Modeling Sulfur Oxides (SOx) Emissions 

Transport from Ships at Sea 
Modeling Sulfur Oxides (SOx) Emissions 

Transport from Ships at Sea 

Assessment and Standards Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency 

Prepared for EPA by


Atmospheric & Environmental Research, Inc.


EPA Contract No. GS-10F-0615P


NOTICE 

This technical report does not necessarily represent final EPA decisions or 


positions. It is intended to present technical analysis of issues using data 


that are currently available. The purpose in the release of such reports is to 


facilitate the exchange of technical information and to inform the public of 


technical developments which may form the basis for a final EPA decision, 


position, or regulatory action.


EPA420-R-07-009 

July 2007 
TABLE OF CONTENTS 

1. Introduction.......................................................................................................... 1-1 

2. Modeling Approach ............................................................................................. 2-1 

2.1 Air Quality Model (CALPUFF)............................................................... 2-1 

2.2 Meteorological Model (CALMET).......................................................... 2-3 

2.3 Approach.................................................................................................. 2-3 

2.3.1 Receptors......................................................................................... 2-4 

2.3.2 Sources............................................................................................ 2-4 

2.3.3 Modeling domains .......................................................................... 2-5 

3. Model Inputs ........................................................................................................ 3-1 

3.1 Meteorology............................................................................................. 3-1 

3.1.1 Measurements ................................................................................. 3-2 

3.1.2 MM5 outputs................................................................................... 3-7 

3.1.3 CALMET winds.............................................................................. 3-7 

3.1.4 CALMET mixing heights ............................................................. 3-17 

3.2 Emissions ............................................................................................... 3-17 

3.2.1 Emission rates ............................................................................... 3-26 

3.2.2 Stack parameters ........................................................................... 3-27 

4. Results.................................................................................................................. 4-1 

4.1 Results for the Southern Pacific U.S. Coastline ...................................... 4-2 

4.2 Results for the Northern Pacific U.S. Coastline .................................... 4-16 

4.3 Results for the Gulf of Mexico Coastline .............................................. 4-32 

4.4 Results for the Atlantic Ocean Coastline ............................................... 4-43 

5. Summary and Conclusions .................................................................................. 5-1 

6. References............................................................................................................ 6-1 

Appendices 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea i 
LIST OF TABLES 

Table 3-1 Stack characteristics............................................................................... 3-28 

Table 5-1 Percentage of SO2 concentrations below the design value as a function of 

the distance from the coastline................................................................. 5-2 

Table 5-2 Percentage of sulfate concentrations below the design value as a function 

of the distance from the coastline. ........................................................... 5-2 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea ii 
LIST OF FIGURES 

Figure 2-1 Modeling domain for the Southern Pacific Ocean U.S. coastline. .......... 2-6 

Figure 3-1 Land-based surface stations and over-water stations for the Southern 

Figure 3-2 Land-based surface stations and over-water stations for the Northern 

Figure 3-3 Land-based surface stations and over-water stations for the Gulf of 

Figure 3-4 Land-based surface stations and over-water stations for the Atlantic Ocean 

Figure 3-6a Wind roses based on CALMET outputs for the southern Pacific Ocean

Figure 3-6b Wind roses based on CALMET outputs for the southern Pacific Ocean

Figure 3-7a Wind roses based on CALMET outputs for the northern Pacific Ocean 

Figure 3-7b Wind roses based on CALMET outputs for the northern Pacific Ocean 

Figure 3-8a Wind roses based on CALMET outputs for the Gulf of Mexico during 

Figure 3-8b Wind roses based on CALMET outputs for the Gulf of Mexico during 

Figure 3-9a Wind roses based on CALMET outputs for the Atlantic Ocean during 

Figure 3-9b Wind roses based on CALMET outputs for the Atlantic Ocean during 

Figure 3-10a Mixing heights for the southern Pacific Ocean during winter and spring

Figure 3-10b Mixing heights for the southern Pacific Ocean during summer and fall 

Figure 3-11a Mixing heights for the northern Pacific Ocean during winter and spring 

Figure 2-2 Modeling domain for the Northern Pacific Ocean U.S. coastline. .......... 2-7 

Figure 2-3 Modeling domain for the Gulf of Mexico coastline. ............................... 2-9 

Figure 2-4 Modeling domain for the Atlantic Ocean coastline. .............................. 2-10 

Pacific Ocean U.S. coastline.................................................................... 3-3 

Pacific Ocean U.S. coastline.................................................................... 3-4 

Mexico coastline ...................................................................................... 3-5 

coastline ................................................................................................... 3-6 

Figure 3-5 MM5 modeling domain ........................................................................... 3-8 

during winter and spring 2002 ................................................................. 3-9 

during summer and fall 2002 ................................................................. 3-10 

during winter and spring 2002 ............................................................... 3-11 

during summer and fall 2002 ................................................................. 3-12 

winter and spring 2002........................................................................... 3-13 

summer and fall 2002............................................................................. 3-14 

winter and spring 2002........................................................................... 3-15 

summer and fall 2002............................................................................. 3-16 

2002........................................................................................................ 3-18 

2002........................................................................................................ 3-19 

2002........................................................................................................ 3-20 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea iii 
Figure 3-11b Mixing heights for the northern Pacific Ocean during summer and fall 

2002........................................................................................................ 3-21 

Figure 3-12a Mixing heights for the Gulf of Mexico during winter and spring 2002 3-22 

Figure 3-12b Mixing heights for the Gulf of Mexico during summer and fall 2002 .. 3-23 

Figure 3-13a Mixing heights for the Atlantic Ocean during winter and spring 2002 . 3-24 

Figure 3-13b Mixing heights for the Atlantic Ocean during summer and fall 2002 ... 3-25 

Figure 4-1 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel ............................................................ 4-3 

Figure 4-2 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Southern Pacific U.S. coastline ............. 4-4 

Figure 4-3 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel ............................................................ 4-5 

Figure 4-4 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Southern Pacific U.S. 

coastline .................................................................................................. 4-6 

Figure 4-5 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel ............................................................ 4-8 

Figure 4-6 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Southern Pacific U.S. coastline ............. 4-9 

Figure 4-7 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-10 

Figure 4-8 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Southern Pacific U.S. 

coastline ................................................................................................ 4-11 

Figure 4-9 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-12 

Figure 4-10 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 375 km from the Southern Pacific U.S. coastline ........... 4-13 

Figure 4-11 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Southern Pacific U.S. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea iv 
coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-14 

Figure 4-12 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Southern Pacific U.S. 

coastline ................................................................................................ 4-15 

Figure 4-13 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-17 

Figure 4-14 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Southern Pacific U.S. 

coastline ................................................................................................ 4-18 

Figure 4-15 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-19 

Figure 4-16 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Northern Pacific U.S. coastline ........... 4-20 

Figure 4-17 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-22 

Figure 4-18 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Northern Pacific U.S. 

coastline ................................................................................................ 4-23 

Figure 4-19 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-24 

Figure 4-20 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Northern Pacific U.S. coastline ........... 4-25 

Figure 4-21 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-26 

Figure 4-22 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Northern Pacific U.S. 

coastline ................................................................................................ 4-27 

Figure 4-23 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Northern Pacific U.S. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea v 
coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-28 

Figure 4-24 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Northern Pacific U.S. 

coastline ................................................................................................ 4-29 

Figure 4-25 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel .......................................................... 4-30 

Figure 4-26 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Northern Pacific U.S. 

coastline ................................................................................................ 4-31 

Figure 4-27 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-33 

Figure 4-28 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Gulf of Mexico coastline ..................... 4-34 

Figure 4-29 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-35 

Figure 4-30 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Gulf of Mexico coastline 4-36 

Figure 4-31 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-37 

Figure 4-32 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Gulf of Mexico coastline ..................... 4-38 

Figure 4-33 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-39 

Figure 4-34 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Gulf of Mexico coastline 4-40 

Figure 4-35 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-41 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea vi 
Figure 4-36 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Gulf of Mexico coastline 4-42 

Figure 4-37 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-44 

Figure 4-38 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Gulf of Mexico coastline 4-45 

Figure 4-39 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-46 

Figure 4-40 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Atlantic Ocean coastline ...................... 4-47 

Figure 4-41 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-48 

Figure 4-42 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Atlantic Ocean coastline 4-49 

Figure 4-43 Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-50 

Figure 4-44 Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Atlantic Ocean coastline ...................... 4-51 

Figure 4-45 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-52 

Figure 4-46 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Atlantic Ocean coastline 4-53 

Figure 4-47 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-55 

Figure 4-48 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Atlantic Ocean coastline 4-56 

Figure 4-49 Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Atlantic Ocean coastline to 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea vii 
the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel ......................................................................... 4-57 

Figure 4-50 Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Atlantic Ocean coastline 4-58 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea viii 
EXECUTIVE SUMMARY 

A screening study was conducted to determine the air quality impacts (annual 

average ground-level concentrations of SO2 and sulfate) on land due to SOx emissions 

from ships burning high-sulfur fuel at sea at various distances from the coastline. The 

CALPUFF dispersion model was used for this screening study. Meteorological inputs 

were prepared with the CALMET model using the outputs of a prognostic meteorological 

model, MM5, in combination with surface measurements over water and on land. The 

meteorology represents the year 2002 because it was the most recent year for which an 

MM5 simulation covering the contiguous United States was available. CALPUFF tends 

to overestimate the conversion of SO2 to sulfate in the gas phase and the results presented 

here are likely to provide conservative estimates of the impacts of emissions from ships at 

sea on inland air quality (because of the simplified treatment of aqueous-phase chemistry 

in CALPUFF, this overestimation may not hold for cases where the interactions of the 

ship plumes with fog dominate sulfate formation). 

Four domains were studied: the southern Pacific coastline, the northern Pacific 

coastline, the Gulf of Mexico coastline and the Atlantic coastline. The results were 

compared with those calculated for ships burning low-sulfur fuel at the coastline to 

determine upper bounds for Sulfur Emission Control Areas (SECAs), i.e., off-shore 

distances at which the switch to high-sulfur fuel would not impair air quality. For each 

offshore distance investigated, the percentage of receptors for which the air quality 

impacts of ships at sea were lower than the impacts of ships at the coastline was 

calculated. 

Emission rates were estimated to be representative of ocean-going ships along U.S. 

coastlines. The sulfur content of the fuel was assumed to be 15,000 ppm within the 

SECA (i.e., here at the coastline) and 27,000 ppm outside the SECA (i.e., at the four offshore distances considered here, 125, 250, 375 and 500 km). The gas-phase SO2 and 

particulate-phase sulfate emissions per ship were estimated to be 100,320 g/h and 3.040 

g/h, respectively, within the SECA and 180,640 g/h and 5,600 g/h, respectively, outside 

the SECA. Based on an analysis of ship traffic off the Pacific coastline, a distance of 25 

km between ships was used for all coastlines. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea E-1 
The results are summarized in Tables E-1 and E-2 for concentration ratios of SO2 

and sulfate, i.e., the ratio of the concentration calculated for ships at sea to the 

concentration calculated for ships at the coastline (the design value). 

The results for SO2 were different from those for sulfate, primarily due to 

differences in the behavior of these two species downwind of a source. For all the 

coastlines studied, the majority of the SO2 concentration ratios were less than one at 

shorter off-shore distances than for sulfate. Thus, sulfate concentration ratios were the 

limiting factor for defining the upper bounds of the SECA for each coastline. 

The results showed some differences in results among the various coastlines 

studied. These differences are due to differences in the wind fields bringing the offshore 

ship emissions and their secondary products to land as well as differences in 

precipitation, which removes pollutants from the atmosphere. 

The results from the two Pacific Ocean coastline simulations were qualitatively 

similar. For both Pacific Ocean coastlines, over 90% of the receptors showed SO2 

concentration ratios less than one for ships at 250 km from the coastline. For sulfate, 

only about 49% and 56% of the receptors had concentrations less than one for ships at 

500 km from the southern Pacific Ocean and northern Pacific Ocean coastlines, 

respectively. 

For the other two coastlines (Atlantic Ocean and Gulf of Mexico), the SO2 results 

were qualitatively similar to those for the Pacific Ocean coastlines, i.e., over 90% of the 

receptors showed SO2 concentration ratios less than one for ships at 250 km from the 

coastline. However, there were some large differences for sulfate. For the Gulf of 

Mexico coastline, over 70% of the receptors showed sulfate concentration ratios less than 

one for ships at 250 km from the coastline. For the Atlantic Ocean coastline, nearly 60% 

of the receptors showed sulfate concentration ratios less than one for ships at 250 km 

from the coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea E-2 
Table E-1. Percentage of SO2 concentrations below the design value as a function of 

the distance from the coastline. 

Distance from coastline 125 km 250 km 375 km 500 km 

Southern Pacific 40.7% 90.7% 100% 100% 

Northern Pacific 46.6% 97.9% 100% 100% 

Gulf of Mexicoa 84.4% 98.1% 100% 100% 

Atlantic 86.6% 100% 100% 100% 

a

Note that Florida values correspond to a shorter ship-coastline distance and the values 

presented in the table should be seen as lower limits. 

Table E-2. Percentage of sulfate concentrations below the design value as a function 

of the distance from the coastline. 

Distance from coastline 125 km 250 km 375 km 500 km 

Southern Pacific 4.4% 24.9% 41.9% 48.7% 

Northern Pacific 0.01% 3.6% 20.3% 55.7% 

Gulf of Mexicoa 40.4% 72.0% 80.5% 84.0% 

Atlantic 1.2% 57.9% 92.5% 100% 

a

Note that Florida values correspond to a shorter ship-coastline distance and the values 

presented in the table should be seen as a lower limits. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea E-3 
These results suggest that an off-shore distance of 500 km should be sufficient 

when conducting refined modeling of the potential impacts of ship emissions on air 

quality inland, if a criterion of about 50% of inland receptors having sulfate 

concentrations below the design value is acceptable to define the SECA. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea E-4 
1. INTRODUCTION 

This document describes a screening study to model on-shore SO2 and sulfate 

concentrations due to emissions of SOx from ships at sea. The objective of this screening 

study is to obtain quantitative information on the shortest distance at which ships burning 

high sulfur fuel (fuel content of 27,000 ppm) will have air quality impacts at land 

receptors that are less than those anticipated from emissions from ships burning low 

sulfur fuel (fuel content of 15,000 ppm) within coastal waters. This distance can 

subsequently be used as the basis for defining the modeling domain for a more refined 

Eulerian modeling study using the U.S. EPA Community Multiscale Air Quality model 

(CMAQ). The results of the CMAQ modeling will yield the information required to 

define the outer boundary of a Sulfur Emission Control Area (SECA) for various U.S. 

coastlines. Because of differences in meteorology and other factors governing the 

transport and transformation of ship emissions among the various coastlines, each 

coastline is modeled separately in the screening study described here. 

A review of available models and data was conducted prior to defining our 

modeling approach (Seigneur et al., 2005a; see Appendix A). The modeling approach 

was then formally documented in an analysis plan that was reviewed by EPA (Seigneur et 

al., 2005b; see Appendix B). 

This report is organized as follows. Section 2 describes the modeling approach, 

including brief descriptions of the air quality model (CALPUFF) used for the screening 

study, and the meteorological preprocessor for CALPUFF, referred to as CALMET. 

