Technical Analysis for 

Hawaii’s Regional Haze 

FIP Report – Task 16: 

Commercial Marine 

Inventory

Work Assignment: 5-12

Contract No: EP-D-07-102

Task No: 16

Version: 1

Date

April 26, 2012

Prepared for

US EPA, Region 9

Prepared by

ICF International

620 Folsom St

Suite 200

San Francisco, CA 94107
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

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Table of Contents

1. Introduction .........................................................................................................................1

2. Data Sources .......................................................................................................................3

2.1. Identified Methods ....................................................................................................... 3

2.2. Identified Data Needs .................................................................................................. 3

2.3. Data Collection Approach............................................................................................ 5

3. Modeling Methods...............................................................................................................7

3.1. Category 3 Ships......................................................................................................... 7

3.1.1. Vessel Characteristics...................................................................................... 7

3.1.2. Activity Determinations..................................................................................... 9

3.1.3. Load Factors.................................................................................................. 10

3.1.4. Emission Factors ........................................................................................... 11

3.1.5. Hotelling Time................................................................................................ 15

3.1.6. Class 1 Visibility Area Analyses ..................................................................... 15

3.1.7. Growth Factors .............................................................................................. 18

3.2. Category 1 and 2 Ships ............................................................................................. 18

3.2.1. Ship Characteristics ....................................................................................... 18

3.2.2. Activity Determinations................................................................................... 19

3.2.3. Load Factors.................................................................................................. 19

3.2.4. Emission Factors ........................................................................................... 20

3.2.5. Growth Factors .............................................................................................. 23

4. Analysis of Results ...........................................................................................................25

4.1. Statewide Emissions ................................................................................................. 25

4.2. Hawaii Class 1 Visibility Area Emissions.................................................................... 28

4.3. Maui Class 1 Visibility Area Emissions ...................................................................... 30

5. References.........................................................................................................................32

Appendix A. Category 3 Ship Growth Rate Details...............................................................34

List of Exhibits

Exhibit 1 Identified Approach and Data Needs for Commercial Marine Inventory ........................4

Exhibit 2: EPA Marine Compression Ignition Engine Categories .................................................7

Exhibit 3 Ocean Going Vessel Ship Types ..................................................................................8

Exhibit 4 Marine Engine Speed Designations..............................................................................8

Exhibit 5 Auxiliary Engine Power Ratios......................................................................................9

Exhibit 6 Vessel Movements and Time-In-Mode Descriptions...................................................10

Exhibit 7 Auxiliary Engine Load Factors ....................................................................................10

Exhibit 8 North American ECA Requirements ...........................................................................11

Exhibit 9 2018 Analysis Propulsion Engine Emission Factors ...................................................12

Exhibit 10 2005 Analysis Propulsion Engine Emission Factors .................................................12

Exhibit 11 Low Load Multiplicative Adjustment Factors .............................................................13

Exhibit 12 2018 Analysis Auxiliary Engine Emission Factors, g/kWh.........................................13

Exhibit 13 2005 Analysis Auxiliary Engine Emission Factors, g/kWh.........................................14

Exhibit 14 Auxiliary Boiler Energy Loads, kW............................................................................14
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Exhibit 15 Average Hotelling Times used for 2018 Analyses.....................................................15

Exhibit 16 Center of Class 1 Visibility Areas..............................................................................16

Exhibit 17 Class 1 Visibility Areas .............................................................................................16

Exhibit 18 Ports of Interest within the two Class 1 Visibility Areas .............................................16

Exhibit 19 Inter-Island Cruise Distances within the HACR Class 1 Visibility Area ......................17

Exhibit 20 Cruise Distances from Ports within the HACR Class 1 Visibility Area to 

outside ......................................................................................................................17

Exhibit 21 Cruise Distances from Ports within the HAVO Class 1 Visibility Area to 

outside ......................................................................................................................17

Exhibit 22 Growth Factors for Category 3 Vessels ....................................................................18

Exhibit 23 Assumed Hotelling Times for Category 2 Ships ........................................................19

Exhibit 24 Activity Hours per Call for Category 1 Vessels..........................................................19

Exhibit 25 Category 2 Vessel Auxiliary Engine Load Factors ....................................................20

Exhibit 26 Load Factors for Category 1 Vessels........................................................................20

Exhibit 27 2018 Analysis Category 2 Domestic Engine Emission Factors .................................21

Exhibit 28 2018 Analysis Category 2 Foreign Flag Engine Emission Factors ............................21

Exhibit 29 2005 Analysis Category 2 Engine Emission Factors .................................................21

Exhibit 30 2018 Analysis Category 1 Engine Emission Factors.................................................22

Exhibit 31 2005 Analysis Category 1 Engine Emission Factors .................................................23

Exhibit 32 Hawaiian Island Movement Commodity Data ...........................................................24

Exhibit 33 2018 Category 3 Statewide Emissions by Port .........................................................25

Exhibit 34 Category 3 Statewide Emission Comparisons between 2005 and 2018 ...................26

Exhibit 35 Total Statewide Emission Comparisons....................................................................26

Exhibit 36 2005 Category 1 & 2 Statewide Emissions by Port ...................................................27

Exhibit 37 2018 Category 1 & 2 Statewide Emissions by Port ...................................................27

Exhibit 38 Category 1 & 2 Statewide Emission Comparisons between 2005 and 

2018..........................................................................................................................28

Exhibit 39 Comparison of ICF and Environ Methods .................................................................28

Exhibit 40 2005 Category 3 Hawaii Class 1 Visibility Area Emissions .......................................29

Exhibit 41 2018 Category 3 Hawaii Class 1 Visibility Area Emissions .......................................29

Exhibit 42 2005 Category 1 & 2 Hawaii Class 1 Visibility Area Emissions .................................29

Exhibit 43 2018 Category 1 & 2 Hawaii Class 1 Visibility Area Emissions .................................29

Exhibit 44 2005 Category 3 Maui Class 1 Visibility Area Emissions ..........................................30

Exhibit 45 2018 Category 3 Maui Class 1 Visibility Area Emissions ..........................................30

Exhibit 46 2005 Category 1 & 2 Maui Class 1 Visibility Area Emissions ....................................31

Exhibit 47 2018 Category 1 & 2 Maui Class 1 Visibility Area Emissions ....................................31

Exhibit 48 Growth Projections for Auto Carriers ........................................................................34

Exhibit 49 Growth Projections for Bulk Carriers.........................................................................35

Exhibit 50 Growth Projections for Container Ships ....................................................................35

Exhibit 51 Growth Projections for General Cargo Ships ............................................................36

Exhibit 52 Growth Projections for Miscellaneous Ships .............................................................36

Exhibit 53 Growth Projections for Passenger/Cruise Ships .......................................................37

Exhibit 54 Growth Projections for RoRo Ships ..........................................................................37

Exhibit 55 Growth Projections for Tanker Ships ........................................................................38

Exhibit 56 Growth Projections for Ocean Going Tugs................................................................38
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1. Introduction

ICF International, though the University of North Carolina, is assisting the US EPA, Region 9 Air 

Division in developing Federal Implementation Plans (FIPs) to establish air quality programs for 

Arizona and Hawaii pursuant to Clean Air Act Section 169A and Regional Haze Rule (RHR), 

40CFR 51.308. Several tasks are addressed under this work assignment. The present report 

deals solely with an update to the commercial marine emission inventory for the State of Hawaii

under Task 16. 

This update is intended to account for recent changes in economic projections as a result of the 

recent global recession not considered in prior analysis. It also accounts for changes in the 

inventory resulting from the establishment of a North American Emission Control Area (NA 

ECA) which regulates fuel sulfur levels and NOx emission control for ships passing within 200 

nautical miles (nm) of the Hawaiian Islands. 

The technical portion of this task consisted of three basic components: 

Assessment of existing data and methods; 

Collection and assembly of remaining data needed for analysis; 

Performing emissions analysis of ship movements to produce an inventory of NOx, CO, 

HC, PM10, PM2.5, SOx and CO2 for 2018 within 30 nm of the various seaports in the State 

of Hawaii; and 

Performing emissions analysis of ship movements within the two Class 1 Visibility Areas 

influencing Hawaii Volcanoes and Haleakala National Parks for 2005 and 2018. 

This report documents each of these phases.
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2. Data Sources

2.1. Identified Methods

ICF received a variety of data through EPA and the State of Hawaii prepared for their most 

recent analysis.1 The documentation and data included:

1. A comparison of the two existing inventories performed with various methods and 

purposes for calendar year 2005, one for AirSHED and one prepared for the NEI. All 

data was provided by the Hawaii Department of Health (DOH). 

2. Ship call data for 2005 for the ports of Hilo, Honolulu, Barbers Point Harbor, Kahului, and 

Nawiliwili.

Based on these items, we agree with the prior assessments that the AirSHED estimates are 

superior to NEI estimates for our purposes since they take into account Hawaii’s local 

information more completely. However, neither set is complete for 2018. Also, the effects of the 

recently adopted NA ECA had notably not yet been included in the AirSHED estimates. 

Based on the information provided and available data, ICF determined an approach to perform 

this analysis using the methodology laid out in the EPA guidance document for preparing port 

emissions inventories2and assessed the remaining data needs for preparing emission 

inventories for 2005 and 2018.

2.2. Identified Data Needs

Using the EPA guidance document for preparing port emission inventories discussed above ICF 

developed a methodology to calculate port emission inventories for the various ports within the 

state of Hawaii for 2018 and for the ports and movements within the two Class 1 Visibility Areas 

for 2005 and 2018. In order to produce these inventories, ICF developed a list of the needed 

inputs for an analysis, then reviewed all the information provided, and assessed its suitability for 

developing port inventories to identify remaining data needs. 

In addition to the technical assessment, a guiding concern for this analysis was available time. 

Given the highly compressed schedule under which this project was performed, a guiding 

principal of the analysis was use readily available data as much as possible, while 

simultaneously exploring the availability of other data from various Federal, State and Local 

sources. However, budget and time severely limited the amount of new data collection allowed. 

 

1

Environ International Corp., "Hawaii Commercial Marine Vessel Activity and Emissions, Technical Memorandum", 

December 30, 2009, Appendix B to "Final Emission Inventory Report: Data Population of Air System for Hawaii’s 

Emissions Data (AirSHED), April 12, 2010.

