United States Offlceof EPA-600/R-93~063
Environmental Protection Research and Development
Agency Washington, DC 20460 April 1993
* EPA Methodologies for Estimating
Air Emissions from Three
Non-Traditional Source
Categories:
Oil Spills,
Petroleum Vessel Loading
and Unloading, and Cooling
Towers
Joint
missions
LOl
^roup
Prepared for Office of Air Quality Planning and Standards
Prepared by Air and Energy Engineering Research Laboratory
-------
TECHNICAL REPORT DATA
(Please read Inilructions on the reverse before comple'
1. REPORT NO. 2.
EPA-600 /R-93-063
3 PB93-18159 2
4 title and subtitle Methodologies for Estimating Air
Emissions from Three Non-Traditional Source Cate-
gories: Gil Spills, Petroleum Vessel Loading and Un-
loading, and Cooling Towers
5. REPORT DATE
April 1993
6. PERFORMING ORGANIZATION CODE
7 AUTHOR(s) W. Ramadan, S. Sleva, K.Dufner, S. Snow
(TRC); S. Kersteter (Science Applications)
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Science Applications International Corporation
206 University Tower
3101 Petty Road
Durham. North Carolina 27707
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-D9-0173, Tasks 1/141,
2/206, 3/304
12. SPONSORING AGENCY NAME AND ADDRESS
EPA, Office of Research and Development
Air and Energy Engineering Research Laboratory
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
Task Final: 10/91 - 3/93
14. SPONSORING AGENCY CODE
EPA/600/13
is.supplementary notes ^EERL project officer is E. Sue Kimbrough, Mail Drop 62, 919/
541-2612. (*)TRC Environmental Corp., 100 Europa Dr. , Suite 150, Chapel Hill, NC
27514. -
16 ABSTRACT
The report discusses part of EPA's program to identify and characterize
emissions sources not currently accounted for by either the existing Aerometric In-
formation Retrieval System (AIRS) or State Implementation Plan (SIP) area source
methodologies and to develop appropriate emissions estimation methodologies and
emission factors for a group of these source categories. Based on the results of the
identification and characterization portions of this research, three source categories
were selected for methodology and emission factor development: oil spills, petroleum
vessel loading and unloading, and cooling towers. The report describes the category
selection process and presents emissions estimation methodologies and emission fac-
tor data for the selected source categories. The discussions for each category inc-
lude general background information, emissions generation activities, pollutants
emitted, sources of activity and pollutant data, emissions estimation methodologies,
and data issues. The information used in these discussions was derived from various
sources including available literature, industrial and trade association publications
and contracts, experts on the category and activity, and knowledgeable federal and
state personnel.
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. cosati Field/Group
Pollution Cooling Towers
Emission
Estimating
Tanker Ships
Loading
Unloading
Pollution Control
Stationary Sources
Oil Spills
13B 13A, 131
14G
13J
13H
18. DISTRIBUTION STATEMENT
Release to Public
19. SECURITY CLASS (This Report)'
Unclassified
21. NO. OF PAGES
116
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73) C~ 7
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EPA REVIEW NOTICE
This report has been reviewed by the U.S. Environmental Protection Agency, and
approved for publication. Approval does not signify that the contents necessarily
reflect the views and policy of the Agency, nor does mention of trade names or
commercial products constitute endorsement or recommendation for use.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
A
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EPA-600/R-93-063
April 1993
METHODOLOGIES FOR ESTIMATING AIR EMISSIONS FROM THREE
NON-TRADITIONAL SOURCE CATEGORIES: OIL SPILLS,
PETROLEUM VESSEL LOADING AND UNLOADING,
AND COOLING TOWERS
FINAL REPORT
Prepared by
Walid Ramadan
Stanley Sleva
Ken Dufner
Scott Snow
TRC Environmental Corporation
100 Europa Drive, Suite 150
Chapel Hill, NC 27514
and
Sharon L. Kersteter
Southern Research Institute
801 Capitola Drive, Suite 12
Durham, NC 27713
EPA Contract No. 68-D9-0173
Work Assignment Nos. 1/141, 2/206, and 3/304
EPA Project Officer: E. Sue Kimbrough
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
Prepared for:
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
(CH-93-12)
-------
ABSTRACT
This report presents the results of work completed under Work Assignment Nos.
1/141, 2/206, and 3/304 under EPA Contract No. 68-D9-0173. This work is part of EPA's
program to identify and characterize emissions sources not currently accounted for by either
the existing AIRS or SIP area source methodologies and to develop appropriate emissions
estimation methodologies and emission factors for a group of these source categories. Based
on the results of the identification and characterization portions of this research, three source
categories were selected for methodology and emission factor development: oil spills,
petroleum vessel loading and unloading, and cooling towers. This report describes the
category selection process and presents emissions estimation methodologies and emission
factor data for the selected source categories.
The discussions for each selected category include general background information,
emissions generation activities, pollutants emitted, sources of activity and pollutant data,
emissions estimation methodologies, and data issues. The information used in these
discussions was derived from various sources including available literature, industrial and
trade association publications and contracts, experts on the category and activity, and
knowledgeable federal and state personnel.
li
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TABLE OF CONTENTS
Section Page
Abstract ii
List of Tables v
List of Figures v
List of Acronyms vi
Conversion Factors vii
1 INTRODUCTION 1-1
BACKGROUND 1-1
PURPOSE OF THE WORK ASSIGNMENT 1-2
CONTENTS 1-2
2 CATEGORY SELECTION 2-1
BACKGROUND 2-1
RANKING PROCESS 2-2
National Versus Regional Importance (N) 2-3
Emissions Magnitude (E) 2-3
Pollutant Rank/Program Requirement (P) 2-5
Potential for Methodology Development (M) 2-7
Weighting Factors 2-7
RESULTS OF THE RANKING PROCESS 2-8
SOURCE SELECTION 2-10
3 OIL SPILLS 3-1
BACKGROUND 3-1
EMISSIONS GENERATION 3-2
Activities 3-2
Pollutants 3-2
SOURCES OF DATA 3-2
Activities 3-2
Pollutants 3-4
METHODOLOGIES 3-4
Method I 3-5
Method II 3-31
Method III 3-32
DATA ISSUES 3-34
REFERENCES 3-42
4 PETROLEUM VESSEL LOADING AND UNLOADING 4-1
BACKGROUND 4-1
EMISSIONS GENERATION 4-2
Activities 4-2
Pollutants 4-4
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TABLE OF CONTENTS
Section
Page
SOURCES OF DATA 4-5
Activity 4-5
Emission Factors 4-8
METHODOLOGIES 4-13
Method I 4-14
Method D 4-18
DATA ISSUES 4-18
REFERENCES 4-20
5 COOLING TOWERS 5-1
BACKGROUND 5-1
Cooling Tower Design and Operation 5-2
HVAC and Refrigeration Systems 5-3
EMISSIONS GENERATION 5-6
Activities 5-6
Pollutants 5-8
SOURCES OF DATA 5-9
Activities 5-9
Pollutants 5-9
METHODOLOGIES 5-10
Industrial Cooling Towers 5-10
Comfort Cooling Towers 5-11
DATA ISSUES 5-15
REFERENCES 5-17
APPENDIX A DERIVATION OF OIL SPILLS METHODOLOGY FOR GASOLINE
AND DIESEL FUEL A-l
APPENDIX B NO AND NOx EMISSION FACTOR DERIVATION B-l
APPENDIX C LEVEL OF DETAIL OF PETROLEUM VESSEL LOADING AND
UNLOADING DATA C-l
IV
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LIST OF TABLES
Number Page
2-1 PREVIOUSLY UNENVENTORIED AREA SOURCE CATEGORY
SCENARIO SUMMARY 2-9
3-1 VOLUME FRACTION EVAPORATED EXAMPLE FOR CRUDE OIL 3-15
3-2 SMOKE YIELD WITH VARIOUS POOL DEPTHS 3-24
3-3 SMOKE YIELDS WITH VARIOUS POOL DIAMETERS AND OIL TYPES . . 3-24
3-4 ADDITIONAL COMBUSTION EMISSIONS INFORMATION 3-25
3-5 CRUDE OIL SPILL HISTORICAL DATA 3-33
3-6 OIL INDUSTRY OUTLOOK INDICATORS 3-37
4-1 SUMMARY OF AP-42 EMISSION FACTORS 4-9
4-2 CARB EMISSION FACTORS 4-12
4-3 SCOTT ENVIRONMENTAL TECHNOLOGY EMISSION FACTORS LOADING/
BALLAST EMISSIONS 4-12
4-4 CALCULATIONS OF STATE-LEVEL VESSEL EMISSIONS 4-15
4-5 CALCULATIONS OF TOTAL VESSEL EMISSIONS 4-17
5-1 STATE UTILIZATION RATES 5-13
LIST OF FIGURES
2-1 Emissions magnitude matrix 2-4
2-2 Pollutant/program requirement matrix 2-6
3-1 Evaporation curve for Norman Wells crude oil at 22°C (72°F) 3-12
3-2 Evaporation curve for crude oil 3-16
3-3 Evaporation curve for gasoline 3-17
3-4 Evaporation curve for diesel fuel 3-18
3-5 Relationship of liquid burning rates at large tray diameters to ratio of heat of
combustion to heat of vaporization 3-28
3-6 Crude oil spill sources - minor and medium 3-35
3-7 Crude oil spill sources - major and combined 3-36
3-8 Major domestic petroleum transport . . . : 3-38
3-9 U.S. refineries operating level 3-39
5-1 Crossflow and counterflow cooling towers 5-4
5-2 Designs of various drift eliminators 5-5
CH-93-I2
V
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LIST OF ACRONYMS
AFS
AIRS Facility Subsystem
AIRS
Aerometric Information Retrieval System
AMS
Area and Mobile Source Subsystem
CAAA
Clean Air Act Amendments
CARB
California Air Resources Board
CCT
Comfort cooling tower
CERCLA
Comprehensive Environmental Response, Compensation and Liability
Act
CO
carbon monoxide
co2
carbon dioxide
CTI
Cooling Tower Institute
CWA
Clean Water Act
DOT
U.S. Department of Transportation
DWT
Deadweight Tons
EF
Emission Factor
EIA
Energy Information Administration
EPA
U.S. Environmental Protection Agency
ERNS
Emergency Response and Notification System
HVAC
Heating, ventilation, and air conditioning
IPCT
Industrial process cooling tower
JEIOG
Joint Emission Inventory Oversight Group
MARAD
Maritime Administration
NADB
U.S. EPA, National Air Data Branch
NAPAP
National Acid Precipitation Assessment Program
NEDS
National Emissions Data System
NO
Nitrogen Oxide
NOx
oxides of nitrogen
NPC
National Petroleum Council
NRC
National Response Center
PAD
Petroleum Administration for Defense
PM
particulate matter
PM-10
particulate matter less than ten fim in diameter
RVP
Reid Vapor Pressure
see
source classification code
SIC
Standard Industrial Classification
SIP
State implementation plan
so2
sulfur dioxide
TPY
tons per year
TSP
total suspended particulate
USCG
U.S. Coast Guard
VOC
volatile organic compound(s)
WOGA
Western Oil and Gas Association
vi
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CONVERSION FACTORS
To Convert From
To
Multiply By
Barrel (bbl)
Liter (1)
159
Barrel (bbl) - petroleum*
Gallon (gal)
42
Centigrade
Fahrenheit
(°C+32) 9/5
Fahrenheit
Centigrade
(°F-32) 5/9
Gallon (gal)
Liter (1)
3.785
Inch (in)
Centimeter (cm)
2.54
Pound (lb)
Kilogram (kg)
0.45
Square foot (ft2)
Square meter (m2)
0.0929
*42 gal/bbl is the standard as used in the oil industry. For other industries, different galions/bbi apply.
"Typical value based on common boiler design parameters. Value will vary depending upon steam temperature and
pressure.
vii
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SECTION 1
INTRODUCTION
BACKGROUND
Area source emissions of particulate matter (PM or TSP), sulfur dioxide (S02), oxides of
nitrogen (NOx), reactive volatile organic compounds (VOC) and carbon monoxide (CO) are
estimated annually by the National Air Data Branch (NADB) of the U.S. Environmental
Protection Agency (EPA). Area sources are typically aggregations of individual sources that are
too small to be defined as point sources in a specific geographic area. Area sources usually
include all mobile sources and any stationary sources that are too small, difficult, or numerous
to be inventoried as point sources. The National Emissions Data System (NEDS) is the data
management and processing system that has historically been used to maintain these annual
emissions data. The statutory requirement for annual inventories defines an area source as an
anthropogenic mobile or stationary source that emits less than 100 tons per year (TPY) of TSP,
S02, NOx or VOC, or 1,000 TPY of CO.
The original NEDS area source methodology and algorithms were developed in 1973 and
1974 using 1960 census data (e.g., population, housing, manufacturing). The NEDS methodology
has remained relatively unchanged over the past 17 years and forms the basis for the Aerometric
Information Retrieval System/Area and Mobile Source Subsystem (AIRS/AMS) methods. The
Joint Emissions Inventory Oversight Group (JEIOG) is currently updating and revising emission
estimation methods using more recent data. In addition, JEIOG is involved in the development
of new emission estimation methodologies. This project has been one of the on-going JEIOG
projects relating to the development of new emission estimation methodologies.
While emissions sources included in current inventory methodologies do cover a large
portion of anthropogenic emissions, many small source categories are not included in the
inventory. Identification, characterization and inclusion of these categories and their emissions
in the inventory will result in a more thorough and complete emissions inventory.
CH-93-12
1-1
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PURPOSE OF THE WORK ASSIGNMENT
The purposes of Work Assignment Nos. 1/141, 2/206, and 3/304 were to identify and
characterize emissions sources not accounted for in the NEDS area source and AIRS/AMS
methodologies. These "missing" or non-traditional sources will be assessed as to their importance
and how their emissions can be included in the inventory. For the purposes of these work
assignments, a non-traditional or "missing" source category is defined as a category that does not
explicitly appear on the NEDS area source category list. Three source categories were selected
for methodology and emission factor development: oil spills, petroleum vessel loading and
unloading, and cooling towers.
CONTENTS
Section 2 of this report describes the category selection process. Sections 3, 4 and 5
present information collected and methodologies developed for oil spills, petroleum vessel loading
and unloading and cooling towers, respectively. References for all information cited in a section
are given at the end of the section. Appendix A presents a derivation of an oil spills
methodology to be used with gasoline and diesel fuel. Appendix B lists NO and NOx emission
factor derivations. Appendix C shows the level of detail of petroleum vessel loading and
unloading data.
CH-93-12
1-2
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SECTION 2
CATEGORY SELECTION
BACKGROUND
Several previous work assignments under Contract No. 68-D9-0173 identified (Phase I,
WA No. 0/107), characterized (Phase n, WA Nos. 0/113 and 1/101), and prioritized (Phase III
WA No. 1/101) emissions sources not currently accounted for by either the existing NEDS or
State implementation plan (SIP) area source methodologies. Of the approximately 200 source
categories identified, 70 were characterized and prioritized. To the extent possible, these 70
categories were characterized in the following areas:
• Definition/description of the category and activity
• Process breakdown (if applicable)
• Importance of the category (i.e., reason for considering the category)
• Pollutant emitted
• Estimate of the pollutant levels
• Point/area source cutoff
• Level of detail of available information
• Level of detail required by users
• Emission factor requirements
• Regional, seasonal, or temporal characteristics
• Urban or rural characteristics
• Potential methodology
• References
In the ranking scheme developed under Work Assignment No. 1/101, the characterizations
were carefully reviewed and the sources were prioritized using the following criteria: national
versus regional importance; emissions magnitude; pollutant ranking; EPA program requirements;
and potential for methodology development. Worksheets were developed for use with the
CH-93-12
2-1
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ranking algorithm and a computerized database system was designed to assist the ranking process.
EPA review comments were used to revise the algorithm.
RANKING PROCESS
Five criteria were developed to prioritize or rank the source categories: national versus
regional importance; emissions magnitude (i.e., contribution of emissions by category to the
national total); pollutant [e.g., VOC, TSP and PM less than 10 microns in diameter (PM-10), CO,
NOx, S02,]; EPA program requirements (e.g., SIP, Clean Air Act, Air Toxics, Global
Climate/Greenhouse Gases, etc.); and potential for methodology development (i.e., difficulty and
duration of emission estimation methodology development). These criteria were then used to
develop an algorithm to rank the missing or previously uninventoried source categories for future
development of emissions estimates and methodologies. The algorithm was designed for use
either within a single program (e.g., SIP methodology development) or across programs.
In the ranking algorithm, the five criteria are incorporated into four variables. The
algorithm shown below has a flexible structure to accommodate both new source categories and
changes in ranking criteria. The four variables (referred to as ranks), each having a weighting
factor (wfx), are assigned values and summed to produce an overall score. If the four variables
are believed to be of equal value, the weighting factors can be dropped.
Overall Score = (N*wfn) + (E*wfe) + (P*wfp) + (M*wfm) (1)
where, N = National or regional importance rank
E = Emissions magnitude rank
P = Ranking factor based on pollutant(s) emitted
and EPA program requirements
M = Potential for methodology development rank
wfx = Weighting factor for each term
As indicated, the five criteria were incorporated into four variables in the algorithm.
These variables are discussed in detail in the following sections. The pollutant and EPA program
CH-93-12 2-2
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requirement criteria have been merged into a single term (P). The combination of these criteria
reflects the pollutant-specific nature of many EPA programs.
Each variable was assigned a ranking value from one (low importance) to five (high
importance). The numeric value of each term (i.e., the rank) was based on the characteristics of
the source category using the methodology presented in this report. The four variables were also
weighted to express the priority of each term. The weighting factors indicated the priorities of
the project team and are, therefore, somewhat subjective. These weighting factors can be
changed to reflect other users and priorities. Applying the algorithm produces a numeric score
that can be used to rank the categories relative to one another. Each of the ranking variables is
discussed in the following sections.
National Versus Regional Importance (N)
This variable refers to the geographic distribution of a source category. National sources
are distributed across most of the country and are considered the highest priority (five). The
ranking for each potential geographic distribution is as follows:
• 5 - Source is nationally distributed. Category is a significant emissions source in most
states.
• 4 - Source affects at least one-half of the United States. Category is a significant
source in at least one-half, but not most, states.
• 3 - Significant source localized to one region or several states. Most emissions from
the category are in a single region or a group of states and it is an important emissions
source in these locations.
• 2 - Source affects one region or several states. Most emissions from the category are
in a single region or a group of states.
• 1 - Source affects one or a few states.
Emissions Magnitude (E)
The emissions magnitude term accounts for differences in emissions by using a matrix,
shown in Figure 2-1, to compare emissions from the sources to be ranked by pollutant. The
CH-93-12
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i
I
%
i
method is most effective when a group of categories is being evaluated, since it relies on
differences in emissions magnitudes to rank the categories, rather than an absolute emissions
scale. A ranking scheme based on an absolute scale, using national emissions data on existing
area source categories, was considered. However, it was decided that a comparative scale was
more useful for ranking the missing categories because it also allows the user to consider one or
any combination of pollutants and to differentiate between the missing source categories.
POLLUTANT
TS PI Air
S02 NOx CO C02 PM10 VOC CH4 Toxic CFC 03
100
T 1,000
P
Y 10,000
100,000
1,000,000
' Identify all applicable cells lor a source category; the value of E is defined by the
cell with the highest rank. The rank cannot exceed 5.
RANK*
Figure 2-1. Emissions magnitude matrix.
Under this scheme, the emissions of each pollutant in TPY from each category are
estimated from the source category characterizations and placed in the matrix. A category is
assigned one cell in the matrix for each pollutant emitted. Once all categories have been placed
in the matrix, each cell is assigned a rank. Each pollutant is appraised separately, that is, each
column is ranked individually with a pollutant-specific emissions magnitude rank. Under this
scheme, the categories with the greatest emissions of a pollutant are assigned a rank of five.
Categories with lower emissions magnitudes are assigned progressively lower ranks. The
distribution of categories by emissions magnitudes can be divided into five equal groups, from
highest to lowest The more categories that can be ranked, the better the opportunity to establish
a sufficiendy broad distribution to assign ranks one through five for each pollutant (column).
CH-93-12 2-4
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The pollutant-specific magnitude ranks (columns) for a category are then considered
together and the greatest single rank is assigned as the value of E for the category. This method
produces a pollutant-neutral assignment of this value (i.e., if the category is a comparatively large
source of any pollutant of concern, it is assigned a high rank). The computer program will allow
for one, several or all pollutants to be considered in the determination of E, according to the
user's needs. (The importance of the pollutant itself, rather than the emissions magnitude, is
considered in the next step.) As more categories are ranked and added to the matrix, E values
for previously evaluated categories may change.
Pollutant Rank/Program Requirement (P)
The rank for this variable is determined from a matrix combining a ranking for each
pollutant and for applicable program requirements. These two criteria are not independent and
have therefore been combined into a single term (P).
