syEPA
United States
Environmental Protection
Agency
EPA AND PORT EVERGLADES PARTNERSHIP:
Emission Inventories and Reduction Strategies
Office of Transportation Air Quality
EPA-420-R-18-013
June 2018
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NOTE
Eastern Research Group 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.
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TABLE OF CONTENTS
1. EXECUTIVE SUMMARY 1-1
1.1 Introduction 1-1
1.2 Partnering with Port Everglades was key to developing methods and lessons learned
that can be applied at other ports 1-3
1.3 Inventories can help benchmark port and port industry progress 1-4
1.4 Emissions are being reduced, but more can be done with available strategies 1-5
1.5 Strategies and scenarios are effective to reduce on-port emissions 1-6
1.6 Potential actions can have benefits beyond a port's boundary 1-7
1.7 Data and methods are available for developing port inventories and analyses 1-8
2. INTRODUCTION 2-1
2.1 Overview of Analysis 2-1
2.2 Overview of Methodology 2-5
2.3 Organization of Report 2-7
3.SUMMARY RESULTS 3-1
3.1 On-port Results Summary 3-1
3.2 Off-port Results Summary 3-7
4. OCEAN GOING VESSELS 4-1
4.1 Baseline and Projected Business as Usual Inventories 4-1
4.2 Emission Reduction Strategies and Scenarios 4-10
4.2.1 Reduced HotellingTime 4-13
4.2.2 At-berth Alternative Control Technology (Capture and Treat) 4-13
4.2.3 Use of Lower Sulfur Fuels 4-14
4.2.4 Use of LNG 4-15
4.2.5 Shore Power 4-15
4.3 Emission Reduction Scenario Results and Lessons Learned 4-16
5. HARBOR CRAFT 5-1
5.1 Baseline and Projected Business as Usual Inventories 5-1
5.2 Emission Reduction Strategies and Scenarios 5-5
5.3 Emission Reduction Scenario Results and Lessons Learned 5-6
6.CARGO HANDLING EQUIPMENT 6-1
6.1 Baseline and Projected Business as Usual Inventories 6-1
6.2 Emission Reduction Strategies and Scenarios 6-7
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6.2.1 Retrofit with Diesel Particulate Filters or Diesel Oxidation Catalysts 6-10
6.2.2 Replace Older Equipment 6-10
6.2.3 Use of Alternative Fuels 6-10
6.2.4 Reefer Electrification 6-11
6.3 Emission Reduction Scenario Results and Lessons Learned 6-11
7. ONROAD VEHICLES 7-1
7.1 Baseline and Projected Business as Usual Inventories 7-1
7.2 Emission Reduction Strategies and Scenarios 7-3
7.2.1 On-portTruck Idle Reduction 7-4
7.2.2 Operational Improvements 7-5
7.2.3 Truck Replacement with Cleaner Diesel Trucks and Electric Vehicles 7-5
7.3 Emission Reduction Scenario Results and Lessons Learned 7-5
8. RAIL 8-1
8.1 Baseline and Projected Business as Usual Inventories 8-1
8.2 Emission Reduction Strategies and Scenarios 8-4
8.3 Emission Reduction Scenario Results and Lessons Learned 8-6
9. OFF-PORT CORRIDOR ANALYSIS 9-1
9.1 Off-port Marine Corridor: Ocean Going Vessels 9-2
9.1.1 Baseline and Projected Business as Usual Inventories 9-3
9.1.2 Emission Reduction Strategies and Scenarios 9-14
9.1.3 Emission Reduction Scenario Results and Lessons Learned 9-17
9.2 Off-port Marine Corridor: Harbor Craft 9-21
9.2.1 Baseline and Projected Business as Usual Inventories 9-21
9.2.2 Emission Reduction Strategies and Scenarios 9-24
9.2.3 Emission Reduction Scenario Results and Lessons Learned 9-25
9.3 Off-port Truck Corridor 9-27
9.3.1 Baseline and Projected Business as Usual Inventories 9-28
9.3.2 Emission Reduction Strategies and Scenarios 9-30
9.3.3 Emission Reduction Scenario Results and Lessons Learned 9-31
9.4 Off-port Rail Corridor 9-33
9.4.1 Baseline and Projected Business as Usual Inventories 9-34
9.4.2 Emission Reduction Strategies and Scenarios 9-35
9.4.3 Emission Reduction Scenario Results and Lessons Learned 9-36
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LIST OF TABLES
Table 1-1. On-port Strategies Considered at Port Everglades 1-5
Table 2-1. Summary of Emission Reduction Strategies 2-7
Table 3-1. Summary of On-port Baseline and BAU Emissions 3-3
Table 3-2. Summary of On-port Emission Reductions 3-5
Table 3-3. Summary of Off-port Baseline and BAU Emissions 3-9
Table 3-4. Summary of Off-port Emission Reductions 3-11
Table 4-1. OGV Types 4-1
Table 4-2. Projected Growth Factors Used for Future OGV Activity 4-2
Table 4-3. Replacement Rate Assumed for Future OGV Fleet 4-3
Table 4-4. 2015 Baseline Emissions for On-port OGVs by Vessel Type 4-5
Table 4-5. 2025 BAU Emissions for On-port OGVs by Vessel Type 4-6
Table 4-6. 2035 BAU Emissions for On-port OGVs by Vessel Type 4-7
Table 4-7. 2050 BAU Emissions for On-port OGVs by Vessel Type 4-8
Table 4-8. Baseline and Projected BAU Emissions for On-port OGVs by Mode 4-9
Table 4-9. Summary of On-port Emission Reduction Scenarios for OGVs 4-11
Table 4-10. On-port OGV Emission Reduction Factors by Scenario 4-12
Table 4-11. Containership Hotelling Time by Vessel Capacity 4-13
Table 4-12. Summary of Non-Frequent Containership and Tanker Port Calls 4-14
Table 4-13. Total Reductions from BAU On-port OGV Emissions by Scenario 4-19
Table 4-14. Percent Reductions from BAU On-port OGV Emissions by Scenario 4-20
Table 5-1. Harbor Craft Vessel Types 5-1
Table 5-2. Projected Growth Factors Used for Future Harbor Craft Activity 5-2
Table 5-3. Baseline Age Distribution of Tugs and Towboats 5-2
Table 5-4. Emission Standards for Category 2 Vessels by Tier Level (g/kW-hr) 5-3
Table 5-5. 2015 Baseline and 2025 and 2035 BAU Emissions for On-port Harbor Craft 5-4
Table 5-6. On-port Harbor Craft Emission Reduction Factors by Strategy 5-5
Table 5-7. Summary of On-port Emission Reduction Scenarios for Harbor Craft 5-6
Table 5-8. Total Reductions from BAU On-port Harbor Craft Emissions by Scenario 5-7
Table 5-9. Percent Reductions from BAU On-port Harbor Craft Emissions by Scenario 5-8
Table 6-1. Projected Growth Factors Used for Future CHE Activity 6-2
Table 6-2. Baseline and Projected CHE Count by Tier Level 6-2
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Table 6-3. CHE Count and Average Tier Level by BAU Year 6-3
Table 6-4. 2015 Baseline Emissions for On-port CHE 6-4
Table 6-5. 2025 BAU Emissions for On-port CHE 6-5
Table 6-6. 2035 BAU Emissions for On-port CHE 6-6
Table 6-7. 2050 BAU Emissions for On-port CHE 6-7
Table 6-8. Summary of Emission Reduction Scenarios for On-port CHE 6-9
Table 6-9. Matching Diesel CHE to Alternative Fuel Equipment 6-11
Table 6-10. Total Reductions from BAU On-port CHE Emissions by Scenario 6-14
Table 6-11. Percent Reductions from BAU On-port CHE Emissions by Scenario 6-15
Table 7-1. Projected Growth Factors Used for Future Onroad Vehicle Activity 7-2
Table 7-2. BAU Emission Projection Factors for Onroad Vehicles 7-2
Table 7-3. Baseline and Projected BAU Emissions for On-port Onroad Vehicles 7-3
Table 7-4. Summary of On-port Emission Reduction Scenarios for Heavy-Duty Trucks 7-4
Table 7-5. Total Reductions from BAU On-port Onroad Vehicle Emissions by Scenario 7-9
Table 7-6. Percent Reductions from BAU On-port Onroad Vehicle Emissions by Scenario 7-10
Table 8-1. Baseline and BAU Projections of Container Handling at Port Everglades ICTF 8-2
Table 8-2. Tier 3 and Dual Fuel Diesel/LNG Locomotive Emission Factors 8-3
Table 8-3. Baseline and Projected BAU Emissions for On-port Rail by Mode 8-4
Table 8-4. Summary of On-port Rail Emission Reduction Scenarios 8-5
Table 8-5. Increases in ICTF Throughput from Truck-to-Rail Intermodal Shift 8-5
Table 8-6. Total Reductions from BAU On-port Onroad Truck Emissions from Truck-to-Rail
Intermodal Shift 8-5
Table 8-7. Increases from BAU On-port Rail Emissions from Truck-to-Rail Intermodal Shift 8-6
Table 8-8. On-port Emission Reductions from Truck-to-Rail Intermodal Shift 8-8
Table 8-9. Percent Reductions from BAU On-port Rail Emissions from Truck-to-Rail Intermodal
Shift 8-8
Table 9-1. Off-port Emission Reduction Strategies 9-2
Table 9-2. OGV Match Rates for Propulsion Engine Power and Vessel Speed 9-6
Table 9-3. Cruise Ship Auxiliary Engine Load Defaults (kW) 9-7
Table 9-4. Vessel Duration Profile for Off-port Marine Corridor 9-8
Table 9-5. 2015 Baseline Emissions for Off-port OGVs by Vessel Type 9-10
Table 9-6. 2025 BAU Emissions for Off-port OGVs by Vessel Type 9-11
Table 9-7. 2035 BAU Emissions for Off-port OGVs by Vessel Type 9-12
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Table 9-8. 2050 BAU Emissions for Off-port OGVs by Vessel Type 9-13
Table 9-9. Summary of Off-port Emission Reduction Scenarios for OGVs 9-15
Table 9-10. Off-port OGV Emission Reduction Factors by Scenario 9-15
Table 9-11. Summary of Off-port OGV Speeds 9-16
Table 9-12. Total Reductions from BAU Off-port OGV Emissions by Scenario 9-19
Table 9-13. Percent Reductions from BAU Off-port OGV Emissions by Scenario 9-20
Table 9-14. Harbor Craft Match Rates for Propulsion Engine Power and Vessel Speed 9-22
Table 9-15. 2015 Baseline and 2025 and 2035 BAU Emissions for Off-port Harbor Craft 9-24
Table 9-16. Off-port Harbor Craft Per Vessel Emission Reduction Factors by Strategy 9-25
Table 9-17. Summary of Off-port Emission Reduction Scenarios for Harbor Craft 9-25
Table 9-18. Total Reductions from BAU Off-port Harbor Craft Emissions by Scenario 9-27
Table 9-19. Percent Reductions from BAU Off-port Harbor Craft Emissions by Scenario 9-27
Table 9-20. Off-port Link Volumes and Source Type Fractions 9-29
Table 9-21. Baseline and Projected BAU Emissions for Off-port Onroad Vehicles 9-30
Table 9-22. Summary of Emission Reduction Scenarios for Off-port Truck Corridor 9-30
Table 9-23. Total Reductions from BAU Emissions for Off-port Truck Replacement Scenarios9-32
Table 9-24. Percent Reductions from BAU Emissions for Off-port Truck Replacement Scenarios
9-33
Table 9-25. Baseline and Projected BAU Emissions for Off-port Rail Corridor 9-35
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LIST OF FIGURES
Figure 1-1. Port Everglades Baseline and Projected BAU On-port NOx Emissions 1-4
Figure 1-2. Harbor Craft Age Distribution (Years Old) 1-4
Figure 1-3. Projected Annual NOx Emission Reductions for Selected On-port Strategies 1-6
Figure 1-4. Projected Annual PM2.5 Emission Reductions for Selected Off-port Strategies 1-7
Figure 2-1. On-port Landside Geographical Domain 2-3
Figure 3-1. On-port Baseline and BAU NOx Emissions 3-2
Figure 3-2. On-port Baseline and BAU PM2.5 Emissions 3-2
Figure 3-3. On-port Baseline and BAU (Xhe Emissions 3-2
Figure 3-4. Selected On-port NOx Reduction Strategies 3-4
Figure 3-5. Selected On-port PM2.5 Reduction Strategies 3-4
Figure 3-6. Selected On-port C02e Reduction Strategies 3-4
Figure 3-7. Off-port Baseline and BAU NOx Emissions 3-8
Figure 3-8. Off-port Baseline and BAU PM2.5 Emissions 3-8
Figure 3-9. Off-port Baseline and BAU C02e Emissions 3-9
Figure 3-10. Selected Off-port NOx Reduction Strategies 3-10
Figure 3-11. Selected Off-port PM2.5 Reduction Strategies 3-10
Figure 3-12. Selected Off-port C02e Reduction Strategies 3-10
Figure 4-1. On-port OGV NOx Reduction Strategies 4-17
Figure 4-2. On-port OGV PM2.5 Reduction Strategies 4-17
Figure 4-3. On-port OGV (Xhe Reduction Strategies 4-18
Figure 5-1. On-port Harbor Craft NOx Reduction Strategies 5-7
Figure 5-2. On-port Harbor Craft PM2.5 Reduction Strategies 5-7
Figure 6-1. On-port CHE NOx Reduction Strategies 6-12
Figure 6-2. On-port CHE PM2.5 Reduction Strategies 6-13
Figure 6-3. On-port CHE C02e Reduction Strategies 6-13
Figure 7-1. On-port Truck NOx Reduction Strategies 7-7
Figure 7-2. On-port Truck PM2.5 Reduction Strategies 7-7
Figure 7-3. On-port Truck C02e Reduction Strategies 7-8
Figure 8-1. On-port Truck-to-Rail Intermodal Shift NOx Reductions 8-7
Figure 8-2. On-port Truck-to-Rail Intermodal Shift PM2.5 Reductions 8-7
Figure 8-3. On-port Truck-to-Rail Intermodal Shift C02e Reductions 8-8
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Figure 9-1. Off-port Marine Corridor 9-3
Figure 9-2. Aggregated AIS Observations 9-4
Figure 9-3. Off-port OGV NOx Reduction Strategies 9-18
Figure 9-4. Off-port OGV PM2.5 Reduction Strategies 9-18
Figure 9-5. Off-port OGV (Xhe Reduction Strategies 9-18
Figure 9-6. Off-port Harbor Craft NOx Reduction Strategies 9-26
Figure 9-7. Off-port Harbor Craft PM2.5 Reduction Strategies 9-26
Figure 9-8. Off-port Truck Corridor 9-28
Figure 9-9. Off-port Truck NOx Reduction Strategies 9-31
Figure 9-10. Off-port Truck PM2.5 Reduction Strategies 9-32
Figure 9-11. Off-port Truck C02e Reduction Strategies 9-32
Figure 9-12. Off-port Rail Corridor 9-34
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LIST OF ACRONYMS AND ABBREVIATIONS
AAPA American Association of Port Authorities
AIS automatic identification system
ARB Air Resources Board (California)
BAU Business as Usual (scenario)
BC black carbon
BEV battery electric vehicle
CH4 methane
CHE cargo handling equipment
CNG compressed natural gas
CO carbon monoxide
CO2 carbon dioxide
CChe carbon dioxide equivalent
DOC diesel oxidation catalyst
DPF diesel particulate filter
DPM diesel particulate matter
DPM10 diesel particulate matter less than or equal to 10 microns in diameter
DPM2.5 diesel particulate matter less than or equal to 2.5 microns in diameter
ECA Emission Control Area
eGRID Emissions & Generation Resource Integrated Database
EPA U.S. Environmental Protection Agency
FECR Florida East Coast Railway
FRCC Florida Reliability Coordinating Council
g/bhp-hr grams per brake horsepower-hour
g/hp-hr grams per horsepower-hour
g/kW-hr grams per kilowatt-hour
GHG greenhouse gas
GREET Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation
hp horsepower
hr hour
ICTF Intermodal Container Transfer Facility
IHS Information Handling Services
kW kilowatt
kW-hr kilowatt-hour
LNG liquefied natural gas
LPG liquefied petroleum gas
MARPOL International Convention for the Prevention of Pollution from Ships
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MOVES
MOtor Vehicle Emissions Simulator
MY
model year
N20
nitrous oxide
NERC
North American Electric Reliability Corporation
NPSA
National Port Strategy Assessment
NOx
nitrogen oxides
OGV
ocean going vessel
PM
particulate matter
PM10
particulate matter less than or equal to 10 microns in diameter
PM2.5
particulate matter less than or equal to 2.5 microns in diameter
PPm
parts per million
RORO
roll-on roll-off (vessel)
RTG
rubber tired gantry
see
source classification code
SCR
selective catalytic reduction
S02
sulfur dioxide
TEU
twenty-foot equivalent unit
tons
short tons
U.S.
United States
ULSD
ultra-low sulfur diesel
VOC
volatile organic compound
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1. EXECUTIVE SUMMARY
1.1 Introduction
Ports are key to the United States economy and serve as gateways to transport cargo, fuel, and
passengers around the globe. Seaport cargo activity alone accounts for over a quarter of the
U.S. Gross Domestic Product and supports the employment of over 23 million Americans.1 As
part of its Ports Initiative, the U.S. Environmental Protection Agency (EPA) recognizes the
importance of working closely with ports to understand the on-the-ground, day-to-day
operations and examine the methods available to estimate associated air pollution emissions.2
In 2016, EPA's Office of Transportation and Air Quality and Broward County's Port Everglades
announced a voluntary partnership to study mobile source emissions.3 Port Everglades is the
first port to partner with EPA in this way. Port Everglades is one of the nation's leading
container ports, South Florida's main seaport for receiving petroleum products, and one of the
busiest cruise ports in the world.4 Port Everglades is located in an area that currently meets
EPA's national ambient air quality standards, and the Port is committed to environmental
stewardship now and in the future.
Port Everglades Passenger Terminal
(Source: Port Everglades)
1 American Association of Port Authorities (AAPA), http://www.aapa-
ports.org/advocatirig/content.aspx7ltem Number=21150.
2 For more information on EPA's Ports Initiative, see https://www.epa.gov/ports-initiative.
3 For further information on the EPA-Port Everglades Partnership, see https://www.epa.gov/ports-initiative/epa-
partnership-agreement-broward-countvs-port-evergiades.
4 For further information on Port Everglades, see http://www.porteverglades.net.
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Through this partnership, Port Everglades developed the 2015 Baseline Air Emissions
Inventory,5 which presents port-related emissions based on 2015 activity levels at Port
Everglades that can be used as a benchmark to measure the impact of future port changes. The
baseline inventory was also used in EPA's development of future hypothetical emission
inventories and scenarios to evaluate potential new strategies to reduce diesel emissions at
Port Everglades. Diesel engines are important components of the American economy, and
although they can be reliable and efficient, older diesel engines can emit significant amounts of
air pollution, including particulate matter (PM) and nitrogen oxides (NOx). Emission sources
that were considered in this partnership included ocean going vessels, harbor craft, cargo
handling equipment, trucks, and locomotives. EPA also evaluated the current and future
emissions and potential strategies for three "off-port" transportation corridors—a marine
corridor, truck corridor, and rail corridor—for port-related traffic outside the Port.
This partnership will help EPA provide future methods, lessons learned, and practical examples
that can be shared with other ports, related agencies, and stakeholders. The findings from this
partnership will inform EPA's update to the Port Emissions Inventory Guidance, so that other
U.S. ports, port-related industry, state and local governments, tribes, and surrounding
communities have clear technical guidance to estimate and understand emission inventories
and potential reductions from port-related strategies. This future guidance update was
included in stakeholder recommendations from the Mobile Sources Technical Review
Subcommittee of the Clean Air Act Advisory Committee.6
This report provides valuable information for Port Everglades and its stakeholders to consider
and can inform other ports of the full range of strategies available for reducing port emissions.
However, it is not a policy document and does not include policy recommendations for Port
Everglades. The emission reduction scenarios are hypothetical, and although EPA considered
several general factors in its analysis, the scenario results do not consider the logistics and costs
for implementation. Additionally, some strategies that were considered are beyond the port's
jurisdictional authority to implement.
Key findings of the Port Everglades Partnership are explored in further detail below.
5 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016
http://www, porteverglades, net/environment/air-quality/air-emissions-inventory.
6 For further information on the "Final Ports Initiative Workgroup Report: Recommendations for the U.S. EPA,"
see: https://www.epa.gov/caaac/final-ports-jnjtiatiye-workgroup-report-recommendations-us-epa.
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1.2 Partnering with Port Everglades was key to developing methods and lessons learned
that can be applied at other ports
Through the partnership, EPA and Port Everglades worked together on common environmental
objectives and shared their perspectives. Port Everglades' leadership helped EPA better
understand port operations and allowed EPA to use the Port as a technical training ground, '
The partnership also supported the Port's overall environmental mission and commitment to
environmental stewardship.8 The Port has invested significantly in cleaner equipment (such as
electric cranes), and has also supported other improvements to enhance operations (such as
reducing on-port truck bottlenecks).
Port Everglades developed the 2015 Baseline Air
Emissions Inventory that identifies and quantifies
pollutants emitted from port-related mobile
vehicles and equipment operating within the Port.
This work guided EPA's development of future
year emission reduction scenarios. Additionally,
Port Everglades leveraged existing relationships
with partners, regional and state agencies, and
others to access non-confidential data not readily
accessible to EPA,9 which allowed EPA to refine its
analysis. This general experience will inform future
EPA guidance.
PORT EVERGLADES
2015 BASELINE AIR EMISSIONS INVENTORY
P- RT EVERGLADES
Through its collaboration with Port Everglades,
EPA can cite practical examples, methods, and
lessons learned with respect to the development
of port-specific inventories and evaluation of
emission reduction strategies that can be shared
with other ports, related agencies, and
stakeholders across the United States. This
ultimately provides Port Everglades with a strong
technical foundation to make informed decisions
with more accurate data, allowing the Port to
continue to support clean air, and meet the needs of its customers, stakeholders, and
community. The lessons learned through EPA's analysis can be applied to other interested
ports.
Port Everglades 2015 Baseline Air Emissions
Inventory
(Source: Starcrest Consulting Group)
1 Neugaard, E. and Buchan, P., "Port Everglades: A Framework for Cooperation with the EPA," Journal of Ports
and Terminals, Ed. 75, Autumn 2017.
8 Port Everglades, "About Us—Mission Statement," http://www.porteverglades.net/about-us.
9 EPA did not receive any confidential business or terminal-specific information through the partnership.
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1.3 Inventories can help benchmark port and port industry progress
An emissions inventory is an important benchmark against which to measure progress and
enables informed decision making. The Port Everglades 2015 Baseline Air Emissions Inventory
was developed from detailed local mobile source activity and fleet information, including ocean
going vessels (OGVs), harbor craft, cargo handling equipment (CHE), onroad vehicles, and rail
operations. EPA used growth projections from Port Everglades' 2014 Master/Vision Plan10 and
fleet turnover rates to produce
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10 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014,
http://www.porteverglades.net/construction/master-vision-plan/master-plan-reports.
11 EPA's analysis included criteria pollutants and precursors (e.g., PM and NOx), greenhouse gases, and air toxics
(i.e., diesel PM). All pollutants were analyzed for the years 2025 and 2035, and for 2050, carbon dioxide
equivalents (COie) were analyzed. For the full set of assumptions used to generate emission inventories and
projections, see the individual sections later in this report.
12 Neugaard, E. and P. Buchan, "Port Everglades: A Framework for Cooperation with the EPA," Journal of Ports and
Terminals, Ed. 75, Autumn 2017.
1-4
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1.4 Emissions are being reduced, but more can be done with available strategies
The BAU inventories show that EPA's engine and fuel regulations, as well as emerging
commercially available technologies, are expected to reduce port-related emissions. For
example, new vehicle and equipment emission standards are already reducing NOx and PM
emission rates as older equipment is replaced at ports across the country. However, voluntarily
implementing operational strategies or accelerating equipment replacement rates, for example,
could further reduce emissions, or reduce emissions sooner. In consultation with Port
Everglades, EPA identified voluntary strategies, listed in Table 1-1, to analyze for additional
reductions beyond the BAU case.
Table 1-1. On-port Strategies Considered at Port Everglades
Sector
Strategy Descriptions
Ocean Going Vessels
• Reduced hotelling time
• At-berth alternative control technology (capture and treat)
• Lower sulfur fuels and alternative fuels such as liquefied natural gas (LNG)
• Shore power
Harbor Craft
• Engine replacement (to Tier 3) and vessel replacement (to Tier 4)
Cargo Handling Equipment
• Equipment replacement (to Tier 4) and equipment electrification
• Diesel particulate filters and oxidation catalysts
Onroad
• Truck replacement to MY2010+ and battery electric vehicles (BEVs)
• Truck idle reduction
Rail13
• Increase modal shift of cargo from truck to rail
Many of these strategies are applicable to any port, but the emission-reducing potential of a
given strategy highly depends on a port's individual characteristics. Attributes such as the
port's primary activity type and level; types of vessels, equipment, and fuels used; and the
technologies and operations utilized onsite impact the emissions reduction potential of a given
strategy. In addition to supporting environmental goals, some strategies have potential co-
benefits, such as reducing fuel usage and improving operational efficiencies that may enhance a
port's competitiveness.
13 Replacing older diesel locomotives, such as switchers, is an effective emission reduction strategy to consider.
However, at Port Everglades, the Florida East Coast Railway has already updated its line-haul locomotive fleet
to cleaner technology and has constructed the Intermodal Container Transfer Facility, which does not use
switcher locomotives, at the Port. For further general information about other rail strategies, see EPA's
National Port Strategy Assessment at: https://www.epa.gov/ports-initiative/national-port-strategy-assessment-
reducing-air-pollution-and-greenhouse-gases-us.
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1.5 Strategies and scenarios are effective to reduce on-port emissions
To evaluate the effectiveness of various strategies, EPA's analysis explored the potential of
hypothetical scenarios, applied at different levels of implementation, to reduce future year
emissions.
Figure 1-3 highlights potential NOx reductions for a selection of on-port strategies, including:
• OGVs: Use LNG in 5-10 percent of containerships
• Harbor Craft: Replace 20 percent of Tier 0 vessels with Tier 4 vessels
• CHE: Replace Tier 0 through Tier 3 equipment with Tier 4 or electric equipment
• Trucks: Limit on-port truck idling to 5 minutes per truck per visit
3.5
kH2o;
..
OGV-LNG Harbor Craft-Vessel CHE - Replacement Trucks-Idle
Replacement Reduction
Figure 1-3. Projected Annual NOx Emission Reductions for Selected On-port Strategies
This chart illustrates that significant reductions are possible from these strategies, which are
just a subset of the strategies examined in EPA's analysis for on-port emissions. A variety of
strategies are available and ports can assess which make the most sense for their specific
conditions. Note that the hypothetical scenarios14 evaluated in this study do not include
specific implementation details but assume coordination and collaboration by the various
maritime industry stakeholders.
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14 In selecting scenarios, EPA qualitatively considered several factors, such as capital costs, market barriers, and
potential for market penetration by analysis year. However, a detailed cost-benefit analysis was not conducted
for this analysis and cost per ton of pollutant reduced was not calculated.
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1.6 Potential actions can have benefits beyond a port's boundary
Ports are a nexus between transportation modes and activities that generate emissions at sea
and on land, both on the port property and on nearby transportation corridors. As part of its
analysis, EPA examined three transportation corridors to estimate emissions from port-related
vessel and vehicle activity occurring outside Port Everglades. The off-port corridors included a
marine corridor, a truck corridor, and a rail corridor.
For each corridor, EPA developed a 2015 off-port baseline inventory and projected future BAU
emissions for the same years and pollutants as the on-port analysis. Hypothetical scenarios
were also developed to examine potential strategies to reduce off-port emissions along
transportation corridors. Figure 1-4 shows potential NOx reductions in 2025 and 2035 for a
selection of off-port reduction strategies, including:
• OGVs: Have 50 percent of vessels participate in voluntary vessel speed reduction to 12
knots or less
• OGVs: Use LNG in 5-10 percent of containerships
• Trucks: Accelerate replacement of pre-2007 and pre-2010 trucks with model year 2010
or later trucks and some BEVs
4.5
4.0
3.5
3.0
.2 2.5
4->
O
-o 2.0
(u
cc
§ 1-5
E 1-0
LU
0.5
0.0
12025
12035
OGV-Speed Reduction OGV-LNG Trucks - Replacement
Figure 1-4. Projected Annual PM2.5 Emission Reductions for Selected Off-port Strategies
Quantifying mobile source emissions using local data along these types of corridors can help
stakeholders identify impacts and opportunities to reduce emissions.
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1.7 Data and methods are available for developing port inventories and analyses
This partnership provided an opportunity to
consider data and methods currently
available for developing the emission
inventories for port-related vehicle and
equipment sectors. For each sector,
inventories relied upon data describing the
emission sources, such as vessel, equipment
or vehicle type; engine type; horsepower;
age; and other parameters. Activity and
operational data, describing the amount of
time and the circumstances in which the
sources operate, were also used. These and
other data are discussed throughout the
report.
Emission estimation methods are currently
available for all land and marine emission
sources at ports. For OGVs, automatic
identification system data from the U.S. Coast
Guard were used to identify vessel movements in conjunction with Port Everglades' vessel call
records. For harbor craft, information was collected about the type of craft and activity
operating at the port. For locomotives, the Florida East Coast Railway, in consultation with Port
Everglades, provided information on its locomotive fleet and operating characteristics.
Additionally, EPA's MOtor Vehicle Emissions Simulator (i.e., MOVES2014a)15 was used to mode)
emissions from both onroad vehicles and nonroad CHE.
