218
2,192
2,160
2,122
2,079
2,034
1,985
1,936
1,887
1,852
1,823
1,794
1,765
Small
Railroads
478
485
429
436
443
450
457
455
462
469
476
483
490
497
504
512
519
527
534
542
550
558
566
574
579
583
588
592
597
601
605
610
614
619
623
Passenger/
Commuter
992
981
797
783
769
754
740
702
686
671
656
640
625
609
594
578
563
548
533
517
505
494
486
481
477
475
474
476
478
482
486
490
494
498
502
Total
31,327
31,274
25,830
25,707
25,562
25,407
25,247
24,340
24,182
24,012
23,830
23,648
23,469
23,290
23,106
22,917
22,725
22,513
22,302
22,083
21,890
21,719
21,572
21,452
21,347
21,266
21,207
21,172
21,162
21,185
21,241
21,336
21,463
21,619
21,802
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Table 3-73 Baseline (50-State) NOX Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large Line-
haul
802,958
791,683
781,652
775,692
765,957
756,495
751,219
747,643
744,236
740,810
737,040
733,648
730,943
729,027
727,038
725,264
723,450
721,953
720,934
720,243
720,287
720,940
722,270
724,347
727,188
730,771
735,073
740,040
745,745
752,326
759,819
768,001
776,894
786,558
797,012
Large Switch
88,191
89,152
89,244
90,220
90,298
91,286
90,636
91,627
90,873
91,866
91,523
92,522
92,775
93,779
91,309
92,294
91,215
91,400
89,923
87,571
87,376
87,055
86,654
86,197
85,620
84,916
84,125
83,298
82,395
81,507
80,635
80,347
80,345
80,358
80,353
Small
Railroads
18,256
18,548
18,845
19,146
19,453
19,764
20,080
20,402
20,728
20,960
21,195
21,431
21,670
21,851
22,032
22,214
22,396
22,578
22,760
22,942
23,124
23,254
23,383
23,509
23,584
23,656
23,723
23,787
23,847
23,902
23,953
24,000
24,042
24,079
24,111
Passenger/
Commuter
38,466
36,409
34,361
32,338
30,370
28,459
27,212
26,017
24,872
24,382
23,325
22,922
22,559
22,197
21,836
21,477
21,119
20,797
20,510
20,256
20,066
19,935
19,860
19,836
19,859
19,926
20,033
20,160
20,305
20,468
20,631
20,797
20,963
21,131
21,300
Total
947,871
935,793
924,102
917,397
906,078
896,004
889,147
885,689
880,710
878,018
873,083
870,523
867,947
866,854
862,215
861,249
858,178
856,728
854,127
851,012
850,854
851,184
852,167
853,890
856,251
859,269
862,953
867,284
872,292
878,203
885,038
893,145
902,243
912,125
922,775
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Regulatory Impact Analysis
Table 3-74 Baseline (50-State) VOC Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large Line-
haul
44,756
44,595
44,431
44,293
44,122
43,933
43,739
43,560
43,392
43,211
43,010
42,809
42,616
42,425
42,227
42,022
41,813
41,605
41,416
41,226
41,085
40,991
40,942
40,943
41,000
41,107
41,261
41,460
41,708
42,014
42,379
42,791
43,249
43,759
44,321
Large Switch
5,585
5,650
5,730
5,797
5,865
5,934
6,004
6,074
6,146
6,218
6,292
6,366
6,441
6,517
6,595
6,673
6,752
6,790
6,814
6,825
6,829
6,819
6,801
6,777
6,740
6,690
6,630
6,567
6,494
6,423
6,352
6,311
6,285
6,261
6,234
Small
Railroads
928
943
958
973
989
,004
,020
,037
,053
,070
,087
,105
,122
,140
,159
,177
,196
,215
,235
,254
,274
,295
,316
,337
,358
,380
,402
,424
,447
,470
,494
,518
,542
,566
,592
Passenger/
Commuter
1,609
1,589
1,568
1,546
1,523
1,500
1,476
1,453
1,429
1,404
1,380
1,356
1,332
1,307
1,283
1,259
1,235
1,212
1,188
1,165
1,146
1,132
1,121
1,114
1,110
1,109
1,111
1,116
1,123
1,132
1,141
1,150
1,159
1,169
1,178
Total
52,878
52,777
52,685
52,609
52,498
52,371
52,239
52,124
52,020
51,904
51,769
51,635
51,511
51,390
51,263
51,131
50,996
50,822
50,653
50,471
50,335
50,237
50,180
50,170
50,208
50,286
50,405
50,567
50,772
51,038
51,366
51,770
52,236
52,755
53,325
5-84
-------
Emission Inventory
Table 3-75 Baseline (50-State) HC Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large Line-
haul
42,503
42,350
42,194
42,064
41,901
41,722
41,537
41,368
41,208
41,036
40,845
40,654
40,471
40,290
40,101
39,907
39,709
39,511
39,331
39,151
39,017
38,928
38,882
38,882
38,936
39,038
39,184
39,373
39,609
39,899
40,246
40,637
41,072
41,557
42,090
Large Switch
5,304
5,366
5,441
5,505
5,570
5,635
5,701
5,769
5,837
5,905
5,975
6,046
6,117
6,189
6,263
6,337
6,412
6,448
6,471
6,482
6,485
6,476
6,459
6,436
6,401
6,353
6,297
6,236
6,168
6,099
6,032
5,994
5,969
5,946
5,920
Small
Railroads
881
895
909
924
939
954
969
985
1,000
1,016
1,033
1,049
1,066
1,083
1,100
1,118
1,136
1,154
1,172
1,191
1,210
1,230
1,249
1,269
1,290
1,310
1,331
1,352
1,374
1,396
1,418
1,441
1,464
1,488
1,511
Passenger/Co
mmuter
1,528
1,509
1,489
1,468
1,446
1,424
1,402
1,379
1,357
1,334
1,311
1,288
1,265
1,242
1,219
1,196
1,173
1,151
1,129
1,107
1,089
1,075
1,064
1,058
1,054
1,053
1,055
1,060
1,067
1,075
1,084
1,092
1,101
1,110
1,119
Total
50,216
50,121
50,034
49,961
49,856
49,735
49,610
49,500
49,402
49,292
49,163
49,036
48,919
48,804
48,683
48,557
48,430
48,264
48,103
47,931
47,801
47,709
47,654
47,645
47,681
47,755
47,868
48,022
48,217
48,469
48,780
49,164
49,607
50,100
50,641
5-85
-------
Regulatory Impact Analysis
Table 3-76 Baseline (50-State) CO Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
118,701
120,601
122,530
124,491
126,483
128,506
130,562
132,651
134,774
136,930
139,121
141,347
143,609
145,906
148,241
150,613
153,023
155,471
157,958
160,486
163,054
165,662
168,313
171,006
173,742
176,522
179,346
182,216
185,131
188,093
191,103
194,161
197,267
200,423
203,630
Large Switch
9,788
9,944
10,103
10,265
10,429
10,596
10,766
10,938
11,113
11,291
11,472
11,655
11,842
12,031
12,224
12,419
12,618
12,820
13,025
13,233
13,445
13,660
13,879
14,101
14,326
14,555
14,788
15,025
15,265
15,510
15,758
16,010
16,266
16,526
16,791
Small
Railroads
1,863
1,893
1,923
1,954
1,985
2,017
2,049
2,082
2,116
2,149
2,184
2,219
2,254
2,290
2,327
2,364
2,402
2,440
2,480
2,519
2,559
2,600
2,642
2,684
2,727
2,771
2,815
2,860
2,906
2,953
3,000
3,048
3,097
3,146
3,196
Passenger/
Commuter
4,201
4,234
4,268
4,302
4,337
4,371
4,406
4,442
4,477
4,513
4,549
4,585
4,622
4,659
4,696
4,734
4,772
4,810
4,849
4,887
4,926
4,966
5,006
5,046
5,086
5,127
5,168
5,209
5,251
5,293
5,335
5,378
5,421
5,464
5,508
Total
134,553
136,672
138,825
141,012
143,234
145,491
147,784
150,113
152,480
154,884
157,326
159,806
162,327
164,887
167,488
170,130
172,814
175,541
178,311
181,125
183,984
186,889
189,839
192,837
195,882
198,975
202,118
205,310
208,553
211,848
215,196
218,596
222,050
225,560
229,125
5-86
-------
Emission Inventory
Table 3-77 Baseline (50-State) SO2 Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
84,429
85,780
10,168
10,330
10,496
10,664
10,834
315
320
325
330
335
340
346
351
357
363
369
375
380
387
393
399
405
412
419
425
432
439
446
453
460
468
475
483
Large Switch
6,685
6,792
805
818
831
844
858
25
25
26
26
27
27
27
28
28
29
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
38
38
Small
Railroads
1,429
1,452
172
175
178
181
183
5
5
5
6
6
6
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
7
8
8
8
8
8
8
Passenger/
Commuter
2,988
3,012
354
357
360
363
366
11
11
11
11
11
11
11
11
11
11
11
11
12
12
12
12
12
12
12
12
12
12
13
13
13
13
13
13
Total
95,531
97,036
11,499
11,680
11,864
12,051
12,241
355
361
367
372
378
384
390
396
403
409
415
422
429
435
442
449
456
464
471
478
486
494
501
509
517
526
534
542
5-87
-------
Regulatory Impact Analysis
Table 3-78 Baseline (50-State) Air Toxics Emissions for Locomotives (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
1999
92
1,467
640
107
104
58
35
2010
84
1,339
584
98
94
42
25
2015
82
1,318
575
96
93
40
24
2020
80
1,280
558
93
90
38
23
2030
76
1,214
530
88
86
34
20
3.3.3 Control Inventory Development
Control inventories were developed in the same manner as the baseline inventories.
The only change was in the emission factors.
3.3.3.1 Control Scenario Modeled
The final regulations will apply in largely the same manner as the existing program.
Thus, the control scenario can be defined simply by the final standards and the model years
for which they become effective. Two new sets of emission standards are being finalized:
line-haul locomotive standards and switch locomotive standards. The line-haul standards
apply for freight and passenger line-haul locomotives, while the switch standards apply for
freight and passenger switch locomotives. Note; we are not changing the emission standards
for CO.
As in the baseline analysis, average in-use emission factors for the analysis of the final
standards were generally assumed to be 10 percent below the applicable standards, to account
for deterioration of emissions throughout the useful life, production variations, and the
compliance margins that manufacturers incorporate into their designs. The exceptions to this
general rule are the HC emissions for all locomotives and the NOX emissions for Tier 4
locomotives. While we are changing the Tier 3 or earlier HC standards, we expect the
emission controls for PMio will generally achieve proportional reductions in HC. For Tier 4
NOX standards, we expect that manufacturers will need to have lower zero-hour emission rates
to account for potential deterioration and include larger compliance margins (expressed as a
percentage of the standards).
The emission factors used to generate the control case inventories are given in Table
3-79 and Table 3-80.
5-88
-------
Emission Inventory
Table 3-79 Projected Line-Haul Emission Factors with Final Standards
Tier
TIERO
TIER1
TIER 2
TIERS
TIER 4
Initial Model
Year
2008/20 10A
2008/20 10A
2013
2012
2015
NOX
(g/bhp-hr)
7.20
6.70
4.95
4.95
1.00
PM10
(g/bhp-hr)
0.20
0.20
0.08
0.08
0.015
HC
(g/bhp-hr)
0.30
0.29
0.13
0.13
0.04
AThe new Tier 0 standard would apply in 2008 where kits are available, and for all locomotives in 2010.
This is modeled as apply the new Tier 0/1 standards to 660 locomotives in 2008 and 2009.
Table 3-80 Projected Switch Emission Factors with Final Standards
Tier
TIERO
TIER1
TIER 2
TIER 3
TIER 4
Initial Model
Year
2008
2008
2013
2012
2015
NOX
(g/bhp-hr)
10.62
9.90
7.30
5.40
1.00
PMio
(g/bhp-hr)
0.23
0.23
0.11
0.08
0.015
HC
(g/bhp-hr)
0.57
0.57
0.26
0.26
0.08
3.3.3.2 Locomotive Control Inventory Summary
The control locomotive inventory is shown separately for PMio, PM2.5, NOX, VOC,
and HC in Table 3-81 through Table 3-85. See section 3.3.2.5 for CO and SC>2 inventories
which are not projected to change as a result of the final standards.
The control air toxic inventory for locomotives is provided in Table 3-86. The gas
phase air toxics are assumed to be controlled proportionately to VOC, while POM is
controlled proportionately to PM.
5-89
-------
Regulatory Impact Analysis
Table 3-81 Control Case PM10 Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
28,477
28,401
23,287
22,804
22,248
21,234
20,203
18,945
18,313
17,451
16,329
15,214
14,363
13,540
12,938
12,324
11,675
11,016
10,367
9,712
9,091
8,492
7,915
7,363
6,844
6,349
5,879
5,431
5,026
4,653
4,326
4,033
3,775
3,556
3,375
Large Switch
2,304
2,329
2,019
2,039
2,019
2,037
,987
,972
,928
,942
,891
,904
,883
,895
,798
,809
,752
,732
,655
,543
,505
,460
,412
,361
,305
,244
,179
,111
,040
969
897
840
801
761
720
Small
Railroads
492
500
442
449
456
464
471
469
477
481
485
490
494
498
502
507
511
515
520
524
528
533
537
542
543
544
545
546
547
547
548
548
549
549
549
Passenger/
Commuter
1,023
1,011
822
807
774
741
701
647
611
574
532
490
448
407
375
350
325
300
275
250
227
207
188
172
157
144
132
121
111
101
93
86
81
76
72
Total
32,296
32,241
26,569
26,100
25,498
24,476
23,362
22,034
21,329
20,448
19,237
18,097
17,188
16,341
15,613
14,990
14,263
13,563
12,817
12,029
11,351
10,692
10,053
9,438
8,849
8,281
7,735
7,209
6,723
6,270
5,864
5,508
5,205
4,941
4,717
5-90
-------
Emission Inventory
Table 3-82 Control Case PM2.5 Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
27,622
27,549
22,588
22,120
21,580
20,597
19,597
18,377
17,764
16,928
15,839
14,757
13,933
13,134
12,550
11,954
11,325
10,685
10,056
9,421
8,818
8,237
7,678
7,143
6,638
6,159
5,703
5,268
4,875
4,513
4,196
3,912
3,662
3,449
3,274
Large Switch
2,235
2,259
,958
,978
,959
,976
,928
,913
,870
,883
,835
,847
,826
,838
,744
,755
,700
,680
,606
,497
,459
,416
,370
,320
,266
,207
,143
,078
,009
940
871
815
111
738
698
Small
Railroads
478
485
429
436
443
450
457
455
462
467
471
475
479
483
487
492
496
500
504
508
513
517
521
525
526
528
529
529
530
531
532
532
532
533
533
Passenger/
Commuter
992
981
797
783
751
718
680
628
593
557
516
475
435
395
364
340
315
291
266
242
220
200
183
167
153
140
128
117
107
98
91
84
78
74
70
Total
31,327
31,274
25,772
25,317
24,733
23,741
22,661
21,373
20,689
19,835
18,660
17,554
16,673
15,850
15,145
14,540
13,835
13,156
12,433
11,668
11,010
10,371
9,751
9,155
8,584
8,033
7,503
6,993
6,521
6,082
5,689
5,342
5,049
4,793
4,575
5-91
-------
Regulatory Impact Analysis
Table 3-83 Control Case NOX Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
802,958
791,683
777,326
769,265
748,176
719,947
706,002
691,886
685,692
664,161
634,126
604,818
584,819
566,469
548,958
531,295
512,821
490,714
468,890
446,847
425,402
404,319
383,636
363,473
344,049
326,929
310,357
294,261
279,046
264,662
251,877
240,339
230,075
221,180
213,678
Large Switch
88,191
89,152
88,424
89,386
88,920
89,750
88,058
88,873
87,106
87,722
86,130
86,724
86,169
86,754
82,365
82,893
80,480
79,595
76,258
71,540
69,917
68,040
65,996
63,825
61,413
58,747
55,897
52,957
49,854
46,750
43,649
41,172
39,498
37,824
36,091
Small
Railroads
18,256
18,548
18,845
19,146
19,453
19,764
20,080
20,402
20,728
20,929
21,131
21,334
21,538
21,636
21,732
21,825
21,915
22,003
22,089
22,171
22,250
22,313
22,372
22,427
22,428
22,423
22,413
22,396
22,374
22,344
22,308
22,266
22,216
22,159
22,094
Passenger/
Commuter
38,466
36,409
34,361
32,338
29,845
27,408
25,933
24,545
23,239
22,225
20,406
19,264
18,185
17,127
16,351
15,591
14,833
14,074
13,316
12,558
11,833
11,182
10,555
9,948
9,355
8,775
8,204
7,641
7,082
6,527
6,048
5,623
5,270
4,986
4,765
Total
947,871
935,793
918,955
910,135
886,393
856,869
840,074
825,706
816,764
795,037
761,792
732,140
710,710
691,985
669,405
651,605
630,049
606,387
580,553
553,116
529,401
505,853
482,558
459,673
437,245
416,875
396,872
377,256
358,355
340,282
323,882
309,400
297,059
286,149
276,629
5-92
-------
Emission Inventory
Table 3-84 Control Case VOC Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
44,756
44,595
43,784
42,751
41,527
39,032
36,485
34,151
32,533
30,731
28,146
25,595
23,874
22,241
21,372
20,495
19,568
18,629
17,708
16,780
15,904
15,061
14,252
13,481
12,758
12,074
11,427
10,812
10,264
9,764
9,332
8,952
8,624
8,353
8,141
Large Switch
5,585
5,650
5,574
5,639
5,572
5,624
5,455
5,505
5,347
5,386
5,207
5,244
5,164
5,200
4,861
4,892
4,691
4,637
4,387
3,999
3,889
3,767
3,636
3,499
3,366
3,220
3,065
2,905
2,738
2,570
2,404
2,274
2,193
2,112
2,029
Small
Railroads
928
943
958
973
989
1,004
1,020
1,037
1,053
1,070
,087
,105
,122
,140
,159
,177
,196
,215
,235
,254
,274
,295
,316
,337
,358
,380
,402
,424
,447
,470
,494
,518
,542
,566
,592
Passenger/
Commuter
1,609
1,589
1,568
1,546
1,470
1,395
1,299
1,205
1,114
1,032
933
837
742
648
582
542
503
463
423
384
348
317
288
263
240
219
200
184
168
154
142
131
123
115
110
Total
52,878
52,777
51,884
50,909
49,558
47,055
44,259
41,898
40,048
38,218
35,374
32,781
30,902
29,229
27,974
27,107
25,958
24,944
23,752
22,416
21,416
20,440
19,492
18,580
17,722
16,892
16,093
15,325
14,617
13,959
13,371
12,875
12,481
12,147
11,871
5-93
-------
Regulatory Impact Analysis
Table 3-85 Control Case HC Emissions for Locomotives (short tons)
Calendar Year
2006
2007
2008
2009
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
Large
Line-haul
42,503
42,350
41,581
40,600
39,437
37,067
34,648
32,432
30,896
29,184
26,729
24,307
22,672
21,121
20,297
19,464
18,583
17,691
16,817
15,935
15,104
14,303
13,535
12,803
12,116
11,466
10,851
10,268
9,747
9,273
8,862
8,501
8,190
7,933
7,731
Large Switch
5,304
5,366
5,293
5,355
5,291
5,341
5,180
5,228
5,077
5,114
4,945
4,980
4,904
4,938
4,616
4,646
4,455
4,404
4,166
3,797
3,694
3,578
3,453
3,323
3,196
3,058
2,910
2,759
2,600
2,441
2,283
2,160
2,083
2,006
1,926
Small
Railroads
881
895
909
924
939
954
969
985
1,000
,016
,033
,049
,066
,083
,100
,118
,136
,154
,172
,191
,210
,230
,249
,269
,290
,310
,331
,352
,374
,396
,418
,441
,464
,488
,511
Passenger/
Commuter
1,528
1,509
1,489
1,468
1,396
1,325
1,233
1,144
1,058
980
886
795
704
615
553
515
477
440
402
364
330
301
274
249
228
208
190
174
160
146
135
125
116
110
104
Total
50,216
50,121
49,272
48,347
47,064
44,687
42,031
39,789
38,032
36,295
33,593
31,131
29,346
27,757
26,566
25,743
24,652
23,688
22,557
21,288
20,338
19,411
18,511
17,644
16,830
16,042
15,283
14,554
13,881
13,256
12,698
12,227
11,853
11,536
11,273
5-94
-------
Emission Inventory
Table 3-86 Control Case Air Toxic Emissions for Locomotives (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
79
1,264
551
92
89
40
25
2015
61
971
424
71
69
30
20
2020
44
698
305
51
49
21
15
2030
27
429
187
31
30
12
8
3.3.4 Projected Locomotive Emission Reductions from the Final Rule
The projected emission reductions for PM 2.5, NOX and VOC for each category of
locomotives and calendar year are given in Table 3-87 through Table 3-89. Table 3-90
presents the air toxic emission reductions.
5-95
-------
Regulatory Impact Analysis
Table 3-87 Projected Locomotive PM2.5 Emission Reductions (short tons)
Calendar Year
2008
2009
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
Large
Line-haul
6
338
719
1,533
2,360
2,730
3,171
3,825
4,718
5,603
6,235
6,841
7,226
7,618
8,040
8,470
8,899
9,331
9,758
10,189
10,624
11,062
11,493
11,927
12,363
12,802
13,227
13,652
14,067
14,473
14,870
15,259
15,638
Large Switch
51
52
93
96
167
164
228
236
307
317
360
370
488
500
578
603
674
775
800
824
848
872
894
915
936
956
976
996
1,016
1,037
1,046
1,056
1,066
Small
Railroads
0
0
0
0
0
0
0
o
J
5
8
11
14
17
20
23
27
30
34
37
41
45
49
52
56
59
63
66
70
74
78
82
86
90
Passenger/
Commuter
0
0
18
36
60
74
93
114
140
165
190
214
230
239
248
257
266
275
285
294
304
314
324
335
347
359
371
384
395
406
416
424
432
Total
58
390
830
1,666
2,586
2,967
3,492
4,178
5,170
6,094
6,796
7,439
7,961
8,377
8,890
9,357
9,869
10,415
10,880
11,348
11,821
12,297
12,764
13,233
13,705
14,180
14,640
15,102
15,552
15,993
16,414
16,826
17,227
5-96
-------
Emission Inventory
Table 3-88 Projected Locomotive NOX Emission Reductions (short tons)
Calendar Year
2008
2009
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
Large
Line-haul
4,327
6,428
17,781
36,548
45,217
55,757
58,545
76,649
102,915
128,830
146,125
162,559
178,080
193,969
210,629
231,239
252,043
273,396
294,886
316,621
338,635
360,874
383,139
403,841
424,715
445,778
466,699
487,665
507,942
527,662
546,818
565,378
583,334
Large Switch
820
834
1,378
1,535
2,578
2,754
3,767
4,144
5,393
5,798
6,605
7,025
8,944
9,401
10,734
11,805
13,665
16,030
17,460
19,015
20,659
22,372
24,207
26,169
28,228
30,341
32,542
34,757
36,986
39,175
40,847
42,533
44,261
Small
Railroads
0
0
0
0
0
0
0
31
64
97
132
215
301
389
480
574
671
771
873
941
,011
,083
,157
,232
,310
,391
,473
,558
,645
,734
,826
,920
2,017
Passenger/
Commuter
0
0
526
1,051
1,278
1,472
1,634
2,157
2,919
3,658
4,374
5,071
5,486
5,885
6,286
6,723
7,195
7,699
8,233
8,753
9,305
9,888
10,504
11,151
11,828
12,519
13,223
13,941
14,584
15,173
15,693
16,145
16,534
Total
5,147
7,261
19,684
39,135
49,073
59,983
63,946
82,981
111,291
138,383
157,237
174,869
192,811
209,644
228,129
250,341
273,574
297,895
321,452
345,331
369,609
394,217
419,006
442,394
466,082
490,029
513,937
537,920
561,156
583,744
605,184
625,976
646,146
5-97
-------
Regulatory Impact Analysis
Table 3-89 Projected Locomotive VOC Emission Reductions (short tons)
Calendar Year
2008
2009
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
Large
Line-haul
638
1,477
2,476
4,727
7,002
9,102
10,527
12,054
14,349
16,617
18,078
19,468
20,122
20,778
21,480
22,194
22,908
23,629
24,346
25,077
25,819
26,570
27,329
28,099
28,878
29,667
30,439
31,220
31,992
32,759
33,521
34,276
35,026
Large Switch
143
144
279
296
534
554
784
817
,067
,104
,259
,299
,714
,760
2,040
2,126
2,395
2,780
2,887
2,993
3,100
3,207
3,297
3,387
3,477
3,566
3,656
3,745
3,835
3,926
4,016
4,107
4,198
Small
Railroads
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Passenger/
Commuter
0
0
52
105
175
242
307
359
428
495
561
625
661
674
687
699
713
726
740
754
770
786
803
822
841
861
882
904
924
943
960
976
990
Total
802
1,700
2,940
5,316
7,980
10,226
11,972
13,686
16,395
18,855
20,610
22,162
23,289
24,024
25,038
25,878
26,900
28,055
28,919
29,797
30,688
31,590
32,486
33,393
34,312
35,242
36,156
37,080
37,994
38,895
39,755
40,608
41,454
Table 3-90 Projected Locomotive Air Toxic Emission Reductions (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3 -BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
5
75
33
5
5
2
1
2015
22
348
152
25
25
11
4
2020
36
581
254
42
41
17
8
2030
49
786
343
57
55
22
12
5-98
-------
Emission Inventory
3.4 Projected Total Emission Reductions from the Final Rule
The total base and control inventories, as well as emission reductions by calendar year,
for PM2.5, NOX, and VOC are given in Table 3-91. The totals include emissions from the
three major categories affected by this final rule: commercial marine diesel engines,
recreational marine diesel engines, and locomotives. The results for PM2 5 and NOX are also
illustrated in Figure 1 and Figure 2. Reductions by pollutant and category are also provided in
Table 3-92 through Table 3-94.
The total air toxics reductions are provided in Table 3-95.
Calendar year 2040 was chosen as the end date for the analysis; however, additional
reductions are expected to occur beyond this date.
Figure 1 Estimated PM2.5 Reductions from Locomotive and Marine Diesel Engine Standards (short tons)
70,000
60,000 -
50,000 -
40,000 - -
30,000 -
20,000 -
10,000 --
Base 50-State
Control 50-State
2005 2010
2015
2020
2025
2030 2035
2040
5-99
-------
Regulatory Impact Analysis
Figure 2 Estimated NOx Reductions from Locomotive and Marine Diesel Engine Standards (short tons)
2,000,000
1,800,000 -
2005 2010
2015 2020 2025 2030 2035
2040
5-100
-------
Emission Inventory
Table 3-91 Total Emissions and Projected Reductions (short tons)
Year
2006
2007
2008
2009
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
PM25
Base
62,797
60,893
54,082
53,942
53,579
53,233
52,810
51,572
49,750
48,296
47,879
47,381
47,002
46,620
46,348
46,266
46,213
46,141
46,070
46,006
45,981
45,993
46,042
46,130
46,247
46,395
46,572
46,781
47,016
47,285
47,591
47,937
48,318
48,729
49,168
Control
62,797
60,893
53,760
53,011
51,921
50,443
48,598
46,338
43,400
40,993
38,986
36,867
35,052
33,376
31,905
30,666
29,347
28,049
26,700
25,330
24,092
22,905
21,768
20,681
19,654
18,679
17,749
16,858
16,017
15,224
14,512
13,896
13,371
12,927
12,586
Reduction
0
0
322
931
1,658
2,790
4,212
5,234
6,350
7,303
8,893
10,514
11,951
13,245
14,443
15,600
16,866
18,092
19,370
20,676
21,889
23,087
24,274
25,449
26,593
27,716
28,823
29,923
30,999
32,061
33,079
34,040
34,947
35,802
36,582
NOX
Base
1,812,229
1,787,163
1,762,615
1,743,151
1,719,287
1,696,911
1,678,040
1,663,297
1,647,759
1,634,987
1,620,503
1,609,712
1,600,291
1,593,148
1,583,847
1,579,669
1,574,245
1,571,689
1,569,185
1,566,788
1,567,997
1,570,259
1,573,643
1,578,219
1,584,378
1,592,027
1,600,710
1,610,338
1,620,871
1,632,511
1,645,247
1,659,436
1,674,792
1,691,093
1,708,303
Control
1,812,229
1,787,163
1,748,592
1,718,947
1,675,398
1,627,108
1,591,136
1,557,820
1,518,782
1,474,272
1,414,569
1,357,341
1,307,606
1,261,385
1,212,782
1,170,501
1,125,428
1,079,540
1,032,778
985,485
943,123
902,211
862,660
824,927
789,523
757,840
727,630
698,634
671,073
645,094
621,689
602,427
587,424
574,726
564,133
Reduction
0
0
14,023
24,204
43,889
69,803
86,904
105,476
128,976
160,715
205,934
252,371
292,686
331,763
371,065
409,167
448,817
492,149
536,407
581,303
624,875
668,048
710,983
753,292
794,855
834,186
873,080
911,704
949,798
987,417
1,023,558
1,057,009
1,087,368
1,116,367
1,144,170
voc
Base
71,875
71,699
71,535
71,391
71,218
71,032
70,846
70,683
70,539
70,392
70,243
70,131
70,061
70,011
69,988
69,991
70,007
69,994
69,996
69,994
70,041
70,128
70,262
70,447
70,685
70,966
71,293
71,666
72,084
72,564
73,107
73,728
74,413
75,152
75,943
Control
71,875
71,699
70,733
69,684
68,262
65,692
62,707
60,078
57,677
55,306
51,869
48,628
46,095
43,788
41,938
40,513
38,828
37,297
35,612
33,823
32,417
31,086
29,827
28,638
27,546
26,520
25,553
24,640
23,806
23,039
22,363
21,814
21,402
21,066
20,806
Reduction
0
0
802
1,708
2,956
5,340
8,139
10,605
12,862
15,086
18,374
21,504
23,966
26,223
28,049
29,478
31,179
32,697
34,384
36,171
37,624
39,042
40,435
41,809
43,140
44,447
45,739
47,025
48,278
49,525
50,744
51,914
53,011
54,087
55,137
5-101
-------
Regulatory Impact Analysis
Table 3-92 Projected Total PM2.S Emission Reductions (short tons)
YEAR
2008
2009
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
COMMERCIAL
MARINE
264
541
828
1,124
1,623
2,262
2,848
3,112
3,706
4,400
5,130
5,776
6,448
7,185
7,933
8,687
9,447
10,203
10,945
11,670
12,378
13,072
13,743
14,391
15,022
15,642
16,253
16,851
17,416
17,933
18,416
18,857
19,233
RECREATIONAL
MARINE
0
0
0
1
3
5
9
13
17
21
25
29
34
38
43
48
53
59
64
70
75
81
86
92
97
101
105
108
111
114
116
119
122
LOCOMOTIVES
58
390
830
1,666
2,586
2,967
3,492
4,178
5,170
6,094
6,796
7,439
7,961
8,377
8,890
9,357
9,869
10,415
10,880
11,348
11,821
12,297
12,764
13,233
13,705
14,180
14,640
15,102
15,552
15,993
16,414
16,826
17,227
TOTAL
322
931
1,658
2,790
4,212
5,234
6,350
7,303
8,893
10,514
11,951
13,245
14,443
15,600
16,866
18,092
19,370
20,676
21,889
23,087
24,274
25,449
26,593
27,716
28,823
29,923
30,999
32,061
33,079
34,040
34,947
35,802
36,582
5-102
-------
Emission Inventory
Table 3-93 Projected Total NOX Emission Reductions (short tons)
YEAR
2008
2009
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
COMMERCIAL
MARINE
8,876
16,942
24,204
30,668
37,792
45,319
64,616
77,077
93,741
112,839
134,052
155,247
176,357
197,373
218,283
239,149
259,918
280,237
299,996
319,036
337,439
354,888
371,411
387,110
402,084
416,556
430,573
444,063
456,832
467,563
476,356
484,440
491,954
RECREATIONAL
MARINE
0
0
0
0
39
174
415
657
902
1,148
1,397
1,647
1,898
2,151
2,405
2,659
2,915
3,171
3,426
3,681
3,935
4,187
4,437
4,682
4,915
5,120
5,288
5,434
5,570
5,702
5,828
5,951
6,070
LOCOMOTIVES
5,147
7,261
19,684
39,135
49,073
59,983
63,946
82,981
111,291
138,383
157,237
174,869
192,811
209,644
228,129
250,341
273,574
297,895
321,452
345,331
369,609
394,217
419,006
442,394
466,082
490,029
513,937
537,920
561,156
583,744
605,184
625,976
646,146
TOTAL
14,023
24,204
43,889
69,803
86,904
105,476
128,976
160,715
205,934
252,371
292,686
331,763
371,065
409,167
448,817
492,149
536,407
581,303
624,875
668,048
710,983
753,292
794,855
834,186
873,080
911,704
949,798
987,417
1,023,558
1,057,009
1,087,368
1,116,367
1,144,170
5-103
-------
Regulatory Impact Analysis
Table 3-94 Projected Total VOC Emission Reductions (short tons)
YEAR
2008
2009
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
COMMERCIAL
MARINE
8,876
16,942
24,204
30,668
37,792
45,319
64,616
77,077
93,741
112,839
134,052
155,247
176,357
197,373
218,283
239,149
259,918
280,237
299,996
319,036
337,439
354,888
371,411
387,110
402,084
416,556
430,573
444,063
456,832
467,563
476,356
484,440
491,954
RECREATIONAL
MARINE
0
0
0
0
39
174
415
657
902
1,148
1,397
1,647
1,898
2,151
2,405
2,659
2,915
3,171
3,426
3,681
3,935
4,187
4,437
4,682
4,915
5,120
5,288
5,434
5,570
5,702
5,828
5,951
6,070
LOCOMOTIVES
5,147
7,261
19,684
39,135
49,073
59,983
63,946
82,981
111,291
138,383
157,237
174,869
192,811
209,644
228,129
250,341
273,574
297,895
321,452
345,331
369,609
394,217
419,006
442,394
466,082
490,029
513,937
537,920
561,156
583,744
605,184
625,976
646,146
TOTAL
14,023
24,204
43,889
69,803
86,904
105,476
128,976
160,715
205,934
252,371
292,686
331,763
371,065
409,167
448,817
492,149
536,407
581,303
624,875
668,048
710,983
753,292
794,855
834,186
873,080
911,704
949,798
987,417
1,023,558
1,057,009
1,087,368
1,116,367
1,144,170
5-104
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Emission Inventory
Table 3-95 Projected Total Air Toxic Emission Reductions (short tons)
HAP
BENZENE
FORMALDEHYDE
ACETALDEHYDE
1,3-BUTADIENE
ACROLEIN
NAPHTHALENE
POM
2010
5
79
35
5
5
2
1
2015
69
693
323
26
31
14
5
2020
202
1,796
857
44
65
28
11
2030
426
3,551
1,716
62
109
45
18
3.5 Contribution of Marine Diesel Engines and Locomotives to Baseline
National Emission Inventories
This section provides the contribution of marine diesel engines and locomotives to
baseline nationwide emission inventories in 2001, 2020, and 2030. The baseline represents
current and future emissions with the existing standards. The calendar years correspond to
those chosen for the air quality modeling.
The pollutants included in this section are directly emitted PM 2.5, NOX, VOC, CO, and
SO2. While we do not provide estimates for other pollutants here, it should be noted that the
affected engines also contribute to national ammonia (NH3) and air toxics inventories.
3.5.1 Categories and Sources of Data
As described more fully earlier in this chapter, our current inventories for marine
diesel engines and locomotives were developed using multiple methodologies, but they all are
based on combining engine populations, hours of use, average engine loads, and in-use
emissions factors. Locomotive emissions were calculated based on estimated current and
projected fuel consumption rates. Emissions were calculated separately for the following
locomotive categories: Large Railroad Line-Haul Locomotives, Large Railroad Switching
(including Class III Switch railroads owned by Class I railroads), Other Line-Haul
Locomotives (i.e., local railroads), Other Switcher/Terminal Locomotives and Passenger
Locomotives. The inventories for marine diesel engines were created separately for Category
1 and 2 propulsion and auxiliary engines, including those less than or equal to 37 kW, and
diesel fueled recreational marine propulsion engines.
The locomotive, commercial marine (Cl & C2), and diesel recreational marine values
given for 2001 are actually 2002 estimates, since that is the base year that was used for air
quality modeling. The stationary, aircraft, onroad diesel, and C3 commercial marine values
are from the PM NAAQS 2001 air quality modeling platform, which is more recent than, but
essentially the same as CAIR (2001 platform) for these sources. The 2030 stationary source
values are set equal to 2020, since no specific estimates for 2030 stationary source emissions
are available. All the stationary source values exclude "non-manmade" sources, such as fires
and fugitive dust. Onroad gasoline vehicle values are from the National Mobile Inventory
5-105
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Regulatory Impact Analysis
Model (NMIM) outputs for the final Mobile Source Air Toxics rulemaking, which includes
the assumed implementation of Renewable Fuels Standards (RFS) and corrections for cold-
start HC effects. Nonroad land-based diesel values are from the latest publicly released
version of EPA's nonroad model (NONROAD2005a). Nonroad spark-ignition (SI) values in
these tables (small SI, SI recreational marine, large SI, and SI recreational vehicles) are also
from NONROAD2005a. The NONROAD2005 model runs were all done at the
nationwide/annual level using single default nationwide temperature & RVP and the full 50-
state equipment population including all California equipment.
3.5.2 PM2.5 Contributions to Baseline
Table 3-96 provides the contribution of locomotives and diesel-fueled recreational and
commercial marine engines to mobile source diesel and to total man-made PM2.5 emissions.
PM2.5 emissions from these sources are 18 percent of the mobile source diesel PM2.5
emissions in 2001, and this percentage increases to about 65 percent by 2030. PM2.5 emissions
from the affected sources decreases from almost 60,000 tons in 2002 to 46,000 tons in 2020
due to the existing emission standards. From 2020 to 2025 emissions remain relatively
constant as growth offsets the effect of continued turnover of older engines to engines
meeting the existing emission standards. These emissions begin to increase again around 2025
and exceed 2015 levels by 2035.
3.5.3 NOX Contributions to Baseline
Table 3-97 provides the contribution of locomotives and diesel-fueled recreational and
commercial marine engines to mobile source NOX and to total man-made NOX emissions.
NOX emissions from these sources are 16 percent of the mobile source NOX emissions in
2001, and this percentage increases to 35 percent by 2030. NOX emissions from affected
sources decrease from about 2 million tons in 2002 to almost 1.6 million tons in 2020 due to
the existing emission standards. From 2020 to 2025 emissions remain relatively constant as
growth offsets the effect of continued turnover of older engines to engines meeting the
existing emission standards. These emissions begin to increase again in 2025 and by 2035
exceed 2015 emission levels.
3.5.4 VOC Contributions to Baseline
Table 3-98 provides the contribution of locomotives and diesel-fueled recreational and
commercial marine engines to mobile source VOC and to total man-made VOC emissions.
Due to the efficient combustion in diesel engines, mobile source VOC emissions are
dominated by spark-ignition engines, and the VOC emissions from the affected sources are
only 0.8 percent of the mobile source VOC in 2001, increasing to 1.3 percent by 2030. VOC
emissions from affected sources increase from 69,000 tons in 2002 to 70,000 tons in 2020 and
71,000 tons in 2030, since the existing emission standards are not aimed at controlling VOC.
3.5.5 CO Contributions to Baseline
Table 3-99 provides the contribution of locomotives and diesel-fueled recreational and
commercial marine engines to mobile source carbon monoxide (CO) and to total man-made
5-106
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Emission Inventory
CO emissions. As with VOC, mobile source CO emissions are dominated by spark-ignition
engines, so the CO emissions from the affected sources are only 0.3 percent of the mobile
source CO in 2001, increasing to 0.5 percent by 2030. CO emissions from affected sources
increase from 281,000 tons in 2002 to 317,000 tons in 2020 and 350,000 tons in 2030, since
the existing emission standards are not aimed at controlling CO.
3.5.6 SO2 Contributions to Baseline
Table 3-100 provides the contribution of locomotives and diesel-fueled recreational
and commercial marine engines to mobile source SO2 and to total man-made SO2 emissions.
SO2 emissions from these sources are 21 percent of the mobile source SO2 emissions in 2001,
and this percentage decreases significantly to about one percent in 2020 and 2030 due to
existing diesel fuel sulfur standards. SO2 emissions from affected sources decrease from
162,000 tons in 2002 to 3,700 tons in 2020. From 2020 to 2030 emissions increase to 4,200
tons due to continued projected growth in these sectors.
5-107
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Regulatory Impact Analysis
Table 3-96 50-State Annual PM 2.s Baseline Emission Levels for Mobile and Other Source Categories
Category
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Commercial Marine (C3)
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 Diesel (distillate) Mobile
Total Mobile Sources
Stationary Point and Area
Sources
Total Man-Made Sources
2001a
short tons
29,660
1,096
28,730
164,180
20,023
25,575
17,101
12,301
1,610
5,664
305,941
109,952
50,277
160,229
333,619
466,170
1,963,264
2,429,434
%of
diesel
mobile
8.9%
0.3%
8.6%
49.2%
-
33.0%
100%
%of
total
1.2%
0.0%
1.2%
6.8%
0.8%
1.1%
0.7%
0.5%
0.1%
0.2%
12.6%
4.5%
2.1%
6.6%
13.7%
19.2%
80.8%
100%
2020
short tons
23,106
1,006
22,236
46,075
36,141
31,083
6,595
11,773
2,421
7,044
187,480
15,800
47,354
63,154
108,223
250,634
1,817,722
2,068,356
%of
diesel
mobile
21.4%
0.9%
20.5%
42.6%
-
14.6%
100%
%of
total
1.1%
0.0%
1.1%
2.2%
1.7%
1.5%
0.3%
0.6%
0.1%
0.3%
9.1%
0.8%
2.3%
3.1%
5.2%
12.1%
87.9%
100%
2030
short tons
21,347
1,140
23,760
17,934
52,682
35,761
6,378
9,953
2,844
8,569
180,368
10,072
56,734
66,806
74,253
247,174
1,817,722
2,064,896
%of
diesel
mobile
28.7%
1.5%
32.0%
24.2%
-
13.6%
100%
%of
total
1.0%
0.1%
1.2%
0.9%
2.6%
1.7%
0.3%
0.5%
0.1%
0.4%
8.7%
0.5%
2.7%
3.2%
3.6%
12.0%
88.0%
100%
Notes:
a The locomotive, commercial marine (Cl & C2), and diesel recreational marine estimates are for calendar year 2002.
going vessels.
5-108
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Emission Inventory
Table 3-97 50-State Annual NOX Baseline Emission Levels for Mobile and Other Source Categories
Category
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Commercial Marine (C3)
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 Diesel (distillate) Mobile
Total Mobile Sources
Stationary Point and Area
Sources
Total Man-Made Sources
2001ฐ
short tons
1,118,786
40,437
834,025
1,548,236
224,100
100,319
42,252
5,488
321,098
83,764
4,318,505
3,750,886
4,354,430
8,105,316
7,292,308
12,423,821
9,355,659
21,779,480
%of
mobile
source
9.0%
0.3%
6.7%
12.5%
1.8%
0.8%
0.3%
0.0%
2.6%
0.7%
34.8%
30.2%
35.0%
65.2%
58.7%
100%
-
-
%of
total
5.1%
0.2%
3.8%
7.1%
1.0%
0.5%
0.2%
0.0%
1.5%
0.4%
19.8%
17.2%
20.0%
37.2%
33.5%
57.0%
43.0%
100%
2020
short tons
862,215
45,477
676,154
678,377
369,160
98,620
83,312
17,496
46,319
105,133
2,982,264
646,961
1,361,276
2,008,237
2,907,578
4,990,501
6,111,866
11,102,367
%of
mobile
source
17.3%
0.9%
13.5%
13.6%
7.4%
2.0%
1.7%
0.4%
0.9%
2.1%
59.8%
13.0%
27.3%
40.2%
58.3%
100%
-
-
%of
total
7.8%
0.4%
6.1%
6.1%
3.3%
0.9%
0.8%
0.2%
0.4%
0.9%
26.9%
5.8%
12.3%
18.1%
26.2%
44.9%
55.1%
100%
2030
short tons
856,251
48,102
680,025
434,466
531,641
114,287
92,188
20,136
46,253
118,740
2,942,089
260,915
1,289,780
1,550,695
2,277,735
4,492,784
6,111,866
10,604,650
%of
mobile
source
19.1%
1.1%
15.1%
9.7%
11.8%
2.5%
2.1%
0.4%
1.0%
2.6%
65.5%
5.8%
28.7%
34.5%
50.7%
100%
-
-
%of
total
8.1%
0.5%
6.4%
4.1%
5.0%
1.1%
0.9%
0.2%
0.4%
1.1%
27.7%
2.5%
12.2%
14.6%
21.5%
42.4%
57.6%
100%
Notes:
a The locomotive, commercial marine (Cl & C2), and diesel recreational marine estimates are for calendar year 2002.
going vessels.
5-109
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Regulatory Impact Analysis
Table 3-98 50-State Annual VOC Baseline Emission Levels for Mobile and Other Source Categories
Category
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Commercial Marine (C3)
Small Nonroad SI
Recreational Marine SI
SI Recreational Vehicles
Large Nonroad SI (>25hp)
Portable Fuel Containers
Aircraft
Total Off Highway
Highway Diesel
Highway non-diesel
Total Highway
Total Diesel (distillate) Mobile
Total Mobile Sources
Stationary Point and Area
Sources
Total Man-Made Sources
2001ฐ
short tons
50,665
1,540
17,229
188,884
9,572
1,314,015
1,212,446
512,059
132,888
244,545
22,084
3,705,926
223,519
4,316,615
4,540,134
479,285
8,246,060
9,692,344
17,938,404
%of
mobile
source
0.6%
0.0%
0.2%
2.3%
0.1%
15.9%
14.7%
6.2%
1.6%
3.0%
0.3%
44.9%
2.7%
52.3%
55.1%
5.8%
100%
-
-
%of
total
0.3%
0.0%
0.1%
1.1%
0.1%
7.3%
6.8%
2.9%
0.7%
1.4%
0.1%
20.7%
1.2%
24.1%
25.3%
2.7%
46.0%
54.0%
100%
2020
short tons
51,263
2,653
16,071
76,047
18,458
999,810
688,774
454,979
12,429
254,479
27,644
2,602,608
123,449
2,646,363
2,769,812
270,844
5,372,420
8,475,443
13,847,863
%of
mobile
source
1.0%
0.0%
0.3%
1.4%
0.3%
18.6%
12.8%
8.5%
0.2%
4.7%
0.5%
48.4%
2.3%
49.3%
51.6%
5.0%
100%
-
-
%of
total
0.4%
0.0%
0.1%
0.5%
0.1%
7.2%
5.0%
3.3%
0.1%
1.8%
0.2%
18.8%
0.9%
19.1%
20.0%
2.0%
38.8%
61.2%
100%
2030
short tons
50,208
3,299
17,178
63,144
27,582
1,156,408
697,712
391,541
10,276
288,630
30,331
2,736,309
138,758
2,987,562
3,126,320
274,189
5,862,629
8,475,443
14,338,072
%of
mobile
source
0.9%
0.1%
0.3%
1.1%
0.5%
19.7%
11.9%
6.7%
0.2%
4.9%
0.5%
46.7%
2.4%
51.0%
53.3%
4.7%
100%
-
-
%of
total
0.4%
0.0%
0.1%
0.4%
0.2%
8.1%
4.9%
2.7%
0.1%
2.0%
0.2%
19.1%
1.0%
20.8%
21.8%
1.9%
40.9%
59.1%
100%
Notes:
a The locomotive, commercial marine (Cl & C2), and diesel recreational marine estimates are for calendar year 2002.
going vessels.
5-110
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Emission Inventory
Table 3-99 50-State Annual CO Baseline Emission Levels for Mobile and Other Source Categories
Category
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Commercial Marine (C3)
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 Diesel (distillate) Mobile
Total Mobile Sources
Stationary Point and Area
Sources
Total Man-Made Sources
2001ฐ
short tons
123,210
6,467
151,331
893,320
19,391
18,843,914
2,816,005
1,229,707
1,801,679
263,232
26,148,256
1,098,213
60,985,008
62,083,221
2,272,530
88,231,477
9,014,249
97,245,726
%of
mobile
source
0.1%
0.0%
0.2%
1.0%
0.0%
21.4%
3.2%
1.4%
2.0%
0.3%
29.6%
1.2%
69.1%
70.4%
2.6%
100%
-
-
%of
total
0.1%
0.0%
0.2%
0.9%
0.0%
19.4%
2.9%
1.3%
1.9%
0.3%
26.9%
1.1%
62.7%
63.8%
2.3%
90.7%
9.3%
100%
2020
short tons
167,488
9,374
139,712
310,258
37,459
27,269,797
2,136,234
1,922,020
304,532
327,720
32,624,593
248,689
32,503,404
32,752,093
877,583
65,376,686
8,641,678
74,018,364
%of
mobile
source
0.3%
0.0%
0.2%
0.5%
0.1%
41.7%
3.3%
2.9%
0.5%
0.5%
49.9%
0.4%
49.7%
50.1%
1.3%
100%
-
-
%of
total
0.2%
0.0%
0.2%
0.4%
0.1%
36.8%
2.9%
2.6%
0.4%
0.4%
44.1%
0.3%
43.9%
44.2%
1.2%
88.3%
11.7%
100%
2030
short tons
195,882
10,930
143,791
155,625
56,713
31,623,016
2,178,413
1,902,925
281,993
358,012
36,907,299
149,784
37,399,211
37,548,995
658,428
74,456,294
8,641,678
83,097,972
%of
mobile
source
0.3%
0.0%
0.2%
0.2%
0.1%
42.5%
2.9%
2.6%
0.4%
0.5%
49.6%
0.2%
50.2%
50.4%
0.9%
100%
-
-
%of
total
0.2%
0.0%
0.2%
0.2%
0.1%
38.1%
2.6%
2.3%
0.3%
0.4%
44.4%
0.2%
45.0%
45.2%
0.8%
89.6%
10.4%
100%
Notes:
a The locomotive, commercial marine (Cl & C2),
This category includes emissions from Category
going vessels.
and diesel recreational marine estimates are for calendar year 2002.
3 (C3) propulsion engines and C2/3 auxiliary engines used on ocean-
5-111
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Regulatory Impact Analysis
Table 3-100 50-State Annual SO2 Baseline Emission Levels for Mobile and Other Source Categories
Category
Locomotive
Recreational Marine Diesel
Commercial Marine (Cl & C2)
Land-Based Nonroad Diesel
Commercial Marine (C3)
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 Diesel (distillate) Mobile
Total Mobile Sources
Stationary Point and Area
Sources
Total Man-Made Sources
2001ฐ
short tons
76,727
5,145
80,353
167,615
166,739
6,723
2,755
1,241
925
7,890
516,113
103,632
169,125
272,757
433,465
788,870
15,057,420
15,846,290
%of
mobile
source
9.7%
0.7%
10.2%
21.2%
21.1%
0.9%
0.3%
0.2%
0.1%
1.0%
65.4%
13.1%
21.4%
34.6%
54.9%
100%
-
-
%of
total
0.5%
0.0%
0.5%
1.1%
1.1%
0.0%
0.0%
0.0%
0.0%
0.0%
3.3%
0.7%
1.1%
1.7%
2.7%
5.0%
95.0%
100%
2020
short tons
396
162
3,104
999
272,535
8,620
2,980
2,643
905
9,907
302,251
3,443
35,195
38,638
8,108
340,889
8,215,016
8,555,905
%of
mobile
source
0.1%
0.0%
0.9%
0.3%
79.9%
2.5%
0.9%
0.8%
0.3%
2.9%
88.7%
1.0%
10.3%
11.3%
2.4%
100%
-
-
%of
total
0.0%
0.0%
0.0%
0.0%
3.2%
0.1%
0.0%
0.0%
0.0%
0.1%
3.5%
0.0%
0.4%
0.5%
0.1%
4.0%
96.0%
100%
2030
short tons
464
192
3,586
1,078
400,329
9,990
3,160
2,784
1,020
11,137
433,741
4,453
42,709
47,162
9,777
480,903
8,215,016
8,695,919
%of
mobile
source
0.1%
0.0%
0.7%
0.2%
83.2%
2.1%
0.7%
0.6%
0.2%
2.3%
90.2%
0.9%
8.9%
9.8%
2.0%
100%
-
-
%of
total
0.0%
0.0%
0.0%
0.0%
4.6%
0.1%
0.0%
0.0%
0.0%
0.1%
5.0%
0.1%
0.5%
0.5%
0.1%
5.5%
94.5%
100%
Notes:
3 The locomotive, commercial marine (Cl & C2), and diesel recreational marine estimates are for calendar year 2002.
This category includes emissions from Category 3 (C3) propulsion engines and C2/3 auxiliary engines used on ocean-
going vessels.
3.6 Contribution of Marine Diesel Engines and Locomotives to Non-
Attainment Area Emission Inventories
Table 3-101 and Table 3-102 show the percent contribution to mobile source diesel
PM2.5 and total mobile source NOX for certain non-attainment areas where there are large rail
yards and/or commercial marine ports. The county-level inventories were estimated by
allocating the nationwide baseline inventories to the counties using the same county:national
ratios as used in the 2002 National Emissions Inventory (NEI).43 It can be seen that
locomotives and diesel marine vessels make up a substantial portion of the PM2.5 and NOX
mobile source inventories in these areas. For instance, the combination of rail and
commercial marine activity in the Huntington-Ashland WV-KY-OH area yields a
contribution over 50% of mobile source diesel PM2.5 in 2002, increasing to 90% in 2030.
Additional details, including the annual tons of PM2.5 and NOx from locomotives,
diesel marine engines, and all mobile sources within each of the counties of these
metropolitan areas are provided in Appendix 3 A of this chapter.
5-112
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Emission Inventory
Table 3-101 Locomotive and Diesel Marine Engine Contributions to Non-Attainment Area Mobile Source
Diesel PM2.5 Emissions
PM2 5 Metropolitan Area
Huntington-Ashland WV-KY-OH
Houston, TX
Los Angeles, CA
Cleveland-Akron-Lorain, OH
Chicago, IL
Cincinnati, OH
Chattanooga, TN
Kansas City, MO
Baltimore, MD
St. Louis, MO
Philadelphia, PA
Seattle, WA
Birmingham, AL
Minneapolis-St. Paul, MN
Boston, MA
San Joaquin Valley, CA
Atlanta, GA
Indianapolis, IN
Phoenix-Mesa, AZ
Detroit, MI
New York, NY
2002
LM%
52.9%
41.9%
31.3%
25.1%
24.6%
23.2%
21.1%
20.6%
22.5%
21.4%
19.6%
17.0%
16.3%
10.7%
7.8%
8.8%
5.2%
5.0%
4.9%
4.1%
3.5%
2020
LM%
82.1%
72.9%
49.3%
56.0%
54.9%
53.6%
56.3%
51.3%
52.6%
51.3%
47.0%
43.3%
46.6%
31.3%
22.9%
19.4%
19.6%
17.5%
17.3%
15.3%
11.1%
2030
LM%
90.4%
84.6%
72.1%
72.0%
70.0%
69.5%
69.5%
68.0%
67.8%
67.5%
63.9%
60.4%
57.5%
47.8%
40.5%
38.2%
29.9%
29.3%
26.8%
26.0%
20.3%
5-113
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Regulatory Impact Analysis
Table 3-102 Locomotive and Diesel Marine Engine Contributions to Non-Attainment Area Total Mobile
Source NOX Emissions
NOx Metropolitan Area
Houston, TX
Kansas City, MO
Birmingham, AL
Chicago, IL
Cleveland-Akron-Lorain, OH
Chattanooga, TN
Cincinnati, OH
Los Angeles, CA
St. Louis, MO
Huntington- Ashland WV-KY-OH
Seattle, WA
San Joaquin Valley, CA
Minneapolis-St. Paul, MN
Philadelphia, PA
Phoenix-Mesa, AZ
Atlanta, GA
Indianapolis, IN
Boston, MA
Baltimore, MD
Detroit, MI
New York, NY
2002
LM%
31.5%
19.3%
16.7%
19.9%
18.8%
15.6%
17.5%
18.1%
15.7%
38.1%
13.2%
8.4%
8.1%
13.4%
5.1%
4.2%
4.3%
6.3%
7.1%
2.8%
4.7%
2020
LM%
46.3%
39.3%
38.3%
37.8%
37.2%
35.7%
35.7%
30.8%
33.8%
41.9%
27.7%
16.0%
17.5%
19.7%
11.7%
10.7%
10.7%
10.6%
10.4%
7.2%
7.4%
2030
LM%
44.8%
43.2%
42.6%
41.1%
39.5%
39.1%
38.3%
37.2%
36.9%
36.2%
30.3%
25.7%
19.4%
18.8%
14.6%
12.8%
12.7%
10.8%
9.7%
8.2%
7.3%
5-114
-------
Emission Inventory
3.7 Emission Inventories Used for Air Quality Modeling
3.7.1 Comparison of Air Quality and Final Rule Inventories
This section describes the differences in the inventories used for the final rule air
quality analysis and the inventories used for the final rule. Chapter 2 of this document
discusses the air quality analysis results and addresses the likely impact of these differences
(if any) on the air quality outcomes from the final rule.
For the commercial marine vessel and diesel recreational marine categories affected
by this rule, the baseline inventories for the air quality analysis are unchanged from those
used for the final rule. For the diesel locomotive category, minor changes have been made to
the baseline inventories. Minor changes to the control case have also been made for all three
categories since the air quality analysis; these changes are described in this section.
In addition to the diesel locomotive, commercial marine vessel, and diesel recreational
marine sources, the air quality inventories include emission contributions from all sources,
including the following sources not directly affected by the final rule:
Stationary and area sources
Aircraft
Oceangoing commercial marine vessels (Category 3)
Onroad (highway) mobile sources
Nonroad mobile sources other than diesel pleasure craft
The emission inventory estimates used in the air quality analysis for these sources are
those included in the 2002-based CMAQ modeling platform. In comparison, the inventory
estimates presented in section 3.5 were taken from the recent Clean Air Interstate Rule
(CAIR)44.
5-115
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Regulatory Impact Analysis
Table 3-103 through Table 3-105 summarize the differences between the air quality
inventories and the final rule inventories for baseline VOC, NOX, and PM2 5. Similarly, Table
3-106 through Table 3-108 summarize the differences between the air quality inventories and
the final rule inventories for control case VOC, NOX, and PM2.5. Lastly, Table 3-109 through
Table 3-111 summarize the differences in ton reductions for these pollutants between the air
quality inventories and the more updated final rule inventories. Only the years 2020 and 2030
are shown for the latter two sets of tables, since this rule has no benefits prior to 2008.
3.7.2 Locomotive Inventory Changes
Since the air quality analysis, changes were made to the baseline inputs, primarily to
more accurately account for PM sulfate reductions from reduced future fuel sulfur levels. In
addition, changes have been made in the control case to include all Class II railroads, exclude
small businesses, and accelerate the Tier 4 NOx standard for the line-haul category. The net
effect of these updates in 2030 is roughly a 4 percent increase in VOC and NOX tons reduced
and a 10 percent decrease in PM2.5 tons reduced.
3.7.3 Marine Diesel Inventory Changes
Since the air quality analysis, changes have been made to expand the remanufacturing
program requirements for Category 1 engines to include Tier 2 engines. Also, a 12 percent
reduction in benefits for the remanufacturing program, affecting both Category 1 and
Category 2 engines, was applied to account for the small business exclusion. For Category 2
engines, the Tier 3 and Tier 4 standards for the 2000-3700 kW category have been revised.
These changes collectively affect NOX, PM, and VOC emissions for the control case
beginning in 2008.
Since the air quality analysis, the Tier 4 NOx and PM standards affecting 2000 hp and
greater recreational marine engines have been eliminated. In addition, there have been minor
changes to the Tier 3 NOx + HC and PM standards for engines greater than 1200 hp.
There was also an error applying the PM sulfur adjustment factor for recreational
marine engines, which only affects the 2020 and 2030 baseline PM emissions used in the air
quality analysis.
The net effect of these updates for marine diesel engines in 2030 is a 3 percent
decrease in VOC tons reduced, a 2 percent increase in NOX tons reduced, and a 9 percent
increase in PM2.s tons reduced.
5-116
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Emission Inventory
Table 3-103 50-State Annual VOC Baseline Emission Levels for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE &
STATIONARY)
TOTAL MAN-MADE
SOURCES
2002
AQ
MODELING
50,665
18,839
16,917,345
16,986,849
FRM*
50,665
18,768
17,868,970
17,938,403
% DIFF
0.0%
-0.4%
5.6%
5.6%
2020
AQ
MODELING
52,634
18,927
12,415,007
12,486,568
FRM
51,263
18,724
13,777,876
13,847,864
% DIFF
-2.6%
-1.1%
11.0%
10.9%
2030
AQ
MODELING
51,813
20,780
12,330,869
12,403,462
FRM
50,208
20,477
14,267,387
14,338,072
% DIFF
-3.1%
-1.5%
15.7%
15.6%
* THE FRM VALUE FOR ALL OTHER SOURCES IN THE "2002" COLUMN IS ACTUALLY A 2001 ESTIMATE.
Table 3-104 50-State Annual NOX Baseline Emission Levels for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE &
STATIONARY)
TOTAL MAN-MADE
SOURCES
2002
AQ
MODELING
1,118,788
868,315
18,820,689
20,807,792
FRM*
1,118,786
874,462
19,786,232
21,779,480
% DIFF
0.0%
0.7%
5.1%
4.7%
2020
AQ
MODELING
860,463
717,259
9,198,907
10,776,629
FRM
862,215
721,632
9,518,521
11,102,368
% DIFF
0.2%
0.6%
3.5%
3.0%
2030
AQ
MODELING
854,238
724,061
8,722,491
10,300,790
FRM
856,251
728,127
9,020,273
10,604,651
% DIFF
0.2%
0.6%
3.4%
2.9%
* THE FRM VALUE FOR ALL OTHER SOURCES IN THE "2002" COLUMN IS ACTUALLY A 2001 ESTIMATE.
Table 3-105 50-State Annual PM2.5 Baseline Emission Levels for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE &
STATIONARY)
TOTAL MAN-MADE
SOURCES
2002
AQ
MODELING
29,214
29,184
2,228,545
2,286,943
FRM*
29,660
29,827
2,369,947
2,429,434
% DIFF
1.5%
2.2%
6.3%
6.2%
2020
AQ
MODELING
25,901
22,300
2,066,257
2,114,458
FRM
23,106
23,242
2,022,009
2,068,357
% DIFF
-10.8%
4.2%
-2. 1%
-2.2%
2030
AQ
MODELING
24,726
23,674
2,062,331
2,110,731
FRM
21,347
24,900
2,018,649
2,064,896
%
DIFF
-13.7%
5.2%
-2.1%
-2.2%
* THE FRM VALUE FOR ALL OTHER SOURCES IN THE "2002" COLUMN IS ACTUALLY A 2001 ESTIMATE.
5-117
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Regulatory Impact Analysis
Table 3-106 50-State Annual VOC Control Case Emission Levels for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE & STATIONARY)
TOTAL MAN-MADE
SOURCES
2020
AQ
MODELING
30,135
13,991
12,415,007
12,459,133
FRM
27,974
13,964
13,777,876
13,819,814
% DIFF
-7.2%
-0.2%
11.0%
10.9%
2030
AQ
MODELING
20,383
9,800
12,330,869
12,361,052
FRM
17,722
9,824
14,267,387
14,294,933
% DIFF
-13.1%
0.2%
15.7%
15.6%
Table 3-107 50-State Annual NOX Control Case Emission Levels for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE & STATIONARY)
TOTAL MAN-MADE
SOURCES
2020
AQ
MODELING
712,492
543,668
9,198,907
10,455,067
FRM
669,405
543,377
9,518,521
10,731,303
% DIFF
-6.0%
-0.1%
3.5%
2.6%
2030
AQ
MODELING
453,651
354,310
8,722,491
9,530,452
FRM
437,245
352,279
9,020,273
9,809,796
% DIFF
-3.6%
-0.6%
3.4%
2.9%
Table 3-108 50-State Annual PM2.S Control Case Emission Levels for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE & STATIONARY)
TOTAL MAN-MADE
SOURCES
2020
AQ
MODELING
16,368
16,767
2,066,257
2,099,392
FRM
15,145
16,760
2,022,009
2,053,914
% DIFF
-7.5%
0.0%
-2.1%
-2.2%
2030
AQ
MODELING
10,512
10,997
2,062,331
2,083,840
FRM
8,584
11,071
2,018,649
2,038,303
% DIFF
-18.3%
0.7%
-2.1%
-2.2%
5-118
-------
Emission Inventory
Table 3-109 50-State Annual VOC Ton Reductions for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE & STATIONARY)
TOTAL MAN-MADE
SOURCES
2020
AQ
MODELING
22,499
4,936
0
27,435
FRM
23,289
4,760
0
28,049
% DIFF
3.5%
-3.6%
0.0%
2.2%
2030
AQ
MODELING
31,430
10,980
0
42,410
FRM
32,486
10,653
0
43,140
% DIFF
3.4%
-3.0%
0.0%
1.7%
Table 3-110 50-State Annual NOX Ton Reductions for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE & STATIONARY)
TOTAL MAN-MADE
SOURCES
2020
AQ
MODELING
147,971
173,591
0
321,562
FRM
192,811
178,255
0
371,065
% DIFF
30.3%
2.7%
0.0%
15.4%
2030
AQ
MODELING
400,587
369,751
0
770,338
FRM
419,006
375,848
0
794,855
% DIFF
4.6%
1.6%
0.0%
3.2%
Table 3-111 50-State Annual PM2 5 Ton Reductions for Mobile and Other Source Categories
CATEGORY
LOCOMOTIVE
MARINE DIESEL
ALL OTHER SOURCES
(MOBILE & STATIONARY)
TOTAL MAN-MADE
SOURCES
2020
AQ
MODELING
9,533
5,533
0
15,066
FRM
7,961
6,482
0
14,443
% DIFF
-16.5%
17.2%
0.0%
-4.1%
2030
AQ
MODELING
14,214
12,677
0
26,891
FRM
12,764
13,829
0
26,593
% DIFF
-10.2%
9.1%
0.0%
-1.1%
5-119
-------
Regulatory Impact Analysis
APPENDIX 3A
Locomotive and Diesel Marine Contributions to County-Specific Mobile Source
Emissions in Non-attainment Areas
5-120
-------
Emission Inventory
Table 3-112 2002 Locomotive and Diesel Marine PM2.5 Tons/Year and Percent of Total Diesel Mobile
Sources
FIPS
13013
13015
13045
13057
13063
13067
13077
13089
13097
13113
13117
13121
13135
13139
13149
13151
13217
13223
13237
13247
13255
13297
24003
24005
24013
24025
24027
24510
1073
1117
1127
9007
25001
25005
25007
25009
25019
25021
25023
25025
25027
33011
MSA
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Birmingham
Birmingham
Birmingham
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
County
Barrow
Bartow
Carroll
Cherokee
Clayton
Cobb
Coweta
DeKalb
Douglas
Fayette
Forsyth
Fulton
Gwinnett
Hall
Heard
Henry
Newton
Paulding
Putnam
Rockdale
Spalding
Walton
Anne Arundel
Baltimore
Carroll
Harford
Howard
Baltimore
Jefferson
Shelby
Walker
Middlesex
Barnstable
Bristol
Dukes
Essex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Hillsborough
ST
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
MD
MD
MD
MD
MD
MD
AL
AL
AL
CT
MA
MA
MA
MA
MA
MA
MA
MA
MA
NH
2002 PM2.5
Diesel
Locomotive
5.77
20.64
5.65
0.00
10.87
28.66
14.35
13.29
5.22
3.71
0.00
39.07
9.95
6.62
0.00
14.63
1.65
12.13
0.35
2.35
0.62
1.99
14.68
39.65
6.14
11.40
17.07
46.07
80.24
41.96
17.15
0.00
7.23
13.57
0.00
17.74
0.00
21.42
11.20
11.57
43.94
1.33
Diesel
Marine
0.01
0.20
0.08
0.19
0.03
0.08
0.06
0.05
0.01
0.04
0.39
0.11
0.07
0.65
0.09
0.04
0.05
0.03
0.30
0.03
0.03
0.01
1.82
1.22
0.04
1.18
0.41
313.45
1.08
0.29
1.08
1.70
20.34
14.82
133.61
4.90
19.79
6.80
4.99
57.64
1.04
0.42
Total
Diesel
Mobile
41
109
92
118
164
504
123
440
68
86
114
857
476
146
11
154
80
86
15
71
53
47
302
576
158
186
203
590
631
157
81
114
179
311
143
424
29
460
256
2,518
556
266
LM
Percent
14.3%
19.1%
6.2%
0.2%
6.7%
5.7%
1 1 .8%
3.0%
7.7%
4.4%
0.3%
4.6%
2.1%
5.0%
0.8%
9.5%
2.1%
14.2%
4.3%
3.4%
1 .2%
4.2%
5.5%
7.1%
3.9%
6.8%
8.6%
60.9%
12.9%
26.9%
22.4%
1 .5%
15.4%
9.1%
93.4%
5.3%
67.4%
6.1%
6.3%
2.7%
8.1%
0.7%
5-121
-------
Regulatory Impact Analysis
FIPS
33015
47065
47115
47153
13047
13083
13295
17031
17043
17063
17089
17093
17097
17111
17197
18089
18127
18029
21015
21037
21117
39017
39025
39061
39165
39007
39035
39085
39093
39103
39133
39153
26093
26099
26115
26125
26147
26161
26163
48039
48071
48157
48167
48201
48291
MSA
Boston
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Houston
Houston
Houston
Houston
Houston
Houston
County
Rockingham
Hamilton
Marion
Sequatchie
Catoosa
Dade
Walker
Cook
DuPage
Grundy
Kane
Kendall
Lake
McHenry
Will
Lake
Porter
Dearborn
Boone
Campbell
Kenton
Butler
Clermont
Hamilton
Warren
Ashtabula
Cuyahoga
Lake
Lorain
Medina
Portage
Summit
Livingston
Macomb
Monroe
Oakland
St. Clair
Washtenaw
Wayne
Brazoria
Chambers
Fort Bend
Galveston
Harris
Liberty
ST
NH
TN
TN
TN
GA
GA
GA
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
KY
KY
KY
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
Ml
Ml
Ml
Ml
Ml
Ml
Ml
TX
TX
TX
TX
TX
TX
2002 PM2.5
Diesel
Locomotive
1.00
40.53
5.67
0.00
12.28
11.66
0.00
708.71
200.17
13.55
70.19
8.97
37.26
20.29
186.94
129.22
45.64
6.21
8.45
16.05
30.93
45.48
1.96
44.25
6.75
30.49
83.10
21.22
50.28
15.82
31.34
25.49
2.47
3.83
18.09
15.09
7.39
4.04
29.94
18.79
1.07
26.30
13.07
68.97
28.79
Diesel
Marine
36.02
29.56
5.70
0.00
0.01
0.00
0.01
209.67
0.14
6.45
0.10
0.01
22.02
0.16
4.74
14.34
12.55
22.72
34.08
23.57
11.78
0.05
44.98
133.23
0.09
178.56
122.90
26.15
113.72
0.06
0.24
0.17
0.07
5.35
8.90
4.59
21.37
0.05
10.03
247.18
7.41
0.09
566.43
1,477.09
3.02
Total
Diesel
Mobile
263
283
63
7
52
46
48
3,661
812
114
371
78
406
189
498
541
216
92
133
95
147
279
181
737
192
310
1,119
190
414
166
198
392
174
437
198
781
224
269
1,140
463
57
270
751
3,940
112
LM
Percent
14.1%
24.7%
18.1%
0.0%
23.6%
25.3%
0.0%
25.1%
24.7%
17.6%
19.0%
1 1 .5%
14.6%
10.8%
38.5%
26.5%
26.9%
31.3%
31 .9%
41 .5%
29.1%
16.3%
25.9%
24.1%
3.6%
67.4%
18.4%
25.0%
39.6%
9.6%
15.9%
6.5%
1 .5%
2.1%
13.6%
2.5%
12.8%
1 .5%
3.5%
57.4%
14.8%
9.8%
77.1%
39.2%
28.3%
5-122
-------
Emission Inventory
FIPS
48339
48473
21019
21127
39001
39053
39087
39145
54011
54053
54099
18011
18057
18059
18063
18081
18095
18097
18109
18145
20091
20103
20121
20209
29037
29047
29049
29095
29107
29165
29177
6037
6059
6065
6071
6111
27003
27019
27037
27053
27123
27139
27163
9001
MSA
Houston
Houston
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
New York
County
Montgomery
Waller
Boyd
Lawrence
Adams
Gallia
Lawrence
Scioto
Cabell
Mason
Wayne
Boone
Hamilton
Hancock
Hend ricks
Johnson
Madison
Marion
Morgan
Shelby
Johnson
Leave nworth
Miami
Wyandotte
Cass
Clay
Clinton
Jackson
Lafayette
Platte
Ray
Los Angeles
Orange
Riverside
San
Bernardino
Ventura
Anoka
Carver
Dakota
Hennepin
Ramsey
Scott
Washington
Fairfield
ST
TX
TX
KY
KY
OH
OH
OH
OH
WV
WV
WV
IN
IN
IN
IN
IN
IN
IN
IN
IN
KS
KS
KS
KS
MO
MO
MO
MO
MO
MO
MO
CA
CA
CA
CA
CA
MN
MN
MN
MN
MN
MN
MN
CT
2002 PM2.5
Diesel
Locomotive
22.38
6.50
11.13
10.86
0.39
3.44
12.48
27.95
24.48
6.12
30.53
6.78
0.16
5.17
18.14
0.91
16.17
31.30
0.41
7.35
55.73
14.29
81.56
30.24
16.72
28.19
0.00
90.00
23.25
22.68
44.83
241.14
63.57
109.12
359.75
12.49
21.27
0.05
12.70
31.68
12.03
2.70
23.15
0.00
Diesel
Marine
0.27
0.04
18.28
5.94
52.61
23.13
34.34
33.28
25.26
39.72
60.21
0.06
0.62
0.03
0.03
0.21
0.12
1.34
0.22
0.02
0.04
0.50
0.15
4.47
0.12
4.43
0.16
33.46
4.16
0.84
3.97
1 ,666.68
176.82
1.01
0.47
231.21
12.73
0.79
11.89
35.83
11.31
1.38
50.70
44.84
Total
Diesel
Mobile
300
45
65
33
88
62
86
124
112
92
133
120
224
107
188
115
156
662
93
102
481
84
139
148
110
188
49
646
124
151
108
5,016
1,696
872
1,040
524
232
82
278
870
349
94
237
705
LM
Percent
7.5%
14.5%
45.2%
51 .6%
60.0%
42.8%
54.5%
49.5%
44.5%
50.0%
68.1%
5.7%
0.3%
4.9%
9.7%
1 .0%
10.5%
4.9%
0.7%
7.2%
1 1 .6%
17.6%
58.6%
23.5%
15.3%
17.3%
0.3%
19.1%
22.1%
15.6%
45.2%
38.0%
14.2%
12.6%
34.6%
46.5%
14.7%
1 .0%
8.9%
7.8%
6.7%
4.3%
31.1%
6.4%
5-123
-------
Regulatory Impact Analysis
FIPS
9005
34003
34013
34017
34019
34023
34025
34027
34029
34031
34035
34037
34039
36005
36047
36059
36061
36071
36081
36085
36087
36103
36119
10003
24015
24029
24031
34005
34007
34011
34015
34021
34033
42017
42029
42045
42101
4013
4021
6019
6029
6031
6039
6047
6077
MSA
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Phoenix
Phoenix
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
County
Litchfield
Bergen
Essex
Hudson
Hunterdon
Middlesex
Monmouth
Morris
Ocean
Passaic
Somerset
Sussex
Union
Bronx
Kings
Nassau
New York
Orange
Queens
Richmond
Rockland
Suffolk
Westch ester
New Castle
Cecil
Kent
Montgomery
Burlington
Camden
Cumberland
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Philadelphia
Maricopa
Pinal
Fresno
Kern
Kings
Madera
Merced
San Joaquin
ST
CT
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
DE
MD
MD
MD
NJ
NJ
NJ
NJ
NJ
NJ
PA
PA
PA
PA
AZ
AZ
CA
CA
CA
CA
CA
CA
2002 PM2.5
Diesel
Locomotive
0.00
26.97
6.64
22.70
9.60
12.54
10.14
6.96
0.52
6.11
13.21
0.99
11.04
0.13
0.00
0.00
0.00
9.19
0.06
0.00
6.91
0.00
0.00
22.95
9.27
0.07
28.82
0.00
4.82
0.57
0.80
5.56
0.27
2.29
11.62
4.55
6.45
98.35
52.54
17.77
92.07
2.57
18.89
17.75
29.94
Diesel
Marine
0.89
3.48
0.99
27.96
0.33
4.94
29.48
0.53
13.26
0.51
0.02
0.63
17.95
0.75
1.30
11.73
0.54
2.55
2.02
2.29
2.69
39.17
3.76
47.44
1.70
1.41
0.53
54.50
21.83
55.22
29.18
6.66
16.91
1.20
0.16
193.17
339.10
0.78
0.17
0.58
0.22
0.02
0.16
0.46
30.32
Total
Diesel
Mobile
109
512
416
402
185
421
418
300
256
233
195
113
355
372
696
518
1,296
288
982
166
125
690
479
458
125
42
485
328
273
155
214
277
86
330
328
409
922
2,828
256
647
635
155
145
218
437
LM
Percent
0.8%
6.0%
1 .8%
12.6%
5.4%
4.1%
9.5%
2.5%
5.4%
2.8%
6.8%
1 .4%
8.2%
0.2%
0.2%
2.3%
0.0%
4.1%
0.2%
1 .4%
7.7%
5.7%
0.8%
15.4%
8.7%
3.6%
6.0%
16.6%
9.8%
36.0%
14.0%
4.4%
19.9%
1.1%
3.6%
48.4%
37.5%
3.5%
20.6%
2.8%
14.5%
1 .7%
13.2%
8.4%
13.8%
5-124
-------
Emission Inventory
FIPS
6099
6107
53029
53033
53035
53045
53053
53061
53067
17027
17083
17119
17133
17163
29055
29071
29099
29113
29183
29189
29219
29510
MSA
San Joaquin
San Joaquin
Seattle
Seattle
Seattle
Seattle
Seattle
Seattle
Seattle
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
County
Stanislaus
Tulare
Island
King
Kitsap
Mason
Pierce
Snohomish
Thurston
Clinton
Jersey
Madison
Monroe
St. Clair
Crawford
Franklin
Jefferson
Lincoln
St. Charles
St. Louis
Warren
St. Louis
ST
CA
CA
WA
WA
WA
WA
WA
WA
WA
IL
IL
IL
IL
IL
MO
MO
MO
MO
MO
MO
MO
MO
2002 PM2.5
Diesel
Locomotive
12.07
26.68
0.00
28.95
0.00
0.00
18.18
36.65
10.80
23.14
1.86
7.81
37.61
8.93
5.23
31.20
8.38
13.80
16.62
26.77
2.82
23.28
Diesel
Marine
0.24
0.16
19.63
191.88
1.27
0.58
173.52
29.32
12.02
0.08
19.07
10.33
16.72
19.78
0.04
2.36
16.93
6.69
15.02
19.32
2.31
261 .28
Total
Diesel
Mobile
267
340
69
1,568
134
37
612
471
179
99
65
247
104
229
45
153
186
87
244
831
47
456
LM
Percent
4.6%
7.9%
28.5%
14.1%
0.9%
1 .6%
31 .3%
14.0%
12.7%
23.5%
32.1%
7.4%
52.1%
12.5%
1 1 .6%
21 .9%
13.6%
23.4%
13.0%
5.5%
10.9%
62.4%
5-125
-------
Regulatory Impact Analysis
Table 3-113 2020 Locomotive and Diesel Marine PM2.5 Tons/Year and Percent of Total Diesel Mobile
Sources
FIPS
13013
13015
13045
13057
13063
13067
13077
13089
13097
13113
13117
13121
13135
13139
13149
13151
13217
13223
13237
13247
13255
13297
24003
24005
24013
24025
24027
24510
1073
1117
1127
9007
25001
25005
25007
25009
25019
25021
25023
25025
25027
33011
MSA
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Birmingham
Birmingham
Birmingham
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
County
Barrow
Bartow
Carroll
Cherokee
Clayton
Cobb
Coweta
DeKalb
Douglas
Fayette
Forsyth
Fulton
Gwinnett
Hall
Heard
Henry
Newton
Paulding
Putnam
Rockdale
Spalding
Walton
Anne Arundel
Baltimore
Carroll
Harford
Howard
Baltimore
Jefferson
Shelby
Walker
Middlesex
Barnstable
Bristol
Dukes
Essex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Hillsborough
ST
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
MD
MD
MD
MD
MD
MD
AL
AL
AL
CT
MA
MA
MA
MA
MA
MA
MA
MA
MA
NH
2020 PM2.5
Diesel
Locomotive
5.45
19.49
5.28
0.00
10.27
26.96
13.55
12.49
4.86
3.50
0.00
36.74
9.33
5.67
0.00
13.81
1.56
11.45
0.31
2.22
0.59
1.88
10.36
34.68
5.34
8.84
12.62
46.50
75.36
39.49
14.91
0.00
6.28
11.82
0.00
15.42
0.00
18.39
9.78
9.83
37.77
1.15
Diesel
Marine
0.01
0.17
0.07
0.17
0.02
0.07
0.05
0.04
0.01
0.03
0.35
0.09
0.06
0.57
0.08
0.03
0.04
0.02
0.26
0.02
0.02
0.01
1.57
1.03
0.03
1.00
0.32
242.61
0.86
0.26
0.86
1.50
16.59
11.64
103.75
4.13
15.54
5.32
4.30
44.70
0.92
0.37
Total
Diesel
Mobile
11
35
19
23
41
137
33
103
16
20
24
224
118
31
2
41
15
24
3
16
10
10
73
154
37
46
56
328
188
65
30
22
55
79
106
101
18
114
65
688
142
56
LM
Percent
49.6%
56.9%
27.6%
0.7%
25.2%
19.8%
41 .2%
12.1%
30.0%
18.0%
1 .5%
16.4%
8.0%
19.9%
4.4%
34.2%
10.4%
47.5%
17.2%
14.2%
6.4%
18.8%
16.4%
23.1%
14.6%
21 .5%
22.9%
88.1%
40.6%
61 .4%
52.9%
6.7%
41 .7%
29.6%
97.6%
19.4%
85.4%
20.9%
21 .8%
7.9%
27.3%
2.7%
5-126
-------
Emission Inventory
FIPS
33015
47065
47115
47153
13047
13083
13295
17031
17043
17063
17089
17093
17097
17111
17197
18089
18127
18029
21015
21037
21117
39017
39025
39061
39165
39007
39035
39085
39093
39103
39133
39153
26093
26099
26115
26125
26147
26161
26163
48039
48071
48157
48167
48201
48291
MSA
Boston
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Houston
Houston
Houston
Houston
Houston
Houston
County
Rockingham
Hamilton
Marion
Sequatchie
Catoosa
Dade
Walker
Cook
DuPage
Grundy
Kane
Kendall
Lake
McHenry
Will
Lake
Porter
Dearborn
Boone
Campbell
Kenton
Butler
Clermont
Hamilton
Warren
Ashtabula
Cuyahoga
Lake
Lorain
Medina
Portage
Summit
Livingston
Macomb
Monroe
Oakland
St. Clair
Washtenaw
Wayne
Brazoria
Chambers
Fort Bend
Galveston
Harris
Liberty
ST
NH
TN
TN
TN
GA
GA
GA
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
KY
KY
KY
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
Ml
Ml
Ml
Ml
Ml
Ml
Ml
TX
TX
TX
TX
TX
TX
2020 PM2.5
Diesel
Locomotive
0.87
38.28
5.36
0.00
11.60
11.01
0.00
608.24
162.78
13.20
59.50
8.18
30.80
17.00
163.07
132.19
40.84
5.59
7.99
15.10
29.20
40.67
1.76
39.70
6.08
27.38
76.82
18.90
45.04
14.17
28.09
22.96
2.33
3.62
17.08
14.21
6.90
3.82
28.47
17.74
1.01
24.70
12.47
65.54
27.14
Diesel
Marine
28.09
22.98
4.45
0.00
0.01
0.00
0.01
164.40
0.12
5.01
0.09
0.01
19.13
0.14
3.70
12.15
10.56
17.59
26.40
18.27
9.12
0.04
34.82
103.13
0.08
138.54
96.57
21.00
88.60
0.05
0.21
0.15
0.06
4.26
6.95
3.58
16.67
0.04
7.97
191.47
5.88
0.08
438.65
1,143.23
2.35
Total
Diesel
Mobile
74
103
18
1
18
16
9
1,362
317
42
138
27
138
61
242
232
85
35
54
43
59
92
63
268
49
185
379
71
190
45
61
101
35
96
60
188
64
61
253
248
16
79
487
1,727
45
LM
Percent
39.1%
59.3%
53.8%
0.0%
63.7%
67.9%
0.1%
56.7%
51.4%
43.5%
43.3%
30.5%
36.2%
28.0%
68.9%
62.3%
60.4%
65.7%
63.8%
77.4%
65.4%
44.2%
58.0%
53.3%
12.5%
89.5%
45.7%
56.4%
70.4%
31 .8%
46.1%
22.8%
6.8%
8.2%
39.7%
9.5%
37.1%
6.3%
14.4%
84.2%
44.1%
31 .5%
92.6%
70.0%
65.6%
5-127
-------
Regulatory Impact Analysis
FIPS
48339
48473
21019
21127
39001
39053
39087
39145
54011
54053
54099
18011
18057
18059
18063
18081
18095
18097
18109
18145
20091
20103
20121
20209
29037
29047
29049
29095
29107
29165
29177
6037
6059
6065
6071
6111
27003
27019
27037
27053
27123
27139
27163
9001
MSA
Houston
Houston
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
New York
County
Montgomery
Waller
Boyd
Lawrence
Adams
Gallia
Lawrence
Scioto
Cabell
Mason
Wayne
Boone
Hamilton
Hancock
Hend ricks
Johnson
Madison
Marion
Morgan
Shelby
Johnson
Leave nworth
Miami
Wyandotte
Cass
Clay
Clinton
Jackson
Lafayette
Platte
Ray
Los Angeles
Orange
Riverside
San
Bernardino
Ventura
Anoka
Carver
Dakota
Hennepin
Ramsey
Scott
Washington
Fairfield
ST
TX
TX
KY
KY
OH
OH
OH
OH
WV
WV
WV
IN
IN
IN
IN
IN
IN
IN
IN
IN
KS
KS
KS
KS
MO
MO
MO
MO
MO
MO
MO
CA
CA
CA
CA
CA
MN
MN
MN
MN
MN
MN
MN
CT
2020 PM2.5
Diesel
Locomotive
21.14
6.14
10.44
9.43
0.35
3.09
11.20
25.08
22.84
5.31
28.80
5.92
0.15
4.58
16.27
0.88
14.62
27.99
0.40
6.54
52.60
13.49
77.03
28.47
15.70
26.78
0.00
85.15
21.96
21.42
42.28
217.08
56.50
93.21
321.96
11.01
19.93
0.05
11.92
29.88
11.29
2.55
21.74
0.00
Diesel
Marine
0.24
0.04
14.15
4.60
40.72
17.90
26.58
25.76
19.57
30.79
46.62
0.05
0.55
0.03
0.03
0.19
0.11
1.19
0.20
0.02
0.03
0.39
0.14
3.46
0.11
3.48
0.14
25.94
3.26
0.67
3.09
1,290.10
136.94
0.90
0.42
179.05
10.06
0.67
9.37
28.17
8.91
1.15
39.42
35.19
Total
Diesel
Mobile
68
15
31
17
49
28
44
63
54
47
85
34
54
28
55
26
45
166
19
29
155
29
92
56
37
64
12
223
49
51
61
2,697
729
380
574
298
72
20
80
242
89
25
96
184
LM
Percent
31 .6%
42.5%
79.9%
84.4%
84.4%
73.8%
85.6%
80.7%
78.0%
76.4%
88.8%
17.6%
1 .3%
16.2%
29.9%
4.2%
32.9%
17.5%
3.1%
22.3%
33.9%
47.4%
83.9%
57.5%
42.4%
47.6%
1 .2%
49.8%
51 .3%
42.9%
74.5%
55.9%
26.6%
24.8%
56.2%
63.8%
41.9%
3.6%
26.5%
24.0%
22.8%
14.6%
63.8%
19.1%
5-128
-------
Emission Inventory
FIPS
9005
34003
34013
34017
34019
34023
34025
34027
34029
34031
34035
34037
34039
36005
36047
36059
36061
36071
36081
36085
36087
36103
36119
10003
24015
24029
24031
34005
34007
34011
34015
34021
34033
42017
42029
42045
42101
4013
4021
6019
6029
6031
6039
6047
6077
MSA
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Phoenix
Phoenix
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
County
Litchfield
Bergen
Essex
Hudson
Hunterdon
Middlesex
Monmouth
Morris
Ocean
Passaic
Somerset
Sussex
Union
Bronx
Kings
Nassau
New York
Orange
Queens
Richmond
Rockland
Suffolk
Westch ester
New Castle
Cecil
Kent
Montgomery
Burlington
Camden
Cumberland
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Philadelphia
Maricopa
Pinal
Fresno
Kern
Kings
Madera
Merced
San Joaquin
ST
CT
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
DE
MD
MD
MD
NJ
NJ
NJ
NJ
NJ
NJ
PA
PA
PA
PA
AZ
AZ
CA
CA
CA
CA
CA
CA
2020 PM2.5
Diesel
Locomotive
0.00
22.36
5.18
19.90
7.47
11.14
6.84
5.01
0.41
4.28
11.03
0.96
8.53
0.12
0.00
0.00
0.00
8.01
0.06
0.00
6.33
0.00
0.00
23.49
7.73
0.06
21.88
0.00
3.47
0.55
0.83
4.55
0.25
1.95
9.26
3.76
5.74
89.13
48.94
15.98
80.81
2.13
17.29
15.33
26.62
Diesel
Marine
0.79
2.76
0.79
21.74
0.29
3.88
23.33
0.47
11.45
0.45
0.01
0.55
13.90
0.62
1.07
9.33
0.44
2.02
1.66
1.84
2.13
32.24
3.02
36.76
1.40
1.21
0.43
42.25
16.92
43.19
22.64
5.17
13.18
1.00
0.14
149.53
262.48
0.69
0.15
0.51
0.19
0.02
0.14
0.40
23.51
Total
Diesel
Mobile
23
146
95
120
41
106
114
73
58
54
51
23
97
75
146
139
364
63
228
39
37
193
123
144
30
12
127
100
72
65
63
64
28
78
81
199
383
709
92
236
265
56
63
84
184
LM
Percent
3.4%
17.2%
6.3%
34.7%
19.0%
14.1%
26.6%
7.6%
20.3%
8.7%
21 .8%
6.6%
23.1%
1 .0%
0.7%
6.7%
0.1%
15.9%
0.8%
4.8%
22.9%
16.7%
2.5%
41 .7%
30.2%
10.5%
17.6%
42.2%
28.3%
67.8%
37.2%
15.3%
47.6%
3.8%
1 1 .7%
77.0%
69.9%
12.7%
53.5%
7.0%
30.6%
3.8%
27.9%
18.6%
27.3%
5-129
-------
Regulatory Impact Analysis
FIPS
6099
6107
53029
53033
53035
53045
53053
53061
53067
17027
17083
17119
17133
17163
29055
29071
29099
29113
29183
29189
29219
29510
MSA
San Joaquin
San Joaquin
Seattle
Seattle
Seattle
Seattle
Seattle
Seattle
Seattle
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
County
Stanislaus
Tulare
Island
King
Kitsap
Mason
Pierce
Snohomish
Thurston
Clinton
Jersey
Madison
Monroe
St. Clair
Crawford
Franklin
Jefferson
Lincoln
St. Charles
St. Louis
Warren
St. Louis
ST
CA
CA
WA
WA
WA
WA
WA
WA
WA
IL
IL
IL
IL
IL
MO
MO
MO
MO
MO
MO
MO
MO
2020 PM2.5
Diesel
Locomotive
10.69
24.00
0.00
27.06
0.00
0.00
16.97
33.68
9.33
21.27
1.73
8.44
33.99
9.49
4.54
29.11
7.90
13.04
15.70
25.09
2.66
22.18
Diesel
Marine
0.21
0.14
15.26
149.20
1.13
0.50
134.63
23.01
9.42
0.07
14.76
8.01
12.95
15.31
0.04
1.86
13.13
5.22
11.75
15.01
1.81
202.23
Total
Diesel
Mobile
101
133
25
484
27
7
238
140
48
41
28
67
60
69
12
54
49
34
73
214
14
256
LM
Percent
10.8%
18.1%
60.2%
36.4%
4.2%
7.1%
63.7%
40.4%
39.1%
51 .8%
57.9%
24.7%
77.8%
36.2%
38.8%
57.6%
43.3%
53.8%
37.4%
18.8%
32.7%
87.7%
5-130
-------
Emission Inventory
Table 3-114 2030 Locomotive and Diesel Marine PM2.5 Tons/Year and Percent of Total Diesel Mobile
Sources
FIPS
13013
13015
13045
13057
13063
13067
13077
13089
13097
13113
13117
13121
13135
13139
13149
13151
13217
13223
13237
13247
13255
13297
24003
24005
24013
24025
24027
24510
1073
1117
1127
9007
25001
25005
25007
25009
25019
25021
25023
25025
25027
33011
MSA
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Birmingham
Birmingham
Birmingham
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
County
Barrow
Bartow
Carroll
Cherokee
Clayton
Cobb
Coweta
DeKalb
Douglas
Fayette
Forsyth
Fulton
Gwinnett
Hall
Heard
Henry
Newton
Paulding
Putnam
Rockdale
Spalding
Walton
Anne Arundel
Baltimore
Carroll
Harford
Howard
Baltimore
Jefferson
Shelby
Walker
Middlesex
Barnstable
Bristol
Dukes
Essex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Hillsborough
ST
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
MD
MD
MD
MD
MD
MD
AL
AL
AL
CT
MA
MA
MA
MA
MA
MA
MA
MA
MA
NH
2030 PM2.5
Diesel
Locomotive
5.25
18.79
5.08
0.00
9.90
25.96
13.06
12.03
4.66
3.37
0.00
35.38
8.98
5.34
0.00
13.32
1.50
11.04
0.29
2.14
0.57
1.81
9.01
32.54
5.05
8.01
11.21
45.29
72.52
38.03
14.10
0.00
5.94
11.25
0.00
14.59
0.00
17.74
9.26
9.40
35.83
1.09
Diesel
Marine
0.01
0.20
0.08
0.19
0.03
0.08
0.06
0.05
0.01
0.04
0.40
0.11
0.07
0.65
0.09
0.04
0.05
0.03
0.30
0.03
0.03
0.01
1.77
1.15
0.04
1.11
0.35
259.26
0.94
0.29
0.93
1.70
18.19
12.53
1 1 1 .06
4.59
16.73
5.72
4.83
47.81
1.04
0.42
Total
Diesel
Mobile
9
28
14
14
27
85
25
66
12
13
14
130
69
21
1
28
9
19
2
10
6
6
43
94
22
28
35
330
143
52
26
14
42
55
112
63
18
72
42
295
91
31
LM
Percent
60.3%
68.0%
37.1%
1 .3%
36.7%
30.8%
53.1%
18.2%
40.2%
26.9%
2.9%
27.4%
13.2%
29.0%
8.2%
47.3%
16.7%
58.6%
26.8%
22.0%
10.2%
28.3%
24.8%
36.0%
23.1%
32.2%
33.5%
92.2%
51 .5%
73.3%
58.7%
12.3%
58.0%
43.6%
98.9%
30.3%
93.2%
32.7%
33.7%
19.4%
40.4%
4.9%
5-131
-------
Regulatory Impact Analysis
FIPS
33015
47065
47115
47153
13047
13083
13295
17031
17043
17063
17089
17093
17097
17111
17197
18089
18127
18029
21015
21037
21117
39017
39025
39061
39165
39007
39035
39085
39093
39103
39133
39153
26093
26099
26115
26125
26147
26161
26163
48039
48071
48157
48167
48201
48291
MSA
Boston
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Houston
Houston
Houston
Houston
Houston
Houston
County
Rockingham
Hamilton
Marion
Sequatchie
Catoosa
Dade
Walker
Cook
DuPage
Grundy
Kane
Kendall
Lake
McHenry
Will
Lake
Porter
Dearborn
Boone
Campbell
Kenton
Butler
Clermont
Hamilton
Warren
Ashtabula
Cuyahoga
Lake
Lorain
Medina
Portage
Summit
Livingston
Macomb
Monroe
Oakland
St. Clair
Washtenaw
Wayne
Brazoria
Chambers
Fort Bend
Galveston
Harris
Liberty
ST
NH
TN
TN
TN
GA
GA
GA
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
KY
KY
KY
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
Ml
Ml
Ml
Ml
Ml
Ml
Ml
TX
TX
TX
TX
TX
TX
2030 PM2.5
Diesel
Locomotive
0.82
36.91
5.16
0.00
11.18
10.61
0.00
583.11
150.13
12.86
55.63
7.87
28.70
15.86
154.37
129.63
39.03
5.39
7.70
14.53
28.15
38.73
1.68
38.03
5.88
26.16
73.82
17.97
42.97
13.67
26.81
21.98
2.25
3.49
16.47
13.69
6.63
3.80
29.36
17.11
0.97
23.77
13.22
67.89
26.15
Diesel
Marine
30.13
24.61
4.78
0.00
0.01
0.00
0.01
176.82
0.14
5.35
0.10
0.01
21.57
0.16
3.97
13.55
11.74
18.81
28.23
19.53
9.75
0.05
37.21
110.20
0.09
148.22
103.97
22.85
94.99
0.06
0.24
0.17
0.06
4.61
7.45
3.84
17.88
0.04
8.63
204.68
6.36
0.09
468.88
1,221.64
2.52
Total
Diesel
Mobile
56
85
15
1
15
14
5
1,069
227
29
91
16
96
37
195
186
68
30
46
40
49
64
53
216
26
185
280
57
165
30
45
63
20
56
42
108
44
35
151
242
12
52
500
1,557
37
LM
Percent
55.2%
72.5%
67.1%
0.0%
74.0%
76.7%
0.1%
71.1%
66.1%
62.4%
61 .3%
48.2%
52.5%
42.9%
81 .2%
77.1%
75.0%
79.5%
78.5%
85.6%
78.1%
60.4%
72.9%
68.7%
23.0%
94.4%
63.4%
71 .2%
83.8%
45.8%
60.8%
35.3%
1 1 .7%
14.6%
56.9%
16.2%
55.4%
11.1%
25.1%
91 .5%
59.3%
45.9%
96.4%
82.8%
77.9%
5-132
-------
Emission Inventory
FIPS
48339
48473
21019
21127
39001
39053
39087
39145
54011
54053
54099
18011
18057
18059
18063
18081
18095
18097
18109
18145
20091
20103
20121
20209
29037
29047
29049
29095
29107
29165
29177
6037
6059
6065
6071
6111
27003
27019
27037
27053
27123
27139
27163
9001
MSA
Houston
Houston
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
New York
County
Montgomery
Waller
Boyd
Lawrence
Adams
Gallia
Lawrence
Scioto
Cabell
Mason
Wayne
Boone
Hamilton
Hancock
Hend ricks
Johnson
Madison
Marion
Morgan
Shelby
Johnson
Leave nworth
Miami
Wyandotte
Cass
Clay
Clinton
Jackson
Lafayette
Platte
Ray
Los Angeles
Orange
Riverside
San
Bernardino
Ventura
Anoka
Carver
Dakota
Hennepin
Ramsey
Scott
Washington
Fairfield
ST
TX
TX
KY
KY
OH
OH
OH
OH
WV
WV
WV
IN
IN
IN
IN
IN
IN
IN
IN
IN
KS
KS
KS
KS
MO
MO
MO
MO
MO
MO
MO
CA
CA
CA
CA
CA
MN
MN
MN
MN
MN
MN
MN
CT
2030 PM2.5
Diesel
Locomotive
20.38
5.92
10.05
8.93
0.34
2.94
10.68
23.91
21.94
5.03
27.75
5.59
0.18
4.35
15.52
1.02
13.96
26.79
0.46
6.23
50.70
13.00
74.26
27.42
15.11
27.23
0.00
85.76
21.17
20.65
42.32
214.05
57.93
87.56
306.89
10.79
19.16
0.05
11.47
28.80
10.87
2.46
20.93
0.00
Diesel
Marine
0.27
0.04
15.13
4.91
43.51
19.13
28.40
27.52
20.93
32.92
49.83
0.06
0.63
0.03
0.03
0.21
0.12
1.35
0.22
0.02
0.04
0.42
0.15
3.70
0.12
3.74
0.16
27.74
3.50
0.74
3.31
1,378.65
146.38
1.02
0.48
191.39
10.87
0.75
10.11
30.34
9.61
1.27
42.22
37.87
Total
Diesel
Mobile
49
10
29
15
48
26
43
58
49
42
82
19
26
16
33
14
29
98
10
17
101
21
81
43
26
48
6
171
36
35
53
2,053
433
189
400
247
51
10
51
153
56
14
81
112
LM
Percent
42.2%
58.2%
87.4%
90.7%
92.1%
85.9%
91 .2%
89.0%
86.9%
89.3%
95.0%
30.0%
3.1%
28.1%
46.7%
8.9%
47.9%
28.7%
6.6%
36.6%
50.4%
63.9%
91 .7%
71 .6%
59.1%
64.9%
2.9%
66.5%
68.5%
61 .6%
86.7%
77.6%
47.2%
46.8%
76.8%
81.7%
59.0%
7.6%
42.4%
38.7%
36.4%
26.4%
78.3%
33.7%
5-133
-------
Regulatory Impact Analysis
FIPS
9005
34003
34013
34017
34019
34023
34025
34027
34029
34031
34035
34037
34039
36005
36047
36059
36061
36071
36081
36085
36087
36103
36119
10003
24015
24029
24031
34005
34007
34011
34015
34021
34033
42017
42029
42045
42101
4013
4021
6019
6029
6031
6039
6047
6077
MSA
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Phoenix
Phoenix
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
County
Litchfield
Bergen
Essex
Hudson
Hunterdon
Middlesex
Monmouth
Morris
Ocean
Passaic
Somerset
Sussex
Union
Bronx
Kings
Nassau
New York
Orange
Queens
Richmond
Rockland
Suffolk
Westch ester
New Castle
Cecil
Kent
Montgomery
Burlington
Camden
Cumberland
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Philadelphia
Maricopa
Pinal
Fresno
Kern
Kings
Madera
Merced
San Joaquin
ST
CT
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
DE
MD
MD
MD
NJ
NJ
NJ
NJ
NJ
NJ
PA
PA
PA
PA
AZ
AZ
CA
CA
CA
CA
CA
CA
2030 PM2.5
Diesel
Locomotive
0.00
20.91
4.68
18.73
6.78
10.49
5.78
4.44
0.36
3.75
10.24
1.10
7.68
0.12
0.00
0.00
0.00
7.53
0.05
0.00
6.09
0.00
0.00
23.04
7.20
0.06
19.61
0.00
3.05
0.64
0.83
4.21
0.26
1.82
8.44
3.48
5.93
85.15
46.98
15.23
76.62
1.98
16.55
14.48
25.33
Diesel
Marine
0.90
2.98
0.85
23.28
0.33
4.17
25.21
0.53
12.87
0.51
0.02
0.63
14.86
0.69
1.18
10.10
0.48
2.18
1.83
2.00
2.31
35.49
3.29
39.30
1.55
1.36
0.46
45.18
18.09
46.39
24.22
5.53
14.13
1.10
0.16
159.80
280.49
0.79
0.17
0.58
0.22
0.02
0.16
0.46
25.14
Total
Diesel
Mobile
13
89
50
79
25
63
75
42
39
30
32
13
59
38
77
78
168
39
103
19
23
118
61
105
20
6
78
76
49
58
45
38
22
44
46
188
347
425
71
101
145
21
32
41
100
LM
Percent
6.6%
26.9%
1 1 .0%
53.1%
28.1%
23.1%
41 .6%
1 1 .9%
33.6%
14.0%
32.2%
12.9%
38.2%
2.1%
1 .5%
12.9%
0.3%
25.2%
1 .8%
10.3%
36.8%
30.1%
5.4%
59.6%
43.2%
22.2%
25.7%
59.6%
43.0%
81.6%
55.3%
25.5%
65.7%
6.7%
18.8%
86.8%
82.6%
20.2%
66.3%
15.7%
52.9%
9.3%
52.1%
36.8%
50.3%
5-134
-------
Emission Inventory
FIPS
6099
6107
53029
53033
53035
53045
53053
53061
53067
17027
17083
17119
17133
17163
29055
29071
29099
29113
29183
29189
29219
29510
MSA
San Joaquin
San Joaquin
Seattle
Seattle
Seattle
Seattle
Seattle
Seattle
Seattle
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
County
Stanislaus
Tulare
Island
King
Kitsap
Mason
Pierce
Snohomish
Thurston
Clinton
Jersey
Madison
Monroe
St. Clair
Crawford
Franklin
Jefferson
Lincoln
St. Charles
St. Louis
Warren
St. Louis
ST
CA
CA
WA
WA
WA
WA
WA
WA
WA
IL
IL
IL
IL
IL
MO
MO
MO
MO
MO
MO
MO
MO
2030 PM2.5
Diesel
Locomotive
10.15
22.89
0.00
26.00
0.00
0.00
16.30
32.24
8.81
20.38
1.66
8.64
32.45
9.36
4.30
27.96
7.62
12.57
15.14
24.13
2.56
23.99
Diesel
Marine
0.23
0.16
16.34
159.80
1.28
0.57
144.03
24.77
10.12
0.08
15.78
8.56
13.84
16.36
0.04
2.00
14.04
5.60
12.62
16.08
1.95
216.11
Total
Diesel
Mobile
45
65
22
344
16
4
206
102
36
29
23
43
52
48
9
43
38
26
51
130
9
260
LM
Percent
23.3%
35.4%
75.7%
54.0%
8.1%
12.8%
77.8%
56.0%
53.2%
69.4%
76.4%
40.3%
88.4%
53.5%
50.9%
70.5%
57.1%
70.5%
54.2%
30.9%
49.3%
92.3%
5-135
-------
Regulatory Impact Analysis
Table 3-115 2002 Locomotive and Diesel Marine NOx Tons/Year and Percent of Total Mobile Sources
FIPS
13013
13015
13045
13057
13063
13067
13077
13089
13097
13113
13117
13121
13135
13139
13149
13151
13217
13223
13237
13247
13255
13297
24003
24005
24013
24025
24027
24510
1073
1117
1127
9007
25001
25005
25007
25009
25019
25021
25023
25025
25027
33011
33015
47065
MSA
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Birmingham
Birmingham
Birmingham
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Chattanooga
County
Barrow
Bartow
Carroll
Cherokee
Clayton
Cobb
Coweta
DeKalb
Douglas
Fayette
Forsyth
Fulton
Gwinnett
Hall
Heard
Henry
Newton
Paulding
Putnam
Rockdale
Spalding
Walton
Anne Arundel
Baltimore
Carroll
Harford
Howard
Baltimore
Jefferson
Shelby
Walker
Middlesex
Barnstable
Bristol
Dukes
Essex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Hillsborough
Rockingham
Hamilton
ST
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
MD
MD
MD
MD
MD
MD
AL
AL
AL
CT
MA
MA
MA
MA
MA
MA
MA
MA
MA
NH
NH
TN
2002 NOx
Diesel
Locomotive
224.1
799.6
219.5
0.0
420.9
1,110.1
555.6
515.4
202.2
143.8
0.0
1,512.7
385.8
258.8
0.0
567.2
64.4
470.2
14.1
91.1
24.5
77.1
520.4
1,243.0
199.2
389.4
594.5
1,282.5
4,615.9
1,156.1
889.2
160.2
318.1
588.4
0.0
777.6
0.0
902.6
493.8
489.2
1,860.6
49.0
37.0
1,569.2
Diesel
Marine
0.5
7.0
3.0
6.8
1.0
2.8
2.0
1.8
0.5
1.3
14.1
3.8
2.5
23.1
3.3
1.3
1.8
1.0
10.6
1.0
1.0
0.5
63.4
41.5
1.3
40.2
12.7
1,670.4
268.9
10.4
116.8
121.4
474.3
238.7
1,589.6
197.2
282.5
163.4
169.6
855.0
36.5
15.0
1,112.9
909.5
Total
Mobile
2,039
5,172
4,762
5,828
9,512
23,542
5,727
26,283
3,952
3,977
4,418
39,991
21,343
6,452
465
6,479
3,584
3,801
630
3,158
2,584
2,211
15,497
24,021
5,995
7,894
8,160
23,591
32,416
6,159
3,687
282
8,446
15,719
2,042
21,303
596
22,498
12,655
38,095
26,614
12,444
1 1 ,846
14,329
LM
Percent
1 1 .0%
15.6%
4.7%
0.1%
4.4%
4.7%
9.7%
2.0%
5.1%
3.6%
0.3%
3.8%
1 .8%
4.4%
0.7%
8.8%
1 .8%
12.4%
3.9%
2.9%
1 .0%
3.5%
3.8%
5.3%
3.3%
5.4%
7.4%
12.5%
15.1%
18.9%
27.3%
99.8%
9.4%
5.3%
77.9%
4.6%
47.4%
4.7%
5.2%
3.5%
7.1%
0.5%
9.7%
17.3%
5-136
-------
Emission Inventory
FIPS
47115
47153
13047
13083
13295
17031
17043
17063
17089
17093
17097
17111
17197
18089
18127
18029
21015
21037
21117
39017
39025
39061
39165
39007
39035
39085
39093
39103
39133
39153
26093
26099
26115
26125
26147
26161
26163
48039
48071
48157
48167
48201
48291
48339
48473
21019
MSA
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Houston
Houston
Houston
Houston
Houston
Houston
Houston
Houston
Huntington
County
Marion
Sequatchie
Catoosa
Dade
Walker
Cook
DuPage
Grundy
Kane
Kendall
Lake
McHenry
Will
Lake
Porter
Dearborn
Boone
Campbell
Kenton
Butler
Clermont
Hamilton
Warren
Ashtabula
Cuyahoga
Lake
Lorain
Medina
Portage
Summit
Livingston
Macomb
Monroe
Oakland
St. Clair
Washtenaw
Wayne
Brazoria
Chambers
Fort Bend
Galveston
Harris
Liberty
Montgomery
Waller
Boyd
ST
TN
TN
GA
GA
GA
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
KY
KY
KY
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
Ml
Ml
Ml
Ml
Ml
Ml
Ml
TX
TX
TX
TX
TX
TX
TX
TX
KY
2002 NOx
Diesel
Locomotive
220.0
0.0
475.9
452.1
0.0
24,769.1
7,028.5
479.6
2,446.9
310.8
1,301.3
700.7
6,401.5
4,656.8
1,588.7
216.3
327.3
621.1
1,197.5
1,581.9
68.2
1,540.5
235.3
1,062.3
2,914.2
738.0
1,749.1
551.8
1,090.9
888.7
95.5
148.2
700.2
584.1
285.7
154.9
1,133.9
728.4
41.6
1,019.2
491.0
2,609.1
1,115.9
867.4
252.5
430.5
Diesel
Marine
176.6
0.0
0.3
0.0
0.3
6,520.5
5.0
198.0
3.5
0.3
774.4
5.8
146.5
490.6
425.4
696.0
1,044.5
722.6
360.8
1.7
1,377.2
4,078.9
3.2
5,482.2
3,832.5
837.5
3,509.5
2.1
8.6
6.0
1.9
169.4
276.4
140.9
662.4
1.3
318.6
7,573.7
234.3
3.3
17,352.7
45,215.7
93.4
9.7
1.5
559.8
Total
Mobile
2,998
270
2,527
2,263
1,996
178,269
31,241
3,244
8,879
1,789
16,423
5,103
16,000
23,491
8,840
3,628
5,966
4,914
7,316
10,604
7,579
34,403
5,948
12,796
49,767
8,866
15,702
6,896
8,119
18,330
7,393
24,046
7,675
38,601
9,871
12,742
68,502
18,133
2,586
11,057
30,023
165,530
4,073
13,754
1,574
3,171
LM
Percent
13.2%
0.0%
18.8%
20.0%
0.0%
17.6%
22.5%
20.9%
27.6%
17.4%
12.6%
13.8%
40.9%
21 .9%
22.8%
25.1%
23.0%
27.3%
21 .3%
14.9%
19.1%
16.3%
4.0%
51.1%
13.6%
17.8%
33.5%
8.0%
13.5%
4.9%
1 .3%
1 .3%
12.7%
1 .9%
9.6%
1 .2%
2.1%
45.8%
10.7%
9.2%
59.4%
28.9%
29.7%
6.4%
16.1%
31 .2%
5-137
-------
Regulatory Impact Analysis
FIPS
21127
39001
39053
39087
39145
54011
54053
54099
18011
18057
18059
18063
18081
18095
18097
18109
18145
20091
20103
20121
20209
29037
29047
29049
29095
29107
29165
29177
6037
6059
6065
6071
6111
27003
27019
27037
27053
27123
27139
27163
9001
9005
34003
34013
34017
MSA
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
New York
New York
New York
New York
New York
County
Lawrence
Adams
Gallia
Lawrence
Scioto
Cabell
Mason
Wayne
Boone
Hamilton
Hancock
Hend ricks
Johnson
Madison
Marion
Morgan
Shelby
Johnson
Leave nworth
Miami
Wyandotte
Cass
Clay
Clinton
Jackson
Lafayette
Platte
Ray
Los Angeles
Orange
Riverside
San
Bernardino
Ventura
Anoka
Carver
Dakota
Hennepin
Ramsey
Scott
Washington
Fairfield
Litchfield
Bergen
Essex
Hudson
ST
KY
OH
OH
OH
OH
WV
WV
WV
IN
IN
IN
IN
IN
IN
IN
IN
IN
KS
KS
KS
KS
MO
MO
MO
MO
MO
MO
MO
CA
CA
CA
CA
CA
MN
MN
MN
MN
MN
MN
MN
CT
CT
NJ
NJ
NJ
2002 NOx
Diesel
Locomotive
425.1
13.7
119.7
433.9
972.1
946.3
239.7
1,182.1
235.9
5.7
179.7
630.8
33.0
563.4
1,089.8
15.0
255.6
2,157.3
553.1
3,157.4
1,170.2
646.8
1,073.0
0.0
3,434.0
899.9
878.0
1,713.2
9,771.2
2,374.1
4,414.1
14,261.8
479.2
822.8
2.0
491.2
1 ,226.2
465.4
104.5
895.5
589.7
100.0
1,055.1
228.1
777.7
Diesel
Marine
181.8
1,610.6
708.1
1,051.2
1,018.7
774.1
1,218.0
1,844.2
2.1
22.6
1.2
1.2
7.6
4.3
48.3
8.0
0.9
1.4
15.5
5.5
137.0
4.4
137.9
5.8
1,026.2
129.2
26.9
122.5
42,754.8
2,363.7
56.3
26.3
4,087.6
399.5
27.0
371.9
1,117.3
353.7
46.1
1,560.4
257.5
31.6
193.9
51.3
1,486.3
Total
Mobile
1,317
3,248
2,184
3,946
4,780
9,978
2,909
4,489
3,600
7,413
3,342
5,968
4,964
6,314
33,822
3,634
3,130
18,312
2,984
4,481
7,329
3,752
8,204
1,517
30,133
3,796
5,793
3,190
257,574
68,174
45,019
56,392
18,815
10,508
2,563
11,559
42,042
18,199
2,947
9,536
28,368
4,615
23,136
21,624
16,558
LM
Percent
46.1%
50.0%
37.9%
37.6%
41 .7%
17.2%
50.1%
67.4%
6.6%
0.4%
5.4%
10.6%
0.8%
9.0%
3.4%
0.6%
8.2%
1 1 .8%
19.1%
70.6%
17.8%
17.4%
14.8%
0.4%
14.8%
27.1%
15.6%
57.5%
20.4%
6.9%
9.9%
25.3%
24.3%
1 1 .6%
1.1%
7.5%
5.6%
4.5%
5.1%
25.8%
3.0%
2.9%
5.4%
1 .3%
13.7%
5-138
-------
Emission Inventory
FIPS
34019
34023
34025
34027
34029
34031
34035
34037
34039
36005
36047
36059
36061
36071
36081
36085
36087
36103
36119
10003
24015
24029
24031
34005
34007
34011
34015
34021
34033
42017
42029
42045
42101
4013
4021
6019
6029
6031
6039
6047
6077
6099
6107
53029
53033
53035
MSA
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Phoenix
Phoenix
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
Seattle
Seattle
Seattle
County
Hunterdon
Middlesex
Monmouth
Morris
Ocean
Passaic
Somerset
Sussex
Union
Bronx
Kings
Nassau
New York
Orange
Queens
Richmond
Rockland
Suffolk
Westch ester
New Castle
Cecil
Kent
Montgomery
Burlington
Camden
Cumberland
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Philadelphia
Maricopa
Pinal
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
Island
King
Kitsap
ST
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
DE
MD
MD
MD
NJ
NJ
NJ
NJ
NJ
NJ
PA
PA
PA
PA
AZ
AZ
CA
CA
CA
CA
CA
CA
CA
CA
WA
WA
WA
2002 NOx
Diesel
Locomotive
331.3
481.9
379.8
234.4
19.6
229.2
509.9
36.0
420.7
5.1
0.0
0.0
0.0
349.9
2.3
0.0
265.0
0.0
0.0
818.9
306.8
2.4
987.2
0.0
182.3
20.8
36.7
193.5
10.3
86.8
435.2
171.7
239.6
3,884.9
2,030.8
765.2
3,687.8
104.0
819.3
790.7
1,287.6
528.7
1,172.3
0.0
1,119.6
0.0
Diesel
Marine
11.7
282.2
682.3
18.7
435.6
18.1
0.6
22.2
1,084.1
203.9
1,713.6
586.4
1,207.0
80.2
2,056.4
2,386.5
16.6
1,361.4
127.5
2,545.5
56.0
48.8
16.9
1,178.2
471.7
1,242.9
633.3
144.7
374.9
40.0
5.7
5,914.4
10,381.6
28.0
6.2
32.2
12.0
1.1
8.9
25.4
603.0
12.5
8.9
2,098.3
5,906.0
45.6
Total
Mobile
7,327
19,497
17,750
13,461
12,234
11,334
8,259
4,546
14,897
18,301
36,548
22,268
44,035
13,475
39,760
8,667
4,886
27,455
16,193
21,119
5,150
984
23,771
13,449
13,996
5,472
10,121
12,609
3,009
13,732
12,150
18,361
44,901
105,636
10,844
24,853
27,768
4,389
5,469
9,353
18,977
12,862
13,310
3,999
68,488
6,933
LM
Percent
4.7%
3.9%
6.0%
1 .9%
3.7%
2.2%
6.2%
1 .3%
10.1%
1.1%
4.7%
2.6%
2.7%
3.2%
5.2%
27.5%
5.8%
5.0%
0.8%
15.9%
7.0%
5.2%
4.2%
8.8%
4.7%
23.1%
6.6%
2.7%
12.8%
0.9%
3.6%
33.1%
23.7%
3.7%
18.8%
3.2%
13.3%
2.4%
15.1%
8.7%
10.0%
4.2%
8.9%
52.5%
10.3%
0.7%
5-139
-------
Regulatory Impact Analysis
FIPS
53045
53053
53061
53067
17027
17083
17119
17133
17163
29055
29071
29099
29113
29183
29189
29219
29510
MSA
Seattle
Seattle
Seattle
Seattle
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
County
Mason
Pierce
Snohomish
Thurston
Clinton
Jersey
Madison
Monroe
St. Clair
Crawford
Franklin
Jefferson
Lincoln
St. Charles
St. Louis
Warren
St. Louis
ST
WA
WA
WA
WA
IL
IL
IL
IL
IL
MO
MO
MO
MO
MO
MO
MO
MO
2002 NOx
Diesel
Locomotive
0.1
703.0
1,279.7
369.2
801.1
64.8
287.0
1,288.0
325.2
204.7
1,206.1
324.2
534.3
643.6
1,035.3
109.1
866.5
Diesel
Marine
26.7
5,327.1
912.6
373.3
2.8
583.9
316.7
512.0
605.6
1.5
73.8
519.4
206.8
465.6
594.2
71.9
7,998.7
Total
Mobile
1,679
27,443
20,798
8,518
2,597
1,759
10,200
3,122
10,049
2,080
6,434
9,205
2,771
10,406
41,254
1,692
23,595
LM
Percent
1 .6%
22.0%
10.5%
8.7%
31 .0%
36.9%
5.9%
57.7%
9.3%
9.9%
19.9%
9.2%
26.7%
10.7%
4.0%
10.7%
37.6%
5-140
-------
Emission Inventory
Table 3-116 2020 Locomotive and Diesel Marine NOx Tons/Year and Percent of Total Mobile Sources
FIPS
13013
13015
13045
13057
13063
13067
13077
13089
13097
13113
13117
13121
13135
13139
13149
13151
13217
13223
13237
13247
13255
13297
24003
24005
24013
24025
24027
24510
1073
1117
1127
9007
25001
25005
25007
25009
25019
25021
25023
25025
25027
33011
33015
47065
MSA
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Birmingham
Birmingham
Birmingham
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Chattanooga
County
Barrow
Bartow
Carroll
Cherokee
Clayton
Cobb
Coweta
DeKalb
Douglas
Fayette
Forsyth
Fulton
Gwinnett
Hall
Heard
Henry
Newton
Paulding
Putnam
Rockdale
Spalding
Walton
Anne Arundel
Baltimore
Carroll
Harford
Howard
Baltimore
Jefferson
Shelby
Walker
Middlesex
Barnstable
Bristol
Dukes
Essex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Hillsborough
Rockingham
Hamilton
ST
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
MD
MD
MD
MD
MD
MD
AL
AL
AL
CT
MA
MA
MA
MA
MA
MA
MA
MA
MA
NH
NH
TN
2020 NOx
Diesel
Locomotive
189.4
675.7
183.4
0.0
355.6
933.8
469.5
433.1
168.0
121.5
0.0
1,272.1
323.3
186.3
0.0
479.3
54.4
397.3
10.3
77.0
20.7
65.1
306.6
936.5
145.4
251.7
366.4
1,186.5
4,173.3
1,026.2
649.1
110.6
232.2
436.1
0.0
567.6
0.0
682.9
363.1
362.6
1,382.7
35.8
27.0
1,326.0
Diesel
Marine
0.6
8.5
3.6
8.1
1.2
3.3
2.4
2.1
0.6
1.5
16.9
4.5
3.0
27.8
3.9
1.5
2.1
1.2
12.7
1.2
1.2
0.6
71.4
45.1
1.5
42.9
10.6
1,357.0
221.1
12.5
97.7
121.2
490.2
214.3
1,332.0
201.2
256.8
140.1
191.5
703.7
43.9
18.0
928.5
749.8
Total
Mobile
682
1,838
1,404
1,834
3,382
7,245
1,995
7,494
1,353
1,333
1,392
15,332
6,226
1,919
128
2,241
996
1,372
202
1,026
728
664
8,342
11,487
2,579
3,608
3,859
15,594
12,112
2,492
1,530
233
4,681
7,364
1,732
9,768
530
10,197
6,163
17,700
12,067
6,327
6,652
5,500
LM
Percent
27.9%
37.2%
13.3%
0.4%
10.6%
12.9%
23.7%
5.8%
12.5%
9.2%
1 .2%
8.3%
5.2%
1 1 .2%
3.1%
21 .5%
5.7%
29.0%
1 1 .4%
7.6%
3.0%
9.9%
4.5%
8.5%
5.7%
8.2%
9.8%
16.3%
36.3%
41 .7%
48.8%
99.6%
15.4%
8.8%
76.9%
7.9%
48.4%
8.1%
9.0%
6.0%
1 1 .8%
0.8%
14.4%
37.7%
5-141
-------
Regulatory Impact Analysis
FIPS
47115
47153
13047
13083
13295
17031
17043
17063
17089
17093
17097
17111
17197
18089
18127
18029
21015
21037
21117
39017
39025
39061
39165
39007
39035
39085
39093
39103
39133
39153
26093
26099
26115
26125
26147
26161
26163
48039
48071
48157
48167
48201
48291
48339
48473
21019
MSA
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Houston
Houston
Houston
Houston
Houston
Houston
Houston
Houston
Huntington
County
Marion
Sequatchie
Catoosa
Dade
Walker
Cook
DuPage
Grundy
Kane
Kendall
Lake
McHenry
Will
Lake
Porter
Dearborn
Boone
Campbell
Kenton
Butler
Clermont
Hamilton
Warren
Ashtabula
Cuyahoga
Lake
Lorain
Medina
Portage
Summit
Livingston
Macomb
Monroe
Oakland
St. Clair
Washtenaw
Wayne
Brazoria
Chambers
Fort Bend
Galveston
Harris
Liberty
Montgomery
Waller
Boyd
ST
TN
TN
GA
GA
GA
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
KY
KY
KY
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
Ml
Ml
Ml
Ml
Ml
Ml
Ml
TX
TX
TX
TX
TX
TX
TX
TX
KY
2020 NOx
Diesel
Locomotive
185.9
0.0
402.1
382.0
0.0
18,683.3
4,853.4
436.8
1,791.2
253.3
930.4
496.6
4,767.5
4,582.7
1,239.8
172.0
276.6
522.3
1,011.3
1,225.0
53.0
1,208.2
188.0
833.8
2,405.6
568.9
1,360.5
438.3
851.4
702.5
80.7
125.2
591.7
492.0
238.4
137.0
1,064.0
615.5
35.1
855.7
481.5
2,463.1
940.8
732.9
213.4
361.2
Diesel
Marine
148.4
0.0
0.3
0.0
0.3
5,549.0
5.9
161.9
4.2
0.3
886.7
7.0
122.8
527.6
449.0
565.9
850.5
588.4
293.3
2.0
1,117.4
3,308.4
3.8
4,487.1
3,286.2
773.0
2,917.8
2.5
10.3
7.2
2.3
151.8
231.4
117.6
552.6
1.6
284.1
6,160.6
208.0
4.0
14,101.9
36,663.4
77.6
11.6
1.8
454.4
Total
Mobile
1,048
73
953
814
555
69,728
11,856
1,367
3,786
774
6,916
1,870
7,685
12,632
4,478
1,708
3,457
2,204
2,771
3,504
3,185
13,388
1,673
9,441
18,923
3,859
8,463
1,945
2,483
4,985
2,010
7,234
2,799
12,011
4,414
3,811
23,915
12,492
1,047
4,021
24,831
88,044
1,866
4,332
593
1,599
LM
Percent
31.9%
0.0%
42.2%
46.9%
0.1%
34.8%
41 .0%
43.8%
47.4%
32.7%
26.3%
26.9%
63.6%
40.5%
37.7%
43.2%
32.6%
50.4%
47.1%
35.0%
36.7%
33.7%
1 1 .5%
56.4%
30.1%
34.8%
50.5%
22.7%
34.7%
14.2%
4.1%
3.8%
29.4%
5.1%
17.9%
3.6%
5.6%
54.2%
23.2%
21 .4%
58.7%
44.4%
54.6%
17.2%
36.3%
51 .0%
5-142
-------
Emission Inventory
FIPS
21127
39001
39053
39087
39145
54011
54053
54099
18011
18057
18059
18063
18081
18095
18097
18109
18145
20091
20103
20121
20209
29037
29047
29049
29095
29107
29165
29177
6037
6059
6065
6071
6111
27003
27019
27037
27053
27123
27139
27163
9001
9005
34003
34013
34017
MSA
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
New York
New York
New York
New York
New York
County
Lawrence
Adams
Gallia
Lawrence
Scioto
Cabell
Mason
Wayne
Boone
Hamilton
Hancock
Hend ricks
Johnson
Madison
Marion
Morgan
Shelby
Johnson
Leave nworth
Miami
Wyandotte
Cass
Clay
Clinton
Jackson
Lafayette
Platte
Ray
Los Angeles
Orange
Riverside
San
Bernardino
Ventura
Anoka
Carver
Dakota
Hennepin
Ramsey
Scott
Washington
Fairfield
Litchfield
Bergen
Essex
Hudson
ST
KY
OH
OH
OH
OH
WV
WV
WV
IN
IN
IN
IN
IN
IN
IN
IN
IN
KS
KS
KS
KS
MO
MO
MO
MO
MO
MO
MO
CA
CA
CA
CA
CA
MN
MN
MN
MN
MN
MN
MN
CT
CT
NJ
NJ
NJ
2020 NOx
Diesel
Locomotive
310.3
10.6
93.0
337.7
755.3
789.0
175.0
997.3
178.0
6.4
138.0
490.3
37.1
444.2
851.8
16.9
197.5
1,821.4
467.1
2,667.9
985.3
543.2
984.8
0.0
3,099.6
760.4
741.9
1,528.5
8,078.6
2,064.2
3,206.9
10,808.1
380.6
688.9
1.7
412.2
1,034.8
390.6
88.3
752.2
497.8
112.5
778.5
153.0
620.9
Diesel
Marine
147.8
1,305.9
574.4
852.5
826.2
630.5
993.3
1,498.1
2.5
27.1
1.4
1.4
9.1
5.2
58.0
9.6
1.0
1.7
13.3
6.6
111.7
5.2
118.0
7.0
837.4
109.5
25.2
101.4
34,699.8
1,935.3
67.6
31.6
3,334.9
350.5
29.2
322.9
960.2
306.8
47.8
1,287.7
269.3
37.9
164.7
43.8
1,217.1
Total
Mobile
706
2,379
1,310
2,252
2,737
10,401
2,088
3,047
1,171
2,259
1,042
1,989
1,445
2,073
11,238
1,015
1,011
6,851
1,177
3,085
2,919
1,476
3,214
435
12,014
1,724
2,964
2,106
126,737
27,820
18,781
26,747
9,593
4,088
848
4,372
16,513
6,337
1,053
4,813
13,775
2,050
1 1 ,244
11,579
8,314
LM
Percent
64.9%
55.3%
50.9%
52.8%
57.8%
13.6%
56.0%
81 .9%
15.4%
1 .5%
13.4%
24.7%
3.2%
21 .7%
8.1%
2.6%
19.6%
26.6%
40.8%
86.7%
37.6%
37.1%
34.3%
1 .6%
32.8%
50.5%
25.9%
77.4%
33.8%
14.4%
17.4%
40.5%
38.7%
25.4%
3.6%
16.8%
12.1%
1 1 .0%
12.9%
42.4%
5.6%
7.3%
8.4%
1 .7%
22.1%
5-143
-------
Regulatory Impact Analysis
FIPS
34019
34023
34025
34027
34029
34031
34035
34037
34039
36005
36047
36059
36061
36071
36081
36085
36087
36103
36119
10003
24015
24029
24031
34005
34007
34011
34015
34021
34033
42017
42029
42045
42101
4013
4021
6019
6029
6031
6039
6047
6077
6099
6107
53029
53033
53035
MSA
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Phoenix
Phoenix
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
Seattle
Seattle
Seattle
County
Hunterdon
Middlesex
Monmouth
Morris
Ocean
Passaic
Somerset
Sussex
Union
Bronx
Kings
Nassau
New York
Orange
Queens
Richmond
Rockland
Suffolk
Westch ester
New Castle
Cecil
Kent
Montgomery
Burlington
Camden
Cumberland
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Philadelphia
Maricopa
Pinal
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
Island
King
Kitsap
ST
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
DE
MD
MD
MD
NJ
NJ
NJ
NJ
NJ
NJ
PA
PA
PA
PA
AZ
AZ
CA
CA
CA
CA
CA
CA
CA
CA
WA
WA
WA
2020 NOx
Diesel
Locomotive
218.2
393.0
216.0
149.1
13.6
139.0
368.6
40.5
278.8
4.3
0.0
0.0
0.0
270.9
2.0
0.0
219.1
0.0
0.0
803.4
213.9
1.8
627.6
0.0
111.6
23.4
38.0
133.5
9.3
65.3
304.0
125.2
215.5
3,043.5
1,689.8
596.5
2,751.1
72.7
652.3
574.3
980.7
401.8
905.5
0.0
935.0
0.0
Diesel
Marine
14.0
235.8
617.7
22.5
500.0
21.8
0.7
26.7
880.2
170.4
1,397.7
506.2
980.8
70.5
1,679.8
1,942.3
19.6
1,342.6
117.2
2,069.6
56.2
53.8
15.6
963.9
385.6
1,063.5
520.5
119.1
315.8
40.8
6.8
4,798.6
8,420.9
33.6
7.5
38.7
14.4
1.4
10.6
30.5
496.4
14.8
10.6
1,709.1
4,874.1
54.6
Total
Mobile
2,859
9,099
8,620
6,081
6,071
5,226
3,670
1,901
7,151
8,855
18,231
11,407
31,145
6,487
22,109
4,992
2,500
14,755
7,870
11,598
2,142
541
12,024
6,299
7,049
3,128
6,743
5,604
1,442
6,119
5,242
12,519
28,921
36,074
4,626
9,566
11,518
1,747
2,530
3,697
7,856
4,881
5,493
2,406
26,130
2,268
LM
Percent
8.1%
6.9%
9.7%
2.8%
8.5%
3.1%
10.1%
3.5%
16.2%
2.0%
7.7%
4.4%
3.1%
5.3%
7.6%
38.9%
9.6%
9.1%
1 .5%
24.8%
12.6%
10.3%
5.3%
15.3%
7.1%
34.8%
8.3%
4.5%
22.5%
1 .7%
5.9%
39.3%
29.9%
8.5%
36.7%
6.6%
24.0%
4.2%
26.2%
16.4%
18.8%
8.5%
16.7%
71.1%
22.2%
2.4%
5-144
-------
Emission Inventory
FIPS
53045
53053
53061
53067
17027
17083
17119
17133
17163
29055
29071
29099
29113
29183
29189
29219
29510
MSA
Seattle
Seattle
Seattle
Seattle
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
County
Mason
Pierce
Snohomish
Thurston
Clinton
Jersey
Madison
Monroe
St. Clair
Crawford
Franklin
Jefferson
Lincoln
St. Charles
St. Louis
Warren
St. Louis
ST
WA
WA
WA
WA
IL
IL
IL
IL
IL
MO
MO
MO
MO
MO
MO
MO
MO
2020 NOx
Diesel
Locomotive
0.1
586.2
1,050.1
267.7
653.3
54.0
321.8
1,017.1
339.2
149.4
1,005.6
273.6
451.5
543.8
867.4
92.1
874.5
Diesel
Marine
28.7
4,359.7
779.7
317.1
3.4
473.6
257.9
415.5
491.8
1.7
63.6
424.7
172.5
393.2
489.5
61.3
6,486.7
Total
Mobile
541
12,505
7,046
3,088
1,223
1,104
3,094
2,060
3,360
640
2,226
2,736
1,301
3,393
12,921
595
13,766
LM
Percent
5.3%
39.6%
26.0%
18.9%
53.7%
47.8%
18.7%
69.5%
24.7%
23.6%
48.0%
25.5%
48.0%
27.6%
10.5%
25.8%
53.5%
5-145
-------
Regulatory Impact Analysis
Table 3-117 2030 Locomotive and Diesel Marine NOx Tons/Year and Percent of Total Mobile Sources
FIPS
13013
13015
13045
13057
13063
13067
13077
13089
13097
13113
13117
13121
13135
13139
13149
13151
13217
13223
13237
13247
13255
13297
24003
24005
24013
24025
24027
24510
1073
1117
1127
9007
25001
25005
25007
25009
25019
25021
25023
25025
25027
33011
33015
47065
MSA
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Atlanta
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Baltimore
Birmingham
Birmingham
Birmingham
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Boston
Chattanooga
County
Barrow
Bartow
Carroll
Cherokee
Clayton
Cobb
Coweta
DeKalb
Douglas
Fayette
Forsyth
Fulton
Gwinnett
Hall
Heard
Henry
Newton
Paulding
Putnam
Rockdale
Spalding
Walton
Anne Arundel
Baltimore
Carroll
Harford
Howard
Baltimore
Jefferson
Shelby
Walker
Middlesex
Barnstable
Bristol
Dukes
Essex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Hillsborough
Rockingham
Hamilton
ST
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
GA
MD
MD
MD
MD
MD
MD
AL
AL
AL
CT
MA
MA
MA
MA
MA
MA
MA
MA
MA
NH
NH
TN
2030 NOx
Diesel
Locomotive
186.5
665.4
180.2
0.0
350.2
918.9
462.3
426.2
165.0
119.7
0.0
1,251.8
318.0
185.4
0.0
472.0
53.5
391.3
10.3
75.8
20.4
64.1
285.6
896.2
145.3
242.3
347.0
1,142.1
4,081.7
1,005.0
648.6
105.1
232.0
435.3
0.0
567.2
0.0
679.2
362.5
360.0
1,368.9
35.8
27.0
1,305.7
Diesel
Marine
0.7
9.2
3.9
8.8
1.3
3.6
2.6
2.3
0.7
1.6
18.3
4.9
3.3
30.1
4.3
1.6
2.3
1.3
13.8
1.3
1.3
0.7
76.7
48.2
1.7
45.7
10.7
1,365.5
223.2
13.6
99.0
127.5
518.9
220.7
1,350.2
212.4
265.1
142.8
205.8
710.3
47.6
19.5
940.3
757.2
Total
Mobile
583
1,596
1,168
1,502
2,912
5,714
1,676
5,791
1,146
1,109
1,115
13,644
4,804
1,581
100
1,860
800
1,152
169
848
597
550
8,572
11,329
2,442
3,508
3,770
17,705
10,639
2,211
1,403
234
4,797
7,523
1,773
9,820
551
10,138
6,197
16,310
11,980
6,461
6,892
5,151
LM
Percent
32.1%
42.3%
15.8%
0.6%
12.1%
16.1%
27.7%
7.4%
14.5%
10.9%
1 .6%
9.2%
6.7%
13.6%
4.3%
25.5%
7.0%
34.1%
14.2%
9.1%
3.6%
1 1 .8%
4.2%
8.3%
6.0%
8.2%
9.5%
14.2%
40.5%
46.1%
53.3%
99.4%
15.7%
8.7%
76.2%
7.9%
48.1%
8.1%
9.2%
6.6%
1 1 .8%
0.9%
14.0%
40.1%
5-146
-------
Emission Inventory
FIPS
