vvEPA
United States
Environmental Protection
Agency
NATIONAL PORT STRATEGY
ASSESSMENT: Reducing Air
Pollution and Greenhouse Gases
at U.S. Ports
Office of Transportation Air Quality
EPA-420-R-16-011
September 2016

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Note
ICF International provided technical support to the U.S. Environmental Protection Agency in the
development of the methodologies, emission inventories, emission reduction strategy analyses, and
other tasks related to this assessment.
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports

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Table of Contents
Contents
Contents	i
Tables	iv
Figures	vii
1.	Executive Summary	1
1.1.	Introduction	1
1.2.	Port-related diesel emissions impact public health and the climate	4
1.3.	Progress is already happening, but more emission reductions are possible	5
1.4.	We can reduce emissions with effective strategies that are currently available	6
1.5.	Replace older, dirtier diesel vehicles and equipment first	7
1.6.	C02 continues to increase, but effective strategies are available	8
1.7.	Reduction potential varies across mobile source sectors	9
1.8.	Effective strategies are available for every type and size of port	10
1.9.	More focus is needed to reduce port-related emissions	11
2.	Introduction	12
2.1.	Purpose of Assessment	12
2.2.	Public Health and Climate Impacts	13
2.3.	Mobile Source Sectors Analyzed	14
2.3.1.	Drayage Trucks	14
2.3.2.	Rail	15
2.3.3.	Cargo Handling Equipment	15
2.3.4.	Harbor Craft	15
2.3.5.	Ocean Going Vessels	15
2.4.	Pollutants Characterized in This Work	16
2.5.	Overview of Assessment Approach	17
2.6.	Port-related Strategies Analyzed	18
2.7.	Organization of Assessment Report	19
3.	Baseline Emission Inventory Development	20
3.1.	Overview	20
3.2.	Drayage Trucks	20
3.2.1.	Methodology and Available Data	20
3.2.2.	Results	21
3.3.	Rail	21
3.3.1.	Methodology and Available Data	21
3.3.2.	Results	22
3.4.	Cargo Handling Equipment	23
3.4.1.	Methodology and Available Data	23
3.4.2.	Results	24
3.5.	Harbor Craft	24
3.5.1.	Methodology and Available Data	24
3.5.2.	Results	25
3.6.	Ocean Going Vessels	25
3.6.1. Methodology and Available Data	26
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3.6.2. Results	27
3.7. Summary of Baseline Inventory Results	28
4.	Business as Usual Emission Inventory Development	29
4.1.	Overview	29
4.2.	Summary of Growth Rates	29
4.3.	Infrastructure Changes That Modify BAU Growth Values	30
4.4.	Drayage Trucks	30
4.4.1.	Methodology	30
4.4.2.	Results	31
4.5.	Rail	31
4.5.1.	Methodology	31
4.5.2.	Results	32
4.6.	Cargo Handling Equipment	32
4.6.1.	Methodology	32
4.6.2.	Results	33
4.7.	Harbor Craft	33
4.7.1.	Methodology	34
4.7.2.	Results	35
4.8.	Ocean Going Vessels	35
4.8.1.	Methodology	35
4.8.2.	Results	36
4.9.	Summary of Business as Usual Inventory Results	37
5.	Assessment of Emission Reduction Strategies	39
5.1.	Introduction	39
5.2.	Drayage Trucks	41
5.2.1.	Technological Strategies	41
5.2.2.	Operational Strategies	46
5.3.	Rail	48
5.3.1.	Line-haul Locomotives	48
5.3.2.	Switcher Locomotives	52
5.3.3.	Summary of Most Promising Locomotive Strategies	56
5.4.	Cargo Handling Equipment	56
5.4.1.	Yard Trucks	57
5.4.2.	Cranes	62
5.4.3.	Container Handlers	65
5.4.4.	Summary of Most Promising CHE Strategies	68
5.5.	Harbor Craft	69
5.5.1.	Tugs	69
5.5.2.	Ferries	73
5.5.3.	Summary of Most Promising Harbor Craft Strategies	77
5.6.	Ocean Going Vessels	78
5.6.1.	Introduction	78
5.6.2.	Baseline Emissions	78
5.6.3.	Strategy Effectiveness	81
5.6.4.	Most Effective Strategies - Container Ships	83
5.6.5.	Most Effective Strategies - Passenger Ships	84
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5.6.6.	Most Effective Strategies - Tanker Ships	85
5.6.7.	Most Effective OGV Strategies	85
5.7. Example Application of Port Strategies in Screening Assessment	86
6.	Analysis of Emission Reduction Scenarios	90
6.1.	Overview	90
6.2.	Drayage Trucks	92
6.2.1.	Technological Strategies	92
6.2.2.	Operational Strategies	94
6.2.3.	Summary of Drayage Truck Scenarios	96
6.3.	Rail	101
6.3.1.	Line-haul Technology Strategies	102
6.3.2.	Line-haul Operational Strategies	103
6.3.3.	Switcher Technology Strategies	103
6.3.4.	Summary of Rail Scenarios	104
6.4.	Cargo Handling Equipment	Ill
6.4.1.	Yard Truck Strategies	Ill
6.4.2.	RTG Crane Strategies	112
6.4.3.	Container Handler Strategies	114
6.4.4.	Summary of CHE Scenario Impacts	115
6.5.	Harbor Craft	122
6.5.1.	Tug Strategies	122
6.5.2.	Ferry Strategies	123
6.5.3.	Summary of Harbor Craft Scenario Impacts	124
6.6.	Ocean Going Vessels	132
6.6.1.	Fuel Change Strategies	132
6.6.2.	Shore Power Strategies	139
6.6.3.	Advanced Marine Emission Control System Strategies	144
6.6.4.	Reduced Hoteling Strategies	146
6.6.5.	Summary of OGV Scenario Impacts	147
6.7.	Summary of Emission Reduction Scenario Analysis	159
7.	Stratified Summary of Results	161
7.1.	Background on Development of Strategy Scenarios	161
7.2.	OGV Stratification	161
7.2.1.	Summary by Port Type	163
7.2.2.	Summary by Port Size	166
7.3.	Non-OGV Stratification	168
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Table of Contents
Tables
Table 1-1. Examples of Strategy Scenarios Assessed	6
Table 1-2. Examples of Effective Port Strategies to Reduce NOx and PM2.5 Emissions	7
Table 1-3. Examples of Effective Port Strategies to Reduce C02 Emissions	8
Table 2-1. Ocean-Going Vessel Ship Types	15
Table 2-2. Summary of Sources, Pollutants, and Geographic Area Covered by Assessment	17
Table 2-3. Summary of Data and Methodology Sources for Baseline and BAU Emission
Inventories	18
Table 2-4. Overview of Strategy Scenarios	19
Table 3-1. Baseline 2011 Emissions for Drayage Trucks, Tons per Year	21
Table 3-2. Relevant SCCsfor Rail Inventory Analysis	22
Table 3-3. 2011 Baseline Emissions for Rail, Tons per Year	23
Table 3-4. 2011 Baseline Emissions for CHE, Tons per Year	24
Table 3-5. Relevant SCCs for Port Inventory Analysis	25
Table 3-6. 2011 Baseline Emissions for Harbor Craft, Tons per Year	25
Table 3-7. Vessel Movements and Time-ln-Mode Descriptions	27
Table 3-8. 2011 Baseline Emissions for OGVs, Tons per Year	27
Table 3-9. 2011 Baseline Emissions for All Sectors and Pollutants, Tons per Year	28
Table 4-1. Compound Annual Growth Rates for 2020 and 2030 by Region and
Commodity	29
Table 4-2. Annual Average Growth Rates by Region Based upon Bunker Fuel Use	30
Table 4-3. Total BAU Emissions for Drayage Trucks, Tons per Year	31
Table 4-4. Total BAU Emissions for Rail, Tons per Year	32
Table 4-5. Total BAU Emissions for CHE, Tons per Year	33
Table 4-6. Total BAU Emissions for Harbor Craft, Tons per Year	35
Table 4-7. BAU Emissions for OGVs, Tons per Year	36
Table 5-1. Example Emission Reduction Strategies for Assessment	40
Table 5-2. EPA Emission Standards for Heavy Duty Vehicles (g/bhp-hr)	41
Table 5-3. Typical Emission Impact per Truck per Year - NOx (lbs)	43
Table 5-4. Typical Emission Impact per Truck per Year - PM2.5 (lbs)	43
Table 5-5. Typical Emission Impact per Truck per Year - C02 (tons)	43
Table 5-6. Distribution of Trucks by Model Year	44
Table 5-7. Most Promising Drayage Truck Technological Strategies	46
Table 5-8. Approximate Annual Typical Port Emission Impacts for Truck Operational
Strategies, 2020	47
Table 5-9. Typical Port Emission Impacts for Each 10 Percent Reduction in Idle/Creep
Time, 2020 and 2030	48
Table 5-10. EPA Emission Factors for Line-Haul Locomotives	49
Table 5-11. Typical Emission Impact per Line-Haul Locomotive per Year - NOx (lbs)	50
Table 5-12. Typical Emission Impact per Line-Haul Locomotive per Year - PM2.5 (lbs)	51
Table 5-13. Distribution of Line-Haul Locomotives by Tier	51
Table 5-14. EPA Emission Factors for Switcher Locomotives	53
Table 5-15. Typical Emission Impact per Switcher Locomotive per Year - NOx (lbs)	54
Table 5-16. Typical Emission Impact per Switcher Locomotive per Year - PM2.5 (lbs)	54
Table 5-17. Distribution of Switcher Locomotives by Tier	55
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Table 5-18. Most Promising Locomotive Emission Reduction Strategies	56
Table 5-19. EPA Emission Standards Applicable to Typical Yard Trucks	57
Table 5-20. Typical Emission Impact per Yard Truck per Year - NOx (lbs)	59
Table 5-21. Typical Emission Impact per Yard Truck per Year - PM2.5 (lbs)	59
Table 5-22. Typical Emission Impact per Yard Truck per Year - C02 (tons)	59
Table 5-23. Distribution of Yard Trucks by Tier	60
Table 5-24. EPA Emission Standards Applicable to RTG Cranes (g/kWh)	62
Table 5-25. Typical Emission Impact per RTG Crane per Year - NOx (lbs)	63
Table 5-26. Typical Emission Impact per RTG Crane per Year - PM2.5 (lbs)	63
Table 5-27. Typical Emission Impact per Yard Truck per Year - C02 (tons)	64
Table 5-28. Distribution of RTG Cranes by Tier	64
Table 5-29. EPA Emission Standards Applicable to Typical Container Handlers (g/kWh)	66
Table 5-30. Typical Emission Impact per Container Handler per Year - NOx (lbs)	66
Table 5-31. Typical Emission Impact per Container Handler per Year - PM2.5 (lbs)	67
Table 5-32. Typical Emission Impact per Container Handler per Year - C02 (tons)	67
Table 5-33. Distribution of Container Handlers by Tier	67
Table 5-34. Most Promising CHE Emission Reduction Strategies	68
Table 5-35. EPA Emission Factors Applicable to Assist Tugs (g/kW-hr)	70
Table 5-36. Typical Emission Impact per Tug per Year - NOx (lbs)	71
Table 5-37. Typical Emission Impact per Tug per Year - PM2.5 (lbs)	71
Table 5-38. Typical Emission Impact per Tug per Year - C02 (tons)	71
Table 5-39. Distribution of Tugs by Tier	71
Table 5-40. Emission Factors Applicable to Ferries (g/kW-hr)	74
Table 5-41. Typical Emission Impact per Ferry per Year - NOx (lbs)	75
Table 5-42. Typical Emission Impact per Ferry per Year - PM2.5 (lbs)	75
Table 5-43. Typical Emission Impact per Ferry per Year - C02 (tons)	75
Table 5-44. Distribution of Ferries by Tier	76
Table 5-45. Most Promising Harbor Craft Emission Reduction Strategies	77
Table 5-46. NOx Emission Factors by Engine Type and Tier (g/kWh)	79
Table 5-47. Average NOx Emission Factor (g/kWh) by Engine Type and Year	80
Table 5-48. PM2.5 Emission Factors by Engine Type and Fuel Type (g/kWh)	80
Table 5-49. C02 Emission Factors by Engine Type (g/kWh)	81
Table 5-50. LNG Emission Factors (g/kWh)	81
Table 5-51. Well-to-Pump/Plug C02 Emission Factors (g/kWh)	81
Table 5-52. Ship Characteristics for Screening Analysis	83
Table 5-53. Percent Frequent Callers by Ship Type	83
Table 5-54. Typical Emission Impact per Year for Container Ships	84
Table 5-55. Typical Emission Impact per Year for Passenger Ships	84
Table 5-56. Typical Emission Impact per Year for Tankers	85
Table 5-57. Equipment Count Assumptions for a Typical Port in Screening Assessment	87
Table 5-58. Example Application of Potential Strategies for 2020	88
Table 5-59. Example Application of Potential Strategies for 2030	89
Table 6-1. Drayage Truck Strategy Scenarios	92
Table 6-2. Relative Reduction Factors for Drayage Truck Technological Strategy
Scenarios	94
Table 6-3. Total Drayage Truck Emission Reductions for Technological Strategy Scenarios	94
Table 6-4. Relative Reduction Factors for Drayage Fleet Operational Strategy Scenarios	95
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Table 6-5. Total Drayage Truck Operational Emission Reductions	95
Table 6-6. Drayage Truck Relative Emission Reduction Summary by Scenario and
Strategy, Percent	97
Table 6-7. Drayage Truck Emission Reduction Summary by Scenario and Strategy, Tons
per Year	99
Table 6-8. Rail Strategy Scenarios	101
Table 6-9. Relative Reduction Factors for Line-haul Technology Strategies	102
Table 6-10. Total Line-haul Technology Emission Reductions	103
Table 6-11. Total Line-haul Operational Emission Reductions	103
Table 6-12. Relative Reduction Factors for Switcher Technology Strategies	103
Table 6-13. Total Switcher Technology Emission Reductions	104
Table 6-14. Rail Emission Relative Reduction Summary by Scenario and Strategy, Percent	105
Table 6-15. Rail Emission Reduction Summary by Scenario and Strategy, Tons per Year	108
Table 6-16. Yard Truck Strategy Scenarios	Ill
Table 6-17. Relative Reduction Factors for Yard Truck Strategies	112
Table 6-18. Total Yard Truck Emission Reductions	112
Table 6-19. RTG Crane Strategy Scenarios	112
Table 6-20. Relative Reduction Factors for RTG Crane Strategies	113
Table 6-21. Total RTG Crane Emission Reductions	113
Table 6-22. Container Handler Strategy Scenarios	114
Table 6-23. Relative Reduction Factors for Container Handler Strategies	114
Table 6-24. Total Container Handler Emission Reductions	114
Table 6-25. CHE Emission Relative Reductions by Scenario and Strategy, Percent- 	116
Table 6-26. CHE Emission Reduction Summary by Scenario and Strategy, Tons per Year	119
Table 6-27. Tug Strategy Scenarios	122
Table 6-28. Relative Reduction Factors for Tug Strategies	122
Table 6-29. Total Tug Emission Reductions	123
Table 6-30. Ferry Strategy Scenarios	123
Table 6-31. Relative Reduction Factors for Ferry Strategies	124
Table 6-32. Total Ferry Emission Reductions, Tons per Year	124
Table 6-33. Harbor Craft Emission Relative Reduction Summary by Scenario and
Strategy, Percent	126
Table 6-34. Harbor Craft Emission Reduction Summary by Scenario and Strategy, Tons
per Year	129
Table 6-35. Fuel Change Strategy Scenarios for OGV Propulsion Engines	133
Table 6-36. Fuel Change Strategy Scenarios for OGV Auxiliary Engines	134
Table 6-37. Relative Reduction Factors for Fuel Scenario 2020/A	135
Table 6-38. Relative Reduction Factors for Fuel Scenario 2020/B	135
Table 6-39. Relative Reduction Factors for Fuel Scenario 2030/A	135
Table 6-40. Relative Reduction Factors for Fuel Scenario 2030/B	136
Table 6-41. Relative Reduction Factors for Scenarios 2050/A and 2050/B	136
Table 6-42. Total Fuel Change Emission Reductions from Propulsion Engines	137
Table 6-43. Total Fuel Change Emission Reductions from Auxiliary Engines	138
Table 6-44. 2050 Total Fuel Change Emission Reductions	138
Table 6-45. Percent Reductions for Fuel Change Scenarios	139
Table 6-46. Shore Power Strategy Scenarios	139
Table 6-47. Average Percent of Frequent Callers, by Ship Type	140
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Table 6-48. Shore Power Effectiveness for Vessel Emissions Only, per call	140
Table 6-49. Power Plant Emission Factors at plug (g/kWh)	141
Table 6-50. Total Shore Power Emission Reductions for 2020 and 2030 Scenarios	142
Table 6-51. Total Shore Power C02 Emission Reductions for 2050 Scenarios (Tons per
Year)	143
Table 6-52. Percent Reductions for Shore Power Scenarios	143
Table 6-53. AMECS Strategy Scenarios	144
Table 6-54. Average Percent of Non-frequent Callers, by Ship Type	144
Table 6-55. AMECS Effectiveness	145
Table 6-56. Total AMECS Emission Reductions for 2020 and 2030 Scenarios	146
Table 6-57. Percent Reductions for AMECS Scenarios	146
Table 6-58. Reduced Hoteling Strategy Scenarios	146
Table 6-59. Total Reduced Hoteling Time Emission Reductions for 2020, 2030, and 2050
Scenarios	147
Table 6-60. Percent Reductions for Reduced Hoteling Scenarios	147
Table 6-61. OGV Emission Reduction Percentages by Scenario and Strategy, Relative to
Select Portions of the OGV BAU Inventory	150
Table 6-62. OGV Emission Reduction Percentages by Scenario and Strategy, Relative to
the Total OGV BAU Inventory	153
Table 6-63. OGV Emission Reduction Summary by Scenario and Strategy, Tons per Year	156
Table 6-64. Total Emission Reductions by Scenario and Sector	159
Figures
Figure 1-1. Ports in Areas Designated Nonattainment or Maintenance for the Clean Air
Act's NAAQS	2
Figure 1-2. Total BAU PM2.5 Emissions by Mobile Source Sector	5
Figure 1-3. Relative Reductions for PM2.5 in 2020 (Scenario A)	5
Figure 1-4. Total BAU C02 Emissions by Mobile Source Sector	8
Figure 1-5. Total NOx Reductions for Land-side Mobile Source Sectors	9
Figure 1-6. NOx Reduction Effectiveness of Different Strategies at Different Kinds of
Ports (Scenario B)	10
Figure 4-1. Total NOx Emissions Aggregated by Sector, Tons/Year	38
Figure 4-2. Total PM2.5 Emissions Aggregated by Sector, Tons/Year	38
Figure 4-3. Total C02 Emissions Aggregated by Sector, Tons/Year	38
Figure 6-1. Drayage Truck Percent Emission Reductions by Scenario and Strategy for
Selected Pollutants	98
Figure 6-2. Drayage Truck Absolute Emission Reductions by Scenario and Strategy for
Selected Pollutants	100
Figure 6-3. Rail Emission Percent Reductions by Scenario and Strategy for Selected
Pollutants	107
Figure 6-4. Rail Absolute Emission Reductions by Scenario and Strategy for Selected
Pollutants	110
Figure 6-5. CHE Percent Emission Reductions by Scenario and Strategy for Selected
Pollutants	118
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Figure 6-6. CHE Absolute Emission Reductions by Scenario and Strategy for Selected
Pollutants	121
Figure 6-7. Harbor Craft Percent Emission Reductions by Scenario and Strategy for
Selected Pollutants	128
Figure 6-8. Harbor Craft Absolute Emission Reductions by Scenario and Strategy for
Selected Pollutants	131
Figure 6-9. OGV Emission Percent Reductions by Scenario and Strategy for Selected
Pollutants, Relative to the Total OGV BAU Inventory	155
Figure 6-10. OGV Absolute Emission Reductions by Scenario and Strategy for Selected
Pollutants	158
Figure 7-1. Comparing NOx Relative Reduction Potential of the OGV Sector	163
Figure 7-2. Comparing PM2.5 Relative Reduction Potential of the OGV Sector	164
Figure 7-3. Comparing C02 Relative Reduction Potential of OGV Sector	164
Figure 7-4. NOx Reduction Effectiveness of Different Strategies at Different Kinds of
Ports (Scenario B)	165
Figure 7-5. NOx Relative Reduction Potential of the OGV Sector for Container Ports	166
Figure 7-6. PM2.5 Relative Reduction Potential of the OGV Sector for Container Ports	167
Figure 7-7. C02 Relative Reduction Potential of OGV Sector for Container Ports	167
Figure 7-8. NOx Relative Reduction Potential of Non-OGV Sector	168
Figure 7-9. PM2.5 Relative Reduction Potential of Non-OGV Sector	169
Figure 7-10. Comparing C02 Relative Reduction Potential of Non-OGV Sectors	170
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Section 1: Executive Summary
1. Executive Summary
1.1. Introduction
Ports are a vital part of the United States economy, with seaports, Great Lakes ports, and inland river
ports serving as gateways for moving freight and passengers across the country and around the world.
Seaports alone account for more than 23 million jobs and seaport cargo activity accounts for 26% of the
United States economy.1 The U.S. Army Corps of Engineers estimates that bigger Post-Panamax size
ships that currently call at U.S. ports will dominate world trade and represent 62% of total container
ship capacity by 2030.2 As our nation adapts to meet these emerging economic and infrastructure
demands, it is critical to understand the potential impacts on air pollution, greenhouse gases (GHGs),
and the people living, working, and recreating near ports.
The U.S. Environmental Protection Agency (EPA) developed this national scale 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 trucks, locomotives,
cargo handling equipment, harbor craft, and ocean-going vessels.3 Diesel engines are the modern-day
workhorse of the American economy, and although they can be reliable and efficient, older diesel
engines can emit significant amounts of air pollution, including fine particulate matter (PM2.5), nitrogen
oxides (NOx), air toxics, and carbon dioxide (C02), which impact human health and the planet.
The entire nation benefits from economic activity from the trade that passes through commercial ports
located around the country. And while those emissions can reach significantly inland,4 it is the people
who live, work, and recreate near ports that experience the most direct impacts on their health and
welfare. EPA estimates that about 39 million people in the United States currently live in close proximity
to ports5; these people can be exposed to air pollution from diesel engines at ports and be at risk of
developing asthma, heart disease, and other health problems.6 Port-related diesel-powered vehicles,
equipment, and ships also produce significant GHG emissions that contribute to climate change. Even
though EPA has adopted stringent emission standards for diesel engines, many ports and related freight
1	American Association of Port Authorities (AAPA), http://www.aapa-ports.org/advocating/content.aspx?ltemNumber=21150.
2	U.S. Army Corps of Engineers, U.S. Port and Inland Waterways Modernization: Preparing for Post-Panamax Vessels: Report
Summary, June 20, 2012.
3	This assessment was conducted to evaluate the emission reduction potential of a range of available strategies based upon a
national scale approach, rather than the cost and other details necessary to apply strategies in a specific area.
4	U.S. Environmental Protection Agency, Control of Emissions from New Marine Compression-Ignition Engines at or Above 30
Liters per Cylinder, 75 FR 24802, April 30, 2010.
5	EPA's analysis is based on overlaying and merging U.S. Census tract level geospatial data (Census Bureau 2010) with EPA's
National Emission Inventory (NEI 2011) ports data indicating that approximately 39 million people lived within 5 kilometers of
ports in the United States.
6	U.S. Environmental Protection Agency, Near Roadway Air Pollution and Health: Frequently Asked Questions, EPA-420-F-14-
044, 2014, https://www3.epa.gov/otaq/nearroadwav.htm.
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Section 1: Executive Summary
corridors and facilities are located in nonattainment or maintenance areas for EPA's ozone and PM2.5
national ambient air quality standards (NAAQS), per Figure 1-1.7
Figure 1-1. Ports in Areas Designated Nonattainment or Maintenance for the Clean Air Act's NAAQS
PM 2 5
502
x PM1°
M02
CO
y Ports -
> ^ fOona«ariment
or Marttenanco
This assessment supports the vision of EPA's Ports Initiative to reduce air pollution and GHGs through a
collaboration of industry, government, and communities.8 EPA already supports voluntary efforts to
reduce diesel emissions through EPA's Clean Diesel Campaign and its SmartWay program. State and local
governments, ports and port operators, Tribes, communities, and other stakeholders can use this
assessment as a tool to inform their priorities and decisions for port areas and achieve more emission
reductions across the United States. Economic growth can go hand-in-hand with continued
improvements in the health and welfare of near-port communities and the safeguarding of our planet.
7	Based on a review of available data, EPA approximates that 40% of "Principal Ports" are located in or near areas that have
violated a NAAQS (nonattainment areas) or have previously violated but are now meeting a NAAQS (maintenance areas).
8	The goals of EPA's Ports Initiative are to reduce air pollution and GHGs, to achieve environmental sustainability for ports, and
improve air quality for near-port communities. For more information, see https://www.epa.gov/ports-initiative.
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Section 1: Executive Summary
EPA developed this assessment in consultation with the Mobile Sources Technical Review Subcommittee
(MSTRS) of the Clean Air Act Advisory Committee (CAAAC) over a two-year period. In 2014, the MSTRS
formed a Ports Workgroup to develop recommendations for developing an EPA-led voluntary ports
initiative, and effectively measuring environmental performance at ports. The MSTRS Ports Workgroup
included technical and policy experts from a range of stakeholders, including industry, port-related
agencies, communities, Tribes, state and local governments, and public interest groups.9
9 For further information on MSTRS Ports Working Group participants, see https://www.epa.gov/sites/production/files/2016-
06/documents/portsinitiativewkerp 2016.pdf.
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Section 1: Executive Summary
1.2. Port-related diesel emissions impact public health and the
climate.
Emissions from diesel engines, especially PM2.5, NOx,
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.10 EPA has
determined that diesel engine exhaust emissions are
a likely human carcinogen,11 and the World Health
Organization has classified diesel emissions as
carcinogenic to humans.12 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.13
Port-related diesel emissions, such as C02 and black carbon, also contribute to climate change. Research
literature increasingly documents the effects that climate change is having and will increasingly have on
air and water quality, weather patterns, sea levels, human health, ecosystems, agricultural crop yield,
and critical infrastructure.14 Other health impacts that are projected from climate change include heat
stroke and dehydration from more frequent and longer heat waves and illnesses from an increase in
water and food-borne pathogens.15 This assessment provides options to inform voluntary, place-based
actions that may be taken by federal, state, and local governments, Tribes, ports, communities, and
other stakeholders to reduce these impacts and enhance public health and environmental protection.
10	Third Report to Congress: Highlights from the Diesel Emission Reduction Program, EPA, EPA-420-R-16-004, February 2016,
https://nepis.epa.gov/Exe/ZvPDF.cgi?Dockev=P1000HMK.pdf: and EPA's Health Assessment Document for Diesel Engine
Exhaust, 2002.
11	Health Assessment Document for Diesel Engine Exhaust, prepared by the National Center for Environmental Assessment for
EPA, 2002.
12	Diesel Engine Exhaust Carcinogenic, International Agency for Research on Cancer (IARC), World Health Organization, June 12,
2012, http://monographs.iarc.fr/ENG/Monographs/voll05/.
13	U.S. Environmental Protection Agency, Control of Emissions from New Marine Compression-Ignition Engines at or Above 30
Liters per Cylinder, 75 FR 24802 (April 30, 2010).
14	U.S. Environmental Protection Agency, Climate Change Indicators in the United States, 4th edition, 2016,
https://www.epa.gov/climate-indicators.
15	United States Global Change Research Program, The Impacts of Climate Change on Human Health in the United States: A
Scientific Assessment, April 2016, http://www.globalchange.gov/health-assessment.
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Section 1: Executive Summary
1.3. Progress is already happening, but more emission reductions are
possible.
EPA's technology standards and fuel sulfur limits are expected to significantly reduce emissions as new
diesel trucks, locomotives, cargo handling equipment (CHE), and ships enter the in-use fleet. For
example, the North American and U.S. Caribbean Sea Emissions Control Areas require lower sulfur fuel
to be used for large ocean-going vessels (OGVs). This has reduced fuel-based PM emissions by about
90%. Some stakeholders have also adopted voluntary strategies like those examined in this assessment.
EPA supports these efforts, encourages them to continue in the future, and hopes that this assessment
will encourage more areas to adopt and incentivize such voluntary programs.
EPA developed this national scale
assessment based on estimated
emissions from a representative sample
of seaports. EPA estimated Business as
Usual (BAU) emissions by projecting
future trends under the status quo. As
shown in Figure 1-2, total PM2.5 emissions
are projected to decrease in the future
for most mobile source sectors and years.
The assessment considered the impact
from all mobile source sectors, and the
levels of emissions shown in Figure 1-2
are based on the assessment's
geographic scope.
Figure 1-3. Relative Reductions for PM2.5 in
2020 (Scenario A)
¦	Drayage
¦	Rail
¦	CHE
¦	Harbor
Craft
¦	OGV
Figure 1-2. Total BAU PM2.5 Emissions by Mobile Source Sector
3,000
2,500
2,000
1,500
1,000
Harbor
Rail
12020 ¦ 2030
CHE
Drayage
EPA then estimated the potential reductions from a suite of
available strategies for all mobile source sectors for the
years 2020, 2030, and 2050. For example, Figure 1-3 shows
the break-out of PM2.5 reductions for all mobile source
sectors for Scenario A in the year 2020, with the highest
emission reductions being achieved in the drayage truck
sector. In this scenario, total PM2.5 emissions are projected
to be reduced by 47% in the year 2020 by replacing older
trucks with newer, cleaner trucks. This example illustrates
that voluntary, place-based actions can reduce emissions
from port activity and benefit public health in the
communities living near truck corridors.
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Section 1: Executive Summary
1.4. We can reduce emissions with effective strategies that are
currently available.
This assessment examined a suite of currently available strategies, including zero emissions (e.g.,
electric) technologies that can be used to develop voluntary programs to achieve additional emission
reductions. Some ports are already using the strategies in this assessment, including emerging
technologies, and their wider use could achieve even greater public health benefits.
Table 1-1 provides examples of some of the strategies in this assessment. The categories include
replacing older diesel fleets; operational improvements to reduce idling; and switching to cleaner fuels.
The strategies examined are not exhaustive; there may be other strategies that could also be effective at
a given port or for another application. For example, diesel retrofit technology has been a highly
effective strategy to reduce diesel emissions from school buses, transit buses, and long-haul trucks. EPA
did not include this technology option in its analysis since retrofitting port drayage trucks is less effective
than simply replacing them. While this assessment included a few strategies to improve operational
efficiency at ports, the focus was primarily on assessing technological strategies. EPA continues to
believe that operational strategies (e.g., reducing truck or locomotive idling) can be effective at reducing
diesel emissions.
Table 1-1. Examples of Strategy Scenarios Assessed
Sector
Scenario Description
Drayage Trucks
Replace older diesel trucks with trucks that meet cleaner EPA standards and
plug-in hybrid electric vehicles.
Rail
Replace older line-haul locomotive engines with cleaner technologies, including
electric locomotives.
Improve fuel economy.
Replace older switcher locomotive engines with cleaner technologies and
Generator Set (GenSet) technology.
Cargo Handling Equipment
Replace older yard truck, crane, and container handling equipment with cleaner
technologies, including electric technologies.
Harbor Craft
Replace or repower older tugs and ferries with cleaner technologies, including
hybrid electric vessels.
Ocean-going Vessels
Switch to lower sulfur fuel levels that are below EPA's regulatory standards, and
liquified natural gas for certain vessel types.
Utilize shore power to reduce hoteling of container, passenger, and reefer
vessels.
Apply Advanced Marine Emission Control Systems for container and tanker
vessels.
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Section 1: Executive Summary
1.5. Replace older, dirtier diesel vehicles and equipment first.
As noted earlier, EPA's regulations for new diesel vehicles and equipment are projected to significantly
reduce NOx and PM2.5 emissions into the future. However,older trucks and equipment are longstanding
fixtures of many port operations, and it will take many years before these fleets turn over to newer
technology. Accelerating the retirement of older port vehicles and equipment and replacing them with
the cleanest technology will reduce emissions and increase public health benefits beyond what would
be achieved without further voluntary actions.
Table 1-2 provides examples of the emission reduction potential of port strategies evaluated in this
assessment. For example, the potential for replacing older drayage trucks with cleaner diesel trucks is
significant, with NOx being reduced in 2020 by 19-48% and PM2.5 being reduced by 43-62% as
compared to the BAU case. In 2030, adding plug-in hybrid electric vehicle fleets resulted in even more
NOx and PM2.5 relative reductions. In another example, shore power reductions of NOx and PM2.5 were
also significant, with higher reductions being expected if shore power was applied to a larger portion of
OGVs.
Table 1-2. Examples of Effective Port Strategies to Reduce NOx and PM2.5 Emissions
Strategy Scenario
Percent reduction from BAU
NOx
PM2.5
2020
2030
2020
2030
Replace older drayage trucks
19-48%
48-60%
43-62%
34-52%
Replace older switcher locomotives
16-34%
17-43%
22-44%
24-47%
Replace older CHE
17-39%
13-25%
18-37%
12-25%
Replace or repower harbor craft
10-24%
25-38%
13-41%
28-37%
Reduce OGV hoteling emissions with shore power16
4-9%
7-16%
3-8%
7-16%
16 The shore power results also account for the emissions from generating electricity.
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Section 1: Executive Summary
1.6. C02 continues to increase, but effective strategies are available.
Port-related C02 emissions are projected to increase from current levels for all mobile sources in all
future years, as shown in Figure 1-4, in large part due to significant increases in economic trade and
activity. In addition, most of EPA's existing regulations and standards do not address C02 emissions for
port mobile source sectors.17
Figure 1-4. Total BAU C02 Emissions by Mobile Source Sector
8,000,000
7,000,000
6,000,000
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Section 1: Executive Summary
1.7. Reduction potential varies across mobile source sectors.
The voluntary strategies examined in this assessment do not achieve the same level of reductions across
all mobile source sectors and pollutants. Specifically, strategy scenarios that target land-side operations
(i.e., drayage trucks, locomotives, and CHE) are generally expected to result in greater emission
reductions than those targeting water-side operations (i.e., harbor craft and OGVs). This is illustrated in
Figure 1-5, which shows the total tons of NOx reduced from the 2020 and 2030 BAU cases assumed in
this assessment for land-side mobile source sectors.
Figure 1-5. Total NOx Reductions for Land-side Mobile Source Sectors
12,000
10,000
ro
a>
>-
8,000
6,000
4,000
2,000
0
I CHE
I Rail
I Dray
I Remaining
2020/A	2020/B	2030/A	2030/B
Land-side Sector NOx Reductions
The 2020 and 2030 BAU emission levels are the total bars for 2020 and 2030, with the amount of NOx
emissions reduced from CHE, rail, and drayage truck strategies shown in different colors respectively.
For each of these years, there were two strategy scenarios examined (i.e., Scenarios A and B),19 with
Scenario B being a more aggressive suite of strategies than Scenario A. The significant levels of
reductions shown above are especially important for the drayage truck and rail sectors since these are
the sectors that are typically closer to neighborhoods, schools, and other parts of communities located
in close proximity to ports.
In contrast, the scenarios for harbor craft and OGV sectors produced lower, but still significant,
reductions from these respective 2020 and 2030 BAU emission levels. In practice, the most effective
emission reduction strategies for any mobile source sector would be those that are tailored to the
specific circumstances of a given port area.
19 For example, "2020/A" shows the emissions reduced from Scenario A in 2020.
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Section 1: Executive Summary
1.8. Effective strategies are available for every type and size of port.
EPA recognizes that many strategies reduce diesel emissions across different port emission profiles, as
illustrated by the effective strategies examined at the assessment's representative sample of U.S.
seaports. But the assessment could also be informative for voluntary decisions at other seaports, Great
Lakes and inland river ports, or other freight and passenger facilities with similar mobile source profiles.
EPA conducted a stratification analysis to further understand the assessment results, since U.S. ports
vary in size, purpose, mix of vessels, and ground transportation. This analysis assessed the effectiveness
of strategies for ports of different types: container, bulk, and passenger; and sizes: large and small.20
The stratification analysis shows that not all strategies can be expected to have the same results at all
ports. For example, Figure 1-6 illustrates the effectiveness of reducing emissions while OGVs are
operating their auxiliary engines. For the year 2020, switching to a cleaner fuel was projected to be
more effective for reducing emissions from ships carrying bulk cargo while shore power technology was
more effective at reducing NOx emissions for passenger ships. Shore power is expected to be more
effective at reducing NOx emissions for a passenger port because passenger ships tend to call the same
ports frequently, making it more feasible to adapt these vessels to use shore power.21 In contrast, ships
carrying bulk cargo typically do not call on the same port as often in a given year.
Stakeholders should consider what combination of strategies should be used to reduce emissions for a
particular port area, depending upon the type of activity at a port.
Figure 1-6. NOx Reduction Effectiveness of Different Strategies at Different Kinds of Ports (Scenario B)
Auxiliary Fuel Change	Shore Power
8%
7%
6%
5%
4% 			¦	"2020
a) 5%
4%
3%
ll ; il
12030
0%
Bulk Container Passenger	Bulk	Container Passenger
20	These terms are not official classifications, but were defined and used in this analysis to differentiate among port sources
considered in this assessment.
21	The shore power results also account for the emissions from generating electricity.
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Section 1: Executive Summary
1.9. More focus is needed to reduce port-related emissions.
State and local governments, ports and port operators, Tribes, communities, and other stakeholders can
use this assessment as a tool to inform priorities and decisions about their port area. EPA's assessment
illustrates how more investment in reducing port-related emissions through voluntary place-based
programs can make a difference. This is important to consider in future planning, with U.S. port and
private sector partners projected to spend $154.8 billion on port-related infrastructure, with an
additional $24.8 billion of investment by the federal government in U.S. ports through 2020.22
Many of the strategies in this assessment are also eligible for existing federal funding sources, such as
EPA's Diesel Emissions Reduction Act (DERA) grant program, which has been instrumental in furthering
emission reductions through clean diesel projects located at ports and goods movement hubs. Since the
first appropriation of the DERA program in Fiscal Year 2008, $148 million has gone toward 129 grants to
fund projects at or near ports, with $80 million of this amount going to projects specifically at port
facilities, including CHE upgrades, drayage truck replacements, locomotive engine repowers, and more.
Other sources of federal funding that have been used for port-related emission reduction projects
include the Department of Transportation's Transportation Investment Generating Economic Recovery
(TIGER) and Congestion Mitigation and Air Quality Improvement (CMAQ) programs, and the Department
of Energy's Clean Cities program.
When assessing strategies for a specific
port area, here are some questions to
consider;
^ Is there a port-specific emission
inventory or clean air plan
available to inform decisions?
S What is the type and size of the
port?
S What source sectors are the
most significant diesel emitters
at the port?
/ How old are the diesel fleets of
each port sector?
J Is there an existing forum for
stakeholder participation?
22 Results of AAPA's Port Planned Infrastructure Investment Survey: Infrastructure investment plans for U.S. ports and their
private sector partners, 2016 through 2020, AAPA, April 6, 2016, http://aapa.files.cms-
plus.com/SeminarPresentations/2016Seminars/2016PRCommitteeMarchMeeting/2Q16-
2020%20Port%20Planned%20lnfrastructure%20lnvestment%20Survev%203-3-2016.pdf.
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Section 2: Introduction
2. Introduction
2.1. Purpose of Assessment
EPA developed this assessment to:
¦	Examine current and future emissions from a variety of diesel sources operating at ports;
¦	Explore the potential effectiveness of a range of emission reduction strategies; and
¦	Inform EPA's Ports Initiative and voluntary port-related efforts across the country.
Ports are a vital part of the U.S. economy, with seaports, Great Lakes ports, and inland river ports
serving as gateways for moving freight and passengers across the country and around the world.
Seaports alone account for more than 23 million jobs and seaport cargo activity accounts for 26% of the
U.S. economy.23 The expansion of the Panama Canal was completed in June 2016, doubling its
capacity.24 The U.S. Army Corps of Engineers estimates that Post-Panamax ships are expected to
dominate world trade and represent 62% of total container ship capacity by 2030.25 In addition, EPA
estimates that about 39 million people in the United States currently live in close proximity to ports.26
These people can be exposed to air pollution from diesel engines at ports and be at risk of developing
asthma, heart disease, and other health problems.27 This assessment is intended to update our
understanding of current and future trends in air pollution and climate emissions as well as the potential
impacts on the people living, working, and recreating near ports.
This assessment also explored the potential of a range of available strategies to reduce diesel emissions
from port-related activity. EPA recognizes that to reduce diesel emissions at the national level, it is
important to identify strategies that are effective for ports with different emission profiles. Ports serve
a variety of purposes as freight and passenger hubs on the seacoasts, freshwater lakes, and rivers across
the United States. Therefore, EPA assessed the effectiveness of a range of available emission reduction
strategies under different scenarios, such as replacing older diesel fleets with newer technologies,
23	American Association of Port Authorities. For further information, see http://www.aapa-
ports.ore/advocatine/content.aspx?ltemNumber=21150.
24	The expansion is anticipated to increase the number of ships passing through the canal as well as introduce a new larger size
of ships (i.e., post-Panamax), which are approximately one and a half times the size of and can carry over twice as much cargo
as ships that currently call at U.S. ports.
25	U.S. Army Corps of Engineers, U.S. Port and Inland Waterways Modernization: Preparing for Post-Panamax Vessels: Report
Summary, June 20, 2012.
26	EPA's analysis is based on overlaying and merging U.S. Census tract level geospatial data (Census Bureau 2010) with EPA's
National Emission Inventory (NEI 2011) ports data indicating that approximately 39 million people lived within 5 kilometers of
ports in the United States.
27	U.S. Environmental Protection Agency, Near Roadway Air Pollution and Health: Frequently Asked Questions, EPA-420-F-14-
044, 2014, https://www3.epa.gov/otaq/nearroadwav.htm.
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Section 2: Introduction
improving operational efficiency to reduce idling, and switching to cleaner fuels. EPA also examined the
potential of zero emissions (e.g., electric) vehicles and equipment and other emerging technologies.
Finally, this assessment can support EPA's Ports Initiative28 and voluntary port-related efforts across the
country. While EPA's regulations have substantially reduced emissions and continue to improve air
quality as new vehicles, engines, and equipment enter the in-use fleet, the large number and high
activity levels of older fleets at port facilities warrant further action. It is critical to focus future efforts
on improving the lives and health of communities impacted by ports and providing place-based options
that improve environmental performance in port areas.
EPA developed this assessment in consultation with the Mobile Sources Technical Review Subcommittee
(MSTRS) of the Clean Air Act Advisory Committee (CAAAC)29 over a two-year period. In 2014, the MSTRS
formed a Ports Workgroup to develop recommendations for developing an EPA-led voluntary ports
initiative, and effectively measuring environmental performance at ports. The MSTRS Ports Workgroup
included technical and policy experts from a range of stakeholders, including industry, port-related
agencies, communities, Tribes, state and local governments, and public interest groups.30
2.2. Public Health and Climate Impacts
Emissions from diesel engines, especially particulate matter (PM), nitrogen oxides (NOx), 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. EPA has determined that diesel engine exhaust emissions are a likely human carcinogen,31
and the World Health Organization has classified diesel emissions as carcinogenic to humans.32
Moreover, many ports and port-related corridors are located in areas with a high percentage of low
income and minority populations who are often disproportionately impacted by higher levels of diesel
emissions.33 NOx also contributes to the formation of ozone and PM through chemical reactions, and
many ports and related freight corridors and facilities are located in nonattainment or maintenance
28	For more information, see https://www.epa.eov/ports-initiative.
29	Chartered under the Federal Advisory Committee Act (FACA), CAAAC was established to advise EPA on issues related to
implementing the Clean Air Act, as amended in 1990. Learn more at: https://www.epa.gov/caaac.
30	For further information on MSTRS Ports Working Group participants, see https://www.epa.gov/sites/production/files/2016-
06/documents/portsinitiativewkgrp 2016.pdf.
31	Health Assessment Document for Diesel Engine Exhaust, prepared by the National Center for Environmental Assessment for
EPA, 2002.
32	Diesel Engine Exhaust Carcinogenic, International Agency for Research on Cancer (IARC), World Health Organization, June 12,
2012, http://monographs.iarc.fr/ENG/Monographs/voll05/.
33	For example, EPA conducted a screening-level modeling analysis in 2008 of 45 nationally representative marine harbor areas
(including port authority and private port operations) in support of EPA's 2010 emission standards for new marine
compression-ignition engines at or above 30 liters per cylinder. The modeling analysis estimated that at least 18 million
people, including a disproportionate number of low-income households, African-Americans, and Hispanics, living in the
vicinity of these 45 ports were exposed to ambient diesel PM levels that were at least 0.2 ng/m3 above levels in areas farther
from these facilities. See 75 FR 22896 (April 30, 2010).
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Section 2: Introduction
areas for EPA's ozone and fine particulate matter (PM2.5) national ambient air quality standards
(NAAQS). Exposure to ozone can aggravate asthma and other respiratory conditions, with children, the
elderly, outdoor workers, and people with heart and lung conditions being most at risk.34
Port-related diesel emissions—such as carbon dioxide (C02) and black carbon—also contribute to
climate change. Research literature increasingly documents the effects that climate change is having
and will increasingly have on air and water quality, weather patterns, sea levels, human health,
ecosystems, agricultural crop yield, and critical infrastructure.35 Black carbon is a component of PM and
is linked to a range of adverse climate impacts, including increased temperatures and accelerated
snowmelt.36 Other health impacts that are projected from climate change include heat stroke and
dehydration from more frequent and longer heat waves, asthma attacks, illnesses from an increase in
water and food-borne pathogens, and exacerbation of other respiratory and cardiovascular health
effects.37
These are significant impacts that further highlight the importance of understanding current and future
port-related diesel emissions and identifying opportunities to reduce these emissions.
2.3. Mobile Source Sectors Analyzed
This assessment focused on the potential of strategies to reduce emissions from diesel-powered
vehicles and equipment.38 More details are included below on the five mobile source sectors that were
analyzed.
2.3.1. Drayage Trucks
Drayage trucks are combination short-haul trucks that move cargo into and out of ports. Drayage trucks
typically travel short distances to and from the port to a nearby rail yard or distribution center. This
truck activity typically involves significant idle or creep time to enter and exit a port as well as load or
unload containers or other cargo.39 Drayage trucks are generally older than the average truck fleet,
since they are usually sold by long-haul trucking firms that tend to have newer fleets and a much faster
turnover rate.
34	Third Report to Congress: Highlights from the Diesel Emission Reduction Program, EPA-420-R-16-004, February 2016; and
EPA's Health Assessment Document for Diesel Engine Exhaust, 2002.
35	U.S. Environmental Protection Agency, Climate Change Indicators in the United States, 4th edition, 2016,
https://www.epa.gov/climate-indicators.
36	For further information on black carbon, see EPA's website at: https://www3.epa.eov/blackcarbon/.
37	United States Global Change Research Program, The Impacts of Climate Change on Human Health in the United States: A
Scientific Assessment, April 2016, http://www.elobalchanee.gov/health-assessment.
38	While other emission sources exist at or near ports (such as electricity generators, boilers, and refineries), these were not
considered in this mobile source assessment.
39	This type of drayage activity includes taking significant time to move short distances, with multiple starts and stops.
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Section 2: Introduction
2.3.2.	Rail
The rail emission sources in this assessment include switcher and line-haul locomotives. Switchers move
rail cars short distances within a rail yard,40 and line-haul locomotives travel out of the port to distant
locations. Switchers connect individual rail cars to form the trains that line-haul locomotives move out of
the port.
2.3.3.	Cargo Handling Equipment
Cargo handling equipment (CHE) are located on a port and move cargo on and off ocean-going vessels
(OGVs) and harbor craft. CHE move cargo around the port so that it can be loaded onto trucks and rail
cars. There are many different kinds of CHE, including forklifts, cranes, and bulk handling equipment
(e.g., tractors, loaders, etc.). This assessment focused on a subset of diesel-powered CHE, specifically
yard tractors, rubber tire gantry (RTG) cranes, and container handlers (top picks and side picks).
2.3.4.	Harbor Craft
Harbor craft assist in moving OGVs around the harbor, move cargo and people into and out of the port
harbor area, and provide fuel to OGVs; they also transport crew and supplies to offshore facilities.
Harbor craft are vessels with engines less than 30 liters per cylinder and are classified as Category 1 and
2 vessels. There are many different kinds of diesel-powered harbor craft, including commercial fishing
boats, government vessels, and dredges. This assessment focused on tugs and ferries.
2.3.5.	Ocean Going Vessels
OGVs move cargo and people into and out of a port and typically travel long distances to or from foreign
ports or may travel to or from other domestic ports. OGVs are vessels with engines of 30 liters per
cylinder or more (i.e., Category 3 vessels); many of the ship types considered in this assessment are
described in Table 2-1.
Table 2-1. Ocean-Going Vessel Ship Types
Ship Type
Description
Auto Carrier
Self-propelled dry-cargo vessel that carries containerized automobiles
Bulk Carrier
Self-propelled dry-cargo ship that carries loose cargo
Container Ship
Self-propelled dry-cargo vessel that carries containerized cargo
General Cargo
Self-propelled cargo vessel that carries a variety of dry cargo
Passenger
Self-propelled cruise ships
Reefer
Self-propelled dry-cargo vessel that often carries perishable items
Roll-on/Roll-off
Self-propelled vessel that handles cargo that is rolled on and off the ship
Tanker
Self-propelled liquid-cargo vessels including chemical tankers, petroleum product
tankers, liquid food product tankers, etc.
40 Please note that in this assessment, on-dock rail is generally characterized as a rail yard in a port.
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Section 2: Introduction
This assessment considered OGV diesel emissions for both propulsion and auxiliary engine activity. The
main propulsion engines on most large ships can stand over three stories tall and run the length of two
school buses. Auxiliary engines on large ships typically range in size from small portable generators to
locomotive size engines.41
2.4. Pollutants Characterized in This Work
Port-related emissions and reductions were estimated for several different criteria pollutants and
precursors, climate change pollutants, and air toxics. Criteria pollutants include common air pollutants
that are identified by the Clean Air Act, such as PM2.542 and ground-level ozone; precursors are air
pollutants that form criteria pollutants, such as NOx and volatile organic compounds (VOCs) which are
emissions that combine to form ground-level ozone. Climate change pollutants include GHGs that
contribute to global warming, while air toxics are hazardous air pollutants that are known or suspected
to cause serious health effects.
The following list includes the specific pollutants characterized in this assessment:
¦	Criteria pollutants and precursors
~	NOx
~	PM2.5
~	sulfur dioxide (S02)
~	VOCs43
¦	Climate change pollutants
~	carbon dioxide (C02)
~	black carbon (BC)
¦	Air toxics
~	benzene
~	acetaldehyde
~	formaldehyde
S02 was not analyzed for the non-OGV mobile source sectors since these sectors in the United States
currently use ultra-low sulfur diesel (ULSD), which is a cleaner-burning diesel fuel that has significantly
reduced the S02 emitted by these sources. S02 emissions from OGVs were estimated because although
these vessels use low sulfur distillate fuels at ports (up to 1000 ppm sulfur), further reductions may be
gained from use of even lower sulfur fuels. In addition, EPA determined that it is premature to evaluate
air toxics that are emitted by OGVs due to data limitations identified with projecting emissions for these
41	Auxiliary boilers were not included in this assessment as they were considered to be a much smaller source of emissions. The
energy consumption of auxiliary boilers is not considered significant, and these engines are not prevalent on every ship.
42	PM2.5 are particles with an aerodynamic diameter less than or equal to a nominal 2.5 micrometers.
43	NOx and VOCs are precursors of ozone and PM2.5 criteria pollutants. S02 is a precursor for PM2.5, as well as a criteria
pollutant.
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Section 2: Introduction
sources, particularly for the future years of interest in this assessment. Air toxic emissions from OGVs
are an area that warrants further research and analysis.
2.5. Overview of Assessment Approach
This assessment was designed to provide a national picture of port-related emission trends and the
potential for emission reduction strategies based on estimated emissions from a representative sample
of 19 seaports. The ports selected featured a range of diverse characteristics, such as different sizes,
types of activity, and geographic location. Baseline and Business as Usual (BAU) national scale
inventories were developed from aggregating inventories from the port areas, followed by the analysis
of various strategies to reduce port-related mobile source emissions.
Separate emission inventories were developed for the drayage truck, rail, CHE, harbor craft, and OGV
sectors. Baseline inventories were developed for the year 2011, while BAU inventories were developed
for all pollutants for 2020 and 2030, and the 2050 BAU inventory was developed for C02 only. Table 2-2
summarizes the mobile source emission sectors included in this assessment, as well as the pollutants
and geographic area covered by each sector.
Table 2-2. Summary of Sources, Pollutants, and Geographic Area Covered by Assessment
Mobile Source
Sector
Type of Emission
Source
Pollutants Analyzed
Geographic Area Covered
Drayage Trucks
On-road Class 8
diesel trucks
NOx, PM2.5, VOCs, CO2,
BC, and select air toxics
All drayage activity within 0.5 km (0.3 mi)
from port boundary.
Rail
Line-haul and
switcher diesel
locomotives
NOx, PM2.5, VOCs, CO2,
BC, and select air toxics
All rail activity within 0.5 km from port
boundary.
CHE
Diesel-powered
CHE
NOx, PM2.5, VOCs, CO2,
BC, and select air toxics
All CHE activity assumed to occur on-port.
Harbor Craft
Diesel-powered
tugs and ferries
NOx, PM2.5, VOCs, CO2,
BC, and select air toxics
All harbor craft activity within 5 km (3 mi)
from port boundary.
OGV
Diesel propulsion
and auxiliary
engines
NOx, PM2.5, VOCs, SO2,
CO2, and BC
All OGV activity within 5 km from port
boundary.
The geographic boundaries of each sector used in this assessment contributed to the relative differences
between the amounts of emissions between sectors. Mobile source impacts along port-related
transportation corridors (e.g., highways and rail lines) are an important environmental challenge, but
this assessment did not focus on corridor impacts.
The data sources and methodology for developing these inventories varied by sector, as summarized in
Table 2-3 below. The assessment relied primarily on existing EPA data and models or other publically
available data.
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Section 2: Introduction
Table 2-3. Summary of Data and Methodology Sources for Baseline and BAU Emission Inventories
Sector
Primary Sources for Baseline
(2011)
Primary Sources for BAU Projections
(2020, 2030, 2050)
Drayage Trucks
DrayFLEET
USACE Waterborne Commerce Statistics
FHWA Freight Analysis Framework
2008 Research Triangle Institute (RTI)
regional growth rates
EPA MOVES2010b model
Rail
EPA National Emissions Inventory
Published rail emission inventories
2008 RTI regional growth rates
EPA Locomotive and Marine Emission
Standards Rulemaking
CHE
Published CHE emission inventories
USACE Waterborne Commerce Statistics
2008 RTI regional growth rates
EPA NONROAD2008a model
Harbor Craft
EPA National Emissions Inventory
2008 RTI regional growth rates
EPA Locomotive and Marine Emission
Standards Rulemaking
OGV
EPAC3 Regulatory Impact Analysis
USACE Entrances and Clearances
Lloyd's Register of Ships
Published OGV emission inventories
2008 RTI bunker fuel growth rates
EPA C3 Regulatory Impact Analysis
EPA North America Emission Control Area
Standards
Further details on these sources are included in Sections 3 and 4 of the report. It should be noted that
this assessment was not intended to provide specific data for local decision-making at individual ports or
specific neighborhoods; the assessment does not report inventory impacts for a particular port.
2.6. Port-related Strategies Analyzed
As described in Sections 5 and 6, based on a literature review and consultations with industry and other
experts, EPA developed a matrix of port-related emission reduction strategies for more detailed
analysis. Two emission reduction scenarios were developed for each mobile source sector and are
described as follows:
¦	Scenario A reflected an increase in the introduction of newer technologies in port vehicles and
equipment beyond what would occur through normal fleet turnover. Operational strategies in
Scenario A reflected a reasonable increase in expected efficiency improvements.
¦	Scenario B reflected a more aggressive suite of strategies as compared to Scenario A. Scenario B
was intended to further accelerate the introduction of clean diesel and zero emissions vehicles and
equipment, in addition to other fuels and technologies. Operational strategies in Scenario B assume
further operational efficiency improvements beyond Scenario A.
Both scenarios would necessitate a major investment in new technologies, with Scenario B requiring a
larger investment than Scenario A. In selecting strategies, EPA qualitatively considered several factors,
such as capital costs, market barriers, and potential for market penetration by analysis year. However,
an in-depth cost-benefit analysis was not conducted.
Table 2-4 provides an overview of the strategy scenarios that were analyzed in this assessment.
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Section 2: Introduction
Table 2-4. Overview of Strategy Scenarios
Sector
Strategy
Scenario Summary Description
Drayage
Trucks
Technological
Truck replacement strategies to accelerate turnover to cleaner
EPA standards and plug-in hybrid electric vehicles (PHEVs).
Operational
Reduced gate queues.
Rail
Line-haul Technology
Locomotive engine replacement strategies, including electric
locomotives.
Line-haul Operational
Fuel economy improvements.
Switcher Technology
Switcher locomotive engine replacement strategies, including
use of GenSets.
CHE
Yard Truck
Yard truck replacement strategies, including battery electric
vehicles.
Rubber Tire Gantry Crane
Crane replacement strategies, including electric cranes.
Container Handler
Container handling equipment replacements, including electric
equipment.
Harbor
Craft
Tug
Tug repower and replacement strategies, including hybrid
electric vessels.