The method determines applicable programs on the basis of specific inclusion of the
source category in the program. The programs considered are current and proposed SEP
programs, sources specified in the Clean Air Act Amendments of 1990 (CAAA), Global Climate,
Air Toxics, Acid Rain, Occupational and Indoor Air Exposure and Other. SIP and CAAA
requirements have been combined as a single category to eliminate the potential for double
counting. Source categories to be ranked are assigned to all applicable programs based on review
and knowledge of the programs. However, the framework allows other EPA programs not listed
here to be included in the matrix at the user's discretion.
For each category, the applicable programs and pollutants are identified along each axis
of the matrix, as shown in Figure 2-2. Programs and pollutants were initially ranked separately
and assigned the values shown on the axes in the matrix. These ranks were based on the
importance of the programs and the pollutants as established by the project team. Each cell
located at the intersection of an applicable pollutant and program is an applicable cell. The value
for each cell is the product of the pollutant and program rankings defined along each axis. The
values from applicable cells are summed to yield a total score. Categories can be evaluated for
any combination of relevant programs and pollutants.
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EPA PROGRAM REQUIREMENT
X
5
4
3
2
2
- 1
Rank
POLLUTANT
SIP/
CAA
xy prod
Global
Climate
uct*
Air
Toxics
Occupational/
Acid Indoor Air
Rain Exposure Other
y
VOC
25
20
15
10
10
5
5
PM10/TSP
25
20
15
10
10
5
lis?
NOx
25
20
15
10
10
5
5
CO
25
20
15
10
10
5
W:s'
S02
20
16
12
8
8
4
m*.
Air Toxic
20
16
12
8
8
4
M4..
CH4
15
12
9
6
6
3
3
CFCs
15
12
9
6
6
3
3
C02
15
12
9
6
6
3
3
Ozone
10
8
6
4
4
2
2
Other
5
4
3
2
2
1
1
TOTAL **
* Each cell contains the product xy, the pollutant rank times the program
requirement rank.
* * Applicable matrix cells are based on the program requirements and pollutants.
Figure 2-2. Pollutant/program requirement matrix.
After the source categories are evaluated, the user determines the distribution of scores.
The categories are arranged from the highest to lowest scores and then divided into five groups.
If possible, each group should contain approximately the same number of categories. This
method is similar to the method used to determine the emissions magnitude rank. The categories
in each of the five groups are then assigned a rank from one to five, with the categories with the
highest scores receiving the highest ranks. As more source categories are characterized, the value
of P may change as the quintile ranks are recomputed.
Pollutant and program requirement rankings (the P matrix axes) were assigned based on
current estimates of their overall priority to the project team and are subject to revision. Other
groups could also alter these rankings to produce priority ranks according to their own
responsibilities and needs.
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Potential for Methodology Development (M)
This variable accounts for the estimated difficulty in developing an emissions estimation
methodology and, subsequently, a county-level emissions estimate as required for most inventory
applications. The ranks are based on information provided in the characterizations and are
subject to change with subsequent investigation. The ranking criteria for this variable are as
follows:
• 5 - Emission factors (EFs) are available or derivable from existing sources of data;
activity data are available and can be resolved to the county level.
• 4 - EFs are available or derivable from existing data sources; activity data are unknown
or difficult to collect, but a reasonable surrogate is available and EFs can be modified to
the surrogate.
• 3 - EFs are available; activity or surrogate data require extensive collection or existing
EFs require extensive modification to existing activity data.
• 2 - No EFs exist; activity or reasonable surrogate data are available.
• 1 - No EFs exist; no activity data or apparent method are available, based on current
information.
Although an objective standard has been defined to assign this rank, information in the
characterization will require that judgment be used to assess the difficulty of data collection and
the applicability of any existing emission factors prior to determining the rank. In some cases,
existing emission factors may be acceptable for some of the pollutants emitted from a source, but
incomplete for other pollutants. In these cases, the user must judge the significance of the
available emission factors in comparison to unavailable emission factors prior to assigning the
rank.
Weighting Factors
Each component of the algorithm is assigned a weighting factor that attempts to assess
the importance of each criterion to the ranking task. Six separate weighting scenarios were used
to rank the characterized source categories. The scenarios and their corresponding variable
CH-93-12
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weights are listed below. Scenario 0 represents the first ranking scenario used and is discussed
in detail in the report titled Ranking of Missing or Unaccounted for Area Sources (Missing
Sources Phase III) - Final Report (February 1991, WA No. 1/101, Contract No. 68-D9-0173).
Scenarios 1 through 5 were developed in April 1991 at the request of the EPA Project Officer
at that time, and the characterizations were reranked using these weighting scenarios. By using
different combinations of weighting factors (i.e., scenarios), the relative importance or
significance of each factor to the ranking process can be shown. The scenarios used in this
ranking process were weighted most heavily to E and P.
• Scenario 0
• Scenario 1
• Scenario 2
• Scenario 3
• Scenario 4
• Scenario 5
E = 35;
P = 35; N = 20; M = 10
E = 75;
P = 15; N = 5; M = 5
E = 75;
P = 25; N = 0; M = 0
E = 65;
P = 20; N = 5; M = 10
E = 50;
P = 50; N = 0; M = 0
E = 50;
P = 30; N = 10; M = 10
RESULTS OF THE RANKING PROCESS
Table 2-1 presents the results of the ranking process for the top 35 source categories. The
categories are listed from highest average rank to lowest. This table shows the ranking under
each scenario, the average rank, the maximum category rank (of the 35 categories), the minimum
rank (of the 35 categories) and the number of times the category was ranked among the top 10
categories (of the 35 categories).
The following source categories consistently appear among the top ten categories for all
the weighting factors scenarios: cigarette smoke; fireplaces; wood stoves; small electric utility
boilers; accidental/catastrophic releases; airport support vehicles; rocket launches and test firing;
mobile sources - evaporative and running losses; petroleum vessel loading and unloading;
charbroiling; cooling towers; inflight aircraft; pesticide application; and refrigeration - leaking
coolant. Three of these source categories ranked first (or tied for first) with a rank of 5.0 for all
weighting scenarios: cigarette smoke, fireplaces and wood stoves.
CH-93-12
2-8
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TABLE 2-1. PREVIOUSLY UMNVENTORIED AREA SOURCE
CATEGORY SCENARIO SUMMARY
RANK
AVG
MAX
MIN TIMES
—Scenario
RANK
RANK
RANK
IN
CATEGORY
0
1
2
3
4
5
TOP 10
1
Cigarette Smoke
5
5
5
5
5
5 I
5.00
1
1
5
1
Fireplaces
5
5
5
5
5
5
5.00
1
1
5
1
Wood stoves
5
5
5
5
5
5
5.00
1
1
5
4
Small Utility Boilers
4.8
4.9
5
5
5
4.8 :
4.92
t
4
5
5
Accidental/Catastrophic Releases
4.4
4.B5
5
5
5
4.7 ;
4.83
1
5
5
5
Airport Support Vehicles
4.4
4.85
5
5
5
4.7
4.83
1
5
5
7
Rocket Launching ar.d Testing
4.4
4.8
5
5
5
4.6
4.80
I
8
5
8
Mobile - Evap. and Running
4.65
4.85
4.75
4.75
4.5
4.7
4.70
5
8
5
9
Vessel Loading
4.35
4.75
4.75
4.75
4.5
4.5 ::
4.60
8
9
5
10
Char5roiling
4.25
4.75
4.75
4.75
4.5
4.5
4.58
8
9
5
10
Cooling Towers
4.25
4.75
4.75
4.75
4.5
4.5
4.58
8
9
5
10
Inflight Aircraft
4.25
4.75
4.75
4.75
4.5
4.5 ;
4.58
8
9
5
10
Pesticide Application
4.25
4.75
4.75
4.75
4.5
4.5 !'
4.58
3
9
5
10
Relrigeration - Leaking Coolant
4.25
4.75
4.75
4.75
4.5
4.5
4.58
8
g
5
15
Lawn Care
4.1
4.7
4.75
4.75
4.5
4.4
4.53
8
>10
2
16
Household Cleaners/Polishes
3.7
4.55
4.5
4.5
4
4.1
4.23
>10
>10
1
15
Oil Spills
4.05
4.1
4.25
4.25
4.5
4.2
4.23
8
>1C
¦
16
Personal Products
3.7
4.55
4.5
4.5
4
4.1
4.23
>10
>10
1
1 c
Waste Incin.: HW Devel. Tech.
4.05
4.1
4.25
4.25
4.5
4.2
4.23
8
>10
C
20
Tank... Cleaning
3.85
4.05
4.25
4.25
4.5
4.1
4.17
8
>10
0
21
Aircraft Refueling
4.1
4.05
4
4
A
4.1
4.04
>10
>10
A
V
22
Commercial Deep Fat Frying
3.9
4
4
4
4
4
3.98
>10
>10
0
22
Landfill Activities (TSP)
3.55
4.45
4.25
4.25
3.5
3.9
3.98
>",G
>10
0
22
Re'rigeration ... Equipment
3.9
4
4
4
4
4
3.98
>10
>10
c
22
Road Construction
3.55
4.45
4.25
4.25
3.5
3.9
3.98
>10
>10
0
22
Traffic Marking
3.55
4.45
4.25
4.25
3.5
3.9
3.98
>10
>10
0
22
Waste Oil Disposal
3.55
4.45
4.25
4.25
3.5
3.9
3.98
>10
>10
A
V
28
Farming
3.35
4.4
4.25
4.25
3.5
3.8
3.93
>10
>10
0
23
Grain Grinding
3.35
4.4
4.25
4.25
3.5
3.8
3.93
>10
>10
v
23
UV/E^ectron Beam Coating
3.7
3.95
4
4
4
3.9
3.93
>1C
>10
A
V
31
Welding
3.15
4.35
4.25
4.25
3.5
3.7
3.87
>10
>10
c
32
Distilleries
3.6
4.4
4
4
3
3.8
3.80
>10
>10
0
33
Landfill Methane
3.4
4.35
4
4
3
3.7
3.74
>10
>10
0
33
Service Stations - Repair
3.75
3.9
3.75
3.75
3.5
3.8
3.74
>10
>10
r>
V
35
Auto Cleaners/Waxes/Polishes
3.55
3.85
3.75
3.75
3.5
3.7
3.68
>10
>10
0
35
EHV Transmission Lines
3.2
4.3
4
4
3
3.6
3.68
>10
>10
0
35
Backyard Charcoal Grills
3.9
3.4
3.5
3.5
4
3.8
3.68
>10
>10
A
SCENARIOS/
E
P
N
M
SUM
VARIABLE WEIGHTS:
Scenario 0
35
35
20
10
100
Scenario 1
75
15
5
5
100
Scenario 2
75
25
0
0
100
Scenario 3
65
20
5
10
100
Scenario 4
50
50
0
0
100
Scenario 5
50
30
10
10
100
2-9
-------
SOURCE SELECTION
The Project Team reviewed and selected categories for further study. In addition to using
the data from the characterizations, the selection process considered factors such as other related
work being performed on specific categories specific EPA Office responsibilities for certain
categories, and whether or not the source category should be handled as a point source category.
Time and resource constraints limited the selection to three source categories: oil spills,
petroleum vessel loading and unloading, and cooling towers.
These categories represent a range of challenges for methodology development. Based
on information from the characterization, emissions estimation methodology development for
petroleum vessel loading and unloading appears to be relatively straightforward. Some emission
factors are available for this category in Compilation of Air Pollutant Emission Factors (AP-42).
The cooling tower source category covers both industrial and comfort cooling towers.
Methodologies for estimating emissions from cooling towers may be very different depending
on their use. Estimating emissions from oil spills requires innovative and non-traditional
methodologies. The experience gained from developing emissions estimation methodologies from
these source types will be invaluable as work on additional source categories progresses.
These categories also represent potential emissions of pollutants important in several
programs. VOC may be emitted from all three categories; potential air toxics emissions may be
of concern from cooling towers and from oil spills. Particulate matter may be emitted from
cooling towers (drift) and oil spills (combustion). Additionally, S02, NOx, CO and carbon
dioxide (C02) emissions may result from combustion of spilled oil.
CH-93-12
2-10
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SECTION 3
OIL SPILLS
BACKGROUND
Oil spills are accidental spills occurring on land and water (both coastal and inland). Such
spills may arise from incidents involving ground transportation such as tanker trucks or railroad
cars; marine transport such as barges, oil tankers or other vessels; spills or blowouts from
pipelines, wells or oil rigs; and releases from spills or accidents at point source facilities such as
refineries or petrochemical plants. Oil spills may include a variety of oil or petroleum products
ranging from thick unrefined crude oils and sludges to highly volatile fuels such as gasoline. Oil
spill materials may include such diverse products as petroleum, sludge, oil refuse, industrial
process oils, gasoline, jet fuel, diesel fuel, kerosene, crude oil and waste oils. The focus of this
section is to determine the emissions from crude oil, gasoline, and diesel fuel spills.
Oil spills may involve large quantities of fuel released over a relatively short time period.
The size of oil spills can range from several gallons to many millions of gallons. For larger
spills, air emissions can be significant and may be a major part of an area's emissions inventory.
Consequently, such spills may have a significant impact on a local area's total emissions.
However, these emissions are not represented in the current NEDS or SIP area source emissions
inventory methodologies. Emissions from spills depend on the type of fuel, meteorological
conditions at the spill site, and the promptness and form of any spill cleanup (e.g., combustion,
chemical treatment or volatilization). If spills are contained and rapid mechanical cleanup occurs,
the resulting emissions will be minimized and will likely include only VOC. If spilled fuels are
combusted (either as a result of the accident or as a deliberate method to clean up the spill),
emissions may include VOC, particulate matter, S02, NOx, C02 and CO. Other potentially toxic
compounds, both in gaseous and particulate form, may be released as a result of combustion of
the fuel or as a result of the chemical cleanup.
CH-93-12
3-1
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EMISSIONS GENERATION
Activities
The types of activities that can result in oil spills include oil tanker accidents such as
cargo tanks cracking during a storm or running aground, tanker collisions, accidental emptying
of cargo, and railroad or highway tanker truck accidents. In addition, pipeline ruptures frequently
occur, and oil well accidents can happen during normal operation or testing situations. A large
number of oil spills can be attributed to operations at point sources and typically include process
operation accidents, storage tank leaks, pump seal failures, pipe corrosion, pressure relief valve
problems, pipe ruptures due to freezing weather and operator errors.
Pollutants
The pollutants emitted from an accidental oil spill depend on several factors, including
the type of material spilled, the type of treatment and whether there is combustion of the spilled
material. Emissions of sulfur oxides, for example, depend on the sulfur content of the spilled
material, while other toxic compounds will be released if they are present as impurities. In
general, emissions from evaporative spills and blowouts are limited to VOC. However, the
combustion of spilled material may result in emissions of sulfur oxides, particulates, NOx, C02,
CO and VOC. In addition, other potentially toxic compounds, such as polycyclic aromatic
hydrocarbons (PAHs), dioxins and furans, heavy metals, and hydrochloric acid, may be released
as combustion products or as a result of the chemical cleanup of spills.
SOURCES OF DATA
Activities
The Emergency Response and Notification System (ERNS) is a national computer
database and retrieval system for the storage and retrieval of information and data on releases of
oil and hazardous substances.1 This system is managed and supported by EPA, the U.S. Coast
CH-93-12
3-2
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Guard (USCG), the National Response Center (NRC), and the U.S. Department of
Transportation's (DOT's) Transportation Systems Center.2 The ERNS is updated through
telephone or written reports of oil or hazardous substance releases. Typically, the NRC, USCG
and EPA (Headquarters or Regional Offices) are the agencies receiving the initial information
on the releases. Of the 28,937 oil and hazardous substance release notifications received in 1988,
57 percent were received by NRC, 22 percent by EPA and 21 percent by the USCG.1 For 1987,
1988, 1989 and 1990, 16,108; 15,799; 16,819 and 19,242 oil notifications were entered into
ERNS, respectively.2
Another major database for oil spill releases is maintained by the NRC, which is managed
and operated by the USCG (in conjunction with the EPA) at Coast Guard Headquarters in
Washington, DC. The NRC is the national communications center for activities related to
discharges of oil spills and hazardous substances. The NRC compiles data and information on
oil spills and hazardous substances discharges and makes these data available to requestors.
In 1990, the NRC database showed a total of 15,200 oil spill notifications with
approximately 11,300 of these spills occurring into water.3 Data from the NRC are submitted
to the ERNS along with data reported to EPA and the USCG. Louisiana, Texas and California
reported the largest number of spills in 1990 with 4,493; 1,607 and 965, respectively.3 For June
1991, spills by substance classification listed oil (57.3 percent), miscellaneous (22.7 percent), the
Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) (18.9
percent) and natural gas (1.1 percent). Spills by event type listed non-transportation
(57.3 percent), offshore (16.1 percent), marine (11.6 percent), highway (6.5 percent), pipeline (5.6
percent), railroad (2.5 percent) and air (0.4 percent).3 The breakdowns by classification and event
are believed to be based on number of incidents.
CERCLA and the Clean Water Act (CWA) require that these oil and hazardous substances
discharges be reported, and the NRC estimates the discharge reporting compliance rate at
approximately 90 percent. The NRC and ERNS have the following significant advantages as
sources of activity data: they are national databases, they have a low cutoff for spill size and
they are relatively complete databases. Other existing oil spill databases include one maintained
by the Minerals Management Service, a few maintained by private firms and many maintained
by state agencies. However, because there are no major incentives for reporting discharges to
these databases, there are concerns about their comprehensiveness. While only some state agency
CH-93-12
3-3
-------
databases may be as accurate as the NRC database for estimating oil spill activity within the state
boundaries, at a minimum, state databases can provide a comparison to validate NRC data.
Pollutants
Data on the pollutants emitted from oil spills may be obtained from a variety of sources.
One such reference is a California Air Resources Board (CARB) study of the relative emissions
from burning a major spill on water versus natural evaporation of an equally-sized spill.4
Another reference, AP-42, may be used to obtain surrogate data on pollutants emitted from oil
spills from sections on open burning, transportation and marketing of petroleum liquids, orchard
heaters and petroleum refining.5 A number of other sources describe the composition of the
pollutants emitted in terms of particular species or classes of compounds, or as individual
pollutants.6,7,8,9
METHODOLOGIES
Emissions from oil spills can be included in the point source inventory or the area source
inventory, and although this report focuses on area emissions, the proposed methodologies can
be used in either situation. Three methods for estimating emissions are proposed: Methods I and
II are for current or past years, and Method III is for estimating spills in future years. For
Methods I and EI, ambient air emissions estimates will depend on particular results of some
variation of the following general procedure, which uses data from oil spill incident reports:
• Determine the activity indicator level (i.e., the number of incidents and amount of
material spilled)
• Estimate the amount of material lost to various media (i.e., soil, water)
• Calculate emissions
Method III, which is proposed for future year estimates, is a probabilistic approach involving
historical data summarization, trend-detection procedures and short-term forecasts.
CH-93-12
3-4
-------
For point source spills, the spill activity could be treated as a special form of fugitive
emissions with one or more special SCCs, or the spill could be treated as an area source spill.
If treated as a point source of fugitive emissions, the emissions would be considered as part of
the point source inventory. The other approach would be to consider point source spills as part
of an area source inventory. In either case, the procedures to estimate emissions could follow
the following methods.
Method I
In the first approach, all spill data for a specified geographical area (state, county, city,
or grid area) for a specified time period would be requested from the NRC, ERNS, or, if
available, the state database. NRC and ERNS data categorize spills according to four
classifications: oil, natural gas, CERCLA, and miscellaneous. It is assumed that states have
similar classifications. The requests for data should include quantitative estimates of the size of
each spill {e.g., gallons of crude oil, gallons of gasoline). However, the NRC or ERNS systems
generally do not include information on the area of the spill, the type of cleanup, the time
interval for cleanup, and the amount of material recovered. Assumptions for these variables
which must be made when calculating air emissions from oil spills are discussed later in this
section.
NRC and ERNS data retrievals requested for the general category "oil spills" will include
all data for over 70 substances such as gasoline, crude oil, benzene or jet fuels. A preview of
data for the year 1990, however, showed that about 10 substances accounted for more than
90 percent of the total number of spills reported to the NRC.3 The top four substances were
crude oil, unknown oil, diesel oil and gasoline. Specific breakdowns by substance may be
obtained with each NRC or ERNS data retrieval request if specifically stated in the request. Such
breakdowns are encouraged, since the information will allow more accurate estimates of the air
emissions. Once the quantitative information on each activity indicator, (i.e., the size of the spill
and type of substance) is obtained, the appropriate equations are applied to calculate ambient air
emissions.
This process is repeated for each of the spills within the specified geographical area and
the emissions estimation time period. The calculated emissions for each spill are summed to
CH-93-12 3 -5
-------
obtain total emissions. The benefit of conducting such a detailed procedure for each spill is a
much smaller uncertainty error in the estimated emissions. The drawback, however, is the
extensive resource expenditures required to obtain the total emissions estimate.