47115
47153
13047
13083
13295
17031
17043
17063
17089
17093
17097
17111
17197
18089
18127
18029
21015
21037
21117
39017
39025
39061
39165
39007
39035
39085
39093
39103
39133
39153
26093
26099
26115
26125
26147
26161
26163
48039
48071
48157
48167
48201
48291
48339
48473
21019
MSA
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chattanooga
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Chicago
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cincinnati
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Cleveland
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Detroit
Houston
Houston
Houston
Houston
Houston
Houston
Houston
Houston
Huntington
County
Marion
Sequatchie
Catoosa
Dade
Walker
Cook
DuPage
Grundy
Kane
Kendall
Lake
McHenry
Will
Lake
Porter
Dearborn
Boone
Campbell
Kenton
Butler
Clermont
Hamilton
Warren
Ashtabula
Cuyahoga
Lake
Lorain
Medina
Portage
Summit
Livingston
Macomb
Monroe
Oakland
St. Clair
Washtenaw
Wayne
Brazoria
Chambers
Fort Bend
Galveston
Harris
Liberty
Montgomery
Waller
Boyd
ST
TN
TN
GA
GA
GA
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
KY
KY
KY
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
Ml
Ml
Ml
Ml
Ml
Ml
Ml
TX
TX
TX
TX
TX
TX
TX
TX
KY
2030 NOx
Diesel
Locomotive
183.1
0.0
395.9
376.2
0.0
18,514.9
4,720.6
427.7
1,750.8
250.2
906.2
488.4
4,733.7
4,451.2
1,230.3
171.1
272.4
514.0
995.8
1,215.2
52.6
1,200.0
187.1
826.5
2,374.0
563.9
1,350.4
435.4
844.5
696.4
79.5
123.3
582.6
484.2
234.3
135.7
1,061.8
606.1
34.6
841.8
483.0
2,459.9
926.1
721.7
210.1
355.3
Diesel
Marine
150.6
0.0
0.3
0.0
0.3
5,645.1
6.5
163.2
4.6
0.4
955.2
7.6
124.5
562.4
477.1
569.5
856.3
592.5
295.2
2.2
1,124.0
3,327.7
4.2
4,523.2
3,348.9
800.5
2,952.3
2.7
11.2
7.8
2.5
156.2
234.6
119.1
559.6
1.7
292.0
6,200.9
213.6
4.3
14,191.0
36,874.9
78.5
12.6
1.9
457.1
Total
Mobile
932
56
830
699
438
63,116
10,269
1,168
3,281
641
6,310
1,548
7,002
12,715
4,520
1,694
3,615
2,128
2,456
2,901
3,076
12,598
1,261
10,335
17,334
3,676
8,584
1,508
2,012
3,944
1,589
6,116
2,409
10,112
4,539
3,199
21,886
13,541
964
3,437
27,937
91,005
1,679
3,561
497
1,606
LM
Percent
35.8%
0.0%
47.8%
53.8%
0.1%
38.3%
46.0%
50.6%
53.5%
39.1%
29.5%
32.0%
69.4%
39.4%
37.8%
43.7%
31 .2%
52.0%
52.6%
42.0%
38.2%
35.9%
15.2%
51 .8%
33.0%
37.1%
50.1%
29.1%
42.5%
17.9%
5.2%
4.6%
33.9%
6.0%
17.5%
4.3%
6.2%
50.3%
25.8%
24.6%
52.5%
43.2%
59.8%
20.6%
42.7%
50.6%
5-147
-------
Regulatory Impact Analysis
FIPS
21127
39001
39053
39087
39145
54011
54053
54099
18011
18057
18059
18063
18081
18095
18097
18109
18145
20091
20103
20121
20209
29037
29047
29049
29095
29107
29165
29177
6037
6059
6065
6071
6111
27003
27019
27037
27053
27123
27139
27163
9001
9005
34003
34013
34017
MSA
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Huntington
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Indianapolis
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Kansas City
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
Minneapolis
New York
New York
New York
New York
New York
County
Lawrence
Adams
Gallia
Lawrence
Scioto
Cabell
Mason
Wayne
Boone
Hamilton
Hancock
Hend ricks
Johnson
Madison
Marion
Morgan
Shelby
Johnson
Leave nworth
Miami
Wyandotte
Cass
Clay
Clinton
Jackson
Lafayette
Platte
Ray
Los Angeles
Orange
Riverside
San
Bernardino
Ventura
Anoka
Carver
Dakota
Hennepin
Ramsey
Scott
Washington
Fairfield
Litchfield
Bergen
Essex
Hudson
ST
KY
OH
OH
OH
OH
WV
WV
WV
IN
IN
IN
IN
IN
IN
IN
IN
IN
KS
KS
KS
KS
MO
MO
MO
MO
MO
MO
MO
CA
CA
CA
CA
CA
MN
MN
MN
MN
MN
MN
MN
CT
CT
NJ
NJ
NJ
2030 NOx
Diesel
Locomotive
310.0
10.5
92.3
335.2
749.9
775.3
174.8
981.9
175.6
6.6
136.6
486.8
37.8
440.3
845.5
17.2
195.8
1,793.4
460.0
2,627.2
969.7
534.4
980.2
0.0
3,078.5
748.8
730.6
1,515.9
8,037.8
2,064.0
3,176.5
10,729.1
379.6
677.4
1.7
405.5
1,018.8
384.3
86.9
740.1
484.0
114.5
756.3
146.0
596.4
Diesel
Marine
148.8
1,313.4
577.8
857.5
831.1
634.9
1,000.4
1,507.4
2.7
29.4
1.6
1.6
9.9
5.6
62.9
10.4
1.1
1.8
13.6
7.1
112.5
5.7
120.2
7.6
843.5
111.3
26.2
102.4
34,907.8
1,951.1
73.4
34.3
3,359.2
359.0
31.1
330.0
979.0
313.5
50.7
1,300.7
285.7
41.2
167.5
44.6
1,227.0
Total
Mobile
704
2,628
1,377
2,351
2,788
13,900
2,292
3,047
922
1,804
816
1,616
1,158
1,721
9,848
785
797
5,960
1,012
2,928
2,648
1,248
2,864
320
10,916
1,515
2,855
1,995
110,332
22,503
12,138
20,287
8,627
3,678
683
3,860
15,108
5,585
871
4,730
13,975
2,010
11,281
13,693
1 1 ,022
LM
Percent
65.2%
50.4%
48.7%
50.7%
56.7%
10.1%
51.3%
81.7%
19.3%
2.0%
16.9%
30.2%
4.1%
25.9%
9.2%
3.5%
24.7%
30.1%
46.8%
90.0%
40.9%
43.3%
38.4%
2.4%
35.9%
56.8%
26.5%
81.1%
38.9%
17.8%
26.8%
53.1%
43.3%
28.2%
4.8%
19.1%
13.2%
12.5%
15.8%
43.1%
5.5%
7.7%
8.2%
1 .4%
16.5%
5-148
-------
Emission Inventory
FIPS
34019
34023
34025
34027
34029
34031
34035
34037
34039
36005
36047
36059
36061
36071
36081
36085
36087
36103
36119
10003
24015
24029
24031
34005
34007
34011
34015
34021
34033
42017
42029
42045
42101
4013
4021
6019
6029
6031
6039
6047
6077
6099
6107
53029
53033
53035
MSA
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Philadelphia
Phoenix
Phoenix
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
San Joaquin
Seattle
Seattle
Seattle
County
Hunterdon
Middlesex
Monmouth
Morris
Ocean
Passaic
Somerset
Sussex
Union
Bronx
Kings
Nassau
New York
Orange
Queens
Richmond
Rockland
Suffolk
Westch ester
New Castle
Cecil
Kent
Montgomery
Burlington
Camden
Cumberland
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Philadelphia
Maricopa
Pinal
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
Island
King
Kitsap
ST
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NJ
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
DE
MD
MD
MD
NJ
NJ
NJ
NJ
NJ
NJ
PA
PA
PA
PA
AZ
AZ
CA
CA
CA
CA
CA
CA
CA
CA
WA
WA
WA
2030 NOx
Diesel
Locomotive
210.5
377.1
196.7
138.6
12.6
129.1
358.4
41.2
265.7
4.3
0.0
0.0
0.0
263.2
1.9
0.0
215.1
0.0
0.0
781.2
210.9
1.8
593.4
0.0
104.7
23.8
36.9
131.1
9.4
63.2
290.2
120.5
213.8
3,019.1
1,660.1
590.6
2,741.2
71.7
644.9
573.0
974.8
398.9
898.7
0.0
919.1
0.0
Diesel
Marine
15.2
238.9
637.0
24.4
539.0
23.6
0.8
29.0
885.6
172.6
1,407.8
516.6
987.0
72.3
1,692.5
1,955.3
21.3
1,408.8
121.2
2,083.0
59.2
57.6
16.1
971.5
388.6
1,083.2
525.2
120.3
320.5
43.1
7.4
4,827.0
8,470.2
36.5
8.1
42.0
15.7
1.5
11.5
33.1
501.1
16.0
11.5
1,720.9
4,923.0
59.2
Total
Mobile
2,703
10,943
8,926
5,958
6,186
5,198
3,620
1,794
8,205
9,872
23,002
11,386
17,781
6,601
24,125
6,930
2,459
14,851
8,399
12,157
2,059
506
12,274
6,198
7,322
3,125
7,922
5,616
1,393
6,003
5,004
13,735
31,412
18,989
4,001
5,860
7,256
902
1,488
2,108
5,322
2,978
3,414
2,318
23,930
1,921
LM
Percent
8.4%
5.6%
9.3%
2.7%
8.9%
2.9%
9.9%
3.9%
14.0%
1 .8%
6.1%
4.5%
5.6%
5.1%
7.0%
28.2%
9.6%
9.5%
1 .4%
23.6%
13.1%
1 1 .7%
5.0%
15.7%
6.7%
35.4%
7.1%
4.5%
23.7%
1 .8%
5.9%
36.0%
27.6%
16.1%
41 .7%
10.8%
38.0%
8.1%
44.1%
28.7%
27.7%
13.9%
26.7%
74.2%
24.4%
3.1%
5-149
-------
Regulatory Impact Analysis
FIPS
53045
53053
53061
53067
17027
17083
17119
17133
17163
29055
29071
29099
29113
29183
29189
29219
29510
MSA
Seattle
Seattle
Seattle
Seattle
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
St. Louis
County
Mason
Pierce
Snohomish
Thurston
Clinton
Jersey
Madison
Monroe
St. Clair
Crawford
Franklin
Jefferson
Lincoln
St. Charles
St. Louis
Warren
St. Louis
ST
WA
WA
WA
WA
IL
IL
IL
IL
IL
MO
MO
MO
MO
MO
MO
MO
MO
2030 NOx
Diesel
Locomotive
0.1
576.1
1,033.3
266.9
645.5
53.2
312.6
1,008.1
328.1
149.3
988.2
269.4
444.6
535.5
853.1
90.7
880.1
Diesel
Marine
30.6
4,394.7
793.9
322.4
3.7
476.4
259.6
417.9
494.8
1.9
64.9
428.0
174.7
399.3
494.2
62.4
6,524.3
Total
Mobile
449
12,254
6,039
2,775
1,056
1,134
2,469
2,049
2,832
526
1,850
2,271
1,179
2,847
11,003
503
14,654
LM
Percent
6.8%
40.6%
30.3%
21 .2%
61.4%
46.7%
23.2%
69.6%
29.1%
28.7%
56.9%
30.7%
52.5%
32.8%
12.2%
30.4%
50.5%
5-150
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Emission Inventory
References
1 "Calculation of Age Distributions in the Nonroad Model: Growth and Scrappage," EPA420-R-05-018,
December 2005. Docket Document EPA-HQ-OAR-2003-0190-0388. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2005/420r05018.pdf
2 "Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling Compression-Ignition," EPA420-P-
04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
3 "Final Regulatory Impact Analysis: Control of Emissions from Nonroad Diesel Engines, Chapter 3" EPA420-
R-04-007, May 2004. Docket Document EPA-HQ-OAR-2003-0012-1032. The RIA is also available online at
http://epa.gov/nonroad-diesel/2004fr/420r04007.pdf
4 "Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling Compression-Ignition," EPA420-P-
04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
5 "Final Regulatory Impact Analysis: Control of Emissions from Nonroad Diesel Engines, Chapter 3" EPA420-
R-04-007, May 2004. Docket Document EPA-HQ-OAR-2003-0012-1032. The RIA is also available online at
http://epa.gov/nonroad-diesel/2004fr/420r04007.pdf
6 "Conversion Factors for Hydrocarbon Emission Components," EPA420-R-05-015, December 2005. Docket
Document EPA-HQ-OAR-2003 -01 90-041 1. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2005/420r05015.pdf
7 "Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling Compression-Ignition," EPA420-P-
04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
8 "Final Regulatory Impact Analysis: Control of Emissions from Nonroad Diesel Engines, Chapter 3" EPA420-
R-04-007, May 2004. Docket Document EPA-HQ-OAR-2003-0012-1032. The RIA is also available online at
http://epa.gov/nonroad-diesel/2004fr/420r04007.pdf
9 "National Scale Modeling of Air Toxics for the Mobile Source Air Toxics Rule; Technical Support Document,"
EPA-454/R-06-002, January 2006. Docket Document EPA-HQ-OAR-2003-0190-0427. The report is available
online at http://www.epa.gov/otaq/regs/toxics/454r06002.pdf
10 "Final Regulatory Impact Analysis: Control of Emissions from Marine Diesel Engines, Chapter 5" EPA-420-
R-99-026, November 1999. Docket Document EPA-HQ-OAR-2004-0308-0003. The RIA is also available
online at http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/ria.pdf
11 Telephone conversation with Doug Scheffler, American Waterways Operators, May 4, 2006. Docket
Document EPA-HQ-OAR-2003 -0 190-03 89 .
12 "Annual Energy Outlook 2006," Energy Information Administration, Report #:DOE/EIA-0383(2006),
February 2006, Table A7. Docket Document EPA-HQ-OAR-2003-0190-0386. The report is available online at
http://www.eia.doe.gov/oiaf/archive/aeo06/pdf/0383(2006).pdf
5-151
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Regulatory Impact Analysis
13 "Final Regulatory Impact Analysis: Control of Emissions from Marine Diesel Engines, Chapter 5" EPA-420-
R-99-026, November 1999. Docket Document EPA-HQ-OAR-2004-0308-0003. The RIA is also available
online at http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/ria.pdf
14 "Exhaust and Crankcase Emission Factors for Nonroad Engine ModelingCompression-Ignition," EPA420-
P-04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
15
Swedish Methodology for Environmental Data (SMED), "Methodology for calculating emissions from ships:
1. Update of emission factors," November 4, 2004. Docket Document EPA-HQ-OAR-2003-0190-0418.
16 Eastern Research Group, Inc. (ERG) 2007. Category 1 and 2 Marine Propulsion Engine Activity,
Port/Underway Splits and Category 2 County Allocation. Prepared for U.S Environmental Protection Agency,
Office of Transportation and Air Quality. Docket Document EPA-HQ-OAR-2003-0190-0423.
17 American Public Transportation Association (APTA), "2006 Public Transportation Fact Book," Ferryboat
chapter. Docket Document EPA-HQ-OAR-2003 -0190-073 9.
18 American Waterways Operators, Letter from Jennifer A. Carpenter to Docket, July 2, 2007. Docket
Document EPA-HQ-OAR-2003-0190-0574.
19 "Commercial Marine Emissions Inventory for EPA Category 2 and 3 Compression Ignition Marine Engines in
the United States and Continental Waterways," EPA420-R-98-020, August, 1998. Docket Document EPA-HQ-
OAR-2003-0190-0417. The report is also available online at
http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/r98020.pdf
20 "Final Regulatory Impact Analysis: Control of Emissions from Marine Diesel Engines, Chapter 5" EPA-420-
R-99-026, November 1999. Docket Document EPA-HQ-OAR-2004-0308-0003. The RIA is also available
online at http://www.epa.gov/otaq/regs/nonroad/marine/ci/fr/ria.pdf
21 EPA, "Control of Emissions of Air Pollution From Nonroad Diesel Engines," 63 FR 56967, October 23, 1998.
Docket Document EPA-HQ-OAR-2005-0119-0002. The Federal Register notice is also available online at
http://www.epa.gov/fedrgstr/EPA-AIR/1998/October/Day-23/a24836.htm
22 "Exhaust and Crankcase Emission Factors for Nonroad Engine ModelingCompression-Ignition," EPA420-
P-04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
23 Ibid.
24 Ibid.
25 "National Scale Modeling of Air Toxics for the Mobile Source Air Toxics Rule; Technical Support
Document," EPA-454/R-06-002, January 2006. Docket Document EPA-HQ-OAR-2003-0190-0427. The report
is available online at http://www.epa.gov/otaq/regs/toxics/454r06002.pdf
26 "Inland River Record Sample Analysis," U.S. EPA, Memorandum from Amy Kopin to Docket No. EPA-HQ-
OAR-2003-0190, January 11, 2008. Docket Document EPA-HQ-OAR-2003-0190-0847.
27 "NONROAD2005 CI Marine NPRM," U.S. EPA. Version used to estimate emissions for the recreational
marine and less than 37 kW commercial marine categories. Docket Document EPA-HQ-OAR-2003-0190-0385.
5-152
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Emission Inventory
28 "Nonroad Engine Growth Estimates," NR-008c, EPA420-P-04-008, April 2004. Docket Document EPA-HQ-
OAR-2003-0190-0387. The report is available online at
http://www.epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04008.pdf
29 "Calculation of Age Distributions in the Nonroad Model: Growth and Scrappage," EPA420-R-05-018,
December 2005. Docket Document EPA-HQ-OAR-2003-0190-0388. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2005/420r05018.pdf
30 "Exhaust and Crankcase Emission Factors for Nonroad Engine ModelingCompression-Ignition," EPA420-
P-04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
31 "Final Regulatory Impact Analysis: Control of Emissions from Nonroad Diesel Engines, Chapter 3" EPA420-
R-04-007, May 2004. Docket Document EPA-HQ-OAR-2003-0012-1032. The RIA is also available online at
http://epa.gov/nonroad-diesel/2004fr/420r04007.pdf
32 Ibid.
33 "National Scale Modeling of Air Toxics for the Mobile Source Air Toxics Rule; Technical Support
Document," EPA-454/R-06-002, January 2006. Docket Document EPA-HQ-OAR-2003-0190-0427. The report
is available online at http://www.epa.gov/otaq/regs/toxics/454r06002.pdf
34 EPA, "Control of Emissions of Air Pollution From Nonroad Diesel Engines," 63 FR 56967, October 23, 1998.
Docket Document EPA-HQ-OAR-2005-0119-0002. The Federal Register notice is also available online at
http://www.epa.gov/fedrgstr/EPA-AIR/1998/October/Day-23/a24836.htm
35 "Exhaust and Crankcase Emission Factors for Nonroad Engine ModelingCompression-Ignition," EPA420-
P-04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
36 Ibid.
37 Ibid.
38 "National Scale Modeling of Air Toxics for the Mobile Source Air Toxics Rule; Technical Support
Document," EPA-454/R-06-002, January 2006. Docket Document EPA-HQ-OAR-2003-0190-0427. The report
is available online at http://www.epa.gov/otaq/regs/toxics/454r06002.pdf
39 "Conversion Factors for Hydrocarbon Emission Components," EPA420-R-05-015, December 2005. Docket
Document EPA-HQ-OAR-2003-0190-0411. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2005/420r05015.pdf
40 "Exhaust and Crankcase Emission Factors for Nonroad Engine ModelingCompression-Ignition," EPA420-
P-04-009, April 2004. Docket Document EPA-HQ-OAR-2003-0190-0410. The report is available online at
http://epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
41 "Annual Energy Outlook 2006," Energy Information Administration, Report #:DOE/EIA-0383(2006),
February 2006, Table A7. Docket Document EPA-HQ-OAR-2003-0190-0386. The report is available online at
http://www.eia.doe.gov/oiaf/archive/aeo06/pdf/0383(2006).pdf
42 "Railroad Ten-Year Trends, 1995-2004", AAR 2205.
5-153
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Regulatory Impact Analysis
43 EPA, 2002 National Emissions Inventory (NEI). County-level fractions of locomotive and commercial marine
diesel emissions. Docket Document EPA-HQ-OAR-2003-0190-0412. NEI documentation is available online at
http://www.epa.gov/ttn/chief/net/2002inventory.html
44 Clean Air Interstate Rule (CAIR). Docket EPA-HQ-OAR-2003-0053. Documentation is also available online
at http://www.epa.gov/air/interstateairquality/index.html
5-154
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Technological Feasibility
CHAPTER 4: LOCOMOTIVE AND MARINE TECHNOLOGICAL FEASIBILITY
2
4.1 Overview of Emissions Standards and Emission Control Technologies 2
4.2 Emission Control Technologies for Remanufactured Engine Standards and for Tier
3 New Engine Interim Standards 4
4.2.1 Diesel Combustion and Pollutant Formation 6
4.2.2 Engine-out Emission Control 13
4.3 Feasibility of Tier 4 Locomotive and Marine Standards 23
4.3.1 Selective Catalytic Reduction (SCR) NOX Control Technology 24
4.3.2 PM and HC Exhaust Aftertreatment Technology 31
4.3.3 SCR and CDPF Packaging Feasibility 38
4.3.4 Mechanical Durability of Aftertreatment Components 40
4.3.5 Stakeholder Concerns Regarding Locomotive NOX Standard Feasibility 41
4.4 Feasibility of Marine NTE Standards 55
4.5 Lead Time 56
4.6 Conclusions 57
4-1
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Regulatory Impact Analysis
CHAPTER 4: Locomotive and Marine Technological Feasibility
In this chapter we describe in detail the analysis of emission control technologies we
used to develop the standards we are finalized in this rulemaking. Because of the range of
engines and applications we cover in this proposal, the standards span a range of emissions
levels. Correspondingly, we have identified a number of different emission control
technologies we expect will be used to meet these standards. These technologies range from
incremental improvements of existing engine components to highly advanced catalytic
exhaust aftertreatment systems.
We first summarize our current locomotive and marine diesel engine standards and
provide an overview of existing and future emission control technologies. We believe that
further improvements in existing technologies will be used to meet the standards for existing
engines that are remanufactured as new (i.e., Tier 0, 1, and 2 locomotives and marine engines
greater than 600 kW manufactured from 1973 through 2011). We then describe how
technologies similar to some of those already being implemented to meet our current and
upcoming heavy-duty highway and nonroad diesel engine emissions standards can be applied
to meet the standards for new engines (i.e., Tier 3). Throughout this chapter, we also address
many of the comments submitted by stakeholders concerning the feasibility, applicability,
performance, and durability of the emission control technologies we presented in the NPRM.
We conclude this section with a discussion of catalytic exhaust aftertreatment technologies
that we believe will be used to meet the Tier 4 standards.
All of our analyses in this chapter include how we expect these technologies to
perform throughout their useful life as well as how we believe they will be implemented
specifically into locomotive and marine applications. Note that much of this chapter's content
is based upon the performance of currently available emission control technologies and results
from testing that has already been completed. In most cases the already-published results
show that currently available emission control technologies can be implemented without
further improvements to meet the standards. In a few cases, we are projecting that further
improvements to these technologies will be made between now and the Tier 4 standards
implementation dates. These projected improvements will enable engine manufacturers to
meet the standards finalized in this rulemaking.
4.1 Overview of Emissions Standards and Emission Control Technologies
Our current locomotive and marine diesel engine standards have already decreased
NOX emissions from unregulated levels. For example, since 1997, NOX emissions standards
for diesel locomotive engines have been reduced from an unregulated level of about 13.5
g/bhp-hr to the current Tier 2 level of 5.5 g/bhp-hr - a 60% reduction when evaluated over the
locomotive line-haul duty cycle. Similar NOX reductions have been realized for Category 1 &
2 (Cl & C2) commercial marine diesel engines. Our Tier 1 marine standards are equivalent to
the International Maritime Organization's NOX regulation known as MARPOL Annex VI.
Beginning in 2004, these standards became mandatory for Cl & C2 Commercial vessels, and
were voluntary in prior years. Beginning in 2007, EPA Tier 2 standards for Cl & C2
Commercial vessels superseded these MARPOL-equivalent standards. For a high-speed
4-2
-------
Technological Feasibility
marine diesel engine, NOX emissions have been reduced from a Tier 1 level of 9.8 g/kW-hr to
7.5 g/kW-hr - a 23% reduction. While these reductions in locomotive and marine NOX
emissions are significant, they do not keep pace with the 90% NOX reduction (from 2.0 g/bhp-
hr to 0.2 g/bhp-hr) set forth in the 2007 Heavy-Duty Highway Rule.l Neither do these
reductions keep pace with the approximately 85% NOX reductions set forth in the Nonroad
Tier 4 Standards for 56 kW to 560 kW engines and for generator sets above 560 kW.2'3 In a
similar manner, locomotive and marine particulate matter (PM) emission reductions also lag
behind the Heavy-Duty Highway and Nonroad Tier 4 Rules. For line-haul and switcher
locomotives, a 67% reduction in PM already has been achieved in going from the Tier 0 to the
Tier 2 standards. On the marine side, PM emissions for Cl & C2 Commercial have been
reduced from essentially unregulated levels prior to May 2005, to a 0.2-0.4 g/kW-hr level for
Tier 2.A
In contrast, the 2007 Heavy-Duty Highway Rule set forth PM reductions of 90% -
from 0.1 g/bhp-hr to 0.01 g/bhp-hr. Similarly, post-2014 Nonroad Tier 4 PM emissions will
be reduced 85 to 95% compared to Tier 3 Nonroad PM emissions for 56 kW to 560 kW
01
engines and for generator sets above 560 kW. ' In the timeframe of the Tier 3 and 4
Locomotive Standards that we are proposing, NOX and PM emissions will continue to be a
serious threat to public health, and, on a percentage basis, the locomotive and marine
contributions to the nationwide inventory of these pollutants would continue to increase
relative to today's levels if current Tier 2 emission levels were maintained. Please refer to
Chapter 3 of the Regulatory Impact Analysis for a more detailed discussion of the
contribution of locomotive and marine emissions to the NOX and PM inventory.
To date, the Tier 0 through Tier 2 locomotive and Tier 1 through Tier 2 marine
emissions reductions have been achieved largely through engine calibration optimization and
engine hardware design changes (e.g. improved fuel injectors, increased injection pressure,
intake air after-cooling, combustion chamber design, injection timing, reduced oil
consumption, etc.) To achieve the Tier 3 PM emission standards we are proposing, further
reductions in lubricating oil consumption will be required. This will most likely be achieved
via improvements to piston, piston ring, and cylinder liner design, as well as improvements to
the crankcase ventilation system. To further reduce NOX and PM emission beyond Tier 3
levels, an exhaust aftertreatment approach will be necessary.
Selective catalytic reduction (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, European heavy-duty truck manufacturers are using this
technology to meet the Euro IV and Euro V limits. In the Category 2 and Category 3 marine
sector, at least 100 vessels are equipped with SCR systems to control NOx emissions.4 To a
lesser extent, SCR has been introduced on diesels in the U.S. market, but the applications
have been limited to marine ferryboat and stationary power generation demonstration projects
in California and several northeast states. However, by 2010, when 100% of the heavy-duty
1 Marine Tier 2 PM emission standards are dependent on an engine's volumetric displacement-per-cylinder.
4-3
-------
Regulatory Impact Analysis
diesel trucks are required to meet the NOX limits of the 2007 heavy-duty Highway Rule,
several heavy-duty truck engine manufacturers have indicated that they will use SCR
technology to meet these standards.5'6 While other promising NOx-reducing technologies
such as lean NOX catalysts, NOX adsorbers, and advanced combustion control continue to be
developed - and may be viable approaches to the standards we are proposing today - our
analysis projects that SCR will be the technology chosen by the locomotive and marine diesel
industries to meet the Tier 4 NOX standards we are proposing. For a complete review of these
other alternative NOX emission control technologies, please refer to the Regulatory Impact
Analysis from our Clean Air Nonroad diesel rule.7
The most effective exhaust aftertreatment used for diesel PM emission control is the
diesel particulate filter (DPF). More than a million light diesel vehicles that are OEM-
equipped with DPF systems have been sold in Europe, and over 200,000 DPF retrofits to
diesel engines have been conducted worldwide.8 Broad application of catalyzed diesel
particulate filter (CDPF) systems with greater than 90% PM control is beginning with the
introduction of 2007 model year heavy-duty diesel trucks in the United States. These systems
use a combination of both passive and active soot regeneration. Our analysis projects that
CDPF systems with a combination of passive and active backup regeneration will be the
primary technology chosen by the locomotive and marine diesel industries to meet the Tier 4
PM standards.
4.2 Emission Control Technologies for Remanufactured Engine Standards
and for Tier 3 New Engine Interim Standards
To meet the locomotive and marine remanufactured engine and Tier 3 standards, we
believe engine manufacturers will utilize incremental improvements of existing engine
components to reduce engine-out emissions. This will be accomplished primarily via
application of technology originally developed to meet our current and upcoming standards
for heavy-duty on-highway trucks and nonroad diesel equipment. This is especially true for
many of the Category 1 and Category 2 marine engines, which are based on nonroad engine
designs. This will allow introduction of technology originally developed to meet nonroad
Tier 3 and Tier 4 standards to be used to meet the Tier 3 marine standards. Table 4-1, Table
4-2 and Table 4-3 provide summaries of the technologies that we believe will be used meet
the remanufactured engine and Tier 3 new engine interim standards for switch locomotives,
line-haul locomotives and marine engines, respectively. The technologies described in Tables
4-1 and 4-2 can also be applied to remanufactured marine engines >600 kW.
4-4
-------
Technological Feasibility
Table 4-1: Technologies for switch locomotive standards through Tier 3
Year
2010
2010
2013
2011
Standard
TO-
Remanufactured
Tl-
Remanufactured
T2-
Remanufactured
T3
NOX
(g/bhp-hr)
11.8
11.0
8.1
5.0
PM
(g/bhp-hr)
0.26
0.26
0.13
0.10
Technology added to engine
New power assemblies to improve oil
consumption, improved mechanical unit
injectors
New power assemblies to improve oil
consumption, electronic unit injection, new unit
injector cam profile
For high-speed engines: Same as Tier 3
nonroad engines
For medium-speed engines: Further
improvements to power assembly and closed
crankcase ventilation system to reduce oil
consumption; new turbocharger (t/c), engine
calibration, and unit injector cam profile
For high-speed engines: Same as Tier 3
nonroad engines
For medium-speed engines: Further
improvements to power assembly and CCV to
reduce oil consumption, high pressure common
rail injection with post-injection PM clean-up,
injection timing retard, new t/c
Table 4-2: Technologies for Line Haul Locomotive Standards up to Tier 3
Year
2010
(2008 if
available)
2010
(2008 if
available)
2013
2012
Standard
TO-
Remanufactured
Tl-
Remanufactured
T2-
Remanufactured
T3
NOX
(g/bhp-
hr)
7.4
7.4
5.5
5.5
PM
(g/bhp-
hr)
0.22
0.22
0.10
0.10
Technology added to engine
New power assemblies to improve oil
consumption, improved mechanical unit
injectors or switch to electronic unit injection,
new t/c
New power assemblies to improve oil
consumption, electronic unit injection, new unit
injector cam profile, new t/c
Further improvements to power assembly and
CCV to reduce oil consumption, electronic unit
injection or high pressure common rail injection
Further improvements to power assembly to
reduce oil consumption, electronic unit injection
or high pressure common rail injection
4-5
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Regulatory Impact Analysis
Table 4-3: Technologies for Marine Category 1 and Category 2 to meet Tier 3 Standards
Year
2009-
2014
2012-
2018
2013
2012
Standard
Category 1 Tier
3 Marine
(< 75 kW)
Category 1 Tier
3 Marine
(75-3700 kW)
Category 2 Tier
3 Marine
7-15 liters/cyl.
Category 2 Tier
3 Marine
15-30 liters/cyl.
HC+NOX
(g/bhp-
hr)
3.5-5.6
4.0-4.3
5.5
6.5-8.2
PM (g/bhp-
hr)
0.22-0.33
0.07-0.11
0.10
0.20
Technology added to engine
Same engine-out NOX technologies as Tier 4
nonroad with no Tier 4 PM aftertreatment
technologies
Recalibration on nonroad Tier 4 engines
without aftertreatment
Same engine-out NOX technologies as pre-
2014, non-generator-set, Tier 4 nonroad
with no Tier 4 PM aftertreatment technologies
Further improvements to power assembly to
reduce oil consumption, electronic unit
injection or high pressure common rail
injection, new t/c
In section 4.2.1.1 we will describe some of the fundamentals of diesel combustion and
pollutant formation. In section 4.2.2 we describe the manner in which engine-out emissions
can be controlled in order to meet the locomotive and marine remanufactured engine
standards and Tier 3 standards.
4.2.1 Diesel Combustion and Pollutant Formation
In this section we describe the mechanisms of pollutant formation. In order to lay the
foundation for this discussion, we begin with a review of diesel combustion, especially as it is
related to 2-stroke cycle and 4-stroke cycle diesel engine operation. We describe both of
these types of diesel engine operation because both 2-stroke and 4-stroke engines are used in
locomotive and marine applications. We then describe NOX, PM, HC, and CO formation
mechanisms.
4.2.1.1 Diesel Combustion
Category 1 marine diesel engines operate on a four-stroke cycle. The larger
displacement Category 2 marine diesel engines and locomotive diesel engines operate on
either a two-stroke cycle or a four-stroke cycle. The four-stroke cycle consists of an intake
stroke, a compression stroke, an expansion (also called the power or combustion) stroke, and
an exhaust stroke. The two-stroke cycle combines the intake and exhaust functions by using
forced cylinder scavenging. Figure 1 provides an overview and brief comparison of the two-
stroke and four-stroke cycles used by marine and locomotive diesel engines.
The diesel combustion event provides the energy for piston work. An example of the
relationship between the different phases of diesel combustion and the net energy released
from the fuel is shown in Figure 4.2. Combustion starts near the end of compression and
continues through a portion of the expansion stroke. Near the end of the piston compression
stroke, fuel is injected into the cylinder at high pressure and mixes with the contents of the
cylinder (air + any residual combustion gases). This period of premixing is referred to as
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Technological Feasibility
ignition delay. Ignition delay ends when the premixed cylinder contents self-ignite due to the
high temperature and pressure produced by the compression stroke in a relatively short,
homogenous, premixed combustion event. Immediately following premixed combustion,
diesel combustion becomes primarily non-homogeneous and diffusion-controlled. The rate of
combustion is limited by the rate of fuel and oxygen mixing. During this phase of
combustion, fuel injection continues creating a region that consists of fuel only. The fuel
diffuses out of this region and air is entrained into this region creating an area where the fuel
to air ratio is balanced (i.e., near stoichiometric conditions) to support combustion. The fuel
burns primarily in this region. One way to visualize this is to roughly divide the cylinder
contents into fuel-rich and fuel-lean sides of the reaction-zone where combustion is taking
place as shown in Figure 3. As discussed in the following subsections, the pollutant rate of
formation in a diesel engine is largely defined by these combustion regions and how they
evolve during the combustion process.9
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Regulatory Impact Analysis
Figure 1: A comparison of 2 complete revolutions of the four-stroke (top) and two-stroke diesel
combustion cycles. Note that the two-stroke cycle relies on intake air-flow to scavenge the exhaust
products from the cylinder. In the case of uniflow scavenged two-stroke diesel engines, cylinder
scavenging is assisted by the use of a centrifugal or positive displacement blower to pressurize the intake
ports located on the sides of the cylinder. Exhaust exits the cylinder through cam-actuated poppet valves
in the cylinder head. Four-stroke diesel engines are the predominant type of Category 1 marine engine.
Both four-stroke and uniflow-scavenged two-stroke diesel engines are used for Category 2 marine and
locomotive applications.
fuel injected near the top of
the compression strol
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Technological Feasibility
Figure 2: An idealized example of the net apparent rate of combustion heat release (derived from high-
speed cylinder pressure measurements) for a direct injection diesel engine with indication of the major
events and phases of combustion.
-10
10
20
30
40
TDC
Degrees of Crankshaft Angle Rotation
Figure 3: An idealized physical schematic of the diesel combustion process.
Piston Bowl
Piston Crown
- Combustion and
Partial-Combustion
^ Products
Fuel Lean
Top View
Profile, Partial Cut-away
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Regulatory Impact Analysis
4.2.1.2 NOX Emissions
Nitrogen oxides (NOX) are formed in diesel engines by the oxidation of molecular
nitrogen (TS^) in the stoichiometric combustion regions of the diffusion-controlled and
premixed diesel combustion phases, described in the previous section. During the premixed
phase of combustion, ignition and flame propagation occurs at high temperatures and at near
stoichiometric mixtures of fuel and air. During diffusion-controlled combustion, the reaction
zone is also near stoichiometric conditions. At the high temperatures present during premixed
combustion or in the diffusion-controlled combustion reaction zone, a fraction of the nitrogen
and oxygen can dissociate, forming radicals which then combine through a series of reactions
to form nitric oxide (NO), the primary NOX constituent. Nitrogen dioxide (NC^), the other
major NOX constituent, is formed from oxidation of NO in the flame region. NO2 formed
during combustion rapidly decomposes to NO and molecular oxygen unless the reaction is
quenched by mixing with cooler cylinder contents. Engine-out emissions of NO are typically
80% or more of total NOX from direct injection diesel engines. The NOX formation rate has a
strong exponential relationship to temperature. Therefore, high temperatures result in high
NOX formation rates.9'10 Any changes to engine design that can lower the peak temperature
realized during combustion, the partial pressures of dissociated nitrogen and oxygen, or the
duration of time at these peak temperatures can lower NOX emissions. Most of the engine-out
NOX emission control technologies discussed in the following sections reduce NOX emissions
by reducing the peak combustion temperatures while balancing impacts on PM emissions,
fuel consumption and torque output.
4.2.1.3 PM Emissions
Particulate matter (PM) emitted from diesel engines is a multi-component mixture
composed chiefly of elemental carbon (or soot), semi-volatile organic carbon compounds,
sulfate compounds (primarily sulfuric acid) with associated water, and trace quantities of
metallic ash.
During diffusion-controlled combustion, fuel diffuses into a reaction zone and burns.
Products of combustion and partial products of combustion diffuse away from the reaction
zone where combustion occurs. At temperatures above 1300 K, fuel compounds on the fuel-
rich side of the reaction zone can be pyrolized to form elemental carbon particles11. Most of
the elemental carbon formed by fuel pyrolysis (80% to 98%) is oxidized during later stages of
combustion.12'13 The remaining elemental carbon agglomerates into complex chain-aggregate
soot particles and leaves the engine as a component of PM emissions.
From this description, the formation of elemental carbon particles during combustion
and emission as PM following the combustion event can be summarized as being dependent
upon three primary factors:
1. Temperature
2. Residence time
3. Availability of oxidants
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Technological Feasibility
Thus, in-cylinder control of elemental carbon PM is accomplished by varying engine
parameters that affect these variables while balancing the resultant effects on NOX emissions
and torque output.
The combinations of organic compounds (volatile and semi-volatile) that contribute to
PM are referred to as the volatile organic fraction (VOF), the soluble organic fraction (SOF),
or as organic carbon PM, depending upon the analytical procedure used to measure the
compounds. Organic carbon PM primarily consists of lubricating oil and partial combustion
products of lubricating oil. Some of the higher molecular weight fuel compounds from
unburned or partially burned diesel fuel also contribute to organic carbon PM. Oil can be
entrained into the cylinder contents from cylinder liner surfaces as they are uncovered by the
piston and by leakage into the cylinder past the valve stems. Uniflow-scavenged two-stroke
diesel engines typically have somewhat higher oil consumption and organic carbon PM
emissions in part due to the lubricating oil entrained into the scavenging flow from around the
intake ports in the cylinder wall. Compliance with the closed crankcase ventilation provisions
in the Tier 0 and later locomotive and Tier 2 marine standards has typically been
accomplished by using coarse filtration to separate a fraction of the oil aerosol from the
crankcase flow and then entraining the crankcase flow directly into the exhaust downstream
of the turbocharger exhaust turbine (Figure 4). Incomplete separation of the oil aerosol from
the crankcase flow can increase the amount of lubricating oil directly entrained into the
exhaust with subsequent formation of organic carbon PM.
Both organic carbon and sulfate PM are formed after cooling and air-dilution of the
exhaust. Sulfur dioxide (802) is formed via combustion of sulfur compounds from the fuel
and lubricating oil burned during combustion. In the absence of post-combustion catalytic
aftertreatment of the exhaust, approximately 1 to 3 % of fuel sulfur is oxidized to ionic sulfate
(SOs") and upon further cooling is present primarily as a hydrated sulfuric acid aerosol. For
example, sulfate PM currently accounts for approximately 0.06 to 0.08 g/bhp-hr over the line-
haul cycle for locomotive engines using 3000 ppm sulfur nonroad diesel fuel.
Diesel oxidation catalysts (DOC) and catalyzed diesel particulate filters (CDPF) using
platinum catalysts can oxidize the organic compounds thereby lowering PM emissions but
they can also oxidize 50% or more of the SO2 emissions to sulfate PM, depending on the
exhaust temperature and the platinum content of the catalyst formulation that is used.
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Regulatory Impact Analysis
Figure 4: Crankcase ventilation system for a medium speed locomotive diesel engine. An eductor uses
compressed air to draw crankcase gases through a coarse coalescing filter (top left photo). The outlet of
the crankcase ventilation system can be clearly seen from the outlet of the locomotive's exhaust stack (top
right photo). The bottom photo shows tubing from a crankcase ventilation system removed from
downstream of a similar coarse coalescing filter. There was considerable wetting of the inner wall of the
tubing with lubricating oil.
Turbocharger
turbine outlet
Crankcase flow vented to exhaust stack
4.2.1.4 HC Emissions
Hydrocarbon (HC) emissions from diesel engines are generally much lower compared
to other mobile sources due to engine operation that, on a bulk-cylinder-content basis, is
significantly fuel-lean of the stoichiometric air-to-fuel ratio. HC emissions primarily occur
due to fuel and lubricant trapped in crevices (e.g., at the top ring land and the injector sac)
which prevents sufficient mixing with air for complete combustion. Fuel related HC can also
be emitted due to "over mixing" during ignition delay, a condition where fuel in the induced
swirl flow has mixed beyond the lean flammability limit. Higher molecular weight HC
compounds adsorb to soot particles or nucleate and thus contribute to the organic carbon PM.
Lower molecular weight HC compounds are primarily emitted in the gas phase. During
engine start-up under cold ambient conditions or following prolonged engine idling, fuel-
related HC can be emitted as a concentrated, condensed aerosol ("white smoke").
4.2.1.5 CO Emissions
Carbon monoxide emissions (CO) from diesel engines are generally low compared to
other mobile sources due to engine operation that, on a bulk-cylinder-content basis, is
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Technological Feasibility
significantly fuel-lean of the stoichiometric air-to-fuel ratio. Catalytic emission controls that
effectively oxidize PM constituents and HC emissions are also effective for oxidation of CO,
reducing CO emissions to even lower levels.
4.2.2 Engine-out Emission Control
Control of diesel emissions via modification of combustion processes is often
characterized by trade-offs in NOX emission control vs. other parameters such as PM
emissions, fuel consumption, and lubricating oil soot loading. For example, lower oxygen
content (lowering the air-to-fuel ratio) lowers NOX formation but increases PM formation.
Advanced (earlier) injection timing reduces PM emissions but increases NOX formation.
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 fuel
injection systems and improved turbocharging can improve these tradeoffs, allowing for
reduced emisssions of both NOX and PM.
4.2.2.1 Ultra Low Sulfur Diesel Fuel
We estimate that the use of ultra low sulfur diesel (ULSD) fuel (<15 ppm S) will
reduce sulfate PM emissions from locomotive and marine engines by approximately 0.06 to
0.08 g/bhp-hr, as compared to PM emissions when -3000 ppm S fuel is used. The use of
ULSD fuel also reduces depletion of TEN in the oil and substantially reduces condensation of
acidic aerosols within cooled exhaust gas recirculation systems (see section 4.2.2.5). In
addition to the direct sulfate PM emissions reductions realized through the use of ULSD, this
fuel is also necessary to enable the use of advanced catalytic exhaust aftertreatment
technologies, as discussed later in this chapter. While we describe the emission reductions
due to the use of lower sulfur diesel fuel here, we should be clear that these reductions are part
of our baseline emissions inventory because ULSD is already in place and this rule does not
change the fuel sulfur standard.
4.2.2.2 Turbocharger Improvements
The majority of Category 1 and 2 marine diesel engines and Tier 0 and later
locomotive diesel engines are equipped with turbocharging and aftercooling. Tier 0 and later
two-stroke locomotive engines (and some Tier 1 and later marine engines) are equipped with
a hybrid mechanical centrifugal supercharger/exhaust turbocharger system. This system is
gear driven up to approximately the notch 6 operating mode and is exhaust driven at higher
operating modes or higher numbered notches (e.g., notches 7 and 8). This arrangement helps
to provide sufficient scavenging boost at lower notch settings where there is insufficient
exhaust energy for the exhaust turbine to drive the compressor. Significant improvements
have been made in recent years in matching turbocharger turbine and compressor
performance to the highway, nonroad, marine, and locomotive diesel engines. Improvements
to turbochargers and the match of the turbocharger's design to the engine reduce the incidence
of insufficient oxygen during transients and help maintain sufficient air flow to the engine
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Regulatory Impact Analysis
during high load operation. The corresponding improvements in oxygen availability
throughout the operational range of the engine reduce the formation of elemental carbon PM.
We expect that new Tier 0 and Tier 1 (remanufactured) locomotive engines will include
improvements to turbocharger design that are similar to those of current Tier 2 locomotive
designs. We also expect that engine manufacturers will continue with incremental
improvements in turbochargers and the match of the turbocharger's design to Tier 3
locomotive and marine engines.
4.2.2.3 Charge Air Cooling
Improvements in engine-out NOX emissions to meet the locomotive and marine
remanufactured engine and Tier 3 standards will be accomplished in part via lowering charge
air cooling temperature. This was one of the primary methods used by locomotive engine
manufacturers to reduce NOX emissions to meet the Tier 1 and Tier 2 locomotive standards
and the Tier 3 nonroad diesel standards. Lowering the intake manifold temperature lowers the
peak temperature of combustion and thus NOX emissions. The NOX reduction realized from
lowering the intake manifold temperature can vary depending upon the engine design but one
estimate suggests NOX emissions can be reduced by five to seven percent with every 10 ฐC
decrease in intake manifold temperature.14 Typically the intake manifold temperature is
lowered by cooling the intake gases through a heat exchanger, also known as a charge air
cooler or aftercooler, located between the turbocharger compressor outlet and the intake
manifold. Locomotive applications typically use air-to-air aftercoolers. Locomotive
aftercoolers use electrically powered auxiliary fans since oftentimes conditions at high torque
output require significant intake air heat rejection, especially at speeds too low for effective
passive air-flow. Operation of the locomotive in multi-engine train configurations or
"consists" can also impede air-flow to heat exchangers. Increased cooling capacity in
locomotive applications can be accomplished via increased air-flow through the air-to-air
after cooler, often through use of either variable speed or multiple-staged electric fans.
Marine applications with access to sea-water heat-exchanger coolant loops typically have
excess heat rejection capacity with respect to charge air cooling. This cooling capacity can be
limited within certain existing hull designs, but new hull designs can typically overcome these
existing hull limitations.
4.2.2.4 Injection Timing
Electronic control of injection timing has been used by locomotive and marine engine
manufacturers to balance NOX emissions, PM emissions, fuel efficiency, engine performance
and engine durability for engines certified to the Tier 2 locomotive and marine engine
standards, Tier 3 nonroad standards, and the 1994 and later heavy-duty highway standards.
We expect similar systems to be used to comply with the remanufactured engine standards
and will continue to be used to comply with the Tier 3 locomotive and marine standards.
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.15'16'17'18 Delaying the start of combustion by retarding
injection timing aligns the heat release from the fuel combustion with the portion of the power
(or combustion) stroke of the engine cycle after the piston has begun to move down. This
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Technological Feasibility
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. Timing retard typically
increases 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.
This 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 diffusion-combustion event to
enhance soot oxidation (see 4.2.2.6 High Pressure Injection, Fuel injection Rate Shaping,
Multiple Injections and Induced Charge Motion). We expect that these strategies will
continue to be used to meet the locomotive and marine remanufactured engine and Tier 3
diesel engine standards.
4.2.2.5 Exhaust Gas Recirculation
Exhaust gas recirculation (EGR) reintroduces or retains a fraction of the exhaust gases
in the cylinder. Most highway diesel engine manufacturers used cooled external EGR to meet
the 2004 and later Heavy-Duty Highway emission standards of 2.5 g/bhp-hr HC + NOX and
0.10 g/bhp-hr PM. EGR has been a key technology used to reduce engine-out NOX emissions
to near 1.0 g/bhp-hr for CDPF-equipped 2007 heavy-duty truck and bus engines in the U.S.
Although we do not expect that EGR will be needed to meet the Tier 3 locomotive and marine
standards for remanufactured engines, we expect that some Category 1 marine diesel engines
and high-speed locomotive switch engines that are based on Tier 3 and Tier 4 nonroad engine
families that already use EGR, will also use EGR for their marine or switch locomotive
applications of these engines to provide additional engine calibration flexibility.
The use of EGR decreases NOX formation in three different ways:
1. EGR can thermally reduce peak combustion temperature. Increasing the mass
of the cylinder contents by increasing carbon dioxide (CC^) and water vapor
concentrations reduces peak cylinder temperatures during combustion.19
2. A fraction of the air within the cylinder is replaced with inert exhaust,
primarily CC>2 and water vapor. This reduces the amount of molecular oxygen
available for dissociation into atomic oxygen, an important step in NOX
formation via the Zeldovich mechanism.10
3. The high temperature dissociation of CC>2 and water vapor is highly
endothermic, and thus can reduce temperatures via absorption of thermal
energy from the combustion process.20
EGR often is routed externally from the exhaust system to the induction system. The use of
externally plumbed EGR can increase the intake manifold temperature substantially. This
reduces intake charge density and lowers the fresh air/fuel ratio for a given level of
turbocharger boost pressure. The result can be a large increase in PM emissions if the boost
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Regulatory Impact Analysis
pressure cannot be increased to compensate for the lower intake charge density. For this
reason, external EGR systems typically cool the exhaust gases using a heat exchanger in the
exhaust recirculation loop. The introduction of ULSD fuel substantially reduces the risk of
sulfuric acid condensation within an EGR cooler. EGR can also be accomplished entirely in-
cylinder (internal EGR) through the use of camshaft phasing or other electronically controlled
variable geometry valve-train systems, particularly when applied to varying two-stroke diesel
engine exhaust scavenging, although it's use is limited by the inability to effectively cool the
residual gases in-cylinder. For both internal and external EGR systems, the EGR rate is
electronically controlled to prevent temporary, overly fuel-rich conditions that can lead to
high PM emissions during transient engine operation.
Although we don't expect that EGR will be required to meet the remanufacturing
standards or the Tier 3 locomotive and marine standards, we do believe that some engine
manufacturers could select EGR as an effective NOX emission control strategy. EGR can also
provide increased flexibility in how engines are calibrated to meet emissions standards with
the potential for improvement in part-load fuel consumption.
4.2.2.6 High Pressure Injection, Fuel injection Rate Shaping, Multiple Injections and
Induced Charge Motion
Inducing turbulent mixing is one means of increasing the likelihood of soot particles
interacting with oxidants within the cylinder to decrease PM emissions. Turbulent mixing can
be induced or increased by a number of means including:
Changes to intake port/valve design and/or piston bowl design
Increased (high) injection pressure
Multiple/split injections using high pressure common rail injection or late post
injection using electronic unit injection
As diesel fuel is injected into the cylinder during combustion, the high pressure fuel
spray causes increased motion of the air and fuel within the cylinder. This increased motion
leads to greater air and fuel interaction and reduced particulate matter emissions. Increasing
fuel injection pressure increases the velocity of the fuel spray and therefore increases the
mixing introduced by the fuel spray.
The most recent advances in fuel injection technology are high-pressure common rail
injection systems with the ability to use rate shaping or multiple injections to vary the delivery
of fuel over the course of a single combustion event. These systems are in widespread use in
heavy-duty on-highway diesel engines, and they are used in many current nonroad diesel
engines. These systems provide both NOX and PM reductions. Igniting a small quantity of
fuel early limits the rapid increase in pressure and temperature characteristic of premixed
combustion and its associated NOX formation. Injecting most of the fuel into an established
flame then allows for a steady burn that limits NOX emissions. Rate shaping can be done
either mechanically or electronically, and has been shown to reduce NOX emissions by up to
20 percent.21 Multiple injection/split injection have also been shown to significantly reduce
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Technological Feasibility
parti culate emissions, most notably in cases that use retarded injection timing or a
combination of injection timing retard and EGR to control NOX.22'23'24'25 The typical
diffusion-burn combustion event is broken up into two events. A main injection is
terminated, and then followed by a short dwell period with no injection, which is in turn
followed by another short post-injection event, see Figure 4-5. The second pulse of injected
fuel induces late-combustion turbulent mixing. The splitting of the injection event into two
events aids in breaking up and entraining the "soot cloud" formed from the first injection
event into the bulk cylinder contents.
Figure 5: An example of using multiple fuel injection events to induce late-combustion mixing and
increase soot oxidation for PM control (Adapted form Pierpont, Montgomery and Reitz, 1995).
o
0
-10 0 10 20 30 40
(TDC)
Increasing the turbulence of the intake air entering the combustion chamber (i.e.,
inducing swirl) can also reduce PM by improving the mixing of air and fuel in the combustion
chamber. Historically, swirl was induced by routing the intake air to achieve a circular
motion in the cylinder. Heavy-duty on-highway and nonroad engine manufacturers are
increasingly using variations of "reentrant" piston designs in which the top surface of the
piston is cut out to allow fuel injection and air motion in a smaller cavity in the piston to
induce additional turbulence (Figure 4-6). Manufacturers have also changed to three or four
valves per cylinder for on-highway and nonroad high-speed diesel engines, and to four valves
per cylinder for medium-speed locomotive engines, which reduces pumping losses and can
also allow for additional intake air charge motion generation. This valve arrangement also
offers better positioning of the fuel injector by allowing it to be placed in-line with the
centerline axis of the piston.
At low loads, increased swirl reduces HC, PM, and smoke emissions and lowers fuel
consumption due to enhanced mixing of air and fuel. NOX emissions might increase slightly
at low loads as swirl increases. At high loads, swirl causes slight decreases in PM emissions
and fuel consumption, but NOX may increase because of the higher temperatures associated
with enhanced mixing and reduced wall impingement.26 A higher pressure fuel system can be
used to offset some of the negative effects of swirl, such as increased NOX, while enhancing
positive effects like increased PM oxidation. Intake air turbulence such as "swirl" can be
induced using shrouded intake valves or by use of a helical-shaped air intake port. Swirl is
important in promoting turbulent mixing of fuel and soot with oxidants, but can also reduce
volumetric efficiency.
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Regulatory Impact Analysis
Piston bowl design can be used to increase turbulent mixing. Reentrant bowl designs
induce separation of the flow over the reentrant "ledge" of the piston and help to maintain
swirl through the compression stroke and into the expansion stroke.10
Figure 6: Schematic examples of a straight-sided piston-bowl (A), a reentrant piston bowl (B), and a deep,
square reentrant piston bowl (C) for high-speed diesel engines.
A)
B)
C)
To meet our locomotive and marine remanufactured engine standards, we expect that
manufacturers will use high pressure electronically controlled unit injection and
improvements to piston bowl design. To meet the Tier 3 locomotive and marine standards,
we expect that manufacturers of high-speed Category 1 and 2 marine diesel engines, high-
speed switch locomotive engines and some Category 2 marine and locomotive medium speed
engines will use advanced electronic fuel systems, including in many cases high-pressure
common rail fuel injection systems.
4.2.2.7 Reduced Oil Consumption
Reducing oil consumption not only decreases maintenance costs, but also VOF and
PM emissions. Reducing oil consumption has been one of the primary ways that heavy-duty
truck diesel engines have complied with the 1994 U.S. PM standard. Reducing oil
consumption also reduces poisoning of exhaust catalysts from exposure to zinc and
phosphorous oil additives.
Redesign of the power assembly (pistons, piston rings and cylinder liner) played an
important role in reducing organic carbon PM emissions from locomotive engines in order to
meet the Tier 2 locomotive standards. Piston rings can be designed to improve the removal of
oil from the cylinder liner surface and drainage back into the crankcase, reducing the amount
of oil consumed. Valve stem seals can be used to reduce oil leakage from the lubricated
regions of the engines valve train into the intake and exhaust ports of the engine.
Improvements to the closed-crankcase ventilation systems that incorporate drain-back to the
crankcase of oil separated from the crankcase flow and the use of high-efficiency filtration,
either with replaceable high-efficiency coalescing filters or multiple-disc inertial separation,
will reduce oil consumption and can remove oil-aerosol from the crankcase flow sufficiently
to allow introduction of the crankcase gases into the turbocharger compressor inlet with little
or no fouling of the turbocharger compressor, aftercooler or the remainder of the induction
system. Euro IV and U.S. 2004 and 2007 heavy-duty truck engine designs that incorporate
these technologies have significantly reduced engine-out organic carbon PM emissions.
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Technological Feasibility
Particularly in the case of medium-speed engines, which have a relatively high
fraction of PM emissions due to organic carbon PM, reduced oil consumption will be an
effective means of meeting the locomotive and marine remanufactured engine and Tier 3 PM
standards. We expect Tier 0 and Tier 1 remanufactured locomotive engines to receive power
assembly designs similar to those of current Tier 2 locomotives. We expect that
remanufactured Tier 2 locomotive engines and new Tier 3 locomotive and marine engines
will receive incremental improvements in the design of the power assembly, valve stem seals
and improved crankcase ventilation systemsespecially if the crankcase ventilation system
routes the crankcase vent to the turbocharger inlet and incorporates high-efficiency oil
separation from the crankcase flow. When applying catalytic exhaust controls to meet the
Tier 4 standards, reduced oil consumption will improve the durability of catalyst systems by
reducing their exposure to zinc- and phosphorous-containing oil additives.
4.2.2.8 Application Specific Differences in Emissions and Emission Control
In much of the preceding discussion we have relied on previous experience primarily
from high-speed (approximately >1600 rpm rated speed) on-highway and nonroad engines to
provide specific examples of emissions formation and engine-out emission control. There
are, however, some important operational and design differences between these engines and
locomotive and marine diesel engines, particularly the medium speed locomotive and marine
engines.
High-speed diesel engines used in on-highway and nonroad applications (with the
exception of generator applications) undergo significant transient operation that can create
temporary conditions of insufficient availability of oxidants due to the inability of the air-
supply from the turbocharger to follow engine transients. For these applications, the majority
of elemental carbon PM is emitted during these transients of insufficient oxygen availability.
Such transients are greatly reduced in locomotive and marine applications. Marine propulsion
engines operate primarily along a propeller curve that effectively forms a narrower outer
boundary within which engine operation occurs. Marine generators and locomotive engines
operate within even narrower bounds. Generators generally operate at close to a fixed engine
speed with varying load. Locomotives operate at 8 distinct speed-load operational notches
with gradual transitions between each notch. Figure 7 illustrates the speed and power ranges
over which typical locomotives and marine engines operate.
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Regulatory Impact Analysis
Figure 7: A comparison engine power output versus engine speed for a locomotive engine operated over
notches one through eight and for a Category 2 marine engine operated over the E3 marine cycle, which
approximates a propeller curve with a cubic relationship between speed and load. A cubic fit through the
locomotive notch points is remarkably similar to the E3 prop-curve. The specific example shown is for
two similar versions of the EMD two-stroke medium-speed diesel engine.
4000
3500
3000
2500
fc 2000
I
0-
1500 -
1000
500
EMD 16-710G3B-T2 Locomotive Engine (Notches 1-8]
EMD L16-710G7C-T2 Category 2 Marine Engine |E3 Test Cycle Points}
100 200 300 400 500 600
Engine Speed (rpm)
700
800
900
1000
In addition to operational differences, medium-speed diesel engines (750 to 1200 rpm
rated speed) are the predominant type used in Category 2 marine and line-haul locomotive
applications. Medium-speed diesel engines are also predominant in older switch locomotives,
although the majority of locomotive switch families certified to the Tier 2 locomotive
standards now use high-speed diesel engines. Medium speed diesel engines typically have
even lower elemental carbon PM emissions due to increased residence time available at high
load conditions for late-cycle burn-up of elemental carbon PM as compared to high-speed
diesel applications such as heavy-duty on-highway engines. The increased duration of
combustion also increases NOX formation for medium-speed diesel engines.
Large-bore locomotive and Category 2 medium speed diesel engines also have
significantly higher lubricating oil consumption than many high-speed diesel engines.
Lubricating oil consumption for current 2007 on-highway diesel truck engines is
approximately 0.09 to 0.13% of fuel consumed versus approximately 0.30 to 0.35% for 2-
stroke medium-speed diesel locomotive and marine engines and approximately 0.25% for 4-
stroke medium-speed locomotive engines. To some degree, this higher consumption of
lubricating oil is by design. Higher lubricating oil consumption allows for a reduced
frequency of complete oil changes, while at the same time the resulting frequent topping off
4-20
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Technological Feasibility
of oil replenishes lubricant additives that maintain the lubricating oil's total base number
(TEN) to prevent acidic corrosion. Frequent topping off also maintains the oil's oxidation
stability to maintain oil viscosity. Because improvements in high-pressure fuel injection
systems and electronic engine management were used to reduce carbon PM emissions to meet
Tier 2 locomotive and marine engine PM standards, only moderate improvements in
lubricating oil consumption were necessary to meet the Tier 2 PM emission standards.
Reduced elemental carbon PM, coupled with still moderately high lubricating oil
consumption, results in a PM composition of medium-speed diesel engines that different from
that of on-highway diesel engines and many nonroad diesel engines. PM emissions from
medium-speed diesel engines have a higher fraction of organic carbon PM emissions than
what has been previously measured from on-highway and most non-road diesel engines.
Figure 4-8 shows the relative contributions of elemental carbon, organic carbon, and sulfate
PM emission from recent testing by AAR of Tier 0, Tier 1 and Tier 2 locomotives using
solvent extraction with gravimetric analysis for determining soluble organic carbon PM and
water extraction and ion chromatography for determining sulfate PM.27 The AAR data shows
soluble organic carbon PM dominating the PM composition. EPA recently conducted testing
at Southwest Research Institute using a newly developed semi-continuous method for direct
mass measurement of organic carbon and elemental carbon (OC-EC). The new OC-EC data
shows somewhat different relative contributions of organic carbon and elemental carbon PM
than the results determined via filter extraction but confirms that Tier 2 locomotives have a
higher fraction of organic carbon PM emissions than other diesel engines, particularly at high-
load conditions.28
Crankcase ventilation flow is considerably higher from very large displacement
medium-speed diesel engine compared with smaller, high-speed engines. This has
complicated the design of crankcase ventilation systems with effective oil-aerosol separation.
Higher capacity, high efficiency inertial disc-type separators are now being introduced in
medium-speed marine applications to reduce bilge water contamination and oil consumption.
Inertial disc-type oil separators originally developed for Euro IV and 2007 U.S. Heavy-duty
On-highway applications have provided sufficient oil separation to allow introduction of
filtered crankcase gases into the turbocharger inlet without oil fouling of the turbocharger or
aftercooler system. Similar systems are now optionally available on Wartsila medium-speed
stationary generator and marine engines (Figure 9). We expect that similar systems will be
used on Tier 3 and Tier 4 Category 2 marine engines and remanufactured Tier 2 and new Tier
3 and Tier 4 locomotive systems. Recent data shows the potential to reduce PM emissions
from Tier 2 locomotives by 10 to 15% via improvements to the crankcase ventilation
28
system.
Improvements in oil formulation, including switching from Group 1 to Group 2 base
oils with greatly improved oxidation stability also reduce the need for oil top-off to replenish
lubricant additives. As Group 1 become unavailable in Europe, we expect increased use of
Group 2 base oil formulations for use with EMD medium-speed engines in Europe. Future
reductions in fuel sulfur for Tier 3 and Tier 4 locomotive and marine engines will also reduce
the need for TEN control.
4-21
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Regulatory Impact Analysis
Figure 8: Emissions for 7 locomotives tested using 2800 ppm sulfur non road diesel fuel.
2006 AAR Data
0.60 g/bhp-hr (Tier 0 PM Standard)
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w
c
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: DSulfate PM (mostly sulfuric acid+associated water)
D Organic PM (mostly lube oil)
D Elemental Carbon PM (soot)
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ง55
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0.45 g/bhp-hr (Tier 1 PM Standard)
16-645F3
EMD SD50 Tier 0
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0.20 g/bhp-hr (Tier 2 PM Standard)
0.1C g/bhp hr(Tier3 PM S andard)
OrS3 q/bhp hr (Tier 4 PM St indard) VV^
I II II 1 I 1
16-710G3B 7FDL16 16-710G3C GEVO12LDB5
EMD SD70M Tier GEAC4400 Tier 1 EMD SD70Ace GE ES44DC Tier 2
1 Tier 2
NS2630 CSXT595 UP8353 BNSF7736
4-22
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Technological Feasibility
Figure 9: Alfa Laval disc-type inertial oil-aerosol separation systems for use with closed crankcase
ventilation systems. The unit on the left is Alfdex system originally developed for Euro IV and U.S. 2007
heavy-duty on-highway applications. This system was designed as "fit for life", or essentially maintenance
free for the useful life of the engine. A much higher volume system (right) was recently developed for
Wartsila medium-speed engines.
Drain oil
outlet
4.3 Feasibility of Tier 4 Locomotive and Marine Standards
In this section we describe the emission control technologies that we believe will be
used to meet the Tier 4 locomotive and marine diesel engine standards. In general, these
technologies involve the use of catalytic exhaust aftertreatment devices placed in an engine's
exhaust system, downstream of an engine's exhaust manifold or turbocharger turbine outlet.
The catalytic coatings of these aftertreatment devices are oftentimes sensitive to other
constituents in diesel exhaust. For example, sulfur compounds within diesel fuel can decrease
the effectiveness or useful life of a catalyst. For this reason, we will require the use of ULSD
fuel in engines that will be designed to meet the Tier 4 emissions standards. We also expect
that engine manufacturers will specify new lubricating oil formulations for these Tier 4
engines because of other trace compounds in some currently used lubricating oils,. These
new oil formulations will help ensure that catalytic exhaust aftertreatment devices will operate
properly throughout their useful life. Because we have already finalized and begun
implementation of similar aftertreatment-forcing standards for both heavy-duty on-highway
and nonroad diesel engines, we are confident that the application of similar, but appropriately
designed, aftertreatment systems for locomotive and marine applications is technologically
feasible, especially given the implementation timeframe of this rulemaking.
4-23
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Regulatory Impact Analysis
4.3.1 Selective Catalytic Reduction (SCR) NOX Control Technology
Recent studies have shown that an SCR system is capable of providing well in excess
of 80% NOX reduction efficiency in high-power, heavy-duty diesel applications.29'30'31 As
shown in Figure 10, Vanadium and base-metal (Cu or Fe) SCR catalysts can achieve
significant NOX reduction throughout much of exhaust gas temperature operating range
observed in heavy-duty diesel engines used in locomotive and marine applications.
Collaborative research and development activities between diesel engine manufacturers, truck
manufacturers, and SCR catalyst suppliers have also shown that SCR is a mature, cost-
effective solution for NOX reduction on heavy-duty diesel engines. While many of the
published studies have focused on heavy-duty highway truck applications, similar trends,
operational characteristics, and NOX reduction efficiencies have been reported for heavy-duty
marine and stationary electrical power generation applications as well.32 An example of the
performance capability of SCR in marine applications is the Staten Island Ferry Alice Austen.
This demonstration project reports that 90-95% NOX reduction is possible under steady-state
conditions (where the exhaust gas temperature is above 270 ฐC.)33 Given the preponderance
of studies and data - and our analysis summarized here - we believe that this technology is
appropriate for both locomotive and marine diesel applications.
4-24
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Technological Feasibility
Figure 10: SCR Catalyst NOX Reduction versus Exhaust Gas Temperature Using an Ammonia-to-NOx
Ratio of 1:13435B
Low-T Base Metal
Vanadium
High-T Base Metal
150
200 250 300 350
Exhaust Gas T @ Catalyst Inlet (ฐC)
400
450
500
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 gasses (>250 ฐC), the urea hydrolyzes to form NHs and CC>2 - the NHs 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 NH3-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). However, given the space limitations in packaging exhaust
aftertreatment devices in mobile applications, an a of 0.85-1.0 is often used to balance the
need for high NOX conversion rates against the potential for NHa slip (where NHs passes
through the catalyst unreacted).
Another approach to prevent NHs slip is to use an oxidation catalyst downstream of
the SCR. This catalyst, also referred to as a slip catalyst, is able to oxidize the NHs which
passes through (or is released from) the SCR. When this approach is used, it is possible to
operate the SCR system at near-peak efficiency by optimizing the urea dosing rate to achieve
the highest-possible level NOX control (i.e. providing adequate NHs for optimum NOX
B The "High-T Base Metal" curve is based on a composite of low and high-space-velocity data provided by
catalyst manufacturers. It is meant to represent high-hour performance of a system at a space velocity of 40,000
hf1.
4-25
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Regulatory Impact Analysis
reduction). A properly-designed slip catalyst, with good selectivity to nitrogen (TS^), can
convert most of the excess NH3 released from the SCR catalayst into N2 and water. Recent
studies have shown that an aged SCR system, equipped with a slip catalyst, can achieve
tailpipe NH3 levels of less of than 10 ppm when tested on the European Stationary Cycle
(ESC) and European Transient Cycle (ETC).36'37 In one study, the system was aged on a
engine dynamometer test cycle which included 400 hours of high-temperature engine
operation at 650 ฐC (to simulate active DPF regeneration events). Comments received from
MECA stated that 90% NOx conversion can be maintained between 250 ฐC and 550 ฐC
following 2000 hours of hydrothermal aging.38 Our analysis of the locomotive engine
operating conditions presumes a primarily "passive" DPF regeneration approach and
maximum, post-turbine exhaust temperatures of 560 ฐC (during operation in non-ventilated
tunnels).39 Under these conditions, we expect slip catalysts to be durable and effective in
reducing NH3 slip.
The urea dosing strategy and the desired a are dependent on the conditions present in
the exhaust gas; namely temperature and the quantity of NOX present (which can be
determined by engine mapping, temperature sensors, and NOX sensors). Overall NOX
conversion efficiency, especially under low-temperature exhaust gas conditions, can be
improved by controlling the ratio of two NOX species within the exhaust gas; NO2 and NO.
This can be accomplished through use of an oxidation catalyst upstream of the SCR catalyst
to promote the conversion of NO to NO2. The physical size and catalyst formulation of the
oxidation catalyst are the principal factors which control the NO2:NO ratio, and by extension,
improve the low-temperature performance of the SCR catalyst.
Published studies show that SCR systems will experience very little deterioration in
NOX conversion throughout the life-cycle of a diesel engine.36'37'40 The principal mechanism
of deterioration in an SCR catalyst is thermal sintering - the loss of catalyst surface area due
to the melting and growth of active catalyst sites under high-temperature conditions (as the
active sites melt and combine, the total number of active sites at which catalysis can occur is
reduced). This effect can be minimized by design of the SCR catalyst washcoat and substrate
for the exhaust gas temperature window in which it will operate. Another mechanism for
catalyst deterioration is catalyst poisoning - the plugging and/or chemical de-activation of
active catalytic sites. Phosphorus from the engine oil and sulfur from diesel fuel are the
primary components in the exhaust stream which can de-activate a catalytic site. The risk of
catalyst deterioration due to sulfur poisoning will be all but eliminated with the 2012
implementation of ULSD fuel (<15 ppm S) for locomotive/marine applications. Catalyst
deterioration due to phosphorous poisoning can be reduced through the use of lubricating oil
with low sulfated-ash, phosphorus, and sulfur content (commonly referred to as "low-SAPS"
oil) and through reduced oil consumption (as discussed in 4.2.2.7). Previous oil formulations
for heavy-duty, on-highway engines, such as API CI-4, did not specify a limit for sulfur
content, and allowed higher levels of phosphorous (0.14% vs 0.12%) and ash (1.2-1.5% vs.
1.0%) content.41 We expect the use of low-SAPS oil improve the performance of durability
of catalyzed-DPF and SCR aftertreatment components in locomotive and marine applications.
The high ash content in current locomotive and marine engine oils is related to the need for a
high total base number (TEN) in the oil formulation. This high-TBN oil has been necessary
because of the high sulfur levels typically present in diesel fuel - a high TEN is necessary to
neutralize the acids created when fuel-borne sulfur migrates to the crankcase. With the use of
4-26
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Technological Feasibility
ULSD fuel, acid formation in the crankcase will not be a significant concern. This oil will be
available for use in heavy-duty highway engines by October 2006 and is specified by the
American Petroleum Institute as "CJ-4."42 The durability of other exhaust aftertreatment
devices, namely the DOC and DPF, will also benefit from the use of ULSD fuel and low-
SAPS engine oil - less sulfur and phosphorous will improve DOC effectiveness and less ash
will increase the DPF ash-cleaning intervals.
The migration of low-SAPS engine oil properties to future locomotive and marine oil
formulations - while beneficial and directionally helpful in regards to the durability,
performance, and maintenance of the exhaust aftertreatment components we reference - is not
a required element of our feasibility analysis. European truck and marine applications have
shown that SCR is a durable technology with low-SAPs oil. Several comments to our NPRM
suggested that these newer, low-SAPS oil formulations, developed for use in on-highway and
nonroad diesel engines, may not be appropriate for locomotive or marine applications. While
we acknowledge that the exact oil formulation for locomotive and marine applications using
ULSD fuel is not known today, we do believe that there is adequate time to develop an
appropriate oil formulation. For example, in the State of California, all intra-state
locomotives, marine vessels (in the SCAQMD), and nonroad engines have been operating
with ULSD fuel since June, 2006 - so there should already be field data/experience available
today to begin developing an oil formulation for ULSD in advance of the implementation date
for aftertreatment-forcing standards. In addition, the nonroad sector will have transitioned to
ULSD fuel nationwide by June, 2010, followed by the locomotive and marine sectors by June,
2012. The staggered introduction of ULSD fuel across these sectors (on-highway, nonroad,
and finally, locomotive/marine), leaves ample time to develop oil formulations which do not
contain any more sulphated-ash than necessary to neutralize crankcase acids. By adjusting
amount of sulfated ash for each sector and the expected fuel sulfur level, it may be possible to
reduce the ash quantity, resulting in extended ash cleaning intervals.
The onboard storage of the aqueous urea solution on locomotives and marine vessels
can be accomplished through segmenting of the existing fuel tanks or 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 at least 5% of the
diesel fuel tank capacity. At the appropriate intervals, the crews will need to refill the urea
tank. For the railroad and marine industries, the distribution and dispensing of urea is
expected to benefit from any solutions put in place by the trucking industry and heavy-duty
highway engine and vehicle manufacturers well in advance of the Tier 4 locomotive and
marine regulations.
We project that locomotive and marine diesel engine manufacturers will benefit from
any development taking place to implement DPF and SCR technologies in advance of the
heavy-duty truck NOX standards in Europe and the U.S. The Manufacturers of Emission
Controls Association (MECA) supports the feasibility and timing of the Tier 4 locomotive and
marine standards we are finalizing, and has stongly stated development work for SCR designs
can begin today, with full implementation of this technology by 2015.43 In addition, today's
urea dosing systems for SCR - already in widespread use across many different diesel
applications - are expected to become more-refined/robust/reliable in advance of the Tier 4
locomotive and marine standards. Given the steady-state operating characteristics of
4-27
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Regulatory Impact Analysis
locomotive and marine engines, DPF regeneration strategies and urea dosing controls will
certainly be capable of controlling PM and NOX at the levels necessary to meet the standards
finalized in this rulemaking.
4.3.1.1 Urea Infrastructure and Feasibility & Cost
The preferred concentration for the aqueous urea solution is 32.5% urea, which is the
eutectic concentration (provides the lowest freezing point and the urea concentration does not
change if the solution is partially frozen).44 With a freezing temperature of-11 ฐC (12 ฐF),
heaters and/or insulation may be necessary in Northern regions for urea storage/dispensing
equipment and the urea dosing apparatus (tank, pump, and lines) on the on the engine. The
centralized nature of locomotive and marine refueling from either large centralized fuel
storage tanks or from tanker trucks with long-term purchase agreements provides a working
example of how urea could also be distributed from storage tanks at centralized fueling
facilities, tanker trucks and/or multi-compartment fuel-oil/urea tanker trucks at remote fueling
sites. Given that only a small percentage of the locomotive and marine fleet will require urea
prior to 2017, EPA believes that the infrastructure for supplying urea from centralized
refueling points and tank trucks can be established to serve the rail and marine industries.
Discussions concerning the urea infrastructure and specifications for an emissions-grade urea
solution are beginning to take place amongst stakeholders in the light-duty and heavy-duty
highway diesel industry. It is possible that these discussions will result in a fully-developed
urea infrastructure for light-duty and heavy-duty diesel highway engine and vehicle
applications by 2010. This will allow time to expand and develop this framework and support
the needs of the railroad and marine industries. Even without these developments underway
in the light-duty and heavy-duty highway industry, the centralized fueling nature of the
locomotive and marine industries lends itself well to adaptation to support a supply of urea at
their normal fueling locations.
In 2015, urea cost is expected to be ~$0.75/gallon for retail facilities dispensing
200,000 - 1,000,000 gallons/month, and ~$1.00/gallon for those dispensing 80,000 - 200,000
gallons/month.45 The additional operating cost incurred by the rail industry will also be
dependent on the volume of urea dispensed at each facility, with smaller refueling sites
experiencing higher costs. It is estimated that 87% of the locomotive fleet is refueled at fixed
facilities and 13% at direct truck-to-locomotive facilities.46 The type of urea
storage/dispensing equipment, and the ultimate cost-per-gallon, for railroad and marine
industries will depend on the volume of fuel & urea dispensed at each site. High-volume
fixed sites may choose to mix emissions-grade dry urea (or urea liquor) and de-mineralized
water on-site, whereas others may choose bulk or container delivery of a pre-mixed 32.5%
urea-water solution. Again, with the possible implementation of SCR for light-duty and
heavy-duty highway applications in 2010, the economic factors for each urea supply option
may be well-known prior to implementation of the 2017 standards. Even without these
developments underway in the light-duty and heavy-duty highway industry, we believe that
the urea supply options for the locomotive and marine industries will be numerous.
Urea production capacity in the U.S. is more than sufficient to meet the additional
needs of the rail and marine industries. For example, in 2003, the total diesel fuel
consumption for Class I railroads was approximately 3.8 billion gallons.47 If 100% of the
4-28
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Technological Feasibility
Class I locomotive fleet were to be equipped with SCR catalysts, approximately 190 million
gallons-per-year of 32.5% urea-water solution would be required.45 It is estimated that 190
million gallons of urea solution requires 0.28 million tons of dry urea (1 ton dry urea is
needed to produce 667 gallons of 32.5% urea-water solution).45 Currently, the U.S. consumes
14.7 million tons of ammonia resources per year, and relies on imports for 41% of that total
(of which, urea is the principal derivative). In 2005 domestic ammonia producers operated
their plants at 66% of rated capacity, resulting in 4.5 million tons of reserve production
capacity.48 In the hypothetical situation above, where 100% of the locomotive fleet required
urea, only 6.2% of the reserve domestic capacity would be needed to satisfy the additional
demand. A similar analysis applied to the marine industry, with a yearly diesel fuel
consumption of 2.2 billion gallons per year, would not significantly impact the urea demand-
to-reserve capacity equation. Since the rate at which urea-SCR technology is introduced to
the railroad and marine markets will be gradual, the reserve urea production will be adequate
to meet the expected demand in the 2015 timeframe for implementation of the Tier 4
standards.
4.3.1.2 Establishing the Tier 4 NOX Standard
The basis for the locomotive Tier 4 Line-Haul NOX standard is the Tier 3 NOX
emission standard (5.5 g/bhp-hr) reduced by the following SCR catalyst efficiency estimates
at full useful life of the engine; 60% efficiency in operating mode notch 2 (where exhaust gas
temperature is near the minimum-level for NOX conversion), 85% conversion efficiency in
operating modes notches 3 and 4 (where lower catalyst space velocities allow optimum
reaction rates), and 83% conversion efficiency in the high-load operating modes, notches 5
through 8.ฐ When these efficiencies are weighted according to the line-haul duty cycle
emissions test, an overall NOX reduction of 78% is obtained.
Figure 11 illustrates EPA's projection of an "aged" locomotive/marine SCR system at
full useful life. When these levels of NOX reduction are applied to engine out emissions from a
typical Tier 2, 4-stroke-cycle locomotive diesel engine producing 5.5 g/bhp-hr of NOX on the
line-haul duty cycle, the worst-case, full useful life standard is established at 1.3 g/bhp-hr.D
This standard includes a compliance margin and we expect that emissions of a new engine -
and the emissions throughout much of the engine's life - will be closer to 0.8 g/bhp-hr.
Because marine diesel engines will also operate under similar engine load/exhaust gas
temperature conditions over their respective cycles, they also will be capable of similar NOX
reductions. As shown in the shaded area of Figure 4-11, the E3 Marine Test Cycle lies within
the peak performance range of an SCR catalyst.
c For conditions present in Tier 0-2 locomotives, extended SCR operation (and hence, NOX reduction) is not
possible at the low power notches (NI, LI, DB, and Nl) due to low exhaust gas temperatures.
D With an overall, duty-cycle-weighted, NOX conversion efficiency of 78%, the remainder NOX emissions will be
22% of the engine-out level (i.e. the Tier 2 Standard is 5.5 g/bhp-hr; 5.5 x 0.22 = 1.2 g/bhp-hr).
4-29
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Regulatory Impact Analysis
Figure 11: Typical 4-Stroke Diesel Locomotive Exhaust Gas Temperatures and Projected SCR Catalyst
Efficiency at Full Useful Life.
500
450
400
p
~ 350
c
I 300
o>
I 250
01
I- 200
V)
a
O 150
uj 100
50
0
-ฉ & -hฉ
f /Typical load-temperature operating
regime for medium-speed diesel
engine on the E3 Marine Test Cycle
100
90
s?
80 ฃ
70 |
60 w
50 |
40 >
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10
0
^ x^
Throttle Notch Setting
-Avg. Exh. Gas Temp. (GE Tier 2 locomotive engine
-O Projected SCR NOx Conversion Efficiency
For applications requiring improved SCR performance at lower exhaust gas
temperatures, several options are available; throttling the engine airflow to increase exhaust
gas temperature, using an SCR formulation designed for the low-temperature NOX conversion,
or a heated urea dosing system (or some combination of all three options). Throttling of the
intake airflow on refuse trucks - which often operate under light-load conditions - has been
shown to substantially increase exhaust gas temperatures.49 Increasing the exhaust gas
temperature at light load not only provides an opportunity for extended SCR operation, it is
also improves performance of the DOC and DPF components. Low-temperature NOX
conversion can also be enhanced by use of a base-metal (Fe or Cu) zeolite SCR catalyst (see
Figure 4-12). Systems for dosing urea at exhaust temperatures below 250 ฐC are being
developed for heavy-duty, highway truck applications. One such system utilizes an
electrically-heated bypass to hydrolyze the urea-water solution and produce NH3 when
exhaust gas temperatures are as low as 160 ฐC - providing an additional 5-25% NOX
reduction relative to a system which stops urea dosing at 250 ฐC.50 Use of a pre-turbocharger
location for a DOC located upstream of the SCR system can also improve low temperature
performance by driving NO to NO2 conversion at lighter engine loads than would be possible
with more remote mounting of the DOC. Use of air-gap or other types of insulated
construction for exhaust system components can also improve thermal management and
increase exhaust gas and catalyst temperatures. For further discussion of manifold-mounting
of the DOC and exhaust system thermal management, see section 4.3.2 PM and HC Exhaust
Aftertreatment Technology.
4-30
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Technological Feasibility
If no improvements were made to technologies which exist today, the 1.3 g/bhp-hr
locomotive standard is technologically feasible. With projected improvements (that are
currently more-difficult to quantify), we are confident in-use operation and end of useful life
NOX emission levels will be less than the 1.3 g/bhp-hr standard finalized in this rulemaking.
4.3.2 PM and HC Exhaust Aftertreatment Technology
The most effective exhaust aftertreatment used for diesel PM emission control is the
diesel particulate filter (DPF). More than a million light diesel vehicles that are OEM-
equipped with DPF systems have been sold in Europe, and over 200,000 DPF retrofits to
diesel engines have been conducted worldwide.8 Broad application of catalyzed diesel
particulate filter (CDPF) systems with greater than 90% PM control is beginning with the
introduction of 2007 model year heavy-duty diesel trucks in the United States. These systems
use a combination of both passive and active soot regeneration. CDPF systems utilizing metal
substrates are a further development that trades off a degree of elemental carbon soot control
for reduced backpressure, greater design and packaging flexibility, improvements in the
ability of the trap to clear oil ash, and better scaling to the large sizes needed for locomotive
and marine applications. Metal-CDPFs were initially introduced as passive-regeneration
retrofit technologies for diesel engines designed to achieve approximately 50 to 60% control
of PM emissions.51 Recent data has shown that metal-CDPF trapping efficiency for
elemental carbon PM can exceed 70% for engines with inherently low elemental carbon
emissions.52 Data from locomotive testing (Figure 12) confirms a relatively low elemental
carbon fraction and relatively high organic fraction for PM emissions from medium-speed
Tier 2 locomotive engines.27 The use of a highly oxidizing PGM catalyst coated directly to
the CPDF combined with a highly oxidizing DOC mounted upstream of the CDPF can
provide 95% or greater removal of HC, including the semi-volatile organic compounds that
contribute to PM.
A functional schematic of a metal-CDPF is shown in Figure 13. In this particular
example, flow restrictions divert a portion of the particle laden exhaust flow through the
porous sintered metal walls. The openings in the flow restrictions are sufficient to allow
accumulated ash to migrate through the CDPF substrate, either reducing or eliminating the
need for periodic ash cleaning.53 The metal-CDPF will most likely be used in combination
with an upstream diesel oxidation catalyst (DOC). A diesel oxidation catalyst mounted
upstream of the metal-CDPF improves NO to NO2 oxidation for both passive soot
regeneration within the CDPF and to increase the NOX reduction efficiency of the SCR
system, particularly during light-load and/or under cold ambient conditions. The DOC can
also assist with oxidation of organic carbon PM, particularly at lower notch positions. The
DOC effectively becomes mass transport limited for NO2 oxidation at notch 6 and above
(approximately 80,000"hr space velocity), but at that point exhaust temperatures at the location
of the metal-CDPF would be sufficient for NO to NO2 oxidation and thus for passive soot
regeneration and also for oxidation of organic carbon. Some or all of the DOC volume can be
installed in a close-coupled position within the exhaust manifold, immediately downstream of
the exhaust ports and upstream of the turbocharger's exhaust turbine (Figure 14) and within
the "vee" of V-type locomotive and marine engines. Air-gapped construction can be used to
provide faster warm-up and retention of heat within exhaust components. Thermal insulation
that is similar to what is already in common use with dry exhaust manifold configurations in
4-31
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Regulatory Impact Analysis
Category 2 marine applications can be used to increase exhaust and catalyst temperatures
(Figure 15).
Figure 16 and Figure 17 shows the expected line-haul locomotive PM reductions for
the following scenarios:
A 4-stroke line-haul Tier 2 locomotive due to reducing fuel sulfur content to 15
ppm
A 4-stroke line-haul Tier 3 locomotive with oil consumption reduced
approximately 50% relative to Tier 2 via improvements to the power assembly and
closed-crankcase ventilation system
A 4-stroke line-haul Tier 4 locomotives with application of a DOC and metal -
CDPF to the Tier 3 engine
A 4-stroke line-haul Tier 4 locomotives with application of a DOC and wall-flow-
CDPF to the Tier 3 engine
Figure 18 and Figure 19 shows the expected marine PM reductions (on the E3 General
Marine Duty Cycle) for the following scenarios:
A 2-stroke medium-speed Category 2 marine diesel engine due to reducing fuel
sulfur content to 15 ppmE
A 2-stroke medium-speed Category 2 marine diesel engine with oil consumption
reduced approximately 50% relative to Tier 2 via improvements to the power
assembly and closed-crankcase ventilation system
A 2-stroke medium-speed Category 2 marine diesel engine with application of a
DOC and metal-CDPF to the Tier 3 engine
For both the 4-stroke line-haul locomotive and 2-stroke Category 2 marine examples,
post-control PM was calculated using both AAR and EPA speciated PM test results. The
relative contributions of elemental carbon and organic carbon to PM mass differed between
the EPA and AAR test results, but the level of expected PM control was similar for the
emissions control systems that were evaluated. Due to the relatively high organic carbon
fraction and low elemental carbon fraction in the PM emissions, the difference in PM
emissions between the metal-CDPF and the wall-flow-CDPF is less than 0.01 g/bhp-hr . The
E For this specific example, speciated data from an EMD 16-710G3C-T2 2-stroke medium speed locomotive
engine was used. This engine is offered in both Category 2 marine and line-haul locomotive applications. The
locomotive application has a slightly higher speed rating and lower NOx emissions. A fit of the data to E3
points for the lower 4000 bhp @ 900 rpm EMD 16-710G7C-T2 marine rating was used to model PM emissions
instead of the 4300 bhp @ 950 rpm rating. The G3C-T2 and G7C-T2 engines are remarkably similar, if not
identical, designs with very similar NOx and PM emissions and appear to differ only with respect to rated power
and rated speed.
4-32
-------
Technological Feasibility
advantages of the metal-CDPF relative to the wall-flow-CDPF are greatly reduced
maintenance requirements and reduced exhaust back-pressure. We estimate that the use of a
metal CDPF will result in PM emissions of approximately 0.020 to 0.022 g/bhp-hr over the
line-haul cycle. The results from a ceramic wall-flow trap would be simlilar at 0.015 to 0.17
g/bhp-hr. Either system would provide sufficient compliance margin to meet the 0.03 g/bhp-
hr Tier 3 line-haul locomotive standard. We expect comparable PM reductions from
Category 2 marine engines and locomotive engines that utilize similar CDPF technology due
to similarities in PM composition between these engines.
Fig 4-20 shows the expected PM removal efficiency of going from Tier 3 to Tier 4
plotted vs. exhaust temperature for all notch positions. The Tier 3 levels were calculated
based on a 4-stroke Tier 2 locomotive engine with improved lubricating oil control. The Tier
4 levels were calculated based on the efficiency of a DOC and metal-CDPF combination at
the end of useful life and taking into account removal efficiency for elemental and organic
carbon and expected sulfate make from fuel and lubricant sulfur. Efficiency is similar or
higher for Category 2 marine applications due to a narrower range of exhaust temperatures
(approximately 250 ฐC to 350 ฐC over the E3 cycle) that are generally above the light-off
temperatures for HC and NO oxidation for typical precious-metal DOC and CDPF
formulations and yet are largely below the temperatures at which peak sulfate-make occurs.
Figure 12: Brake-specific PM emissions speciated into soluble organic, soluble sulfate, and insoluble
elemental carbon over the Federal Line-Haul duty cycle.
2006 AAR Data
0.600
0.550
0.500
0.450
0.400
0.350
0.300
0.250
0.200
0.150
0.100
0.050
0.000
0.60 g/bhp-hr (Tier 0 PM Standard)
DSulfate PM (mostly sulfuric acid+associated water)
D Organic PM (mostly lube oil)
D Elemental Carbon PM (soot)
0.45 g/bhp-hr (Tier 1 PM Standard)
0.20 g/bhp-hr (Tier 2 PM Standard)
4-33
-------
Regulatory Impact Analysis
Figure 13: Cross-sectional functional schematic for a metal-CDPF (not to scale). Flow restrictions force
part of the particle laden exhaust flow through the porous sintered metal layers. High efficiencies are
possible with engines having relatively low elemental carbon PM emissions.
Porous sintered metal layer
Exhaust flow
Legend
Flow through porous layer to adjoining channel
Re-entrained flow through porous layer
Flow restriction
2. Flow re^trlptiopS Jayse
a portion of the p^rticHe-taden
flow through fhe porous Tayei
.
4-34
-------
Technological Feasibility
Figure 14: Metal-monolith diescl oxidation catalysts (DOC) mounted within the exhaust manifold of an
EMD 710-series locomotive diesel engine. Use of a close-coupled DOC extends the range of light-load
operation where NO to NO2 oxidation can occur. Oxidation of engine-out NO to NO2 assists with passive
regeneration of the CDPF and increases the low temperature performance of the urea SCR system. The
system also improves oxidation of organic carbon PM at light load conditions (locomotive notches 1
through 6).
Figure 15: A two-stroke medium-speed Category 2 marine diesel engine with an insulated exhaust
manifold and exhaust turbine in use in New York Harbor.
4-35
-------
Regulatory Impact Analysis
Figure 16: Brake-specific PM emissions over the line-haul duty cycle for a Tier 2 locomotive and the
expected reductions in PM emissions due to reduced fuel sulfur levels and application of PM emissions
controls. PM composition based on 2006 AAR testing.27
Tier 2 0.20 g/bhp-hr PM Standard
t 0-170 -
n ฐ-160 ~
iii U-1JU "
o U'11U "
im 0 100 ^
o_ o 090
ro
' n nnn
OS
nr
DE
ulfate (mostly sulfuric acid
rganic (mostly lube oil)
lemental Carbon (soot)
I- water)
60% reduction 85% reduction
from Tier 2 from Tier 2
Fuel
reduction
^.