CALPUFF is recommended by EPA for regulatory applications to assess the long-range 

transport of pollutants. While CALPUFF has some limitations, as discussed in Section 2, 

it is suitable for a screening study since it will tend to overestimate the oxidation of SO2 

to sulfate in the gas phase (Karamchandani et al., 2006) and may thus provide a 

conservative bound for the distance of interest for defining the SECA (because of the 

simplistic treatment of aqueous-phase chemistry in CALPUFF, one cannot assess 

whether sulfate concentrations would be overestimated if fog processes dominate sulfate 

formation). Section 3 describes the development of meteorological, emissions and 

geophysical data inputs for the CALPUFF simulations. Section 4 presents the results for 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 1-1 
the various U.S. coastlines that were simulated, and Section 5 provides a summary of the 

study and presents some conclusions. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 1-2 
2. MODELING APPROACH 

2.1 Air Quality Model (CALPUFF) 

We used the EPA-recommended long-range transport model, CALPUFF, for this 

screening study. CALPUFF is a multi-layer, multi-species non-steady-state puff 

dispersion model that can simulate the effects of time- and space-varying meteorological 

conditions on pollutant transport, transformation, and removal. It can accommodate 

arbitrarily varying point source, area source, volume source, and line source emissions. It 

is intended for use on scales from tens of meters to hundreds of kilometers from a source. 

Detailed descriptions of the formulation and features of CALPUFF are provided in 

the CALPUFF documentation (Scire et al., 2000a). Here, we briefly summarize some of 

the features of CALPUFF that are relevant to our study and discuss the limitations of 

CALPUFF in its treatment of atmospheric chemistry. CALPUFF includes algorithms for 

near-source effects such as building downwash, transitional plume rise, partial plume 

penetration, sub-grid scale terrain interactions as well as longer range effects such as 

pollutant removal due to wet and dry deposition, simplified chemical transformations, 

vertical wind shear, over-water transport and coastal interaction effects. Because the 

latter features were relevant to simulating the transport and chemistry of SOx emissions 

from ships, they were activated for our study. 

CALPUFF offers several options to simulate the formation of secondary sulfate and 

nitrate particles from the oxidation of the emitted primary gaseous pollutants, SO2 and 

NOx respectively. Since the oxidation of SO2 to sulfate was of interest for this study, we 

selected the more advanced chemistry module available in CALPUFF, which is based on 

the RIVAD/ARM3 chemical mechanism (Morris et al., 1988). This option treats the NO 

and NO2 conversion processes in addition to the NO2 to inorganic nitrate and SO2 to 

sulfate conversions. The scheme assumes low background VOC concentrations and is 

not suitable for urban regions. The NO-NO2-O3 chemical system is first solved to get 

pseudo-steady-state concentrations of NO, NO2, and O3. During the day, this system 

consists of the NO2 photolysis reaction to yield NO and O3 and the NO-O3 titration 

reaction to yield NO2. During the night, only the NO-O3 titration reaction is considered. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-1 
In the implementation of the RIVAD/ARM3 scheme in CALPUFF, the background 

O3 concentration is used as the initial O3 concentration at each puff chemistry time step 

(i.e., the plume O3 concentration does not evolve as a function of the downwind distance 

but instead it is replenished at each time step). This may lead to errors if the sources that 

are being simulated are large NOx emitters. For such sources, the high NO 

concentrations in the plume deplete the O3 concentrations near the source and, as a result, 

OH concentrations are very low and the gas-phase rates of NO2 and SO2 oxidation to 

HNO3 and H2SO4, respectively, are negligible (Karamchandani et al., 1998; 

Karamchandani and Seigneur, 1999). In CALPUFF, the lack of depletion of O3 in the 

plume leads to an overestimate of the steady-state daytime concentration of the hydroxyl 

radical, OH, which is calculated from the final O3 concentration after the solution of the 

NO-NO2-O3 system and is, therefore, also overestimated in the near field. Because the 

OH concentrations are overestimated, CALPUFF overestimates the rates of formation of 

HNO3 and H2SO4 in the near field. 

CALPUFF uses dry deposition velocities to calculate the dry deposition of gaseous 

and particulate pollutants to the surface. These dry deposition velocities can either be 

user-specified or calculated internally in CALPUFF using a resistance-based model. For 

this study, we selected the latter option to calculate dry deposition velocities. For 

gaseous pollutants, the resistances that are considered are the atmospheric resistance, the 

deposition layer resistance, and the canopy resistance. For particles, a gravitational 

settling term is included and the canopy resistance is assumed to be negligible. The 

various resistances and particle settling rates are calculated as functions of atmospheric 

variables (e.g., stability and wind speed), surface characteristics (e.g., surface roughness, 

vegetation type, physiological state), and the properties of the depositing material (gas 

diffusivity, solubility, and reactivity; particle size, shape, and density). 

CALPUFF uses the scavenging coefficient approach to parameterize wet deposition 

of gases and particles. The scavenging coefficient depends on pollutant characteristics 

(e.g., solubility and reactivity), as well as the precipitation rate and type of precipitation. 

The model provides default values for the scavenging coefficient for various species and 

two types of precipitation (liquid and frozen). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-2 
2.2 Meteorological Model (CALMET) 

The recommended meteorological inputs for applying CALPUFF are the timedependent outputs of CALMET, a meteorological model that contains a diagnostic wind 

field module and overwater and overland boundary layer modules (Scire et al., 2000b). 

The outputs of CALMET are hourly gridded fields of micro-meteorological parameters 

and three-dimensional wind and temperature fields. The wind field module in CALMET 

combines an objective analysis procedure using wind observations with parameterized 

treatments of slope flows, valley flows, terrain kinematic effects, terrain blocking effects, 

and sea/lake breeze circulations. The boundary layer modules of CALMET produce 

gridded fields of micrometeorological parameters, such as friction velocity, convective 

velocity scale, and Monin-Obukhov lengths, as well as mixing heights and PGT stability 

classes. 

Inputs to CALMET include surface and upper air meteorological data. Optionally, 

CALMET can also use the outputs of prognostic meteorological models, such as MM5 

and CSUMM, to supplement observations and create the meteorological fields required 

by CALPUFF. A processor (CALMM5) is available to convert MM5 data to the format 

required for CALMET. For this study, we used the U.S. EPA’s MM5 simulation outputs 

for 2002. The MM5 domain contains the entire contiguous United States and portions of 

Canada and Mexico and extends out to the Pacific Ocean in the west, the Gulf of Mexico 

to the south and the Atlantic Ocean in the east. Thus, MM5 results for all the coastlines 

relevant to our study were available from the EPA. Section 3 provides additional details 

on the preparation of the meteorological data inputs for CALPUFF for this study. 

2.3 Approach 

For each coastline, a number of annual CALPUFF simulations were conducted. We 

used 2002 as our reference year because it corresponds to the most recent year for which 

an MM5 simulation covering all coastlines was available. The first simulation for each 

coastline was to establish the target values of annual-average SO2 and sulfate 

concentrations at an array of inland receptors (the placement of the receptors is described 

in Section 2.3.1 below). These target values correspond to emissions from ships at 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-3 
dockside, i.e., those ships that are within the SECA and, therefore, will likely have to 

burn low sulfur fuel (15,000 ppm fuel content). Then, we conducted annual CALPUFF 

simulations for ships located at various distances from the coastline. For these 

simulations, the ship emissions used were those based on ships burning high sulfur fuel 

(i.e., 27,000 ppm fuel content). The comparisons of annual-average concentrations of 

SO2 and sulfate from these simulations with the target values determined previously 

provide a basis for defining the SECA modeling domain for the CMAQ simulations to be 

conducted by EPA. 

In the following sections, we provide additional details on the placement of 

receptors and sources for the simulations as well as the modeling domain for each 

coastline. 

2.3.1 Receptors 

Ground-level receptors were located on land along the coastline and at various 

distances from the coastline. The first line of receptors was located along the coastline, 

with a distance of 10 km between adjacent receptors. This distance provides a finer 

spatial resolution than that of the ship emissions (see Section 3). Nine additional lines of 

receptors were then located inland parallel to the coastline receptors. The distances 

between adjacent lines of receptors were variable, with higher resolutions near the 

coastline and coarser resolutions further inland. The first line of inland receptors was 

located at 10 km from the coastline receptors, while the last line of receptors was located 

at 240 km (about 150 miles) from the coastline. Depending on the coastline being 

simulated, the total number of receptors varied from about 1100 to 2800. 

2.3.2 Sources 

Ship emissions were represented by a set of stationary point sources. Each point 

source represents one ship. The use of stationary sources to represent moving ships is an 

appropriate approximation for this screening modeling study, because using stationary 

sources will overestimate the downwind air quality impacts (emissions will be 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-4 
concentrated in specific locations rather than continuously distributed along the shipping 

lane, thereby leading to greater ambient air concentrations). 

For each simulation, the sources were located at a selected distance from shore 

(along the coastline for the target value simulations, and at 125 km, 250 km, 375 km, and 

500 km from the coastline for the SECA boundary simulations). The spacing between 

adjacent ships for a given simulation was determined from ship traffic and estimated 

shipping lane density (see Section 3). We maintained the same number of ships for the 

at-sea emissions scenarios as the number of ships for the dockside emissions scenario. 

This number varied from about 40 to 100 depending on the coastline being simulated. 

2.3.3 Modeling domains 

The following U.S. coastlines were simulated in this screening study: 

 Southern Pacific Ocean coastline 

 Northern Pacific Ocean coastline 

 Gulf of Mexico coastline 

 Atlantic Ocean coastline 

All modeling domains were selected to allow an off-shore distance of at least 500 

km from the coastline to include all ship-at-sea scenarios (see above) and an inland 

distance of at least 240 km from the coastline to provide sufficient spatial coverage for 

calculating air quality impacts. 

The modeling domain for the Southern Pacific U.S. coastline extends from about 30 

degrees North to 38 degrees North and includes Southern California, the Central 

California coastline, and the southern portion of Northern California. Figure 2-1 shows 

this domain as well as the locations of coastline ships for the target value simulation and 

the locations of the receptors at the coastline and inland where SO2 and sulfate 

concentrations were calculated. 

Figure 2-2 shows the domain for the Northern Pacific U.S. coastline, which extends 

from about 35 degrees North to about 52 degrees North and includes Northern California, 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-5 
Figure 2-1. Modeling domain for the Southern Pacific Ocean U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-6 
Figure 2-2. Modeling domain for the Northern Pacific Ocean U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-7 
Oregon, and Washington in the U.S., and the southern half of the British Columbia 

coastline in Canada. 

In the east-west direction, the modeling domains for both the Southern Pacific and 

Northern Pacific coastlines begin at the western boundary of the modeling domain for the 

MM5 simulations that provided the hourly 3-D meteorological inputs for our study (see 

Section 3). The eastern boundaries of the modeling domains for the Southern and 

Northern Pacific coastline extend to about 115 degrees West and 112 degrees West, 

respectively. 

The modeling domain for the Gulf of Mexico coastline is shown in Figure 2-3. The 

east-west extent of the modeling domain is from Western Texas (about 105 degrees 

West) in the west to Florida and the Atlantic Ocean (about 75 degrees West). The 

southern boundary of the modeling domain coincides with the southern boundary of the 

MM5 domain while the northern boundary is at about 34 degrees North. 

The southern boundary of the Atlantic Ocean modeling domain, shown in Figure 2­

4, also coincides with the southern boundary of the MM5 domain. The northern 

boundary is at about 52 degrees North, just a few degrees lower than the northern 

boundary of the MM5 domain. The western boundary of the Atlantic Ocean domain is at 

about 85 degrees West, while the eastern boundary coincides with the eastern boundary 

of the MM5 domain. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-8 
Figure 2-3. Modeling domain for the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-9
Figure 2-4. Modeling domain for the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 2-10 
3. MODEL INPUTS 

The following inputs were required for the CALPUFF simulations 

 Meteorology 

 Emissions 

 Land use and terrain elevation data 

 Coastline data 

Terrain elevation data at 1 degree DEM (Digital Elevation Model) resolution were 

downloaded from the U.S. Geological Survey (USGS). Land use data were also obtained 

from the USGS at a 1:250,000 scale. These data were processed by the 

CALPUFF/CALMET preprocessors: TERREL, CTGCOMP, CTGPROC, and 

MAKEGEO. 

Coastline data were obtained using the ZXPLOT package from the Center for the 

Analysis and Prediction of Storms at the University of Oklahoma. 

The preparation of meteorological and emission inputs for the CALPUFF 

simulations is described below. 

3.1 Meteorology 

As described in Section 2.2, CALMET is the companion meteorological model that 

is used to prepare the meteorological fields used by CALPUFF. CALMET is a 

diagnostic meteorological model that can use standard surface and upper air 

meteorological data, and also has an over-water option that allows the use of special 

over-water measurements for grid cells that are over the ocean. In addition, CALMET 

can use 3-D gridded meteorological fields from prognostic models, such as MM5, to 

either supplement observations or to provide an initial guess field for the diagnostic 

procedure. 

For this study, we used a combination of land-based surface measurements, overwater measurements, and MM5 outputs to create the CALPUFF meteorological fields. 

The MM5 fields provide the vertical structure with sufficient temporal (hourly) and 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-1 
spatial (36 km) resolution to supplement the surface measurements. This approach 

provides consistency with the subsequent grid-based modeling that will be conducted by 

OAQPS to define SECAs using CMAQ, because CMAQ will be driven with the MM5 

meteorology. It also addresses a weakness in the official release of CALMET (Scire et 

al., 2005) in its calculation of mixing heights over-water surfaces. The mixing height 

algorithm in CALMET underestimates over-water mixing heights, especially during light 

wind conditions over warm water, since it only calculates mechanically-derived mixing 

over water surfaces. This weakness has been corrected in a new version of CALMET 

described by Scire et al. (2005). However, this new version was not available to us at the 

time we performed the CALMET simulations for this study. Based on our discussions 

with the CALMET developers (Scire, 2005), we used the MM5 mixing heights directly in 

CALMET. 

3.1.1 Measurements 

The National Climatic Data Center (NCDC) Integrated Surface Hourly 

Observations database provided the land-based hourly surface measurements. These 

include wind speed, wind direction, temperature, and dew point temperature. Over-water 

measurements were available for all the coastlines from the National Data Buoy Center 

(NDBC) (http://www.ndbc.noaa.gov). These measurements are taken from buoys. The 

buoys are at varying distances from the coast. Those near the coast are frequently near 

harbors or bays. Most of the buoys are owned and operated by NDBC but there are also 

several other agencies that submit their data to the NDBC database. The over-water 

measurement coverage is sparse, as shown in Figures 3-1 through 3-4, which show the 

locations of the land-based surface and over-water measurements for each of the 

coastlines that were simulated in this study. We used 2002 observations for consistency 

with the MM5 outputs (see below). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-2 
Figure 3-1. Land-based surface stations and over-water stations for the Southern 

Pacific Ocean U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-3 
Figure 3-2. Land-based surface stations and over-water stations for the Northern 

Pacific Ocean U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-4 
Figure 3-3. Land-based surface stations and over-water stations for the Gulf of 

Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-5 
Figure 3-4. Land-based surface stations and over-water stations for the Atlantic Ocean 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-6 
 3.1.2 MM5 outputs 

We used the outputs of the 2002 MM5 simulations sponsored by the U.S. EPA to 

supplement the meteorological measurements. These outputs were provided to us by 

ENVIRON Corporation. The MM5 modeling domain, shown in Figure 3-5, covers the 

entire contiguous United States and extends significantly over the oceans. The horizontal 

spatial resolution for the MM5 outputs is 36 km. 

An interface program (CALMM5) converts the MM5 data into a form compatible 

with CALMET. A beta version (not yet officially approved by the EPA) of CALMM5 

processes MM5 Version 3 output data directly. This processor is available from the 

CALPUFF-CALMET Download BETA-Test page. 

