Proceedings: Annual Acid Deposition Emmission
Inventory Symposium (2nd), November 1985
Radian Corp., Research Triangle Park, NC
Prepared for
Environmental Protection Agency
Research Triangle Park, NC
Apr 86
PB86-217148
U.S. Mpartnwnt of
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EPA/600/9-86/010
April 1986
PROCEEDINGS:
SECOND ANNUAL ACID DEPOSITION
EMISSION INVENTORY SYMPOSIUM
(November 1985)
James B. Homolya and
Patricia A. Cruse, Compilers
Radian Corporation
Box 13000
Research Triangle Park, North Carolina 27709
EPA Contract No. 68-02-3994, Task 032
EPA Project Officer:
J. David Mobley
Air and Energy Engineering Research Laboratory
U. S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
AIR AND ENERGY ENGINEERING RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, NC 27711
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TECHNICAL REPORT DATA
{Plcasf rraii /wn/urfiuni on the rrtenf bffort (.o
\ R t PORT MO
EPA/600/9-86/010
J TiTLt A\O SUBTITLE
Proceedings: Second Annual Acid Deposition
Emission Inventory Symposium (November 1985)
5 REPORT DATE
April 1986
6 PE RFORMING ORGANIZATION CODE
'AuTnORtSI
James B. Hornolya and Patricia A. Cruse, Compilers
8 PERFORMING ORGANIZATION REPORT NO
9 PERFORMING ORGANIZATION NAME ANO AUORESS
Radian Corporation
P.O. Box 13000
Research Triangle Park, North Carolina 27709
3 RECIPIENT S ACCESSIOWNO
? 171 48 /AS
10 PROGRAM E LEMENT NO.
11 CONTRACT/GHANT NO
68-02-3994, Task 32
12 SPONSORING AGENCY NAME ANO 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
Proceedings; 11 /
14. SPONSORING AGENCY CODE
EPA/600/13
15 SUPPLEMENTARY NOTES AEERL project officer is J. David Mobley, Mail Drop 61. 919/
541-2612.
16 ABSTRACT -phase proceedings document a 2-day symposium, held to discuss progress
made by the National Acid Precipitation Program (NAPAP) and other organizations
in developing emission inventories. The symposium was sponsored by EPA's Air
and Energy Engineering Research Laboratory, in cooperation with EPA's Office of
Air Quality Planning and Standards, the U. S. Department of Energy, the National
Oceanic and Atmospheric Administration, and NAPAP. The meeting was intended
primarily for government, academic, and private sector individuals involved in
developing or using emission inventories for acid deposition related activities.
Topics addressed included historical emissions estimates, the 1980 and 1985 emis-
sion inventories, Eulerian modeling analyses, and uncertainties in emission inven-
tories. The proceedings provide valuable documentation of results of efforts to date
to develop emission factors and emission inventories for anthropogenic and natural
sources.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Pollution
Emission
Inventories
Assessments
Precipitation
(Meteorology)
Acidification
Euler Equations of
Motion
Mathematical Models
Analyzing
b IDENTIFIERS/OPEN ENDED TERMS
Pollution Control
Stationary Sources
Emission Inventories
Acid Precipitation
Emission Factors
Eulerian Modeling
c. COSATI 1 leld/Group
13 B
14G
15E
14 B
04B
07B.07C
12 A
3 DISTRIBUTION STATEMENT
Release to Public
19 SECURITY CLASS (THll Krporl/
Unclassified
NO OF PAGES
279
20 SECURITY CLASS (Thilpagr/
Unclassified
22 PRICE
EPA Form 2220-1 (»-73)
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NOTICE
This document has been reviewed in accordance with
U.S. Environmental Protection Agency policy and
approved for publication. Mention of trade names
or commercial products does not constitute endorse-
ment or recommendation for use.
11
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ABSTRACT
A two-day symposium was held to discuss progress made by the National
Acid Precipitation Assessment Program and other organizations in the
development of emission inventories. The symposium was sponsored by the
Environmental Protection Agency's Air and Energy Engineering Research
Laboratory, Research Triangle Park, North Carolina, in cooperation with the
EPA Office of Air Quality Planning and Standards, the U. S. Department of
Energy, the National Oceanic and Atmospneric Administration, and the National
Acid Precipitation Assessment Program. The meeting was intended primarily
for government, academic, and private sector individuals involved in the
development or use of emission inventories for acid deposition. Topics
addressed at the meeting included historical emissions estimates and the 1980
emission inventory, the 1985 emission inventory, Eulerian modeling analyses,
and uncertainties in emission inventories. The symposium proceedings provide
a valuable -"'"T'jm^r.i.ation Of results of efforts to date to develop emission
factors end emission inventories for anthropogenic and natural sources.
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ABSTRACT
A two-day symposium was held to discuss progress made by the National
Acid Precipitation Assessment Program and other organizations in the
development of emission inventories. The symposium was sponsored by the
Environmental Protection Agency's Air and Energy Engineering Research
Laboratory, Research Triangle Park, North Carolina, in cooperation with the
EPA Office of Air Quality Planning and Standards, the U. S. Department of
Energy, the National Oceanic and Atmospheric Administration, and the National
Acid Precipitation Assessment Program. The meeting was intended primarily
for government, academic, and private sector individuals involved in the
development or use of emission inventories for acid deposition. Topics
addressed at the meeting included historical emissions estimates and the 1980
emission inventory, the 1985 emission inventory, Eulerian modeling analyses,
and uncertainties in emission inventories. The symposium proceedings provide
a valuable documentation of results of efforts to date to develop emission
factors and emission inventories for anthropogenic and natural sources.
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TABLE OF CONTENTS
Page
ABSTRACT i i i
SESSION 1: DEVELOPMENT OF NAPAP EMISSION INVENTORIES FOR
ANTHROPOGENIC SOURCES 1
Ed Trexler, Chairman
Overview of NAPAP Emission Inventory Activities for
Anthropogenic Sources 2
J. David Mobley (Speaker), Dale Pahl, and Frederick Sellars
Assessment of the Final 1980 NAPAP Emissions Inventory 13
Douglas Toothman
Development of the NAPAP Utility Reference File 22
Edward Pechan (Speaker), James Wilson, and Kristin Graves
Development of an Emissions Inventory to Support Testing of the
Eulerian Regional Acid Deposition Model 31
Frederick Sellars
Uncertainty Analysis of the NAPAP Emissions Inventory 43
Carmen Benkovitz
SESSION 2: DEVELOPMENT OF NAPAP EMISSION INVENTORIES FOR
ANTHROPOGENIC SOURCES (continued) 54
John Bosch, Chairman
Application of the NAPAP Emission Inventories to Eulerian
Model ing 55
Joan Novak (Speaker) and Paulette Middleton
Historic Emissions of SO- and NO Since 1900 by Stack Height
Range and by Season 61
Gerhardt Gschwandtner
Development of Monthly Emissions Trends for Recent Years 71
Duane Knudson
Application of Historic Emissions Inventories to the Development
of the 1984 Acid Deposition Assessment 86
Paul Schwengels
Overview of the Development of the 1985 NAPAP Inventory 88
Charles Mann
Preceding page blank
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Page
Assistance to the States in the Development of the 1985 NAPAP
Emissions Inventory ................................................. 94
David Johnson (Speaker) and Mark Hodges
SESSION 3: FORMULATION OF MAN-MADE POLLUTANT EMISSION FACTORS ...... 120
Dale Pahl , Chairman
Development of NAPAP Emission Factors for Anthropogenic Sources ..... 121
Jim Homolya
Size-Selective Participate Emission Factors for Emission
Inventories [[[
Frank Noonan
Field Measurement Studies for the Development of Point Source
Emission Factors [[[ 153
James Ekmann
VOC Composition of Automotive Exhaust and Solvent Usage in
Europe [[[ 161
C. Veldt
SESSION 4: DEVELOPMENT OF EMISSION INVENTORIES FOR NATURAL
SOURCES ................................................. 176
Fred Fehsenfeld, Chairman
Measurement of Biogenic Sulfur Fluxes at Three Sites in the
Eastern United States ............................................... 177
Paul Goldan (Speaker), W. C. Kuster, F. C. Fehsenfeld, and
D. L. Albritton
Determination of Nitrogen Emissions from Natural Sources ............ 184
Fred Fehsenfeld (Speaker), E. J. Williams, and D. D. Parrish
Alkaline Aerosols Emissions .......................... 193
Dale Gillette
Methodology for Estimating Natural Hydrocarbon Emissions ............ 201
James Reagan
SESSION 5: RELATED EMISSION INVENTORY DEVELOPMENT ACTIVITIES ....... 207
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Page
Generation of Temporally-Resolved Emission Inventories for
Canada 220
Trevor Scholtz (Speaker) and Frank Vena
Historical Analysis of Sulfur Dioxide and Nitrogen Oxide
Emissions in Canada 234
Tom Furmanczyk (presented by Frank Vena)
United Kingdom Emission Inventories 245
Simon Cjgleston
APPENDIX: ATTENDEES 261
VI 1
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SESSION 1: DEVELOPMENT OF NAPAP EMISSION INVENTORIES FOR
ANTHROPOGENIC SOURCES
Chairman: Ed Trexler
U. S. Department of Energy FE-13
Washington, D.C. 20545
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OVERVIEW OF NAPAP EMISSIONS INVENTORY
ACTIVITIES FOR ANTHROPOGENIC SOURCES
by
J. David Mobley and Dale A. Pahl
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Frederick M. Sellars
GCA/Technology Division
Bedford, Massachusetts 01730
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
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OVERVIEW OF NAPAF EMISSIONS INVENTORY
ACTIVITIES FOX ANTHROPOGENIC SOURCES
ABSTRACT
The National Acid Precipitation Assessment Program (NAPAP) has
charged its Task Group B on Man-Made Sources with the development of
comprehensive and accurate inventories of emissions from anthropogenic
sources believed to be important in acid deposition processes. This
effort involves developing estimates of past, present, and future acid
deposition precursor emissions with adequate geographic, temporal, and
sectoral resolution to support the research requirements of NAPAP. It
also entails quantifying the degree of uncertainty associated with those
estimates. The major anticipated needs for emissions data include:
historical analyses of short- and long-term trends in emissions;
atmospheric modeling using Lagrangian and Eulerian techniques; and
overall assessments of the acid deposition phenomenon. This paper
presents an overview of the current and future activities related to the
development of anthropogenic emissions inventory data. Included are
descriptions of the products that have been generated by Task Group B
and plans for the integration of activities surrounding the development
of the 1985 NAPAP Emissions Inventory.
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OVERVIEW OF NAPAP EMISSIONS INVENTORY
ACTIVITIES FOR ANTHROPOGENIC SOURCES
INTRODUCTION
The National Acid PrecipitatVn Assessment Program (NA°AP) was
established by Congress in 1980 to coordinate and expand research on
problems posed by acid deposition in and around the United States. The
program is composed of 10 task groups having specific technical
responsibilites. One of these groups, Task Group B: Man-Made Sources,
is charged with providing a complete and accurate inventory of emissions
from anthropogenic sources thought to be important in acid-deposition
processes.
To fulfill its stated objectives and to support other related NAPAP
research, Task Group B either has generated or is planning the following
major data bases:
• Historical Emissions Estimates.
• 1980 NAPAP Emissions Inventory (Versions 1.0 through 5.2).
• 1985 NAPAP Emissions Inventory.
• Regional Acid Deposition Model Field Validation Emissions
Inventory.
The primary focus of FY 85 emissions inventory activities was
directed toward fulfillment of the emissions data base requirements for
development and testing of the Eulerian Regional Acid Deposition Model
(RADM). Within the EPA's Office of Research and Development, the
Atmospheric Sciences Research Laboratory has been assigned the lead
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responsibility for developing the RADM. National Center for Atmospheric
Research (NCAR) has been assigned the Usk of developing the model
framework which includes a number of chemical transformation modules.
The variety of these modules under development dictates the specific
chemical species required in the emissions inventory.
The FY 85 emissions inventory development program was also directly
supportive of certain "assessment" activities. The emissions inventory's
needs for assessment purposes are generally less detailed and resource
intensive than modeling requirements, but are nonetheless extremely
important to the overall NAPAP program. Assessment projects use more
aggregated emissions information In combination with models or other
analytic techniques to evaluate the relative importance of various
pollutants, regions, and types of sources, to the acid deposition
problem. Results of these studies have implications for planning
additional research needed and development of potential
control/mitigation strategies.
DISCUSSION
The major tasks accomplished during FY 85 and planned for FY 86 are
discussed below.
Historical Emissions Estimates
In order to provide a basis for evaluating acid precipitation
related damage and for studying trends in water chemistry and deposition
m< Jtoring data, it is important to understand both historic (long-term)
and recent (short-term) trends in emissions. Historic SO and NO
emission levels for the U.S. were estimated by individual source
category on the state level from 1900 to 1980 for every fifth year and
for 1978. These emissions were calculated from fuel consumption and
industrial output statistics, estimates of average statewide fuel
properties, and estimates of emission factors specific to each source
category. The emissions estimates were then aggregated to show the
emissions trends by state, region, and all states combined.
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To support a number of short-term trends analyses, Task Group B
developed monthly SO- and NO emissions estimates for the years 1975
through 1983. Annual state total S0? and NO estimates were used
with fuel consumption and industrial production data to provide monthly
values on a state-by-state basis. A system to provide continually
updated and refined monthly data, using periodically published
information, was also formulated as part of this effort.
Long- and short-term historical S0_ emissions are depicted in
Figures 1 and 2, respectively.
1980 Emissions Inventory
The contents of the 1980 NAPAP Emissions Inventory (Version 5.0)
and corresponding Eulerian Modeling Inventory (Version 5.2) are shown in
Figure 3. Compilation of these products required the integration of
several unique, but related, work efforts, as shown in Figure 4.
The 1980 NAPAP Emissions Inventory, representing the most
comprehensive and highest quality emissions data available for the 1980
base year, was completed. The emissions inventory was compiled, starting
with the 1980 "snapshot" inventory, from EPA's National Emissions Data
System (NEDS). Updates were made to address known deficiencies in the
NEDS data. These included substitutions of specific data with
information from other inventories or data bases that were believed to
be more reliable (e.g., replacement of fuel data for major utility
boilers using 1980 Federal Power Commission data). Emission factors and
corresponding emissions estimates for a number of pollutants not
contained in NEDS were also developed and incorporated. Data covering
Canada were added, and improvements were made to methods used to
calculate area source and highway .-ehicle emissions. Systematic quality
control checks were also completed for all significant data items in the
emissions inventory, and estimates of uncertainty were made.
The importance of the utility industry has been recognized by Task
Group B, which is responsible for not only developing estimates of
current emissions from the utility sector but also for projecting future
emissions. Because of different but overlapping needs, Task Group B has
developed a single data has* that will meet the utility-related data
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needs of all NAPAP task groups, the NAPAP Utility Reference File
(NURF). The NURF consists of four component files: the master unit
data file (containing information on dll electric utility generating
units), the fuel specific emissions file (containing emissions
information by fuel and input), the stack parameters file (containing
stack information on a unit-specific basis), and the announced unit file
(containing unit-specific information on units coming on-line or
converting to coal-firing after 1980). The NURF was utilized to derive
and verify emissions data from the utility sector in the 1980 NAPAP
Emissions Inventory.
As previously stated, one of the most extensive applications of the
1980 NAPAP Emissions Inventory is to support development and testing of
the RADM. For this purpose, the 1980 NAPAP Emissions Inventory
(Version 5.0) had to be further resolved temporally, spatially, and by
component species (Version 5.2).
Annual emissions had to be allocated to hourly profiles for a
typical weekday, Saturday, and Sunday in each season; county-level area
sources and minor point sources had to be spatially resolved to modeling
grid cells; N0x emissions had to be split into NO and NO^; TSP
emissions had to be assigned to alkalinity classes; and VOC emissions
had to be apportioned into 30 photochemical reactivity classes.
Development of a methodology and a computerized data base for
estimating the uncertainty associated with the 1980 NAPAP Emissions
Inventory was also undertaken. A workshop was held during which expert
opinion was solicited and a modified Delphi method was applied to arrive
at quantitative estimates for the auxiliary data needed to calculate the
uncertainties of emissions values. Methodologies are now being
developed for the use of expert opinion to generate the auxiliary data
needed to calculate emissions uncertainties for the NAPAP 1985 base year.
1985 Emissions Inventory
FY 86 activities have been focused on tl^e development of the
1985 NAPAP Emissions Inventory. Much of the work that went into the
development of the 1980 inventory will be drawn upon to create the 1985
data base, as shown in Figure 5. One important departure from the
approach used to develop the 1980 NAPAP Emissions Inventory is the
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enlistment of individual state agencies to supply new 1985 emissions
data for the NEDS system, specifically for the NAPAP effort. Previous
efforts have started with NEDS "snapshot" files which did not
necessarily represent the best data available from the states. As a
result, a major state interface/assistance component will be involved.
In addition, efforts related to development of the 1985 data base
will include: incorporation of 1985 Canadian data, 1985-specific
temporal allocation factor development, enhancements to spatial
allocation and speciation data, verification tests to support emission
factor refinements, and an enhanced QA program.
RADM Field Evaluation Emissions Inventory
Another focus area for FY 86 relates to a proposed field study for
validating the Eulerian Regional Acid Deposition Model (RADM). This
would entail development of an "episodic" emissions inventory for
pre-set intensive study periods including collection of actual (rather
than typical) hourly emission values using Continuous Emissions
Monitoring (CEM) for major sources, and accounting for phenomena such as
major forest fires, chemical spills, and process upsets. The episodic
inventories ccjld then be used with corresponding deposition and
atmospheric chemistry measurements to validate the RADM.
CONCLUSIONS
Task Group B has generated a number of data bases to fulfill its
stated objectives. These include estimates of historic emissions back
to 1900 to support long-term trends analyses; estimates of monthly
emissions from 1975 through 1983 to support short-term trends analyses;
estimates of 1980 emissions on both an annual basis, and with the
necessary temporal, spatial, and pollutant species resolution to support
Eulerian modeling analyses; and estimates of uncertainty associated with
the 1980 NAPAP Emissions Inventory. Work planned for FY 86 includes
development of an emissions inventory for the 1985 base year, and
development of an episodic emissions inventory to support field
validation of the RADM.
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Figure 1. Overall trena in $02 and NOX emissions from 1900 to 1980
for the U.S. and by source category for each study year.
CO
O
C
O
C
O
E
u
2.6
2.4
O.2
/
•v.
&
' f ' " f ' " i' ' " i' ' " i' ' " i' ' " i' ' " i* '-" i' ' " i' ' '* I
Jon F»b Mor Apr Moy Jun Jul Auq S»p Oc< Nov 0»c
Month
Figure 2. Monthly trends in U.S. S02 emissions for 1980.
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TEMPORAL
RESOLUTION
GEOGRAPHIC
DOMAIN/
RESOLUTION
POLLUTANTS
1980 NAPAP
ANNUAL EMISSIONS
INVENTORY
Annual/seasonal
48 Contiguous
states and
Canada with area
sources at the
county level
S00
TSP
Pb
CO
HC1
HF
NCx
VOC
1980 NAPAP EULERIAN
ACID DEPOSITION
MODELING EMISSIONS INVENTORY
Hourly emissions values for a
typical weekday, Saturday, and Sunday
for all four seasons
48 States and Canada; separate
major point source file with minor
point sources and area sources
assigned to 63,000 20 x 20 km
grid eel Is
so2
so4
TSP:
- Ca
- Mg
- K
- Na
Pb
CO
HC1
HF
NO
VOC:
- Methane
- Ethane
- Ethylene
- Propane
- Propylene
- N-butane
- 1,2-butene
- Isobutane
VOC (cont.)
- Isobutene
- Trans-2 butene
- Pentane
- Isopentane
- 2,3-dimetnylbutane
- Other alkenes
- Other alkanes
- Formic acid
- Acetic acid
- Other organic acids
- Formaldehyde
- Acetaldehyde
- Propionaldehyde
- Acetone
- Other ketones
- Other aldehydes
- Xylene
- Benzene
- Toluene
- Ethyl benzene
- Other aromatics
Figure 3. Contents of the 1980 NAPAP emissions inventories.
10
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NAPAP UTILITY
REFERENCE FILE
EMISSION
FACTORS
STATE EMISSIONS DATA
FOR 1980
1
1 NAPAP EMISSIONS INVENTORY
| FOR 1980
.
1
f '
'
1
1
EMISSIONS INVENTORY FOR THE
EULERIAN ATMOSPHERIC MODEL
FOR 1980
QUALITY
ASSURANCE
UNCERTAINTY
ESTIMATES
Figure 4. Major program components for developing the
1980 NAPAP Emissions Inventory.
11
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STATE
ASSISTANCE
1985
NEDS FILES
SO?, MOX, CO, VOC,
PARTICULATES
SOX/NOX
ALLOCATION
FACTORS
VOC ALLOCATION
FACTORS
HOURLY EMISSION
PROFILES
INVENTORY
IMPROVEMENTS AND
ADDITIONS
SPATIAL SOURCE
ALLOCATIONS
1985 K'APAP
EMISSIONS INVENTORY
CANADIAN
INVENTORY
EMISSION
FACTORS
VERIFICATION
TESTS
UNCERTAINTY
ESTIMATES
QUALITY
ASSURANCE
Figure 5. Integration of activities for developing
the 1985 NAPAP Emissions Inventory.
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ASSESSMENT OF THE FINAL
1980NAPAP EMISSIONS INVENTORY
Douglas A. Toothman
Engineering-Science, Inc.
10521 Rosehaven Street
Fairfax, Virginia 22030
EFA Contract No. 68-02-3996
Work Assignment Nos. 1, 2, 10, and 11
EPA Project Officer: J. David Mobley
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
13
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ASSESSMENT OF THK r'INAL
1980 NAPAP EMISSIONS INVENTORY
oy: Douglas A. Toothman
Engineering-Science, Ir.c.
Ka i rf ax , Virginia 22U30
ABSTRACT
A detailed 1980 base year emissions inventory has been developed to
support the needs of various tas'-: groups within the. National Acid Precipi-
tation Assessment Program (NAPAP). The emissions inventory was compiled
startinq with the 1980 "snapshot" inventory fr0.1 EPA's National Emissions
Data System (NL^iS) which was converted to Emissions Inventory System (EIS)
format. Updates were made to address areas whf>re the NEDS inventory was
known to be deficient. In addition to S'JX, NOX, nor.-me thane V(XJ, T.^P,
and CO which are included in NEDS, emissions estimates fvr S'J,j, N H ^, to-
tal VU_"
emissions estimates for tne highway vehicle, res i i--n tial wood c-j'ib'js t ion,
and organic solvent use area source categories have been improved. Sys-
tematic quality control checks have be?n completed for all significant
data items in the emissions inventory for major point sources. The most
recent version of the emissions inventory. Version 5.0, is now b^ing fi-
nalized. Therefore, emissions data presented herein reflect Versions
3.0 and 4.0 for which detailed summaries are available. Emissions of
SOX, NOX, and VOC, which are of primary interest for acid deposition
research, are 27.1, 23.7, and 23.3 million tons p~ r year, respectively.
Emissions in the NAPAP data base agree reasonably well with Work Group
38 and EPA/OAQPS emissions trends estimates. NAPAP fuel use data show
reasonable agreement with fuel values in DOE's State Energy Data Report.
Version 5.0 of the NAPAP data base represents the he^r detailed 1980
emissions inventory presently available.
14
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ASSESSMENT OF THE FINAL
1980 NAPAP EMISSIONS INVENTORY
INTRODUCTION
This project required development of a central, qua li ty -assured data
base of emissions of pollutants of interest for ao id deposition research
and modeling. The pollutants believed to b^ most important in acid depo-
sition processes — sulfur oxides, nitrogen oxides, primary sulfate, vola-
tile organic compounds (VO-Cs), ammonia, chlorides, fluorides, and others
— were addressed. The data needed consist primarily of emissions esti-
mates for the 19HO base year with adequate geographic and temporal detail.
The area covered includes the 48 contiguous states of the U.S., the Dis-
trict of Columbia, and the 10 provinces and 2 territories of Canada.
The starting point for the 1980 NAPAP emissions data base was the
1980 "snapshot" data file of the National Emissions Data System (NEUS),
maintained by the U.S. Environmental Protection Agency (EPA) at Research
Triangle Park, North Carolina. Activities to Create the initial detailed
NAPAP emissions inventory from the 1980 NEUS "sncirshot" file began in Jan-
uary 1983, The Fhiissions Inventory System (EIS) was selected to store
the NAPAP emissions data base. A goal of the initial conversion to EIS
was to maintain equivalency between emissions totals in NEDS and EIS.
DISCUSSION
In an effort to improve the quality of the initial NAPAP emissions
data base, updates were initiated to address areas where the NEDS inven-
tory was known to be deficient. The following updates resulted in Ver-
sion 1.0 of the inventory (11/29/83) and include:
o Incorporating latest EPA emission factors (through Supplement 14
of AP-42).
o Substituting other NEDS point source data that more represent
calendar year 1980 for 12 states.
15
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o Updating fuel type, quantity and quality, source classification
code (SCO, control equipment and efficiency, and boiler capa-
city for electric utilities that could be matched in the Pechan
unit inventory (1980) and calculating updated emissions using
AP-42 emission factors.
o Updating seasonal throughput for all boilers matched in the
Pechcin unit inventory using FPC Form 4 data for 1980.
o Adding seasonal factors for area source emissions by category.
Subsequent updates which resulted in Version 2.0 of the 1980 NAPAP
emissions inventory (12/30/83) include:
o Updating copper smelters to reflect SOX emissions in Work Group
3B inventory (1980) .
o Substituting plants in Northeast Corridor Regional Modeling Pro-
ject (NECRMP) inventory (1980) for those in NAPAP except for
power plants updated with Pechan data and plants that exhibited
no improvement i.n SOX emissions.
o Incorporating throjgh Supplement 14 emission factors in NECRMP
data substituted.
o Correcting several problems with previous power plant updates.
Additional updates made to the emissions inventory in generating
Version 3.0 (6/27/fa4) include:
o Updating power plant SOX emissions to be consistent with Pecha •>
plant inventory.
o Correcting NAPAP as appropriate to eliminate the largest fuel
discrepancies between NAPAP arj DOE's State Energy Data Report
(SEDR).
o Updating area sources to incorporate data for 15 counties pre-
viously omitted.
o Making additional power plant updates for consistency with
the Pechan unit inventory, to add plants/units not previously
matched, and to better identify plant names.
o Revising incorrect SCCs associated with fuel discrepancies and
power plant changes.
In creating Version 4.0 of the data base (9/18/84), the improvements
made include:
o Adding sulfate and ammonia emission factors, control device data,
and emissions.
16
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o Eliminating roundoff error present in earlier emission factor
files for point sources.
o Incorporating emissions estimates for point sources/pollutants
that had an emission factor but no emission estimate in the file.
o Adding latitude/longitude and/or Universal Traverse Mercator ( UTM)
coordinates for all point sources.
After some additional processing to put the data base in the format needed
b/ GCA, this version of the inventory was supplied to GCA for generating
Eulerian model input.
Version 5.0, the final 1960 NAPAP emissions inventory, was scheduled
tor completion by October 31, 1985. The additional updates being made to
create Version 5.0 of the data base include:
•-j Incorporating 1980 Canadian point and area source emissions data.
o Substituting improved 1980 utility data from the NAPAP Utility
Reference File.
o Adding chloride, fluoride, and lead emission factors, control
device data, and emissions,
o Performing a systematic quality control check for important data
base items to identify missing or anomalous data and correct as
appropriate using average or typical values.
o Updating area sourre data for highway vehicles, residential wood
combustion, and onianic solvent use to reflect improved data/
procedures for calculating VOC emissions.
o Adding total VOC emissions to the inventory for point and area
sources (previous emissions reflected non-methane VOC only).
Emissions summaries of the 1980 NAPAP emissions data base are pre-
sented in this section. Table 1 shows the difference in emissions for
the five most important pollutants from the four existing versions of
the data base. Little difference exists between Versions 3.0 and 4.0 for
SOX, nox, and VOC. Table 2 indicates that SOX emissions are dominated by
electric utilities, primarily from coal-fired generating stations in the
eastern U.S. For NOX, the largest sources are transportation (mostly
highway vehicles), electric utilities, and industrial combustion. VOC
emissions result largely from miscellaneous sources (including organic
solvent use, gasoline service stations, and forest wildfires), transpor-
taticn, and other industrial processes. The geographic breakdown of SO
17
-------
emissions in Table 3 shows that EPA Regions 5 and 4 are the largest con-
tributors, and the eastern 31 states account for over 82% of total emis-
sions. Regions 6, 5, and 4 are the highest NOX emitters, with the eastern
J1 states accounting for about 64% of national emissions. Regions 5, 4,
and 6 contribute the largest amount of VOC emissions, and the eastern 31
states account for about 66% of nationwide emissions. Table 4 indicates
that nearly all VOC and about 6H% of NOX emissions are released below 120
feet. Nearly 4U% of all SOX is released above 480 feet. Table 5 identi-
fies source category contributions to nationwide sulfate and ammonia emis-
sions. Electric utilities and industrial point sources account for over
80% of the total sulfate emissions while area sources, primarily manure
field application, contribute about 80% of the total ammonia emissions.
Table 6 summarizes Canadian emissions by source category and indicates
that electric utilities have much less influence than in the United
States. Smelters and area sources, however, are more significant emit-
ters in Canada.
CONCLUSIONS
The point and area source inventory represents year 1980 well with
over 80% of emissions of SOX/ NOX, and VOC having an indicated year of
record of 1980. Virtually all significant 3OX and NOX emitting plants
are included in the NAPAP point source file. Outside of the NECRMP do-
main, the completeness of the NAPAP point source file for VOC is likely
to be inconsistent depending on the thoroughness of the states. All
point sources have location coordinates and reasonable stack data in
Version 5.0.
Fuel summaries from NAPAP Version 3.0 and the SEDR show reasonable
agreement with NAPAP quantities being generally higher. Differences in
Version 5.0 of the inventory are likely to be less. Emissions data in
NAPAP Version 3.0 show reasonable agreement with emissions in Trends and
Work Group 3B. Some comparisons may improve when Version 5.0 of the in-
ventory is created.
Version 5.0 of the NAPAP emissions inventory represents the best
detailed 1980 emissions inventory presently available.
-------
Table 1
National Summary of Emissions
fron all Versions of the 1980 NAPAP Inventory
( 1 O3 tons/year)
Pollutant
SOX
NOX
VOC
S04
NH3
1 .0
27,916
22,905
22,582
Emissions Inventory Version
2.0
27,784
23,198
22,520
3.0
27, 1 1 1
23,667
23,269
4.0
27,222
23,833
23,307
947
4,250
Table 2
NAPAP Emissions by Source Category
( 106 tons/year)
Electric Utilities
Industrial Combustion
Residential/Commercial Combustion
Non-ferrous Smelters
Other Industrial Processes
Transportation
Miscellaneous
Total
27.1
NO
VOC
17.3
3.7
0.9
1 .2
3.0
0.9
0.1
8.1
4.5
0.7
Neg
1 .0
9.1
0.3
0.1
1 .0
0.1
Neg
4.5
8.0
9.6
23.7 23.3
19
-------
Table 3
NAPAP Emissions by Region3
( 1 fl6 tons/yea r )
NOV VOC
LPA Region 1 0.7 0.6 1.2
EPA Region 2 1.2 1.2 1.8
EPA Region 3 3.8 2.3 2.1
EPA Region 4 6.5 4.1 4.0
EPA Region 5 7.9 4.8 4.5
EPA Region 6 2.3 5.3 4.0
EPA Region 7 2.0 1.8 1.4
EPA Region 8 0.8 1.2 0,9
EPA Region 9 1.5 1.7 2.4
EPA Region 10 0.4 0.7 1.0
31 Eastern States5 22.3 15.1 15.3
Nation3 27.1 23.7 23.3
d Includes Continental U.S. only.
b Includes tier of staces from Minnesota
south to Louisiana and all states east.
Table 4
NAPAP Emissions by Release Height Range
(percent of total)
Range (ft) SOX NOX VOC
0-1 20
1 21-240
241-480
>480
Total ( 106
tons/year)
26
1 4
20
40
27.1
68
8
1 0
1 4
23.7
99
1
0
0
23
.3
20
-------
Table 5
National Summary of Sulfate and
Ammonia Rnissions by Source Category.
(1O3 tons/year)
Category
Emissions
NH-
Point Source
Electric Utility Boilers
Industrial Boilers
Commercial/Institutional Boilers
Industrial Processes
Total
Area Source
Stationary Fuel Combustion
Mobile Fuel Combustion
Field Application of Manure
Anhydrous Ammonia Fertilizer
Application
Beef Cattle Feedlots
Total
Grand Total
448
172
25
149
794
561
63
3
219
846
1 18
35
0
0
0
153
947
16
0
3,31 1
53
24
3,404
4,250
Table 6
Summary of Canadian Bnissions by Source Category
( 1 O3 tons/year)
Pollutant Emissions
Source Category
Electric Utilities
Non-Ferrous Smelters
Other Industrial
Processes
Industrial Combustion
Area Source Stationary
Combustion
Transportation
Mi seel lane ous
Total
sox
844
1,507
1 ,754
21 3
577
151
65
5,111
NOX
235
114
34
31 3
1,181
259
2,1 36
voc
5
417
<1
52
878
2,231
3,583
SU4
18
29
87
6
43
5
1
189
NH3 Alkaline
15
— —
20 96
1
3
<1
<1 6,840
22 6,955
21
-------
nFVELOPMFNT OF THE NAPAP UTILITY PFFERENCE FILE
by
Edward H. Pechan, James H. Wilson, Kristin Graves
E. H. Pechan & Associates, Inc.
5537 Henipstead Way
Springfield, Virginia 22151
EPA Contract No. 68-02-4070
EPA Project Officer:
J. David Mcbley
Air and Energy Engineering Research Laboratory
U. S. Environmental Protection Agency
Research Triangle Park, North Caroline 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985,
22
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DEVELOPMENT OP THE NAPAP UTILITY REFERENCE FILE
Edward H. Pechan, James H. Wilson, Jr., and Kristin Graves
E.H. Pechan & Associates, Inc.
ABSTRACT
Emissions from electric utilities account for a large share
of total acid deposition precursor emissions. The importance
of the utility industry has been recognized by NAPAP through
many of the activities of NAPAP1s Task Group B (Man-Made Sources),
which has sponsored work in both developing estimates of current
emissions from the utility industry and projecting future emissions.
Different components of NAPAP have overlapping but not identical
dati needs; the purpose of this project was to develop a single
data base that would meet the utility-related data needs of
all NAPAP task groups. Because existing data files were inadequate
for this purpose, Task Group B requested that E.H. Pechan &
Associates, Inc. (Pechan) develop a single, comprehensive utility-
related data file. This paper documents the resulting data
system, designated the NAPAP Utility Reference File (NURF).
-------
DEVELOPMENT OP THE NAPAP UTILITY REFERENCE FILE
INTRODUCTION
Different components of NAPAP have overlapping but not
identical data needs; the purpose of this project was to develop
a single data base that would meet the uti1ity-related data
needs of all NAPAP task groups. Existing data files developed
under Task Group B sponsorship were inadequate for this purpose.
For example, Version 4.0 of the ?.980 NAPAP emissions inventory
(Toothman, 1984), between its point source and area source compo-
nents, includes only anthropogenic sources of major acid deposition
precursor pollutants for that year. As another example, the
Unit Inventory (Pechan, 1983) was developed to meet data requirements
of the Advanced Utility Simulation Model (AUSM); the Unit Inventory
contains unit-specific information for only a subset of generating
units, however. In response to the needs of NAPAP, Task Group
B requested that E.H. Pechan & Associates, Inc. (Pechan) develop
a single, comprehensive utilitv-related data file. This data
base, designated the NAPAP Utility Reference File (NURF), will
be used as an input to Task Group B utility emissions models.
DISCUSSION
Figure 1 provides an overview of the NURF data system.
NURF comprises four component files: the master unit data file
(containing information on all electric utility generating units),
the fuel specific emissions file (containing emissions information
by fuel and unit), the stack parameters file (containing stack
information on a unit-specific basis), and the announced unit
file (containing unit-specific information on units coming on-line
or converting to coal-firing after 1980). In addition, as shown
in Figure 1, three files were derived from NURF and made available
for distribution: the NAPAP emissions inventory updates file
(containing corrections and addendums to Version 4.0 of the
1980 NAPAP emissions inventory) , and information for AUSM, including
a 1980 generating Unit Inventory (an updated version of the
existing file containing unit-specific information on larger
generating units and aggregated information on smaller units)
and the announced inventory (containing information on units
coming on-line or planned for conversion to coal after 1980).
NURF was developed using information from Version 4.0 of
the 1980 NAPAP emissions inventory, the Unit Inventory, and
new data; additional updates were obtained from a variety of
sources. Table 1 lists major data inputs to NURF. In developing
NURF, the greatest reliance was placed on data available from
public sources, especially files available in machine-readable
form. A variety of processing techniques were required to format
-------
Figure 1
OVERVIEW OF NURF ELEMENTS
ro
CJl
NURF Component
Files
Master Unit
Data File
Fuel Specific
Emissions File
Stack
Parameters File
Announced
Unit File
NURF Derivative Files
a
Input to 1 980
NAPAP Emissions
Inventory,
Version 5.0
1
Input to I
AUSM
1 980 Generating
Unit iventory
Announced
Inventory
existing plants emitting S02, NO , or TSP
existing plants aggregated
cplanned plants (or conversions)
Note: The three NURF derivative files were made available for distribution.
-------
Table 1
Major Data Inputs to NURF
CT>
Mame
EIA Form 759
FPC Forr, 423
FPC Forn 6?
FGDIS
NAPAP Inventory
Generating Unit
Reference File
EPA State
Implementation
Plan file
NERC planned plants
NERC coal conversions
DOE coal conversions
Pechan nuclear plant
status
NO control update
AWL firing data
IX££i
A
A
A
A
A
A
A
M
M
M
M
M
A
Lfii'fiLj
Plant
°lant
Boiler,
Boiler
Boiler
Unit
Unit
Uni t
Unit
Unit
Unit
Unit
Url t
tfLLiliil
Fuel consumption and genernticr,
Cost and quality of fuels
Fuels cor.surr.ed, control equipment,
firing typo, and tot ton type
SO- scruttor data
Stack para-^ters
Year online, year retired, capacity
TSP, SO and NO Emission
Limits x
New plants
Plants converted or planning
conversion to coal
Plant: converted or planning
corversion to coal
Status of planned nuclear units
NO control measures
Suppl'vnental data on firing typ^s
and botton type
•ArAutonated
-------
the available information from these sources into a single consistent
data system.
Other data elements (e.g., heat rate and capacity factor)
were simply not available from standard sources and, therefore,
had to be calculated from data that were available. For those
cases in which the calculated values were unreasonable, judgements
were made as to which of the input values were the most accurate;
other data were adjusted on a unit-specific basis so that all
resultant values were reasonable.
Because of the wide range of types of data processing required
to create NURF, a combination of programming languages and meth-
odologies was used in its development. Initial data reduction
of the larger data files was performed by a series of programs
written in Programming Language/I (PL/I). These larger files
were reduced to one record per unit (or plant if a plant-level
file). The reduced files were converted to a consistent format
using the Statistical Analysis System (SAS). These SAS files
were then combined and manipulated using a series of SAS programs.
Examples of the processing required include calculation of default
state average fuel quality data and assignment of plant technology
codes. The result of these manipulations was a final NURF in
SAS format. The final processing steps converted the NURF data
in their component file form into the set of derivative files
which were discussed earlier.
Development of NURF was a multi-step process. The first
step was to identify the universe of units to be included.
Because the coverage of the major contributing data files differs,
it was necessary to compare several data files on a plant-specific
basis in order to develop the best possible universe of facilities.