^^
Reduced
lubricating
oil
consumpton
Oxidatiojk
& CDPF *,- . '
Tier 3 0.10 a/bhD-hr PM Standard
Tier 4 0.03 a/bhp-hr PM Standard
1 ^f- , ,
1 [ Soot trapping 1 Q( -i- 1 1
Tier2GE Tier2GE TierSGE Tier 4 GE Tier4GE
Locomotive, 3000 Locomotive, 15 ppm Locomotive, 15 ppm Locomotive, 15 ppm Locomotive, 15 ppm
ppm S Fuel S Fuel S Fuel S Fuel, Metal- S Fuel, Wall-flow
substrate CDPF CDPF
Figure 17: Brake-specific PM emissions over the line-haul duty cycle for a Tier 2 locomotive and the
expected reductions in PM emissions due to reduced fuel sulfur levels and application of PM emissions
controls. PM composition based on 2007 EPA Testing.28
0.2
0.19
0.18
Tier 2 0.20 g/bhp-hr PM Standard
g 0.01
Total PM
DSulfate (mostly sulfuric acid + water)
Q Organic (mostly lube oil)
D Elemental Carbon (soot)
60% reductic
Tier2GE
Locomotive, 3000
ppm S Fuel
Tier2GE
Locomotive, 15 ppm
SFuel
TierSGE
Locomotive, 15 ppm
SFuel
Tier4GE
Locomotive, 15 ppm
S Fuel, Metal-
substrate CDPF
Tier4GE
Locomotive, 15 ppm
S Fuel, Wall-flow
CDPF
4-36
-------
Technological Feasibility
Figure 18: Brake-specific PM emissions over the E3 General Marine Duty Cycle for a Tier 2 medium-
speed Category 2 diesel engineE and the expected reductions in PM emissions due to reduced fuel sulfur
levels and application of PM emissions controls. PM composition based on 2006 AAR testing.27
-3 n -ifin
w
t 0.130 -
o ฐ-110 "
0 U.UbU -
0
0 U-U^U "
n nnn
n S
o
jlfate (mostly sulfuric acid + water)
rganic (mostly lube oil)
Elemental Carbon (soot)
Tier 2 0.20 g/bhp-hr (0.27 g/kW-hr) PM Standard
55% reduction 90% reduction
Fuel
sulTur
^
Reduced
lubricating
oil
consumption
Tier 2 EMD C2 Marine, Tier 2 EMD C2 Marin
3000 ppm S Fuel ppm S Fuel
i
bv DOC ^k '
& CDPF ^
Soot trapping ^
Tier 3
0.10 g/bhp-hr
(0.13 g/kW-hr)
Tiprd
0.03 g/bhp-hr
(0.04 g/kW-hr)
' PM Standard
^
3,15 Tier 3 EMD C2 Marine, 15 Tier 4 EMD C2 Marine, 15
ppm S Fue ppm S Fuel, Metal-
substrate CDPF
Figure 19: Brake-specific PM emissions over the E3 General Marine Duty Cycle for a Tier 2 medium-
speed Category 2 diesel engineE and the expected reductions in PM emissions due to reduced fuel sulfur
levels and application of PM emissions controls. PM composition based on 2007 EPA Testing.28
0.200
0.190
0.180
0.170
0.160
0.150
0.140
0.130
0.120
0.110
0.100
2. 0.090
a, 0-080
B 0.070
0.060
ง 0.050
O 0.040
B* 0.030
A ฐ-020
ฃ 0.010
0.000
o> ,
CO
m
Tier 2 0.20 g/bhp-hr (0.21 g/kW-hr| PM Standard
Total PM
DSulfate (mostly sulfuric acid + water)
D Organic (mostly lube oil)
D Elemental Carbon (soot)
50% reduction 85% reduction
from Tier 2 from Tier 2
Tier 2 EMD C2 Marine, Tier 2 EMD C2 Marine, 15 Tier 3 EMD C2 Marine, 15 Tier 4 EMD C2 Marine, 15
3000 ppm S Fuel ppm S Fuel ppm S Fuel ppm S Fuel, Metal-
substrate CDPF
4-37
-------
Regulatory Impact Analysis
Figure 20: Expected PM reduction versus exhaust temperature for a combined DOC and Metal-CDPF
system using 15 ppm sulfur fuel when applied to a Tier 3 locomotive. Below 200 ฐC, PM is dominated by
organic carbon emissions, which can only be removed via catalytic oxidation and not by filtration since
they are in the gas-phase in the raw exhaust. Thus (organic) PM removal is limited by the kinetically-
limited HC oxidation rates over the precious metal catalyst applied to the DOC and the CDPF. The level
of PM control is reduced at temperatures between 300 and 450 ฐC due to the formation of sulfate PM over
the CDPF. Note that the percentage reduction is relative to the emissions of a Tier 3 locomotive, not a
Tier 2 locomotive.
% PM Reduction (Tier 3 to Tier 4)
90%
80%
^^ Based on PM composition from 2006 filter extraction data
Based on PM composition from 2007 OC-EC data
100
150
200
250
300
350
400
450
Post-turbine Exhaust T (degC)
4.3.3 SCR and CDPF Packaging Feasibility
We expect that locomotive and marine manufacturers will design exhaust,
turbocharger, and intake air aftercooling systems to accommodate the aftertreatment
components. It is acknowledged that the existing overall length, width, and height
dimensions of the locomotive are constrained by the existing infrastructure such as tunnel
height, but our analysis shows the packaging requirements are such that they can be
accommodated within the constraints of a locomotive. For commercial marine vessels, our
discussions with marine architects and engineers, along with our review of vessel
characteristics, leads us to conclude for engines >600 kW on-board commercial marine
vessels, adequate engine room space can be made available to package aftertreatment
components. Packaging of these components, and analyzing their mass/placement effect on
vessel characteristics, will become part of design process undertaken by naval architecture
and marine engineering firms.54
To achieve an acceptable balance between SCR performance and exhaust system
backpressure, we estimate the volume of the SCR will need to be approximately 2.5 times the
engine displacement. This volume includes the volume required for an ammonia-slip-catalyst
4-38
-------
Technological Feasibility
zone coated to the final 15% of the volume of the SCR monoliths. The SCR volume is
determined by sizing the device so that pollutants/reductants have adequate residence time
within catalyst to complete the chemical reactions under peak exhaust flow (maximum power)
conditions. The term used by the exhaust aftertreatment industry to describe the relationship
between exhaust flow rate and catalyst residence time is "space velocity". Space velocity is
the ratio of an engine's peak exhaust flow (in volume units-per-hour) to the volume of the
aftertreatment device - this ratio is expressed as "inverse hours", or "hr. For example, an
engine with a displacement of 200 liters (L), 300,000 L/min of exhaust flow, and a 450 L
SCR would have a space velocity of 40,000"hr and a catalyst-to-engine displacement ratio of
2.25:1.F Typical space velocities for SCR on existing Euro 5 heavy-duty truck applications
range from 60,000 to 80,000"hr.
To achieve acceptable elemental carbon PM capture efficiency, organic carbon PM
oxidation efficiency and exhaust system backpressure, the volume of a metal-CDPF for
locomotive applications will need to be approximately 1.7 times the engine displacement,
which results in a maximum space velocity of approximately 60,000"hr. The exhaust-
manifold-mounted DOC located upstream of the metal CDPF will need to be approximately
0.8 times the engine displacement with a maximum space velocity of approximately 80,000"^
in notch 6 (approximately 120,000 hr in notch 8). Typical space velocity for combined
DOC/CDPF systems for Euro 4, Euro 5, and U.S. 2007 heavy-duty truck applications range
from approximately 60,000 to 80,000"hr.
The volume of the space above the engine available for packaging of exhaust
aftertreatment components on a locomotive is approximately 2300 L. For a 200L engine,
with DOC, DPF, and SCR volume-to-displacement ratios of 0.8, 1.7, and 2.5 respectively,
approximately 1000-L of space would be occupied by these aftertreatment components,
leaving 1300 L of space available for the ducts, urea dosing/mixing hardware, and catalyst
support structures. An example of an aftertreatment system design concept which satisfies the
packaging space and volume criteria was developed by Tennecoฎ and is shown in Figure 21.
Space Velocity =300,000 L/min * 1/450 L * 60 min/hr, Catalyst-to-Engine Displacement Ratio = 450 L/200 L.
4-39
-------
Regulatory Impact Analysis
Figure 21: Tennecoฎ DPF + SCR aftertreatment concept for line-haul locomotive applications.
DPF section with ducts/valves
(light brown) to balance flow
between filter elements
SCR substrates (ammonia slip
catalysts shown in dark brown)
Urea mixing section
Exhaust flow from turbine
outlet
One commenter stated that the EPA projections for space requirements of
aftertreatment components was underestimated by a factor of 2. Our projection for
catalyst/component volume was based on assigning a "reasonable" space velocity (one which
provided a good balance between emissions reduction and exhaust backpressure) to each
component - 120,000'hr for the DOC, 60,000'hr for the DPF, and 40,000'hr for the SCR. In our
analysis, we used engine data from the AAR's locomotive in-use emissions test program to
calculate the exhaust flow rate in units of "standard" cubic feet per minute (or SCFM, the
conventional unit for volumetric flow used by catalyst manufacturers to calculate space
velocity). In the commenter's analysis, the "actual" exhaust flow rate instead of one corrected
to "standard" conditions, as is industry practice. This method of analysis resulted in a flow
rate which was approximately twice that of the value used in the EPA analysis, resulting in a
space velocity which was two times greater as well. Once corrected to "standard" conditions,
the commenter's results for space velocity (and by extension, component volume) are very
close to the EPA analysis.
4.3.4 Mechanical Durability of Aftertreatment Components
The exhaust components in any diesel application are subject to stresses from thermal
expansion, vibration, and shock loads - all of which can affect the durability of the
aftertreatment system. These stresses - and their associated affect on component durability -
can be managed through the selection of proper materials and the design of support and
mounting structures which are capable of withstanding them throughout the exected useful
life and service conditions of a particular engine application. One commenter to our NPRM
stated that shock loading for a locomotive catalyst is estimated to be 10-12 g. This level of
shock loading is consistent with the levels that catalyst substrate manufacturers, catalyst
canners, and exhaust system manufacturers are currently designing to (for OEM
4-40
-------
Technological Feasibility
aftertreatment systems and components subject to the durability requirements of on-highway,
marine, and nonroad applications). Nonroad applications such as logging equipment are
subject to shock loads in excess of 10 g and on-highway applications can exceed 30 g (with
some OEM applications specifying a 75 g shock load requirement).55 In addition, the
American Bureau of Shipping (ABS) specification for exhaust manifolds on diesel engines
states that these parts may need to withstand vibration levels as high as +/-10 g at 600 ฐC for
90 minutes.56 Given these examples of shock and vibration requirements for today's nonroad,
on-highway, and marine environments , we believe that appropriate support structures can be
designed and developed for the aftertreatment devices we expect to be used on Tier 4
locomotives.
4.3.5 Stakeholder Concerns Regarding Locomotive NOX Standard Feasibility
One stakeholder has expressed a number of concerns regarding the feasibility of the
1.3 g/bhp-hr Tier 4 locomotive NOX standard. The issues raised by the stakeholder can be
summarized into three broad areas of concern:
1. Ammonia (urea) dosing
2. Deterioration of SCR catalyst NOX control
3. Locomotive parity with the marine Tier 4 NOX standard
4.3.5.1 Ammonia/Urea dosing
The dosing concern specified that variability in urea quality (concentration), urea
delivery (dosing), and engine-out NOX level limits the maximum NOX reduction potential of
the SCR system in order to control ammonia slip to a level <20 ppm. This concern is valid
only if urea dosing is controlled in an "open-loop" manner (or operated without consideration
of - or inputs from - actual conditions present in the exhaust system and within the SCR
catalysts.) If the urea dosing is controlled in a "closed-loop" manner, where feedback from
NOX and exhaust gas temperature sensors before/after the SCR catalyst is used to adjust the
urea dosing rate, the SCR catalyst can operate at near-peak NOX conversion efficiency while
minimizing NFL? slip. The use of an NH3 slip catalyst can clean up any ammonia released
from the SCR to levels less than 10 ppm, providing an additional level of robustness to the
closed-loop urea dosing system.36 For example, if exhaust gas and SCR temperature
conditions at a particular engine speed/load point allowed for a maximum of 60% NOX
conversion efficiency, it is not be necessary to dose urea at an NH3-to-NOx ratio (a) of 1:1
(which could allow up to 40% of the NHs to slip) when an a of-0.6 could achieve nearly the
same level of NOX control while minimizing NFFj slip.57 As shown in Figure 22, the
relationship between dosing ratio and NOX conversion is linear up to a ratio of-0.95 (i.e. an a
of 0.7 yields a NOX conversion of 70%, an a of 0.8 yields a NOX conversion of 80%, and so
on). If the dosing ratio is increased beyond 0.95, the additional NFFj injected will not produce
a corresponding increase in NOX conversion, but will begin to result in NH slip. An effective
urea dosing system will operate at this "knee" in curve to maximize NOX conversion while
keeping slip below a designated target value.
4-41
-------
Regulatory Impact Analysis
Figure 22: Effect of dosing ratio on NOX conversion efficiency and NH3 slip.5
100
90 -
80 -
70 -
O 60 -
50
I
o
O
0.7 0.8 0.9 1.0
NH3/NOx Molar Ratio
25
-20 I-
Q.
- 15 ฃ
CO
- 10 -|
o
-5 |
0 "^
1.1
A NOX sensor before (or upstream of) the SCR can be used as a "feed forward" control
input to set the target urea dosing rate and a sensor after (or downstream of) the SCR can be
used as "feedback" to fine-tune the dosing rate for optimum NOX reduction while limiting
ammonia slip. In addition, the feedback control provided by a closed-loop urea dosing system
also mitigates any variation in concentration of the urea-water solution and engine-out NOX
levels by adjusting the control sytem to compensate by increasing/decreasing the urea dosing
rate. The closed-loop system can also adjust to changes in the NOX conversion efficiency as
the SCR ages - as efficiency drops, the a can adapt downward, preventing excessive ammonia
slip.
Closed-loop urea injection systems are already under development for 2010 U.S.
heavy-duty highway diesel engines, U.S. and European light-duty diesel vehicles, and Euro V
on-highway diesel trucks, and these applications have similarif not more dynamicengine
operation as compared to locomotive and marine engine operation. Figure 23 illustrates a
closed-loop urea-SCR control system for onroad diesel applications.58 Figure 24 illustrates a
urea-SCR system concept developed by Volkswagen to meet U.S Tier 2, Bin 5 passenger car
emission standards.59
4-42
-------
Technological Feasibility
Figure 23: Adapted from "SCR Technology for NOX Reduction: Series Experience and State of
Development".
58
SCR Technology for NOx Reduction
System layout for HD/MD, non-air assisted
Temp.-
sensor
1 C 05-CV/EST | 7/7/2005 | SRc:.-
such as copying ana passmo on So tnnrl parties
Engine CAN
Diagn. CANT)
Temp.- Exhaust
sensori a gas sensor
AdBlue - tank
AdBlue level
sensor
BOSCH
4-43
-------
Regulatory Impact Analysis
Figure 24: Adapted from "LNT or Urea SCR Technology: Which is the right technology for TIER 2 BIN
5 passenger vehicles?"59
SCR-System Structure
AdBlue Tank
T Sensor ECU NO, Sensor
Heating
AdBlue Pipe
Metering Valve
To ensure accurate urea injection across all engine operating conditions, these systems
utilize NOX sensors to maintain closed-loop feedback control of urea dosing. These NOX-
sensor-based feedback control systems are similar to oxygen-sensor-based systems that are
used with three-way catalytic converters on virtually every gasoline vehicle on the road today.
The control logic to which the sensors provide input allows for correction of urea dosing to
adequately compensate for both production variation and in-use catalyst degradation. We
believe these NOx-sensor-based control systems are directly applicable to locomotive and
marine engines.
Urea dosing systems under development to meet the light-duty Tier 2 and Heavy-duty
2010 diesel emissions standards also use sophisticated models that predict the mass of NHa
stored within the catalyst system and continuously adjust dosing while taking into account
NH3 storage and release. Prediction of stored NH3 reduces NH3 slip and allows additional
NOX reduction to occur by using stored NH3 for NOx reduction at light load and idle
conditions where exhaust temperatures are typically too low for urea injection and hydrolysis.
EPA's analysis of SCR NOx efficiency in section 4.3.1.2 is thus somewhat conservative since
the ability to reduce NOX emissions using stored NH3 under many conditions where urea
injection and urea hydrolysis are problematic (e.g., operation in notch one and under dynamic
brake conditions) was not taken into consideration. Internal EPA engine testing shows that
using a closed-loop controlled urea dosing system with prediction of stored NH3 can allow
sustained operation at exhaust conditions equivalent to notch 1 operation with 40 to 50% NOX
control.60
4-44
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Technological Feasibility
Ammonia emissions, which are already minimized through the use of closed-loop
feedback urea injection, can be all-but-eliminated with an ammonia slip catalyst downstream
of the SCR catalyst. Such catalysts are in use today and have been shown to be 95% effective
at reducing ammonia emissions. Ammonia slip catalysts that have been developed for Euro V
and U.S. 2010 truck applications have reduced selectivity for NOX formation from ammonia
oxidation and can provide additional SCR NOX conversion via reaction with ammonia within
the slip catalyst itself.
4.3.5.2 Deterioration of NOX Control with Urea-SCR Systems
A concern has been raised by the stakeholder that the iron-zeolite catalysts (as
compared to the vanadium-based catalyst used in trucks in Europe) age rapidly in the
presence of real exhaust and when exposed to elevated temperatures. Part of this concern is
related to data provided by the stakeholder that had originally been presented by researchers
at Ford and General Motors.35'61 The data was characterized as reaching two conclusions:
1. Fe-zeolite catalysts have NOX reduction efficiency of only 55% to 65% when NOX
emissions are predominantly NO.61
2. The NO to NC>2 conversion efficiency of PGM-based DOC's would rapidly
degrade to zero, and thus could not be relied upon to provide any degree of NO to NO2
oxidation to improve the efficiency of Fe-zeolite SCR catalysts.
The first point may be the case for some Fe-zeolite catalysts when operated at catalyst
space velocities much higher than those that would be used for locomotive applications (see
Figure 25). The research cited intentionally undersized the SCR catalyst to accentuate the
impact of NO:NO2 ratio on NOX conversion When comparing the Fe-Zeolite SCR catalyst
example in Figure 25 to a similar, aged Fe-Zeolite system at a lower space velocity (Figure
26), the NOX conversion efficiency increases to approximately 80% to 90% over the exhaust
temperature range for a line-haul locomotive application for the lower space velocity example
with no conversion of NO to NO2. There are two likely reasons for the differences seen
between the results in Figure 25 and the results in Figure 26:
1. Differences in space velocity between the two SCR catalyst systems.
2. Differences in catalyst formulation and/or the supplier of the SCR catalyst
system.
For an appropriately sized locomotive SCR system, >80% NOX conversion for notches 2
through 8 is still possible even with no oxidation of NO to NO2 upstream of the SCR catalyst.
Even when taking into consideration that the catalyst in Figure 25 is undersized, it was
capable of greater than 75% NOX conversion with NO2 as 25% of NOX and greater than 90%
NOX conversion with NO2 as 50% of NOX.
The second point cites NO2 conversion of only 5-30% at the end of life for a passenger
car and then further extrapolates this conversion to near-zero over the life of a locomotive.
4-45
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Regulatory Impact Analysis
Upon reviewing the research in question, it was apparent that the 5 to 30% range referred to
average conversion over the light-duty FTP cycle, and that the lower end of the range (5%)
referred to results achieved when saturating the catalyst with fuel-hydrocarbons. The graph in
Figure 27 is from the same research cited by the stakeholder, and shows the level of reduced
effectiveness for NO to NO2 of the up-front DOC in a compact-SCR system. The four
conditions plotted on the curve all represent NO to NO2 oxidation performance at the same
level of thermal aging but with increasing injection of hydrocarbons. The lowest NO2
oxidation levels reported are for a condition during which the catalyst is completely saturated
with hydrocarbons from direct fuel injection into the exhaust. Once fuel injection ceased,
NO2 oxidation returned to the efficiency represented by the upper curve on the chart. The test
was meant to show how NO2 oxidation degrades if the catalyst becomes temporarily
hydrocarbon saturated during PM trap forced-regeneration or during cold start, and does not
represent aged vs. non-aged DOC results for NO2 oxidation since all of the conditions shown
represent approximately the same thermally-aged condition. Furthermore, in the range of
post-turbine exhaust temperatures encountered by 4-stroke line-haul locomotive engines in
notches 2 through 8 (approximately 275 ฐC to 450 ฐC), NO to NO2 oxidation ranged from
approximately 20% to 50%.
Figure 25: A comparison of zeolite-based and vanadium based urea-SCR catalyst formulations at a space
velocity of 50,000 hr ~l while varying NO2 as a percentage of NOX. Adapted from "Evaluation of Supplier
Catalyst Formulations for the Selective Catalytic Reduction of NOX with Ammonia".61
Formulation Dependence on NO:NO
100
-+ 100% NO2
-*- 75% NO2
* 50% NO2
-ป- 25% NO2
0% NO2
100
150 250 350 450 550
Catalyst Inlet Temperature ("C)
150 250 350 450 550
Catalyst Inlet Temperature ("C)
150 250 350 450 550
Catalyst Inlet Temperature ("C)
** Cu-zeolite
** Fe-zeolite
** Vanadium-based
Maximum NOX conversion for Fe, V at 50% N02 fraction
Maximum NOX conversion for Cu at 75% NO2
Cu-zeolite least sensitive to NO2 fraction at 225ฐC, where N0/N02 matters
Fe-zeolite best at high temperatures (>450ฐC)
** Aged catalysts
4-46
-------
Technological Feasibility
Figure 26: NOX conversion efficiency for an Fe-Zeolite urea-SCR catalyst system while varying NO2 as a
percentage of NOX.62 Note that the black line represents the case of NOX that is 100% NO (0% NO2).
100
SV=30K/hr, NH3=350ppm, (NO+NO,)=350ppm
Aging: 700C/50h/10%H2O
NO/NOx=1
NO/NOx=0.8
N0/N0x=0.5
N0/N0x=0.2
100 200 300 400
Temperature (C)
500
600
Figure 27: Oxidation of NO to NO2 using a PGM-containing DOC and increasing levels of direct fuel
hydrocarbon injection into the exhaust. Exhaust temperatures representative of operation of a 4-stroke
line-haul locomotive are marked in red. Adapted from "Urea SCR and DPF System for Tier 2 Diesel
Light-Duty Truck".35
DOC Performance Evaluation: NO Oxidation
120K mi Equivalent Lab Aging
7 no/
cno/ .
1 no/
no/. -
Exhaust Temperatures
(*
^n-B-S
I
i1!1 ]
1
i
i
i
I
1
f 4Tl
T
ฃฃ
^Iป.^l
D NO2 Curve_HCL_COL
NO2 Curve HCM COL
NO2 Curve HCH COL
NO2 Curve_HCH(LC)_COL
30K hr1
Increasing HC Concentration
iali!T,aj ^ Long Chain HCs -
^^iz^z^On^^^Downstream Fuel Injectk
J'lii*^B
'I^*^^*a^ill$a
^.x. r x-^111'!^^
100 200 300 400
Temperature (ฐC)
500
600
700
4-47
-------
Regulatory Impact Analysis
Figure 28 shows SCR system performance from the same work by Ford researchers,
which shows greater than 90% NOX control over exhaust temperatures consistent with
locomotive operation in notches 2 through 8. The results shown following 20 hours of
thermal aging at 700 ฐC are approximately representative of the maximum thermal aging that
a stakeholder claimed could be encountered during the useful life of a locomotive. The
results for 40 hours of thermal aging at 700 ฐC (or roughly double the thermal conditions
encountered due to locomotive consist operation in tunnels) still shows nearly identical NOX
performance to the 20 hour results in the range of temperatures representative of locomotive
notches 2 through 8 and are generally consistent with the results shown in Figure 26 at
comparable NC>2 as a percentage of NOX. However, the temperature used for aging is still
much higher than what could be achieved even under the most severe locomotive operation.
The typical maximum exhaust temperature for a locomotive is 450 ฐC. During tunnel
operation in a consist, a stakeholder claimed that this temperature can reach 700 ฐC. Recent
work by EPA has shown that the peak exhaust temperature encountered during consist
operation in non-ventilated tunnels will not exceed 560 ฐC - 140 degrees less that previously
stated.39 Futhermore, the peak temperature achieved during the EPA testing was limited by
the locomotives electronic controls to prevent damage to the engine or locomotive, thus it
represents a self-limiting upper bound to in-use post-turbine exhaust temperatures.
Under this lower peak temperature scenario, thermal sintering of the SCR catalyst is
diminished, and durability of the system is enhanced, relative to on-highway applications of
this technology. Therefore, we do not believe that deterioration of the PM and NOx
aftertreatment technologies will be any greater than that stated in our NPRM. Given this
recent information, we are confident that locomotive manufacturers will be able to meet the
Tier 4 standards by the 2015 implementation date.
Comments from a locomotive manufacturer claimed that operation in tunnels for
limited numbers of locomotives could be as high as 50 hours per year.63 Figure 29 shows
NOx conversion and ammonia slip for a combined DPF and Fe-zeolite SCR system before
and after 400 hours of engine dynamometer aging. Engine exhaust temperatures at the SCR
inlet were elevated to 650 ฐC using the DPF's forced regeneration system for the entire 400
hour duration.36 The truck engine used for the tests was a Euro IV configuration with higher
engine-out NOx emissions than that of a Tier 2 line-haul locomotive. NOx efficiencies of
approximately 85 to 95% were achieved at the end of aging. This would represent thermal
degradation beyond the end of useful life even for the limited number of locomotives that
operate in unventilated tunnels for 50 hours per year, especially when considering that the
temperatures during the aging tests exceeded what could be attained during locomotive
operation.
A stakeholder also provided citations to recent SCR durability data generated by the
Ford Motor Company during development of combined base-metal zeolite SCR and CDPF
emission control systems under development to meet Tier 2 bin 5 standards with future light-
duty diesel vehicles. This recent data provided useful insight into the performance
characteristics of some base-metal zeolite SCR formulations at temperatures more severe than
those that could be attained during locomotive operation.64'65'66 High temperature
hydrothermal aging and aging that combined hydrothermal and wet urea injection effects
showed virtually little or no degradation from the fresh condition for temperatures of 670 ฐC
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Technological Feasibility
and below.64'65 Engine durability testing to high hours showed that oil poisoning via
deposition of phosphorus, zinc, and calcium compounds was limited to the first 1" to 1.5"
from the catalyst face, which is the catalyst substrate region often impacted by direct oil
deposition via turbulent diffusion.66 NOx efficiency downstream of this region was effectively
maintained for the duration of the aging tests. The use of a CH-4 lubricant with no limits on
chemical properties during the engine durability testing was confirmed for the Ford engine
tests at the 2007 DEER Conference in Detroit, Michigan.67 Considering the chemical limits
on zinc, phosphorus, and sulfonated ash specified within the current LMOA-approved
locomotive lubricating oils and within the API CJ-4 service category specifications developed
for use with aftertreatment-equipped heavy-duty diesels engines, EPA expects even less
impact from oil poisoning than was seen during the Ford testing using CH-4 lubricant. The
physical layout of the Ford system necessitated by the stringent light-duty Tier 2 cold-start
NOx requirements (DOC followed by SCR with CDPF at the rear) also accentuated the
impact of oil poisoning on the SCR substrates in a manner that would not occur with systems
under development for heavy-duty, nonroad, locomotive or marine applications that typically
place the less oil sensitive DOC and CDPF components upstream of the SCR monoliths.
Such heavy-duty diesel engine system configurations have demonstrated good durability
following extended engine aging using CJ-4 type lubricants.36'37
With respect to combined thermal and lubricating oil consumption effects, EPA
recently conducted engine dynamometer emissions tests with four different combined DPF
and base-metal zeolite SCR systems following engine dynamometer aging for approximately
700 to 1200 hours (hour levels differed among the four systems) at conditions equivalent to
locomotive "notch 8". The operation also included over 100 hours of operation at 580 ฐC
using a forced regeneration system and either 600 to 1100 hours of operation with oil ash
accumulation accelerated by a factor of six relative to the ash accumulation expected from
normal oil consumption. Modifications were made to the electronic engine management
system of a heavy-duty truck engine to provide exhaust temperature and gaseous composition
equivalent to that of a Tier 2 GE 7FDL "GEVO" engine at each of the 8 loaded locomotive
"throttle notch" positions. SCR catalyst volume for the four systems tested was sized for a
maximum space velocity of approximately 40,000 hr"1 at the simulated locomotive "throttle
notch 8" condition, and exhaust flow was scaled relative to " throttle notch 8" for the
remaining loaded conditions. The tested systems were each configured with a DOC and
partial-flow, metal-substrate DPF immediately downstream of the exhaust turbine, followed
by a urea dosing system, static mixer, SCR substrates, and an ammonia slip catalysts. SCR
NOX efficiency was assumed to be negligible for the dynamic brake and idle conditions. NOx
efficiencies of 85% to 98% were observed for the simulated "notch 2" through "notch 8"
conditions following the engine-dynamometer aging procedures (see Figure 30 and Figure
31). This corresponded to emissions of 0.4 to 0.6 g/bhp-hr NOx emissions over the line-haul
cycle for the tested systems.60 Ammonia slip in the exhaust stack outlet did not exceed 10
ppm for any of the tested conditions (Figure 32).
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Regulatory Impact Analysis
Figure 28: NOX conversion efficiency with 20% conversion of NO to NOi for Fe-Zeolite SCR following
different thermal aging conditions. The condition of 20 hours at 700 ฐC represents a condition with
considerably higher temperatures than highest temperatures encountered during line-haul locomotive
tunnel operation as part of a consist. Adapted from "Urea SCR and DPF System for Tier 2 Diesel Light-
Duty Truck".35
SCR Catalyst Durability:
High Temperature
Line-haul Locomotive
100
90 -
c
o
'
g
o
x
O
4k mi SCR catalyst
20h700ฐC
40h 700ฐC
20h725ฐC
20h 750ฐC
20h 800 ฐC
not I/
T-appLO-Xiniately equal to line-haul
e full-life thermal aging based on
Hslst condition
30K h-<
N02/N0x = 0.
NHj/NOx = 1
150 200 250 300
350
400 450 500 550
600
Temperature (3C>
With 20% NO2/NOx feed, the catalyst is durable to 750 ฐC
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Technological Feasibility
Figure 29: NOx conversion efficiency and NH3 slip before and after 400 hours of engine dynamometer
aging at the SCR inlet of 650 ฐC using forced DPF regeneration to increase the exhaust temperature,
adapted from G. Smedler's presentation at the 2007 SAE Heavy Duty Diesel Emissions Symposium,
Gothenburg, Sweden.36 Testing was conducted with a maximum SCR space velocity of 60,000 hr ~l using a
high-engine-out NOx Euro IV HD truck engine.
CO
I
o
o
8
70
60
50
40
30
20
DPF + SCR - with slip cat (NOx), low hrs.
DPF + SCR - with slip cat (NOx), 400 hrs. @ 650 ฐC
'DPF + SCR - with slip cat (NH3), low hrs.
-X -DPF + SCR - with slip cat (NH3), 400 hrs. @ 650 ฐC
200
250
300 350
Temp (C)
400
450
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Regulatory Impact Analysis
Figure 30: NOX reduction efficiency for an Fe-zeolite urea SCR systems. Simulated throttle-notch, space
velocity and turbine outlet temperature are shown on the X-axis. The 1270-hour point corresponds to
1160 hours of notch 8 operation (390 ฐC, ~40,000 hr * space velocity) with oil consumption and ash
poisoning accelerated 6-fold and 110 cumulative hours of operation at an elevated temperature of 580 ฐC.
Urea was dosed throughout the hour accumulation. No significant change in line-haul cycle brake specific
NOX emissions was observed for the Fe-zeolite system during hour accumulation.
"System A" SCR NOx Reduction Efficiency
Throttle Notch
Inlet Temperature
Space Velocity
System A @ 100 hours
-ฉ- System A @ 285 hours
-*- System A @ 560 hours
-- System A @1270 hours
170ฐC
5,200 hr-
7
390 ฐC 400 ฐC
32,000 hr-1 38,000 hr1
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Technological Feasibility
Figure 31: NOX reduction efficiency for Cu-zeolite urea SCR systems. The 730-hour point corresponds to
610 hours of notch 8 operation (390 ฐC, ~40,000 hr * space velocity) with oil consumption and ash
poisoning accelerated 6-fold and 100 cumulative hours of operation at an elevated temperature of 580 ฐC.
Urea was dosed throughout the hour accumulation. A significant NOx reduction was observed at the
"notch 1" condition at low hours. Reduction at this condition was dependent on NH3 storage on the
catalyst sufaces since urea dosing was only used at conditions of "notch 2" and above. The ability to
reduce NOx with stored ammonia at "Notch 1" was less at high hours. NOx reduction over the line-haul
cycle at high hours was comparable to the Fe-Zeolite formulation even though SCR catalyst volume was
20% smaller for the Cu-zeolite formulation (note the higher maximum space velocity in Throttle Notch 8).
System "D" SCR NOx Reduction Efficiency
100%
20%
System D @ 50 hrs.
-e- System D @ 100 hrs.
-*- System D @ 390 hrs.
-*- System D @ 730 hrs.
Throttle Notch
Inlet Temperature
Space Velocity
180ฐC
6,500 hr1
2
280 ฐC
7,000 hr1
3
360 ฐC
13,000 hr1
4
430 ฐC
17,000 hr1
5
400 ฐC
25,000 hr1
6
390 ฐC
33,000 hr1
7 8
380 ฐC 390 ฐC
39,000 hr1 48,000 hr1
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Regulatory Impact Analysis
Figure 32: Ammonia slip for each locomotive "throttle notch" condition following hour accumulation for
the Fe-zeolite urea SCR system (A) and the Cu-zeolite urea SCR system (D). Each system was configured
with an ammonia slip catalyst.
20.0
18.0
16.0
E 14.0
Q.
Q.
I
0
10.0
8.0
System A @ 560 hours
System D @ 390 hours
12345678
Locomotive Throttle Notch
4.3.5.3 Locomotive Parity with the Marine Tier 4 NOX Standard
The stakeholder also expressed concern that with everything else being equal, a
marine engine capable of achieving the 1.3 g/bhp-hr NOX when tested to the marine duty
cycle would only meet 1.7 g/bhp-hr NOX when tested to the locomotive duty cycle. This
would be due primarily to the way that the respective duty cycles used for emissions testing
are conducted and weighted. The E3 Marine Duty Cycle operational points have exhaust
temperatures that correspond to relatively high NOX reduction efficiency with urea-SCR
catalyst systems. The line-haul locomotive test cycle includes some operational points with
exhaust temperatures that may be too low for high SCR NOX reduction efficiency (low idle,
high idle, dynamic brake and Notch 1). But, all things aren't equal. The locomotive
emissions test cycle allows adjustments for reduced idle emissions from the new electronic
control systems such as "automated start/stop" that we expect to be used by all manufacturers.
The Category 2 marine engines that are comparable to, or larger than, line-haul locomotive
engines will meet the same 1.3 Tier 4 NOX standard with SCR three years sooner. They will
also be meeting the Tier 4 NOX standard from a higher engine-out NOX emissions baseline
since many Category 2 Tier 2 Marine engines are currently meeting a 7.3 g/bhp-hr NOX
standard versus current Tier 2 locomotive standard at 5.5 g/bhp-hr NOX. Thus the Tier 4
standards actually represent a slightly higher 82% NOX reduction for Tier 4 marine engines vs.
77% for Tier 4 locomotives. Therefore we believe that the Tier 4 NOX standards for marine
diesel engines are appropriate and represent roughly the same level of emissions stringency.
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Technological Feasibility
4.4 Feasibility of Marine NTE Standards
Changes to the marine diesel engine NTE standards based upon our understanding of
in-use marine engine operation and based upon the underlying Tier 3 and Tier 4 duty cycle
emissions standards that we are finalizing. As background, we determine NTE compliance by
first applying a multiplier to the corresponding duty-cycle emission standard, and then we
compare to that value an emissions result that is recorded when an engine runs within a
certain range of engine operation. This range of operation is called an NTE zone. Refer to 40
CFR 94.106 for details on how we currently define this zone and how we currently apply the
NTE multipliers within that zone.
Based upon our best information of in-use marine engine operation, we will broaden
certain regions of the marine NTE zones, while narrowing other regions. It should be noted
that the first regulation of ours that included NTE standards was the commercial marine diesel
regulation, finalized in 1999. After we finalized that regulation, we promulgated other NTE
regulations for both heavy-duty on-highway and nonroad diesel engines. We also finalized a
regulation that requires heavy-duty on-highway engine manufacturers to conduct field testing
to demonstrate in-use compliance with the on-highway NTE standards. Throughout our
development of these other regulations, we have learned many details about how best to
specify NTE zones and multipliers that help ensure the greatest degree of in-use emission
control, while at the same time help avoid disproportionately stringent requirements for
engine operation that has only a minor contribution to an engine's overall impact on the
environment. Specifically, we are broadening the NTE zones in order to better control
emissions in regions of engine operation where an engine's emissions rates (i.e. grams/hour,
tons/day) are greatest; namely at high engine speed and high engine load. This is especially
important for controlling emissions from commercial marine engines because they typically
operate at steady-state at high-speed and high-load. This also will make our marine NTE
zones much more similar to our on-highway and nonroad NTE zones.
Additionally, we analyzed different ways to define the marine NTE zones, and we
determined a number of ways to improve and simplify the way we define and calculate the
borders of these zones. We feel that these improvements will help clarify when an engine is
operating within a marine NTE zone. We are also finalizing NTE zones for auxiliary marine
engines for both Tier 3 and Tier 4 standards. Because these engines are very similar to
constant-speed nonroad engines, we will adopt the same NTE provisions for auxiliary marine
engines that have already been adopted for constant-speed nonroad engines. Note that we
currently specify different duty cycles to which a marine engine may be certified, based upon
the engine's specific application (e.g., fixed-pitch propeller, controllable-pitch propeller,
constant speed, etc.). Correspondingly, we also have a unique NTE zone for each of these
duty cycles. These different NTE zones are intended to best reflect an engine's real-world
range of operation for that particular application. Refer to the figures in 40 CFR Part 1042,
Appendix III, for illustrations of the changes we are finalizing as part of this rulemaking.
We are also including changes to the NTE multipliers. We have analyzed how the
Tier 3 and Tier 4 emissions standards will affect the stringency of our current marine NTE
standards, especially in comparison to the stringency of the underlying duty cycle standards.
We recognized that in certain sub-regions of our NTE zones, slightly higher multipliers are
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Regulatory Impact Analysis
necessary because of the way that our more-stringent Tier 3 and Tier 4 emissions standards
affect the stringency of the NTE standards. For comparison, our current marine NTE
standards contain multipliers that range in magnitude from 1.2 to 1.5 times the corresponding
duty cycle standard. In the changes we have finalized, the new multipliers range from 1.2 to
1.9 times the standard. Refer to the figures in 40 CFR Part 1042, Appendix III, for
illustrations of the changes we are finalizing.68
We are also adopting other NTE provisions for marine engines that are similar to our
existing heavy-duty on-highway and nonroad diesel NTE standards. These particular changes
to account for the implementation of catalytic exhaust aftertreatment devices on marine
engines and to account for when a marine engine rarely operates within a limited region of the
NTE zone.
Aftertreatment systems generally utilize metallic catalysts, which become highly
efficient at treating emissions above a minimum exhaust temperature. For the most
commonly used metallic catalysts, this minimum temperature occurs in the range of about
(150 to 250) ฐC. In our recent on-highway and nonroad regulations, we identified NOX
adsorber-based aftertreatment technology as the most likely type of technology for on-
highway and nonroad NOX aftertreatment. This NOX adsorber technology utilizes barium
carbonate metals that become active and efficient at temperatures at or above 250 ฐC. Also,
in our on-highway and nonroad rulemakings we identified platinum and platinum/palladium
diesel oxidation catalyst technology for hydrocarbon emission control. This technology also
becomes active and efficient at temperatures at or above 250 ฐC. Therefore, in our on-
highway and nonroad rulemakings for NOX and hydrocarbons emissions, we set a lower
exhaust temperature NTE limit of 250 ฐC, as measured at the outlet of the last aftertreatment
device. We only considered engine operation at or above this temperature as potential NTE
operation.
For marine applications we have hydrocarbon aftertreatment emission control
technology similar to that used in on-highway engines (i.e. diesel oxidation catalyst or DOC).
However, we have identified different aftertreatment technology for NOX control, as
compared to our on-highway and nonroad rulemakings. Specifically, we have identified
selective catalytic reduction (SCR) NOX control technology, which we discussed in detail
earlier in this chapter. We believe that the performance of this different technology needs to
be considered in setting the proper exhaust temperature limits for the marine NTE standards.
While some testing has shown that it is possible to dose urea when exhaust temperatures are
as low as 150 ฐC, the majority of SCR applications require a minimum exhaust gas
temperature of 250 ฐC for effective urea hydrolysis.50 That is why our NTE standards for
both NOX and HC will remain consistent with our on-highway and nonroad regulations (see
40 CFR 86.1370-2007 (g)) and apply only when exhaust gas temperatures are equal to or
greater than 250 ฐC, as measured within 12 inches of the outlet of the aftertreatment device.
4.5 Lead Time
In selecting the models years for which each of the new standards will begin, we
sought to apply them as soon as possible considering the amount of lead time needed by the
manufacturers to design, evaluate, and certify the modified or new engines. For marine
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Technological Feasibility
engines, this was relatively straightforward, since most marine engines have land-based
counterparts that are already scheduled to be subject to new standards. In general, the marine
standards closely follow the land-based standards.
With respect to the amount of lead time needed to develop new locomotive designs, it
is helpful to consider how locomotive development compares to the development process for
highway truck engines and high-speed nonroad diesel engines. For these other categories, we
generally provide the manufacturers at least four years of lead time to develop new engines,
and even more when it requires a major technological shift. For both categories, when
adopting our Tier 4 standards that required the addition of catalysts, we provided
approximately nine years of lead time between the time the standards were adopted and the
first model year the NOx and PM standards had to be fully met (from 2001 to 2010 for heavy-
duty trucks and from 2004 to 2014 for nonroad equipment).
While locomotive manufacturers will benefit to some degree from the transfer of
technologies from these categories, there are two key factors that will offset these advantages.
First, locomotive manufacturers have more limited engineering resources and testing
facilities, and they will need to use these resources to redesign their locomotives to meet the
Tier 4 standards at the same time that they are developing lower emission kits for their Tier 0,
1 and 2 locomotives. Locomotive manufacturers generally have research staffs of a few
dozen engineers and have a handful of test cells. For comparison, highway truck engine
manufacturers typically have thousands of engineers and dozens of test cells. Equally
important, the long useful lives and heavy normal use patterns for locomotives means that
merely proving the durability of new designs can take more than three years even in the best
case.
For these reasons, we believe that 2015 is the earliest that we can apply catalyst-based
Tier 4 standards for locomotives. Moreover, we believe that by requiring compliance this
soon, we also need to adopt the interim flexibilities described in ง1033.150. This timing will
allow manufacturers to finalize their designs over the next few years and perform field testing
before 2015. Since manufacturers are much closer to having their Tier 3 locomotive designs
ready for field testing, those standards can begin in 2012, and those technologies can be
retrofitted to Tier 2 locomotives the following year. Finally, we do not believe that field
testing will be required for the Tier 0 and Tier 1 technologies, so those standards can begin by
2010.
4.6 Conclusions
Even though this rulemaking covers a wide range of engines - and thus requires the
implementation of a range of emission controls technologies - we believe we have identified a
range of technologically feasible emission control technologies that likely will be used to
meet standards. Some of these technologies are incremental improvements to existing engine
components, and many of these improved components have already been applied to similar
engines. The other technologies we identified involve catalytic exhaust aftertreatment
systems. For these technologies we carefully examined the catalyst technology, its
applicability to locomotive and marine engine packaging constraints, its durability with
respect to the lifetime of today's locomotive and marine engines, its impact on the
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Regulatory Impact Analysis
infrastructure of the rail and marine industries, and the safety of its use. From our analysis,
based upon numerous data from automotive, truck, locomotive, and marine industries, we
conclude that incremental improvements to engine components and the implementation of
catalytic PM and NOX exhaust aftertreatment technology are technologically feasible for
locomotive and marine applications, and thus can be used to meet the emissions standards
finalized in this rulemaking.
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Technological Feasibility
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Regulatory Impact Analysis
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Technological Feasibility
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48 "Mineral Commodity Summaries 2006," page 118, U.S. Geological Survey,
www.minerals.usgs.gov/minerals/pubs/mcs/mcs2006.pdf.
49 "Diesel Paniculate Filter Technology for Low-Temperature and Low-NOx/PM Applications", presented by
Sougato Chatterjee, 10th DEER Conference, July 2004.
50 Kowatari, T. et al., "A Study of a New Aftertreatment System (1): A New Dosing Device for Enhancing Low
Temperature Performance of Urea-SCR," SAE 2006-01-0642.
51 Jacobs, T., Chatterjee, S., Conway, R. Walker, A., Kramer, J., Mueller-Hass, K. "Development of Partial Filter
Technology for HDD Retrofit", SAE Technical Paper Series, No. 2006-01-0213, 2006.
52 Jacob, E., Lammerman, R., Pappenheimer, A., Rothe, D. "Exhaust Gas Aftertreatment System for Euro 4
Heavy-duty Engines", MTZ, June, 2005.
53 Pace, L., Konieczny, R., Presti, M. "Metal Supported Paniculate Matter-Cat, A Low Impact and Cost Effective
Solution for a 1.3 Euro IV Diesel Engine", SAE Technical Paper Series, No. 2005-01-0471, 2005.
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Regulatory Impact Analysis
54 Telephone conversation between Brian King, Elliot Bay Design Group, and Brian Nelson, EPA, July 24, 2006.
55 Correspondence from Adam Kotrba of Tenneco. This document is available in Docket EPA-HQ-OAR-2003-
0190-0742.
56 "ABS Rules for Building and Classing - Steel Vessels Under 90 Meters (295 Feet) In Length," Part 4 - Vessel
Systems and Machinery, American Bureau of Shipping, 2006.
57 Ming, C. et al., "Modelling and Optimization of SCR-Exhaust Aftertreatment Systems," SAE 2005-01-0969,
2005.
58 "SCR Technology for NOx Reduction: Series Experience and State of Development," presented by Manuel
Hesser, 11th DEER Conference, August 2005.
59 "LNT or Urea SCR Technology: Which is the right technology for TIER 2 BIN 5 passenger vehicles?,"
presented by Richard Dorenkamp, 12th DEER Conference, August 2006.
60 McDonald, J. "EPA Evaluation of Base-metal Zeolite Urea SCR Systems." This document is available in
Docket EPA-HQ-OAR-2003-0190.
61 "Evaluation of Supplier Catalyst Formulations for the Selective Catalytic Reduction of NOx with Ammonia",
Presented by Steven J. Schmieg and Jong H. Lee at the U.S. DOE 9th CLEERS Workshop, May 2-5, 2006.
62 Data provided to the U.S. EPA by Johnson Matthey Catalytic Systems Division, November 6, 2006.
63 "Comments of General Electric Transportation on Proposed Rule Regarding Control of Emissions of Air
Pollution From Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Liters per
Cylinder," page A-9. This document is available in Docket EPA-HQ-OAR-2003-0190-0590.1
64 Cheng, Y, Hoard, J., Lambert, C., Kwak, J.H., Peden, C.H.F. "Impact of Urea on Hydrothermally Aged
Cu/Zeolite SCR Catalysts." North American Catalysis Society - 20th North American Meeting, June 17-22,
2007.
65 Cavataio, G., Girard, J., Patterson, J.E., Montreuil, C., Cheng, Y. Lambert, C.K. "Laboratory testing of Urea-
SCR Formulations to Meet Tier 2 Bin 5 Emissions." SAE Technical Paper Series, No. 2007-01-1575, 2007.
66 Cheng, Y., Xu, L., Jagner, M., Lamber, C. "Laboratory Postmortem Analysis of 120k mi Engine Aged Urea
SCR Catalyst." SAE Technical Paper Series, No. 2007-01-1579, 2007.
67 Lambert, C. "Post-Mortem of DOC-SCR-DPF System for Tier 2 Light-Duty Diesel Truck." Presentation at
the 2007 Diesel Engine-Efficiency & Emissions Research Conference, August 14, 2007.
68 Online at http://www.gpoaccess.gov/cfr/index.html.
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Engineering Cost Estimates
CHAPTER 5: ENGINEERING COST ESTIMATES 5-2
5.1 Methodology for Estimating Engine and Equipment Engineering Costs 5-3
5.2 Engineering Costs for Freshly Manufactured Engines 5-5
5.2.1 Fixed Engineering Costs 5-5
5.2.2 Variable Engineering Costs 5-24
5.3 Engineering Costs for Freshly Manufactured Equipment 5-51
5.3.1 Fixed Engineering Costs 5-52
5.3.2 Variable Engineering Costs 5-56
5.4 Operating Costs for Freshly Manufactured Tier 4 Engines 5-64
5.4.1 Increased Operating Costs Associated with Urea Use 5-64
5.4.2 Increased Operating Costs Associated with DPF Maintenance 5-65
5.4.3 Increased Operating Costs Associated with Fuel Consumption Impacts 5-65
5.4.4 Total Increased Operating Costs Associated with Freshly Manufactured Tier 4
Engines 5-67
5.5 Engineering Hardware Costs and Operating Costs Associated with the Locomotive
and Marine Remanufacturing Programs 5-73
5.6 Summary of Final Program Engineering Costs 5-82
5.6.1 Engineering Costs for Freshly Manufactured Engines 5-82
5.6.2 Engineering Costs for Freshly Manufactured Equipment 5-83
5.6.3 Operating Costs for Freshly Manufactured Tier 4 Engines 5-84
5.6.4 Engineering Hardware and Operating Costs for Remanufactured Engines ...5-85
5.6.5 Total Engineering and Operating Costs Associated with the Final Program..5-85
5.7 Engineering Costs and Savings Associated with Idle Reduction Technology 5-88
5.8 Analysis of Energy Effects 5-94
5.9 Cost Effectiveness 5-97
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Regulatory Impact Analysis
CHAPTER 5: Engineering Cost Estimates
This chapter presents the engine and equipment engineering costs we have estimated
for meeting the new engine emissions standards.A Section 5.1 includes a brief outline of the
methodology used to estimate the engine and equipment costs. Sections 5.2 and 5.3 present
the projected costs of the individual technologies we expect manufacturers to use to comply
with the new emissions standards, along with a discussion of fixed costs such as research,
tooling, certification, and equipment/vessel redesign. Section 5.4 presents our estimate of
changes in the operating costs that would result from the program and section 5.5 presents
costs associated with the locomotive and marine remanufacturing programs. Section 5.6
summarizes these costs and presents the total program costs. Section 5.7 presents our analysis
of the potential of costs and savings associated with idle reduction technology. Section 5.8
presents our analysis of energy effects and section 5.9 presents our cost-effectiveness
calculations associated with the costs presented in sections 5.2 through 5.6.
To maintain consistency in the way our emission reductions, costs, and cost-
effectiveness estimates are calculated, our cost methodology relies on the same projections of
locomotive and marine engine growth as those used in our emissions inventory projections.
Our emission inventory analyses for marine engines and for locomotives include estimates of
future engine populations that are consistent with the future engine sales used in this cost
analysis.
Note that the costs here do not reflect changes to the fuel used to power locomotive
and marine engines. Our Nonroad Tier 4 rule controlled the sulfur level in all nonroad fuel,
including that used in locomotives and marine engines.8 The sulfur level in the fuel is a
critical element of the locomotive and marine program. However, since the costs of
controlling locomotive and marine fuel sulfur have been considered in our Nonroad Tier 4
rule, they are not considered here. This analysis considers only those costs associated with
the locomotive and marine program.
Additionally, the costs presented here do not reflect any savings that are expected to
occur because of the engine ABT program and the various flexibilities included in the
program. These program features have the potential to provide savings for both engine and
locomotive/vessel manufacturers. While we fully expect companies to use them to reduce
compliance costs, we do not factor them into the cost analysis because they are voluntary
programs. This analysis of compliance costs relates to regulatory requirements that are part of
the final rule for Tiers 3 and 4 emissions standards for locomotive and marine engines.
Unless noted otherwise, all costs are in 2005 dollars.
A We use the term "engineering costs" to differentiate from "social costs." Social costs are discussed in Chapter
7 of this final RIA. For simplicity, the terms "cost" and "costs" throughout the discussion in this Chapter 5
should be taken as referring to "engineering costs."
B See the Regulatory Impact Analysis for the Nonroad Tier 4 final rule, EPA420-R-04-007, May 2004.
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Engineering Cost Estimates
5.1 Methodology for Estimating Engine and Equipment Engineering Costs
This analysis makes several simplifying assumptions regarding how manufacturers
will comply with the new emission standards. First, for each tier of emissions standards
within a given category of engine, we assume a single technology recipe. For example, all
Tier 4 engines in the locomotive category are estimated to be fitted with a selective catalytic
reduction (SCR) system, a diesel particulate filter (DPF), and a diesel oxidation catalyst
(DOC). However, we expect that each manufacturer will evaluate all possible technology
avenues to determine how to best balance costs while ensuring compliance. As noted, for
developing cost estimates, we have assumed that the industry does not make use of the
averaging, banking, and trading program, even though this program offers industry the
opportunity for significant cost reductions. Given these simplifying assumptions, we believe
the projections presented here overestimate the costs associated with different compliance
approaches manufacturers may ultimately take.
Through our background work for this locomotive and marine rule, our past
locomotive and marine rules, and our recent highway and nonroad diesel rules, we have
sought input from a large section of the regulated community regarding the future costs of
applying the emission control technologies expected for diesel engines within the context of
this final program. Under contract with EPA, ICF International (formerly ICF Consulting)
provided questions to several engine and parts manufacturers regarding costs associated with
emission control technologies for diesel engines. The responses to these questions were used
to estimate costs for "traditional" engine technologies such as EGR, fuel-injection systems,
and for marinizing systems for use in a marine environment.l'2
Costs for exhaust emission control devices (e.g., catalyzed DPFs, SCR systems, and
DOCs) were estimated using the methodology used in our 2007 heavy-duty highway
rulemaking. In that rulemaking effort, surveys were provided to nine engine manufacturers
seeking information relevant to estimating the costs for and types of emission-control
technologies that might be enabled with low-sulfur diesel fuel. The survey responses were
used as the first step in estimating the costs for advanced emission control technologies
anticipated for meeting the 2007 heavy-duty highway standards. We then built upon these
costs based on input from members of the Manufacturers of Emission Controls Association
(MECA). We also used this approach as the basis for estimating costs for our recent nonroad
tier 4 (NRT4) rulemaking effort. Because the anticipated emission control technologies for
use on locomotive and marine engines are the same as, or similar to, those expected for
highway and nonroad engines, and because the suppliers of the technologies are the same for
of these engines, we have used that analysis as the basis for estimating the costs of these
technologies in this rulemaking.3
Costs of control include variable costs (for new hardware, its assembly, and associated
markups) and fixed costs (for tooling, research, redesign efforts, and certification). For
technologies sold by a supplier to the engine manufacturers, costs are either estimated based
on a direct cost to manufacture the system components plus a 29 percent markup to account
for the supplier's overhead and profit or, when available, based on estimates from suppliers
on expected total costs to the manufacturers (inclusive of markups).4 Estimated variable costs
for new technologies include a markup to account for increased warranty costs. Variable
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Regulatory Impact Analysis
costs are additionally marked up to account for both manufacturer and dealer overhead and
carrying costs. The manufacturer carrying costestimated to be four percent of the direct
costsaccounts for the capital cost of the extra inventory and the incremental costs of
insurance, handling, and storage. The dealer carrying costestimated to be three percent of
their direct costsaccounts for the cost of capital tied up in extra inventory. We adopted this
same approach to markups in the 2007 heavy-duty highway rule and the NRT4 rule, based on
industry input.5
We have also identified various factors that cause costs to decrease over time, making
it appropriate to distinguish between near-term and long-term costs. Research on the costs of
manufacturing has consistently shown that, as manufacturers gain experience in production,
they are able to apply innovations to simplify machining and assembly operations, use lower
cost materials, and reduce the number or complexity of component parts. This analysis
incorporates the effects of this learning curve as described in Section S.2.2.6
Fixed costs for engine research are estimated to be incurred over the five-year period
preceding introduction of the engine. Fixed costs for engine tooling and certification are
estimated to be incurred one year ahead of initial production. Fixed costs for equipment
redesign are also estimated to be incurred one year ahead of production. We have also
included lifetime operating costs where applicable. These include costs associated with fuel
consumption impacts and urea use, and increased maintenance demands resulting from the
addition of new emission-control hardware. We have also included incremental costs
associated with an increase in remanufacturing costs due to the inclusion of additional
hardware as part of the remanufactured engine.
A simplified overview of the methodology used to estimate engine and equipment
costs is as follows:
For engine research, we have estimated the total dollars that we believe each engine
manufacturer will spend on research to make DPF and SCR systems work together.
We refer to such efforts as corporate research. Also for engine research, we have
estimated the dollars spent to tailor the corporate research to each individual engine
line in the manufacturer's product mix. We refer to such efforts as engine-line
research.
For engine-related tooling costs, we have estimated the dollars that we believe each
engine manufacturer will spend on tooling for each of its engine lines. This amount
varies depending on whether the manufacturer makes only locomotive and/or marine
engines or also makes highway and/or nonroad engines. This amount also varies
depending on the emissions standards to which the engine line is certified (i.e., Tier 3
or 4).
For engine variable costs (i.e., emission-control hardware), we use a three-step
approach:
First, we estimate the cost per piece of technology/hardware. As described in detail in
Section 5.2.2, emission-control hardware costs tend to be directly related to engine
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Engineering Cost Estimates
characteristicsfor example, most emission control devices are sized according to
engine displacement so costs vary by displacement. Because of this relationship, we
are able to determine a variable cost equation as a function of engine displacement.
Second, we determine a sales weighted baseline technology package using a database
from Power Systems Research of all locomotive and marine engines sold in the United
States.7 That database lists engine characteristics for every one of over 40,000
locomotive and marine engines sold in the United States in any given year. Using the
baseline engine characteristics of each engine, the projected technology package for
that engine, and the variable cost equations described in Section 5.2.2, we calculate a
variable cost for the sales weighted average engine in each of several different engine
categories.
Third, this weighted average variable cost is multiplied by the appropriate projected
sales in each year after the new standards take effect to give total annual costs for each
engine category. The sum total of the annual costs for all engines gives the fleetwide
variable costs per year.
Equipment related costsi.e., marine vessels or locomotivesare generated using the
same methodology to estimate the fixed costs for equipment redesign efforts and the
variable costs for new brackets, bolts, and sheet metal that we expect will be required.
This chapter addresses a number of costs including: Engine costs - fixed costs then
variable costs; equipment costs - fixed costs then variable costs; and, operating costs - urea,
maintenance, and fuel consumption impacts; and, remanufacturing program costs. A
summation of these costs is presented in Section 5.6. Variable cost estimates for both engines
and equipment represent an expected incremental cost of the engine or piece of equipment in
the model year of introduction. Variable costs per engine decrease in subsequent years as a
result of several factors, as described below, although these factors do not apply to equipment
variable costs. All costs are presented in 2005 dollars.
5.2 Engineering Costs for Freshly Manufactured Engines
5.2.1 Fixed Engineering Costs
Engine fixed costs consist of research, tooling, and certification. For these costs, we
have made a couple of simplifying assumptions with regard to the timing of marine-related
expenditures due to the complexity of the roll out of the marine engine standards. We have
estimated that, in general, the marine engine fixed costs would be incurred during the years
prior to 2012 (for Tier 3 related costs) and 2016 (for Tier 4 related costs). While this
approach impacts the timing of marine-related expenditures and, thus, the annual costs during
the early years of implementation, it has no impact on the total costs we would estimate in
association with the new standards. However, while having no impact on the total costs we
estimate would be incurred, this approach does have a very minor impact on the net present
value of costs since some early costs (e.g., those for <75 kW Tier 3 engines and >3,700 kW
Tier 4 NOX) are effectively pushed back a couple of years. We believe that the approach
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Regulatory Impact Analysis
taken makes it easier to follow the presentation of costs while having no impact on the results
of the analysis.
5.2.1.1 Engine and Emission Control Device Research
As noted, we estimate costs for two types of engine researchcorporate research, or
that research conducted by manufacturers using test engines to learn how NOX and PM control
technologies work and how they work together in a system; and, engine line research, or that
research done to tailor the corporate knowledge to each particular engine line. For the Tier 3
standards, we are estimating no corporate research since the technologies expected for Tier 3
are "existing" technologies and are well understood. However, we have estimated engine-line
research associated with Tier 3 since those technologies will still need to be tailored to each
engine-line. For Tier 4, we have estimated considerable corporate research since the
technologies expected for Tier 4 are still considered "new" technologies in the diesel engine
market. We have also estimated more engine-line research for Tier 4 so that the corporate
research may be tailored to each engine.
We start this discussion with the more global corporate research. The technologies
described in Chapter 4 represent those technologies we believe will be used to comply with
the new emission standards. These technologies are also part of an ongoing research and
development effort geared toward compliance with the 2007 heavy-duty highway and the
nonroad Tier 4 standards and, to some extent, the current and future light-duty diesel vehicle
standards in the US and Europe. Those engine manufacturers making research expenditures
toward compliance with either highway or nonroad emission standards will have to undertake
some research effort to transfer emission-control technologies to engines they wish to sell into
the locomotive and/or marine markets. These research efforts will allow engine
manufacturers to develop and optimize these new technologies for maximum emission control
effectiveness, while continuing to design engines with good performance, durability, and fuel
efficiency characteristics. However, many engine manufacturers are not part of the ongoing
research effort toward compliance with highway and/or nonroad emission standards because
they do not sell engines into the highway or nonroad markets. These manufacturers-i.e., the
locomotive/marine-only manufacturers-are expected to learn from the research work that has
already occurred and will continue through the coming years through their contact with
highway and nonroad manufacturers, emission-control device manufacturers, and the
independent engine research laboratories conducting relevant research. Despite these
opportunities for learning, we expect the research expenditures for these loco/marine-only
manufacturers to be higher than for those manufacturers already conducting research in
response to the highway and nonroad rules.
We are projecting that SCR systems and DPFs will be the most likely technologies
used to meet the new Tier 4 emission standards. Because these technologies are being
researched for implementation in the highway and nonroad markets well before the
locomotive and marine emission standards take effect, and because engine manufacturers will
have had several years complying with the highway and nonroad standards, we believe that
the technologies used to comply with the locomotive and marine Tier 4 standards will have
undergone significant development before reaching locomotive and marine production. This
ongoing research will likely lead to reduced costs in three ways. First, we expect research
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Engineering Cost Estimates
will lead to enhanced effectiveness for individual technologies, allowing manufacturers to use
simpler packages of emission-control technologies than we would predict today, given the
current state of development. Second, we anticipate that the continuing efforts to improve the
emission-control technologies will include innovations that allow lower-cost production. And
finally, we believe manufacturers will focus research efforts on any drawbacks, such as fuel
economy impacts or maintenance costs, in an effort to minimize or overcome any potential
negative effects.
We anticipate that manufacturers will introduce a combination of primary technology
upgrades to meet the new emission standards. Achieving very low NOX emissions requires
basic research on NOX emission-control technologies and improvements in engine
management. Manufacturers are expected to address this challenge by optimizing the engine
and exhaust emission-control system to realize the best overall performance. This will entail
optimizing the engine and emission control system for both emissions and fuel economy
performance in light of the presence of the new exhaust emission control devices and their
ability to control pollutants previously controlled only via in-cylinder means or with exhaust
gas recirculation. The NOX control technology in particular is expected to benefit from re-
optimization of the engine management system to better match the NOX catalyst's
performance characteristics. The majority of the dollars we have estimated for corporate
engine research is expected to be spent on developing this synergy between the engine and
NOX exhaust emission-control systems. Therefore, for engines where we project use of
exhaust aftertreatment devices, we have attributed two-thirds of the research expenditures to
NOX+NMHC control, and one-third to PM control. This approach is consistent with that
taken in our 2007 heavy-duty highway and NRT4 rules.
To estimate corporate research costs, we begin with our 2007 heavy-duty highway
rule. In that rule, we estimated that each engine manufacturer would expend $35 million for
corporate research toward successfully implementing diesel particulate filters (DPF) and NOX
control catalysts. For this locomotive/marine analysis, we express all monetary values in
2005 dollars which means our starting point equates to just under $39 million.8 For their
locomotive/marine research efforts, engine manufacturers that also sell into the highway
and/or nonroad markets will incur some level of research expense but not at the level incurred
for the highway rule. In many cases, the engines used by highway/nonroad manufacturers in
marine products are based on the same engine platform as those engines used in their
highway/nonroad products. This is also true for locomotive switchers. However, power and
torque characteristics are often different, so manufacturers will need to expend some effort to
accommodate those differences. For these manufacturers, we assume that they will incur an
average corporate research expense of roughly $4 million. This $4 million expense allows for
the transfer of learning from highway/nonroad research to their locomotive/marine engines.
For reasons noted above, two-thirds of this money is attributed to NOX+NMHC control and
one-third to PM control.
For those engine manufacturers that sell engines only into the locomotive and/or
marine markets, and where those engines will be meeting the new Tier 4 standards, we
believe they will incur a corporate research expense approaching that incurred by highway
manufacturers for the 2007 highway rule although not quite at the same level. These
manufacturers will be able to learn from the research efforts already underway for both the
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Regulatory Impact Analysis
2007 highway and nonroad Tier 4 rules (66 FR 5002 and 69 FR 38958, respectively), and for
the Tier 2 light-duty highway rule (65 FR 6698) and analogous rules in Europe. This learning
may come from seminars, conferences, technical publications regarding diesel engine
technology (e.g., Society of Automotive Engineers technical papers), and contact with
highway manufacturers, emission-control device manufacturers, and the independent engine
research laboratories conducting relevant research. In the NRT4 rule, we estimated that this
learning would result in nonroad-only manufacturers incurring 70 percent of the expenditures
as highway manufacturers for the 2007 highway rule. Similarly, we would expect that
locomotive/marine-only manufacturers would incur that same 70 percent of the expenditures
incurred by highway manufacturers for the 2007 highway rule. This numberroughly $27
million versus $39 million in the highway rulereflects the transfer of knowledge to
locomotive/marine-only manufacturers from the many stakeholders in the diesel industry.
Two-thirds of this corporate research is attributed to NOX+NMHC control and one-third to
PM control.
The $4 million and $27 million estimates represent our estimate of the average
corporate research expenditures for engine manufacturers. Any particular manufacturer may
incur more or less than these average figures.
These corporate research estimates are outlined in Table 5-1.
Table 5-1 Estimated Corporate Research Expenditures by Type of Engine Manufacturer Totals per
Manufacturer over Five Years (SMillion, 2005 dollars)
Manufacturer sells into highway and/or
nonroad markets
Manufacturer sells only into locomotive
and/or marine markets
% allocated to PM
% allocated to NOX+NMHC
Manufacturer sells only Tier 3
engines
$0
$0
n/a
n/a
Manufacturer sells Tier 4
engines
$4
$27
33%
67%
Note: Since we expect that the majority of the costs we have estimated for corporate engine research would be
spent on developing the synergy between the engine and NOX exhaust emission-control systems, we have
attributed two-thirds of the corporate research expenditures to NOX+NMHC control and one-third to PM
control.
The PSR database shows that there were 47 engine manufacturers that sold engines
into the locomotive and marine markets in 2002. Of these 47, 12 sold engines into the market
segments required to meet the Tier 4 standards (i.e., expected to need exhaust aftertreatment
devices and, therefore, need to conduct this research). Of those 12, three sold exclusively
into the locomotive and/or marine markets, while the other nine sold engines into the highway
and/or nonroad markets in addition to the locomotive and/or marine markets. As a result, we
estimate that three manufacturers will need to spend the full $27 million conducting research
and nine will spend $4 million, for a total corporate research expenditure of just under $117
million.
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Engineering Cost Estimates
Further, six of these 12 manufacturers sold into both the locomotive and marine
markets and, therefore, will spend a portion of their corporate research dollars during the five
years prior to 2015 (to support locomotive engines), and a portion during the five years prior
to 2016 (to support marine engines). Of the six remaining manufacturers, five sold only into
the marine market so will spend their dollars during the five years prior to 2016. The
remaining manufacturer sold only into the locomotive switcher market and will spend its
corporate research dollars during the five years prior to 2015. Further allocation of corporate
research into marine Cl, marine C2, locomotive switcher, and locomotive line-haul segments
based on the segments into which each manufacturer sold in 2002 results in the total corporate
research expenditures by market segment shown in Table 5-2. We then spread these costs
over the five years in advance of the applicable standards to get the annual costs shown in
Table 5-3. Note that the corporate research expenditures for manufacturers that sell into both
the locomotive line-haul and marine C2 categories are split equally between those two
categories. The same approach is taken for those manufacturers that sell engines across other
categories.
Table 5-2 Estimated Corporate Research Expenditures Allocated by Market Segment (SMillion, 2005
dollars)
Market Segment
Locomotive Switcher/Passenger
Locomotive Line-Haul
Marine Cl
Marine C2
Total Industry Expenditure
Total Corporate Research Expenditure
$10.4
$27.2
$45.4
$33.7
$116.6
PM
$3.4
$9.0
$15.0
$ 11.1
$38.5
NOX+NMHC
$7.0
$ 18.2
$30.4
$22.6
$78.1
Notes: Since we expect that the majority of the dollars we have estimated for corporate engine research would
be spent on developing the synergy between the engine and NOX exhaust emission-control systems, we have
attributed two-thirds of the corporate research expenditures to NOX+NMHC control and one-third to PM
control.
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Regulatory Impact Analysis
Table 5-3 Estimated Corporate Research Expenditures by Year (SMillions, 2005 dollars)
Locomotive Switchers Locomotive Line-Haul
Calendar
Year PM Nฐx+ Subtotal PM Nฐx+ Subtotal
NMHC NMHC
2006
2007
2008
2009
2010 $0.7 $1.4 $2.1 $1.8 $3.6 $5.4
2011 $0.7 $1.4 $2.1 $1.8 $3.6 $5.4
2012 $0.7 $1.4 $2.1 $1.8 $3.6 $5.4
2013 $0.7 $1.4 $2.1 $1.8 $3.6 $5.4
2014 $0.7 $1.4 $2.1 $1.8 $3.6 $5.4
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
Total $3.4 $7.0 $10.4 $9.0 $18.2 $27.2
NPVat7% $2.1 $4.3 $6.5 $5.6 $11.4 $17.0
NPVat3% $2.8 $5.7 $8.4 $7.3 $14.8 $22.1
Marine C1 Marine C2 Totals
PM Nฐx+ Subtotal PM Nฐx+ Subtotal Iฐta' PM Nฐx+
NMHC NMHC sPent NMHC
$7.5 $2.5 $5.0
$3.0 $6.1 $9.1 $2.2 $4.5 $6.7 $23.3 $7.7 $15.6
$3.0 $6.1 $9.1 $2.2 $4.5 $6.7 $23.3 $7.7 $15.6
$3.0 $6.1 $9.1 $2.2 $4.5 $6.7 $23.3 $7.7 $15.6
$3.0 $6.1 $9.1 $2.2 $4.5 $6.7 $23.3 $7.7 $15.6
$3.0 $6.1 $9.1 $2.2 $4.5 $6.7 $15.8 $5.2 $10.6
$15.0 $30.4 $45.4 $11.1 $22.6 $33.7 $116.6 $38.5 $78.1
$8.8 $17.8 $26.5 $6.5 $13.2 $19.7 $69.7 $23.0 $46.7
$11.8 $24.0 $35.8 $8.8 $17.8 $26.6 $93.0 $30.7 $62.3
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Engineering Cost Estimates
As shown in Table 5-3, the net present value of the corporate research is estimated at
$93 million using a three percent discount rate, and $70 million using a seven percent
discount rate.0 We can estimate these expenditures on a per engine basis considering the time
value of money and engine sales for 2006 through 2040, as shown in Table 5-4.
Table 5-4 Estimated Corporate Research per Engine (2005 dollars)
Locomotive
Switcher/Passenger
Locomotive Line Haul
Marine Cl >600 kW
Marine C2
Total
Estimated Cost Allocation
(SMillions)
$8.4
$22.1
$35.8
$26.6
$93.0
Estimated Sales from 2006 to
2040
3,212
19,453
20,039
6,647
49,352
$/engine
$ 2,630
$ 1,140
$ 1,790
$ 4,000
$ 1,880
Note: Net present values of sales are calculated using zero as the sales figure for 2006.
For engine line researchthose engine research efforts done to tailor the corporate
research to each particular engine linewe have first determined the number of engine lines
by considering that, typically, the same basic diesel engine design can be increased or
decreased in size by simply adding or subtracting cylinders. As a result, a four-, six-, or eight-
cylinder engine may be produced from the same basic engine design. While these engines
have different total displacement, they each have the same displacement per cylinder. Using
the PSR database, we grouped each engine manufacturer's engines into distinct engine lines
using increments of 0.5 liters per cylinder. This way, engines having similar displacements
per cylinder are grouped together and are considered to be one engine line. Doing this, we
found there to be 88 engine lines that will need Tier 3 engine line research and 31 engine lines
that will need Tier 4 engine line research. Of the 88 Tier 3 engine lines, eight are locomotive
switcher lines, two are locomotive line haul lines, 13 are C2 marine lines, and 65 are other
marine lines which, due to their size, generally span at least two of the three categories of Cl
marine, recreational, and small commercial marine. For these 65 marine lines, we have
weighted each manufacturer's estimated engine line research costs according to total engine
lines sold into each of these three categories by the particular manufacturer. Of the 31 Tier 4
engine lines, four engine lines had sales in both the locomotive and the marine markets, so we
have split evenly the engine line research between the appropriate segments; two of these four
Throughout Chapter 5 of this RIA, net present value (NPV) calculations are based on the period 2006-2040,
reflecting the period when the NPRM analysis was completed. This has the consequence of discounting the
current year costs, 2007, and all subsequent years are discounted by an additional year. The result is a slightly
smaller NPV of engineering costs than by calculating the NPV over 2007-2040 (3% smaller for 3% NPV and 7%
smaller for 7% NPV). The same convention applies for the emission inventories as shown in Table 5-66. We
have used 2006 because we intended to publish the proposal in 2006. For the final analysis, we have chosen to
continue with 2006 to make comparisons between proposal and final analyses more clear.
5-11
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Regulatory Impact Analysis
were marine-CI/locomotive-switcher engine lines, while the other two were marine-
C2/locomotive-line haul engine lines.
Consistent with our NRT4 rule, for those engine lines adding aftertreatment devices
(i.e., the Tier 4 engine lines) we have estimated the engine line research at $3.2 million per
line for those engines under 600 kW, $6.5 million per line for non-locomotive line-haul
engines over 600 kW, and $55 million per line for locomotive line-haul engines. The
locomotive line-haul estimate is considerably higher than the others because of the high cost
of prototypes for that category. For engine line research associated with the Tier 3 standards,
we have estimated the expenditure per locomotive line-haul engine line at $15 million and at
$1.6 million for all other engine lines. These values are lower than the amount estimated for
Tier 4 since the Tier 3 effort should amount to recalibration work which is less costly than the
work expected for Tier 4 engine lines. The estimated engine line research expenditures by
type of engine manufacturer are shown in Table 5-5 and by market segment for Tier 3 in
Table 5-6 and for Tier 4 in Table 5-7.
Table 5-5 Estimated Engine Line Research Expenditures by Type of Engine Manufacturer Totals per
Engine Line for Tiers 3 & 4 (SMillion, 2005 dollars)
Manufacturer sells into highway
and/or nonroad markets
Manufacturer sells only into
locomotive and/or marine markets
Locomotive Line-haul engine line
% allocated to PM
% allocated to NOX+NMHC
Tier 3 engine line
$ 1.6
$ 1.6
$15.0
33%
67%
Tier 4 engine line <600
kW
$3.2
$3.2
33%
67%
Tier 4 engine line >600
kW
$6.5
$6.5
$55.0
33%
67%
Note: Since we expect that the majority of the dollars we have estimated for engine line research would be spent
on developing the synergy between the engine and NOX exhaust emission-control systems, we have attributed
two-thirds of the engine line research expenditures to NOX+NMHC control and one-third to PM control.
5-12
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Engineering Cost Estimates
Table 5-6 Tier 3 Engine Line Research Expenditures by Market Segment (SMillion, 2005 dollars)
Segment
Small Commercial Marine
Recreational Marine
Marine Cl
Marine C2
Locomotive Switcher/Passenger
Locomotive Line Haul
Total
Engine Lines
<600 kW
Engine Lines
>600kW
65
0
6ฐ
0
63
13
2
2
25
Tier3
$/line
$1.6
$ 1.6
$1.6
$ 15.0
Total
$104
$20.8
$12.8
$30.0
$ 167.6
Note that we have developed hardware costs for switchers based on a single large engine of, generally, over
2000 hp. However, many switchers are powered by several nonroad engines placed in series to arrive at a large
horsepower locomotive. Perhaps it would have been more appropriate to assume research costs for those
engines to be $0 since the effort is, presumably, being done for the nonroad Tier 4 rule. However, to be
conservative, we have included engine line research costs for these engines.
Table 5-7 Tier 4 Engine Line Research Expenditures by Market Segment (SMillion, 2005 dollars)
Segment
Marine Cl
Marine-Cl/Loco-
Switcher/Passenger
Locomotive Switcher/Passenger
Marine C2
Loco-LineHaul
Total
Engine Lines <600
kW
n/a
0
6a
0
0
6
Engine Lines >600
kW
10
2
0
12
2
25
Tier 4
$/line
$6.5
$6.5
$3.2
$6.5
$55.0
Total
$65.0
$ 13.0
$ 19.2
$78.0
$ 110.0
$285.2
Note that we have developed hardware costs for switchers based on a single large engine of, generally, over
2000 hp. However, many switchers are powered by several nonroad engines placed in series to arrive at a large
horsepower locomotive. We could have assumed research costs for those engines to be $0 since the effort is,
presumably, being done for the nonroad Tier 4 rule. However, to be conservative, we have included engine line
research costs for these engines.
We estimate that these engine line research expenditures will be made over a five year
period in advance of the standard for which the cost is incurred. Spreading the costs this way
results in the annual cost streams shown in Table 5-8 for Tier 3 and Table 5-9 for Tier 4 and
Table 5-10 for the final program (i.e., Tiers 3 and 4). D
D Note that we show the Tier 3 engine-line research costs beginning in calendar year 2007 even though this rule
will not be final until the end of 2007 at the earliest. While we usually do not account for investments made
prior to a rule being finalized, we understand that manufacturers have begun spending money that, arguably,
could be considered costs associated with this rule and believe it is appropriate that this rule reflect those
estimates.
5-13
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Regulatory Impact Analysis
Table 5-8 Estimated Tier 3 Engine Line Research Expenditures by Year (SMillions, 2005 dollars)
Locomotive Switchers Locomotive Line Haul
Calendar
Year PM Nฐx+ Subtotal PM Nฐx+ Subtotal
NMHC NMHC
2006
2007 $0.8 $1.7 $2.6 $2.0 $4.0 $6.0
2008 $0.8 $1.7 $2.6 $2.0 $4.0 $6.0
2009 $0.8 $1.7 $2.6 $2.0 $4.0 $6.0
2010 $0.8 $1.7 $2.6 $2.0 $4.0 $6.0
2011 $0.8 $1.7 $2.6 $2.0 $4.0 $6.0
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
Total $4.2 $8.6 $12.8 $9.9 $20.1 $30.0
NPVat7% $3.2 $6.6 $9.8 $7.6 $15.4 $23.0
NPVat3% $3.8 $7.6 $11.4 $8.8 $17.9 $26.7
Marine C1 ; Recreational; n,rir,Q no -1-^,1=.
Small Commercial Marlne C2 Totals
PM Nฐx+ Subtotal PM Nฐx+ Subtotal Iotal, PM Nฐx+
NMHC NMHC sPent NMHC
$6.9 $13.9 $20.8 $1.4 $2.8 $4.2 $33.5 $11.1 $22.5
$6.9 $13.9 $20.8 $1.4 $2.8 $4.2 $33.5 $11.1 $22.5
$6.9 $13.9 $20.8 $1.4 $2.8 $4.2 $33.5 $11.1 $22.5
$6.9 $13.9 $20.8 $1.4 $2.8 $4.2 $33.5 $11.1 $22.5
$6.9 $13.9 $20.8 $1.4 $2.8 $4.2 $33.5 $11.1 $22.5
$34.3 $69.7 $104.0 $6.9 $13.9 $20.8 $167.6 $55.3 $112.3
$26.3 $53.4 $79.7 $5.3 $10.7 $15.9 $128.4 $42.4 $86.1
$30.5 $62.0 $92.5 $6.1 $12.4 $18.5 $149.0 $49.2 $99.9
5-14
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Engineering Cost Estimates
Table 5-9 Estimated Tier 4 Engine Line Research Expenditures by Year (SMillions, 2005 dollars)
Locomotive Switchers Locomotive Line Haul
Calendar
Year PM Nฐx+ Subtotal PM Nฐx+ Subtotal
NMHC NMHC
2006
2007
2008
2009
2010 $1.7 $3.4 $5.1 $7.3 $14.7 $22.0
2011 $1.7 $3.4 $5.1 $7.3 $14.7 $22.0
2012 $1.7 $3.4 $5.1 $7.3 $14.7 $22.0
2013 $1.7 $3.4 $5.1 $7.3 $14.7 $22.0
2014 $1.7 $3.4 $5.1 $7.3 $14.7 $22.0
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
Total $8.5 $17.2 $25.7 $36.3 $73.7 $110.0
NPVat7% $5.3 $10.8 $16.1 $22.7 $46.1 $68.8
NPVat3% $6.9 $14.0 $20.9 $29.5 $60.0 $89.5
Marine C1 > 600 kW Marine C2 Totals
PM Nฐx+ Subtotal PM Nฐx+ Subtotal Iฐta' PM Nฐx+
NMHC NMHC sPent NMHC
$27.1 $9.0 $18.2
$4.7 $9.6 $14.3 $5.1 $10.5 $15.6 $57.0 $18.8 $38.2
$4.7 $9.6 $14.3 $5.1 $10.5 $15.6 $57.0 $18.8 $38.2
$4.7 $9.6 $14.3 $5.1 $10.5 $15.6 $57.0 $18.8 $38.2
$4.7 $9.6 $14.3 $5.1 $10.5 $15.6 $57.0 $18.8 $38.2
$4.7 $9.6 $14.3 $5.1 $10.5 $15.6 $29.9 $9.9 $20.0
$23.6 $47.9 $71.5 $25.7 $52.3 $78.0 $285.2 $94.1 $191.1
$13.8 $28.0 $41.8 $15.0 $30.6 $45.6 $172.3 $56.9 $115.4
$18.6 $37.8 $56.5 $20.3 $41.3 $61.6 $228.6 $75.4 $153.1
5-15
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Regulatory Impact Analysis
Table 5-10 Estimated Tier 3 & Tier 4 Engine Line Research Expenditures by Year (SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
Total
NPVat7%
NPVat3%
Locomotive Switchers
PM Nฐx+ Subtotal
NMHC
$0.8 $1.7 $2.6
$0.8 $1.7 $2.6
$0.8 $1.7 $2.6
$2.5 $5.2 $7.7
$2.5 $5.2 $7.7
$1.7 $3.4 $5.1
$1.7 $3.4 $5.1
$1.7 $3.4 $5.1
$12.7 $25.8 $38.5
$8.5 $17.3 $25.9
$10.7 $21.6 $32.3
Locomotive Line Haul
PM Nฐx+ Subtotal
NMHC
$2.0 $4.0 $6.0
$2.0 $4.0 $6.0
$2.0 $4.0 $6.0
$9.2 $18.8 $28.0
$9.2 $18.8 $28.0
$7.3 $14.7 $22.0
$7.3 $14.7 $22.0
$7.3 $14.7 $22.0
$46.2 $93.8 $140.0
$30.3 $61.5 $91.8
$38.3 $77.9 $116.2
Marine C1 ; Recreational;
Small Commercial
PM Nฐx+ Subtotal
NMHC
$6.9 $13.9 $20.8
$6.9 $13.9 $20.8
$6.9 $13.9 $20.8
$6.9 $13.9 $20.8
$11.6 $23.5 $35.1
$4.7 $9.6 $14.3
$4.7 $9.6 $14.3
$4.7 $9.6 $14.3
$4.7 $9.6 $14.3
$57.9 $117.6 $175.5
$40.1 $81.4 $121.5
$49.2 $99.8 $149.0
Marine C2
PM Nฐx+ Subtotal
NMHC
$1 .4 $2.8 $4.2
$1 .4 $2.8 $4.2
$1 .4 $2.8 $4.2
$1 .4 $2.8 $4.2
$6.5 $13.2 $19.8
$5.1 $10.5 $15.6
$5.1 $10.5 $15.6
$5.1 $10.5 $15.6
$5.1 $10.5 $15.6
$32.6 $66.2 $98.8
$20.3 $41.2 $61.5
$26.4 $53.7 $80.1
Totals
Total RM NOX+
sPent NMHC
$33.5 $11.1 $22.5
$33.5 $11.1 $22.5
$33.5 $11.1 $22.5
$60.7 $20.0 $40.6
$90.6 $29.9 $60.7
$57.0 $18.8 $38.2
$57.0 $18.8 $38.2
$57.0 $18.8 $38.2
$29.9 $9.9 $20.0
$452.8 $149.4 $303.4
$300.8 $99.2 $201.5
$377.6 $124.6 $253.0
5-16
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Engineering Cost Estimates
Table 5-10 shows the total estimated costs associated with engine line research. This
table combines the costs for Tier 3 (Table 5-8) and Tier 4 (Table 5-9). As shown in Table
5-10, the net present value of the engine line research is estimated at $378 million using a
three percent discount rate and $301 million using a seven percent discount rate. We can
estimate these expenditures on a per engine basis considering the time value of money and
engine sales for 2006 through 2040, as shown in Table 5-11.
Table 5-11 Estimated Engine Line Research per Engine (2005 dollars)
Locomotive Switcher/Passenger
Locomotive Line Haul
Small Commercial Marine
Recreational Marine
Marine Cl <600 kW
Marine Cl >600 kW
Marine C2
Total
Estimated Cost Allocation
(SMillions)
$32.3
$ 116.2
$7.1
$23.8
$44.5
$73.6
$80.1
$ 377.6
Estimated Sales from
2006 to 2040
3,212
19,453
228,857
561,291
303,024
20,039
6,647
1,142,525
$/engine
$ 10,050
$ 5,970
$30
$40
$150
$ 3,670
$12,050
$330
Note: Net present values of sales are calculated using zero as the sales figure for 2006.
5.2.1.2 Engine-Related Tooling Costs
Once engines are ready for production, new tooling will be required to accommodate
the assembly of the freshly manufactured engines. In the 2007 heavy-duty highway rule, we
estimated approximately $1.6 million per engine line for tooling costs associated with
DPF/NOX aftertreatment systems. For the NRT4 rule, we estimated that a manufacturer that
sold only into the landbased nonroad market would incur the same amount - $1.65 million
expressed in 2002 dollars - for each engine line that required a DPF/NOX aftertreatment
system. In this rule, we estimate the same level of tooling costs associated with DPF/NOX
aftertreatment for those manufacturers selling only into the locomotive/marine markets, or
$1.8 million in 2005 dollars. We have estimated the same level of tooling costs as in the 2007
highway and NRT4 rules because we expect freshly manufactured locomotive/marine engines
to use technologies with similar tooling needs (i.e., a DPF and a NOX aftertreatment device).
For those manufacturers that sell into the highway and/or nonroad markets and have,
therefore, already made considerable tooling investments, we have estimated an expenditure
of 25 percent of this amount, or $450,000, for those engine lines that will require DPF/NOX
aftertreatment systems for the locomotive/marine market. These costs are assigned equally to
NOX+NMHC control and PM control since the tooling for one should be no more costly than
that for the other.
The tooling estimates discussed above represent our estimates, per engine line, for
engine lines expected to meet the Tier 4 requirements. As noted above in our discussion of
engine line research, we estimate 31 engine lines that will incur these costs. Of those 31 lines,
we estimate that five belong to manufacturers selling exclusively into the locomotive and/or
5-17
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Regulatory Impact Analysis
marine markets. The remaining 26 lines belong to manufacturers that also sell into the
highway and/or nonroad markets. The resultant tooling expenditures associated with the Tier
4 standards are then $22.1 million.
For meeting the Tier 3 requirements, we have estimated lower costs per line because
the engines will require far less in terms of new hardware and, in fact, are expected only to
require upgrades to existing hardware (i.e., new fuel systems). As such, we have estimated
that those manufacturers selling exclusively into the locomotive and/or marine markets will
spend $450,000 per engine line, while manufacturers that also sell into the highway and/or
nonroad markets will spend $180,000 per engine line. The PSR database shows 88 engine
lines that we expect to meet the Tier 3 standards, 13 of which belong to manufacturers that
sell only into the locomotive and/or marine markets. The resultant tooling expenditures
associated with the Tier 3 standards are then $19.4 million. As with the Tier 4 tooling costs,
these costs are assigned equally to NOX control and PM control.
We have applied tooling costs by engine line assuming that engines in the same line
are produced on the same production line. Typically, the same basic diesel engine design can
be increased or decreased in size by simply adding or subtracting cylinders. As a result, a
four-, six-, or eight-cylinder engine may be produced from the same basic engine design.
While these engines have different total displacement, they each have the same displacement
per cylinder. Using the PSR database, we grouped each engine manufacturer's engines into
distinct engine lines using increments of 0.5 liters per cylinder. This way, engines having
similar displacements per cylinder are grouped together and are considered to be built on the
same production line. Note that a tooling expenditure for a single engine line may cover
engines over several market segments. To allocate the tooling expenditure for a given
production line to a specific market segment, we have divided costs equally among the
segments (i.e., an engine line used in both the marine Cl and the locomotive switchers
segments would have its tooling costs split evenly between those two segments).
We estimate that the tooling expenditures would be made one year in advance of
meeting the standards for which the money is spent. A summary of the tooling costs per
manufacturer are shown in Table 5-12. The tooling costs by market segment are shown in
Table 5-13 and the annual cost streams are shown in Table 5-14.
Table 5-12 Estimated Tooling Expenditures by Type of Engine Manufacturer Totals per Engine Line
(SMillion, 2005 dollars)
Manufacturer sells into highway and/or nonroad markets
Manufacturer sells only into locomotive and/or marine markets
% allocated to PM
% allocated to NOX+NMHC
Tier 3 engine lines
$0.18
$0.45
50%
50%
Tier 4 engine lines
$0.45
$ 1.8
50%
50%
Note: We have attributed the tooling costs equally to NOX+NMHC and PM control because we have no
reason to believe that the tooling costs would be greater for one than the other.
5-18
-------
Engineering Cost Estimates
Table 5-13 Estimated Engine Tooling Expenditures by Market Segment and Tier (SMillion, 2005 dollars)
Segment
Marine Cl <600 kW
Marine Cl >600 kW
Marine C2
Recreational Marine
Small Commercial Marine
Locomotive Switcher
Locomotive Line Haul
Total
TierS
$7.9
$1.9
$2.6
$4.2
$ 1.2
$ 1.0
$0.6
$ 19.4
Tier 4
$0
$7.8
$8.9
$0
$0
$3.1
$2.3
$22.1
Total
$7.9
$9.7
$ 11.5
$4.2
$ 1.2
$4.1
$2.8
$41.4
5-19
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Regulatory Impact Analysis
Table 5-14 Estimated Tier 3 and Tier 4 Engine Tooling Expenditures by Year (SMillions, 2005 dollars)
Locomotive
Calendar Year
Switchers Line-Haul Subtotal Marine C
2006
2007
2008
2009
2010
2011 $1.0 $0.6 $1.6 $9.8
2012
2013
2014 $3.1 $2.3 $5.4
2015 $7.8
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
Total $4.1 $2.8 $6.9 $17.6
NPVat7% $2.4 $1.6 $4.0 $10.5
NPVat3% $3.2 $2.2 $5.4 $14.0
Marine Totals
1 Marine C2 Recreational _ Sma" . . Subtotal Total Spent PM Nฐx+
Commercial ^ NMHC
$2.6 $4.2 $1.2 $17.8 $19.4 $9.7 $9.7
$5.4 $2.7 $2.7
$8.9 $16.7 $16.7 $8.3 $8.3
$11.5 $4.2 $1.2 $34.5 $41.4 $20.7 $20.7
$6.2 $2.8 $0.8 $20.3 $24.3 $12.1 $12.1
$8.8 $3.5 $1.0 $27.3 $32.7 $16.4 $16.4
5-20
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Engineering Cost Estimates
As shown in Table 5-14, the net present value of the engine tooling expenditures are
estimated at $33 million using a three percent discount rate, and $24 million using a seven
percent discount rate. We can estimate these expenditures on a per engine basis considering
the time value of money and engine sales for 2006 through 2040, as shown in Table 5-15.
Table 5-15 Estimated Engine Tooling Costs per Engine (2005 dollars)
Locomotive Switcher/Passenger
Locomotive Line Haul
Small Commercial Marine
Recreational Marine
Marine Cl <600 kW
Marine Cl >600 kW
Marine C2
Total
Estimated Cost
Allocation ($Millions)
$3.2
$2.2
$ 1.0
$3.5
$8.2
$5.8
$8.8
$32.7
Estimated Sales from 2006 to 2040
3,212
19,453
228,857
561,291
303,024
20,039
6,647
1,142,525
$/engine
$ 1,000
$110
$4
$10
$30
$290
$ 1,320
$30
Note: Net present values of sales are calculated using zero as the sales figure for 2006.
5.2.1.3 Engine Certification Costs
Manufacturers would incur more than the normal level of certification costs during the
first few years of implementation because all engines would need to be fully certified to the
new emission standards rather than using the normal practice of carrying certification data
over from prior years.E Consistent with our past locomotive and marine standard setting
regulations, we have estimated engine certification costs as shown in Table 5-16. These costs
are consistent with past rulemakings, but have been updated to 2005 dollars. Certification
costs (for engines in all market segments) apply equally to all engine families for all
manufacturers regardless of the markets into which the manufacturer sells.
Note that all engines are certified every year, but most annual certifications involve carrying over test data from
prior years since the engine being certified has not changed in an "emissions-meaningful" way. Since new
standards preclude use of carry-over data, we estimate new certification costs for all engines. Note that this is,
effectively, a conservative estimate since some engines would have changed sufficiently absent our new
standards to require new certification data.
5-21
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Regulatory Impact Analysis
Table 5-16 Certification Costs per Engine Family (2005 dollars)
Locomotive
Small Commercial Marine
Marine Cl 0.92.5
Marine C2 L/cyl>5
$/engine family
$ 42,000
$ 32,000
$ 32,000
$ 43,000
$ 54,000
$ 54,000
# of engine families
46
24
7
19
13
5
To determine the number of engine families to be certified, we looked at our
certification databases for the 2004 model year. For marine engines, our database provides
the number of engine families, the liters per cylinder for each, and specifies whether it is
certified as a Cl or a C2 engine. For locomotive engines, the database provides the engine
displacement. We have also split the Marine Cl certification costs evenly between the Cl
Marine and Recreational Marine market segments in the Tier 3 timeframe. In the Tier 4
timeframe, only those Cl Marine engines over 600 kW would incur certification costs since
those Cl engines under 600 kW will not be meeting the Tier 4 standards. For the small
commercial marine segment, we have estimated the number of engine families at 24 based on
an estimated two families per each of 10 manufacturers selling into that market, and then
another four families sold by marinizers. The costs for small commercial marine would be
incurred only in the Tier 3 timeframe since they will not be meeting the Tier 4 standards.
Similarly, the locomotive certification costs have been split evenly between locomotive
switchers and locomotive line haul for both Tiers 3 and 4. The resultant annual cost streams
are shown in Table 5-17. As shown in the table, the Tier 3 certification costs are estimated at
$4.7 million, while the Tier 4 certification costs are estimated at around $2.8 million.
The total certification expenditures are estimated at $7.4 million, or $6.0 million at a
three percent discount rate and $4.6 million at a seven percent discount rate. The table also
makes clear what portion of the costs are allocated to NOX+NMHC and PM, with a 50/50
allocation.
We can estimate these expenditures on a per engine basis considering the time value
of money and engine sales for 2006 through 2040, as shown in Table 5-18.
5-22
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Engineering Cost Estimates
Table 5-17 Estimated Engine Certification Costs by Year (SMillions, 2005 dollars)
Locomotive
Calenda
Switchers ^ Mar,
2006
2007
2008
2009
2010
2011 $1.0 $1.0 $0.3
2012
2013
2014 $1.0 $1.0
2015 $0.3
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
Total $1.9 $1.9 $0.5
NPVat7% $1.2 $1.2 $0.3
NPVat3% $1.5 $1.5 $0.4
Marine Totals
3 Marrine Recreational lorn- a' PM NOx+
01 mercial Spent NMHC
$0.9 $0.9 $0.8 $4.7 $2.4 $2.4
$1.9 $1.0 $1.0
$0.4 $0.7 $0.4 $0.4
$1.3 $0.9 $0.8 $7.4 $3.7 $3.7
$0.8 $0.6 $0.5 $4.6 $2.3 $2.3
$1.1 $0.7 $0.6 $6.0 $3.0 $3.0
Table 5-18 Estimated Engine Certification Costs per Engine (2005 dollars)
Locomotive
Switcher/Passenger
Locomotive Line Haul
Small Commercial Marine
Recreational Marine
Marine Cl
Marine C2
Total
Estimated Total Cost
Allocation (SMillions)
$1.5
$ 1.5
$0.7
$0.7
$1.1
$0.4
$6.0
Estimated Sales from 2006 to 2040
3,212
19,453
228,857
561,291
323,064
6,647
1,142,525
$/engine
$480
$80
$3
$1
$3
$60
$10
Note: Net present values of sales are calculated using zero as the sales figure for 2006.
5-23
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Regulatory Impact Analysis
Note that these certification costs may overestimate actual costs because they assume
all engines would be certified as a result of the new emission standards. However, some
engines would have been scheduled for new certification independent of the new standards
due to design changes or power increases among other possible reasons. For such engines,
the incremental certification cost would be zero. However, to remain conservative, here we
have applied the certification costs to all engine families.
5.2.2 Variable Engineering Costs
Engine variable costs are those costs for new hardware required to meet the new Tier 4
emission standards. We have estimated no incremental hardware costs associated with the
Tier 3 standards. Unlike the Tier 4 standards, the Tier 3 standards are not based on the
introduction of new emission control technologies on locomotive or marine diesel engines.
Rather, the Tier 3 standards represent the largest level of emission reductions possible from
the emission control systems we project that locomotive and marine engines will already have
in the timeframe of Tier 3 implementation. For example, the marine Tier 3 standards are
predicated on the use of the most modern nonroad Tier 4 base engine technologies without the
use of the nonroad Tier 4 aftertreatment based emission solutions. While these base engines
may represent significant technical advances from the marine Tier 2 engines they replace
having better high pressure fuel systems, better injectors, improved turbochargers, and more
sophisticated electronic control unitswe do not expect the manufacturing costs for these
individual components to increase over the cost of the Tier 2 components they will replace.
In fact, the shift from the Tier 2 engine's electronic unit pump system to the Tier 3 engine's
common rail fuel system may actually result in a fuel system that is cheaper to produce, not
more expensive. Similarly, while the processing power of the Tier 3 engine control computer
may increase significantly, the cost of the computer chip that makes this possible is likely to
be lower. This does not mean that the Tier 3 emission controls come for free. We project
there will be costs incurred to optimize the control strategies to meet the stringent Tier 3
standards and further to test and certify these engines. These costs are accounted for as fixed
costs described further in section 5.2.1 of this RIA.F
For the variable cost estimates presented here, we have used the same methodology to
estimate costs as was used in our 2007 highway and our NRT4 rules. Because of the wide
variation of engine sizes in the locomotive and marine markets, we have chosen an approach
that results not in a specific cost per engine for engines within a given power range or market
segment, but rather a set of equations that can be used to determine the variable costs for any
engine provided its displacement and number of cylinders are known. Using the equations
F To clarify, we have analyzed the fixed costs associated with the switch from unit injectors to common rail fuel
systems reflecting our belief that this transition will come in part because of our regulation. Because we estimate
that common rail fuel systems will be no more expensive than unit injector systems, and may in fact be cheaper,
we have made no estimate of an incremental increase in variable costs due to this switch. Similarly, we have not
made an estimate of what savings (if any) might be realized from this switch.
5-24
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Engineering Cost Estimates
presented in this section, we have then estimated the engine variable costs for the sales
weighted average engine in different power ranges within each market segment.0
The discussion here considers both near-term and long-term cost estimates. We
believe there are factors that cause hardware costs to decrease over time, making it
appropriate to distinguish between near-term and long-term costs. Research in the costs of
manufacturing has consistently shown that as manufacturers gain experience in production,
they are able to apply innovations to simplify machining and assembly operations, use lower
cost materials, and reduce the number or complexity of component parts, all of which allows
them to lower the per-unit cost of production. These effects are often described as the
manufacturing learning curve.9
The learning curve is a well documented phenomenon dating back to the 1930s. The
general concept is that unit costs decrease as cumulative production increases. Learning
curves are often characterized in terms of a progress ratio, where each doubling of cumulative
production leads to a reduction in unit cost to a percentage "p" of its former value (referred to
as a "p cycle"). Organizational learning, which brings about a reduction in total cost, is
caused by improvements in several areas. Areas involving direct labor and material are
usually the source of the greatest savings. Examples include, but are not limited to, a
reduction in the number or complexity of component parts, improved component production,
improved assembly speed and processes, reduced error rates, and improved manufacturing
process. These all result in higher overall production, less scrappage of materials and
products, and better overall quality. As each successive p cycle takes longer to complete,
production proficiency generally reaches a relatively stable plateau, beyond which increased
production does not necessarily lead to markedly decreased costs.
Companies and industry sectors learn differently. In a 1984 publication, Button and
Thomas reviewed the progress ratios for 108 manufactured items from 22 separate field
studies representing a variety of products and services.10 The distribution of these progress
ratios is shown in Figure 5-1. Except for one company that saw increasing costs as
production continued, every study showed cost savings of at least five percent for every
doubling of production volume. The average progress ratio for the whole data set falls
between 81 and 82 percent. Other studies (Alchian 1963, Argote and Epple 1990, Benkard
1999) appear to support the commonly used p value of 80 percent, i.e., each doubling of
cumulative production reduces the former cost level by 20 percent.
G For example, if two engines are sold with one being 100 hp and having 5 sales, the other being 200 hp and
having 20 sales, the sales weighted horsepower of engines sold would not be 150 hp but would instead be 180 hp
(100x5 + 200x20 = 4,500; 4,500/25 = 180).
5-25
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Regulatory Impact Analysis
Figure 5-1 Distribution of Progress Ratios (Button and Thomas 1984)
15
10
Distribution of Progress Ratios
55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 191 103 105 107
Progress Ratio
From 22 field studies (n = 108).
The learning curve is not the same in all industries. For example, the effect of the
learning curve seems to be less in the chemical industry and the nuclear power industry where
a doubling of cumulative output is associated with 11 percent decrease in cost (Lieberman
1984, Zimmerman 1982). The effect of learning is more difficult to decipher in the computer
chip industry (Gruber 1992).
We believe the learning curve is appropriate to consider in assessing the cost impact of
diesel engine emission controls. The learning curve applies to new technology, new
manufacturing operations, new parts, and new assembly operations. Neither locomotive nor
marine diesel engines currently use any form of NOX or PM aftertreatment except in very
limited retrofit applications. Therefore, these are new technologies for these engines and will
involve some new manufacturing operations, new parts, and new assembly operations beyond
those anticipated in response to the 2007 highway and NRT4 rules. Since this will be a
freshly manufactured product, we believe this is an appropriate situation for the learning
curve concept to apply. Opportunities will exist to reduce unit labor and material costs and
increase productivity as discussed above. We believe a similar opportunity exists for the new
control systems that will integrate the function of the engine and emission-control
technologies. While impacted diesel engines beginning with Tier 3 compliance are expected
to have the basic components of this systemadvanced engine control modules (computers),
advanced engine air management systems (cooled EGR, and variable geometry
turbocharging), and advanced electronic fuel systems including common rail systemsthey
will be applied in some new ways in response to the Tier 4 standards. Additionally some new
components will be applied for the first time. These freshly manufactured parts and
assemblies will involve new manufacturing operations. As manufacturers gain experience
with these systems, comparable learning is expected to occur with respect to unit labor and
5-26
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Engineering Cost Estimates
material costs. These changes require manufacturers to start new production procedures,
which will improve with experience.
We have applied a p value of 80 percent beginning with the first year of introduction
of any new technology. That is, variable costs were reduced by 20 percent for each doubling
of cumulative production following the year in which the technology was first introduced in a
given market segment. Because the timing of the emission standards in this final rule follows
that of the 2007 highway and NRT4 rules, we have used the first stage of learning done via
those rules collectively as the starting point of learning for locomotive and marine engines. In
other words, one learning phase is factored into the baseline costs for locomotive/marine
engines. We have then applied one additional learning step from that baseline. In the 2007
highway rule, we applied a second learning step following the second doubling of production
estimated to occur at the end of the 2010 model year. We could have chosen that point as our
baseline case for this rule and then applied a single learning curve effect from there. Instead,
to remain conservative, we have chosen to use only the first learning step from the
highway/nonroad rules. The approach taken here is consistent with the approaches taken in
our Tier 2 light-duty highway rule and the 2007 highway rule for heavy-duty gasoline
engines. There, compliance was being met through improvements to existing technologies
rather than the development of new technologies. We argued in those rules that, with existing
technologies, there is less opportunity for lowering production costs. For that reason, we
applied only one learning curve effect. The situation is similar for locomotive and marine
engines. Because these will be existing technologies by the time they are introduced into the
market, there would arguably be less opportunity for learning than there will be for the
highway engines on which the technologies were first introduced.
Another factor that plays into our near-term and long-term cost estimates is that for
warranty claim rates. In our 2007 highway rule, we estimated a warranty claim rate of one
percent. Subsequent to that rule, we learned from industry that repair rates can be as much as
two to three times higher during the initial years of production for a new technology relative
to later years.u As a result, in our NRT4 rule, we applied a three percent warranty claim rate
during the first two years and then one percent warranty claim rate thereafter. We have used
the same approach here as used in the NRT4 rule. This difference in warranty claim rates, in
addition to the learning effects discussed above, is reflected in the different long-term costs
relative to near-term costs.
5.2.2.1 SCR System Costs
The NOX aftertreatment system anticipated for the Tier 4 standards is the selective
catalytic reduction (SCR) system. For the SCR system to function properly, a systems
approach that includes a reductant metering system and control of engine-out NOX emissions
is necessary. Many of the new air handling and electronic system technologies developed to
meet past locomotive and marine standards, and past highway and nonroad standards can be
applied to accomplish the SCR system control functions as well. Some additional hardware
for exhaust NOX or oxygen sensing may also be required.
We have used the same methodology to estimate costs associated with SCR systems as
was used in our 2007 highway and NRT4 rulemakings for other aftertreatment devices. The
5-27
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Regulatory Impact Analysis
basic components of the SCR system are well known and include the following material
elements:11
a ceramic substrate upon which a NOX catalyst washcoating is applied;
a can to hold and support the substrate;
a reductant injector and associated plumbing;
an exhaust gas sensor (e.g., a NOX sensor) used for control.
Examples of these material costs are summarized in Table 5-19 and represent costs to
the engine manufacturers inclusive of supplier markups. The manufacturer costs shown in
Table 5-19 include additional markups to account for both manufacturer and dealer overhead
and carrying costs. The application of overhead and carrying costs is consistent with the
approach taken in the 2007 highway and NRT4 rulemakings. In those rules, we estimated the
markup for catalyzed emission-control technologies based on input from catalyst
manufacturers. Specifically, we were told that device manufacturers could not mark up the
cost of the individual components within their products because those components consist of
basic commodities (for example, precious metals used in the catalyst could not be arbitrarily
marked up because of their commodity status). Instead, manufacturing entities could mark up
costs only where they add a unique value to the product. In the case of catalyst systems, the
underlying cost of precious metals, catalyst substrates, PM filter substrates, and canning
materials were well known to both buyer and seller and no markup or profit recovery for
those component costs could be realized by the catalyst manufacturer. In essence, these are
components to which the supplier provides little value-added engineering.
The one component that is unique to each catalyst manufacturer (i.e., the component
where they add a unique value) is the catalyst washcoat support materials. This mixture
(which is effectively specialized clays) serves to hold the catalytic metals in place and to
control the surface area of the catalytic metals available for emission control. Although the
price for the materials used in the washcoat is almost negligible (i.e., perhaps one or two
dollars), we have estimated a substantial cost for washcoating based on the engineering value
added by the catalyst manufacturer in this step. This is reflected in the costs presented for
SCR systems and DPF systems. This portion of the cost estimate - the washcoating - is
where the catalyst manufacturer recovers the fixed cost for research and development as well
as realizes a profit. To these manufacturer costs, we have added a four percent carrying cost
to account for the capital cost of the extra inventory, and the incremental costs of insurance,
handling, and storage. A dealer carrying cost is also included to cover the cost of capital tied
up in extra inventory. Considering input received from industry, we have adopted this
H Note that our draft cost analysis included costs for the urea storage tank and computer controller in the SCR
system costs. For our final cost analysis, we have removed those costs from the SCR system and are, instead,
accounting for those costs in our discussion of equipment related variable costs. We have also made a
corresponding reduction in the labor costs for SCR systems since the urea tank and controller labor is now being
considered at the equipment level. That discussion is in section 5.3.2 of this RIA.
5-28
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Engineering Cost Estimates
approach of estimating individually the manufacturer and dealer markups in an effort to better
reflect the value each entity adds at various stages of the supply chain.12 Also included is our
estimate of warranty costs for the system.
5-29
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Regulatory Impact Analysis
Table 5-19 SCR System Costs (costs shown are costs per SCR system for the given engine power/displacement, 2005 dollars)
Typical Engine Power (kW)
Typical Engine Displacement (Liter)
Material and component costs
Catalyst Volume (Liter)
Substrate
Washcoating and Canning
Platinum
Catalyst Can Housing
Urea Injection Assembly
Reductant Solution Tank & Controls (see section 5.3.2)
NOX sensor (1 sensor/engine)
DOC for cleanup
Direct Labor Costs
Estimated Labor hours
Labor Rate ($/hr)
Labor Cost
Labor Overhead @ 40%
Total Direct Costs to Mfr.
Warranty Cost (3% claim rate)
Mfr. Carrying Cost - Near term
Total Cost to Dealer - Near term
Dealer Carrying Cost - Near term
Baseline Cost to Buyer - Near term
Loco/Marine Cost to Buyer (includes highway learning) - Near term
Warranty Cost (1 % claim rate)
Mfr. Carrying Cost - Long term
Total Cost to Dealer - Long term
Dealer Carrying Cost - Long term
Baseline Cost to Buyer - Long term
Baseline Cost to Buyer (includes Highway Learning) - Long term
Loco/Marine Cost to Buyer (includes Loco/Marine learning) - Long term
7
0.4
1.0
$29
$423
$0
$12
$500
$0
$200
$236
3
$18
$54
$22
$1 ,476
$111
$59
$1 ,646
$49
$1,695
$1,356
$37
$59
$1,572
$47
$1,619
$1,295
$1,036
25
i""s
3.8
$113
$517
$0
$12
$527
$0
$200
$255
3
$18
$54
$22
$1 ,699
$128
$68
$1 ,895
$57
$1 ,952
$1,561
$43
$68
$1,810
$54
$1 ,864
$1 ,491
$1,193
57 ! 187
3.9 : 7.6
9.8 19.1
$294 ' $573
$721 $1 ,035
$0 ' $0
$13 ; $15
$585 $674
$0 i $0
$200 $200
$297 ' $362
3 3
$18 : $18
$54 $54
$22 ! $22
$2,186 $2,935
$164 ; $220
$87 $117
$2,438 : $3,273
$73 $98
$2,511 I $3,371
$2,009 $2,697
$55 I $73
$87 $117
$2,329 ' $3,126
$70 $94
$2,399 ' $3,220
$1,919 ! $2,576
$1,535 I $2,061
375
18.0
45.0
$1 ,350
$1,910
$0
$20
$922
$0
$200
$543
3
$18
$54
$22
$5,021
$377
$201
$5,599
$168
$5,767
$4,613
$126
$201
$5,348
$160
$5,508
$4,406
$3,525
746
34.5
86.3
$2,588
$3,302
$0
$28
$1,318
$0
$200
$831
6
$18
$108
$43
$8,419
$626
$337
$9,382
$281
$9,663
$7,730
$209
$337
$8,964
$269
$9,233
$7,387
$5,909
3730
188.0
470.0
$14,100
$16,258
$0
$100
$5,000
$0
$200
$3,511
6
$18
$108
$43
$39,321
$2,944
$1,573
$43,838
$1,315
$45,153
$36,122
$981
$1,573
$41 ,875
$1,256
$43,131
$34,505
$27,604
5-30
-------
Engineering Cost Estimates
We have estimated the cost of this system based on information from several
reports.13' 14' 15 The individual estimates and assumptions used to estimate the cost for the
system are touched upon in the following paragraphs.
SCR Catalyst Volume
During development of this rule, engine and aftertreatment device manufacturers have
indicated that SCR catalyst volumes could be from one to three times engine displacement for
locomotive and marine applications. As explained in Chapter 4 of this RIA, we have used a
ratio of SCR volume to engine displacement equal to 2.5:1.
SCR Catalyst Substrate
The ceramic flow-through substrates used for the SCR catalyst were estimated to cost
$30 per liter.
SCR Catalyst Washcoating and Canning
We have estimated a "value-added" engineering and material product, called
washcoating and canning, based on feedback from members of the Manufacturers of Emission
Control Association (MECA). By using a value-added component that accounts for fixed
costs (including R&D), overhead, marketing and profits from likely suppliers of the
technology, we can estimate this fraction of the cost for the technology apart from other
components that are more widely available as commodities (e.g, precious metals and catalyst
substrates). Based on conversations with MECA, we understand this element of the product
to represent the catalyst manufacturer's value added and, therefore, their opportunity for
markup. As a result, the washcoating and canning costs shown in Table 5-19 represent costs
with manufacturer markups included. The washcoating and canning costs can be expressed as
$34(x) + $390, where x is the catalyst volume in liters. This washcoating cost is higher than
our past rulemakings because of dual washcoating process we anticipate will be used to "zone
coat" the diesel oxidation function onto a portion of the SCR catalyst (as discussed below).
SCR Catalyst Precious Metals
We expect that the SCR catalysts used in locomotive and marine applications will
contain no precious metals (e.g., the platinum group metals platinum, palladium, and
rhodium). As a result, we have estimated zero costs associated with these commodities.
SCR Can Housing
The material cost for the can housing is estimated based on the catalyst volume plus
20 percent for transition (inlet/outlet) cones, plus 20 percent for scrappage (material
purchased but unused in the final product) and a price of $1 per pound for 18 gauge stainless
steel as estimated in a contractor report to EPA and converted into $2005.16
5-31
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Regulatory Impact Analysis
Reductant Injection Assembly
The costs for the reductant injection assembly are based in part on our past contractor
report that estimated the costs at $250 to $300 for units meant for 12 to 26 liter catalysts.
Here, we have adjusted the numbers based on recent conversations with industry by
estimating the costs for the smallest engines at $500 and the largest at $5,000. We then used a
linear interpolation to arrive at the costs for engines in between.
Reductant Solution Tank and Brackets
These costs are now addressed in section 5.3.2 where we present equipment-related
hardware costs.
NOX Sensor Cost
We believe that one sensor will be needed per catalyst and have used an estimated cost
of $200 per sensor based on today's cost of $300 for use in retrofit applications (retrofit
applications are typically considerably more costly than new). With increased NOX sensor
sales volumes in future locomotive, marine, highway, and nonroad markets, we believe that
NOX sensor costs may well be in the $50 to $100 range, if not lower. For this analysis,
reflecting the relatively low sales volumes of locomotive and marine engines relative to
highway engines, we have chosen to remain conservative by using the $200 per sensor
estimate.
DOC for Cleanup
Included in the costs for the SCR system are costs for a diesel oxidation catalyst
(DOC) for clean-up of possible excess ammonia emissions that might occur as a result of
excessive urea usage. The methodology used to estimate DOC costs is consistent with the
SCR system cost methodology and is presented below in Table 5-20. These cost estimates
use a DOC to engine displacement ratio of 0.8:1 because the low emissions conversion
demand placed on the DOC is not expected to require a larger device. This ratio is higher
than the ratio used in the draft cost analysis where we used a ratio of 0.5:1. The 0.8:1 ratio is
consistent with our technological feasibility discussion in Chapter 4 of this RIA.
5-32
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Engineering Cost Estimates
Table 5-20 Diesel Oxidation Costs (costs shown are costs per SCR system for the given engine power/displacement, 2005 dollars)
Typical Engine Power (kW)
Typical Engine Displacement (Liter)
Material and component costs
Catalyst Volume (liter)
Substrate
Washcoating and Canning
Platinum
Catalyst Can Housing
Direct Labor Costs
Estimated Labor hours
Labor Rate ($/hr)
Labor Cost
Labor Overhead @ 40%
Total Direct Costs to Mfr.