Partnering with Port Everglades allowed EPA to refine inventory development methods and will
inform EPA's next update of the Port Emissions Inventory Guidance. Since the release of EPA's
existing guidance in 2009,16 additional information and methods have become available. For
example, the MOVES model was not yet available when the existing guidance was issued, and
its predecessor did not have the same capabilities. Lessons learned and methods developed
from the EPA-Port Everglades partnership will be incorporated into EPA's updated guidance and
will inform future inventory development and strategy analyses across the U.S.
MOVES Jr»d Related Models
" " Emissions Models and Other
Methods to Produce Emission
Inventories
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Emissions inventory resources
15 More information on EPA's MOVES model can be found at: https://www.epa.gov/moves.
16 U.S. EPA, Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories Final Report,
April 2009, https://www.epa.gov/moves/current-methodologies-preparing-mobile-source-port-related-
emission-inventories-final-report.
1-8
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2. INTRODUCTION
2.1 Overview of Analysis
EPA conducted this analysis to develop baseline and future year emission inventories at
Broward County's Port Everglades and to evaluate available technology and operational
strategies for emission reductions. While this report provides valuable information for Port
Everglades and port stakeholders to consider, it is not a policy document and does not include
policy recommendations for Port Everglades. This work will inform EPA's future update of its
Port Emissions Inventory Guidance.
Background. Ports are key to the United States economy and serve as gateways to transport
cargo, fuel, and passengers around the globe. Seaport cargo activity alone accounts for over a
quarter of the U.S. Gross Domestic Product and supports the employment of over 23 million
Americans.17 Diesel engines are important components of the American economy, and
although they can be reliable and efficient, older diesel engines can emit significant amounts of
air pollution. There are a wide range of technological and operational strategies that can
reduce port-related emissions.
This analysis is part of EPA's broader Ports Initiative that works in collaboration with port
industry, communities, and all levels of government to improve environmental performance
and increase economic prosperity.18 In 2016, EPA released the National Port Strategy
Assessment: Reducing Air Pollution and Greenhouse Gases at U.S. Ports (NPSA). The NPSA
provides a national picture of port-related emission trends and the potential for emission
reduction strategies based on estimated emissions from a sample of 19 seaports that represent
a variety of activities and locations around the country.19
Partnership. In 2016, EPA and Broward County's Port Everglades (hereafter also referred to as
"the Port") announced a voluntary partnership to develop baseline and future year emission
inventories, and to evaluate technological and operational strategy scenarios to reduce air
pollution emissions at ports.20 Port Everglades is Florida's largest container port and one of the
busiest cruise ports in the world. The Port also receives, stores, and distributes refined
petroleum products for South Florida. While Port Everglades is located in an area that currently
meets EPA's national ambient air quality standards, the port is committed to environmental
stewardship now and in the future. Port Everglades is the first port in the U.S. to partner with
EPA in this way.
17 American Association of Port Authorities (AAPA), http://www.aapa-
ports,org/advocating/content,aspx?ltemNumber=21150.
18 For more information, see https://www.epa.gov/pprts-initiative.
19 For further information on the National Port Strategy Assessment, see https://www, epa.gov/po rts-
initiative/national-port-strategy-assessment-reducing-air-pollution-and-greenhouse-gases-us,
20 For further information on the EPA-Port Everglades Partnership Agreement, see
https://www.epa.gov/sites/production/files/2016-06/docyments/ei3a-Port Everglades-partnership-agreement-
executed.pdf.
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As part of the partnership, Port Everglades developed the Port Everglades 2015 Baseline Air
Emissions Inventory21 (hereafter referred to as the "2015 On-port Baseline Inventory"), which
presents port-related emissions based on 2015 activity levels at Port Everglades.
Using that information, as part of the partnership, EPA developed:
• Hypothetical emission inventories and reduction scenarios for Port Everglades for future
analysis years.
• Emission inventories for certain off-port mobile source corridors outside Port
Everglades.
• Documentation of methods, lessons learned, and practical examples that may be shared
with other ports, related agencies, and stakeholders.
Throughout the partnership, EPA and Port Everglades worked together on all deliverables in
addition to consulting with each other and providing technical assistance throughout the
development of the 2015 On-port Baseline Inventory and EPA's analyses.
Geographical Scope. In this report, "on-port" refers to the geographical area covered by the
2015 On-port Baseline Inventory. The on-port landside geographical scope used for the 2015
On-Port Baseline Inventory and EPA's on-port analysis is shown in Figure 2-1. "Off-port" refers
to the port-related corridors included in this analysis that extend beyond Port Everglades.
These include a marine corridor, a truck corridor, and a rail corridor. The off-port corridors are
described further in Section 9.
21 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016,
httpi//www,|3orte¥erglades,net/en¥ironment/air-guality/a[r-er!iissions-in¥entorv.
2-2
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Figure 2-1. On-port Landside Geographical Domain
22 Ibid.
2-3
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Mobile Source Sectors Analyzed. This analysis focused on the potential of strategies to reduce
emissions from diesel-powered vehicles and equipment.23 The five mobile source sectors
analyzed were:
• Ocean going vessels (OGVs): OGVs are ships with engines of 30 liters24 displacement per
cylinder or more (i.e., Category 3 engines).25 There are many kinds of OGVs; the ship
types that were considered in this analysis are described in Section 4.
• Harbor craft: Harbor craft assist in moving OGVs around the harbor, move cargo and
people around the port harbor area, and provide fuel to OGVs; they also transport crew
and supplies to offshore facilities. Harbor craft are vessels with engine displacements of
less than 30 liters per cylinder and are classified as Category 1 and 2 vessels. There are
many kinds of harbor craft; however, this analysis focused specifically on tugs and
towboats.
• Cargo handling equipment (CHE): CHE are located on-port to move cargo on and off
OGVs and harbor craft. Additionally, CHE move cargo around the port so that it can be
loaded onto trucks and rail cars. A wide selection of CHE was accounted for by this
analysis, including yard tractors, container handlers, and cranes.
• Onroad vehicles: The primary contributors to the onroad emissions inventory are heavy-
duty diesel trucks that transport cargo into and out of the port. The most common type
is the combination truck, usually configured to haul cargo containers, liquids, or
standard box trailers.
• Rail: The rail emission sources included in this analysis are line-haul locomotives, which
move cargo into and out of the Port. Rail yard, or switcher, locomotives are not used at
Port Everglades' Intermodal Container Transfer Facility (ICTF), and therefore, these
types of locomotives were not included in the 2015 On-port Baseline Inventory or EPA's
analysis.
Pollutants. Port-related emissions and reductions were estimated for several different criteria
pollutants and precursors, climate related pollutants, and air toxics. Even though Port
Everglades is located in an area that currently meets EPA's national ambient air quality
standards, this analysis evaluates all of these pollutants so that it can serve as a practical
example for ports across the U.S. that have different air quality circumstances. Criteria
pollutants include common air pollutants that are identified by the Clean Air Act, such as
particulate matter (PM) and ground-level ozone. Precursors are air pollutants that form criteria
pollutants, such as nitrogen oxides (NOx) and volatile organic compounds (VOCs), which
23 Even though the 2015 On-port Baseline Inventory includes stationary sources, such as administrative building
electrical power consumption, this analysis focuses on only mobile source emission estimates and reductions.
24 30 liters is approximately 8 gallons.
25 Note that some OGVs can have smaller Category 2 engines; however, for simplicity in this analysis, all OGVs
were assumed to have Category 3 engines.
2-4
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combine to form ground-level ozone. Climate related pollutants include greenhouse gases
(GHGs), 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 analysis:
• Criteria pollutants and precursors:
o NOx
o Particulate matter less than or equal to 10 microns (PMio)
o Particulate matter less than or equal to 2.5 microns (PM2.5)
o Sulfur dioxide (SO2)
o VOCs
• Climate related pollutants:
o Carbon dioxide equivalents (CChe)
o Black carbon (BC)
• Air toxics:
o Diesel particulate matter less than or equal to 10 microns (DPM10)
o Diesel particulate matter less than or equal to 2.5 microns (DPM2.5)
Consistent with the 2015 On-port Baseline Inventory, CChe are calculated by weighting three
GHGs by the following global warming potentials:26
• Carbon dioxide (CO2): 1
• Methane (CH4): 25
• Nitrous oxide (N2O): 298
SO2 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 SO2 emitted by these sources. SO2 emissions from OGVs were
estimated because, although these vessels are required to use low sulfur distillate fuels (up to
1000 ppm sulfur content) while operating in the North American Emission Control Area,
including operations at ports, there is a potential for additional reductions through the use of
even lower sulfur fuels.
2.2 Overview of Methodology
EPA's analysis builds on the methodology established in the 2015 On-port Baseline Inventory.
First, future year emission inventories were developed based on anticipated operational growth
26 U.S. Environmental Protection Agency, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2013, April
2015, https://www.epa.gov/sites/production/files/2016-03/documents/us-ghg-inventorv-2015-main-text.pdf.
2-5
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at Port Everglades and the expected normal replacement of older, higher-emitting equipment
with newer, lower-emitting equipment over time. Then, hypothetical emission reduction
strategy scenarios were developed in consultation with the Port and analyzed to quantify their
potential for reducing emissions. Additionally, baseline and future emission inventories as well
as the potential for additional emission reductions were explored for three off-port corridors: a
marine corridor, truck corridor, and a rail corridor.
2015 Baseline Emissions Inventory. This analysis builds on the results of the 2015 On-Port
Baseline Inventory, which includes inventories for each of the mobile source sectors described
above in Section 2.1. Because this inventory is primarily based on local activity data collected
with the support of Port Everglades, it is a strong foundation for EPA's analysis. The baseline
inventory relied on local activity data collected for the 2015 calendar year from a variety of
public and proprietary sources, including U.S. Coast Guard automatic identification system (AIS)
data, Information Handling Services' (IHS) Register of Ships, Starcrest's Vessel Boarding
Program, vessel call logs shared by the Port, and confidential surveys of terminal and facility
operational managers. Note that EPA and Port Everglades respected the privacy and
confidentiality of the terminal operators at Port Everglades, and EPA did not receive
confidential business or terminal-specific information through this partnership. For details on
the data collection and inventory development methodology, please see the 2015 On-port
Baseline Inventory.
The 2015 On-port Baseline Inventory included the same pollutants as this analysis (listed in
Section 2.1), except for BC and DPM2.5, which were added in EPA's analysis. Additionally,
carbon monoxide (CO) was included in the 2015 baseline analysis but was not included here. In
EPA's analysis, BC and DPM2.5 were calculated from the particulate matter emissions that were
included in the 2015 On-port Baseline Inventory.
Future Emission Projections. To project future emissions, Business as Usual (BAU) emission
scenarios were developed based on the most recent local information available at the time of
EPA's analysis for anticipated growth and changes at Port Everglades, as identified in the 2014
Master/Vision Plan.27 Hypothetical future emission inventories were estimated for 2025, 2035,
and 2050,28 based on the Port's anticipated growth in throughput and past fleet turnover rates.
Although these hypothetical future emission inventories are based on local information, they
are presented to illustrate EPA's analysis and are not intended to form the basis for policy
recommendations.
Reduction Strategies and Scenarios. The hypothetical emission reduction scenarios were
developed in consultation between EPA and Port Everglades, and include strategies to use
cleaner technologies and operational improvements. Table 2-1 lists the emission reduction
strategies analyzed for each mobile source sector. It should be noted that EPA's analysis
included hypothetical scenarios of potential strategies for which Port Everglades has no direct
27 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014,
http://www.porteyerglades.net/construction/master-yjsion-plan/master-plan-reports
28 Note that for 2050, only CChe inventories and reductions were quantified.
2-6
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control. The analysis methodology did not make assumptions regarding the details, logistics,
costs and/or other implications of how to apply or implement the reduction strategies nor did it
assume which entity or entities would implement each strategy. The scenarios do not consider
jurisdiction or geographical boundaries, except when determining if the emission reductions
would occur on-port or off-port. Some of the strategies considered only apply to the on-port or
off-port analysis, and some apply to both.
Table 2-1. Summary of Emission Reduction Strategies
Sector
Strategy Descriptions
OGV
• Vessel speed reduction
• Reduced hotelling time
• At-berth alternative control technology (capture and treat)
• Lower sulfur fuels and alternative fuels such as liquefied natural gas (LNG)
• Shore power
Harbor Craft
• Engine replacement (to Tier 3)
• Vessel replacement (to Tier 4)
CHE
• Equipment replacement (to Tier 4) and equipment electrification
• Diesel particulate filters and oxidation catalysts
Onroad
• Truck replacement to MY2010+ and battery electric vehicles (BEVs)
• Truck idle reduction
Rail
• Increase modal shift of cargo from truck to rail
In most cases, high and low implementation scenarios were developed for each strategy. For
strategies involving new technologies, both the high and low scenarios would involve
substantial investments in new vehicles, equipment, vessels, and/or fuels, with the high
scenario assuming a larger investment than the low scenario. For the operational strategies
that go above and beyond the improvements continuously being sought at Port Everglades, the
high scenario represents a greater achievement in operational improvements than the low
scenario. In selecting scenarios, EPA qualitatively considered several factors, such as capital
costs, market barriers, and potential for market penetration. However, a detailed cost-benefit
analysis was not conducted for this analysis and cost per ton of pollutant reduced was not
calculated. Please note that totals in tables contained in this report may not equal the
aggregated displayed totals due to rounding.
2.3 Organization of Report
The remainder of the report is organized as follows:
Section 3—Summary Results provides an overview of the baseline emissions, projected BAU
emissions, and potential emission reductions for the mobile source categories operating on-
port and in off-port corridors.
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Sections 4 through 8 present on-port results for the five source categories examined. Each
section summarizes the on-port baseline emissions for 2015; presents the methodology and
results for projecting BAU emissions for 2025, 2035, and 2050; and evaluates the potential for
various emission reduction strategies. The considered source categories are presented in the
following order:
• OGVs (Section 4)
• Harbor craft (Section 5)
• CHE (Section 6)
• Onroad vehicles (Section 7)
• Rail (Section 8)
Section 9—Off-port Corridor Analysis provides off-port results for the source categories that
operate in off-port marine, truck, and rail corridors. This section includes a description of how
the off-port corridors were selected, the methodology and results for the baseline and
projected off-port emission inventories, and the potential for various emission reduction
strategies. Please note that CHE do not operate in the off-port corridors, and thus are not
relevant for the off-port analysis.
2-8
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3. SUMMARY RESULTS
3.1 On-port Results Summary
This section summarizes the results of the components of EPA's analysis of mobile source
emissions at Port Everglades. The on-port mobile source sectors analyzed include ocean going
vessels (OGVs), harbor craft, cargo handling equipment (CHE), onroad vehicles, and rail.
On-port 2015 baseline emissions and Business as Usual (BAU) emission projections for the years
2025, 2035, and 2050 for NOx, PM2.5, and CChe emissions are summarized in Figure 3-1, Figure
3-2, and Figure 3-3, respectively. As seen in the figures, OGVs are the biggest source of
emissions and are expected to remain so in future years despite the Emission Control Area
(ECA) emission requirements.29 Rail emissions are not visible in the figures as they are orders of
magnitude smaller than emissions for the other sectors.
Baseline emissions and BAU projections are presented in Table 3-1 for all pollutants considered
in EPA's analysis. Note that SO2 was only evaluated for OGVs. Additionally, for the 2050
analysis, only C02e inventories and reductions were quantified. Baseline and projected
inventories like these are useful to examine emission trends by source, which may help ports
identify potential emission reduction opportunities and prioritize future investment or
operational changes to reduce emissions.
Selected on-port NOx, PM2.5, and C02e emission reduction strategies are highlighted in Figure
3-4, Figure 3-5, and Figure 3-6, respectively. These figures show that a variety of strategies are
available and ports can assess which make the most sense for their specific conditions.
However, note that cost per ton of pollutant reduced was not calculated as part of this analysis,
which is an important part of cost-benefit analysis that would inform strategy selection.
A summary of results of all analyzed on-port strategies and scenarios for each source category
is presented in Table 3-2. This summary only includes NOx, PM2.5, and C02e; however, on-port
results for all pollutants are included along with methodology details in Sections 4 through 8.
Increased use of natural gas-powered OGVs is projected to decrease NOx and PM2.5 emissions
through 2035 and C02e emissions through 2050. Accelerated replacement of harbor craft and
CHE has the potential to reduce emissions above what is projected in the BAU case. Idle
reduction may also facilitate significant reductions in truck emissions.
As described in later sections, some strategies and scenarios were not evaluated for all three
future years of 2025, 2035, and 2050, and some were not evaluated for all pollutants (i.e., some
strategies only targeted a subset of the pollutants). EPA's analysis also includes percent
reductions from the BAU for each strategy scenario. See subsequent sections for details on all
emission inventories, strategy scenarios, and results.
29 U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from
Category 3 Marine Diesel Engines, EPA-420-R-09-019, December 2009,
https://nepis.epa.gov/Exe/ZyPU RLcgi?Dockev=P1005ZGH.txt.
3-1
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2,500
S 2,000
£
— 1,500
tn
c
o
¦| 1,000
3
£
£
<
500
12015
12025
12035
OGV Harbor Craft CHE Onroad Rail
Figure 3-1. On-port Baseline and BAU NOx Emissions
70
15 60
(u
s-
50
40
C
0
"S 30
E
LU
« 20
1 10
12015
12025
12035
I
OGV Harbor Craft CHE Onroad Rail
Figure 3-2. On-port Baseline and BAU PM2.5 Emissions
250,000
« 200,000
c
— 150,000
tn
c
o
¦| 100,000
(O
i 50,000
c
<
... rill ....
OGV Harbor Craft CHE Onroad Rail
Figure 3-3. On-port Baseline and BAU C02e Emissions
12015
12025
12035
2050
3-2
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Table 3-1. Summary of On-port Baseline and BAU Emissions
Year
Mode
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02ea
201530
OGV
2,000.82
43.73
41.07
37.95
35.66
31.64
88.45
73.44
139,046.22
Harbor
Craft
159
4.36
4.01
4.36
4.01
3.09
a
6.09
10,457.61
CHE
218.16
13.82
13.38
13.82
13.38
4.66
--
24.81
27,259.02
Onroad
54.04
3.96
3.65
3.94
3.64
1.69
--
5.99
11,887.31
Rail
1.41
0.02
0.02
0.02
0.02
0.01
--
0.04
142.54
Total
2,433.43
65.89
62.13
60.09
56.71
41.09
--
110.37
188,792.70
2025
OGV
2,065.47
58.18
54.67
51.07
47.99
42.08
116.56
98.24
183,165.83
Harbor
Craft
168.66
4.57
4.20
4.57
4.20
3.23
--
6.69
12,496.85
CHE
120.61
7.14
6.93
7.14
6.93
2.42
--
13.83
40,704.41
Onroad
24.32
1.42
1.31
1.41
1.30
0.61
--
2.25
14,777.72
Rail
1.57
0.03
0.03
0.03
0.03
0.02
--
0.36
180.17
Total
2,380.63
71.34
67.14
64.22
60.45
48.36
--
121.37
251,324.98
2035
OGV
1,753.08
67.02
62.98
58.75
55.16
48.47
134.23
113.7
210,972.08
Harbor
Craft
284.29
7.59
6.98
7.59
6.98
5.37
--
11.78
24,115.26
CHE
78.42
2.60
2.52
2.60
2.52
0.88
--
13.73
49,929.53
Onroad
15.54
0.56
0.52
0.55
0.51
0.07
--
1.16
17,558.34
Rail
1.51
0.04
0.04
0.04
0.04
0.03
--
0.82
205.91
Total
2,132.84
77.81
73.04
69.53
65.21
54.82
--
141.19
302,781.12
2050
OGV
--
--
--
--
--
--
--
--
233,860.74
Harbor
Craft
--
--
--
--
--
--
--
--
--
CHE
--
--
--
--
--
--
--
--
60,521.19
Onroad
--
--
--
--
--
--
--
--
20,753.28
Rail
--
--
--
--
--
--
--
--
212.72
Total
--
--
--
--
--
--
--
--
--
a A double dash represents a value that was not calculated as part of this analysis.
30 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
3-3
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70
o 50
C 40
Iso
¦a
(D
* 20
o
8 10
o
£ 0.5
£
m 0.0
ll
12025
12035
OGV - LNG (High) Harbor Craft - Vessel CHE - Replacement Trucks-Idle
Replacement (High) (High) Reduction (High)
Figure 3-4. Selected On-port NOx Reduction Strategies
_ 3.5
ro
ji. 3.0
tn
0 2.5
-M
1 2'°
| 1.5
1 ¦ I ¦ 2035
* 1.0
.1
12025
OGV - LNG (High) Harbor Craft - Vessel CHE - Replacement Trucks-Idle
Replacement (High) (High) Reduction (High)
Figure 3-5. Selected On-port PM2.5 Reduction Strategies
___ 50,000
S 45,000
> 40,000
35,000
£ 30,000
o ¦ 2025
¦5 25,000
£ 20,000 ¦ 2035
1 15'000 I 2050
.2 10,000
I 5,000
0
OGV - LNG (High) CHE - Replacement (High) Trucks - Idle Reduction
(High)
Figure 3-6. Selected On-port C02e Reduction Strategies
3-4
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Table 3-2. Summary of On-port Emission Reductions
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PM2.5
C02e
2025
2035
2025
2035
2025
2035
2050
Ocean Going Vessels
Reduced Hotelling Time
Low
13.60
13.48
0.31
0.38
847.75
1,039.97
2,520.72
High
27.20
26.97
0.63
0.77
1,695.51
2,079.94
5,041.44
At-Berth Alternative Control
Technology
Low
0.97
3.77
0.07
0.24
-118.80
-668.04
a
High
4.83
7.54
0.37
0.48
-593.98
-1,336.09
--
Lower Sulfur Fuels
Low
--
--
0.32
1.86
--
--
--
High
--
--
0.81
3.71
--
--
--
Liquefied Natural Gas (LNG)
Low
4.26
8.28
0.10
0.25
91.07
223.44
676.96
High
21.28
41.42
0.52
1.27
455.35
1,117.18
2,030.89
Shore Power
High
--
182.18
--
4.33
--
2,940.91
8,099.06
Harbor Craft
Engine Replacement
Low
13.93
10.45
0.63
0.48
--
--
--
High
22.63
13.93
1.03
0.63
--
--
--
Vessel Replacement
Low
13.46
10.10
0.37
0.28
--
--
--
High
26.92
20.19
0.74
0.56
--
--
--
Cargo Handling Equipment
Diesel Particulate Filters
Low
--
--
2.00
0.72
--
--
--
High
--
--
3.37
0.82
--
--
--
Diesel Oxidation Catalysts
Low
--
--
0.44
0.16
--
--
--
High
--
--
0.78
0.18
--
--
--
Equipment Replacement
Low
25.37
54.12
1.37
1.88
0.00
13,041.27
42,848.10
High
48.19
59.74
3.07
2.16
2,091.53
24,751.53
46,535.95
Alternative Fuels
Low
16.36
7.68
0.79
0.50
--
--
--
High
21.51
9.39
1.20
0.69
--
--
--
Reefer Electrification
High
1.48
1.82
0.04
0.06
3,136.57
3,848.32
4,663.77
3-5
-------
Table 3-2. Summary of On-port Emission Reductions
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PM2.5
CChe
2025
2035
2025
2035
2025
2035
2050
Onroad Vehicles
Idle Reduction
Low
3.36
2.17
0.20
0.08
1,571.73
1,881.45
2,271.77
High
10.08
6.50
0.61
0.24
4,715.20
5,644.36
6,815.30
Operational Improvements
Low
0.67
0.43
0.04
0.02
314.35
376.29
454.35
High
1.34
0.87
0.08
0.03
628.69
752.58
908.71
Truck Replacement
Low
5.87
2.92
0.89
0.11
0.00
2,505.10
5,923.40
High
7.26
4.66
0.90
0.15
0.00
4,921.36
9,872.34
Rail
Truck-to-Rail Intermodal Shift
High
0.30
-0.06
0.05
0.02
613.06
1,275.06
2,390.23
a A double dash represents a value that was not calculated as part of this analysis.
3-6
-------
3.2 Off-port Results Summary
This section summarizes the results of the off-port components of EPA's analysis of emissions.
The off-port mobile source sectors analyzed include OGVs, harbor craft, onroad vehicles, and
rail in the following corridors:
1. Marine corridor: The marine corridor accounted for OGV and harbor craft activity
occurring from the state/federal waters boundary located 3 nautical miles offshore to
the international border with the Bahamas (i.e., the continental shelf boundary), which
is approximately 20 to 25 nautical miles from shore.
2. Truck corridor: The onroad freight corridor focused on truck activity on the 1-595 spur
from 1-95 into the Port boundary.
3. Rail corridor: The off-port rail corridor covered the 10 kilometers of a railway line
operated by Florida East Coast Railway extending north of the Intermodal Container
Transfer Facility spur.
Off-port 2015 baseline emissions and BAU emission projections for NOx, PM2.5, and CChe
emissions are summarized for the years 2025, 2035, and 2050 in Figure 3-7, Figure 3-8, and
Figure 3-9, respectively. As seen in the figures, OGVs are the biggest source of emissions and
are expected to remain so in future years. Rail emissions are not visible in the figures as they
are orders of magnitude smaller than emissions for the other sectors. Note that the absolute
magnitude of the emissions for each sector is highly dependent on the size of the corridor and
how much activity occurs in the corridor. For example, the marine corridor is much larger than
both landside corridors; however, harbor craft have very little activity in the marine corridor.
Baseline emissions and BAU projections are presented in Table 3-3 for all pollutants considered
in EPA's analysis. Note that SO2 was only evaluated for OGVs. Additionally, for the 2050
analysis, only C02e inventories and reductions were quantified.
Selected off-port NOx, PM2.5, and C02e emission reduction strategies are highlighted in Figure
3-10, Figure 3-11, and Figure 3-12, respectively. These figures show that potential actions
taken to reduce emissions can have benefits beyond a port's boundary. Given the assumed
implementation conditions, the voluntary vessel speed reduction strategy is effective at
reducing OGV emissions in off-port corridors. Accelerating fleet turnover to cleaner technology
through truck replacements has the potential to reduce NOx and PM2.5 emissions significantly
through 2035, despite the projected growth in truck activity. Since replacement of trucks with
battery electric vehicles is not assumed to occur before 2035, C02e emission reductions from
this strategy are not projected in 2025.
A summary of results of all analyzed off-port strategies and scenarios for each source category
is presented in Table 3-4. This summary only includes NOx, PM2.5, and C02e; however, off-port
results for all pollutants are included along with methodology details in Section 9. This section
also includes results by percent reduction from the BAU for each strategy scenario.
3-7
-------
As described in Section 9, some strategies and scenarios were not evaluated for all three future
years of 2025, 2035, and 2050, and some were not evaluated for all pollutants (i.e., some
strategies only targeted a subset of the pollutants). Additionally, not all emissions for the
considered pollutants occurring in the Port's off-port corridors are captured by EPA's analysis.
1,200
| 1,000
800 |l
I 600
400 III
! : III
OGV Harbor Craft Onroad Rail
Figure 3-7. Off-port Baseline and BAU NOx Emissions
¦ 2015
¦ 2025
¦ 2035
30
™ 25
ai "
s-
20
o 15
10
(O
3
£
£
<
12015
12025
12035
OGV Harbor Craft Onroad Rail
Figure 3-8. Off-port Baseline and BAU PM2.5 Emissions
3-8
-------
90,000
-c- 80,000
(D
>- 70,000
§ 60,000
£ 50,000
o
40,000
|S 30,000
| 20,000
< 10,000
12015
12025
12035
2050
OGV Harbor Craft Onroad Rail
Figure 3-9. Off-port Baseline and BAU C02e Emissions
Table 3-3. Summary of Off-port Baseline and BAU Emissions
Year
Source
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02e
2015
OGV
918.91
17.28
16.59
17.08
16.40
12.76
29.14
41.56
45,779.34
Harbor Craft
23.40
0.99
0.97
0.99
0.97
0.75
a
1.02
1,324.75
Onroad
23.69
1.43
1.31
1.42
1.30
0.61
--
1.64
6,657.57
Rail
2.59
0.04
0.04
0.04
0.04
0.03
--
0.07
261.04
Total
968.59
19.74
18.91
19.53
18.71
14.15
--
44.29
54,022.70
2025
OGV
979.99
23.53
22.50
23.25
22.28
17.36
39.63
56.37
62,298.97
Harbor Craft
24.82
1.04
1.02
1.04
1.02
0.79
--
1.13
1,583.07
Onroad
10.66
0.51
0.47
0.50
0.46
0.22
--
0.63
8,251.94
Rail
2.88
0.06
0.05
0.06
0.05
0.03
--
0.66
329.95
Total
1,018.35
25.14
24.04
24.85
23.81
18.40
--
58.79
72,463.93
2035
OGV
727.51
26.87
25.74
25.65
25.43
19.80
45.19
64.63
71,044.82
Harbor Craft
41.84
1.73
1.69
1.73
1.69
1.30
--
1.98
3,054.86
Onroad
6.76
0.20
0.19
0.20
0.18
0.03
--
0.31
9,774.84
Rail
2.76
0.07
0.07
0.07
0.07
0.05
--
1.49
377.09
Total
778.87
28.87
27.69
27.65
27.37
21.18
--
68.41
84,251.61
2050
OGV
--
--
--
--
--
--
--
--
78,603.92
Harbor Craft
--
--
--
--
--
--
--
--
--
Onroad
--
--
--
--
--
--
--
--
11,530.98
Rail
--
--
--
--
--
--
--
--
389.56
Total
--
--
--
--
--
--
--
--
--
a A double dash represents a value that was not calculated as part of this analysis.