3.1.3 CALMET Winds 

As mentioned above, the wind fields were calculated with CALMET using the 

outputs of MM5 in combination with available data. To illustrate the variability of wind 

speed and direction with location and season, we present wind roses over the ocean based 

on the calculated CALMET wind fields for the southern Pacific coastline, northern 

Pacific coastline, Gulf of Mexico coastline and Atlantic coastline in Figures 3-6, 3-7, 3-8 

and 3-9, respectively. 

In the southern Pacific Ocean, winds are mostly from the southwest except during 

winter in the northern part of the domain where the wind direction is more variable. In 

the northern Pacific, the prevailing winds are from the west in the southern part of the 

domain (i.e., off the coast of California and Oregon) during spring, summer and fall. 

Wind direction is variable during winter in the southern part of the domain and for all 

seasons in the northern part of the domain. 

In the Gulf of Mexico, the wind direction varies with season and location. During 

winter, in the western part of the domain, the prevailing winds are from the southwest 

and the northeast; they are mostly from the west and north in the central part of the 

domain and with more variable direction near the Florida coast. During spring and 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-7
Figure 3-5. MM5 modeling domain. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-8 
Figure 3-6a. Wind roses based on CALMET outputs for the southern Pacific Ocean 

during winter 2002 (top) and spring 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-9 
Figure 3-6b. Wind roses based on CALMET outputs for the southern Pacific Ocean 

during summer 2002 (top) and fall 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-10 
Figure 3-7a. Wind roses based on CALMET outputs for the northern Pacific Ocean 

during winter 2002 (top) and spring 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-11 
Figure 3-7b. Wind roses based on CALMET outputs for the northern Pacific Ocean 

during summer 2002 (top) and fall 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-12 
Figure 3-8a. Wind roses based on CALMET outputs for the Gulf of Mexico during 

winter 2002 (top) and spring 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-13 
Figure 3-8b. Wind roses based on CALMET outputs for the Gulf of Mexico during 

summer 2002 (top) and fall 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-14 
Figure 3-9a. Wind roses based on CALMET outputs for the Atlantic Ocean during 

winter 2002 (left) and spring 2002 (right). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-15 
Figure 3-9b. Wind roses based on CALMET outputs for the Atlantic Ocean during 

summer 2002 (left) and fall 2002 (right). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-16 
summer, the winds in the western and central parts of the domain are mostly from the 

north, but they are variable in direction near the Florida coast (the prevailing wind 

direction varies from north-north-east in the western part of the domain to north-northwest in the eastern part of the domain). During fall, the winds are more variable with a 

tendency to be from the west to north-east in the western part of the domain and from the 

north to north-west in the central and eastern parts of the domain. 

In the Atlantic Ocean, winds are mostly from the south to south-west in the 

southern part of the domain. They are more variable in the northern part of the domain 

with a prevailing northern trend that evolves from a northeastern direction during winter 

to a northwestern direction during summer. 

3.1.4 CALMET Mixing heights 

As mentioned above, the CALMET mixing heights were obtained from the MM5 

outputs. They vary spatially and temporally. We illustrate such variability in Figures 3­

10 through 3-13 where seasonally-averaged mixing heights are depicted for the southern 

Pacific coast, northern Pacific coast, gulf of Mexico coast and Atlantic coast, 

respectively. 

Mixing heights are lowest in winter (December – February) and highest in summer 

(June – August). They are lower over water than over land; they also tend to be greater 

over the Gulf of Mexico than over the Pacific and Atlantic oceans. Ship emissions were 

predominantly released after plume rise within the mixing layer. 

3.2 Emissions 

As described in Section 2.3.2, ship emissions were represented by a set of stationary 

point sources. The point source emissions information required for the CALPUFF 

simulations include stack locations, stack characteristics such as stack heights and stack 

flow rates, and emission rates of SO2, sulfate, NO and NO2. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-17 
Figure 3-10a. Mixing heights for the southern Pacific Ocean during winter 2002 (top) 

and spring 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-18 
Figure 3-10b. Mixing heights for the southern Pacific Ocean during summer 2002 (top) 

and fall 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-19 
Figure 3-11a. Mixing heights for the northern Pacific Ocean during winter 2002 (top) 

and spring 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-20 
Figure 3-11b. Mixing heights for the northern Pacific Ocean during summer 2002 (top) 

and fall 2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-21 
Figure 3-12a. Mixing heights for the Gulf of Mexico during winter 2002 (top) and spring 

2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-22 
Figure 3-12b. Mixing heights for the Gulf of Mexico during summer 2002 (top) and fall 

2002 (bottom). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-23 
Figure 3-13a. Mixing heights for the Atlantic Ocean during winter 2002 (left) and spring 

2002 (right). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-24 
Figure 3-13b. Mixing heights for the Atlantic Ocean during summer 2002 (left) and fall 

2002 (right). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-25 
 3.2.1 Emission rates 

Emission factors are needed to estimate the emissions of SOx (gas-phase SO2 and 

particulate-phase sulfate) associated with various ship activities. Based on the review of 

available emission factors of Seigneur et al. (2005), the most recent EPA emission factors 

were selected (EPA, 2002). Those emission factors pertain to ships with engines with 

displacement exceeding 30 liters (so-called Category 3 engines). Emission factors are 

reported for three different engine types (slow speed, medium speed and steam boiler) for 

transit modes and hoteling modes. For this study of ships at sea, we are interested in 

medium speeds for transit modes. 

The SO2 emission factor per unit of work is reported to be 9.56 g/hp-h for a 3% 

sulfur fuel (i.e., 30,000 ppm) for a ship at slow or medium speed in transit mode. This is 

equivalent to 12.8 g/kW-h. For a ship within the SECA, we assumed a fuel sulfur content 

of 15,000 ppm, resulting in an emission factor of 6.4 g/kW-h. For ships at sea outside of 

the SECA, a fuel sulfur content of 27,000 ppm was assumed. Therefore, the emission 

factor for such ships was estimated to be 11.52 g/kW-h. 

EPA assumes that 2% of sulfur is emitted as primary sulfate PM from Category 3 

marine diesel engines. Therefore, we treated 2% of total sulfur emissions as sulfate 

emissions and the SO2 emission factor was adjusted down accordingly to maintain the 

sulfur mass balance. (Note that for the same amount of S, the sulfate emission factor is 

1.5 the SO2 emission factor to account for the different molecular weights of SO2 and 

sulfate.) 

Therefore, within the SECA, the gas-phase SO2 and particulate-phase sulfate 

emission factors are 6.27 g/kW-h and 0.19 g/kW-h, respectively. Outside of the SECA, 

the gas-phase SO2 and particulate-phase sulfate emission factors are 11.29 g/kW-h and 

0.35 g/kW-h, respectively. 

The sulfate emission rates calculated above are consistent with available data on the 

sulfate fraction of particulate matter (PM) emitted from ship diesel engines. Fleischer et 

al. (1998) report that 20 to 30% of PM emissions from ship diesel engines are sulfate (for 

a 3% sulfur fuel content). The EPA (2002) emission factor for PM is 1.3 g/hp-h, i.e., 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-26
1.74 g/kW-h. These values lead to an emission factor for sulfate in the range of 0.31 to 

0.47 g/kW-h for a sulfur fuel content of 27,000 ppm. The emission factor of 0.35 g/kW-h 

calculated above falls within this range. 

Based on data from Corbett and Koehler (2003), the power of a typical ship was 

estimated to be 16,000 kW (Corbett, 2005). It should be noted that there is a wide range 

of power among various ships, with the largest container ships having power exceeding 

65,000 kW. 

The gas-phase SO2 and particulate-phase sulfate emissions per ship are then 

calculated to be 100,320 g/h and 3,040 g/h, respectively, within the SECA and 180,640 

g/h and 5,600 g/h, respectively, outside the SECA 

A similar approach was used to calculate the NO and NO2 emission rates. The NOx 

emission factor per unit of work is reported to be 12.38 g/hp-h (as NO2) for a ship at slow 

or medium speed in transit mode (EPA, 2002). This is equivalent to 16.6 g/kW-h. For a 

typical ship with a power of 16,000 kW, the resulting NOx emission rate is 266,000 g/h 

(as NO2). Assuming that 5% of the NOx emissions are released as NO2 on a molar basis, 

the NO and NO2 emission rates were calculated to be 164,800 g/h and 13,300 g/h, 

respectively. These emission rates were used for ships within and outside the SECA, i.e., 

it was assumed that the switch to lower sulfur content fuel within the SECA did not affect 

the NOx emission rates. 

3.2.2 Stack parameters 

These parameters include the locations of the sources and their stack characteristics. 

As discussed in Section 2.3.2, the ships were placed along the coastline for the target 

value calculations and at various distances from the coastline for the SECA boundary 

estimation. In this section, we discuss the spatial density of the ships, i.e., the spacing 

between each ship. This was determined based on analysis of ship activity data, as 

described below. 

We used the average number, N, of ships in transit along the coast per year and 

average cruising speed, V (km/h), to calculate the average distance, D (km), between two 

ships along a shipping lane. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-27 
D = V * (24 h/day * 365 days/yr) / N 

The annual number of ships transiting along the southern California coast was 

estimated to be 13,000 (ICOADS, 2002). This number includes all ships transiting to and 

from ports located on the southern Pacific coast as well as ships transiting 

southward/northward from/to ports located on the northern Pacific coast. It is likely to be 

an overestimate of the number of ships transiting along the coast because a fraction of 

those ships will be transiting along shipping lanes that extend from the ports westward 

into the Pacific Ocean. The cruising speed varies according to ship type. It is about 24 

knots for container ships and about 16 knots for tankers. Here, the average ship cruising 

speed was estimated to be about 20 knots, i.e., 36 km/h (ICOADS, 2002). Thus, the 

average distance estimated for the southern Pacific coast was calculated as follows. 

D = 36 * 24 * 365 / 13,000 = 24.3 km 

Based on this analysis, we used a distance of 25 km between ships to calculate ship 

emissions. The same distance was used for the other coastlines. 

The other stack parameters required include stack characteristics such as stack 

height, stack diameter, stack exhaust velocity, and stack exit temperature. These 

parameters were obtained for typical container and tanker ship type categories from an 

ARB report (ARB, 2000). For this study, we used the average values for these two 

categories (see Table 3-1). 

Table 3-1. Stack characteristics. 

Stack height 35.3 m 

Stack diameter 1.9 m 

Exhaust velocity 24.6 m/s 

Exhaust temperature 537 K 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 3-28 
4. RESULTS 

The initial CALPUFF baseline (i.e., ships along the coastline) and SECA boundary 

simulations for the Southern Pacific, Northern Pacific, and Gulf of Mexico coastlines 

were conducted using the latest EPA-approved version of CALPUFF. However, after 

discussions with the CALPUFF developers (Scire, 2006), it was decided that the final 

simulations would be conducted using the latest BETA-Test version of the model. This 

version addresses problems reported to the model developers by CALPUFF users. The 

results presented here are all based on simulations conducted with the beta version of 

CALPUFF. 

Because the objective of the study is to identify upper limits for the off-shore 

distances at which sea-going ships may switch from cleaner fuel to high-sulfur content 

fuel, the results are presented in terms of the ratios of the ground-level SO2 and sulfate 

concentrations at land-based receptors calculated from the off-shore source simulations to 

those calculated from the coastline source simulations. This allows us to determine the 

percentage of receptors at which the emissions from the sea-going ships will lead to air 

quality impacts that are less than or equal to the target values, i.e., the ground-level SO2 

and sulfate concentrations calculated from the baseline simulation. 

Before presenting the results, it is useful to discuss the expected differences 

between SO2 and sulfate in terms of the evolution of their downwind concentrations, and 

how these differences affect the results obtained here. SO2 and sulfate concentrations 

will display different behaviors downwind of the ships. SO2 concentrations will decrease 

continuously with distance from the source (due to dilution, removal, and conversion to 

sulfate), whereas sulfate concentrations will first decrease (dilution and removal of 

primary, i.e., directly emitted sulfate), then increase (formation of secondary sulfate from 

the oxidation of SO2) before finally decreasing (dilution and removal exceeding 

formation). 

This behavior of sulfate introduces an additional complication: the sulfate target 

values at receptors near the coastline will be determined by the directly emitted sulfate, 

while the target values at larger distances inland will be determined by some combination 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-1 
of primary and secondary sulfate, with the secondary sulfate component increasing and 

the primary sulfate component decreasing. Even further inland, both components will 

decrease as the rate of dilution and removal exceeds the formation of sulfate. 

These differences between the behavior of SO2 and sulfate suggest that the SO2 

concentrations will become smaller than the design values at a smaller distance than the 

sulfate concentrations will. The SO2 concentrations due to the higher SOx emissions 

from the ships at sea burning higher sulfur fuel will be offset by the dilution and 

conversion of SO2 much sooner than the sulfate concentrations since the latter will 

initially experience an increase from the SO2 conversion. 

In the discussion of the results that follows, we will refer to concentrations 

calculated from the emissions of coastline sources (i.e., ships within the SECA burning 

low-sulfur fuel) as the “target” values, and the concentrations due to emissions from ships 

at sea (i.e., ships outside the SECA burning high-sulfur fuel) as the “design” values. The 

ratios of the “design” concentrations to the “target” concentrations will be referred to as 

the “design ratios”. 

4.1 Results for the Southern Pacific U.S. Coastline 

Figure 4-1 shows the spatial patterns of the design ratios of the ground-level annual 

average SO2 concentrations for ships at 125 km from the coastline. While there are large 

areas where the ratios are less than one, particularly near the southern part of the domain, 

the ratios are larger than one for the majority of the receptors. This is depicted in Figure 

4-2, which shows the cumulative frequency distribution of the design ratios. The design 

ratios are less than one at about 41% of the receptors. 

The spatial distribution of the sulfate design ratios for ships at 125 km from the 

coastline is shown in Figure 4-3. In contrast to the SO2 results, the sulfate ratios are less 

than one over a very small portion of the domain near the southern boundary. From 

Figure 4-4, we see that the percentage of receptors for which the sulfate design ratios are 

less than one is only about 4%. These differences between the SO2 and sulfate results are 

consistent with our expectations as discussed earlier. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-2 
Figure 4-1. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-3 
Figure 4-2. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Southern Pacific U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-4 
Figure 4-3. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-5 
Figure 4-4. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Southern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-6 
The SO2 results for ships at 250 km from the coastline are shown in Figures 4-5 and 

4-6. From Figure 4-5, we see that, except for a small region in the Central Valley of 

California (Kings county, most of Fresno county, and portions of Tulare and Kern 

counties) and isolated locations along the coast in Santa Barbara county, most of the 

receptors have ratios less than one. Figure 4-6 shows that the percentage of receptors that 

have ratios less than one for ships at 250 km from the coastline is nearly 91%. 

For sulfate, even when the ships are at a distance of 250 km, we see from Figure 4-7 

that the sulfate design ratios are less than one only near the southern portion of the 

modeling domain, in Orange and San Diego counties, southern Imperial county, western 

Riverside county, and a small region of southern Los Angeles county. In the rest of the 

domain, the design ratios are larger than one, suggesting that increases in downwind 

sulfate concentrations from the conversion of SO2 to sulfate are still the determining 

factors for ship emissions at 250 km. Figure 4-8 shows that the percentage of receptors 

for which the sulfate design ratios is less than one for ships at 250 km from the coastline 

is only about 25%. 

Figures 4-9 and 4-10 show the SO2 results for ships at 375 km from the coastline. 

As seen in Figure 4-9, except for one location along the coastline in Santa Barbara 

county, all the receptors show design ratios less than one. The cumulative frequency 

distribution, shown in Figure 4-10, confirms that SO2 air quality impacts from the ships 

burning high-sulfur fuel are less than those from coastline ships burning low-sulfur fuel 

at over 99.99% of the land-based receptors. 

