*>EPA
United States
Environmental Protection
Agency
METHODOLOGIES FOR ESTIMATING PORT-RELATED
AND GOODS MOVEMENT MOBILE SOURCE
EMISSION INVENTORIES , ¦
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|| ill I
Office of Transportation Air Quality
EPA-420-D-20-001
February 2020
DRAFT
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Note:
This is a public draft document. This draft describes the latest, state-of-the-science methodologies for
preparing a port-related and/or goods movement emissions inventory for the following mobile source
sectors: ocean-going vessels, harbor craft, recreational marine, cargo handling equipment, onroad
vehicles, and rail. The U.S. Environmental Protection Agency is seeking feedback on this public draft
through March 31, 2020. To submit comments and feedback on this draft document, please email them
to talkaboutports@epa.gov.
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U.S. Environmental Protection Agency 2020 Public Draft
Table of Contents
List of Abbreviations vim
1 Introduction 1
1.1 Purpose 1
1.2 Background 2
1.3 Importance of Port-related Emission Inventories 2
1.4 Organization of This Document 3
1.5 Additional Information 4
2 Planning a Port-Related Emissions Inventory 5
2.1 Overview 5
2.2 Purposes of the Inventory 5
2.3 General Inventory Approaches 6
2.4 Mobile Source Sectors 8
2.4.1 Ocean-Going Vessels 8
2.4.2 Harbor Craft 8
2.4.3 Recreational Marine Vessels 8
2.4.4 Cargo Handling Equipment 8
2.4.5 Onroad Vehicles 9
2.4.6 Rail 9
2.5 Pollutants of Concern 9
2.6 Geographical Domain 10
2.6.1 Marine Boundary 11
2.6.2 Land-side Boundary 11
2.6.3 Determining Geographical Scope 11
2.7 Time Domains and Future Inventories 13
3 Ocean-Going Vessels 15
3.1 Source Description 15
3.2 Emissions Estimation Overview 16
3.3 Vessel Characteristics 17
3.3.1 Vessel Identification 17
3.3.2 Engine Characteristics 18
3.3.2.1 Engine Category 18
3.3.2.2 Engine Type 19
3.3.3 Ship Type and Subtype 19
3.3.4 Engine Operating Power 21
3.3.5 Filling Gaps in Vessel Characteristic Data Sets 22
3.4 Vessel Activity Data Sources 23
3.4.1 Automatic Identification System 23
3.4.2 Local Logs 24
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3.4.3 Survey Data 24
3.4.4 Entrances and Clearances 24
3.4.5 Waterborne Commerce 25
3.5 Emission Factors 25
3.5.1 Nitrogen Oxides (NOx) 26
3.5.2 Brake Specific Fuel Consumption (BSFC) 27
3.5.3 Particulate Matter (PM), Diesel Particulate Matter (DPM), and Black Carbon (BC) 28
3.5.4 Volatile Organic Compounds (VOC), Carbon Monoxide (CO), and Methane (CH4) 29
3.5.5 Nitrous Oxide (N20) 29
3.5.6 Carbon Dioxide (C02) 30
3.5.7 Sulfur Dioxide (S02) 30
3.6 Auxiliary Engine and Boiler Loads by Operating Mode 31
3.6.1 Transit 31
3.6.2 Maneuvering 31
3.6.3 Restricted Speed Zone 31
3.6.4 Hotelling 31
3.6.5 Anchorage 32
3.7 Low Load Adjustment Factors 32
3.8 AIS Inventory Calculations 33
3.8.1 Link Each AIS Record to Vessel Characteristic Data 33
3.8.2 Clean AIS Data 33
3.8.3 Fill Temporal Gaps in AIS Activity 34
3.8.4 Calculate Propulsion Engine Operating Power and Load Factor 34
3.8.5 Assign Operating Mode 36
3.8.6 Calculate Propulsion Engine Emissions 36
3.8.7 Calculate Auxiliary Engine and Boiler Emissions 37
3.8.8 Aggregate Emissions 37
3.8.9 Perform Quality Control Checks 38
3.9 Alternative Inventory Calculations 39
3.9.1 Link Each Vessel Call Record to Vessel Characteristic Data 39
3.9.2 Calculate Activity by Operating Mode 40
3.9.2.1 Transit 40
3.9.2.2 Restricted Speed Zone 41
3.9.2.3 Maneuvering 41
3.9.2.4 Hotelling 42
3.9.2.5 Anchorage 42
3.9.3 Calculate Propulsion Engine Operating Power and Emissions 42
3.9.3.1 Propulsion Engine Operating Power 42
3.9.3.2 Calculating Load Factor and Determining Low Load Adjustment Factor 43
3.9.3.3 Calculating Propulsion Engine Emissions 43
3.9.4 Calculate Auxiliary and Boiler Emissions 43
3.9.5 Aggregate Emissions 44
3.9.6 Perform Quality Control Checks 44
3.10 Projecting Future Emission Inventories 45
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4 Harbor Craft 47
4.1 Source Description 47
4.2 Emissions Estimation Overview 48
4.3 Vessel Characteristics 49
4.3.1 Vessel Identification 49
4.3.2 Engine Characteristics 50
4.3.3 Ship Type 51
4.3.4 Filling Gaps in Vessel Characteristic Data Sets 51
4.4 Vessel Activity Data Sources 51
4.4.1 Survey Data 51
4.4.2 Automatic Identification System 52
4.4.3 Other Vessel Activity Data Sources 53
4.5 Emission Factors 53
4.5.1 Nitrogen Oxides (NOx) 53
4.5.2 Brake Specific Fuel Consumption (BSFC) 54
4.5.3 Particulate Matter (PM), Diesel Particulate Matter (DPM), and Black Carbon (BC) 54
4.5.4 Volatile Organic Compounds (VOC), Carbon Monoxide (CO), and Methane (CH4) 54
4.5.5 Nitrous Oxide (N20) 54
4.5.6 Carbon Dioxide (C02) 55
4.5.7 Sulfur Dioxide (S02) 55
4.6 Load Factors 55
4.7 AIS Inventory Calculations 56
4.7.1 Link Each AIS Record to Vessel Characteristic Data 57
4.7.2 Clean AIS Data 57
4.7.3 Fill Temporal Gaps in AIS Activity 57
4.7.4 Assign Operating Mode and Calculate Emissions 58
4.7.5 Aggregate and/or Allocate Emissions 59
4.7.6 Perform Quality Control Checks 59
4.8 Alternative Inventory Calculations 60
4.8.1 Link Each Vessel to Vessel Characteristic Data 60
4.8.2 Assign Load Factors, Emission Factors, and Operating Hours 60
4.8.3 Calculate Vessel Emissions 61
4.8.4 Aggregate and/or Allocate Emissions 61
4.8.5 Perform Quality Control Checks 61
4.9 Projecting Future Emission Inventories 62
5 Recreational Marine 64
5.1 Source Description 64
5.2 Emissions Estimation Overview 64
5.3 Vessel Characteristics 65
5.3.1 Vessel Type and Fuel Type 66
5.3.2 Engine Model Year 66
5.3.3 Rated Engine Power 67
5.4 Vessel Activity 68
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5.5 Emission Factors 69
5.5.1 Running MOVES-Nonroad 69
5.5.2 Nitrous Oxide (N20) 70
5.5.3 Black Carbon (BC) 71
5.6 AIS Inventory Calculations 71
5.6.1 Assign Each Vessel the Appropriate Vessel Characteristics and Emission Factors 71
5.6.2 Clean AIS Data 72
5.6.3 Fill Temporal Gaps in AIS Activity 72
5.6.4 Calculate Vessel Activity and Emissions 72
5.6.5 Aggregate and/or Allocate Emissions 73
5.6.6 Perform Quality Control Checks 73
5.7 Alternative Inventory Calculations 74
5.7.1 Missing Model Year Data 75
5.7.2 Missing Hours of Use and/or Engine Power Data 75
5.7.3 Missing Vessel Count Data 75
5.8 Projecting Future Emission Inventories 76
5.8.1 Determine Projected Activity 76
5.8.2 Determine Projected Emission Factors 77
5.8.3 Calculate the Future Inventory 77
6 Cargo Handling Equipment 78
6.1 Source Description 78
6.2 Emissions Estimation Overview 79
6.3 Equipment Characteristics 80
6.3.1 Equipment Type and Fuel Type 80
6.3.2 Engine Model Year 82
6.3.3 Rated Engine Power 83
6.3.4 Equipment Retrofit and Replacement Projects 84
6.4 Equipment Activity 84
6.5 Emission Factors 85
6.5.1 Running MOVES-Nonroad 85
6.5.2 Nitrous Oxide (N20) 87
6.5.3 Black Carbon (BC) 87
6.6 Detailed Inventory Calculations 88
6.6.1 Calculating an Emissions Inventory Per Unit 88
6.6.2 Aggregating Per Unit Emissions 88
6.6.3 Perform Quality Control Checks 89
6.7 Alternative Inventory Calculations 89
6.7.1 Missing Model Year Data 89
6.7.2 Missing Equipment Hours of Use and/or Engine Power Data 90
6.8 Projecting Future Emission Inventories 90
7 Onroad Vehicles 92
7.1 Source Description 92
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7.2 Overview of Approaches and Considerations for Developing an Onroad Vehicle Emissions
Inventory 92
7.2.1 Inventory Purpose and Other Considerations 93
7.2.2 Geographical Scope 94
7.3 Overview of MOVES 95
7.3.1 Scale and Calculation Type 95
7.3.2 Pollutants and Processes 96
7.4 Port-Related Onroad Vehicle Inventory Data Needs 96
7.4.1 Fleet Characteristics 97
7.4.1.1 Vehicle Types 97
7.4.1.2 Vehicle Counts 99
7.4.1.3 Age Distribution 99
7.4.1.4 Vehicle Retrofits and Replacements 100
7.4.2 Vehicle Activity 100
7.4.2.1 Running Activity 100
7.4.2.2 Vehicles Parked and Starts 101
7.5 County Scale Approach for Developing an Onroad Vehicle Inventory 102
7.5.1 Setting up a County Scale RunSpec for a Port 103
7.5.2 Using the County Data Manager to Enter Port-Specific Data 104
7.5.2.1 Meteorology Data 104
7.5.2.2 Source Type Population 104
7.5.2.3 Age Distribution 104
7.5.2.4 Vehicle Miles Traveled (VMT) 105
7.5.2.5 Hotelling 105
7.5.2.6 Fuel 105
7.5.2.7 Inspection and Maintenance (l/M) 106
7.5.2.8 Retrofit and Replacement Data 106
7.5.2.9 Road Type Distribution 106
7.5.2.10 Average Speed Distribution 106
7.5.2.11 Starts 106
7.5.2.12 Running MOVES 107
7.6 Project Scale Approach for Developing an Onroad Vehicle Emissions Inventory 107
7.6.1 Major Considerations for the Project Scale Approach 108
7.6.1.1 Number of Links 108
7.6.1.2 Number of Runs 108
7.6.1.3 Pollutants and Processes to Include 109
7.6.2 Project Scale Generic Link Approach 109
7.6.3 Creating a Run Specification for the Generic Link Approach 110
7.6.4 Using the Project Data Manager for the Generic Link Approach Ill
7.6.4.1 Meteorology Data Ill
7.6.4.2 Age Distribution Ill
7.6.4.3 Fuel 112
7.6.4.4 Inspection and Maintenance (l/M) 112
7.6.4.5 Retrofit Data 113
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7.6.4.6 Links 113
7.6.5 Post-Processing Project Scale Output for Inventory Development 115
7.7 Projecting Future Emission Inventories 115
8 Rail 117
8.1 Source Description 117
8.2 Emissions Estimation Overview 118
8.3 Locomotive Characteristics 118
8.4 Locomotive Activity 119
8.4.1 Activity Based on Fuel Consumption 119
8.4.2 Activity Based on Number of Trains 120
8.4.3 Activity Based on Gross Ton-miles 121
8.5 Emission Factors 121
8.5.1 Diesel 121
8.5.1.1 Nitrogen Oxides (NOx), Particulate Matter (PM), Black Carbon (BC), Volatile Organic
Compounds (VOC), and Carbon Monoxide (CO) 121
8.5.1.2 Brake Specific Fuel Consumption (BSFC) 122
8.5.1.3 Carbon Dioxide (C02) 123
8.5.1.4 Methane (CH4) 123
8.5.1.5 Nitrous Oxide (N20) 123
8.5.1.6 Sulfur Dioxide (S02) 123
8.5.2 LNG and LNG/Diesel Dual Fuel 124
8.6 Inventory Calculations 124
8.7 Alternative Methodologies 125
8.7.1 Activity Calculations 125
8.7.1.1 Activity Based on Number of Trains 125
8.7.1.2 Activity Based on Gross Ton-miles 126
8.7.1.3 Switcher Locomotive Hours 126
8.7.2 Fleet Average Emission Factors 127
8.8 Projecting Future Emission Inventories 129
9 References 131
Appendix A Estimating Port-Related Energy Consumption 136
A.l Ocean-Going Vessels 136
A.l.l AIS Inventory Methodology 136
A.l.2 Alternative Inventory Methodology 137
A.2 Harbor Craft 138
A.2.1 AIS Inventory Methodology 138
A.2.2 Alternative Inventory Methodology 139
A.3 Recreational Marine 140
A.3.1 AIS Inventory Methodology 140
A.3.2 Alternative Inventory Methodology 140
A.4 Cargo Handling Equipment 141
A.5 Onroad Vehicles 141
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A.6 Rail 141
Appendix B Determining CI and C2 EngineTiers 142
Appendix C Filling Gaps in Vessel Characteristics for OGV 144
C.l Average Installed Propulsion Power, Service Speed, and Maximum Draft 144
C.2 Average Differences Between Keel-laid Year and Build Year 157
Appendix D HAP Speciation Profiles for Commercial Marine Engines 159
Appendix E Default OGV Auxiliary Engine and Boiler Loads 161
Appendix F OGV Sulfur Dioxide Low Load Adjustment Factors 165
Appendix G Default Harbor Craft Vessel Characteristics and Activity 166
Appendix H Tables of CI and C2 Emission Factors 168
H.l Nitrogen Oxides (NOx) 168
H.2 Particulate Matter (PM), Diesel Particulate Matter (DPM), and Black Carbon (BC) 172
H.2.1 ULSD 172
H.2.2 Other Diesel Fuels 177
H.3 Volatile Organic Compounds (VOC) and Methane (CH4) 179
H.4 Carbon Monoxide (CO) 183
H.5 Average Emission Factors 185
Appendix I Additional Details for Calculating an Onroad Inventory 186
I.1 Project Scale Refined Approach 186
1.2 Hypothetical Port Example 186
I.2.1 Details of Hypothetical Port 187
1.2.2 PDM Tabs Inputs 187
1.2.3 Post-Processing Project Scale Output for Inventory Development 189
Appendix J HAP Speciation Profiles for Locomotive Engines 191
Appendix K Estimating Number of Trucks and Rail Cars 196
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List of Abbreviations
2020 Public Draft
AIS Automatic Identification System
ARB Air Resources Board (California)
AVFT Alternative Vehicle and Fuels Technology (component of MOVES)
BC black carbon
BSFC brake specific fuel consumption
BTU British thermal units
CI Category 1 (commercial marine engines)
C2 Category 2 (commercial marine engines)
C3 Category 3 (commercial marine engines)
CAAAC Clean Air Act Advisory Committee
CDM County Data Manager (component of MOVES)
CFR Code of Federal Regulations
CH4 methane
CHE cargo handling equipment
CNG compressed natural gas
CO carbon monoxide
C02 carbon dioxide
DPM diesel particulate matter
DPM2.5 diesel particulate matter with an aerodynamic diameter less than or equal to 2.5 microns
DPM 10 diesel particulate matter with an aerodynamic diameter less than or equal to 10 microns
DOT Department of Transportation
DWT deadweight tonnage
E-85 a blend of gasoline and denatured ethanol containing up to 85% ethanol
E&C Vessel Entrances and Clearances
ECA Emissions Control Area
EF emission factor
EPA U.S. Environmental Protection Agency
FAF Freight Analysis Framework
FHWA Federal Highway Administration
g gram
g/hp-h gram per horsepower-hour
g/hr gram per hour
g/kWh gram per kilowatt-hour
g/mi gram per mile
g/start gram per vehicle start
gal gallon
GHG greenhouse gas
GIS geographic information system
GPS global positioning system
GT gas turbine
GT-ED electric drive gas turbine
GTM gross ton-mile
GUI graphical user interface
GVWR gross vehicle weight rating
h hour
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HAP hazardous air pollutant
HC hydrocarbons
HFO heavy fuel oil
hp horsepower
hp-h horsepower-hour
hp-h/gal horsepower-hour per gallon
HPMS Highway Performance Monitoring System
HSD high-speed diesel
l/M inspection and maintenance
ID identifier
IMO International Maritime Organization
in inch
in3 cubic inch
J joule
kJ kilojoule
kn knot
kW kilowatt
kWh kilowatt-hour
L liter
L/cyl liter per cylinder
lb pound
lb/ft3 pound per cubic foot
LF load factor
LLAF low load adjustment factor
LNG liquified natural gas
LPG liquified petroleum gas
m meter
m2 square meter
m3 cubic meter
MDO marine diesel oil
MGO marine gas oil
MMSI Maritime Mobile Service Identity
MOVES MOtor Vehicle Emission Simulator
mph miles per hour
MSAT mobile source air toxic
MSD medium-speed diesel
MSD-ED electric drive medium-speed diesel
MSTRS Mobile Sources Technical Review Subcommittee
N/A not applicable
N20 nitrous oxide
NAAQS national ambient air quality standard
NEC not elsewhere classified
NEI National Emissions Inventory
NEPA National Environmental Policy Act
NOx nitrogen oxides
OGV ocean-going vessels
PAMS portable activity measurement system
PDM Project Data Manager (component of MOVES)
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PM
particulate matter
PM2.5
particulate matter with an aerodynamic diameter less than or equal to 2.5 microns
PM10
particulate matter with an aerodynamic diameter less than or equal to 10 microns
ppm
parts per million
reefer
refrigerated (vessel cargo)
RIA
Regulatory Impact Analysis
RM
residual marine (fuel oil)
RORO
roll-on/roll-off (vessel cargo)
rpm
revolutions per minute
RTG
rubber-tired gantry
RunSpec
run specification (component of MOVES)
RVP
Reid Vapor Pressure
see
source classification code
SCTG
Standard Classification of Transported Goods
SIP
state implementation plan
SITC
Standard International Trade Classification
S02
sulfur dioxide
SSD
slow-speed diesel
ST
steam turbine
STB
Surface Transportation Board
TEU
twenty-foot equivalent unit
ton
U.S. ton
ton/m3
U.S. ton per cubic meter
ULSD
ultra-low sulfur diesel
U.S.
United States
USACE
U.S. Army Corps of Engineers
USCG
U.S. Coast Guard
VHT
vehicle hours traveled
VMT
vehicle miles traveled
VOC
volatile organic compounds
WCS
Waterborne Commerce Statistics
wt%
percentage by weight
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1 Introduction
1.1 Purpose
This document describes how to develop a mobile source port-related air pollution emissions inventory,
which is a quantification of all air emissions of selected pollutants that occur within a designated area by
mobile sources for a given time period. The U.S. Environmental Protection Agency (EPA) intends this
document to help port authorities and other port operators, state and local governments, Tribes, those
doing business at ports (such as terminal operators, tenants, and shipping companies), communities,
and other stakeholders who want to prepare emission inventories. This document supersedes the
previous April 2009 document Current Methodologies in Preparing Mobile Source Port-Related Emission
Inventories. This document may be used for regulatory, voluntary, and research purposes. Note that
there are a few instances where alternative methodologies presented in this document would not be
appropriate for regulatory purposes, and these instances are noted within the text. This document
specifies the data inputs, methods, and analysis approaches available for developing emission
inventories of varying levels of detail based on user capacity, available resources, and the intended end
use of the inventory. A variety of scales are included, such as project, terminal, sector, port, and
regional levels.
This document covers base year and future inventories at different kinds of ports and associated port-
related activity in the United States (U.S.), including activity occurring in:
• Seaports
• Great Lakes ports
• River ports
• Railyards
• Freight terminals
• Intermodal facilities
• Freight corridors
This document could be used in whole or in part depending on the purpose and scope of the port-
related emissions inventory. For example, a seaport inventory may include all sectors addressed in this
document, while an inland rail-to-truck intermodal transfer facility could apply the sections of this
document that cover emissions from the onroad, cargo handling equipment, and rail sectors. While this
document focuses on mobile source activity at ports and uses port-related terminology throughout the
document, the methodologies and many of the data sources are broadly applicable to other goods
movement facilities, such as railyards and intermodal facilities. This document relies on existing
resources, regulations, models, and best practices to ensure that these emission inventories are created
using the latest methods, science, and data, commensurate with resource availability and the end
purpose of the inventories.
This document does not repeat detailed information on how to run various models or tools that are
included in other documentation, but instead covers the various methodologies and sources of input
data that are necessary to develop an inventory and refers readers to those other sources for "how-to"
information. Note that this document also does not provide methodologies to quantify specific
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strategies for reducing emissions at ports. EPA already has a number of other tools and documents that
cover this information, such as the National Port Strategy Assessment,1 EPA and Port Everglades
Partnership: Emission Inventories and Reduction Strategies,2 and the Diesel Emissions Quantifier,3
among others.3
1.2 Background
Ports are key to the U.S. economy and serve as gateways to transport cargo, fuel, and passengers
around the globe. Seaport cargo activity alone accounts for over a quarter of the U.S. Gross Domestic
Product and supports the employment of over 23 million Americans.4 Because ports are a significant
part of the U.S. economy, it is critical to understand their potential impacts on air pollution, greenhouse
gases (GHGs), and the people living, working, and recreating near ports. As part of its Ports Initiative,
EPA recognizes the importance of working closely with ports to understand the on-the-ground, day-to-
day operations and examine the methods available to estimate associated air pollution emissions.15 This
includes providing technical resources to help port stakeholders examine emission trends by source,
identify potential opportunities for emission reductions, and prioritize future investment or operational
changes to reduce emissions.
EPA formed the Ports Initiative Workgroup under the Mobile Sources Technical Review Subcommittee
(MSTRS) of the Clean Air Act Advisory Committee (CAAAC) to advise on the development and
implementation of an EPA-led voluntary initiative to improve port environmental performance and air
quality for port communities. The CAAAC recommended, among other things, that EPA develop and
assess emissions inventory methodologies, and update the information as needed. It also
recommended that EPA should assist and encourage states to support port authorities and other port
operators as needed to develop refined inventories of port-related operations.5
EPA developed the National Port Strategy Assessment to examine current and future emissions from a
variety of diesel sources operating in port areas, and to explore the potential of a range of available
strategies to reduce emissions from port-related mobile source activity.1 Additionally, EPA worked with
Broward County's Port Everglades of Southeast Florida through a voluntary partnership to study port-
related mobile source emissions.2 As a result of this partnership and other work, EPA developed
methods, lessons learned, and practical examples that can be shared with other ports, related agencies,
and stakeholders. The Port Everglades Partnership also informed this update, so that other U.S. ports,
port-related industry, state and local governments, Tribes, and surrounding communities have clear
technical methodologies to estimate and understand emission inventories and potential reductions from
port-related strategies in support of the Workgroup's recommendations.
1.3 Importance of Port-related Emission Inventories
A port-related emissions inventory may be developed for a variety of different purposes. Regulatory
purposes include an inventory developed for state implementation plans (SIPs), National Environmental
Policy Act (NEPA) analyses, transportation conformity determinations, or general conformity
evaluations, among others. An emissions inventory may also be developed for research purposes.
a Additional resources are available at httpsi//www.epa.gov/state-and-local-transportation/transportation-
related-documents-state-and-local-transportation.
b For more information on EPA's Ports Initiative, see https://www.epa.gov/ports-initiative.
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Voluntary purposes include evaluating the effectiveness of emission reduction strategies or creating a
benchmark to make informed planning decisions. This document may be used for all these purposes
and may also be a useful technical resource for state and local regulatory or voluntary implementation,
as well as port- or freight-related research modeling. Section 2 of this document provides more
discussion about inventory purposes.
Most emissions from mobile source port-related activity come from diesel engines.1 Emissions from
diesel engines, especially particulate matter, nitrogen oxides, and air toxics such as benzene and
formaldehyde, can contribute to significant health problems—including premature mortality, increased
hospital admissions for heart and lung disease, and increased respiratory symptoms—for children, the
elderly, outdoor workers, and other sensitive populations.6 EPA has determined that diesel engine
exhaust emissions are a likely human carcinogen,7 and the World Health Organization has classified
diesel emissions as carcinogenic to humans.8 Many ports and port-related corridors are also located in
areas with a high percentage of low income and minority populations who are often disproportionately
impacted by higher levels of diesel emissions.9
Other port-related diesel emissions, such as carbon dioxide and black carbon, contribute to climate
change.10 An emissions inventory is an important tool that may be used by federal, state, and local
governments, Tribes, port authorities and port operators, communities, and other stakeholders to
reduce these impacts and enhance public health and environmental protection. It is also a benchmark
against which to measure progress and enables informed decision making. With this information, a port
can examine emission trends by source, identify potential opportunities for emission reductions, and
prioritize future investment or operational changes to reduce emissions.
Ports are a nexus between transportation modes and activities that generate emissions on water and on
land, both within the port boundary and on nearby transportation corridors. Quantifying all port-related
mobile source emissions using local data can help stakeholders identify impacts and opportunities to
reduce emissions. EPA's technology standards and fuel sulfur limits are expected to significantly reduce
emissions as new diesel trucks, cargo handling equipment, ships, and locomotives enter the in-use fleet.
However, implementing voluntary operational strategies or accelerating equipment replacement or
retrofit rates could further reduce emissions, or reduce emissions sooner. The emission-reducing
potential of a given strategy highly depends on a port's individual characteristics. Attributes such as the
port's primary activity type and level; types of vessels, equipment, and fuels used; and the technologies
and operations utilized onsite impact the emissions reduction potential of a given strategy.
In addition to supporting environmental goals, creating an inventory of emissions can help a port
prioritize investments. Some of the voluntary strategies a port could adopt have potential co-benefits,
such as reducing fuel usage and improving operational efficiencies that may enhance a port's
competitiveness. While this document does not cover how to quantify specific emission reduction
strategies, an emissions inventory would be an important first step. EPA supports these efforts to
reduce port-related emissions and encourages more areas to adopt and incentivize such programs.
1.4 Organization of This Document
The remainder of this document is organized as follows:
• Section 2 describes the purpose and scope of port-related emission inventories.
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• Sections 3 through 8 detail how to develop inventories for the various source sectors at ports:
o Section 3: Ocean-going vessels
o Section 4: Harbor craft
o Section 5: Recreational marine
o Section 6: Cargo handling equipment
o Section 7: Onroad vehicles
o Section 8: Rail
• There are also several appendices that include emission factors, detailed methodologies, and
other supporting material.
1.5 Additional Information
For specific questions concerning the development of an inventory for a particular port, please contact
the appropriate EPA Regional Office. A list of the EPA Regions, the states they cover, and contact
information for staff that can coordinate work related to state implementation plans and state and local
transportation can be found at the following website: www.epa.gov/state-and-local-
transportation/epa~regional~contacts~regarding~state~and~local~transportation.
For specific questions about estimating emissions for the onroad, nonroad, and recreational marine
source sectors using MOVES, please contact the MOVES team at mobilegepa.gov.
Any other general questions about this document can be directed to talkaboutports@epa.gov.
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2 Planning a Port-Related Emissions Inventory
2020 Public Draft
2.1 Overview
When planning a port-related emissions inventory, it is important to consider what sources and
pollutants are to be included, the geographical area to be covered, and the timeframe of the inventory.
The overall purpose, or end use, of the inventory should guide these decisions, as the purpose is the
primary factor for determining the scope and level of detail:
• The scope of an inventory covers the sectors included, geographical boundaries, and time
domains.
• The level of detail refers to the type of activity data underlying the inventory calculations and
how refined those data are. Some purposes will necessitate more information than others.
This section includes a discussion of inventory purposes (Section 2.2) and general inventory approaches
(Section 2.3), followed by subsections that cover scope-related decisions to be considered when
planning an inventory:
• Mobile source sectors to include (Section 2.4)
• Pollutants to include (Section 2.5)
• The geographical area to be covered (Section 2.6)
• The time period to be covered (Section 2.7)
EPA encourages emission inventories to be developed based on the latest local information whenever
possible. Using local information results in more accurate and representative inventories, empowering
stakeholders to make informed decisions. For example, if a port authority desires to evaluate the
potential of various operational strategies to improve efficiency and reduce fuel use and emissions,
having an inventory based on local information would allow for a port or terminal to tailor strategies
and best practices to their particular circumstances, depending on their business and environmental
goals.
2.2 Purposes of the Inventory
Inventories can have varying levels of detail, depending on the purpose of the inventory and the
resources available to create it. The choice of modeling approach, geographical scope, and time domain
covered by the inventory will depend on the purpose of the inventory. If the purpose of the inventory is
regulatory, EPA guidance is available for some sectors, and the reader is referred to those where
appropriate. For example, a potential regulatory purpose could be for use in a state implementation
plan (SIP), National Environmental Policy Act (NEPA) analysis, or general conformity evaluation. Note
that existing SIP inventories for areas where ports are located may not have estimated the contribution
specifically from the port in the past, but included these emissions in overall estimates. With this
document, EPA hopes to improve the estimation of emissions from port-related and goods movement
activity because they are a significant source of emissions from diesel engines.
Non-regulatory purposes for a port emissions inventory could include general port planning purposes, to
provide information to the port and the surrounding community about emissions, or an analysis of an
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individual transportation corridor. For these purposes, there can be additional flexibility in the approach
and scope for an inventory.
Regardless of whether the purpose is regulatory or not, an inventory with a finer resolution may provide
greater value for port authorities and terminal operators for identifying effective emission reduction
strategies or other areas for operational efficiency improvements. A detailed emissions inventory,
which reflects the latest modeling approaches and detailed activity information, could be valuable for
larger ports and their stakeholders in nonattainment and maintenance areas for the applicable national
ambient air quality standards (NAAQS), but also for ports where a screening level inventory would be
insufficient for their planning purposes. A fine level of geographical and temporal detail would be
necessary if the inventory is to be used in air quality dispersion or photochemical modeling.
Additionally, sufficient detail is needed if the purpose of the inventory is to analyze emission reduction
strategies.
However, alternative approaches that do not include this same level of detail can be appropriate for
various purposes as well. Some of the less-detailed approaches in this document would still provide
valuable information to those undertaking the inventory. For example, a screening level emissions
inventory could be valuable at ports that do not yet have a detailed emissions inventory and want to
understand overall emissions and relative contributions of different mobile source sectors. A screening
level emissions inventory can take many forms, but it typically involves a combination of port-specific
data and default activity assumptions. This kind of inventory could be intended to provide an order of
magnitude estimation of emissions to inform comprehensive port or terminal planning, or provide
stakeholders a preliminary context for how emissions compare at a local or regional level.
Another option is an equipment-only inventory. While this type of inventory is not an emissions
inventory, it could be relevant for smaller ports or ports without an emissions inventory to make certain
fleet- or sector-level decisions. An equipment inventory could be useful even if it covers only one
mobile source sector of interest, such as a port's or terminal's cargo handling equipment fleet. Including
activity levels associated with an entire fleet or sector could inform clean air investments. For example,
older equipment that is used most frequently could be prioritized for replacement with newer
equipment that meet the most stringent emission standards. Such an inventory would be a first step
towards developing a complete emissions inventory.
This document includes various methodologies to calculate emission inventories at the level of detail
needed for the purpose of the inventory. Sections 3 through 8 describe:
• Best practices to develop a detailed emissions inventory based on the latest modeling
approaches and detailed activity information
• Alternative methods that can be used to develop a less detailed inventory
2.3 General Inventory Approaches
Fundamentally, a quantitative emissions inventory is developed using the number (i.e., the population)
of vessels, vehicles, and equipment operating in a specific area, along with data on their operational
activity combined with appropriate emission factors. In addition to vessel, vehicle, and equipment
counts, the population data also include other information, such as model year or engine tier, engine
size, and fuel type, among others. This information allows the appropriate emission factor to be applied
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to the vessel, vehicle, or equipment's activity. The operational activity data can take many forms
depending on the sector and type of activity, but generally includes information on hours of use, engine
load, and/or miles travelled.
In general, the better the data about the emission sources and their activity, the more precise the
inventory will be. Inventory preparers should consider their resources and determine how best to
allocate them in the gathering of data. Inventory preparers should also consider the entities that may
have information relevant to inventory development, such as the port authority itself, the port tenants,
terminal operators, or other agencies, and consider involving them early in the process of developing
the inventory. Gaining the cooperation of these entities to share information would help to ensure that
the inventory accurately reflects port-related emissions. The better the inventory, the more helpful it
can be for making future decisions, such as investments in technologies or operational practices that
could reduce emissions and result in a cleaner environment.
The subsequent sections of this document describe best practices as well as alternative methods to
develop a port-related emissions inventory. Regardless of the method used in developing an inventory,
there are specific elements that are important to inform decision-making:
1. The latest available information should be used whenever possible and feasible.
2. Local, state, or regional data should be used if available; however, national, default, or other
surrogate data may be adequate, depending on the analysis.
3. Emission factors should reflect the latest EPA emission models and regulations for applicable
vessels, vehicles, equipment, and fuels.
4. An inventory should be developed through consultation with the involved parties, including port
authorities and other port operators, those doing business at ports (such as terminal operators,
tenants, beneficial cargo owners, and shipping and rail companies), state and local
governments, Tribes, local communities, federal agencies, and the public. In addition, the
appropriate EPA Regional Office is a key resource and should be consulted from the beginning of
inventory planning. Note also that inventories for some regulatory purposes will require specific
interagency consultation processes that include EPA.
5. The resulting inventory and documentation describing how it was developed should be widely
available to the public.
6. When the inventory purpose is regulatory, all components of an inventory should meet the
relevant requirements, such as those for SIP development (where the inventory is to be based
on the latest information available at the time the SIP is developed).3
7. Investments and commitments to port-related emission reduction strategies need to be assured
before being included in a projected future emissions inventory used for regulatory purposes.15
These elements inform decision-making pertinent to the purpose of the inventories. The remainder of
this section provides background information useful for determining the scope of an emissions
inventory.
a Based on the requirements of Clean Air Act section 172(c)(3).
b Based on the requirements of Clean Air Act section 110(a)(2)(A).
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2.4 Mobile Source Sectors
This document focuses on port-related diesel emissions from the following mobile source sectors:
• Ocean-going vessels (OGV)
• Harbor craft
• Recreational marine
• Cargo handling equipment (CHE)
• Onroad vehicles
• Rail
While some or all these source sectors are present at most U.S. seaports, Great Lakes ports, and river
ports, they may also be present in various combinations at inland rail or truck distribution centers,
intermodal facilities, truck or rail corridors, railyards, and freight terminals. Each sector is briefly
described below.
Note that there may also be other sources of air emissions present, such as electricity generation,
fugitive dust, refineries, or fuel storage. While these sources may also be important to include in a
comprehensive air emissions inventory, this document only covers the mobile source sector
contributions.
2.4.1 Ocean-Going Vessels
The OGV source sector covers ships that transport cargo and/or people between different ports.
"Ocean-going" is used here as a descriptive term, since many of these vessels operate in the oceans,
either navigating internationally across oceans or operating extensively in coastal areas. However, this
source sector also covers vessels that transport cargo and/or people between different ports in the
Great Lakes and inland rivers.
OGV typically have Category 3 (C3) propulsion engines, which have a cylinder displacement of 30 liters
or more; however, some OGV have smaller Category 1 (CI) or Category 2 (C2) engines. See Section 3 for
more information about the OGV sector.
2.4.2 Harbor Craft
The harbor craft source sector covers all commercial marine vessels that are not considered in the OGV
sector, such as tug boats and work boats. Unlike OGV, harbor craft typically spend most of their
operating time in or near a single port or region, and they typically have CI or C2 engines. See Section 4
for more information about the harbor craft sector.
2.4.3 Recreational Marine Vessels
Recreational marine vessels are operated primarily for pleasure, such as motorboats, cruisers, yachts,
and other types of pleasure craft. See Section 5 for more information about the recreational marine
sector.
2.4.4 Cargo Handling Equipment
The CHE sector encompasses equipment such as yard tractors and cranes used for moving cargo,
products, and supplies around a port or other terminal, and on and off marine vessels, railcars, and
onroad trucks. CHE are typically classified as "nonroad equipment," i.e., mobile equipment that do not
operate on roads. See Section 6 for more information about the CHE sector.
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2.4.5 Onroad Vehicles
The onroad vehicles sector is primarily comprised of heavy-duty diesel trucks, but it also includes cars,
light-duty trucks, and buses. See Section 7 for more information about the onroad sector.
2.4.6 Rail
Two types of locomotives typically support port-related cargo operations: switcher locomotives and line-
haul locomotives. Switchers, also referred to as "yard engines," assemble and disassemble trains. Line-
haul locomotives are the engines that move cargo long distances and are typically larger than switchers.
See Section 8 for additional information about what is included in the rail sector.
2.5 Pollutants of Concern
The pollutants included in a port-related emissions inventory should be determined by the purpose of
the inventory. The pollutants of concern in a port-related emissions inventory could include criteria
pollutants and precursors, climate-related pollutants, and air toxics. Criteria pollutants include common
air pollutants that are identified by the Clean Air Act, such as particulate matter and ground-level ozone.
Precursors are air pollutants that form criteria pollutants, such as nitrogen oxides and volatile organic
compounds, which combine to form ground-level ozone. Climate-related pollutants include greenhouse
gases, while air toxics are hazardous air pollutants that are known or suspected to cause serious health
effects.
The preparer of an inventory should consider which pollutants to include at the beginning of the process
and may want to consult with other agencies and stakeholders on this decision. Considerations include
whether or not the port or terminal is located in a nonattainment or maintenance area for a criteria
pollutant; if so, that pollutant and its precursors should be included. An inventory preparer may want to
include any and all other pollutants from the start: for sectors that are estimated using EPA's MOVES
model,c for example, it may save time to include every pollutant in the initial MOVES run rather than to
determine later that another pollutant is needed, creating the need to run MOVES again for that
additional pollutant.
This document includes specific information on how to develop inventories of the following pollutants:
• Criteria pollutants and precursors:
o Nitrogen oxides (NOx)
o Particulate matter with an aerodynamic diameter less than or equal to 2.5 microns
(PM25)
o Particulate matter with an aerodynamic diameter less than or equal to 10 microns
(PM10)
o Sulfur dioxide (S02)
o Volatile organic compounds (VOC)
• Climate-related pollutants:
o Carbon dioxide (C02)
EPA's MOtor Vehicle Emission Simulator (MOVES) is a state-of-the-science emission modeling system for mobile
sources. For port-related emission inventories, it is used in the development of onroad, CHE, and recreational
marine inventories as discussed in each of those sections of this document. For more information about MOVES,
see https://www.epa.gov/moves.
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o Methane (CH4)
o Nitrous oxide (N20)
o Black carbon (BC)
• Mobile source air toxics (MSATs):
o Diesel particulate matter with an aerodynamic diameter less than or equal to 10
microns (DPM25)
o Diesel particulate matter with an aerodynamic diameter less than or equal to 2.5
microns (DPMio)
While this list generally applies broadly to all sectors, S02 port-related inventories are primarily relevant
for the OGV sector. The non-OGV sectors at ports in the United States are required to use ultra-low
sulfur diesel (ULSD) and lower sulfur gasoline. These cleaner-burning fuels have significantly reduced
the S02 emissions from the sectors that use them. In addition, onroad SIP and transportation
conformity inventories typically do not include S02 as the onroad sector has not been a significant
portion of these emissions. However, this document includes best practice methods to estimate S02
emissions for all sectors for implementers that wish to include this pollutant.
Additionally, methods to develop inventories for the criteria pollutant carbon monoxide (CO) are
included for those who wish to include this pollutant. Diesel-fueled equipment are not large sources of
CO, so this is typically not a pollutant of concern for port-related inventories.
Note that methods to develop inventories of total hydrocarbons (HC) are also included throughout this
document for modeling purposes, as VOC and CH4 emissions are generally calculated from HC emissions.
Depending on the specific purpose and scope of an emissions inventory, it may be desirable to include
additional pollutants, such as the MSATs benzene and formaldehyde. Where applicable, this document
contains references to various resources available for including other pollutants that are not specifically
discussed here. Similarly, while this document focuses on quantifying pollution that is directly emitted
from primarily diesel-fueled vessels, equipment, and vehicles, road dust is also a mobile source of PM
pollution for certain sectors in PM10 and in certain PM2 5 nonattainment and maintenance areas; this
document highlights these cases and references resources available for including road dust as
appropriate.
In addition to the pollutants discussed above, energy consumption may be of interest. Energy
consumption is an important measure of port-related activity and it may be useful to include as part of
the inventory. Appendix A provides methods that can be used to estimate energy consumed for each
source sector.
2.6 Geographical Domain
The area covered by an inventory (i.e., the geographical domain) will be closely tied to the inventory's
purpose and scope. In general, an inventory should cover all source sectors and geographical areas of
interest. This typically includes, at a minimum, the geographical area within the port authority or other
port operator's jurisdiction. It frequently also includes port-related traffic in nearby transportation
corridors, depending on the purpose of the inventory.
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The following subsections describe how the marine and landside boundaries should be determined and
concludes with a discussion of geographical scope.
2.6.1 Marine Boundary
The marine boundaries should be set so that all port-related activities of interest for the inventory's
purpose and scope occur within them. Common areas included in the marine portion of an emissions
inventory include:
• Transit areas: Locations where vessels are typically traveling at normal cruising speed
• Restricted speed zones: Areas where travel speeds are limited due to safety or other reasons,
typically within waterways leading to a port
• Maneuvering areas: Locations within a harbor area, where large vessels are typically moved
with the assistance of tugs or other harbor craft
• Hotelling areas: Berthing, mooring, and docking areas where vessels can load or unload cargo or
people
• Anchorage zones: Areas where vessels wait at anchor for an open berth
2.6.2 Land-side Boundary
The land-side boundaries should be set so that all port-related activities of interest for the inventory's
purpose and scope occur within them. Common areas included in the land-side portion of an emissions
inventory include:
• Freight or intermodal terminals for the loading and unloading of cargo from ships, trucks, and/or
trains
• Gates, queues, and staging areas for onroad vehicles, such as diesel trucks
• Railyards
• On-port roads
• Parking lots
• On-dock storage of cargo, product, or containers
Additional land-side activities and areas that may be included even though they occur outside the port
authority or other port operator's jurisdiction, but still within the geographical domain of the inventory:
• Common drayage truck and other port-related vehicle routes
• Rail lines
• Intermodal facilities that handle and/or warehouse port-related cargo
Whether or not to include port-related transportation corridors (e.g., highways and rail lines) and other
facilities in emission inventories is especially important when considering people living and working near
these facilities. Additionally, analyzing emissions in transportation corridors can provide insight into the
benefits of emission reduction strategies that could be realized beyond the boundaries of a port.
2.6.3 Determining Geographical Scope
The purpose of an inventory should be carefully considered when determining the geographical scope to
ensure the inventory covers all areas of interest and can be used by all stakeholders to make informed
decisions. Frequently, port-related inventories cover an entire port (as defined by the port authority or
other port operator's jurisdictional boundaries). Generally, EPA recommends that the geographical
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scope for each source sector also include emissions associated with moving freight through to the first
intermodal transfer point. The following list includes geographical scope suggestions to be considered
for each source sector:
• OGV: All restricted speed zones, maneuvering areas, hotelling areas, and anchorage zones that
are within the port's boundaries, or are used by vessels when calling on the port. For coastal
seaports, this could also include transit areas to the international boundary.
• Harbor craft: Typically, the harbor craft geographical scope should be the same as the OGV
geographical scope. It should cover all areas where harbor craft support OGVs that call on the
port, as well as all other activities by harbor craft that operate out of the port.
• Recreational marine: Typically, the recreational marine geographical scope should be the same
as the OGV geographical scope.
• CHE: All areas where CHE activity occurs within the port's boundary.
• Onroad: All areas where heavy-duty truck activity occurs within the port's boundary, including
gates, queues, on-port roads, and loading/unloading areas, in addition to off-port transportation
corridors to the first intermodal transfer point.
• Rail: All railyards within the port's boundary and possibly nearby port-related line-haul activity.
However, some inventories may have a smaller geographical domain, such as:
• One or more terminals
• One or more mobile source sectors
• The marine geographical boundary only
• The landside geographical boundary only
• A port-related truck, rail, or vessel corridor
• An off-port freight distribution or intermodal facility
A smaller geographical domain may be useful if resources are limited and the purpose of the inventory is
to answer specific questions or make decisions regarding only a portion of port-related activity.
Alternatively, an inventory may have a larger geographical domain than an entire port for various
purposes:
• An entire state (e.g., for a state freight plan)
• An entire nonattainment or maintenance area (e.g., for a SIP)
In these cases, the port-related inventory will be used in conjunction with other inventories (e.g., county
inventories), and the geographical boundaries should be carefully considered to avoid double counting
emissions or missing any emission sources. If the emissions inventory will support regulatory purposes,
the interagency consultation process should be used to determine the geographical boundaries and how
to address and minimize double counting or missing emissions. Furthermore, if the purpose of the
emissions inventory is to support air quality modeling, a high level of geographical activity detail will be
needed in each sector, as described in each of the subsequent sector sections.
Consider, for example, a hypothetical port inventory that will be used to quantify emissions in a
nonattainment area as part of a SIP. In this case, the port inventory boundaries will need to be selected
in such a way that they do not overlap with other inventories that quantify emissions in the rest of the
nonattainment area. If overlap is unavoidable, the interagency consultation process should be used to
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avoid or reduce the possibility of emissions being counted twice. In the example, onroad and rail
emissions could be available in the county-wide inventory which includes all publicly accessible roads
and the rail line extending outside the port's boundary. In this case, the port inventory could be
calculated with two separate components: an "on-port" component, which includes the geographical
area within the port's jurisdiction, and an "off-port" component, which covers the port-related traffic in
nearby transportation corridors. By doing so, the on-port inventory could be combined with the county-
wide inventory without double counting some emissions.
Regardless of scope, the geographical domain of an inventory should be clearly documented, so that
anyone reviewing it understands what is and what is not included.
2.7 Time Domains and Future Inventories
The purpose of the emissions inventory will also determine the time domain and level of temporal detail
used when calculating the inventory. While most port-specific base year emission inventories are
annual, for some purposes, a seasonal or daily inventory may be needed (e.g., the scope for inventories
used in SIPs would depend on the specific NAAQS involved). If inventories are to be used for multiple
purposes, it may be useful to report emissions at multiple temporal levels (e.g., annual emissions for
planning purposes and hourly emissions for air quality modeling purposes).
If the purpose of the emissions inventory is to support air quality modeling, a high level of temporal
activity detail will be necessary in each sector. If emissions are calculated at the annual scale, they may
need to be allocated to a finer level of detail, depending on the purpose of the inventory (e.g., a 24-hour
period), as described in each of the subsequent sections.
Generally, the time domain should be a recent year that data is available or for which data can be
collected. If future year emission inventories are needed (e.g., for SIPs or analyzing emission reduction
strategies):
1. The base year inventory should be completed first (i.e., a retrospective inventory should be
developed for a recent year with measured activity data).
2. Then the activity used in the base year inventory should be scaled to estimate activity levels in
the future year inventory using local port and sector specific growth projections, if available.
3. Finally, any planned action that has been committed to that would influence future emissions as
well as fleet turnover should be accounted for while estimating the future inventories. For
example, if an emission reduction strategy is planned, its impact on future activity and/or
emission factors should be included. However, the same emissions inventory methodology
should be used to calculate both the base year and future year inventory.
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations. Using these local data sources in
consultation with all involved stakeholders result in better data for a better inventory. If local port and
sector specific growth projections are unavailable, the Freight Analysis Framework (FAF) can be used to
forecast growth by sector.11 The FAF contains projected tons of commodities flow by transport mode at
the state and regional level for both historic and future years. Growth factors can be derived by dividing
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the projected future tons of commodity flow by the appropriate historic year tons. These growth factors
can then be applied to the base year inventory's activity to estimate future activity levels.
Each of the subsequent sections describe in more detail how a base year or future year emissions
inventory can be calculated, and how the FAF can be used to estimate future activity when local port
and sector specific growth projections are not available.
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U.S. Environmental Protection Agency
3 Ocean-Going Vessels
2020 Public Draft
3.1 Source Description
The ocean-going vessels (OGV) source sector covers ships that transport cargo and/or people between
different ports. "Ocean-going" is used here as a descriptive term, since many of these vessels operate in
the oceans, either navigating internationally across oceans or operating extensively in coastal areas.
However, this source sector also covers vessels that transport cargo and/or people between different
ports in the Great Lakes and inland rivers.
OGV typically have Category 3 (C3) propulsion engines, which have a cylinder displacement of 30 liters
or more; however, some OGV have smaller Category 1 (CI) or Category 2 (C2) engines. Table 3.1 lists
the various ship types that comprise the OGV source sector. These ship types can be further described
by various subtypes (see Section 3.3.3). Note that there may be specialized types of OGV that do not
appear on this list. However, this source sector does not include harbor craft, which are discussed in
Section 4 or recreational marine vessels or vessels with gasoline engines, which are discussed in Section
5.
Table 3.1. OGV Ship Types
Ship Type
Description
Bulk Carrier
Dry-cargo vessels that carry loose cargo (e.g., grain, ore)
Chemical Tanker
Liquid-cargo vessels that transport chemicals in bulk
Container Ship
Dry-cargo vessels that carry containerized cargo
Cruise
Passenger vessels used for commercial pleasure voyages
Ferry/Passenger (C3)*
Passenger vessels used for transport
Ferry/Roll-on/Passenger (C3)
Passenger vessels used for transporting people and their vehicles
Fishing (C3)
C3 vessels used in commercial fishing operations
General Cargo
Dry-cargo vessels that are not specialized for a particular type of cargo
Liquified Gas Tanker
Cargo vessels specifically designed to transport liquified gas at high
pressure and/or low temperature
Miscellaneous (C3)
C3 vessels not otherwise designated in this table
Offshore Support/Drillship
Vessels that support offshore oil and gas platforms or perform
exploratory offshore drilling
Oil Tanker
Liquid-cargo vessels that transport petroleum products in bulk
Other Service
Vessels that perform support services (e.g., oil spill cleanup)
Other Tanker
Liquid-cargo vessels that transport cargo not otherwise designated in
this list
Refrigerated (Reefer)
Vessels that carry refrigerated cargo
Roll-on/Roll-off (RORO)
Vessels that handle cargo that is rolled on and off the ship, such as
trucks and construction equipment
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Ship Type
Description
Vehicle Carrier
Dry-cargo vessels that transport vehicles
Yacht (C2/C3)**
Private passenger vessels
* C3 in a ship type designates that emissions from vessels of the specified ship type should be estimated
according to the methodologies presented in this section if they have C3 propulsion engine(s). If they have CI
or C2 propulsion engine(s), their emissions should be estimated according to the methodologies presented in
Section 4.
" Emissions from yachts should be quantified using the methodologies presented in this section if they have C2
or C3 propulsion engines. If they have CI or gasoline engines, their emissions should be quantified as
described in Section 5. See Table 3.2 for how to distinguish between the different categories of marine
engines.
In general, emissions for all OGV operating within the geographical domain for the inventory should be
estimated. However, taking this approach may include innocent passage emissions, which are emissions
from vessel activity not related to the port(s) for which the inventory is being calculated (i.e., vessels just
passing through the geographical domain). Depending on the purpose of the inventory, it may be
important to quantify emissions from innocent passage separately from vessels calling on the port. See
Section 2 of this document for more discussion about inventory purpose, geographical domains, and
temporal detail.
OGV typically have three kinds of emission sources:
• Propulsion engines, also referred to as main engines, which supply power to move the vessel
• Auxiliary engines, which supply power for non-propulsion (e.g., electrical) loads
• Boilers, which heat fuel and water
3.2 Emissions Estimation Overview
OGV base year emissions from each type of emission source can be estimated for each vessel using
Equation 3.1:
E = PxAxEFx LLAF Equation 3.1
Where E = per vessel emissions (g)
P = engine operating power (kW)
A = engine operating activity (h)
EF = emission factor (g/kWh)
LLAF = low load adjustment factor, a unitless factor that reflects increasing propulsion
emissions during low load operations (always 1 for auxiliary engines and boilers)
Each of the above parameters vary by vessel and emission source (propulsion engine, auxiliary engine,
or boiler). Therefore, it is important to accurately account for vessel characteristics (discussed in Section
3.3) and activity (Section 3.4) to ensure the operating power and hours are calculated correctly and that
the right emission factors (Section 3.5), auxiliary loads (Section 3.6) and low load adjustment factors
(Section 3.7) are applied to this activity.
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There are different methods that can be used for estimating OGV emissions for a base year emissions
inventory depending on data and resource availability. The two methods described in this document are
an Automatic Identification System (AIS) based approach (Section 3.8) and an alternative approach
based on vessel trip records (Section 3.9):
• With the AIS based approach, emissions are calculated for each AIS record. Emission factors
(EF) are assigned by engine type, fuel, and other characteristics; operating power (P), activity
(A), and low load adjustment factor (LLAF) are derived from AIS data as described in Section
3.8.
• The vessel trip records approach relies on using the same vessel characteristics and emission
factors as the AIS based approach; however, P, A, and LLAF are derived by operating mode for
each vessel trip rather than AIS record, as described in Section 3.9.
The AIS approach allows for a highly detailed OGV inventory, which may be desirable for inventories
that need a fine level of temporal or geospatial resolution (e.g., for air quality analyses, looking at
different types of activities, or analyzing emission reduction strategies). However, this approach can be
resource intensive. Therefore, the vessel trip records approach can be used instead if the purpose of
the inventory does not necessitate a fine level of detail. Either approach could be used for most
regulatory or voluntary purposes. The chosen approach is usually determined by the purpose of the
inventory and the availability of activity data and the resources to process them.
Projections of future year emission inventories are discussed in Section 3.10.
3.3 Vessel Characteristics
Both the AIS and the vessel trip records approach involve data related to the characteristics of the
vessels operating in the geographical domain. This information may be available for purchase in the
form of vessel registry databases. Port records, vessel surveys, federal databases,3 and online searches
can supplement and validate these data. The following subsections detail the various data fields that
comprise vessel characteristic data:
• Fields used to identify vessels to cross-reference various data sets (Section 3.3.1)
• Fields used to characterize engines to determine appropriate emission factors (Section 3.3.2)
• Fields used to determine ship type and subtype to fill data gaps and to group similar activity
patterns (Section 3.3.3)
• Fields used as part of the calculation to determine engine operating power (Section 3.3.4)
The final subsection, Section 3.3.5, discusses techniques to fill data gaps in vessel characteristic data
sets.
3.3.1 Vessel Identification
All vessels have unique identifiers that can be used to match their activity data to vessel characteristic
data. The following vessel identifiers are useful when matching OGV records in different data sets:
a The U.S. Coast Guard maintains the following databases which may contain useful vessel characteristic data for
estimating emissions: Merchant Vessels of the United States (accessible by searching https://wyy.w-dep.-uscg. mil)
and U.S. Coast Guard Port State Information Exchange (accessible at https://cgmix.uscg.mil/PSIX/Default.aspx).
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• International Maritime Organization (IMO) number
• Maritime Mobile Service Identity (MMSI)
The IMO number is generally the best field to use for vessel identification, as this number is uniquely
assigned to each vessel under IMO resolutions12 and does not change over its lifespan. However, if the
IMO number is not available, the MMSI (which is uniquely assigned to each AIS transmitter) can also be
used to match vessel records. If neither IMO number or MMSI are available, the vessel name and call
sign can possibly be used to match local port records to local vessel survey data. However, vessel name
and call sign are not unique identifiers and thus are not recommended for matching AIS records to
national or global vessel characteristic data sets.