2

ICF International, Current Methodologies in Preparing Mobile Source Port Related Emission Inventories, Final 

Report, Prepared for U.S. Environmental Protection Agency Sector Strategies Program, April 2009. 

http://www.epa.gov/sectors/sectorinfo/sectorprofiles/ports/ports-emission-inv-april09.pdf.
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

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Error! Reference source not found. lists the final set of data whose needs were identified and 

provides an overview of the method employed in the analysis. Details are provided in the exhibit 

below. 

Exhibit 1 Identified Approach and Data Needs for Commercial Marine Inventory

Input Typical Data Sources General Approach

Ship Calls

Marine Exchange/Port 

Authority (MEPA) Data or US 

Army Corps of Engineers 

(USACE) Entrances and 

Clearances Data

MEPA data was not available after 2005. Because ICF was projecting to 

2018, USACE Entrances and Clearances data for 20093(latest year 

available) was used for Ocean Going Vessels (OGVs). Since the Entrances 

and Clearances data only covers foreign cargo movements, IHS Fairplay

Movements data4was used for 2009 for domestic OGVs and tug/barge, 

ferry and workboat movements. Because timing didn't allow ICF to 

purchase Lloyds Movement data for 2005, 2009 Movements data was used 

with growth factors to predict tug/barge, ferry and workboat movements for 

2005. Call data supplied by Hawaii State Department5of Health was used 

for 2005 ship calls for the Class 1 Visibility Areas.

Ship 

Characteristics

Lloyds Register of Ships Data 

(Sea-web)

Data on ship characteristics was taken directly from Sea-web6. In most 

cases, auxiliary engine data was not available for OGVs so ratios of 

auxiliary to propulsion power were developed from recent Port of Los 

Angeles7and Port of Long Beach8data and applied to the propulsion power 

found in Sea-web.

Age Profile

Lloyds Register of Ships Data 

(Sea-web)

For the 2005 analysis, actual ship build dates were used to generate the 

age profile. For the 2018 analysis, the build dates for the 2009 call and ship 

characteristics data was used and all build dates were increased by 9 years 

to obtain the age profile for the 2018 analysis.

Growth Factors Varies

Growth factors for OGVs were determined from USACE Entrances and 

Clearances data from 2002 to 2009. Yearly changes were averaged and 

used to project growth from 2009 to 2018. For tugs/barges, ferries and 

workboats, USACE commodity tonnage movements9within Hawaii 

movements (Hawaii to Hawaii) from 2001 to 2010 was used to project 

growth to 2018.

Distances 

between Ports Varies

Google Earth10 was used to determine the 150 km Class 1 Visibility Areas 

as well as distances travelled within those areas between ports.

 

3

U.S. Army Corps of Engineers Navigation Data Center, Foreign Traffic Vessel Entrances and Clearances. 

http://www.ndc.iwr.usace.army.mil//data/dataclen.htm. 

4

IHS Fairplay Sea-web Movements Module, http://www.sea-web.com/seaweb_Movements_module.html

5

Email from Scott Takamoto, Hawaii State Department of Health, February 29, 2012.

6

IHS Fairplay Sea-web, http://www.sea-web.com

7

Starcrest Consulting Group, Port of Los Angeles Air Emissions Inventory -- 2010, July 2011. 

http://www.portoflosangeles.org/pdf/2010_Air_Emissions_Inventory.pdf

8

Starcrest Consulting Group, Port of Long Beach Air Emissions Inventory -- 2010, July 2011. 

http://www.polb.com/environment/air/emissions.asp

9

.S. Army Corps of Engineers Navigation Data Center, State to State Commodity Tonnages. 

http://www.ndc.iwr.usace.army.mil//data/datapdom.htm

10 http://www.google.com/earth/index.html
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2.3. Data Collection Approach

To collect the information identified above, we first followed EPA guidance and contacted Scott 

Takamoto at Hawaii’s Department of Health (DOH). Mr. Takamoto provided a collection of port 

call data files for previous modeling efforts done by ENVIRON. These were used as the basis of 

the 2005 inventory modeling for the two Class 1 Visibility Areas. The data provided ship name, 

date and time of arrival, date and time of departure, port of origin and port departing to for each 

call. Ship names were used to find International Maritime Organization (IMO) numbers for the 

corresponding ship. In addition, average hotelling times by port and ship type were determined 

from this data and used in the 2018 projections. 

For 2018 inventories, entrances and clearances data from U.S. Army Corps of Engineers for 

2009 was used. This provided data on foreign cargo movements. The Maritime Administration 

(MARAD) maintains the Foreign Traffic Vessel Entrances and Clearances database, which 

contains statistics on U.S. foreign maritime trade. Data are compiled during the regular 

processing of statistics on foreign imports and exports. The database contains information on 

the type of vessel, commodities, weight, customs districts and ports, and origins and 

destinations of goods. Unfortunately , this data only represents foreign cargo movements. Thus 

domestic traffic, U.S. ships delivering cargo from one U.S. port to another U.S. port covered 

under the Jones Act11, is not accounted for in the database. To estimate domestic cargo

movements by ocean going vessels, tugs/barges, ferries and workboats, the Sea-web 

Movements module was used to gather data for 2009. Unfortunately due to time constraints, 

movement data for 2005 could not be obtained and thus 2009 domestic tug/barge, ferry and 

work boat movements were scaled to 2005 using growth factors.

Ship characteristic data was taken Sea-web by matching the IMO number for a given ship with 

the Sea-web database. IHS Fairplay Sea-web provides details on more than 180,000 ships 

over 100 gross tons. Sea-Web provided data on ship characteristics such as ship type, build 

year, total propulsion power, propulsion engine cylinder bore and stroke, service speed, flag, 

and dead weight tons (DWT). Propulsion engine cylinder bore and stroke were used to 

determine EPA marine engine categories described in Section 3.

Growth factors were determined from USACE Entrances and Clearances data from 2002 to 

2009. Installed Power, calls times total propulsion power, was used as a metric from emission 

growth. Installed power was calculated by ship type for each year. Average growth from year 

to year was calculated and used to project from 2009 to 2018 for OGVs. For tugs/barges, 

ferries and workboats, commodity tons moved within Hawaii was determined from the USACE 

State to State Commodity Tonnages database from 2001 to 2010 and extrapolated to 2018 as 

described in Section 3. Growth from 2005 to 2009 was also determined using this method to 

project the 2009 domestic movements data to 2005.

 

11 Merchant Seaman Protection and Relief 46 USCS Appx § 688 (2002) Title 46. Appendix. Shipping Chapter 18.
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Distances within the Class 1 Visibility Areas traveled were determined using Google Earth. The 

most likely route was mapped and measured.
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3. Modeling Methods 

The current practice to calculate emissions from ships is to use energy-based emission factors 

together with activity profiles for each vessel. The bulk of the work involves determining 

representative engine power ratings for each vessel and the development of activity profiles for 

each ship call. Using this information, emissions per ship call and mode can be determined 

using the equation below.

E = P x LF x A x EF

Where E = Emissions (grams [g])

P = Maximum Continuous Rating Power (kilowatts [kW])

LF = Load Factor (percent of vessel’s total power)

A = Activity (hours [h])

EF = Emission Factor (grams per kilowatt-hour [g/kWh])

The emission factor is in terms of emissions per unit of energy from the engine. It is multiplied 

by the power needed to move the ship in a particular activity.

The methodology described below is different based upon the propulsion engine category 

described in Exhibit 2. Each methodology is described in below

Exhibit 2: EPA Marine Compression Ignition Engine Categories

Category Specification Use

Approximate 

Power 

Ratings

1

Gross Engine Power ≥ 37 kWa

Displacement < 7 liters per cylinder

Small tugs, fishing and 

workboats. Smaller auxiliary 

engines

< 1,000 kW

2

Displacement ≥ 7 and < 30 liters 

per cylinder

OGV auxiliary engines, larger 

tug, ferry, fishing and workboat 

propulsion engines

1,000 – 3,000 

kW 

3 Displacement ≥ 30 liters per cylinder OGV propulsion > 3,000 kW

a EPA assumes that all engines with a gross power below 37 kW are used for recreational 

applications and are treated separately from the commercial marine category.

3.1. Category 3 Ships

3.1.1. Vessel Characteristics

Ocean going vessels (OGV) typically have Category 3 propulsion engines. OGVs vary greatly 

in speed and engine sizes based on ship type. Various studies break out vessel types 

differently, but it makes most sense to break vessel types out by the cargo they carry. Exhibit 3 

lists various OGV types that should be described in any detailed inventory. 

Other characteristics that should be determined from Lloyd’s Data are the propulsion engine 

power, type and engine speed, build date, and vessel service speed. Engine speed 
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

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designations are shown in Exhibit 4. Most ships have diesel engines, although some older ships 

are steamships. . Generally auxiliary engine power is not readily available but can be estimated 

from the Ports of Los Angeles and Long Beach Air Emissions Inventories.12 13 Calculated 

auxiliary to propulsion power ratios by ship type can be found in Exhibit 5.

Exhibit 3 Ocean Going Vessel Ship Types

Ship Type Description

Auto Carrier Self-propelled dry-cargo vessels that carry containerized automobiles.

Bulk Carrier Self-propelled dry-cargo ship that carries loose cargo.

Container Ship Self-propelled dry-cargo vessel that carries containerized cargo.

Cruise Ship Self-propelled cruise ships.

General Cargo Self-propelled cargo vessel that carries a variety of dry cargo.

Miscellaneous Category for those vessels that do not fit into one of the other categories or 

are unidentified.

Oceangoing 

Tugs/Tows

Self-propelled tugboats and towboats that tow/push cargo or barges in the 

open ocean.

Reefer Self-propelled dry-cargo vessels that often carry perishable items.

Roll-on/Roll-off 

(RORO)

Self-propelled vessel that handles cargo that is rolled on and off the ship, 

including ferries.

Tanker Self-propelled liquid-cargo vessels including chemical tankers, petroleum 

product tankers, liquid food product tankers, etc.

