>vEPA
United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park. NC 27711
EPA-454/R-93-021a
May 1993
Air
REGIONAL INTERIM
EMISSION INVENTORIES
(1987-1991)
VOLUME I: DEVELOPMENT METHODOLOGIES
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EPA-454/R-93-021a
REGIONAL INTERIM
EMISSION INVENTORIES
(1987-1991)
VOLUME I: DEVELOPMENT METHODOLOGIES
Office Of Air Quality Planning And Standards
Office Of Air And Radiation
U. S. Environmental Protection Agency
Research Triangle Park, NC 27711 U.S. Environment , .--?'.! jn Agency
Region 5, Library VPL-1?J)
May 1993 77 West Jackson Boulevard, 12th Floor
J Chicago, IL 60604-3590
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This report has been reviewed by the Office Of Air Quality Planning And Standards, U. S. Environmental
Protection Agency, and has been approved for publication. Any mention of trade names or commercial
products is not intended to constitute endorsement or recommendation for use.
EPA-454/R-93-021a
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FOREWORD
The purpose of these interim inventories is to provide a preliminary base year
regional inventory from which Regional Oxidant Modeling (ROM) can be performed in
support of the State Urban Airshed Modeling (UAM). The primary reason for releasing
these inventories at this time is to allow for comparison between the emissions data
currently being used in ROM and the State emissions data submitted into AIRS and being
used in the UAM State Implementation Plan applications.
EPA's long term plan is to incorporate the State submitted emissions data from AIRS
into these interim inventories thereby assuring that the ROM modeling and UAM
modeling are based on consistent inventories. In releasing these inventories now, before
this full incorporation is complete, we hope to avoid any major problems in unknown data
inconsistencies which may occur due to the differences in the two data sets.
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ACKNOWLEDGEMENTS
This report describes the development of Interim Regional Emission Inventories for
the years 1987 - 1991, a project administered by the U.S. Environmental Protection
Agency (EPA) Office of Air Quality Planning and Standards (OAQPS). The project has
been a cooperative effort involving personnel from both the OAQPS Emission Inventory
(EIB) and Source Receptor Analysis (SRAB) Branches.
Principal data gathering, computer analysis and quality assurance were performed by
E.H. Pechan and Associates, Incorporated and EC/R Incorporated under EPA Contract No.
68-DO-0120, Work Assignment No. 11-60. Chet Wayland of SRAB was the principal Work
Assignment Manager. David Mobley, Steve Bromberg, and David Misenheimer of the EIB
and Norm Possiel of the SRAB also contributed to this effort.
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ICUTTVE SUMMARY
The Clean Air Act Amendments of 1990 (Act) require many States to perform urban
scale modeling analyses to demonstrate that proposed control strategies are sufficient to
attain the National Ambient Air Quality Standard (NAAQS) for ozone. Results obtained
with urban models may be sensitive to assumptions made about pollution transported into
the urban modeling domain. Thus, the Environmental Protection Agency (EPA) will be
running the ROM to provide base and future year boundary conditions. For the base
year, this entails multiple ROM runs covering approximately 180 episode days over a 5
year period (1987-91). For the future base year modeling, attainment years 1996, 1999,
2005 and 2007 will need to be modeled. To support ROM runs, an emission inventory is
needed for the regional airshed. Since States are not required to develop or submit State-
wide emission inventories for all source categories and since nonattainment area emission
inventories are not required to be submitted and approved in a time-frame to support
ROM runs, EPA developed an interim emission inventory for 1987 to 1991 base years.
The 1987 - 1991 Interim Regional Emission Inventories are composed of annual,
county-level estimates by source category of point, area and mobile source emissions. The
methodologies used in developing these components are discussed in detail in "1987-1991
Interim Regional Emission Inventories: Volume I, Development Methodologies". "Volume
II, Interim Emissions Summary", contains summaries of the results. "Volume III,
Incorporation Methodologies", will describe methodologies to incorporate the State data
into the interim data. "Volume IV, Emissions Summary", will present results from State
submittals and EPA estimates. Volumes III and IV should be released later this year.
Because urban model performance will be evaluated for episodes in 1987-91, a
regionwide inventory must be available for use in ROM for each of these years. This
regional inventory is labeled as a "interim inventory", because the plan is to ultimately
incorporate the State 1990 submittals into the 1990 interim regional inventory to ensure
that the ROM and the UAM are using emissions data which are as similar as possible.
Areas where State submittals are not available or required would be covered by the
interim inventory.
Initially, the base year ROM runs (1987-91) will be based entirely on the interim
regional inventory in order to provide timely information to States for their evaluation of
urban model performance. The future year (1996, 1999, 2005, 2007) ROM runs will be
based on a revised version of the 1990 interim inventory which includes as much State
data as can be included by the time the modeling must begin.
As previously noted, the interim regional inventories are not intended to replace the
State inventory submittals. Further, the 1987 - 1991 interim regional inventories are
county-level, annual emission estimates (i.e., they include no activity data or emission
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factor data.) Thus, the information provided by the interim inventory is not compatible
with the information required for AIRS submittals.
A summary of how the 1987 - 1991 interim regional inventories have been derived
follows.
• Point Source Data:
Fossil-Fuel Steam Utilities
Derived from Forms EIA-767 and EIA-759 for each year (1987-91)
Non-Utility Point
Projected from 1985 NAPAP Inventory values for each year ('87-'91)
• Area Source Data:
Solvents
Solvent usage estimates obtained for 1989 and backcasted/projected for
each year ('87-'88, '90-'9D based on U.S. Paint Industry Data Base and
Industrial Solvent Marketing reports
Other Area Sources
Projected from the 1985 NAPAP Inventory for each year ('87-'9D using
Bureau of Economic Analysis (BEA) earnings and population data and
State Energy Data System (SEDS) fuel consumption data
Off-Highway Sources
Based on EPA's 1990 off-highway emission estimates and
projected/backcasted using BEA data for other years ('87-89, '91)
• Mobile Source Data:
Vehicle Miles Traveled (VMT)
Federal Highway Administrations's Highway Performance Monitoring
System (HPMS) for all years C87-'91)
Mobile Emission Factors
EPA's MOBILES Mobile Source Emission Factor Model for all years ('87-
'91)
This methodology should produce an emission inventory which presents a reasonable
representation of aggregate emissions from a large geographic area. The results for a
given source or locality (e.g., nonattainment area) cannot be as accurate as estimates
derived from site-specific information. Therefore, caution should be exercised in any
interpretation or use of information from the interim inventory.
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ABBREVIATIONS AND ACRONYMS
AADT
AAR
AFS
AIRS
AMS
APCD
ASTM
BEA
Btu
CAA
CCME
CNOI
CO
CTG
DOE
EIA
Effi
EPA
ERCAM-VOC
FAA
FGD
FGDIS
FHWA
FID
FIPS
FREDS
FTP
GIS
GT
HDDV
HDGV
HPMS
1C
I/M
LDDT
LDDV
LDGT
LDGV
LTO
MPG
MPH
MVMA
MW
NAAQS
NADB
NAPAP
average daily traffic
American Association of Railroads
AIRS Facility Subsystem
Aerometric Information' Retrieval System
Area and Mobile Source Subsystem
air pollution control district
American Society for Testing and Materials
Bureau of Economic Analysis
British thermal unit
Clean Air Act
Canadian Council of Ministers for the Environment
Census Number of Inhabitants
carbon monoxide
Control Techniques Guideline
Department of Energy
Energy Information Administration
Emission Inventory Branch
Environmental Protection Agency
Emission Reduction and Cost Analysis Model for Volatile Organic
Compounds
Federal Aviation Administration
flue gas desulfurization
Flue Gas Desulfurization Information System
Federal Highway Administration
Flame lonization Detection
Federal Information Processing Standards
Flexible Regional Emissions Data System
Federal Test Procedure
Geographic Information System
gas turbine
heavy-duty diesel vehicle
heavy-duty gasoline vehicle
Highway Performance Monitoring System
internal combustion
Inspection and Maintenance
light-duty diesel truck
light-duty diesel vehicle
light-duty gasoline truck
light-duty gasoline vehicle
landing-takeoff operations
miles per gallon
miles per hour
'Motor Vehicle Manufacturers Association
megawatt
National Ambient Air Qualify Standard
National Allowance Data Base
National Acid Precipitation Assessment Program
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ABBREVIATIONS AND ACRONYMS (continued)
NEDS
NMOG
NO,
NRC
NURF
OAQPS
PCE
RACT
ROM
RVP
SCC
SEOS
SIC
SIP
S02
SRAB
TIUS
TSDF
UAM
VMT
VOC
WBD
National Emissions Data System
nonmethane organic gas
oxides of nitrogen
National Research Council
National Utility Reference File
Office of Air Quality Planning and Standards
personal consumption expenditures
Reasonably Available Control Technology
Regional Oxidant Model
Reid Vapor Pressure
Source Classification Code
State Energy Data System
Standard Industrial Classification
State Implementation Plan
sulfur dioxide
Source Receptor Analysis Branch
Truck Inventory and Use Survey
Treatment Storage and Disposal Facility
Urban Airshed Modeling
vehicle miles traveled
volatile organic compound
wood-burning device
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REFEREI
AAR, 1991: Association of American Railroads, "Railroad Ten-Year Trends 1981-1990,"
Washington, DC, 1991.
ASTM, 1988: American Society for Testing and Materials, "1988 Annual Book of ASTM
Standards" (Section 5: Petroleum Products, Lubricants, and Fossil Fuels; Volume
05.01: Petroleum Products and Lubricants (I): D56-D 1947), Philadelphia, PA
1988.
Battye, 1987: William Battye, Alliance Technologies Corporation, Chapel Hill, NC,
"Ozone Cost Study Files," memorandum and computer files to Jim Wilson, E.H.
Pechan & Associates, Inc., April 3, 1987.
BEA, 199 la: Bureau of Economic Analysis, "Table SA-5 - Total Personal Income by
Major Sources 1969-1990," data files, U.S. Department of Commerce, Washington,
DC, September 1991.
BEA, 199 Ib: Bureau of Economic Analysis, "Survey of Current Business," U.S.
Department of Commerce, Washington, DC, July 1986, July 1987, July 1988, July
1989, July 1990, July 1991.
BEA, 1992a: Bureau of Economic Analysis, "Table SQ-5 - Quarterly State Personal
Income 1987: I -1991: IV," data files, U.S. Department of Commerce, Washington,
DC, April 1992.
BEA, 1992b: Bureau of Economic Analysis, Survey of Current Business, U.S. Department
of Commerce, Washington, DC, March 1992.
BOC, 1983: Bureau of the Census, "1980 Census of Population, Volume I Characteristics
of Population, Chapter B Number of Inhabitants," U.S. Department of Commerce,
Washington, DC, April 1983.
BOC, 1987: Bureau of the Census, "1987 Census of Agriculture, Volume 1: Geographic
Area Series," county data file, U.S. Department of Commerce, Washington, DC, 1987.
BOC, 1988a: Bureau of the Census, "County Business Patterns," U.S. Department of
Commerce, Washington, DC, 1988.
BOC, 1988b: Bureau of the Census, City/County Data Base, data files, UJ3. Department
of Commerce, Washington, DC, 1988.
BOC, 1990: Bureau of the Census, "1987 Census of Transportation, Truck Inventory and
Use Survey," U.S. Department of Commerce, Washington, DC, August 1990.
CCME, 1990: Canadian Council of Ministers of the Environment, "Management Plan for
Nitrogen Oxides and Volatile Organic Compounds," Phase I, November 1990.
113
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(continued)
Connolly et al., 1990: Connolly et aL, "U.S. Paint Industry Data Base,"
prepared by SRI International for the National Paint and Coatings Association, Inc.,
Washington, DC, 1990.