3.3.2 Engine Characteristics
Emission factors for each emission source depend on engine category and type. The following data
fields can be used to determine the vessel's propulsion engine characteristics:
• Engine category (CI, C2, or C3)
• Engine bore (the diameter of each engine cylinder)
• Engine stroke (the stroke length of each engine cylinder)
• Engine type (typically slow- or medium-speed diesel, among others as described below)
• Engine speed (revolutions per minute [rpm])
• Keel-laid year (used to determine engine tier)
3.3.2.1 Engine Category
If the engine category field is missing from the vessel characteristic data, it can be determined by
calculating cylinder displacement in liters using Equation 3.2, assuming the engine bore and stroke are
measured in millimeters:
TC _ ,
Cylinder Displacement = —x Bore/x Stroke x 10 6 Equation 3.2
Propulsion engines with a cylinder displacement of 30 liters or greater are C3 engines. For other
engines, Table 3.2 can be used to determine the engine category from the cylinder displacement and
engine tier.13 For engines with a cylinder displacement less than 30 liters and unknown engine tier, it
can be determined using the information presented in Appendix B. If the fields used to calculate
displacement are also missing, engine category can be assigned based on the defaults presented in
Appendix C.
Table 3.2. Classifying Marine Propulsion Engines
Engine Category
Engine Tier
Cylinder Displacement
1
Uncontrolled, 1, 2
displacement < 5 L
3,4
displacement < 7 L
2
Uncontrolled, 1, 2
5 L < displacement < 30 L
3,4
7 L < displacement < 30 L
3
All
displacement > 30 L
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3.3.2.2 Engine Type
Emission factors for OGV depend not only on engine category, but also engine type. There are several
different propulsion engine types seen on C3 vessels:
• Slow-speed diesel (SSD)
• Medium-speed diesel (MSD)
• High-speed diesel (HSD)
• Gas turbine (GT)
• Steam turbine (ST)
• Electric drive MSD or GT (identified as MSD-ED or GT-ED)
• Liquified natural gas (LNG)
If the engine type field is missing, it may be possible to identify it based on the descriptive propulsion
type, engine speed, or engine stroke type fields in the vessel characteristic data. The descriptive
propulsion type field often indicates if the engine is diesel, GT, ST, MSD-ED, or GT-ED. If the engine is
diesel but it is unknown if it is SSD, MSD, or HSD, Table 3.3 can be used to assign engine type based on
engine speed and/or stroke type.
Table 3.3. Marine Diesel Engine Speed Designations
Diesel Engine Type
Typical Engine Speed Range
Engine Stroke Type
SSD
< 500 rpm
2
MSD
500 -1,400 rpm
4
HSD
> 1,400 rpm
4
While there is no definite rpm cutoff between SSD and MSD diesel engines, EPA assigns a C3 vessel that
is missing engine type information to the SSD category if its engine speed is less than 500 rpm and MSD
if otherwise.14 If all fields used to determine the propulsion engine type are missing, C3 vessels can be
assumed to have SSD propulsion engines. For vessels with missing data on auxiliary engine type, all
auxiliary engines can be assumed to be MSD.
For C1/C2 propulsion engines, the engine speed is not necessary for assigning emission factors.
3.3.3 Ship Type and Subtype
Ship type and subtype information are used to group similar ships together to fill gaps in vessel
characteristic data, as well as for assigning auxiliary engine and boiler loads by operating mode. The
following vessel characteristic fields can be used to determine ship type and subtype:
• Ship type
• Gross tonnage
• Deadweight tonnage (DWT)
• Twenty-foot equivalent units (TEUs)
Depending on the source of the vessel characteristic data, the ship type field can have varying levels of
detail. Ship type can generally be aggregated to the categories listed in Table 3.1.
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Ship subtypes are assigned to each vessel according to its ship type and size class. If the default auxiliary
and boiler loads are used (as discussed in Section 3.6 and presented in Appendix E), the subtypes listed
in Table 3.4 are appropriate, which are primarily based on the Third IMO Greenhouse Gas Study.15
However, if detailed local data on auxiliary and boiler loads are available, alternate and/or more detailed
subtypes may be appropriate for some ship types. For example, cruise ships may be assigned to
subtypes based on passenger capacity if that is how information on auxiliary and boiler loads are
available.
Table 3.4. Ship Subtype Mapping Based on Ship Type and Size
Ship Type
Size
Units
Subtype
Bulk Carrier
0-9,999
DWT
Small
10,000-34,999
Handysize
35,000-59,999
Handymax
60,000-99,999
Panamax
100,000-199,999
Capesize
> 200,000
Capesize Largest
Chemical Tanker
0-4,999
DWT
Smallest
5,000-9,999
Small
10,000-19,999
Handysize
> 20,000
Handymax
Container Ship
0-999
TEU
1,000 TEU
1,000-1,999
2,000 TEU
2,000-2,999
3,000 TEU
3,000-4,999
5,000 TEU
5,000-7,999
8,000 TEU
8,000-11,999
12,000 TEU
12,000-14,499
14,500 TEU
> 14,500
Largest
Cruise
0-1,999
Gross Tonnage
2,000 Ton
2,000-9,999
10,000 Ton
10,000-59,999
60,000 Ton
60,000-99,999
100,000 Ton
> 100,000
Largest
Ferry/Passenger (C3)
0-1,999
Gross Tonnage
2,000 Ton
> 2,000
Largest
Ferry/Roll-on/Passenger (C3)
0-1,999
Gross Tonnage
2,000 Ton
> 2,000
Largest
Fishing (C3)
All
N/A
All C3 Fishing
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Ship Type
Size
Units
Subtype
0-4,999
5,000 DWT
General Cargo
5,000-9,999
DWT
10,000 DWT
> 10,000
Largest
0-49,999
50,000 DWT
Liquified Gas Tanker
50,000-99,999
DWT
100,000 DWT
100,000-199,999
200,000 DWT
> 200,000
Largest
Miscellaneous (C3)
All
N/A
All C3 Miscellaneous
Offshore Support/Drillship
All
N/A
All Offshore
Support/Drillship
0-4,999
Smallest
5,000-9,999
Small
10,000-19,999
Handysize
Oil Tanker
20,000-59,999
DWT
Handymax
60,000-79,999
Panamax
80,000-119,999
Aframax
120,000-199,999
Suezmax
> 200,000
VLCC
Other Service
All
N/A
All Other Service
Other Tanker
All
N/A
All Other Tanker
Reefer
All
N/A
All Reefer
RORO
0-4,999
Gross Tonnage
5,000 Ton
> 5,000
Largest
Vehicle Carrier
0-3,999
Vehicles
4,000 Vehicles
> 4,000
Largest
Yacht(C2/C3)
All
N/A
C2/C3 Yacht
3.3.4 Engine Operating Power
Engine operating power varies with different kinds of activity, and its calculation depends on the activity
data source. The following vessel characteristics are needed to calculate propulsion engine operating
power:
• Total installed propulsion power, also known as the vessel's maximum continuous rated engine
power (kW)
• Service speed or maximum speed (kn)
• Maximum draft, also known as the vessel's summer load line (m)
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Vessel service speed, also known as cruise speed, is used when calculating propulsion engine operating
power. However, if only vessel maximum speed is known from the vessel characteristic data, service
speed can be estimated at 94 percent of maximum speed.16
Section 3.6 discusses auxiliary and boiler operating power and Sections 3.8.4 and 3.9.3 discuss how to
calculate propulsion engine operating power.
3.3.5 Filling Gaps in Vessel Characteristic Data Sets
Missing data is a common occurrence in vessel characteristic data sets. The best practice for filling gaps
in vessel characteristic data is to use information from vessels with known values operating in the
geographical domain. For categorical fields, such as engine type, the most common values can be
identified from the known vessels. For numerical values, such as installed propulsion power, the
average of the known vessels can be used, weighted by time spent within the geographical boundary if
known or weighted by number of vessels otherwise. The following lists general considerations for
performing a gap filling analysis:
• Size indicators in the vessel characteristic data are DWT and/or gross tonnage for most ship
types, except TEUs are used for container ships and number of vehicles are used for vehicle
carriers. Table 3.4 shows which size indicator is used for each ship type when assigning ship
subtypes. In some cases, gross tonnage is known, but DWT, TEUs, or number of vehicles is
missing and needs to be gap filled in order to assign ship subtype. In these cases, the missing
DWT, TEUs, or number of vehicles can be regressed from gross tonnage by ship type from
vessels that are not missing these data. However, predicted values based on a regression
analysis should be used only if they fall within the expected range of that ship type. If gross
tonnage is also missing or if the data are not robust enough to support a regression analysis,
ships can be assigned the average DWT, TEUs, or number of vehicles by ship type, and then can
be accordingly assigned a subtype.
• Keel-laid year is used when determining the correct emission factors to assign to a vessel. In
some cases, keel-laid year is missing, but vessel build year is known. In these cases, keel-laid
year can be estimated from vessel build year by calculating the average difference between
these two fields by ship subtype from vessels that are not missing these data. If the amount of
time a vessel spends within the geographical boundary is known, the average difference should
be time-weighted.
• Engine category and type are also used when determining the correct emission factors to assign
to a vessel. To gap fill these fields, the most common values should be determined from vessels
that are not missing these data. Specifically:
o If just engine type is missing, the most common value should be determined by ship
type, subtype, and engine category,
o If both engine category and type are missing, the most common value should be
determined by ship type and subtype.
• Any other missing numeric parameters (such as service speed or maximum draft) can be filled
using average values, calculated from vessels that are not missing these data and weighted by
time spent within the geographical boundary. The time-weighted average at the most detailed
grouping should be prioritized in gap-filling these fields, after which averages determined by less
detailed groupings can be applied.
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If the data are not robust enough to support the above gap filling analysis, or if this kind of analysis is
not practical for other purposes, national average values listed in Appendix C can be assigned to vessels
with missing vessel characteristics.
3.4 Vessel Activity Data Sources
There are many different data sources available to estimate vessel activity at U.S. ports. This section
describes the most useful data sources for calculating emission inventories. These data sources
generally include vessel identifiers, such as IMO number, which can be used to match vessel activity data
with vessel characteristic data, as described in Section 3.3. This is important to assign the correct
emission factors and to estimate engine load appropriately.
3.4.1 Automatic Identification System
AIS equipment is used on vessels to aid navigation and to avoid collisions by broadcasting and receiving
messages containing vessel position, bearing, speed, and draft, in addition to vessel identifiers (such as
IMO number and MMSI) and other information. Most OGV use AIS because the IMO's International
Convention for the Safety of Life at Sea12 requires AIS to be fitted aboard all passenger vessels as well as
vessels with gross tonnage of 300 or more that are involved in international trips. This makes AIS a good
and highly detailed data source for vessel activity. AIS data can be analyzed to estimate time-in-mode
(e.g., hours spent hotelling), as well as propulsion engine load. However, AIS data do not contain
information on auxiliary engine or boiler loads, which are estimated using other methods.
AIS messages are recorded by the U.S. Coast Guard (USCG) as well as by commercial vendors for various
purposes. Marine Cadastre is a joint initiative of the Bureau of Ocean Energy Management and the
National Oceanic and Atmospheric Administration that provides publicly available AIS data derived from
USCG records.b Alternatively, U.S. federal, state, local, and Tribal government agencies can request
historical data from the USCG Navigation Center.c Depending on the data source, individual AIS records
may be provided for intervals between 2 seconds to 5 minutes or longer. While a shorter interval will
provide higher resolution and more precise determination of operating modes, it will also increase the
size and complexity of the data set. The purpose of the emissions inventory should determine the
acceptable level of AIS record aggregation. For example, a detailed inventory supporting air quality
analysis may benefit more from a shorter time AIS interval than an annual, port-wide inventory.
Similarly, the geographical boundary of the emissions inventory should determine the geographical
extent of the AIS data acquisition.
Note that there are two kinds of AIS receivers: terrestrial- and satellite-based. Depending on the data
source, some AIS data sets may contain one or both types. Terrestrial-based AIS data sets usually have
good coverage in and around U.S. ports, and include AIS messages at a higher frequency than satellite-
based AIS data sets. However, they can only receive messages within line-of-sight. In contrast, satellite-
based AIS data sets include messages at farther distances from shore, which may be important for
inventories that have a broad geographical domain. Occasionally, in very high traffic areas, terrestrial-
based receivers may be unable to handle the load of recording all messages received and some records
may be dropped. Combining terrestrial- and satellite-based AIS data can improve the total coverage of a
b For more information, see httpsi//mariInecadastre.gov/ais.
c For more information, see https://www.navcen.uscg.gov.
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given area. In general, if a dataset includes both terrestrial- and satellite-based data, and if there are AIS
messages for the same vessel and timestamp from both kinds of receivers, the message from the
terrestrial receiver should be used instead of the satellite receiver.
3.4.2 Local Logs
The local port authority, marine exchange, board of trade, or other local organizations may have
information on local vessel movements. These data sources (referred to as "local logs") usually include
vessel identification data (such as IMO number and/or vessel name), and date and time of vessel arrival
and departure. They may also record ship type, pier/wharf/dock information, cargo type, cargo
tonnage, vessel draft, and other information. Generally, one record of data corresponds to one vessel
call, although some data sets will also include vessel shifts between berths within the area of interest.
These records may be able to provide time-in-mode estimates (e.g., hours spent hotelling) and whether
tug support was involved during maneuvering.
If the purpose of the emissions inventory is to focus on only vessels that visit a port, or to quantify the
differences in emissions between innocent passage and vessels that call at a port, local logs can be a
primary data source to identify the specific vessels to be included in the inventory.
A potential limitation of local logs is that they may not include all OGV activity in a port. For example, a
port authority might not collect data on vessels that call at private terminals. Additionally, local logs do
not contain information on innocent passage, propulsion engine loads, or auxiliary engine and boiler
loads. The availability and cost of local logs vary by source.
3.4.3 Survey Data
Interviews with harbor pilots and/or surveys of vessels operating within the geographical domain can
provide useful data for estimating emissions. For example, interviews with harbor pilots can provide a
quality control check on average vessel speeds. Surveys of vessels can provide information on auxiliary
engine and boiler loads, which are typically not available from the other data sources described in this
section.
If there are not resources available to collect data directly on auxiliary engine and boiler loads by ship
type, size, and operating mode (as described in Section 3.6), surrogate data sources will be needed. If a
similar portd has recently conducted an inventory and collected these kinds of data, those could be used
instead. Alternatively, defaults are discussed in Section 3.6, although these data do not reflect local
operating conditions, which may impact auxiliary engine and boiler loads.
3.4.4 Entrances and Clearances
The U.S. Army Corps of Engineers (USACE) maintains the Vessel Entrances and Clearances (E&C) data
set, which is part of the Waterborne Foreign Cargo series.17 Records in this publicly available data
source include vessel identification data (such as IMO number), type of vessel, vessel draft, and
origin/destination of goods.
d Ideally, a "similar port" would be a different port in the same region with similar kinds and levels of activity.
However, any port with similar kinds and levels of activity could have useful surrogate data. For example, a port
with a lot of cruise ship activity could find useful data on cruise ship auxiliary engine and boiler loads from
inventory work done at a different port with similar levels of cruise ship activity.
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While this data source includes vessels that call at both public and private terminals, it only includes
foreign vessel movements; U.S. ships delivering cargo from one U.S. port to another U.S. port are not
accounted for in this data source. Instead, these vessel trips will appear in the Waterborne Commerce
data set, described below.
A limitation of E&C data is that they do not contain information on vessel speed, hours spent hotelling,
propulsion engine loads, or auxiliary engine and boiler loads.
3.4.5 Waterborne Commerce
USACE maintains the Waterborne Commerce Statistics (WCS) data set of domestic vessel movements.®
The WCS data provide vessel trips for individual vessels and include vessel identification data, type of
vessel, vessel draft, and trip route. These detailed data are available to U.S. Federal government
agencies but note that the data are confidential business information and not available for public
release.
A limitation of WCS data is that they do not contain information on vessel speed, hours spent hotelling,
propulsion engine loads, or auxiliary engine and boiler loads. Additionally, this data source may not
have good coverage of vessel activity unrelated to cargo movement (e.g., ferries).
3.5 Emission Factors
Emission factors vary by engine category (CI, C2, or C3), group (propulsion, auxiliary, or boiler), fuel
type, keel-laid year, and engine type (SSD, MSD, GT, ST, LNG, or boiler). For inventories of 2015 activity
and later, all diesel C3 marine vessels operating within the North American Emissions Control Area
(ECA)18 can be assumed to be using distillate marine gas oil (MGO) or marine diesel oil (MDO) to comply
with fuel sulfur regulations, unless local data indicate that specific vessels are using residual marine (RM)
or heavy fuel oil (HFO) with exhaust scrubbers. For inventories of activity before 2015, OGV can be
assumed to be using RM/HFO.
Note that electric drive engines are not assigned distinct emission factors. For example, MSD-ED
engines are assigned the same emission factors as MSD engines.
Emission factors for vessels with C3 propulsion engines, which comprise the majority of OGV, are given
below. The tables include emission factors for C3 propulsion engines, as well as smaller auxiliary
engines and boilers operating on C3 vessels. These emission factors apply for all C3 vessels, regardless if
they are considered to be OGV or harbor craft. They reflect the latest information available and reflect
implementation of the applicable EPA regulations.
For OGV that have CI or C2 propulsion engines, see Section 4.5 for the appropriate propulsion and
auxiliary engine emission factors.
Speciation profiles of additional hazardous air pollutants for all commercial marine vessels are
presented in Appendix D.
For methods to estimate energy consumption for this source sector, see Appendix A.
e For more information, see https://www.iwr.usace.armv.mjj/About/Technicaj-Centers/WCSC-Waterborne-
Commerce-Statistics-Center.
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3.5.1 Nitrogen Oxides (NOx)
NOx emission factors vary by engine group, fuel type, engine tier (as determined by keel-laid year), and
engine type. Emission factors for vessels with C3 propulsion engines are presented in Table 3.5.16
Table 3.5. Category 3 Vessel NOx Emission Factors (g/kWh)
Engine Group
Fuel Type
Keel-laid Year
(NOx Tier, if applicable)
Engine Type
NOx Emission
Factor (g/kWh)
Source
Any
ST
2.0
19
GT
5.7
19
1999 and earlier
SSD
17.0
19
MSD
13.2
19
MGO/MDO
2000-2010
SSD
16.0
20
(Tier 1)
MSD
12.2
20
2011-2015
SSD
14.4
20
(Tier II)
MSD
10.5
20
2016 and later
SSD
3.4
20
(Tier III)
MSD
2.6
20
Propulsion
Any
ST
2.1
19
GT
6.1
19
1999 and earlier
SSD
18.1
19
MSD
14.0
19
RM/HFO
2000-2010
SSD
17.0
21
(Tier 1)
MSD
13.0
21
2011-2015
SSD
15.3
21
(Tier II)
MSD
11.2
21
2016 and later
SSD
3.4
20
(Tier III)
MSD
2.6
20
LNG
Any
LNG
1.3
22
1999 and earlier
MSD
10.9
20
HSD
13.8
20
2000-2010
MSD
9.8
20
MGO/MDO
(Tier 1)
HSD
12.2
20
Auxiliary
2011-2015
MSD
7.7
20
(Tier II)
HSD
10.5
20
2016 and later
MSD
2.0
20
(Tier III)
HSD
2.6
20
RM/HFO
1999 and earlier
MSD
14.7
15
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Engine Group
Fuel Type
Keel-laid Year
(NOxTier, if applicable)
Engine Type
NOx Emission
Factor (g/kWh)
Source
HSD
11.6
15
2000-2010
MSD
13.0
15
(Tier 1)
HSD
10.4
15
2011-2015
MSD
11.2
15
(Tier II)
HSD
8.2
15
2016 and later
MSD
2.0
20
(Tier III)
HSD
2.6
20
LNG
Any
LNG
1.3
22
Boiler
MGO/MDO
Any
Boiler
2.0
19
RM/HFO
2.1
19
3.5.2 Brake Specific Fuel Consumption (BSFC)
BSFC rates vary by engine group, fuel type, and engine type. Note that particulate matter, carbon
dioxide, and sulfur dioxide are calculated based on these values. BSFC rates for vessels with C3
propulsion engines are presented in Table 3.6.
Table 3.6. Category 3 Vessel BSFC Rates (g/kWh)
Engine Group
Fuel Type
Engine Type
BSFC (g/kWh)
Source
SSD
185
23
MGO/MDO
MSD
205
23
ST
300
23
GT
300
23
Propulsion
SSD
195
23
RM/HFO
MSD
215
23
ST
305
23
GT
305
23
LNG
LNG
166
24
MGO/MDO
MSD
217
23
HSD
217
23
Auxiliary
RM/HFO
MSD
227
23
HSD
227
23
LNG
LNG
166
24
Boiler
MGO/MDO
Boiler
300
23
RM/HFO
305
23
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3.5.3 Particulate Matter (PM), Diesel Particulate Matter (DPM), and Black Carbon (BC)
PM io and DPMio C3 Gmission factors arG calculated for SSD and MSD propulsion and auxiliary engines
and boilers according to Equation 3.3:
EFPMio = PMbase + (Sact x BSFC x FSC x MWR) Equation 3.3
Where EFPMiq = PM 10 and DPMio emission factor adjusted for fuel sulfur (g/kWh)
PMbase = Base emission factor assuming zero fuel sulfur
= 0.1545 g/kWh for distillate fuel (MGO and MDO)
= 0.5761 g/kWh for residual fuel (RM and HFO)
Sact = actual fuel sulfur level (weight ratio)
= 0.001 for most vessel activity within the ECA in 2015 and beyond
= 0.027 for all vessel activity outside the ECA before 2020
= 0.005 for all vessel activity outside the ECA in 2020 and beyond
BSFC = brake specific fuel consumption (g/kWh) as calculated according to Section 3.5.2
FSC = fraction of sulfur in fuel that is converted to direct sulfate PM16
= 0.02247
MWR = molecular weight ratio of sulfate PM to sulfur
= 224/32 = 7
The base PMio emission factor assuming zero fuel sulfur is from the 2017 NEI.26 In the ECA, fuel is
required to have a maximum sulfur content of 0.1%. If local port data indicate that diesel with a sulfur
content less than 0.1% is being used, or if the inventory is being calculated for an earlier year than 2015,
the actual fuel sulfur level should be used in the Equation 3.3. If the port has a low sulfur fuel program
for OGV in the base year, the proportion of vessels using the lower sulfur fuel should be accounted for
when determining the actual fuel sulfur level. Additionally, if there is a formal commitment to
implement such a program in a future, projected future inventories should reflect the anticipated actual
fuel sulfur level.
Equation 3.3 is not used for ST, GT, and LNG engines. Instead, the PMio and DPMio emission factors for
these engines are presented in Table 3.7.
Table 3.7. PMio Emission Factors (g/kWh) for ST, GT, and LNG Engines on OGV
Fuel Type
Engine Type
PMio Emission
Factor (g/kWh)
DPMio Emission
Factor (g/kWh)
Source
MGO/MDO
ST
0.16
0.16
23
GT
0.01
0.01
23
RM/HFO
ST
0.93
0.93
23
GT
0.06
0.06
23
LNG
LNG
0.03
0.00
22
For all C3 engines, PM2.5 and DPM2.5 emission factors should be calculated as 92% of the PMio and DPMio
emission factors, respectively.16 BC emission factors should be calculated as 3% of PM2.5 emission
factors for C3 engines.27 28
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3.5.4 Volatile Organic Compounds (VOC), Carbon Monoxide (CO), and Methane (ChU)
Hydrocarbon (HC) and CO emission factors for vessels with C3 propulsion engines vary by engine group
and type and these factors are presented in Table 3.8. VOC and CH4 emission factors are derived from
the HC emission factors, as described below.
Table 3.8. Category 3 Vessel HC and CO Emission Factors (g/kWh)
Engine Group
Engine Type
HC Emission
Factor (g/kWh)
CO Emission
Factor (g/kWh)
Source
Propulsion
SSD
0.6
1.4
16
MSD
0.5
1.1
16
ST
0.1
0.2
16
GT
0.1
0.2
16
LNG
0.0
1.3
22
Auxiliary
MSD
0.4
1.1
20
HSD
0.4
0.9
20
LNG
0.0
1.3
22
Boiler
Boiler
0.1
0.2
20
VOC emission factors should be calculated as 1.053 times the HC emission factors.13 CH4 emission
factors should be calculated as 2% of HC emission factors.23
3.5.5 Nitrous Oxide (N2O)
N20 emission factors for vessels with C3 propulsion engines vary by engine group and type and these
factors are presented in Table 3.9.
Table 3.9. Category 3 Vessel N20 Emission Factors (g/kWh)
Engine Group
Fuel Type
Engine Type
N20 Emission Factor
(g/kWh)
Source
SSD
0.029
20
MGO/MDO
MSD
0.029
20
ST
0.075
20
Propulsion
GT
0.075
20
SSD
0.031
23
RM/HFO
MSD
0.031
23
ST
0.080
23
GT
0.080
23
MGO/MDO
MSD
0.029
20
Auxiliary
HSD
0.029
20
RM/HFO
MSD
0.031
23
HSD
0.031
23
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Engine Group
Fuel Type
Engine Type
N20 Emission Factor
(g/kWh)
Source
Boiler
MGO/MDO
Boiler
0.075
20
RM/HFO
0.080
23
Lacking better data on N20 emissions from LNG engines, this emission factor can be assumed to be the
same as that for SSD engines using MDO fuel: 0.029 g/kWh.
3.5.6 Carbon Dioxide (CO2)
C02 emission factors depend on BSFC rates and fuel type and should be calculated for vessels with C3
propulsion engines according to Equation 3.4:
EFCo2 = BSFC x CCF Equation 3.4
Where EFCq2 = C02 emission factor (g/kWh)
BSFC = brake specific fuel consumption (g/kWh) as calculated according to Section 3.5.2
CCF = carbon content factor,15 which varies by fuel type (g C02/g fuel)
= 3.206 for MGO/MDO
= 3.114 for RM/HFO
= 2.75 for LNG
3.5.7 Sulfur Dioxide (SO2)
S02 emission factors should be calculated according to Equation 3.5:
EFSo2 = BSFC x Sact x FSC x MWR Equation 3.5
Where EF
so2
BSFC
Sact
FSC
MWR
= S02 emission factor (g/kWh)
= brake specific fuel consumption (g/kWh) as calculated according to Section 3.5.2
= actual fuel sulfur level (weight ratio)
= 0.001 for most vessel activity within the ECA in 2015 and beyond
= 0.027 for all vessel activity outside the ECA before 2020
= 0.005 for all vessel activity outside the ECA in 2020 and beyond
= fraction of sulfur in fuel that is converted to S0216
= 0.97753
= molecular weight ratio of S02 to sulfur
= 64/32 = 2
If local port data indicate that diesel with a sulfur content less than 0.1% is being used, or if the
inventory is being calculated for an earlier year than 2015, the actual fuel sulfur level should be used in
Equation 3.5. If the port has a low sulfur fuel program for OGV in the base year, the proportion of
vessels using the lower sulfur fuel should be accounted for when determining the actual fuel sulfur level.
Additionally, if there is a formal commitment to implement such a program in a future, projected future
inventories should reflect the anticipated actual fuel sulfur level.
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3.6 Auxiliary Engine and Boiler Loads by Operating Mode
Auxiliary engines support electrical generators for auxiliary vessel power, and boilers provide heat and
steam on vessels for a variety of purposes/ Unlike propulsion engine loads (the calculation of which is
discussed in Sections 3.8 and 3.9), auxiliary engine and boiler usage cannot be obtained from vessel
activity data sets. In addition, these engines are generally not included in vessel characterization data
sets.
If resources allow, data on auxiliary engine and boiler usage can be directly collected from the vessels
operating in the geographical domain via surveys, interviews, or other data collection methods. If a
similar port has recently conducted an inventory and collected these kinds of data, those could be used
instead. Alternatively, the default auxiliary engine and boiler loads presented in the Third IMO
Greenhouse Gas Study15 can be used. These default values are presented in Appendix E by the operating
modes described below. Activity in each of the operating modes listed below is estimated in hours of
operation.
3.6.1 Transit
The transit operating mode covers vessels moving within the geographical domain, but outside the
breakwater8 or restricted speed zone. Auxiliary engine and boiler usage are generally low in this
operating mode.
3.6.2 Maneuvering
The maneuvering operating mode covers vessels moving between the breakwater and the
pier/wharf/dock or anchorage zone. OGV moving in this mode are frequently assisted by tugs or
towboats. If a vessel shifts between different piers/wharfs/docks or anchorage zones, it is usually
moving in this operating mode. Auxiliary and maneuvering thruster usage is expected to be high in this
operating mode, and boilers are also often used in this mode.
3.6.3 Restricted Speed Zone
The restricted speed zone operating mode generally covers vessels moving at speeds between those of
transit and maneuvering. Some restricted speed zones have enforced speed limits, whereas others are
voluntary. Not all ports have this operating mode (e.g., if the only area of the port with speed limits is
within the maneuvering area, it has the maneuvering operating mode and not the restricted speed zone
operating mode). Auxiliary engine and boiler usage in this operating mode is usually similar to the
transit operating mode.
3.6.4 Hotelling
The hotelling operating mode covers vessels that are moored, berthed, or docked at a pier/wharf/dock.
When hotelling, a vessel either uses its auxiliary engines and boilers, or it uses shore power if available
f Another group of engines that could be present on OGV are maneuvering thrusters, which provide transverse
propulsive forces for vessels and are also known as bow or stern thrusters. While engines that provide power to
maneuvering thrusters are regulated as propulsion engines, these loads are usually included in the auxiliary
engine loads for modeling purposes.
g The breakwater is a geographical marker for the change from open water to inland waterway. For ports that do
not have a physical breakwater, the point at which ships enter the restricted speed zone or where ships slow
down to start maneuvering operations should be used instead.
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and the ship is equipped to use it (this is also known as cold ironingh). Propulsion engines are not used
in this mode. Auxiliary engine and boiler usage in this operating mode is expected to be high if not using
shore power, particularly for self-unloading vessels.
3.6.5 Anchorage
This operating mode covers vessels that are at anchor. Many ports have specified anchorage zones.
While at anchor, a vessel uses its auxiliary engines and boilers; propulsion engines are not used in this
mode. Auxiliary engine and boiler usage in this operating mode varies by ship type and size.
3.7 Low Load Adjustment Factors
The propulsion engine emission factors presented in Section 3.5 assume that the vessel's propulsion
load is more than 20% of its total installed propulsion power. Below that threshold, emissions per unit
of energy tend to increase as the engine load decreases. This is because diesel engines are less efficient
at low loads and BSFC tends to increase. To account for this, low load adjustment factors (LLAFs) should
be applied when the propulsion engines are operating at less than 20% load. Table 3.10 presents LLAF
by propulsion engine load and pollutant.16 Sections 3.8 and 3.9 discuss how these LLAFs should be
incorporated in the inventory calculations in further detail.
The PM low load adjustment applies to PMio, PM2.5, DPM10, DPM2.5, and BC emissions. The NOx
adjustment also applies to N20 emissions, and the HC adjustment also applies to VOC and CH4
emissions. Note that the S02 LLAF depends on the fuel sulfur content. If a fuel with a sulfur level other
than 0.1% is used, use the equations in Appendix F to calculate the S02 LLAF. These equations were
used to generate the factors in this table.
Additionally, note that there is no LLAF for BSFC; instead, the adjustments are applied separately for
each pollutant.
Table 3.10. C3 Propulsion Engine Low Load Adjustment Factors (unitless)
Propulsion Engine
Load Factor
NOx
HC
CO
PM
C02
S02 (0.1% fuel
sulfur content)
< 2%
4.63
21.18
9.68
7.29
3.28
9.54
3%
2.92
11.68
6.46
4.33
2.44
6.38
4%
2.21
7.71
4.86
3.09
2.01
4.79
5%
1.83
5.61
3.89
2.44
1.76
3.85
6%
1.60
4.35
3.25
2.04
1.59
3.21
7%
1.45
3.52
2.79
1.79
1.47
2.76
8%
1.35
2.95
2.45
1.61
1.38
2.42
9%
1.27
2.52
2.18
1.48
1.31
2.16
10%
1.22
2.20
1.96
1.38
1.25
1.95
11%
1.17
1.96
1.79
1.30
1.21
1.78
h Shore power is a strategy to reduce auxiliary engine emissions while a ship is dockside by "plugging in" to
electrical power sources on shore. For more information, see reference 25.
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Propulsion Engine
Load Factor
NOx
HC
CO
PM
C02
S02 (0.1% fuel
sulfur content)
12%
1.14
1.76
1.64
1.24
1.17
1.63
13%
1.11
1.60
1.52
1.19
1.14
1.51
14%
1.08
1.47
1.41
1.15
1.11
1.41
15%
1.06
1.36
1.32
1.11
1.08
1.32
16%
1.05
1.26
1.24
1.08
1.06
1.24
17%
1.03
1.18
1.17
1.06
1.04
1.17
18%
1.02
1.11
1.11
1.04
1.03
1.11
19%
1.01
1.05
1.05
1.02
1.01
1.05
> 20%
1.00
1.00
1.00
1.00
1.00
1.00
Auxiliary and electric drive (MSD-ED or GT-ED) engines do not need this adjustment factor because of
the way they are generally operated: when only low loads are needed, one or more engines are shut off,
allowing the remaining engines to maintain operation at a more efficient level. Additionally, LLAFs are
not applied to boilers.
3.8 AIS Inventory Calculations
A detailed emissions inventory can be calculated using AIS activity data from the base year. In general,
the base year inventory calculation is done at the AIS record level through the following steps:
1. Link each AIS record to vessel characteristic data
2. Clean AIS data
3. Fill temporal gaps in AIS activity
4. Calculate propulsion engine operating power and load factor
5. Assign operating mode
6. Calculate propulsion engine emissions
7. Calculate auxiliary engine and boiler emissions
8. Aggregate emissions
9. Perform quality control checks
The subsections below explain each of these steps in further detail.
3.8.1 Link Each AIS Record to Vessel Characteristic Data
Each AIS record contains vessel identification fields that can be used to link the AIS activity data to vessel
characteristic data. This is important not only for calculating emissions, but also for data cleaning and
quality control steps as well. Section 3.3 describes how vessel identifiers can be used to determine the
engine and vessel characteristics, and how to fill missing vessel characteristic data.
3.8.2 Clean AIS Data
It is not uncommon for AIS data to contain errors or extraneous data that need to be identified and
addressed before emissions can be calculated. The source of the AIS data will affect the amount of data
cleaning that will be involved. Some AIS vendors include data cleaning in their processes, while others
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supply raw data that need more cleaning. While this is not a comprehensive list of all AIS data cleaning
procedures, the following list describes commonly performed cleaning steps:
• Remove records for vessels that are not identified as OGV operating within the geographical
boundary. Note that these records may be useful for a harbor craft or recreational marine
inventory, but not an OGV inventory.
• Remove records where the coordinates appear outside the inventory's geographical boundary.
• Remove duplicate records (records with identical timestamps and vessel identifiers).
• Remove records with speeds above 1.5 times the service speed of the vessel.
Depending on the purposes of the emissions inventory, additional data processing at this phase may be
desired. For example, if an inventory needs to differentiate between vessels that call at the port and
innocent passage, AIS records will need to be marked accordingly. This step can be processed in
different ways:
• Matching AIS records to local logs, Entrances & Clearances data, or Waterborne Commerce data,
or
• Identifying individual vessel trips in the AIS records, geofencing berths within the geographical
boundary, and flagging every record in the trip if any of the records show the vessel entering
them.
3.8.3 Fill Temporal Gaps in AIS Activity
Temporal gaps between AIS records may occur for a variety of reasons, including:
• The vessel left the geographical domain
• The vessel's AIS transponder malfunctioned or was turned off
• Records were removed as part of the cleaning process described above
A gap due to a vessel leaving the geographical domain can be identified by extrapolating vessel activity,
assuming a constant speed and heading from the last record before the gap. If the extrapolated position
is outside the geographical domain, then the gap should not be filled, and emissions should not be
calculated for it. However, gaps occuring for other reasons should be filled in by interpolating location,
speed, and draft data at the expected frequency of the AIS records (e.g., if the AIS data has been
aggregated to 5-minute intervals, the gaps should be filled in by interpolating the data at 5-minute
intervals).
After filling the temporal gaps, each AIS record can be assumed to represent the same time interval
(e.g., 5 minutes), which will be used when calculating the emissions of each record as described in the
following sections.
3.8.4 Calculate Propulsion Engine Operating Power and Load Factor
Propulsion engine operating power and load factor should be calculated for each AIS record. There are
several methods that can be used to estimate a vessel's propulsion engine operating power. One such
method is the propeller law, which estimates that propulsion engine operating power varies with the
cube of vessel speed.29 While this does not account for vessel draft or hull resistance, which can
significantly affect ship propulsion load, it relies on few vessel characteristics and is easy to calculate.
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The propeller law can be used to estimate a vessel's operating power for each AIS record as shown in
Equation 3.6:
Pp = Pref x Equation 3.6
Where Pp = propulsion engine operating power (kW)
Pref = vessel's total installed propulsion power (kW)
V = AlS-reported speed before the record interval (kn)
Vref = vessel's service speed (kn)
An improvement on the propeller law is the admiralty formula,15 which also includes terms for the
impact of draft on propulsion power as shown in Equation 3.7:
Pp = P„/X(J_)3x(_£.)3 Ration 3,
Where Pp = propulsion engine operating power (kW)
Pref = vessel's total installed propulsion power (kW)
V = AlS-reported speed before the record interval (kn)
Vref = vessel's service speed (kn)
D = AlS-reported draft before the record interval (m)
Dref = vessel's maximum draft (m)
The admiralty formula is preferred over the propeller law when the vessel's draft is known.1 If it is
unavailable, the vessel can be assumed to be operating at maximum draft, in which case the propeller
law and admiralty formula yield the same result, as the propeller law is an upper bound for the
admiralty formula.
Regardless of which method is used to calculate the instantaneous power, the chosen method should be
clearly indicated in the documentation for the resulting inventory. In addition, the maximum limit of the
result should be set to the vessel's total installed propulsion power (Pref), such that its load factor does
not exceed 100%. Load factor describes how much power an engine is producing as a fraction of its
maximum rated power. It is also used to determine the vessel's operating mode (see Section 3.8.5) and
to determine if low load adjustment factors need to be applied when calculating propulsion engine
emissions. The propulsion engine load factor should be calculated for each AIS record as shown
Equation 3.8:
Pp
LF = —— Equation 3.8
Pref
Where LF = propulsion engine load factor (unitless)
1 There are other methods available to estimate propulsion engine load based on vessel hull resistances. However,
the admiralty formula provides a reasonable estimate of engine load using few vessel parameters and is
therefore the preferred approach for individual port inventories.
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Pp = propulsion engine operating power for each AIS record (kW), from Equation 3.6 or
Equation 3.7
Pref = vessel's total installed propulsion power (kW)
3.8.5 Assign Operating Mode
The ship's operating mode should be determined for each AIS record, as this information is used when
calculating emissions as described in Sections 3.8.6 and 3.8.7. This is best done considering both
geographical and speed data from each AIS record, because operating modes are generally associated
with certain locations within the port. To help determine operating mode, each area of interest within
the port where specific operating modes are observed (e.g., the maneuvering area between the
breakwater and each pier/wharf/dock) can be defined as a polygon using geographic information
system (GIS) software. Each AIS record can then be flagged according to the area of interest where it
appears, so this information can be considered along with speed and load in determining operating
mode. General considerations for determining a vessel's operating mode for each AIS record are listed
in Table 3.11.
Table 3.11. Considerations for Determining Operating Mode
Operating Mode
Geospatial
Considerations
General Speed
Considerations
General Propulsion Engine
Load Factor Considerations
Transit
Outside the breakwater
or restricted speed zone
> 3 kn
> 20%
Maneuvering
Between the breakwater
and pier/wharf/dock or
anchorage zone
> 1 kn
< 20%
Restricted Speed Zone
Varies by port
Varies by port
Varies by port
Hotelling
At a pier/wharf/dock
< 1 kn
N/A
Anchorage
In an anchorage zone
<3 kn
N/A
3.8.6 Calculate Propulsion Engine Emissions
Propulsion engine emissions are calculated for each time interval between consecutive AIS records for
each vessel using Equation 3.9:
Ep = Pp x A x EF x LLAF Equation 3.9
Where Ep
= propulsion engine emissions for each AIS record (g)
Pp
= propulsion engine operating power for each AIS record (kW), from Equation 3.6 or
Equation 3.7
A
= time interval between consecutive AIS records (h)
EF
= emission factor (g/kWh)
LLAF
= low load adjustment factor determined for each AIS record (unitless)
Propulsion engine emission factors (as described in Section 3.5) should be assigned to each vessel based
on its engine characteristics and the actual sulfur level of the fuel used. If the load factor for an
individual AIS record is less than 20%, the low load adjustment factors should be applied as described in
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Section 3.7. Note that propulsion engine emissions should only be calculated for AIS records that are
determined to be in the transit, maneuvering, or restricted speed zone operating modes (i.e., propulsion
engines can be assumed to be off while hotelling or at anchor).
These emissions can be then aggregated at the most useful level for the purposes of the inventory. This
process is discussed in further detail in Section 3.8.8.
3.8.7 Calculate Auxiliary Engine and Boiler Emissions
Auxiliary engine and boiler emission factors should be assigned to each vessel based on the actual sulfur
level used in the geographical domain as described in Section 3.5. Then, auxiliary engine and boiler
loads should be estimated for each operating mode as described in Section 3.6. With this information,
emissions for auxiliary engines should be calculated for each time interval between consecutive AIS
records for each vessel using Equation 3.10:
Ea = Pax Ax EF Equation 3.10
Where Ea = auxiliary engine emissions for each AIS record (g)
Pa = auxiliary engine operating power for each AIS record based on operating mode (kW)
A = time interval between consecutive AIS records (h)
EF = emission factor (g/kWh)
Emissions for boilers should be calculated for each time interval between consecutive AIS records for
each vessel using Equation 3.11:
Eb = Pb x A x EF Equation 3.11
Where Eb = boiler emissions for each AIS record (g)
Pb = boiler load for each AIS record based on operating mode (kW)
A = time interval between consecutive AIS records (h)
EF = emission factor (g/kWh)
3.8.8 Aggregate Emissions
Total emissions for each time interval between consecutive AIS records should be calculated using
Equation 3.12:
E = Ep + Ea + Eb Equation 3.12
Where E = total emissions for each AIS record (g)
Ep = propulsion engine emissions for each AIS record (g) from Equation 3.9
Ea = auxiliary engine emissions for each AIS record (g) from Equation 3.10
Eb = boiler emissions for each AIS record (g) from Equation 3.11
The total emissions at the AIS record level can then be aggregated to the most useful level for the
purposes of the inventory:
• For an annual inventory without a need for spatial considerations, all emissions of a particular
pollutant can be summed together. Note that even for annual inventories, reporting more
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detailed emissions in addition to the annual results can be useful as described below in Section
3.8.9.
• If the inventory has a spatial component to it, the emissions calculated at the AIS record level
should be allocated to the location of the record before the interval. These emissions can then
be aggregated to the most useful spatial resolution for the purpose of the inventory (e.g., 100
m2 grid cells for a detailed analysis or summed for the entire port for planning purposes).
• Similarly, if the inventory has a temporal component to it, the emissions calculated at the AIS
record level should be allocated to the timestamp of the record before the interval. These
emissions can then be aggregated to the most useful resolution for the purpose of the inventory
(e.g., at the hourly level for a detailed analysis).
3.8.9 Perform Quality Control Checks
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of vessel activity and emissions for an inventory. An inconsistency in one check that is
not reflected in others is indicative that additional scrutiny of input data sets and calculations may
reveal useful insights. Likewise, an anomaly that shows up in several checks may suggest an issue with
input data or methodology implementation. Note that unless otherwise specified, the analytical
calculations listed below should be aggregated by ship type. The following distributions and metrics are
useful to examine as quality control checks and to facilitate comparisons between different inventories:
• Distributions of vessel speed, vessel draft, and propulsion load factor: Examining these
distributions allow for general checks to ensure that vessels are modeled to be operating within
reasonable limits and with expected patterns of behavior. For example, tankers often have a bi-
modal draft distribution, which reflects activity where a full vessel offloads its cargo and then
departs empty.
• Vessel counts, number of trips, and total operating hours: Examining these values provides an
estimate of the scale of vessel activity contributing to the inventory and for enabling cross-
comparisons with other inventories.
• Installed power: Examining this helps to estimate the relative impact that a given ship type
should have on the inventory. For example, container ships tend to have relatively large
engines, and so may contribute more emissions than their activity might otherwise suggest.
• Hotelling hours and anchorage hours by ship subtype: Examining both totals and distributions
provides an estimate of the scale of vessel activity contributing to the inventory and for enabling
cross-comparisons with other inventories.
• Total energy consumption (kWh) for propulsion engines and for auxiliary engines: Examining
energy consumption by ship type and engine group provides an estimate of the scale of vessel
activity contributing to the inventory and for enabling cross-comparisons with other inventories.
Other quality control checks include:
• Comparing the distribution of propulsion load factor with relative vessel speed (i.e., speed
divided by service speed): This is a normalized map of engine load vs. vessel speed, with both
axes ranging from 0 to 1, and it should show a roughly cubic relationship between these
parameters.
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• Examining geospatial heatmaps of energy consumption: This helps identify if there are gaps in
the AIS data, or if there are anomalies in the data such as vessels being allocated to land or
shallow regions where they should be unable to operate.
• For annual inventories, examining emissions per day by ship type over the course of the year:
This helps identify anomalies in input data that significantly impact emissions over a short
period of time. For example, if a ship is in harbor for an extended period (i.e., much longer than
it normally takes to load/unload a ship of its size), its auxiliary engines are not likely running the
entire time. If this case is not correctly handled when filling temporal gaps (as discussed in
Section 3.8.3), examining emissions by ship type as a time series may show changes of several
orders of magnitude that warrant a closer review. Similarly, if a local AIS receiver experiences
data recording issues, no AIS messages may be logged, which could have a significant impact on
emissions calculated for the duration.
• Searching for transitions between operating modes that are unlikely: This check at the AIS
record level for transitions such as going from hotelling directly to transit can identify anomalies
in the data that warrant a closer review.
• Searching for rapid toggling between modes: This check at the AIS record level for irregularities
such as switching between hotelling and maneuvering too frequently can identify anomalies in
the data that warrant a closer review.
3.9 Alternative Inventory Calculations
If AIS data or the resources to process them are unavailable, an alternative method may be used to
calculate a base year emissions inventory. This method relies on using the same vessel characteristics
and emission factors as described above; however, the derivation of ship activity and propulsion power
are different. In general, the emissions calculation is performed at the vessel trip level through the
following steps:
1. Link each vessel call record to vessel characteristic data
2. Calculate activity by operating mode
3. Calculate propulsion engine operating power and emissions
4. Calculate auxiliary engine and boiler emissions
5. Aggregate emissions
6. Perform quality control checks
The subsections below explain each of these steps in further detail.
3.9.1 Link Each Vessel Call Record to Vessel Characteristic Data
In the alternative method, the primary data sources for vessel activity are local logs (vessel call records
from the local port authority, marine exchange, board of trade, or other local organization); Entrances
and Clearances data; and Waterborne Commerce data. These sources generally have vessel
identification data that can be used to link the activity record to vessel characteristic data. Section 3.3
describes how the vessel identifiers can be used to determine the engine and vessel characteristics, and
how to fill missing vessel characteristic data. If local logs are used in conjunction with Entrances and
Clearances and Waterborne Commerce, the data should be combined appropriately so that vessel calls
are not double counted. For example, if an individual vessel call appears in more than one data set,
emissions associated with this vessel call should still be counted only once.
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Similarly, if alternative inventory calculations are performed to supplement an AIS analysis (e.g., if there
is not full AIS data coverage), care will need to be taken to avoid vessel calls being double counted.
3.9.2 Calculate Activity by Operating Mode
Hours of engine operation need to be estimated for each vessel call by the various operating modes that
a typical vessel call includes. The best source for this information is usually AIS data (see Section 3.8 for
calculating inventories from AIS data). However, information from interviewing pilots and/or surveying
vessels operating within the area of interest can also provide valuable data for these estimations.
Many variables affect one or more time-in-mode calculations. These variables cannot be accurately
predicted for a ship type category over an entire year of calls. Traffic conditions, weather, vessel
schedule, and current all affect how much time is spent in each operating mode. For example:
• Traffic conditions may make travel in the waterway slower because a wake is more damaging in
a congested waterway, forcing vessels to be more careful and travel at slower speeds. In
addition, docking at a pier/wharf/dock takes much longer on busy days, resulting in more time
spent in the maneuvering operating mode.
• Bad weather in the form of high winds causes vessel maneuvering to be more difficult and less
predictable. Rain and fog obscure visibility and can significantly reduce a vessel's maximum
speed. Like congested conditions, bad weather increases the time it takes for vessels to dock,
resulting in more time spent in the maneuvering operating mode.
• River or strait currents can also impact travel speeds, time-in-mode, and propulsion engine
loads, depending on the direction of travel.
• Vessel schedule also affects time-in-mode. If a vessel is ahead of schedule, it may travel at
slower speeds to conserve fuel and arrive closer to schedule. Conversely, if a vessel is behind
schedule, it may travel at the maximum allowed speed to get back on schedule.
When calculating averages for time-in-mode by ship type, the effects of these types of issues should be
included to ensure the averages are representative of annual activity. The following subsections provide
additional information on how hours of operation can be estimated for each operating mode, which
typically vary by ship type.
3.9.2.1 Transit
For each call, it can be assumed that each vessel is in the transit operating mode twice: once when it
enters the area of interest and approaches the breakwater or restricted speed zone, and again when it
leaves the breakwater or restricted speed zone. Local data sources may be able to provide transit
speeds. If these are unavailable, average transit speeds derived by EPA from national 2017 AIS data can
be used instead. Table 3.12 presents the most common transit speeds normalized by the vessel's
service speed.
Table 3.12. Mode of National Transit Speed Ratios by Ship Type
Ship Type
Mode of Transit Speed Ratios
Bulk Carrier
0.81
Chemical Tanker
0.86
Container Ship
0.79
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Ship Type
Mode of Transit Speed Ratios
Cruise
0.80
Ferry/Passenger (C3)
0.99
Ferry/Roll-on/Passenger (C3)
0.99
Fishing (C3)
0.79
General Cargo
0.72
Liquified Gas Tanker
0.86
Miscellaneous (C3)
0.79
Offshore Support/Drillship
0.87
Oil Tanker
0.88
Other Tanker
0.83
Reefer
0.85
RORO
0.78
Yacht(C2/C3)
0.61
The typical distance traveled at this speed can be determined from typical shipping routes that are
within the area of interest but outside the breakwater or restricted speed zone. Hours of operation in
the transit operating mode per vessel call can then be calculated by dividing the distance traveled by the
vessel speed.
3.9.2.2 Restricted Speed Zone
If a port has a restricted speed zone, it can be assumed that each vessel is in this operating mode twice:
once on its way into the port, and once on its way out. Pilots can generally report the average vessel
speed for restricted speed zones; however, lacking this data, a conservative estimate is to assume the
vessels travel at the maximum speed allowed in the restricted speed zone. The typical distance traveled
at this speed can be determined from typical shipping routes. Hours of operation in this operating mode
per vessel call can then be calculated by dividing the distance traveled by the vessel speed.
If the restricted speed zone's speed limit is part of a voluntary program to reduce emissions, using AIS
data and following the approach discussed in Section 3.8 would allow for more precision and result in a
more valuable analysis of emissions in the restricted speed zone.
3.9.2.3 Maneuvering
For each call, it can be assumed that each vessel is in the maneuvering operating mode at least twice:
once on its way into the port, and once on its way out. Average maneuvering speeds vary depending on
direction and ship type (generally, outbound speeds are greater because the vessel does not need to
dock). The speeds also depend on the location and the approach to the destination terminal and the
turning requirements of the vessel. Because of the expected variance in maneuvering speeds by ship
type and size, these speeds should be estimated based on conversations with pilots. The typical
distance traveled in this operating mode can be estimated as the average distance from the breakwater
to each pier/wharf/dock. Hours of operation in this operating mode per vessel call can then be
calculated by dividing the distance traveled by the vessel speed.
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If the local logs also include information on vessel shifts (when a vessel moves from one pier/wharf/dock
to another, typically at a different terminal), this can be used to determine additional maneuvering time.
3.9.2.4 Hotel ling
The hours of operation in the hotelling operating mode can usually be determined from the local logs.
They can be determined directly if the logs include timestamps when a vessel entered and left its berth.
Other logs keep track of when a vessel enters and exits the breakwater. In this case, hours of hotelling
can be calculated by determining the total time a vessel spent in port and subtracting time spent in the
maneuvering operating mode. Lacking these data sources, hotelling times can also be determined from
pilot records of vessel arrival and departure times. Hotelling times should be calculated separately for
ships that are using shore power or other methods of reducing hotelling emissions and those that are
not.
3.9.2.5 Anchorage
If possible, anchorage time (where a vessel is at anchor, but not at a pier/wharf/dock) should be
determined separately from the hotelling operating mode. If these data are not available in the local
logs, these may possibly be determined from pilot interviews.
3.9.3 Calculate Propulsion Engine Operating Power and Emissions
First, propulsion engine emission factors should be assigned to each vessel based on its engine
characteristics and the actual sulfur level of the fuel used, as described in Section 3.5. Then, the
propulsion engine operating power should be calculated for each vessel call and for each of the transit,
reduced speed zone, and maneuvering operating modes. Finally, a low load adjustment factor should
be assigned if necessary.
3.9.3.1 Propulsion Engine Operating Power
Several methods can be used to estimate a vessel's propulsion engine operating power. One method is
the propeller law, which estimates that propulsion engine load varies with the cube of vessel speed.29
While this does not account for vessel draft or hull resistance, which can significantly affect ship
propulsion power, it relies on few vessel characteristics and is easy to calculate. The propeller law can
be used to estimate a vessel's operating power for each of the transit, reduced speed zone, and
maneuvering operating modes as shown in Equation 3.13:
Where Pp j = propulsion engine operating power for operating mode i (kW)
Pref = vessel's total installed propulsion power (kW)
Vi = average speed in operating mode i (kn)
Vref = vessel's service speed (kn)
If either V\ or Vref are unknown, the transit speed ratios presented in Table 3.12 can be used in place of
the Vi/Vref term in Equation 3.13 (i.e., the values in the table should be cubed and multiplied by the
vessel's total installed propulsion power to determine the vessel's operating power for the transit
operating mode). If a vessel's draft is known, EPA recommends using the admiralty formula instead, as
described in Section 3.8.4. Regardless of which method is used to calculate the propulsion engine
Equation 3.13
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operating power, the maximum limit of the result should be set to the vessel's total installed propulsion
power.
3.9.3.2 Calculating Load Factor and Determining Low Load Adjustment Factor
To determine if low load adjustment factors need to be applied, the propulsion engine load factor
should be calculated at each operating mode as shown in Equation 3.14:
p .
LFi = —— Equation 3.14
'ref
Where LFt = propulsion engine load factor for operating mode i (unitless)
Pp i = propulsion engine operating power for operating mode i (kW)
Pref = vessel's total installed operating power (kW)
If the load factor is less than 20%, the low load adjustment factors should be applied as described in
Section 3.7.
3.9.3.3 Calculating Propulsion Engine Emissions
Propulsion engine emissions are calculated for each vessel call and for each of the applicable operating
modes using Equation 3.15:
Ep i = Pp i x At x EF x LLAFi Equation 3.15
Where Ep^ = propulsion engine emissions for operating mode i (g)
Pp i = propulsion engine operating power for operating mode i (kW)
Ai = time spent in operating mode i (h)
EF = emission factor (g/kWh)
LLAF = low load adjustment factor for operating mode i (unitless)
These emissions can be then aggregated at the most useful level for the purposes of the inventory. This
process is discussed in further detail in Section 3.9.5.