Conflicts between these files occurred in many cases. These
had to be resolved on a case-by-case basis. In cases where
a conflict occurred, if two or more files contained consistent
information, those data were chosen. Otherwise, preference
was given to the U.S. Department of Energy's (DOE) 1980 Form
67 data (U.S. DOE, 1980b) and the Generating Unit Reference
File (GURF -- U.S. DOE, 1981b), both of which contain the most
recently updated information for 1980.
Operating characteristics such as total generation and
total fuels consumed for generation were obtained from DOE's
Form 4 (U.S. DOE, 1980a). Form 4 is a monthly data base; for
use in NURF, however, the monthly data for 1980 were aggregated
into annual totals. Form 4 data are reported by plant and prime
mover. For example, a plant having both steam and combustion
turbine units would have fuel use and generation data provided
for each of these two prime movers.
Unit-specific operational data for 1980 were estimated
by applying 1980 unit shares computed from 1980 Form 67 data
on fuel use and generation to the corresponding data elements
from the 1980 plant and prime mover totals from Form 4. This
27
-------
method was adopted to correct erro-rs associated with the use
of incorrectly reported units on Form 67 submissions. Because
the Form 67 data were used only to compute shares of validated
totals, unit errors in Form 67 data were not carried through
to NURF.
Fuel quality data were obtained from the Federal Power
Commission (FPC) Fcrro 423 (U.S. DOE, 1981a). For units with
no reported Form 423 information, state average data obtained
from Form 423 were used.
CONCLUSIONS
NURF is a central repository of data for utility operations
and emissions, making analysis of the electric utility sector
convenient. The largest sources of generated power and sulfur
dioxide emissions have been thoroughly covered. In addition,
data on all large units (including fossil-fired, nonfossil-fired,
existing, and planned) are provided in a comprehensive manner.
The major user files derived from NURF are inputs to Version
5.0 of the 1980 NAPAP emissions inventory and the 1980 generating
Unit Inventory, an input to AUSM. Due to data coverage and
desired data base size considerations, both of these derivative
files have been segmented into components comprising large and
small generating units. The size cutoff utilized in the Unit
Inventory is more restrictive than that used to update Version
4.0 of the 1980 NAPAP emissions inventory because the Unit Inventory
is used as the basis for projection of emissions and fuel use
in AUSM; detailed projections of the activity of smaller units
cannot reasonably be made. For example, the 1980 generating
Unit Inventory includes unit-specific data on only 30 percent
of all fossil-fired units, while Version 5.0 of the 1980 NAPAP
emissions inventory contains detailed data on 62 percent of
all fossil-fired units; because the units represented in detail
in these data files are the larger units, these files have more
extensive coverage of generating capacity, generation, and emis-
sions. For fossil-fired generating capacity, 92 percent of
the total is represented in unit-specific data in the 1980 generating
Unit Inventory and 96 percent of the total is included in Version
5.0 of the 1980 NAPAP emissions inventory file. Generation
and emissions coverage is almost complete for Version 5.0 of
the 1980 NAPAP emissions inventory file and is extremely high
(more than 98 percent) for the 1980 generating Unit Inventory. Note
that the Unit Inventory also includes nonfossil units, which
are not included in the NAPAP inventory-
Table 2 provides some summary statistics on NURF's coverage
of generation capacity, generation, and emissions, by fuel and
plant type. Fossil-fired units account for more than 75 percent
of capacity and generation, and 100 percent of emissions. Table
2 also shows that the proportion of coal-fired generation is
larger than the proportion of coal-fired capacity; the opposite
is true for oil-fired units. As expected, coal-fired units
28
-------
Table 2
Summary Statistics by Plant Type
Plant Type
Coal steam
Oil steam
Gas steam
Oil nonsteam
Gas nonsteam
TOTAL FOSSIL
Ifciclear
Hydroelectric
Other
TOTAL
Capacity % of
(W) Total
242,700 42
67,600 11
93,500 16
29,300 5
24,400 4
457,500 78
48,900 8
81,500 14
900 0
588,800 100
Generation % of
(TWh) Total
1,171,000 51
217,000 10
338,000 15
7,000 0
21,000 1
1,754,000 77
233,000 10
287,000 13
5,000 0
2,279,000 100
S02 % of
(10 3 tons) Total
— ^
16,070 91
1,320 8
120 1
10 0
0 0
17,520 100
0 0
0 0
0 0
17,520 100
NOX % of
(103 tons) Total
5,200 79
400 6
750 12
40 1
100 2
6,490 100
0 0
0 0
0 0
6,490 100
TSP % of
(103 tons) Total
570 88
60 9
20 3
3 0
2 0
655 100
0 0
0 0
0 0
655 100
Note: Percentages calculated from detailed data.
-------
account for the majority of emissions.
NURF was compiled from every major publicly available data
file. By matching and combining this information, the development
of NURF gathered all relevant information into one data file.
Discrepancies that existed in the past between data bases are
resolved in NURF; the result is a cohesive and comprehensive
electric utility operations and emissions data file. Because
NURF is a composite of the best data available from a number
of sources, it does not exactly match any other individual file.
Aggregate measures of key variables are in excellent agreement
with published statistics, however. NURF is important as an
input to NAPAP's emission efforts, as well as an important utility
operations data base in its own right.
REFERENCES
Pechan, 1983: E.H. Pechan & Associates, Inc., "Electric Utility
Unit Inventory: Database Technical Documentation," prepared
for University of Illinois at Urbana Champaign, May 1983.
Toothman, 1984: Toothman, Douglas A., John C. Yates, and Edward
J. Sabo, "Status Report on the Development of the NAPAP Emission
Inventory for the 1980 Base Year and Summary of Preliminary
Data," EPA-600/7-34-091 (NTIS No. PB8b-167930), December 1984.
U.S. DOE, 198Ca: U.S. Department of Energy, "Monthly Power
Plant Report," EIA-759 data file, 1980.
U.S. DOE, 1980b: U.S. Department of Energy, "Steam-Electric
Plant Operation and Design Report," EIA-767 data file, 1980.
U.S. DOE, 1981a: U.S. Department of Energy, "Cost and Quality
of Fuels for Electric Utility Plants," DOE/EIA-0075(80), May
1981.
U.S. DOE, 1981b: U.S. Department of Energy, "Inventory of Powf-r
Plants in the United States: December 1980," DOE/EIA-0348(83),
1984.
30
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DEVELOPMENT OF AN EMISSIONS INVENTORY TO
SUPPORT TESTING OF THE EULERIAN REGIONAL
ACID DEPOSITION MODEL
Frederick M. Sellars
GCA/Technology Division
Bedford, Massachusetts 01730
EPA Contract No. 68-02-3997
Task No. 9
EPA Project Officer:
J. David Mobley
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
31
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DEVELOPMENT OF AN EMISSIONS INVENTORY TO
SUPPORT TESTING OF THE EULERIAN REGIONAL
ACID DEPOSITION MODEL
by: Frederick M. Sellars
GCA/Technology Division
Bedford, Massachusetts 01730
ABSTRACT
One of the most extensive applications of the National Acid
Precipitation Assessment Program (NAPAP) Emissions Inventory is to
support development and testing of the Eulerian Regional Acid Deposition
Model (RADM). To accomplish this, the 1980 NAPAP Emissions Inventory
had to be further resolved temporally, spatially, and by component
species. Annual emissions had to be allocated to hourly for a typical
weekday. Saturday, and Sunday in each season; county-level area sources
and minor point sources had to be spatially resolved to modeling grid
cells; NO emissions had to be split into NO and NO,,; TSP emissions
had to be assigned to alkalinity classes; and VOC emissions had to be
apportioned into 30 photochemical reactivity classes. To create the
NAPAP Eulerian Modeling Emissions Inventory, sets of temporal, spatial,
and pollutant species allocation factors were developed and applied to
the annual data. This paper present., a discussion of the processes,
assumptions, and data sources used to generate the 1980 NAPAP Eulerian
Modeling Emissions Inventory and presents results of that effort.
32
-------
DEVELOPMENT OF AN EMISSIONS INVENTORY TO
SUPPORT TESTING OF THE EULERIAN REGIONAL
ACID DEPOSITION MODEL
INTRODUCTION
The 1980 NAPAP Emissions Inventory contains annual emissions from
point and area sources, with area sources compiled on a county basis.
To support testing and development of the Eulerian Regional Acid
Deposition Model (RADM):
• annual emissions had to be further resolved to hourly values;
t county-level area source data had to be spatially allocated to
grid cells;
• NOX emissions had to be split into NO and N02J
• TSP emissions had to be assigned to alkalinity classes; and
• VOC emissions had to be assigned to photochemical reactivity
classes.
To create Version 5.2 of the 1980 NAPAP Eulerian Modeling Emissions
Inventory, sets of temporal, spatial, and pollutant species allocation
factors were developed and applied to the annual data contained in the
1980 NAPAP Emissions Inventory. Development of a more efficient and
flexible data handling system, the Flexible Regional Emissions Data
System (FREDS), was also required. Development of the 1980 NAPAP
Eulerian Modeling Emissions Inventory, the associated allocation
factors, and the data handling system is discussed below.
33
-------
DISCUSSION
Temporal Allocation
Temporal allocation of the NAPAP emissions data was accomplished by
applying a set of seasonal, daily, and hourly fractions to the annual
emissions totals to generate hourly emissions values for a typical
weekday, Saturday, and Sunday in each season.
For area sources, temporal allocation factors were derived based on
oublished activity statistics (e.g., heating degree days, gasoline
Sales, air traffic activity). Where such data were unavailable,
patterns for similar studies were utilized or engineering judgement was
employed.
For electric utilities in the Eastern United States, State and SCC-
specific hourly temporal factors were developed based on hourly power
plant fuel use data previously collected for use in EPRI's SURE Program.
The SURE data were also used to derive SCC-specific patterns for the
rest of the United States. For other point sources, point-specific
patterns were derived based on operating rate information contained in
the annual inventory records.
Since the NAPAP study area spans several time zones, temporal
allocation factors were adjusted to represent Greenwich Mean Time.
Adjustments were alsf; made to reflect Daylight Savings Time during the
appropriate seasons in applicable areas.
Spatial Allocation
The NAPAP modeling grid system (Version 5.2) is comprised of 63,000
grid cells (210 rows, 300 columns) dimensioned 1/6° latitude by 1/4"
longitude (approximately 20 x 20 km). Point source records in the NAPAP
Emissions Inventory contain locational information making their
assignment to grid cells straightforward. Area source emissions are
allocated from counties to grid cells using spatial allocation factors,
fractional multipliers that assign a portion of each county's emissions
to a particular grid cell. Generally, since the subcounty distribution
of emissions is unknown, emissions are apportioned on the basis of the
known distribution of some surrogate indicator.
34
-------
Spatial allocation factors were derived for population, housing,
total land area, 10 land use classifications, and 1 composite land use
category. Population and housing counts from the 1980 Census were
obtained by enumeration district. Spatial allocation factors were
created for those two surrogates by assigning populations and housing
units to grid cells based on the location of the centroid of each
enumeration district.
Land use data, derived from Landsat mosaic images, were obtained
and contain 10 land cover/use percentages for each NAPAP grid cell.
These land use percentages were utilized with grid/county land area
relationships to derive spatial allocation factors. The final step in
spatially allocating county-level emissions to grid cells was to assign
the most appropriate of the 14 possible surrogates to each of the 88
area source categories.
Species Allocation
To be used in the RADM, three of the pollutants in the NAPAP
Emissions Inventory. NO , TSP, and VOC, had to be further refined.
NO emissions had to be split into NO and NO,,, TSP emissions
assigned to alkalinity classes, and VOC emissions broken down by
photochemical reactivity class.
Profiles of NO emissions, referenced by Source Classification
A
Code (SCC), were developed using patterns previously derived for the
SURE and Northeast Corridor Regional Modeling Project (NECRMP)
inventories. Since the modelers desire the flexibility to test a number
of different chemistries, a more complex approach was necessitated for
VOC emissions. Using primarily published information, a set of species
profiles were developed. Each profile provides a breakdown of a
category's VOC emissions into a typical set of component species. By
distributing emissions to individual species, the profiles become
independent of any reactivity scheme, providing the flexibility desired
by the modeling community. To "speciate" emissions, two additional
files were employed. First, the SCC Index File matches each SCC with
the most appropriate profile. Next, the Class Assignments File assigns
each of the 160 species contained in the profiles to one of the 30
photochemical classes specified by the modelers. Alkaline dust emission
35
-------
Spatial allocation factors were derived for population, housing,
total land area, 10 land use classifications, and 1 composite land use
category. Population and housing counts from the 1980 Census were
obtained by enumeration district. Spatial allocation factors were
created for those two surrogates by assigning populations and housing
units to grid cells based on the location of the centroid of each
enumeration district.
Land use data, derived from Landsat mosaic images, were obtained
and contain 10 land cover/use percentages for each NAPAP grid cell.
These land use percentages were utilized with grid/county land area
relationships to derive spatial allocation factors. The final step in
spatially allocating county-level emissions to grid cells was to assign
the most appropriate of the 14 possible surrogates to each of the 88
area source categories.
Species Allocation
To be used in the RADM, three of the pollutants in the NAPAP
Emissions Inventory, NO , TSP, and VOC, had to be further refined.
NO emissions had to be split into NO and NOp, TSP emissions
assigned to alkalinity classes, and VOC emissions broken down by
photochemical reactivity class.
Profiles of NO emissions, referenced by Source Classification
A
Code (SCO, were developed using patterns previously derived for the
SURE and Northeast Corridor Regional Modeling Project (NECRMP)
inventories. Since the modelers desire the flexibility to test a number
of different chemistries, a more complex approach was necessitated for
VOC emissions. Using primarily published information, a set of species
profiles were developed. Each profile provides a breakdown of a
category's VOC emissions into a typical set of component species. By
distributing emissions to individual species, the profiles become
independent of any reactivity scheme, providing the flexibility desired
by the modeling community. To "speciate" emissions, two additional
files were employed. First, the SCC Index File matches each SCC with
the most appropriate profile. Next, the Class Assignments File assigns
each of the 160 species contained in the profiles to one of the 30
photochemical classes specified by the modelers. Alkaline dust emission
35
-------
factors were used to develop allocation factors to apportion TSP into
five alkalinity classes. A list of species contained in the NAPAP
Eulerian Modeling Emissions Inventory is provided in Figure 1.
Eulerian Modeling Files
In addition to development of allocation factors to address the
above requirements, a data handling system capable of creating subsequent
versions of the NAPAP Emissions Inventory has been developed. The
Flexible Regional Emissions Data System (FREDS), consisting of six
primary independent subsystems written in the command language of the
Statistical Analysis System (SAS), is being used to preprocess EIS
formatted emissions data for use in regional scale atmospheric
simulation modeling. The function of each module and its relationship
to the system as a whole are presented in Figure 2.
In addition to preprocessing annual emissions data in Emissions
Inventory System (EIS) Master File format and allocating these emissions
by time, pollutant species, and location, FREDS calculates emissions
uncertainty at any given level of temporal, species, and spatial
allocation. For example, percent error values can be assigned to annual
emissions which have not been allocated in space, time, or by pollutant
species. On the other hand, the percent error values can be assigned
for SCC level emissions which have been fully allocated.
RESULTS
Hourly emissions of S0x, N0x> VOC, and NH3 for a typical
summer weekday, nationwide, are shown in Figure 3. Figure 4 shows the
distribution of VOC emissions by reactivity class as a function of time
for a typical summer weekday. Spatial distribution of SO emissions
for 1600 Greenwich Mean Time of a typical summer weekday is depicted in
Figure 5. (Note that, for ease of interpretation, each grid cell
depicted in Figure 5 actually represents 24 of the NAPAP grid cells.)
36
-------
CONCLUSIONS
An emissions data base with the spatial, temporal, and species
resolution necessary to support development and testing of the
Eulerian Regional Acid Deposition Model (RADM) has been developed.
A corresponding data handling system, which addresses the extensive
requirements of the RADM, has also been developed and provides
substantial improvements in efficiency over the predecessor system.
37
-------
TEMPORAL RESOLUTION:
GEOGRAPHIC DOMAIN/RESOLUTION:
POLLUTANTS
Hourly emissions values for a typical
weekday, Saturday, and Sunday for all
four seasons
48 States and Canada; separate
major point source file with minor
point sources and area sources
assigned to 63,000 20 x 20 km
grid colls
SO,
so4
TSP:
- Ca
- Mg
K
- Na
Pb
CO
HC1
HF
NO
N02
NH3
VOC:
- Methane
- Ethane
- Ethylene
- Propane
- Propylene
- N-butane
- 1,2-butene
- Isobutane
VOC (cont.)
- Isobutene
- Trans-2 butene
- Pentane
- Isopentane
- 2,3-dirnethyl butane
- Other alkenes
Other alkanes
- Formic acid
- Acetic acid
- Other organic acids
- Formaldehyde
- Acetaldehyde
- Propionaldehyde
- Acetone
- Other ketones
- Other aldehydes
- Xylene
- Benzene
- Toluene
- Ethyl benzene
- Other aromatics
Figure 1. Contents of the 1980 NAPAP Eulerian Modeling
Emissions Inventory.
38
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ANNUAL EIS
EMISSIONS DATA
MODEL DATA EXTRACTION MODULE
Accepts EIS formatted annual emissions data and extracts
pertinent information only. A SAS data file is created
for each user-defined industry group. Separates major
point sources from minor sources and area sources based
on user-designated size cutoffs.
l
TEMPORAL ALLOCATION MODULE
Matches each emission record with the appropriate set of
seasoi al, daily, and hourly temporal allocation factors
from the Temporal Allocation Factor File. Where a pattern
is not supplied, one will be generated based on operating
hours data contained in each EIS record.
SPECIATION MODULE
Matches each emission record with the appropriate set of
speciation factors contained in the Speciation Factor File.
Can provide 30 subspecies each for up to 15 pollutant
categories. Resolves NO- into NO and NO;?, TSP into
alkalinity classes, and VOC into reactivity classes for NAPAP.
SPATIAL ALLOCATION MODULE
Assigns point sources to grid cells based on latitude/
longitude. Assigns area sources to grid cells using
spatial allocation factors based on surrogates (e.g.,
population, housing, land use) and matchings of area
source categories to most appropriate surrogate indicators.
i ~~
UNCERTAINTY MODULE
Calculates estimates of uncertainty associated with the
emissions data and corresponding temporal, spatial, and
species allocation factors.
i
NAPAP MODEL INPUT PREPROCESSOR
Accepts SAS emission records into which allocation factors
have been merged. Applies allocation factors to emissions
as designated by the user. Sorts and reformats as required
by the Regional Acid Deposition Model (P.ADM).
Figure 2. Major components of the Flexible Regional
Emissions Data System.
39
-------
Q
CO Z
UJ <
CO
a SOX
i + NOX
o voc
A NH3
t * ^
>"**-** *
-------
AJ.KANES •_, ALKtNES
:•? kCTHANE & ORQAMC ACOS
0)
u
J
t~~,
s .
• 'I--.
-~."
c^rTi
• 'r ^ r - * ' *<
* *• • * '* *«
i". r-\ •"; p •; — •".
^rU-iH":!-
r~i
l ' „
; -«
(i ^ 1 0 I I i z 1 1 I t 1 1 It, ' "• ! a 1 9 i<-' 21 ^2 2} 21
HOUR (GMT) TYPICAL SUMMER WEEKDAY
Figure 4. Diurnal VOC distribution by reactivity class for a
typical summer weekday, contiguous United States.
41
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LEGEND: SOX LHJ<5 iSiSSI 5-20
-20
Figure 5. SOX emission density (g-moles/hr/km2),
1600 GMT for a typical summer weekday.
-------
UNCERTAINTY ANALYSIS OF NAPAP EMISSIONS INVENTORY
Carnen M. Benkovltz
Brookhaven National Laboratory
Upton. New York 11973
EPA Interagency Agreement No. DU89930122-01-1
EPA Project Officer:
J. David Mobley
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
U.S. DOE Project Officer:
Edvird C. Trexler
Fossi1 Energy
U.S. Department of Energy
1000 Independence Ave. SW
Washington, DC 20460
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, SC
November 12-14, 1985
43
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UNCERTAINTY ANALYSIS OF NAPAP EMISSIONS INVENTORY
Carmen M. Benkovitz
Brookhaven National Laboratory
ABSTRACT
A major goal of Task Group B is the development and maintenance of
detailed inventories of anthropogenic emissions to support acid deposition
research. Estimates of the uncertainties of the emissions values are an
integral part of any inventory developed. Detailed quantification of these
uncertainties in the scale required by NAPAP researchers has never been
attempted before. Methods used to estimate emissions were studied, and sta-
tistical methodologies were derived which will provide the best estimate of
the uncertainties associated with these emissions values. These methodolo-
gies do not rely on any assumptions as to the statistical properties of the
data needed to quantify the emissions uncertainties. Auxl'iary data needed
to estimate the uncertainties have been identified. A basic framework com-
puter software has been developed to allow the calculation of the uncertain-
ties associated with the emissions values in the NAPAP inventory. A work-
shop was held during which expert opinion was solicited, and the Delphi
method was applied to arrive at quantitative estimates for the auxiliary
data needed to calculate the uncertainties of emissions values for the NAPAP
i960 base year. Statistical formulations have been developed to incorporate
these data into the methodologies selected to estimate the uncertainties
associated with the emissions values. Development of the computerized data
base and calculation of the emissions uncertainties are proceeding. Meth-
odologies are being developed for the use of expert opinion to generate the
auxiliary data needed to calculate emissions uncertainties for the NAPAP
1985 base year. Calculation of the 1985 base year uncertainties is expected
to follow the 1985 data base development.
44
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INTRODUCTION
A major goal of Task Group E is the development and maintenance of
detailed inventories of anthropogenic emissions to support both assessment
of the effects of acid deposition and the development, evaluation, and use
of long range transport and transformation models for acid deposition
research. Estimates of the uncertainties of the emissions values are an
integral part of any inventory developed. The objectives of this project
are:
1. To develop a methodologies framework to assess the uncertainties
associated with the emissions data as presented in the NAPAP emissions
inventory.
2. To develop and implement a prototype software package to calculate
the uncertainties associated with the emissions values of the NAPAP emis-
sions inventory.
3. To develop the data base needed to calculate the uncertainties
associated with the values for the 1980 base year emissions.
4. To develop the data base needed to calculate the uncertainties
associated with the emissions values for the 1985 base year.
DISCUSSION
The NAPAP emissions inventory was based on the National Emissions Data
System (NEDS) currently operated by the Office of Air Quality Planning and
Standards (OAQPS) of EPA. NEDS provided the basic data froir which all other
levels of aggregation or disaggre^ation will be calculated. The basic NEDS
data are statistical averaged parameters which allow the calculation of
yearly emissions of the five criteria pollutants (particulates, SOX,
NOX, hydrocarbons, and CO) on an individual source/process basis for point
sources and on a county level for area sources. Current plans call for the
application of spatial, temporal, and species disaggregation algorithms
which will be based on disaggregation factors (or modifications thereof)
developed for the Northeast Corridor Regional Modeling Project (NECRMP).
Higher levels of aggregation will be calculated as sums of the basic NAPAP
data.
For each individual point source/process, yearly emissions are esti-
mated using one of the following methods:
1. Stack tests or other emission measurements
2. Material balance
3. Calculated using federal (AP-42) emission factors, where emission
factors are the rate at which a pollutant is released as a result of •rme
activity
45
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4. Guess
5. Calculated using special emission factors.
Emissions estimated using Methods 3 and 5 are calculated using the
equation:
EM = E (EF1)(A1)(Fl) (O (1)
i=l
where
EM = total emissions from a point source of a given pollutant
P = number of processes contributing to emissions from point source
EF^ = emission factor for process i
AJ = ash or sulfur content of fuel used by process i (if appropriate)
Fj = material or fuel throughput for process i
C = (1-control efficiency of control equipment) for a given pollutant
Yearly emissions for area sources are calculated by geographic county
using th'i equation:
EMC = E EMa = T. (EFa) (Aa) (ACa) (ADa) (2)
a=l a=l
where
EMC = area source emissions for county c
A = number of activities contributing to emissions in county c
EMa •» area source emissions from activity a for county c
EFa = area source emission factor for activity a (this parameter can
also be county specific)
Aa - ash or sulfur content of fuel used in activity a (if appropriate)
ACa = appropriate measurement of level of activity a in county c
ADa = adjustment factor for area source category
Several previous projects have addressed the problem of assigning, in
statistical terms, quantitative values to the errors in emissions data.
Final reports from the following projects were reviewed.
46
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1. Weighted Sensitivity Analysis of Emissions Data, project conducted
by IBM Corporation under contract to the Office of Air Quality
Planning and Standards (OAQPS), EPA, July 1973.
2. Source Inventory and Emission Factor Analysis (SIEFA) project con-
ducted by PEDCo - Environmental Specialists, Inc., under contract
to OAQPS, September 1974.
3. Emissions Inventory for the SURE Region, project conducted by GCA
Corporation under contract to the Electric Power Research Institute
(EPRI). April 1981.
4. Emissions, Costs and Engineering Assessment, Work Group 3B,
US-Canada Memorandum of Intent (MOI) on Transboundary Air Pollu-
tion, June 1982.
5. Preliminary Evaluation of Acidic Deposition Assessment Uncertain-
ties, project conducted by Argonne National Laboratory (ANL) under
contract to the U.S. Department of Energy, November 1982 (prelimi-
nary report).
All these projects have based their calculations on the statistical
formulas for error propagation as derived for "small" values of the errors;
i.e., the Taylor series expansion included only the first derivatives of the
function. Some of the error values used in subsequent calculations have
been as high as 80-90% of the mean.
In calculating the mean squared error of emissions estimated such as
those above, we take the stance that the component parts of each expression
are themselves estimated, and that these component estimates have known (or
estimable) expected values and variances. Further, the estimation errors of
the components are independent of one another. The mean squared error of
the emissions estimate then follows from simple formulas giving variances of
algebraic combinations of random variables; e.g., for N independent random
variables U^,..., UN:
= £V(Ui) (3)
n E2(Ut) + V(Ui) - uE2 (4)
Since the errors of estimation are presumably independent across geo-
graphic space, the mean squared error of the estimate of an aggregate is
simply the sum of the mean squared errors of its components.
The second objective of this project addresses the design and implemen-
tation of the basic framework of computer software needed to calculate
uncertainties associated with yearly emissions values for both point and
area sources. The conceptual .-sign is independent of the software system
used to support the NAPAP inventory; the design and implementation of the
software modules will allow portability between computer systems and will be
as independent as possible of the current NAPAP inventory software system.
Outputs generated by this software include values for the uncertainties of
47
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emission, at the point, plant, county, state, or national level for point
sources and at the couaty, state, or national level for area sources.
Uncertainty values associated with each parameter used in calculating
emission values are expected to be applicable to whole classes of these
parameters rather than just to individual sources. To avoid needless
repetition of data (with the associated increase in storage costs and the
ever present danger of errors at update times), a file with uncertainty
"profiles" was designed. When the data are developed, this file will con-
tain ail the variance information needed to calculate the uncertainty value
associated witl. the yearly emissions of a point source or an area source
category. Each uncertainty profile will be identified by a unique code; at
retrieval time the appropriate uncertainty profiles can be referenced to
allow the calculation of uncertainty values associated with the reported
emissions. Figure I presents a schematic of this design.
Given the wide range of elements requiring uncertainty estimation for
eventual use in estimating the uncertainty of the emissions values in the
1980 NAPAP Emissions Inventory, the use of a panel of experts was considered
as an approach to begin the task of building the data base needed to perform
these calculations. As the initial activity of Objective 3 for this
project, an uncertainty workshop concept was formulated to convene a panel
with expertise in many of the elements included in an emissions inventory
uncertainty analysis. The 1980 NAPAP Emission Inventory Uncertainty Work-
shop was held at the EPA Air and Energy Engineering Research Laboratory,
Research Triangle Park, North Carolina, on May 7, 1985. The panel was
queried on individual uncertainty estimates for the elements discussed above
which are part of the emissions estimation process. The Delphi technique
was applied to elicit the experts' opinions in a systematic manner leading
to useful results. This technique involves iterative questionnaires admin-
istered to individual experts; feedback of results accompanies each itera-
tion of the questionnaire. This process continued until a convergence of
opinion was reached. The end product is the consensus of experts, including
their commentary, on each of the questionnaire items.
NAPAP Emissions
Inventory
Data Files
Uncertainty
"Profiles" File
Emissions Reports
- emissions values
- uncertainty values
Figure 1
Software to Calculate Uncertainty Values
48
-------
For each uncertainty value desired, the workshop participants were
asked to estimate p in the statement: "90% of the data fall within p% of
the mean." Table 1 summarizes the results of the workshop.
To allow the use of the values developed in the workshop with Equations
(3) and (4) the concept of "fractional error" was developed. Suppose 9 ~ N
(9, a ) so that the quoted phrase above is equivalent to:
Pr f (l-p) 9 <_ 9 _< (1+p) 01 - 0.9
zo
that is, p = — where, for the normal distribution, z - 1.6448. We call p
the "fractional error associated with *} as an estimate of ^ . "
Fractional errors may be developed for algebraic combinations of inde-
pendent random variables as follows:
N 2 N
> for X - T. Vl (5)
1-i 1-1 i-l
N N
P2 - z2 n (1 + k2P2.) -L for X - n I'l (t>)
i-1 bl i-l
(Note that the relation between p and the variance depends on the
normal assumption, and also that the product of normal random variables is
not norma I. )
Table 2 presents the distribution of confidence rating values of the
point source emis'lon factors by pollutant. Uncertainty profiles were
developed based on the Delphi results, and a subset of the NAPAP I960 base
year Version 3 major point source file was used to perform initial calcula-
tions. The subset chosen Included data for the state of Delaware and for
the District of Columbia. Preliminary results Indicate that, for annual
point source emissions, calculated uncertainties are in the range of 20-100%
for individual point sources and in the range 5-14% at the state level.
Uncertainty profiles for annual emissions from area sources are currently
being developed; uncertainty calculations will follow.
The use of expert teams will be extended in Objective 4 of this pro-
ject. A draft plan for the development of the uncertainty values for the
1985 data base has been prepared. A finer breakdown of source categories
and an increased number of pollutants are to be considered in the 1985 base
year exercise. Four expert teams have been identified; these teams will
address the utility, industrial combustion, Industrial processes, and trans-
portation sectors. Expert opinion will be obtained via individual inter-
views using the most appropriate formulation of probability encoding tech-
niques. A classical statistical approach will be followed -- explicit
specification of an underlying model followed by derivation of the problem
49
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Table 1
Proposed Uncertainties for the NAPAP 1980 Base Year Inventory
Uncertainty Range (%)
Parameter
Fuel S content
Point source emission factors
Method 1 (stack tests)
2 (material balance)
3 (AP-42 emission factors)
confidence rating A
B
C
D
E
5 (state emission factor)
4,6,7,0 and blank
Point source production throughput
Control equipment efficiency
Area source emission factors
Mobile sources
"Other" sources
Area source activity level
Mobile
Other
Point source temporal apportionment
Seasonal profiles
Dally profiles
Hourly profiles
Area sources temporal apportionment
Seasonal profiles
Daily profiles
Hourly profiles
Area sources spatial apportionment factors
Chemical speciatlon factors
N0/N02
voc
SOX
25
10
10
25
50
75
100
25
100
15
25
*
25
10
25
50
10
25
50
25
•Apply same criteria as for point source emission
NOX
25
25
10
25
50
75
100
50
100
15
25
50
25
10
25
50
10
25
50
25
VOC
25
50
10
25
50
75
100
50
100
15
25
100
100
10
25
75
10
25
75
25
Across all
Pollutants
10
25
25
25
100
factors.
50
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Table 2
Emission Factor Confidence Level (from EIS Point Source Emission Factor File)
I
1 I
I
2 I
I
3 I
I
41 27 I
I
5 I I 8
I
I I....
0 10
PERCENT
I
1 I
I
2 I
I
3 I
I
41 18 I
I
+
5 I I 6
I
I I....
0 8
PERCENT
(
PERCENT 1
Sulfur Oxides
134 I 40.6
90 I 27.3
71 I 21.5
8.2
2.4
I I I I
20 30 40 50
Nitrogen Oxides
104 I 34.7
88 I 29.3
84 I 28.0
6.0
2.0
I I I I
16 24 32 40
CUMULATIVE
(Continued)
-------
Table 2(continued)
CUMULATIVE
PERCENT PERCENT
Volatile Organic Compounds
14.8 14.8
I
II 111 I
+
I
, +
21 369 I 49.1 63.9
, . •».
I
31 172 I 22.9 86.8
+
I
41 83 I 11.1 97.9
— — — — — — =• — •*•
I
—+
5 I I 16 2.1 100.0
I
I I I I I I
0 10 20 30 40 50
PERCENT
52
-------
solution ii"der the assumptions of the model. Towards this end, a documenta-
tion packet is being compiled to be sent to participants on expert teams
prior to the interviews. All appropriate definitions, assumptions, and
statistical questions will be addressed in the packet.
CONCLUSIONS
Strict estimation of the uncertainties associated with the emissions
values as presented in the NAPAP emissions inventory requires the explicit
specification of the sources of uncertainties in each method used to esti-
mate these emissions and of the underlying statistical model and assumptions
to be used in estimating the desired uncertainties. The development of the
auxiliary data needed for the calculation of uncertainties associated with
the 1980 base year emissions had to be carried out within restricted time
and resource bounds. This exercise provided a basic framework within which
to refine the techniques being developed to estimate the uncertainties of
the 1985 base year emissions.
BIBLIOGRAPHY
Benkovitz, C.M., "Framework for Uncertainty Analysis of the NAPAP Emis-
sions Inventory," EPA-600/7-85-036, NTIS-PB86-112570 (September 1985).
Ditto, F.H., L.T. Gutierrez, T.H. Lewis, and L.J. Rusbrook. Weighted Sensi-
tivity Analysis of Emissions Data: Volumes I and II. EPA-450/3-74-022
a and b, NTIS-PB258413 and 258414, 1973.
Klimm, H.A. and R.J. Brennan.
EPRI-EA-1913, 1981.
Emissions Inventory In the SURE Region.
Knudson, D. , M. Davis, J. Shannon, D. Sisterson, S. Viessman, M. Wisely, and
R. Whitfield. Preliminary Evaluation of Acidic Deposition Assessment
Uncertainties. ANL/EES-TM-XXX (Draft), 1982.
Office of Air Quality Planning and Standards, U.S. Environmental Protection
Agency, "Compilation of Air Pollutant Emission Factors," third edition
(plus supplements 8-15), AP-42, NTIS-PB275525 (1977).
Office of Air Quality Planning and Standards, Environmental Protection
Agency. Source Inventory and Emission Factor Analysis. Volumes I
II, EPA-450/3-75-082 a and b, NTIS-PB247743 and 248829, 1974.
and
Rivers, M.E. and K.W. Rit;j«fcl (Eds.). Emissions, Costs and Engineering
Assessment Work Group 3B. United States-Canada Memorandum of Intent
on Transboundary Air Pollution, 1982.
Toothman, D.A. , Yates, J.C. and Sabo, E.J., "Status Report on the Develop-
ment of the NAPAP Emission Inventory for the 1980 Base Year and Summary
of Preliminary Data," EPA-600/7-84-091, NTIS-PB85-167930 (December
1984).
53
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SESSION 2: DEVELOPMENT OF NAPAP EMISSION INVENTORIES FOR
ANTHROPOGENIC SOURCES (continued)
Chairman: John Bosch, Chief
National Air Data Branch
U. S. Envircnmental Protection Agency (MD-14)
Office of Air Quality Planning and Standards
Pesearch Triangle Park, NC 27711
54
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APPLICATION OF THE NAPAP EMISSIONS INVENTORIES TO EULERIAN MODELING
By
Joan H. Novak
Atmospheric Sciences Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
and
Paulette Middleton
National Center for Atmospheric Research
P.O. Box 3000
Boulder, Colorado 30307
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, SC
November 12-14, 1985
55
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ABSTRACT
This paper presents the schedule for development and evaluation of
Eulerian Acid Deposition Models as part of the National Acid Precipitation
Assessment Program and discusses the critical need to reduce uncertainties
in emissions inventories to provide more reliable modeling results for
policy decision making. A strong recommendation is made to expand,
improve, and standardize quality assurance procedures for emission inven-
tory development and to incorporate knowledge gained through modeling
sensitivity studies in ranking emissions inventory development activities.
INTRODUCTION
One of the primary goals of the National Acid Precipitation Assessment
Program (NAPAP) is to develop a comprehensive Regional Acid Deposition
Model (RADM) suitable for assessing source-receptor relationships. RADM
also forms the scientific basis for development of a series of simpler
"engineering models" useful for addressing policy and assessment questions
NAPAP has established the following schedule for development and evalua-
tion of these Eulerian acid deposition models.
February 1986 Preliminary Evaluation of the First Generation
Regional Acid Deposition Model (RADM)
October 1986 Testing dnd Preliminary Assessment of a sulfur
deposition Engineering Model
56
-------
October 1987 Testing and Evaluation of an Advanced Engineering
Model Operational For Multiple Species
January 1988 Operational Second Generation RADM
March 1989 Evaluation of Second Generation RADM
NAPAP has planned two major assessments designed to provide decision
makers with scientific information necessary for developing acid deposi-
tion control strategies. Both the Euleriai models and the emissions
inventories will play an important role in th,> 1987 and 1989 assessments.
The 1987 assessment will use an unevaluated bet of models for preliminary
regulatory analysis, whereas the 1989 assessment will use the evaluated
models. Thus a major field study has been proposed for 1987 through
early 1988 to collect data necessary for model evaluation. Knowledge of
uncertainty both within the model and each associated input data set
is required to assess confidence in model predictions. This paper will
focus on uncertainty in the enissions data base as related to these
Eulerian modeling efforts.
DISCUSSION
From a modeler's viewpoint, uncertainties in emission inventories can
be categorized into two types: 1) uncertainties associated with errors or
inadequacies in the data base, and 2) uncertainties associated with the
representativeness of typical daily emissions patterns for any parti-
cular day being modeled. Both the emissions inventory developers and the
57
-------
modeling groups have begun to address the first type of uncertainty, but
from different perspectives. The developers have been primarily concerned
with improving and verifying those raw data elements which are used in
estimating annual point and county level emissions. Those elements in-
clude emissions factors, fuel utilization and quality, production acti-
vity, and others. They have also been concerned with improving procedures
and data necessary to provide the temporal, spatial, and species resolu-
tion required by the Eulerian models. Most of the quality control tests
have been performed on these individual data elements and efforts are
underway to associate a level of uncertainty with each of the individual
elements comprising the final emissions estimates at point, county and
grid 1evel.
The modelers, on the other hand, primarily work with the emissions
inventories in their most resolved form - hourly gridded emissions.
Their quality control tests search mainly for individual grids that appear
to be inconsistent with their surroundings, subregions of the modeling
domain that appear unexpectedly high or low, VOC species ratios that seem
inconsistent with ambient measurement data and unexpected temporal pat-
terns within a subregion. Both the developers and the modelers have
compared the NAPAP inventory with other inventories with somewhat differ-
ent results because of the different frames of reference. Generally,
the State totals for individual species favorably agree with other inven-
tories, or discrepancies can be explained by differences in methodology.
However, the modelers have found that even when State totals agree there
are sometimes significant differences in the spatial or temporal patterns
of the gridded emissions, and at times differences in the relative magni-
58
-------
tudes of the reactive species. This contradiction is often caused by
errors in the State emissions which have cancelled out in the State total.
Thus it is important for the developers to begin to incorporate into
their quality control procedures more analytical tests typically performed
by the modelers. In addition, it is important for the modelers to have a
better understanding of the quality control procedures and estimates of
inherent variability of the individual data elements used in computing
emissions.
Uncertainties in emissions introduced by the question of representa-
tiveness are crucial for some of the proposed model evaluation studies.