Figures 4-11 and 4-12 show that the sulfate results for ships at 375 km from the 

coastline still show larger air quality impacts than the coastline ships for a large majority 

of the receptors. From Figure 4-11, a clear north-south gradient is evident. In the region 

north of Los Angeles county, and including portions of northern Los Angeles county, the 

sulfate ratios are larger than one. In the region south, all the sulfate ratios are less than 

one. Figure 4-12 shows that about 42% of the receptors have sulfate ratios less than one. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-7 
Figure 4-5. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-8 
Figure 4-6. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Southern Pacific U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-9 
Figure 4-7. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-10 
Figure 4-8. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Southern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-11 
Figure 4-9. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-12 
Figure 4-10. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 375 km from the Southern Pacific U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-13 
Figure 4-11. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-14 
Figure 4-12. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Southern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-15 
The sulfate results for ships at 500 km from the coastline are shown in Figures 4-13 

and 4-14 (the corresponding SO2 results are not shown here since the 375 km results 

presented earlier show that a distance of 375 km is more than adequate for setting the 

upper limit of the SECA for SO2 impacts). The north-south gradient is still evident, as 

shown in Figure 4-13, but the boundary between the two regions of ratios less than one in 

the south to ratios larger than one in the north has shifted to the north (to Ventura county 

in the west and to Kern and Tulare counties in the east). The two regions are 

approximately equal in area, as confirmed by the cumulative frequency distribution in 

Figure 4-14. 

In these analyses, the Santa Barbara area tends to show higher concentrations of 

SO2 and sulfate and, in some cases high concentration/target value ratios. One reason for 

such high concentrations is that the Santa Barbara area extends westward into the Pacific 

Ocean and, as a result, receptors near the coast have more ship emission sources in their 

close vicinity than receptors located in other areas along the coast. All sources will not 

impact the Santa Barbara receptors simultaneously because such impacts will depend on 

the wind flow (see Figure 3-6). Nevertheless, the probability of impact from ship 

emission sources should be higher for the Santa Barbara area than for other areas along 

the southern Pacific coast because of the design of the source/receptor locations in this 

screening study. This characteristic of the source/receptor relationship should be kept in 

mind when interpreting the simulation results. Note that the air quality modeling to be 

conducted later with the 3-D CMAQ model will locate ship emissions along shipping 

lanes and, therefore, will provide a more realistic set of source/receptor relationships. 

4.2 Results for the Northern Pacific U.S. Coastline 

Figures 4-15 and 4-16 show the SO2 results for ships at 125 km from the Northern 

Pacific coastline. We see from Figure 4-15 that the regions with ratios less than one are 

approximately equal in area to the regions with ratios greater than one. As shown in 

Figure 4-16, the ratios are less than one at about 47% of the receptors. The higher ratios 

typically occur inland in areas of high elevation (e.g., the Cascade mountain range). The 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-16 
Figure 4-13. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Southern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-17 
Figure 4-14. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Southern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-18 
Figure 4-15. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-19 
Figure 4-16. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Northern Pacific U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-20 
corresponding sulfate results are shown in Figures 4-17 and 4-18. The sulfate ratios are 

larger than one over the entire domain except for a few isolated locations. Over a large 

portion of the domain, the ratios range from 1.4 to 1.8. From Figure 4-18, we see that 

over 99.99% of the receptors have ratios larger than one. The results from the San 

Francisco Bay Area are similar to those that were obtained for the southern Pacific 

domain, which suggests that most of the ships impacting this area are within the 

modeling domains. 

At 250 km from the coastline, the SO2 ratios are less than one at nearly 100% of the 

receptors, as shown in Figures 4-19 and 4-20. However, sulfate ratios are still larger than 

one at a majority (nearly 96%) of the receptors, as shown in Figures 4-21 and 4-22. 

The SO2 ratios for ships at 375 km and 500 km from the North Pacific U.S. 

coastline are less than one at all the receptors and are not shown here. Figure 4-23 shows 

the spatial distribution of the sulfate ratios for ships at 375 km from the coastline, while 

Figure 4-24 shows the cumulative frequency distribution of the ratios. From Figure 4-24, 

we see that only about 20% of the receptors show ratios less than one. However, over a 

very large part of the domain, the ratios larger than one are usually in the range of 1 to 

1.4, as shown in Figure 4-23. The largest ratios, in the range of 1.4 to 1.8, are 

concentrated in the western parts of southern Oregon and northern California, near the 

boundary between the two states. This area is in the center of the domain and is, 

therefore, exposed to the ship emissions located west and southwest from its coastline 

(see wind roses in Figure 3-7). 

The sulfate results for ships at 500 km from the North Pacific U.S. coastline are 

shown in Figures 4-25 and 4-26. At a majority (56%) of the receptors, the ratios are less 

than one for ships at this distance. The largest ratios are again near the boundary region 

between California and Oregon. The results for the San Francisco Bay Area are 

significantly lower than those obtained for the southern Pacific domain because, at that 

distance, most of the ships that impact this area are located southwest of this area (see 

windroses in Figures 3-6 and 3-7). 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-21 
Figure 4-17. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-22 
Figure 4-18. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Northern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-23 
Figure 4-19. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-24 
Figure 4-20. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Northern Pacific U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-25 
Figure 4-21. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-26 
Figure 4-22. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Northern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-27 
Figure 4-23. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-28 
Figure 4-24. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Northern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-29 
Figure 4-25. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Northern Pacific U.S. 

coastline to the concentrations (target values) due to dockside ships at the 

coastline burning low-sulfur fuel. The red dots represent the locations of 

the sea-going ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-30 
Figure 4-26. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Northern Pacific U.S. 

coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-31 
4.3 Results for the Gulf of Mexico Coastline 

The results for the Gulf of Mexico coastline are quite different from the two 

coastlines on the West Coast. The relative air quality impacts at land-based receptors 

from ships at sea are generally lower for the Gulf of Mexico than for the Pacific Ocean 

even for ships located at 125 km from the coastline. The SO2 results for ships at 125 km 

from the Gulf of Mexico coastline are shown in Figures 4-27 and 4-28. From Figure 4­

27, we see that the SO2 ratios are less than one over most of the receptor network, except 

in southern Florida. The ratios are larger than one at only about 16% of the receptors, as 

shown in Figure 4-28. The larger values simulated in Florida result in part from the 

design of the “shipping lane” that is located 125 km south of the coastline but, in the case 

of Florida, closer from a coastline located directly east from the ships. Therefore, the 

fraction of receptors that have ratios below one should be seen as a lower limit. 

The sulfate results for ships at 125 km from the Gulf of Mexico coastline, shown in 

Figures 4-29 and 4-30, are also different from the sulfate results for the Pacific Ocean 

coastlines. Nearly 40% of the receptors have sulfate ratios less than one. Ratios larger 

than one are seen in Florida, Georgia, Alabama, and portions of Mississippi and 

Louisiana, as well as at the tip of southern Texas near the border with Mexico. 

The SO2 results for ships at 250 km from the Gulf of Mexico coastline are shown in 

Figures 4-31 and 4-32. We see from Figure 4-31 that, except for a small region in 

southern Florida, the ratios at all the receptors are less than one. The percentage of 

receptors with ratios less than one is over 98%, as shown in Figure 4-32. Figures 4-33 

and 4-34 show the 250 km results for sulfate. We see from Figure 4-33 that the region 

with sulfate ratios larger than one is confined to most of Florida and southern Georgia. 

Figure 4-34 shows that only 28% of the receptors have sulfate ratios larger than one. 

We only show the sulfate results for the 375 km and 500 km distances from the 

Gulf of Mexico coastline, since all receptors satisfy the criterion of SO2 ratios less than 

one at these distances. Figure 4-35 shows the spatial pattern of sulfate ratios for ships at 

375 km from the coastline. Ratios larger than one are only seen in Florida and small 

areas of southern Georgia. From Figure 4-36, we see that over 80% of the receptors 

show sulfate ratios less than one. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-32 
Figure 4-27. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-33 
Figure 4-28. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-34 
Figure 4-29. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-35 
Figure 4-30. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-36 
Figure 4-31. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-37 
Figure 4-32. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-38 
Figure 4-33. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-39 
Figure 4-34. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-40 
Figure 4-35. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-41 
Figure 4-36. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-42 
The sulfate results for ships at 500 km from the Gulf of Mexico coastline are 

qualitatively similar to the 375 km distance results, as shown in Figures 4-37 and 4-38. 

For the 500 km scenario, sulfate ratios are larger than one only in Florida, as shown in 

Figure 4-37. Figure 4-38 shows that the percentage of receptors with sulfate ratios less 

than one increases only marginally (by about 3.5%) when the ships are placed at 500 km 

instead of 375 km. 

4.4 Results for the Atlantic Ocean Coastline 

Figure 4-39 shows the spatial distribution of annual-average SO2 ratios for ships at 

125 km from the Atlantic Ocean coastline, while Figure 4-40 shows the cumulative 

frequency distribution of the ratios. As in the case of the Gulf of Mexico coastline, the 

SO2 ratios are less than for a majority of the receptors at the 125 km distance. From 

Figure 4-39, we see that the ratios are larger than one only in southern Georgia, most of 

North Carolina, and portions of Connecticut and Massachusetts. The percentage of 

receptors with SO2 ratios less than one is nearly 87%, as shown in Figure 4-40. In 

contrast, the 125 km sulfate results for the Atlantic Ocean show that the ratios are larger 

than one for almost the entire domain, as shown in Figures 4-41 and 4-42. 

The SO2 results for ships at 250 km from the Atlantic Ocean coastline are shown in 

Figures 4-43 and 4-44. At this distance, the SO2 ratios are less than one throughout the 

domain. Figures 4-45 and 4-46 show the corresponding results for sulfate. We see from 

Figure 4-45 that sulfate ratios are less than one in the southeastern U.S. (Florida, Georgia, 

and South Carolina) and some of the New England states, such as Vermont, New 

Hampshire and Maine. The ratios are larger than one in most of North Carolina, eastern 

Virginia, eastern Pennsylvania, New Jersey, southern New York, Connecticut, Rhode 

Island, and southern Massachusetts. Figure 4-46 shows that the sulfate ratios are less 

than one at nearly 58% of the receptors. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-43 
Figure 4-37. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Gulf of Mexico coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-44 
Figure 4-38. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Gulf of Mexico coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-45 
Figure 4-39. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-46 
Figure 4-40. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 125 km from the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-47 
Figure 4-41. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 125 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-48 
Figure 4-42. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 125 km from the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-49 
Figure 4-43. Ratios of annual-average SO2 concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-50 
Figure 4-44. Cumulative frequency distribution of design ratios of SO2 concentrations 

from ships at 250 km from the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-51 
Figure 4-45. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 250 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-52 
Figure 4-46. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 250 km from the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-53 
Figure 4-47 shows the spatial distribution of sulfate ratios for ships at 375 km from 

the Atlantic Ocean coastline. We see that the sulfate ratios are less than one almost 

everywhere, except in portions of eastern North Carolina and southern Massachusetts. 

As shown in Figure 4-48, the sulfate ratios are less than one at over 92% of the receptors. 

For ships at 500 km from the Atlantic Ocean coastline, the sulfate ratios are less 

than one everywhere as shown in Figures 4-49 and 4-50. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-54 
Figure 4-47. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 375 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-55 
Figure 4-48. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 375 km from the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-56 
Figure 4-49. Ratios of annual-average sulfate concentrations due to sea-going ships 

burning high-sulfur fuel at 500 km from the Atlantic Ocean coastline to 

the concentrations (target values) due to dockside ships at the coastline 

burning low-sulfur fuel. The red dots represent the locations of the seagoing ships. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-57 
Figure 4-50. Cumulative frequency distribution of design ratios of sulfate 

concentrations from ships at 500 km from the Atlantic Ocean coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 4-58 
5. SUMMARY AND CONCLUSIONS 

A screening study with the CALPUFF dispersion model was conducted to 

determine the air quality impacts (annual average ground-level concentrations of SO2 and 

sulfate) at an array of land-based receptors due to SOx emissions from ships burning 

high-sulfur fuel at sea at various distances from the coastline. CALPUFF tends to 

overestimate the conversion of SO2 to sulfate in the gas phase (Karamchandani et al., 

2006) and the results presented here are likely to provide conservative estimates of the 

impacts of emissions from ships at sea on inland air quality. (Because of the simplified 

treatment of aqueous-phase chemistry in CALPUFF, this assessment may be altered if the 

interactions of the ship plumes with fog dominate sulfate formation.) The results were 

compared with those calculated for ships burning low-sulfur fuel at the coastline to 

determine upper bounds for Sulfur Emission Control Areas (SECAs), i.e., off-shore 

distances at which the switch to high-sulfur fuel would not impair air quality. For each 

offshore distance investigated, the percentage of receptors for which the air quality 

impacts of ships at sea were lower than the impacts of ships at the coastline was 

calculated. 

The U.S. coastlines considered in this study include the Pacific Ocean coastline, the 

Gulf of Mexico coastline, and the Atlantic Ocean coastline. The northern and southern 

parts of the Pacific Ocean coastline were studied separately. The results are summarized 

in Tables 5-1 and 5-2 for concentration ratios of SO2 and sulfate, i.e., the ratio of the 

concentration calculated for ships at sea to the concentration calculated for ships at the 

coastline. 

The results for SO2 were different from those for sulfate, primarily due to 

differences in the behavior of these two species downwind of a source. For all the 

coastlines studied, the majority of the SO2 concentration ratios were less than one at 

shorter off-shore distances than for sulfate. Thus, sulfate concentration ratios were the 

limiting factor for defining the upper bounds of the SECA for each coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 5-1 
Table 5-1. Percentage of SO2 concentrations below the design value as a function of 

the distance from the coastline. 

Distance from coastline 125 km 250 km 375 km 500 km 

Southern Pacific 40.7% 90.7% 100% 100% 

Northern Pacific 46.6% 97.9% 100% 100% 

Gulf of Mexicoa 84.4% 98.1% 100% 100% 

Atlantic 86.6% 100% 100% 100% 

a

Note that Florida values correspond to a shorter ship-coastline distance and the values 

presented in the table should be seen as lower limits. 

Table 5-2. Percentage of sulfate concentrations below the design value as a function 

of the distance from the coastline. 

Distance from coastline 125 km 250 km 375 km 500 km 

Southern Pacific 4.4% 24.9% 41.9% 48.7% 

Northern Pacific 0.01% 3.6% 20.3% 55.7% 

Gulf of Mexicoa 40.4% 72.0% 80.5% 84.0% 

Atlantic 1.2% 57.9% 92.5% 100% 

a

Note that Florida values correspond to a shorter ship-coastline distance and the values 

presented in the table should be seen as lower limits. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 5-2 
The results showed some differences in results among the various coastlines 

studied. These differences are due to differences in the wind fields bringing the offshore 

ship emissions and their secondary products to land as well as differences in 

precipitation, which removes pollutants from the atmosphere. 

The results from the two Pacific Ocean coastline simulations were qualitatively 

similar. For both Pacific Ocean coastlines, over 90% of the receptors showed SO2 

concentration ratios less than one for ships at 250 km from the coastline. For sulfate, 

only about 49% and 56% of the receptors had concentrations less than one for ships at 

500 km from the southern Pacific Ocean and northern Pacific Ocean coastlines, 

respectively. 