3.9.4 Calculate Auxiliary and Boiler Emissions
First, auxiliary engine and boiler emission factors (as described in Section 3.5) should be assigned to
each vessel based on its engine characteristics and the actual sulfur level of the fuel used. Then,
auxiliary engine and boiler loads should be estimated for each operating mode as described in Section
3.6. Emissions for auxiliary engines should be calculated for each vessel call and for each operating
mode using Equation 3.16:
Ea,i = Pa,i xAiXEF Equation 3.16
Where Ea^ = auxiliary emissions for operating mode i (g)
Pa i = auxiliary engine operating power for operating mode i (kW)
Ai = time spent in operating mode i (h)
EF = emission factor (g/kWh)
Emissions for boilers should be calculated for each vessel call and for each operating mode using
Equation 3.17:
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Eb,i = Pbi xAiXEF Equation 3.17
Where Eb^ = boiler emissions for operating mode i (g)
Pbi = boiler load for operating mode i (kW)
Ai = time spent in operating mode i (h)
EF = emission factor (g/kWh)
3.9.5 Aggregate Emissions
Total emissions for each vessel should be calculated by operating mode using Equation 3.18:
Ei = EP,i + Ea,i + Eb,i Equation 3.18
Where Ei = total emissions by vessel for operating mode i (g)
Ep i = propulsion engine emissions for operating mode i (g)
Ea i = auxiliary engine emissions for operating mode i (g)
Eb i = boiler emissions for operating mode i (g)
The total emissions for each vessel can then be aggregated to the most useful level for the purposes of
the inventory:
• For an annual inventory without a need for spatial considerations, all emissions of a particular
pollutant can be summed together. Note that even for annual inventories, reporting more
detailed emissions in addition to the annual results can be useful as described below in Section
3.9.6.
• If the inventory has a spatial component to it, emissions by operating mode should be assigned
as appropriate to shipping lanes or specific berths. Transit, restricted speed zone, and
maneuvering emissions should be assigned to the typical path that vessels take entering and
exiting port; hotelling and anchorage emissions should be assigned to the appropriate
pier/wharf/dock or anchorage zone, respectively.
• If the inventory has a temporal component to it, the purpose of the inventory will direct the
resolution needed. Because the vessel activity data used in the alternative inventory
calculations are not as finely detailed as AIS, additional assumptions may need to be made to
allocate emissions to a finer level of detail. In general, the temporal dimension of emissions by
operating mode should be based on the timestamp of the vessel call offset by the time spent in
the other operating modes.
3.9.6 Perform Quality Control Checks
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of vessel activity and emissions for an inventory. An inconsistency in one check that is
not reflected in others is indicative that additional scrutiny of input data sets and calculations may
reveal useful insights. Likewise, an anomaly that shows up in several checks may suggest an issue with
input data or methodology implementation. Note that unless otherwise specified, the analytical
calculations listed below should be aggregated by ship type. The following distributions and metrics are
useful to examine as quality control checks and to facilitate comparisons between different inventories:
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• Vessel speeds and operating hours by operating mode: Examining these values allow for
general checks to ensure that vessels are modeled to be operating within reasonable limits and
with expected patterns of behavior.
• Vessel counts and number of trips: Examining these values provides an estimate of the scale of
vessel activity contributing to the inventory and for enabling cross-comparisons with other
inventories.
• Installed power: Examining this helps to estimate the relative impact that a given ship type
should have on the inventory. For example, container ships tend to have relatively large
engines, and so may contribute more emissions than their activity might otherwise suggest.
• Total energy consumption: Examining energy consumption provides an estimate of the scale of
vessel activity contributing to the inventory and for enabling cross-comparisons with other
inventories.
• Outliers in hotelling times: Checking for vessels with abnormally long hotelling times is useful,
because it may not be appropriate to include these when calculating averages as they may
represent ships at a pier/wharf/dock that may not be running auxiliary engines for the entire
time.
3.10 Projecting Future Emission Inventories
Future OGV emissions should be projected from a base year inventory, developed as described in the
sections above. In general, the projection process follows these steps:
1. Activity growth rates are applied to the base year activity to estimate future activity
2. Vessel keel-laid dates are adjusted to account for fleet turnover to newer, cleaner engines and
emission factors are reassigned
3. Projected emissions are calculated using the estimated future activity
4. Projected emissions are aggregated to the same level of detail as the base year inventory, as
determined by the purpose of the inventory
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations. Projected changes in activity should
be determined for each ship type. Local port projections or other regional forecasts are usually by
commodity type and/or business sector; growth can be grouped by the ship types that carry the various
commodities.
If local port projections or other regional forecasts are unavailable, the Freight Analysis Framework
(FAF)11 can be used to forecast growth instead. If this is used, the commodity flows in the FAF assigned
to the water transportation mode should be grouped by the appropriate ship type. For example, all
commodity types that can be containerized should be included when determining the container vessel
growth rates.J
The growth rates should be applied to the base year activity. If the original base year inventory was
developed using AIS data, the growth rate for the appropriate ship type should be applied to the activity
(kilowatt-hours) calculation for each AIS record. If the original inventory was developed using alternate
J See Table K.l in Appendix K for a description of common conveyance types by commodity type.
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sources of vessel activity, the growth rate should be applied to the hours of activity for each vessel in
each operating mode.
To reflect fleet turnover, the vessel keel-laid dates used in the base year inventory should be adjusted
for use in the future year inventory. If the port or local fleet operator has already identified an expected
future age distribution, that should be used in determining how to adjust the keel-laid dates. If the
future age distribution is unknown, it can be assumed to be the same as the base year age distribution.
That is, it can be assumed that in the future, the percentages of vessels that are brand new, one year
old, two years old, etc. are the same as those percentages in the base year inventory. Functionally, this
can be implemented by adding the difference between the future and base years to each keel-laid date
used in the base year inventory, to get a new set of keel-laid dates for the future year inventory. For
example, if the base year inventory is for 2020 and the projected inventory is for 2030, the difference of
10 years is added to each keel-laid year. In this example, a keel-laid year 2005 vessel in the base year
inventory would be a keel-laid year 2015 vessel in the 2030 inventory. Emission factors should be
reassigned to all vessels using the adjusted keel-laid dates.k
Additionally, any planned action or emission reduction strategies that have been committed to that
would affect future emissions should be included according to the actual expected implementation of
such commitments. For example, if a port has committed to encouraging the use of LNG through
authorization of funds for such a program, the target percentage of vessels using LNG should be used
when assigning emission factors. Note that if the future year inventory is for a regulatory purpose,
planned future actions should be included only if written commitments have been made by the agency
or operator with the power to implement them.
Once the base year activity has been scaled and appropriate emission factors are assigned to each
vessel, the projected future emissions can be calculated using the same methodology at the same level
of detail as the base year inventory.
k Note that there is uncertainty regarding the implementation of Tier III, which reduces NOx emissions from
engines on ocean-going vessels, both domestic and foreign. EPA may revise this document in the future to
improve the modeling of NOx emissions from these engines when more is known about the implementation of
Tier III.
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U.S. Environmental Protection Agency
4 Harbor Craft
2020 Public Draft
4.1 Source Description
The harbor craft source sector covers all commercial marine vessels that are not ocean-going vessels
(OGV). Unlike OGV, harbor craft typically spend most of their operating time in or near a single port or
region. These vessels typically have Category 1 (CI) or Category 2 (C2) engines3 and use distillate diesel
fuel. While the methodologies listed in this section are generally similar to those described in the OGV
section, this source sector focuses on commercial vessels that have different travel patterns than OGV.
This distinction is important because harbor craft are frequently part of captive fleets owned by the port
or a company operating them within the port or regional area, and their data sources and strategies for
reducing their emissions can be different from the other source sectors. Table 4.1 lists the various ship
types that comprise the harbor craft source sector. Note that there may be specialized types of harbor
craft that do not appear on this list. The harbor craft source sector includes barges and other vessels
that are not self-propelled. However, it does not include any vessels with gasoline engines or
recreational diesel vessels; these are discussed in Section 5.b
In general, emissions from all harbor craft operating within the geographical domain for the inventory
should be estimated. However, taking this approach may include innocent passage emissions, which are
emissions that occur from vessel activity not related to the port(s) for which the inventory is being
calculated (i.e., vessels just passing through the geographical domain). For the harbor craft source
sector, innocent passage emissions are generally limited to barges moving through the geographical
domain. Depending on the purpose of the inventory, it may be important to quantify emissions from
innocent passage separately from all other harbor craft. See Section 2 of this document for more
discussion about inventory purpose, geographical domains, and temporal detail.
Harbor craft typically have two kinds of emission sources:
• Propulsion engines, also referred to as main engines, which supply power to move the vessel
• Auxiliary engines, which supply power for non-propulsion loads
Table 4.1. Harbor Craft Ship Types
Ship Type
Description
Barge
Flat-bottomed vessels used to transport goods; typically not self-propelled,
but may have auxiliary engines
Crew and Supply
Passenger vessels used to carry personnel and supplies to and from offshore
and in-harbor locations
Dredging
Vessels that perform or assist in performing dredging activities
Excursion
Passenger vessels typically engaged in partial- or single-day specialty cruises
a Category 1 and 2 engines are marine engines with less than 30 liters displacement per cylinder (approximately 8
gallons).
b Note, some diesel vessels may appear to be recreational but are considered commercial for the purposes of the
national marine diesel engine regulatory program. As explained in Section 5, the decision on whether to include
these vessels with the commercial inventory may depend on local usage patterns.
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Ship Type
Description
Fishing (C1/C2)*
CI or C2 vessels used in commercial fishing operations
Government
Coast Guard, police, fire, or other government-owned vessels
Harbor Ferry (C1/C2)
Commercial CI or C2 vessels used for passenger transport
Miscellaneous (C1/C2)
Commercial CI or C2 vessels not otherwise designated in this list
Pilot
Vessels used to transport pilots to or from OGV
Towboat/Pushboat
Vessels used to push barges and pontoons; typically used in harbors and
inland waterways
Tug Boat
Vessels that assist maneuvering other vessels; can be used in open sea, inland
waterways, and harbors
Work Boat
Vessels used for utility, inspection, survey, spill response, research, mining,
training, and construction
* C1/C2 in a ship type designates that emissions from vessels of the specified ship type should be estimated
according to the methodologies presented in this section if they have CI or C2 propulsion engine(s). If they
have C3 propulsion engine(s), their emissions should be estimated according to the methodologies presented
in Section 3.
4.2 Emissions Estimation Overview
Harbor craft base year emissions from both propulsion and auxiliary engines can be determined for each
vessel using Equation 4.1:
E = PxLFxAxEF Equation 4.1
Where E = per vessel emissions (g)
P = engine power (kW)
LF = engine load factor (unitless)
A = engine operating activity (h)
EF = emission factor (g/kWh)
Each of the above parameters vary by vessel and emission source (propulsion or auxiliary engine).
Therefore, it is important to accurately account for vessel characteristics (discussed in Section 4.3) and
activity (Section 4.4) to ensure the operating power and hours are calculated correctly and that the right
emission factors (Section 4.5) are applied to this activity.
There are different modeling methods that can be used to estimate harbor craft emissions for a base
year emissions inventory depending on data and resource availability. The two methods described in
this document are an Automatic Identification System (AIS) based approach (Section 4.7) and an
alternative approach based on estimated annual operating hours (Section 4.8):
• With the AIS based approach, emissions are calculated for each vessel. Engine power (P) and
load factor (LF) are assigned according to vessel characteristics; emission factors (EF) are
assigned by engine category, model year, and other engine characteristics; and engine operating
activity (A) is derived from AIS data as described in Section 4.7.
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• The alternative approach relies on using the same vessel characteristics and emission factors as
the AIS based approach; however, vessel activity (A) is derived from alternative sources, as
described in Section 4.8.
The AIS approach allows for a highly detailed harbor craft inventory, which may be desirable for
inventories that need a fine level of temporal or geospatial resolution (e.g., for air quality analyses or
when analyzing the effectiveness of operational strategies to reduce emissions for harbor craft, where
more detailed activity information would be important to consider). However, the alternative approach
could be used if the purpose of the inventory does not necessitate a fine level of detail, or if the AIS data
do not fully cover harbor craft activity. Additionally, harbor craft activity may not be fully represented in
AIS data for some ship types, therefore, harbor craft inventories may be calculated using the AIS
approach for some ship types and using the alternative approach for others. If this dual approach is
used, care should be taken to not double count emissions for the same vessel in both approaches.
Projections of future year emission inventories are discussed in Section 4.9.
4.3 Vessel Characteristics
Both the AIS and the alternative approach for estimating emissions involve data related to the
characteristics of the vessels operating in the geographical domain. This information may be available
for purchase in the form of vessel registry databases; however, local data sources such as port records
and vessel surveys are the best source for harbor craft vessel characteristics. Federal databases0 and
online searches can supplement and validate these data. The following subsections detail the various
data fields that comprise vessel characteristic data:
• Fields used to identify vessels to cross-reference various data sets (Section 4.3.1)
• Fields used to characterize engines to determine appropriate emission factors (Section 4.3.2)
• Fields used to determine ship type to fill data gaps and to group similar activity patterns (Section
4.3.3)
The final subsection (Section 4.3.4) discusses techniques to fill data gaps in vessel characteristic data
sets.
4.3.1 Vessel Identification
All vessels have unique identifiers that can be used to match vessel activity data to vessel characteristic
data. The following vessel identifiers are useful when matching harbor craft records in different data
sets:
• International Maritime Organization (IMO) number
• Maritime Mobile Service Identity (MMSI)
• Vessel name
• Vessel call sign
c The U.S. Coast Guard maintains the following databases which may contain useful vessel characteristic data for
estimating emissions: Merchant Vessels of the United States (accessible by searching https://wyy.w-dep.-uscg. mil)
and U.S. Coast Guard Port State Information Exchange (accessible at https://cgmix.uscg.mil/PSIX/Default.aspx).
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The IMO number is generally the best field to use for vessel identification, as this number is uniquely
assigned to each vessel under IMO resolutions12 and does not change over its lifespan. However, if the
IMO number is not available, the MMSI (which is uniquely assigned to each AIS transmitter) can also be
used to match vessel records. If neither IMO number or MMSI are available, the vessel name or call sign
can possibly be used to match vessel characteristics for harbor craft; however, this should be done with
care as vessel names and call signs can change and are not necessarily unique identifiers.
4.3.2 Engine Characteristics
Emission factors for each emission source depend on engine category and tier, among other factors.
The following data fields can be used to determine the vessel's propulsion engine characteristics:
• Engine category (CI, C2, or C3)
• Engine bore (the diameter of each engine cylinder)
• Engine stroke (the stroke length of each engine cylinder)
• Rated engine size (kW)
• Total installed propulsion power (kW)
• Engine model year
• Remanufacture year, if applicable
If the engine category field is missing from the vessel characteristic data, it can be determined by
calculating cylinder displacement in liters using Equation 4.2, assuming the engine bore and stroke are
measured in millimeters:
TC _ ,
Cylinder Displacement = —x Bore/x Stroke x 10 b Equation 4.2
Table 4.2 lists how to determine if a vessel's propulsion engine is CI or C2 from the cylinder
displacement.13 d If engine tier is unknown, it can be determined using the information presented in
Appendix B.
Table 4.2. Classifying CI and C2 Engines
Engine Category
Engine Tier
Cylinder Displacement
1
Uncontrolled, 1, 2
displacement < 5 L
3,4
displacement < 7 L
2
Uncontrolled, 1, 2
5 L < displacement < 30 L
3,4
7 L < displacement < 30 L
Emission factors for most pollutants are assigned based on engine category, cylinder displacement,
rated engine size, and engine model year (see Section 4.5 for more information). Engine model year can
generally be assumed to be the same as the vessel model year if this detail is not explicitly included in
the vessel characteristic data. The emissions inventory calculations (detailed in Sections 4.7 and 4.8) use
d Some harbor craft, such as large tugs, may have C3 engines, as determined by having a cylinder displacement of
30 L or more. Emissions from these vessels should be calculated as described in this section, with the exception
that the appropriate emission factors for these vessels are presented in Section 3.5.
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the total installed propulsion power and not rated engine size. The total installed propulsion power is
the sum of the rated engine sizes for all propulsion engines installed on the vessel. If the vessel only has
one propulsion engine, the total installed propulsion power is the same as the rated engine size. If the
vessel characteristic data only indicate total installed propulsion power and number of engines, the
rated engine size can be estimated for all installed propulsion engines by dividing the total installed
propulsion power by the number of engines.
4.3.3 Ship Type
Ship type information is used to group similar vessels together to fill gaps in vessel characteristic and
activity data. It is also used to assign load factors. Depending on the source of the vessel characteristic
data, the ship type field can have varying levels of detail. Ship type can generally be aggregated to the
categories listed in Table 4.1.
4.3.4 Filling Gaps in Vessel Characteristic Data Sets
Missing data is a common occurrence for harbor craft in vessel characteristic data sets. If resources are
available, data such as number, displacement, rated size, and model year of propulsion and auxiliary
engines can be collected through interviewing pilots and/or surveying vessels operating in the
geographical domain, and averages by ship type can be applied to any remaining data gaps. Otherwise,
default assumptions on propulsion and auxiliary engine sizes as presented in Appendix G can be applied
by ship type, although these data have the limitation in that they do not reflect local conditions that
would affect vessel operation and thus emissions. Appendix G presents defaults by ship type and engine
group (propulsion or auxiliary) for the following data fields:
• Average rated engine size (kW)
• Average installed power (kW)
• Average engine operating hours (hours)
4.4 Vessel Activity Data Sources
There are many different data sources available to estimate vessel activity at U.S. ports. This section
describes the most useful data sources for calculating emission inventories. These data sources
generally include vessel identifiers, which can be used to match vessel activity data with vessel
characteristic data, as described in Section 4.3. This is important to assign the correct emission factors
and to estimate engine load appropriately.
4.4.1 Survey Data
Interviews with harbor pilots and/or surveys of vessels operating within the geographical domain can
provide useful data for estimating emissions. For example, interviews with harbor pilots can provide
average vessel speeds. Surveys of vessels can provide information on engine model year, size, and
annual hours of use for both propulsion and auxiliary engines.
Interviews and surveys should be used when available, and EPA encourages this type of information to
be collected for developing port-related inventories when possible. However, surrogate survey data
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could be used instead, if a similar port® has recently conducted an inventory and collected these kinds of
data. However, these data would have the limitation that they do not reflect local operating conditions.
4.4.2 Automatic Identification System
AIS equipment is used on vessels to aid navigation and to avoid collisions by broadcasting and receiving
messages containing vessel position, bearing, and speed, in addition to vessel identifiers (such as IMO
number and MMSI) and other information. While AIS coverage of CI and C2 vessels is not as complete
as it is for C3, many harbor craft are outfitted with AIS transponders, making it a suitable source of
activity data for some CI and C2 vessel types such as ferries and tug boats. AIS data can be analyzed to
estimate hours of operation. However, AIS data do not contain information on auxiliary engine loads,
which are estimated using other methods. Additionally, it is difficult to accurately estimate propulsion
engine load for some harbor craft ship types using AIS data (e.g., tugs that are assisting OGV have higher
propulsion engine loads than what would be indicated by only analyzing their speed).
AIS messages are recorded by the U.S. Coast Guard (USCG) as well as by commercial vendors for various
purposes. Marine Cadastre is a joint initiative of the Bureau of Ocean Energy Management and the
National Oceanic and Atmospheric Administration that provides publicly available AIS data derived from
USCG records/ Alternatively, U.S. federal, state, local, and Tribal government agencies can request
historical data from the USCG Navigation Center.8 Depending on the data source, individual AIS records
may be provided for intervals between 2 seconds to 5 minutes or longer. While a shorter interval will
provide higher resolution and more precise determination of operating modes, it will also increase the
size and complexity of the data set. The purpose of the emissions inventory should determine the
acceptable level of AIS record aggregation. For example, a detailed inventory supporting air quality
analysis may benefit more from a shorter time AIS interval than an annual, port-wide inventory.
Similarly, the geographical boundary of the emissions inventory should determine the geographical
extent of the AIS data acquisition.
Note that there are two kinds of AIS receivers: terrestrial- and satellite-based. Depending on the data
source, some AIS data sets may contain one or both types. Terrestrial-based AIS data sets usually have
good coverage in and around U.S. ports, and include AIS messages at a higher frequency than satellite-
based AIS data sets. While they can only receive messages within line-of-sight, this is unlikely to be an
issue for most harbor craft. Occasionally, in very high traffic areas, terrestrial-based receivers may be
unable to handle the load of recording all messages received and some records may be dropped.
Therefore, combining terrestrial- and satellite-based AIS data can improve the total coverage of a given
area. In general, if a dataset includes both terrestrial- and satellite-based data, and if there are AIS
messages for the same vessel and timestamp from both kinds of receivers, the message from the
terrestrial receiver should be used instead of the satellite receiver.
e Ideally, a "similar port" would be a different port in the same region with similar kinds and levels of activity.
However, any port with similar kinds and levels of activity could have useful surrogate data.
f For more information, see https://marinecadastre.gov/ais.
g For more information, see https://www.navcen.uscg.gov.
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4.4.3 Other Vessel Activity Data Sources
In addition to the sources discussed above, there are other data sources that may be used to estimate
harbor craft activity.
Information on tug, barge, and other harbor craft activity may be available in the U.S. Army Corps of
Engineers (USACE) Vessel Entrances and Clearances (E&C) data set, which is part of the Waterborne
Foreign Cargo series,17 as well as the Waterborne Commerce Statistics (WCS) data set of domestic vessel
movements.h USACE also has information on dredging activity.1
In addition, the local port authority, marine exchange, board of trade, or other local organizations may
have information on vessel movements. While these data sources typically focus on OGV activity, they
can be used to estimate tug boat activity, as most C3 vessels can be assumed to need the support of tug
boats. Additionally, these sources may contain information on excursion vessels and other harbor craft
ship types.
Alternatively, Appendix G provides average annual propulsion and auxiliary engine hours by ship type
that can be used instead. However, these data do not reflect local conditions, which likely impact vessel
operation.
4.5 Emission Factors
Emission factors vary by engine category (CI, C2, or C3), group (propulsion or auxiliary), cylinder
displacement, engine power, model year, and fuel sulfur level. For inventories of 2012 activity and later,
all CI and C2 marine vessels can be assumed to be using ultra low sulfur diesel (ULSD) to comply with
domestic fuel sulfur regulations.30 If the inventory is being calculated for a year prior to 2012, different
emission factors should be used as described in the subsections below.
Emission factors for U.S. flagged vessels with diesel CI and C2 propulsion engine(s), which comprise
most harbor craft, are discussed below and are presented in Appendix H. These apply to all vessels with
CI or C2 propulsion engine(s), regardless of whether the vessels are considered to be OGV or harbor
craft. Emission factors for vessels with C3 propulsion engines are presented in Section 3.5, and
emissions for recreational marine and marine engines fueled by gasoline are discussed in Section 5.
Speciation profiles of additional hazardous air pollutants for all commercial marine vessels are
presented in Appendix D.
For methods to estimate energy consumption for this source sector, see Appendix A.
4.5.1 Nitrogen Oxides (NOx)
NOx emission factors vary by engine category, group (propulsion or auxiliary), cylinder displacement,
engine power, and model year. Emission factors for CI and C2 NOx are presented in Appendix H.l.
h For more information, see httpsi//www,iwr,usace,army,mil/About/Technical-Centers/WCSC-Waterborne-
Commerce-Statistics-Center.
' For more information, see httpsi//publibrary,planusace,us/#/series/Dredging%20lnformation.
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4.5.2 Brake Specific Fuel Consumption (BSFC)
BSFC rates vary by engine power range. Note that particulate matter, carbon dioxide, nitrous oxide, and
sulfur dioxide are calculated based on these values. BSFC rates for CI and C2 engines are presented in
Table 4.3.13
Table 4.3. Category 1 and 2 BSFC Rates (g/kWh)
Power Range
BSFC (g/kWh)
kW < 37
248
kW > 37
213
4.5.3 Particulate Matter (PM), Diesel Particulate Matter (DPM), and Black Carbon (BC)
PMio emission factors vary by engine category, group (propulsion or auxiliary), cylinder displacement,
engine power, and model year. Emission factors for engines using ULSD are presented in Appendix
H.2.1
If the port emissions inventory is being calculated for engines not using ULSD (e.g., activity occuring
prior to 2012), emission factors for PMio will need to be adjusted to reflect the actual sulfur content
used by harbor craft vessels during the time period of the inventory. This adjustment is described in
Appendix H.2.2.
PM2.5 emission factors are estimated to be 97% of the PMio emission factors.13 For all vessels using
ULSD, the DPM 10 and DPM2.5 emission factors are equal to the PMio and PM2.5 emission factors,
respectively. BC emission factors are 77% of PM2.5 emission factors for marine CI and C2 engines.27
For CI and C2 marine engines that have been remanufactured using a certified remanufacture system,
all PM emission factors (including PMio, PM2.5, DPM10, DPM2.5, and BC) should be multiplied by 0.75,
which represents a 25% reduction in PM emissions.31j
4.5.4 Volatile Organic Compounds (VOC), Carbon Monoxide (CO), and Methane (CH4)
Hydrocarbon (HC) and CO emission factors vary by engine category, group (propulsion or auxiliary),
cylinder displacement, engine power, and model year. VOC and CH4 emission factors are derived from
the HC emission factors. HC emission factors for CI and C2 are presented in Appendix H.3 and CO
emission factors for CI and C2 are presented in Appendix H.4.
VOC emission factors are 1.053 times the HC emission factors.13 CH4 emission factors are 2% of HC
emission factors.23
4.5.5 Nitrous Oxide (N2O)
N20 emission factors can be estimated from BSFC using Equation 4.3:
EFN2o = BSFC x NCF Equation 4.3
Where EFN2q = N20 emission factor (g/kWh)
J For more information, see https://www.epa.gov/vehicle-and-engine-certification/remanufacture-svstems-
category- l-and-2-marine-diesel-engines.
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BSFC = brake specific fuel consumption (g/kWh) as determined according to Section 4.5.2
NCF = N20 conversion factor (g N20/g fuel)
= 0.000156 for CI and C2 engines32
4.5.6 Carbon Dioxide (CO2)
C02 is directly proportional to fuel consumption. Therefore, the C02 emission factor is determined
according to Equation 4.4:
EFCo2 = BSFC x CCF Equation 4.4
Where EFCq2 = C02 emission factor (g/kWh)
BSFC = brake specific fuel consumption (g/kWh) as determined according to Section 4.5.2
CCF = carbon content factor (g C02/g fuel)
= 3.19 for diesel33
4.5.7 Sulfur Dioxide (SO2)
S02 should be calculated according to Equation 4.5:
EFSo2 = BSFC x Sact x FSC x MWR Equation 4.5
Where EFSq2 = S02 emission factor (g/kWh)
BSFC = brake specific fuel consumption (g/kWh) as determined according to Section 4.5.2
$act = actual fuel sulfur level (weight ratio)
= 15xl0"6 for vessels using ULSD
FSC = percentage of sulfur in fuel that is converted to S0213
= 0.97753
MWR = molecular weight ratio of S02 to sulfur
= 64/32 = 2
If the port emissions inventory is being calculated for a year prior to 2012, or if a fuel with a different
sulfur level was used by harbor craft, then the actual fuel sulfur level should be used in Equation 4.5.
4.6 Load Factors
Load factor describes how much power an engine is producing as a fraction of its maximum rated
power. These values vary by ship type as different kinds of vessels perform different kinds of work (e.g.,
a harbor ferry compared to a tug boat), and load factors are inherently linked to duty cycle. Average
annual load factors are useful when modeling emissions as they capture average engine power usage.
Local propulsion engine average annual load factors can be estimated using the methodology developed
by California Air Resources Board (ARB),34 which is summarized here.
Average annual load factors for propulsion engines by ship type can be determined using average fuel
consumption, rated engine size, and annual hours of use by ship type using Equation 4.6:
FC„
LF' = BSFC xP„xA Equation 4.6
Where LFp = average annual propulsion engine load factor (unitless)
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FCp = average annual propulsion engine fuel consumption (g)
BSFC = brake specific fuel consumption (g/kWh) as determined according to Section 4.5.2
Pp = average total installed propulsion power (kW)
A = average total annual activity (h)
If fuel consumption data are measured in gallons, they can be converted to grams using a conversion
factor of 3,200 g/gal for diesel.33
However, if estimating local load factors is not feasible, default propulsion engine load factors from ARB,
as presented in Table 4.4, can be used instead.34 An auxiliary engine load factor of 0.43 can be assumed
for all ship types unless detailed local data indicate otherwise.k Note that barges do not have a
propulsion engine load factor because they are typically not self-propelled. However, if they have
auxiliary engines, those emissions should be included in the inventory. Additionally, note that if local
load factors are not available for dredging vessels, an average value of 0.66 can be used for all engines
present on a dredging vessel.1
Table 4.4. Default Harbor Craft Propulsion and Auxiliary Engine Load Factors
Ship Type
Propulsion Engine Load
Factor
Auxiliary Engine Load
Factor
Barge
-
0.43
Crew and Supply
0.45
0.43
Excursion
0.42
0.43
Fishing (C1/C2)
0.52
0.43
Government
0.45
0.43
Harbor Ferry (C1/C2)
0.42
0.43
Miscellaneous (C1/C2)
0.52
0.43
Pilot
0.51
0.43
Towboat/Pushboat
0.68
0.43
Tug Boat
0.50
0.43
Work Boat
0.45
0.43
4.7 AIS Inventory Calculations
A detailed emissions inventory can be calculated using AIS activity data from the base year. In general,
the base year inventory calculation is done at the individual vessel level through the following steps:
1. Link each AIS record to vessel characteristic data
2. Clean AIS data
3. Fill temporal gaps in AIS activity
k The 0.43 value is based on the estimated load factor for nonroad diesel generators from reference 35.
1 The 0.66 value is an activity weighted average load factor based on data presented in reference 36. For
additional information about estimating emissions from dredging vessels, see Appendix G.
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4. Assign operating mode and calculate emissions
5. Aggregate and/or allocate emissions
6. Perform quality control checks
The subsections below explain these steps in further detail.
4.7.1 Link Each AIS Record to Vessel Characteristic Data
Each AIS record contains vessel identification fields that can be used to link the AIS activity data to vessel
characteristic data. This is important not only for calculating emissions, but also for data cleaning and
quality control steps as well. Section 4.3 describes how vessel identifiers can be used to determine the
engine and vessel characteristics, and how to fill missing vessel characteristic data.
4.7.2 Clean AIS Data
It is not uncommon for AIS data to contain errors or extraneous data that need to be identified and
addressed before emissions can be calculated. The source of the AIS data will affect the amount of data
cleaning that will be involved. Some AIS vendors include data cleaning in their processes, while others
supply raw data that need more cleaning. While this is not a comprehensive list of all AIS data cleaning
procedures, the following list describes commonly performed cleaning steps:
• Remove records for vessels that are not identified as harbor craft vessels operating within the
geographical boundary. Note that these records may be useful for an OGV or recreational
marine inventory, but not a harbor craft inventory.
• Remove records where the coordinates appear outside the inventory's geographical boundary.
• Remove duplicate records (records with identical timestamps and vessel identifiers).
• Remove records with speeds above 1.5 times the service speed of the vessel.
Depending on the purposes of the emissions inventory, additional data processing at this phase may be
desired. For example, if an inventory needs to differentiate between vessels that call at the port and
innocent passage, AIS records will need to be marked accordingly. This step can be processed in
different ways:
• Matching AIS records to local logs, Entrances & Clearances data, or Waterborne Commerce
Statistics data, or
• Identifying individual vessel trips in the AIS records, geofencing harbor craft berths within the
geographical boundary, and flagging every record in the trip if any of the records show the
vessel entering them.
4.7.3 Fill Temporal Gaps in AIS Activity
Temporal gaps between AIS records may occur for a variety of reasons, including:
• The vessel left the geographical domain
• The vessel's AIS transponder malfunctioned or was turned off
• Records were removed as part of the cleaning process described above
A gap due to a vessel leaving the geographical domain can be identified by extrapolating vessel activity,
assuming a constant speed and heading from the last record before the gap. If the extrapolated position
is outside the geographical domain, then the gap should not be filled, and emissions should not be
calculated for it. Similarly, if the vessel is at berth and is not transmitting AIS messages, it may be
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assumed that the vessel's engines are not operating, and therefore this gap should not filled. However,
gaps occuring for other reasons should be filled in by interpolating location, speed, and draft data at the
expected frequency of the AIS records (e.g., if the AIS data has been aggregated to 5-minute intervals,
the gaps should be filled in by interpolating the data at 5-minute intervals).
After filling the temporal gaps, each AIS record can be assumed to represent the same time interval
(e.g., 5 minutes), which will be used when calculating the emissions of each vessel trip as described in
the following sections.
4.7.4 Assign Operating Mode and Calculate Emissions
When estimating emissions for harbor craft using AIS data, there are two important operating modes to
consider: hotelling and non-hotelling. When a harbor craft vessel is hotelling, it should be assumed that
its auxiliary engine is running, but not its propulsion engines. When not hotelling, it should be assumed
that both auxiliary and propulsion engines are running.
Operating mode can be determined by geofencing the harbor craft berthing areas (e.g., defining
polygons using geographic information system (GIS) software for the berthing areas used exclusively by
harbor craft). If the vessel is transmitting AIS messages from within these areas, those records should
be assigned to the hotelling operating mode; otherwise, harbor craft AIS records should be assigned to
the non-hotelling operating mode. Total activity in hours should then be calculated for each vessel by
operating mode by counting the number of AIS records in each operating mode and multiplying by the
time interval between each record, (e.g., 30 records in the hotelling operating mode x 5-minute time
interval = 150 minutes, or 2.5 hours hotelling).
Propulsion and auxiliary engine emission factors and load factors should be assigned to each vessel as
described in Sections 4.5 and 4.6, respectively. Then, emissions for each vessel can be estimated for
each operating mode. Non-hotelling emissions for each harbor craft vessel can be calculated using
Equation 4.7:
Enh
— (Pp x LFp x EFp + Pa x LFa x EFa) x Anh Equation 4.7
Where Enh = non-hotelling emissions for each vessel (g)
Pp = total installed propulsion engine power (kW)
LFp = propulsion engine load factor (unitless)
EFp = propulsion engine emission factor (g/kWh)
Pa = total installed auxiliary engine power (kW)
LFa = auxiliary engine load factor (unitless)
EFa = auxiliary engine emission factor (g/kWh)
Anh = non-hotelling activity (h)
Hotelling emissions for each harbor craft vessel can be calculated using Equation 4.8:
Eh = Pax LFa xEFaxAh Equation 4.8
Where Eh = hotelling emissions for each vessel (g)
Pa = total installed auxiliary engine power (kW)
LFa = auxiliary engine load factor (unitless)
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EFa = auxiliary engine emission factor (g/kWh)
Ah = hotelling activity (h)
4.7.5 Aggregate and/or Allocate Emissions
Total emissions should be calculated using Equation 4.9:
E — Enh + Eh Equation 4.9
Where E = total harbor craft emissions (g)
Enh = propulsion engine emissions for each AIS record (g)
Eh = hotelling emissions for each vessel (g)
The total emissions can then be aggregated or allocated to the most useful level for the purposes of the
inventory:
• For an annual inventory without a need for spatial considerations, all emissions for a particular
pollutant can be summed together. Note that even for annual inventories, reporting more
detailed emissions in addition to the annual results can be useful as described below in Section
4.7.6.
• If the inventory has a spatial component to it, the hotelling emissions should be allocated to the
berthing area where they occur, and the non-hotelling emissions should be allocated equally
across the vessel tracking paths derived from the AIS data. These emissions can then be
aggregated across all vessels to the most useful spatial resolution for the purpose of the
inventory (e.g., 100 m2 grid cells for a detailed analysis or summed for the entire port for
planning purposes).
• Similarly, if the inventory has a temporal component to it, the emissions can be allocated
according to the temporal distribution of AIS records. These emissions can then be aggregated
to the most useful resolution for the purpose of the inventory (e.g., at the hourly level for a
detailed analysis or yearly for an annual inventory).
4.7.6 Perform Quality Control Checks
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of vessel activity and emissions for an inventory. An inconsistency in one check that is
not reflected in others is indicative that additional scrutiny of input data sets and calculations may
reveal useful insights. Likewise, an anomaly that shows up in several checks may suggest an issue with
input data or methodology implementation. Note that unless otherwise specified, the analytical
calculations listed below should be aggregated by ship type. The following distributions and metrics are
useful to examine as quality control checks and to facilitate comparisons between different inventories:
• Distributions of vessel speed: Examining these distributions allow for general checks to ensure
that vessels are modeled to be operating within reasonable limits and with expected patterns of
behavior.
• Vessel counts and total operating hours and hotelling hours: Examining both totals and
distributions provides an estimate of the scale of vessel activity contributing to the inventory
and for enabling cross-comparisons with other inventories.
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• Installed power: Examining this helps to estimate the relative impact that a given ship type
should have on the inventory. For example, harbor ferries tend to have relatively large engines,
and so may contribute more emissions than their activity might otherwise suggest.
• Total energy consumption (kWh): Examining energy consumption by ship type and engine
group provides an estimate of the scale of vessel activity contributing to the inventory and for
enabling cross-comparisons with other inventories.
Other quality control checks include:
• Examining geospatial heatmaps of energy consumption: This helps identify if there are gaps in
the AIS data, or if there are anomalies in the data such as vessels being allocated to land or
shallow regions where they should be unable to operate.
• Reviewing vessel characteristics: This ensures values are consistent with ship types (e.g., pilot
boats likely do not have very high-power engines).
• Searching for rapid toggling between modes: This check at the AIS record level for irregularities
such as switching between hotelling and non-hotelling too frequently can identify anomalies in
the data that warrant a closer review.
4.8 Alternative Inventory Calculations
If AIS data are incomplete for some harbor craft ship types, an alternative method may be used to
calculate a base year emissions inventory for the remaining vessels. This method relies on using the
same vessel characteristics, installed power, load factors, and emission factors as described above;
however, the derivation of ship activity is different. In general, the alternative emissions calculation is
performed at the annual scale for each vessel through the following steps:
1. Link each vessel to vessel characteristic data
2. Assign load factors, emission factors, and operating hours
3. Calculate vessel emissions
4. Aggregate and/or allocate emissions as needed for the purposes of the inventory
5. Perform quality control checks
4.8.1 Link Each Vessel to Vessel Characteristic Data
Each harbor craft vessel identified in the local logs or other vessel activity data source as described in
Section 4.4 should be linked to corresponding vessel characteristic data. This step may be accomplished
implicitly depending on the data source (e.g., if the data source is vessel surveys, the surveys should be
designed to collect both vessel activity [propulsion engine operating hours and auxiliary engine
operating hours] as well as vessel characteristics [model year, installed propulsion power, and installed
auxiliary power]). Alternatively, it may be accomplished by linking data sets using vessel identifiers as
described in Section 4.3, which describes how vessel identifiers can be used to determine the engine
and vessel characteristics, and how to fill missing vessel characteristic data.
4.8.2 Assign Load Factors, Emission Factors, and Operating Hours
Propulsion and auxiliary engine emission factors and load factors should be assigned to each vessel as
described in Sections 4.5 and 4.6, respectively. If operating hours for each vessel are known (e.g., from
surveying the vessel operators), total emissions for each vessel should be calculated using the annual
operating hours for each vessel. For vessels with unknown operating hours, average annual hours by
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ship type should be used. Lacking that information, average annual hours by ship type from a similar
port or the defaults provided in Appendix G can be used, although these options do not reflect local
conditions, which likely impact vessel operation.
4.8.3 Calculate Vessel Emissions
Total emissions for each harbor craft vessel can be calculated using Equation 4.10:
E = Pp x LFp x Ap x EFp + Pa x LFa x Aa x EFa Equation 4.10
Where E = emissions for each vessel (g)
Pp = total installed propulsion engine power (kW)
LFp = propulsion engine load factor (unitless)
Ap = propulsion engine activity (h)
EFp = propulsion engine emission factor (g/kWh)
Pa = total installed auxiliary engine power (kW)
LFa = auxiliary engine load factor (unitless)
EFa = auxiliary engine emission factor (g/kWh)
Aa = auxiliary engine activity (h)
4.8.4 Aggregate and/or Allocate Emissions
The total emissions can then be aggregated or allocated to the most useful level for the purposes of the
inventory:
• For an annual inventory without a need for spatial considerations, all emissions of a particular
pollutant can be summed together. Note that even for annual inventories, reporting more
detailed emissions in addition to the annual results can be useful as described below in Section
4.8.5.
• If the inventory has a spatial component to it but detailed activity data (such as AIS) are
unavailable, emissions should be allocated as appropriate to shipping lanes or specific berths.
• If the inventory has a temporal component to it but detailed activity data are lacking, the
emissions can be allocated using the OGV temporal allocations as a surrogate data source.
These emissions can then be aggregated to the most useful resolution for the purpose of the
inventory (e.g., at the hourly level).
4.8.5 Perform Quality Control Checks
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of vessel activity and emissions for an inventory. An inconsistency in one check that is
not reflected in others is indicative that additional scrutiny of input data sets and calculations may
reveal useful insights. Likewise, an anomaly that shows up in several checks may suggest an issue with
input data or methodology implementation. Note that unless otherwise specified, the analytical
calculations listed below should be aggregated by ship type. The following distributions and metrics are
useful to examine as quality control checks and to facilitate comparisons between different inventories:
• Vessel counts: Examining these values provides an estimate of the scale of vessel activity
contributing to the inventory and for enabling cross-comparisons with other inventories.
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• Installed power: Examining this helps to estimate the relative impact that a given ship type
should have on the inventory. For example, harbor ferries tend to have relatively large engines,
and so may contribute more emissions than their activity might otherwise suggest.
• Total energy consumption: Examining energy consumption provides an estimate of the scale of
vessel activity contributing to the inventory and for enabling cross-comparisons with other
inventories.
• Outliers in hotelling times: Checking for vessels with abnormally long hotelling times is useful,
because it may not be appropriate to include these when calculating averages as they may
represent ships at a pier/wharf/dock that may not be running auxiliary engines for the entire
time.
4.9 Projecting Future Emission Inventories
Future harbor craft emissions should be projected from a base year inventory, developed as described in
the sections above. In general, the projection process follows these steps:
1. Activity growth rates are applied to the base year activity to estimate future activity
2. Model years are adjusted to account for fleet turnover to newer, cleaner engines and emission
factors are reassigned
3. Projected emissions are calculated using the estimated future activity
4. Projected emissions are aggregated to the same level of detail as the base year inventory, as
determined by the purpose of the inventory
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations. Projected changes in activity should
be determined for each ship type. Local port projections or other regional forecasts are usually by
commodity type and/or business sector; growth can be grouped by the ship types associated with the
various business sectors. For example, all commodity types can be grouped together to determine
growth in tug and pilot boat activity.
If local port projections or other regional forecasts are unavailable, the Freight Analysis Framework
(FAF)11 can be used to forecast growth instead. If this is used, the growth in total commodity flows in
the FAF assigned to the water transportation mode can be applied to all ship types. Note that this
method may not reflect possible differences in the growth of activity by ship type.
The growth rates should be applied to the base year activity. If the original base year inventory was
developed using AIS data, this growth rate is applied to the hours of operation in each operating mode
calculation for each vessel trip. If the original inventory was developed using alternate sources of vessel
activity, the growth rate should be applied to the total hours of activity for each vessel.
To reflect fleet turnover, the vessel model years used in the base year inventory should be adjusted for
use in the future year inventory. If the port or local fleet operator has already identified an expected
future vessel age distribution (e.g., if written commitments have been made to replace older vessels),
that should be used in determining how to adjust the model years. If the future age distribution is
unknown, it can be assumed to be the same as the base year age distribution. That is, it can be assumed
that in the future, the percentages of vessels that are brand new, one year old, two years old, etc. are
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the same as those percentages in the base year inventory. Functionally, this can be implemented by
adding the difference between the future and base years to each model year used in the base year
inventory, to get a new set of model years for the future year inventory. For example, if the base year
inventory is for 2020 and the projected inventory is for 2030, the difference of 10 years is added to each
model year. In this example, a model year 2005 vessel in the base year inventory would be a model year
2015 vessel in the 2030 inventory. Emission factors should be reassigned to all vessels using the
adjusted model years.
Additionally, any planned action or emission reduction strategies that have been committed to that
would affect future emissions should be included according to the actual expected implementation of
such commitments. For example, if a port has committed to replacing or repowering its oldest tugs
through authorization of funds for such purchases, the effects of such a program should be reflected in
the projected age distribution. Note that if the future year inventory is for a regulatory purpose,
planned future actions should be included only if written commitments have been made by the agency
or operator with the power to implement them.
Once the base year activity has been scaled and appropriate emission factors are assigned to each
vessel, the projected future emissions can be calculated using the same methodology at the same level
of detail as the base year inventory.
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5 Recreational Marine
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5.1 Source Description
Recreational marine vessels are boats that are operated primarily for pleasure or are leased, rented, or
chartered to another for the latter's pleasure. This category includes motorboats, cruisers, yachts,
personal water craft, and other types of motorized pleasure craft.3 It also includes all gasoline-powered
vessels. Recreational marine vessels typically are operated only a small number of hours per year.
However, some seemingly recreational vessels are more similar to commercial vessels in that they are
operated continuously during the year or a boating season, and these additional hours of use may have
an impact on the local emission inventory. Therefore, EPA's regulatory definition of "recreational
vessel" excludes vessels below 100 gross tons that carry more than 6 passengers, or vessels at or above
100 gross tons that carry one or more passengers.b This means that some sport fishing vessels and
excursion boats may be commercial vessels, which should be included in harbor craft inventory.
Additionally, vessels used solely for competition are not considered to be recreational.
When planning the scope of an inventory, it is important to determine whether the recreational marine
sector should be included. For example, not all ports have marina facilities for recreational marine
vessels or have significant recreational marine activity within the geographical domain of the inventory.
In these cases, it may not be important to include this sector in a port emissions inventory. However,
ports that do have significant recreational marine activity, or ports that expect significant increases or
decreases in future recreational marine activity may find it important to include emissions from this
sector at the level of detail consistent with the purpose of the inventory and the expected contributions
of this sector to the overall port-related emissions inventory.
If this sector is included in a detailed analysis, recreational marine emissions should be calculated at the
marina level, and both public and private marinas should be represented. Note that data may be less
readily accessible for private terminals. Regardless of whether a detailed or alternative approach is
employed, the scope of the inventory should be determined in advance of any calculations and in
accordance with the overall inventory purposes. Additionally, the inventory should be calculated at the
temporal level of detail necessitated by the purpose of the inventory (e.g., at the year level for an
annual inventory). See Section 2 of this document for more discussion about inventory purpose,
geographical domains, and temporal detail.
5.2 Emissions Estimation Overview
This section describes recreational marine data sources and general approaches that are relevant for
any port, regardless of location. For U.S. states and territories other than California, the nonroad
module of EPA's MOVES model (referred to here as MOVES-Nonroad) is the primary tool for estimating
a Sailboats also typically have auxiliary installed onboard, but those engines tend to be low power and not
continuously operated.
b A passenger is someone who provides payment as a condition of boarding a vessel. See EPA's definitions of
recreational vessel and passenger at 40 CFR 1042.901.
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emissions from recreational marine vessels.0 When using MOVES to develop a base year recreational
marine emissions inventory, the most recent version should be used. Inventories of recreational marine
emissions for ports in California should use California Air Resources Board's resources for pleasure craft
and outboard marine tank emissions instead of the information here for using MOVES-Nonroad.d
The MOVES Technical Guidance37 provides detailed information on how to generate emission
inventories using MOVES-Nonroad. However, the general equation for calculating per vessel emissions
based on MOVES-Nonroad output is as shown in Equation 5.1:
E = Ne x P x LF x A x EF Equation 5.1
Where E = per unit emissions (g)
Ne = number of engines on the vessel
P = rated engine power (hp)
LF = engine load factor (unitless)
A = engine operating activity (h)
EF = emission factor (g/hp-h)
Each of the above parameters may vary by vessel. Therefore, it is important to accurately account for
vessel characteristics (Section 5.3) and activity (Section 5.4) to ensure the operating power and hours
are calculated correctly and that the right emission factors (Section 5.5) are applied to this activity.
There are different methods that can be used for estimating base year emissions from recreational
marine vessels, depending on data and resource availability:
• The primary method used to calculate a detailed emissions inventory is based on Automatic
Identification System (AIS) data and is described in Section 5.6, where emissions are calculated
for each vessel. Rated engine power (P), load factor (LF), and emission factors (EF) are
assigned according to vessel characteristics, and engine operating activity (A) is derived from AIS
data.
• Alternative methodologies can be used where port-specific data on vessel activity, engine
power, and/or model year are not available. These methodologies rely on surrogate sources of
data that may not be specific to the port and are presented in Section 5.7.
Section 5.8 describes how to project future year emission inventories for recreational marine vessels.
5.3 Vessel Characteristics
To inform inputs for Equation 5.1 above, characteristic data for each recreational vessel should be
collected if possible. The best sources of detailed data on recreational vessels are surveys of and/or
interviews with marina operators. The following data for each vessel are useful when calculating a
recreational vessel emissions inventory:
• Vessel type
c For more information, see https://www.epa.gov/moves.
d For more information, see https://ww2.arb.ca.gov/our-work/programs/mobile-soyrce-emissions-inventory/roacl-
docymeritation/msei-documentation-offroad.
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• Fuel type
• Engine model year
• Rated engine power
• Number of engines
These data may be difficult to collect, particularly from private marinas. Therefore, default assumptions
can be made for some of these characteristics. Each of these data fields are discussed in more detail in
the remainder of this section.
5.3.1 Vessel Type and Fuel Type
MOVES-Nonroad categorizes various types of recreational marine vessels into source classification codes
(SCCs). A list of the recreational marine vessel SCCs in MOVES-Nonroad is presented in Table 5.1. Each
recreational vessel in the geographical domain should be assigned an appropriate SCC.
Table 5.1. Recreational Vessel SCCs in MOVES-Nonroad
MOVES-Nonroad Recreational Vessel Type
Source Classification Code
(SCC)
Gasoline (2-Stroke) Outboard
2282005010
Gasoline (2-Stroke) Personal Water Craft
2282005015
Gasoline (4-Stroke) Inboard/Sterndrive
2282010005
Diesel Inboard/Sterndrive
2282020005
Diesel Outboard
2282020010
In general, the default fuel characteristics in MOVES can be used as-is, which will be automatically
applied in a MOVES-Nonroad run for the county containing the port. MOVES users should review the
default fuel supply and fuel formulation information provided in MOVES, and make changes only where
precise local volumetric fuel property information is available or where local fuel requirements have
changed.
One exception is in the case of Reid Vapor Pressure (RVP); the MOVES user should change this value to
reflect any specific local regulatory requirements and differences between ethanol- and non-ethanol
blended gasoline not reflected in the default database (e.g., the default database may not reflect a
recent regulatory action to change an RVP requirement). Any changes to RVP (or to any other gasoline
fuel formulation parameters) should be made using the "Fuels Wizard" tool in the Fuel Tab of the
Nonroad Data Importer. This process is described in more detail in Section 5.2.2 of the MOVES
Technical Guidance. Note that the Fuels Wizard only applies to gasoline fuels. If any diesel fuel
properties (such as the diesel sulfur content) need to be changed, MOVES users should modify the
property in the fuel formulation table for the modeled county using the Nonroad Data Importer.
5.3.2 Engine Model Year
Engine model year is an important vessel characteristic, as newer recreational marine engines and
vessels meet more stringent EPA emission standards. The MOVES-Nonroad model internally associates
an emission standard tier based on an engine's model year and power rating, and accounts for other
factors that vary by model year and/or age, including tier phase-in, specific technology penetration
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rates, and deterioration. Therefore, it is not necessary to collect data on tier distributions or different
technology types, as these are accounted for by the model year parameter.
Note that due to assumptions made in MOVES-Nonroad regarding median life,35 a single model run may
not be sufficient to generate emission factors for all recreational vessel model years present during the
timespan of the analysis. That is, there may be recreational vessels at the port that are older than the
oldest vessels assumed in the model. Therefore, it may be necessary to run MOVES-Nonroad for
multiple calendar years to ensure emission factors for all model years are calculated. This is discussed in
further detail in Section 5.5.
If a representative sample of recreational marine vessels have model year data, vessels with missing
model years can be assumed to have the average value. However, in the likely scenario that there are
insufficient model year data for this kind of analysis, default assumptions can be made as described in
Section 5.7.1.
5.3.3 Rated Engine Power
In addition to vessel type, fuel type, and model year, emission factors from MOVES-Nonroad vary by
rated engine power bin. Therefore, each vessel should be assigned to the appropriate bin. Table 5.2
lists the definitions of the engine power bins in MOVES-Nonroad.
Table 5.2. MOVES-Nonroad Engine Power Bins
Bin ID*
Rated Engine Power (hp)
Rated Engine Power (kW)
1
0 < hp < 1
0 < kW < 0.7
3
1 < hp < 3
0.7 < kW < 2.2
6
3 < hp < 6
2.2 < kW < 4.5
11
6 < hp < 11
4.5 < kW < 8.2
16
11 < hp < 16
8.2 < kW < 12
25
16 < hp <25
12 < kW < 19
40
25 < hp <40
19 < kW < 30
50
40 < hp < 50
30 < kW < 37
75
50 < hp <75
37 < kW < 56
100
75 < hp <100
56 < kW < 75
175
100 < hp <175
75 < kW < 130
300
175 < hp <300
130 < kW < 224
600
300 < hp <600
224 < kW < 447
750
600 < hp <750
447 < kW < 559
1000
750 < hp <1,000
559 < kW < 746
1200
1,000 < hp < 1,200
746 < kW < 895
2000
1,200 < hp < 2,000
895 < kW< 1,491
3000
2,000 < hp < 3,000
1,491 < kW < 2,237
* Corresponds to values in the hpID column of MOVES-Nonroad output tables.
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Engine power ratings can in most cases be obtained from the vessel's physical engine tag.38 If the
engine tag does not provide this information, rated power can be determined from the specification
guide or owner's manual for the engine model.
If a power value cannot be determined for a vessel (e.g., because engine manufacturer and/or model is
not known), the average of known power values from similar recreational vessels at the port can be
used instead. However, in the likely scenario that there are insufficient data for this kind of analysis,
default assumptions can be made as described in Section 5.7.2.
5.4 Vessel Activity
Activity profiles should be developed for each type of recreational vessel; these include information on
hours of use (specifically, hours of engine operation during the analysis time period) and load factor
(fraction of full engine power used, on average, over a given period).
The best data source for hours of operation is Automatic Identification System (AIS) data. AIS
equipment is used on vessels to aid navigation and to avoid collisions by broadcasting and receiving
messages containing ship position, bearing, and speed, in addition to vessel identifiers and other
information. While AIS coverage of recreational vessels is not as complete as it is for harbor craft, many
recreational vessels are outfitted with AIS transponders, making it a suitable source of activity data for
some recreational marine vessels.
AIS messages are recorded by the U.S. Coast Guard (USCG) as well as by commercial vendors for various
purposes. Marine Cadastre is a joint initiative of the Bureau of Ocean Energy Management and the
National Oceanic and Atmospheric Administration that provides publicly available AIS data derived from
USCG records.® Alternatively, U.S. federal, state, local, and Tribal government agencies can request
historical data from the USCG Navigation Center/ Depending on the data source, individual AIS records
may be provided for intervals between 2 seconds to 5 minutes or longer. While a shorter interval will
provide higher resolution and more precise determination of operating modes, it will also increase the
size and complexity of the data set. The purpose of the emissions inventory should determine the
acceptable level of AIS record aggregation. For example, a detailed inventory supporting air quality
analysis may benefit more from a shorter time AIS interval than an annual, port-wide inventory.
Similarly, the geographical boundary of the emissions inventory should determine the geographical
extent of the AIS data acquisition.
Note that there are two kinds of AIS receivers: terrestrial- and satellite-based. Depending on the data
source, some AIS data sets may contain one or both types. Terrestrial-based AIS data sets usually have
good coverage in and around U.S. ports, and include AIS messages at a higher frequency than satellite-
based AIS data sets. While they can only receive messages within line-of-sight, this is unlikely to be an
issue for most recreational vessels. Occasionally, in very high traffic areas, terrestrial-based receivers
may be unable to handle the load of recording all messages received and some records may be dropped
Therefore, combining terrestrial- and satellite-based AIS data can improve the total coverage of a given
area. In general, if a dataset includes both terrestrial- and satellite-based data, and if there are AIS
e For more information, see httpsi//mariInecadastre.gov/ais.
f For more information, see https://www.navcen.uscg.gov.