Ferry
Ferry repower and replacement strategies, including hybrid
electric vessels.
OGV
Fuel Change in Propulsion Engines
Fuel use switch strategies to 500 ppm sulfur fuels, 200 ppm
sulfur fuels, and liquefied natural gas (LNG) for bulk, container,
passenger, and tanker vessels.
Fuel Change in Auxiliary Engines
Fuel use switch strategies to ultra-low sulfur diesel (ULSD) fuel
and LNG for bulk, container, passenger, and tanker vessels.
Shore Power
Shore power for container, passenger, and reefer vessels.
AMECS
Advanced Marine Emission Control Systems (AMECS) for
container and tanker vessels.
Reduced Hoteling
Hoteling time reduction for container vessels.
2.7. Organization of Assessment Report
This report is organized as follows:
¦	Section 3 describes how the 2011 baseline emission inventory for this assessment was developed,
and additional supporting documentation is included in Appendix A.
¦	Section 4 describes how the BAU inventories for 2020, 2030, and 2050 were developed, and
Appendix B contains further details on the BAU methodology.
¦	Section 5 includes an assessment of the range of available port-related emission reduction
strategies, and identifies the most effective strategies for the years 2020 and 2030 for NOx, PM2.5,
and C02 reductions. In addition, this section includes a generic analysis of the potential of emission
reductions for all mobile source sectors at a hypothetical port.
¦	Section 6 contains the sector-by-sector analysis of different strategies under Scenarios A and B. See
Appendix C for further information on the development of the strategy analysis methodology.
¦	Section 7 includes an analysis that stratifies the emission reduction results from the assessment by
port type and size, with additional details in Appendix D.
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Section 3: Baseline Emission Inventory Development
3. Baseline Emission Inventory Development
3.1.	Overview
Baseline emission inventories for 2011 were developed for the five mobile source emissions sectors.
Each sector inventory was developed separately using the best available data and methodologies for this
national scale assessment. An overview of the data, methodologies, and results for each of the five
sectors is detailed below. As noted in Section 2, the totals presented in each of the results sections are
the aggregated baseline emissions of all port areas included in this assessment. Additional details for the
baseline emission inventories are included in Appendix A.
3.2.	Drayage Trucks
The 2011 baseline inventory for the drayage truck sector was developed using the EPA DrayFLEET
Model.44 Port-specific truck activity was estimated from total freight activity at each port, as reported in
the U.S. Army Corps of Engineers' (USACE) Waterborne Commerce Statistics, and allocated to the share
of freight moved by truck using the Federal Highway Administration's (FHWA's) Freight Analysis
Framework (FAF).
3.2.1. Methodology and Available Data
The baseline emission inventories were calculated using DrayFLEET, a model designed to estimate the
impact of management practices, terminal operations, and cargo volume on drayage truck emissions
and activity. Some of the primary inputs to the model include an estimate of annual containerized
freight throughput in twenty-foot equivalent units (TEUs) and the distance traveled to common off-port
destinations. A secondary input is tons of truck freight throughput, which captures bulk, liquid, and
other kinds of drayage truck traffic.
Annual port-specific freight activity data came from Waterborne Commerce Statistics on TEUs45 and
tonnage46 by port for the 2011 base year. Since this source only includes data on domestic empty
containers and not foreign empty containers, data on foreign empty containers were collected
separately from ports or other sources.47
The percentage of containers and non-containerized freight moved by drayage at each port was
estimated using the 2012 FAF48 and applied to the 2011 base year data. FAF identifies the port of export,
the domestic mode of transportation, and the foreign mode. For freight moving via water in the foreign
44	U.S. Environmental Protection Agency, SmartWay DrayFLEET, Truck Drayage Environment and Energy Model: Version 2.0
User's Guide, EPA Report EPA-420-B-12-065, June 2012.
45	Available at: http://www.navieationdatacenter.us/wcsc/bv portnamesll.html.
46	Available at: http://www.navigationdatacenter.us/db/wcsc/archive/xls/manll/.
47	Available at: http://aapa.files.cms-
plus.com/Statistics/N0RTH%20AMERICAN%20P0RT%20C0NTAINER%20TRAFFIC%202Qll.pdf.
48	Available at: http://www.ops.fhwa.dot.gov/freieht/freight analvsis/faf/.
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Section 3: Baseline Emission Inventory Development
mode of transportation, exports and imports were combined and the percentage moving by truck for
the domestic mode was estimated. TEUs moved by drayage were converted to number of truckloads by
estimating the average TEUs per container, which was 1.75 for most ports. The number of non-
containerized truckloads was determined based on the cargo densities and payload estimates by
commodity.
Using the activity estimates described above, DrayFLEET was used to estimate port-specific drayage
emission inventories. Where the information was available, port-specific gate queues and average
marine terminal transaction times were also used; the default values were otherwise retained. The age
distribution of drayage trucks come from EPA's MOVES2010b national default age distribution for
combination short-haul trucks.
In addition to the on-port emissions, this assessment included a 0.5 km (0.3 mi) port boundary
extension, modeled separately. This was accomplished by estimating the distance drayage vehicles
travel inside the port and the distance they travel outside the port within a 0.5 km of the port boundary.
A visual inspection of port maps was made to estimate these distances. For more details on the 2011
baseline analysis for drayage trucks, including pollutants not estimated in DrayFLEET, please see
Appendix A.
3.2.2. Results
The total 2011 baseline emissions for the drayage truck sector for this assessment are given in Table 3-1.
Table 3-1. Baseline 2011 Emissions for Drayage Trucks, Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
9,819
811
785
625
1,486,914
32
7
77
3.3. Rail
The 2011 baseline inventory for the rail sector was derived from published port emission inventories
where available and from EPA's 2011 National Emissions Inventory (NEI) for all other ports. This sector
was divided into two categories: rail line and rail yard. Rail line corresponds to emissions from line-haul
locomotives and rail yard corresponds to switcher locomotive emissions. The emission inventories
include both emissions that occur within port boundaries and emissions that occur within a 0.5 km
extension of rail lines leading to and from the port.
3.3.1. Methodology and Available Data
There were four ports with published rail inventories that were included in this assessment. However,
in some cases, these published inventories did not include all the pollutants covered for this assessment
(i.e. VOC, C02, black carbon (BC), acetaldehyde, benzene, and formaldehyde). Inventories for these
pollutants were calculated from speciation factors, using methodologies discussed in Appendix A.
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Section 3: Baseline Emission Inventory Development
Version 1 of EPA's 2011 NEI was used to develop the baseline rail emissions estimates for the other
ports.49 In the NEI, emissions are reported by source classification codes (SCCs). Table 3-2 shows the rail
sector SCCs and their categories (point and nonpoint). Rail yards are categorized in the NEI as point
sources.50 It should be noted that the SCCs do not distinguish between the types of rail activities;
therefore, there is no way to explicitly differentiate the port-related locomotive emissions from other
rail emissions in the NEI.
Table 3-2. Relevant SCCs for Rail Inventory Analysis
SCC
NEI Data Category
Description
2285002006
Nonpoint
Line-haul Locomotives: Class 1 Operations
2285002007
Nonpoint
Line-haul Locomotives: Class II / III Operations
28500201
Point
Yard Locomotives
Using NEI port and rail shapefiles,51 the rail lines were mapped in a geographic information system (GIS)
program. These shapefiles were updated for some ports where better data were available. Rail yards
were also mapped using latitude and longitude data associated with each rail yard in the NEI point
source database. The rail lanes used in this assessment extend 0.5 km from the port boundaries to
include line-haul emissions. The ratio of the area of the 0.5 km rail line compared to the whole rail line
length in the NEI was used to adjust the emissions proportionally. For example, if 10% of a rail line
length lies within the 0.5 km buffer, 10% of the total line haul emissions assigned to that shape were
allocated to the port.
The 2011 NEI database and shapefiles identify counties with Federal Information Processing Standard
(FIPS) codes. For the rail line inventory, total county locomotive emissions were allocated to each rail
segment according to the length of the line within the assessment area. The rail yard inventory was then
calculated by summing all rail emissions that occurred within the assessment area.
Using these steps, the emissions for the rail lines and rail yards in this area were estimated. However,
these emissions were limited to those pollutants quantified in the first version of the 2011 NEI, including
NOx, VOCs, PM2.5, benzene, acetaldehyde, and formaldehyde. The other pollutants assessed in this
assessment (i.e., BC and C02) were estimated as described in Appendix A.
3.3.2. Results
The total 2011 baseline emissions for the rail sector are given in Table 3-3.
49	Version 1 was the latest version available at the time of this analysis. The 2011 NEI is available at: https://www.epa.eov/air-
emissions-inventories/2011-national-emissions-inventorv-nei-data.
50	There is an additional SCC in the NEI for nonpoint yard locomotives (2285002010). However, all EPA estimates in the NEI for
yard locomotive emissions are recorded as point sources, so the additional SCC was not included in this assessment.
51	Available at: https://www.epa.gov/air-emissions-inventories/2011-national-emissions-inventorv-nei-documentation.
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Section 3: Baseline Emission Inventory Development
Table 3-3. 2011 Baseline Emissions for Rail, Tons per Year
Mode
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
Rail Yard
1,248
35
86
27
60,455
1
0
2
Rail Line
1,491
46
81
36
83,806
1
0
3
Total
2,739
81
167
63
144,261
2
0
5
3.4. Cargo Handling Equipment
The 2011 baseline inventory for the cargo handling equipment (CHE) sector was based on published CHE
emission inventories. A regression model was developed to establish the relationship between cargo
throughput and CHE emissions using the published inventories. This was then applied at all ports
without a published inventory.
3.4.1. Methodology and Available Data
A regression model was used to estimate CHE emissions based on the observed relationship between
port cargo throughput and CHE emissions. This involved:
¦	Collecting recent CHE emission inventories
¦	Filling any gaps to determine total annual CHE emissions for all pollutants considered
¦	Collecting cargo throughput in both tonnage52 and TEUs53 from USACE
¦	Processing USACE data to represent throughput by various conveyance methods at ports
¦	Building statistical regression relationships of emissions against throughput for known ports
¦	Using these relationships to estimate CHE emissions at the remaining ports
Four published inventories formed the basis of this regression analysis. Since there are many different
kinds of CHE and each published inventory included different kinds of CHE, the analysis was performed
using total CHE emissions instead of using emissions from individual equipment types.
Regression was performed to determine trends of NOx, VOC, PM2.5, and C02 emissions in tons per year
against cargo throughput. Three different methods were explored, each regressing total CHE emissions
for each pollutant against the following cargo throughput quantifications:
¦	Method 1: cargo throughput categorized as bulk, container, liquid, or other
¦	Method 2: cargo throughput in total non-container tonnage and number of TEUs
¦	Method 3: total tonnage of cargo throughput, excluding conveyance type
When compared back to the published inventories, the success of each method varied by pollutant.
Lacking a clear distinction in the prediction capabilities between the three methods, an unweighted
average of the predictions from the above three methods was employed to calculate the inventories at
52	Available at: http://www.navigationdatacenter.us/db/wcsc/archive/xls/manll/.
53	Available at: http://www.navieationdatacenter.us/wcsc/bv portnamesll.html.
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Section 3: Baseline Emission Inventory Development
all of the modeled ports. The results presented in the next section include values from the four
published inventories combined with the modeled results for the other ports.
This regression model has a similar level of detail as the rail and harbor craft analysis, which relied on
NEI values. As with those sectors, it does not allow characterization of emissions by equipment age, fuel
type, terminal type, existing use of control technology, or other discriminators. For more details on the
CHE baseline inventory and why the NEI was not used for this sector, see Appendix A.
3.4.2. Results
The total 2011 baseline emissions for the CHE sector are given in Table 3-4.
Table 3-4. 2011 Baseline Emissions for CHE, Tons per Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
6,701
258
361
199
893,188
18
7
40
3.5. Harbor Craft
The 2011 baseline inventory for the harbor craft sector was derived from the 2011 NEI for all ports. This
sector includes emissions from harbor craft that occur both within the port boundaries in addition to a 5
km buffer zone surrounding each port. The results are reported by two activity modes: maneuvering and
cruise.
3.5.1. Methodology and Available Data
The term "harbor craft" is used synonymously for all vessels with Category 1 and Category 2 (C1/C2)
engines, including tugs, ferries, commercial fishing boats, government vessels, work boats, and dredges.
Version 2 of EPA's 2011 NEI was used to develop the baseline harbor craft emissions estimates for all
ports.54 Existing port inventories were not used to assess harbor craft emissions because most port
inventories only included harbor craft emissions related to their own port operations, and did not
include other harbor craft activity, such as activity occurring at private terminals. The NEI includes such
activity and was used to develop the baseline harbor craft inventory for this assessment.
In the NEI, emissions are reported by source classification codes (SCCs). Table 3-5 shows the harbor craft
sector SCCs and their emission type codes (maneuvering or cruise). Maneuvering emissions occur within
a port's boundaries and cruise emissions occur at sea. The NEI does not estimate at-berth emissions for
C1/C2 as it assumes that neither propulsion nor auxiliary engines would be operating at dockside.
54 Available at: https://www.epa.eov/air-emissions-inventories/2011-national-emissions-inventorv-nei-data.
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Section 3: Baseline Emission Inventory Development
Table 3-5. Relevant SCCs for Port Inventory Analysis
see
Emission Type Code*
Description
2280002100
M
Harbor Craft at Port
2280002200
C
Harbor Craft underway
* Emission type codes for C1/C2 vessels are defined as M=maneuvering (in port) and C=cruise (out of port).
Using NEI port and rail shapefiles,55 near-port shipping lanes were mapped in a GIS program. These shapefiles
were updated for some ports where better data were available. The off-port corridors used in this
assessment extend 5 km from the port boundaries in order to include harbor craft cruising emissions. Since
all ports have differently shaped and sized marine corridors leading to them, having a uniform 5 km buffer
zone allowed future reduction strategies to be modeled on the same basis at each port. However, since the
NEI's defined shipping lanes extended beyond 5 km for most ports, the emissions assigned by the NEI to each
shipping lane were scaled proportionally. For example, if 10% of a shipping lane shape lies within the 5 km
buffer, 10% of the total cruising emissions assigned to that shape were allocated to the port.
The emission inventories for this sector were determined by summing the maneuvering emissions at
each port combined with the proportion of cruise emissions allocated to each port. However, these
emissions were limited to NOx, VOCs, and PM2.5. The other pollutants in this assessment (i.e. BC, C02,
benzene, acetaldehyde, and formaldehyde) were estimated as described in Appendix A.
3.5.2. Results
The total 2011 baseline emissions for the harbor craft sector are given in Table 3-6.
Table 3-6. 2011 Baseline Emissions for Harbor Craft, Tons per Year
Mode
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
Cruise
24,239
777
555
598
1,800,965
26
7
52
Maneuver
23,541
755
539
581
1,749,103
30
8
60
Total
47,780
1,532
1,093
1,179
3,550,068
56
15
112
3.6. Ocean Going Vessels
The 2011 baseline inventory for the ocean going vessel (OGV) sector was calculated using EPA's
Category 3 Marine Engine Rulemaking (C3 RIA)56 methodology, which used energy-based emission
factors together with activity profiles for each vessel. The shipping activity came from USACE's Entrances
and Clearances data, and four activity modes were included: reduced speed zone (RSZ), maneuvering,
hoteling, and at anchor.
55	Available at: https://www.epa.gov/air-emissions-inventories/2011-national-emissions-inventorv-nei-documentation.
56	U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Category 3
Marine Diesel Engines, EPA Report EPA-420-R-09-019, December 2009. Available at:
http://www.epa.gov/otaq/regs/nonroad/marine/ci/420r09019.pdf.
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Section 3: Baseline Emission Inventory Development
3.6.1. Methodology and Available Data
The OGV sector includes emissions from Category 3 (C3) commercial marine vessels' main propulsion
engines and auxiliary engines. C3 vessels are propelled by engines with 30 liters per cylinder
displacement or more. Emissions for each ship and for each mode were estimated for both main
propulsion and auxiliary engines using the following equation:
E = PxLFxAxEF	Eq. 3-1
Where
E = Emissions (grams [g]),
P = Maximum Continuous Rating Power (kilowatts [kW]),
LF = Load Factor (percent of vessel's total power),
A = Activity (hours [h]) (hours/call * # of calls), and
EF = Emission Factor (grams per kilowatt-hour [g/kWh]).
The other components of the above equation are dependent on individual ship characteristics, such as
ship type, size, power, and cruise speed. The ship calls from the 2011 USACE Entrances and Clearances
data were matched to Lloyd's data57 to determine the maximum continuous power rating, load factor,
and emission factor that should be applied to each activity record.
The emission factors were based on the C3 RIA and vary by engine type (propulsion or auxiliary), tier,
fuel type, fuel sulfur level, ship type, and load factor. In addition to the other criteria pollutants and
precursors, S02 is analyzed for OGVs. This is because the fuel that OGVs use has a much higher sulfur
content than the other sectors. While the introduction of the North American Emission Control Area
(ECA) fuel sulfur limit (1000 ppm sulfur) will reduce S02 in projected years, additional reductions may be
gained from the use of even lower sulfur fuels. It was assumed that all ships' propulsion engines and
most ships' auxiliary engines operated on heavy fuel oil (HFO) with a sulfur level of 2.7% in the 2011
baseline year.58
Cruise emissions were not included since ships were expected to be operating at speeds less than cruise
speed within the areas of interest for this assessment (which focused on in-port activity and as ships
approach or leave the port entrance) for safety and/or environmental reasons. However, activity in
reduced speed zones (RSZs), maneuvering, hoteling, and at anchorage was included. Most hoteling and
maneuvering times come from Marine Exchange/Port Authorities data as detailed in a 1999 report59 that
described how to calculate marine vessel activity at deep seaports and contained detailed port activities
of eight deep seaports. More recently published emission inventories that contain data on hoteling and
57	Produced by IHS Global Limited and available at: http://www.sea-web.com.
58	It was assumed that ships that did not use HFO in their auxiliary engines used distillate instead. For more details, see
Appendix A.
59	ARCADIS Geraghty & Miller, Commercial Marine Activity for Deep Sea Ports in the United States, EPA Report EPA420-R-99-
020, September 1999. Available at http://www.epa.eov/otaq/models/nonrdmdl/c-marine/r99020.pdf.
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Section 3: Baseline Emission Inventory Development
maneuvering times were used where appropriate. See Table 3-7 for a description of the various activity
modes and their associated analysis. Further details on the activity data sources, emission boundaries,
derivation of emission factors, the definition of RSZ boundaries, and the calculation of RSZ,
maneuvering, hoteling, and anchorage activity may be found in Appendix A.
Table 3-7. Vessel Movements and Time-ln-Mode Descriptions
Summary Table Field
Description
Call
A call is one entrance and one clearance. Since the USACE Entrances and Clearances
data do not provide a record for an entrance where no foreign cargo discharged or a
record of a clearance where no foreign cargo is loaded at a port, the number of
entrances and clearances may not be the same. Therefore, the number of calls were
taken as the maximum of the entrances or clearances at a port as grouped by ship type,
engine type, and deadweight tonnage bin.
Reduced Speed Zone
(RSZ) (hr/call)
Time when a ship reduces speed before entering a port. This can be a long distance
down a river or channel and generally ends at the port entrance.
Maneuver (hr/call)
Time when a ship is being berthed or de-berthed, traveling to an anchorage or moving
between berths. Maneuvering is assumed to occur within the port area, generally
beginning and ending at the entrance of the port. This will include shifts within a port
area moving from one berth to another. For purposes of calculating load factors,
maneuvering was assumed to occur at an average speed of 5.8 knots. Maneuvering
times were taken from the typical port data or calculated from published inventories.
Hoteling (hr/call)
Hoteling is the time at berth when the vessel is operating auxiliary engines only.
Auxiliary engines are operating at some load conditions the entire time the vessel is
manned, but peak loads will occur after the propulsion engines are shut down. The
auxiliary engines are then responsible for all onboard power or are used to power off-
loading equipment, or both.
Anchorage (hr/call)
If the port data included anchorage, it is broken out separately for this analysis. Some
emission reduction techniques cannot be applied while at anchorage. This mode was
ignored if not specifically identified.
Emission inventories for air toxics were not developed for OGVs due to data limitations. Air toxic
emissions from OGVs is an area that warrants further research and analysis.
3.6.2. Results
The total 2011 baseline emissions for the OGV sector are given in Table 3-8.
Table 3-8. 2011 Baseline Emissions for OGVs, Tons per Year
Mode
NOx
PM2.5
VOC
BC
CO2
SO2
RSZ
3,838
324
169
10
160,787
2,582
Maneuver
3,661
361
296
11
157,023
2,375
Hotel
26,016
2,209
836
66
1,408,951
20,115
Anchor
44
4
1
0
2,345
32
Total
33,560
2,897
1,302
87
1,729,106
25,104
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Section 3: Baseline Emission Inventory Development
3.7. Summary of Baseline Inventory Results
The above sections listed the baseline emission inventory results for this assessment by sector and by
operating mode or subsector within each, where included in the analysis. Table 3-9 summarizes the
resulting total inventory for all ports included in this assessment and for all pollutants. Note that since
S02 is not estimated for non-OGV sectors and air toxics are not estimated for OGVs, totals are not
presented for these pollutants.
Table 3-9. 2011 Baseline Emissions for All Sectors and Pollutants, Tons per Year
Pollutant
Drayage
Rail
CHE
Harbor Craft
OGV
Total
PM2.5
811
81
258
1,532
2,897
5,580
NOx
9,819
2,739
6,701
47,780
33,560
100,599
CO2
1,486,914
144,261
899,701
3,550,068
1,729,106
7,810,049
VOC
785
167
361
1,093
1,302
3,708
BC
625
63
199
1,179
87
2,153
SO2
-
-
-
-
25,104
N/A
Formaldehyde
77
5
40
112
-
N/A
Acetaldehyde
32
2
18
56
-
N/A
Benzene
7
0.3
7
15
-
N/A
See Section 4.9 of this report for comparisons between the 2011 baseline and 2020, 2030, and 2050
business as usual inventories for relevant pollutants and precursors.
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Section 4: Business as Usual Emission Inventory Development
4. Business as Usual Emission Inventory Development
4.1.	Overview
Projected Business as Usual (BAU) port emission inventories for years 2020 and 2030 were developed
for the five mobile source sectors: drayage trucks, rail, CHE, harbor craft, and OGVs. The inventories
include NOx, PM2.5, VOC, BC, and C02. In addition, the non-OGV inventories include select air toxics
(acetaldehyde, benzene, and formaldehyde), and the OGV inventory includes S02. Projected inventories
of C02 emissions in 2050 were also developed for all sectors.
The methodology for projecting the baseline 2011 emissions inventories to future years varied by
sector. In addition to baseline growth, the BAU inventory analysis also considered recent or planned
changes in port operations that were anticipated to impact future emission inventories. An overview of
the methodology and results is presented for each of the five mobile source sectors below. Additional
details for the BAU emission inventories are included in Appendix B.
4.2.	Summary of Growth Rates
Non-OGV growth rates for projecting the baseline inventories to 2020 and 2030 were derived from
commodity movements (both imports and exports) in a 2008 study by Research Triangle Institute (RTI).60
Compound annual growth rates relative to the 2011 baseline year were calculated for each commodity
and region and are shown in Table 4-1.
Table 4-1. Compound Annual Growth Rates for 2020 and 2030 by Region and Commodity
Conveyance
Category
U.S. ATLANTIC-
Imports + Exports
U.S. PACIFIC NORTH-
Imports + Exports
U.S. PACIFIC SOUTH -
Imports + Exports
U.S. GULF COAST -
Imports + Exports
2020
2030
2020
2030
2020
2030
2020
2030
Bulk
3.2%
2.7%
4.0%
4.0%
3.9%
3.8%
3.3%
3.2%
Container
4.0%
4.4%
4.0%
4.5%
4.3%
4.9%
3.8%
4.1%
Liquid
0.5%
1.1%
1.5%
1.6%
1.1%
1.1%
1.4%
1.6%
Other
5.0%
4.9%
5.0%
4.8%
7.4%
7.2%
3.9%
4.2%
Total
2.7%
2.9%
3.8%
4.0%
3.5%
4.0%
2.2%
2.3%
The OGV growth rates for projecting the baseline inventories to 2020 and 2030 were derived from
regional annual growth rates in bunker fuel used by the international cargo fleet (including both imports
and exports) in the 2008 RTI study. The average annual growth factors by region that were used in EPA's
C3 RIA and this assessment are presented in Table 4-2.
60 Research Triangle Institute, Global Trade and Fuel Assessment - Future Trends and Effects of Requiring Cleaner Fuels in the
Marine Sector, EPA Report EPA420-R-08-021, November 2008.
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Section 4: Business as Usual Emission Inventory Development
Table 4-2. Annual Average Growth Rates by Region Based upon Bunker Fuel Use
Region
Average Annual Growth Rate
East Coast
4.5%
Gulf Coast
2.9%
South Pacific
5.0%
North Pacific
3.3%
4.3.	Infrastructure Changes That Modify BAU Growth Values
In addition to baseline growth, the projected BAU inventory analysis also considered recent or planned
changes in port operations that could substantially change operational efficiency, and thus emissions, in
future years. For example, plans for construction of on-dock rail would change the mode split and shift
cargo from truck to rail, and would need to be included in this analysis. Only minor adjustments were
made due to such considerations; more information may be found in Appendix B.
4.4.	Drayage Trucks
The baseline 2011 drayage truck activity was grown using the commodity growth rates. This projected
activity was then used with the EPA DrayFLEET Model61 to develop the projected BAU inventory.
4.4.1. Methodology
The cargo tonnage moved by drayage trucks at each port in 2011 was grown to 2020 and 2030 using the
region-specific total compound annual growth rates listed in Table 4-1. The percentage of total cargo
throughput at ports moved by drayage was assumed to stay constant at the base year level. However,
changes in truck age distributions were incorporated based on national default age distributions in
MOVES2010b.
DrayFLEET was run as described in Section 3.2.1 with the baseline 2011 cargo volumes and the 2020 age
distribution. These intermediate emission inventories were then scaled by the ratio of projected truck
tonnage in 2020 to the baseline 2011 truck tonnage to calculate the 2020 drayage BAU inventory. This
was then repeated with the 2030 age distribution and projected 2030 tonnage. Finally, the 2030
inventories were scaled to 2050 using projected tonnage for C02 only. As such, EPA's heavy-duty
greenhouse gas (GHG) regulations are not reflected in this analysis.62
For pollutants not included in DrayFLEET and more details on the drayage truck BAU methodology,
please see Appendix B.
61	U.S. Environmental Protection Agency, SmartWay DrayFLEET, Truck Drayage Environment and Energy Model: Version 2.0
User's Guide, EPA Report EPA-420-B-12-065, June 2012.
62	Specifically, the C02 reductions of EPA's heavy-duty engine and vehicle GHG regulations were not included in the drayage
inventory, due to the timing of the assessment. If such programs were included, EPA would expect smaller C02 increases in
drayage truck emissions in 2030 and 2050.
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Section 4: Business as Usual Emission Inventory Development
4.4.2. Results
Total projected BAU emissions for drayage trucks for 2020, 2030, and 2050 are given in Table 4-3.
Table 4-3. Total BAU Emissions for Drayage Trucks, Tons per Year
Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020
5,241
386
433
297
1,866,145
23
4
64
2030
2,630
155
205
120
2,509,173
13
3
41
2050
-
-
-
-
4,417,155
-
-
-
4.5. Rail
The baseline 2011 rail sector activity was grown using the commodity growth rates shown in Table 4-1.
Emission factors were then calculated from the baseline inventories and adjusted for EPA's future
emission standards. The emission factors were then applied to the projected activity to determine the
BAU inventories.
4.5.1. Methodology
The projected 2020 and 2030 BAU emission inventories for rail were developed as the product of
emission factors and activity data. Gross emission factors were calculated from the baseline rail
inventory using the following equation:
EF = E / (C x S)	Eq. 4-1
Where
EF = Emission factor for a specific pollutant, port, and locomotive type (grams per ton [g/ton]),
E = Total annual emissions for a specific pollutant, port, and locomotive type (grams),
C = Total cargo throughput for a specific port (tons), and
S = Share of cargo throughput moved by rail for a specific port (percent of total cargo tonnage).
To calculate the gross emission factors, the total annual emissions came from the baseline rail
inventories (see Section 3.3), which were distinguished by locomotive type (line-haul or switcher
locomotives). The total cargo throughput came from USACE's Waterborne Commerce Statistics,63 as
used in the drayage and CHE baseline inventories (see Sections 3.2.1 and 3.4.1, respectively). The
share of cargo throughput moved by rail came from the Freight Analysis Framework,64 which was
assumed to remain constant in the projected years for consistency with other sectors. Combining all
of these yields gross emission factors that are valid for the 2011 locomotive fleet at each port.
However, since fleets turn over to newer models in future years that meet stricter emission
63	Available at: http://www.navigationdatacenter.us/db/wcsc/archive/xls/manll/.
64	Available at: http://www.ops.fhwa.dot.eov/freieht/freieht analvsis/faf/.
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Section 4: Business as Usual Emission Inventory Development
standards, these emission factors needed to be adjusted. Therefore, the gross emission factors
were scaled for use in 2020 and 2030 based on projected fleet emission factors listed in EPA's 2008
Locomotive and Marine Emission Standards Rulemaking.65 The emission factors given in the
rulemaking were not used directly because they are in terms of grams per gallon, and the un its
required here were grams per ton of cargo moved.
For the projected BAU inventories for this assessment, the cargo tonnage moved by rail at each port
in 2011 was grown to 2020 and 2030 using the region-specific total compound annual growth rates
listed in Table 4-1. Projected BAU inventories were calculated by multiplying the grown activities by
the corresponding gross emission factors. For more detail on this methodology, please see
Appendix B.
4.5.2. Results
Total projected BAU emissions for rail for 2020, 2030, and 2050 are given in Table 4-4.
Table 4-4. Total BAU Emissions for Rail, Tons per Year
Year
Mode
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020
Rail Yard
1,282
35
83
27
78,198
3
1
7
Rail Line
1,233
30
47
23
104,327
2
0
4
Total
2,515
65
130
50
182,525
5
1
11
2030
Rail Yard
1,091
29
66
22
104,899
3
1
7
Rail Line
863
17
32
13
136,692
1
0
4
Total
1,954
46
98
35
241,591
4
1
11
2050
Rail Yard
—
—
—
—
189,988
—
—
—
Rail Line
—
—
—
—
232,236
—
—
—
Total
-
-
—
—
422,224
-
-
-
4.6. Cargo Handling Equipment
The baseline 2011 cargo handling equipment (CHE) sector activity was grown using the commodity
growth rates shown in Table 4-1. Emission factors were calculated from the baseline inventories and
adjusted for future emission standards. The emission factors were then applied to the projected activity
to determine the BAU inventories.
4.6.1. Methodology
The projected 2020 and 2030 BAU emission inventories for CHE were developed as the product of
emission factors and activity data. Gross emission factors were calculated from the baseline CHE
inventory using the following equation:
65 Emission Factors for Locomotives, EPA-420-F-09-025, April 2009, Tables 5-7.
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Section 4: Business as Usual Emission Inventory Development
EF = E / C	Eq. 4-2
Where
EF = Emission factor for a specific pollutant and port (grams per ton [g/ton]),
E = Total annual emissions for a specific pollutant and port (grams), and
C = Total cargo throughput for a specific port (tons).
To calculate the gross emission factors, the total annual emissions came from the baseline CHE
inventories (see Section 3.4), which were not distinguished by equipment type. The total cargo
throughput came from USACE's Waterborne Commerce Statistics,66 which was also used in the drayage
and CHE baseline inventories (see Sections 3.2.1 and 3.4.1, respectively). Combining these yields gross
emission factors that are valid for the 2011 CHE fleet at each port. However, since fleets turn over to
newer models in future years that meet stricter emission standards, these emission factors needed to
be adjusted. Therefore, the gross emission factors were scaled for use in 2020 and 2030 based on
changes in average emission factors per unit of CHE derived from running EPA's NONROAD model.67 The
emission factors calculated from NONROAD were not used directly because they are in terms of grams
per unit of CHE, and the units required here were grams per ton of cargo moved.
For the projected BAU inventories, the total cargo tonnage throughput at each port in 2011 was grown
to 2020 and 2030 using the region-specific total compound annual growth rates listed in Table 4-1.
Projected BAU inventories were calculated by multiplying the grown activities by the corresponding
gross emission factors. For more detail on this methodology, please see Appendix B.
4.6.2. Results
The total projected BAU emissions for CHE for 2020, 2030, and 2050 are given in Table 4-5.
Table 4-5. Total BAU Emissions for CHE, Tons per Year
Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020
3,251
121
361
93
1,106,410
3
6
7
2030
2,686
73
213
56
1,422,146
3
7
6
2050
-
-
-
-
2,376,567
-
-
-
4.7. Harbor Craft
The baseline 2011 harbor craft sector activity related to goods movement was grown using the
commodity growth rates shown in Table 4-1. Emission factors were calculated from the baseline
inventories and adjusted for future emission standards. The emission factors were then applied to the
projected activity to determine the BAU inventories.
66	Available at: http://www.navigationdatacenter.us/db/wcsc/archive/xls/manll/.
67	Available at: https://www.epa.eov/otaq/nonrdmdl.htm.
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Section 4: Business as Usual Emission Inventory Development
4.7.1. Methodology
The projected 2020 and 2030 BAU emission inventories were developed as the product of emission
factors and activity data. To facilitate this, the sector was split into two categories: goods-moving and
non-goods moving. For the goods-moving harbor craft, gross emission factors were calculated from the
baseline inventory using the following equation:
Where
EF = Emission factor for a specific pollutant and port (grams per ton [g/ton]),
E = Goods-moving annual emissions for a specific pollutant and port (grams), and
C = Total cargo throughput for a specific port (tons).
To calculate the gross emission factors for goods-moving harbor craft, the total annual emissions came
from the baseline inventory (see Section 3.5), which were further allocated by vessel type. Only vessels
directly tied to goods movement (e.g., tug, tow, and push) were included in these calculations. The total
cargo throughput came from USACE's Waterborne Commerce Statistics,68 which was also used in the
drayage and CHE baseline inventories (see Sections 3.2.1 and 3.4.1, respectively). Combining these
yields gross emission factors that are valid for the 2011 goods-moving harbor craft fleet at each port.
For non-goods moving harbor craft, gross fuel-based emission factors were calculated from the baseline
inventory using the following equation:
Where
EF = Emission factor for a specific pollutant and port (grams per gallon [g/gal]),
E = Non-goods moving annual emissions for a specific pollutant and port (grams), and
FC = Non-goods moving annual fuel consumption (gallons).
The non-goods moving portion of the total annual emissions came from the baseline inventory,
including vessel types such as ferries, support, fishing, and government. The fuel consumption was
estimated from the non-goods moving baseline C02 inventories: ECo2 [g] / (26.34% [fuel carbon content]
* 3207 [g/gal] * 3.664 [C02 to C ratio]). Combining these yields gross emission factors that are valid for
the 2011 non-goods moving harbor craft fleet at each port.
However, since fleets turn over to newer models in future years that meet stricter emission standards,
both sets of emission factors needed to be adjusted. Therefore, the gross emission factors were scaled
for use in 2020 and 2030 based on projected emissions per vessel as calculated from EPA's 2008
68 Available at: http://www.navieationdatacenter.us/db/wcsc/archive/xls/manll/.
EF = E/C
Eq. 4-3
EF = E / FC
Eq. 4-4
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Section 4: Business as Usual Emission Inventory Development
Locomotive and Marine Emission Standards Rulemaking.69 The emission factors calculated from the
rulemaking were not used directly because they are in terms of grams per vessel, and the units required
here were grams per ton of cargo moved and in grams per gallon of fuel consumed.
For the goods-moving projected BAU inventories, the cargo tonnage moved at each port in 2011 was
grown to 2020 and 2030 using the region-specific total compound annual growth rates listed in Table
4-1. For the non-goods moving BAU inventories, the activity was assumed to be inelastic to changes in
cargo movement and therefore assumed to have no growth.
The total harbor craft projected BAU inventories were calculated by multiplying the activities by the
corresponding emission factors, and summed together. For more detail on this methodology, please see
Appendix B.
4.7.2. Results
The total projected BAU emissions for harbor craft for 2020, 2030, and 2050 are given in Table 4-6.
Table 4-6. Total BAU Emissions for Harbor Craft, Tons per Year
Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020
35,079
997
814
768
4,106,875
30
7
66
2030
23,937
699
535
538
4,977,640
20
4
46
2050
-
-
-
-
7,398,445
-
-
-
4.8. Ocean Going Vessels
The baseline 2011 OGV sector activity was grown using the bunker fuel growth rates presented in Table
4-2. The emission factors used for the baseline inventory development were adjusted for future
emission standards and fuel changes. The emission factors were then applied to the projected activity to
determine the BAU inventories.
4.8.1. Methodology
The projected 2020 and 2030 BAU emission inventories were developed by adjusting the 2011 baseline
inventories to account for growth in activity and reductions in emission factors due to fleet turnover and
fuel changes as described in the following equation:
Efy = E2011 x EAFfy x Afy / A2011	Eq. 4-5
Where
Efy = Emissions of a pollutant at a specific port in a future year (tons),
69 U.S. Environmental Protection Agency, Control of Emissions of Air Pollution from Locomotive Engines and Marine
Compression Ignition Engines Less than 30 Liters per Cylinder, EPA420-R-08-001, March 2008.
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Section 4: Business as Usual Emission Inventory Development
E2oii= Emissions of a pollutant at a specific port in 2011 (tons),
EAFfy = Emission adjustment factor for a future year,
Afy = Total activity at a specific port in a future year (kWh), and
A2011 = Total activity at a specific port in 2011 (kWh).
The 2011 emissions came directly from the baseline calculations (see Section 3.6). The ratio of increased
activity came from applying the region-specific bunker fuel growth rates listed in Table 4-2 to the base
year activity. The emission adjustment factor for NOx was dependent on changes in age distributions,
whereas the adjustment factors for the other pollutants depended on the changes in fuel sulfur content.
Average NOx emission factors for 2020 and 2030 were calculated by applying the future expected age
distributions to NOx emission rates (which vary by engine type and regulatory tier), based on the C3
RIA.70 The NOx EAFfy was calculated by taking the ratio of the future year emission factor to the base
year factor. Average PM, BC, S02, and C02 emission adjustment factors were calculated by taking the
ratio of the 0.1% sulfur fuel emission rates to the 2.7% sulfur fuel emission rates. It is assumed that all
propulsion and auxiliary engines will use 0.1% sulfur fuel in 2020 and 2030 as required by EPA's North
America Emission Control Area (ECA) Regulations.71 Additional information on this methodology may be
found in Appendix B.
4.8.2. Results
Total projected BAU emission inventories for OGVs for 2020, 2030, and 2050 are given in Table 4-7. Note
that, due to data limitations, this does not include reductions for air toxics emitted from OGVs. Air toxic
emissions from OGVs is an area that warrants further research and analysis.
Table 4-7. BAU Emissions for OGVs, Tons per Year
Year
Mode
NOx
PM2.5
VOC
BC
CO2
SO2
2020
RSZ
3,432
60
232
4
211,091
131
Maneuver
3,410
71
418
4
213,414
132
Hotel
24,047
450
1,131
28
1,863,177
1,139
Anchorage
43
1
2
0
3,405
2
Total
30,932
582
1,783
36
2,291,088
1,404
2030
RSZ
2,230
85
332
5
300,887
187
Maneuver
2,271
105
617
6
313,268
194
Hotel
15,063
637
1,600
40
2,636,134
1,612
Anchorage
31
1
3
0
5,288
3
Total
19,595
828
2,552
52
3,255,577
1,995
70	U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Category 3
Marine Diesel Engines, Report EPA-420-R-09-019, December 2009.
71	U.S. Environmental Protection Agency, Control of Emissions from New Marine Compression-Ignition Engines at or Above 30
Liters per Cylinder, Federal Register, Vol 75, No 83, April 30, 2010.
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Section 4: Business as Usual Emission Inventory Development
Year
Mode
NOx
PM2.5
VOC
BC
CO2
SO2