Under Method I, spills are differentiated depending on whether the emissions result from
volatilization to the atmosphere or from combustion of the oil spill. The following subsections
describe the procedures for estimating air emissions from volatilization and combustion.
Volatilization
To estimate the amount of material from an oil spill that is volatilized, it is first necessary
to consider the quantity of material that is available for evaporation. During a spill some
material may be absorbed into the ground, sink to the bottom of bodies of water, be flushed into
water treatment facilities, or be recovered through physical or chemical treatment. Each of these
items represents the loss of some amount of material that was available for evaporation. The sum
of these losses determines the total amount of material that remains available to be evaporated.
The term "loss factor" is often used to describe the fraction of spilled material that is available
for evaporation to the atmosphere. The methodology proposed here is for the reader to review
the literature for various types of spills and use the typical loss factors found therein. In some
cases, the loss factor may be determined, in whole or in part, from an incident report if the report
includes information about recovered material. In other cases, particularly for evaporative spills,
the loss factor may have to be determined from one or more models also used to estimate
emissions. In the absence of reliable or semi-quantitative numbers, the loss factor will be
assumed to be one, (i.e., all material spilled is available to be lost to the atmosphere). Having
made the assumption that the loss factor is one, the following paragraphs describe methods for
estimating emissions from oil spill volatilization. The discussion on volatilization begins with
a presentation on the equations used to calculate evaporative losses to the ambient air and is
followed by an example calculation.
CH-93-12
3-6
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Emissions estimating equation
Stiver and Mackay have developed a method for estimating evaporation from hydrocarbon
spills that is based on the following equation for estimating the evaporating molar flux:6
N = — (1)
RT
where N = molar flux (mol/s)
k = mass transfer coefficient under prevailing weather conditions (m/s)
a = surface area of spilled liquid (m2)
P = spilled liquid's vapor pressure (Pa or atm)
R = universal gas constant (8.314 Pa - m3/K-mol)
T = ambient temperature (K)
Stiver and Mackay rearranged Equation 1 to describe oil spill emissions in terms of
fraction volatilized:
= Pv ka (2)
d/ RT Vo
where Fv = volume fraction evaporated
t = elapsed time (s)
v = liquid's molar volume (m3/mol)
V0 = initial volume of spilled liquid (m3)
Equation 2 can then be rewritten in terms of the initial spill depth:
CH-93-12 3 -7
-------
Pv k
(3)
d/ RT da
where d0
initial spill depth (m)
Equation 2 and Equation 3 can be integrated and MW/p substituted for v to give the
volume fraction evaporated as a function of time:
The following paragraphs discuss methods for estimating the parameters in Equation 4
or Equation 5. The value for t can be viewed as the elapsed time until the spill is essentially
cleaned or has sunk below the surface, or its vapor pressure has dropped to the point that
evaporation has essentially ceased. The initial depth of the spill, d0, or alternatively the spill
volume, V0, and area, a, may be available from the NRC database or other sources. If not, the
spill area may be estimated using techniques described in the following discussion on spill area
estimation.
For both oil spill evaporation and combustion (discussed later), the area of the spill is an
important input parameter. If the spill area is not available from observation, estimation
techniques must be used. The Handbook of Chemical Hazard Analysis Procedures1 classifies
spills in the following ways according to the rate of release and the duration of the spill.
(4)
(5)
where MW
P
molecular weight of the spilled liquid (g/mol)
vapor density (kg/m3)
CH-93-12
3-8
-------
• Continuous spill - the spill continues at a specified finite rate for long duration
• Instantaneous spill - the spill occurs in a very short time
• Finite duration spill - a given volume of liquid is spilled over a given duration of time:
both the release rate and the release duration are finite
The method used to calculate the spill area depends upon the category of the spill. The
spill area also depends upon the spill rate, duration and type of surface on which the spill occurs.
For continuous spills, the spill area increases until the rate of loss from the spill due to
evaporation or burning equals the spill rate. The spill area is given by the following equation:
A^ = V/y (6)
where Aeq = steady state (equilibrium) area of the pool (m2)
V = liquid spill rate (m3/s)
y = surface regression rate due to burning or evaporation (m/s)
The surface regression rate is the rate at which the surface would drop per unit of time
due to the loss of mass during either evaporation or burning. This assumes that none of the
liquid is being replaced. This equation also assumes that the liquid regression rate is constant
and that all mass is lost through evaporation or burning (e.g., no mass is lost into the supporting
earth or water surface). This equation also assumes that the spill is unconfined by dikes or other
restraining structures.
In addition, the Handbook of Chemical Hazard Analysis Procedures describes methods
for estimating the time and spill diameter needed to reach steady state. The handbook also
provides methods for estimating the maximum spill diameter and the time to reach the maximum
for both finite duration and instantaneous spills for land and water surfaces.
Having addressed the spill area, the temperature of the spilled oil (T) in Equations 4 and
5 can be estimated from the seasonal water temperature for spills on water, or on the average
daily temperature for spills on land.
CH-93-12
3-9
-------
Estimation of k is more complex because it depends on wind speed, atmospheric stability
and the physicochemical properties (e.g., Schmidt number) and degree of mixing of the spilled
liquid. The overall value of k consists of two components: the liquid-phase and the vapor-phase
mass transfer coefficients.
The vapor-phase coefficient is essentially independent of the liquid properties and depends
primarily on wind speed and atmospheric stability. The vapor-phase mass transfer coefficient
expresses the degree to which a gas can be transported across a layer of air. Mackay and Yeun
present the following correlation for predicting the vapor-phase mass transfer coefficient for
neutral atmospheric stability:11
kg = 1.0 x 10"3 + 46.2 x 10"5(6.1 + 0.63l/10)05C/10 ScG061 (7>
where Ul0 = the wind speed (m/s) measured at 10 meters
ScG = the Schmidt number of the substance in gas phase
Atmospheric stability usually varies throughout the day, and is typically unstable during
the day and stable at night. Since long-term average emissions estimates are desired for this
application, neutral stability estimates using Equation 7 are probably an adequate first
approximation to the average long-term vapor phase mass transfer coefficient.
The liquid-phase mass transfer coefficient accounts for the time required for an
evaporating component of a multi-component mixture to diffuse up from the bulk of the liquid
to the surface, where it can evaporate. The liquid-phase mass transfer coefficient depends
primarily upon wind speed, the substance's liquid-phase Schmidt number (the ratio of the
substance's kinematic viscosity to mass diffusivity), the liquid's composition (i.e., a single- versus
multi-component liquid) and the degree of mixing within the liquid.8 If the liquid is pure, (i.e.,
consists of only one substance), or if the liquid is well-mixed, the concentration at the liquid
surface is constant and the liquid-phase mass transfer coefficient is essentially infinite. No
liquid-phase mass transfer coefficients have been identified for hydrocarbon mixtures; however,
Stiver and Mackay indicate that the liquid-phase mass transfer coefficient is believed to be
unimportant for hydrocarbon spills, with the following three exceptions:6
CH-93-12
3-10
-------
(1) If the oil layer is viscous, deep and poorly mixed, it is difficult for the more volatile
components to diffuse to the liquid surface
(2) If a "skin" of evaporation residue forms at the surface further evaporation will be reduced
(3) If the oil contains components of high-volatility - In this case, the highly volatile
components will evaporate quickly so that an otherwise large liquid-phase mass transfer
coefficient may be the limiting factor. This effect is most important early in the
evaporation process and becomes less important for longer time periods.
In general, if the liquid-phase mass transfer coefficient is neglected {i.e., assumed infinite), the
resultant evaporation rate will be an overestimate.
The vapor pressure, P, and molar volume, v, for a pure hydrocarbon spill (a spill
containing only one chemical component) do not vary with time. For this situation, the integral
in Equation 5 can be evaluated, yielding the following equation:
•-1 P MW kt (V.
v -7 w
pRT d
Equation 8 was derived to estimate volatilization for pure hydrocarbon species only. For
most significant oil spills, however, the oil is a mixture of components with varying vapor
pressures. When a spill occurs, the components with the highest vapor pressures will evaporate
most rapidly. The vapor pressure of the spill will decrease with time, which violates the
assumptions used in deriving Equation 8. As a result, if the vapor pressure of a "fresh" oil spill
is used in Equation 8, the fraction evaporated will be overestimated.
To obtain more accurate volatilization estimates for hydrocarbon mixtures, the change of
vapor pressure and density with time must be accounted for. Stiver and Mackay present an
approach which requires experimental data specific to the hydrocarbon.6 Their method requires
data specifying the volume fraction of oil evaporated as a function of a variable that they refer
to as evaporative exposure. A plot of data that they determined for a Norman Wells crude oil
at 22°C (72°F) is shown in Figure 3-1. The data shown in Figure 3-1 are essentially an
experimental evaluation of the integral in Equation 4 or Equation 5. The evaporative exposure
is defined as:
CH-93-12
3-11
-------
u>
0
ILI
1 Q«0
o
a.
>
Ui
^ 020
cc
u.
UJ
2^
o
>
y/ S
y/ ¦
m
JT ¦
/
a/
<2^-——
^ O GAS stripping
. TRAY EVAPORATION
w
*
DISTILLATION PREDICTION
9
/
o
/
7
3
'
2000
5000
10000
103
10"
10
EVAPORATIVE EXPOSURE 0
Figure 3-1. Evaporation curve for Norman Wells crude oil at 22°C (72°F).*
(Reprinted with permission from Environmental
Science and Technology. Copyright @ 1984.
American Chemical Society.)
CH-93-12
3-12
-------
8 = kat / V0
= k 11 d0
(9)
where 0 =
= evaporative exposure (dimensionless)
k
= mass transfer coefficient (m/s)
a =
= area of the oil surface (m2)
t =
: elapsed time since the spill (s)
V0 =
= volume of the spill (m3)
d0 =
= depth of the spill (m)
By calculating the exposure from Equation 9 and referring to a plot of Fv versus 0 for
the estimated temperature, such as in Figure 3-1, the volume fraction evaporated may be
estimated.
The measured volume fractions volatilized that are shown in Table 3-1 were determined
using this approach. For example, for the entry in Table 3-1 corresponding to an elapsed time
of one hour, the evaporative exposure is calculated as:
8 = k t /d0
= (0.00542 m/s)(3600 s)/0.01 m
= 1,951
Referring to Figure 3-1, the volume fraction evaporated, Fv, corresponding to an evaporative
exposure of 1,951 is estimated to be 0.21.
As an example of the error associated with using Equation 8 for a hydrocarbon mixture
(assuming constant vapor pressure), assume that a crude oil spill occurs with a depth of one cm.
The ambient temperature is 60°F, the wind speed is 5 meters per second (m/s), and the vapor
pressure of the fresh crude is 2.8 psia. Assuming a gas-phase Schmidt number of 2.0, the gas-
phase mass transfer coefficient determined from Equation 7 at this wind speed is 0.0054 m/s.
The liquid phase mass transfer coefficient is assumed to be infinite. The vapor molecular weight
and condensed vapor density of the crude oil are 50 g/mol and 4.5 lb/gal, respectively. Using
these values in Equation 8, the calculated volume fraction (Fv) evaporated at various times is
shown in Table 3-1. The results of laboratory measurements of a Norman Wells crude oil by
CH-93-12 3-13
-------
Stiver and Mackay that account for the decrease of vapor pressure with time are also shown in
Table 3-1 (via Figure 3-1).6 The table shows that estimates using Equation 8 are in error by
percentages ranging from 592 percent after one hour up to 6,022 percent after 16 hours. Thus,
for this particular example, Equation 8 is adequate only for order of magnitude estimates for very
short elapsed times. Consequently, Equation 8 should be used with great caution for hydrocarbon
mixtures. Note that the accuracy of this approach will vary depending on the hydrocarbon
mixture.
Stiver and Mackay developed the relationship in Equation 9 only for crude oil, however,
the purpose here is to develop evaporation rates for crude oil, gasoline, and diesel fuel. Stiver
and Mackay then present an equation developed to relate the evaporative exposure to the volume
fraction evaporated for a hydrocarbon mixture:6
Fv = In [1 + B(Tc/T)9e
-------
TABLE 3-1. VOLUME FRACTION EVAPORATED EXAMPLE FOR CRUDE OIL
Volume
Vapor
Pressure
(psia)
Vapor
Molecular
Weight
(g/mol)
Condensed
Vapor
Density
(lb/gal)
Gas
Constant
(Pa-m3/K-mol)
Temp.
(F)
Mass Transfer
Coefficient
(m/s)
Time
(hours)
Time
(sec)
Evap.
Exp.
Initial
Depth
(m)
Volume
Fraction
Volatilized
(Eqn 8)
Fraction
Volatilized
(measured-
Stiver & Mackay)
Volume
Fraction
Volatilized
% error
2.8
50
4.5
8.314E-05
60
5.42E-03
1
3,600
1,950
0.01
1.454
0.21
592
2.8
50
4.5
8.314E-05
60
5.42E-03
2
7,200
3,899
0.01
2.908
0.25
1,063
2.8
50
4.5
8.314E-05
60
5.42E-03
4
14,400
7,799
0.01
5.816
0.30
1,839
2.8
50
4.5
8.314E-05
60
5.42E-03
8
28,800
15,597
0.01
11.632
0.32
3,535
2.8
50
4.5
8.314E-05
60
5.42E-03
16
57,600
31,194
0.01
23.263
0.38
6,022
Assuming a wind speed of 5 m/s
-------
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I
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V
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1
II
m
e
F
r
a
c
t
i
0
n
E
v
a
P
o
r
a
t
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d
0.80
0.70 -
0.60 -
0.50 -
0.40
0.30
0.20 -
0.10 -
0.00
1.0E+00
. j —». -i.i. 4
: : MM!!
: :
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1.0E+02
i rrrm
1.0E+03 1.0E+04
Evoporatlvo lfxpo3uro
35"C (95*F)
29"C (85T)
24"C (75'F)
TC (45*F)
1.0E+05
1.0E+06
I IIIIIII
1.0E+07
Figure 3-2. Evaporation curve for crude oil.
-------
I
-J
V
0
1
u
m
e
F
r
a
c
t
i
o
n
E
v
a
P
o
r
a
t
e
d
35*C (95T)
(85* F)
24'C (75T)
TC (45*F)
1.00
0.90 -
0.80 -
0.70 -
0.60 -
0.50 -
0.40 -
0.30
0.20 -
0.10 -
0.00
1.0E+00
I 1—I I I I 11
1.0E+01
"1 1—I I Mill 1 I I I IMM
1.0E+02 1.0E+03 1.0E+04 1.0E+05
Evaporallvo Exposure
Figure 3-3. Evaporation curve for gasoline.
-------
UJ
I
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oo
V
0
1
u
m
e
F
r
a
c
t
i
o
n
E
v
a
P
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r
a
t
e
d
1.00
0.90
0.80 -
0.70
0.60
0.50 -
0.40
0.30
0.20 -
0.10 -
0.00 - -
1.0E+00
j-L U;-i>
I I i mi
»•••<••!••>•? 1-1
: : : :
: :
. : : I in
: : :
: :
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u
i ll-
:
!"!"!'!'!!•
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i ; i : :i:
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;
l.r.l
35"C (95*F)
~ 29"C (85T)
24"C (75T)
TC (45-F)
TTrrin
1.0E+01
.0E+02
ttiI r—i—i-rrri t
I.0E+03 1.0E+04
Evaporotlvo Exposure
I I I I III
1.0E+05
1.0E+06
1.0E+07
Figure 3-4. Evaporation curve for diesel fuel.
-------
evaporate at generally lower evaporative exposures than does crude oil. However, the
evaporative exposures may be quite different for each of the three fuels.
Once the volume fraction evaporated is determined from Figures 3-2, 3-3, or 3-4, the mass
evaporated can be calculated by multiplying by the initial volume of the spill and liquid density
of the evaporating components, p:
M = F,V#v (11)
where M = mass evaporated (kg)
Fv = volume fraction evaporated
V0 = initial spill volume (m3)
pv = liquid density of the evaporating components (kg/m3)
Note that determination of the liquid density of the evaporating components is non-trivial,
because the composition of those components is changing with time. A first approximation to
the liquid density of the evaporating components may be obtained from the density of the "fresh"
liquid's condensed vapor. This is only an approximation because the density of the condensed
vapor will change with time. The magnitude of the resultant error increases with time and
depends on the hydrocarbon mixture.
R. C. Little also obtained data on the evaporation of crude oils and found that the data
conformed well to an empirical equation of the following type:9
W!W„ - '/(' 1/2 ~ ') <12)
where W = weight percent volatiles lost at time t
Wm = initial weight percent volatiles of oil
tm = time when 50 percent of volatiles have evaporated
CH-93-12
3-19
-------
Evaporative loss example for hydrocarbon mixture spill
Estimation of the evaporation loss from a hydrocarbon spill typically involves the
following steps:
• Determine spill area
• Determine elapsed time
• Calculate mass transfer coefficient
• Calculate evaporative exposure
• Determine volume fraction evaporated from graph
• Calculate mass evaporated
The example assumes that a Norman Wells crude oil spill of 10,000 gallons occurs on water.
The water temperature is 24°C (75°F). The wind speed measured at 10 m is 5 m/s. The spill
area is observed to be 10,000 m2. The spill is assumed to be cleaned up in seven days.
Determine pool area. In this example, the spill area is observed to be 10,000 m2. If direct
observations were not available, an estimate could be made using methods referenced in the text.
That approach would be complicated, however, by the fact that the evaporation rate of a crude
oil mixture varies with time. Thus, only a rough estimate may be practical using those methods.
Determine elapsed time. The elapsed time is the time from the beginning of the spill until it is
cleaned up or has been otherwise dispersed. For this example, the spill is cleaned up in seven
days.
Determine mass transfer coefficient. The gas-phase mass transfer coefficient is calculated from
Equation 7 in the text.
kg = 1.0 x 10"3 + 46.2 x 10 5(6.1 + O.63f/10)05t/10 ScG061
CH-93-12
3-20
-------
where kg
Ui0
ScG
gas phase mass transfer coefficient (m/s)
the wind speed measured at 10 meters (m/s)
the Schmidt number of the substance in gas phase
A Schmidt number appropriate to crude oil evaporation is difficult to choose, since crude oil is
a mixture of a variety of organic species. Mackay and Yeun list the Schmidt number for a
variety of pure organic compounds.8 The values range from 1.99-2.58. For this example, a
Schmidt number of 2.25 is used to approximate the Schmidt number of crude oil.
Thus, the gas-phase mass transfer coefficient is given by:
kg = 1.0 x 10"3 + 46.2 x 10~5(6.1 + 0.63(5m/s))05 (5m/s) 2.25"067
= 0.005 m/s
The spill is assumed to be well mixed so that the liquid-phase mass transfer coefficient is
assumed to be infinite. Consequently, it does not enter the calculations.
Calculate evaporative exposure. The evaporative exposure is given by Equation 9:
0 = k a t / V0, or
= k 11 d0
0
evaporative exposure (dimensionless)
k
mass transfer coefficient (m/s)
a =
area of the oil surface (m2)
t =
elapsed time since the spill (s)
V0 =
volume of the spill (m3)
do =
depth of the spill (m)
CH-93-12
3-21
-------
Using the oil spill area (10,000 m2), the spill volume (10,000 gal=37.85 m3), and the elapsed time
(7 days=604,800 s), the evaporative exposure is calculated as follows:
0 = (0.005 m/s)(10,000 m2)(604,800s)/(37.85m3)
= 7.99 x 105
Determine volume fraction evaporated from graph. The evaporative exposure value is used to
determine the corresponding volume fraction evaporated from the plot in Figure 3-2, for an
ambient temperature of 24°C (75°F). Referring to Figure 3-2, the volume fraction evaporated
corresponding to an evaporative exposure of 7.99 x 105 is approximately 0.52.
Calculate mass evaporated. The mass evaporated is given by Equation 11:
The liquid density of the evaporating components is estimated from the liquid's condensed vapor
density. The condensed vapor density of crude oil (RVP 5) is 4.5 lb/gal @60°F (15.5°C), as
obtained from AP-42 Table 4.3.2, Physical Properties of Typical Organic Liquids.5 Note that the
difference between the spill temperature, 24°C, and the condensed vapor density reference
temperature, 15.5°C, is neglected; however, the resultant error is expected to be small relative
to the other approximations being made.
M = WPv
where M
F,
Pv
mass evaporated (kg)
volume fraction evaporated (0.52)
initial spill volume (37.85 m3 or 10,000 gal)
liquid density of the evaporating components (kg/m3)
CH-93-12
3-22
-------
The mass evaporated is thus given by:
M = (0.52) (10,000 gal) (4.5 lb/gal)
= 23,400 lb
Combustion
Several papers and reports, including some from the National Institute of Standards and
Technology (NIST) and one regarding the Kuwait oil well fires, have provided information on
smoke (particulate), CO, C02 and NOx emissions from oil spill fires. Limited information is
available on S02 emissions, however, the upper limit would be based on the mass of sulfur
available. No data were provided for lighter weight petroleum products such as gasoline. Tables
3-2, 3-3 and 3-4 summarize the findings presented in the articles. The tables show that emission
factors can be estimated for particulate matter, CO, smoke and NOx.