The RADM will be examined in an episodic mode; thus, any major deviation
of the estimated typical hourly emissions from actual emissions for the
particular days being modeled has the potential to influence the model
results. Additional burden is then placed on the inventory developers
and modelers to ensure that there are no atypical operations in major
sources during the modeling periods. For studies of the first generation
RADM existing information on the major SOj point source emissions will be
used to check the representativeness of the NAPAP emissions. Since the
field study is still in the planning stages more options are available to
reduce uncertainty in the emissions for the second generation RADM studies
Some of the choices include acquisition of data on any anomalous plant
operation during the period of interest, installation and operation of
continuous emissions monitors (CEM) on major sources, the collection of
actual hourly fuel use or production data, improved activity data for
area source emissions estimates, etc. All of these options involve signi-
59
-------
ficant additional cost beyond the production of a typical oase year
inventory. Therefore, there is a definite requirement to rank data needs
to most effectively accommodate improvements in the base inventory as
well as the specialized needs of episodic model studies. In response to
this need, modeling studies using RADM are currently being performed to
gain a better understanding of the sensitivity of the model to uncertain-
ties in emissions. Attention is being given to spatial and temporal
variability in all of the major chemical species, and speciation of VOC.
These sensitivity studies should provide information useful to optimize
the data collection activities and to reduce uncertainties in critical
areas.
CONCLUSIONS
In order to confidently use emissions inventories in the development,
evaluation, and application of large scale Eulerian models like RADM, it
is essential to have an understanding of the quality of the input data
bases. Standardized quality assurance and uncertainty estimation proce-
dures must be established by the emission data base developers to provide
emissions inventories that are reliable and directly useful for a variety
of NAPAP applications. Current modeling sensitivity studies will provide
feedback to effectively rank future emissions inventory improvement
activities.
60
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HISTORIC EMISSIONS OF S02 AND NO SINCE I99C
BY STACK HEIGHT RANGE AND BY SEASON
by
Gerhard Gschwandtner
Pacific Environmental Services, Inc.
1905 Chapel Hill Road
Durham, North Carolina 27707
EPA Contract No. 68-02-3887
Assignment No. 11
EPA Project Officer:
J. David Mobley
Air and Energy Engineering Research Laboratory
U. S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
61
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ABSTRACT
Historic emissions of sulfur oxides and nitrogen oxides were
estimated for each state of the conterminous United States. The
emissions were estimated by ir>ai vicijal source category on the state
level from 1900 to 1980 for every fifth year and for 1978. The source
categories included power plants, industrial boilers, industrial
processes, commercial and residential heaters, natural gas pipelines,
highway vehicles, off-highway diesel engines, and all other anthropogenic
sources. These emissions were calculated from salient statistics
indicative of fuel consumption or industrial output, estimations of
average statewide fuel properties, and estimations of emission factors
specific to each source category. The emission estimates were then
aggregated to show the emission trends by state, region, and all
states combined.
This paper summarizes the national historic emission trends by
emission release (stack) height and by season. The paper outlines
the approach taken and presents general results.
62
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HISTORIC EMISSIONS OF S02 AND NOX SINCE 1900
INTRODUCTION
Sulfur dioxide (SOj) and nitrogen oxides (NOX) are considered
primary precursors of acidic precipitation. The anthropogenic
emissions of these pollutants are suspected causes of many biological
and chemical effects observed in recent years. Understanding the
historic emission trends is important to understanding the development
of acid-precipitation-related problems and causes of observed
environmental effects.
Average emission rates for each study year were calculated for
individual source categories for each state. The source categories
are listed in Table 1 according to the fuel consumed. These categories
represent all types of boilers, furnaces, engines, processes, and
other anthropogenic emission sources. The basic steps involved in
calculating state emissions have been described in detail by
Gschwandtnerl and by Gschwandtner et al.2 The emissions by source cate-
gory were totaled by year to provide an estimate of overall national
emission trends.
Analysis by Release (Stack) Height
The percentage distribution of national emissions was then esti-
mated for each source category according to four broad ranges of stack
heights. In the case of electric utilities, individual power plant
emission estimates and stack height data were used to determine the
national distribution by height from 1950 to 1980. For earlier years
and for other sources, a general trend in the percentage of emissions
by stack height range was estimated based largely on engineering judg-
ment. It was assumed that the percentage emissions of each category
changed linearly over time. The percentages estimated for each year
63
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TABLE 1. FUEL TYPES AND EMISSION SOURCE CATEGORIES
Bituminous Coal:
Anthracite Coal:
Residual Oil:
Distil late Oi1:
Natural Gas:
Wood:
Gasoline and Diesel
Fuel :
Other:
Electric Utilities
Industrial Boilers and Space Heaters
Commercial and Residential Uses
Steam Railroads
Coice Plants
All Uses
Electric Utilities
Industrial Boilers and Space Heaters
Commercial and Residential Uses
Vessels
Electric Utilities
Industrial Boilers and Space Heaters
Commercial and Residential Uses
Railroads
Vessels
Electric Utilities
Industrial Boilers and Space Heaters
Pipeline Compression Stations
Commercial and Residential Uses
Electric Utilities
Industrial Boilers and Space Heaters
Commercial Heating
Residential Wood Stoves and Fireplaces
Highway Vehicles
Off-Highway Vehicles
Vessels
Wildfires
Cement Plants
Copper, Lead,
Mi seellaneous
Miscellaneous
and Zinc Smelters
Industrial Processes
Other Sources
64
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were then multiplied by the total emissions of each category. These
results provide a general indication of the national trend.
Analysis by Season
The seasonal emissions were also estimated for major source
categories. These estimates were based on monthly fuel data available
for only certain years, and an assumed percentage distribution of the
emissions by season over time. The distribution for each category
was weighted by the historic emission estimates to yield an average
seasonal distribution for each study year for all categories combined.
DISCUSSION
Distribution by Release (Stack) Height
Figure 1 shows the overall national trend of SU^ and NOX emissions
by stack height range. This analysis does not include stack exit
velocities or atmospheric mixing heights, which are also important
considerations. The analysis in this study suggests that more S0£
emissions were released into the atmosphere from stacks taller than
24'J ft* than from stacks shorter than this height since about 1945. By
1980, approximately 30 percent of the SOj emissions were emitted above
480 ft, for example, compared to only ab"ut 5 percent above this height
in 19bO. In 19bO, six power plants reported ? maximum stack height greater
than 480 ft. Not only have the percentages increased, but tot?l national
S0£ emissions also increased and peaked around 1970. The percentage of
the total S02 emissions released below 120 ft has generally decreased
over the study period. The distribution of NOX emissions has histori-
cally remained constant, although on the national level the total
emissions have steadily increased. Approximately 60 percent of the
total NOX emissions in 1980 were released from ground level sources;
predominantly from transportation sources.
(*) 1 ft = 0.3048m
65
-------
STACK HEIGHT, ft
1 ton = 9O7.18 kg
1 ft = 0.3048 m
1900 1910 1920 1930 1940 1950 1960 1970
Figure 1. Total national S02 and NOx emissions by stack height ranges.
66
-------
Analysis of the electric utility category alone suggests that, in
the 1950's and 60's, most of the S02 ana NOX emissions from this cate-
gory were released below 480 ft -- mostly between 240 and 480 ft. Sy
1980, about 50 percent of the total S02 emissions and 40 percent of
the NOX emissions from this source category were released above 480 ft
as a result of the trend toward taller stacks. Since the emissions
from electric utilities constitute a large portion of the total national
emissions in recent years, as shown by Gschwandtner e_t al ,^ they have a
significant effect on the overall distribution of emissions by release
height.
Distribution by Season
Table 2 presents the estimated percentage distribution of emis-
sions by season on the national level. The percentage of wintertime
S02 emissions appears to have decreased from about 35 percent of the
total annual emissions in 1900 to about 26 percent of the total in
1980. This gradual decrease is largely a result of switching from coal
to fuel oil and gas for heating, and also an increase in summertime
fuel combustion by power plants to meet the demands of refrigeration
and air conditioning. The seasonal distribution is more pronounced on
a regional level where climatic conditions deviate from the national
average. NOX emissions appear more evenly distributed by season than
S02 emissions. This is primarily due to an assumed distribution of
highway vehicle emissions by season, and the fact that the major
sources of S02i which are seasonally /ariable, emit less NOX.
Figure 2 shows the trend in the quantity of emissions by season
on the national level. While the S02 percentage distribution shows a
gradual change, the increase in the quantity of S02 emissions is
more evident, especially in the summertime.
67
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TABLE 1. PERCENTAGE DISTRIBUTION OF EMISSIONS BY SEASON
Percentage S02 Emissions
Year Winter Spring Summer
01
en
Fall
Year
Percentage NOX Emissions
Winter Spring Summer
Fall
19UO
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1978
1980
34.8
34.5
34.3
34.3
34.2
34.0
34.0
33.4
32.5
32.3
30.8
30.2
29.5
28.0
26.7
26.1
26.4
26.4
19.4
19.4
19.4
19.3
19.4
19.5
19.4
19.4
19.8
20.0
21.0
21.9
22.7
23.3
23.5
23.5
23.4
23.4
23.6
24.1
24.5
24.7
24.8
25.0
25.4
26.0
26.3
26.4
26.3
25.7
25.4
25.6
25.8
26.1
26.1
26.1
22.2
22.0
21.9
21.7
21.6
21.4
21.2
21.2
21.3
21.3
21.9
22.2
22.5
23.1
23.9
24.2
24.1
24.1
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1978
1980
30.8
31.1
31.7
31.9
31.6
30.3
29.5
28.8
29.8
28.5
27.6
27.2
26.5
25.7
24.6
24.2
24.5
24.5
19.9
19.8
19.8
19.8
20.2
20.4
20.7
20.9
21.2
21.2
22.3
23.0
23.4
23.9
24.1
24.1
24.0
24.0
26.1
26.9
25.8
25.8
25.8
26.5
27.0
27.4
27.3
27.5
27.0
26.7
26.5
26.6
27.2
27.3
27.2
27.2
23.2
23.0
22.6
22.4
22.4
22.7
22.9
22.9
22.7
22.8
23.0
23.2
23.5
23.9
24.2
24.3
24.3
24.3
Winter = December. January, February
Spring = March, April, May
Summer = June, July, August
Fall = September, October, November
-------
1900 1910 1920 1930 1940 1950 1960 1970 1980
Figure 2. Total national S02 and N3x emissions by season.
69
-------
CONCLUSION
The historic emission estimates presented are consistent in trie
estimating methodology used. They provide a basis for studying the
relationship between emissions in the past and observed environmental
effects including tree-ring growth patterns, material damage, and
acidic deposition. The emission trends shown in this presentation
should De considered the best available estimates at this time, but
it should be remembered that, as work in this area continues, more
Defined estimates may be made. The historic emission estimates show a
definite trend in terms of the total nation by stack height range and
by seasonal distribution.
REFERENCES
1. G. Gschwandtner. Historic Emissions of S02 and NOX Since 1900.
In Proceedings: First Annual Acid Deposition Emissions Inventory
Symposium, EPA-60G/9-85-015 (NTIS PB 85-200004/AS), U.S. Environ-
mental Protection Agency, Research Triangle Park, NC, pp 38-46
May 1985.
2. G. Gschwandtner, K.C. Gschwandtner, K. Eldridge, "Historic Emissions
of Sulfur and Nitrogen Oxides in the United States crom 1900 to 1980,"
Volumes I and II. EPA-600/7-85-009a and 009b (PB 8S-191 195/AS and
PB 85-191 203/AS), U.S. Environmental Protection Agenc). Research
Triangle Park, NC. April 1985.
70
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DEVELOPMENT OF MONTHLY EMISSIONS TRENDS
FOR RECENT YEARS
by
Di ane Knudson
Argonne National Laboratory
DOE Contract No. W-31-109-Eng-38
DOE Project Officer:
Edward Trexler
Office of Fossil Energy
U. S. Department of Energy
Washington, DC
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
71
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Development of Monthly Emissions Trends
for Recent Years
D. Knudson
ABSTRACT
As atmospheric transport and deposition modeling capabilities increase
and monitoring data are accumulated, it becomes desirable to also have
representative emissions data. This paper describes the methodology and
results of an effort to generate state-total source category-specific monthly
S02 and NOX emission estimates for the period 1975-1983. These data
complement other data bases and support a variety of analytical efforts. The
basis of the monthly emission estimates are source category-specific state-
total S02 and NO emission values from the 1980 NAPAP emissions inventory.
Annual emissions from the electric utility industry are allocated to monthly
values using actual monthly fuel use for each year in the period. Annual
emission values for other source groups were apportioned to monthly values
using data which provides an indication of the monthly activity for each
source group in the inventory year (1980). Annual state-total source category
emissions for other years in the period were derived from the EPA emissions
trends data.
The results indicate that intra-annual variability of SCK and NO
emissions for each state depend on the variability of source categories
contributing most to state total emissions. In states with S02 emissions
dominated by the electric utility sector, maximum emissions occur in the
summer and winter. The relative importance of these two peaks depends on such
factors as climate and utility prime mover and fuel mix. Monthly NO
emissions variations are also a function of the variability of source groups
contributing the most to total state N0x emissions. In all states, vehicle
fuel consumption contributes substantially to total state NO emissions.
Monthly variability of NOX emissions attributable to this source category
shows only small variability in most states.
72
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DEVELOPMENT OF MONTHLY EMISSIONS TRENDS
FOR RECENT YEARS
INTRODUCTION
Evaluation of long-term data on such parameters as atmospheric
deposition, biological response, geochemical changes, and response
characteristics of other receptor systems for trends is facilitated by
appropriate emissions data for the specific period. In many cases accurate
evaluation of the measured deposition and/or response of a subject receptor
requires emissions data with a temporal resolution matching the critical
period of the receptor. For establishing correlations and functional
relationships between receptor response and emissions for trends evaluation,
monthly emissions estimates are sometimes required. The data base developed
in this project, therefore, complements the commitment to collection of long-
term deposition and receptor system response data.
This paper describes the development and presents an overview of
monthly S02 and NOX emission estimates for the period 1975-1983. Review of
the methodology will address the utility sector separately from all other
source groups. This is because of the generally large contribution of SC^ and
NO emissions by the utility -.ector and because the methodology is more
X
detailed for this source category. Portioning of annual state-total emissions
estimates for the diverse group comprising the nonutility sector uses a number
of different data bases. The selection of the appropriate monthly data base
for allocation of annual emissions is a critical step in the data base
development. A more thorough presentation of the methodology is provided in
Reference 1.
The state-total source category-specific monthly S02 and NOX estimates
for all years in the period 1975-1983 are condensed into two summaries for
73
-------
presentation. Total regional seasonal S02 and NOX values are presented for
Federal Regions 1 through 6 to illustrate regional emission trends. Then, to
provide an indication of differences in source category contributions to
monthly emissions variability, monthly source category specific S02 and N0x
emissions are presented for 1980 for Illinois and New York.
METHODOLOGY
The 1980 NAPAP SOo and NO emissions inventory (version 3.0) provided
state-total source category-specific emission values for S02 and NOX> A six-
digit level of specificity of the Source Classification Code (SCC) was used
for point sources to identify the major source category (e.g., industrial
boiler) activity (e.g., combustion and incineration), and fuel (coal and
residual oil). For area sources, the eight digit code unique to the NAPAP
inventory was used to define source groups. The apportioning of the state
annual emissions used data bases that provide some measure of activity for the
source category, operation, and/or fuel use on a monthly basis.
Utility Poinc Sources - All Years
Computation of monthly 862 emissions for the electric utility sector
used plant emission values furnished by E.H. Pechan and Associates for the
fy
years 1975-1982 in combination with monthly fuel consumption reported by
Energy Information Administration (EIA) Form 759 "Monthly Power Plant Report".
Annual emission calculations for 1983 were performed by Argonne National
Laboratory according to methodology developed by Pechan.
Computation of monthly NOX emissions for this sector used the monthly
fuel use from EIA Form 759 with plant-average NOX emission factors. The
emission factors were derived from AP-42 firing type and fuel-specific
emission factors in combination with 1980 unit-level fuel use for firing of
74
-------
coal, lignite, gas, residual oil, and distillate oil in conventional boilers;
internal combustion of natural gas and distillate oil; and gas turbines.
These emission factors coincide with the fuel use categories on Form 759.
Nonutility Sources, 1980
Allocating annual SC>2 and NOX emissions to monthly values for the
diverse group of nonatility sources requires a number of equally diverse data
bases. The source categories and the data bases supporting monthly allocation
are defined in Table 1.
Nonutility Point and Area Sources for Other Years
Monthly SC^ and NOX emission estimates for nonutility source categories
were derived from national emission estimates in the EPA report, "National Air
Pollutant Emission Estimates: 1940-1983.' Values from that report for
source categories matching those used for the monthly emissions estimation
were normalized, with 1980 as the base year. This provided fractional
national emission changes relative to 1980 for all years in the period.
Therefore, the monthly source category emission fractions developed for 1980
were held constant throughout the analysis.
RESULTS
Figures 1 through 5 present seasonal total 862 and NOX emissions for
the period 1975 through 1983 for Federal Regions I and II, III, IV. V, and VI
respectively. A characteristic apparent in all regions is the lack of
seasonal variability in NOX emissions compared to S02. This is probably
attributable to the large contribution of vehicle fuel combustion to total NPX
emissions in most states, and the lack, of variability in monthly vehicle fuel
combustion.
For total S02 and N0x emissions in Regions I and II (Figure 1), there
is a small difference between S02 and NOX emissions, with NOX being slightly
75
-------
Table 1. Data Sources for Estimation of Nonutility Monthly S02
and NOV Fractions for Apportioning Annual Emissions
Description
Industrial external coal combustion
Industrial external oil combustion
Commercial and Institutional external
coal combustion
Commercial and institutional external
oil combustion
Commercial, institutional, and industrial
external combustion for space heating
Commercial, institutional, and industrial
internal oil combustion
Industrial chemicals: sulfuric
acid, plastics, organic chemicals,
explosives, carbon black, printing
ink
Food product processing
Primary metal: c ".e manufacturing,
steel production, copper smelters,
zinc, and other primary metals
Secondary smelting: o^uminum, copper
lead, etc.
Mineral products: glass, fiberglass,
gypsum products, cement, brick,
pottery
In-process fuel use
Petroleum refining
Wood and paper products
(including Kraft pulping)
Crude oil and natural gas extraction
(including gas sweetening)
Solvent use
Solid waste disposal
Industrial internal gas combustion
Data Source or Approach for
Estimating Monthly Fractions
Quarterly Coal Report
Adjusted FRB monthly produc-
tion indexes
Quarterly Coal Report
Uniformly distributed3
Local climatological data -
heating-degree-day
accumulation
Uniformly distributed3
FRB monthly production indexes
for SIC 2819; inorganic
chemicals
FRB monthly production indexes
for SIC 209: miscellaneous
food preparation
FRB monthly production indexes
for SIC 331: basic steel,
coking, mill production; SIC
333-6,9: nonferrous metals
FRB monthly production indexes
for SIC 333-6, 9: non-
ferrous metals
FRB monthly production indexes
for SIC 326: concrete and
miscellaneous clay
FRB monthly production indexes
for SIC 326: concrete and
miscellaneous clay
FRB monthly production indexes
for SIC 291: petroleum
refining
FRB monthly production indexes
for SIC 261: pulp and paper
FRB monthly production indexes
f
-------
Table 1 (Cont'd)
Data Source or Approach for
Description Estimating Monthly Fractions
Incineration and open burning Uniformly distributed3
Miscellaneous area sources0 Uniformly distributed3
Diesel and gasoline vehicles 1980 Highway Statisticsb
aAnnual data assumed to be uniformly distributed throughout the year,
due to lack of monthly data.
Nox only
cRailroad locomotives, military aircraft LTO's, civil aircraft LTO's,
commercial aircraft LTO's, coal vessels, diesel oil vessels, residual
oil vessels, gasoline vessels, solvent purchased, gasoline marketed,
unpaved road travel, unpaved airstrip LTO's, construction, wind
erosion, land tilling, forest wild fires, managed burning, agricultural
burning, frost control, and structural fires.
less. SOn emissions have been relatively constant, while NOX emissions are
increasing slightly. Winter is the season of peak emissions for S02 and N0x
for the region through the entire period.
Region 3 (Figure 2) shows a small 502 trend downward, and no
discernible NO trend. N0x emissions are about 50 to 60% of regional S02
emissions for all years in the period. Winter is the peak season for SO-, and
NO for all years except 1983, in which summer is the peak emission season.
Region IV shows a steady decline in S02 emissions from a maximum in
1977. There is little change in t,'0x emissions through the period, with NOX
being about 50% of the S02 emissions.
In Region V, S02 emissions have decreased steadily since 1977 to a
value about double the NOX emissions in 1983. NOX emissions have changed
little throughout the period. Winter is the peak season for NOX and S02
emissions for all years in the period.
77
-------
M
600-1
500-
400-
r>
c
•2 soo-
z o
o
c
o
*5>
io
200-
100-
75 76 77 78 79 80 81
Season and Year
82
Figure 1 Regions 1 and 2 Seasonal SO and NO Emission Totals for
the Period 1975-1983. L x
REGION 3
c
to
in
'E
lOOO-i
800-
•O p
§1
C?"o
•5 ^
O
O
.O
600-
400-
200-
75 76 77 78 79 80
Season and Year
81 82
Figure 2 Region 3 ^Seasonal S02 and N0x Emission Totals for the
-------
REGION 4
n
o
2000-T
1500-
O £
>"o
O o
"5
c
o
'o>
c
or
1000-
500-
scx
75 76 77 78 79 BO
Season and Year
81
82
83
Figure 3 Region A Seasonal SO and NO Emission Totals for the Period
1975-1983. x
REGION 5
c
o
'in
m
2500
2000-
1500
O o
z o 1000
"5
c
o
0
ot
io
500-1
SO,
75 76 77 78 79 80
Season and Year
81
82
Figure 4 Region 5 Seasonal SCK and NO Emission Totals for the
Period 1975-1983. X
-------
REGION 6
1500-1
5
w
CM
O
1000-
o .2
O
O
EC
^
"o
500-
so,
75 76 77 78 79 80
Season and Year
81
82
Figure 5 Region 6 Seasonal SO. and NO Emission Totals for the
X
Period 1975-1983.
80
-------
New York
linn.
MAMJ JASOND
J F
CD Industrial Coal
EZJ Industrial Oil
Industrial Process
Miscellaneous
Utility Oil
Utility Coal
Illinois
ttO-,
JFMAMJJASOND
CD Industrial Coal
ZZ3 Industrial Oil
Industrial Process
Miscellaneous
Utility Oil
Utility Coal
.Figure 6 Monthly 1980 SO Emissions by Source Category for
New York and Illinois.
81
-------
Mew York
J F
CD Vehicle
E3 Industrial Fuel
E33 Industrial Process
Q Miscellaneous
EZ Utility Oil & Gas
•I Utility Coal
Illinois
100
CH Vehicle
E2 Industrial Fuel
ESS Industrial Process
HZ) Miscellaneous
Utility Oil & Gas
Utility Coal
Figure 1 Monthly 1980 NO Emissions by Source Category for
New York and Illinois.
-------
In Region VI, NOX emissions are roughly a factor of two higher than S02
emissions. Neither SC>2 nor NOX emissions have changed significantly over the
period of interest. There is a slight winter peak for both pollutants for all
years except 1983, for which summer is the season for maximum S02 emissions.
Figures 6 and 7 present 1980 monthly source category SC^ and NOX
emission estimates for Illinois and New York, respectively. In both states
the utility sector contributes the most to SCK emissions. In Illinois monthly
variability in utility coal combustion dominates the total state monthly S02
emissions variations. In comparison, utility coal derived SC^ emissions for
New York have little variability through the year. The variations in total
New York ttate SC^ emissions is largely attributable to utility oil combustion
fluctuations. In New York, source categories defined as industrial oil and
miscellaneous also have substantial contributions to total state SO-,
emissions, but show little monthly variability in SO*? emission rates.
Monthly emissions of N0y also show differences between the two states
(Figure 7). NOX emissions in Illinois are clearly dominated by utility coal
combustion and vehicle fuel use. The vehicle source category is the
overwhelming contributor to NOX emissions In New York State. However,
coincident minimum monthly NOX emissions for the utility oil, miscellaneous,
and industrial oil combustion categories combine to yield a state-total
minimum NO emission rate in the late spring to early summer period, even
though vehicle-related emissions are not at their minimum during these months.
CONCLUSIONS
Monthly state-total S02 and NOX emissions by source category for the
years 1975-J983 have been prepared. The allocation of annual emissions to
monthly values used a diverse set of data describing source category-specific
83
-------
fuel use or related activity. Definition of the monthly data base used for
allocation is the critical step in the development of the monthly data.
General regional patterns of monthly S02 and NOX emissions are
dependent on the characteristics of each region. In the northeast (Regions
I-III), S02 emissions have decreased slightly while NOX emissions have been
increasing through the 1975-1983 period. In these regions winter is the peak
S02 and NOX emission season. Region IV has experienced a significant decline
in S02 emissions and little to no increase in NOX, with summer being the
season of maximum emissions for both pollutants. Region V has shown the
largest decrease in S02 emissions, with little change in NOX emissions across
the period. Winter is the season of maximum S02 and NOX emissions for Region
V. The relative portions and trends in S02 and NOX emissions for Region VI
are distinctively different from the patterns in the eastern regions. In
Region VI, N0x emissions are roughly a factor of two higher than S02
emissions, with neither showing any trend through the period. Unexpectedly
for Region VI, winter is the season of peak S02 and NOX emissions for all
years in the period, except 1983. In 1983, S02 emissions peaked in the
summer.
Generalizations of state-level monthly emissions variability are
impossible to make. The pattern of monthly S02 and NOX emissions dopends on
the relative contributions of source categories in each state and their
monthly emission pattern.
ACKNOWLEDGEMENT
This research has been funded as part of the National Acid
Precipitation Assessment Program's Man-Made Sources Task Group by the U.S.
Department of Energy Office of Fossil Energy. The DOE Project Officer was
Edward Trexler. Special thanks is given to Marylynn Placet of Argonne
National Laboratory for her assistance in methodology development and data
base selection.
84
-------
REFERENCES
1. Knudson, D,A. "An Inventory of Monthly Sulfur Dioxide Emissions for the
Years 1975-1983," ANL/EES-TM-277 (April 1985).
2. E.H. Pechan and Associates, "Estimates of Sulfur Dioxide Emissions from
the Electric Utility Industry," EPA 600/7-82-061a and b (November 1982).
3. U.S. EPA "National Air Pollutant Emission Estimates, 1940-1983," EPA
450/4-84-028 (December 1984).
85
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APPLICATIONS OF EMISSIONS DATA IN
THE NAPAP ASSESSMENT REPORT
Paul Schwengels
Office of Air and Radiation
U.S. Environmental Protection Agency
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
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APPLICATIONS OF EMISSIONS DATA IN THE NAPAP ASSESSMENT REPORT
By: Paul Schwengels
Office of Air and Radiation
U. S. Environmental Protection Agency
ABSTRACT
A great deal of emission^ data has been assembled for use in the
forthcoming NAPAP Assessment Report. This includes natural and man-mac'e
sources of a number of relevant chemical species or classes in both the
United States and Canada. Emissions data will be used in the report in
several ways. First, an emissions section will summarize best available
information on substances of interest, compare natural and man-made levels
provide regional distributions and comparisons, and evaluate national and
regional trends in man-made emissions where possible. In addition,
emissions data have been used to support analyses and modeling for the
atmospheric processed and materials damage sections of the report. This
paper briefly describes the various data sets which have been assembled to
meet these different needs in the assessment. It identifies the different
types of data needed to support different types of analyses or comparisons.
Uncertainties and limitations in available data and their impact on
assessment will be reviewed, as well as data improvements needed to support
improved assessments in the future. Some preliminary approaches to analysis
and presentation of data being considered for the Assessment Report will
also be discussed.
Note: The text of this paper was not available at the time of publication
of the proceedings.
87
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OVERVIEW OF THE DEVELOPMENT OF THE
1985 NAPAP EMISSIONS INVENTORY
Charles 0. Mann
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, SC
November 12-14, 1985
88
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OVERVIEW OF THE DEVELOPMENT OF THE
1985 NAPAP EMISSIONS INVENTORY
ABSTRACT
The National Acid Precipitation Assessment Program (NAPAP) needs a
current and detailed emissions inventory to support its activities. To meet
this objective, NAPAP and the United States Environmental Protection Agency
(EPA) have selected 1985 as the base year for the inventory. Data collected
by the States during 1985 for the National Emissions Data System (NEDS) will
be used to develop the NAPAP emissions inventory. The NEDS was selected to
permit the design of a data collection program that will meet NAPAP's require-
ments for both quality assurance and spatial, temporal, and species resolu-
tion. Ensuring the accuracy of more than 4 million items of data that the
States will collect for NEDS is a challenging task. To meet this challenge,
EPA has developed a five part management strategy. This strategy emphasizes
the high priority of the NEDS in 1985, establishes EPA and State accounta-
bility for the NEDS data, delineates quality assurance procedures for the
data, provides financial assistance to States that require it, and ensures
that participating State and EPA personnel clearly understand the NEDS data
requirements. This management strategy will result in the development of
NEDS data that will have unparalleled quality.
INTRODUCTION
The National Acid Precipitation Assessment Program (NAPAP) requires
emissions data for three reasons: to support atmospheric modeling, to explore
relationships between sources of emissions and receptors of acid deposition,
and to facilitate examination of regulatory alternatives. The reliability of
NAPAP's activities in these areas can be no better than the data on which
they are based. Thus, to produce reliable results, these activities must be
founded on the development of a comprehensive emissions inventory with a high
degree of quality control and of species, temporal, and spatial resolution.
As illustrated in Figure 1, the basis for NAPAP's estimates of anthropo-
genic emissions will be the 1985 emissions inventory conducted by the States
for the National Emissions Data System (NEDS). This system is maintained by
the National Air Data Branch of the U.S. Environmental Protection Agency
(EPA). The goal of this project is to ensure the best ever development of a
NEDS data base to meet NAPAP's needs for 1985 emission inventory data.
89
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DISCUSSION
The NEDS is a computerized system which accepts, stores, and reports
source data and emissions data for both point and area _ sources. Point
sources are considered to be stationary sources of pollution that emit at
least 100 tons annually of particulate matter, sulfur dioxide nitrogen
oxides, or reacti e volatile organic hydrocarbons, or that emit at least
1UUU tons annually of carbon monoxide. Area sources are considered to be
stationary sources with emission rates below these thresholds and all mobile
souses of particulate matter, sulfur dioxide, nitrogen oxides, reactive
volatile organic hydrocarbons, or carbon monoxide.
Point source data are collected by both State and local air pollution
control agencies. The data are obtained for each source at an individual
plant through questionnaires, visits, and emission tests. For an average
plant a State must collect, check, and report 350 items of data. After
conducting quality assurance checks on the data, States enter the data onto
forms or computer tapes compatible with NEDS and transmit the data to their
EPA Regional Offices. States are required to make an annual report to EPA
for all of the sources meeting the above criteria.
Area source data are developed by EPA's National Air Data Branch.
Development of the area source data relies upon published information for
calculating area source activity levels, such as quantities of fuels distri-
buted to States, vehicle-miles travelled by motor vehicles and so forth.
State level data are allocated to counties using employment, population,
or similar statistics. Emissions are calculated using emission factors from
standard EPA references such as AP-42 and the MOBILE3 highway vehicle emission
factor model.
The major thrust of the 1985 data collection effort is to ensure a high
quality, timely point source data submittal by the States. In deciding to
use 198b NEDS emissions data for NAPAP's purposes, r_PA recognized that careful
management would be needed to superimpose NAPAP's data requirements on the
State emissions inventory process. The management strategy that EPA has
developed to help the States meet NAPAP's requirements consists of five
elements:
0 Emphasizing priority: emphasizing the importance of meeting the
NAPAP data requirements to managers in State offices and EPA Regional
Offices;
0 Establishing accountability: establishing a network of managers in
the State offices and EPA Regional Offices that will be responsible
for the NEDS data;
0 Ensuring accuracy: establishing quality control procedures for prep-
aration and submittal of the source and emissions data;
90
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0 Assisting States: pinpointing and eliminating any State resource
constraints; and
0 Establishing communication: ensuring that all participating State
and EPA personnel understand the NAPAP requirements 1or the emissions
data to be col 1ected.
The first element of the strategy was to establish the priority for the
1985 State NEDS inventory. This has been accomplished through a memorandum
from EPA Adninistrator Lee Thomas to State Air Program Directors and to EPA
Regional Administrators. This letter urged State and EPA Regional assistance
to produce an accurate and comprehensive emissions inventory. The letter
alsu empnasized the high priority that EPA attached to tne^e goals. To focus
additional attention on these goals within EPA, the Administrator's Strategic
Planning and Management System for fiscal year 1986 includes NEDS performance
milestones for managers in the Regional Offices.
The second element of the strategy was to establish accountability. A
network of managers responsible for ensuring the quality and scheduling of
the emissions data was established during August and September 198b. This
network will consist of individuals in both Regional Offices and State Air
Program Offices. Accountability for EPA managers is further emphasized
through the performance milestones mentioned above.
The third element of the strategy is the most challenging one. Ensuring
the accuracy of more than 4 million items of source and emissions data that
will be collected during 1985 is a difficult task under the best of circum-
stances. Given the limited resources typically encountered in the State air
program offices, the task of selecting appropriate quality assurance pro-
cedures is nade even more complex. The quality assurance procedures that
NAPAP and EPA are to employ attempt to strike a balance between vigorous
investigations and limited State resources. States and EPA Regional Offices
will oe provided with written guidance concerning the quality assurance checks
that NAPAP will conduct. This will not only focus attention both on critical
elements in the NEDS data and on appropriate calculation procedures, but will
also minimize errors. Also, Regional Officec will be provided with copies of
computer programs designed to check the data submitted by the States for
potential errors. When questions about the data are raised, the Regional
Offices will contact the States to resolve any problems. Finally, NAPAP will
perform its quality assurance checks on high-priority data items to ensure
that errors have been corrected by the State and Regional Office efforts.
NAPAP will also cross-check the data received wi ch independent data sources,
such as U.S. Department of Energy data for individual electric utility plants.
The fourth element of the strategy is assisting the States. F.PA has
allocated $500,000 from Clean Air Act Section 105 air quality grants to help
States that need extra resources. A similar amount of assistance as contract
support is to be provided from NAPAP funds. The resource assistance plan
is discussed in detail in the paper by David Johnson, titled Assistance to
States In the Development of the 1985 NAPAP Emission Tnventory.
91
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The final element of the management strategy is communication. On
July 30 1985, OAQPS transmitted written guidance to each EPA Regional Office
Air Program Director which discusseo three initiatives being taken to ensure
that the network of State and EPA personnel responsible for the NEDS emissions
data understand both their roles and the data collection requirements. These
initiatives include the organization of telephone conferences to coordinate
work between EPA personnel in OAQPS and in the Regional Offices, and the
preparation of written quality assurance guidance for EPA and State personnel.
A workshop for State and Regional project managers was held on October 24 and
25. OAQPS will maintain contact with the Regional and State project managers
throughout the remainder of the project to follow up on specific problems
that develop.
Work is also planned to improve the methodology for calculation of NEDS
area source emissions to ensure that all significant source categories of
emissions are accounted for. Development of an improved methodology for
highway vehicles is also anticipated. This is necessary to improve the
accuracy of the emissions estimates for this source category which accounts
for about one-third of national NOX and VOC emissions. The new methodology
will produce better estimates of vehicle-miles travelled to be used with
MOBILE3 emission factors to calculate emissions.
Finally, the NEDS point and area source data developed by the States
and NADB will be processed by NAPAP to produce the spatial, temporal, and
species resolution of emissions needed by NAPAP. The procedures for accom-
plishing this have been described by Fred Sellars in the paper titled Develop-
ment of an Emissions Inventory to Support Testing of the Eulerian Regional
Acid Deposition Model.
CONCLUSION
The management strategy developed by EPA represents a strong commitment
to achieving NAPAP's goals for a 1985 emissions inventory. This effort has
the highest priority of any emission inventory project conducted since the
initial development of NEDS in the early 1970's. To achieve the desired
goals will require an intensive and coordinated effort by the States and EPA,
The expectation is that the inventory data developed will be the best ever
during the time NEDS has been in existence.
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STATE EMISSIONS INVENTORIES
1985 NEDS FILES
S02, NOX, CO, VOC, PARIICULATES
STATE
ASSISTANCE
EMISSIONS INVENTORY
SYSTEM FOR POINT
AND AREA SOURCES
SPECIES
ALLOCATION
FACTORS
INVENTORY IMPROVEMENTS
AND ADDITIONS
CANADIAN
INVENTORY
EMISSIONS
FACTORS
HOURLY EMISSION
PROFILES
SPATIAL SOURCE
ALLOCATIONS
DOE DATA
VERIFICATION
TESTS
UNCERTAINTY
ESTIMATES
QUALITY
ASSURANCE
1985 NAPAP EMISSIONS INVENTORY
(INCLUDES 40 POLLUTANT SPECIES)
Figure 1. Relationship Between State and NAPAP
Emissions Inventories for the 1985 Base Year
93
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ASSISTANCE TO STATES IN THE
DEVELOPMENT OF THE 1985
NAPAP EMISSION INVENTORY
by
David Johnson and Mark Hodges
Technical Guidance Section
U. S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
EPA Contract No.
EPA Project Officer:
U. S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
94
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ABSTRACT
The Environmental Protection Agency (EPA) is working with the State
and Territorial Air Pollution Program Administrators (STAPPA) Acid Rain
Committee to identify the capabilities and needs of States with regard to
cevelopnent of tne 1985 National Acid Precipitation Assessment Program
J.APAP; emission inventory. A survey nas been distributed to the States
asKing them to determine what level of inventory effort they could provide
for 1985 given their current resources and activities and what types and
levels of support are needed to ensure the desired information can be
collected and submitted. The results of the survey will be used in
determining wnat type of assistance will be provided with the additional
fjnds available for tnis project.
95
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Introduction
The 1985 NAPAP emission inventory effort will call on States to make
a concerted effort to collect and submit emission-related data. However,
since trie emission inventory development and maintenance activities and
capabilities vary across the States, it is necessary to determine what
assistance or support mignt be needed to enable all States to produce
consistent and high-quality emission inventory information. Once these
needs are determined, an appropriate strategy to provide the assistance can
be developed based on program goals and available resources,
Background
In June 1985, the Administrator of the U.S. Environmental Protection
Agency (EPA) wrote to each State Environmental Director explaining the
importance of the 1985 emission inventory and the role of States in the
development of the inventory. The Administrator said that he was giving
the 1985 inventory project a high priority within EPA, and he urged the
State Directors to also give the project high priority in their States.
The Administrator also commented that he realized that the inventory
cevelopnent activities and capabilities varied across the States anc that
trie critical needs associated with producing consistent and nign-quality
emission inventories snould oe identified. Once these needs were identified
ways of satisfying tnese needs and solving major problems should be
determi ned.
The Administrator stressed his desire to work closely with the States
in aeternining their inventory capabilities and needs. He stated that
EPA's interface with the States would be through the STAPPA Acid Rain
Committee, chaired by Mr. Jim Hair.bright (head of the Pennsylvania air
program). Staff of EPA first met with the STAPPA committee in April 1985
to discuss the objectives of the 1985 inventory project and how EPA and
STAPPA could work together to identify and address Stace inventory needs
and concerns. The STAPPA committee and EPA agreed that a greater'effort
within the existing National Emission Data System (NEDS) context could
produce a worthwhile improvement in emission inventory information and
that an appropriate way to determine the capabilities and needs of States
would be through a survey.
A survey was developed and mailed by STAPPA to the 48 contiguous
States and the District of Columbia in July 1985. The primary goals of
the survey were to determine (1) what level of inventory effort the States
could provide for 1985, given their current inventory activities and
resources and (2) what types and levels of support were needed to ensure
the States could provide the desired emission inventory information.
96
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-.esults CT~ tie STAPPA Emission Inventory Survey
Tne survey drew an effective and widespread response from the States.