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messages for the same vessel and timestamp from both kinds of receivers, the message from the
terrestrial receiver should be used instead of the satellite receiver.
If a representative sample of recreational marine vessels have AIS data, vessels without such data can be
assumed to have the average hours of use. Alternatively, hours of use can be estimated through surveys
of and/or interviews with marina operators. If resources are not available or the data sources are not
robust enough, default assumptions can be made as described in Section 5.7.2.
As for load factors, the default values from MOVES-Nonroad can be used unless vessel operators have
reason to believe their engines are operating with significantly different load factors. Gasoline and
diesel recreational marine engines can be assumed to have load factors of 0.21 and 0.35, respectively.35
5.5 Emission Factors
Recreational marine emission factors for most pollutants come from post-processing MOVES-Nonroad
output. However, MOVES-Nonroad cannot estimate emissions for nitrous oxide (N20) or black carbon
(BC), so if these pollutants are included in the inventory, they will need additional post-processing as
described below.
For methods to estimate energy consumption for this source sector, see Appendix A.
5.5.1 Running MOVES-Nonroad
MOVES-Nonroad calculates emissions based on model inputs for vessel activity, age distributions,
meteorological conditions, fuel characteristics, and other variables. In some cases, the default inputs
are specific to the region or county being modeled. The recommended approach for incorporating local
port activity data in a MOVES-Nonroad analysis is to first run MOVES-Nonroad for the geographical
domain and time period of the inventory with default inputs, and then post-process the output using
scripts included in MOVES to calculate emission factors. These emission factors can then be applied to
local activity data to generate an emissions inventory. Note that the latest version of MOVES-Nonroad
should be used, and the MOVES User Guide39 and the latest MOVES Technical Guidance contain
background information on how to use MOVES-Nonroad.
When setting up a Run Specification (RunSpec) using the MOVES Graphical User Interface (GUI), the
following selections should be made:
1. Time Spans Panel: Select the calendar year of analysis and all months/day types
(weekday/weekend).
2. Geographic Bounds Panel: Select the county containing the port.g
3. Nonroad Vehicle Equipment Panel: Select gasoline and marine diesel Pleasure Craft.
4. Pollutants and Processes Panel: Select all processes for the pollutants of interest (refer to
Section 2):
5. Output Emissions Detail Panel: Select model year, SCC, and hp class (i.e., engine power bin).
g If the geographical domain spans multiple counties, the county containing most of the geographical domain
should be selected.
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If user supplied fuel data needs to be included (see Section 5.3.1), this input should be configured using
the Nonroad Data Importer after setting up the RunSpec as described in Section 5.2.2 of the MOVES
Technical Guidance.
The run will produce inventory output for the months and day types selected in the Time Spans Panel by
the selected level of detail in the General Output Panel. After the run has finished, the MOVES-Nonroad
post-processing menu should be used to run the EmissionFactors_per_hphr_by_SCC_and_ModelYear.sql
script on the output database. This step will generate emission factors in grams per horsepower-hour
by SCC, engine power bin, and model year (for each month and day type) for each pollutant selected
based on the model run output. Section 5.3 of the MOVES Technical Guidance provides more details on
how to run MOVES-Nonroad post-processing scripts.
After the script finishes, the MOVES user should inspect the results. If there are vessels at the port that
are older than the earliest model years appearing in the MOVES-Nonroad results, another MOVES run is
needed. The same steps outline above should be taken, except the MOVES user should select an earlier
calendar year as appropriate. To determine which calendar year should be selected, calculate the oldest
age that MOVES-Nonroad can model for the vessel type(s) at the port for which the first MOVES-
Nonroad run did not produce output. This can be done by subtracting the modelYearlD from the yearlD
in the MOVES output. Then, add this age to the oldest model year vessel at the port; this is the calendar
year that should be run. Note that MOVES-Nonroad cannot be run for calendar years prior to 1990 or
1991-1998. Additionally, note that the default fuel sulfur level for both gasoline and diesel should be
inspected before running earlier calendar years; it should be set to the same value that was used in the
base year run because this run is simulating emissions from the older model years operating in the base
year.
If the temporal scale of the analysis is daily, the appropriate emission factor for the time domain should
be used. However, if the temporal scale of the analysis is annual or seasonal, weighted average
emission factors for each SCC, engine power bin, and model year can be estimated from the month-day
type specific emission factors:
• Emission factors should be weighted by seasonal or weekday/weekend activity information, if
those data are available.
• Otherwise, the emission factors could be weighted by the number of times a given month-day
type occurs in the analysis year.
Note, if model year information is not available in the activity data, see Section 5.7.1 for a modified
methodology for generating fleet average emission factors using MOVES-Nonroad.
5.5.2 Nitrous Oxide (N2O)
N20 emission factors can be estimated from brake specific fuel consumption (BSFC) using Equation 5.2:
EFNzo = BSFC x NCF Equation 5.2
Where EFN2q = N20 emission factor (g/hp-h)
BSFC = brake specific fuel consumption (g/hp-h) as determined according to Section 5.5.1
NCF = N20 conversion factor (g N20/g fuel) as presented in Table 5.332
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Table 5.3. Recreational Marine N20 Conversion Factors
Fuel Type
N20 Conversion Factor (g N20/g fuel)
Gasoline (2 Stroke)
0.000023
Gasoline (4 Stroke)
0.000083
Diesel
0.000156
5.5.3 Black Carbon (BC)
BC emission factors can be estimated from particulate matter less than or equal to 2.5 microns (PM2.5)
emission factors using Equation 5.3:
EFbc = EFPM25 x BCF Equation 5.3
Where EFBC = BC emission factor (g/hp-h)
EFpM2 = PM2.5 emission factor (g/hp-h) as determined according to Section 5.5.1
BCF = black carbon fraction27 (g BC/g PM2.5)
= 0.77 for diesel engines
= 0.10 for gasoline engines
5.6 AIS Inventory Calculations
A detailed emissions inventory can be calculated using AIS activity data from the base year. In general,
the base year inventory calculation is done at the individual vessel level through the following steps,
which are explained further below:
1. Assign each vessel the appropriate vessel characteristics and emission factors
2. Clean AIS data
3. Fill temporal gaps in AIS activity
4. Calculate vessel activity and emissions
5. Aggregate and/or allocate emissions
6. Perform quality control checks
The subsections below explain these steps in further detail.
5.6.1 Assign Each Vessel the Appropriate Vessel Characteristics and Emission Factors
This includes the following steps:
1. Assign each vessel to the appropriate MOVES-Nonroad SCC as described in Section 5.3.1, and a
MOVES-Nonroad engine power bin as described in Section 5.3.3.
2. Assign each vessel an appropriate load factor as described in Section 5.4.
3. Run MOVES-Nonroad and the post-processing script as described in Section 5.5. If needed,
calculate a weighted emission factor for all months and day types (e.g., if the activity data is on
an annual basis), also as described in Section 5.5.
4. Assign each vessel the appropriate emission factor (or sets of emission factors by month and day
type, e.g. if the activity data has that level of detail) for each pollutant, based on SCC, engine
power bin (labeled as hpID in MOVES output), and model year.
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5.6.2 Clean AIS Data
It is not uncommon for AIS data to contain errors or extraneous data that need to be identified and
addressed before emissions can be calculated. The source of the AIS data will affect the amount of data
cleaning that will be involved. Some AIS vendors include data cleaning in their processes, while others
supply raw data that need more cleaning. While this is not a comprehensive list of all AIS data cleaning
procedures, the following list describes commonly performed cleaning steps:
• Remove records for vessels that are not identified as recreational marine operating within the
geographical boundary. Note that these records may be useful for an OGV or harbor craft
inventory, but not a recreational marine inventory.
• Remove records where the coordinates appear outside the inventory's geographical boundary.
• Remove duplicate records (records with identical timestamps and vessel identifiers).
Depending on the purposes of the emissions inventory, additional data processing at this phase may be
desired. For example, if an inventory needs to differentiate between vessels that call at the port and
innocent passage, AIS records will need to be marked accordingly. This step can be processed in
different ways:
• Matching AIS records to marina logs, or
• Identifying individual vessel trips in the AIS records, geofencing the marina(s) within the
geographical boundary, and flagging every record in the trip if any of the records show the
vessel entering them.
5.6.3 Fill Temporal Gaps in AIS Activity
Temporal gaps between AIS records may occur for a variety of reasons, including:
• The vessel left the geographical domain
• The vessel's AIS transponder malfunctioned or was turned off
• Records were removed as part of the cleaning process described above
A gap due to a vessel leaving the geographical domain can be identified by extrapolating vessel activity,
assuming a constant speed and heading from the last record before the gap. If the extrapolated position
is outside the geographical domain, then the gap should not be filled, and emissions should not be
calculated for it. Similarly, if the vessel is at moored or at berth and is not transmitting AIS messages, it
may be assumed that the vessel's engines are not operating, and therefore this gap should not filled.
However, gaps occuring for other reasons should be filled in by interpolating location and speed data at
the expected frequency of the AIS records (e.g., if the AIS data has been aggregated to 5-minute
intervals, the gaps should be filled in by interpolating the data at 5-minute intervals).
After filling the temporal gaps, each AIS record can be assumed to represent the same time interval
(e.g., 5 minutes), which will be used when calculating the emissions of each vessel as described in the
following sections.
5.6.4 Calculate Vessel Activity and Emissions
Calculate hours of activity by counting the number of AIS records for each vessel and multiplying the
time interval between each record, (e.g., 5 minutes). For vessels that do not have any AIS records
associated with them, assign them the average number of hours of activity by vessel type.
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Emissions can then be calculated for each vessel using Equation 5.4:
E = Ne x P x LF x A x EF Equation 5.4
Where E = per unit emissions (g)
Ne = number of engines on the vessel
P = rated engine power (hp)
LF = engine load factor (unitless)
A = engine operating activity (h)
EF = emission factor (g/hp-h)
5.6.5 Aggregate and/or Allocate Emissions
Total recreational marine emissions can be aggregated or allocated to the most useful level for the
purposes of the inventory:
• For an annual inventory without a need for spatial considerations, all emissions for a particular
pollutant can be summed together. Note that even for annual inventories, reporting more
detailed emissions in addition to the annual results can be useful as described below in Section
5.6.6.
• If the inventory has a spatial component to it, emissions should be allocated equally across the
vessel tracking paths derived from the AIS data. These emissions can then be aggregated across
all vessels to the most useful spatial resolution for the purpose of the inventory (e.g., 100 m2
grid cells for a detailed analysis or summed for the entire port for aggregate emissions data).
• Similarly, if the inventory has a temporal component to it, the emissions can be allocated
according to the temporal distribution of AIS records. These emissions can then be aggregated
to the most useful resolution for the purpose of the inventory (e.g., at the hourly level for a
detailed analysis or yearly for an annual inventory).
5.6.6 Perform Quality Control Checks
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of vessel activity and emissions for an inventory. An inconsistency in one check that is
not reflected in others is indicative that additional scrutiny of input data sets and calculations may
reveal useful insights. Likewise, an anomaly that shows up in several checks may suggest an issue with
input data or methodology implementation. Note that unless otherwise specified, the analytical
calculations listed below should be aggregated by vessel type. The following distributions and metrics
are useful to examine as quality control checks and to facilitate comparisons between different
inventories:
• Distributions of vessel speed: Examining these distributions allow for general checks to ensure
that vessels are modeled to be operating within reasonable limits and with expected patterns of
behavior.
• Vessel counts and total operating hours: Examining both totals and distributions provides an
estimate of the scale of vessel activity contributing to the inventory and for enabling cross-
comparisons with other inventories.
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• Average engine power: Examining this helps to estimate the relative impact that a given vessel
type should have on the inventory.
• Fuel consumption: Comparing fuel consumption with the total fuel sold for recreational vessels
is a good check to see if there is substantial missing vessel activity. Note that the calculated fuel
consumption based on AIS data should be lower than the fuel sales estimates if the geographical
domain of the inventory does not span the entire area where the recreational vessels operate.
• Total energy consumption (kWh): Examining energy consumption provides an estimate of the
scale of vessel activity contributing to the inventory and for enabling cross-comparisons with
other inventories.
Other quality control checks include:
• Examining geospatial heatmaps of energy consumption: This helps identify if there are gaps in
the AIS data, or if there are anomalies in the data such as vessels being allocated to land or
shallow regions where they should be unable to operate.
• Comparing CO? emissions with fuel consumption: C02 emissions and fuel consumption should
have a linear relationship for recreational marine vessels.
5.7 Alternative Inventory Calculations
This section describes alternative methodologies for developing a base year recreational marine
emissions inventory when port-specific data on vessel activity, engine power, and/or model year are not
available. These methodologies rely on surrogate sources of data that are not specific to the port;
therefore, the resulting inventory may not be as useful for decision making purposes compared to an
inventory produced following the detailed methodology described in Section 5.6. However, such
inventories may be useful to estimate the order of magnitude of recreational marine emissions in
comparison with other port sectors, which could be useful in determining which sector or sectors
should be the focus of additional data gathering efforts.
In general, when using the surrogate data sources discussed in this section, total emissions can be
calculated for each vessel type using Equation 5.5 with fleet average values:
E = Nv x P x LF x A x EF Equation 5.5
Where E = fleet emissions for each vessel type (g)
Nv = number of recreational vessels
P = average engine power (hp)
LF = average load factor (unitless)
A = average operating activity (h)
EF = emission factor (g/hp-h)
When using Equation 5.5, the average operating activity in hours should account for the number of
engines. These emissions can be then aggregated to the most useful level for the purposes of the
inventory.
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5.7.1 Missing Model Year Data
If a representative sample of recreational marine vessels have model year data, vessels with missing
model years can be assumed to have the average value. However, if there are not enough model year
data for this kind of analysis, a weighted emission factor that does not vary by model year can be used in
the inventory calculation instead. This method relies on the median life and scrappage assumptions
used by MOVES-Nonroad.35 The same steps outlined in Section 5.5 should be used to produce
recreational marine emission factors with the following modifications:
1. In the General Output Panel, only select SCC (do not select model year or hp class).
2. After the run has finished, the MOVES-Nonroad post-processing menu should be used to run the
EmissionFactors_per_hphr_by_SCC.sql script on the output database. This step will generate
emission factors in grams per horsepower-hour by SCC (for each month and day type) for each
pollutant selected based on the model run output.
These emission factors should then be applied in Equation 5.5 as described above. Alternatively, an AIS-
based emissions inventory could be calculated following the same steps in Section 5.6, except the
emission factors are assigned only by SCC instead of by SCC, model year, and engine power bin.
5.7.2 Missing Hours of Use and/or Engine Power Data
If a representative sample of recreational marine vessels have hours of use and/or engine power data,
vessels missing these data can be assumed to have the average value(s). However, if there are
insufficient data for this kind of analysis, the national average values used in MOVES-Nonroad may be
used instead (see Table 5.4), but the resulting inventory would not reflect local conditions, which could
have a significant impact on the resulting emissions inventory.
Table 5.4. Average Hours of Use and Engine Size of Recreational Vessels in MOVES-Nonroad
MOVES-Nonroad Recreational Vessel
Type
Average Annual Hours of
Operation
Average Engine Size (hp)
Gasoline (2-Stroke) Outboard
34.8
83
Gasoline (2-Stroke) Personal Water Craft
77.3
121
Gasoline (4-Stroke) Inboard/Sterndrive
47.6
242
Diesel Inboard/Sterndrive
200
250
Diesel Outboard
150
32
When using this surrogate data, recreational marine emissions should be calculated at the fleet level
using the methodology described above. Note that when using these defaults, it can be assumed that
the average annual hours of operation accounts for the average number of engines on each vessel.
5.7.3 Missing Vessel Count Data
If an accurate count of recreational vessels that operate in the geographical domain is unavailable, the
number of slips (berthing or mooring locations) in the geographical domain can be used as a surrogate
number. The number of slips may not exactly correspond to the number of recreational vessels
operating in a port area, as some slips may be unoccupied, or multiple vessels may share a slip. If
necessary, the number of slips in a geographical domain can usually be determined using satellite
imagery. These vessels should be assigned the most common vessel type observed at the port.
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When using this surrogate data, recreational marine emissions should be calculated at the sector level
using the methodology described above.
5.8 Projecting Future Emission Inventories
Future recreational marine emissions should be projected from a base year inventory, developed as
described in the sections above. In general, the projection process follows these steps:
1. Determine projected activity, using local port projections or activity growth factors from
MOVES-Nonroad, applied to the base year
2. Determine future emission factors using MOVES-Nonroad
3. Calculate the future inventory with the projected activity and future emission factors, using the
same methodology used to calculate the base year inventory
4. Aggregate the future inventory to the same level of detail as the base year inventory
The remainder of this section describes these steps in further detail.
5.8.1 Determine Projected Activity
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations. Local port projections or other
regional forecasts are usually by commodity type and/or business sector; if expected growth in
recreational boating is known, this should be used to estimate future activity.
If local port projections are unavailable, regional growth factors employed by MOVES-Nonroad can be
used instead. These can be calculated by performing a run as described here. When setting up the
RunSpec, the following selections should be made:
1. Time Spans Panel: Select base year of the analysis and the projected year. Select July for the
month and Weekdays for the days selection.h
2. Geographic Bounds Panel: Select the county containing the port.1
3. Nonroad Vehicle Equipment Panel: Select gasoline and diesel Pleasure Craft.
4. Pollutants and Processes Panel: Select Brake Specific Fuel Consumption (BSFC).
5. Output Emissions Panel: Do not make any selections.
After the run has finished, locate the MOVES-Nonroad population output, specifically rows in the
movesactivityoutput table with activityTypelD 6. Dividing the population of the projection year by the
population for the base year results in the regional growth factor. This growth factor can then be
applied to the base year activity to estimate the projection year activity:
• If the base year inventory was calculated using the AIS methodology, this growth factor should
be applied to the engine operating activity term of Equation 5.4 in Section 5.6.4.
h MOVES-Nonroad only models equipment and vessel populations on an annual basis; that is, it does not model
different populations for different months or day types. Because the runs described here will only be used to
extract population growth, the month and day selections are arbitrary. Only one month and one day type are
selected for performance purposes, as well as to simplify the post-processing.
' If the geographical domain spans multiple counties, the county containing most of the geographical domain
should be selected.
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• If the base year inventory was calculated using the alternative methodologies, this growth factor
should be applied to the average operating activity term of Equation 5.5 in Section 5.7.
5.8.2 Determine Projected Emission Factors
Due to the complexity of projecting future age distributions for recreational marine vessels, the median
life and scrappage assumptions used by MOVES-Nonroad can be used instead of attempting to project a
local age distribution for this sector. The same steps outlined in Section 5.5 should be used to produce
future recreational marine emission factors with the following modifications:
1. In the General Output Panel, only select SCC (do not select model year or hp class).
2. After the run has finished, the MOVES-Nonroad post-processing menu should be used to run the
EmissionFactors_per_hphr_by_SCC.sql script on the output database. This step will generate
emission factors in grams per horsepower-hour by SCC (for each month and day type) for each
pollutant selected based on the model run output.
5.8.3 Calculate the Future Inventory
The future inventory should be calculated using the same equation as the base year inventory. If the
base year inventory was calculated using the AIS methodology, Equation 5.4 should be used with the
grown engine operating activity term and the future emission factors as described above. If the base
year inventory was calculated using the alternative methodologies, Equation 5.5 should be used with
the grown average operating activity term and the future emission factors as described above. Finally,
the resulting emissions inventory should be aggregated to the same level of detail as the base year
inventory.
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U.S. Environmental Protection Agency
6 Cargo Handling Equipment
2020 Public Draft
6.1 Source Description
The cargo handling equipment (CHE) sector encompasses equipment used for moving cargo, products,
and supplies around a port or other freight terminal, and on and off marine vessels, railcars, and onroad
trucks. This section could be used to quantify CHE emission inventories at ports or at other locations
where cargo is moved, such as off-port cargo distribution centers or intermodal freight terminals where
freight is transferred between rail and trucks. CHE are typically classified as "nonroad equipment," i.e.,
mobile equipment that do not operate on roadways.
Equipment types to be considered in an emissions inventory for a port's CHE sector may include (but are
not limited to):
• Aerial lifts
• Compressors
• Cranes
• Empty container handlers
• Excavators
• Forklifts
• Generators/power packs
• Light towers
• Manlifts
• Off-highway trucks
• Rail pushers
• Reach stackers
• Rollers
• Rubber-tired gantry (RTG) cranes
• Side handlers
• Skid steer loaders
• Sweepers
• Top handlers
• Tractors/loaders/backhoes
• Welders
• Yard tractors
The scope of the inventory should be determined in advance of any calculations and in accordance with
the overall inventory purposes, as discussed in Section 2. For example, while a port may have many
different types of cargo handling equipment, it may be decided that it is most important to include
equipment types that are most in use or the oldest, i.e., the equipment types that make up the largest
contribution to emissions or those that would be the focus of replacement. Alternatively, it may be
decided that every type of CHE present at the facility will be included, but the effort to gather detailed
information would be focused on the most important equipment types. Information needed for a CHE
inventory will likely come from the CHE owners or operators, which could include the port authority or
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port operator, port tenants, terminal operators, or other agencies, which highlights the importance of
cooperation in the process of developing an inventory. Additionally, the inventory should be calculated
at the temporal level of detail necessitated by the purpose of the inventory (e.g., at the year level for an
annual inventory). See Section 2 of this document for more discussion about inventory purpose and
time period covered.
6.2 Emissions Estimation Overview
This section describes CHE data sources and general approaches that are relevant for any port or freight
terminal inventory, regardless of location. For U.S. states and territories other than California, the
nonroad module of EPA's MOVES model (referred to here as MOVES-Nonroad) is the primary tool for
estimating emissions from CHE.a When using MOVES to develop a CHE emissions inventory, the most
recent version should be used. Inventories of CHE emissions in California should reference guidance for
the latest version of California Air Resources Board's CHE emissions model instead of the information
here for using MOVES-Nonroad.b
Information on all CHE present at the port should be gathered from terminal operators, and both public
and private terminals should be represented. Based on this information, MOVES-Nonroad can be used
to produce emission factors that can be multiplied by port-specific activity data to generate a base year
inventory. The MOVES Technical Guidance37 provides detailed information on how to generate emission
inventories using MOVES-Nonroad. However, the general equation for calculating per unit CHE
emissions based on MOVES-Nonroad output is as shown in Equation 6.1:
E = PxLFxAxEF Equation 6.1
Where E = per unit emissions (g)
P = rated engine power (hp)
LF = engine load factor (unitless)
A = engine operating activity (h)
EF = emission factor (g/hp-h)
Each of the above parameters may vary by equipment type and per unit. Therefore, it is important to
account for equipment characteristics (Section 6.3) and activity (Section 6.4) accurately to ensure that
operating power and hours are calculated correctly and that the right emission factors (Section 6.5) are
applied to this activity.
There are different methods that can be used for estimating base year emissions from CHE, depending
on data and resource availability:
• The primary method used to calculate a detailed emissions inventory is based on detailed CHE
activity data and is described in Section 6.6, where emissions are calculated for each unit of CHE.
Rated engine power (P), load factor (LF), and emission factors (EF) are assigned according to
equipment characteristics, and engine operating activity (A) is determined from local CHE
activity data.
a For more information, see https://www.epa.gov/moves.
b For more information, see https://ww2.arb.ca.gov/msei-documentation-offroad-diesel-equipment.
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• Alternative methodologies can be used where port-specific data on CHE activity, engine power,
and/or model year are not available. These methodologies rely on surrogate sources of data
and are presented in Section 6.7.
Section 6.8 describes how to project future year emission inventories for CHE.
6.3 Equipment Characteristics
To inform inputs for Equation 6.1 above, equipment characteristic data for each unit of CHE should be
collected. The best sources of detailed data on equipment characteristics are surveys of and/or
interviews with terminal operators. While default assumptions can be made for various characteristics,
the more detailed the data that are collected, the more representative the resulting emissions inventory
will be, and the more useful it will be for decision-making purposes. Specifically, the following data for
each unit of CHE are useful when calculating a CHE emissions inventory:
• Equipment type
• Fuel type (e.g., diesel, gasoline, electric)
• Engine model year
• Rated engine power
• Retrofit devices or other emission mitigation measures employed (if applicable)
Each of these data fields are discussed in more detail in the remainder of this section. In addition to the
equipment characteristics listed above, activity data (such as hours of operation and engine load factor)
should be collected for each unit of CHE; these are discussed in detail in Section 6.4.
6.3.1 Equipment Type and Fuel Type
The majority of CHE can be classified based on existing MOVES-Nonroad source classification codes
(SCCs), which categorize nonroad engines by equipment type and fuel type. Note that MOVES-Nonroad
does not include electricity as a fuel type. If there is electric CHE at a port, their tailpipe emissions
would be zero. For methods to estimate energy consumption for this source sector, including electric
equipment, see Appendix A.
A mapping of common CHE types to MOVES-Nonroad equipment types is presented in Table 6.1. This
table does not include every type of CHE that could be operating at an individual port. In practice, CHE
can include any equipment operating at a port that does not belong to one of the other source sectors.
Emissions from CHE types not listed in the table can be estimated using the "Other General Industrial
Equipment" type.
Table 6.1. Mapping CHE Types to MOVES-Nonroad Equipment Types
CHE Type
MOVES-Nonroad Equipment Type
MOVES-Nonroad Sector
Aerial Lifts
Aerial Lifts
Industrial
Compressors
Air Compressors
Commercial
Cranes
Cranes
Construction
Empty Container Handlers
Other General Industrial Equipment
Industrial
Excavators
Excavators
Construction
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CHE Type
MOVES-Nonroad Equipment Type
MOVES-Nonroad Sector
Forklifts
Forklifts
Industrial
Generators/Power Packs
Generator Sets
Commercial
Light Towers
Signal Boards/Light Plants
Construction
Manlifts
Aerial Lifts
Industrial
Off-highway T rucks
Off-highway T rucks
Construction
Pumps
Pumps
Commercial
Rail Pushers
Other General Industrial Equipment
Industrial
Reach Stackers
Other General Industrial Equipment
Industrial
Rollers
Rollers
Construction
RTG Cranes
Other General Industrial Equipment
Industrial
Side Handlers
Other General Industrial Equipment
Industrial
Skid Steer Loaders
Skid Steer Loaders
Construction
Sweepers
Sweepers/Scrubbers
Industrial
Top Handlers
Other General Industrial Equipment
Industrial
Tractor/Loader/Backhoes
T ractors/Loaders/Backhoes
Construction
Welders
Welders
Commercial
Yard Tractors
Terminal Tractors
Industrial
A mapping of MOVES-Nonroad equipment types and fuel types to SCC is presented in Table 6.2. For
each unit of CHE, the appropriate MOVES-Nonroad equipment type should be determined using Table
6.1, and then it should be assigned an SCC using Table 6.2.
Table 6.2. Mapping MOVES-Nonroad Equipment Types and Fuel Types to SCC
MOVES-Nonroad
Equipment Type
Source Classification Code (SCC) by Fuel Type
Diesel
2-Stroke
Gasoline
4-Stroke
Gasoline
LPG*
CNG
Aerial Lifts
2270003010
N/A"
2265003010
2267003010
N/A
Air Compressors
2270006015
2260006015
2265006015
2267006015
2268006015
Cranes
2270002045
N/A
2265002045
2267002045
N/A
Excavators
2270002036
N/A
N/A
N/A
N/A
Forklifts
2270003020
N/A
2265003020
2267003020
2268003020
Generator Sets
2270006005
2260006005
2265006005
2267006005
2268006005
Off-highway T rucks
2270002051
N/A
N/A
N/A
N/A
Other General Industrial
Equipment
2270003040
2260003040
2265003040
2267003040
2268003040
Pumps
2270006010
2260006010
2265006010
2267006010
2268006010
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MOVES-Nonroad
Equipment Type
Source Classification Code (SCC) by Fuel Type
Diesel
2-Stroke
Gasoline
4-Stroke
Gasoline
LPG*
CNG
Rollers
2270002015
N/A
2265002015
2267002015
N/A
Signal Boards/Light Plants
2270002027
2260002027
2265002027
N/A
N/A
Skid Steer Loaders
2270002072
N/A
2265002072
2267002072
N/A
Sweepers/Scrubbers
2270003030
2260003030
2265003030
2267003030
2268003030
Terminal Tractors
2270003070
N/A
2265003070
2267003070
2268003070
T ractors/Loaders/Backhoes
2270002066
N/A
2265002066
2267002066
N/A
Welders
2270006025
N/A
2265006025
2267006025
N/A
* CHE using propane should be matched to an appropriate LPG SCC.
" N/A indicates that MOVES-Nonroad cannot model this combination of equipment type and fuel type. If such a
combination is present, emissions can be estimated using the "Other General Industrial Equipment" type.
In general, the default fuel characteristics in MOVES can be used as-is, which will be automatically
applied in a MOVES-Nonroad run for the county containing the port. MOVES users should review the
default fuel supply and fuel formulation information provided in MOVES, and make changes only where
precise local volumetric fuel property information is available or where local fuel requirements have
changed.
One exception is in the case of Reid Vapor Pressure (RVP); the MOVES user should change this value to
reflect any specific state or local regulatory requirements and differences between ethanol- and non-
ethanol blended gasoline not reflected in the default database (e.g., the default database may not
reflect a recent regulatory action to change an RVP requirement). Any changes to RVP (or to any other
gasoline fuel formulation parameters) should be done using the "Fuels Wizard" tool in the Fuel Tab of
the Nonroad Data Importer. This process is described in more detail in Section 5.2.2 of the MOVES
Technical Guidance. Note that the Fuels Wizard only applies to gasoline fuels. If any diesel fuel
properties (such as the diesel sulfur content) need to be changed, MOVES users should modify the
property in the fuel formulation table for the modeled county using the Nonroad Data Importer.
6.3.2 Engine Model Year
Engine model year is important for an emissions inventory, as newer CHE meet more stringent EPA
emission standards. The MOVES-Nonroad model internally associates an emission standard tier based
on an engine's model year and power rating, and accounts for other factors that vary by model year
and/or age, including tier phase-in, specific technology penetration rates, and deterioration. Therefore,
it is not necessary to collect data on tier distributions or different technology types, as these are
accounted for by the model year parameter.
Note that due to assumptions made in MOVES-Nonroad regarding median life,35 a single model run may
not be sufficient to generate emission factors for all CHE model years present during the timespan of
analysis. That is, there may be CHE at the port that are older than the oldest equipment assumed in the
model. Therefore, it may be necessary to run MOVES-Nonroad for multiple calendar years to ensure
emission factors for all model years are calculated. This is discussed in further detail in Section 6.5.
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If a representative sample of CHE have model year data, equipment of the same type with missing
model years can be assumed to have the average value. If there are insufficient model year data for this
kind of analysis, default assumptions can be made as described in Section 6.7.1. However, using default
data would not reflect local conditions, which could have a significant impact on the resulting emissions
inventory.
6.3.3 Rated Engine Power
In addition to equipment type, fuel type, and model year, emission factors from MOVES-Nonroad vary
by rated engine power bin. Therefore, each unit of equipment should be assigned to the appropriate
bin. Table 6.3 lists the definitions of the engine power bins in MOVES-Nonroad. Each CHE type is
generally represented in a subset of the listed power ranges (e.g., diesel aerial lifts span the range 6 < hp
< 175).
Table 6.3. MOVES-Nonroad Engine Power Bins
Bin ID*
Rated Engine Power (hp)
Rated Engine Power (kW)
1
0 < hp < 1
0 < kW < 0.7
3
1 < hp < 3
0.7 < kW < 2.2
6
3 < hp < 6
2.2 < kW < 4.5
11
6 < hp < 11
4.5 < kW < 8.2
16
11 < hp < 16
8.2 < kW < 12
25
16 < hp < 25
12 < kW < 19
40
25 < hp < 40
19 < kW < 30
50
40 < hp < 50
30 < kW < 37
75
50 < hp <75
37 < kW < 56
100
75 < hp <100
56 < kW < 75
175
100 < hp < 175
75 < kW < 130
300
175 < hp < 300
130 < kW < 224
600
300 < hp < 600
224 < kW < 447
750
600 < hp < 750
447 < kW < 559
1000
750 < hp <1,000
559 < kW < 746
1200
1,000 < hp < 1,200
746 < kW < 895
2000
1,200 < hp < 2,000
895 < kW< 1,491
3000
2,000 < hp < 3,000
1,491 < kW< 2,237
* Corresponds to values in the hpID column of MOVES-Nonroad output tables.
Engine power ratings can in most cases be obtained from the equipment's physical engine tag.38 If the
engine tag does not provide this information, rated power can be determined from the specification
guide or owner's manual for the equipment model.
If an equipment-specific power value cannot be determined for a CHE unit (e.g., because equipment
manufacturer and/or model is not known), the average of known power values from similar equipment
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in the CHE fleet can be used instead. If there are insufficient data for this kind of analysis, alternative
assumptions can be made as described in Section 6.7.2. However, using alternative data would not
reflect local conditions, which could have a significant impact on the resulting emissions inventory.
6.3.4 Equipment Retrofit and Replacement Projects
MOVES-Nonroad does not account for state or local projects to retrofit emission reduction technologies
on nonroad diesel equipment or to replace older engines or equipment with newer, cleaner ones. If the
port has such a program, it should be accounted for using MOVES-Nonroad. EPA has a guidance
document, Diesel Retrofit and Replacement Projects: Quantifying and Using Their Emission Benefits in
SIPs and Conformity, which addresses the quantification of diesel retrofit and replacement projects in
detail.40 Section 2.7 of that document describes how to quantify emission reductions from nonroad
retrofit projects and Section 2.8 describes how to quantify emission reductions from nonroad
equipment or engine replacement projects. EPA also provides a "Nonroad Retrofit Tool" to simplify the
creation of a nonroad retrofit input file for use in MOVES, which applies when retrofitting an existing
diesel engine with new technology or devices.0
6.4 Equipment Activity
As described in Section 6.2, emissions are directly related to activity. To create a detailed CHE emissions
inventory, activity profiles should be developed for each unit of CHE; this includes information on hours
of use (specifically, hours of engine operation during the analysis time period) and load factor (fraction
of full engine power used, on average, over a given period). This information may be available from the
CHE owners or operators, which could include the port authority or port operator, the port tenants,
terminal operators, or other agencies.
The best source of data for hours of use is hour-meter readings. When hour-meter information is
unavailable, estimates of hours of use can be derived from interviews or surveys with terminal
operators. Note that equipment usage patterns likely differ by equipment type. If hour usage
information is not available for individual equipment units in the fleet, averages by equipment type
operating at the same terminal (if available) or port can be used. If there are insufficient data for this
kind of analysis, alternative assumptions can be made as described in Section 6.7.2. However, using
alternative data would not reflect local conditions, which could have a significant impact on the resulting
emissions inventory.
In general, the default load factors from MOVES-Nonroad can be used.35 d Default load factors for
MOVES-Nonroad equipment types are presented in Table 6.4.
c Available at httpsi//www,epa,gov/moves/tools-develop-or-convert-moves-inputs.
d While it is possible to determine port-specific load factors by installing portable activity measurement systems
(PAMS) on CHE, this is likely to be useful only for very detailed CHE emission inventories and when terminal
operators have reason to believe their equipment are operating with significantly different load factors than the
defaults.
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Table 6.4. MOVES-Nonroad Engine Load Factors by Fuel Type
MOVES-Nonroad
Equipment Type
Diesel
2-Stroke
Gasoline
4-Stroke
Gasoline
LPG
CNG
Aerial Lifts
0.21
N/A*
0.46
0.46
N/A
Air Compressors
0.43
0.56
0.56
0.56
0.56
Cranes
0.43
N/A
0.47
0.47
N/A
Excavators
0.59
N/A
N/A
N/A
N/A
Forklifts
0.59
N/A
0.30
0.30
0.30
Generator Sets
0.43
0.68
0.68
0.68
0.68
Off-highway T rucks
0.59
N/A
N/A
N/A
N/A
Other General Industrial
Equipment
0.43
0.54
0.54
0.54
0.54
Pumps
0.43
0.69
0.69
0.69
0.69
Rollers
0.59
N/A
0.62
0.62
N/A
Signal Boards/Light Plants
0.43
0.72
0.72
N/A
N/A
Skid Steer Loaders
0.21
N/A
0.58
0.58
N/A
Sweepers/Scrubbers
0.43
0.71
0.71
0.71
0.71
Terminal Tractors
0.59
N/A
0.78
0.78
0.78
T ractors/Loaders/Backhoes
0.21
N/A
0.48
0.48
N/A
Welders
0.21
N/A
0.68
0.68
N/A
* N/A indicates that MOVES-Nonroad cannot model this combination of equipment type and fuel type. If such a
combination is present, use the load factor associated with the "Other General Industrial Equipment" type.
6.5 Emission Factors
CHE emission factors for most pollutants come from post-processing MOVES-Nonroad output.
However, MOVES-Nonroad cannot estimate emissions for nitrous oxide (N20) or black carbon (BC), so if
these pollutants are included in the inventory, they will need additional post-processing as described
below.
For methods to estimate energy consumption for this source sector, see Appendix A.
6.5.1 Running MOVES-Nonroad
MOVES-Nonroad calculates emissions based on model inputs for equipment activity, age distributions,
meteorological conditions, fuel characteristics, and other variables. In some cases, the default inputs
are specific to the region or county being modeled. The recommended approach for incorporating local
port activity data in a MOVES-Nonroad analysis is to first run MOVES-Nonroad for the geographical
domain and time period of the inventory with default inputs, and then post-process the output using
scripts included in MOVES to calculate emission factors. These emission factors can then be applied to
local activity data to generate an emissions inventory. Note that the latest version of MOVES-Nonroad
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should be used, and the MOVES User Guide39 and the latest MOVES Technical Guidance contain
background information on how to use MOVES-Nonroad.
When setting up a Run Specification (RunSpec) using the MOVES Graphical User Interface (GUI), the
following selections should be made:
1. Time Spans Panel: Select the calendar year of analysis and all months/day types
(weekday/weekend).
2. Geographic Bounds Panel: Select the county containing the port.®
3. Nonroad Vehicle Equipment Panel: Add the fuel type/source sector combinations represented
at the port, based on the mapping of port CHE types to SCCs (as described in Section 6.3.1).
4. Pollutants and Processes Panel: Select all processes for the pollutants of interest (refer to
Section 2).
5. Output Emissions Detail Panel: Select model year, SCC, and hp class (i.e., engine power bin).
If user supplied fuel data (see Section 6.3.1) or a retrofit or replacement program (see Section 6.3.4)
needs to be included, those inputs should be configured using the Nonroad Data Importer after setting
up the RunSpec as described in Section 5.2.2 of the MOVES Technical Guidance.
The MOVES-Nonroad run will produce inventory output for the months and day types selected in the
Time Spans Panel by the selected level of detail in the General Output Panel. After the run has finished,
the MOVES-Nonroad post-processing menu should be used to run the
EmissionFactors_per_hphr_by_SCC_and_ModelYear.sql script on the output database. This step will
generate emission factors in grams per horsepower-hour by SCC, engine power bin, and model year (for
each month and day type) for each pollutant selected based on the model run output. Section 5.3 of the
MOVES Technical Guidance provides more details on how to run MOVES-Nonroad post-processing
scripts.
After the script finishes, the MOVES user should inspect the results. If there are equipment at the port
that are older than the earliest model years appearing in the MOVES-Nonroad results, another MOVES
run is needed. The same steps outlined above should be taken, except the MOVES user should select an
earlier calendar year as appropriate. To determine which calendar year should be selected, calculate the
oldest age that MOVES-Nonroad can model for the equipment type(s) of CHE at the port for which the
first MOVES-Nonroad run did not produce output. This can be done by subtracting the modelYearlD
from the yearlD in the MOVES output. Then, add this age to the oldest model year of CHE at the port;
this is the calendar year that should be run. Note that MOVES-Nonroad cannot be run for calendar
years prior to 1990 or 1991-1998. Additionally, note that the default fuel sulfur level for both gasoline
and diesel should be inspected before running earlier calendar years; it should be set to the same value
that was used in the base year run because this run is simulating emissions from the older model years
operating in the base year.
If the temporal scale of the analysis is daily, the appropriate emission factor for the time domain should
be used. However, if the temporal scale of the analysis is annual or seasonal, weighted average
e If the geographical domain spans multiple counties, the county containing most of the geographical domain
should be selected.
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emission factors for each SCC, engine power bin, and model year can be estimated from the month-day
type specific emission factors:
• Emission factors should be weighted by seasonal or weekday/weekend cargo throughput if
those data are available.
• Otherwise, the emission factors could be weighted by the number of times a given month-day
type occurs in the analysis year.
Note, if model year information is not available in the activity data, see Section 6.7.1 for an alternative
method for generating fleet average emission factors using MOVES-Nonroad.
6.5.2 Nitrous Oxide (N2O)
N20 emission factors can be estimated from brake specific fuel consumption (BSFC) using Equation 6.2:
EFn2o = BSFC x NCF Equation 6.2
= N20 emission factor (g/hp-h)
= brake specific fuel consumption (g/hp-h) as determined according to Section 6.5.1
= N20 conversion factor (g N20/g fuel) as presented in Table 6.532
Table 6.5. CHE N20 Conversion Factors
Fuel Type
N20 Conversion Factor
(g NzO/g fuel)
Gasoline (2 Stroke)
0.000020
Gasoline (4 Stroke)
0.000071
Diesel
0.000147
CNG
0.000201
LPG
0.000201
6.5.3 Black Carbon (BC)
BC emission factors can be estimated from particulate matter less than or equal to 2.5 microns (PM2.5)
emission factors using Equation 6.3:
EFbc = EFpM25 x BCF Equation 6.3
Where EFBC = BC emission factor (g/hp-h)
EFpM2 = PM2.5 emission factor (g/hp-h) as determined according to Section 6.5.1
BCF = black carbon fraction27 (g BC/g PM2.5)
= 0.77 for diesel equipment
= 0.10 for other equipment
Where EFN2o
BSFC
NCF
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6.6 Detailed Inventory Calculations
A detailed emissions inventory is first calculated at the per unit level as described in Section 6.6.1 and
then aggregated across all equipment to the most useful level for the purposes of the inventory (Section
6.6.2). The final step is to perform quality control checks, as described in Section 6.6.3.
6.6.1 Calculating an Emissions Inventory Per Unit
A detailed base year emissions inventory can be calculated for CHE on a per unit basis through the
following steps:
1. Assign each CHE unit to the appropriate MOVES-Nonroad equipment type and SCC as described
in Section 6.3.1, and a MOVES-Nonroad engine power bin as described in Section 6.3.3.
2. Assign each CHE unit an appropriate load factor as described in Section 6.4.
3. Run MOVES-Nonroad and the post-processing script as described in Section 6.5. If needed,
calculate a weighted emission factor for all months and day types (e.g., if the activity data is on
an annual basis), also as described in Section 6.5.
4. Assign each CHE unit the appropriate emission factor (or sets of emission factors by month and
day type, e.g. if the activity data has that level of detail) for each pollutant, based on SCC, engine
power bin (labeled as hpID in MOVES output), and model year.
5. Calculate emissions for each CHE unit using Equation 6.4:
E = PxLFxAxEF Equation 6.4
Where E = per unit emissions (g)
P = rated engine power (hp)
LF = engine load factor (unitless)
A = engine operating activity (h)
EF = emission factor (g/hp-h)
6.6.2 Aggregating Per Unit Emissions
These emissions can be then aggregated across all equipment to the most useful level for the purposes
of the inventory.
• If the inventory has a spatial component to it, CHE emissions should be allocated to the terminal
area where they occur. For example, the location of emissions is important if the purpose of
estimating emissions is for use in air quality modeling or if different types of CHE activity occur
in different parts of the port.
• If the inventory has a temporal component to it and the activity data are at a finer level of
detail, the CHE emissions should be aggregated to the level of detail necessitated by the
purpose of the inventory. For example, if the port has significant seasonal variation in activity or
if the purpose of the inventory is to support air quality modeling, how emissions change over
time is a key input. If activity data are available to estimate emissions for specific times of day
and/or seasons of the year, these data can be applied to other hours as appropriate in the air
quality model.
However, if the activity data are at a coarser level of temporal detail than what is necessitated by the
purpose of the inventory, the emissions will need to be allocated temporally using surrogate data. This
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surrogate data can come from other sectors in the port inventory, if those have sufficient detail (e.g.,
CHE activity could be temporally allocated based on AlS-derived OGV hotelling activity, if available).
6.6.3 Perform Quality Control Checks
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of equipment activity and emissions for an inventory. An inconsistency in one check
that is not reflected in others is indicative that additional scrutiny of input data sets and calculations
may reveal useful insights. Likewise, an anomaly that shows up in several checks may suggest an issue
with input data or methodology implementation. Note that unless otherwise specified, the analytical
calculations listed below should be aggregated by equipment type and fuel type. The following
distributions and metrics are useful to examine as quality control checks and to facilitate comparisons
between different inventories:
• Equipment counts: Examining both totals and distributions provides an estimate of the scale of
equipment activity contributing to the inventory and for enabling cross-comparisons with other
inventories.
• Engine power and operating hours: Examining both totals and distributions helps to estimate
the relative impact that a given equipment type should have on the inventory.
• Model year range and engine tier distribution: Examining the minimum and maximum observed
values and average age, along with the distribution of engine tiers, provides an indication of
how old the equipment are and can help in determining which equipment contribute
substantially to the inventory.
• Total energy consumption (in horsepower-hours): Examining energy consumption by
equipment type provides an estimate of the scale of equipment activity contributing to the
inventory and for enabling cross-comparisons with other inventories.
• Comparing CO? emissions with fuel consumption: C02 emissions and fuel consumption should
have a linear relationship.
6.7 Alternative Inventory Calculations
This section describes alternative methodologies for developing a base year CHE emissions inventory
when port-specific data on equipment activity, engine power, and/or model year are not available. As
these methodologies rely on surrogate sources of data that are not specific to the port, the resulting
inventory may not be as useful for decision making purposes as an inventory calculated with the
detailed methodology described above. For example, an inventory that relies on surrogate sources
would not necessarily help determine which specific types of CHE should be targeted for future
replacements. However, at a minimum, such inventories may be useful to estimate the order of
magnitude of CHE emissions in comparison with other port sectors, which could be useful in
determining which sector or sectors should be the focus of additional data gathering efforts.
6.7.1 Missing Model Year Data
If a representative sample of an equipment type has model year data, units with missing model years
can be assumed to have the average value. However, if there are not enough model year data for this
kind of analysis, a weighted emission factor that does not vary by model year can be used in the
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inventory calculation instead. This method relies on the median life and scrappage assumptions used by
MOVES-Nonroad.35 The same steps outlined in Section 6.5 should be used to produce CHE emission
factors with the following modifications:
1. In the General Output Panel, only select SCC (do not select model year or hp class).
2. After the run has finished, the MOVES-Nonroad post-processing menu should be used to run the
EmissionFactors_per_hphr_by_SCC.sql script on the output database. This step will generate
emission factors in grams per horsepower-hour by SCC (for each month and day type) for each
pollutant selected based on the model run output.
The emissions inventory can then be calculated following the same five steps in Section 6.6, except the
emission factors are assigned only by SCC instead of SCC, model year, and engine power bin.
6.7.2 Missing Equipment Hours of Use and/or Engine Power Data
If a representative sample of units of an equipment type have hours of use and/or engine power data,
units missing these data can be assumed to have the average value(s). However, if there are insufficient
data for this kind of analysis, surrogate averages from an existing detailed port inventory may be used
instead, but the resulting inventory would be less precise than using local data. This method assumes
that the surrogate port's CHE activity is similar in scope as the port in question. Therefore, care should
be taken in reviewing recent port inventories; a surrogate port should have the same order of
magnitude of cargo throughput and similar operational profiles. If a suitable match is found, the
emissions inventory can be calculated following the same steps in Section 6.6, just using the average
values by equipment type for CHE hours of use and/or engine power data from the surrogate port's
detailed emissions inventory.
6.8 Projecting Future Emission Inventories
Future CHE emissions should be projected from a base year inventory, developed as described in the
sections above. In general, the projection process follows these steps:
1. Activity growth rates are applied to the base year activity to estimate future activity
2. Equipment model years are adjusted to account for fleet turnover to newer, cleaner engines
and emission factors are reassigned
3. Projected emissions are calculated using the estimated future activity
4. Projected emissions are aggregated to the same level of detail as the base year inventory, as
determined by the purpose of the inventory
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations. Projected changes in activity should
be determined for each CHE type. Local port projections or other regional forecasts are usually by
commodity type and/or business sector; these projections by commodity type can be applied to the CHE
types that handle the various commodities (i.e., containerized, dry bulk, liquid bulk, and break bulk).
If local port projections or other regional forecasts are unavailable, the Freight Analysis Framework
(FAF)11 can be used to forecast growth instead. If this is used, the commodity flows in the FAF assigned
to all transportation modes should be grouped by the appropriate CHE types when calculating growth.
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For example, all commodity types that can be containerized should be included when determining the
growth rates for CHE types that move containers. If detailed growth by commodity type and/or
business sector is not available, or for CHE types that are involved in moving different kinds of cargo,
total port growth can be used instead of commodity-specific growth.
The growth rates should then be applied to the base year hours of operation for each CHE unit.
To reflect fleet turnover, the equipment model years that were used in the base year inventory should
be adjusted for use in the future year inventory. If the port or region has already identified an expected
future age distribution (or if a fleet manager has identified their expected fleet retirements and
replacements), that information should be used in determining how to adjust the model years. If the
future age distribution is unknown, it can be assumed to be the same as the base year age distribution.
That is, it can be assumed that in the future, the percentages of CHE that are brand new, one year old,
two years old, etc. are the same as those percentages in the base year inventory. Functionally, this can
be implemented by adding the difference between the future and base years to each model year used in
the base year inventory, to get a new set of model years for the future year inventory. For example, if
the base year inventory is for 2020 and the projected inventory is for 2030, the difference of 10 years is
added to each model year. In this example, a model year 2005 CHE in the base year inventory would be
model year 2015 CHE in the 2030 inventory.
Additionally, any planned action or emission reduction strategies that have been committed to that
would affect future emissions should be included according to the actual expected implementation of
such commitments. For example, if a port has committed to replacing or repowering its oldest ship-to-
shore cranes through authorization of funds for such purchases, the effects of such a program should be
reflected in the projected age distribution. Note that if the future year inventory is for a regulatory
purpose, planned future actions should be included only if written commitments have been made by the
agency or operator with the power to implement them.
The emission factors for the projection year should be determined using the same method as the base
year (as described in Section 6.5), except the MOVES user should select the projection year on the Time
Spans Panel instead of the base year. The resulting emission factors should be assigned to each CHE
unit using the adjusted model years.
Once the base year activity has been scaled and appropriate emission factors are assigned to each unit,
the projected future emissions can be calculated using the same methodology at the same level of detail
as the base year inventory, and the resulting emissions inventory should be aggregated to the same
level of detail as the base year inventory.
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7 Onroad Vehicles
7.1 Source Description
The onroad vehicles sector includes cars, buses, trucks, and other motor vehicles that operate on roads.
This section could be used to quantify emissions for onroad vehicle activity occurring on the grounds of
a port and also on nearby transportation corridors outside the port boundary that are determined to be
appropriate to include, based on the purpose of the inventory. For convenience, the term "port-
related" in this section refers to the onroad emissions being included, whether just at the port or also
outside the port's boundary. Section 7.2.2 discusses geographical scope in further detail.
While this section is focused on estimating emissions that are port-related, it could also be used to
estimate emissions at other locations where cargo is moved, such as off-port cargo distribution centers
or intermodal freight terminals where freight is transferred between rail and trucks.
The types of onroad vehicles and their activity included in a port-related inventory will depend on the
main function(s) of a given port. For example, a facility focused on freight will likely be serviced by an
onroad vehicle fleet consisting of heavy-duty diesel trucks, whereas a cruise port may include large
numbers of gasoline-fueled passenger vehicles and shuttle buses as well as diesel vehicles that service
cruise ships with fuel and other supplies. Vehicle types to be considered in a port-related emissions
inventory may include (but are not limited to):
Heavv-Dutv Vehicles Light-Duty Vehicles
• Drayage Trucks • Passenger Cars and Trucks
• Long-Haul Trucks • Passenger Vans
• Shuttle Buses • Import/Export Vehicles
• Refueling Trucks • Maintenance Vehicles
While this document does not specifically include methodologies for all onroad vehicle activity cases, it
seeks to provide some conceptual approaches to address a range of activities. For example, a port that
includes vehicle imports or exports via roll-on/roll-off vessels (i.e., where vehicles are driven off a ship)
may want to include the emissions from those vehicle movements and storage. The methods and
approaches in this document can be applied or adapted to most onroad vehicle activity.
7.2 Overview of Approaches and Considerations for Developing an Onroad Vehicle
Emissions Inventory
This section describes data sources and general approaches could be relevant for any port or freight
terminal inventory, regardless of location. For U.S. states and territories other than California, EPA's
MOVES model is the primary tool for estimating emissions from onroad vehicles.3 When using MOVES
to develop an onroad emissions inventory, the most recent version should be used. Inventories of
onroad vehicle emissions in California should reference guidance for the latest version of California Air
a For more information, see https://www.epa,gov/moves.
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Resources Board's onroad emissions model, EMFAC, instead of the information here for using MOVES.b
Note, neither MOVES nor EMFAC can estimate road dust emissions. EPA has alternate methods for
calculating road dust detailed in Section 6 of EPA's PM Hot-spot Guidance.41
MOVES includes the ability to model onroad emissions at different analysis "scales" and with different
calculation types, which are discussed further in Section 7.3. MOVES also allows users to make choices
that reflect the conditions in their local area. The two scales discussed in this document are:
• County Scale: This scale uses local data on the number and types of vehicles, how many miles
they travel within the geographical domain, and various fleet characteristics, such as age
distributions. When using this scale to estimate port-related onroad emissions, the
geographical domain of the inventory is modeled as a "county" that includes only the activity
occurring in that area (i.e., the activity that is port-related), and MOVES produces a total onroad
vehicle emissions inventory that does not need further post-processing. The approach that uses
County Scale is detailed in Section 7.5.
• Project Scale: This scale uses more detailed data than County Scale. In addition to the local data
described above, Project Scale allows the MOVES user to model a series of links that represent
different types of vehicle activity that is port-related. Using this scale, activity-based emission
factors for each onroad vehicle type operating in the area of interest are developed, and the
port-related onroad emissions inventory is calculated by post-processing the MOVES results.
Then, link emissions rates are scaled up and summed to develop an inventory for a specific
period of time, such as a day or a year. The approaches that use Project Scale are detailed in
Section 7.6 and Appendix I.
These scales are discussed in more detail below in Section 7.3.1. Additionally, the MOVES Technical
Guidance37 and MOVES User Guide39 contain background information on how to use MOVES. Note that
EPA has issued guidance for developing inventories for onroad sources. Rather than duplicating existing
guidance, this section describes the general approaches for developing an onroad vehicle inventory but
refers the reader to EPA's existing guidance as appropriate.
7.2.1 Inventory Purpose and Other Considerations
The choice of modeling approach and the geographical scope covered by the inventory will depend on
the purpose or end use of the inventory. If the purpose of the inventory is regulatory, please consult the
appropriate EPA guidance document. The following discussion highlights some potential inventory
purposes and associated analysis considerations.
• Regulatory Application - State Implementation Plan (SIP): If the purpose of the emissions
inventory is for use in a SIP, the analysis should follow the MOVES Technical Guidance to ensure
that the applicable SIP requirements are met.
• Regulatory Application - Hot-spot Analysis: If the purpose of the analysis is to develop
emissions for use in a PM hot-spot analysis, emissions must be geographically allocated.
Guidance on the use of the Project Scale in MOVES for quantitative hot-spot analysis in
b For more information, see httpsi//ww3,arbxa,go¥/ms_ei/msei,htm.
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nonattainment and maintenance areas is described in the PM Hot-spot Guidance.0 See
Appendix I for more information.