Corp of Engineers, 1991: UJ3. Army Corp of Engineers, "Waterborne Commerce of the
United States, Calendar Year 1989," WRSC-WCUS-89, Part 5, New Orleans, LA, June
1991.
DOE, 1986: U.S. Department of Energy, Energy Information Administration, "1985
Petroleum Supply Annual," DOE/EIA-0340, Office of Oil and Gas, Washington, DC,
May 1986.
DOE, 1991a: UJ5. Department of Energy, Energy Information Administration, "State
Energy Data Report - Consumption Estimates 1960-1989, "DOE/EIA-02U(89),
Washington, DC, May 1991.
DOE, 1991b: U.S. Department of Energy, Energy Information Administration, "Fuel Oil
and Kerosene Sales 1990," Washington, DC, October 1991.
DOE, 1991c: U.S. Department of Energy, Energy Information Administration, "1990
Petroleum Supply Annual, "DOE/EIA-0340, annual publications for 1985 through
1990, Office of Oil and Gas, Washington, DC, May 1991.
DOE, 1992: U.S. Department of Energy, Energy Information Administration, "Monthly
Power Plant Report," Form EIA-759, data files for 1990 and 1991.
DOE, 1987-1990: U.S. Department of Energy, Energy Information Administration,
"Steam-Electric Plant Operation and Design Report," Form EIA-767, data files for
1987, 1988, 1989, and 1990.
DOE, 1989-1991: U.S. Department of Energy, Energy Information Administration,
"Inventory of Power Plants in the United States 1988,1989, and 1990," Washington,
DC, October 1991.
EC, 1990: Environment Canada, "Eastern Canada Acid Rain Control Program, Draft
Report," Quebec, Canada, 1990.
EPA, 1986: U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, "National Air Pollutant Emission Estimates, 1940-1985," Research
Triangle Park, NC, 1986.
EPA, 1988: U.S. Environmental Protection Agency, "Area Source Documentation for the
1985 NationaLAtid Precipitation Assessment Program Inventory," EPA-600/8-88-106,
Air and Energy Engineering Research Laboratory, Research Triangle Park, NC,
December 1988.
114
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REFERENCES (continued)
EPA, 1989a: U.S. Environmental Protection Agency, The 1985 NAPAP Emissions
Inventory (Version 2): Development of the Annual Data and Modeler's Tapes," EPA-
600/7-89-012a, Air and Energy Engineering Research Laboratory, Research Triangle
Park, NC, November 1989.
EPA, 1989b: U.S. Environmental Protection Agency, Office of Mobile Sources,
"MOBILE4 Fuel Consumption Model (Draft)," Ann Arbor, MI, January 1989.
EPA, 1989c: U.S. Environmental Protection Agency, "User's Guide to MOBILE4 (Mobile
Source Emission Factor Model)," EPA-AA-TEB-89-01, Office of Mobile Sources, Ann
Arbor, MI, February 1989.
EPA, 1989d: U.S. Environmental Protection Agency, TSDF Inventory File, computer file
transferred to E JL Pechan & Associates, Inc., from Emission Standards Division, via
Alliance Technologies, April 1989.
EPA, 1989e: U.S. Environmental Protection Agency, "The 1985 NAPAP Emissions
Inventory (Version 2); Development of the National Utility Reference File, "EPA-
600/7-89-013a, November 1989.
EPA, 1990: U.S. Environmental Protection Agency, "The 1985 NAPAP Emissions
Inventory. Development of Temporal Allocation Factors," EPA-600/7-89-010d, Air and
Energy Engineering Research Laboratory, Research Triangle Park, NC, April 1990.
EPA, 1991a: U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, "National Air Pollutant Emission Estimates 1940-1990," EPA-450/4-91-
026, Research Triangle Park, NC, November 1991.
EPA, 1991b: U.S. Environmental Protection Agency, "Supplement D to Compilation of Air
Pollutant Emission Factors, Volume I: Stationary Point and Area Sources," AP-42,
September 1991.
EPA, 199 Ic: U.S. Environmental Protection Agency, "Inspection/Maintenance Program
Summary," Ann Arbor, MI, July 1991.
EPA, 1991d: U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, "Regional Ozone Modeling for Northeast Transport (ROMNET)," EPA-
450/4-91-002a, Research Triangle Park, NC, 1991.
EPA, 1991e: U.S. Environmental Protection Agency, Office of Mobile Sources, "Procedures
for Emission Inventory Preparation, Volume IV: Mobile Sources," Draft revision,
Chapter 6, Ann Arbor, MI, 1991.
EPA, 1991f: U.S. Environmental Protection Agency, Office of Mobile Sources, "Procedures
for Emission Inventory Preparation, Volume IV: Mobile Sources," Draft revision,
Chapter 5, Ann Arbor, MI, November 1991.
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REFERENCES (continued)
EPA, 1992a: U.S. Environmental Protection Agency, "User's Guide to MOBILES (Mobile
Source Emission Factor Model)," Draft, Chapter 2, Ann Arbor, MI, December 1992.
EPA, 1992b: U.S. Environmental Protection Agency, "Documentation for Estimation of
Nonroad Emission Estimates for the United States," Research Triangle Park, NC,
November 1992.
EPA, 1992c: U.S. Environmental Protection Agency, "Nonroad Engine Emission
Inventories for CO and Ozone Nonattainment Boundaries," Ann Arbor, MI, October
1992.
FAA, 1991a: Federal Aviation Administration, "Air Traffic Activity," U.S. Department of
Transportation, 1991.
FAA, 1991b: Federal Aviation Administration, "Terminal Area Forecasts, FY 1991-2005,"
FAA-APO-91-5, U.S. Department of Transportation, July 1991. _
FHWA, 1985: Federal Highway Administration, "Traffic Monitoring Guide," U.S.
Department of Transportation, Washington, DC, June 1985.
FHWA, 1987a: Federal Highway Administration, "Highway Performance Monitoring
System Field Manual," U.S. Department of Transportation, Washington, DC,
December 1987.
FHWA, 1987b: Federal Highway Administration, "Highway Performance Monitoring
System Analytical Process, Volume H — Version 2.1 Technical Manual," U.S.
Department of Transportation, Washington, DC, December 1987.
FHWA, 1991: Federal Highway Administration, "Highway Statistics 1990," U.S.
Department of Transportation, Washington, DC, November 1991.
FHWA, 1992a: Federal Highway Administration, Highway Performance Monitoring
System, 1990 data files, U.S. Department of Transportation, Washington, DC,
February 1992.
FHWA, 1992b: Federal Highway Administration, Highway Performance Monitoring
System Impact Analysis Output, received from FHWA, U.S. Department of
Transportation, Washington, DC, April 1992.
Freedonia Group, 1989: The Freedonia Group, "Solvents, Industry Study #264,"
Cleveland, Ohio, 1989.
Frost & Sullivan, 1989: Frost & Sullivan, Inc., "Industrial Solvents (Report A2180)," New
York, New York, 1989.
Gill, 1992: William Gill, Texas Air Control Board, personal communication, April 23,
1992.
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REFERENCES (continued)
Kimbrough, 1992: Sue Kimbrough, U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, personal communication, March 1992.
Lavallee and Terrillon, 1991: Francois Lavallee and Francois Terrillon, "Air
Pollution Emissions and Controls: Adapting MOBILE4 to Model the Canadian Motor
Vehicle Fleet & the Use of MOBILE4C for Canadian Emissions Inventories,"
Transportation Systems Division, Environment Canada, Quebec, February 1991.
Lavallee, 1991: Francois Lavallee, Environment Canada, personal communication,
November 1991.
Meszler, 1992: Dan Meszler, State of Maryland Department of the Environment,
letter to Maureen Mullen, E.H. Pechan & Associates, Inc., April 1992.
Meyer, 1991: Edwin L. Meyer, Chief, Model Application Section, SRAB, TSD, OAQPS,
U.S. Environmental Protection Agency, Research Triangle Park, NC, "Growth and
Control Input Parameters for a Regional Oxidant Model Analysis of the 1990 Clean
Air Act Amendments," memorandum, July, 199 L
MVMA, 1987-1991: Motor Vehicle Manufacturers Association, "Motor Gasoline Survey,"
1987-1991.
MVMA, 1990: Motor Vehicle Manufacturers Association, "Motor Gasoline Survey,"
city/state, Summer 1990.
NOAA, 1982: U.S. National Oceanic and Atmospheric Administration, "Climatology of the
United States," No. 81, September 1982.
NEC, 1991: National Research Council, "Rethinking the Ozone Problem in Urban and
Regional Air Pollution," National Academy Press, Washington, DC, 1991.
Pechan, 1988: E.H. Pechan & Associates, Inc., "National Assessment of VOC, CO, and
NO, Controls, Emissions, and Costs," prepared for Office of Policy Planning and
Evaluation, U.S. Environmental Protection Agency, September 1988.
Pechan, 1992a: E.H. Pechan & Associates, Inc., "Estimating Peak Electric Utility
Generation Emissions for Regional Oxidant Modeling, Draft Report," prepared for
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,
May 1992.
Pechan, 1992b: E.H. Pechan & Associates, Inc., "Regional Oxidant Modeling — Emission
Inventory Development and Emission Control Scenarios," prepared for U.S.
Environmental Protection Agency, Office of Air Quality Standards and Planning, June
1992.
Shedd, 1991: Steve Shedd, U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards, personal communication, November 13,1991.
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REFERENCES (continued)
Wolcott, 1992: Mark Wolcott, U.S. Environmental Protection Agency, OfiEice of Mobile
Sources, "Historic Fuel Volatility in Selected Cities," memorandum to Jim Wilson,
E.H. Pechan & Associates, Inc., May 1992.