Exhibit 4 Marine Engine Speed Designations

Speed Category Engine RPMa Engine Stroke Type

Slow < 130 RPM 2

Medium 130 – 1,400 RPM 4

High > 1,400 RPM 4

a RPM = revolutions per minute

 

12 Starcrest Consulting Group, Port of Los Angeles Air Emissions Inventory -- 2010, July 2011. 

http://www.portoflosangeles.org/pdf/2010_Air_Emissions_Inventory.pdf.

13 Starcrest Consulting Group, Port of Long Beach Air Emissions Inventory -- 2010, July 2011. 

http://www.polb.com/environment/air/emissions.asp
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Exhibit 5 Auxiliary Engine Power Ratios

Ship Type

Auxiliary to 

Propulsion 

Power Ratio

Auto Carrier 0.472

Bulk Carrier, General 0.248

Bulk Carrier, Heavy Load 0.390

Bulk Carrier, Wood Chips 0.201

Container 0-1000 TEUs 0.220

Container 1000-2000 TEUs 0.220

Container 2000-3000 TEUs 0.224

Container 3000-4000 TEUs 0.127

Container 4000-5000 TEUs 0.253

Container 5000-6000 TEUs 0.154

Container 6000-7000 TEUs 0.152

General Cargo 0.278

Miscellaneous 0.236

Passenger/Cruise Ship 0.094

RoRo 0.706

Reefer 0.281

Tanker 0-30K DWT 0.356

Tanker 30-60K DWT 0.200

Tanker 60-90K DWT 0.212

Tanker 90-120K DWT 0.207

Tanker > 120K DWT 0.169

Tugs 0.018

3.1.2. Activity Determinations

Ship activity during a typical port call is best accomplished by breaking down the call into 

sections that have similar speed characteristics. Vessel movements for each call are described 

by using five distinct time-in-mode calculations. A call combines all modes. Each time-in-mode 

is associated with a speed and, therefore, an engine load that has unique emission 

characteristics. While there will be variability in each vessel’s movements within a call, these 

time-in-modes allow an average description of vessel movements at each port. Time-in-modes 

should be calculated for each vessel call occurring in the analysis year over the waterway area 

near the port. The time-in-modes are described in Exhibit 6.
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Exhibit 6 Vessel Movements and Time-In-Mode Descriptions

Activity Description

Cruise

This is time during which the ship is in open water and at service speed. Service speed is 

considered to be 94 percent of maximum speed and 83 percent of maximum continuous 

rating (MCR). This mode starts 5 nm from the port entrance.

Reduced Speed Zone 

(RSZ)

Time at 70 percent of maximum speed (34 percent MCR) as a ship approaches the port. 

This mode is from 5 nm to 1 nm before reaching and after leaving a port.

Pilot Pick up During the last (first) nm before reaching a port (or upon leaving a port), the vessel must 

slow to pick up (or drop off) a pilot to guide the ship into port. Speed is set at 5 knots.

Maneuver Time in the port area between the breakwater and the dock. Maneuvering within a port is 

assumed to occur at 4 knots on average.

Hotelling

Hotelling is the time at the dock when the vessel is operating auxiliary engines only to 

generate power for all onboard power or are used to power off-loading equipment, or 

both.

3.1.3. Load Factors

Load factors are expressed as a percent of the vessel’s total propulsion or auxiliary power. At 

service or cruise speed, the propulsion load factor is assumed to be 83 percent. At lower 

speeds, the Propeller Law should be used to estimate ship propulsion loads, based on the 

theory that propulsion power varies by the cube of speed as shown in the equation below.

LF = (AS/MS)3

Where LF = Load Factor (percent)

AS = Actual Speed (knots)

MS = Maximum Speed (knots)

While load factors should be calculated using the above propeller law for each call, load factors 

below 2 percent should be set to 2 percent as a minimum. Load factors for auxiliary engines 

vary by ship type and time-in-mode. Auxiliary engines are on all of the time. Auxiliary engine 

load factors for OGVs are given in Exhibit 7.

Exhibit 7 Auxiliary Engine Load Factors

Ship Type Cruise RSZ Pilot Maneuver Hotel

Auto Carrier 0.15 0.30 0.45 0.45 0.26

Bulk Carrier 0.17 0.27 0.45 0.45 0.10

Container Ship 0.16 0.25 0.55 0.55 0.16

Passenger Ship 0.80 0.80 0.80 0.80 0.64

General Cargo 0.17 0.27 0.45 0.45 0.22

Miscellaneous 0.17 0.27 0.45 0.45 0.22

RoRo 0.15 0.30 0.45 0.45 0.26

Reefer 0.15 0.30 0.45 0.45 0.32

Tanker 0.13 0.24 0.33 0.33 0.26

Tugs 0.17 0.27 0.45 0.45 0.22
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3.1.4. Emission Factors

The United States Government, together with Canada and France, has established a North 

American Emission Control Area (NA ECA) that will put in place lower sulfur marine fuel 

standards and other requirements beginning in August 2012. The ECA was established under 

the auspices of Annex VI of the International Convention for the Prevention of Pollution from 

Ships ((MARPOL Annex VI), a treaty developed by the International Maritime Organization. 

This ECA will require use of lower sulfur fuels in ships operating within 200 nautical miles of the 

majority of the U.S. and Canadian coastline, including the U.S. Gulf Coast. Exhibit 8 shows the 

NOx and fuel sulfur reductions required by the ECA.

Exhibit 8 North American ECA Requirements

Requirements Outside ECA Inside ECA

NOx 20% reduction in new 

vessels by 2011 

80% reduction in new 

vessels by 2016

Fuel Sulfur (%) – 2012: 3.50%

– 2020: 0.50%

– The 2020 fuel 

standard could be 

delayed to 2025; 

subject to 2018 fuel 

availability review

– 2010-14: 1.00%

– 2015: 0.10%

In addition, the International Maritime Organization (IMO) adopted NOx limits in Annex VI to the 

International Convention for Prevention of Pollution from Ships in 1997. These NOx limits apply 

for all marine engines over 130 kilowatts (kW) for engines built on or after January 1, 2000, 

including those that underwent a major rebuild after January 1, 2000.

Emission factors for OGV propulsion engines are given in Exhibit 9 for slow speed diesel 

engines (SSD), medium speed diesel engines (MSD), gas turbines (GT) and steam turbines 

(ST) for the 2018 analysis and are based upon using a marine gas oil (MGO) with a sulfur level 

of 0.1 percent. These are based upon studies done by Entec. 14 The factors from the Entec

study are generally accepted as the most current set available. The Entec analysis included 

emissions data from 142 propulsion engines and 2 of the most recent research programs: 

Lloyd’s Register Engineering Services in 1995 and IVL Swedish Environmental Research 

Institute in 2002. Emission factors for the 2005 analysis are given in Exhibit 10 and are based 

upon using residual oil (RO) with a fuel sulfur level of 2.7 percent.

 

14 Entec UK Limited, Quantification of Emissions from Ships Associated with Ship Movements between Ports in the 

European Community, prepared for the European Commission, July 2002. Available at 

http://www.europa.eu.int/comm/environment/air/background.htm
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Exhibit 9 2018 Analysis Propulsion Engine Emission Factors

Build Years Engine 

Type

Propulsion Engine Emission Factors (g/kWh)

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

Pre-2000

MSD 13.2 1.1 0.5 0.19 0.17 0.40 646.08 203

SSD 17.0 1.4 0.6 0.19 0.17 0.36 588.79 185

STM 2.0 0.2 0.1 0.17 0.15 0.57 922.97 290

GT 5.7 0.2 0.1 0.17 0.15 0.57 922.97 290

2000 -2015

MSD 11.8 1.1 0.5 0.19 0.17 0.40 646.08 203

SSD 15.1 1.4 0.6 0.19 0.17 0.36 588.79 185

STM 2.0 0.2 0.1 0.17 0.15 0.57 922.97 290

GT 5.7 0.2 0.1 0.17 0.15 0.57 922.97 290

2016+

MSD 2.4 1.1 0.5 0.19 0.17 0.40 646.08 203

SSD 3.0 1.4 0.6 0.19 0.17 0.36 588.79 185

STM 2.0 0.2 0.1 0.17 0.15 0.57 922.97 290

GT 5.7 0.2 0.1 0.17 0.15 0.57 922.97 290

Exhibit 10 2005 Analysis Propulsion Engine Emission Factors

Build Years Engine 

Type

Propulsion Engine Emission Factors (g/kWh)

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

Pre-2000

MSD 14.0 1.1 0.5 1.05 0.97 11.24 677.91 213

SSD 18.1 1.4 0.6 0.98 0.91 10.29 620.62 195

STM 2.1 0.2 0.1 1.41 1.30 16.10 970.71 305

GT 6.1 0.2 0.1 1.41 1.30 16.10 970.71 305

2000+ 

MSD 12.5 1.1 0.5 1.05 0.97 11.24 677.91 213

SSD 16.1 1.4 0.6 0.98 0.91 10.29 620.62 195

STM 2.1 0.2 0.1 1.41 1.30 16.10 970.71 305

GT 6.1 0.2 0.1 1.41 1.30 16.10 970.71 305

Emission factors are considered to be constant down to about 20 percent load. Below that 

threshold, emission factors tend to increase as the load decreases. This trend results because 

diesel engines are less efficient at low loads and the BSFC tends to increase. Thus, while mass 

emissions (grams per hour) decrease with low loads, the engine power tends to decrease more 

quickly, thereby increasing the emission factor (grams per engine power) as load decreases. 