3-9
-------
_ 200
S 180
| 160
| 140
mm
¦I100
" II
||
OGV-Speed Reduction OGV-LNG (High) Trucks - Replacement (High)
(Low)
Figure 3-10. Selected Off-port NOx Reduction Strategies
4.5
Ol H-.U
> 3.5
o
ii 3.0
y 2.0
T3
2 1-5
.2 !-0
\n
¦| 0.5
m 0.0
12025
12035
OGV-Speed Reduction
(Low)
OGV-LNG (High)
Trucks - Replacement (High)
Figure 3-11. Selected Off-port PM2.5 Reduction Strategies
14,000
ro
(D
>
12,000
o 10,000
| 8,000
= 6,000
"O
(D
^ 4,000
o
8 2,000
£
0
I
I
12025
12035
2050
OGV-Speed Reduction
(Low)
OGV - LNG (High) Trucks - Replacement (High)
Figure 3-12. Selected Off-port C02e Reduction Strategies
3-10
-------
Table 3-4. Summary of Off-port Emission Reductions
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PM2.5
CChe
2025
2035
2025
2035
2025
2035
2050
Ocean Going Vessels
Vessel Speed Reduction During Transit
Low
175.19
124.05
3.59
4.02
10,417.25
11,661.24
12,689.28
High
315.34
223.29
6.46
7.24
18,751.04
20,990.23
22,840.70
Lower Sulfur Fuels
Low
a
--
0.13
0.76
--
--
--
High
--
--
0.33
1.52
--
--
--
LNG
Low
2.30
3.89
0.05
0.12
34.48
84.60
256.31
High
11.51
19.45
0.24
0.59
172.40
422.98
768.94
Harbor Craft
Engine Replacement
Low
1.37
1.03
0.10
0.07
--
--
--
High
2.23
1.37
0.16
0.10
--
--
--
Vessel Replacement
Low
1.33
0.99
0.06
0.04
--
--
--
High
2.65
1.99
0.11
0.09
--
--
--
Onroad Vehicles
Truck Replacement
Low
2.52
1.25
0.32
0.04
0.00
1,376.60
3,255.01
High
3.12
2.00
0.32
0.05
0.00
2,704.37
5,425.02
a A double dash represents a value that was not calculated as part of this analysis.
3-11
-------
4. OCEAN GOING VESSELS
For the purpose of this analysis, ocean going vessels (OGVs) are considered to be ships with
engines of 30 liters displacement per cylinder or more (i.e., Category 3 engines). While some
OGVs can have smaller Category 2 engines, it was assumed for simplicity in this analysis that all
OGVs had Category 3 engines. These vessels may be used to transport cargo or people; some
engage in trans-oceanic voyages while others may stay in the region or even in coastal waters.
Table 4-1 lists the vessel types that were included in this analysis.
Table 4-1. OGV Types
Ship Type
Description
Auto Carrier
Dry-cargo vessel that carries containerized automobiles
Bulk Carrier
Dry-cargo vessel that carries loose cargo
Containership
Dry-cargo vessel that carries containerized cargo
Cruise Ship
Passenger vessel used for pleasure voyages
General Cargo Ship
Cargo vessel that carries a variety of dry cargo
Roll-on/Roll-off (RORO)
Vessel that handles cargo that is rolled on and off the ship
Tankers
Liquid-cargo vessel including chemical tankers, petroleum product tankers, liquid
food product tankers, etc.
Miscellaneous
Vessel that transports cargo that is not otherwise designated above
This section presents the on-port baseline emissions inventory and projected Business as Usual
(BAU) emissions for OGVs (Section 4.1), the considered strategies and scenarios to reduce OGV
emissions (Section 4.2), and a summary of the primary results and lessons learned (Section 4.3).
Note that OGV emissions occurring in off-port corridors are presented in Section 9.1.
4.1 Baseline and Projected Business as Usual Inventories
The 2015 On-port Baseline Inventory31 contains on-port emission estimates for OGV activity
based on U.S. Coast Guard automatic identification system (AIS) data, Information Handling
Services' (IHS) Register of Ships, Starcrest's Vessel Boarding Program, and wharfinger vessel call
data supplied by Port Everglades. The geographical scope of the inventory includes all
waterways and berths within the Port and state waters associated with Broward County, which
extend three nautical miles from the shoreline. The baseline inventory includes emissions from
main propulsion engines, auxiliary engines, and boilers, and are provided by vessel type as well
as by the following operating modes:32
• Maneuvering: When a vessel is moving inside the geographical domain.
• Hotelling: When a vessel is stationary at the dock/berth.
31 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
32 Note that there is no transit (or "at-sea") mode of operation in the on-port geographical domain.
4-1
-------
• At-Anchorage: When a vessel is stationary within the anchorage area (i.e., in the coastal
zone).
For details on the data collection and inventory development methodology, please see the
2015 On-port Baseline Inventory. The OGV baseline emission inventories presented here
include pollutants from the 2015 On-port Baseline Inventory as well as DPM2.5 and BC, which
EPA added for its analysis.33 34 Additionally, the (Xhe results, which were presented in metric
tons in the baseline inventory, were converted to short tons here for consistency with the other
pollutants.
A hypothetical BAU scenario was developed based on anticipated growth and changes at Port
Everglades as identified in the 2014 Master/Vision Plan.35 Growth factors by vessel/cargo type
were developed from projected throughput at the Port, as summarized in Table 4-2.36
Table 4-2. Projected Growth Factors Used for Future OGV Activity
Vessel/Cargo Type (units)
Projected Throughput
Growth Factor (unitless)
2015
2025
2035
2050
2015
2025
2035
2050
Bulk (tons)3
1,565,000
1,870,000
3,609,000
3,906,000
1.000
1.195
2.306
2.496
Container (TEUs)a
1,060,000
1,435,000
1,761,000
2,134,000
1.000
1.354
1.661
2.013
Cruise (passengers)15
3,773,000
5,306,000
5,730,000
6,065,000
1.000
1.406
1.519
1.607
Liquid Bulk (barrels/day)0
305,000
357,000
381,000
416,000
1.000
1.170
1.249
1.364
Average
1.000
1.281
1.684
1.870
a Projections derived from the "Baseline-Plus Estimate" given in the 2014 Master/Vision Plan for these sectors
b Projections derived from the "Medium Estimate" given in the 2014 Master/Vision Plan for this sector
c Projections derived from the only estimate given in the 2014 Master/Vision Plan for this sector
Additionally, it was assumed that the future age distribution of the vessel fleet would be similar
to the current fleet, such that the fraction of vessels less than ten years old would be identical
in each of the projected years. Table 4-3 provides the fraction of vessels under ten years old by
vessel type based on wharfinger vessel call data supplied by Port Everglades. Please note that
this assumption implies that the current OGV fleet will be completely replaced prior to 2050 in
the BAU scenario.
33 DPM2.5 was calculated as a fraction of DPM10 by applying the ratio of PM2.5 to PM10 emissions from diesel-
powered main and auxiliary engines. BC was calculated as 77% of PM2.5 based on the EPA's Report to Congress
on Black Carbon.
34 U.S. Environmental Protection Agency, Report to Congress on Black Carbon, EPA-450/R-12-001, p. 87, March
2012, https://www3.epa.gov/airqualitv/blackcarbon/2012report/fullreport.pdf.
35 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
36 Growth factors for 2035 and 2050 are not included in the range of projections provided in the 2014
Master/Vision Plan cited in this report. Therefore, the factors were extrapolated from expected growth
between 2028 and 2033, the last five years presented in the 2014 Master/Vision Plan.
4-2
-------
Table 4-3. Replacement Rate Assumed for
Future OGV Fleet
Vessel Type
% Under 10 Years Old
Containerships
33%
Cruise ships
42%
Liquid bulk carriers
66%
Bulk carriers
61%
Fleet Average
35%
The assumed future vessel replacement rates are important because new vessels will need to
comply with international Tier III standards, which have lower NOx emissions. For slow speed
engines—the most common engine type found on OGVs calling at Port Everglades—this
standard is 3.4 grams of NOx per kW-hr.37 For comparison, the average emission factor for
vessels calling at Port Everglades in 2015 was 14.65 grams of NOx per kW-hr. Note that the
simplifying assumption that the age distribution of OGVs calling at Port Everglades will remain
the same in the future results in a more aggressive fleet turnover to the Tier III standards than
what is predicted at other ports.38 39
Hypothetical future emission inventories were then estimated for 2025, 2035, and 205040 by
first applying the growth factors by vessel or cargo type to the 2015 baseline emissions to
reflect increased trade, and then applying adjustment factors based on expected changes in the
fleet emission factors subject to the assumptions described above.
The subsequent tables in this section show the on-port OGV baseline and hypothetical BAU
emissions, presented by vessel type and modal operation. Table 4-4 shows the 2015 baseline
emissions for on-port OGVs by vessel type. Table 4-5 presents the 2025 BAU emissions, Table
4-6 presents the 2035 BAU emissions, and Table 4-7 presents the 2050 BAU emissions. Table
4-8 summarizes the inventories for 2015, 2025, 2035, and 2050 by the following modes:
anchorage, hotel ling, and maneuvering. Note that a containership classified as "Container—
1000" vessel is assumed to accommodate up to 1,999 twenty-foot equivalent units (TEUs) in
this analysis.
As shown in the tables, BAU inventories for almost all pollutants are projected to increase in
the future due to the anticipated growth in marine freight and cruise traffic. The exception is
37 U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from
Category 3 Marine Diesel Engines, EPA-420-R-09-019, December 2009,
https://nepis.epa.gov/Exe/ZvPURL.cgi?Dockev=P1005ZGH.txt.
38 Starcrest Consulting Group, LLC, Bay Wide Ocean-Going Vessel International Maritime Organization Tier
Forecast 2015-2050, June 2017, https://www.portoflosangeles.org/pdf/CAAP Vessel Tier Forecasts 2015-
2050-Final.pdf.
39 This simplifying assumption regarding future OGV tier distributions was appropriate based on the purpose and
on data available for this analysis.
40 Note that for 2050, only CChe inventories and reductions were quantified.
4-3
-------
for NOx emissions, which are projected to decrease in 2035 due to the compliance with the
Emission Control Area (ECA) NOx standards. However, these results are highly dependent on
the assumptions described above regarding OGV fleet turnover, and actual future emissions will
depend largely on actual vessel turnover to the cleaner emission standards.
4-4
-------
Table 4-4. 2015 Baseline Emissions for On-port OGVs by Vessel Type
Vessel Type
Annual Emissions (tons/year)41
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
VOC
C02e
Auto Carrier
2.69
0.06
0.06
0.05
0.05
0.04
0.11
0.15
165.91
Bulk
33.48
0.81
0.76
0.61
0.58
0.59
1.82
1.28
2,866.65
Bulk—Heavy Load
2.50
0.05
0.05
0.04
0.04
0.04
0.12
0.08
183.48
Container—1000
288.18
6.25
5.87
5.33
5.01
4.52
12.87
10.22
20,229.01
Container—2000
38.77
0.84
0.79
0.73
0.69
0.61
1.52
1.96
2,387.71
Container—3000
23.67
0.55
0.52
0.46
0.43
0.40
0.95
1.60
1,502.33
Container—4000
40.54
0.91
0.85
0.79
0.75
0.66
1.45
2.83
2,290.38
Container—5000
27.97
0.66
0.62
0.56
0.52
0.48
1.12
1.92
1,758.09
Container—6000
29.13
0.65
0.61
0.55
0.51
0.47
1.06
2.10
1,667.33
Container—9000
1.30
0.03
0.03
0.03
0.02
0.02
0.07
0.08
107.58
Cruise
995.61
19.67
18.48
19.66
18.47
14.23
35.69
32.36
55,940.55
General Cargo
138.93
2.86
2.68
2.51
2.36
2.06
5.83
4.41
9,158.84
Miscellaneous
6.68
0.14
0.13
0.12
0.11
0.10
0.29
0.21
451.19
RORO
81.47
1.75
1.64
1.58
1.48
1.27
3.49
2.73
5,486.49
Tanker—Chemical
207.13
5.34
5.01
3.78
3.55
3.86
12.51
7.90
19,705.17
Tanker—Handysize
42.52
1.56
1.46
0.62
0.58
1.12
4.61
1.81
7,283.55
Tanker—Panamax
38.14
1.55
1.45
0.51
0.48
1.12
4.77
1.75
7,541.21
Tanker—Suezmax
2.11
0.07
0.07
0.03
0.03
0.05
0.20
0.08
320.75
Total
2,000.82
43.73
41.07
37.95
35.66
31.64
88.45
73.44
139,046.22
41 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
4-5
-------
.53
.64
.26
.08
.96
.15
.18
.45
.56
.66
.42
.48
.97
.20
.05
.75
.21
.28
.83
4-6
Table 4-5. 2025 BAU Emissions for On-port OGVs by Vessel Type
Annual Emissions (tons/year)
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
0.08
0.07
0.07
0.06
0.06
0.14
0.97
0.91
0.73
0.69
0.70
2.18
0.06
0.06
0.05
0.05
0.05
0.14
8.47
7.95
7.22
6.78
6.12
17.42
1.13
1.06
0.99
0.93
0.82
2.05
0.75
0.70
0.62
0.58
0.54
1.29
1.23
1.16
1.07
1.01
0.89
1.97
0.89
0.84
0.75
0.71
0.64
1.51
0.88
0.83
0.74
0.70
0.64
1.43
0.05
0.04
0.04
0.03
0.03
0.09
27.65
25.98
27.65
25.97
20.00
50.18
3.66
3.44
3.21
3.02
2.64
7.47
0.17
0.17
0.15
0.14
0.13
0.37
2.24
2.11
2.02
1.90
1.62
4.48
6.24
5.86
4.42
4.15
4.51
14.63
1.82
1.71
0.72
0.68
1.32
5.39
1.81
1.70
0.59
0.56
1.31
5.58
0.08
0.08
0.03
0.03
0.06
0.24
58.18
54.67
51.07
47.99
42.08
116.56
-------
.39
.49
.10
.38
.99
.36
.33
.18
.43
.69
.70
.49
.80
.25
.76
.15
.97
.62
.08
4-7
Table 4-6. 2035 BAU Emissions for On-port OGVs by Vessel Type
Annual Emissions (tons/year)
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
0.10
0.10
0.09
0.08
0.07
0.18
1.88
1.76
1.42
1.33
1.36
4.20
0.12
0.12
0.10
0.09
0.09
0.27
10.38
9.75
8.86
8.32
7.51
21.37
1.39
1.31
1.22
1.15
1.00
2.52
0.91
0.86
0.76
0.71
0.66
1.58
1.51
1.42
1.32
1.24
1.09
2.41
1.09
1.03
0.92
0.87
0.79
1.85
1.08
1.02
0.91
0.85
0.78
1.76
0.06
0.05
0.04
0.04
0.04
0.11
29.87
28.07
29.87
28.06
21.61
54.21
4.81
4.52
4.22
3.97
3.48
9.82
0.23
0.22
0.20
0.18
0.17
0.48
2.95
2.77
2.66
2.50
2.13
5.88
6.67
6.26
4.72
4.43
4.82
15.62
1.95
1.83
0.77
0.72
1.41
5.76
1.93
1.81
0.63
0.59
1.40
5.96
0.09
0.08
0.04
0.03
0.06
0.25
67.02
62.98
58.75
55.16
48.47
134.23
-------
Table 4-7. 2050 BAU Emissions for On-
port OGVs by Vessel Type
Vessel Type
Annual C02e Emissions
(tons/year)
Auto Carrier
310.25
Bulk
7,155.15
Bulk—Heavy Load
457.97
Container—1000
40,720.99
Container—2000
4,806.46
Container—3000
3,024.18
Container—4000
4,610.54
Container—5000
3,539.03
Container—6000
3,356.34
Container—9000
216.55
Cruise
89,896.47
General Cargo
17,127.03
Miscellaneous
843.72
RORO
10,259.74
Tanker—Chemical
26,877.86
Tanker—Handysize
9,934.76
Tanker—Panamax
10,286.21
Tanker—Suezmax
437.50
Total
233,860.74
-------
Table 4-8. Baseline and Projected BAU Emissions for On-port OGVs by Mode
Year
Mode
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02e
201542
At-Anchorage
94.22
2.21
2.07
1.73
1.62
1.59
4.93
3.13
7,756.29
Hotelling
1,525.74
33.86
31.79
28.76
27.01
24.48
71.29
50.22
112,075.96
Maneuvering
380.84
7.67
7.21
7.46
7.01
5.55
12.23
20.09
19,213.96
Total
2,000.82
43.73
41.07
37.95
35.66
31.64
88.45
73.44
139,046.22
2025
Anchorage
74.34
2.75
2.58
2.16
2.03
1.99
6.13
3.90
9,639.89
Hotelling
1,598.22
45.09
42.34
38.84
36.47
32.60
93.86
67.42
147,529.53
Maneuvering
392.90
10.34
9.73
10.07
9.47
7.49
16.55
26.92
25,996.40
Total
2,065.47
58.18
54.67
51.07
47.99
42.08
116.56
98.24
183,165.83
2035
Anchorage
69.41
3.32
3.11
2.62
2.46
2.39
7.37
4.72
11,605.03
Hotelling
1,357.09
51.59
48.45
44.34
41.64
37.31
107.62
77.04
169,154.56
Maneuvering
326.59
12.10
11.38
11.77
11.07
8.76
19.23
31.94
30,212.48
Total
1,753.08
67.02
62.98
58.75
55.16
48.47
134.23
113.70
210,972.08
2050
Anchorage
a
--
--
--
--
--
--
--
13,161.01
Hotelling
--
--
--
--
--
--
--
--
186,845.38
Maneuvering
--
--
--
--
--
--
--
--
33,854.35
Total
--
--
--
--
--
--
--
--
233,860.74
a A double dash represents a value that was not calculated as part of this analysis.
42 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
4-9
-------
4.2 Emission Reduction Strategies and Scenarios
The following on-port emission reduction strategies were selected in consultation with Port
Everglades:
• Reduced hotelling time (5 or 10 percent reduction)43
• At-berth alternative control technology (capture and treat)
• Use of lower sulfur fuels (500 ppm or 200 ppm sulfur content)
• Use of liquefied natural gas (LNG)
• Application of shore power to reduce auxiliary engine operations while dockside44
Because Port Everglades does not have direct control over implementing these strategies, the
hypothetical scenarios for each are predicated on the assumption of the coordination and
collaboration between various maritime industry stakeholders for implementation. Table 4-9
summarizes applicability and implementation assumptions for each strategy and scenario.
Several factors were considered when developing the emission reduction strategies, including
the specific vessel types best targeted by each strategy as well as the feasibility of
implementing the fuel and technology strategies. As part of this consultation, the Port shared
its non-confidential vessel call log with EPA, which allowed for incorporation of more detailed
vessel characteristics into this portion of the analysis. Emission reductions for some strategies,
such as shore power, were applied only to OGVs that visited Port Everglades multiple times a
year (i.e., "frequent callers") due to high per-vessel capital costs, while other strategies, such as
at-berth alternative control technology, were applied only to non-frequent callers. In addition,
some strategies were applied to either propulsion or auxiliary OGV engines and their respective
types of emissions (e.g., targeting auxiliary engines would reduce OGV hotelling emissions).
Hypothetical emission reductions were calculated for every emission reduction strategy and
low/high scenario in Table 4-9 using the emission reduction factors presented in Table 4-10.
Some strategies (e.g., reduced hotelling time) impact all pollutants proportionally, while the
impacts of others vary by pollutant. For example, use of lower sulfur fuels would only reduce
SO2 and PM emissions. Reductions were calculated independently for all scenarios relative to
the applicable portion of the BAU inventories. For example, strategies that address hotelling
emissions were applied to the portion of hotelling emissions in the BAU inventories. Additional
details on the selected emission reduction strategies and scenarios are presented in Sections
4.2.1 through 4.2.5.
43 The reduced hotelling time strategy is hypothetical and would go above and beyond the dockside
improvements continuously being sought at Port Everglades. This analysis does not attempt to predict or
dictate the exact nature of how the reduced hotelling would be achieved, but assumes it would comply with all
safety regulations and guidelines.
44 Note that Port Everglades has previously evaluated the potential of using shore power and concluded that it is
not economically feasible to implement at present. This strategy is included in this hypothetical analysis
because, as technologies advance, various stakeholders in the maritime industry may continue to evaluate the
feasibility of shore power at Port Everglades and other ports.
4-10
-------
Table 4-9. Summary of On-port Emission Reduction Scenarios for OGVs
Strategy
Affected Vessel
Types
Scenario
Implementation Rates
Notes
2025
2035
2050
Reduced Hotelling Time
Containerships
Low
100%
100%
100%
Assumed 5% reduction in hotelling
High
100%
100%
100%
Assumed 10% reduction in hotelling
At-Berth Alternative Control
Technology
Containerships
& tankers
Low
1%
5%
N/A
Applied to non-frequent callers only
High
5%
10%
N/A
Lower Sulfur Fuels
All OGVs
Low
10% use of
500 ppm
25% use of
200 ppm
N/A
High
25% use of
500 ppm
50% use of
200 ppm
N/A
LNG
Containerships
Low
1%
2%
5%
High
5%
10%
15%
Shore Power
Passenger &
containerships
High
0%
25%
passenger
10%
container
60%
passenger
35%
container
Assumed 2 hours for connecting and
disconnecting
4-11
-------
Table 4-10. On-port OGV Emission Reduction Factors by Scenario
Strategy
Scenario
Notes
NOx
PMio
PM2.5
DPM
voc
SO2
CO2
CH4
N2O
Reduced Hotelling
Time
Low
5% reduction in
dockside duration
5.0%
5.0%
5.0%
5.0%
5.0%
5.0%
5.0%
5.0%
5.0%
High
10% reduction in
dockside duration
10.0%
10.0%
10.0%
10.0%
10.0%
10.0%
10.0%
10.0%
10.0%
At-Berth
Alternative
Control
Technology
Low/High
Containerships
73.0%
78.0%
78.0%
78.0%
78.0%
78.0%
-9.0%
a
-
Tankers
75.0%
80.0%
80.0%
80.0%
80.0%
80.0%
-7.0%
-
-
Lower Sulfur Fuels
Low/High
500 ppm
--
5.9%
5.9%
5.9%
--
50.0%
-
-
-
200 ppm
--
11.8%
11.8%
11.8%
--
80.0%
-
-
-
LNG
High
87.7%
82.4%
82.4%
82.4%
16.7%
99.0%
22.4%
-
26.7%
Shore Power
High
Reduction in
emissions relative
to local eGRID
and GREET
emission factors
97.3%
80.8%
80.0%
80.8%
98.0%
12.7%
20.1%
-365.8%
82.4%
a A double dash represents a value that was not calculated as part of this analysis.
4-12
-------
4.2.1 Reduced Hotelling Time
Because the emissions of dockside auxiliary engines while hotelling are generally significant,
any reduction in time spent hotelling is likely to reduce emissions. For this strategy, this
analysis focused on containership hotelling. The reduced hotelling times presented in Table
4-11, in hours and by vessel capacity, were respectively calculated by assuming 5 and 10
percent reductions in hotelling above and beyond the dockside improvements continuously
being sought at Port Everglades.
Table 4-11. Containership Hotelling Time by Vessel Capacity
Container Capacity
(TEUs)
Average Hotelling
Time (hrs)45
Hotelling Time
with 5%
Reduction (hrs)
Hotelling Time
with 10%
Reduction (hrs)
1000
20
19.0
18.0
2000
17
16.2
15.3
3000
11
10.5
9.9
4000
10
9.5
9.0
5000
17
16.2
15.3
6000
19
18.1
17.1
9000
63
59.9
56.7
Please note that this analysis does not attempt to predict or dictate the exact nature of how the
reduced hotelling would be achieved, but assumes it would comply with all safety regulations
and guidelines.46 The reduced hotelling times presented above were used in conjunction with
the on-port containership auxiliary hotelling emissions to estimate the associated emission
reductions.
4.2.2 At-berth Alternative Control Technology (Capture and Treat)
At-berth alternative control systems, also known as "capture and treat systems," reduce
dockside marine vessel emissions by capturing a vessel's stack emissions and routing them to
an after-treatment based emission control device located alongside the vessel. These systems
typically are based on selective catalytic reduction (SCR) technology. There are two variants of
these systems: 1) a mobile version that operates from a barge adjacent to the vessel; and 2) a
stationary version located on the dock. In either case, the system captures the emissions and
routes them through an SCR reactor. This analysis assumes the system is barge mounted and
takes 2 hours per call to connect to and disconnect from the vessel's exhaust stack. When the
45 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
46 The opportunities and challenges for reducing hotelling time vary substantially, not only from port to port, but
also between business lines. For example, the activities that occur while a ship is dockside are very different for
cruise ships and cargo ships. Examining the opportunities for reducing hotelling time for each business line at
Port Everglades was outside the scope for this analysis; however, ports are encouraged to look for
opportunities where possible.
4-13
-------
system is being connected or disconnected, the vessel's emissions are not being captured and
treated. While the efficiency of this technology can vary by case, it was assumed in this analysis
that it was 90-95 percent effective at reducing auxiliary engine hotelling emissions while it is
operating. In addition, it was assumed that an auxiliary generator on the barge produces
emissions while the system is in place.
For the scenario analysis, at-berth alternative control technology reductions were only applied
to containerships and tankers that visited the port less than five times per year (i.e., non-
frequent callers). This is because the strategy does not require high per-ship investments, so it
should be feasible to apply it to non-frequent callers. Table 4-12 summarizes the percentage of
non-frequent containerships and tankers calling at Port Everglades based on the Port's vessel
call log.
Table 4-12. Summary of Non-Frequent Containership and Tanker Port Calls
Vessel Type
Total Vessel Count
Non-Frequent Caller Count
Percent Non-Frequent Caller
Containership
146
39
27%
Tanker
225
171
76%
It was assumed that the frequency of port calls will remain the same for the projected future
years. To calculate the emission impacts of this strategy for each scenario, the non-frequent
caller proportion of the projected BAU auxiliary hotelling emissions in Table 4-12 was reduced
based on the rate of implementation in Table 4-9 and the anticipated emission reductions
noted in Table 4-10.
4.2.3 Use of Lower Sulfur Fuels
Since the designation and entry into force of the ECA through amendment to Annex VI to the
International Convention for the Prevention of Pollution from Ships (MARPOL) in 2012, ships
operating in the boundaries of that area are required to use lower sulfur fuel. The original
sulfur limit, 10,000 ppm, was reduced to 1,000 ppm beginning on January 1, 2015. This sulfur
limit is much lower than the global marine fuel sulfur limit of 35,000 ppm that applies outside
designated ECAs.47
For additional emission reductions, this strategy assumes a proportion of ships would use fuel
with a sulfur concentration of 500 ppm in 2025 and 200 ppm in 2035. The assumed
implementation rates for the low and high scenarios are listed in Table 4-9 and the emission
reductions associated with use of lower sulfur fuels are listed in Table 4-10.
47 More information about the North American ECA can be found in U.S. Environmental Protection Agency,
Designation of North American Emission Control Area to Reduce Emissions from Ships, EPA-420-F-10-015,
March 2010, https://nepis.epa.gov/Exe/ZvPDF.cgi/P100AU0I.PDF?Dockev=P100AU0l.pdf.
4-14
-------
4.2.4 Use of LNG
Increased use of natural gas-powered vessels can reduce emissions from NOx, CO2, PM, and
SO2. This analysis does not account for fugitive methane emissions from natural gas use, such
as from equipment leakage. In addition, assumptions were not made regarding
implementation details, such as whether LNG use would be increased through retrofits or new
vessels only, or the nature of LNG refueling infrastructure.
The LNG implementation rates for containerships from Table 4-9 and the emission reductions
noted in Table 4-10 were applied to the projected BAU containership emissions in Table 4-8 to
evaluate the anticipated changes in emissions from this strategy.
4.2.5 Shore Power
Another way to reduce emissions at ports is by using shore power technology, also known as
"cold ironing." Shore power allows ships to plug into electrical power sources on shore and
turn off their auxiliary diesel engines while at dock. Because the cost of the shore power
infrastructure for both vessels and port terminals can be substantial,48 this strategy was only
applied to passenger vessels and containerships that frequently called at the Port (defined in
this analysis as vessels that called at Port Everglades 5 or more times per year).
The potential emission reductions depend on the fuel and electricity generation technology mix
of the power source. For this analysis, emission factors were derived from EPA's Emissions &
Generation Resource Integrated Database (eGRID),49 using data for the Florida Reliability
Coordinating Council (FRCC) North American Electric Reliability Corporation (NERC) region. The
eGRID data were supplemented with complementary Greenhouse Gases, Regulated Emissions,
and Energy Use in Transportation (GREET)50 data from Argonne National Laboratories to gap-fill
missing pollutants (i.e., VOCs and particulate matter). The emission reduction estimates
presented in Table 4-10 were calculated by comparing these emission factors to those of Tier 2
medium speed auxiliary Category 2 engines.
To estimate the emission impacts of this strategy, the frequent caller proportion of the
projected BAU auxiliary hotelling emissions from containerships and passenger vessels were
reduced based on the implementation rates in Table 4-9 and the anticipated emission
reductions noted in Table 4-10.51
48 For an example of the required port-side infrastructure, when Port Everglades previously evaluated shore
power, they found that they would need a 40 MW substation to accommodate two cruise terminals, in addition
to infrastructure to bring the power from the substation to the vessel berth.
49 U.S. Environmental Protection Agency, Emissions & Generation Resource Integrated Database (eGRID2014),
2017, httpsi//www,epa,gov/energy/emissions-generation-resource-integrated~database-egrid.
50 Argonne National Laboratory, U.S. Department of Energy, GREET2016 Model, 2016,
httpsi//greet,es,anl,gov/index,php.
51 It was assumed that connecting and disconnecting the ship from shore power would take 2 hours per call.
4-15
-------
4.3 Emission Reduction Scenario Results and Lessons Learned
The modeled emission reductions by strategy and scenario are summarized in Figure 4-1, Figure
4-2, Figure 4-3, and Table 4-13 for on-port operations, while Table 4-14 shows the emission
reductions as a percentage of wider OGV emissions for each pollutant. The percent reductions
for reduced hotelling time, at-berth alternative control technology, and shore power are shown
relative to total on-port OGV hotelling emissions, as these strategies only address emissions
from hotelling for certain vessel types. Percent reductions for increased use of low sulfur fuels
are shown relative to total OGV emissions, as they reduce emissions from all considered OGV
modes of operation. Similarly, the percent reductions for increased use of LNG in
containerships are shown relative to total OGV emissions.