• Non-Regulatory Application - Air Quality Analysis: If the inventory is for an air quality analysis
not related to transportation conformity, such as corridor level analysis, MOVES at the Project
Scale should be used with the project scale refined approach (see Appendix I for more
information). However, since the purpose is non-regulatory, there would be more discretion
regarding the number of runs needed to capture variations in activity levels and the overall
geographical scope to be included in the analysis.
Another consideration is whether emissions of volatile organic compounds (VOCs) or air toxics are to be
included in the analysis for the onroad vehicle inventory. Evaporative processes that occur when
gasoline vehicles are parked can account for a significant portion of gaseous hydrocarbon emissions
from gasoline vehicles. Because the MOVES at the Project Scale estimates emissions for one hour at a
time, it does not capture evaporative process emissions associated with soak activity. If VOCs or air
toxics need to be included in the inventory, these can be estimated with the County Scale. Either the
County Scale approach can be used for the entire inventory, or a Project Scale approach can be
supplemented with a County Scale run for just these emissions.
In general, if the purpose of the inventory is not related to a regulatory application, there can be more
flexibility in the approach and geographical scope. Additionally, an inventory with a finer level of detail
may provide greater value for port authorities and terminal operators for identifying potentially efficient
mitigation strategies or control measures or other areas for operational changes.
7.2.2 Geographical Scope
The geographical scope of the inventory is a key consideration for the onroad vehicle sector, and part of
this consideration is to determine what near-port transportation corridors and associated road types to
include in the inventory. For example, the boundary of the inventory may include areas under
jurisdiction of the local port authority only and exclude transportation corridors servicing the port.
Alternatively, boundaries may be chosen to characterize all port-related emissions in an air basin and
would thus include activity on nearby transportation corridors such as drayage movements to off-port
rail facilities, short-haul truck movements to cross-docking facilities and local customers, or passenger
car trips and long-haul truck movements to and from the boundary of the defined geographical scope.
Regardless of which approach is employed, the scope of the inventory should be decided in advance of
any calculations and remain consistent and in accordance with the inventory's purpose.
If the port-related emissions inventory is to be combined with a larger regional emissions inventory
(e.g., for SIP purposes), including roads outside of the port could possibly result in double counting the
emissions from activity on these roads. However, there could be cases where roads outside the port
boundary should be included in the port onroad inventory. For example, if the port has a long access
road that is not a public road and therefore not included in the regional transportation network model,
activity on that access road would be appropriate to include in the port inventory. If the purpose of the
c A PM hot-spot analysis is an estimation of likely future localized pollutant concentrations and a comparison of
those concentrations to the relevant NAAQS. It is required only for certain kinds of transportation projects in
PMio and PM2.5 nonattainment and maintenance areas. See 40 CFR 93.101, Hot-spot analysis definition, and 40
CFR 93.123(b).
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inventory is related to an overall inventory for a SIP, the interagency consultation process should be
used to determine the geographical scope of the port-related inventory.
7.3 Overview of MOVES
MOVES can be used to estimate emissions from port-related onroad vehicles directly or to develop
emission factors that can then be used to create an inventory outside of the model. This section
summarizes the different ways that MOVES can be run, including basic inputs, advantages, and
limitations of each approach.
7.3.1 Scale and Calculation Type
A key feature of MOVES is the ability to estimate emissions at different analysis scales and calculation
types. MOVES can analyze mobile emissions at different scales: National, County, and Project. For the
purposes of port-related onroad vehicle inventory development, EPA recommends using either the
County or Project scales.d For more information on MOVES scales, see Section 3.2.2 of the MOVES
Technical Guidance for more information.
The County Scale can be used to create onroad vehicle emissions inventories for an individual or multi-
county area, a metropolitan area, a region of a state, an entire state, or a multi-state area or region. The
County Scale can also be used to model a smaller geographical area, such as the area covered by the
port-related inventory.
The Project Scale allows the modelling of a set of individual roadway links and/or parking area(s) where
driving activity occurs or where vehicle parking and starts occur, and links can be defined to represent
the port-related activity.® At the Project Scale, each MOVES run represents one specific hour of a single
day of a single year. Therefore, if the Project Scale approach is selected for generating a port related
onroad vehicle inventory, the MOVES user would need to consider the number of runs needed to
represent the port conditions at the temporal scale of the inventory, such as a day or a year (discussed
further in section 7.6.1.2).
MOVES can also be configured between two calculation types: Inventory or Emission Rates. Selecting
Inventory produces an output of total emissions in a specified unit of mass. Selecting Emission Rates will
provide emission factors in terms of units of mass per unit of activity, which can then be multiplied by
d At the National Scale, MOVES uses a default national database that allocates emissions to the state and county
level based on a mix of national data, allocation factors, and some preloaded local data. As the default data in
the national database may not be the most current or best available information for any specific area, it is not
recommended to use the National scale option when developing port-related emission inventories.
e Note that hotelling activity is usually not included in port-related onroad inventories. In this context, hotelling
refers to the activity of long-haul trucks when the vehicle is parked, often overnight, during driver rest periods
while heating/cooling equipment or appliances are in use. This activity places a load on the engine, auxiliary
power unit, or electrical hookup. This activity is characterized separately from idling during "workday" truck
operation such as queuing at a distribution center, loading freight, etc. Hotelling is assumed not to occur directly
on ports, however, may occur within the broader region. For more details on hotelling activity, refer to Section
4.13 of the MOVES Technical Guidance or Module 3 of the MOVES Training (see reference 42).
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different units of activity for inventory development/ Both the County Scale Approach (Section 7.5) and
the Project Scale Generic Link Approach (Section 7.6.2) use the Inventory calculation type.
7.3.2 Pollutants and Processes
MOVES can provide onroad vehicle emissions for many pollutants including criteria air pollutants,
greenhouse gases, and air toxics. Those selected when running MOVES would be based on the purpose
of the inventory, as discussed in Section 2.
In MOVES, "Pollutant" refers to particular types of pollutants or pollutant precursors, such as nitrogen
oxides (NOx), while "Process" refers to the mechanism by which emissions are created, such as running
exhaust or start exhaust. Processes in MOVES are mutually exclusive types of emissions, and users need
to select all processes associated with a specific pollutant to account for all emissions of that pollutant.
Typically, it is recommended to select all processes for each pollutant selected. However, some
processes may not be applicable for a given port-related inventory. For example, if no onroad vehicle
refueling occurs within the scope of the inventory, "Refueling Displacement Vapor Loss and Refueling
Spillage Loss" could be excluded; likewise, assuming the port has no hotelling activity (i.e., a truck driver
runs the engine overnight while sleeping in the cab), the "Extended Idle and Auxiliary Power Unit"
processes would not be included in the MOVES runs. Note, some pollutants in MOVES need the
selection of other prerequisite pollutants and processes. For example, selecting the prerequisites for
"Primary Exhaust PM2.5 - Total" will select elemental carbon, which is an indicator for black carbon
(BC).
In general, pollutant and process selections should be consistent with the specific purpose and scope of
the emissions inventory. If there is the possibility that a pollutant would be needed in the emissions
inventory, it may be desirable to include it. It is easier to request MOVES results for pollutants that are
ultimately not used than to decide after MOVES is run that another pollutant is needed. In such a case,
another MOVES run would be necessary.
For methods to estimate energy consumption for this source sector, see Appendix A.
7.4 Port-Related Onroad Vehicle Inventory Data Needs
This section describes the data needs and possible sources for developing a port-related onroad vehicle
emissions inventory. Gathering accurate data on vehicle characteristics (vehicle types, counts, age, etc.)
and activities (vehicle travel speeds, idling time, etc.) is paramount for developing a robust onroad
vehicle inventory. Likewise, better vehicle data improves the potential for identifying specific
operational improvements.
Generally, vehicle data can be gathered from a variety of sources. In many cases, conducting site-
specific manual counts and surveys can yield the most complete data set for use in inventory
development. Additionally, port authorities or port operators could partner with their state's
transportation or air quality agency to conduct traffic studies and collect vehicle activity and fleet
characteristic information. These types of partnerships encourage information sharing and can improve
the data used to develop an inventory.
f A port-related inventory could be developed using the Emission Rates calculation type, but this method is not
covered in this document.
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7.4.1 Fleet Characteristics
An onroad emissions inventory should account for the type, number, and the ages of vehicles in a fleet
operating at a port and on nearby onroad transportation corridors if within the scope. To conduct a
MOVES run, the following information is needed to describe the onroad vehicle population:
• Vehicle types (called "source types" in MOVES)
• Vehicle counts (by source type)
• Vehicle age (model years of vehicles are used to determine an age distribution by source type),
and
• Diesel retrofit devices and replacements or other emission mitigation measures in use.g
7.4.1.1 Vehicle Types
An onroad vehicle emissions inventory should include all the vehicle types used within the inventory
scope. Vehicle counts should be aggregated by vehicle type. In MOVES, vehicles are classified into
source types, which are groups of vehicles with similar activity and usage patterns. MOVES source types
and the associated Federal Highway Administration (FHWA) Highway Performance Monitoring System
(HPMS) vehicle classes are listed in Table 7.1, and the various source type and fuel type combinations
that MOVES can model are listed in Table 7.2 below.43
Table 7.1. MOVES2014 Onroad Vehicle Source Types
SourceTypelD
Source Type
HPMSTypelD
HPMS Description
11
Motorcycle
10
Motorcycles
21
Passenger Car
25
Light Duty Vehicles
31
Passenger Truck
32
Light Commercial Truck
41
Intercity Bus
40
Buses
42
Transit Bus
43
School Bus
51
Refuse Truck
50
Single Unit Trucks
52
Single Unit Short-haul Truck
53
Single Unit Long-haul Truck
54
Motor Home
61
Combination Short-haul Truck
60
Combination Trucks
62
Combination Long-haul Truck
g For onroad vehicles such as drayage vehicles, retiring older trucks and engines and replacing them with new
equipment plays a major role in reducing emissions. In general, vehicle replacement, rather than retrofit, is a
more effective option for port-related heavy-duty vehicles.
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Table 7.2. Allowable Source Type and Fuel Type Combinations in MOVES2014 (Allowable
combinations are marked with X)
SourceTypelD
Source Type
Gasoline
Diesel
CNG
E-85
Capable
Electricity
11
Motorcycle
X
21
Passenger Car
X
X
X
X
31
Passenger Truck
X
X
X
X
32
Light Commercial Truck
X
X
X
X
41
Intercity Bus
X
42
Transit Bus
X
X
X
43
School Bus
X
X
51
Refuse Truck
X
X
52
Single Unit Short-haul Truck
X
X
53
Single Unit Long-haul Truck
X
X
54
Motor Home
X
X
61
Combination Short-haul Truck
X
62
Combination Long-haul Truck
X
A port-related onroad vehicle fleet may include vehicles such as drayage trucks, shuttle buses, service
vehicles, and different varieties of passenger cars and trucks. Generally, the types of vehicles serving a
port could include the following, and should be modeled as the MOVES source types noted:
• Drayage trucks and other local delivery tractor-trailer trucks: Drayage trucks are generally
diesel-fueled, heavy duty (Class 8) trucks that transport containers and bulk freight between the
port and intermodal railyards, distribution centers, and other near-port locations. A common
practice is to use older trucks that are near the end of their useful life to serve as drayage trucks
because of the lower annual mileage accumulation and proximity to repair facilities. In MOVES,
drayage trucks and other local delivery tractor-trailer trucks should be modeled as Combination
Short-haul Trucks (sourceTypelD 61).
• Tractor-trailers operating on long-distance routes: These vehicles are generally diesel-fueled,
heavy-duty (Class 8) trucks that transport containers and bulk freight long distances (i.e., 200
miles or more from the port). In MOVES, these vehicles should be modeled as Combination
Long-haul Trucks (sourceTypelD 62).
• Passenger vehicles: These vehicles are light-duty cars and trucks used for passenger transport.
In MOVES, these vehicles should be modeled as Passenger Cars and Passenger Trucks,
(sourceTypelDs 21 and 31, respectively).
• Light-duty service vehicles: These vehicles include may include gasoline or diesel-fueled
maintenance trucks and shuttle vans. In MOVES, these vehicles should be modeled as Light
Commercial Trucks (sourceTypelD 32).
• Shuttle buses and motor coaches: These vehicles are used to bring passengers to or from the
site or transport passengers on-site. In MOVES, these vehicles should be modeled as Intercity
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Buses (sourceTypelD 41) if they operate over long distances, or as Transit Buses (sourceTypelD
42) if they operate on regular, fixed schedules.
• Other heavy-duty trucks: These vehicles are generally large, heavy-duty service vehicles, such as
refueling trucks and other support vehicles. In MOVES, these vehicles should be modeled as
Single Unit Short-haul Truck (sourceTypelD 52) or as Long-haul Truck (sourceTypelD 53) if used
on long distance routes (i.e., routes that extend 200 miles or more from the port).
7.4.1.2 Vehicle Counts
Capturing the number of vehicles by source type is another key aspect of developing an onroad vehicle
emission inventory. Vehicle counts can be gathered from a variety of sources. Many state Departments
of Transportation (DOTs) have permanent highway sensors in place that can separate heavy-duty truck
counts from passenger cars and trucks, and other vehicles. However, these sensors are typically located
on highway segments, which means the raw traffic volume numbers do not account for traffic entering
and exiting via highway ramps. These counts are generally available through FHWA HPMS data sets,
state DOTs, or local transportation planning agencies. These counts could serve as a basis of port-
related vehicle counts, but further refinement may be necessary.
There are numerous other technologies that could assist with vehicle counts. Automatic vehicle
classification counters co-located with manual survey locations may best provide an overall estimate of
the traffic volume, vehicle type, and vehicle speeds. Automatic counters provide continuous counts for
a longer period than is practical with manual surveys. Vehicle classification counters that identify the
type of trucks can only be deployed across a single lane of traffic, while the more commonly used total
vehicle counters can be used over multiple lanes. FHWA has identified other equipment for traffic data
collection in the Highway Performance Monitoring System Traffic Data for High-Volume Routes: Best
Practices and Guidelines report.44
In addition to the vehicle count sources above, depending on the type of port activity, vehicle gate
counts, parking receipts, and passenger counts could also be sources of information to determine the
number of vehicles arriving at and operating on port.
7.4.1.3 Age Distribu tion
Age is an important factor in calculating onroad vehicle emission inventories because older vehicles tend
to produce higher emissions. A vehicle's age is the difference between its model year and the inventory
year. Age distributions in MOVES vary by source type and range from zero to 30+ years, so that all
vehicles 30 years and older are modeled together. As such, an age distribution is comprised of 31
fractions, where each fraction represents the number of vehicles present at a certain age divided by the
vehicle population for all ages.
To build a MOVES-compatible age distribution table, there are three options depending on data
availability that are presented in order of specificity. For each vehicle type, inventory preparers should
use the best option for age distribution that is supported by the data available. Age distribution can
have a considerable impact on emission estimates, so the most specific information available should be
used:
1. For fleets that operate locally, such as drayage trucks, the MOVES user should provide specific
fleet age distribution data. For these locally-based fleets, an exact age distribution could be
obtained from on-terminal truck registrations or license plates studies.
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2. If a port-specific age distribution is not available, MOVES users should use the latest state or
local age distribution assumptions from their SIP or transportation conformity regional
emissions analysis, which would be available from the state air quality agency or the local
metropolitan planning organization if the port is located in or near an ozone, PM, or other
nonattainment or maintenance area.
3. If no state or local age distribution is available, the MOVES default age distribution could be
used.h The MOVES user can select the analysis year(s) and find the corresponding age
distribution. These fractions are national defaults and could be significantly different than the
local age distribution. Default data should be used only if more representative data set (e.g.,
reflecting port-related vehicles or a state or local information) cannot be obtained.
Short-distance, drayage transportation of freight tends to be performed by older trucks, while long-
distance movements generally rely on newer and more fuel-efficient equipment. The age distributions
used for combination short-haul and combination long-haul trucks should reflect differences in the ages
of these different source types.
Truck license plate sampling is a direct way to collect and determine truck age distributions and other
fleet characteristics. For example, at the Port of Oakland, researchers developed and implemented a
truck-traffic survey in West Oakland, California. During the manual truck counts, the license plates of at
least 10 trucks that entered the survey intersection per hour were recorded. License plate information
was cross-refenced with a California's Department of Motor Vehicles database to gather information on
the model year, fuel type, manufacturer's maximum gross vehicle weight ratings (GVWR), the number of
axles, the city of registration, and zip code of registration.45
7.4.1.4 Vehicle Retrofits and Replacements
The MOVES model does not incorporate assumptions on the existence of any local projects to retrofit
emission reduction technologies on onroad diesel vehicles or to replace older vehicles with newer,
cleaner ones. If such a program is in place, MOVES users should account for it in a port-related
inventory. For more information, see EPA's Diesel Retrofit and Replacement Guidance which addresses
retrofit and replacement projects in detail.40 Section 2.5 of the Diesel Retrofit and Replacement
Guidance describes how to quantify emission reductions from diesel emission reduction strategies, such
as a drayage truck replacement program; Section 2.6 describes how to quantify emission reductions
from onroad vehicle or engine replacement projects.
7.4.2 Vehicle Activity
Characterizing vehicle activity for on-port terminals and on near-port corridors is critical for calculating
emission inventories. Vehicle activity in this context includes running, parking, and starting activity.
7.4.2.1 Running Activity
Generally, port-related running activity can be broken down into three stages: activity on near-port
transportation corridors (if within the inventory's scope), queuing activities such as creep and idling
occurring at gates, and activity within the port.
If within the inventory scope, port-related vehicle activity on transportation corridors such as highways
and access roads to the port should be included in the onroad vehicle emissions inventory. This activity
h For more information, see www.epa.gov/otaq/models/moves/tools.htm.
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captures vehicle travel to and from the port facilities such as truck trips to nearby freight facilities or
warehouses and passenger travel. To characterize this activity, MOVES users would define the route
lengths, in miles, and estimate the number of port-related trips by vehicle type and vehicle speeds in
miles per hour.
Gate queuing, which includes creep and idling, should be characterized separately from activity on near-
port transportation corridors because it has a substantially different driving cycle. Users should consider
where gate queuing activity occurs. Gate queuing by drayage vehicles or passenger vehicles may occur
in different areas as vehicles approach different terminals. The length of the queuing area may vary
depending on the level of activity at a given terminal but should generally reflect the distance from
where gate queuing starts to the terminal entrance gate. Gate queuing activity should also be
characterized by distance traveled (in miles) within the queuing area, number of trips by source type,
and vehicle speeds (in miles per hour) within the queuing area. Truck queuing data may be limited if the
terminal operators do not capture queue times; however, surveying drivers may be a helpful source of
information.46 Alternatively, if hours of wait time by source type is known, this information can be used
in the Project Scale approach described in Section 7.6 without the other information (distance traveled,
number of trips by source type, or vehicle speeds).
Running activity within the port may include driving along drayage routes and driveways. This activity is
likely dominated by low speed driving with frequent stops and short periods of acceleration.
Running activity types described above are quantified as vehicle miles traveled (VMT) by source type
and allocated by road type. Most or all running travel activity in a port-related onroad vehicle emissions
inventory would most likely correspond to the urban unrestricted road type in MOVES (roadTypelD 5).
However, if the inventory includes other road types, such as restricted access highways (i.e., highways
with entrance and exit ramps), the MOVES user will need to estimate this activity by source type, and
distribute travel activity by source type to other road types as appropriate. If the emissions inventory
will support regulatory purposes, the interagency consultation process should be used to determine the
geographical boundaries, including which roads to include, and how to address and minimize double
counting or missing emissions.
Estimating a vehicle speed distribution can be a complex process. For a county-wide inventory, a typical
approach for estimating average speeds is to post-process the output from a travel demand network
model. However, travel demand models are unlikely to cover the details of traffic within a port. A
detailed approach is to process on-vehicle Global Positioning System (GPS) data. GPS dataloggers could
be used to collect speed data from a sample of vehicles traveling within the port. This data could then
be used to construct an average speed distribution for use in the County Scale approach, calculate a link-
level average speeds for the Project Scale approach, or develop a second-by-second link drive schedule
for use in the Project Scale approach.
7.4.2.2 Vehicles Parked and Starts
Depending on the port's business activities, the port may store large numbers of vehicles on site for
some duration. For example, at a cruise terminal, cruise passengers may park their vehicles during the
duration of their trip at a terminal parking facility. Similarly, a terminal that handles a high number of
new passenger import/export vehicles may store these vehicles in onsite lots at some stage during their
shipment. While stored, vehicles can still produce emissions through evaporative processes. To
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estimate this activity, the number of vehicles and duration of time parked by source type should be
captured. As noted earlier, emissions associated with evaporative processes would be estimated at the
County Scale.
Vehicle start emissions are closely associated with parking activity. Start emissions are determined
based on the time a vehicle has been parked prior to the engine starting ("soak"). Vehicle start
emissions can be estimated with either the County Scale or the Project Scale approach. At the County
Scale, MOVES applies an average default operating mode distribution that will apply to the parking
activity. For the Project Scale approach, users can define parking activity with the operating mode IDs
(opModelD) in Table 7.3 to describe the amount of time a vehicle is parked.
Table 7.3. MOVES Parking-Related Operating Modes
OpModelD
Operating Mode
101
Soak Time < 6 minutes
102
6 minutes < Soak Time < 30 minutes
103
30 minutes < Soak Time < 60 minutes
104
60 minutes < Soak Time < 90 minutes
105
90 minutes < Soak Time < 120 minutes
106
120 minutes < Soak Time < 360 minutes
107
360 minutes < Soak Time < 720 minutes
108
720 minutes < Soak Time
All start and parking activity would be modeled using the off-network road type in MOVES (roadTypelD
1).
Parking and start activity information can be gathered from a variety of sources. For passenger vehicles,
parking receipts may be a source of information detailing parking duration (soak time) and starts can be
approximated as one start per park. For service vehicles, starts and parking activity should be collected
for a "typical" work day. For vehicles such as drayage trucks, some local governments and port
authorities have instituted policies and programs that require truck drivers to turn off engines if idling is
expected to exceed a certain duration such as during queuing, loading, and unloading activities. These
programs may generate additional start activity that should be included in the onroad vehicle emissions
inventory.
7.5 County Scale Approach for Developing an Onroad Vehicle Inventory
Running MOVES at County Scale takes advantage of features built into MOVES that simplify the process
of developing a base year inventory. In this approach, the MOVES user treats the area included in the
inventory as if it were a county, using inputs that describe the total fleet and activity within the area
rather than the total fleet and activity in the whole county.
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Table 7.4. Overview of Developing Onroad Vehicle Emission Inventories Using MOVES at the County
Scale
Data Needs
Advantages
Considerations
Local information for:
• VMT
• Vehicle population
• Fleet age distribution
• Average speed distribution
• Road type distribution
• Fuel characteristics
• Access to MOVES default
database for some inputs
• Includes output for all
evaporative emission processes
• Can produce an annual inventory
without post-processing
• Does not provide the detailed
spatial distribution of
emissions provided by a
Project Scale approach, which
may be useful depending on
the inventory purpose(see
Section 7.2.1)
7.5.1 Setting up a County Scale RunSpec for a Port
To produce an onroad vehicle emissions inventory using the County Scale, a MOVES Run Specification
(RunSpec) is created to define elements such as time period(s), geographical area, source types, etc. to
be included in the modeling. These elements are defined in a series of panels in the MOVES Graphical
User Interface (GUI). When setting up a County Scale RunSpec for a port-related and/or goods
movement onroad vehicle emissions inventory, the following selection should be made:
1. Scale Panel: Select "Onroad" model and "County" for domain/scale. Calculation type should be
specified as "Inventory."
2. Time Spans Panel: Select the inventory year (e.g., 2020 for a 2020 base year inventory), all
months, both day types (weekday/weekend), and all hours to ensure the inventory includes the
entire year. Time aggregation should be set to "hour," which indicates no pre-aggregation and
most accurate inventory calculation. Note, only a single year can be selected in a County Scale
run.
3. Geographic Bounds Panel: Select the county containing the port in the Geographic Bounds
panel. Note, if the port spans multiple counties, the county containing most of the port should
be selected.
4. Onroad Vehicle Equipment Panel: Add the fuel type/source type combinations operated within
the boundaries of the port-related inventory (as described in Section 7.4.1). For fuels, select all
fuel types available for each source type.
5. Road Type Panel: Select the road types that are to be included in the inventory scope. The
driving behavior of vehicles traveling within the port itself is likely to be most like the Urban
Unrestricted category, which includes urban arterials, collectors, and local streets. If the area of
analysis includes other roads types, such as a restricted access highway with ramps that provide
access to the port, include the Urban Restricted category as well. Always select Off-Network to
include calculation of emissions from engine starts and evaporative emissions from parked
gasoline vehicles.
6. Pollutants and Processes Panel: Select all processes of the pollutants of concern. Note, running
MOVES at the County Scale can estimate emissions associated with the fuel vapor venting
process; these emissions cannot be estimated using MOVES at the Project Scale (see Section
7.2.1).
7. Manage Input Data Sets Panel: This panel is not needed and should be skipped.
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8. Strategies Panel: The Strategies Panel provides access to the Rate of Progress option. The Rate
of Progress Panel includes a checkbox which, when checked, disables all motor vehicle
requirements of the 1990 Clean Air Act Amendments. This panel is not needed for inventory
development and should be skipped.
9. General Output Panel: Choose units for emissions and distance. EPA recommends choosing
"grams" and "miles" for these units. EPA also recommends selecting "Distance Travelled" and
"Population" under the "Activity" heading. These results can be used as a quality assurance
check when reviewing the run's output.
10. Output Emissions Detail Panel: Select the level of detail needed in the model output. Selecting
more detail results in larger output files but provides more flexibility for further review and
analysis of the MOVES results. For example, choosing "Year" for the time period will result in a
simple annual inventory. Choosing "Month" produces results for each month, which may allow
the analysis of how emissions vary throughout the year. The inventory purpose will inform the
level of detail needed for the time period selections in this panel. Of the other choices, "Source
Use Type" might be a useful option to select, as it allows the user to distinguish the relative
contributions of different source types to the total inventory.
11. Advanced Performance Features Panel: This panel is not needed and should be skipped.
7.5.2 Using the County Data Manager to Enter Port-Specific Data
Once the RunSpec is completed, the County Data Manager (CDM) is used to enter activity and fleet
information specific to the area of analysis. For a typical county-level inventory, the MOVES user would
enter information that applies to the entire county. In this case, the MOVES user will enter the
applicable port-related information.
7.5.2.1 Meteorology Data
The meteorology input allows the MOVES user to enter an average 24-hour temperature and humidity
profile for each month of the year. The MOVES default database includes average monthly meteorology
data for every county in the country based on 10 years of data from the National Climatic Data Center.
For non-regulatory purposes (e.g., will not be used as part of a SIP or conformity analysis), the default
data in MOVES for the county containing the port can be used. When the port-related inventory will be
incorporated into a larger inventory to be used for a SIP or conformity analysis, the meteorology inputs
should be the same as those used for the rest of the inventory.
7.5.2.2 Source Type Population
At County Scale, vehicle populations by source type are used to calculate evaporative emissions and can
also be used to calculate start emissions. It is a necessary input at this scale and should represent the
average number of vehicles in a typical day, by source type, that are present within the boundaries of
the geographical area addressed by the inventory. See section 7.4.1.2 for more information on sources
of vehicle counts for source type population inputs.
7.5.2.3 Age Distribution
As discussed in Section 7.4.1.3, the age distribution of the vehicles in the analysis is an important input
in MOVES and having accurate vehicle data improves the potential for identifying specific operational
improvements. The age distribution by source type should be representative of the vehicles in use at
the port.
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7.5.2.4 Vehicle Miles Traveled (VMT)
Vehicle miles traveled is a necessary input and should be based on estimates of vehicle activity within
the boundaries of the inventory. MOVES can accept VMT information provided in terms of HPMS
vehicles types or MOVES sources types and provides two options for the time period of VMT
information as either an annual or daily value. Any of these combinations can be used, depending on
data availability. Choices include entering VMT by:
7.5.2.5 Hotelling
In the onroad context, hotelling refers to the activity of long-haul trucks when the vehicle is parked,
often overnight, during driver rest periods while heating/cooling equipment or appliances are in use.
Hotelling is assumed not to occur directly on ports; however, MOVES includes default hoteling activity
for county scale runs. Default activity is based on VMT assigned to the rural restricted road type
(roadTypelD 5). If the rural restricted road type is included within the geographical scope of the
analysis, it is necessary to enter zeros for all rows in the hoteling hours column in the HotellingHours
table for the Hotelling tab input. If this is not done, the county scale run will calculate extended idling
emissions if the rural restricted road type is included.
7.5.2.6 Fuel
Onroad vehicle emissions also depend on what fuels and fuel mixes are used. MOVES includes default
fuel information by county, month, and year. MOVES users should review the default fuel supply and
fuel formulation information provided in MOVES and make changes only where precise local volumetric
fuel property information is available or where local fuel requirements have changed.
One exception is in the case of Reid Vapor Pressure (RVP); the MOVES user should change this value to
reflect any specific local or state regulatory requirements and differences between ethanol- and non-
ethanol blended gasoline not reflected in the default database. Any changes to RVP (or to any other
gasoline fuel formulation parameters) should be made using the "Fuels Wizard" tool in the Fuel Tab of
the CDM. This process is described in more detail in Section 4.9.1 of the MOVES Technical Guidance.
Note that the Fuels Wizard only applies to gasoline fuels. If any diesel fuel properties (such as the diesel
sulfur content) need to be changed, MOVES users should modify the property in the fuel formulation
table for the modeled county using the CDM.
Additionally, the Alternative Vehicle and Fuels Technology (AVFT) table defines the fractional mix of
vehicles capable of using different fuels for each model year. In most cases, the default AVFT table
should be used. However, in some cases the fleet of vehicles that operate in the port may have a
unique mix of fuel types that is different from the national average used to create the default table. For
example, a cruise ship port might have a fleet of passenger shuttle buses that operates only on
compressed natural gas (CNG). In this case, the AVFT table should be adjusted to reflect that the local
fleet of shuttle buses (sourceTypelD 42) does not include any diesel or gasoline buses.1
' In this specific example, the CNG-fueled shuttle buses should be modeled as Transit Buses (sourceTypelD 42) in
MOVES, because that is the only source type that can be modeled with CNG in MOVES2014.
Input by:
• HPMS vehicle types; or
• MOVES source types
• Annual; or
• Daily
VMT value:
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For more information on Fuels in MOVES, including the primary fuels tables, see Section 4.9 of the
MOVES Technical Guidance.
7.5.2.7 Inspection and Maintenance (l/M)
Some counties have local inspection and maintenance (l/M) programs to reduce emissions from the
passenger car and light duty truck fleet. If the local county containing the port has an l/M program,
coordinate with the state or local air agency administering the l/M program to verify that the default
inputs in MOVES are consistent with the local program. Refer to Section 4.10 of the MOVES Technical
Guidance for more information.
7.5.2.8 Retrofit and Replacement Data
This tab allows users to enter retrofit replacement program data that apply adjustments to vehicle
emission rates.J There is no default retrofit data in MOVES and users do not have to input retrofit data
into MOVES unless they have a retrofit program that they wish to model. Users should consult the
Diesel Retrofit and Replacement Guidance40 for more information.
7.5.2.9 Road Type Distribution
As noted in Section 7.4.2, most or all travel activity in a port-related area would most likely correspond
to the Urban Unrestricted Road Type or Off-network Road Type in MOVES. However, if any other road
type activity, such as urban restricted activity (i.e., driving on highways with entrance and exit ramps for
access) occurs within the port area, the user will need to distribute travel activity, by source type, across
the road types included in the analysis. See section 4.7 of the MOVES Technical Guidance for more
information on this input.
7.5.2.10 Average Speed Distribution
MOVES needs an average speed distribution for each source type, road type, and hour of day included in
the analysis. The MOVES user would distribute vehicle hours traveled (VHT, rather than vehicle miles
traveled) into 16 speed bins; these fractions should sum to 1 across source type, road type, and hour of
day.k For sourceTypelDs 61 and 62, which represent short- and long-haul combination trucks, there may
be a substantial amount of activity in the lower speed bins because of their queuing activity.
7.5.2.11 Starts
At County Scale, start information is an optional input. By default, MOVES uses vehicle population to
estimate start emissions. However, for a port-related onroad vehicle emission inventory, using the
starts input is a more precise way to estimate start emissions. The starts input contains multiple tables,
which allow the user to:
• enter the total number of starts for all source types in the inventory area for a typical weekday
and weekend day,
• distribute the total number of starts by source type and by hour of the day, and/or
J For onroad vehicles, retiring older vehicles and engines and replacing them with new equipment plays a major
role in reducing emissions. In general, vehicle replacement, rather than retrofit, is a more effective option for
port-related heavy-duty vehicles.
k More information about how this input is developed can be found in Section 4.6 of the MOVES Technical
Guidance.
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• enter monthly adjustment factors to account for cases where number of starts varies by month.
There is also the option to use the operating mode distribution table to change the default distribution
of vehicle soak times (the length of time between key-off and key-on) represented by opModelD 101
through 108, as discussed in Section 7.4.2.2. Ports are likely to have soak time distributions that are
different from national defaults. For example, a cargo port might have a high percentage of short soak
times, while a port with a cruise terminal that includes a long-term parking structure might have a
higher percentage of long soak times.
7.5.2.12 Running MOVES
Once the input database is complete, MOVES can be run. The results will be the port-related emissions
inventory at the level of detail chosen in the Output Emissions Detail Panel of the RunSpec, which may
need additional aggregation. For example, if source type was chosen in the output emissions detail
panel, emissions from each of the source types would need to be summed to get total port emissions
inventory for the onroad sector.
7.6 Project Scale Approach for Developing an Onroad Vehicle Emissions Inventory
Using MOVES at the Project Scale can provide a greater level of detail for developing a base year onroad
vehicle emission inventory. Additionally, as discussed in Section 7.2, using MOVES at the Project Scale
can provide emissions at enough geographical resolution to conduct air quality modeling if setup
correctly following the methods described in the PM Hot-spot Guidance. As noted in the introduction of
this section, this document does not provide step-by-step instructions on how to run MOVES, but
discusses an overview of the process of using MOVES at the Project Scale.
There are several ways that MOVES at the Project Scale could be used to create an inventory of port-
related onroad emissions, and this document focuses on two of them:
1. Generic Link Approach: Using MOVES at the Project Scale to model a series of generic links that
represent different types of activity at the port. This section primarily focuses on the Generic
Link Approach.
2. Refined Approach: Using MOVES at the Project Scale to model a series of specific links that
represent specific locations at the port. This is a more detailed approach applicable for areas
conducting refined air quality modeling requiring geographically allocated emissions. Refer to
Appendix I for more information about this approach.
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Table 7.5. Overview of Developing Onroad Vehicle Emission Inventories Using MOVES at the Project
Scale
Data Needs
Advantages
Considerations
• Link level characterization of
port activity
• VMT
• Fleet age distributions
• Fuel characteristics
• Can provide a detailed link-
based spatial distribution
of emissions
• Allows for a detailed
analysis of different kinds
of activity (e.g., queuing)
• Post-processing is needed to
produce an inventory for the time
period needed (e.g., daily or
annual emissions)
• No MOVES default database
information available
• Does not includes output for all
evaporative emission processes
7.6.1 Major Considerations for the Project Scale Approach
The following items should be carefully considered when developing a modeling plan for a project scale
approach, which are discussed in further detail below:
1. Number of links
2. Number of runs
3. Pollutants and processes to include
7.6.1.1 Number of Links
A link represents a segment of road or driveway or other location where a certain type of vehicle activity
occurs. A link should be a segment with similar traffic/activity conditions and characteristics. Where
vehicle volumes or vehicle activity changes, a new link should be defined.
There are two primary types of links: running and off-network.
• Running links are used to describe driving activity (e.g. free-flow cruising, deceleration, idle, and
acceleration activity). Near-port onroad transportation corridors, on terminal drayage routes,
driveways, loading and unloading zones, and queuing areas would be characterized by running
links.
• An off-network link is used to describe areas of start and hotelling activity (e.g. parking areas
truck or transit terminals). Generally, long term hotelling activity does not occur on ports and
therefore is not included in this document; however, if hotelling occurs within the overall
project geographical scope of the analysis, refer to Section 4 of the PM Hot-spot Guidance for
more information on how to characterize this activity in MOVES.
As indicated in Section 7.4, near-port corridor and on-port vehicle activity may include different running,
queuing, and parking activity. There is no limit on the number of running links in a run, but only one off-
network link can be defined per run.
7.6.1.2 Number of Runs
At the Project Scale, each MOVES run covers one specific hour of a single day of a single year.
Therefore, determining the number of Project Scale runs depends on the inventory purpose, how
activity levels, meteorological conditions, and fuels vary over the course of the time period of the
inventory.
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The inventory purpose, whether it be an annual emissions inventory or an inventory for a specific
national ambient air quality standard (NAAQS), determines the number of runs needed. For example,
for the annual PM2.5 NAAQS, an annual SIP inventory is necessary, whereas ozone SIPs are developed for
a typical summer day, and the 24-hour PM2.5 and PM10 NAAQS need daily inventories. For more
information on the number of runs for a specific NAAQS, please consult the appropriate EPA guidance.
One advantage to the Project Scale Generic Link Approach, discussed in 7.6.2, is that one MOVES run
may be all that is needed to generate emission rates for the entire year for non-regulatory purposes.
However, more than one run may be necessary to account for variation in fuel type and possibly
temperature across seasons. If multiple runs are necessary, the resulting rates would need to be
multiplied by the appropriate fraction of the yearly activity, and the products aggregated as discussed
further in Section 7.6.5.
7.6.1.3 Pollutants and Processes to Include
MOVES cannot estimate emissions from fuel vapor venting at the Project Scale. Fuel vapor venting is
the emission process in MOVES that accounts for evaporative emissions from parked gasoline vehicles.
(See Section 7.2.1 for more information). If the ports inventory needs to include these emissions, the
user can either supplement this Project Scale method with an additional run using the County Scale that
only includes the "evap fuel vapor venting" process, or create the whole inventory using the County
Scale Approach described in Section 7.5.
7.6.2 Project Scale Generic Link Approach
A simplified Project Scale approach could be used if the inventory is not done for regulatory purposes
and is not needed for air dispersion modeling. In this approach, a set of generic links can be created for
each different type of activity: one link for each type of activity and for each source type engaged in that
activity. Given this set up, these generic links result in emission rates (even though the Inventory
calculation type is used) that can then be multiplied by the appropriate activity for each of those source
types (e.g., VMT, hours idling, or starts).
The number of generic links used should sufficiently capture the different types of activity occuring in
the scope of the inventory. The links defined in this approach would include a set of running links and
one off-network link.
• Each running link would include just one vehicle, and all running links would be defined as a
length of one mile.
• The off-network link should include one of each source type with start activity for the
geographical area.
With this approach, multiple areas within the port where similar activity occurs can be represented by
the same link. For example, if within the port there are different areas where trucks and other vehicles
are queuing, these different areas of queuing can be represented with one link for each source type.
Table 7.6 provides a simple example of this approach representing links for one source type.
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Table 7.6. Generic Link Approach Sample Link Characterization
Activity Type
Generic Link Description
Output Emission Rate
MOVES Link Example
Driving to and
from port
Running link with
representative average speed
of near-port onroad
transportation corridors
mass per mile (e.g. g/mi)
Running link with 30
mph average speed
Queuing (including
idling and
creeping) at gates
or terminals
Running link with low average
speed
mass per mile converted
to mass per hour (e.g.
g/mi to g/hr)
Running link with 1.8
mph average speed
Driving activities
on-port
Running link with
representative average speeds
of driving on-port to capture all
drayage routes and driveways
mass per mile (e.g. g/mi)
Running link with 10
mph average speed
Vehicle Parking
and Starts
Off-network link to represent
all parking areas to capture
number of vehicles parked and
starting*
mass per start (e.g.
g/start)
Off-network Link
* MOVES at the Project Scale does not capture evaporative process emissions associated with soak activity from
parked vehicles. If VOCs or air toxics need to be included in the inventory, these can be estimated with an
additional County Scale run for just these emissions.
This example includes four links for this source type; similar links would be defined for other source
types. The resulting MOVES output, which represent emission rates for a given pollutant, can then be
multiplied by the number of vehicles of that source type and activity amount, and then aggregated to
create a total onroad vehicle emissions inventory.
7.6.3 Creating a Run Specification for the Generic Link Approach
To produce emission factors for use in the calculation of an onroad vehicle inventory, the user would
run MOVES for the representative time periods of interest for the analysis. As discussed in Section
7.6.1.2, the MOVES user should consider whether more than one run is necessary to account for
variation in fuel type and temperature. If more than one run is needed, separate RunSpecs should be
developed for each run.
When setting up a RunSpec for a Project Scale Generic Link run, the following selections should be
made:
1. Scale Panel: Select "Onroad" model and "Project" scale. Calculation type should be specified as
"Inventory." Because running links will be defined with one vehicle with a length of one mile,
selecting "Inventory" results in a set of emission rates for these links, e.g., grams/vehicle-mile.
2. Time Spans Panel: Select the calendar year, a month, a day type (weekday/weekend), and an
hour of analysis. The selection of month will affect the fuel MOVES uses, but otherwise, the
selections for month, day type, and hour do not matter for this approach. Time aggregation
should be set to "hour," which indicates no pre-aggregation.
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3. Geographic Bounds Panel: Select the county containing the port in the Geographic Bounds
Panel. Note, if the port spans multiple counties, users should select the county containing most
of the port.
4. Onroad Vehicle Equipment Panel: Add the fuel type/source type combinations represented at
the port (as described in Section 7.4.1.1).
5. Road Type Panel: Select the road types that are to be included in the project scope. Always
select "Off-Network" to include calculation of emissions from engine starts and evaporative
emissions from parked gasoline vehicles.
6. Pollutants and Processes Panel: Select all processes of the pollutants of concern. Note, VOC
and air toxics emissions from the fuel vapor venting process cannot be estimated using MOVES
at the Project Scale and would necessitate a supplemental County Scale run.
7. Manage Input Data Sets Panel: This panel is not needed and should be skipped.
8. Strategies Panel: The Strategies Panel provides access to the Rate of Progress option. The Rate
of Progress Panel includes a checkbox which, when checked, disables all motor vehicle
requirements of the 1990 Clean Air Act Amendments. This panel is not needed for inventory
development and should be skipped.
9. General Output Panel: Choose units for emissions and distance. EPA recommends choosing
"grams" and "miles" for these units. EPA also recommends selecting "Distance Travelled" and
"Population" under the "Activity" heading. This can be used as a check for the output, since
distance travelled should be 1 mile, and population should be 1 vehicle for each link, based on
input database choices described below.
10. Output Emissions Detail Panel: Select check the box for "Source Use Type" to obtain start
emission rates by source type.
11. Advanced Performance Features Panel: This panel is not needed and should be skipped.
Before executing this run, the user will need to create an input database to describe the activity by link
for the inventory, as described in the next section.
7.6.4 Using the Project Data Manager for the Generic Link Approach
The Project Data Manager (PDM) in MOVES is used to import tables containing the information needed
to populate a Project Scale input database. This section assumes familiarity with creating a MOVES
input database by exporting the spreadsheet templates (or in the case of fuel, default data) for each of
the inputs, and importing completed templates into the input database. A simple, hypothetical example
is provided in Appendix I to illustrate some of the PDM tab inputs for the Project Scale Generic Link
Approach.
The following subsections provide information on how to populate the PDM tabs for the Generic Links
Approach.
7.6.4.1 Meteorology Data
Enter the average monthly temperature and humidity for the month selected in the RunSpec.
7.6.4.2 Age Distribution
As discussed in Section 7.4.1.3, the age distribution of the vehicles in the analysis is an important input
in how MOVES calculates emission rates. In the Generic Link Approach, each running link consists of one
vehicle and the off-network link has only one vehicle of each type. The age distribution for each source
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type should be representative of the fleet of those vehicles at the port. This fleet age distribution is
then assigned as a composite age for the single vehicle included in the link. If available, use the specific
fleet age distribution from the port.
7.6.4.3 Fuel
Onroad vehicle emissions also depend on what fuels and fuel mixes are used. MOVES includes default
fuel information by county, month, and year. MOVES users should review the default fuel supply and
fuel formulation information provided in MOVES and make changes only where precise local volumetric
fuel property information is available or where local fuel requirements have changed.
One exception is in the case of Reid Vapor Pressure (RVP); the MOVES user should change this value to
reflect any specific local or state regulatory requirements and differences between ethanol- and non-
ethanol blended gasoline not reflected in the default database. Any changes to RVP (or to any other
gasoline fuel formulation parameters) should be made using the "Fuels Wizard" tool in the Fuel Tab of
the CDM. This process is described in more detail in Section 4.9.1 of the MOVES Technical Guidance.
Note that the Fuels Wizard only applies to gasoline fuels. If any diesel fuel properties (such as the diesel
sulfur content) need to be changed, MOVES users should modify the property in the fuel formulation
table for the modeled county using the CDM.
Additionally, the Alternative Vehicle and Fuels Technology (AVFT) table defines the fractional mix of
vehicles capable of using different fuels for each model year. In most cases, the default AVFT table
should be used. However, in some cases the fleet of vehicles that operate in the port may have a
unique mix of fuel types that is different from the national average used to create the default table. For
example, a cruise ship port might have a fleet of passenger shuttle buses that operates only on
compressed natural gas (CNG). In this case, the AVFT table should be adjusted to reflect that the local
fleet of shuttle buses (sourceTypelD 42) does not include any diesel or gasoline buses.1
For more information on Fuels in MOVES, including the primary fuels tables, see Section 4.9 of the
MOVES Technical Guidance.
7.6.4.4 Inspection and Maintenance (l/M)
Some counties have local inspection and maintenance (l/M) programs to reduce emissions from the
passenger car and light duty truck fleet. If the local county containing the port has an l/M program,
coordinate with the state or local air agency program administrator to verify that the default inputs in
MOVES are consistent with the local program. For ports that do not serve cruise ships (i.e., those ports
that do not have large numbers of passenger vehicles), this panel may potentially be skipped. Ports that
serve cruise ships will have more light-duty vehicle activity; in such a case, enter the details of the l/M
program in the county selected in the RunSpec panel. Refer to Section 4.10 of the MOVES Technical
Guidance for more information.
1 In this specific example, the CNG-fueled shuttle buses should be modeled as Transit Buses (sourceTypelD 42) in
MOVES, because that is the only source type that can be modeled with CNG in MOVES2014.
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7.6.4.5 Retrofit Data
This tab allows users to enter retrofit program data that apply adjustments to vehicle emission rates."1
There is no default retrofit data in MOVES and users do not need to input retrofit data into MOVES
unless they have a retrofit program that they wish to model. Users should consult the Diesel Retrofit
and Replacement Guidance for more information.
7.6.4.6 Links
The Link input table is where the MOVES user defines the links. For the Generic Link Approach, each
running link includes just one vehicle, and all running links are defined as a length of one mile. Table 7.7
describes the columns in the Link input table.
Table 7.7. Project Scale Link Input Table Description
Column Name
Entry
linkID
Each link should have a unique linkID made up of letters, numbers, and underscores.
For running links, use a unique link for each source type present at each average
speed of interest. Only one off-network link can be defined.
countylD
The first row for this column will be pre-populated based on selections in the
RunSpec. Copy the first-row entry into the other rows of the column.
zonelD
The first row for this column will be pre-populated based on selections in the
RunSpec. Copy the first-row entry into the other rows of the column.
roadTypelD
Running links: specify the appropriate road type (e.g., roadTypelD 5).
Off-network link: specify road type 1.
linkLength
Running links: link length of 1 (in miles).
Off-network link: link length of 0.
linkVolume
Running links: link volume of 1.
Off-network link: link volume equal to the number of source types with start activity
(e.g. For 4 source types parking and starting, the link volume for the off-network link
would be 4).
linkAvgSpeed
Running links: use average speeds to reflect the vehicle activity. Examples in Table 7.6
includes running links for three different speeds, representing driving to and from the
port (30 mph), driving on the port (10 mph), and queuing activity (1.8 mph).
Off-network link: use an average speed of 0 mph.
linkDescription
Text can be entered in this field to keep track of which link corresponds to which
source type and activity.
linkAvgGrade
This can be left blank or 0 can be entered for each link, unless there are roads in the
geographical domain with significant grade (most links in or near ports likely have 0
grade).
m For onroad vehicles, retiring older vehicles and engines and replacing them with new equipment plays a major
role in reducing emissions. In general, vehicle replacement, rather than retrofit, is a more effective option for
port-related heavy-duty vehicles.
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Link Source Type: This input applies to running links only. Table 7.8 describes the columns in the
LinksSourceTypeHour input table.
Table 7.8. Project Scale LinksSourceTypeHour Input Table Description
Column Name
Entry
linkID
Include all roadway linklDs defined in the Links input table.
sourceTypelD
Include one source type per link.
sourceTypeHourFraction
This fraction needs to sum to one for each link. As there is only one source
type per link, enter 1 in this column.
Off-Network: An off-network link should include all source types with start or soak activity. Table 7.9
describes the columns in the OffNetworkLink input table.
Table 7.9. Project Scale OffNetworkLink Input Table Description
Column Name
Entry
zonelD
This will be pre-populated based on the RunSpec; copy the zonelD from the
first cell for the rows in the column.
sourceTypelD
Include all source types present in the off-network link, one source type in each
row.
vehiclePopulation
Enter 1 for each source type.
startFraction
Enter 1 for each source type. (100 percent of the vehicles are starting during
the hour.)
extended IdleFraction
This column represents hotelling activity of long-haul combination trucks. This
column can be left blank because it is assumed that that long-term truck
hotelling activity does not occur at ports.
parkedVehicleFraction
Leave blank
Operating Mode Distribution: This input is needed for an off-network link to describe how long vehicles
have been soaking before they are started. Table 7.10 describes the columns in the OpModeDistribution
input table.
Table 7.10. Project Scale OpModeDistribution Input Table Description
Column Name
Entry
sourceTypelD
Add a row for each of the source types present.
hourDaylD
This is a combination of the hourlD (1-24) and daylD (weekday, 5, or weekend day,
2). For example, if the hour chosen in the RunSpec was 10:00-10:59 (hourlD 11),
and the day type chosen was weekday (daylD 5), then 115 would be entered in this
column.
linkID
Include the linkID used for the off-network link in the Links input table.
pollutantProcessID
This is a combination of the pollutantID and the processlD. While any number of
pollutants may be of interest, for the purposes of this method, the only relevant
processlD is 02, "Start Exhaust."
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Column Name
Entry
opModelD
Select appropriate opModelDs from Table 7.3.
A simplifying assumption is that all light-duty vehicle starts at a port have the
opModelD 108, because most light-duty starts will be either from vehicles being
driven on or off a vehicle carrier, or from vehicles being driven after their owners
have returned from a cruise.
Similarly, a simplifying assumption is that all heavy-duty vehicle starts have the
opModelD 102, because these vehicles will not stop for long periods of time on
port. (Note, opModelDs in the 200s are used to describe hotelling.)
opModeFraction
The fraction of the vehicle population that is in each operating mode; these
fractions needs to sum to 1 for each source type and pollutant process. Assuming
one opModelD is chosen for each source type (i.e., 108 for light-duty source types,
and 102 for all heavy-duty source types), enter 1 for each cell in this column.
7.6.5 Post-Processing Project Scale Output for Inventory Development
After executing a generic link run, MOVES will produce a link-by-link emission mass for each pollutant,
for the hour specified within the RunSpec. The result of such a run would be a set of emission rates, for
each source type as follows:
• Running activity: emissions per mile
• Creeping/idling activity (e.g., trucks waiting at the gate): MOVES results of emissions per mile
can be converted to emissions per hour
• Off-network activity: emissions per start
As discussed in Section 7.6.1, each MOVES Project Scale run covers a single hour, and that hour may
represent a longer span of time for the purposes of inventory development. The resultant output
emission factors can then be multiplied by the corresponding amount and type of annual activity (e.g.,
VMT, hours of wait time, and number of starts) and the products aggregated to produce an annual
emissions inventory for each pollutant.
For the Project Scale Generic Link Approach, the output is an emission rate by source type per mile or
per start. To produce a total annual inventory for a given pollutant, each of these rates would then be
multiplied by the corresponding activity occuring in the time span in which the MOVES run represents
(e.g. if the hourly run represents annual activity at the port, the emission rates by source type should be
multiplied by annual activity values by source type). This calculation should be performed for each
source type and summed to produce a total emission value. A hypothetical example is provided in
Appendix I to illustrate the post-processing of emission rates produced from a Project Scale Generic Link
run.
7.7 Projecting Future Emission Inventories
Future onroad emissions should be projected from a base year inventory, developed as described in the
sections above. In general, the projection process follows these steps:
1. Activity growth rates are applied to the base year activity to estimate future activity (described
below)
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2. Age distributions are adjusted to account for fleet turnover to newer, cleaner engines
3. MOVES is run for the future analysis year to estimate emissions
4. Projected emissions are aggregated to the same level of detail as the base year inventory, as
determined by the purpose of the inventory
Onroad activity rates (VMT, starts, etc.) should be adjusted based on anticipated future port growth.
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations. Local port projections, if available,
are usually by commodity type and/or business sector; growth can be grouped by the vehicle types that
are associated with the various business sectors (i.e., projected cargo throughput for truck activity or
projected increases in cruise activity for passenger travel). Annual activity for port-related onroad
vehicles should be adjusted in proportion to the anticipated growth rate for a given business activity
between the base year and future year inventories. For example, if the projection year is 2030 and the
port's total projected growth in cargo throughput between the base year and 2030 is 15 percent; then
drayage activity would be projected to increase by 15 percent. If the Freight Analysis Framework (FAF)11
is used to forecast growth, the commodity flows assigned to the truck mode should be used when
calculating growth. The growth rates should then be applied to the base year activity estimates.
Based on the future year specified in the RunSpec, MOVES accounts for changes in emissions rates from
expected improvements in powertrain and emissions technology, however, some MOVES inputs should
be projected. If available, a port-specific age distribution can be applied to the projection year. EPA has
developed the Age Distribution Projection Tool,47 which projects a base year age distribution by source
type to a future distribution using a similar algorithm to what was used to generate the national
projected age distributions. Additionally, any planned action or emission reduction strategies that have
been committed to that would affect future emissions should be included according to the actual
expected implementation of such commitments. For example, a port may implement a future vehicle
electrification program for certain port-related vehicles, therefore the AVFT table should reflect the
program components. Note that if the future year inventory is for a regulatory purpose, planned future
actions should be included only if written commitments have been made by the agency or operator with
the power to implement them.
The emissions inventory for the projection year should be determined using the same method as the
base year, except the MOVES user should select the projection year on the Time Spans Panel instead of
the base year and ensure that all inputs entered through the County Data Manager or Project Data
Manager correctly reflect the chosen analysis year. Finally, the resulting emissions inventory should be
aggregated to the same level of detail as the base year inventory.
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8 Rail
8.1 Source Description
The rail sector covers emissions from locomotives. Port-related rail operations are typically
characterized into two categories: line-haul and switching activity. Line-haul operations in a port setting
refer to the movement of cargo at the beginning or end of a line-haul trip, where cargo is either picked
up or delivered for transport to off-port locations via land or water. Switching activities involve the
assembling and disassembling of trains, the sorting of rail cars, and the delivery of empty rail cars to
terminals.
Compared to line-haul operations, switching operations generally include more idling activity and
involve older locomotives; it is not unusual for older line-haul locomotives to be converted to switcher
locomotives as newer, higher-powered line-haul models are produced. At some ports, cargo handling
equipment (CHE) perform the assembling and disassembling of trains, and switcher locomotives are not
used. In these cases, the rail sector includes only line-haul activity; emissions from CHE are calculated as
described in Section 6. Note, this section can be used to quantify emissions related to locomotives at
ports, or also at other locations of locomotive activity, such as intermodal freight terminals where
freight is transferred between rail and trucks.