The low load factors shown in Exhibit 11 were applied to MSD and SSD engines only. In 

addition, the low load factors should not be applied to ships with electric drive propulsion.
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Exhibit 11 Low Load Multiplicative Adjustment Factors

Load NOx CO HC PM SO2 CO2

2% 4.63 9.68 21.18 7.29 3.36 3.28

3% 2.92 6.46 11.68 4.33 2.49 2.44

4% 2.21 4.86 7.71 3.09 2.05 2.01

5% 1.83 3.89 5.61 2.44 1.79 1.76

6% 1.60 3.25 4.35 2.04 1.61 1.59

7% 1.45 2.79 3.52 1.79 1.49 1.47

8% 1.35 2.45 2.95 1.61 1.39 1.38

9% 1.27 2.18 2.52 1.48 1.32 1.31

10% 1.22 1.96 2.20 1.38 1.26 1.25

11% 1.17 1.79 1.96 1.30 1.21 1.21

12% 1.14 1.64 1.76 1.24 1.18 1.17

13% 1.11 1.52 1.60 1.19 1.14 1.14

14% 1.08 1.41 1.47 1.15 1.11 1.11

15% 1.06 1.32 1.36 1.11 1.09 1.08

16% 1.05 1.24 1.26 1.08 1.07 1.06

17% 1.03 1.17 1.18 1.06 1.05 1.04

18% 1.02 1.11 1.11 1.04 1.03 1.03

19% 1.01 1.05 1.05 1.02 1.01 1.01

20% 1.00 1.00 1.00 1.00 1.00 1.00

As with propulsion engines, the most current set of auxiliary engine emission factors comes 

from Entec except as noted above. Exhibit 12 provides these auxiliary engine emission factors

for the 2018 analysis based upon using MGO with 0.1 percent sulfur. . 

Exhibit 12 2018 Analysis Auxiliary Engine Emission Factors, g/kWh

Build Year

Auxiliary Engine Emission Factors (g/kWh)

NOx PM10 PM2.5 HC CO SOx CO2 BSFC

Pre-2000 13.9 0.18 0.17 0.40 1.10 0.42 690.64 217

2000 - 2015 12.4 0.18 0.17 0.40 1.10 0.42 690.64 217

2016+ 2.5 0.18 0.17 0.40 1.10 0.42 690.64 217

For the 2005 analysis, ARB survey15 results were used to compute auxiliary engine emission 

factors. The survey found that only 29 percent of all ships (except passenger ships) used 

marine diesel oil (MDO) in their auxiliary engines, with the remaining 71 percent using RO. 

However, only 8 percent of passenger ships used MDO in their auxiliary engines, while the 

other 92 percent used RO. The results of this survey were used as reasonable approximations 

for calculations of emission factors assuming RO with 2.7 percent fuel sulfur and MDO with 1.5 

 

15 California Air Resources Board, 2005 Oceangoing Ship Survey, Summary of Results, September 2005.
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percent fuel sulfur. The auxiliary engine emission factors used for the 2005 analysis are shown 

in Exhibit 13.

Exhibit 13 2005 Analysis Auxiliary Engine Emission Factors, g/kWh

Build Years Ship Type

Auxiliary Engine Emission Factors, g/kWh

NOx CO HC PM10 PM2.5 SO2 CO2

Pre-2000

Passenger 14.6 1.1 0.4 1.07 0.99 11.53 719.92

Other 14.5 1.1 0.4 0.98 0.90 10.35 713.24

2000+

Passenger 13.0 1.1 0.4 1.07 0.99 11.53 719.92

Other 12.9 1.1 0.4 0.98 0.90 10.35 713.24

In addition to the auxiliary engines that are used to generate electricity onboard ships, most 

OGVs also have boilers used to heat RO to make it fluid enough to use in diesel engines and to 

produce hot water. These boilers are not typically used during cruise or reduced speed zone 

modes because most vessels are equipped with exhaust heat recovery systems 

("economizers") that use heat from the main engine's exhaust for their hot water needs. The 

fuel-fired boilers are used when the main engine exhaust flow and/or temperature fall below 

what is needed for the economizer to provide adequate heat, such as during maneuvering and 

when the main engines are shut down at berth. Auxiliary boiler energy loads are presented in

Exhibit 14 and come from the 2010 Port of Los Angeles emissions inventory.

16

Exhibit 14 Auxiliary Boiler Energy Loads, kW

Ship Type

Boiler Load, kW

Maneuver Hotel

Auto Carrier 246 246

Bulk Carrier 137 137

Container 0-1000 TEU 228 228

Container 1000-2000 TEU 348 348

Container 2000-3000 TEU 497 497

Container 3000-4000 TEU 530 530

Container 4000-5000 TEU 629 629

Container 5000-6000 TEU 578 578

Container 6000-7000 TEU 497 497

Passenger Ship 1393 1393

General Cargo 137 137

Miscellaneous 137 137

RORO 301 301

 

16 Starcrest Consulting Group, Port of Los Angeles Air Emissions Inventory -- 2010, July 2011. 

http://www.portoflosangeles.org/pdf/2010_Air_Emissions_Inventory.pdf.
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Ship Type

Boiler Load, kW

Maneuver Hotel

Reefer 212 212

Tanker 371 2500

Tug 0 0

Steam turbine propulsion emission factors were used for calculating boiler emissions in the 

various modes. Emissions from boilers should be calculated as follows.

Boiler emissions (g/mode) = Boiler Energy (kW) x ST EFs (g/kWh) x time in mode (hrs)

Cruise ships and tankers have much higher auxiliary boiler usage rates than the other vessel 

types. Cruise ships have higher boiler usage due to the number of passengers and need for hot 

water. Tankers provide steam for steam-powered liquid pumps, inert gas in fuel tanks, and to 

heat fuel for pumping.

3.1.5. Hotelling Time

The 2005 ship call data received from Hawaii Department of Health was used directly to 

calculate hotelling times (departure date and time - arrival date and time) for all ships for the 

2005 analyses. For the 2018 analyses, average hotelling times by ship type by port were used 

and are listed in Exhibit 15.

Exhibit 15 Average Hotelling Times used for 2018 Analyses

Ship Type

Hotelling Time, hours

Honolulu Barbers 

Point Kahului Nawiliwili Hilo

Auto Carrier 12.00 7.80 5.95 6.70

Bulk Carrier, General 41.68 154.68 34.93

Bulk Carrier, Heavy Load 57.06 36.50

Bulk Carrier, Wood Chips 11.61

Container Ship 45.04 9.47 7.03

Fishing 13.67

General Cargo 42.87 189.20 31.23

Passenger/Cruise 16.84 33.84 19.12 9.28

Reefer 14.11

RoRo 26.75 10.10 8.04

Tanker 43.57 25.49 11.33 11.92 30.48

Tug 119.89 27.85

3.1.6. Class 1 Visibility Area Analyses

An additional task requested under this work assignment was the determination of ship 

emissions that influences the two Class 1 Visibility Areas: Haleakala and Hawaii Volcanoes 
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National Parks. The locations of the monitors were representing each park were provided by 

EPA and are listed in Exhibit 16. A radius of 150 km was chosen for each park following EPA 

recommendations and is shown in Exhibit 17. Ports of interest within the two Class 1 areas are 

listed in Exhibit 18.

Exhibit 16 Center of Class 1 Visibility Areas

Monitor Latitude Longitude

Haleakala (HACR) 20o 45' 30.6" N 156o 16' 56.28" W

Hawaii (HAVO) 19o 25' 50.84" N 155o 15' 28.44 W

Exhibit 17 Class 1 Visibility Areas

Exhibit 18 Ports of Interest within the two Class 1 Visibility Areas

Class 1 Visibility Area Ports of Interest

Maui (HACR)

Kahului, Maui

Lahaina, Maui

Kona, Hawaii

Kawaihae, Hawaii

Hawaii (HAVO)

Hilo, Hawaii

Kona, Hawaii

Kawaihae, Hawaii
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In addition to emissions generated from the ports within the two Class 1 Visibility Areas, there is 

also innocent passage. Innocent passage is related to ships that travel within the Class 1 areas 

(from a port outside the Class 1 area to a port outside the Class 1 area) but do not stop within 

the Class 1 area. All innocent passage is assumed to occur in cruise mode. Distances used to 

calculate cruise within the Maui Class 1 area from Hawaiian port to Hawaiian port are given in 

Exhibit 19 and from Hawaiian ports of interest to areas outside the Hawaiian islands are given in 

Exhibit 20. Cruise distances for the Hawaii Class 1 area is shown in Exhibit 21. For inter-island 

distances, half the cruise distance was applied to the port of origin and half to the destination 

port.

Exhibit 19 Inter-Island Cruise Distances within the HACR Class 1 Visibility Area

From/To

Cruise Distances, nautical miles

Nawiliwili Honolulu Kahului Lahaina Hilo Kawaihae Kona

Nawiliwili 0 0 70 72 168 114 144

Honolulu 0 0 76 54 180 114 130

Kahului 70 76 0 30 102 94 124

Lahaina 54 54 30 0 110 64 82

Hilo 168 180 102 110 0 76 12

Kawaihae 114 114 94 64 76 0 32

Kona 144 130 124 82 12 32 0

Exhibit 20 Cruise Distances from Ports within the HACR Class 1 Visibility Area to outside

From/To Nautical 

Miles

Honolulu ↔ West Coast 97

Honolulu ↔ East Asia 22

Honolulu ↔ Out to Sea 50

Kahului ↔ West Coast 78

Kahului ↔ East 70

Hilo ↔ East 158

Exhibit 21 Cruise Distances from Ports within the HAVO Class 1 Visibility Area to outside

From/To Nautical 

Miles

Hilo ↔ West Coast 58

Hilo ↔ East or North 68

Hilo ↔ Southeast 115

Hilo ↔ Kona 170

Kona ↔ West Coast 120

Kona ↔ East or North 34

Kawaihae ↔ North 35
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3.1.7. Growth Factors

In order to project emissions from Category 3 ships in 2018 from 2009 call data, growth factors 

needed to be developed. There are several trends that can be examined to develop growth 

factors such as cargo moved and other economic indicators. However, the best indicator of 

emission growth is the growth in ship installed power over time. Installed power is defined as 

total ship propulsion power times number of calls. It is directly related to emission production. 

U.S. Army Corps of Engineers maintains the entrances and clearances data of all foreign cargo 

movements. While domestic cargo movements are not included, the entrances and clearances 

data is a good indicator of ship call data for category 3 vessels since most ships are foreign flag. 

Entrance and clearance data from 2002 to 2009 were analyzed and matched with IHS Sea-web 

data to determine ship type and total propulsion power for ships that stopped at Hawaiian island 

ports. Because of the Great Recession, cargo movements during the period 2009 through 2011 

were depressed. Thus growth during 2009 through 2011 was estimated as reduced. From 

2012 through 2018, growth was calculated as the average growth during the period 2004 to 

2008. The resulting growth factors are shown in Exhibit 22 for the period 2009 to 2018 and 

compared against actual growth during the period 2002 through 2009. More details on growth 

factor development can be found in Appendix A.