RSZ
-
-
-
-
622,272
-

Maneuver
-
-
-
-
685,835
-
2050
Hotel
-
-
-
-
5,372,510
-

Anchorage
-
-
-
-
12,753
-

Total
--
--
--
--
6,693,370
--
4.9. Summary of Business as Usual Inventory Results
The bar charts shown below, which combine the 2011 baseline inventories with the future year BAU
emission projections, illustrate the anticipated trends across the analysis period. For all pollutants, this
includes 2011, 2020, and 2030; 2050 is also included for C02 only. In each case, emissions in each sector
are aggregated across all ports considered in this assessment. Figure 4-1 presents total NOx emissions
from OGV, harbor craft, CHE, rail, and drayage trucks. Figures 4-2 and 4-3 present emission inventories
for PM2.5 and C02, respectively. Similar charts for S02, BC, VOC, acetaldehyde, benzene, and
formaldehyde are presented in Appendix B.
In general, the trends seen in these emissions are as expected. For most sectors and pollutants,
emissions decrease over time due to the effect of EPA's emission regulations. For example, PM25 trends
show an initial reduction due to EPA's ECA fuel sulfur regulations, which reduce fuel sulfur from 2.7% to
0.1%. However, PM25 then increases in 2030 due to growth in the OGV sector. This is in contrast to NOx,
where the effects of the phase-in of more stringent standards72 overcome the anticipated growth in this
sector for the 2020 and 2030 inventories. For VOCs from the OGV sector and for C02 in all sectors, there
are no controls in the BAU case to reduce these emissions, so they increase over time with sector
growth. Note that, for C02, the growth rates used for emissions from OGVs do not take into
consideration of C02 improvements resulting from the Energy Efficient Design Index73 (EEDI), any shift in
cargo movements from expansion of the Panama Canal, or any potential impacts from slow steaming. In
addition, the C02 reductions of EPA's heavy-duty engine and vehicle GHG regulations were not included
in the drayage inventory, due to the timing of the assessment. If such programs were included, EPA
would expect smaller C02 increases in drayage truck and OGV emissions in 2030 and 2050.
72	For example, Tier III NOx regulations, which represent an 80% reduction from Tier I, become effective for engines above 130
kW installed on ships built in 2016 and later.
73	See: http://www.imo.0rg/en/OurWork/Environment/PollutionPrevention/AirPollution/Pages/Technical-and-Operational-
Measures.aspx.
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Section 4: Business as Usual Emission Inventory Development
Figure 4-1. Total NOx Emissions Aggregated by Sector, Tons/Year
50,000
40,000
-
= 20,000
I-
10,000
0
12011
12020
12030
OGV
Harbor Craft
Rail
Mode
CHE
Drayage
Figure 4-2. Total PM2.5 Emissions Aggregated by Sector, Tons/Year
3,000
2,500
£ 2,000
a>
> 1,500
E
° 1,000
500
0
12011
12020
12030
OGV	Harbor Craft	Rail	CHE	Drayage
Mode
Figure 4-3. Total C02 Emissions Aggregated by Sector, Tons/Year
8,000,000
7,000,000
6,000,000
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Section 5: Assessment of Emission Reduction Strategies
5. Assessment of Emission Reduction Strategies
5.1. Introduction
One of the purposes of this assessment is to assess the effectiveness of port-related emission reduction
strategies. This section describes the "screening" assessment that was conducted to determine which
strategies would be most effective in reducing port-related NOx, PM2.5, and C02 emissions in future
years. This section is organized to assess the effectiveness of strategies for the five mobile source
sectors: drayage trucks, rail, cargo handling equipment (CHE), harbor craft, and ocean going vessels
(OGVs). The final part of this section summarizes all of the most promising strategies and potential
reductions for a "typical port".74 The results of this screening assessment were then used to develop
the more detailed strategy scenarios described in Section 6 and Appendix C of this report.
The most promising strategies are assessed for their potential impact in 2020 and 2030, since these are
the future analysis years of interest for all pollutants. In addition, this section documents the
considerations that EPA used to determine potential strategies to be modeled for C02 reductions in
2050. The screening assessment involved identifying potential strategies for each sector, estimating a
"baseline" emissions level, and calculating the effectiveness of each strategy based on additional
reductions beyond this baseline.75 In most cases, this was estimated for the strategy as applied to a
single vehicle, piece of equipment, or vessel. The results of this screening are presented as percent
reductions in NOx, PM2.5, and C02 emissions as well as annual tons reduced.
As described further below, other criteria were used to categorize and assess the available strategies to
reduce emissions at U.S. ports:
¦	Capital Cost: Cost for most technological strategies, such as replacements or repowers, to be
applied to a single vehicle, piece of equipment, or vessel. Cost for infrastructure and operational
strategies to be implemented as an entire program or installation.
¦	Market Penetration: Current market penetration and maximum potential market penetration at
U.S. ports in future years.
¦	Market Barriers: Market barriers, including technological and logistical barriers, preventing
adoption by U.S. marine and inland ports.
¦	Funding: Availability of funding sources and other incentives to encourage adoption.
74	A "typical port" in this assessment is intended to establish a hypothetical port that allows EPA to illustrate the relative
impacts of a particular strategy and/or scenario.
75	Please note that the "baseline emissions level" in this screening assessment is different from the 2011 baseline inventory
described in Section 3 of this report.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-1 includes examples of some of the strategies that were assessed in this section.
Table 5-1. Example Emission Reduction Strategies for Assessment
Target Sector/Mode
Strategy
Drayage Truck
Replace with model year (MY) 2007+ or MY2010+ truck
Replace with plug-in hybrid electric vehicles (PHEVs)
Replace with battery electric vehicles (BEVs)
Reduce truck queue idling
Rail - Line-haul
Replace with Tier 4 locomotive
Rebuild Tier 0/pre-Tier 0 engines to meet Tier 0+ standard
Automatic shut-down devices
Rail - Switcher
Replace with Tier 4 locomotive
Repower Tier 3 GenSet switcher with Tier 4 nonroad engine
Rebuild to meet Tier 1+ standard
Cargo Handling Equipment
Replace with Tier 3 or 4 equipment
Repower with Tier 3 or 4 engine
Replace with compressed natural gas (CNG)/liquified natural
gas (LNG) equipment
Replace diesel RTG crane with electric RTG
Harbor Craft
Diesel particulate filter (DPF)
Repower with Tier 2 or 3
Replace with diesel hybrid-electric tug
Use ultra-low sulfur diesel (ULSD) fuel (15 ppm sulfur)
Ocean Going Vessels
Use ULSD fuel in auxiliary engines
Use 500 ppm sulfur diesel fuel
Shore power
Advanced marine emission control system
Improve land-side operational efficiency
Additional documentation on the screening assessment is provided below, including assumptions and
data sources, capital costs, and feasibility. Where capital cost is a major factor in the adoption of specific
strategies, it is expected that a combination of public and private funds would be necessary for
implementation purposes. Finally, while many strategies were initially assessed for this section of the
report, not all of the strategies were included in the final strategy scenarios in Section 6.
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Section 5: Assessment of Emission Reduction Strategies
5.2. Drayage Trucks
Drayage trucks are used to move cargo to and from a port. Nearly all existing drayage trucks are Class 8b
tractor-trailer vehicles, and most drayage trucks in the U.S. are diesel-fueled.76 Drayage truck activity
and emissions tend to be much higher at container terminals than bulk terminals. In this screening
assessment, EPA considered both technological and operational strategies for reducing drayage truck
emissions.
5.2.1. Technological Strategies
5.2.1.1. Baseline Emissions
To evaluate emission reduction strategies, emissions were estimated from typical drayage trucks that
are using current (baseline) technologies (i.e., no application of emission reduction strategies was
assumed). Baseline emission factors were assumed to be equal to the EPA emission standard in effect
for the original truck year of manufacture, as shown in Table 5-2.77
Table 5-2. EPA Emission Standards for Heavy Duty Vehicles (g/bhp-hr)
Beginning Model Year
NOx
PM
1988
10.7
0.6
1990
6
0.6
1991
5
0.25
1994
5
0.1
1998
4
0.1
2004
2
0.1
2007
1.2
0.01
2010
0.2
0.01
The following activity assumptions for a typical drayage truck were applied to the baseline emission
factors (i.e., activity multiplied by the emission factors) to calculate the baseline emissions:78
¦	1.5 shifts per day, 8-hour shifts (or 12 hours per day)
¦	199.4 kWh/shift
¦	250 days operation per year
76	Exceptions include the Port of Los Angeles and the Port of Long Beach, where there are significant numbers of natural gas
drayage trucks.
77	U.S. Environmental Protection Agency, Emission Standards Reference Guide. Available at:
http://www.epa.gov/otaq/standards/heavv-dutv/hdci-exhaust.htm.
78	TIAX, Roadmap to Electrify Goods Movement, Phase 1, Vol 1, Prepared for Edison International, 2012.
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Section 5: Assessment of Emission Reduction Strategies
5.2.1.2. Strategy Effectiveness
Next, the per truck percent reduction was estimated for the application of each of the following
strategies:
¦	For truck replacements and repowers using conventional technology, the emission reduction was
based on the EPA standards shown in Table 5-2.
¦	For diesel oxidation catalysts (DOCs) and DPFs, a 25% and 85% reduction in PM2.5, respectively was
assumed, consistent with typical EPA and California Air Resources Board (CARB) verified diesel
emission control values. There are no NOx or C02 reduction benefits for these technologies.
¦	For CNG/LNG, a 35% reduction in NOx and 20% reduction in PM2.5 was assumed, as compared to a
MY2010 diesel truck, based on CARB engine certification values.79 A 16% reduction in C02 emissions
was assumed, based on parameters in Argonne National Laboratory's 2013 GREET model.80 Note,
the magnitude of these benefits are uncertain. Natural gas engines can likely achieve larger
reductions but have not been required to demonstrate emission levels below current standards.
There are also concerns regarding high levels of ammonia emissions from some natural gas trucks;
ammonia can produce secondary particulates that could offset the PM2.5 benefits of natural gas.
¦	For biodiesel (B20), NOx and PM2.5, impacts were based on MOVES2010b simulations—a 0.4%
increase in NOx and a 3.2% reduction in PM2.5. C02 impacts were based on the 2013 GREET model81
and assumed a 14% reduction in C02 on a well-to-wheels82 basis.
¦	For hybrid electric vehicles (HEVs), PHEVs, and BEVs, emission reductions were based on an analysis
for the Southern California Regional Goods Movement Plan83 and a review of recent literature,
including a 2010 National Academy of Sciences report.84 Emission reductions were based on limited
testing of HEVs and assumptions about the portion of vehicle operation in electric mode for HEVs
and PHEVs. For BEVs, zero tailpipe emissions were assumed; BEVs were assumed to generate a small
amount of PM2.5 due to tire and brake wear. For C02 emissions, a 20% reduction for HEVs, a 25%
reduction for PHEVs, and a 55% reduction for BEVs was assumed (all on a well-to-wheels basis).
For this assessment, the percentage reductions for each strategy was applied to the baseline annual per
truck emissions. Tables 5-3 and 5-4 show the results of the analysis with typical annual NOx and PM2.5
79	ICF International, Comprehensive Regional Goods Movement Plan and Implementation Strategy: Task 10.2 Evaluation of
Environmental Mitigation Strategies, prepared for the Southern California Association of Governments, April 2012. Available
at: www.freiehtworks.ore/DocumentLibrarv/Task%2010%202%20report%20April%202012%20final%20no%20watermark.pdf.
80	Argonne National Laboratory's 2013 GREET model released October 2013. Available at:
https://ereet.es.anl.eov/ereet/index.htm.
81	Ibid.
82	"Well-to-wheels" refers to all C02 emissions that are generated in the extraction, processing, shipment and final combustion
of the fuel. This is in contrast to "tail-pipe" emissions that are typically just the emissions from final combustion.
83	ICF International, Comprehensive Regional Goods Movement Plan and Implementation Strategy: Task 10.2 Evaluation of
Environmental Mitigation Strategies, prepared for the Southern California Association of Governments, April 2012. Available
at: www.freiehtworks.ore/DocumentLibrarv/Task%2010%202%20report%20April%202012%20final%20no%20watermark.pdf.
84	Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National Academy of
Sciences, 2010.
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Section 5: Assessment of Emission Reduction Strategies
emission impacts for each strategy combination, for a typical drayage truck. Negative values denote
emission reductions.
Table 5-3. Typical Emission Impact per Truck per Year - NOx (lbs)

Model Year
New/lm
proved Equipment

2007-09
2010+
DOC
DPF
CNG/LNG
B20
HEV
PHEV
BEV

pre-1991
-1,061
-1,282
0
0
-1,298
5
-1,298
-1,301
-1,326
c
1991-93
-840
-1,061
0
0
-1,077
4
-1,077
-1,080
-1,105
£
1994-97
-840
-1,061
0
0
-1,077
4
-1,077
-1,080
-1,105

1998-2003
-619
-840
0
0
-856
4
-856
-859
-884
LU
2004-06
-177
-398
0
0
-413
2
-414
-417
-442
o
2007-09

-221
0
0
-237
1
-237
-240
-265

2010+


0
0
-15
0
-16
-19
-44
Table 5-4. Typical Emission Impact per Truck per Year - PM2.5 (lbs)

Model Year
New/Improved Equipment

2007
2010+
DOC
DPF
CNG/LNG
B20
HEV
PHEV
BEV

pre-1991
-130.4
-130.4
-33.2
-112.7
-130.9
-4.2
-130.7
-131.2
-132.2
C
1991-93
-53.1
-53.1
-13.8
-47.0
-53.5
-1.8
-53.4
-53.9
-54.8
£
1994-97
-19.9
-19.9
-5.5
-18.8
-20.3
-0.7
-20.2
-20.7
-21.7

1998-2003
-19.9
-19.9
-5.5
-18.8
-20.3
-0.7
-20.2
-20.7
-21.7
LU
2004-06
-19.9
-19.9
-5.5
-18.8
-20.3
-0.7
-20.2
-20.7
-21.7
O
2007-09

0.0
0.0
0.0
-0.4
-0.1
-0.3
-0.5
-1.8

2010+


0.0
0.0
-0.4
-0.1
-0.3
-0.5
-1.8
Table 5-5 shows C02 emission impacts for each strategy combination, for a typical drayage truck. These
values reflect well-to-wheel emissions.
Table 5-5. Typical Emission Impact per Truck per Year - C02 (tons)

Model Year
New/Improved Equipment

2007
2010+
DOC
DPF
CNG/LNG
B20
HEV
PHEV
BEV

pre-1991
0.0
0.0
0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1
C
1991-93
0.0
0.0
0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1
£
1994-97
0.0
0.0
0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1

1998-2003
0.0
0.0
0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1
LU
2004-06
0.0
0.0
0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1
O
2007-09

0.0
0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1

2010+


0.0
0.0
-3.5
-3.1
-4.4
-5.5
-12.1
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Section 5: Assessment of Emission Reduction Strategies
Next, the future year distribution of port drayage trucks was estimated by model year bins
corresponding to the EPA heavy-duty vehicle emission standards.85 This distribution, shown in Table 5-6,
was based on a MOVES2010b analysis for all the counties with port activity considered in this
assessment. Note that in some cases, this may underestimate the number of older drayage trucks
remaining in operation, because the drayage truck fleet may be older than the total countywide truck
fleet.
Table 5-6. Distribution of Trucks by Model Year
Model Year
2011
2020
2030
2050
pre-1991
20%
5%
0%
0%
1991-93
9%
6%
0%
0%
1994-97
21%
13%
0%
0%
1998-2003
24%
16%
7%
0%
2004-06
12%
9%
5%
0%
2007-09
10%
8%
5%
0%
2010+
4%
44%
84%
100%
Total
100%
100%
100%
100%
By understanding how fleet turnover is expected to occur without additional action, the screening
assessment could identify which strategies would be most effective in accelerating fleet turnover to
cleaner future fleets. However, the truck distribution used in this screening assessment is not intended
to be reflective of the rate of fleet turnover for a specific port or area.
5.2.1.3. Most Effective Drayage Truck Technological Strategies in 2020
In 2020, more than half of drayage trucks in operation would pre-date EPA's MY2010 emission
standards, and 48 percent would pre-date the MY2007 standards. By 2020, pre-2007 trucks would be at
least 14 years old and not likely be good candidates for DPFs. The older age of these trucks, combined
with their low average speed, which can increase the maintenance requirements for the DPFs, makes
scrappage and replacement with post-MY2007 or 2010 trucks a more cost-effective alternative.
Repowering older trucks with MY2007-compliant or MY2010-compliant engines is generally not feasible,
because the new engine and aftertreatment devices do not fit on older chassis. Thus, to achieve both
NOx and PM2.5 reductions, an effective strategy in 2020 would be to replace and scrap pre-2007 trucks.
MY2010+ diesel trucks provide significant emissions benefits over pre-2007 trucks; for example, a
MY2010 truck has 90% lower NOx and PM2.5 emissions than a MY2006 truck.86 The cost of a new Class 8
85	The assessment's estimates for drayage trucks do not include the impacts of EPA's heavy-duty engine and vehicle GHG
regulations, due to the timing of the assessment.
86	Based on the percent difference between the MY2007 and MY2010 emission standards for trucks. U.S. EPA's Office of
Transportation and Air Quality, Emission Standards Reference Guide. Available at: http://www.epa.gov/otaq/standards/heavv-
dutv/hdci-exhaust.htm.
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Section 5: Assessment of Emission Reduction Strategies
tractor is approximately $110,000.87 A used truck is considerably less expensive and can still provide
nearly equivalent emissions benefits. Based on CARB's estimates for the California "Truck and Bus
Regulation" and the "Drayage Truck Regulation/' a cost of a four-year-old Class 8 tractor is about 50
percent that of a new tractor ($55,000).88
When focused on replacing pre-MY2007 trucks, the alternative fuel and advanced technology trucks
provide only small additional criteria pollutant emissions benefits as compared to a MY2010+ truck. For
example, replacing a pre-2007 truck with a natural gas, HEV, or PHEV would reduce NOx and PM2.5
emissions by 92-95%, as compared to a 90% reduction with a newer conventional diesel truck. These
advanced technology trucks carry a price premium of $40,000 to $80,000 compared to conventional
diesel, and therefore are less cost effective as replacements for pre-2007 trucks. However, these same
technologies, while higher in cost, can also be effective in helping to reduce C02 emissions.
5.2.1.4. Most Effective Drayage Truck Technological Strategies in 2030
As shown in Table 5-6, 84% of the drayage fleet are assumed to meet the MY2010 emission standards in
2030, and those that do not are likely to have a short remaining useful life. Due to the significant fleet
turnover of older fleets assumed in this assessment to occur by 2030, the most effective strategies
involve replacing conventional diesel trucks with advanced technology and alternative fuel trucks. To
date, there has been limited commercial release of Class 8 HEV trucks, and Class 8 PHEV and BEV trucks
are still in demonstration and research and development phases. EPA acknowledges that there may be
limitations for applying these technologies for port drayage operations. However, advances in battery
technology could enable all-electric port drayage trucks by 2030.
The cost of HEV, PHEV, and BEV trucks in 2030 is uncertain but likely to be 1.5 to 2 times the cost of a
conventional diesel truck. Because a dray fleet operator would be purchasing a new diesel truck anyway
under a replacement strategy, the cost incurred by a port or other public agency would likely be the
incremental cost difference between a conventional diesel truck and an advanced technology truck.
Given the expected emission benefits of BEVs over PHEVs and HEVs, and the likelihood that an all-
electric option would be viable for drayage truck applications by 2030, the replacement with BEV may
be the most cost-effective drayage truck strategy for 2030.
87	California Air Resources Board, Truck and Bus 2010 Rulemaking Initial Statement of Reasons, Appendix I: Costs and Cost
Methodology, p. 1-5, 2010. Available at: http://www.arb.ca.gov/regact/2010/truckbusl0/truckbusappi.pdf.
88	Ibid.
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Section 5: Assessment of Emission Reduction Strategies
5.2.1.5. Summary of Most Promising Drayage Truck Technological Strategies
Table 5-7 summarizes the most promising technological strategies for drayage trucks in 2020 and 2030
in this screening assessment.
Table 5-7. Most Promising Drayage Truck Technological Strategies
Strategy
Per Truck Reduction
Cost Per Truck
Years
Effective
NOx
(lbs)
PM2.5
(lbs)
CO2
(tons)


Replace MY1998-2003 with MY2010+
840
19.9
0.0
$110,000 (new); $55,000 (4 yrs used)
2020
Replace MY2004-2006 with MY2010+
398
19.9
0.0
$110,000 (new); $55,000 (4 yrs used)
2020
Replace MY 2010+ Diesel with Battery
Electric
44
1.8
12.1
$220,000 (new, est.)
2030
5.2.2. Operational Strategies
Operational strategies for drayage trucks focus on efficiency improvements that reduce truck delay
and/or reduce truck travel at and around ports. DrayFLEET89 was used to conduct a screening
assessment of operational strategies that reduce truck idling:90
¦	Reduced Inbound Gate Queues: Reducing the time drayage drivers spend waiting in queues outside
terminal gates.
¦	Automated Gates: Handling containers at automated terminal gates (e.g., via optical character
recognition (OCR), swipe card, radio frequency identification (RFID), or other technology) typically
reduces time at the gates.
¦	Container Information Systems: Developing container status and appointment systems to reduce
terminal congestion and waiting time. This may also reduce non-productive trips when containers
are not ready to move.
¦	Extended Gate Hours: Changing the hours of operation at a port. Marine terminal hours can start at
7-8 am and end at 4-5 pm, depending on local practice. Access outside those times requires
"extended" gate hours. Extended gate hours tend to reduce peak period congestion and
idling/queuing time. Extended gate hours may also reduce the need for drayage firms to park and
store containers overnight.
¦	Minutes per Transaction: Improving on-terminal drayage operations can reduce the transaction
time spent by drayage trucks, which reduces idle time. This factor reflects the minutes required
inside the marine terminal container yard to complete a single transaction. Such transactions
89	U.S. Environmental Protection Agency, SmartWay DrayFLEET, Truck Drayage Environment and Energy Model: Version 2.0
User's Guide, EPA Report EPA-420-B-12-065, June 2012.
90	Strategy descriptions are taken from DrayFLEET: EPA SmartWay Drayage Activity and Emissions Model and Case Studies,
Prepared for U.S. EPA and U.S. Federal Highway Administration, Prepared by The Tiaoga Group, Inc., 2008.
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Section 5: Assessment of Emission Reduction Strategies
include picking up or draying a loaded or empty container or chassis, locating or draying a bare
chassis, switching containers between chassis (a "chassis flip"), or live lifts of containers on or off a
chassis.
To evaluate these strategies, the DrayFLEET model was applied to a typical port, based on the average
annual twenty-foot equivalent units (TEUs) and tonnage for the port profiles considered in this
assessment (i.e., 1.7 million TEUs, 7.5 million export tons, and 8.7 million import tons). Default values in
the DrayFLEET model were otherwise used. Variations in the five operational strategies were explored
by changing assumptions for the level of penetration or participation in the model. For example,
DrayFLEET was used to analyze the impact of reducing average inbound gate queues from 20 to 10
minutes. Using the port's drayage fleet size, age distribution, and annual number of trips, DrayFLEET, in
this example, can calculate the reduction in creep idle emissions that would occur from reducing gate
queues.
Table 5-8 shows the approximate annual emission reductions for each strategy, for a typical container
port in 2020. These reductions are compared against baseline annual drayage truck emissions of 1,105
tons of NOx, 77.0 tons of PM2.5, and 339,084 tons of C02 (well-to-wheels).
Table 5-8. Approximate Annual Typical Port Emission Impacts for Truck Operational Strategies, 2020
Strategy
NOx
PM2.5
CO2
Tons
Percent
Tons
Percent
Tons
Percent
Reduce Inbound Gate Queues
50% Reduction (from 20 to 10 min)
-5.3
-0.5%
-1.54
-2.0%
-6,933
-2.0%
25% Reduction (from 20 to 15 min)
-2.6
-0.2%
-0.77
-1.0%
-3,466
-1.0%
Automated Gates
100% of Gate Transactions
-10.8
-1.0%
-3.10
-4.0%
-13,918
-4.1%
50% of Gate Transactions
-5.4
-0.5%
-1.55
-2.0%
-6,959
-2.1%
25% of Gate Transactions
-2.7
-0.2%
-0.78
-1.0%
-3,479
-1.0%
Container Information System
75% of TEUs Covered
-3.1
-0.3%
-0.21
-0.3%
-708
-0.2%
50% of TEUs Covered
-2.1
-0.2%
-0.14
-0.2%
-472
-0.1%
Extended Gate Hours
50% of traffic off-peak
-7.7
-0.7%
-1.71
-2.2%
-7,480
-2.2%
30% of traffic off-peak
-4.6
-0.4%
-1.02
-1.3%
-4,488
-1.3%
10% of traffic off-peak
-1.5
-0.1%
-0.34
-0.4%
-1,496
-0.4%
Minutes per Transaction
20% reduction (from 30 min to 24)
-17.0
-1.5%
-1.00
-1.3%
-3,831
-1.1%
By varying input parameters in DrayFLEET, a generalized drayage truck operational strategy was
developed to demonstrate how much emissions were reduced for every 10% reduction in the amount of
time dray trucks spend in idle and creep mode. This outcome could be achieved in a variety of ways.
One way, for example, would be to reduce drayage truck transaction time from 30 minutes to 24
minutes and also deploy extended gate hours for 30% to achieve drayage truck visits during off-peak
hours. Table 5-9 shows the average "typical" emission reductions resulting from this generalized
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Section 5: Assessment of Emission Reduction Strategies
strategy. If drayage idle and creep were reduced by 20%, it would double these benefits. For terminals
that substantially reduce major congestion or delay problems, the benefits could be double or triple the
amounts presented.
Table 5-9. Typical Port Emission Impacts for Each 10 Percent Reduction in Idle/Creep Time, 2020 and 2030
Strategy
NOx
PM2.5
CO2
Tons
Percent
Tons
Percent
Tons
Percent
10% reduction in Idle and Creep time
-22
-2.0%
-2
-2.6%
-8,940
-2.6%
5.3. Rail
As noted earlier, port-related rail can include both line-haul and switcher locomotives. The baseline
emissions and reduction options differ for these two categories, so they are discussed separately below.
5.3.1. Line-haul Locomotives
5.3.1.1. Baseline Emissions
To conduct a screening-level assessment of emission reduction strategies, emissions from a typical line-
haul locomotive were calculated using current (baseline) technologies (i.e., no application of emission
reduction strategies). Line-haul locomotives typically travel long distances across multiple states, and an
individual locomotive spends only a small fraction of its operating time at a port. However, it is useful to
analyze emission reduction strategies on a per-locomotive basis, to be consistent with the approach
used for most other port strategies in this section.
To develop a representative estimate of line-haul locomotive activity at a typical port, an approach was
used that was similar to the Port of Los Angeles 2012 emission inventory.91 This report estimated that
line-haul locomotives operate for 35,292 hours by year "on-port." The vast majority of these
locomotives were used to move container trains. The 2012 container throughput at the Port of Los
Angeles was 8,077,714 TEUs. For this screening assessment, an annual container throughput of 3 million
TEUs was assumed, which is similar to the median container throughput at the ports examined in this
assessment. This corresponds to 13,107 line-haul locomotive operating hours at a typical port.
The Port of Los Angeles inventory report also assumed line-haul locomotives had a load factor of 0.28
and an average horsepower of 4,000. Thus, the annual aggregate line-haul locomotive horsepower
hours at a typical port for the purposes of this screening assessment was estimated to be 14,680,000
(i.e., 13,107 * 0.28 * 4,000).
91 Port of Los Angeles, Inventory of Air Emissions for Calendar Year 2012, prepared by Starcrest Consulting Group, July 2013.
Available at: https://www.portoflosangeles.org/pdf/2012 Air Emissions lnventorv.pdf.
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Section 5: Assessment of Emission Reduction Strategies
An individual line-haul locomotive typically consumes 250,000 to 500,000 gallons of fuel per year.92
Using the mid-point of this range, and assuming brake-specific fuel consumption (BSFC) of 20.8 hp-hr
per gallon, an individual line-haul locomotive was estimated to have 7,800,000 annual horsepower
hours, or roughly one-half of the total line-haul locomotive horsepower hours at a typical port.
Therefore, for the purposes of this screening assessment, one can assume that the equivalent of two
line-haul locomotives are operating full-time at a typical port, recognizing that in reality there are many
locomotives each spending a fraction of their time at the port.
To estimate baseline emissions for this section, emission factors based on EPA's regulations were
applied; EPA's in-use emission factors are shown in Table 5-10.93
Table 5-10. EPA Emission Factors for Line-Haul Locomotives
Tier
Year of Manufacture
In-Use Emission Factors (g/hp-hr)
NOx
PMio
Pre-Tier 0
Pre-1973
13
0.32
TierO
1973 - 2001
8.6
0.32
Tier 0+
2008/2010
7.2
0.2
Tier 1
2002 - 2004
6.7
0.32
Tier 1+
2008/2010
6.7
0.2
Tier 2
2005
4.95
0.18
Tier 2+
2008/2013
4.95
0.08
Tier 3
2012 - 2014
4.95
0.08
Tier 4
2015/2017
1
0.015
5.3.1.2. Strategy Effectiveness
EPA evaluated the effectiveness of a range of line-haul locomotive strategies that included:
¦	Replacements or rebuilds of older locomotives: Due to the extended lifetime and turnover, there is
great potential to reduce emissions from replacing or rebuilding older line-haul locomotives.
¦	Idle reduction: There are several technologies currently available to reduce unnecessary locomotive
idling, including use of an auxiliary power unit (or APU) or automatic engine stop/start system.
The primary emission reduction strategies for line-haul locomotives involve replacing or rebuilding of
older line-haul locomotives. Tier 0, Tier 1, and Tier 2 locomotives are required to meet a more stringent
emission standard upon rebuild. For line-haul locomotives, the Tier 2 rebuild (Tier 2+) emission rates are
equivalent to Tier 3. Tier 4 standards were required for new locomotives beginning in 2015.
92	California Air Resources Board, Technical Options to Achieve Additional Emissions and Risk Reductions from California
Locomotives and Railyards, August 2009. Available at: https://www.arb.ca.gov/railvard/ted/083109tedr.pdf.
93	U.S. Environmental Protection Agency, Technical Highlights: Emission Factors for Locomotives. EPA-420-F-09-025. April 2009.
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Section 5: Assessment of Emission Reduction Strategies
EPA estimates that a line-haul locomotive idles for 38 percent of its operating time, or about 1,650
hours per year.94 There are several technologies currently available to reduce unnecessary locomotive
idling. An auxiliary power unit (APU) employs a small diesel engine to run cab accessories, heat and
circulate water and oil, and charge the locomotive batteries, rather than operating the much larger
locomotive engine. An APU costs $25,000 to $32,000, according to EPA.95 Another option is the
automatic engine stop/start system (AESS), which is an electronic control system that shuts down a
locomotive engine when it is idling unnecessarily. The AESS alone may not significantly reduce idling in
cold weather, because of the need to idle the locomotive to prevent freezing of engine coolant (i.e.,
water). However, an AESS can be combined with an APU to provide substantial idle reduction in all
weather. EPA estimates the cost of an AESS system to be $10,000.96
Because of their effectiveness and relatively low cost, EPA now requires an AESS on all newly-built Tier 3
and Tier 4 locomotives, and on all existing locomotives when they are first remanufactured. According to
EPA's projections for the Regulatory Impact Analysis for the 2008 standards (presented below), it was
expected that nearly all line-haul locomotives will be Tier 3, Tier 4, or remanufactured units by 2020.
Thus, additional benefits from AESS would only accrue where the port was working with locomotive
operators to insure that the AESS system was being implemented beyond the minimum requirements.
Tables 5-11 and 5-12 show annual NOx and PM2.5 emission reductions expected for each replacement
strategy, assuming a typical line-haul locomotive as outlined above.
Table 5-11. Typical Emission Impact per Line-Haul Locomotive per Year - NOx (lbs)


Tier0+
Tier 1+
Tier 2+
Tier 3
Tier 4

Pre-Tier 0
-99,736
-108,334
-138,427
-138,427
-206,351

TierO
-24,074
-32,672
-62,765
-62,765
-130,689
c
Tier 0+

-8,598
-38,691
-38,691
-106,614
£
Tier 1

0
-30,093
-30,093
-98,017

Tier 1+


-30,093
-30,093
-98,017
LU
Tier 2


0
0
-67,924
O
Tier 2+



0
-67,924

Tier 3




-67,924

Tier 4





94	U.S. Environmental Protection Agency, 2008. Regulatory Impact Analysis: Control of Emissions of Air Pollution from
Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Liters per Cylinder. EPA-420-R-08-001, February
2008.
95	Ibid.
96	Ibid.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-12. Typical Emission Impact per Line-Haul Locomotive per Year - PM2.5 (lbs)


Tier0+
Tier 1+
Tier 2+
Tier 3
Tier 4

Pre-Tier 0
-2,064
-2,064
-4,127
-4,127
-5,245

TierO
-2,064
-2,064
-4,127
-4,127
-5,245
c
(D
E
Tier 0+

0
-2,064
-2,064
-3,181
Tier 1

-2,064
-4,127
-4,127
-5,245
"5
Tier 1+


-2,064
-2,064
-3,181
LU
Tier 2


-1,720
-1,720
-2,837
O
Tier 2+



0
-1,118

Tier 3




-1,118

Tier 4





EPA's emission standards for line-haul locomotives are not designed to address C02 emissions. Although
newer locomotive tend to be more fuel efficient, it is difficult to determine the fuel or C02 reduction that
would be associated with replacement of an older locomotive with a newer one. The aggregate fuel
efficiency of U.S. freight railroads improved about 31% between 1990 and 2010, or 1.4% annually, in terms of
gallons per revenue ton-mile. However, those improvements are the net outcome of multiple changes in
railroad traffic mix, technological improvements, and operating practices. For the purposes of this screening
analysis, no change in C02 emissions was assumed when moving from one tier to another for line-haul
locomotives. In this assessment, any further reductions in C02 emission rates from technological changes was
assumed to come from the implementation of zero emissions technologies.
Table 5-13 shows the expected distribution of line-haul locomotives by tier in 2011, 2020, 2030, and 2050,
using assumptions from EPA's Regulatory Impact Analysis for the 2008 locomotive emission regulation.97
Compared to trucks, the locomotive fleet has a slower assumed fleet turnover resulting in a significant
fraction of older (pre-Tier 4) engines remaining in the fleet even in 2030.
Table 5-13. Distribution of Line-Haul Locomotives by Tier
Tier
2011
2020
2030
2050
Pre-Tier 0
10%
0%
0%
0%
TierO
37%
3%
0%
0%
Tier 0+
19%
33%
10%
0%
Tier 1
4%
0%
0%
0%
Tier 1+
6%
9%
5%
0%
Tier 2
24%
0%
0%
0%
Tier 2+
0%
22%
17%
0%
Tier 3
0%
10%
9%
0%
Tier 4
0%
23%
59%
100%
Total
100%
100%
100%
100%
97 U.S. Environmental Protection Agency, 2008. Regulatory Impact Analysis: Control of Emissions of Air Pollution from
Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Liters per Cylinder. EPA-420-R-08-001, February
2008.
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Section 5: Assessment of Emission Reduction Strategies
It is important to understand when baseline fleet turnover is expected to occur, to accurately assess the
potential of reducing line-haul locomotive emissions through replacement and rebuild strategies.
However, the line-haul locomotive distributions shown in Table 5-13 are national default assumptions
and are not intended to be reflective of the rate of fleet turnover in practice for a specific port or area.
5.3.1.3.	Most Effective Line-haul Strategies in 2020
In the year 2020 for this analysis, strategies should focus on replacing Tier 0+ line-haul locomotives with
newer equipment. A new Tier 4 locomotive costs approximately $3 million and would provide the
largest emission reduction benefit. However, significant benefits could also be obtained from replacing
Tier 0+ with a (used) Tier 2+ or Tier 3 locomotive. If the railroad serving the port is a short line and
therefore operates a small fleet over a limited area, it could be cost effective to use a combination of
private and government funds to scrap the Tier 0+ locomotives and replace them with Tier 2+/3
locomotives obtained from another railroad. The cost effectiveness of this strategy would depend on
the locomotive purchase price.
5.3.1.4.	Most Effective Line-haul Strategies in 2030
In 2030, the remaining Tier 0+ locomotives will have little useful service life and will probably be used
sparingly. Therefore, for this assessment, the emission reduction strategies should focus on replacing
the Tier 2+ and Tier 3 locomotives with Tier 4 locomotives. The cost effectiveness of this strategy would
depend on whether the replacement engines are purchased new or used, and whether the old
equipment is re-deployed or scrapped.98
5.3.2. Switcher Locomotives
5.3.2.1. Baseline Emissions
For switcher locomotives (unlike line-haul), it was assumed for the purposes of this screening
assessment that a small fleet of switchers would be dedicated to port service and operated entirely in
and around a port. To estimate baseline emissions (i.e., without emission reduction strategies), a typical
switcher locomotive was assumed to have the following parameters:99
¦	Annual fuel consumption of 50,000 gallons
¦	Brake-specific fuel consumption (BSFC) of 20.8 hp-hours per gallon
To estimate baseline emissions, EPA's in-use emission factors as shown in Table 5-14 were applied.100
98	Detailed information on trends in locomotive fuel efficiency and strategies are discussed in Comparative Evaluation of Rail
and Truck Fuel Efficiency on Competitive Corridors, Final Report for the Federal Railroad Administration, March 31, 2009.
Available at: https://www.fra.dot.eov/eLib/details/L04317.
99	California Air Resources Board, Technical Options to Achieve Additional Emissions and Risk Reductions from California
Locomotives and Railyards, August 2009.
100	U.S. Environmental Protection Agency, Technical Highlights: Emission Factors for Locomotives. EPA-420-F-09-025. April
2009.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-14. EPA Emission Factors for Switcher Locomotives
Tier
Year of Manufacture
In-Use Emission Factors (g/hp-hr)
NOx
PM10
Pre-Tier 0
Pre-1973
17.4
0.44
TierO
1973 - 2001
12.6
0.44
Tier 0+
2008 / 2010
10.6
0.23
Tier 1
2002 - 2004
9.9
0.43
Tier 1+
2008 / 2010
9.9
0.23
Tier 2
2005
7.3
0.19
Tier 2+
2008 / 2013
7.3
0.11
Tier 3
2012 - 2014
4.5
0.08
Tier 4
2015 / 2017
1
0.015
Tier 3 GenSet
2006
3
0.15
Tier 4 GenSet
2011-2014
0.3
0.01
5.3.2.2. Strategy Effectiveness
EPA evaluated the effectiveness of a range of switcher locomotive strategies:
¦	Replacements, rebuilds, and Generator Sets (GenSets): Accelerating fleet turnover to newer EPA
standards and/or the use of GenSets could reduce significant levels of emissions attributed to older
switcher locomotives.
¦	Idle reduction: EPA also considered the potential impact of reducing switcher locomotive emissions
through the use of automatic engine stop/start systems (AESS).
Switcher locomotive emission reduction strategies are similar to line-haul strategies, but also include
GenSet technology. GenSets are typically powered by a bank of three nonroad engines, one or two of
which can be shut down during periods of lower demand. By 2015, new-model GenSets will by fully
compliant with EPA's Tier 4 nonroad engine standards, so they can significantly reduce emissions and
fuel use.
Idle reduction could also be an effective strategy for switcher locomotives in 2020. As discussed above,
the addition of idle reduction technology is not expected to provide additional benefits for line-haul
locomotives in 2020 and later because nearly all line-haul locomotives will have an AESS installed upon
rebuild. However, switchers are not rebuilt as frequently, and EPA projected that approximately 46% of
the switcher fleet will already be pre-Tier 0, Tier 0, or Tier 2 in 2020 (see below). EPA estimated that use
of an AESS could reduce Tier 2 switcher emissions by 880 lbs of NOx and 14 lbs of PM2.5 annually.101
Installation on pre-Tier 0 and Tier 0 switchers would provide larger reductions, but these retrofits may
101 U.S. Environmental Protection Agency, 2008. Regulatory Impact Analysis: Control of Emissions of Air Pollution from
Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Liters per Cylinder. EPA-420-R-08-001, February
2008.
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Section 5: Assessment of Emission Reduction Strategies
be impractical for very old locomotives facing retirement. The cost of a basic AESS is approximately
$10,000. EPA notes that the system was assumed to would reduce operating cost by saving 2,000
gallons of fuel per year; this equates to about 22 tons of C02 emissions reduced per year.102
Tables 5-15 and 5-16 show the results of the screening assessment with annual NOx and PM2.5 emission
reductions expected for each replacement strategy, assuming a typical switcher locomotive that
consumes 50,000 gallons of fuel per year.
Table 5-15. Typical Emission Impact per Switcher Locomotive per Year - NOx (lbs)


New/Improved Equipment

Tier
Tier0+
Tier 1+
Tier 2+
Tier 3
Tier 4
T3 GenSet
T4 GenSet

Pre-Tier 0
-15,591
-17,196
-23,157
-29,577
-37,602
-33,016
-39,207

TierO
-4,586
-6,191
-12,152
-18,572
-26,596
-22,011
-28,201

Tier 0+

-1,605
-7,566
-13,986
-22,011
-17,425
-23,616
c
Tier 1

0
-5,961
-12,381
-20,406
-15,820
-22,011
£
Tier 1+


-5,961
-12,381
-20,406
-15,820
-22,011

Tier 2


0
-6,420
-14,445
-9,859
-16,049
LU
Tier 2+



-6,420
-14,445
-9,859
-16,049
O
Tier 3




-8,025
-3,439
-9,630

Tier 4






-1,605

Tier 3 GenSet






-6,191

Tier 4 GenSet







Table 5-16. Typical Emission Impact per Switcher Locomotive per Year - PM2.5 (lbs)


New/Improved Equipment

Tier
Tier0+
Tier 1+
Tier 2+
Tier 3
Tier 4
T3 GenSet
T4 GenSet

Pre-Tier 0
-481
-481
-757
-825
-974
-665
-986

TierO
-481
-481
-757
-825
-974
-665
-986

Tier 0+

0
-275
-344
-493
-183
-504
C
Tier 1

-459
-734
-802
-952
-642
-963
£
Tier 1+


-275
-344
-493
-183
-504

Tier 2


-183
-252
-401
-92
-413
LU
Tier 2+



-69
-218
92
-229
O
Tier 3




-149
160
-160

Tier 4






-11

Tier 3 GenSet






-321

Tier 4 GenSet







C02 emission reductions will result from replacement with GenSet locomotives, or an equivalent
strategy. The fuel savings from GenSet switchers can vary depending on duty cycle—values of 20% to
102 Ibid.
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Section 5: Assessment of Emission Reduction Strategies
50% are reported/03 and 25% fuel savings was assumed for the purpose of this screening assessment. It
was assumed that replacements of any non-GenSet switcher with a GenSet switcher would reduce C02
emissions by 177 tons per year, assuming typical operation. As discussed above for line-haul
locomotives, no C02 reductions resulted from replacements with newer conventional locomotives.
Table 5-17 shows the expected distribution of switcher locomotives by Tier in 2011, 2020, 2030, and
2050, using assumptions from EPA's Regulatory Impact Analysis for the 2008 locomotive emission
regulations. Unlike line-haul locomotives, EPA projected the switcher fleet would contain a significant
portion (38%) of Pre-Tier 0 (uncontrolled) locomotives in 2020, in addition to 46% Tier 0/0+. Even in
2030, EPA projected that 60% of the switcher fleet will be Pre-Tier 0 or Tier 0+. Pre-Tier 0 are exempt
from EPA's rebuild requirements.
Table 5-17. Distribution of Switcher Locomotives by Tier

2011
2020
2030
2050
Pre-Tier 0
74%
38%
8%
0%
TierO
7%
1%
0%
0%
Tier 0+
10%
45%
52%
0%
Tier 1
1%
0%
0%
0%
Tier 1+
0%
1%
1%
0%
Tier 2
7%
7%
0%
0%
Tier 2+
0%
0%
6%
0%
Tier 3
1%
3%
3%
0%
Tier 4
0%
5%
29%
100%
Total
100%
100%
100%
100%
As stated elsewhere, the switcher locomotive distribution used in this screening assessment is not
intended to be reflective of the rate of fleet turnover in practice for a specific port or area.
5.3.2.3. Most Effective Switcher Strategies in 2020
Based on this assessment's assumptions, switcher strategies in 2020 should focus on the Pre-Tier 0 and
Tier 0+ locomotives, which will dominate the fleet Pre-Tier 0 engines could potentially be re-built to
meet Tier 0+ standards at relatively low cost, even though Pre-Tier 0 locomotives are exempt from the
re-build requirement.104 However, there may be little economic incentive for railroads to remanufacture
these older pre-Tier 0 switch locomotives to reduce emissions because they have little residual value.
Thus, this screening assessment supports the use of 2020 strategies that focus on scrapping and
replacing the Pre-Tier 0 and Tier 0+ locomotives with newer equipment.
103	California Air Resources Board, Technical Options to Achieve Additional Emissions and Risk Reductions from California
Locomotives and Railyards, August 2009. Available at: https://www.arb.ca.gov/railvard/ted/083109tedr.pdf.
104	California Air Resources Board, Technical Options to Achieve Additional Emissions and Risk Reductions from California
Locomotives and Railyards, August 2009.
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Section 5: Assessment of Emission Reduction Strategies
The greatest emission reduction benefits are assumed to come from deployment of Tier 4 GenSet switchers.
Large emission reductions in 2020 can also be obtained through deployment of Tier 2+, Tier 3, Tier 3 GenSet,
and Tier 4 switchers. The cost of a new GenSet locomotive is approximately $1.5 million. The cost of a Tier 2+
or Tier 3 locomotive will depend on its age; it has been common for railroads to redeploy older line-haul
locomotives to switcher service. The cost effectiveness of each of these strategy options will depend on the
purchase price of the new or used equipment and the remaining service life of the old locomotive to be
replaced. In addition, GenSets have lower power than conventional switchers and may not be suitable for
some switching applications with high power demands. As a result, some of the switcher replacements may
involve conventional Tier 4 units rather than GenSets. A combination of private and public funds may be the
most effective option for encouraging early adoption of these cleaner technologies.
Installation of AESS to reduce idling has relatively small emission reduction benefits but is very cost effective.
The fuel savings from this strategy ensures a payback period of less than three years. AESS installation should
focus on Tier 2 locomotives that have not been rebuilt, as well as any pre-Tier 0 switchers that have expected
remaining service life.
5.3.2.4. Most Effective Switcher Strategies in 2030
In 2030, switcher strategies should focus on replacement of the remaining Tier 0+ locomotives and the Tier
2+/Tier 3 locomotives. The new replacement locomotives should be Tier 4 or Tier 4 GenSets. The Tier 4
GenSets have the lowest emissions. However, as noted for 2020, GenSets can have lower power than
conventional switchers, so some of the switcher replacements may also involve conventional Tier 4 units.
5.3.3. Summary of Most Promising Locomotive Strategies
Table 5-18 summarizes the most promising locomotive strategies for this assessment. The costs are
approximate values for the full purchase price of new equipment, with the assumption that used equipment
could be purchased at a lower cost.
Table 5-18. Most Promising Locomotive Emission Reduction Strategies