Cut of tne -? surveys that were mailed, 42 had been returned by October 17,
l'-S5. Figure 1 snows the response in each EPA Region, which illustrates
cr, effective response to the survey across the country. It was also
evident mat nany States gave considerable time and effort in preparing
tneir responses, with some States providing detailed estimates of man-hour
and material needs associated with the 1985 effort. The following
ciscussion summarizes the results of the survey.
Inventory Capabilities With Current Resources - The first primary
question of tne survey asked whether States would be able to provide by
J'jly 1, 1986, the 1985 emission data for various sources given the States'
curnent inventory activities and resources. States were asked to specify
v/netner they would be anle co provide emission data needed for (a) all,
'b' more tnar naif, (c) less than half, or (d) none of the sources grouped
by jollutant and size categories. The responses of the States are summarized
r~,;ures 2-b. Figure 2 illustrates that over two-thirds of tne States
cojld provide the emission-related information tor all sulfur dioxide
"SI^.1 sources greater tnan 2,500 tons per year 'TRY) with current resources,
?'. er rial* could provide tne data for SO? sources greater than 1,000 TRY;
ana c.'er a tnird could provide the data for all S0£ sources greater than
I'.i-j TPr witnout needing additional assistance. The most significant
cnan.je in tne distribution occurs when the size cutoff is lowered to 100
T^Y. Considerably fewer States are able to provide data for all sources
emitting more tnan 100 TDY of S0£, and most States could provide the data
*•";.- only a portion or none of their sources.
Figure 3 illustrates an almost identical pattern in the capability
of States regarding sources of oxides of nitrogen (NOX). The similarity in
Figures 2 and 3 shows an expected pattern, which is apparent also for
sources of volatile organic compounds (VOC's), particulate matter (PK),
and carbon monoxide (CO), that reflects the increasing demands on State
resources as the size cut-off becomes smaller. However, the similarity
in a State's capabilities regarding S0£ and NOX sources also results from
the considerable overlap in sources; that is, most sources of SOp emissions
sre also sources of NOX and vice ve^sa.
Figure 4 snows the capabilities of States to provide the emission
data for VOC sources. Figures 5 and 6 ->how the capabilities of the
States to provide the emissions data fo sources of particulate and
carbon monoxide. Although the patterns in the capability of States to
provide data for these sources are quite similar to the patterns illustrated
in Figures 2 and 3 for SO;? and NOX, acrus: the board there are fewer
States capable of providing data for al1 sources of VOC, PM, and CO in
the particular size categories.
97
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Figure 1. SURVEY RESPONSES RECEIVED
1985 NAPAP EMISSIONS INVENTORY
co
8
RESPONSES
10
9
8
7
6
4
3
2
1
0
EPA REGION NUMBER
Based upon 42 of 49 possible responses.
October- 3O. 19R5
fe
x>
.-.-x
tx-^d :<1 i>x
No reponse received
tV\
SResponse received
-------
Figure 2.
VO
VO
STATVS
45
40
35
30 £•
r
25 F-
I-
20 [-
.15 F.
10 r.
»-
5 "•
ABILITY TO PROVIDE 1985 EMISSIONS
DATA FOR S02 SOURCES
( NAPAP Emissions Inventory )
IT * \ v v ' V
\ \ \ \
\ x
\
\ ' N ' N.
\
\
\
~.V\
F N
k J
data
100% Of •ju.'.it'Ll;'/
vicio u,ita fj
of ;iw;jfi.(.i
U: cKit.i f»j:
Of S5uuri'.f;
Jt; dcitei fo,
jn -I.: jf -ili i.uvoii.'h. :•;.
-------
Figure 3.
O
o
ABILITY TO PROVIDE 1985 EMISSIONS
DATA FOR NOx SOURCES
( NAPAP Emissions Inventory )
NOx > 2500 tpy NOx > 1000 tpy NOx > 100 tpy
SOURCE SIZE CATEGORY
Provide data for
100% of sources
Provide data for
> 50% of sources
Provide data for
< 50% of sources
Provide data for
0% of sources
Based upon 42 of ^9 total possible r-esponses
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Figure 4.
STATES
45
40
35
30
25
20
15
10
5
0
ABILITY TO PROVIDE 1985 EMISSIONS
DATA FOR VOC SOURCES
( NAPAP Emissions Inventory )
VOC > 2500 tpy VOC > 1000 tpy VOC > 100 tpy
SOURCE SIZE CATEGORY
Based upon 42 of 49 total possible responses.
October 30. 1985
Provide data for
100% of sources
Provide data for
> 50% of sources
Provide data for
< 50% of sources
Provide data for
0% of sources
-------
Figure 5.
o
PO
ABILITY TO PROVIDE 1985 EMISSIONS
DATA FOR PARTICULATE MATTER SOURCES
( NAPAP Emissions Inventory )
PM > 2500 tpy PM > 1000 tpy PM > 100 tpy
SOURCE SIZE CATEGORY
upon 42 of 49 total possible responses.
Provide data for
100% of sources
Provide data for
> 50% of sources
Provide data for
< 50% of sources
Provide data for
0% of sources
-------
o
Co
Figure 6. ABILITY TO PROVIDE 1985 EMISSIONS
DATA FOR CARBON MONOXIDE (CO) SOURCES
( NAPAP Emissions Inventory )
STATES
40
35
30
25
15
10
5
\
\
\
*T^
- -4
>
CO > 2500 tpy CO > 1000 tpy
SOURCE SIZE CATEGORY
Based upon responses from 40 of 49 total
' ";Provide data for
:> ..\ 100% of sources
•'' ~; Provide data for
':. ,.'> 50% of sources
^•T7>Provide data for
K'.-..J< 50% of sources
Provide data for
0% of sources
necnnn'
-------
It sno.ild be noted that these figures are based on the number of
3tatfs"r-es;,e cifferent. For example, Figure 7 illustrates the number of
sources and emission points associated with the States' ability to provide
e-.issicn cata for sources emitting more than 2,500 TRY of SOj. In this
case, considering either the number of State responses or the associated
plants or points'would seem to have the same implications for the coverage
of emission sources. However, for NOX (see Figure 8), the implications
are efferent depending on whether State responses or number of plants or
points are used. Still, neither of these figures show what portion of
tr.e total inventory would be accounted for, which could have other
^-plications for resource allocation. All of these variables will need
to be considered as further evaluation of the surveys occurs.
In acdition to oeing asked about their being able to provide the
;ssired emission information, States were askea whether they could also
..., . -,._, ^vission estimates with their S02 and NOX sources. Figure 9
• • ;5f = tes ''c-.' HC"_; Steles could confirm the emission estimates they
a: 1 ^ to c-> e", 01 for sources emitting more than 2,SOU TRY of SC^.
e, of tne 26 States that would b.e able to develop emission
£it:-,£.tes for all sources emitting over 2.5UU TRY of SOj, 21 would be
aL.le to confirm t'icse estimates and five States would be able to confirm
tie estimates of only a portion or none of those sources. Figure 10
i "i: jstrat&s similar confirmation capabilities regarding SG£ sources
er-ittirg more than 1,000 TRY. The responses regarding NOX sources were
similar. One indication of these figures is that almost all States that
would be able to estimate emissions for all their sources would be able
to confirm tnose emissions, whereas those" States who could estimate
emissions for only a portion of tneir sources would be able to confirm
emissions for only a portion of those sources.
Amount and Type of Assistance Needed - If a State would need assistance
in providing the 19R5 emission inventory information that was needed, it
was asked to determine the amount of assistance (in man-hours and material
costs) that would De needed to (a) develop and confirm emission estimates
for sources emitting more than 2,500 TRY of SO? or NOX; (b) develop
emission estimates for sources emitting more than 100 TRY of SO?, NOX, or
''••'".; and 'r] -e/^0p emission estimates for sour.es emitting more than
i'Ju TRY of ?\\ or l.Juu TRY of CO. Figure 11 presents the total requested
assistance associated with these three levels of inventory development.
Of the total S2.05 million requested, about 20 percent or 5410,000 would
Dr: needed to develop and confirm emission estimates for sources emitting
Tore than 2,500 TRY of S02 or NOX. Over half of the amount requested
w:uld^he used to develop the emission estimates for sources emitting more
t1^ 1'JO 1DV of SOj, NOX, or VOC, and about a fourth would be needed for
-••. sources of ftf and CO.
104
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Figure 7. ABILITY TO PROVIDE 1985 EMISSIONS
FOR S02 SOURCES >2500 TRY
( NAPAP Emissions Inventory )
PERCENT OF TOTAL
100% r
Provide data for
100X of sources
Provide data for
> 50% of sources
Provide data for
< 50% of sources
Provide data for
0% of sources
105
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Figure 8. ABILITY TO PROVIDE 1985 EMISSIONS
FOR NOx SOURCES > 2500 TRY
( NAPAP Emissions Inventory )
PERCENT OF TOTAL
100X
90
80
70
60
50
40
30
20
10
0
Provide data fop
100% of sources
Provide data for
> 50% of sources
Provide data for
< 50% of sources
Provide data for
0% of sources
106
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Figure 9
STATE RESPONSES
30
25
20
15
10
5
0
ABILITY TO CONFIRM 1985 EMISSIONS
FOR S02 SOURCES > 2500 TRY
( NAPAP Emissions Inventory )
R vConflri 100X of
Confirm > SOX of
sources
Confirm < 50% of
Sii sources
none of
sources
Provide data fnr
100X of sources
Provide data for
50X of sources
Provide data for
< SOX of sources
I Provide data for
OX of sources
STATE CAPABILITIES TO PROVIDE
DATA ( Numbers of States )
107
-------
Figure 10
ABILITY TO CONFIRM 1985 EMISSIONS
FOR S02 SOURCES > 1000 TRY
( NAPAP Emissions Inventory )
STATE RESPONSES
25
20
15
10
5
0
Confirm none of
sources
Confine > SOX of
sources
Confirm < SOX of
sources
! Confirm 100X of
_ sources
Provide data for
100X of sources
Provide data for
> SOX of sources
Provide data for
< SOX of sources
Provide data for
OX of sources
STATE CAPABILITIES TO PROVIDE
DATA ( Numbers of States )
108
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Figure 11
LEVEL OF ASSISTANCE REQUESTED TO
DEVELOP 1985 NAPAP INVENTORY
>100 tpy S02/NOx/VOC~55X^
>2500 tpy S02/N0x~20%
PM and CO--25X
Total Assistance Requested =
$ 2. 052, 688
-------
A'- ir.r^rtant indication from tnese numbers is that, based on the
•.••-.-.-. =1 State calculations, available funds (about SI million) could
•.:"::ariv support tne level of assistance needed to ensure the development
:'" e~:ssi;^ in. entries o* sources emitting more than 2,500 TPY of 502 or
vjx. nowever, the remaining funds do not appear sufficient to ensure
aae^ate coverage o* sources emitting more than 100 TPY of S02, NOX, VOC,
zr ?'•' or l.OOJ TPY of CO. Subsequent evaluations will determine whether
tne assistance needed can be provided in a way to produce considerable
cost savings, whetner the data and inventory needs should be modified, or
wnetier additional funding sources should be sought.
T?i s a-.e tvpe o'~ information on assistance requested has been summarized
cr> a Regional sasis. Figure 12 shows that acquiring emission data for
so,rces"e~itv>.3 -lore than 100 TPY of S02, NOX, or VOC accounts for the
largest portion of requested assistance in almost all EPA Regions.
It is interesting to note that the 20 percent of requested assistance
fjr nevelopiny e^ssi'jn aata for the large 502 and NOX sources would help
=•-,„'= tiat o.er j'j percent of S02 point source emissions ana over 80
.-'_--.; a*' '. jr po^"-t soijrce emissions are ccvered in the -'nventory effort.
5:-. r'-j'e lj. •':•- fie jtner na^cj, tne assistance requestea for S02. NOX,
c_nj: v^C sources ^rtr.ter than 10'J TPY would be associated with less than
"..Percent of t^c S02 point source emissions and less than 20 percent of
f= '.0A e:--,-; ssi 3rs. It is important to add, nowever, that tnis later
: also address about 95 percent of tne VOC point source emission
As e>,;;e:tec, tne level of assistance needed generally increases with
*."e r'-"t:er of so^-ces ?. State has, although there are exceptions. Figure
1 •* ""i^strates tne req'jestea assistance for developing the inventory for
sources err.tting nore than 2,500 TPY of 862 and NOX as a function of the
ij-ner of those sources in the State. Further evaluation reveals that
tie cost ^er source is widely variable and, if any trend can be discerned,
it is generally constant over the range of the number of sources per
State. Fi^'jre 15 shows the wide range for cost per source associated
w-tn the assistance requested for sources emitting more than 2,500 TPY
SO? or ;,0r. A similar graph for developing the inventory of sources
e' ittiry nortf tnan ijj -PY of 502, NOX, VOC, or PM or 1,000 TPY of CO is
s'uwn in Figure 16. A slight downward trend is shown by the regression
ana1ys-is, rut the >:ide range in costs per sources is apparent.
States indicated tnat most of the assistance needed would involve
aata eaiting and quality assurance activities, data collection from the
screes, or data processing to enter the data into the State files.
Mgure 17 illustrate the responses of the States, given the seven categories
listed. States also indicated a preference for receiving direct supplemental
-r2nt assistance as opposed to contractor support. See Figure 18.
110
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Figure 12
LEVEL OF ASSISTANCE NEEDED FOR
1985 NAPAP INVENTORY EFFORT
( by EPA Region )
% OF TOTAL REQUESTED
10
v vi
REGION
VII VIII IX
X
> 2500 tpy
S02 or NOx
> 100 tpy
S02. NOx or VOC
> 100 tpy PM and/or
> 1000 tpy CO
October 17. 1985
-------
Figure 13. COVERAGE OF EMISSIONS INVENTORY AT
TWO LEVELS OF ASSISTANCE
PERCENT Or TOTAL
100
90
80
70
60
5 50
40 L
30
20
10
0
> 2500 tpy MOO and <2SOO tpy +
SOUrlCrJ S1ZK CUT-OFr
* Point sources only. (1980 NAPAP Inventury)
+ > 100 tpv VUG
October 16. 1985
Percent of Total
Funds Requested
% Total S02 *
% Total NOx x
1. lotal VOC
> 100 tpy
-------
Figure 14. NUMBER OF S02 AND NOx SOURCES
> 2500 TRY vs. LEVEL OF
ASSISTANCE REQUESTED *
LEVEL Or ASSISTANCE REQUESTED ( $ ) .
25. 000 r
*
20. 000
15. 000
10. 000
5000
o
0
^ * :
*
• ^ i ' i • i
10 20 30
*
,-*
i
-10
*
-1
70
bO 60 70 80
NUMBER Or SG2 AND NOx SOURCES
Overlap may nave occurred in adding S02
$ as f (# sources)
90 100
-------
Figure 15.
COST PER SOURCE
(>2500 TRY S02 or NOx)
AS FUNCTION OF NUMBER OF SOURCES *
COST PER SOURCE ( $ )
600 r
500
400
300
200
100
0
A
A
A
A
A
A
....A.
A
-A-
A
A
A
A
A
A
A
o
10
20 30 40 50 60 70 80
NUMBER OF S02 AND NOx SOURCES
Overlap may occur in adding SO2 and NOx
90
Cost per source
(as f (# sources))
A
100
-------
Figure 16
COST PER SOURCE ( $ )
1000 r
900 -
800 -
700
600
500
400
300
200
100
O
O
O
b o
- o
O
COST PER SOURCE, TOTAL INVENTORY
( MOO tpy S02, NOx, VOC and PM, and
>1000 tpy CO )
O
o
GOO
Cost per source
(as f (# sources))
O
i . . . . i . . .
0
TOTAL NUMBER OF SOURCES (by State)
Overlap may occur in adding S02 and NOx
t*ni innPQ
-------
Figure 17. TYPES OF ASSISTANCE NEEDED
( 1985 NAPAP INVENTORY )
DATA PROCESSING TO ENTER
DATA INTO STATE SYSTEM/
FILES - 22%
DATA PROCESSING TO
PRODUCE NEDS SUBMITTAL -
9%
SOFTWARE CHANGES TO STATE
SYSTEM TO PRODUCE NEDS
SUBMITTAL - 4%
OBTAIN DATA FROM
SOURCES - 21%
OTHER - 6%
DATA EDITING/QUALITY
ASSURANCE - 23%
CALCULATION OF EMISSIONS
ESTIMATE - 15%
42 of 49 total possible responses received
-------
Figure 18.
ASSISTANCE REQUESTED BY STATES FOR
1985 NAPAP INVENTORY
( by Type and Amount )
Section 105—68%
Section 105—75%
Other—9%
Both—9%
Contractor—15%
PROPORTION OF STATES REQUESTING
ASSISTANCE. BY MECHANISM
Other—IX
Both—18%
Contractor—6%
AMOUNTS REQUESTED. BY
MECHANISM
-------
Alnost all States noted that they would not be able to submit the
.lislr&a cata significantly before July 1, 1937. Nineteen iI3; States
in-icatea t^at tneir requests ^or assistance would oe reduced if two or
t.-iree accifio.nal months were allowed for their subnittal. See Figure 19.
Eignt of inese 19 States were able to estimate a total reduction in
resource requirements of about $325,000; the other States did not provide
estimates of reductions.
Process for Providing Assistance
The survey responses will be used to determine the types and levels
or assistance needed by States to provide the desired emission data.
-!.>out SI million (S500K in Section 105 funds and S500K in NAPAP funds)
are available to provide direct financial assistance to States or to
ueveiop appropriate contractor projects to satisfy the needs of tne
States. In addition to the survey responses, follow-up discussion with
States and Regional Offices will be used to identify alternative approaches
*or providing tne assistance needed. The alternative approaches will be
•'•-I/1-;wec wit'; tni STn^PA committee, and a final plan for providing tne
*;si5tenct '."11 be ctveloped. By December 1935, appropriate grant
-.•'•i":~er.ts to States sroulc be made and contractor projects should 3e
developed.
118
-------
•JO
Figure 19
OF STATES
25 r
20
15
10
WOULD ADDITIONAL TIME REDUCE
RESOURCE REQUIREMENTS ?
15
fx>x-^x^:^x^
^.,\>-S,y^\
^X--;\'X<-:
f\ \ •«. xX \ . . yx ' y **
rvX^c/vA^Xi-c-^
Yes
K&M^&S^
No
Not Applicable
-------
SESSION 3: FORMULATION OF MAN-MADE POLLUTANT EMISSION FACTORS
Chairman: Dale Pahl
Air and Energy Engineering Research Laboratory (MD-61)
U. S. Environmental Protection Agency
Research Triangle Park, NC 27711
120
-------
DEVELOPMENT OF NAPAP EMISSION FACTORS
FOR ANTHROPOGENIC SOURCES
BY
J.B. Homolya
Radian Corporation
P.O. Box 13000
Research Triangle Park, NC 27709
EPA Contract No. 68-02-3994
Work Assignment No. 32
EPA Project Officer:
J. David Mob ley
A1r and Energy EnglneMng Research Laboratory
Research Triangle Park, NC
Presented At:
Second Annual Add Deposition Emission Inventory Symposium
Charleston, SC
November 12-14, 1985
121
-------
DEVELOPMENT OF NAPAP EMISSION FACTORS FOR ANTHROPOGENIC SOURCES
BY: J.B. Homolya
Radian Corporation
ABSTRACT
The NAPAP emissions Inventory activities from 1980 to 1985 have
Included the development of anthropogenic emissions Inventories to
support the formulation and testing of an Eulerian atmospheric
transport, transformation, and deposition model. The model requires
high levels of species* temporal, spatial, and sectoral resolution for
emissions Inventory Input parameters. A numhar of the pollutant species
Included 1n the Inventory development required the formulation of
source-categorized emission factors which were developed from
assessments of data available in the literature. To date, detailed
emission factor assessments have been prepared for primary sulfates,
ammonia, hydrochloric acid, and hydrofluoric acid. For certain source
categories, the assessments were compared with additional stack
measurements conducted to address data gaps or to verify the quality of
the emission factors. An assessment of alkaline dust emission factors
has pointed to the need for both detailed chemical composition and
particle size distribution data to support emission factor development.
Ongoing research is addressing this need and providing further
development of VOC emission factor data needed to support the 1985 NAPAP
emissions Inventory.
INTRODUCTION
The Eulerian acid deposition model currently being developed by the
National Center for Atmospheric Research requires emissions data based
on certain chemical species which act as direct acidic emissions to the
atmosphere, scavengers of primary or secondary adds 1n the atmosphere,
or catalysts 1n atmospheric transformation processes. Most of the
chemical compounds or classes of compounds needed for input into the
modules describing chemical transformation and deposition processes
122
-------
are non-criteria pollutants. Because of this, limited Information is
available concerning emission factors for most of these species.
Therefore, an anthropogenic emission factor development program within
NAPAP was designed to formulate appropriate emissions Inventories using
the best pollutant speclatlon data available. Emission factor
development was Initiated In 1983 with the preparation of emission
factor assessments for primary sulfate , ammonia, hydrochloric add, and
hydrofluoric add. These species were selected because they are the
priority pollutant species required for use 1n both Lagranglan modeling
projects and the preliminary development of the Eulerian model.
The assessments began with a review of a compilation of data
available 1n the literature. Where data were Incomplete, a series of
emission tests were conducted at the Department of Energy, Pittsburgh
Energy Technology Center. To date, emissions tests have been conducted
for bituminous coal combustion omissions of HC1, HF, and primary
sulfate.
During 1985 preliminary assessments were performed on the
development of point source alkaline partlculate emission factors.
Emphasis was given to the consideration of particle size distribution
and the chemical cctnposltlon of the alkaline fraction of total
particulate emissions. Further, source categories were Identified which
require the development of VX emission factors. Priorities have been
assigned and Incorporated 1n an implementation plan for data gathering.
This paper summarizes the current results of the NAPAP emission
factor development program by presenting tabulated estimates of emission
factors derived for the above species. The estimates are provided
according to source classification code (SCO format and Include
emissions calculations for 1980.
123
-------
PRIMARY SULFATE EMISSIONS
Sulfur present 1n fossil fuels 1s emitted to the atmosphere mainly
as SO . However, some of the sulfur 1s oxidized further 1n the
combustion process and 1s emitted as primary sulfate compounds. The
largest source of primary sulfate emissions (PSE) is from the combustion
of coal and oil. The amount of primary sulfates emitted from a
particular combustion source is dependent on a number of factors
including fuel type and composition, combustion equipment design,
operating parameters, and emissions controls.
A significantly higher conversion of fuel sulfur to primary
sulfates occurs during oil firing as compared to coal firing. Enhanced
PSE from oil combustion are due to the low ash, fast burning properties
of fuel oil. Also, many residual oils contain high levels of vanadium
which can catalyze the formation of SO. in a furnace.
Sulfates are formed in combustion processes 1n both the flame
region and downstream in the heat transfer section. The major primary
sulfate formation mechanisms include oxidation of S0_ to SO.,, hydration
of SO, to H_SO., corrosion of boiler internals by H_SO., and conversion
of metallic oxides 1n fuel ash to particulate sulfates. In combustion
flames, the predominant sulfate formation mechanism 1s reaction of
molecular oxygen to form SO-. The final SO., concentration leaving the
flame zone depends on 0_ concentration, cooling rate, and the location
and rate of mixing of excess air.
Increased PSE can be affected by the heterogeneous catalytic
oxidation of S0_ by metals, metal oxides, and soot suspended 1n the
stream of combustion gases or deposited on boiler internal surfaces.
Residual fuel oils from Venezuela and the Middle East contain
significant amounts of vanadium which 1s liberated as V^O,. during
combustion. V_05 has been used extensively in the chemical
manufacturing Industry, as an oxidation catalyst. The major
constituents of coal fly ash, S102 and Al^. are only weak catalysts.
SulfuMc add is formed hy reaction of SO, with water vapor 1n
combustion product gases. The acid can adsorb on ash or soot particles,
condense on cooler parts of the combustion equipment, or be emitted to
the atmosphere as a mist. The SO.-to-H.SO. conversion is temperature-
and moisture-dependent.
124
-------
REVIEW OF AVAILABLE PRIMARY SULFATE EMISSION FACTOR DATA BASES
Prior to the current need for NAPAP Task Group B to Inventory PSEf
two separate environmental program activities have Included assessments
of PSE factors for use 1n emissions Inventory development. The Electric
Power Research Institute sponsored a sulfate regional experimental study
which included a summary of existing measurements data on primary
sulfates and recommended generalized emission factors for a number of
source categories. Many of the factors were based upon an extrapolation
of a limited data set for uncontrolled fossil fuel combustion sources
along with data contained 1n the EPA Emission Factor Guidelines (AP-42).
The United States/Canada Work Group 36 (WG 3B) prepared an emission
Inventory report 1n accordance with the Memorandum of Intent on
Transboundary A1r Pollution of August 1980. The report Included a
study of U.S. and Canadian PSE using factors abstracted from the
literature along with unpublished emissions data from Canadian
measurements obtained from the use of a variety of sampling and analysis
methods.
Following review of the EPRI and WG 3B sulfate emissions data sets,
an extensive literature review was conducted to Include al• contemporary
PSE measurements data in a final analysis and tabulation of emission
factors appropriate for the NAPAP emissions Inventory. Where available,
all field measurements using the controlled condensation system (CCS)
procedure were considered as the prime data set. Emissions data
acquired through the use of methods other than CCS were Included only 1f
multiple measurements yielded precise data. Sulfate emission
assessments were aggregated for different point sources within the same
source category only 1f fuel composition and emission controls were
similar.
PSE factors recommended for use 1n the NAPAP Emissions Inventories
are listed 1n Table 1. The factors are reported for source classifi-
cation codes (SCCs) and reflect sulfate emitted as SO. (molecular
4
weight = 96) based on the chemical analyses of source test samples.
Much of the current data set 1s for fossil fuel combustion 1n the
Industrial and utility sectors which contribute most of the regional
mass emissions of primary sulfates. Table 1 also contains an estimate
of the uncertainty for each emission factor. The estimates are based on
a Qualitative assessment of the representation of available source test
125
-------
TABLE 1. PRIMARY SULFATE EMISSION FACTORS FOR NAPAP EMISSIONS INVENTORY
Source category
Electric Utilities - External Combustion
Eastern bituminous coal
Western bituninous coal
Lignite
Residual oil (>li sulfur content)
Industrial - External Combustion
Eastern bituminous coal
Res i dual oi 1
Ccwiercial/Institutional - External Combustion
Residual oil (<-lX sulfur content)
Space Heating - External Combustion
Distil late oi 1
Industrial Process - Cheaical Manufacturing
H2S04-contact process
Industrial Process - Prinary Metals
Primary copper smelters
NEDS Source
classification
code (!,CC)
1-01-002
1-01-002
1-01-003
1-01-004
1-02-002
1-02-004
1-03-004
1-05-001-05
3-01-023
3-03-005-1
3-03-005-2
3-03-005-3
3-03-005-4
Control device
ESP
ESP and FGD
ESP
ESP and FGO
ESP
Fuel oil additive
Multiclones
Multiclones and FGO
Mult (clones
Multiclones and FGO
Fuel oi 1 additive
None
Deoister
ESP
ESP
ESP
ESP
Prinary sulfatei* Uncertainty
emission factor range*
0.385 Ib/ton
0.250T
1.290
0.761
1.951
5.439 lb/1,000
gal Ions
2 646 Ib/ton
0.462
5.296 lb/1,000
gallons
2.616
25.07 lb/1,0005
gal Ions
5.65 lb/1,000
gal Ions
0.100 Ib/ton
acid produced
22.5 Ib/ton
concentrated ore
1.08
5.76
15.66
A
C
8
C
C
B
8
C
0
D
C
C
B
C
C
0
0
(continued)
126
-------
TABLE 1. Concluded
Sourct category
Industrial Process - Primary Petals (Cont'd)
Primary zinc smelters
Primary aluminum smelter
Iron production
Cokt
Industrial Process - Wood Products
Kraft pulp «i 1 1
Sulfltt pulp mill
Wood/bark wastt
Industrial Process - Mineral Products
Cement manufacturing
Cypsjmi rianufacturing
NEDS Source
classification
code (SCO
3-03-030
3-04-001
3-03-008
3-03-003
3-07-001
3-07-002
1-02-009
3-05-006 and
3-05-007
3-05-015
Control device
ESP
ESP
ESP
Baghoust
ESP
ESP
Hulticlones
ESP
ESP
Primary sulfateit
emission factor
55.5 Ib/ton
processed
0.5X of SO,
2. OX of SO,
0.320 Ib/ton
coal charged
»
**
3.6 Ib/ton
bark
TT
§*
Uncertainty
range*
0
0
0
0
c
c
0
D
0
Industrial Process - Petroleum Industry
Fluid crackers
Sulfur recovery Claus plants
3-06-002
3-01-032
ESP
None
15.0 lb/1,000
barrels 011
2.8 Ib/ton
produced
* Estimated Mission factor uncertainty. Assumes that 90S of the values for an individual source He within the
wan uncertainty estimates. Corresponding values are: A = tlOX; B = t25X; C = i50X; and 0 = t75X.
r Emission factor based on averagi sulfatt scrubbing efficiency of 35X.
i Emission factor applicable cnly to low sulfur content (0.3X S) resiaual fuel oil.
I Total sulfate Missions for kraft pulp Bills estiMted as B5X of NEOS total particulate missions from kraft
recovery taoilers.
•• Total sulfatt Missions fro* sodluvbtst sulfite Bills estimated as 70X of NEDS SO, emissions; for calciua-bas*
sulfitt "ills tstiMted as 2SX of NEDS SO, Missions.
tT Total sulfatt Missions froe ceewnt kilns estimated as 5.6 Ib/ton of cemnt on an uncontrolled basis. Average-
particulate control efficiency fro" N€OS data assused to apply in order to calculate actual Missions.
H ToUt sulfatt frot) gyptut) plants estimated as 56X as NEDS actual particulate Missions.
H Although tt It EPA policy to utilize ••trie untti. non-*»tr1c units have bewn used In this paper since. th«
NAPAP emission factor file It In non-attr1c unit*. For conversion froa non-**tr1c units to oetric units not*.
that 1 Ib - 0.4S3 kg and that 1 ton (non-e»tr1c) • 1 short ton - 2000 Ibt - 0.907 m*tr1c tons.
127
-------
data to the assignment of SCC-level factors. Improvements are needed 1n
the data base for low sulfur residual-oil-fired industrial and
commercial boilers which represent a significant source of sulfur
emission in major metropolitan areas in the eastern U.S. Also, sulfate
emission from the pulp and paper Industry needs further refinement.
Pulp mill operations are concentrated in the acid deposition sensitive
Northeast and represent a major SCL and particulate source contributor
in the southeastern United States.
HYDROCHLORIC ACID EMISSIONS
Table 2 lists the sources of hydrochloric acid emissions along with
emission factors and estimates of emissions for 1980. Coal combustion
is the largest source of HC1 emissions, accounting for
467,000 ton/yr.
Coal is formed over eons from successive layers of fallen
vegetation. As vegetation accumulates, physical and chemical changes,
such as loss of water and volatile matter, occur. Over time, the
vegetation turns from peat to lignite, the earliest stage in the
formation of coal. As lignite is compressed with deeper burial, the
heat ai Delated with the compression drives off volatile components. As
more volatile components are driven off, the rank and quality of the
coal increase from lignite to subbituminous, bituminous, and anthracite.
The chlorine concentrations of domestic coals vary over a large range.
The coal fields with the highest chlorine content are in the Illinois
basin. The molecular form of chlorine in coal is not clearly
understood. Chlorine in coal exists in both organic and Inorganic
forms. Although 1t has been shown that chlorine occurs in coal 1n a
form more volatile than sodium chloride, no correlation has been
developed between the molecular form of chlorine 1n coal and its
combustion products.
COAL COMBUSTION IN UTILITY BOILERS
There are three principal types of coal-fired utility boilers:
stoker-fired, cyclone furnaces, and pulverized-coal-fired (PC-f1red).
Of the three types currently used, PC-fired is the most common.
Scrubbers, electrostatic predpitators (ESP), cyclones, and baghouses
-------
TABLE 2. MAJOR SOURCES OF HYDROCHLORIC ACID EMISSIONS
ro
I-D
Source
Coal combustion
Utility and Industrial
bituminous
lignite
Commerc 1 al / 1 nst 1 tut 1 onal
anthracite
bituminous
lignite
Incineration
Municipal refuse
multiple chamber
single chamber
conical design- refuse
Industrial wastes
multiple chamber
single chamber
controlled air
conical design-refuse
Liquid wastes
Emission factor*
(Ib emitted/unit)
1.9
0.01
3.07
1.48
0.351
5.0
5.0
5.0
5.35
5.35
5.35
5.35
1.19
I960
Emissions
(ton/yr) SCC
467,000
1-01, 02-002
1-01, 02-003
1-03-001
1-03-002
1-03-003
75,000
5-01-001-01
5-01-001-02
5-01-005-07
5-03-001-01
5-03-001-02
5-03-001-03
5-03-001-04
NA
SCC units
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
* Although 1t Is EPA policy to utilize metric units, non-metric units have been used In this paper since the
NAPAP emission factor file 1s 1n non-metric units. For conversion from non-metric units to metric units note
that 1 Ib ** 0.453 kg and that 1 ton (non-metric) = 1 short ton = 2000 Ibs = 0.907 metric tons.
-------
are used frequently as flue gas control techniques. These control
devices are effective for different pollutants and often are used in
combination. An ESP or a baghouse has no demonstrated effect on HC1
emissions. However, alkaline materials are sometimes used in
conjunction with a baghouse to remove sulfur compounds. This could also
result in a removal of HC1.
Cyclones or centrifugal separators also are used in the control of
particles from utility boilers. Cyclones are assumed to have no effect
on HC1 emi ssions.
Wet scrubbers also are used to remove particles from flue gas
streams. A wet scrubber can use a variety of methods to wet the
contaminant particles in order to remove them from the gas stream. The
efficiency of a wet scrubbing device for HC1 emissions control should be
greater than that ?. a baghouse or ESP. One study demonstrated an
80 percent efficiency for HC1 removal from bituminous-coal-fired utility
boi1ers.
Gaseous sulfur compounds typically are removed from flue gas
streams by flue gas desulfurization (FGD) systems. In FGD, the sulfur
compounds are reacted with an alkaline substance. The resulting
compound then is removed from the flue gas stream. HC1 should be
removed from flue gases with FGD systems; however, little data are
available to quantify the removal efficiency.
COAL COMBUSTION IN INDUSTRIAL BOILERS
Industrial boilers are smaller than utility boilers and are used by
industry to provide steam or hot water. Only 10 to 15 percent of the
industrial boiler coal consumption 1s used for electricity generation.
Coal burning Industrial boilers are classified by heat transfer method,
arrangement of heat transfer surface, and fuel feed system. The three
types of heat transfer systems are watertube, flretube, and cast iron.
Most newly Installed Industrial boilers are e.ther watertube or
firetube. Fuel feed systems are the same as discussed under utility
boilers—stoker, cyclone, and PC-f1red. Emission factors for HC1 have
not been developed for industrial boilers. Emission factors developed
100
-------
for utility boilers can be used for Industrial boilers when the type of
boiler and fuel are the same. A1r pollution control technologies for
industrial boilers are the same as those discussed under utility
bollers.
COAL COMBUSTION IN RESIDENTIAL BOILERS
At the present time» approximately 1 percent of the nation's homes
are heated with coal. Lignite is burned for residential heating in
North Dakota only; anthracite combustion is limited to northern states
east of the Mississippi Riven with 64 percent in Pennsylvania; and
bituminous coal is burned In every state except Connecticut* Delaware.
Maine, Maryland, New Hampshire, New Jersey, North Dakota, Rhode Island,
and Vermont. HC1 emission factors have been reported as
60.5xlO~9, IZO.OxlO"9, and 35.1xlO~9 Ib/Btu for bituminous, anthracite,
and lignite combustion, respectively.
INCINERATION
HC1 is emitted during the Incineration of wastes containing
chlorinated hydrocarbons, chlorine-containing plastics such as polyvlnyl
chloride, and chlorine or chlorides, often 1n the form of common salt.
Incineration 1s a combustion process used to change the chemical or
physical characteristics of waste by oxidation which, even under ideal
combustion conditions, results in Inorganic solid residues and exhaust
gases.
HC1 is emitted as a result of incomplete combustion from three
types of incinerators: !1) municipal incinerators that burn public
garbage; (2) municipally owned Incinerators that burn primarily
Industrial wastes; and (3) Incinerators that burn liquid wastes such as
polychlorlnated waste, waste oil, and various other hydrocarbon 'liquids.
Emissions from the public Incineration of apn- dmately 30x10 tons of
collected refuse 1n the United States 1n 1. produced estimated
emissions of 75,000 tons of HC1. The emission factor for this source 1s
calculated as 5 Ib HCl/ton of refuse burned.
Emission factors for municipally owned Industrial waste
Incinerators range from 2.0 to 7.0 Ib HCl/ton of wastes burned with a
mean value of 5.35 Ib/ton. Several sources were tested for emissions
131
-------
from Incineration of liquid wastes. Emission factors from the test data
ranged from 0.72 to 1.61 Ib HCl/ton of waste burned with a mean
uncontrolled emission factor of 1.19 Ib/ton.
HYDROFLUORIC ACID EMISSIONS
Table 3 shows the major HF emissions sources and provides a summary
of total emlsslonst emission factors, and applicable SCCs. Coal
combustion 1s the largest source of HF emissions* accounting for
58,000 tons/yr. Fluorine present 1n coal 1s converted to HF during the
combustion process and emitted to the atmosphere. The effectiveness of
emissions controls for HF 1s assumed to be similar to that discussed
previously for HC1.
PRIMARY ALUMINUM INDUSTRY
The base ore for primary aluminum production 1s bauxite* a hydrated
oxide of aluminum consisting of 30 to 70 percent alumina (AI^O,) and
lesser amounts of Iron, silicon, and titanium. Bauxite ore 1s first
purified to alumina by the Bayer process, and then the alumina 1s
reduced to elemental aluminum. The production of alumina and the
reduction of alumina to aluminum are two separate processes, seldom
accomplished at the same location. Fluoride emissions from primary
aluminum production are from the reduction process only.
Fluoride emissions from primary aluminum production occur 1n the
gaseous phase as HF with a small amount of silicon tetrafluorlde (S1FJ,
and 1n the partlculate phase as cryolite (Na-AlF,). The ratio of
gaseous to partlculate fluorides varies with the particular emission
point within the process.
The principal points of HF emissions are the primary and secondary
emissions from the potrooms housing the reduction cells and, 1n the case
of the prebake cell, the emissions from the associated anode bake
plants. HF emissions from bauxite grinding and aluminum hydroxide
production are negligible. The manufacture of anodes for prebake cells
emits HF from the fluorides 1n the recycled anode butts.
132
-------
TABLE 3. MAJOR SOURCF.S OF HYDROFLUORIC ACID EMISSIONS
CO
CO
1980
Emission factor* Emissions
Source (lb emitted/unit) (ton/yr)
Coal combustion
Utility
bituminous
lignite
Industrial
bituminous
Commercial/ Institutional
anthracite
bituminous
lignite
Primary aluminum production
Anode baking furnace
Prebaked reduction cell
Prebaked fugitive emissions
Vertical Soderberg stud cells
Vertical Soderberg stud cells
fugitive emissions
Horizontal Soderberg stud cells
Horizontal Soderberg stud cells
fugitive emissions
Gypsum ponds
58,000
0.23
0.01
0.62-0.81
0.13
0.17
0.063
13,300
0.52
4.9
1.2
0.6
4.9
1.9
2.2
1.275 6,400
sec
1-01-002
1-01-003
1-02-002
1-03-001
1-03-002
1-03-003
3-03-001-05
3-03-001-01
3-03-001-08
3-03-001-03
3-03-001-10
3-03-001-02
3-03-001-09
3-01-016-02
SCC units
ton burned
ton burned
ton burned
ton burned
ton burned
ton burned
ton produced
ton produced
ton produced
ton produced
ton produced
ton produced
ton produced
tons P 05
produced
• Although It Is EPA policy to utilize metric units, non-metric units have been used In this paper since the
NAPAP emission factor file Is In non-metric units. For conversion from non-metric units to metric units, note
that 1 lb = 0.453 kg and that 1 ton (non-metric) = 1 short ton = 2000 Ibs = 0.907 metric tons.