Exhibit 22 Growth Factors for Category 3 Vessels

Ship Type

Growth Factors

2002-2009 2009-2018

Auto Carrier 1.023 1.152

Bulk Carrier 0.691 1.012

Container Ship 2.222 2.952

General Cargo 2.028 2.142

Miscellaneous 2.521 2.554

Passenger 0.431 1.772

RoRo 0.055 2.053

Tanker 1.371 1.695

Tug 1.827 1.447

3.2. Category 1 and 2 Ships

3.2.1. Ship Characteristics

Category 1 and 2 ships are typically tugs and tows that move barges from port to port and within 

a port, commercial fishing vessels, ferries and workboats such as anchor handling tug supply 

boats, research survey boats, cable layers and patrol boats. In addition, some smaller OGVs 

have Category 2 propulsion engines. All Category 2 ships had Category 1 auxiliary engines.

Ship calls for 2009 were obtained from the IHS Sew-web Movements Module for Barbers Point 

Harbor, Hilo, Honolulu, Kahului, Kawaihae, and Nawiliwili. The data included ship name, IMO 
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number, the port they stopped at and the dates of arrival and departure. These were matched 

using IMO numbers to Sea-Web to obtain ship type, propulsion and auxiliary engine power, 

propulsion engine bore and stroke, build year, service speed and flag. Propulsion engine bore 

and stroke was used to determine EPA engine category.

3.2.2. Activity Determinations

Since specific port of origin and port of destination information was not readily available, for 

purposes of these analyses, all Category 2 ships were assumed to travel from port to port while 

all Category 1 ships were assumed to operate within a port. Date of arrival and departure and 

port were used to determine movements for Category 2 ships. Category 2 ships were assumed 

to operate in four modes, namely cruise at service speed up to 5 nm from a port, RSZ at 70 

percent maximum speed up to 5 nm from a port, maneuvering within a port at 4 knots, and 

hotelling. For the statewide inventory, cruise distances of 25 nm were used, while for the Class 

1 area analyses, distances listed in Exhibits 19 through 21 were used. Estimated hotelling 

times for Category 2 ships are given in Exhibit 23.

Exhibit 23 Assumed Hotelling Times for Category 2 Ships

Ship Type Hours

Bulk Carrier 35.00

Ferry 6.80

Fishing 13.70

General Cargo 31.00

RoRo 8.00

Tanker 11.50

Tug 28.00

Work Boat 28.00

For Category 1 ships, average operating times per call were estimated from the EPA guidance 

on preparing port inventories and the average number of calls per ship per port. Operating 

times for propulsion and auxiliary engines are shown in Exhibit 24.

Exhibit 24 Activity Hours per Call for Category 1 Vessels

Ship Type

Hours per call

Propulsion Auxiliary

Fishing 38.00 17.30

Tug 27.90 24.20

Work Boat 10.60 12.50

3.2.3. Load Factors

Load factors for Category 2 propulsion engines are calculated similar to Category 3 propulsion 

engine load factors, i.e., using the propeller law as discussed in Section 3.1.3. Auxiliary engines 
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on Category 2 ships are typically Category 1 engines. Load factors for auxiliary engines for 

Category 2 ships are listed in Exhibit 25. Load factors for propulsion and auxiliary engines for 

Category 1 ships are listed in Exhibit 26.

Exhibit 25 Category 2 Vessel Auxiliary Engine Load Factors

Ship Type Cruise RSZ Maneuver Hotel

Bulk Carrier 0.17 0.27 0.45 0.10

Ferry 0.15 0.30 0.45 0.26

Fishing 0.17 0.27 0.45 0.22

General Cargo 0.17 0.27 0.45 0.22

RORO 0.15 0.30 0.45 0.26

Tanker 0.13 0.24 0.33 0.67

Tug 0.17 0.27 0.45 0.22

Work Boat 0.17 0.27 0.45 0.22

Work Boat - ED 0.10 0.15 0.25 0.12

Exhibit 26 Load Factors for Category 1 Vessels

Ship Type Propulsion Auxiliary

Fishing 0.27 0.43

Tug 0.31 0.43

Work Boat 0.38 0.32

Work Boat - ED 0.38 0.13

3.2.4. Emission Factors

Emission factors for U.S. flag Category 2 ships for the 2018 analysis are shown in Exhibit 27. 

Tier 0, 1, and 2 emission factors came from EPA guidance on preparing port inventories17 while 

Tier 3 and 4 emission factors come from EPA rulemaking.18 The emission factors given in 

Exhibit 27 are based upon ships using ultra low sulfur diesel fuel (ULSD) with a fuel sulfur level 

of 15 ppm. Category 2 emission factors for foreign flag vessels for the 2018 analysis are shown 

in Exhibit 28 and assume the use of MGO with a fuel sulfur level of 1000 ppm (0.1 percent).

Category 2 emission factors for the 2005 analysis are shown in Exhibit 29 and assume the use 

of MDO with a fuel sulfur level of 1.5 percent.

 

17 ICF International, Current Methodologies in Preparing Mobile Source Port Related Emission Inventories, Final 

Report, Prepared for U.S. Environmental Protection Agency Sector Strategies Program, April 2009. 

http://www.epa.gov/sectors/sectorinfo/sectorprofiles/ports/ports-emission-inv-april09.pdf.

18 EPA, Final Regulatory Impact Analysis: Control of Emissions of Air Pollution from Locomotives and Marine 

Compression-Ignition Engines Less Than 30 Liters per Cylinder , EPA420-R-08-001a, May 2008. 

http://www.epa.gov/otaq/regs/nonroad/420r08001a.pdf
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All Category 1 engines were assumed to be domestic and subject to EPA rulemaking. For the 

2018 analysis, engines were assumed to run on ULSD with a fuel sulfur level of 15 ppm. The 

emission factors for Category 1 vessels and auxiliary engines for the 2018 analysis are shown 

in Exhibit 30. Emission factors for Category 1 vessels and auxiliary engines were based upon 

using MDO with 1.5 percent sulfur and are shown in Exhibit 31. Both sets of emission factors 

come from the EPA port emission inventory guidance document19 and represent the most 

current emission factors.

Exhibit 27 2018 Analysis Category 2 Domestic Engine Emission Factors

Tier Begin 

Year

Min 

kW

Category 2 Engine Emission Factors, g/kWh

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

0 -- 37 13.36 2.48 0.134 0.15 0.14 0.01 691 217

1 2000 37 10.55 2.48 0.134 0.15 0.14 0.01 691 217

2 2004 37 8.33 2.00 0.134 0.15 0.14 0.01 691 217

3 2013 37 5.97 2.00 0.07 0.11 0.11 0.01 691 217

4

2018 600 1.30 2.00 0.02 0.03 0.03 0.01 691 217

2017 1,000 1.30 2.00 0.02 0.03 0.03 0.01 691 217

2016 1,400 1.30 2.00 0.02 0.03 0.03 0.01 691 217

2015 2,000 1.30 2.00 0.02 0.03 0.03 0.01 691 217

2014 3,700 1.30 2.00 0.07 0.23 0.22 0.01 691 217

2017 3,700 1.30 2.00 0.01 0.05 0.05 0.01 691 217

Exhibit 28 2018 Analysis Category 2 Foreign Flag Engine Emission Factors

Tier Begin 

Year

Category 2 Engine Emission Factors, g/kWh

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

0 -- 13.9 1.1 0.4 0.18 0.18 0.42 691 217

1 2000 12.4 1.1 0.4 0.18 0.18 0.42 691 217

3 2016 2.5 1.1 0.4 0.18 0.18 0.42 691 217

Exhibit 29 2005 Analysis Category 2 Engine Emission Factors

Tier Begin 

Year

Category 2 Engine Emission Factors, g/kWh

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

0 -- 13.36 2.48 0.134 0.66 0.64 6.36 691 217

1 2000 10.55 2.48 0.134 0.66 0.64 6.36 691 217

2 2004 8.33 2.00 0.134 0.66 0.64 6.36 691 217

 

19 ICF International, Current Methodologies in Preparing Mobile Source Port Related Emission Inventories, Final 

Report, Prepared for U.S. Environmental Protection Agency Sector Strategies Program, April 2009. 

http://www.epa.gov/sectors/sectorinfo/sectorprofiles/ports/ports-emission-inv-april09.pdf
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Exhibit 30 2018 Analysis Category 1 Engine Emission Factors

Tier Begin 

Year

Min 

kW

Category 1 Engine Emission Factors, g/kWh

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

0 --

37 11.0 2.0 0.27 0.77 0.75 0.01 691 217

75 10.0 1.7 0.27 0.34 0.33 0.01 691 217

130 10.0 1.5 0.27 0.34 0.33 0.01 691 217

225 10.0 1.5 0.27 0.26 0.25 0.01 691 217

450 10.0 1.5 0.27 0.26 0.25 0.01 691 217

560 10.0 1.5 0.27 0.26 0.25 0.01 691 217

1,000 13.0 2.5 0.27 0.26 0.25 0.01 691 217

1 2000

37 9.8 2.0 0.27 0.77 0.75 0.01 691 217

75 9.8 1.7 0.27 0.34 0.33 0.01 691 217

130 9.8 1.5 0.27 0.34 0.33 0.01 691 217

225 9.8 1.5 0.27 0.26 0.25 0.01 691 217

450 9.8 1.5 0.27 0.26 0.25 0.01 691 217

560 9.8 1.5 0.27 0.26 0.25 0.01 691 217

1,000 9.8 2.5 0.27 0.26 0.25 0.01 691 217

2 2004

37 6.8 2.0 0.27 0.34 0.33 0.01 691 217

75 6.8 1.7 0.27 0.26 0.25 0.01 691 217

130 6.8 1.5 0.27 0.26 0.25 0.01 691 217

225 6.8 1.5 0.27 0.26 0.25 0.01 691 217

450 6.8 1.5 0.27 0.26 0.25 0.01 691 217

560 6.8 1.5 0.27 0.26 0.25 0.01 691 217

1,000 6.8 2.5 0.27 0.26 0.25 0.01 691 217

3

2009 37 5.70 2.00 0.30 0.17 0.16 0.01 691 217

2014 37 3.56 2.00 0.30 0.17 0.16 0.01 691 217

2012 75 4.08 1.70 0.14 0.08 0.08 0.01 691 217

2013 130 4.54 1.50 0.13 0.05 0.05 0.01 691 217

2014 225 4.69 1.50 0.10 0.07 0.07 0.01 691 217

2018 225 4.69 1.50 0.10 0.06 0.06 0.01 691 217

2012 450 4.81 1.50 0.10 0.07 0.07 0.01 691 217

2018 450 4.81 1.50 0.10 0.06 0.06 0.01 691 217

2012 600 4.81 1.50 0.10 0.07 0.07 0.01 691 217

2012 1,000 4.81 2.50 0.10 0.07 0.07 0.01 691 217

4

2018 600 1.30 1.50 0.04 0.03 0.03 0.01 691 217

2017 1,000 1.30 2.50 0.04 0.03 0.03 0.01 691 217

2016 1,400 1.30 2.50 0.04 0.03 0.03 0.01 691 217
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Exhibit 31 2005 Analysis Category 1 Engine Emission Factors