Per Locomotive


Type
Strategy
Reduction
Cost
Years Effective
NOx
(lbs)
PM2.5
(lbs)
CO2
(tons)
Line-Haul
Replace Tier 0+ with Tier 2+/3
38,691
2,064
0
$3,000,000
2020
Replace Tier 2+/3 with Tier 4
67,924
1,118
0
$3,000,000
2030

Replace Pre-TO and T0+ with Tier 2+/3
7,566
275
0
$1,500,000
2020
Switcher
Replace Pre-TO, T0+ with Tier 4 GenSet
23,616
504
177
$1,500,000
2020, 2030
Install AESS on Tier 2
880
14
28
$10,000
2020

Replace Tier 2+/3 with T4 or T4 GenSet
9,630
160
177
$1,500,000
2030
5.4. Cargo Handling Equipment
The cargo handling equipment (CHE) emission source category encompasses a wide variety of
equipment types, and the mix of CHE at a given port can vary widely depending on the types of cargo.
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Section 5: Assessment of Emission Reduction Strategies
At a typical port with significant container operations, the bulk of CHE emissions are associated with
yard trucks, cranes, and container handlers (side picks and top handlers).105 Thus, this assessment
focused on potential CHE emission reduction strategies for yard trucks, cranes, and container handlers.
5.4.1. Yard Trucks
Yard trucks are assumed to make up the bulk of CHE emissions at container terminals, and are referred
to as terminal tractors or yard hostlers. A yard truck is typically a low power semi-tractor with a single-
person cab and a very short wheelbase.
5.4.1.1. Baseline Emissions
First, for this screening assessment, baseline emissions were estimated for typical yard trucks that are
using current (baseline) technologies (i.e., no application of emission reduction strategies). To do this,
the following assumptions were made for a typical yard truck:106
¦	Average engine size of 206 hp
¦	Load factor of 0.65
¦	1,861 hours of operation per year
Baseline emission factors were assumed to be equal to the federal Nonroad Compression-Ignition
Engine Exhaust Emission Standard in effect for the average rated power (i.e., 206 hp) and model year of
the engine, as shown in Table 5-19. C02 emission factors for all tiers were assumed to be 396 g C02 /
kW-hr.107
Table 5-19. EPA Emission Standards Applicable to Typical Yard Trucks
Tier
Model Year (beginning)
NMHC
NMHC+NOx
NOx
PM
1
1996
1.3
-
9.2
0.54
2
2003
-
6.6
-
0.2
3
2006
-
4
-
0.2
4
2011
-
4
-
0.02
4
2014
0.19
-
0.4
0.02
5.4.1.2. Strategy Effectiveness
Next, the per yard truck percent reduction in emissions was estimated for the application of each of the
following strategies:
105	This assumption is based on a review of the emission inventories for the Ports of Charleston, Oakland, Long Beach, Los
Angeles, and Virginia that found these three CHE types collectively account for more than 80% of CHE emissions.
106	U.S. Environmental Protection Agency, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories,
April 2009.
107	Ibid.
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Section 5: Assessment of Emission Reduction Strategies
¦	Vehicle replacement and repower. Using conventional equipment, the emission reduction is based
on the EPA Nonroad Emission Standards shown in Table 5-19.
¦	Diesel particulate filters (DPFs). An 85% reduction in PM25 was assumed, consistent with typical
EPA-verified diesel emission control strategy values.108 Please note that DPFs have no impact on
NOx and C02 emissions.
¦	Compressed natural gas (CNG) and liquified natural gas (LNG). The screening assessment assumed
a 20% reduction in NOx and PM25 compared to a Tier 4 diesel yard truck, based on the California Air
Resources Board's certification tests of natural gas versus diesel engines.109 Note that the magnitude
of these benefits are uncertain. Natural gas engines can likely achieve larger reductions, but have
not been required to demonstrate emission levels below current standards. There have also been
concerns regarding high levels of ammonia emissions from some natural gas trucks; ammonia can
produce secondary particulates that could offset the PM25 benefits of natural gas. This assessment
assumed a 16% reduction in C02 emissions, based on Argonne National Laboratory's GREET
model.110
¦	Plug-in hybrid electric vehicle (PHEV), hydraulic hybrid, and all-electric yard trucks. Emission
reductions were based on emission rate estimates from a 2009 report at the Port of Long Beach.111
Emission reductions were calculated based on comparing the study's emission rates for pluggable
hybrid electric terminal tractors (PHETTs) and Tier 3 yard trucks. Because in-use emissions data were
not available for hydraulic hybrids, it was assumed that they experience the same reductions as
plug-in hybrids. Zero tailpipe emissions were assumed for all-electric tractors. C02 emissions for
plug-in hybrids were based on the average fuel rates measured in the PHETT study; C02 emissions
for hydraulic hybrids were based on EPA estimates of 50-60% fuel efficiency increases.112
Further details on these strategies are offered below. In this screening assessment, the percentage
reductions for each strategy were applied to the baseline annual per yard truck emissions.
Tables 5-20 and 5-21 show estimated annual NOx and PM2 5 emission reductions per yard truck for each
strategy combination for this screening assessment.
108	U.S. Environmental Protection Agency, Technologies Diesel Retrofit Devices. Available at:
http://www.epa.eov/cleandiesel/technoloeies/retrofits.htm.
109	California Air Resources Board, On-Road New Vehicle & Engine Certification Program. Available at:
http://www.arb.ca.eov/msproe/onroad/cert/cert.php.
110	Argonne National Laboratory's 2013 GREET model released October 2013. Available at:
https://ereet.es.anl.eov/ereet/index.htm.
111	TIAX, Pluggable Hybrid Electric Terminal Tractor (PHETT) Demonstration at the Port of Long Beach, prepared for the Port of
Long Beach, September 2009. Available at: http://www.cleanairactionplan.ore/documents/capacitv-plue-in-hvbrid-terminal-
tractor-phett-demonstration-polb-final-report.pdf.
112	U.S. Environmental Protection Agency. Hydraulic Hybrid Yard Hostlers. Faster Freight - Cleaner Air Conference. July 9, 2008.
Presentation. Available at: http://www.fasterfreiehtcleanerair.com/pdfs/Presentations/FFCAEC2008/John%20Kareul.pdf.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-20. Typical Emission Impact per Yard Truck per Year - NOx (lbs)

New/Improved Equipment
+J
£
CD

Tier 2
Tier 3
Tier 4
DPF
CNG/LNG
PHEV
Hydraulic
Hybrid
Electric
£
Q.
Tier 1
-1,065
-2,130
-3,605
0
-3,638
-3,669
-3,669
-3,769
3
O"
Tier 2

-1,065
-2,540
0
-2,573
-2,604
-2,604
-2,704
2
Tier 3


-1,475
0
-1,508
-1,539
-1,539
-1,639
O
Tier 4



0
-33
-64
-64
-164
Table 5-21. Typical Emission Impact per Yard Truck per Year - PM2.5 (lbs)

New/Improved Equipment
+-<
£
CD

Tier 2
Tier 3
Tier 4
DPF
CNG/LNG
PHEV
Hydraulic
Hybrid
Electric
£
Q.
Tier 1
-139
-139
-213
-188
-215
-217
-217
-221
3
O"
Tier 2

0
-74
-70
-75
-78
-78
-82
2
Tier 3


-74
-70
-75
-78
-78
-82
O
Tier 4



0
-2
-4
-4
-8
Table 5-22 shows estimated annual C02 emission reductions per yard truck for each strategy
combination, calculated on a well-to-wheels basis.
Table 5-22. Typical Emission Impact per Yard Truck per Year - C02 (tons)

New/Improved Equipment
+-<
£
CD

Tier 2
Tier 3
Tier 4
DPF
CNG/LNG
PHEV
Hydraulic
Hybrid
Electric
£
Q.
Tier 1
0
0
0
0
-17
-19
-52
-34
3
O"
Tier 2

0
0
0
-17
-19
-52
-34
2
Tier 3


0
0
-17
-19
-52
-34
O
Tier 4



0
-17
-19
-52
-34
To identify strategies that would be applicable and the most effective in future years, the future year
distribution of yard trucks was estimated with using EPA's NONROAD2008 model.113 Table 5-23 shows
the assumed distribution of yard trucks by tier in 2011, 2020, 2030, and 2050.
113 Yard trucks are identified in NONROAD as Terminal Tractors (SCC: 2270003070).
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Section 5: Assessment of Emission Reduction Strategies
Table 5-23. Distribution of Yard Trucks by Tier

2011
2020
2030
2050
Tier 1
9%
0%
0%
0%
Tier 2
17%
0%
0%
0%
Tier 3
64%
3%
0%
0%
Tier 4
10%
97%
100%
100%
Total
100%
100%
100%
100%
EPA notes that the yard truck distribution used in this screening assessment is not intended to be
reflective of the rate of fleet turnover in practice for a specific port or area.
5.4.1.3. Most Effective Yard Truck Strategies in 2020
In 2020, based on the NONROAD national default age distribution, nearly all yard tractors are expected
to meet EPA's highest emission standards (i.e., Tier 4). Therefore, strategies to further reduce emissions
is limited in this screening assessment to replacing conventional diesel yard trucks with advanced
technology or alternative fuel equipment. Hybrid yard trucks are in the early stages of
commercialization. In 2009, Capacity released its PHETT, and in 2010, Kalmar/Cargotec produced a
hydraulic hybrid terminal tractor. Demonstration hybrid yard truck projects at the Port of Los Angeles
and Port of Long Beach found significant emission reduction benefits compared to a Tier 3 baseline
vehicle.114
EPA has supported development of a hydraulic hybrid yard truck, which increases system efficiency by
capturing energy from braking as pressurized hydraulic fluid. This vehicle was tested at the Port of Long
Beach and Port of New York/New Jersey.115 Because a typical yard truck duty cycle is characterized by
frequent starting and stopping, low travel speeds, and significant idling, hybrid technologies can
potentially realize significant emission benefits. However, the magnitude of emission reduction benefits
and the incremental costs of these technologies compared to conventional Tier 4 diesel yard trucks are
uncertain. It was assumed that a PHEV and hydraulic hybrid truck would both yield 39% NOx and 53%
PM2.5 reductions, based on demonstrations at the Port of Long Beach. To estimate C02 impacts, for this
screening assessment, a PHEV is assumed to reduce fuel use by 34% (based on the Long Beach
demonstration) and a hydraulic hybrid would reduce fuel use by 50% (based on EPA's demonstration).
114	TIAX LLC, Pluggable Hybrid Electric Terminal Truck (PHETT™) Demonstration at the Port of Los Angeles, prepared for the Port
of Los Angeles. May 2010. Available at: http://www.cleanairactionplan.ore/documents/capacitv-plue-in-hvbrid-terminal-
tractor-phett-demonstration-polb-final-report.pdf.
115	Calstart, Hybrid Yard Hostler Demonstration and Commercialization Project, prepared for Ports of Los Angeles and Long
Beach. March 2011. Available at: http://www.cleanairactionplan.org/documents/hvbrid-vard-hostler-demonstration-and-
commercialization-proiect-final-report.pdf.
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Section 5: Assessment of Emission Reduction Strategies
In terms of costs, a pilot project study found that the costs for hybrid-electric yard trucks were currently
60% higher than a conventional diesel truck, with the project prototypes costing $134,000.116 In the
future, this cost increment may decline, but hybrid-electric vehicles are still expected to carry a
significantly higher purchase price than conventional diesel trucks. Like other advanced technologies,
adoption of these strategies would require a combination of public and private funds.
An all-electric yard truck would offer emission reductions beyond Tier 4 standards and hybrid
technologies, with zero tailpipe emissions. Like hybrids, battery electric yard trucks are in the
development and demonstration phase. Tenants at the Port of Los Angeles have been testing plug-in
battery electric yard trucks made by Balqon Corporation—the Nautilus XE20 and XR E20 models.117 The
vehicles operate on lithium-ion batteries. The vehicle and charging equipment for a Port of Los Angeles
demonstration project cost approximately $210,000; future costs for all-electric vehicles are uncertain
but would be substantially higher than a diesel yard truck.118
Some CNG and LNG yard trucks are available from heavy-duty truck manufacturers (e.g., Capacity,
Cargotec/Kalmar). Because they are also relatively early in their development and use, emission
reductions are not well documented, particularly as compared to Tier 4 diesel yard trucks. In the future,
advanced natural gas engines may offer NOx and PM2.5 benefits beyond Tier 4 levels. This screening
assessment assumed a 20% NOx and PM2.5 benefit, based on CARB certification tests of natural gas
versus diesel engines,119 as well as a 16% C02 benefit.
Natural gas vehicles are expected to carry a higher purchase price than diesel for the foreseeable future.
Natural gas vehicles are estimated to cost approximately $30,000 more than comparable diesel vehicles
in future years.
5.4.1.4. Most Effective Yard Truck Strategies in 2030
By 2030, as described above, this assessment assumes that all yard truck are expected to meet the Tier 4
emission standards. Thus, to achieve emission reductions beyond baseline emissions, vehicle
technologies with lower tailpipe emissions than Tier 4 systems (e.g., electric trucks) would need to be
employed. Therefore, the same strategies presented above for 2020 would also be effective strategies
to reduce emissions in 2030.
116	Ibid.
117	The Port of Los Angeles, Electric Truck Demonstration Project Fact Sheet, prepared for The Port of Los Angeles. Available at:
http://www.portoflosaneeles.ore/DOC/Electric Truck Fact Sheet.pdf.
118	Ibid.
119	California Air Resources Board, On-Road New Vehicle & Engine Certification Program. Available at:
http://www.arb.ca.eov/msproe/onroad/cert/cert.php.
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Section 5: Assessment of Emission Reduction Strategies
5.4.2. Cranes
Cranes include rubber tire gantry (RTG) cranes, rail-mounted gantry (RMG) cranes, wharf (ship-to-shore)
cranes, aerial lifts, and cable cranes. RTG cranes are typically powered by diesel engines and account for
the bulk of crane emissions at most container terminals. In contrast, RMG cranes and wharf cranes are
often electrically powered. As a result, this screening assessment focused on strategies that reduce
diesel emissions from RTG cranes.
5.4.2.1. Baseline Emissions
The following assumptions for a typical RTG crane were used to estimate baseline emissions:120
¦	Average engine size of 453 hp
¦	Load factor of 0.43
¦	2,641 hours of operation per year
Baseline emission factors were assumed to be equal to EPA's Nonroad Compression-Ignition Engine
Exhaust Emission Standard in effect for the average rated power (i.e., 453 hp) and model year of the
engine, as shown in Table 5-24.121
Table 5-24. EPA Emission Standards Applicable to RTG Cranes (g/kWh)
Tier
Model Year (beginning)
NMHC122
NMHC+NOx
NOx
PM2.5
1
1996
1.3
-
9.2
0.54
2
2001
-
6.4
-
0.2
3
2006
-
4
-
0.2
4
2011
-
4
-
0.02
4
2014
0.19
-
0.4
0.02
5.4.2.2. Strategy Effectiveness
Next, the per crane percent reduction in emissions was estimated for the application of each of the
following strategies:
¦	Replacements or repowers. For the vehicle replacement and repower strategies using a lower
emission diesel engine, the emission reductions were based on the EPA's Nonroad Emission
Standards shown in Table 5-24 above.
¦	Diesel particulate filters (DPFs). Consistent with typical EPA-verified diesel emission control
strategy values, an 85% reduction in PM2.5 was assumed. The California Air Resources Board (CARB)
120	U.S. Environmental Protection Agency, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories,
April 2009.
121	U.S. Environmental Protection Agency, Emission Standards Reference Guide for Nonroad Compression-Ignition Engines.
Available at: http://www.epa.gov/otaa/standards/nonroad/nonroadci.htm.
122	NMHC stands for Nonmethane hydrocarbons.
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Section 5: Assessment of Emission Reduction Strategies
has approved a DPF specifically for use on RTG cranes for reducing PM25; DPFs do not affect NOx or
C02 emissions.
¦	Installation of a hybrid energy storage system. Cranes with energy storage systems (ESS) can
reduce, but not eliminate, diesel engine emissions by using stored energy to supplement diesel
power. Reductions in NOx and PM25 emissions are estimated to be up to 25%, based on a CARB staff
assessment.123 C02 emission reductions were estimated based on fuel saving measurements from a
2008 study of recapturing energy in cranes through flywheels.124
¦	Conversion to all-electric cranes. For all-electric cranes (e-RTG), zero NOx and PM25 emissions were
assumed. Well-to-wheel C02 emissions are assumed to be 58 percent of a diesel RTG crane's C02
emissions, based on the GREET model.125
The percentage reductions for each strategy were applied to the baseline annual per crane emissions in
this screening assessment. Tables 5-25 and 5-26 show the annual emission reduction for each strategy
alternative for a typical RTG crane.
Table 5-25. Typical Emission Impact per RTG Crane per Year - NOx (lbs)

New/Improved Equipment
c

Tier 2
Tier 3
Tier 4
DPF
RTG ESS
Electric
£
Tier 1
-2,368
-4,398
-7,442
0
-1,945
-7,781

Tier 2

-2,030
-5,074
0
-1,353
-5,413
LU
Tier 3


-3,045
0
-846
-3,383
O
Tier 4



0
-85
-338
Table 5-26. Typical Emission Impact per RTG Crane per Year - PM2.5 (lbs)

New/Improved Equipment
C

Tier 2
Tier 3
Tier 4
DPF
RTG ESS
Electric
£
Tier 1
-288
-288
-440
-388
-114
-457

Tier 2

0
-152
-144
-42
-169
LU
Tier 3


-152
-144
-42
-169
O
Tier 4



0
-4
-17
Table 5-27 shows estimated annual C02 emission reductions per RTG crane for each strategy
combination, calculated on a well-to-wheels basis.
123	California Air Resources Board. Technical Options to Achieve Additional Emissions and Risk Reductions from California
Locomotives and Railyards. August 2009.
124	Mark M. Flynn, Patrick McMullen, & Octavio Solis. Saving Energy Using Flywheels: Energy recovery and emission cutting in a
mobile gantry crane. IEEE Industry Applications Magazine. 2008.
125	Argonne National Laboratory's 2013 GREET model released October 2013. Available at:
https://ereet.es.anl.eov/ereet/index.htm.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-27. Typical Emission Impact per Yard Truck per Year - C02 (tons)

New/Improved Equipment
c
(D
£

Tier 2
Tier 3
Tier 4
DPF
RTG ESS
Electric
Tier 1
0
0
0
0
-45
-70
"d
Tier 2

0
0
0
-45
-70
LU
Tier 3


0
0
-45
-70
0
Tier 4



0
-45
-70
To identify strategies that would be applicable and the most effective in future years, the future year distribution
of RTG cranes was estimated using EPA's NONROAD2008 model.126 Table 5-28 shows the expected distribution of
RTG cranes by Tier in 2011, 2020, 2030, and 2050. This assessment's assumption for a crane's long lifespan results
in a slower turnover of equipment compared to other CHE and greater potential reductions.
Table 5-28. Distribution of RTG Cranes by Tier
Tier
2011
2020
2030
2050
Uncontrolled
6%
1%
0%
0%
Tier 1
27%
3%
0%
0%
Tier 2
20%
5%
1%
0%
Tier 3
38%
17%
2%
0%
Tier 4
9%
74%
98%
100%
Total
100%
100%
100%
100%
EPA notes that the crane distribution used in this screening assessment is not intended to be reflective
of the rate of fleet turnover in practice for a specific port or area.
5.4.2.3. Most Effective Crane Strategies in 2020
In 2020, for this screening assessment, approximately a quarter of the RTG crane fleet was estimated to be
below the Tier 4 nonroad engine standards, making engine repowering and replacement reasonable
strategies to consider for this screening assessment. The cost to repower a RTG crane is estimated to be
$200,000. However, since RTG cranes have high horsepower engines (typically 500hp to 800hp), high activity
rates, and long service lives, strategies to replace or repower older cranes can provide significant benefits per
piece of equipment.
In addition to engine replacements, adding DPFs can provide PM2.5 reductions at a lower cost. DPF
installation costs were assumed to be equivalent to the DPF installation costs for drayage trucks ($10,000).127
However, DPF retrofits as a stand-alone strategy are most likely only applicable in the short term because
exhaust aftertreatment devices are expected to become integrated into Tier 4 rebuilds or replacements;
thus, DPFs were not considered a relevant strategy for the 2020 analysis year for this assessment.
126	RTG cranes are identified in NONROAD as Cranes (SCC: 2270002045).
127	U.S. Environmental Protection Agency, Technical Bulletin: Diesel Particulate Filter General Information, prepared by EPA's
Clean Diesel Program.
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Section 5: Assessment of Emission Reduction Strategies
5.4.2.4. Most Effective Crane Strategies in 2030
By 2030, Tier 4 RTG cranes are projected in this assessment to dominate the fleet and advanced technology hybrid
and electric systems would be needed to achieve additional emission reductions. A hybrid ESS could be added to a
crane to recapture energy in its lift mechanisms; regenerative brakes could be applied as a crane lowers materials,
reducing energy demands from the engine. The flywheel system made by VYCON Energy is one example of this
technology. CARB has estimated the cost of these systems as $160,000 - $320,000.128 However, as long as this
system is applied in tandem with a diesel engine, there would still be some level of diesel emissions.
To fully eliminate emissions, some ports have deployed electric RTG cranes. An electric RTG (e-RTG) crane
removes the diesel generator and powers the motors directly from an external electricity supply. In some
cases, diesel RTG cranes have been converted to fully electric RTG cranes; in many cases, e-RTG cranes are
selected when new cranes are installed. E-RTG cranes are a relatively new technology, with most appearing
in the last 6 years. China appears to be adopting this technology; much of the testing for e-RTGs was found in
this study to be completed at Chinese ports. Other countries with marine terminals using e-RTGs include
Japan, South Korea, Vietnam, Brazil, and the United Kingdom. In 2012, the Port of Savannah became the first
North American port to permanently install an e-RTG crane.129 Retrofitting a crane for full electrification may
range from $200,000 to $300,000, and a demonstration project at the Port of Los Angeles totaled $1.2
million for two electric RTG cranes.130 Costs and cost-effectiveness would vary widely depending on the
remaining life of a crane, the drivetrain of a crane,131 and the electrical infrastructure needs at a terminal.
5.4.3. Container Handlers
Container handlers are pieces of mobile equipment that lift, move, and stack containers in a port
terminal; they include side picks and top picks (also called top handlers).
5.4.3.1. Baseline Emissions
The following assumptions were made to estimate baseline emissions for a typical top handler:132
¦	Average engine size of 282 hp
¦	Load factor of 0.59
¦	1,955 hours of operation per year
128	California Air Resources Board. Technical Options to Achieve Additional Emissions and Risk Reductions from California
Locomotives and Railyards. August 2009.
129	Port Technology, GPA Introduces North America's First ERTG, December 17, 2012. Available at:
http://www.porttechnoloev.ore/news/epa introduces north americas first erte.
130	Port of Los Angeles, Environmental Management Division, Electric Rubber-Tire Gantry Crane Demonstration Project With
West Basin Container Terminal At Berths 97-109, China Shipping Container Lines, March 25, 2009.
131	Some cranes already have electric drivetrains powered by diesel generators, making it possible to retrofit the equipment.
132	U.S. Environmental Protection Agency, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories,
April 2009.
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Section 5: Assessment of Emission Reduction Strategies
Baseline emission factors were assumed to be equal to the EPA Nonroad Compression-Ignition Engine
Exhaust Emission Standards in effect for the average rated power (i.e., 282 hp) and model year of the
engine, as shown in Table 5-29.133
Table 5-29. EPA Emission Standards Applicable to Typical Container Handlers (g/kWh)
Tier
Model Year (beginning)
NMHC
NMHC + NOx
NOx
PM2.5
1
1996
1.3
-
9.2
0.54
2
2003
-
6.6
-
6.6
3
2006
-
4
-
4
4
2011
-
4
-
4
4
2014
0.19
-
0.4
0.02
5.4.3.2. Strategy Effectiveness
Next, the per vehicle percent reduction in emissions was estimated for the application of the following
strategies:
¦	Replacements or repowers. For vehicle replacement and repower using a lower emission diesel engine,
the emission reductions were based on the EPA Nonroad Emission Standards shown in Table 5-29 above.
¦	DPF retrofits. Aftertreatment of diesel exhaust was assumed an 85% reduction in PM2.5 consistent with
typical EPA-verified diesel emission control strategy values.134 DPFs do not result in NOx or C02
reductions.
¦	Electric container handlers. This assessment assumed zero emissions from employing electric container
handler technology. EPA notes that such an option was modeled in this screening assessment, even
though electric hybrid or full electric options for container handlers are not currently available. It is
possible that such options may become available in the future.
The percentage reductions for each strategy were applied to the baseline annual per vehicle emissions for
this screening assessment.
Tables 5-30 and 5-31 show the results of the screening assessment of the expected annual emission
reduction per container handler for each strategy option.
Table 5-30. Typical Emission Impact per Container Handler per Year - NOx (lbs)

New/Improved Equipment
C
(D
£

Tier 2
Tier 3
Tier 4
DPF
Electric
Tier 1
-1,390
-2,781
-4,706
0
-4,920
"d
Tier 2

-1,390
-3,315
0
-3,529
LU
Tier 3


-1,925
0
-2,139
0
Tier 4



0
-214
133	U.S. Environmental Protection Agency, Emission Standards Reference Guide for Nonroad Compression-Ignition Engines.
Available at: http://www.epa.gov/otaa/standards/nonroad/nonroadci.htm.
134	U.S. Environmental Protection Agency, Technologies Diesel Retrofit Devices. Available at:
http://www.epa.eov/cleandiesel/technoloeies/retrofits.htm.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-31. Typical Emission Impact per Container Handler per Year - PM2.5 (lbs)

New/Improved Equipment
c

Tier 2
Tier 3
Tier 4
DPF
Electric
£
Tier 1
-182
-182
-278
-245
-289

Tier 2

0
-96
-91
-107
LU
Tier 3


-96
-91
-107
O
Tier 4



0
-11
Table 5-32 shows estimated annual C02 emission reductions per container handler for each strategy
combination, calculated on a well-to-wheels basis.
Table 5-32. Typical Emission Impact per Container Handler per Year - C02 (tons)

New/Improved Equipment
C
(D
E

Tier 2
Tier 3
Tier 4
DPF
Electric
Tier 1
0
0
0
0
-44
"5
Tier 2

0
0
0
-44
LU
Tier 3


0
0
-44
O
Tier 4



0
-44
To identify strategies that would be applicable and the most effective in future years, the future year
distribution of container handlers was estimated using EPA's NONROAD2008 model.135 Table 5-33 shows the
expected distribution of container handlers by Tier in 2011, 2020, 2030, and 2050.
Table 5-33. Distribution of Container Handlers by Tier
Tier
2011
2020
2030
2050
Uncontrolled
2%
0%
0%
0%
Tier 1
26%
1%
0%
0%
Tier 2
23%
2%
0%
0%
Tier 3
44%
15%
0%
0%
Tier 4
5%
81%
100%
100%
Total
100%
100%
100%
100%
EPA notes that the container handler distribution used in this screening assessment is not intended to
be reflective of the rate of fleet turnover in practice for a specific port or area.
5.4.3.3. Most Effective Container Handler Strategies in 2020
In 2020, in this screening assessment, approximately 18% of all container handlers are still expected to have
engines at Tier 3 standards or below. Retrofitting equipment with at least seven years of remaining useful life
with DPFs would be a cost-effective strategy for reducing PlVbsemissions, although DPFs do not affect NOxor
C02. DPF installation costs were assumed to be equivalent to the costs for installing DPFs for drayage trucks
($19,000).
135 Container handlers are identified in NONROAD as Rubber Tire Loader (SCC: 2270002060).
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Section 5: Assessment of Emission Reduction Strategies
Repowering or replacing/scrapping older equipment to meet Tier 4 standards would be an effective strategy
to reduce both NOx and PM2.5 emissions. As with yard trucks, it is unclear at this time if repowering with Tier
4 engines would be feasible for all container handlers, since Tier 4 compliance would likely involve use of
selective catalytic reduction (SCR) systems. A number of container handlers were repowered in Diesel
Emission Reduction Act (DERA) funded projects for an average full unit cost (equipment and installation) of
$53,484 and top handlers for $63,641. When repowering with Tier 4 is feasible, it would be the most cost
effective option; otherwise, replacement with Tier 4 handlers would be preferable.
5.4.3.4. Most Effective Container Handler Strategies in 2030
By 2030, all container handlers were expected to be at the highest emission standards based on the national fleet
turnover assumed. To reduce emissions beyond the Tier 4 standards, container handlers would have to shift towards
advanced technology options, possibly including hybrids, alternative fuels, and electric technologies. Given the
increasing availability of hybrid options in other types of port vehicles and equipment, such as drayage trucks and
yard trucks, it may be possible that manufacturers would offer hybrid handlers in the future. However, given that top
and side picks use a considerable portion of energy to lift containers, hybrid drivetrains may not provide significant
reductions at this time. Similarly, battery-electric systems may not be available at this time to meet the energy-
intensive lifting demands.136 Top picks must be able to repeatedly lift up to 75,000 lbs by 10 to 40 feet.137
Equipment manufacturers may also develop natural gas options for container handlers. CNG or LNG engines could
potentially reduce emission levels beyond level of Tier 4 standards; however, these options have not been tested for
this type of equipment and little information was found on their emission reduction potential. The relatively low
production volumes of side picks and top picks might also affect manufacturers from pursuing advanced technology
options.
5.4.4. Summary of Most Promising CHE Strategies
Table 5-34 summarizes the most promising emission reduction strategies for CHE in 2020 and 2030.
Table 5-34. Most Promising CHE Emission Reduction Strategies


Per Vehicle Reduction

Years
Effective
CHE Type
Strategy
NOx
PM2.5
C02
Cost


fibs)
(lbs)
(tons)


Replace Tier 4 with CNG/LNG
33
2
17
$30,000
2020, 2030
Yard Truck
Replace Tier 4 with PHEV
64
4
19
$150,000
2020, 2030

Replace Tier 4 with Battery Electric
164
8
34
$210,000
2020, 2030

Retrofit Tier 3 with DPF
0
144
0
$19,000
2020
RTG Crane
Repower Tier 3 with Tier 4
3,045
152
0
$200,000
2020
Install Tier 4 with ESS
85
4
45
$240,000
2020, 2030

Convert Tier 4 to Electric
338
17
70
$500,000
2020, 2030
Container Handler
Retrofit Tier 3 with DPF
0
91
0
$19,000
2020
Repower Tier 3 with Tier 4
1,925
96
0
$64,000
2020
136	TIAX, Roadmap to Electrify Goods Movement Subsystems for the Ports of Los Angeles and Long Beach, Phase 1: Near-Dock
Container Movements, January 2012.
137	TIAX, Assessment of Zero-Emissions Cargo Handling Equipment at the San Pedro Bay Ports, Presented at the
AQMD Clean Fuels Program Advisory Group Meeting, August 29, 2012.
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Section 5: Assessment of Emission Reduction Strategies
5.5. Harbor Craft
Harbor craft includes a wide array of vessel types that largely stay within or near a harbor or port area.
Harbor craft includes tugs, ferries, commercial fishing boats, government vessels, work boats, and
dredges, and they have Category 1 or 2 engines. After ocean going vessels, harbor craft are generally the
next largest contributors of emissions at ports.138
To evaluate emission reduction strategies for harbor craft, this screening assessment considered the two
types of harbor vessels that are the largest contributors to port emissions: tugs and ferries. EPA based
this assumption on existing port emission inventories that identified tugs and ferries as the largest
sources of harbor craft emissions.139,140
5.5.1. Tugs
5.5.1.1. Baseline Emissions
First, emissions were estimated from typical assist tugs that were assumed to be using current (baseline)
technologies (i.e., no application of emission reduction strategies). To do this, the following assumptions
were made for an average assist tug:141
¦	Two Category 1 propulsion engines per tug
¦	Average engine power of 1,540 kW
¦	1,861 annual operating hours
¦	Load factor of 0.79, based on average tug engine displacement category and power142
Baseline emission factors were obtained from the EPA Regulatory Impact Analysis for the 2008
Locomotive and Marine Compression Ignition Engine rulemaking.
Table 5-35 summarizes the emission factors from EPA's 2008 rulemaking that apply to the engine
displacement and power category for tugs.
138	U.S. Environmental Protection Agency, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories,
April 2009.
139	Starcrest Consulting Group, LLC, Puget Sound Maritime Air Emissions Inventory, prepared for Puget Sound Maritime Air
Forum, pg. 156, 2011. Available at:
http://www.pugetsoundmaritimeairforum.org/uploads/PV FINAL POT 2011 PSEI Report Update 23 May 13 sce.pdf.
140	Port of Long Beach, Air Emissions Inventory, pg. 46, 2013. Available at:
http://www.polb.com/civica/filebank/blobdload.asp?BloblD=12238.
141	U.S. Environmental Protection Agency, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories,
2009. Document references Puget Sound emissions inventory, which indicates 90% of all tug engines are Category 1.
142	U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Locomotive
Engines and Marine Compression Ignition Engines Less than 30 Liters Per Cylinder, 2008.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-35. EPA Emission Factors Applicable to Assist Tugs (g/kW-hr)
Tier
Beginning Standards Year
NOx
PM10
Pre-Control

11
0.3
Tier 1
2000
9.2
0.3
Tier 2
2004-2007
6
0.13
Tier 3
2012
4.81
0.07
Tier 4
2016
1.3
0.03
5.5.1.2. Strategy Effectiveness
Next, the percent reduction in emissions was estimated, per tug, for each strategy. More details on the
strategies and relevant assumptions are listed as follows:
¦	Replacements and repowers. For vessel engine replacement and repower using conventional
equipment, the emission reduction for the screening assessment was based on the emission factors
shown in Table 5-35.
¦	Diesel oxidation catalysts (DOCs) and DPFs. For these technologies, a 25% and 85% reduction in PM2.5
was assumed, respectively, consistent with typical EPA-verified diesel emission control strategy values.
These strategies do not impact NOx and C02 emissions.
¦	Biodiesel (B20). For this fuel, NOx and PM2.5impacts were based on comparisons with diesel using
MOVES2010b simulations for heavy-duty vehicles—a 0.4% increase in NOx and a 3.2% reduction in
PM2.5.143 C02 impacts were based on the GREET model and assumed a 14% reduction compared to diesel
on a well-to-wheels basis.
¦	Hybrid-electric tugs. The assessment assumed for this alternate technology, a 30%, 25%, and 30%
reduction in NOx, PM2.5, and C02 respectively, consistent with EPA-verified retrofit technology.144
¦	LNG. The emissions benefits of LNG tugs as compared to Tier 4 are uncertain at this time, as this is an
emerging technology and has not been subject to extensive testing.145 This screening assessment
assumed LNG provided a 25% NOx reduction, a 20% PM25 reduction, and C02 reductions similar to a Tier
4 diesel engine, based on evidence from other diesel sectors.146
The percentage reductions for each strategy were applied to the baseline annual per tug emissions.
Tables 5-36, 5-37, and 5-38 show estimated annual emission reductions for a typical tug for each potential
strategy. C02 emission reductions are calculated on a well-to-wheels basis.
143	For purposes of this screening assessment, results were taken from a prior analysis done with MOVES2010b. This is not
expected to differ significantly from MOVES2014 or MOVES2014a, and is the best available model for estimating these effects
since the current NONROAD model does not predict emissions for the commercial marine sector.
144	Based on EPA-verified Foss Maritime/AKA XeroPoint Hybrid Tugboat Retrofit System. Available at:
https://www.epa.gov/verified-diesel-tech/verified-technologies-list-clean-diesel.
145	The world's first LNG tug was announced in early 2012. See: http://articles.maritimepropulsion.com/article/Worlde28099s-
First-LNG-Fuelled-Tue65983.aspx.
146	ICF International, Comprehensive Regional Goods Movement Plan and Implementation Strategy: Task 10.2 Evaluation of
Environmental Mitigation Strategies, prepared for the Southern California Association of Governments, April 2012. Available
at: www.freightworks.org/DocumentLibrarv/Task%2010%202%20report%20April%202012%20final%20no%20watermark.pdf.
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Table 5-36. Typical Emission Impact per Tug per Year - NOx (lbs)


New/Improved Equipment


Tier 1
Tier 2
Tier 3
Tier 4
DOC
DPF
B20
Hybrid
LNG

Pre-Control
-17,970
-49,917
-61,798
-96,840
0
0
439
-100,733
-100,084
Did
ipmen
Tier 1

-31,947
-43,828
-78,870
0
0
367
-82,763
-82,114
Tier 2


-11,880
-46,922
0
0
240
-50,816
-50,167
3
O"
Tier 3



-35,042
0
0
192
-38,936
-38,287
LU
Tier 4




0
0
52
-3,894
-3,245
Table 5-37. Typical Emission Impact per Tug per Year - PM2.5 (lbs)

New/Improved Equipment


Tier 1
Tier 2
Tier 3
Tier 4
DOC
DPF
B20
Hybrid
LNG
+j
Pre-Control
0
-1,697
-2,296
-2,696
-749
-2,546
-96
-2,770
-2,755
c
a;
"a E
O ¦Q-
Tier 1

-1,697
-2,296
-2,696
-749
-2,546
-96
-2,770
-2,755
Tier 2


-599
-998
-324
-1,103
-42
-1,073
-1,058
3
cr
Tier 3



-399
-175
-594
-22
-474
-459

Tier 4




0
0
-10
-75
-60
Table 5-38. Typical Emission Impact per Tug per Year - C02 (tons)

New/Improved Equipment


Tier 1
Tier 2
Tier 3
Tier 4
DOC
DPF
B20
Hybrid
LNG
Old
Equipment
Pre-Control
0
0
0
0
0
0
-627
-1,320
-903
Tier 1

0
0
0
0
0
-627
-1,320
-903
Tier 2


0
0
0
0
-627
-1,320
-903
Tier 3



0
0
0
-627
-1,320
-903
Tier 4




0
0
-627
-1,320
-903
To identify which strategies would be most effective in future years, the future year distributions of tugs
were modeled using a methodology based on the growth and scrappage assumptions in EPA's
NONROAD2008 model. Table 5-39 shows expected distribution of tugs by tier in the future analysis years.
Table 5-39. Distribution of Tugs by Tier
Tier
2011
2020
2030
2050
TierO
61%
10%
0%
0%
Tier 1
35%
24%
3%
0%
Tier 2
4%
33%
7%
0%
Tier 3
0%
30%
80%
61%
Tier 4
0%
3%
10%
39%
Total
100%
100%
100%
100%
EPA notes that the tug national distribution used in this screening assessment is not intended to be
reflective of the rate of fleet turnover in practice for a specific port or area.
5.5.1.3. Most Effective Tug Strategies in 2020
In this screening assessment, by 2020, only a small fraction of tugs are projected to be Tier 0, and
these vessels may have limited remaining useful service life, so they were not considered for the
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Section 5: Assessment of Emission Reduction Strategies
strategy scenarios in this assessment. Tier 1 vessels accounted for nearly a quarter of all tugs in 2020;
provided these tugs have some remaining service life, the most cost-effective strategies would target
these vessels. Repowering of tug propulsion engines costs approximately $500,000 (installation plus
purchase cost) per vessel, based on past DERA grants. Repowering with a Tier 4 engine requires
additional space in the engine room and would not be possible in all tugs. Given the long useful life of
these engines, combining public and private funds may help pay the costs of repowering a tug and
result in cost-effective emission reductions; such an approach would be less expensive than buying a
new vessel.
Retrofitting with DPFs would also be an effective PM2.5 reduction strategy for tug engines with
significant remaining service life. In this assessment, a large fraction (33%) of the 2020 tug fleet
would be Tier 2, with engines 13-16 years old, and 24% would be Tier 1, with engines 16-20 years old.
PM2.5 reductions of approximately 85% can be achieved using DPF retrofits. The cost of a DPF retrofit
for a tug is approximately $60,000.147 As noted above, this strategy does not affect NOx or C02
emissions.
Another potential strategy would be replacement of a Tier 2 tug with a new Tier 4 tug. This strategy
achieved large NOx and PM2.5 reductions. However, the full cost of a new assist tug would be high,
often more than $10 million. Advanced technology LNG and hybrid tugs are estimated to add an
additional 20 to 40% above cost of new conventional diesel boats. If a port is replacing a Tier 2 vessel
with Tier 4, the additional cost of an LNG or hybrid technology may not be warranted, given the small
additional emission reduction benefit.
5.5.1.4. Most Effective Tug Strategies in 2030
In 2030, an estimated 90% of tugs would still be pre-Tier 4 tugs, based on the assumptions in this
assessment. Thus, retirement and replacement with Tier 4 vessels could yield significant NOx and
PM2.5 benefits. The cost-effectiveness of this strategy depends on the remaining useful service life of
the older tugs. For tugs with the space configuration to accommodate Tier 4 technologies, repowering
would be an option and significantly more cost-effective than a full tug replacement.
Advanced technologies or alternative fuels would be necessary to achieve emission reductions beyond
Tier 4 levels for tugs. These vessels are just starting to become commercially available, so the
emission reduction benefits and costs of these options are uncertain. The world's first LNG tug was
placed in commercial service in Norway in 2014.148 Foss Maritime has operated two diesel-hybrid tugs
147	ICF International, Tug/Towboat Emission Reduction Feasibility Study, Prepared for U.S. EPA, 2009.
148	Maritime Journal, Sanmar completes the world's first LNG tug, Nov 12, 2013. Available at:
http://www.maritimeiournal.com/newsl01/tugs.-towing-and-salvage/sanmar-completes-the-worlds-first-lng-tug.
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Section 5: Assessment of Emission Reduction Strategies
at the Ports of Los Angeles and Long Beach.149 Both of these options have the potential to produce
lower emissions than a conventional diesel Tier 4 tug, but the magnitude of emission reduction
benefits is uncertain at this time. These advanced technology tugs would also carry a higher cost than
diesel, with the incremental costs likely to decline if production volumes grow in the future.
Shore power (or cold ironing) is another potential strategy that was considered for tugs, but this
technology may not be as feasible for tugs because of their typical operating cycles.150 However, shore
power is being used to various degrees in select locations. For example, Constellation Maritime keeps
all their tugs on shore power whenever they are at the dock at the Port of Boston.151 Tugboat cold
ironing has also been done at the Port of Philadelphia.152 This strategy was not included in the
screening assessment, as this assessment did not include idling emissions from tugs at dock.
However, that assumption may not apply to every port in practice, and ports with significant tug idling
can consider shore power as a potential strategy.
5.5.2. Ferries
Ferries can be a major source of emissions at some ports. For example, in the 2011 Puget Sound
emission inventory, ferries were responsible for about half of harbor craft emissions and 10 to 15% of
total NOx and PM emissions included in the inventory.153 At other ports, ferries may be a much smaller
contributor.
5.5.2.1. Baseline Emissions
The emissions from "typical" ferries in this screening assessment were estimated using current
(baseline) technologies (i.e., no application of emission reduction strategies). The following assumptions
were made for an average ferry:154
¦	Average of 1.9 Category 2 propulsion engines per vessel
¦	Average engine power of 857.5 kW
¦	1,693 annual operating hours
¦	Load factor of 0.85, based on average tug engine displacement category and power155
149	Foss Maritime Company, World's First True Hybrid to be Built by Foss Maritime, March 2, 2007. Available at:
http://www.foss.com/press-releases/worlds-first-true-hvbrid-tue-to-be-built-bv-foss-maritime/.
150	ICF International, Tug/Towboat Emission Reduction Feasibility Study, Prepared for U.S. EPA, 2009.
151	Ibid.
152	Ibid.
153	Port of Seattle, Puget Sound Maritime Air Emissions Inventory, 2011. Available at:
https://www.portseattle.org/Environmental/Air/Seaport-Air-Qualitv/Paees/Puget-Sound-Maritime-Air-Emissions-
Inventorv.aspx.
154	U.S. Environmental Protection Agency, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories,
2009.
155	U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Locomotive
Engines and Marine Compression Ignition Engines Less than 30 Liters Per Cylinder, 2008.
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Section 5: Assessment of Emission Reduction Strategies
Baseline emission factors were obtained from the EPA Regulatory Impact Analysis for the 2008
Locomotive and Marine Compression Ignition Engine rulemaking, and Table 5-40 summarizes the
emission factors that apply to the engine displacement and power category for ferries.
Table 5-40. Emission Factors Applicable to Ferries (g/kW-hr)
Tier
Beginning Standards Year
NOx
PM10
TierO
-
13.36
0.32
Tier 1
2004
10.55
0.32
Tier 2
2007
8.33
0.32
Tier 3
2013
5.97
0.11
Tier 4
2018
1.3
0.03
5.5.2.2. Strategy Effectiveness
The per-ferry percent reduction in emissions was estimated for the application of each of the following
strategies:
¦	Replacements and repowers. For vessel engine replacement and repower using conventional
equipment, the emission reduction was based on the emission factors shown in Table 5-40.
¦	DOCs and DPFs. For these technologies, a 25% and 85% reduction in PM2.5 was assumed,
respectively, consistent with typical EPA-verified diesel emission control strategy values.156 These
strategies do not reduce NOx and C02 emissions.
¦	Biodiesel (B20). NOx and PM2.5 impacts from B20 fuel were based on comparisons with diesel using
MOVES2010b simulations for heavy-duty vehicles—a 0.4% increase in NOx and a 3.2% reduction in
PM 143. CO2 impacts are based on the GREET model and assumed a 14% reduction compared to
diesel on a well-to-wheels basis.
¦	Hybrid-electric ferries. There is little emissions data available in the literature for hybrid-electric
technology for ferries, so the same emission reductions were assumed as for hybrid tugs: a 30%,
25%, and 30% reduction in NOx, PM2.5, and C02 respectively.
The percentage reductions for each strategy were applied to the baseline annual per ferry emissions.
Tables 5-41, 5-42, and 5-43 show typical annual emission reductions for each ferry strategy considered
in this screening assessment. C02 emission reductions are calculated on a well-to-wheels basis.
156 U.S. EPA, Technologies Diesel Retrofit Devices. Available at: https://www.epa.gov/verified-diesel-tech/verified-technologies-
list-clean-diesel.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-41. Typical Emission Impact per Ferry per Year - NOx (lbs)

New/Improved Equipment


Tier 1
Tier 2
Tier 3
Tier 4
DOC
DPF
B20
Hybrid
Old
Equipment
Pre-Control
-14,524
-25,999
-38,198
-62,336
0
0
276
-64,352
Tier 1

-11,475
-23,673
-47,812
0
0
218
-49,828
Tier 2


-12,198
-36,337
0
0
172
-38,353
Tier 3



-24,139
0
0
123
-26,154
Tier 4




0
0
27
-2,016
Table 5-42. Typical Emission Impact per Ferry per Year - PM2.5 (lbs)