Warranty Cost - Near Term (3% claim rate)
Mfr. Carrying Cost - Near Term
Total Cost to Dealer - Near Term
Dealer Carrying Cost - Near Term
Loco/Marine Cost to Buyer
7 :
0.4 !
:
0.3
$0
$189
$2
$0 ;
0.5 :
$18
$9 !
$4
$203 i
$17
$8 I
$229
$7 !
$236 I
25 !
i.5 ;
:
1.2
$0 '
$201
$6 '
$0 !
0.5 !
$18
$9 !
$4
$220 |
$19
$9 I
$247
$7 :
$255 I
57 !
3.9 :
3.1
$0 '
$228
$16 '
$0 ;
0.5 :
$18
$9 i
$4
$257 ;
$21
$10 I
$289
$9 !
$297 |
187 !
7.6 :
:
6.1
$0 '
$270
$31
$0 !
0.5 !
$18
$9 !
$4
$313 ;
$26
$13 I
$352
$11 !
$362 I
375 !
18.0 :
:
14.4
$0 '
$385
$73 '
$0 !
0.5 !
$18
$9 !
$4
$471 !
$37
$19 I
$527
$16 !
$543 I
746 !
34.5 :
:
27.6
$0 '
$568
$141
$0 ;
0.5 :
$18
$9 !
$4
$722 !
$56
$29 I
$807
$24 !
$831 I
3730
188.0
150.4
$0
$2,275
$768
$0
0.5
$18
$9
$4
$3,056
$231
$122
$3,409
$102
$3,511
5-33
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Regulatory Impact Analysis
Important to note here is that we expect the DOC function to be fulfilled within the
confines of the SCR catalyst using a process known as "zone coating" by which the DOC
washcoat is applied to the tail end of the SCR catalyst substrate. By doing this, a physically
separate DOC is not necessary. We have remained conservative in our cost analysis by
including costs associated with canning of the DOC.
Direct Labor Costs
The direct labor costs for the catalyst are estimated based on an estimate of the number
of hours required for assembly and established labor rates. Additional overhead for labor was
estimated as 40 percent of the labor costs.
SCR Warranty Costs
We have estimated both near-term and long-term warranty costs. Near-term warranty
costs are based on a three percent claim rate and an estimate of parts and labor costs per
incident, while long-term warranty costs are based on a one percent claim rate and an estimate
of parts and labor costs per incident.17 The labor rate is assumed to be $50 per hour with four
hours required per claim, and parts costs are estimated to be 2.5 times the original
manufacturing cost for the component. The calculation of near-term warranty costs for the 7
kW engine shown in Table 5-19 is as follows:
[($29+$423+$12+$500+$200+$236)(2.5) + ($50)(4hours)](3%) = $111
Manufacturer and Dealer Carrying Costs
The manufacturer's carrying cost was estimated at 4 percent of the direct costs. This
reflects primarily the costs of capital tied up in extra inventory, and secondarily the
incremental costs of insurance, handling and storage. The dealer's carrying cost was
estimated at 3 percent of the incremental cost, again reflecting primarily the cost of capital
tied up in extra inventory.
SCR System Cost Estimation Function
Using the example SCR system costs shown in the table, we calculated a linear
regression to determine the SCR system cost as a function of engine displacement. This way,
the function can be applied to the wide array of engines in the locomotive line haul and
marine fleets to determine the total or per engine costs for SCR hardware. The functions
calculated for SCR system costs in line-haul locomotives and marine applications are shown
in Table 5-21.
For locomotive switcher applications, we have used the costs developed for our NRT4
rulemaking because locomotive switchers tend to be powered by land based nonroad engines.
For this reason, it seemed most appropriate to use the same costs developed for that rule.
These costs are also shown in Table 5-21.
5-34
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Engineering Cost Estimates
Table 5-21 SCR System Costs as a Function of Engine Displacement, x, in Liters (2005 dollars)
Line haul locomotive; marine
Switcher locomotive
Near-term cost function
Long-term cost function
Near-term cost function
Long-term cost function
Linear Regression
$185(x) + $1,293
$142(x) + $988
$103(x) + $183
$83(x) + $160
R2
0.999
0.999
0.999
0.999
Note: Near term costs include a 3 percent warranty claim rate while long term costs include a 1 percent
warranty claim rate and the learning effect.
This table shows both a near-term and a long-term cost function for SCR system costs.
The near-term function incorporates the near-term warranty costs determined using a three
percent claim rate, while the long-term function incorporates the long-term warranty costs
determined using a one percent claim rate. Additionally, the long-term function incorporates
learning curve effects.
5.2.2.2 DPF System Costs
One means of meeting the Tier 4 PM standard is to use a diesel particulate filter (DPF)
system like that expected to be used for highway and NRT4 applications. However, as
explained in Chapter 4 of this RIA, here we are projecting a DPF volume to engine
displacement ratio of 1.7:1. In the highway and nonroad rules, we projected ratios of 1.5:1.
For the DPF to function properly, a systems approach that includes precise control of engine
air-fuel ratio is also necessary. Many of the new air handling and electronic fuel system
technologies developed in order to meet the highway, nonroad, and past locomotive/marine
standards can be applied to accomplish the DPF control functions as well.
We have used the same methodology to estimate costs associated with DPF systems as
was used in our 2007 highway and NRT4 rulemakings. The basic components of the DPF are
well known and include the following material elements:
An oxidizing catalyst, typically platinum;
a substrate upon which the catalyst washcoating is applied and upon which PM is trapped;
a can to hold and support the substrate.
Examples of these material costs are summarized in Table 5-22 and represent costs to
the engine manufacturers inclusive of supplier markups. The total direct cost to the
manufacturer includes an estimate of warranty costs for the DPF system. Hardware costs are
additionally marked up to account for both manufacturer and dealer overhead and carrying
costs. The manufacturer's carrying cost was estimated to be four percent of the direct costs
accounting for the capital cost of the extra inventory, and the incremental costs of insurance,
handling, and storage. The dealer's carrying cost was marked up three percent reflecting the
cost of capital tied up in inventory. We have adopted this approach of estimating individually
the manufacturer and dealer markups in an effort to better reflect the value added at each
5-35
-------
Regulatory Impact Analysis
stage of the supply chain based on industry input.18 Note that our final costs for DPF systems
are identical to those presented in the draft cost analysis.
5-36
-------
Engineering Cost Estimates
Table 5-22 DPF System Costs (costs shown are costs per DPF system for the given engine power/displacement, 2005 dollars)
Typical Engine Power (kW)
Typical Engine Displacement (Liter)
Material and component costs
Filter Volume (Liter)
Filter Trap
Washcoating and Canning
Platinum
Filter Can Housing
Differential Pressure Sensor
Direct Labor Costs
Estimated Labor hours
Labor Rate ($/hr)
Labor Cost
Labor Overhead @ 40%
Total Direct Costs to Mfr.
Warranty Cost - Near Term (3% claim rate)
Mfr. Carrying Cost - Near Term
Total Cost to Dealer - Near Term
Dealer Carrying Cost - Near Term
Savings by removing silencer
Baseline Cost to Buyer - Near Term
Loco/Marine Cost to Buyer (includes highway learning) - Near term
Warranty Cost - Long Term (1 % claim rate)
Mfr. Carrying Cost - Long Term
Total Cost to Dealer Long Term
Dealer Carrying Cost - Long Term
Savings by removing muffler
Baseline Cost to Buyer - Long Term
Baseline Cost to Buyer (includes Highway Learning) - Long term
Loco/Marine Cost to Buyer (includes Loco/Marine learning) - Long term
7 !
0.4
0.7 ;
$46 !
$96
$41
$9 !
$52 :
4
$18 :
$72 i
$29
$345
$21 !
$14 ;
$380
$11
($52) ;
$340
$272
$7 :
$14 I
$366
$11
($52) |
$325 :
$260
$208 |
25 !
1.5
2.6 i
$176 !
$111
$156
$10 !
$52 !
4
$18 !
$72 ,
$29
$606
$41 i
$24 ;
$671
$20
($52) i
$640
$512
$14 :
$24 i
$644
$19
($52) !
$611 i
$489
$391 |
57 :
3.9
6.7 ;
$461 |
$143
$408
$11
$52
4
$18
$72
$29
$1,175
$84 i
$47 ;
$1,306
$39
($52) .
$1,293
$1,035
$28 :
$47 ]
$1,250
$38
($52) !
$1,236 ;
$989
$791 |
187 !
7.6
1 3.0 :
$898 ;
$192
$796 "
$12 :
$52
4 "
$18
$72
$29
$2,051
$149 ;
$82
$2,282
$68 "
($52) i
$2,298
$1,839
$50 "
$82 i
$2,182
$65 "
($52) "
$2,196 ;
$1,757
$1,405 1
375 :
Tab'
30.6 ;
$2,117 ;
$328
$1,874
$16
$52 i
4
$18 :
$72
$29
$4,488 '
$332 ;
$180 i
$4,999
$150 '
($52) i
$5,098
$4,078
$111 :
$180 ;
$4,778
$143
($52) i
$4,870 i
$3,896
$3,117 I
746 !
34.5
58.7 i
$4,057 !
$546
$3,592
$21 !
$52 !
8
$18 !
$145 ,
$58
$8,471
$623 I
$339 ;
$9,433
$283
($52) i
$9,664
$7,731
$208 :
$339 i
$9,017
$271
($52) !
$9,236 i
$7,389
$5,911 |
3730
188.0
319.6
$22,108
$2,571
$19,575
$74
$52
8
$18
$145
$58
$44,583
$3,332
$1,783
$49,698
$1,491
($52)
$51,137
$40,910
$1,111
$1,783
$47,477
$1 ,424
($52)
$48,849
$39,080
$31,264
5-37
-------
Regulatory Impact Analysis
DPF Volume
During development of this rule, engine manufacturers have suggested that DPF
volumes could be up to three times engine displacement. The size of the DPF is based largely
on the maximum allowable flow restriction for the engine. Generically, the filter size is
inversely proportional to its resistance to flow (a larger filter is less restrictive than a similar
smaller filter). In the 2007 highway and NRT4 rules, we estimated that the DPF would be
sized to be 1.5 times the engine displacement based on the responses received from EMA and
on-going research aimed at improving filter porosity control to give a better trade-off between
flow restrictions and filtering efficiency. As explained in Chapter 4 of this RIA, here we have
estimated a ratio of 1.7:1.
DPF Substrate
The DPF can be made from a wide range of filter materials including wire mesh,
sintered metals, fibrous media, or ceramic extrusions. The most common material used for
DPFs for heavy-duty diesel engines is cordierite. Here we have based our cost estimates on
the use of silicon carbide (SiC) even though it is more expensive than other filter materials.
In the 2007 highway rule, we estimated that DPFs would consist of a cordierite filter costing
$30 per liter. To remain conservative in our cost estimates for nonroad applications, we
assumed the use of silicon carbide filters costing double that amount, or $60 per liter, because
silicon carbide filters are more durable. As discussed in Chapter 4 of this RIA, we believe
that metal substrates may be choice for locomotive and marine DPFs, which would cost less
than a silicon carbide substrate. Nonetheless, to be conservative in our cost estimates, we
have assumed use of silicon carbide filters for locomotive and marine applications, so have
based costs on the $60 per liter cost estimate. This cost is directly proportional to filter
volume, which is proportional to engine displacement. We have converted the $60 value to
$2005 using the Producer Price Index (PPI) for manufacturing industries; the end result being
a cost of $62 per liter.19
DPF Washcoating and Canning
These costs are based on costs developed under contract for our 2007 highway rule.20
We converted those costs to $2005 using the PPI for manufacturing industries. We then
calculated a linear "best fit" to express the washcoating and canning costs as $8(x) + $91,
where x is the DPF volume in liters.
DPF Precious Metals
The total precious metal content for DFPs is estimated to be 60 g/ft3 with platinum as
the only precious metal used in the filter. In our NRT4 rule, we used a price of $542 per troy
ounce for platinum. Here we have used the 2005 average monthly price of $899 per troy
ounce for platinum.21
DPF Can Housing
The material cost for the can housing is estimated based on the DPF volume plus 20
percent for transition (inlet/outlet) cones, plus 20 percent for scrappage (material purchased
5-38
-------
Engineering Cost Estimates
but unused in the final product) and a price of $1 per pound for 18 gauge stainless steel as
estimated in a contractor report to EPA and converted into $2005.
DPF Differential Pressure Sensor
We believe that the DPF system will require the use of a differential pressure sensor to
provide a diagnostic monitoring function of the filter. A contractor report to EPA estimated
the cost for such a sensor at $45.22 A PPI adjusted cost of $52 per sensor has been used in
this analysis.
DPF Direct Labor
Consistent with the approach for SCR systems, the direct labor costs for the DPF are
estimated based on an estimate of the number of hours required for assembly and established
labor rates. Additional overhead for labor was estimated as 40 percent of the labor costs.
DPF Warranty
Consistent with the approach taken for SCR system costs, we have estimated both
near-term and long-term warranty costs. Near-term warranty costs are based on a three
percent claim rate and an estimate of parts and labor costs per incident, while long-term
warranty costs are based on a one percent claim rate and an estimate of parts and labor costs
per incident. The labor rate is estimated to be $50 per hour with two hours required per claim,
and parts cost are estimated to be 2.5 times the original manufacturing cost for the component.
DPF Manufacturer and Dealer Carrying Costs
Consistent with the approach for SCR systems, the manufacturer's carrying cost was
estimated at four percent of the direct costs. This reflects primarily the costs of capital tied up
in extra inventory, and secondarily the incremental costs of insurance, handling and storage.
The dealer's carrying cost was estimated at three percent of the incremental cost, again
reflecting primarily the cost of capital tied up in extra inventory.
Savings Associated with Silencer Removal
DPF retrofits are often incorporated in, or are simply replacements for, the silencer
(muffler) for diesel-powered vehicles and equipment. We believe that the DPF could be
mounted in place of the silencer, although it may have slightly larger dimensions. We have
estimated that applying a DPF allows for the removal of the silencer due to the noise
attenuation characteristics of the DPF. We have accounted for this savings and have
estimated a silencer costs at $52. The $52 estimate is an average for all engines; the actual
savings will be higher for some and lower for others.
DPF System Cost Estimation Function
Using the example DPF costs shown in Table 5-22, we calculated a linear regression
to determine the DPF system cost as a function of engine displacement. This way, the
function can be applied to the wide array of engines in the locomotive line haul and/or marine
5-39
-------
Regulatory Impact Analysis
fleets to determine the total or per engine costs for DPF system hardware. The functions
calculated for DPF system costs for locomotive line-haul and marine applications are shown
in Table 5-23.
For locomotive switcher applications, we have used the costs developed for our NRT4
rulemaking because locomotive switchers tend to be powered by land based nonroad engines
making it appropriate to use the same costs developed for that rule. These costs are also
shown in Table 5-23.
Table 5-23 DPF System Costs as a function of Engine Displacement, x, in Liters (2005 dollars)
Line-haul locomotive; marine
Switcher locomotive
Near-term cost function
Long-term cost function
Near-term cost function
Long-term cost function
Linear Regression
$217(x) + $199
$166(x) + $153
$146(x) + $75
$112(x) + $57
R2
0.999
0.999
0.999
0.999
Note: Near term costs include a 3 percent warranty claim rate while long term costs include a 1 percent
warranty claim rate and the learning effect.
The near-term and long-term costs shown in Table 5-23 change due to the different
warranty claim rates and the application of a 20 percent learning curve effect.
5.2.2.3 Aftertreatment Marinization Costs
For marine engines, the Tier 4 requirements will entail increased costs associated with
marinizing the engines for the marine environment. Marine Cl and C2 engines are typically
land based nonroad engines that are marinized for the marine environment. This marinization
can take many forms, but is generally a matter of altering the cooling system to make use of
sea or lake water rather than relying on ambient air since marine engines tend to be enclosed
within vessels where ambient air radiators like those used in land based engines cannot
operate efficiently. Such marinization efforts have been done for years and will continue but
do not represent incremental costs associated with the new standards. Marinization costs
associated with the new aftertreatment devices that would be added to comply with the Tier 4
standardsto control the surface temperatures in the typically tight space constraints onboard
a vesseldo represent incremental costs associated with the final program and, thus, they
must be considered.
Under contract to EPA, ICF International conducted a study that considered the costs
01
associated with marinizing aftertreatment devices. In their study, ICF looked at the costs
associated with two methods of marinization: triple wall stainless steel; and, insulating
blankets. Both methods could be used to control the surface temperature of the aftertreatment
device such that accidental touching would not cause burns or otherwise compromise safety.
The triple wall insulation method proved more cost efficient. Using this method, the device
would, essentially, have three layers of stainless steel surrounding the substrate rather than the
5-40
-------
Engineering Cost Estimates
single layer normally used on land based engines. These layers would be separated by a few
millimeters to provide an insulating air gap.
The ICF study looked at aftertreatment marinizing costs for a range of engine sizes in
a manner similar to that discussed above for SCR and DPF systems. The details of these
estimates are contained in the final report.24 In the report, ICF calculated costs using a 1:1 or a
1.5:1 device volume to engine displacement ratio. However, as noted earlier, our analysis
leads us to believe that a 2.5:1 ratio (SCR) and 1.7:1 ratio (DPF) are more applicable. As a
result, we have adjusted the ICF results somewhat higher to reflect a larger sized device being
insulated; these adjustments are reflected in Table 5-24 for marinization of SCR systems and
in Table 5-25 for marinization of DPF systems. The resultant linear regression best fit curves
for marinization costs as a function of engine displacement are shown in Table 5-26.
5-41
-------
Regulatory Impact Analysis
Table 5-24 SCR System Marinization Costs (2005 dollars)
Typical Engine Power (kW)
Typical Engine Displacement (L)
SCR Catalyst Marinization Hardware Cost
Assembly
Labor @ $28/hr
Overhead @ 40%
Total Assembly Cost
Markup on Hardware and Assembly @ 29%
Total SCR Catalyst Marinization Costs- Near term
Total SCR Catalyst Marinization Costs - Long term
64 ! 93
4.2 7
$23 $28
$0 $0
$3 i $3
$1 i $1
$4 $4
$8 $9
$34 : $42
$27 I $33
183
10.5
$29
$0
$3
$1
$4
$9
$42
$34
620
27
$65
$0
$3
$1
$4
$20
$90
$72
968
34.5
$77
$0
$3
$1
$4
$24
$105
$84
1425
51.8
$91
$0
$3
$1
$4
$28
$123
$98
1902
111
$173
$0
$3
$1
$4
$51
$228
$182
3805
222
$292
$0
$3
$1
$4
$86
$382
$305
5968
296
$350
$0
$3
$1
$4
$103
$456
$365
Table 5-25 DPF System Marinization Costs (2005 dollars)
Typical Engine Power (kW)
Typical Engine Displacement (L)
DPF Marinization Hardware Cost
Assembly
Labor @ $28/hr
Overhead @ 40%
Total Assembly Cost
Markup on Hardware and Assembly @ 29%
Total DPF Marinization Costs - Near term
Total DPF Marinization Costs - Long term
64
4.2
$15
$0
$3
$1
$4
$6
$25
$20
93
7
$22
$0
$3
$1
$4
$8
$34
$27
183
10.5
$29
$0
$3
$1
$4
$9
$42
$34
620
27
$52
$0
$3
$1
$4
$16
$72
$58
968
34.5
$61
$0
$3
$1
$4
$19
$84
$67
1425
51.8
$75
$0
$3
$1
$4
$23
$102
$81
1902
111
$112
$0
$3
$1
$4
$34
$150
$120
3805
222
$218
$0
$3
$1
$4
$64
$286
$229
5968
296
$262
$0
$3
$1
$4
$77
$343
$274
5-42
-------
Engineering Cost Estimates
Table 5-26 Marinization Costs as a function of Engine Displacement, x, in Liters (2005 dollars)
SCR System Marinization
DPF System Marinization
Near-term cost function
Long-term cost function
Near-term cost function
Long-term cost function
Linear Regression
$l(x) + $42
$l(x) + $34
$l(x) + $35
$l(x) + $28
R2
0.990
0.990
0.991
0.991
Note: Near term costs include a 3 percent warranty claim rate while long term costs include a 1 percent
warranty claim rate and the learning effect.
5.2.2.4 Summary of Engine Variable Cost Equations
Engine variable costs are discussed in detail in sections 5.2.2.1 through 5.2.2.3. As
described in those sections, we have generated cost estimation equations for SCR systems,
DPF systems, and aftertreatment marinization as a function of engine displacement. These
equations are summarized in Table 5-27. Note that not all equations were used for all engines
and all market segments; equations were used in the manner shown in the table. We have
calculated the aggregate engine variable costs and present them later in this chapter.
5-43
-------
Regulatory Impact Analysis
Table 5-27 Summary of Cost Equations for Engine Variable Costs (x represents the dependent variable,
2005 dollars)
Engine Technology
SCR System Costs
SCR System Costs
DPF System Costs
DPF System Costs
SCR Marinization Costs
DPF Marinization Costs
Time Frame
Near term
Long term
Near term
Long term
Near term
Long term
Near term
Long term
Near term
Long term
Near term
Long term
Cost Equation
$185(x) + $1,293
$142(x) + $988
$103(x) + $183
$83(x) + $160
$217(x) + $199
$166(x) + $153
$146(x) + $75
$112(x) + $57
$l(x) + $42
$l(x) + $34
$l(x) + $35
$l(x) + $28
Dependent
Variable
Engine
Displacement
(Liters)
Engine
Displacement
(Liters)
Engine
Displacement
(Liters)
Engine
Displacement
(Liters)
Engine
Displacement
(Liters)
Engine
Displacement
(Liters)
How Used
Tier 4
Locomotive
Line-haul and
Marine Engines
Tier 4
Locomotive
Switcher
Engines
Tier 4
Locomotive
Line-haul and
Marine Engines
Tier 4
Locomotive
Switcher
Engines
Tier 4 Marine
Engines
Tier 4 Marine
Engines
Using these equations, we can calculate the variable costs associated with the Tier 4
standards for any engine provided we know its displacement, power, and intended application.
We could do this for every compliant engine expected to be sold in the years following
implementation of the new standards, total the results, and we would have the total annual
variable costs associated with the rule. We can achieve essentially the same thing by
calculating a sales weighted variable cost. This could be done for a single engine that could
represent the entire fleet provided we sales weighted the critical characteristics of that engine.
Doing this for one engine would not provide a particularly good look at the impact of the new
standards on costs since the sizes of engines, their power, and use varies so much. Therefore,
we have broken the fleet first into the market segments according to our regulatory definitions
(i.e., marine Cl, marine C2, locomotive, etc.). We have further broken each market segment
into several power ranges, some of which are arbitrary and meant only to provide more
stratification of the results, and some of which are chosen to align properly with the structure
of the new standards (e.g., marine Cl has a power cutpoint at 600 kW since the Tier 4
standards apply to marine engines above 600 kW).
The necessary engine characteristics for sales weighting are engine displacement,
power, and application. We have used the PSR database and sales figures from 2002. The
resultant sales weighted engines within given market segments and power ranges are shown in
Table 5-28. For example, the sales weighted engine in the marine Cl segment, power range
5-44
-------
Engineering Cost Estimates
800 to 2000 hp, has an engine displacement of 33.4 liters and is 1266 hp (944 kW). Empty
cells in the table mean that there are no engines in that power range and market segment.
Table 5-28 Sales Weighted Engine Characteristics by Market Segment and Power Range
Power Range
0=2000hp
0=2000hp
Loco-LineHaul ; Loco-Switcher
2.7
! 5.8
7.7
18.9
! 51.8
174.2 ! 69.0
; Marine C1
Sales Weighted
2.5
i 5.5
10.5
17.6
! 33.4
! 61.0
: Marine C2 :
Displacement (Liters)
| i
: 93.0 :
: 176.4 !
Marine
Recreational
2.6
5.0
4.9
8.8
28.9
60.6
; Small
; Commercial
: Marine
0.6
1.6
|
Sales Weighted Horsepower
! 67.0
157.7
227.3
! 660.0
! 1500.0
4895.2 I 2000.0
! 58.2
149.6
301.1
! 553.2
! 1266.3
i 2144.4
! 1508.6 !
I 4014.5 I
61.1
159.1
269.7
457.2
1226.1
2935.1
15.8
: 36.0
:
Using these sales weighted engines shown in Table 5-28 and the variable cost
equations shown in Table 5-27, we can calculate the individual piece costs for the various
hardware elements expected to be added to engines to comply with the new standards. Those
elements, as discussed above, being SCR systems, DPF systems, and costs associated with
marinizing the SCR and the DPF systems (for marine engines only). The resultant piece costs
are shown in Table 5-29. The table includes costs for engines in power ranges that are
expected to add the new hardware or upgrade existing hardware. Empty cells reflect our
belief that the technology will not be added as a result of our final rule. The rows containing
data for "All engines" are costs for the sales weighted engine within each market segment.
For Marine Cl, we have also broken out the sales weighted costs for engines below and above
600 kW (805 hp). We use these valuesthose for "All engines" or, for the Cl marine
segment, those for "<600 kW" or ">600 kW"for our total cost calculations presented in
section 5.6.
5-45
-------
Regulatory Impact Analysis
Table 5-29 Piece Costs for Engine Hardware by Market Segment and Power Range (2005 dollars)
Power Range =
!
0800 hp only !
Line-Haul : Switchers : Marine C1 : Marine C2 : Rec Marine
SCR System Costs
; |
$460
$778
! $979 !
| $2,140 |
! $5,532 !
$33,567 $7,315
$33,567 " $1,639
$852
! $6,449 !
- Near term
; ;
1 1
$7,485 ! $18,527 !
$12,591 $33,988
$30,476
$8,782 ! !
i SCR Marinization Costs - Near term
0800 hp only
i
0800 hp only
; |
DPF System Costs
| $467 j
! $918 !
$1,203
$2,847
$7,650
$37,924 | $10,175 I
$37,924 ! $2,137 !
$1,023
$8,949
$91 " $178
$131 $300
! $272 !
; ;
$101
- Near term
| |
$7,437 $20,344
$13,405 | $38,416 I
; $34,312 |
$8,953
i DPF Marinization Costs - Near term
0800 hp only !
; |
$71 ! $135 !
$101 $225
'_ $205 '_
$79 ! !
Power Range ,
i
0800 hp only !
Line-Haul : Switchers : Marine C1 : Marine C2 : Rec Marine
SCR System Costs
; ;
$381
$635
! $796 !
| $1,723 |
! $4,431 !
$25,651 $5,855
$25,651 " $1,323
$695
! $5,163 !
Long term
1 ;
1 1
$5,720 ! $14,158 !
$9,622 $25,973
$23,290
$6,711 ! !
i SCR Marinization Costs - Long term
0800 hp only
>2000kWonly j
0800 hp only
; ;
DPF System Costs
| $357 |
! $702 !
$920
$2,177
$5,850
$28,982 | $7,781 I
$28,982 ! $1,634 !
$782
$6,843
$73 $143
$106 $242
! $219 !
| ;
$81
Long term
| |
$5,684 $15,547
$10,245 | $29,358 I
| $26,222 !
$6,843
I DPF Marinization Costs - Long term
0800 hp only !
; ;
$57 ! $108 !
$80 $180
'_ $163 '_
$63 ! !
5-46
-------
Engineering Cost Estimates
5.2.2.5 Annual Engine Variable Engineering Costs
Using the hardware piece costs shown in Table 5-29, we can calculate the annual costs
for each market segment by multiplying piece costs by estimated future sales. Table 5-30
through Table 5-34 show these costs. These costs are associated with the Tier 4 standards
since only Tier 4 engines are expected to incur new hardware costs. The PM/NOX+NMHC
cost allocations for engine variable costs used in this cost analysis are as follows: SCR
systems including marinization costs on marine applications are attributed 100% to
NOX+NMHC control; and DPF systems including marinization costs on marine applications
are attributed 100% to PM control.
Table 5-30 Annual Locomotive Line-haul Engine Variable Costs; Freshly Manufactured Tier 4 Engines
Only (SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Sales DPF SCR
767
765 | |
780
816 | $30.9 | $27.4
854
$32.4
$28.7
877 $25.4 $22.5
894
917
$25.9
$26.6
$22.9
$23.5
948 | $27.5 | $24.3
979
$28.4
$25.1
1007 | $29.2 | $25.8
1034
$30.0
$26.5
1048 I $30.4 I $26.9
1078
$31.2
$27.6
1096 | $31.8 | $28.1
1119 I $32.4 I $28.7
1136 | $32.9 | $29.1
1150
$33.3
$29.5
1158 | $33.6 | $29.7
1173
$34.0
$30.1
1190 $34.5 $30.5
1209
1223
1231
1197
$35.0
$35.5
$35.7
$34.7
$31.0
$31.4
$31.6
$30.7
1172 | $34.0 | $30.1
1144
$33.2
$29.3
1112 I $32.2 I $28.5
1078
$31.2
$196.5
$27.7
$173.9
I $426.6 I $377.6
Total PM Nฐx+
! ! NMHC
$58.3 | $30.9 | $27.4
$61.1
$32.4
$28.7
$47.9 $25.4 $22.5
$48.8
$50.1
$25.9
$26.6
$22.9
$23.5
$51.8 | $27.5 | $24.3
$53.5
$28.4
$25.1
$55.0 | $29.2 | $25.8
$56.5
$30.0
$26.5
$57.2 I $30.4 I $26.9
$58.9
$31.2
$27.6
$59.9 | $31.8 | $28.1
$61.1 I $32.4 I $28.7
$62.1 | $32.9 | $29.1
$62.8
$33.3
$29.5
$63.3 | $33.6 | $29.7
$64.1
$34.0
$30.1
$65.0 $34.5 $30.5
$66.0
$66.8
$67.3
$65.4
$35.0
$35.5
$35.7
$34.7
$31.0
$31.4
$31.6
$30.7
$64.0 | $34.0 | $30.1
$62.5
$33.2
$29.3
$60.8 I $32.2 I $28.5
$58.9
$370.4
$31.2
$196.5
$27.7
$173.9
$804.2 I $426.6 I $377.6
5-47
-------
Regulatory Impact Analysis
Table 5-31 Annual Locomotive Switcher & Passenger Engine Variable Costs; Freshly Manufactured Tier
4 Engines Only (SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Sales | DPF | SCR
92
92
93 | |
93
$0.9
$0.7
94 | $1.0 | $0.7
94
$0.7
$0.5
94 I $0.7 I $0.5
94 I $0.7 I $0.6
94 | $0.7 | $0.6
94
$0.7
$0.6
95 | $0.7 | $0.6
160
$1.2
$0.9
183 | $1.4 | $1.1
201
$1.6
$1.2
212 $1.6 $1.2
227
239
$1.8
$1.9
$1.3
$1.4
247 | $1.9 | $1.4
263
$2.0
$1.5
281 | $2.2 | $1.6
292
$2.3
$1.7
296 I $2.3 I $1.7
305
$2.4
$1.8
302 | $2.3 | $1.8
294 I $2.3 I $1.7
287 | $2.2 | $1.7
278
$2.2
$1.6
269 | $2.1 | $1.6
263
$2.0
$8.6
$1.5
$6.4
$20.4 $15.3
Total I PM I Nฐx+
! ! NMHC
$1.6
$0.9
$0.7
$1.6 I $1.0 I $0.7
$1.3
$0.7
$0.5
$1.3 I $0.7 I $0.5
$1.3 I $0.7 I $0.6
$1.3 | $0.7 | $0.6
$1.3
$0.7
$0.6
$1.3 | $0.7 | $0.6
$2.2
$1.2
$0.9
$2.5 | $1.4 | $1.1
$2.7
$1.6
$1.2
$2.9 $1.6 $1.2
$3.1
$3.3
$1.8
$1.9
$1.3
$1.4
$3.4 | $1.9 | $1.4
$3.6
$2.0
$1.5
$3.8 | $2.2 | $1.6
$4.0
$2.3
$1.7
$4.0 I $2.3 I $1.7
$4.2
$2.4
$1.8
$4.1 | $2.3 | $1.8
$4.0 I $2.3 I $1.7
$3.9 | $2.2 | $1.7
$3.8
$2.2
$1.6
$3.7 | $2.1 | $1.6
$3.6
$15.0
$2.0
$8.6
$1.5
$6.4
$35.8 $20.4 $15.3
5-48
-------
Engineering Cost Estimates
Table 5-32 Annual C2 Marine Engine Variable Costs; Freshly Manufactured Tier 4 Engines Only
(SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Sales | DPF | SCR | Marinization
| | |
i i i
299 | | I
301
304 ! : \
307 i j j
309 ' $10.6 ' $9.4 ' $0.1
312 ! $10.7 ! $9.5 ! $0.1
315 ' $8.3 ' $7.3 ' $0.1
318 i $8.3 $7.4 $0.1
321 $8.4 $7.5 $0.1
324 j $8.5 $7.5 $0.1
327 ' $8.6 $7.6 $0.1
330 ; $8.6 $7.7 $0.1
332 ' $8.7 $7.7 $0.1
335 i $8.8 $7.8 $0.1
338 $8.9 $7.9 $0.1
342 j $9.0 $8.0 $0.1
345 $9.0 $8.0 $0.1
348 i $9.1 $8.1 $0.1
351 $9.2 $8.2 $0.1
354 ' $9.3 ' $8.2 ' $0.1
357 ! $9.4 ! $8.3 ! $0.1
360 ' $9.5 ' $8.4 ' $0.1
364 !- $9.5 ! $8.5 !- $0.1
367 $9.6 $8.5 $0.1
370 ! $9.7 ! $8.6 ! $0.1
374 ' $9.8 ' $8.7 ' $0.1
377 ! $9.9 : $8.8 ! $0.1
380 ' $10.0 ' $8.9 ' $0.1
384 ! $10.1 ! $8.9 i $0.1
! $54.4 ! $48.3 j $0.8
$119.3 $106.0 $1.7
Total
$20.2
$20.4
$15.7
$15.9
$16.0
$16.1
$16.3
$16.4
$16.6
$16.7
$16.9
$17.0
$17.2
$17.3
$17.5
$17.7
$17.8
$18.0
$18.1
$18.3
$18.5
$18.6
$18.8
$19.0
$19.1
$103.4
$227.0
PM
$10.7
$10.8
$8.3
$8.4
$8.5
$8.5
$8.6
$8.7
$8.8
$8.9
$8.9
$9.0
$9.1
$9.2
$9.3
$9.4
$9.4
$9.5
$9.6
$9.7
$9.8
$9.9
$10.0
$10.0
$10.1
$54.7
$120.2
NOX+
NMHC
$9.5
$9.6
$7.4
$7.5
$7.5
$7.6
$7.7
$7.7
$7.8
$7.9
$7.9
$8.0
$8.1
$8.2
$8.2
$8.3
$8.4
$8.5
$8.5
$8.6
$8.7
$8.8
$8.9
$8.9
$9.0
$48.7
$106.8
5-49
-------
Regulatory Impact Analysis
Table 5-33 Annual Cl Marine (>600 kW/805 hp) Engine Variable Costs; Freshly Manufactured Tier 4
Engines Only (SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Sales | DPF | SCR | Marinization
: : :
| | |
1 1 :
900 I | I
908
916 ! ! \
925 i i i
933 ' $8.4 ' $8.2 ' $0.2
941 ! $8.4 i $8.3 ! $0.2
950 ' $6.5 ' $6.4 ' $0.1
958 i $6.6 ! $6.4 i $0.1
967 $6.6 $6.5 $0.1
976 j $6.7 j $6.5 i $0.1
985 ' $6.7 ' $6.6 ' $0.1
993 ; $6.8 ! $6.7 ! $0.1
1002 ' $6.9 ' $6.7 ' $0.1
1011 i $6.9 j $6.8 j $0.1
1020 $7.0 $6.8 $0.1
1030 i $7.0 j $6.9 ! $0.1
1039 $7.1 $7.0 $0.1
1048 i $7.2 j $7.0 i $0.2
1058 $7.2 $7.1 $0.2
1067 ' $7.3 ' $7.2 ' $0.2
1077 ! $7.4 ! $7.2 ! $0.2
1086 ' $7.4 ' $7.3 ' $0.2
1096 ! $7.5 ! $7.4 ! $0.2
1106 $7.6 $7.4 $0.2
1116 ! $7.6 ! $7.5 ! $0.2
1126 ' $7.7 ' $7.6 ' $0.2
1136 : $7.8 ! $7.6 ! $0.2
1146 ' $7.8 ' $7.7 ' $0.2
1157 ! $7.9 I $7.8 I $0.2
! $42.8 j $41.9 ! $0.9
$93.9 $92.1 $2.0
Total PM I Nฐx+
i NMHC
$16.7 I $8.4 I $8.3
$16.9
(tp C
$O.O
$8.4
$13.0 ! $6.6 ! $6.4
$13.1 I $6.6 I $6.5
$13.2 | $6.7 | $6.6
$13.4
$6.7
$6.6
$13.5 | $6.8 | $6.7
$13.6
$6.9
$6.7
$13.7 | $6.9 | $6.8
$13.9
$7.0
$6.9
$14.0 $7.1 $6.9
$14.1
$14.2
$7.1
$7.2
$7.0
$7.0
$14.4 | $7.2 | $7.1
$14.5
$7.3
$7.2
$14.6 | $7.4 | $7.2
$14.7
$7.4
$7.3
$14.9 I $7.5 I $7.4
$15.0
$7.6
$7.4
$15.2 | $7.6 | $7.5
$15.3 I $7.7 I $7.6
$15.4 | $7.8 | $7.6
$15.6
$7.9
$7.7
$15.7 | $7.9 | $7.8
$15.8
$85.6
$8.0
$43.2
$7.8
$42.4
$187.9 $94.8 $93.0
5-50
-------
Engineering Cost Estimates
Table 5-34 Total Annual Engine Variable Costs; Freshly Manufactured Tier 4 Engines Only (SMillions,
2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Locomotive j ^e | Ma^e | Recreationa, \ ^m^
ill i
$60.0 j j j j
$62.7 ' $16.7 ' $20.2
$49.2 | $16.9 ! $20.4 j |
$50.1 $13.0 $15.7
$51.4 'l $13.1 l $15.9 l l
$53.1 $13.2 $16.0
$54.8 ! $13.4 ! $16.1 ! !
$56.3 $13.5 $16.3
$58.7 ! $13.6 ! $16.4 ! !
$59.7 $13.7 $16.6
$61.6 ' $13.9 ' $16.7
$62.8 ; $14.0 ; $16.9 ; ;
$64.2 ' $14.1 ' $17.0
$65.3 $14.2 $17.2 i
$66.2 $14.4 $17.3
$66.9 $14.5 $17.5 i
$67.9 $14.6 $17.7
$69.0 $14.7 $17.8 ;
$70.1 $14.9 $18.0
$71.0 $15.0 $18.1 i
$71.4 $15.2 $18.3
$69.4 $15.3 $18.5 ]
$67.9 $15.4 $18.6
$66.3 $15.6 $18.8 !
$64.4 $15.7 $19.0
$62.5 ' $15.8 ' $19.1
$385.5 $85.6 $103.4
$839.9 I $187.9 I $227.0 I I
Total
$60.0
$99.6
$86.4
$78.9
$80.4
$82.3
$84.3
$86.1
$88.7
$90.1
$92.2
$93.7
$95.4
$96.7
$97.9
$98.9
$100.2
$101.6
$102.9
$104.2
$104.8
$103.1
$102.0
$100.7
$99.1
$97.5
$574.5
$1,254.8
PM
$31.9
$52.5
$45.4
$41.5
$42.3
$43.4
$44.4
$45.4
$46.8
$47.5
$48.6
$49.4
$50.3
$51.1
$51.7
$52.2
$52.9
$53.6
$54.4
$55.0
$55.4
$54.5
$53.8
$53.1
$52.3
$51.4
$303.1
$662.1
NOX+
NMHC
$28.1
$47.1
$41.0
$37.3
$38.1
$39.0
$39.9
$40.7
$41.9
$42.6
$43.6
$44.2
$45.0
$45.7
$46.2
$46.7
$47.3
$47.9
$48.6
$49.1
$49.5
$48.7
$48.1
$47.5
$46.8
$46.1
$271 .4
$592.8
Table 5-34 shows the net present value of the annual engine variable costs through
2040 as $1.3 billion at a three percent discount rate or $0.6 billion at a seven percent discount
rate. These costs are fairly evenly split between NOX+NMHC and PM.
5.3 Engineering Costs for Freshly Manufactured Equipment
In this section, we present our estimated costs associated with the piece of equipment
into which the freshly manufactured engines are placedi.e., the locomotive itself or the
marine vessel itself. In general, we refer generically to equipment rather than specifically to
locomotives or vessels. Costs of control to equipment manufacturers include fixed costs
(those costs for equipment redesign), and variable costs (for new hardware and increased
equipment assembly time).
5-51
-------
Regulatory Impact Analysis
5.3.1 Fixed Engineering Costs
5.3.1.1 Equipment Redesign Costs
The projected modifications to equipment resulting from the new emission standards
relate to the need to package emission control hardware that engine manufacturers will
incorporate into their engines. As discussed above, the additional emission control hardware
for equipment into which a Tier 4 engine is installed is proportional in size to engine
displacement by roughly a 4:1 ratio (2.5x engine displacement for the SCR system and 1.7x
engine displacement for the DPF system). We expect that equipment manufacturers will have
to redesign their equipment to accommodate this new volume of hardware. As such, we
would expect such costs for only those pieces of equipment that will be installing a Tier 4
engine since Tier 3 engines are expected to incorporate controls that will not result in a larger
engine or otherwise require any more space within the piece of equipment.
To determine marine-related redesign costs, our first step was to determine the number
of vessels sold each year. To estimate vessel sales, we looked first at the number of engines
being sold as marine engines. Since only C2 engines and Cl engines >600 kW (805 hp)
would be complying with the Tier 4 standards, we limited ourselves to those engines.
Further, we eliminated those engines sold as auxiliary engines since we know that there exists
a direct correlation between vessel sales and propulsion engine sales because every freshly
manufactured vessel will have at least one propulsion engine while having anywhere from
zero to many auxiliary engines. Based on the 2002 PSR database and our marine engine sales
growth rates, our analysis estimates that, in the year 2015one year before vessels would be
adding engines equipped with aftertreatment devices and, hence, being redesignedthere will
be 751 marine Cl propulsion engines >600 kW and 147 marine C2 propulsion engines.
We know that most vessels in these larger marine categories are fitted with more than
one engine. In our draft cost analysis, we estimated 1.5 propulsion engines, on average, per
vessel. For our final cost analysis, we have increased that to 2 propulsion engines per vessel
based on our industry characterization work (see Chapter 1 of this RIA). This results in an
estimated 375 marine Cl and 74 marine C2 vessels sold in 2015.
We believe that not every vessel will require a full redesign. Instead, we believe that,
while some vessels truly are a one-design/one-vessel effort, many vessels are a one-
design/five-vessel or even ten or more-vessel effort. To be conservative and as was done in
our draft cost analysis, we have estimated that a redesign effort will accommodate two freshly
manufactured vessels. That is, on average, a fleet of 74 freshly manufactured C2 vessels
would require 37 redesign efforts. We have estimated the costs per redesign at $50,000 for
Cl vessel redesigns and $100,000 for C2 vessel redesigns. These estimates are summarized
in Table 5-35.
5-52
-------
Engineering Cost Estimates
Table 5-35 Estimated Vessel Redesigns in 2015 and Costs per Redesign (2005 dollars)
Marine-C1
propulsion
Marine-C2
propulsion
Total
Power
Range
>800hp
All
! Propulsion
I Engines in
! 2015
I 751
147
| 898
Engines/ |
Vessel ',
2 |
2
E
Vessels I
375 |
74
449 |
Vessels /
Redesign
2
2
i Redesigns
| 188
37
| 225
i
i $/Redesign
| $50,000
$100,000
Using these estimates, we can estimate the annual total costs associated with vessel
redesigns. But first it is important to note that we do not believe that the vessel fleets will
require these redesign efforts every year. Nor will the need to redesign vessels cease once the
Tier 4 standards are implemented. Instead, in the second year of implementation we would
expect vessel sales to be similar but in many ways different than in year one. Such is the
nature of the marine fleet in contrast to say, the automotive fleet where a freshly
manufactured vehicle design is typically carried-over for four to six years with no significant
redesign. Nonetheless, a first year redesign effort will no doubt make a second year redesign
effort less costly given what was learned by redesign and construction firms during the first
year. To estimate this effect, we considered year two to require half the effort of year one,
year three half again, and year four half again. We then carried this effort forward until we
had accumulated at least 1,000 redesigns which, we believe, is sufficient to have fully
redesigned the applicable fleet. The number of marine redesign efforts and the annual total
costs are shown in Table 5-36.
5-53
-------
Regulatory Impact Analysis
Table 5-36 Estimated Total Number of Vessel Redesigns and the Associated Annual Costs; Freshly Manufactured Tier 4 Equipment only (monetary
entries are in SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
Total
NPVat7%
NPVat3%
C1 I C2 i Annuf I Cumulative
Redesigns ; Redesigns ; Redesians i Redesigns
I i [
188 | 37 | 224 | 224
90 20 110 334
50 | 10 | 60 | 394
30 10 40 434
30 ; 10 ; 40 ; 474
30 10 40 514
30 | 10 | 40 | 554
30 10 40 594
30 : 10 ! 40 : 634
30 i 10 i 40 674
30 ' 10 40 714
30 : 10 j 40 754
30 10 40 794
30 10 i 40 834
30 10 40 874
30 10 i 40 914
30 10 40 954
30 10 j 40 994
30 10 40 1,034
C1
Redesign
Costs
$9.4
$4.5
$2.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$40.4
$14.3
$25.2
C2
Redesign
Costs
$3.7
$2.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$22.7
$7.5
$13.7
Annual
Total Costs
$13.1
$6.5
$3.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$2.5
$63.1
$21.8
$38.9
PM
$6.5
$3.3
$1.8
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$31.5
$10.9
$19.4
NOX+NMHC
$6.5
$3.3
$1.8
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$31.5
$10.9
$19.4
5-54
-------
Engineering Cost Estimates
For locomotive redesign efforts, we believe that the cost per redesign should be
roughly equivalent to that for a C2 marine vessel, or $100,000 dollars per redesign, since the
engine sizes and corresponding aftertreatment sizes should be roughly the same. Unlike the
marine industry, the locomotive industry generally sells many of units of the same design. In
fact, we estimate that there are only seven locomotive modelstwo line haul and five
switcherthat comprise the hundreds of locomotives sold each year. Therefore, we have
estimated that one redesign effort per model will suffice. The number of locomotive redesign
efforts and the annual total costs are shown in Table 5-37.
Table 5-37 Estimated Total Number of Locomotive Redesigns and the Associated Annual Costs; Freshly
Manufactured Tier 4 Equipment only (monetary entries are in SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
Total
NPVat7%
NPVat3%
Line haul | Switcher
Redesigns ; Redesigns
2
5
Line haul ; Switcher
Redesign ; Redesign
Costs i Costs
$0.2
$0.5
$0.2 I $0.5
$0.1 | $0.3
$0.2
$0.4
Annual : ;
Total ; PM ; Nฐx+
Costs I ! NMHC
$0.7
$0.4
$0.4
$0.7 I $0.4 I $0.4
$0.4 | $0.2 | $0.2
$0.5
$0.3
$0.3
5-55
-------
Regulatory Impact Analysis
The net present value of the vessel redesign costs are estimated at $39 million using a
three percent discount rate and at $22 million using a seven percent discount rate. The net
present value of the locomotive redesign costs are estimated at $0.5 million using a three
percent discount rate and at $0.4 million using a seven percent discount rate. In total, the net
present value of the equipment redesign costs are estimated at $40 million using a three
percent discount rate and at $22 million using a seven percent discount rate. These equipment
redesign costs are split evenly between NOX+NMHC and PM control.
5.3.2 Variable Engineering Costs
As discussed above, we are projecting that SCR systems and DPFs will be the most
likely technologies used to comply with the Tier 4 standards. Upon installation in a freshly
manufactured locomotive or a freshly manufactured marine vessel, these devices would
require some new equipment related hardware in the form of brackets and/or new sheet metal.
Based on engineering judgement, we estimated this cost as shown in Table 5-38. Since the
equipment variable costs are linked closely with the size of aftertreatment devices being
installed (i.e., the large the diesel engine being installed in the piece of equipment, the larger
the aftertreatment devices and, therefore, the larger the necessary brackets and/or greater the
necessary sheet metal), it makes sense to scale the equipment hardware costs accordingly.
Note that these costs would be incurred by only those pieces of equipment required to comply
with the Tier 4 standards. Note also that we termed these costs "equipment variable costs" in
our draft cost analysis and have more precisely named them "aftertreatment housing" costs for
our final cost analysis. This helps to distinguish them from the reductant system costs,
discussed below, that were included as engine-related costs in our draft analysis but are
considered equipment-related costs in the final analysis. These two cost elements -
aftertreatment housing and reductant system - now constitute the overall equipment variable
costs.
Table 5-38 Estimated Aftertreatment Housing Costs per Piece of Freshly Manufactured Equipment (2005
dollars)
Locomotive Line-haul
Locomotive Switcher
Marine Cl (600-1492 kW; 805-2000 hp)
Marine Cl (>1492 kW; >2000 hp)
Marine C2 (600-1492 kW; 805-2000 hp)
Marine C2 (>1492 kW; >2000 hp)
$/piece of equipment
$4,000
$4,000
$2,000
$4,000
$2,000
$4,000
For our final cost analysis, we have removed reductant tank and controller costs from
the engine-related SCR system costs and are accounting for these costs at the equipment level.
We have chosen to do so because we believe it is most appropriate given that some
equipment, especially vessels, would be equipped with more than one engine but probably
only one reductant tank and dosing controller to accommodate all engines.
5-56
-------
Engineering Cost Estimates
For the reductant tank, just as was done in our draft cost analysis, the estimated costs
for the reductant solution tank and brackets is based on industry input that fuel tank size is
roughly one gallon per engine horsepower and reductant dosing rate is roughly four percent of
the fueling rate. We also estimated that a reductant tank would cost $60 per 10 gallons of
capacity. Using these estimates, the needed reductant tank size and associated cost can be
estimated.
We have increased the final cost estimates for the reductant dosing controller based on
input from EMA, although we have not used all of the EMA estimates directly. In their
comments, EMA estimated the cost of a dosing panel at $10,000 to -$15,000 per vessel,
depending on power, and the cost of the dosing controls at $20,000 per vessel. We believe
that those estimates were based on discussions with retrofit companies who, we have no
doubt, are today charging those types of prices for those items. However, we believe that
once the 2007/2010 HD highway truck program is underway, control and dosing system
hardware will be available at a small fraction of today's retrofit price. In our draft analysis,
we estimated the cost of the controller and reductant injector at $500. After considering
EMA's comments, we believe that cost estimate was more applicable to a higher production
quantity market (i.e., highway/nonroad production). For our final analysis, while the
reductant injector itself remains part of the SCR catalyst system (described in section 5.2.2.1),
we have estimated that the reductant dosing panel and controller will cost 10% of the amounts
estimated by EMA. We base that on the cost of new DPF and/or SCR systems being roughly
10% of the cost of typical retrofit systems. For the same reasons, we have applied the same
10% factor to EMA's estimates for a reductant tank heater (EMA estimated at $500) and a
reductant pump (EMA estimated at $4,400), neither of which were included in our draft cost
analysis but are included in our final cost analysis. We used the same methodology as
described in section 5.2.2 (with the exception that we have not estimated any learning from
the highway program that will reduce costs in the locomotive and marine program) to
determine the final cost of the reductant system including labor and markups, etc., and these
are shown in Table 5-39.
5-57
-------
Regulatory Impact Analysis
Table 5-39. Estimated Reductant Tank and Dosing System Cost per Piece of Freshly Manufactured
Equipment (2005 dollars)
Typical Equipment Power (kW)
Material and Component Costs
Reductant Solution Tank & Brackets
Reductant Tank Heaters & Pumps
Reductant dosing panel & controls
Direct Labor Costs
Estimated Labor hours
Labor Rate ($/hr)
Labor Cost
Labor Overhead @ 40%
Total Direct Costs to Mfr.
Warranty Cost (3% claim rate)
Mfr. Carrying Cost - Near term
Total Cost to Dealer - Near term
Dealer Carrying Cost - Near term
Baseline Cost to Buyer - Near term
L/M Cost to Buyer (includes no Highway Learning) - Near term
Warranty Cost (1 % claim rate)
Mfr. Carrying Cost - Long term
Total Cost to Dealer - Long term
Dealer Carrying Cost - Long term
Baseline Cost to Buyer - Long term
Baseline Cost to Buyer (includes no Highway Learning) - Long term
L/M Cost to Buyer (includes Loco/Marine Learning) - Long term
1400
$450
$490
$3,000
$2
$18
$36
$14
$3,991
$302
$160
$4,452
$134
$4,586
$4,586
$101
$160
$4,251
$128
$4,379
$4,379
$3,503
10000
$3,217
$490
$3,518
$2
$18
$36
$14
$7,276
$548
$291
$8,115
$243
$8,358
$8,358
$183
$291
$7,749
$232
$7,982
$7,982
$6,385
We have used the lower costs shown in Table 5-39 for locomotive switchers and
vessels equipped with propulsion engines in the 800 to 2000 horsepower range (-600-
ISOOkW) and the higher costs for locomotive line-haul and vessels equipped with propulsion
engines over 2000 horsepower. Note that, for marine, we estimate two Tier 4 propulsion
engines per vessel in those power ranges and nearly two (1.9 on average) auxiliary engines
per vessel.25 For vessels in the 800 to 2000 horsepower range, we anticipate that Tier 3
auxiliary engines will be used which will not require reductant tank capacity. Looking at the
sales weighted horsepowers shown in Table 5-28 we can estimate total vessel power requiring
urea which, for vessels powered by 800 to 2000 horsepower engines, we estimate at just under
2000 kW for Cl vessels and just under 2300 kW for C2 vessels. For the over 2000
horsepower vessels, we similarly anticipate two Tier 4 propulsion engines and nearly two Tier
4 auxiliary engines (rather than Tier 3) which will require urea tank capacity. Looking at the
sales weighted horsepowers shown in Table 5-28 we can estimate total vessel power requiring
reductant which, for vessels powered by over 2000 horsepower engines, we estimate at just
under 6300 kW for Cl vessels and just under 12,000 kW for C2 vessels. Therefore, the costs
shown in Table 5-39 are roughly appropriate.
Using these costs and estimated future sales of locomotives and vessels, we can
estimate the annual costs for the fleet. These costs are shown in Table 5-40 for locomotives,
Table 5-41 for Cl marine, and Table 5-42 for C2 marine. Table 5-43 summarizes these costs
and presents the total costs. As shown, we estimate the net present value of annual equipment
variable costs at $220 million using a three percent discount rate and $100 million using a
5-62
-------
Engineering Cost Estimates
seven percent discount rate. These costs are split evenly between NOX+NMHC and PM
control.
5-59
-------
Regulatory Impact Analysis
Table 5-40 Annual Locomotive Variable Costs; Freshly Manufactured Tier 4 Equipment Only (SMillions, 2005 dollars)
Calendar Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Sales i
816
854
877
894
917
948
979
1,007
1,034
1,048
1,078
1,096
1,119
1,136
1,150
1,158
1,173
1,190
1,209
1,223
1,231
1,197
1,172
1,144
1,112
1,078
I
Locomotive Line
Aftertreatment i
Housing Costs i
$3.3
$3.4
$3.5
$3.6
$3.7
$3.8
$3.9
$4.0
$4.1
$4.2
$4.3
$4.4
$4.5
$4.5
$4.6
$4.6
$4.7
$4.8
$4.8
$4.9
$4.9
$4.8
$4.7
$4.6
$4.4
$4.3
$26.1
$57.4 |
Haul
Reductant I
System i
Costs I
$6.8
$7.1
$5.6
$5.7
$5.9
$6.1
$6.2
$6.4
$6.6
$6.7
$6.9
$7.0
$7.1
$7.3
$7.3
$7.4
$7.5
$7.6
$7.7
$7.8
$7.9
$7.6
$7.5
$7.3
$7.1
$6.9
$43.3
$94.0
Subtotal i Sales i
$10.1
93
$10.6 | 94
$9.1
94
$9.3 94
$9.5
$9.8
$10.2
$10.5
94
94
94
95
$10.7 I 160
$10.9
183
$11.2 | 201
$11.4
212
$11.6 I 227
$11.8 I 239
$11.9 | 247
$12.0
263
$12.2 | 281
$12.4
292
$12.6 | 296
$12.7
305
$12.8 302
$12.4
$12.2
294
287
$11.9 | 278
$11.6
269
$11.2 I 263
$69.4
$151.4
Locomotive
Aftertreatment i
Housing Costs i
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.6
$0.7
$0.8
$0.8
$0.9
$1.0
$1.0
$1.1
$1.1
$1.2
$1.2
$1.2
$1.2
$1.2
$1.1
$1.1
$1.1
$1.1
$4.3
$10.3
Switcher
Reductant I
System i
Costs !
$0.4
$0.4
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.6
$0.6
$0.7
$0.7
$0.8
$0.8
$0.9
$0.9
$1.0
$1.0
$1.0
$1.1
$1.1
$1.0
$1.0
$1.0
$0.9
$0.9
$3.9
$9.2
Subtotal
$0.8
$0.8
$0.7
$0.7
$0.7
$0.7
$0.7
$0.7
$1.2
$1.4
$1.5
$1.6
$1.7
$1.8
$1.9
$2.0
$2.1
$2.2
$2.2
$2.3
$2.3
$2.2
$2.2
$2.1
$2.0
$2.0
$8.2
$19.5
5-60
-------
Engineering Cost Estimates
Table 5-41 Annual Cl Marine Vessel Variable Costs; Freshly Manufactured Tier 4 Equipment Only (SMillions, 2005 dollars)
Calendar Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
C1 800-2000hp |
Vessel i
Sales ;
268
270
272
275
277
280
282
285
287
290
293
295
298
301
303
306
309
312
314
317
320
323
326
329
332
Aftertreatment
Housing Costs
$0.5
$0.5
$0.5
$0.5
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.6
$0.7
$0.7
$0.7
$3.4
$7.6
Reductant I
System i
Costs !
$1.2
$1.2
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.0
$1.1
$1.1
$1.1
$1.1
$1.1
$1.1
$1.1
$1.1
$1.1
$1.1
$1.2
$1.2
$6.3
$13.8
Subtotal i Vessel |
$1.8 | 111
$1.8
112
$1.5 113
$1.5
$1.5
$1.5
$1.6
114
115
116
117
$1.6 | 118
$1.6
119
$1.6 | 120
$1.6
122
$1.6 I 123
$1.6 I 124
$1.7 I 125
$1.7
126
$1.7 I 127
$1.7
128
$1.7 | 129
$1.7
131
$1.7 132
$1.8
$1.8
133
134
$1.8 | 135
$1.8
137
$1.8 I 138
$9.7 |
$21.4
C1 >2000hp
Aftertreatment j R|
Housing Costs i ,
$0.4
$0.4
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.6
$2.8
$6.3
$0.9
$0.9
$0.7
$0.7
$0.7
$0.7
$0.7
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.9
$0.9
$0.9
$0.9
$4.8
$10.4
Subtotal
$1.4
$1.4
$1.2
$1.2
$1.2
$1.2
$1.2
$1.2
$1.2
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.3
$1.4
$1.4
$1.4
$1.4
$1.4
$1.4
$1.4
$7.6
$16.8
5-61
-------
Regulatory Impact Analysis
Table 5-42 Annual C2 Marine Vessel Variable Costs; Freshly Manufactured Tier 4 Equipment Only (SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Vessel I
Sales |
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
C2 800-2000hp
Aftertreatment ! Reductant !
Housing Costs | System Costs |
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.1
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.1
$0.2
Subtotal V.ซe,
$0.0
71
$0.0 71
$0.0
$0.0
72
73
$0.0 | 73
$0.0
74
$0.0 I 75
$0.0
75
$0.0 I 76
$0.0
77
$0.0 | 77
$0.0 I 78
$0.0 | 79
$0.0
80
$0.0 | 80
$0.0
81
$0.0 82
$0.0
$0.0
$0.0
$0.0
83
83
84
85
$0.0 I 86
$0.0
86
$0.0 I 87
$0.0
$0.1
88
$0.3 I
C2>
Aftertreatment
Housing Costs
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.4
$1.8
$4.0
2000hp
| Reductant |
I System Costs [
$0.6
$0.6
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.5
$0.6
$0.6
$0.6
$3.0
$6.7
Subtotal
$0.9
$0.9
$0.7
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.9
$0.9
$0.9
$0.9
$0.9
$0.9
$0.9
$0.9
$4.8
$10.7
5-62
-------
Engineering Cost Estimates
Table 5-43 Annual Equipment Variable Costs; Freshly Manufactured Tier 4 Equipment Only (SMillions,
2005 dollars)
Calendar Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Locomotive
$10.9
$11.4
$9.8
$10.0
$10.2
$10.6
$10.9
$11.2
$11.9
$12.3
$12.7
$13.0
$13.3
$13.6
$13.8
$14.0
$14.3
$14.6
$14.8
$15.0
$15.0
$14.6
$14.3
$14.0
$13.6
$13.2
$77.6
$170.9
AnCoaItTs0tal
$10.9
$4.0 $15.4
$4.1
$3.4
$13.9
$13.4
$3.5 | $13.7
$3.5
$14.1
$3.5 I $14.4
$3.6
$14.7
$3.6 I $15.5
$3.6
$15.9
$3.7 | $16.4
$3.7 I $16.7
$3.7 | $17.1
$3.8
$17.4
$3.8 | $17.6
$3.8
$17.8
$3.9 $18.2
$3.9
$3.9
$4.0
$4.0
$18.5
$18.7
$19.0
$19.1
$4.0 | $18.7
$4.1
$18.4
$4.1 | $18.1
$4.2
$17.7
$4.2 I $17.4
$22.3 | $99.9
$49.1 I $220.0
PM
$5.4
$7.7
$6.9
$6.7
$6.9
$7.0
$7.2
$7.4
$7.8
$7.9
$8.2
$8.3
$8.5
$8.7
$8.8
$8.9
$9.1
$9.2
$9.4
$9.5
$9.5
$9.3
$9.2
$9.0
$8.9
$8.7
$49.9
$110.0
NOX+ NMHC
$5.4
$7.7
$6.9
$6.7
$6.9
$7.0
$7.2
$7.4
$7.8
$7.9
$8.2
$8.3
$8.5
$8.7
$8.8
$8.9
$9.1
$9.2
$9.4
$9.5
$9.5
$9.3
$9.2
$9.0
$8.9
$8.7
$49.9
$110.0
5-63
-------
Regulatory Impact Analysis
5.4 Operating Costs for Freshly Manufactured Tier 4 Engines
We anticipate an increase in costs associated with operating locomotives and marine
vessels. We anticipate three sources of increased operating costs: urea use; DPF
maintenance; and a fuel consumption impact. Increased operating costs associated with urea
use would occur only in those locomotives/vessels equipped with a urea SCR engine.
Maintenance costs associated with the DPF (for periodic cleaning of accumulated ash
resulting from unburned material that accumulates in the DPF) would occur in those
locomotives/vessels that are equipped with a DPF engine. The fuel consumption impact is
anticipated to occur more broadlywe expect that a one percent fuel consumption increase
would occur for all freshly manufactured Tier 4 locomotive and marine engines due to higher
exhaust backpressure resulting from aftertreatment devices. We also expect a one percent
fuel consumption increase would occur for remanufactured Tier 0 locomotives and two
percent for C2 marine engines due to our expectation that the tighter NOX standard may in
part be met using retarded fuel injection timing. The operating costs associated with the
remanufacturing program are presented in section 5.5
5.4.1 Increased Operating Costs Associated with Urea Use
Freshly manufactured Tier 4 engines are expected to be equipped with SCR systems.
The costs associated with the SCR system, including the reductant tank and dosing system,
are discussed in section 5.2.2.1 of this chapter. To estimate the costs associated with
reductant use, we first considered the dosage rate. For this analysis, we have used a dosing
rate of four percent reductant to every gallon of fuel burned. Using our marine and
locomotive emissions analysis work (see Chapter 3 of this RIA), we can determine the gallons
of fuel burned every year by SCR equipped pieces of equipment. The amount of reductant
used each year is then four percent of those gallons.
The cost per gallon of reductant would be dependent on the volume dispensed at each
facility, with smaller refueling sites experiencing higher costs. The type of reductant
storage/dispensing equipment, and the ultimate cost-per-gallon, for railroad and marine
industries will depend on the volume of fuel and reductant dispensed at each site. We expect
that the most common reductant will be urea and estimate that high-volume fixed sites may
choose to mix emissions-grade dry urea (or urea liquor) and de-mineralized water on-site,
whereas others may choose bulk or container delivery of a pre-mixed 32.5 percent urea-water
solution.1 In 2015, one source suggests that urea cost is expected to be ~$0.75/gallon for
retail facilities dispensing 200,000 - 1,000,000 gallons/month, and ~$1.00/gallon for those
dispensing 80,000 - 200,000 gallons/month.26 With the implementation of SCR for the on-
highway truck fleet in 2010, the economic factors for each urea supply option will be well-
known prior to implementation of the 2015 and 2016 NOX standards for locomotive and
1 While the discussion here is focussed on urea as a reductant, other reductants may be used and, if used, we
would expect them to be used only if they result in lower costs than urea. As such, we believe our estimates,
based on urea as the reductant, are conservative.
5-64
-------
Engineering Cost Estimates
marine engines, respectively/ In our draft cost analysis, we used a value of $1.00/gallon of
urea. To remain conservative and based on input from comments, for the final cost analysis
we have used a urea cost of $1.34/gallon. This cost should cover the costs associated with
distributing urea to the necessary point of transfer to locomotive and/or vessel (i.e., the
necessary infrastructure). The resultant increased operating costs associated with urea use are
presented in section 5.4.4. The costs associated with urea use are attributed solely to
NOX+NMHC control.
5.4.2 Increased Operating Costs Associated with DPF Maintenance
The maintenance demands associated with the addition of DPF hardware are discussed
in Chapter 4 of this RIA. For this analysis, we have estimated a maintenance interval of
200,000 gallons of fuel burned between DPF ash maintenance events. For a typical
locomotive engine having -4000 hp this equates to roughly 7000 hours of operation between
maintenance events. By comparison, our NRT4 rule estimated a maintenance interval of
3,000 hours for engines under 175 hp and 4,500 hours for engines over 750 hp. We believe
that the estimate of nearly 7,000 hours for the size engines used in applicable marine vessels
and locomotives is appropriate, especially given potential use of "flow-through" DPF
technologies as discussed in Chapter 4 of this RIA. We have also estimated the ash
maintenance event to take four hours per event at $50 per hour for labor, or $200 per event.
By using only those gallons burned in DPF equipped engines, we are then able to
calculate the maintenance costs associated with DPF maintenance. These costs are presented
in section 5.4.4. The costs associated with DPF maintenance are attributed solely to PM
control.
5.4.3 Increased Operating Costs Associated with Fuel Consumption Impacts
The high efficiency emission-control technologies expected to be used to meet the
Tier 4 standards involve wholly new system components integrated into engine designs and
calibrations and, as such, would be expected to change the fuel consumption characteristics of
the overall engine design. After reviewing the likely technology options available to the
engine manufacturers, we believe the integration of the engine and exhaust emission-control
systems into a single synergistic emission-control system will lead to locomotive and marine
engines that can meet demanding emission-control targets with only a small impact on fuel
consumption. Technology improvements have historically eliminated these marginal impacts
in the past and it is our expectation that this kind of continuing improvement will eliminate
the modest impact estimated here. However, because we cannot project the time frame for
1 Note that some marine C2 engines will meet the Tier 4 standards beginning in 2014. The operating costs
presented here in section 5.4 reflect that implementation schedule while the engine and equipment costs
presented in sections 5.2 and 5.3 do not. In those earlier sections, we chose to present all marine costs as though
their standards began in 2016 for ease of presentation. However, the operating costs are linked directly to
gallons burned which are, in turn, linked directly to emission inventories and reductions. Because our inventory
and emission reduction analysis must correspond directly to the actual implementation of the standards, our
operating costs are likewise presented according to the actual implementation of standards. Therefore, the
marine C2 operating costs are shown as beginning in 2014.
5-65
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Regulatory Impact Analysis
when this improvement would be realized, we have included this impact in our cost estimates
for the full period of the program to avoid underestimating costs.
Diesel particulate filters are anticipated to provide a step-wise decrease in PM
emissions by trapping and oxidizing the PM. The trapping of the very fine diesel PM is
accomplished by forcing the exhaust through a porous filtering media with extremely small
openings and long path lengths. This approach, called a wall flow filter, results in filtering
efficiencies for diesel PM greater than 90 percent but requires additional pumping work to
force the exhaust through these small openings. The impact of this additional pumping work
on fuel consumption is dependent on engine operating conditions. At low exhaust flow
conditions (i.e., low engine load, low turbocharger boost levels), the impact is so small that it
typically cannot be measured, while at very high load conditions, with high exhaust flow
conditions, the fuel economy impact can be as large as one to two percent. In our NRT4 rule,
for wall flow filters, we estimated that the average impact of this increased pumping work
was equivalent to an increased fuel consumption of approximately one percent. To be
conservative in this analysis, we have used this one percent impact regardless of DPF
technology even though the flow through technology that may be used is expected to have a
lower impact on fuel consumption because it results in less pumping work to force the exhaust
through the device.
As for the urea SCR system, we do not expect a fuel consumption increase associated
with this device. Urea SCR catalysts are flow through devices and while they do indeed
represent a slight increase in backpressure (i.e., increased pumping work to force exhaust
through the device), we expect that impact to be easily offset through engine control changes
that take advantage of the high NOX conversion afforded by the SCR system. Therefore, in
total, we expect a one percent fuel consumption increase for all freshly manufactured Tier 4
engines.
Using the gallons burned in freshly manufactured DPF equipped engines and, for line-
haul and passenger locomotives, the gallons burned in remanufactured Tier 0 engines, along
with an estimated diesel fuel price less taxes of $1.57/gallon, the costs associated with a fuel
consumption impact can be calculated.K These costs are presented in section 5.4.4 of this
chapter. The costs associated with the fuel consumption impact are split evenly between NOX
and PM control.
K To estimate the diesel fuel price, we started with the annual average nationwide price for 2006 for high sulfur
diesel fuel (excluding taxes) sold to commercial consumers from Table 41 of the Energy Information
Administration (EIA) Petroleum Marketing Annual 2006. We adjusted this 2006 price of $2.03/gallon to a 2012
price using the ratio of projected consumer purchased diesel fuel price in 2012 to the consumer purchased diesel
fuel price in 2006 as reported in Table 12 of the Annual Energy Outlook (AEO) 2007. We chose to use the
actual price in 2006 as the basis for estimating the future price, instead of directly relying on the projected prices
in AEO 2007, because refinery models, like the one used for the AEO, are better at estimating changes in prices
than they are at estimating actual prices. The actual price is a function of all the market forces that shape the
price, whereas refinery models can only approximately estimate these effects. Note that, in the draft cost
analysis, we used a value of $1.24/gallon of diesel fuel. As a result, if we exclude C2 marine remanufacturing
program fuel consumption impact which were not considered in the draft cost analysis, the fuel consumption cost
estimates are roughly 27% higher in the final cost analysis.
5-66
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Engineering Cost Estimates
Note that, as discussed in sections 4.2 and 5.2.2, we expect marine Tier 3 engines to
generally be recalibrated and marinized nonroad engines originally developed to meet
nonroad Tier 4 standards, except for the application of aftertreatment needed to meet nonroad
Tier 4 but not marine Tier 3. These advanced engines represent significant technical advances
from the marine Tier 2 engines having better high pressure fuel systems, better injectors,
improved turbochargers, and more sophisticated electronic control units. Likewise, they are
expected to have brake specific fuel consumption that is as good as, or better than, that of
marine Tier 2 engines, while producing significantly less NOx. We have therefore
conservatively assumed no impact of the marine Tier 3 standards on fuel consumption.
5.4.4 Total Increased Operating Costs Associated with Freshly Manufactured
Tier 4 Engines
The increased annual operating costs for each applicable market segmentlocomotive
line haul; switcher/passenger; marine Cl>600 kW; marine C2are presented in Table 5-44,
Table 5-45, Table 5-46, and Table 5-47, respectively. These costs are summarized to give the
total increased operating costs in Table 5-48. Table 5-49 shows the increased operating costs
by cost elementreductant, DPF maintenance, and fuel consumption impact.
Note that operating costs are attributed as follows: costs associated with reductant use
are attributed solely to NOX+NMHC control; costs associated with DPF maintenance are
attributed solely to PM control; and, costs associated with the fuel consumption impact are
split evenly between NOX+NMHC and PM control.
5-67
-------
Regulatory Impact Analysis
Table 5-44 Estimated Increased Operating Costs for Freshly Manufactured Tier 4 Line Haul Locomotives (monetary entries in 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
SCR
Equipped
Fuel Usage
(MM gal)
207
423
645
870
1100
1337
1581
1833
2091
2349
2611
2873
3136
3400
3663
3925
4185
4445
4706
4965
5221
5466
5702
5929
6147
6355
Reductant
Usage
(MM gal)
8
17
26
35
44
53
63
73
84
94
104
115
125
136
147
157
167
178
188
199
209
219
228
237
246
254
Annual
Reductant
Cost
($MM)
$11.1
$22.7
$34.6
$46.6
$58.9
$71.6
$84.7
$98.2
$112.1
$125.9
$139.9
$154.0
$168.1
$182.2
$196.4
$210.4
$224.3
$238.3
$252.2
$266.1
$279.8
$293.0
$305.6
$317.8
$329.5
$340.6
$814.1
$2,100.0
DPF
Equipped
Fuel Usage
(MM gal)
207
423
645
870
1100
1337
1581
1833
2091
2349
2611
2873
3136
3400
3663
3925
4185
4445
4706
4965
5221
5466
5702
5929
6147
6355
# of DPF
Maintenance
Events/Year
1036
2117
3224
4350
5499
6683
7905
9163
10456
11747
13055
14365
15682
17001
18317
19623
20926
22227
23529
24825
26105
27329
28510
29647
30736
31777
Annual DPF
Maintenance
Cost
($MM)
$0.2
$0.4
$0.6
$0.9
$1.1
$1.3
$1.6
$1.8
$2.1
$2.3
$2.6
$2.9
$3.1
$3.4
$3.7
$3.9
$4.2
$4.4
$4.7
$5.0
$5.2
$5.5
$5.7
$5.9
$6.1
$6.4
$15.2
$39.2
Tier 4
Fuel
Usage
(MM gal)
207
423
645
870
1100
1337
1581
1833
2091
2349
2611
2873
3136
3400
3663
3925
4185
4445
4706
4965
5221
5466
5702
5929
6147
6355
Increased
Fuel
Consumption
at 1 percent
(MM gal)
2
4
6
9
11
13
16
18
21
23
26
29
*^1
34
37
39
42
44
47
50
52
55
57
59
61
64
Annual Cost
of Fuel
Consumption
Impact
($MM)
$3.3
$6.6
$10.1
$13.7
$17.3
$21.0
$24.8
$28.8
$32.8
$36.9
$41.0
$45.1
$49.2
$53.4
$57.5
$61.6
$65.7
$69.8
$73.8
$77.9
$81.9
$85.8
$89.5
$93.0
$96.5
$99.7
$238.3
$614.8
Annual
Increased
Operating
Costs
($MM)
$14.6
$29.8
$45.3
$61.1
$77.3
$93.9
$111.1
$128.8
$147.0
$165.1
$183.5
$202.0
$220.5
$239.0
$257.5
$275.9
$294.2
$312.5
$330.8
$349.0
$367.0
$384.2
$400.8
$416.8
$432.1
$446.7
$1 ,067.6
$2,754.0
5-68
-------
Engineering Cost Estimates
Table 5-45 Estimated Increased Operating Costs for Freshly Manufactured Tier 4 Switcher & Passenger Locomotives (monetary entries in 2005
dollars)
Calendar
Year
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPVat7%
NPVat3%
SCR
Equipped
Fuel Usage
(MM gal)
Reductant
Usage
(MM gal)
Annual
Reductant
Cost
($MM)
10
21
0
1
$0.6
$1.1
31 I 1 I $1.7
42 I 2 I $2.2
53
63
2
3
$2.8
$3.4
74 I 3 I $4.0
85 I 3 I $4.6
101
119
A
5
$5.4
$6.4
138 I 6 I $7.4
159 I 6 I $8.5
180
203
7
8
$9.7
$10.9
227 I 9 I $12.2
253 10 $13.6
281
310
11
12
$15.0
$16.6
340 I 14 I $18.2
371
15
$19.9
403 I 16 I $21.6
434
17
$23.3
464 I 19 I $24.9
494
524
20
21
$26.5
$28.1
553 | 22 | $29.6
$52.1
I | $141.3
DPF
Equipped
Fuel Usage
(MM gal)
# of DPF
Maintenanc
e
Events/Year
Annual DPF
Maintenance
Cost
($MM)
10
21
51
104
$0.0
$0.0
31 I 156 I $0.0
42 I 209 I $0.0
53
63
263
317
$0.1
$0.1
74 I 371 I $0.1
85 I 426 I $0.1
101
119
505
594
$0.1
$0.1
138 I 691 I $0.1
159 I 793 I $0.2
180
203
902
1016
$0.2
$0.2
227 I 1137 I $0.2
253 1265 $0.3
281
310
1404
1549
$0.3
$0.3
340 I 1699 I $0.3
371
1856
$0.4
403 I 2014 I $0.4
434
2170
$0.4
464 I 2322 I $0.5
494
524
2472
2619
$0.5
$0.5
553 | 2764 [ $0.6
$1.0
I | $2.6
! Increased I
Tier 4
Passenger
Fuel Usage
(MM gal)
Passenger
Fuel
Consumptio
nat 1
percent (MM
Annual Cost
of Fuel
Consumptio
n Impact
($MM)
I gal) I
7
14
0
0
$0.1
$0.2
22 I 0 I $0.3
29 I 0 I $0.5
36
44
0
0
$0.6
$0.7
51 I 1 I $0.8
58 I 1 I $0.9
66
73
1
1
$1.0
$1.1
80 I 1 I $1.3
88 : 1 : $1.4
95
102
1
1
$1.5
$1.6
109 : 1 : $1.7
116 1 $1.8
123
131
1
1
$1.9
$2.0
138 I 1 I $2.2
146
1
$2.3
154 I 2 I $2.4
161
2
$2.5
168 I 2 I $2.6
173
178
2
2
$2.7
$2.8
183 | 2 | $2.9
$7.2
I | $18.5
Annual
Increased
Operating
Costs
($MM)
$0.7
$1.4
$2.0
$2.7
$3.4
$4.1
$4.9
$5.6
$6.5
$7.6
$8.8
$10.0
$11.3
$12.7
$14.1
$15.6
$17.3
$19.0
$20.7
$22.6
$24.4
$26.2
$28.0
$29.7
$31.4
$33.0
$60.3
$162.4
5-69
-------
Regulatory Impact Analysis
Table 5-46 Estimated Increased Operating Costs for Freshly Manufactured Tier 4 Marine Cl Engines >600 kW (monetary entries in 2005 dollars)
Calendar
Year
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPVat
7%
NPVat
3%
SCR
Equipped
Fuel
Usage
(MM gal)
54
149
281
412
542
671
800
927
1052
1176
1297
1415
1529
1629
1708
1771
1822
1869
1911
1949
1983
2015
2044
2071
2096
Reductant
Usage (MM
gai)
2
6
11
16
22
27
32
37
42
47
52
57
61
65
68
71
73
75
76
78
79
81
82
83
84
Annual
Reductant
Cost
($MM)
$2.9
$8.0
$15.0
$22.1
$29.0
$36.0
$42.9
$49.7
$56.4
$63.0
$69.5
$75.9
$82.0
$87.3
$91.6
$94.9
$97.7
$100.2
$102.5
$104.5
$106.3
$108.0
$109.6
$111.0
$112.4
$322.0
$825.6
DPF
Equipped
Fuel Usage
(MM gal)
54
149
281
412
542
671
800
927
1052
1176
1297
1415
1529
1629
1708
1771
1822
1869
1911
1949
1983
2015
2044
2071
2096
# of DPF
Maintenance
Events/Year
272
745
1403
2058
2709
3356
3999
4635
5262
5880
6486
7077
7645
8144
8542
8853
9112
9345
9557
9746
9917
10074
10219
10355
10482
Annual DPF
Maintenance
Cost
($MM)
$0.1
$0.1
$0.3
$0.4
$0.5
$0.7
$0.8
$0.9
$1.1
$1.2
$1.3
$1.4
$1.5
$1.6
$1.7
$1.8
$1.8
$1.9
$1.9
$1.9
$2.0
$2.0
$2.0
$2.1
$2.1
$6.0
$15.4
Tier 4
Fuel
Usage
(MM gal)
54
149
281
412
542
671
800
927
1052
1176
1297
1415
1529
1629
1708
1771
1822
1869
1911
1949
1983
2015
2044
2071
2096
Increased
Fuel
Consumption
at 1 percent
(MM gal)
1
1
3
4
5
7
8
9
11
12
13
14
15
16
17
18
18
19
19
19
20
20
20
21
21
Annual Cost
of Fuel
Consumption
Impact
($MM)
$0.9
$2.3
$4.4
$6.5
$8.5
$10.5
$12.5
$14.5
$16.5
$18.5
$20.4
$22.2
$24.0
$25.6
$26.8
$27.8
$28.6
$29.3
$30.0
$30.6
$31.1
$31.6
$32.1
$32.5
$32.9
$94.3
$241 .7
Annual
Increased
Operating
Cost
($MM)
$3.8
$10.5
$19.7
$28.9
$38.1
$47.2
$56.2
$65.2
$74.0
$82.7
$91.2
$99.5
$107.5
$114.5
$120.1
$124.5
$128.1
$131.4
$134.4
$137.0
$139.4
$141.6
$143.7
$145.6
$147.4
$422.2
$1,082.7
5-70
-------
Engineering Cost Estimates
Table 5-47 Estimated Increased Operating Costs for Freshly Manufactured Tier 4 Marine C2 Engines (monetary entries in 2005 dollars)
Calendar
Year
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
NPVat
7%
NPVat
3%
SCR
Equipped
Fuel
Usage
(MM gal)
110
212
313
417
520
624
728
831
934
1037
1140
1243
1345
1447
1549
1650
1751
1850
1949
2045
2140
2233
2321
2391
2446
2497
2546
Reductant
Usage (MM
gai)
4
13
17
21
25
29
33
37
41
46
50
54
58
62
66
70
74
78
82
86
89
93
96
98
100
102
Annual
Reductant
Cost
($MM)
$5.9
$11.3
$16.8
$22.3
$27.9
$33.5
$39.0
$44.6
$50.1
$55.6
$61.1
$66.6
$72.1
$77.6
$83.0
$88.5
$93.8
$99.2
$104.4
$109.6
$114.7
$119.7
$124.4
$128.2
$131.1
$133.9
$136.4
$386.7
$964.4
DPF
Equipped
Fuel Usage
(MM gal)
110
212
313
417
520
624
728
831
934
1037
1140
1243
1345
1447
1549
1650
1751
1850
1949
2045
2140
2233
2321
2391
2446
2497
2546
# of DPF
Maintenance
Events/Year
551
1058
1566
2083
2602
3121
3639
4156
4672
5187
5700
6213
6725
7235
7745
8251
8753
9250
9743
10227
10702
11165
11604
11957
12232
12487
12728
Annual DPF
Maintenance
Cost
($MM)
$0.1
$0.2
$0.3
$0.4
$0.5
$0.6
$0.7
$0.8
$0.9
$1.0
$1.1
$1.2
$1.3
$1.4
$1.5
$1.7
$1.8
$1.9
$1.9
$2.0
$2.1
$2.2
$2.3
$2.4
$2.4
$2.5
$2.5
$7.2
$18.0
Tier 4 Fuel
Usage
(MM gal)
110
212
313
417
520
624
728
831
934
1037
1140
1243
1345
1447
1549
1650
1751
1850
1949
2045
2140
2233
2321
2391
2446
2497
2546
Increased
Fuel
Consumption
at 1 percent
(MM gal)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
17
18
19
19
20
21
22
23
24
24
25
25
Annual Cost
of Fuel
Consumption
Impact
($MM)
$1.7
$3.3
$4.9
$6.5
$8.2
$9.8
$11.4
$13.0
$14.7
$16.3
$17.9
$19.5
$21.1
$22.7
$24.3
$25.9
$27.5
$29.0
$30.6
$32.1
$33.6
$35.0
$36.4
$37.5
$38.4
$39.2
$39.9
$113.2
$282.3
Annual
Increased
Operating
Cost
($MM)
$7.7
$14.9
$22.0
$29.3
$36.6
$43.9
$51.2
$58.4
$65.7
$72.9
$80.1
$87.3
$94.5
$101.7
$108.9
$116.0
$123.1
$130.0
$137.0
$143.8
$150.5
$157.0
$163.1
$168.1
$172.0
$175.5
$178.9
$507.1
$1,264.7
5-71
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Regulatory Impact Analysis
Table 5-48 Estimated Increased Operating Costs by Market Segment; Freshly Manufactured Tier 4
Engines (SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Locomotive 0 .. , Marine C1 Marine
Line-haul Switcher & >6QOkw Q2
Passenger
1 l
; ; $7.7
$14.6 ! $0.7 ! $14.9
$29.8 $1.4 $3.8 $22.0
$45.3 $2.0 $10.5 $29.3
$61.1 I $2.7 I $19.7 $36.6
$77.3 : $3.4 : $28.9 $43.9
$93.9 ' $4.1 ' $38.1 $51.2
$111.1 $4.9 $47.2 $58.4
$128.8 ! $5.6 ! $56.2 $65.7
$147.0 ! $6.5 ! $65.2 : $72.9
$165.1 $7.6 $74.0 $80.1
$183.5 $8.8 $82.7 $87.3
$202.0 ! $10.0 ! $91.2 ! $94.5
$220.5 ! $11.3 ! $99.5 ! $101.7
$239.0 ' $12.7 ' $107.5 ' $108.9
$257.5 $14.1 $114.5 $116.0
$275.9 ! $15.6 ! $120.1 ! $123.1
$294.2 i $17.3 I $124.5 i $130.0
$312.5 $19.0 $128.1 $137.0
$330.8 $20.7 $131.4 $143.8
$349.0 i $22.6 i $134.4 i $150.5
$367.0 i $24.4 I $137.0 i $157.0
$384.2 $26.2 $139.4 $163.1
$400.8 i $28.0 i $141.6 i $168.1
$416.8 : $29.7 : $143.7 i $172.0
$432.1 $31.4 $145.6 $175.5
$446.7 $33.0 $147.4 $178.9
$1,067.6 $60.3 $422.2 $507.1
$2,754.0 I $162.4 I $1,082.7 I $1,264.7
Total
$7.7
$30.1
$57.0
$87.1
$120.2
$153.5
$187.3
$221.6
$256.3
$291.6
$326.9
$362.3
$397.7
$433.0
$468.1
$502.1
$534.6
$565.9
$596.5
$626.7
$656.4
$685.4
$713.0
$738.5
$762.1
$784.6
$806.1
$2,057.2
$5,263.7
PM
$1.0
$3.8
$7.1
$10.9
$15.0
$19.2
$23.5
$27.8
$32.1
$36.5
$40.9
$45.3
$49.6
$54.0
$58.3
$62.5
$66.5
$70.3
$74.0
$77.7
$81.3
$84.8
$88.1
$91.2
$94.0
$96.7
$99.3
$255.9
$653.9
NOX+
NMHC
$6.8
$26.3
$49.8
$76.2
$105.1
$134.3
$163.9
$193.9
$224.2
$255.1
$286.0
$317.1
$348.1
$379.0
$409.8
$439.6
$468.2
$495.7
$522.5
$549.0
$575.1
$600.6
$624.8
$647.3
$668.1
$687.9
$706.8
$1,801.3
$4,609.9
5-72
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Engineering Cost Estimates
Table 5-49 Estimated Increased Operating Costs by Cost Element Associated with the Final Program
(SMillions, 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Reductant DPF Fuel
Use Maintenance Impact
$5.9 I $0.1 I $1.7
$23.0
$43.5
$0.4
$0.8
$6.7
$12.6
$66.6 I $1.2 I $19.3
$91.8 $1.7 $26.7
$117.3
$143.1
$2.2
$2.7
$34.1
$41.6
$169.3 I $3.2 I $49.2
$195.8
$3.7
$56.9
$222.8 I $4.2 I $64.7
$249.8
$4.7
$72.4
$277.0 I $5.2 I $80.2
$304.1
$331.2
$5.7
$6.2
$87.9
$95.6
$358.1 I $6.7 I $103.2
$384.3 I $7.2 I $110.6
$409.3
$433.4
$7.6
$8.1
$117.7
$124.4
$457.0 I $8.5 I $131.0
$480.3 I $9.0 I $137.4
$503.2
$525.6
$9.4
$9.8
$143.8
$150.0
$546.9 I $10.2 I $155.8
$566.7 I $10.6 I $161.2
$585.0
$602.4
$10.9
$11.2
$166.2
$170.9
$619.1 I $11.6 I $175.4
$1 ,574.8
$29.4
$453.0
$4,031.2 I $75.2 I $1,157.3
Total PM Nฐx+
I I NMHC
$7.7 I $1.0 I $6.8
$30.1
$57.0
$3.8
$7.1
$26.3
$49.8
$87.1 I $10.9 I $76.2
$120.2 $15.0 $105.1
$153.5
$187.3
$19.2
$23.5
$134.3
$163.9
$221.6 I $27.8 I $193.9
$256.3
$32.1
$224.2
$291.6 I $36.5 I $255.1
$326.9
$40.9
$286.0
$362.3 I $45.3 I $317.1
$397.7
$433.0
$49.6
$54.0
$348.1
$379.0
$468.1 I $58.3 I $409.8
$502.1 I $62.5 I $439.6
$534.6
$565.9
$66.5
$70.3
$468.2
$495.7
$596.5 I $74.0 I $522.5
$626.7 I $77.7 I $549.0
$656.4
$685.4
$81.3
$84.8
$575.1
$600.6
$713.0 I $88.1 I $624.8
$738.5 I $91.2 I $647.3
$762.1
$784.6
$94.0
$96.7
$668.1
$687.9
$806.1 I $99.3 I $706.8
$2,057.2
$255.9
$1,801.3
$5,263.7 I $653.9 I $4,609.9
As shown in Table 5-49, the net present value of the annual operating costs is
estimated at $5.3 billion at a three percent discount rate or $2.1 billion at a seven percent
discount rate. The primary increased operating cost is associated with reductant use which
accounts for nearly three quarters of the estimated costs. Since reductant use is meant for
NOX+NMHC control, most of the increased operating costs are attributed to NOX+NMHC
control.
5.5 Engineering Hardware Costs and Operating Costs Associated with the
Locomotive and Marine Remanufacturing Programs
Our program also contains requirements that remanufactured locomotives meet more
stringent standards than those to which they were designed originally. For the final rule, we
have included an analogous requirement for remanufactured marine engines. Because the
standards for those engines are more stringent, they cannot necessarily be remanufactured to
5-73
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Regulatory Impact Analysis
their original configuration but must, instead, include some new technology and/or engine
controls to ensure compliance with the more stringent standards. The incremental costs
associated with those new technologies must be considered as part of this rule. The
remanufacturing process is not a low cost endeavor. However, it is much less costly than
purchasing a freshly manufactured engine. The costs we have estimated for the
remanufacturing program are meant to capture the incremental costs associated with
remanufacturing.
To summarize the requirements, the existing fleet of locomotives that are currently
subject to Tier 0 standards would need to comply with a new Tier 0 PM standard and a new
Tier 0 NOX line-haul standard, except that Tier 0 locomotives that were freshly manufactured
before 1994 would remain subject to the existing Tier 0 NOX standards. In general, these new
Tier 0 standards would apply when the locomotive is remanufactured as early as January 1,
2008. For locomotives currently subject to Tier 1 and Tier 2 standards, more stringent PM
standards would apply at the point of next remanufacture as early as January 1, 2008, but not
later than 2010. For marine engines, where an appropriate locomotive remanufacture kit
exists, one must be used when the marine engine is remanufactured.
To meet the locomotive remanufactured engine standards, we project that engine
manufacturers will utilize incremental improvements to existing engine components. In many
cases, similar improvements have already been implemented on freshly manufactured
locomotives to meet our current locomotive standards. To meet the lower NOX standard
required for Tier 0 locomotives, we expect possible improvements in the fuel system, the
turbo charger, and the engine calibration. Such changes are expected to increase fuel
consumption by one percent as discussed below. We have estimated the incremental
hardware costs associated with the remanufacture of a Tier 0 locomotive to be $33,800 for the
first remanufacture and $22,300 for the second one. The lower cost for the second
remanufacture is because not all of the new technology would have to be remanufactured
during the second effort. We have estimated that first remanufacture would occur through
2016 with the second one occurring after 2016.
To meet the PM standards for the Tier 1 remanufacturing program, we expect that
lubricating oil consumption controls will be implemented, along with the ultra low sulfur
diesel fuel requirement for locomotive engines (which was previously finalized in our
nonroad clean diesel rulemaking). Because of the significant fraction of lubricating oil
present in PM from today's locomotives, we believe that existing low-oil-consumption piston
ring-pack designs, when used in conjunction with improvements to closed crankcase
ventilation systems, will provide significant, near-term PM reductions. We have estimated
these hardware costs to be roughly equivalent to the hardware costs associated with the Tier 0
remanufacturing. We have also estimated the first remanufacture would occur through 2016
with the second one occurring after 2016. We do not expect a fuel consumption impact for
these remanufactured engines.
To meet the more stringent PM standards for the Tier 2 remanufacturing program, we
expect use of improved fuel systems. Based on work previously done for our NRT4 rule, we
have estimated the incremental hardware cost of a new fuel system on a line haul locomotive
at $11,750 and on a switcher at $8,700. This cost differential exists because the line haul
5-74
-------
Engineering Cost Estimates
locomotives have larger engines and, hence, larger fuel rails and pumps, etc. We have not
estimated an incremental hardware cost associated with a second remanufacture for Tier 2
locomotives because we would not expect the fuel system would need a second
remanufacture. We have estimated that the first remanufacture would occur prior to 2020.
We do not expect a fuel consumption impact for these remanufactured engines.
We have not estimated any incremental costs for Tier 3 remanufacturing because these
locomotives would not meet a remanufactured standard more stringent than their original
design. Therefore, while costs would be incurred to remanufacture these engines, those costs
would not be different from current remanufacturing kits.
In the case of our locomotive standards, it is worthwhile to note the difference in how
we have handled variable costs for the remanufactured Tier 2 engines versus the new Tier 3
standards. In some cases, we believe manufacturers may choose to introduce more modern
common rail fuel systems for both their freshly manufactured Tier 3 products and for
application to their existing Tier 2 products at the time of remanufacturing. In the case of the
freshly manufactured Tier 3 engine, we are projecting no increase in engine variable cost
because, for example, we expect the common rail fuel system to be no more expensive (and
perhaps cheaper) than the fuel system that would have been used absent our new standards.
However, we have accounted for these higher costs for the remanufactured Tier 2 engines
reflecting the fact that the new fuel system is an incremental cost for the rebuild that would
not have occurred absent our new standard (because the existing fuel system could be reused
at remanufacture absent the new standard).
For Tier 4 remanufacturing, we have estimated that locomotive engines would need a
new set of aftertreatment devices and a remanufactured fuel system. We have estimated the
aftertreatment device costs at slightly lower than the original equipment costs because we
would expect that precious metals would be recycled from the device being removed and
replaced. This results in remanufactured DPF and SCR system costs of 60 percent and 97
percent, respectively, relative to the original cost. The 60/97 differential occurs because of
the larger amount of precious metals contained in the DPF versus the SCR catalyst which
contains only a small amount of precious metal for the DOC function. For the
remanufactured fuel system, we have included the hardware costs already mentioned above
associated with costs for Tier 2 remanufacturing (i.e., $11,750 or $8,700). We do not expect a
fuel consumption impact for these remanufactured engines since they will not be meeting a
more stringent standard than their original design.
For marine engines, we expect the same kits to be used as are used for locomotives.
For C2 engines, we have used identical hardware costs as used for Tier 0 locomotives. For
Cl engines, we have used half that value simply because the engines are smaller. We do not
expect a second remanufacturing event on these engines as is expected for locomotives.
However, by the time that some of the Cl engines have been remanufactured, we expect the
5-75
-------
Regulatory Impact Analysis
available locomotive kits to be less costly. We do not expect a fuel consumption impact for
the Cl engines, but do expect one for the C2 engines, as discussed below.L
These estimated incremental remanufacturing hardware costs are summarized in Table
5-50.
L Note that the costs associated with the marine remanufacturing program are consistent with the inventory
reductions discussed in section 3.1.3 of this RIA. Our estimate of the number of remanufactured engines is
presented in a memorandum from Amy Kopin to the docket for this rule (see Docket Item No. EPA-HQ-OAR-
2003-0190-0847).
5-76
-------
Engineering Cost Estimates
Table 5-50 Estimated Incremental Hardware Costs Associated with the Locomotive Remanufacturing
Program ($/remanufacture, 2005 dollars)
Segment
Locomotive Line-haul
Locomotive Switcher/Passenger
Cl Marine
C2 Marine
Tier
TierO
Tierl
Tier 2
TierS
Tier 4
TierO
Tierl
Tier 2
TierS
Tier 4
TierO
TierO
1st Remanufacture
$33,800
$33,800
$11,750
$0
$66,000
$33,800
$33,800
$8,700
$0
$21,700
$16,900/$11,150
$33,200
2nd Remanufacture
$22,300
$22,300
$0
$0
$66,000
$22,300
$22,300
$0
$0
$21,700
N/A
N/A
We have also estimated an incremental operating cost associated with the locomotive
and marine remanufacturing programs. We expect a fuel consumption impact would occur
for those engines remanufactured to a more stringent NOX standard than the NOX standard to
which they were designed originally. We would expect this because those engines are
expected to employ engine control changesretarded injection timingto help control NOX
emissions. The result of such a change is slightly higher fuel consumption on the order of one
percent. For locomotives, only Tier 0 locomotives would be remanufactured to a more
stringent NOX standard than that for which they were originally designed. Therefore, we have
estimated a one percent fuel consumption increase for remanufactured Tier 0 locomotives.
On the marine side, only C2 marine remanufactured engines are expected to experience a fuel
consumption impact. As noted, the locomotives are expected to see a one percent fuel
consumption impact. However, the impacted marine C2 engines will be going from an
uncontrolled state to a controlled state resulting in a larger impact relative to the locomotives
for which the kits are actually made. Therefore, we have estimated a two percent fuel
consumption increase for remanufactured C2 marine engines.
Of note in the following tables is the annual reduction of gallons consumed by
remanufactured Tier 0 locomotives and pre-Tier 3 C2 marine engines. This is a result of older
Tier 0 locomotives and C2 vessels slowly being retired from duty and being replaced by
freshly manufactured Tier 4 locomotives and vessels. There are no fuel consumption impacts
shown for remanufactured Tier 1, 2 and 3 locomotives or Cl marine engines because we
expect no fuel consumption impacts for them as a result of this program (no new
aftertreatment devices so no urea nor DPF maintenance costs and no fuel consumption
impact).
Using these remanufacturing kit hardware costs and estimated fuel consumption
impacts, we can calculate the total costs associated with the final remanufacturing program.
These costs are presented in Table 5-51 for line haul locomotives, Table 5-52 for switchers
and passenger locomotives, and Table 5-53 for marine engines. See Chapter 3 of this final
RIA for how we determined the rate at which locomotives are remanufactured. The number
5-79
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Regulatory Impact Analysis
remanufactured and the calendar years in which they occur are also shown in the tables. As
shown, the net present value of the annual remanufacturing costs is estimated at $1.5 billion
and $0.8 billion for line haul locomotives at a three percent and seven percent discount rate,
respectively. For switchers and passenger locomotives, we have estimated the net present
value of the annual costs at $157 million and $90 million at a three and seven percent discount
rate, respectively. For marine engines, these costs are $450 million and $289 million,
respectively. Note that, while not shown in Table 5-51 through Table 5-53, the costs
associated with the locomotive remanufacturing program are split evenly between
NOX+NMHC and PM control. This split is shown in Table 5-59.
5-78
-------
Engineering Cost Estimates
Table 5-51 Estimated Annual Costs Associated with the Remanufacturing Program for Line Haul Locomotives (monetary entries in 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat
7%
NPVat
3%
TierO
Remans
1651
1220
2096
984
1310
624
393
1186
1179
1284
231
370
579
1103
501
646
622
610
505
$/reman
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
Hardware
Costs
($MM)
$55.8
$41.2
$70.8
$33.3
$44.3
$21.1
$13.3
$40.1
$26.3
$28.6
$5.2
$8.2
$12.9
$24.6
$11.2
$14.4
$13.9
$13.6
$11.3
$260.3
$365.3
Reman
TierO
Fuel
Usage
(MMgal)
146.7
145.5
375.4
779.8
947.0
1,174.3
1,227.5
1,232.2
1,401.1
1,554.2
1,511.8
1 ,443.7
1,334.6
1,219.3
1,108.5
1,002.3
900.6
804.3
710.3
622.0
539.1
462.4
393.2
330.1
272.8
220.6
168.3
123.9
88.0
57.7
33.4
15.7
4.8
Incressed
Fuel
Consumption
(MM 9^0
1.5
1.5
3.8
7.8
9.5
11.7
12.3
12.3
14.0
15.5
15.1
14.4
13.3
12.2
11.1
10.0
9.0
8.0
7.1
6.2
5.4
4.6
3.9
3.3
2.7
2.2
1.7
1.2
0.9
0.6
0.3
0.2
0.0
Fuel
Costs
($MM)
$2.3
$2.3
$5.9
$12.2
$14.9
$18.4
$19.3
$19.3
$22.0
$24.4
$23.7
$22.7
$20.9
$19.1
$17.4
$15.7
$14.1
$12.6
$11.1
$9.8
$8.5
$7.3
$6.2
$5.2
$4.3
$3.5
$2.6
$1.9
$1.4
$0.9
$0.5
$0.2
$0.1
$139.9
$230.4
Subtotal
($MM)
$58.1
$2.3
$47.1
$83.1
$48.1
$62.7
$40.4
$32.6
$62.1
$50.7
$52.4
$27.8
$29.2
$19.1
$30.3
$40.3
$25.3
$27.0
$11.1
$9.8
$22.3
$20.9
$17.4
$5.2
$4.3
$3.5
$2.6
$1.9
$1.4
$0.9
$0.5
$0.2
$0.1
$400.2
$595.7
Tier!
Hardware
Remans $/reman Costs
($MM)
803 $33,800 $27.1
489 $33,800 $16.5
931 $33,800 $31 .5
803 $22,300 $17.9
489 $22,300 $10.9
931 $22,300 $20.8
442 $22,300 $9.8
220 $22,300 $4.9
419 $22,300 $9.3
$72.1
$105.2
Tier 2
Hardware
Remans $/reman Costs
($MM)
719 $11,749 $8.4
791 $11,749 $9.3
693 $11,749 $8.1
712 $11,749 $8.4
737 $1 1 ,749 $8.7
770 $1 1 ,749 $9.0
791 $1 1 ,749 $9.3
719
791
693
712
737
770
791
324
356
312
320
332
$29.3
$44.3
Tier 4
Remans
838
874
896
910
930
957
989
1018
1045
1059
1928
1983
2026
2060
2095
2133
2181
2229
$/reman
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
$67,108
Hardware
Costs
($MM)
$56.2
$58.7
$60.1
$61.1
$62.4
$64.2
$66.3
$68.3
$70.2
$71.1
$129.4
$133.1
$136.0
$138.2
$140.6
$143.2
$146.4
$149.6
$273.1
$767.1
Annual
Costs
($MM)
$58.1
$29.4
$47.1
$99.6
$79.6
$71.1
$49.7
$40.8
$70.4
$59.3
$61.4
$55.0
$29.2
$30.0
$51.1
$96.6
$84.0
$87.1
$72.2
$72.1
$86.6
$87.2
$85.7
$85.2
$75.4
$132.8
$140.6
$147.3
$139.6
$141.5
$143.7
$146.6
$149.6
$774.8
$1,512.4
5-79
-------
Regulatory Impact Analysis
Table 5-52 Estimated Annual Costs Associated with the Remanufacturing Program for Switcher and Passenger Locomotives (monetary entries in
2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Tier 0& Tier 1
Remans
31
78
314
312
309
307
307
269
271
273
274
276
278
279
281
318
315
311
266
260
253
245
236
226
190
179
166
154
142
132
123
114
105
Hardware
$/reman Costs
($MM)
$33,800 $1.1
$33,800 $2.6
$33,800 $10.6
$33,800 $10.5
$33,800 $10.5
$33,800 $10.4
$33,800 $10.4
$33,800 $9.1
$33,800 $9.2
$22,300 $6.1
$22,300 $6.1
$22,300 $6.2
$22,300 $6.2
$22,300 $6.2
$22,300 $6.3
$22,300 $7.1
$22,300 $7.0
$22,300 $6.9
$22,300 $5.9
$22,300 $5.8
$22,300 $5.6
$22,300 $5.5
$22,300 $5.3
$22,300 $5.0
$22,300 $4.2
$22,300 $4.0
$22,300 $3.7
$22,300 $3.4
$22,300 $3.2
$22,300 $2.9
$22,300 $2.7
$22,300 $2.5
$22,300 $2.3
$75.0
$123.9
Reman
Tier 0
r^ Increased Fuel
Passenger
Usage ฐSK
(MMgal)
4.8 0.0
16.9 0.2
28.9 0.3
40.0 0.4
44.4 0.4
48.0 0.5
50.9 0.5
47.2 0.5
48.5 0.5
49.3 0.5
43.7 0.4
38.4 0.4
33.0 0.3
27.6 0.3
22.2 0.2
17.5 0.2
13.5 0.1
9.8 0.1
6.8 0.1
4.3 0.0
2.5 0.0
1.2 0.0
0.4 0.0
Fuel
Costs
($MM)
$0.1
$0.3
$0.5
$0.6
$0.7
$0.8
$0.8
$0.7
$0.8
$0.8
$0.7
$0.6
$0.5
$0.4
$0.3
$0.3
$0.2
$0.2
$0.1
$0.1
$0.0
$0.0
$0.0
$4.6
$6.8
Subtotal
/
-------
Engineering Cost Estimates
Table 5-53 Estimated Annual Costs Associated with the Remanufacturing Program for Marine Engines (monetary entries in 2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
C1 Marine
Reman
Remans $/reman a* w.are
($MM)
403 $16,900 $6.8
369 $16,900 $6.2
298 $16,900 $5.0
241 $16,900 $4.1
184 $16,900 $3.1
128 $11,150 $1.4
73 $11,150 $0.8
$15.1
$21.1
C2 Marine
C2 Reman 0,
Remans $/reman Hardware . .. ,
Costs ($MM) controlled
325 $33,800 $11.0 9%
331 $33,800 $11.2 18%
337 $33,800 $11.4 26%
343 $33,800 $11.6 35%
349 $33,800 $11.8 44%
324 $33,800 $11.0 53%
241 $33,800 $8.1 62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
62%
$51.5
$64.0
Pre-T3
C2 fuel
(MMgal)
2,044
2,063
2,081
2,100
2,119
2,105
2,021
1,937
1,853
1,769
1,685
1,602
1,519
1,436
1,354
1,272
1,191
1,110
1,030
949
870
791
713
637
562
488
417
349
289
247
218
193
170
21,279
30,735
Controlle
d C2 fuel
(MMgal)
158
319
483
650
820
978
1,095
1,050
1,004
959
913
868
823
778
734
690
646
602
558
515
471
429
387
345
304
265
226
189
157
134
118
104
92
7,089
1 1 ,628
Increase
dfuel
due to
FE
penalty
(MMgal)
3.2
6.4
9.7
13.0
16.4
19.6
21.9
21.0
20.1
19.2
18.3
17.4
16.5
15.6
14.7
13.8
12.9
12.0
11.2
10.3
9.4
8.6
7.7
6.9
6.1
5.3
4.5
3.8
3.1
2.7
2.4
2.1
1.8
141.8
232.6
C2
Subtotal
($MM)
$5.0
$10.0
$15.2
$20.4
$25.7
$30.7
$34.4
$32.9
$31.5
$30.1
$28.7
$27.2
$25.8
$24.4
$23.0
$21.6
$20.3
$18.9
$17.5
$16.1
$14.8
$13.5
$12.1
$10.8
$9.6
$8.3
$7.1
$5.9
$4.9
$4.2
$3.7
$3.3
$2.9
$222.5
$364.9
Annual
Costs
($MM)
$16.0
$21.2
$26.6
$32.0
$44.3
$47.9
$47.6
$37.0
$34.6
$31.5
$29.5
$27.2
$25.8
$24.4
$23.0
$21.6
$20.3
$18.9
$17.5
$16.1
$14.8
$13.5
$12.1
$10.8
$9.6
$8.3
$7.1
$5.9
$4.9
$4.2
$3.7
$3.3
$2.9
$289.1
$450.1
5-81
-------
Regulatory Impact Analysis
5.6 Summary of Final Program Engineering Costs
Details of our engine and equipment cost estimates were presented in Sections 5.2 and
5.3. Here we summarize the cost estimates. Section 5.6.1 summarizes the engine-related
costs associated with the new Tier 4 standards for freshly manufactured engines. Section
5.6.2 summarizes the equipment-related costs associated with the new Tier 4 standards for
freshly manufactured equipment. Section 5.6.3 summarizes the operating costs associated
with the freshly manufactured Tier 4 engines and equipment. Section 5.6.4 summarizes the
hardware costs and operating costs associated with the locomotive and marine
remanufacturing programs. Section 5.6.5 summarizes all these costs and presents the total
estimated costs for the final program. Note that all present value costs presented here are
2006 through 2040 numbers (the net present values in 2006 of the stream of costs occurring
from 2006 through 2040, expressed in $2005).
5.6.1 Engineering Costs for Freshly Manufactured Engines
5.6.1.1 Fixed Engineering Costs
Engine fixed costs include costs for engine R&D, tooling, and certification. These
costs are discussed in detail in Section 5.2.1. The total estimated engine fixed costs are
summarized in Table 5-54. The table also includes net present values using both a three
percent and a seven percent discount rate.
Table 5-54 Summary of Engine-Related Fixed Costs for Freshly Manufactured Tier 4 Engines (SMillions,
2005 dollars)
Engine and Emission Control Research
Engine Tooling
Engine Certification
Total Engine Fixed Costs
Total Allocated to PM
Total Allocated to NOX+NMHC
Costs Incurred
$569
$41
$7
$618
$212
$406
2006-2040 NPV at 3%
$471
$33
$6
$509
$ 175
$335
2006-2040 NPV at 7%
$371
$24
$5
$399
$ 137
$263
Note: As explained in the text, we have attributed engine fixed costs to NOX+NMHC and PM control as
follows: engine research costs are split two-thirds to NOX+NMHC control and one-third to PM control; engine
tooling costs are split equally; engine certification costs are split equally except where new standards are
implemented in different years (e.g., for Tier 4 locomotive standards).
5.6.1.2 Variable Engineering Costs
Engine variable, or hardware, costs are discussed in detail in Section 5.2.2. For engine
variable costs, we have generated cost estimation equations as a function of engine
displacement (see Table 5-27). Using these equations, we have calculated the hardware costs
for freshly manufactured engines meeting the Tier 4 standards for each year through 2040.
We present those annual engine variable costs in Section 5.2.2. Table 5-55 shows the net
5-82
-------
Engineering Cost Estimates
present value of those annual costs using a three percent discount rate and a seven percent
discount rate.
Table 5-55 Summary of Engine-Related Variable Costs for Freshly Manufactured Tier 4 Engines
(SMillions, 2005 dollars)
Locomotive
Cl Marine
C2 Marine
Small Commercial Marine & Recreational Marine
Total Engine Variable Costs
Total Allocated to PM
Total Allocated to NOX+NMHC
2006-2040 NPV at 3%
$840
$ 188
$227
$0
$ 1,255
$662
$593
2006-2040 NPV at 7%
$386
$86
$103
$0
$575
$303
$271
Note: The PM/NOX+NMHC cost allocations for engine variable costs are as follows: SCR systems including
marinization costs on marine applications are attributed 100% to NOX+NMHC control; and, DPF systems
including marinization costs on marine applications are attributed 100% to PM control.
5.6.2 Engineering Costs for Freshly Manufactured Equipment
5.6.2.1 Fixed Engineering Costs
Equipment fixed costs are discussed in detail in Section 5.3.1. Table 5-56 shows the
estimated equipment fixed costsfor redesign effortsassociated with the Tier 4 program.
The table also includes net present values of the annual costs using both a three percent and a
seven percent discount rate.
Table 5-56 Summary of Equipment-Related Fixed Costs for Freshly Manufactured Tier 4 Equipment
(SMillions, 2005 dollars)
Locomotive
Cl Marine
C2 Marine
Small Commercial Marine & Recreational
Marine
Total Equipment Fixed Costs
Total Allocated to PM
Total Allocated to NOX+NMHC
Costs
Incurred
$0.7
$40
$23
$0
$64
$32
$32
2006-2040 NPV at
3%
$0.5
$25
$ 14
$0
$39
$20
$20
2006-2040 NPV at
7%
$0.4
$14
$8
$0
$22
$11
$ 11
Note: Equipment fixed costs are split evenly between NOX+NMHC and PM control.
5-83
-------
Regulatory Impact Analysis
5.6.2.2 Variable Engineering Costs
Equipment variable costs are discussed in detail in Section 5.3.2. Using the costs
presented there we have calculated the hardware costs for new pieces of equipment
locomotives and vesselsmeeting the new Tier 4 standards for each year through 2040. We
present those annual equipment variable costs in Section 5.3.2. Table 5-57 shows the net
present value of those annual costs using a three percent and a seven percent discount rate.
Table 5-57 Summary of Equipment-Related Variable Costs for Freshly Manufactured Tier 4 Equipment
(SMillions, 2005 dollars)
Locomotive
Cl Marine
C2 Marine
Small Commercial Marine & RecMarine
Total Equipment Variable Costs
Total Allocated to PM
Total Allocated to NOX+NMHC
2006-2040 NPV at 3%
$171
$38
$ 11
$0
$220
$110
$ 110
2006-2040 NPV at 7%
$78
$ 17
$5
$0
$ 100
$50
$50
Note: Equipment variable costs are split evenly between NOX+NMHC and PM control.
5.6.3 Operating Costs for Freshly Manufactured Tier 4 Engines
Operating costs are discussed in detail in Section 5.4 where we present the operating
costs for each year through 2040. Operating costs consist of costs associated with urea use,
DPF maintenance, and a fuel consumption impact on some engines. Table 5-58 shows the net
present value of those annual operating costs using a three percent and a seven percent
discount rate.
Table 5-58 Summary of Operating Costs for Freshly Manufactured Tier 4 Engines (SMillions, 2005
dollars)
Locomotive
Cl Marine
C2 Marine
Small
Commercial
Marine &
RecMarine
Total
Operating
Costs
Total
Allocated to
PM
Total
2006-2040 NPV at 3%
Reductant
$2,241
$826
$964
$0
$4,031
$0
$4,031
DPF
Maint.
$42
$15
$18
$0
$75
$75
$0
Fuel
$633
$242
$282
$0
$1,157
$579
$579
Total
$2,916
$1,083
$1,265
$0
$5,264
$654
$4,610
2006-2040 NPV at 7%
Reductant
$866
$322
$387
$0
$1,575
$0
$1,575
DPF
Maint.
$16
$6
$7
$0
$29
$29
$0
Fuel
$246
$94
$113
$0
$453
$227
$227
Total
$1,128
$422
$507
$0
$2,057
$256
$1,801
5-84
-------
Engineering Cost Estimates
Allocated to
NOX+NMHC
Note: Operating costs are attributed as follows: costs associated with reductant use are attributed solely to
NOX+NMHC control; costs associated with DPF maintenance are attributed solely to PM control; and, costs
associated with the fuel consumption impact are split evenly between NOX+NMHC and PM control.
5.6.4 Engineering Hardware and Operating Costs for Remanufactured Engines
Costs associated with the locomotive and marine remanufacturing programs are
discussed in detail in Section 5.5 where we present the costs for each year through 2040.
These costs include the hardware costs that are incremental to current remanufacturing
practices and any increased operating costs. Table 5-59 shows the net present value of those
annual remanufacturing costs using a three percent and a seven percent discount rate.