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CONTENTS
FORWARD iii
ACKNOWLEDGEMENTS v
EXECUTIVE SUMMARY vii
I INTRODUCTION 1
II ELECTRIC UTILITY EMISSIONS 7
A. 1987-1990 STEAM ELECTRIC UTILITY EMISSION INVENTORIES 7
1. Processing Computerized Raw Data 8
2. Emissions Algorithms 9
B. 1991 STEAM EMISSION INVENTORY 12
C. EMISSION SUMMARIES 13
•
III POINT SOURCE EMISSIONS 21
A. GROWTH INDICATORS 21
. B. CONTROL EFFICIENCY REVISIONS 22
C. RULE EFFECTIVENESS ASSUMPTIONS AND
EMISSION CALCULATIONS 22
D. EMISSION SUMMARY 29
IV MOTOR VEHICLE EMISSIONS 33
A. BACKGROUND ON HPMS 33
1. Description of HPMS 33
2. Rationale for Using HPMS to Estimate VMT 35
3. Problems with Using HPMS to Estimate VMT 35
B. GENERATION OF VMT ESTIMATES 36
1. Distribution of HPMS VMT to Counties 36
2. Allocation of VMT to the AIRS-AMS Vehicle Types 38
3. Projecting VMT to Other Inventory Years 44
C. EMISSION FACTOR CALCULATION 44
D. CALCULATION OF MOTOR VEHICLE EMISSIONS 50
1. Seasonal Emission Factors 50
2. Seasonal Allocation of VMT 52
3. Emission Summary 56
V AREA SOURCE SOLVENT EMISSIONS 59
A. OVERALL NATIONAL EMISSIONS ESTIMATES 59
B. DISTRIBUTION OF SOLVENT EMISSIONS TO STATES
AND COUNTIES 60
C. DEDUCTION OF POINT SOURCE EMISSIONS 63
D. PROJECTING SOLVENT EMISSIONS TO OTHER
INVENTORY YEARS 63
E. EMISSION SUMMARY 63
IX
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CONTENTS (continued)
VI AREA SOURCE EMISSIONS 65
A. GROWTH INDICATORS 65
B. REVISED EMISSION ESTIMATES 69
C. EMISSION FACTOR CHANGES 70
D. CONTROL EFFICIENCY ASSUMPTIONS 76
E. NONROAD MOBILE SOURCE EMISSION ESTIMATES 76
1. Creation of National County-Level 1990 Nonroad Emission
Estimates 77
2. Distribution of Total Nonroad Emissions to SCCs 77
3. Adjusting 1990 Estimates to Other Inventory Years 81
F. CORRESPONDENCE TO AMS 81
G. EMISSION SUMMARY 81
VII CANADIAN EMISSIONS 89
A. POINT AND AREA SOURCES 89
B. MOBILE SOURCES 89
VIII QUALITY ASSURANCE AND QUALITY CONTROL 101
A. DATA AND PROGRAM INTEGRITY ASSURANCE 101
B. QUALITY ASSURANCE OF UTILITY INVENTORIES 102
1. Emission Estimates 102
2. Coverage of Plants 103
C. QUALITY ASSURANCE OF NON-UTILITY POINT SOURCES 103
D. QUALITY ASSURANCE OF MOTOR VEHICLE DATA 104
E. QUALITY ASSURANCE OF SOLVENT INVENTORIES 104
F. QUALITY ASSURANCE OF AREA SOURCE INVENTORIES 108
ABBREVIATIONS AND ACRONYMS Ill
REFERENCES 113
APPENDIX A - COMPUTER FILES A-l
APPENDIX B - PETROLEUM REFINERY VOC EMISSIONS B-1
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TABLES
1-1 Interim Inventories - Major Data Sources 2
1-2 Interim Inventory - National Emission Summary 4
II-l Steam Electric Utility Unit Source Classification
Code Relationships 10
II-2 Summary of Steam Electric Utility Emissions 14
II-3 1990 Steam Electric Utility NOX Emissions by State
and Fuel Type 15
II-4 1990 Steam Electric Utility SO2 Emissions by State
and Fuel Type 16
II-5 1990 Interim Inventory Top 50 Steam Utility NOX Emitters 17
II-6 1990 Interim Inventory Top 50 Steam Utility S02 Emitters 18
III-l BEA Industry Earnings Data Classification 23
III-2 BEA SA-5 National Changes in Earnings by Industry 25
III-3 BEA SQ-5 National Growth in Earnings by Industry 27
III-4 SCCs With 100 Percent CO Rule Effectiveness 30
III-5 Summary of National Non-Utility Point Source Emissions 31
IV-1 Data Components of HPMS ' 34
IV-2 AMS Vehicle/Road Types 39
IV-3 Distribution of Truck Travel Activity 42
IV-4 National VMT Estimates 45
IV-5 HPMS Average Overall Travel Speeds for 1990 47
IV-6 Average Speeds by Road Type and Vehicle Type 48
IV-7 Summer RVPs Used to Model Motor Vehicle Emission Factors 49
IV-8 1990 Seasonal RVP (psi) by State 53
IV-9 Seasonal Maximum and Minimum Temperatures (°F) by State 54
IV-10 Temporal Allocation Factors by Vehicle Type 55
IV-11 Summary of Motor Vehicle Emissions ' 57
V-l National Material Balance for Solvent Emissions 61
V-2 Data Bases Used for County Allocation 62
V-3 Solvent Inventory Emission Summary 64
VI-1 Area Source Growth Indicators 66
VI-2 SEDS National Fuel Consumption 68
VI-3 Railroad Locomotives Diesel Fuel Consumption
1985 to 1990 71
VI-4 Railroad Emission Factors 71
VI-5 Residential Wood Combustion Emission Factors 72
VT-6 Civil Aircraft SO2 Emission Factors 74
VI-7 Average Annual Service Station Stage II VOC
Emission Factors 75
VI-8 Ozone Nonattainment Areas with OMS-Prepared Nonroad
Emission Estimates 78
VI-9 Source Categories Used for Nonroad Emission Estimates 80
VI-10 Nonroad Source Activity Indicators 82
VI-11 AMS to NAPAP Source Category Correspondence 83
VI-12 Summary of National Area Source Emissions 87
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TABLES (continued)
VII-1 Source Categories Used to Project Canadian Growth 90
VII-2 Canadian Emissions and Growth Factors 91
VII-3 Summary of Canadian Point Source Emissions, 1987-1991 94
VII-4 Summary of Canadian Area Source Emissions, 1987-1991 96
VII-5 1990 Canadian VMT Estimates 99
A-l Interim Inventory Data Files A-2
A-2 Point Source Files File Format A-3
A-3 Canadian Point Source Files File Format A-5
A-4 Area Source Files File Format A-6
A-5 Canadian Area Source Files File Format A-7
A-6 Mobile Source Emission Files File Format A-8
A-7 Annual Vehicle Miles Traveled (VMT) Files File Format A-9
A-8 Canadian Annual Vehicle Miles Traveled (VMT) Files File Format A-10
A-9 ' Highway Vehicle Emission Factor File File Format A-11
A-10 Canadian Highway Vehicle Emission Factor File File Format A-12
A-ll County I/M Correspondence File File Format A-13
A-12 AMS-NAPAP Correspondence File File Format A-14
B-l Comparison of Trends and NAPAP - Petroleum Refinery Emissions B-2
B-2 1985 NAPAP Slowdown Emissions B-2
B-3 Comparison of NAPAP and Trends Emission Factors B-4
B-4 Alternative Estimates of National VOC Emissions
Petroleum Refinery Slowdown Systems B-5
FIGURES
IV-1 Average Annual Daily Emissions vs. Average Ozone Season
Daily Emissions for Motor Vehicles 58
VI-1 Assignment of Surrogate Nonattainment Areas 79
VIII-1 Comparison of Maryland County VMT 105
VIII-2 Comparison of Arizona County VMT Distribution 106
VIII-3 Comparison of New Jersey Vehicle Type VMT Distribution 107
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CHAPTER I
INTRODUCTION
The U.S. Environmental Protection Agency (EPA) is planning to conduct regional
oxidant modeling for much of the Eastern United States. To support this modeling, a
comprehensive 1990 emission inventory is needed. Under the Clean Air Act (CAA), States
were required to submit 1990 emission inventories, but many of these inventories were
not completed by the November 1992 deadline. In addition, States were required to
submit inventories only for their nonattainment areas, while regional modeling requires
emissions for all counties. Theoretically, this 1990 point source data should be available
from the AIRS Facility Subsystem (AFS), but few States have updated their point source
data to reflect a base year of 1990, or are expected to do so in time to be utilized in this
analysis.
This effort focused on the development of a comprehensive 1990 emissions inventory --
the 1990 Interim Inventory. Since many of the ozone episodes to be simulated occurred in
years other than 1990, emission inventory data for years other than 1990 (1987, 1988,
1989, 1990, and 1991) are also needed. The pollutants covered in this inventory are
volatile organic compounds (VOC), nitrogen oxides (NO,), carbon monoxide (CO), and
sulfur dioxide (S02).
The Interim Inventory effort was divided, by source type, into five components. These
are: (1) fossil-fuel steam utilities, (2) non-utility point sources, (3) motor vehicles, (4)
solvents, and (5) other area sources. Each component has separate data sources and
methodologies associated with the development of its inventories. As a result, separate
inventory files were provided for each component. Table 1-1 lists the major data sources
used to produce each of these inventories.
The fossil-fuel steam utility inventories were developed from steam, boiler-level data
submitted to the U.S. Department of Energy (DOE) Energy Information Administration
(EIA). These data were submitted to EIA each year by facilities with boilers of 10 MW or
greater. The utility emission estimates are based, therefore, on actual fuel use data
submitted by .the utilities for four of the 5 inventory years. For 1991, fossil-fuel steam
plant data were used.
Non-utility point source inventories were developed based on the 1985 National Acid
Precipitation Assessment Program (NAPAP) Point Source Emissions Inventory (Version
2). Emissions included in the utility inventory were deleted from this file. Emissions
were projected to the inventory years based on historical earnings data (by industry class)
compiled by the Bureau of Economic Analysis (BEA). This assumed the same level of
control technology found in the 1985 NAPAP Emissions Inventory.
-------
Table 1-1
Interim Inventories - Major Data Sources
Inventory
Data Sources
Report Chapter
Fossil-Fuel Steam Utility
Non-Utility Point
Motor Vehicle:
VMT
Emission Factors
Solvent
Area Source
Form EIA-767 (Steam-Electric Plant Operation and
Design Report) - data available for inventory years 1987-
1990
Form EIA-759 (Monthly Power Plant Report) - data
available for 1990 and 1991
1985 NAPAP Point Source Inventory
BEA Historical Earnings Data
HPMS
MOBILES
Solvent Usage Estimates:
Paints and Coatings: U.S. Paint Industry Data Base
Other Categories: Industrial Solvent Marketing Reports
BEA Earnings and Population Data
1985 NAPAP Area Source Inventory
BEA Historical Earnings and Population Data
SEDS Fuel Consumption Data
II
IV
V
VI
-------
The motor vehicle inventory is made up of two components. Vehicle miles traveled
(VMT) for highway vehicles were estimated using 1990 travel data from the Federal
Highway Administration's (FHWA) Highway Performance Monitoring System (HPMS).
The VMT data were adjusted to be representative of the other inventory years using
State-specific gasoline consumption data from DOE's State Energy Data System (SEDS).
Emission factors for highway vehicles were estimated using EPA's MOBILES mobile
source emission factor model.
The solvent inventory was based on a material balance on total nationwide solvent
consumption for 1989. National solvent usage estimates by end-use category were
obtained from three main sources. For paints and coatings, the main source was a data
base developed by the U.S. paint industry. Solvent usage estimates for other categories
were obtained from industrial solvent marketing reports. The 1985 NAPAP methodology
for solvent destruction calculations in the nationwide material balance were also used.
The area source inventory was developed based on the 1985 NAPAP Area Source
Emissions Inventory. Emissions were projected to the inventory years based on historical
BEA earnings data by industry, historical estimates of fuel consumption by sector and
fuel type from DOE's SEDS, population, and other special category-specific indicators.
Emission factor updates/changes were incorporated for railroads, residential wood
combustion, and aircraft.
Stationary source VOC, NOX, and CO emission estimates were revised to incorporate
the effects of rule effectiveness. EPA-recommended 80 percent rule effectiveness was
applied to all stationary source control efficiencies, except those sources for which 80
percent rule effectiveness was judged to be unreasonable. The sources for which an 80
percent rule effectiveness was not applied are discussed in Chapter III. Incorporating
rule effectiveness increases the controlled emission estimate by discounting the reported
efficiency of control devices.
The development of each of the inventories mentioned above is described more fully in
the following chapters. Chapter VHI presents the quality assurance and quality control
procedures followed during the development of the inventories.
Table 1-2 shows the national emission estimates by source type for 1987 through
1991. These emissions are for the 48 contiguous States. More detailed emission
summaries are presented in Volume II of this report.
Non-utility point source emission totals for the Interim Inventory are significantly
different from 1985 NAPAP Inventory values for VOC and CO because an 80 percent rule
effectiveness factor was applied in computing stationary source emissions for the Interim
Inventory. Discounting for rule effectiveness produces the largest emission differences at
emission sources where the efficiencies of existing controls are high. Despite efforts taken
during this study to correct control efficiencies for sources that were obviously in error,
other high control efficiencies hi the 1985 NAPAP Inventory point source file appear to
have caused some large increases when rule effectiveness was applied at the source level.