New/Improved Equipment


Tier 1
Tier 2
Tier 3
Tier 4
DOC
DPF
B20
Hybrid
Old
Equipment
Pre-Control
0
0
-1,085
-1,499
-414
-1,406
-53
-1,538
Tier 1

0
-1,085
-1,499
-414
-1,406
-53
-1,538
Tier 2


-1,085
-1,499
-414
-1,406
-53
-1,538
Tier 3



-414
-142
-483
-18
-452
Tier 4




0
0
-5
-39
Table 5-43. Typical Emission Impact per Ferry per Year - C02 (tons)

New/Improved Equipment


Tier 1
Tier 2
Tier 3
Tier 4
DOC
DPF
B20
Hybrid
Old
Equipment
Pre-Control
0
0
0
0
0
0
-325
-683
Tier 1

0
0
0
0
0
-325
-683
Tier 2


0
0
0
0
-325
-683
Tier 3



0
0
0
-325
-683
Tier 4




0
0
-325
-683
To identify which strategies would be most effective in future years, the future year distributions of
ferries was modeled using a methodology based on the growth and scrappage assumptions in EPA's
NONROAD2008 model. Table 5-44 shows the estimated distribution of ferries by tier by analysis year for
this assessment. Ferries have longer service life and consequently slower fleet turnover than tugs, and
therefore, relatively few ferries are projected to meet Tier 4 standards in 2020 and 2030.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-44. Distribution of Ferries by Tier
Tier
2011
2020
2030
2050
TierO
75%
39%
10%
0%
Tier 1
21%
18%
12%
0%
Tier 2
4%
10%
8%
1%
Tier 3
0%
28%
59%
60%
Tier 4
0%
5%
11%
39%
Total
100%
100%
100%
100%
EPA notes that the national ferry distribution used in this screening assessment is not intended to be
reflective of the rate of fleet turnover in practice for a specific port or area.
5.5.2.3.	Most Effective Ferry Strategies in 2020
Strategies to reduce ferry emissions in 2020 focused on the vessels with pre-control (Tier 0) and Tier 1
engines, since they account for a large fraction of the ferry fleet in this screening assessment and have the
highest emission rates. Repowering ferries with Tier 3 engines has been a successful use of DERA funds, and
the cost is approximately $200,000—far less expensive than full vessel replacement. It is unclear if
repowering with Tier 4 engines would be feasible for ferries, given the additional space requirements for Tier
4 emission controls. Given the long useful life of these engines, repowering a ferry can result in cost-effective
emission reductions, especially if combining public and private funds to pay for such an investment.
Another cost-effective option for PM2.5 reductions is a retrofit with a DPF, provided the engine has substantial
remaining service life. DPFs eliminate approximately 85% of PM emissions, but this strategy does not affect
NOx or C02 emissions. The cost of a DPF retrofit for a ferry is approximately $60,000.157
Large NOx and PM emission reductions in 2020 could be achieved in this assessment by replacing older
ferries with new Tier 4 ferries, or possibly with used Tier 3 ferries. The full cost of a large new ferry can be
extremely high. For example, Washington State Ferries is adding two new 144-car, 1,500 passenger ferries
for service in Puget Sound; each will cost about $130 million.158
5.5.2.4.	Most Effective Ferry Strategies in 2030
By 2030, 89% of the ferry fleet would still be below Tier 4 standards in this assessment, and strategies could
focus on replacing or repowering these ferries. For ferries that have the spatial configuration to
accommodate the emission control technologies, the most cost-effective approach would be to repower
these vessels with Tier 4 engines. Additionally, repowering would be more cost-effective for newer vessels
with longer remaining service lives. The cost of repowering with Tier 4 is unknown, but may likely be higher
than costs to date for Tier 2 or 3 repowers. This assessment assumed $300,000 for the purposes of this
screening assessment.
157	ICF International, Tug/Towboat Emission Reduction Feasibility Study, Prepared for U.S. EPA, 2009.
158	Washington State Department of Transportation, Ferries-Olympic Class (144-Car) Ferries, 2015. Available at:
http://www.wsdot.wa.eov/proiects/ferries/144carferries/.
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Section 5: Assessment of Emission Reduction Strategies
For Tier 2 ferries, retrofits with DPFs are an effective strategy to reduce PM2.5 emissions. However, because
the Tier 2 ferries would be approximately 20 years old in 2030 in this assessment, retrofits will only make
sense for ferries and engines with significant remaining service life. In most cases, retirement of old Tier 2
ferries is more likely to be in the best interest of the operator.
Because the bulk of the ferry fleet is projected in this assessment to be Tier 3 or lower in 2030, there may be
little incentive to pursue the use of advanced technologies that can potentially achieve emission rates lower
than Tier 4 standards. However, when new ferries are purchased, advanced technologies like diesel hybrids
would likely be viable and potentially cost-effective by 2030, since they reduce operating costs. Hybrid ferries
are an emerging technology—with several in service or on order in the United States and Europe. The
magnitude of emission reduction benefits and incremental costs associated with hybrid ferries is difficult to
predict in future years. This screening assessment assumed 30% NOx, 25% PM2.5, and 30% C02 emission
reductions over new Tier 4 diesel ferries.
Shore power may be another potential strategy to reduce ferry emissions; but since ferry idling at dock was
not included in this assessment, it was not considered in this screening assessment. The cost effectiveness of
this approach is uncertain because infrastructure costs range widely depending on a number of terminal-
specific factors. However, as shore power projects are implemented around the world, more data on the
benefits and costs of this strategy may be available in the future.
5.5.3. Summary of Most Promising Harbor Craft Strategies
Table 5-45 summarizes the most promising emission reduction strategies for harbor craft in 2020 and 2030.
Table 5-45. Most Promising Harbor Craft Emission Reduction Strategies
Vessel
Type
Strategy
Per Vessel Reduction
Cost
Years
Effective
NOx (lbs)
PMz.sllbs)
CO2 (tons)
Tugs
Retrofit Tier 1 with DPF
0
2,546
0
$60,000
2020
Retrofit Tier 2 with DPF
0
1,103
0
$60,000
2020
Repower Tier 1 with Tier 3
43,828
2,296
0
$500,000
2020
Replace Tier 3 with Tier 4
35,042
399
0
$10 million
2030
Ferries
Retrofit Tier 1/2 with DPF
0
1,406
0
$60,000
2020
Repower Tier 0 with Tier 3
38,198
1,085
0
$200,000
2020
Repower Tier 1 with Tier 3
23,673
1,085
0
$200,000
2020
Repower Tier 1/2 with Tier 4
36,337
1,499
0
$300,000
2030
Repower Tier 3 with Tier 4
24,139
414
0
$300,000
2030
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Section 5: Assessment of Emission Reduction Strategies
5.6. Ocean Going Vessels
5.6.1.	Introduction
Ocean Going Vessels (OGVs) have historically been the largest contributor to port emissions. Examples
of OGVs include containerships, tankers, bulk carriers, auto carriers, refrigerated vessels (reefers), roll-
on/roll-off (RORO), and passenger cruise ships. OGV emissions are produced by main (propulsion)
engines and by auxiliary engines. OGV activity modes include reduced speed zone (RSZ), maneuvering,
and hoteling. During hoteling, the propulsion engine is turned off and only the auxiliary engine operates
unless the vessel is relying on shore power (i.e., plugging the OGV into the shore-side electricity grid).
The majority of the emissions from OGVs within the boundaries of this assessment are from hoteling.
5.6.2.	Baseline Emissions
The baseline emissions for the screening assessment include the impacts of EPA's OGV engine and fuel
standards for appropriate years. The methodology is generally consistent with the methodology used in
EPA's Category 3 Marine Engine Rulemaking,159 unless otherwise noted. The following paragraphs
describe the background and factors considered when quantifying baseline emissions.
The International Maritime Organization (IMO) adopted mandatory NOx emission limits in Annex VI to
the International Convention for Prevention of Pollution from Ships in 1997. These NOx limits apply for
all marine engines over 130 kilowatts (kW) for engines built on or after January 1, 2000, including those
engines that underwent a major rebuild after January 1, 2000. For the Category 3 Marine Engine
Rulemaking Regulatory Impact Analysis (C3 RIA)160, EPA determined the effect of the IMO standard to be
a reduction in the NOx emission rate of 11% below that for engines built before 2000. For engines built
between 2000 and 2010 (Tier I), a NOx factor of 0.89 should be applied to the calculation of NOx
emissions for both propulsion and auxiliary engines. IMO Tier II NOx emission standards start in 2011
and EPA determined the effect of Tier II to be a NOx reduction of 2.5 g/kWh reduction over Tier I
engines. In addition, starting August 2012, any ships traveling within 200 nautical miles of the U.S.
coastline must adhere to regulations set for the North American Emission Control Area (ECA)161. These
include fuel sulfur levels at 1% starting August 2012 and 0.1% starting 2015. Furthermore any engine
above 130 kW installed on a ship constructed beginning in 2016 must meet Tier III NOx levels which EPA
determined were an 80% reduction from Tier I. Thus Tier III emission factors are 20% of Tier I emission
factors. NOx emission factors by Tier and engine type are shown in Table 5-46. Engine types include
159	U.S. Environmental Protection Agency, Control of Emissions from New Marine Compression-Ignition Engines at or Above 30
Liters per Cylinder, Federal Register, Vol 75, No 83, April 30, 2010.
160	U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Category 3
Marine Diesel Engines, EPA Report EPA-420-R-09-019, December 2009. Available at:
http://www.epa.gov/otaa/regs/nonroad/marine/ci/420r09019.pdf.
161	U.S. Environmental Protection Agency, Designation of North American Emission Control Area to Reduce Emissions from
Ships, Fact Sheet EPA-420-F-10-015, March 2010.
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Section 5: Assessment of Emission Reduction Strategies
medium speed diesel (MSD) propulsion engines, slow speed diesel (SSD) propulsion engines and
auxiliary engines.
Table 5-46. NOx Emission Factors by Engine Type and Tier (g/kWh)
Emission Tier
MSD
SSD
Auxiliary
0
13.2
17
13.9
1
11.7
15.1
12.4
II
9.4
12.1
9.9
III
2.3
3.0
2.5
In addition to the MARPOL Annex VI emission limits that apply to all ships engaged in international
transportation, U.S. vessels must also comply with EPA's Clean Air Act requirements for engines and
fuels. The NOx emission limits for Category 3 (C3) engines are equivalent to the MARPOL Annex VI NOx
limits. EPA's sulfur limit for distillate locomotive or marine (LM) diesel fuel sold in the United States is
more stringent than the ECA fuel sulfur limit; the sulfur limit for ECA fuel for use on C3 marine vessels is
equivalent to the MARPOL Annex VI SOx limits. EPA also has standards for C3 engines162 which are
generally the same or more stringent. However, almost all C3 engines used in international shipping fall
under IMO regulations.
In addition, as part of the new IMO standards, marine diesel engines built between 1990 and 1999 that
are 90 liters per cylinder or more need to be retrofitted to meet Tier I emission standards upon engine
rebuild if a retrofit kit is available to the ships. Also consistent with the C3 RIA, this assessment assumed
that 80% of all ships > 90L / cylinder will have retrofit kits available. In the C3 RIA, it was assumed that
this phase in will happen over 5 years, 20% of eligible ships each year, starting in 2011. Since the 2011
phase in represents less than 0.4% of NOx emissions by ships at the 19 ports, no engines were assumed
to be rebuilt in this assessment's baseline estimated. However for 2015 and later, 80% of 1990 through
1999 engines greater than 90 liters per cylinder were assumed rebuilt to Tier I standards.
In order to calculate NOx reductions due to fleet turnover, NOx adjustment factors were calculated for
2020 and 2030.163 To accomplish this, installed power age profiles by engine type for propulsion engines
and by vessel type for auxiliary engines were developed using 2011 Entrances and Clearances data164
and Lloyd's vessel characterization data.165 It was important to calculate separate baseline emissions for
both propulsion and auxiliary engines, to reflect the different types of operation modes that occur as
well as to target specific emission reduction strategies.
162	U.S. Environmental Protection Agency, Control of Emissions from New Marine Compression-Ignition Engines at or Above 30
Liters per Cylinder, 75 FR 83, April 30, 2010.
163	The same NOx emission factors were applied across the entire OGV inventory in this analysis.
164	U.S. Army Corps of Engineers, Vessel Entrances and Clearances. Available at:
http://www.navigationdatacenter.us/data/dataclen.htm.
165Available at: http://www.sea-web.com.
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Section 5: Assessment of Emission Reduction Strategies
For OGV propulsion engines that operate when the vessel is maneuvering, installed power by engine
type was calculated for each model year based upon the sum of the total propulsion power over the
Entrances and Clearances data. In addition, to calculate the effect of retrofitting Tier 0 engines of more
than 90 liters per cylinder, installed power was also calculated for MSD and SSD engines that were over
90 liters per cylinder. Ages were determined by subtracting the build year from 2011. This 2011 age
profile was then used in both 2020 and 2030, adjusting model years to fit the age profile.166 This same
methodology was used in the EPA's C3 RIA.
Auxiliary engines typically operate when a vessel is hoteling. In this assessment, auxiliary power was
calculated from the propulsion power using the auxiliary power to propulsion power ratios by ship type.
This is a slight variation from the C3 RIA, which used the propulsion installed power to calculate auxiliary
engine NOx factors. Auxiliary engines were only segregated into passenger ships and other because in
2011 different residual oil (RO) to marine gas oil (MGO) ratios were used.
Average NOx emission factors by year and engine type, calculated as described above, are listed below
in Table 5-47. Auxiliary engines are broken into those in passenger ships and those in other vessels
because passenger ships were assumed to use different RO/distillate fuel ratios in 2011 than other
ships, as described in Appendix B.
Table 5-47. Average NOx Emission Factor (g/kWh) by Engine Type and Year
Year
Propulsion Engines
Auxiliary Engines
MSD
SSD
Passenger
Other
2020
9.4
10.6
10.3
8.6
2030
3.7
5.0
3.7
4.1
PM2.5 emissions factors for various fuel sulfur levels are shown in Table 5-48. These were calculated by
using the equations listed below which were determined by EPA in its C3 rulemaking and applying the
0.92 conversion factor for PM2.5 to PM10 emissions.
PM10 EF = 0.23 + BSFC x 7 x 0.02247 x (Fuel Sulfur Fraction - 0.0024)	Eq. 5-1
Table 5-48. PM2.5 Emission Factors by Engine Type and Fuel Type (g/kWh)
Fuel
Sulfur (ppm)
MSD
SSD
Auxiliary
MDO/MGO
1,000
0.17
0.17
0.17
500
0.16
0.16
N/A
200
0.15
0.15
N/A
ULSD
15
N/A
N/A
0.14
166 For example, a 5-year old engine in 2011 is a 2006 model year, but in 2020, such an engine is a 2015 model year (and in 2030
a 2025 model year).
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Exhaust C02 emission factors are assumed to only vary by engine type and are shown in Table 5-49.
Table 5-49. C02 Emission Factors by Engine Type (g/kWh)
MSD
SSD
Auxiliary
646
589
691
For the purpose of this assessment, LNG emission factors are determined from the IMO GHG study167
and are shown in Table 5-50. They are applied for both propulsion and auxiliary engines.
Table 5-50. LNG Emission Factors (g/kWh)
NOx
PM2.5
CO2
1.3
0.03
457
Finally well-to-pump/plug emission factors are shown in Table 5-51 and were determined using
GREET2014.168
Table 5-51. Well-to-Pump/Plug C02 Emission Factors (g/kWh)
Fuel
SSD
MSD
Auxiliary
Otto
2020
2030
2020
2030
2020
2030
2020
2030
MGO/MDO
99
105
108
115
116
123
N/A
N/A
ULSD
N/A
N/A
N/A
N/A
115
123
N/A
N/A
LNG
N/A
N/A
N/A
N/A
N/A
N/A
98
94
Electricity
N/A
N/A
N/A
N/A
517
477
N/A
N/A
5.6.3. Strategy Effectiveness
The primary opportunities to reduce OGV emissions analyzed for this report are listed below with
additional details.
¦ Diesel fuel with 500 ppm sulfur in propulsion engines for bulk carriers, container ships, passenger
ships and tankers. Conventional OGV propulsion engine fuel has been residual fuel oil, which can
have sulfur content of 2 to 3%. Since 2015, all vessels entering the ECA are required to use 0.1%
sulfur (1,000 ppm) distillate (MDO/MGO). Using 500 ppm sulfur diesel fuel instead of MDO/MGO in
propulsion engines would reduce PM2.5 emissions per call by 0.5 to 1.4%, depending on ship type.
This strategy does not affect NOx and C02 emissions.
167	International Maritime Organization, Third IMO GHG Study, June 2014. Available at
http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Pages/Relevant-links-to-Third-IMO-GHG-
Studv-2014.aspx.
168	Argonne National Laboratories, GREET Model 2014. Available at: https://ereet.es.anl.eov/.
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Section 5: Assessment of Emission Reduction Strategies
¦	Diesel fuel with 200 ppm sulfur in propulsion engines for bulk carriers, container ships, passenger
ships and tankers. Using 200 ppm diesel fuel instead of MDO/MGO in propulsion engines would
reduce PM25 emissions per call by 0.7 to 2.2%, depending on ship type. However, this strategy does
not affect NOx and C02 emissions.
¦	Ultra-low sulfur diesel (ULSD) fuel in auxiliary engines for bulk carriers, container ships, passenger
ships and tankers. ULSD has sulfur content of 15 ppm. Compared to the 1,000 ppm MDO/MGO
required for all vessels entering the ECA as of 2015, use of ULSD would further reduce PM25
emissions by 15.1 to 17.4%, depending on ship type. This strategy does not affect NOx or exhaust
C02 emissions but reduces well-to-generator C02 emissions by 0.1%.
¦	LNG in propulsion engines for bulk carriers, container ships and tankers. LNG has negligible sulfur
content and reduces NOx, PM25and C02 emissions. Use of LNG to replace 1,000 ppm sulfur
MDO/MGO in propulsion engines reduces per call NOx emissions by 4.8 to 14.0% depending on ship
type, PM2.5 emissions by 5.6 to 14.9%, exhaust C02 emissions by 1.0 to 2.2% and well-to-propeller
C02 emissions by 0.9 to 2.0%.
¦	Use of LNG in auxiliary engines for bulk carriers, container ships and tankers. Use of LNG to replace
1,000 ppm sulfur MDO/MGO in auxiliary engines reduces per call NOx emissions by 57.5 to 79.3%
depending on ship type, PM25 emissions by 67.3 to 76.6%, exhaust C02 emissions by 30.6 to 32.3%
and well-to-propeller C02 emissions by 28.2 to 30.3%.
¦	Shore power for container ships, passenger ships and reefers. In this strategy, the ship is connected
to the electrical grid while at berth. This strategy would be limited to frequent callers because of the
retrofit cost per vessel to accept shore power. A frequent caller is a vessel that goes to the same
port multiple times during the same year. This assessment assumed that approximately 2 hours per
call would be used to connect and disconnect the cables to the ship. During the time the cables are
connected, auxiliary engines are shut off, greatly reducing ship emissions. There are some C02
emissions generated from the power plant supplying electricity to the ship, but these are generally
less than those generated by the auxiliary engines. Exhaust emissions during hoteling are reduced
80 to 97% depending upon ship type. This reduces per call NOx emissions by 62.1 to 89.9%
depending on ship type, PM25 emissions by 62.0 to 89.4%, exhaust C02 emissions by 62.3 to 90.9%
and well-to-propeller C02 emissions by 22.4 to 37.6%.
¦	Advanced Marine Emission Control System (AMECS) for container ships and tankers. In this
strategy, the ship's exhaust is captured and processed, and the AMECS is barge mounted and uses
the barge auxiliary engine to power the system. The AMECS draws 165 kW to operate the emission
reduction equipment. The bonnet captures 90% of the exhaust and reduces captured NOx emissions
by 90% and PM25emissions by 95%.169 However, AMECS strategies do not reduce C02 emissions.
Like shore power, it is assumed that roughly 2 hours is necessary to install and remove the AMECS
from a given vessel, during which time both the barge and ship auxiliary engines are operating and
169 California Air Resources Board, Executive Order AB-15-01 - Clean Air Engineering-Maritime, Inc., June 2015. Available at
http://www.arb.ca.eov/ports/shorepower/eo/ab-15-01.pdf.
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Section 5: Assessment of Emission Reduction Strategies
producing emissions. This strategy would be most applicable for use on non-frequent caller vessels.
This reduces per call NOx emissions by 67.0 to 80.0% depending on ship type, PM2.5 emissions by
65.7 to 80.3%, and increases exhaust C02 emissions by 7.4 to 9.5% as well as well-to-propeller C02
emissions by the same amount.
¦ Reduced hoteling time for container ships. By improving cargo handling equipment operation,
unloading and loading times for a container ship can be improved. For this strategy, hoteling time is
estimated to be reduced by 10%, which directly reduces hoteling emissions by 10%. This reduces per
call NOx emissions by 7.3%, PM2.5 emissions by 7.1%, C02 emissions (both exhaust and well-to-
propeller) by 7.8%.
As part of this analysis, a screening assessment was conducted for OGV strategies in 2020 for three
typical ship types: an average container ship, an average passenger (cruise) ship, and an average tanker
ship. In practice, these three vessel types can account for the vast majority of OGV emissions at most
ports. The screening assessment relied on assumptions for typical vessel size and operating
characteristics for these vessels. These are shown in Table 5-52.
Table 5-52. Ship Characteristics for Screening Analysis
Ship Type
Propulsion
Auxiliary
Engine
Service
Speed
(knots)
RSZ
Maneuver
Engine
RSZ
Maneuver
Hotel
kW
Type
LF
Hrs
LF
Time
kW
LF
Hrs
LF
Hrs
LF
Hrs
Container
47,172
SSD
23.8
0.18
0.40
0.02
1.4
10,325
0.25
0.40
0.50
1.4
0.17
30.8
Passenger
49,970
MSD-ED
22.6
0.24
0.40
0.02
1.4
13,892
0.80
0.40
0.80
1.4
0.64
10.1
Tanker
10,842
SSD
14.9
0.34
0.50
0.05
3.1
2,288
0.27
0.50
0.45
3.1
0.67
37.9
A frequent caller was defined in this screening assessment as a ship making 6 calls per year at a given
port during a year for all vessel types other than passenger ships. Frequent calling passenger ships were
defined as those making five calls per year at each port. Percent of installed power relating to frequent
callers for each ship type was calculated at each port from 2011 Entrances and Clearances data.
Frequent caller percentages for the three ship types are shown in Table 5-53.
Table 5-53. Percent Frequent Callers by Ship Type
Ship Type
Frequent Caller Percentage
Container Ship
65%
Passenger Ship
97%
Tanker
13%
5.6.4. Most Effective Strategies - Container Ships
This screening assessment relied upon the following assumptions for a "typical" container port:
¦	718 total container ship calls in a given year
¦	65% of calls by frequent callers and 35% by infrequent callers
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Section 5: Assessment of Emission Reduction Strategies
Container ship strategies were reflected as follows:
¦	Fuel strategies were applied to 25% of the ships calling at the port.
¦	Shore power was applied to 80% of the frequent caller calls.
¦	AMECS were applied to 20% of the non-frequent callers.
¦	Reduced hoteling time was applied to 100% of calls.
Table 5-54 shows the impacts of strategies on a typical container ship and port for this screening
assessment.
Table 5-54. Typical Emission Impact per Year for Container Ships
Strategy
Reduction Per Call (lbs)
Reduction Per Port (tons)
NOx
PM2.5
CO2
CO2
WTW
NOx
PM2.5
CO2
CO2
WTW
500 ppm in Propulsion Engines
-
0.39
-
-
-
0.03
-
-
200 ppm in Propulsion Engines
-
0.62
-
-
-
0.06
-
-
ULSD in Auxiliary Engines
-
4.25
-
64
-
0.38
-
6
LNG in Propulsion Engines
196.41
4.18
2,279
2,295
17.63
0.38
205
206
LNG in Auxiliary Engines
1,002.97
18.91
32,150
34,624
90.02
1.70
2,885
3,108
Shore Power
958.42
18.68
77,008
32,294
178.92
3.49
14,376
6,029
AMECS
941.68
18.46
(7,742)
(9,039)
23.66
0.46
(195)
(227)
Reduced Hoteling
102.50
2.00
8,236
9,616
36.80
0.72
2,957
3,452
5.6.5. Most Effective Strategies - Passenger Ships
To estimate the reduction for a "typical" passenger port, the following assumptions were used:
¦	194 total passenger ship calls in a given year
¦	97% of calls by frequent callers and 3% by infrequent callers
Passenger ship strategies were reflected as follows:
¦	Fuel strategies were applied to 25% of the ships calling at the port.
¦	Shore power was applied to 80% of the frequent caller calls.
Table 5-55 shows the impacts of strategies on a typical passenger ship and port for this screening
assessment.
Table 5-55. Typical Emission Impact per Year for Passenger Ships
Strategy
Reduction Per Call (lbs)
Reduction Per Port (tons)
NOx
PM2.5
CO2
CO2
WTW
NOx
PM2.5
CO2
CO2
WTW
500 ppm in Propulsion Engines
-
0.20
-
-
-
0.00
-
-
200 ppm in Propulsion Engines
-
0.32
-
-
-
0.01
-
-
ULSD in Auxiliary Engines
-
7.49
-
113
-
0.18
-
3
Shore Power
1,635.29
26.62
109,707
46,007
123.09
2.00
8,258
3,463
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5.6.6. Most Effective Strategies - Tanker Ships
To estimate the reduction for a "typical" tanker port, the following assumptions were used:
¦	913 total tanker calls in a given year
¦	13% of calls by frequent callers and 87% by infrequent callers
Tanker ship strategies were reflected as follows:
¦	Fuel strategies were applied to 25% of the ships calling at the port.
¦	AMECS was applied to 20% of the non-frequent caller calls.
Table 5-56 shows the impacts of strategies on a typical tanker ship and port for this screening
assessment.
Table 5-56. Typical Emission Impact per Year for Tankers
Strategy
Reduction Per Call (lbs.)
Reduction Per Port (tons)
NOx
PM2.5
CO2
CO2
WTW
NOx
PM2.5
CO2
CO2
WTW
500 ppm in Propulsion Engines
-
0.18
-
-
-
0.02
-
-
200 ppm in Propulsion Engines
-
0.28
-
-
-
0.03
-
-
ULSD in Auxiliary Engines
-
4.20
-
63
-
0.48
-
7
LNG in Propulsion Engines
100.84
1.89
1,397
1,407
11.51
0.22
159
161
LNG in Auxiliary Engines
991.36
18.69
31,778
34,223
113.14
2.13
3,627
3,906
AMECS
1,025.59
20.10
(9,526)
(11,123)
81.46
1.60
(757)
(883)
5.6.7. Most Effective OGV Strategies
From the analysis presented above, some conclusions can be made about the most effective OGV
emission reduction strategies, and the circumstances under which a given strategy would be most
effective. It is more difficult to assess the costs of the OGV strategies than with the other source
categories, because the costs of shore-side improvements can vary widely and the costs of ship
improvements will be largely borne by the ocean carriers.
Switching to lower sulfur fuels beyond EPA's existing requirements can be an effective strategy to
further reduce PM2.5- ULSD was one of the most effective of these strategies where using ULSD in
auxiliary engines would achieve roughly 30 to 40 times the PM2.5 reduction per vessel call as compared
to switching to 200 or 500 ppm sulfur diesel fuel in propulsion engines. While passenger ships showed
the biggest reduction, other considerations may limit the practical application of ULSD in passenger
ships.170 Applying ULSD for container and tanker ships would be feasible, and based on the screening
assessment, show significant reductions of auxiliary engine emissions.
170 For example, many passenger ships use Category 3 engines in a diesel-electric configuration. While those engines are MSD
and more likely to handle ULSD than SSD engines, there may be some compatibility issues in using ULSD in those engines.
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Section 5: Assessment of Emission Reduction Strategies
Using LNG in propulsion and auxiliary engines produced a large reduction in NOx, PM2.5 and C02
emissions. This strategy produced roughly nine times the benefit of using it in the propulsion engines in
this screening assessment; this result also reflects the larger amount of hoteling emissions (from
auxiliary engines) that are included in the baseline for this assessment. NOx reductions in 2020 are
much larger than in 2030 due to the expected penetration of Tier III engines by 2030.
Shore power was highly effective at reducing NOx, PM2.5 and C02 emissions. Because it requires
upgrades to ships, however, shore power would be most feasible for frequent calling ships, and may be
cost-prohibitive for infrequent callers. Thus, the largest benefits from shore power would be expected
to occur at terminals and ports with a high fraction of frequent callers (i.e., usually cruise ship terminals
and container terminals). Tankers and other bulk ships are less likely to be frequent callers. Shore
power requires extensive work by a port to install the shore-side infrastructure, including trenching and
installation of cables, switchgear, and transformers. The costs to install shore power infrastructure can
vary widely. For example, the Port of Long Beach has invested approximately $200 million in shore
power infrastructure, while the Port of Los Angeles has invested approximately $70 million. Long Beach
has faced higher costs because of the need to bring new electrical service lines from Interstate 405 into
the Harbor District in order to supply the appropriate power. In contrast, the Port of Los Angeles already
had the main electrical trunk lines in place from which to "step-down" and condition power for use by
ships.171
Per call, the effectiveness of the AMECS at reducing emissions is comparable to shore power for both
NOx and PM2.5. However, the C02 emissions increase due to the barge auxiliary engines operating to
support the emission reduction equipment. This approach could be considered at ports and terminals
with large numbers of infrequent callers, since the AMECS can be applied without special equipment or
fuel storage capacity on a given vessel. This is considered an emerging technology, and its cost and
feasibility may change in the future.
Finally, reduced hoteling time for container ships produced larger reductions than using lower sulfur
distillate in propulsion engines. Such strategies would also be expected to increase productivity by
moving ships in and out of a port more efficiently.
5.7. Example Application of Port Strategies in Screening Assessment
The final step in the screening assessment was to estimate the impacts of the strategies for a "typical"
port, which allows comparison across sectors and comparison of technology-based strategies with
operational or port-wide strategies. To do this, the hypothetical port was assumed to handle 2 million
TEUs per year. Based on a review of existing port emission inventories, representative populations for
each equipment type were selected, as shown in Table 5-57. Please note that OGV strategies were
171 Port of Los Angeles and Port of Long Beach, San Pedro Bay Ports Clean Air Action Plan 2010 Update, October 2010.
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Section 5: Assessment of Emission Reduction Strategies
applied only to container and tanker vessels in this example, and not passenger cruise vessels. See
Section 5.6 above for further information on effective strategies for that vessel type.
Table 5-57. Equipment Count Assumptions for a Typical Port in Screening Assessment
Equipment Type
Count
Drayage Trucks
1,000
Line-Haul Locomotives
2
Switch Locomotives
3
Yard Tractors
200
RTG Cranes
25
Container Handlers
50
Tugs
20
Ferries
5
Containership Total Calls
718
Tanker Ship Total Calls
913
Note that some strategies in these tables are aggregations of individual retrofit, replacement, and/or
repower combinations. For example, "Retrofit Tier 1/2 Tug with DPF" includes retrofitting Tier 1 and Tier
2 tugs, each of which can have different emission reduction benefits. For the sake of simplicity, in these
cases, emission reductions are presented for the strategy permutation that affects the newest
equipment (i.e., Tier 2 in this example), which is conservative in that the emission reduction benefits will
be lower than if applied to the older equipment.
Table 5-58 and Table 5-59 present a summary of the most effective strategies from this example to help
illustrate the relative impacts these different strategies can have on reducing emissions at a "typical"
port. For drayage trucks, rail, CHE, and harbor craft, the tables show annual emission reductions per
vehicle or per equipment piece—consistent with the estimates presented earlier in this section. OGV
emission reductions are shown on a per vessel call basis, consistent with Section 5.6. The tables also
show the estimated cost per vehicle or per equipment piece.
The middle set of columns show the number of vehicle/equipment pieces (or OGV calls) that would be
affected by a given strategy, and the affected vehicle/equipment as a percent of total
vehicle/equipment. For example, of the 50 container handlers at the typical port, 15% will be Tier 3 in
2020, so the strategy was applied to eight container handlers in that year. Note that line-haul
locomotives usually travel long distances, and therefore, the equivalent annual operation of two
locomotives was assumed here although the actual number affected in practice would be larger. Note
also that, for this screening assessment, OGV per-call results are the same as are the grid-based C02
emission factors, but per-port results differ due to an increased penetration assumed in future years.
The final set of columns show the emission reduction assuming the strategy is applied to all affected
vehicle/equipment pieces or OGV calls at the typical port.
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Section 5: Assessment of Emission Reduction Strategies
Table 5-58. Example Application of Potential Strategies for 2020
Sector
Strategy
Per Vehicle/Equipment or
Per OGV Call Reduction
Affected
Vehicle/Equipment
or OGV Calls per
Per Port Reduction






Port





NOx
PM2.5
CO2
Cost
Count
% of
NOx
pm2.
CO2


(lbs)
(lbs)
(tons)


Total
(tons)
5
(tons)
Drayage
Replace pre-2007 with MY 2010+
398
20
0
$110,000
320
32%
63.7
3.2
0
Trucks
Operational Efficiency (Reduce Idle and Creep 10%)
N/A
N/A
N/A
N/A
N/A
N/A
22.0
2.0
8,940
Rail
Replace Tier 0+ Line-haul with Tier 2+/3
38,691
2,064
0
$3,000,000
1
33%
19.3
1.0
0

Install AESS on Tier 2 Switcher
880
14
28
$10,000
1
7%
0.4
0.0
28

Replace Pre-Tier 0/Tier 0+ Switcher with Tier 2+/3
7,566
275
0
$1,500,000
2
61%
7.6
0.3
0

Replace Pre-Tier 0/Tier 0+ Switcher with T4 GenSet
23,616
504
177
$1,500,000
2
61%
23.6
0.5
354
CHE
Replace Tier 4 Yard Truck with CNG/LNG
33
2
17
$30,000
195
97%
3.2
0.2
3,313

Replace Tier 4 Yard Truck with PHEV
64
4
19
$150,000
195
97%
6.2
0.4
3,667

Retrofit Tier 3 RTG Crane with DPF
0
144
0
$19,000
4
17%
0.0
0.3
0

Repower Tier 3 RTG Crane with Tier 4
3,045
152
0
$200,000
4
17%
6.1
0.3
0

Retrofit Tier 3 Container Handler with DPF
0
91
0
$19,000
8
15%
0.0
0.4
0

Repower Tier 3 Container Handler with Tier 4
1,925
96
0
$64,000
8
15%
7.7
0.4
0
Harbor
Retrofit Tier 1/2 Tug with DPF
0
1,103
0
$60,000
11
56%
0.0
6.1
0
Craft
Repower Tier 1 Tug with Tier 3
43,828
2,296
0
$500,000
5
24%
109.6
5.7
0

Retrofit Tier 1/2 Ferry with DPF
0
1,406
0
$60,000
1
28%
0.0
0.7
0

Repower Tier 0/1 Ferry with Tier 3
23,673
1,085
0
$200,000
3
57%
35.5
1.6
0
OGVs
500 ppm in Propulsion Engines
0
0
0
N/A
108
15%
0.0
0.0
0
(Container)
200 ppm in Propulsion Engines
0
1
0
N/A
108
15%
0.0
0.0
0
ULSD in Auxiliary Engines
0
4
0
N/A
108
15%
0.0
0.2
3

LNG in Propulsion Engines
196
4
1
N/A
108
15%
10.6
0.2
124

LNG in Auxiliary Engines
1,003
19
17
N/A
108
15%
54.0
1.0
1,865

Shore Power
958
19
16
varies
287
40%
137.6
2.7
4,637

AM ECS
942
18
-5
N/A
72
10%
33.8
0.7
-324

Reduced Hoteling
102
2
5
N/A
359
50%
18.4
0.4
1,726
OGVs
500 ppm in Propulsion Engines
0
0
0
N/A
137
15%
0.0
0.0
0
(Tanker)
200 ppm in Propulsion Engines
0
0
0
N/A
137
15%
0.0
0.0
0
ULSD in Auxiliary Engines
0
4
0
N/A
137
15%
0.0
0.3
4

LNG in Propulsion Engines
101
2
1
N/A
137
15%
6.9
0.1
96

LNG in Auxiliary Engines
991
19
17
N/A
137
15%
67.9
1.3
2,343

AM ECS
1,026
20
-6
varies
91
10%
46.8
0.9
-508
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Section 5: Assessment of Emission Reduction Strategies
Table 5-59. Example Application of Potential Strategies for 2030


Per Vehicle/Equipment or
Affected
Per Port Reduction
Sector
Strategy
Per OGV Call Reduction
Vehicle/Equipment









or OGV Calls per









Port





NOx
PM2.5
CO2
Cost
Count
% of
NOx
PM2.5
CO2


(lbs)
(lbs)
(tons)


Total
(tons)
(tons)
(tons)
Drayage
Replace MY 2010+ Diesel with BEV
44
2
12
$220,000
840
84%
18.6
0.7
10,145
Trucks
Operational Efficiency (Reduce Idle and Creep 10%)
N/A
N/A
N/A
N/A
N/A
N/A
15.4
1.4
8,940
Rail
Replace Tier 2+/3 Line-haul with Tier 4
67,924
1,118
0
$3,000,000
1
25%
34.0
0.6
0

Replace Tier 0+ Switcher with Tier 4 GenSet
23,616
504
177
$1,500,000
2
52%
23.6
0.5
354

Replace Tier 2+/3 Switcher w/ T4 or T4 GenSet (avg)
9,630
160
177
$1,500,000
1
9%
4.8
0.1
177
CHE
Replace Tier 4 Yard Truck with CNG/LNG
33
2
17
$30,000
200
100%
3.3
0.2
3,398

Replace Tier 4 Yard Truck with Battery Electric
164
8
34
$210,000
200
100%
16.4
0.8
6,773

Install Tier 4 RTG Crane with ESS
85
4
45
$240,000
24
98%
1.0
0.1
1,072

Convert Tier 4 RTG Crane to Electric
338
17
70
$500,000
24
98%
4.1
0.2
1,679
Harbor
Replace Tier 3 Tug with Tier 4
35,042
399
0
$10 million
3
14%
52.6
0.6
0
Craft
Repower Tier 1/2 Ferry with Tier 4
36,337
1,499
0
$300,000
2
35%
36.3
1.5
0

Repower Tier 3 Ferry with Tier 4
24,139
414
0
$300,000
2
35%
24.1
0.4
0
OGVs
500 ppm in Propulsion Engines
0
0
0
N/A
180
25%
0.0
0.0
0
(Container)
200 ppm in Propulsion Engines
0
1
0
N/A
180
25%
0.0
0.1
0
ULSD in Auxiliary Engines
0
4
0
N/A
180
25%
0.0
0.4
6

LNG in Propulsion Engines
196
4
1
N/A
180
25%
17.6
0.4
206

LNG in Auxiliary Engines
1,003
19
17
N/A
180
25%
90.0
1.7
3,108

Shore Power
958
19
16
varies
574
80%
275.3
5.4
9,275

AMECS
942
18
-5
N/A
144
20%
67.6
1.3
-649

Reduced Hoteling
102
2
5
N/A
718
100%
36.8
0.7
3,452
OGVs
500 ppm in Propulsion Engines
0
0
0
N/A
228
25%
0.0
0.0
0
(Tanker)
200 ppm in Propulsion Engines
0
0
0
N/A
228
25%
0.0
0.0
0
ULSD in Auxiliary Engines
0
4
0
N/A
228
25%
0.0
0.5
7

LNG in Propulsion Engines
101
2
1
N/A
228
25%
11.5
0.2
161

LNG in Auxiliary Engines
991
19
17
N/A
228
25%
113.1
2.1
3,906

AMECS
1,026
20
-6
varies
183
20%
93.6
1.8
-1,015
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Section 6: Analysis of Emission Reduction Scenarios
6. Analysis of Emission Reduction Scenarios
This section describes the scenario analyses that were conducted for various combinations of emission
reduction strategies (i.e., "strategy scenarios"). This section provides an overview of EPA's intent in
developing the scenarios as well as the specific strategies and analysis results for each mobile source
sector. Further details on the methodology and assumptions for this section are included in Appendix C.
6.1. Overview
The strategy scenarios were composed of various technological and operational strategies that
could be applied to the Business as Usual (BAU) inventories for the five mobile source sectors. As
described in Section 5, EPA conducted a screening-level assessment of the range of potential
technological and operational strategies to reduce port-related emissions, and considered the
potential to accelerate the introduction of newer technologies that reflect EPA's most recent
emission standards. EPA also developed the strategy scenarios in consultation with the Mobile
Sources Technical Review Subcommittee (MSTRS) of the Clean Air Act Advisory Committee (CAAAC).
In 2014, the MSTRS formed a Ports Workgroup to develop recommendations for an EPA-led
voluntary ports initiative, and effectively measuring environmental performance at ports. The
MSTRS Ports Workgroup included technical and policy experts from a range of stakeholders,
including industry, port-related agencies, communities, Tribes, state and local governments, and
public interest groups.172 After extensive discussions and other research, a final list of strategy
scenarios was determined for more detailed analysis.
Strategy scenarios were developed for each mobile source sector for the years 2020 and 2030 for all
pollutants173 and for only C02 in 2050. Although the specific strategies differ between sectors, the
scenarios were intended to address the following:
¦	Scenario A reflected an increase in the introduction of newer technologies in port vehicles and
equipment beyond what would occur through normal fleet turnover. Operational strategies in
Scenario A reflected a reasonable increase in expected efficiency improvements for drayage
truck, rail, and OGV sectors. For the OGV sector, moderate levels of fuel switching and other
emission control strategies were also analyzed.
¦	Scenario B reflected a more aggressive suite of strategies as compared to Scenario A. Scenario
B was intended to further accelerate the introduction of clean diesel and zero emissions
vehicles and equipment, in addition to other fuels and technologies. Operational strategies in
Scenario B assume further operational efficiency improvements beyond Scenario A.
172	For further information on MSTRS Ports Working Group participants, see https://www.epa.gov/sites/production/files/2016-
06/documents/portsinitiativewkgrp 2016.pdf.
173	See Section 2 for more background on the pollutants that were analyzed for the different mobile source sectors.
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Section 6: Analysis of Emission Reduction Scenarios
Both scenarios would necessitate a major investment in new technologies, with Scenario B requiring
a larger investment than Scenario A. In selecting strategies, EPA qualitatively considered several
factors, such as capital costs, market barriers, and potential for market penetration by analysis year.
However, an in-depth cost-benefit analysis was not conducted.
In many cases, a sector was broken down into groups of scenarios applied to a specific subtype or
operational mode of the sector. In these cases, the impact of selected strategies was applied to the
applicable portion of the BAU inventory. For example, there are rail sector scenarios for line-haul
technologies, line-haul operational scenarios, and switcher technologies, with the applicable
strategies being applied to the relevant portion of the BAU inventory (e.g., switcher strategies were
applied to the switcher emissions in the BAU inventory for each analysis year). Emission reductions
for all pollutants in the BAU emission inventory were considered here. However, analysis results
are provided for NOx, PM2.5, and C02 reductions in this section, with the remaining pollutant results
included in Appendix C.
Finally, strategy scenarios were estimated by developing typical or average emission relative
reduction factors (RRFs) for each sector/mode under each scenario. In general, once an RRF was
determined, it was applied uniformly to the applicable BAU emission inventory at each port in this
national scale analysis, except for cases where a sector was not in service at a port or where an
existing local program produced the same or better results than the proposed scenario.
Assessment results are reported for each scenario as both percent and total reductions from the
relevant BAU inventory for a given sector. Unless otherwise noted, all scenario reductions were
determined relative to the same BAU emission inventories that are described in Section 4 of this
report, independently, in order to allow comparison across scenarios in a consistent manner.
Accordingly, the reductions presented here would be reasonable for each individual strategy, but in
some cases, may overestimate the cumulative impact if multiple strategies were applied
simultaneously (without accounting for overlap between scenarios).174
174 For example, the reduction from applying both fuel switching and shore power for OGV hoteling emissions should be less
than the sum of the OGV strategies. If in practice, fuel switching was applied first, there would be less available emissions to
which shore power could be applied.
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Section 6: Analysis of Emission Reduction Scenarios
6.2. Drayage Trucks
Strategy scenarios for drayage trucks fall into two categories: Technological and Operational. Table 6-1
shows the strategy scenarios analyzed for Scenarios A and B for the different analysis years. For
example, column "2020/A" for the Technological category includes the drayage truck technological
strategies assumed for Scenario A in the 2020 analysis year.
Table 6-1. Drayage Truck Strategy Scenarios
Strategy
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B

Replace all
Replace all
Replace 100%
Replace 100%
Replace 25%
Replace 50%

pre-1994
pre-1998
of pre-2004
of pre-2007
of post-2010
of post-2010

trucks with
trucks with
trucks with
trucks with
trucks with
trucks with
Technological
50% post-
50% 2007,
2010 trucks.
50% 2010 and
PHEV
PHEV
1998, 30%
40% 2010,
Replace 20%
50% PHEV.