Preliminary soot (particulate) emission factors from the Kuwait oil pool fires were
determined to be significantly lower than those obtained from controlled burns of oil pools.10
The soot emission factor for Kuwait pool fires was estimated at 1 to 2 percent (1-2 g soot/100
g fuel), as compared to 8 to 17 percent reported for controlled burns. The reason for this
difference has not been determined. The S02 emission factors were estimated at 3.35 percent
(3.35 g S02/100 g fuel). Data describing emissions of PAHs have also been obtained.11,1213
Emissions of particulate matter can be estimated directly from the figures provided in
Tables 3-2, 3-3 and 3-4. Based on the controlled burn data, large offshore crude oil burns are
anticipated to produce approximately 0.15 g of particulate matter per gram of fuel. For crude
oil with a density of 7.3 lb/gal, this emission factor becomes 1.1 lb of particulate matter per
gallon of crude oil (1,100 lb/1,000 gal).
CH-93-12
3-23
-------
TABLE 3-2. SMOKE YIELD WITH VARIOUS POOL DEPTHS1113
Smoke yield
Pool depth
(Ssmoke^ Sfuel)
(mm)
Oil type
0.035
2
Alberta Sweet Crude
0.050
3
Alberta Sweet Crude
0.080
5
Alberta Sweet Crude
0.080
10
Alberta Sweet Crude
0.100
30
Alberta Sweet Crude
pool diameter = 0.6m
organic carbon content of smoke, by weight: 14-21 percent
elemental carbon content of smoke, by weight: 79-86 percent
TABLE 3-3. SMOKE YIELDS WITH VARIOUS POOL DIAMETERS AND OIL
TYPES14
Approximate
Pool
smoke yield3
diameter
(Ssn'.okt/ Sfuel)
(m)
Oil type
0.08
0.4
Alaskan North Slope Crude
0.10
0.4
Alaskan North Slope Crude
0.08
0.6
Alaskan North Slope Crude
0.08
0.6
Alaskan North Slope Crude
0.07
0.6
Alberta Sweet Crude
0.11
0.6
Alberta Sweet Crude
0.14
7.0
Louisiana Crude
0.09
1.0
Arabian/Murban Mix Crude
0.095
1.0
Arabian/Murban Mix Crude
0.10
1.0
Arabian/Murban Mix Crude
0.11
1.0
Arabian/Murban Mix Crude
0.135
3.0
Arabian/Murban Mix Crude
0.145
3.0
Arabian/Murban Mix Crude
0.16
3.0
Arabian/Murban Mix Crude
0.13
0.4
Fuel Oil
0.145
0.4
Fuel Oil
0.145
0.4
Fuel Oil
0.20
15.0
Fuel Oil
'Values obtained from Figure 6 in Reference 14 Authors anticipate large offshore crude oil bums will produce a nominal
smoke yield of 0.15 g!mtygfud.
CH-93-12
3-24
-------
TABLE 3-4. ADDITIONAL COMBUSTION EMISSIONS INFORMATION
Evans et al., 198713
Day et al., 197915
pool diameter (m)
oil type
smoke yield (gsmoke/gfud)
Alberta Sweet Crude
0.079 - 0.087
0.6
0.02 - 0.05
0.023 - 0.125;
CO/C02, by volume
NO/C02, by volume
NOx/C02, by volume
1.5xl0'4 - 1.6X10"4
4.0x10'4 - 5.0x10'4
0.038
not reported
not reported
'Ratio was originally given as COj/CO (range of 8-43). No units were given to express the ratio in terms of volume or mass.
CO emissions can be estimated from a carbon balance of crude oil and its emissions. The
carbon content of crude oil is approximately 86 percent by mass. Benner et al indicate that the
organic and elemental carbon content of smoke are 14 to 21 percent and 79 to 86 percent by
weight, respectively.11 Therefore, the percent of organic and elemental carbon in the smoke by
weight will be assumed to be 17 percent and 83 percent, respectively. Assuming that the organic
fraction has the same carbon fraction by weight as the unburned crude (86 percent), the carbon
content of the smoke is 98 percent (83 percent element carbon plus 17 percent multiplied by
86 percent organic carbon) by weight. It is also assumed that the ratio of CO to C02 is 0.038,
by volume, and that CO and C02 are the only gaseous carbon products.13 Performing the carbon
mass balance yields:
Mc(fue[) = Mc(smoke) + Mc(CO) + Mc(C02)
(13)
where Mc(fuel)
Mc( smoke)
mass of carbon in fuel burned = 0.86 MF
mass of carbon in smoke = (0.98)(0.15) M?
mass of carbon in CO
Mc( CO)
Mc(C02)
m¥
mass of carbon in C02 = A/c(C0J/(O.O38)
mass of fuel burned
Substituting these values in the carbon mass balance equation yields:
CH-93-12
3-25
-------
(0.86)A/f =
Solving for Mc(CO) yields:
(0.98) (0.1 5)Mf + Mc(CO) + Mc(CO)/(0.038)
Mc(CO) = (0.026)MF
(14)
Converting the mass of carbon as CO to the mass of CO yields:
Mco = Mc{CO)(MWcJMWc)
Mco = (0.026) Mf (28)/(12)
Mco = 0.061 Mf
(15)
where Mco
MWC
MWqq
mass of CO
molecular weight of CO
molecular weight of C
Thus, the emission factor for CO is approximately six percent by weight. For a crude oil
with a density of 7.3 lb/gal, this emission factor becomes 0.44 lb CO per gallon of crude oil
(440 lb CO/1,000 gal fuel).
Ratios by volume of nitric oxide (NO)/C02 and NOx/C02 from Evans et al. are also
presented in Table 3-4.613 From these ratios, it can be shown that:
Mm = 2.58 x 10"4 Mf and
mNOx = .0011 Mf
(16)
where MN0
mass of NO
mass of NOx as NO:
mass of fuel
CH-93-I2
3-26
-------
If the spill burns completely, the total mass burned is equal to the total mass of the spill.
If the spill does not burn to completion, for example, if it is extinguished, then the rate of burn
must be known in order to estimate the total mass burned.
For crude oil fires, two modes of combustion have been observed: a steady state mode
and a vigorous or "boil-over" mode.12,1314 In the steady state mode, the oil burns steadily.
Toward the latter part of a burn, the water beneath the oil will begin to boil. The boiling is
accompanied by an increase in the burning rate, which is apparently due to increased mixing of
the oil. The boiling is ascribed to the increased oil surface temperature due to the higher boiling
point of the oil at the latter stages of burning, when only the heavier, higher boiling point
fractions remain due to distillation.12 Thus, oils with lower boiling points may not exhibit boil-
over behavior.
The burn rate of an oil pool also depends on the diameter of the pool. The bum rate
increases with pool diameter up to approximately five meters. Above pool diameters of
approximately five meters, the burn rate is approximately constant for crude oil.14 It is assumed
that for this application all fires will be over five meters in diameter.
Reference 13 presents data that indicate that a burning velocity of 0.06 mm/s is
representative of a variety of crude oils on water for pool diameters greater than five meters.
This rate is assumed to be a composite that includes both the steady state and vigorous burning
modes. Since the rate includes the boil-over phase, it will overestimate pool fires on land
surfaces. For other petroleum products, ranges of burning rates of 6 to 12 in/hr for gasoline and
five to eight in/hr for kerosene have been quoted.16 The range is due to variations in the liquid's
properties as lighter fractions are preferentially burned first.
For other oils, correlations have been developed that relate the burning velocity to the
oil's chemical properties. Figure 3-5, presents data relating the pool burning rate to the ratio of
the liquid's heat of combustion to heat of vaporization.17 Another correlation has been developed
that relates the burning rate to the boiling point of the liquid.18
92.6 e
-0.0043T.
8 MW 10"7
y =
(17)
P
6
CH-93-12
3-27
-------
E
\
E
U
UJ
cc
o
cc
D
CO
• Aviation gasoline
UDMH
Me OH
0 100 200 300
^ ^ combustion ^ vaporization
Figure 3-5. Relationship of liquid burning rates at large tray diameters to ratio of
heat of combustion to heat of vaporization. 17
(Reprinted with permission from INTERNATIONAL
SYMPOSIUM ON THE USE OF MODELS IN FIRE
RESEARCH, National Academy of Sciences, Publi-
cation 786, 1959. Courtesy of the National Academy
Press, Washington, D. C.)
3-28
-------
where y = burning velocity (m/s)
MW = molecular weight (kg/kgmol)
p = liquid-specific gravity (dimensionless)
Th = normal boiling point (°F)
Example Emission Calculation for Oil Spill Fire
Estimating emissions from an oil fire typically involves the following steps.
• Determine burning velocity
• Determine spill area
• Determine elapsed time of fire
• Determine mass of fuel burned
• Determine mass of pollutant released
The following discussion is an example of calculating the evaporative loss from a crude oil pool
fire. The example assumes that a crude oil spill of 10,000 gallons occurs on water. The oil is
ignited and burns to exhaustion. The pool area is observed to be 10,000 m2.
Determine burning velocity. A burning velocity of 0.06 mm/s is assumed, which is consistent
with the data of Evans and Tennyson.14
Determine spill area. In this example, the spill area is observed to be 10,000 m2. If direct
observations were not available, an estimate could be made using methods referenced in the text.
Determine elapsed time of fire. The elapsed time is used to determine the mass of oil that is
consumed by the fire before it is extinguished. Since the fire burns to exhaustion in this
scenario, the entire spill will be consumed and, consequently, the elapsed time is not required.
CH-93-12
3-29
-------
Determine mass of fuel burned. The entire mass of the 10,000 gallon spill is stated to have
burned. The density of crude oil as given by Table 4.3-2 of AP-42 is 7.1 lb/gal.5 Thus, the mass
of fuel burned is
32,206 kg = 10,000 gal x 7.1 lb/gal x 0.4536 kg/lb
Determine mass of pollutant released. The soot (particulate) emission factor as determined from
the Kuwait pool fires is one to two percent (1-2 g soot/100 g fuel). Controlled burns indicate
that the emission factor is 8 to 17 percent. For the given spill, the range of soot emitted is given
by:
1 percent emission factor:
322 kg (soot) = 32,206 kg x 0.01
17 percent emission factor:
5,475 kg (soot) = 32,206 kg x 0.17
Using an S02 emission factor of 3.35 percent (g S02/g fuel) the mass of S02 released is given
by:
1,079 kg (S02) = 32,206 kg x 0.0335
The emission factor for CO as derived in the text is 0.061 (g CO/g fuel). Using this factor, the
mass of CO released is given by:
1,965 kg (CO) = 32,206 kg x 0.061
CH-93-12
3-30
-------
The emission factors for NO and N02 as derived in the text are 0.000258 (g NO/g fuel) and
0.0011 (g NOx as N02/g fuel). Using these factors, the mass of NO and NOx released are given
by:
8.3 kg (NO) = 32,206 kg x 0.000258
35.4 kg (NOx as N02) = 32,206 kg x 0.0011
Method II
Method II is similar to Method I in that the procedure for estimating emissions from oil
spills, whether the emissions are evaporative loss or resulting from the combustion of oil spills,
begins by obtaining the activity indicators (i.e., the number of spills and quantity of oil released)
from the NRC, ERNS or state database. In Method I, emissions for each spill in a geographic
location are calculated separately using a number of equations. The total emissions for the
geographic location are obtained by summing the total emissions calculated for each spill.
Method II, however, proposes a much simpler approach. The procedure suggested here would
first add together the quantity of material from each spill that occurred in the specified
geographical location. The total quantity of material spilled and evaporated or combusted would
then be multiplied by a single emission factor to calculate the total emissions rather than using
the equations presented in Method I.
In the basic version of Method n, the emission factor would be based on a large number
of simplifying assumptions. Examples of the assumptions include these items: all of the spills
were of the same material; spills were of average areas; a uniform time elapsed for volatilization
or combustion; and an average wind speed, average Schmidt number, and an average liquid
density of the evaporating components is appropriate.
The major benefit of this approach is that it is significantly less labor intensive than
Method I. However, the emissions estimate could be extremely uncertain. The uncertainty of
Method II could be improved by such techniques as dividing the total number of spills into
categories having common traits, such as high volatiles, semi-volatiles and low volatiles. A
separate emission factor could then be developed for each of the categories. Other variables in
CH-93-12
3-31
-------
the computation equations can also be considered that might be specific to the conditions in a
given state, county or other geographical location. The development of these categorical
emission factors would require examinations of the historical activity indicator databases and
experimentation with appropriate variables in the emission estimation equations.
Method III
The third approach (probabilistic accident estimation) involves three steps: historical data
summarization, trend-detection procedures and possible one- to five-year forecasts.
The historical information on oil spills associated with production, transportation, storage
and use of crude oils, fuels and other petroleum products is available through several sources,
including the NRC, ERNS and state database systems. These data sources can be used to
determine the national, state or local trends in oil spills by oil product type and oil spill source.
Trends in historical oil-spill volumes can then be compared with historical petroleum industry
production and activity indicators such as those found in the Predicasts' Basebook.18 The
Predicasts' Basebook has a variety of indicators for the years 1976 through 1989. If the oil-spill
volume and petroleum industry indicator trends coincide, forecasts may be possible. Both general
and activity-specific petroleum industry indicators should be reviewed to select the most
appropriate indicator for comparison with oil-spill trends. Examples of these indicators include
world oil demand and pipeline transport of crude oil in specific states.
If appropriate indicators are found, oil industry forecasts such as those found in Oil
Industry Outlook19 or Predicasts' Forecasts20 can be used to estimate oil-spill volumes for the
next one to five years. If a simple and direct relationship between petroleum industry indicators
and oil spill volumes does not exist, other factors, such as new facility construction and
environmental protection expenditures, may need to be considered.
An example of the use of the three step probabilistic approach which consists of (1)
historical data summarization, (2) trend detection, and (3) future year forecasts follows.
NRC information indicates that the petroleum-product category "crude oil" accounted for
the largest number of spills in 1990.3 More detailed information on spills for the years 1987
through 1990 indicates that the greatest volume of crude oil spilled was from three sources:
fixed facilities, pipelines and marine facilities. This information is presented in Table 3-5 by the
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TABLE 3-5. CRUDE OIL SPILL HISTORICAL DATA
Spill size category
Largest sources
1987
1988
1989
1990
Minor
Fixed Facility
number of spills
gallons
3,531
764,170
3,610
832,139
3,399
1,083,572
4,396
1,232,253
Pipeline
number of spills
gallons
832
828,766
767
660,768
1,078
788,404
1,449
1,041,344
Percent of Minor
Category by gallons
Medium
Fixed Facility
number of spills
gallons
66%
40
1,021,570
65%
50
1,488,850
64%
66
1,735,898
72%
63
1,736,235
Pipeline
number of spills
gallons
55 42 56 62
1,559,232 1,180,404 1,488,436 1,559,082
Percent of Medium
Category by gallons
Major
Fixed Facility
number of spills
gallons
92%
91%
90%
7 6 15
2,085,000 1,559,878 23,659,200
88%
1,070,866
Pipeline
number of spills
gallons
5 9 11 3
923,454 22,407,630 1,901,399 672,000
Marine
number of spills
gallons
3,660,000
3,011,274
2
6,216,000
5,184,900
Percent of Major
Category by gallons
Combined
Percent of All
Categories by gallons
Combined gallons
100%
90%
100%
97%
95%
10,842,192 31,140,943 36,872,909
87%
98%
12,496,680
90%
Source: Reference 3
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spill-size categories minor (less than 1,000 gallons spilled), medium (1,000 to 30,000 gallons)
and major (greater than 30,000 gallons spilled). Some trends over time are shown in Figure 3-6.
Including additional years would assist in further assessing these observed trends.
There is no evidence of a trend (i.e., random variation) for two of the major sources and
the combined categories shown in Figure 3-7. The addition of subsequent years may provide
some indication of a trend. If no trend is detected, random variability over time must be
assumed.
Table 3-6 includes some petroleum industry indicators from the Predicasts' Basebookw
and Oil Industry Outlook19 that may coincide with the oil-spill trends observed in Figure 3-6.
Figures 3-8 and 3-9 display some of the historical trends seen in petroleum industry
indicators as well as a short-term forecast. The most interesting trend comparison is with the
minor fixed facility spills shown in Figure 3-6 and the refinery operating capacity shown in
Figure 3-9.
DATA ISSUES
Several data issues need to be resolved before acceptable methodologies for estimating
activity levels and emission factors can be developed. To date, the NRC has provided estimates
on the number of reported incidents and statistics on the quantity of material spilled. However,
data on such items as the area of the spill, the type of cleanup and the amount of material
recovered are not generally available from the NRC or ERNS. Other sources that might be able
to provide this type of information should be explored. Also, additional work may be necessary
to clarify the differences between the smoke/particulate production rates of controlled and
uncontrolled oil fires, the evaporation rates for hydrocarbons other than crude oil, diesel fuel and
gasolines, and the evaporation rates for other than the ambient temperature range of 7 to 35°C
(45 to 95°F). Further efforts also appear warranted concerning the enhancement of the
probabilistic approach for projecting future air emissions from oil spills. These efforts would
include the acquisition of spill data for years prior to 1987, the analysis of monthly and seasonal
oil data for trend indicators and a more thorough comparison of oil industry trend indicators and
oil spill trends.
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1967
1968
1989
1990
~ Fixed Foe. - Minor
Year
+ Fixed Foe. - Medium
A Pipeline - Medium
0 Pipeline - Minor
CH-93-12
Figure 3-6. Crude oil spill sources - minor and medium.
3-35
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40
35
30
25
20
15
10
5
0
1987
1990
1988
1989
Year
~ Fixed Foe-Major + Hpefine-Uajor $ Combined Sources
Figure 3-7. Crude oil spill sources • major and combined.
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TABLE 3-6. OIL INDUSTRY OUTLOOK INDICATORS
Indicator
Units
Source
Years
Gross National Product (1982 $)
billion S
R. Beck
1989-95
U.S. Petro Demand (data)
U.S. Petro Demand (forecast)
1,000 bbl/day
1,000 bbl/day
Basebook
R. Beck
1976-89
1989-95
U.S. Oil Refining Throughputs
World Oil Refining Throughputs
1,000 bbl crude/day
1,000 bbl crude/day
R. Beck
R. Beck
1980-89
1980-95
U.S. Active Oil Rigs (data)
U.S. Active Oil Rigs (forecast)
number
number
R. Beck
R. Beck
1979-89
1989-95
U.S. Producing Wells (data)
U.S. Producing Wells (forecast)
number
number
R. Beck
R. Beck
1981-89
1989-95
U.S. Petro Refining (data)
U.S. Petro Refining (forecast)
% capacity
% capacity
Basebook
Forecasts
1976-89
1990-91
U.S. Petro Imports (data)
U.S. Petro Imports (forecast)
1,000 bbl/day
1,000 bbl/day
R. Beck
R. Beck
1979-89
1989-95
U.S. Petro Pipeline Transport
U.S. Crude Pipeline Transport
U.S. Crude Ship Transport
109 ton-miles
109 ton-miles
109 ton-miles
Basebook
R. Beck
R. Beck
1976-88
1976-87
1976-87
Source: References 18 and 19
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700
600
500
400
300
200
100
1976 1977 1978 1979 1980 1981 1982 1983 198+ 1985 1986 1987 1988
Year
~ Petro Pipeline + Crude Oil Pipeline © Crude Oil Ship
Figure 3-8. Major domestic petroleum transport
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68 i 1 1 I l I I I l I I | l I I I l I l I
1976 I 1978 I 1980 I 1982 I 198+ I 1986 I 1988 I 1990 I 1992 I 199+ I
1977 1979 1981 1983 1985 1987 1989 1991 1993 1995
Year
~ R. Beck data + R. Beck forecost
Figure 3-9. U.S. refineries operating level.
3-39
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There are also several policy issues to be resolved. The first is the treatment of some oil
spills as point source emissions and other spills as area source emissions. The second is
determining which offshore oil spills that are included in inventories will be treated as a function
of distance from the coast or in terms of potential impact on geographic areas near coastlines.
It is proposed that oil spills at point source facilities be handled as point source emissions
within the AIRS or SIP point source inventory database. This strategy will eliminate the question
of what cutoff level to use to consider a spill a point source when the definition of a major
source may vary with the severity of an area's nonattainment status. However, this strategy does
imply that even major spills elsewhere (e.g., from a pipeline rupture) would always be treated
as area sources. Also, treating spills at point source facilities as identifiable point source
emissions will require additional SCCs. The number and type of these additional codes need to
be defined.