-------
Table 1-2
Interim Inventory - National Emission Summary
(thousand tons per year)
Pollutant/Category
VOC
Utility*
Non-Utility Point
Solvent
Area Source
Motor Vehicle
Total
NOX
Utility*
Non-Utility Point
Solvent
Area Source
Motor Vehicle
Total
CO
Utility*
Non-Utility Point
Solvent
Area Source
Motor Vehicle
Total
S02
Utility*
Non-Utility Point
Solvent
Area Source
Motor Vehicle
Total
1985
NAPAP
39
2,120
4,630
8,002
7,363
22,154
6,614
2,853
0
4,249
6,810
20,526
310
5,151
0
20,485
34,987
60,933
16,025
5,156
0
1,446
511
23,138
1987
32
4,166
4,672
7,798
7,997
24,644
7,064
2,907
0
4,955
8,018
22,944
289
5,642
0
27,770
66,519
100,219
15,661
4,931
0
1,347
655
22,594
1988
36
4,200
4,838
7,887
7,860
24,797
7,464
3,004
0
5,172
8,141
23,781
301
5,882
0
27,662
66,249
100,094
15,934
5,089
0
1,347
690
23,060
1989
36
4,175
4,862
7,707
6,927
23,685
7,542
2.971
0
5,247
7,880
23,639
307
5,918
0
27,040
61,169
94,434
16,161
4,990
• o
1,315
703
23,169
1990
34
4,184
4,887
7,614
6,779
23,474
7,460
2,989
0
5,278
8,024
23,750
303
5,877
0
26,398
61,146
93,724
15,813
4,926
0
1,308
741
22,788
1991
34
4,168
4,919
7,497
6,619
23,214
7,386
2,972
0
5,294
7,934
23,585
299
5,795
0
25,759
60,297
92,149
15,555
4,860
0
1,389
769
21,883
NOTES: ' Utility = Fossil-Fuel Steam Utilities.
-------
As an example, one petroleum refinery catalytic cracking unit, whose CO emissions are
controlled by a CO boiler, with a listed control efficiency of 99.9 percent, has CO
emissions of 5,000 tons per year before rule effectiveness is applied. After a rule
effectiveness factor is applied, estimated CO emissions from this source are one million
tons per year. Because EPA's AP-42 says that CO waste heat boilers reduce CO
emissions from FCC units to negligible levels, it seems unlikely that the rule effectiveness
policy can be accurately simulated hi all cases through an across-the-board 80 percent
factor. A 100 percent rule effectiveness factor was applied to sources in a selected group
of SCCs to prevent overestimation of emissions as in the above example.
Differences between 1985 NAPAP motor vehicle emitted CO emissions and those for
1987 through 1991 occur because the MOBILES emission factors used in the Interim
Inventory differ from those of the motor vehicle emission factor model used to construct
the NAPAP Inventory, and the assignment of speeds to roadway types is different in the
two inventories. While these differences also exist for NOX and VOC, the resulting
emissions difference is greater for CO because the MOBILES CO speed correction factors
are more severe than those for the other pollutants.
. Area source totals also show a large increase from the 1985 NAPAP estimates to the
Interim Inventory estimates. This increase in area source emissions is due almost
entirely to the inclusion of the new nonroad vehicle emission data supplied by EPA.
National CO emissions from nonroad sources increased from approximately 730,000 tons
in the 1985 NAPAP Inventory to between 1.4 and 1.5 million tons in the Interim
Inventory.
-------
CHAPTER n
ELECTRIC UTILITY EMISSIONS
The electric utility industry in the United States accounted for 67 percent of SO2 and
30 percent of NOX emissions in 1980. The U.S. Congress has responded to increased
public concern about the environment by passing the Clean Air Act Amendments of 1990
(CAA). Title IV of the CAA, which addresses acid deposition, requires emission reductions
to be achieved in stages. As a result of Title IV, electric utilities will be expected (by the
year 2010) to achieve 87 percent of the 10 million ton reduction required by Title IV for
SO2 (8.7 million tons) and to achieve 100 percent (2 million tons) of the NOX emissions
reduction required by Title IV.
As suggested by a recommendation from the National Research Council (NRC) (NRC,
1991), NOj control will probably be necessary either.to complement or substitute for VOC
control to substantially reduce ozone concentrations in many urban, suburban, and rural
areas of the United States; this will likely increase the focus on the contribution of
utilities to the country's ozone nonattainment problems.
With the potential contribution of utilities to both nonattainment and acid deposition
problems, it is crucial to use the most specific and detailed information available in
developing the steam electric utility portion of the emission inventories used for 1987
through 1991. Data sources and methods used in computing steam-electric utility
emissions are described below.
A. 1987-1990 STEAM ELECTRIC UTILITY EMISSION INVENTORIES
As mentioned in Chapter I, EIA collects monthly boiler-level data on a yearly basis
from Form EIA-767 (Steam-Electric Plant Operation and Design Report) (DOE, 1987-
1990). The EIA also collects plant-level fossil-fuel data from all electric utility plants from
Form EIA-759 (Monthly Power Plant Report) (DOE, 1992). Currently, Form EIA-767 data
are available for the years 1987 through 1990, while Form EIA-759 data are available
through the year 1991. The steam portion of the emission inventories for 19.87 through
1991 includes data from these two forms. These steam inventories only include boiler-
level data - not data for gas turbines (GT) or internal combustion (1C) engines. (The
latter account for a very small share of electric utility fuel use and corresponding
emissions and are included in the non-utility point source inventory.)
The steam emission inventory data for 1987 through 1990 are based on the
aggregated monthly electric utility steam boiler-level data from Form EIA-767. All plants
of at least 10 megawatts (MW) that have at least one operating boiler are required to
provide this information to EIA, although the amount of data required from plants with
less than 100 MW of steam-electric generating capacity is much less. For plants with a
-------
nameplate rating from 10 MW to less than 100 MW, only selected pages of the Form EIA-
767 must be completed. Stack and flue information is not required for these smaller
plants.
1. Processing Computerized Raw Data
The basis for the fossil-fuel-fired steam electric utility component of the Interim
Inventory is the reported primary utility data collected by EIA. The data from these EIA
forms are transferred to data tapes that are not initially serviceable to the public. Pechan
has developed customized computer code to process these data and to account for the
various characteristics of the data tapes.
a. Form EIA-767
Form EIA-767 data are reported by the operating utility for each plant with fossil-fuel
steam boilers of 10 MW or greater. The written form is designed so that information for
each plant is reported on separate pages that relate to different levels of data. The
relevant data levels are as follows:
• Plant-level: One page for delineating the plant configuration, which
establishes the number of boilers and the IDs for each boiler, as well as the
associated generators), flue gas desulfurization (FGD) unit(s), flue(s) and
stack(s). These do not necessarily have a one-to-one correspondence.
• Boiler-level: One page per boiler for monthly fuel consumption and quality
data (for coal, oil, gas, and other), one page for regulatory data, and one page
for design parameters.
• Generator-level: One page for data relating to up to five generators.
• FGD-level: One page for up to five FGD units for annual operating data and
one page for each FGD unit for design parameter data.
• Flue- and stack-level: One page per flue-stack for design parameter data.
Processing Form EIA-767 is accomplished in a series of steps aimed at converting the
computerized data into data base form. Each "page" format is reproduced on the
computer file exactly as it appears on the written page of the form. The data from each
"page" must be extracted from the computer file, associated with the correct boiler, and
combined with all corresponding data from the other pages for that boiler.
For example, fuel-related boiler data - monthly values for each fuel burned, along
with the fuel's associated sulfur, ash, and heat content — are reported on page six. These
data must be aggregated for each fuel hi order to produce annual estimates for each boiler
before they are combined with the other data (such as control devices and efficiencies,
plant location data, associated generator generation, and associated stack parameters).
After Source Classification Codes (SCCs) are assigned to each reported fuel for each
boiler within a plant, the SCC-specific data are then separated so that each Interim
Steam Inventory data base observation is on the plant-boiler-SCC level.
8
-------
These data were subject to a review that resulted in some changes to boiler firing
configuration and bottom type. In some cases, the utilities had just updated their Form
EIA-767 submittals. These changes subsequently changed some SCC assignments, NO,
control efficiencies, and emissions.
6. Form EIA-759
Form EIA-759 data are also processed in a series of steps, using a less intricate
method, since the data for each plant are not reported at the boiler level, but instead are
reported by prime mover (steam, hydro, 1C, GT, combined cycle, for example) and fuel
type.
For each plant-prime mover combination (in this case, for the steam prime mover),
plant ID data, as well as monthly fuel-specific generation and consumption data, are
reported. The monthly plant steam prime mover data are aggregated to annual estimates
for each fuel (that has been categorized as coal, residual oil, distillate oil, natural gas, or
other) and combined to produce a single annual steam plant-level data observation.
These data were utilized to "grow" the 1990 fuel and emissions data for 1991, as
described later in this chapter.
2. Emissions Algorithms
Data that were not obtained directly from the computerized data files (or converted to
other measurement units) were developed by Pechan using algorithms that have been
utilized since the 1980s. These variables include heat input, pollutant emissions, NOX
control efficiencies, and SCC. Emission factors from AP-42 (EPA, 1991b) were obtained
from EPA's OAQPS CHIEF Bulletin Board and used in calculating emissions. The
emission factor used depends upon the SCC and pollutant, as explained below.
• The appropriate SCC is assigned to each fuel based on its characteristics. For
coal, the SCC is based on the American Society for Testing and Materials (ASTM)
criteria for moisture, mineral-free matter basis (if greater than 11,500 Btu/lb,
coal type is designated to be bituminous; if between 8,300 and 11,500 Btu/lb, coal
type is designated to be subbituminous; and if less than 8,300 Btu/lb, coal type is
designated to be lignite) and the boiler type (firing configuration and bottom type)
as specified by AP-42 (EPA, 1991b). If both coal and oil were burned in the same
boiler, it is assumed that the oil is distillate; otherwise, it is assumed to be
residual. Then, based on the fuel and boiler type, the SCC is assigned. For
natural gas, the SCC is based on fuel and boiler type. See Table II-1 for a
complete list of the relationships among fuel type, firing type, bottom type, and
SCC.
• NO, control efficiency is based on the assumption that the unit would be
controlled so that its emission rate would equal its limit, expressed on an annual
equivalent basis. After calculating the heat input, controlled emissions assuming
compliance with the applicable standard is back-calculated. After calculating the
uncontrolled NOX emissions, the presumed net control efficiency is calculated.
-------
Table 11-1
Steam Electric Utility Unit
Source Classification Code Relationships
Fossil-Fuel Firing Type
Coal
Bituminous No data
Wall*
Opposed
Tangential
Stoker
Cyclone
Fluidized Bed
Subbituminous No data
Wall
Opposed
Tangential
Stoker
Cyclone
Lignite No data
Wall
Opposed
Tangential
Stoker
Cyclone
Bottom Type
No data
Wet
Dry
No data
Wet
Dry
No data
Wet
Dry
No data
Wet
Dry
All
All
,N/A
No data
Wet
Dry
No data
Wet
Dry
No data
Wet
Dry
No data
Wet
Dry
All
All
All
All
All
All
All
All
sec
10100202
10100201
10100202
10100202
10100201
10100202
10100202
10100201
10100202
10100212
10100201
10100212
10100204
10100203
10100217
10100222
10100221
10100222
10100222
10100221
10100222
10100222
10100221
10100222
10100226
10100221
10100226
10100224
10100223
10100301
10100301
10100301
10100302
10100306
10100303
10
-------
Table 11-1 (continued)
Fossil-Fuel
Residual Oil
Distillate Oil
Natural Gas
Firing Type
No data
Wall
Opposed
Tangential
Stoker
Cyclone
No data
Wall
Opposed
Tangential
Stoker
Cyclone
No data
Wall
Opposed
Tangential
Stoker
Cyclone
Bottom Type
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
sec
10100401
10100401
10100401
10100404
10100401
10100401
10100501
10100501
10100501
10100501
10100501
10100501
10100601
10100601
10100601
10*100604
10100601
10100601
NOTES: 'Wall firing includes front, arch, concentnc, rear, side, vertical, and duct burner finng.