-------
All three types of reduction cells emit HF from thermal hydrolysis
of volatilized bath materials, particularly cryolite. The reaction of
solid and vaporized fluorides at elevated tenperatures occurs primarily
at the point where the hot gases escape through vents 1n the crust at
the cell surface. The hydrogen required for the formation of HF 1s
supplied 1n part from water vapor in the air. Other sources of hydrogen
Include residual moisture 1n the alumina and bath raw materials and
hydrocarbons in the carbon anodes. The HF emission factor for prebake
cells 1s the sum of the HF emission factors for the anode baking furnare
and the prebake reduction cell.
AMMONIA EMISSIONS
Most ammonia emissions result from natural and biological
processes, primarily through the decomposition of organic matter such as
dead plants and animal and human excrement. Other natural sources
Include forest fires and volatilization from land and ocean masses.
Table 4 lists the major sources of ammonia emissions. Emission factors
are given along with the total estimated emissions.
AMMONIA FROM LIVESTOCK WASTES
The major sources of ammonia emissions from the production of
livestock Include beef production operations and manure spreading.
Production of beef cattle can be divided Into four stages: calf
production, backgrounding, finish feeding, and slaughtering. The wastes
excreted by cattle grazing on pastures or range areas are disperse,
allowing the soil to assimilate the excrement. However, manure produced
In feedlot situations must be removed and processed because of space
restrictions. Animal manure contains complex carbohydrates, protein,
and fats which are metabolized Into simpler compounds by microorganisms.
In the presence of oxygen, the end products of metabolism are heat, 00^,
and H_0. This process, called aerobic metabolism, 1s dependent upon
temperature, oxygen, and moisture. In the absence of oxygen, anaerobic
metabolism occurs with ammonia as an end product.
134
-------
TABLE 4. MAJOR SOURCES OF AMMONIA EMISSIONS
o
n
Source
Livestock wastes
Manure field application
beef cattl 9
dairy cows
hogs
broilers
other chickens
Beef cattle feed lots
Coal combustion
Ammonium nitrate manufacture
Neutral izer
Solids formation
Emission factor*
(Ib emitted/unit)
34
71
7.5
0.47
0.47
2.1
2.0
0.86-36.0
0.54-33.4
I960
Emissions
(ton/yr)
1,900,000
390,000
240,000
920,000
56,000
24,000
525,000
3,100-130,000
920- 57,000
sec
NA
NA
NA
NA
NA
3-02-020-02
1-02, 02, 03
3-01-027
5-01-027
SCC units
per animal
per animal
per animal
per animal
per animal
per animal
ton burned
ton produced
ton produced
•Although It Is EPA policy to utilize metric units, non-metric units have been used 1n this paper since the
NAPAP emission factor file Is In non-metric units. For conversion from non-metric units to metric units, note
that 1 Ib » 0.453 kg and that 1 ton (non-metric) 3 1 short ton = 2000 Ibs = 0.907 metric tons.
-------
Anmonia is emitted from beef production operations as a result of
anaerobic decomposition and volatilization of cattle wastes. Anaerobic
decomposition occurs in the solid manure beneath the feedlot surface, in
manure stockpiles, and 1n runoff holding ponds. Feedlot disturbances,
such as mounding and manure removal, greatly increase the release of
ammoniacal compounds to the atmosphere. Although 25 to 40 percent
moisture levels are necessary on feedlot surfaces for aerobic
decomposition, too much rain or watering, resulting 1n puddling and wet
spots, can trigger increased ammonia production. In addition, about
half of the nitrogen that cattle excrete is 1n the form of urea 1n
cattle urine. The urea In urine 1s hydrol1zed to ammonia and can be
released to the atmosphere.
The spreading of livestock manure on agricultural land 1s another
source of ammonia emissions. Field experiments Indicate that, when
dairy manure was spread 1n the field preparation for plowing under, an
85 percent loss of total ammonia by volatilization occurred. The dairy
manure volatilization rate may be applied to other types of domestic
livestock manure. The ammonia emission estimates from the field
application of livestock manure given in Table 4 were derived by
multiplying ammonia excretion rates by animal population levels for 1980
and by the 85 percent loss factor. Manure from beef cattle 1s the major
source of these emissions. The total emissions estimate for ammonia
from field application of livestock waste is 3.5 million tons.
AMMONIA NITRATE MANUFACTURE
Ammonia nitrate is produced by mixing nitric add and ammonia 1n a
reactor or neutral 1zer. Either ammonia or nitric add 1s emitted from
the neutralizing depending upon which reactant 1s added in excess to the
process. Most plants today operate the neutral1zer with excess ammonia.
An 83 percent aqueous ammonium nitrate solution 1s produced 1n the
neutral 1zer and may be sold for use as a fertilizer or further
concentrated for use 1n solid ammonium nitrate formation.
COAL COMBUSTION
Ammonia emissions from coal combustion were estimated from a
limited set of measurements data. An emission factor of 2 Ib NH /ton
coal burned was applied to all external combustion boilers for
anthracite, bituminous, and lignite fuels.
-------
ALKALINE DUST EMISSION FACTORS
Anthropogenic point source alkaline participate emission factors
have been calculated from available alkaline dust emissions data
reported by Meteorological and Environmental Planning, Ltd. and the
Ontario Research Foundation. The emissions data were based on the
Identification of major anthropogenic sources of partlculate Ca. Mg, Na,
and K emissions. Total partlculate emissions from these sources were
estimated along with the amount of the alkali ir.etals contained 1n the
partlculate.
Table 5 1s a summary of emission factors for each alkali metal
assigned to Individual SCC categories. Tho basic assumption 1s that the
alkali metal contents of U.S. and Canadian partlculate emissions are
Identical. For power generation and fuelwood combustion, the emission
factors are assumed to be applicable for utllltyi Industrial, and
commercial/Institutional source categories. Additional refinement of
the emission factors should Include estimates of the particle size
distribution of the alkaline partlculate emissions to assess the degree
to which the particles remain suspended 1n the atmosphere as a
neutralization sink for add.
VOC EMISSIONS
Although total VOC emissions have been Inventoried by the EPA
within the National Emissions Data System (NEDS), the EuleMan add
deposition model requires that VOC emission must be disaggregated Into
refined component species. VOC emissions must be classified by
photochemical reactivity with the flexibility of varying the assignments
to a class depending upon the modeling chemistry used.
Several major SCCs have either Incomplete or no VOC emission factor
and speclatlon data. Available emission factor data are being reviewed
to develop the best approch to fulfill the 1985 NAPAP Inventory
development needs. The program will pursue priorities for VOC emission
factor development which reflects NAPV needs and schedules, the
availability of existing data, and the most effective use of project
resources to fill current Information data gaps.
137
-------
TABLE 5. ANTHROPOGENIC POINT SOURCE ALKA1INE PARTICIPATE EMISSION FACTORS
Generic tource «**crlpt1on
Unit*
Percenttge of total pcrtlcuUte
e*)tulon «» *n «lk«)l Bet*!* Uncertainty
C« Hg N« K r*t1nj«
3-03-023
3-03-006
3-03-006
3-04-006
3 -OS -020
3-05-016
3-05-020
J -05-025
3-05-006
3-OS-OU
3-05-00*
3-07-O01
1-01-001
1-01-002
1-01-OO3
1 -O2-001
1-02-002
1-O2-003
1-03-001
1-03-002
1-09-003
3-40-001
3-40-002
3-40-003
1-01-00*
1-02-009
1-03-00*
1-05-002-0*
3-40-00*
5-02-002-01
5-01-001
S-O 1-002-01
5-01-O05-O7
5 -02-O01
Iron ore alr'ng and benedclatlon
Iron and tteal Industry
Ferroalloy Manufacture
MagnealuB production
Mining and rock quarrying
I IB* Manufacture
Stone procMiIng
Sand and gravel
CMBMMt Manufacture
Concrete hatch toy
Cl ay products aanuf actur*
Sulfata (Kraft) pulping
Poeer generation by utilities
Fuelvood coMbuitton
Municipal Incineration
Ton* pellet* produced
Ton* produced
Ton* produced
Ton* processed
Ton* raw aaterlal
Ton* 11 MB* tone processed
Ton* ra» Material
Ton* product
Ton* ceaent produced
Tjn» processed
Ton* Input to process
Air dry tons until eacited
pulp
Ton* burned
Ton* burned
Tons burned
0.49
3.98
1.06
23.81
5.77
35.89
14.36
0.65
28.50
46.00
0.85
0.12
1.62
0.05
0.57
0.24
1.66
1.45
13.90
1.69
5.01
4.12
0.^0
0.78
1.50
0.90
0
1.71
0.04
0.14
0
1.74
1.35
0
0
o.so
0
0
0
0
0
1.38
0.82
0.04
0.57
0
5.63
0
0
0
0
0
0
0
0
0
0
0.44
1.95
0.46
E
E
C
C
0
c
c
0
B
C
0
c
c
E
E
•Cx*>pl*: for SCC 3-03-023. e»1»»1oo* of *lktUne c«)du*> ptrttcultt*
-------
CONCLUSIONS
Emission factors have been developed for point and area sources of
primary sulfate, ammonia, and hydrochloric and hydrofluoric acids for use in
the 1980 and 1985 NAPAP emissions inventories. Preliminary alkaline dust
emission factors have been developed for anthropogenic point sources from an
emissions data set prepared in Canada. Alkaline dust emission factors are
needed which consider the particulate size distribution and neutralization
capacity of each mass/size fraction. Considerable additions and improvements
are needed for VOC emission factors and the level of speciation required to
support the development of the Eulerian chemical transformation modules.
NOTE: Although it is EPA policy to utilize metric units, non-metric units
have been used in this paper since the NAPAP emission factor file is in
non-metric units. For conversion from non-metric units to metric units, note
that 1 Ib = 0.453 kg that 1 ton (non-metric) = 1 short ton = 2000 Ibs =
0.907 metric tons.
139
-------
REFERENCES
1. Homolya, J. Primary Sulfate Emission Factors for the NAPAP
Emissions Inventory. EPA-600/7-85-037 (NTIS PB86-108263), U.S.
Environmental Protection Agency, Research Triangle Park, NC,
September L985.
2. Homolya, J. "Stationary Source Emission Factor Development,"
presented at the First Annual Add Deposition Emission Inventory
Symposium, Raleigh, NC, December 3-4, 1984.
3. Anthropogenic Sources and Emissions of Primary Sulfates in Canada,
Ontario Research Foundation, Contract No. 47SS.KE204-1-0318,
November 1981.
4. Anthropogenic Sources and Emissions of Alkaline Particjlate Matter
1n Canada, Meteorological and Environmental Planning Ltd., and
Ontario Research Foundation, Contract No. 52SS.KE145-3-0403, April
1984.
140
-------
SIZE SELECTIVE PARTICIPATE EMISSION FACTORS
FOR EMISSION INVENTORIES
by
Frank M. Noonan
Air Management Technology Branch (MD-14)
U. S. Environmental Protection Agency
Monitoring and Data Analysis Division
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
EPA Contract No.
EPA Project Officer:
U. S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
141
-------
SIZE SELECTIVE PARTICULATE EMISSION FACTORS
FOR EMISSION INVENTORIES
BY: Frank M. Noonan
Air Management Technology Branch
U. S. Environmental Protection Agency
ABSTRACT
Size specific Particulate Matter emission factors have been developed by
the U. S. Environmental Protection Agency (EPA) ao a result of source tests
performed on eleven major source categories. Within each source category, a
number of individual process operations have been characterized by particulate
matter size distribution emission rate measurements, along with levels of source
activity. In addition, size specific emission factors have been developed for
source categories based on information in EPA's Fine Particulate Emission
Information System (FPEIS) and in published literature.
INTRODUCTION
In order to implement size specific Particulate Matter National Ambient
Air Quality Standards, the U. S. Environmental Protection Agency has been dev-
eloping data bases for source categories, through the combined efforts of the
Office Of Air Quality Planning And Standards (OAQPS) and the Office Of Research
And Development (ORD), mainly ORD's Air And Energy Engineering Research Labora-
tory (AEERL). The primary purpose of this data base development is to produce
particle size related emission factors for these source categories to be used
principally by States in developing State Implementation Plans when a revised
Particulate Matter standard is promulgated by the Agency. These emission
factors also can be employed in developing emission inventories.
This paper summarizes briefly the source categories for which particle
size emission factors have been developed and made available or are presented
In draft reports now undergoing external peer review before their publication
in EPA's Compilation Of Air Pollutant Emission Factors, AP-42.
142
-------
DISCUSSION
Size selective particulate matter emission factor information, resulting
from U. S. Environmental Protection Agency's (EPA) emission factor development
program, is presented in terms of two efforts; (1) completion of source cate-
gory reports based primarily on EPA sponsored source testing of selected source
categories, and (2) particle size distribution and emission factor information
for additional source categories developed from data in the Fine Particulate
Emission Information System (FPEIS) and from open literature.
This source catsgoriee selected for testing are given in Table 1. Table 2
lists processes within each of these major source categories and presents
particle size distribution data from 2.5 to 10.0 micrometers. Fugitive dust
particle size emission factor data for urban paved roads, unpaved roads and
industrial paved roads are presently available in the Fourth Edition of EPA's
Compilation Of Air Pollutant Emission Factors, AP-42. The other source cate-
gory reports listed in Table 2 are in the process of external peer review
before publication of their emission factors in AP-42.
Table 3 presents a list of additional source categories for which particle
size data and emission factors are being developed from data in the FPEIS and
open literature. These factors are presently in draft form for external peer
review.
CONCLUSION
Particle size distribution data and emission factors have been developed
for eleven major source categories and a list of sources for which data is
available as a result of EPA's efforts. Particle size distribution data range
from 2.5 to 10.0 micrometers. Upon publication in AP-42, these data may be
used by States for emission inveitory and modeling purposes.
143
-------
TABLE 1. INHALABLE PARTICULATE PROGRAM SELECTED SOURCE CATEGORIES
PAVED ROADS
INDUSTRIAL AND UNPAVED ROADS
IRON AND STEEL
METALLURGICAL COKE
IRON FOUNDRIES
FERROALLOY
PRIMARY AND SECONDARY NONFERROUS METALS
CEMENT AND LIME
ASPHALTIC CONCRETE
KRAFT PDLP MILLS
COMBUSTION
144
-------
TABLE II. PARTICLE SIZE CHARACTERIZATION OF MAJOR SOURCE
CATEGORIES PROCESSES
IRON AND STEEL
A source category report for iron and steel presents particle size emission
factors for the following:
"Sinter plant windbox - uncontrolled, and controlled
with cyclone, scrubber, electrostatic precipitator
(ESP) arJ baghouse
"Sinter breakers - controlled with baghouse
"Blast furnace casthouse - uncontrolled
"Basic oxygen furnace (BOF) charging and tapping -
uncontrolled, and controlled with baghouse
"Basic oxygen furnace (BOF) refining (02 blow) -
controlled with scrubber
"Open hearth - uncontrolled, and controlled with ESP
"Quelle-Basic Oxygen Process (Q-BOP) - uncontrolled,
and controlled refining cycle with scrubber
"Electric arc furnace - uncontrolled, and controlled
with baghouse
"Hot metal desulfurization - uncontrolled, and
controlled with baghouse
METALLURGICAL COKE
The draft report presents particle size emission factors for the following:
"Coal preheating - uncontrolled, and controlled with
scrubber
"Coal charging sequential
"Coke pushing - uncontrolled, and controlled with
scrubber
'Push cars in both travel and push nodes - controlled
with scrubber
"Coke quenching - uncontrolled (with dirty and clean
water), and controlled with baffles
"Coke oven combustion stacks - uncontrolled
145
-------
IRON FOUNDRIES
The draft report presents particle size emission factors for the following:
"Cupola - uncontrolled, and controlled with baghouse
and scrubber
"Metal pouring and cooling - uncontrolled
"Shakeout process - uncontrolled
FERROALLOY
The draft report presents particle size emission factors for the following:
"50 percent FeSi open furnace - uncontrolled, and
controlled with baghouse
"80 percent FeMn open furnace - uncontrolled, and
controlled with baghouse
°Si metal open furnace - uncontrolled, and
controlled with baghouse
°SlMn open furnace - uncontrolled, and controlled
with scrubber
"FeCr open furnace - uncontrolled, and controlled
with ESP.
PRIMARY AND SECONDARY NONFERROUS METALS
The draft report presents particle size distribution information for the
following operations in the primary aluminum, copper, lead, and secondary lead
smelting industries.
"Primary Aluminum
Fugitive particulate emissions from a prebake
plant - uncontrolled
Fugitive particulate emissions from a horizontal
Soderberg plant - uncontrolled
Prebake reduction cells - uncontrolled
Horizontal Soderberg reduction cells - uncontrolled
146
-------
'Primary Copper
Multihearth roaster and reverberatory smelter
operations - uncontrolled
Reverberatory smelter operations - uncontrolled
and controlled with ESP
Converter operations - uncontrolled and controlled
with ESP
Reverberatory furnace matte tapping operation
fugitives - uncontrolled
Reverberatory furnace slag tapping operation
fugitives - uncontrolled
Converter slag and copper blow operations fugitives
uncontrolled
'Primary Lead
Blast furnace - controlled with baghouse
Blast furnace fugitives - uncontrolled
Ore storage fugitives - controlled
Sinter machine fugitives - uncontrolled
Reverberatory furnace fugitives - uncontrolled
Dross kettle fugitives - controlled
'Secondary Lead
Blast furnace - controlled with baghouse
Blast furnace - (ventilation system fugitives
from charging hood, metal and slag tapping
hoods) - uncontrolled
Blast furnace (ventilation system as above) -
controlled with baghouse
147
-------
CEMENT AND LIME
External peer review of the Portland Cement Industry and the Lime Industry
Source Category reports have been completed. Reviewer comments are under con-
sideration by EPA and ORD contractors to accommodate these comments and make
revisions, where necessary. Particle size distribution and related emissions
factors are presented as follows:
"Portland Cement
Wet kiln - uncontrolled, and controlled with ESP
Dry kiln - uncontrolled, and controlled with
multiple cyclone and baghouse
Clinker cooler - uncontrolled, and controlled with
gravel bed filter
"Lime
Rotary kiln - uncontrolled
Rotary kiln - controlled with cyclone, multiple
cyclone, ESP and baghouse
Product loading fugitives - limestone into open
trucks and enclosed trucks, and lime into
enclosed trucks
ASPHALTIC CONCRETE
External peer review of the source category report is completed. The
report is presently being revised to reflect reviewers comments. The report
presents particle size emission factors for the following:
"Conventional asphalt plant
Stack emissions - uncontrolled, and controlled
with cyclone collector, multiple centifugal
scrubber, gravity apray tower and baghouse
"Drum mix plants - uncontrolled, and controlled with baghouse
148
-------
KRAFT PULP MILLS
External peer review of the source category report is complete. The
report presents particle size emission factors for the following:
°Direct contact evaporator (DCE) recovery boiler -
uncontrolled, and controlled with ESP
"Nondirect contact evaporator recovery boiler -
uncontrolled, and controlled with ESP
"Lime Iciln - uncontrolled, and controlled with
venturi scrubber or ESP
"Smelt dissolve tank vent - uncontrolled, and
controlled with packed tower or venturi scrubber
COMBUSTION
The source category report is currently in external peer review. Particle
size emission factors for the following were presented in the draft source
category report.
BITUMINOUS COAL
"Dry bottom boiler - uncontrolled, and controlled with
multiple cyclone, scrubber, ESP or baghouse
"Wet bottom boiler - uncontrolled, and controlled with
multiple cyclone or electrostatic precipator
"Cyclone furnace - uncontrolled, and controlled with
scrubber or ESP
"Spreader stoker 'overfeed and underfeed) - controlled,
and controlled
-------
"Spreader sto* . r with and without flyash reinjection -
uncontroi: i, and controlled with multiple cyclone,
ESP, or bit; louse
"Spreader st.-.er (overfeed and underfeed) - uncontrolled,
and controj.led with multiple cyclone
SUBBITUMINOUS (LIGNITE) COAL
"Dry bottom boiler - controlled, and uncontrolled with
multiple cyclone
"Spreader stoker - controlled, and uncontrolled with
multiple cyclone
ANTHRACITE COAL
"Dry bottom boiler - uncontrolled, and controlled with
multiple cyclone
"Stoker - uncontrolled, and controlled with cyclone
RESIDUAL OIL
"Utility boiler - uncontrolled, and controlled with
ESP or scrubber
"industrial boiler - uncontrolled, and controlled
with multiple cyclone
"Commercial boiler - uncontrolled
WQOE WASTE
"Bark boilers - uncontrolled, and controlled
"Wood and b.irk boilers - uncontrolled, and controlled
150
-------
TABLE III. ADDITIONAL SOURCE CATEGORIES FOR WHICH SOME PARTICLE SIZE
DATA AND EMISSION FACTORS ARE AVAILABLE
Combustion in boilers
Bark/Sawdust Boiler
Wood Bark/Sawdust Boiler
Bagasse Boiler
Municipal Garbage Boiler
Off-Highway Diesel Internal Combustion
Automobile Spray Booth
Carbon Black Oil Furnace of Gas Boiler
Soap and Detergents Spray Dryer
Sodium Carbonate*
Calciner
Trona Dryer
Dryer
Rotary Predryer
Bleacher Dryer
Cotton Ginning
Lint Cleaner Air Exhaust
Bactery Condenser
Saw Gin - Gin Stand and Bale Press
Roller Gin - Gin Stand and Bale Press
Feed and Grain Mills and Elevators
Grain Unloading
Grain Elevators
Agricultural Feed Production
Ammonium Sulfate Fertilizer Bed Dryer
Ca^ob Kibble Dryer
Cereal Dryer
Rice Dryer
Bauxite Processing
Ship Unloading
Fine Ore Storage Bin
Secondary Aluminum
Reverberatory Furnace Exhaust
Chlorine Demagging
Steel Foundries
Open Hearth Exhaust
Shakeout Hood Duct Exhaust
*AP-A2 Sections being updated.
151
-------
TABLE III (CONTINUED). ADDITIONAL SOURCE CATEGORIES FOR WHICH SOME
PARTICLE SIZE DATA AND EMISSION FACTORS ARE AVAILABLE
Lead Battery Manufacture
Grid Casting and Small Parts
Casting Pot
Paste Mixing
Lead Oxide Mill
Element Assembly Operations
Assembly and Ball Mill Processes
Reclamation Furnace
Bricks and Related Clay Products*
Screening and Grinding
Tunnel Kiln Exhaust
Sawdust Firing Brick Kiln
Coal Cleaning
Air Table
Thermal Dryer
Glass Manufacturing*
Furnace Exhaust
Glass Fiber Manufacturing
Flame Attenuation Forming Line
Exhaust
Phosphate Rock Processing
Calcining
Grinding - Ballmill
Oil Fired Rotary Dryer
Oil Fired Rotary and Fluidized Bed
Rock Dryer
Taconite Ore Processing*
Main Waste Gas Stream
Fluorospar Processing
Rotary Drum Dryer
Petroleum Refining
Gas fired Boiler
Gasoline Cracking - CO Boiler Exhaust
Gas Fired Process Heater
Wood Products Industry
Sanding and Sawmills
Belt Sander Hood Exhaust
*AP-42 Sections being updated.
152
-------
FIELD MEASUREMENTS STUDIES FOR THE DEVELOPMENT
OF POINT SOURCE EMISSION FACTORS
J.M. Ekmann
DOE PTPA No. 5-083
DOE Project Officer:
Edward Trexler
Fossil Energy
U.S. Department of Energy
Presented at:
Second Annual Acirf Deposition Emission Inventory Symposium
Charleston, SC
November 12-1H. 1985
153
-------
FIELD MEASUREMENTS STUDIES FOR THE DEVELOPMENT
OF POINT SOURCE EMISSION FACTORS
INTRODUCTION
The models ander development for prediction of acid deposition require
detailed emission data on a number of chemical species. These compounds or
elements may act as direct acidic emissions to the atmosphere or may be
involved in reactions that produce or eliminate acidic species. Many of the
species in question are non-criteria pollutants, and limited information is
available concerning emission factors for them. Furthermore, emission data
have been requested at levels of temporal and spatial resolution not
generally available. A number of projects have been developed to address
the need for such data, including literature studies and field tests. This
project largely focuses on a series of actual measurements for two
particular categories: sulfate emissions from residential and commercial
combustion of fuel oil; and emission of chlorine species from coal
combustion.
Projects aimed at developing emissions data from literature sources
identified gaps in available test data for several categories.1' In the
area of sulfate emissions, data on sulfates emitted from the residential and
commercial combustion of fuel oil were either absent or based on analytical
approaches that have been superseded by more reliable techniques. Data on
chlorine emissions from combustion of coal were judged unreliable. It was
felt that new measurements should be made employing recent advances in
analytical techniques.
TECHNICAL APPROACH
As the emission Inventory requirements include spatial and temporal
resolution and some measures of addressing uncertainty in the data, a multi-
task project was initiated. These tasks include the following:
o Ttsts for sulfate emissions from two boilers at the Pittsburgh Energy
Technology Center (PETC)
o Tests for sulfate emissions at sites external to PETC that are typical
of residential and commercial combustion of No. 6 oil
o A literature search and data-base development leading to information on
the state or regional distribution of vanadium and nickel in residual
fuel oils and the possible impact of these on sulfate emissions
o Tests for chlorine and, incidentally, for fluorine emissions from coal
combustion based on the use of a furnace simulator at the Pittsburgh
Energy Technology Center (PETC)
o A literature search to develop information on the chlorine content of
U.S. coals, and calculation of the equilibrium distribution of chlorine
species in flue gas
The sulfate tests at PETC were conducted in two package boilers; a 20-
hp fire-tube boiler (700 Ib/hr of steam) and a 7CO-hp watertube boiler
154
-------
(24,000 Ib/hr of steam). These boilers are typical of those package boilers
widely used for raising steam in commercial and residential applications.
Tests were conducted in the 700-hp facility for high-sulfur No. 6 oils at
two excess air levels. Data are reported for four tests in the 20-hp boiler
on both No. 2 and No. 6 oil. For the No. 6 oil test, two different excess
air levels were studied. All tests were conducted at full load. Samples
were drawn using a controlled condensation sampling (CCS) train; analysis of
the samples was performed using ion chromatography, with occasional
duplicate analyses performed via barium-thorin titration.
Field tests were conducted, through a subcontract to Roy Weston, Inc.,
at three sites: a residential site with a boiler rated at 1^5 RBtu/hr; a
commercial site with a unit rated at 98 RBtu/hr; and a light industrial
facility with a boiler rated at 63 RBtu/hr. Triplicate samples using the
CCS method were taken at all locations, and supporting tests using a
modified EPA reference method 8 were performed at the commercial site.
Studies nave shown that the trace metal content of fuel oils,
particularly vanadium, can affect the conversion of sulfur species to SO3. 3
As extensive data to quantify this dependence are absent, a literatur'
search was made, through a contract with Radian, to develop data on the
current and past emissions of vanadium and nickel from combustion sources.
These data were used to project sulfate emissions as a function of the
variations in vanadium content and fuel use; for one state, these
projections were compared, to the sulfate emissions calculated from the best
currently available emission factors. It was hoped that this information
would contribute to uncertainty estimates in this area.
Chlorine emission tests were conducted in a coal-fir 3d furnace simu-
lator having a firing rate of 500 Ib/hr of coal. These tests were piggy-
backed into a series of tests examining spray dryer/E?P performance in this
unit. A sampling train was used that allowed us to collect all chlorine and
fluorine species. The train consisted of a glass-lined probe inserted into
the stack, a quartz fiber particulate filter, and an impinger train. The
solutions in the impinger varied with the test method chosen; both the "LA"
method and a method proposed by GCA were used. "* > 5 Samples were analyzed
using ion chromatography. Additional samples vere obtained or samples were
split where appropriate and analyzed using the Volhard technique.1*
Finally, data in the literature indicate that although the chlorine
content of United States, coal is low, the actual chlorine content can vary
substantially within a given seam. For commercially significant coals in
the United States data regarding the chlorine content and its variation were
collected from a number of literature sources. In addition, multiphase
equilibrium calculations have been performed to provide a basis for com-
parison with the experimental data.
RESULTS
Table 1 presents the amount of total sulfur converted to sulfates for
the tests at PETC. Levels of conversion are typical of equilibrium levels
at high temperature with the exceptions of test PS-06. This test was run
after 30 hours of operation on No. 6 fuel oil without cleaning the inside of
the boiler except for the fire tube itself. Operator comments indicated
that the gas passes did have ash deposits in them. With the exception of
PS-06, no evidence of conversion due to catalysis by Vz^s was found;
155
-------
however, boiler surfaces were generally clean at the start of each of these
tests.
TABLE 1. Test Results from Sulfate Runs
Test
PS04
PS05A
PS05B
PS06
PS07
PS08
Fuel/?02
0.3?S,No.6F.O./2.2?
0. 35?S, No. 6F.O./2.0?
0.35?S,No.6F.O./3.1?
0.35$S,No.6F.O./3.3?
1.4556S, No. 6F.O./2.0?
1.1*3, No. 6F.O./3.0*
Sulfate
% Total Sulfur
1.4
2.1
2-1
8.4
1.2
1.8
V/Ni (ppm)a Boiler
1.4/0.1
6.4/8.6
6.4/8.6
6.4/8.6
94/22.8
64/12
a Vanadium and Nickel content of fuel oil (ppm)
20 hp
20 hp
20 hp
20 hp
700 hp
700 hp
A field test program was initiated after reviewing these results.
Objectives of the activity were to test typical units, preferably units that
had some degree of deposit buildup inside the furnace that might be charac-
teristic of the normal condition of residential and commercial units. In
addition, it was planned to conduct tests at one site that had been pre-
viously studied and to compare the total measured sulfate from the CCS train
to that found by a modified Method 8 train. Table 2 presents data regarding
the facilities and operating conditions.
Site
( — )
TABLE 2. Site Information for Field Sulfate Runs
Type Rating Capacity Factor Excess Air % S in
(---) (MM Btu/hr) (% of Full load) (*) No. 6 Oil
Starrett City Residential 145.0
98.0
63.0
Philadelphia Commercial
State Hospital
Wyeth Light
Laboratories Industrial
50
21
75
40
170
25
0.3
0.5
1.0
The field tests were conducted in the spring and summer, accounting for
the low load factors at the residential and commercial sites and accounting
for the high excess air at the commercial site. The residential boiler had
been cleaned immediately before to the start of testing; the boiler at the
commercial site had fired fuel oil for 72 hours before the testing; the
industrial boiler had not been cleaned in the recent past. Table 3 provides
a summary of the results.
156
-------
TABLE 3. Test Results from Field Tests
Site Method V/Nia % S from Fuel as Primary Sulfate
Starrett City CCS^ 1U.9/16.1 1.5? (37? as acid)
Philadelphia
State Hospital CCS 15.5/30.8 0.95? (46? as acid)
Philadelphia
State Hospital IPAC 15.5/30.8 1.5?
Wyeth
Laboratories CCS 15.1/27.5 3.8? (82? as acid)
a Vanadium and Nickel (ppm)
b Controlled Condensation Sampling Train
G Modified EPA Reference Method 8
These data that the conversion to sulfate was 2.0? or less for the lower
load tests with boilers that had been cleaned recently. Only for the Wyeth
Laboratories test was a higher sulfate conversion noted, and all of this
increase appeared as acid. In addition, the results from the modified
Method 8 test were consistently higher than from the tests using the CCS
train.6
Some results from the vanadium data base are shown in Figure 1. Calcu-
lated emissions are shown by state for the years 1950 and 1980. Only Ohio,
Oregon, Pennsylvania, and Rhode Island have shown a decrease. Otner states
that now have reasonably large emissions have shown a significant increase
over the 1950 numbers. Among these are Alabama (4-fold), Delaware (7-fold),
Florida (6-fold), Louisiana (18-fold), Mississippi (88-fold), and North
Carolina (9-fold). Each of these six states emits over 100,000 kilograms of
vanadium per year (1980) and each has sho^n more than a 400? increase in
such emissions since 1950.7
Results of the chlorine and fluorine tests have been reduced to the
form of emission factors, and are presented in Table 4 as pounds per million
Btu per percent of the element in the fuel. The values calculated from the
emission tests in the stack are in reasonably good agreement with the
quantities of each element that entered in the fuel. Furthermore, the
results indicate that essentially all the chlorine and fluorine are present
as HC1 and HF.
Equilibrium calculations were performed using a multiphase equilibrium
program available at PETC. These calculations predict that HC1 would be the
dominant gas phase species (by over two orders of magnitude) at the tempera-
tures of interest. These calculations agree with earlier studies.8' >
157
-------
TABLE 4. Calculated Emission Factors
Calculated Emission Factors
Element
(X) lb/(flBtu)a Ib/CflBtu x ?X)a
a
b
Cl 4.4 x 10-2 0.69
F 4.4 x 10-3 0.87
Calculated From Emission Tests
Calculated Fron Fuel Compositions and Feed Rate
lb/(flBtu x ?X)b
0.76
0.71
CONCLUSIONS
In general, the results of all the sulfate tests indicate low conver-
sions of sulfur to primary sulfate. However for two tests, where the boiler
may have contained significant deposits, higher conversions were noted.
Data have been developed for a rang? of unit sizes, operating conditions,
and fuel properties.
Chlorine and fluorine emissions follow the concentration of these
elements in the fuel; HC1 and HF are the dominant gas-phase species.
158
-------
References
1. D. Misenheimer, R. Sommer, H.R. Glowers, and A.S. Werner, "Assessment
of Ammonia, Hydrogen Chloride, Hydrogen Fluoride Emission Factors for
the NAPAP Emission Inventory," CCA Corporation EPA Contract No. 68-02-
3168, TASK No. 90, Revised Draft Final Report, March 1985.
2. J. Hornolya, "Primary Sulfate Emission Factors for the NAPAP Emissions
Inventory," Radian Corporation, EPA Contract No. 68-02-399^, Task No.
5, Revised Draft Final Report, July 1985.
3- Workshop Proceedings on Primary Sulfate Emissions from Combustion
Source, Volume 2, U.S. Environmental Protection Agency, NTIS PB-287
1436, August 1978.
^. J. Driscoll, Flue Gas Monitoring Techniques, Ann Arbor Science
Publishers, Inc., Ann Arbor, Mich.
5. D.A. Stern, B.M. Myatt, J.F. Lachowski, and K.T. McGregor, "Speciation
of Halogen and Hydrogen Halide Compounds in Gaseous Emissions,"
presented at the Ninth Annual Research Symposium, Land Disposal,
Incineration, and Treatment of Hazardous Waste, Ft. Mitchell, Ky. ,
(May, 1983).
6. "Characterization of Primary Sulfate Emission from a Residential and a
Commercial Boiler Firing No. 6 Fuel Oil," draft final report by
Ray F. Weston under Subtask 7.9, U.S. DOE Contract DE-AC-22-8^PC75571
(August 1985).
7. S. Kulkarni, C. Arnold, J. Homolya, and J. Dickermann, "Vanadium Nickel
and Primary Sulfate Emissions From the Combustion of Fossil Fuels in
the United States of America," draft final report by Radian Corporation
under U.S.DOE Contract No. DE-AC-8HPC71505 (August 1985).
°. T.L. Tapalucci, R.J. Demski, and D. Bienstock, "Chlorine in Coal
Combustion," U.S. Department of the Interior RI7260 (May 1969).
9. M.J. Hodges, W.R. Ladner, and T.G. Martin, "Chlorine in Coal: A Review
of Its Origin and Mode of Occurrence," Journal of the Institute of
Energy, pp. 158-169 (September 1983).
10. W.D. Halstead and E. Raask, "The Behavior of Sulphur and Chlorine
Compounds in Pulverized-Coal-Fired Boilers," Journal of the Institute
of Fuel, pp. 3^-3^9 (September 1969).
159
-------
Figure 1. Computed Vanadium Distribution
For 1950 and 1980
\ANADIfM EMIcsIGN DENSITi LTi .-TATt;
V._-
LEOENC
C!
25'
\ANADICM EMISSION DENSITY BY cflA
•'—*£:- --4 \ "r*" c
' '•-. J"1" ^' I- < . -*z^ i—
^^Lrf} ^
LEGEND
o C;
10
0. I
25
160
-------
VOC COMPOSITION OF AUTOMOTIVE EXHAUST
AND SOLVENT USE IN EUROPE
C. Veldt
TNO
(Netherlands Organization for Applied
Scientific Research)
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
161
-------
VOC COMPOSITION OF AUTOMOTIVE EXHAUST
AND SOLVENT USE IN EUROPE
by: C. Veldt
TNO
(Netherlands Organization for
Applied Scientific Research)
ABSTRACT
Compositions of automotive exhaust hydrocarbons and aldehydes are
presented at a level of detail relevant for input into photochemical air
pollution and acid deposition models. Data were compiled from literature
for gasoline-, diesel- and LPG-powered vehicles without exhaust controls.
For gasoline-derived compositions, data were converted to separate profile?
for saturates, unsaturates and aromates. Relations between gasoline
composition and exhaust composition were used to combine the average profile
compositions to one average overall composition. A comparison with fuels
measurements was made.
An attempt has also been made to estimate an average solvent
consumption resp. emission pattern for Western European countries. Since
data appeared to be very scarce, all available material both inside Europe
and abroad was used for a first approximation. An average mass rate per
capita and an average composition is proposed. Spatial distribution
criteria are suggested. The results should be used as default values
anticipating more reliable data.
162
-------
VOC COMPOSITION OF AUTOMOTIVE EXHAUST
AND SOLVENT USE IN EUROPE
INTRODUCTION
The two largest contributors to total anthropogenic VOC emissions in
most European countries are non-catalyst automobiles and the evaporation of
solvents (ca. 50 percent and ca. 35 percent of total VOC emissions
respectively). For the purpose of modeling photochemical air pollution and
acid deposition, it is necessary to know the composition of these pollutants
as detailed as relevant. Modeling large areas in Europe implies the
possibility that nationally different emission factors have to be used.
While differences in vehicle fleets as well as driving habits can reasonably
be taken into account in estimating mass emissions, their influences on
composition are not known. When solvent emissions have to be assessed,
considerably larger problems must be faced as both mass emission rates and
compositions are sufficiently known for only a few countries.
The need of widely applicable emission factors being apparent, an
attempt has been made and is presented in this paper to quantify:
a. exhaust hydrocarbon composition from gasoline-powered vehicles
with only fuel composition as a variable,
b. exhaust hydrocarbon compositions of diesel- and LPG-powered
vehicles,
c. an average per capita mass emission factor fir solvent use,
d. an average composition of solvent emissions
and, finally, to draw up spatial distribution criteria for solvent emissions.
DISCUSSION
1. Exhaust Emissions
For gasoline-powered vehicles, the literature was searched for test
data satisfying the following demands: a) test vehicle(s) without exhaust
control, b) VOC-analysis comprising at least main components, c) complete
163
-------
(or nearly complete) mass balance. Eleven investigations answered these
demands (Table 1).
All data were converted to percent by weight to facilitate combination
with mass emission factors. As could be expected, averaging absolute
fractions was not of much use. Therefore, composition profiles were
calculated for saturates, unsaturates and aromates. These resulted in
applicable averages (Tables 2a and 2b).
Next the profiles had to be integrated to one average composition.
Only for aromates a useful correlation between fuel- and exhaust composition
appeared to exist (Figure 1). It has been shown, however (12, 13), that
there is a relation between fuel aromates and exhaust olefines (Figure 2).
With this, exhaust composition can be estimated by the aromatic content of
the fuel (Figure 3). Finally, a correction for oxygenates is needed.
Oxygenate content and composition, as well as diesel- and LPG-exhaust
composition were estimated from literature data satisfying the same
above-mentioned demands (Tables 3-5). In contrast with gasoline-exhaust
composition, useful material was scarce; for diesel fuel only six more or
less incomplete data sets were found, for LPG only two (20, 22).