2007, 20%
and 10%
of 2004-09
Replace 10%



2010 or
PHEV
trucks with
of post-2010



newer trucks

PHEV
with PHEV



Reduce gate
Reduce gate
Reduce gate
Reduce gate
Reduce gate
Reduce gate
Operational
queues by
queues by
queues by
queues by
queues by
queues by

25%
50%
25%
50%
25%
50%
The Technological category includes truck replacement strategies from accelerating turnover to cleaner
diesel trucks that meet EPA's more recent emission standards. Plug-in hybrid electric vehicles (PHEV)
were also assumed in this category for most scenarios, and PHEVs were assumed to also be a surrogate
for the potential reductions from other types of electric trucks (such as hybrid electric vehicles (HEVs)
and battery electric vehicles (BEVs).175 Reduced gate queues were assumed to occur at different levels
in the Operational category.
For the drayage truck sector, technological and operational strategies were applied separately, but to
the same BAU inventory, which caused some overlap between the two sets of scenarios for all
pollutants.176 See Section 5 and Appendix C for further background on drayage truck strategies and the
methodology used in the scenario analyses.
6.2.1. Technological Strategies
The Technological strategy scenarios for drayage trucks are found in the first row of Table 6-1.
175	PHEVs were determined to be the most likely technology for commercial availability, based on the screening assessment in
Section 5.
176	As described in Section 4, the BAU emission inventories for drayage trucks were based on projected port cargo tonnage
multiplied by composite drayage truck fleet emission factors (in terms of emissions per ton) that were developed using EPA's
DrayFLEET model. The BAU inventory also included adjustments for select ports where existing local programs had modified
the age distribution of drayage trucks.
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Section 6: Analysis of Emission Reduction Scenarios
6.2.1.1. Relative Reduction Factors
A relative reduction factor (RRF) was calculated for each scenario strategy, and then applied to the
relevant BAU inventory for each analysis year. For each strategy scenario, a fleet-average RRF was
calculated as follows:
RRF = 1-Scenario EF/BAUEF	Eq. 6-1
Where
Scenario EF = the emission factor for a given scenario, and
BAU EF = the emission factor for the given Business as Usual inventory.
Equation 6-1 shows how a fleet-average RRF was calculated as the scenario emissions divided by the
BAU emissions. To simplify calculations, the DrayFLEET model was used to develop a generic, average
fleet RRF to represent an average port (or "typical port"), rather than generating a separate model for
each port that is part of this national scale assessment. This is different from how the BAU inventories
for drayage trucks were developed, where a default truck fleet age distribution from MOVES2010b was
used in the DrayFLEET model. For each strategy scenario analysis, the BAU age distribution was
replaced with alternative distributions for respective replacements in each scenario.
Criteria pollutant emission factors for conventional diesel drayage trucks were drawn from EPA emission
standards, and emission factors for air toxics were derived from existing EPA methods and models. C02
emission factors came from GREET 2015,177 and for these calculations, no change in fuel economy or C02
emission rates were assumed between model year standards.178
Because the DrayFLEET model cannot readily model each of the scenarios, the fleet-average emission
factors were weighted by truck population distributions specific to each scenario. To develop the truck
population distributions for each scenario, the default truck fleet age distribution from the BAU
methodology was used, which was drawn from MOVES2010b. No PHEV trucks were assumed in the
BAU fleet mixes.
Table 6-2 shows the resulting Technological strategy scenario RRFs for the drayage truck sector,
applicable to a typical port.179
177	GREET2015 was released Oct 2, 2015. All calculations in this draft have been updated to GREET2015 results. For information
on the model, see https://ereet.es.anl.eov/.
178	Note that BAU inventories are based on the DrayFLEET model, which was based on MOVES2010b. As a result and as noted
in Section 4, the drayage results in this assessment do not include EPA's heavy-duty engine and vehicle GHG regulations.
179	A "typical port" in this assessment is intended to establish a hypothetical port that that allows EPA to illustrate the relative
impacts of a particular strategy and/or scenario.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-2. Relative Reduction Factors for Drayage Truck Technological Strategy Scenarios
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
19%
43%
14%
43%
0%
10%
11%
7%
2020/B
48%
62%
35%
62%
1%
21%
26%
12%
2030/A
48%
34%
33%
34%
0%
20%
24%
14%
2030/B
60%
52%
39%
52%
4%
22%
27%
15%
2050/A
-
-
-
-
6%
-
-
-
2050/B
-
-
-
-
12%
-
-
-
Note that use of emission factors to determine RRFs in this manner implies that other technological and
operational parameters, such as engine load and power, were unchanged between a BAU inventory and
scenario analysis.
6.2.1.2.	Application of Relative Reduction Factors
As described above, the RRFs found in Table 6-2 were based on drayage truck fleet averages at a typical
port. Next, the RRFs that were estimated for each scenario and pollutant were then applied to each
port's BAU drayage truck emission inventory for each analysis year. Adjustments were made in 2020 to
the BAU drayage age distribution at a limited number of ports to account for local programs in effect
that would out-pace the scenarios considered in this assessment. For those cases, no additional
emission reductions were applied. No similar changes were made in 2030 and 2050 at any ports, so the
full RRF was applied for all scenarios in those analysis years.
6.2.1.3.	Result Summary
Table 6-3 shows the total tons reduced from the BAU inventory for the Technological strategy scenarios
for the drayage sector.
Table 6-3. Total Drayage Truck Emission Reductions for Technological Strategy Scenarios
Scenario
Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
997.7
166.6
59.6
128.3
-
2.3
0.5
4.6
2020/B
2,503.4
240.7
151.9
185.3
10,827
5.0
1.2
7.8
2030/A
1,250.7
52.1
68.1
40.2
11,987
2.7
0.6
6.0
2030/B
1,573.1
81.0
79.7
62.4
88,511
3.0
0.7
6.4
2050/A
-
-
-
-
276,072
-
-
-
2050/B
-
-
-
-
552,144
-
-
-
6.2.2. Operational Strategies
Next, the Operational strategy scenarios in the second row of Table 6-1 were analyzed.
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Section 6: Analysis of Emission Reduction Scenarios
6.2.2.1. Development and Application of Relative Reduction Factors
The DrayFLEET model was used to estimate the emission impacts of generalized drayage truck efficiency
improvements. These improvements would reduce the time drayage trucks spend in idle and creep
mode by 25% and 50%, respectively, for Scenarios A and B. These outcomes could be achieved by ports
in a variety of ways, as discussed in Section 5 of this report.
Gate queue reduction factors were determined with the DrayFLEET model, and similar to the
Technological scenarios, a different RRF was developed for each scenario and pollutant based on activity
at a "typical port." Table 6-4 shows the resulting operational strategy RRFs.
Table 6-4. Relative Reduction Factors for Drayage Fleet Operational Strategy Scenarios
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
0%
1%
0%
1%
1%
0%
0%
0%
2020/B
1%
2%
1%
2%
2%
1%
0%
1%
2030/A
0%
1%
0%
1%
1%
1%
0%
0%
2030/B
1%
2%
1%
2%
2%
1%
0%
1%
2050/A
-
-
-
-
1%
-
-
-
2050/B
-
-
-
-
2%
-
-
-
Note that in developing the BAU inventories, the number of drayage trucks increased with each future
year to accommodate growth in port throughput. However, in the modeled scenarios the percent of
truck operating time spent in gate queues did not vary by calendar year.
The RRFs for each drayage Operational strategy scenario were applied to each port's BAU emissions,
similar to how RRFs were applied for the Technological strategy scenarios.
6.2.2.2. Result Summary
Table 6-5 shows the total emission reductions for the drayage Operational strategy scenarios.
Table 6-5. Total Drayage Truck Operational Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
10.5
3.9
1.7
3.0
18,662
0.1
0.0
0.3
2020/B
26.2
7.7
3.0
5.9
37,323
0.2
0.0
0.5
2030/A
5.3
1.6
0.8
1.2
25,092
0.1
0.0
0.2
2030/B
13.1
3.1
1.4
2.4
50,184
0.1
0.0
0.3
2050/A
-
-
-
-
44,172
-
-
-
2050/B
-
-
-
-
88,343
-
-
-
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Section 6: Analysis of Emission Reduction Scenarios
6.2.3. Summary of Drayage Truck Scenarios
Tables 6-6 and 6-7 illustrate the reductions from the Technological and Operational strategy scenarios.
In Table 6-6, the relative emission reduction from the drayage BAU inventories are shown as percent
reductions for all pollutants. Figure 6-1 graphs the percentage reductions for NOx, PM2.5, and C02.
Table 6-7 shows absolute emission reductions from the BAU inventories by scenario and strategy in tons
reduced per analysis year, and Figure 6-2 graphs the tons/year reductions for NOx, PM2.5, and C02.
Similar charts for other pollutants can be found in Appendix C.
Scenarios that supported accelerated fleet turnover had a significant effect on reducing drayage truck
emissions for most pollutants and years, and the introduction of electric technologies further decreased
C02 emissions in the longer term. Technological drayage scenarios produced significant NOx and PM2.5
reductions. For example, total relative NOx reductions from drayage technological strategies produced
significant reductions between Scenarios A and B; in 2020, reductions ranged from 19-48% and from 48-
60% in 2030 from the total drayage BAU inventories for those years. Similar reductions were observed
for PM2.5, where 2020 PM2.5 reductions were estimated between 43-62% and 2030 reductions were 34-
52% for the drayage Technological scenarios from the total BAU case. In addition, an estimated 6-12%
C02 reductions were observed in 2050 for the Technological scenarios for that year.180
Not surprisingly, Scenario B consistently showed greater reductions than Scenario A for all Technological
scenarios. The Operational scenarios, on the other hand, provided much smaller reductions of criteria
pollutant and air toxic emissions as compared to the Technological scenarios. However, EPA believes this
is most likely due to how the Operational scenarios were designed in this assessment; operational
strategies that significantly reduce truck idling continue to be important options to consider for reducing
drayage emissions. In contrast, Operational scenarios were more effective in reducing C02 emissions in
the 2020/A, 2020/B, and 2030/A scenarios as compared to truck replacement strategies; with the major
shift to PHEVs in the 2030/B scenario producing greater results than reduced gate queues.
Please note that drayage reductions for all strategy scenarios were limited to the assessment's modeled
domain of 0.5 km from the port boundary, as described in Section 3. In practice, additional emissions
and potential reductions would occur beyond the immediate port area, since drayage trucks typically
travel through off-port corridors to freight distribution centers or commercial businesses in the larger
region. The tables and figures also do not show total emission reductions for the drayage sector. For
the drayage sector, all reductions were calculated relative to the total BAU inventory. That is,
operational and technological strategies were both computed separately, both relative to the same BAU
inventory and could apply to the same vehicles. Thus, there may be significant overlap between the two
sets of scenarios for all pollutants.
180 Please note that EPA's heavy-duty engine and vehicle GHG regulations were not reflected due to the timeframe of the
assessment and its reliance on a now older version of the MOVES model.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-6. Drayage Truck Relative Emission Reduction Summary by Scenario and Strategy, Percent
Scenario
Strategy
Type
% reduction from BAU
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Scenario
2020/A
Technological
19%
43%
14%
43%
0%
10%
11%
7%
Replace all pre-1994 trucks with 50% 2004, 30%
2007, 20% 2010 or newer trucks
Operational
0%
1%
0%
1%
1%
0%
0%
0%
Reduce Gate Queues by 25%
2020/B
Technological
48%
62%
35%
62%
1%
21%
26%
12%
Replace all pre-1998 trucks with 50% 2007, 40%
2010, and 10% PHEV
Operational
1%
2%
1%
2%
2%
1%
0%
1%
Reduce Gate Queues by 50%
2030/A
Technological
48%
34%
33%
34%
0%
20%
24%
14%
Replace 100% of pre-2004 trucks with 2010
trucks. Replace 20% of 2004-09 trucks with
PHEV
Operational
0%
1%
0%
1%
1%
1%
0%
0%
Reduce Gate Queues by 25%
2030/B
Technological
60%
52%
39%
52%
4%
22%
27%
15%
Replace 100% of pre-2007 trucks with 50% 2010
and 50% PHEV. Replace 10% of post-2010 with
PHEV
Operational
1%
2%
1%
2%
2%
1%
0%
1%
Reduce Gate Queues by 50%
2050/A
Technological
-
-
-
-
6%
-
-
-
Replace 25% of post 2010 trucks with PHEV
Operational
-
-
-
-
1%
-
-
-
Reduce Gate Queues by 25%
2050/B
Technological
-
-
-
-
12%
-
-
-
Replace 50% of post 2010 trucks with PHEV
Operational
-
-
-
-
2%
-
-
-
Reduce Gate Queues by 50%
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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-1. Drayage Truck Percent Emission Reductions by Scenario and Strategy for Selected Pollutants
2020/A	2020/B
2030/A
2030/B
2020/A
2020/B
2030/A
2030/B
CO,

14%
D
12%
<

CO
£
10%
O

1_
M—
8%
c

o
4->
6%
u

3

T3
-------
Section 6: Analysis of Emission Reduction Scenarios
Table 6-7. Drayage Truck Emission Reduction Summary by Scenario and Strategy, Tons per Year
Scenario
Strategy Type
Tons Reduced per Year
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Scenario
2020/A
Technological
997.7
166.6
59.6
128.3
0
2.2
0.5
4.4
Replace all pre-1994 trucks with 50% 2004, 30%
2007, 20% 2010 or newer trucks
Operational
10.5
3.9
1.7
3.0
18,661
0.1
0.02
0.3
Reduce Gate Queues by 25%
2020/B
Technological
2,503.4
240.7
151.9
185.3
10,827
4.8
1.1
7.5
Replace all pre-1998 trucks with 50% 2007, 40%
2010, and 10% PHEV
Operational
26.2
7.7
3.0
5.9
37,323
0.2
0.03
0.4
Reduce Gate Queues by 50%
2030/A
Technological
1,250.7
52.1
68.1
40.3
11,987
2.7
0.6
5.9
Replace 100% of pre-2004 trucks with 2010
trucks. Replace 20% of 2004-09 trucks with PHEV
Operational
5.3
1.6
0.8
1.2
25,092
0.1
0.01
0.2
Reduce Gate Queues by 25%
2030/B
Technological
1,573.1
81.0
79.7
62.6
88,511
3.0
0.7
6.3
Replace 100% of pre-2007 trucks with 50% 2010
and 50% PHEV. Replace 10% of post-2010 with
PHEV
Operational
13.1
3.1
1.4
2.4
50,183
0.1
0.02
0.3
Reduce Gate Queues by 50%
2050/A
Technological
-
-
-
-
276,072
-
-
-
Replace 25% of post 2010 trucks with PHEV
Operational
-
-
-
-
44,172
-
-
-
Reduce Gate Queues by 25%
2050/B
Technological
-
-
-
-
552,144
-
-
-
Replace 50% of post 2010 trucks with PHEV
Operational
-
-
-
-
88,343
-
-
-
Reduce Gate Queues by 50%
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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-2. Drayage Truck Absolute Emission Reductions by Scenario and Strategy for Selected Pollutants
NOx PM25
3,000 		250
2/500	H	200
>-	2,000
ra	ro
oi	ai
>- „ „„ ¦ 	 >-
1,500
1,000
500
0
to
¦ Technological
>-
600,000
500,000
400,000
300,000
200,000
100,000
0
150
O 100
I I I I I L . I
2020/A	2020/B	2030/A	2030/B	2020/A	2020/B	2030/A	2030/B
CO,
I
I Operational
2020/A	2020/B	2030/A	2030/B	2050/A	2050/B
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Section 6: Analysis of Emission Reduction Scenarios
6.3. Rail
Rail strategy scenarios fall into three categories: Line-haul Technology, Line-haul Operational, and
Switcher Technology. Table 6-8 shows the strategy scenarios analyzed for Scenarios A and B for the
different analysis years.
Table 6-8. Rail Strategy Scenarios
Strategy
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Line-haul—
Technology
Replace 50%
of Tier 0+
engines with
Tier 2+
engines
Replace 100%
of Tier 0+
engines with
50% 2+
engines and
50% Tier 4
engines
Replace 100%
of Tier 1+ and
earlier engines
with 50% 2+
engines and
50% Tier 4
engines
Replace all pre-
Tier 4 engines
with Tier 4
engines.
Replace 10%
of Tier 4 with
zero
emissions
locomotive
Replace 25%
of Tier 4 with
zero emissions
locomotive
Line-haul—
Operational
1%
improvement
in fuel
efficiency
5%
improvement
in fuel
efficiency
5%
improvement
in fuel
efficiency
10%
improvement
in fuel
efficiency
10%
improvement
in fuel
efficiency
20%
improvement
in fuel
efficiency
Switcher
Technology
Replace 50%
of Pre-TierO
engines with
95% Tier 2+
engines and
5% Tier 4
Genset
Replace all
Pre-Tier 0
engines with
90% Tier 2+
and 10% Tier
4 Genset
Replace all Pre-
Tier 0 engines
and 20% of Tier
0+ with 90%
Tier 2+ engines
and 10% Tier 4
Genset
Replace all Pre-
Tier 0 engines
and 40% of
Tier 0+ with
70% Tier 4
engines and
30% Tier 4
Genset
Assume 30%
Tier 4 Genset
Assume 50%
Tier 4 Genset
The Line-haul Technology category includes locomotive replacement strategies to accelerate fleet
turnover to newer diesel engines that meet cleaner diesel engine standards, with electric technology
being included in the 2050 analysis year. Increasing levels of improved fuel efficiency was analyzed for
the Line-haul Operational category. Finally, accelerating turnover to cleaner switcher standards, as well
as increased use of Genset technologies are considered in the Switcher Technology scenarios.
For the rail sector, emission reductions were applied to the individual parts of the BAU inventory for the
individual strategies and to the sector total for the cumulative results. That is, for both the Line-haul
Technology and Line-haul Operational categories, relative reductions were applied to the rail line
component of the BAU inventory and the rail switcher emission reductions were applied to the rail yard
component of the BAU inventory. The total rail reductions are estimated as the sum of Line-haul
Technology, Line-haul Operational, and Switcher Technology strategy emission reductions relative to the
total rail BAU inventory. See Section 5 and Appendix C for further background on rail strategies and the
methodology used in the scenario analysis.
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Section 6: Analysis of Emission Reduction Scenarios
6.3.1. Line-haul Technology Strategies
Line-haul technology strategies are shown in the first row of Table 6-8 above. For each strategy scenario
and pollutant, a relative reduction factor (RRF) was calculated using an average emission factor (EF) for
both the scenario and the BAU emission inventory. Each emission factor was determined as the
emission rate for each tier weighted by the locomotive engine population distribution in that tier. This
approach was applied to both the rail line portion of the BAU emissions inventory and the relevant
strategy scenario. The RRF was calculated from these as:
RRF = 1 - Scenario EF/BAU EF	Eq. 6-2
RRFs for the Line-haul Technology strategy scenarios are shown in Table 6-9. Note that it is assumed
that the new engines described in Table 6-8 will have similar duty cycles, rated power, and annual usage
as the engines they replace, such that emission changes are due solely to changes in the engine emission
rates (e.g., in g/kWh).
Table 6-9. Relative Reduction Factors for Line-haul Technology Strategies
Scenario
Overall Emission Reduction Factors (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
7%
16%
15%
16%
0%
17%
26%
15%
2020/B
28%
41%
37%
41%
0%
34%
26%
38%
2030/A
6%
13%
10%
13%
0%
7%
0%
11%
2030/B
66%
76%
62%
76%
0%
65%
69%
62%
2050/A
-
-
-
-
5%
-
-
-
2050/B
-
-
-
-
13%
-
-
-
Note that accelerating fleet turnover for line-haul locomotives to more stringent EPA standards provides
PM2.5 and NOx reductions. However, as described in Section 5, no C02 reductions would be expected
from moving to newer line-haul technologies for the years 2020 and 2030. Also, note that Scenario
2030/A has lower RRFs than Scenario 2020/A for all pollutants (other than C02 which remains 0
percent). This is due to the significantly reduced BAU emission factors in 2030, due primarily to
significant reduction in the Tier 0 and Tier "0+" engines and the increased share of Tier 4 engines
between 2020 and 2030. As a result, the scenarios significantly lower the BAU baseline from which
scenario reductions are taken. See Appendix C for more information on the methodology and
assumptions for calculating RRFs for the Line-haul Technology category.
6.3.1.1. Result Summary
Table 6-10 presents the total emission reductions of the Line-haul Technology strategy scenarios.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-10. Total Line-haul Technology Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
90.4
4.8
6.9
3.7
0
0.3
0.1
0.6
2020/B
339.6
12.3
17.4
9.5
0
0.6
0.1
1.5
2030/A
56.1
2.2
3.3
1.7
0
0.1
0.0
0.4
2030/B
573.8
13.0
20.0
10.0
0
0.9
0.2
2.2
2050/A
-
-
-
-
10,218
-
-
-
2050/B
-
-
-
-
25,546
-
-
-
6.3.2. Line-haul Operational Strategies
The Line-haul Operational strategy scenarios are shown in the second row of Table 6-8, and these
scenarios involve only fuel efficiency improvements. Therefore, it was assumed that these scenarios
affect only C02 emissions and no other pollutants. Accordingly, the RRFs are based on the increase in
fuel efficiency and were applied to the line-haul portion of the C02 BAU inventory for each analysis year.
6.3.2.1. Result Summary
Table 6-11 shows the total emission reductions of the Line-haul Operational strategy scenarios.
Table 6-11. Total Line-haul Operational Emission Reductions
CO2 Tons per Year
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
1,043
5,216
6,835
13,669
23,224
46,447
6.3.3. Switcher Technology Strategies
Switcher Technology strategy scenarios are shown in the last row of Table 6-8. While GenSet
locomotives can be built to Tier 3 or Tier 4 standards, it was assumed that the Tier 4 standards are more
appropriate for all GenSet locomotives in these scenarios. The RRFs were calculated as described by
Equation 6-2 above, and the underlying methodology and assumptions were similar to the Line-haul
Technology scenarios. See Appendix C for further details. Table 6-12 shows the resulting RRFs for the
Switcher strategy scenarios.
Table 6-12. Relative Reduction Factors for Switcher Technology Strategies
Scenario
Overall Emission Reduction Factors (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
16%
22%
21%
22%
0%
19%
15%
20%
2020/B
34%
44%
41%
44%
1%
39%
10%
40%
2030/A
17%
24%
22%
25%
0%
21%
4%
19%
2030/B
43%
47%
40%
47%
2%
32%
7%
26%
2050/A
-
-
-
-
6%
-
-
-
2050/B
-
-
-
-
10%
-
-
-
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Section 6: Analysis of Emission Reduction Scenarios
6.3.3.1. Result Summary
Table 6-13 presents the total emission reductions of the Switcher Technology strategy scenarios.
Table 6-13. Total Switcher Technology Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
208.6
7.6
17.1
5.9
150
0.6
0.1
1.4
2020/B
431.2
15.4
34.4
11.9
600
1.2
0.3
2.8
2030/A
181.9
7.0
14.8
5.4
396
0.6
0.1
1.4
2030/B
471.7
13.4
26.5
10.3
1,843
0.9
0.2
1.9
2050/A
-
-
-
-
11,399
-
-
-
2050/B
-
-
-
-
18,999
-
-
-
6.3.4. Summary of Rail Scenarios
Table 6-14 summarizes the relative emission reduction results for all pollutants by scenario and strategy
for the rail sector. Figure 6-3 shows the relative reductions for NOx, PM2.5, and C02. Note that line-haul
and switcher reductions were calculated separately relative to the respective rail line and rail yard BAU
inventories. Table 6-15 lists total emission reductions for the rail sector for each pollutant, and Figure
6-4 graphs the reductions for NOx, PM2.5, and C02. Similar charts for other pollutants can be found in
Appendix C. Summing the reductions in this manner is appropriate for the criteria and air toxics
pollutants, since there is no overlap between Line-haul Technology, Line-haul Operational, and Switcher
Technology strategy scenarios (as the operational strategies only reduce C02). Similarly, there is no
overlap between line-haul and switcher strategies for any pollutant because the reductions are
determined from separate portions of the BAU inventories. Total C02 emission reductions are also
shown for the combined impacts of all strategy scenarios, but this overlap only occurs in 2050 scenarios
with minimal impact.
As expected, Scenario B consistently showed greater reductions than Scenario A for all pollutants and
years. Rail strategy scenarios that included replacing older locomotive engines showed significant
reductions for criteria and air toxics emissions in 2020 and 2030. Total relative NOx reductions from
Line-haul and Switcher Technology scenarios reduced 2020 BAU emissions from 12-31% and 2030 BAU
emissions from 12-54%. Similar reductions were observed for PM2.5, where 2020 PM2.5 reductions were
estimated between 19-43% and 2030 reductions were 20-58% from the BAU inventories. Line-haul
Operational scenarios showed the greatest potential for C02 reductions for all years, especially in 2030
and 2050. The potential for further line-haul locomotive reductions for this assessment was not fully
realized due to the limited geographic scope of the rail analysis, where the modeled domain was 0.5 km
from the facility edge for the baseline and BAU inventories. Additional line-haul reductions could be
gained outside a port area for line-haul strategies beyond that quantified here.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-14. Rail Emission Relative Reduction Summary by Scenario and Strategy, Percent
Scenario
Rail Type
Percent Reduction from BAU
NOx
PM2.5
VOC
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy Summary
2020/A
Line-haul Technology
7%
16%
15%
16%
0%
17%
26%
15%
Replace 50% of Tier 0+ engines with
Tier 2+ engines
Switcher
16%
22%
21%
22%
0%
19%
15%
20%
Replace 50% of Pre-Tier 0 engines with
95% Tier 2+ engines and 5% Tier 4
GenSet
Line-haul Operational
-
-
-
-
1%
-
-
-
1% improvement in fuel efficiency
Total
12%
19%
18%
19%
1%
19%
19%
18%

2020/B
Line-haul Technology
28%
41%
37%
41%
0%
34%
26%
38%
Replace 100% of Tier 0+ engines with
50% 2+ engines and 50% Tier 4
engines
Switcher
34%
44%
41%
44%
1%
39%
10%
40%
Replace all Pre-Tier 0 engines with
90% Tier 2+ and 10% Tier 4 Genset
Line-haul Operational
-
-
-
-
5%
-
-
-
5% improvement in fuel efficiency
Total
31%
43%
40%
43%
3%
37%
12%
39%

2030/A
Line-haul Technology
6%
13%
10%
13%
0%
7%
0%
11%
Replace 100% of Tier 1+ and earlier
engines with 50% 2+ engines and 50%
Tier 4 engines
Switcher
17%
24%
22%
25%
0%
21%
4%
19%
Replace all Pre-Tier 0 engines and 20%
of Tier 0+ with 90% Tier 2+ engines
and 10% Tier 4 Genset
Line-haul Operational
-
-
-
-
5%
-
-
-
5% improvement in fuel efficiency
Total
12%
20%
18%
20%
3%
17%
3%
17%

2030/B
Line-haul Technology
66%
76%
62%
76%
0%
65%
69%
62%
Replace all pre-Tier 4 engines with Tier
4 engines.
Switcher
43%
47%
40%
47%
2%
32%
7%
26%
Replace all Pre-Tier 0 engines and 40%
of Tier 0+ with 70% Tier 4 engines and
30% Tier 4 Genset
Line-haul Operational
-
-
-
-
10%
-
-
-
10% improvement in fuel efficiency
Total
54%
58%
47%
58%
6%
43%
13%
38%

National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Rail Type
Percent Reduction from BAU
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy Summary
2050/A
Line-haul Technology
-
-
-
-
5%
-
-
-
Replace 10% of Tier 4 with zero
emissions locomotive
Switcher
-
-
-
-
6%
-
-
-
Assume 30% Tier 4 Genset
Line-haul Operational
-
-
-
-
10%
-
-
-
10% improvement in fuel efficiency
Total
-
-
-
-
11%
-
-
-

2050/B
Line-haul Technology
-
-
-
-
13%
-
-
-
Replace 25% of Tier 4 with zero
emissions locomotive
Switcher
-
-
-
-
10%
-
-
-
Assume 50% Tier 4 Genset
Line-haul Operational
-
-
-
-
20%
-
-
-
20% improvement in fuel efficiency
Total
-
-
-
-
23%
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-3. Rail Emission Percent Reductions by Scenario and Strategy for Selected Pollutants181
NOx	PM25
70% 		80%
D 60%	I	D 70%
<	¦	<
% 50%	I	% 60%
O	I	p 50%
£ 40%	¦¦	£
§ -	¦¦	§ 40%
£ 30% ¦	¦¦	£
¦ I	¦¦	3 30%
15 20% 	 II 	 ||	"S 20%
S? 10%
^ 10%
ll II .1
0%	™ ™	™ ™	™ ™	™ ™	0%
2020/A	2020/B	2030/A	2030/B	2020/A	2020/B	2030/A	2030/B
C02
25%
D
< 20%
CO
E
^ 15%		1 	 ¦ Line Haul Operational
o	¦ Line Haul Technology
10%
-a
ai
oe 5%
0%
I - I
1.1.1
I Switcher
2020/A	2020/B	2030/A	2030/B	2050/A	2050/B
181 Bars are omitted where no emission reductions were estimated, due to a strategy not being applicable for a specific pollutant, (e.g. Line Haul Operational for NOx and PM2.5)
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-15. Rail Emission Reduction Summary by Scenario and Strategy, Tons per Year
Scenario
Rail Type
Tons Reduced per Year
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy Summary
2020/A
Line-haul Technology
90.4
4.8
6.9
3.7
0
0.3
0.1
0.6
Replace 50% of Tier 0+ engines with Tier 2+
engines
Switcher
208.6
7.6
17.1
5.9
150
0.6
0.1
1.4
Replace 50% of Pre-Tier 0 engines with 95%
Tier 2+ engines and 5% Tier 4 GenSet
Line-haul Operational
-
-
-
-
1,043
-
-
-
1% improvement in fuel efficiency
Total
299.0
12.5
24.0
9.6
1,193
0.9
0.2
2.0

2020/B
Line-haul
339.6
12.3
17.4
9.5
0
0.6
0.1
1.5
Replace 100% of Tier 0+ engines with 50% 2+
engines and 50% Tier 4 engines
Switcher
431.2
15.4
34.4
11.9
600
1.2
0.3
2.8
Replace all Pre-Tier 0 engines with 90% Tier 2+
and 10% Tier 4 Genset
Line-haul Operational
-
-
-
-
5,216
-
-
-
5% improvement in fuel efficiency
Total
770.7
27.8
51.8
21.4
5,817
1.9
0.4
4.3

2030/A
Line-haul
56.1
2.2
3.3
1.7
0
0.1
0.0
0.4
Replace 100% of Tier 1+ and earlier engines
with 50% 2+ engines and 50% Tier 4 engines
Switcher
181.9
7.0
14.8
5.4
396
0.6
0.1
1.4
Replace all Pre-Tier 0 engines and 20% of Tier
0+ with 90% Tier 2+ engines and 10% Tier 4
Genset
Line-haul Operational
-
-
-
-
6,835
-
-
-
5% improvement in fuel efficiency
Total
238.0
9.2
18.1
7.1
7,231
0.7
0.2
1.8

2030/B
Line-haul
573.8
13.0
20.0
10.0
0
0.9
0.2
2.2
Replace all pre-Tier 4 engines with Tier 4
engines.
Switcher
471.7
13.4
26.5
10.3
1,844
0.9
0.2
1.9
Replace all Pre-Tier 0 engines and 40% of Tier
0+ with 70% Tier 4 engines and 30% Tier 4
Genset
Line-haul Operational
-
-
-
-
13,669
-
-
-
10% improvement in fuel efficiency
Total
1,045.5
26.4
46.5
20.3
15,513
1.8
0.4
4.1

2050/A
Line-haul
-
-
-
-
12,076
-
-
-
Replace 10% of Tier 4 with zero emissions
locomotive
Switcher
-
-
-
-
11,399
-
-
-
Assume 30% Tier 4 Genset
Line-haul Operational
-
-
-
-
23,224
-
-
-
10% improvement in fuel efficiency
Total
-
-
-
-
46,699
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Rail Type
Tons Reduced per Year
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy Summary
2050/B
Line-haul
-
-
-
-
30,191
-
-
-
Replace 25% of Tier 4 with zero emissions
locomotive
Switcher
-
-
-
-
18,999
-
-
-
Assume 50% Tier 4 Genset
Line-haul Operational
-
-
-
-
46,447
-
-
-
20% improvement in fuel efficiency
Total
-
-
-
-
95,637
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-4. Rail Absolute Emission Reductions by Scenario and Strategy for Selected Pollutants182
N0X	PM25
600 		16
14
500	~
		12
-	400 _	__	_
as	¦	¦ ¦	as 10
a>	¦	¦¦	-
300
200
100
0
.1 II .1 II i ll II .1
2020/A	2020/B	2030/A	2030/B	2020/A	2020/B	2030/A	2030/B
CO,
50,000
40,000
$ 30,000
>-
,2 20'000	|	| m ¦ Switcher
10,000
0

In
I Line Haul Operational
I Line Haul Technology
2020/A	2020/B	2030/A	2030/B	2050/A	2050/B
182 Bars are omitted where no emission reductions were estimated, due to a strategy not being applicable for a specific pollutant (e.g. Line Haul Operational for NOx and PM2.5).
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
6.4. Cargo Handling Equipment
As described in Section 4, this assessment focused on CHE strategies for those equipment types that
contribute the bulk of CHE emissions at most ports: yard trucks, RTG cranes, and container handlers. See
Section 5 for further background on CHE strategies/83 and see Appendix Cfor more information on the
methodology and assumptions used for the CHE scenario analyses.
6.4.1. Yard Truck Strategies
Table 6-16 shows the yard truck strategy scenarios analyzed for Scenarios A and B for the three analysis
years. These strategy scenarios focused on replacement, especially for battery electric yard trucks due
to the underlying assumptions for fleet turnover in the BAU inventory.184
Table 6-16. Yard Truck Strategy Scenarios
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Replace all Tier
Replace all Tier
Replace 10%
Replace 25%
Replace
Replace 50%
3 with Tier 4
3 with Tier 4,
Tier 4 diesel
Tier 4 diesel
25% of Tier
of Tier 4

and replace 5%
with battery
with battery
4 diesel
diesel

of Tier 4 with
electric
electric
engines
engines with

battery electric


with
battery




battery
electric




electric

6.4.1.1. Relative Reduction Factors
For each scenario, a relative reduction factor was calculated using the emission rate for each tier
weighted by the population distribution in that tier. EPA's nonroad standards185 were used as criteria
pollutant emission factors for conventional diesel yard trucks. C02 emission factors were calculated
using GREET 2015 and several other assumptions to characterize the diesel and battery technologies in
the scenario strategies. RRFs were applied uniformly across the BAU inventory. See Appendix C for
further details on the methodology and assumptions used.
RRFs for yard truck strategy scenarios are shown in Table 6-17.
183	Note that all strategies are presented in terms of diesel equipment. Accordingly, all analyses were based on emission and
speciation factors for diesel-fueled CHE.
184	As described in Section 5 and Appendix C, the yard truck population distribution from the NONROAD model resulted in no
Tier 1 and Tier 2 yard trucks in operation in 2020 (and only 3% of the population is Tier 3). By 2030, no Tier 3 yard trucks were
assumed to be in operation.
185	EPA NONROAD Compressed Ignition Emission Standards. Available at
http://www.epa.gov/otaa/standards/nonroad/nonroadci.htm.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-17. Relative Reduction Factors for Yard Truck Strategies186
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
20%
21%
1%
21%
-0%
-1%
-0%
-1%
2020/B
24%
25%
6%
25%
4%
4%
5%
4%
2030/A
10%
10%
10%
10%
8%
10%
10%
10%
2030/B
25%
25%
25%
25%
19%
25%
25%
25%
2050/A
-
-
-
-
19%
-
-
-
2050/B
-
-
-
-
39%
-
-
-
6.4.1.2. Result Summary
Table 6-18 presents the total yard truck emission reductions by strategy scenario.
Table 6-18. Total Yard Truck Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
205.9
9.7
0.8
7.4
-3
-0.0
-0.0
-0.0
2020/B
247.1
11.5
4.0
8.8
19,824
0.0
0.1
0.1
2030/A
85.1
2.7
7.1
2.1
52,106
0.1
0.2
0.2
2030/B
212.8
6.9
17.7
5.3
130,266
0.2
0.5
0.5
2050/A
-
-
-
-
218,151
-
-
-
2050/B
-
-
-
-
436,303
-
-
-
6.4.2. RTG Crane Strategies
Table 6-19 shows the RTG crane strategy scenarios analyzed for Scenarios A and B for the three analysis
years. These strategy scenarios focused on replacement, especially for battery electric cranes due to the
underlying assumptions for fleet turnover in the BAU inventory.187
Table 6-19. RTG Crane Strategy Scenarios
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Replace all
Uncontrolled and
50% of Tier 1 and
2 with 50% Tier 3
and 50% Tier 4
Replace all
Uncontrolled,
Tier 1 and 2 with
75% Tier 4 and
25% electric
Replace all Tier 2
and 3 with 50%
Tier 4 and 50%
electric. Replace
10% Tier 4 with
electric
Replace all Tier 2
and 3 with 50%
Tier 4 and 50%
electric. Replace
25% Tier 4 with
electric
Replace 50%
Tier 4 with
electric
Replace 75%
Tier 4 with
electric
186	Here and in other tables, very small negative reduction values are shown as "-0%" and "-0.0" Note that the air toxic
reductions for Scenario 2020/A were small and negative while the VOC reductions were small and positive. This is due to Tier
4 aftertreatment, which changes the toxic speciation profiles.
187	As described in Section 5 and Appendix C, the RTG crane population distribution from the NONROAD model resulted in no
uncontrolled or Tier 1 cranes in operation in 2030 (and only 3% of the population is Tier 2 or Tier 3, with the rest being Tier 4).
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Section 6: Analysis of Emission Reduction Scenarios
6.4.2.1. Relative Reduction Factors
Relative reduction factors were determined using a similar methodology and assumptions as for yard
trucks described above; see Appendix C for further information. RRFs for RTG crane strategy scenarios
are shown in Table 6-20.
Table 6-20. Relative Reduction Factors for RTG Crane Strategies
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
19%
24%
9%
24%
-0%
5%
6%
3%
2020/B
42%
44%
21%
44%
2%
11%
13%
6%
2030/A
25%
24%
12%
24%
8%
10%
11%
10%
2030/B
37%
36%
26%
36%
20%
25%
25%
25%
2050/A
-
-
-
-
39%
-
-
-
2050/B
-
-
-
-
58%
-
-
-
6.4.2.2. Result Summary
Table 6-21 presents the total RTG crane emission reductions for the strategy scenarios.
Table 6-21. Total RTG Crane Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
174.4
7.6
5.6
5.9
-16
0.0
0.1
0.1
2020/B
377.6
13.8
13.3
10.6
4,676
0.1
0.2
0.1
2030/A
185.7
4.5
8.2
3.5
29,472
0.1
0.2
0.2
2030/B
272.7
6.8
18.0
5.2
69,368
0.2
0.5
0.5
2050/A
-
-
-
-
227,962
-
-
-
2050/B
-
-
-
-
341,943
-
-
-
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Section 6: Analysis of Emission Reduction Scenarios
6.4.3. Container Handler Strategies
Table 6-22 shows the container handler strategy scenarios analyzed for Scenarios A and B for the three
analysis years. These strategy scenarios focused on replacement, especially for battery electric
equipment due to the underlying assumptions for fleet turnover in the BAU inventory.188
Table 6-22. Container Handler Strategy Scenarios
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Replace all Tier 1
and 2 engines
with 50% Tier 3
and 50% Tier 4.
Replace Tier 1 and 2
engines with Tier 4
engines. Replace
Tier 3 with 50% Tier
4 and 50% elec.
engines
Replace 10% of
Tier 4 diesel
engines with
electric
engines
Replace 25% of
Tier 4 diesel
engines with
electric
Replace 50% of
Tier 4 diesel
engines with
electric
Replace 75% of
Tier 4 diesel
engines with
electric
6.4.3.1. Relative Reduction Factors
Relative reduction factors were determined using a similar methodology and assumptions as for yard trucks
described above; see Appendix C for further information. Table 6-23 shows resulting RRFs for container
handler scenarios.
Table 6-23. Relative Reduction Factors for Container Handler Strategies
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
17%
14%
10%
14%
-0%
5%
6%
3%
2020/B
68%
69%
23%
69%
6%
8%
11%
3%
2030/A
10%
10%
10%
10%
8%
10%
10%
10%
2030/B
25%
25%
25%
25%
19%
25%
25%
25%
2050/A
-
-
-
-
39%
-
-
-
2050/B
-
-
-
-
58%
-
-
-
6.4.3.2. Result Summary
Table 6-24 presents the total container handler emission reductions by strategy scenario.
Table 6-24. Total Container Handler Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
163.7
4.2
5.6
3.2
-7
0.0
0.1
0.1
2020/B
650.7
19.8
12.3
15.3
13,071
0.1
0.2
0.0
2030/A
78.8
1.7
6.0
1.3
22,873
0.1
0.2
0.2
2030/B
197.0
4.4
15.1
3.4
57,181
0.2
0.4
0.4
2050/A
-
-
-
-
191,518
-
-
-
2050/B
-
-
-
-
287,277
-
-
-
188 As described in Section 5 and Appendix C, the container handler population distribution from the NONROAD model resulted
in only Tier 4 equipment in operation in 2030 and 2050.
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Section 6: Analysis of Emission Reduction Scenarios
6.4.4. Summary of CHE Scenario Impacts
Table 6-25 shows the emission reductions relative to the BAU inventory. The percentages for each CHE
type are relative to the individual BAU inventory for that CHE type, whereas the total reductions from all
three CHE types considered are shown relative to the total CHE BAU inventory to illustrate the relative
magnitude of the reductions.189 Figure 6-5 shows the percentage reductions for NOx, PM2.5, and C02
relative to the individual BAU for each CHE type.
Absolute emission reduction results by scenario and strategy are shown in Table 6-26 for all pollutants
for the three specific types of CHE considered here. This table includes total emission reductions as the
sum over these three types of equipment strategies analyzed. This is appropriate in this situation
because there is no overlap for criteria, air toxic, or climate change pollutants between any of the three
equipment types since each set of reductions is derived from its own BAU inventory. Figure 6-6 shows
the tons/year reductions for NOx, PM2.5, and C02. Similar charts (as Figures 6-5 and 6-6) for other
pollutants can be found in Appendix C.
CHE strategy scenarios resulted in significant emission reductions for criteria, air toxic, and climate
change pollutants, and Scenario B consistently showed greater reductions than Scenario A. For
example, total relative NOx reductions from technology scenarios for all CHE types reduced 2020 BAU
NOx emissions by 17-39% and 2030 BAU emissions from 13-25%. Similar reductions were estimated for
PM2.5, where 2020 PM2.5 reductions were estimated between 18-37% and 2030 reductions were 12-25%
from the BAU case. As shown in Figure 6-6, the absolute NOx and PM2.5 emission reductions were
observed in 2020 and generally larger than or roughly equal to those for 2030, which may reflect the
significant rate of fleet turnover between 2020 and 2030. Finally, C02 reductions estimated in this
analysis were substantial, especially in 2030 and 2050 where reductions were estimated as 7-18% and
27-45% respectively. These significant C02 reductions demonstrate the potential of the electric
technologies that were modeled in later years.
It is important to caveat the CHE results in accordance with how this assessment was completed. All
CHE were considered to operate on-port, and thus all reductions reported here are limited to a modeled
port facility. Although the three types of CHE analyzed here were selected due to their dominance in
CHE inventories, additional benefits could be gained by applying these, or similar strategies, to other
CHE types.
189 Specifically, the total CHE BAU inventory is the sum of all CHE types, both the three types considered here and other
equipment (e.g., forklifts) not targeted for reductions in this analysis. For this reason, the percent reductions calculated from
the sum of all three types of CHE is smaller than the sum of the percent reductions of the three CHE types. This would not be
the case if the denominator in the percent reductions were limited to the total BAU emissions of only the three types of
equipment that these strategies were applied to.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-25. CHE Emission Relative Reductions by Scenario and Strategy, Percent190'191
Scenario
Equipment Type
Percent Reduction from BAU
NOx
PM
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy
2020/A
Yard Tractor
20%
21%
1%
21%
-0%
-1%
-0%
-1%
Replace all Tier 3 with Tier 4
Container Handler
17%
14%
10%
14%
-0%
5%
6%
3%
Replace all Tier 1 and 2 engines
with 50% Tier 3 and 50% Tier 4
RTG Crane
19%
24%
9%
24%
-0%
5%
6%
3%
Replace all Uncontrolled and 50%
of Tier 1 and 2 with 50% Tier 3 and
50% Tier 4
Total
17%
18%
6%
18%
-0%
2%
3%
1%

2020/B
Yard Tractor
24%
25%
6%
25%
4%
4%
5%
4%
Replace all Tier 3 with Tier 4, and
replace 5% of Tier 4 with battery
electric
Container Handler
68%
69%
23%
69%
6%
8%
11%
3%
Replace Tier 1 and 2 engines with
Tier 4 engines.
Replace Tier 3 with 50% Tier 4 and
50% electric engines
RTG Crane
42%
44%
21%
44%
2%
11%
13%
6%
Replace all Uncontrolled, Tier 1
and 2 with 75% Tier 4 and 25%
electric
Total
39%
37%
14%
37%
3%
7%
8%
4%

2030/A
Yard Tractor
10%
10%
10%
10%
8%
10%
10%
10%
Replace 10% Tier 4 diesel with
battery electric
Container Handler
10%
10%
10%
10%
8%
10%
10%
10%
Replace 10% of Tier 4 diesel
engines with electric engines
RTG Crane
25%
24%
12%
24%
8%
10%
11%
10%
Replace all Tier 2 and 3 with 50%
Tier 4 and 50% electric
Replace 10% Tier 4 with electric
Total
13%
12%
9%
12%
7%
9%
9%
9%

2030/B
Yard Tractor
25%
25%
25%
25%
19%
25%
25%
25%
Replace 25% Tier 4 diesel with
battery electric
190	As noted in the text, total percent reductions are determined relative to a total BAU CHE inventory that includes more than the three types of CHE analyzed here. Thus, the
total percent reduction values are less than the sum of the percent reductions from each of the three CHE types shown in the table.
191	Strategies 2020/A Yard Tractor for Benzene emissions and 2020/A C02 emissions for all three CHE types produce very small negative percent reductions. These are shown
here as -0%, consistent with the resolution of other values.
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Equipment Type
Percent Reduction from BAU
NOx
PM
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy
Container Handler
25%
25%
25%
25%
19%
25%
25%
25%
Replace 25% of Tier 4 diesel
engines with electric
RTG Crane
37%
36%
26%
36%
20%
25%
25%
25%
Replace all Tier 2 and 3 with 50%
Tier 4 and 50% electric
Replace 25% Tier 4 with electric
Total
25%
25%
22%
25%
18%
21%
21%
21%

2050/A
Yard Tractor
-
-
-
-
19%
-
-
-
Replace 25% of Tier 4 diesel
engines with battery electric
Container Handler
-
-
-
-
39%
-
-
-
Replace 50% of Tier 4 diesel
engines with electric
RTG Crane
-
-
-
-
39%
-
-
-
Replace 50% Tier 4 with electric
Total
-
-
-
-
27%
-
-
-

2050/B
Yard Tractor
-
-
-
-
39%
-
-
-
Replace 50% of Tier 4 diesel
engines with battery electric
Container Handler
-
-
-
-
58%
-
-
-
Replace 75% of Tier 4 diesel
engines with electric
RTG Crane
-
-
-
-
58%
-
-
-
Replace 75% Tier 4 with electric
Total
-
-
-
-
45%
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-5. CHE Percent Emission Reductions by Scenario and Strategy for Selected Pollutants
NO„
PM,
70%
D 60%
<
CO
£ 50%
0
40%
c
30%
u
1	20%
cc
S? 10%
0%
70%
D 60%
<
co
£ 50%
0
40%
c
30%
u
1	20%
cc
S? 10%
0%
2020/A
2020/B
2030/A
2030/B
¦II
2020/A
2020/B	2030/A	2030/B
CO,
60%
< 50%
CO
I 40%
i-
M—
= 30%
-a
ai
cc
20%
10%
0%
I Container Handler
I RTG Crane
I Yard Tractor
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-26. CHE Emission Reduction Summary by Scenario and Strategy, Tons per Year192
Scenario
Equipment Type
Tons Reduced per Year
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy
2020/A
Yard Tractor
205.9
9.7
0.8
7.4
-3
-0.0
-0.0
-0.0
Replace all Tier 3 with Tier 4
Container Handler
163.7
4.2
5.6
3.2
-7
0.0
0.1
0.1
Replace all Tier 1 and 2 engines
with 50% Tier 3 and 50% Tier 4
RTG Crane
174.4
7.6
5.6
5.9
-16
0.0
0.1
0.1
Replace all Uncontrolled and 50%
of Tier 1 and 2 with 50% Tier 3 and
50% Tier 4
Total
544.0
21.4
12.0
16.5
-26
0.1
0.2
0.1

2020/B
Yard Tractor
247.1
11.5
4.0
8.8
19,824
0.0
0.1
0.1
Replace all Tier 3 with Tier 4, and
replace 5% of Tier 4 with battery
electric
Container Handler
650.7
19.8
12.3
15.3
13,071
0.1
0.2
0.0
Replace Tier 1 and 2 engines with
Tier 4 engines.
Replace Tier 3 with 50% Tier 4 and
50% electric engines
RTG Crane
377.6
13.8
13.3
10.6
4,676
0.1
0.2
0.1
Replace all Uncontrolled, Tier 1
and 2 with 75% Tier 4 and 25%
electric
Total
1,275.4
45.1
29.6
34.7
37,572
0.2
0.5
0.3

2030/A
Yard Tractor
85.1
2.7
7.1
2.1
52,106
0.1
0.2
0.2
Replace 10% Tier 4 diesel with
battery electric
Container Handler
78.8
1.7
6.0
1.3
22,873
0.1
0.2
0.2
Replace 10% of Tier 4 diesel
engines with electric engines
RTG Crane
185.7
4.5
8.2
3.5
29,472
0.1
0.2
0.2
Replace all Tier 2 and 3 with 50%
Tier 4 and 50% electric
Replace 10% Tier 4 with electric
Total
349.6
9.0
21.3
7.0
104,451
0.3
0.6
0.5

2030/B
Yard Tractor
212.8
6.9
17.7
5.3
130,266
0.2
0.5
0.5
Replace 25% Tier 4 diesel with
battery electric
Container Handler
197.0
4.4
15.1
3.4
57,181
0.2
0.4
0.4
Replace 25% of Tier 4 diesel
engines with electric
192 Some strategies, particularly 2020/A Yard Tractor TAC emissions, produce very small negative numbers. These are shown here as -0.0, consistent with the resolution of other
values.
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Equipment Type
Tons Reduced per Year
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Strategy
RTG Crane
272.7
6.8
18.0
5.2
69,368
0.2
0.5
0.5
Replace all Tier 2 and 3 with 50%
Tier 4 and 50% electric
Replace 25% Tier 4 with electric
Total
682.5
18.0
50.8
13.9
256,815
0.6
1.4
1.3