Tier Begin 

Year

Min 

kW

Category 1 Engine Emission Factors, g/kWh

NOx CO HC PM10 PM2.5 SOx CO2 BSFC

0 --

37 11.0 2.0 0.27 0.90 0.87 1.30 691 217

75 10.0 1.7 0.27 0.40 0.39 1.30 691 217

130 10.0 1.5 0.27 0.40 0.39 1.30 691 217

225 10.0 1.5 0.27 0.30 0.29 1.30 691 217

450 10.0 1.5 0.27 0.30 0.29 1.30 691 217

560 10.0 1.5 0.27 0.30 0.29 1.30 691 217

1,000 13.0 2.5 0.27 0.30 0.29 1.30 691 217

1 2000

37 9.8 2.0 0.27 0.90 0.87 1.30 691 217

75 9.8 1.7 0.27 0.40 0.39 1.30 691 217

130 9.8 1.5 0.27 0.40 0.39 1.30 691 217

225 9.8 1.5 0.27 0.30 0.29 1.30 691 217

450 9.8 1.5 0.27 0.30 0.29 1.30 691 217

560 9.8 1.5 0.27 0.30 0.29 1.30 691 217

1,000 9.8 2.5 0.27 0.30 0.29 1.30 691 217

2 2004

37 6.8 2.0 0.27 0.40 0.39 1.30 691 217

75 6.8 1.7 0.27 0.30 0.29 1.30 691 217

130 6.8 1.5 0.27 0.30 0.29 1.30 691 217

225 6.8 1.5 0.27 0.30 0.29 1.30 691 217

450 6.8 1.5 0.27 0.30 0.29 1.30 691 217

560 6.8 1.5 0.27 0.30 0.29 1.30 691 217

1,000 6.8 2.5 0.27 0.30 0.29 1.30 691 217

3.2.5. Growth Factors

Growth factors are used to project 2009 data to 2018 and to back cast 2009 data to 2005. 

Since there is no multiyear call data readily available to calculate installed power like for the 

Category 3 ships, another metric needed to be used. Since the majority of calls are related to 

tugs pushing barges and barges are relatively small compared with cargo compartments on 

Category 3 ships, cargo movement data can be used as a indicator of Category 1 and 2 ship 

growth. U.S. Army Corps of Engineers maintains the State to State Commodity Tonnage 

database20 for calendar years 2001 to 2010. Since most of the Category 1 and 2 vessels are 

engaged in island to island or within port movements, the data for Hawaii to Hawaii was used.

Because of the Great Recession, cargo movements during the period 2009 through 2011 were 

depressed. For 2011 and 2012, growth was estimated as reduced. Growth in 2011 was 

 

20 U.S. Army Corps of Engineers, State to State Commodity Tonnage Database.

http://www.ndc.iwr.usace.army.mil//data/datapdom.htm
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estimated at -3 percent and growth in 2012, growth was estimated at +2 percent. Growth from 

2013 to 2018 was estimated at +4 percent. The resulting actual and projected cargo tons are 

shown in Exhibit 22. Growth factor to extrapolate 2009 data to 2018 was calculated at 1.183 

and to back cast 2009 data to 2005 at 2.116.

Exhibit 32 Hawaiian Island Movement Commodity Data

0

2

4

6

8

1 0

1 2

1 4

1 6

2000 2005 2010 2015 2020

Cargo Tons (Millions)

Calendar Year

Actual

Projected
UNC-EMAQ 5-12-017.v1 25 April 26, 2012

4. Analysis of Results

4.1. Statewide Emissions

Statewide emissions for Category 1, 2, and 3 ships were calculated for 2018. Category 3 

emissions by port for 2018 are shown in Exhibit 33. In port is defined as occurring within 1 nm 

of the port and at sea is outside 1 nm of the port. In port includes pilot pick-up, maneuvering, 

and hotelling, while at sea includes the 25 nm cruise and the 4 nm RSZ.

Exhibit 33 2018 Category 3 Statewide Emissions by Port

Port Name Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Honolulu

in port 881.19 97.20 43.98 24.65 22.67 67.34 109,596

at sea 976.25 104.39 45.58 18.62 17.13 43.15 70,245

Barbers Point

in port 80.97 9.01 4.08 3.42 3.15 10.53 17,137

at sea 80.80 9.87 4.21 1.36 1.25 2.65 4,314

Pearl Harbor

in port 3.62 0.52 0.23 0.18 0.16 0.52 854

at sea 3.22 0.52 0.22 0.07 0.07 0.14 225

Kahului

in port 574.49 53.70 24.50 10.33 9.51 24.18 39,370

at sea 243.15 22.65 10.29 3.83 3.52 8.23 13,401

Nawiliwili

in port 92.63 8.60 3.93 1.70 1.57 4.06 6,605

at sea 65.04 6.02 2.73 1.04 0.95 2.26 3,673

Hilo

in port 168.04 15.57 7.09 3.11 2.86 7.46 12,149

at sea 223.53 20.71 9.39 3.61 3.32 7.94 12,931

Kona

in port 52.76 4.91 2.22 0.96 0.88 2.27 3,687

at sea 68.39 6.33 2.86 1.09 1.00 2.38 3,877

Total

in port 1,853.71 189.52 86.03 44.34 40.80 116.36 189,398

at sea 1,660.38 170.49 75.29 29.61 27.24 66.75 108,665

Category 3 Statewide emissions are compared to those calculated by ENVIRON for 200521 in 

Exhibits 34 and 35. Overall, NOx decreased by 2 percent, CO increased by 6 percent, HC 

increased by 31 percent, PM10 decreased by 75 percent, PM2.5 by 74 percent and SOx 

emissions by 95 percent. The PM and NOx reductions are mostly due to use of low sulfur 

distillate fuel. It should be noted that ENVIRON used a 20 nm cruise area for Oahu for the 2005 

analysis while ICF used a 25 nm cruise area for all ports in the 2018 analysis. Also ENVIRON 

did not include the ports of Pearl Harbor in Oahu and Kona in Hawaii that were part of the ICF 

2018 analysis.

 

21 Environ International Corp., "Hawaii Commercial Marine Vessel Activity and Emissions, Technical Memorandum", 

December 30, 2009, Appendix B to "Final Emission Inventory Report: Data Population of Air System for Hawaii’s 

Emissions Data (AirSHED), April 12, 2010.
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UNC-EMAQ 5-12-017.v1 26 April 26, 2012

Exhibit 34 Category 3 Statewide Emission Comparisons between 2005 and 2018

Island Analysis 

Year

Tons per Year

NOx CO HC PM10 PM2.5 SOx

Oahu

2005 1,882.53 199.19 64.85 156.52 142.47 2,107.54

2018 2,026.06 221.51 98.32 48.29 44.43 124.33

Maui

2005 575.62 48.74 18.82 47.32 43.37 510.09

2018 801.64 74.85 34.09 13.88 12.77 31.78

Hawaii

2005 478.84 41.11 17.60 38.37 33.90 396.30

2018 512.72 47.52 21.56 8.77 8.07 20.05

Kauai

2005 634.54 53.49 21.64 47.55 43.64 506.64

2018 157.67 14.61 6.66 2.74 2.52 6.31

Total

2005 3,571.53 342.53 122.91 289.76 263.38 3,520.57

2018 3,498.09 358.50 160.63 73.68 67.79 182.48

Exhibit 35 Total Statewide Emission Comparisons

Category 1 and 2 vessel emissions, ICF used a different methodology than was used by 

Environ.22 ICF used actual call data to estimate emissions from category 1 and 2 vessels while 

Environ used counts of vessels registered to Hawaiian ports and estimates of activity levels 

from the EPA guidance document for preparing port inventories.23 Thus to provide "apples to 

 

22 Environ International Corp., "Hawaii Commercial Marine Vessel Activity and Emissions, Technical Memorandum", 

December 30, 2009, Appendix B to "Final Emission Inventory Report: Data Population of Air System for Hawaii’s 

Emissions Data (AirSHED), April 12, 2010.

23 ICF International, Current Methodologies in Preparing Mobile Source Port Related Emission Inventories, Final 

Report, Prepared for U.S. Environmental Protection Agency Sector Strategies Program, April 2009. 

http://www.epa.gov/sectors/sectorinfo/sectorprofiles/ports/ports-emission-inv-april09.pdf

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

NOx CO HC PM-1 0 PM-2.5 SOx

tons per year

2005

2018
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

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UNC-EMAQ 5-12-017.v1 27 April 26, 2012

apples" comparison, ICF recalculated the 2005 Category 1 and 2 statewide inventory using the 

methodology described in Section 3.2. Emissions estimates using the ICF methodology are 

shown in Exhibit 36 for 2005 and Exhibit 37 for 2018. Emissions for 2005 and 2018 are 

compared by island in Exhibit 38. Again in port is defined as within 1 nm of the port while at sea 

is defined as 1 to 30 nm from the port. Overall, NOx decreased by 58 percent, CO by 47 

percent, HC by 53 percent, PM10 and PM2.5 by 78 percent, SOx by 99.7 percent and CO2 by 44 

percent. The installed power decreased by 44 percent from 2005 to 2018.