11
-------
The following equation is used to compute controlled NO, emissions (with EPA-
specified 80 percent rule effectiveness):
The following equation is used to compute controlled SO2 emissions:
. * - + % j^r * (1 - e/57100) * (1/2000) (2)
(to/is) burned emf ' "
• The following equation is used to compute uncontrolled VOC and CO emissions
(there were no control efficiencies):
VOC and CO = fuel + AP-42 * (1/2000) (3)
(tons) burned emf
• The following equation is used to compute heat input:
heat input _ fuel ^ heat (4)
(MMBtu) burned content
Although Form EIA-767 data are collected from plants with a total plant capacity of
at least 10 MW, there are fewer required data elements (identification data, boiler fuel
quantity and quality data, and FGD data, if applicable) for those plants with a total
capacity between 10 MW and 100 MW. Thus, missing values are introduced in these
situations. Because of time constraints, most data elements are not assigned a default
value other than zero. If variables for boiler faring and bottom type were missing (these
are needed in the SCC assignment) the default values for wall-fired and dry bottom type
are assigned. If the longitude and latitude for a specific boiler were missing, they were
replaced whenever possible with either (1) the latitude and longitude from other boilers in
that same plant or (2) county centroid coordinates.
B. 1991 STEAM EMISSION INVENTORY
The 1991 monthly computerized fossil-fuel plant-level data from Form EIA-759 are
used in conjunction with 1990 Form EIA-767 data to develop the 1991 steam emission
inventory file, since the 1991 Form EIA-767 data are not available. The data for the 1991
steam emission inventory are the same as those for the 1990 inventory, except that the
fuel quantity and emissions variables are grown by a factor based on the ratio of the 1991
Form EIA-759 plant-level, fuel-specific data to the data for 1990.
Note that no new plants were added or subtracted from the 1990 steam inventory to
produce the 1991 steam inventory, so that the six new plants with data in the 1991 Form
EIA-759 file are not included in the 1991 inventory records and their fuel data are not
12
-------
included in the growth ratios. However, additional boilers were added or retired from the
1990 inventory that were considered for the 1991 Form EIA-759 plant-level data.
Although these boilers would not be physically included in or excluded from the records in
the 1991 steam inventory, their fuel data would be incorporated in the growth ratios and
would be reflected in the 1991 data for the other boilers in the plant. As a result, the
1991 figures should be considered to be preliminary estimates only.
C. EMISSION SUMMARIES
Steam electric utility emission summaries are provided in Tables II-2 through II-6.
Table II-2 is a summary of VOC, NOX, CO, and SO2 emissions by fuel type for each
inventory year. As Table II-2 shows, overall emissions increased for all four pollutants in
1988 and 1989, while overall emissions declined in 1990.and 1991. Observations
regarding these trends are summarized below.
• For coal (the largest emissions contributor) this same pattern holds
for NOX and S02.
• For oil, all four pollutants had increased emissions from 1987 to 1989.
• For natural gas, VOC and SO2 emissions remained constant from
1987 to 1991, while for NOX and C02, emissions decreased in 1988
and increased hi 1989.
Table II-3 is a summary of 1990 NOX emissions by State and fuel type. Table II-4
shows the same information for SO2. Table II-5 lists the top 50 N0x-emitting steam
electric utility plants for 1990. Table II-6 lists the top 50 SO2-emitting facilities for the
same year.
Ohio and Indiana are the two States that emit the most S02. Pennsylvania is the
third greatest SO2 emitter. These three States account for almost one-third of the S02
emissions from fossil-fuel steam boilers (see Table II-3). Ohio and Indiana are also the
top two coal NOX emitters. When natural gas NO, emissions are included, Texas becomes
the top State NOX emitter. These three States account for almost one-fourth of the NOX
emissions from fossil-fuel steam boilers (see Table II-4).
The top utility emitters can be determined from Table II-5 and Table II-6. Nine
plants, three of which are in Ohio and three of which are in Indiana, are among the top
20 plant emitters of both NO, and SO2. Two Indiana plants - Gibson and Clifty Creek ~
are among the top six emitters of both pollutants.
13
-------
Table 11-2
Summary of Steam Electric Utility Emissions
Pollutant
VOC
Coal
Oil
Gas
Total
NO,
Coal
Oil
Gas
Total
CO
Coal
Oil
Gas
Total
S02
Coal
Oil
Gas
Total
1987
25
5
2
32
6,275
190
599
7,064
217
19
53
289
15,033
627
1
15,661
Emissions
1988
27
7
2
36
•
6,666
247
551
7,464
229
24
48
301
15,224
709
1
15,934
(thousand tons)
1989
27
7
2
36
6,706
258
578
7,542
231
25
51
307
15,407
753
1
16,161
1990
27
5
2
34
6,705
196
559
7,460
233
19
51
303
15,200
612
1
15,813
1991
27
5
2
34
6,633
196
557
7,386
•
231
18
50
299
14,937
617
1
15,555
14
-------
Table 11-3
1990 Steam Electric Utility NOX Emissions by State and Fuel Type
State
AL
AR
AZ
CA
CO
CT
DC
DE
FL
GA
IA
IL
IN
KS
KY
LA
MA
MD
ME
Ml
MN
MO
MS
MT
NC
NO
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VA
VT
WA
Wl
WV
WY
Total
Coal-Fired
194.0
75.9
117.4
0.0
127.4
8.7
0.0
18.9
238.4
229.4
120.7
338.7
506.0
116.4
330.5
78.4
38.6
85.2
0.0
289.3
154.3
268.2
35.8
60.3
161.4
115.1
77.6
20.4
41.4
111.7
56.7
89.0
522.6
102.7
5.7
366.1
0.0
81.0
20.4
192.1
477.2
99.8
69.4
0.0
36.7
156.7
306.9
161.9
6,705.0
NOX Emissions
Oil-Fired
0.1
0.1
0.1
8.8
0.0
14.4
0.7
2.8
47.9
0.2
0.0
1.9
0.2
0.0
0.1
0.2
27.2
7.7
3.7
1.6
0.0
0.1
1.7
0.0
0.1
0.0
0.0
3.4
5.5
0.0
0.6
57.4
0.3
0.1
0.0
5.4
0.5
0.1
0.0
0.1
0.8
0.0
1.3
0.0
0.0
0.0
0.2
0.0
195.5
(thousand
Gas-Fired
0.7
6.4
2.7
101.8
1.4
0.7
0.0
2.4
36.5
0.3
0.7
1.5
1.4
4.0
0.0
52.7
10.2
3.0
0.0
2.1
1.2
0.7
13.2
0.0
0.0
0.0
0.6
0.0
8.4
3.8
5.8
39.5
0.1
36.5
0.0
0.2
1.5
0.9
0.0
0.0
217.4
0.0
0.1
0.2
0.0
0.5
0.0
0.0
559.4
tons)
Total
194.8
82.3
120.2
110.6
128.8
23.8
0.7
24.2
322.8
229.9
121.4
342.0
507.6
120.5
330.6
131.4
75.9
95.9
3.7
292.9
155.5
269.0
50.7
60.4
161.6
115.1
78.1
23.7
55.3
115.4
63.1
186.0
523.1
139.3
5.7
371.8
2.0
81.9
20.5
192.2
695.5
99.8
70.9
0.2
36.7
157.3
307.1
161.9
7,459.9
15
-------
Table 11-4
1990 Steam Electric Utility SO2 Emissions by State and Fuel Type
State
AL
AR
AZ
CA
CO
CT
DC
DE
FL
GA
IA
IL
IN
KS
KY
LA
MA
MD
ME
Ml
MN
MO
MS
MT
NC
NO
NE
NH
NJ.
MM
NV
NY
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VA
VT
WA
Wl
WV
WY
Total
Coat-Fired
528.5
69.0
120.3
0.0
86.9
10.6
0.0
38.9
484.2
874.7
180.5
895.5
1,510.7
87.6
905.5
98.2
102.3
256.7
0.0
372.3
84.4
783.8
107.7
17.9
336.3
126.5
50.6
43.1
70.9
64.0
54.5
269.9
2,240.2
101.6
4.9
1,200.7
0.0
167.2
31.2
796.4
466.7
32.0
154.2
0.0
.58.7
284.8
945.0
84.6
15,200.3
SO2 Emissions
Oil-Fired
0.1
0.1
0.1
7.7
0.0
42.5
2.5
8.1
161.7
0.8
0.1
3.7
0.3
0.1
0.2
0.4
130.0
25.8
11.5
3.4
0.0
0.4
11.4
0.0
0.2
0.0
0.0
25.4
6.2
0.1
1.2
146.8
0.9
0.2
0.0
12.7
1.1
0.2
0.0
0.1
1.2
0.0
4.4
0.0
0.0
0.1
0.3
0.0
612.3
(thousand tons)
Gas-Fired
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.8
Total
528.6
69.2
120.4
7.8
87.0
53.0
2.5
47.0
645.9
875.5
180.5
899.2
1,511.0
87.7
905.6
98.7
232.3
282.5
11.5
375.8
84.5
784.2
119.1
17.9
336.5
126.5
50.6
68.5
77.1
64.1
55.8
416.8
2,241.1
101.9
4.9
1,213.4
1.1
167.4
31.2
796.5
468.2
32.1
158.6
0.0
58.7
284.9
945.4
84.6
15,813.3
16
-------
Table 11-5
1990 Interim Inventory
Top 50 Steam Utility NOX Emitters
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
SO
State
KY
TX
Ml
IN
NM
IN
OH
IN
TX
TX
IL
GA
TN
OH
OH
WV
MO
AZ
MN
PA
WIT
OH
WY
WV
PL
IL
FL
PA
IL
TX
WY
!A
NC
OH
KS
KS
GA
NC
Ml
PA
FL
OH
Ml
MO
AL
MO
UT
WA
AL
IN
County
MUHLENBURG
RUSK
MONROE
GIBSON
SAN JUAN
JEFFERSON
ADAMS
SPENCER
TITUS
FORT BEND
RANDOLPH
SARTOW
STEWART
GALLIA
GALLIA
PUTNAM
NEW MADRID
COCONINO
SHERBURNE
BEAVER
ROSEBUD
JEFFERSON
SWEETWATER
HARRISON
HILLSBOROUGH
CHRISTIAN
CITRUS
INDIANA
TAZEWELL
FAYETTE COUNTY
PLATTE
WOOD8URY
PERSON
WASHINGTON-MORGAN
LINN
POTTAWATOMIE
PUTNAM
STOKES
STCLAIR
GREENE
HILLSBOROUGH
JEFFERSON
ST CLAIH
FRANKUN
JEFFERSON
ST CHARLES
MILLARO
LEWIS
SHELBY
DEARBORN
Plant
ID
1378
6146
1733
6113
2442
983
2850
6166
6147
3470
889
703
3399
8102
2876
3935
2167
4941
6090
6094
6076
2866
8066
3944
645
876
628
3122
879
6179
6204
1091
2712
2872
1241
6068
709
8042
6034
3179
646
2828
1743
2103
6002
2107
6481
3845
26
988
Plant Name
PARADISE
MARTIN LAKE
MONROE
GIBSON
FOUR CORNERS
CLIFTY CREEK
J M STUART
HOCKPORT
MONTICELLO
W A PARISH
BALDWIN
SOWEN
CUMBERLAND
GEN J M GAVIN
KYGER CREEK
JOHN E AMOS
NEW MADRID
NAVAJO
SHERBURNE CNTY
BRUCE MANSFIELD
COLSTRIP
W H SAMMIS
JIM BRIDGER
HARRISON
BIG BEND
KINCAID
CRYSTAL RIVER
HOMER CITY
POWERTON
SAM SEYMOUR
LARAMIE RIVER
GEORGE NEAL
ROXBORO
MUSKINGUM RIVER
LA CYGNE
JEFFREY ENERGY
HARLLEE BRANCH
BELEWS CREEK
BELLE RIVER
HATFIELD'S FERRY
F J GANNON
CARDINAL
ST CLAIR
LABAOIE
JAMES H MILLER JR
SIOUX
INTERMOUNTAIN
CENTRAUA