The treatment of offshore oil spills is an issue because preliminary data from the NRC
seem to indicate that such spills (from oil rigs and tankers) may be a significant fraction of the
incidents reported and quantity of material released.3 If this is indeed the case, some guidance
will need to be developed concerning when such offshore events are likely to have a significant
impact on near coastal land areas. This guidance might need to consider several factors such as
the distance offshore, magnitude of the spill and prevailing conditions (e.g., tides and winds).
Specific recommendations include the following:
• Compare estimates of spills for point source facilities with those obtained using
modifications of the area source methodologies.
• Contact experts on volatilization and combustion of oil spills for their best assessments
of the important factors for emission rates and quick and rough estimates of emission
factors.
• Investigate the availability of sources of information on such items as the area of oil
spills, the types of cleanup and the amount of material recovered.
• Analyze oil spill incident data and oil volume data.
• Conduct in-depth comparisons between oil industry indicators and oil spill data in order
to choose the more appropriate indicators.
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Acquire monthly oil spill data to examine seasonal trends for the most appropriate
indicators.
Acquire and analyze oil spill data for states or local areas having the largest number of
oil spills.
Compare the rough factors provided by the experts with those from modified AP-42
emission factors and the results from more sophisticated models.
Create a table or other handy reference of reasonably reliable and simple sets of
categorical emission factors.
Investigate the differences between the smoke/particulate production rates determined
from controlled oil fires and uncontrolled (Kuwait) oil fires.
No volume fraction evaporated versus exposure data have been identified for
hydrocarbons other than crude oil. Depending on the importance of other hydrocarbons
(especially gasoline and diesel fuel) to the emissions inventory, the availability of such
data for other hydrocarbons should be investigated. The estimation techniques given for
gasoline and diesel fuel should be verified against these data. If necessary, additional
measurements should be obtained.
An error analysis could be performed for the molecular weight methodologies of gasoline
and diesel fuel. This analysis would provide a better estimate of the minimum,
maximum, and average error associated with all the simplifying assumptions used to
derive Fv vs. 0 curves from Equation 10.
A more detailed analysis and presentation of the molecular weight methodologies for
gasoline and diesel fuel could be provided so that readers may determine their own Fv vs.
0 curves. Additional work by the reader may then be done to experimentally verify their
results.
Emission factors could be developed using the current methodology and assuming certain
case scenarios. For example, one could assume an oil spill occurred at an ambient
temperature of 75°F with a wind speed of 10 knots and construct a table of emission
factors that vary according to time and spill volume/area. Many of these tables could be
derived by developing different case scenarios.
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REFERENCES
1. U.S. Environmental Protection Agency. The Emergency Response Notification System.
EPA9360.0-21 (NTIS PB90-249715). Office of Emergency and Remedial Response.
Washington, DC. August 1989.
2. U.S. Environmental Protection Agency. Selected Data on Oil and Hazardous Substance
Release Notifications. Emergency Response Division, Emergency Response Notification
System. Washington, DC. January 7, 1991.
3. Personal communication. Wallace, K., National Response Center, to Stanley Sleva,
Alliance Technologies Corporation, Chapel Hill, NC, September 20, 1991. Information
from the NRC database concerning spills.
4. Memorandum and Attachments. Boyd, James D., Executive Officer, California Air
Resources Board to Donald R. Irwin, Office of Emergency Services, State of California,
March 16, 1990. Air Pollution Study of Oil Spill.
5. U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors.
Fourth Edition and Supplements, AP-42. Research Triangle Park, NC. September 1985
through September 1991.
6. Stiver, W., and D. Mackay. "Evaporation Rate of Spills of Hydrocarbons and Petroleum
Mixtures," Environmental Science and Technology, Vol. 18, No. 11. 1984.
7. Federal Emergency Management Agency. Handbook of Chemical Hazard Analysis
Procedures. Washington, DC.
8. Mackay, D., and A. Yeun. "Mass Transfer Coefficient Correlations for Volatilization of
Organic Solutes from Water," Environmental Science and Technology, Vol. 17, No. 4.
1983.
9. Little, R.C. "Chemical Demulsification of Aged, Crude Oil Emulsions," Environmental
Science and Technology, Vol. 15, Number 10. 1981.
10. Personal communication. Ferek, R., University of Washington, to Ken Dufner, Alliance
Technologies Corporation, Chapel Hill, NC, November 18, 1991. Kuwait Oil Fires
Particulate Emission Factors.
11. Brenner, B.A., et al. "Polycyclic Aromatic Hydrocarbon Emissions from the Combustion
of Crude Oil on Water," Environmental Science and Technology, Vol. 24, No. 9. 1990.
12. Evans, D., et al. Burning, Smoke Production, and Smoke Dispersion from Oil Spill
Combustion. NIST report NISTIR 89-4091. May 1988. Issued October 1989.
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13. Evans, D., et al. Environment Effects of Oil Spill Combustion. NIST report NISTIR 88-
3822, September 1987. Issued September, 1988.
14. Evans, D., and E.J. Tennyson. In-Situ Burning -- A Promising Oil Spill Response Strategy,
Seventh Symposium on Coastal and Ocean Management. Long Beach, CA. July 8-12,
1991.
15. Day, T., et al., "Emissions from In Situ Burning of Crude Oil in the Arctic", Water, Air,
and Soil Pollution, Vol. 11, 139-152. 1979.
16. National Fire Protection Association. Fire Protection Handbook, 13th Edition. 1969.
17. Burgess, D.S., J. Grumer, and H.G. Wolfhard. Burning Rates of Liquid Fuels in Large
and Small Open Trays. International Symposium on the Use of Models in Fire Research.
W. G. Berl (editor). National Academy of Sciences, National Research Council.
Publication 786, 1959.
18. Predicasts Basebook. Predicasts, Inc. Cleveland, OH. 1990.
19. Beck, R. J. Oil Industry Outlook. Pen Well Publishing Company. Tulsa, OK. November
1990.
20. Predicasts Forecasts. Predicasts, Inc. Cleveland, OH. 1991.
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SECTION 4
PETROLEUM VESSEL LOADING AND UNLOADING
BACKGROUND
In 1989, 52.4 percent of the crude oil and 35 percent of the refined petroleum products
were transported in the United States by water carriers.1 This waterborne traffic comprises both
foreign and domestic carriers. Foreign traffic consists mainly of imports of foreign crude oil
carried by ocean-going tankers. Domestic traffic includes all commercial traffic between points
in the United States (including Alaska, Hawaii, Puerto Rico, the Virgin Islands and Guam).2
Different types and sizes of vessels are used to transport crude oil and other petroleum products
depending on the length of haul. Short-haul coastal trade is serviced primarily by small, shallow-
draft coastal tankers and ocean-going tug-barge units, and longer-haul trade is serviced by deep-
draft tankers. Inland trade is serviced primarily by inland tank barges pushed by towboats.
Towboats represent the second largest component of the domestic petroleum product
transportation sector and are exceeded only by pipelines.
The primary distribution system gathers crude oil, transports it to refineries, refines it into
products and delivers those products in bulk to the secondary distribution system. In the
waterborne component of the system, barges are used to move crude oil from lease tanks (in
which oil from a producing well is accumulated) and deliver it into intermediate storage for
further movement to refining facilities. Crude oil from foreign sources enters the primary system
through tankers and barges at marine terminals and refineries. Exports of crude oil are allowed
only for the following activities: (1) crude oil derived from fields under the state waters of
Alaska's Cook inlet, (2) domestically produced crude oil destined for Canada and (3) crude oil
shipments to U.S. territories. Once delivered to a refinery, crude oil is converted to various
products. Tankage is required at refineries to receive and hold both unfinished oils and finished
products. Finished products exit the refinery through the primary product distribution, which
consists of facilities similar to those in the crude oil distribution system: terminals to store
products for further distribution, barges and tankers.
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Under current air quality regulations, emissions from tank vessels are generally not subject
to controls. However, several states are considering implementing controls in order to meet
federal air quality standards for ozone.
EMISSIONS GENERATION
Activities
Evaporative emissions from marine vessels result from three processes: loading, ballasting
and transit. Loading-loss emissions occur as organic vapors in empty cargo tanks are displaced
to the atmosphere by the liquid being loaded into the tanks. Ballasting loss emissions occur as
organic vapors in empty cargo tanks are displaced to the atmosphere by the water pumped into
the tank. Transit losses occur while vessels are underway or are fleeted.
Loading Losses
During the loading operations, turbulence and vapor/liquid contact result in vapor
generation and loss. These vapors are a composite of (1) vapors formed in the empty tank by
evaporation of residual product from previous loads, (2) vapors transferred to the tank in vapor
balance systems as product is being unloaded and (3) vapors generated in the tank as the new
product is being loaded.
Loading losses depend on the method of loading. One such method is splash loading, in
which the fill pipe dispensing the cargo is lowered only partway into the cargo tank, resulting
in high turbulence during loading and subsequent high levels of vapor generation and loss. A
second method of loading is submerged loading. In submerged loading, the fill pipe extends
almost to the bottom of the cargo tank or a permanent fill pipe is attached to the cargo tank
bottom. Submerged loading significantly controls liquid turbulence, resulting in much lower
vapor generation than encountered during splash loading. In the case of tankers and barges, all
loading activities use submerged loading methods.3
Cargo carriers may be designated to transport only one product (dedicated service) or may
switch loads. Prior to loading, if the carrier has transported volatile liquids and has not been
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vented, the carrier tank may contain volatile organic vapors which are expelled during the loading
operation. These vapors depend on the physical and chemical characteristics of both the previous
and new cargos.
Most U.S. harbors are too shallow to receive large tankers. Instead, these tankers must
remain outside the harbor area and off-load their cargo to smaller vessels in a process known as
lightering. Approximately 60 million tons of cargo is lightered at U.S. ports annually. Since
most lightering occurs more than 30 miles offshore, emissions from these operations are well
dispersed before reaching the land. However, nearly one-third of the lightered cargo, mainly
crude oil, was transferred nearer to shore in 1985.4
Ballasting Losses
Certain carriers, such as some crude oil tankers, are frequently used in one-way service
only. The return trip is usually with an unloaded ship. In this case, the ship must be ballasted
for stability and maneuverability. Ballasting is defined as filling the cargo tank compartments
with sea water after the cargo has been unloaded in order to stabilize the empty tanker during
subsequent voyages. The ballasting emissions occur as vapor in the empty cargo tank is
displaced to the atmosphere by the water pumped into the tank. It is estimated that
approximately 30 percent of the volume of the tanker is filled with ballast water. In addition,
it is estimated that in 1985, 5.8 percent of foreign vessels and 4.6 percent of U.S. vessels did not
have equipment to prevent ballasting emissions.4
Ballasting emissions will diminish in the future because most tankers built since 1980 are
required by domestic law and international agreement to use segregated ballast tanks, preventing
emissions of vapors due to ballasting.4
Transit Losses
In addition to loading and ballasting losses, losses occur while the cargo is in transit.
Transit losses can be thought of as breathing losses from petroleum storage tanks at bulk
terminals. These emissions are small and occur mainly away from ports while vessels are
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underway, or, in the case of barges, while they are fleeted.4 No estimates of the time spent in
transit were located.
Regional and Seasonal Characteristics
Emissions from loading and unloading petroleum products and crude oil from marine
vessels are concentrated in coastal areas, areas surrounding the Great Lakes and areas adjacent
to ports on inland waterways. Few seasonal variations are expected except in those areas where
wintertime frozen waters make ports inaccessible, such as in Alaska and the Great Lakes area.
Pollutants
Pollutants Emitted
The 1985 National Acid Precipitation Assessment Program (NAPAP) inventory estimated
that 29,564 TPY of VOC were emitted from marine vessels handling petroleum products and
crude oil.5 AP-42 reports that nonmethane-nonethane VOC emission factors for crude oil vapors
have been found to range from approximately 55 to 100 weight percent of the total organic
factors.3 AP-42 also recommends that when specific vapor composition information is not
available, the VOC emission factor can be estimated by taking 85 percent of the total organic
factor.6 Methane and ethane have been found to constitute a negligible weight fraction of the
evaporative emissions from gasoline.7,8
The Marine Board estimates that hydrocarbon vapor emissions displaced by filling vessel
tanks totaled 56,600 metric tons in the United States in 1985 (about 0.2 percent of national VOC
emissions). About 95 percent of the emissions were from crude oil and gasoline cargoes, two-
thirds came from inland barges and the remainder from ocean-going barges and tankers.4
Point/Area Source Cutoff
Although there are certain ports where handling of crude oil and other petroleum products
may result in large emissions, annual VOC emissions at most ports would not exceed 100 tons.
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Emissions from petroleum vessel loading and unloading operations generally should be
considered area sources.
SOURCES OF DATA
Activity
Several data sources are available on movement of crude oil and other petroleum products,
tonnage shipped and received, and capacities of refineries and bulk terminals at the national,
regional, Petroleum Administration for Defense (PAD) District, state and local levels.
Appendix C includes a listing of the available activity data at each level. Brief descriptions of
the data sources are provided in the following sections.
Water Resources Support Center
Waterborne Commerce of the United States is a five-part annual publication obtained
through the U.S. Department of the Army, Corps of Engineers' Water Resources Support Center.9
It contains the most detailed statistics available to the public on the movement and throughput
of foreign and domestic cargo and vessels at the ports and harbors of the United States. In the
document, petroleum products are disaggregated into the following classes: crude oil; gasoline;
jet fuel; kerosene; distillate fuel oil; residual fuel oil; lubricating oils and greases; naphtha,
mineral spirits and other solvents; and liquefied petroleum gases. The document also provides
statistics on the number of tankers and barges, their drafts and their direction of travel. Imports
include inbound merchandise for direct consumption and entries into custom bonded storage
warehouses. Shipments of domestic merchandise to other countries and re-exports of foreign
merchandise are termed exports. Transit merchandise is treated as an import when unloaded from
a vessel and as an export when loaded on a vessel.
Domestic traffic includes all commercial movements between points in the United States,
Puerto Rico and the Virgin Islands. Domestic traffic is divided into coastwise, lakewise and
internal. Coastwise traffic represents the portion of domestic traffic that occurs over the ocean,
the Gulf of Mexico and between Great Lakes ports and seacoast ports when transport is over the
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ocean. Lakewise traffic occurs between U.S. ports on the Great Lakes. Inland traffic includes
traffic between ports wherein the entire movement takes place on inland waterways. Also
included in inland traffic are movements involving transport on both inland waterways and waters
of the Great Lakes, and movement between offshore installations and inland waterways. Finally,
local traffic includes movements within the confines of a port. However, it is not known whether
lightering activities are considered as part of the local component of traffic movement.
Moreover, while Waterborne Commerce of the United States actually includes data on shipments
and receipts and data on types of vessels, it does not actually include the type of product that
each vessel carried.
The Water Resources Support Center also handles special requests for waterborne
commerce statistics through its Data Request Office. This office was contacted to investigate the
possibility and cost of obtaining, through special request handling, port- and harbor-specific
information regarding shipping and receiving operations.10 Requested data parameters included
the following:
• Crude oil and other petroleum products shipped and received at each harbor aggregated
by fuel type and type of vessel (i.e., tankers versus barges)
• National, regional, PAD District or state estimates of the percentage of each fuel type
carried by barges versus tankers
• Refinery receipts of crude oil and petroleum products by method of transportation (barges
versus tankers)
• Refinery shipments of crude oil and petroleum products by method of transportation
(barges versus tankers)
A sample of the data was received which consisted of estimates of petroleum products
shipped from New Jersey to every state. For some products shipped, only one shipping company
may be operating on certain lines. If the Data Request Center were to reveal the tonnage for
each product shipped, the Center might be compromising the confidential business information
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for that particular company. As a result, the Data Request Center prefers to submit the data as
a lump sum without specifying the tonnage to each destination.
Energy Information Administration
The Petroleum Supply Annual is an annual report published by the U.S. Department of
Energy (DOE), Energy Information Administration (EIA). The report includes statistics on
imports and exports of crude oil and other petroleum products by PAD district and imports of
residual fuel oil by state of entry." In addition, it provides statistics on waterborne movements
of crude oil and petroleum products between PAD districts and statistics on number and capacity
of operable petroleum refineries by PAD district and state. Finally, the report includes data on
refinery receipts of crude oil by method of shipment (barge versus tanker, domestic versus
foreign) by PAD district.
National Petroleum Council
As part of the federal government's overall review of emergency preparedness planning,
the National Petroleum Council (NPC) completed a study in April 1989 to determine the
capacities of the nation's petroleum and gas storage and transportation facilities. The results of
the NPC study were presented in a five-volume comprehensive report titled Petroleum Storage
and Transportation. Appendix G of the report includes statistics on storage capacity of
petroleum terminals located on the U.S. inland waterway system and in the U.S. coastal and
Great Lakes ports.12 Petroleum products considered include crude petroleum, fuel oil, asphalt and
mixed products (i.e., all other petroleum products combined).
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U.S. Maritime Administration
The U.S. Maritime Administration (MARAD) reports national estimates of principal
commodities carried between U.S. ports by non-self-propelled tank barges.13 According to
MARAD, in 1985 41.4 percent of the barges carried gasoline (including additives), 18.5 percent
carried distillate oil, 17.6 percent carried residual oil, 6.4 percent carried crude petroleum, 4.9
percent carried jet fuel and 11.2 percent of the barges carried all other commodities. In addition,
MARAD provides regional estimates of barge activity. In 1985, 17.5 percent of total tonnage
moved by barges occurred in the Northeast, 12.3 percent over the Atlantic inland waterway, 30.3
percent over the Gulf inland waterways, 18.5 percent over the lower Mississippi, 4.3 percent over
the upper Mississippi, 8.4 percent over the Ohio River, 4.4 percent in California, 3.2 percent in
the Pacific Northwest and 1.2 percent in the Great Lakes area.
Stalsby/Wilson Press
The Stalsby/Wilson Press publishes the Stalsby's Petroleum Terminal Encyclopedia, a
listing of the major oil company terminals and independent terminal operators in the United
States and Canada, as well as selected major ports throughout the world.14 The encyclopedia
provides information on terminal characteristics including location, terminal receiving capabilities
{i.e., barge, tanker, etc.), method for out-loading at the terminal, storage capacity listed by
product, high and low water depths, berth length and products handled at the facility. The
encyclopedia is published every year and a half.
Emission Factors
AP-42
Emission factors for transportation and marketing of petroleum liquids are available in
Section 4.4 of AP-42 and are summarized in Table 4-1 of this report. In AP-42, evaporative
emissions from marine vessels are separated into three categories: loading losses, transit losses
and ballasting losses. Two classes of marine vessels are considered: (1) ships and ocean barges
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TAHLE 4-1. SUMMARY OF AF-42 EMISSION FACTORS3
tyh; oi; i.oss
GASOLINE
GASOLINE
<;
ASOLINI-:
CRUDE OIL
JET
DISTILLATE
RESIDUAL
ICT
IIVI' 13
KVI' 10
RVP 7
RVP5
KEROSENE
EUEI. No 2
OIL No 6
NAPHTHA
LOADING LOSSES: SHIPS
CI = Cg ~ C.
Ll = I2.46SPM/T
Ll = 12 I6SPM/T
Ll - I2.46SPM/T
U = I2.46SPM/T
CK = 1 84|0 449-0.42|MG/T
S = 0.2
S ^ 0.2
S = 0.2
S = 0.2
UNCLEANED-VOLATILE
2.6
2.6
2 6
C„ ^ 0.86
D ALL ASTRO - VOLATILE
1.7
1.7
1.7
Cn = 0.46
CLEANED - VOLATILE
1.5
15
1.5
Ca = 0.33
GAS FREE - VOLATILE
0.7
0.7
0.7
C. = 0.33
ANY CONDITION - NON VOLATII P.
0 7
0 7
0 7
C« = 0 33
GAS FREE - ANY CARGO
N/A
N/A
N/A
N/A
TYPICAL OVERALL SITUATION
IB
I.I
18
0 61
0.005
0 005
0 00004
0.5
LOADING LOSSES. I1ARCES
Ll = I2.46SPM/T
1.1 = 12 46SPM/T
Ll = 12.46SPM/T
Ll = 12.46SPM/T
S =* 0.5
S = 0.5
S " 0.5
S = 0.5
UNCI.EANED - VOLATILE
3 9
3.9
.3 9
N/A
ballasted - volatile
0
0
0
N/A
CLEANED - VOLATILE
N/A
N/A
N/A
N/A
OAS FREE - VOLATILE
N/A
N/A
N/A
N/A
ANY CONDITION - NON VOLATILE
N/A
N/A
N/A
N/A
GAS FREE - ANY CARGO
2
2
2
N/A
TYPICAL OVERALL SITUATION
3.4
J 4
3.-)
1
0 013
0 012
0.00009
1.2
DALLASTING LOSSES: SHIPS
l.li ^ 0 3hO.2PiO.OIPU.