The analysis shows that on-port OGV emissions are dominated by hotelling operations;
therefore, emission reduction strategies that focus on hotelling operations such as shore power
are projected to have the greatest overall impact. The fuel use strategies that impact all OGV
operations also show notable reductions.
This analysis benefited from access to highly detailed baseline inventories based on AIS data
and the Port's non-confidential vessel call records. However, a more nuanced approach to
future OGV tier distributions based on studies done for other U.S. ports would improve the
projected BAU inventories.
4-16
-------
200
— 180
J. 160
I 140
-M
£ 120
| 100
I 80
cc
c 60
o
'« 40
£
^ 20
12025
12035
Reduced Hotelling Reduced Hotelling At-Berth Alt. At-Berth Alt.
(Low) (High) Control (Low) Control (High)
LNG (Low)
¦I
LNG (High)
Shore Power
(High)
Figure 4-1. On-port OGV NOx Reduction Strategies
5.0
¥ 4.5
(D
^ 4.0
tn
0 3.5
£ 3.0
1 2.5
I 2.0
* 1-5
| i.o
£ 0.5
0.0
¦I ll _¦ ll J
1 ll
1 .1
12025
12035
Reduced
Hotelling
(Low)
Reduced
Hotelling
(High)
At-Berth Alt. At-Berth Alt. Lower Sulfur Lower Sulfur
Control (Low) Control (High) Fuels (Low) Fuels (High)
LNG (Low) LNG (High)
Shore Power
(High)
Figure 4-2. On-port OGV PM2.5 Reduction Strategies
4-17
-------
9,000
„ 8,000
I 7,000
tn
o 6,000
| 5,000 — ¦ ¦ 2025
3 4,000 | | ¦ 2035
(D
^ 3,000
o
2,000
m 1,000
0
.¦I III -.1 I
Reduced Hotelling (Low) Reduced Hotelling (High) LNG (Low) LNG (High) Shore Power (High)
Figure 4-3. On-port OGV C02e Reduction Strategies
2050
4-18
-------
Table 4-13. Total Reductions from BAU On-port OGV Emissions by Scenario
Year
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02ea
Reduced Hotelling
Low
13.60
0.33
0.31
0.33
0.31
0.24
0.60
0.54
847.75
Time
High
27.20
0.67
0.63
0.67
0.63
0.49
1.21
1.09
1,695.51
At-Berth Alternative
Low
0.97
0.08
0.07
0.08
0.08
0.05
0.05
0.30
-118.80
2025
Control Technology
High
4.83
0.38
0.37
0.42
0.42
0.28
0.27
1.48
-593.98
Lower Sulfur Fuels
Low
a
0.34
0.32
0.30
0.28
0.25
5.83
-
-
High
-
0.86
0.81
0.75
0.71
0.62
14.57
-
-
LNG
Low
4.26
0.11
0.10
0.09
0.09
0.08
0.26
0.05
91.07
High
21.28
0.55
0.52
0.47
0.44
0.40
1.28
0.23
455.35
Reduced Hotelling
Low
13.48
0.41
0.38
0.41
0.38
0.29
0.74
0.67
1,039.97
Time
High
26.97
0.82
0.77
0.82
0.77
0.59
1.48
1.34
2,079.94
At-Berth Alternative
Low
3.77
0.25
0.24
0.25
0.24
0.18
0.41
0.37
-668.04
Control Technology
High
7.54
0.50
0.48
0.50
0.48
0.37
0.82
0.75
-1,336.09
2035
Lower Sulfur Fuels
Low
-
1.98
1.86
1.73
1.63
1.43
26.84
-
-
High
-
3.95
3.71
3.46
3.25
2.86
53.69
-
-
LNG
Low
8.28
0.27
0.25
0.23
0.22
0.19
0.63
0.11
223.44
High
41.42
1.35
1.27
1.15
1.09
0.98
3.13
0.57
1,117.18
Shore Power
High
182.18
4.65
4.33
1.49
1.39
3.33
1.32
9.22
2,940.91
Reduced Hotelling
Low
-
-
-
-
-
-
-
-
2,520.72
Time
High
-
-
-
-
-
-
-
-
5,041.44
2050
LNG
Low
-
-
-
-
-
-
-
-
676.96
High
-
-
-
-
-
-
-
-
2,030.89
Shore Power
High
-
-
-
-
-
-
-
-
8,099.06
a A double dash represents a value that was not calculated as part of this analysis.
4-19
-------
Table 4-14. Percent Reductions from BAU On-port OGV Emissions by Scenario
Year
Strategy
Scenario
Percent Reductions from BAU Emissions
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02ea
Reduced Hotelling
Low
0.85%
0.73%
0.73%
0.85%
0.85%
0.74%
0.64%
0.80%
0.57%
Time
High
1.70%
1.49%
1.49%
1.73%
1.73%
1.50%
1.29%
1.62%
1.15%
At-Berth Alternative
Low
0.06%
0.18%
0.17%
0.21%
0.22%
0.15%
0.05%
0.44%
-0.08%
2025
Control Technology
High
0.30%
0.84%
0.87%
1.08%
1.15%
0.86%
0.29%
2.20%
-0.40%
Lower Sulfur Fuels
Low
a
0.58%
0.59%
0.59%
0.59%
0.59%
5.00%
0.00%
-
High
-
1.48%
1.48%
1.47%
1.47%
1.47%
12.50%
0.00%
-
LNG
Low
0.21%
0.19%
0.18%
0.18%
0.19%
0.19%
0.22%
0.05%
0.05%
High
1.03%
0.95%
0.95%
0.92%
0.92%
0.95%
1.10%
0.23%
0.25%
Reduced Hotelling
Low
0.99%
0.79%
0.78%
0.92%
0.91%
0.78%
0.69%
0.87%
0.61%
Time
High
1.99%
1.59%
1.59%
1.85%
1.85%
1.58%
1.38%
1.74%
1.23%
At-Berth Alternative
Low
0.28%
0.48%
0.50%
0.56%
0.58%
0.48%
0.38%
0.48%
-0.39%
Control Technology
High
0.56%
0.97%
0.99%
1.13%
1.15%
0.99%
0.76%
0.97%
-0.79%
2035
Lower Sulfur Fuels
Low
-
2.95%
2.95%
2.94%
2.96%
2.95%
20.00%
-
-
High
-
5.89%
5.89%
5.89%
5.89%
5.90%
40.00%
-
-
LNG
Low
0.47%
0.40%
0.40%
0.39%
0.40%
0.39%
0.47%
0.10%
0.11%
High
2.36%
2.01%
2.02%
1.96%
1.98%
2.02%
2.33%
0.50%
0.53%
Shore Power
High
13.42%
9.01%
8.94%
3.36%
3.34%
8.93%
1.23%
11.97%
1.74%
Reduced Hotelling
Low
-
-
-
-
-
-
-
-
1.35%
Time
High
-
-
-
-
-
-
-
-
2.70%
2050
LNG
Low
-
-
-
-
-
-
-
-
0.29%
High
-
-
-
-
-
-
-
-
0.87%
Shore Power
High
-
-
-
-
-
-
-
-
4.33%
a A double dash represents a value that was not calculated as part of this analysis.
4-20
-------
5. HARBOR CRAFT
In the context of port operations, harbor craft include marine watercraft that assist in moving
ocean going vessels (OGVs) around the harbor, move cargo and people around the port harbor
area, and provide fuel to OGVs. Harbor craft are assumed to have main engines with
displacements less than 30 liters per cylinder (i.e., Category 1 and 2 engines). While many kinds
of harbor craft operate at ports across the country, only articulated tugs, assist tugs, and
towboats (collectively referred to as tugs and towboats hereafter) are presented and included
in this analysis, as described in Table 5-1. Pilot boats and recreational vessels, which were
included in the 2015 On-port Baseline Inventory,52 are not considered here, since they would
not be affected by the hypothetical emission reduction strategies and scenarios modeled, as
discussed later in this section.
Table 5-1. Harbor Craft Vessel Types
Vessel Type
Description
Articulated Tug Barges
Tugs specifically designed to work with tank barges
Assist Tugs
Tugs that assist and escort OGVs calling at the port
Towboats
A broad category of ocean tugs, pushboats, and towboats that tow/push barges
This section presents the on-port baseline emissions inventory and projected Business as Usual
(BAU) emissions for harbor craft (Section 5.1), the hypothetical strategies and scenarios to
reduce harbor craft emissions (Section 5.2), and a summary of the results and lessons learned
(Section 5.3). For harbor craft emissions occurring in off-port corridors, see Section 9.2.
5.1 Baseline and Projected Business as Usual Inventories
The 2015 On-port Baseline Inventory, contains emission estimates for harbor craft activity
based on U.S. Coast Guard automatic identification system (AIS) data, Information Handling
Services' (IHS) Register of Ships, Starcrest's Vessel Boarding Program, and wharfinger vessel call
data. The geographical scope of the inventory includes all waterways and berths within the
Port and state waters associated with Broward County, which extend three nautical miles from
the shoreline. Emissions are presented by vessel type from both propulsion and auxiliary
engines.
For details on the data collection and inventory development methodology, please see the
2015 On-port Baseline Inventory. The harbor craft baseline emission inventories presented
here include emissions53 from only the harbor craft types listed in Table 5-1 from the 2015 On-
52 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
53 Note that unlike the OGV inventories, the harbor craft inventories are presented by vessel type only, not by
operating mode.
5-1
-------
port Baseline Inventory as well as DPM2.5 and BC, which EPA added for its analysis.5455
Additionally, the CChe results, which were presented in metric tons in the baseline inventory,
were converted to short tons in this analysis for consistency with the other pollutants.
A hypothetical BAU scenario was developed based on anticipated growth and changes at Port
Everglades as identified in the 2014 Master/Vision Plan.56 Table 5-2 summarizes the projected
growth rates for bulk cargo movements, which were used as surrogates for growth of tug and
towboat operations.57 Note that growth factors for 2050 were not necessary for the harbor
craft analysis, as only greenhouse gases were included for that year in EPA's analysis, and the
selected emission reduction strategies (discussed in Section 5.2) do not address greenhouse
gases.
Table 5-2. Projected Growth Factors Used for Future Harbor Craft Activity
Vessel/Cargo Type
Projected Throughput (tons)
Growth Factor (unitless)
2015
2025
2035
2015
2025
2035
Bulk3
1,565,000
1,870,000
3,609,000
1.000
1.195
2.306
a Projections derived from the "Baseline-Plus Estimate" given in the 2014 Master/Vision Plan for this sector
Additionally, it was assumed that the future age distribution of the vessel fleet would be like
that of the current fleet, such that the fraction of vessels less than ten years old would remain
the same in each of the projection years. The assumed ten-year vessel replacement rate is
given in Table 5-3 as the fraction of vessels in the age 0 to 10 category. Please note that this
assumption implies that there will still be Tier 0 vessels in the fleet in 2035 in the BAU scenario.
The actual future emissions will depend largely on actual vessel turnover.
Table 5-3. Baseline Age Distribution of Tugs and Towboats
Vessel Age (years)
Vessel Count
Age Distribution
Oto 10
8
13%
11 to 20
12
20%
21 to 30
4
7%
31 to 40
24
39%
Greater than 40
13
21%
Total
61
100%
54 DPM2.5 was calculated as a fraction of DPM10 by applying the ratio of PM2.5 to PM10 emissions from diesel-
powered main and auxiliary engines. BC was calculated as 77% of PM2.5 based on the EPA's Report to Congress
on Black Carbon.
55 U.S. Environmental Protection Agency, Report to Congress on Black Carbon, EPA-450/R-12-001, p. 87, March
2012.
56 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
57 Growth factors for 2035 were not included in the range of projections provided in the 2014 Master/Vision Plan
cited in this report. Therefore, the factors were extrapolated from expected growth between 2028 and 2033,
the last five years presented in the 2014 Master/Vision Plan.
5-2
-------
The assumed future vessel replacement rates are important because new vessels will need to
comply with Tier 4 emission standards.58 59 Based on the 2015 tug and towboat fleet age
distribution shown in Table 5-3, it was assumed that all vessels retired and replaced in future
years due to normal attrition would be Tier 0 replaced with Tier 4. Table 5-4 compares these
emission standards and presents the expected percent reductions when Tier 0 vessels are
replaced with Tier 4 vessels. For simplicity, this reduction was calculated assuming that all tugs
and towboats at Port Everglades have Category 2 engines.
Table 5-4. Emission Standards for Category 2 Vessels by Tier Level (g/kW-hr)
Tier
NOx
PMio
PM2.5
DPM
BC
voc
CO2
ch4
n20
Emission Standard60
TierO
13.20
0.72
0.72
0.72
0.72
0.50
690.00
0.01
0.03
Tier 4
1.80
0.04
0.04
0.04
0.04
0.19
690.00
0.01
0.03
Percent Emission Reduction
Tier 0 to 4
86.4%
94.4%
94.4%
94.4%
94.4%
62.0%
0.0%
0.0%
0.0%
Hypothetical future emission inventories were then estimated for 2025 and 2035 by starting
with the 2015 baseline emissions, applying the growth factors, and then applying adjustment
factors based on expected changes in the fleet emission factors due to the turnover to new
standards. Emission inventories were not calculated for 2050 because the selected emission
reduction strategies (discussed below) do not address greenhouse gases.
A summary of baseline and BAU projected emissions is presented in Table 5-5. Based on the
assumptions in this analysis, emissions are projected to increase for all pollutants due to the
anticipated increase in marine freight traffic, and emissions from assist tugs are the largest
share of this category.
58 For the purposes of this analysis, it was assumed that all harbor craft at Port Everglades are U.S. flagged vessels
that comply with EPA's emission standards. Note that for simplicity, this analysis did not consider the impact of
EPA's Marine Remanufacture Program, which reduces PM emissions from legacy fleet vessels. For more
information on this program, see U.S. Environmental Protection Agency, Frequently Asked Questions from
Marine Engine Owners and Rebuilders about EPA's Marine Remanufacture Program, EPA-420-F-09-003,
February 2009, https://nepis.epa.gov/Exe/ZvPDF.cgi?Dockev=P1002UMW.PDF.
59 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, Federal Register, Vol. 73, No. 126, June
2008, https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-control-emissions-air-
pollution-locomotive.
60 Ibid.
5-3
-------
Table 5-5. 2015 Baseline and 2025 and 2035 BAU Emissions for On-port Harbor Craft
Year
Vessel Type
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
VOC
CChe
201561
Articulated
Tug Barge
17.00
0.44
0.41
0.44
0.41
0.32
0.51
1,297.41
Assist Tug
131.00
3.60
3.31
3.60
3.31
2.55
5.25
8,502.12
Towboat
11.00
0.32
0.29
0.32
0.29
0.22
0.33
658.08
Total
159.00
4.36
4.01
4.36
4.01
3.09
6.09
10,457.61
2025
Articulated
Tug Barge
18.03
0.46
0.43
0.46
0.43
0.33
0.56
1,550.42
Assist Tug
138.96
3.77
3.47
3.77
3.47
2.67
5.77
10,160.03
Towboat
11.67
0.34
0.30
0.34
0.30
0.23
0.36
786.40
Total
168.66
4.57
4.20
4.57
4.20
3.23
6.69
12,496.85
2035
Articulated
Tug Barge
30.40
0.77
0.71
0.77
0.71
0.55
0.99
2,991.85
Assist Tug
234.23
6.26
5.76
6.26
5.76
4.44
10.15
19,605.88
Towboat
19.67
0.56
0.50
0.56
0.50
0.39
0.64
1,517.53
Total
284.29
7.59
6.98
7.59
6.98
5.37
11.78
24,115.26
61 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
5-4
-------
5.2 Emission Reduction Strategies and Scenarios
The following emission reduction strategies were selected in consultation between EPA and
Port Everglades:
• Engine replacement (to Tier 3)
• Vessel replacement (to Tier 4)
Because Port Everglades does not have direct control over implementing these strategies, the
hypothetical scenarios for each are predicated on the assumption of the coordination and
collaboration of various maritime industry stakeholders for implementation. Several factors
were considered when developing these strategies, including the specific vessel types best
targeted by each strategy as well as the feasibility of implementation. As part of EPA's
consultation with Port Everglades, the Port shared its non-confidential vessel call log with EPA,
which allowed for more detail in this portion of the analysis.
Based on the age distribution of the tug and towboat fleet and the expected remaining life for
most vessels at Port Everglades, it was determined that there are many Tier 0 vessels that could
be candidates for engine or vessel replacement with cleaner diesel technologies; therefore,
only these types of technologies were included in this analysis.62 Since engine replacement on
older vessels to Tier 4 engines may not always be possible due to engine room and other vessel-
based limitations, the engine replacement strategy assumes that Tier 0 engines will be replaced
with Tier 3 engines. Since new vessels do not have this structural limitation, the vessel
replacement strategy assumes that the replacement vessels will be equipped with Tier 4
engines.
Table 5-6. On-port Harbor Craft Emission Reduction Factors by Strategy
Strategy
Notes
NOx
PMio
PM;.5
DPM
BC
VOC
Engine Replacement
Per vessel reductions from
replacing Tier 0 with Tier 3
44.7%
80.6%
80.6%
80.6%
80.6%
__a
Vessel Replacement
Per vessel reductions from
replacing Tier 0 with Tier 4
86.4%
94.4%
94.4%
94.4%
94.4%
62.0%
a VOC emission reductions from engine replacement were not calculated as part of this analysis.
Table 5-6 shows the percent emission reductions assumed for these two strategies by pollutant.
As Tier 3 and 4 emission standards for marine engines do not address greenhouse gas
emissions, these pollutants are not included in Table 5-6. Additionally, since the 2050 analysis
only included greenhouse gas pollutants, emission reductions for 2050 were not calculated for
62 Harbor craft shore power was not evaluated in this analysis because the 2015 On-port Baseline Inventory did
not present harbor craft at-berth emissions separately from the total harbor craft emissions; consequently,
there was not enough detail available to include this strategy.
5-5
-------
harbor craft.63 The emission reduction values presented in Table 5-6 were applied to the 2025
and 2035 BAU inventories for the number of vessels affected by each scenario, as summarized
in Table 5-7.
Table 5-7. Summary of On-port Emission Reduction Scenarios for Harbor Craft
Strategy
Scenario
Implementation Rates
Notes
2025
2035
Engine
Replacement
Low
20% (8 vessels)
20% (6 vessels)
Replacing Tier 0 engines with
Tier 3 engines
High
30% (13 vessels)
30% (8 vessels)
Vessel
Replacement
Low
10% (4 vessels)
10% (3 vessels)
Replacing Tier 0 vessels with
Tier 4 vessels
High
20% (8 vessels)
20% (6 vessels)
5.3 Emission Reduction Scenario Results and Lessons Learned
The projected emission reductions by scenario are summarized in Figure 5-1, Figure 5-2, and
Table 5-8 for on-port harbor craft operations. Table 5-9 shows the percent emission reductions
for each scenario relative to total on-port harbor craft emissions for tugs and towboats. This
analysis shows that due to the longevity of tugs and towboats, significant emission reductions
may be possible through voluntary programs that support the replacement of older engines
and vessels. While normal fleet turnover to newer emission standards can reduce the BAU
growth in emissions, accelerated engine and vessel replacement have the potential to reduce
total harbor craft emissions above what is projected in the BAU case. The reductions possible
in 2025 are greater than those in 2035 because there are more vessels available for
replacement (i.e., older vessels) in earlier years.
This analysis benefited from knowing the age distribution of the tug and towboat fleet
operating at Port Everglades. A more detailed baseline inventory, such as separating hotelling
emissions from other operating modes, could have enabled the analysis of additional strategies,
such as anti-idling measures or the application of shore power for harbor craft.
63 Note that there are technologies involving electrification that do address greenhouse gases in addition to shore
power that were not included here. For more information, see EPA's National Port Strategy Assessment,
https://www.epa.gov/ports-initiative/national-port-strategy-assessment-reducing-air-pollution-and-
greenhouse-gases-us.
5-6
-------
_ 30
i—
H3
(D
>; 25
to
C
o
ii 20
£ 15
10 ¦¦ ¦ 2035
12025
Engine Replacement Engine Replacement Vessel Replacement Vessel Replacement
(Low) (High) (Low) (High)
Figure 5-1. On-port Harbor Craft NOx Reduction Strategies
_ 1.2
i—
CD
(D
>; 1.0
to
C
o
ii 0.8
¦B 0.6
0.0
0.4 ¦¦ ¦¦ ¦ 2035
0.2
ll
12025
Engine Replacement Engine Replacement Vessel Replacement Vessel Replacement
(Low) (High) (Low) (High)
Figure 5-2. On-port Harbor Craft PM2.5 Reduction Strategies
Table 5-8. Total Reductions from BAU On-port Harbor Craft Emissions by Scenario
Year
Strategy
Scenario
Emission Reductions
tons/year)
NOx
PM10
PM2.5
DPM10
DPM2.5
BC
voc
2025
Engine Replacement
Low
13.93
0.69
0.63
0.69
0.63
0.49
a
High
22.63
1.12
1.03
1.12
1.03
0.79
--
Vessel Replacement
Low
13.46
0.40
0.37
0.40
0.37
0.28
0.37
High
26.92
0.81
0.74
0.81
0.74
0.57
0.75
2035
Engine Replacement
Low
10.45
0.52
0.48
0.52
0.48
0.37
--
High
13.93
0.69
0.63
0.69
0.63
0.49
--
Vessel Replacement
Low
10.10
0.30
0.28
0.30
0.28
0.22
0.28
High
20.19
0.61
0.56
0.61
0.56
0.43
0.56
5-7
-------
Table 5-9. Percent Reductions from BAU On-port Harbor Craft Emissions by Scenario
Year
Strategy
Scenario
Percent Reductions from BAU Emissions
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
2025
Engine Replacement
Low
8.26%
15.10%
15.00%
15.10%
15.00%
15.17%
--
High
13.42%
24.51%
24.52%
24.51%
24.52%
24.46%
--
Vessel Replacement
Low
7.98%
8.75%
8.81%
8.75%
8.81%
8.67%
5.53%
High
15.96%
17.72%
17.62%
17.72%
17.62%
17.65%
11.21%
2035
Engine Replacement
Low
3.68%
6.85%
6.88%
6.85%
6.88%
6.89%
--
High
4.90%
9.09%
9.03%
9.09%
9.03%
9.12%
--
Vessel Replacement
Low
3.55%
3.95%
4.01%
3.95%
4.01%
4.10%
2.38%
High
7.10%
8.04%
8.02%
8.04%
8.02%
8.01%
4.75%
a A double dash represents a value that was not calculated as part of this analysis.
5-8
-------
6. CARGO HANDLING EQUIPMENT
Cargo handling equipment (CHE) includes nonroad equipment that are critical for moving cargo,
passenger luggage, products, and supplies on and off vessels and around the port. The
following CHE types in operation at Port Everglades were included in EPA's analysis:
This section begins with an overview of the baseline emissions inventory and projected
Business as Usual (BAU) emissions for CHE (Section 6.1), which is followed by a presentation of
the hypothetical CHE emission reduction strategies and scenarios (Section 6.2) and a discussion
of the key results and lessons learned (Section 6.3).
6.1 Baseline and Projected Business as Usual Inventories
The 2015 On-port Baseline Inventory64 includes emissions for each piece of CHE operating at
Port Everglades using data on equipment counts, engine characteristics, and activity. Existing
relationships between Port Everglades and its tenants were critical for obtaining this supporting
information through confidential surveys of terminal and facility operational managers.65
Only emissions from diesel CHE are considered in EPA's analysis, since emissions from the few
gasoline and propane CHE at Port Everglades (6 and 10 units, respectively) are not impacted by
the strategies and scenarios presented in Section 6.3. The presented emission inventories
include pollutants from the 2015 On-port Baseline Inventory, in addition to DPM2.5 and BC.6667
C02e results were converted from metric tons in that report to short tons here for consistency
with the other pollutants. Given the sole focus on diesel CHE, the baseline PM and DPM
inventories are identical. Note that the CHE baseline inventory only covers equipment
operating on the port; no off-port CHE was considered in this analysis. For additional details on
the data collection and baseline inventory development methodology, please refer to the 2015
On-port Baseline Inventory.
64 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
65 Note that EPA did not receive any confidential business or terminal-specific information through the
partnership.
66 DPM2.5 emissions were calculated to be equal to PM2.5 emissions, and BC emissions were calculated to be 34.9%
of PM2.5 emissions. The BC fraction is based on EPA's SPECIATE 4.3 repository.
67 U.S. Environmental Protection Agency, SPECIATE 4.3, September 2011, https://www.epa.gov/air-emissions-
modeling/speciate-version-45-through-4Q.
Aerial lifts
Cranes
Empty container handlers
Excavators
• Power packs
• Reach stackers
• Rubber tired gantry (RTG) cranes
• Scissor lifts
• Skid steer loaders
• Sweepers
• Top loaders
• Yard tractors
Forklifts
Loaders
Manlifts
Off-highway trucks
6-1
-------
In line with the 2014 Master/Vision Plan,68 a hypothetical Business as Usual scenario was
developed based on anticipated growth and changes at Port Everglades. The growth factors in
Table 6-1 are based on projected throughput of container freight at the Port, which was used as
a surrogate for growth of CHE operations, and were applied directly to the unit-specific baseline
data to estimate future emissions.69
Table 6-1. Projected Growth Factors Used for Future CHE Activity
Vessel/Cargo Type
Projected Throughput (TEUsa)
Growth Factor (unitless)
2015
2025
2035
2050
2015
2025
2035
2050
Container
1,060,000
1,435,000
1,761,000
2,134,000
1.000
1.354
1.661
2.013
a Twenty-foot equivalent units
In addition to accounting for anticipated growth in port traffic in emission estimates, the
hypothetical estimates were adjusted to reflect the incorporation of newer equipment that
complies with the latest emission standards70 based on past fleet turnover rates. The
methodology used to estimate engine tier level distributions for 2025, 2035, and 2050 ensures
that the in-use model year distributions for future analysis years are consistent with the 2015
baseline distribution. The resulting CHE counts by tier level in each analysis year are presented
in Table 6-2, while Table 6-3 summarizes the projected population and average tier level of
each CHE type by analysis year.
Table 6-2. Baseline and Projected CHE Count by Tier Level
Tier
2015
2025
2035
2050
TierO
45
26
7
4
Tier 1
38
30
20
8
Tier 2
196
142
56
2
Tier 3
108
125
30
8
Tier 4
36
250
590
829
Total
423
573
703
851
68 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
69 Growth factors for 2035 and 2050 are not included in the range of projections provided in the 2014
Master/Vision Plan cited in this report. Therefore, the factors were extrapolated from expected growth
between 2028 and 2033, the last five years presented in the 2014 Master/Vision Plan.
70 U.S. Environmental Protection Agency, Nonroad Compression-Ignition Engines: Exhaust Emission Standards,
March 2016, https://nepis.epa.gov/Exe/ZvPDF.cgi?Dockev=P100QA05.pdf.
6-2
-------
Table 6-3. CHE Count and Average Tier Level by BAU Year
Equipment Type
2025
2035
2050
Count
Average
Tier Level
Count
Average
Tier Level
Count
Average
Tier Level
Aerial Lifts
4
2
5
2
6
2
Cranes
5
3
6
4
8
4
Empty Container Handlers
3
4
3
4
4
4
Excavators
1
3
2
3
2
4
Forklifts
241
3
294
4
356
4
Loaders
1
3
2
3
2
3
Manlifts
1
1
2
1
2
1
Off-highway Trucks
5
3
7
3
8
4
Power Packs
7
4
8
4
10
4
Reach Stackers
5
4
6
4
8
4
RTG Cranes
4
4
5
4
6
4
Scissor Lifts
5
2
7
2
8
4
Skid Steer Loaders
1
0
2
0
2
0
Sweepers
4
3
5
3
6
4
Top Loaders
74
3
90
4
109
4
Yard Tractors
212
3
259
4
314
4
Total
573
a
703
--
851
--
a A double dash represents a value that was not calculated as part of this analysis.
For most pollutants, per-unit projected BAU emissions were calculated71 by multiplying the
equipment type-specific emission factor—extracted from MOVES2014a-NONROAD72 outputs—
by the product of annual operating hours, rated horsepower, and load factor. Because the
MOVES model does not produce N2O or BC estimates, fuel-based emission factors for N2O and
the elemental carbon fraction of PM2.5 were used to estimate these emissions.
Table 6-4 presents the CHE 2015 baseline inventory results. A summary of projected CHE BAU
emissions are presented in Table 6-5, Table 6-6, and Table 6-7 for the analysis years 2025, 2035,
and 2050, respectively.
Even though freight traffic activities are projected to increase during the 2015-2035 period,
aggregate emissions for most considered pollutants do not increase in the BAU scenario due to
expected fleet turnover of older, high-emitting equipment with newer diesel equipment that
meets EPA's latest emission standards. However, emissions could be further reduced by
71 For average rated horsepower, average annual operating hours, assumed load factor, and MOVES2014a-
NONROAD source classification code (SCC) by CHE type, see Tables 5.1 and 5.2 of the 2015 On-port Baseline
Inventory.
72 EPA's MOtor Vehicle Emission Simulator (MOVES) is a state-of-the-science emission modeling system that
estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants,
greenhouse gases, and air toxics. For more information, see https://www.epa.gov/moves.
6-3
-------
voluntarily implementing the hypothetical emission reduction strategies presented in the
following section.