Since only one report about field measurements was found that could be
used as a comparison (21), an average road traffic exhaust composition was
calculated for that purpose (Netherlands, 1978; Table 6). In this table, a
comparison based on a reactivity scheme has been added because this is what
ultimately is of interest.
2. Solvent Emissions
Assuming that a society's solvent consumption, with respect both to
quantity and substances used, depends on the level of industrialization and
material development, it can be expected that comparable emission patterns
exist in several European countries. This was checked by collecting as much
data as possible about solvent emissions from different countries and taking
averages wherever it made sense (Tables 7 and 8). Due to divergencies among
data and uncertainties about representativeness the results should be
characterized as default values only. Another approach, in progress now, is
the assessment of mass balances to which solvent consumption factors are
applied. It is not certain yet whether this will give more reliable
results.
164
-------
The geographic distribution of solvent emissions is complex because a
comprehensive source type-substance matrix is involved. In view, however,
of the very large number of small sources and the relatively few large ones
it seems justifiable to distribute all emissions proportional to population
density and make corrections for large area sources afterwards. This
approach is valid only for meso- and macro-scale modeling.
CONCLUSIONS
An average composition of road traffic exhaust (dominated by gasoline
powered vehicles), based on a literature survey comprising old as well as
recent investigations, has a variation that is considered appropriate for
air pollution modeling. Taking into account the scarce data about the
influence of vehicle speed, vehicle age and ambient temperature on
composition, indicating that these influences cause no larger variations
than those presented in this study, it seems reasonable to assume that no
better input data can be expected to be available for modeling than these.
The quality of emission factors for solvent use can not easily be
estimated since there is insufficient knowledge about the reliability of
individual national data. Analysis of national mass balances may possibly
improve the factors.
165
-------
LITERATURE
1. J.D. Caplan, SAE Progr Tech. Ser. 12 (1967) 20-31.
2. M.W. Jackson, ibid, 241-67.
3. I.D. Lytollis, MIRA Report Nr. 1971/1 (1970).
4. W.E. Morris, K.T. Dishart, ASTM STP 487 (1971) 63-101.
5. K. Schofield, Env. Sci. and Tech. 8, 9 (1974) 826-3*.
6. L.J. Papa, 'SAE Progr. Tech. Ser. H (1971) 43-65.
7. B. Dimitriaderl et aJL, Bur. of Mines Rep. of Inv. 7700 (1972).
8. S. Yanagihara, Proc. 16th FISITA-Congress, Tokyo 1976, 2-149-56.
9. P.M. Black, I.E. High, EPA-600/2-80-085 (PB 203136), JAPCA 30, 11
(1980) 1216-21.
10. P.P. Nelson, S.M. Quigly, Atm. Env. 18, 1 (1984) 79-87.
11. R. Steenlage, R.C. Rijkeboer, MT-TNO Rep. Nr. G 1115 (1985).
12. E.E. Wigg, et al.. SAE-Paper 720251 (1972).
1J. K. Hosaka, et al.. SAE Tech. Paper Ser. 780625 (1?78).
14. P.M. Carey, EPA-AA-CTAB-PA-81-11 (PB 82-118159) (1981). (a) 4 LDV's
(1970); FTP; DNPH. (b) 10 LDV's (1970-1973); FTP; DNPH. (c) AMC Pacer
(1977); FTP; DNPH (average value of five types of malfunction).
15. See 12. 1970 repr. test vehicle; FTP; MBTH (total), DNPH (ind.)
16. P.E. Oberdorfer, SAE Progr. Tech. Ser. 14, 32-40 (1971).
17. C.S. Wodkowski, et al.. West Coast APCA Mtg., San Francisco 1970 (cit.
from Vapor-Phase Organic Pollutants, EPA 600/1-75-005, PB 249357);
a = 30 mph, b = FTP).
18. M.F. Fracchia, et iL, Env. Sci. and Tech. I, 11 (1967) 915-22.
19. Nat'l Res. Council, EPA 600/6-82-002 (PB 82-180498); a = idle, b = FTP.
20. R. Steenlage, R.C. Rijkeboer, MT-TNO Rep. Nr. G 1115 (1985) (Dutch.
Org. for Appl. Sci. Res.); Opel Ascona 1.6 S (1983), EEC-cycle, MBTH;
a = optimal, b = rich.
166
-------
21. R. Guicherit, Th.R. Thijsse, IMG-TNO Rep. Nr. G 1198 (1982).
22. K.E. Egeback, et al.. Nat'l Swedish Environ. Protect Board Rep.
Nr. 1635 (1983).
23. Umweltbundesamt Berlin.
24. CITEPA, Paris.
25. K.A. Brice, R.G. Derwent, Atm. Env. 12 (1978) 2045-54.
26. Project Emission Registration, Min. of Housing, Physical Planning and
Environment (Netherlands).
27. Swedish Environ. Res. Inst., Stockholm.
28. EPA, Office of Air Quality Planning and Standards.
29. Environ. Protect. Progr. Dir., Report EPA 3-EP-83-10 (1983).
30. Photochemical Smog, OECD, Paris 1982.
31. R. Schaaf, Wasser, Luft and Betrieb, 1984-3, 36-8.
32. C. Morley, Shell Res. Ltd., Thornton Res. Centre, England; paper for
submission to Atmospheric Environment (1981).
33. P.F- Nelson, et al_, Atm. Env. 17, 3 (1983) 439-49.
167
-------
60
40 r
.c
X
HI
c 40
20
20 40 -60
Wt.Z aromates in fuel
Fig. 1
.c
x
r=0.53
• (this work)
v r=0.94
(Wigg et al)
20 40 60
Wf.Z aromates in fuel
Fig.2
100
80
60
u 40
20
saturates
aromates
20 40 60
Wt.% aromates in fuel
Fig.3
168
-------
Table 1
Investigations of automotive exhaust; gasoline powered vehicles; experi-
mental data.
Lit.
nr .
1
2
3
4
5
6
7
8
9
10
11
Test vehicle(s)
no data
0.63 1 single cyl .
motor; compression
ratio = 8.9/1
1 of A cyl . of 1 .3 1
motor; compression
ratio = 8.5/1
Automobile without
control system
No data; "represen-
tative composition"
"62 privately owned
and operated automo-
biles" Composition of
one of these is given.
1969 Valiant; 3.8 1
"pre-emission control-
led car with retrofit
device of retarding
ignition timing"
1963 Chevrolet 283 V8
67 automobiles repre-
sentative for Sydney
fleet. Ages: < ' 72 -
> '78. Weighed average
composition given.
Test
procedure
Calif, cycle
7-mode Calif.
cycle. Each
fuel : rich,
resp. lean;
with, resp.
without vacuum
spark advance
Hot 10-mode,
6 cycles
FTP
1975 FTP
Opel Ascona 1.6 S (1983) EEC-cycle,
rich and opti-
mal ;
90 km/h opt.
120 km/h opt.
Gasoline
composition (wt.%)
sat. unsat. arom.
55 10 35
46 16 38
59 10 31
a) t i.5 H.5 22
b) 5? 10 33
c) 48 2 50
a) 51 b 4j
b) 71 i: 17
0 C2 12 26
d) 59.5 0.6- 40
e) 41 19 40
f) 40 12 48
g) 33 11 5t>
69 5 Jb
63.5 6 30.5
Approx. ye
of invest!
1967
1967
1970
1968
1971
1970
1971
1975
197?
198(
198
169
-------
Table 2.
Investigations of automotive exhaust; gasoline powered vehitles. Hydrocarbon aualyses
Hydroca rbon
methane
propane
butanes
pentanes
hexanes
heptanes
octanes
C > 9 saturates
wt . X aba .
et Ly lene
acetylene
propy !ene
propad i cne
methyl acetylene
1 -butenes
I ,3-butadiene
\ -pentenes
2-pentenes
1 -hexenes
C > 7 unsaturates
wt. X abs
a roma 1 1 c
benzene
toluene
xy I enes
ethylbenzene
st y**ne
1 ,2,4-1 rime thy) benzene
1,3,'i-triinrthyl benzene
} , 2, 3-tri me thy! benzene
other Cg-« mmates
C > 10 aromales
wt. X abs
3 naphLa 1 cne
1 2 3
22.0 16 0 20. 1 1
4.7 5.1 12.0 1
13.3 14.9 19.8 1
94 12.4 17.4 1
7.5 9.4 13.5 1
40 3 35.9 10.5 .
2.2 2.0 ''
30.8 27.8 21.2 4
21.5 18.3 33.6 2
15 9 13.1 24.5 1
12.6 15.8 13.1 1
2-6 b &
1.8 1
Il2 5 )l6 0 >8 5 '
1 ' 1 I ' )
3.1 3.5 3.7
7.0 6.9 4.6 2
4.7 4.2 1.4
14.6 12.2 1.5
32.0 33.7 40 6 3
8.2 7.2 11.3 1
47.2 46.7 20.1 3
11.2 11.0 23.2 2;
3.0 3.5 5.4
7.8V 9.8 f
1.2 1.5 2.9 I
29.2J 8.6 12.0 I18
13.7 14.0 '
37.2 38.5 36.2 2(
456
2 8 23.7 19 1
D.3 11.0
f>.0 14.0
). 1 16.3
1.4 12 3
20 8
3 4.8
2.8 34 5 44.4
9." 22.4 25.5
96 25.8 35. 7
S. 5 175 11.8
2.3 0.5
1 0
3.6 12 g 5.7
3.6
.4 7 9
1 2
1 .5
).3 37.1 24.9
.0 12.5 8 1
.5 40 8 20.8
.5 14.0 21 4
.5 ' 4.0 4.3
.5 8.1
2 5
H5
22.2
.9 28 4 30 7
7
a b c
14 8 12 9 15.7
5.7 6.0 11.6
12.7 16.9 13.7
24.8 19.5 11.9
14.7 10.4 11 .6
10.7 9.3 21 .4
15 0 23.6 12.6
40 3 15.0 28.0
29.1 24 6 22.8
22.4 214 27.8
113 10 4 15.4
0.7 0.5 1.0
1.2 1.3 2.1
4.2 3.5 6.4
28 2.5 16
2.8 4.2 2.5
4.2 5.9 5 '1
3.6 2.9 4 2
12.2 15.7 6. 1
30.2 25.3 IB.O
5 7 2.6 2.9
14 5 10.0 14. 7
18 5 19 6 25 7
1.6 35 5.8
1.3 0.9 0.9
98 96 75
23 1.9 1.5
}ll 4 }|1.9 JI0.6
12.9 40.0 10.4
21 5 19 7 54 0
8
a h c d p f g
14.6 22.9 22 4 28.0 40.3 28.6 31 . 1
0.2 0.3 0.4 0.5 03 0.4 05
3.7 4.6 3.9 2.6 4.7 4.1 2.7
22 7 10.7 116 151 18.2 18.4 19.6
35.4 15.0 18.5 22 8 19.8 27.6 26.2
8.7103 62 74 68 9.5 10.0
10.2 34.1 10.3 20.8 51 6.4 6.3
4.5 2.1 4.7 2.8 48 5.0 36
41.7 58.8 56 8 53.4 50 6 42.1 17 4
33.2 30.7 32.9 39.1 31 9 36.2 J9.0
24 9 25.4 28.1 24,1 23 8 39.7 29 4
13.1 23 5 158 13.8 16.7 8.9 11.6
3.7 4.0 3.7 3.7 41 3.1 2.6
5.1 3.4 3.7 1.6 3.3 1.4 2.3
10.3 4.0 4.4 3.8 7.6 2.1 3.0
3.5 1.3 2.0 40 1.6 2.1 2.6
3.6 4.1 6.5 2.3 3.6 5.0
15.5 24.6 20.4 14.1 22.6 19.9 13.9
14.9 14.7 15.0 12.3 162 14.8 46.2
32.0 2C.3 27.3 32 3 31.1 16 2 21.5
23.7 23.5 24.0 22.2 24 4 24.3 15.8
5.4 6.3 5.8 6.1 65 71 4.1
5.4 5.6 4.5 4.4 24 3.6 2.7
2.2 2.5 1.3 18 10 0.7
3.9 15 2.0 10 1.1 1.5
6.4 86 6.8 7.0 51 6.7 1.8
6.1 11.0 146 144 111 5.2 1.7
42 >• 16 6 22 fl 32.5 26.6 38 0 48 ?
93) 10" 11
28. S U 8 217
0.2 0.3
10.7 7.7 6.1
9.0 211 25 2
14.8 22.0 2 0
9.7 117 97
16.7 10 1 272
5.2 9.6 3.5
37.3 38 8 270
34.4 31.2 28 2
24.6 27.5 42 4
14.8 13.6 11 9
0.8 1 3
1.9 1.2
6.4 6.2 12.2
4.3 1 1
6.0 1.5
2.0 3.4
1.4 ,
0.2 1
40.3 29.5 25. ,
17.6 14 0 10 1
22.7 29.2 23
-------
Table 2b
Investigations of automotive exhaust; gasoline powered vehicles
Average values (wt. %)
Hydrocarbon
saturated
methane
ethane
propane
butanes
pentanes
hexanes
heptanes
octanes
C9 + saturates
C. + saturates
4
unsaturated
ethylene
acetylene
propylene
propadiene
methyl acetylene
1-butenes
1 ,3-butadiene
1-pentenes
2-pentenes
1-hexenes
2- and 3-b.exenes
C unsaturates
aromatic
benzene
toluene
xylenes
ethylbenzene
styrene
1 , 2, 4- 1 rime. -benzene
1 ,3,5-trime .-benzene
1 ,2 ,3-trime . -benzene
other C9 aroraates
C . aromates
average
21
3
0
6
16
18
10
18
6
101
76
29
26
14
1
1
5
2
3
5
2
2
6
100
12
28
23
5
6
2
1
7
14
102
6 ±
1 ±
3 ±
5 ±
4 ±
6 ±
2 ±
6 t
2 ±
5
7 ±
7 ±
1 ±
3 ±
2 ±
6 ±
3 ±
5 ±
2 ±
1 ±
7 ±
6 ±
4 ±
9
9 ±
9 ±
1 ±
8 ±
6 ±
0 ±
6 ±
6 ±
0 ±
6
7.3
1.3
0.1
3.2
4.2
7.5
2.4
11.4
5.9
7.3
5.9
7.2
3.3
0.8
0.5
2.8
1.2
1.2
2.3
1 .2
1.0
5.2
9.1
9.9
6.8
2.1
2.8
0.9
1.0
2.3
10.5
34
44
33
49
26
41
23
6!
95
9
20
28
23
67
31
52
47
39
45
46
41
81
71
34
29
37
42
44
61
30
75
average
(excl. 2o)
%o
20
3
0
6
15
18
10
18
5
99
77
29
25
13
1
1
4
2
3
4
2
2
6
100
11
28
22
5
1
6
1
1
7
12
98
5
1
3
5
9
6
2
6
5
2
6
7
2
S
2
6
9
5
0
8
7
6
4
9
1
9
5
3
6
8
3
6
1
3
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
±
+
+
+
+
+
5.9
1.3
0. 1
3.2
3.7
5.2
2.4
11.4
3.9
6.1
5.9
6.2
2.5
0.8
0.5
2. 1
1.2
1.0
1.9
1.2
1.0
5.2
4.5
9.9
6.1
1.6
2.8
0.7
0.4
2.3
7.9
29
44
33
49
23
28
23
61
70
8
20
25
18
67
31
43
47
34
40
46
41
81
40
34
27
30
42
36
32
30
65
a
18
12
9
18
17
16
18
18
15
17
19
18
18
8
7
14
5
15
15
15
15
14
18
19
19
19
4
15
14
7
11
15
adoptf
averaj
19
3
0.
77
100
29
25
14
6
2
j
I
\
\
I
10i
2
2
1
1
171
-------
Table 3
Oxygenates in automotive exhaust; gasoline-po;vered vehicles (wt. X)
Component
i
forma 1 defiyde
aceta 1 dehyde
acetone
propiona Idehyde
aero 1 e'l n
buty la] dehydea
hexana 1 dehyde
benzi Idehyde
tolualdehyde
other aldehydea
total oxygenates
14 IS 16 17 18 19 20
abc at atab
86 74.2 48.7 48 5 .16 9 42 0 53 0 53.9 49.3 50.0 46.0
13.5 19.6 9.3 7 3 12 9 67 91 92 13.4
5.2 ... , 0.5 8.2 0.8 3 0 9.0 23.0
|22 . 2
1 12.7 3.0 8 7
1 0.7 4.4 1.5 30 3.0 2.0
1.2
12.4 20.8 7.2 11.6 H.I 11.2 10.2
12.3 14.5 7.5
0.9 9.5 15.9 26.9 12.1 13.7 2.1
2.0 5.8 1.9 2.31.6
average
(exc 1 . 2o) %o
50.3 t ').fl 20
11.2*40 36
4.5(0.5-9)
8. 1(3-12.7)
2.4*1.3 54
12 1 » 4 2 35
11 .4(7.5-14.51
2.7*1.7 64
adopted
average
50
10
5
10
10
15
2
Se> 1 ist of references tor experimental data
Table 4
Compos i t ion of dlese 1 exhaust
Compos iti on of I.PG-exhaus I
Component
methane
ethane
sat tirates C— -
'•I hy I rut-
ac ety 1 ene
propy lene
1 -butenea
penteneg
benzene
aronales Cr-r
formaldehyde
aliph. aldehydes C-
unsat. aldehydes C-
acetone
organic acids C =
a
3
0
SO
1 1
3
3
1
0
2
2
8
5
4
0
2
1
vera
.7 1
.5
.0 !
.2 i
.4 »
5 *
.7
6 1
.9 i
.5
(0.
"
1 .5
1.4
1.6
i .n
0 5
i i
2 5
6-3.6)
adopted
average
4
0.5
50
11
3 !
3.5
1 5
0.5
2
2.5
8
'6
4
0.5
2
1
Component
met hane
ethane
p ropane
ethyl em-
acet y 1 ene
propy lene
benzene
to 1 urne
aylenes
forma 1 dehyde
ac^Laldehyde
organic acids
average
8
2
34
15
21
7
0
0
1
3
0
1
.9
.7
.5
.6
,8
.6
(1.
• 0
* 6
* 4
* 5
1 2
. 15(0
.3
.5
.4
.6
.7
(0
(0.
* 1
1 1
3-16.4)
8
0
9
.7
. 1
03-0.4)
06-0.5)
OI.-3.5)
.5
.0
adopted
average
9
3
35
15
22
8
1
4
1
1
5
5
-------
Table 6
Road traffic exhaust composition (ut. % and mole/kg )
methane
ethane
propane
€,-€,„ saturates
ti 10
C saturates
etnylene
acetylene
propylene
propadiene
methyl acetylene
1 -butenes
1 ,3-butadiene
2-butenes
1-pentenes
2-pentenes
1-hexenes
2- and 3-hexenes
C.+ unsaturates
benzene
toluene
xylenes
ethylbenzene
styrene
1 , 2, 4- 1 rime . -benzene
1 ,2,5-trime . -benzene
1 , 2, 3- 1 rime . -benzene
other Cg-aromates
C,. aromates
10+
formaldehyde
other oxygenates
OLE
PAR
TOL
m
FORM
ALD
ETH
UHR
calculated
8.0
1.3
1.2
29.8
5.5
7.9
6.3
3.6
0.2
0.3
1.4
0.5
0.5
0.7
0.9
0.5
0.5
1.5
3.:
7.2
5.7
1.2
0.3
1.6
0.5
0.4
2.0
3.9
1.6
1.8
1.4
32.7
0.9
1.2
1.5
0.6
2.8
11.1
measured
(21)
7.2
0.6
0.6
32.3
2.2
6.6
4.8
2.6
1 .0
0.4
1.2
1.3
2. 4
0.7
3.9
9.9
6.4
2.3
0.8
2.3
1.3
0.6
2.8
3.7
1. 1
1.0
1.1
31.1
1.3
1.4
0.7
1.0
2.4
10.0
!7
2)
30% aromates in gasoline, gasoline exhaust: 86%, diesel exhaust:
LPC exhaust 3% (Dutch 1978 average).
Chemical bond species (CBM-X, SAI)
11%,
173
-------
Table 7
VOC-emissions from solvent use
(kg/cap. year)
INDUSTRIAL
paiut application
degreasing
printing
chemical industry
storage & handling
metal products manuf.
glues, adhesives
other
total from industry
NON- INDUSTRIAL
paint application
chemical cleaning
consumer products
- a.w. aerosol cans
total non-industrial
total emissions
total paint appli-
cation
OECD-estimation 1975
1985
23 24
FRG France
1978-'80 1979
3.25
2.31} 1.65
1.15 0.65
0.8
0.3
7.8
2.6
0.25 0.55
13.7 13
5.85 3.7
13.2 12.2
18.8 17.5
25 26
27 28 29
UK Nether- Sweden USA Canada
lands
1975 1981
(2)2)
0.45
0.55
1.3
0. 15
0.7
2.4
5.1
2.6 2.7
0.66 0.25
3.5
1.25
6.45
1984 1982 1978
2.4
1.2
0.85
^
'0.35
'
6.8
1.6 2.25
1.3
•4.1
4.8 13.8
1.2
0.18
3.83)
•
5.2
2.85
0.95 0.7
3.5 0.9
7.3
5.5 11.6 10 21.1 5.6
4.7
3.6
9.65
5.55) 11.4 12.1 29.5 10.0
7.4 15.3
16.1 40.4 13.5
defa
valo
2
1,
1.
2
0
3
6
12
4
'or 1.9
2);
3)
5)
included in industrial emissions
OECD-figure
Ref. 30
from ref. 25
174
-------
Table 8
Compositions of VOC-eroissions from solvent use
(wt. %)
sat. hydrocarbons C,
4+
toluene
xylenes
other aromates
total aromates
methylalcohol
ethylalcohol
isopropylalcohol
butanoles
cellosolves
other alcohols
total alcohols
acetone
me thy le thy Ike tone
methy lisobuty Ike tone
other ketones
total ketones
acetates
other esteres
total esteis
ethers
methylene chloride
trichloroethylene
perchloroethylene
other Cl-hydrocarbons
total Cl-hydrocarbons
Cl-F- hydrocarbons
other solvents
31 24 32 26 28 33
FRC France OECD Nether- USA Sydney
Eur°Pe2) lands
1982 1978 1981 1982
19.2 27 36.3 42.5 5.9.3 25.7
5.4 5.1 >6.6 18.4
3.9 4.0 >3.1 10.6
1.6 9.8 1.6 16.6
10.9 24 19.5 45.6
3.8 1 .. .i 5.0 — |
3.3 6.1 .0 5.3 13.7
1.4 (6) 6.7 2.6 ^
6.7 ) „ 1.5 , ,
r'-8 r-3
5.3 , xj.6.4 4. r
241)| J C.2 J
20.5 20.4 13.7 19.3 15.0
(6) 6.. ...3 3.2 1.6
3.2 4.1 2.9
2.1 ^.0 1.0 1.0
0.3
5.4 J 11.4 4.3 8.6 5.5
7.1 95.1 2.8 2.6
0.5
7.6 5.1 3.9 2.8 2.6
11.9 1.9
6.0 5.5 4.6 1.8
2.2 4.4 1.3 1.3 1.9
4.4 4.8 3.5 4.0 0.4
4.9 3.0 1.0 1.6 1.5
def ai
.•alue
32
6
4
5
2
6
5
5
i
2
6
2
2
4
2
1.75 16 17.7 10.4 6.9 5,6
3.8 3.6
3.2 0.2 1.5
3
1),
2)
incl. ethers
Non-reactive compounds not included. Added for this study: 300 kt acetone,
60 kt methylalcohol, 270 kt methylene chloride, 150 kt trichloroethane.
175
-------
SESSION 4: DEVELOPMENT OF EMISSION INVENTORIES FOR NATURAL SOURCES
Chairman: Fred Fehsenfeld
National Oceanic and Atmospheric Administration
Aeronomy Laboratory
R/E/AL6 325 Broadway
Boulder, CO 80303
176
-------
MEASUREMENT OF BIOGENIC SULFUR FLUXES AT
THREE SITES IN THE EASTERN UNITED STATES
P. D. Goldan
W. C. Kuster
F. C. Fehsenfeld
D. L. Albritton
Aeronomy Laboratory
National Oceanic and Atmospheric Administration
Boulder, Colorado 80303
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
177
-------
MEASUREMENT OF BIOGENIC SULFUR FLUXES AT
THREE SITES IN THE EASTERN UNITED STATES
INTRODUCTION
An assessment of the significance of natural biogenic sulfur sources
compared to anthropogenic sources as potential contributors to the
acidification of rainfall requires measurement of fluxes at or below 10 ng
^
S/m min over large geographic areas. To date, such an assessment has
rested almost entirely on one study completed in 1979, by Adams, et al. (1).
In view of the importance attached to these measurements, the analytical
difficulties recognized by previous workers, and recent improvements and
advances in measurement technology for trace sulfur species, a reassessment
of the strengths of natural sulfur fluxes was deemed desirable.
Consequently, simultaneous measurements at three previously-measured sites
were undertaken jointly by NOAA, Washington State University Air Resources
Laboratory and University of Idaho Department of Chemistry in July and
August 1985.
Measurements were based on the use of enclosures that were placed over
bare soil, various types of agricultural crops, and naturally occurring
vegetative cover, and were flushed with controlled flows of synthetic air or
scrubbed ambient air. Concentrations of H-S, OCS, S0?, CH,SH, DMS
(CH3-S-CH3), CS2, DES (C^-S-C^), MES (CH3-S-C2H5) and DMDS (CH3-S-S-CH3)
in the enclosures were measured gas chromatographically by the NOAA group
using a one-step cryogenic sample enrichment technique in a microbore Teflon
capillary sample loop. Concentrations of OCS, DMS, CS? and DMDS were
measured gas chromatographically by the Washington State group using a
two-step cryogenic sample enrichment technique similar to that used by
Adams et al. (1). In addition, H2$ was measured by the Washington State
group using an impregnated filter fluorometric quenching technique (2),
and total sulfur was measured by the University of Idaho group using a Metal
Foil Collection - Flash Vaporization technique (3). Surface and biomass
fluxes were related to the concentration measurements by means of the known
178
-------
flush gas flow rate (typically 1.5 Std L/Min), the biomass enclosed
(measured by weighing at the end of a suitable measurement period) and the
surface area covered.
Although an intercomparison of the results of the various data sets is
an important goal of the measurement program, we will discuss here only the
details of the NOAA measurements. Preliminary intercomparison has, however,
shown that no gross discrepancies exist in the sulfur fluxes measured using
the various techniques.
RESULTS
Measurements in the vicinity of Ames, Iowa and Celeryville, Ohio, over
bare soil demonstrated a high degree of correlation between the observed
fluxes and the enclosure air temperatures. Plots of log (flux) versus
temperature showed a linear relationship with correlation coefficients
ranging from 0.89 to 0.98. Although in agreement with the results of
Adams et al. (1), the observed correlation coefficients were significantly
higher than those obtained in the earlier study. The inclusion of various
types of actively growing vegetative cover dramatically altered the fluxes
of DMS and DCS, the former being significantly increased and the latter
decreased. The other significant sulfur flux contributors, H~S and CS-,
were affected to a much lesser degree by the presence of vegetation.
Table 1 summarizes our findings of hLS, DCS, DMS and CS^ fluxes from bare
soils and soils with different vegetative cover for Ames, Iowa. Similar
results were obtained in Celeryville, Ohio, over bare histosol soils and
several native "grassy" ground covers. The fluxes measured in this study of
o
approximately 10 ng/S/m min at both Ames, Iowa and Celeryville, Ohio are
2 2
much smaller than the values of 350 ng S/m min and 130 ng S/m min reported
by Adams et al. (1) for the same two sites, respectively.
The results obtained over salt water marshes at Cedar Island, North
Carolina were much more temporally and spatially variable and, therefore
difficult to summarize. Measurements taken over Spartina Alterniflora in
the same location, as were many of the measurements of Adams et al. (1),
show obvious tidal effects; a radical diminution of the H?S flux and a
179
-------
temporary diminution of the DMS flux when the enclosed surface was covered
by water. Measurements made over tidal mud flats covered by the species
Juncus Romerianus, which appears to comprise more than 95 percent of the
tidal marshes in the Cedar Island-Beaufort area, again showed the I^S flux
to have high temporal variability, sometimes changing by more than a factor
of 100 in a half-hour period, and frequently surpassing the DMS flux as the
dominant species. Although it is difficult to generalize from a few
measurements in such a highly variable environment, it appears certain that
FLS and DMS are the dominant species, with DCS, CS,, and CHjSH playing a
lesser role and DMDS hardly even appearing in quantifiable amounts. The
results of our measurements in saline marsh environments are summarized in
Table 2. Extreme ranges observed and estimated mean fluxes are listed for
H2S, COS, CH3SH, DMS and C$2. No other significant contributors to the
natural sulfur flux were observed chromatographically. For comparison, the
fluxes measured by Adams et al. (1) and Aneja et al. (4, 5) are also shown.
CONCLUSIONS
The strong correlation of sulfur gas flux with ambient air temperature
noted in earlier studies has been corroborated by the present GC
measurements at Ames, Iowa and Celeryville, Ohio. Absolute flux values at
weighted mean daily temperatures are found, however, to be about a factor of
10, lower than previoMsly reported. Similar measurements carried out over
saline marshes at Cedar Island, North Carolina also show a mean flux
averaged over tidal cycles, about a factor of 10 lower than previously
reported measurements. Concurrent measurements of H?S and total sulfur
fluxes by entirely independent techniques substantiate the lower fluxes
reported here.
180
-------
REFERENCES
1. Adams, D.F., Farwell, S.O., Robinson, E., Pack, M.R., and
Bamesberger, W.L., tJiogenic sulfur source strengths, Environ. Sci.
Tech.. 15, 1493-1498, 1981.
2. Natusch, D.F.S., Klonis, H.B., Axelrod, H.D., Teck, R.J., and
Lodge, J.P., Sensitive method for measurement of atmospheric hydrogen
sulfide, Anal. Chem.. 44, 2067-2070, 1972.
3. Kagel, R.A., and Farwell, S.O., Evaluation of different metallic foils
for the preconcentration of sulfur-containing gases witli subsequent
flash desorption/flame photometric detection, Anal. Chem.. (submitted,
1985).
4. Aneja, V.P., Overton, J.H., Jr., Cupitt, L.T., Durham, J.L., and
Wilson, W.E., Direct measurements of emission rates of some atmospheric
biogenic compounds, Tell us. 3_1, 174-178, 1979.
5. Aneja, V.P., Overton, J.H., Jr., Cupitt, L.T., Durham, J.L., and
Wilson, W.E., Carbon disulphide and carbonyl sulphide from biogenic
sources and their contributions to the global sulphur cycle, Nature,
282. 493-496, 1979.
181
-------
TABLE 1. AMES, IOWA, JULY 1985
Bare Soil Flux
F(T) = AEBT (ng S/m2 min)
A B F(25.5)
Vegetative Cover Flux at ?5.5
Oat Gramma Soy
Grass Grass Plants
0.124
0.0643
0.6
3.0+1.0
2.3+0.8 1.0+0.4
COS 0.301
0.0870
2.8
2.0+0.8
1.7+C.6 0.7+0.3
DMS 0.0461 0.115
0.9
6.2+3.4
3.5+1.0 5 3+2.9
CS2 0.0711 0.0831
TOTALS
0.6
0.6+C 2
5.0+1.3 11.8+4.4
0.4+0.2 C.5+0.2
7.9+2.6 7.5+3.8
182
-------
TABLF 2. PREDOMINANT NATURAL SOURCES (ng S/m2 min)
CEDAR ISLAND, NORTH CAROLINA SALINE MARSHES
H2S
COS
CH3SH
DMS
cs2
TOTALS
Adams et al
10-77 5-78
33 38
4 19
13 76
17
55 150
7-78
300
38
0.6
3000
114
3450
Ane.ia et al
7-78
100
80
1500
400
2080
NOAA,
Juncus
Tidallv
Observed
Auqust
1985
and Spartina
Flooded
Range
3 ---> >10,000
4 ---
1 ---
60 ---
2 ---
> 15
> 80
> 9''0
> 12
Me, "Si es
Mec n
100
8
7
200
6
220
183
-------
DETERMINATION OF NITROGEN EMISSIONS FROM NATURAL SOURCES
F. C. Fehsenfeld
E. J. Williams
D. D. Parrish
Aeronomy Laboratory
National Oceanic and Atmospheric Administration
Boulder, Colorado 80303
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
184
-------
DETERMINATION OF NITROGEN EMISSIONS FROM NATURAL SOURCES
by: F. C. Fehsenfeld
E. J. Williams
D. D. Parrish
Aeronomy Laboratory
National Oceanic and
Atmospheric Administration
Boulder, Colorado
ABSTRACT
The estimated fluxes of NO (NO + NO-) from the principal natural
A L~
sources a^e presented. According to our present understanding, the largest
natural sources of NO on the North American continent are lightning and
biogenic activity in the soils. However, because of the large uncertainties
associated with the estimation of soil emission, improvements in these
estimates have been given a high priority. Accordingly, two of the
techniques used to measure biogenic NO emissions from the soil have been
'ntercompared. The agreement between the techniques was good. One of tnese
techniques, an enclosure method, has beer, subsequently used to measure the
NO fluxes from the soils at a grassland site in Colorado. The measured NO
fluxes compare favorably with NO fluxes measured at a similar site in
Australia.
185
-------
DETERMINATION OF NITROGEN EMISSIONS FROM NATURAL SOURCES
INTRODUCTION
Natural sources of NOX (NO + N02) are important, not only because they
represent the irreducible minimum for the precursors of the nitrate
component of acid precipitation, but also because they dominate the NOX
budget in the upper troposphere, as well as remote regions of the lower
troposphere. This budget is important because NO controls the
A
photochemical production of ozone and influences the concentration of
tropospheric hydroxyl radicals (OH).
Five natural sources of NO have been identified: lightning, biogenic
A
processes ir soil, oxidation of ammonia, stratospheric injection, and
photolytic processes in the oceans. Table 1 lirts the emission inventories
for the identified sources for global and North American continental
averages. The NO fluxes contained in Table 1 are based on the estimates of
Logan (1983), updated to account for recent developments in this field that
have been reported in the current literature. With regards to North
America, the emission estimates presented in Table 1 can be summarized as
follows: natural NO production is dominated by two sources, lightning and
soil emissions. Presently, the greatest uncertainty lies in the estimation
of soil emissions by NO An improved quantification of NO soil fluxes
A A
demands the development of improved field methods, intercomparison of new
and existing field methods, and extensive field studies. This is the
objactive of the present study.
INTERCOMPARISON OF METHODS USED TO MEASURE NO FLUXES FROM SOILS
Several techniques have been utilized to measure NO fluxes from the
soil, including principally enclosure, gradient, and eddy correlation
methods. The enclosure technique measures the NO flux from a small,
o X
enclosed area of soil surface (typically -1 m ), while the gradient and eddy
186
-------
correlation techniques determine the average NO fluxes from larger areas
32 x
(typically -10 m ). The enclosure method is genially simpler a^ n^re
convenient than the other two techniques, but it is possible that the fluxes
that it is intended to measure are modified due to the disturbance of the
soil environment by the presence of the enclosure. Thus far, all the
published measurements of NO soil (Galbally and Roy, 1978; Johansson and
Granat, 1984; Johansson, 1984; Slemr and Seiler, 1984) fluxes have relied on
the enclosure technique.
In the present study, a gradient technique for measuring NO fluxes from
the soil during nighttime hours has been developed. This technique relies
on the measured (NO) gradient with height above the ground to define the
vertical mixing and, thus, does not require the simultaneous measurement of
micrometeorological parameters. Intercomparison of results from the
gradient technique with those from enclosure measurements were made at a
site located in Colorado during August and September 1985. The NO fluxes
during this period of intercomparison ranged from 0.3 ng N m s to
-2 -1
25 ng N m s . Results obtained during this intercomparison are shown in
Table 2. The agreement appears to be good over a wide range of NO fluxes.
MEASUREMENTS OF N0x FLU/ES FROM THE SOIL
Following the intercompar'son studies, a larger set of flux
measurements has been obtained using the enclosure technique. These fluxes
were measured from unfertilized, ungrazed, grass-covered soils in a period
between 1 August 1985 and 28 October 1985. NO fluxes measured during this
-2-1
period using the enclosure technique ranged between 0.03 ng N m s and
-2 -1
40 ng N m s . The average flux of NO determined in these studies is in
good agreement with the fluxes of NO from ungrazed pastures in Australia
measured by Gal bally and Roy (1978). The NO flux was found to depend
strongly on soil temperature, increasing rapidly with increasing soil
temperature. A compilation of these results for data obtained between
5 September 1985 and 28 October 1985 is shown in Table 3. In addition, this
sampling period was marked by an extended dry period during the August and
October measurement periods. For similar soil temperatures, the NO flux was
187
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lowest toward the end of the dry periods and increased sharply with the
onset of precipitation. At the end of the extended dry periods, NC^ is
observed to be present in the effluent from the sampling enclosure.
CONCLUSIONS
Present estimates indicate that, pertaining to the North American
continent, lightning and biogenic activity in the soil are the largest
natural sources of NO . However, the estimates of the soil emissions are
very uncertain. In the present study, two techniques used to measure
biogenic soil emissions, an enclosure technique and a gradient technique,
have been intercompared during the nighttime hours. The agreement between
the techniques was good. In addition, the enclosure technique has been used
to systematically measure the NO fluxes at a grassland site and to study
the climatological factors that control the NO fluxes. There are no other
results published reporting measurements of NO fluxes on the North American
continent. However, the present results agree with NO fluxes measured at a
temperate grassland site in Australia (Galbally and Roy, 1978).
188
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REFERENCES
1. Galbally, J.E., and C.R. Roy, Loss of fixed nitrogen from soils by
nitric oxide exhalation, Nature. 275. 734-735, 1978.
2. Johansson, C., Field measurements of emission of nitric oxide *
fertilized and unfertilized forest soils in Sweden, J. Atmos. Chem. . 1,
429-442, 1984.
3. Johansson, C., and L. Granat, Emissions of nitric oxide from arable
land, Tellus. 36B, 26-37, 1984.
4. Logan, J.A., Nitrogen oxides in the troposphere: global and regional
budgets, J. Geophvs. Res.. 38, 10785-10807, 1983.
5. Slemr, F., and W. Seiler, Field measurements of NO and NCL emissions
from fertilized and unfertilized soils, J. Atmos. Chem.. 2, 1-24, 1984.
189
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TABLE 1. ESTIMATED OF NATURAL SOURCES OF
Global North America
Lighting 4 0.3
(2 - 8) (0.09 - 0.6)
Soil Emission 8 ~ 0.6
(1 16) (0.08 - 1.5)
Ammonia Oxidation (0 10) (0 0.15)
Stratospheric Injection 0.55 <0.04
(0.37 - 0.67)
Oceans 0.2 —
(0.1 - 1)
aUnits of flux are Tg N yr" . Estimated range of uncertainty .isted in
parentheses.
190
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TABLE 2. INTERCOMPARISON OF BOX AND GRADIFNT
MEASUREMENTS OF NO FLUX3
Date
8/24
8/25
8/26
8/27
8/30
8/31
9/01
Box
0.35
0.28
0.83
0.83
0.37
0.37
20.0
Gradient
0.88
0.20
0.81
1.49
0.21
0.16
17.0
aThe result gives the value (or average value) of the NO flux determined
during the nighttime hours of each of these dates. Units of flux are
Ng N m s .
191
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TABLE 3. THE AVERAGE FLUX OE NO MEASURED AS A FUNCTION OF SOIL
TEMPERATURE OVER 5U INCREMENTS OF SOIL TEMPERATURE"
Soil Temperature Average Flux
Range NO, ,
(°C) (n? N m"" s~l)
0 - 5 0.075
(0.028 - 0.16)
5 iO 0.34
(0.075 1.4)
10 - 15 0.94
(0.20 - 3.9)
15-20 2.5
(0.72 10)
20 - 25 4.5
(2.4 7.3)
25-30 3.9
(2.9 8.1)
The range of measured fluxes for each temperature increment is listed in
parentheses.