FULLY LOADED
N/A
N/A
N/A
0.9
N/A
N/A
N/A
N/A
SHORT-LOADED
N/A
N/A
N/A
1.4
N/A
N/A
N/A
N/A
TYPICAL OVERALL SITUATION
N/A
0 8
N/A
II
N/A
N/A
N/A
N/A
IIAI.I.ASTING LOSSES: MAHGE.S
0
0
0
0
0
0
0
0
TRANSIT LOSSES: SHIPS
Li = 0.11'W
Ll = 0. IPW
l.i
- 0.IPW
l.i = 0.IPW
I.I = 0.1PW
l.i = 0 IPW
H = 0.IPW
U = 0.IPW
TYPICAL OVERALL SITUATION
N/A
2 7
N/A
1.3
0 005
0 005
3i10-5
0.7
TRANSIT LOSSES. MARGES
Ll = 0 IPW
1.1 = 0.11'W
Ll
0.1PW
l.i = 0.11'W
U = 0.1 r\V
Ll 0 IPW
Ll - 0.IPW
Ll = 0.1 PW
TYPICAL OVERALL SITUATION
N/A
2.7
N/A
1.3
0 005
0 005
J«l0-5
0.7
LI : Loading losses. lb/1000 gal of liquid loaded Fully loaded: Arrival ullage < 5 feel, typically 2 feet
$ : Saturation factor Short-loaded: Arrivnl ullage > 5 feet, typically 20 (ctl
K1 ; Molecular weight of vapors. Ih/lb-molc (Table 4.3-2 in AI*-42) Ship! Include oceou barges of nearly 40 feet draft
P : True vapor prendre of liquid loaded In psia (Tahle 4.3-2 in AP-42) Harget arc shallow drafted, 10-12 feel
T : Temperature of bulk liquid loaded, in R (P«460) Volatile products: true vapor pressure > l.Spsia
CI ; Total loading losses, ll>/1000 gal of crude oil loaded Ballasting; Typically, a vessel Is ballasted |5 to 40 percent of capacity
G : Vapor growth factor - 1.02
Lb : ballasting emission factor, in lb/1000 gal of ballast water
Ua : Arrival cargo true ullage, distance between the cargo surface level nud the deck level in feet
Ll : Transit loss from ships and barges, in lb*/week- 1000 gal trans|>oricd
\V : Demiiy of the condensed v«|w>r». In lb/gal (Table 4.3-2 In AP-42)
Ca : Arrivnl emission f»ei»»r. contributed by vn|«ors In the eiupiy innk compntlnicni prior to loading, lb/1000 gnl of liquid loaded
-------
with tank compartment depths of about 40 feet, and (2) shallow draft barges with compartment
depths of 10 to 12 feet. Petroleum products are separated into the following classes: gasoline,
Reid vapor pressure (RVP) 13; gasoline, RVP 10; gasoline, RVP 7; distillate fuel no. 2; residual
oil no. 6; crude oil, RVP 5; jet naphtha; and jet kerosene.
AP-42 provides an equation that estimates emissions from loading petroleum liquids other
than gasoline and crude oil as a function of the physical and chemical characteristics of the liquid
being loaded.
For gasoline, AP-42 provides emission factors specific to loading operation type.
Characteristics considered include vessel tank condition {i.e., uncleaned, ballasted, cleaned, gas-
freed, any condition), previous cargo (i.e., volatile, nonvolatile, any cargo) and type of vessel.
AP-42 also provides typical VOC emission factors to be used when vessel tank condition and
previous cargo are unknown.
Another equation has been developed specifically for estimating emissions from loading
of crude oil. In this equation, emission factors contributed by vapors in the empty tank
compartment prior to loading are added to generated emission factors contributed by evaporation
during loading to produce total crude oil loading loss. Arrival emission factors are available for
various cargo tank conditions. Generated emission factors are calculated as a function of the
physical and chemical characteristics of the crude oil being loaded. The computed total crude
oil loading losses represent total organic compounds. When specific vapor composition
information is not available, the VOC emission factor can be estimated as 85 percent of the total
organic factor.6
Because ballasting emissions occur as vapor in the empty cargo tank is displaced to the
atmosphere by water being pumped into the tank, the quantity of vapors emitted during
subsequent tanker loading is reduced. Tabulated emission factors, based on average conditions,
are available. VOC emissions average about 85 percent of total organic emissions resulting from
ballasting operations.3
Finally, transit losses are estimated using the same equation for barges and tankers.
AP-42 also provides emission factors based on average conditions that can be used when physical
and chemical characteristics of the fuel are unknown.
CH-93-12
4-10
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California Air Resources Board
The CARB developed a methodology to estimate hydrocarbon emissions associated with
marine petroleum loading and unloading.15 Emission factors used in this methodology are
summarized in Table 4-2. The emission factor for crude oil lightering is the same as for loading
and was obtained from a 1977 Western Oil and Gas Association (WOGA) study.16 The emission
factors for loading gasoline into tankers and barges and jet fuel into barges were obtained from
a CARB study.17 Emission factors for loading residual oil, ballasting crude oil and gasoline
vessels were taken from a 1980 study by Scott Environmental Technology, Inc.18 Table 4-3
includes other emission factors developed by Scott Environmental Technology used for both
ballasting and loading losses.
The following categories of emission sources are included in inventorying hydrocarbon
emissions from marine petroleum products.
• Tankers loading crude oil
• Tankers loading gasoline
• Tankers loading jet fuel
• Barges loading gasoline
• Tankers loading residual fuels
Data on the amounts of crude oil, gasoline, jet fuel and residual oil shipped from
California ports were obtained from the 1986 Waterborne Commerce of the United States. To
use these data for the 1987 inventory, the 1986 data were scaled to 1987 using ratios that CARB
developed based on 1986 and 1987 California Energy Commission data.19,20 21 In addition, based
on a survey of oil companies and marine operators conducted by CARB's Stationary Source
Division, it was assumed that 100 percent of the gasoline was loaded into tankers in the Los
Angeles/Long Beach harbors and that 64 percent of the gasoline was loaded into tankers and 36
percent into barges in the Bay Area.17 Moreover, 100 percent of the crude oil, residual oil and
jet fuel are assumed to be loaded into tankers in each of the two regions. Multiplying the 1987
adjusted shipment data by the percent of activity of barges and tankers results in estimates of the
tonnage of each petroleum product shipped by barges versus tankers. VOC emissions at each
CH-93-12
4-11
-------
TABLE 4-2. CARB EMISSION FACTORS
Fuel IVpe
Vessel
VOC Hydrocarbon Emissions
lb/1,000 gal
Crude Oil Loading
Gasoline Loading
Jet Fuel Loading
Residual Fuel
Crude Oil Ballasting
Gasoline Ballasting
Crude Oil Lightening
Tankers
Tankers
Barges
Tankers
Tankers
1.0
1.8
3.4
0.8
0.3
0.9
1.8
1.0
TABLE 4-3. SCOTT ENVIRONMENTAL TECHNOLOGY EMISSION FACTORS
LOADING/BALLAST EMISSIONS
Fuel Type VOC Hydrocarbon Emissions
lb/1,000 gal
Benzene 1.0
JP-4 0.6
JP-5 0.005
Kerosene 0.005
Mixed Chemicals 0.005
Lube Oil 0.005
Naphtha 0.3
Solvents 0.3
Distillate Oil 0.005
CH-93-12 4-12
-------
port can be estimated by multiplying the tonnage by the corresponding emission factors for
tankers or barges.
The following categories of emission sources are included in inventorying hydrocarbon
emissions from marine petroleum unloading (lightering and ballasting).
• Crude petroleum lightering
• Crude petroleum ballasting
• Gasoline ballasting
Data on the amounts of crude oil and gasoline unloaded at California ports were obtained
from the 1986 Waterborne Commerce of the United States. To use the data for the 1987
inventory, the 1986 data were scaled up using ratios developed by CARB based on 1986 and
1987 California Energy Commission data. In addition, it was assumed that 21 percent of vessels
carrying gasoline and 17 percent of those carrying crude oil are ballasted. Multiplying the
tonnage of each product unloaded at a harbor by the corresponding fuel density and ballasting
factors result in estimates of volumes of water ballasted during operation. Estimates of emissions
from ballasting were then obtained by multiplying the volume of water ballasted by the
corresponding ballasting emission factor for gasoline and crude oil.
METHODOLOGIES
Two potential methodologies have been developed for estimating emissions from
petroleum vessel loading and unloading operations. The key factor in these methods is to
estimate the share of crude and petroleum products carried by tankers as compared to barges for
each port and harbor in the United States. Such information is highly detailed and is not usually
available to the public. Thus, activity must be estimated at the state level and then allocated to
the harbor and port level.
CH-93-12
4-13
-------
Method I
In the first method, state-level estimates of crude oil and the different petroleum products
shipped (and received) in tankers versus barges can be obtained from the Data Request Office
of the Water Resources Support Center. As previously mentioned, not all the activity data may
be disclosed because confidentiality may be compromised. This matter is being pursued and
alternative uses for the data are being devised to minimize the impact of the excluded data on
overall estimates of pollutants. One such alternative would be to develop a national estimate of
the activities kept confidential (this may be provided by the Data Request Office in the future)
and then allocate the national estimate to different states based on state-level total capacity of
refineries obtained from the Stalsby's Petroleum Terminal Encyclopedia.14 State-level emissions
are estimated using the equations in Table 4-4, which were developed using the following
assumptions.
• It is estimated that approximately 30 percent of the volume of a tanker is filled with
ballast water.4
For foreign vessels carrying crude oil, 5.8 percent of the deadweight tons (dwt) of these
vessels does not have equipment to prevent ballasting emissions.4 Therefore, it is
assumed that 5.8 percent of the ballasting emissions will escape to the atmosphere (not
controlled).
For U.S. vessels carrying crude oil, 4.6 percent of the dwt of these vessels does not have
equipment that would prevent ballasting emissions.4 As a result, it is assumed that 4.6
percent of the ballasting emissions will escape to the atmosphere (not controlled).
Nearly 30 percent of the cargo shipped was lightered near the shore in 1985. Most of the
lightered cargo was crude oil.4 Assuming that 90 percent of the lightered cargo is crude
oil, it is concluded that 27 percent of crude oil and 3 percent of all other petroleum
products are lightered each year near the shore.
About 25 percent of the foreign fleet carrying petroleum products (other than crude oil)
does not have equipment to control ballasting emissions.4 As a result, it is assumed that
25 percent of the ballasting emissions from petroleum products is actually emitted to the
atmosphere.
CH-93-12
4-14
-------
TABLE 4-4. CALCULATIONS OF STATE-LEVEL VESSEL EMISSIONS
Cargo
Trade
Vessel
Loading
Ballasting
Lightering
Transit
Type
Type
Emissions
Emissions
Emissions
Emissions
Crude
Import
Tanker
0
EFx0.058x0.3xM/D
FFx0.27xM/D
EFxWxM/D
Crude
Export
Tanker
EFxM/D
0
0
0
Crude
Domestic
Tanker
EFxM/D
EFx0.046x0.3xM/D
EFx0.27xM/D
EFxWxM/D
Crude
Domestic
Barge
EFxM/D
0
0
EFxWxM/D
Other Products
Import
Tanker
0
EFx0.25x0.3xM/D
EFx0.03xM/D
EFxWxM/D
Other Products
Export
Tanker
EFxM/D
0
0
EFxWxM/D
Other Products
Domestic
Tanker
EFxM/D
EFx0.21 x0.3xM/D
EFx0.()3xM/D
EFxWxM/D
Other Products
Domestic
Barge
EFxM/D
0
0
EFxWxM/D
EF: Commodity-specific emission factor corresponding to the vessel type and type of loss obtained from AP-42, CARB, or Scott Environmental Technology
(Tables 1, 2 and 3)
-------
• About 21 percent of the U.S. fleet carrying petroleum products (other than crude oil) does
not have equipment to control ballasting emissions.4 As a result, it is assumed that 21
percent of the ballasting emissions from petroleum products is actually emitted to the
atmosphere.
• It is assumed that emission factors for lightering are the same as for loading.
• The VOC emission factor can be estimated by taking 85 percent of the total organic
factors.3
Once state-level pollutant estimates are obtained for crude oil and each petroleum product,
the estimates can be allocated to refineries and petroleum terminals based on storage capacities
listed in the Stalsby's Petroleum Terminal Encyclopedia.'4 Alternatively, state-level pollutant
estimates for crude oil and each petroleum product can be allocated to refineries and petroleum
terminals based on the total tonnage of each product shipped (and received) as reported in the
Waterborne Commerce of the United States.9
As mentioned earlier, if not all the state-level tonnages shipped and received are disclosed,
national estimates of tonnages kept confidential (obtained from the Data Request Center for each
type of trade, cargo, and vessel) are allocated to different states based on the capacities of state
refineries.
(State estimate) ^(National estimate)x ^tate ^eve^ Capacity (1)
National-level capacity
These state-level estimates of fuel tonnages shipped and received are then added to the detailed
state-level data provided by the Data Request Center to determine total state shipment and receipt
of fuels by type of fuel, vessel, and trade. The algorithms for estimating emissions based on type
of trade, cargo, and vessels are presented in Table 4-5. Emissions are finally apportioned to ports
and harbors using Waterborne Commerce data on shipment and receipt of port-level commodities
by type of fuel.
CH-93-12
4-16
-------
TABLE 4-5. CALCULATIONS OF TOTAL VESSEL EMISSIONS
Activity
Cargo
TYade
Vessel T^pe
Loading
Ballasting
Lightering
Transit
Type
Emissions
Emissions
Emissions
Emissions
Import
Crude
Foreign
Foreign Tanker
0
EFx0.058x0.3xM/D
EFx().27xM/D
EFxWxM/D
Import
Crude
Foreign
Domestic Tanker
0
EFx0.046x0.3xM/D
EFx0.27xM/D
EFxWxM/D
Export
Crude
Foreign
Domestic Tanker
EFxM/D
0
EFx0.27xM/D
0
Shipment
Crude
Domestic
Tanker
EFxM/D
0
EFx0.27xM/D
0
Receipt
Crude
Domestic
Tanker
0
EFx0.046x0.3xM/D
EFx0.27xM/D
EFxWxM/D
Shipment
Crude
Domestic
Barge
EFxM/D
0
0
0
Receipt
Crude
Domestic
Barge
0
0
0
EFxWxM/D
Import
Products
Foreign
Foreign Tanker
0
EFx0.25x0.3xM/D
EFx().03xM/D
EFxWxM/D
Import
Products
Foreign
Domestic Tanker
0
EFx0.21 x0.3xM/D
EFx0.03xM/D
EFxWxM/D
Export
Products
Foreign
Domestic Tanker
EFxM/D 0
EFx0.03xM/D 0
Export
Products
Foreign
Foreign Tanker
EFxM/D
0
EFXO 03XM/D
0
Shipment
Products
Domestic
Tanker
EFxM/D
0
EFx0.03xM/D
0
Receipt
Products
Domestic
Tanker
0
EFx0.21 x0.3xM/D
EFx0.03xM/D
EFxWxM/D
Shipment
Products
Domestic
Barge
EFxM/D
0
0
0
Receipt
Products
Domestic
Barge
0
0
0
EFxWxM/D
EF: Commodity-specific emission factor corresponding to the vessel type and type of loss obtained from AP-42, CARB, or Scott Environmental Technology
(Tables 9, 10, and 11)
M: Cargo weight in tons
D: Density of product carried in tons/1,000 gal
W: Time spent in transit in weeks
-------
(.Port Tonnage)..
(Port Emissions) ..=( State Emissions)., x -
y y (State Tonnage)^
where
i = type of trade
j = type of fuel
Method II
After loading a river barge, a Coast Guard-certified "tankerman" places a loading
manifest aboard that includes information on the product loaded, the quantity loaded, the
loading port and the destination port. These cargo handling arrangements also apply to
oceangoing barges.4 For tanker loadings, additional information collected during the
loading operation will include ullage and cargo temperature. If state agencies can obtain
these data from individual ports and harbors, emissions can be estimated directly at the
local level. By using these data, more accurate emissions estimates can be computed
because it will be possible to apply the equations in AP-42 instead of using the average
evaporative emission factors. County-level estimates of pollutants emitted are obtained
by summing emissions from all facilities located within a county.
DATA ISSUES
AP-42 provides equations that estimate loading and transit losses from ships and
barges, and ballasting losses from ships. However, to apply these equations, information
on the physical and chemical characteristics of the product being shipped should be
known. These characteristics include molecular weight of vapor, true vapor pressure of
liquid loaded, temperature of bulk liquid, density of the condensed vapors and arrival
ullage. In addition, information on the vessel condition (uncleaned, ballasted, gas-free)
is also required to apply these equations. As a result, most of the emission factors
provided in AP-42 can be used only when Method II is applied, which requires the
cooperation of officials at local harbors and ports.
CH-93-12
4-18
-------
No information on time spent in transit was located. Such information may best
be obtained from local port authorities. Alternatively, it may be appropriate to make a
judgement regarding how long it would take a vessel to complete its journey if the state
of origin and destination were known. Information on states of origin and destination is
included in the data provided by the Water Resources Support Center. In all cases, these
emissions are small and occur mainly away from ports while vessels are underway or
while barges are fleeted.4
Finally, if fuel tonnage data are available for some petroleum products not covered
in AP-42, the emission factor developed by Scott Environmental Technologies (labeled
Mixed Chemical), is recommended. It is not known if either the molecular weight or
vapor pressure corrections were applied to this emission factor.
CH-93-12
4-19
-------
REFERENCES
1. U.S. Department of Transportation. National Transportation Statistics, Annual
Report. Research and Special Programs Administration. Washington, DC. July
1990.
2. U.S. Department of Energy. Petroleum Storage and Transportation, Volumes I
through V: Petroleum Inventories and Storage. National Petroleum Council.
Washington, DC. April 1989.
3. U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission
Factors, Fourth Edition and Supplements. AP-42. Office of Air Quality Planning
and Standards. Research Triangle Park, NC. September 1985 through September
1991.
4. National Research Council. Controlling Hydrocarbon Emissions from Tank Vessel
Loading. Marine Board. Washington, DC. 1987.
5. Saeger, M.L., et al. The 1985 NAPAP Emissions Inventory (Version 2):
Development of the Annual Data and Modelers' Tapes, EPA-600/7-89-012a (NTIS
PB91-119669). U.S. Environmental Protection Agency. Research Triangle Park,
NC. November 1989.
6. LaFlam, G.A. Revision of Marine Vessel Evaporative Emission Factors. Pacific
Environmental Services, Inc. Durham, NC. November 1984.
7. LaFlam, G.A., S. Osbourn and R.L. Norton. Revision of Tank Truck Loading
Hydrocarbon Emission Factors. Pacific Environmental Services, Inc. Durham, NC.
May 1982.
8. Burklin, C.E., et al. Background Information on Hydrocarbon Emissions from
Marine Terminal Operations, EPA-450/3-76-038a and EPA-450/3-76-038b (NTIS
PB 264381 and PB 264382). U.S. Environmental Protection Agency. Research
Triangle Park, NC. November 1976.
9. U.S. Department of the Army. Waterborne Commerce of the United States,
Calendar Year 1988, Parts 1 through 5. Army Corps of Engineers, Water
Resources Support Center. Ft. Belvoir, VA. June 1990.
10. Letter. Ramadan, W., Alliance Technologies Corporation, to Waterborne
Commerce Statistics Center, U.S. Army Corps of Engineers, New Orleans, LA.
August 20, 1991. Special request for waterborne commerce statistics.
11. U.S. Department of Energy. Petroleum Supply Annual 1989. Energy Information
Administration. Washington, DC. May 1990.
CH-93-12
4-20
-------
12. U.S. Department of Energy. Petroleum Storage and Transportation, Volume II:
System Dynamics. National Petroleum Council. Washington, DC. April 1989.
13. U.S. Maritime Administration, Domestic Waterborne Trade of the U.S.. Office of
Domestic Shipping. Washington, DC. 1985.
14. Stalsby's Petroleum Terminal Encyclopedia, 1986-1987. Stalsby/Wilson Press.
Houston, TX. 1987.
15. California Air Resources Board. Methods for Assessing Area Source Emissions in
California. Emission Inventory Branch. Sacramento, CA. September 1991.
16. Hydrocarbon Emissions During Marine Loading of Crude Oils. Western Oil and
Gas Association. August 1977.
17. California Air Resources Board. Report to the Legislature on Air Pollutant
Emissions from Marine Vessels. Sacramento, CA. June 1984.
18. Scott Environmental Technology, Inc. Inventory of Emissions from Marine
Operations Within the California Coastal Waters. Preliminary Draft.
Plumsteadville, PA. November 1980.
19. California Energy Commission. Quarterly Oil Report - Second Quarter 1987.
Sacramento, CA. September 1987.
20. California Energy Commission. Quarterly Oil Report - Second Quarter 1988.
Sacramento, CA. September 1988.