E C GASTON
TANNERS CREEK
Latitude
037 1539
032 15 38
041 5328
038 21 32
03641 26
0384420
0383814
0375532
033 05 30
029 29 00
038 12 18
034 07 32
036 23 39
038 56 09
038 5458
038 28 29
0363054
036 5445
0452250
0403803
04553 04
04031 58
041 45 00
0392300
027 47 40
039 38 55
028 57 59
040 30 51
040 33 05
029 55 02
042 06 36
042 1900
0362900
039 35 27
0382053
039 1708
033 11 39
036 1652
0424632
03951 00
0275425
0401508
0424552
038 33 30
0333758
0385457
039 30 39
04642 00
033 14 39
0390459
Longitude
0865842
09434 15
0832040
0874642
108 28 56
0852509
08341 44
087 02 14
095 02 30
0953759
08951 16
084 55 09
08739 14
082 06 59
082 07 41
081 49 30
089 33 41
111 23 30
093 2252
080 24 52
1063650
08037 59
10848 00
080 19 00
082 24 13
089 28 40
082 41 49
079 1 1 49
089 40 41
096 45 02
104 52 16
0962200
079 04 29
081 40 47
0943844
0960636
083 17 58
0800337
0822942
0795500
082 25 24
0803855
082 28 16
0905010
0870332
090 1730
1123445
122 51 00
0862724
08451 29
Emissions
(tpy)
97,829
89,677
85,442
74,632
72,280
70,692
68.629
63.882
62,526
62,274
61 ,352
51,236
59,646
59,512
57,472
57,296
56,763
56,332
56.210
55.409
55,001
54,171
53,894
51 ,050
48,905
48.338
48.230
47,834
47.029
46.212
45.612
45,359
45,297
43,749
43.407
43,337
41,771
41,690
40,934
39,639
39.607
38,897
38,859
38.775
38.747
37.470
36.654
36,401
35,647
34,949
17
-------
Table 11-6
1990 Interim Inventory
Top 50 Steam Utility SO2 Emitters
Rank
1
2
3
4
5
6
7
a
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
SO
State
OH
TN
WV
IN
IN
GA
MO
OH
OH
IL
GA
KY
OH
PA
MO
OH
IL
PA
OH
AL
WV
Ft
OH
PA
WV
TN
KY
PA
Ml
PA
IN
IL
IN
IL
OH
AL
PA
OH
GA
OH
KY
IN
GA
FL
TN
OH
MS
FL
TN
MA
County
GALUA
STEWART
HARRISON
JEFFERSON
GIBSON
BARTOW
FRANKLIN
GALUA
WASHINGTON-MORGAN
RANDOLPH
HEARD
JEFFERSON
ADAMS
INDIANA
NEW MADRID
JEFFERSON
CHRISTIAN
GREENE
JEFFERSON
SHELBY
MARSHALL
HILLSBOROUGH
LAKE
MONTOUR
GRANT
SUMNER
MUHLENBURG
ARMSTRONG
MONROE
YORK
WARRICK
MASSAC
VERMIUJON
MONTGOMERY
COSHOCTON
WALKER
INDIANA
CLERMONT
COWETA
HAMILTON
CARROLL
PIKE
PUTNAM
ESCAMBIA
ROANE
LORAIN
HARRISON
CITRUS
HUMPHREYS
BRISTOL
Plant ID
8102
3399
3944
983
6113
703
2103
2876
2872
889
6052
1364
2850
3118
2167
2866
876
3179
2828
26
3947
645
2837
3149
3954
3403
1378
3136
1733
3140
6705
887
1001
861
2840
8
3122
2830
728
2832
1356
994
709
641
3407
2836
2049
628
3406
1619
Plant Name
GEN J M GAVIN
CUMBERLAND
HARRISON
CLIFTY CREEK
GIBSON
BOWEN
LABAOIE
KYGER CREEK
MUSKINGUM
RIVER
BALDWIN
WANSLEY
MILL CREEK
J M STUART
CONEMAUGH
NEW MADRID
W H SAMMIS
KINCAID
HATFIELD'S
FERRY
CARDINAL
E C GASTON
KAMMER
BIG BEND
EASTLAKE
MONTOUR
MT STORM
GALLATIN
PARADISE
KEYSTONE
MONROE
BRUNNER
ISLAND
WARRICK
JOPPA STEAM
CAYUGA
COFFEEN
CONESVILLE
GORGAS
HOMER CITY
WALTER C
BECKJORD
YATES
MIAMI FORT
GHENT
PETERSBURG
HARLLEE
BRANCH
CRIST
KINGSTON
AVON LAKE
JACK WATSON
CRYSTAL RIVER
JOHNSONVILLE
BRAYTON POINT
Latitude
0385609
0362339
0392300
0384420
038 21 32
034 07 32
0383330
0385458
0393527
038 1218
033 25 00
03803 11
038 38 14
040 23 04
036 30 54
040 31 58
039 38 55
039 51 00
040 1508
033 1439
039 50 47
027 47 40
041 40 15
041 04 12
039 12 05
036 18 56
037 1539
04039 09
041 5328
0400800
037 54 55
037 12 38
0395403
0390331
040 11 10
033 38 39
040 30 51
0385930
0332747
0390640
0384459
038 31 42
03311 39
03033 57
035 S3 57
041 30 15
0302621
0285759
03601 40
041 42 39
Longitude
0820659
0873914
0801900
0852509
0874642
08455 09
090 50 10
082 07 41
081 40 47
08951 16
085 02 00
0855436
083 41 44
079 03 42
089 33 41
080 37 59
089 28 40
079 55 00
080 38 55
086 27 24
0894908
082 24 13
081 28 45
076 39 59
079 16 00
086 24 02
0865842
079 20 31
0832040
076 43 00
087 20 01
088 51 28
087 2449
089 24 1 1
081 5244
088 11 50
079 11 49
084 17 50
08457 18
084 48 15
0850206
087 1508
083 1758
087 1329
084 31 10
08203 00
089 01 35
082 41 49
087 59 10
071 11 41
Emissions
(tpy)
374,921
303.349
289,732
275,893
271.362
255,407
249,870
249.418
240,870
230,525
223.964
211.073
180.603
179289
169.017
168.581
166.399
163,432
163,186
160,599
155.374
155,122
144.581
142,681
141,839
140.997
140.870
134,849
128,514
128,160
122,923
122,204
117,313
114,315
113,636
113,412
109,448
105,504
104.764
102.235
100,790
100,173
99,818
98.530
92.820
89,512
87,141
36,823
86,687
85.436
18
-------
The General Gavin plant in Ohio was the top S02 emitter in 1985 and 1990. It was
the 14th highest NOX emitter in 1990. Paradise, a Kentucky plant, was the top NOX
emitter (and the 27th highest emitter of SO2).
19
-------
CHAPTER
POINT SOURCE EMISSIONS
Non-utility point source emissions in the Interim Inventories include emissions from
all point sources except external combustion (steam) electric utility sources (see Chapter
II). Electric utility internal combustion engines and gas turbines are included with this
portion of the Interim Inventory because the 1985 NAPAP was the best source of readily
available information on these emitters. Emissions from non-utility point sources were
based on the 1985 NAPAP Inventory point source emissions (EPA, 1989a). NAPAP point
source emissions were projected to the years 1987 through 1991 using BE A historical
earnings data. This chapter describes the methodology used to estimate emissions,
including computation of growth indicators, control efficiency revisions, and rule
effectiveness assumptions.
A. GROWTH INDICATORS
Emission estimates from each point source in the 1985 NAPAP Inventory (excluding
steam electric utilities) were projected to the years 1987 through 1991 based on the
growth in earnings by industry (2-digit Standard Industrial Classification Code [SIC]).
Historical earnings data from BEA's Table SA-5 (BEA, 1991a) were used to represent
growth in earnings from 1985 through 1990. (Earnings data from a different BEA source,
Table SQ-5 discussed below, were used to estimate 1991 emissions.) Table SA-5 historical
annual earnings data are by State and industry.
The 1985 through 1990 earnings data in Table SA-5 were in nominal dollars. In
order to be used to estimate growth, these values were converted to constant dollars to
remove the effects of inflation. Earnings data for each year were converted to 1982
constant dollars using the implicit price deflator for personal consumption expenditures
(PCEXBEA, 199Ib). The PCE deflators used to convert each year's earnings data to 1982
dollars are:
Year 1982 PCE Deflator
1985 111.6
1987 114.3
1988 124.2
1989 129.6
1990 136.4
Several BEA categories did not contain a complete time series of data for the years
1985 through 1990. Since the SA-5 data must contain 1985 earnings and earnings for
each inventory year (1987 through 1990) to be useful for estimating growth, a log linear
regression equation was used to fill in missing data elements where possible. This
regression procedure was performed on all categories that were missing at least one data
point and which contain at least three data points in the time series.
21
-------
Each record in the point source inventory was matched to the BEA earnings data
based on the State and the 2-digit SIC. Table III-l shows the BEA earnings category
used to project growth for each of the 2-digit SICs found in the 1985 NAPAP Inventory.
No growth in emissions was assumed for all point sources for which the matching BEA
earnings data was not complete. Table III-2 shows the national average growth and
earnings by industry from Table SA-5.
At the time the Interim Inventory was compiled, 1991 BEA earnings data were not
available in Table SA-5. Earnings data from BEA Table SQ-5 (BEA, 1992a) were used to
estimate emissions for 1991. Table SQ-5 contains historical quarterly earnings data by
State and 1-digit SIC. These data were converted to an annual constant dollars basis.
The 1991 quarterly earnings data were first summed to compute annual totals. Since
the PCE deflator used to convert to constant 1982 dollars was not available for 1991, a
1987 PCE deflator (BEA, 1992b) was used to convert the 1990 and 1991 earnings data
from Table SQ-5 to a 1987 constant dollar basis. The PCE deflators are as follows:
Year 1987 PCE Deflator
1990 114.7
1991 119.3
The 1991 inventory was then developed by growing the 1990 inventory based on the
changes in State industry earnings (by 1-digit SIC) from 1990 to 1991. National average
growth in earnings by industry is shown below in Table III-3.
B. CONTROL EFFICIENCY REVISIONS
In the 1985 NAPAP point source estimates, control efficiencies for VOC, NOX, CO, and
S02 sources in Texas were judged to be too high for their process/control device
combination. These high control efficiencies occurred because Texas did not ask for
control efficiency information, and simply applied the maximum efficiency for the reported
control device (Gill, 1992). High control efficiencies lead to high future growth in
modeling scenarios based on uncontrolled emissions (which are based on the control
efficiency and reported actual emissions). High control efficiencies also lead to extreme
increases in emission estimates when rule effectiveness is incorporated.