Exhibit 36 2005 Category 1 & 2 Statewide Emissions by Port

Port Name Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Honolulu

in port 412.97 82.84 9.65 13.73 13.32 72.60 26,284

at sea 327.80 64.20 3.56 17.07 16.56 163.45 18,003

Barbers Point

in port 103.14 21.04 2.50 2.95 2.86 12.93 6,446

at sea 18.41 3.42 0.19 0.91 0.89 8.75 962

Kahului

in port 40.41 7.57 0.81 1.82 1.77 13.70 2,679

at sea 83.13 17.89 0.99 4.75 4.61 45.63 5,008

Nawiliwili

in port 11.73 2.06 0.27 0.34 0.33 1.66 704

at sea 7.85 1.46 0.08 0.39 0.38 3.70 408

Hilo

in port 15.30 2.84 0.31 0.50 0.48 2.80 864

at sea 27.32 5.07 0.28 1.35 1.31 12.88 1,419

Kawaihae

in port 4.79 0.79 0.11 0.18 0.18 1.05 309

at sea 11.15 2.07 0.11 0.55 0.53 5.26 579

Total

in port 588.34 117.14 13.65 19.52 18.94 104.75 37,286

at sea 475.67 94.10 5.21 25.02 24.27 239.66 26,379

Exhibit 37 2018 Category 1 & 2 Statewide Emissions by Port

Port Name Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Honolulu

in port 165.39 45.01 4.15 4.20 4.08 0.26 14,522

at sea 148.83 32.26 2.10 2.55 2.47 0.65 10,069

Barbers Point

in port 47.02 11.76 1.06 1.00 0.97 0.04 3,601

at sea 10.22 1.89 0.11 0.12 0.12 0.02 538

Kahului

in port 12.69 4.20 0.36 0.49 0.48 0.02 1,498

at sea 21.68 8.71 0.38 0.82 0.80 0.03 2,801

Nawiliwili

in port 6.56 1.15 0.15 0.15 0.15 0.00 394

at sea 4.39 0.81 0.05 0.05 0.05 0.00 228

Hilo

in port 8.57 1.57 0.18 0.18 0.18 0.01 483

at sea 15.35 2.65 0.19 0.18 0.17 0.06 794

Kawaihae

in port 2.69 0.41 0.07 0.07 0.06 0.01 173

at sea 6.35 0.87 0.12 0.08 0.08 0.09 324

Total in port 242.92 64.10 5.97 6.10 5.92 0.35 20,671
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UNC-EMAQ 5-12-017.v1 28 April 26, 2012

at sea 206.83 47.20 2.95 3.80 3.68 0.85 14,754

Exhibit 38 Category 1 & 2 Statewide Emission Comparisons between 2005 and 2018

Island Analysis 

Year

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Oahu

2005 862.32 171.50 15.90 34.66 33.62 257.73 51,695

2018 371.46 90.91 7.43 7.87 7.63 0.97 28,730

Maui

2005 123.54 25.46 1.80 6.58 6.38 59.33 7,687

2018 34.37 12.91 0.74 1.32 1.28 0.05 4,299

Hawaii

2005 58.57 10.77 0.81 2.57 2.49 21.99 3,172

2018 32.96 5.50 0.55 0.51 0.49 0.17 1,774

Kauai

2005 19.58 3.52 0.35 0.73 0.71 5.37 1,112

2018 10.95 1.97 0.19 0.20 0.19 0.01 622

Total

2005 1,064.01 211.24 18.86 44.54 43.21 344.41 63,665

2018 449.75 111.29 8.92 9.89 9.60 1.20 35,425

In presenting Category 1 and 2 emission results in their report, Environ only reported tugs and 

ferries. Tugs make up 51.5 percent of the Category 1 and 2 installed power for 2005 while 

ferries make up 43.4 percent. The other 5.1 percent is made up of smaller OGVs, fishing 

vessels and work boats. Emissions comparisons between the ICF methodology and the 

Environ methodology for 2005 for tugs and ferries is shown in Exhibit 39. The methodology 

used by Environ for tugs tended to overestimate at sea emissions and underestimate in port 

emissions. It also overestimated NOx and PM by not taking into account the reductions from 

Tier 1 and Tier 2 engines and underestimates SOx by assuming vessels used non-road diesel 

with a sulfur level of 0.15 percent instead of MDO with a 1.5 percent sulfur level.

Exhibit 39 Comparison of ICF and Environ Methods

Vessel 

Type Methodology

Tons per Year

NOx CO HC PM10 SOx

Tugs

ICF 828.96 161.12 15.27 31.59 227.71

Environ 1,564.33 130.35 59.27 85.33 74.67

Ferries

ICF 167.09 38.30 2.30 10.08 95.19

Environ 489.47 50.09 17.06 23.58 24.85

4.2. Hawaii Class 1 Visibility Area Emissions

Class 1 Visibility Area emissions for the island of Hawaii are shown in Exhibit 40 for 2005 and 

Exhibit 41 for 2018 for Category 3 ships. In port is defined as within 1 nm of the port, near port 

from1 to 30 nm, and far port is beyond 30 nm to the extent of the 150 km surrounding the Class 

1 area HAVO monitor. Innocent passage is defined as cruise by ships which travel through the 

Class 1 area but do not stop at the ports within the Class 1 area. Overall, NOx decreased by 14 
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

Analysis of Results

UNC-EMAQ 5-12-017.v1 29 April 26, 2012

percent, CO and HC by 1 percent, PM10 and PM2.5 decreased by 85 percent and SOx by 97 

percent. There was a 3 percent drop in installed power between 2005 and 2018.

Exhibit 40 2005 Category 3 Hawaii Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Hilo

in port 176.42 14.31 6.56 20.20 18.58 219.95 13,330

near port 243.59 19.54 8.82 22.86 21.03 247.49 14,943

Kona

in port 67.07 5.41 2.40 7.56 6.95 81.98 4,987

near port 73.38 5.82 2.60 6.65 6.11 71.86 4,345

Far port and innocent passage 519.40 42.02 18.98 47.01 43.25 507.43 30,635

Totals 1,079.86 87.10 39.36 104.27 95.93 1,128.71 68,240

Exhibit 41 2018 Category 3 Hawaii Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Hilo

in port 168.04 15.57 7.09 3.11 2.86 7.46 12,149

near port 223.65 20.72 9.39 3.61 3.32 7.95 12,949

Kona

in port 52.76 4.91 2.22 0.96 0.88 2.27 3,687

near port 68.39 6.33 2.86 1.09 1.00 2.38 3,877

Far port and innocent passage 421.05 38.83 17.59 6.82 6.27 15.07 24,540

Totals 933.89 86.35 39.15 15.59 14.34 35.14 57,202

Category 1 and 2 vessel emissions within the Hawaii Class 1 Visibility Area are shown in Exhibit 

42 for 2005 and Exhibit 43 for 2018. Overall, NOx decreased 44 percent, CO 49 percent, HC 

31 percent, PM10 and PM2.5 83 percent and SOx 99 percent. There was a 44 percent drop in 

installed power from 2005 to 2018.

Exhibit 42 2005 Category 1 & 2 Hawaii Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Hilo

in port 15.30 2.84 0.31 0.46 0.45 1.87 864

near port 27.32 5.06 0.28 1.35 1.31 12.87 1,419

Kawaihae

in port 4.79 0.79 0.11 0.17 0.17 0.74 309

near port 11.15 2.07 0.11 0.55 0.53 5.26 579

Far port and innocent passage 46.92 8.70 0.48 2.31 2.24 22.16 2,435

Totals 105.48 19.46 1.29 4.84 4.70 42.90 5,607

Exhibit 43 2018 Category 1 & 2 Hawaii Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Hilo in port 8.57 1.57 0.18 0.18 0.18 0.01 483
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UNC-EMAQ 5-12-017.v1 30 April 26, 2012

near port 15.35 2.65 0.19 0.18 0.17 0.06 794

Kawaihae

in port 2.69 0.41 0.07 0.07 0.06 0.01 173

near port 6.35 0.87 0.12 0.08 0.08 0.09 324

Far port and innocent passage 26.40 4.48 0.34 0.31 0.30 0.13 1,362

Totals 59.36 9.98 0.90 0.82 0.79 0.30 3,136

4.3. Maui Class 1 Visibility Area Emissions

Class 1 Visibility Area emissions for the island of Maui are shown in Exhibit 44 for 2005 and 

Exhibit 45 for 2018 for Category 3 ships. In port is defined as within 1 nm of the port, near port 

from1 to 30 nm, and far port is beyond 30 nm to the extent of the 150 km surrounding the Class 

1 area HACR monitor. No data was provided for Lahaina for 2018. Innocent passage is 

defined as cruise by ships which travel through the Class 1 area but do not stop at the ports 

within the Class 1 area. Overall, NOx increased by 49 percent, CO increased by 81 percent HC

increased by 80 percent, PM10 and PM2.5 decreased by 73 percent and SOx decreased by 94

percent. While there was only a 7 percent increase in installed power from 2005 to 2018 for the 

area, Kahului increased 811 percent and innocent passage by ships leaving Honolulu increased 

79 percent. There was a 76 percent drop off in installed power for Kona and Lahaina.