Table 5-59 Summary of Remanufacturing Program Costs (SMillions, 2005 dollars)
Line Haul
Switcher & Passenger
Cl Marine
C2 Marine
Total Remanufacturing Costs
Total Allocated to PM
Total Allocated to NOX+NMHC
2006-2040 NPV at 3%
$ 1,512
$157
$21
$429
$2,120
$ 1,060
$ 1,060
2006-2040 NPV at 7%
$775
$90
$ 15
$274
$1,153
$577
$577
Note: Costs associated with the locomotive and marine remanufacturing programs are split evenly between
NOX+NMHC and PM control.
5.6.5 Total Engineering and Operating Costs Associated with the Final Program
Table 5-60 shows the total annual costs for each market segmentlocomotive line
haul, C2 marine, etcfor the final program. Table 5-61 shows the total annual costs for each
cost elementengine, equipment, operating, etc.on an annual basis for the final program.
As shown, the net present value of the annual costs is estimated at $9.4 billion at a three
percent discount rate and $4.3 billion at a seven percent discount rate. In the year 2030, the
annual costs are estimated at $759 million.
Note that costs throughout this cost analysis have been allocated as follows: engine
research costs are split two-thirds to NOX+NMHC control and one-third to PM control; engine
tooling costs are split equally; engine certification costs are split equally except where new
standards are implemented in different years (e.g., for Tier 4 locomotive standards); SCR
systems including marinization costs on marine applications are attributed 100% to
NOX+NMHC control; DPF systems including marinization costs on marine applications are
5-85
-------
Regulatory Impact Analysis
attributed 100% to PM control; equipment fixed and variable costs are split evenly between
NOX+NMHC and PM control; costs associated with reductant use are attributed solely to
NOX+NMHC control; costs associated with DPF maintenance are attributed solely to PM
control; costs associated with the fuel consumption impact are split evenly between
NOX+NMHC and PM control; and, costs associated with the locomotive remanufacturing
program are split evenly between NOX+NMHC and PM control.
Table 5-60 Estimated Annual Engineering Costs by Market Segment for the Final Program (SMillions,
2005 dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat
7%
NPVat
3%
Locomotive
Line Haul owitcner &
Passenger
$6.0
$2.6
$64.1 | $3.7
$35.4
$5.5
$80.6 $20.8
$134.6
$22.9
$107.0 $18.4
$98.6 | $18.4
$80.5
$22.9
$123.7 I $13.9
$171.8
$15.1
$161.7 I $11.7
$180.7
$12.3
$192.0 | $13.0
$184.8 I $13.6
$204.8 | $13.5
$245.4
$14.2
$310.8 | $17.3
$317.2
$18.7
$340.7 $21.2
$345.4
$22.6
$365.4 $24.1
$399.4
$419.5
$25.5
$26.9
$436.9 I $28.5
$455.7
$30.3
$465.2 I $31.5
$542.2
$34.5
$569.2 | $36.7
$594.3
$38.6
$601.6 | $40.2
$618.5 I $42.0
$634.8 | $43.6
$651.1
$45.0
$666.5 | $46.7
$2,393.9 | $209.3
$5,364.1 $420.7
Marine
C1 C1
.. . Marine Marine Recreational ma
Marine >60okW <600kW commercial
$4.2 i $2.3 $10.9 $5.8 $1.7
$20.1 ' $2.3 $10.9 $5.8 $1.7
$25.4 i $2.3 $10.9 $5.8 $1.7
$30.7 $2.3 $10.9 $5.8 $1.7
$61.3 i $31.0 $16.2 $10.9 $3.7
$59.9 $30.2 $0.0 $0.0 $0.0
$64.0 j $29.6 $0.0 $0.0 $0.0
$72.6 $28.4 $0.0 $0.0 $0.0
$83.0 ' $44.8 ' $0.2 ' $0.0 ' $0.0
$76.6 $31.3 $0.0 $0.0 $0.0
$81.7 ' $34.4 ' $0.0 ' $0.0 ' $0.0
$82.7 ! $37.7 ! $0.0 $0.0 I $0.0
$88.8 $46.3 $0.0 $0.0 $0.0
$94.8 ! $55.5 ! $0.0 ' $0.0 ! $0.0
$100.8 $64.8 $0.0 $0.0 $0.0
$106.8 | $74.0 I $0.0 I $0.0 ; $0.0
$112.8 ' $83.1 ' $0.0 ' $0.0 ' $0.0
$118.8 | $92.0 I $0.0 | $0.0 [ $0.0
$124.8 $100.9 $0.0 $0.0 $0.0
$130.8 i $109.5 i $0.0 '. $0.0 i $0.0
$136.7 $118.0 $0.0 $0.0 $0.0
$142.7 i $126.1 i $0.0 ', $0.0 i $0.0
$148.6 $133.3 $0.0 $0.0 $0.0
$154.6 j $139.0 j $0.0 i $0.0 i $0.0
$160.4 $143.6 $0.0 $0.0 $0.0
$166.2 ' $147.4 ' $0.0 ' $0.0 ' $0.0
$171.9 ; $150.8 ; $0.0 ; $0.0 ; $0.0
$176.6 ' $152.5 ' $0.0 ' $0.0 ' $0.0
$182.1 : $155.3 : $0.0 $0.0 ' $0.0
$187.4 $157.8 $0.0 $0.0 $0.0
$191.8 : $160.2 : $0.0 : $0.0 : $0.0
$195.4 $162.4 $0.0 $0.0 $0.0
$198.7 | $164.5 I $0.0 | $0.0 I $0.0
$201.9 ' $166.5 ' $0.0 ' $0.0 ' $0.0
$984.7 $639.5 $45.4 $25.7 $8.0
$2,061.2 $1,468.2 $53.0 $30.2 $9.4
Total
$33.5
$108.7
$87.1
$152.9
$280.7
$215.4
$210.5
$204.5
$265.7
$294.8
$289.4
$313.4
$340.0
$348.8
$383.9
$440.3
$524.0
$546.8
$587.5
$608.4
$644.2
$693.8
$728.3
$759.1
$790.0
$810.3
$899.4
$934.9
$970.3
$987.1
$1,012.6
$1 ,036.2
$1 ,059.3
$1,081.5
$4,306.5
$9,406.8
5-86
-------
Engineering Cost Estimates
Table 5-61 Estimated Annual Engineering Costs by Cost Element for the Final Program (SMillions, 2005
dollars)
Calendar
Year
2006
2007
2008
2009
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
NPVat7%
NPVat3%
Tier 4 Tier 4 Reman Tier 4
Engine Equipment Program Operating
Costs Costs Costs Costs
$33.5 '
$33.5 ! i $75.2 !
$33.5 ' ' $53.5
$68.2 ] ! $84.7 i
$137.9 $142.8
$80.4 i i $135.1 i
$80.4 $130.2
$87.6 : $0.7 ; $108.4 : $7.7
$123.1 $23.9 $88.6 $30.1
$99.6 ' $21.9 ' $116.3 ' $57.0
$86.4 $17.4 $98.5 $87.1
$78.9 ' $15.9 ' $98.5 ' $120.2
$80.4 ! $16.2 ! $89.8 ! $153.5
$82.3 $16.6 $62.5 $187.3
$84.3 ! $16.9 ! $61.1 '' $221.6
$86.1 $17.2 $80.7 $256.3
$88.7 | $18.0 | $125.6 ] $291.6
$90.1 ' $18.4 ' $111.4 $326.9
$92.2 | $18.9 | $114.1 | $362.3
$93.7 $19.2 $97.8 $397.7
$95.4 i $19.6 I $96.2 i $433.0
$96.7 $19.9 $109.1 $468.1
$97.9 \ $20.1 i $108.2 i $502.1
$98.9 $20.3 $105.2 $534.6
$100.2 i $20.7 ! $103.1 ! $565.9
$101.6 $21.0 $91.2 $596.5
$102.9 ' $21.2 ' $148.6 ' $626.7
$104.2 ; $19.0 ; $155.4 ; $656.4
$104.8 ' $19.1 ' $161.1 ' $685.4
$103.1 i $18.7 i $152.3 i $713.0
$102.0 $18.4 $153.7 $738.5
$100.7 j $18.1 j $155.4 I $762.1
$99.1 $17.7 $157.9 $784.6
$97.5 ! $17.4 : $160.6 ! $806.1
$973.8 $122.0 $1,153.4 $2,057.2
$1,764.1 | $259.5 | $2,119.5 | $5,263.7
Total PM NOX+NMHC
$33.5 | $11.1 | $22.5
$108.7
$48.7
$60.1
$87.1 | $37.8 | $49.2
$152.9
$64.9
$88.0
$280.7 $121.0 $159.7
$215.4
$94.1
$121.4
$210.5 $91.6 $118.9
$204.5 | $85.7 | $118.8
$265.7
$115.7
$150.0
$294.8 | $128.7 [ $166.1
$289.4
$114.3
$175.1
$313.4 | $113.8 | $199.7
$340.0
$114.6
$225.4
$348.8 | $106.4 | $242.4
$383.9 I $111.2 I $272.7
$440.3 | $126.4 | $313.9
$524.0
$155.1
$368.9
$546.8 | $153.3 [ $393.5
$587.5
$160.4
$427.1
$608.4 $157.6 $450.8
$644.2
$162.2
$481 .9
$693.8 $173.8 $519.9
$728.3
$759.1
$178.3
$181.4
$550.0
$577.6
$790.0 | $185.1 | $604.8
$810.3
$183.8
$626.5
$899.4 | $217.0 | $682.5
$934.9
$223.5
$711.4
$970.3 I $230.2 I $740.1
$987.1 I $228.1 I $759.0
$1,012.6 | $231.1 | $781.5
$1 ,036.2
$233.9
$802.4
$1,059.3 | $236.8 | $822.5
$1,081.5
$239.7
$841 .9
$4,306.5 I $1,333.4 I $2,973.1
$9,406.8
$2,680.0
$6,726.8
5-87
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Regulatory Impact Analysis
5.7 Engineering Costs and Savings Associated with Idle Reduction
Technology
Locomotives idle for many reasons, not all of which can be avoided. The primary
reason they idle is to protect their engines. Locomotives use water, rather than antifreeze for
engine cooling because water is more efficient at removing heat despite its higher freezing
point. Therefore, by keeping the locomotive engine idling, the cooling water is kept from
freezing and damaging the engine block. Engineers may also idle a locomotive to maintain
critical system parameters: the batteries must maintain a certain charge in order to be able to
restart the engine, the air brake system must be kept pressurized, and in some cases the
locomotive is left to idle in order to properly cool down after heavy use. It may also be
necessary to idle a locomotive to provide and maintain cab comfort for the crew or to
otherwise comply with applicable government regulations.. Idling locomotives can be found
both inside and outside of the switchyard, for example, line-hauls may idle while waiting on
sidings for other trains to pass, during crew changes, or while moving (when some
locomotives in a consist pulling a train are not needed to provide power).
There are several technologies currently available to reduce unnecessary locomotive
idling or idling emissions. First, shore power systems allow for the locomotive engine to be
plugged into a stationary power source to keep the batteries charged, and to heat and circulate
the water and oil. They range in price from $4,000 - $14,000 depending on the options
installed.M These systems are most widely used on passenger trains that return to the same
location at night, but are not always practical for switchers that idle in different locations
throughout a switchyard, or for line-hauls that generally stop in many locations outside a
switchyard. Second, Low Emission Idle Systems (LEI) made by Energy Conversions Inc.
work by alternating the banks of cylinders that fire during idle. LEI runs the engine on half of
its cylinders at idle which increases the load on the firing cylinders and causes them to burn
fuel more efficiently, however, while this system may reduce some idling emissions it does
not eliminate idling. The cost of the system is approximately $4000, and it can be installed in
just two hours.N Third, an Auxiliary Power Unit (APU) is an idle reduction technology that
reduces the amount of time when locomotive engine idling is necessary. APUs are small (less
than 50 hp) diesel engines that stop and start themselves as needed to provide heat to both
engine coolant and engine oil, and power to charge the batteries and run cab accessories,
instead of this work being done by the much larger (2,000-4,000 hp) locomotive engine.
There are two main manufacturers of APUs, EcoTrans which makes the K9 APU and Kim
Hotstart which makes the Diesel Driven Heating System (DDKS). APUs can provide
substantial fuel savings depending on a number of variables, such as: what the function of a
locomotive is (e.g. a switcher or a line-haul), where it operates (i.e. geographical area), and
what its operating characteristics are (e.g. number of hours per day that it operates). The cost
of an APU ranges from $25,000 - $32,000, depending on the options installed, although Kim
Hotstart has just developed a "Junior" model with a smaller engine that is priced around
M Docket ID # OAR-2003-0190-0588.1
N www.energyconversions.com/leil .htm
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Engineering Cost Estimates
$16,000.1;ฐ Fourth, a more complex solution has been demonstrated by the Advanced
Locomotive Emissions Control Systems (ALECS). It uses emission reduction technology
developed for stationary sources to capture the emissions from both stationary and slow
moving trains in a railyard. Its cost can be upwards of one million dollars, but it can be used
on any locomotive that enters the railyard.P Fifth, locomotive engines can be replaced with
two or three smaller non-road engines, referred to as gensets.Q This configuration allows the
locomotive to idle using only one small engine, while the other engines only operate when
more power is needed. Sixth, a hybrid-electric system has been designed for switch yard
purposes only (known as the GreenGoat.)R The hybrid-electric switcher engine only operates
when the batteries need to be charged. The locomotive is powered by the batteries and can sit
in a state of readiness without idling, similar to an electric car.
Finally, one of the most cost effective onboard solutions that can provide idle
reduction benefits to both line-haul and switcher locomotives nearly anywhere they operate is
an automatic engine stop/start system (AESS). AESS is an electronic control system that
reduces idling by shutting down a locomotive engine when it is idling unnecessarily e.g. it is
not needed to maintain critical system parameters such as brake system pressure. AESS is a
microprocessor technology that operates by continually monitoring certain operating
parameters such as: reverser and throttle position, engine coolant and ambient air temperature,
battery charge, brake system pressure, and time spent idling. The AESS will shutdown the
locomotive engine after a prescribed period of time spent idling, usually fifteen to thirty
minutes, if conditions meet a preprogrammed set of values (for example the ambient
temperature must be greater than 32ฐF, and the water temperature must be greater than 100ฐF),
and will restart the engine if one of the aforementioned parameters goes out of its specified
range in order to both protect the locomotive engine and keep it in a ready-to-use state.
AESS is limited in its ability to provide idle reduction in cold weather as it can only
monitor the conditions under which the locomotive engine is operating and the condition of
the engine itself. An APU can provide further reductions for those locomotives operating in
colder climates by actually maintaining the necessary engine parameters, and is included as
part of some Tier 0 certified kits. In fact, EPA demonstrated an APU/AESS combined
systems approach in one of its grant projects using a Kim Hotstart DDHS.S An AESS alone
can provide some fuel savings during the cold winter, but when combined with an APU will
achieve considerable fuel savings. AESS systems will be required on all freshly
manufactured Tier 3 and Tier 4 locomotives, and on all existing locomotives when they are
0 http://www.epa.gov/otaq/smartway/idlingtechnologies.htm#loco-mobile-apu
p Tom Christofk, "Statewide Railyard Agreement" Presentation given at Second Public Meeting 7/13/06 for
Placer County Air Pollution Control District
htttp://www.placer.ca.gov/upload/apc/documents/up/up_arb_public_meeting_7_13_06.pdf
Q www.northeastdiesel.org. "Multi-Engine GenSet Ultra Low Emissions Road-Switcher Locomotive"
presentation by National Railway Equipment Co., Jan, 2006.
R www.railpower.com
s See "Case Study: Chicago Locomotive Idle Reduction Project" (EPA420-R-04-003) (March, 2004), available
at http://www.epa.gov/smartway/documents/420r04003 .pdf
5-89
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Regulatory Impact Analysis
first remanufactured under the revised remanufacturing program (see section III.B.(l)(c) of
the Preamble for more details on the idle reduction program).
If installed at the time of remanufacture, the AESS installation costs vary depending
on the age and characteristics of the locomotive. On average, the cost of a basic system is
approximately $10,000, and in some cases volume discounts may be available.M'T This cost
estimate includes $2,500 in labor costs for installation, and $7,500 for the hardware costs for a
basic AESS microprocessor system and monitoring equipment (systems including GPS or
satellite uplink optional features are more expensive).0'1 The cost may also vary depending
on whether the locomotive is already equipped with the necessary sensors, and whether the
AESS would require a stand alone electronic control unit as may be the case for older
locomotives that are completely mechanical and do not have electronic controls. If installed
on a new locomotive, costs should be much lower since the equipment could be installed at
the factory and integrated with the original design of the locomotive.
Idle reduction technology (e.g., AESS systems) can provide substantial emission
reductions as well as cost savings by reducing fuel consumption. We estimated these cost
savings for both a line-haul and switcher locomotive using 4,350 annual hours of operation
for a line-haul or 36,500 hours over one useful life, and 4,450 annual hours for a switcher or
101,000 hours over one useful life (see section 3.3.2 of this RIA for more details on the useful
life of locomotives). The regulatory duty cycle (see 40CFR 92.132) indicates that a line-haul
locomotive idles 38% of its operating time, and that a switcher locomotive idles 59.8% of its
operating time. Using these values, we can estimate that a line-haul locomotive idles
approximately 1,650 hours annually or nearly 14,000 hours over one useful life, and a
switcher locomotive idles approximately 2,660 hours annually or slightly over 60,000 hours
over one useful life (cost and emission savings estimates used the net present value of these
idle hour values).
These duty cycles include two types of idling: normal idle and low idle. Low idle
indicates that there is no accessory load on the engine where normal idle indicates a load on
the engine (for example, an accessory load occurs when the locomotive engine is charging a
battery). As a conservative estimate, we are calculating that AESS provides a 50% reduction
in low idling, although additional reductions in both low and normal idling may be
possible11'v'w. Using this reduction value, we have estimated that AESS will reduce
unnecessary idling by over 410 hours a year on a line-haul locomotive, and approximately
660 hours a year on a switcher locomotive. This means that over the useful life of a line-haul
locomotive, we expect at least 2,900 hours of idling at a 3% net present value (2,500 at 7%
T Jessica Montanez and Matthew Mahler, "Reducing Idling Locomotives Emissions", North Carolina
Department of Environment and Natural Resources, DAQ http://daq.state.nc.us/planning/locoindex.shtml
u David E. Brann, "Locomotive Idling Reduction",
http://wwwl.eere.energy.gov/vehiclesandfuels/pdfs/idling_2004/brann.pdf
v http://www.arb.ca. gov/railyard/ryagreement/aess_electromotive.pdf
w Draft Maryland Locomotive Idle Reduction Program Demonstration Project - DE-FG36-02GO12022
http://www.osti.gov/bridge/servlets/purl/838872-D6MxUD/838872.PDF
5-90
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Engineering Cost Estimates
net present value) to have been eliminated, and at least 11,000 hours of idling at a 3% net
present value (7,400 hours at 7% net present value) over the course of one useful life for a
switcher locomotive.
Using a fuel consumption value of three gallons per hour idled from Tier 2
Certification data, a cost value of $1.57 per gallon of diesel fuel (see section 5.4.3 for
information on how this cost was derived) and the yearly amount of idle hours avoided, we
can estimate that this technology will pay for itself in just over three years on a switcher
locomotive, and slightly over five years on a line-haul locomotive. It is important to note that
locomotives typically operate for more than one useful life, and this technology does not have
to be replaced upon remanufacture of the locomotive and therefore, it should continue to
provide savings throughout the additional useful lives of that locomotive. It is also important
to note that our estimates are conservative when compared to estimates by other groups, and
when compared to data from locomotives equipped with AESS in the field. For comparative
purposes, Table 5-62 shows the different payback times associated with the different savings
estimates. Data from locomotives in the field indicate that this technology will pay for itself
in eight months. That figure is derived from data that has been collected from a large number
of locomotives, over many years of operation, in several different geographical regions of the
country, and averaged separately for both line-haul and switcher locomotives.
Table 5-62 Estimates of Typical AESS Payback Time by other Sources (monetary entries in 2005
dollars)
Source of Estimate
RIA for this rule
DOE
SmartStart Reports
Hours of
Idle per
switcher
locomotive
per year
2,650
5,300
3,840a
AESS
reduced
hours of
idle
665
2,650
2,050
Fuel
Usage
during
idle
(gal/hour)
3d
4.5
4.5
Gallons
Saved
per
Year
2,000
12,000
9,200
Cost
of
Fuel6
$1.57
$1.57
$1.57
Fuel
Savings
($)
$3,120
$18,800
$14,400
Payback
time of
AESSC
3.2 years
6 months
8 months
Notes:
locomotives
The $1.57 cost of a gallon of diesel is calculated in Chapter 5 of this RIA
c Payback time of AESS is based on average price of $10,000 which includes installation costs
3 gal/hr is based on Tier 2 Certification Data
For simplicity we are presenting savings and emission reductions for a single useful
life, even though locomotives are typically remanufactured at least three times before being
scrapped. The AESS hardware would generally be expected to last for the remainder of a
x These values have changed since the NPRM due to the increase estimate in the price of diesel fuel, see section
5.4.3 of this chapter for more information.
5-91
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Regulatory Impact Analysis
locomotive's service life, which could be as little as one useful life for a very old locomotive
being remanufactured for the last time, to more than four useful lives for a freshly
manufactured locomotive. Thus actual cost savings will be significantly higher than the
single useful life values presented here, even when discounted.
It is also important to note that while we present annual and per-useful life emission
reductions in this analysis, in Table 5-63, and in Table -5-64, these reductions are not
aggregated into our final program as part of the emission reductions from the finalized
program. In the past and in this recently finalized program, locomotives are tested and
emissions are calculated to reflect the emission reductions associated with idle reduction
technologies. AESS systems are currently being used by some manufacturers and
remanufacturers as part of their certified locomotive emission controls. From both a
regulatory and inventory perspective, the use of AESS is considered the same as installing
aftertreatment or recalibrating the engine. The emission reductions are presented here merely
to show the environmental significance of AESS.
Reduced idling time means reduced fuel consumption. Tier 2 certification data
indicates that modern locomotives typically burn 3 gallons of fuel an hour during low-idle.
We estimated the cost savings of using an AESS based on an estimated diesel fuel cost (less
taxes) of $1.57/gallon. For a line-haul locomotive, use of an AESS is estimated to provide
fuel cost savings of almost $1,900 annually. Over the useful life, this would mean a net
present value savings of nearly $13,700 at a three percent discount rate ($11,600 at a seven
percent discount rate). For a switcher locomotive, an AESS could provide fuel savings of
nearly $3,100 annually or, over its useful life, a net present value savings of approximately
$50,000 at a three percent discount rate ($35,000 at a seven percent discount rate).
Reduced idling time also means reducing idle emissions. Tier 2 certification data
suggests that locomotives emit an average of lOg/hr of PM and 600g/hr of NOX during low
idle. This means that a line-haul locomotive's emissions could be reduced by over 0.005 tons
of PM and 0.27 tons of NOX annually. Over the useful life, the net present value of PM
reductions could be 0.032 tons at a three percent discount rate (0.027 tons at a seven percent
discount rate). Likewise, the net present value of NOX reductions could be 1.9 tons at a three
percent discount rate (1.5 tons at a seven percent discount rate). A switcher locomotive's
emissions can be reduced by over 0.007 tons of PM and 0.44 tons NOX annually. Over the
useful life of the switcher, the net present value of PM reductions could be 0.12 tons at a three
percent discount rate (0.08 tons at a seven percent discount rate) and, for NOX reductions, 7.0
tons at a three percent discount rate (4.9 tons at a seven percent discount rate), older switchers
would be expected to emit more pollutants than the Tier 2 estimates given here.
Table 5-63 shows the annual fuel savings, the associated cost savings, and the
emissions reductions we estimate would result from the AESS requirements. These values
would be expected to be consistent for newer locomotives, although older locomotives may
provide greater savings as they may consume more fuel at idle. Table -5-64 shows this
information on a useful life basis along with net present value information and a net cost. The
idle emission reductions are particularly important considering that we do not expect
aftertreatment technologies to reduce NOX emissions for extended periods of idle, and further,
we expect PM control to be reduced due to poor oxidation efficiency at idle. The ability of
5-92
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Engineering Cost Estimates
aftertreatment technologies to control emissions during idle operation is discussed in more
detail in Chapter 4 of this RIA. Because of the limitations of the aftertreatment technology at
idle, idle reduction via an AESS system is one of the best methods to ensure control of
emissions at idle.
Table 5-63 Annual Effects of Using AESS on Line-Haul and Switcher LocomotivesY (monetary entries in
2005 dollars)
Annual Estimates for a Typical Tier 2 Locomotive
Type of
Locomotive
Line-Haul
Switcher
Time
Spent
T 11- <2
Idling
(hrs)
1,650
2,650
Idling
Reduced
Using AESS6
(hrs)
413
663
Fuel
Savings'^
(gals)
1,238
1,988
Fuel
c d
Savings
($)
1,943
3,120
PM Emission
Reductions2
(tons)
0.005
0.007
NOX Emission
Reductions
(tons)
0.27
0.44
Notes:
Assuming 50% of low-idle is reduced by AESS
c Using 3 gallons of fuel burned per hour at low-idle (estimated from Tier 2 Certification Data)
Using diesel fuel price less taxes of $1.57/gallon (see section 5.4.3)
e Using PM estimate of lOg/hr emitted during low idle (estimated from Tier 2 Certification Data)
Using NOX estimate of 600g/hr emitted during low idle (estimated from Tier 2 Certification Data)
Y These values have changed since the NPRM due to the increase estimate in the cost of diesel fuel, see section
5.4.3 of this chapter for more information.
5-93
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Regulatory Impact Analysis
Table -5-64 NPV 3% & 7% Effects of Using AESS Over the First Useful Life on Line-Haul and Switcher
Locomotives2 (monetary entries in 2005 dollars)
Estimates Over the First" Useful Life of a Typical Tier 2 Locomotive
Type of
Locomotive
Line -Haul
NPV
Factor
NPV 3%
NPV 7%
Time
Spent
Idling
(his)
12,000
9,900
Idling
Reduced
Using
AESSC
(his)
2,900
2,500
Fuel
c d
Savings
(gals)
8,700
7,400
Fuel
Savings'3
($)
13,700
11,600
Average
Installation
Cost of
AESS($)f
10,000
10,000
Net
Savings
($)
3,700
1,600
PM
Emission
Reductions^
(tons)
0.032
0.027
NOX
Emission
Reductions
(tons)
1.9
1.6
Switcher
NPV 3%
NPV 7%
42,000
29,000
11,000
7,400
32,000
22,000
50,000
35,000
10,000
10,000
40,000
25,000
0.12
0.08
7.0
4.9
Notes:
consumption, and fuel savings over subsequent useful lives of a locomotive's full lifetime.
b Using 38% idling time for line-hauls and 59.8% for switchers from Duty-Cycle (see 40CFR 92.132)
c Assuming 50% of low-idle is reduced by AESS
Using 3 gallons of fuel burned per hour at low-idle (estimated from Tier 2 Certification Data)
e Using diesel fuel price less taxes of $1.57 gallon (see section 5.4.3)
Average cost assumes AESS was bought and paid for the first year of installation
g Using PM estimate of lOg/hr emitted during low idle (estimated from Tier 2 Certification Data)
Using NOX estimate of 600g/hr emitted during low idle (estimated from Tier 2 Certification Data)
Note that we have not included the costs and savings associated with AESS systems in
the overall cost analysis of the program summarized in Section 5.6. The primary reason for
this is the expectation that these systems would be in widespread use absent a requirement
from EPA, even in retrofit applications on existing locomotives. We did not believe it would
be appropriate to assume no one would employ these systems absent a requirement, nor did
we want to assume that everyone would absent a requirement. Further, as shown in Table -
5-64, a net savings is likely, which would in effect, reduce the overall cost of our final
program were we to include the costs and savings associated with AESS systems. Because of
the difficulty and uncertainty involved in estimating their use absent a requirement, and their
net effect of providing savings to users, we decided to present the costs and savings separately
from the overall program.
5.8 Analysis of Energy Effects
Under E.O. 13211, a "significant energy action" is any regulatory action that might
have a significant adverse effect on the supply, distribution, or use of energy. A significant
adverse effect is, along with several other factors, any outcome that could reduce crude oil
supply in excess of 10,000 barrels per day, reduce fuel production in excess of 4,000 barrels
z These values have changed since the NPRM due to the increase estimate in the price of diesel fuel, see section
5.4.3 of this chapter for more information.
5-94
-------
Engineering Cost Estimates
per day, or increase energy usage in excess of either of those thresholds. The final locomotive
and marine program is projected to have an impact on fuel usage in excess of one of these
thresholds.
Sections 5.4.3 and 5.5 of this RIA present our analysis of the increased costs
associated with fuel consumption impacts that would result from both the addition of diesel
particulate filters to some locomotive and marine engines, and the remanufacture of Tier 0
locomotive and C2 marine engines. Table 5-44 through Table 5-47 show the increased
number of gallons we have estimated would be consumed as a result of the final program.
Table 5-51 through Table 5-53 show the increased number of gallons we have estimated
would be consumed as a result of the remanufacturing programs. Using the metrics of 42
gallons of fuel per barrel of crude oil and 365 days in a year, the projected number of barrels
of oil per day can be calculated as shown in Table 5-65. As shown, in the year 2022, our
program is projected to result in excess of 4,000 barrels of oil per day in increased energy
usage. Note that the fuel consumption estimates shown in Table 5-65 do not reflect the
potential fuel savings associated with automatic engine stop/start (AESS) systems or other
idle reduction technologies. As discussed in section 5.7, such technologies can provide
significant fuel savings which could offset the increased fuel consumption estimates shown in
Table 5-65.
5-95
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Regulatory Impact Analysis
Table 5-65 Estimated Increase in Fuel Consumed in Million Gallons per Year and Average Barrels per
Day
Calendar
Year
2006
2007
2008
2009
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
Increase in Fuel Consumed
(Million gallons per year)
Tier 4 | Tier 4 | Locomotive
Locomotive I Marine I Reman
0 | 0 | 0
0 I 0 I 0
0 | 0 | 2
0
0
2
0 | 0 | 4
0
0
8
0 | 0 | 10
0
0
12
0 1 13
2
4
2
4
13
14
7 \ 6 | 16
9
8
16
11 I 10 I 15
14
13
14
16 I 15 I 12
19
17
11
22 | 20 | 10
24 I 22 I 9
27 | 24 | 8
30
26
7
32 | 29 | 6
35
31
5
38 33 5
40
43
46
48
35
36
38
39
4
3
3
2
51 I 41 I 2
54
42
1
56 I 43 I 1
59
44
1
61 I 45 I 0
63 I 46 I 0
65 I 46 I 0
Marine
Reman
0
0
3
6
10
13
16
20
22
21
20
19
18
17
16
16
15
14
13
12
11
10
9
9
8
7
6
5
5
4
3
3
2
2
2
Total
0
0
5
8
14
21
26
32
36
38
43
48
51
54
57
59
62
65
68
71
74
77
81
84
87
89
92
95
98
101
103
106
109
111
114
Barrels/day
0
0
305
523
894
1383
1717
2073
2335
2482
2781
3101
3315
3516
3695
3874
4060
4253
4449
4649
4851
5055
5260
5461
5653
5838
6020
6203
6382
6562
6740
6915
7086
7253
7416
5-96
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Engineering Cost Estimates
5.9 Cost Effectiveness
As discussed in Chapter 6, this rule is very cost beneficial, with social benefits far
outweighing social costs. However, this does not shed light on how cost effective this control
program is compared to other control programs at providing the expected emission reductions.
One tool that can be used to assess the value of the final program is the ratio of engineering costs
incurred per ton of emissions reduced and comparing that ratio to other control programs. As we
show in this section, the PM and NOx emissions reductions from the new locomotive and marine
diesel program compare favorablyin terms of cost effectivenessto other mobile source
control programs that have been or will soon be implemented. We note that the locomotive and
marine final rule builds upon the efforts undertaken by the engine manufacturing industry to
comply with our recent 2007/2010 heavy-duty highway and nonroad Tier 4 (NRT4)
rulemakings. As such, and as discussed at length in section 5.2.1 of this final RIA, much of the
research and development associated with diesel emission controls builds upon the work done to
comply with those earlier rules. This does not change the conclusion that the cost effectiveness
of the locomotive and marine standards compares favorably with other actions deemed
appropriate for society.
Table 5-66 shows the emissions reductions associated with the final locomotive and
marine program. These reductions are discussed in more detail in Chapter 3 of this final RIA.
Table 5-66 Estimated Emissions Reductions Associated with the Final Locomotive and Marine Program
(Short tons)
Year
2015
2020
2030
2040
NPVat3%
NPV at 7%
PM2.5
7,000
14,000
27,000
37,000
308,000
134,000
PMio"
8,000
15,000
27,000
38,000
318,000
139,000
NOX
161,000
371,000
795,000
1,144,000
8,757,000
3,708,000
NMHC
14,000
26,000
40,000
52,000
492,000
221,000
Note that, PIVh.s is estimated to be 97 percent of the more inclusive PMio emission inventory. In
Chapter 3 we generate and present PIVh.s inventories since recent research has determined that these
are of greater health concern. Similarly, NMHC is estimated to be 93 percent of the more inclusive
VOC emission inventory. Traditionally, we have used PMio and NMHC in our cost effectiveness
calculations. Since cost effectiveness is a means of comparing control measures to one another, we
use PMio and NMHC in our cost effectiveness calculations for comparisons to past control
measures.
Using the costs associated with PM and NOX control shown in Table 5-61 and the
emission reductions shown in Table 5-66, we can calculate the $/ton associated with the final
program. These are shown in Table 5-67. The resultant cost per ton numbers depend on how the
costs are allocated to each pollutant. We have allocated costs as closely as possible to the
pollutants for which they are incurred. These allocations are also discussed in detail in Section
5.6 of this final RIA.
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Regulatory Impact Analysis
Table 5-67 Final Program Aggregate Cost per Ton and Long-Term Annual Cost per Ton (2005 dollars)
Pollutant
NOX+NMHC
PM
2006 Thru 2040
Discounted Lifetime
Cost Per Ton At 3%
$730
$8,440
2006 Thru 2040
Discounted Lifetime
Cost Per Ton At 7%
$760
$9,620
Cost Per Ton In 2030
$690
$6,620
Cost Per Ton In 2040
$700
$6,360
The costs per ton shown in Table 5-67 for 2006 through 2040 use the net present value of
the annualized costs and emissions reductions associated with the program for the years 2006
through 2040. We have also calculated the costs per ton of emissions reduced in the years 2030
and 2040 using the annual costs and emissions reductions in those specific years. These numbers
are also shown in Table 5-67. All of the costs per ton include costs and emission reductions that
will occur from the locomotive and marine remanufacturing programs.
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Engineering Cost Estimates
REFERENCES
1 "Electronic Systems and EGR Costs for Nonroad Engines," Final Report, ICF Consulting, December, 2002,
Public Docket No. A-2001-28, Docket Item II-A-10.
2 "Aftertreatment Marinizing Costs for CI Engines <30 L/cyl," Final Report, ICF International, September 2006;
Docket ID Number EPA-HQ-OAR-2003-0190.
3 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
4 "Update of EPA's Motor Vehicle Emission Control Equipment Retail Price Equivalent (RPE) Calculation
Formula," Jack Faucett Associates, Report No. JACKFAU-85-322-3, September 1985, Public Docket No. A-
2001-28, Docket Item II-A-74.
5 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
6 "Learning Curves in Manufacturing," Linda Argote and Dennis Epple, Science, February 23, 1990, Vol. 247,
pp. 920-924.
7 Power Systems Research, OELink Sales Version, 2002.
8 Bureau of Labor Statistics at http://data.bls.gov. Producer Price Index for Total Manufacturing Industries,
series ID PCUOMFG--OMFG, shows an annual PPI value for 2005 of 150.8 versus a March 2004 value
(publication of the NRT4 rule) of 140.3 for a PPI adjustment of 1.075 (150.8/140.3).
9 "Learning Curves in Manufacturing," Linda Argote and Dennis Epple, Science, February 23, 1990, Vol. 247,
pp. 920-924.
10 "Treating Progress Functions As Managerial Opportunity", J.M Dutton and A. Thomas, Academy of
Management Review, Rev. 9, 235, 1984, Public Docket A-2001-28, Docket Item II-A-73.
11 Nonconformance Penalty Final Rule, 67 FR 51464, August 8, 2002.
12 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
13 "Estimated Economic Impact of New Emission Standards for Heavy-Duty On-Highway Engines," March
1997, EPA420-R-97-009, Public Docket A-2001-28, Docket Item II-A-136.
14 Estimates for Heavy-Duty Gasoline Vehicles," Arcadis Geraghty & Miller, September 1998, EPA Air Docket
A-2001-28, Docket Item II-A-77.
15 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
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Regulatory Impact Analysis
16 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
17 Nonconformance Penalty Final Rule, 67 FR 51464, August 8, 2002.
18 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
19 Bureau of Labor Statistics at http ://data.bls. gov. Producer Price Index for Total Manufacturing Industries,
series ID PCUOMFG--OMFG, shows an annual PPI value for 2005 of 150.8 versus a January 2000 value
(publication of the 2007 HD Highway rule) of 130.8 for a PPI adjustment of 1.153 (150.8/130.8).
20 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
21 Johnson Matthey, www.platinum.matthev.com.
22 "Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction of Diesel Fuel
Sulfur Content," Engine, Fuel, and Emissions Engineering, Incorporated, December 15, 1999, Public Docket No.
A-2001-28, Docket Item II-A-76.
23 "Aftertreatment Marinizing Costs for CI Engines <30 L/cyl," Final Report, ICF International, September
2006; Docket ID Number EPA-HQ-OAR-2003-0190.
24 "Aftertreatment Marinizing Costs for CI Engines <30 L/cyl," Final Report, ICF International, September
2006; Docket ID Number EPA-HQ-OAR-2003-0190.
25 "Marine Vessel Sales" Memorandum from John Mueller, Office of Transportation and Air Quality, to docket
EPA-HQ-OAR-2003-0190, February 28, 2007.
26 "Viability of Urea Infrastructure for SCR Systems," presented by M.D. Jackson, at the U.S. EPA Clean Diesel
Implementation Workshop, August 6, 2003.
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Cost-Benefit Analysis
CHAPTER 6: COST-BENEFIT ANALYSIS 6-2
6.1 Overview 6-2
6.2 Air Quality Impacts for Benefits Analysis 6-6
6.2.1 Converting CMAQ Outputs to Full-Season Profiles for Benefits Analysis 6-6
6.2.2 Ozone and PM2.5 Air Quality Results 6-7
6.3 Characterizing Uncertainty: Moving Toward a Probabilistic Framework for Benefits
Assessment 6-11
6.4 Health Impact Functions 6-13
6.4.1 Potentially Affected Populations 6-13
6.4.2 Effect Estimate Sources 6-13
6.4.3 Baseline Incidence Rates 6-31
6.5 Economic Values for Health Outcomes 6-33
6.5.1 Mortality Valuation 6-34
6.5.2 Hospital Admissions Valuation 6-34
6.5.3 Asthma-Related Emergency Room Visits Valuation 6-34
6.5.4 Minor Restricted Activity Days Valuation 6-35
6.5.5 School Absences 6-35
6.6 Benefits Analysis Results for the Final Standards 6-41
6.7 Comparison of Costs and Benefits 6-51
APPENDIX 6A: HEALTH-BASED COST EFFECTIVENESS ANALYSIS ..6-54
APPENDIX 6.B: SENSITIVITY ANALYSES OF KEY PARAMETERS IN THE
BENEFITS ANALYSIS 6-63
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Regulatory Impact Analysis
CHAPTER 6: Cost-Benefit Analysis
6.1 Overview
This chapter presents our analysis of the health and environmental benefits that are
estimated to occur as a result of the final locomotive and marine engine standards throughout
the period from initial implementation through 2030. Nationwide, the engines subject to the
final emission standards in this rule are a significant source of mobile source air pollution.
The final standards will reduce exposure to direct PM2.5, NOx and air toxics emissions and
help avoid a range of adverse health effects associated with ambient ozone and PM2.5 levels.
EPA is required by Executive Order (E.O.) 12866 to estimate the benefits and costs of
major new pollution control regulations. Accordingly, the analysis presented here attempts to
answer three questions: (1) what are the physical health and welfare effects of changes in
ambient air quality resulting from particulate matter (PM) and ozone precursor emission
reductions (direct PM and NOx)? (2) what is the monetary value of the changes in these
effects attributable to the final rule? and (3) how do the monetized benefits compare to the
costs? It constitutes one part of EPA's thorough examination of the relative merits of this
regulation.
The benefits analysis relies on three major components to answer these questions:
Calculation of the impact of the final rule on the national nonroad emissions inventory of
precursors to ozone and PM2.5, specifically NOx, and direct PM, for two future years
(2020 and 2030).
Air quality modeling for 2020 and 2030 to determine changes in ambient concentrations
of ozone and PM2.5, reflecting baseline and post-control emissions inventories.
A benefits analysis to determine the changes in human health and welfare, both in terms
of physical effects and monetary value, that result from the projected changes in ambient
concentrations of ozone and PM2.5 for the modeled standards.
A wide range of human health and welfare effects are linked to the emissions of direct
PM and NOx and the resulting impact on ambient concentrations of ozone and PM2 5. Recent
studies have linked short-term ozone exposures with premature mortality. Exposure to ozone
has also been linked to a variety of respiratory effects including hospital admissions and
illnesses resulting in school absences. Potential human health effects associated with PM2 5
range from premature mortality to morbidity effects linked to long-term (chronic) and shorter-
term (acute) exposures (e.g., respiratory and cardiovascular symptoms resulting in hospital
admissions, asthma exacerbations, and acute and chronic bronchitis). Welfare effects
6-2
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Cost-Benefit Analysis
potentially linked to PM include materials damage and visibility impacts, while ozone can
adversely affect the agricultural and forestry sectors by decreasing yields of crops and forests.
The benefits modeling 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. All of the benefit estimates for the
control options in this analysis are based on an analytical structure and sequence consistent
with benefits analyses performed for the recent analysis of the proposed Ozone NAAQS and
the final PM NAAQS analysis.1'2 For a more detailed discussion of the principles of benefits
analysis used here, we refer the reader to those documents, as well as to the EPA Guidelines
for Economic Analysis.
Table 6.1-1 summarizes the annual monetized health and welfare benefits associated
with the final standards for two years, 2020 and 2030. The estimates in Table 6.1-1, and all
monetized benefits presented in this chapter, are in year 2006 dollars. There are a few items
to note about these benefits:
Using the most conservative benefits estimate, the 2020 benefits outweigh the costs by a
factor of 10. Using the upper end of the benefits range, the benefits could outweigh the
costs by a factor of 25. Likewise, in 2030 benefits outweigh the costs by at least a factor
of 10 and could be as much as a factor of 28. Thus, even taking the most conservative
benefits assumptions, benefits of the final standards clearly outweigh the costs.
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 final emission control program. The differences reflect
further refinements of the regulatory program since we performed the air quality modeling
for this rule. Chapter 3 of the 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.
The RIA for the proposal for this rulemaking only quantified benefits from PM; in the
current RIA we quantify and monetize the ozone-related health and environmental
impacts associated with the final rule. The science underlying the analysis is based on the
current ozone criteria document.3 The analytic approach to characterizing uncertainty is
consistent with the analysis used in the RIA for the proposed O3 NAAQS.
The range of ozone benefits associated with the final standards is based on risk reductions
using several sources of ozone-related mortality effect estimates. There is considerable
uncertainty in the magnitude of the association between ozone and premature mortality.
This analysis presents four alternative estimates for the association based upon different
functions reported in the scientific literature. Recognizing that additional research is
necessary to clarify the underlying mechanisms causing these effects, we also consider the
possibility that the observed associations between ozone and mortality may not be causal
in nature.
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Regulatory Impact Analysis
For this analysis, we observed two urban areas that, to some degree, experience ozone
disbenefits related to NOx control: Southern California and the metropolitan Chicago
area.A Ozone disbenefits associated with NOx control typically occur during nighttime
and early morning hours, when NOx titrates ozone. Because human exposure to ozone is
a function of the temporal and spatial patterns of ambient concentrations of ozone in the
atmosphere, the ozone-related health impacts analysis is sensitive to which ozone
exposure metric we use in the health impact functions. For example, the 24-hour average
incorporates both nighttime and daytime hours, which means the decrease in ozone
titration caused by reduced NOx emissions can cause relatively large increases in 24-hour
average ozone. This is not the most relevant ozone exposure metric to characterize
population-level exposure given that the majority of the people tend to be outdoors during
the daylight hours. Furthermore, concentrations are highest during the daylight hours.
Together, this means that the most biologically relevant metric, and the one used in the
ozone NAAQS since 1997, is the 8-hour maximum standard. Thus, although
epidemiological studies often present their results in terms of 24-hour average ozone
levels, for the final rule analysis, we have converted health impact functions that use a 24-
hour average ozone metric to 8-hour maximum ozone concentration using standard
conversion functions.
A In areas prone to ozone disbenefits, our ability to draw conclusions based on air quality modeling conducted
for the final rule is limited. Marginal ozone changes in these areas are much more dependent upon baseline air
quality conditions than PM due to nonlinearities present in the chemistry of ozone formation. A marginal
decrease in NOx emissions modeled on its own in these areas, as was done for this analysis, may yield a very
different ambient ozone concentration than if it were modeled in combination with other planned or future
controls. This is because "yet-to-occur" emission reductions in these areas, associated with local controls and
other unknown measures, are not accounted for in our analytical approach. Within these regions, we expect that
the additional NOx reductions from SIP-based controls will lead to fewer ozone disbenefits from the marginal
changes modeled here.
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Cost-Benefit Analysis
Table 6.1-1. Estimated Monetized PM- and Ozone-Related Health Benefits of the Final
Locomotive and Marine Engine Standards
2030 Total Ozone and PM Benefits - PM Mortality Derived from American Cancer Society Analysis3
Premature Ozone
Mortality Function or
Assumption
NMMAPS
Meta-analysis
Reference
Bell etal., 2004
Bell et al., 2005
Ito et al., 2005
Levy etal., 2005
Assumption that association is not causal
Mean Total Benefits
(Billions, 2006$, 3%
Discount Rate)c'd
$9.7
$11
$11
$11
$9.2
Mean Total Benefits
(Billions, 2006$, 7%
Discount Rate) c'd
$8.9
$9.8
$10
$10
$8.4
2030 Total Ozone and PM Benefits - PM Mortality Derived from Expert Elicitationb
Premature Ozone
Mortality Function or
Assumption
NMMAPS
Meta-analysis
Reference
Bell etal., 2004
Bell et al., 2005
Ito et al., 2005
Levy etal., 2005
Assumption that association is not causal
Mean Total Benefits
(Billions, 2006$, 3%
Discount Rate) c'd
$5.2 to $37
$6.2 to $38
$6.7 to $39
$6.7 to $39
$4.7 to $37
Mean Total Benefits
(Billions, 2006$, 7%
Discount Rate) c'd
$4.8 to $34
$5.8 to $35
$6.3 to $35
$6.4 to $35
$4.4 to $33
a Total includes ozone and PM2 5 benefits. Range was developed by adding the estimate from the ozone
premature mortality function to the estimate of PM2 5-related premature mortality derived from the American
Cancer Society analysis (Pope et al., 2002).
b Total includes ozone and PM25 benefits. Range was developed by adding the estimate from the ozone
premature mortality function to both the lower and upper ends of the range of the PM2 5 premature mortality
functions characterized in the expert elicitation. The effect estimates of five of the twelve experts included in the
elicitation panel fall within the empirically-derived range provided by the ACS and Six-Cities studies. One of
the experts fall below this range and six of the experts are above this range. Although the overall range across
experts is summarized in this table, 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.
0 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 6.4-1.
d 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.
Table 6.1-1 reflects those human health and welfare effects we are able to quantify and
monetize. However, the full complement of human health and welfare effects associated with
PM, ozone and air toxics 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 acidification in lakes and streams and
eutrophication in coastal areas. As a result, we may underestimate the total benefits
attributable to the implementation of the final standards.
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Regulatory Impact Analysis
This chapter is organized as follows. In Section 6.2, we provide an overview of the air
quality impacts modeled for the final standards that are used as inputs to the benefits analysis.
In Section 6.3, we discuss how uncertainty is characterized in this analysis. Section 6.4
discusses the literature on ozone- and PM-related health effects and describes the specific set
of health impact functions we used in the benefits analysis. Section 6.5 describes the
economic values selected to estimate the dollar value of ozone- and PM-related health
impacts. In Section 6.6, we report the results of the analysis for human health and welfare
effects. Finally, Section 6.7 presents a comparison of the costs and benefits associated with
the final standards.
6.2 Air Quality Impacts for Benefits Analysis
In Chapter 2, we summarize the methods for and results of estimating air quality for
the 2020 and 2030 base case and final control scenario. These air quality results are in turn
associated with human populations and ecosystems to estimate changes in health and welfare
effects. For the purposes of the benefits 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 final standards. We estimate ambient PM2.5 and ozone concentrations
using the Community Multiscale Air Quality model (CMAQ). The air quality modeling
Technical Support Document (TSD), which can be found in the docket for this rule, contains
detailed information about the modeling conducted for this rule. In this section, we describe
how the modeled air quality results were used for the benefits analysis.
We remind the reader that the emission control scenarios used in the air quality and
benefits modeling are slightly different than the final emission control program. The
differences reflect further refinements of the regulatory program since we performed the air
quality modeling for this rule. Emissions and air quality modeling decisions are made early in
the analytical process. Chapter 3 of the 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.
6.2.1 Converting CMAQ Outputs to Full-Season Profiles for Benefits Analysis
This analysis 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
R r1
Retrieval System (AIRS) to generate ozone concentrations for the entire ozone season. '
B The ozone season for this analysis is defined as the 5-month period from May to September.
c Based on AIRS, there were 961 ozone monitors with sufficient data (i.e., 50 percent or more days reporting at
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Cost-Benefit Analysis
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., the Environmental Benefits Mapping and Analysis Program [BenMAP]).
To estimate ozone-related health and welfare 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.D'E
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 PM2.5 concentrations was
created by interpolating Federal Reference Monitor ambient data and IMPROVE ambient
data. Gridded fields of PM2.s 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.s 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 final emissions controls. Full documentation of the revised SMAT
methodology is contained in the Air Quality Modeling TSD.
6.2.2 Ozone and PM2.s Air Quality Results
This section provides a summary of the predicted ambient PM2.s and ozone
concentrations from the CMAQ model for the 2020 and 2030 base cases and changes
least nine hourly observations per day [8 am to 8 pm] during the ozone season).
D The 12-km grid squares contain the population data used in the health benefits analysis model, BenMAP.
E 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.
6-7
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Regulatory Impact Analysis
associated with the final rule. Table 6.2-1 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 6.2-1. Summary of CMAQ-Derived Population-Weighted Ozone and PM2.5 Air
Quality Metrics for Health Benefits Endpoints Due to the Final Locomotive and Marine
Engine Standards
Statistic3
2020
Baseline
Change"
2030
Baseline
Change"
Ozone Metrics: National Population- Weighted Average (ppb)ฐ
Daily 1 -Hour Maximum Concentration
Daily 8-Hour Maximum Concentration
Daily 8-Hour Average Concentration
Daily 24-Hour Average Concentration
49.13
42.89
41.71
28.16
0.060
0.033
0.031
-0.033
48.78
42.65
41.49
28.11
0.202
0.137
0.130
-0.039
PM2 5 Metrics: National Population- Weighted Average (ug/m3)
Annual Average Concentration
11.85
0.061
11.87
0.122
a Ozone and PM2 5 metrics are calculated at the CMAQ grid-cell level for use in health effects estimates
based on the results of spatial and temporal Voronoi Neighbor Averaging. Ozone metrics are calculated over
relevant time periods during the daylight hours of the "ozone season" (i.e., May through September). For the 8-
hour average, for example, the relevant time period is 9 am to 5 pm.
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.
6.2.2.1 Modeled Ozone-Related Disbenefits and Treatment in Benefits Analysis
While this rule will reduce ozone levels generally and provide national ozone-related
health benefits, as demonstrated in Table 6.2-1, this is not always the case at the local level.
Due to the complex photochemistry of ozone production, reductions in NOX emissions lead to
both the formation and destruction of ozone, depending on the relative quantities of NOX,
VOC, and ozone 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 can result from NOx emissions reductions in these localized areas. According to the
North American Research Strategy for Tropospheric Ozone (NARSTO) Ozone Assessment,
these disbenefits are generally limited to small regions within specific urban cores and are
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Cost-Benefit Analysis
surrounded by larger regions in which NOX control is beneficial.F For this analysis, we
observed two urban areas that experience ozone disbenefits: Southern California and, to a
lesser degree, the metropolitan Chicago area. Full documentation of these disbenefits is
contained in the Air Quality Modeling TSD, located in the docket for this rule.
Marginal changes in ozone in these areas are much more dependent upon baseline air
quality conditions than PM due to nonlinearities present in the chemistry of ozone formation.
A marginal decrease in NOx emissions modeled on its own in these areas, as was done for
this analysis, may yield a very different ambient ozone concentration than if it were modeled
in combination with other planned or future controls. For example, recent California SIP
modeling indicates that with a combined program of national and local controls, including the
final locomotive and marine controls, Southern California can reach ozone attainment by
2024 through a mixture of substantial NOx (and VOC) reductions.0
In areas prone to ozone disbenefits, such as Southern California, our ability to draw
conclusions based on air quality modeling conducted for the final rule is limited because the
yet-to-occur emission reductions in these areas are not accounted for in our analytical
approach. Within these regions, it is expected that the additional NOx reductions from SIP-
based controls would lead to fewer ozone disbenefits from the marginal changes modeled
here. The ozone benefits in these regions may therefore be underestimated.
EPA has been aware of the issue of ozone disbenefits for a number of years. We have
recognized the implications of this issue for cost-benefit analyses of mobile source strategies
in our recent rulemakings for heavy duty onroad and nonroad diesel engines. For example, in
the Nonroad Diesel rule RIA, we noted that "our ozone air quality modeling showed that the
NOx emissions reductions from the preliminary modeled standards are projected to result in
increases in ozone concentrations for certain hours during the year, especially in urban, NOx-
limited areas. Most of these increases are expected to occur during hours where ozone levels
are low (and often below the one-hour ozone standard)."
EPA has always incorporated ozone-related disbenefits into our estimates of total
benefits. In the Nonroad Diesel rule RIA, we provided this statement regarding disbenefits:
"Ozone benefits arising from this rule are in aggregate positive for the nation. However, due
to ozone increases occurring during certain hours of the day in some urban areas, in 2020 the
F The NARSTO Assessment Document synthesizes the scientific understanding of ozone pollution, giving
special consideration to behavior on expanded scales over the North American continent, encompassing Canada,
the United States, and Mexico. Successive drafts of this Assessment Document experienced progressive stages
of review by its authors and by outside peers, and transcripts were recorded containing the review comments and
the corresponding actions. This included an external review by the NRC, the comments of which were
addressed and incorporated in the final draft. NARSTO, 2000. An Assessment of Tropospheric Ozone Pollution
- A North American Perspective. NARSTO Management Office (Envair), Pasco, Washington, http://narsto.org/
G SCAQMD (2007). Final 2007 Air Quality Management Plan. Available at:
http://www.aqmd.gov/aqmp/07aqmp/index.html. Accessed November 8, 2007.
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net effect is an increase in ozone-related minor restricted activity days (MRAD), which are
related to changes in daily average ozone (which includes hours during which ozone levels
are low, but are increased relative to the baseline based on the preliminary modeling).
However, by 2030, there is a net decrease in ozone-related MRAD consistent with widespread
reductions in ozone concentrations from the increased NOx emissions reductions. Note that
in both years, the overall impact of changes in both PM and ozone is a large decrease in the
number of MRAD. Overall, ozone benefits are low relative to PM benefits for similar
endpoint categories because of the increases in ozone concentrations during some hours of
some days in certain urban areas."
The addition of ozone mortality to our health impacts analysis has led to an increased
focus on the issue of ozone disbenefits for two related reasons: (1) The monetized value of
ozone-related benefits, in terms of ozone's contribution to total rule-related benefits, has
increased due to the inclusion of ozone mortality; and (2) The overall ozone impacts of NOx
reductions in certain geographic regions of the U.S., when modeled on the margin, may be
negative.
Figure 1 shows the diurnal pattern of ozone concentrations in the 2030 baseline and
post-control scenarios for a grid cell in Orange County, CA during July. From this figure it is
clear that the disbenefits (points when the control case ozone levels are higher than the
baseline) are occurring primarily during nighttime hours when ozone is generally low.
This diurnal pattern means that the extent of the disbenefits is not as large as one
might have thought. Our conversion from using a 24-hour metric to using the maximum 8-
hour average metric in the ozone mortality studies (see page 6-4 and the health impacts
section) excludes the nighttime hours when NOx-related disbenefits are most likely to occur.
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Cost-Benefit Analysis
Monthly time-series of CMAQ 2030 base and control modeling for grid cell ( row 44, col 42)
75-i
7O-
65-
60-
55-
5O-
I45-,
$ 40-
x35"
I 30-
25-
20-
15-
1O-
5-
0-
Legend
- 2030 baseline
2030 control
12345
7 8
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 3O 31
Day of Month
Figure 1. July 2030 time-series of CMAQ base and control modeling for Orange County, CA
6.3 Characterizing Uncertainty: Moving Toward a Probabilistic
Framework for Benefits Assessment
The National Research Council (NRC)4 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.11 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. In
H 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.
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Regulatory Impact Analysis
addition, we characterize the uncertainty introduced by the inability of existing empirical
studies to discern whether the relationship between ozone and pre-mature mortality is causal
by providing an effect estimate preconditioned on an assumption that the effect estimate for
pre-mature mortality from ozone is zero.
For premature mortality associated with exposure to PM, we follow the same approach
that has been used in several recent RIAs.I:J'K 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 6.5-
1.
Second, we use the results of our expert elicitation of the concentration response
function describing the relationship between premature mortality and ambient PM2.5
concentration.1^ M Incorporating only the uncertainty from random sampling error omits
important sources of uncertainty (e.g., in the functional form of the model; whether or not a
threshold may exist). This second approach attempts to incorporate these other sources of
uncertainty.
Use of the expert elicitation and incorporation of the standard errors approaches
provide insights into the likelihood of different outcomes and about the state of knowledge
regarding the benefits estimates. Both approaches have different strengths and weaknesses,
which are fully described in Chapter 5 of the PM NAAQS RIA.
1 U.S. Environmental Protection Agency, 2004a. Final Regulatory Analysis: Control of Emissions from Nonroad
Diesel Engines. EPA420-R-04-007. Prepared by Office of Air and Radiation. Available at
http://www.epa.gov/nonroad-diesel/2004fr/420r04007.pdf
1 U.S. Environmental Protection Agency, 2005. Regulatory Impact Analysis for the Clean Air Interstate Rule.
EPA 452/-03 -001. Prepared by Office of Air and Radiation. Available at:
http://www.epa.gov/interstateairqualitv/tsd0175.pdf
K U.S. Environmental Protection Agency, 2006. Regulatory Impact Analysis for the PM NAAQS. EPA Prepared
by Office of Air and Radiation. Available at: http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--
Benefits.pdf
L Expert elicitation is a formal, highly structured and well documented process whereby expert judgments,
usually of multiple experts, are obtained (Ayyb, 2002).
M Industrial Economics, Inc. 2006. Expanded Expert Judgment Assessment of the Concentration-Response
Relationship Between PM2.5 Exposure and Mortality. Prepared for EPA Office of Air Quality Planning and
Standards, September. Available at: http://www.epa.gov/ttn/ecas/regdata/Uncertaintv/pm ee report.pdf
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Cost-Benefit Analysis
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.
6.4 Health Impact Functions
Health impact functions measure the change in a health endpoint of interest, such as
hospital admissions, for a given change in ambient ozone or PM concentration. Health impact
functions are derived from primary epidemiology studies, meta-analyses of multiple
epidemiology studies, or expert elicitations. A standard health impact function has four
components: 1) an effect estimate from a particular study; 2) a baseline incidence rate for the
health effect (obtained from either the epidemiology study or a source of public health
statistics such as the Centers for Disease Control); 3) the size of the potentially affected
population; and 4) the estimated change in the relevant ozone or PM summary measures.
A typical health impact function might look like:
where yo is the baseline incidence (the product of the baseline incidence rate times the
potentially affected population), 3 is the effect estimate, and )x is the estimated change in the
summary pollutant measure. There are other functional forms, but the basic elements remain
the same. Section 6.2 described the ozone and PM air quality inputs to the health impact
functions. The following subsections describe the sources for each of the other elements:
size of potentially affected populations; effect estimates; and baseline incidence rates.
6.4.1 Potentially Affected Populations
The starting point for estimating the size of potentially affected populations is the
2000 U.S. Census block level dataset.5 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.6
6.4.2 Effect Estimate Sources
The most significant monetized benefits of reducing ambient concentrations of ozone
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Regulatory Impact Analysis
and PM are attributable to reductions in human health risks. EPA's Ozone and PM Criteria
Documents7'8 and the World Health Organization's 2003 and 20049'10 reports outline
numerous health effects known or suspected to be linked to exposure to ambient ozone and
PM. EPA recently evaluated the PM literature for use in the benefits analysis for the 2006
PM NAAQS RIA. Because we used the same literature for the PM benefits analysis in this
RIA, and also in the RIA for the proposed rule, we do not provide a detailed discussion of
individual effect estimates for PM in this section. Instead, we refer the reader to the 2006 PM
NAAQS RIA and the proposed Locomotive and Marine RIA for details.N
The RIA for the proposal for this rulemaking only quantified benefits from PM; in the
current RIA we quantify and monetize the ozone-related health and environmental impacts
associated with the final rule using an approach consistent with the proposed ozone NAAQS
RIA. More than one thousand new ozone health and welfare studies have been published
since EPA issued the 8-hour ozone standard in 1997. Many of these studies investigated the
impact of ozone exposure on health effects such as: changes in lung structure and
biochemistry; lung inflammation; asthma exacerbation and causation; respiratory illness-
related school absence; hospital and emergency room visits for asthma and other respiratory
causes; and premature death. We provide a discussion of those ozone-related impacts in this
section. For a more detailed discussion of the health effects of ozone exposure, we point the
reader to EPA's ozone Criteria Document.u
It is important to note that we were not able to separately quantify all of the PM and
ozone health effects that have been reported in the ozone and PM criteria documents in this
analysis for four reasons: (1) the possibility of double counting (such as hospital admissions
for specific respiratory diseases); (2) uncertainties in applying effect relationships that are
based on clinical studies to the potentially affected population; (3) the lack of an established
concentration-response relationship; or 4) the inability to appropriately value the effect (for
example, changes in forced expiratory volume) in economic terms. Table 6.4-1 lists the
human health and welfare effects of pollutants affected by the alternate standards. Table 6.4-2
lists the health endpoints included in this analysis.
N U.S. Environmental Protection Agency, 2005. Regulatory Impact Analysis for the PM NAAQS. EPA Prepared
by Office of Air and Radiation. Available at: http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--
Benefits.pdf pp. 5-29.
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Table 6.4-1 Human Health and Welfare Effects of Pollutants Affected by the Final
Standards
Quantified and Monetized in Base
Pollutant/Effect
Estimates
Unqualified Effects - Changes in:
PM/Health
b
PM/Welfare
Ozone/Health
f
Premature mortality based on both
cohort study estimates and on expert
elicitationc'
Bronchitis: chronic and acute
Hospital admissions: respiratory
and cardiovascular
Emergency room visits for asthma
Nonfatal heart attacks (myocardial
infarction)
Lower and upper respiratory illness
Minor restricted-activity days
Work loss days
Asthma exacerbations (asthmatic
population)
Respiratory symptoms (asthmatic
population)
Infant mortality
Premature mortality: short-term
exposures
Hospital admissions: respiratory
Emergency room visits for asthma
Minor restricted-activity days
School loss days
Asthma attacks
Acute respiratory symptoms
Subchronic bronchitis cases
Low birth weight
Pulmonary function
Chronic respiratory diseases other than chronic bronchitis
Nonasthma respiratory emergency room visits
UVb exposure (+/-)e
Visibility in Southeastern Class I areas
Visibility in northeastern and Midwestern Class I areas
Household soiling
Visibility in we stern U.S. Class I areas
Visibility in residential and non-Class I areas
U Vb exposure (+/-)e
Cardiovascular emergency room visits
Chronic respiratory damage8
Premature aging of the lungs8
Nonasthma respiratory emergency room visits
UVb exposure (+/-)e
Ozone/Welfare
CO Health
Decreased outdoor worker
productivity
Yields for commercial crops
Yields for commercial forests and noncommercial crops
Damage to urban ornamental plants
Recreational demand from damaged forest aesthetics
Ecosystem functions
U Vb exposure (+/-)e
Behavioral effects
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Regulatory Impact Analysis
Pollutant/Effect
Quantified and Monetized in Base
Estimates
Unqualified Effects - Changes in:
Nitrogen
Deposition/
Welfare
NOx/Health
HC/Toxics
Health11
HC/Toxics
Welfare11
Commercial forests due to acidic sulfate and nitrate
deposition
Commercial freshwater fishing due to acidic deposition
Recreation in terrestrial ecosystems due to acidic
deposition
Commercial fishing, agriculture, and forests due to
nitrogen deposition
Recreation in estuarine ecosystems due to nitrogen
deposition
Ecosystem functions
Passive fertilization
Lung irritation
Lowered resistance to respiratory infection
Hospital admissions for respiratory and cardiac diseases
Cancer, including lung (benzene, 1,3-butadiene,
formaldehyde, acetaldehyde, naphthalene)
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)
Neurotoxicity (n-hexane, toluene, xylenes)
Direct toxic effects to animals
Bioaccumulation in the food chain
Damage to ecosystem function
Odor
Primary quantified and monetized effects are those included when determining the primary estimate of
total monetized benefits of the final standards.
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.
c Cohort estimates are designed to examine the effects of long term exposures to ambient pollution, but
relative risk estimates may also incorporate some effects due to shorter term exposures (see Kunzli, 2001 for a
discussion of this issue).
While some of the effects of short-term exposure are likely to be captured by the cohort estimates,
there may be additional premature mortality from short-term PM exposure not captured in the cohort estimates
included in the primary analysis.
e May result in benefits or disbenefits.
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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.
8 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.
h The categorization of unqualified toxic health and welfare effects is not exhaustive.
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Table 6.4-2. Ozone- and PM-Related Health Endpoints
Endpoint
Pollutant
Study
Study Population
Premature Mortality
Premature mortality -
daily time series, non-
accidental
Premature mortality
cohort study, all-
cause
Premature mortality,
total exposures
Premature mortality
all-cause
03
PM25
PM25
PM25
Bell et al (2004) (NMMAPS study)12
Meta-analyses:
Belletal(2005)13
Itoetal(2005)14
Levy etal (2005) 15
Pope et al. (2002)16
Laden etal. (2006) 17
Expert Elicitation (lEc, 2006) 18
Woodruff etal. (1997)19
All ages
>29 years
>25 years
>24 years
Infant (<1 year)
Chronic Illness
Chronic bronchitis
Nonfatal heart attacks
PM25
PM25
Abbey etal. (1995)20
Peters etal. (200 1)21
>26 years
Adults (>18 years)
Hospital Admissions
Respiratory
O3
PM9
PM25
PM25
PM9
Pooled estimate:
Schwartz (1995) - ICD 460-519 (all resp)22
Schwartz (1994a; 1994b) - ICD 480-486
(pneumonia)23'24
Moolgavkar et al. (1997) - ICD 480-487
(pneumonia)25
Schwartz (1994b) - ICD 491-492, 494-496
(COPD)
Moolgavkar et al. (1997) - ICD 490-496
(COPD)
Burnett etal. (2001)2
Pooled estimate:
Moolgavkar (2003)ICD 490-496 (COPD)27
Ito (2003)ICD 490-496 (COPD)28
Moolgavkar (2000)ICD 490-496 (COPD)
29
Ito (2003)ICD 480-486 (pneumonia)
Sheppard (2003)ICD 493 (asthma)
30
>64 years
<2 years
>64 years
20-64 years
>64 years
<65 years
Cardiovascular
PM,
PM25
Pooled estimate:
Moolgavkar (2003)ICD 390-429 (all
cardiovascular)
Ito (2003)ICD 410-414, 427-428 (ischemic
heart disease, dysrhythmia, heart failure)
>64 years
Moolgavkar (2000)-
cardiovascular)
-ICD 390-429 (all
20-64 years
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Endpoint
Asthma-related ER
visits
Asthma-related ER
visits (con't)
Pollutant
O3
PM25
Study
Pooled estimate:
Jaffe et al (2003)31
Peel et al (2005)32
Wilson et al (2005)33
Norrisetal. (1999)34
Study Population
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
O3
PM25
Dockeryetal. (1996)35
Popeetal. (1991)36
Schwartz and Neas (2000)37
Pooled estimate:
Ostro et al. (200 1)38 (cough, wheeze and
shortness of breath)
Vedal et al. (1998) (cough)
Ostro (1987)40
Pooled estimate:
Gilliland et al. (200 1)41
Chenetal. (2000)42
Ostro and Rothschild (1989)43
Ostro and Rothschild (1989)
8-12 years
Asthmatics, 9-1 1
years
7-14 years
6-18 years3
18-65 years
5-17 years'3
18-65 years
18-65 years
a The original study populations were 8 to 13 for the Ostro et al. (2001) study and 6 to 13 for the Vedal et al.
(1998) study. Based on advice from the Science Advisory Board Health Effects Subcommittee (SAB-HES),
we extended the applied population to 6 to 18, reflecting the common biological basis for the effect in
children in the broader age group. See: U.S. Science Advisory Board. 2004. Advisory Plans for Health
Effects Analysis in the Analytical Plan for EPA's Second Prospective Analysis -Benefits and Costs of the
Clean Air Act, 19902020. EPA-SAB-COUNCIL-ADV-04-004. See also National Research Council
(NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution Regulations. Washington,
DC: The National Academies Press.
b Gilliland et al. (2001) studied children aged 9 and 10. Chen et al. (2000) studied children 6 to 11. Based on
recent advice from the National Research Council and the EPA SAB-HES, we have calculated reductions in
school absences for all school-aged children based on the biological similarity between children aged 5 to 17.
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.44'45
A number of endpoints that are not health-related also may significantly contribute to
monetized benefits. Potential welfare benefits associated with ozone exposure include:
increased outdoor worker productivity; increased yields for commercial and non-commercial
crops; increased commercial forest productivity; reduced damage to urban ornamental plants;
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Regulatory Impact Analysis
increased recreational demand for undamaged forest aesthetics; and reduced damage to
ecosystem functions.46'47 While we include estimates of the value of increased outdoor
worker productivity, estimation of other welfare impacts is beyond the scope of this analysis.
6.4.2.1 Ozone Exposure Metric
Because several of the ozone mortality epidemiology studies report their base results
relating mortality to 24-hour average ozone, the importance of understanding the biological
relevance of the 24-hour metric relative to other possible metrics is critical.
As mentioned above, ozone-related disbenefits are projected to occur in small regions
within specific urban cores (though yet-to-occur emissions reductions related to ozone
attainment efforts are not accounted for in our current air quality modeling approach). When
NOx reductions increase ozone in these regions, however, it is typically during nighttime and
early morning hours, when NOx titrates ozone. Because human exposure to ozone is a
function of the temporal and spatial patterns of ambient concentrations of ozone in the
atmosphere, the ozone-related health impacts analysis is especially sensitive to which ozone
exposure metric we use in the health impact functions.0
Prior to the addition of ozone-related premature mortality functions to the health
impacts analysis, most of our ozone health impact functions have used metrics which are less
sensitive to ozone disbenefits (e.g., 8-hour daily average). For example, emergency
department visits for asthma are related to 1- or 8-hour maxima. School absences are based
on 8-hour mean and 1-hour maximum ozone levels. It should be noted that ozone disbenefits
that occur during daylight hours, when ozone is higher, are accounted for in these averages.
Epidemiology studies are retrospective in nature and focus on identifying a statistical
relationship between some measure of ozone and a health outcome. The specific
epidemiological studies that form the basis for the ozone mortality impact estimates use time-
series statistical methods that estimate the relationship between daily ozone levels and
mortality based on day to day variations in ozone and mortality. The focus of these studies is
not as much on a specific ozone averaging time as on the day to day variation in the ozone
metrics. In fact, epidemiologists often analyze and report results for multiple ozone metrics,
but may report results for only one metric in the abstract of an article.
In most cases, the day to day variation in different metrics (24-hour average vs 8-hour
maximum, for example) is highly correlated. As such, the relationships between mortality
0 An exposure metric is a measure of air quality calculated as the average or maximum of modeled ambient
concentrations over a relevant time period, such as during the daylight hours of the "ozone season" (which is
May through September for this analysis). The 24-hour average is therefore calculated as the average of all
hourly ozone concentrations throughout the day (from 12am to ll:59pm). The 8-hour maximum is the
maximum hourly value observed between 9am and 5pm each day. The 1-hour maximum is the maximum hourly
value observed throughout an entire day.
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and different ozone metrics will be highly correlated as well. However, when we apply the
mortality impact functions derived from these time-series results to evaluate the impacts of a
specific control measure, we do not focus on the day to day variation in ozone levels so much
as the shift in the overall distribution of ozone concentrations over an entire season. Because
specific emission control strategies might result in a different diurnal profile than was
observed in the monitored ozone data used in the studies, it is important to choose an ozone
metric that is best suited to capturing changes in ozone that are likely to occur during hours
where populations are likely to be exposed to the ozone.
To address this issue in the final rule analysis, we have used standard conversion
functions to convert ozone-related premature mortality health impact functions that use a 24-
hour average or 1-hour maximum ozone metric to functions that use an 8-hour maximum
ozone concentration instead. This is consistent both with the available exposure modeling
and with the form of the current ozone standard. This conversion also does not affect the
relative magnitude of the health impact function. An equivalent change in the 24-hour
average and 8-hour maximum will provide the same overall change in incidence of a health
effect. The conversion ratios are based on observed relationships between the 24-hour
average and 8-hour maximum ozone values. For example, in the Bell et al., 2004 analysis of
ozone-related premature mortality, the authors found that the relationship between the 24-
hour average, the 8-hour maximum, and the 1 -hour maximum was 2:1.5:1, so that the derived
health impact effect estimate based on the 1-hour maximum should be half that of the effect
estimate based on the 24-hour values (and the 8-hour maximum three-quarters of the 24-hour
effect estimate).
The conversion of ozone metrics does not require adjustment to the air quality
modeling. It preserves the observed patterns of ozone-related disbenefits, and allows for
disbenefits to occur in the health impact estimates if those disbenefits occur during hours
when populations are likely to be exposed. In future analyses, we will also convert the ozone
exposure metrics in morbidity studies that do not use an 8-hour exposure metric.
6.4.2.2 Premature Mortality Effect Estimates
While particulate matter is the criteria pollutant most clearly associated with
premature mortality, recent research suggests that short-term repeated ozone exposure likely
contributes to premature death. The 2006 Ozone Criteria Document states: "Consistent with
observed ozone-related increases in respiratory- and cardiovascular-related morbidity, several
newer multi-city studies, single-city studies, and several meta-analyses of these studies have
provided relatively strong epidemiologic evidence for associations between short-term ozone
exposure and all-cause mortality, even after adjustment for the influence of season and PM"
(EPA, 2006: E-17).48 The epidemiologic data are also supported by newly available
experimental data from both animal and human studies which provide evidence suggestive of
plausible pathways by which risk of respiratory or cardiovascular morbidity and mortality
could be increased by ambient ozone. With respect to short-term exposure, the ozone Criteria
Document concludes: "This overall body of evidence is highly suggestive that ozone directly
or indirectly contributes to non-accidental and cardiopulmonary-related mortality, but
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Regulatory Impact Analysis
additional research is needed to more fully establish underlying mechanisms by which such
effects occur" (pg. E-18).
With respect to the time-series studies, the conclusion regarding the relationship
between short-term exposure and premature mortality is based, in part, upon recent city-
specific time-series studies such as the Schwartz (2004) analysis in Houston and the Huang et
al. (2004) analysis in Los Angeles.p This conclusion is also based on recent meta-analyses by
Bell et al. (2005), Ito et al. (2005), and Levy et al. (2005), and a new analysis of the National
Morbidity, Mortality, and Air Pollution Study (NMMAPS) data set by Bell et al. (2004),
which specifically sought to disentangle the roles of ozone, PM, weather-related variables,
and seasonality. The 2006 Criteria Document states that "the results from these meta-
analyses, as well as several single- and multiple-city studies, indicate that co-pollutants
generally do not appear to substantially confound the association between ozone and
mortality" (p. 7-103). However, CASAC raised questions about the implications of these
time-series results in a policy context. Specifically, CASAC emphasized that".. .while the
time-series study design is a powerful tool to detect very small effects that could not be
detected using other designs, it is also a blunt tool" (Henderson, 2006: 3). They point to
findings (e.g., Stieb et al., 2002, 2003) that indicated associations between premature
mortality and all of the criteria pollutants, indicating that "findings of time-series studies do
not seem to allow us to confidently attribute observed effects to individual pollutants" (id.).
They note that "not only is the interpretation of these associations complicated by the fact that
the day-to-day variation in concentrations of these pollutants is, to a varying degree,
determined by meteorology, the pollutants are often part of a large and highly correlated mix
of pollutants, only a very few of which are measured" (id.). Even with these uncertainties, the
CASAC Ozone Panel, in its review of EPA's Staff Paper, found "... premature total non-
accidental and cardiorespiratory mortality for inclusion in the quantitative risk assessment to
be appropriate."
Consistent with the methodology used in the ozone risk assessment found in the
Characterization of Health Risks found in the Review of the National Ambient Air Quality
Standards for Ozone: Policy Assessment of Scientific and Technical Information, we included
ozone mortality in the primary health effects analysis, with the recognition that the exact
magnitude of the effects estimate is subject to continuing uncertainty. We used effect
estimates from the Bell et al. (2004) NMMAPS analysis, as well as effect estimates from the
three meta-analyses. In addition, we include the possibility that there is not a causal
association between ozone and mortality, i.e., that the effect estimate for premature mortality
could be zero.
p For an exhaustive review of the city-specific time-series studies considered in the ozone staff paper, see: U.S.
Environmental Protection Agency, 2007. Review of the National Ambient Air Quality Standards for Ozone:
Policy Assessment of Scientific and Technical Information. Prepared by the Office of Air and Radiation.
Available at http://www.epa.gov/ttn/naaqs/standards/ozone/data/2007_0l_ozone_staff_paper.pdf. pp. 5-36.
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We estimate the change in mortality incidence and estimated credible interval*2
resulting from application of the effect estimate from each study and present them separately
to reflect differences in the study designs and assumptions about causality. However, it is
important to note that this procedure only captures the uncertainty in the underlying
epidemiological work, and does not capture other sources of uncertainty, such as uncertainty
in the estimation of changes in air pollution exposure (Levy et al., 2000).
6.4.2.3 Respiratory Hospital Admissions Effect Estimates
Detailed hospital admission and discharge records provide data for an extensive body
of literature examining the relationship between hospital admissions and air pollution. This is
especially true for the portion of the population aged 65 and older, because of the availability
of detailed Medicare records. In addition, there is one study (Burnett et al., 2001) providing
an effect estimate for respiratory hospital admissions in children under two.
Because the number of hospital admission studies we considered is so large, we used
results from a number of studies to pool some hospital admission endpoints. Pooling is the
process by which multiple study results may be combined in order to produce better estimates
of the effect estimate, or p. For a complete discussion of the pooling process, see Abt (2005).R
To estimate total respiratory hospital admissions associated with changes in ambient ozone
concentrations for adults over 65, we first estimated the change in hospital admissions for
each of the different effects categories that each study provided for each city. These cities
included Minneapolis, Detroit, Tacoma and New Haven. To estimate total respiratory
hospital admissions for Detroit, we added the pneumonia and COPD estimates, based on the
effect estimates in the Schwartz study (1994). Similarly, we summed the estimated hospital
admissions based on the effect estimates the Moolgavkar study reported for Minneapolis
(Moolgavkar et al., 1997). To estimate total respiratory hospital admissions for Minneapolis
using the Schwartz study (1994), we simply estimated pneumonia hospital admissions based
on the effect estimate. Making this assumption that pneumonia admissions represent the total
impact of ozone on hospital admissions in this city will give some weight to the possibility
that there is no relationship between ozone and COPD, reflecting the equivocal evidence
represented by the different studies. We then used a fixed-effects pooling procedure to
combine the two total respiratory hospital admission estimates for Minneapolis. Finally, we
used random effects pooling to combine the results for Minneapolis and Detroit with results
from studies in Tacoma and New Haven from Schwartz (1995). As noted above, this pooling
approach incorporates both the precision of the individual effect estimates and between-study
variability characterizing differences across study locations.
Q A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a
confidence interval used in frequentist statistics.
R Abt Associates, Incorporated. Environmental Benefits Mapping and Analysis Program, Technical Appendices.
May 2005. pp. 1-3
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6.4.2.4 Asthma-Related Emergency Room Visits Effect Estimates
We used three studies as the source of the concentration-response functions we used to
estimate the effects of ozone exposure on asthma-related emergency room (ER) visits: Peel et
al. (2005); Wilson et al. (2005); and Jaffe et al. (2003). We estimated the change in ER visits
using the effect estimate(s) from each study and then pooled the results using the random
effects pooling technique (see Abt, 2005). The study by Jaffe et al. (2003) examined the
relationship between ER visits and air pollution for populations aged five to 34 in the Ohio
cities of Cleveland, Columbus and Cincinnati from 1991 through 1996. In single-pollutant
Poisson regression models, ozone was linked to asthma visits. We use the pooled estimate
across all three cities as reported in the study. The Peel et al. study (2005) estimated asthma-
related ER visits for all ages in Atlanta, using air quality data from 1993 to 2000. Using
Poisson generalized estimating equations, the authors found a marginal association between
the maximum daily 8-hour average ozone level and ER visits for asthma over a 3-day moving
average (lags of 0, 1, and 2 days) in a single pollutant model. Wilson et al. (2005) examined
the relationship between ER visits for respiratory illnesses and asthma and air pollution for all
people residing in Portland, Maine from 1998-2000 and Manchester, New Hampshire from
1996-2000. For all models used in the analysis, the authors restricted the ozone data
incorporated into the model to the months ozone levels are usually measured, the spring-
summer months (April through September). Using the generalized additive model, Wilson et
al. (2005) found a significant association between the maximum daily 8-hour average ozone
level and ER visits for asthma in Portland, but found no significant association for
Manchester. Similar to the approach used to generate effect estimates for hospital
admissions, we used random effects pooling to combine the results across the individual study
estimates for ER visits for asthma. The Peel et al. (2005) and Wilson et al. (2005) Manchester
estimates were not significant at the 95 percent level, and thus, the confidence interval for the
pooled incidence estimate based on these studies includes negative values. This is an artifact
of the statistical power of the studies, and the negative values in the tails of the estimated
effect distributions do not represent improvements in health as ozone concentrations are
increased. Instead these should be viewed as a measure of uncertainty due to limitations in
the statistical power of the study. Note that we included both hospital admissions and ER
visits as separate endpoints associated with ozone exposure, because our estimates of hospital
admission costs do not include the costs of ER visits, and because most asthma ER visits do
not result in a hospital admission.
6.4.2.5 Minor Restricted Activity Days Effects Estimate
Minor restricted activity days (MRADs) occur when individuals reduce most usual
daily activities and replace them with less-strenuous activities or rest, but do not miss work or
school. We estimated the effect of ozone exposure on MRADs using a concentration-
response function derived from Ostro and Rothschild (1989). These researchers estimated
the impact of ozone and PM2.5 on MRAD incidence in a national sample of the adult working
population (ages 18 to 65) living in metropolitan areas. We developed separate coefficients
for each year of the Ostro and Rothschild analysis (1976-1981), which we then combined for
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use in EPA's analysis. The effect estimate used in the impact function is a weighted average
of the coefficients in Ostro and Rothschild (1989, Table 4), using the inverse of the variance
as the weight.
6.4.2.6 School Absences Effect Estimate
Children may be absent from school due to respiratory or other acute diseases caused,
or aggravated by, exposure to air pollution. Several studies have found a significant
association between ozone levels and school absence rates. We use two studies (Gilliland et
al., 2001; Chen et al., 2000) to estimate changes in school absences resulting from changes in
ozone levels. The Gilliland et al. study estimated the incidence of new periods of absence,
while the Chen et al. study examined daily absence rates. We converted the Gilliland et al.
estimate to days of absence by multiplying the absence periods by the average duration of an
absence. We estimated 1.6 days as the average duration of a school absence, the result of
dividing the average daily school absence rate from Chen et al. (2000) and Ransom and Pope
(1992) by the episodic absence duration from Gilliland et al. (2001). Thus, each Gilliland et
al. period of absence is converted into 1.6 absence days.
Following recent advice from the National Research Council (2002), we calculated
reductions in school absences for the full population of school age children, ages five to 17.
This is consistent with recent peer-reviewed literature on estimating the impact of ozone
exposure on school absences (Hall et al. 2003). We estimated the change in school absences
using both Chen et al. (2000) and Gilliland et al. (2001) and then, similar to hospital
admissions and ER visits, pooled the results using the random effects pooling procedure.
6.4.2.7 Worker Productivity
To monetize benefits associated with increased worker productivity resulting from
improved ozone air quality, we used information reported in Crocker and Horst (1981).
Crocker and Horst examined the impacts of ozone exposure on the productivity of outdoor
citrus workers. The study measured productivity impacts. Worker productivity is measuring
the value of the loss in productivity for a worker who is at work on a particular day, but due to
ozone, cannot work as hard. It only applies to outdoor workers, like fruit and vegetable
pickers, or construction workers. Here, productivity impacts are measured as the change in
income associated with a change in ozone exposure, given as the elasticity of income with
respect to ozone concentration. The reported elasticity translates a ten percent reduction in
ozone to a 1.4 percent increase in income. Given the national median daily income for
outdoor workers engaged in strenuous activity reported by the U.S. Census Bureau (2002),
$68 per day (2000$), a ten percent reduction in ozone yields about $0.97 in increased daily
wages. We adjust the national median daily income estimate to reflect regional variations in
income using a factor based on the ratio of county median household income to national
median household income. No information was available for quantifying the uncertainly
associated with the central valuation estimate. Therefore, no uncertainty analysis was
conducted for this endpoint.
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6.4.2.8 Unqualified Effects
6.4.2.8.1 Direct Ozone Effects on Vegetation
The Ozone Criteria Document notes that "current ambient concentrations in many
areas of the country are sufficient to impair growth of numerous common and economically
valuable plant and tree species." (U.S. EPA, 2006, page 9-1). Changes in ground-level ozone
resulting from the implementation of alternative ozone standards are expected to affect crop
and forest yields throughout the affected area. Recent scientific studies have also found the
ozone negatively impacts the quality or nutritive value of crops (U.S. EPA, 2006, page 9-16).
Well-developed techniques exist to provide monetary estimates of these benefits to
agricultural producers and to consumers. These techniques use models of planting decisions,
yield response functions, and the supply of and demand for agricultural products. The
resulting welfare measures are based on predicted changes in market prices and production
costs. Models also exist to measure benefits to silvicultural producers and consumers.
However, these models have not been adapted for use in analyzing ozone-related forest
impacts. Because of resource limitations, we are unable to provide agricultural or benefits
estimates for the final rule.
An additional welfare benefit expected to accrue as a result of reductions in ambient
ozone concentrations in the United States is the economic value the public receives from
reduced aesthetic injury to forests. There is sufficient scientific information available to
reliably establish that ambient ozone levels cause visible injury to foliage and impair the
growth of some sensitive plant species (U.S. EPA, 2006, page 9-19). However, present
analytic tools and resources preclude EPA from quantifying the benefits of improved forest
aesthetics.
Urban ornamentals (floriculture and nursery crops) represent an additional vegetation
category likely to experience some degree of negative effects associated with exposure to
ambient ozone levels and likely to affect large economic sectors. 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 economic benefits analysis has
been conducted. The farm production value of ornamental crops was estimated at over $14
billion in 2003 (USDA, 2004). This is therefore a potentially important welfare effects
category. However, information and valuation methods are not available to allow for
plausible estimates of the percentage of these expenditures that may be related to impacts
associated with ozone exposure.
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6.4.2.8.2 Nitrogen Deposition
Deposition to Estuarine and Coastal Waters
Excess nutrient loads, especially of nitrogen, cause a variety of adverse consequences
to the health of estuarine and coastal waters. These effects include toxic and/or noxious algal
blooms such as brown and red tides, low (hypoxic) or zero (anoxic) concentrations of
dissolved oxygen in bottom waters, the loss of submerged aquatic vegetation due to the light-
filtering effect of thick algal mats, and fundamental shifts in phytoplankton community
structure (Bricker et al., 1999). A recent study found that for the period 1990-2002,
atmospheric deposition accounted for 17 percent of nitrate loadings in the Gulf of Mexico,
where severe hypoxic zones have been existed over the last two decades (Booth and
Campbell, 2007)s.
Reductions in atmospheric deposition of NOx are expected to reduce the adverse
impacts associated with nitrogen deposition to estuarine and coastal waters. However, direct
functions relating changes in nitrogen loadings to changes in estuarine benefits are not
available. The preferred WTP-based measure of benefits depends on the availability of these
functions and on estimates of the value of environmental responses. Because neither
appropriate functions nor sufficient information to estimate the marginal value of changes in
water quality exist at present, calculation of a WTP measure is not possible.
Deposition to Agricultural and Forested Land
Implementation strategies for alternative standards which reduce NOx emissions, will
also reduce nitrogen deposition on agricultural land and forests. There is some evidence that
nitrogen deposition may have positive effects on agricultural output through passive
fertilization. Holding all other factors constant, farmers' use of purchased fertilizers or
manure may increase as deposited nitrogen is reduced. Estimates of the potential value of this
possible increase in the use of purchased fertilizers are not available, but it is likely that the
overall value is very small relative to other health and welfare effects. The share of nitrogen
requirements provided by this deposition is small, and the marginal cost of providing this
nitrogen from alternative sources is quite low. In some areas, agricultural lands suffer from
nitrogen over-saturation due to an abundance of on-farm nitrogen production, primarily from
animal manure. In these areas, reductions in atmospheric deposition of nitrogen from PM
represent additional agricultural benefits.
Information on the effects of changes in passive nitrogen deposition on forests and
other terrestrial ecosystems is very limited. The multiplicity of factors affecting forests,
including other potential stressors such as ozone, and limiting factors such as moisture and
s Booth, M.S., and C. Campbell. 2007. Spring Nitrate Flux in the Mississippi River Basin: A Landscape Model
with Conservation Applications. Environ. Sci. Technol.; 2007; ASAP Web Release Date: 20-Jun-2007; (Article)
DOI: 10.1021/es070179e
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Regulatory Impact Analysis
other nutrients, confound assessments of marginal changes in any one stressor or nutrient in
forest ecosystems. However, reductions in deposition of nitrogen could have negative effects
on forest and vegetation growth in ecosystems where nitrogen is a limiting factor (US EPA,
1993). Moreover, any positive effect that nitrogen deposition has on forest productivity would
enhance the level of carbon dioxide sequestration as well.T'u'v
On the other hand, there is evidence that forest ecosystems in some areas of the United
States (such as the western U.S.) are nitrogen saturated (US EPA, 1993). Once saturation is
reached, adverse effects of additional nitrogen begin to occur such as soil acidification which
can lead to leaching of nutrients needed for plant growth and mobilization of harmful
elements such as aluminum. Increased soil acidification is also linked to higher amounts of
acidic runoff to streams and lakes and leaching of harmful elements into aquatic ecosystems.
6.4.2.8.3 Ultraviolet Radiation
Atmospheric ozone absorbs a harmful band of ultraviolet radiation from the sun called
UV-B, providing a protective shield to the Earth's surface. The majority of this protection
occurs in the stratosphere where 90% of atmospheric ozone is located. The remaining 10% of
the Earth's ozone is present at ground level (referred to as tropospheric ozone) (NAS, 1991;
NASA). Only a portion of the tropospheric fraction of UV-B shielding is from anthropogenic
sources (e.g., power plants, byproducts of combustion). The portion of ground level ozone
associated with anthropogenic sources varies by locality and over time. Even so, it is
reasonable to assume that reductions in ground level ozone would lead to increases in the
same health effects linked to in UV-B exposures. These effects include fatal and nonfatal
melanoma and non-melanoma skin cancers and cataracts. The values of $15,000 per case for
non-fatal melanoma skin cancer, $5,000 per case for non-fatal non-melanoma skin cancer, and
$15,000 per case of cataracts have been used in analyses of stratospheric ozone depletion
(U.S. EPA, 1999). Fatal cancers are valued using the standard VSL estimate, which for 2020
is $6.6 million (1999$). UV-B has also been linked to ecological effects including damage to
crops and forest. For a more complete listing of quantified and unquantified UV-B radiation
effects, see Table G-4 and G-7 in the Benefits and Costs of the Clean Air Act, 1990-2010
(U.S. EPA, 1999. UV-B related health effects are also discussed in the context of
stratospheric ozone in a 2006 report by ICF Consulting, prepared for the U.S. EPA.
There are many factors that influence UV-B radiation penetration to the earth's
surface, including latitude, altitude, cloud cover, surface albedo, PM concentration and
T Peter M. Vitousek et. al., "Human Alteration of the Global Nitrogen Cycle: Causes and Consequences" Issues
in Ecology No. 1 (Spring) 1997.
u Knute J. Nadelhoffer et. al., "Nitrogen deposition makes a minor contribution to carbon sequestration in
temperate forests" Nature 398, 145-148 (11 March 1999)
v Martin Kochy and Scott D. Wilson, "Nitrogen deposition and forest expansion in the northern Great Plains
Journal of Ecology Journal of Ecology 89 (5), 807-817
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Cost-Benefit Analysis
composition, and gas phase pollution. Of these, only latitude and altitude can be defined with
small uncertainty in any effort to assess the changes in UV-B flux that may be attributable to
any changes in tropospheric O3 as a result of any revision to the O3 NAAQS. Such an
assessment of UV-B related health effects would also need to take into account human habits,
such as outdoor activities (including age- and occupation-related exposure patterns), dress and
skin care to adequately estimate UV-B exposure levels. However, little is known about the
impact of these factors on individual exposure to UV-B.
Moreover, detailed information does not exist regarding other factors that are relevant
to assessing changes in disease incidence, including: type (e.g., peak or cumulative) and time
period (e.g., childhood, lifetime, current) of exposures related to various adverse health
outcomes (e.g., damage to the skin, including skin cancer; damage to the eye, such as
cataracts; and immune system suppression); wavelength dependency of biological responses;
and interindividual variability in UV-B resistance to such health outcomes. Beyond these well
recognized adverse health effects associated with various wavelengths of UV radiation, the
Criteria Document (section 10.2.3.6) also discusses protective effects of UV-B radiation.
Recent reports indicate the necessity of UV-B in producing vitamin D, and that vitamin D
deficiency can cause metabolic bone disease among children and adults, and may also
increase the risk of many common chronic diseases (e.g., type I diabetes and rheumatoid
arthritis) as well as the risk of various types of cancers. Thus, the Criteria Document
concludes that any assessment that attempts to quantify the consequences of increased UV-B
exposure on humans due to reduced ground-level O3 must include consideration of both
negative and positive effects. However, as with other impacts of UVB on human health, this
beneficial effect of UVB radiation has not previously been studied in sufficient detail. The
Agency is currently exploring the feasibility of estimating the effects of increased UVB
exposures resulting from reductions in tropospheric ozone.
6.4.2.8.4 Climate Implications of Tropospheric Ozone
Although climate and air quality are generally treated as separate issues, they are
closely coupled through atmospheric processes. Ozone, itself, is a major greenhouse gas and
climate directly influences ambient concentrations of ozone.
The concentration of tropospheric ozone has increased substantially since the pre-
industrial era and has contributed to warming. Tropospheric ozone is (after CO2 and CH4)
the third most important contributor to greenhouse gas warming. The National Academy of
Sciences recently statedw that regulations targeting ozone precursors would have combined
benefits for public health and climate. As noted in the OAQPS Staff Paper, the overall body
of scientific evidence suggests that high concentrations of ozone on a regional scale could
have a discernible influence on climate. However, the Staff Paper concludes that insufficient
information is available at this time to quantitatively inform the secondary NAAQS process
w National Academy of Sciences, "Radiative Forcing of Climate Change: Expanding the Concept and
Addressing Uncertainties," October 2005.
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with regard to this aspect of the ozone-climate interaction.
Climate change can affect tropospheric ozone by modifying emissions of precursors,
chemistry, transport and removal.x Climate change affects the sources of ozone precursors
through physical response (lightning), biological response (soils, vegetation, and biomass
burning) and human response (energy generation, land use, and agriculture). Increases in
regional ozone pollution are expected due to higher temperatures and weaker circulation.
Simulations with global climate models for the 21st century indicate a decrease in the lifetime
of tropospheric ozone due to increasing water vapor which could decrease global background
ozone concentrations.
The Intergovernmental Panel on Climate Change (IPCC) recently released a reportY
which projects, with "virtual certainty," declining air quality in cities due to warmer and
fewer cold days and nights and/or warmer/more frequent hot days and nights over most land
areas. The report states that projected climate change-related exposures are likely to affect the
health status of millions of people, in part, due to higher concentrations of ground level ozone
related to climate change.
The IPCC also reports2 that the current generation of tropospheric ozone models is
generally successful in describing the principal features of the present-day global ozone
distribution. However, there is much less confidence in the ability to reproduce the changes
in ozone associated with perturbations of emissions or climate. There are major discrepancies
with observed long-term trends in ozone concentrations over the 20th century, including after
1970 when the reliability of observed ozone trends is high. Resolving these discrepancies is
needed to establish confidence in the models.
The EPA is currently leading a research effort with the goal of identifying changes in
regional US air quality that may occur in a future (2050) climate, focusing on fine particles
and ozone. The research builds first on an assessment of changes in US air quality due to
climate change, which includes direct meteorological impacts on atmospheric chemistry and
xDenman, K.L., G. Brasseur, A. Chidthaisong, P. Ciais, P.M. Cox, R.E. Dickinson, D. Hauglustaine, C. Heinze,
E. Holland, D. Jacob, U. Lohmann, S Ramachandran, P.L. da Silva Dias, S.C. Wofsy and X. Zhang, 2007:
Couplings Between Changes in the Climate System and Biogeochemistry. In: Climate Change 2007: The
Physical Science Basis. Contribution of Working Group I to the Fourth Assessment
Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M.
Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA.
Y IPCC, Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability,
Summary for Policymakers
z Denman, et al, 2007: Couplings Between Changes in the Climate System and Biogeochemistry. In: Climate
Change 2007: The Physical Science Basis.
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Cost-Benefit Analysis
transport and the effect of temperature changes on air pollution emissions. Further research
will result in an assessment that adds the emission impacts from technology, land use,
demographic changes, and air quality regulations to construct plausible scenarios of US air
quality 50 years into the future. As noted in the Staff Paper, results from these efforts are
expected to be available for consideration in the next review of the ozone NAAQS.
6.4.3 Baseline Incidence Rates
Epidemiological studies of the association between pollution levels and adverse health
effects generally provide a direct estimate of the relationship of air quality changes to the
relative risk of a health effect, rather than estimating the absolute number of avoided cases.
For example, a typical result might be that a 100 ppb decrease in daily ozone levels might, in
turn, decrease hospital admissions by 3 percent. The baseline incidence of the health effect is
necessary to convert this relative change into a number of cases. A baseline incidence rate is
the estimate of the number of cases of the health effect per year in the assessment location, as
it corresponds to baseline pollutant levels in that location. To derive the total baseline
incidence per year, this rate must be multiplied by the corresponding population number. For
example, if the baseline incidence rate is the number of cases per year per 100,000 people,
that number must be multiplied by the number of 100,000s in the population.
Table 6.4-3 summarizes the sources of baseline incidence rates and provides average
incidence rates for the endpoints included in the analysis. For both baseline incidence and
prevalence data, we used age-specific rates where available. We applied concentration-
response functions to individual age groups and then summed over the relevant age range to
provide an estimate of total population benefits. In most cases, we used a single national
incidence rate, due to a lack of more spatially disaggregated data. Whenever possible, the
national rates used are national averages, because these data are most applicable to a national
assessment of benefits. For some studies, however, the only available incidence information
comes from the studies themselves; in these cases, incidence in the study population is
assumed to represent typical incidence at the national level. Regional incidence rates are
available for hospital admissions, and county-level data are available for premature mortality.
We have projected mortality rates such that future mortality rates are consistent with our
projections of population growth (Abt Associates, 2005).
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Table 6.4-3. National Average Baseline Incidence Rates3
Endpoint
Mortality
Respiratory
Hospital
Admissions.
Asthma ER visits
Minor Restricted
Activity Days
(MRADs)
School Loss
Days
Source
CDC Compressed Mortality File,
accessed through CDC Wonder
(1996-1998)
1999 NHDS public use data files'3
2000 NHAMCS public use data
files'; 1999 NHDS public use data
files'3
Ostro and Rothschild
(1989, p. 243)
National Center for Education
Statistics (1996) and 1996 HIS
(Adams et al., 1999, Table 47);
estimate of 180 school days per
year
Notes
non-
accidental
incidence
incidence
incidence
all-cause
Rate per 100 people per yeard by Age Group
<18
0.025
0.043
1.011
990.0
18-24
0.022
0.084
1.087
780
25-34
0.057
0.206
0.751
780
35-44
0.150
0.678
0.438
780
45-54
0.383
1.926
0.352
780
55-64
1.006
4.389
0.425
780
65+
4.937
11.62
9
0.232
The following abbreviations are used to describe the national surveys conducted by the National Center for
Health Statistics: HIS refers to the National Health Interview Survey; NHDS - National Hospital Discharge Survey;
NHAMCS - National Hospital Ambulatory Medical Care Survey.
b See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHDS/
0 See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHAMCS/
All of the rates reported here are population-weighted incidence rates per 100 people per year. Additional details
on the incidence and prevalence rates, as well as the sources for these rates are available upon request.
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Table 6.4-3 National Average Baseline Incidence Rates (continued)
Endpoint
Asthma Exacerbations
Source
Ostroetal. (2001)
Vedaletal. (1998)
Notes
Incidence (and
prevalence)
among
asthmatic
African-
American
children
Incidence (and
prevalence)
among
asthmatic
children
Daily wheeze
Daily cough
Daily dyspnea
Daily wheeze
Daily cough
Daily dyspnea
Rate per 100 people per
year
0.076(0.173)
0.067(0.145)
0.037 (0.074)
0.038
0.086
0.045
6.5 Economic Values for Health Outcomes
Reductions in ambient concentrations of air pollution generally lower the risk of future
adverse health effects for a large population. Therefore, the appropriate economic measure is
willingness-to-pay (WTP) for changes in risk of a health effect rather than WTP for a health
effect that would occur with certainty (Freeman, 1993). Epidemiological studies generally
provide estimates of the relative risks of a particular health effect that is avoided because of a
reduction in air pollution. We converted those to units of avoided statistical incidence for ease
of presentation. We calculated the value of avoided statistical incidences by dividing
individual WTP for a risk reduction by the related observed change in risk. For example,
suppose a pollution-reduction regulation is able to reduce the risk of premature mortality from
2 in 10,000 to 1 in 10,000 (a reduction of 1 in 10,000). If individual WTP for this risk
reduction is $100, then the WTP for an avoided statistical premature death is $1 million
($100/0.0001 change in risk).
WTP estimates generally are not available for some health effects, such as hospital
admissions. In these cases, we used the cost of treating or mitigating the effect as a primary
estimate. These cost-of-illness (COI) estimates generally understate the true value of
reducing the risk of a health effect, because they reflect the direct expenditures related to
treatment, but not the value of avoided pain and suffering (Harrington and Portney, 1987;
Berger, 1987). We provide unit values for health endpoints (along with information on the
distribution of the unit value) in Table 6.5-1. All values are in constant year 2000 dollars,
adjusted for growth in real income out to 2020 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
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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. Table 6.5-1 presents the values
for individual endpoints adjusted to year 2020 income levels. The discussion below provides
additional details on ozone related endpoints not previously included in the proposal for this
rule. For details on valuation estimates for PM related endpoints, see the 2006 PM NAAQS
RIA and the proposed Locomotive and Marine RIA.
6.5.1 Mortality Valuation
To estimate the monetary benefit of reducing the risk of premature death, we used the
"value of statistical lives" saved (VSL) approach, which is a summary measure for the value
of small changes in mortality risk for a large number of people. The VSL approach applies
information from several published value-of-life studies to determine a reasonable monetary
value of preventing premature mortality. The mean value of avoiding one statistical death is
estimated to be roughly $5.5 million at 1990 income levels (2000 $), and $6.6 million at 2020
income levels. This represents an intermediate value from a variety of estimates in the
economics literature (see the 2006 PM NAAQS RIA for more details on the calculation of
VSL).
6.5.2 Hospital Admissions Valuation
In the absence of estimates of societal WTP to avoid hospital visits/admissions for
specific illnesses, estimates of total cost of illness (total medical costs plus the value of lost
productivity) typically are used as conservative, or lower bound, estimates. These estimates
are biased downward, because they do not include the willingness-to-pay value of avoiding
pain and suffering.
The International Classification of Diseases (ICD-9, 1979) code-specific COI
estimates used in this analysis consist of estimated hospital charges and the estimated
opportunity cost of time spent in the hospital (based on the average length of a hospital stay
for the illness). We based all estimates of hospital charges and length of stays on statistics
provided by the Agency for Healthcare Research and Quality (AHRQ 2000). We estimated
the opportunity cost of a day spent in the hospital as the value of the lost daily wage,
regardless of whether the hospitalized individual is in the workforce. To estimate the lost
daily wage, we divided the 1990 median weekly wage by five and inflated the result to year
2000$ using the CPI-U "all items." The resulting estimate is $109.35. The total cost-of-
illness estimate for an ICD code-specific hospital stay lasting n days, then, was the mean
hospital charge plus $109 X n.
6.5.3 Asthma-Related Emergency Room Visits Valuation
To value asthma emergency room visits, we used a simple average of two estimates
from the health economics literature. The first estimate comes from Smith et al. (1997), who
reported approximately 1.2 million asthma-related emergency room visits in 1987, at a total
cost of $186.5 million (1987$). The average cost per visit that year was $155; in 2000$, that
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Cost-Benefit Analysis
cost was $311.55 (using the CPI-U for medical care to adjust to 2000$). The second estimate
comes from Stanford et al. (1999), who reported the cost of an average asthma-related
emergency room visit at $260.67, based on 1996-1997 data. A simple average of the two
estimates yields a (rounded) unit value of $286.
6.5.4 Minor Restricted Activity Days Valuation
No studies are reported to have estimated WTP to avoid a minor restricted activity
day. However, one of EPA's contractors, lEc (1993) has derived an estimate of willingness to
pay to avoid a minor respiratory restricted activity day, using estimates from Tolley et al.
(1986) of WTP for avoiding a combination of coughing, throat congestion and sinusitis. The
lEc estimate of WTP to avoid a minor respiratory restricted activity day is $38.37 (1990$), or
about $52 ($2000).
Although Ostro and Rothschild (1989) statistically linked ozone and minor restricted
activity days, it is likely that most MRADs associated with ozone exposure are, in fact, minor
respiratory restricted activity days. For the purpose of valuing this health endpoint, we used
the estimate of mean WTP to avoid a minor respiratory restricted activity day.
6.5.5 School Absences
To value a school absence, we: (1) estimated the probability that if a school child
stays home from school, a parent will have to stay home from work to care for the child; and
(2) valued the lost productivity at the parent's wage. To do this, we estimated the number of
families with school-age children in which both parents work, and we valued a school-loss
day as the probability that such a day also would result in a work-loss day. We calculated this
value by multiplying the proportion of households with school-age children by a measure of
lost wages.
We used this method in the absence of a preferable WTP method. However, this
approach suffers from several uncertainties. First, it omits willingness to pay to avoid the
symptoms/illness that resulted in the school absence; second, it effectively gives zero value to
school absences that do not result in work-loss days; and third, it uses conservative
assumptions about the wages of the parent staying home with the child. Finally, this method
assumes that parents are unable to work from home. If this is not a valid assumption, then
there would be no lost wages.
For this valuation approach, we assumed that in a household with two working
parents, the female parent will stay home with a sick child. From the Statistical Abstract of
the United States (U.S. Census Bureau, 2001), we obtained: (1) the numbers of single,
married and "other" (widowed, divorced or separated) working women with children; and (2)
the rates of participation in the workforce of single, married and "other" women with
children. From these two sets of statistics, we calculated a weighted average participation rate
of 72.85 percent.
Our estimate of daily lost wage (wages lost if a mother must stay at home with a sick
child) is based on the year 2000 median weekly wage among women ages 25 and older (U.S.
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Census Bureau, 2001). This median weekly wage is $551. Dividing by five gives an estimated
median daily wage of $103. To estimate the expected lost wages on a day when a mother has
to stay home with a school-age child, we first estimated the probability that the mother is in
the workforce then multiplied that estimate by the daily wage she would lose by missing a
work day: 72.85 percent times $103, for a total loss of $75. This valuation approach is
similar to that used by Hall et al. (2003).
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Table 6.5-1. Unit Values Used for Economic Valuation of Health Endpoints (2000$)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
$5,500,000
$6,600,000
$6,800,000
Point estimate is the mean of a normal distribution with a 95 percent
confidence interval between $1 and $10 million. Confidence interval
is based on two meta-analyses of the wage-risk VSL literature: $1
million represents the lower end of the interquartile range from the
Mrozek and Taylor (2002)49 meta-analysis and $10 million
represents the upper end of the interquartile range from the Viscusi
and Aldy (2003)50 meta-analysis. The VSL represents the value of a
small change in mortality risk aggregated over the affected
population.
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]51) 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. Lost
earnings estimates are based on Cropper and Krupnick (1990). 52
Direct medical costs are based on simple average of estimates from
Russell et al. (1998)53 and Wittels et al. (1990).54
Lost earnings:
Cropper and Krupnick (1990). Present discounted value of 5 years of
lost earnings:
at 7%
$7,855
$11,578
$66,920
age of onset: at 3%
25-44 $8,774
45-54 $12,932
55-65 $74,746
Direct medical expenses: An average of:
1. Wittels et al. (1990) ($102,658 no discounting)
2. Russell et al. (1998), 5-year period ($22,33 1 at 3% discount rate;
$2 1 , 1 1 3 at 7% discount rate)
(continued)
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Table 6.5-1. Unit Values Used for Economic Valuation of Health Endpoints (2000$)a (continued)
Health Endpoint
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
2020 Income
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)55 (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) $3 11.55, from Smith etal. (1997) 56 and
(2) $260.67, from Stanford et al. (1999).57
(continued)
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Cost-Benefit Analysis
Table 6.5-1. Unit Values Used for Economic Valuation of Health Endpoints (2000$)a (continued)
Health Endpoint
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
2020 Income
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
58
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
59
"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
$390
Assumes a 6-day episode, with daily value equal to the average of
low and high values for related respiratory symptoms recommended
in Neumann et al. (1994)
60
(continued)
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Regulatory Impact Analysis
Table 6.5-1. Unit Values Used for Economic Valuation of Health Endpoints (2000$)a (continued)
Health Endpoint
Central Estimate of Value Per Statistical
Incidence
1990 Income
Level
2020 Income
Level
2030 Income
T ib
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).
Median WTP estimate to avoid one MRAD from Tolley et al. (1986).
Although the unit values presented in this table are in year 2000 dollars, all monetized annual benefit estimates associated with the final standards 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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Cost-Benefit Analysis
6.6 Benefits Analysis Results for the Final Standards
Applying the impact and valuation functions described previously in this chapter to
the estimated changes in PM2.5 and ozone associated with the final standards results in
estimates of the changes in health damages (e.g., premature mortalities, cases, admissions)
and the associated monetary values for those changes. Estimates of physical health impacts
are presented in Table 6.6-1. Monetized values for those health endpoints are presented in
Table 6.6-2. Total aggregate monetized benefits are presented in Table 6.6-3 and Table 6.6-4
using either a 3 percent or 7 percent discount rate, respectively. All of the monetary benefits
are in constant-year 2006 dollars. For each endpoint presented in Tables 6.6-1 and 6.6-2, we
provide both the mean estimate and the 90% confidence interval.
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 final standards is thus
equal to the subset of monetized PM2.5- 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.
Total monetized benefits are dominated by benefits of mortality risk reductions. We
provide results based on concentration response functions from the American Cancer Society
Study (ACS), Six Cities, and Expert Elicitation to give an indication of the sensitivity of the
benefits estimates to alternative assumptions. Following the recommendations of the NRC
report (NRC, 2002), we identify those estimates which are based on empirical data, and those
which are based on expert judgments. EPA intends to ask its Science Advisory Board to
evaluate how EPA has incorporated expert elicitation results into the benefits analysis, and the
extent to which they find the presentation in this RIA responsive to the NRC (2002) guidance
to incorporate uncertainty into the main analysis and further, whether the agency should move
toward presenting a central estimate with uncertainty bounds or continue to provide separate
estimates for each of the 12 experts as well as from the ACS and Six Cities studies, and if so,
the appropriateness of using Laden et al 2006, the most recently published update, as the
estimate for the Six Cities based model.
Using the ACS and Six-Cities results, we estimate that the final standards would result
in between 490 and 1,100 cases of avoided PM2.s-related premature deaths annually in 2020
and between 1,100 and 2,600 avoided premature deaths annually in 2030. When the range of
expert opinion is used, we estimate between 220 and 2,200 fewer premature mortalities in
2020 and between 500 and 4,900 fewer premature mortalities in 2030. Note that in the case
of the premature mortality estimates derived from the expert elicitation, we report the 90%
credible interval, which encompasses a broader representation of uncertainty relative to the
statistical confidence intervals provided for the effect estimates derived from the
epidemiology literature.
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Regulatory Impact Analysis
The range of ozone benefits associated with the final standards is estimated based on
risk reductions estimated using several sources of ozone-related mortality effect estimates.
There is considerable uncertainty in the magnitude of the association between ozone and
premature mortality. This analysis presents four alternative estimates for the association
based upon different functions reported in the scientific literature. We also consider the
possibility that the observed associations between ozone and mortality may not be causal in
nature. EPA has requested advice from the National Academy of Sciences on how best to
quantify uncertainty in the relationship between ozone exposure and premature mortality in
the context of quantifying benefits associated with ozone control strategies.
For ozone-related premature mortality, we estimate a range of between 13 to 62 fewer
premature mortalities as a result of the final rule in 2020 and between 54 to 250 in 2030,
assuming that there is a causal relationship between ozone exposure and mortality. The
increase in annual benefits from 2020 to 2030 reflects additional emission reductions from the
final standards, as well as increases in total population and the average age (and thus baseline
mortality risk) of the population.
Our estimate of total monetized benefits in 2020 for the final standards, using the ACS
and Six-Cities PM mortality studies and the range of ozone mortality assumptions, is between
$3.7 billion and $8.8 billion, assuming a 3 percent discount rate, or between $3.6 billion and
$8.0 billion, assuming a 7 percent discount rate. In 2030, we estimate the monetized benefits
to be between $9.2 billion and $22 billion, assuming a 3 percent discount rate, or between
$8.4 billion and $20 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 benefits categories (see Table 6.4-1). 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 in Table 6.6-2.
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Cost-Benefit Analysis
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 6.6-5 and 6.6-6 present the distributions of the reduction in
PM2.s-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.
The effect estimates of five of the twelve experts included in the elicitation panel fall
within the empirically-derived range provided by the ACS and Six-Cities studies. One of the
experts fall below this range and six of the experts are above this range. 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.