2050/A
Yard Tractor
-
-
-
-
218,151
-
-
-
Replace 25% of Tier 4 diesel
engines with battery electric
Container Handler
-
-
-
-
191,518
-
-
-
Replace 50% of Tier 4 diesel
engines with electric
RTG Crane
-
-
-
-
227,962
-
-
-
Replace 50% Tier 4 with electric
Total
-
-
-
-
637,631
-
-
-

2050/B
Yard Tractor
-
-
-
-
436,303
-
-
-
Replace 50% of Tier 4 diesel
engines with battery electric
Container Handler
-
-
-
-
287,277
-
-
-
Replace 75% of Tier 4 diesel
engines with electric
RTG Crane
-
-
-
-
341,943
-
-
-
Replace 75% Tier 4 with electric
Total
-
-
-
-
1,065,523
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-6. CHE Absolute Emission Reductions by Scenario and Strategy for Selected Pollutants
NOx	PM25
700 		20
18
16
500	H	14
600
(D	¦	fU	1 n
a;	400 ¦	a>	12
>	¦—	>	10
a	¦¦	g	8
200
100
0
III III .I. ill i ill III .!¦ ill
2020/A	2020/B	2030/A	2030/B	2020/A	2020/B	2030/A	2030/B
C02
450,000
400,000
350,000
i- 300,000
Si	¦ Container Handler
>! 250,000
200,000					— ¦RTG Crane
150,000					— ¦ Yard Tractor
100,000
50,000	m
o			 mUM
.1
2020/A	2020/B	2030/A	2030/B	2050/A	2050/B
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Section 6: Analysis of Emission Reduction Scenarios
6.5. Harbor Craft
The analysis of emission reduction strategies for harbor craft focused on the two types of vessels that
contribute the bulk of harbor craft emissions at most ports: tugs and ferries. See Section 5 for further
background on harbor craft strategies, as well as Section 4 and Appendix C for more information on the
development of the harbor craft BAU inventories and scenario analysis.
6.5.1. Tug Strategies
Table 6-27 shows the tug strategy scenarios analyzed for Scenarios A and B for the different analysis
years. Due to the slower fleet turnover assumed, tug strategies analyzed included more repowers and
replacements of cleaner diesel engines for all years, with an introduction of hybrid electric technology in
2030 and 2050.
Table 6-27. Tug Strategy Scenarios
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Repower/
Repower/
Repower/
Repower/ Replace
Repower/
Repower/
Replace all
Replace all
Replace all Tier
all Tier 1 and 2
Replace 50% of
Replace all Tier 3
Pre-Control
Pre-Control
1 and 2 with
with Tier 4
Tier 3 engines
engines with Tier
engines with
and Tier 1
Tier 4
Repower/ Replace
with Tier 4
4 engines
Tier 3 engines
with Tier 3
Repower/
50% of Tier 3
engines
Repower/

Repower 10%
Replace 25% of
engines with Tier
Repower/
Replace 25% of

of Tier 2 with
Tier 3 engines
4 engines
Replace 10% of
Tier 4 with hybrid

Tier 3 hybrid
with Tier 4
Repower/ Replace
Tier 4 with hybrid
electric

electric
engines
25% of Tier 4 with
hybrid electric
electric

6.5.1.1. Relative Reduction Factors
A relative reduction factor (RRF) was calculated for each scenario using the emission rate for each tier
weighted by the population distribution in that tier. This method was applied consistently for all
strategies outlined in Table 6-27 and applied uniformly across the tug portion of the BAU inventory. The
resulting RRFs for tug strategy scenarios are shown in Table 6-28.
Table 6-28. Relative Reduction Factors for Tug Strategies
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
9%
14%
9%
14%
0%
9%
9%
9%
2020/B
27%
49%
34%
49%
1%
33%
33%
32%
2030/A
27%
30%
28%
30%
0%
17%
20%
7%
2030/B
42%
41%
39%
41%
1%
21%
27%
6%
2050/A
-
-
-
-
1%
-
-
-
2050/B
-
-
-
-
3%
-
-
-
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Section 6: Analysis of Emission Reduction Scenarios
6.5.1.2. Result Summary
Table 6-29 presents the total emission reductions of tug strategy scenarios.
Table 6-29. Total Tug Emission Reductions
Scenario
Tons per Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
2,390.5
102.5
55.5
78.9
0
2.0
0.4
4.4
2020/B
7,108.1
364.2
205.7
280.4
30,300
7.3
1.6
15.9
2030/A
5,099.2
164.4
117.1
126.6
0
2.6
0.7
2.6
2030/B
7,961.4
222.6
165.5
171.4
29,312
3.3
0.9
2.0
2050/A
-
-
-
-
73,301
-
-
-
2050/B
-

-
-
183,253
-
-
-
6.5.2. Ferry Strategies
Table 6-30 shows the ferry strategy scenarios analyzed for the relevant analysis years in this
assessment. As with tugs, scenarios included more repower and replacement strategies for cleaner
diesel engines, with some opportunity for hybrid electric technology in all analysis years.
Table 6-30. Ferry Strategy Scenarios
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Repower/
Repower/
Repower/
Repower/
Repower/
Repower/
Replace all Pre-
Replace all Pre-
Replace all Tier
Replace all Tier
Replace all Tier
Replace all Tier
Control engines
Control and Tier
0,1 and 2 with
0,1 and 2 with
2 and 50% of
2 and 3 engines
with Tier 3
1 with Tier 3
Tier 4
Tier 4
Tier 3 engines
with Tier 4
engines
Repower 10% of
Repower/
Repower/
with Tier 4
engines

Tier 2 with Tier
Replace 25% of
Replace 50% of
engines
Repower/

3 hybrid electric
Tier 3 engines
Tier 3 engines
Repower/
Replace 25% of


with Tier 4
with Tier 4
Replace 10% of
Tier 4 with


engines
engines.
Repower/
Replace 25% of
Tier 4 with
hybrid electric
Tier 4 with
hybrid electric
hybrid electric
6.5.2.1. Relative Reduction Factors
A relative reduction factor (RRF) was calculated using the emission rate for each tier weighted by
the population distribution in that tier. This method was applied consistently for all strategies
outlined in Table 6-30 and applied uniformly to all ports within this national scale analysis.
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Section 6: Analysis of Emission Reduction Scenarios
The RRFs for ferry strategy scenarios are shown in Table 6-31.
Table 6-31. Relative Reduction Factors for Ferry Strategies
Scenario
Overall Emission Reductions (%)
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
30%
33%
23%
33%
0%
22%
23%
22%
2020/B
39%
50%
34%
50%
0%
34%
34%
33%
2030/A
51%
60%
50%
60%
0%
39%
42%
29%
2030/B
62%
68%
59%
68%
1%
44%
49%
32%
2050/A
-
-
-
-
1%
-
-
-
2050/B
-
-
-
-
3%
-
-
-
6.5.2.2. Result Summary
Table 6-32 presents the total ferry emission reductions by strategy scenario.
Table 6-32. Total Ferry Emission Reductions, Tons per Year
Scenario
Tons per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
952.2
30.2
16.8
23.2
0
0.6
0.1
1.3
2020/B
1,249.1
45.2
25.3
34.8
1,124
0.9
0.2
2.0
2030/A
926.4
31.6
20.0
24.3
0
0.6
0.1
1.0
2030/B
1,108.0
35.5
23.6
27.3
3,090
0.6
0.2
1.1
2050/A
-
-
-
-
4,383
-
-
-
2050/B
-
-
-
-
10,957
-
-
-
6.5.3. Summary of Harbor Craft Scenario Impacts
Table 6-33 shows the emission reductions relative to the BAU inventory, and Figure 6-7 shows the
percentage reductions for NOx, PM2.5, and C02. Similar charts for other pollutants can be found in
Appendix C. To better illustrate the relative magnitude of the reductions, the values are presented for
both the total BAU emissions for the sector (including other types of Category 1 and 2 vessels not
characterized here) as well as for specific vessel types. In Table 6-33, the percentages for each vessel
type are calculated against the individual BAU inventory for that vessel type, and the total reductions
from both vessel types considered are shown relative to the total harbor craft BAU inventory.193
Table 6-34 summarizes absolute emission reduction results for all pollutants by scenario and strategy for
the two specific types of harbor craft considered here. This table includes total emission reductions as
the sum over these two vessel types. This is appropriate in this situation because there is no overlap for
criteria, toxic, or C02 pollutants between these two vessel types since each set of reductions is derived
193 Specifically, the total harbor craft BAU inventory is the sum of all harbor craft types, both the two types considered here and
other kinds (e.g., research vessels) not targeted for reductions in this analysis. For this reason, the percent reductions
calculated from the sum of both kinds of harbor craft is smaller than the sum of the percent reductions of tugs and ferries.
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Section 6: Analysis of Emission Reduction Scenarios
from its own BAU inventory. Figure 6-8 shows the tons/year reductions for NOx, PM2.5, and C02, and
similar charts for other pollutants can be found in Appendix C.
By accelerating fleet turnover through the introduction of cleaner technologies, the harbor craft strategy
scenarios produced significant NOx and PM25 reductions. For example, total relative NOx reductions
from all harbor craft strategies produced significant reductions between Scenarios A and B; in 2020,
reductions ranged from 10-24% and from 25-38% in 2030 from the total harbor craft BAU inventories
for those years. Similar reductions were observed for PM2.5, where total 2020 PM25 reductions were
estimated between 13-41% and total 2030 reductions were from 28-37% from the BAU case. In
contrast, minimal C02 reductions were observed for all scenarios, with a 1-3% C02 reduction estimated
in 2050; no significant C02 reductions were estimated in 2020 or 2030 since no or limited hybrid electric
replacements occurred in those analysis years. These particular results should not be viewed as
reflecting the full potential of hybrid electric technologies; instead the low performance of these
strategies in this assessment is due to the slower rate of turnover assumed for this sector in the analysis
(and thus, the reduced opportunity for applying such technologies).
There are also noteworthy differences between comparing relative and absolute reductions for this
sector. Figure 6-7 illustrates the importance of assessing the potential of emission reductions for a given
scenario, where ferry strategy scenarios show a higher relative reductions in criteria polllutants as
compared to tug scenarios for all modeled scenarios. This is most likely due to the higher relative
reduction factors for ferry scenarios that reflect more replacement of lower tier diesel engines. In
contrast, the opposite is true for total emission reductions in Figure 6-8, where tug strategy scenarios
produce a significantly larger absolute emission reduction than ferry scenarios for criteria pollutants,
due to the large number of tugs assumed relative to ferries in the harbor craft BAU inventories.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-33. Harbor Craft Emission Relative Reduction Summary by Scenario and Strategy, Percent194
Scenario
Vessel
Percent Reduction from BAU
Strategy
Type
NOX
PM2.5
VOC
BC
co2
Acetaldehyde
Benzene
Formaldehyde

Tug
9%
14%
9%
14%
0%
9%
9%
9%
Repower/ Replace all Pre-Control engines with
Tier 3 engines
2020/A
Ferry
30%
33%
23%
33%
0%
22%
22%
22%
Repower/ Replace all Pre-Control engines with
Tier 3 engines

Total
10%
13%
9%
13%
0%
9%
9%
9%











Repower/ Replace all Pre-Control and Tier 1 with

Tug
27%
49%
34%
49%
1%
33%
33%
32%
Tier 3. Repower 10% of Tier 2 with Tier 3 hybrid
electric.
2020/B









Repower/ Replace all Pre-Control and Tier 1 with

Ferry
39%
50%
34%
50%
0%
34%
34%
33%
Tier 3. Repower 10% of Tier 2 with Tier 3 hybrid
electric.

Total
24%
41%
28%
41%
1%
28%
28%
27%











Repower/ Replace all Tier 1 and 2 with Tier 4.

Tug
27%
30%
28%
30%
0%
16%
20%
7%
Repower/ Replace 25% of Tier 3 engines with Tier
4 engines.
2030/A









Repower/ Replace all Tier 0,1 and 2 with Tier 4.

Ferry
51%
60%
50%
60%
0%
39%
42%
29%
Repower/ Replace 25% of Tier 3 engines with Tier
4 engines.

Total
25%
28%
26%
28%
0%
16%
19%
8%











Repower/ Replace all Tier 1 and 2 with Tier 4.

Tug
42%
41%
39%
41%
1%
21%
27%
6%
Repower/ Replace 50% of Tier 3 engines with Tier
4 engines. Repower/ Replace 25% of Tier 4 with
hybrid electric.
2030/B









Repower/ Replace all Tier 0,1 and 2 with Tier 4.

Ferry
62%
67%
59%
67%
1%
44%
49%
32%
Repower/ Replace 50% of Tier 3 engines with Tier
4 engines. Repower/ Replace 25% of Tier 4 with
hybrid electric.

Total
38%
37%
35%
37%
1%
20%
24%
7%

194 As noted in the text, total percent reductions are determined relative to a total BAU harbor craft inventory that includes more than the two types of harbor craft analyzed
here. (It also includes fishing vessels, government vessels, support vessels, etc.) Thus, the total percent reduction values are less than the sum of the percent reductions from
each of the two harbor craft types shown in the table.
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Vessel
Type
Percent Reduction from BAU
Strategy
NOX
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
2050/A
Tug
-
-
-
-
1%
-
-
-
Repower/ Replace 50% of Tier 3 engines with Tier
4 engines. Repower/ Replace 10% of Tier 4 with
hybrid electric.
Ferry
-
-
-
-
1%
-
-
-
Repower/ Replace all Tier 2 and 50% of Tier 3
engines with Tier 4 engines. Repower/ Replace
10% of Tier 4 with hybrid electric.
Total
-
-
-
-
1%
-
-
-

2050/B
Tug
-
-
-
-
3%
-
-
-
Repower/ Replace all Tier 3 engines with Tier 4
engines. Repower/ Replace 25% of Tier 4 with
hybrid electric.
Ferry
-
-
-
-
3%
-
-
-
Repower/ Replace all Tier 2 and 3 engines with
Tier 4 engines. Repower/ Replace 25% of Tier 4
with hybrid electric.
Total
-
-
-
-
3%
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-7. Harbor Craft Percent Emission Reductions by Scenario and Strategy for Selected Pollutants
li
2030/B
C02
3.5%
3 3.0%
<
CO
£ 2.5%
o
£ 2.0%
£
•£ 1.5%
u
| 1.0%	_
s? 0.5%
0.0%	®
2020/A	2020/B
20201k
2020/B
2030/A
2030/B
2020/A
2020/B
2030/A
2030/A
2030/B
2050/A
2050/B
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-34. Harbor Craft Emission Reduction Summary by Scenario and Strategy, Tons per Year
Scenario
Vessel
Type
Tons Reduced per Year
Strategy
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
2020/A
Tug
2,390.5
102.5
55.5
78.9
0
2.0
0.4
4.4
Repower/ Replace all Pre-Control engines with
Tier 3 engines
Ferry
952.2
30.2
16.8
23.2
0
0.6
0.1
1.3
Repower/ Replace all Pre-Control engines with
Tier 3 engines
Total
3,342.7
132.6
72.3
102.1
0
2.6
0.6
5.8

2020/B
Tug
7,108.1
364.2
205.7
280.4
30,300
7.3
1.6
15.9
Repower/ Replace all Pre-Control and Tier 1 with
Tier 3. Repower 10% of Tier 2 with Tier 3 hybrid
electric.
Ferry
1,249.1
45.2
25.3
34.8
1,124
0.9
0.2
2.0
Repower/ Replace all Pre-Control and Tier 1 with
Tier 3. Repower 10% of Tier 2 with Tier 3 hybrid
electric.
Total
8,357.2
409.4
231.0
315.2
31,424
8.2
1.8
17.9

2030/A
Tug
5,099.2
164.4
117.1
126.6
0
2.6
0.7
2.6
Repower/ Replace all Tier 1 and 2 with Tier 4.
Repower/ Replace 25% of Tier 3 engines with Tier
4 engines.
Ferry
926.4
31.6
20.0
24.3
0
0.6
0.1
1.0
Repower/ Replace all Tier 0,1 and 2 with Tier 4.
Repower/ Replace 25% of Tier 3 engines with Tier
4 engines.
Total
6,025.5
196.0
137.1
150.9
0
3.2
0.8
3.6

2030/B
Tug
7,961.4
222.6
165.5
171.4
29,312
3.3
0.9
2.0
Repower/ Replace all Tier 1 and 2 with Tier 4.
Repower/ Replace 50% of Tier 3 engines with Tier
4 engines. Repower/ Replace 25% of Tier 4 with
hybrid electric.
Ferry
1,108.0
35.5
23.6
27.3
3,090
0.6
0.2
1.1
Repower/ Replace all Tier 0,1 and 2 with Tier 4.
Repower/ Replace 50% of Tier 3 engines with Tier
4 engines. Repower/ Replace 25% of Tier 4 with
hybrid electric.
Total
9,069.5
258.1
189.1
198.7
32,402
3.9
1.1
3.1

2050/A
Tug
-
-
-
-
73,301
-
-
-
Repower/ Replace 50% of Tier 3 engines with Tier
4 engines. Repower/ Replace 10% of Tier 4 with
hybrid electric.
Ferry
-
-
-
-
4,383
-
-
-
Repower/ Replace all Tier 2 and 50% of Tier 3
engines with Tier 4 engines. Repower/ Replace
10% of Tier 4 with hybrid electric.
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Vessel
Type
Tons Reduced per Year
Strategy
NOx
PM2.5
voc
BC
co2
Acetaldehyde
Benzene
Formaldehyde
Total
-
-
-
-
77,684
-
-
-

2050/B
Tug
-
-
-
-
183,253
-
-
-
Repower/ Replace all Tier 3 engines with Tier 4
engines. Repower/ Replace 25% of Tier 4 with
hybrid electric.
Ferry
-
-
-
-
10,957
-
-
-
Repower/ Replace all Tier 2 and 3 engines with
Tier 4 engines. Repower/ Replace 25% of Tier 4
with hybrid electric.
Total
-
-
-
-
194,210
-
-
-

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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-8. Harbor Craft Absolute Emission Reductions by Scenario and Strategy for Selected Pollutants
NO„
PM,
(O
CD
LO
£
O
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
I
400
350
300
250
200
150
100
50
0
2020/A
2020/B
2030/A
2030/B
.1
2020/A
.1
2020/B
2030/A
2030/B
CO,
200,000
180,000
160,000
140,000
120,000
100,000
80,000
60,000
40,000
20,000
0
I
I Ferry
I Tug
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
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Section 6: Analysis of Emission Reduction Scenarios
6.6. Ocean Going Vessels
OGV scenarios covered several different types of strategies, and these were grouped under the
following categories:
¦	Fuel Change
¦	Shore Power
¦	Advanced Marine Emission Control System (AMECS)195
¦	Reduced Hoteling Time
Several factors were considered here, similar to the considerations that port stakeholders would need to
understand when deciding among several strategies. EPA considered the specific vessel types that
would best be targeted for a given strategy as well as the feasibility of implementing fuel and technology
strategies. Some strategies, such as shore power, were applied only to OGVs that were assumed to visit
the same port multiple times a year (i.e., "frequent callers"), while other strategies could be
implemented for frequent and non-frequent callers of an appropriate vessel type. In addition, some
strategies were applied to either propulsion or auxiliary OGV engines and the respective types of
emissions involved (e.g., targeting auxiliary engines would reduce OGV hoteling emissions).
The following sections summarize the methodology and results for each of these four categories of
strategy scenarios. Reductions were calculated for all scenarios relative to the applicable portion of the
BAU inventories, independently. For example, strategies that address auxiliary engines were compared
to the portion of auxiliary emissions in the BAU inventories. Further background on OGV strategies can
be found in Section 5 of this report, and see Appendix C for details on the methodology and assumptions
for OGV strategy scenarios.
6.6.1. Fuel Change Strategies
The Fuel Change strategy scenarios included several fuel types that substituted for the fuel required in
the North American Emission Control Area (ECA) (i.e., 1,000 ppm sulfur distillate fuel).196
¦	Use 500 ppm sulfur diesel fuel in propulsion engines for bulk carriers, container ships, passenger
ships and tankers.
¦	Use 200 ppm sulfur diesel fuel in propulsion engines for bulk carriers, container ships, passenger
ships and tankers.
¦	Use ultra-low sulfur diesel (ULSD) in auxiliary engines for bulk carriers, container ships, passenger
ships and tankers.
¦	Use liquefied natural gas (LNG) in propulsion engines for bulk carriers, container ships and tankers.
¦	Use LNG in auxiliary engines for bulk carriers, container ships and tankers.
Fuel Change scenarios are presented separately for propulsion and auxiliary engines, and as discussed
earlier, these engines are involved in different types of OGV activity that may be important to consider
195	AMECS is the term used by the California Air Resources Board (CARB) for this technology, sometimes also referred to as
"stack bonnets."
196	U.S. Environmental Protection Agency, Control of Emissions from New Marine Compression-Ignition Engines at or Above 30
Liters per Cylinder, 75 FR 24802 (April 30, 2010).
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Section 6: Analysis of Emission Reduction Scenarios
when deciding the priority of individual strategies (e.g., propulsion and auxiliary engines are used for
OGV maneuvering activity within a harbor while only auxiliary engines are used for hoteling at land-
side). Table 6-35 shows the Fuel Change scenarios considered for propulsion engines. Each of these
scenarios reflects the penetration rates of new fuel with the remaining fuel assumed to be 1,000 ppm S
Marine Diesel Oil (MDO)/Marine Gas Oil (MGO), as required by the ECA. For example, in Scenario A in
2020 ("2020/A"), the total fuel for propulsion engine activity was assumed to be 10% 500 ppm S, 2%
LNG, and 88% 1,000 ppm S.
Table 6-35. Fuel Change Strategy Scenarios for OGV Propulsion Engines
Ship Type
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Bulk
10% use 500
ppm sulfur
fuel; 2% use
LNG
25% use 500
ppm sulfur
fuel; 10% use
LNG
25% use 200
ppm sulfur
fuel; 4% use
LNG
50% use 200
ppm sulfur
fuel; 15% use
LNG
8% use LNG
25% use LNG
Container
10% use 500
ppm sulfur
fuel; 1% use
LNG
25% use 500
ppm sulfur
fuel; 5% use
LNG
25% use 200
ppm sulfur
fuel; 2% use
LNG
50% use 200
ppm sulfur
fuel; 5% use
LNG
5% use LNG
5% use LNG
Passenger
10% use 500
ppm sulfur
fuel
25% use 500
ppm sulfur
fuel
25% use 200
ppm sulfur
fuel
50% use 200
ppm sulfur
fuel
-
-
Tanker
10% use 500
ppm sulfur
fuel; 2% use
LNG
25% use 500
ppm sulfur
fuel; 10% use
LNG
25% use 200
ppm sulfur
fuel; 4% use
LNG
50% use 200
ppm sulfur
fuel; 15% use
LNG
8% use LNG
25% use LNG
The percentages were applied to that portion of the installed auxiliary power (i.e., calls times total
auxiliary power) and the remaining percentage in each scenario was assumed to be 1,000 ppm sulfur
fuel. LNG was limited to 5% in container ships, and LNG was not applied to passenger ships due to
passenger safety issues.197 Note also that the 2050 reductions were calculated only for C02 emissions,
so only strategies that affect C02 emission were included for scenarios in that year. Table 6-36 shows the
Fuel Change strategy scenarios for auxiliary engines.
197 Lloyd's Register Marine, Global Marine Fuel Trends 2030, 2014. Available at http://www.lr.org/en/ images/213-
34172 Global Marine Fuel Trends 2030.pdf.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-36. Fuel Change Strategy Scenarios for OGV Auxiliary Engines
Ship Type
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Bulk
10% use
ULSD; 2% use
LNG
20% use
ULSD; 10%
use LNG
30% use
ULSD; 4% use
LNG
40% use
ULSD; 15%
use LNG
8% use LNG
25% use LNG
Container
10% use
ULSD; 1% use
LNG
20% use
ULSD; 5% use
LNG
30% use
ULSD; 2% use
LNG
40% use
ULSD; 5% use
LNG
5% use LNG
5% use LNG
Passenger
10% use
ULSD
20% use
ULSD
30% use
ULSD
40% use
ULSD
-
-
Tanker
10% use
ULSD; 2% use
LNG
20% use
ULSD; 10%
use LNG
30% use
ULSD; 4% use
LNG
40% use
ULSD; 15%
use LNG
8% use LNG
25% use LNG
As described above, all percentages were applied according to that portion of the installed auxiliary
power (i.e., calls times total auxiliary power) and the remaining percentage in each scenario was
assumed to be 1,000 ppm sulfur fuel. The LNG assumptions for propulsion engines also were applied to
auxiliary engines and the 2050 scenarios.
6.6.1.1. Relative Reduction Factors
To calculate emission reductions for the scenarios listed in Table 6-35 and Table 6-36, BAU emission
inventories were separated into propulsion and auxiliary engine emissions for four ship types: bulk
carrier, container, passenger, and tanker vessels. Emissions related to propulsion engines during
reduced speed zone (RSZ) and maneuvering modes were combined into the propulsion engine
emissions. Emissions related to auxiliary engines during RSZ, maneuvering, and hoteling modes were
combined into the auxiliary engine emissions. In addition, hoteling-only emissions were also calculated
by ship type to use for strategies that affect only hoteling emissions, and were included in the auxiliary
engine emissions of the BAU inventories. BAU emissions assumed the use of 1,000 ppm S fuel in
propulsion and auxiliary engines.
Relative reduction factors (RRFs) were calculated for each scenario by developing emission factors by
engine type and fuel type for each ship type. The RRFs for OGV Fuel Change scenarios are shown in
Table 6-37 through Table 6-41.198
198 Please note that use of emissions factors to determine RRF implies that other technical and operational parameters, such as
engine load, are unchanged between the BAU and analysis scenario. Negative RRFs imply an increase in emissions from the
scenario.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-37. Relative Reduction Factors for Fuel Scenario 2020/A199
Engine
Vessel
Overall Emission Reductions (%)
NOx
PM2.5
HC200
BC
CO2
S02
Propulsion
Bulk
2%
3%
0%
1%
0%
7%
Container
1%
2%
0%
1%
0%
6%
Passenger
0%
1%
0%
1%
0%
5%
Tanker
2%
3%
0%
1%
1%
7%
Auxiliary
Bulk
2%
4%
-1%
2%
1%
12%
Container
1%
3%
-0%
2%
0%
11%
Passenger
0%
2%
0%
2%
0%
10%
Tanker
2%
4%
-1%
2%
1%
12%
Table 6-38. Relative Reduction Factors for Fuel Scenario 2020/B
Engine
Vessel
Overall Emission Reductions (%)
NOx
PM2.5
HC
BC
CO2
SO2
Propulsion
Bulk
9%
10%
2%
2%
2%
22%
Container
4%
6%
1%
2%
1%
18%
Passenger
0%
2%
0%
2%
0%
13%
Tanker
9%
10%
2%
2%
2%
22%
Auxiliary
Bulk
9%
12%
-3%
3%
3%
30%
Container
4%
8%
-1%
4%
2%
25%
Passenger
0%
5%
0%
5%
0%
25%
Tanker
9%
12%
-3%
3%
3%
30%
Table 6-39. Relative Reduction Factors for Fuel Scenario 2030/A
Engine
Vessel
Overall Emission Reductions (%)
NOx
PM2.5
HC
BC
CO2
SO2
Propulsion
Bulk
3%
6%
1%
3%
1%
24%
Container
2%
5%
0%
3%
1%
22%
Passenger
0%
3%
0%
3%
0%
20%
Tanker
3%
7%
1%
3%
1%
24%
Auxiliary
Bulk
3%
9%
-1%
5%
1%
34%
Container
1%
7%
-1%
5%
1%
32%
Passenger
0%
6%
0%
6%
0%
30%
Tanker
3%
9%
-1%
5%
1%
34%
199	As done previously, the very small negative percent reductions for HC for Container Ship Auxiliary Engines are shown as -0%.
200	Note that, consistent with the baseline and BAU emission inventory development, OGV results are reported in hydrocarbons
(HC) while all other sectors report volatile organic compounds (VOC).
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-40. Relative Reduction Factors for Fuel Scenario 2030/B
Engine
Vessel
Overall Emission Reductions (%)
NOx
PM2.5
HC
BC
CO2
SO2
Propulsion
Bulk
11%
19%
3%
6%
3%
55%
Container
4%
10%
1%
6%
1%
45%
Passenger
0%
7%
0%
7%
0%
40%
Tanker
11%
19%
2%
6%
3%
55%
Auxiliary
Bulk
10%
20%
-4%
7%
5%
54%
Container
3%
12%
-1%
7%
2%
44%
Passenger
0%
7%
0%
7%
0%
39%
Tanker
10%
20%
-4%
7%
5%
54%
Table 6-41. Relative Reduction Factors for Scenarios 2050/A and 2050/B
Engine
Vessel
Scenario Reductions (%)
2050/A
2050/B
Propulsion
Bulk
1.8%
5.6%
Container
1.1%
1.1%
Passenger
0.0%
0.0%
Tanker
1.8%
5.7%
Auxiliary
Bulk
2.7%
8.5%
Container
1.7%
1.7%
Passenger
0.0%
0.0%
Tanker
2.7%
8.5%
See Appendix C for further details on the methodology and assumptions used to develop RRFs for these
scenarios.
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Section 6: Analysis of Emission Reduction Scenarios
6.6.1.2. Result Summary
Table 6-42 shows the total emission reductions of the 2020 and 2030 Fuel Change scenarios for
propulsion engines.
Table 6-42. Total Fuel Change Emission Reductions from Propulsion Engines
Scenario
Ship Type
Combined Emission Reductions (Tons per Year)
NOx
PM2.5
HC
BC
C02
SO2
2020/A
Bulk
12.5
0.3
0.2
0.0
177
1.7
Container
15.4
0.6
0.5
0.0
187
3.1
Passenger
-
0.0
-
0.0
-
0.4
Tanker
18.1
0.5
0.3
0.0
264
2.5
Totals
46.0
1.4
1.0
0.0
628
7.7
2020/B
Bulk
62.5
1.3
1.0
0.0
885
5.5
Container
77.1
2.3
2.3
0.1
935
9.2
Passenger
-
0.1
-
0.0
-
0.9
Tanker
90.2
1.9
1.6
0.0
1,318
8.0
Totals
229.8
5.6
4.9
0.1
3,139
23.6
2030/A
Bulk
13.5
1.1
0.5
0.0
486
8.0
Container
18.2
2.7
1.4
0.1
566
17.4
Passenger
-
0.2
-
0.0
-
2.1
Tanker
19.2
1.6
0.9
0.1
716.3
11.7
Totals
50.9
5.6
2.8
0.2
1,769
39.2
2030/B
Bulk
50.5
3.2
2.0
0.1
1,823
18.3
Container
45.6
5.9
3.4
0.2
1,416
35.6
Passenger
-
0.3
-
0.0
-
4.3
Tanker
71.9
4.8
3.3
0.1
2,686
26.7
Totals
168.0
14.2
8.7
0.4
5,925
85.0
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-43 shows the total emission reductions of the 2020 and 2030 Fuel Change scenarios for auxiliary
engines.
Table 6-43. Total Fuel Change Emission Reductions from Auxiliary Engines
Scenario
Ship Type
Combined Emission Reductions (Tons per Year)
NOx
PM2.5
HC
BC
CO2
SO2
2020/A
Bulk
63.5
2.6
-0.9
0.1
2,026
21.7
Container
52.9
3.2
-0.7
0.1
1,677
32.9
Passenger
-
2.2
-
0.1
-
29.4
Tanker
124.4
5.1
-1.7
0.2
4,012
43
Totals
240.9
13.0
-3.3
0.5
7,714
127.1
2020/B
Bulk
317.7
8.7
-4.3
0.1
10,130
54.4
Container
264.7
9.4
-3.6
0.3
8,383
74.9
Passenger
-
5.5
-
0.3
-
73.6
Tanker
622.0
17.3
-8.6
0.3
20,059
107.7
Totals
1,204.3
40.9
-16.5
1.0
38,572
310.5
2030/A
Bulk
65.9
8.9
-2.4
0.3
5,573
84.6
Container
59.7
12.9
-2.1
0.6
5,012
143.2
Passenger
-
9.3
-
0.6
-
127.7
Tanker
128.7
17.5
-4.7
0.6
10,999
167
Totals
254.3
48.5
-9.2
2.1
21,584
522.4
2030/B
Bulk
247.2
19.9
-8.9
0.4
20,897
137
Container
149.3
20.7
-5.4
0.8
12,530
201.4
Passenger
-
12.4
-
0.7
-
170.3
Tanker
482.6
39.2
-17.6
0.8
41,247
270.4
Totals
879.1
92.1
-31.9
2.7
74,675
779.1
Table 6-44 shows total emission reductions for 2050 Fuel Change scenarios for propulsion and auxiliary
engines.
Table 6-44. 2050 Total Fuel Change Emission Reductions
Ship Type
CO2 Tons per Year
2050/A
2050/B
Propulsion
Auxiliary
Propulsion
Auxiliary
Bulk
1,860
21,370
5,811
66,782
Container
3,273
28,325
3,273
28,325
Passenger
-
-
-
-
Tanker
2,667
41,839
8,335
130,746
Totals
7,799
91,534
17,419
225,853
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-45 shows percent reductions for each Fuel Change scenario when compared with the BAU levels
for propulsion and auxiliary engines, respectively.
Table 6-45. Percent Reductions for Fuel Change Scenarios201
Scenario
Engine
Emission Reductions Relative to Propulsion/Auxiliary BAU Emissions
NOx
PM2.5
HC
BC
CO2
SO2
2020/A
Propulsion
1%
2%
0%
1%
0%
6%
Auxiliary
1%
3%
-0%
2%
0%
10%
2020/B
Propulsion
6%
7%
1%
2%
2%
18%
Auxiliary
5%
8%
-1%
3%
2%
24%
2030/A
Propulsion
2%
5%
0%
3%
1%
21%
Auxiliary
2%
7%
-1%
5%
1%
29%
2030/B
Propulsion
6%
12%
1%
6%
2%
44%
Auxiliary
5%
13%
-2%
6%
3%
43%
2050/A
Propulsion
-
-
-
-
1%
-
Auxiliary
-
-
-
-
2%
-
2050/B
Propulsion
-
-
-
-
3%
-
Auxiliary
-
-
-
-
3%
-
6.6.2. Shore Power Strategies
As described in Section 5, shore power technology involves connecting a vessel to the electrical grid while at
berth. By using land-side power in this manner, an OGV's auxiliary engines can be turned off during the time
the shore power cables are connected, with the result being significantly reduced hoteling emissions while at
port. The Shore Power strategy scenarios are found below in Table 6-46, with the technology penetration
rates are shown for the three ship types for each scenario: container, passenger, and reefer ships.
Table 6-46. Shore Power Strategy Scenarios
Ship Type
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Container
1%
10%
5%
20%
15%
35%
Passenger
10%
20%
20%
40%
30%
60%
Reefer
1%
5%
5%
10%
10%
20%
The technology penetration values in Table 6-46 represent the percentage of installed auxiliary power
that shore power is applied to for frequent callers per ship type. Installed power was calculated for
frequent callers by ship type at each port in this national scale analysis. Installed power directly relates
to emissions for a given ship type, so by specifying the percent of installed power related to frequent
callers, the amount of eligible frequent caller emissions can be estimated. The methodology and
assumptions for calculating emission reductions for these scenarios is included below and in Appendix C.
201 As before, the very small negative percent reductions for HC Auxiliary Engines in scenario 2020/A are shown as -0%.
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Section 6: Analysis of Emission Reduction Scenarios
6.6.2.1. Determining Frequent Callers and Relative Reduction Factors
Shore Power strategy scenarios were applied only to frequent callers, due to the significant investment
that would be necessary to retrofit a vessel to accept shore power. Frequent callers were defined here
as individual vessels calling at a port a minimum number of times per year. For passenger (cruise ship)
vessels, frequent callers were defined as 5 calls or more per year, while frequent callers for container
and reefer vessel were assumed to call 6 times or more times per year. Table 6-47 shows the resulting
average percentages of frequent callers by ship type; overall, the average percentage of frequent callers
for these three ship types was 53% for this assessment. See Appendix C for a more detailed explanation
of how these percentages were determined.
Table 6-47. Average Percent of Frequent Callers, by Ship Type
Ship Type
% Frequent Caller
Container
56%
Passenger
96%
Reefer
72%
Although there are C02 emissions generated from the power plant supplying electricity to the ship,
these are generally less than those generated by the auxiliary engines. Similarly, conventional power
plants emit criteria air pollutants, thus shore power would be responsible for additional emissions at the
location of the power plant. Consistent with ARB's shore power regulation,202 shore power was applied
to container, passenger, and reefer ships that stop at the ports in this assessment.
EPA assumed approximately 2 hours to connect and disconnect cables during a call. Thus, the strategy's
effectiveness is based upon the number of hours connected versus the total hoteling time. Average
hoteling times by vessel type were used to calculate effectiveness by ship type, and then those values
were applied to all ports. The same share of installed power by ship type by port was also applied for all
future years. Shore power effectiveness is the number of hours connected divided by total average
hoteling time. The number of hours connected is calculated as the total average hoteling time minus 2
hours. Table 6-48 shows per call effectiveness for shore power by ship type, considering only emissions
from the vessels themselves.
Table 6-48. Shore Power Effectiveness for Vessel Emissions Only, per call
Ship Type
Average Hoteling Time (hrs)
Shore Power Reduction (%)
Container
30.7
93%
Passenger
10.1
80%
Reefer
64.3
97%
202 CARB, Airborne Toxic Control Measure for Auxiliary Diesel Engines Operated on Ocean-Going Vessels At- Berth in a California
Port, Final Regulation Order, 2010. Available at: http://www.arb.ca.eov/ports/shorepower/finalreeulation.pdf.
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Section 6: Analysis of Emission Reduction Scenarios
Emission reductions for each ship type at the port are calculated as the BAU emissions times the RRF
where RRF is defined as:
RRF = FC x PR x Eff	Eq. 6-3
Where
RRF = is the relative reduction factor,
FC = is the percent of installed power for frequent callers,
PR = is the technology penetration levels (Table 6-46), and
Eff = is the emission reduction effectiveness (Table 6-48).
Since the proportion of frequent callers by ship type vary by port, relative reduction factors are not
presented here. See Appendix C for more details.
In addition to vessel emissions, C02 and criteria air pollutant emissions were assumed to be generated
by the power plants providing the shore power. While these plants would typically be outside a port's
footprint, their emissions were considered here because the emissions result from producing electricity
used as shore power by the ships. Emission factors for electricity generation are shown in Table 6-49.
Table 6-49. Power Plant Emission Factors at plug (g/kWh)
Year
NOx
PMio
PM2.5
HC
BC
C02
SO2
2020
0.119
0.037
0.015
0.004
0.001
489
0.67
2030
0.124
0.040
0.016
0.005
0.001
478
0.633
2050
-
-
-
-
-
460
-
Please note that the Shore Power scenario analysis accounted in the BAU inventory for two ports where
shore power is currently being implemented or is sufficiently planned to occur in the future. In those
cases, the BAU emissions inventories were revised to account for this technology and any associated
impacts; no double counting of strategies occurred for applicable years.
6.6.2.2. Result Summary
The results from the Shore Power strategy scenarios are presented below in Tables 6-50 and 6-51. Table
6-50 presents the total emissions reductions of the Shore Power strategy scenarios for 2020 and 2030.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-50. Total Shore Power Emission Reductions for 2020 and 2030 Scenarios
Scenario
Ship Type
Auxiliary Engine Emission Reductions (Tons per Year)
Power Plant Emissions from Shore Power (Tons per Year)
NOx
PM2.5
HC
BC
co2
so2
NOx
PM2.5
HC
BC
co2
so2
2020/A
Container
27.2
0.5
1.3
0.0
2,161
1.3
-0.4
0.0
0.0
0.0
-1,531
-2.1
Passenger
430.1
7.3
17.4
0.4
29,978
18.4
-5.0
-0.5
-0.2
0.0
-21,230
-29.1
Reefer
3.0
0.1
0.1
0.0
220
0.1
0.0
0.0
0.0
0.0
-156
-0.2
Totals
460.3
7.9
18.7
0.5
32,359
19.9
-5.4
-0.6
-0.2
-0.1
-22,916
-31.4
2020/B
Container
272.3
5.3
12.5
0.3
21,612
13.3
-3.8
-0.4
-0.1
0.0
-15,305
-21.0
Passenger
866.8
14.7
35.0
0.9
60,404
37.1
-10.1
-1.0
-0.4
-0.1
-42,777
-58.6
Reefer
15.0
0.3
0.6
0.0
1,102
0.7
-0.2
0.0
0.0
0.0
-781
-1.1
Totals
1,154.1
20.2
48.1
1.2
83,118
51.1
-14.0
-1.4
-0.5
-0.1
-58,863
-80.7
2030/A
Container
95.4
3.9
9.3
0.2
16,076
9.9
-2.9
-0.3
-0.1
0.0
-11,133
-14.7
Passenger
440.1
20.6
49.1
1.2
84,695
52.0
-14.7
-1.5
-0.6
-0.2
-58,652
-77.6
Reefer
10.1
0.4
0.9
0.0
1,581
1.0
-0.3
0.0
0.0
0.0
-1,095
-1.5
Totals
545.6
24.8
59.3
1.5
102,351
62.9
-17.9
-1.9
-0.7
-0.2
-70,879
-93.8
2030/B
Container
381.5
15.6
37.2
0.9
64,303
39.5
-11.6
-1.2
-0.5
-0.1
-44,530
-58.9
Passenger
919.4
42.9
102.4
2.6
176,789
108.6
-30.6
-3.2
-1.3
-0.3
-122,428
-162.0
Reefer
20.2
0.8
1.8
0.0
3,162
1.9
-0.6
-0.1
0.0
0.0
-2,189
-2.9
Totals
1,321.1
59.3
141.5
3.6
244,253
150.0
-42.8
-4.4
-1.8
-0.5
-169,148
-223.8
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-51 presents the resulting emission reductions for 2050 Shore Power scenarios.
Table 6-51. Total Shore Power C02 Emission Reductions for 2050 Scenarios (Tons per Year)
Ship Type
2050A
2050/B
Auxiliary
Power Plant
Auxiliary
Power Plant
Container
108,073
-71,915
252,170
-167,803
Passenger
262,863
-174,918
545,468
-362,973
Reefer
6,621
-4,406
13,242
-8,811
Totals
377,557
-251,239
810,880
-539,588
Table 6-52 shows the percent reductions for Shore Power scenarios relative to the BAU emission
inventories for frequent caller hoteling emissions.
Table 6-52. Percent Reductions for Shore Power Scenarios
Scenario
Engine
Percent Reductions Relative to BAU Frequent Caller Hoteling Emissions
NOx
PM2.5
HC
BC
CO2
SO2
2020/A
Auxiliary
4%
3%
3%
3%
3%
3%
Power Plant
0%
0%
0%
0%
-2%
-5%
Net
4%
3%
3%
3%
1%
-2%
2020/B
Auxiliary
9%
8%
8%
8%
8%
8%
Power Plant
0%
-1%
0%
-1%
-6%
-13%
Net
9%
8%
8%
8%
0%
-5%
2030/A
Auxiliary
7%
7%
7%
7%
7%
7%
Power Plant
0%
-1%
0%
-1%
-5%
-11%
Net
7%
7%
7%
6%
2%
-4%
2030/B
Auxiliary
16%
17%
17%
17%
17%
17%
Power Plant
-1%
-1%
0%
-2%
-12%
-26%
Net
16%
16%
17%
15%
5%
-9%
2050/A
Auxiliary
-
-
-
-
13%
-
Power Plant
-
-
-
-
-9%
-
Net
-
-
-
-
4%
-
2050/B
Auxiliary
-
-
-
-
28%
-
Power Plant
-
-
-
-
-19%
-
Net
-
-
-
-
10%
-
Note that in both Tables 6-51 and 6-52, power plant emissions supporting shore power are broken out
and reported separately. The net emissions impact (i.e., "Net" in the above tables) reflects the sum of
auxiliary engine reductions and power plant emissions increases. In practice, power plants that would
supply the electricity for shore power would not be expected to be located near a port or possibly even
within an applicable nonattainment or maintenance area.
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Section 6: Analysis of Emission Reduction Scenarios
6.6.3. Advanced Marine Emission Control System Strategies
Advance Marine Emission Control Systems (AMECS) also provide emission reductions while a ship is at
berth. This is accomplished by attaching a funnel over the exhaust stack of the ship and then vacuuming
ship-generated emissions through a duct to a barge mounted Emission Treatment System (ETS) where
95-99 percent of pollutants are removed. The AMECS that was assumed for this analysis was verified by
ARB in 2015.203
Table 6-53 shows the technology penetration values of the AMECS strategy scenarios as the percentage
of installed auxiliary power by ship type. The AMECS strategy scenarios were applied to non-frequent
callers only for container and tanker ships types. In addition, smaller tankers (chemical and product
ships) tend may be good candidates for AMECS since these vessels use diesel driven cargo pumps (i.e.,
the main source of tanker emissions at berth); larger tankers tend to use boilers to power steam driven
cargo pumps.
Table 6-53. AMECS Strategy Scenarios
Ship Type
2020/A
2020/B
2030/A
2030/B
Container
1%
5%
5%
10%
Tanker
1%
5%
5%
10%
6.6.3.1. Determining Non-frequent Callers and Relative Reduction Factors
The percent of installed power for non-frequent callers (less than 6 calls at a given port within a year for
container ships and tankers) by ship type at each port from 2011 Entrances and Clearances data204.
Installed power directly relates to emissions for a given ship type, so by specifying the percent of
installed power related to non-frequent callers, the amount of eligible non-frequent caller emissions can
be estimated.
Table 6-54 shows the resulting average percentages of non-frequent callers by ship type. Overall, non-
frequent callers for these ship types were 47%. See Appendix C for a more detailed explanation of how
these percentages were determined.
Table 6-54. Average Percent of Non-frequent Callers, by Ship Type
Ship Type
% Non-frequent Caller
Container
44%
Tanker
81%
203	California Air Resources Board, Executive Order AB-15-01 - Clean Air Engineering-Maritime, Inc., June 2015. Available at:
http://www.arb.ca.gov/ports/shorepower/eo/ab-15-01.pdf. The system limits auxiliary power while hoteling to a maximum
of 2,500 kW. This excludes its use on passenger ships which generate roughly 9,000 kW while hoteling. Current AMECS use
barge auxiliary engines to power the emission reduction system. Based upon the Executive Order, the needed generator load
is 166 kW.
204	U.S. Army Corps of Engineers, Vessel Entrances and Clearances. Available at:
http://www.navieationdatacenter.us/data/dataclen.htm.
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Section 6: Analysis of Emission Reduction Scenarios
Emissions from the ship auxiliaries and from the AMECS barge auxiliary generator produce emissions
during the estimated 2 hours while they are being started and shut down as well as when the system is
in place. Consistent with the ARB Executive Order, a 90 and 95% AMECS effectiveness was assumed for
NOx and PM2.5 emissions, respectively, when the system would be installed; a 95% effectiveness was
assumed to also pertain to the other pollutants modeled for OGVs. Table 6-55 shows reduction
effectiveness for the two ship types considered.
Table 6-55. AMECS Effectiveness
Ship Type
Reductions
CO2 Increase
NOx
Others3
Container
73%
78%
9%
Tanker
75%
80%
7%
a Other emissions include PM10, PM2.5, HC, S02, and TACs.
Emission reductions by ship type by port were calculated as the BAU emissions times the RRF:
RRF = NFC x PR x Eff	Eq. 6-4
Where
RRF = the relative reduction factor,
NFC = the percent of installed power for non-frequent callers,
PR = the penetration levels given, and
Eff = the emission reduction effectiveness.
Since the proportion of non-frequent callers by ship type vary by port, relative reduction factors are not
presented here. See Appendix C for more details.
6.6.3.2. Result Summary
Table 6-56 shows the total emission reductions of the AMECS strategy scenarios; Table 6-57 shows the
percent reductions relative to non-frequent caller BAU hoteling emissions.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-56. Total AMECS Emission Reductions for 2020 and 2030 Scenarios
Scenario
Ship Type
Tons per Year
NOx
PM2.5
HC
BC
CO2
SO2
2020/A
Container
15.9
0.3
0.8
0.0
-163
0.8
Tanker
43.3
0.9
2.2
0.1
-349
2.3
Totals
59.2
1.2
2.9
0.1
-512
3.1
2020/B
Container
79.6
1.6
3.9
0.1
-816
4.1
Tanker
213.3
4.4
10.6
0.3
-1,717
11.2
Totals
292.8
6.1
14.5
0.4
-2,533
15.4
2030/A
Container
56.0
2.4
5.8
0.2
-1,220
6.2
Tanker
140.2
6.2
14.8
0.4
-2,396
15.7
Totals
196.2
8.6
20.6
0.5
-3,616
21.8
2030/B
Container
112.0
4.9
11.6
0.3
-2,440
12.3
Tanker
280.3
12.4
29.6
0.7
-4,792
31.4
Totals
392.3
17.3
41.2
1.0
-7,232
43.7
Table 6-57. Percent Reductions for AMECS Scenarios
Scenario
Percent Reductions Relative to BAU Non-frequent Caller Hoteling Emissions
NOx
PM2.5
HC
BC
CO2
S02
2020/A
1%
1%
1%
1%
-0%
1%
2020/B
3%
3%
3%
3%
-0%
3%
2030/A
3%
3%
3%
3%
-0%
3%
2030/B
6%
6%
6%
6%
-1%
6%
Note that AMECS were not modeled in 2050 since there is no C02 benefit. In addition, since the original
analysis was done, another AMECS has been verified by ARB that shows reduced emissions due to the use of
Tier 4 auxiliary engines on the barge which the AMECS is mounted, in addition to lower energy demand, thus
reducing the C02 emissions.205
6.6.4.Reduced Hoteling Strategies
Improved cargo handling equipment and other efficiency measures can improve unloading and loading times
for container ships.206 Table 6-58 shows the hoteling time reductions by the scenarios analyzed.
Table 6-58. Reduced Hoteling Strategy Scenarios
Ship Type
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
Container
5%
10%
5%
10%
5%
10%
205	More information can be found at: http://www.arb.ca.gov/ports/shorepower/shorepower.htm.
206	Additional study would be necessary to determine if reduced hoteling time is a viable strategy for tanker or bulk vessels, and
therefore, other vessel types were not considered for this assessment. For example, tanker hoteling is a function of how fast
these vessels can load or unload cargo, which can be limited by several factors, including pipeline sizes.
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Section 6: Analysis of Emission Reduction Scenarios
RRFs and hoteling emissions are equal to the reduction in hoteling time. These reductions were applied
to BAU hoteling emissions for container ships at applicable ports in this national scale analysis.
6.6.4.1. Result Summary
Table 6-59 presents the total emission reductions for the Reduced Hoteling strategy scenarios.
Table 6-59. Total Reduced Hoteling Time Emission Reductions for 2020, 2030, and 2050 Scenarios
Scenario
Tons per Year
NOx
PM2.5
HC
BC
CO2
SO2
2020/A
254.0
4.9
11.7
0.3
20,161
12.4
2020/B
508.0
9.8
23.4
0.6
40,321
24.8
2030/A
178.3
7.3
17.4
0.4
18.5
30,055
2030/B
356.6
14.6
34.8
0.9
36.9
60,109
2050/A
-
-
-
-
-
67,607
2050/B
-
-
-
-
-
135,214
Table 6-60 shows the percent emission reductions for the Reduced Hoteling scenarios relative to total
hoteling time.
Table 6-60. Percent Reductions for Reduced Hoteling Scenarios
Scenario
Tons per Year
NOx
PM2.5
HC
BC
CO2
SO2
2020/A
1%
1%
1%
1%
1%
1%
2020/B
2%
2%
2%
2%
2%
2%
2030/A
1%
1%
1%
1%
1%
1%
2030/B
2%
2%
2%
2%
2%
2%
2050/A
-
-
-
-
1%
-
2050/B
-
-
-
-
3%
-
6.6.5. Summary of OGV Scenario Impacts
The complexity of the OGV strategy scenarios warrant a more detailed examination of results so that we
can understand the potential of applying modeled strategies under appropriate circumstances in
practice. Table 6-61 illustrates the potential of OGV strategies to reduce specific types of emissions
under relevant situations. This table shows the percent emission reductions relative to the following:
¦	Fuel Change Propulsion relative to total propulsion engine emissions
¦	Fuel Change Auxiliary relative to total auxiliary engine emissions
¦	Shore Power relative to frequent caller hoteling emissions
¦	Stack Bonnet relative to non-frequent caller hoteling emissions
¦	Reduced Hoteling Time relative to total hoteling emissions
Understanding the general applicability of these strategies to reducing all or a portion of OGV emissions
is critical to making decisions for state and local priorities. For example, Fuel Change scenarios were
generally applied to all propulsion or auxiliary emissions, respectively, whereas Shore Power, AMECS
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Section 6: Analysis of Emission Reduction Scenarios
and Reduced Hoteling Time scenarios were applied to only a portion of the total OGV BAU emissions for
certain vessel types and/or caller frequency.
In contrast, Table 6-62 shows a similar set of values as Table 6-61, but percent reductions are taken
relative to the entire OGV BAU inventory (i.e., including the portions of the inventory that are not
addressed by a given strategy scenario). Figure 6-9 shows the percentage reductions for NOx, PM2.5, and
C02 relative to the total OGV BAU inventory. Similar charts for other pollutants can be found in
Appendix C.
Table 6-63 shows total absolute emission reductions from the BAU case summed by scenario strategy,
and Figure 6-10 shows the tons/year reductions for NOx, PM2.5, and C02. Similar charts for other
pollutants can be found in Appendix C; no total values are shown in these charts to avoid potentially
overestimating the impact due to interaction between OGV scenarios. For all strategies, it is important
to note that the scope of this assessment focused on activity within and near the port and within the
harbor; as a result, hoteling emissions from auxiliary engines were the majority of OGV BAU emissions
with some propulsion engine emissions occurring as OGVs enter and exit the port and maneuver within
the port.
Fuel Change scenarios provide significant emission reductions of PM2.5, BC, and S02 that are beyond the
already significant reductions of EPA's ECA regulations. Significant reductions were observed in the
2020 and 2030 BAU emission inventories due to the low sulfur fuel required and penetration of cleaner
engines by 2030. The additional low sulfur fuels modeled in the Fuel Change scenarios only reduced
PM2.5, BC, and S02 emissions, while the reductions for NOx and C02 were from the LNG fuel strategy
modeled.207 For example, total relative NOx reductions from using LNG in auxiliary engines (and when
compared to the total OGV BAU inventories) produced reductions in 2020 from 1-4% and from 1-5% in
2030. For PM2.5, the most significant fuel change was for using ULSD in auxiliary engines, where total
2020 PM2.5 reductions were estimated between 2-7% and total 2030 reductions were from 6-11% from
the total OGV BAU case. Fuel changes in auxiliary engines shown here provide a much bigger effect than
for propulsion engines, since hoteling emissions are the largest portion of the OGV BAU inventories in
this assessment. Also, note that the geographic area that assumed was limited to port areas and did not
include open ocean cruise activity. If the cruise mode were included, propulsion engines would likely
provide a bigger reduction opportunity.
Shore power provides significant per vessel emission reductions for NOx, PM2.5 and C02, particularly for
passenger ships which have high auxiliary engine loads and emissions while hoteling and a high frequent
caller percentage. Because it requires upgrades to ships and shore-side port infrastructure, shore power
is most feasible for frequent calling ships, and may be cost-prohibitive for infrequent callers. Thus, the
207While exhaust C02 is lower from LNG use, the potential for increased methane emissions (not quantified here) may offset
some of the total GHG emission reductions implied from the estimated LNG C02 reduction.
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Section 6: Analysis of Emission Reduction Scenarios
largest benefits from shore power occur at terminals and ports with a high fraction of frequent callers,
usually cruise ship terminals and container terminals. However, passenger ships have the highest
auxiliary load while hoteling; the container ships have an auxiliary load that is only 15% of that for
passenger ships and reefers have an auxiliary load that is 22% of passenger ships while hoteling.
Per call, the effectiveness of AMECS at reducing emissions is comparable to shore power for both NOx
and PM2.5. However, the C02 emissions increase due to the barge auxiliary engines running for the
emission reduction equipment are significant; future technology development (including electrification)
could improve the efficiency of the technology to mitigate C02 emission increases. AMECS strategies
may be most feasible at ports and terminals with large numbers of infrequent callers where reductions
in NOx and PM2.5 are the highest priority.
Finally, the emissions benefits of reduced hoteling time were in the 1-2% range for all pollutants in most
years, which is not as significant an impact as other strategies. These results are most likely affected by
the lower level of detail used in the assessment's methodology, and therefore, further analysis would be
necessary to fully understand the true potential of increasing operational efficiency for reducing the
time that container ships spend at the dock while they are loaded or unloaded. Any strategies that
reduce hoteling time (and auxiliary engine emissions at berth) are critical to consider for improving air
quality and climate change objectives in port areas.
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-61. OGV Emission Reduction Percentages by Scenario and Strategy, Relative to Select Portions of the OGV BAU Inventory208
Scenario
Strategy
Percent Reduction from Portion of BAU
Relative to
Strategy Description
NOx
PM2.5
HC
BC
co2
so2
2020/A
Fuel Change
Propulsion
1%
2%
0%
1%
0%
6%
Propulsion
BAU
All Ships
Bulk: 10% use 500 ppm sulfur fuel; 2%
use LNG. Container: 10% use 500 ppm
sulfur fuel; 1% use LNG. Passenger: 10%
use 500 ppm sulfur fuel. Tanker: 10% use
500 ppm sulfur fuel; 2% use LNG
Fuel Change
Auxiliary
1%
3%
-0%
2%
0%
10%
Auxiliary BAU
All Ships
Bulk: 10% use ULSD; 2% use LNG.
Container: 10% use ULSD; 1% use LNG.
Passenger: 10% use ULSD. Tanker: 10%
use ULSD; 2% use LNG
Shore Power
Auxiliary
4%
3%
3%
3%
1%
-2%
Hoteling BAU
Frequent
Callers (FCs)
Shore power penetration of: Container:
1%. Passenger: 10%. Reefer: 1%
AM ECS
Auxiliary
1%
1%
1%
1%
-0%
1%
Hoteling BAU
Non-FCs
AMECS penetration of: Container: 1%.
Tanker: 1%
Reduced Hoteling
Time
Auxiliary
1%
1%
1%
1%
1%
1%
Hoteling BAU
All Ships
Container: 5% hoteling time reduction
2020/B
Fuel Change
Propulsion
6%
7%
1%
2%
2%
18%
Propulsion
BAU
All Ships
Bulk: 25% use 500 ppm sulfur fuel; 10%
use LNG. Container: 25% use 500 ppm
sulfur fuel; 5% use LNG. Passenger: 25%
use 500 ppm sulfur fuel. Tanker: 25% use
500 ppm sulfur fuel; 10% use LNG
Fuel Change
Auxiliary
5%
8%
-1%
3%
2%
24%
Auxiliary BAU
All Ships
Bulk: 20% use ULSD; 10% use LNG.
Container: 20% use ULSD; 5% use LNG.
Passenger: 20% use ULSD. Tanker: 20%
use ULSD; 10% use LNG
Shore Power
Auxiliary
9%
8%
8%
8%
2%
-5%
Hoteling BAU
Frequent
Callers
Shore power penetration of: Container:
10%. Passenger: 20%. Reefer: 5%
AM ECS
Auxiliary
3%
3%
3%
3%
-0%
3%
Hoteling BAU
Non-FCs
AMECS penetration of: Container: 5%.
Tanker: 5%
Reduced Hoteling
Time
Auxiliary
2%
2%
2%
2%
2%
2%
Hoteling BAU
All Ships
Container: 10% hoteling time reduction
208 Very small negative percent reductions are shown as -0%.
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Strategy
Percent Reduction from Portion of BAU
Relative to
Strategy Description
NOx
PM2.5
HC
BC
co2
so2