Exhibit 44 2005 Category 3 Maui Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Kahului

in port 57.62 4.82 2.20 5.98 5.50 64.92 3,920

near port 27.05 2.25 1.02 2.55 2.35 27.55 1,662

Lahaina

in port 79.04 6.43 2.87 8.70 8.00 94.25 5,719

near port 88.84 7.06 3.17 7.74 7.12 83.41 5,041

Kona

in port 247.15 20.23 9.14 25.28 23.26 274.09 16,571

near port 165.67 13.24 5.98 14.10 12.97 151.60 9,154

Far port and innocent passage 2,051.40 166.13 74.18 208.24 191.58 2,267.82 137,036

Totals 2,716.77 220.17 98.55 272.58 250.78 2,963.64 179,103

Exhibit 45 2018 Category 3 Maui Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Kahului

in port 574.49 53.70 24.50 10.33 9.51 24.18 39,370

near port 243.15 22.65 10.29 3.83 3.52 8.23 13,401

Kona

in port 52.76 4.91 2.22 0.96 0.88 2.27 3,687

near port 58.69 5.44 2.46 0.93 0.86 2.04 3,316

Far port and innocent passage 3,106.71 312.31 137.75 58.72 54.02 139.49 227,076

Totals 4,035.80 399.02 177.22 74.77 68.79 176.21 286,851
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

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UNC-EMAQ 5-12-017.v1 31 April 26, 2012

Category 1 and 2 vessel emissions within the Maui Class 1 Visibility Area are shown in Exhibit 

46 for 2005 and Exhibit 47 for 2018. Overall, NOx decreased 56 percent, CO 50 percent, HC 

42 percent, PM10 and PM2.5 84 percent and SOx 99.6 percent. There was a 44 percent drop in 

installed power from 2005 to 2018.

Exhibit 46 2005 Category 1 & 2 Maui Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Kahului

in port 38.28 8.20 0.81 1.82 1.77 13.70 2,679

near port 83.13 17.89 0.99 4.75 4.61 45.63 5,008

Kawaihae

in port 4.79 0.79 0.11 0.18 0.18 1.05 309

near port 11.15 2.07 0.11 0.55 0.53 5.26 579

Far port and innocent passage 688.24 134.23 7.40 35.69 34.62 342.15 37,578

Totals 825.59 163.18 9.42 43.00 41.71 407.78 46,154

Exhibit 47 2018 Category 1 & 2 Maui Class 1 Visibility Area Emissions

Port Location

Tons per Year

NOx CO HC PM10 PM2.5 SOx CO2

Kahului

in port 12.69 4.20 0.36 0.49 0.48 0.02 1,498

near port 28.35 11.32 0.49 1.07 1.03 0.04 3,638

Kawaihae

in port 2.69 0.41 0.07 0.07 0.06 0.01 173

near port 6.35 0.87 0.12 0.08 0.08 0.09 324

Far port and innocent passage 312.35 64.45 4.43 5.03 4.88 1.55 20,180

Totals 362.43 81.26 5.47 6.74 6.53 1.70 25,813
UNC-EMAQ 5-12-017.v1 32 April 26, 2012

5. References

California Air Resources Board, 2005 Oceangoing Ship Survey, Summary of Results, 

September 2005

Environ International Corp., Hawaii Commercial Marine Vessel Activity and Emissions, 

Technical Memorandum, December 30, 2009, Appendix B to Final Emission Inventory 

Report: Data Population of Air System for Hawaii’s Emissions Data (AirSHED), April 12, 

2010.

Email from Scott Takamoto, Hawaii State Department of Health, February 29, 2012.

Google Earth. http://www.google.com/earth/index.html

ICF International, Current Methodologies in Preparing Mobile Source Port Related Emission 

Inventories, Final Report, Prepared for U.S. Environmental Protection Agency Sector 

Strategies Program, April 2009. 

http://www.epa.gov/sectors/sectorinfo/sectorprofiles/ports/ports-emission-inv-april09.pdf

IHS Fairplay Sea-web, http://www.sea-web.com

IHS Fairplay Sea-web Movements Module,

http://www.sea-web.com/seaweb_Movements_module.html

Merchant Seaman Protection and Relief 46 USCS Appx § 688 (2002) Title 46. Appendix. 

Shipping Chapter 18

Starcrest Consulting Group, Port of Long Beach Air Emissions Inventory -- 2010, July 2011. 

http://www.polb.com/environment/air/emissions.asp

Starcrest Consulting Group, Port of Los Angeles Air Emissions Inventory -- 2010, July 2011. 

http://www.portoflosangeles.org/pdf/2010_Air_Emissions_Inventory.pdf

U.S. Army Corps of Engineers Navigation Data Center, Foreign Traffic Vessel Entrances and 

Clearances. http://www.ndc.iwr.usace.army.mil//data/dataclen.htm. 

U.S. Army Corps of Engineers Navigation Data Center, State to State Commodity Tonnages. 

http://www.ndc.iwr.usace.army.mil//data/datapdom.htm

U.S. Environmental Protection Agency, Final Regulatory Impact Analysis: Control of Emissions 

of Air Pollution from Locomotives and Marine Compression-Ignition Engines Less Than 

30 Liters per Cylinder , EPA420-R-08-001a, May 2008. 

http://www.epa.gov/otaq/regs/nonroad/420r08001a.pdf
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References

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page
UNC-EMAQ 5-12-017.v1 34 April 26, 2012

Appendix A. Category 3 Ship Growth Rate Details

Growth rates for Category 3 ships were developed using U.S. Army Corps of Engineers 

entrances and clearances data matched with IHS Sea-web data to determine ship type, total 

propulsion power, and propulsion engine category. While the entrances and clearances data 

only covers foreign cargo moves, foreign cargo moves represent 66 percent of installed power 

stopping at the Hawaiian islands. Major ship types include container ships (39 percent), 

passenger/cruise ships (51 percent) and tankers (6 percent). Of those three ship types, foreign 

cargo moves represents 46 percent of container ship installed power, 78 percent of 

passenger/cruise ship installed power and 80 percent of tanker installed power. Installed power 

is total propulsion power multiplied by ship calls. Even though container ships are 

underrepresented, it is likely that domestic trends would follow foreign cargo movements for that 

ship type. 

Growth rates were projected from entrances and clearances data from 2002 to 2009 taking into 

account the Great Recession. The Great Recession started in December 2007 and lasted 

through July 2009. The effects of the recession were felt through 2011 in many industries 

including tourism and the cruise ship industry. That had a significant effect on shipping in 

Hawaii.

The following sections provide growth rates for each ship type.

A.1. Auto Carriers

Auto carrier installed power generally increased from 2002 through 2008 but had an 11.6 

percent drop off in 2009. For projection purposed, the average growth rate during 2005 to 2008 

was determined (2.8 percent) and used to project growth after 2011. Growth rate for 2010 was 

set at -4.4% and -0.8 percent for 2011.

Exhibit 48 Growth Projections for Auto Carriers

400

450

500

550

600

650

700

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

Appendix A -- Category 3 Ship Growth Rate Details

UNC-EMAQ 5-12-017.v1 35 April 26, 2012

A.2. Bulk Carriers

Bulk carrier installed power decreased between 2002 and 2004 then increased from 2004 

through 2006 and then fell off sharply. The average growth rate from 205 to 2008 was 2.4 

percent which was used to project after 2012. Growth rates for 2010, 2011 and 2012 were 

projected at -7.9 percent, - 4 percent and -1 percent.

Exhibit 49 Growth Projections for Bulk Carriers

A.3. Container Ships

Container ship installed power continued to grow from 2002 through 2009. Average growth rate 

was 13.1 percent. Growth during 2010 was set at 10.4 percent followed by 13.1 percent from 

2011 through 2018. 

Exhibit 50 Growth Projections for Container Ships

200

250

300

350

400

450

500

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

Appendix A -- Category 3 Ship Growth Rate Details

UNC-EMAQ 5-12-017.v1 36 April 26, 2012

A.4. General Cargo

General cargo ship installed power varied greatly over the period 2002 through 2009. From 

2004 through 2008, installed power for general cargo ships grew by 16 percent. The growth 

rate for 2010 was set at -20 percent and 2011 set at -5 percent. Growth after 2011 was set at 

16 percent.

Exhibit 51 Growth Projections for General Cargo Ships

A.5. Miscellaneous

Miscellaneous ships included pipe layers, cable layers, research survey vessels, anchor 

handling tug supply, drilling ships and fishery patrol boats. Miscellaneous installed power varied 

during 2002 through 2007, then began to increase from 2007 through 2009. Average growth 

was 11 percent over the period 2002 through 2009. That rate was applied to growth projections 

for 2010 through 2018.

Exhibit 52 Growth Projections for Miscellaneous Ships

0

2 0

4 0

6 0

8 0

100

120

140

160

180

200

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected

0

5 0

100

150

200

250

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected
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UNC-EMAQ 5-12-017.v1 37 April 26, 2012

A.6. Passenger/Cruise Ships

Cruise ship installed power tended to decrease during most of the period between 2002 and 

2009. However, during 2005 to 2007, cruise ship growth was 8.7 percent. Growth for 2010 was 

set at -3.5 percent and growth for 2011 was set at +2.5 percent. Growth from 2012 to 2018 was 

set at 8.7 percent.

Exhibit 53 Growth Projections for Passenger/Cruise Ships

A.7. Roll-Off/Roll-On

Roll-off/Roll-on (RoRo) ship installed power varied between 2002 and 2006 but fell rapidly from 

2006 to 2009. Average growth in installed power from 2003 to 2007 was 12 percent. Growth 

for 2010 was set at -10 percent and 2011 was set at 3 percent. Growth from 2012 through 2018 

was set at 12 percent.

Exhibit 54 Growth Projections for RoRo Ships

0

5,000

10,000

15,000

20,000

25,000

30,000

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected

0

2 0

4 0

6 0

8 0

100

120

140

160

180

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected
Technical Analysis for Hawaii’s Regional Haze FIP Report – Task 16: Commercial Marine Inventory

Appendix A -- Category 3 Ship Growth Rate Details

UNC-EMAQ 5-12-017.v1 38 April 26, 2012

A.8. Tankers

Tanker installed power grew from 2002 to 2006 at an average rate of 7.4 percent, then fell off 

some during the recessionary period. Growth during 2010 was set at -0.5 percent and 2011 at 

3.5 percent. Growth after 2011 was set at 7.4 percent.

Exhibit 55 Growth Projections for Tanker Ships

A.9. Tugs

Category 3 ocean going tug installed power growth varied during the 2002 to 2009 period. 

Average growth was 4.5 percent. Growth for 2010 was set at 2 percent and growth after 2010 

was set at 4.5 percent.

Exhibit 56 Growth Projections for Ocean Going Tugs

0

500

1,000

1,500

2,000

2,500

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

4 5

2000 2005 2010 2015 2020

Installed Power (MW)

Calendar Year

Actual

Projected