Table 6-4. 2015 Baseline Emissions for On-port CHE
Equipment Type
Annual Emissions (tons/year)73
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
VOC
CChe
Aerial Lifts
0.16
0.02
0.02
0.02
0.02
0.01
0.03
18.74
Cranes
13.72
0.70
0.68
0.70
0.68
0.24
1.07
2,925.53
Empty Container Handlers
1.24
0.06
0.06
0.06
0.06
0.02
0.11
155.43
Excavators
0.19
0.02
0.02
0.02
0.02
0.01
0.01
38.58
Forklifts
28.06
2.83
2.74
2.83
2.74
0.96
4.86
3,571.48
Loaders
0.07
0.01
0.01
0.01
0.01
0.00
0.01
13.23
Manlifts
0.03
0.00
0.00
0.00
0.00
0.00
0.01
3.31
Off-highway Trucks
0.26
0.04
0.03
0.04
0.03
0.01
0.02
60.63
Power Packs
22.90
1.08
1.04
1.08
1.04
0.36
1.92
2,087.78
Reach Stackers
1.28
0.04
0.04
0.04
0.04
0.01
0.19
610.68
RTG Cranes
0.12
0.00
0.00
0.00
0.00
0.00
0.06
263.45
Scissor Lifts
0.05
0.01
0.01
0.01
0.01
0.00
0.01
5.51
Skid Steer Loaders
0.04
0.01
0.01
0.01
0.01
0.00
0.01
3.31
Sweepers
0.14
0.01
0.01
0.01
0.01
0.00
0.01
34.17
Top Loaders
74.01
2.67
2.59
2.67
2.59
0.90
4.30
8,935.32
Yard Tractors
75.89
6.32
6.12
6.32
6.12
2.14
12.19
8,531.88
Total
218.16
13.82
13.38
13.82
13.38
4.66
24.81
27,259.02
73 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
6-4
-------
Table 6-5. 2025 BAU Emissions for On-port CHE
Equipment Type
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
VOC
CChe
Aerial Lifts
0.22
0.03
0.03
0.03
0.03
0.01
0.04
28.98
Cranes
30.48
0.77
0.75
0.77
0.75
0.26
1.42
4,387.19
Empty Container Handlers
0.11
0.00
0.00
0.00
0.00
0.00
0.06
232.09
Excavators
0.26
0.03
0.03
0.03
0.03
0.01
0.02
57.96
Forklifts
23.23
2.18
2.11
2.18
2.11
0.74
2.16
5,207.63
Loaders
0.09
0.01
0.01
0.01
0.01
0.00
0.01
19.98
Manlifts
0.05
0.01
0.01
0.01
0.01
0.00
0.01
5.00
Off-highway Trucks
0.35
0.05
0.05
0.05
0.05
0.02
0.03
89.94
Power Packs
1.48
0.04
0.04
0.04
0.04
0.01
0.81
3,136.57
Reach Stackers
1.73
0.07
0.07
0.07
0.07
0.02
0.25
915.86
RTG Cranes
0.16
0.00
0.00
0.00
0.00
0.00
0.09
394.97
Scissor Lifts
0.06
0.01
0.01
0.01
0.01
0.00
0.02
8.00
Skid Steer Loaders
0.05
0.01
0.01
0.01
0.01
0.00
0.02
4.00
Sweepers
0.16
0.01
0.01
0.01
0.01
0.00
0.01
27.98
Top Loaders
26.16
0.99
0.96
0.99
0.96
0.34
3.91
13,405.91
Yard Tractors
36.02
2.93
2.84
2.93
2.84
0.99
4.97
12,779.35
Total
120.61
7.14
6.93
7.14
6.93
2.42
13.83
40,704.41
6-5
-------
Table 6-6. 2035 BAU Emissions for On-port CHE
Equipment Type
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
VOC
CChe
Aerial Lifts
0.27
0.04
0.03
0.04
0.03
0.01
0.05
34.98
Cranes
37.39
0.95
0.92
0.95
0.92
0.32
1.74
5,380.01
Empty Container Handlers
0.14
0.01
0.01
0.01
0.01
0.00
0.08
285.05
Excavators
0.32
0.03
0.03
0.03
0.03
0.01
0.02
69.96
Forklifts
13.73
0.57
0.56
0.57
0.56
0.19
1.77
6,390.31
Loaders
0.11
0.02
0.02
0.02
0.02
0.01
0.02
23.98
Manlifts
0.06
0.01
0.01
0.01
0.01
0.00
0.01
6.00
Off-highway Trucks
0.43
0.06
0.06
0.06
0.06
0.02
0.04
111.92
Power Packs
1.82
0.06
0.06
0.06
0.06
0.02
1.00
3,848.32
Reach Stackers
1.22
0.02
0.02
0.02
0.02
0.01
0.30
1,122.72
RTG Cranes
0.19
0.01
0.01
0.01
0.01
0.00
0.11
483.91
Scissor Lifts
0.08
0.01
0.01
0.01
0.01
0.00
0.02
10.00
Skid Steer Loaders
0.06
0.02
0.02
0.02
0.02
0.01
0.02
5.00
Sweepers
0.19
0.01
0.01
0.01
0.01
0.00
0.01
33.98
Top Loaders
12.77
0.38
0.37
0.38
0.37
0.13
4.35
16,443.56
Yard Tractors
9.64
0.42
0.40
0.42
0.40
0.14
4.20
15,679.83
Total
78.42
2.60
2.52
2.60
2.52
0.88
13.73
49,929.53
6-6
-------
Table 6-7. 2050 BAU Emissions for On-port
CHE
Equipment Type
Annual C02e
Emissions (tons/year)
Aerial Lifts
43.11
Cranes
6,521.54
Empty Container Handlers
345.53
Excavators
87.04
Forklifts
7,746.66
Loaders
28.32
Manlifts
8.43
Off-highway Trucks
135.26
Power Packs
4,663.77
Reach Stackers
1,361.42
RTG Cranes
586.24
Scissor Lifts
13.02
Skid Steer Loaders
7.31
Sweepers
41.86
Top Loaders
19,929.85
Yard Tractors
19,001.83
Total
60,521.19
6.2 Emission Reduction Strategies and Scenarios
The following CHE emission reduction strategies were modeled for diesel-powered CHE:
• Retrofit with diesel particulate filters (DPFs)
• Retrofit with diesel oxidation catalysts (DOCs)
• Replace older equipment with cleaner diesel and/or electric technologies
• Replace with new alternative fuel units (i.e., liquefied petroleum gas [LPG] or
compressed natural gas [CNG])
• Reefer power pack electrification
These strategies were developed in consultation with Port Everglades based on the
characteristics of the port. The associated emission reduction scenarios are summarized in
Table 6-8, which provides the number of units affected by each scenario in years 2025, 2035,
and 2050, assuming low and high implementation rates.
CHE units with the greatest potential for future emission reductions, i.e., younger units that do
not meet the latest emission standards, were specifically targeted by the retrofit and
replacement scenarios. As a result, adoption rates of most of the considered CHE strategies
were highly dependent on tier level and engine age distribution in each of the analysis years.
6-7
-------
The number of units targeted for retrofit or replacement in the first projection year, 2025, was
calculated by multiplying the projected number of units in each tier level in Table 6-2 by the
technology penetration percentages in Table 6-8.
Note that by targeting CHE with the longest remaining useful life, some older units are not
included in this strategy. However, it is assumed that these older units will be retired and
replaced through natural attrition in higher proportions than average. This "accelerated
retirement" effect was considered when defining the "high" retrofit scenarios in 2035; the
underlying assumption is that all potential targets for these scenarios have been removed from
the fleet through attrition by this year and, thus, the number of targeted units is 0.
Additionally, note that only strategies that had a quantifiable impact on greenhouse gas
emissions were included for 2050.
The hypothetical CHE emission reduction strategies are described in more detail in Sections
6.2.1 through 6.2.4.
6-8
-------
Table 6-8. Summary of Emission Reduction Scenarios for On-port CHE
Strategy
Affected
Equipment
Types
Scenario
Units Targeted
Percent Implementation by Engine Tier and Analysis Yeara
2025
2035
2050
Retrofit with DPFs
All pre-Tier 4
diesel
Low
95*
30**
N/A
* 50% Tier 0 and 1, 25% Tier 2 and 3
** 100% Tier 0 and 1,50% Tier 2 and 3
High
190*
o**
N/A
* 100% Tier 0 and 1, 50% Tier 2 and 3
** 100% Tier 0 and 1, 75% Tier 2 and 3
Retrofit with DOCs
All pre-Tier 4
diesel
Low
95*
30**
N/A
* 50% Tier 0 and 1, 25% Tier 2 and 3
** 100% Tier 0 and 1,50% Tier 2 and 3
High
190*
o**
N/A
* 100% Tier 0 and 1, 50% Tier 2 and 3
** 100% Tier 0 and 1, 75% Tier 2 and 3
Replace older equipment
with cleaner diesel
and/or electric
technologies
All diesel
Low
112*
123**
366***
* 100% Tier 0 and 50% of Tier 1 and 2 replaced with 50% Tier
3 and 50% Tier 4
** 100% Tier 0-3 replaced with 50% Tier 4 and 50% electric;
10% Tier 4 replaced with electric
*** 100% Tier 0-3 replaced with electric; 50% Tier 4 replaced
with electric
High
198*
236**
382***
* 100% Tier 0-2 replaced with 75% Tier 4 and 25% electric
** 100% Tier 0-3 replaced with 50% Tier 4 and 50% electric;
25% Tier 4 replaced with electric
*** 100% Tier 0-3 replaced with electric; 75% Tier 4 replaced
with electric
Replace with new
alternative fuel units
All pre-Tier 4
diesel
Low
49*
43**
N/A
* 25% Tier 0-2 replaced with alt. fuel meeting Tier 4
** 50% Tier 0-3 replaced with alt. fuel meeting Tier 4
High
100*
32**
N/A
* 50% Tier 0-2 replaced with alt. fuel meeting Tier 4
** 75% Tier 0-3 replaced with alt. fuel meeting Tier 4
Reefer electrification
Power packs
High
7*
1*
2*
* 100% of units replaced with electric
a Percentages reflect the proportion of equipment being retrofitted/replaced, relative to the scenario populations by engine tier and analysis year.
6-9
-------
6.2.1 Retrofit with Diesel Particulate Filters or Diesel Oxidation Catalysts
Of the considered retrofit strategies, DPFs are effective at reducing PM and VOC emissions,
while DOCs facilitate a reaction between PM, VOCs, and CO in the exhaust steam of an engine
to produce CO2 and water.
The anticipated emission reductions from retrofitting CHE with DPFs and DOCs are based on
data from the California Air Resources Board (ARB) and EPA's list of verified retrofit systems for
nonroad mobile equipment.7475 Approximately 20 DPF retrofit technologies are currently
verified by EPA and each is associated with PM and VOC reductions of 90 percent. Two DOC
retrofit products are verified, with documented reductions for PM and VOCs of 20 percent and
80 percent, respectively. These emission reduction factors were applied to the target fraction
of the Tier 0-3 equipment emissions from the BAU case, as specified by the assumed
implementation rates listed in Table 6-8.
6.2.2 Replace Older Equipment
Replacing older diesel equipment with equipment meeting Tier 4 standards can reduce
emissions because Tier 4 engines emit significantly less pollution than earlier models.76 This
strategy also includes engine replacements to Tier 4 engines as well as upgrades to hybrid or
full-battery electric systems.
The emission reductions associated with this scenario were modeled by assuming that new
diesel and hybrid engines have the same emission rates as corresponding new Tier 3 and Tier 4
units, while fully electric units were assumed to have zero tailpipe emissions.77 Tier 3 units
were assigned a model year of 2008, while Tier 4 units were assumed to be new in each
analysis year.
6.2.3 Use of Alternative Fuels
Shifting from diesel to alternative fuel systems is an effective way to reduce NOx and PM
emissions. The emission reductions associated with this shift were derived from LPG and CNG
emission rates extracted from MOVES2014a-NONROAD output. Since LPG and CNG emission
factors were not available for all considered CHE types, several cross-type substitutions were
made, as documented in Table 6-9. Deviations in horsepower across matches were not
expected to significantly impact results, as MOVES g/bhp-hr emission factors are similar across
horsepower bins for a given source classification code (SCC).
74
75
gov/diesel/verdev/vt/cvt.htm.
List of ARB-verified retrofits available at: httpsi//www,arb,ca
List of EPA-verified retrofits available at: https://www.esi
clean-diesel.
U.S. Environmental Protection Agency, Nonroad Compression-Ignition Engines: Exhaust Emission Standards,
March 2016, https://nepis.epa.goy/Exe/ZyPDF.cgi?Dockey=P1000A05.pdf.
Upstream emissions for replacing equipment with electric models were not included in this analysis.
6-10
-------
Table 6-9. Matching Diesel CHE to Alternative Fuel Equipment
Diesel CHE
Alternative Fuel CHE
Equipment Type
see
HP Bin
Equipment Type
HP Bin
Diesel Excavators
2270002036
600
N/Aa
Diesel Cranes
2270002045
3000
LPG Cranes
175
Diesel Off-highway Trucks
2270002051
175
LPG Forklifts
175
Diesel Skid Steer Loaders
2270002072
75
LPG Skid Steer Loaders
75
Diesel Skid Steer Loaders
2270002072
300
LPG Skid Steer Loaders
100
Diesel Aerial Lifts
2270003010
40
LPG Aerial Lifts
40
Diesel Aerial Lifts
2270003010
100
LPG Aerial Lifts
75
Diesel Aerial Lifts
2270003010
175
LPG Aerial Lifts
175
Diesel Forklifts
2270003020
75
CNG Forklifts
50
Diesel Forklifts
2270003020
100
CNG Forklifts
50
Diesel Forklifts
2270003020
175
CNG Forklifts
50
Diesel Sweepers
2270003030
75
CNG Sweepers
300
Diesel Other General
Industrial Equipment
2270003040
600
CNG Other General Industrial
Equipment
100
Diesel Yard Tractors
2270003070
175
CNG Yard Tractors
175
a The CHE inventory included only one excavator, and there was no suitable equipment-horsepower
surrogate available from the MOVES2014a-NONROAD model. Therefore, the excavator was excluded
from the low and high alternative fuel scenarios (i.e., the excavator remains diesel-fueled).
To estimate BC reductions, the ratio of elemental carbon to exhaust PM2.5 (0.0955), derived
from MOVES2014a onroad output, was applied. The impact of the alternative fuel strategies on
CChe and VOC emissions were not included due to uncertainty in accurately quantifying the
impact of methane slippage.
6.2.4 Reefer Electrification
Emission reductions are possible by electrifying the power packs used to power refrigerated
containers while dockside. The associated emission reductions were estimated by assuming
that a proportion of power packs, given the number of units targeted, produces zero emissions
in each analysis year. Note that upstream emissions associated with this strategy were not
included in this analysis.
6.3 Emission Reduction Scenario Results and Lessons Learned
The emission reductions from the hypothetical CHE strategies and scenarios are summarized in
Figure 6-1, Figure 6-2, Figure 6-3, and Table 6-10 for each analysis year. Table 6-11 displays
these emission reductions as a percentage of total CHE emissions for each pollutant. Since just
CChe emission reductions are presented for 2050, only the strategies that impact greenhouse
gas emissions (i.e., replace with cleaner diesel and/or electric technologies and reefer
electrification) are presented for that year.
6-11
-------
Given high implementation assumptions, retrofitting diesel CHE with DPFs is projected to
reduce PM and DPM emissions by 49 percent in 2025 and 33 percent in 2035, while retrofitting
diesel CHE with DOCs is associated with PM and DPM emission reductions of 11 and 7 percent
in 2025 and 2035, respectively. Replacing older CHE with advanced technology engines or
alternative fuel units was determined to be feasible for reducing emissions over a broad range
of pollutants and engine sizes. Specifically, the equipment replacement strategy is associated
with NOx emission reductions of 21 percent in 2025 and 69 percent in 2035 under low
implementation and 40 percent in 2025 and 76 percent in 2035 under high implementation.
The effectiveness of the considered emission control strategies was found to be sensitive to
expected hours of use and remaining engine life of targeted units, highlighting the importance
of accurate inputs for the development of realistic emission projections. This analysis benefited
from the availability of highly detailed fleet characterization data (e.g., engine-specific model
year, horsepower, and annual hours of operation data), which facilitated a detailed emissions
inventory and allowed for precise evaluations of emission reduction scenarios.
70
60
C
o
o
¦a
(D
cc
c
o
50
40
30
20
E 10
ll
i. Ii
12025
12035
Replacement Replacement Alt. Fuels (Low) Alt. Fuels (High) Reefer
(Low) (High) Electrification
(High)
Figure 6-1. On-port CHE NOx Reduction Strategies
6-12
-------
3.5
$ 3.0
s-
.1 2'°
+-»
o
¦i 1-5
(D
al
c 1.0
o
'to
0.5
0.0
i
i.
i. I.
12025
12035
DPFs (Low) DPFs (High) DOCs (Low) DOCs (High) Repower/ Repower/ Alt. Fuels
Replace (Low) Replace (High) (Low)
Figure 6-2. On-port CHE PM2.5 Reduction Strategies
Alt. Fuels
(High)
Reefer
Electrification
(High)
50,000
45,000
> 40,000
to
o 35,000
c 30,000
0
25,000
1 20,000
.2 15,000
£ 10,000
LU
5,000
0
12025
12035
2050
I
Replacement (Low) Replacement (High) Reefer Electrification (High)
Figure 6-3. On-port CHE C02e Reduction Strategies
6-13
-------
Table 6-10. Total Reductions from BAU On-port CHE Emissions by Scenario
Year
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
DPFs
Low
a
2.06
2.00
2.06
2.00
0.70
2.95
--
High
--
3.47
3.37
3.47
3.37
1.18
4.08
--
DOCs
Low
--
0.46
0.44
0.46
0.44
0.16
2.63
--
High
--
0.80
0.78
0.80
0.78
0.27
3.82
--
2025
Equipment Replacement
Low
25.37
1.42
1.37
1.42
1.37
0.48
1.11
0.00
High
48.19
3.17
3.07
3.17
3.07
1.07
3.02
2,091.53
Alternative Fuels
Low
16.36
0.82
0.79
0.82
0.79
0.34
--
--
High
21.51
1.25
1.20
1.25
1.20
0.50
--
--
Reefer Electrification
High
1.48
0.04
0.04
0.04
0.04
0.01
0.81
3,136.57
DPFs
Low
--
0.74
0.72
0.74
0.72
0.25
0.79
--
High
--
0.85
0.82
0.85
0.82
0.29
0.90
--
DOCs
Low
--
0.17
0.16
0.17
0.16
0.06
0.71
--
High
--
0.19
0.18
0.19
0.18
0.06
0.80
--
2035
Equipment Replacement
Low
54.12
1.94
1.88
1.94
1.88
0.66
4.71
13,041.27
High
59.74
2.23
2.16
2.23
2.16
0.75
7.42
24,751.53
Alternative Fuels
Low
7.68
0.52
0.50
0.52
0.50
0.21
--
--
High
9.39
0.72
0.69
0.72
0.69
0.28
--
--
Reefer Electrification
High
1.82
0.06
0.06
0.06
0.06
0.02
1.00
3,848.32
Equipment Replacement
Low
--
--
--
--
--
--
--
42,848.10
2050
High
--
--
--
--
--
--
--
46,535.95
Reefer Electrification
High
--
--
--
--
--
--
--
4,663.77
a A double dash represents a value that was not calculated as part of this analysis.
6-14
-------
Table 6-11. Percent Reductions from BAU On-port CHE Emissions by Scenario
Year
Strategy
Scenario
Percent Reductions from BAU Emissions
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
DPFs
Low
a
28.85%
28.86%
28.85%
28.86%
28.93%
21.33%
--
High
--
48.60%
48.63%
48.60%
48.63%
48.76%
29.50%
--
DOCs
Low
--
6.44%
6.35%
6.44%
6.35%
6.61%
19.02%
--
High
--
11.20%
11.26%
11.20%
11.26%
11.16%
27.62%
--
2025
Equipment Replacement
Low
21.03%
19.89%
19.77%
19.89%
19.77%
19.83%
8.03%
0.00%
High
39.96%
44.40%
44.30%
44.40%
44.30%
44.21%
21.84%
5.14%
Alternative Fuels
Low
13.56%
11.48%
11.40%
11.48%
11.40%
14.05%
--
--
High
17.83%
17.51%
17.32%
17.51%
17.32%
20.66%
--
--
Reefer Electrification
High
1.23%
0.56%
0.58%
0.56%
0.58%
0.41%
5.86%
7.71%
DPFs
Low
--
28.46%
28.57%
28.46%
28.57%
28.41%
5.75%
--
High
--
32.69%
32.54%
32.69%
32.54%
32.95%
6.55%
--
DOCs
Low
--
6.54%
6.35%
6.54%
6.35%
6.82%
5.17%
--
High
--
7.31%
7.14%
7.31%
7.14%
6.82%
5.83%
--
2035
Equipment Replacement
Low
69.01%
74.62%
74.60%
74.62%
74.60%
75.00%
34.30%
26.12%
High
76.18%
85.77%
85.71%
85.77%
85.71%
85.23%
54.04%
49.57%
Alternative Fuels
Low
9.79%
20.00%
19.84%
20.00%
19.84%
23.86%
--
--
High
11.97%
27.69%
27.38%
27.69%
27.38%
31.82%
--
--
Reefer Electrification
High
2.32%
2.31%
2.38%
2.31%
2.38%
2.27%
7.28%
7.71%
Equipment Replacement
Low
--
--
--
--
--
--
--
70.80%
2050
High
--
--
--
--
--
--
--
76.89%
Reefer Electrification
High
--
--
--
--
--
--
--
7.71%
a A double dash represents a value that was not calculated as part of this analysis.
6-15
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7. ONROAD VEHICLES
Onroad vehicles at Port Everglades include heavy-duty diesel trucks that are used to move
cargo in and out of the port, light-duty and medium-duty vehicles that transport passengers to
and from the cruise ship terminals, and vehicles owned and operated by the Port. Specifically,
emissions from passenger cars, transit buses, light trucks/vans, and heavy-duty trucks are
considered in EPA's analysis, although the strategy scenarios target only heavy-duty diesel
trucks. This section of the report includes the on-port emissions from onroad vehicles. The
associated off-port emissions are discussed in Section 9.3.
This section begins with a presentation of the baseline emissions inventory and projected
Business as Usual (BAU) emissions for onroad vehicles (Section 7.1). This is followed by a
discussion of the considered emission reduction strategies and scenarios to reduce onroad
emissions (Section 7.2) and the primary results and lessons learned (Section 7.3).
7.1 Baseline and Projected Business as Usual Inventories
The 2015 On-port Baseline Inventory78 contains onroad emission estimates from trucks,
passenger vehicles, and Port-owned vehicles based on gate counts and confidential surveys of
terminal and facility operational managers. EPA did not receive any confidential business or
terminal-specific information through the partnership. For details on the data collection and
inventory development methodology, please see the 2015 On-port Baseline Inventory.
The onroad baseline inventory presented here includes the information from the 2015 On-port
Baseline Inventory as well as DPM2.5 and BC, which EPA added for its analysis.79 80 Additionally,
the C02e results, which were presented in metric tons in the baseline inventory, were
converted to short tons for consistency with the other pollutants.
A hypothetical BAU scenario was developed based on anticipated growth and changes at Port
Everglades as identified in the 2014 Master/Vision Plan.81 Expected growth in containerized
throughput was used to project future heavy-duty truck activity, and growth in the number of
cruise passengers was used to project future light-duty and bus activity. These growth factors
are summarized in Table 7-1.82
78 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
79 DPM2.5 emissions were calculated relative to the PM2.5 emissions based on the ratio of diesel to gasoline
vehicles. All passenger cars were assumed to be gasoline and 6.5% of light-duty trucks and all heavy-duty
vehicles were assumed to be diesel. BC emissions were calculated to be 34.9% of PM2.5 emissions. The BC
fraction is based on EPA's SPECIATE 4.3 repository.
80 U.S. Environmental Protection Agency, SPECIATE 4.3, September 2011.
81 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
82 Growth factors for 2035 and 2050 are not included in the range of projections provided in the 2014
Master/Vision Plan cited in this report. Therefore, they were extrapolated from expected growth between
2028 and 2033, the last five years presented in the 2014 Master/Vision Plan.
7-1
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Table 7-1. Projected Growth Factors Used for Future Onroad Vehicle Activity
Vessel/Cargo Type
(units)
Projected Throughput
Growth Factor (unitless)
2015
2025
2035
2050
2015
2025
2035
2050
Cruise (passengers)
3,773,000
5,306,000
5,730,000
6,065,000
1.000
1.406
1.519
1.607
Container (TEUsa)
1,060,000
1,435,000
1,761,000
2,134,000
1.000
1.354
1.661
2.013
a Twenty-foot equivalent units
Hypothetical BAU emission inventories were then estimated for 2025, 2035, and 205083 by
starting with the 2015 baseline emissions, applying the growth factors by vessel or cargo type,
and then applying adjustment factors based on expected changes in the fleet emission factors.
The fleet emission factors change over time because as vehicles age out of the fleet, they are
replaced with newer vehicles that meet newer, cleaner emission standards. EPA's MOVES
model incorporates the effects of fleet turnover in its emission factors for future years.84 Table
7-2 presents the combined effect of the growth factors and changes in fleet emission factors,
which were derived from running MOVES2014a.
Table 7-2. BAU Emission Projection Factors for Onroad Vehicles
Year
Vehicle Type
Factors Relative to 2015 Emissions
NOx
PMio
PM2.5
DPM
BC
voc
CChe
2025
Passenger Car
0.14
0.95
0.84
0.00
0.84
0.10
0.92
Light Truck/Van
0.27
0.64
0.63
0.27
0.63
0.18
1.05
Transit Bus
0.46
0.39
0.39
0.39
0.39
0.46
1.36
Heavy Truck
0.46
0.36
0.36
0.36
0.36
0.41
1.26
2035
Passenger Car
0.06
0.69
0.61
0.00
0.61
0.07
0.84
Light Truck/Van
0.10
0.48
0.46
0.14
0.31
0.11
1.20
Transit Bus
0.20
0.14
0.14
0.14
0.05
0.12
1.61
Heavy Truck
0.29
0.14
0.14
0.14
0.04
0.21
1.51
2050
Passenger Car
a
-
-
-
-
-
0.78
Light Truck/Van
-
-
-
-
-
-
0.93
Transit Bus
-
-
-
-
-
-
1.52
Heavy Truck
-
-
-
-
-
-
1.83
a A double dash represents a value that was not calculated as part of this analysis.
The emission projection factors were then applied to each element of the on-port onroad
vehicle inventory. Note that for most of the criteria pollutants and precursors, the effect of
83 Note that for 2050, only CChe inventories and reductions were quantified.
84 EPA's MOtor Vehicle Emission Simulator (MOVES) is a state-of-the-science emission modeling system that
estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants,
greenhouse gases, and air toxics. For more information, see https://www.epa.gov/moves.
7-2
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fleet turnover outweighs the increase in activity in future years (as the factors are generally less
than 1).
Emission results for the 2015 baseline and 2025, 2035, and 2050 BAU onroad vehicle
inventories are presented in Table 7-3. Results in this table are expressed as short tons per
year. This analysis does not account for EPA's Heavy-Duty GHG Phase 2 rule85 because it is
currently not included in MOVES2014a.
Table 7-3. Baseline and Projected BAU Emissions for On-port Onroad Vehicles
Year
Annual Emissions (tons/year)
NOx
PMio
PMzs
DPMio
DPM2.5
BC
voc
C02ea
201586
54.04
3.96
3.65
3.94
3.64
1.69
5.99
11,887.31
2025
24.32
1.42
1.31
1.41
1.30
0.61
2.25
14,777.72
2035
15.54
0.56
0.52
0.55
0.51
0.07
1.16
17,558.34
2050
b
-
-
-
-
-
-
20,753.28
a CChe values were calculated based on a factor of 101.17 gallons per metric ton CC>2e and weighted by the 2015
on-port onroad baseline inventory mix of 85/15 diesel/gas consumption.
bA double dash represents a value that was not calculated as part of this analysis.
Even though onroad vehicle activity is assumed to increase in the future, criteria pollutant
emissions are projected to decrease due to the introduction of newer vehicles that meet
cleaner emission standards. However, for CChe, the increase in activity results in CChe
increases in the future.
7.2 Emission Reduction Strategies and Scenarios
The following on-port emission reduction strategies were selected in consultation between EPA
and Port Everglades:
• On-port truck idle reduction
• Additional operational improvements
• Truck replacement with cleaner diesel and electric technologies (e.g., 2007/2010
compliant trucks and battery electric vehicles [BEVs])
Because Port Everglades does not have direct control over implementing these strategies, the
hypothetical scenarios for each are predicated on the assumption of the coordination and
collaboration of various maritime industry stakeholders for implementation. The
implementation rates for all considered scenarios are provided in Table 7-4. Details on the
modeling approaches for these strategy scenarios are presented in Sections 7.2.1-7.2.3 below.
85 U.S. Environmental Protection Agency, Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium-
and Heavy-Duty Engines and Vehicles—Phase 2, Federal Register, Vol. 81, No. 206, October 25, 2016,
https://www.gpo.gov/fdsvs/pkg/FR-2016-10-25/pdf/2016-212Q3.pdf.
86 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
7-3
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Note that an additional strategy for reducing onroad emissions was also considered in this
analysis, a truck-to-rail intermodal shift, which is discussed in Section 8.
Table 7-4. Summary of On-port Emission Reduction Scenarios for Heavy-Duty Trucks
Strategy
Scenario
Implementation Rate
2025
2035
2050
Idle Reduction
Low
25% idle reduction
25% idle reduction
25% idle reduction
High
75% idle reduction
75% idle reduction
75% idle reduction
Operational
Improvements
Low
5% idle reduction
5% idle reduction
5% idle reduction
High
10% idle reduction
10% idle reduction
10% idle reduction
Truck
Replacement
Low
Replace 100% pre-2007
trucks with 50% 2007,
50% 2010+
Replace 100% pre-2010
trucks with 2010+
Replace 15% of 2010+
with BEV
Replace 30% 2010+ with
BEV
High
Replace 100% pre-2007
trucks with 40% 2007-
2009, 40% 2010+, 20%
BEV
Replace 100% pre-2010
trucks with BEV
Replace 30% of 2010+
with BEV
Replace 50% 2010+ with
BEV
7.2.1 On-port Truck Idle Reduction
This strategy would apply to heavy-duty diesel trucks that idle on-port while waiting to pick up
or drop off cargo.