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Regulatory Impact Analysis
Table 6.6-1. Estimated Reduction in Incidence of Adverse Health Effects Related to the
Final Standards21
Health Effect
2020
2030
Mean Incidence Reduction
(5th- 95th %ile)
PM-Related Endpoints
Premature Mortality -
Derived from Epidemiology
Literature
Premature Mortality -
Derived from Expert
Elicitationb
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 etal. 1997
Adult, age 25+ - Lower
Bound (Expert K)
Adult, age 25+ - Upper Bound
(Expert E)
Chronic bronchitis (adult, age 26 and over)
Acute myocardial infarction (adults, age 18 and older)
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 (adults, age 18-65)
Minor restricted-activity days (adults, age 18-65)
490
(190-790)
1,100
(610 - 1,600)
1
(1-2)
220
(0 - 1,100)
2,200
(1,100-3,300)
310
(56 - 560)
1,000
(550 - 1,500)
120
(58 - 170)
240
(150-330)
410
(240 - 580)
1,000
(-35-2,100)
9,200
(4,400 - 14,000)
6,700
(2,100-11,000)
8,400
(920 - 24,000)
59,000
(51,000-67,000)
350,000
(290,000 - 400,000)
1,100
(440 - 1,800)
2,600
(1,400 - 3,700)
2
(1-3)
500
(0 - 2,400)
4,900
(2,500 - 7,500)
680
(130-1,200)
2,500
(1,300-3,600)
270
(130-400)
600
(380 - 820)
890
(520 - 1,300)
2,300
(-77 - 4,600)
20,000
(9,700-31,000)
15,000
(4,600 - 25,000)
19,000
(2,000 - 53,000)
120,000
(110,000-140,000)
720,000
(610,000-830,000)
Ozone-Related Endpoints
Premature Mortality, All ages
- Derived from NMMAPS
Premature Mortality, All ages
- Derived from Meta-analyses
Bell et al., 2004
Bell et al., 2005
Ito etal., 2005
Levy etal., 2005
Premature Mortality - Assumption that association between
13
(-22 - 49)
44
(-47 - 140)
60
(-34 - 150)
62
(-14-138)
0
54
(-43 - 150)
180
(-69 - 420)
240
(-14 - 500)
250
(44 - 450)
0
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Cost-Benefit Analysis
ozone and mortality is not causal
Hospital admissions- respiratory causes (children, under 2;
adult, 65 and older)6
Emergency room visit for asthma (all ages)
Minor restricted activity days (adults, age 18-65)
School absence days
14
(-146 - 170)
69
(-89 - 270)
84,000
(43,000 - 120,000)
33,000
(-17,000 - 77,000)
260
(-350 - 890)
250
(-190-830)
290,000
(150,000-430,000)
110,000
(-15,000 - 240,000)
Incidence is rounded to two significant digits. PM and ozone estimates represent impacts from the
final standards nationwide.
Based on effect estimates derived from the full-scale expert elicitation assessing the uncertainty in the
concentration-response function for PM-related premature mortality (lEc, 2006). The effect estimates of five
of the twelve experts included in the elicitation panel fall within the empirically-derived range provided by the
ACS and Six-Cities studies. One of the experts fall below this range and six of the experts are above this range.
Although the overall range across experts is summarized in this table, 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.
Respiratory hospital admissions for PM include admissions for COPD, pneumonia, and asthma.
Cardiovascular hospital admissions for PM include total cardiovascular and subcategories for
ischemic heart disease, dysrhythmias, and heart failure.
Respiratory hospital admissions for ozone include admissions for all respiratory causes and
subcategories for COPD and pneumonia.
^ Industrial Economics, Incorporated (IEc). 2006. Expanded Expert Judgment Assessment of the
Concentration-Response Relationship Between PM2.5 Exposure and Mortality. Peer Review Draft. Prepared
for: Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle
Park, NC. August.
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Regulatory Impact Analysis
Table 6.6-2. Estimated Monetary Value in Reductions in Incidence of Health and
Welfare Effects (in millions of 2005$fb
PM2 5-Related Health Effect
Premature Mortality -
Derived from
Epidemiology
Studies0'4
Premature mortality -
Derived from Expert
Elicitationc'd'e
Adult, age 30+ - ACS study
(Pope et al., 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)
3% discount rate
7% discount rate
Adult, age 25+ - Lower bound
(Expert K)
3% discount rate
7% discount rate
Adult, age 25+ - Upper bound
(Expert E)
3% discount rate
7% discount rate
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)
2020 2030
Estimated Mean Value of Reductions
(5th and 95th %ile)
$3,400
($8 10 -$7,00)
$3,100
($730 - $6,300)
$7,800
($2,200 -$15,000)
$7,000
($1,900 -$13,000)
$7
($2 -$14)
$7
($2 -$13)
$1,500
($0 - $7,700)
$1,400
($0 - $7,000)
$15,000
($4, 100 -$30,000)
$14,000
($3,700 - $27,000)
$150
($12 -$500)
$110
($34 - $230)
$110
($31 -$230)
$2.1
($1.0 -$3.2)
$6.7
($4.2 - $9.2)
$0.15
($0.08 - $0.23)
$0.08
($0 - $0.2)
$0.18
$8,100
($1,900 -$16,000)
$7,300
($1,700 -$15,000)
$18,000
($5,100 -$35,000)
$17,000
($4,600 - $32,000)
$13
($3.5 - $26)
$12
($3.1 -$23)
$3,600
($0-$ 18,000)
$3,200
($0-$ 16,000)
$36,000
($9,500 - $70,000)
$32,000
($8,600 - $63,000)
$340
($28 - $1,100)
$260
($74 - $550)
$250
($69 - $540)
$4.9
($2.4 - $7.3)
$17
($11 -$23)
$0.33
($0.18 -$0.49)
$0.17
($0 - $0.42)
$0.40
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Cost-Benefit Analysis
Upper respiratory symptoms (asthma, 9-11)
Asthma exacerbations
Work loss days
Minor restricted-activity days (MRADs)
Recreational Visibility, 86 Class I areas
($0.07 - $0.33)
$0.21
($0.06 - $0.46)
$0.45
($0.05 -$1.3)
$8.9
($7.7 - $10)
$22
($13 -$32)
$
(na)f
($0.15 -$0.73)
$0.46
($0.13 -$1.0)
$1.0
($0.11 -$2.9)
$18
($16 -$21)
$46
($27 - $66)
$
(na)
Ozone-related Health Effect
Premature Mortality, All
ages - Derived from
NMMAPS
Premature Mortality, All
ages - Derived from Meta-
analyses
Bell et al., 2004
Bell etal., 2005
Ito et al., 2005
Levy et al., 2005
Premature Mortality - Assumption that association between
ozone and mortality is not causal
Hospital admissions- respiratory causes (children, under 2;
adult, 65 and older)
Emergency room visit for asthma (all ages)
Minor restricted activity days (adults, age 18-65)
School absence days
Worker Productivity
$100
(-$170 -$420)
$340
(-$360 - $1,200)
$460
(-$260 - $1,400)
$480
(-$110 -$1,300)
$0
-$0.54
(-$4.6 -$3.3)
$0.03
(-$0.03 -$0.1)
$2.5
(-$4.0 - $9.9)
$2.9
(-$1.5 -$6.8)
$0.53
(na)f
$440
(-$340 -$1,400)
$1,400
(-$550 - $3,900)
$1,900
(-$120 -$4,700)
$2,000
($280 - $4,400)
$0
$2.7
(-$11 -$17)
$0.09
(-$0.07 - $0.30)
$8.8
(-$7.8 - $28)
$11
(-$1.3 -$21)
$2.9
(na)f
Monetary benefits are rounded to two significant digits for ease of presentation and computation. PM
and ozone benefits are nationwide.
Monetary benefits adjusted to account for growth in real GDP per capita between 1990 and the
analysis year (2020 or 2030)
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).
The valuation of adult premature mortality, derived either from the epidemiology literature or the
expert elicitation, is not additive. Rather, the valuations represent a range of possible mortality benefits.
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Regulatory Impact Analysis
Based on effect estimates derived from the full-scale expert elicitation assessing the uncertainty in the
T3T3
concentration-response function for PM-related premature mortality (lEc, 2006). The effect estimates of five
of the twelve experts included in the elicitation panel fall within the empirically-derived range provided by the
ACS and Six-Cities studies. One of the experts fall below this range and six of the experts are above this range.
Although the overall range across experts is summarized in this table, 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.
We are unable at this time to characterize the uncertainty in the estimate of benefits of worker
productivity and improvements in visibility at Class I areas. As such, we treat these benefits as fixed and add
them to all percentiles of the health benefits distribution.
Table 6.6-3 Total Monetized Benefits of the Final Locomotive and Marine Engine Rule
3% Discount Rate
Total Ozone and PM Benefits (billions, 2006$) -
PM Mortality Derived from Epidemiology Studies (ACS and Six Cities)
2020
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Assumption that
not causal
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
association is
Mean Total
Benefits
$4.0 to $8.4
$4.2 to $8.6
$4.4 to $8.8
$4.4 to $8.8
$3. 9 to $8.3
2030
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
Assumption that association is
not causal
Mean Total
Benefits
$9.7 to $20
$11 to $21
$11 to $21
$11 to $22
$9.2 to $20
Total Ozone and PM Benefits (billions, 2006$) -
PM Mortality Derived from Expert Elicitation (Lowest and Highest Estimate)
2020
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
Mean Total
Benefits
$2. Ito $16
$2.4 to $16
$2.5 to $16
$2.5 to $16
2030
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
Mean Total
Benefits
$5.2 to $37
$6.2 to $38
$6.7 to $39
$6.7 to $39
BB Industrial Economics, Incorporated (IEc). 2006. Expanded Expert Judgment Assessment of the
Concentration-Response Relationship Between PM2.5 Exposure and Mortality. Peer Review Draft. Prepared
for: Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle
Park, NC. August.
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Cost-Benefit Analysis
Assumption that association is $2.0 to $ 16
not causal
Assumption that association is $4.7 to $37
not causal
Table 6.6-4 Total Monetized Benefits of the Final Locomotive and Marine Engine Rule
7% Discount Rate
Total Ozone and PM Benefits (billions, 2006$) -
PM Mortality Derived from Epidemiology Studies (ACS and Six Cities)
2020
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Assumption that
not causal
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
association is
Mean Total
Benefits
$3. 7 to $7.6
$3. 9 to $7.9
$4.0 to $8.0
$4.0 to $8.0
$3.6 to $7.5
2030
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
Assumption that association is
not causal
Mean Total
Benefits
$8.9 to $18
9.8 to $19
$10 to $20
$10 to $20
$8.4 to $18
Total Ozone and PM Benefits (billions, 2006$) -
PM Mortality Derived from Expert Elicitation (Lowest and Highest Estimate)
2020
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Assumption that
not causal
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
association is
Mean Total
Benefits
$2.0 to $14
$2.2 to $15
$2.3 to $15
$2.3 to $15
$1.9 to $14
2030
Ozone
Mortality
Function
NMMAPS
Meta-analysis
Assumption that
not causal
Reference
Belletal.,
2004
Belletal.,
2005
Ito et al., 2005
Levy etal.,
2005
association is
Mean Total
Benefits
$4.8 to $34
$5. 8 to $35
$6.3 to $35
$6.4 to $35
$4.4 to $33
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Regulatory Impact Analysis
Table 6.6-5. Results of Application of Expert Elicitation: Annual Reductions in
Premature Mortality in 2020 Associated with the Final Standards
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
190
610
320
180
240
190
1,100
840
0
4
210
310
0
150
Mean
490
1,100
1,700
1,300
1,300
920
2,200
1,200
770
980
1,300
1,100
220
930
95th Percentile
790
1,600
3,200
2,800
2,800
1,500
3,300
1,700
1,400
2,300
2,300
2,300
1,100
1,800
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Cost-Benefit Analysis
Table 6.6-6. Results of Application of Expert Elicitation: Annual Reductions in
Premature Mortality in 2030 Associated with the Final Standards
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
440
1,400
730
410
540
440
2,500
1,900
0
8
470
720
0
340
Mean
1,100
2,600
4,000
3,000
3,000
2,100
4,900
2,700
1,800
2,200
3,000
2,400
500
2,100
95th Percentile
1,800
3,700
7,200
6,500
6,500
3,400
7,500
3,900
3,200
5,100
5,300
5,300
2,400
4,000
6.7 Comparison of Costs and Benefits
In estimating the net benefits of the final standards, the appropriate cost measure is
'social costs.' Social costs represent the welfare costs of a rule to society. These costs do not
consider transfer payments (such as taxes) that are simply redistributions of wealth. Table
6.7-1 contains the estimates of monetized benefits and estimated social welfare costs for the
final rule and each of the final control programs. The annual social welfare costs of all
provisions of this final rule are described more fully in Chapter 7 of this RIA.
The results in Table 6.7-1 suggest that the 2020 monetized benefits of the final
standards are greater than the expected social welfare costs. Specifically, the annual benefits
of the total program will range between $3.9 to $8.8 billion annually in 2020 using a three
percent discount rate,or between $3.6 to $8.0 billion assuming a 7 percent discount rate,
compared to estimated social costs of approximately $330 million in that same year. These
benefits are expected to increase to between $9.2 and $22 billion annually in 2030 using a
three percent discount rate,or between $8.4 and $20 billion assuming a 7 percent discount
rate, while the social costs are estimated to be approximately $740 million. Though there are
a number of health and environmental effects associated with the final standards that we are
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Regulatory Impact Analysis
unable to quantify or monetize (see Table 6.4-1), the benefits of the final standards far
outweigh the projected costs.
Using the most conservative benefits estimate, the 2020 benefits outweigh the costs by
a factor of 10. Using the upper end of the benefits range, the benefits could outweigh the
costs by a factor of 25. Likewise, in 2030 benefits outweigh the costs by at least a factor of
10 and could be as much as a factor of 28. Thus, even taking the most conservative benefits
assumptions, benefits of the final standards clearly outweigh the costs.
Table 6.7-1. Summary of Annual Benefits and Costs of the Final Standards3
(Millions of 2006 dollars)
Description
Estimated Social Costs
Locomotive
Marine
Total Social Costs
Estimated Health Benefits of the Final Standards0' 'e'
Locomotive
3 percent discount rate
7 percent discount rate
Marine
3 percent discount rate
7 percent discount rate
Total Benefits
3 percent discount rate
7 percent discount rate
Annual Net Benefits (Total Benefits - Total Costs)
3 percent discount rate
7 percent discount rate
2020
(Millions of 2006 dollars)
$200
$140
$330
$2,000 to $4,400
$1,900 to $4,000
$1,900 to $4,400
$1,700 to $4,000
$3,900 to $8,800
$3,600 to $8,000
$3,600 to $8,500
$3,300 to $7,700
2030
(Millions of 2006
dollars)
$460
$280
$740
$4,300 to $11,000
$4,000 to $10,000
$4,900 to $11, 000
$4,400 to $10,000
$9,200 to $22,000
$8,400 to $20,000
$8,500 to $21,000
$7,700 to $19,000
All estimates represent annualized benefits and costs anticipated for the years 2020 and 2030. Totals
may not sum due to rounding.
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 do 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.
c Total includes ozone and PM2 5 benefits. Range was developed by adding the estimate from the ozone
premature mortality function, including an assumption that the association is not causal, to both estimates of
PM2 s-related premature mortality derived from the ACS (Pope et al., 2002) and Six-Cities (Laden et al., 2006)
studies, respectively.
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Cost-Benefit Analysis
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 (US EPA, 2000 and OMB, 2003).CC'DD
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).
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 6.4-1.
CCU.S. Environmental Protection Agency, 2000. Guidelines for Preparing Economic Analyses.
www.vosemite 1 .epa.gov/ee/epa/eed/hsf/pages/Guideline.html.
Office of Management and Budget, The Executive Office of the President, 2003. Circular A-4.
http://www.whitehouse.gov/omb/circulars.
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Regulatory Impact Analysis
Appendix 6A: Health-Based Cost Effectiveness Analysis
Health-based cost-effectiveness analysis (CEA) and cost-utility analysis (CUA) have
been used to analyze numerous health interventions but have not been widely adopted as tools
to analyze environmental policies. The Office of Management and Budget (OMB) recently
issued Circular A-4 guidance on regulatory analyses, requiring federal agencies to "prepare a
CEA for all major rulemakings for which the primary benefits are improved public health and
safety to the extent that a valid effectiveness measure can be developed to represent expected
health and safety outcomes." Environmental quality improvements may have multiple health
and ecological benefits, making application of CEA more difficult and less straightforward.
For the recently finalized PM NAAQS analysis, CEA provided a useful framework for
evaluation: non-health benefits were substantial, but the majority of quantified benefits came
from health effects. EPA included in the PM NAAQS RIA a preliminary and experimental
application of one type of CEAa modified quality-adjusted life-years (QALYs) approach.
A detailed description of this QALY approach is provided in Appendix G of the final PM
NAAQS RIA. For the analysis presented here, we use the same modified QALY approach to
characterize the health-based cost effectiveness of the final standards.
QALYs were developed to evaluate the effectiveness of individual medical treatments,
and EPA is still evaluating the appropriate methods for CEA of environmental regulations.
Agency concerns with the standard QALY methodology include the treatment of people with
fewer years to live (the elderly); fairness to people with preexisting conditions that may lead
to reduced life expectancy and reduced quality of life; and how the analysis should best
account for nonhealth benefits, such as improved visibility.
The Institute of Medicine (a member institution of the National Academies of Science)
established the Committee to Evaluate Measures of Health Benefits for Environmental,
Health, and Safety Regulation to assess the scientific validity, ethical implications, and
practical utility of a wide range of effectiveness measures used or proposed in CEA. This
committee prepared a report titled "Valuing Health for Regulatory Cost-Effectiveness
Analysis," which concluded that CEA is a useful tool for assessing regulatory interventions to
promote human health and safety, although not sufficient for informed regulatory decisions
(Miller, Robinson, and Lawrence, 2006).63 They emphasized the need for additional data and
methodological improvements for CEA analyses, and urged greater consistency in the
reporting of assumptions, data elements, and analytic methods. They also provided a number
of recommendations for the conduct of regulatory CEA analyses. EPA is evaluating these
recommendations and will determine a response for upcoming analyses.
The methodology derived from the final PM NAAQS analysis is not intended to stand
as precedent either for future air pollution regulations or for other EPA regulations where it
may be inappropriate. It is intended solely to demonstrate one particular approach to
estimating the cost-effectiveness of reductions in ambient PM2.5 in achieving improvements in
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Cost-Benefit Analysis
public health. Reductions in ambient PM2.5 likely will have other health and environmental
benefits that will not be reflected in this CEA. Other EPA regulations affecting other aspects
of environmental quality and public health may require additional data and models that may
preclude the development of similar health-based CEAs. A number of additional
methodological issues must be considered when conducting CEAs for environmental policies,
including treatment of nonhealth effects, aggregation of acute and long-term health impacts,
and aggregation of life extensions and quality-of-life improvements in different populations.
The appropriateness of health-based CEA should be evaluated on a case-by-case basis subject
to the availability of appropriate data and models, among other factors.
The final locomotive and marine standards are expected to result in substantial
reductions in potential population exposure to ambient concentrations of PM by 2030. The
benefit-cost analysis presented in Chapter 6 of the RIA shows that the standards will achieve
substantial health benefits whose monetized value far exceeds costs (net benefits are between
$8.5 and $21 billion in 2030, based on empirically derived estimates of PM mortality and
using a 3 percent discount rate). Despite the risk of oversimplifying benefits, cautiously-
interpreted cost-effectiveness calculations may provide further evidence of whether the costs
associated with the final standards are a reasonable health investment for the nation.
This analysis provides estimates of commonly used health-based effectiveness
measures, including lives saved, life years saved (from reductions in mortality risk), and
QALYs saved (from reductions in morbidity risk) associated with the reduction of ambient
PM2.5 due to the final standards. In addition, we use an alternative aggregate effectiveness
metric, Morbidity Inclusive Life Years (MILY) to address some of the concerns about
aggregation of life extension and quality-of-life impacts. It represents the sum of life years
gained due to reductions in premature mortality and the QALY gained due to reductions in
chronic morbidity. This measure may be preferred to existing QALY aggregation approaches
because it does not devalue life extensions in individuals with preexisting illnesses that reduce
quality of life. However, the MILY measure is still based on life years and thus still
inherently gives more weight to interventions that reduce mortality and morbidity impacts for
younger populations with higher remaining life expectancy. This analysis focuses on life
extensions and improvements in quality of life through reductions in two diseases with
chronic impacts: chronic bronchitis (CB) and nonfatal acute myocardial infarctions. Monte
Carlo simulations are used to propagate uncertainty in several analytical parameters and
characterize the distribution of estimated impacts. While the benefit-cost analysis presented
in the RIA characterizes mortality impacts using a number of different sources for the PM
mortality effect estimate, for this analysis, we focus on the mortality results generated using
the effect estimate derived from the Pope et al. (2002) study.
Presented in three different metrics, the analysis suggests the following:
In 2020, the locomotive and marine standards will result in:
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Regulatory Impact Analysis
490(95%CI: 190 - 790) premature PM-related deaths avoided, or
5,500 (95% CI: 2,100 - 8,800) PM-related life years gained (discounted at 3
percent), or
7,800 (95% CI: 2,600 - 14,000) MILYs gained (discounted at 3 percent).
In 2030, the final standards will result in:
1,100 (95% CI: 4400 - 1,800) premature PM-related deaths avoided, or
12,000 (95% CI: 4,800 - 20,000) PM-related life years gained (discounted at 3
percent), or
17,000 (95% CI: 5,700 - 31,000) MILYs gained (discounted at 3 percent).
Using a 7 percent discount rate, mean discounted life years gained are 4,100 for the
final standards in 2020 and 9,300 in 2030; mean MILYs gained are 5,800 in 2020 and
13,000 in 2030. (The estimates of premature deaths avoided are not affected by the
discount rate.)
The associated reductions in CB and nonfatal acute myocardial infarctions will reduce
medical costs by approximately $150 million in 2020 and $340 million in 2030 based
on a 3 percent discount rate, or $130 million in 2020 and $300 million in 2030 based
on a 7 percent discount rate.
Other health and visibility benefits are valued at $210 million in 2020 and $490
million in 2030.
Direct private compliance costs for the final standards are $340 million in 2020 and $750
million in 2030 (see Chapter 7 of this RIA for more discussion of the cost estimates).
Therefore, the net costs (private compliance costs minus avoided cost of illness minus other
benefits) are negative, indicating that the final standards result in cost savings. As such,
traditional cost-effectiveness ratios are not informative. However, it is possible to calculate
the maximum costs for the rule that would still result in cost-effective improvements in public
health compared with standard benchmarks of $50,000 and $100,000 per MILY:
Taking into account avoided medical costs and other benefits, annual costs of the final
standards would need to exceed $750 million (95% CI: $360 million - $1,200 million) in
2020 and $1.7 billion (95% CI: $0.8 billion - $2.8 billion) in 2030 to have a cost per
MILY that exceeds a benchmark of $50,000, based on a 3 percent discount rate.
Annual costs of the final standards would need to exceed $1.1 billion (95% CI: $0.5
billion - $1.9 billion) in 2020 and $2.6 billion (95% CI: $1.1 billion - $4.3 billion) in
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Cost-Benefit Analysis
2030 to have a cost per MILY that exceeds a benchmark of $100,000, based on a 3
percent discount rate.
Using a 7 percent discount rate, annual costs of the final standards would need to exceed
$630 million in 2020 and $1.4 billion in 2030 to have a cost per MILY that exceeds a
benchmark of $50,000, and would need to exceed $0.9 billion in 2020 and $2.1 billion in
2030 to have a cost per MILY that exceeds a benchmark of $100,000.
Given costs of $340 million and $750 million in 2020 and 2030, respectively, the
locomotive and marine standards are clearly a very cost-effective way to achieve
improvements in public health.
Tables 6.A-1 through 6.A-9 present the intermediate and summary results of the
health-based CEA of the final standards. Note that the methods used to generate these
estimates follow the same methods as those explained in Appendix G of the final PM NAAQS
RIA. We refer the reader to that document for more details about this modified QALY
approach to health-based CEA.
Table 6.A-1: Estimated Reduction in Incidence of All-cause Premature Mortality Associated with the
Final Standards in 2020 and 2030
Age Interval
30-34
35-44
45-54
55-64
65-74
75-84
85+
Total
Reduction in All-Cause Premature Mortality
(95% CI)
2020
4
(2-7)
13
(5-21)
26
(10-43)
65
(25-105)
106
(41-170)
120
(48-200)
150
(59-240)
490
(190-790)
2030
8
(3-13)
26
(10-42)
47
(18-75)
110
(44-180)
250
(98-400)
350
(140-550)
340
(130-540)
1,100
(440-1,800)
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Regulatory Impact Analysis
Table 6.A-2: Estimated Life Years Gained from All-cause Premature Mortality Risk Reductions
Associated with the Final Standards in 2020 and 2030
Age Interval
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total
Life Years Gained from Mortality Risk Reduction, 3% Discount Rate
(95% CI)
2020
120
(45-190)
330
(130-530)
580
(230-930)
1,200
(470-1,900)
1,500
(600-2,400)
1,200
(460-1,900)
600
(230-960)
5,500
(2,100-8,800)
2030
210
(83-340)
650
(260-1,100)
1,000
(400-1,600)
2,000
(800-3,300)
3,500
(1,400-5,700)
3,400
(1,300-5,400)
1,300
(520-2,100)
12,000
(4,800-20,000)
Table 6.A-3: Estimated Reduction in Incidence of Chronic Bronchitis Associated with the Final
Standards in 2020 and 2030
Age Interval
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total
Reduction in Incidence (95% Confidence Interval)
2020
57
(10-100)
62
(11-110)
58
(11-110)
59
(11-110)
41
(8-74)
20
(4-37)
9
(2-16)
310
(56-560)
2030
120
(21-210)
140
(26-250)
120
(22-210)
110
(21-210)
110
(19-190)
62
(12-110)
22
(4-39)
680
(130-1,200)
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Cost-Benefit Analysis
Table 6.A-4: QALYs Gained per Avoided Incidence of CB
Age Interval
Start Age
25
35
45
55
65
75
85+
End Age
34
44
54
64
74
84
QALYs Gained per Incidence
Undiscounted
12.15
(4.40-19.95)
9.91
(3.54-16.10)
7.49
(2.71-12.34)
5.36
(1.95-8.80)
3.40
(1.22-5.64)
2.15
(0.77-3.49)
0.79
(0.27-1.29)
Discounted (3%)
6.52
(2.36-10.71)
5.94
(2.12-9.66)
5.03
(1.82-8.29)
4.03
(1.47-6.61)
2.84
(1.02-4.71)
1.92
(0.69-3.13)
0.77
(0.26-1.25)
Table 6.A-5: Estimated Reduction in Nonfatal Acute Myocardial Infarctions Associated with the Final
Standards in 2020 and 2030
Age Interval
18-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total
Reduction in Incidence (95% Confidence Interval)
2020
1
(0-1)
1
(0-1)
33
(18-48)
100
(56-150)
250
(130-360)
290
(160-430)
220
(120-320)
120
(64-170)
1,000
(550-1,500)
2030
1
(1-2)
1
(1-2)
73
(40-110)
210
(110-310)
470
(260-690)
760
(410-1,100)
670
(360-970)
290
(160-430)
2,500
(1,300-3,600)
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Regulatory Impact Analysis
Table 6.A-6: QALYs Gained per Avoided Nonfatal Myocardial Infarction
Age Interval
Start Age
18
25
35
45
55
65
75
85+
End Age
24
34
44
54
64
74
84
QALYs Gained per Incidence
Undiscounted
4.18
(1.24-7.09)
3.48
(1.09-5.87)
2.81
(0.88-4.74)
2.14
(0.67-3.61)
1.49
(0.42-2.52)
0.97
(0.30-1.64)
0.59
(0.20-0.97)
0.32
(0.13-0.50)
Discounted (3%)
2.17
(0.70-3.62)
2.00
(0.68-3.33)
1.79
(0.60-2.99)
1.52
(0.51-2.53)
1.16
(0.34-1.95)
0.83
(0.26-1.39)
0.54
(0.19-0.89)
0.31
(0.13-0.49)
Table 6.A-7. Estimated Gains in 3 Percent Discounted MILYs Associated with the Final Standards in
2020a
Age
18-24
25-34
35-44
45-54
55-64
65-74
Life Years Gained
from Mortality Risk
Reductions
(95% CI)
-
120
(45-190)
330
(130-530)
580
(230-930)
1,200
(470-1,900)
1,500
QALY Gained from
Reductions in Chronic
Bronchitis
(95% CI)
-
370
(52-850)
370
(50-870)
290
(41-700)
240
(32-560)
120
QALY Gained from
Reductions in Acute
Myocardial Infarctions
(95% CI)
1
(0-3)
1
(0-2)
58
(15-120)
160
(40-320)
280
(70-570)
240
Total Gain in
MILYs
(95% CI)
1
(0-3)
490
(97-1,100)
750
(190-1,500)
1,000
(310-1,900)
1,700
(570-3,000)
1,800
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75-84
85+
Total
(580-2.400)
1,200
(460-1,900)
600
(230-960)
5,500
(2,100-8,800)
(16-280)
39
(5-92)
7
(1-18)
1,400
(200-3,400)
(53-490)
120
(31-230)
35
(10-69)
880
(230-1,800)
(660-3,200)
1,300
(500-2,200)
640
(250-1,000)
7,800
(2,600-14,000)
Note that all estimates have been rounded to two significant digits.
Table 6.A-8: Estimated Gains in 3 Percent Discounted MILYs Associated with the Final Standards in
2030a
Age
18-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total
Life Years Gained
from Mortality Risk
Reductions
(95% CI)
-
210
(83-340)
650
(260-1,100)
1,000
(400-1,600)
2,000
(800-3,300)
3,500
(1,400-5,700)
3,400
(1,300-5,400)
1,300
(520-2,100)
12,000
(4,800-20,000)
QALY Gained from
Reductions in
Chronic Bronchitis
(95% CI)
-
760
(110-1,800)
820
(110-2,000)
600
(82-1,400)
460
(63-1,100)
300
(42-710)
120
(16-290)
16
(2-39)
3,100
(420-7,200)
QALY Gained from
Reductions in Acute
Myocardial Infarctions
(95% CI)
o
5
(1-5)
2
(1-5)
130
(34-260)
310
(80-640)
530
(130-1,100)
620
(160-1,300)
350
(94-710)
86
(25-170)
2,000
(530-4,100)
Total Gain in
MILYs
(95% CI)
3
(1-5)
970
(190-2,100)
1,600
(400-3,300)
1,900
(560-3,700)
3,000
(1,000-5,400)
4,500
(1,600-7,700)
3,800
(1,400-6,400)
1,400
(550-2,400)
17,000
(5,700-31,000)
Note that all estimates have been rounded to two significant digits.
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Regulatory Impact Analysis
Table 6.A-9: Summary of Health-Based Cost Effectiveness Results for the Final Standards in 2020 and
2030a
Life years gained from mortality
risk reductions
QALY gained from reductions in
chronic bronchitis
QALY gained from reductions in
acute myocardial infarctions
Total gain in MILYs
Avoided cost of illness
Chronic bronchitis
Nonfatal AMI
Other benefits (based on COI and
WTP estimates)
Implementation strategy costs'3
Net cost per MILY
Result Using 3% Discount Rate (95% Confidence Interval)
2020
5,500
(2,100-8,800)
1,400
(200-3,400)
880
(230-1,800)
7,800
(2,600-14,000)
$37 Million
($6.9 - $68 Million)
$110 Million
($29 - $250 Million)
$210 Million
($190 -$220 Million)
$340 Million
Cost Savings
2030
12,000
(4,800-20,000)
3,100
(420-7,200)
2,000
(530-4,100)
17,000
(5,700-31,000)
$78 Million
($14 -$140 Million)
$260 Million
($64 - $580 Million)
$490 Million
($460 - $520 Million)
$750 Million
Cost Savings
All summary results are reported at a precision level of two significant digits to reflect limits in the
precision of the underlying elements.
Costs are the private firm costs of control, as discussed in Chapter 7, and reflect discounting using firm
specific costs of capital.
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Appendix 6.B: Sensitivity Analyses of Key Parameters in the Benefits Analysis
The primary analysis presented in Chapter 6 is based on our current interpretation of
the scientific and economic literature. That interpretation requires judgments regarding the
best available data, models, and modeling methodologies and the assumptions that are most
appropriate to adopt in the face of important uncertainties and resource limitations. The
majority of the analytical assumptions used to develop the primary estimates of benefits have
been used to support similar rulemakings and approved by EPA=s Science Advisory Board
(SAB). Both EPA and the SAB recognize that data and modeling limitations as well as
simplifying assumptions can introduce significant uncertainty into the benefit results and that
alternative choices exist for some inputs to the analysis, such as the mortality C-R functions.
This appendix supplements our primary estimates of benefits with a series of
sensitivity calculations that use other sources of health effect estimates and valuation data for
key benefits categories. The supplemental estimates examine sensitivity to both valuation
issues and for physical effects issues. These supplemental estimates are not meant to be
comprehensive. Rather, they reflect some of the key issues identified by EPA or commentors
as likely to have a significant impact on total benefits. The individual adjustments in the
tables should not simply be added together because: 1) there may be overlap among the
alternative assumptions; and 2) the joint probability among certain sets of alternative
assumptions may be low.
6.B.1 Premature Mortality - Alternative Threshold Analysis
To consider the impact of a threshold in the response function for the chronic
mortality endpoint, we have constructed a sensitivity analysis by assigning different cutpoints
below which changes in PM2.5 are assumed to have no impact on premature mortality. In
applying the cutpoints, we have adjusted the mortality function slopes accordingly. Five
cutpoints (including the base case assumption) were included in the sensitivity analysis: (a) 14
|ig/m3 (assumes no impacts below the alternative annual NAAQS), (b) 12 |ig/m3 (c) 10
|ig/m3 (reflects comments from CASAC, 2005) 64, (d) 7.5 |ig/m3 (reflects recommendations
from SAB-HES to consider estimating mortality benefits down to the lowest exposure levels
considered in the Pope 2002 study used as the basis for modeling chronic mortality) 65 and (e)
background or 3 |ig/m3 (reflects NRC recommendation to consider effects all the way to
background).66 We repeat this sensitivity analysis for the RIA of the final standards, the
results of which can be found in Table 6B-1.
Note that this analysis only adjusted the mortality slopes for the 10 ug/m3, 12 ug/m3 and 14 ug/m3 cutpoints
since the 7.5 ug/m3 and background cutpoints were at or below the lowest measured exposure levels reported in
the Pope et al. (2002) study for the combined exposure dataset.
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Regulatory Impact Analysis
Table 6B-1. PM-Related Mortality Benefits of the Final Standards: Cutpoint Sensitivity
Analysis Using the ACS Study (Pope et al., 2002)a
Certainty that Benefits
are At Least Specified
Value
More C
Benefits
as
^
LessC
Benefits
as
:ert,
Are
Lar
V
ertฃ
Are
Lar
ain that
at Least
ge
7
dn that
at Least
ge
Level of
Assumed
Threshold
14 ug/m3 b
12 ug/m3
10 ug/m3 c
7.5 ug/m3
3 ug/m3
PM Mortality Incidence
2020
140
200
490
600
640
2030
320
490
1,100
1,400
1,500
' Note that this table only presents the effects of a cutpoint on PM-related mortality incidence.
' Alternative annual PM NAAQS.
c Primary threshold assumption based on
d SAB-HES (2004)8
e NAS (2002)87
CASAC (2005).
6.B.2 Premature Mortality - Alternative Lag Structures
Over the last ten years, there has been a continuing discussion and evolving advice
regarding the timing of changes in health effects following changes in ambient air pollution.
It has been hypothesized that some reductions in premature mortality from exposure to
ambient PM2.5 will occur over short periods of time in individuals with compromised health
status, but other effects are likely to occur among individuals who, at baseline, have
reasonably good health that will deteriorate because of continued exposure. No animal
models have yet been developed to quantify these cumulative effects, nor are there
epidemiologic studies bearing on this question.
The SAB-HES has recognized this lack of direct evidence. However, in early advice,
they also note that "although there is substantial evidence that a portion of the mortality effect
of PM is manifest within a short period of time, i.e., less than one year, it can be argued that,
if no lag assumption is made, the entire mortality excess observed in the cohort studies will be
analyzed as immediate effects, and this will result in an overestimate of the health benefits of
improved air quality. Thus some time lag is appropriate for distributing the cumulative
mortality effect of PM in the population," (EPA-SAB-COUNCIL-ADV-00-001, 1999, p. 9).67
In recent advice, the SAB-HES suggests that appropriate lag structures may be developed
based on the distribution of cause-specific deaths within the overall all-cause estimate (EPA-
SAB-COUNCIL-ADV-04-002, 2004). They suggest that diseases with longer progressions
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Cost-Benefit Analysis
should be characterized by longer-term lag structures, while air pollution impacts occurring in
populations with existing disease may be characterized by shorter-term lags.
A key question is the distribution of causes of death within the relatively broad
categories analyzed in the long-term cohort studies. Although it may be reasonable to assume
the cessation lag for lung cancer deaths mirrors the long latency of the disease, it is not at all
clear what the appropriate lag structure should be for cardiopulmonary deaths, which include
both respiratory and cardiovascular causes. Some respiratory diseases may have a long period
of progression, while others, such as pneumonia, have a very short duration. In the case of
cardiovascular disease, there is an important question of whether air pollution is causing the
disease, which would imply a relatively long cessation lag, or whether air pollution is causing
premature death in individuals with preexisting heart disease, which would imply very short
cessation lags.
The SAB-HES provides several recommendations for future research that could
support the development of defensible lag structures, including using disease-specific lag
models and constructing a segmented lag distribution to combine differential lags across
causes of death (EPA-SAB-COUNCIL-ADV-04-002, 2004). The SAB-HES indicated
support for using "a Weibull distribution or a simpler distributional form made up of several
segments to cover the response mechanisms outlined above, given our lack of knowledge on
the specific form of the distributions," (EPA-SAB-COUNCIL-ADV-04-002, 2004, p. 24).
However, they noted that "an important question to be resolved is what the relative
magnitudes of these segments should be, and how many of the acute effects are assumed to be
included in the cohort effect estimate," (EPA-SAB-COUNCIL-ADV-04-002, 2004, p. 24-25).
Since the publication of that report in March 2004, EPA has sought additional clarification
from this committee. In its follow-up advice provided in December 2004, the SAB suggested
that until additional research has been completed, EPA should assume a segmented lag
structure characterized by 30 percent of mortality reductions occurring in the first year, 50
percent occurring evenly over years 2 to 5 after the reduction in PM2 5, and 20 percent
occurring evenly over the years 6 to 20 after the reduction in PM2.5
(EPA-COUNCIL-LTR-05-001, 2004).68 The distribution of deaths over the latency period is
intended to reflect the contribution of short-term exposures in the first year, cardiopulmonary
deaths in the 2- to 5-year period, and long-term lung disease and lung cancer in the 6- to 20-
year period. Furthermore, in their advisory letter, the SAB-HES recommended that EPA
include sensitivity analyses on other possible lag structures. In this appendix, we investigate
the sensitivity of premature mortality-reduction related benefits to alternative cessation lag
structures, noting that ongoing and future research may result in changes to the lag structure
used for the primary analysis.
In previous advice from the SAB-HES, they recommended an analysis of 0-, 8-, and
15-year lags, as well as variations on the proportions of mortality allocated to each segment in
the segmented lag structure (EPA-SAB-COUNCIL-ADV-00-001, 1999,
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Regulatory Impact Analysis
(EPA-COUNCIL-LTR-05-001, 2004). The 0-year lag is representative of EPA=s assumption
in previous RIAs. The 8- and 15-year lags are based on the study periods from the Pope et al.
(1995)69 and Dockery et al. (1993)70 studies, respectively.FF However, neither the Pope et al.
nor Dockery et al. studies assumed any lag structure when estimating the relative risks from
PM exposure. In fact, the Pope et al. and Dockery et al. analyses do not support or refute the
existence of a lag. Therefore, any lag structure applied to the avoided incidences estimated
from either of these studies will be an assumed structure. The 8- and 15-year lags implicitly
assume that all premature mortalities occur at the end of the study periods (i.e., at 8 and 15
years).
In addition to the simple 8- and 15-year lags, we have added two additional sensitivity
analyses examining the impact of assuming different allocations of mortality to the segmented
lag of the type suggested by the SAB-HES. The first sensitivity analysis assumes that more of
the mortality impact is associated with chronic lung diseases or lung cancer and less with
acute cardiopulmonary causes. This illustrative lag structure is characterized by 20 percent of
mortality reductions occurring in the first year, 50 percent occurring evenly over years 2 to 5
after the reduction in PM2.5, and 30 percent occurring evenly over the years 6 to 20 after the
reduction in PM2.5. The second sensitivity analysis assumes the 5-year distributed lag
structure used in previous analyses, which is equivalent to a three-segment lag structure with
50 percent in the first 2-year segment, 50 percent in the second 3-year segment, and 0 percent
in the 6- to 20-year segment.
The estimated impacts of alternative lag structures on the monetary benefits associated
with reductions in PM-related premature mortality (estimated with the Pope et al. ACS impact
function) are presented in Table 6B-2. These estimates are based on the value of statistical
lives saved approach (i.e., $5.5 million per incidence) and are presented using both a 3 percent
and 7 percent discount rate over the lag period.
FF Although these studies were conducted for 8 and 15 years, respectively, the choice of the duration of the study
by the authors was not likely due to observations of a lag in effects but is more likely due to the expense of
conducting long-term exposure studies or the amount of satisfactory data that could be collected during this time
period.
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Table 6B-2. Sensitivity of Benefits of Premature Mortality Reductions to Alternative Lag Assumptions
(Relative to Primary Benefits Estimates of the Final Standards)
Avoided Incidences Value
(ACS; Pope et al., 2002)a (million 2006$)b
Description of Sensitivity Analysis 2020 2030 2020 2030
Alternative Lag Structures for PM-Related Premature Mortality
30 percent of incidences occur in 1st
year, 50 percent in years 2 to 5, and
Primary 20 percent in years 6 to 20
3% Discount Rate 490 1,100 $3,400 $8,100
7% Discount Rate 490 1,100 $3,100 $7,300
None Incidences all occur in the first year 490 1,100 $3,800 $8,900
8-year Incidences all occur in the 8th year
3% Discount Rate 490 1,100 $3,100 $7,300
7% Discount Rate 490 1,100 $2,400 $5,600
15-year Incidences all occur in the 15th year
3% Discount Rate 490 1,100 $2,500 $5,900
7% Discount Rate 490 1,100 $1,500 $3,500
20 percent of incidences occur in 1st
Alternative year, 50 percent in years 2 to 5, and
Segmented 30 percent in years 6 to 20
3% Discount Rate 490 1,100 $3,300 $7,800
7% Discount Rate 490 1,100 $2,900 $6,800
50 percent of incidences occur in
5-Year years 1 and 2 and 50 percent in years
Distributed 2 to 5
3% Discount Rate 490 1,100 $3,600 $8,500
7% Discount Rate 490 1,100 $3,400 $8,000
a Incidences rounded to two significant digits.
Dollar values rounded to two significant digits. The alternative lag structure analysis presents benefits
calculated using both a 3 percent and 7 percent discount rate.
The results of the scaled alternative lag sensitivity analysis demonstrate that choice of
lag structure can have a large impact on benefits. Because of discounting of delayed benefits,
the lag structure may have a large downward impact on monetized benefits if an extreme
assumption that no effects occur until after 15 years is applied. However, for most reasonable
distributed lag structures, differences in the specific shape of the lag function have relatively
small impacts on overall benefits.
6.B.3 Visibility Benefits in Additional Class I Areas
The Chestnut and Rowe (1990)71 study from which the primary visibility valuation
estimates are derived only examined WTP for visibility changes in Class I areas (national
parks and wilderness areas) in the southeast, southwest, and California. To obtain estimates
of WTP for visibility changes at national parks and wilderness areas in the northeast,
northwest, and central regions of the U.S., we have to transfer WTP values from the studied
regions. This introduces additional uncertainty into the estimates. However, we have taken
steps to adjust the WTP values to account for the possibility that a visibility improvement in
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Regulatory Impact Analysis
parks in one region is not necessarily the same environmental quality good as the same
visibility improvement at parks in a different region. This may be due to differences in the
scenic vistas at different parks, uniqueness of the parks, or other factors, such as public
familiarity with the park resource. To take this potential difference into account, we adjusted
the WTP being transferred by the ratio of visitor days in the two regions.
Based on this benefits transfer methodology (implemented within the preference
calibration framework discussed in Chapter 5 and Appendix I of the final PM NAAQS RIA),
estimated additional visibility benefits in the northwest, central, and northeastern U.S. are
provided in Table 6B-3.
Table 6.B-3: Monetary Benefits Associated with Improvements in Visibility in Additional Federal Class I
Areas in 2020 and 2030 (in millions of 2006$)a
Year
2020
2030
Northwest13
$13
$34
Centraf
$27
$41
Northeastd
$9
$32
Total
$49
$110
All estimates are rounded to 2 significant digits. All rounding occurs after final summing of unrounded
estimates. As such, totals will not sum across columns
Northwest Class I areas include Crater Lake, Mount Rainier, North Cascades, and Olympic national parks,
and Alpine Lakes, Diamond Peak, Eagle Cap, Gearhart Mountain, Glacier Peak, Goat Rocks, Hells
Canyon, Kalmiopsis, Mount Adams, Mount Hood, Mount Jefferson, Mount Washington, Mountain Lakes,
Pasayten, Strawberry Mountain, and Three Sisters wilderness areas.
Cental Class I areas include Craters of the Moon, Glacier, Grand Teton, Theodore Roosevelt, Badlands,
Wind Cave, and Yellowstone national parks, and Anaconda-Pintlar, Bob Marshall, Bridger, Cabinet
Mountains, Fitzpatrick, Gates of the Mountain, Lostwood, Medicine Lake, Mission Mountain, North
Absaroka, Red Rock Lakes, Sawtooth, Scapegoat, Selway-Bitterroot, Teton, U.L. Bend, and Washakie
wilderness areas.
Northeast Class I areas include Acadia, Big Bend, Guadalupe Mountains, Isle Royale, Voyageurs, and
Boundary Waters Canoe national parks, and Brigantine, Caney Creek, Great Gulf, Hercules-Glades, Lye
Brook, Mingo, Moosehorn, Presidential Range-Dry Roosevelt Campobello, Seney, Upper Buffalo, and
Wichita Mountains wilderness areas.
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Cost-Benefit Analysis
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Study of Multiple Pollutants." Environmental Research 50:238-247.
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Washington, DC, November; EPA report no. EPA-410-R-99-001.
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Oxidants. National Center for Environmental Assessment, Office of Research and Development, U.S.
Environmental Protection Agency, Research Triangle Park, NC EPA 600/R-05/004aF
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59 Rowe, R.D., and L.G. Chestnut. 1986. "Oxidants and Asthmatics in Los Angeles: A Benefits Analysis
Executive Summary." Prepared by Energy and Resource Consultants, Inc. Report to the U.S. Environmental
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65 EPA-SAB-COUNCIL_ADV_04-002. March 2004. Advisory on Plans for Health Effects Analysis in the
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Advisory by the Health Effects Subcommittee of the Advisory Council on Clean Air Compliance Analysis.
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Journal of Respiratory Critical Care Medicine 151:669-674.
70 Dockery, D.W., C.A. Pope, X.P. Xu, J.D. Spengler, J.H. Ware, M.E. Fay, E.G. Ferris, and F.E. Speizer. 1993.
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71 Chestnut, L.G., and R.D. Rowe. 1990. Preservation Values for Visibility Protection at the National Parks:
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CO.
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Economic Impact Analysis
CHAPTER 7: ECONOMIC IMPACT ANALYSIS
7.1 Overview and Results 7-2
7.1.1 What is an Economic Impact Analysis? 7-2
7.1.2 What Methodology Did EPA Use in this Economic Impact Analysis? 7-3
7.1.3 What Economic Sectors are Included in the Economic Impact Model? 7-4
7.1.4 Summary of Results 7-9
7.2 Economic Methodology 7-20
7.2.1 Behavioral Economic Models 7-20
7.2.2 What is the Economic Theory Underlying the EIM? 7-21
7.2.3 How Is the EIM Used to Estimate Economic Impacts? 7-28
7.3 EIM Data Inputs and Model Solution 7-37
7.3.1 Market Equilibrium Conditions 7-38
7.3.2 Compliance Costs 7-46
7.3.3 Behavioral Parameters 7-62
7.3.4 Economic Impact Model Structure 7-68
7.3.5 Estimating Impacts 7-70
7.4 Methods for Describing Uncertainty 7-70
Appendix 7A: Impacts on Marine Engine Markets 7-76
Appendix 7B: Impacts on the Equipment Markets 7-83
Appendix 7C: Impacts on Transportation Service Markets 7-105
Appendix 7D: Time Series of Social Costs 7-108
Appendix 7E: Model Equations 7-112
7E.1 Economic Model Equations 7-112
7E.1.1 Supply Equations 7-112
7E.1.2 Demand Equations 7-113
7E.1.3 Market Equilibrium Conditions 7-114
7E.2 Computing With-Regulation Equilibrium Conditions within Spreadsheet. 7-114
7E.3 Social Costs: Consumer and Producer Economic Welfare Calculations 7-116
Appendix 7F: Elasticity Parameters for Economic Impact Modeling 7-118
Appendix 7G: Initial Market Equilibrium - Price Forecasts 7-124
Appendix 7H: Sensitivity Analysis 7-126
7H.1 Model Elasticity Parameters 7-127
7H.2 Fixed Cost Shift Scenario 7-131
7H.3 Marine Operating Cost Scenario 7-134
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Regulatory Impact Analysis
CHAPTER 7: Economic Impact Analysis
We prepared an Economic Impact Analysis (EIA) to estimate the economic impacts of
the new emission control program on the locomotive and marine diesel engine and vessel
markets. In this chapter we describe the Economic Impact Model (EIM) we developed to
estimate the market-level changes in prices and outputs for affected markets, the social costs
of the program, and the expected distribution of those costs across stakeholders. We also
present the result of our analysis.
We estimate the social costs of the new program to be approximately $738 million in
2030.^ B The rail sector is expected to bear about 62.5 percent of the social costs of the
program in 2030, and the marine sector is expected to bear about 37.5 percent. In each of
these two sectors, these social costs are expected to be born primarily by producers and users
of locomotive and marine transportation services (62 and 36 percent, respectively). The
remaining 2 percent is expected to be borne by locomotive, marine engine, and marine vessel
manufacturers and fishing and recreational vessel users.
The impact of these costs on society are expected to be minimal, with the prices of rail
and marine transportation services in 2030 estimated to increase by less about 0.6 percent for
locomotive transportation services and about 1.1 percent for marine transportation services.
7.1 Overview and Results
7.1.1 What is an Economic Impact Analysis?
An EIA is prepared to inform decision makers about the potential economic
consequences of a regulatory action. The analysis consists of estimating the social costs of a
regulatory program and the distribution of these costs across stakeholders. These estimated
social costs can then be compared with estimated social benefits (as presented in Chapter 6).
As defined in EPA's Guidelines for Preparing Economic Analyses, social costs are the value
of the goods and services lost by society resulting from a) the use of resources to comply with
and implement a regulation and b) reductions in output. * In this analysis, social costs are
explored in two steps. In the market analysis, we estimate how prices and quantities of goods
and services affected by the new emission control program can be expected to change once
the program goes into effect. In the economic welfare analysis, we look at the total social
costs associated with the program and their distribution across key stakeholders.
A All estimates presented in this section are in 2005$.
B The estimated 2030 social welfare cost of $738 million is based on draft compliance costs for this final rule,
which estimated $740 million engineering costs in 2030 (see Table 7-3). The final compliance cost estimate for
2030 is somewhat higher, at $759 million; see Section 7.3.2 for an explanation of the difference. This difference
is not expected to have an impact on the results of the market analysis or on the expected distribution of social
costs among stakeholders.
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Economic Impact Analysis
7.1.2 What Methodology Did EPA Use in this Economic Impact Analysis?
The EIM is the behavioral model we developed to estimate market-level impacts
(price and quantity changes) and social welfare costs associated with an emission control
program. The model relies on basic microeconomic theory to simulate how producers and
consumers of products and services affected by the emission requirements can be expected to
respond to an increase in production costs as a result of the new emission control program.
The economic theory that underlies the model is described in detail in Section 7.2.
The ELM is designed to estimate the economic impacts of the new program by
simulating economic behavior. This is done by creating a model of the initial, pre-control
market for a product, shocking that model by the estimated compliance costs, and observing
the impacts on the market. At the initial, pre-control market equilibrium, a market is
characterized by a price and quantity combination at which producers are willing to produce
the same amount of a product that consumers are willing to purchase at that price (supply is
equal to demand). The control program under consideration would increase the production
costs of affected goods by the amount of the compliance costs. This generates a "shock" to
the initial 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. In response to the price increases, consumers will decrease
their demand for the affected good (a change in the quantity demanded). Producers will react
to the decrease in quantity demanded by decreasing the quantity they produce; the market will
react by setting a higher price for those fewer units. These interactions continue until a new
market equilibrium price and quantity combination is achieved. The amount of the
compliance costs that can be passed on to consumers is ultimately limited by the price
sensitivity of purchasers and producers in the relevant market (represented by the price
elasticity of demand and supply). The EIM explicitly models these behavioral responses and
estimates new equilibrium prices and output and the resulting distribution of social costs
across these stakeholders (producers and consumers).
The EIM is a behavioral model. The estimated social costs of this emission control
program are a function of the ways in which producers and consumers of the engines and
equipment affected by the standards change their behavior in response to the costs incurred in
complying with the standards. These behavioral responses are incorporated in the EIM
through the price elasticity of supply and demand (reflected in the slope of the supply and
demand curves), which measure the price sensitivity of consumers and producers. 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
demand). 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 demand). A price elasticity of one is unit elastic, meaning there is a one-to-one
correspondence between a change in price and change in demand. The price elasticities used
in this analysis are described in Section 7.3 and are either from peer-reviewed literature or
were estimated using well-established econometric methods. It should be noted that the price
elasticity of demand for the locomotive and marine engine and vessel markets is internally
derived from the rail and marine transportation service markets as part of the process of
running the model. This is an important feature of the EIM, which allows it to link the engine
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Regulatory Impact Analysis
and equipment components of each model and simulate how compliance costs can be
expected to ripple through the affected markets.
7.1.3 What Economic Sectors are Included in the Economic Impact Model?
In this EIA we estimate the impacts of the new emission control program on two broad
sectors: rail and marine. The characteristics of the markets analyzed that are relevant to the
EIM are summarized in Table 7-1, and described in more detail in Section 7.3.
Table 7-1. Summary of Markets in Economic Impact Model
Model Dimension Rail Sector Marine Sector
Description of Markets:
Supply
Description of Markets:
Demand
Geographic Scope
Market Structure
Locomotive: locomotive
manufacturers (integrated
manufacturers); 3 categories
Line Haul
Passenger
Switcher
Note: Passenger and switcher markets
are combined into one market in this
analysis
Rail Transportation Services: Entities
that provide rail transportation
services (railroads, primarily Class I)
Locomotive: Railroads (primarily
Class I)
Rail transportation services: Entities
that use rail transportation services
(power, chemical, agricultural
companies; personal transportation)
50 states
Perfectly competitive
Marine Engines:
3 Applications
Commercial Propulsion
Recreational Propulsion
Auxiliary
7 Engine Sizes
Small:
<50hp
Category 1:
50-200 hp
200-400 hp
400-800 hp
800-2,000 hp
> 2,000 hp
Category 2:
800-2,000 hp
> 2,000 hp
Marine Vessels: 7 Applications
Tug/tow/pushboats
Cargo vessels
Ferry vessels
Supply /crew boats
Other commercial vessels
Fishing boats
Recreational boats
Marine Transportation Services: Entities
that provide marine transportation services
(excludes small fishing and recreational
vessels)
Marine Engines: Vessel manufacturers
Marine Vessels: Marine vessel users
(owners of all types of marine vessels)
Marine transportation services: Entities
that use marine transportation services
(power, chemical, agricultural companies;
personal transportation)
50 states
Perfectly competitive
7-4
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Economic Impact Analysis
Model Dimension
Rail Sector
Marine Sector
Baseline Population
Same as locomotive inventory
analysis
PSR 2002 OE Link Sales Database
Growth Projections
Based on projected fuel consumption
from Energy Information Agency
Commercial marine: 0.9% (0.009);
Recreational marine: Based on EPA's
Nonroad Model
Supply Elasticity
Locomotives (all): 2.7 (elastic)
Rail Transportation Market: 1.6
(inealastic)
Engines: 3.8 (elastic)
Vessels: 2.3 (elastic)
Marine Transportation Market: 1.6
(inelastic)
Demand Elasticity
Locomotives (all): Derived
Rail Transportation Market: -0.5
(inelastic)
Engines: Derived
Vessels:
Commercial: Derived
Recreational and small Fishing : -2.0
(elastic)
Marine Transportation Market: -0.5
(inelastic)
Regulatory Shock
Locomotive Market: direct engine
and equipment compliance costs cause
shift in supply function
Rail Transportation Market: direct
operating and remanufacturing
compliance costs, in addition to higher
locomotive prices, cause shift in
supply function
Marine diesel engine: direct engine
compliance costs cause shift in supply
function
Marine vessels: direct vessel compliance
costs, in addition to higher engine prices,
cause shift in supply function
Marine Transportation Market: direct
operating costs in addition to higher vessel
prices cause shift in supply function
7.1.3.1 Rail Sector Component
The rail sector component of the EIM is a two-level model consisting of suppliers and
users of locomotives and rail transportation equipment and services.
Locomotive Market. The locomotive market consists of locomotive manufacturers
(line haul, switcher, and passenger) on the supply side and railroads on the demand side. The
vast majority of locomotives built annually are for line haul applications; a small number of
passenger locomotives are built annually, and even fewer switchers. The locomotive market
is characterized by integrated manufacturers (the engine and locomotive are made by the same
manufacturer) and therefore the engine and equipment impacts are modeled together. The
ELM does not distinguish between power bands for locomotives. This is because while there
is some variation in power for different engine models, the range is not large. On average line
haul locomotives are typically about 4,000 hp, passenger locomotives are about 3,000 hp, and
switchers are about 2,000 hp.
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Regulatory Impact Analysis
Recently, a new switcher market is emerging in which manufacturers are expected to
be less integrated, with the manufacturer of the engine expected to be different from the
manufacturer of the switcher.0 Because the characteristics of this new market are speculative
at this time, the switcher market component of the EIM is modeled in the same way as line
haul locomotives for future years (integrated manufacturers; same behavioral parameters), but
with different baseline equilibrium prices and quantities and different compliance costs.
Consistent with the cost analysis, the passenger market is combined with the switcher
market in this EIA.
Rail Transportation Services. The rail transportation services market consists of
entities that provide and utilize rail transportation services. On this supply side, these are the
railroads. On the demand side, these are rail transportation service users such as the chemical
and agricultural industries and the personal transportation industry. Most of the goods moved
by rail are bulk goods such as coal, chemicals, minerals, petroleum, and the like. About 26
percent of the carloads in 2004 were miscellaneous mixed shipments (mostly intermodal, e.g.,
containers) and about 6 percent were motor vehicles and equipment. This means that about
68 percent of the goods moved by rail are production inputs.2 The EIM does not estimate the
economic impact of the new emission control program on ultimate finished goods markets
that use rail transportation services as inputs. This is because transportation services are only
a small portion of the total variable costs of goods and services manufactured using these bulk
inputs. Also, changes in prices of transportation services due to the estimated compliance
costs are not expected to be large enough to affect the prices and output of goods that use rail
transportation services as an input.
7.1.3.2 Marine Sector Component
The marine sector component of the EIM distinguishes between engine, vessel, and
ultimate user markets (marine transportation service users, fishing users, recreational users).
This is because, in contrast to the locomotive market, manufacturers in the diesel marine
market are not integrated. Marine diesel engines and vessels are manufactured by different
entities.
Marine Engine Market. The marine engine markets consist of marine engine
manufacturers on the supply side and vessel manufacturers on the demand side. The model
distinguishes between three types of engines, commercial propulsion, recreational propulsion,
and auxiliary. Engines are broken out into eight categories based on horsepower and
displacement.
Small marine diesel engines
c Until recently, switchers have typically been converted line haul locomotives and very few, if any, new
dedicated switchers were built in any year. Recently, however, the power and other characteristics of line haul
locomotives have made them less attractive for switcher usage. Their high power means they consume more
fuel than smaller locomotives, and they have less attractive line-of-sight characteristics than what is needed for
switchers. Therefore, the industry is anticipating a new market for dedicated switchers.
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Economic Impact Analysis
<50 hp
Cl engines
50-200 hp
200-400 hp
400-800 hp
800-2,000 hp
>2,000 hp
C2 engines
800-2,000 hp
>2,000 hp
The engine categories used in this EIA are different from the categories used for the
emission limits, both in term of units (horsepower instead of kilowatt) and in terms of the
range of power included in each group of engines. The EIA categories were chosen for ease
of analysis. Note, however, that the power threshold for the Tier 4 standards is 600 kW or
900 hp, which is consistent with this analysis.
For the purpose of the EIA, the C1/C2 threshold is 5 1/cyl displacement, even though
the new C1/C2 threshold is 7 1/cyl displacement. The 5 1/cyl threshold was used because it is
currently applicable limit. In addition, there is currently only one engine family in the 5 to 7
1/cyl range, and it is not possible to project what future sales will be in that range or if more
engine families will be added.
Marine Vessel Market. The marine vessel market consists of marine vessel
manufacturers on the demand side and marine vessel users on the supply side. The model
distinguishes between seven vessel categories. Each of these vessels would have at least one
propulsion engine and at least one auxiliary engine, although many may have more:
Recreational
Fishing
Tow/tug/push
Ferry
Supply/crew
Cargo
Other commercial
For recreational applications, the purchasers of those vessels are the end users, and so
the EIM is a two-level model for that market. Demand for vessels comes directly from
households that use these vessels for recreational activities and acquire them for the personal
enjoyment of the owner. For the other commercial vessel markets (tow/tug/push, ferry,
supply/crew, cargo, other), demand for those vessels is derived from the transportation
services they provide. Therefore it is necessary to include a marine transportation services
market in the model.
For the fishing applications, we use a dual approach. Small fishing vessels, those that
use engines below 800 hp, are treated like recreational vessels, as a two-level market. The
7-7
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Regulatory Impact Analysis
physical and operating characteristics of these vessels are very similar to recreational vessels.
Small fishing vessels often have fiberglass hulls, have fewer hours of use per year than large
commercial fishing vessels, and their engines have higher power density. Smaller fishing
vessels are typically operated for day fishing, their catch is more likely subject to seasonal
restrictions, and they have very small or no crew apart from the owner. Demand for these
vessels is less likely to be tied to a downstream market like the industrial fish processing or
other food or industrial markets and be more a function of the local fish market, the demand
for fresh fish for restaurants, and the individual preferences of the owner/operator.
Large fishing vessels, those that use engines above 800 hp, are treated like marine
transportation service vessels, as a three-level market. These vessels tend to be uniquely built,
used for offshore fishing, and are manned by professional crews. They may be at sea for
extended period of time, and many have fish processing facilities onboard. Demand for these
vessels is tied more directly to the fish consumption market, including industrial fish
processing companies.
Marine Transportation Services. The marine transportation services market consists
of entities that provide and utilize marine transportation services: vessel owners on the supply
side and marine transportation service users on the demand side. The firms that use these
marine transportation services are very similar to those that use locomotive transportation
services: those needing to transport bulk chemicals and minerals, coal, agricultural products,
etc. These transportation services are production inputs that depend on the amount of raw
materials or finished products being transported and thus marine transportation costs are
variable costs for the end user. Demand for these transportation services will determine the
demand for vessels used to provide these services (tug/tow/pushboats, cargo, ferries,
supply/crew, other commercial vessels).
7.1.3.3 Market Linkages
The submarkets in each of the marine and rail markets are linked; this provides
feedback mechanism between consumers and producers in the relevant markets, which
simulates dynamic interactions in the actual markets. The locomotive and marine components
of the EIM are not linked however, meaning there is no feedback mechanism between the
locomotive and marine sectors. Although locomotives and marine vessels such as tugs,
towboats, cargo, and ferries provide the same type of transportation service, the characteristics
of these markets are quite different and are subject to different constraints that limit switching
from one type of transportation service to the other. For example, switching from rail services
to marine services requires having access to a port and the waterway system; if the production
facility is not located on a waterway it would also be necessary to transport the goods to and
from port. Similarly, users of marine transportation services typically transport bulk goods in
large quantities (by barge or by container); these quantities may be more complicated and
costly to transport by rail. Because the services provided by the locomotives and marine
markets are not completely interchangeable, a change in the price of one is not expected to
have an impact on the price for the other.
For the limited number of cases where there is direct competition between rail and
marine transportation services, we do not expect this rule to change the dynamics of the
7-8
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Economic Impact Analysis
choice between marine or rail providers of these services because 1) the estimated compliance
costs imposed by this rule are relatively small in comparison with the total production costs of
providing transportation services, and 2) both sectors would be subject to the new standards.
So, for example, while an increase in the price of marine diesel engines may lead to an
increase in the price of marine transportation services, this will not likely have much impact
on the demand for rail services because the rail sector is also expected to see increased costs.
7.1.4 Summary of Results
The EIA consists of two parts: a market analysis and welfare analysis. The market
analysis looks at expected changes in prices and quantities for affected products. The welfare
analysis looks at economic impacts in terms of annual and present value changes in social
costs.
We performed a market analysis for all years and all engines and equipment. The
detailed results can be found in the appendices to this chapter. On the marine side, all
propulsion markets were modeled even though marine engines below 800 hp are not expected
to be affected by the program (they are not subject to Tier 4 standards and the only
compliance costs associated with Tier 3 standards are fixed costs). The results for engines
less than 800 hp can be found in a Technical Support Document.3 In addition, to facilitate
and accommodate computer programming constraints, only auxiliary engines above 800 hp
were included in the model (see section 7.3.2.2).
In this section we present summarized results for selected years: 2012, which
illustrates the impacts of the marine and locomotive remanufacture programs (there are no
variable costs for the Tier 3 standards, and therefore the Tier 3 standards do not affect market
impacts in that year); 2016, which illustrates the market impacts of the Tier 4 standards; and
2030, when per unit compliance costs are stabilized.
Due to the structure of the program, the sources of the estimated social costs impacts
of the program change over time. In the early years of the program, prior to 2016, the social
costs are due to the fixed and variable costs associated with the phase-in of the new emission
standards. By 2016, operating costs and the remanufacture program costs are about half the
total costs of the program; the share of these two segments increases to about 83 percent of
total program costs in 2030 and 90 percent in 2040. The remainder is due to variable costs for
the engine standards. Consequently, a large share of the long-term social costs of the program
fall on the marine and rail transportation service sectors. Results for all years can be found in
the appendices to this Chapter.
The results of the economic impact analysis presented below are based on an earlier
version of the engineering costs developed for this rule (see Section 7.3.2).
7.1.4.1 Market Analysis Results
In the market analysis, we estimate how prices and quantities of goods affected by the
new emission control program can be expected to change once the program goes into effect.
The analysis relies on the baseline equilibrium prices and quantities for each type of
7-9
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Regulatory Impact Analysis
equipment and the price elasticity of supply and demand. It predicts market reactions to the
increase in production costs due to the new compliance costs (variable, operating, and
remanufacturing costs). It should be noted that this analysis does not allow any other factors
to vary. In other words, it does not consider that manufacturers may adjust their production
processes or marketing strategies in response to the control program.
The market data presented below is aggregated across sub-markets. The absolute
price changes and relative price/quantity changes reported below are production-weighted
averages of the individual market-level estimates generated by the model for each group of
engine/equipment markets, and not the expected price or quantity change for a particular
engine model or vessel market. So, for example, the estimated price changes for marine
diesel engines are production-weighted averages of the estimated results for all of the marine
diesel engine markets included in that group.0 The absolute change in quantity reported for
each group of engine/equipment markets, on the other hand, is the sum of the decrease in
units produced across sub-markets within each engine/equipment group. The aggregated data
presented in Table 7-2 is intended to provide a broad overview of the expected market
impacts that is useful when considering the impacts of the rule on the economy as a whole and
not the impacts on a particular engine or equipment category.
More detailed results for each of the submarkets are presented in the appendices to this
chapter and in a Technical Support Document.4 As explained in Section 7.2.2.1, this is a
market-level analysis and the results are not intended to reflect expected price or quantity
changes for a particular engine or equipment model.
Locomotive Sector Impacts. On the locomotive side, the new program is expected to
have a negligible impact on locomotive prices and quantities. In 2012, the expected impacts
are mainly the result of the operating costs associated with locomotive remanufacturing
standards. These standards impose an operating cost on railroad transportation providers and
are expected to result in a slight increase in the price of locomotive transportation services
(about 0.1 percent, on average) and a slight decrease in the quantity of services provided
(about 0.1 percent, on average). Due to the decrease in quantity of services provided, the
locomotive remanufacturing program is also expected to have a small impact on the new
locomotive market. The remanufacturing program will increase railroad operating costs,
which expected to result in an increase in the price of transportation services. This increase
will results in a decrease in demand for rail transportation services and ultimately in a
decrease in the demand for locomotives and a decrease in their price. In other words, the
market will contract slightly. We estimate a reduction in the price of locomotives of about
0.03 percent on average.
Beginning in 2016, the market impacts are affected by both the operating costs and the
direct costs associated with the Tier 4 standards. As a result of both of these impacts, the
price of a new locomotive is expected to increase by about 4.2 percent for a line haul
locomotive and one percent for a switcher; the quantity produced of either is expected to
D As a result, estimates for specific types of engines and equipment may be different than the reported group
average. The detail results for markets are reported in the Appendices to Chapter 7 of the RIA.
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Economic Impact Analysis
decrease by about 0.1 percent, on average. Locomotive transportation service prices are
expected to increase by about 0.3 percent. By 2030, the price increase for a new line haul
locomotive is expected to decrease to about 3.2 percent; prices for switchers are expected to
increase by about 1.5 percent. The expected quantity decrease for either is approximately 0.3
percent. The price of rail transportation services is expected to increase by about 0.6 percent.
Marine Sector Impacts. On the marine engine side, the expected impacts are different
for engines above and below 800 hp.
With regard to engines above 800 hp and the vessels that use them, there are
negligible impacts in the early years of the program. The slight expected decrease in prices
and in quantity produced is due to the market impacts of the remanufacture program; there are
no market impacts for the Tier 3 standards. Beginning in 2016, market impacts due to the
Tier 4 standards begin to occur, with expected price increases up to 17 percent for engines and
7 percent for vessels expected to occur. The impact on marine transportation markets,
however, is expected to be small, at less than 0.5 percent. The results in 2030 are similar,
with expected price increases up to 13 percent for engines and 5 percent for vessels, but
marine transportation market price increase of only about 1 percent.
It should be noted that the actual social welfare impacts for producers and consumers
of vessels is likely to be less that these estimated impacts, however. By allocating all of the
auxiliary engines above 800 hp to the vessels that will be affected by this program, this
analysis over-estimates the vessel impacts of the program. In fact, not all of the very large
auxiliary engines are actually used on the commercial vessels that are subject to this program;
some will be installed on vessels with Category 3 marine diesel engines. While it is
appropriate to consider these costs in the economic impact analysis for this program, it is clear
that not all of these social costs will be passed on to the producers and users of vessels
directly affected by this program.
With regard to engines below 800 hp, the market impacts of the program are expected
to be negligible.E This is because there are no variable costs associated with the standards for
these engines. The market impacts associated with the program are indirect effects that stem
from the impacts on the marine service markets for the larger engines that would be subject to
direct compliance costs. Changes in the equilibrium outcomes in those marine service
markets may lead to reductions for marine services in other marine engine and vessel markets,
including the markets for smaller marine diesel engines and vessels. The result is that in some
years there may be small declines in the equilibrium price in the markets for marine diesel
engines less than 800 hp. This would occur because an increase in the price and a decrease in
the quantity of marine transportation services provided by vessels with engines above 800 hp
that results in a change in the price of marine transportation services may have follow-on
effects in other marine markets and lead to decreases in prices for those markets. For
E The market results for engines and vessels below 800 hp are provided in a Technical Support Document. See
U.S. EPA. Technical Support Document for the Final Locomotive /Marine Rule: Detailed Results from
Economic Impact Model (EDVI). EPA420-R-07-014. December 2007. A copy of this document can be found in
the docket for this rule, EPA-HQ-OAR-2004-0190.
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Regulatory Impact Analysis
example, the large vessels used to provide transportation services are affected by the rule.
Their compliance costs lead to a higher vessel price and a reduced demand for those vessels.
This reduced demand indirectly affects other marine transportation services that support the
larger vessels, and leads to a decrease in price for those markets as well.
Table 7-2. Summary of Estimated Market Impacts for 2011,2016,2030 (2005$)
Market Average
Variable
Engineering
Cost Per Unit
Change in Price Change in Quantity
Absolute Percent Absolute Percent
2012
Rail Sector
Locomotives
Switcher/Passenger
Transportation Services
$0
$0
NA
-$535
-$348
NAa
-0.03%
-0.03%
0.1%
-1
0
NAa
-0.1%
-0.1%
-0.1%
Marine Sector
Engines
Auxiliary >800 hp
Propulsion Cl>800 hp
Propulsion C2>800 hp
Other marine
$0
$0
$0
$0
-$47
-$8
-$139
$0
0.00%
0.00%
-0.03%
0.00%
0
0
0
0
-0.1%
0.0%
-0.1%
0.0%
Vessels
Cl>800 hp
C2>800 hp
Other marine
Transportation Services
$0
$0
$0
NA
-$174
-$2,419
-$3
NAa
-0.01%
-0.07%
0.00%
0.2%
0
0
1
NAa
0.0%
-0.1%
0.0%
-0.1%
2016
Rail Sector
Locomotives
Switcher/Passenger
Transportation Services
$84,274
$14,175
NA
$83,227
$13,494
NAa
4.2%
1.0%
0.3%
-1
0
NAa
-0.1%
-0.1%
-0.1%
Marine Sector
Engines
Auxiliary >800 hp
Propulsion Cl>800 hp
Propulsion C2>800 hp
Other marine
$37,097
$18,483
$71,806
$0
$35,569
$16,384
$71,602
$0
17.1%
8.5%
16.3%
0.00%
-11
-15
0
0
-3.4%
-3.7%
-0.2%
0.0%
Vessels
Cl>800 hp
C2>800 hp
Other marine
Transportation Services
$8,277
$12,107
$0
NA
$34,043b
$255,143b
-$4
NAa
2.1%
7.0%
0.00%
0.4%
-14
0
-1
NAa
-3.7%
-0.2%
0.0%
-0.2%
2030
Rail Sector
7-12
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Economic Impact Analysis
Market Average
Variable
Engineering
Cost Per Unit
Locomotives
Switcher/Passenger
Transportation Services
$65,343
$21,139
NA
Change in Price Change in Quantity
Absolute Percent Absolute Percent
$63,019
$19,628
NAa
3.2%
1.5%
0.6%
-4
-1
NAa
-0.3%
-0.3%
-0.3%
Marine Sector
Engines
Auxiliary >800 hp
Propulsion Cl>800 hp
Propulsion C2>800 hp
Other marine
$28,359
$14,131
$54,893
$0
$27,021
$12,479
$54,264
-$1
13.0%
6.5%
12.3%
0.0%
-11
-13
-1
0
-2.8%
-2.9%
-0.5%
0.0%
Vessels
Cl>800 hp
C2>800 hp
Other marine
Transportation Services
$6,933
$10,169
$0
NA
$25,768b
$164,774b
-$12
NAa
1.6%
5.1%
0.0%
1.1%
-12
0
-4
NAa
-2.9%
-0.5%
0.0%
-0.5%
a The prices and quantities for transportation services are normalized ($1 for 1 unit of services
provided) and therefore it is not possible to estimate the absolute change price or quantity; see
7.3.1.5.
b The estimated vessel impacts include the impacts of direct vessel compliance costs and the indirect
impacts of engine markets for both propulsion and auxiliary engines. See Chapter 7 of the RIA.
7.1.4.2 Economic Welfare Analysis
In the economic welfare analysis we look at the costs to society of the new emission
control program in terms of losses to key stakeholder groups that are the producers and
consumers in the rail and marine markets. The estimated surplus losses presented below
reflect all engineering costs associated with the new program (fixed, variable, operating, and
remanufacturing costs). Detailed economic welfare results for the new program for all years
are presented in the Appendices to this chapter and are summarized below.
A summary of the estimated annual net social costs is presented in Table 7-3 and
Figure 7-1. Table 7-3 shows that total social costs for each year are slightly less than the total
engineering costs. This is because the total engineering costs do not reflect the decreased
sales of locomotives, engines and vessels that are incorporated in the total social costs. In
addition, in the early years of the program the estimated social costs of the program are not
expected to increase regularly over time. This is because the compliance costs for the
locomotive remanufacture program are not constant over time.
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Regulatory Impact Analysis
Table 7-3 Estimated Annual Engineering and Social Costs Through 2040 (2005$, Smillion)
Marine Marine Marine Engine Rail operating Rail Remanuf. Rail New Total Total Social
operating costs Remanuf. and Vessel costs costs Locomotive Engineering Costs
Costs costs costs
2007
2008
2009
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
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$7.2
$21.3
$38.1
$54.8
$71.4
$88.1
$104.6
$121.0
$137.3
$153.5
$169.5
$185.2
$200.7
$215.1
$228.1
$239.8
$250.8
$261.3
$271.5
$281.2
$290.6
$22.4
$22.4
$22.4
$22.4
$71.0
$29.7
$29.7
$29.7
$53.8
$35.2
$32.5
$25.1
$25.3
$25.5
$25.8
$26.0
$26.2
$26.4
$26.6
$26.8
$27.0
$27.3
$25.0
$25.2
$25.4
$25.7
$25.9
$26.1
$26.4
$26.6
$0.0
$18.1
$24.1
$30.2
$36.4
$50.4
$54.4
$54.1
$42.1
$39.3
$35.8
$33.5
$31.0
$29.4
$27.8
$26.2
$24.6
$23.0
$21.5
$19.9
$18.4
$16.8
$15.3
$13.8
$12.3
$10.9
$9.4
$8.1
$6.7
$5.6
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$14.3
$29.3
$45.5
$61.8
$78.4
$95.6
$113.3
$131.9
$151.3
$170.3
$189.7
$209.1
$228.8
$248.5
$268.1
$287.7
$307.4
$327.1
$346.8
$366.5
$386.0
$404.6
$0.0
$25.8
$32.3
$58.2
$110.1
$90.3
$82.3
$61.0
$50.9
$80.8
$66.1
$68.2
$62.1
$36.7
$36.7
$57.7
$102.8
$90.2
$94.3
$79.6
$79.6
$94.1
$94.5
$92.8
$92.0
$81.4
$138.8
$147.0
$153.9
$146.3
$8.6
$8.6
$8.6
$38.4
$41.9
$34.7
$34.7
$40.4
$74.9
$80.7
$59.5
$60.6
$61.9
$63.9
$65.9
$67.8
$71.0
$72.3
$74.7
$76.1
$77.9
$79.3
$80.3
$81.3
$82.6
$83.9
$85.2
$86.4
$86.8
$84.4
$33.5
$77.4
$89.9
$151.7
$279.6
$221.1
$217.1
$201.2
$258.4
$284.9
$273.3
$297.0
$323.4
$332.5
$367.5
$424.2
$507.0
$529.8
$570.6
$591.5
$627.5
$677.2
$709.1
$739.7
$770.5
$790.7
$878.6
$916.7
$952.3
$969.5
$33.5
$77.4
$89.9
$151.7
$279.5
$221.0
$217.0
$201.1
$258.3
$284.4
$272.8
$296.6
$322.9
$332.0
$367.0
$423.5
$506.1
$528.9
$569.5
$590.4
$626.2
$675.8
$707.6
$738.1
$768.7
$788.9
$876.5
$914.4
$949.9
$967.0
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Economic Impact Analysis
2037
2038
2039
2040
aEPA
$299.6
$308.2
$316.0
$322.4
$26.8
$27.1
$27.3
$27.6
$4.8
$4.2
$3.7
$3.3
2040 NPV at
2040 NPV at
2030 NPV at
2030 NPV at
presents the present value of cost and benefits estimates
$422.6
$440.0
$456.7
$472.6
3%a'b
7%a'b
3%a'b
7%a'b
$148.5
$150.7
$153.5
$156.6
$82.6
$80.6
$78.4
$76.0
$996.5
$1,022.5
$1,047.3
$1,070.3
$9,166.7
$4,186.6
$5,364.1
$2,992.4
$993.8
$1,019.8
$1,044.5
$1,067.3
$9,149.2
$4,179.8
$5,356.3
$2,988.5
using both a three percent and a seven percent social discount rate. According to OMB
Circular A-4, "the 3 percent discount rate represents the 'social rate of time preference' . . . [which] means the rate at which 'society' discounts future
consumption flows to their present value"; "the seven percent rate is an estimate of the average before-tax rate of return to private capital in the U.S. economy
. . . [that] approximates the opportunity cost of capital."
bNote
These NPV calculations are based on the period 2006-2040, reflecting the period when the analysis was completed. This has the consequence of
discounting the current year costs, 2007, and all subsequent years are discounted by an additional year. The result is a smaller stream of social costs than by
calculating the NPV over 2007-2040 (3% smaller for 3% NPV and 7% smaller for 7% NPV).
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Regulatory Impact Analysis
Table 7-4 shows how the social costs are expected to be shared across stakeholders,
for selected years. According to these results, the rail sector is expected to bear most of the
costs of the program, ranging from 56.5 percent in 2012 to 67.0 percent in 2016. Producers
and consumers of locomotive transportation services are expected to bear most of those costs,
ranging from 31.0 percent in 2012 to 48.8 percent in 2016. The marine sector is expected to
bear the remaining social costs, ranging from 43.5 percent in 2012 to 33.0 percent in 2016.
Producers of marine diesel engines are expected to bear more of the program costs in the early
years (20.7 percent in 2012), but by 2020 producers and consumers in the marine
transportation services market are expected to bear a larger share of the social costs, 37.3
percent.
Figure 7-1. Estimated Annual Social Costs, 2007-2040 (2005$, Smillion)
Total Loco/Marine Program Costs
$1,200,000,000 -,
$1,000,000,000
$800,000,000
$600,000,000
$400,000,000
$200,000,000
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Economic Impact Analysis
Table 7-4. Summary of Estimated Net Social Costs for 2011,2016,2020,2030 (2005$, Smillion)
Surplus Percent Surplus Percent
Change Change
2012
2016
Locomotives
Locomotive Producers
Line haul producers
Switcher/Passenger producers
Rail transportation service providers
Rail transportation service consumers
Total locomotive sector
-$35.1
-$27.8
-$7.2
-$21.4
-$68.4
-$124.9
15.9%
12.6%
3.3%
9.7%
31.0%
56.6%
-$8.3
-$0.9
-$7.4
-$43.4
-$138.9
-$190.6
2.9%
0.3%
2.6%
15.3%
48.8%
67.0%
Marine
Marine engine producers
Auxiliary >800 hp
Cl > 800 hp
C2 > 800 hp
Other marine
Marine vessel producers
Cl > 800 hp
C2 > 800 hp
Other marine
Recreational and fishing vessel consumers
Marine transportation service providers
Marine transportation service consumers
Auxiliary Engines <800 hp
Total marine sector
TOTAL PROGRAM
-$45.8
-$16.0
-$19.0
-$10.7
$0.0
-$0.3
-$0.1
-$0.1
-$0.1
$0.0
-$11.9
-$38.1
-$0.0
-$96.1
-$221.0
20.7%
7.3%
8.6%
4.9%
0.0%
0.1%
0.0%
0.1%
0.0%
0.0%
5.4%
17.3%
0.0%
43.5%
-$2.1
-$0.5
-$1.6
$0.0
$0.0
-$15.8
-$13.5
-$2.2
-$0.1
$0.0
-$18.1
-$57.9
$0.0
-$93.8
-$284.4
0.7%
0.2%
0.5%
0.0%
0.0%
5.6%
4.7%
0.8%
0.0%
0.0%
6.4%
20.3%
0.0%
33.0%
Surplus
Change
Percent
2020
Surplus
Change
Percent
2030
Locomotives
Locomotive Producers
Line haul producers
Switcher/Passenger producers
Rail transportation service providers
Rail transportation service consumers
Total locomotive sector
-$1.1
-$1.0
-$0.1
-$46.4
-$148.6
-$196.1
0.3%
0.3%
0.0%
14.0%
44.8%
59.1%
-$3.1
-$2.7
-$0.4
-$109.0
-$348.9
-$461.1
0.4%
0.4%
0.1%
14.8%
47.3%
62.5%
Marine
Marine engine producers
Auxiliary >800 hp
Cl > 800 hp
C2 > 800 hp
Other marine
Marine vessel producers
Cl > 800 hp
C2 > 800 hp
Other marine
Recreational and fishing vessel consumers
Marine transportation service providers
-$1.8
-$0.4
-$1.3
$0.0
$0.0
-$10.3
-$8.8
-$1.3
-$0.1
$0.0
-$29.5
0.5%
0.1%
0.4%
0.0%
0.0%
3.1%
2.7%
0.4%
0.0%
0.0%
8.9%
-$2.0
-$0.5
-$1.4
-$0.1
$0.0
-$9.2
-$8.2
-$0.7
-$0.3
$0.0
-$63.3
0.3%
0.1%
0.2%
0.0%
0.0%
1.2%
1.1%
0.1%
0.0%
0.0%
8.6%
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Regulatory Impact Analysis
Surplus Percent Surplus Percent
Change Change
Marine transportation service consumers
Auxiliary Engines <800 hp
Total marine sector
TOTAL PROGRAM
-$94.4
$0.0
-$135.9
$332.0
28.4%
0.0%
40.9%
-$202.5
$0.0
-277.0
$738.1
27.4%
0.0%
37.5%
Table 7-5 provides additional detail about the sources of surplus changes, for 2020
when the per unit compliance costs are stable. On the marine side, this table shows that
engine and vessel producers are expected to pass along much of the engine and vessel
compliance costs to the marine transportation service providers who purchase marine vessels.
These marine transportation service providers, in turn, are expected to pass some of the costs
to their customers. This is also expected to be the case in the rail sector.
Table 7-5. Distribution of Estimated Surplus Changes by Market and Stakeholder for 2020 (2005$,
Smillion)
Marine Markets
Engine Producers
Vessel Producers
Engine price changes
Equipment cost changes
Recreational and Fishing Consumers
Engine price changes
Equipment cost changes
Transportation Service Providers
Increased price vessels
Operating costs
Remanufacture costs
Transportation Service Consumers
Increased price vessels
Operating costs
Remanufacture costs
Rail Markets
Locomotive Producers
Rail Service Providers
Increased price new locomotives
Operating costs
Remanufacture costs
Rail Transportation Service Consumers
Increased price new locomotives
Operating costs
Remanufacture costs
TOTAL
Total Engineering
Costs
$29.4
$6.0
SO
$100.8
$63.9
$132.3
$332.5
Surplus Change
-$1.8
-$10.3
-$1.7
-$8.6
$0
$0
$0
-$34.3
-$6.0
-$16.7
$6.9
-$41.2
-$19.1
-$53.4
$21.9
-$1.1
-$46.4
-$15.1
-$22.6
-$8.7
-$148.6
-$48.4
-$72.4
-$27.8
$332.0
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Economic Impact Analysis
The present value of net social costs of the new standards through 2040, shown in Table
7-3, is estimated to be is estimated to be $9.1 billion (2005$).F This present value is
calculated using a social discount rate of 3 percent and the stream of social welfare costs from
2006 through 2040. We also performed an analysis using a 7 percent social discount rate.0
Using that discount rate, the present value of the net social costs through 2040 is estimated to
be $4.2 billion (2005$).
Table 7-6 shows the distribution of total surplus losses for the program from 2007
through 2040. This table shows that the rail sector is expected to bear about 62 percent of the
total program social costs through 2040 (NPV 3%), and that most of the costs are expected to
be borne by the rail transportation consumers. The marine sector is expected to bear about 38
percent of the total program social costs through 2040 (NPV 3%), most of which are also
expected to be borne by the marine transportation consumers. This is consistent with the
structure of the program, which leads to high compliance costs for those stakeholder groups.
Table 7-6 Estimated Net Social Costs Through 2040 by Stakeholder (Smillion, 2005$)
Stakeholder Groups
Locomotives
Locomotive producers
Line Haul
Switcher/Passenger
Rail trans, service providers
Rail trans, service consumers
Total locomotive sector
Marine
Marine engine producers
Auxiliary >800 hp
Cl > 800 hp
C2 > 800 hp
Other marine
Marine vessel producers
Cl > 800 hp
C2 > 800 hp
Other marine
Surplus
Change
Percent of
Total Surplus
NPV 3%
-$221.1
-$172.2
-$48.9
-$1,302.7
-$4,168.7
-$5,692.6
2.4%
14.2%
45.6%
62.2%
-$307.5
-$87.3
-$106.8
-$56.8
-$56.7
-$150.0
-$126.8
-$19.7
-$3.5
3.4%
1.6%
Surplus
Change
Percent of
Total Surplus
NPV 7%
-$160.4
-$124.5
-$35.9
-$568.6
-1,819.5
-$2,548.5
3.8%
13.6%
43.5%
61.0%
-$229.4
-$64.0
-$74.6
-$42.6
-$48.1
-$72.5
-$60.8
-$10.2
-$1.5
5.5%
1.7%
F Note: These NPV calculations are based on the period 2006-2040, reflecting the period when the analysis was
completed. This has the consequence of discounting the current year costs, 2007, and all subsequent years are
discounted by an additional year. The result is a smaller stream of social costs than by calculating the NPV over
2007-2040 (3% smaller for 3% NPV and 7% smaller for 7% NPV).
G EPA has historically presented the present value of cost and benefits estimates using both a 3 percent and a 7
percent social discount. The 3 percent rate represents a demand-side approach and reflects the time preference
of consumption (the rate at which society is willing to trade current consumption for future consumption). The 7
percent rate is a cost-side approach and reflects the shadow price of capital.
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Regulatory Impact Analysis
Recreational and small
fishing vessel consumers
Marine trans, service providers
Marine trans, service consumers
Auxiliary Engines <800 hpa
Total marine sector
TOTAL PROGRAM
$0.2
-$704.6
-$2,254.7
-$40.2
$3,456.7
-$9.149.2
7.7%
24.6%
0.4%
37.8%
$0.1
-$308.4
-$986.9
-$34.2
-$1,631.3
-$4,179.8
7.4%
23.6%
-0.8%
39.0%
"Marine auxiliary engines <800 hp are not subject to Tier 4 standards, and there are no variable costs
associated with the Tier 3 standards. Consequently, there would be no direct compliance impacts for
producers or users of these engines. Social costs are limited to fixed costs associated with tooling and
certification for Tier 3 standards (those costs occur 2007-2011).
7.2 Economic Methodology
Economic impact analysis uses a combination of theory and econometric modeling to
evaluate potential behavior changes associated with a new regulatory program. As noted
above, the goal is to estimate the impact of the regulatory program on affected markets (prices
and quantities) and stakeholder groups (the share of total social costs to be borne by producers
and consumers). This is done by creating a mathematical model based on economic theory
and populating the model using publicly available price and quantity data. A key factor in
this type of analysis is the responsiveness of the quantity of engines, equipment, and
transportation services demanded by consumers or supplied by producers to a change in the
price of that product. This relationship is called the price elasticity of demand or supply.
The EIM's methodology is rooted in applied microeconomic theory and was
developed following the OAQPS Economic Analysis Resource Document.5 This section
discusses the economic theory underlying the modeling for this EIA and several key issues
that affect the way the model was developed.
7.2.1 Behavioral Economic Models
Models incorporating different levels of economic decision making can generally be
categorized as w/Y/z-behavior responses or without-behavior responses. The EIM is a
behavioral model.
Engineering cost analysis is an example of the latter and provides detailed estimates of
the cost of a regulation based on the projected number of affected units and engineering
estimates of the annualized costs. The result is an estimate of the total compliance costs for a
program. However, these models do not attempt to estimate how a regulatory program will
change the prices or output of an affected industry. Therefore, the results may over-estimate
the total costs of a program because they do not take decreases in quantity produced into
account. In addition, engineering cost analysis does not address which stakeholders are
expected to bear the costs of the regulation.
The w/Y/z-behavior response approach builds on the engineering cost analysis and
incorporates economic theory related to producer and consumer behavior to estimate changes
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Economic Impact Analysis
in market conditions. As Bingham and Fox note, this framework provides "a richer story" of
the expected distribution of economic welfare changes across producers and consumers.6 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, that will
generally affect the market environment in which they operate. As producers change their
production levels in response to a new regulation, consumers of the affected goods are
typically faced with changes in prices that cause them to alter the quantity that they are
willing to purchase. These changes in price and output resulting from the market adjustments
are used to estimate the distribution of social costs between consumers and producers.
If markets are competitive and per-unit regulatory costs are small, the behavioral
approach will yield approximately the same total cost impact as the engineering cost
approach. However, the advantage of the w/Y/z-behavior response approach is that it illustrates
how the costs flow through the economic system and it identifies which stakeholders
(producers and consumers) are most likely to be affected.
7.2.2 What is the Economic Theory Underlying the EIM?
The EIM is a multi-market partial equilibrium numerical simulation model that
estimates price and quantity change in the intermediate run under competitive market
conditions. Each of these model features is described in this section.
7.2.2.1 Partial Equilibrium Multi-Market Model
In the broadest sense, all markets are directly or indirectly linked in the economy, and
a new regulatory program will theoretically affect all commodities and markets to some
extent. However, not all regulatory programs have noticeable impacts on all markets. For
example, a regulation that imposes significant per unit direct compliance costs on the
production of an important manufacturing input, such as steel, would be expected to have a
large impact on the national economy. However, a regulation that imposes a small direct
compliance cost on an important input, or any direct compliance costs on an input that is only
a small share of production costs would be expected to have less of an impact on all markets
in the economy.
The appropriate level of market interactions to be included in an economic impact
analysis is determined by the number of industries directly affected by the requirements and
the ability of affected firms to pass along the regulatory costs in the form of higher prices.
There are at least three alternative approaches for modeling interactions between economic
sectors, which reflect three different levels of analysis.
In ^partial equilibrium model, individual markets are modeled in isolation. The only
factor affecting the market is the cost of the regulation on facilities in the industry being
modeled; there are no interaction effects with other markets. Conditions in other markets are
assumed either to be unaffected by a policy or unimportant for cost estimation.
In a multi-market model, a subset of related markets is modeled together, with sector
linkages, and hence selected interaction effects, explicitly specified. This approach represents
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Regulatory Impact Analysis
an intermediate step between a simple, single-market partial equilibrium approach and a full
general equilibrium approach. This technique has most recently been referred to in the
literature as "partial equilibrium analysis of multiple markets."7
In a. general equilibrium model, all sectors of the economy are modeled together,
incorporating interaction effects between all sectors included in the model. General
equilibrium models operationalize neoclassical microeconomic theory by modeling not only
the direct effects of control costs but also potential input substitution effects, changes in
production levels associated with changes in market prices across all sectors, and the
associated changes in welfare economy-wide. A disadvantage of general equilibrium
modeling is that substantial time and resources are required to develop a new model or tailor
an existing model for analyzing regulatory alternatives.
This analysis uses a multi-market partial equilibrium approach in that it models only
those markets that are directly affected by the new emission control program: producers and
consumers in the rail and marine sectors. These two sectors are modeled separately, and the
locomotive and marine components of the EIM are not linked (there is no feedback
mechanism between the locomotive and marine diesel market segments; see Section 7.1.3.3).
The results of the analysis will be estimated price and quantity changes in the locomotive and
rail transportation services markets and in the marine engine, vessel, and transportation
services markets, as well as estimates of how the compliance costs will be shared between
producers and consumers in the relevant markets.
The EIM does not estimate the economic impact of the new emission control program
on finished goods that use rail or marine transportation services as inputs. For example, while
we look at the impacts of the program on locomotive transportation costs, we do not look at
the impacts of the controls on electricity produced using coal transported by rail, or on
manufactured products that use that electricity. Similarly, while we look at the impacts of the
control program on the price of large fishing vessels, we do not look at the impacts of the
controls on the prices of food products that use fish as an input. This is because these inputs
(rail transportation, fishing vessel) are only a small portion of the total inputs of the final
goods and services produced using them. Therefore, a change in the price of these inputs on
the order anticipated by this program would not be expected to significantly affect the prices
and quantities of finished products that use transportation or other services provided by
locomotives or marine vessels as an input.
It should also be noted that the economic impact model employed for this analysis
estimates the aggregate economic impacts of the control program on the relevant markets. It
is not a firm-level analysis and therefore the supply elasticity or individual compliance costs
facing any particular manufacturer may be different from the market average. This difference
can be important, particularly where the rule affects different firms' costs over different
volumes of production. However, to the extent there are differential effects, EPA believes
that the wide array of flexibilities provided in this rule are adequate to address any cost
inequities that may arise.
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Economic Impact Analysis
7.2.2.2 Perfect Competition Model
For all markets that are modeled, the analyst must characterize the degree of
competition within each market. The discussion generally focuses on perfect competition
(price-taking behavior) versus imperfect competition (the lack of price-taking behavior). This
EEVI relies on an assumption of perfect competition. This means that consumers and firms are
price takers and do not have the ability to influence market prices.
In a perfectly competitive market at equilibrium 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 perfect competition assumption 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 perfect competition include absence of barriers to entry, absence of
strategic behavior among firms in the market, and product differentiation.11 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).
In contrast, imperfect competition implies firms have some ability to influence the
market price of output they produce. One of the classic reasons firms may be able to do this
is their ability to produce commodities with unique attributes that differentiate them from
competitors' products. This allows them to limit supply, which in turn increases the market
price, given the traditional downward-sloping demand curve. Decreasing the quantity
produced increases the monopolist's profits but decreases total social surplus because a less
than optimal amount of the product is being consumed. In the monopolistic equilibrium, the
value society (consumers) places on the marginal product, the market price, exceeds the
marginal cost to society (producers) of producing the last unit. Thus, social welfare would be
increased by inducing the monopolist to increase production. Social cost estimates associated
with an emission control program would be larger with monopolistic market structures and
other forms of imperfect competition because the regulation exacerbates the existing social
inefficiency of too little output from a social perspective. The Office of Management and
Budget (OMB) explicitly mentions the need to consider these market power-related welfare
costs in evaluating regulations under Executive Order 12866.8
Perfect competition is widely accepted for this type of analysis and only in rare cases
are other approaches used.9 For the markets under consideration in this EIA we assume the
perfectly competitive market structure. This is because these markets do not exhibit evidence
of noncompetitive behavior: there are no indications of barriers to entry, the firms in these
markets are not price setters, and there is no evidence of high levels of strategic behavior in
the price and quantity decisions of the firms.
H The number of firms in a market is not a necessary condition for a perfectly competitive market. See Robert
H. Frank, Microeconomics and Behavior, 1991, McGraw-Hill, Inc., p 333.
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Regulatory Impact Analysis
On the marine side, the markets included in this analysis do not exhibit evidence of
noncompetitive behavior. On the engine side, these markets are matured, as evidenced by
unit sales growing at the rate of population increases. Pricing power in such markets is
typically limited. There is also excess capacity, especially on the engine side. Marine diesel
engines are typically marinized land-based highway or nonroad engines, and it is possible for
marine diesel engine manufacturers to produce additional marine engines with minimal
production constraints if a high demand is present. On the vessel side, there are hundreds of
shipyards that can be engaged in the production of vessels, and vessels from one firm can be
purchased instead of engines and vessels from another firm. Finally, there are hundreds of
marine transportation service providers, ranging from individuals who own their own tug or
supply boat to firms that employ a fleet. It is also not uncommon for owners to move vessels
among coasts and waterways to take advantage of local markets. For all of these reasons it is
appropriate to model the market markets as competitive.
The locomotive markets are also modeled as competitive. While there are two main
locomotive producers, EMD and GE, their products are homogeneous and railroads can easily
purchase locomotives from one or the other. The high cost of fuel for the rail transportation
services sector also contributes to competition among locomotive manufacturers, in that
railroads will shift their purchases from one manufacturer to the other if they can achieve a
reduction in fuel costs. The new switcher market will add to the competitive pressure in this
market as well. On the rail transportation side, although the Government Accountability
Office (GAO) has expressed concerns regarding the amount of competition in the rail road
industry due to mergers over the past decades, it also acknowledges that a more "rigorous
analysis of competitive markets" was needed to show the industry was not competitive.10 The
Association of American Railroads (AAR), a trade group representing the freight railroads of
North America, has suggested that mergers have actually made the rail road industry more
competitive. According to the AAR, most mergers have been "end-to-end" mergers that
reduce the need to interchange traffic to a connecting railroad (creating a single line service),
as opposed to the merger of competing railroads with parallel lines. These mergers increase
competition by creating more efficient, lower cost railway networks.u AAR also argues that
recent mergers have not given railroads excessive market power that would come with
uncompetitive markets. They note that productivity is up, prices are down, innovative new
operating strategies are being tested, profits are not in excess of a competitive rate of return,
and they do not have an excessive share of the national transportation market.12
7.2.2.3 Intermediate-Run Model
In developing a multi-market partial equilibrium model, the choices available to
producers must be considered. For example, are producers able to increase their factors of
production (e.g., increase production capacity) or alter their production mix (e.g., substitution
between materials, labor, and capital)? These modeling issues are largely dependent on the
time horizon for which the analysis is performed. Three benchmark time horizons are
discussed below: the very short run, the long run, and the intermediate run. This discussion
relies in large part on the material contained in the OAQPSEconomic Analysis Resource
Guide13
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Economic Impact Analysis
The EIM models market impacts in the intermediate run. The use of the intermediate
run means that some factors of production are fixed and some are variable. This modeling
period allows analysis of the economic effects of the rule's compliance costs on current
producers. As described below, a short-run analysis imposes all compliance costs on
producers, while a long-run analysis imposes all costs on consumers. The use of the
intermediate time frame is consistent with economic practices for this type of 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. In essence, this is equivalent to the nonbehavioral model described earlier.
Neither the price nor quantity changes and the manufacturer's compliance costs become fixed
or sunk costs. Under this time horizon, the impacts of the regulation fall entirely on the
regulated entity. Producers incur 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.
Figure 7-2. Short Run: All Costs Borne By Producers
Price
Q
Output
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
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Regulatory Impact Analysis
average costs of production are constant with respect to output.1 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.
Figure 7-3 Long-Run: Full-Cost Pass-Through
Price
Increase
^ With Regulation
Unit Cost Increase
S Without Regulation
Output
Market demand is represented by the standard downward-sloping curve. The market
is assumed here to be perfectly 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. The shift causes the market price to
increase by the full amount of the per-unit control cost (i.e., from PO 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" and is illustrated in Figure 7-3.
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
1 The constancy of marginal costs reflects an underlying assumption of constant returns to scale of production,
which may or may not apply in all cases.
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Economic Impact Analysis
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.
The intermediate run time frame allows examination of impacts of a regulatory
program during the transition between the 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 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.
Figure 7-4 Intermediate Run: Partial-Cost Pass-Through
Price
Increase
: With Regulation
Unit Cost Increase
b ^ S0 : Without Regulation
Qo
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.
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Regulatory Impact Analysis
Consistent with other economic impact analyses performed by EPA, this EIM uses an
intermediate run approach. This approach allows us to examine the market and social welfare
impacts of the program as producers adjust their output and consumers adjust their
consumption of affected products in response to the increased production costs. During this
period, the distribution of the welfare losses between producer and consumer depends in large
part on the relative supply and demand elasticity parameters used in the model. For example,
if demand for marine vessels or locomotives is relatively inelastic (i.e., demand does not
decrease much as price increases), then most of the direct compliance costs on vessel or
locomotive manufacturers will be passed along to the owners and operators of this equipment
in the form of higher prices.
7.2.3 How Is the EIM Used to Estimate Economic Impacts?
7.2.3.1 Estimation of Market Impacts (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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Economic Impact Analysis
Figure 7-5 Market Equilibrium Without and With Regulation
= P
Domestic Supply
Foreign Supply
a) Baseline Equilibrium
Q
Market
P'
P
S',
I
P'
P
q'd qd
Domestic Supply
Foreign Supply
b) With-Regulation Equilibrium
Q' Q
Market
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 constant demand curve. In contrast, changes in any of the other variables would lead
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Regulatory Impact Analysis
to change in demand and are illustrated as shifts in the position of the demand curve/ 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 as people choose to buy more of a good at a given price. Changes in the prices of
related good and tastes or preferences can also lead to demand curve shifts.
The new standards are expected to increase the costs of production in all the affected
markets (locomotive, rail transportation services, marine engines, marine vessels, and marine
transportation services) and ultimately lead to higher equilibrium prices in the affected
markets. As these prices increase, the quantity demanded falls (i.e., the price change leads to
a movement along the demand curve). However, the new emission control program is not
expected to lead to shifts in the locomotive and marine transportation service market demand
curves for several reasons. First, the demand for transportation services is determined by the
national economy. The growth in the size of the national economy determines the demand for
transportation services. We presume the cost of the new standards will not change the size of
the national economy in measurable ways since these sectors are relatively small contributors
to GDP. Therefore, we do not expect a change in demand in these sectors. Second, the
business decisions of users of rail and marine transportation services will not be changed due
to the new standards. These users will still need to use rail and marine transportation services
to ship their products to their destinations for intermediate or final users of those products. In
this sense, transportation services are part of an integrated production process that will not be
changed by this program. For all of these reasons, it would be inappropriate to shift the
demand curve for this analysis.
7.2.3.2 Incorporating Multi-Market Interactions
The above description is typical of the expected market effects for a single product
markets considered in isolation (for example the locomotive or engine markets). However,
the markets considered in this EIA are more complicated because of the need to investigate
impacts on each component of the affected markets (engine, vessel and transportation services
on the marine side and locomotives and transportation services on the locomotive side) and
the relationships between those components.
For example, with regard to the commercial vessel markets, the new emission control
program is expected to affect vessel producers in two ways. First, these producers are
affected by higher input costs (increases in the price of marine diesel engines) associated with
the rule. Second, the standards will also impose additional production costs on vessel
producers associated with vessel changes necessary to accommodate compliant engines.
Similarly, the rail and marine transportation services markets will be affected by increases in
the price of engines and equipment (locomotives and marine vessels) as well as direct
increases in operating costs.
1 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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Economic Impact Analysis
In the marine market case, the demand for engines is directly linked to the production
of vessels that uses those engines.K For this reason, 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. 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.
K In the marine vessel market, one or two engines are used per vessel, depending on its intrinsic design, and this
configuration is insensitive to small changes in the engine used.
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Regulatory Impact Analysis
Figure 7-6 Derived-Demand Curve for Engines
Price
Vessels
($/Q)
APE
DE
AQE
Q - Vessels
Price
Engines
($/Q)
AP
eng
eng
Unit Cost Increase
Derived
Demand
AQeng
AQE = AQeng
Q - Engines
Consider an event in the marine equipment market (vessel market) that causes the
price of equipment to increase by AP (such as an increase in the price of engines). This
increase in the price of equipment will cause the supply curve in the equipment market to shift
up, leading to a decreased quantity (AQE). The change in equipment production leads to a
decrease in the demand for engines (AQEng). The new point (QE - ACh, P - AP) traces out the
derived demand curve. Note that the supply and demand curves in the marine equipment
markets are needed to identify the derived demand in the engine market. All of the market
supply and demand curves and the elasticity parameters are described in Appendix 7F.
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Economic Impact Analysis
7.2.3.3 Estimation of Social Costs
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).
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Regulatory Impact Analysis
Figure 7-7. Economic Welfare Calculations: Changes in Consumer, Producer, and Total Surplus
$/Q
Q/t
(a) Change in Consumer Surplus with
Regulation
$/Q
Q2 Q,
(b) Change in Producer Surplus with
Regulation
Q/t
$/Q
Q2 Q,
(c) Net Change in Economic Welfare with
Regulation
Q/t
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 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.
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Economic 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 consumers' 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 - Ch.
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.
7.2.3.4 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.
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Regulatory Impact Analysis
$/q
Figure 7-8 Modeling Fixed Regulatory Costs
MC'
P _
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.
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Economic 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 accounted
for in the year in which they occur and are attributed to the respective locomotive, marine
engine, and vessel manufacturers. These manufacturers are expected to see losses of producer
surplus as early as 2007.
7.3 EIM Data Inputs and Model Solution
The EIM is a computer model comprised of a series of spreadsheet modules that
simulate the supply and demand characteristics of the markets under consideration. The
model equations, presented in Appendix 7E, are based on the economic relationships
described in Section 7.2. The EIM analysis consists of four basic steps:
Define the initial market equilibrium conditions of the markets under consideration
(equilibrium prices and quantities and behavioral parameters; these yield equilibrium
supply and demand curves).
Introduce a policy "shock" into the model based on estimated compliance costs that
shift the supply functions.
Use a solution algorithm to estimate a new, with-regulation equilibrium price and
quantity for all markets.
Estimate the change in producer and consumer surplus in all markets included in the
model.
Supply responses and market adjustments can be conceptualized as an interactive
process. Producers facing increased production costs due to compliance are willing to supply
smaller quantities at the baseline price. This reduction in market supply leads to an increase
in the market price that all producers and consumers face, which leads to further responses by
producers and consumers and thus new market prices, and so on. The new with-regulation
equilibrium reflects the new market prices where total market supply equals market demand.
This section describes the markets and data used to construct the EIM: initial
equilibrium market conditions (equilibrium prices and quantities), compliance cost inputs, and
model elasticity parameters. Also included is a brief discussion of the solution algorithm used
to estimate with-regulation market conditions.
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Regulatory Impact Analysis
7.3.1 Market Equilibrium Conditions
The starting point for the economic impact analysis is initial market equilibrium
conditions (prices and quantities) that exist prior to the implementation of the new standards.
At pre-control market equilibrium conditions, consumers are willing to purchase the same
amount of a product that producers are willing to produce at that market price.
7.3.1.1 Locomotive Initial Equilibrium Quantities
For equilibrium baseline sales for the locomotive markets, the EIM uses the same
locomotive sales quantities that are used in the locomotive engineering cost analysis presented
in Chapter 5. These sales were derived using the inputs for our locomotive emissions
inventory analysis. In that analysis, we projected future locomotive populations and the
number of locomotives remanufactured for given years. An estimated sales figure can be
derived from those projected populations by comparing the given year's population to the
prior year's population. The difference, after backing out the number of older locomotives
that are projected to be removed from services, can be considered the new sales for the given
year. Locomotive sales for all years of the analysis are contained in Table 7-7. Note that, to
be consistent with the engineering costs analysis, passenger locomotives sales are included
with the switcher locomotive sales.
Table 7-7 Locomotive Sales (2007 through 2040)
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
Line Haul Sales
646
666
693
729
751
767
765
780
816
854
877
894
917
948
979
,007
,034
,048
,078
,096
,119
,136
,150
,158
,173
Switcher/Passenger
Sales
92
92
92
92
92
92
92
93
93
94
94
94
94
94
94
95
160
183
201
212
227
239
247
263
281
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Economic Impact Analysis
Year
2032
2033
2034
2035
2036
2037
2038
2039
2040
Line Haul Sales
,190
,209
,223
,231
,197
,172
,144
,112
,078
Switcher/Passenger
Sales
292
296
305
302
294
287
278
269
263
7.3.1.2 Locomotive Initial Equilibrium Prices
The baseline equilibrium price used for new line-haul locomotives used in the EIM is
$2 million (2005$). The baseline equilibrium price for the switcher/passenger category is
$1.3 million (2005$). These prices are based on conversations with the locomotive
manufacturers. These prices are used for all years of the analysis. The analysis assumes a
constant (real) price of goods and services over time and so equilibrium prices for future years
are the same as the initial year equilibrium prices. This is reasonable because, in the absence
of shocks to the economy or the supply of raw materials, economic theory suggests that the
equilibrium market price for goods and services should remain constant over time (see
Appendix 7G for a discussion of the constant price assumption).
7.3.1.3 Marine Engine and Vessel Initial Equilibrium Quantities
Propulsion Engine Quantities. For baseline equilibrium sales for the marine
propulsion engine markets, the EIM uses the same marine engine sales quantities that are used
in the marine engineering cost analysis presented in Chapter 5. These are based on the Power
Systems Research OELink database, for 2002. These sales figures are reproduced in Table 7-
Table 7-8. Marine Diesel Engine Sales (2002)
Marine Diesel Engine
Categories (by hp)
< 50 hpa
50-200 hp
200-400 hp
400-800 hp
Cl 800-2,000 hp
Cl >2,000 hp
C2 800-2,000 hp
Annual Sales
Auxiliary
9,332
4,019
1,773
956
142
13
56
Annual Sales
Commercial
Propulsion
67
2,665
1,398
1,634
472
196
6
Annual Sales
Recreational
Propulsion
3,924
6,294
2,663
4,220
598
177
0
Total
13,323
12,978
5,834
6,810
1,212
386
62
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Regulatory Impact Analysis
C2 >2,000 hp
Total
86
16,377
125
6,563
0
17,876
211
40,816
aThe cost analysis does not differentiate between auxiliary, commercial propulsion, and recreational
propulsion engines <50 hp; these engines were allocated to the engine categories based on PSR
OELink sales splits for 2002.
Vessel Quantities. Baseline equilibrium vessel sales for the commercial vessel
markets were derived by apportioning the commercial propulsion engine sales in Table 7-8 to
vessel types based on the characteristics of the current vessel populations. This yields the
number of propulsion engines by application. We then assumed the average number of
propulsion engines per vessel and applied that value to the number of engines by application
(one or two) to obtain the number of vessels by application.14
For the recreational vessel market, baseline equilibrium vessels sales were estimated
by assuming one engine per vessel for engines up to 200 hp, and 2 engines per vessel for
larger vessels. There are no Category 2 recreational vessels because our program does not
allow Category 2 engines to be categorized as recreational. Consequently, any recreational
vessels with Category 2 engines would be included in the commercial vessel categories. This
approach is not expected to affect the results of the analysis because the number of vessels
that use Category 2 marine diesel engines is small (less than 200 in 2002) and it is unlikely
that recreational vessels that use engines of this size would number more than a few, if any.
The estimated vessel sales for 2002 are reproduced in Table 7-9.
Table 7-9. Marine Vessel Sales (2002)
Hp Bin
0-50
50-200
200-400
400-800
Cl 800-2,000
Cl >2,000
C2 800-2,000
C2 >2,000
Total
Fishing
65
2,293
602
702
202
85
0
10
3,958
Tow/Tug
/Push
0
247
65
76
22
9
1
29
449
Ferries
1
40
10
12
4
1
0
3
71
Supply/
Crew
0
41
11
13
4
2
2
16
88
Cargo
0
13
3
4
1
0
0
4
25
Other
Commerc'l
1
31
8
10
o
5
i
0
i
55
Recreatn'l
3,924
6,294
1,332
2,110
299
89
0
0
14,047
Total
3,991
8,959
2,031
2,927
535
187
o
5
63
18,695
Auxiliary Engine Quantities. In general, every marine vessel has at least one auxiliary
engine (and often two, in the case of commercial vessels) to provide power in case of
emergency and/or to power various electric equipment that the operator may want to use
without running the main propulsion engine (for example, galley equipment on a recreational
vessel or various crew support equipment on a commercial vessel). The 16,377 auxiliary
engines set out in Table 7-8, are those specifically produced and identified as marine auxiliary
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Economic Impact Analysis
engines. This is fewer that the minimum number that would be required to provide two
auxiliary engines for each commercial vessels and one for each fishing and recreational
vessel. This discrepancy is explained by the fact that not all auxiliary engines used onboard
marine vessels are marine-specific; instead, some may be non-installed nonroad engines,
which are not required to be certified as marine diesel engines in our marine diesel engine
emission control program.
The existence of separate marine auxiliary engines creates a complication when
estimating the economic impacts of the new standards, since increases in auxiliary engine
prices will have a separate impact on vessel markets. To estimated the combined effects of
the indirect impacts of propulsion and auxiliary engine prices increases and the direct impacts
of vessel compliance costs, it is necessary to allocate auxiliary as well as propulsion engines
to vessels.
Because there are no variable costs associated with auxiliary engine below 800 hp, it is
not necessary to allocate those engines to vessels.L The only auxiliary engines that must be
allocated to vessels are those larger than 800 hp (those that will need to comply with the Tier
4 standards). These auxiliary engines are distributed as follows, for the purpose of this
anlaysis:
All auxiliary engines from 800 to 2,000 hp are allocated to vessels with Cl
propulsion engines above 2,000 hp (except tows) and supply and crew vessels
with C2 propulsion engines above 2,000 hp
All auxiliary engines above 2,000 hp are allocated to vessels with C2
propulsion engines above 2,000 hp (except supply and crew vessels and those
in the "other" category).
The results of this allocation scheme are set out in Table 7-10. Note that this approach
modifies the auxiliary engine sales from the Power Systems Research OELink database, for
2002 set out in Table 7-8, although the total number of auxiliary engines from 600 to 2,000 hp
(198 engines) and above 2,000 hp (99 engines) are the same.