Revised VOC control efficiencies were developed for Texas for the Emission Reduction
and Cost Analysis Model for VOC (ERCAM-VOC) (Pechan, 1988). For this analysis,
revised efficiencies were also developed by SCC and control device combination for NOX,
SO-j, and CO using engineering judgement. These revised control efficiencies were applied
to sources in Texas. A large number of point sources outside of Texas had VOC and CO
control efficiencies that were also judged to be too high. The VOC and CO control
efficiencies used for Texas were also applied to these sources.
C. RULE EFFECTIVENESS ASSUMPTIONS AND EMISSION CALCULATIONS
Controlled emission estimates for each inventory year were recalculated, assuming
that reported VOC, NO,, and CO controls were 80 percent effective. SO2 controls were
assumed to be 100 percent effective. A three-step process was used to calculate emission
22
-------
Table III-1
BEA Industry Earnings Data Classification
SIC BEA Industry Earnings*
01 Farm
02 Farm
07 Agricultural services, forestry, fisheries, and other
08 Agricultural services, forestry, fisheries, and other
09 Agricultural services, forestry, fisheries, and other
10 Metal mining
11 Coal mining
12 Coal mining
13 Oil and gas extraction
14 Nonmetallic minerals, except fuels
15 Construction
16 Construction
17 Construction
20 Food and kindred products
21 Tobacco manufactures
22 Textile mill products
23 Apparel and other textile products
24 Lumber and wood products
25 Furniture and fixtures
26 Paper and allied products
27 Printing and publishing
28 Chemicals and allied products
29 Petroleum and coal products
30 Rubber and miscellaneous plastic products
31 Leather and leather products
32 Stone, clay, and glass products
33 Primary metal industries
34 Fabricated metal products
35 Machinery, except electrical
36 Electric and electronic equipment
37 Transportation equipment, excluding motor vehicles
38 Instalments and related products
39 Miscellaneous manufacturing industries
40 Railroad transportation
41 Local and interurban passenger transit
42 Trucking and warehousing
44 Water transportation
45 Transportation by air
46 Pipelines, except natural gas
47 Transportation services
48 Communication
49 Electric, gas, and sanitary services
50 Wholesale trade
23
-------
Table III-1 (continued)
SIC BEA Industry Earnings*
01 Farm
51 Wholesale trade
52 Retail trade
53 Retail trade
54 Retail trade
55 Retail trade
56 Retail trade
57 Retail trade
58 Retail trade
59 Retail trade
60 Banking and credit agencies
61 Banking and credit agencies
62 Holding companies and investment services
63 Insurance
64 Insurance
65 Real estate
66 Real estate
67 Holding companies and investment services
70 Hotels and other lodging places
72 Personal services
73 Business and miscellaneous repair services
75 Auto repair, services, and garages
76 Business and miscellaneous repair services
78 Amusement and recreation services and motion pictures
79 Amusement and recreation services and motion pictures
80 Health services
81 Legal services
82 Educational services
83 Social services and membership organizations
84 Miscellaneous professional services
86 Social services and membership organizations
88 Private households
89 Miscellaneous professional services
91 Federal government, civilian
92 State and local government
93 State and local government
94 State and local government
95 State and local government
96 State and local government
97 Federal government, civilian
371 Motor vehicles and equipment
NOTES: *State earnings by industry were matched to each of the 2- and 3-digit SICs to develop
annual growth rates.
24
-------
Table 111-2
BEA SA-5 National Changes In Earnings By Industry
Percent Growth from:
Industry
Farm
Agricultural services, forestry, fisheries, and other
Coal mining
Oil and gas extraction
Metal mining
Nonmetallic minerals, except fuels
Construction
Manufacturing
Nondurable goods
Food and kindred products
Textile mill products
Apparel and other textile products
Paper and allied products
Printing and publishing
Chemicals and allied products
Petroleum and coal products
Tobacco manufactures
Rubber and miscellaneous plastic products
Leather and leather products
Durable goods
Lumber and wood products
Furniture and fixtures
Primary metal industries
Fabricated metal products
Machinery, except electrical
Electric and electronic equipment
Transportation equipment, excluding motor vehicles
Motor vehicles and equipment
Stone, day, and glass products
Instruments and related products
Miscellaneous manufacturing industries
Railroad transportation
Trucking and warehousing
1985 to 1987
14.67
23.58
-17.46
-39.23
-3.03
2.33
7.27
-0.39
2.54
1.67
a.so
-1.72
2.62
7.44
1.75
-10.82
-1.97
5.27
-9.39
-2.03
10.03
6.82
-9.09
-4.72
-5.72
-3.17
8.44
-6.45
-0.23
-0.04
1.84
-14.13
5.63
1987 to 1988
-2.73
5.43
-6.37
4.94
18.01
3.74
4.81
2.95
3.26
1.34
-0.64
1.25
0.94
5.67
6.94
-3.22
2.43
5.51
-1.64
2.76
5.15
2.35
5.32
2.55
6.02
-18.01
-1.57
2.20
-1.61
60.65
6.92
-2.53
3.26
1988 to 1989
14.58
1.01
-4.16
-3.88
8.94
-2.79
-1.36
-0.97
-0.67
-1.20
-1.39
-1.62
-0.14
-0.81
0.32
-3.02
-2.43
0.68
-3.58
-1.14
-3.54
-1.46
-0.34
-0.86
-0.32
-1.91
0.55
-2.96
-1.96
-0.82
-2.21
-3.83
-0.20
1989 to 1990
-3.11
2.48
4.73
5.16
4.56
-0.45
-3.80
-1.85
-0.38
-0.24
-4.97
-4.22
-0.39
0.43
1.61
1.06
-5.01
-0.14
-2.55
-2.72
-3.71
-2.98
-3.03
-1.91
-1.92
-3.22
-1.07
-5.43
-3.19
-2.91
-2.54
-6.03
0.99
25
-------
Table 111-2 (continued)
Percent Growth from:
Industry
Water transportation
Local and interurban passenger transit
Transportation by air
Pipelines, except natural gas
Transportation services
Communication
Electric, gas, and sanitary services
Wholesale trade
Retail trade
Banking and credit agencies
Insurance
Real estate
Holding companies and investment services
Services
Hotels and other lodging places
Personal services
Private households
Business and miscellaneous repair services
Auto repair, services, and garages
Amusement and recreation services and motion
pictures
Health services
Legal services
Educational services
Social services and membership organizations
Miscellaneous professional services
Government and government enterprises
Federal, civilian
Federal, military
State and local
1985 to 1987
-6.92
13.45
12.01
-5.21
15.92
1.94
0.07
5.01
5.19
12.44
14.09
92.14
39.05
14.83
12.65
7.17
-5.68
17.05
6.65
17.93
15.15
20.14
9.35
17.39
11.28
5.43
-0.54
1.96
7.88
1987 to 1988
0.07
0.51
4.63
3.67
8.52
0.68
3.05
5.87
4.39
2.45
4.20
-6.98
-34.36
7.84
5.59
2.35
2.41
-17.34
2.46
16.43
7.08
9.92
7.17
8.45
5.04
3.20
3.79
-1.07
3.63
1988 to 1989
-1.02
2.14
4.94
-4.93
4.60
-2.81
0.63
2.44
0.65
-0.33
1.52
-7.87
-12.18
5.27
1.71
7.44
0.83
5.79
3.00
4.06
5.11
4.09
3.88
7.95
7.08
2.33
1.21
-1.58
3.19
1989 to 1990
2.83
1.44
4.36
3.53
4.97
2.07
0.39
-1.02
-0.94
-0.49
2.71
-0.48
16.91
4.87
2.29
5.41
-3.69
4.34
3.93
7.59
6.28
4.80
2.60
7.37
4.12
2.26
1.96
-3.19
3.04
26
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Table 111-3
BEA SQ-5 National Growth In Earnings By Industry
Percent
Growth from
Industry 1990 to 1991
Farm -18.38
Agricultural services, forestry, fisheries, and other -5.06
Coal mining -0.75
Construction -10.37
Manufacturing -3.01
Nondurable goods -0.89
Durable goods -4.30
Wholesale trade -2.55
Retail trade . -2.84
Services 1.91
Government and government enterprises 1.16
Federal, civilian -0.49
Federal, military -1.94
State and local 2.00
27
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estimates incorporating rule effectiveness. First, base year controlled emissions are
projected to the inventory year using the following formula:
CErCE^CE^EG) (1)
where:
= Controlled Emissions for inventory year i
CEBY = Controlled Emissions for base year
= Earnings Growth for inventory year i
Earnings growth (EG) is calculated as:
DATi (2)
DATBY
where:
DAT; = Earnings data for inventory year i
DATBY = Earnings data in the base year
Second, uncontrolled emissions in the inventory year are back-calculated from the
controlled emissions based on the control efficiency with the following formula
(I-CEFF/IQQ)
where:
(3)
= Uncontrolled Emissions for inventory year i
= Controlled Emissions for inventory year i
CEFF = Control Efficiency (%)
Third, controlled emissions are recalculated incorporating rule effectiveness using the
following formula:
a&ruM***L}(™L^ (4)
' ^ (^ 100 ) ( 100 })
where:
= Controlled Emissions Incorporating Rule Effectiveness
UC; = Uncontrolled Emissions
REFF = Rule Effectiveness (%)
CEFF = Control Efficiency (%)
The 80 percent rule effectiveness assumption was judged to be unreasonable for
several VOC and CO source categories. The VOC rule effectiveness was changed to 100
percent for bulk storage tank sources that had VOC control devices of 90, 91, or 92.
These three codes represent conversion to variable vapor space tank, conversion to
floating roof tank, and conversion to pressurized tank, respectively. These controls were
28
-------
judged to be irreversible process modifications (there are SCCs which represent these
types of tanks), and therefore 100 percent rule effectiveness was applied. VOC and CO
rule effectiveness was changed to 100 percent for all Petroleum Industry - Fluid Catalytic
Cracking Units (FCCs), SCC 30600201. AP-42 lists CO wasteheat boilers as a control for
these units with both CO and hydrocarbon emissions reduced to negligible levels. Since
these boilers handle VOCs and CO as a fuel rather than as an emission, they are treated
as a process instead of as control device, and therefore are not subject to rule
effectiveness. Unfortunately, there is no control device code for CO boilers in NAPAP. In
order to implement this set of revisions, all FCCs were assumed to have CO boilers. In
addition, the CO rule effectiveness was changed to 100 percent for sources in 6 other
SCCs that burn CO as a fuel. The justification for this approach is the same as for
revising the rule effectiveness for FCCs. Finally, the CO rule effectiveness was changed
to 100 percent for sources with In-Process Fuel Use SCCs. According to AP-42, there
should be no CO emissions from these sources. We did not delete emissions from the
inventory, however applying 80 percent rule effectiveness resulted in CO emission
estimates of up to 36,000 tons from some In-Process Fuel Use sources. Changing the rule
effectiveness to 100 percent for sources in these SCCs retains the emissions, but at more
reasonable levels. Table ni-4 lists the SCCs for which the CO rule effectiveness was
changed to 100 percent.
D. EMISSION SUMMARY
An emission summary by major source category for the non-utility point source
inventories is shown in Table III-5. The emission summaries in Table III-5 represent
emissions from non-utility point sources contained in the 1985 NAPAP Inventory,
adjusted to subsequent inventory years. There are uncertainties associated with using
this methodology to estimate point source emissions, however. The primary uncertainty
related to this approach is that it does not consider plant shutdowns and new plant
openings, which, if occurring after 1985, could increase or decrease the level of emissions
estimated for subsequent inventory years. While the earnings-based growth indicators
will account for growth/decline in industries, these factors will be applied to all sources
within the State rather than accounting for individual plant openings/shutdowns.