• The "high" idle reduction scenario adopts a five-minute limit on idling within port for
drayage trucks. As the 2015 On-port Baseline Inventory assumes 30 minutes of on-port
idle per truck, a five-minute limit would amount to an 83 percent reduction in idle. For
implementing the scenario, a 75 percent reduction was chosen to account for
exceptions to the five-minute limit for work-related idle87 and driver safety.
• For the "low" idle reduction scenario, a 25 percent reduction in idle was chosen, which,
for example, could represent idle restrictions only in certain locations.
Note that it may be difficult to achieve these levels of idling reductions at Port Everglades due
to truck drivers' air conditioning needs in Broward County's subtropical climate. While this
issue could be partially alleviated by using alternatives to idling, this level of detail was not
considered in this analysis. Instead, these scenarios were modeled as a straightforward post-
processing step, where truck idle emissions were reduced proportionally. This was possible
because idle emissions were broken out separately in the 2015 On-port Baseline Inventory.
Other operational methods to reduce truck idle are discussed in the following strategy. The
87 Work-related idle occurs when the truck is idling while loading or unloading cargo (e.g., to power accessories).
7-4
-------
percent reductions in idle for each scenario were applied to the BAU idle emissions in each of
the projection years.
7.2.2 Operational Improvements
This strategy would reduce vehicle idling and queue time and improve traffic flow; it is assumed
that the improvements would proportionally reduce the amount of time trucks spend in the
Port. This analysis does not attempt to predict or dictate the exact nature of the operational
improvements, but assumes they would comply with all safety regulations and guidelines.88 For
each projection year, the percent reductions for each operational scenario were applied to the
BAU idle emissions for heavy-duty diesel trucks.
Note that this strategy is hypothetical, supplementing the operational improvements
continuously being sought at Port Everglades. For example, in 2014, the Port rebuilt Mcintosh
Road, the main on-port truck cargo route, as a multi-lane loop road to reduce truck congestion
and idling.89 In addition, some terminals at Port Everglades have implemented truck
appointment systems, which reduce the amount of time trucks spend on-port.
7.2.3 Truck Replacement with Cleaner Diesel Trucks and Electric Vehicles
Significant emission reductions are also possible through programs that accelerate adoption of
current engine technologies by truck operators using older vehicles. This strategy assumed that
older diesel trucks would be replaced by 2007/2010 model year diesel trucks or BEVs.
MOVES2014a was used to estimate the emission reductions from truck replacements by using
different inputs to reflect newer age distributions of trucks and the transition to battery electric
vehicles. This was done for both the low and high scenarios in each year as shown in Table 7-4
above.
7.3 Emission Reduction Scenario Results and Lessons Learned
Emission reductions for the onroad scenarios are presented in Figure 7-1, Figure 7-2, Figure 7-3,
and Table 7-5. Table 7-6 shows the percentage emission reductions associated with each
scenario in each year, based on the total onroad on-port emissions in that year.
In general, except for emissions of CChe, accelerating fleet turnover to cleaner technology
through truck replacements has the potential to reduce emissions significantly through 2035,
despite the projected growth in truck activity. Truck replacement is especially effective in the
year 2025, reducing NOx by about 30 percent and PM by about 70 percent compared to the
88 Some examples of operational improvements include increasing the physical capacity of the gate complex,
automated truck registration and container identification systems, and extending the operational hours of the
gate system.
89 Port Everglades, Port Everglades Realigns Southport Roadway for Efficient, Safer Truck Movement, March 2014,
http://www.porteyergjades.net/articles/post/port-evergjades-realigns-southport-roadwav-for-efficient-safer-
truck-movement.
7-5
-------
BAU case. Note that this strategy would not reduce emissions of CChe in 2025, as it assumes
that trucks would be replaced with newer model year conventional trucks; not until 2035 are
BEV replacements assumed. In 2035, truck replacement still shows benefits, as it would reduce
emissions of NOx by about 30 percent and PM by about 30 percent compared to the BAU case.
Idle reduction also has the potential to reduce truck emissions significantly, and the high
implementation scenario would reduce NOx by about 40 percent in both 2025 and 2035, and
PM by more than 45 percent in both years.
This analysis benefited from having details in the baseline inventory such as hours of on-port
idling and truck counts. However, having additional detail, such as the local truck age
distribution, could have strengthened this analysis further.
Note that the onroad inventories for 2015 and the BAU years include all vehicles visiting the
port, both light-duty and heavy-duty. In contrast, the strategies examined would apply only to
heavy-duty trucks, which are the largest part of the onroad vehicle inventory. Had the onroad
inventories included only the heavy-duty trucks, the emission reductions from the strategies
considered would have been an even larger percentage of the total.
7-6
-------
12
S 10
c
o
c
o
Vj 6
3
¦a
(D
c
o
I 2
ll
12025
12035
Idle Reduction (Low) Idle Reduction (High) Operational Operational Truck Replacement Truck Replacement
Improvements (Low) Improvements (High) (Low) (High)
Figure 7-1. On-port Truck NOx Reduction Strategies
£
O
'+J
u
3
T3
CD
C£
£
O
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
12025
12035
I.
I
Idle Reduction (Low) Idle Reduction (High) Operational Operational
Improvements (Low) Improvements (High)
Truck Replacement
(Low)
Truck Replacement
(High)
Figure 7-2. On-port Truck PM2.5 Reduction Strategies
7-7
-------
12,000
S 10,000
>•
tn
j[ 8,000
I 6,000 ( l -2025
¦II I ¦! 1 2035
|| I II - 2050
! : hi III il II
Idle Reduction (Low) Idle Reduction (High) Operational Operational Truck Replacement Truck Replacement
Improvements (Low) Improvements (High) (Low) (High)
Figure 7-3. On-port Truck C02e Reduction Strategies
7-8
-------
Table 7-5. Total Reductions from BAU On-port Onroad Vehicle Emissions by Scenario
Year
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2025
Idle Reduction
Low
3.36
0.22
0.20
0.22
0.20
0.10
0.38
1,571.73
High
10.08
0.67
0.61
0.67
0.61
0.29
1.13
4,715.20
Operational
Improvements
Low
0.67
0.04
0.04
0.04
0.04
0.02
0.08
314.35
High
1.34
0.09
0.08
0.09
0.08
0.04
0.15
628.69
Truck
Replacement
Low
5.87
0.96
0.89
0.96
0.89
0.41
1.23
0.00
High
7.26
0.97
0.90
0.97
0.90
0.42
1.26
0.00
2035
Idle Reduction
Low
2.17
0.09
0.08
0.09
0.08
0.01
0.19
1,881.45
High
6.50
0.26
0.24
0.26
0.24
0.03
0.58
5,644.36
Operational
Improvements
Low
0.43
0.02
0.02
0.02
0.02
0.00
0.04
376.29
High
0.87
0.03
0.03
0.03
0.03
0.00
0.08
752.58
Truck
Replacement
Low
2.92
0.12
0.11
0.12
0.11
0.02
0.22
2,505.10
High
4.66
0.17
0.15
0.17
0.15
0.02
0.33
4,921.36
2050
Idle Reduction
Low
a
--
--
--
--
--
--
2,271.77
High
--
--
--
--
--
--
--
6,815.30
Operational
Improvements
Low
--
--
--
--
--
--
--
454.35
High
--
--
--
--
--
--
--
908.71
Truck
Replacement
Low
--
--
--
--
--
--
--
5,923.40
High
--
--
--
--
--
--
--
9,872.34
a A double dash represents a value that was not calculated as part of this analysis.
7-9
-------
Table 7-6. Percent Reductions from BAU On-port Onroad Vehicle Emissions by Scenario
Year
Strategy
Scenario
Percent Reductions from BAU Emissions
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2025
Idle Reduction
Low
13.82%
15.49%
15.27%
15.60%
15.38%
16.39%
16.89%
10.64%
High
41.45%
47.18%
46.56%
47.52%
46.92%
47.54%
50.22%
31.91%
Operational Improvements
Low
2.75%
2.82%
3.05%
2.84%
3.08%
3.28%
3.56%
2.13%
High
5.51%
6.34%
6.11%
6.38%
6.15%
6.56%
6.67%
4.25%
Truck Replacement
Low
24.14%
67.61%
67.94%
68.09%
68.46%
67.21%
54.67%
0.00%
High
29.85%
68.31%
68.70%
68.79%
69.23%
68.85%
56.00%
0.00%
2035
Idle Reduction
Low
13.96%
16.07%
15.38%
16.36%
15.69%
14.29%
16.38%
10.72%
High
41.83%
46.43%
46.15%
47.27%
47.06%
42.86%
50.00%
32.15%
Operational Improvements
Low
2.77%
3.57%
3.85%
3.64%
3.92%
0.00%
3.45%
2.14%
High
5.60%
5.36%
5.77%
5.45%
5.88%
0.00%
6.90%
4.29%
Truck Replacement
Low
18.79%
21.43%
21.15%
21.82%
21.57%
28.57%
18.97%
14.27%
High
29.99%
30.36%
28.85%
30.91%
29.41%
28.57%
28.45%
28.03%
2050
Idle Reduction
Low
a
--
--
--
--
--
--
10.95%
High
--
--
--
--
--
--
--
32.84%
Operational Improvements
Low
--
--
--
--
--
--
--
2.19%
High
--
--
--
--
--
--
--
4.38%
Truck Replacement
Low
--
--
--
--
--
--
--
28.54%
High
--
--
--
--
--
--
--
47.57%
a A double dash represents a value that was not calculated as part of this analysis.
7-10
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8. RAIL
Two types of locomotives typically support port-related cargo operations: yard engines and
line-haul engines. Yard engines, also referred to as "switchers," disassemble and assemble
trains for shipment. The on-port Intermodal Container Transfer Facility (ICTF) at Port
Everglades, provided by the Florida East Coast Railway (FECR), is designed to move only
intermodal containers, which are transferred to and from rail cars using cargo handling
equipment.90 Because rail cars are not decoupled in this process, the ICTF does not require
switcher locomotives. Thus, only emissions from line-haul engines are considered in EPA's
analysis. In addition, this analysis reflects the significant investment by FECR in cleaner
locomotive technology, as described in more detail below.
The emission inventories derived from rail activity for the baseline year and in future years
under BAU conditions are described in Section 8.1. This is followed by a discussion of the
emission reductions that could result from the implementation of a truck-to-rail intermodal
shift strategy in Section 8.2 and a summary of results and lessons learned in Section 8.3.
A rail strategy, such as the truck-to-rail intermodal shift strategy considered, may be effective at
reducing emissions both on-port and off-port when it impacts locomotive operations within the
port boundary and in the off-port rail corridor servicing the port. However, this section
addresses rail emissions occurring on-port only; see Section 9.4 for more information on the
off-port rail corridor analysis.
8.1 Baseline and Projected Business as Usual Inventories
The 2015 On-port Baseline Inventory91 contains emission estimates for rail activity based on
information provided by FECR. For details on the data collection and inventory development
methodology, please see the 2015 On-port Baseline Inventory.
The rail baseline emission inventories presented here include pollutants from the 2015 On-port
Baseline Inventory as well as DPM2.5 and BC, which EPA added for its analysis.9293 Additionally,
the C02e results, which were presented in metric tons in the baseline inventory, were
converted to short tons here for consistency with the other pollutants. Emissions are
separately presented for two modes: locomotive idling and transit. The 2015 locomotive
emissions are based on the use of Tier 3 locomotives.
90 For more information, see https://www.fecrwv.com/news/fec-unveils-new-rail-facilitv-adiacent-port-
everglades.
91 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
92 DPM2.5 was calculated as a fraction of DPM10 by applying the ratio of PM2.5 to PM10 emissions from diesel-
powered main and auxiliary engines. BC was calculated as 77% of PM2.5 based on the EPA's Report to Congress
on Black Carbon.
93 U.S. Environmental Protection Agency, Report to Congress on Black Carbon, EPA-450/R-12-001, p. 87, March
2012.
8-1
-------
A hypothetical BAU scenario was developed based on anticipated growth and changes at Port
Everglades as identified in the 2014 Master/Vision Plan.94 Table 8-1 summarizes projected
growth rates for containerized throughput relative to the 2015 baseline, which are used as
surrogates for growth in rail activity.95 The BAU scenario assumes the current fraction of total
container cargo at Port Everglades diverted to rail remains constant at 8.59 percent in future
analysis years (e.g., 91,070 ICTF twenty-foot equivalent units [TEUs]/l,060,000 port TEUs =
0.0859).
Table 8-1. Baseline and BAU Projections of Container Handling
at Port Everglades ICTF
Year
TEU Growth
Factor3
BAU Port TEUs
BAU TEUs Handled
by ICTF
2015
1.000
1,060,000
91,070
2025
1.354
1,435,000
123,267
2035
1.661
1,761,000
151,270
2050
2.013
2,134,000
183,311
a Relative to 2015 base year
The baseline rail emission inventories developed in 2015 assumed all port rail activity was
diesel-powered. At the time of EPA's analysis, the FECR was in the process of converting its
fleet to dual fuel diesel/liquefied natural gas (LNG) locomotives. Therefore, the BAU inventory
projections developed for this analysis reflect the turnover to LNG fuel. The following
implementation rates were assumed to account for anticipated future use of diesel/LNG fueled
locomotives under BAU conditions: 25 percent of the fleet by 2025, 50 percent by 2035, and
100 percent by 2050. After this analysis was completed, FECR announced that all locomotives
operating at Port Everglades were dual fuel diesel/LNG capable by the end of 2017.96
Therefore, while the BAU inventories presented here overestimate expected future rail
emissions due to the accelerated turnover of FECR's entire fleet to clean technology, the LNG
conversion program doesn't affect the emission reductions analysis since LNG conversion was
not included as a reduction strategy for this sector.
94 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
95 Growth factors for 2035 and 2050 are not included in the range of projections provided in the 2014
Master/Vision Plan cited in this report. Therefore, the factors were extrapolated from expected growth
between 2028 and 2033, the last five years presented in the 2014 Master/Vision Plan.
96 For more information, see https://www.fecrwv.com/node/618.
8-2
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Table 8-2 lists Tier 3 locomotive emission factors9798 and dual fuel diesel/LNG emission
factors,99 100 along with composite, weighted emission factors for each projection year that
account for the rate of adoption of dual fuel locomotives in the future. It also lists the
corresponding emission adjustment factors, relative to the baseline emissions. This analysis
does not account for fugitive methane emissions from natural gas use, such as from equipment
leakage.
Table 8-2. Tier 3 and Dual Fuel Diesel/LNG Locomotive Emission Factors
Engine
Emission Factors (g/hp-hr)
NOx
PM10
PM2.5
DPM10
DPM2.5
BC
voc
CO2
CH4
N2Oa
Tier 3
(g/hp-hr)
4.95
0.08
0.07
0.08
0.07
0.05
0.14
494
0.04
0.013
Diesel/LNG
(g/hp-hr)
1.40
0.09
0.08
0.09
0.08
0.06
3.30
370
b
0.013
Year
Weighted Emission Factors (g/hp-hr)
2025
4.063
0.083
0.073
0.083
0.073
0.049
0.930
462.0
-
0.013
2035
3.175
0.085
0.075
0.085
0.075
0.050
1.720
430.0
-
0.013
2050
1.400
0.090
0.080
0.090
0.080
0.005
3.300
366.0
-
0.013
Year
Emission Adjustment Factors Relative to 2015 (unitless)
2025
0.821
1.031
1.036
1.031
1.036
0.701
6.643
0.935
-
1.000
2035
0.641
1.063
1.071
1.063
1.071
0.725
12.286
0.870
-
1.000
2050
0.283
1.125
1.143
1.125
1.143
0.773
23.571
0.741
-
1.000
a It was assumed N2O emissions are the same for Tier 3 and dual fuel locomotives in this analysis.
bA double dash represents a value that was not calculated as part of this analysis.
Hypothetical future emission inventories were then estimated for 2025, 2035, and 2050101 by
starting with the 2015 baseline emissions, applying the appropriate growth factors, and then
applying adjustment factors based on expected changes in the fleet emission factors. A
summary of baseline and BAU projected emissions is presented in Table 8-3.
Locomotives are a small emission source at Port Everglades due to the relatively small volume
of rail throughput compared to other sectors. Because the assumptions regarding FECR's
97 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, Federal Register, Vol. 73, No. 126, June
2008, https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-control-emissions-air-
pollution-locomotive.
98 U.S. Environmental Protection Agency, Emission Factors for Locomotives, EPA-420-F-09-025, April 2009,
https://nepis.epa.gov/Exe/ZvPDF.cgi/P100500B.PDF?Dockev=P100500B.pdf.
99 BNSF Railway Company/Union Pacific Railroad Company/Association of American Railroads/California
Environmental Associates, An Evaluation of Natural Gas-Fueled Locomotives, November 2007,
https://www.arb.ca.gov/railva rd/rvagreement/112807lngqa.pdf.
100 Energy Conversions, Inc., Emissions and Natural Gas Locomotives,
https://www.energvconversions.com/locoemis.htm.
101 Note that for 2050, only CChe inventories and reductions were quantified.
8-3
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planned increase in the use of dual fuel diesel/LNG powered engines assumed a much longer
phase in period, these projections likely overestimate expected future rail emissions.
Table 8-3. Baseline and Projected BAU Emissions for On-port Rail by Mode
Year
Mode
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2015102
Idling
0.79
0.01
0.01
0.01
0.01
0.01
0.02
79.49
Transit
0.63
0.01
0.01
0.01
0.01
0.01
0.02
63.05
Total
1.41
0.02
0.02
0.02
0.02
0.01
0.04
142.54
2025
Idling
0.88
0.02
0.02
0.02
0.02
0.01
0.20
100.47
Transit
0.70
0.01
0.01
0.01
0.01
0.01
0.16
79.70
Total
1.57
0.03
0.03
0.03
0.03
0.02
0.36
180.17
2035
Idling
0.84
0.02
0.02
0.02
0.02
0.01
0.46
114.82
Transit
0.67
0.02
0.02
0.02
0.02
0.01
0.36
91.09
Total
1.51
0.04
0.04
0.04
0.04
0.03
0.82
205.91
2050
Idling
a
-
-
-
-
-
-
118.62
Transit
-
-
-
-
-
-
-
94.10
Total
"
--
--
--
--
--
--
212.72
a A double dash represents a value that was not calculated as part of this analysis.
8.2 Emission Reduction Strategies and Scenarios
Since rail is generally considered to be more efficient at transporting cargo than using heavy-
duty diesel trucks, one option for reducing overall emissions is to encourage the intermodal
shift of cargo from truck to rail. An intermodal shift from truck to rail is the only rail strategy
considered in this analysis, given the cleaner technology already used in FECR's line-haul fleet
and that Port Everglades does not have switcher locomotives. Because Port Everglades does
not have direct control over implementing these strategies, this hypothetical scenario is
predicated on the assumption of the coordination and collaboration of various maritime
industry stakeholders for implementation.
The maximum design capacity of the ICTF is the primary constraint on the amount of cargo that
can be shifted from truck to rail at Port Everglades. The on-port rail strategy scenario
summarized in Table 8-4 is characterized by the increases in ICTF throughput and assumed
implementation rates shown in Table 8-5. The ratio between the annual TEU rail throughput
and ICTF design capacity103 for each scenario year is the adjustment factor used to calculate the
increase in locomotive emissions associated with maximizing the throughput of the ICTF.
102 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
103 Port Everglades, FEC Unveils New Rail Facility at Port Everglades, July 2014,
http://www.porteverglades.net/articles/post/fec-unveils-new-rail-facilitv-at-port-everglades.
8-4
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Table 8-4. Summary of On-port Rail Emission Reduction Scenarios
Strategy
Scenario
Implementation Rate
Notes
2025
2035
2050
Truck-to-Rail
Intermodal Shift
High
43%
66%
100%
Percentages represent ICTF operations
relative to its maximum design
throughput
Table 8-5. Increases in ICTF Throughput from Truck-to-Rail Intermodal Shift
Year
BAU TEUs Handled
byICTF
Implementation
Rate
Scenario TEUs
Handled by ICTF
Rail TEU Adjustment Factor of
Scenario Relative to BAU
2025
123,267
43%
193,621
1.57
2035
151,270
66%
296,173
1.96
2050
183,311
100%
450,000
2.45
Under this scenario, train operations were linearly increased between the activity presented in
the 2015 On-port Baseline Inventory and the ICTF maximum design capacity of 450,000 lifts in
2050, which will be approximately five times the 2015 throughput of the ICTF. Table 8-5
presents the number of TEUs handled by the ICTF in this hypothetical scenario. The number of
containers diverted to rail corresponds to 5.4 percent fewer containers moved by truck in 2025,
9.0 percent in 2035, and 13.7 percent in 2050. Therefore, hypothetical emission reductions
were calculated by reducing the BAU truck emissions by these fractions, and the results are
presented in Table 8-6.
Table 8-6. Total Reductions from BAU On-port Onroad Truck Emissions from Truck-to-Rail
Intermodal Shift
Year
Scenario
Emission Reductions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
C02e
2025
High
1.27
0.07
0.07
0.07
0.07
0.03
0.11
732.54
2035
High
1.38
0.05
0.05
0.05
0.05
0.01
0.10
1,472.30
2050
High
a
-
-
-
-
-
-
2,699.70
a A double dash represents a value that was not calculated as part of this analysis.
However, to calculate the net emission reductions from the intermodal shift of cargo from truck
to rail, the increased rail emissions must be considered together with the corresponding
decrease in truck emissions. To account for the changes in locomotive emissions in this
scenario, the BAU rail emissions were increased using the factors shown in Table 8-5. The
resulting increases in locomotive emissions due to this scenario are presented in Table 8-7.
8-5
-------
Table 8-7. Increases from BAU On-port Rail Emissions from Truck-to-Rail Intermodal Shift
Year
Mode
Emissions Increases (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2025
Idling
0.50
0.01
0.01
0.01
0.01
0.01
0.11
57.34
Transit
0.47
0.01
0.01
0.01
0.01
0.01
0.23
62.13
Total
0.97
0.02
0.02
0.02
0.02
0.01
0.35
119.48
2035
Idling
0.80
0.02
0.02
0.02
0.02
0.01
0.44
109.99
Transit
0.64
0.02
0.02
0.02
0.02
0.01
0.35
87.25
Total
1.44
0.04
0.03
0.04
0.03
0.02
0.78
197.24
2050
Idling
a
-
-
-
-
-
-
172.58
Transit
-
-
-
-
-
-
-
136.90
Total
"
--
--
--
--
"
--
309.47
a A double dash represents a value that was not calculated as part of this analysis.
8.3 Emission Reduction Scenario Results and Lessons Learned
The net emission reductions for the intermodal shift strategy are presented in Figure 8-1, Figure
8-2, Figure 8-3, and Table 8-8. This includes the emission reductions associated with the
removal of onroad truck traffic as well as the increase in emissions associated with the shift of
truck cargo to rail. Emission impacts change over time and vary depending on the pollutant. All
emissions are initially reduced in 2025, and while PM and CChe reductions increase overtime,
NOxemissions increase slightly in 2035. These net reductions are also presented in Table 8-9 as
percentage reductions relative to the total on-port onroad BAU emissions (see Table 7-3).
As described above, additional cleaner locomotive technologies were not considered for this
analysis since FECR has already made significant investments in its fleets as well as in the
construction of the Intermodal Container Transfer Facility.104 It is also important to note that
due to the timing of this analysis, the conversion of locomotives to dual fuel diesel/LNG engines
was assumed to take much longer than what occurred in practice. Consequentially, the
projected locomotive emissions in future years for both the BAU case and the emissions
reduction scenario are expected to be less than presented here. Additionally, the reduction
scenario assumed that all locomotive activity, including idling, would increase proportionally
with rail throughput. Having more detailed assumptions regarding the implementation of this
strategy could improve this analysis. Furthermore, lacking information on the local truck age
distribution, as noted in Section 6, limits the analysis of truck emission reductions associated
with this scenario. It is important to note that this analysis did benefit from having detailed
cargo throughput data received from FECR through consultation with Port Everglades. Taken
104 Replacing older diesel locomotives, such as switchers, is an effective emission reduction strategy to consider.
For further general information about other rail strategies, see EPA's National Port Strategy Assessment at:
https://www.epa.gov/ports-initiative/national-port-strategy-assessment-reducing-air-pollution-and-
greenhouse-gases-us.
8-6
-------
together, further refinements to this analysis are likely to show additional benefits to the truck-
to-rail intermodal shift strategy.
0.35
— 0.30
CD
(D
¦5; 0.25
tn
3 0.20
£
o
0.15
5 0.10
T3
CD
^ 0.05
£
8 0.00
rn -0.05
12025
12035
-0.10
Figure 8-1. On-port Truck-to-Rail Intermodal Shift NOx Reductions
0.06
(D
S 0.04
c
o
¦R 0.03
3
¦a
(D
cc
c
o
0.02
0.01
0.00
12025
12035
Figure 8-2. On-port Truck-to-Rail Intermodal Shift PM2.5 Reductions
8-7
-------
3,000
S 2,500
s-
tn
2, 2,000
tn
c
¦¦§ 1,500
¦a
^ 1,000
c
o
500
12025
12035
2050
Figure 8-3. On-port Truck-to-Rail Intermodal Shift C02e Reductions
Table 8-8. On-port Emission Reductions from Truck-to-Rail Intermodal Shift
Year
Strategy
Emission Reductions (tons/year)a
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2025
Onroad
1.27
0.07
0.07
0.07
0.07
0.03
0.11
732.54
Rail
-0.97
-0.02
-0.02
-0.02
-0.02
-0.01
-0.35
-119.48
Net Reduction
0.30
0.05
0.05
0.05
0.05
0.02
-0.24
613.06
2035
Onroad
1.38
0.05
0.05
0.05
0.05
0.01
0.10
1,472.30
Rail
-1.44
-0.04
-0.03
-0.04
-0.03
-0.02
-0.78
-197.24
Net Reduction
-0.06
0.01
0.02
0.01
0.02
-0.01
-0.68
1,275.06
2050
Onroad
b
--
--
--
--
--
--
2,699.70
Rail
--
--
--
--
--
--
--
-309.47
Net Reduction
--
--
--
--
--
--
--
2,390.23
a Negative numbers indicate an increase in emissions.
bA double dash represents a value that was not calculated as part of this analysis.
Table 8-9. Percent Reductions from BAU On-port Rail Emissions from Truck-to-Rail
Intermodal Shift
Year
Percent Reductions from BAU Emissions3
NOx
PM10
PM2.5
DPM10
DPM2.5
BC
VOC
C02e
2025
1.23%
3.52%
3.81%
3.55%
3.84%
3.30%
-10.65%
4.15%
2035
-0.39%
1.78%
3.84%
1.80%
3.90%
-13.99%
-58.65%
7.26%
2050
b
--
--
--
--
--
--
11.52%
a Negative numbers indicate an increase in emissions.
bA double dash represents a value that was not calculated as part of this analysis.
8-8
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9. OFF-PORT CORRIDOR ANALYSIS
As part of this analysis, EPA examined three off-port transportation corridors to estimate
emissions from port-related vessel and vehicle activity occurring outside of the Port. The off-
port corridors included in this analysis were a marine corridor, a truck corridor, and a rail
corridor.
EPA conducted this off-port analysis to learn more about the local data that can be used to
quantify mobile source emissions for port-related transportation corridors (i.e., corridors that
are related to port activity but outside of the Port). This work will inform EPA's future update
of its Port Emissions Inventory Guidance by providing hypothetical examples and technical
methods for analyzing such corridors, which may be important for people living and working
near ports and coastal areas. Additionally, analyzing emissions in transportation corridors can
provide insight into the benefits of emission reduction strategies that could be realized beyond
the boundaries of a port.
The selection of which corridors to include in the analysis and the definition of their boundaries
required careful consideration, as these decisions can have a significant impact on the results.
Corridors were defined so that the analysis only captured port-related activity, and were of
sufficient length to apply data and methods in a credible way. EPA acknowledges that its off-
port analysis covers only a portion of the off-port activity related to Port Everglades cargo and
passenger throughput. Note that EPA's analysis included hypothetical strategies and scenarios
over which Port Everglades has no direct control. The analysis methodology used for each
scenario does not make assumptions regarding the details, logistics, and costs of how or by
which entity or entities each emissions reduction strategy would be implemented.
Furthermore, the scenarios do not consider jurisdiction or geographical boundaries, except
when determining if the emission reductions would occur on-port or off-port.
These corridors were chosen so that Business as Usual (BAU) inventories and emission
reduction strategies could be analyzed for each of the sectors with off-port activity (e.g., ocean
going vessels [OGVs], harbor craft, onroad vehicles, and rail). The three selected off-port
corridors are further described as follows:
1. Marine corridor: The marine corridor accounted for OGV and harbor craft activity
occurring from the state/federal waters boundary located 3 nautical miles offshore to
the international border with the Bahamas (i.e., the continental shelf boundary), which
is approximately 20 to 25 nautical miles from shore.
2. Truck corridor: The onroad freight corridor focused on heavy-duty diesel truck activity
on the 1-595 spur from 1-95 into the port boundary.
3. Rail corridor: The off-port rail corridor covered the 10 kilometers of a railway line
operated by Florida East Coast Railway (FECR) extending north of the Intermodal
ContainerTransfer Facility (ICTF) spur.
9-1
-------
The off-port analysis included the same pollutants as the on-port analysis. Baseline emissions
for 2015 were calculated for each corridor, and then hypothetical BAU emission inventories
were estimated for the years 2025, 2035, and 2050,105 based on the Port's anticipated growth
in throughput and past fleet turnover rates. Table 9-1 summarizes the off-port emission
reduction strategies considered in EPA's analysis. Although these future emission inventories
are based on local information, they are purely hypothetical for the purposes of EPA's analysis
and are not intended to form the basis for policy recommendations.