The Surface Transportation Board (STB) divides railroad companies into three classes based on annual
operating revenues.3 Class I carriers are the largest operators, Class II carriers operate regional
railroads, and Class III carriers operate shortline railroads. Class I railroads are required to report
locomotive counts and fuel use for switching and line-haul operations to the STB; Class II and III carriers
are not subject to these requirements. Due in part to this fact, default assumptions regarding
locomotive duty cycles and other characteristics by class are generally not available for use in the
development of a rail emissions inventory. Thus, with a few exceptions, the methodologies presented in
this section are not distinguished by carrier class.
For a detailed inventory, locomotive emissions should be calculated for each locomotive type (line-haul
and switcher) and each rail terminal/railyard. The scope of the inventory should be determined in
advance of any calculations and in accordance with the overall inventory purposes. For example, the
boundary of the rail inventory may potentially include only areas under the jurisdiction of the local port
authority and exclude rail corridors servicing the port. Alternatively, if the inventory considers port-
related emissions over a broader area, the inventory may include emissions from rail corridors beyond
the port's boundary. Additionally, the inventory should be calculated at the temporal level of detail
necessitated by the purpose of the inventory (e.g., at the year level for an annual inventory). See
Section 2 of this document for more discussion about inventory purpose, geographical domains, and
temporal detail.
a The Surface Transportation Board is a U.S. federal government entity created in 1995, charged with the
fundamental missions of resolving railroad rate and service disputes and reviewing proposed railroad mergers.
For more information, see https://www.stb.gov/stb/faqs.html.
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8.2 Emissions Estimation Overview
In general, base year locomotive emissions can be calculated as shown in Equation 8.1:
E = AxEF Equation 8.1
Where E = emissions (g)
A = activity (hp-h)
EF = emission factor (g/hp-h)
As the data available for locomotives vary from port to port and vary by type of locomotive (i.e.,
switcher vs. line-haul locomotive), multiple strategies for developing inputs for this calculation are
described in the following sections. Locomotive characteristics, activity, and emission factors are
described in Sections 8.3, 8.4, and 8.5, respectively. These inputs can be used to calculate a detailed
base year rail inventory, as described in Section 8.6. Alternative methodologies are presented in Section
8.7, and Section 8.8 explains how to project port rail emission inventories for future years.
When developing a rail inventory, rail technologies currently in place at the port (e.g., automatic engine
stop/start systems, auxiliary power units, and air compressor systems) should be included in the base
year inventory.
8.3 Locomotive Characteristics
Locomotives serving ports generally include both line-haul and switcher locomotives. Data needed for
estimating a base year emissions inventory will depend on the methodology used to estimate fleet
equipment activity (see Section 8.4) and may include the following characteristics:
• Number of locomotives per train: For line-haul operations, the average number of locomotives
used in each train.
• Rated engine size: Measured in hp.
• In-use locomotive load factor: The percent of maximum available power used by the locomotive
engine over the course of its duty cycle.
• Engine model year/tier (age) distribution: The emission tier level information should reflect the
current tier level of the locomotive engine (i.e., reflect the latest repower/replacement of the
engine, if applicable), rather than the emission tier level of the engine when the locomotive was
first manufactured.
• Use of emission reduction technologies: Technologies such as automatic engine stop/start
systems, auxiliary power units, and air compressor systems should be accounted for if present.
This information, if available, could be obtained in consultation with the local port authority and/or the
railroad company servicing the port. This will be most feasible for switcher locomotives, which are
typically a captive fleet. Because line-haul locomotives transport commodities over long-distances, it is
often the case that no identifiable fleet of line-haul locomotives that calls exclusively at a specific port.
As a result, characteristics of nationwide fleets of line-haul locomotives, published in the Surface
Transportation Board's annual R-l reports, can be considered in lieu of port-specific data. These reports
are available for each Class I railroad. However, if information on line-haul activity within the
geographical domain of the inventory is available in consultation with the local port authority and/or the
railroad company servicing a port, it should be used, as it will result in higher quality rail activity data.
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The Association of American Railroads maintains a directory of contact information for representatives
of rail companies operating within each state.48
8.4 Locomotive Activity
Activity rates for locomotives, measured in horsepower-hours, can be estimated based on:
• Fuel consumption (preferred methodology for switcher locomotives);
• Number of trains (preferred methodology for line-haul locomotives); or
• Gross ton-miles.
These approaches are discussed in detail in Sections 8.4.1, 8.4.2, and 8.4.3, respectively. The method
that relies on fuel consumption is preferred for switchers because it relies on a robust source of data.
Similarly, the method that relies on the number of trains at a port is preferred for line-haul because it
incorporates more specificity about the locomotives at the port than the method that relies on gross
ton-miles. Although the first two methods are preferred, all three approaches can be used to estimate
both switching and line-haul activity within the geographical domain, and the choice of method may
depend on data availability.
If the purpose of the inventory is for a refined analysis involving air quality modeling, see Appendix I of
EPA's PM Hot-spot Guidance41 for a detailed rail inventory methodology.
8.4.1 Activity Based on Fuel Consumption
The fuel consumption approach for calculating locomotive activity combines data on fuel consumption
and a conversion factor to estimate work done by the locomotive.
As fuel consumption information for locomotives servicing a specific port is likely to be more readily
available (in consultation with the local port authority and/or the railroad company servicing the port)
for a captive fleet, this method is likely more feasible for characterizing switching operations than for
long-haul operations. Fuel consumption information may not be available for line-haul locomotives,
because it is often the case that no identifiable fleet of line-haul locomotives that calls exclusively on any
specific port.
EPA has estimated conversion factors for different locomotive types, as shown in Table 8.1.33 These
conversion factors relate fuel consumption to the usable power of the locomotive engine. Older
locomotives and locomotives used in lower powered applications, such as switching, tend to be less fuel
efficient. If fleet-specific conversion factors are available, those should be used instead of the factors in
Table 8.1.
Table 8.1. Locomotive Fuel Consumption to Horsepower-Hour Conversion Factors
Locomotive Type
Conversion Factor (hp-h/gal)
Line-haul (Class 1)
20.8
Line-haul (Class ll/lll)
18.2
Switcher
15.2
Activity for a locomotive fleet based on fuel consumption and a conversion factor can be determined
using Equation 8.2:
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A = FC x CF Equation 8.2
Where A = locomotive activity (hp-h)
FC =fuel consumption (gal)
CF = conversion factor (hp-h/gal)
8.4.2 Activity Based on Number of Trains
When fuel consumption information is not readily available, the number of trains combined with fleet
characteristics can be used to estimate locomotive activity. This strategy is likely more applicable to
line-haul locomotives operating within the geographical domain of the inventory. To implement this
approach, the following data are needed:
• Number of trains visiting the port, over the time period chosen for the inventory
• Average number of locomotives per train
• Average time spent on port per train trip
• Average locomotive rated power
• Average in-use locomotive load factor
This data, if available, could be obtained in consultation with the local port authority and/or the railroad
company servicing the port. The equation that can be applied for estimating activity based on these
fleet characteristics is shown in Equation 8.3:
A = Nt x Ni x H x P x LF Equation 8.3
Where A = fleet activity (hp-h)
Nt = number of trains visiting the port
Ni = average number of locomotives per train
H = average time spent on port per train trip (h)
P = average rated power of locomotives (hp)
LF = average in-use load factor (unitless)
The load factor here is defined as the percent of maximum available power used by the locomotive
engine over the course of its duty cycle. Most locomotives employ a diesel engine coupled to an
electrical drive system, which operates in a series of discrete steady-state power settings called
"notches." Notch positions typically range from one to eight (from least to most powerful), idle, and
dynamic braking, which allows for speed reduction using the locomotive's drive system. As line-haul
and switcher locomotives have different duty cycles, they are expected to have different load factors. A
port-specific load factor could be calculated for each type of locomotive if the percent of maximum
power used by the engine in each notch setting is known, as well as the time spent in each notch setting
(i.e., the duty cycle). Appendix I of EPA's PM Hot-spot Guidance provides detailed instructions on
applying this methodology.
If detailed information to inform the calculation of fleet-specific load factors is not available, a national
average load factor of 28% for line-haul and 10% for switcher locomotives can be assumed.13
In Equation 8.3, the product of trains visiting the port, locomotives per train, and time spent on port per
train trip represents the aggregate activity of the locomotive fleet. To more precisely determine
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locomotive activity using this methodology, activity data loggers could be installed on the locomotives or
other telematics data could be used.
8.4.3 Activity Based on Gross Ton-miles
A third approach for determining locomotive activity involves estimating locomotive fuel consumption
from gross ton-miles, which is the product of total train weight and distance moved, and the fleet
average fuel consumption factor, as described in Equation 8.4 below. This estimated fuel consumption
value can, in turn, be used with Equation 8.2 in Section 8.4.1 to estimate annual activity. This approach
is most applicable to line-haul locomotives for which port-specific fleet characteristics are unknown.
Equation 8.4 can be applied to estimate fuel consumption based on gross ton-miles:
FC = GTM x FCF Equation 8.4
Where FC = fuel consumption (gal)
GTM = gross ton-miles (ton-mi)
FCF = fleet average fuel consumption factor (gal/ton-mi)
The fuel consumption factor (FCF) is a measure of fuel efficiency that relates fuel consumption to work
performed. For Class I fleets, a national average value can be derived from information in the railroad's
latest R-l report, published annually by the STB.49 Specifically, the railroad's fleet average FCF can be
calculated by dividing national fuel consumption (reported in R-l, Schedule 750, Line 4) by national
gross ton-miles (reported in R-l, Schedule 755, Line 104; note that this number is reported in thousands,
and therefore needs to be multiplied by 1,000 to get it in units of ton-miles).50
8.5 Emission Factors
Emission factors for locomotives vary by emissions tier and fuel type consistent with EPA's regulations,
as described below. For methods to estimate energy consumption for this source sector, see Appendix
A.
8.5.1 Diesel
The diesel emission factors given below are from EPA's Emission Factors for Locomotives,33 unless
otherwise noted. Speciation profiles of additional hazardous air pollutants for locomotive engines are
presented in Appendix J.
8.5.1.1 Nitrogen Oxides (NOx), Particulate Matter (PM), Black Carbon (BC), Volatile Organic Compounds
(VOC), and Carbon Monoxide (CO)
Emission factors for NOx, PM, and CO are provided in Table 8.2 and Table 8.3 for Class I line-haul and
switcher locomotives, respectively. The plus ("+") in the tables below reflect the emission factors that
should be used if a locomotive engine has been rebuilt to meet the revised standards in 40 CFR Part
1033. For example, if a locomotive was initially Tier 0 but has been rebuilt to meet the Tier 1 standards,
use the emission factors in the "Tier 1+" row. Emission factors for hydrocarbons (HC) are also included
in the tables below, which are the basis for the VOC emission factors, as described later.
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Table 8.2. Line-Haul Emission Factors for NOx, PMU, HC, and CO (g/hp-h)
Tier Level
NOx
PM10
HC
CO
Uncontrolled
13.00
0.32
0.48
1.28
Tier 0
8.60
0.32
0.48
1.28
Tier 0+
7.20
0.20
0.30
1.28
Tier 1
6.70
0.32
0.47
1.28
Tier 1+
6.70
0.20
0.29
1.28
Tier 2
4.95
0.18
0.26
1.28
Tier 2+
4.95
0.08
0.13
1.28
Tier 3
4.95
0.08
0.13
1.28
Tier 4
1.00
0.015
0.04
1.28
+ Indicates that these are the revised standards in 40 CFR Part 1033.
Table 8.3. Switcher Emission Factors for NOx, PMi0, HC, and CO (g/hp-h)
Tier Level
NOx
PM10
HC
CO
Uncontrolled
17.40
0.44
1.01
1.83
Tier 0
12.60
0.44
1.01
1.83
Tier 0+
10.60
0.23
0.57
1.83
Tier 1
9.90
0.43
1.01
1.83
Tier 1+
9.90
0.23
0.57
1.83
Tier 2
7.30
0.19
0.51
1.83
Tier 2+
7.30
0.11
0.26
1.83
Tier 3
4.50
0.08
0.26
1.83
Tier 4
1.00
0.015
0.08
1.83
+ Indicates that these are the revised standards in 40 CFR Part 1033.
PM2.5 emission factors are calculated as 97% of the PM10 emission factors. As these are emission factors
for diesel fuel, the DPM10 and DPM2.5 emission factors are equal to the PM10 and PM2.5 emission factors,
respectively. BC emission factors are 73% of PM2.5 emission factors.27
VOC emission factors are 1.053 times the HC emission factors.13
For Class ll/lll line-haul locomotives, the uncontrolled line-haul emission factors should be used.
8.5.1.2 Brake Specific Fuel Consumption (BSFC)
BSFC rates vary by locomotive type. Note that carbon dioxide, methane, nitrous oxide, and sulfur
dioxide are calculated based on these values. BSFC rates by locomotive type are presented in Table 8.4.
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Table 8.4. Locomotive BSFC Rates (g/hp-h)
Locomotive Type
BSFC Rate (g/hp-h)
Line-haul (Class 1)
154
Line-haul (Class ll/lll)
176
Switcher
211
8.5.1.3 Carbon Dioxide (CO2)
C02 is directly proportional to fuel consumption. Therefore, the C02 emission factor is determined
according to Equation 8.5:
EFCo2 = BSFC x CCF Equation 8.5
Where EFCq2 = C02 emission factor (g/hp-h)
BSFC = brake specific fuel consumption (g/hp-h) as determined according to Section 8.5.1.2
CCF = carbon content factor (g C02/g fuel)
= 3.19 for diesel33
8.5.1.4 Methane (CH4)
CH4 emission factors can be estimated from BSFC using Equation 8.6:
EFCh4 = BSFC x MCF Equation 8.6
Where EFCH4 = CH4 emission factor (g/hp-h)
BSFC = brake specific fuel consumption (g/hp-h) as determined according to Section 8.5.1.2
MCF = methane conversion factor (g CH4/g fuel)
= 0.00025 for diesel locomotive engines32
8.5.1.5 Nitrous Oxide (N2O)
N20 emission factors can be estimated from BSFC using Equation 8.7:
EFN 0 = BSFC x NCF Equation 8.7
Where EFNz0 = N20 emission factor (g/hp-h)
BSFC = brake specific fuel consumption (g/hp-h) as determined according to Section 8.5.1.2
NCF = N20 conversion factor (g N20/g fuel)
= 0.00008 for diesel locomotive engines32
8.5.1.6 Sulfur Dioxide (SO2)
S02 should be calculated according to Equation 8.8:
EFSo2 = BSFC x Sact x FSC x MWR Equation 8.8
Where EFS02 = S02 emission factor (g/hp-h)
BSFC = brake specific fuel consumption (g/hp-h) as determined according to Section 8.5.1.2
Sact = actual fuel sulfur level (weight ratio)
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= 15xl0"6 for locomotives using ULSD
FSC = percentage of sulfur in fuel that is converted to S0213
= 0.97753
MWR = molecular weight ratio of S02 to sulfur
= 64/32 = 2
If the port emissions inventory is being calculated for a year prior to 2012, or if a fuel with a different
sulfur level was used by locomotives, then the actual fuel sulfur level should be used.30
8.5.2 LNG and LNG/Diesel Dual Fuel
For alternative fuel locomotive fleets, emission factors from the engine manufacturer should be used, if
available. However, if manufacturer data are unavailable, the following resources could be used
instead:
• LNG-fueled locomotives: See the emission factors presented in An Evaluation of Natural Gas-
fueled Locomotives,51 a joint publication from the BNSF Railway and Union Pacific Railroad
companies, the Association of American Railroads, and California Environmental Associates.
• LNG/diesel dual fueled locomotives: See the emission factors published in Argonne National
Laboratory's Future Restrictions on Diesel Fuel Combustion in California: Energy and Emissions
Implications of Four Scenarios report.52
8.6 Inventory Calculations
The base year locomotive emissions are calculated as the product of the locomotive activity estimate
and a pollutant-specific (and in some cases tier-specific) emission factor, where the activity has been
determined based on locomotive fuel consumption, number of trains, or gross ton-miles (as described in
Section 8.4), for both line-haul and switcher locomotives. If both the emission standard tier and the
activity estimate are known for each locomotive (more likely for captive switcher fleets), emissions
should be quantified on a per-locomotive basis.
If the emission standard tier is not known for individual locomotives, but the fleet average distribution is
known (which is more likely for line-haul fleets), a fleet average emission factor should be calculated,
weighted by the percentage of total fleet activity or population in each tier. If the fleet average tier
distribution is unknown, EPA's default fleet average emission factors for PM, HC, NOx, and CO can be
used instead (see Section 8.7.2 for more details). In these cases, the emissions should be quantified
separately for the fleet of line-haul and switcher locomotives.
These emissions can be then aggregated across all locomotives to the most useful level for the purposes
of the inventory. If the inventory has a spatial component to it, switcher emissions should be allocated
to the railyard where they occur, and line-haul emissions should be allocated to the rail lines where they
occur.
If the inventory has a temporal component to it and the activity data are at a finer level of detail, the
locomotive emissions should be aggregated to the level of detail for the purpose of the inventory.
However, if the activity data are at a coarser level of temporal detail than what is necessitated by the
purpose of the inventory, the emissions will need to be allocated to smaller units of time using surrogate
data. This surrogate data can come from other sectors in the port inventory, if those have enough
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detail. For example, locomotive activity could be temporally allocated based on AlS-derived OGV
container ship calls.
Performing quality control checks and including them in the supporting documentation for an inventory
are useful steps that support the results of the inventory, help stakeholders understand the results, and
facilitate comparisons between different inventories. The various checks listed below should provide a
consistent view of rail activity and emissions for an inventory. An inconsistency in one check that is not
reflected in others is indicative that additional scrutiny of input data sets and calculations may reveal
useful insights. Likewise, an anomaly that shows up in multiple checks may suggest an issue with input
data or methodology implementation. Note that unless otherwise specified, the analytical calculations
listed below should be aggregated by locomotive type and fuel type. The following distributions and
metrics (if available) are useful to examine as quality control checks and to facilitate comparisons
between different inventories:
• Engine power and operating hours: Examining both totals and distributions helps to estimate
the relative impact that a given locomotive type should have on the inventory.
• Model year range and engine tier distribution: Examining the minimum and maximum observed
values and average age, along with the distribution of engine tiers, provides an indication of
how old the locomotives are and can help in determining which locomotives contribute
substantially to the inventory.
• Total energy consumption (in horsepower-hours): Examining energy consumption provides an
estimate of the scale of locomotive activity contributing to the inventory and for enabling cross-
comparisons with other inventories.
• Comparing CO? emissions with fuel consumption: C02 emissions and fuel consumption should
have a linear relationship.
8.7 Alternative Methodologies
The methodologies described in this section can be used as an alternative if there is not enough local
information to fully implement the detailed methodologies described above. National data or default
activity assumptions do not necessarily reflect local conditions, and their use may have a significant
effect on the resulting emissions inventory.
8.7.1 Activity Calculations
The following sections contain alternative methodologies that make use of national data or default
assumptions that can be used to calculate locomotive activity.
8.7.1.1 Activity Based on Number of Trains
If precise values are not available from the rail company for use in Equation 8.3 in Section 8.4.2, the
alternative methodologies presented in this section can be used to fill any gaps as necessary.
Average locomotive engine power for Class I locomotives of a railroad can be determined based on
information from the STB's annual R-l reports. Specifically, average locomotive engine power can be
calculated by dividing the aggregate capacity (hp) of units by total number of units in service (columns k
and j, respectively, of R-l Schedule 710; line-hauls are reported on line 1, switchers on line 4).
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The total number of trains visiting the port can be estimated by determining the number of trains
needed to move the rail modal share of port throughput of containerized and non-containerized cargo
separately. While trains can be comprised of both containerized and non-containerized cargo, these
cargo types can be modeled separately for simplicity.
The number of container trains visiting the port can be estimated using Equation 8.9:
TEU
Tc = tfii w/p x (1 + RER) Equation 8.9
ItUmX UR
Where Tc = Number of container trains
TEUp = Port throughput of TEUs moved by rail
TEUm = Maximum train capacity (TEUs per train)
UR = Utilization ratio
RER = Return empty ratio
The number of TEUs at the port can be found in the U.S. Army Corps of Engineers Waterborne Container
Traffic statistics,53 published annually. If the fraction of TEUs that enter or exit a port via the rail mode is
unknown, it can be approximated using a region specific fraction of cargo throughput by mode from the
Freight Analysis Framework (FAF).11
If the other factors of Equation 8.9 are unknown, the following general assumptions can be used:
• For TEUm, the maximum train capacity: assume 500 TEUs per train.
• For UR, the utilization ratio (an estimation of how many platforms are filled or how many
double stack platforms are totally utilized): assume 80%.
• For RER, the return empty ratio (share of loaded railcars that return empty): assume 0.5.
Note that the above assumptions do not reflect local conditions, which likely impact rail activity. Also,
Equation 8.9 can be adapted for other forms of cargo (such as bulk) as necessary. If the number of rail
cars moved by the port for other forms of cargo is unknown, it can be estimated using the methodology
presented in Appendix K.
8.7.1.2 Activity Based on Gross Ton-miles
If precise values are not available from the rail company for use in Equation 8.4 in Section 8.4.3, the
following alternative methodologies can be used to fill any gaps as necessary:
• Gross ton-miles: Estimated by multiplying the average weight of each train (including the
weight of the locomotives, rail cars, and cargo), the distance traveled by each train within the
geographical domain, and the number of train visits. Gross ton-miles should be summed for all
train routes and directions. This aggregate value can then be used in Equation 8.4 to calculate
annual fuel consumption based on fleet gross ton-miles.
• Number of rail cars: Estimated using the methodology presented in Appendix K.
8.7.1.3 Switcher Locomotive Hours
If fuel consumption data are not available from the rail company to estimate the activity for switcher
locomotives, the following alternative methodologies can be used to fill any gaps as necessary:
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• Number of switcher locomotive hours: Estimated by multiplying the number of rail cars visiting
the port by the average number of switching hours per rail car.
• Number of rail cars: Estimated using the methodology presented in Appendix K.
• Number of switching hours per rail car: An average value of 0.182 hours can be assumed, based
on an analysis of data from the Federal Railroad Administration.54
The switcher activity in horsepower-hours can then be estimated by multiplying the switcher locomotive
hours by the average switcher rated power times 10% (i.e., the average switcher load factor).
8.7.2 Fleet Average Emission Factors
If the tier level of locomotives visiting the port is not known, national average fleet emission factors for
PMio, HC, NOx, and CO can be used instead (presented in Table 8.5 and Table 8.6), which are not specific
to engine tier.33 The other pollutants should be calculated as described in Section 8.5.
Table 8.5. Fleet Average Line-Haul Emission Factors for NOx, PMio, HC, and CO (g/hp-h)
Calendar Year
NOx
PMio
HC
CO
2006
8.65
0.31
0.46
1.28
2007
8.41
0.30
0.45
1.28
2008
8.13
0.25
0.43
1.28
2009
7.93
0.24
0.42
1.28
2010
7.55
0.23
0.40
1.28
2011
7.16
0.21
0.37
1.28
2012
6.92
0.20
0.34
1.28
2013
6.68
0.18
0.31
1.28
2014
6.49
0.17
0.29
1.28
2015
6.20
0.16
0.27
1.28
2016
5.82
0.15
0.25
1.28
2017
5.48
0.14
0.22
1.28
2018
5.19
0.13
0.20
1.28
2019
4.95
0.12
0.19
1.28
2020
4.76
0.11
0.17
1.28
2021
4.52
0.11
0.16
1.28
2022
4.28
0.10
0.15
1.28
2023
4.04
0.09
0.14
1.28
2024
3.80
0.08
0.13
1.28
2025
3.56
0.08
0.13
1.28
2026
3.32
0.07
0.12
1.28
2027
3.13
0.07
0.11
1.28
2028
2.93
0.06
0.10
1.28
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Calendar Year
NOx
PMio
HC
CO
2029
2.74
0.05
0.10
1.28
2030
2.55
0.05
0.09
1.28
2031
2.36
0.05
0.08
1.28
2032
2.21
0.04
0.08
1.28
2033
2.07
0.04
0.07
1.28
2034
1.92
0.03
0.07
1.28
2035
1.78
0.03
0.06
1.28
2036
1.68
0.03
0.06
1.28
2037
1.59
0.03
0.06
1.28
2038
1.49
0.02
0.05
1.28
2039
1.39
0.02
0.05
1.28
2040
1.35
0.02
0.05
1.28
Table 8.6. Fleet Average Switcher Emission Factors for NOx, PMi0, HC, and CO (g/hp-h)
Calendar Year
NOx
PMio
HC
CO
2006
16.45
0.43
0.99
1.83
2007
16.38
0.43
0.99
1.83
2008
15.99
0.36
0.95
1.83
2009
15.86
0.36
0.95
1.83
2010
15.53
0.36
0.93
1.83
2011
15.46
0.35
0.92
1.83
2012
14.93
0.34
0.88
1.83
2013
14.80
0.33
0.88
1.83
2014
14.28
0.32
0.84
1.83
2015
14.14
0.32
0.83
1.83
2016
13.68
0.30
0.79
1.83
2017
13.55
0.30
0.78
1.83
2018
13.29
0.29
0.76
1.83
2019
13.16
0.29
0.75
1.83
2020
12.30
0.27
0.69
1.83
2021
12.17
0.26
0.68
1.83
2022
11.64
0.26
0.64
1.83
2023
11.32
0.24
0.63
1.83
2024
10.66
0.23
0.59
1.83
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 128
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Calendar Year
NOx
PMio
HC
CO
2025
9.87
0.21
0.53
1.83
2026
9.47
0.20
0.50
1.83
2027
9.08
0.20
0.48
1.83
2028
8.68
0.18
0.45
1.83
2029
8.29
0.18
0.43
1.83
2030
7.83
0.16
0.41
1.83
2031
7.37
0.16
0.38
1.83
2032
6.91
0.14
0.36
1.83
2033
6.45
0.14
0.34
1.83
2034
5.99
0.13
0.31
1.83
2035
5.53
0.11
0.29
1.83
2036
5.07
0.11
0.26
1.83
2037
4.67
0.10
0.24
1.83
2038
4.41
0.09
0.24
1.83
2039
4.14
0.09
0.22
1.83
2040
3.95
0.08
0.21
1.83
8.8 Projecting Future Emission Inventories
Future locomotive emission inventories should be projected from a base year inventory, developed as
described in the sections above. In general, the projection process follows these steps:
1. Activity growth rates are applied to the base year activity to estimate future activity
2. Locomotive tier distributions are adjusted to account for fleet turnover to newer, cleaner
engines and emission factors are reassigned
3. Projected emissions are calculated using the estimated future activity
4. Projected emissions are aggregated to the same level of detail as the base year inventory, as
determined by the purpose of the inventory
Activity growth rates should be derived from local port growth projections or regional economic
forecasts, if available, which could be obtained in consultation with the local port authority, marine
exchange, board of trade, or other local and/or state organizations.
If local port projections or other regional forecasts are unavailable, the FAF11 can be used to forecast
growth instead. If this is used, the commodity flows in the FAF assigned to the rail transportation mode
should be used when calculating growth. The growth rates should then be applied to the base year
horsepower-hours activity estimate for both locomotive types.
If the age distribution of a port locomotive fleet in the future analysis year can be anticipated (e.g., for a
captive fleet), this age distribution should inform the assignment of future emission factors for the
future fleet. If this information is not available, the emission factors presented in Section 8.7.2 can be
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 129
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used instead. These fleet-average emission factors are not specific to engine tier and are available for
future years through 2040. For other pollutants of concern that are not included in Section 8.7.2, the
emission factor estimation methodologies from Section 8.5 should be applied.
Additionally, any planned action or emission reduction strategies that have been committed to that
would affect future emissions should be included according to the actual expected implementation of
such commitments. For example, if a port has committed to replacing or repowering its oldest switcher
locomotives through authorization of funds for such purchases, the effects of such a program should be
reflected in the projected age distribution. Note that if the future year inventory is for a regulatory
purpose, planned future actions should be included only if written commitments have been made by the
agency or operator with the power to implement them.
Once the base year activity has been scaled and appropriate emission factors are assigned to each unit,
the projected future emissions can be calculated using the same methodology at the same level of detail
as the base year inventory. Finally, the resulting emissions inventory should be aggregated to the same
level of detail as the base year inventory.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 131
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Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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Appendix A Estimating Port-Related Energy Consumption
This appendix can be used to estimate energy consumption for each of the port-related mobile source
sectors covered in this document. As discussed in Section 2, energy consumption is an important
measure of port activity. The following subsections discuss how to estimate energy consumption for
each source sector in the context of estimating an emissions inventory.
Note that some of the sectors use kilowatt hours (kWh) as the unit for energy consumption, whereas
others use horsepower-hours (hp-h) for historical purposes. The following conversion factor can be
used to convert hp-h into kWh:
1 hp-h = 0.7457 kWh
A.l Ocean-Going Vessels
Energy in kWh is a measure of activity for the ocean-going vessels (OGV) sector and is calculated as part
of the inventory development process. Section A.l.l describes how to calculate energy using the
Automatic Identification System (AIS) methodology corresponding to Section 3.8; Section A.l.2
describes how to calculate energy using the alternative methodology corresponding to Section 3.9.
A.l.l AIS Inventory Methodology
When calculating an emissions inventory for OGV using AIS data, propulsion engine emissions are
calculated at the AIS record level by multiplying engine load by hours of operation, an emission factor,
and a low load adjustment factor (LLAF), as described in Section 3.8.6. Propulsion engine energy
consumption is calculated using these components without the emission factor, as shown in Equation
A.l:
Energyp = Ppx Ax LLAF Equation A.l
Where Energyp = propulsion engine energy consumption for each AIS record (kWh)
Pp = propulsion engine operating power for each AIS record (kW), from Equation 3.6 or
Equation 3.7
A = time interval between consecutive AIS records (h)
LLAF = low load adjustment factor determined for each AIS record (unitless)
If the load factor for an individual AIS record is less than 20% (as calculated using Equation 3.8), the LLAF
for C02 should be applied (see Section 3.7). If the load factor is 20% or greater, no LLAF is needed. Note
that propulsion engine energy consumption should only be calculated for AIS records that are
determined to be in the transit, maneuvering, or restricted speed zone operating modes (i.e., propulsion
engines can be assumed to be off while hotelling or at anchor).
As for auxiliary engines and boilers, their emissions are calculated at the AIS record level by multiplying
engine load by hours of operation and an emission factor, as described in Section 3.8.7 (note, auxiliary
engine and boiler loads are estimated for each operating mode as described in Section 3.6). Energy
consumption for these sources is calculated using these components without the emission factor, as
shown in Equation A.2 and Equation A.3:
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Energya = Pa x A Equation A.2
auxiliary engine energy consumption for each AIS record (kWh)
auxiliary engine operating power for each AIS record based on operating
mode (kW)
time interval between consecutive AIS records (h)
Energyb = Pb x A Equation A.3
Where Energyb = boiler energy consumption for each AIS record (kWh)
Pb = boiler load for each AIS record based on operating mode (kW)
A = time interval between consecutive AIS records (h)
Total energy consumption for each time interval between consecutive AIS records should be calculated
using Equation A.4:
Energy = Energyp + Energya + Energyb Equation A.4
Where Energy = total energy consumption for each AIS record (kWh)
Energyp = propulsion engine energy consumption for each AIS record (kWh) from
Equation A.l
Energya = auxiliary engine energy consumption for each AIS record (kWh) from
Equation A.2
Energyb = boiler energy consumption for each AIS record (kWh) from Equation A.3
The total energy consumption at the AIS record level can then be aggregated to the same levels as the
OGV emissions inventory, as described in Section 3.8.8.
A.l.2 Alternative Inventory Methodology
When calculating an emissions inventory for OGV using the alternative inventory methodology,
propulsion engine emissions are calculated for each vessel call and for each of the transit, reduced
speed zone, and maneuvering operating modes. Specifically, the emissions are calculated by multiplying
engine load by hours of operation, an emission factor, and a low load adjustment factor (LLAF), as
described in Section 3.9.3. Propulsion engine energy consumption is calculated using these components
without the emission factor, as shown in Equation A.5:
Energyp i = Ppi x At x LLAFt Equation A.5
Where Energyp j = propulsion engine energy consumption for operating mode i (kWh)
Pp i = propulsion engine operating power for operating mode i (kW), from Equation 3.13
Ai = time spent in operating mode i (h)
LLAFi = l°w l°acl adjustment factor for operating mode i (unitless)
If the load factor for an operating mode is less than 20% (as calculated using Equation 3.14), the LLAF for
C02 should be applied (see Section 3.7). If the load factor is 20% or greater, no LLAF is needed.
As for auxiliary engines and boilers, their emissions are calculated for all operating modes by multiplying
engine load by hours of operation and an emission factor, as described in Section 3.9.4 (note, auxiliary
Where Energya =
Pa
A
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2020 Public Draft
engine and boiler loads are estimated for each operating mode as described in Section 3.6). Energy
consumption for these sources is calculated using these components without the emission factor, as
shown in Equation A.6 and Equation A.7:
Energya i = Pa i x At Equation A.6
Where Energyai = auxiliary engine energy consumption for operating mode i (kWh)
Pa i = auxiliary engine operating power for operating mode i (kW)
Ai = time spent in operating mode i (h)
Energybi = Pbi x At Equation A.7
Where Energybi = boiler energy consumption for operating mode i (kWh)
Pb i = boiler load for operating mode i (kW)
Ai = time spent in operating mode i (h)
Total energy consumption for each vessel should be calculated using Equation A.8:
Energyt = Energyp i + Energya i + Energyb i Equation A.8
Where Energyt = total energy consumption for operating mode i (kWh)
Energyp i = propulsion engine energy consumption for operating mode i (kWh) from
Equation A.6
Energya i = auxiliary engine energy consumption for operating mode i (kWh) from
Equation A.7
Energyb i = boiler energy consumption for operating mode i (kWh) from Equation A.8
The total energy consumption for each vessel can then be aggregated to the same levels as the OGV
emissions inventory, as described in Section 3.9.5.
A.2 Harbor Craft
Energy in kWh is a measure of activity for the harbor craft sector and is calculated as part of the
inventory development process. Section A.2.1 describes how to calculate energy using the AIS
methodology corresponding to Section 4.7; Section A.2.2 describes how to calculate energy using the
alternative methodology corresponding to Section 4.8.
A.2.1 AIS Inventory Methodology
When calculating an emissions inventory for harbor craft using AIS data, two operating modes are
considered: hotelling and non-hotelling. Emissions are calculated at the vessel level by multiplying the
installed power by a load factor, an emission factor, and hours of operation for each operating mode, as
described in Section 4.7.4. Energy consumption is calculated using these components without the
emission factor. Equation A.9 describes how non-hotelling energy consumption is calculated, and
Equation A.10 describes the calculation for hotelling energy consumption.
Energynh = (Pp x LFp +Pax LFa) x Anh Equation A.9
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
138
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Appendix A. Estimating Port-Related Energy Consumption
2020 Public Draft
Where Energynh = non-hotelling energy consumption for each vessel (kWh)
Pp = total installed propulsion engine power (kW)
LFp = propulsion engine load factor (unitless)
Pa = total installed auxiliary engine power (kW)
LFa = auxiliary engine load factor (unitless)
Anh = non-hotelling activity (h)
Energyh = Pa x LFa x Ah
Equation A.10
Where Energyh = hotelling energy consumption for each vessel (kWh)
Pa = total installed auxiliary engine power (kW)
LFa = auxiliary engine load factor (unitless)
Ah = hotelling activity (h)
Total energy consumption for the harbor craft sector should be calculated using Equation A.11.
Where Energy = total energy consumption for each vessel (kWh)
Energynh = non-hotelling energy consumption for each vessel (kWh)
Energyh = hotelling energy consumption for each vessel (kWh)
The total energy consumption can then be aggregated or allocated to the same levels as the harbor craft
emissions inventory, as described in Section 4.7.5.
A.2.2 Alternative Inventory Methodology
When calculating an emissions inventory for harbor craft using the alternative inventory methodology,
emissions are calculated at the vessel level by multiplying the installed power by a load factor, an
emission factor, and hours of operation for both propulsion and auxiliary engines, as described in
Section 4.8.3. Energy consumption is calculated using these components without the emission factor.
Equation A.12 describes how energy consumption is calculated using this methodology:
The total energy consumption can then be aggregated or allocated to the same levels as the harbor craft
emissions inventory, as described in Section 4.8.4.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 139
Energy = Energynh + Energyh
Equation A.ll
Energy Pp x LFp x Ap Pa x LFa x Aa
Equation A.12
Where Energy = energy consumption for each vessel (kWh)
Pp = total installed propulsion engine power (kW)
LFp = propulsion engine load factor (unitless)
Ap = propulsion engine activity (h)
Pa = total installed auxiliary engine power (kW)
LFa = auxiliary engine load factor (unitless)
Aa = auxiliary engine activity (h)
-------
Appendix A. Estimating Port-Related Energy Consumption
2020 Public Draft
A.3 Recreational Marine
Energy in hp-h is a measure of activity for the recreational marine sector and is calculated as part of the
inventory development process. Section A.3.1 describes how to calculate energy using the AIS
methodology corresponding to Section 5.6; Section A.3.2 describes how to calculate energy using the
alternative methodology corresponding to Section 5.7.
A.3.1 AIS Inventory Methodology
When calculating an emissions inventory for recreational marine using AIS data, emissions are calculated
at the vessel level by multiplying the number of engines on the vessel by the rated engine power, load
factor, operating activity, and an emission factor, as described in Section 5.6.4. Energy consumption is
calculated using these components without the emission factor. Note that because this does not
include the emission factor, it is not necessary to run MOVES-Nonroad to estimate energy consumption
from recreational marine vessels. Equation A.13 describes how energy consumption is calculated using
this methodology:
Energy = Ne x P x LF x A Equation A.13
Where Energy = energy consumption for each vessel (hp-h)
Ne = number of engines on the vessel
P = rated engine power (hp)
LF = engine load factor (unitless)
A = engine operating activity (h)
The total energy consumption can then be aggregated or allocated to the same levels as the recreational
marine emissions inventory, as described in Section 5.6.5.
A.3.2 Alternative Inventory Methodology
When calculating an emissions inventory for recreational marine using the alternative inventory
methodology, emissions are calculated at the fleet level by multiplying the number of recreational
vessels by the average engine power, average load factor, average operating activity, and an emission
factor, as described in Section 5.7. Energy consumption is calculated using these components without
the emission factor. Note that because this does not include the emission factor, it is not necessary to
run MOVES-Nonroad to estimate energy consumption from recreational marine vessels. Equation A.14
describes how energy consumption is calculated using this methodology for each vessel type with fleet
average values:
Energy = Nv x P x LF x A Equation A.14
Where Energy = fleet energy consumption for each vessel type (hp-h)
Nv = number of recreational vessels
P = average engine power (hp)
LF = average load factor (unitless)
A = average operating activity (h)
The total energy consumption can then be aggregated or allocated to the same levels as the recreational
marine emissions inventory, as described in Section 5.7.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
140
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Appendix A. Estimating Port-Related Energy Consumption
2020 Public Draft
A.4 Cargo Handling Equipment
Energy in hp-h is a measure of activity for the cargo handling equipment (CHE) sector and is calculated as
part of the inventory development process. Emissions are calculated in this sector for each unit of CHE
by multiplying the unit's rated engine power by a load factor, operating activity, and an emission factor,
as described in Section 6.6.1. Energy consumption is calculated using these components without the
emission factor. Note that because this does not include the emission factor, it is not necessary to run
MOVES-Nonroad to estimate energy consumption from CHE. Equation A. 15 describes how energy
consumption is calculated using this methodology:
The total energy consumption can then be aggregated or allocated to the same levels as the CHE
emissions inventory, as described in Section 6.6.2.
A.5 Onroad Vehicles
Energy consumption for onroad vehicles can be estimated in the same manner as any pollutant selected
for this sector. Regardless if the County Scale (Section 7.5) or Project Scale (Section 7.6) approach is
used, the model setup and post-processing for energy consumption is identical to those steps taken for
the rest of the onroad inventory development process. The MOVES user simply needs to select "Total
Energy Consumption" in the Pollutants and Processes Panel when setting up the run specification
(RunSpec). Note that the unit of energy consumption for the onroad sector can be joules (J), kilojoules
(kJ), or million British thermal units (BTU), as selected by the user when setting up the RunSpec.
The following conversion factors can be used to convert these units into kWh:
• Divide energy consumption in joules by 3,600,000 to get energy consumption in kWh
• Divide energy consumption in kilojoules by 3,600 to get energy consumption in kWh
• Multiply energy consumption in million BTU by 293.07107 to get energy consumption in kWh
Energy in hp-h is the primary measurement of activity for the rail sector and it is directly and specifically
calculated as part of the inventory development process. It is either calculated based on fuel
consumption (Section 8.4.1), number of trains (Section 8.4.2), or gross ton-miles (Section 8.4.3). See
Section 8.4 for more information.
Energy = P x LF x A
Equation A.15
Where Energy = per unit energy consumption (hp-h)
P = rated engine power (hp)
LF = engine load factor (unitless)
A = engine operating activity (h)
A.6 Rail
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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U.S. Environmental Protection Agency
2020 Public Draft
Appendix B Determining CI andC2 Engine Tiers
This appendix can be used to determine the applicable engine tier of Category 1 and 2 (CI and C2,
respectively) propulsion engines on U.S. flagged ships based on cylinder displacement range, power
range, and engine model year. As described in Sections 3.3.2 and 4.3.2, this is a necessary step if the CI
and C2 vessel characteristic data do not include engine tier information, but do include cylinder
displacement, engine power rating, and engine model year data. The information in this table is
consistent with the CI and C2 emission factors presented in Appendix H.
CI and C2 engine tiers vary by cylinder displacement, engine power, and model year, and are presented
in Table B.l.13 Note that if the cylinder displacement is 30 L or greater, it is a C3 engine, and those tiers
are discussed in Section 3.5.1.
Table B.l. Category 1 and 2 Engine Tiers
Cylinder Displacement
Range (L/cyl)
Power Range
Model Year
Range
Engine Tier
All
0 < kW < 19
Pre-2000
19 < kW < 37
Pre-1999
Uncontrolled
Disp < 5
kW > 37
Pre-2004
5 < Disp < 30
All
Pre-2004
All
0 < kW < 19
2000-2004
19 < kW < 37
1999-2003
Disp < 0.9
kW > 37
2004
Tier 1
2.5 < Disp < 5
kW > 37
2004-2006
5 < Disp < 30
All
2004-2006
All
0 < kW < 19
2005-2008
19 < kW < 37
2004-2008
Disp < 0.9
37 < kW < 75
2005-2008
75 < kW < 600
2005-2011
0.9 < Disp < 1.2
kW > 37
2004-2012
Tier 2
1.2 < Disp < 2.5
kW > 37
2004-2013
2.5 < Disp < 3.5
kW > 37
2007-2012
3.5 < Disp < 5
kW > 37
2007-2011
5 < Disp < 15
All
2007-2012
15 < Disp < 30
All
2007-2013
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
142
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Appendix B. Determining CI and C2 Engine Tiers
2020 Public Draft
Cylinder Displacement
Range (L/cyl)
Power Range
Model Year
Range
Engine Tier
All
0 < kW < 37
2009+
Disp < 0.9
37 < kW < 75
2009+
75 < kW < 600
2012+
0.9 < Disp < 1.2
kW < 600
2013+
1.2 < Disp < 2.5
kW < 600
2014+
2.5 < Disp < 3.5
kW < 600
2013+
3.5 < Disp < 7
kW < 600
2012+
1.2 < Disp < 2.5
600 < kW < 1000
2014-2017
2.5 < Disp < 3.5
600 < kW < 1000
2013-2017
3.5 < Disp < 7
600 < kW < 1000
2012-2017
Tier 3
1.2 < Disp < 2.5
1000 < kW < 1400
2014-2016
2.5 < Disp < 3.5
1000 < kW < 1400
2013-2016
3.5 < Disp < 7
1000 < kW < 1400
2012-2016
kW > 1400
2012-2015
kW < 600
2013+
7 < Disp < 15
600 < kW < 1000
2013-2017
1000 < kW < 1400
2013-2016
1400 < kW < 2000
2013-2015
15 < Disp < 30
1400 < kW < 2000
2014-2015
1.2 < Disp < 7
600 < kW < 1000
2018+
1.2 < Disp < 3.5
1000 < kW < 1400
2017+
3.5 < Disp < 7
1000 < kW < 1400
2017+
kW > 1400
2016+
600 < kW < 1000
2018+
1000 < kW < 1400
2017+
7 < Disp < 15
1400 < kW < 2000
2016+
Tier 4
2000 < kW < 3700
2014+
kW > 3700
2014-2016
kW > 3700
2017+
1400 < kW < 2000
2016+
15 < Disp < 30
2000 < kW < 3700
2014+
kW > 3700
2014-2016
kW > 3700
2017+
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 143
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U.S. Environmental Protection Agency 2020 Public Draft
Appendix C Filling Gaps in Vessel Characteristics for OGV
Missing data is a common occurrence in vessel characteristic data sets. The best practice for filling gaps
in vessel characteristic data is to use information from vessels with known values operating in the
geographical domain, as described in Section 3.3.5. However, if the data are not robust enough to
support such analysis, or if the analysis is not practical for other purposes, national average values
presented here can be used instead. Section C.l presents the national averages for installed propulsion
power, service speed, and maximum draft, which are all used to calculate propulsion engine operating
power. Section C.2 presents average differences between keel-laid year and build year, which is used to
estimate engine tier if only build year is known.
C.l Average Installed Propulsion Power, Service Speed, and Maximum Draft
National average values for installed propulsion power, service speed, and maximum draft are
presented in the following tables with diminishing levels of detail. At the lowest levels of detail, national
average values for propulsion engine category and engine type are also presented. This appendix
contains the following tables:
• Table C.l. Average OGV Installed Power, Service Speed, and Maximum Draft by Ship Type,
Subtype, Engine Category, and Engine Type
• Table C.2. Average OGV Engine Type, Installed Power, Service Speed, and Maximum Draft by
Ship Type, Subtype, and Engine Category
• Table C.3. Average OGV Engine Category, Engine Type, Installed Power, Service Speed, and
Maximum Draft by Ship Type and Subtype
• Table C.4. Average OGV Engine Category, Engine Type, Installed Power, Service Speed, and
Maximum Draft by Ship Type
When using defaults presented in these tables, values should be assigned at the most detailed grouping
available. That is, values should be assigned from the first table if possible, then the second, and so
forth. The average vessel characteristics presented in this appendix were used to fill gaps for the 2017
NEI CMV analysis.26 In the tables below, italicized text indicates the look up values. For example, Table
C.l can be used to look up average installed propulsion power, service speed, and maximum draft by the
following italicized values: ship type, subtype, engine category, and engine type. In contrast, Table C.2
can be used to look up the most common engine type and average installed propulsion power, service
speed, and maximum draft by the following italicized values: ship type, subtype, and engine category.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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Appendix C. Filling Gaps in Vessel Characteristics for OGV 2020 Public Draft
Table C.l. Average OGV Installed Power, Service Speed, and Maximum Draft by Ship Type, Subtype,
Engine Category, and Engine Type
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Bulk Carrier
Small
1
MSD
3,400
15.0
3.1
Bulk Carrier
Small
2
MSD
3,500
14.0
5.7
Bulk Carrier
Small
2
SSD
4,400
16.0
7.8
Bulk Carrier
Small
3
MSD
1,700
13.2
6.2
Bulk Carrier
Small
3
SSD
3,300
12.5
6.9
Bulk Carrier
Handy size
2
MSD
3,500
13.7
7.8
Bulk Carrier
Handy size
2
SSD
5,100
14.0
8.6
Bulk Carrier
Handy size
2
ST
2,900
12.0
7.6
Bulk Carrier
Handy size
3
MSD
6,200
14.2
8.7
Bulk Carrier
Handy size
3
MSD-ED
22,500
20.0
9.1
Bulk Carrier
Handy size
3
SSD
6,900
14.3
9.8
Bulk Carrier
Handy size
3
ST
5,100
14.3
8.1
Bulk Carrier
Handymax
2
SSD
5,700
13.9
9.2
Bulk Carrier
Handymax
3
MSD
8,700
14.4
9.8
Bulk Carrier
Handymax
3
SSD
8,500
14.4
11.5
Bulk Carrier
Panamax
2
SSD
10,500
15.0
10.1
Bulk Carrier
Panamax
3
MSD
12,000
14.8
9.2
Bulk Carrier
Panamax
3
SSD
10,200
14.5
13.9
Bulk Carrier
Capesize
3
SSD
16,400
14.8
17.2
Bulk Carrier
Capesize Largest
3
SSD
17,400
15.5
18.2
Chemical Tanker
Smallest
2
MSD
2,200
10.6
5.0
Chemical Tanker
Smallest
3
MSD
3,000
13.5
6.2
Chemical Tanker
Small
2
MSD
2,800
14.4
7.1
Chemical Tanker
Small
3
MSD
3,700
14.2
6.9
Chemical Tanker
Small
3
SSD
3,300
13.3
7.5
Chemical Tanker
Handy size
2
MSD
3,700
12.7
7.6
Chemical Tanker
Handy size
3
MSD
5,500
14.5
8.6
Chemical Tanker
Handy size
3
SSD
5,300
14.2
9.1
Chemical Tanker
Handymax
2
MSD-ED
9,700
16.1
11.4
Chemical Tanker
Handymax
3
MSD
7,700
14.7
11.7
Chemical Tanker
Handymax
3
MSD-ED
9,000
14.5
12.2
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Chemical Tanker
Handymax
3
SSD
9,000
14.7
12.3
Chemical Tanker
Handymax
3
ST
12,900
15.0
10.8
Container Ship
1,000 TEU
2
MSD
2,700
15.1
5.6
Container Ship
1,000 TEU
3
MSD
7,600
17.4
7.3
Container Ship
1,000 TEU
3
SSD
13,100
18.8
8.8
Container Ship
2,000 TEU
3
MSD
10,600
19.6
9.0
Container Ship
2,000 TEU
3
SSD
15,600
20.0
9.9
Container Ship
2,000 TEU
3
ST
23,500
22.0
10.4
Container Ship
3,000 TEU
3
MSD
20,800
21.8
9.5
Container Ship
3,000 TEU
3
SSD
21,800
21.6
11.4
Container Ship
3,000 TEU
3
ST
22,200
21.1
11.3
Container Ship
5,000 TEU
3
SSD
37,000
23.6
12.4
Container Ship
8,000 TEU
3
SSD
55,800
24.9
13.9
Container Ship
12,000 TEU
3
SSD
61,000
24.3
14.4
Container Ship
14,500 TEU
3
SSD
65,000
24.1
15.2
Container Ship
Largest
3
SSD
49,000
24.1
14.0
Cruise
2,000 Ton
3
MSD
2,300
12.0
4.5
Cruise
10,000 Ton
1
MSD
3,800
13.6
3.6
Cruise
10,000 Ton
2
MSD
5,800
16.8
4.6
Cruise
10,000 Ton
3
MSD
7,100
18.0
5.0
Cruise
10,000 Ton
3
SSD
2,500
16.0
4.6
Cruise
60,000 Ton
2
MSD
14,700
19.2
6.6
Cruise
60,000 Ton
3
MSD
16,200
19.2
6.4
Cruise
60,000 Ton
3
MSD-ED
20,700
19.7
7.0
Cruise
60,000 Ton
3
SSD
23,400
19.2
7.5
Cruise
100,000 Ton
1
GT-ED
40,200
24.0
8.1
Cruise
100,000 Ton
3
GT-ED
37,900
22.8
8.2
Cruise
100,000 Ton
3
MSD
23,100
20.1
7.6
Cruise
100,000 Ton
3
MSD-ED
34,000
21.9
8.0
Cruise
Largest
3
GT-ED
86,000
24.0
10.3
Cruise
Largest
3
MSD
41,700
21.0
8.6
Cruise
Largest
3
MSD-ED
41,700
22.1
8.6
Cruise
Largest
3
SSD
60,000
22.6
9.3
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 146
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Ferry/Roll-on/Passenger
(C3)
2,000 Ton
1
SSD
2,200
19.0
2.2
Ferry/Roll-on/Passenger
(C3)
2,000 Ton
2
SSD
2,700
14.2
3.2
Ferry/Roll-on/Passenger
(C3)
2,000 Ton
3
SSD
900
14.2
3.1
Ferry/Roll-on/Passenger
(C3)
Largest
1
MSD
3,900
15.9
4.7
Ferry/Roll-on/Passenger
(C3)
Largest
1
MSD-ED
3,700
14.0
3.8
Ferry/Roll-on/Passenger
(C3)
Largest
2
MSD
10,000
19.9
4.3
Ferry/Roll-on/Passenger
(C3)
Largest
2
MSD-ED
5,400
14.0
3.7
Ferry/Roll-on/Passenger
(C3)
Largest
2
ST
1,100
10.0
2.6
Ferry/Roll-on/Passenger
(C3)
Largest
3
MSD
10,800
19.6
5.1
Ferry/Roll-on/Passenger
(C3)
Largest
3
MSD-ED
11,000
21.0
5.8
Ferry/Roll-on/Passenger
(C3)
Largest
3
ST
6,000
14.0
5.7
Fishing (C3)
All C3 Fishing
1
MSD
700
11.3
3.6
Fishing (C3)
All C3 Fishing
1
SSD
1,000
11.4
3.1
Fishing (C3)
All C3 Fishing
2
MSD
2,600
12.8
5.6
Fishing (C3)
All C3 Fishing
2
SSD
2,200
12.5
4.4
Fishing (C3)
All C3 Fishing
3
MSD
3,200
13.0
5.4
Fishing (C3)
All C3 Fishing
3
SSD
4,000
16.9
5.7
General Cargo
5,000 DWT
1
MSD
1,500
10.8
3.0
General Cargo
5,000 DWT
2
MSD
1,300
11.8
4.4
General Cargo
5,000 DWT
3
MSD
1,100
11.9
4.1
General Cargo
10,000 DWT
2
MSD
2,500
12.5
6.7
General Cargo
10,000 DWT
3
MSD
3,500
13.0
7.2
General Cargo
10,000 DWT
3
SSD
3,300
15.5
6.9
General Cargo
Largest
3
MSD
14,400
16.9
8.3
General Cargo
Largest
3
SSD
15,900
17.3
8.4
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 147
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
General Cargo
Largest
3
ST
14,200
21.0
8.4
Liquified Gas Tanker
50,000 DWT
2
MSD
2,900
13.6
6.2
Liquified Gas Tanker
50,000 DWT
3
MSD
2,700
14.3
6.1
Liquified Gas Tanker
50,000 DWT
3
SSD
2,600
14.9
5.5
Liquified Gas Tanker
100,000 DWT
2
SSD
3,500
14.8
6.8
Liquified Gas Tanker
100,000 DWT
3
MSD
4,100
15.0
7.3
Liquified Gas Tanker
100,000 DWT
3
SSD
4,900
15.3
7.4
Liquified Gas Tanker
200,000 DWT
2
MSD
5,000
13.5
8.0
Liquified Gas Tanker
200,000 DWT
3
MSD
7,000
16.1
9.3
Liquified Gas Tanker
200,000 DWT
3
SSD
7,000
16.8
9.2
Liquified Gas Tanker
Largest
3
MSD
22,900
13.0
12.5
Liquified Gas Tanker
Largest
3
MSD-ED
25,600
18.9
11.9
Liquified Gas Tanker
Largest
3
SSD
12,400
16.4
11.5
Liquified Gas Tanker
Largest
3
ST
27,400
19.5
12.0
Miscellaneous (C3)
All C3 Misc.
1
MSD
2,200
11.9
4.2
Miscellaneous (C3)
All C3 Misc.
1
MSD-ED
3,300
13.0
5.4
Miscellaneous (C3)
All C3 Misc.
1
SSD
1,300
10.6
2.8
Miscellaneous (C3)
All C3 Misc.
2
MSD
6,300
16.4
5.2
Miscellaneous (C3)
All C3 Misc.
2
MSD-ED
6,400
14.3
5.4
Miscellaneous (C3)
All C3 Misc.
2
SSD
3,700
14.0
4.3
Miscellaneous (C3)
All C3 Misc.
3
MSD
6,000
15.1
8.0
Miscellaneous (C3)
All C3 Misc.