21. Rodman, Dale. California Petroleum Shipments of Major Marketers by
Transportation Method. California Energy Commission. Sacramento, CA. April
1989.
CH-93-12
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SECTION 5
COOLING TOWERS
BACKGROUND
Cooling towers are heat exchangers which are used to dissipate large heat loads to the
atmosphere.1,2 They are used in a variety of industrial and commercial settings, including the
following:2
• In power generation cycles requiring the condensation of a working fluid, such as
steam, to complete the cycle and return the condensed fluid to the boiler. The
cooling tower is used to dissipate the heat of condensation to the environment.
• In process cooling, such as in the petrochemical and various materials production
industries which must condense and/or cool the product to complete a process step
or finish the operation.
• In air conditioning cycles which require both the dissipation of the heat removed
from the air-conditioned space and the dissipation of the working energy required
to operate the air conditioning equipment, such as a chiller.
Cooling towers may range in size from less than 5 x 106 Btu/hour (5.3 x 106 kJ/hour) for small
air conditioning cooling towers to over 5,000 x 106 Btu/hour (5,275 x 106 kJ/hour) for large
power plant cooling towers.1,2 All cooling towers that are used to remove heat from an industrial
process or chemical reaction are referred to as industrial process cooling towers (IPCTs). Towers
that are used to cool heating, ventilation and air conditioning (HVAC) and refrigeration systems
are referred to as comfort cooling towers (CCTs).3
Cooling towers are classified primarily as either wet towers or dry towers (although some
hybrid wet-dry combinations exist) and can be further subclassified by type of draft and/or
location of draft relative to the heat transfer medium, type of heat transfer medium, relative
direction of air movement, and type of distribution system. Dry cooling towers rely on the
sensible exchange of heat between the process and the air passing through the cooling tower.
Wet or evaporative cooling towers may be used when water is used as the heat transfer medium.
Wet cooling towers rely on the latent heat of evaporation of water to exchange heat between the
process and the air passing through the cooling tower.1,2
CH-93-12
5-1
-------
Wet cooling towers typically have a wetted media, or fill, to promote evaporation by
providing a large surface area and/or creating many water drops with a large cumulative surface
area. Because the cooling water and the air passing through the tower are in direct contact in
wet cooling towers, some of the water may be entrained in the air stream and carried out of the
tower as "drift" droplets. The constituents of the drift droplets are classified as emissions.1,2
Some industrial cooling towers for refineries have been included in the point source
inventory. However, a review of the AIRS/Facility Subsystem (AFS) SCC listing showed cooling
tower SCCs only for refineries; cooling tower SCCs for other industries were not found.4 No
methodologies exist for including cooling tower emissions in the area source inventory.
This chapter discusses only wet (evaporative) cooling towers as sources of emissions and
focuses on comfort cooling towers, although industrial cooling towers are addressed.
Cooling Tower Design and Operation
As described earlier in this chapter, comfort cooling towers are used to maintain a
specified environment or refrigeration system, while industrial process cooling towers are used
to control the temperatures of process fluids in industrial production units. The major
components of a cooling tower include the fan or fans, the fill material, the water distribution
deck or header, the drift eliminator, the structural frame and the cold water basin. Other
components affecting cooling tower operations include the pumps and pipes necessary to circulate
the cooling water through the cooling tower and heat exchanger loops.35 CCTs are most
commonly mounted at ground level near a building or on the roof of the building they serve.
A CCT is most likely to operate during the spring, summer and fall.5
Cooling towers are designed with mechanically induced-, mechanically forced- or natural-
draft airflow. Induced-draft is provided by propeller-type axial fans located in the stack at the
top of the tower. Forced-draft towers are usually smaller than induced-draft towers and have
either centrifugal fans located at the base of the tower or axial fans located on the side of the
tower. Natural-draft towers rely on buoyancy or air currents created by temperature differences
between the air in the tower and the atmosphere.3,5 Natural-draft airflow is not used in CCTs.5
The direction of airflow through a mechanical-draft tower can be either crossflow or
counterflow. Crossflow refers to horizontal airflow through the fill, while counterflow refers to
CH-93-12
5-2
-------
upward vertical flow.3,5 Diagrams of crossflow and counterflow cooling towers are shown in
Figure 5-1. The fill material is used to maintain an even distribution of water across the
horizontal plane of the tower and create as much water surface area as practical to enhance
evaporation and sensible heat transfer.3
Water droplets and the dissolved and suspended solids they contain that are entrained in
the air and emitted from the cooling tower stack are referred to as drift. Drift eliminators are
installed at the exits of the fill sections to reduce the drift in the exiting airflow. The drift
removal efficiency of a drift eliminator is a function of its design.5 The performance of a drift
eliminator is affected primarily by the droplet or particle size and the airflow velocities through
the drift eliminator. Small droplets result from both evaporation of larger droplets and the
physical breakage of larger droplets into small droplets. The rate of evaporation and the size of
droplets created are affected by the water distribution system, the type of fill, the type of tower,
the meteorological conditions, and the temperature of the recirculating water.3
There are four major types of drift eliminators: blade-type; waveform; cellular or
honeycomb; and herringbone (similar to the blade-type). Blade-type and herringbone drift
eliminators are typically the least efficient. Waveform drift eliminators are moderately efficient;
cellular units are the most efficient.5 Figure 5-2 shows various drift eliminator designs.
HVAC and Refrigeration Systems
HVAC and refrigeration systems are composed of the cooling distribution system, a heat
rejection system and the refrigeration machine. The refrigeration machine is commonly referred
to as a chiller system. The cooling distribution system consists of the air handling units. The
heat rejection system consists of the cooling tower. The chiller system can be either a
compression-cycle or an absorption type.5
The required cooling tower size for a given air conditioning load depends on the type of
chiller system used. Water is evaporated at the rate of 1.9 gallons and 3.7 gallons per hour per
ton of cooling in the cooling towers used with compression and absorption systems, respectively.5
CH-93-12
5-3
-------
K* OvrfU*
0-*-0
mini
W ',7^ />7^
Watar
OulM
LTiTiij
-=^=^=u
Ki
Air OutM
1 1 1 1 1
Waa*
Inhat
FJI*^
=~~~~~ J
Fan
W««r
Induotd Drrt Cojnfrfloo Tww
roread Dnrft Courtarilowr Tew
Ait OutM
Fan
WH«
n 1 1 1 I I n
Waia*
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Walar Inlal
Waiw OuBat
Induoad Draft CnaaAow Tw«
Foroad DraJI Croaa Rom Toaur
Figure 5-1. Crossflcw and counterflow cooling towers.2
5-4
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.wood Lavn
9too»s
HERRINGBONE
(BLADE-TYPE)
ELIMINATOR
WAVEFORM
ELIMINATOR
CELLULAR
ELIMINATOR
Figure 5-2. Designs of various drift eliminators.3
5-5
-------
EMISSIONS GENERATION
The two types of emissions from cooling towers are drift and evaporative. Drift emissions
are water droplets containing dissolved and suspended solids. Evaporative emissions are made
up of water. The dissolved and suspended solids in drift droplets are the result of various
chemical treatment programs. The magnitude and formation of drift depend on tower design,
operation and maintenance.
Activities
Chemical Treatment5
Chemicals are added to the recirculating cooling water to inhibit the corrosive effects of
water, control the rate of scaling and fouling, and control the growth of microorganisms in the
cooling tower water and the heat exchangers. As evaporation occurs during cooling, the chemical
constituents of the water become concentrated. To maintain acceptable percentages of dissolved
and suspended solids, a portion of the recirculated water is intentionally discharged (blowdown).
In addition, as water cascades through the tower, some is entrained and emitted from the stack
as drift. Fresh water is added to make up for the losses resulting from the evaporation,
blowdown and drift.
Typical water treatment chemicals include a corrosion inhibitor, an antiscalant, an
antifoulant, a dispersant, a surfactant, a biocide and an acid and/or caustic soda for pH control.
The quality of the cooling tower water supply directly affects the type and quantity of chemicals
required to maintain satisfactory protection. Major water chemistry parameters affecting the type
of chemical treatment selected include pH, calcium hardness (calcium ion concentration),
alkalinity (bicarbonate, carbonate, and hydroxide ions), chloride, sulfate, silica, dissolved solids
(conductivity), and suspended solids.
Water quality also affects the number of cycles of concentration that can be maintained.
The number of cycles of concentration is defined as the ratio of conductivity or calcium hardness
of the recirculating water to that of make-up water. The maximum level of either parameter is
based on the chemical treatment program and the acceptable rates of corrosion and scaling.
CH-93-12
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Corrosion. Corrosion is defined as the oxidation of a metal by an oxidizing agent in the
environment. Chromates have historically been used to protect against corrosion. The chemicals
most commonly added to chromate-based formulations are zinc and phosphate. Other chemicals
such as organic compounds, polysilicates and molybdates have also been used.
Scaling and Fouling. Scale formation occurs when dissolved solids and gases in cooling
water reach their limit of solubility and precipitate out onto piping and heat transfer surfaces.
Scaling reduces the heat transfer capacity of heat exchangers. Fouling occurs when deposits of
dirt, leaves and/or floes of insoluble salts or hydrous oxides form corrosive agglomerate in the
heat exchanger tubes. Fouling hinders the flow of water through heat exchangers.
Polyphosphates and phosphonates are commonly used to control the rate of scaling and
are the most effective chemical compounds used. Polymeric dispersants (with a molecular weight
less than 20,000) reduce the potential for fouling.
Microbiological Control. The three types of microorganisms found in cooling tower
water systems are bacteria, fungi and algae. Microbiocides can be classified as oxidizing agents,
enzymes poisons, organic chemical compounds, and miscellaneous compounds. Oxidizing agents
include chlorine, bromine and iodine. Enzyme poisons include methylene bisthiocyanate, acrolein
and heavy metals. However, acrolein and heavy metals are not widely used and are not used in
comfort cooling towers. Organic compounds include the following: dodecylquamide
hydrochloric and quaternary ammonia salts; hydrolyzable materials such as 2,2-dibromo-3-
nitrilopropionamide, chlorinated cyanurates and halogenated hydantoins; hydrolyzable and
detoxifiable compounds such as methylene bis-thiocyanate and bromonitrostyrene; and
detoxifiable materials such as isothiazolin. Miscellaneous compounds include diothiocarbamates.
Formation of Drift
Water droplets are formed as the water splashes down through the fill material and from
the shearing action of the airflow along the water surfaces within the tower. These water
droplets, containing suspended and dissolved solids, become entrained in the air and are emitted
from the cooling tower. These emissions, known as drift, are independent of the water lost by
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evaporation.1,5 Evaporation rates are typically one to two percent of the circulating water flow
rate with drift rates ranging from less than 0.0001 percent to 0.01 percent.1
The magnitude of drift loss is influenced by the number and size of droplets produced
within the cooling tower, which in turn are influenced by the fill design, air and water patterns
and other interrelated factors. Tower maintenance and operation also influence the formation of
drift droplets. Excessive water flow, excessive airflow and water bypassing the tower drift
eliminators can promote and/or increase drift emissions.1,2 However, the airflow rate has the
largest impact on the drift rate.5
The velocity of the airflow in the fill is typically 300 to 700 feet per minute (91.4 to 215
meters per minute). Drift rates are highest when the air velocity is at either end of the range.
Most towers are designed with an airflow rate that produces a drift rate as near to the minimum
as is practical.5 Drift eliminators are usually incorporated into the cooling tower design to reduce
the drift from cooling towers by removing as many droplets as practical from the air stream
before it exits the tower. The drift eliminators rely on inertial separation caused by directional
changes while passing through the eliminators. Important design considerations for drift
eliminators include the air velocity and pressure drop through the eliminators, as well as
provisions for reducing or eliminating droplet reentrainment and air leakage.1 Better drift
eliminators expand the range of airflow rates that produce minimum drift rates and reduce the
effect of substantially higher or lower airflow rates on the drift rate.5
Pollutants
Large drift droplets settle out of the tower exhaust air stream and deposit near the tower.
This deposition can result in wetting, icing, salt deposition and damage to equipment and
vegetation. Other drift droplets may evaporate before being deposited in the area surrounding
the tower and may result in PM-10 emissions. PM-10 is generated when the drift droplets
evaporate leaving fine particulate matter formed by crystallization of dissolved solids.1,2
Drift droplets have the same water chemistry as the water circulating through the tower.
VOC, particulate matter and air toxic compounds are emitted from cooling towers due to process
contaminants in the cooling water; anti-corrosion, anti-scaling, anti-fouling and other water
conditioning additives; biocides; and suspended and entrained organics and particulate matter
CH-93-12
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carried in the water vapor.5,6 Some of the compounds used in chemical treatment programs were
listed in the section on Chemical Treatment. Chlorination of fresh waters as a biocide produces
volatile trihalomethanes (THM) such as chloroform, trichloroethylene, tetrachloroethylene, etc.,
that are released to the atmosphere.7,8
SOURCES OF DATA
Activities
The Cooling Tower Institute (CTI) in Houston, Texas was contacted for information on
cooling tower specifications and operations. CTI personnel suggested contacting Mr. Robert
Fulkerson in Kansas City, Missouri for specific technical information. Mr. Fulkerson answered
several general questions and offered to forward a book containing general information on
cooling towers. To date, this material has not been received.9 In addition, the CTI regularly
publishes information on cooling towers. Publications lists can be obtained from the CTI.
Detailed information on comfort cooling towers and model comfort cooling tower systems
may be obtained from Reference 5. These data include cooling tower population and
corresponding building size distribution, model tower cooling requirements and flow rates,
percent utilization, etc. Data on commercial building characteristics are available in the U.S.
Department of Energy publication Commercial Buildings Characteristics.10 County-specific data
on commercial, institutional and industrial building space and characteristics can be obtained from
county or community economic commissions and Chambers of Commerce.
Pollutants
Section 11.4 of AP-42 provides particulate emission factors for wet cooling towers.
Separate emission factors are given for induced draft and natural draft cooling towers. Chromium
emission factors or emission rates may be found in Reference 5 and chloroform emission factors
or emission rates may be found in Reference 7. In addition, Reference 4 contains industrial
emission factors.
CH-93-12
5-9
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The Cooling Tower Institute's list of publications and bibliography of technical papers
were reviewed for references to emission factors. From the titles alone, no emission factor data
were identified. In a brief discussion concerning cooling tower emission factors for pollutants
other than chromium and particulate matter, EPA personnel indicated that it may be reasonable
to assume that emission factors for other pollutants would have the same ratio of pollutant to
water as does particulate matter.11
METHODOLOGIES
Several methodologies were developed for estimating emissions from cooling towers. The
majority of this discussion focuses on comfort cooling towers, although a short section on
industrial cooling towers is presented.
The most difficult part of these methodologies will be developing the emission factors.
The emission factors will have to account for various tower designs and drift eliminators, how
and when additives are used, differences in cooling requirements, etc. For example, chemical
treatment usually occurs on a daily basis throughout the summer and uses automatic, rather than
manual, feed. Use and amount of algacides, fungicides and anti-corrosives are based in part on
the size of the tower, how much space is being cooled and whether the tower is located inside
or outside, in the sun or in the shade. If a tower is located outside or in the sun, more biocides
are needed than if it is located inside or in the shade.9
Emission factors may be developed using total amount of compound used nationally,
assuming an emission rate and allocating this amount to the total population of towers or to
number of employees in SICs 50 through 99. Emission factor work for chromium and particulate
matter emissions from cooling towers should be carefully reviewed.
Industrial Cooling Towers
It is estimated that IPCTs are used at approximately 190 petroleum refineries, 1,800
chemical manufacturing plants, 240 primary metals plants and 730 plants in the miscellaneous
industries.12 The miscellaneous industries include utilities, tobacco, tire and rubber, textiles and
glass manufacturing.3 Most, if not all, of the facilities having IPCTs should be included in the
CH-93-12 5-10
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point source inventory. An IPCT at one of these facilities should be coded as a point within the
facility.
Since SCCs exist only for cooling towers at refineries, additional SCCs for cooling towers
at other types of facilities will need to be developed. AP-42 provides guidance for estimating
particulate emissions for wet cooling towers. Since the emission factors given for induced draft
and natural draft cooling towers are markedly different, the cooling tower SCCs will need to
account for specific cooling tower characteristics. To use the existing emission factors, the
source must know the water flow of the cooling tower.
Refinery cooling tower emission factors are 6 lbs VOC/MG cooling water and 10 lbs
VOC/1,000 bbls refinery feed. No other emission factors were identified for VOC and air toxic
emissions (other than chromium) associated with cooling towers.
Comfort Cooling Towers
Over 250,000 comfort cooling towers are found throughout the United States, primarily
in urban areas. Major users of CCTs with HVAC systems include hospitals, hotels, schools,
office buildings and shopping malls. Refrigeration systems that may use CCTs include ice
skating rinks, cold storage warehouses and other commercial operations.3
Three methodologies for estimating emissions from comfort cooling towers are presented
in the following paragraphs. These methodologies treat comfort cooling towers as area sources
of emissions and vary in level of detail of information needed to use the methodologies.
Method 1
Chapter 4 of Reference 5 provides data on model comfort cooling towers, including total
estimated number of cooling towers in the nation, percent of each building size class having
cooling towers and the average building size in each size class with corresponding tower cooling
requirements, flow rates (recirculation rate, evaporation rate and blowdown rate) and chromium
emissions per tower. Using these data and the corresponding assumptions, this method would
assume a direct, static relationship between square feet of space to be cooled and number of
gallons or "tons" of air conditioning needed. The required cooling capacity of central HVAC
CH-93-12
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systems for large buildings is based on the amount of floorspace in the building. However, the
capacity of the cooling tower must be about 25 percent greater than the capacity of the HVAC
system to account for the heat added to compress the refrigerant.5 In general, a one ton cooling
capacity is sufficient to handle 350 to 400 square feet of commercial space.
Next, factors would be developed relating the amount of various additives to gallons of
water used. These additives would include anti-corrosives, anti-fouling and anti-scaling
compounds, and biocides. These factors may differ depending on the region or county location
and/or average temperature, etc. Table 5-1 provides utilization rates for each state. The
utilization rate is the number of days the cooling tower is used annually and depends on the
climate at the CCT site and the building use. The calculation of the utilization rates in Table 5-1
assumed that the fan is not used on days when the average temperature is below 60°F. The
nationwide utilization rate is 46 percent, with state values ranging from 100 percent in Hawaii
to 0 percent in Alaska.5
The factors would assume a certain number of pounds of additive per gallon of water.
This information could be developed into a single term for the algorithm, an emission factor (or
series of emission factors, one for each type of additive), that would take into account both the
amount of additive used and the emission of the additive.
The square footage of commercial space by building size would be needed. The
DOE/ELA publication Commercial Buildings Characteristics only provides information by Census
Region. Therefore, commercial space data would need to be obtained from other sources, such
as Chambers of Commerce, real estate offices, etc. Following the methodology used in
Reference 5, county building data should aggregated into the following building size classes:
• 5,000 ft2 or less
5,001 ft2 to 10,000 ft2
10,001 ft2 to 25,000 ft2
25,001 ft2 to 50,000 ft2
50,001 ft2 to 100,000 ft2
100,001 ft2 to 200,000 ft2
• Greater than 200,000 ft2
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TABLE 5-1. STATE UTILIZATION RATES
State
Utilization Rate
(percent)
State
Utilization rate
(percent)
Alabama
59
Montana
25
Alaska
0
Nebraska
38
Arizona
55
Nevada
39
Arkansas
56
New Hampshire
27
California
54
New Jersey
42
Colorado
29
New Mexico
39
Connecticut
33
New York
33
Delaware
33
North Carolina
53
District of
Columbia
50
North Dakota
25
Florida
89
Ohio
39
Georgia
59
Oklahoma
54
Hawaii
100
Oregon
23
Idaho
21
Pennsylvania
39
Illinois
42
Rhode Island
33
Indiana
42
South Carolina
59
Iowa
38
South Dakota
33
Kansas
42
Tennessee
50
Kentucky
42
Texas
63
Louisiana
65
Utah
31
Maine
21
Vermont
25
Maryland
46
Virginia
42
Massachusetts
33
Washington
20
Michigan
33
West Virginia
42
Minnesota
29
Wisconsin
31
Mississippi
59
Wyoming
25
Missouri
42
TOTAL
46
Source: Reference 5
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Not all buildings with central cooling will have cooling towers. Using DOE data and engineering
judgement, Reference 5 assumed the following distribution (percent) of cooling towers over
building size classes:
• Under 5,000 ft2 - not cost-effective to have a cooling tower
• 5,001 ft2 to 10,000 ft2 - 5 percent have CCTs
• 10,001 ft2 to 25,000 ft2 - 25 percent have CCTs
• 25,001 ft2 to 50,000 ft2 - 40 percent have CCTS
• 50,001 ft2 to 100,000 ft2 - 60 percent have CCTs
• 100,001 ft2 to 200,000 ft2 - 90 percent have CCTs
• Greater than 200,000 ft2 - 95 percent have CCTs
For systems that employ cooling towers, it is generally recommended that a chemical system be
in use, but it is mandatory for chiller systems in excess of 600 tons (over 200,000 ft2 building).