Bulk: 25% use 200 ppm sulfur fuel; 4%









Propulsion
BAU

use LNG. Container: 25% use 200 ppm

Fuel Change
Propulsion
2%
5%
0%
3%
1%
21%
All Ships
sulfur fuel; 2% use LNG. Passenger: 25%










use 200 ppm sulfur fuel. Tanker: 25% use
200 ppm sulfur fuel; 4% use LNG











Bulk: 30% use ULSD; 4% use LNG.
2030/A
Fuel Change
Auxiliary
2%
7%
-1%
5%
1%
29%
Auxiliary BAU
All Ships
Container: 30% use ULSD; 2% use LNG.
Passenger: 30% use ULSD. Tanker: 30%
use ULSD; 4% use LNG

Shore Power
Auxiliary
7%
7%
7%
6%
2%
-4%
Hoteling BAU
Frequent
Callers
Shore power penetration of: Container:
5%. Passenger: 20%. Reefer: 5%

AM ECS
Auxiliary
3%
3%
3%
3%
-0%
3%
Hoteling BAU
Non-FCs
AMECS penetration of: Container: 5%.
Tanker: 5%

Reduced Hoteling
Time
Auxiliary
1%
1%
1%
1%
1%
1%
Hoteling BAU
All Ships
Container: 5% hoteling time reduction











Bulk: 50% use 200 ppm sulfur fuel; 15%









Propulsion
BAU

use LNG. Container: 50% use 200 ppm

Fuel Change
Propulsion
6%
12%
1%
6%
2%
44%
All Ships
sulfur fuel; 5% use LNG. Passenger: 50%










use 200 ppm sulfur fuel. Tanker: 50% use
200 ppm sulfur fuel; 15% use LNG











Bulk: 40% use ULSD; 15% use LNG.
2030/B
Fuel Change
Auxiliary
5%
13%
-2%
6%
3%
43%
Auxiliary BAU
All Ships
Container: 40% use ULSD; 5% use LNG.
Passenger: 40% use ULSD. Tanker: 40%
use ULSD; 15% use LNG

Shore Power
Auxiliary
16%
16%
17%
15%
5%
-9%
Hoteling BAU
Frequent
Callers
Shore power penetration of: Container:
20%. Passenger: 40%. Reefer: 10%

AM ECS
Auxiliary
6%
6%
6%
6%
-1%
6%
Hoteling BAU
Non-FCs
AMECS penetration of: Container: 10%.
Tanker: 10%

Reduced Hoteling
Time
Auxiliary
2%
2%
2%
2%
2%
2%
Hoteling BAU
All Ships
Container: 10% hoteling time reduction

Fuel Change
Propulsion
-
-
-
-
1%
-
Propulsion
BAU
All Ships
Bulk: 8% use LNG. Container: 5% use
LNG. Tanker: 8% use LNG
2050/A
Fuel Change
Auxiliary
-
-
-
-
2%
-
Auxiliary BAU
All Ships
Bulk: 8% use LNG. Container: 5% use
LNG. Tanker: 8% use LNG
Shore Power
Auxiliary
-
-
-
-
4%
-
Hoteling BAU
Frequent
Callers
Shore power penetration of: Container:
15%. Passenger: 30%. Reefer: 10%

AM ECS
Auxiliary
-
-
-
-
N/A
-


N/A
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Strategy
Percent Reduction from Portion of BAU
Relative to
Strategy Description
NOx
PM2.5
HC
BC
co2
so2
Reduced Hoteling
Time
Auxiliary
-
-
-
-
1%
-
Hoteling BAU
All Ships
Container: 5% hoteling time reduction
2050/B
Fuel Change
Propulsion
-
-
-
-
3%
-
Propulsion
BAU
All Ships
Bulk: 25% use LNG. Container: 5% use
LNG. Tanker: 25% use LNG
Fuel Change
Auxiliary
-
-
-
-
4%
-
Auxiliary BAU
All Ships
Bulk: 25% use LNG. Container: 5% use
LNG. Tanker: 25% use LNG
Shore Power
Auxiliary
-
-
-
-
10%
-
Hoteling BAU
Frequent
Callers
Shore power penetration of: Container:
35%. Passenger: 60%. Reefer: 20%
AM ECS
Auxiliary
-
-
-
-
N/A
-


N/A
Reduced Hoteling
Time
Auxiliary
-
-
-
-
3%
-
Hoteling BAU
All Ships
Container: 10% hoteling time reduction
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-62. OGV Emission Reduction Percentages by Scenario and Strategy, Relative to the Total OGV BAU Inventory209
Scenario
Strategy
Percent Reduction from Total BAU
Strategy Description
NOx
PM2.5
HC
BC
co2
so2
2020/A
Fuel Change
Propulsion
0%
0%
0%
0%
0%
1%
Bulk: 10% use 500 ppm sulfur fuel; 2% use LNG. Container: 10% use 500 ppm
sulfur fuel; 1% use LNG. Passenger: 10% use 500 ppm sulfur fuel. Tanker: 10%
use 500 ppm sulfur fuel; 2% use LNG
Fuel Change
Auxiliary
1%
2%
-0%
1%
0%
9%
Bulk: 10% use ULSD; 2% use LNG. Container: 10% use ULSD; 1% use LNG.
Passenger: 10% use ULSD. Tanker: 10% use ULSD; 2% use LNG
Shore Power
Auxiliary
2%
1%
1%
1%
0%
-1%
Shore power penetration of: Container: 1%. Passenger: 10%. Reefer: 1%
AM ECS
Auxiliary
0%
0%
0%
0%
0%
0%
AMECS penetration of: Container: 1%. Tanker: 1%
Reduced Hoteling
Time
Auxiliary
1%
1%
1%
1%
1%
1%
Container: 5% hoteling time reduction
2020/B
Fuel Change
Propulsion
1%
1%
0%
0%
0%
2%
Bulk: 25% use 500 ppm sulfur fuel; 10% use LNG. Container: 25% use 500 ppm
sulfur fuel; 5% use LNG. Passenger: 25% use 500 ppm sulfur fuel. Tanker: 25%
use 500 ppm sulfur fuel; 10% use LNG
Fuel Change
Auxiliary
4%
7%
-1%
3%
1%
22%
Bulk: 20% use ULSD; 10% use LNG. Container: 20% use ULSD; 5% use LNG.
Passenger: 20% use ULSD. Tanker: 20% use ULSD; 10% use LNG
Shore Power
Auxiliary
4%
3%
3%
3%
1%
-2%
Shore power penetration of: Container: 10%. Passenger: 20%. Reefer: 5%
AM ECS
Auxiliary
1%
1%
1%
1%
-0%
1%
AMECS penetration of: Container: 5%. Tanker: 5%
Reduced Hoteling
Time
Auxiliary
2%
2%
1%
2%
1%
2%
Container: 10% hoteling time reduction
2030/A
Fuel Change
Propulsion
0%
1%
0%
0%
0%
2%
Bulk: 25% use 200 ppm sulfur fuel; 4% use LNG. Container: 25% use 200 ppm
sulfur fuel; 2% use LNG. Passenger: 25% use 200 ppm sulfur fuel. Tanker: 25%
use 200 ppm sulfur fuel; 4% use LNG
Fuel Change
Auxiliary
1%
6%
-0%
4%
0%
26%
Bulk: 30% use ULSD; 4% use LNG. Container: 30% use ULSD; 2% use LNG.
Passenger: 30% use ULSD. Tanker: 30% use ULSD; 4% use LNG
Shore Power
Auxiliary
3%
3%
2%
3%
1%
-2%
Shore power penetration of: Container: 5%. Passenger: 20%. Reefer: 5%
AM ECS
Auxiliary
1%
1%
1%
1%
-0%
1%
AMECS penetration of: Container: 5%. Tanker: 5%
Reduced Hoteling
Time
Auxiliary
1%
1%
1%
1%
1%
1%
Container: 5% hoteling time reduction
209 Very small negative percent reductions are shown as -0%.
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Strategy
Percent Reduction from Total BAU
Strategy Description
NOx
PM2.5
HC
BC
co2
so2
2030/B
Fuel Change
Propulsion
1%
2%
0%
1%
0%
4%
Bulk: 50% use 200 ppm sulfur fuel; 15% use LNG. Container: 50% use 200 ppm
sulfur fuel; 5% use LNG. Passenger: 50% use 200 ppm sulfur fuel. Tanker: 50%
use 200 ppm sulfur fuel; 15% use LNG
Fuel Change
Auxiliary
5%
11%
-1%
5%
1%
39%
Bulk: 40% use ULSD; 15% use LNG. Container: 40% use ULSD; 5% use LNG.
Passenger: 40% use ULSD. Tanker: 40% use ULSD; 15% use LNG
Shore Power
Auxiliary
7%
7%
6%
6%
1%
-4%
Shore power penetration of: Container: 20%. Passenger: 40%. Reefer: 10%
AM ECS
Auxiliary
2%
2%
2%
2%
-0%
2%
AMECS penetration of: Container: 10%. Tanker: 10%
Reduced Hoteling
Time
Auxiliary
2%
2%
1%
2%
1%
2%
Container: 10% hoteling time reduction
2050/A
Fuel Change
Propulsion
-
-
-
-
0%
-
Bulk: 8% use LNG. Container: 5% use LNG. Tanker: 8% use LNG
Fuel Change
Auxiliary
-
-
-
-
1%
-
Bulk: 8% use LNG. Container: 5% use LNG. Tanker: 8% use LNG
Shore Power
Auxiliary
-
-
-
-
2%
-
Shore power penetration of: Container: 15%. Passenger: 30%. Reefer: 10%
AM ECS
Auxiliary
-
-
-
-
N/A
-
N/A
Reduced Hoteling
Time
Auxiliary
-
-
-
-
1%
-
Container: 5% hoteling time reduction
2050/B
Fuel Change
Propulsion
-
-
-
-
0%
-
Bulk: 25% use LNG. Container: 5% use LNG. Tanker: 25% use LNG
Fuel Change
Auxiliary
-
-
-
-
3%
-
Bulk: 25% use LNG. Container: 5% use LNG. Tanker: 25% use LNG
Shore Power
Auxiliary
-
-
-
-
4%
-
Shore power penetration of: Container: 35%. Passenger: 60%. Reefer: 20%
AM ECS
Auxiliary
-
-
-
-
N/A
-
N/A
Reduced Hoteling
Time
Auxiliary
-
-
-
-
2%
-
Container: 10% hoteling time reduction
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-9. OGV Emission Percent Reductions by Scenario and Strategy for Selected Pollutants, Relative to the Total OGV BAU Inventory2
NCL
PM
2.5
D
<
CO
E
o
-a
a>
cc
8%
7%
6%
5%
4%
3%
2%
1%
0%











1

11
tl
1
ll
II1
2020/A
2020/B
2030/A
1.1
2030/B
-a
ai
cc
12%
10%
8%
6%
4%
2%
0%
I ¦¦ ilil ilnLJ
2020/A	2020/B	2030/A	2030/B
4.5%
D	4.0%
ai	3.5%
|	3.0%
^	2.5%
•2	2.0%
|	1-5%
a 1.0%
^ 0.5%
0.0%
CO-






.1
I AM ECS
I Fuel Change (Auxiliary)
I Fuel Change (Propulsion)
I Reduced Hoteling Time
Shore Power
2020/A
2020/B
2030/A
2030/B
2050/A
2050/B
210 Bars are omitted where no emission reductions were estimated, due to a strategy not being applicable for a specific pollutant or due to a strategy increasing emissions.
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Table 6-63. OGV Emission Reduction Summary by Scenario and Strategy, Tons per Year
Scenario
Strategy
Tons per Year
Strategy Description
NOx
PM2.5
HC
BC
co2
so2
2020/A
Fuel Change
Propulsion
46.0
1.4
1.0
0.0
628
7.7
Bulk: 10% use 500 ppm sulfur fuel; 2% use LNG. Container: 10% use
500 ppm sulfur fuel; 1% use LNG. Passenger: 10% use 500 ppm sulfur
fuel. Tanker: 10% use 500 ppm sulfur fuel; 2% use LNG
Fuel Change
Auxiliary
240.9
13.0
-3.3
0.5
7,714
127.1
Bulk: 10% use ULSD; 2% use LNG. Container: 10% use ULSD; 1% use
LNG. Passenger: 10% use ULSD. Tanker: 10% use ULSD; 2% use LNG
Shore Power
Auxiliary
454.9
7.4
18.5
0.4
9,443
-11.5
Shore power penetration of: Container: 1%. Passenger: 10%. Reefer:
1%
AM ECS
Auxiliary
59.2
1.2
2.9
0.1
-512
3.1
AMECS penetration of: Container: 1%. Tanker: 1%
Reduced Hoteling
Time
Auxiliary
254.0
4.9
11.7
0.3
20,160
12.4
Container: 5% hoteling time reduction
2020/B
Fuel Change
Propulsion
229.8
5.6
4.8
0.1
3,139
23.6
Bulk: 25% use 500 ppm sulfur fuel; 10% use LNG. Container: 25% use
500 ppm sulfur fuel; 5% use LNG. Passenger: 25% use 500 ppm sulfur
fuel. Tanker: 25% use 500 ppm sulfur fuel; 10% use LNG
Fuel Change
Auxiliary
1,204.3
40.9
-16.5
1.0
38,572
310.5
Bulk: 20% use ULSD; 10% use LNG. Container: 20% use ULSD; 5% use
LNG. Passenger: 20% use ULSD. Tanker: 20% use ULSD; 10% use LNG

Shore Power
Auxiliary
1,140.1
18.8
47.6
1.1
24,256
-29.6
Shore power penetration of: Container: 10%. Passenger: 20%. Reefer:
5%

AM ECS
Auxiliary
292.8
6.1
14.5
0.4
-2,533
15.4
AMECS penetration of: Container: 5%. Tanker: 5%

Reduced Hoteling
Time
Auxiliary
508.0
9.8
23.4
0.6
40,321
24.8
Container: 10% hoteling time reduction
2030/A
Fuel Change
Propulsion
50.9
5.6
2.8
0.2
1,769
39.2
Bulk: 25% use 200 ppm sulfur fuel; 4% use LNG. Container: 25% use
200 ppm sulfur fuel; 2% use LNG. Passenger: 25% use 200 ppm sulfur
fuel. Tanker: 25% use 200 ppm sulfur fuel; 4% use LNG
Fuel Change
Auxiliary
254.3
48.5
-9.2
2.1
21,584
522.4
Bulk: 30% use ULSD; 4% use LNG. Container: 30% use ULSD; 2% use
LNG. Passenger: 30% use ULSD. Tanker: 30% use ULSD; 4% use LNG

Shore Power
Auxiliary
527.7
22.9
58.6
1.3
31,472
-30.9
Shore power penetration of: Container: 5%. Passenger: 20%. Reefer:
5%

AM ECS
Auxiliary
196.2
8.6
20.6
0.5
-3,616
21.8
AMECS penetration of: Container: 5%. Tanker: 5%

Reduced Hoteling
Time
Auxiliary
178.3
7.3
17.4
0.4
30,054
18.5
Container: 5% hoteling time reduction
2030/B
Fuel Change
Propulsion
168.0
14.1
8.7
0.4
5,925
84.9
Bulk: 50% use 200 ppm sulfur fuel; 15% use LNG. Container: 50% use
200 ppm sulfur fuel; 5% use LNG. Passenger: 50% use 200 ppm sulfur
fuel. Tanker: 50% use 200 ppm sulfur fuel; 15% use LNG
Fuel Change
Auxiliary
879.1
92.1
-31.9
2.7
74,675
779.1
Bulk: 40% use ULSD; 15% use LNG. Container: 40% use ULSD; 5% use
LNG. Passenger: 40% use ULSD. Tanker: 40% use ULSD; 15% use LNG
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Strategy
Tons per Year
Strategy Description
NOx
PM2.5
HC
BC
co2
so2
Shore Power
Auxiliary
1,278.3
54.9
139.7
3.1
75,105
-73.8
Shore power penetration of: Container: 20%. Passenger: 40%. Reefer:
10%
AM ECS
Auxiliary
392.3
17.3
41.2
1.0
-7,232
43.7
AMECS penetration of: Container: 10%. Tanker: 10%
Reduced Hoteling
Time
Auxiliary
356.6
14.6
34.8
0.9
60,109
36.9
Container: 10% hoteling time reduction
2050/A
Fuel Change
Propulsion
-
-
-
-
7,799
-
Bulk: 8% use LNG. Container: 5% use LNG. Tanker: 8% use LNG
Fuel Change
Auxiliary
-
-
-
-
91,534
-
Bulk: 8% use LNG. Container: 5% use LNG. Tanker: 8% use LNG

Shore Power
Auxiliary
-
-
-
-
126,318
-
Shore power penetration of: Container: 15%. Passenger: 30%. Reefer:
10%

AM ECS
Auxiliary
-
-
-
-
N/A
-
N/A

Reduced Hoteling
Time
Auxiliary
-
-
-
-
67,607
-
Container: 5% hoteling time reduction
2050/B
Fuel Change
Propulsion
-
-
-
-
17,419
-
Bulk: 25% use LNG. Container: 5% use LNG. Tanker: 25% use LNG
Fuel Change
Auxiliary
-
-
-
-
225,853
-
Bulk: 25% use LNG. Container: 5% use LNG. Tanker: 25% use LNG

Shore Power
Auxiliary
-
-
-
-
271,293
-
Shore power penetration of: Container: 35%. Passenger: 60%. Reefer:
20%

AM ECS
Auxiliary
-
-
-
-
N/A
-
N/A

Reduced Hoteling
Time
Auxiliary
-
-
-
-
135,214
-
Container: 10% hoteling time reduction
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 6: Analysis of Emission Reduction Scenarios
Figure 6-10. OGV Absolute Emission Reductions by Scenario and Strategy for Selected Pollutants
NO„
PM,
ro
ai
>-
1,400
1,200
1,000
800
600
400
200
0
.1.1 I
ll ll.
2020/A
2020/B
2030/A
ll.ll
2030/B
100
90
80
70
60
50
40
30
20
10
0
alalh Hall
2020/A	2020/B	2030/A
I
2030/B
CO,
300,000
250,000
200,000
S 150,000
I 100,000
I-
50,000
0
-50,000
2020/A
U .. Ll Ll
2020/B
2030/A
2030/B
2050/A
2050/B
I AM ECS
I Fuel Change (Auxiliary)
I Fuel Change (Propulsion)
I Reduced Hoteling Time
Shore Power
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Section 6: Analysis of Emission Reduction Scenarios
6.7. Summary of Emission Reduction Scenario Analysis
Table 6-64 shows the potential emission reductions achievable by scenario for each sector and in total.
These values were determined from the total absolute emission reductions from each sector
individually.
Table 6-64. Total Emission Reductions by Scenario and Sector211
Scenario
Sector
Tons Reduced per Year
NOx
PM2.5
voc
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
2020/A
Drayage*
1,008.2
170.5
61.3
131.3
18,661
2.30
0.50
4.60
Rail
299.0
12.5
24.0
9.6
1,193
0.90
0.20
2.00
CHE
544.0
21.4
12.0
16.5
-26
0.10
0.20
0.10
Harbor Craft
3,342.7
132.6
72.3
102.1
0
2.60
0.60
5.80
OGV*
1,055.0
27.9
32.4
1.4
37,433
-
-
-
Total
6,248.9
364.9
202.0
260.9
57,261
-
-
-
2020/B
Drayage*
2,529.6
248.4
154.9
191.3
48,150
5.00
1.20
7.90
Rail
770.7
27.8
51.8
21.4
5,817
1.90
0.40
4.30
CHE
1,275.4
45.1
29.6
34.7
37,572
0.20
0.50
0.30
Harbor Craft
8,357.2
409.4
231.0
315.2
31,424
8.20
1.80
17.90
OGV*
3,375.0
81.2
77.7
3.2
103,755
-
-
-
Total
16,307.9
811.9
545.0
565.8
226,718
-
-
-
2030/A
Drayage*
1,256.0
53.7
68.9
41.5
37,079
2.70
0.60
6.10
Rail
238.0
9.2
18.1
7.1
7,231
0.70
0.20
1.80
CHE
349.6
9.0
21.3
7.0
104,451
0.30
0.60
0.50
Harbor Craft
6,025.5
196.0
137.1
150.9
0
3.20
0.80
3.60
OGV*
1,207.4
92.9
95.0
4.5
81,263
-
-
-
Total
9,076.5
360.8
340.4
211.0
230,024
-
-
-
2030/B
Drayage*
1,586.2
84.1
81.1
65.0
138,694
3.10
0.70
6.50
Rail
1,045.5
26.4
46.5
20.3
15,513
1.80
0.40
4.10
CHE
682.5
18.0
50.8
13.9
256,815
0.60
1.40
1.30
Harbor Craft
9,069.5
258.1
189.1
198.7
32,402
3.90
1.10
3.10
OGV*
3,074.3
193.0
202.7
8.1
208,582
-
-
-
Total
15,458.0
579.6
570.2
306.0
652,006
-
-
-
2050/A
Drayage*
-
-
-
-
320,244
-
-
-
Rail
-
-
-
-
46,699
-
-
-
CHE
-
-
-
-
637,631
-
-
-
Harbor Craft
-
-
-
-
77,684
-
-
-
211 No air toxic pollutant reductions were calculated for the OGV sector as discuss elsewhere in this report, so no totals are
shown for those species.
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Section 6: Analysis of Emission Reduction Scenarios
Scenario
Sector
Tons Reduced per Year
NOx
PM2.5
VOC
BC
CO2
Acetaldehyde
Benzene
Formaldehyde
OGV*
-
-
-
-
293,258
-
-
-
Total
-
-
-
-
1,375,516
-
-
-
2050/B
Drayage*
-
-
-
-
640,487
-
-
-
Rail
-
-
-
-
95,637
-
-
-
CHE
-
-
-
-
1,065,523
-
-
-
Harbor Craft
-
-
-
-
194,210
-
-
-
OGV*
-
-
-
-
649,779
-
-
-
Total
-
-
-
-
2,645,636
-
-
-
In cases where the preceding sections showed a total reduction (CHE, harbor craft, and rail), the listed
totals accurately reflect the available potential reduction. For the other sectors (drayage and OGV212),
totals presented would generally overestimate the available reduction because they do not completely
account for interaction between the various components of a scenario. These are represented with an
asterisk in Table 6-56. The totals shown for OGVs also reflect power plant emissions related to shore
power for all pollutants.
212 Note that HC emissions from OGV are converted to VOC here for comparison to other sectors.
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Section 7: Stratified Summary of Results
7. Stratified Summary of Results
The results of this assessment were stratified in a number of ways to examine which types of strategies
may have more potential to reduce emissions at different kinds of ports. This analysis was performed
separately for the OGV and non-OGV sectors due to the nature of the various strategies applied in each
sector. This section discusses how the ports were grouped, presents charts showing the stratified
emissions reductions, and discusses observations concerning strategies that may be most effective at
reducing emissions at different kinds of ports.
7.1.	Background on Development of Strategy Scenarios
As described in Section 6, strategy scenarios were developed for each mobile source sector for the years
2020 and 2030 for all pollutants213 and for only C02 in 2050. Although the specific strategies differ
between sectors, the purpose of all scenarios are as follows:
¦	Scenario A was intended to reflect an increase in the introduction of newer technologies in port
vehicles and equipment beyond what would occur through normal fleet turnover. Operational
strategies in Scenario A reflect a reasonable increase in expected efficiency improvements for
drayage truck, rail, and OGV sectors. For the OGV sector, moderate levels of fuel switching and
other emission reduction strategies are also analyzed. All of the strategies included in Scenario A
may be supported by a moderate increase in public and private funding.
¦	Scenario B reflected a more aggressive suite of strategies as compared to Scenario A. Scenario B
would necessitate a major public and private investment to accelerate introduction of low emission
vehicles, equipment, and vessels, in addition to different fuels and other technologies. Operational
strategies in Scenario B assume further operational efficiency improvements beyond Scenario A.
The stratification analysis is based on the emission reduction results that are covered in further detail in
Section 6.
7.2.	OGV Stratification
To examine the potential impact of the various OGV strategies at different kinds of ports, the ports were
grouped by type and size. The ports were broken into three types: container, bulk, and passenger; they
were also classified in two sizes: large and small. The ports were classified as "container" if their cargo
throughput was greater than 100,000 twenty-foot equivalent units (TEUs). Container ports were further
classified as "small" if their cargo throughput was less than 1 million TEUs and "large" if it was more.
Additionally, ports were considered "bulk" if their non-container throughput was greater than 20,000
tons per year (tpy); the cutoff between large and small bulk ports was 50,000 tpy. Finally, ports were
classified as "passenger" based on a cursory review of available data. Large passenger ports were ports
with more than 750,000 annual passengers.
213 See Section 2 for more information on the pollutants that were analyzed for the different mobile source sectors.
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Section 7: Stratified Summary of Results
Each classification was made independently of the others, so that each port might fall into any number
of categories and may have different size distinctions. For example, a port could be labeled as both a
small passenger port and a large container port. However, it is important to note that these
classifications and distinctions are not official determinations, but are simply used in this analysis to
differentiate generally between the different kinds of ports included in this assessment. The distinctions
"large" and "small" only serve to compare between ports in this assessment and do not facilitate other
comparisons. The cutoff points between the two distinctions were chosen such that the large and small
ports within a classification contained a roughly equal number of ports. The grouping procedure
resulted in 14 container ports (7 large and 7 small), 14 bulk ports (7 large and 7 small), and 7 passenger
ports (4 large and 3 small). Additional information on how ports were stratified and other details for
this analysis may be found in Appendix D.
As discussed in Section 6.6, OGV scenarios covered several different types of strategies, and these were
grouped under the following categories:
¦	Fuel Change
¦	Shore Power
¦	Advanced Marine Emission Control System (AMECS)214
¦	Reduced Hoteling Time
The details of these sources and the application of these strategies are discussed in detail in Sections 5
and 6. To analyze the effectiveness of different reduction strategies at different types and sizes of ports,
the emissions reductions relevant for each strategy, scenario, year, and pollutant were summed for the
ports that fell into the relevant group. For example, the potential PM2.5 reduction from the shore power
strategy at container ports was determined by summing together all PM2.5 emission reductions from
shore power at the 14 container ports. This was done for each pollutant and scenario in both 2020 and
2030, as well as in 2050 for C02 where applicable, and for all OGV strategies included in this assessment.
Charts for NOx and PM2.5 and a discussion of observations on the types of strategies that might be more
effective at the various types and sizes of ports are included below. It is important to note that these
stratification results cannot be directly applied to an individual port. The charts and observations are
based on the aggregate emissions reductions at all of the ports in a given grouping of ports. The
discussion in this section is meant to help guide stakeholders for different kinds of ports as they consider
emissions reduction strategies; however, any strategies they select should be based on factors relevant
to a given port. For example, the number and type of OGVs and the number that make frequent calls at
a specific port must be considered as these factors would influence decisions about the use of shore
power and AMECS. Charts for the remaining pollutants are presented in Appendix D.
214 Advanced Marine Emission Control System (AMECS) is the term used by the California Air Resources Board (CARB) for this
technology, sometimes also referred to as "stack bonnets."
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Section 7: Stratified Summary of Results
7.2.1. Summary by Port Type
Figures 7-1, 7-2, and 7-3 present the relative emission reductions of NOx, PM2.5, and C02 respectively,
resulting from the strategies applied to the OGV source categories stratified by the three types of ports.
Figure 7-1. Comparing NOx Relative Reduction Potential of the OGV Sector
4%
056
J. J.

Scenario
n

I 2020/A
D
QJ

I 2020/B
3
fD

| 2030/A


1 203-0.;E
These charts show that switching the fuels that are burned in the propulsion and/or auxiliary engines
can be effective in reducing NOx and PM2.5 emissions at all types of ports. In this assessment, it was
assumed that some ships would use either a lower sulfur fuel or liquified natural gas (LNG) in their
propulsion and/or auxiliary engines. It is noteworthy that the more aggressive fuel change strategies
applied under Scenario B in both 2020 and 2030 provide about three times the emissions reductions
than Scenario A in those years. The primary differences between these scenarios are twofold: Scenario B
assumes that more ships switch to LNG as the fuel for either their propulsion or auxiliary engines and
more used ULSD (used in auxiliary engines) and lower sulfur fuels (used in propulsion engines). In sum,
the results indicate that significant NOx and PM2.5 emissions reductions can be achieved from the use of
these cleaner fuels, particularly LNG.
National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 7: Stratified Summary of Results
Figure 7-2. Comparing PM2.5 Relative Reduction Potential of the OGV Sector
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Figure 7-3. Comparing C02 Relative Reduction Potential of OGV Sector

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Section 7: Stratified Summary of Results
The charts also show that the use of shore power can result in significant emission reductions of NOx and
PM2.5. However, as discussed in Section 6, the potential emissions reductions largely depend on the number
of frequent callers at a port. Available data show that passenger and container ports have significantly more
frequent callers than bulk ports. The charts show that on a percent reduction basis passenger and container
ports would get two to three times the reductions that are projected at bulk ports. Conversely, bulk ports,
which typically have fewer frequent callers than container and passenger ports, are expected to benefit more
from the use of AMECS technology. AMECS can be applied to ships that are not frequent callers at a port
because these systems do not require modifications to the ships. AMECS is an emerging technology and
currently in limited use. It is possible that over the next several years, its use and availability could expand at
a greater rate than assumed in this assessment and even greater emissions reductions could be achieved.
It should be noted that use of shore power also results in some reductions in C02 because the ship's engines are
not being used for power while in port and power plant C02 emissions resulting from generating the needed
electricity to power the ship are less than the C02that the ship's engines would have produced. However, the
use of AMECS results in some C02 emission increases because not only are the ship's engines running but also
because the AMECS unit is mounted on a barge and the barge engines are used to power the AMECS.
The NOx and PM2 5 emissions reductions attributed to reduced hoteling are the result of improving the
efficiency of cargo handling operations associated with containers. Therefore, the results are only applicable
to container operations and are directly related to the efficiency gains that can be made at a given port.
Figure 7-4 illustrates the effectiveness of reducing emissions while OGVs are operating their auxiliary engines.
In the year 2020, switching to a cleaner fuel is expected to be effective for reducing emissions from ships
carrying bulk cargo while shore power technology was more effective at reducing NOx emissions for
passenger ships. Shore power is expected to be more effective at reducing NOx emissions for a passenger
port because passenger ships tend to call the same ports frequently, making it feasible to adapt these vessels
to use shore power. In contrast, ships carrying bulk cargo typically do not call on the same port as often in a
given year. This shows that stakeholders should consider what combination of strategies should be used to
reduce emissions for a particular port area, depending upon the type of activity at a port.
Figure 7-4. NOx Reduction Effectiveness of Different Strategies at Different Kinds of Ports (Scenario B)
Auxiliary Fuel Change	Shore Power
8% 		8%
7% 		7%
6% I	6%
5% II	5%
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National Port Strategy Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports
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Section 7: Stratified Summary of Results
7.2.2. Summary by Port Size
The results for container ports are used as an example because the results for this type of port are
similar to the results for bulk and passenger ports. As a reminder, the stratification analysis identified 7
large and 7 small container ports. Figures 7-5, 7-6, and 7-7 present the relative reductions for NOx,
PM2.5, and C02 resulting from the strategies applied to OGVs at container ports.
Figure 7-5. NOx Relative Reduction Potential of the OGV Sector for Container Ports
Scenario
I 2020/.4
| 2020/0.
I 203 0/A
I 2D3D/B
The results presented in these figures are consistent with results presented in Figures 7-1, 7-2, and 7-3.
In addition to reinforcing those results, Figures 7-5, 7-6 and 7-7 indicate that reductions from OGVs are
possible at both large and small container ports as defined in this assessment. Therefore, the types of
strategies applied to OGVs in this assessment are candidates that should be considered at both large
and small ports, while taking into account the type of port (container, bulk, and/or passenger).
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Section 7: Stratified Summary of Results
Figure 7-6. PM2.5 Relative Reduction Potential of the OGV Sector for Container Ports
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Section 7: Stratified Summary of Results
Charts presenting the results for bulk and passenger port types and the other pollutants examined in
this assessment are presented in Appendix D.
7.3. Non-OGV Stratification
In this assessment, as described in Section 6, the following strategy scenarios were applied to non-OGV
sources:
¦	Technological strategy scenarios involved accelerating fleet turnover for cargo handling equipment
(CHE) (container handlers, rubber tire gantry (RTG) cranes, and yard tractors), drayage trucks, and
harbor craft (tugs and ferries); and
¦	Operational improvement scenarios in drayage and rail.
The OGV sector strategy scenarios were highly dependent on the number and type of vessels that called
on the port, but there is no corresponding level of detail in the non-OGV sectors. The relative emission
reductions do not depend on the type or size of a port. For example, the drayage strategy scenarios did
not examine different kinds of drayage trucks that would operate at a bulk port versus a container port.
The result is that any port that has drayage truck activity similar to what was modeled in this assessment
would see the same relative reductions in emissions.
Figures 7-8, 7-9, and 7-10 present the relative emission reductions for NOx, PM2.5, and C02from the
non-OGV source categories.
Figure 7-8. NOx Relative Reduction Potential of Non-OGV Sector
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Section 7: Stratified Summary of Results
Technology strategies applied to CHE could provide NOx, PM2.5, and C02 emission reductions at some
ports, but the magnitude depends on the age and number of pieces of equipment to be repowered or
replaced. It would also depend on the types of equipment that operate at the port. In this assessment,
several types of equipment (cargo handlers, RTG cranes and yard tractors) that are common at
container ports were evaluated. Other types of ports may have other types of equipment that could be
repowered or replaced resulting in NOx, PM2.5, and/or C02 reductions.
The charts also show that accelerating the turnover of older drayage trucks to newer trucks that meet
more stringent EPA standards or that employ newer technology engines (e.g., such as plug-in hybrid
electric vehicles) can provide significant reductions of NOx and particularly of PM2.5 at ports with
significant drayage fleets. The potential for the greatest reductions is in the 2020 timeframe, as the
assessment's assumptions resulted in the removal of the very oldest trucks from the fleet in that year. In
practice, the age distribution of a given port's drayage fleet is expected to vary from the assumptions in
this assessment, with the possibility that many older drayage trucks will continue to operate at ports
well beyond the year 2020. The amount of emissions from drayage trucks that could be reduced is highly
dependent on the number and age of the drayage trucks that operate at a port. It should also be
remembered that the drayage truck emissions reductions are based on the trucks operating within 0.5
km of the port. Total emissions reductions would be greater if the total miles traveled by the drayage
trucks was considered.
Figure 7-9. PM2.5 Relative Reduction Potential of Non-OGV Sector
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169
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Section 7: Stratified Summary of Results
Technology strategies for ferries and rail can be effective at reducing NOx and PM2.5 emissions at some
ports, but the amount of emissions that can be reduced will likely vary from port to port and depend on
a number of factors such as: the number of ferries that operate at the port, the number of switcher
locomotives involved and their hours of operation during a year, the magnitude of the use of line-haul
rail to move freight from the port, and the length of the corridor used when calculating the emission
reductions from line-haul locomotives. This assessment assumed a line-haul corridor scope of within 0.5
km of the port.
These charts show that accelerating the replacement or repowering of older tugs with newer tugs or
engines that meet more stringent emissions standards results in significant emission reductions of both
NOx and PM2.5. It is likely that there is potential for significant emission reductions at most ports since
tugs are typically present at most ports for a number of purposes and tugs generally have a long useful
life that may result in older diesel fleets.
Figure 7-10. Comparing C02 Relative Reduction Potential of Non-OGV Sectors
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