Table 7-10 Adjusted Auxiliary Engine Sales (2002)
Vessel Type Number of Vessels Auxiliary Engine Per Total Auxiliary Engines
Vessel
Auxiliary engines 600-2,000 hp
Cl >2000 hp Fishing
Cl >2000 hp Ferries
Cl >2000 hp Supply/Crew
85
1
2
1.9
1.9
1.9
198
159
2
4
L There are no variable costs associated with marine auxiliary engines <800 hp because there are no variable
costs associated with the Tier 3 standard and these engines are not subject to Tier 4 standards. Since there are no
direct compliance costs, it is not necessary to allocate these auxiliary engines to vessels. There are fixed costs
associated with the Tier 3 standards, however, and these costs are appropriately included in the total social
welfare impacts of the program. These costs are incurred in 2007 through 2011.
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Regulatory Impact Analysis
Cl >2000 hp Other
C2 >2000 hp Supply/Crew
C2 > 2000 hp Other
1
16
1
1.9
1.9
1.9
Auxiliary Engines >2000 hp
C2 >2000 hp Fishing
C2 >2000 hp Tow/Tug
C2 >2000 hp Ferries
C2 >2000 Cargo
10
29
3
4
2.2
2.2
2.2
2.2
2
30
2
99
22
62
6
9
By allocating all of the auxiliary engines above 800 hp to the vessels that will be
affected by this program, this analysis over-estimates the vessel impacts of the program. In
fact, not all of the very large auxiliary engines are actually used on the commercial vessels
that are subject to this program; some will be installed on vessels with Category 3 marine
diesel engines. However, it is appropriate to consider these costs in the economic impact
analysis for this program.
Projected Sales for Future Years. To project marine engine sales for future years, the
ELM uses the same technique as is used in the cost analysis, which consists of applying a
1.009 growth factor to the 2002 sales, for commercial marine diesel engines, and by applying
the NONROAD model growth rate to the 2002, for recreational marine engines. Note that for
the purpose of this analysis, small engine projections are estimated using only the commercial
growth factor of 1.009.
To project marine vessel sales for future years, the same technique was used as for the
baseline equilibrium vessel sales described above.
7.3.1.4 Marine Engine and Vessel Initial Equilibrium Prices
Propulsion Engine Prices. The baseline equilibrium engine prices for Cl commercial
propulsion engines used in the EIM were obtained from an internet search of engine prices.15
The baseline equilibrium prices for C2 propulsion engines were estimated by multiplying the
Cl commercial propulsion engine prices by 1.5. This reflects the larger cylinder displacement
of these engines and the fact that they are built for longer hours of use. The baseline
equilibrium prices for recreational propulsion engines were estimated by multiplying the Cl
commercial propulsion engine prices by 1.25. This reflects the fact that while recreational
engines are often similar to commercial engines they are designed for higher power and use at
higher engine load. Recreational engines also often have esthetic features (e.g., chrome
fixtures) that set them apart from their recreational counterparts. There are no prices for
Category 2 recreational vessels; all engines with per cylinder displacement above 7 liters are
considered to be commercial regardless of the application in which they are used. The
baseline equilibrium prices for marine diesel propulsion engines are set out in Table 7-11.
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Economic Impact Analysis
Table 7-11. Per Unit Marine Diesel Propulsion Engine Prices (2005$)
Marine Diesel Engine
Categories (by hp)
<50hp
50-200 hp
200-400 hp
400-800 hp
Cl 800-2,000 hp
Cl > 2,000 hp
C2 800-2,000 hp
C2 > 2,000 hp
Commercial
Propulsion
$7,000
$16,000
$21,000
$50,000
$155,000
$300,000
$230,000
$450,000
Recreational
$8,750
$20,000
$26,250
$62,500
$193,750
$375,000
NA
NA
Auxiliary Engine Prices. With the exception of auxiliary engine above 2,000 hp, the
estimated baseline equilibrium prices for auxiliary engines are the same as similar propulsion
engines. Engine manufacturers indicated that for engines in this size range, the propulsion
and auxiliary engines are typically very similar packages. For the larger engines, those above
2,000 hp, engine manufacturers informed us that the price of an auxiliary engine is typically
slightly less than for propulsion, with the price of an auxiliary engine at about 85 percent of
the price for a propulsion engine. While they are the same base engine, they have a different
package of accessories.
As described above, auxiliary engines are allocated among commercial vessels based
on power and not based on engine category. Therefore, it is necessary to adjust the auxiliary
engine baseline equilibrium prices for auxiliary engines to reflect a weighted average price for
Category 1 and Category 2 auxiliary engines. The weights used in the calculation reflect the
estimated share of engines for each hp category in the baseline population. It is not necessary
to construct a weighted price for engines above 2,000 hp; all of these engines are assumed to
be Category 2 engines, and their price is $385,000 (85 percent of the price of a propulsion
engine, $450,000).
Average auxiliary engine price (800-2,000 hp) = 0.84x$155,000 + 0.16x$230,000 = $167,000
Table 7-12 Per Unit Marine Auxiliary Diesel Engine Prices
Auxiliary Engine Propulsion Auxiliary Engine Share Auxiliary Engine
Market in EIM Engine Baseline Baseline Baseline Price
Price Quantity
800-2,000 hp
Cl 800 to 2000 hp
C2 800 to 2000 hp
>2,000 hp
$155,000
$230,000
$385,000
198 engines
166 engines
32 engines
99 engines
100%
(166/198) = 84%
(32/198) =16%
100%
$167,000
$385,000
Vessel Prices. The estimated baseline equilibrium price for marine vessels used in the
EIM were estimated based on the engine prices, by applying an assumed ratio of the price of a
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Regulatory Impact Analysis
vessel to the price of the propulsion engines onboard. Table 7-13 sets out the ratios used to
estimate the vessel prices, and Table 7-14 sets out the vessel prices used in the EIA.
Table 7-13. Ratio of Vessel Price to Marine Diesel Engine Price
Hp Bin
0-50
50-200
200-400
400-800
Cl 800-2,000
Cl >2,000
C2 800-2,000
C2 >2,000
Fishing
5
5
3.5
3.5
3.5
3.5
3.5
3.5
Tow/Tug/
Push Boat
6
4
4.5
5
5
5
5
Ferries
6
6
4
4.5
5
5
5
5
Supply/
Crew
6
8
9
10
10
10
10
Cargo
6
4
4.5
10
10
10
10
Other
Commercial
5
5
3.5
3.5
3.5
3.5
3.5
3.5
Recreational
6
6
4
4
4
4
4
4
Table 7-14. Per Unit Marine Vessel Prices (2005$)
Hp Bin
0-50
50-200
200-400
400-800
Cl 800-
2,000
Cl >2,000
C2 800-
2,000
C2 >2,000
Fishing
$35,000
$80,000
$147,000
$350,000
$1,085,000
$2,100,000
$1,610,000
$3,150,000
Tow/Tug/
Push Boat
$96,000
$168,000
$450,000
$1,550,000
$3,000,000
$2,300,000
$4,500,000
Ferries
$42,000
$96,000
$168,000
$450,000
$1,550,000
$3,000,000
$2,300,000
$4,500,000
Supply/
Crew
$96,000
$336,000
$900,000
$3,100,000
$6,000,000
$2,300,000
$4,500,000
Cargo
$96,000
$168,000
$450,000
$3,100,000
$6,000,000
$4,600,000
$9,000,000
Other
Commercial
$35,000
$80,000
$147,000
$350,000
$1,085,000
$2,100,000
$1,610,000
$3,150,000
Recreational
$52,500
$120,000
$210,000
$500,000
$1,550,000
$3,000,000
NA
NA
With respect to future prices, this analysis assumes a constant (real) price of goods and
services over time and the equilibrium prices for future years are the same as the baseline
equilibrium prices. This is reasonable because, in the absence of shocks to the economy or
the supply of raw materials, economic theory suggests that the equilibrium market price for
goods and services should remain constant over time (see Appendix 7G for a discussion of the
constant price assumption).
7.3.1.5 Baseline Quantities and Equilibrium Prices for Transportation Markets
The nature of the locomotive and marine transportation services markets makes it
difficult to identify the baseline equilibrium prices and quantities for this analysis. Instead of
trying to estimate these values, the EEVI uses an alternative approach based on total revenues
for each sector. In this approach, annual revenue data is used as a proxy for production data.
This data is normalized such that the baseline price is set equal to $ I/unit and the baseline
quantity is then equal to the annual revenue. This allows estimation of the relative price
change and the relative quantity change due to the new standards, although it does not allow
estimation of the absolute price and absolute quantity change.
7-44
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Economic Impact Analysis
Baseline data for the EIM's railroad and marine service revenues are reported in Table
7-15.16 Revenue data for the rail transportation services market for 2005 comes from the
Association of American Railroads Freight Railroad Statistics, Condensed Income
17
Statement. The data for revenue for freight and passenger services are used
M
Revenue data for the marine transportation services sector come from the U.S. Census
reports revenues for the marine service sector for 2002.N Revenue data for 2002 was obtained
for the marine transportation sectors that are likely to be affected by this rule.18 These are:
4831: Deep sea, coastal, and Great Lakes transportation - 2 sectors were used:
o 483113: Coast and Great Lakes Freight
o 483114: Coast and Great Lakes Passenger
4832: Inland water transportation
4872: Scenic & sightseeing transportation, water
4883: Support activity for water transportation - the revenue for this sector
was adjusted to reflect only the portion of support activity that would be
associated with sectors 4831 and 4832 (water transportation excluding deep
sea), by applying the ratio of affected water transportation revenue to total
revenues for Sectors 4831 and 4832.
Table 7-15. Railroad and Marine Service Markets Baseline Revenue Data (Sbillions)
Transportation Service Market
Railroad Services Market
Freight revenue: $44,457M
Passenger revenue: $65M
Marine Services Market
2002
NR
$13.8
Annual Growth Rate
0.9%
0.9%
2005
$44.5
$15.4
The 2002 marine revenue data was adjusted for 2005 using the GDP deflator index.
To estimate revenue for 2005, we applied growth rates used for engine sales. Revenue for all
future years of the analysis (2007 to 2040) were calculated by applying annual growth rates to
the 2005 data set as follows:
Revenue2oox = Revenue2oos x (1+0.009)'
(200X-2005)
M It should be noted that this revenue estimate includes a return on investment, which reflects the prices for
transportation services experienced by rail transportation service consumers.
N The revenue estimate for the marine transportation sector used in this analysis is based on an earlier estimate of
revenues from the affected marine transportation sectors. Our final draft estimate is slightly lower. The
difference is less than 5 percent and will not change the conclusions of this economic impact analysis .
7-45
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Regulatory Impact Analysis
This data suggests that the rail transportation sector is much larger than the marine
transportation sector. However, the difference in the amount of tons of goods moved is
smaller. According to AAR, the rail transportation sector moved about 1,844.2 million tons
of freight in 2004.19 The marine sector accounted for about 1,047.1 million tons in that
^f\
year. This suggests that while some of the difference in revenue is due to differences in the
amount of freight transported, part of the difference is due to differences in the characteristics
of each sector. For example, railroads are responsible for maintaining the rail system; they
pass some of those costs to their customers through higher prices. The marine system, in
contrast, is maintained by public authorities (U.S. Army Corps of Engineers, state and local
governments), and so those costs would not be reflected in the prices of marine transportation
services. Similarly, while rail yards are maintained by railroads, ports are owned and
operated by various public and private authorities. Finally, marine transportation is somewhat
more fuel efficient than rail, with one tug or towboat able to transport more goods than one
locomotive.
7.3.2 Compliance Costs
The social costs of the new standards are estimated by shocking the initial market
equilibrium conditions by the amount of the compliance costs.
The engineering costs we used in the EIA are an earlier version of the estimated
compliance costs developed for this rule. The net present value of the engineering costs used
in the EIA is estimated to be approximately $9.17 billion (NPV over the period of analysis at
3 percent discount rate), which is about $240 million less than the net present value of the
final estimated engineering costs of about $9.41 billion. This difference is the sum of various
cost adjustments, the largest of which are an increase of about $222 million in operating costs
for the marine markets and $42 million in the operating costs for the rail markets (NPV over
the period of analysis at 3 percent discount rate). These changes are not expected to have a
substantial impact on the market level results because the differences are relatively small on
an annual basis. For example, operating costs for C2 marine markets increase by about 15
percent in 2030 (from $107 million to $123 million). The previous estimate of $107 million
was associated with an increase of approximately 1.1 in the price of marine transportation
services and a decrease of approximately 0.5 percent in the quantity of marine transportation
services provided. A small increase in operating costs is not likely to change those results by
very much. The market-level impacts on the other downstream markets are also likely to be
very small and not economically significant. Finally, the difference in compliance costs will
not affect the distribution of social costs, which is a function of the price elasticity of supply
and demand.
Table 7-16 summarizes how the compliance costs are applied to each component of
the EIM to simulate the effect of the emission control program. On the supply side, only
variable costs are used to shift the supply curve in the relevant markets (see Section 7.2.3.4).
Fixed costs are added to the social costs of the program as a separate line item. In this model,
the demand curves are not shifted because the program does not regulate consumers or
impose direct compliance costs on them and therefore would not cause a change in demand
(see Section 7.2.3.1).
7-46
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Economic Impact Analysis
Table 7-16. Summary of Types of Compliance Costs
Market
Rail
Marine
Category
Locomotive
Transportation
Services
<800 hp
>800 hp
Transportation
Services
Supply Shift
Entity
Loco Mfr
Railroad
Engine Mfr
Vessel
Engine mfr
Vessel
Vessel
Owner
Direct Costs
Variable costs
Reductant, fuel,
remanufacture kit
Variable costs = 0
Variable costs = 0
Variable costs
Variable costs
Reductant, fuel,
remanufacture kit
Indirect Costs
N/A
Higher
locomotive
prices
N/A
Higher engine
prices
N/A
Higher engine
prices
Higher engine
and vessel prices
Demand Shift
No demand
shift; see
7.2.3.1
The compliance costs used in the EIM are based on the estimated engineering
compliance costs described in Chapter 5.
For marine diesel engine variable costs, we used the piece costs shown in Table 5-29.
Note that, as explained in Chapter 5, there are no variable costs associated with the Tier 3
standards for the marine program. We do not expect the prices of engine components used to
meet the Tier 3 standards will be different from those used to meet the Tier 2 standards. For
marine diesel engine fixed costs in the EIA, we simply divided the annual engine fixed costs
presented in Tables 5-3, 5-10, 5-14, and 5-17 by the projected sales for the given year. When
doing this, it is important to stay within category (e.g., marine Cl annual costs should be
divided by marine Cl annual sales). This makes the fixed costs per engine appear rather large
in the EIA since those costs are being spread over a relatively small number of engines during
the years in which the cost are incurred.
On the vessel side, there are no compliance costs, fixed or variable, associated with the
Tier 3 standards since the engine-based controls are not expected to affect the footprint of the
engine. For the Tier 4 compliance costs we used the vessel hardware costs shown in Tables
5-38 and 5-39. Importantly, the costs associated with engines (discussed above) are incurred
for every engine (auxiliary and propulsion), while the vessel hardware costs show in Tables 5-
38 and 5-39 are incurred for every vessel. To arrive at a per vessel cost for the EIA, we added
the aftertreatment housing costs shown in Table 5-38 to the reductant system costs shown in
Table 5-39, keeping in mind the near-term (years one and two) and long-term (years three and
later) costs presented in Table 5-39. The vessel fixed costs are the annual redesign costs
shown in Table 5-36 divided by the projected number of vessel sales during the given years as
shown in Tables 5-41 and 5-42. Tier 4 marine vessel compliance costs (costs for vessel
redesign) are incurred over an 18-year period that is derived from the number of vessel types
that will have to be modified (see Chapter 5 for an explanation of how these costs are
calculated).
7-47
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Regulatory Impact Analysis
For locomotives, we used essentially the same methodology. The variable costs are
taken from Tables 5-29, 5-38, and 5-39. Annual fixed costs are simply divided by the sales
for the given year in which the costs are incurred. In the EIA, since the locomotive and its
engine are considered to be one in the same, there was no need to differentiate between purely
engine costs and equipment costs.
For all markets, fixed costs are allocated to the year in which they occur. For this
analysis, fixed costs are spread over five years in advance of the applicable standards with the
exception of tooling and certification costs, which are allocated to the year before the
standards are effective. Variable costs begin to be incurred only when the programs go into
effect. For simplicity of presentation, we have estimated marine engine and equipment costs
as though all marine Tier 3 standards begin in 2011 and all marine Tier 4 standards begin in
2016. For locomotives and marine diesel engines, this means a staggered set of fixed costs, as
described in Table 7-17, with the compliance costs for the different tiers overlapping on some
years.
The annual compliance costs used to shock the model are the sum of the relevant
compliance costs for a given year. The staggered nature of the emission control programs
means that for the initial years of the program the annual estimated variable costs may include
fixed costs for complying with both Tier 3 and Tier 4 requirements. Similarly, fixed costs
may combine Tier 3 and Tier 4 compliance costs, depending on which programs are phased-in
for that year. As a result, the compliance costs described below may be due to Tier 3 costs,
Tier 4 costs, or both. This approach is appropriate because the EIA is intended to look at the
social costs of the regulatory program as a whole and not by tier of standards.
Table 7-17 Examples of Locomotive and Marine Engine Staggered Compliance Costs Schedule
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Line haul Locomotive
TierS
Fixed
Fixed
Fixed
Fixed
Fixed (inc. cert.)
Effective Date;
Variable
Variable
Variable
Variable
Variable
Variable
Tier 4
Fixed
Fixed
Fixed
Fixed
Fixed (inc. cert.)
Effective Date;
Variable
Variable
Variable
Commercial Marine
3.5-7 1/cyl, 1,400-2,000 hp
Marine T3
Fixed
Fixed
Fixed
Fixed
Fixed (inc. cert.)
Effective Date;
Variable
Variable
Variable
Variable
Variable
Variable
Marine T4
Fixed
Fixed
Fixed
Fixed
Fixed (inc. cert.)
Effective Date;
Variable
Variable
7-48
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Economic Impact Analysis
7.3.2.1 Locomotive Compliance Costs
The estimated per unit compliance costs for new locomotives used in the EIM are
summarized in Table 7-18. These costs are dominated by fixed costs in the early years of the
program. Variable costs do not occur until 2015, when the aftertreatment standards begin.
This reflects the fact that there are no variable costs associated with the Tier 3 standards.
Fixed costs reflect both the Tier 3 and Tier 4 costs.
Table 7-18 Estimated Per Unit Compliance Costs - New Locomotives (2005$)
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019+
Line Haul Locomotive
Variable
$0
$0
$0
$0
$0
$0
$0
$0
$84,274
$84,274
$65,343
$65,343
$65,343
Fixed
$9,294
$9,007
$8,657
$45,894
$46,534
$35,791
$35,878
$39,278
$0
$0
$0
$0
$0
Total
$9,294
$9,007
$8,657
$45,894
$46,534
$35,791
$35,878
$39,278
$84,274
$84,274
$65,343
$65,343
$65,343
Switcher, Passenger Locomotive
Variable
$0
$0
$0
$0
$0
$0
$0
$0
$14,175
$14,175
$23,682
$23,682
$21,139
Fixed
$27,904
$27,904
$27,904
$53,856
$75,341
$78,642
$78,175
$104,927
$51,847
$78,520
$0
$0
$0
Total
$27,904
$27,904
$27,904
$53,856
$75,341
$78,642
$78,175
$104,927
$66,023
$92,695
$23,682
$23,682
$21,139
7.3.2.2 Marine Diesel Engine Compliance Costs
The estimated per unit compliance costs for new marine diesel engines used in the
ELM are summarized in Table 7-19 (C2 propulsion engines), Table 7-20 (Cl propulsion
engines), Table 7-21 (recreational engines), and Table 7-22 (small engines). In the early
years, 2007 through 2011, there are fixed costs associated with the Tier 3 standards.
Beginning in 2012, there are no compliance costs associated with the Tier 3 standards because
there are no variable costs for those standards. The Tier 4 standards apply only to engines
above 800 hp. As a result, there are fixed costs attributed to those engines through 2015, after
which time the only costs are variable costs associated with the aftertreatment devices.0
In our engineering cost analysis, propulsion and auxiliary engines have the same
compliance costs. To facilitate and accommodate computer programming constraints,
however, it was necessary to run the model using a simplified approach for the auxiliary
engine markets, in which the compliance costs are a weighted average of all compliance costs
0 For simplicity, the marine engine and equipment standards are estimated as though all marine Tier 4 standards
begin in 2016 even though some Tier 4 standards for very large engines begin in 2014. While this affects the
individual year results for early years, the differences disappear by 2016 at which time all marine diesel engines
above 800 hp are subject to aftertreatment standards.
7-49
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Regulatory Impact Analysis
for engines above 800 hp. This weighted average is applied to auxiliary engines 800-2,000 hp
and those above 2,000 hp. This means that the supply shift is the same for both of the
auxiliary engine markets even though the actual program impacts are different for them. The
weighted average compliance costs was obtained by dividing the total compliance costs for
engines above 800 hp by the number of engines above 800 hp. This results in estimated
compliance costs of $37,097 in 2016, the first year of the Tier 4 program. If separate
compliance costs had been used for the two auxiliary engine markets, they would have been
$19,073 for 800-2,000 hp, and $67,255 for above 2,000 in that year. The aggregated
compliance costs approach results in a higher price impact for auxiliary engines 800-2,000 hp
and a smaller price impact for auxiliary engines above 2,000 hp. These price impacts would
be passed along to the vessel markets as indirect costs of the program, with associated
impacts. We performed a sensitivity analysis that examines the impact of this approach; the
results of that analysis, reported in Appendix H, suggest that the results of the analysis would
not change very much if this simplifying approach were not used.
Table 7-19 Estimated Per Unit Compliance Costs - C2 Commercial Propulsion Engines (2005$)
Hp
Category
800-2,000
>2,000
Cost Type
Variable
Fixed
Total
Variable
Fixed
Total
2007
$0
$14,571
$14,571
$0
$14,571
$14,571
2008
$0
$14,441
$14,441
$0
$14,441
$14,441
2009
$0
$14,312
$14,312
$0
$14,312
$14,312
2010
$0
$14,184
$14,184
$0
$14,184
$14,184
2011
$0
$99,121
$99,121
$0
$99,121
$99,121
2012
$0
$74,808
$74,808
$0
$74,808
$74,808
Hp
Category
800-2,000
>2,000
Cost Type
Variable
Fixed
Total
Variable
Fixed
Total
2013
$0
$74,140
$74,140
$0
$74,140
$74,140
2014
$0
$73,479
$73,479
$0
$73,479
$73,479
2015
$0
$102,680
$102,680
$0
$102,680
$102,680
2016
$39,428
$0
$39,428
$73,360
$0
$73,360
2017
$39,428
$0
$39,428
$73,360
$0
$73,360
2018+
$30,142
$0
$30,142
$56,081
$0
$56,081
Table 7-20 Estimated Per Unit Compliance Costs - Cl Commercial Propulsion Engines (2005$)
Hp
Category
50-200
200-400
Cost Type
Variable
Fixed
Total
Variable
2007
$0
$836
$836
$0
2008
$0
$829
$829
$0
2009
$0
$822
$822
$0
2010
$0
$814
$814
$0
2011
$0
$1,549
$1,549
$0
2012
$0
$0
$0
$0
7-50
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Economic Impact Analysis
400-800
800-2,000
>2,000
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
$836
$836
$0
$836
$836
$0
$2,710
$2,710
$0
$2,710
$2,710
$829
$829
$0
$829
$829
$0
$2,686
$2,686
$0
$2,686
$2,686
$822
$822
$0
$822
$822
$0
$2,662
$2,662
$0
$2,662
$2,662
$814
$814
$0
$814
$814
$0
$2,638
$2,638
$0
$2,638
$2,638
$1,549
$1,549
$0
$1,549
$1,549
$0
$29,554
$29,554
$0
$29,554
$29,554
$0
$0
$0
$0
$0
$0
$25,963
$25,963
$0
$25,963
$25,963
Hp
Category
50-200
200-400
400-800
800-2,000
>2,000
Cost Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2013
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$25,732
$25,732
$0
$25,732
$25,732
2014
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$25,502
$25,502
$0
$25,502
$25,502
2015
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$34,190
$34,190
$0
$34,190
$34,190
2016
$0
$0
$0
$0
$0
$0
$0
$0
$0
$15,196
$0
$15,196
$26,401
$0
$26,401
2017
$0
$0
$0
$0
$0
$0
$0
$0
$0
$15,196
$0
$15,196
$26,401
$0
$26,401
2018+
$0
$0
$0
$0
$0
$0
$0
$0
$0
$11,618
$0
$11,618
$20,183
$0
$20,183
Table 7-21 Estimated Per Unit Compliance Costs - Recreational Engines (2005$)
Hp
Category
0-50
50-200
200-400
400-800
800-2,000
Cost Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2007
$0
286
286
$0
$286
$286
$0
$286
$286
$0
$286
$286
$0
$286
$286
2008
$0
279
279
$0
$279
$279
$0
$279
$279
$0
$279
$279
$0
$279
$279
2009
$0
272
272
$0
$272
$272
$0
$272
$272
$0
$272
$272
$0
$272
$272
2010
$0
266
266
$0
$266
$266
$0
$266
$266
$0
$266
$266
$0
$266
$266
2011
$0
486
486
$0
$486
$486
$0
$486
$486
$0
$486
$486
$0
$486
$486
2012
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
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Regulatory Impact Analysis
>2,000
Variable
Fixed
Total
$0
$286
$286
$0
$279
$279
$0
$272
$272
$0
$266
$266
$0
$486
$486
$0
$0
$0
Hp
Category
0-50 hp
50-200
200-400
400-800
800-2,000
>2,000
Cost Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2013
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
2014
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
2015
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
2016
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
2017
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
2018+
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
Table 7-22 Estimated Per Unit Compliance Costs - Small Marine Engines (2005$)
Hp
Category
0-50
Cost Type
Variable
Fixed
Total
2007
$0
$178
$178
2008
$0
$176
$176
2009
$0
$175
$175
2010
$0
$173
$173
2011
$0
$365
$365
2012
$0
$0
$0
Hp
Category
0-50
Cost Type
Variable
Fixed
Total
2013
$0
$0
$0
2014
$0
$0
$0
2015
$0
$0
$0
2016
$0
$0
$0
2017
$0
$0
$0
2018+
$0
$0
$0
7.3.2.3 Marine Vessel Compliance Costs
There are no direct vessel compliance costs associated with the Tier 3 standards. This
is because the Tier 3 engine footprint (engine size and weight) is not expected to be modified
from the Tier 2 configuration and therefore no vessel redesign or modification will be
required to accommodate Tier 3 engines. There are also no indirect vessel compliance costs
7-52
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Economic Impact Analysis
associated with the Tier 3 standards as there are no variable costs to the engine manufacturers
for the Tier 3 standards (the only Tier 3 compliance costs are fixed costs).
Direct vessel compliance costs are associated with the Tier 4 aftertreatment standards.
These compliance costs are not differentiated by vessel application; they are the same for all
commercial vessels that use Tier 4 propulsion engines. The magnitude of the compliance
costs varies depending on if they are Category 1 or Category 2 engines. The vessel
compliance costs begin to occur in 2015, with the fixed costs, which continue through 2028,
depending on the size of the engine.1" Variable costs begin to occur in 2016 and continue for
all years of the analysis.
Table 7-23 Per Unit Compliance Costs - Vessels with C2 Propulsion Engines (2005$; vessel equipped with
2 propulsion engines)
HP
Category
50-200
200-400
400-800
800-2,000
>2,000
Cost
Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2015
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$50,000
$50,000
$0
$50,000
$50,000
2016
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,586
$26,935
$33,520
$12,358
$26,935
$39,293
2017
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,586
$13,347
$19,933
$12,358
$13,347
$25,705
2018
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$13,228
$18,731
$10,385
$13,228
$23,614
2019
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$13,110
$18,613
$10,385
$13,110
$23,496
2020
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$12,993
$18,496
$10,385
$12,993
$23,379
2021
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$12,877
$18,380
$10,385
$12,877
$23,263
Hp
Category
50-200
200-400
400-800
Cost
Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2023
$0
$0
$0
$0
$0
$0
$0
$0
$0
2024
$0
$0
$0
$0
$0
$0
$0
$0
$0
2025
$0
$0
$0
$0
$0
$0
$0
$0
$0
2026
$0
$0
$0
$0
$0
$0
$0
$0
$0
2027
$0
$0
$0
$0
$0
$0
$0
$0
$0
2028
$0
$0
$0
$0
$0
$0
$0
$0
$0
2029
$0
$0
$0
$0
$0
$0
$0
$0
$0
2022
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$12,762
$18,265
$10,385
$12,762
$23,148
2030+
$0
$0
$0
$0
$0
$0
$0
$0
$0
p For simplicity, the marine engine and equipment standards are estimated as though all marine Tier 4 standards
begin in 2016 even though some Tier 4 standards for very large engines begin in 2014. While this affects the
individual year results for early years, the differences disappear by 2016 at which time all marine diesel engines
above 800 hp are subject to aftertreatment standards.
7-53
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Regulatory Impact Analysis
800-2,000
>2,000
Variable
Fixed
Total
Variable
Fixed
Total
$5,503
$12,649
$18,152
$10,385
$12,649
$23,034
$5,503
$12,536
$18,039
$10,385
$12,536
$22,921
$5,503
$12,424
$17,927
$10,385
$12,424
$22,809
$5,503
$12,313
$17,816
$10,385
$12,313
$22,699
$5,503
$12,203
$17,706
$10,385
$12,203
$22,589
$5,503
$12,095
$17,597
$10,385
$12,095
$22,480
$5,503
$0
$5,503
$10,385
$0
$10,385
$5,503
$0
$5,503
$10,385
$0
$10,385
Table 7-24 Cl Per Unit Compliance Costs - Vessels with Cl Propulsion Engines (2005$; vessel equipped
with 2 propulsion engines)
HP
Category
50-200
200-400
400-800
800-2,000
>2,000
Cost
Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2015
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$25,000
$25,000
$0
$25,000
$25,000
2016
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,586
$11,885
$18,470
$12,358
$11,885
$24,243
2017
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,586
$6,544
$13,129
$12,358
$6,544
$18,902
2018
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,891
$9,394
$10,385
$3,891
$14,277
2019
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,857
$9,359
$10,385
$3,857
$14,242
2020
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,822
$9,325
$10,385
$3,822
$14,208
2021
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,788
$9,291
$10,385
$3,788
$14,173
Hp
Category
50-200
200-400
400-800
800-2,000
>2,000
Cost
Type
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
Variable
Fixed
Total
2023
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,721
$9,224
$10,385
$3,721
$14,106
2024
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,688
$9,191
$10,385
$3,688
$14,073
2025
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,655
$9,158
$10,385
$3,655
$14,040
2026
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,622
$9,125
$10,385
$3,622
$14,007
2027
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,590
$9,093
$10,385
$3,590
$13,975
2028
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,558
$9,061
$10,385
$3,558
$13,943
2029
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$0
$5,503
$10,385
$0
$10,385
2022
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$3,754
$9,257
$10,385
$3,754
$14,140
2030+
$0
$0
$0
$0
$0
$0
$0
$0
$0
$5,503
$0
$5,503
$10,385
$0
$10,385
In addition to the direct vessel costs for Tier 4, there are also indirect costs associated
with the Tier 4 engine standards, for both propulsion and auxiliary engines. This means it is
necessary to shift the supply curve by the increase in price for both the propulsion and
7-54
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Economic Impact Analysis
auxiliary engines on the vessel that occurs as a result of the engine compliance costs. As
explained in Section 7.3.1.3, we assume each affected vessel has 2 propulsion engines and an
average of about 2 marine auxiliary engines. We allocated all auxiliary engines above 800 hp
to the vessels in this analysis even though some of these large auxiliary engines will be
installed on vessels with Category 3 propulsion engines that are not part of this rule. As a
result, while this rule considers the costs of all auxiliary engines, in fact not all of those costs
will be borne by stakeholders included in this rulemaking, and the share of the costs for
marine stakeholders is likely to be less.
7.3.2.4 Operating Costs
There are two types of operating costs that are affected by the control program: the
additional costs associated with operating vessels and locomotives equipped with the emission
control technologies that would be required by the program, and the additional costs
associated with the locomotive and marine remanufacture programs. Each of these is
described below. In the EIA, each of these is applied to the transportation markets because
they are costs that accrue to the operators of the regulated locomotives or marine vessels.
7-55
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Regulatory Impact Analysis
$1,200,000,000
$1,000,000,000
$800,000,000
$600,000,000
$400,000,000
$200,000,000
Figure 7-9. Estimated Total Compliance Costs by Type, 2007-2040
n'V
-New Marine Engines
-Loco operating
- New Marine Vessels
-Marine reman
New Locomotives
Loco reman
Marine operating
-Total Costs
7-56
-------
Economic Impact Analysis
Operating Costs. As explained in Chapter 5, we anticipate three sources of increased
costs associated with operating vessels and locomotives equipped with the emission control
technologies that would be required by the program: reductant use, DPF maintenance, and
fuel consumption. The costs associated with reductant use would affect only those
locomotives or vessels equipped with a SCR engine. Maintenance costs associated with the
DPF (for periodic cleaning of accumulated ash resulting from unburned material that
accumulates in the DPF) would occur only in those locomotives or vessels equipped with a
DPF engine. Thus, those costs are limited to Tier 4 engines. Fuel consumption impacts are
limited to Tier 4 locomotives and marine engines and, to a much smaller extent, for
remanufactured Tier 0 locomotives. As explained in section 5.4.3, and discussed in sections
4.2 and 5.2.2, Tier 3 engine are not expected to have a fuel impact. As illustrated in Figure 7-
9, the estimated operating costs are substantial when compared with the compliance costs
associated with engine and equipment modifications.
The EIM applies the operational costs solely to the rail and marine transportation
services markets.*2 This is accomplished by shifting the transportation service sector supply
curves by the amount of the operating costs for that sector for that year. This was done by
dividing the total operating costs for each service sector by the revenue for that year, where
revenue represents the quantity produced in each service sector (due to normalized costs; see
7.3.1.4). The operating costs per unit are then interpreted as costs per dollar of output.
Applying these costs to the locomotive transportation market, in the rail sector case, is
appropriate because all locomotives built after the Tier 4 standards go into effect will incur
these operating costs. On the marine side, the EIM uses a simplifying assumption that applies
all marine operating costs to the marine transportation services market and large fishing sector
(marine vessels that use engines >800 hp) and does not allocate any of these costs to the
recreational or small fishing sectors. This approach is appropriate because the operating costs
(fuel and reductant consumption) are estimated based on fuel consumption and most of the
fuel consumed in the marine sector is by vessels in the marine transportation services sector.
While many of the new non-recreational vessels built each year are small fishing vessels, the
use of fishing vessels is highly seasonal and hence they would not be expected to use as much
fuel as the other commercial vessels (tug/tow/pushboats, ferries, cargo vessels, and
supply/crew boats) that are used extensively all year around. Nevertheless, there are expected
to be some Tier 4 engines used in the fishing sector and depending on the extent to which this
occurs the estimated impacts on the marine transportation service market may be somewhat
over-estimated.
1 As explained above, the marine transportation market also includes large fishing vessels.
7-57
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Regulatory Impact Analysis
Table 7-25 Marine and Locomotive Operating Costs 2007-2040 (2005$)
2006
2007
2008
2009
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
Marine Cl>800Hp
$0
$0
$0
$0
$0
$0
$0
$0
$0
$0
$3,870,419
$10,570,247
$19,868,812
$29,127,012
$38,333,253
$47,486,990
$56,568,548
$65,562,936
$74,437,500
$83,177,448
$91,751,957
$100,108,209
$108,149,904
$115,215,712
$120,856,169
$125,288,414
$128,976,388
$132,310,485
$135,336,373
$138,043,673
$140,480,248
$142,716,999
$144,794,853
$146,732,986
$148,542,610
Marine C2
$0
$0
$0
$0
$0
$0
$0
$0
$oa
$oa
$3,293,306
$10,712,210
$18,184,444
$25,658,771
$33,115,211
$40,569,128
$48,025,843
$55,465,093
$62,887,279
$70,294,373
$77,704,458
$85,118,907
$92,522,545
$99,897,508
$107,239,121
$114,551,129
$121,812,042
$129,005,921
$136,127,702
$143,164,690
$150,075,487
$156,843,456
$163,398,588
$169,244,421
$173,848,627
Loco-Line haul
$0
$0
$0
$0
$0
$0
$0
$0
$0
$14,185,772
$29,032,183
$44,269,726
$59,812,022
$75,760,270
$92,240,224
$109,253,188
$126,758,381
$144,738,379
$162,686,068
$180,873,965
$199,101,463
$217,434,039
$235,760,387
$254,018,232
$272,104,628
$290,126,726
$308,100,481
$326,059,441
$343,920,178
$361 ,555,878
$378,402,501
$394,649,956
$410,285,116
$425,260,693
$439,565,559
Loco-Switcher &
Passenger
$0
$0
$0
$0
$0
$0
$0
$0
$0
$123,493
$247,890
$1,271,179
$1 ,964,807
$2,663,752
$3,368,108
$4,077,974
$5,181,423
$6,548,724
$7,632,591
$8,803,576
$10,036,091
$11,329,994
$12,693,251
$14,115,012
$15,635,903
$17,261,263
$18,968,553
$20,726,018
$22,559,417
$24,413,611
$26,218,259
$27,989,727
$29,715,888
$31,393,184
$33,044,952
Total
$0
$0
$0
$0
$0
$0
$0
$0
$0
$14,309,265
$36,443,798
$66,823,362
$99,830,086
$133,209,805
$167,056,796
$201,387,280
$236,534,195
$272,315,132
$307,643,438
$343,149,362
$378,593,969
$413,991,150
$449,126,087
$483,246,465
$515,835,820
$547,227,532
$577,857,463
$608,101,865
$637,943,670
$667,177,853
$695,176,495
$722,200,137
$748,194,446
$772,631,284
$795,001 ,748
For simplicity, the marine engine and equipment standards are estimated as though all marine Tier 4 standards begin in
2016 even though some Tier 4 standards for very large engines begin in 2014. While this affects the individual year results
for early years, the differences disappear by 2016 at which time all marine diesel engines above 800 hp are subject to
aftertreatment standards.
7-58
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Economic Impact Analysis
Remanufacturing Costs. The rail and marine transportation markets are also subject to
costs associated with the remanufacture standards for their existing engines. Locomotive
owners are currently required to use certified remanufacture kits when they rebuild engines
originally built in 1973 through 2001 (called Tier 0 locomotives). This program will extend
the remanufacturing requirements both to tighten the standards associated with Tier 0
locomotives and to add requirements for engines built after 2001 (Tier 1 and Tier 2
locomotives). The new emission control program also includes a program for existing marine
diesel engines, according to which owners would be required to use a certified remanufacture
system when they rebuild their engines if such a system is available. This program applies
only to marine diesel engines above 800 hp that were manufactured from 1973 through Tier 2.
In the EIM, these remanufacture costs are treated as operating costs and applied to the
rail and marine transportation sectors along with the reductant and fuel costs. This approach
was chosen because these costs are periodic and recurring throughout the life of the engine, at
five to seven year intervals. An important consequence of this modeling approach is that it
assumes that the owner bears the full cost of the remanufacturing kit and that the kit
manufacturer does not bear any of the cost. This simplifying assumption is appropriate
because the mandatory nature of the requirement results in a price elasticity of demand that is
close to zero (inelastic): if a railroad owns a Tier 0, Tier 1, or Tier 2 locomotive it very
simply must purchase a kit or it can no longer operate the locomotive. Similarly, if a vessel
operator owns an engine for which a kit is available, he or she is required use that kit when
rebuilding the engine. The cost of a remanufacture kit would have to be very high before the
option of pulling a locomotive or marine vessel out of service or purchasing a new engine one
would become attractive.
As explained in Chapter 5, the remanufacturing costs for Tier 0 and Tier 1
locomotives represent the difference between the cost of current remanufacture kits and those
that will be required pursuant to the standards. For these kits, first time rebuilds will require
additional fuel system components that are not required in subsequent rebuilds and therefore
the cost for the initial rebuild is more than for future rebuilds. For Tier 2 locomotives, there
are additional costs for the initial rebuild, but not for future rebuilds. There are no additional
costs associated with Tier 3 rebuilds because these locomotives have all of the essential
components when they are built new. Finally, there are rebuild costs for Tier 4 locomotives
associated with the aftertreatment devices. Tier 4 locomotives begin to be rebuilt in 2023.
For marine diesel engines, there is currently only one tier of requirements.
Tables 7-26 and 7-27 set out the estimated compliance costs for the locomotive
remanufacture program for line haul and switcher/passenger locomotives. These tables reflect
both the year in which the costs apply and the cost per unit. Also included are the fuel costs
associated with the use of Tier 0 remanufacture systems.
7-59
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Regulatory Impact Analysis
Table 7-26 Line Haul Locomotive Remanufacture Costs - Per Unit and Total Fuel Costs
Year Tier 0 Tier 1 Tier 2 Tier 4 Tier 0 Fuel Costs
($MM)
2006
2007
2008
2009
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
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$33,800
$33,800
$33,800
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$1 1 ,749
$1 1 ,749
$1 1 ,749
$1 1 ,749
$1 1 ,749
$1 1 ,749
$1 1 ,749
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$67,534
$2,302,054
$2,282,427
$5,890,678
$12,215,776
$14,835,459
$18,419,581
$19,255,764
$19,332,128
$21 ,973,242
$24,371,317
$23,707,717
$22,654,591
$20,943,018
$19,132,536
$17,393,944
$15,727,242
$14,132,429
$12,621,451
$11,145,346
$9,760,539
$8,459,667
$7,255,299
$6,169,878
$5,180,024
$4,280,592
$3,461,230
$2,640,362
$1 ,944,832
$1,380,746
$906,104
$524,244
$246,131
$74,669
7-60
-------
Economic Impact Analysis
Table 7-27 Switcher and Passenger Remanufacture Costs - Per Unit and Total Fuel Costs
Year Tier 0 & 1 Tier 2 Tier 4 Tier 0 Fuel Costs
($MM)
2006
2007
2008
2009
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
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$22,300
$8,728
$8,728
$8,728
$8,728
$8,728
$8,728
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$21 ,937
$75,733
$265,064
$452,881
$627,823
$695,983
$752,782
$798,979
$740,665
$761,113
$773,987
$685,380
$602,074
$518,011
$433,190
$347,613
$274,152
$212,051
$153,737
$106,026
$68,159
$39,381
$18,933
$6,059
Table 7-28 sets out the estimated compliance costs for the marine remanufacture
program locomotives. This table reflect both the year in which the costs apply and the cost
per unit. Also included are the fuel costs associated with the program.
7-61
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Regulatory Impact Analysis
Table 7-28 Marine Remanufacture Costs - Per Unit and Total al Fuel Costs
Year Category 1 Category 2 Fuel Costs ($MM)
2006
2007
2008
2009
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
$16,900
$16,900
$16,900
$16,900
$16,900
$11,150
$11,150
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$33,800
$5,644,717
$11,391,038
$17,240,336
$23,193,999
$29,253,431
$34,882,042
$39,067,796
$37,438,192
$35,809,907
$34,190,014
$32,575,327
$30,962,228
$29,357,401
$27,761,110
$26,173,086
$24,593,388
$23,021 ,891
$21 ,458,087
$19,900,133
$18,351,377
$16,812,402
$15,290,458
$13,788,862
$12,311,399
$10,857,990
$9,442,047
$8,067,051
$6,749,194
$5,591 ,972
$4,774,057
$4,211,541
$3,723,095
$3,286,099
7.3.3 Behavioral Parameters
A key feature of the EIM is that it is a behavioral model in that it incorporates
economic theory related to producer and consumer behavior to estimate changes in market
conditions. As explained in 7.2.1, a behavioral model allows us to examine how
manufacturers of affected goods make out adjustments in response to higher production costs
due to complying with the control program, and how consumers can be expected to change
their consumption choices in response to higher prices resulting from producers passing along
at least some part of the compliance costs. The result of these market interactions determines
both the new market equilibrium price and quantity and the portion of the compliance costs
7-62
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Economic Impact Analysis
that will be born by producers and consumers. Thus, the price elasticity of supply and
demand are important parameters in behavioral models such as the EIM because they
represent how much production and consumption can be expected to change as a result of a
price increase.
Tables 7-29 and 7-30 provide a summary of the price elasticities of demand and
supply that are used as behavioral parameters in the EIM. Elasticities from peer-reviewed
literature were used when possible. If no peer-reviewed elasticities were available, they were
estimated for this economic impact analysis using generally accepted empirical methods (see
Appendix 7F for a discussion of how they were estimated). Several demand elasticities (those
for locomotives, commercial marine vessels, and marine diesel engines) are derived internally
by the EIM based on upstream markets (transportation markets). This is another behavioral
feature of the model that allows linkages between the different components of the model.
It should be noted that the price elasticities of supply and demand used in the model
reflect intermediate-run behavioral changes. This is appropriate because the EIM is intended
to estimate economic impacts as markets adjust to increases in compliance costs. In the long
run, supply and demand behavioral responses are expected to be more elastic since more
changes can be made to production processes.
7.3.3.1 Price Elasticity of Demand for Affected Markets
The EIM requires that values be specified for the price elasticity of demand for the rail
and marine transportation markets, the recreational vessel market, and the small fishing vessel
markets.
The price elasticity for rail transportation services demand is from the peer-reviewed
literature and is inelastic (-0.5).21 This means that the quantity demanded is not expected to
be sensitive to price changes (a one percent increase in price is expected to result in a 0.5
percent decrease in the quantity demand). This is reasonable because, as described above,
users of these transportation services typically chose them because they are the best solution
for transporting their goods. The decision to choose rail transportation services is a function
of many things and the price may not be the most important factor.
We were unable to find a price elasticity of demand for the marine transportation
sector in the peer-reviewed literature. Due to difficulties in gathering the appropriate data to
estimate this elasticity, we instead use the same demand elasticity as the rail transportation
services market. This is reasonable because a significant portion of the marine transportation
sector is engaged in the same basic activity, although with different geographic constraints.
Like locomotives, vessels used in marine transportation services (e.g., cargo vessels, ferries,
supply/crew boats, and tow/tug/pushboats) are engaged in transporting materials and people,
and the demand for those services is likely to be inelastic because the users have few, if any,
alternatives.
For the recreational vessel market, we used the same price elasticity of demand used in
the Economic Impact Analysis for our recently proposed SI marine standards.22 This price
elasticity of demand is elastic (-2.0), meaning that consumers are expected to be sensitive to a
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change in price (a one percent increase in price is expected to result in a two percent decrease
in the quantity demanded). This is reasonable because recreational marine vessels are a
discretionary purchase and consumers have other recreational alternatives.
We were also unable to find a price elasticity of demand for the fishing sector in the
peer-reviewed literature. In this analysis, we used a dual approach. Specifically, for large
fishing vessels (those with propulsion engines above 800 hp) we applied the same price
elasticity of demand as for commercial vessels (as explained elsewhere, this demand elasticity
is derived as part of the model from the transportation services sector); for small fishing
vessels (those with propulsion engines below 800 hp) we applied the same price elasticity of
demand as for recreational vessels. This approach is appropriate because smaller fishing
vessels are not used in the same way as larger fishing vessels. Smaller vessels are often
personally operated by the owner of the vessel; if there is a crew it would be very small.
These vessels are used for specific applications in which catches are small and speed is
essential (e.g., lobster fishing). This market can very competitive: the catch is bought the
same day as the vessel returns to port, with the earliest arrivers getting the best price. Because
of these dynamics, the price elasticity of fishing vessels is likely to be fairly elastic (fish
vessel purchasers likely to be sensitive to an increase in the price of a vessel). Vessels with
larger engines, on the other hand, are likely to be part of a large commercial operation,
making them less sensitive to vessel price changes. These vessels have larger crews and will
go out for several weeks or months. The catch will be larger and may even be processed
onboard the vessel or frozen for shore processing. For these vessels, we used the same
approach as commercial vessels, in which the price elasticity of demand for the equipment is
derived from the transportation market. This approach implies that the price elasticity of
demand for final consumers offish is inelastic (-0.5); this is reasonable given a previously-
estimated price elasticity of demand for the agricultural products market estimated for our
2004 Nonroad Rule (-0.2).23
7.3.3.2 Supply Elasticities
Unlike the price elasticity of demand, the EEVI requires that values be specified for the
price elasticity of supply for each of the markets included in the model; none of these values
are derived by the model.
The price elasticity of supply for the rail transportation service market is the same as
that estimated for the economic impact analysis for our Clean Air Nonroad Diesel (Nonroad
Tier 4) rule. 24 This price elasticity of supply is elastic (1.6), meaning that producers are
expected to be sensitive to a change in price (a 1 percent price increase is expected to result in
a 1.6 increase in the quantity produced). This reflects extra production capacity in the market
and the relative ease with which railroads can alter their production of transportation services
(e.g., by making trains longer or shorter).
A published estimate of the price elasticity of supply for the locomotive market was
unavailable. Therefore we estimated a value for this parameter using the calibration method
approach (this approach and the results are described in Appendix 7F). At 2.7, the price
elasticity of supply for the locomotive market is elastic, meaning that producers are expected
to be sensitive to changes in price (a one percent increase in price is expected to result in a 2.7
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percent increase in quantity produced). This reflects extra production capacity in the market.
The EIM uses the same value for the price elasticity of supply for all locomotive markets:
line haul, switcher, and passenger. Using this estimated price elasticity of supply for the
switcher market is somewhat speculative since that market is currently not very developed
(most existing switchers are modified line haul locomotives; see above).
For the marine transportation services market, we used the same approach as for the
economic impact analysis for our Clean Air Nonroad Diesel rule and applied the price
elasticity of supply used for the train transportation market. 25 This approach is reasonable
because the marine transportation service sector provides a similar service, although with
different geographic constraints.
A published estimate of the price elasticity of supply for the commercial vessel market
was unavailable. Therefore we estimated a value for this parameter using the calibration
method approach (this approach and the results are described in Appendix 7F). At 2.3, the
price elasticity of supply for the locomotive market is elastic, meaning that producers are
expected to be sensitive to changes in price (a one percent increase in price is expected to
result in a 2.3 percent increase in quantity produced). This reflects excess production capacity
in the market.
For the recreational vessel market, we used the same price elasticity of supply used in
the Economic Impact Analysis for our recently proposed SI marine standards.26 This price
elasticity of supply is elastic (2.3), meaning that producers are expected to be sensitive to a
change in price (a one percent increase in price is expected to result in a 2.3 percent increase
in the quantity produced). This is reasonable since recreational vessels are typically serially
produced with no specific buyer in mind, using fiberglass molds. Therefore a price increase
may have to be higher before affecting production. Also, to some extent, these vessels are
more "portable" and can be inventoried, although model year and design may limit the ability
of manufacturers to inventory large numbers of these vessels.
For the fishing vessel market, we used the same approach described above for the
supply elasticity of demand, applying the price elasticity of supply for commercial vessels to
fishing vessels with engines greater than 800 hp, and the price elasticity of supply for
recreational vessels for fishing vessels with engines less than 800 hp. This is reasonable
because smaller vessels have many of the same characteristics as recreational vessels (high-
speed planning vessels with fiberglass hulls), while larger vessels are produced more like
commercial vessels (uniquely built for an identified purchaser based on designs that are
typically modified by the purchaser before production). Because of these similarities, the
processes used to produced small and large fishing vessels would be more like recreational
and commercial vessels, respectively. It should be noted that, in this case, the price
elasticities of supply for both markets are the same (2.3).
For the marine diesel engine market, we used the same price elasticity of supply for
diesel engines that was estimated for the economic impact analysis for our 2004 Clean Air
Nonroad Diesel rule.27 This approach is reasonable because the vast majority of marine diesel
engines affected by this rule are derived from land-based marine or highway diesel engines.
This price elasticity of supply is elastic (3.8), meaning that producers are expected to be
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Regulatory Impact Analysis
sensitive to a change in price (a one percent increase in price is expected to result in a 3.8
increase in supply). This is due to excess production capacity.
Because the price elasticity of demand and supply are key inputs to the model, a
sensitivity analysis was performed to consider the uncertainty that is associated with the
estimation process. The sensitivity analysis includes alternative values for the price elasticity
of supply for locomotives and marine vessels estimated using an alternative method in lieu of
the calibration method. The results are presented in Appendix 7H.
Table 7-29. Price Elasticities of Demand Used in EIM
Market
Estimate
Source
Method
Data Source
Rail
Rail Transp.
Svcs
Locomotives
-0.5
Literature
estimate
Literature
review
Boyer, K.D. 1997. Principles of
Transportation Economics. Reading, MA:
Addison- Wesley.
Derived
Marine
Marine
Transp. Svcs
Vessels
Commercial
Fishing
(>800 hp)
Vessels
Fishing
(<800 hp)
Vessels
Recreational
Engines
-0.5
Literature
estimate
Assumed
value
Uses the same elasticity as the locomotive
transportation services sector.
Derived
-2.0
-2.0
Econometric
estimate
Econometric
estimate
Assumed
value
Previous
EPA
economic
analysis
Uses the same elasticity as the recreation
vessels sector.
U.S. Environmental Protection Agency
(EPA). 2007. Control of Emissions from
Marine SI and Small SI Engines, Vessels,
and Equipment Draft Regulatory Impact
Analysis. EPA420-D-07-004. Available at
.
Derived
Table 7-30. Supply Elasticities Used in EIM
Market
Estimate
Source
Method
Input Data Source
Rail
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Economic Impact Analysis
Rail Transp.
Svcs
1.6
Literature
estimate
Method based
on cost
elasticities
reported in
Ivaldi and
McCollough
(2001)
Ivaldi, M. and McCullough, G. 2001.
"Density and Integration Effects on Class I
U.S. Freight Railroads." Journal of Regulatory
Economics 19:161-162.
Locomotives
2.7
EPA
estimate
Calibration
method
U.S. Bureau of the Census. 2004a. "Railroad
Rolling Stock Manufacturing: 2002." 2002
Economic Census Manufacturing Industry
Series. EC02-311-336510 (RV). Washington,
DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2005. "Statistics
for Industry Groups and Industries: 2004"
Annual Survey of Manufacturers. M04(AS)-1.
Washington, DC: U.S. Bureau of the Census.
Table 2.
Marine
Marine
Transp. Svcs
1.6
Assumed value; uses the same elasticity as the rail transportation services sector
Vessels
Commercial
and large
fishing
2.3
EPA
estimate
Calibration
method
U.S. Bureau of the Census. 2004b. "Ship
Building and Repairing: 2002." 2002
Economic Census Manufacturing Industry
Series. EC02-31I-336611 (RV). Washington,
DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2005. "Statistics
for Industry Groups and Industries: 2004"
Annual Survey of Manufacturers. M04(AS)-1.
Washington, DC: U.S. Bureau of the Census.
Table 2.
Vessels
Recreational
and small
fishing
2.3
Econometric
estimate
Previous EPA
economic
analysis
U.S. Environmental Protection Agency
(EPA). 2007. Control of Emissions from
Marine SI and Small SI Engines, Vessels, and
Equipment Draft Regulatory Impact Analysis.
EPA420-D-07-004. Available at
.
Engines
Econometric
estimate
Previous EPA
economic
analysis
U.S. Environmental Protection Agency
(EPA). 2004. Final Regulatory Impact
Analysis: Control of Emissions from Nonroad
Diesel Engines. EPA420-R-04-007.
Available at .
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7.3.4 Economic Impact Model Structure
7.3.3.1 Estimating With-Regulation Equilibrium Conditions
The economic impact analysis is conducted using the data and the supply and demand
framework described above. The price and quantity data, along with the supply and demand
elasticities, are used to identify the market supply and demand curves. The regulatory costs
are then used to shift the supply curve, and the resulting new equilibrium determines the
market impacts and distribution of social impacts.
Figure 7-10 illustrates the economic impact modeling structure. Point A represents the
initial baseline equilibrium price and quantity (corresponding to the prices and quantities
presented in section 7.3.1). The slope of the supply and demand curves passing through the
baseline point A are determined by applying the appropriate supply and demand elasticities
presented in section 7.3.2.6. These slopes reflect the responsiveness of producers and
consumers when prices change and determine how much of the compliance costs producers
are able to pass along to consumers in the with-regulation equilibrium.
The compliance costs associated with the regulation (presented in Section 7.3.2) enter
the model expressed as per-unit costs and result in an upward shift in the supply curve from So
to Si in Figure 7-10. Note that the demand curve does not shift because consumer preferences
and income are not affected by the regulation (see Section 7.3.2.1)
With the addition of the compliance costs, if prices were not allowed to adjust
demanders would still want to consume the quantity at point A, but suppliers would only be
willing to supply the quantity at point B (i.e., demand exceeds supply at the baseline price, P).
The model then solves for the new equilibrium price (P*) where the quantity demanded
equals the quantity supplied. The movement from the baseline equilibrium point A to with-
regulation equilibrium point C determines the market impacts (changes in price and quantity)
as well as the distribution of social costs. Appendix 7E describes the set of supply and
demand equations included in the model. Given the number of equations included in the
model, the solution algorithm described below is used to identify the new with-regulation set
of equilibrium prices and quantities (Point C).
The analysis illustrated in Figure 7-10 is repeated for each year included in the period
of analysis. For future years, a projected time series of prices and quantities are developed
and used as the baseline (point A) from which market changes are evaluated. The engineering
cost analysis provides quantities for future years using historical annual growth rates. In
contrast, there is much more uncertainty surrounding future prices for these markets. As a
result, we use a constant 2005 observed prices for the relevant markets during the period of
analysis.
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Figure 7-10 Estimating With-Regulation Equilibrium
$/Q
Price
Increase
: With Regulation
S0: Without
Regulation
Q/t
7.3.3.2 Solution Algorithm
Supply responses and market adjustments can be conceptualized as an interactive
process. Producers facing increased production costs due to compliance are willing to supply
smaller quantities at the baseline price. This reduction in market supply leads to an increase
in the market price that all producers and consumers face, which leads to further responses by
producers and consumers and thus new market prices, and so on. The new with-regulation
equilibrium is the result of a series of iterations in which price is adjusted and producers and
consumers respond, until a set of stable market prices arises where total market supply equals
market demand. Market price adjustment takes place based on a price-revision rule, described
below, that adjusts price upward (downward) by a given percentage in response to excess
demand (excess supply).
The EIM model uses a similar type of algorithm for determining with-regulation
equilibria and the process can be summarized by six recursive steps:
1. Impose the control costs on affected supply segments, thereby affecting their supply
decisions.
2. Recalculate the market supply in each market. Excess demand currently exists.
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3. Determine the new prices via a price revision rule. We use a rule similar to the factor
price revision rule described by Kimbell and Harrison.28 P; is the market price at
iteration I, qd is the quantity demanded, and qs is the quantity supplied. The parameter
z influences the magnitude of the price revision and speed of convergence. The
revision rule increases the price when excess demand exists, lowers the price when
excess supply exists, and leaves the price unchanged when market demand equals
market supply. The price adjustment is expressed as follows:
4. Recalculate market supply with new prices,
5. Compute market demand in each market.
6. Compare supply and demand in each market. If equilibrium conditions are not
satisfied, go to Step 3, resulting in a new set of market prices. Repeat until
equilibrium conditions are satisfied (i.e., the ratio of supply and demand is arbitrarily
close to one). When the ratio is appropriately close to one, the market- clearing
condition of supply equals demand is satisfied.
7.3.5 Estimating Impacts
Using the static partial equilibrium analysis, the EIM model loops through each year
calculating new market equilibriums based on the projected baseline economic conditions and
compliance cost estimates that shift the supply curves in the model. The model calculates
price and quantity changes and uses these measures to estimate the social costs of the rule and
partition the impact between producers and consumers. This approach follows the classical
treatment of tax burden distribution in the public finance literature.29
7.4 Methods for Describing Uncertainty
Every economic impact analysis examining the market and social welfare impacts of a
regulatory program is limited to some extent by limitations in model capabilities, deficiencies
in the economic literatures with respect to estimated values of key variables necessary to
configure the model, and data gaps. In this EIA, there are three main potential sources of
uncertainty: (1) uncertainty resulting from the way the EIM is designed, particularly from the
use of a partial equilibrium model; (2) uncertainly resulting from the values for key model
parameters, particularly the price elasticity of supply and demand; and (3) uncertainty
resulting from the values for key model inputs, particularly baseline equilibrium price and
quantities. Sources of uncertainty that have a bearing on the results of the EIA for the new
emission control program are listed and described in more detail in Table 7-31.
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The values used for the price elasticities of supply and demand are critical parameters
in the EIM. The values of these parameters have an impact on both the estimated change in
price and quantity produced expected as a result of compliance with the new standards and on
how the burden of the social costs will be shared among producer and consumer groups. In
selecting the values to use in the EIM it is important that they reflect the behavioral responses
of the industries under analysis.
The first source of values for elasticities of supply and demand is the published
economic literature. These estimates are peer reviewed and generally constitute reasonable
estimates for the industries in question. In this analysis, we use published elasticity from
peer-reviewed literature for the rail transportation services sector, for both demand and
supply.30 We used these elasticities for the marine transportation sector as well.
When published elasticities of supply or demand are not available, it is necessary to
estimate these values econometrically.
We used previously-estimated values for the price elasticity of supply for engines and
recreational vessels in this analysis, (see Appendix 7F). These estimates reflect a production
function approach using data at the aggregate industry level. This method was chosen
because of limitations with the available data: we were not able to obtain firm-level or plant-
level production data for companies that operate in the affected sectors. However, the use of
aggregate industry level data may not be appropriate or an accurate way to estimate the price
elasticity of supply compared to firm-level or plant-level data. This is because, at the
aggregate industry level, the size of the data sample is limited to the time series of the
available years and because aggregate industry data may not reveal each individual firm or
plant production function (heterogeneity). There may be significant differences among the
firms that may be hidden in the aggregate data but that may affect the estimated elasticity. In
addition, the use of time series aggregate industry data may introduce time trend effects that
are difficult to isolate and control.
To estimate the price elasticity of supply for the locomotive and commercial marine
vessel markets, we used a calibration method. This involves specifying an economic model
of supply, treating some of the parameters of the model as fixed using secondary data, and
solving for unknown parameters that replicate a benchmark data set (see Appendix F). This
approach introduces uncertainty in that the results are dependent on the underlying
assumptions and data used to construct the economic model. In our proposal, we noted that
we intended investigate alternative estimates for the price elasticity of supply for these two
industries, using the production function approach and cross-sectional data model at either the
firm-level or plant level from the U.S. Census. Because the results of that analysis have not
yet been peer reviewed, we did not use them in our primary analysis. However, we performed
a sensitivity analysis using those alternative values (see Appendix H).
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Table 7-31 Primary Sources of Uncertainty in the Economic Impact Analysis
Source of Uncertainly
Description
Potential Impact
UNCERTAINTIES ASSOCIATED WITH ECONIMIC IMPACT MODEL STRUCTURE
Partial equilibrium model -
The EIM domain is limited to the economic
sectors directly affected by the emission control
program; impacts on secondary markets are not
accounted for. However, the impacts are not
expected to be large as directly affected products
and services (locomotives and marine engines and
vessels) are production inputs (transportation
services) and are not a large share of total
production costs for final goods and services, or
are final goods for household consumption
Results may
understate social
costs; magnitude of
impact is uncertain
National level model
The EIM considers only national-level impacts;
regional impacts are not modeled. This is
appropriate because locomotive and marine
engine and vessel markets are national markets.
While there may be some regional differences
these are likely to be small due to the competitive
nature of the transportation industry.
Impacts uncertain
Supply side assumptions
On the supply side, industries are assumed to be
mature and behave linearly within the range of
analysis; no substitution between production
inputs. This is appropriate because per unit
compliance costs are not large enough to prompt a
major change in product design or assembly.
Impacts uncertain
Demand side assumptions
On the demand side, end consumer preferences or
consumption patterns are assumed to be constant
and behave linearly within the range of analysis.
This is appropriate because all other factors in the
demand function will not be changed by the new
standards.
Impacts uncertain
Constant price assumption
Prices are assumed to be constant across the
period of analysis. This is a reasonable
assumption since it is not possible to predict
changes in these prices over time (see Appendix
7H).
Impacts uncertain
Period of analysis
Each period of analysis is assumed to be
independent of previous period and producers are
assumed to not engage in long-term planning.
This means the impacts of multi-tier standards are
not smoothed among periods. Because the new
engine standards will not go into effect for several
years after the program is finalized, producers
may in fact take the full program into account in
production plans to minimize their costs
Estimated price
changes may be too
high for early
periods, too low for
later periods;
magnitude of impact
is uncertain
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Market shock
In the EIM, the market shocked by variable costs
only; fixed costs do not disturb the market
equilibrium. This is a result of the perfect
competition assumption implies market supply
curve is the industry average marginal cost curve.
This is appropriate because producers in these
industries generally plan for R&D and model
changes. A sensitivity analysis performed that
includes fixed costs in supply shift
Results may overstate
distribution of social
costs to some
producers, understate
market impacts;
magnitude of impact
is uncertain
Sensitivity analysis
performed
UNCERTAINTIES ASSOCIATED WITH PRICE ELASTICITY ESTIMATION
Uncertainty resulting from the functional form
used in the estimation, the data used (aggregate or
firm-level), the time period involved, sample size.
Impacts on
distribution of social
costs among
stakeholders (e.g.,
higher supply
elasticity would result
in less social costs for
manufacturers and
more social costs for
consumers)
Impacts on market
analysis (change in
price, change in
quantity produced)
; magnitude of impact
is uncertain
Sensitivity analysis
performed
UNCERTAINTIES ASSOCIATED WITH DATA INPUTS
Submarket groupings
Baseline equilibrium prices
Baseline equilibrium quantities
Submarket data is assumed to be representative
and capture the range of affected equipment.
However, the product groupings in NAICS or SIC
4-digit categories may include other engines or
equipment that may not have the same production
or consumption characteristics; these groupings
not behave the same way as the directly -affected
industries.
Estimated baseline equilibrium prices are
assumed to be representative and capture the
range of affected equipment, and reflect actual
transaction prices. However, the actual prices
paid by consumers may be different. Also, the
mix of products included in price analysis may
not be representative of the population.
Estimated baseline equilibrium quantities and
future quantities assumed to be representative;
these are the same as the cost analysis
Impacts on social
welfare and market
analyses uncertain
Impacts on market
analysis uncertain
Impacts on market
analysis uncertain
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To explore the effects of key sources of uncertainty, we performed a sensitivity
analysis in which we examine the results of using alternative values for the price elasticity of
supply and demand and alternative methods to shock to the market equilibrium (fixed and
variable costs). We also examined the results of using alternative values for the equipment
supply elasticities (locomotives and marine vessels) estimated using an alternative
methodology, and we examined the impacts of using a weighted average compliance cost for
auxiliary marine engines above 800 hp. These analysis and their results are described in more
detail in Appendix 7H. A summary of the results are presented in Table 7-32.
Table 7-32. Results of Sensitivity Analysis
Parameter
Year
Change in
Value
Impact
Price
Elasticity of
Supply
2020
More elastic
Negligible impact on expected price increase and quantity decrease
Higher value associated with increase in social cost burden for users
of rail and marine transportation services
2020
Less elastic
Negligible impact on expected price increase and quantity decrease
Lower value associated with increase in social cost burden for
suppliers of marine vessels and providers of rail and marine
transportation services
Price
Elasticity of
Demand
2020
More elastic
Negligible impact on expected price increase and quantity decrease
Higher value associated with increase in social cost burden for
suppliers of marine vessels and providers of rail and marine
transportation services
2020
Less elastic
Negligible impact on expected price increase and quantity decrease
Lower value associated with increase in social cost burden for users
of rail and marine transportation services
Market
Supply Shift
2014
Include
fixed and
variable
costs;
analysis
performed
for
locomotive
and
propulsion
marine >800
hponly
Price increase larger than primary case, but decrease in quantity
produced remains small, less than 3.5 percent (less than 20 units) for
commercial marine engines and vessels. Negligible change in
locomotive markets. Distribution of social costs shifts from
manufacturers to user groups.
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Alternative
Method of
Estimating
Price
Elasticity of
Supply -
Equipment
Markets
Alternative
Compliance
Cost for
Auxiliary
Marine
Engines
Above 800
hp
2020
2016,
2030
Supply
elasticites
for
locomotives
and marine
vessels more
elastic
Separate
compliance
costs for
auxiliary
engines 800-
2,000 hp and
above 2,000
hp
Differences in market impacts (price and quantity changes) and
distribution of costs among stakeholders are negligible. The share of
compliance costs borne by vessel manufacturers is slightly less, and
the share of engine manufactures and rail transportation service
providers and users increases slightly. Similarly, the share of
locomotive producers is slightly less than the primary case, and the
share of rail transportation service producers and consumers is
slightly more.
Market impacts are different, with smaller price increase for
auxiliary engines 800 to 2,000 hp and larger price increase for
auxiliary engines above 2,000 hp. Slight reduction in the decrease in
quantity produced for small engines; no change for larger engines.
Slight shift in social welfare cost burden from marine engine and
vessel producers to marine transportation service producers and
consumers.
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Appendix 7A: Impacts on Marine Engine Markets
This appendix provides the time series of impacts from 2007 through 2040 for selected
auxiliary and propulsion marine engines markets. R Table 7A-1 through Table 7A-6 provide
the time series of impacts and include the following:
average engineering costs (variable) per engine
absolute change in the market price ($)
relative change in market price (%)
relative change in market quantity (%)
total engineering costs (variable and fixed) associated with each engine market
changes in engine manufacturer surplus
All prices, costs, and surplus changes are presented in 2005 dollars, and real engine or
equipment prices are assumed to be constant during the period of analysis. Net present values
for 2006 were calculated using social discount rates of 3% and 7% over the 2007 and 2040
time period.
Results are presented for only those markets that are expected to incur direct variable
costs under Tier 3 or Tier 4 standards. This means that results are not presented for marine
engine markets less than 800 hp or for recreational propulsion engine markets. For these
engine markets, the results are expected to be negligible and any change in price or quantity
would be incidental to the changes in the larger engine markets. It should also be noted that
all engine markets would incur fixed costs. However, as explained in 7.2.3.4, fixed costs are
not included in the EIM.
The NPV calculations presented in this Appendix are based on the period 2006-2040,
reflecting the period when the analysis was completed. This has the consequence of
discounting the current year costs, 2007, and all subsequent years are discounted by an
additional year. The result is a smaller stream of social costs than by calculating the NPV
over 2007-2040 (3% smaller for 3% NPV and 7% smaller for 7% NPV).
R The engineering costs we used in the EIA are an earlier version of the estimated compliance costs developed
forthisrule; see Section 7.3.2 for an explanation of the difference. This difference is not expected to have an
impact on the results of the market analysis or on the expected distribution of social costs among stakeholders.
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Table 7A-1.
Year
2007
2008
2009
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%
Impact on Auxiliary
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$37,097
$37,096
$28,360
$28,359
$28,363
$28,360
$28,359
$28,363
$28,360
$28,361
$28,361
$28,359
$28,361
$28,360
$28,359
$28,360
$28,359
$28,359
$28,360
$28,359
$28,361
$28,359
$28,360
$28,357
$28,362
Engine Market:
Absolute Change
in Price
($)
$0
-$4
-$5
-$6
-$7
-$10
-$10
-$10
-$8
$34,894
$34,891
$26,653
$26,650
$26,652
$26,646
$26,643
$26,644
$26,639
$26,638
$26,635
$26,631
$26,632
$26,628
$26,626
$26,626
$26,624
$26,622
$26,622
$26,620
$26,622
$26,619
$26,619
$26,616
$26,620
800-2000 hp (Average
Change
Price per
Change
in Price in Quantity
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
20.9%
20.9%
16.0%
16.0%
16.0%
16.0%
16.0%
16.0%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
15.9%
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-5.0%
-5.0%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
-3.9%
^.0%
-4.0%
-4.0%
-4.0%
-4.0%
-4.0%
-4.0%
-4.0%
Engine = $167,000)a'b
Total
Engineering Costs
(million S)
$1.7
$1.7
$1.7
$1.7
$13.5
$10.7
$10.7
$10.7
$14.9
$8.3
$8.4
$6.5
$6.5
$6.6
$6.7
$6.7
$6.8
$6.8
$6.9
$7.0
$7.0
$7.1
$7.2
$7.2
$7.3
$7.3
$7.4
$7.5
$7.5
$7.6
$7.7
$7.8
$7.8
$7.9
$147.5
$83.4
Change in Engine
Manufacturers' Surplus
(million S)
-$1.7
-$1.7
-$1.7
-$1.7
-$13.5
-$10.7
-$10.7
-$10.7
-$14.9
-$0.5
-$0.5
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$59.5
-$43.3
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-77
-------
Regulatory Impact Analysis
Table 7A-2.
Year
2007
2008
2009
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%
Impact on Auxiliary
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$37,097
$37,096
$28,360
$28,359
$28,363
$28,360
$28,359
$28,363
$28,360
$28,361
$28,361
$28,359
$28,361
$28,360
$28,359
$28,360
$28,359
$28,359
$28,360
$28,359
$28,361
$28,359
$28,360
$28,357
$28,362
Engine Market:
Absolute Change
in Price
(S)
$0
-$45
-$60
-$74
-$88
-$122
-$130
-$128
-$99
$36,919
$36,895
$28,142
$28,111
$28,083
$28,049
$28,017
$27,991
$27,959
$27,932
$27,904
$27,876
$27,853
$27,829
$27,809
$27,793
$27,778
$27,764
$27,753
$27,740
$27,732
$27,719
$27,710
$27,698
$27,697
>2000 hp (Average
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
9.6%
9.6%
7.3%
7.3%
7.3%
7.3%
7.3%
7.3%
7.3%
7.3%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
7.2%
Price per Engine
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
= $385,000)a'b
Total
Engineering Costs
(million S)
$0.9
$0.9
$0.9
$0.9
$6.7
$5.3
$5.3
$5.3
$7.4
$4.2
$4.2
$3.2
$3.3
$3.3
$3.3
$3.4
$3.4
$3.4
$3.5
$3.5
$3.5
$3.5
$3.6
$3.6
$3.6
$3.7
$3.7
$3.7
$3.8
$3.8
$3.8
$3.9
$3.9
$3.9
$73.8
$41.7
Change in Engine
Manufacturers' Surplus
(million S)
-$0.9
-$0.9
-$0.9
-$0.9
-$6.8
-$5.4
-$5.4
-$5.4
-$7.5
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$27.7
-$20.7
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-78
-------
Economic Impact Analysis
Table 7A-3. Impact on Cl Commercial Propulsion
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$15,196
$15,196
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
$11,618
Absolute Change
in Price
($)
$0
-$2
-$3
-$4
-$5
-$7
-$7
-$7
-$5
$13,995
$13,993
$10,680
$10,678
$10,677
$10,675
$10,673
$10,672
$10,670
$10,669
$10,667
$10,666
$10,664
$10,663
$10,662
$10,661
$10,660
$10,660
$10,659
$10,658
$10,658
$10,657
$10,657
$10,656
$10,656
Engine Market
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
9.0%
9.0%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
6.9%
: 800-2000 hp (Average Price per Engine = $155,000)a'b
Change
in Quantity
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-2.9%
-2.9%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.3%
-2.4%
-2.4%
-2.4%
-2.4%
-2.4%
-2.4%
-2.4%
Total
Engineering Costs
(million S)
$1.3
$1.3
$1.3
$1.3
$15.1
$13.4
$13.4
$13.4
$18.1
$8.1
$8.2
$6.3
$6.4
$6.4
$6.5
$6.6
$6.6
$6.7
$6.7
$6.8
$6.9
$6.9
$7.0
$7.0
$7.1
$7.2
$7.2
$7.3
$7.4
$7.4
$7.5
$7.6
$7.6
$7.7
$154.1
$88.6
Change in Engine
Manufacturers' Surplus
(million S)
-$1.3
-$1.3
-$1.3
-$1.3
-$15.1
-$13.4
-$13.4
-$13.4
-$18.1
-$0.6
-$0.6
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$0.5
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$70.1
-$50.3
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-79
-------
Regulatory Impact Analysis
Table 7A-4. Impact on Cl Commercial Propulsion
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$26,401
$26,401
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
$20,183
Absolute Change
in Price
($)
$0
-$4
-$6
-$7
-$8
-$11
-$12
-$12
-$9
$22,137
$22,134
$16,886
$16,884
$16,880
$16,878
$16,875
$16,872
$16,869
$16,867
$16,864
$16,862
$16,859
$16,857
$16,855
$16,854
$16,853
$16,851
$16,850
$16,849
$16,848
$16,847
$16,846
$16,845
$16,845
Engine Market
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
7.4%
7.4%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
5.6%
: >2000 hp (Average Price per Engine = $300,000)a'b
Change
in Quantity
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-5.4%
-5.4%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
-4.2%
Total
Engineering Costs
(million S)
$0.6
$0.6
$0.6
$0.6
$6.3
$5.6
$5.6
$5.6
$7.5
$5.9
$5.9
$4.6
$4.6
$4.6
$4.7
$4.7
$4.8
$4.8
$4.9
$4.9
$4.9
$5.0
$5.0
$5.1
$5.1
$5.2
$5.2
$5.3
$5.3
$5.4
$5.4
$5.5
$5.5
$5.6
$92.0
$49.5
Change in Engine
Manufacturers' Surplus
(million S)
-$0.6
-$0.6
-$0.6
-$0.6
-$6.3
-$5.6
-$5.6
-$5.6
-$7.5
-$0.9
-$0.9
-$0.7
-$0.7
-$0.7
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.8
-$0.9
-$0.9
-$0.9
-$0.9
-$0.9
-$0.9
-$0.9
-$36.6
-$24.3
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-80
-------
Economic Impact Analysis
Table 7A-5. Impact on C2 Commercial Propulsion
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$39,428
$39,428
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
$30,142
Absolute Change
in Price
($)
$0
-$27
-$36
-$44
-$53
-$73
-$78
-$76
-$59
$39,322
$39,308
$30,012
$29,994
$29,975
$29,956
$29,938
$29,920
$29,902
$29,886
$29,869
$29,854
$29,838
$29,825
$29,813
$29,804
$29,795
$29,787
$29,779
$29,772
$29,766
$29,759
$29,753
$29,748
$29,745
Engine Market
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
17.1%
17.1%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
13.0%
12.9%
12.9%
12.9%
12.9%
12.9%
12.9%
12.9%
: 800-2000 hp (Average Price per Engine = $230,000)a'b
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.1
$0.1
$0.1
$0.1
$0.6
$0.5
$0.5
$0.5
$0.7
$0.3
$0.3
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.3
$0.3
$5.6
$3.3
Change in Engine
Manufacturers' Surplus
(million S)
-$0.1
-$0.1
-$0.1
-$0.1
-$0.6
-$0.5
-$0.5
-$0.5
-$0.7
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$2.6
-$1.9
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-81
-------
Regulatory Impact Analysis
Table 7A-6. Impact on C2 Commercial Propulsion
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$73,360
$73,360
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
$56,081
Absolute Change
in Price
($)
$0
-$53
-$70
-$87
-$103
-$142
-$152
-$150
-$115
$73,152
$73,125
$55,827
$55,791
$55,753
$55,717
$55,681
$55,646
$55,612
$55,579
$55,547
$55,516
$55,487
$55,460
$55,437
$55,418
$55,401
$55,385
$55,371
$55,357
$55,345
$55,332
$55,320
$55,310
$55,303
Engine Market
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
16.3%
16.2%
12.4%
12.4%
12.4%
12.4%
12.4%
12.4%
12.4%
12.4%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
12.3%
: >2000 hp (Average Price per Engine = $450,000)a'b
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$1.9
$1.9
$1.9
$1.9
$13.4
$10.2
$10.2
$10.2
$14.4
$10.4
$10.5
$8.1
$8.2
$8.2
$8.3
$8.4
$8.5
$8.5
$8.6
$8.7
$8.8
$8.8
$8.9
$9.0
$9.1
$9.2
$9.3
$9.3
$9.4
$9.5
$9.6
$9.7
$9.8
$9.9
$169.9
$93.4
Change in Engine
Manufacturers' Surplus
(million S)
-$1.9
-$1.9
-$1.9
-$1.9
-$13.4
-$10.2
-$10.2
-$10.2
-$14.4
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$54.2
-$40.7
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-82
-------
Economic Impact Analysis
Appendix 7B: Impacts on the Equipment Markets
This appendix provides the time series of impacts from 2007 through 2040 for selected
equipment markets (vessels and locomotives).8 Results are presented for 21 separate
equipment markets: 2 locomotive markets (line-haul and switchers) and 19 vessel markets.
Table 7B-1 through Table 7B-21 provide the time series of impacts and include the following:
average engineering costs (variable) per equipment
absolute change in the market price ($)
relative change in market price (%)
relative change in market quantity (%)
total engineering costs (variable and fixed) associated with each engine market
changes in equipment manufacturer surplus (selected commercial vessel and locomotive
markets)
changes in total surplus (fishing markets only)
All prices, costs, and surplus changes are presented in 2005 dollars, and real
equipment prices are assumed to be constant during the period of analysis. Net present values
for 2006 were calculated using social discount rates of 3% and 7% over the 2007 and 2040
time period.
Results are presented for only those markets that are expected to incur direct variable
costs under Tier 3 or Tier 4 standards. This means that results are not presented for marine
vessel markets for vessels that have propulsion engines less than 800 hp or for recreational
vessel markets. For these vessel markets, the results are expected to be negligible and any
change in price or quantity would be incidental to the changes in the larger vessel markets. It
should also be noted that fixed costs are limited to only the Tier 4 standards. There are no
fixed costs associated with the Tier 3 standards because Tier 3 engines are expected to have
the same engine footprint as Tier 2 engines. For Tier 4 vessels, as explained in 7.2.3.4, fixed
costs are not included in the EIM.
The NPV calculations presented in this Appendix are based on the period 2006-2040,
reflecting the period when the analysis was completed. This has the consequence of
discounting the current year costs, 2007, and all subsequent years are discounted by an
additional year. The result is a smaller stream of social costs than by calculating the NPV
over 2007-2040 (3% smaller for 3% NPV and 7% smaller for 7% NPV).
s The engineering costs we used in the EIA are an earlier version of the estimated compliance costs developed
forthisrule; see Section 7.3.2 for an explanation of the difference. This difference is not expected to have an
impact on the results of the market analysis or on the expected distribution of social costs among stakeholders.
7144
7-83
-------
Table 7B-1. Impact on Locomotive Market: Line-Haul (Average Price per Locomotive = $2,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$84,274
$84,274
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
$65,343
Absolute Change
in Price
($)
$0
-$158
-$197
-$351
-$658
-$535
-$483
-$355
$83,494
$83,227
$64,374
$64,273
$64,217
$64,261
$64,163
$63,950
$63,600
$63,574
$63,454
$63,439
$63,345
$63,181
$63,093
$63,019
$62,939
$62,909
$62,547
$62,431
$62,328
$62,313
$62,252
$62,196
$62,144
$62,095
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
4.2%
4.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.2%
3.1%
3.1%
3.1%
3.1%
3.1%
3.1%
3.1%
3.1%
3.1%
3.1%
Change
in Quantity
(%)
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
Total
Engineering Costs
(million S)
$6.0
$6.0
$6.0
$33.4
$35.0
$27.4
$27.4
$30.7
$68.8
$72.0
$57.3
$58.4
$59.9
$61.9
$64.0
$65.8
$67.6
$68.5
$70.4
$71.6
$73.1
$74.2
$75.1
$75.7
$76.7
$77.8
$79.0
$79.9
$80.4
$78.2
$76.6
$74.8
$72.7
$70.4
$1,102.4
$553.6
Change in Equipment
Manufacturers' Surplus
(million S)
-$6.0
-$6.1
-$6.1
-$33.7
-$35.5
-$27.8
-$27.8
-$30.9
-$0.6
-$0.9
-$0.8
-$1.0
-$1.0
-$1.0
-$1.2
-$1.4
-$1.8
-$1.9
-$2.0
-$2.1
-$2.2
-$2.5
-$2.6
-$2.7
-$2.8
-$2.9
-$3.4
-$3.6
-$3.7
-$3.6
-$3.6
-$3.6
-$3.6
-$3.5
-$172.2
-$124.5
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-84
-------
Table 7B-2. Impact on Locomotive Market: Switcher/Passenger (Average Price per Locomotive = $1,300,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$14,175
$14,175
$23,682
$23,682
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
$21,139
Absolute Change
in Price
($)
$0
-$103
-$128
-$228
-$428
-$348
-$314
-$231
$13,668
$13,494
$23,052
$22,986
$20,407
$20,436
$20,372
$20,233
$20,006
$19,989
$19,911
$19,901
$19,840
$19,734
$19,676
$19,628
$19,576
$19,557
$19,321
$19,246
$19,179
$19,169
$19,130
$19,093
$19,059
$19,028
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
1.1%
1.0%
1.8%
1.8%
1.6%
1.6%
1.6%
1.6%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
Change
in Quantity
(%)
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
Total
Engineering Costs
(million S)
$2.6
$2.6
$2.6
$4.9
$6.9
$7.2
$7.2
$9.7
$6.2
$8.7
$2.2
$2.2
$2.0
$2.0
$2.0
$2.0
$3.4
$3.9
$4.2
$4.5
$4.8
$5.0
$5.2
$5.6
$5.9
$6.2
$6.3
$6.4
$6.4
$6.2
$6.1
$5.9
$5.7
$5.6
$99.0
$56.7
Change in Equipment
Manufacturers' Surplus
(million S)
-$2.6
-$2.6
-$2.6
-$5.0
-$7.0
-$7.2
-$7.2
-$9.8
-$4.9
-$7.4
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.2
-$0.2
-$0.2
-$0.3
-$0.3
-$0.3
-$0.4
-$0.4
-$0.4
-$0.5
-$0.5
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$48.9
-$35.9
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-85
-------
Table 7B-3. Impact on Cl Fishing Vessel Market: 800-2000 hp (Average Price per Vessel = $1,085,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,585
$6,587
$5,504
$5,501
$5,503
$5,504
$5,504
$5,504
$5,504
$5,503
$5,502
$5,504
$5,502
$5,504
$5,505
$5,501
$5,501
$5,505
$5,504
$5,503
$5,505
$5,503
$5,504
$5,504
$5,504
Absolute Change
in Price (S)
$0
-$3
-$3
-$4
-$5
-$7
(TO
3>o
-$7
-$6
$18,493
$18,493
$14,369
$14,366
$14,365
$14,363
$14,362
$14,360
$14,358
$14,356
$14,354
$14,354
$14,351
$14,351
$14,350
$14,347
$14,347
$14,348
$14,346
$14,345
$14,346
$14,344
$14,344
$14,344
$14,343
Change in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
1.7%
1.7%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
Change in
Quantity (%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-3.4%
-3.4%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
-2.6%
Total
Engineering
Costs (million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$5.7
$4.2
$3.0
$2.2
$2.2
$2.2
$2.2
$2.2
$2.3
$2.3
$2.3
$2.3
$2.3
$2.3
$1.4
$1.4
$1.4
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.5
$1.6
$1.6
$31.5
$16.2
Change in Equipment
Manufacturers'
Surplus (million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
-$5.7
-$6.3
-$5.2
-$3.8
-$3.8
-$3.8
-$3.9
-$3.9
-$3.9
-$3.9
-$4.0
-$4.0
-$4.0
-$4.1
-$3.2
-$3.2
-$3.2
-$3.3
-$3.3
-$3.3
-$3.3
-$3.4
-$3.4
-$3.4
-$3.5
-$3.5
-$54.5
-$26.7
Change in Total
Surplus
(million S)
$0.0
Loss less than $0.
Loss less than $0.
Loss less than $0.
Loss less than $0.
Loss less than $0.
Loss less than $0.
Loss less than $0.
-$5.7
-$6.4
-$5.2
-$3.8
-$3.8
-$3.8
-$3.9
-$3.9
-$3.9
-$3.9
-$4.0
-$4.0
-$4.0
-$4.0
-$3.2
-$3.2
-$3.2
-$3.3
-$3.3
-$3.3
-$3.3
-$3.4
-$3.4
-$3.4
-$3.5
-$3.5
-$54.5
-$26.7
1
1
1
1
1
1
1
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-86
-------
Table 7B-4. Impact on Cl Fishing Vessel Market: >2000 hp (Average Price per Vessel = $2,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,359
$12,362
$10,383
$10,382
$10,389
$10,386
$10,382
$10,387
$10,382
$10,385
$10,387
$10,389
$10,389
$10,389
$10,388
$10,386
$10,384
$10,389
$10,385
$10,389
$10,383
$10,385
$10,387
$10,387
$10,387
Absolute Change
in Price (S)
$0
-$8
-$11
-$13
-$16
-$22
-$23
-$23
-$18
$65,202
$65,198
$50,284
$50,278
$50,279
$50,270
$50,261
$50,262
$50,251
$50,248
$50,244
$50,239
$50,237
$50,231
$50,227
$50,224
$50,219
$50,219
$50,216
$50,215
$50,212
$50,209
$50,209
$50,205
$50,208
Change in
Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
3.1%
3.1%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
2.4%
Change in
Quantity (%)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-6.2%
-6.2%
^.8%
^.8%
^.8%
^.8%
^t.8%
^.8%
^.8%
^.8%
^t.8%
^t.8%
^.8%
^.8%
^.8%
^t.8%
^.8%
^.8%
^.8%
^.8%
^t.8%
^.8%
^.8%
^.8%
^t.8%
Total
Engineering
Costs (million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$2.4
$2.3
$1.8
$1.4
$1.4
$1.4
$1.4
$1.4
$1.4
$1.5
$1.5
$1.5
$1.5
$1.5
$1.1
$1.1
$1.1
$1.2
$1.2
$1.2
$1.2
$1.2
$1.2
$1.2
$1.2
$1.2
$20.0
$9.9
Change in Equipment
Manufacturers'
Surplus (million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
-$2.4
-$6.4
-$6.0
-$4.6
-$4.6
-$4.6
-$4.7
-$4.7
-$4.8
-$4.8
-$4.8
-$4.9
-$4.9
-$4.9
-$4.6
-$4.6
-$4.7
-$4.7
-$4.8
-$4.8
-$4.9
-$4.9
-$4.9
-$5.0
-$5.0
-$5.1
-$65.7
-$30.7
Change in Total
Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$2.4
-$6.4
-$6.0
-$4.6
-$4.6
-$4.6
-$4.7
-$4.7
-$4.8
-$4.8
-$4.8
-$4.9
-$4.9
-$4.9
-$4.6
-$4.7
-$4.7
-$4.7
-$4.8
-$4.8
-$4.9
-$4.9
-$5.0
-$5.0
-$5.0
-$5.1
-$65.7
-$30.7
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-87
-------
Table 7B-5. Impact on C2 Fishing Vessel Market: >2000 hp (Average Price per Vessel = $2,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,398
$12,379
$10,360
$10,358
$10,355
$10,351
$10,346
$10,428
$10,421
$10,413
$10,405
$10,396
$10,386
$10,376
$10,365
$10,354
$10,422
$10,408
$10,394
$10,379
$10,364
$10,348
$10,408
$10,390
$10,372
Absolute Change
in Price (S)
$0
-$613
-$807
-$1,002
-$1,196
-$1,643
-$1,759
-$1,731
-$1,335
$237,339
$237,000
$181,220
$180,801
$180,373
$179,939
$179,518
$179,203
$178,796
$178,410
$178,031
$177,662
$177,316
$176,996
$176,723
$176,490
$176,359
$176,162
$175,980
$175,807
$175,650
$175,486
$175,410
$175,271
$175,184
Change in
Price
(%)
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
11.3%
11.3%
8.6%
8.6%
8.6%
8.6%
8.5%
8.5%
8.5%
8.5%
8.5%
8.5%
8.4%
8.4%
8.4%
8.4%
8.4%
8.4%
8.4%
8.4%
8.4%
8.4%
8.4%
8.3%
8.3%
Change in
Quantity (%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering
Costs (million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.5
$0.4
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.3
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$3.3
$1.7
Change in Equipment
Manufacturers'
Surplus (million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
-$0.5
-$0.3
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$2.3
-$1.3
Change in Total
Surplus
(million S)
$0.0
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.6
-$0.3
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$2.3
-$1.3
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-88
-------
Table 7B-6. Impact on Cl Tow/Tug/Push Vessel Market: 800-2000 hp (Average Price per Vessel = $1,550,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,604
$6,585
$5,498
$5,488
$5,516
$5,506
$5,495
$5,521
$5,510
$5,498
$5,485
$5,509
$5,497
$5,519
$5,505
$5,492
$5,512
$5,498
$5,517
$5,502
$5,487
$5,504
$5,488
$5,505
$5,488
Absolute Change
in Price
($)
$0
-$306
-$404
-$501
-$598
-$821
-$879
-$865
-$667
$33,409
$33,232
$25,412
$25,195
$25,007
$24,784
$24,566
$24,390
$24,182
$23,980
$23,783
$23,628
$23,445
$23,314
$23,170
$23,045
$22,967
$22,861
$22,796
$22,702
$22,613
$22,559
$22,474
$22,433
$22,377
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
2.2%
2.1%
1.6%
1.6%
1.6%
1.6%
1.6%
1.6%
1.6%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.4%
1.4%
1.4%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.6
$0.5
$0.3
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.3
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$3.4
$1.8
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.6
-$0.3
-$0.2
-$0.1
-$0.1
-$0.1
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.2
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$2.6
-$1.4
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-89
-------
Table 7B-7. Impact on Cl Tow/Tug/Push Vessel Market: >2000 hp (Average Price per Vessel = $3,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,321
$12,403
$10,387
$10,388
$10,389
$10,389
$10,389
$10,387
$10,385
$10,382
$10,378
$10,373
$10,368
$10,362
$10,355
$10,347
$10,423
$10,413
$10,403
$10,392
$10,380
$10,368
$10,355
$10,421
$10,406
Absolute Change
in Price
($)
$0
-$592
-$780
-$967
-$1,155
-$1,587
-$1,698
-$1,672
-$1,289
$54,303
$54,079
$41,362
$40,963
$40,544
$40,135
$39,735
$39,342
$38,961
$38,589
$38,228
$37,879
$37,544
$37,241
$36,982
$36,760
$36,646
$36,460
$36,286
$36,123
$35,969
$35,818
$35,672
$35,627
$35,536
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
1.8%
1.8%
1.4%
1.4%
1.4%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
1.2%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.3
$0.3
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$2.1
$1.1
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.3
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$1.5
-$0.8
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-90
-------
Table 7B-8. Impact on C2 Tow/Tug/Push Vessel Market: 800-2000 hp (Average Price per Vessel = $1,550,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,469
$6,411
$5,776
$5,725
$5,674
$5,623
$5,573
$5,523
$5,474
$5,425
$5,377
$5,329
$5,281
$5,758
$5,706
$5,655
$5,605
$5,555
$5,505
$5,456
$5,408
$5,359
$5,312
$5,264
$5,691
Absolute Change
in Price
($)
$0
-$355
-$468
-$581
-$694
-$953
-$1,020
-$1,005
-$775
$83,929
$83,688
$64,356
$64,063
$63,761
$63,464
$63,173
$62,889
$62,612
$62,341
$62,079
$61,824
$61,578
$61,876
$61,673
$61,493
$61,329
$61,173
$61,025
$60,885
$60,751
$60,619
$60,491
$60,377
$60,759
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
5.4%
5.4%
4.2%
4.1%
4.1%
4.1%
4.1%
4.1%
4.0%
4.0%
4.0%
4.0%
4.0%
4.0%
4.0%
4.0%
4.0%
3.9%
3.9%
3.9%
3.9%
3.9%
3.9%
3.9%
3.9%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.1
$0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
$0.4
$0.2
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.3
-$0.2
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-91
-------
Table 7B-9. Impact on C2 Tow/Tug/Push Vessel Market: >2000 hp (Average Price per Vessel = $3,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,367
$12,349
$10,391
$10,388
$10,385
$10,381
$10,376
$10,399
$10,392
$10,385
$10,377
$10,396
$10,386
$10,376
$10,392
$10,381
$10,395
$10,382
$10,394
$10,379
$10,390
$10,374
$10,383
$10,390
$10,397
Absolute Change
in Price
($)
$0
-$788
-$1,038
-$1,288
-$1,538
-$2,113
-$2,261
-$2,226
-$1,717
$236,621
$236,192
$180,411
$179,874
$179,322
$178,766
$178,226
$177,737
$177,219
$176,723
$176,240
$175,797
$175,354
$174,945
$174,625
$174,328
$174,087
$173,839
$173,635
$173,417
$173,243
$173,038
$172,872
$172,726
$172,641
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
7.9%
7.9%
6.0%
6.0%
6.0%
6.0%
5.9%
5.9%
5.9%
5.9%
5.9%
5.9%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$1.6
$1.3
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.8
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$9.9
$5.1
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
-$0.1
-$0.1
-$1.6
-$0.9
-$0.5
-$0.5
-$0.5
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.6
-$0.7
-$0.7
-$0.2
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$7.9
-$4.1
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-92
-------
Table 7B-10. Impact on Cl Ferries Vessel Market: 800-2000 hp (Average Price per Vessel = $1,550,000)'
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,644
$6,585
$5,438
$5,605
$5,555
$5,506
$5,457
$5,408
$5,566
$5,516
$5,467
$5,418
$5,569
$5,519
$5,470
$5,421
$5,565
$5,515
$5,466
$5,417
$5,554
$5,504
$5,455
$5,587
$5,537
Absolute Change
in Price
($)
$0
-$306
-$404
-$501
-$598
-$821
-$879
-$865
-$667
$33,450
$33,232
$25,353
$25,313
$25,046
$24,784
$24,528
$24,277
$24,239
$23,998
$23,764
$23,537
$23,517
$23,314
$23,134
$22,975
$23,020
$22,878
$22,744
$22,617
$22,681
$22,559
$22,441
$22,515
$22,426
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
2.2%
2.1%
1.6%
1.6%
1.6%
1.6%
1.6%
1.6%
1.6%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.5%
1.4%
1.5%
1.4%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
$0.6
$0.3
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Lossless than $0.1
Lossless than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.5
-$0.2
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-93
-------
Table 7B-11. Impact on Cl Ferries Vessel Market: >2000 hp (Average Price per Vessel = $3,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,224
$12,115
$10,291
$10,199
$10,108
$10,018
$10,756
$10,660
$10,565
$10,471
$10,378
$10,285
$10,193
$10,102
$10,012
$10,686
$10,591
$10,497
$10,403
$10,310
$10,218
$10,127
$10,037
$10,658
$10,563
Absolute Change
in Price
($)
$0
-$598
-$789
-$979
-$1,169
-$1,605
-$1,718
-$1,691
-$1,304
$119,473
$119,052
$91,121
$90,623
$90,114
$89,606
$89,937
$89,452
$88,968
$88,503
$88,048
$87,604
$87,183
$86,789
$86,444
$86,901
$86,612
$86,339
$86,081
$85,834
$85,602
$85,367
$85,144
$85,648
$85,483
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
4.0%
4.0%
3.0%
3.0%
3.0%
3.0%
3.0%
3.0%
3.0%
3.0%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.8%
2.8%
2.9%
2.8%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
$0.2
$0.1
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
-$0.2
-$0.1
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-94
-------
Table 7B-12. Impact on C2 Ferries Vessel Market: >2,000 hp (Average Price per Vessel = $3,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,491
$12,379
$10,360
$10,268
$10,444
$10,351
$10,259
$10,428
$10,335
$10,499
$10,405
$10,312
$10,470
$10,376
$10,284
$10,435
$10,342
$10,488
$10,394
$10,301
$10,442
$10,348
$10,484
$10,390
$10,298
Absolute Change
in Price
($)
$0
-$788
-$1,038
-$1,288
-$1,538
-$2,113
-$2,261
-$2,226
-$1,717
$236,744
$236,223
$180,381
$179,754
$179,381
$178,737
$178,109
$177,766
$177,161
$176,837
$176,268
$175,713
$175,437
$174,945
$174,516
$174,382
$174,034
$173,945
$173,635
$173,339
$173,295
$173,013
$172,974
$172,726
$172,542
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
7.9%
7.9%
6.0%
6.0%
6.0%
6.0%
5.9%
5.9%
5.9%
5.9%
5.9%
5.9%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
5.8%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
$1.1
$0.6
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.9
-$0.5
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-95
-------
Table 7B-13. Impact on Cl Supply/Crew Vessel Market: 800-2,000 hp (Average Price per Vessel = $3,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,644
$6,585
$5,438
$5,605
$5,555
$5,506
$5,457
$5,408
$5,566
$5,516
$5,467
$5,418
$5,569
$5,519
$5,470
$5,421
$5,565
$5,515
$5,466
$5,417
$5,554
$5,504
$5,455
$5,587
$5,537
Absolute Change
in Price
($)
$0
-$608
-$801
-$994
-$1,186
-$1,630
-$1,744
-$1,717
-$1,324
$32,266
$31,892
$23,908
$23,663
$23,183
$22,713
$22,252
$21,803
$21,571
$21,143
$20,728
$20,325
$20,137
$19,783
$19,475
$19,206
$19,154
$18,923
$18,705
$18,501
$18,492
$18,300
$18,114
$18,132
$18,004
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
1.0%
1.0%
0.8%
0.8%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
$0.6
$0.3
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.7
-$0.3
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-96
-------
Table 7B-14. Impact on Cl Supply/Crew Vessel Market: >2,000 hp (Average Price per Vessel = $6,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,224
$12,547
$10,291
$10,199
$10,530
$10,436
$10,343
$10,250
$10,565
$10,471
$10,378
$10,285
$10,193
$10,491
$10,397
$10,305
$10,213
$10,497
$10,403
$10,310
$10,218
$10,489
$10,395
$10,302
$10,211
Absolute Change
in Price
($)
$0
-$1,182
-$1,557
-$1,932
-$2,308
-$3,169
-$3,392
-$3,340
-$2,575
$117,183
$116,893
$88,324
$87,431
$86,930
$86,014
$85,120
$84,253
$83,806
$82,977
$82,170
$81,387
$80,641
$80,344
$79,746
$79,225
$78,752
$78,683
$78,264
$77,867
$77,495
$77,485
$77,127
$76,808
$76,572
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
2.0%
1.9%
1.5%
1.5%
1.4%
1.4%
1.4%
1.4%
1.4%
1.4%
1.4%
1.4%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
1.3%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
$0.5
$0.2
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.5
-$0.3
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-97
-------
Table 7B-15. Impact on C2 Supply/Crew Vessel Market: 800-2,000 hp (Average Price per Vessel = $3,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,469
$6,411
$5,776
$5,725
$5,674
$5,623
$5,573
$5,523
$5,474
$5,425
$5,377
$5,329
$5,281
$5,758
$5,706
$5,655
$5,605
$5,555
$5,505
$5,456
$5,408
$5,359
$5,312
$5,264
$5,691
Absolute Change
in Price
($)
$0
-$657
-$865
-$1,074
-$1,283
-$1,762
-$1,886
-$1,856
-$1,432
$82,746
$82,348
$62,911
$62,414
$61,898
$61,393
$60,898
$60,415
$59,944
$59,487
$59,042
$58,611
$58,198
$58,345
$58,014
$57,725
$57,463
$57,217
$56,986
$56,769
$56,562
$56,359
$56,164
$55,993
$56,336
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
2.7%
2.7%
2.0%
2.0%
2.0%
2.0%
2.0%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.8%
1.8%
1.8%
1.8%
1.8%
1.8%
1.8%
1.8%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
$0.4
$0.2
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
-$0.4
-$0.2
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-98
-------
Table 7B-16. Impact on C2 Supply/Crew Vessel Market: >2,000 hp (Average Price per Vessel = $6,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,380
$12,379
$10,360
$10,376
$10,391
$10,404
$10,364
$10,376
$10,387
$10,396
$10,405
$10,363
$10,370
$10,376
$10,382
$10,386
$10,390
$10,392
$10,394
$10,395
$10,395
$10,394
$10,393
$10,390
$10,387
Absolute Change
in Price
($)
$0
-$1,279
-$1,685
-$2,092
-$2,498
-$3,431
-$3,672
-$3,615
-$2,788
$219,369
$218,705
$166,274
$165,421
$164,537
$163,660
$162,753
$161,927
$161,112
$160,327
$159,564
$158,773
$158,072
$157,435
$156,894
$156,435
$156,026
$155,647
$155,296
$154,968
$154,665
$154,361
$154,073
$153,825
$153,666
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
3.7%
3.6%
2.8%
2.8%
2.7%
2.7%
2.7%
2.7%
2.7%
2.7%
2.7%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
2.6%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.9
$0.7
$0.5
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.4
$0.5
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
$5.5
$2.8
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.1
-$0.1
-$0.1
-$0.9
-$0.6
-$0.3
-$0.3
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.4
-$0.5
-$0.5
-$0.5
-$0.5
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.3
-$0.4
-$0.4
-$0.4
-$0.4
-$6.0
-$3.0
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-99
-------
Table 7B-17. Impact on Cl Cargo Vessel Market: 800-2,000 hp (Average Price per Vessel = $3,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,201
$7,024
$5,221
$5,174
$5,128
$5,082
$5,876
$5,824
$5,772
$5,721
$5,670
$5,619
$5,569
$5,519
$5,470
$5,421
$5,373
$5,325
$5,277
$5,230
$5,184
$5,137
$5,819
$5,767
$5,716
Absolute Change
in Price
($)
$0
-$608
-$801
-$994
-$1,186
-$1,630
-$1,744
-$1,717
-$1,324
$31,823
$32,331
$23,690
$23,232
$22,756
$22,289
$22,672
$22,219
$21,777
$21,348
$20,930
$20,526
$20,137
$19,783
$19,475
$19,206
$18,962
$18,733
$18,517
$18,314
$18,122
$17,933
$18,478
$18,312
$18,182
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
1.0%
1.0%
0.8%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.7%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
0.6%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
$0.2
$0.1
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.2
-$0.1
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-100
-------
Table 7B-18. Impact on C2 Cargo Vessel Market: >2,000 hp (Average Price per Vessel = $6,000,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,283
$12,379
$10,429
$10,336
$10,444
$10,351
$10,456
$10,363
$10,464
$10,371
$10,469
$10,375
$10,470
$10,376
$10,467
$10,374
$10,462
$10,368
$10,453
$10,360
$10,442
$10,348
$10,427
$10,334
$10,410
Absolute Change
in Price
($)
$0
-$1,371
-$1,806
-$2,242
-$2,677
-$3,677
-$3,935
-$3,874
-$2,988
$234,245
$233,630
$177,652
$176,629
$175,776
$174,728
$173,903
$172,913
$172,128
$171,184
$170,454
$169,559
$168,895
$168,111
$167,617
$167,027
$166,672
$166,170
$165,877
$165,431
$165,188
$164,769
$164,542
$164,185
$164,094
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
3.9%
3.9%
3.0%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.9%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.7%
2.7%
2.7%
2.7%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.2
$0.2
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$0.1
$1.5
$0.8
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
-$0.3
-$0.2
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$0.1
-$1.6
-$0.8
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-101
-------
Table 7B-19. Impact on Cl Other Commercial Vessel Market: 800-2,000 hp (Average Price per Vessel = $1,085,000)'
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$6,496
$6,731
$5,511
$5,462
$5,413
$5,365
$5,597
$5,547
$5,497
$5,448
$5,400
$5,619
$5,569
$5,519
$5,470
$5,421
$5,629
$5,578
$5,529
$5,479
$5,430
$5,382
$5,576
$5,527
$5,477
Absolute Change
in Price
($)
$0
-$216
-$284
-$353
-$421
-$579
-$620
-$610
-$470
$33,657
$33,780
$25,859
$25,664
$25,462
$25,264
$25,350
$25,158
$24,970
$24,787
$24,608
$24,702
$24,531
$24,373
$24,232
$24,105
$24,243
$24,129
$24,019
$23,915
$23,814
$23,715
$23,861
$23,770
$23,693
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
3.1%
3.1%
2.4%
2.4%
2.3%
2.3%
2.3%
2.3%
2.3%
2.3%
2.3%
2.3%
2.3%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
2.2%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
$0.5
$0.2
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
-$0.3
-$0.2
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-102
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Table 7B-20. Impact on Cl Other Commercial Vessel Market: >2,000 hp (Average Price per Vessel = $2,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,224
$12,115
$10,291
$10,199
$10,108
$10,018
$10,756
$10,660
$10,565
$10,471
$10,378
$10,285
$10,193
$10,102
$10,012
$10,686
$10,591
$10,497
$10,403
$10,310
$10,218
$10,127
$10,037
$10,658
$10,563
Absolute Change
in Price
($)
$0
-$423
-$558
-$692
-$827
-$1,136
-$1,216
-$1,197
-$923
$120,160
$119,830
$91,960
$91,580
$91,196
$90,808
$91,258
$90,889
$90,517
$90,161
$89,811
$89,469
$89,146
$88,840
$88,569
$89,090
$88,857
$88,636
$88,427
$88,224
$88,034
$87,840
$87,657
$88,193
$88,051
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
5.7%
5.7%
4.4%
4.4%
4.3%
4.3%
4.3%
4.3%
4.3%
4.3%
4.3%
4.3%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
4.2%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0. 1
$0.2
$0.1
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
-$0.1
-$0.1
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-103
-------
Table 7B-21. Impact on C2 Other Commercial Vessel Market: >2,000 hp (Average Price per Vessel = $2,100,000)
a,b
Year
2007
2008
2009
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%
Variable
Engineering
Cost/Unit
$0
$0
$0
$0
$0
$0
$0
$0
$0
$12,491
$12,379
$10,633
$10,538
$10,444
$10,351
$10,259
$10,167
$10,076
$10,755
$10,659
$10,564
$10,470
$10,376
$10,284
$10,192
$10,101
$10,726
$10,630
$10,535
$10,442
$10,348
$10,256
$10,165
$10,074
Absolute Change
in Price
($)
$0
-$521
-$686
-$852
-$1,017
-$1,397
-$1,496
-$1,472
-$1,135
$222,458
$222,075
$170,182
$169,733
$169,278
$168,819
$168,373
$167,944
$167,513
$167,869
$167,458
$167,057
$166,677
$166,319
$166,004
$165,724
$165,464
$165,934
$165,695
$165,466
$165,251
$165,032
$164,824
$164,629
$164,480
Change
in Price
(%)
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
10.6%
10.6%
8.1%
8.1%
8.1%
8.0%
8.0%
8.0%
8.0%
8.0%
8.0%
8.0%
7.9%
7.9%
7.9%
7.9%
7.9%
7.9%
7.9%
7.9%
7.9%
7.9%
7.8%
7.8%
7.8%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0. 1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
Less than $0.1
$0.4
$0.2
Change in Equipment
Manufacturers' Surplus
(million S)
$0.0
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Lossless than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0.1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0. 1
Loss less than $0.1
-$0.3
-$0.1
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-104
-------
Appendix 7C: Impacts on Transportation Service Markets
This appendix provides the time series of impacts from 2007 through 2040 for two
transportation service markets (railroad and marine).1 Table 7C-1 through Table 7C-2 provide
the time series of impacts and include the following:
relative change in market price (%)
relative change in market quantity (%)
total engineering costs (variable and fixed) associated with each engine market
changes in service user surplus
changes in service provider surplus
changes in total surplus
All costs and surplus changes are presented in 2005 dollars and real service prices are
assumed to be constant during the period of analysis. Net present values for 2006 are
calculated using a social discount rate of 3% and 7% over the 2007 and 2040 time period.
The NPV calculations presented in this Appendix are based on the period 2006-2040,
reflecting the period when the analysis was completed. This has the consequence of
discounting the current year costs, 2007, and all subsequent years are discounted by an
additional year. The result is a smaller stream of social costs than by calculating the NPV
over 2007-2040 (3% smaller for 3% NPV and 7% smaller for 7% NPV).
T The engineering costs we used in the EIA are an earlier version of the estimated compliance costs developed
forthisrule; see Section 7.3.2 for an explanation of the difference. This difference is not expected to have an
impact on the results of the market analysis or on the expected distribution of social costs among stakeholders.
7-105
-------
Table 7C-1. Impact on Railroad Services Market
Year
2007
2008
2009
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%
Change
in Price
(%)
0.0%
0.0%
0.1%
0.1%
0.2%
0.1%
0.1%
0.1%
0.2%
0.3%
0.3%
0.3%
0.3%
0.3%
0.3%
0.4%
0.5%
0.5%
0.5%
0.5%
0.5%
0.6%
0.6%
0.6%
0.6%
0.7%
0.8%
0.8%
0.8%
0.8%
0.8%
0.8%
0.9%
0.9%
Change
in Quantity
(%)
0.0%
0.0%
0.0%
0.0%
-0.1%
-0.1%
-0.1%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
-0.4%
Total
Engineering Costs
(million S)
$0.0
$25.8
$32.3
$58.2
$110.1
$90.3
$82.3
$61.0
$65.2
$110.0
$111.6
$130.0
$140.5
$132.3
$150.0
$189.6
$254.1
$260.5
$284.0
$288.8
$308.4
$342.6
$362.6
$380.5
$399.4
$408.4
$485.6
$513.5
$539.9
$550.9
$571.1
$590.7
$610.2
$629.2
$4,499.2
$1,941.2
Change in Service
Consumer Surplus
(million S)
$0.0
-$19.5
-$24.5
-$44.1
-$83.5
-$68.4
-$62.4
-$46.3
-$102.5
-$138.9
-$129.6
-$144.4
-$153.3
-$148.6
-$163.5
-$194.8
-$245.9
-$251.7
-$271.2
-$275.9
-$292.0
-$318.8
-$334.8
-$348.9
-$364.2
-$372.0
-$431.1
-$453.0
-$473.2
-$479.9
-$493.9
-$507.3
-$520.3
-$533.0
-$4,168.7
-$1,819.5
Change in Service
Provider Surplus
(million S)
$0.0
-$6.1
-$7.7
-$13.8
-$26.1
-$21.4
-$19.5
-$14.5
-$32.0
-$43.4
-$40.5
-$45.1
-$47.9
-$46.4
-$51.1
-$60.9
-$76.8
-$78.7
-$84.7
-$86.2
-$91.3
-$99.6
-$104.6
-$109.0
-$113.8
-$116.2
-$134.7
-$141.6
-$147.9
-$150.0
-$154.3
-$158.5
-$162.6
-$166.6
-$1,302.7
-$568.6
Change in
Total Surplus
(million S)
$0.0
-$25.7
-$32.2
-$57.9
-$109.6
-$89.8
-$81.8
-$60.7
-$134.6
-$182.3
-$170.1
-$189.5
-$201.2
-$195.0
-$214.6
-$255.7
-$322.7
-$330.4
-$355.9
-$362.1
-$383.3
-$418.4
-$439.4
-$458.0
-$478.0
-$488.2
-$565.9
-$594.5
-$621.1
-$629.8
-$648.2
-$665.8
-$682.9
-$699.6
-$5,471.4
-$2,388.1
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-106
-------
Table 7C-2. Impact on Marine Services Market
Year
2007
2008
2009
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%
Change
in Price
(%)
0.0%
0.1%
0.1%
0.1%
0.2%
0.2%
0.3%
0.3%
0.2%
0.4%
0.4%
0.4%
0.5%
0.6%
0.6%
0.7%
0.7%
0.8%
0.8%
0.9%
1.0%
1.0%
1.0%
1.1%
1.1%
1.1%
1.2%
1.2%
1.2%
1.2%
1.3%
1.3%
1.3%
1.3%
Change
in Quantity
(%)
0.0%
0.0%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.1%
-0.2%
-0.2%
-0.2%
-0.2%
-0.3%
-0.3%
-0.3%
-0.4%
-0.4%
-0.4%
-0.5%
-0.5%
-0.5%
-0.5%
-0.5%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.6%
-0.7%
-0.7%
Total
Engineering Costs
(million S)
$0.0
$18.1
$24.1
$30.2
$36.4
$50.4
$54.4
$54.1
$42.1
$46.5
$57.1
$71.6
$85.7
$100.8
$115.8
$130.8
$145.6
$160.3
$174.9
$189.4
$203.6
$217.5
$230.4
$241.9
$252.2
$261.6
$270.8
$279.5
$288.0
$296.1
$304.3
$312.4
$319.7
$325.7
$2,644.6
$1,151.2
Change in Service
Consumer Surplus
(million S)
$0.0
-$13.7
-$18.2
-$22.8
-$27.5
-$38.1
-$41.2
-$40.9
-$31.8
-$57.9
-$66.1
-$71.9
-$82.8
-$94.4
-$105.9
-$117.3
-$128.7
-$140.0
-$151.1
-$162.2
-$173.1
-$183.7
-$193.7
-$202.5
-$210.4
-$217.7
-$224.8
-$231.6
-$238.1
-$244.5
-$250.8
-$257.1
-$262.8
-$267.5
-$2,254.7
-$986.9
Change in Service
Provider Surplus
(million S)
$0.0
-$4.3
-$5.7
-$7.1
-$8.6
-$11.9
-$12.9
-$12.8
-$9.9
-$18.1
-$20.6
-$22.5
-$25.9
-$29.5
-$33.1
-$36.7
-$40.2
-$43.7
-$47.2
-$50.7
-$54.1
-$57.4
-$60.5
-$63.3
-$65.7
-$68.0
-$70.2
-$72.4
-$74.4
-$76.4
-$78.4
-$80.3
-$82.1
-$83.6
-$704.6
-$308.4
Change in
Total Surplus
(million S)
$0.0
-$18.0
-$23.9
-$30.0
-$36.1
-$50.1
-$54.1
-$53.7
-$41.8
-$75.9
-$86.7
-$94.4
-$108.7
-$123.8
-$138.9
-$154.0
-$168.9
-$183.7
-$198.4
-$212.9
-$227.2
-$241.2
-$254.2
-$265.8
-$276.1
-$285.8
-$295.0
-$303.9
-$312.5
-$320.9
-$329.2
-$337.4
-$344.9
-$351.1
-$2,959.3
-$1,295.3
a Figures are in 2005 dollars.
b Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
7-107
-------
Regulatory Impact Analysis
Appendix 7D: Time Series of Social Costs
This appendix provides a time series of the rule's estimated social costs from 2007
through 2040.u Costs are presented in 2005 dollars. In addition, this appendix includes the
net present values by stakeholder for 2006 using social discount rates of 3% and 7% over the
2007 and 2040 time period. As a result, it illustrates how the choice of discount rate
determines the present value of the total social costs of the program.