For the other two coastlines (Atlantic Ocean and Gulf of Mexico), the SO2 results 

were qualitatively similar to those for the Pacific Ocean coastlines, i.e., over 90% of the 

receptors showed SO2 concentration ratios less than one for ships at 250 km from the 

coastline. However, there were some large differences for sulfate. For the Gulf of 

Mexico coastline, over 70% of the receptors showed sulfate concentration ratios less than 

one for ships at 250 km from the coastline. For the Atlantic Ocean coastline, nearly 60% 

of the receptors showed sulfate concentration ratios less than one for ships at 250 km 

from the coastline. 

These results suggest that an off-shore distance of 500 km should be sufficient 

when conducting refined modeling of the potential impacts of ship emissions on air 

quality inland, if a criterion of about 50% of inland receptors having sulfate 

concentrations below the design value is acceptable to define the SECA. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 5-3 
6. REFERENCES 

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Control Strategies in the South Coast Air Basin, California Air Resources Board, 

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Corbett, J.J. and H.W. Koehler, 2003. Updated emissions from ocean shipping, J. 

Geophys. Res., 108, doi:10.1029/2003JD003751. 

Corbett, J.J., 2005. Private communication to Christian Seigneur, AER, July 2005. 

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prepared by ENVIRON International Corporation, U.S. Environmental Protection 

Agency, Office of Transportation and Air Quality, Ann Arbor, MI. 

Fleischer, F., E.J. Ulrich, R. Krapp and W. Grundmann, 1998. Comments on particulate 

emissions from diesel engines when burning heavy fuels, Proc. Of the 22nd 

CIMAC Internat. Congress on Combustion Engines, Vol. 6, Copenhagen, 

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ICOADS, 2002. International Comprehensive Ocean Atmospheric Data Set, as 

transmitted from ERG by Office of Transportation and Air Quality, U.S. 

Environmental Protection Agency, Washington, D.C. 

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mechanism for atmospheric plume chemistry, Environ. Sci. Technol., 32, 1709– 

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Karamchandani, P., and C. Seigneur, 1999. Simulation of sulfate and nitrate chemistry in 

power plant plumes, J. Air Waste Manage. Assoc., 49, PM-175–181. 

Karamchandani, P., S.-Y. Chen, N. Kumar and M. Gupta, 2006. A comparative 

evaluation of two reactive puff models using power plant plumes measurements, 

AWMA Guideline on Air Quality Models Conference, Denver CO, 26-28 April. 

Morris, R.E., R.C. Kessler, S.G. Douglas, K.R. Styles and G.E. Moore, 1988. Rocky 

Mountain Acid Deposition Model Assessment: Acid Rain Mountain Mesoscale 

Model (ARM3), report prepared for the U.S. EPA, Research Triangle Park, NC. 

Scire, J.S., D.G. Strimaitis and R.J. Yamartino, 2000a. A User’s Guide for the CALPUFF 

Dispersion Model (Version 5), Earth Tech, Inc. Report, Concord, MA, January 

2000. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 6-1 
Scire, J.S., F.R. Robe, M.E. Fernau and R.J. Yamartino, 2000b. A User’s Guide for the 

CALMET Dispersion Model (Version 5), Earth Tech, Inc. Report, Concord, MA, 

January 2000. 

Scire, J.S., 2005. Communication via e-mail of Christian Seigneur, AER, with Joe Scire, 

EarthTech, 18-19 March 2005. 

Scire, J.S., D.G. Strimaitis and F.R. Robe, 2005. Evaluation of enhancements to the 

CALPUFF model for offshore and coastal applications, Proceedings of the 10th 

International Conference on Harmonisation with Atmospheric Dispersion 

Modelling for Regulatory Purposes, Crete, Greece, 17-20 October 2005. 

Scire, J.S., 2006. Private communication to Prakash Karamchandani, AER, February 

2006. 

Seigneur, C., K. Lohman and P. Karamchandani, 2005a. Review of Technical 

Information relevant to Sulfur Oxides (SOx) Emissions Transport for Ships at Sea, 

Final Report to Office of Transportation and Air Quality, U.S. Environmental 

Protection Agency, Washington, D.C. 

Seigneur, C., P. Karamchandani and K. Lohman, 2005b. Analysis Plan - Modeling Sulfur 

Oxides (SOx) Emissions Transport for Ships at Sea, Final Report to Office of 

Transportation and Air Quality, U.S. Environmental Protection Agency, 

Washington, D.C. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea 6-2 
APPENDIX A 

REVIEW OF TECHNICAL INFORMATION RELEVANT TO 

SULFUR OXIDES (SOx) EMISSIONS TRANSPORT 

FOR SHIPS AT SEA 

Prepared by 

Christian Seigneur 

Kristen Lohman 

Prakash Karamchandani 

Atmospheric & Environmental Research, Inc. 

2682 Bishop Drive, Suite 120 

San Ramon, CA 94583 

Prepared for 

U.S. Environmental Protection Agency 

Office of Transportation and Air Quality 

1200 Pennsylvania Avenue, NW 

Washington, DC 20460 

Document CP212-05-01b 

June 2005 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-1 
INTRODUCTION 

Marine shipping represents a major and growing source of uncontrolled air 

pollution in coastal regions and inland areas downwind of coastal regions in many parts 

of the world, particularly North America and Europe. This can be attributed to both 

growth in global trade and port activity, as well as controls on land-based emissions. In 

1973, an international conference of the International Maritime Organization (IMO) 

adopted the International Convention for the Prevention of Marine Pollution from Ships 

(MARPOL) designed to prevent pollution from ships. In 1997, the IMO agreed to 

MARPOL Annex VI, a global treaty to reduce air emissions from ships. This treaty went 

into effect on May 19, 2005. The treaty sets limits on emissions of sulfur oxides (SOx) 

and nitrogen oxides (NOx) and prohibits the international emissions of ozone-depleting 

substances, such as chlorofluorocarbons. One key element of Annex VI is the 

establishment of “SOx Emission Control Areas” (SECAs) near coastal regions where 

controls on SOx emissions from ships are more stringent (1.5% fuel content or 15,000 

ppm) than in the open seas (4.5% or 45,000 ppm). 

Countries wanting to obtain SECA designation for their coastal areas must submit 

a formal application to the IMO. The U.S. Environmental Protection Agency (EPA) is 

currently in the process of exploring the feasibility of a SECA for U.S. coastal areas and 

plans to work with affected states to obtain the necessary data. As part of the application 

process, emissions inventories will be developed and air quality modeling analyses will 

be conducted. 

EPA will conduct the air quality modeling analyses for the SECA application inhouse using three-dimensional (3-D) grid-based models such as CMAQ and/or CAMx. 

One of the issues of interest for this modeling exercise is the determination of the “scales 

of interest”, i.e., a delineation of the extent and scope of the SECA for each coastal region 

that will be considered in the analysis. This determination will be performed using a 

“screening-level” modeling analysis, in which a methodology will be developed and 

applied to estimate SOx emissions transport from ships at sea to areas off the U.S. coasts 

(Pacific, Atlantic, and the Gulf of Mexico) using realistic ship emissions and 

meteorology. SOx emissions transport from ships on the Great Lakes will be addressed 

separately under the U.S.-Canada binational program. 

This document describes the first component of the SOx emissions transport 

methodology, which is a literature review of available tools and data to quantify the 

transport and residence times of SOx over water. The fate and transport of pollutants over 

water has long been of interest because of the potential impacts of off-shore platforms on 

air quality over land and the potential impacts of ship emissions on global climate change 

and air quality over land. Consequently, there is a significant body of information 

available on the atmospheric transport, dispersion and chemistry of pollutants emitted 

over water. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-1 
The Minerals Management Service (MMS) has conducted several studies to 

investigate the meteorology and the fate and transport of oil platform emissions in the 

Gulf of Mexico (e.g., Yocke et al., 1998). Those studies are not directly applicable to the 

present study because the emission source is different; nevertheless, some valuable data 

and useful experience were obtained in the MMS studies that are relevant to the present 

study. The relevant aspects are discussed in this report. The U.S. Navy investigated the 

potential of ship emissions reaching shore and that report provides useful information 

regarding the different meteorological regimes along the U.S. coastline (Eddington and 

Rosenthal, 2003). The California Air Resources Board (2000) also conducted a modeling 

study of the transport and dispersion of NOx emissions from ships in the southern 

California region. There have also been several academic investigations on the fate and 

transport of pollutants emitted from ships. The most recent and relevant one (Song et al., 

2003) pertains to the simulation of sulfur chemistry in a ship plume released in the 

marine boundary layer. The authors used a simple box model to simulate the plume. 

They concluded that, in the presence of non-precipitating clouds, non-sea salt sulfate 

could attain about 2 μg/m3 after a few hours of plume travel time. The SO2/sulfate 

chemistry was found to be linear (i.e., a change in SO2 emissions would lead to a 

proportional change in sulfate concentrations) except near the ship where SO2 

concentrations exceeded the hydrogen peroxide (H2O2) concentrations. 

In this report, we first examine the fate and transport models available for 

simulating the transport of pollutants over water. Then, available data sources are 

discussed for some of the most important input data beginning with meteorology, then 

emission factors, and finally ship activity data. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-2 
AIR QUALITY MODELS 

Air quality models can be grouped in two major categories: grid-based Eulerian 

models and Lagrangian plume (or puff) models. Eulerian models are well suited to 

address air quality for urban and regional pollutants that are emitted from a large variety 

of sources. However, their spatial resolution is limited by the grid size and they are not 

well suited for addressing air quality impacts associated with individual sources or groups 

of sources. Plume or puff models are better suited for such air quality impacts since their 

formulation takes into account the dispersion of the emitted material from the source to 

the downwind distances of interest. 

For this screening study of the potential impacts of SOx emissions from ships at 

sea, we are considering Lagrangian plume and puff models since they are the most 

suitable. We are considering three models: OCD, CALPUFF and SCICHEM. We briefly 

describe these models below and discuss their advantages and shortcomings before 

making our recommendations for the air quality model to be used for this study. 

OCD 

OCD was developed under funding from the Minerals Management Service 

(MMS) to simulate plume dispersion and transport from offshore sources to receptor 

areas on land or water. 

OCD is a steady-state Gaussian model that uses hourly inputs. The steady-state 

assumption implies that the wind direction and speed are constant for an air parcel after it 

leaves the source regardless of the time needed for an air parcel to travel between the 

source and the receptor point. Its formulation includes enhancements that take into 

account differences between overwater and overland dispersion characteristics, the sealand interface and off-shore platform aerodynamic effects. 

OCD requires both overwater and overland meteorological data (i.e., including 

wind speed and direction, water surface temperature, overwater air temperature, mixing 

height and relative humidity). Missing overwater meteorological data such as turbulence 

intensities are parameterized using bulk aerodynamic wind and temperature profile 

relationships. 

The effect of the source on plume dispersion (stack-tip downwash and building 

downwash) can be taken into account. Corrections are made for the presence of complex 

terrain. The evolution of the thermal boundary layer near the coast is simulated. 

Transitional plume rise and the partial penetration of elevated temperature inversions are 

simulated. 

OCD can simulate the chemical decay of pollutants using first-order 

transformation rates that are user-specified. However, the formation of secondary 

pollutants from an emitted primary pollutant (e.g., formation of sulfate from emitted SO2) 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-3 
cannot be simulated; this is a major deficiency for this study since it addresses the 

possible impacts of sulfate concentrations on air quality. Removal processes (e.g., dry 

deposition) are simulated using a first-order decay. 

OCD is listed by EPA as a guideline model but only for primary pollutants 

(Federal Register, 2003). Therefore, it is not recommended by EPA for secondary air 

pollutants such as sulfate formed from SO2 oxidation in the atmosphere. 

CALPUFF 

CALPUFF was originally developed under funding from the California Air 

Resources Board (ARB) along with its associated meteorological model, CALMET 

(Scire et al., 2000a, 2000b). 

CALPUFF is a non-steady-state puff dispersion model that can simulate the 

effects of time- and space-varying meteorological conditions on pollutant transport, 

transformation, and removal. It can accommodate arbitrarily varying point, area, volume, 

and line source emissions. 

The recommended meteorological inputs for applying CALPUFF are the timedependent outputs of CALMET, a meteorological model that contains a diagnostic wind 

field module and overwater and overland boundary layer modules. Optionally, 

CALMET can use the outputs of prognostic meteorological models, such as MM5 and 

CSUMM, to create the meteorological fields required by CALPUFF. 

CALPUFF includes algorithms for near-source effects such as building 

downwash, transitional plume rise, partial plume penetration, sub-grid scale terrain 

interactions as well as longer range effects such as pollutant removal due to wet and dry 

deposition, simplified chemical transformations, vertical wind shear, overwater transport 

and coastal interaction effects. 

CALPUFF offers several options to simulate the formation of secondary sulfate 

and nitrate particles from the oxidation of the emitted primary gaseous pollutants, SO2 

and NOx respectively. The oxidation of SO2 to sulfate is of interest for this study. The 

more advanced chemistry module available in CALPUFF uses the RIVAD/ARM3 

chemical mechanism (Morris et al., 1988). This simple mechanism treats the conversion 

of NO to NO2 accompanied by its further transformation to total nitrate and conversion of 

SO2 to sulfate. It is assumed that background concentrations of reactive hydrocarbons 

(VOC) are low and, therefore, this mechanism is not considered suitable for urban 

regions. It may be suitable for oversea situations where VOC concentrations are not too 

high. However, in areas such as southern California, where urban coastal pollution may 

be transported over the ocean via the land-sea breeze, the assumption of low background 

VOC concentrations may sometimes be invalid. 

In the RIVAD/ARM3 chemical mechanism, the NO-NO2-O3 chemical system is 

first solved to generate pseudo-steady-state concentrations of NO, NO2, and O3. During 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-4 
the day, this system consists of the NO2 photodissociation to yield NO and O3 and the 

NO-O3 titration reaction to yield NO2. During the night, only the NO-O3 titration 

reaction is considered. The steady-state daytime concentration of the hydroxyl radical 

(OH) is calculated from the O3 concentration after the solution of the NO-NO2-O3 

system. Gupta et al. (2001) have noted that the O3 concentrations are incorrectly treated 

in CALPUFF, resulting in the overestimation of OH concentrations, and thus 

overestimations in the gas-phase oxidation rates of SO2 to sulfate and NOx to nitrate. The 

RIVAD/ARM3 mechanism does not explicitly calculate the aqueous-phase oxidation of 

SO2 to sulfate. Instead, a constant heterogeneous SO2 oxidation rate (0.2% per hour) is 

added to the gas phase conversion rate. The partitioning of semi-volatile chemical 

species (ammonium nitrate) between the gas phase and the particulate phase is simulated 

with a simple thermodynamic model. 

CALMET is the companion meteorological model that is used with CALPUFF. 

A weakness of CALMET has recently been identified (Wheeler, 2005). CALMET does 

not correctly handle cases of unstable convective atmospheric conditions over water 

(when water temperature is warm and air temperature is cold, for example) because it 

assumes near-neutral conditions over water. Consequently, the mixing height is 

calculated based on a neutral mixing relationship and, under conditions of light wind 

speeds when the mechanical mixing heights are small, CALMET underpredicts the actual 

mixing height. This weakness can be an issue in areas such as the Gulf of Mexico where 

warm water temperatures are possible. EarthTech, the developer of CALMET is 

addressing this problem by adding a convective mixing height calculation in CALMET. 

This new version of the model is currently being tested but it is not yet publicly available. 

Based on our discussion with EarthTech (Scire, 2005), we will circumvent this potential 

problem by inputting measured or modeled mixing heights directly into CALMET 

(meteorological data are discussed in Section 3). 

CALPUFF is listed by EPA as a preferred air quality model for assessing the 

long-range transport of air pollutants and on a case-by-case basis for certain near-field 

applications involving complex meteorological conditions (Federal Register, 2003). 