Table 9-1. Off-port Emission Reduction Strategies
Mobile Source Sector
Strategy Descriptions
OGV
• Vessel speed reduction
• Lower sulfur fuels and alternative fuels
Harbor Craft
• Engine replacement (to Tier 3)
• Vessel replacement (to Tier 4)
Onroad
• Truck replacement to MY2010+ and battery electric vehicle (BEVs)
Rail3
• Intermodal shift of cargo from truck to rail
a Note that the rail strategy was only qualitatively included in the off-port analysis. See Section 9.4
for more information.
A description of how the off-port corridors were selected, the methodology applied to calculate
baseline and BAU projected off-port emission inventories, the associated baseline/BAU results,
and the various emission reduction strategies analyzed are presented below for OGVs (Section
9.1), harbor craft (Section 9.2), onroad trucks (Section 9.3), and rail (Section 9.4).
9.1 Off-port Marine Corridor: Ocean Going Vessels
The off-port marine corridor for OGVs was chosen to complement the on-port OGV
geographical boundary, which extends 3 nautical miles from the shoreline to the state/federal
waters boundary and covers the entire north/south extent of Broward County (see Figure 1-1).
Specifically, the off-port marine corridor begins at the state/federal waters boundary and
extends to the international boundary with the Bahamas. The international boundary, which is
approximately 20 to 25 nautical miles from shore, was chosen as the outer boundary of the
analysis so that the focus would be on vessel operations in U.S. waters only. While not
identical, the off-port north/south boundaries are similar to those of the on-port marine
geographical domain. Figure 9-1 delineates the off-port marine corridor in yellow, the Port in
red, and shipping lanes based on U.S. Department of Transportation shape files in light blue.
Descriptions of the vessels included in this analysis are given in Section 4.
105 Note that for 2050, only CChe inventories and reductions were quantified.
9-2
-------
Figure 9-1. Off-port Marine Corridor
The remainder of this sub-section presents the off-port baseline emissions inventory and the
projected BAD emissions for OGVs (Section 9.1.1), the considered strategies to reduce
emissions (Section 9.1.2), and a summary of the associated results (Section 9.1.3). Note that
the same vessel types included in the on-port analysis and listed in Table 4-1 were included in
this off-port analysis.
9.1.1 Baseline and Projected Business as Usuai Inventories
The 2015 baseline inventory and future BAU projection methodologies used to estimate off-
port OGV emissions were consistent with the on-port emission methodologies, as described in
Section 4.1. To ensure consistency of the on-port and off-port results, the same vessels were
included in both analyses based on the Port's non-confidential vessel call log. This has the
advantage of including emissions from only those vessels that call on the Port and excluding
emissions from other vessels that may be operating in "innocent passage" and that are not
directly related to activities at Port Everglades. Additionally, the same activity data sources
were used for both the on-port and off-port analyses, namely U.S. Coast Guard automatic
identification system (AIS) data, Information Handling Services' (IHS) Register of Ships,
Starcrest's Vessel Boarding Program, wharfinger vessel call data, and Port Everglades' 2014
9-3
-------
Master/Vision Plan. Irs addition to ensuring consistency between the on-port and off-port
analyses, using AIS data in the off-port analysis will inform EPA's future update of its Port
Emissions Inventory Guidance.
EPA obtained AIS data for the year 2015 for the off-port marine corridor from the U.S. Coast
Guard Navigation Center, summarized into 5-minute averages for each vessel.106 This initial
pre-processing step reduced the computational complexity for the subsequent analyses
described below. At 5-minute aggregation, a vessel traveling at 12 knots would be observed in
the data at every nautical mile of travel. The aggregated AIS vessel observations are presented
in Figure 9-2.107
Legend
Port Everglades
Off-port Marine Corridor
Nautical Miles
0 5 10 20
AIS Data Extent
Figure 9-2. Aggregated AIS Observations
These data were used to determine vessel movements, estimate hours of operation, and
quantify propulsion engine loads. Note that in reviewing the data, it was discovered that some
of the vessel observations were from vessels that called at Port Everglades at some point in the
year 2015 but undertook separate trips through the analysis area that were unrelated to Port
Everglades activity (i.e., some of their trips were "innocent passage"). This resulted in some
non-Port Everglades activity that was not successfully filtered out of the dataset; however, this
106 For more information, see https://www.navcen.uscg.gov.
107 Note that AIS data were available for a larger north/south cross-section; however, the data extent used by EPA
in this analysis (see the white box in Figure 9-2) was limited to reduce the computational complexity.
9-4
-------
activity accounted for 1 percent or less of the total observations. Given the level of effort
required to improve this filtering, no adjustments were made to the traffic data. Therefore,
port-related emissions may be slightly less than the calculated emissions presented below.
In general, the 2015 baseline emissions for off-port OGVs were calculated using the following
equation:
E = MCR x LF x HR x EF x LLAF x UCF Eq. 9-1
In the off-port marine corridor, transit (or "at-sea") was the only considered mode of operation
for OGVs, as the modes of operation considered in the on-port analysis were not applicable.
The following subsections describe the derivation of each of the components of Eq. 9-1, which
was used to calculate emissions on a per-vessel basis for both propulsion and auxiliary engines
and boilers.
9.1.1.1 Maximum Continuous Rated Engine Power and Engine Loads
The maximum continuous rated engine power was determined for most vessels' propulsion
engines by cross referencing the Port's vessel call log and the AIS dataset with IHS's Register of
Ships.108 Table 9-2 presents the number of vessels that could be successfully matched with a
propulsion engine power rating.
Where:
LF
HR
EF
LLAF
UCF
E
MCR
Emissions (tons)
Maximum continuous rated engine power (kW)
Load factor (dimensionless)
Hours of operation (hr)
Emission factor (g/kW-hr)
Low load adjustment factor (dimensionless)
Unit conversion factor (1.102xl0~6 ton/g)
108 No vessel-specific data are presented in this analysis since IHS requires the removal of vessel identifiers or the
aggregation of vessel characteristics data by vessel type to protect the confidentiality of individual vessels.
9-5
-------
Table 9-2. OGV Match Rates for Propulsion Engine Power and Vessel Speed
Vessel Type
Total
Count
Count with
Propulsion
Engine Match
Percent with
Propulsion Engine
Match
Count with
Max. Speed
Match
Percent with Max.
Speed Match
Auto Carrier
3
3
100%
3
100%
Bulk Carrier
36
35
97%
35
97%
Container
124
124
100%
124
100%
Cruise
45
44
98%
44
98%
General Cargo
76
75
99%
76
100%
Miscellaneous
8
7
88%
6
75%
Roll-On/Roll-Off
(RORO)
6
6
100%
6
100%
Tanker
161
153
95%
158
98%
Total
459
447
97%
452
98%
Vessels that could not be matched were assigned the average value by vessel type. Propulsion
engine loads were determined by applying load factors to the maximum continuous rated
engine power as described in Section 9.1.1.2 below.
Other information was used to characterize auxiliary engines and boilers. Since IHS data do not
necessarily include information on auxiliary engines and boilers, the primary data source for
these power ratings was Starcrest's Vessel Boarding Program. Because transiting load defaults
were not available, this analysis relied on the maneuvering load defaults for auxiliary engines
and boilers presented in the 2015 On-port Baseline Inventory109 for all vessel types except
cruise ships, which used the defaults presented in Table 9-3. The cruise ship defaults assumed
in this analysis for transit operations generally fall between the maneuvering and hotelling
loads, as presented in the 2015 On-port Baseline Inventory. See Section 4.1 for further
background.
109 Starcrest Consulting Group, LLC, Port Everglades 2015 Baseline Air Emissions Inventory, December 2016.
9-6
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Table 9-3. Cruise Ship Auxiliary Engine
Load Defaults (kW)
Passenger Capacity
(range)
Transit Operations
(kW)
0-1,499
3,500
1,500-1,999
7,000
2,000-2,499
10,500
2,500-2,999
11,000
3,000-3,499
11,500
3,500-3,999
12,000
4,000-4,499
12,500
4,500-4,999
13,000
5,000-5,499
13,500
5,500-5,999
14,000
6,000-6,499
14,500
6,500 +
15,000
9.1.1.2 Load Factors
Since vessel engines do not always operate at their maximum continuous power rating, load
factors are needed to estimate their actual power output. The Propeller Law, which estimates
that propulsion engine load varies with the cube of vessel speed,110 was used in this analysis as
a simplifying assumption to determine load factors for propulsion engines:
LF = (AS/MS)3 Eq. 9-2
Where:
LF = Load factor
AS = Actual vessel speed
MS = Maximum vessel speed
The actual vessel speed was derived from the AIS dataset, and the maximum vessel speed was
determined for most vessels by cross referencing the Port's vessel call log and AIS dataset with
IHS's Register of Ships. Table 9-2 above presents the number of vessels that could be
successfully matched with a maximum speed rating. Vessels that could not be matched were
assigned the average value by vessel type.
Note that since the auxiliary engine and boiler loads, as described above, already represent the
actual power demand, calculating a load factor for these sources is unnecessary.
110 MAN Diesel & Turbo, Basic Principles of Ship Propulsion, December 2011.
9-7
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9.1.1.3 Hours of Operation
To estimate hours of OGV operation in the off-port marine corridor, the duration between
consecutive observations for each vessel in the AIS dataset was calculated. As a quality
assurance check, the distribution of these durations was inspected, as shown in Table 9-4.
Table 9-4. Vessel Duration Profile for Off-port Marine Corridor
Duration
Percent of Observations
0 min (point of entry into the marine corridor)
0.4%
5 min
88.5%
10 min (missing one transmission)
4.3%
15 min (missing two transmissions)
0.2%
20 min (missing three transmissions)
0.1%
25 min (missing four transmissions)
0.1%
30 min (missing five transmissions)
0.1%
35-60 minutes (missing six or more transmissions)
0.3%
1-2 hours
0.2%
2-3 hours
0.1%
Greater than 3 hours
5.7%
As expected, most observations were captured at 5-minute intervals; however, approximately
10 percent of the observations were associated with longer durations between consecutive
transmittances. These longer durations could have been caused by a vessel leaving the area of
interest or because a vessel transmitter malfunctioned, was turned off, or failed to link up to
the AIS receiver. Because most of these longer duration observations appear around the
boundaries of the off-port marine corridor, they were attributed to a vessel leaving the area of
interest and returning later. To account for this, observations associated with durations longer
than 30 minutes were assigned a duration of 5 minutes when calculating hours of operation to
represent the last observation before leaving the boundaries of the corridor.
9.1.1.4 Emission Factors
Emission factors for propulsion and auxiliary engines and boilers vary by engine type, engine
speed, tier, and fuel type. The emission factors used in this analysis are the same as those used
for the 2015 On-port Baseline Inventory. These primarily come from the ENTEC 2002 study,111
except for PM and greenhouse gas emission factors, which were derived from the IVL Swedish
Environmental Research Institute 2004 study.112
111 Entec UK Limited, Quantification of emissions from ships associated with ship movements between ports in the
European Community, European Commission Final Report, July 2002,
http://ec.europa.eu/environment/air/pdf/chapterl ship emissions.pdf.
112 IVL Swedish Environmental Research Institute, Methodology for Calculating Emissions from Ships: Update on
Emission Factors, February 2004.
9-8
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9.1.1.5 Low Load Adjustment Factors
Low load adjustment factors were applied to the emission factors when propulsion engines
were determined to be operating at or below 20 percent load using Eq. 9-2 above. This is
because diesel engines are known to have higher emissions per kilowatt hour when operating
in this range. The low load emission adjustment factors used in this analysis vary by load and
pollutant, and are the same as those used in the 2015 On-port Baseline Inventory analysis.
9.1.1.6 Projected Business as Usual Inventories
To estimate BAU emissions from OGVs for future years, the same BAU scenario developed for
the on-port analysis was used for the off-port analysis, based on Port Everglades' 2014
Master/Vision Plan.113 Hypothetical BAU emission inventories were estimated for 2025, 2035,
and 2050114 by starting with the 2015 off-port baseline inventory (as described in sub-sections
9.1.1.1 through 9.1.1.5). Then, growth factors were applied by vessel or cargo type and
adjustment factors were applied based on expected changes in the fleet emission factors,
consistent with the on-port methodology. See Section 4.1 for additional details.
The 2015 off-port baseline inventory is presented in Table 9-5, and the BAU emission
projections for 2025, 2035, and 2050 are presented in Table 9-6, Table 9-7, and Table 9-8,
respectively. These results show that cruise ships are the largest category, followed by
containerships and tankers. This is consistent with the on-port inventory estimates. Note that
results are not presented by mode as in the on-port analysis, because transit activity is the only
off-port mode of operation considered. Over time, BAU emissions for almost all considered
pollutants are projected to increase due to the anticipated growth in marine freight and cruise
traffic. The exception is for NOx emissions, which are projected to decrease in 2035 due to
assumed fleet turnover to vessels with engines that comply with the Emission Control Area
(ECA) NOx standards.115 However, these results are highly dependent on the assumptions
described in Section 4.1 regarding OGV fleet turnover, and future emissions will depend largely
on the actual engine tier distribution of vessels calling on Port Everglades.
113 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
114 Note that for 2050, only CChe inventories and reductions were quantified.
115 U.S. Environmental Protection Agency, Regulatory Impact Analysis: Control of Emissions of Air Pollution from
Category 3 Marine Diesel Engines, EPA-420-R-09-019, December 2009,
httpsi//nepis,epa,gov/Exe/ZvPURL,cgi?Dockey=P1005ZGH,txt.
9-9
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Table 9-5. 2015 Baseline Emissions for Off-port OGVs by Vessel Type
Vessel Type
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
VOC
C02e
Auto Carrier
1.02
0.02
0.02
0.02
0.02
0.01
0.03
0.04
42.05
Bulk Carrier
7.24
0.12
0.12
0.12
0.12
0.09
0.20
0.32
315.47
Container—1000
110.07
2.02
1.94
1.99
1.91
1.49
3.44
4.76
5,412.79
Container—2000
18.77
0.32
0.31
0.31
0.30
0.24
0.52
0.90
815.42
Container—3000
36.71
0.62
0.59
0.60
0.58
0.46
0.97
1.79
1,526.24
Container—4000
30.60
0.54
0.52
0.52
0.50
0.40
0.82
1.69
1,295.41
Container—5000
26.81
0.46
0.44
0.45
0.43
0.34
0.70
1.33
1,106.43
Container—6000
28.70
0.51
0.49
0.49
0.47
0.38
0.74
1.73
1,167.48
Container—9000
0.52
0.01
0.01
0.01
0.01
0.01
0.01
0.04
18.60
Cruise
495.12
9.70
9.30
9.70
9.30
7.16
16.70
21.60
26,219.95
General Cargo
43.65
0.82
0.79
0.81
0.77
0.61
1.43
1.82
2,249.44
Miscellaneous
2.65
0.05
0.05
0.05
0.05
0.04
0.09
0.12
144.21
RORO
31.72
0.62
0.59
0.61
0.59
0.45
1.06
1.42
1,657.45
Tanker
23.15
0.40
0.38
0.38
0.36
0.29
0.65
1.04
1,021.96
Tanker—Chemical
40.16
0.69
0.67
0.66
0.64
0.51
1.15
1.85
1,804.75
Tanker—Handysize
13.14
0.22
0.21
0.21
0.20
0.16
0.37
0.57
575.44
Tanker—Panamax
8.17
0.15
0.15
0.14
0.14
0.11
0.24
0.50
375.98
Tanker—Suezmax
0.71
0.01
0.01
0.01
0.01
0.01
0.02
0.04
30.27
Total
918.91
17.28
16.59
17.08
16.40
12.76
29.14
41.56
45,779.34
9-10
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Table 9-6. 2025 BAU Emissions for Off-port OGVs by Vessel Type
Vessel Type
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
VOC
C02e
Auto Carrier
1.24
0.02
0.02
0.02
0.02
0.02
0.03
0.06
53.87
Bulk Carrier
5.52
0.15
0.14
0.15
0.14
0.11
0.24
0.39
376.99
Container—1000
113.74
2.74
2.62
2.69
2.58
2.02
4.66
6.44
7,328.91
Container—2000
17.63
0.44
0.42
0.43
0.41
0.32
0.70
1.22
1,104.08
Container—3000
44.30
0.84
0.80
0.81
0.78
0.62
1.31
2.43
2,066.53
Container—4000
30.02
0.76
0.70
0.71
0.68
0.54
1.11
2.29
1,753.99
Container—5000
35.41
0.612
0.59
0.60
0.58
0.46
0.95
1.80
1,498.11
Container—6000
20.77
0.69
0.66
0.66
0.64
0.51
1.00
2.34
1,580.76
Container—9000
0.70
0.01
0.01
0.01
0.01
0.01
0.02
0.05
25.18
Cruise
598.08
13.64
13.07
13.64
13.07
10.07
23.48
30.37
36,865.25
General Cargo
24.95
1.05
1.01
1.03
0.99
0.78
1.83
2.33
2,881.54
Miscellaneous
2.65
0.07
0.06
0.07
0.06
0.05
0.12
0.15
184.73
RORO
38.04
0.79
0.76
0.78
0.75
0.58
1.35
1.82
2,123.19
Tanker
15.58
0.46
0.44
0.45
0.43
0.34
0.76
1.22
1,195.69
Tanker—Chemical
22.76
0.81
0.78
0.78
0.74
0.60
1.34
2.16
2,111.56
Tanker—Handysize
4.74
0.26
0.24
0.24
0.23
0.19
0.43
0.67
673.27
Tanker—Panamax
3.68
0.18
0.17
0.17
0.16
0.13
0.28
0.59
439.90
Tanker—Suezmax
0.19
0.01
0.01
0.01
0.01
0.01
0.02
0.04
35.42
Total
979.99
23.53
22.50
23.25
22.28
17.36
39.63
56.37
62,298.97
9-11
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Table 9-7. 2035 BAU Emissions for Off-port OGVs by Vessel Type
Vessel Type
Annual Emissions (tons/year
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
VOC
C02e
Auto Carrier
1.54
0.03
0.03
0.03
0.03
0.02
0.05
0.07
70.82
Bulk Carrier
4.46
0.29
0.27
0.28
0.27
0.21
0.46
0.75
727.48
Container—1000
125.04
3.36
3.22
3.30
3.17
2.48
5.71
7.91
8,990.64
Container—2000
9.30
0.54
0.52
0.52
0.50
0.40
0.86
1.49
1,354.41
Container—3000
18.63
1.03
0.99
0.10
0.96
0.76
1.61
2.98
2,535.09
Container—4000
26.35
0.90
0.87
0.87
0.83
0.66
1.36
2.81
2,151.68
Container—5000
27.77
0.76
0.73
0.74
0.71
0.56
1.17
2.21
1,837.78
Container—6000
13.78
0.85
0.81
0.81
0.78
0.63
1.23
2.87
1,939.18
Container—9000
0.86
0.02
0.02
0.02
0.01
0.01
0.02
0.06
30.89
Cruise
398.99
14.74
14.12
14.74
14.12
10.87
25.36
32.81
39,828.11
General Cargo
24.21
1.38
1.32
1.36
1.30
1.02
2.41
3.07
3,788.06
Miscellaneous
1.84
0.09
0.09
0.09
0.08
0.07
0.15
0.20
242.84
RORO
49.56
1.04
0.99
1.03
0.99
0.76
1.78
2.40
2,791.14
Tanker
6.81
0.49
0.47
0.48
0.46
0.36
0.81
1.30
1,276.43
Tanker—Chemical
11.94
0.87
0.83
0.83
0.79
0.64
1.43
2.30
2,254.13
Tanker—Handysize
3.75
0.27
0.26
0.26
0.25
0.20
0.46
0.72
718.73
Tanker—Panamax
2.48
0.19
0.18
0.18
0.17
0.14
0.30
0.63
469.60
Tanker—Suezmax
0.20
0.02
0.02
0.01
0.01
0.01
0.02
0.05
37.81
Total
727.51
26.87
25.74
25.65
25.43
19.80
45.19
64.63
71,044.82
9-12
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Table 9-8. 2050 BAU Emissions for Off-port
OGVs by Vessel Type
Vessel Type
Annual C02e Emissions
(tons/year)
Auto Carrier
78.64
Bulk Carrier
787.42
Container—1000
10,895.94
Container—2000
1,641.44
Container—3000
3,072.33
Container—4000
2,607.66
Container—5000
2,227.25
Container—6000
2,350.13
Container—9000
37.44
Cruise
42,135.47
General Cargo
4,206.46
Miscellaneous
269.66
RORO
3,099.42
Tanker
1,393.95
Tanker—Chemical
2,461.68
Tanker—Handysize
784.90
Tanker—Panamax
512.84
Tanker—Suezmax
41.29
Total
78,603.92
9-13
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9.1.2 Emission Reduction Strategies and Scenarios
The following off-port emission reduction strategies were selected in consultation between EPA
and Port Everglades:
• Vessel speed reduction during transit
• Use of lower sulfur fuels (500 ppm or 200 ppm sulfur content)
• Use of liquefied natural gas (LNG)
Because Port Everglades does not have direct control over implementing these strategies, the
hypothetical scenarios for each are predicated on the assumption of the coordination and
collaboration of various maritime industry stakeholders for implementation. Additionally, the
scenarios do not consider jurisdiction or geographical boundaries. Table 9-9 summarizes the
implementation assumptions for each scenario. The anticipated reduction values for each
strategy scenario are presented in Table 9-10. Hypothetical emission reductions were
calculated for every emission reduction strategy and low/high implementation scenario relative
to the total off-port OGV BAU emissions. Additional details on the selected emission reduction
strategies and scenarios are presented in Sections 9.1.2.1 through 9.1.2.3.
9-14
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Table 9-9. Summary of Off-port Emission Reduction Scenarios for OGVs
Strategy
Affected Vessel Types
Scenario
Implementation Rates
Notes
2025
2035
2050
Vessel speed reduction during transit
All OGVs
Low
50%
50%
50%
Max speed 12 knots
High
90%
90%
90%
Lower sulfur fuels
All OGVs
Low
10% use of
500 ppm
25% use of
200 ppm
N/A
High
25% use of
500 ppm
50% use of
200 ppm
N/A
LNG
Containerships
Low
1%
2%
5%
High
5%
10%
15%
Table 9-10. Off-port OGV Emission Reduction Factors by Scenario
Strategy
Scenario
Notes
NOx
PMio
PM2.5
DPM
voc
SO2
CO2
CH4
N2O
Vessel speed
reduction during
transit
Low/High
Emission reductions vary by individual vessel, depending on speed of travel. Please see Section 9.1.2.1 for
more details.
Lower sulfur fuels
Low
500 ppm
a
5.9%
5.9%
5.9%
--
50.0%
--
--
--
High
200 ppm
--
11.8%
11.8%
11.8%
--
80.0%
--
--
--
LNG
High
87.7%
82.4%
82.4%
82.4%
16.7%
99.0%
22.4%
--
26.7%
bA double dash represents a value that was not calculated as part of this analysis.
9-15
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9.1.2.1 Vessel Speed Reduction
Reducing vessel speed is an effective way to reduce ship fuel consumption and emissions
because it lowers the power demand on the vessel's main engines.116 For this analysis, the
following assumptions were made:
• The vessel speed reduction zone covers all the off-port marine corridor (approximately
20 to 25 nautical miles from shore, as shown in Figure 9-1)117
• Vessels would voluntarily slow down to 12 knots or less within the corridor118
• All vessel types would be covered by the program
• Vessels would not change their trajectories due to the program
• The low and high implementation scenarios for this analysis assume 50 percent and 90
percent participation rates, respectively
To analyze the impacts of this strategy on emissions, actual vessel speeds were derived from
the 2015 AIS dataset. It was determined that 22 percent of all OGVs had average speeds
greater than 12 knots, as shown in Table 9-11. While the implementation details of this
hypothetical strategy are not considered in this analysis, it is important to note that most
vessels affected by this strategy are cruise ships.
Table 9-11. Summary of Off-port OGV Speeds
Vessel Type
Count of Vessels with
Average Speeds > 12 knots
Percent of All Vessels Calling
at Port Everglades
Auto Carrier
1
0.2%
Bulk
1
0.2%
Containership
19
4.4%
Cruise
42
9.7%
General Cargo
15
3.5%
Miscellaneous
0
0.0%
RORO
1
0.2%
Tanker
18
4.1%
Total
97
22.4%
Emission reductions from this strategy were estimated by calculating the hypothetical
reductions in propulsion engine load using the Propeller Law (see Section 9.1.1.2). In addition,
when a vessel's reduced speed engine load factor was calculated to be less than 20 percent,
116 In addition to reducing engine load, slow-steaming has the potential to reduce time spent waiting for berth or
crane availability. While this would reduce auxiliary engine use, this co-benefit was not included in this analysis
for simplicity.
117 In practice, it would be logical for a voluntary vessel speed reduction zone to cover a radius from the port,
tracing geographic semi-circle. However, because of the limited extent of the AIS data used in this analysis, the
emission reductions associated with the vessel speed reduction strategy were only calculated for the
highlighted range in Figure 9-1.
118 The speed reduction to 12 knots was chosen based on vessel speed reduction programs at California ports.
9-16
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low load adjustment factors were applied, as described in Section 9.1.1.5. While adjustments
were not made to the time spent by vessels in each mode (i.e., to account for the slower transit
speeds), the average delay was estimated to be approximately 10 minutes, assuming all vessels
transit the full length of the corridor at reduced speed.
9.1.2.2 Use of Lower Sulfur Fuels
For this strategy, a proportion of ships were assumed to use fuel with a sulfur concentration of
500 ppm in 2025 and 200 ppm in 2035. The assumed implementation rates for the low and
high implementation scenarios are listed in Table 9-9, and the emission reductions associated
with the lower sulfur fuels are listed in Table 9-10. See Section 4.2.3 for additional information
on this strategy.
9.1.2.3 Use of LNG
The LNG rates of implementation for containerships from Table 9-9 and the emission
reductions noted in Table 9-10 were applied to the projected BAU containership emissions to
evaluate the anticipated changes in emissions. See Section 4.2.4 for additional information on
this strategy.
9.1.3 Emission Reduction Scenario Results and Lessons Learned
The modeled emission reductions for each scenario are summarized in Figure 9-3, Figure 9-4,
Figure 9-5, and Table 9-12 for off-port operations. Table 9-13 shows the relative percent
emission reductions for each scenario. The percent reductions are shown relative to the total
off-port OGV emissions, as there is only one off-port mode of operation.
The analysis for the voluntary vessel speed reduction strategy suggests it may be effective at
significantly reducing OGV emissions for all pollutants outside of the Port. However, because
specific implementation details for this strategy were not considered, there is uncertainty as to
what the actual vessel emission reductions would be if such a strategy were to be
implemented. For example, it is unclear how many vessels would reduce their speed.
The fuel strategies were also shown to be effective at reducing emissions outside the port,
particularly the lower sulfur fuels strategy for reducing PM emissions. The percent reductions
for the LNG strategy appear low; however, this strategy was only applied to a fraction of
containerships and the comparison is presented against all off-port OGV emissions.
This analysis could be further improved by refining the geographical bounds of the analysis
zone (i.e., choosing a semi-circle centered at the port extending to the international waters
boundary), refining vessel speed reduction targets by vessel type (e.g., setting a different speed
limit for certain vessels), and accounting for longer travel durations in the off-port corridor due
to slower transit speeds. This analysis benefited from having a highly detailed baseline
inventory based on AIS data and the Port's non-confidential vessel call records.
9-17
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350
o 250
5 200
Lso
t 100
50
12025
12035
Speed Reduction Speed Reduction LNG (Low) LNG (High)
(Low) (High)
Figure 9-3. Off-port OGV NOx Reduction Strategies
™ 7
(D /
>
> 6
o
it 5
tn
o 4
I
12025
12035
Speed Speed Lower Sulfur Lower Sulfur LNG (Low) LNG (High)
Reduction Reduction Fuels (Low) Fuels (High)
(Low) (High)
Figure 9-4. Off-port OGV PM2.5 Reduction Strategies
25,000
(D
C
o
20,000
£ 15,000
o
'¦M
-g 10,000
CD
cc
.2 5,000
12025
12035
2050
Speed Reduction
(Low)
Speed Reduction
(High)
LNG (Low)
LNG (High)
Figure 9-5. Off-port OGV C02e Reduction Strategies
9-18
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Table 9-12. Total Reductions from BAU Off-port OGV Emissions by Scenario
Year
Strategy
Scenario
Emission Reductions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02e
2025
Vessel Speed
Reduction During
Transit
Low
175.19
3.74
3.59
3.76
3.61
2.76
6.65
7.80
10,417.25
High
315.34
6.74
6.46
6.77
6.49
4.97
11.97
14.03
18,751.04
Lower Sulfur Fuels
Low
a
0.14
0.13
0.14
0.13
0.10
1.98
--
--
High
--
0.35
0.33
0.34
0.33
0.25
4.95
--
--
LNG
Low
2.30
0.05
0.05
0.05
0.05
0.04
0.10
0.03
34.48
High
11.51
0.25
0.24
0.24
0.23
0.18
0.48
0.14
172.40
2035
Vessel Speed
Reduction During
Transit
Low
124.05
4.20
4.02
4.22
4.05
3.10
7.44
8.77
11,661.24
High
223.29
7.56
7.24
7.60
7.29
5.57
13.40
15.79
20,990.23
Lower Sulfur Fuels
Low
--
0.79
0.76
0.78
0.75
0.59
9.04
--
--
High
--
1.58
1.52
1.57
1.50
1.17
18.08
--
--
LNG
Low
3.89
0.12
0.12
0.12
0.11
0.09
0.24
0.07
84.60
High
19.45
0.61
0.59
0.60
0.57
0.45
1.18
0.34
422.98
2050
Vessel Speed
Reduction During
Transit
Low
--
--
--
--
--
--
--
--
12,689.28
High
--
--
--
--
--
--
--
--
22,840.70
LNG
Low
--
--
--
--
--
--
--
--
256.31
High
--
--
--
--
--
--
--
--
768.94
a A double dash represents a value that was not calculated as part of this analysis.