The NPV calculations presented in this Appendix are based on the period 2006-2040,
reflecting the period when the analysis was completed. This has the consequence of
discounting the current year costs, 2007, and all subsequent years are discounted by an
additional year. The result is a smaller stream of social costs than by calculating the NPV
over 2007-2040 (3% smaller for 3% NPV and 7% smaller for 7% NPV).
u The engineering costs we used in the EIA are an earlier version of the estimated compliance costs developed
forthisrule; see Section 7.3.2 for an explanation of the difference. This difference is not expected to have an
impact on the results of the market analysis or on the expected distribution of social costs among stakeholders.
7-108
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Economic Impact Analysis
Table 7D-1. Time Series of Social Costs: 2007 to 2040 ($2005, $million)a'b
Stakeholder Groups 2007
Rail Sector
Locomotive Producers -$8.6
Line-Haul -$6.0
Switcher/Passenger -$2.6
Rail Transportation Service $0.0
Providers
Rail Transportation Service $0.0
Consumers
Total Locomotive Sector -$8.6
Marine Sector
Marine Engine Producers -$17.3
Auxiliary >800 hp -$2.6
Cl>800hp -$1.9
C2 >800 hp -$2.0
Other Marine -$10.8
Marine Vessel Producers $0.0
Cl>800hp $0.0
C2 >800 hp $0.0
Other Marine $0.0
Recreation and Fishing $0.0
Vessel Consumers
Marine Transportation $0.0
Service Providers
Marine Transportation $0.0
Service Consumers
Auxiliary Engines < 800 hpc -$7.6
Total Marine Sector -$25 .0
Total Program -$33.5
2008
-$8.7
-$6.1
-$2.6
-$6.1
-$19.5
-$34.3
-$17.3
-$2.6
-$1.9
-$2.0
-$10.8
-$0.1
$0.0
-$0.1
$0.0
$0.0
-$4.3
-$13.7
-$7.6
-$43.1
-$77.4
2009
-$8.7
-$6.1
-$2.6
-$7.7
-$24.5
-$40.9
-$17.3
-$2.6
-$1.9
-$2.0
-$10.8
-$0.1
$0.0
-$0.1
$0.0
$0.0
-$5.7
-$18.2
-$7.6
-$49.1
-$89.9
2010
-$38.7
-$33.7
-$5.0
-$13.8
-$44.1
-$96.6
-$17.3
-$2.6
-$1.9
-$2.0
-$10.8
-$0.2
$0.0
-$0.1
$0.0
$0.0
-$7.1
-$22.8
-$7.6
-$55.1
-$151.7
2011
-$42.4
-$35.5
-$7.0
-$26.1
-$83.5
-$152.0
-$76.2
-$20.2
-$21.4
-$14.1
-$20.5
-$0.2
$0.0
-$0.1
$0.0
$0.0
-$8.6
-$27.5
-$15.0
-$127.6
-$279.5
2012
-$35.1
-$27.8
-$7.2
-$21.4
-$68.4
-$124.9
-$45.8
-$16.0
-$19.0
-$10.7
$0.0
-$0.3
-$0.1
-$0.1
-$0.1
$0.0
-$11.9
-$38.1
$0.0
-$96.1
-$221.0
2013
-$35.1
-$27.8
-$7.2
-$19.5
-$62.4
-$116.9
-$45.8
-$16.0
-$19.0
-$10.7
$0.0
-$0.3
-$0.1
-$0.2
-$0.1
$0.0
-$12.9
-$41.2
$0.0
-$100.1
-$217.0
2014
-$40.7
-$30.9
-$9.8
-$14.5
-$46.3
-$101.4
-$45.8
-$16.0
-$19.0
-$10.7
$0.0
-$0.3
-$0.1
-$0.1
-$0.1
$0.0
-$12.8
-$40.9
$0.0
-$99.7
-$201.1
2015
-$5.5
-$0.6
-$4.9
-$32.0
-$102.5
-$140.1
-$63.1
-$22.3
-$25.7
-$15.1
$0.0
-$13.3
-$9.4
-$3.8
$0.0
$0.0
-$9.9
-$31.8
$0.0
-$118.2
-$258.3
2016
-$8.3
-$0.9
-$7.4
-$43.4
-$138.9
-$190.6
-$2.1
-$0.5
-$1.6
$0.0
$0.0
-$15.8
-$13.5
-$2.2
-$0.1
$0.0
-$18.1
-$57.9
$0.0
-$93.8
-$284.4
2017
-$0.9
-$0.8
-$0.1
-$40.5
-$129.6
-$171.0
-$2.1
-$0.5
-$1.6
$0.0
$0.0
-$12.9
-$11.6
-$1.2
-$0.1
$0.0
-$20.6
-$66.1
$0.0
-$101.8
-$272.8
2018
-$1.0
-$1.0
-$0.1
-$45.1
-$144.4
-$190.5
-$1.7
-$0.4
-$1.2
$0.0
$0.0
-$10.0
-$8.7
-$1.3
-$0.1
$0.0
-$22.5
-$71.9
$0.0
-$106.1
-$296.6
(continued)
7-109
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Regulatory Impact Analysis
a,b
Table 7D-1. Time Series of Social Costs: 2007 to 2040 ($2005, Smillion) ' (continued)
Stakeholder Groups 2019
Rail Sector
Locomotive Producers -$1.1
Line-Haul -$1.0
Switcher/Passenger -$0. 1
Rail Transportation Service -$47.9
Providers
Rail Transportation Service -$153.3
Consumers
Total Locomotive Sector -$202.3
Marine Sector
Marine Engine Producers -$1.7
Auxiliary >800 hp -$0.4
Cl>800hp -$1.2
C2 >800 hp $0.0
Other Marine $0.0
Marine Vessel Producers -$10.2
Cl>800hp -$8.7
C2>800hp -$1.3
Other Marine -$0.1
Recreation and Fishing $0.0
Vessel Consumers
Marine Transportation -$25.9
Service Providers
Marine Transportation -$82.8
Service Consumers
Auxiliary Engines < 800 hpc $0.0
Total Marine Sector -$120.6
Total Program -$322.9
2020
-$1.1
-$1.0
-$0.1
-$46.4
-$148.6
-$196.1
-$1.8
-$0.4
-$1.3
$0.0
$0.0
-$10.3
-$8.8
-$1.3
-$0.1
$0.0
-$29.5
-$94.4
$0.0
-$135.9
-$332.0
2021
-$1.2
-$1.2
-$0.1
-$51.1
-$163.5
-$215.8
-$1.8
-$0.4
-$1.3
-$0.1
$0.0
-$10.5
-$8.9
-$1.4
-$0.2
$0.0
-$33.1
-$105.9
$0.0
-$151.2
-$367.0
2022
-$1.5
-$1.4
-$0.1
-$60.9
-$194.8
-$257.2
-$1.8
-$0.4
-$1.3
-$0.1
$0.0
-$10.6
-$9.0
-$1.4
-$0.2
$0.0
-$36.7
-$117.3
$0.0
-$166.4
-$423.5
2023
-$2.0
-$1.8
-$0.2
-$76.8
-$245.9
-$324.7
-$1.8
-$0.4
-$1.3
-$0.1
$0.0
-$10.8
-$9.1
-$1.5
-$0.2
$0.0
-$40.2
-$128.7
$0.0
-$181.5
-$506.1
2024
-$2.1
-$1.9
-$0.2
-$78.7
-$251.7
-$332.5
-$1.9
-$0.5
-$1.3
-$0.1
$0.0
-$10.9
-$9.2
-$1.5
-$0.2
$0.0
-$43.7
-$140.0
$0.0
-$196.4
-$528.9
2025
-$2.3
-$2.0
-$0.2
-$84.7
-$271.2
-$358.2
-$1.9
-$0.5
-$1.3
-$0.1
$0.0
-$11.0
-$9.2
-$1.6
-$0.2
$0.0
-$47.2
-$151.1
$0.0
-$211.3
-$569.5
2026
-$2.3
-$2.1
-$0.3
-$86.2
-$275.9
-$364.4
-$1.9
-$0.5
-$1.3
-$0.1
$0.0
-$11.2
-$9.3
-$1.6
-$0.3
$0.0
-$50.7
-$162.2
$0.0
-$226.0
-$590.4
2027
-$2.5
-$2.2
-$0.3
-$91.3
-$292.0
-$385.8
-$2.0
-$0.5
-$1.4
-$0.1
$0.0
-$11.3
-$9.4
-$1.6
-$0.3
$0.0
-$54.1
-$173.1
$0.0
-$240.4
-$626.2
2028
-$2.8
-$2.5
-$0.3
-$99.6
-$318.8
-$421.2
-$2.0
-$0.5
-$1.4
-$0.1
$0.0
-$11.5
-$9.5
-$1.7
-$0.3
$0.0
-$57.4
-$183.7
$0.0
-$254.6
-$675.8
2029
-$2.9
-$2.6
-$0.4
-$104.6
-$334.8
-$442.3
-$2.0
-$0.5
-$1.4
-$0.1
$0.0
-$9.1
-$8.1
-$0.7
-$0.3
$0.0
-$60.5
-$193.7
$0.0
-$265.3
-$707.6
2030
-$3.1
-$2.7
-$0.4
-$109.0
-$348.9
-$461.1
-$2.0
-$0.5
-$1.4
-$0.1
$0.0
-$9.2
-$8.2
-$0.7
-$0.3
$0.0
-$63.3
-$202.5
$0.0
-$277.0
-$738.1
(continued)
7-110
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Economic Impact Analysis
a,b
Table 7D-1. Time Series of Social Costs: 2007 to 2040 ($2005, Smillion) ' (continued)
Stakeholder Groups
Rail Sector
Locomotive Producers
Line-Haul
Switcher/Passenger
Rail Transportation Service
Providers
Rail Transportation Service
Consumers
Total Locomotive Sector
Marine Sector
Marine Engine Producers
Auxiliary >800 hp
Cl >800 hp
C2 >800 hp
Other Marine
Marine Vessel Producers
Cl >800 hp
C2 >800 hp
Other Marine
Recreation and Fishing
Vessel Consumers
Marine Transportation
Service Providers
Marine Transportation
Service Consumers
Auxiliary Engines < 800 hpฐ
Total Marine Sector
Total Program
2031
-$3.3
-$2.8
-$0.4
-$113.8
-$364.2
-$481.2
-$2.1
-$0.5
-$1.4
-$0.1
$0.0
-$9.3
-$8.2
-$0.8
-$0.3
$0.0
-$65.7
-$210.4
$0.0
-$287.5
-$768.7
2032
-$3.4
-$2.9
-$0.5
-$116.2
-$372.0
-$491.6
-$2.1
-$0.5
-$1.4
-$0.1
$0.0
-$9.5
-$8.3
-$0.8
-$0.3
$0.0
-$68.0
-$217.7
$0.0
-$297.3
-$788.9
2033
-$3.9
-$3.4
-$0.5
-$134.7
-$431.1
-$569.8
-$2.1
-$0.5
-$1.4
-$0.1
$0.0
-$9.6
-$8.4
-$0.8
-$0.4
$0.0
-$70.2
-$224.8
$0.0
-$306.7
-$876.5
2034
-$4.1
-$3.6
-$0.6
-$141.6
-$453.0
-$598.7
-$2.1
-$0.5
-$1.4
-$0.1
$0.0
-$9.7
-$8.5
-$0.8
-$0.4
$0.0
-$72.4
-$231.6
$0.0
-$315.8
-$914.4
2035
-$4.3
-$3.7
-$0.6
-$147.9
-$473.2
-$625.4
-$2.2
-$0.5
-$1.5
-$0.1
$0.0
-$9.8
-$8.6
-$0.9
-$0.4
$0.0
-$74.4
-$238.1
$0.0
-$324.5
-$949.9
2036
-$4.2
-$3.6
-$0.6
-$150.0
-$479.9
-$634.0
-$2.2
-$0.5
-$1.5
-$0.1
$0.0
-$9.9
-$8.7
-$0.9
-$0.4
$0.0
-$76.4
-$244.5
$0.0
-$333.0
-$967.0
2037
-$4.2
-$3.6
-$0.6
-$154.3
-$493.9
-$652.4
-$2.2
-$0.5
-$1.5
-$0.1
$0.0
-$10.1
-$8.7
-$0.9
-$0.4
$0.0
-$78.4
-$250.8
$0.0
-$341.4
-$993.8
2038
-$4.2
-$3.6
-$0.6
-$158.5
-$507.3
-$670.0
-$2.2
-$0.6
-$1.5
-$0.1
$0.0
-$10.2
-$8.8
-$0.9
-$0.4
$0.0
-$80.3
-$257.1
$0.0
-$349.8
-$1,019.8
2039
-$4.1
-$3.6
-$0.6
-$162.6
-$520.3
-$687.1
-$2.3
-$0.6
-$1.5
-$0.1
$0.0
-$10.3
-$8.9
-$1.0
-$0.4
$0.0
-$82.1
-$262.8
$0.0
-$357.4
-$1,044.5
2040
-$4.0
-$3.5
-$0.6
-$166.6
-$533.0
-$703.6
-$2.3
-$0.6
-$1.5
-$0.1
$0.0
-$10.4
-$9.0
-$1.0
-$0.4
$0.0
-$83.6
-$267.5
$0.0
-$363.7
-$1,067.3
NPV
(3%)
-$221.1
-$172.2
-$48.9
-$1,302.7
-$4,168.7
-$5,692.6
-$307.5
-$87.3
-$106.8
-$56.8
-$56.7
-$150.0
-$126.8
-$19.7
-$3.5
$0.2
-$704.6
-$2,254.7
-$40.2
-$3,456.7
-$9,149.2
NPV
(7%)
-$160.4
-$124.5
-$35.9
-$568.6
-$1,819.5
-$2,548.5
-$229.4
-$64.0
-$74.6
-$42.6
-$48.1
-$72.5
-$60.8
-$10.2
-$1.5
$0.1
-$308.4
-$986.9
-$34.2
-$1,631.3
-$4,179.8
Figures are in 2005 dollars.
Net present values for 2006 are calculated using a social discount rate of 3% and 7% over the 2007 to 2040 time period.
Marine auxiliary engines <800 hp are not subject to Tier 4 standards, and there are no variable costs associated with the Tier 3 standards. Consequently,
there would be no direct compliance impacts for producers or users of these engines. Social costs are limited to fixed costs associated with tooling and
certification for Tier 3 standards (those costs occur 2007-2011).
7-111
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Regulatory Impact Analysis
Appendix 7E: Model Equations
To develop the economic impact model, we use a set of nonlinear supply and demand
equations for the affected markets and transform them into a set of linear supply and demand
equations. These resulting equations describe stakeholder production and consumption
responses to policy-induced cost and price changes in each market. They are also used to
specify the conditions for a new with-policy equilibrium. We describe these equations in
more detail below.
7E.1 Economic Model Equations
7E.1.1 Supply Equations
First, we consider the formal definition of the elasticity of supply with respect to
changes in own price:
dQJQ,
s , .
dpi p
Next, we can use "hat" notation to transform Eq. (7E.1) to proportional changes and
rearrange terms:
4 = esp (7E.la)
where
s*.
y* = percentage change in the quantity of market supply,
ys = market elasticity of supply, and
P = percentage change in market price.
As Fullerton and Metcalf note, this approach takes the elasticity definition and turns it
into a linear behavioral equation for each market.
31
To introduce the direct impact of the regulatory program, we assume the direct per-
unit compliance cost (c) leads to a proportional shift in the marginal cost of production. Under
the assumption of perfect competition (price equals marginal cost), we can approximate this
shift at the initial equilibrium point as follows:
--. (TRlb)
7-112
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Economic Impact Analysis
The with-regulation supply response to price and cost changes can now be written as:
Qs = ss(p-MC) (7E.lc)
For equipment producers, the supply response also simultaneously accounts for
changes in equilibrium input prices (engines). To do this, we modify Eq. (7E. Ib) as follows:
c +
(7E. Id)
where Apengine is the equilibrium change in the engine price and a is the ratio of engines used
per unit of equipment. For example, if one piece of equipment uses only one engine, then a =
1 . This equation can accommodate other input-output ratios by multiplying Apeng by the
appropriate input-to-output ratio (a).
For transportation service providers, the supply response also simultaneously accounts
for changes in equilibrium input prices (equipment). To do this, we use an equation similar to
Eq. (TE.l.d):
where Apequip is the equilibrium change in the equipment price and a is the ratio of equipment
used per unit of transportation services.
7E.1.2 Demand Equations
Similar to supply, we can characterize services and selected equipment demand
responses to price changes as:
(7E.2)
where
^d = percentage change in the quantity of market demand,
r|d = market elasticity of demand, and
P =
percentage change in market price.
v The equipment markets are recreational vessels and fishing vessels. The remaining vessel and locomotive
demand curves are derived from the supply decisions of the appropriate downstream transportation service
markets.
7-113
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Regulatory Impact Analysis
In contrast the demand for engines and selected equipment markets is a derived
demand and is related to equipment or service supply decisions. In order to maintain a
constant input-to-output ratio, the derived demand for inputs is specified as:
/^ /^
z--input ~ z--output \'*^-*)
7E.1.3 Market Equilibrium Conditions
In response to the exogenous increase production costs, stakeholder responses are
completely characterized by represented in Eq. (7E.l.c)(service, equipment and engine
supply), Eq. (7E.2) (service and selected equipment demand), Eq. (7E.3) (derived demand for
selected equipment and engine). Next, we specify the relationship that must hold for markets
to "clear", that is, supply in each market equals demand. Given the equations specified above,
the new equilibrium satisfies the condition that for each market, the proportional change in
supply equals the proportional change in demand:
Q,=Qd- (7E-4)
7E.2 Computing With-Regulation Equilibrium Conditions within the
Spreadsheet
The French economist Leon Walras proposed one early model of market price
adjustment by using the following thought experiment. Suppose there is a hypothetical agent
that facilitates market adjustment by playing the role of an "auctioneer." He announces prices,
collects information about supply and demand responses (without transactions actually taking
place), and continues this process until market equilibrium is achieved.
For example, consider the with-regulation supply and demand conditions at the
without-regulation equilibrium price (P) (see Figure 7E-1). The auctioneer determines that the
quantity demanded (A) exceeds the quantity supplied (B) at this price and calls out a new
(higher) price (P') based on the amount of excess demand. Consumers and producers make
new consumption and production choices at this new price (i.e., they move along their
respective demand and supply functions), and the auctioneer checks again to see if excess
demand or supply exists. This process continues until P = P* (point C in Figure 7E-1) is
reached (i.e., excess demand is zero in the market). A similar analysis takes place when
excess supply exists. The auctioneer calls out lower prices when the price is higher than the
equilibrium price.
7-114
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Economic Impact Analysis
$/Q
Price
Increase
: With Regulation
S0: Without
Regulation
Q/t
Figure 7E-1. Computing With-Regulation Equilibrium
The economic model uses a similar type of algorithm for determining with-regulation
equilibria, and the process can be summarized by six recursive steps:
1. Impose the control costs on affected supply segments, thereby affecting their
supply decisions.
2. Recalculate the market supply in each market. Excess demand currently exists.
3. Determine the new prices via a price revision rule. We use a rule similar to the
factor price revision rule described by Kimbell and Harrison.32 P; is the market
price at iteration i, qd is the quantity demanded, and qs is the quantity supplied. The
parameter z influences the magnitude of the price revision and the speed of
convergence. The revision rule increases the price when excess demand exists,
lowers the price when excess supply exists, and leaves the price unchanged when
market demand equals market supply. The price adjustment is expressed as
follows:
(7E.5)
4. Recalculate market supply with new prices.
5. Compute market demand in each market.
7-115
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Regulatory Impact Analysis
6. Compare supply and demand in each market. If equilibrium conditions are not
satisfied, go to Step 3, resulting in a new set of market prices. Repeat until
equilibrium conditions are satisfied (i.e., the ratio of supply and demand is
arbitrarily close to one). When the ratio is appropriately close to one, the market-
clearing condition of supply equals demand is satisfied.
7E.3 Social Costs: Consumer and Producer Economic Welfare Calculations
The change in consumer surplus in the affected markets can be estimated using the
following linear approximation method:
JCS = -[Q} x>] + [0.5 x^Q x>]. (7E.6)
As shown, higher market prices and reduced consumption lead to welfare losses for
consumers. A geometric representation of this calculation is illustrated in Figure 7E-2.
For affected supply, the change in producer surplus can be estimated with the
following equation:
)PS = [Q} x >] - [Qj x jMC} - [0.5 x )Q x ()p-)MC)l (7E.7)
Increased regulatory costs and output declines have a negative effect on producer surplus,
because the net price change Qp - )MC) is negative. However, these losses are mitigated, to
some degree, as a result of higher market prices. A geometric representation of this
calculation is also illustrated in Figure 7E-2.
Throughout this report, changes in surplus reflect the social costs of the emission
control program. These calculations exclude any environmental benefits associated with the
rule.
7-116
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Economic Impact Analysis
Price
Increase
S-i: With Regulation
Cost Increase
S0: Without Regulation
Output
) consumer surplus = -[fghd + dhc]
) producer surplus = [fghd - aehb] - bdc
) total surplus = -[aehb + dhc + bdc]
Figure 7E-2. Economic Welfare Calculations: Changes in Consumer, Producer,
and Total Surplus
7-117
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Regulatory Impact Analysis
Appendix 7F: Elasticity Parameters for Economic Impact
Modeling
Elasticities were obtained from peer-reviewed literature or were obtained from other
EPA rule that estimated these parameters using empirical methods (i.e. econometrically).
Table 7F-1 and Table 7F-2 summarize the price elasticities of supply and demand used in this
analysis. The methodologies for estimating the supply and demand elasticities are described
in the documents identified in the data source column. The unknown parameters for the
analysis were the locomotive and commercial marine vessel supply elasticities. This
appendix describes the methods and data used to identify these two supply elasticites used in
the economic impact analysis.
It should be noted that the methods we used to estimate the price elasticites have
certain limitations. The production function approach that was previously used to estimate
the supply elasticity or the approach described in this appendix was limited in available data.
Specifically, firm level or plant level data was unavailable for the companies that operate in
the affected sectors. As a result, the supply elasticities were estimated with industry level
aggregate data. However, the use of aggregate industry level data may not be appropriate or
an accurate way to estimate the price elasticity of supply compared to firm-level or plant-level
data. This is because, at the aggregate industry level, the size of the data sample is limited to
the time series of the available years and because aggregate industry data may not reveal each
individual firm or plant production function (heterogeneity). There may be significant
differences among the firms that may be hidden in the aggregate data but that may affect the
estimated elasticity. In addition, the use of time series aggregate industry data may introduce
time trend effects that are difficult to isolate and control.
To address these concerns, EPA intends to investigate estimates for the price elasticity
of supply for the affected industries for which published estimates are not available, using
alternative methods and data inputs. This research program will use the cross-sectional data
model at either the firm-level or plant level from the U.S. Census Bureau to estimate these
elasticities. We plan to use the results of this research provided the results are robust and that
they are available in time for the analysis for the final rule.
Table 7F-1. Summary of Market Demand Elasticities Used in EIM
Market
Estimate
Source
Method
Data Source
Rail
Rail Transp.
Svcs
Locomotives
-0.5
Literature
estimate
Literature
review
Boyer, K.D. 1997. Principles of
Transportation Economics. Reading, MA:
Addison- Wesley.
Derived
Marine
7-118
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Economic Impact Analysis
Marine
Transp. Svcs
Vessels
Commercial
Fishing
(>800 hp)
Vessels
Fishing
(<800 hp)
Vessels
Recreational
Engines
-0.5
Literature
estimate
Assumed
value
Uses the same elasticity as the locomotive
transportation services sector.
Derived
-2.0
-2.0
Econometric
estimate
Econometric
estimate
Assumed
value
Previous
EPA
economic
analysis
Uses the same elasticity as the recreation
vessels sector.
U.S. Environmental Protection Agency
(EPA). 2007. Control of Emissions from
Marine SI and Small SI Engines, Vessels,
and Equipment Draft Regulatory Impact
Analysis. EPA420-D-07-004. Available at
.
Derived
Table 7F-2. Summary of Supply Elasticities Used in EIM
Market
Estimate
Source
Method
Input Data Source
Rail
Rail Transp.
Svcs
Locomotives
1.6
2.7
Literature
estimate
EPA
estimate
Method based
on cost
elasticities
reported in
Ivaldi and
McCollough
(2001)
Calibration
method
Ivaldi, M. and McCullough, G. 2001.
"Density and Integration Effects on Class I
U.S. Freight Railroads." Journal of Regulatory
Economics 19:161-162.
U.S. Bureau of the Census. 2004a. "Railroad
Rolling Stock Manufacturing: 2002." 2002
Economic Census Manufacturing Industry
Series. EC02-3 11-3365 10 (RV). Washington,
DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2005. "Statistics
for Industry Groups and Industries: 2004"
Annual Survey of Manufacturers. M04(AS)-1.
Washington, DC: U.S. Bureau of the Census.
Table 2.
Marine
Marine
Transp. Svcs
1.6
Assumed value; uses the same elasticity as the rail transportation services sector
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Regulatory Impact Analysis
Vessels
Commercial
and large
fishing
Vessels
Recreational
and small
fishing
Engines
2.3
2.3
3.8
EPA
estimate
Econometric
estimate
Econometric
estimate
Calibration
method
Previous EPA
economic
analysis
Previous EPA
economic
analysis
U.S. Bureau of the Census. 2004b. "Ship
Building and Repairing: 2002." 2002
Economic Census Manufacturing Industry
Series. EC02-31I-336611 (RV). Washington,
DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2005. "Statistics
for Industry Groups and Industries: 2004"
Annual Survey of Manufacturers. M04(AS)-1.
Washington, DC: U.S. Bureau of the Census.
Table 2.
U.S. Environmental Protection Agency
(EPA). 2007. Control of Emissions from
Marine SI and Small SI Engines, Vessels, and
Equipment Draft Regulatory Impact Analysis.
EPA420-D-07-004. Available at
.
U.S. Environmental Protection Agency
(EPA). 2004. Final Regulatory Impact
Analysis: Control of Emissions from Nonroad
Diesel Engines. EPA420-R-04-007.
Available at .
The technique we used to quantify the locomotive and commercial marine vessel
industry supply elasticity is described as "calibration approach" in Handbook of of
33
Econometrics, Volume 5. This approach involves specifying an economic model of supply,
treating some of the parameters of the model as fixed using secondary data, and solving for
unknown parameters that replicate a benchmark data set.w The specific procedure uses an
analytical expression for a short-to-intermediate run supply elasticity derived by Rutherford
and recent benchmark data sets from Economic Census data between 1997 and 2004.
34
As described by Rutherford, the procedure specifies that the functional form of the
production function is the constant elasticity of substitution (CES). It also assumes there is a
fixed capital input that makes it consistent with the intermediate-run time frame of the
analysis. As Rutherford shows, the price elasticity of supply can be expressed as
s = (1 - 0) x G/ 0,
where 0 represents the value share of capital and G represents the elasticity of substitution
between inputs. For this analysis, we assume an elasticity of substitution of one (G =1), which
yields a Cobb-Douglas production technology that is a special case of the CES production
A complete discussion of the meaning, merits and criticism, and best practices of these types of techniques can
be found in Dawkins, Christina & T. N. Srinivasan, & John Whalley, (2001). "Calibration" in Handbook of
Econometrics, Volume 5, ed. J. J. Heckman & E. E. Learner, (Amsterdam: Elsevier).
7-120
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Economic Impact Analysis
function. The Cobb-Douglas production function is one of the most commonly used
production functions in economics studies.
We collected the latest Economic Census data for NAICS 336510 (Railroad Rolling
Stock Manufacturing) that provides an estimate of the value share of capital 0 for
locomotives. To compute this value share, we subtracted reported payroll costs from the
reported industry value added and divided by the total value of shipments (see Table 7F-3).
Using the elasticity formula, o = 1, and annual value share data reported in Table 7F-3, we
computed an average supply elasticity value of 2.7 for this industry. Accounting for
variability of the value share parameter across 1997 to 2004, we computed a 95% confidence
interval for the elasticity value that ranges from 1.9 to 3.4.
Similarly, we estimated the value share of capital 9 for commercial marine vessels
from latest Economic Census data for NAICS 336611 (Ship Building and Repairing
Manufacturing). Using the elasticity formula, o = 1, and annual value share data reported in
Table 7F-4, we computed an average supply elasticity value of 2.3 for this industry. By the
value share parameter across 1997 to 2004, we computed a 95% confidence interval for the
elasticity value that ranges from 1.3 to 3.2.
The parameter estimates suggest both locomotive and commercial marine vessel
supplies are elastic and firms can change production levels in response to changes in market
prices. Two factors support an elastic supply estimate for this sector. First, industries that are
less capital intensive typically have more flexibility to adjust variable inputs (e.g. labor and/or
materials) and can change production levels in response to variations in market prices. The
Census data for locomotive and ship building manufacturing are consistent with this
observation and suggest the capital share of production costs in the locomotive or ship
building industry is small relative to other inputs. The value share of capital is ranging from
20% to 30% for locomotives and from 25% to 38% for ship building and repairing. Second,
industries with excess production capacity also have more flexibility to change output levels
in response to price changes. Data from the Census also suggest the locomotive
manufacturing industry's capacity utilization rates have been low, implying excess capacity
exists. Data for the fourth quarters of 2000 to 2004 show utilization rates ranging from 45% to
69%. For ship building and repairing industry, the production capacity utilization ratio for the
fourth quarters of 2000 to 2004 is ranging around 50% to 80% according to U.S. Bureau of
the Census data.
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Regulatory Impact Analysis
Table 7F-3. Benchmark Supply Elasticities for NAICS 336510 (Railroad Rolling Stock
Manufacturing): 1997-2004 ($1,000)
Value of
Year Shipments Value Added
2004 $7,566,129 $3,216,704
2003 $7,404,763 $2,909,834
2002 $7,793,382 $3,741,703
2001 $8,578,053 $3,824,449
2000 $9,722,424 $4,360,089
1999 $10,352,310 $4,460,735
1998 $9,256,810 $3,848,408
1997 $8,263,395 $3,345,283
Payroll Costs
$1,123,054
$1,156,084
$1,195,073
$1,449,784
$1,480,181
$1,532,969
$1,440,110
$1,319,135
Value Share
of Capital (0)a
28%
24%
33%
28%
30%
28%
26%
25%
Supply Elasticity
ฃ = (1 - 0) x a/ 0
0=1
(Cobb-Douglas)
2.6
3.2
2.1
2.6
2.4
2.5
2.8
3.1
Parameter Statistics
Average
Standard deviation
Upper bound (95% confidence interval)
Lower bound (95% confidence interval)
2.7
0.4
3.4
1.9
"The value share of capital is computed by subtracting payroll costs from reported value added and dividing by
the total value of shipments.
Sources: U.S. Bureau of the Census. 2004. "Railroad Rolling Stock Manufacturing: 2002." 2002 Economic
Census Manufacturing Industry Series. EC02-311-336510 (RV). Washington, DC: U.S. Bureau of the Census.
Table 1.
U.S. Bureau of the Census. 2005. "Statistics for Industry Groups and Industries: 2004." Annual Survey of
Manufacturers. M04(AS)-1. Washington, DC: U.S. Bureau of the Census. Table 2.
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Economic Impact Analysis
Table 7F-4. Benchmark Supply Elasticities for NAICS 336611 (Ship Building &
Repairing): 1997-2004 ($1,000)
Year
2004
2003
2002
2001
2000
1999
1998
1997
Value
Value of Shipments Added
$13,705,958
$13,485,503
$12,814,574
$11,792,832
$11,380,112
$11,070,960
$11,143,246
$10,542,961
$8,573,286
$8,679,730
$8,449,010
$6,968,749
$6,324,192
$6,328,784
$6,728,975
$6,202,797
Payroll
Costs
$3,772,590
$3,692,026
$3,628,382
$3,439,474
$3,435,806
$3,336,632
$3,347,525
$3,353,414
Value Share
of Capital (6)a
35%
37%
38%
30%
25%
27%
30%
27%
Supply
e = (l-9)
Elasticity
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Regulatory Impact Analysis
Appendix 7G: Initial Market Equilibrium - Price Forecasts
The EIM analysis begins with current market conditions: equilibrium supply and
demand. To estimate the economic impact of a regulation, standard practice uses projected
market equilibrium (time series of prices and quantities) as the baseline and evaluates market
changes from this projected baseline. Consequently, it is necessary to forecast equilibrium
prices and quantities for future years.
$/Q
SRS1
SRS
SRS,
Long Run
Supply
Figure 7G-1. Prices and Quantities in Long Run Market Equilibrium
Equilibrium price forecasts typically use one of two approaches.35 The first assumes a
constant (real) price of goods and services over time. The second models a specific time
series where prices may change over time due to exogenous factors.
In the absence of shocks to the economy or the supply of raw materials, economic
theory suggests that the equilibrium market price for goods and services should remain
constant over time. As shown in Figure 7G-1, demand grows over time, in the long run,
capacity will also grow as existing firms expand or new firms enter the market and eliminate
any excess profits. This produces a flat long run supply curve. Note that in the short to
medium run time frame the supply curve has a positive slope due to limitations in how
quickly firms can react.
If capacity is constrained (preventing the outward shift of the baseline supply curve) or
if the price of production inputs increase (shifting the baseline supply curve upward over
time), then prices may trend upward reflecting that either the growth in demand is exceeding
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Economic Impact Analysis
supply or the commodity is becoming more expensive to produce.
It is very difficult to develop forecasts events (such as those mentioned above) that
influence long run prices. As a result, the approach used in this analysis is to use a constant
2005 observed price.
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Regulatory Impact Analysis
Appendix 7H: Sensitivity Analysis
The economic impact analysis presented in this Chapter is based on an economic
impact model developed specifically for this analysis. The EIM reflects specific assumptions
about behavioral responses (represented the price elasaticities of supply and demand) and how
the engineering compliance costs are included in the market supply function shift (supply
affected by variable costs only, in accordance with the underlying assumption of perfect
competition). This appendix examines the sensitivity of the market and social welfare
impacts estimated by the model to the values used for these key parameters. Alternative
values for these parameters are selected and the results are compared to the results of the
primary analysis described in Section 7.1. Four model components are examined:x
Scenario 1: alternative market supply and demand elasticity parameters for all markets
Scenario 2: alternative ways to treat the market supply shifts (variable and fixed costs)
Scenario 3: alternative supply elasticity parameter for equipment markets, based on
supply elasticities estimated using an alternative methodology
Scenario 4: alternative way to treat compliance costs for auxiliary engines above 800 hp
The results of these four sensitivity analysis scenarios are presented below. Although
estimates of market impacts and total economic welfare changes for the different scenarios are
similar for to the primary case, the different assumptions highlight the role the assumptions
play in determining the distribution of welfare changes among stakeholders.
x An additional sensitivity analysis was included in the draft RIA prepared for the NPRM in which we examined
an alternative methodology of allocating operating costs (fuel costs associated with Tier 4 and marine
remanufacture costs). In the primary case for the draft EIA, all marine operating costs were allocated to the
marine transportation service providers; in the sensitivity analysis we explored a scenario that allocated
operating costs to fishing and recreational vessels as well. This scenario is not relevant for the final rule for two
reasons. First, recreational engines are not subject to the Tier 4 standards in the final rule, and recreational
engines above 800 hp are not expected to come under the marine remanufacture program due to their operational
characteristics. Second, fishing vessels below 800 hp are not subject to the Tier 4 standards or marine
remanufacture requirements, and fishing vessels above 800 hp are now modeled as being directly consumed in
the transportation services market (see 7.1.3.2).
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Economic Impact Analysis
7H.1 Model Elasticity Parameters
Key model parameters include estimates of the price elasticity of supply and demand
used by the model to characterize behavioral responses of producers and consumers in each
market in response to a change in price.
Consumer demand and producer supply responsiveness to changes in the commodity
prices are referred to by economists as "elasticity." The measure is typically expressed as the
percentage change in quantity (demanded or supplied) brought about by a percent change in
own price. A detailed discussion regarding the estimation and selection of the supply and
demand elasticities used in the EEVI are discussed in Appendix 10F. This component of the
sensitivity analysis examines the impact of changes in selected elasticity values, holding other
parameters constant. The goal is to determine whether alternative elasticity values
significantly alter conclusions in this report.
There are at least two ways to examine the sensitivity of the EIA results to
assumptions about the price elasticity of supply or demand. The first is to choose upper and
lower bounds for these variables based on the ranges of values reported in the literature or
based on sensitivity analysis constructed around estimated values. This method was not
available for this study because, as described in Appendix F, many of these parameters were
obtained from secondary sources and information was not readily available to compute
confidence intervals for them. Therefore, an alternative approach was used in which the
supply or demand elasticity parameters were increased/decreased by about 25 percent while
holding all other model parameters (including the other elasticities) constant. Table 7H-1
reports the upper- and lower-bound demand and supply elasticity estimates used in this
analysis.
Parameter
Elasticity Source
Lower Bound
Base Case
Upper Bound
DEMAND ELASTICITIES
Rail and marine
transportation
services
Locomotive
Commercial
vessels
Recreational and
fishing vessels
Marine engines
Literature
estimate
Derived
Derived
Econometric
Estimate
Derived
-0.4
-0.5
-0.6
N/A
N/A
-1.5
-2.0
-2.5
N/A
SUPPLY ELASTICITIES
Rail and marine
transportation
services
Locomotives
Commercial
marine vessels
Literature
estimate
Calibration
Estimate
Calibration
Estimate
1.2
2.0
1.7
1.6
2.7
2.3
2.0
3.4
2.9
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Regulatory Impact Analysis
Recreational and
fishing vessels
Marine engines
Econometric
Estimate
Econometric
Estimate
1.7
2.9
2.3
3.8
2.9
4.8
The results of this analysis for 2020 are presented in Tables 7H-2 and 7H-3. Varying
the model's elasticity parameters does not significantly change the estimated impacts on total
economic welfare. However, varying the model parameters has an impact on how the
regulatory program costs are distributed across stakeholders. The elasticity parameters play
an important role in determining the economic incidence of the regulatory program.
In scenarios in which the supply side of the service markets is more responsive to
price changes (more elastic) users of services would bear more of the burden of the regulatory
program. Thus, when the elasticity of supply is more elastic (producers are more sensitive to
a change in price) and demand is held constant, the expected surplus loss to users of
transportation services increases from 28 percent to 30 percent for marine and from 45
percent to 47 percent for rail, respectively (see Table 7H-2). Similarly, when the elasticity of
demand is less elastic (consumers are less sensitive to a change in price) and the supply
elasticity is held constant, the expected surplus loss to users of transportation services
increases from 28 percent to 31 percent for marine and from 45 percent to 48 percent for rail,
respectively (see Table 7H-3).
In contrast, when the supply side of the service market is less responsive to price
changes (the elasticity of supply is less elastic) or the demand side of the service is more
sensitive to price changes (the elasticity of demand is more elastic), service providers would
bear more of the burden of the regulatory program. Here, when the elasticity of supply is
decreased but the elasticity of demand is held constant, the expected surplus loss to providers
of transportation services increases from 9 percent to 11 percent for marine and from 14
percent to 17 percent for rail, respectively (see Table 7H-2). When the elasticity of demand is
more elastic (consumers are more sensitive to a change in price) and the supply elasticity is
held constant, the expected surplus loss to providers of transportation services increases from
9 percent to 10 percent for marine and from 14 percent to 17 percent for rail, respectively (see
Table 7H-3).
With regard to locomotive, marine vessel, and marine diesel engine suppliers, their
share of the surplus loss increases when the price elasticity of supply is less elastic (they are
less sensitive to prices changes) or when the price elasticity of demand is more elastic
(consumers are more sensitive to price changes).
With regard to market effects, price increases and quantity decreases are somewhat
higher when the price elasticity of supply is more elastic or the price elasticity of demand is
less elastic and somewhat lower when the price elasticity of supply is less elastic or the price
elasticity of demand is more elastic.
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Table 7H-2. Sensitivity Analysis for Supply Elasticity Parameters: 2020a
Variable
Engineering
Market-Level Impacts Cost Per Unit
Rail Sector
Locomotives
Line Haul $65,343
Switcher/Passenger $21,139
Transportation services NA
Marine Sector
Engines
Auxiliary >800 hp $28,363
Cl>800hp $14,131
C2 >800 hp $54,893
Other marine $0
Equipment
Cl>800hp $6,936
C2>800hp $10,174
Other marine $0
Transportation services NA
Welfare Impacts (Million $)
Locomotives
Locomotive producers
Line Haul
Switcher/Passenger
Rail transport, service providers
Users of rail transport, services
Total locomotive sector
Marine
Marine engine producers
Auxiliary >800 hp
Cl >800hp
C2 >800 hp
Other marine
Marine vessel producers
Cl>800hp
C2 >800 hp
Other marine
Recreat'l and small /fishing vessel
Marine transport, service providers
Users of marine transport, services
Fixed engineering costs (engines
<800 hp)
Total marine sector
Total program
Primary Case
Change in Price
Absolute Percent
$64,261 3.2%
$20,436 1.6%
NA 0.3%
$27,129 13.1%
$12,497 6.5%
$54,573 12.4%
-$1 0.0%
$26,158 1.6%
$170,164 5.3%
-$6 0.0%
NA 0.6%
Surplus Change
-$1.1
-$1.0
-$0.1
-$46.4
-$148.6
-$196.1
-$1.8
-$0.4
-$1.3
$0.0
$0.0
-$10.3
-$8.8
-$1.3
-$0.1
$0.0
-$29.5
-$94.4
$0.0
-$135.9
-$332.0
Change in Quantity
Absolute Percent
-1 -0.1%
0 -0.1%
NA -0. 1%
-9 -2.7%
-12 -2.9%
0 -0.3%
0 0.0%
-11 -2.9%
0 -0.3%
-2 0.0%
NA -0.3%
Share
0.3%
0.3%
0.0%
14.0%
44.8%
59.1%
0.5%
0.1%
0.4%
0.0%
0.0%
3.1%
2.7%
0.4%
0.0%
0.0%
8.9%
28.4%
0.0%
40.9%
100.0%
Supply Upper
Change in Price
Absolute Percent
$64,433 3.2%
$20,548 1.6%
NA 0.3%
$27,267 13.1%
$12,676 6.6%
$54,621 12.4%
$0 0.0%
$28,705 1.8%
$171,103 5.3%
-$5 0.0%
NA 0.6%
Surplus Change
-$0.9
-$0.9
-$0.1
-$39.0
-$156.1
-$196.1
-$1.6
-$0.4
-$1.1
$0.0
$0.0
-$9.4
-$8.0
-$1.3
-$0.1
$0.0
-$25.0
-$99.9
$0.0
-135.9
-$332.0
Change in Quantity
Absolute Percent
-1 -0.2%
0 -0.2%
NA -0.2%
-10 -3.0%
-13 -3.2%
0 -0.3%
0 0.0%
-12 -3.2%
0 -0.3%
-2 0.0%
NA -0.3%
Share
0.3%
0.3%
0.0%
11.8%
47.0%
59.1%
0.5%
0.3%
0.0%
0.0%
2.8%
2.4%
0.4%
0.0%
0.0%
7.5%
30.1%
0.0%
40.9%
100.0%
Supply Lower
Change in Price
Absolute Percent
$64,009 3.2%
$20,271 1.6%
NA 0.3%
$26,950 13.0%
$12,267 6.4%
$54,502 12.4%
-$1 0.0%
$22,890 1.4%
$168,818 5.2%
-$8 0.0%
NA 0.5%
Surplus Change
-$1.3
-$1.3
-$0.1
-$57.3
-$137.5
-$196.1
-$2.0
-$0.5
-$1.4
-$0.1
$0.0
-$11.5
-$9.9
-$1.4
-$0.2
$0.0
-$36.0
-$86.4
$0.0
-$135.9
-$332.0
Change in Quantity
Absolute Percent
-1 -0.1%
0 -0.1%
NA -0.1%
-8 -2.3%
-10 -2.4%
0 -0.3%
0 0.0%
-10 -2.4%
0 -0.3%
-2 0.0%
NA -0.3%
Share
0.4%
0.4%
0.0%
17.3%
41.4%
59.1%
0.6%
0.4%
0.0%
0.0%
3.5%
3.0%
0.4%
0.1%
0.0%
10.8%
26.0%
0.0%
40.9%
100.0%
Figures are in 2005 dollars.
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Regulatory Impact Analysis
Table 7H-3. Sensitivity Analysis for Demand Elasticity Parameters: 2020"
Variable
Engineering
Market-Level Impacts Cost Per Unit
Locomotives
Line Haul $65,343
Switcher/Passenger $21,139
Transportation services NA
Marine
Engines
Auxiliary>800 hp $28,363
Cl>800hp $14,131
C2 >800 hp $54,893
Other marine $0
Equipment
Cl>800hp $6,936
C2>800hp $10,174
Other marine $0
Transportation services NA
Welfare Impacts (Million $)
Locomotives
Locomotive producers
Line Haul
Switcher/Passenger
Rail transport, service providers
Users of rail transport, services
Total locomotive sector
Marine
Marine engine producers
Auxiliary >800 hp
Cl>800hp
C2 >800 hp
Other marine
Marine vessel producers
Cl>800hp
C2 >800 hp
Other marine
Rec/fishing vessel consumers
Marine transport, service providers
Users of marine transport services
Fixed Engineering Costs (all
engines <800 hp)
Total marine sector
Total program
Primary Case
Change in Price
Absolute Percent
$64,261 3.21%
$20,436 1.57%
NA 0.29%
$27,129 13.07%
$12,497 6.52%
$54,573 12.42%
-$1 0.00%
$26,158 1.63%
$170,164 5.28%
-$6 0.00%
NA 0.55%
Surplus
Change Share
-$1.1 0.3%
-$1.0 0.3%
-$0.1 0.0%
-$46.4 14.0%
_$148.6 44.8%
-$196.1 59.1%
-$1.8 0.5%
-$0.4
-$1.3 0.4%
$0.0 0.0%
$0.0 0.0%
-$10.3 3.1%
-$8.8 2.7%
-$1.3 0.4%
-$0.1 0.0%
$0.0 0.0%
-$29.5 8.9%
-$94.4 28.4%
$0.0 0.0%
-$135.9 40.9%
-$332.0 100.0%
Change in Quantity
Absolute Percent
-1 -0.15%
0 -0.15%
NA -0.15%
-9 -2.69%
-12 -2.86%
0 -0.28%
0 -0.01%
-11 -2.86%
0 -0.28%
-2 -0.01%
NA -0.28%
Surplus
Change
Demand Upper Bound
Change in Price
Absolute Percent
$64,068 3.20%
$20,310 1.56%
NA 0.28%
$26,990 12.99%
$12,318 6.44%
$54,518 12.41%
-$1 0.00%
$23,616 1.47%
$169,132 5.25%
-$7 0.00%
NA 0.52%
Share
-$1.3 0.4%
-$1.2 0.4%
-$0.1 0.0%
-$54.7 16.5%
-$140.1 42.2%
-$196.1 59.1%
-$1.9 0.6%
-$0.5
-$1.4 0.4%
-$0.1 0.0%
$0.0 0.0%
-$11.2 3.4%
-$9.6 2.9%
-$1.4 0.4%
-$0.2 0.1%
$0.0 0.0%
-$34.5 10.4%
-$88.2 26.6%
$0.0 0.0%
-135.8 40.9%
-$331.9 100.0%
Change in Quantity
Absolute Percent
-2 -0.17%
0 -0.17%
NA -0.17%
-10 -2.98%
-13 -3.17%
0 -0.32%
0 -0.01%
-12 -3.17%
0 -0.32%
-2 -0.01%
NA -0.32%
Surplus
Change Share
Demand Lower Bound
Change in Price
Absolute Percent
$64,479 3.22%
$20,577 1.58%
NA 0.31%
$27,306 13.17%
$12,727 6.62%
$54,634 12.43%
$0 0.00%
$29,434 1.85%
$171,356 5.31%
-$5 0.00%
NA 0.59%
-$0.9 0.3%
-$0.8 0.2%
-$0.1 0.0%
-$37.1 11.2%
-$158.2 47.6%
-$196.1 59.1%
-$1.5 0.5%
-$0.4
-$1.1 0.3%
$0.0 0.0%
$0.0 0.0%
-$9.2 2.8%
-$7.8 2.4%
-$1.3 0.4%
-$0.1 0.0%
$0.0 0.0%
-$23.8 7.2%
-$101.5 30.6%
$0.0 0.0%
-$136.0 40.9%
-$332.1 100.0%
Change in Quantity
Absolute Percent
-1 -0.12%
0 -0.12%
NA -0.12%
-8 -2.31%
-10 -2.45%
0 -0.22%
0 -0.01%
-10 -2.45%
0 -0.22%
-1 -0.01%
NA -0.22%
Figures are in 2005 dollars.
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Economic Impact Analysis
7H.2 Fixed Cost Shift Scenario
As discussed in 7.2.3.4, in the primary economic analysis only the variable costs are
used to shift the supply curve in the engine and equipment markets. This is because in a
competitive market the industry supply curve is generally based on the market's marginal cost
curve and fixed costs do not influence production decisions on the margin.
In this scenario, the supply shift for engine and equipment producers includes fixed as
well as variable costs that are incurred in 2014. The year 2014 was chosen because engine
and equipment manufacturers will be incurring R&D and other fixed costs associated with the
Tier 4 standards, but not the one-time certification costs that will be incurred in 2015. The
analysis also includes the Tier 3 variable costs that will continue until the Tier 4 engines and
equipment become available.
Results are provided for all locomotive markets. For the marine sector, only
propulsion marine diesel engines above 800 hp are included. There are two reasons for this.
First, the Economic Impact Model (EIM) does not permit adding marine diesel engines below
800 hp for this sensitivity analysis. Because the smaller marine engines are not subject to the
Tier 4 standards, and there are no variable costs associated with the Tier 3 standards, those
markets were omitted from the EIM to simplify model development. Therefore it is not
possible to include them. Second, as explained in 7.3.2.3, the primary analysis uses one
compliance cost, based on the weighted average compliance costs, for both auxiliary marine
engine markets (800-2,000 hp and above 2,000 hp). This results in an over-estimate of the
market impacts for auxiliary engines 800-2,000 hp and an under-estimate of the market
impacts for auxiliary engines above 2,000 hp, and also affects the impacts on the vessel
markets to which these auxiliary engines were allocated. These effects would be even more
exaggerated if a weighted average of the fixed costs were used. Therefore, the analysis omits
the large auxiliary engines and considers only marine propulsion engines above 800 hp. The
results of this sensitivity analysis are compared with an adjusted primary case that includes
locomotives and marine propulsion engines above 800 hp.
The results of this analysis are presented in Table 7H-4.
In 2014, the changes in the results are considerable. In the rail sector, the expected
price change for line haul locomotives increases from $355 to $38,688 (a 1.9 pecent increase
instead a small price decrease). The expected price change for switcher/passenger
locomotives increases from -$231 to $104,544 for switcher/passenger locomotives (a 8.0
percent price increase instead of a small price decrease. With regard to the social welfare
costs, the burden of the program shifts from locomotive manufacturers to trail transportation
service providers and consumers, as the locomotive manufacturers pass their costs to
downstream consumers. The share of the social costs burden for locomotive manufacturers
drops from 15 percent and 5 percent for line haul and switcher/passenger locomotives,
respectively, to nearly zero. The share of the burden for transportation service providers and
consumers increases from 7.2 percent and 23 percent to 12 percent and 38 percent,
respectively.
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Regulatory Impact Analysis
The results are similar for the marine sector. In this case, engine and vessel prices
change from a slight drop in prices (less than $150 for engines and less than $2,500 for
vessels) to a price increase of 13 to 17 percent for engines ($23,800 and $73,275) and 2 to 5
percent for vessels ($28,388 and $143,674), depending on engine size. With regard to the
social welfare costs, there is also a shift to equipment and the marine transportation sectors
similar to that in the locomotive sector. However, in the marine case equipment
manufacturers are not able to pass along the entire amount of the fixed costs to the
transportation markets, and therefore bear a larger share of the burden. Specifically, the share
of the burden of the program for engine manufacturers drops from 15 percent ($30M) to less
than 1 percent ($1M), while the share of the burden for vessel manufacturers increases from
0.1 percent ($200,000) to 3.6 percent ($7.2M). The burden for marine transportation
providers increases from 6 percent to 9 percent ($12.8M to $17.9M); the burden for marine
transportation service consumers increases from 20 percent to 29 percent ($41 to $57.2M).
Even with these cost and welfare shifts, the overall production of locomotives and
marine diesel engines and vessels is not expected to decrease significantly, and prices of rail
and marine transportation services are not expected to increase significantly. Locomotive
sales would decrease by about 1 locomotive, and marine engines and vessels would decrease
by about 16 engines and 13 vessels. The impact on rail and marine transportation service
prices would be negligible, and both are below 0.5 percent even when fixed costs are
included. This is because rail and marine transportation services are production inputs for
other goods and services, and an increase in their prices would be a relatively small increase
to the total production costs of goods and services using these inputs.
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Economic Impact Analysis
Table 7H-4. Sensitivity Analysis for Supply Shifts (Fixed and Variable Costs): 2014"
Variable Cost Only Supply Shift Fixed and Variable Cost Supply Shift Scenario
Market-Level Impacts
Locomotives
Line Haul
Switcher/Passenger
Transportation services
Marine
Engines
Auxiliary >800 hp
Cl >800 hp
C2 >800 hp
Other marine
Equipment
Cl >800 hp
C2 >800 hp
Other marine
Transportation services
Welfare Impacts (Million $)
Locomotives
Locomotive producers
Line Haul
Switcher/Passenger
Rail transport, service providers
Users of rail transport, services
Total locomotive sector
Marine
Marine engine producers
Auxiliary >800 hp
Cl >800 hp
C2 >800 hp
Other marine
Marine vessel producers
Cl >800 hp
C2 >800 hp
Other marine
Rec/fishing vessel consumers
Marine transport, service providers
Users of marine transport services
Auxiliary marine >800 hp
Total marine sector
Total program
Change in Price
Absolute
-$355
-$231
NA
Percent
0.0%
0.0%
0.1%
Change in Quantity
Absolute
0
0
NA
Percent
0.0%
0.0%
0.0%
Excluded from analysis; see text
-$9
-$147
$0
-$181
-$2,354
$0
NA
0.0%
0.0%
0.0%
0.0%
-0.1%
0.0%
0.3%
Surplus Change
-$40.7
-$30.9
-$9.8
-$14.5
-$46.3
-$101.4
-$29.7
0
0
0
0
0
0
NA
Share
20.2%
15.4%
4.9%
7.2%
23.0%
50.4%
14.8%
0.0%
-0. 1%
0.0%
0.0%
-0. 1%
0.0%
-0.1%
Excluded from analysis; see text
-$19.0
-$10.7
$0.0
-$0.2
-$0.1
-$0.2
$0.0
$0.0
-$12.8
-$41.0
-$16.0
-$99.7
-$201.1
9.4%
5.3%
0.0%
0. 1%
0.0%
0. 1%
0.0%
0.0%
6.4%
20.4%
8.0%
49.6%
100.0%
Change in Price
Absolute
$38,688
$104,544
NA
Percent
1.9%
8.0%
0.2%
Change in Quantity
Absolute
-1
0
NA
Percent
-0.1%
-0.1%
-0.1%
Excluded from analysis; see text
$23.842
$73,275
$0
$28,388
$143,674
$0
NA
13.2%
17.0%
0.0%
2.1%
4.5%
0.0%
0.4%
Surplus Change
-$0.5
-$0.5
$0.0
-$24.0
-$76.9
-$101.4
-$1.2
-16
0
0
-13
0
0
NA
Share
0.2%
0.2%
0.0%
12.0%
38.3%
50.5%
0.6%
-3.5%
-0.2%
0.0%
-3.5%
-0.2%
0.0%
-0.2%
Excluded from analysis; see text
-$1.2
$0.0
$0.0
-$7.2
-$7.0
-$0.2
$0.0
$0.0
-$17.9
-$57.2
-$16.0
-$99.5
-$200.9
0.6%
0.0%
0.0%
3.6%
3.5%
0.1%
0.0%
0.0%
8.9%
28.5%
8.0%
49.5%
100.0%
a Figures are in 2005 dollars.
b Auxiliary engines above 800 were excluded from the model for this sensitivity analysis; this is a line item entry that reflects the engineering costs for these markets.
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Regulatory Impact Analysis
7H.3 Alternative Equipment Supply Elasticity Scenario
In the third sensitivity scenario, we use alternative estimates for the price elasticity of
supply for the locomotive and marine vessel markets.
The supply elasticities used in the primary analysis were estimated using a calibration
approach as described in Appendix F, and aggregate industry data over the years 1997
through 2004 forNAICS 336510 (railroad rolling stock manufacturing) andNAICS 336611
(ship building and repairing). This method was chosen because of limitations with the
available data: we were not able to obtain firm-level or plant-level production data for
companies that operate in the affected sectors. However, as we noted in the proposal for this
rule, the use of aggregate industry level data may not be appropriate or an accurate way to
estimate the price elasticity of supply compared to firm-level or plant-level data. This is
because, at the aggregate industry level, the size of the data sample is limited to the time
series of the available years and because aggregate industry data may not reveal each
individual firm or plant production function (heterogeneity). There may be significant
differences among the firms that may be hidden in the aggregate data but that may affect the
estimated elasticity. In addition, the use of time series aggregate industry data may introduce
time trend effects that are difficult to isolate and control.
To address these concerns, we investigated estimates for the price elasticity of supply
for the affected industries for which published estimates are not available using alternative
methods and data inputs.36 This analysis used a cross-sectional data model and
establishment-level data from the U.S. Census Bureau to estimate these supply elasticities. It
should be noted that this analysis is still in draft form and the estimated supply elasticities
have not yet been peer-reviewed. Therefore, we are providing them as a sensitivity analysis
and not incorporating them into the primary analysis.
Supply elasticities were estimated for 3 markets: NAICS 336611: Ship Building and
Repairing (for commercial marine vessels); NAICS industry 336612: Boat Building (for
recreational marine vessels); andNAICS industry 366510: Railroad Rolling Stock
Manufacturing (for locomotives). We used a panel data set comprised of confidential
establishment-level data from the 1972, 1977, 1982, 1992, 1997 and 2002 Census of
Manufacturers (COM).
It should be noted that while the use of data at the establishment addresses uncertainty
introduced in the analysis by using data aggregated on a yearly basis, it does not resolve
uncertainty due to the variety of establishments included in each NAICS category. Each of
the NAICS categories includes firms engaged in activities that are not affected by the new
standards. In addition, the production processes and thus production function of the non-
affected firms may be very different from those firms that are affected by the rule.
For example, NAICS 336611 includes repair yards as well as yards that produce new
vessels. Repair yards, as well as yards that engaged in specialized services such as scaling,
may not have the same production function as yards that produce new vessels. In addition,
the production function of a yard that engages in all of these activities may be different from a
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Economic Impact Analysis
yard that engages solely in new vessel construction. In addition, NAICS 336611 includes all
shipyards, ranging from yards that make very large ocean-going vessels, to military vessels, to
medium and small commercial craft such as tugs, fishing boats, supply boats, and passenger
vessels, as well as non-self-propelled barges. This large variety of commercial vessels
reflects a range of production processes, not all of which can be expected to be the same as
those used to produce the vessels that will be affected by the rule. For example, the
production processes used to make OGV and military vessels are likely to be different from
those used to make non-self-propelled barges and these are likely to be different from those
used to make commercial self-propelled vessels. In addition, commercial self-propelled
vessels that use engines are likely to have different production processes from smaller
commercial vessels. Large commercial vessels are more likely to be unique designs produced
for a specific customer while small commercial vessels may be serially produced with
minimal customization or even built with fiberglass hulls.
With regard to NAICS 336612, that category includes all boat building, for gasoline as
well as diesel powered vessels. The vast majority of recreational vessels are gasoline
powered and therefore are not affected by this rule. In addition, gasoline-powered vessels are
primarily fiberglass hull vessels. This construction process is very different from aluminum
or wooden hulls used in higher end vessels that are more likely to have diesel engines.
Finally, with regard to NAICS industry 366510: Railroad Rolling Stock
Manufacturing, this category is comprised of roughly 100 establishments primarily involved
in one or more of the following manufacturing activities: manufacturing and/or rebuilding
locomotives, locomotive frames and parts; manufacturing railroad, street, and rapid transit
cars and car equipment for operation on rails for freight and passenger service; and
manufacturing rail layers, ballast distributors, rail tamping equipment and other railway track
maintenance equipment. Many of these establishments are not engaged in locomotive
manufacturing, such as track or rail manufacturing and maintenance, ancillary equipment and
maintenance - these products may involve different technologies or production
processes/functions by using different total labor or materials input from the locomotive
manufacturing. In addition, for the emerging switcher market, we don't know what their
production process is. We assume they have the same production function as the line haul
locomotive manufacturers. But, in fact, the production function of the switcher manufacturers
may be different because they are expected to purchase the "merchant engine" from other
non-road engine manufacturers.
The alternative supply elasticities are set out in Table 7H-6. These supply elasticities
are all more elastic than those used in the primary analysis, suggesting that manufacturers of
locomotives and marine vessels are more sensitive to price changes (a one percent change in
price leads to more than a 1 percent change in quantity supplied).
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Regulatory Impact Analysis
Table 7H-6. Alternative Supply Elasticities
NAICS Primary Case Sensitivity Analysis
NAICS 336510 (locomotives)
NAICS 336611 (commercial marine)
NAICS 336612 (recreational marine)
2.7
2.3
2.3
5.9
7.1
4.2
The results of the sensitivity analysis for 2020 are set out in Table 7H-7. Despite the significant
change in the locomotive and marine vessel supply elasticities, the results of the analysis are not affected by
very much. This suggests that the main driver of the market response to this regulatory program is the
inelastic price elasticity of demand in the affected transportation service markets. There are small increases
in the expected market results, but the price and quantity changes are very small. The price change for
locomotives increases from $64,261 to $64,843 for line haul and from $20,436 to $20,814 for
switcher/passenger locomotives, with no change in the quantity produced. The price change for marine
engines above 800 hp decreases, from $12,497 to $11,842 for Cl engines, and from $54,573 to $54,563 for
C2 engines, with a small change in the quantity produced (less than 20). For vessels, the price change
increases from $26,158 to $34,917 for vessels Cl engines and $170,164 to $172,803 for vessels with C2
engines.
These small impacts occur because the only change in the analysis is to the supply elasticities for the
equipment markets (locomotives and marine vessels). Notably, the supply and demand elasticities for the
rail and marine transportation sectors as well as the supply elasticities for marine engines remain the same.
The more elastic supply elasticities for the equipment markets means suppliers can pass on more of the direct
compliance costs to consumers (in this case, the transportation services market) in the form of higher prices
relative to the primary case. These higher prices lead to a larger decrease in the quantity of equipment
demanded than in the primary case. In the case of marine vessels, the drop in demand is high enough to
slightly offset the price increase associated with the direct compliance costs, resulting in a smaller increase in
prices when compared to the primary case.
There is also a change in the way the social costs are distributed among stakeholders, although these
changes are small. In the rail sector, the share allocated to the transportation services market consumers
increases from 44.8 percent to 44.9 percent, while the share for locomotive producers decreases from 0.3
percent to 0.2 percent. In the marine sector, the share of social costs attributed to marine service providers
and consumers increases from 8.9 percent to 9.1 percent, and 28.4 percent to 29.3 percent, respectively. The
share attributed to engine manufacturers increases somewhat, from 0.5 percent to 0.7 percent, while the share
attributed to vessel producers decreases from 3.1 percent to 1.8 percent.
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Economic Impact Analysis
Table 7H-7. Sensitivity Analysis for Alternative Equipment Supply Elasticities: 2020a
Primary Case Elasticities Alternative Locomotive and Vessel Supply Elasticities
Market-Level Impacts
Rail Sector
Locomotives
Line Haul
Switcher/Passenger
Transportation services
Marine Sector
Engines
Auxiliary >800 hp
Cl>800hp
C2 >800 hp
Other Marine
Equipment
Cl>800hp
C2 >800 hp
Other marine
Transportation services
Welfare Impacts (Million S)
Locomotives
Locomotive Producers
Line Haul
Switcher/Passenger
Rail transportation service providers
Users of rail transportation service
Total locomotive sector
Marine
Marine engine producers
Auxiliary >800 hp
Cl>800hp
C2 >800 hp
Other marine
Marine vessel producers
Cl>800hp
C2 >800 hp
Other marine
Rec/fishing vessel consumers
Marine transportation svc providers
Users of marine transportation service
Total marine sector
Total program
Change in Price
Absolute
$64,261
$20,436
N/A
$27,129
$12,497
$54,573
-$1
$26,158
$170,164
-$6
N/A
Percent
3.2%
1.6%
0.3%
13.1%
6.5%
12.4%
0.0%
1.6%
5.3%
0.0%
0.6%
Surplus Change
$1.1
-$1.0
-$0.1
-$46.4
-$148.6
-$196.1
-$1.8
-$0.4
-$1.3
$0.0
$0.0
-$10.3
-$8.8
-$1.3
-$0.1
$0.0
-$29.5
-$94.4
-$135.9
-$332.0
Change in Quantity
Absolute
-1
0
N/A
-9
-12
0
0
-11
0
-2
N/A
Share
0.3%
0.3%
0.0%
14.0%
44.8%
59.1%
0.5%
0.1%
0.4%
0.0%
0.0%
3. 1%
2.7%
0.4%
0.0%
0.0%
8.9%
28.4%
40.9%
Percent
-0.1%
-0.1%
-0. 1%
-2.7%
-2.9%
-0.3%
0.0%
-2.9%
-0.3%
0.0%
-0.3%
Change in Price
Absolute
$64,843
$20.814
N/A
$26,677
$11,842
$54,563
-$1
$34,917
$172,803
-$3
N/A
Percent
3.2%
1.6%
0.3%
12.8%
6.2%
12.4%
0.0%
2.2%
5.3%
0.0%
0.6%
Surplus Change
-$0.5
-$0.5
$0.0
-$46.6
-$149.0
-$196.1
-$2.4
-$0.6
-$1.8
-$0.1
$0.0
-$6.0
-$4.8
-$1.1
$0.0
$0.0
-$30.4
-$97.2
-$135.9
-$322.0
Change in Quantity
Absolute
-1
0
N/A
-13
-17
0
0
-16
0
-2
N/A
Share
0.2%
0. 1%
0.0%
14.0%
44.9%
59.1%
0.7%
0.2%
0.5%
0.0%
0.0%
1.8%
1.4%
0.3%
0.0%
0.0%
9.1%
29.3%
40.9%
Percent
-0.1%
-0.1%
-0.1%
-3.7%
-4.0%
-0.3%
0.0%
-4.0%
-0.3%
0.0%
-0.3%
Figures are in 2005 dollars
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Regulatory Impact Analysis
7H.4 Alternative Auxiliary Engine Compliance Cost Scenario
In the fourth sensitivity scenario, we use alternative compliance costs for marine
auxiliary engines above 800 hp.
As explained in section 7.3.2.2, the compliance costs for marine auxiliary engines above
800 hp are a weighted average of all compliance costs for those engines. This weighted average
is applied to both categories of auxiliary marine engines examined in this anlaysis: those 800-
2,000 hp and those above 2,000 hp. This means that the supply shift is the same for both of the
auxiliary engine markets even though the actual program impacts are different for them. The
weighted average compliance costs were obtained by dividing the total compliance costs for
engines above 800 hp by the number of engines above 800 hp. This results in estimated
compliance costs of $37,097 in 2016, the first year of the Tier 4 program.
In this analysis, we apply separate compliance costs to each of the two auxiliary marine
engine markets, using the compliance costs set out in Table 7H-8. We performed the analysis for
2016 and 2030. The results are reported in Tables 7H-9 and 7H-10.
Table 7H-7. Sensitivity Analysis for Alternative Compliance Costs: Marine Auxiliary
Markets
Engine Category Primary Case Sensitivity Analysis
Aux. Marine 800-2,000
Aux Marine >2,000 hp
$37,097
$28,359
2016
$19,073
$14,582
2030
$67,255
$51,414
As expected, the market results for this analysis are different for marine auxiliary
engines. In 2016, the expected price impacts for engines 800 to 2,000 hp is lower than the
primary case (10.4 percent price increase instead of 20.9 percent) and the expected price impacts
for engines above 2,000 hp being higher (18.3 percent price increase instead of 9.6 percent).
There is only a small change in quantity produced, however, with a slightly smaller decrease for
auxiliary engines 800 to 2,000 hp and no change for the larger engines. These results are similar
for a 2030.
The social welfare impacts change only negligibly for the marine markets (less
than 0.5 percent change), with marine engine and vessel producers bearing slightly less of the
total social welfare costs and marine transportation service providers and users bearing slightly
more. Specifically, in 2016 the share for engine manufacturers decreases to 0.6 percent from 0.7,
while vessel manufacturers would see their share decrease from 5.8 percent to 5.1 percent.
Marine transportation service providers would see their share increase from 6.4 percent to 6.5
percent, and marine transportation service users would see their share increase from 20.3 percent
to 20.7 percent. We expect that actual social welfare impacts would be less that these estimated
impacts, however. By allocating all of the auxiliary engines above 800 hp to the vessels that will
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Economic Impact Analysis
be affected by this program, this analysis over-estimates the vessel impacts of the program. In
fact, not all of the very large auxiliary engines are actually used on the commercial vessels that
are subject to this program; some will be installed on vessels with Category 3 marine diesel
engines. While it is appropriate to consider these costs in the economic impact analysis for this
program, it is clear that not all of these social costs will be passed on to the producers and users
of vessels directly affected by this program.
In conclusion, the simplifying method of using weighted average compliance costs for
auxiliary engines above 800 hp does not change the results of the analysis.
Table 7H-9. Sensitivity Analysis for Auxiliary Engine Compliance Costs: 2016a
Primary Scenario Sensitivity Scenario
Market-Level
Impacts
Locomotives
Line Haul
Switcher/Passenger
Transportation services
Marine
Engines
Aux 800 to 2000 hp
Aux > 2000 hp
Cl>800hp
C2 >800 hp
Other marine
Equipment
Cl >800 hp
C2 >800 hp
Other marine
Transportation
services
Welfare Impacts
(Million $)
Locomotives
Locomotive producers
Line Haul
Switcher/Passenger
Rail transport, service
providers
Users of rail
transport, services
Total locomotive
sector
Marine
Marine engine
producers
Aux 800 to 2000 hp
Aux > 2000 hp
Cl >800 hp
C2 >800 hp
Other marine
Marine vessel
producers
Cl >800 hp
Change in Price
Absolute
$84,227
$13,494
NA
$34,894
$36,919
$16,384
$71,602
$0
$34,043
$225,143
-$4
NA
Percent
4.2%
1.0%
0.3%
20.9%
9.6%
8.5%
16.3%
0.0%
2.1%
7.0%
0.0%
0.4%
Surplus
Change
-$8.3
-$0.9
-$7.4
-$43.4
-$138.9
-$190.6
-$2.1
-$0.4
-$0.1
-$1.6
$0.0
$0.0
-$15.8
-$13.5
Change in Quantity
Absolute
-1
0
NA
-11
0
-15
0
0
-14
0
-1
NA
Share
2.9%
0.3%
2.6%
15.3%
48.8%
67.0%
0.7%
0.1%
0.0%
0.5%
0.0%
0.0%
5.6%
4.7%
Percent
-0.1%
-0.1%
-0.1%
-5.0%
-0.2%
-3.7%
-0.2%
0.0%
-3.7%
-0.2%
0.0%
-0.2%
Change in Price
Absolute
$84,227
$13,494
NA
$17,417
$67,084
$16,696
$71,600
$0
$29,574
$262,231
-$4
NA
Percent
4.2%
1.0%
0.3%
10.4%
18.3%
8.6%
16.3%
0.0%
1.9%
8.4%
0.0%
0.4%
Surplus
Change
-$8.3
-$0.9
-$7.4
-$43.4
-$138.9
-$190.6
-$1.8
-$0.3
-$0.1
-$1.3
-$0.0
$0.0
-$14.5
-$12.2
Change in Quantity
Absolute
-1
0
NA
-8
0
-14
0
0
-12
0
-1
NA
Share
2.9%
0.3%
2.6%
15.3%
48.8%
67.0%
0..6%
0.1%
0.0%
0.5%
0.0%
0.0%
5.1%
4.3%
Percent
-0.1%
-0. 1%
-0.1%
-3.8%
-0.2%
-3.3%
-0.2%
0.0%
-3.3%
-0.2%
0.0%
-0.2%
7-139
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Regulatory Impact Analysis
C2 >800 hp
Other marine
Rec/fishing vessel
consumers
Marine transport.
service providers
Users of marine
transport services
Total marine sector
Total program
-$2.2
-$0.1
$0.0
-$18.1
-$57.9
-$93.8
-$284.4
0.8%
0.0%
0.0%
6.4%
20.3%
33.0 %
100.0%
-$2.2
$0.1
$0.0
-$18.3
-$58.7
-$93.3
-$283.8
0.8%
0.0%
0.0%
6.5%
20.7%
32.9%
100.0%
Figures are in 2005 dollars
7-140
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Economic Impact Analysis
Table 7H-10. Sensitivity Analysis for Auxiliary Engine Compliance Costs: 2030a
Primary Scenario Sensitivity Scenario
Market Level
Impacts
Locomotives
Line Haul
Switcher/Passenger
Transportation services
Marine
Engines
Aux 800 to 2000 hp
Aux > 2000 hp
Cl >800hp
C2 >800 hp
Other marine
Equipment
Cl >800 hp
C2 >800 hp
Other marine
Transportation
services
Welfare Impacts
(Million $)
Locomotives
Locomotive producers
Line Haul
Switcher/Passenger
Rail transport, service
providers
Users of rail
transport, services
Total locomotive
sector
Marine
Marine engine
producers
Aux 800 to 2000 hp
Aux > 2000 hp
Cl >800 hp
C2 >800 hp
Other marine
Marine vessel
producers
Cl >800 hp
C2 >800 hp
Other marine
Rec/fishing vessel
consumers
Marine transport.
service providers
Users of marine
transport services
Total marine sector
Total program
Change in Price
Absolute
$63,019
$19,628
NA
$26,626
$27,809
$12,479
$54,264
-$1
$25,768
$164,774
-$12
NA
Percent
3.2%
1.5%
0.6%
15.9%
7.2%
6.5%
12.3%
0.0%
1.6%
5.1%
0.0%
1.1%
Surplus
Change
-$3.1
-$2.7
-$0.4
-$109.0
-$348.9
-$461.1
-$2.0
-$0.4
-$0.1
-$1.4
-$0.1
$0.0
-$9.2
-$8.2
-$0.7
$0.3
$0.0
-$63.3
-$202.5
-$277.0
-$738.1
Change in Quantity
Absolute
-4
-1
NA
-10
-1
-13
-1
0
-12
0
-4
NA
Share
0.4%
0.4%
0.1%
14.8%
47.3%
62.5%
0..3%
0.1%
0.0%
0.2%
0.0%
0.0%
1.2%
1.1%
0.1%
0.0%
0.0%
8.6%
27.4%
37.5%
100.0%
Percent
-0.3%
-0.3%
-0.3%
-3.9%
-0.5%
-2.9%
-0.5%
0.0%
-2.9%
-0.5%
0.0%
-0.5%
Change in Price
Absolute
$63,019
$19,628
NA
$13,267
$50,890
$12,718
$54,262
-$1
$22,352
$193,158
-$12
NA
Percent
3.2%
1.5%
0.6%
7.9%
13.9%
6.6%
12.3%
0.0%
1.5%
6.2%
0.0%
1.0%
Surplus
Change
-$3.1
-$2.7
-$0.4
-$109.0
-$348.9
-$461.1
-$1.7
-$0.3
-$0.1
-$1.2
-$0.1
$0.0
-$8.1
-$7.0
-$0.7
$0.3
$0.0
-$63.5
-$203.2
-$276.5
-$737.5
Change in Quantity
Absolute
-4
-1
NA
-8
-1
-12
-1
0
-11
0
-4
NA
Share
0.4%
0.4%
0.1%
14.8%
47.3%
62.5%
0.2%
0.1%
0.0%
0.2%
0.0%
0.0%
1.1%
1.0%
0.1%
0.0%
0.0%
8.6%
27.5%
37.5%
100.0%
Percent
-0.3%
-0.3%
-0.3%
-3.0%
-0.5%
-2.6%
-0.5%
0.0%
-2.6%
-0.5%
0.0%
-0.5%
Figures are in 2005 dollars
7-141
-------
Regulatory Impact Analysis
REFERENCES
1 U.S. EPA "EPA Guidelines for Preparing Economic Analyses." EPA240-R-00-003. September 2000, p. 113. A
copy of this document can be found at http://vosemite.epa.gov/ee/epa/eed.nsf/webpates/guidelines.html
2 Association of American Railroads (AAR). Railroad Facts, 2006 Edition. November 2006. Policy and
Economics Department, Association of American Railroads, 50 F Street NW, Washington DC 20001. www.aar.org.
3 U.S. EPA. Technical Support Document for the Final Locomotive /Marine Rule: Detailed Results from Economic
Impact Model (EIM). December 2007. A copy of this document can be found in the docket for this rule, EPA-HQ-
OAR-2004-0190.
4 U.S. EPA. Technical Support Document for the Final Locomotive /Marine Rule: Detailed Results from Economic
Impact Model (EIM). December 2007. A copy of this document can be found in the docket for this rule, EPA-HQ-
OAR-2004-0190.
5 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
6 Bingham, T.H., and T.J. Fox. "Model Complexity and Scope for Policy Analysis." Public Administration
Quarterly, 23(3), 1999.
7 Berck, P., and S. Hoffman. "Assessing the Employment Impacts." Environmental and Resource Economics
22:133-156. 2002.
8 Office of Management and Budget. "Executive Analysis of Federal regulations Under Executive Order 12866."
Executive Office of the President, Office of Management and Budget. January 11, 1996. A copy of this document
is available at http://www.whitehouse.gov/omb/inforeg/print/riaguide.html
9 U.S. EPA "EPA Guidelines for Preparing Economic Analyses." EPA240-R-00-003. September 2000, p. 126. A
copy of this document can be found at http://yosemite.epa.gov/ee/epa/eed.nsf/webpates/guidelines.html
10 U.S. Government Accountability Office. "Freight Railroads: Industry Health Has Improved, but Concerns about
Competition and Capacity Should Be Addressed." GAO-07-94, October 2006, pg. 42. A copy of this document can
be found at www.gao.gov/new.items/d0794.pdf
11 Association of American Railroads (AAR). Railroad Facts, 2006 Edition. November 2006. Policy and
Economics Department, Association of American Railroads, 50 F Street NW, Washington DC 20001. www.aar.org.
12 Association of American Railroads (AAR). Railroad Facts, 2006 Edition. November 2006. Policy and
Economics Department, Association of American Railroads, 50 F Street NW, Washington DC 20001. www.aar.org.
13 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
14 "Marine Vessel Sales" Memorandum from John Mueller, Office of Transportation and Air Quality, to docket
EPA-HQ-OAR-2003-0190, February 28, 2007.
7-142
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Economic Impact Analysis
15 "Marine Diesel Engine Prices" Memorandum from John Mueller, Office of Transportation and Air Quality, to
docket EPA-HQ-OAR-2003-0190, February 28, 2007.
16 RTI international. Memo to Chi Li, US EPA, "Documentation for EIM Baseline Data for Transportation Service
Markets", December 17, 2007. A copy of this document can be found in the docket for this rule, EPA-HQ-OAR-
2004-0190.
17 Association of American Railroads (AAR). Railroad Facts, 2006 Edition. November 2006. Policy and
Economics Department, Association of American Railroads, 50 F Street NW, Washington DC 20001. www.aar.org.
18 Memorandum, Documentation for EIM Baseline Data for Transportation Services Markets, from Brooks Depro,
RTI International, to Chi Li, U.S. EPA, Dated December 12, 2007.
19 Association of American Railroads (AAR). Railroad Facts, 2006 Edition. November 2006. Policy and
Economics Department, Association of American Railroads, 50 F Street NW, Washington DC 20001. www.aar.org.
20 U.S. Army Corps of Engineers (USAGE), Waterborne Commerce Statistics Center 2005. "Final Waterborne
Commerce Statistics for Calendar Year 2004." Washington, DC: U.S. Army Corps of Engineers.
21 Boyer, K.D. 1997 Principles of Transportation Economics. Reading, MA: Addison-Wesley.
22 U.S. Environmental Protection Agency (EPA). 2007. Control of Emissions from Marine SI and Small SI
Engines, Vessels, and Equipment Draft Regulatory Impact Analysis. EPA420-D-07-004. Available at
.
23 U.S. Environmental Protection Agency (EPA) 2004. Final Regulatory Impact Analysis: Control of Emissions
from Nonroad Diesel Engines. EPA420-R-04-007. Available at http://www.epa.gov/nonroad-
diesel/2004fr/420r04007.pdf
24 U.S. Environmental Protection Agency (EPA) 2004. Final Regulatory Impact Analysis: Control of Emissions
from Nonroad Diesel Engines. EPA420-R-04-007. Available at http://www.epa.gov/nonroad-
diesel/2004fr/420r04007.pdf
25 U.S. Environmental Protection Agency (EPA) 2004. Final Regulatory Impact Analysis: Control of Emissions
from Nonroad Diesel Engines. EPA420-R-04-007. Available at http://www.epa.gov/nonroad-
diesel/2004fr/420r04007.pdf
26 U.S. Environmental Protection Agency (EPA). 2007. Control of Emissions from Marine SI and Small SI
Engines, Vessels, and Equipment Draft Regulatory Impact Analysis. EPA420-D-07-004. Available at
.
27 U.S. Environmental Protection Agency (EPA) 2004. Final Regulatory Impact Analysis: Control of Emissions
form Nonroad Diesel Engines. EPA420-R-04-007. Available at http://www.epa.gov/otaq/nonroad-
diesel/2004fr/420r04007.pdf
28 Kimbell, L.I, and G.W. Harrison. 1986. "On the Solution of General Equilibrium Models." Economic Modeling
3:197-212.
29 See, for example, Harberger, Arnold C. 1974. Taxation and Welfare. Chicago: University of Chicago Press.
7-143
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Regulatory Impact Analysis
30 Ivaldi, M. and McCullough, G. 2001. "Density and Integration Effects on Class I U.S. Freight Railroads."
Journal of Regulatory Economics 19:161-162; see also Boyer, K.D. 1997. Principles of Transportation Economics.
Reading, MA: Addison-Wesley.
31 Fullerton, D., and G. Metcalf. 2002. "Tax Incidence." In A. Auerbach and M. Feldstein, eds., Handbook of Public
Economics, Vol.4, Amsterdam: Elsevier
32 Kimbell, L.J., and G.W. Harrison. 1986. "On the Solution of General Equilibrium Models." Economic Modeling
3:197-212.
33 Handbook of of Econometrics, Volume 5, ed. J. J. Heckman & E. E. Learner (2001, Amsterdam: Elsevier)
34 Rutherford, T. 1998. "CES Preferences and Technology: A Practical Introduction." GAMS MPSGE Guide.
Washington, DC: GAMS Development Corporation.
35 U.S. EPA. "OAQPS Economic Analysis Resource Document." Research Triangle Park, NC: EPA 1999, pages
5-25. A copy of this document can be found at http://www.epa.gov/ttn/ecas/econdata/6807-305.pdf
36 "Supply Elasticity Estimation Report," Memorandum from Nathalie Simon, National Center for Environmental
Economics, January 31, 2008. A copy of this document can be found in Public Docket EPA-HQ-OAR-2003-0190.
7-144
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Regulatory Alternatives
CHAPTER 8: Regulatory Alternatives 8-2
8.1 Alternatives Considered 8-2
8.1.1 Alternative 1: Proposed Program from the NPRM 8-3
8.1.2 Alternative 2: Exclusion of Remanufacturing Standards 8-3
8.1.3 Alternative 3: Elimination of Tier 3 8-3
8.1.4 Alternative 4: Tier 4 Exclusively in 2013 8-4
8.2 Emission Inventory Impacts 8-4
8.2.1 Methodology 8-4
8.2.2 Analysis 8-5
8.3 Summary of Results 8-13
8.3.1 Alternative 1: Proposed Program from the NPRM 8-13
8.3.2 Alternative 2: Exclusion of Remanufacturing Standards 8-13
8.3.3 Alternative 3: Elimination of Tier 3 8-14
8.3.4 Alternative 4: Tier 4 Exclusively in 2013 8-14
3-1
-------
Regulatory Impact Analysis
CHAPTERS: Regulatory Alternatives
The program we are finalizing today represents a broad and comprehensive approach
to reducing emissions from locomotive and marine diesel engines. As we developed this final
rule, we considered a number of alternatives with regard to the scope and timing of the
standards. After carefully evaluating these alternatives, we believe that our new program
provides the best opportunity for achieving timely and substantial emission reductions from
locomotive and marine diesel engines. Our final program balances a number of key factors:
(1) achieving very significant emissions reductions as early as possible, (2) providing
appropriate lead time to develop and apply advanced control technologies, and (3)
coordinating requirements in this final rule with existing highway and nonroad diesel engine
programs. The alternative scenarios described here were constructed to further evaluate each
individual aspect of our program, and have enabled us to achieve the appropriate balance
between these key factors. This chapter presents a detailed explanation of our analysis,
including a year by year breakout of expected costs and emission reductions.
8.1 Alternatives Considered
Our final rule consists of a comprehensive three-part program to address emissions
from diesel locomotive engines and marine diesel engines below 30 liters per cylinder
displacement. First, we are adopting stringent emission standards for existing locomotives
and standards for existing commercial marine diesel engines above 600 kW. These standards
apply when an engine is remanufactured. Second, we are adopting a set of near-term
emission standards, referred to as Tier 3, for newly-built locomotives and marine engines that
reflect the application of technologies to reduce engine-out PM and NOX. Third, we are
adopting longer-term standards, referred to as Tier 4, for newly-built locomotives and marine
engines that utilize high-efficiency catalytic aftertreatment technology enabled by the
availability of Ultra-Low Sulfur Diesel (ULSD). We are also adopting standards to eliminate
emissions from unnecessary locomotive idling. As we developed this final rule, we evaluated
alternative scenarios that looked at the impact of varying the timing and scope of our final
standards.
Table 8-1 gives a brief summary of the alternatives we considered. The first
alternative compares our proposed program to our final program. Alternatives 1 and 2 look at
the effects of eliminating both the remanufacturing programs and the Tier 3 near-term
standards that our final rule includes. Finally, Alternative 4 examines the effects of moving
Tier 4 ahead to 2013 and eliminating both the remanufacturing programs and the Tier 3 near-
term standards.
8-2
-------
Regulatory Alternatives
Table 8-1 Summary of Alternatives and Standards
Final Rule
Alternative 1: Proposed Program from the
Notice of Proposed Rulemaking
Alternative 2: Exclusion of Remanufacturing
Standards
Alternative 3: Elimination of Tier 3
Alternative 4: Tier 4 Exclusively in 2013
Locomotive Remanufacturing
Marine Remanufacturing,
Tier 3 Near-term program,
Tier 4 Long-term standards
Proposed Locomotive Remanufacturing program,
Proposed Tier 3 Near-term program,
Proposed Tier 4 Long-term standards
Tier 3 Near-term program,
Tier 4 Long-term standards
Locomotive Remanufacturing,
Marine Remanufacturing,
Tier 4 Long-term standards
Tier 4 Long-term standards only in 2013
8.1.1 Alternative 1: Proposed Program from the Notice of Proposed Rulemaking
Alternative 1 examines the differences between the program we proposed and the
program we are finalizing in this rulemaking. The final rule makes a number of important
changes to the program originally set out in the proposal which we believe will yield greater
overall NOX and PM reductions, especially in the critical early years of the program. In
particular, the adoption of standards for remanufactured marine engines and a 2-year pull-
ahead of the Tier 4 NOX requirements for line-haul locomotives and for 2000-3700 kW
marine engines provide greater near-term reductions than the proposal. The final rule also
expands the remanufactured locomotive program to include Class II railroads. The analysis of
this alternative illustrates the additional benefits gained through the development process
which resulted in our final program.
8.1.2 Alternative 2: Exclusion of Remanufacturing Standards
Alternative 2 examines the potential impacts of the locomotive and marine
remanufacturing programs by excluding them from the analysis (see sections III.B.(l)(a)(/'),
III.B.(l)(b), and III.B.(2)(b) of our Preamble for more details on the remanufacturing
standards). Alternative 2 is identical to the final program with the exception of the removal of
both the locomotive and marine remanufacturing standards, as the timing and scope of Tier 3
and Tier 4 standards remain unchanged in this alternative. These results can be compared
with the results of the primary program to estimate the benefits that would be lost if we did
not finalize either the locomotive or marine remanufacturing standards.
8.1.3 Alternative 3: Elimination of Tier 3
Alternative 3 eliminates the Tier 3 standards, while retaining the Tier 4 standards and
the combined locomotive and marine remanufacturing requirements. The timing and scope of
8-3
-------
Regulatory Impact Analysis
both the Tier 4 and the locomotive and marine remanufacturing programs would remain
unchanged. These results can be compared with the results of the final program to estimate
the benefits that would be foregone if the near-term standards were not finalized.
8.1.4 Alternative 4: Tier 4 Exclusively in 2013
Alternative 4 most closely reflects the program described in our Advanced Notice of
Proposed Rulemaking (ANPRM), whereby we would set new aftertreatment based emission
standards as soon as possible. In this case, we believe the earliest that such standards could
logically be started is in 2013 (three months after the introduction of 15 ppm ULSD in this
sector). This alternative would eliminate the Tier 3 standards and both the locomotive and
marine remanufacturing standards, while pulling the Tier 4 standards ahead to 2013 for all
portions of the Tier 4 program. These results show the benefits of the comprehensive
program we are finalizing today compared to the aggressive but narrow approach outlined in
our ANPRM.
8.2 Emission Inventory Impacts
8.2.1 Methodology
8.2.1.1 Inventory Impacts
Based on our primary case, we estimated inventory impacts using a methodology
based on engine population, hours of use, average engine loads, and in-use emissions factors
for each alternative. (Refer to Chapter 3 of this RIA for a more complete discussion of how
the primary control inventories were generated). The results are shown in Table 8-2.
8.2.1.2 Costs
We have estimated the costs associated with each alternative using the same methods
employed for the final rule. The cost estimates for the locomotive remanufacturing program
include adjustments for costs associated with hardware requirements. The cost estimates for
the marine remanufacturing program were generated in a similar manner as those generated
for the locomotive remanufacturing program. We have estimated the cost per remanufactured
marine engine as equal to that for a remanufactured locomotive engine because we would
expect a similar or identical remanufacture kit to be used. At this time, for alternative 4 we
are unable to make an accurate estimate of the cost for pulling ahead Tier 4 technologies,
since we do not believe it to be feasible at this time. However, we have reported costs in the
summary table reflecting the same cost estimation aaproach we have used for our final
program and have denoted unestimated additional costs as 'C'. These additional unestimated
costs would include costs for additional engine test cells, engineering staff, and engineering
facilities necessary to accelerate the development of Tier 4. The details of our estimated
remanufacturing program costs can be found in Chapter 5 of this RIA. The results are shown
in Table 8-2.
8-4
-------
Regulatory Alternatives
8.2.1.3 Benefits
To estimate the PM-related monetized benefits for each of the alternative scenarios,
we used a benefits transfer approach to scale the PM benefits from the final Locomotive and
Marine Engine control scenario. The PM benefits scaling approach is similar to the scaling
approach conducted for the Clean Air Nonroad Diesel (CAND) Rule (see Chapter 9 of the
CAND RIA). For the estimate of benefits generated for the final rule, we ran a sophisticated
photochemical air quality model, the Community Multiscale Air Quality model (CMAQ), to
estimate baseline and post-control ambient concentrations of PM for 2030. Benefits for the
final standards were then generated using the inputs and methods described in Chapter 6 of
the RIA for this rule. We then scaled these PM benefits to reflect the magnitude of the PM2 5
precursor emissions changes estimated to occur as a result of the alternative control scenarios.
The results are shown in Table 8-2.
8.2.2 Analysis
Table 8-2 includes the expected yearly emission reductions associated with each
alternative, including: the estimated PM and NOX reductions for years 2006-2040 expressed as
a net present value (NPV) using discounting rates of 3% and 7%. The yearly estimated costs
are also expressed in this table at both 3% and 7% NPV. The benefit analysis from 2020 and
the analysis from 2030 are also included on this table. For further analysis, Table 8-3 and
Table 8-4 summarize the PM and NOX emission reductions and costs for each alternative
through 2040; and Table 8-5 and Table 8-6 summarize the emission reductions, costs and
benefits for the year 2020 and the year 2030. Figure 8.2-1 and Figure 8.2-2 illustrate the
inventory impacts of each alternative from 2006-2040 for comparison.
3-5
-------
Regulatory Impact Analysis
Table 8-2 Inventory, Cost, and Benefits year from 2006-2040
Calendar
Year
2006
2007
2008
2009
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%
Final Program
PM2.5
Emissions
Reductions
(tons)
0
0
320
930
1,700
2,800
4,200
5,200
6,300
7,300
8,900
11,000
12,000
13,000
14,000
16,000
17,000
18,000
19,000
21,000
22,000
23,000
24,000
25,000
27,000
28,000
29,000
30,000
31,000
32,000
33,000
34,000
35,000
36,000
37,000
308,000
134,000
NOX
Emissions
Reductions
(tons)
0
0
14,000
24,000
44,000
70,000
87,000
110,000
130,000
160,000
210,000
250,000
290,000
330,000
370,000
410,000
450,000
490,000
540,000
580,000
620,000
670,000
710,000
750,000
790,000
830,000
870,000
910,000
950,000
990,000
1,000,000
1,100,000
1,100,000
1,100,000
1,100,000
8,760,000
3,710,000
Total
Costs
(Millions)
$0
$30
$110
$90
$150
$280
$220
$210
$200
$270
$290
$290
$310
$340
$350
$380
$440
$520
$550
$590
$610
$640
$690
$730
$760
$790
$810
$900
$930
$970
$990
$1,000
$1,000
$1,100
$1,100
$9,410
$4,310
PM-only
Benefits a'b
(Billions)
3% I! 7%
$3.9
$9.2
$3.6
$8.4
Alternative 1: Proposed Program from Notice of
Proposed Rulemaking
PM15
Emissions
Reductions
(tons)
0
0
60
390
840
1,700
2,700
3,300
4,300
5,300
6,900
8,600
10,000
11,000
13,000
14,000
15,000
17,000
18,000
20,000
21,000
22,000
23,000
25,000
26,000
27,000
28,000
29,000
31,000
32,000
33,000
34,000
35,000
36,000
36,000
286,000
121,000
NOX
Emissions
Reductions
(tons)
0
0
5,100
7,300
20,000
39,000
51,000
65,000
82,000
95,000
120,000
180,000
220,000
260,000
310,000
350,000
390,000
460,000
520,000
570,000
610,000
660,000
700,000
740,000
780,000
820,000
860,000
900,000
940,000
980,000
1,000,000
1,100,000
1,100,000
1,100,000
1,100,000
8,140,000
3,320,000
Total
Costs
(Millions)
$0
$30
$90
$70
$110
$230
$170
$160
$160
$200
$220
$240
$270
$290
$300
$330
$390
$470
$500
$570
$590
$630
$680
$710
$750
$780
$800
$890
$930
$960
$980
$1,000
$1,000
$1,100
$1,100
$8,760
$3,900
PM-only
Benefits8'11
(Billions)
3%
$3.3
$8.8
7%
$3.0
$8.0
a Note that the range of PM-related benefits reflects the use of an empirically-derived estimate of PM mortality benefits, based on
the ACS cohort study (Pope et al., 2002) and the extension of the Harvard Six-Cities study (Laden et al. 2006).
b 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 (US EPA, 2000
and OMB, 2003).U.S. Environmental Protection Agency, 2000. Guidelines for Preparing Economic Analyses.
http://vosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html.
-------
Regulatory Alternatives
2006
2007
2008
2009
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%
Alternative 2: Exclusion of Remanufacturing
Standards
PM15
Emissions
Reductions
(tons)
0
0
60
90
110
140
440
840
1,500
2,400
3,500
4,800
6,100
7,500
8,800
10,000
12,000
13,000
15,000
16,000
18,000
19,000
21,000
22,000
24,000
25,000
26,000
28,000
29,000
30,000
32,000
33,000
34,000
35,000
36,000
240,000
96,000
NOX
Emissions
Reductions
(tons)
0
0
600
2,600
4,400
6,500
9,800
14,000
31,000
65,000
100,000
150,000
190,000
240,000
280,000
330,000
370,000
420,000
470,000
520,000
570,000
620,000
670,000
720,000
760,000
810,000
850,000
890,000
930,000
970,000
1,000,000
1,000,000
1,100,000
1,100,000
1,100,000
7,640,000
3,030,000
Total
Costs
(Millions)
$0
$30
$30
$30
$70
$140
$80
$80
$100
$180
$180
$190
$210
$250
$290
$320
$360
$450
$490
$530
$570
$610
$650
$690
$720
$760
$790
$880
$920
$950
$980
$1,000
$1,000
$1,100
$1,100
$8,080
$3,430
PM-only
Benefits8'11
(Billions)
3%
$2.5
$8.2
7%
$2.3
$7.5
Alternative 3: Elimination of Tier 3
PM2.5 Emissions
Reductions
(tons)
0
0
320
930
1,700
2,800
3,700
3,600
3,500
3,800
4,800
6,000
6,900
7,700
8,800
9,900
11,000
12,000
14,000
15,000
16,000
17,000
19,000
20,000
21,000
23,000
24,000
25,000
26,000
28,000
29,000
30,000
31,000
32,000
33,000
237,000
100,000
NOX Emissions
Reductions
(tons)
0
0
14,000
24,000
44,000
70,000
85,000
100,000
120,000
150,000
190,000
230,000
270,000
310,000
350,000
380,000
420,000
460,000
510,000
550,000
590,000
640,000
680,000
720,000
760,000
800,000
840,000
880,000
920,000
950,000
990,000
1,000,000
1,100,000
1,100,000
1,100,000
8,360,000
3,530,000
Total
Costs
(Millions)
$0
$0
$80
$50
$120
$220
$220
$210
$200
$270
$290
$290
$310
$340
$350
$380
$440
$520
$550
$590
$610
$640
$690
$730
$760
$790
$810
$900
$930
$970
$990
$1,000
$1,000
$1,100
$1,100
$9,240
$4,160
PM-only
Benefits''11
(Billions)
3%
$2.8
$7.8
7%
$2.6
$7.1
aNote that the range of PM-related benefits reflects the use of an empirically-derived estimate of PM mortality benefits, based on the ACS
cohort study (Pope et al., 2002) and the extension of the Harvard Six-Cities study (Laden et al. 2006).
b 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 (US EPA, 2000 and OMB,
2003).U.S. Environmental Protection Agency, 2000. Guidelines for Preparing Economic Analyses.
http://vosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html.
3-7
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Regulatory Impact Analysis
Alternative 4: Tier 4 Exclusively in 2013
2006
2007
2008
2009
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%
PM2.5
Emissions
Reductions
(tons)
0
0
60
90
120
150
200
1,500
2,600
3,800
5,000
6,300
7,500
8,800
10,000
11,000
13,000
14,000
16,000
17,000
18,000
20,000
21,000
22,000
24,000
25,000
26,000
28,000
29,000
30,000
31,000
32,000
33,000
34,000
34,000
249,000
101,000
NOX
Emissions
Reductions
(tons)
0
0
600
2,600
4,400
6,300
8,700
51,000
93,000
140,000
180,000
220,000
270,000
310,000
350,000
400,000
440,000
490,000
530,000
580,000
620,000
660,000
710,000
750,000
790,000
830,000
870,000
900,000
940,000
980,000
1,000,000
1,000,000
1,100,000
1,100,000
1,100,000
8,320,000
3,420,000
Total Costs8
(Millions)
$0
$0
$80
(hon
4>oU
oU
$80
$120
$140
$170
$180
$210
$250
$280
$320
$360
$450
$490
$530
$570
$610
$640
$680
$710
$750
$780
$810
$850
$940
$970
$1,000
$1,000
$1,000
$1,100
$1,100
$1,100
$9,070 + C
$3,950 + C
PM-only
Benefits'1'0
(Billions)
3% || 7%
$3.0
$8.4
$2.8
$7.6
a The 'C' represents the additional costs necessary to accelerate the introduction of Tier 4 technologies that
we are unable to estimate at this time, such additional engine test cells, engineering staff, and engineering
facilites necessary to introduce Tier 4 one year earlier.
b Note that the range of PM-related benefits reflects the use of an empirically-derived estimate of PM
mortality benefits, based on the ACS cohort study (Pope et al, 2002) and the extension of the Harvard Six-
Cities study (Laden et al. 2006).
0 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 (US EPA, 2000 and OMB, 2003).U.S. Environmental Protection Agency,
2000. Guidelines for Preparing Economic Analyses.
http: //yosemite. epa. gov/ee/epa/eed.nsf/webpages/Guidelines.html.
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Regulatory Alternatives
Table 8-3 Summary of Total Inventory and Costs Through 2040 NPV 3%
Program
Final Program
Alternative 1 : Proposed Program from
Notice of Proposed Rulemaking
Alternative 2: Exclusion of
Remanufacturing Standards
Alternative 3: Elimination of Tier 3
Alternative 4: Tier 4 Exclusively in
2013
PM Emissions
Redcutions (tons)
2006-2040
NPV 3%
308,000
286,000
240,000
237,000
249,000
NOX Emissions
Reductions
(tons) 2006-
2040
NPV 3%
8,760,000
8,140,000
7,640,000
8,360,000
8,320,000
Total Costs8
(Millions)
2006-2040
NPV 3%
$9,410
$8,760
$8,080
$9,240
$9,070 + C
'C' represents additional costs necessary to accelerate the introduction of Tier 4 technologies that we are unable
to estimate at this time.
Table 8-4 Summary of Total Inventory and Costs Through 2040 NPV 7%
Program
Final Program
Alternative 1 : Proposed Program from
Notice of Proposed Rulemaking
Alternative 2: Exclusion of
Remanufacturing Standards
Alternative 3: Elimination of Tier 3
Alternative 4: Tier 4 Exclusively in
2013
PM Emissions
Redcutions (tons)
2006-2040
NPV 7%
134,000
121,000
96,000
100,000
101,000
NOX Emissions
Reductions
(tons) 2006-
2040
NPV 7%
3,710,000
3,320,000
3,030,000
3,530,000
3,420,000
Total Costs8
(Millions)
2006-2040
NPV 7%
$4,310
$3,900
$3,430
$4,160
$3,950 + C
'C' represents additional costs necessary to accelerate the introduction of Tier 4 technologies that we are unable
to estimate at this time.
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Regulatory Impact Analysis
Table 8-5 Summary of Inventory, Costs, and Benefits for 2020
Program
Final Program
Alternative 1 : Proposed Program
from Notice of Proposed Rulemaking
Alternative 2: Exclusion of
Remanufacturing Standards
Alternative 3: Elimination of Tier 3
Alternative 4: Tier 4 Exclusively in
2013
2020 PM
Emissions
Reductions
(tons)
14,000
13,000
8,800
8,800
10,000
2020 NOX
Emissions
Reductions
(tons)
370,000
310,000
280,000
350,000
350,000
2020 Total
Costs8
(Millions)
$350
$300
$290
$350
$360 + C
2020 Benefits'10
(Billions) PM
only
3%
$3.9
$3.3
$2.5
$2.8
$3.0
7%
($3.6)
($3.0)
($2.3)
($2.6)
($2.8)
a The 'C' represents the additional costs necessary to accelerate the introduction of Tier 4 technologies that we are
unable to estimate at this time, such additional engine test cells, engineering staff, and engineering facilites necessary
to introduce Tier 4 one year earlier.
b Note that the range of PM-related benefits reflects the use of an empirically-derived estimate of PM mortality
benefits, based on the ACS cohort study (Pope et al., 2002) and the extension of the Harvard Six-Cities study (Laden
et al. 2006).
0 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 (US EPA, 2000 and OMB, 2003).U.S. Environmental Protection Agency, 2000. Guidelines for
Preparing Economic Analyses. http://vosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html.
Table 8-6 Summary of Inventory, Costs, and Benefits for 2030
Program
Final Program
Alternative 1 : Proposed Program from
Notice of Proposed Rulemaking
Alternative 2: Exclusion of
Remanufacturing Standards
Alternative 3: Elimination of Tier 3
Alternative 4: Tier 4 Exclusively in
2013
2030 PM
Emissions
Reductions
(tons)
27,000
26,000
24,000
21,000
24,000
2030 NOX
Emissions
Reductions
(tons)
790,000
780,000
760,000
760,000
790,000
2030 Total
Costs8
(Millions)
$760
$750
$720
$760
$780 + C
2030 Benefits"0
(Billions)
PM only
3% (7%)
3%
$9.2
$8.8
$8.2
$7.8
$8.4
7%
$8.4
$8.0
$7.5
$7.1
$7.6
a The 'C' represents the additional costs necessary to accelerate the introduction of Tier 4 technologies that we are
unable to estimate at this time, such additional engine test cells, engineering staff, and engineering facilites necessary
to introduce Tier 4 one year earlier.
b Note that the range of PM-related benefits reflects the use of an empirically-derived estimate of PM mortality
benefits, based on the ACS cohort study (Pope et al., 2002) and the extension of the Harvard Six-Cities study (Laden
et al. 2006).
0 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 (US EPA, 2000 and OMB, 2003).U.S. Environmental Protection Agency, 2000. Guidelines for
Preparing Economic Analyses. http://vosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html.
8-10
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Regulatory Alternatives
Figure 8.2-1 PM2S Inventories for 2006-2040
63 -
Base
A1: Proposed Program from Notice of Proposed Rulemaking
A2: Exclusion of Remanufacturing Standards
A3: Elimination of TierS
A4: Tier 4 Exclusivelyin 2013
Final Program
2006
2011
2016
2021
2026
2031
2036
8-11
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Regulatory Impact Analysis
Figure 8.2-2 NOX Inventories for 2006-2040
1,900 -
1,725 -
3 1,550 -
o
? 1,375
in
| 1,200 -
3
O
i. 1,025 H
X
O
2 850 -
675 -
500
Base
A1: Proposed Program from Notice of Proposed Rulemaking
A2: Exclusion of Remanufacturing Standards
A3: Elimination of TierS
A4: Tier 4 Exclusively in 2013
Final Program
2006
2011
2016
2021
2026
2031
2036
8-12
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Regulatory Alternatives
8.3 Summary of Results
8.3.1 Alternative 1: Proposed Program from the Notice of Proposed Rulemaking
Table 8-2 shows the changes in inventory that arise from comparing our proposal to
our final rulemaking. As a stand-alone program, through the year 2040 Alternative 1 provides
PM2.5 reductions of 286,000 tons NPV 3%, or 121,000 tons NPV 7%, and NOX reductions of
8,140,000 tons NPV 3%, or 3,320,000 tons NPV 7%. The cost of this alternative through
2040 is estimated to be $8,760 million NPV 3%, or $3,900 million NPV 7%. In 2020, this
alternative provides monetized health and welfare benefits of $3.3 billion at a 3% discount
rate, or $3.0 billion at a 7% discount rate, and $8.8 billion in 2030 at a 3% discount rate or
$8.0 billion at a 7% discount rate. Through 2040 our final program provides additional PM2.5
reductions of 22,000 tons NPV 3%, or 13,000 tons NPV 7%, and additional NOX reductions
of 620,000 tons NPV 3%, or 390,000 tons NPV 7%. Through 2040, the additional costs of
our final program will be $650 million NPV 3%, or $410 million NPV 7%. The additional
PM2.5 monetized health and welfare benefits in 2020 of our final program are $0.6 billion at a
3% discount rate, or $0.6 billion at a 7% discount rate, while in 2030 the additional monetized
health and welfare benefits total $0.4 billion at a 3% discount rate, or $0.4 billion at a 7%
discount rate. Figures 8.1 and Figure 8.2 show the increase in emission reductions that our
final program provides over our proposed program. The decrease in PM2.5 inventory of our
final program as compared to the proposed program is almost immediate; the decrease in NOX
inventory is also greatest in the near-term as compared to our proposed program. Figure 8.1
and Figure 8.2 demonstrate that the changes made to the proposed program result in a final
program that provides greater overall NOX and PM reductions in the critical early years of the
program.
8.3.2 Alternative 2: Exclusion of Remanufacturing Standards
Our analysis of this alternative shows the valuable emission reductions and health and
welfare benefits that the locomotive and marine remanufacturing standards provide. The
locomotive and marine remanufacturing programs provide inventory impacts and benefits
both in the near-term and the long-term. As a stand-alone program, Alternative 2 provides
PM2.5 reductions of 240,000 tons NPV 3%, or 96,000 tons NPV 7%, and NOX reductions of
7,640,000 tons NPV 3%, or 3,030,000 tons NPV 7% through the year 2040. The cost of this
alternative through 2040 is estimated to be $8,080 million NPV 3%, or $3,430 million NPV
7%. In 2020, this alternative provides monetized health and welfare benefits of $2.5 billion at
a 3% discount rate, or $2.3 billion at a 7% discount rate, and $8.2 billion in 2030 at a 3%
discount rate, or $7.5 billion at a 7% discount rate. Compared to the final program, our
analysis shows that by 2040 eliminating the locomotive and marine remanufacture programs
lessen PM2.5 emission reductions by 68,000 tons NPV 3%, or 38,000 tons NPV 7%, and NOX
emission reductions by nearly 1,120,000 tons NPV 3% or 680,000 tons NPV 7%. The cost of
this alternative, as compared to our final program through 2040, is estimated to be $1,330
million less than our proposal at NPV 3%, or $880 million less at NPV 7%. Compared to our
final program, eliminating the locomotive and marine remanufacture programs reduce the
monetized health and welfare benefits by $1.4 billion at a 3% discount rate, or $1.3 billion at
a 7% discount rate in 2020, and $1.0 billion at a 3% discount rate, or $0.9 billion at a 7%
discount rate in 2030. Figure 8.1 shows that the remanufacturing programs provide PM2.5
8-13
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Regulatory Impact Analysis
emission reductions throughout the entire length of the program. Eliminating the locomotive
and marine remanufacturing programs would also reduce the NOX emission benefits that our
final program provides. Figure 8.2-2 shows the loss of early NOX benefits that this alternative
would result in as compared to our final program. This alternative shows that when our final
program includes the locomotive and marine remanufacture programs it provides significant
additional emission reductions, and over one-third more health and welfare benefits in 2020
alone.
8.3.3 Alternative 3: Elimination of Tier 3
Alternative 3 eliminates the Tier 3 standards, while retaining Tier 4 and the combined
locomotive and marine remanufacturing requirements. This alternative allows us to consider
the value of combining the Tier 4 standards with the locomotive and marine remanufacturing
standards together as one program, and conversely, allows us to see the additional benefits
gained when combining them with the Tier 3 standards. Although the remanufacturing
programs provide significant benefits in the near-term, as evidenced by the analysis of
Alternative 2, it is clear that Tier 3 also plays an important role in providing both near-term
and long-term emission reductions. As a stand-alone program, Alternative 3 provides PM2.5
reductions of 237,000 tons NPV 3%, or 100,000 tons NPV 7%, and NOX reductions of
8,360,000 tons NPV 3%, or 3,530,000 tons NPV 7% through the year 2040. The cost of this
alternative through 2040 is estimated to be $9,240 million NPV 3%, or $4,160 million NPV
7%. In 2020, this alternative provides monetized health and welfare benefits of $2.8 billion at
a 3% discount rate, or $2.6 billion at a 7% discount rate and $7.8 billion in 2030 at a 3%
discount rate, or $7.1 billion at a 7% discount rate. Comparing this alternative to our final
program allows us to consider the value of the Tier 3 standards on their own merits.
Specifically, this alternative would lessen PM2.5 emissions reductions by nearly 71,000 tons
NPV 3%, or 34,000 tons NPV 7%, and NOX emissions by 400,000 tons NPV 3 %, or 180,000
tons NPV 7%. The cost of this alternative, as compared to our final program through 2040, is
estimated to be $170 million less at NPV 3%, or $150 million less at NPV 7%. The
monetized health and welfare benefits that would be forgone by eliminating Tier 3 are $1.1
billion at a 3% discount rate, or $1.0 billion at a 7% discount rate in 2020, and $1.4 billion at
a 3% discount rate, or $1.3 billion at a 7% discount rate in 2030. Figure 8.2-1 shows the
decrease in PM2.5 emission reductions that this alternative results in. Figure 8.2-2 shows that
this alternative also provides decreased long-term NOX reductions. This alternative shows that
by eliminating Tier 3 from our final program, we would lose almost one-quarter of the total
PM emissions reductions and over one-quarter of the PM health and welfare benefits in 2020
alone. As these alternatives show, each element of our comprehensive program: the
locomotive and marine remanufacturing programs, the Tier 3 emission standards, and the Tier
4 emission standards, represents a valuable emission control program on its own, while the
collective program results in the greatest emission reductions we believe to be possible giving
consideration to all of the elements described in our final rule.
8.3.4 Alternative 4: Tier 4 Exclusively in 2013
Alternative 4 eliminates the Tier 3 standards along with the locomotive and marine
remanufacturing standards, while pulling the Tier 4 standards ahead to 2013 for all portions of
the Tier 4 program. As stated in our NPRM, we are concerned that it may not be feasible to
8-14
-------
Regulatory Alternatives
introduce Tier 4 technologies on locomotive and marine diesel engines earlier than the
proposal specifies. We have used the same cost estimation approach for this alternative as
that of our final program, however, we are unable to make an accurate estimate of the cost for
such an approach since we do not believe it to be technologically feasible at this time.
Therefore, we have denoted the unestimated costs that are necessary to accelerate the
development of Tier 4 technologies with a 'C' in the summary tables. These additional
unestimated costs would include costs for additional engine test cells, engineering staff, and
engineering facilities necessary to introduce Tier 4 one year earlier. As a stand-alone
program, Alternative 4 provides PM2.5 reductions of 249,000 tons NPV 3%, or 101,000 tons
NPV 7%, and NOX reductions of 8,320,000 tons NPV 3%, or 3,420,000 tons NPV 7% through
the year 2040. In 2020, this alternative provides monetized health and welfare benefits of
$3.0 billion at a 3% discount rate, or $2.8 billion at a 7% discount rate, and $8.4 billion in
2030 at a 3% discount rate, or $7.6 billion at a 7% discount rate. Through 2040, this
alternative, as compared to our final program, would decrease PM2 5 reductions by more than
59,000 tons NPV 3%, or 33,000 tons NPV 7%, and NOX emissions by 440,000 tons NPV 3%,
or 290,000 tons NPV 7%. Compared to our final program, the reduction in monetized health
and welfare benefits of this alternative are $0.9 billion at a 3% discount rate or $0.8 billion at
a 7% discount rate in 2020, while in 2030 the reductions in monetized benefits are $0.8 billion
at a 3% discount rate, or $0.8 billion at a 7% discount rate. This alternative shows that in
addition to the technical challenges necessary to introduce Tier 4 technologies, it would
actually result in higher PM2.5 and NOX emissions and lower health and welfare benefits than
our final program.
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Regulatory Impact Analysis
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