CALPUFF is also recommended by the Federal Land Managers’ Air Quality Values 

Workgroup (FLAG) for assessing the effects of distant plumes on atmospheric visibility. 

SCICHEM 

SCICHEM is an extension of the Second-order Closure Integrated PUFF model 

(SCIPUFF) that includes atmospheric chemical transformations. It has been developed 

under funding from EPRI and the Defense Threat Reduction Agency (DTRA) ((Sykes et 

al., 1988, 1993; Sykes and Henn, 1995; Karamchandani et al., 2000; EPRI, 2000). 

SCICHEM is a non-steady-state multi-species model that incorporates a 

comprehensive treatment for gas- and aqueous-phase chemistry, and PM formation. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-5 
SCIPUFF represents a plume with a multitude of three-dimensional puffs that are 

advected and dispersed by the local micrometeorological conditions. Each puff has a 

Gaussian representation of the concentrations of individual species. SCIPUFF simulates 

the plume transport and dispersion using a second-order closure approach to solve the 

turbulent diffusion equations, which provide a direct connection between measurable 

velocity statistics and predicted dispersion rates. 

SCIPUFF can assimilate observational data ranging from a single wind 

measurement to multiple profiles. Alternatively, three-dimensional gridded wind and 

temperature fields generated by a prognostic model or other analyses can be used as input 

to the model. SCIPUFF can simulate the effect of wind shear since individual puffs 

evolve according to their respective locations in an inhomogeneous velocity field. As 

puffs grow larger, they may encompass a volume that cannot be considered homogenous 

in terms of the meteorological variables. A puff splitting algorithm accounts for such 

conditions by splitting puffs that have become too large into a number of smaller puffs. 

Conversely, individual puffs that are affected by the same (or very similar) 

micrometeorology may also merge to produce a larger single puff. Also, the effects of 

buoyancy on plume rise and initial dispersion are simulated by solving the conservation 

equations for mass, heat, and momentum. 

For PM related regulatory applications, it is important that the underlying model 

should account for processes responsible for phase-dependent chemical transformations 

and PM characterization. We provide a brief description of chemical and PM 

components of SCICHEM. 

In SCICHEM, the gas-phase chemical reactions within the puffs are simulated 

using a general framework that allows any chemical kinetic mechanism (e.g., CBM-IV, 

SAPRC) to be treated. Therefore, SCICHEM can simulate atmospheric conditions 

ranging from the clean atmosphere to polluted areas. To minimize the need for 

computational resources needed to treat the typical chemical mechanisms, the gas-phase 

puff chemistry can optionally be simulated using a three-staged chemical kinetic 

mechanism where the number of reactions treated increases as the puff mixes with 

background air (Karamchandani et al., 1998). This multistage approach offers reasonable 

accuracy (within ±10%) with increased computational speed. 

Chemical species concentrations in the puffs are treated as perturbations from the 

background concentrations. This approach allows the treatment of overlapping puffs and, 

therefore, provides great flexibility for simulating processes such as calm conditions, 

wind shear and overlapping plumes for different sources. Optionally, SCICHEM can 

explicitly simulate the effect of turbulence on chemical kinetics. 

SCICHEM includes aqueous-phase chemistry. It is simulated using the RADM 

chemical mechanism. When the aqueous-phase chemistry option is selected, the wet 

deposition of pollutants is computed from the cloud water concentrations of pollutants 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-6 
and the precipitation rate. Otherwise, scavenging coefficients are used to calculate wet 

deposition. The partitioning of semi-volatile chemical species between the gas phase and 

the particulate phase is simulated with the thermodynamic model ISORROPIA. 

EPA has added SCIPUFF to the list of alternate models (Appendix B of the EPA 

Guideline on Air Quality Models, Federal Register, 2003) for the simulation of the longrange transport and dispersion of air pollutants. 

Recommendations 

Table 2-1 presents a summary of the advantages and shortcomings of the three 

models reviewed here. The major shortcomings of OCD are its use of the steady-state 

assumption and its lack of treatment of chemical transformations. The steady-state 

assumption implies that the wind direction and wind speed are assumed to be constant for 

a puff released from the source, whereas the other two models allow for changes in wind 

direction and wind speed. Chemical transformations in OCD are limited to a simple 

decay of the emitted pollutants and do not allow the treatment of secondary pollutant 

formation (such as the formation of sulfate from SO2). The major shortcoming of 

CALPUFF is its simplified chemistry that tends to overestimate sulfate formation in the 

gas phase and uses a simple parameterization for the cloud/fog aqueous phase. 

CALPUFF offers the major advantage of being widely used and being an EPA preferred 

guideline model for the long-range transport of SOx. SCICHEM offers a more 

comprehensive formulation than CALPUFF. However, SCICHEM is not yet an EPA 

preferred guideline model. It is still considered a research-grade model and its 

computational requirements are significantly greater than those of the other two models. 

On the basis of this review, we recommend that CALPUFF be used to simulate 

the transport, transformation and deposition of SOx emissions from ships, with the caveat 

that one must bear its limitations in mind. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-7 
Table 2-1. Comparison of the advantages and shortcomings of three plume/puff 

models for emissions from off-shore sources. 

Characteristics OCD CALPUFF SCICHEM 

Steady-state vs. 

transient 

Steady-state Transient Transient 

Spatial resolution Gaussian plume Puffs Puffs 

Wind-shear No Yes Yes 

Plume overlaps Yes Yes Yes 

Near-source effects Yes Yes Yes 

Chemical 

transformations 

First-order decay Simplified 

chemistry 

Comprehensive 

chemistry 

Dry deposition First-order decay Yes Yes 

Wet deposition No Yes Yes 

Source types Point, line and area Point, line, area and 

volume 

Point 

Regulatory status EPA preferred 

guideline model for 

primary pollutants 

released over water 

EPA preferred 

guideline model for 

long-range transport 

and visibility 

impacts of air 

pollutants 

EPA alternate 

guideline model 

Computational 

requirements 

Low Moderate High 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-8 
METEOROLOGICAL DATA 

Meteorological data are necessary to run an air dispersion model. For the 

CALPUFF model, the meteorological input data must first be formatted by the CALMET 

pre-processor. CALPUFF requires standard surface and upper air meteorological data. 

CALMET also has an overwater option that allows the use of special overwater 

measurements for grid cells that are over the ocean. The data required for the overwater 

option are: air-sea temperature difference, air temperature, relative humidity, wind speed 

and wind direction. Two optional measurements, overwater mixing height and overwater 

temperature gradients, may be supplied if available. If the optional parameters are not 

supplied, CALMET uses default values. 

Land-based Measurements 

Land-based meteorological measurements are required for both surface and upper 

air observations above land portions of the domain. The data required are standard 

format data from the National Climatic Data Center (NCDC) (Scire et al., 2000). The 

upper air data required are standard NCDC format TD6201 radiosonde data including 

pressure, elevation, temperature, wind direction, and wind speed for each sounding level. 

The surface observations that are needed are provided in the NCDC Integrated Surface 

Hourly Observations. These include wind speed, wind direction, temperature, and dew 

point temperature. 

Fixed Overwater Measurements 

The required parameters are all available for the Pacific and Atlantic oceans near 

the U.S. coastline and for the Gulf of Mexico and Great Lakes from the National Data 

Buoy Center (NDBC) (NDBC, 2005). The measurements are taken from buoys. The 

buoys are at varying distances from the coast. Those near the coast are frequently near 

harbors or bays. Though the coverage is not uniform, the full length of the continental 

U.S. coastline is covered by those data. Most of the buoys are owned and operated by 

NDBC but there are also several other agencies that submit their data to the NDBC 

database. Figures 3-1 through 3-6 show the locations of the NDBC buoys as well as 

those that are run by other agencies and are included in the NDBC database. 

The Minerals Management Service (MMS) has performed modeling for the 

Breton National Wilderness Area which is on the Coast of the Gulf of Mexico. The 

MMS has provided us additional overwater data for the Gulf of Mexico including both 

surface and upper air data. The availability of upper air data will allow a more thorough 

modeling of the unique conditions above the Gulf of Mexico. These data are available 

for the years 1999-2001. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-9 
Figure 3-1. NDBC buoys along the Washington, Oregon, and northern California 

coastline. 

Figure 3-2. NDBC buoys along the southern California coastline 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-10 
Figure 3-3. NDBC buoys along the western Gulf of Mexico 

Figure 3-4. NDBC buoys along the eastern Gulf of Mexico 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-11 
Figure 3-5. NDBC buoys along the southeastern U.S. coastline 

Figure 3-6. NDBC buoys along the northeastern U.S. coastline. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-12 
Data from Ships 

The CALMET preprocessor also allows for the location of meteorological 

observations to vary so that measurements made from ships can be used for modeling as 

well. NCDC as well as other agencies have shipboard measurements. 

One available database is the International Comprehensive Ocean-Atmosphere 

Data Set (ICOADS) from NOAA (NOAA, 2005). It provides data on the location of the 

ship, as well as air temperature, sea temperature, wind speed and direction, pressure, and 

dew point. These data are available from 1950 through 2002. 

Model Outputs 

The outputs of meteorological models can be used, particularly in cases where 

there are insufficient meteorological observations. This may be the case for upper air 

data in the Atlantic and Pacific Oceans. Examples of model outputs that could be used as 

surrogates for upper air data include those from the 2001 or 2002 MM5 simulations 

sponsored by EPA, those from the NCEP/NCAR reanalysis project and those from the 

Advanced Climate Modeling and Environmental Simulations (ACMES) database. 

Recommendations 

There appears to be sufficient meteorological data to model the transport of SOx 

emissions from ships. The availability of upper air data for the Gulf of Mexico will be 

particularly valuable. In the absence of upper air data over water for the other areas, 

either some default assumptions will need to be made regarding atmospheric stability or 

the outputs of archived meteorological simulations will be used. We will discuss our 

proposed technical approach in the Analysis Plan that will be prepared in Task 2. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-13 
4. EMISSION FACTORS 

Emission factors are needed to estimate the emissions of SOx associated with 

various ship activities. We reviewed available emission factors and provide our 

recommendations below. 

EPA (2000) Emission Factors 

Emission factors for air pollutant emissions from ships are provided in the report 

titled “Analysis of Commercial Marine Vessels Emissions and Fuel Consumption Data” 

(EPA, 2000). Emission factors are provided for several air pollutants including SO2 and 

PM. Those emission factors are provided for different oceangoing ship categories that 

include bulk carriers and tankers, general cargo ships, container/RoRo/auto 

carriers/refrigerated ships, and passenger ships. The emission factors are a function of 

the operating mode of the engine; four modes were considered: normal cruise, slow 

cruise, maneuvering and docking (hoteling). 

For SO2, the emission factor is a function of the fuel consumption rate and sulfur 

content of the fuel. The fuel consumption rate is provided per unit of work (i.e., g/kW-h) 

as a function of the fractional load. The engine work (kW-h) is a function of the ship 

type (see above) and ship deadweight. The fractional load is the ratio of the actual engine 

output and rated engine output; it is a function of the engine mode and ship type. 

If one assumes a fuel sulfur content of 3%, the SO2 emission factor per unit of 

work is 16 g/kW-h for a cruising ship and 20 to 25 g/kW-h for a maneuvering ship. The 

SO2 emission factor per unit of fuel is 71 kg/metric ton. 

EC Emission Factors 

A recent report from the European Commission (EC) provides emission factors 

for air pollutants from ships (EC, 2002). Emission factors are reported for pollutants 

including SO2 and PM. The emission factors are provided either by engine type and fuel 

type (15 combinations) or by ship type (16 oceangoing ship types); different factors are 

provided for at sea and in port activities (emission factors for PM are only provided for in 

port activities). 

The emission factors are reported in g/kW-h. Thus, the engine horsepower must 

be estimated as a function of the ship type and activity. 

The SO2 emission factor per unit of work is in the range of 10 to 13 g/kW-h for a 

ship at sea and 11 to 13 g/kW-h for a ship at port. The SO2 emission factor per unit of 

fuel is in the range of 46 to 54 kg/metric ton. These emission factors are slightly lower 

(by 20 to 35%) than those reported in the EPA report cited above. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-14 
EPA (2002) Emission Factors 

A recent EPA report (2002) presents a review of emission factors available from 

several sources. The emission factors reviewed were for ships with engines with 

displacement exceeding 30 liters (so-called Category 3 engines). 

Emission factors are reported for three different engine types (slow speed, 

medium speed and steam boiler) for transit modes and hoteling modes. 

For slow and medium speed engines, the SO2 emission factor per unit of work is 

about 13 g/kW-h for a ship in transit mode, and 1.4 g/kW-h for a ship in hoteling mode. 

For steam boilers, the SO2 emission factor per unit of work is 20 g/kW-h for a ship in 

both transit and hoteling modes. The SO2 emission factor per unit of fuel is assumed to be 

60 kg/metric ton in transit and 7 kg/metric ton when hoteling (steam boilers were 

assumed to use the same fuel while hoteling as in transit, i.e., 30 kg/metric ton). These 

emission factors appear to be consistent with those from the EC and lower than those 

from the EPA 2000 report. 

Recommendations 

This brief review of available emission factors for SO2 emissions from ships show 

that there is some general consistency among the different sources of information. The 

differences among the various references are well within the uncertainty ranges that one 

would expect for emission factors of air pollutants. We propose to use the most recent 

EPA emission factors (EPA, 2002) for this study because they represent the most recent 

source of information. These emission factors combined with ship type and ship activity 

data will provide emission rates of SO2. 

It should be noted that there are no emission factors for sulfate. SO2 emission 

factors are estimated as a function of the sulfur content of the fuel and the implicit 

assumption is that all sulfur is emitted as gaseous SO2. There is evidence that particulate 

sulfate emissions are associated with diesel engines. For example, sulfate may account 

for up to 12% of PM emissions from cars and trucks (Shi et al., 2000). PM emission 

factors are available for ship emissions. By using the EPA (2002) PM emission factor for 

diesel engines of a ship in transit and assuming that PM is 12% sulfate, we obtain an 

emission factor of 0.2 g/kW-h. This value corresponds to 1.6% of the SO2 emission 

factor. Data from the Navy Pilot Emission Control Program (NPECP) on PM emissions 

from marine diesel engines confirm these results, although the sulfate fraction of PM 

depends on the fuel type and the engine regime, ranging from 2 to 19% of PM. 

Furthermore, EPA assumes that 2% of sulfur is emitted as primary sulfate PM from 

Category 3 marine diesel engines (i.e., those engines with displacement > 30 liters per 

cylinder). Because the rate of oxidation of SO2 to sulfate is slow in the absence of fog or 

clouds (on the order of 1% per hour), emissions of sulfate from ships may contribute 

significantly under such conditions to the sulfate concentrations over land that are due to 

ship emissions. Therefore, we will treat 2% of total sulfur emissions as sulfate emissions 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-15 
and the SO2 emission factor will be adjusted down accordingly to maintain the sulfur 

mass balance. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-16 
5. SHIP ACTIVITY DATA 

Ship activity data must be determined so that the emission factors can be applied 

to provide air pollutant emissions from ships. The activity data are typically calculated 

based on four types of information: port locations, vessel descriptions, trip records, and 

shipping lane definitions. Port locations are available from the United States Army Corps 

of Engineers (USACE) (USACE, 2005). For efficiency, these data should be aggregated 

so that all nearby ports are treated as one. 