9-19
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Table 9-13. Percent Reductions from BAU Off-port OGV Emissions by Scenario
Year
Strategy
Scenario
Percent Reductions from BAU Emissions
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
SO2
voc
C02e
2025
Vessel Speed
Reduction During
Transit
Low
17.88%
15.92%
15.93%
16.18%
16.19%
15.93%
16.78%
13.83%
16.72%
High
32.18%
28.66%
28.67%
29.13%
29.14%
28.67%
30.20%
24.89%
30.10%
Lower Sulfur Fuels
Low
a
0.59%
0.59%
0.59%
0.59%
0.59%
5.00%
--
--
High
--
1.48%
1.48%
1.48%
1.47%
1.48%
12.50%
--
--
LNG
Low
0.23%
0.21%
0.21%
0.21%
0.21%
0.21%
0.24%
0.05%
0.06%
High
1.17%
1.06%
1.06%
1.05%
1.05%
1.06%
1.22%
0.25%
0.28%
2035
Vessel Speed
Reduction During
Transit
Low
17.06%
15.65%
15.65%
15.92%
15.93%
15.65%
16.48%
13.59%
16.42%
High
30.70%
28.17%
28.18%
28.66%
28.67%
28.18%
29.67%
24.45%
29.56%
Lower Sulfur Fuels
Low
--
2.95%
2.95%
2.95%
2.95%
2.95%
20.01%
--
--
High
--
5.90%
5.90%
5.90%
5.90%
5.90%
40.02%
--
--
LNG
Low
0.53%
0.46%
0.46%
0.45%
0.45%
0.46%
0.52%
0.11%
0.12%
High
2.67%
2.29%
2.29%
2.26%
2.26%
2.29%
2.62%
0.53%
0.60%
2050
Vessel Speed
Reduction During
Transit
Low
--
--
--
--
--
--
--
--
16.14%
High
--
--
--
--
--
--
--
--
29.06%
LNG
Low
--
--
--
--
--
--
--
--
0.33%
High
--
--
--
--
--
--
--
--
0.98%
a A double dash represents a value that was not calculated as part of this analysis.
9-20
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9.2 Off-port Marine Corridor: Harbor Craft
The off-port marine corridor for harbor craft is the same corridor for OGVs described above in
Section 9.1 and shown in Figure 9-1. This section presents the baseline emissions inventory and
projected BAU emissions for harbor craft in this corridor (Section 9.2.1), the considered
strategies to reduce emissions (Section 9.2.2), and a summary of the associated results and
lessons learned (Section 9.2.3). Note that the same vessel types included in the on-port harbor
craft analysis, as listed in Table 5-1, were included in this off-port analysis. Due to the nature of
harbor craft, these vessels have limited activity in the off-port marine corridor relative to OGVs.
However, this section describes the harbor craft activity in the corridor that was observed in
the AIS data.
9.2.1 Baseline and Projected Business as Usual Inventories
The baseline and BAU projection methodologies for estimating off-port harbor craft emissions
is consistent with the methodologies for estimating on-port emissions as described in Section
5.1. To ensure consistency, the same vessels were included in both analyses, based on the
Port's non-confidential vessel call log. Additionally, the same activity data sources were used
for both the on-port and off-port analysis, namely U.S. Coast Guard AIS data, IHS's Register of
Ships, Starcrest's Vessel Boarding Program, wharfinger vessel call data, and Port Everglades'
2014 Master/Vision Plan. While not all harbor craft are required to have AIS transponders, a
comparison between the AIS data and the wharfinger vessel call data showed that the majority
of relevant vessels appeared in the AIS data. In addition to ensuring consistency between the
on-port and off-port analyses, using AIS in the off-port analysis will inform EPA's future update
of its Port Emissions Inventory Guidance.
The raw AIS data were summarized into 5-minute averages for each vessel by the U.S. Coast
Guard Navigation Center. This initial pre-processing step reduced the computational
complexity for the subsequent analyses described below.
In general, the baseline emissions for off-port harbor craft were calculated similarly as those for
off-port OGVs (described in Section 9.1.1) using the following equation:
E = MCR x LF x HR x EF x UCF
Eq. 9-3
Where:
LF
HR
EF
UCF
E
MCR
Emissions (tons)
Maximum continuous rated engine power (kW)
Load factor (dimensionless)
Hours of operation (hr)
Emission factor (g/kW-hr)
Unit conversion factor (1.102xl0~6 ton/g)
9-21
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In the off-port marine corridor, transit was the only considered mode of operation for harbor
craft, as the modes of operation considered in the on-port analysis were not applicable. The
following subsections describe the derivation of each of the components of Eq. 9-3, which was
used to calculate emissions on a per-vessel basis for both propulsion and auxiliary engines.
9.2.1.1 Maximum Continuous Rated Engine Power and Engine Loads
The maximum continuous rated engine power was determined for most vessels' propulsion
engines by cross referencing the Port's vessel call log and the AIS dataset with IHS's Register of
Ships. Table 9-14 presents the number of vessels that could be successfully matched with a
propulsion engine power rating. Vessels that could not be matched were assigned the average
value by vessel type, as given in the 2015 On-port Baseline Inventory.
Table 9-14. Harbor Craft Match Rates for Propulsion Engine Power and Vessel Speed
Total
Count
Count with
Percent with
Count with
Percent with
Vessel Type
Propulsion Power
Match
Propulsion Power
Match
Max. Speed
Match
Max. Speed
Match
Articulated
Tug Barge
17
17
100%
9
53%
Assist Tug
1
1
100%
0
0%
Towboat
30
26
87%
13
43%
Total
48
44
92%
22
46%
All auxiliary engine characteristics came from Starcrest's Vessel Boarding Program. Engine
loads for both propulsion and auxiliary engines were determined by applying load factors to the
maximum continuous rated engine power as described in the following section.
9.2.1.2 Load Factors
Harbor craft propulsion engine load factors were calculated similarly as those for off-port OGVs
(described in Section 9.1.1.2) using the Propeller Law. The actual vessel speed was derived
from the AIS dataset, and the maximum vessel speed was determined where possible by cross
referencing the Port's vessel call log and the AIS dataset with IHS's Register of Ships. Table 9-14
above presents the number of vessels that could be successfully matched with a maximum
speed rating. Vessels that could not be matched were assigned the average value by vessel
type. Load factors for harbor craft auxiliary engines came from the 2015 On-port Baseline
Inventory.
9.2.1.3 Hours of Operation
Harbor craft hours of operation in the marine corridor were derived similarly as in the off-port
OGV case (described in Section 9.1.1.3) by calculating the duration between each AIS
observation for each vessel.
9-22
-------
9.2.1.4 Emission Factors
Emission factors for harbor craft propulsion and auxiliary engines vary by engine power rating
and tier. The emission factors used in this analysis are the same as those used in the 2015 On-
port Baseline Inventory.
9.2.1.5 Projected Business as Usual Emissions
To estimate BAU emissions from harbor craft for future years, the same BAU scenario
developed for the on-port analysis was used for the off-port analysis, based on Port Everglades'
2014 Master/Vision Plan.119 Hypothetical BAU emission inventories were estimated for 2025
and 2035 by starting with the 2015 baseline emissions, applying the growth factors, and then
applying adjustment factors based on expected changes in the fleet emission factors. Emission
inventories were not calculated for 2050, as only greenhouse gases were included for that year
in this analysis, and the selected emission reduction strategies (discussed below) do not address
greenhouse gases.120 See Section 5.1 for additional details on this analysis.
A summary of the baseline and BAU projected emissions is presented in Table 9-15. Based on
the assumptions in this analysis, emissions are projected to increase for all pollutants from the
2015 baseline year due to the anticipated increase in marine freight traffic.
119 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
120 Note that there are technologies involving electrification that do address greenhouse gases that were not
included here. For more information, see EPA's National Port Strategy Assessment,
https://www.epa.gov/ports-initiative/national-port-strategy-assessment-reducing-air-pollution-and-
greenhouse-gases-us.
9-23
-------
Table 9-15. 2015 Baseline and 2025 and 2035 BAU Emissions for Off-port Harbor Craft
Year
Vessel Type
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
VOC
CChe
2015
Articulated
Tug Barge
12.75
0.61
0.59
0.61
0.59
0.45
0.60
737.72
Assist Tug
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.52
Towboat
10.64
0.39
0.38
0.39
0.38
0.29
0.43
586.50
Total
23.40
0.99
0.97
0.99
0.97
0.75
1.02
1,324.75
2025
Articulated
Tug Barge
13.53
0.64
0.62
0.64
0.62
0.48
0.65
881.58
Assist Tug
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.62
Towboat
11.29
0.41
0.40
0.41
0.40
0.31
0.47
700.87
Total
24.82
1.04
1.02
1.04
1.02
0.79
1.13
1,583.07
2035
Articulated
Tug Barge
22.80
1.05
1.03
1.05
1.03
0.79
1.15
1,701.18
Assist Tug
0.02
0.00
0.00
0.00
0.00
0.00
0.00
1.20
Towboat
19.02
0.67
0.66
0.67
0.66
0.51
0.83
1,352.47
Total
41.84
1.73
1.69
1.73
1.69
1.30
1.98
3,054.86
9.2.2 Emission Reduction Strategies and Scenarios
The following off-port emission reduction strategies were selected in consultation with Port
Everglades:
• Engine replacement (to Tier 3)
• Vessel replacement (to Tier 4)
These are the same emission reduction strategies selected in the on-port harbor craft analysis.
Information on why these strategies were selected can be found in Section 5.2. Because Port
Everglades does not have direct control over activity in the off-port marine corridor, the
hypothetical scenarios for each are predicated on the assumption of the coordination and
collaboration of various maritime industry stakeholders for implementation.
The emission reduction values presented in Table 9-16 were applied to the BAU inventories for
the number of engines or vessels replaced with cleaner diesel technology under each scenario
as summarized in Table 9-17.
9-24
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Table 9-16. Off-port Harbor Craft Per Vessel Emission Reduction Factors by Strategy
Strategy
Notes
NOx
PMio
PM2.5
DPM
BC
VOC
Engine Replacement
Per vessel reductions from
replacing Tier 0 with Tier 3
44.7%
80.6%
80.6%
80.6%
80.6%
a
Vessel Replacement
Per vessel reductions from
replacing Tier 0 with Tier 4
86.4%
94.4%
94.4%
94.4%
94.4%
62.0%
a VOC emission reductions from engine replacement were not calculated as part of this analysis.
Table 9-17. Summary of Off-port Emission Reduction Scenarios for Harbor Craft
Strategy
Scenario
Implementation Rates
Notes
2025
2035
Engine
Replacement
Low
20% (8 vessels)
20% (6 vessels)
Replacing Tier 0 engines with
Tier 3 engines
High
30% (13 vessels)
30% (8 vessels)
Vessel
Replacement
Low
10% (4 vessels)
10% (3 vessels)
Replacing Tier 0 vessels with
Tier 4 vessels
High
20% (8 vessels)
20% (6 vessels)
9.2.3 Emission Reduction Scenario Results and Lessons Learned
The projected off-port emission reductions by scenario are summarized in Figure 9-6, Figure
9-7, and Table 9-18. Table 9-19 shows the percent emissions reduction for each scenario
relative to the total off-port harbor craft BAU emissions.
This analysis benefited from knowing the age distribution of the tug and towboat fleets
operating at Port Everglades. Due to the longevity of tugs and towboats, significant reductions
may be possible through voluntary programs that support the replacement of older engines
and vessels. While normal fleet turnover to newer emission standards can reduce the BAU
growth in emissions, this off-port corridor analysis shows that accelerated diesel engine and
vessel replacement have additional long-term benefits beyond the reductions seen on-port.
9-25
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12025
_ 3.0
i_
ro
(D
>; 2.5
iSi
c
o
ii 2.0
tn
¦S 1.5
0
1 1.0 ¦¦ ¦ _ | ¦ 2035
c
o
¦jg °-5
£
m 0.0
Engine Replacement Engine Replacement Vessel Replacement Vessel Replacement
(Low) (High) (Low) (High)
Figure 9-6. Off-port Harbor Craft NOx Reduction Strategies
_ 0.18
| 0.16
> 0.14
0.12
| 0.10
| 0.08 ¦¦ H 2025
1 0.06 H H ¦ 2035
o 0.04
\n
¦| 0.02
0.00
ll
Engine Replacement Engine Replacement Vessel Replacement Vessel Replacement
(Low) (High) (Low) (High)
Figure 9-7. Off-port Harbor Craft PM2.5 Reduction Strategies
9-26
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Table 9-18. Total Reductions from BAU Off-port Harbor Craft Emissions by Scenario
Year
Strategy
Scenario
Emission Reductions
tons/year
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
2025
Engine
Replacement
Low
1.37
0.10
0.10
0.10
0.10
0.08
a
High
2.23
0.16
0.16
0.16
0.16
0.12
--
Vessel
Replacement
Low
1.33
0.06
0.06
0.06
0.06
0.05
0.03
High
2.65
0.12
0.11
0.12
0.11
0.08
0.07
2035
Engine
Replacement
Low
1.03
0.07
0.07
0.07
0.07
0.05
--
High
1.37
0.10
0.10
0.10
0.10
0.08
--
Vessel
Replacement
Low
0.99
0.04
0.04
0.04
0.04
0.03
0.03
High
1.99
0.09
0.09
0.09
0.09
0.07
0.05
a A double dash represents a value that was not calculated as part of this analysis.
Table 9-19. Percent Reductions from BAU Off-port Harbor Craft Emissions by Scenario
Year
Strategy
Scenario
Percent Reductions from BAU Emissions
NOx
PM10
PM2.5
DPM10
DPM2.5
BC
VOC
2025
Engine
Replacement
Low
5.52%
9.55%
9.55%
9.55%
9.55%
9.55%
a
High
8.98%
15.51%
15.51%
15.51%
15.51%
15.51%
--
Vessel
Replacement
Low
5.34%
5.59%
5.59%
5.59%
5.59%
5.59%
3.09%
High
10.68%
11.18%
11.18%
11.18%
11.18%
11.18%
6.18%
2035
Engine
Replacement
Low
2.46%
4.31%
4.31%
4.31%
4.31%
4.31%
--
High
3.28%
5.75%
5.75%
5.75%
5.75%
5.75%
--
Vessel
Replacement
Low
2.38%
2.53%
2.53%
2.53%
2.53%
2.53%
1.32%
High
4.75%
5.05%
5.05%
5.05%
5.05%
5.05%
2.63%
a A double dash represents a value that was not calculated as part of this analysis.
9.3 Off-port Truck Corridor
Since Port Everglades sees significant freight and cruise activity, the off-port onroad emissions
inventory included roads frequently travelled by port-related cargo and passenger traffic.
Specifically, this inventory included the off-port truck corridor, which is the 1-595 highway spur
connecting Port Everglades to 1-95, as well as several surface streets that connect the Port to
the airport and nearby hotels. Figure 9-8 shows the roads included in the off-port emission
inventory, where the 1-595 off-port truck corridor is highlighted in pink, the selected surface
streets are highlighted in blue, and Port Everglades is outlined in red. While other streets, such
as SR-84, are used by port-related truck traffic, only 1-595 was included for simplicity.
This section presents the baseline off-port onroad emission inventory and the projected BAU
emissions (Section 9.3.1), the considered strategies to reduce emissions in the off-port truck
corridor (Section 9.3.2), and a summary of the associated results and lessons learned (Section
9.3.3).
9-27
-------
Legend
Port Everglades
Roads - Passenger Vehicle Traffic
• Off-port Truck Corridor
Kilometers
Figure 9-8. Off-port Truck Corridor
9.3.1 Baseline and Projected Business as Usual Inventories
The baseline and BAD projection methodologies for estimating off-port emissions from onroad
vehicles are consistent with the methodologies used for estimating the on-port emissions, as
described in Section 7.1. To ensure consistency, the same vehicles were included in both
analyses, based on gate counts and confidential surveys of terminal and facility operational
managers. EPA did not receive any confidential business or terminal-specific information
through the partnership.
Off-port onroad emissions were estimated using EPA's MOVES2014am model at the project
scale. At this scale, links are defined to represent segments of roads with information about
the vehicles operating on the links, including vehicle activity. The 1-595 spur, the off-port truck
corridor, was modeled as a set of "restricted roadway" links in MOVES. These links captured
port-related heavy-duty diesel truck traffic, modeled as combination short-haul trucks and
combination long-haul trucks. The numerous surface streets included in the corridor were
modeled as a set of "unrestricted roadway" iinks in MOVES. These captured the majority of
cruise passenger traffic, modeled as passenger cars, light commercial trucks, and transit buses.
121 EPA's MOtor Vehicle Emission Simulator (MOVES) is a state-of-the-science emission modeling system that
estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants,
greenhouse gases, and air toxics. For more information, see https://www.epa.gov/moves.
9-28
-------
An additional link was included to estimate emissions from vehicles idling while waiting to pick
up cruise passengers at the airport.
The vehicle mix accounted for by the MOVES links was derived from information about the total
number of vehicles from the 2015 On-port Baseline Inventory, combined with information
about l-595's traffic volume and vehicle mix in 2015, as reported by Florida Department of
Transportation.122 The resulting link volumes and source type fractions are shown in Table
9-20. MOVES inputs regarding vehicle characteristics such as age and fuel type distributions are
the same as what were used for the on-port inventory, since the vehicles are the same in both
analyses. This analysis does not account for EPA's Heavy-Duty GHG Phase 2 rule because it is
currently not included in MOVES2014a.
Table 9-20. Off-port Link Volumes and Source Type Fractions
Source Type
1-595 Link: Truck Corridor
(Urban Restricted Road)
Surface Streets
(Urban Unrestricted Road)
Volume
Source Type
Fraction
Volume
Source Type
Fraction
Passenger Car
54,326
13.0%
217,306
19.2%
Light Commercial Truck
36,083
8.7%
144,330
12.8%
Transit Bus
5,399
1.3%
21,597
1.9%
Combination Short-Haul
152,700
36.6%
354,817
31.4%
Combination Long-Haul
168,245
40.4%
390,939
34.6%
Total Link Volume
416,753
100%
1,128,988
100%
To estimate onroad BAU emissions for future years, the same BAU scenario developed for the
on-port analysis was used for the off-port analysis, based on Port Everglades' 2014
Master/Vision Plan.123 Hypothetical BAU emission inventories were estimated for 2025, 2035,
and 2050124 by starting with the 2015 baseline off-port emissions, applying the growth factors
by vehicle type, and then applying adjustment factors based on expected changes in the fleet
emission factors. See Section 7.1 for details on the methodology used for this step in the
analysis. A summary of baseline and BAU projected emissions is presented in Table 9-21.
Based on the assumptions in this analysis, emissions are projected to decrease over time for
most pollutants (except (Xhe) due to fleet turnover to lower-emitting vehicles.
122 Florida Department of Transportation, Florida Traffic Online, 2015,
http://flto.dot.state.fl.us/website/FloridaTrafficOnline/viewer.html.
123 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
124 Note that for 2050, only CChe inventories and reductions were quantified.
9-29
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Table 9-21. Baseline and Projected BAU Emissions for Off-port Onroad Vehicles
Year
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPMio
DPM2.5
BC
voc
CChe
2015
23.69
1.43
1.31
1.42
1.30
0.61
1.64
6,657.57
2025
10.66
0.51
0.47
0.50
0.46
0.22
0.63
8,251.94
2035
6.76
0.20
0.19
0.20
0.18
0.03
0.31
9,774.84
2050
a
--
--
--
--
--
--
11,530.98
a A double dash represents a value that was not calculated as part of this analysis.
9.3.2 Emission Reduction Strategies and Scenarios
Only one emission reduction strategy considered for the on-port inventory also applied to the
truck corridor as well. This strategy, to replace trucks with cleaner diesel and electric
technologies (e.g., 2007/2010 compliant trucks and battery electric vehicles [BEVs]), was
selected in consultation with Port Everglades. It mirrors the truck replacement strategy
selected for the on-port onroad analysis. It is the only off-port strategy considered because the
other onroad strategies considered for the on-port inventory discussed in Section 7.2, such as
idle reduction, did not apply to off-port truck activity. See Section 7.2.3 for background
information on this strategy.
Because Port Everglades does not have direct control over implementing this strategy (since the
Port does not own these fleets), the hypothetical scenarios for each are predicated on the
assumption of the coordination and collaboration of various stakeholders for implementation.
Table 9-22 summarizes applicability and implementation assumptions for each scenario.
Table 9-22. Summary of Emission Reduction Scenarios for Off-port Truck Corridor
Strategy
Scenario
Implementation Rate
2025
2035
2050
Truck
replacement
Low
Replace 100% pre-2007
trucks with 50% 2007,
50% 2010+
Replace 100% pre-2010
trucks with 2010+
Replace 15% of 2010+
with BEV
Replace 30% of 2010+
with BEV
High
Replace 100% pre-2007
trucks with 40% 2007-
2009, 40% 2010+, 20%
BEV
Replace 100% pre-2010
trucks with BEVs
Replace 30% of 2010+
with BEV
Replace 50% of 2010+
with BEV
Hypothetical emission reductions were calculated for each scenario relative to the total off-port
onroad BAU inventories using MOVES2014a.
9-30
-------
9.3.3 Emission Reduction Scenario Results and Lessons Learned
The projected off-port emission reductions by scenario are summarized in Figure 9-9, Figure
9-10, Figure 9-11, and Table 9-23. Table 9-24 shows the percent emission reductions for each
scenario relative to the total off-port onroad BAU emissions.
In general, except for emissions of CChe, accelerating fleet turnover to cleaner technology
through truck replacements has the potential to reduce emissions significantly through 2035,
despite the projected growth in truck activity. Truck replacement is especially effective in the
year 2025, reducing NOx by about 30 percent and PM by about 70 percent compared to the
BAU case. Note that this strategy would not reduce emissions of CChe in 2025, as it assumes
that trucks would be replaced with newer model year conventional trucks; not until 2035 are
BEV replacements assumed. In 2035, truck replacement still shows benefits, as it would reduce
emissions of NOx by about 30 percent and PM by about 30 percent compared to the BAU case.
Having additional detail, such as the truck age distribution, could have strengthened this
analysis further.
Note that the off-port, onroad inventories for 2015 and BAU years included all vehicles visiting
the Port within these defined corridors, rather than only heavy-duty diesel trucks. Had the BAU
emissions included only trucks, the reductions from the truck replacement strategy would have
resulted in an even larger percentage of total emissions.
3.5
¦
II H
I 11
Truck Replacement (Low) Truck Replacement (High)
Figure 9-9. Off-port Truck NOx Reduction Strategies
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0.35
I I
¦ ¦
I I
s"°
¦ !¦
Truck Replacement (Low) Truck Replacement (High)
Figure 9-10. Off-port Truck PM2.5 Reduction Strategies
I ¦ 2035
¦ 2050
Truck Replacement (Low) Truck Replacement (High)
Figure 9-11. Off-port Truck C02e Reduction Strategies
Table 9-23. Total Reductions from BAU Emissions for Off-port Truck Replacement Scenarios
Year
Scenario
Emissions (tons/year
NOx
PM10
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2025
Low
2.52
0.34
0.32
0.34
0.32
0.15
0.33
-
High
3.12
0.35
0.32
0.35
0.32
0.15
0.33
-
2035
Low
1.25
0.04
0.04
0.04
0.04
0.01
0.06
1,376.60
High
2.00
0.06
0.05
0.06
0.05
0.01
0.09
2,704.37
2050
Low
a
--
--
--
--
--
--
3,255.01
High
--
--
--
--
--
--
--
5,425.02
a A double dash ("-") represents a value that was not calculated as part of this analysis.
¦ 2025
¦ 2035
3
T3
CD
DC
£
O
6,000
5,000
4,000
3,000
2,000
£ 1,000
£
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Table 9-24. Percent Reductions from BAU Emissions for Off-port Truck Replacement
Scenarios
Year
Scenario
Percent Reductions from BAU Emissions
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2025
Low
23.65%
66.91%
67.02%
68.04%
68.04%
67.77%
52.08%
--
High
29.25%
67.67%
67.78%
68.81%
68.81%
68.54%
53.29%
--
2035
Low
18.55%
21.53%
21.55%
22.21%
22.16%
21.52%
18.61%
14.08%
High
29.56%
29.28%
29.39%
30.20%
30.23%
29.35%
28.02%
27.67%
2050
Low
a
--
--
--
--
--
--
28.23%
High
--
--
--
--
--
--
--
47.05%
a A double dash represents a value that was not calculated as part of this analysis.
9.4 Off-port Rail Corridor
The off-port rail corridor was defined as the rail segment that starts at the on-port boundary of
the ICTF spur and extends 10 kilometers north of Port Everglades. The FECR operates both the
on-port ICTF as well as the port-related activity in the rail corridor. As with the off-port marine
and truck corridors, determining the length of the off-port rail corridor was a challenging but
important decision, as it is a primary determinant of the estimated size of the emission
inventory and the potential for emission reductions. For this analysis, a length of 10 kilometers
was chosen, because it is expected that most trains leaving Port Everglades can reach a steady-
state travel speed by this distance. A longer corridor was not selected to simplify the analysis
and to keep the scope of the inventories limited to the vicinity of the Port. Figure 9-12
illustrates the rail corridor, highlighted in green, and Port Everglades, outlined in red.
This section presents the baseline emissions inventory and the projected Business as Usual
emissions for the off-port rail corridor (Section 9.4.1), a discussion of considered strategies to
reduce emissions (Section 9.4.2), and a summary of the related results and lessons learned
(Section 9.4.3).
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Fort
Lauderdale
Legend
Port Everglades
Off-port Rail Corridor
Kilometers
Figure 9-12. Off-port Rail Corridor
9.4.1 Baseline and Projected Business as Usual Inventories
The baseline and BAU projection methodologies used to estimate off-port rail emissions are
consistent with the methodologies used to estimate on-port emissions as described in Section
8.1. To ensure consistency, the same rail throughput was included in both analyses. However,
unlike in the on-port analysis where both idling and transit activity occur, in the off-port rail
corridor, no idling activity was assumed and transit was the only mode of operation included in
the analysis.
In general, the 2015 baseline emissions for each train trip were calculated on an activity basis
using the following equation;
E = LxGTx FCFx EF x UCF Eq. 9-4
Where:
E
Emissions (tons)
L
Length of rail corridor (km)
GT
Gross mass per train (tons)
FCF
Fuel consumption factor (gal/ton-km)
EF
Emission factor (g/gal)
UCF =
Unit conversion factor (l,102xl0~6 ton/g)
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Annual baseline off-port rail emissions were determined by defining a rail corridor length of 10
kilometers and using assumptions that are consistent with the 2015 On-port Baseline Inventory,
such as the number of annual train trips, gross mass per train, fuel consumption factor, and
emission factors.
To estimate BAU off-port rail emissions for future years, the same BAU scenario developed for
the on-port analysis was used for this off-port analysis, based on Port Everglades' 2014
Master/Vision Plan.125 Hypothetical future emission inventories were estimated for 2025,
2035, and 2050126 by starting with the 2015 baseline off-port emissions, applying the projected
container freight growth factors, and then applying adjustment factors based on expected
changes in the fleet emission factors for each future year. See Section 8.1 for further details on
this analysis. A summary of baseline and BAU projected emissions for the off-port rail corridor
are presented in Table 9-25.
Table 9-25. Baseline and Projected BAU Emissions for Off-port Rail Corridor
Year
Mode
Annual Emissions (tons/year)
NOx
PMio
PM2.5
DPM10
DPM2.5
BC
voc
CChe
2015
Transit
2.59
0.04
0.04
0.04
0.04
0.03
0.07
261.04
2025
Transit
2.88
0.06
0.05
0.06
0.05
0.03
0.66
329.95
2035
Transit
2.76
0.07
0.07
0.07
0.07
0.05
1.49
377.09
2050
Transit
a
--
--
--
--
--
--
389.56
a A double dash represents a value that was not calculated as part of this analysis.
Based on the assumptions in this analysis, emissions are projected to increase for most
pollutants due to projected growth in freight throughput. These projections likely overestimate
expected future rail emissions because the assumptions regarding FECR's planned increase in
the use of dual fuel diesel/LNG powered engines assumed a much longer phase in period.
9.4.2 Emission Reduction Strategies and Scenarios
The only on-port rail emission reduction strategy considered was an intermodal shift of cargo
from truck to rail. This serves as an example case where the actions a port takes to reduce
emissions on-port can also reduce emissions beyond the boundary of the port itself. However,
quantifying the emission reductions for the corridors selected in this analysis is of limited value.
Because the truck and rail corridors were defined to be different lengths, emission reductions in
the truck corridor due to this strategy are not directly comparable to the associated emission
increases in the rail corridor. Therefore, emission reductions resulting from the truck-to-rail
intermodal shift strategy are not reported here quantitatively.
Directionally, truck emissions occurring in the off-port onroad truck corridor would be reduced
while locomotive emissions in the off-port rail corridor would increase. It is expected that if the
125 Port Everglades, 2014 Master/Vision Plan reports, June 24, 2014.
126 Note that for 2050, only CChe inventories and reductions were quantified.
9-35
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analysis could calculate total emissions for all trips, from origin to destination, for both truck
and rail modes, the modal shift from truck to rail would result in net decreases in emissions.
9.4.3 Emission Reduction Scenario Results and Lessons Learned
While of limited use for comparing off-port emission reduction strategies for this analysis, the
off-port truck emission inventories and the truck-to-rail intermodal shift strategy emission
reduction results, described in Section 8.3, can be instructive and provide an indication of the
potential of the strategy for reducing emissions off-port. It is important to note that this
analysis benefited from having detailed cargo throughput data to form the basis of these
inventories. Data received from FECR through consultation with Port Everglades improved the
analysis. However further improvements could be achieved by refining the geographical bounds
of the analysis zone to facilitate comparison with the onroad corridor results, as well as
accounting for the conversion of locomotives to dual fuel diesel/CNG engines earlier than what
was assumed in the BAU scenario.
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