192
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ALKALINE AEROSOLS EMISSIONS
Dale A. GUlette
Geophysical Monitoring for Climatic Change
Air Resources Laboratory
National Oceanic and Atmospheric Administration
Boulder, Colorado 80303
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, SC
November 12-14, 1985
193
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ABSTRACT
Alkaline compounds contained In aerosols emitted from open (non-combus-
tion) sources may have the potential to neutralize acid precipitation. This
potential depends on the quantity of aerosol mass emitted, Its transport,
fraction of alkaline compounds In the total aerosol mass, solubility of the
alkaline compounds, and neutralization potential. It Is the mission of the
Alkaline Aerosols Project to estimate the total neutralizing alkaline aerosol
fluxes by evaluating the above factors.
Provisional estimates of alkaline aerosol fluxes showed the following:
(1) That the two most important sources (unpaved road dust and wind erosion)
dominate all other sources.
(2) That methods to estimate total alkaline aerosol emissions give total
fluxes that are larger than observed deposition rates. This and other
inconsistencies of the estimates show that strong efforts are needed to
develop new methods to estimate emissions of alkaline aerosol.
(3) Knowledge Is lacking o.i the fraction of suspended emitted aerosols,
Knowledge is also lacking on solubility and neutralization potential of
the aerosol.
Research efforts have been planned to estimate dust emissions from wind
erosion, dust devils, and unpaved roads. Solubility and neutralization poten-
tial of aerosols produced by these sources will be determined for several
experiments.
194
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OPEN SOURCES OF ALKALINE AEROSOLS
INTRODUCTION
Alkaline compounds carried In aerosols emitted from open sources may have
the potential to neutralize acid rain. To determine the importance of open
sources of aerosols for neutralizing precipitation, a systematic appr_*ch was
laid out to estimate the flux of alkaline aerosol having sufficient residence
time i i the atmosphere to Interact with precipitation systems. After a
general framework of the estimation was laid out, existing data and models
were used to give a provisional estimate of alkaline aerosol em. sions.
Additional work was undertaken to determine solubility and neutralization
potential of the aerosols. The estimate for quantity of emitted soluble alka-
line aerosols was examined to find shortcomings and to plan a more thorough
estimation method.
DISCUSSION
Emission fluxes of alkaline aerosols (F) that have potential to neutralize
acid rain are expressed as follows:
E A' Cf SX N
A
E » Emission factor [mass/(area yr)]
A' - Area of emission
C - Elemental abundance of parent material (fraction of mass)
f • Fractionatlon of aerosol composition to parent material
composition
(1)
195
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S » Fraction of aerosol mass suspended
X - Solubility of suspended aerosol
N » Neutralization factor (fraction)
A » Total area in question.
An initial evaluation of eq. (1) was made state-by-state. The values for
EA1 were those reported by Evans and Cooper (1980). Relative abundance of the
alkaline compounds was assumed to be the same in the aerosols as in the parent
material (fractionatlon of unity). Solubility for alkaline elements was taken
to be that derived from two soluble/insoluble data sets; daily bulk data from
St. Louis and I year of weekly sampling data for wet side precipitation from
Glen Ellyn, Illinois (Gatz, et al., 1984). The composition of the parent
material was taken to be the median value of the state soil chemical survey
data (Boerngen and Shacklette, 1981) for soil erosion and soil tilling and to
be a combination of median state soil chemical composition and chemical com-
position of other road surface materials (see Barnard, et al., 1985) for
unpaved roads. The fraction of aerosol mass suspended was 0.4 based on the
fraction of mass smaller than 10 pm and published aerosol sl^e distributions.
Neutralization potential (N) was set to one even though this can only be an
upper limit.
Results of the provisional evaluation of eq. (1) are shown for the 31
eastern states in Table 1 (after Gatz, et al., 1985). The results show the
dominance of the two most important open sources (unpaved roads and wind ero-
sion) over conventional sources for all the alkaline elements but sodium,
which has little neutralizing potential.
196
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Table I. (after Gatz, et aL., 1985). Total mass and estimated cation
omissions from major open and conventional sources in the 31
"eastern" states. Emission estimates for open sources are
Limited to soluble materials < 10 |jm; these limitations do
not apply to the estimates of emissions from conventional
sources.
Source category
OPEN**
Wind erosion
Tilling
Unpaved roads
Sum
CONVENTIONAL***
Total
mass
37,500
7.420
117,000
162,000
8,410
Thousands
Na
107
18.9
172
297
109
of tonnes/y
Mg
47.4
8.28
531
587
119
r (1980)*
K
123
23.7
231
378
71.6
k
Ca
109
18.7
4,110
4,240
274
* Rounded to three significant figures.
*" Total mass emissions are from Evans and Cooper (1980); element
emissions are based on the work of Stensland et al. (1985).
*** Sum of separate emissions estimated for the following categories:
Fuel combustion, industrial processes, solid wai_e disposal,
transportation, and miscellaneous (less unpaved roads). Total mass
emissions are from U.S. EPA (1982); element abundances used to
calculate emissions are from Gatz et al. (1985).
Comparisons on a state-by-state basis gave total mass fluxes that are much
larger than downward fluxes calculated from NADP/NTN data. This poor
agreement pointed to overestimation by the provisional evaluation cf eq. (1)
and pointed to needed research especially emission factors (E), fractionatlon
factors (f), solubility (X), chemical abundance of roads (c), and neutraliza-
tion potential (N).
197
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To correct for this overestimation and to Improve our knowledge of alka-
line aerosols our plans for research Include:
I). Development of new wind erosion emission equation. The equation will be
physically based and will reiy on results of past research and new
research.
2). Development of dust devil emission estimations. These estimates will be
based on aircraft baaed dust devil sampling and meteorological classifi-
cation/generalization to the American Southwest.
3). Development of a new emission equation for unpaved roads. This will be
based on new experimentation ano theory of dust emissions by vehicles on
unpaved roads.
4). Experimentally determined fractionation factors. These factors will be
developed by examining ratios of relative composition of emitted aerosols
to parent material for both unpaved road emissions and wind erosion.
5). Experimentally determined solubility factors. This effort will be for
alkaline aerosols material collected in experiments on road emissions and
wind erosion.
6). Chemical survey of unpaved roads in the U.S. This chemical survey will
fill a gap In knowledge on the parent materials of U.S. unpaved roads.
7). Experimentally determined neutralization potentials. This work is
necessary because alkaline cations are not always associated with anions
such that H Ions are readily replaced. Composition of the alkaline aero-
sols must be carefully studied.
198
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CONCLUSIONS
The present state-of-the-art In estimating alkaline aerosol emissions
having potential to neutralize acid rain gives numbers which are larger than
NADP/NTN observed deposition by roughly a factor 2-3. The research needed to
improve the estimates will Include development of emission equations for wind
erosion and unpaved roads. Research into solubility, neutralization potential
and fractionation factors will be incorporated into the new estimations.
Chemical surveys of the national unpaved roads will also be executed.
REFERENCES
Barnard, W, R., G. J. Stensland, and D. F. Gatz, 1985: Alkaline materials
flux from unpaved roads: Source strength, chemistry and potential for acid
rain neturalization. Submitted to Water, Air, and Soil Pollution.
Boerngen, J. G., and Shacklette, H. T. , 1981: Chemical analysis of soil and
other surficial materials of the conterminous United States. Open File
Report 81-197, U.S. Geological Survey, U.S. Dept. of Interior, Denver,
Colo.
Evans, J. S., and Cooper, D. W., 1980: An Inventory of participate emissions
from open sources. J. Air Pollut. Control Assoc., 30, 1298.
Gatz, D. F., W. R. Barnard, and G. J. Stensland, 1985: The role of alkaline
materials In precipitation chemistry: A review of the issues. Submitted
to Water, Air and Soil Pollution.
Gatr., 0. F. , Stensland, G. J. Miller, M. V., and Chu, L.-C., 1984: Alkaline
aerosols: An Initial Investigation of their role In determining preclplta-
199
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tlon acidity. Final Rept. NSF Grant ATM 77-24294. Illinois State Water
Survey Contract Report No. 343.
200
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METHODOLOGY FOR ESTIMATING NATURAL HYDROCARBON EMISSIONS
By
James A.
Atmospheric Sciences
U.S. Environmental
Research Triangle Park,
Reagan
Research Laboratory
Protection Agency
North Carolina 27711
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, SC
November 12-14, 1985
201
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ABSTRACT
An emission inventory system for biogenic sources of hydrocarbons
has been developed. It is based on modifications of the classic formula:
Emissions = £ Biomass * Area * Emission Factor
It accomodates multiple sources with emission factors dependent on season,
temperature and sol<_r intensity. It provides emissions on a latitude
longitude based grid system aggregated by plant specie, hydrocarbon com-
pound, study area (county, state, etc.), or time interval. The emission
calculations from this inventory have better spatial, source, temporal
and hydrocarbon compound resolution than prior work has provided.
INTRODUCTION
Part of the evaluation of the Regional Acid Deposition Modeling
effort will include natural source contributions and effects. The new
chemistry model has been extended to incorporate biogenic hydrocarbons in
the simulation. The use of kinetic reactions employing natural sources
of hydrocarbons in air and water requires definition of their emissions.
Such an emission inventory should recognize production of biogenic hydro-
carbons from:
- the foliage of trees, shrubs, and crops
- decaying leaf 1itter
- grasses in urban areas, pastures, and grasslands
- decaying vegetation in rivers, lakes, marshes, and oceans.
Methane, monoterpenes, and isoprene are the dominant hydrocarbon compounds
produced by biogenic sources.
202
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A syste atic methodology was needed for the estimation of biogenic
hydrocarbon emissions. Such an inventory should have the following capa-
bilities:
- Generate hourly gridded emissions
(a) for a variable number of hydrocarbon species;
(b) from a variable number of plant species, leaf litter, and
surface waters;
(c) for any latitude/longitude-based grid system.
- Apply temporal variations to emission factors on a diurnal and/or
seasonal basis.
- Adjust emission factors for variations in temperature and solar
radiation.
- Allow for future modification of emission factors to incorporate
submodel calculations, including leaf temperature, fol iar density,
soil types, moisture availability, and disease prevalence.
- Provide summary reports of emissions by grid cell, county, U.S.
Forest Service (USFS) region, and state.
Such a system has been developed for the Northeastern United States and
offers the potential for meeting one of the requirements of the Regional
Acid Deposition Model.
DISCUSSION
Biogenic hydrocarbon emissions are a function of emission rate and
biomass within a given area. An emission inventory for them includes of
building files of descriptive data on land use, emitter density, and emis-
sion factors. It also includes algorithms implementing the relations
between the data elements of these descriptive files.
Area categorization has been primarily derived from the USGS Land
Use and Land Cover map series supplemented as needed from other satellite
203
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and aerial sources. Coverage areas for the following land use classifi-
cations were estimated to the nearest five percent for each grid cell:
-urban -water
-agricultural -barren land
-rangeland -nonforested wetland
-deciduous forest -mixed agricultural and rangeland
-coniferous forest -rocky open areas occupied by low
growing shrubs and lichen (not
-mixed forest (including including tundra)
forested wetland)
Mixed forest was split between the coniferous and deciduous classi-
fications, with data from the U. S. Forest Service inventories used to
allocate area to individual species. The canopy area is a function of
the diameter at breast height (dbh), which is divided into ten intervals
or classes. The area for one tree in a dbh class multiplied by the num-
ber of trees in the class and summed across classes gives the total area
for a specie. A mix ratio of the specie area to the total area summed
across all species of the same forest type, deciduous or coniferous, was
used to allocate the proportion of the corresponding forest type area to
that specie. Agricultural land was apportioned among crops based on the
1978 Census of Agriculture as aggregated to the county level by the Oak
Ridge National Laboratory. Several state atlases were used to resolve
the split between fresh and salt water, especially in estuaries. A file
of the overlap between grid cells and study unit (county, forest region,
etc.) was used to partition classification areas among the grid cells.
It is used in reverse to summarize emissions at the study unit level.
Most of the hydrocarbons emitted by vegetation are released by the
foliage. The branches, twigs, bole, and root emissions are negligible in
204
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comparison. Foliage weight can be estimated from algorithms which relate
foliage weight to tree diameters. Tree diameter inventories are compiled
by the U. S. Forest Service for each state. Emission factors for surface
waters, leaf litter, and some crops are area dependent and do not require
a foliar weight estimate.
The emission factor is expressed as moles or micrograms of hydrocar-
bon emitted over a time interval per unit of land area or dry foliar
weight. The identity of the hydrocarbons emitted is reported as isoprene,
monoterpene, and/or unspecified nonmethane hydrocarbon. When emission
factors were unavailable for a particular vegetative type, an emission
factor from a biologically similar vegetation type was used. These emis-
sion factors have several possible sources of error:
- Measurement error due to the experimental method employed disturb-
ing the natural emission process.
- Inappropriate substitution of emission factors due to unavailable
data.
- Emission factors may vary with environmental parameters including
geographic location, soil conditions, and elevation.
Because emission factors are known to vary with light and tempera-
ture, the system accounts for seasonal changes in solar radiation and
surface temperature. It is assumed that the leaves of all plants are
exposed to full sun and the same surface temperature. Because there may
be large variations in solar radiation and surface temperature, hourly
estimates are made of these variables. Solar radiation is derived from
formulas that give the solar zenith angle as a function of latitude,
longitude, date, and time of day. The system does not currently account
for attenuation due to clouds and aerosols, but provision has been made
for this variable in future versions of the system. Thus, the emissions
205
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generated by the system are maximum rates with respect to the effects of
Sunlight. Surface temperatures from the National Weather Service are
transformed to average grid cell temperatures by an objective mapping
technique for mesoscale processes based on numerical filtering. All of
the emission factors have been standardized to 30°C. It has been assumed
that all monoterpene emitters and nonmethane hydrocarbon emitters (other
than isoprene) respond to temperature in a manner similar to monoterpene
emissions from slash pine. Likewise all isoprene emitters have been
assumed to respond to changes in light And temperature as does isoprene
from 1ive oak.
CONCLUSIONS
An emission inventory system has been developed to meet the require-
ments of the ne.; kinetic reactions employing natural sources of hydrocar-
bons in air and water. It provi ies much better resolution than prior
inventories especially in terms of spatial and temporal variation. It is
open ended allowing inclusion of different areas, sources, emission fac-
tors and temporial variations. It will provide insight into the relative
contribution of a few species to the total emissions in an area. A syste-
matic, detailed inventory increases the confidence in the emissions since
variances can be reasonably calculated. Future research on emission fac-
tor development, module extensions, etc. can be guided by the knowledge
gained from the system.
?06
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SESSION 5: RELATED EMISSION INVENTORY DEVELOPMENT ACTIVITIES
Chairman: J. David Mobley
Air and Energy Engineering Research Laboratory (Mp-61)
U. S. Environmental Protection Agency
Research Triangle Park, NC 2771_
207
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SUMMARY OF A 1982 NATIONAL EMISSIONS INVENTORY
FOR REGIONAL MODEL DEVELOPMENT
Steven L. Heisler
Environmental Research and Technology, Inc.
975 Business Center Circle
Newbury Park, Jalifornia 91320
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Caroline
November 13-14, 1985
208
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SUMMARY OF A 1982 NATIONAL EMISSIONS INVENTORY
FOR REGIONAL MODEL DEVELOPMENT
By: S.L. Heisler
Environmental Research and Technology, Inc,
975 Business Center Circle
Newbury Park, California 91320
ABSTRACT
None of the regional and national emissions inventories available in
1982 were suitable for regional deposition or air quality modeling.
Therefore, procedures were developed and applied to produce a suitable
1982 inventory for the United States and southeastern Canada. The
inventory includes total emitted particulate matter (TEP), alkaline TEP,
SO., primary SO,, NO, N0_, NH_, and hydrocarbons in nine photochemical
reactivity classes. Point source geographic locations are resolved to
±100 meters, and stack data are available for calculating emission
injection height. Area source emissions are available by county or
within 1/4° longitude by 1/6° latitude elements of a grid system. The
inventory contains annual, seasonal, weekday, weekend, and 3-hourly
average emission rates. United States emissions of TEP, S02, NO and HC
in the inventory are 1,698, 26.5, 23.8, and 20.8 million tons per year,
respectively. The point source data are from various years; about
one-half of the S09 and NO emissions pertain to 1982. Older data for
£. A
some states are currently being updated. This inventory is currently
being compared with the 1980 National Acid Precipitation Assessment
Program (NAPAP) inventory by source category and state to identify and
evaluate differences. Procedures used to develop them are also being
compared to evaluate consistency between the inventories and improve
inventory development procedures in general.
209
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SUMMARY OF A 1982 NATIONAL EMISSIONS INVENTORY
FOR REGIONAL MODEL DEVELOPMENT
INTRODUCTION
None of the regional and national emissions inventories that were
available in 1982 ' ' ' ' were suitable for regional modeling
applications throughout the United States and eastern Canada. They were
limited with respect to geographic coverage, data concurrency, chemical
substances, or spatial resolution, or specification of uncertainties.
To improve upon the situation, the Electric Power Research Institute
(EPRI) sponsored the development and application of procedures to compile
a 1982 emissions inventory for the contiguous United States and south-
eastern Canada ' .
The inventory includes total emitted particulate matter (TEP),
alkaline TEP, SO primary 30^, NO, NO , NH and hydrocarbons (HC) in
nine photochemical reactivity classes. Point sources geographic
locations are nominally resolved to ±100 meters. Stack heights,
diameters, flow rates, and exit temperatures are included for calculating
emission injection height. Area source emission rates are available by
county. Factors to allocate these county-wide data to elements of a
1/4° longitude by 1/6° latitude grid system are also available. The
inventory contains annual, seasonal, weekday, weekend, and diurnal
(3-hour resolution) average emission rates.
DISCUSSION
Annual emissions from point and area sources are in Table 1. Almost
all TEP emissions are from wind erosion and agricultural tilling area
sources. Point sources emit over 90% of the SO in the country. Point
and area sources contribute equally to NO emissions, and area sources
account for 70% of HC emissions.
210
-------
Although the nominal time period of the inventory is 1982, it
contains point source data from several years. The national distribution
of annual point source emissions by year-of-record is in Table 2. About
one-half of the SO and NO emissions and 30% and 27% of the TEP and HC
^ X
emissions are for 1982. Less than half of the point source emissions for
any material pertain to years before 1981.
Most point source SO and NO emissions are from a relatively small
^ X
number of large sources. Almost 80% of point source SO emissions are
from 406 facilities that each emit more than 10,000 tons per year, and
about 70% of point source NO emissions are from 440 facilities that each
emit more than 5,000 tons per year. The 1,289 largest emitters account
for about 73% of point source TEP emissions, and the 784 largest emitters
account for about 75% of point source HC emissions.
Annual emissions by source category are shown in Table 3. Almost
all of the TEP is emitted by fugitive area sources, particularly wind
erosion and agricultural tilling. Emissions from unpaved roads are also
substantial. Industrial processes are the largest point source
contributors to national TEP emissions, and residential fuel use is the
largest combustion source. TEP emissions from mining, which could be
important in some parts of the country, are not in the inventory.
Fossil-fueled electric utility boilers account for 66% of SO,
emissions. Industrial boilers and industrial processes each contribute
14%. The remaining 6% is from-other fuel combustion.
Electric utility and industrial boilers account for 53% of national
NO emissions, and motor vehicles contribute 30%. Industrial processes,
X
which include refinery and chemical plant process heaters, contribute 9%.
Industrial processes, motor vehicles, miscellaneous solvent uses,
and residential fuel combustion are the largest HC emitters. Most
industrial process emissions are from storage tanks and solvent use.
Wood combustion accounts for most HC emissions from residential fuel use.
Annual NH_ and alkaline TEP emissions are listed by source category
in Table 4. Emissions from bacterial action in the ground and from
livestock account for most of the NH» in the inventory. However,
emissions from fertilizer use are not included. This category may be
significant. Wind erosion and agricultural tilling emit most of the
alkaline TEP.
211
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Tables 5 and 6 show comparisons of total United States SO- and NO
emissions with Version 3.0 of the 1980 National Acid Precipitation
Q
Assessment Program (NAPAP) inventory . Although these national totals
agree within 5%, some of the procedures and data sources used to develop
the inventories were different. In particular, electric utility data in
NAPAP were derived from forms filed by utilities with the Department of
Energy, while data in the EPRI inventory came from the National Emissions
Data System , state inventories, and some plant operators. These and
other differences may have produced significant differences in emission
rates from some source categories in some regions of the country. It is
important tha* such differences be identified and evaluated, since they
could affect results of regional modeling applications.
Procedures used to c. ulate primary SO,, NO, N07, and EC reactivity
class emissions also differed between the inventories, as did procedures
used to calculate seasonal, day-of-week, and diurnal average emission
rates. The effects of these differences must also be evaluated.
212
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CONCLUSIONS
The data in the inventory indicate that area sources, particularly
wind erosion and agricultural tilling, dominate annual United States TEP
and alkaline TEP emissions. Point sources, principally electric utility
boilers, emit most of the S02 in the United States. Point and area
sources emit nearly equal amounts of NO Motor vehicles, industrial
processes, miscellaneous solvent uses, and residential combustion are the
major sources of EC. Animals and bacterial action in the ground are the
major sources of NH_.
The inventory does not currently include fugitive TEP emissions frora
surface mining, which could be significant in some parts of the country.
NH_ emissions from fertilizer use also are not included. These sources
will be added to ""he inventory in the future.
A major fraction of national point source emissions in the inventory
pertain to time periods before 1982. Work is under way to update some of
the older values to improve data concurrency
Although total S0» and N'O emission rates for the United States are
almost the same in the EPRI and 1980 NAPAP inventories, some data sources
and procedures used to develop these inventories were different. These
differences may have caused emissions from some sources to differ signif-
icantly in some parts of the country. Therefore, these inventories
are currently being compared by source category and state to identify and
evaluate differences. Procedures used to develop the two inventories are
also being compared to evaluate the consistency between the inventories
and, hopefully, improve inventory development procedures in general.
Acknowledgement. This work was supported under Electric Power
Research Institute Contract RP1630-23.
REFERENCES
1. AEROS Manual Series; Volume II: AEROS User's Manual, USEPA Research
Triangle Park, NC, EPA-450/2-76-029, December 1976.
213
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2. H. A. Klemm and R. J. Brennan, Emissions Inventory for the SURE
Region, GCA/Technology Division for the Electric Power Research
Institute (EPRI), EA-1913, April 1981.
3. C. M. Benkovitz, "Compilation of an Inventory of Anthropogenic
Emissions in the United States and Canada." Atmos. Environ. 16 (6):
1551 (1982).
4. F. M. Sellars, et al., Northeast Corridor Regional Modeling Project
Annual Emission Inventory Compilation and Formatting, Volumes I
through XVIII, EPA-450/4-82-013a-r, August 1982-July 1983.
5. Emissions, Costs, and Engineering Assessments, Work Group 3B,
U.S./Canada Memorandum of Intent on Transboundary Air Pollution,
Junr 1982.
6. S. L. Heisler, "Emission Inventory Requirements for Deposition and
Regional Air Quality Model Development: A Summary." In:
Proceedings: First Annual Aicd Deposition Emissions Inventory
Symposium, Research Triangle Park, NC, EPA-600/9-85-015, May 1985.
7. S. L. Heisler, et al., "The EPRI 1982 Air Pollutant Emission
Inventory." Presented at the 78th Annual Meeting of the Air
Pollution Control Association, Paper 85-4.3, Detroit, MI,
June 16-21, 1985.
8. D. A. Toothman, et al., Status Report on the Development of the
NAPAP Emission Inventory for the 1980 Base Year and Summary of
Preliminary Data, Research Triangle Park, NC, EPA-600/7r84-091,
December 1984.
214
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3. C. M. Benkovitz, "Compilation of an Inventory of Anthropogenic
Emissions in the United States and Canada." Atmos. Environ. 16 (6)
1551 (1982)
4. F. M. Sellars, et al., Northeast Corridor Regional Modeling Project
Annual Emission Inventory Compilation and Formatting, Volumes I
through XVIII, EPA-450/4-82-013a-r, August 1982-July 1983.
5. Emissions, Costs, and Engineering Assessments, Work Group 3B,
U.S./Canada Memorandum of Intent on Transboundary Air Pollution,
Junr 1982.
6. S. L. Heisler, "Emission Inventory Requirements for Deposition and
Regional Air Quality Model Development: A /ummary." In:
Proceedings: First Annual Aicd Deposition Enissions Inventory
Symposium, Research Triangle Park, NC, EPA-6CfV9-85-015 , May 1985.
7. S. L. Heisler, et al., "The EPRI 1982 Air Pollutant Emission
Inventory " Presented at the 78th Annual Meeting of the Air
Pollution Control Association, Paper 85-4.3, Detroit, MI,
June 16-21, 1985.
8. D. A. Toothman, et al., Status Report on the Development of the
NAPAP Emission Inventory for the 1980 Base Year and Summary of
Preliminary Data, Research Triangle Park, NC, EPA-600/7-84-091,
December 1984.
215
-------
Table 1. ANNUAL UNITED STATES POINT AND AREA SOURCE EMISSIONS
Point Sources
Area Sources
Total
Emissions
(million tons/year)
TEP
5.1
1693
1698
—2
24.4
2.1
26.5
NO
X
11.9
11.9
23.8
HC
5.9
15.9
20.8
Table 2. DISTRIBUTION OF INVENTORIED UNITED STATES
POINT SOURCE SMISSIONS BY YEAR-OF-RECORD
Emissions (percent of total)
(million tons/year)
Before 1980
1980
1981
1982
After 1982
TSP
so2
NO
X
HC
1.4
1.8
1.3
2.2
(27%)
(7%)
(11%)
(37%)
0.7
2.5
1.3
0.9
(14%)
(10%)
(11%)
(15%)
0.9
5.5
2.8
0.6
(17%)
(23%)
(24%)
(10%)
1
13
5
1
.5
.0
.8
.6
(30%)
(53%)
(48%)
(27%)
0.6
1.5
0.8
0.6
(12%)
(6%)
(6%)
(10%)
216
-------
Table 3. ANNUAL UNITED STATES EMISSIONS BY SOURCE CATEGORY
Emissions
(thousand tons/year)
Source Category
Stationary Source Fuel
Combustion
Electric Utilities
Industrial Boilers
Commercial/ Institutional
Residential
Subtotal
Industrial Processes
Non-Ferrous Smelters
Other Processes
Subtotal
Solid Waste Disposal
Transportation
TEP
800
588
115
1,011
2,514
184
3,457
3,641
418
Motor Vehicles 129,519*
Airplanes
Vessels
Railroads
Other Off-Highway
Subtotal
Miscellaneous
Wind Erosion
Agricultural Tilling
Construction
Cattle Feedlots
Forest Fires
Other Burning
Gasoline Marketing
Miscellaneous Solvents
Subtotal 1,
Total 1,
^Includes entrained particulate
Includes entrained particulate
82
26
49
59
129,735
956,300
595,000
9,432
440
288
560
0
0
562,020
698,328
matter
matter
SO,
i
17,380
3,699
610
177
21,866
1,092
2,690
3,782
44
365
12
172
112
114
775
0
0
0
0
3
3
0
0
6
26,473
NO
7,920
4,138
354
404
12,816
47
1^994
2,041
176
6,869
109
141
725
827
8,671
0
0
0
0
68
102
0
0
170
23,874
1
2
3
5
5
6
7
3
4
21
HC
59
,039
15
,089
,202
16
,529
,545
677
,195
161
427
176
517
.476
0
0
0
0
325
417
960
,157
,859
,759
from road surfaces.
from unpaved air strips.
217
-------
Table 4. ANNUAL UNITED STATES NH3 AN^ ALKALINE TEP EMISSIONS
Emissions
(thousand tons/year)
Fuel Combustion
Industrial Processes
Unpaved Roads
Paved Roads
Construction
Wind Erosion
Agricultural Tilling
Cattle Feedlots
Other Livestock
Land Surfaces
Human Beings and Pets
Total
1
4
5
NH
774
23
0
0
0
0
0
,189
,900
,103
266
Alkaline TEP
0
0
3,972
111
300
46,960
18,880
168
0
0
0
12,255
70,39 1
Expressed as equivalent calcium carbonate.
-------
Table 5. COMPARISON OF ANNUAL SO EMISSIONS WITH
THE 1980 NAPAP INVENTORY
Emissions
(million tons/year)
NAPAP3 EPRI
Electric Utilities 17.3 17.4
Non-Utility Combustion 4.6 4.5
Non-Ferrous Smelters 1.2 1.1
Transportation 0.9 0.8
Other Sources 3.1 2.7
Total 27 1 26.5
Table 6. COMPARISON OF ANNUAL NO EMISSIONS
WITH THE 19SO NAPAP INVENTORY
Emi ss i ons
(mi1 lion to n s/yea r_)
NAPAPa EPRI
Electric Utilities 8.1 7.9
Non-Utility Combustion 5.2 •* 9
Non-Ferrous Smelters 0 0
Transportation 9.1 8.7
Other Sources 1 • 3 1 -3
Total 23.7 22.8
3National Acid precipitation Assessment Program I960 inventory
Version 3.0s.
219
-------
GENERATION OF TEMPORALLY-RESOLVED
EMISSIONS INVENTORIES FOR CANADA
Trevor Scholtz
MEP Company, Markham, Ontario, Canada
Frank Vena
Environment Canada, Hull, Quebec, Canada
Presented at:
Second Annual Acid Deposition Emission Inventory Synposium
Charleston, South Carolina
November 12-14, 1985
-------
ABSTRACT
Processing of North American anthropogenic and natural source
emissions for the Canadian long-range transport model (ADOM) Involves
the generation of an hourly speciated emissions file on the 127 km
Eulerian grid. Some anthropogenic and most natural emissions are
strongly dependent on local climate and hourly meteorology. The use of
generally derived or average temporal factors for these sources can
lead to inconsistencies between between prevailing meteorology and the
estimated emission rates used in evaluating the ADOM model. This paper
describes a system for preprocessing of anthropogenic and natural
source emissions using the ADOM database of hourly gridded
meteorological data and other temporally variable parameters to provide
an hourly emissions file which avoids some of the inconsistencies
inherent in the use of average temporal factors.
221
-------
i. INTRODUCTION
A Eulerian long-range transport model Is presently being
developed by the Ontario Ministry of the Environment, with Environment
Canada and the Federal Republic of Germany as co-sponsors. This model,
known as the ADOM model, includes a model of the atmospheric chemistry
which requires a detailed knowledge of the reactant mix in each 127 x
127 km grid cell. This mix is partly dependent on the spatial and
temporal distribution of speciated emissions. While presently
available emissions Inventories provide reasonably good spatial
resolution of the annual average emissions, temporal factors are
generally based on typical seasonal and diurnal variations rather than
year specific or hourly meteorological data. The use of typical
temporal profiles for climatologically and meteorologically dependent
sources such as open anthropogenic and natural sources can lead to
Inconsistencies between the prevailing hourly meteorology and the
estimated emission rate. Since under some circumstances, open sources
and other meteorologically dependent emissions can overwhelm their
better defined process-related counterparts, it is important for
purposes of model evaluation to provide a more realistic temporal
resolution of these emissions. Part of the database for the ADOM model
comprises hourly meteorological data as well as soil moisture and
temperature, gridded to the 127 km Eulerian grid for the subject
period. The availablity of this database, facilitates the more
realistic estimation of meteorologically forced emissions.
This paper describes an emissions preprocessor for
anthropogenic and natural sources which provides a first level of
refinement In preparing an hourly resolved emissions file and which
avoids many of the Inconsistencies inherent in using typical temporal
factor profiles. This preprocessor will have as Its first application,
the preparation of an emissions file for the 1980 PEPE/NEROS
experimental period. Details of the methodology used to derive
seasonal, day-of-week and diurnal temporal factors for anthropogenic
area sources and natural sources are given In References (1) and (2).
222
-------
2. DISCUSSION
2.1 Emissions Processing System for the ADOM
Figure 1 shows the general steps taken in processing the
(1980) Canadian and U.S. point and area source emissions. The Canadian
emissions file contains annual average 1980 anthropogenic emissions for
area and minor point sources together with temporal factors for the
PEPE/NEROS period for a selection of major point sources. The area
source emissions are provided on a 127 x 127 'urn gridded basis. The
U.S. anthropogenic emissions inventory is on a county basis and
includes some temporal factor information as part of the file. The
system provides a facility to allocate the U.S. emissions to the ADOM
grid, reformat and merge them with the Canadian data to provide a
single emissions file. This merged file is then processed through the
emissions preprocessor which applies the temporal factors to
process-oriented emissions and which uses appropriate climatological
arid meteorological data to generate temporally and spatially resolved
open anthropogenic and natural source emissions. The output from the
system is a file of gridded hourly emission rates for a specified
period. While the system is intended to process both Canadian and U.S.
sources , the climatological data and other emission parameter data for
open and natural sources as well as other meteorologically dependent
sources have so far only been prepared for Canada for the year 1980.
2.2 Temporal Emissions Preprocessor
Figure 2 shows the subsystem for generation of temporally
resolved emissions. For purposes of this preprocessor, emissions are
divided into the following three classes:
223
-------
(1) Production., Consumption and
Process Related Emissions
For sources in this class, the preprocessor function is
simply to apply prescribed seasonal, day-of-week and diurnal temporal
factors to the annual average emission rates. Some sectors in this
class do have a climatic component (for example, gasoline and diesel
marketing, motor vehicle and residential heating emissions). The
gridded annual average emissions in A are processed by G using
seasonal, day-of-week and diurnal factors contained in file B.
Seasonal factors are based on 1980 quarterly and monthly production,
consumption or other statistics available from Statistics Canada.
These statistics give an estimate of the province-wide monthly or
quarterly relative activity variations. The annual average emissions
are available for Canada on the 127 km grid and the seasonal activity
profile and therefore the seasonal temporal factors are assumed to be
uniform throughout the province. Where climate dependence is
significant (Table 1) the normalized seasonal profiles of the relevant
climate variable/s have been estimated for some thirty-five climate
zones of approximately 4 in latitude width as shown in Figure (3) from
Reference (2). These zonal factors which reflect the intra-province
variation of climate extremes are used to weight the activity related
temporal factors to resolve the spatial variation of seasonal temporal
factors in each province. These spatially resolved seasonal factors
are contained in file B. Where possible, 1980 climate data have been
used; heating degree day distribution for example. Figures 4 and 5
from Reference (1) are examples of the computed latitude variation of
seasonal temporal factors for diesel and gasoline marketing and
gasoline powered motor vehicles.
Specific data on day-of-week or diurnal activity profiles
were not available and these temporal factors are extracted from other
studies as well as from a limited survey of industry practice.
224
-------
(ii) Open Anthropogenic Sources
Sources in this class (Table 1) are mainly contributors to
suspended particulate bearing alkali and alkaline earth metals as well
as iron and manganese. The alkaline material is important for pH
dependent wet chemical reactions while the Fe and Mn ions catalyse wet
SOn oxidation. Open source particulate emissions are strongly
dependent on prevailing meteorology, vegetative and snow cover, as well
as silt and moisture content. Emissions in this class are computed in
module E using the hourly gridded meteorological data in C. In some
cases an emissions algorithm is used to estimate the grid average rate,
for others only a likelihood weighting factor for certain activities
can be assessed on the basis of meteorology (for example spraying
activities, slash burning). Some emissions which are primarily
determined by non-meteorological factors such as road dust are
suppressed during and subsequent to precipitation events. Again,
climate related parameters in the emission algorithm have been
estimated on a 4 latitude basis while parameters such as soil type and
area of agricultural land have been gridded to the 127 km resolution.
(iii) Natural Sources
Apart from time-stationary factors such as vegetation and
soil type, natural source emissions are entirely determined by climatic
and meteorological factors. While some annual average emission
estimates are available for natural sources, these are used where only
seasonal variation is resolved, for all other natural sources, the
hourly emission rates are determined using an emission algorithm
together with zonal climate data and hourly gridded meteorological data
(Table 2).
225
-------
3. CONCLUSIONS
In order to resolve natural and oorae anthropogenic emission
rates to the spatial and temporal scales required by the ADOM Eulerian
long-range transport model, it is necessary to consider the impact of
spatial climate variability as well as hourly meteorology on the
temporal variation of emission rates. Using the hourly gridded
meteorological fields and other data from the ADOM database it is
possible to prepare an hourly emissions record which refines the
emissions estimates by including these effects.
REFERENCES
I. MEP Company and Ontario Research Foundation, "Temporal Factors for
1980 National Anthropogenic Area Source Emissions", Report
prepared for Environment Canada, July 1985.
2. Environmental Applications Group Ltd., "Gridded Natural Emissions
Inventory and Temporal Algorithms", Report prepared for
Environment Canada, May 1985.
226
-------
Table 1
Climatologically and Meteorologically
Dependent Anthropogenic Area Sources
Source
Gasoline Powered Motor Vehicles
Gasoline and Diesel Marketing
Residential Heating
Paved and LFnpaved Roads
Pesticide Application
Slash Burning
Tailings Piles
Landfill Sites
Tilling
Parameters
Seasonal mean e_ (T)
Monthly mean e (T)
Seasonal degree days
Precipitation
Wind, Precipitation
Wind, Precipitation
Wind, Seasonal PE
Growing degree days
Precipitation
227
-------
Table 2
Natural Sources
Source
Seasonal Diurnal
Species
Parameters
Marine Salt
Ca, Mg, K, SO
Fe, Mn
wind, ice cover
Soils
NH-, VOC, NOX,
S(B2S)
soil temperature,
air temperature,
snow cover
Vegetation
VOC
vegetative state,
air temperature
Soil Erosion
K, Mg, Ca, Fe,
Mn, particulate
wind, snow cover,
vegetative state,
soil moisture
Lightning
Animal Wastes
NOX
, VOC
climatological
climatological
Forest Fires
SO-, CO, NOX,
VOC, Ca, Mg, K,
SO particulate
climatological
Marines Waters
VOC, CO
ice cover
228
-------
Canadian 1980
Point and Area
Source Emissions
U.S. 1980 Point
and Area Source
Emissions
Merge and
Grid to
ADOM Grid
Cl imatological and
Meteorological Data
fc
Temporal
Emissions
Preprocessor
•fej
Hourly
tmissions
File
Figure 1: Emissions Processing for the ADOM Model
-------
1980 Annual
Averaged
gridded
emissions
inventory
Zonal temporal
factors for
emissions
Emissions
Preprocessor
Hourly
resolved
1980 emissions
file
Hourly gridded
meteorological
data
Zonal temporal
factors for
emission
parameters
Emission
Algorithms
Other data
and parameter
files from
Eulerian
model input
Figure 2: Computation of temporally resolved emissions for the ADOM Model.
-------
CLIMATE ZONES
Figure 3
-------
29 DIESEL S, GRSOLINE MflRKETING
SIC: 60802 GflSOLINE MflRKETING
RLL POLL
ZONEi 02
1.12 -
0.90 .
0.03 .
0.09 .
118
77
1.39
FILL POLL
ZONEi OIL
1.10 .
0.90 .
0.77 .
0.30 .
127
68
flLL POLL
RLL ZONES
HI SP SU FA
HI SP SU FA
1.17 -
1.09 .
0.00 .
0.17 .
42
165
HI SP SU FA
35 ONTRRIO
60 YUKON
Figure 4: Seasonal temporal factors adjusted for Climate, Diesel and Gasoline Marketing.
-------
nui ufiuaI LC5
1.07
12100 TOf. PflRT.
RLL ZONES
1.03 .
1.00 -
O. SO -
Ci.93
105
95
112603 N1TRO. OXIDE
ZONEi 02
UI SP SU FM
1.02 .
1.00 .
0.87 .
0.93 -
103 103
96
i.to
(12101 CHRB.MONOXI
ZONEi 02
1.11 .
1.00
0.00 .