An algorithm can be developed that requires only limited information from the
inventorying agency. This algorithm may take the following form:
Emission
Total Commercial * Gallons Water per x Utilization x Factor (lbs = lbs additive
Space (sq ft) sq ft per hour Rate additive/gal) emmitted/yr
This algorithm can be performed for each size class and the emissions summed or the terms in
the algorithm can be weighted to reflect the building size population.
The method makes many assumptions about cooling tower design and use of additives.
Regional testing of CCT operations and emissions and development of regional emission factors
may reduce some of the uncertainty.
Method 2
Using many of the assumptions from Method One and procedures cited in Analysis of Air
Toxics Emissions, Exposures, Cancer Risks and Controllability in Five Urban Areas, Volume I,
regional or state per capita or per employee emission factors could be developed for each
CH-93-12
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pollutant.13 This would require knowledge of state or regional use of various additives and would
account for differences in cooling seasons and other variables. Employment in SICs 50 through
99 would be used with the per employee factors.
The general algorithm is as follows:
County Employment Per Employee
SICs 50 through 99 x Emission Factor = Emissions per year
Additional information is required to develop these emission factors. Some data may be
available from the Cooling Tower Institute. These data may include information on the
distribution of types of towers and drift eliminators and use of various anti-corrosive, anti-fouling
and anti-scaling, and biocide additives.
Method 3
Some data may be available to make more detailed estimates of cooling tower emissions.
For example, Reference 10 contains information on building size, weekly operating schedules,
percent of buildings cooled, cooling equipment, exterior wall and roof materials, etc. However,
these data are only available at the Census Region level and would need to be allocated to the
state and county levels. Once allocated, this information can be used to estimate specific cooling
requirements and chiller and cooling tower size and characteristics. Emission factors would need
to be developed for each set of characteristics and pollutants.
A method based on using these data may not be practical to use on a county-level basis.
DATA ISSUES
Some additional information and data are needed before the proposed methods for
estimating cooling tower air emissions can be implemented. For Method 1, further investigation
is needed on the validity of the assumptions made concerning cooling tower design and the use
of additives. Also, it is suggested that additional information and data be acquired to develop
emission factors for the Method 2 algorithm. For Method 3, additional investigation is
CH-93-12
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recommended to determine the feasibility of obtaining state- and county-level data on a wide
variety of factors that will affect the levels of emissions from cooling towers.
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REFERENCES
1. Midwest Research Institute. Development of Particulate Emission Factors for Wet
Cooling Towers, prepared for the U.S. Environmental Protection Agency, Research
Triangle Park, NC, under EPA Contract No. 68-02-4395, July 27, 1990.
2. U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors,
Volume I, Fourth Edition and Supplements. AP-42. Research Triangle Park, NC.
September 1985 through September 1991.
3. Shular, J. et al. Locating and Estimating Air Emissions from Sources of Chromium
(Supplement), EPA-450/2-89-002 (NTIS PB90-103243). Research Triangle Park, NC.
August 1989.
4. Stockton, M.B. and J.H. E. Stelling. Criteria Pollutant Emission Factors for the 1985
NAPAP Emissions Inventory, EPA-600/7-87-015 (NTIS PB87-198735). Research Triangle
Park, NC. May 1987.
5. U.S. Environmental Protection Agency. Chromium Emissions from Comfort Cooling
Towers - Background Information for Proposed Standards, EPA-450/3-87-010a (NTIS
PB88-197298). Research Triangle Park, NC. March 1988.
6. Airborne Emissions from Power Plant Cooling Towers. Electric Power Research Institute,
August 1986.
7. Science Applications International Corporation. Sources and Concentrations of
Chloroform Emissions in the South Coast Air Basin, ARB/R-88/344. Manhatten Beach,
CA. April 1988.
8. Smith, J.H., J.C. Harper and B.C. DaRos. "Atmospheric Emissions from Electric Power
Plant Cooling Systems," In Water Chlorination: Environmental and Health Effects,
Volume 4, Book 2. R.L. Jolley, Ed. 1984.
9. Telecon. Kersteter, Sharon L., Alliance Technologies Corporation, Chapel Hill, NC, with
Robert Fulkerson, Cooling Tower Institute, Kansas City, MO. August 1991. Cooling
tower information.
10. U.S. Department of Energy. Commercial Buildings Characteristics 1989. Energy
Information Administration. Washington, DC. June 1991.
11. Telecon. Kersteter, Sharon L., Alliance Technologies Corporation, Chapel Hill, NC, with
Dennis Shipman, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC. August 1991. Cooling tower emission
factors.
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12. U.S. Environmental Protection Agency. Chromium Emissions from Industrial Process
Cooling Towers - Background Information for Proposed Standards, EPA-453/R-93-022.
Research Triangle Park, NC. May 1993.
13. Wilson, J. et al. Analysis of Air Toxics Emissions, Exposures, Cancer Risks and
Controllability in Five Urban Areas, Volume I - Base Year Analysis and Results, EPA-
450/2-89-012a (NTIS PB89-207161). Research Triangle Park, NC. July 1989.
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APPENDIX A
DERIVATION OF OIL SPILLS METHODOLOGY FOR
GASOLINE AND DIESEL FUEL
CH-93-12
A-l
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Section 3 of this report presented plots of Fv vs. 0 for crude oil, gasoline, and diesel fuel
that were derived using Equation 10 from that section. Equation 10 includes certain parameters
that were derived experimentally by Stiver and Mackay for crude oil; however, no experimental
data were given for gasoline and diesel fuel.1 This appendix describes the alternative
methodologies that were used to determine these parameters for gasoline and diesel fuel. Also
included here is a discussion of the possible errors associated with the alternative methodologies.
Equation 10 includes some new terminology which warrants discussion: the TB, Fv line
referred to in Equation 10 is a representative distillation curve of the oil. Next, the dimensionless
constant B of Equation 10 is defined as:1
B = AHJ(RTJ (1)
where B = dimensionless constant
AH = enthalpy of vaporization (kJ/mol)
R = gas constant (8.314 Pa-m3/(mol-K))
Tb = boiling point (K)
According to Trouton's rule, B is a fairly constant value of 10.6 for all nonpolar liquids
that is accurate to within about 30 percent.1,2 From experimental data results, Stiver and Mackay
determined B for crude oil to be 10.3. For the purposes of this methodology, B will be assumed
to equal 10.6 for gasoline and diesel fuel.
Also, Equation 10 includes the dimensionless constant A which is defined as:1
A = \n[PAvl(R1)] * B (2)
A
dimensionless constant
Pa =
atmospheric pressure (101,325 PA)
V =
liquid molar volume (m3/mol)
T
ambient temperature (K)
B
dimensionless constant
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A-2
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As stated previously for dimensionless constant B, Stiver and Mackay used experimental data to
determine the value of A for crude oil to be 6.3. For the purposes of this methodology, other
means were required to find A for gasoline and diesel fuel.
If Equation 2 is broken down, it becomes apparent that the only unknown parameter is
v (molar volume) which depends on average molecular weight and density of the fuel. Data on
the average density of gasoline and diesel fuel are readily available, however, average molecular
weight data are generally not available. Therefore, two distinctly different methods were derived
to calculate an average molecular weight for gasoline and diesel fuel.
The first method involves the simplifying assumption that gasoline and diesel fuel may
be assumed to have the chemical formula of a straight-chain alkane compound (i.e., molecular
formula CnH2n+2). Then, using distillation data for each fuel (TB, Fv line discussed earlier), a
carbon number corresponding to the boiling point of each fraction evaporated is determined from
Reference 3. This carbon number (or molecular formula; i.e., molecular weight) is assumed to
represent the appropriate fraction of a volume percent of the fuel species. By summing up the
contributing fractions' carbon numbers, a weighted-average carbon number can be found for the
fuel. Applying the formula for a straight-chain alkane, the average molecular weight of the fuel
can be determined.
The second method involves a simpler, but possibly less accurate, calculation for
determining the average molecular weight of a fuel. By assuming Trouton's rule applies to
gasoline and diesel fuel, the molecular weight may be found by simply back-calculating.
Specifically, Trouton's rule states that the ratio of a nonpolar liquid's enthalpy of vaporization
to its boiling temperature is approximately 0.088 or AH/T0 = 0.088 kJ/(mol-K).2 Since it is the
average molecular weight that is required, if the average enthalpy of vaporization" and average
boiling point are known for a particular fuel, the average molecular weight may be calculated as
follows:
AHavt, X X/1,000 = Ttovg x 0.088 (3)
where AH^.g = average enthalpy of vaporization (kJ/kg)
% = average molecular weight (g/mol)
Tfiavg = average boiling temperature (K)
CH-93-12
A-3
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Solving this equation for % determines the average molecular weight of the fuel.
Distillation data for the first molecular weight method are available from several sources.
National Institute for Petroleum and Energy Research reports contain distillation data for different
grades of fuel by national average and for each section or area of the country.4,5 Average
distillation curves are also available for many different fuel types from References 6 and 7. Data
for the second molecular weight method are available for gasoline and crude oil in Reference 6.
Another source of data for either molecular weight estimation method is the American Petroleum
Institute (API).
After determining the average molecular weight of the fuel of interest, the molar volume
(d) may be calculated by dividing the molecular weight by density of the fuel. Data on the
density of fuels are available from Reference 6. These methods require the assumption that
density of the fuel is constant over an ambient temperature range of 7° to 35°C (45° to 95°F)
which is a fair approximation for the purposes of this report. More importantly, however, this
assumption requires that the density remains constant as fractions of the fuel are evaporated.
This assumption results in an overestimation of the fraction evaporated at larger exposures.
Using Equation 2, the dimensionless constant A may now be calculated (assuming an average
ambient temperature of 21°C or 70°F).
The final two pieces of data needed for Equation 10 in Section 3 are the gradient TG and
the initial boiling temperature T0. These data can be easily found from the distillation data in
References 4, 5, 6, and/or 7. T0 is simply found by determining the boiling point at the zero
intercept of the percent distilled axis. TG requires performing a regression analysis of the
distillation curve data to determine the slope (or gradient) of the line.
For the purpose of this methodology, the distillation data method was used to determine
the average molecular weight of both gasoline and diesel fuel. With each of the variables in
Equation 10 now determined, a plot for Fv vs 0 can be made for crude oil, gasoline, and diesel
fuel for the ambient temperature range of 7° to 35° C (45° to 95°F). These curves are plotted
in Figures 3-2, 3-3, and 3-4 of Section 3.
It is now important to discuss the errors associated with the methodology to generate Fv
vs 0 curves for gasoline and diesel fuel. It should be noted that these errors are associated with
the parameters of Equation 10 and do not reflect the total error in the resultant Fv vs 0 curves
(this is discussed later). As stated previously, Stiver and Mackay used experimental data to
CH-93-12 A-4
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determine the constants A and B for Equation 10 in the case of crude oil. For the purpose of
determining these constants for gasoline and diesel fuel, several simplifying assumptions were
made which may cause errors in the Fv vs 0 curves: the assumption that Trouton's rule for
constant B applies to gasoline and diesel fuel has a possible error of 30 percent. Also, the
assumption was made that the average molecular weight of gasoline and diesel fuel could be
approximated by assuming a straight-chain alkane chemical formula. The error in this
assumption is unknown although a comparison of the molecular weights from Stiver and Mackay
(derived from Equation 2 using their constants for A and B) and using the distillation data
revealed an error of 24 percent. The assumption that density of the fuel is constant over the
specified ambient temperature range introduces an error believed to be relatively small (less than
10 percent).
Another source of error in the distillation data method for determining average molecular
weight is the assumption of an average composition of each fuel. In reality there are many
grades of gasoline (low, medium, and high octane; gasohol, etc.) which vary according to area
of the country and time of the year.4 Also, there are different grades of diesel fuel in which the
composition varies according to the type of service required of the fuel.5,6 However, an error
analysis using three different data sets for gasoline (high/low octane, and gasohol) revealed a
maximum difference of less than 5 percent between their Fv vs 0 curves.
The final question involves these individual errors affect on the total error in the final Fv
vs 0 curves. The only basis available for determining this error is to compare the results of
Stiver and Mackay to the results of the distillation methodology for crude oil only. These
comparisons showed that the error varied considerably with exposure time and that there was an
average error of 13 percent with a maximum error of 52 percent. It should be noted that the
larger errors occurred at low evaporative exposures (an elapsed time of a few hours) and leveled
off at higher evaporative exposures (an elapsed time of a few days). It is also critical to note that
this analysis does not compensate for best and worst case scenarios. Instead, it is based on a
single scenario and therefore, the actual errors could be much greater than those stated here.
Stiver and Mackay indicate that their analysis for crude oil tended to overestimate (by up to 20
percent) the fraction evaporated at high evaporative exposure. This error for gasoline and diesel
fuel is unknown.
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REFERENCES
1. Stiver, Warren, and Donald Mackay. "Evaporation Rate of Spills of Hydrocarbons and
Petroleum Mixtures." Environmental Science and Technology, Vol. 18, No. 11. 1984.
2. Felder, Richard M. and Ronald W. Rousseau. Elementary Principles of Chemical
Processes. John Wiley & Sons. New York, NY. 1978. pg. 329.
3. Speight, James. G. The Chemistry and Technology of Petroleum. Second Edition.
Marcel Decker, Inc. New York, NY. 1991. pp. 279-285.
4. Dickson, Cheryl L. and Paul W. Woodward. Motor Gasolines, Summer 1988. National
Institute for Petroleum and Energy Research. ITT Research Institute. Bartlesville, OK.
March 1989.
5. Dickson, Cheryl L. and Paul W. Woodward. Diesel Fuel Oils, 1991. National Institute
for Petroleum and Energy Research. ITT Research Institute. Bartlesville, OK. October
1991.
6. Avallone, Eugene A. and Theodore Baumeister m, eds. Mark's Standard Handbook for
Mechanical Engineers. Ninth Edition. McGraw-Hill, Inc. New York, NY. 1978. pp. 7-
12 to 7-18.
7. Perry, Robert H, Don W. Green, and James O. Maloney, eds. Perry's Chemical
Engineers'Handbook. Sixth Edition. McGraw-Hill, Inc. New York, NY. 1984. pp. 13-
71 to 13-74.
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APPENDIX B
NO AND NOx EMISSION FACTOR DERIVATION
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NQC02(by volume)=.000'\5
N0fC02{by mass)=.000] 5
where MWNO is the molecular weight of NO
MWox is the molecular weight of C02
Is the mass of NO
is the mass of C02
Solving for MNO gives
Afwo=.00015 (MWJMW^Mco,
Also given by Evans et al. Reference 13, Section 3 is
C0iC02{by volume)=.038
CQC02{by mass)=.038
Solving for gives
038)
Substituting into the previous equation for MNO yields
Mno=.000\ SiMW^MW^M^i.O^)
Substituting as determined previously yields
MJI{.038)
Substituting for the molecular weights and simplifying yields
MNO=2.58x1 0"4 Mf
Similarly, starting with
N0)jC02{by volume)=.0004
it can be shown that
M^.OOO^MW^MW^i.OB] /l^/(.038)
Expressed as N02
Mnox=. 0011 Mf
B-2
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APPENDIX C
LEVEL OF DETAIL OF PETROLEUM VESSEL LOADING AND
UNLOADING DATA
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The following information is currently available for petroleum vessel loading and
unloading activity at these various levels of detail.
NATIONAL LEVEL
Percent of principal commodities carried between U.S. ports by non-self propelled tank barge:
- Crude oil
- Gasoline
- Jet fuel
- Distillate fuel oil
- Residual fuel oil
- Asphalt, tar and pitches
- All other commodities
PAD LEVEL
Movements between PAD district by barges and tankers combined:
- Crude oil
- Liquified petroleum gases
- Unfinished Oils
- Motor gasoline blending components
- Finished leaded motor gasoline
- Finished unleaded motor gasoline
- Finished aviation gasoline
- Jet fuel, naphtha type
- Jet fuel, kerosene type
- Kerosene
- Distillate fuel oil
- Residual fuel oil
- Petrochemical feedstocks
- Special naphtha
- Lubricants
- Waxes
- Asphalt and road oils
- Miscellaneous products
Working storage capacity at refineries and gasoline blending plants:
- Crude oil
- Finished leaded motor gasoline
- Finished unleaded motor gasoline
- Gasoline blending components
- Middle distillates
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- Residual fuel oil
- Asphalt and road oil
- Lubricants
- Jet fuel, naphtha type
- Jet fuel, kerosene type
- All other products
Stocks at refineries and/or bulk terminals:
- Crude oil
- All petroleum products other than crude oil
- Liquified petroleum gases
- Unfinished oils
- Motor gasoline blending components
- Aviation gasoline blending components
- Finished leaded motor gasoline
- Finished unleaded motor gasoline
- Finished aviation gasoline
- Naphtha-type jet fuel
- Kerosene-type jet fuel
- Kerosene
- Distillate fuel oil
- Residual fuel oil
- Naphtha for petrochemical feedstock use
- Other oils for petrochemical feedstock use
- Special naphtha
- Lubricants
- Waxes
- Petroleum coke
- Asphalt and road oil
- Miscellaneous products
Net refinery production of finished petroleum product by PAD district and refining districts
within each PAD district:
- Liquified refinery gases
- Finished leaded motor gasoline
- Finished unleaded motor gasoline
- Finished aviation gasoline
- Naphtha-type jet fuel
- Kerosene-type jet fuel
- Kerosene
- Distillate fuel oil
- Residual fuel oil
- Naphtha for petrochemical feedstock use
- Other oils for petrochemical feedstock use
- Special naphtha
- Lubricants, naphthenic
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- Lubricants, paraffinic
- Waxes
- Petroleum coke
- Asphalt and road oil
- Miscellaneous products, fuel use
- Miscellaneous products, non-fuel use
Exports and imports by PAD district:
- Crude oil
- Natural gas liquids
- Finished motor gasoline
- Naphtha-type jet fuel
- Kerosene-type jet fuel
- Kerosene
- Distillate fuel oil
- Residual fuel oil
- Naphtha for petrochemical feedstock use
- Other oils for petrochemical feedstock use
- Special naphtha
- Lubricants
- Waxes
- Petroleum coke
- Asphalt and road oil
- Miscellaneous products
Refinery receipts of crude oil by method of transportation by PAD district:
- Domestic tankers
- Foreign tankers
- Domestic barges
- Foreign barges
Supply, disposition and ending stocks:
- Crude oil
- Natural gas liquids
- Finished unleaded motor gasoline
- Finished leaded motor gasoline
- Finished aviation gasoline
- Naphtha-type jet fuel
- Kerosene-type jet fuel
- Kerosene
- Distillate fuel oil
- Residual fuel oil
- Petrochemical feedstocks
- Special naphtha
- Lubricants
- Waxes
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- Petroleum coke
- Asphalt and road oil
- Miscellaneous products
Imports of residual oils by sulfur content
REGIONAL LEVEL
Percent of barge activity by location
- Northeast
- Atlantic inland waterways
- Gulf inland waterways
- Lower Mississippi
- Upper Mississippi
- Ohio and Tributaries
- California
- Pacific Northwest
- Great Lakes
STATE-LEVEL
Working storage capacity at refineries and gasoline blending plants:
- Crude oil
- Finished leaded motor gasoline
- Finished unleaded motor gasoline
- Gasoline blending components
- Middle distillates
- Residual fuel oil
- Asphalt and road oil
- Lubricants
- Jet fuel, naphtha type
- Jet fuel, kerosene type
- all other products
Capacity of operable petroleum refineries in barrels per stream day
Imports of residual oil by sulfur content and state of entry
Number and capacity of operable petroleum refineries
REFINERY AND/OR PORT LEVEL
Refiners' operable atmospheric crude oil distillation capacity
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Capacity of operable petroleum refineries in barrels per stream day
Storage capacity of petroleum terminals (in thousands of barrels) located on (1) the U.S. inland
waterway system and (2) in U.S. coastal and Great Lakes ports:
- Crude oil
- Refined petroleum
- Fuel oil
- Asphalt
- Mixed products
Domestic and foreign shipment and receipt of crude oil and petroleum products in tons:
- Crude oil
- Gasoline, natural gasoline
- Jet fuel
- Kerosene
- Distillate fuel oil
- Residual fuel oil
- Lubricating oils and greases
- Naphtha, mineral spirits, other solvents
- Liquified petroleum gases
Number of tankers and number of barges by draft and direction of travel
Methods of supply and out-loading at a terminal, storage capacity by product:
- Leaded regular gasoline
- Unleaded regular gasoline
- Unleaded premium gasoline
- Diesel
- AV jet
- AV gas
- Residuals
- Fuel oil
- Ethanol
- Leaded premium gasoline
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