Once port data have been aggregated, trip data need to be added. Trip data are 

necessary to track how many of each type of ship move between each port. The emission 

factors will be applied according to ship type, therefore, it is important to characterize the 

ship types per shipping lane per year. The USACE provides data on entrances and 

clearances (USACE, 2005) for vessels traveling under foreign flags. This database lists 

each entry and departure of a vessel bearing a foreign flag. Through these databases, a 

ship can be traced through its travels through U.S. ports. Information on domestic ship 

traffic is also compiled by the USACE. 

The entrances and clearances databases list a ship code that can then be matched 

up to another USACE database. This database provides data on each foreign ship that 

has registered at a U.S. port providing information on type, size, and power. 

Once all of these data have been gathered and processed, they can be combined to 

provide a list of potential trips (e.g., Portland to San Francisco) by type of ship. The final 

step is to provide a geographic location for the ship emissions. Since CALPUFF allows 

the modeling of line sources, we need to determine the geographic definitions of the 

shipping lanes that will be input into the model. These data are available from the 

USACE in the form of the Waterways Network (USACE, 2005). It provides information 

on the latitude and longitude of each node in the U.S. waterways. 

Alternatively, the ICOADS database that provides meteorological measurements 

from ships can be used to determine shipping lanes (NOAA, 2005). ICOADS provides 

time- and space-resolved meteorological data. Because each record provides both the 

ship code and a latitude and longitude, ships can be traced along their actual route. In 

some places this approach may vary significantly from the theoretical ship lanes available 

from the USACE Waterways Network. 

Recommendations 

Information on ship activity data is not currently available in a format ready to use 

for an air quality modeling study. For the Pacific coast, a moderate amount of work 

would be required to complete the processing of the available data into a format suitable 

for air quality modeling. For the other areas, a large amount of work would be required 

based on the data that we identified. One may consider using hypothetical ship emissions 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-17 
for this air quality modeling study; however, those hypothetical emissions should be 

representative of actual ship emissions in order to lead to realistic air quality predictions. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-18 
6. REFERENCES 

California Air Resources Board. 2000. Air Quality Impacts from NOx Emissions of Two 

Potential Marine Vessel Control Strategies in the South Coast Air Basin. Final 

Report, prepared by the California Air Resources Board and the South Coast Air 

Quality Management District in Consultation with the Deep Sea Vessel/Shipping 

Channel Technical Working Group, Sacramento, CA. 

EC, 2002. Quantification of emissions from ships associated with ship movements 

between ports in the European Community, Final Report prepared by Entec UK 

Limited. 

Eddington, L. and J. Rosenthal, 2003. The Frequency of Offshore Emissions Reaching 

the Continental United States Coast Based on Hourly Surface Winds from a 10 

Year Mesoscale Model Simulation, Naval Air Systems Weapons Division, Point 

Mugu, CA. 

EPA, 2000. Analysis of Commercial Marine Vessels Emissions and Fuel Consumption 

Data, EPA-420-R-00-002, U.S. Environmental Protection Agency, Office of 

Transportation and Air Quality, Washington, DC 

EPA, 2002. Commercial Marine Emission Inventory, Final Report from PECHAN, 

prepared by ENVIRON International Corporation, U.S. Environmental Protection 

Agency, Office of Transportation and Air Quality, Ann Arbor, MI. 

. 

EPRI, 2000. SCICHEM Version 1.2: Technical Documentation, EPRI Report 1000713, 

EPRI, Palo Alto, CA. 

Federal Register, 2000. Environmental Protection Agency, 40 CFR Part 51, Requirements 

for Preparation, Adoption, and Submittal of State Implementation Plans 

(Guideline on Air Quality Models); Proposed Rule, Vol. 65, No. 78, Friday, April 

21, 2000, pp. 21506–21542. 

Federal Register, 2003. 40 CFR Part 51, Revision to the Guideline on air quality Models: 

Adoption of a Preferred Long Range Transport Model and Other Revisions; Final 

Rule, 18440-18482, April 15, 2003. 

Gupta, M., N. Kumar, P. Karamchandani, and S.-Y. Wu, 2001. Intercomparison of 

SCICHEM and CLAPUFF models using Cumberland plume data, Air & Waste 

Management Association Conference on Guidelines on Air Quality Models: A 

New Beginning, April 4-6, Newport, RI. 

Hanna, S., L. Schulmann, R. Paine, and J. Pleim, 1984. The Offshore and Coastal 

Dispersion (OCD) Model User’s Guide Revised, MMS 84-0069, Minerals 

Management Service. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-19 
Hanna, S., L. Schulman, R. Paine, J. Pleim and M. Baer, 1985. Developoment and 

evaluation of the offshore and coastal dispersion (OCD) model, J. Air Pollut. 

Control Assoc., 35, 1039-1047. 

Karamchandani, P.; A. Koo; C. Seigneur, 1998. Environ. Sci. Technol., 32, 1709–1720. 

Karamchandani, P.; L. Santos; I. Sykes; Y. Zhang; C. Tonne; C. Seigneur, 2000. Environ. 

Sci. Technol., 34, 870–880. 

Morris, R.E., R.C. Kessler, S.G. Douglas, K.R. Styles and G.E. Moore, 1988. Rocky 

Mountain Acid Deposition Model Assessment: Acid Rain Mountain Mesoscale 

Model (ARM3), Report prepared for the U.S. EPA, Research Triangle Park, NC. 

National Ocean and Atmospheric Administration (NOAA), 2005. 

http://www.cdc.noaa.gov/coads/ “ICOADS” Last accessed April 20, 2005. 

National Data Buoy Center (NDBC), 2005. http://www.ndbc.noaa.gov/index.shtml 

“National Data Buoy Center” Last accessed April 20, 2005. 

Scire, J.S., D.G. Strimaitis and R.J. Yamartino, 2000. A User’s Guide for the CALPUFF 

Dispersion Model (Version 5), Earth Tech, Inc. Report, Concord, MA, January 

2000. 

Scire, J.S., F.R. Robe, M.E. Fernau and R.J. Yamartino, 2000. A User’s Guide for the 

CALMET Dispersion Model (Version 5), Earth Tech, Inc. Report, Concord, MA, 

January 2000. 

Scire, J.S., 2005. Communication via e-mail of Christian Seigneur, AER, with Joe Scire, 

EarthTech, 18-19 March 2005. 

Shi, J.P., D. Mark and R.M. Harrison, 2000. Characterization of particles from a current 

technology heavy-duty diesel engine, Environ. Sci. Technol., 34, 748-755. 

Song, C.H., G. Chen and D. Davis, 2003. Chemical evolution and dispersion of ship 

plumes in the remote marine boundary layer: investigation of sulfur chemistry, 

Atmos. Environ., 37, 2663-2679. 

Sykes, R. I., W. S. Lewellen, S. F. Parker and D. S. Henn, 1988. A Hierarchy of 

Dynamic Plume Models Incorporating Uncertainty, Volume 4: Second-order 

Closure Integrated Puff, EPRI, EPRI EA-6095 Volume 4, Project 1616-28. 

Sykes, R. I.; S. F. Parker; D. S. Henn; W. S. Lewellen, 1993 J. Appl. Met., 32, 929–947. 

Sykes, R. I.; D. S. Henn, 1995. J. Appl. Met., 34, 2715–2723. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-20 
United States Army Corps of Engineers, 2005. 

http://www.iwr.usace.army.mil/ndc/data/data1.htm “Navigation Data Center – 

U.S. Waterway Data” Last accessed April 20, 2005. 

Wheeler, N., 2005. Private communication from Neil Wheeler, Sonoma Technology, 

Inc. to Christian Seigneur, AER, 14 March. 

Yocke, M.A. et al., 1998. Meteorology of the northeastern Gulf of Mexico. ENVIRON 

International Corp. U.S. DOI. OCS Study: final report, data from 1995 to 1997. 

2000. 154 p. Available from GOM (with 3 CD's). MMS 2000-075. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea A-21 
APPENDIX B 

ANALYSIS PLAN 

MODELING SULFUR OXIDES (SOx) EMISSIONS TRANSPORT 

FOR SHIPS AT SEA 

Prepared by

Christian Seigneur 

Prakash Karamchandani 

Kristen Lohman 

Atmospheric & Environmental Research, Inc. 

2682 Bishop Drive, Suite 120 

San Ramon, CA 94583 

Prepared for 

U.S. Environmental Protection Agency 

Office of Transportation and Air Quality 

1200 Pennsylvania Avenue, NW 

Washington, DC 20460 

Document CP212-05-02a 

July 2005 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-1 
INTRODUCTION 

This document describes the analysis plan for modeling the SO2 and sulfate 

concentrations due to emissions of SOx from ships at sea. The results of this screening 

modeling study will provide quantitative information on the shortest distance at which 

ships burning higher sulfur fuel (here, 27,000 ppm) will have air quality impacts at land 

receptors that are less than those anticipated from emissions from ships burning low 

sulfur fuel (here, 15,000 ppm) within coastal waters. This resulting distance can 

subsequently be used as the basis for defining the modeling domain for sources to be 

included in a subsequent modeling study using an Eulerian model (CMAQ). The results 

of the CMAQ modeling will yield information to define the outer boundary of a Sulfur 

Emission Control Area (SECA). We focus here on the southern Pacific coast. The 

methodology presented here is consistent with an approach developed by the Office of 

Transportation and Air Quality (OTAQ) of the U.S. Environmental Protection Agency 

(EPA) which included input from EPA regional modelers, and staff from the U.S. Navy. 

We first describe the overall modeling approach including the fate and transport 

model, CALPUFF, that will be used to simulate the transport, transformation and 

removal of pollutants over water and land. Then, we describe the selection of the model 

input data including meteorological data, SOx emissions and ship activity data. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-1 
2. AIR QUALITY MODELING APPROACH 

Air Quality Model 

For this screening study of the potential impacts of SOx emissions from ships at 

sea, we will use the CALPUFF model (Scire et al., 2000a, 2000b). CALPUFF is a nonsteady-state puff dispersion model that can simulate the effects of time- and spacevarying meteorological conditions on pollutant transport, transformation, and removal. 

The rationale for selecting CALPUFF was described in the Task 1 report (Seigneur et al., 

2005). 

The recommended meteorological inputs for applying CALPUFF are the timedependent outputs of CALMET, a meteorological model that contains a diagnostic wind 

field module and overwater and overland boundary layer modules. Optionally, 

CALMET can use the outputs of prognostic meteorological models, such as MM5 and 

CSUMM, to create the meteorological fields required by CALPUFF. The preparation of 

the meteorological data inputs for CALPUFF for this study is described in Section 3. 

CALPUFF includes algorithms for near-source effects such as building 

downwash, transitional plume rise, partial plume penetration, sub-grid scale terrain 

interactions as well as longer range effects such as pollutant removal due to wet and dry 

deposition, simplified chemical transformations, vertical wind shear, overwater transport 

and coastal interaction effects. Because the latter features are relevant to simulating the 

transport and chemistry of SOx emissions from ships, they will all be activated for our 

study. 

CALPUFF offers several options to simulate the formation of secondary sulfate 

and nitrate particles from the oxidation of the emitted primary gaseous pollutants, SO2 

and NOx respectively. Since the oxidation of SO2 to sulfate is of interest for this study, 

we will select the more advanced chemistry module available in CALPUFF which is 

based on the RIVAD/ARM3 chemical mechanism (Morris et al., 1988). The limitations 

of this chemistry module were discussed in the Task 1 report (Seigneur et al., 2005). 

Modeling Domain 

The modeling domain for the southern Pacific coast will extend from about 32 

degrees North to 36 degrees North and will, therefore, cover southern California. 

(Northern California will be grouped with Oregon and Washington, i.e., from 36 degrees 

North to 50 degrees North, to constitute the modeling domain for the northern Pacific 

coast.) The modeling domain will extend 240 km (150 miles) inland to allow enough 

distance to assess the potential air quality impacts of emissions from ships at sea. It will 

extend over water at a distance from the coast that corresponds to air quality impacts 

below the target concentration at all receptors. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-2 
Physiographic data (coastline and terrain elevation) will be obtained from the U.S. 

Geological Survey. 

Receptors 

Receptors will be located on land as follows. A line of receptors will be located 

at the coastline, 10 km apart. Such a distance provides a finer spatial resolution than that 

of the ship emissions along the coast (see Section 5). Inland receptors will then be 

located eastward at 10, 10, 20, 20, 30, 30, 40, 40 and 40 km apart from each other, i.e., up 

to 240 km (150 miles) from the coastline; there will, therefore, be 10 lines of receptors 

from the coast (included) up to 240 km inland. All receptors will be located at ground 

level. The total number of receptors is, therefore, estimated to be on the order of 500. 

Sources 

Ship emissions will be represented by a set of stationary point sources. Each 

point source will represent a ship. They will be located at a selected distance from shore 

(see below) and apart at a distance to be defined based on ship traffic (see Section 5). 

The use of stationary sources to represent moving ships is an appropriate approximation 

for this screening modeling study, because using stationary sources will overestimate the 

downwind air quality impacts (emissions will be concentrated in specific locations rather 

than continuously distributed along the shipping lane, thereby leading to greater ambient 

air concentrations). 

We considered but rejected an alternative approach. The approach would treat 

each ship as an individual source and simulate its impact on air quality inland. Target 

concentrations would be calculated from individual ships at the coast (dockside mode) 

with the highest concentration obtained at each receptor being selected as the target 

concentration for that receptor. Then, the impacts of individual ships would be evaluated 

against those target concentrations. This alternative approach offers the advantage of 

providing more detailed information regarding the impacts from ships since it addresses 

individual ships rather than a shipping lane; thus, different SECA distances could be 

identified in different parts of the domain. Such an approach requires many more model 

simulations than the approach proposed here, however, and, therefore, could not be 

considered for this screening study. Also, comparing with the highest concentration 

obtained for that receptor does not account for variability of concentrations at receptors, 

and may result in an overestimation of the boundary distance. Nevertheless, we point out 

below how the variability of the SECA distance within the study domain will be 

addressed. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-3 
Modeling Approach 

Our modeling approach will consist of two phases. In the first phase, we will 

calculate, at each inland receptor, the target values for the SO2 and sulfate concentrations 

that correspond to emission from ships at dockside; i.e., those ships that are within the 

SECA and therefore must burn low sulfur fuel; i.e., 15,000 ppm). These will be annual 

average concentrations. (It is not necessary to calculate the light extinction coefficient 

because it will be proportional here to the sulfate concentration.) In the second phase, we 

will calculate the annual average values of the SO2 and sulfate concentrations 

corresponding to emissions from ships burning high sulfur fuel (i.e., 27,000 ppm) at 

various distances from the coast and will compare those values to the target values 

obtained in the first modeling phase. 

All simulations will be conducted for one year and we will calculate and use 

annual average values in our analysis. We propose to use 2002 as our reference year 

because it corresponds to the year that will be used for grid-based air quality modeling by 

the EPA Office of Air Quality Planning and Standards (OAQPS). 

For the first phase, we will locate the ships at the coastline (dockside mode). 

They will be distributed spatially according to their estimated density in a shipping lane 

(see Section 5). The SECA SOx emission rates will be used (see Section 4). We will 

calculate the annual SO2 and, sulfate concentrations at each receptor. These values will 

be defined as the target values that will be used as benchmarks for the Phase 2 modeling. 