3
MSD-ED
16,300
14.5
11.3
Miscellaneous (C3)
All C3 Misc.
3
SSD
8,900
16.0
9.5
Miscellaneous (C3)
All C3 Misc.
3
ST
21,200
19.2
9.8
Offshore Support/Drillship
All Offshore
Support / Drillship
1
MSD
3,100
15.2
3.6
Offshore Support/Drillship
All Offshore
Support / Drillship
1
MSD-ED
5,400
12.9
5.7
Offshore Support/Drillship
All Offshore
Support / Drillship
1
SSD
1,400
12.6
3.2
Offshore Support/Drillship
All Offshore
Support / Drillship
2
MSD
5,300
13.3
5.6
Offshore Support/Drillship
All Offshore
Support / Drillship
2
MSD-ED
13,000
12.5
9.6
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 148
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Offshore Support/Drillship
All Offshore
Support / Drillship
2
SSD
4,700
13.0
4.6
Offshore Support/Drillship
All Offshore
Support / Drillship
3
MSD
9,200
13.6
6.9
Offshore Support/Drillship
All Offshore
Support / Drillship
3
MSD-ED
26,300
12.5
10.9
Offshore Support/Drillship
All Offshore
Support / Drillship
3
SSD
11,300
14.8
13.4
Oil Tanker
Handymax
3
SSD
8,700
14.6
12.1
Oil Tanker
Aframax
3
SSD
12,200
14.8
14.6
Oil Tanker
Suezmax
3
SSD
16,900
14.7
16.9
Other Tanker
All Other Tanker
1
MSD
1,600
8.2
3.2
Other Tanker
All Other Tanker
1
MSD-ED
2,300
6.0
3.0
Other Tanker
All Other Tanker
1
SSD
1,200
7.9
2.2
Other Tanker
All Other Tanker
2
MSD
3,300
12.8
4.5
Other Tanker
All Other Tanker
2
MSD-ED
14,000
18.0
9.0
Other Tanker
All Other Tanker
2
SSD
3,400
12.5
4.6
Other Tanker
All Other Tanker
3
GT
78,300
26.0
11.9
Other Tanker
All Other Tanker
3
MSD
4,700
13.5
8.0
Other Tanker
All Other Tanker
3
MSD-ED
20,000
15.3
18.8
Other Tanker
All Other Tanker
3
SSD
15,700
15.2
15.5
Other Tanker
All Other Tanker
3
ST
21,600
16.9
16.6
Reefer
All Reefer
1
MSD
1,300
10.0
0.0
Reefer
All Reefer
2
MSD
2,200
12.5
5.9
Reefer
All Reefer
2
SSD
2,200
12.0
5.5
Reefer
All Reefer
3
MSD
9,200
20.4
8.6
Reefer
All Reefer
3
SSD
9,800
19.2
8.6
RORO
5000 Ton
1
MSD
1,700
11.8
3.1
RORO
5000 Ton
2
MSD
1,300
11.1
3.4
RORO
5000 Ton
2
SSD
2,400
14.0
4.5
RORO
5000 Ton
3
MSD
3,200
15.4
4.7
RORO
5000 Ton
3
SSD
2,300
15.6
4.5
RORO
Largest
1
MSD-ED
7,000
18.5
9.3
RORO
Largest
2
MSD
3,500
14.2
5.9
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 149
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
RORO
Largest
2
SSD
5,900
15.0
3.7
RORO
Largest
3
GT
45,100
25.2
10.2
RORO
Largest
3
MSD
18,500
18.4
8.2
RORO
Largest
3
MSD-ED
39,500
24.0
9.0
RORO
Largest
3
SSD
15,600
20.0
10.0
RORO
Largest
3
ST
49,400
24.5
10.0
Yacht(C2/C3)
C2/C3 Yacht
1
MSD
3,000
17.6
2.7
Yacht(C2/C3)
C2/C3 Yacht
2
MSD
5,400
15.8
3.7
Yacht(C2/C3)
C2/C3 Yacht
3
MSD
3,900
16.0
4.7
Yacht(C2/C3)
C2/C3 Yacht
3
SSD
5,000
17.3
6.0
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 150
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Appendix C. Filling Gaps in Vessel Characteristics for OGV 2020 Public Draft
Table C.2. Average OGV Engine Type, Installed Power, Service Speed, and Maximum Draft by Ship
Type, Subtype, and Engine Category
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Bulk Carrier
Small
1
MSD-ED
3,400
15.0
3.1
Bulk Carrier
Small
2
SSD
4,400
16.0
7.8
Bulk Carrier
Small
3
MSD
1,800
13.1
6.3
Bulk Carrier
Handysize
2
SSD
4,300
13.7
8.2
Bulk Carrier
Handysize
3
SSD
7,100
14.4
9.6
Bulk Carrier
Handymax
2
SSD
5,700
13.9
9.2
Bulk Carrier
Handymax
3
SSD
8,500
14.4
11.5
Bulk Carrier
Pan am ax
2
SSD
10,500
15.0
10.1
Bulk Carrier
Pan am ax
3
SSD
10,300
14.5
13.8
Bulk Carrier
Capesize
3
SSD
16,400
14.8
17.2
Bulk Carrier
Capesize Largest
3
SSD
17,400
15.5
18.2
Chemical Tanker
Smallest
2
MSD
2,200
10.6
5.0
Chemical Tanker
Smallest
3
MSD
3,000
13.5
6.2
Chemical Tanker
Small
2
MSD
2,800
14.4
7.1
Chemical Tanker
Small
3
SSD
3,400
13.5
7.3
Chemical Tanker
Handysize
2
MSD
3,700
12.7
7.6
Chemical Tanker
Handysize
3
SSD
5,400
14.3
8.9
Chemical Tanker
Handymax
2
MSD-ED
9,700
16.1
11.4
Chemical Tanker
Handymax
3
SSD
9,100
14.7
12.3
Container Ship
1,000 TEU
2
MSD
2,700
15.1
5.6
Container Ship
1,000 TEU
3
MSD
8,600
17.7
7.6
Container Ship
2,000 TEU
3
SSD
14,700
20.0
9.7
Container Ship
3,000 TEU
3
SSD
21,800
21.5
11.3
Container Ship
5,000 TEU
3
SSD
37,000
23.6
12.4
Container Ship
8,000 TEU
3
SSD
55,800
24.9
13.9
Container Ship
12,000 TEU
3
SSD
61,000
24.3
14.4
Container Ship
14,500 TEU
3
SSD
65,000
24.1
15.2
Container Ship
Largest
3
SSD
49,000
24.1
14.0
Cruise
2,000 Ton
1
MSD
2,300
12.0
4.5
Cruise
2,000 Ton
3
MSD
2,300
12.0
4.5
Cruise
10,000 Ton
1
MSD
3,800
13.6
3.6
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
151
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Cruise
10,000 Ton
2
MSD
5,800
16.8
4.6
Cruise
10,000 Ton
3
MSD
6,300
17.7
4.9
Cruise
60,000 Ton
2
MSD
14,700
19.2
6.6
Cruise
60,000 Ton
3
MSD-ED
19,600
19.5
6.9
Cruise
100,000 Ton
1
GT-ED
40,200
24.0
8.1
Cruise
100,000 Ton
3
MSD-ED
34,300
22.0
8.0
Cruise
Largest
3
MSD-ED
42,900
22.1
8.6
Ferry/Roll-on/Passen ger
(C3)
2,000 Ton
1
MSD
2,200
19.0
2.2
Ferry/Roll-on/Passen ger
(C3)
2,000 Ton
2
SSD
2,700
14.2
3.2
Ferry/Roll-on/Passen ger
(C3)
2,000 Ton
3
SSD
900
14.2
3.1
Ferry/Roll-on/Passen ger
(C3)
Largest
1
MSD
3,900
15.5
4.5
Ferry/Roll-on/Passen ger
(C3)
Largest
2
SSD
8,500
18.2
4.1
Ferry/Roll-on/Passen ger
(C3)
Largest
3
MSD
10,700
19.7
5.2
Fishing (C3)
All C3 Fishing
1
MSD
700
11.3
3.5
Fishing (C3)
All C3 Fishing
2
MSD
2,400
12.6
5.1
Fishing (C3)
All C3 Fishing
3
MSD
3,200
13.2
5.4
General Cargo
5,000 DWT
1
MSD
1,500
10.8
3.0
General Cargo
5,000 DWT
2
MSD
1,300
11.8
4.4
General Cargo
5,000 DWT
3
MSD
1,100
11.9
4.1
General Cargo
10,000 DWT
2
MSD
2,500
12.5
6.7
General Cargo
10,000 DWT
3
MSD
3,400
14.2
7.1
General Cargo
Largest
3
MSD
14,900
17.4
8.4
Liquified Gas Tanker
50,000 DWT
2
MSD
2,900
13.6
6.2
Liquified Gas Tanker
50,000 DWT
3
SSD
2,600
14.8
5.6
Liquified Gas Tanker
100,000 DWT
2
MSD
3,500
14.8
6.8
Liquified Gas Tanker
100,000 DWT
3
SSD
4,800
15.2
7.4
Liquified Gas Tanker
200,000 DWT
2
MSD
5,000
13.5
8.0
Liquified Gas Tanker
200,000 DWT
3
SSD
7,000
16.8
9.2
Liquified Gas Tanker
Largest
3
SSD
14,800
16.8
11.5
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 152
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Miscellaneous (C3)
All C3 Misc.
1
MSD
2,100
11.8
4.0
Miscellaneous (C3)
All C3 Misc.
2
MSD
6,100
16.1
5.1
Miscellaneous (C3)
All C3 Misc.
3
MSD
7,500
15.5
8.5
Offshore Support/Drillship
All Offshore
Support / Drillship
1
MSD
3,300
14.6
3.9
Offshore Support/Drillship
All Offshore
Support / Drillship
2
MSD
6,200
13.1
5.8
Offshore Support/Drillship
All Offshore
Support / Drillship
3
SSD
14,200
14.1
12.0
Oil Tanker
Handymax
3
SSD
8,700
14.6
12.1
Oil Tanker
Aframax
3
SSD
12,200
14.8
14.6
Oil Tanker
Suezmax
3
SSD
16,900
14.7
16.9
Other Tanker
All Other Tanker
1
MSD
1,600
8.0
3.0
Other Tanker
All Other Tanker
2
SSD
3,300
12.6
4.6
Other Tanker
All Other Tanker
3
SSD
15,800
15.2
15.4
Reefer
All Reefer
1
MSD
1,300
10.0
5.7
Reefer
All Reefer
2
SSD
2,200
12.2
5.7
Reefer
All Reefer
3
SSD
9,700
19.3
8.6
RORO
5000 Ton
1
MSD
1,700
11.8
3.1
RORO
5000 Ton
2
SSD
2,200
13.3
4.2
RORO
5000 Ton
3
MSD
2,900
15.5
4.6
RORO
Largest
1
MSD-ED
7,000
18.5
9.3
RORO
Largest
2
MSD
4,500
14.5
5.0
RORO
Largest
3
SSD
19,900
20.3
9.7
Yacht(C2/C3)
C2/C3 Yacht
1
MSD
3,000
17.6
2.7
Yacht(C2/C3)
C2/C3 Yacht
2
MSD
5,400
15.8
3.7
Yacht(C2/C3)
C2/C3 Yacht
3
MSD
3,900
16.0
4.7
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 153
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Appendix C. Filling Gaps in Vessel Characteristics for OGV 2020 Public Draft
Table C.3. Average OGV Engine Category, Engine Type, Installed Power, Service Speed, and Maximum
Draft by Ship Type and Subtype
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Bulk Carrier
Small
3
MSD
2,500
13.9
6.7
Bulk Carrier
Handysize
3
SSD
6,900
14.4
9.5
Bulk Carrier
Handymax
3
SSD
8,500
14.4
11.4
Bulk Carrier
Pan am ax
3
SSD
10,300
14.5
13.7
Bulk Carrier
Capesize
3
SSD
16,400
14.8
17.2
Bulk Carrier
Capesize Largest
3
SSD
17,400
15.5
18.2
Chemical Tanker
Smallest
2
MSD
2,300
10.7
5.1
Chemical Tanker
Small
3
SSD
3,200
13.8
7.2
Chemical Tanker
Handysize
3
SSD
5,300
14.3
8.9
Chemical Tanker
Handymax
3
SSD
9,100
14.7
12.3
Container Ship
1,000 TEU
3
MSD
8,200
17.5
7.4
Container Ship
2,000 TEU
3
SSD
14,700
20.0
9.7
Container Ship
3,000 TEU
3
SSD
21,800
21.5
11.3
Container Ship
5,000 TEU
3
SSD
37,000
23.6
12.4
Container Ship
8,000 TEU
3
SSD
55,800
24.9
13.9
Container Ship
12,000 TEU
3
SSD
61,000
24.3
14.4
Container Ship
14,500 TEU
3
SSD
65,000
24.1
15.2
Container Ship
Largest
3
SSD
49,000
24.1
14.0
Cruise
2,000 Ton
1
MSD
2,300
12.0
4.5
Cruise
10,000 Ton
1
MSD
4,500
14.6
3.9
Cruise
60,000 Ton
3
MSD-ED
19,100
19.5
6.9
Cruise
100,000 Ton
3
MSD-ED
34,500
22.1
8.0
Cruise
Largest
3
MSD-ED
42,900
22.1
8.6
Ferry/Roll-on/Passen ger
(C3)
2,000 Ton
1
MSD
2,400
16.6
2.7
Ferry/Roll-on/Passen ger
(C3)
Largest
2
MSD
8,800
18.5
4.7
Fishing (C3)
All C3 Fishing
1
MSD
1,000
11.6
3.8
General Cargo
5,000 DWT
1
MSD
1,400
11.3
3.6
General Cargo
10,000 DWT
3
MSD
3,400
14.2
7.1
General Cargo
Largest
3
MSD
14,900
17.4
8.4
Liquified Gas Tanker
50,000 DWT
3
SSD
2,700
14.4
5.8
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
154
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service
Speed
(kn)
Max
Draft
(m)
Liquified Gas Tanker
100,000 DWT
3
SSD
4,700
15.2
7.3
Liquified Gas Tanker
200,000 DWT
3
SSD
7,000
16.7
9.2
Liquified Gas Tanker
Largest
3
SSD
14,800
16.8
11.5
Miscellaneous (C3)
All C3 Misc.
3
MSD
5,800
14.6
6.7
Offshore Support/Drillship
All Offshore
Support / Drillship
1
MSD
6,300
14.2
6.1
Oil Tanker
Handymax
3
SSD
8,700
14.6
12.1
Oil Tanker
Aframax
3
SSD
12,200
14.8
14.6
Oil Tanker
Suezmax
3
SSD
16,900
14.7
16.9
Other Tanker
All Other Tanker
3
SSD
11,800
13.7
11.9
Reefer
All Reefer
3
SSD
9,200
18.8
8.4
RORO
5000 Ton
2
MSD
2,100
13.1
3.9
RORO
Largest
3
SSD
19,600
20.2
9.6
Yacht(C2/C3)
C2/C3 Yacht
1
MSD
3,100
17.6
2.7
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 155
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Appendix C. Filling Gaps in Vessel Characteristics for OGV 2020 Public Draft
Table C.4. Average OGV Engine Category, Engine Type, Installed Power, Service Speed, and Maximum
Draft by Ship Type
Ship Type
Engine
Category
Engine
Type
Installed
Propulsion
Power (kW)
Service Speed
(kn)
Max Draft (m)
Bulk Carrier
3
SSD
8,800
14.4
11.8
Chemical Tanker
3
SSD
8,200
14.6
11.5
Container Ship
3
SSD
35,300
22.3
11.8
Cruise
3
SSD
34,800
21.5
8.0
Ferry/Roll-on/Passenger
(C3)
1
MSD
6,500
17.8
4.0
Fishing (C3)
1
MSD
1,000
11.6
3.8
General Cargo
3
SSD
4,800
13.3
5.5
Liquified Gas Tanker
3
SSD
12,000
16.5
10.5
Miscellaneous (C3)
3
SSD
5,800
14.6
6.7
Offshore Support/Drillship
1
MSD
6,300
14.2
6.1
Oil Tanker
3
SSD
10,100
14.7
13.1
Other Tanker
3
SSD
11,800
13.7
11.9
Reefer
3
SSD
9,200
18.8
8.4
RORO
3
SSD
16,800
19.1
8.7
Yacht(C2/C3)
1
MSD
3,100
17.6
2.7
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
156
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
C.2 Average Differences Between Keel-laid Year and Build Year
The activity time-weighted national average differences between keel-laid year and build year by ship
type and subtype, based on the 2017 NEI C3 AIS data set, are presented in Table C.5. This difference is
important for assigning emission factors to C3 vessels because the C3 emission standards are based on
keel-laid year. If the vessel build year is known, but the keel-laid year is not, the average build time can
be subtracted from the build year to estimate the keel-laid year.
Table C.5. Average OGV Difference Between Keel-laid Year and Build Year by Ship Type and Subtype
Ship Type
Subtype
Average Build Time
(Years)
Bulk Carrier
Small
0
Bulk Carrier
Handysize
1
Bulk Carrier
Handymax
1
Bulk Carrier
Pan am ax
1
Bulk Carrier
Capesize
1
Bulk Carrier
Capesize Largest
2
Chemical Tanker
Smallest
2
Chemical Tanker
Small
2
Chemical Tanker
Handysize
1
Chemical Tanker
Handymax
1
Container Ship
1,000 TEU
1
Container Ship
2,000 TEU
1
Container Ship
3,000 TEU
1
Container Ship
5,000 TEU
1
Container Ship
8,000 TEU
1
Container Ship
12,000 TEU
1
Container Ship
14,500 TEU
1
Container Ship
Largest
2
Cruise
2,000 Ton
1
Cruise
10,000 Ton
2
Cruise
60,000 Ton
2
Cruise
100,000 Ton
2
Cruise
Largest
2
Ferry/Roll-on/Passen ger
(C3)
2,000 Ton
1
Ferry/Roll-on/Passen ger
(C3)
Largest
1
Fishing (C3)
All C3 Fishing
1
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 157
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Appendix C. Filling Gaps in Vessel Characteristics for OGV
2020 Public Draft
Ship Type
Subtype
Average Build Time
(Years)
General Cargo
5,000 DWT
1
General Cargo
10,000 DWT
2
General Cargo
Largest
2
Liquified Gas Tanker
50,000 DWT
2
Liquified Gas Tanker
100,000 DWT
1
Liquified Gas Tanker
200,000 DWT
1
Liquified Gas Tanker
Largest
1
Miscellaneous (C3)
All C3 Miscellaneous
Offshore Support/Drillship
All Offshore Support/Drillship
1
Oil Tanker
Smallest
1
Oil Tanker
Small
Oil Tanker
Handysize
1
Oil Tanker
Handymax
1
Oil Tanker
Pan am ax
Oil Tanker
Aframax
1
Oil Tanker
Suezmax
1
Other Tanker
All Other Tanker
1
Reefer
All Reefer
1
RORO
5000 Ton
1
RORO
Largest
1
Yacht(C2/C3)
C2/C3 Yacht
3
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Appendix D HAP Speciation Profiles for Commercial Marine
Engines
Hazardous air pollutants (HAPs) are calculated from various basis pollutants. The basis emission factors
for Category 3 (C3) engines are given in Section 3.5. The basis emission factors for Category 1 and 2 (CI
and C2) engines are described in Section 4.5 and are presented in Appendix H. Emission factors for HAPs
are calculated by multiplying the appropriate basis emission factor by the fraction listed in Table D.l.26
Table D.l. HAP Speciation Profiles for Commercial Marine Engines
Pollutant
Pollutant Code
Basis
Fraction
Source
1,3-Butadiene*
106990
voc
0.001013
55
2,2,4-Trimethylpentane
540841
voc
0.00712
56
Acenaphthene*
83329
voc
0.0000509
55
Acenaphthylene*
208968
voc
0.000118
55
Acetaldehyde*
75070
voc
0.009783
55
Acrolein*
107028
voc
0.001848
55
Ammonia
nh3
PM2.5
0.019247
23
Anthracene*
120127
voc
0.000344
55
Antimony*
7440360
PM2.5
0.000615
55
Arsenic
7440382
PM2.5
0.0000259
23
Benz[a] Anthracene*
56553
PM2.5
0.00000882
55
Benzene*
71432
voc
0.004739
55
Benzo[a]Pyrene
50328
PM2.5
0.00000418
23
Benzo[b]Fluoranthene
205992
PM2.5
0.00000835
23
Benzo[k]Fluoranthene
207089
PM2.5
0.00000418
23
Benzo(g,h,i)Fluoranthene*
203123
PM2.5
0.000132
55
Cadmium*
7440439
PM2.5
0.000236
55
Chrysene*
218019
PM2.5
0.0000163
55
Chromium (VI)
18540299
PM2.5
0.00000000724
56
Dibenzo[a,h]anthracene*
53703
PM2.5
0.00000865
55
Ethyl Benzene*
100414
voc
0.000439
55
Fluoranthene*
206440
PM2.5
0.0000897
55
Fluorene*
86737
voc
0.000164
55
Formaldehyde*
50000
voc
0.042696
55
lndeno[l,2,3-c,d]Pyrene
193395
PM2.5
0.00000835
23
Lead
7439921
PM2.5
0.000125
23
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Appendix D. HAP Speciation Profiles for Commercial Marine Engines
2020 Public Draft
Pollutant
Pollutant Code
Basis
Fraction
Source
Manganese
7439965
PM2.5
0.00000322
56
Mercury
7439976
PM2.5
0.0000000418
23
Naphthalene*
91203
voc
0.031304
55
Hexane
110543
voc
0.00279
56
Nickel
7440020
PM2.5
0.000687
23
Polychlorinated Biphenyls
1336363
PM2.5
0.000000418
23
Phenanthrene*
85018
voc
0.001356
55
Propionaldehyde*
123386
voc
0.001517
55
Pyrene*
129000
PM2.5
0.0000337
55
Selenium
7782492
PM2.5
0.0000000438
23
Toluene*
108883
voc
0.002035
55
Xylenes (Mixed Isomers)*
1330207
voc
0.001422
55
o-Xylene*
95476
voc
0.000513
55
* Used data for auxiliary engine which burned marine gas oil with 0.06 wt% sulfur and 0.001 wt% ash content.
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Appendix E Default OGV Auxiliary Engine and Boiler Loads
If resources allow, data on auxiliary engine and boiler usage can be directly collected from the ocean-
going vessels (OGV) operating in the geographical domain via surveys, interviews, or other data
collection methods. If a similar port has recently conducted an inventory and collected these kinds of
data, those could be used instead. Alternatively, the auxiliary engine and boiler loads used in the Third
IMO Greenhouse Gas Study15 can be used. These data are primarily based on Starcrest's Vessel Boarding
Program in the Port of Los Angeles, the Port of Long Beach, the Port Authority of New York & New
Jersey, the Port of Houston Authority, the Port of Seattle, and the Port of Tacoma, along with data
collected by the Finnish Metrological Institute. Table E.l presents default auxiliary engine loads and
Table E.2 presents default boiler loads. The operating modes listed in these tables are described in
detail in Section 3.6. If the geographical domain includes vessel activity in a restricted speed zone, the
transit operating loads should be used for that activity because auxiliary engine and boiler usage in this
operating mode is usually similar to the transit operating mode.
Table E.l. Default OGV Auxiliary Engine Operating Loads by Mode
Ship Type
Subtype
Transit (kW)
Maneuvering
(kW)
Hotelling
(kW)
Anchorage
(kW)
Bulk Carrier
Small
190
310
280
190
Handysize
190
310
280
190
Handymax
260
420
370
260
Panamax
420
680
600
420
Capesize
420
680
600
420
Capesize Largest
420
680
600
420
Chemical Tanker
Smallest
80
110
160
80
Small
230
330
490
230
Handysize
230
330
490
230
Handymax
550
780
1,170
550
Container Ship
1,000 TEU
300
550
340
300
2,000 TEU
820
1,320
600
820
3,000 TEU
1,230
1,800
700
1,230
5,000 TEU
1,390
2,470
940
1,390
8,000 TEU
1,420
2,600
970
1,420
12,000 TEU
1,630
2,780
1,000
1,630
14,500 TEU
1,960
3,330
1,200
1,960
Largest
2,160
3,670
1,320
2,160
Cruise
2,000 Ton
450
580
450
450
10,000 Ton
450
580
450
450
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Appendix E. Default OGV Auxiliary Engine and Boiler Loads
2020 Public Draft
Ship Type
Subtype
Transit (kW)
Maneuvering
(kW)
Hotelling
(kW)
Anchorage
(kW)
60,000 Ton
3500
5,460
3,500
3,500
100,000 Ton
11,480
14,900
11,480
11,480
Largest
11,480
14,900
11,480
11,480
Ferry/Passenger (C3)
2,000 Ton
186
186
186
186
Largest
524
524
524
524
Ferry/Roll-on/Passenger
(C3)
2,000 Ton
105
105
105
105
Largest
710
710
710
710
Fishing (C3)
All C3 Fishing
200
200
200
200
General Cargo
5,000 DWT
60
90
120
60
10,000 DWT
170
250
330
170
Largest
490
730
970
490
Liquified Gas Tanker
50,000 DWT
240
360
240
240
100,000 DWT
240
360
240
240
200,000 DWT
1,710
2,565
1,710
1,710
Largest
1,710
2,565
1,710
1,710
Miscellaneous (C3)
All C3 Misc.
190
190
190
190
Offshore
Support/Drillship
All Offshore
Support/Drillship
320
320
320
320
Oil Tanker
Smallest
250
375
250
250
Small
375
563
375
375
Handysize
625
938
625
625
Handymax
750
1,125
750
750
Panamax
750
1,125
750
750
Aframax
1,000
1,500
1,000
1,000
Suezmax
1,250
1,875
1,250
1,250
VLCC
1,500
2,250
1,500
1,500
Other Service
All Other Service
220
220
220
220
Other Tanker
All Other Tanker
500
750
500
500
Reefer
All Reefer
1,170
1,150
1,080
1,170
RORO
5,000 Ton
600
1,700
800
600
Largest
950
2,720
1,200
950
Vehicle Carrier
4,000 Vehicles
500
1,125
800
500
Largest
500
1,125
800
500
Yacht
C2/C3 Yacht
130
130
130
130
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 162
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Appendix E. Default OGV Auxiliary Engine and Boiler Loads 2020 Public Draft
Table E.2. Default OGV Boiler Loads by Operating Mode
Ship Type
Subtype
Transit (kW)
Maneuvering
(kW)
Hotelling
(kW)
Anchorage
(kW)
Small
0
50
50
50
Handysize
0
50
50
50
Bulk Carrier
Handymax
0
100
100
100
Panamax
0
200
200
200
Capesize
0
200
200
200
Capesize Largest
0
200
200
200
Smallest
0
125
125
125
Chemical Tanker
Small
0
250
250
250
Handysize
0
250
250
250
Handymax
0
250
250
250
1,000 TEU
0
120
120
120
2,000 TEU
0
290
290
290
3,000 TEU
0
350
350
350
Container Ship
5,000 TEU
0
450
450
450
8,000 TEU
0
450
450
450
12,000 TEU
0
520
520
520
14,500 TEU
0
630
630
630
Largest
0
700
700
700
2,000 Ton
0
250
250
250
10,000 Ton
0
250
250
250
Cruise
60,000 Ton
0
1,000
1,000
1,000
100,000 Ton
0
500
500
500
Largest
0
500
500
500
Ferry/Passenger (C3)
2,000 Ton
0
0
0
0
Largest
0
0
0
0
Ferry/Roll-
2,000 Ton
0
0
0
0
on/Passenger(C3)
Largest
0
0
0
0
Fishing (C3)
All C3 Fishing
0
0
0
0
5,000 DWT
0
0
0
0
General Cargo
10,000 DWT
0
75
75
75
Largest
0
100
100
100
Liquified Gas Tanker
50,000 DWT
100
200
1,000
200
100,000 DWT
150
300
1,500
300
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Appendix E. Default OGV Auxiliary Engine and Boiler Loads
2020 Public Draft
Ship Type
Subtype
Transit (kW)
Maneuvering
(kW)
Hotelling
(kW)
Anchorage
(kW)
200,000 DWT
300
600
3,000
600
Largest
300
600
3,000
600
Miscellaneous (C3)
All C3 Misc.
0
0
0
0
Offshore
Support/Drillship
All Offshore
Support/Drillship
0
0
0
0
Oil Tanker
Smallest
0
100
500
100
Small
0
150
750
150
Handysize
0
250
1,250
250
Handymax
150
300
1,500
300
Panamax
150
300
1,500
300
Aframax
200
400
2,000
400
Suezmax
250
500
2,500
500
VLCC
300
600
3,000
600
Other Service
All Other Service
0
0
0
0
Other Tanker
All Other Tanker
100
200
1,000
200
Reefer
All Reefer
0
270
270
270
RORO
5,000 Ton
0
200
200
200
Largest
0
300
300
300
Vehicle Carrier
4,000 Vehicles
0
268
268
268
Largest
0
268
268
268
Yacht
C2/C3 Yacht
0
0
0
0
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Appendix F OGV Sulfur Dioxide Low Load Adjustment Factors
As discussed in Section 3.7, diesel engines are generally less efficient at low loads, and so propulsion
engine emissions per unit of energy tend to increase as engine load decreases. To account for this, low
load adjustment factors (LLAFs) should be applied when the propulsion engines are operating at less
than 20% load. Table 3.10 in Section 3.7 presents LLAFs by engine load and pollutant for 0.1% sulfur
fuel. However, the sulfur dioxide (S02) LLAFs are dependent on the fuel sulfur level. If a fuel with a
sulfur level other than 0.1% is used, this appendix can be used to calculate the appropriate S02 LLAFs.
Based on the Regulatory Impact Analysis for EPA's C3 rulemaking,16 LLAFs for S02 can be calculated by
normalizing load- and sulfur-dependent S02 emission factors to 20% load using Equation F.l:
2.3735 X f14,1^05 + 205.7169) X Sact - 0.4792
LLAFS02 = /141?nr Equation F.l
2.3735 X ( q 2 + 205.7169] X Sact - 0.4792
A simplified version of the above equation is shown in Equation F.2:
2.3735 x(Mj|g£ + 2Q5.7169)x5ml-0.4792 Equation F.2
502 655.8441 X Sact - 0.4792
Where LLAFSq2 = low load adjustment factor for S02 (unitless)
LF = fractional engine load, ranging from 0.02-0.20 (unitless)
Sact = actual fuel sulfur level (weight ratio)
The underlying data used to calculate the coefficients in the above equations rely on tests performed on
engines rated below 10,000 kW using diesel fuel. This introduces uncertainty regarding the use of these
coefficients for Category 3 engines; however, these are the best estimates evaluated by EPA. Equation
F.2 was used to calculate the S02 LLAF for 0.1% sulfur fuel as presented in Table 3.10. To determine the
effect of low load on S02 emissions of C3 engines using fuel with a different sulfur level, Equation F.2
should be used with the actual fuel sulfur level for fractional engine loads between 0.02 and 0.2.
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Appendix G Default Harbor Craft Vessel Characteristics and
Activity
Engine size, installed power, and operating hours are important data when calculating vessel activity.
Sections 4.3 and 4.4 discuss harbor craft vessel characteristics (which include engine size and installed
power) and activity (which includes operating hours), respectively. If these vessel characteristics and
activity data are unavailable from local data sources, defaults by ship type and engine group (propulsion
or auxiliary) for the following data fields can be used instead:
• Average rated engine size (kW)
• Average installed power (kW)
• Average engine operating hours (hours)
These defaults are based on data collected by Starcrest for the averages of harbor craft operating at the
Port of Los Angeles,57 Port of Long Beach,58 in the Puget Sound,59 and at Port Everglades.60 While these
defaults can be used if local data are unavailable, they have the limitation that they do not reflect local
conditions, which likely impact vessel operation.
Table G.l. Default Harbor Craft Engine Sizes and Annual Activity
Ship Type
Average
Propulsion
Engine Size
(kW)
Average
Installed
Propulsion
Power (kW)
Average
Propulsion
Engine Hours
Average
Auxiliary
Engine Size
(kW)
Average
Installed
Auxiliary
Power (kW)
Average
Auxiliary
Engine Hours
Barge
-
-
-
171
622
581
Crew and
Supply
427
1,037
747
42
50
766
Excursion
283
513
1,038
30
24
1,268
Fishing
(C1/C2)
520
909
170
224
186
139
Government
724
1,343
423
502
389
251
Harbor Ferry
(C1/C2)
1,516
3,658
3,329
201
419
1,865
Misc. (C1/C2)
735
1,309
799
168
205
802
Pilot
606
1,211
1,344
14
28
137
Towboat /
Pushboat
846
1,559
864
68
97
1,137
Tug Boat
1,720
3,512
1,683
126
285
1,404
Work Boat
283
464
753
46
36
732
The above references do not include estimates for dredging vessels. As with the other vessel types, if
local data on engine type, size, and hours of operation are available for dredging vessels, these data
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
166
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Appendix G. Default Harbor Craft Vessel Characteristics and Activity
2020 Public Draft
should be used in conjunction with the appropriate emission factors for the engines present. That is,
propulsion and auxiliary engines should be assigned the appropriate Category 1 or Category 2 emission
factors (see Appendix H), and the dredging equipment should be assigned the appropriate emission
factors from MOVES-Nonroad (see Section 6). If local load factors are not available for the engines
present on dredging vessels, an average value of 0.66 can be used for all engines (propulsion, auxiliary,
and dredging).36
If local data on engine type and size for dredging vessels are unavailable, average total power ratings by
dredging vessel type can be used, as listed in Table G.2.61
Table G.2. Power Rating for Dredging Vessels by Dredging Type
Dredging Type
Total Power Rating (kW)
Bucket or mechanical
1,600
Hopper
7,272
Non-conventional (Specialty)
2,093
Pipeline (Cutterhead)
7,161
Pipeline and Hopper Combination
4,080
Undefined (Average)
5,028
Note that the power ratings in Table G.2 are sum totals of all engines on dredging vessels, including
propulsion engine(s) if present and dredging equipment engines. Since these defaults are for a
combination of different engines, the average emission factors for this sector should be used, as
presented in Appendix H, specifically Table H.6.
If hours of operation for dredging vessels are unknown, they can be estimated from the length of the
project (measured in days) and assuming that the vessels are operating 21.6 hours per day (i.e.,
operating 90% of the time).61
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Appendix H Tables of CI and C2 Emission Factors
2020 Public Draft
This appendix contains tables of Category 1 and 2 (CI and C2, respectively) emission factors for U.S.
flagged ships, which are from EPA's 2008 C1/C2 Regulatory Impact Analysis (RIA),13 unless otherwise
noted. These emission factors are further discussed in Section 4.5. Note that these emission factors
apply to engines on vessels with CI and C2 propulsion engines, regardless if the vessel is considered to
be an OGV or harbor craft. Emission factors for vessels with C3 propulsion engines are presented in
Section 3.5, and emissions for recreational marine and marine engines fueled by gasoline are discussed
in Section 5.
These emission factors for each pollutant of concern should be multiplied by the corresponding relevant
activity measurement in kilowatt-hours. This appendix contains the following detailed tables, which
present emission factors by engine category, group, cylinder displacement, engine power, and model
year:
• Table H.l. Category 1 and 2 NOx Emission Factors (g/kWh)
• Table H.2. Category 1 and 2 PM ULSD Emission Factors (g/kWh)
• Table H.3. Category 1 and 2 Base PMio Emission Factors for Other Diesel Fuels (g/kWh)
• Table H.4. Category 1 and 2 HC, VOC, and CH4 Emission Factors (g/kWh)
• Table H.5. Category 1 and 2 CO Emission Factors (g/kWh)
If cylinder displacement and power range are unknown, average emission factors by engine tier are
presented in Table H.6.
H.l Nitrogen Oxides (NOx)
NOx emission factors vary by engine category, group, cylinder displacement, engine power, and model
year. Emission factors for CI and C2 NOx are presented in Table H.l.
Table H.l. Category 1 and 2 NOx Emission Factors (g/kWh)
Engine
Category
Engine Group
Cylinder
Displacement Range
(L/cyl)
Power Range
Model Year
Range
NOx (g/kWh)
Uncontrolled
0 < kW < 8
Pre-2000
13.41
All
All
8 < kW < 19
Pre-2000
11.40
19 < kW < 37
Pre-1999
9.25
Disp < 0.9
kW > 37
Pre-2004
10.00
CI
0.9 < Disp < 1.2
kW > 37
Pre-2004
10.00
Propulsion
1.2 < Disp < 2.5
kW > 37
Pre-2004
10.00
2.5 < Disp < 3.5
kW > 37
Pre-2004
10.00
3.5 < Disp < 5
kW > 37
Pre-2004
11.00
Auxiliary
Disp < 0.9
kW > 37
Pre-2004
11.00
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine Group
Cylinder
Displacement Range
(L/cyl)
Power Range
Model Year
Range
NOx (g/kWh)
0.9 < Disp < 1.2
kW > 37
Pre-2004
10.00
1.2 < Disp < 2.5
kW > 37
Pre-2004
10.00
2.5 < Disp < 3.5
kW > 37
Pre-2004
10.00
3.5 < Disp < 5
kW > 37
Pre-2004
11.00
C2
All
5 < Disp < 30
All
Pre-2004
13.36
Tier 1
0 < kW < 8
2000-2004
7.01
All
All
8 < kW < 19
2000-2004
5.95
19 < kW < 37
1999-2003
6.34
Disp < 0.9
kW > 37
2004
9.80
CI
Propulsion
2.5 < Disp < 3.5
kW > 37
2004-2006
9.10
3.5 < Disp < 5
kW > 37
2004-2006
9.20
Disp < 0.9
kW > 37
2004
9.80
Auxiliary
2.5 < Disp < 3.5
kW > 37
2004-2006
9.10
3.5 < Disp < 5
kW > 37
2004-2006
9.20
C2
All
5 < Disp < 30
All
2004-2006
10.55
Tier 2
0 < kW < 8
2005-2008
5.89
All
All
8 < kW < 19
2005-2008
4.87
19 < kW < 37
2004-2008
4.98
Disp < 0.9
37 < kW < 75
2005-2008
5.70
75 < kW < 600
2005-2011
5.70
Propulsion
0.9 < Disp < 1.2
kW > 37
2004-2012
6.10
1.2 < Disp < 2.5
kW > 37
2004-2013
6.00
CI
2.5 < Disp < 3.5
kW > 37
2007-2012
6.00
3.5 < Disp < 5
kW > 37
2007-2011
6.00
Disp < 0.9
37 < kW < 75
2005-2008
5.70
75 < kW < 600
2005-2011
5.70
Auxiliary
0.9 < Disp < 1.2
kW > 37
2004-2012
5.40
1.2 < Disp < 2.5
kW > 37
2004-2013
6.10
2.5 < Disp < 3.5
kW > 37
2007-2012
6.10
3.5 < Disp < 5
kW > 37
2007-2011
6.10
C2
All
5 < Disp < 15
All
2007-2012
8.33
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 169
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine Group
Cylinder
Displacement Range
(L/cyl)
Power Range
Model Year
Range
NOx (g/kWh)
15 < Disp < 30
All
2007-2013
8.33
Tier 3
0 < kW < 8
2009+
4.39
8 < kW < 19
2009-2013
3.63
All
All
8 < kW < 19
2014+
2.32
19 < kW < 37
2009-2013
3.71
19 < kW < 37
2014+
2.32
37 < kW < 75
2009-2013
5.7
Disp < 0.9
37 < kW < 75
2014+
3.56
75 < kW < 600
2012+
4.08
0.9 < Disp < 1.2
kW < 600
2013+
4.54
1.2 < Disp < 2.5
kW < 600
2014+
4.69
2.5 < Disp < 3.5
kW < 600
2013+
4.69
Propulsion
3.5 < Disp < 7
kW < 600
2012+
4.81
1.2 < Disp < 2.5
600 < kW < 1000
2014-2017
4.69
2.5 < Disp < 3.5
600 < kW < 1000
2013-2017
4.69
3.5 < Disp < 7
600 < kW < 1000
2012-2017
4.81
CI
1.2 < Disp < 2.5
1000 < kW < 1400
2014-2016
4.69
2.5 < Disp < 3.5
1000 < kW < 1400
2013-2016
4.69
3.5 < Disp < 7
1000 < kW < 1400
2012-2016
4.81
kW > 1400
2012-2015
4.81
37 < kW < 75
2009-2013
5.70
Disp < 0.9
37 < kW < 75
2014+
3.56
75 < kW < 600
2012+
4.08
0.9 < Disp < 1.2
kW < 600
2013+
4.02
1.2 < Disp < 2.5
kW < 600
2014+
4.77
Auxiliary
2.5 < Disp < 3.5
kW < 600
2013+
4.77
3.5 < Disp < 7
kW < 600
2012+
4.89
1.2 < Disp < 2.5
600 < kW < 1000
2014-2017
4.77
2.5 < Disp < 3.5
600 < kW < 1000
2013-2017
4.77
3.5 < Disp < 7
600 < kW < 1000
2012-2017
4.89
2.5 < Disp < 3.5
1000 < kW < 1400
2013-2016
4.77
3.5 < Disp < 7
1000 < kW < 1400
2012-2016
4.89
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 170
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine Group
Cylinder
Displacement Range
(L/cyl)
Power Range
Model Year
Range
NOx (g/kWh)
kW > 1400
2012-2015
4.89
C2
All
7 < Disp < 15
kW < 600
2013+
5.97
600 < kW < 1000
2013-2017
5.97
1000 < kW < 1400
2013-2016
5.97
1400 < kW < 2000
2013-2015
5.97
15 < Disp < 30
1400 < kW < 2000
2014-2015
6.77
Tier 4
CI
Propulsion
1.2 < Disp < 2.5
600 < kW < 1000
2018+
1.30
2.5 < Disp < 3.5
600 < kW < 1000
2018+
1.30
3.5 < Disp < 7
600 < kW < 1000
2018+
1.30
1.2 < Disp < 2.5
1000 < kW < 1400
2017+
1.30
2.5 < Disp < 3.5
1000 < kW < 1400
2017+
1.30
3.5 < Disp < 7
1000 < kW < 1400
2017+
1.30
kW > 1400
2016+
1.30
Auxiliary
1.2 < Disp < 2.5
600 < kW < 1000
2018+
1.30
2.5 < Disp < 3.5
600 < kW < 1000
2018+
1.30
3.5 < Disp < 7
600 < kW < 1000
2018+
1.30
2.5 < Disp < 3.5
1000 < kW < 1400
2017+
1.30
3.5 < Disp < 7
1000 < kW < 1400
2017+
1.30
kW > 1400
2016+
1.30
C2
All
7 < Disp < 15
600 < kW < 1000
2018+
1.30
1000 < kW < 1400
2017+
1.30
1400 < kW < 2000
2016+
1.30
2000 < kW < 3700
2014+
1.30
kW > 3700
2014-2016
1.30
kW > 3700
2017+
1.30
15 < Disp < 30
1400 < kW < 2000
2016+
1.30
2000 < kW < 3700
2014+
1.30
kW > 3700
2014-2016
1.30
kW > 3700
2017+
1.30
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
171
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
H.2 Particulate Matter (PM), Diesel Particulate Matter (DPM), and Black Carbon (BC)
PM emission factors vary by engine category, group, cylinder displacement, engine power, and model
year. They also vary by fuel sulfur content. For inventories of 2012 activity and later, all CI and C2
marine engines can be assumed to be using ultra low sulfur diesel (ULSD), and the corresponding
emission factors are presented in Section H.2.1. Emission factors for engines using other fuels are
presented in Section H.2.2.
H.2.1 ULSD
PM emission factors for engines using ULSD are presented in Table H.2. The PMio and PM2.5 values were
derived from the 2008 C1/C2 RIA; however, the emission factors for uncontrolled engines as well as Tier
1 and 2 engines were adjusted to reflect the use of ULSD.a b
Table H.2. Category 1 and 2 PM ULSD Emission Factors (g/kWh)
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
PM10 &
DPM10
(g/kWh)
PM2.5 &
DPM2.5
(g/kWh)
BC
(g/kWh)
Uncontrolled
0 < kW < 8
Pre-2000
1.213
1.1764
0.9058
All
All
8 < kW < 19
Pre-2000
1.079
1.0463
0.8057
19 < kW < 37
Pre-1999
0.945
0.9162
0.7055
Disp < 0.9
kW > 37
Pre-2004
0.430
0.4170
0.3211
0.9 < Disp < 1.2
kW > 37
Pre-2004
0.360
0.3491
0.2688
Propulsion
1.2 < Disp < 2.5
kW > 37
Pre-2004
0.230
0.2230
0.1717
CI
2.5 < Disp < 3.5
kW > 37
Pre-2004
0.190
0.1842
0.1419
3.5 < Disp < 5
kW > 37
Pre-2004
0.190
0.1842
0.1419
Disp < 0.9
kW > 37
Pre-2004
0.730
0.7080
0.5452
0.9 < Disp < 1.2
kW > 37
Pre-2004
0.420
0.4073
0.3137
Auxiliary
1.2 < Disp < 2.5
kW > 37
Pre-2004
0.230
0.2230
0.1717
2.5 < Disp < 3.5
kW > 37
Pre-2004
0.210
0.2036
0.1568
3.5 < Disp < 5
kW > 37
Pre-2004
0.190
0.1842
0.1419
C2
All
5 < Disp < 30
All
Pre-2004
0.210
0.2036
0.1568
a Base PM10 emission factors were calculated from the PM10 emission factors in the 2008 C1/C2 RIA to reflect
theoretical emissions from using sulfur-free fuel (presented in Table H.3), using the methodology described in
reference 26. Adjusted PM10 emission factors for 15 ppm sulfur fuel were then calculated according to Equation
H.l in Section H.2.2.
b BC emission factors are estimated to be 77% of PM2.5 emission factors, based on reference 27.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
172
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
PMio &
DPMio
(g/kWh)
PM2.5 &
DPM2.5
(g/kWh)
BC
(g/kWh)
Tier 1
0 < kW < 8
2000-2004
0.475
0.4610
0.3549
All
All
8 < kW < 19
2000-2004
0.234
0.2268
0.1747
19 < kW < 37
1999-2003
0.328
0.3179
0.2448
Disp < 0.9
kW > 37
2004
0.430
0.4170
0.3211
CI
Propulsion
2.5 < Disp < 3.5
kW > 37
2004-2006
0.190
0.1842
0.1419
3.5 < Disp < 5
kW > 37
2004-2006
0.190
0.1842
0.1419
Disp < 0.9
kW > 37
2004
0.730
0.7080
0.5452
Auxiliary
2.5 < Disp < 3.5
kW > 37
2004-2006
0.210
0.2036
0.1568
3.5 < Disp < 5
kW > 37
2004-2006
0.190
0.1842
0.1419
C2
All
5 < Disp < 30
All
2004-2006
0.210
0.2036
0.1568
Tier 2
0 < kW < 8
2005-2008
0.497
0.4816
0.3708
All
All
8 < kW < 19
2005-2008
0.242
0.2345
0.1805
19 < kW < 37
2004-2008
0.295
0.2865
0.2206
Disp < 0.9
37 < kW < 75
2005-2008
0.219
0.2122
0.1634
75 < kW < 600
2005-2011
0.219
0.2122
0.1634
Propulsion
0.9 < Disp < 1.2
kW > 37
2004-2012
0.109
0.1055
0.0812
1.2 < Disp < 2.5
kW > 37
2004-2013
0.119
0.1152
0.0887
CI
2.5 < Disp < 3.5
kW > 37
2007-2012
0.119
0.1152
0.0887
3.5 < Disp < 5
kW > 37
2007-2011
0.119
0.1152
0.0887
Disp < 0.9
37 < kW < 75
2005-2008
0.219
0.2122
0.1634
75 < kW < 600
2005-2011
0.219
0.2122
0.1634
Auxiliary
0.9 < Disp < 1.2
kW > 37
2004-2012
0.199
0.1928
0.1485
1.2 < Disp < 2.5
kW > 37
2004-2013
0.139
0.1346
0.1037
2.5 < Disp < 3.5
kW > 37
2007-2012
0.139
0.1346
0.1037
3.5 < Disp < 5
kW > 37
2007-2011
0.139
0.1346
0.1037
C2
All
5 < Disp < 15
All
2007-2012
0.309
0.2995
0.2306
15 < Disp < 30
All
2007-2013
0.309
0.2995
0.2306
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 173
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
PMio &
DPMio
(g/kWh)
PM2.5 &
DPM2.5
(g/kWh)
BC
(g/kWh)
Tier 3
0 < kW < 8
2009+
0.240
0.2328
0.1793
All
All
19 < kW < 37
2009-2013
0.180
0.1746
0.1344
19 < kW < 37
2009+
0.180
0.1746
0.1344
Disp < 0.9
37 < kW < 75
2009+
0.170
0.1649
0.1270
75 < kW < 600
2012+
0.080
0.0776
0.0598
0.9 < Disp < 1.2
kW < 600
2013+
0.050
0.0485
0.0373
1.2 < Disp < 2.5
kW < 600
2014-2017
0.070
0.0679
0.0523
kW < 600
2018+
0.061
0.0592
0.0456
2.5 < Disp < 3.5
kW < 600
2013-2017
0.070
0.0679
0.0523
kW < 600
2018+
0.061
0.0592
0.0456
3.5 < Disp < 7
kW < 600
2012-2017
0.070
0.0679
0.0523
kW < 600
2018+
0.061
0.0592
0.0456
Propulsion
1.2 < Disp < 2.5
600 < kW <
1000
2014-2017
0.070
0.0679
0.0523
2.5 < Disp < 3.5
600 < kW <
1000
2013-2017
0.070
0.0679
0.0523
CI
3.5 < Disp < 7
600 < kW <
1000
2012-2017
0.070
0.0679
0.0523
1.2 < Disp < 2.5
1000 < kW <
1400
2014-2016
0.070
0.0679
0.0523
2.5 < Disp < 3.5
1000 < kW <
1400
2013-2016
0.070
0.0679
0.0523
3.5 < Disp < 7
1000 < kW <
1400
2012-2016
0.070
0.0679
0.0523
kW > 1400
2012-2015
0.070
0.0679
0.0523
Disp < 0.9
37 < kW < 75
2009+
0.170
0.1649
0.1270
75 < kW < 600
2012+
0.080
0.0776
0.0598
0.9 < Disp < 1.2
kW < 600
2013+
0.080
0.0776
0.0598
Auxiliary
1.2 < Disp < 2.5
kW < 600
2014-2017
0.080
0.0776
0.0598
kW < 600
2018+
0.070
0.0679
0.0523
2.5 < Disp < 3.5
kW < 600
2013-2017
0.080
0.0776
0.0598
kW < 600
2018+
0.070
0.0679
0.0523
3.5 < Disp < 7
kW < 600
2012-2017
0.080
0.0776
0.0598
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 174
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
PMio &
DPMio
(g/kWh)
PM2.5 &
DPM2.5
(g/kWh)
BC
(g/kWh)
kW < 600
2018+
0.070
0.0679
0.0523
1.2 < Disp < 2.5
600 < kW <
1000
2014-2017
0.080
0.0776
0.0598
2.5 < Disp < 3.5
600 < kW <
1000
2013-2017
0.080
0.0776
0.0598
3.5 < Disp < 7
600 < kW <
1000
2012-2017
0.080
0.0776
0.0598
2.5 < Disp < 3.5
1000 < kW <
1400
2013-2016
0.080
0.0776
0.0598
3.5 < Disp < 7
1000 < kW <
1400
2012-2016
0.080
0.0776
0.0598
kW > 1400
2012-2015
0.080
0.0776
0.0598
C2
All
7 < Disp < 15
kW < 600
2013+
0.110
0.1067
0.0822
600 < kW <
1000
2013-2017
0.110
0.1067
0.0822
1000 < kW <
1400
2013-2016
0.110
0.1067
0.0822
1400 < kW <
2000
2013-2015
0.110
0.1067
0.0822
2000 < kW <
3700
2013-2015
0.110
0.1067
0.0822
15 < Disp < 30
1400 < kW <
2000
2014-2015
0.300
0.2910
0.2241
2000 < kW <
3700
2014-2015
0.300
0.2910
0.2241
Tier 4
CI
Propulsion
1.2 < Disp < 2.5
600 < kW <
1000
2018+
0.030
0.0291
0.0224
2.5 < Disp < 3.5
600 < kW <
1000
2018+
0.030
0.0291
0.0224
3.5 < Disp < 7
600 < kW <
1000
2018+
0.030
0.0291
0.0224
1.2 < Disp < 2.5
1000 < kW <
1400
2017+
0.030
0.0291
0.0224
2.5 < Disp < 3.5
1000 < kW <
1400
2017+
0.030
0.0291
0.0224
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
175
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
PMio &
DPMio
(g/kWh)
PM2.5 &
DPM2.5
(g/kWh)
BC
(g/kWh)
3.5 < Disp < 7
1000 < kw <
1400
2017+
0.030
0.0291
0.0224
kW > 1400
2016+
0.030
0.0291
0.0224
1.2 < Disp < 2.5
600 < kW <
1000
2018+
0.030
0.0291
0.0224
2.5 < Disp < 3.5
600 < kW <
1000
2018+
0.030
0.0291
0.0224
Auxiliary
3.5 < Disp < 7
600 < kW <
1000
2018+
0.030
0.0291
0.0224
2.5 < Disp < 3.5
1000 < kW <
1400
2017+
0.030
0.0291
0.0224
3.5 < Disp < 7
1000 < kW <
1400
2017+
0.030
0.0291
0.0224
kW > 1400
2016+
0.030
0.0291
0.0224
600 < kW <
1000
2018+
0.030
0.0291
0.0224
1000 < kW <
1400
2017+
0.030
0.0291
0.0224
7 < Disp < 15
1400 < kW <
2000
2016+
0.030
0.0291
0.0224
2000 < kW <
3700
2016+
0.030
0.0291
0.0224
C2
All
kW > 3700
2014-2016
0.100
0.0970
0.0747
kW > 3700
2017+
0.040
0.0388
0.0299
1400 < kW <
2000
2016+
0.040
0.0388
0.0299
15 < Disp < 30
2000 < kW <
3700
2016+
0.040
0.0388
0.0299
kW > 3700
2014-2016
0.230
0.2231
0.1718
kW > 3700
2017+
0.050
0.0485
0.0373
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 176
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
H.2.2 Other Diesel Fuels
For engines using diesel fuel with a different sulfur level than ULSD, PMio and DPMio emission factors for
uncontrolled engines and Tiers 1 and 2 should be calculated according to Equation H.l:26 c
EFPMw = PMbase + (Sact x BSFC x FSC x MWR) Equation H.l
Where EFPMiq = PM io and DPMio emission factor adjusted for fuel sulfur (g/kWh)
PMbase = Base emission factor assuming zero fuel sulfur as listed in Table H.3 (g/kWh)
Sact = actual fuel sulfur level (weight ratio)
= e.g., 0.0005 for 500 ppm sulfur fuel
BSFC = brake specific fuel consumption13
= 248 g/kWh for vessels with power range less than 37 kW
= 213 g/kWh for vessels with power range of 37 kW or more
FSC = fraction of sulfur in fuel that is converted to direct sulfate PM13
= 0.02247
MWR = molecular weight ratio of sulfate PM to sulfur
= 224/32 = 7
Similar to the analysis performed for the 2017 NEI for C3 PM emissions, base PMio emission factors were
calculated from the PMio emission factors in the 2008 C1/C2 RIA to reflect theoretical emissions from
using sulfur-free fuel. These base PMio emission factors are presented in Table H.3.
PM2.5 emission factors are estimated to be 97% of the PMio emission factors.13 For all engines using
ULSD, DPM 10 and DPM2.5 emission factors are equal to the PMio and PM2.5 emission factors, respectively.