0.72
120
80
UI SP SU FA
UI SP SU FR
U3101 VOTflLlIC
ZONEi Oc'.
i.ao
1.14
1.00 .
0.00 .
0.72
120
HI SP SU FA
ro
U)
OJ
12100 TOT.
flLL ZONES
1.03 -
1.02 .
0.90 .
0.94 .
107
35 ONTARIO
142603 NITFlO. OXIDE U2101 CRRB.MONOXI U3101 TOTflL HC
ZONEi 05 ZONEi 05 ZONEi 05
1.21 ., „ I.21
UI SP SU Ffi
1.01 .
1.00 .
0.99 .
0.97 .
98
102
1.09 .
0.97
0.03
UI 8P SU FP
0.73
114
8n
1.09 .
0.97 .
0.03 .
0.73
114
80
UI SP SU FA
UI SP SU FA
60 YUKON
Fl'gure 5: Seasonal temporal factors adjusted for Climate; Gas Powered Motor Vehicles.
-------
HISTORICAL ANALYSIS OF SULPHUR DIOXIDE
AMD NITROGEN OXIDES EMISSIONS IN CANADA
Tom Furmanczyk
Environment Canada
Ottawa, Ontario, Canada
Presented At:
Second Annual Acid Deposition Emission Inventory Symposiun
Charleston, South Carolina
November 12-14, 1985
234
-------
ABSTRACT
Anthropogenic sulphur dioxide and nitrogen oxides emissions in Canada
were calculated biennially from 1970 to 1980. For the most part, emissions
were based on national statistics covering the production, distribution and
consumption of goods and services and on estimates of appropriate emission
factors.
The trend in the emisisons of sulphur dioxide has been steadily down-
ward in the last decade. Traditionally the largest source of sulphur dioxide
has been the non-ferrous smelting sector where emissions have decreased by 44
percent. Other major sources are the generation of thermal power from which
emissions have been rising and the combustion of fuels in industrial,
residential and commercial applications where a downward trend in emissions was
observed. The emissions of nitrogen oxides come predominantly from transporta-
tion and the combustion of fuels, including thermal power generation, which
account for dhout 60 and 35 percent respectively of total emissions. This
ratio has remained relatively constant during the study period.
?35
-------
1. INTRODUCTION
The current concern with the long range transport of air pollutants
(LRTAP) is with sulphur dioxide ($02) and nitrogen oxides (NOX) which give
rise to what has become known as "acid rain" or, more appropriately, acid
deposition. This phenomenon occurs because prolonged atmospheric transport of
sulphur and nitrogen oxides provides sufficient time for these compounds to
undergo chemical and physical transformations into acidic compounds, which are
subsequently deposited either in wet or dry form at locations distant from the
originating sources of pollution. This acidic deposition causes acidification
of sensitive freshwater lakes and soils, as has become evident in parts of
Eastern North America, adversely affecting various ecosystems.
This paper summarizes the results of a retrosoective emissions
inventory for Canada of SOj and NOX from 1970 to 1980. The inventory of
acid rain precursor pollutants is presented nationally and regionally by major
source sectors and categories. This information is important in understanding
the relationships between releases of pollutants to the atmosphere and
potential environmental effects and in the assessment of control options.
The source categories included in the analysis are industrial
processes, fuel combustion from stationary sources, transportation and all
other important anthropogenic sources. The emissions are calculated from
statistics covering fuel consumption and industrial output by using consistent
methodologies within each sector.
2. DISCUSSION
2.1 Methodology
The emission trends inventory was compiled on a sector level by
province. The emission estimates were then aggregated to give provincial
236
-------
(regional) and national emissions. The calculation procedure by sector can
generally be expressed as:
Emission = Activity Level x Emission Factor
In order to provide a common basis for comparison for the period 1970-1980 it
was necessary that each sector be treated consistently in terms of the statis-
tical data on production, fuel consumption, etc and using the most up-to-date
uncontrolled emission factors as well as the abatement technology utilized by
industry for each year of the analysis.
Most of the industrial production and fuel consumption data were
derived from national statistics compiled and maintained by Statistics Canada
(SC) and the Department of Energy. Mines and Resources (EMR). Emission factors
were obtained primarily from the latest U.S. EPA AP-42 publication and emission
control information was gleaned from the literature and determined from surveys
carried out by the Department of the Environment (DOE). Average sulphur (and
ash) contents of coal were derived from EMR surveys and for liquid fuels, from
information supplied to DOE by fuel producers as a regulatory requirement. For
the non-ferrous smelting sector, historical S02 emission data provided by
individual companies was judged the most representative and was used for this
analysis.
Transportation emissions of $03 and NOX were determined in three
ways: vehicle registration, fuel consumption and use statistics such as take-
off and landing cycles or calls at port. Vehicle registrations were used to
calculate emissions from automobiles and trucks (road vehicles); the emission
factors were developed using software based on ERA'S Mobile 2.
Fuel consumption data were used to calculate the emissions from
railroads as well as off-road diesel and gasoline powered vehicles. Motive
fuels used in railroads were: coal, heavy and light fuel oil and diesel.
237
-------
Average emission rates by engine type were used to calculate the emissions for
aircraft (landing and take-off cycle) and marine (calls at port) sectors. The
numbers of calls at port and LTD (landing and take-off) cycles were obtained
from Statistics Canada.
2.1.1 Sulphur Dioxide
Sulphur dioxide emissions come primarily from two main source cate-
gories, industrial processes and stationary fuel combustion. The trend has
been steadily downward, total national emissions going from 6.7 million tonnes
in 1970 to 4.6 million tonnes in 1980 (Figure 1). Since 1970 S02 emissions
from non-ferrous smelters, the largest emitting sector, have decreased by 44%,
this includes the emissions from primary copper, nickel, lead, zinc and
aluminum. As shown in Figure 2 the industrial contribution to total S02
emissions decreased from 76% in 1970 to 67% in 1980. The stationary fuel
combustion contribution to total S02 emissions rose from 23% in 1970 to 30%
in 1980, however in absolute terms emissions decreased by 11%. Residential,
commercial and industrial (non-utility) fuel combustion S02 emissions
decreased 40% while utility S02 emissions increased 52%.
The decrease in the non-ferrous smelting sector can be attributed to
process improvements, increased pyrrhotite rejection at some operations and the
expansion or addition of acid plants at others. The decreases in the non-
utility fuel combustion emissions can be attributed to reduction of the sulphur
content of fuels, the decline in the use of coal for industrial and residential
use as well as a shift to cleaner fuels like natural gas and light oil.
The power utilities used additional low sulphur coal, introduced coal
blending and coal washing and shifted to alternate electric power generation
technologies. These measures served to limit the increase of sulphur dioxide
emissions to 52%, the total power generation from coal-fired plants increased
by 83% during this time.
238
-------
2.1.2 Nitrogen Oxides
Nitrogen oxides predominantly come from the transportation sectors
and stationary fuel combustion categories. The 30% increase in national emis-
sions during the period 1970-1980 (Figure 3) generally reflects the increase in
energy demand or fuel consumed throughout the decade. The relative amounts, as
seen from Figure 4, contributed by each category to total emissions has
remained essentially the same. Mitrogen oxides from stationary fuel combustion
were largely uncontrolled.
In transportation, there was an increase in NOx emissions from
light-duty vehicles from 1970 to 1980. The enactment of light-duty vehicle
regulations in the early seventies had a moderating effect on this increase.
As the older uncontrolled vehicles are removed from the total fleet the ''per
vehicle" emissions decreased substantially however this trend is offset by the
increasing vehicle population. The increase in transportation emissions was
36% with the largest percentage increases occurring in uncontrolled heavy duty
vehicles such as trucks, off-road diesel engines, aircraft ar.d marine
equipment.
The 20% increase in nitrogen oxide emissions from stationary fuel
combustion was incurred mainly because of a 60% increase in utility emissions.
Despite a growing population, non-utility fuel combustion emissions were
unchanged from 1970 to 1980; this reflects the change in fuel use patterns to
natural gas and electricity and energy conservation practices. During the
seventies Canadian utilities heavily promoted electricity for industrial and
home use while government grant programs were instrumental in the rapid expan-
sion and improvement of the gas pipeline distribution systems especially in
central and eastern Canada.
239
-------
3. CONCLUSION
National emission trends of sulphur dioxide and nitrogen oxides have
been presented for the period 1970 to 1980. The emissions of sulphur dioxide
have steadily declined with the major decrease occurring in the non-ferrous
smelting sector. Nitrogen oxides have increased reflecting the general
increase in energy demand, the contribution from transportation and stationary
fuel combustion having increased at an equivalent rate.
Due to the limitations inherent in a retrospective emissions inven-
tory exercise it should be stressed that the data are more suited to the study
of emission trends. If comparisons tc other studies are made, a prudent basis
for comparison would be on the degree of change in the emissions.
240
-------
National Sulphur Dioxide Emission Trends
7000
6000
5000
4000 \
3000
,000 tonnes
2000H
r
1000h
L
OL
1970
S02
j
1972
1974 1976
Year
Figure 1
1978
1980
-------
DISTRIBUTION
OF S02
1970
EMISSIONS
NON-FERROUS 54-. 9%
3665
FERROUS 5..&r.,
385 \.
FOSSIL FUEL 13.2
885
OTHER I NDUSTR t 1 . 6X
110
TRANSPORTATION 1.3X
85
NON-UTILITY 15.7%
1050
UTILITIES 7.5X
500
Ki I otonnes
DISTRIBUTION OF S02 EMISSIONS
1980
NON-FERROUS 4-4.9%
2070
FERROUS 5.4%
250
FOSSIL FUEL 13.9X
640
OTHER INDUSTRI 2
TRANSPORTATION 3.OX
140
NON-UTILITY 1 3.5X
625
130
UTILITIES 16.5X
760
f i gure 2
-------
National Nitrogen Oxides Emission Trends
N02
,000
1800r
i-
1600JJ-
1400L
1200
1000
800
600^-
400 £-
i-
2001-
oL
tonnes
1970
1972
1974 1976
Year
Figure 3
1978
1980
1
H
•n
1
H
i
-------
DISTRIBUTION OF NOX EMISSIONS
1970
NON-UTILITY 25.7%
LIGHT DUTY 21.1%
VEHICLES 280
UTILITIES 12.1X
160
OTHER INDUSTRY 2.
30
9.15S AIR/RAIL/MARINE
120
29.8X OTHER TRANSPORTATION
395
K1 lotonnes
1980
NON-UTILITY 19.5X
335
LIGHT DUTY 20.7X
VEHICLES 356
UTILITIES 15.1X
260
OTHER INDUSTRY 2.9!
50
10.5X AIR/RAIL/MARINE
180
540
OTHER TRANSPORTATION
FIGURE 4
-------
UNITED KINGDOM EMISSION INVENTORIES
H. S. Eggleston
G. Mclnnes
Warren Spring Laboratory
Stevenage, Herts.
United Kingdom
Presented at:
Second Annual Acid Deposition Emission Inventory Symposium
Charleston, South Carolina
November 12-14, 1985
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UNITED KINGDOM EMISSION INVENTORIES
by: H. S. Eggleston
G. Mclnnes
Warren Spring Laboratory
Stevenage, Herts.
United Kingdom
ABSTRACT
Warren Spring Laboratory (WSL) is an environmental/industrial research
e tablishment of the United Kingdom Department of Trade and Industry. WSL's
Air Pollution division is a major center for research on the physical and
chemical aspects of air pollution in the United Kingdom and covers emission,
dispersion and ambient air quality. National emission estimates for S0_,
NO , CO and VOC have been made for several years. A new project is now in
progress to produce spatially disaggregated emission inventories for the
United Kingdom. Estimates of SO- have been made and work is proceeding to
cover other pollutants, initially NO and VOC. The disaggregated
inventories will be based on a relational data base which, in addition to air
quality information, will contain emission information on large plants and
estimates of area emissions mainly on a 20 x 20 km grid basis using emission
information and surrogate statistics to cover smaller emission sources.
Emissions from fuel combustion as well as from industrial processes and
evaporative emissions are included using, where available, emissions factors
based on emission measurements made under United Kingdom conditions by WSL
and others. The emissions data base will be used by WSL primarily in
numerical dispersion modeling of urban and longer range transport, chemical
reactions and depositions, as well as assisting in the assessment and
interpretation of the data from the national United Kingdom monitoring
networks for acid deposition, smoke, S02, N0x, and ozone, coordinated by
WSL.
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UNITED KINGDOM EMISSION INVENTORIES
INTRODUCTION
Warren Spring Laboratory (WSL) is a research establishment of the
United Kingdom Department of Trade and Industry whose interests cover
environmental and industrial fields. The Air Pollution division is a major
center for research on the physical and chemical aspects of air pollution in
the United Kingdom and covers emission, dispersion and ambient air quality.
Current research topics include the measurement of combustion and process
emissions from mobile and stationary sources, modeling of air pollution, and
the operation and coordination of monitoring networks measuring smoke and
SO-, acid deposition, NO , ozone, hydrocarbons and suspended particulates
including lead. New projects are the construction of a national automated
network of NO and ozone measurement sites, the development of spatially
disaggregated emission inventories and the creation of a new computer system
based on a relational data base. The data base will include information
held by WSL on emissions and related statistics, measurements of air quality
and deposition, meteorological data and other relevant information.
Tha different monitoring networks are designed for a variety of
purposes. The smoke and sulphur dioxide monitoring networks were created in
1961. They provide daily measurements and are voluntarily operated sites
coordinated by WSL. The aim was to provide baseline information about the
distribution and trends of smoke and S02 in the United Kingdom. This was
reorganized in 1982 into a number of networks with separate aims.
Continuous monitoring of NO, N02> CO, 03 and S02 also is undertaken by WSL.
Sites representative of urban and rural situations have been monitored for
up to 10 years. The results of these surveys are published and summaries
are given in the DOE Digest of Environmental Protection and Water
Statistics. The continuous monitoring network is being extended with the
construction of a network of fully automatic N0x/0j monitoring stations.
There is also a national network of sites measuring pollution concentration
247
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in rain. A network of remote rural sites collects samples of precipitation
and these are analyzed for a variety of ions. These results plus sulphur
measurements form the United Kingdom input to the United Nations Economic
Commission for Europe's European Monitoring and Evaluation Program
investigating the long-range transport of air pollutants.
EMISSION INVENTORIES
National Aggregates
For several years WSL has estimated national emissions of S0?, NO , CO
w A
and hydrocarbons in the United Kingdom. These estimates are mainly based on
emissions from fuel combustion, but they do include estimates of emissions
from other sources. Originally, the emission factors used relied heavily on
American data but now most are based in measurements made under United
Kingdom conditions by WSL and others. These estimates were published in the
Department of the Environment Digest of Environmental Protection and Water
Statistics (Reference 1).
Emissions of SO- since 1960 are shown in Figure 1. The emissions were
about 6 million tonnes during the 1960s, but have not fallen by about
40 percent to 3.54 million tonnes in 1983. This has been due to the large
reduction in low and medium level sources and has resulted in a reduction in
average urban levels of S0? of over 70 percent. This reduction is still
continuing and the total emissions have fallen by nearly 25 percent since
1980.
The estimates of emissions for 1983 are shown in Table 1. These
figures show clearly the most significant sources of each pollutant. Over
70 percent of SO. is emitted from power stations and most of the remainder
from industrial sources. The largest sources of NO are power stations and
road transport both emitting about 40 percent of the total. Road vehicles
also account for nearly 84 percent of the CO and are a significant source of
non-methane hydrocarbons emitting a similar quantity to solvent evaporation
and industrial processes.
Recent measurements, made on 72 commercial and industrial boilers in
Scotland (Walker et al., Reference 2), with sizes between 430 and 14,200 kW,
have resulted in the adoption of new emission factors for NO , CO and VOC.
248
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Comparison of the factors with the previously used factors is complicated
because the study used different size ranges for the boilers. However, the
factors used to calculate the national emissions have been altered as shown
in Tdble 2.
Many of the factors are only altered slightly, but for some there are
more substantial differences. As a result of these changes, the estimate of
emissions from commercial and industrial fuel consumption has changed. A
comparison is shown in Table 3 for the year 1982.
Until 1983, vehicle emissions were estimated on the same basis as
emissions from stationary sources by applying an emission factor to the
total fuel consumed. However, as emissions from vehicles are related to the
speed of the vehicle and the manner in which it is driven as well as the
amount of fuel consumed, this method took no account of varying patterns of
road use. Measurements on the road, rather than on a dynamometer, were made
by WSL of emissions from motor vehicles at a range of speeds so that the
variation of emission with speed could be determined (Potter and Savage,
Reference 3). Emission factors for pollutant emission per kilometer driven
at each speed could then be estimated. The sample of cars tested was chosen
to reflect the makeup of the United Kingdom car fleet. Road traffic
statistics give the number of vehicle-kilometers driven on different types
of roads and the average speeds of different categories of vehicles.
Measurements of vehicle speeds in the United Kingdom indicate that the
distribution of vehicle speed about the mean is approximately gaussian with
a standard deviation of one-sixth of the mean. This enables a speed
distribution for a particular type of road to be calculated and then using
the measured speed-related emission factors, the emissions can be estimated
(Reference 4). Emissions estimated using this method have the advantage
that they reflect the types of roads and driving patterns and are sensitive
to any changes in them. A comparison of the results obtained using the
single emission factor method and the new speed-related method is given in
Table 4.
Data Base
WSL has recently installed a new GEC 63/30 computer running the AT&T
UNIX System 5 operating system. It has 8 M bytes of random access memory,
over 1 G byte of backing store and is accessed through an open-system local
249
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area network which is also connected to other computers and services. A
relational data base management system, MISTRESS, has also been purchased
and will be usod to store the national air pollution data base.
The data base will be central to the work of the air pollution division
of WSL. It will store all the information relating to air pollution:
ambient air monitoring, acid deposition measurements and meteorological data,
was well as emission inventories. The system is illustrated in Figure 2,
Data will be processed into the data base and will be available for
comparison with other data or with model results. The emissions data will
be collected in separate data base files along with surrogate statistics.
Only completed and validated inventories will be stored in the main data base
and be available for general interrogation and input to modeling programs.
The data base will be linked to statistical and graphical packages as well
as report writing facilities. The system, which should be fully operational
in the first half of 1986, will provide an integrated and comprehensive
package of retrieval, presentational and analytical routines.
Spatially Disaggregated Inventories
The estimation of spatially disaggregated inventories for the United
Kingdom is a new project started this year. The inventories are to be
prepared on a 20 x 20 km grid for the whole United Kingdom but smaller grids
will be used for some areas.
A few local authorities have compiled local, spatially disaggregated
inventories and these are being collected by WSL. They are mainly compiled
from questionnaires to local firms and estimates of local fuel consumption
in various sectors. These can be used as direct input to the national
inventories but will also be used to help validate the disaggregation
procedures adopted to provide information for the United Kingdom as a whole.
The Greater London Council has compiled an inventory for London in 1976
and is in the process of updating this. Sheffield and Coventry have
inventories for S02 in 1983, compiled from fuel use information.
There is no comprehensive national program for the routine measurement
of emissions in the United Kingdom, so that there are very few actual
emission measurements available for inclusion in an emission inventory.
Emissions, therefore, must be estimated from other information available
250
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about individual sources or by using surrogate statistics. Uhere
appropriate, emission sources will be stored as point sources within the
data base, otherwise emissions will be aggregated on an area basis. The
following approaches have been adopted by WSL for the production of the
spatially-disaggregated inventories for the United Kingdom.
Power Stations: most of these are publicly owned and information is
available on type, age, power output and efficiency of individual stations.
Pollutant emission factors can, therefore, be applied to the appropriate
statistic, fuel consumption or power output, in order to estimate emissions
from each station. To date, it has been assumed that 10 percent of the
sulphur in coal is retained in the ash at each station; recent evidence
suggests that this may be a high estimate of retention and investigations
are under way to determine a more realistic figure.
Other industrial sources: directly relevant information on these are
not so readily available. Contact is being established with the relevant
industry associations with a view to obtaining more information on
individual large plant on a voluntary basis and questionnaires are being
used to obtain such information in a consistent and readily usable form. To
date, emissions from large emission source categories, where available, have
been estimated from emission factors and national throughput disaggregated
in proportion to plant capacity to provide estimates of point source
emissions.
Emissions fron other stationary sources including smaller industrial
source categories, commerce, and housing will be treated as area sources.
These emissions will be estimated from spatially disaggregated statistics on
fuel deliveries or from nationally aggregated statistics, for example
production, output or national fuel consumption and then disaggregated using
an appropriate surrogate statistic (e.g., population or employment).
A statistical data base, called PINGAR, is available for petroleum
deliveries into 10 km squares for the whole United Kingdom with densely
populated areas covered at a 1 km resolution. These statistics cover
different fuels and users and provide a basis for estimation of emissions
from all stationary petroleum consumption. While this will not directly
provide data on individual point sourcas, it will locate accurately
251
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consumption within the corract grid square. Other surrogate statistics are
not usually available on a grid basis; an exception is census data for
Scotland. Other statistics which can be used are population and household
density from census returns, land use, employment and agriculture. These
are provided for various areas (e.g., counties) and have to be transposed to
a grid before they can be used. Spatially disaggregated domestic emissions
will be estimated from regional coal consumption and population.
Motor vehicles contribute over 40 percent of the NO and VOC emissions
/\
so considerable effort is necessary to account adequately for these sources.
In London, vehicle counts have been made so that total vehicle kilometers
are available for each borough for motorways and other roads and for peak
and off-peak hours together with average speeds, so it is possible to use
the speed-related emission factors to estimate emissions in each borough.
Outside London, there is less information available on traffic on a
spatially resolved basis, but the Department of Transportation does produce
statistics on vehicle kilometers for each county in the United Kingdom.
Another source of information is the 1981 Census which provides statistics
on the distribution of cars in the country. This will be used to
disaggregate the county estimates.
The emission inventory data base will contain details of individual
point sources source category, location, height, number and size of
stacks, thermal input, abatement details (if present), fuel consumption and
type, period covered by the information, etc., as well as emission
estimates. It will, therefore, be possible to interrogate the data base
using a number of search criteria. For example, emission estimates could be
computer-mapped to show the spatial distribution or used as input to a
predictive model. It will also be possible to use the system to convert the
emission estimates from one spatial-grid system to another.
Sulphur Dioxide
Using the above mentioned approaches, an emission inventory for SO, on
a 20 x 20 km grid, based on the United Kingdom's Ordinance Survey grid, has
been produced for 1983 and is shown in a graphical form in Figure 3.
252
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Nitrogen Oxides
The production of a disaggregated inventory for NO involved a similar
approach to that for S02 with the major difference being that more effort
was required to account for emissions from vehicle sources as motor vehicles
contribute dbout 40 percent of the emissions. The accuracy of the
disaggregated inventory will be dependent on the method used to distribute
these emissions across the grid cells. Using the method described aoove, a
first estimate has been made and this could be further refined with the use
of more appropriate traffic statistics.
Other Inventories
The most important of these will be the hydrocarbon inventory. The two
main sources are vehicles, which are dealt with as above, and evaporative
and process emissions. The latter will be difficult to quantify accurately
in a spatially disaggregated inventory due to both the lack of individual
plant or area production/consumption data and reliable emission factors for
individual hydrocarbons. For the foreseeable future, surrogate statistics
(e.g., industrial floorspace or employment in particular industrial sectors)
and bulk hydrocarbon emission factors will continue to be used.
Active consideration is being given to other pollutants such as NH,.
This will require further study to determine the major sources and the best
statistics that are available to describe them.
Another long-term aim is to provide temporal disaggregation of
emissions. Relevant information is being collected, but such refinements
will take second priority to the annual inventories.
CONCLUSIONS
Spatially disaggregated emission inventories are being produced for a
variety of atmospheric pollutants. In the United Kingdom, surrogate
statistics have to be used to overcome the scarcity of emission
measurements. Future work will involve the establishment of inventories of
other pollutants and the estimation of temporally disaggregated inventories,
as well as the refinement of existing inventories.
253
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This work will be integrated via the new data base system with
monitoring and modeling of air pollution in the United Kingdom and Europe to
improve our understanding of the dispersion and deposition of atmospheric
pollutants.
254
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REFERENCES
1. Digest of Environmental Protection and Water Statistics No. 7 (1984),
HMSO, London, United Kingdom.
2. Walker, D.S., Galbraith, R., and Galbraith, J.M., Warren Spring
Laboratory, Report LR 524 (1985), Survey of Nitrogen Oxides, Carbon
Monoxide and Hydrocarbon Emissions from Industrial and Commercial
Boilers in Scotland.
3. Potter, C.J., Savage C.A., Warren Spring Laboratory, Report LR 470
(1983). A Survey of Gaseous Pollutant Emissions from Tuned In-Service
Gasoline Engined Cars over a Range of Road Operating Conditions:
Executive Summary.
4. Rodgers, F.S.M., Warren Spring Laboratory, Report LR 508 (1984), A
Revised Calculation of Gaseous Emissions from United Kingdom Motor
Vehicles.
255
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TABLE 1. NATIONAL EMISSIONS OF AIR POLLUTANTS 1983 (MILLION TONNES)
SO,,
Mt %
By Fuel:
Coal
Solid Smokeless
Motor Spirit
DERV
Burning Oil
Gas Oil
Fuel Oil
Refinery Fuel
All Gas
Bv Consumer:
Domestic
Commercial/Public Service
Power Stations
Refineries
Agriculture
Other Industry
Rail Transport
Road Transport
Incineration
Process and Evaporation
TOTAL
2.
0.
0.
0.
-
0.
0.
0.
-
0.
0.
2.
0.
-
0.
-
0.
-
-
3.
81
10
02
03
-
05
53
16
-
19
14
53
16
-
52
-
04
-
-
72
76
3
--
1
--
2
14
4
--
5
4
68
4
--
17
--
1
--
--
0
0
0
0
0
NO
Kt
.80
.04
.52
.19
--
.06
0.09
0
0
0
0
0
0
0
0
0
0
1
.03
.08
.05
.04
.76
.03
--
.18
.04
.70
.01
--
.85
A
%
43
2
28
10
--
3
5
2
4
3
2
41
2
--
10
2
38
1
--
0
0
3
0
0
0
0
0
0
0
0
0
4
0
5
CO
Mt %
.37 7
.20 4
.99 79
.25 5
.-
.02 --
.01 --
.-
.01 --
.46 9
.01
.05 1
--
-.
.07 1
.01
.23 83
.22 4
--
.08
VOC
Mt
0.08
--
0.49
0.04
--
0.01
--
--
--
0.07
--
0.01
--
--
--
0.01
0.53
0.04
0.60
1.27
%
6
--
39
3
--
1
--
--
--
6
--
1
--
--
1
42
3
47
Note: The figures are mainly based on fuel related emission factors and will
underestimate the emissions from industrial processes of all but VOCs. This
will only be a few percent of the total emissions. The total for hydrocarbons
excludes leakage from the distribution system. This is mainly methane and
amounted to about 2.2 million tonnes in 1983.
256
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TABLE 2. COMPARISON OF "OLD" AND "NEW" COMMERCIAL
AND INDUSTRIAL EMISSION FACTORS
Emission Factor
(g/kg or Gas kq/Mtherm)
N0v
X
CO
voc
Fuel
Coal
Solid Smokeless
Gas Oilc
Fuel Oil
Natural Gas
Coal
Solid Smokeless
Gas Oilc
Fuel Oil
Natural Gas
Coal
Sol id Smokeless
Gas Oil
Fuel Oil
Natural Gas
"Old"a
7.79
7.79
2.6
7.5
5280
6.64
6.64
0.24
0.5
247.5
0.115
0.115
0.07
0.06
165.0
"New"5
4.8
4.8
2.6
7.4
5340
4.1
4.1
0.24
0.50
250.0
0.07
0.07
0.07
0.06
153.0
aThe "old" factors are based on U.S. ERA factors, but they have been updated
to take into account previous measurements in the United Kingdom.
bThe "new" factors result from a series of measurements made on United
Kingdom boilers (Reference 2).
GThe factor for Gas Oil has not been updated as too few measurements were
made to provide an accurate figure, however, the measurements agreed with
the "old" value rather than with the U.S. EPA factor.
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TABLE 3. EMISSIONS FROM COMMERCIAL AND INDUSTRIAL FUEL CONSUMPTION 1983
Emission (k tonnes)
01da Newb
NOV 221 (13%)c 187 (11%)
A
CO 82 (1.6%) 54 (1.1%)
VOC (non-methane) 4 (0.3%) 3.2 (0.2%)
a01d refers to the U.S. EPA based (but modified by United Kingdom measure-
ments) factor.
New refers to the factor based on measurements made in the United Kingdom.
GThe numbers in brackets are percentages of the national total emission.
TABLE 4. EMISSIONS FROM MOTOR CARS (1983)
N0x
CO
VOC
Single
Emission Factor
508
8107
538
Speed
Related Factors
725
4502
538
a(k tonnes).
258
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level emmert
Medum level emmei
Low l«v«l emitters
Power stations
R« Trie net
Otfief nduslry
Oiher non domestic
Domesoc
CONCENTRATION
WOEX
1981/82-100
r- 320
-120
1974
1976
1978 1980 1982
1984
Emmioni from fuel combuitton only. E*dud« emunoni Ifom Source. Wtmn Spring Ltttorttory, D*p*rrm»or of Tr#Jt *nd Industry
chemicel «r»t»b(f throughouT th* 196Oi ind eerly I970l »t about 6 I oni hgv* fallen by over 70 p«r cent irnc« 1962. m line wrth the reduc-
million tonne* • y*»' After 1973 however, ennuel emunoni fell to tion in emmioni from low-level wurcet (tee T§b»* 2 4 end Addmonel
•bout S mrllion tonnet in 1976. 1977 »nd 1978, to 4 0 milhon tonnri Tablet A1 and A3).
Figure 1. Sulphur dioxide emissions froiji fuel combustion and
average urban concentrations.
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Figure 2.
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20 x 20 km grid
Scale: 1=346.5 tonnes
•i i
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APPENDIX
ATTENDEES
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SECOND ANNUAL ACID DEPOSITION SYMPOSIUM
LIST OF ATTENDEES
1. Linda Allison
ORNL/AODNET
Oak Ridge National Laboratory
Post Office Box X, Building 1505
Oak Ridge, TN 37831
(615) 576-5454
2. Wil1iam Bain
Tennessee Valley Authority
445 Chestnut Street, Tower 2
Chattanooga, TN 37401
(615) 751-0011
3. David Beecy
U.S. OOE/Office of Fossil Energy, FE-13
Washington, DC 20545
(301) 353-2617
4. Carmen Benkovitz
Brookhaven National Laboratory
Building 51
Upton, NY 11973
(516) 282-4135
5. Chris Bergesen
Utility Data Institute
2011 I Street, S.W., #700
Washington, DC 20006
(202) 466-3660
6. John Bosch
Office of Air Quality Planning and Standards
U.S. EPA (MD-14)
Research Triangle Park, NC 27711
(919) 541-5582
7. Art Braswell
South Carolina Department of Health
and Environmental Control
2600 Bull Street
Columbia, SC 29201
(803) 758-5406
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8. Lyle Chinkin
Systems Applications, Inc.
101 Lucas Valley Road
San Rafael, CA 94903
(415) 472-4011
9. Christian Cleutinx
Commission of the European Communities
2100 M Street, N.W.
Washington, DC 20037
(202) 862-9570
10. David Davies
Environment Canada
West Isle Office Towers
2121 Trans Canada Highway
Dorval, Quebec, Canada H9P 1J3
(514) 636-3026
11. Jim Democker
Office of Air and Radiation
U.S. EPA
401 M Street, S.W.
Washington, DC 20460
(202) 382-5580
12. Alan Dresser
Colorado Air Pollution Control Division
4210 East llth Aven'ie
Denver, CO 80220
(303) 331-8524
13. Simon Eggleston
Warren Spring Laboratory
Department Trade and Energy U.K.
Gunnels Wood Road
Stevenage, Hertsfordshire SG123Y
Phone: Stevenage 71887
14. J.M. Ekmann
U.S. DOE/Pittsburgh Energy Technology Center
Post Office Box 10940
Pittsburgh, PA 15236
15. Todd Ellsworth
State of Maryland
Air Management Administration
201 West Preston Street
Baltimore, MO 21201
(301) 383-3245
263
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16. Fred Fehsenfeld
NOAA/ERL Aeronomy Laboratory
Mail Code R/E/AL6
325 Broadway
Boulder, CO 80303
(303) 497-5819
17. Elizabeth Field
Florida Department of
Environmental Regulation
2600 Blairstone Road
Tallahassee, FL 32301
(904) 487-1855
18. Bob Friedman
Office of Technology Assessment
U.S. Congress
Washington, DC 20510
(202) 224-8713
19. Douglas Fulle
EBASCO Services, Inc.
145 Technology Park
Norcross, GA 30092
(404) 449-5800
20. William Gill
Texas Air Control Board
6330 Highway 290E
Austin, TX 28723
(512) 451-5711
21. Dale Gillette
NOAA R/E/AR4
325 Broadway
Boulder, CO 80303
(303) 494-3842
22. Paul Goldan
NOAA/ERL
325 South Broadway
Boulder, CO 80303
(303) 497-3814
23. Gerhardt Gschwandtner
Pacific Environmental Services
1905 Chapel Hill Road
Durham, NC 27707
(919) 493-3536
264
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24. Steven Heisler
ERT
975 Business Center Circle
Newbury Park, CA 91320
(805) 499-1922
25. Merrill Heit
U.S. DOE
Environmental Measurements Laboratory
376 Hudson Street
New York, NY 10014
(212) 620-3625
26. George Hendrey
Brookhaven National Laboratory
Terrestrial and Aquatic Ecology Division
Building 318
Upton, NY 11973
(516) 282-3262
27. Edward Hi!Isman
Oak Ridge National Laboratory
Post Office Box X, Building 4500N
Oak Ridge, TN 37831
(615) 574-5938
28. Andy Hoffer
Ontario Hydro
700 University Avenue (H10D 2)
Toronto, Ontario, Canada M5G 1X6
(416) 423-7508
29. James Homolya
Radian Corporation
Post Office Box 13000
Research Triangle Park, NC 27709
(919) 481-0212
30. Allen Hughes
The Mitre Corporation
1820 Dolley Madison Blvd.
McLean, VA 22102
(703) 883-6064
31. Quang-Tuyen Huynh
J.W. Environmental Data, Inc.
60 Cowan Avenue, Suite 1505
Toronto, Ontario, Canada M4K 3X9
(416) 248-3245
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32. Marty Irwin
Hoosiers for Economic Development
11 South Meridian, Suite 1005
Indianapolis, IN 46204
(317) 632-3952
33. Kurt Jakobson
Office of Research and Development
U.S. EPA
Washington, DC 20460
(202) 382-2583
34. David Johnson
Office of Air Quality Planning and Standards
U.S. EPA (MD-15)
Research Triangle Park, NC 27711
(919) 541-5516
35. Terry Juchnowski
New Jersey Department of
Environmental Protection
CN 027
Trenton, NJ 08625
(609) 292-6704
36. James Kelley
U.S. DOE
Office of Environmental Analysis
Forrestal Building, Room 4G-036
1000 Independence Avenue, S.W.
Washington, DC 20585
(202) 252-8420
37. Ismail A. Khatri
Indiana State Board of Health
1330 West Michigan Street
Indianapolis, IN 46206
(317) 633-8591
38. Stephen Kiel
State of Maryland
Air Management Administration
201 West Preston Street
Baltimore, MD 21201
(301) 383-3245
39. Duane Knudson
Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439
(312) 972-5102
266
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40. Harry Lins
U.S. Geological Survey
410 National Center
Reston, VA 22092
(703) 860-6927
41. Robert Lott
Tennessee Valley Authority
417 Multipurpose Building
Muscle Shoals, AL 35660
(205) 386-2033
42. Gerald Lowry
SAIC
1710 Goodridge Drive
McLean, VA 22102
(703) 821-4555
43. Thomas Lukow
U.S. DOE
Morgantown Energy Technology Center
Post Office Box 880
Collins Ferry Road
Morgantown, WV 26507
(304) 291-4622
44. Terry McGuire
California Air Resources Board
Post Office Box 2815
Sacramento, CA 95821
(916) 322-2990
45. Charles 0. Mann
Office of Air Quality Planning and Standards
U.S. EPA (MD-14)
Research Triangle Park, NC 27711
(919) 541-5694
46. Mike Maxwell
Air and Energy Engineering Research Laborator
U.S. EPA (MD-61)
Research Triangle Park, NC 27711
(919) 541-3091
47. Deborah Metrin
Florida Department of
Environmental Regulation
2600 Blairstone Road
Tallahassee, FL 32301
(904) 488-0870
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48. David Mobley
Air and Energy Engineering Research Laboratory
U.S. EPA (MD-61)
Research Triangle Park, NC 27711
(919) 541-2612
49. Frank Noonan
Office of Air Quality Planning and Standards
U.S. EPA (MD-14)
Research Triangle Park, NC 27711
(919) 541-5585
50. Joan Novak
Atmospheric Sciences Research Laboratory
U.S. EPA (MD-80)
Research Triangle Park, NC 27711
(91S) 541-4545
51. William Oliver
Radian Corporation
10395 Old Placerville Road
Sacramento, CA 95827
(916) 362-5332
52. Dale Pan!
Air and Energv Engineering Research Laboratory
U.S. EPA (MD-"l)
Research Triangle Park, NC 27711
(919) 541-5578
53. Diana Parker
Kentucky Department of
Environmental Protection
18 Reilly Road
Fort Boone Plaza
Frankfort, KY 40601
(502) 564-3382
54. Stephen Pearl
Public Service Indiana
1000 East Main Street
Plainfield, IN 46168
(317) 838-1758
55. Edward Pechan
E.H. Pechan and Associates
5537 Hempstead Way
Springfield, VA 22151
(703) 642-1120
268
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56. David Powell
Battelle Pacific Northwest Laboratory
2400 Stephens
Richland, WA 99352
(509) 375-3888
57. Brian Price
The Mitre Corporation
1820 Dolley Madison Blvd.
McLean, VA 22102
(703) 883-6064
58. James Reagan
Atmospheric Sciences Research Laboratory
U.S. EPA (MD-20)
Research Triangle Park, NC 27711
(919) 541-4480
59. David Roberts
Washington Department of Ecology
PV-11
Olympia, WA 98504
(206) 459-6000
60. Trevor Scholtz
MEP Company
7050 Woodbine Avenue, Suite 100
Markham, Ontario, Canada L3R 4G8
(416) 477-0870
61. Paul Schengels
Office of Air and Radiation
U.S. EPA (AR-445)
Washington, DC 20460
(202) 475-8468
62. Frederick M. Sellars
GCA/Technology Division
213 Burlington Road
Bedford, MA 01730
(617) 275-5444
63. Butch Smith
Midwest Research Institute
5405 Creedmoor Road
Raleigh, NC 27612
(919) 781-5750
64. Lowell Smith
Office of Research and Development
U.S. EPA (RD-676)
Washington, DC 20460
(202) 382-5717
269
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65. Douglas Toothman
Engineering Science
10521 Rosehaven Street
Fairfax, VA 22030
(703) 591-7575
66. E.C. Trexler
Office of Fossil Energy
U.S. DOE (FE-13)
Washington, DC 20545
(301) 353-2683
67. C. Veldt
Division of Technology, Society TNO
Post Office Box 342
7300 AH Apeldoorn
The Netherlands
055-773344
68. Frank Vena
Environment Canada
14 Floor, Place Vincent Massey
Ottowa, Ontario, Canada K1A 1C8
(819) 994-3127
69. Ron Whitfield
Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439
(312) 972-8430
70. Joan Willey
University of North Carolina at Wilmington
Chemistry Department
601 South College Road
Wilmington, NC 28403
(919) 395-3459
71. Simon Wong
Ontario Ministry of Environment
Air Resources Branch
125 Resources Road, East Wing
Rexdale, Ontario, Canada T6B 2X3
(416) 248-3245
72. Daniel Woo
Environment Canada
4999 98th Avenue
Edmonton, Alberta, Canada T6B 2X3
(403) 468-8031
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