For the second phase, we will locate the ships at various distances from the 

coastline. For a given modeling scenario, all ships will be at the same distance from the 

coastline; they will be distributed spatially according to their estimated density in a 

shipping lane (see Section 5), and for all modeling scenarios the number of dockside 

ships will equal the number of off-shore ships. The SOx emission rates outside of the 

SECA will be used (see Section 4). The objective is to determine a set of distances at 

which those ship emissions will lead to air quality impacts that are less than or equal to 

the target values calculated in Phase 1 for the following percents of onshore receptors: 

50, 60, 70, 80, and 90. To that end, we will conduct CALPUFF annual simulations for 

various distances from the coastline. We will start with a 100 km distance, and receptor 

percentage of 50. If the modeling results show air quality impacts lower than the target 

values, at 50 percent or more of the onshore receptors we will then use a shorter distance 

(50 km). Conversely, if the modeling results show air quality impacts greater than the 

target values at 50 percent or more of the onshore receptors, we will use a greater 

distance (200 km). This process will be repeated until we identify the distance of interest 

(i.e., the distance where air quality impacts are commensurate with the target values). 

For example, if the modeling results conducted for a distance of 50 km show air quality 

impacts lower than the target values, for at least 50 percent of the onshore receptors, we 

will next use a shorter distance (20 or 30 km). If those modeling results show air quality 

impacts greater than the target values for at least 50 percent of the onshore receptors, we 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-4 
will then use a greater distance (70 or 80 km). We will stop when we have identified a 

distance that leads to air quality impacts commensurate with the target values. This 

process will be repeated for the other percentages of onshore receptors (60, 70, 80 and 

90). For all percentages, a tolerance of plus/minus 2 percent will be used. We propose to 

use a resolution of 10 km (i.e., we will not refine those distances within less than 10 km 

increments). 

The criterion of percentages of onshore receptors is used as an initial 

investigation. As we approach the distance of interest, some receptors will show values 

greater than the target values whereas other receptors may show values lower than the 

target values. The distribution of these receptors is significant. For example, by 

definition, fewer receptors have concentrations in excess of target concentrations at the 

60% level than 50%. But if the receptors in excess of the target concentrations at both 

the 50 and 60% levels are located say, within 10 km of the coastline, then even at the 

greater distances comparable levels of population may still be exposed to concentrations 

greater than target levels. In this example, the distribution may indicate that a greater 

distance should be considered. Therefore, evaluation of these various distances will be 

conducted by the modeling review team as part of the Task 3 analysis. 

Another reason for using the criterion of percentages of onshore receptors is that 

SO2 and sulfate concentrations will display different behaviors downwind of the ships. 

SO2 concentrations will decrease continuously with distance from the source (due to 

dilution, removal, and conversion to sulfate), whereas sulfate concentrations will first 

decrease (dilution and removal of primary, i.e., directly emitted sulfate), then increase 

(formation of secondary sulfate from the oxidation of SO2) before finally decreasing 

(dilution and removal exceeding formation). 

This behavior of sulfate introduces an additional complication: the sulfate target 

values at receptors near the coastline will be determined by the directly emitted sulfate, 

while the target values at larger distances inland will be determined by some combination 

of primary and secondary sulfate, with the secondary sulfate component increasing and 

the primary sulfate component decreasing. Even further inland, both components will 

decrease as the rate of dilution and removal exceeds the formation of sulfate. 

To understand how this complex behavior of sulfate may impact the analysis, let 

us consider the extreme case of no primary sulfate, i.e., all the SOx is emitted as SO2. In 

this case, the target sulfate values next to the coastline will be negligible because there 

will be minimal time for conversion of SO2 to sulfate. However, there will be some 

plume travel time for emissions from ships at sea that will allow some conversion of SO2 

to sulfate. Consequently, it may be impossible in this extreme case to meet target values 

at the coastline receptors unless a very large SECA is defined. 

Therefore, it is possible that all sulfate concentrations may not fall below the 

target values as we approach the distance of interest for the SECA. Accordingly, we will 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-5 
need to report the results in terms of the fraction (or percentage) of receptors that exceed 

the target values for each pollutant. 

We will report the results for each distance in terms of maximum concentration, 

average concentration and fraction of receptors above the target value for SO2 and for 

sulfate (all values will be for receptors over land). If significant differences appear for 

different areas of the study domain (e.g., one area shows impacts above target 

concentrations for at least 50 percent of the onshore receptors for a shorter distance than 

another area), we will identify those differences and discuss whether they suggest the 

need for some variability for the SECA distance within the study domain. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-6 
3. METEOROLOGICAL DATA 

CALMET is the companion meteorological model that is used to prepare the 

meteorological fields used by CALPUFF. 

A weakness of CALMET has recently been identified (Wheeler, 2005). 

CALMET does not correctly handle cases of unstable convective atmospheric conditions 

over water (when water temperature is warm and air temperature is cold, for example) 

because it assumes near-neutral conditions over water. Consequently, the mixing height 

is calculated based on a neutral mixing relationship and, under conditions of light wind 

speeds when the mechanical mixing heights are small, CALMET underpredicts the actual 

mixing height. This weakness can be an issue in areas where warm water temperatures 

are possible, such as the Gulf of Mexico, the southern Pacific coast and the southern 

Atlantic coast. Therefore, we address this potential issue here as it is important for this 

area as well as for subsequent modeling areas. Based on our discussion with the 

CALMET developer, EarthTech (Scire, 2005), we will circumvent this potential problem 

by inputting measured or modeled mixing heights directly into CALMET. For the 

southern Pacific coast, no upper air measurements are available over water and we will, 

therefore, use modeled mixing heights, as described below. 

Meteorological data are necessary to run an air dispersion model. For the 

CALPUFF model, the meteorological input data must first be formatted by the CALMET 

pre-processor. CALPUFF requires standard surface and upper air meteorological data. 

CALMET also has an overwater option that allows the use of special overwater 

measurements for grid cells that are over the ocean. The data required for the overwater 

option are: air-sea temperature difference, air temperature, relative humidity, wind speed 

and wind direction. Two optional measurements, overwater mixing height and overwater 

temperature gradients, may be supplied if available. If the optional parameters are not 

supplied, CALMET uses default values. We propose to supply temperature gradients 

obtained from the outputs of a prognostic meteorological model (see below). 

Land-based Measurements 

Land-based meteorological measurements are required for both surface and upper 

air observations above land portions of the domain. The data required are standard 

format data from the National Climatic Data Center (NCDC) (Scire et al., 2000b). 

The upper air data required are standard NCDC format TD6201 radiosonde data 

including pressure, elevation, temperature, wind direction, and wind speed for each 

sounding level. There are four upper air stations that are located within the modeling 

domain: 

• San Nicolas Island (33.25 degrees North, -199.45 degrees West) 

• Miramar (32.87 degrees North, -117.15 degrees West) 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-7 
• Point Mugu (34.10 degrees North, -119.12 degrees West) 

• Vandenberg (34.67 degrees North, -120.58 degrees West) 

The surface observations that are needed are provided in the NCDC Integrated 

Surface Hourly Observations. These include wind speed, wind direction, temperature, 

and dew point temperature. There are many surface stations within the modeling domain 

(255 for the state of California). 

Overwater Measurements 

The required CALMET parameters are all available for the Pacific Ocean near the 

U.S. coastline from the National Data Buoy Center (NDBC) (NDBC, 2005). The 

measurements are taken from buoys. The buoys are at varying distances from the coast. 

Those near the coast are frequently near harbors or bays. Most of the buoys are owned 

and operated by NDBC but there are also several other agencies that submit their data to 

the NDBC database. Though the coverage is not uniform, there is a fairly comprehensive 

coverage for the southern Pacific coast. Figure 3-1 shows the locations of the NDBC 

buoys as well as those that are run by other agencies and are included in the NDBC 

database. 

Model Outputs 

The outputs of meteorological models can be used, particularly in cases where 

there are insufficient meteorological observations. This is the case for upper air data over 

water in the Pacific Ocean. Examples of model outputs that could be used as surrogates 

for upper air data include those from the 2001 or 2002 MM5 simulations sponsored by 

EPA, those from the NCEP/NCAR reanalysis project and those from the Advanced 

Climate Modeling and Environmental Simulations (ACMES) database. 

CALMET can take as input the output of MM5. It can also combine MM5 output 

with observations. An interface program (CALMM5) converts the MM5 data into a form 

compatible with CALMET. A new version of this processor has been added to the 

CALPUFF-CALMET Download BETA-Test page recently (May 25, 2005). This beta 

version (not yet officially approved by the EPA) of CALMM5 processes MM5 Version 3 

output data directly. Using the output of another meteorological model (e.g., ACMES) 

would require the development of a new CALMET pre-processor that would be outside 

the scope of this project. Therefore, we will use the MM5 output for this application. 

Another advantage of using the MM5 outputs is that it will provide consistency with the 

subsequent grid-based modeling that will be conducted by OAQPS using the Community 

Multiscale Air Quality model (CMAQ), because CMAQ will be driven with the MM5 

meteorology. 

The MM5 modeling domain covers the entire contiguous United States and 

extends significantly over the oceans. For the southern Pacific coast domain, it extends 

at least 400 to 900 km westward from the coast. Therefore, it will cover the CALPUFF 

modeling domain needed to address the SECA. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-8 
Figure 3-1. NDBC buoys along the southern California coastline 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-9 
Summary 

We will use a combination of MM5 model output, surface observations over 

water from the NDBC database, surface observations over land from the NCDC database 

and upper air observations over land from four stations from the NCDC database. These 

data will be processed by CALMET to prepare a three-dimensional meteorological data 

set for CALPUFF. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-10 
 4. SOx EMISSIONS 

Emission factors are needed to estimate the emissions of SOx (gas-phase SO2 and 

particulate-phase sulfate) associated with various ship activities. Based on the review of 

available emission factors of Seigneur et al. (2005), the most recent EPA emission factors 

were selected (EPA, 2002). Those emission factors pertain to ships with engines with 

displacement exceeding 30 liters (so-called Category 3 engines). 

Emission factors are reported for three different engine types (slow speed, 

medium speed and steam boiler) for transit modes and hoteling modes. For this study of 

ships at sea, we are interested in medium speeds for transit modes. 

The SO2 emission factor per unit of work is reported to be 9.56 g/hp-h for a 3% 

sulfur fuel (i.e., 30,000 ppm) for a ship at slow or medium speed in transit mode. This is 

equivalent to 12.8 g/kW-h. 

For a ship within the SECA, a fuel sulfur content of 15,000 ppm will be assumed. 

Therefore, the emission factor will be 6.4 g/kW-h. 

For a ship at sea outside of the SECA, a fuel sulfur content of 27,000 ppm will be 

assumed. Therefore, the emission factor will be 11.52 g/kW-h. 

EPA assumes that 2% of sulfur is emitted as primary sulfate PM from Category 3 

marine diesel engines. Therefore, we treat 2% of total sulfur emissions as sulfate 

emissions and the SO2 emission factor is adjusted down accordingly to maintain the 

sulfur mass balance. (Note that for the same amount of S, the sulfate emission factor is 

1.5 the SO2 emission factor to account for the different molecular weights.) 

Therefore, within the SECA, the gas-phase SO2 and particulate-phase sulfate 

emission factors will be 6.27 g/kW-h and 0.19 g/kW-h, respectively. Outside of the 

SECA, the gas-phase SO2 and particulate-phase sulfate emission factors will be 11.29 

g/kW-h and 0.35 g/kW-h, respectively. 

The sulfate emission rates calculated above are consistent with available data on 

the sulfate fraction of particulate matter (PM) emitted from ship diesel engines. Fleischer 

et al. report that 20 to 30% of PM emissions from ship diesel engines are sulfate (for a 

3% sulfur fuel content). The EPA (2002) emission factor for PM is 1.3 g/hp-h, i.e., 1.74 

g/kW-h. These values lead to an emission factor for sulfate in the range of 0.31 to 0.47 

g/kW-h for a sulfur fuel content of 27,000 ppm. The emission factor of 0.35 g/kW-h 

calculated above falls within this range. 

Based on data from Corbett and Koehler (2003), the power of a typical ship was 

estimated to be 16,000 kW (Corbett, 2005). It should be noted that there is a wide range 

of power among various ships, with the largest container ships having power exceeding 

65,000 kW. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-11
The gas-phase SO2 and particulate-phase sulfate emissions per ship are then 

calculated to be 100,320 g/h and 3,040 g/h, respectively, within the SECA and 180,640 

g/h and 5,600 g/h, respectively, outside the SECA. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-12 
5. SHIP ACTIVITY DATA 

Ship activity data must be estimated so that the density of ships within the 

modeling domain can be calculated. Knowing the average number, N, of ships in transit 

along the southern Pacific coast per year and assuming an average cruising speed, V 

(km/h), we can calculate the average distance, D (km), between two ships along a 

shipping lane. 

D = V * (24 h/day * 365 days/yr) / N 

The annual number of ships transiting along the southern California coast was 

estimated to be 13,000 (ICOADS, 2002). This number includes all ships transiting to and 

from ports located on the southern Pacific coast as well as ships transiting 

southward/northward from/to ports located on the northern Pacific coast. It is likely to be 

an overestimate of the number of ships transiting along the coast because a fraction of 

those ships will be transiting along shipping lanes that extend from the ports westward 

into the Pacific Ocean. The cruising speed varies according to ship type. It is about 24 

knots for container ships and about 16 knots for tankers. Here, the average ship cruising 

speed was estimated to be about 20 knots, i.e., 36 km/h (ICOADS, 2002). Thus, the 

average distance is estimated for the southern Pacific coast as follows. 

D = 36 * 24 * 365 / 13,000 = 24.3 km 

Based on this analysis, we propose to use a distance of 25 km between ships to 

calculate ship emissions. 

Modeling Sulfur Oxides (SOx) Emissions Transport From Ships At Sea B-13 
6. REFERENCES 

Corbett, J.J. and H.W. Koehler, 2003. Updated emissions from ocean shipping, J. 

Geophys. Res., 108, doi:10.1029/2003JD003751. 

Corbett, J.J., 2005. Private communication to Christian Seigneur, AER, July 2005. 

EPA, 2002. Commercial Marine Emission Inventory, Final Report from PECHAN, 

prepared by ENVIRON International Corporation, U.S. Environmental Protection 

Agency, Office of Transportation and Air Quality, Ann Arbor, MI. 

Fleischer, F., E.J. Ulrich, R. Krapp and W. Grundmann. Comments on particulate 

emissions from diesel engines when burning heavy fuels. 

. 

ICOADS, 2002. International Comprehensive Ocean Atmospheric Data Set, as 

transmitted from ERG by Office of Transportation and Air Quality, U.S. 

Environmental Protection Agency, Washington, D.C. 

Morris, R.E., R.C. Kessler, S.G. Douglas, K.R. Styles and G.E. Moore, 1988. Rocky 

Mountain Acid Deposition Model Assessment: Acid Rain Mountain Mesoscale 

Model (ARM3), Report prepared for the U.S. EPA, Research Triangle Park, NC. 

Scire, J.S., D.G. Strimaitis and R.J. Yamartino, 2000a. A User’s Guide for the CALPUFF 

Dispersion Model (Version 5), Earth Tech, Inc. Report, Concord, MA, January 

2000. 

Scire, J.S., F.R. Robe, M.E. Fernau and R.J. Yamartino, 2000b. A User’s Guide for the 

CALMET Dispersion Model (Version 5), Earth Tech, Inc. Report, Concord, MA, 

January 2000. 

Scire, J.S., 2005. Communication via e-mail of Christian Seigneur, AER, with Joe Scire, 

EarthTech, 18-19 March 2005. 

Seigneur, C. K. Lohman and P. Karamchandani, 2005. Review of Technical Information 

relevant to Sulfur Oxides (SOx) Emissions Transport for Ships at Sea, Final 

Report to Office of Transportation and Air Quality, U.S. Environmental 

Protection Agency, Washington, D.C. 

Wheeler, N., 2005. Private communication from Neil Wheeler, Sonoma Technology, 

Inc. to Christian Seigneur, AER, 14 March. 

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