BC emission factors for CI and C2 engines are 77% of PM2.5 emission factors.27
Table H.3. Category 1 and 2 Base PMio Emission Factors for Other Diesel Fuels (g/kWh)
Engine
Category
Engine Group
Cylinder Displacement
Range (L/cyl)
Power Range
Model Year
Range
Base PMio
(g/kWh)
Uncontrolled
0 < kW < 8
Pre-2000
1.2122
All
All
8 < kW < 19
Pre-2000
1.0781
19 < kW < 37
Pre-1999
0.9440
Disp < 0.9
kW > 37
Pre-2004
0.4294
0.9 < Disp < 1.2
kW > 37
Pre-2004
0.3594
CI
Propulsion
1.2 < Disp < 2.5
kW > 37
Pre-2004
0.2294
2.5 < Disp < 3.5
kW > 37
Pre-2004
0.1894
3.5 < Disp < 5
kW > 37
Pre-2004
0.1894
Disp < 0.9
kW > 37
Pre-2004
0.7294
Auxiliary
0.9 < Disp < 1.2
kW > 37
Pre-2004
0.4194
1.2 < Disp < 2.5
kW > 37
Pre-2004
0.2294
c Emission factors for Tiers 3 and 4 are provided in Section H.2.1, as these vessels cannot use fuels with higher
sulfur levels than ULSD.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 177
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine Group
Cylinder Displacement
Range (L/cyl)
Power Range
Model Year
Range
Base PMio
(g/kWh)
2.5 < Disp < 3.5
kW > 37
Pre-2004
0.2094
3.5 < Disp < 5
kW > 37
Pre-2004
0.1894
C2
All
5 < Disp < 30
All
Pre-2004
0.2094
Tier 1
0 < kW < 8
2000-2004
0.4746
All
All
8 < kW < 19
2000-2004
0.2333
19 < kW < 37
1999-2003
0.3271
Disp < 0.9
kW > 37
2004
0.4294
CI
Propulsion
2.5 < Disp < 3.5
kW > 37
2004-2006
0.1894
3.5 < Disp < 5
kW > 37
2004-2006
0.1894
Disp < 0.9
kW > 37
2004
0.7294
Auxiliary
2.5 < Disp < 3.5
kW > 37
2004-2006
0.2094
3.5 < Disp < 5
kW > 37
2004-2006
0.1894
C2
All
5 < Disp < 30
All
2004-2006
0.2094
Tier 2
0 < kW < 8
2005-2008
0.4959
All
All
8 < kW < 19
2005-2008
0.2411
19 < kW < 37
2004-2008
0.2948
Disp < 0.9
37 < kW < 75
2005-2008
0.2183
75 < kW < 600
2005-2011
0.2183
Propulsion
0.9 < Disp < 1.2
kW > 37
2004-2012
0.1083
1.2 < Disp < 2.5
kW > 37
2004-2013
0.1183
CI
2.5 < Disp < 3.5
kW > 37
2007-2012
0.1183
3.5 < Disp < 5
kW > 37
2007-2011
0.1183
Disp < 0.9
37 < kW < 75
2005-2008
0.2183
75 < kW < 600
2005-2011
0.2183
Auxiliary
0.9 < Disp < 1.2
kW > 37
2004-2012
0.1983
1.2 < Disp < 2.5
kW > 37
2004-2013
0.1383
2.5 < Disp < 3.5
kW > 37
2007-2012
0.1383
3.5 < Disp < 5
kW > 37
2007-2011
0.1383
C2
All
5 < Disp < 15
All
2007-2012
0.3083
15 < Disp < 30
All
2007-2013
0.3083
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 178
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
H.3 Volatile Organic Compounds (VOC) and Methane (ChU)
Emission factors for VOC and CH4 vary by engine category, group, cylinder displacement, engine power,
and model year. Emission factors for CI and C2 hydrocarbons (HC), VOC, and CH4 are presented in Table
H.4.
Table H.4. Category 1 and 2 HC, VOC, and CH4 Emission Factors (g/kWh)
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
HC
(g/kWh)
VOC
(g/kWh)
ch4
(g/kWh)
Uncontrolled
0 < kW < 8
Pre-2000
2.012
2.1181
0.0402
All
All
8 < kW < 19
Pre-2000
2.280
2.4006
0.0456
19 < kW < 37
Pre-1999
2.414
2.5418
0.0483
Disp < 0.9
kW > 37
Pre-2004
0.410
0.4317
0.0082
0.9 < Disp < 1.2
kW > 37
Pre-2004
0.320
0.3370
0.0064
Propulsion
1.2 < Disp < 2.5
kW > 37
Pre-2004
0.270
0.2843
0.0054
CI
2.5 < Disp < 3.5
kW > 37
Pre-2004
0.270
0.2843
0.0054
3.5 < Disp < 5
kW > 37
Pre-2004
0.270
0.2843
0.0054
Disp < 0.9
kW > 37
Pre-2004
0.410
0.4317
0.0082
0.9 < Disp < 1.2
kW > 37
Pre-2004
0.320
0.3370
0.0064
Auxiliary
1.2 < Disp < 2.5
kW > 37
Pre-2004
0.270
0.2843
0.0054
2.5 < Disp < 3.5
kW > 37
Pre-2004
0.270
0.2843
0.0054
3.5 < Disp < 5
kW > 37
Pre-2004
0.270
0.2843
0.0054
C2
All
5 < Disp < 30
All
Pre-2004
0.134
0.1411
0.0027
Tier 1
0 < kW < 8
2000-2004
1.019
1.0732
0.0204
All
All
8 < kW < 19
2000-2004
0.590
0.6213
0.0118
19 < kW < 37
1999-2003
0.375
0.3954
0.0075
Disp < 0.9
kW > 37
2004
0.410
0.4317
0.0082
CI
Propulsion
2.5 < Disp < 3.5
kW > 37
2000-2006
0.270
0.2843
0.0054
3.5 < Disp < 5
kW > 37
2000-2006
0.270
0.2843
0.0054
Disp < 0.9
kW > 37
2004
0.410
0.4317
0.0082
Auxiliary
2.5 < Disp < 3.5
kW > 37
2004-2006
0.270
0.2843
0.0054
3.5 < Disp < 5
kW > 37
2004-2006
0.270
0.2843
0.0054
C2
All
5 < Disp < 30
All
2004-2006
0.134
0.1411
0.0027
Tier 2
CI
All
All
0 < kW < 8
2005-2008
0.912
0.9602
0.0182
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
179
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
HC
(g/kWh)
voc
(g/kWh)
ch4
(g/kWh)
8 < kW < 19
2005-2008
0.282
0.2965
0.0056
19 < kW < 37
2004-2008
0.724
0.7625
0.0145
Disp < 0.9
37 < kW < 75
2005-2008
0.410
0.4317
0.0082
75 < kW < 600
2005-2011
0.410
0.4317
0.0082
Propulsion
0.9 < Disp < 1.2
kW > 37
2004-2012
0.320
0.3370
0.0064
1.2 < Disp < 2.5
kW > 37
2004-2013
0.190
0.2001
0.0038
2.5 < Disp < 3.5
kW > 37
2007-2012
0.190
0.2001
0.0038
3.5 < Disp < 5
kW > 37
2007-2011
0.190
0.2001
0.0038
Disp < 0.9
37 < kW < 75
2005-2008
0.410
0.4317
0.0082
75 < kW < 600
2005-2011
0.410
0.4317
0.0082
Auxiliary
0.9 < Disp < 1.2
kW > 37
2004-2012
0.320
0.3370
0.0064
1.2 < Disp < 2.5
kW > 37
2004-2013
0.210
0.2211
0.0042
2.5 < Disp < 3.5
kW > 37
2007-2012
0.210
0.2211
0.0042
3.5 < Disp < 5
kW > 37
2007-2011
0.210
0.2211
0.0042
C2
All
5 < Disp < 15
All
2007-2012
0.134
0.1411
0.0027
15 < Disp < 30
All
2007-2013
0.134
0.1411
0.0027
Tier 3
0 < kW < 8
2009+
0.430
0.4528
0.0086
CI
All
All
8 < kW < 19
2009+
0.210
0.2211
0.0042
19 < kW < 37
2009+
0.410
0.4317
0.0082
Disp < 0.9
37 < kW < 75
2009+
0.300
0.3159
0.0060
75 < kW < 600
2012+
0.140
0.1474
0.0028
0.9 < Disp < 1.2
kW < 600
2013+
0.130
0.1369
0.0026
1.2 < Disp < 2.5
kW < 600
2014+
0.100
0.1053
0.0020
2.5 < Disp < 3.5
kW < 600
2013+
0.100
0.1053
0.0020
3.5 < Disp < 7
kW < 600
2012+
0.100
0.1053
0.0020
CI
Propulsion
1.2 < Disp < 2.5
600 < kW <
1000
2014-2017
0.100
0.1053
0.0020
2.5 < Disp < 3.5
600 < kW <
1000
2013-2017
0.100
0.1053
0.0020
3.5 < Disp < 7
600 < kW <
1000
2012-2017
0.100
0.1053
0.0020
1.2 < Disp < 2.5
1000 < kW <
1400
2014-2016
0.100
0.1053
0.0020
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 180
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
HC
(g/kWh)
voc
(g/kWh)
ch4
(g/kWh)
2.5 < Disp < 3.5
1000 < kw <
1400
2013-2016
0.100
0.1053
0.0020
3.5 < Disp < 7
1000 < kW <
1400
2012-2016
0.100
0.1053
0.0020
kW > 1400
2012-2015
0.100
0.1053
0.0020
Auxiliary
Disp < 0.9
37 < kW < 75
2009+
0.300
0.3159
0.0060
75 < kW < 600
2012+
0.140
0.1474
0.0028
0.9 < Disp < 1.2
kW < 600
2013+
0.130
0.1369
0.0026
1.2 < Disp < 2.5
kW < 600
2014+
0.110
0.1158
0.0022
2.5 < Disp < 3.5
kW < 600
2013+
0.110
0.1158
0.0022
3.5 < Disp < 7
kW < 600
2012+
0.110
0.1158
0.0022
1.2 < Disp < 2.5
600 < kW <
1000
2014-2017
0.110
0.1158
0.0022
2.5 < Disp < 3.5
600 < kW <
1000
2013-2017
0.110
0.1158
0.0022
3.5 < Disp < 7
600 < kW <
1000
2012-2017
0.110
0.1158
0.0022
2.5 < Disp < 3.5
1000 < kW <
1400
2013-2016
0.110
0.1158
0.0022
3.5 < Disp < 7
1000 < kW <
1400
2012-2016
0.110
0.1158
0.0022
kW > 1400
2012-2015
0.110
0.1158
0.0022
C2
All
7 < Disp < 15
kW < 600
2013+
0.070
0.0737
0.0014
600 < kW <
1000
2013-2017
0.070
0.0737
0.0014
1000 < kW <
1400
2013-2016
0.070
0.0737
0.0014
1400 < kW <
2000
2013-2015
0.070
0.0737
0.0014
15 < Disp < 30
1400 < kW <
2000
2014-2015
0.090
0.0948
0.0018
Tier 4
CI
Propulsion
1.2 < Disp < 2.5
600 < kW <
1000
2018+
0.040
0.0421
0.0008
2.5 < Disp < 3.5
600 < kW <
1000
2018+
0.040
0.0421
0.0008
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
181
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine
Group
Cylinder
Displacement
Range (L/cyl)
Power Range
Model Year
Range
HC
(g/kWh)
voc
(g/kWh)
ch4
(g/kWh)
3.5 < Disp < 7
600 < kW <
1000
2018+
0.040
0.0421
0.0008
1.2 < Disp < 2.5
1000 < kW <
1400
2017+
0.040
0.0421
0.0008
2.5 < Disp < 3.5
1000 < kW <
1400
2017+
0.040
0.0421
0.0008
3.5 < Disp < 7
1000 < kW <
1400
2017+
0.040
0.0421
0.0008
3.5 < Disp < 7
kW > 1400
2016+
0.040
0.0421
0.0008
1.2 < Disp < 2.5
600 < kW <
1000
2018+
0.040
0.0421
0.0008
2.5 < Disp < 3.5
600 < kW <
1000
2018+
0.040
0.0421
0.0008
Auxiliary
3.5 < Disp < 7
600 < kW <
1000
2018+
0.040
0.0421
0.0008
2.5 < Disp < 3.5
1000 < kW <
1400
2017+
0.040
0.0421
0.0008
3.5 < Disp < 7
1000 < kW <
1400
2017+
0.040
0.0421
0.0008
kW > 1400
2016+
0.040
0.0421
0.0008
600 < kW <
1000
2018+
0.020
0.0211
0.0004
1000 < kW <
1400
2017+
0.020
0.0211
0.0004
7 < Disp < 15
1400 < kW <
2000
2016+
0.020
0.0211
0.0004
2000 < kW <
3700
2014+
0.020
0.0211
0.0004
C2
All
kW > 3700
2014-2016
0.060
0.0632
0.0012
2017+
0.030
0.0316
0.0006
1400 < kW <
2000
2016+
0.010
0.0105
0.0002
15 < Disp < 30
2000 < kW <
3700
2014+
0.010
0.0105
0.0002
kW > 3700
2014-2016
0.070
0.0737
0.0014
2017+
0.010
0.0105
0.0002
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 182
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
H.4 Carbon Monoxide (CO)
CO emission factors vary by engine category, group, cylinder displacement, engine power, and model
year. Emission factors for CI and C2 CO are presented in Table H.5. Note that unlike other pollutants
listed in this appendix, the emission factors for CO do not change after Tier 2.
Table H.5. Category 1 and 2 CO Emission Factors (g/kWh)
Engine
Category
Engine Group
Cylinder
Displacement Range
(L/cyl)
Power Range
Model Year
Range
CO (g/kWh)
Uncontrolled
0 < kW < 8
Pre-2000
5.00
All
All
8 < kW < 19
Pre-2000
5.00
19 < kW < 37
Pre-1999
5.00
Disp < 0.9
kW > 37
Pre-2004
1.60
0.9 < Disp < 1.2
kW > 37
Pre-2004
1.60
Propulsion
1.2 < Disp < 2.5
kW > 37
Pre-2004
1.60
CI
2.5 < Disp < 3.5
kW > 37
Pre-2004
1.60
3.5 < Disp < 5
kW > 37
Pre-2004
1.80
Disp < 0.9
kW > 37
Pre-2004
2.00
0.9 < Disp < 1.2
kW > 37
Pre-2004
1.70
Auxiliary
1.2 < Disp < 2.5
kW > 37
Pre-2004
1.50
2.5 < Disp < 3.5
kW > 37
Pre-2004
1.50
3.5 < Disp < 5
kW > 37
Pre-2004
1.80
C2
All
5 < Disp < 30
All
Pre-2004
2.48
Tier 1
0 < kW < 8
2000-2004
4.11
All
All
8 < kW < 19
2000-2004
2.16
19 < kW < 37
1999-2003
1.53
Disp < 0.9
kW > 37
2004
1.60
CI
Propulsion
2.5 < Disp < 3.5
kW > 37
2000-2006
1.60
3.5 < Disp < 5
kW > 37
2000-2006
1.80
Disp < 0.9
kW > 37
2004
2.00
Auxiliary
2.5 < Disp < 3.5
kW > 37
2004-2006
1.50
3.5 < Disp < 5
kW > 37
2004-2006
1.80
C2
All
5 < Disp < 30
All
2004-2006
2.48
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
183
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
Engine
Category
Engine Group
Cylinder
Displacement Range
(L/cyl)
Power Range
Model Year
Range
CO (g/kWh)
Tier 2
0 < kW < 8
2005+
4.11
All
All
8 < kW < 19
2005+
2.16
19 < kW < 37
2004+
1.53
Disp < 0.9
kW > 37
2005+
1.60
0.9 < Disp < 1.2
kW > 37
2004+
0.90
Propulsion
1.2 < Disp < 2.5
kW > 37
2004+
1.10
CI
2.5 < Disp < 3.5
kW > 37
2007+
1.10
3.5 < Disp < 5
kW > 37
2007+
1.10
Disp < 0.9
kW > 37
2005+
1.60
0.9 < Disp < 1.2
kW > 37
2004+
0.80
Auxiliary
1.2 < Disp < 2.5
kW > 37
2004+
0.90
2.5 < Disp < 3.5
kW > 37
2007+
0.90
3.5 < Disp < 5
kW > 37
2007+
0.90
C2
All
5 < Disp < 30
All
2007+
2.00
Tier 3 and Tier 4
0 < kW < 8
2005+
4.11
All
All
8 < kW < 19
2005+
2.16
19 < kW < 37
2004+
1.53
Disp < 0.9
kW > 37
2005+
1.60
0.9 < Disp < 1.2
kW > 37
2004+
0.90
Propulsion
1.2 < Disp < 2.5
kW > 37
2004+
1.10
CI
2.5 < Disp < 3.5
kW > 37
2007+
1.10
3.5 < Disp < 7
kW > 37
2007+
1.10
Disp < 0.9
kW > 37
2005+
1.60
0.9 < Disp < 1.2
kW > 37
2004+
0.80
Auxiliary
1.2 < Disp < 2.5
kW > 37
2004+
0.90
2.5 < Disp < 3.5
kW > 37
2007+
0.90
3.5 < Disp < 7
kW > 37
2007+
0.90
C2
All
7 < Disp < 30
All
2007+
2.00
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 184
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Appendix H. Tables of CI and C2 Emission Factors
2020 Public Draft
H.5 Average Emission Factors
If cylinder displacement and power range are unknown, average emission factors by engine tier can be
used instead. The emission factors presented in Table H.6 are based on the detailed emission factors
described in Section 4.5 and presented above in this appendix, weighted by 2017 national CI and C2
vessel populations.62
Table H.6. Average Harbor Craft Emission Factors by Engine Tier
Tier
NOx
(g/kWh)
PMio
(g/kWh)
PMz.5
(g/kWh)
VOC
(g/kWh)
CO
(g/kWh)
C02
(g/kWh)
S02
(g/kWh)
Tier 0
10.28152
0.258902
0.251135
0.295615
1.612632
679.47
0.006246
Tier 1
9.624039
0.258902
0.251135
0.295615
1.61
679.47
0.006246
Tier 2
5.642273
0.148049
0.143608
0.295615
0.918732
679.47
0.006246
Tier 3
4.749214
0.082975
0.080486
0.124798
0.918732
679.47
0.006246
Tier 4
1.3
0.03
0.0291
0.124798
0.918732
679.47
0.006246
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
185
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U.S. Environmental Protection Agency 2020 Public Draft
Appendix I Additional Details for Calculating an Onroad
Inventory
This appendix provides additional details as a supplement to Section 7. Section 1.1 discusses the Project
Scale Refined Approach, which uses MOVES at the Project Scale to model a series of specific links that
represent specific locations at the port. This approach is more detailed than the Project Scale Generic
Link Approach (discussed in Section 7.6) and is applicable for port-related inventories intended to
support refined air quality modeling requiring geographically allocated emissions.
Additionally, a hypothetical example is provided in Section 1.2 to illustrate inputs for the Project Scale
Generic Link Approach.
1.1 Project Scale Refined Approach
The Project Scale Refined Approach uses MOVES at the Project Scale in Inventory calculation type, to
create a series of links that represent specific locations at the port. Activity on each specific link is
defined for a specific hour. In this approach, the MOVES user should include information about source
types, vehicle volumes, and activity on each link. As noted, this method provides a total inventory for
just one hour; additional runs would be needed to account for variation in activity over the course of a
year. These results would then be "scaled up" to develop an inventory that covers an entire year. This
approach is most appropriate for air quality dispersion modeling applications and is described in detail
in EPA's PM Hot-spot Guidance.41
For the refined approach, multiple MOVES Project Scale runs are needed to represent activity and
temperature differences over a 24-hour period, and activity, temperature, and fuel differences across
seasons of the year. Refer to Section 4.3 of the PM Hot-spot Guidance for more details on developing
representative hourly runs.3 The emissions results from these runs would then be applied to all hours of
the year in the air dispersion modeling step.
For the Project Scale Refined Inventory Approach, the output is emission mass quantities for the source
types present and activities occuring within the one-hour period. These mass quantities should be
multiplied by the number annual hours that the time span in the MOVES run represents (e.g., if the
hourly run represents an 8-hour peak period during a typical weekday at the port, the emission quantity
should be multiplied by 8 hrs x 5/7 days/week x 52 weeks). To produce a total annual inventory for a
given pollutant, this calculation should be performed for each link for each run and aggregated to
produce a total emission value.
1.2 Hypothetical Port Example
The following discussion provides a hypothetical example to illustrate how to estimate onroad emissions
for a port in an unspecified county. The example illustrates some of the Project Data Manager (PDM)
a Note, the minimum of 16 runs specified in the PM Hot-spot Guidance—representing four time periods of a day,
in each of four seasons—does not apply unless the emissions inventory is being conducted for hot-spot analysis
purposes.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
186
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Appendix I. Additional Details for Calculating an Onroad Inventory
2020 Public Draft
inputs for the Project Scale Generic Link Approach, detailed in Section 7, and how the results would be
post-processed to develop an onroad inventory. Note that this example involves a hypothetical port,
but the approach could be applicable for estimating emissions from a port-related onroad vehicle
corridor or other onroad goods movement activity.
1.2.1 Details of Hypothetical Port
For simplicity, the number of sources and types of activity at this hypothetical port have been limited:
• There are only three source types present: combination short-haul trucks (sourceTypelD 61) and
combination long-haul trucks (sourceTypelD 62) performing freight functions, and passenger
cars (sourceTypelD 21) that arrive and park on port.
• The default fuel splits between gasoline and diesel for combination short-haul trucks and
between gasoline, diesel, and E-85 for passenger cars are used. (MOVES can only model diesel
combination long-haul trucks.)
• The port has only four types of activity, listed in Table 1.1 below.
Table 1.1. Example Project Scale Generic Link Approach Activity Types
Activity Type
MOVES Link Example
Driving to and from the port
Running link with observed 25 mph average speed
Queuing and creeping activities at gates
Running link with observed 1.8 mph average speed
Drayage driving activities on port
Running link with observed 10 mph average speed
Vehicle starts
Off-network Link
• In this example, all vehicles (the three source types) have start activity while on port. Passenger
cars are parked for 12 or more hours before starting (opModelD 108), while combination short-
and long-haul trucks are parked approximately 15 minutes before starting (opModelD 102),
while queuing and loading.
• All running activity is on urban unrestricted roads (roadTypelD 5) with a 0 percent average road
grade.
1.2.2 PDM Tabs Inputs
Links: In the Generic Link Approach, each link has only one source type. For this example, the Link input
would include 9 links: 8 running links + 1 off-network link, and would look as follows in Table 1.2:
Table 1.2. Example Input for Link Table
Q
*
Q
>
*
0
01
d
Q)
Q.
>
|—
-C
•*-*
euo
c
Q)
Q)
£
3
O
"O
-------
Appendix I. Additional Details for Calculating an Onroad Inventory
2020 Public Draft
q
*
Q
>
zonelD*
Q
01
Q.
>.
linkLength
Ol
E
_3
linkAvgSpeed
£
O
'5
a.
LinkAvgGrade
c
c
3
O
u
1-
T3
(0
O
O
£
c
u
01
Q
c
4
5
1
1
25.0
Long-haul arterial
0
5
5
1
1
10.0
Long-haul on port
0
6
5
1
1
1.8
Long-haul queue
0
7
5
1
1
25.0
Car arterial
0
8
5
1
1
10.0
Car on port
0
9
1
0
3
0.0
Off-network
0
*The countylD and zonelD fields are populated based on selections made in the RunSpec.
Link 9 is the off-network link in this example. Note that unlike the other links, this link volume equals 3
to include the three source types (sourceTypelDs 21, 61, and 62) present in the example.
Link Source Type: This input applies to running links only. In the Generic Link Approach, each link is set
up with only one source type therefore the sourceTypeHourFraction is set to 1 (i.e., 100 percent). For
the example, the LinkSourceTypeHour table would look as follows in Table 1.3:
Table 1.3. Example Input for LinkSourceTypeHourTabie
linkID
sourceTypelD
sourceTypeHourFraction
1
61
1
2
61
1
3
61
1
4
62
1
5
62
1
6
62
1
7
21
1
8
21
1
Off-Network: This input describes the off-network link (see Table 1.4). For the Generic Link approach,
the user would indicate a vehicle population of 1 with 100 percent of the vehicles are starting during the
hour (i.e., startFraction is 1) to get a start emission rate per vehicle for each source type in the MOVES
output. No extended idling activity is assumed to occur on port, and therefore the last two columns
should be left blank.
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Appendix I. Additional Details for Calculating an Onroad Inventory 2020 Public Draft
Table 1.4. Example Input for OffNetworkLinkTabie
zonelD
sourceTypelD
vehiclePopulation
startFraction
extendedldleFraction
parkedVehicleFraction
21
1
1
61
1
1
62
1
1
*The zonelD field is populated based on selections made in the RunSpec.
Operating Mode Distribution: This input is needed for an off-network link to describe how long vehicles
have been soaking when they are started. The opModelD corresponds to the amount of soak time for
each source type in the analysis. The pollutantProcessID is a combination of the pollutantID and the
processlD. While any number of pollutants may be of interest, for the purposes of this method, the only
relevant process is "Start Exhaust/' processlD 02. In the example, nitrogen oxides (NOx), pollutantID 3,
is the pollutant of interest, so the polProcessID is 302. The example specifies that passenger cars are
parked for 12 or more hours (opModelD 108) while combination short- and long-haul trucks are parked
for 15 minutes (opModelD 102) while queuing and loading.
A completed OpModeDistribution input table for this example would look as follows in Table 1.5:
Table 1.5. Example Input for OpModeDistribution Table
sourceTypelD
hourDaylD*
linkID
polProcessID*
opModelD
opModeFraction
21
9
302
108
1
61
9
302
102
1
62
9
302
102
1
*The hourDaylD and polProcessID fields are populated based on selections made in the RunSpec.
1.2.3 Post-Processing Project Scale Output for Inventory Development
As discussed in Section 7.6.5, MOVES will produce a link-by-link emission mass for each pollutant, for the
hour specified within the RunSpec. The running links have emissions per mile and the off-network link
has emissions per start. These emission rates by pollutant would then be multiplied by the
corresponding vehicle activity. For purposes of illustration only, the hypothetical annual activity for
combination long-haul trucks (sourceTypelD 62) is:
• 2,000,000 VMT approaching/leaving the port;
• 250,000 VMT on port;
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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Appendix I. Additional Details for Calculating an Onroad Inventory
2020 Public Draft
• 500,000 hours of truck queuing activity, which includes the activity of idling and creeping at the
gate as well as other idling while the truck is at the port, such as idling while loading and
unloading; and
• 500,000 starts.
The total emissions of combination long-haul trucks would be calculated as:
Total emissions for sourceTypelD 62 = Link4 g/mi x (2,000,000 mi)
Link5 g/mi x (250,000 mi)
Link6 g/mi x (1.8 miles/hour) x (500,000 hr)
+ Link9 g/start for sourceTypelD 62 x (500,000 starts)
Total g for sourceTypelD 62
Emissions from the activity of each source type would need to be summed in a similar fashion and all of
them aggregated together for the total onroad inventory.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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U.S. Environmental Protection Agency 2020 Public Draft
Appendix J HAP Speciation Profiles for Locomotive Engines
Hazardous air pollutants (HAPs) are calculated from various basis pollutants. The basis emission factors
for diesel line-haul and switcher locomotives are given in Section 8.5.1. Emission factors for HAPs are
calculated by multiplying the appropriate basis emission factor by the fraction listed in Table J.l.63
Table J.l. HAP Speciation Profiles for Locomotive Engines
Pollutant
Pollutant
Code
Basis
Locomotive Type
Fraction
1,2,3,4,6,7,8-Heptachlorodibenzofuran
67562394
PM2.5
Line-haul (Class 1)
2.63351E-09
1,2,3,4,6,7,8-Heptachlorodibenzofuran
67562394
PM2.5
Line-haul (Class ll/lll)
2.30432E-09
1,2,3,4,6,7,8-Heptachlorodibenzofuran
67562394
PM2.5
Switcher
1.43217E-09
1,2,3,4,6,7,8-Heptachlorodibenzo-p-Dioxin
35822469
PM2.5
Line-haul (Class 1)
5.08608E-09
1,2,3,4,6,7,8-Heptachlorodibenzo-p-Dioxin
35822469
PM2.5
Line-haul (Class ll/lll)
4.45032E-09
1,2,3,4,6,7,8-Heptachlorodibenzo-p-Dioxin
35822469
PM2.5
Switcher
2.76596E-09
1,2,3,4,7,8-Hexachlorodibenzofuran
70648269
PM2.5
Line-haul (Class 1)
9.78351E-10
1,2,3,4,7,8-Hexachlorodibenzofuran
70648269
PM2.5
Line-haul (Class ll/lll)
8.56057E-10
1,2,3,4,7,8-Hexachlorodibenzofuran
70648269
PM2.5
Switcher
5.32055E-10
1,2,3,6,7,8-Hexachlorodibenzofuran
57117449
PM2.5
Line-haul (Class 1)
5.16649E-10
1,2,3,6,7,8-Hexachlorodibenzofuran
57117449
PM2.5
Line-haul (Class ll/lll)
4.52068E-10
1,2,3,6,7,8-Hexachlorodibenzofuran
57117449
PM2.5
Switcher
2.80969E-10
1,2,3,6,7,8-Hexachlorodibenzo-p-Dioxin
57653857
PM2.5
Line-haul (Class 1)
1.25979E-10
1,2,3,6,7,8-Hexachlorodibenzo-p-Dioxin
57653857
PM2.5
Line-haul (Class ll/lll)
1.10232E-10
1,2,3,6,7,8-Hexachlorodibenzo-p-Dioxin
57653857
PM2.5
Switcher
6.85111E-11
1,2,3,7,8,9-Hexachlorodibenzofuran
72918219
PM2.5
Line-haul (Class 1)
3.69227E-10
1,2,3,7,8,9-Hexachlorodibenzofuran
72918219
PM2.5
Line-haul (Class ll/lll)
3.23073E-10
1,2,3,7,8,9-Hexachlorodibenzofuran
72918219
PM2.5
Switcher
2.00796E-10
1,2,3,7,8,9-Hexachlorodibenzo-p-Dioxin
19408743
PM2.5
Line-haul (Class 1)
5.81649E-10
1,2,3,7,8,9-Hexachlorodibenzo-p-Dioxin
19408743
PM2.5
Line-haul (Class ll/lll)
5.08943E-10
1,2,3,7,8,9-Hexachlorodibenzo-p-Dioxin
19408743
PM2.5
Switcher
3.16317E-10
1,2,3,7,8-Pentachlorodibenzofuran
57117416
PM2.5
Line-haul (Class 1)
1.68866E-09
1,2,3,7,8-Pentachlorodibenzofuran
57117416
PM2.5
Line-haul (Class ll/lll)
1.47758E-09
1,2,3,7,8-Pentachlorodibenzofuran
57117416
PM2.5
Switcher
9.18341E-10
1,3-Butadiene
106990
voc
Line-haul (Class 1)
1.86000E-03
1,3-Butadiene
106990
voc
Line-haul (Class ll/lll)
1.86000E-03
1,3-Butadiene
106990
voc
Switcher
1.86000E-03
2,2,4-Trimethylpentane
540841
voc
Line-haul (Class 1)
7.12000E-03
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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Appendix J. HAP Speciation Profiles for Locomotive Engines
2020 Public Draft
Pollutant
Pollutant
Code
Basis
Locomotive Type
Fraction
2,2,4-Trimethylpentane
540841
voc
Line-haul (Class ll/lll)
7.12000E-03
2,2,4-Trimethylpentane
540841
voc
Switcher
7.12000E-03
2,3,4,7,8-Pentachlorodibenzofuran
57117314
PM2.5
Line-haul (Class 1)
2.70052E-09
2,3,4,7,8-Pentachlorodibenzofuran
57117314
PM2.5
Line-haul (Class ll/lll)
2.36295E-09
2,3,4,7,8-Pentachlorodibenzofuran
57117314
PM2.5
Switcher
1.46862E-09
2,3,7,8-Tetrachlorodibenzofuran
51207319
PM2.5
Line-haul (Class 1)
7.90722E-09
2,3,7,8-Tetrachlorodibenzofuran
51207319
PM2.5
Line-haul (Class ll/lll)
6.91881E-09
2,3,7,8-Tetrachlorodibenzofuran
51207319
PM2.5
Switcher
4.30017E-09
2,3,7,8-Tetrachlorodibenzo-p-Dioxin
1746016
PM2.5
Line-haul (Class 1)
2.70722E-10
2,3,7,8-Tetrachlorodibenzo-p-Dioxin
1746016
PM2.5
Line-haul (Class ll/lll)
2.36881E-10
2,3,7,8-Tetrachlorodibenzo-p-Dioxin
1746016
PM2.5
Switcher
1.47226E-10
Acenaphthene
83329
voc
Line-haul (Class 1)
3.79000E-04
Acenaphthene
83329
voc
Line-haul (Class ll/lll)
3.79000E-04
Acenaphthene
83329
voc
Switcher
3.79000E-04
Acenaphthylene
208968
voc
Line-haul (Class 1)
4.95000E-04
Acenaphthylene
208968
voc
Line-haul (Class ll/lll)
4.95000E-04
Acenaphthylene
208968
voc
Switcher
4.95000E-04
Acetaldehyde
75070
voc
Line-haul (Class 1)
7.83000E-02
Acetaldehyde
75070
voc
Line-haul (Class ll/lll)
7.83000E-02
Acetaldehyde
75070
voc
Switcher
7.83000E-02
Acrolein
107028
voc
Line-haul (Class 1)
1.60000E-02
Acrolein
107028
voc
Line-haul (Class ll/lll)
1.60000E-02
Acrolein
107028
voc
Switcher
1.60000E-02
Anthracene
120127
PM2.5
Line-haul (Class 1)
9.46972E-05
Anthracene
120127
PM2.5
Line-haul (Class ll/lll)
9.49449E-05
Anthracene
120127
PM2.5
Switcher
1.38785E-04
Arsenic
7440382
PM2.5
Line-haul (Class 1)
1.07887E-03
Arsenic
7440382
PM2.5
Line-haul (Class ll/lll)
9.44008E-04
Arsenic
7440382
PM2.5
Switcher
5.86718E-04
Benz[a] Anthracene
56553
PM2.5
Line-haul (Class 1)
8.46970E-06
Benz[a] Anthracene
56553
PM2.5
Line-haul (Class ll/lll)
8.48693 E-06
Benz[a] Anthracene
56553
PM2.5
Switcher
1.15358E-05
Benzene
71432
voc
Line-haul (Class 1)
2.25000E-02
Benzene
71432
voc
Line-haul (Class ll/lll)
2.25000E-02
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 192
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Appendix J. HAP Speciation Profiles for Locomotive Engines
2020 Public Draft
Pollutant
Pollutant
Code
Basis
Locomotive Type
Fraction
Benzene
71432
voc
Switcher
2.25000E-02
Benzo[a]Pyrene
50328
PM2.5
Line-haul (Class 1)
2.13000E-06
Benzo[a]Pyrene
50328
PM2.5
Line-haul (Class ll/lll)
2.13000E-06
Benzo[a]Pyrene
50328
PM2.5
Switcher
2.13000E-06
Benzo[b]Fluoranthene
205992
PM2.5
Line-haul (Class 1)
2.60000E-06
Benzo[b]Fluoranthene
205992
PM2.5
Line-haul (Class ll/lll)
2.60000E-06
Benzo[b]Fluoranthene
205992
PM2.5
Switcher
2.60000E-06
Benzo[g,h,i,]Perylene
191242
PM2.5
Line-haul (Class 1)
3.60144E-06
Benzo[g,h,i,]Perylene
191242
PM2.5
Line-haul (Class ll/lll)
3.60797E-06
Benzo[g,h,i,]Perylene
191242
PM2.5
Switcher
4.76314E-06
Benzo[k]Fluoranthene
207089
PM2.5
Line-haul (Class 1)
2.03000E-06
Benzo[k]Fluoranthene
207089
PM2.5
Line-haul (Class ll/lll)
2.03000E-06
Benzo[k]Fluoranthene
207089
PM2.5
Switcher
2.03000E-06
Chromium (VI)
18540299
PM2.5
Line-haul (Class 1)
5.21340E-06
Chromium (VI)
18540299
PM2.5
Line-haul (Class ll/lll)
4.56173E-06
Chromium (VI)
18540299
PM2.5
Switcher
2.83520E-06
Chrysene
218019
PM2.5
Line-haul (Class 1)
1.25129E-05
Chrysene
218019
PM2.5
Line-haul (Class ll/lll)
1.25335E-05
Chrysene
218019
PM2.5
Switcher
1.61789E-05
Dibenzo[a,h] Anthracene
53703
PM2.5
Line-haul (Class 1)
9.64000E-07
Dibenzo[a,h] Anthracene
53703
PM2.5
Line-haul (Class ll/lll)
9.64000E-07
Dibenzo[a,h] Anthracene
53703
PM2.5
Switcher
9.64000E-07
Ethyl Benzene
100414
voc
Line-haul (Class 1)
3.84000E-03
Ethyl Benzene
100414
voc
Line-haul (Class ll/lll)
3.84000E-03
Ethyl Benzene
100414
voc
Switcher
3.84000E-03
Fluoranthene
206440
PM2.5
Line-haul (Class 1)
1.02580E-04
Fluoranthene
206440
PM2.5
Line-haul (Class ll/lll)
1.02859E-04
Fluoranthene
206440
PM2.5
Switcher
1.52285E-04
Fluorene
86737
PM2.5
Line-haul (Class 1)
8.69565E-04
Fluorene
86737
PM2.5
Line-haul (Class ll/lll)
8.72240E-04
Fluorene
86737
PM2.5
Switcher
1.34567E-03
Formaldehyde
50000
voc
Line-haul (Class 1)
2.23000E-01
Formaldehyde
50000
voc
Line-haul (Class ll/lll)
2.23000E-01
Formaldehyde
50000
voc
Switcher
2.23000E-01
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 193
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Appendix J. HAP Speciation Profiles for Locomotive Engines
2020 Public Draft
Pollutant
Pollutant
Code
Basis
Locomotive Type
Fraction
Hexane
110543
voc
Line-haul (Class 1)
2.79000E-03
Hexane
110543
voc
Line-haul (Class ll/lll)
2.79000E-03
Hexane
110543
voc
Switcher
2.79000E-03
lndeno[l,2,3-c,d]Pyrene
193395
PM2.5
Line-haul (Class 1)
1.53000E-06
lndeno[l,2,3-c,d]Pyrene
193395
PM2.5
Line-haul (Class ll/lll)
1.53000E-06
lndeno[l,2,3-c,d]Pyrene
193395
PM2.5
Switcher
1.53000E-06
Manganese
7439965
PM2.5
Line-haul (Class 1)
2.31856E-03
Manganese
7439965
PM2.5
Line-haul (Class ll/lll)
2.02874E-03
Manganese
7439965
PM2.5
Switcher
1.26090E-03
Mercury
7439976
PM2.5
Line-haul (Class 1)
1.43000E-06
Mercury
7439976
PM2.5
Line-haul (Class ll/lll)
1.25000E-06
Mercury
7439976
PM2.5
Switcher
7.80000E-06
Naphthalene
91203
voc
Line-haul (Class 1)
2.73000E-03
Naphthalene
91203
voc
Line-haul (Class ll/lll)
2.73000E-03
Naphthalene
91203
voc
Switcher
2.73000E-03
Nickel
7440020
PM2.5
Line-haul (Class 1)
4.05412E-03
Nickel
7440020
PM2.5
Line-haul (Class ll/lll)
3.54736E-03
Nickel
7440020
PM2.5
Switcher
2.20475E-03
Octachlorodibenzofuran
39001020
PM2.5
Line-haul (Class 1)
2.25825E-09
Octachlorodibenzofuran
39001020
PM2.5
Line-haul (Class ll/lll)
1.97597E-09
Octachlorodibenzofuran
39001020
PM2.5
Switcher
1.22810E-09
Octachlorodibenzo-p-Dioxin
3268879
PM2.5
Line-haul (Class 1)
1.96340E-08
Octachlorodibenzo-p-Dioxin
3268879
PM2.5
Line-haul (Class ll/lll)
1.71798E-08
Octachlorodibenzo-p-Dioxin
3268879
PM2.5
Switcher
1.06775E-08
Phenanthrene
85018
PM2.5
Line-haul (Class 1)
1.87585E-03
Phenanthrene
85018
PM2.5
Line-haul (Class ll/lll)
1.88136E-03
Phenanthrene
85018
PM2.5
Switcher
2.85664E-03
Propionaldehyde
123386
voc
Line-haul (Class 1)
3.86000E-02
Propionaldehyde
123386
voc
Line-haul (Class ll/lll)
3.86000E-02
Propionaldehyde
123386
voc
Switcher
3.86000E-02
Pyrene
129000
PM2.5
Line-haul (Class 1)
1.40005 E-04
Pyrene
129000
PM2.5
Line-haul (Class ll/lll)
1.40360E-04
Pyrene
129000
PM2.5
Switcher
2.03327E-04
Toluene
108883
voc
Line-haul (Class 1)
2.15000E-02
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 194
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Appendix J. HAP Speciation Profiles for Locomotive Engines
2020 Public Draft
Pollutant
Pollutant
Code
Basis
Locomotive Type
Fraction
Toluene
108883
voc
Line-haul (Class ll/lll)
2.15000E-02
Toluene
108883
voc
Switcher
2.15000E-02
Xylenes (Mixed Isomers)
1330207
voc
Line-haul (Class 1)
1.64400E-02
Xylenes (Mixed Isomers)
1330207
voc
Line-haul (Class ll/lll)
1.64400E-02
Xylenes (Mixed Isomers)
1330207
voc
Switcher
1.64400E-02
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 195
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U.S. Environmental Protection Agency
2020 Public Draft
Appendix K Estimating Number of Trucks and Rail Cars
This appendix provides a detailed methodology for estimating the number of trucks and rail cars moved
by a port based on waterborne cargo activity. This method should be applied when more precise values
cannot be obtained from relevant organizations (e.g., the railroad company servicing the port), as
described in Sections 7.4.2 and 8.4.
This methodology relies upon publicly available data on tonnage and TEUs of waterborne cargo
throughput from the U.S. Army Corps of Engineers (USACE). These data are used to determine the
tonnage (for non-containerized cargo) and TEUs (for containerized cargo) of cargo throughput in each
commodity class. Mode split for each commodity class is estimated based on data from the Federal
Highway Administration, which enables the calculation of tonnage and TEUs moved by truck and rail.
Average tonnage per rail car and truck by commodity class is determined based on rail car and truck
configuration (e.g., volume capacity, payload) and commodity density.
As part of the Waterborne Commerce Series, USACE publishes annual data on tonnage of freight traffic
by commodity (Waterborne Commerce of the United States reports3) and TEUs of container traffic
moved by port (Waterborne Container Traffic statistics53). In the Waterborne Commerce of the United
States reports, commodities are coded using nine major commodity classes and approximately 140
detailed classes. These data allow the commodity mix at each port to be determined, which is valuable
given that the mode share of the domestic leg of a foreign movement is generally correlated with the
commodity carried. The same is true for domestic waterborne movements.
This commodity mix can be applied to both containerized and non-containerized cargo, resulting in
number of TEUs and tonnage, respectively, by port and by commodity. The USACE commodity classes
can be divided in four categories based on the transportation equipment that is most likely to be
utilized to transport the commodity by truck or rail: containerized, liquid bulk, dry bulk, and break bulk.
This division is necessary to estimate the number of rail cars and trucks generated by each commodity
at each port. Table K.l provides a list of commodities moved by each conveyance type. It is important
to note that for some commodities, this correspondence will vary by port; the specialization of the port
should be considered when classifying such commodities. For example, food and agricultural products
can be shipped as dry bulk or containerized cargo. Such commodities are more likely to be shipped as
containerized cargo at ports that handle substantial amounts of containerized cargo and shipped as dry
bulk at ports that predominantly handle bulk products. Although this adds some degree of uncertainty
to the calculation of rail loads associated with specific equipment types (i.e., intermodal cars, tank cars,
flat cars), the total number of rail cars and trucks should not vary widely depending on the classification
of specific commodities.
a For more information, see https://www.iwr.usace.armv.mjj/About/Technicaj-Centers/WCSC-Waterborne-
Commerce-Statistics-Center.
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories
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Appendix K. Estimating Number of Trucks and Rail Cars 2020 Public Draft
Table K.l. Commodities by Conveyance Type
Conveyance
Type*
Commodities"
Containerized
Petrol, jelly & waxes; fertilizers (nitrogenous fert.; phosphatic fert.); other chemicals &
related products (nitrogen func. comp.; organo-inorganic comp.; organic comp.
NEC***; sulfuric acid; sodium hydroxide; inorganic elements, oxides & halogen salts;
inorganic chem. NEC; radioactive material; pigments & paints; coloring mat. NEC;
medicines; perfumes & cleansers; plastics; starches, gluten, glue; explosives; chemical
additives; wood & resin chem.; chem. products NEC); rubber & gums; wood chips;
non-ferrous scrap; non-metallic min. NEC; paper products; glass & glass products;
misc. mineral products; primary non-ferrous metal products (smelted products NEC;
fab. metal products); fish; grain (wheat; rice; oats; sorghum grains); oilseeds
(soybeans; flaxseed); vegetable products; wheat flower; hay & fodder; other
agricultural products (meat, fresh, frozen; meat, prepared; dairy products; fish,
prepared; tallow, animal oils; animals & prod. NEC; bananas & plantains; fruit & nuts
NEC; fruit juices; sugar; coffee; alcoholic beverages; groceries; food products NEC;
tobacco & products; cotton; natural fibers NEC; farm products NEC); manufactured
equipment & machinery products (machinery [not elec.]; electrical machinery;
ordnance & access; manufactured wood products; textile products; rubber & plastic
products; empty containers; manufactured products NEC); waste & scrap NEC;
unknown or NEC
Liquid bulk
Crude petroleum; petroleum products (gasoline; kerosene; distillate fuel oil; residual
fuel oil; lube oil & greases; naphtha & solvents; asphalt, tar & pitch; hydrocarbon &
petrol gases, liquefied & gaseous; petrol, products NEC); fertilizers (potassic fert.; fert.
& mixes NEC); other chemicals & related products (acyclic hydrocarbons; benzene &
toluene; other hydrocarbons; alcohols; carboxylic acids; sulfur, liquid; ammonia;
pesticides)
Dry bulk
Coal; petroleum coke; metallic salts; soil, sand, gravel, rock & stone (limestone; sand
& gravel; dredged material; waterway improv. material; soil & fill dirt); iron ore &
scrap; marine shells; non-ferrous ore & scrap (copper ore; aluminum ore; manganese
ore; non-ferrous ores NEC); sulfur, dry; salt; slag; lime; cement & concrete; grain
(corn, barley & rye); peanuts; other agricultural products (molasses; cocoa beans;
water & ice)
Break bulk
Forest products & wood (fuel wood; wood in the rough; lumber; forest products NEC);
pulp & waste paper; building stone; gypsum; phosphate rock; clay & refractory
material; primary iron & steel products; copper; aluminum; primary wood products;
oilseeds NEC; grain mill products; animal feed, prep.; vehicles & parts; aircraft & parts;
ships & boats
*The provided commodity classifications are for a typical port. For some commodities, the correspondence
with conveyance type may vary across ports.
" Listed commodities may not be inclusive of all cargo handled at ports.
"* NEC indicates "not elsewhere classified".
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Appendix K. Estimating Number of Trucks and Rail Cars
2020 Public Draft
The number of containers moved by the port in TEUs can be taken directly from the USACE Waterborne
Container Traffic statistics. The commodity split should then be determined based on the latest
Waterborne Commerce of the United States report for the port. More specifically, TEUs should be
allocated in proportion to the percentage of total tonnage belonging to a given USACE commodity type.
In the case of non-containerized cargo, the tonnage of non-container freight throughput by commodity
should be determined using the latest Waterborne Commerce of the United States report for the port.
The number of non-container equipment (e.g., rail gondolas, flat cars) used to move this cargo will be
estimated below based on this information. Figure K-l summarizes this step.
Figure K-l. Calculation of Port Tonnage by Commodity
i k
Port Commodity
Mix (USACE)
Port Containerized Tonnage
Port Containerized Tonnage by
Commodity
Port Non-containerized
Tonnage
Port Non-containerized
Tonnage by Commodity
For ports without on-dock rail terminals, it can be assumed that all commodities will be moved by truck.
For those ports with on-dock rail accessibility, it is necessary to understand how different shipments are
distributed amongst truck and rail pathways. Aside from infrastructure availability (e.g., rail terminals),
the best indicator of transportation mode is commodity type.
Mode split data can be taken from the Freight Analysis Framework (FAF).11 It includes international and
domestic shipments with information on origin, destination, port of entry (for international imports) or
exit (for international exports), commodity type, transportation mode used on the domestic leg, value,
and weight. Modes included are truck, rail, water, air, and others. The geographical zones for which
estimates are available are varied; some zones include a large part of a state, while other zones are
limited to a single metropolitan area.
Based on mode split by port and by commodity, it is possible to estimate the number of TEUs of
containerized cargo and tonnage of non-containerized cargo of each commodity type that is moved by
rail and truck. To do so, the total TEUs/tonnage of a given commodity moved by the port (derived from
the USACE Waterborne Commerce Series) should be multiplied by the proportion of that commodity
type moved by truck/rail (derived from the FAF), as shown in Figure K-2.
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2020 Public Draft
Port TEU by Commodity
Mode Split by Port and by
Commodity (FAF)
Port Non-containerized
Tonnage by Commodity
Port TEU by Commodity
Moved by Rail
Port Tonnage by Commodity
Moved by Rail
To estimate the number of trucks and rail cars for non-containerized cargo, it is necessary to investigate
commodity densities to determine whether a commodity would "weigh out" or "cube out." Very dense
commodities tend to weigh out (i.e., reach tonnage capacity before it reaches the volume capacity of
transportation equipment), while less dense commodities tend to cube out (i.e., reach volume capacity
before it reaches tonnage capacity). Average densities for 18 commodity groups, based on the Standard
International Trade Classification (SITC) system of classifying commodities and listed by Standard
Classification of Transported Goods (SCTG) code, are presented in Table K.2.64 The USACE commodity
types can be matched to the SITC commodity groups for which densities are available.
Table K.2. Commodity Densities
SCTG
Code
Product Name
SITC
Code
Product Name
Density
(lb/ft3)
Density
(ton/m3)
4
Animal Feed and Prod, of
Animal
8
Feeding-Stuff for Animals
20
0.3204
7
Prepared Foodstuffs and
Fats and Oils
9
Miscellaneous Food
Preparations
38
0.6087
18
Fuel Oils
22
Oil-Seeds, Oil-Nuts and Oil
Kernels/Essential Oils and
Perfume Products
29
0.4645
25
Logs and Other Wood in
the Rough
24
Wood, Lumber, and Cork
25
0.4005
27
Pulp, Newsprint, Paper,
and Paperboard
25
Pulp and Waste Paper
34
0.5446
22
Fertilizer
27
Crude Fertilizers and Crude
Materials
64
1.0252
15
Coal
32
Coal, Coke, and Briquettes
53
0.8490
19
Coal and Petroleum
Products, NEC*
33
Petroleum and Petroleum
Products/Mineral Tar and
Crude Petroleum
Chemicals
51
0.8169
17
Gasoline and Aviation
Turbine Fuel
34
Gas, Natural and
Manufactured
26
0.4165
Methodologies for Estimating Port-Related and Goods Movement Mobile Source Emission Inventories 199
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Appendix K. Estimating Number of Trucks and Rail Cars
2020 Public Draft
SCTG
Code
Product Name
SITC
Code
Product Name
Density
(lb/ft3)
Density
(ton/m3)
20
Basic Chemicals
51
Chemical Elements and
Compounds
64
1.0252
20
Basic Chemicals
59
Chemical Materials and
Products
36
0.5767
27
Pulp, Newsprint, Paper,
and Paperboard
64
Paper, Paperboard and
Manufactured Thereof
20
0.3204
12
Gravel and Crushed
Stone
66
Concrete Brick/Block—
Glazed Brick/Block
80
1.2815
31
Nonmetallic Mineral
Products
66
Non-Metallic Mineral
Manufactures
60
0.9611
32
Base Metal in Primary or
Semifinished Forms and
in Finished Basic Shapes
67
Iron and Steel
139
2.2266
32
Base Metal in Primary or
Semifinished Forms and
in Finished Basic Shapes
69
Manufactures of Metal
39
0.6247
26
Wood Products
82
Furniture
7
0.1121
43
Mixed Freight
89
Miscellaneous
Manufactures Articles,
NEC
21
0.3364
* NEC indicates "not elsewhere classified".
Because of packaging issues, transportation equipment cannot be 100% utilized, even for commodities
that cube out. For example, some beverage products are bottled and packaged in boxes. The space
between bottles and the packaging material account for a share of the total volume being shipped.
Additionally, depending on the shape of the packaging material, it might not be possible to utilize the
full volume capacity of the transportation equipment. Bulk materials, on the other hand, can utilize
100% of the rail car or truck capacity if they do not weigh out first.
The commodity densities in Table K.2 can be multiplied by equipment utilization rates to obtain adjusted
commodity densities. Table K.3 presents utilization assumptions for the four commodity types, as well
as the equipment types commonly used to move each commodity type by truck and rail.
Table K.3. Truck and Rail Equipment Types and Utilization Rates by Conveyance Type
Conveyance Type
Truck/Rail Equipment Types
Equipment
Utilization Rate
Containerized
Truck: Container on chassis
Rail: Container on double-stack train
85%
Liquid bulk
Truck: Tanker truck
Rail: Rail tank car
100%
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Appendix K. Estimating Number of Trucks and Rail Cars
2020 Public Draft
Conveyance Type
Truck/Rail Equipment Types
Equipment
Utilization Rate
Dry bulk
Truck: Dump truck
Rail: Gondola
100%
Break bulk*
Truck: Flat trailer
Rail: Flat car
85%
*The following break bulk commodities are assumed to have a rail car utilization rate
of 50%:
• Aircraft and aircraft parts
• Electrical machinery
• Explosives
• Fabricated metal products
• Glass and glass products
• Non-electrical machinery
• Radioactive material
• Vehicles and vehicle parts
Table K.4 presents assumed physical dimensions and payload capacities for these rail and truck
equipment types.
Table K.4. Equipment Dimensions
Equipment
Length
(in)
Width (in)
Height (in)
Volume
(in3)
Volume
(m3)
Maximum
Payload
(tons)
Maximum
Theoretical
Density
(ton/m3)
20' Container
233
92
95
2,036,420
33
22
0.65
40' Container
475
93
94
4,152,450
68
27
0.39
Flat Car
804
96
102
7,872,768
129
120
0.93
Gondola
660
108
84
5,987,520
98
120
1.22
Rail Tank
240
96
102
2,350,080
39
120
3.10
Flat Trailer
570
102
110
6,395,400
105
21
0.20
Dump Truck
570
102
110
6,395,400
105
40
0.48
Tanker Truck
570
102
110
6,395,400
105
27
0.25
A maximum theoretical equipment density can be calculated as the ratio between the equipment's
payload capacity and volume. Commodities with adjusted densities that are lower than the maximum
theoretical equipment density will cube out, and commodities with adjusted densities that are higher
than the maximum theoretical equipment density will weigh out. Based on the adjusted commodity
densities and whether commodities generally weigh out or cube out, the average tonnage per rail car
could be determined for each commodity, as shown in Figure K-3.
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Appendix K. Estimating Number of Trucks and Rail Cars 2020 Public Draft
Figure K-3. Calculation of Tonnage per Rail Car by Commodity
Rail Equipment
Dimensions
Rail Equipment
Maximum Payload
Commodity Density
(Table K.2)
Equipment Utilization
by Commodity
Commodity
weighs out or
cubes out?
Adjusted
Commodity
Density
Maximum
Theoretical
Equipment
Density
Tonnage per Rail
Car per Commodity
If a given commodity type will weigh out, the maximum payload per container should be assumed. For
commodities that will cube out, average tonnage per rail car/truck can be calculated using Equation K.l:
T = D xV Equation K.l
Where T = average tonnage per rail car/truck
D = adjusted commodity density (ton/m3)
V = equipment volume (m3)
To calculate the total number of rail cars moved annually, the total tonnage of the commodity moved by
truck/rail can be divided by the maximum payload tonnage (if the commodity weighs out) or the
calculated average tonnage per rail car/truck value (if the commodity cubes out).
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