29
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Table 111-4
SCCs With 100 Percent CO Rule Effectiveness
sec
Process
30300801 Primary Metals Production - Iron Production - Blast Furnaces
30300913 Primary Metals Production -Steel Production - Basic Oxygen Furnace: Open Hood-Stack
30300914 Primary Metals Production -Steel Production - Basic Oxygen Furnace: Closed Hood-Stack
30500401 Mineral Products - Calcium Carbide - Electric Furnace (Hoods and Main Stack)
30600201 Petroleum Industry - Fluid Catalytic Cracking Units
31000205 Oil and Gas Production - Natural Gas Production - Flares
31000299 Oil and Gas Production - Natural Gas Production - Other Not Classified
39000689 In-Process Fuel Use - Natural Gas - General
39000797 In-Process Fuel Use - Process Gas - General
30
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Table III-5
Summary of National Non-Utility Point Source Emissions
Emissions (thousand tons)
Category
VOC
Utility
Industrial Combustion
Other Combustion
Chemical Manufacturing
Metals
Petroleum
Other Industrial
Solvent
Storage and Transport
Waste Disposal
Miscellaneous
Total
NOX
Utility
Industrial Combustion
Other Combustion
Chemical Manufacturing
Metals
Petroleum
Other Industrial
Solvent
Storage and Transport
Waste Disposal
Miscellaneous
Total
1987
1
404
9
1,204
70
338
377
1,178
577
7
0
4,166
48
1,881
94
397
76
101
314
3
3
18
0
2,907
1988
1
270
9
1,305
74
318
396
1,219
599
3
1
4,200
50
1,904
97
397
82
100
310
3
3
19
0
3,004
1989
1
264
10
1,301
74
317
396
1,213
591
8
1
4,175
49
1,918
97
393
83
97
306
3
3
19
0
2,971
1990
1
264
10
1,315
72
323
399
1,199
593
8
1
4,184
50
1,933
99
398
81
100
301
2
3
20
0
2,989
1991
1
268
10
1,324
69
326
397
1,168
595
a
1
4,168
50
1,922
99
400
79
103
293
2
4
20
0
2,972
31
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Table 111-5 (continued)
Emissions (thousand tons)
Category
CO
Utility
Industrial Combustion
Other Combustion
Chemical Manufacturing
Metals
Petroleum
Other Industrial
Solvent
Storage and Transport
Waste Disposal
Miscellaneous
Total
S02
Utility
Industrial Combustion
Other Combustion
Chemical Manufacturing
Metals
Petroleum
Other Industrial
Solvent
Storage and Transport
Waste Disposal
Miscellaneous
Total
1987
10
468
92
1,756
1,984
455
711
2
91
73
0
5,642
29
2,461
184
410
946
445
416
1
19
20
0
4,931
1988
11
479
91
1,873
2,101
441
708
2
100
76
0
5,882
31
2,507
193
433
1,032
443
409
1
21
21
0
5,089
1989
11
475
92
1,880
2,132
436
714
2
101
76
0
5,918
30
2,477
198
423
987
429
403
1
20
21
0
4,990
1990
11
475
90
1,893
2,080
435
715
2
102
76
0
5,877
31
2,479
203
424
908
440
399
1
21
21
0
4,926
1991
11
472
87
1,906
1,992
439
709
2
103
74
0
5,795
30
2,449
204
426
874
444
390
1
21
21
0
4,860
32
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CHAPTER IV
MOTOR VEHICLE EMISSIONS
Motor vehicle emissions in the 1990 Interim Inventory include all gasoline- and
diesel-fueled highway vehicles. Two major groups of data were developed for the Interim
Inventory. A 1990 VMT inventory was developed based on data from the FHWA's HPMS
(FHWA, 1992a). The 1990 VMT estimates were then adjusted to the other inventory
years based on gasoline consumption data. EPA's MOBILES mobile source emission
factor model (EPA, 1992a) was used to develop emission factors for each of the inventory
years.
Two sets of emission factors were developed for each inventory year in the revised
Interim Inventory. The first set was modeled with summer season Reid Vapor Pressure
(RVP) levels and a wide range of temperatures. These emission factors were created for
use as input to the Regional Oxidant Model (ROM) model. The second set of emission
factors were modeled with RVPs for each season and average seasonal temperatures for
each State. Together with the VMT estimates, these emission factors were used to
calculate annual emission estimates. This chapter describes the methodologies used to
develop VMT data, emission factors, and emission estimates.
A. BACKGROUND ON HPMS
1. Description of HPMS
HPMS is a national data collection and reporting system administered by FHWA in
cooperation with State highway programs. HPMS contains data on the mileage, extent,
and usage of the various functional road systems, the condition and performance of
pavements, physical attributes of roads, road capacity and improvement needs, and other
data important to the structural integrity and operation of the nation's road systems
(FHWA, 1987a). The data that make up HPMS are submitted to FHWA annually by each
State highway program.
HPMS has three main data components: (1) the universe data base, (2) the sample
data base (a subset of the universe data base), and (3) the areawide data base. The
universe data base contains a complete inventory of all mileage for all functional systems,
except local roads. The sample data base contains more detailed information for a subset
of the highway sections in the universe data base. Each record in the sample data base is
part of a sample panel which can be expanded to represent the universe of highway
mileage. The areawide data base contains annual State-level summaries of the major
components of HPMS. Most of the State-level data in the areawide data base are divided
into rural, small urban, and individualized urban area components. Table IV-1 illustrates
33
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Table IV-1
Data Components of HPMS
Universe - All Road Mileage
Identification
System
Jurisdiction
Operation
Other
Contains State, county, and rural/small urbanized codes and a unique
identification of location reference.
Optionally, the latitude and longitude coordinates for the beginning and
ending points of universe and sample sections are provided.
Provides for coding of functional system and Federal-aid system.
Provides for coding of State or local highway system and special
funding category.
Includes type of facility, truck prohibition, and toll.
Contains length of highway section and fields for the coding of AADT
and the number of through lanes.
Sample - Statistical Sample of Universe
Identification
Computational Elements
Pavement Attributes
Improvements
Geometries/Configuration
Traffic/Capacity
Environment
Supplemental Data
Contains unique identification for the sample section portion of the
record.
Provides data items used to expand sample information to universe
values.
Contains data items used to evaluate the physical characteristics of
pavement, pavement performance, and the need for pavement overlays.
Describes the improvement type for the year of the improvement
completion.
Describes the physical attributes used to evaluate the capacity and
operating characteristics of the facility. '
Provides operational data items used to calculate the capacity of a
section and the need for improvements.
Contains items that marginally affect the operation of a facility but are
important to its structural integrity.
Provides linkage to existing structure and railroad crossing information
systems.
Areawide • State Summaries
Mileage
Travel
Accidents
Injuries
Population
Road mileage
Vehicle miles traveled, percent travel by vehicle type
Number of accidents
Number of injuries
Area population
34
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the main data components of HPMS and the type of data they contain (FHWA, 1987a).
The travel data in HPMS are of great interest in estimating VMT. HPMS travel data are
based on samples of daily traffic counts taken at various points in a State's roadway
network. These daily traffic counts are expanded to annual average daily traffic (AADT).
To calculate VMT for a specific section of road, the AADT for that section of road is
multiplied by the road length (FHWA, 1985).
HPMS also includes an analysis component which uses a series of computer programs
to analyze the data furnished by the States. The impact analysis (one of several different
analyses in the analysis component) provides a comparison of vehicle performance
measures under different scenarios. One of the performance measures in the impact
analysis is average overall travel speed (FHWA, 1987b). The average overall travel speed
output from the HPMS impact model was used as the basis for determining the
distribution of speeds to use in estimating emissions. The impact analysis average overall
speed output and the derivation of the speeds used to model emissions will be discussed
later in this chapter.
2. Rationale for Using HPMS to Estimate VMT
There are two primary reasons for using HPMS data to estimate VMT. First, HPMS
has the best available VMT data for 1990. HPMS is a source of consistent VMT data
from States. Integrity of the data, which is consolidated in a single source, has been
checked at both the State and Federal (FHWA) level. Second, EPA has directed States to
use HPMS to estimate VMT for their 1990 State Implementation Plan (SIP) inventories.
The use of HPMS data to estimate VMT for the 1990 Interim Inventory closely
approximates the methods that will be used in the 1990 SIP inventories, and will
therefore yield VMT estimates that are consistent with those in SIP inventories.
3. Problems with Using HPMS to Estimate VMT
There are several complexities associated with using HPMS data to estimate VMT for
this inventory. The county is the basic geographic unit in the 1990 Interim Inventory,
while all data in HPMS are divided into rural, small urban, and individualized urban
geographic areas. In order to use the HPMS data, a mechanism to distribute VMT from a
rural, small urban, and individual urban area level to a county level had to be developed.
In addition, the level of detail of reporting in the sample data base (the most detailed data
base which contained VMT information) varied from State to State. Some States reported
data for each individual urban area, some States reported data for all individual urban
areas together, and some States reported data separately for some individual urban areas
and reported data for the remaining individual urban areas together. This made
distributing VMT from the sample data base to counties a difficult task. In the areawide
data base, however, all States reported data for individual urban areas separately.
Finally, travel data for local road systems were only contained in the areawide data base.
Given the problems described above and the limited timeframe of the project, the
areawide data base was used to generate county-level VMT estimates. The methodology
used to generate county-level VMT estimates is described below.
35
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B. GENERATION OF VMT ESTIMATES
County-level VMT estimates for 1990 were developed based on VMT data from the
1990 HPMS areawide data base. The HPMS areawide data base contains estimates of
daily VMT for each State. For each State, the HPMS areawide data base contains
estimates (segregated by functional road system) of daily VMT for all travel in rural
areas, estimates of daily VMT for all travel in small urban areas, and separate estimates
of daily VMT for travel in each of the State's large urbanized area.
Three procedures had to be performed to the HPMS VMT in order for it to be used in
the Interim Inventory. First, the rural, small urban, and large urban 1990 VMT in each
State had to be distributed to the counties in that State based on population data.
Second, 1990 county-level VMT estimates had to be allocated to the six vehicle types used
in the AERS-Area and Mobile Source Subsystem (AIRS-AMS) based on HPMS and other
FHWA data. Finally, the 1990 county-level VMT estimates were adjusted to the other
inventory years based on gasoline consumption data (DOE, 199 la). The methods used to
perform each of these three procedures are described below.
1. Distribution of HPMS VMT to Counties
VMT from the HPMS areawide data base was distributed to counties based on each
county's rural, small urban, and urbanized area population. Two tables in the Bureau of
the Census 1980 Number of Inhabitants (CNOI) documents (BOG, 1983) were used as the
source for population data. The 1980 population data had to be used to allocate the VMT
because the Census Urbanized Area boundaries were changed for the 1990 census.
Although not exactly the same, the large urban area boundaries used in HPMS are based
on the 1980 Census Urbanized Area boundaries. Use of the 1990 Census Urbanized Area
boundaries would prevent a one-to-one match between HPMS large, urban-area VMT and
urbanized area population, making VMT distribution difficult.
The 'two CNOI tables used to distribute VMT to counties are:
• Table 3: Population of Counties by Urban and Rural
Residence. This table lists the urban population living inside
census-defined urbanized areas, the urban population living outside
census-defined urbanized areas, and the rural population for each
county.
• Table 13: Population of Urban Areas. This table divides an
urbanized area's population among the counties that contain
portions of that urbanized area.
County-level rural VMT, small urban VMT, and urbanized area VMT were calculated
separately using the following methodology. The methodology described below was
performed for each functional road system.
a. Rural VMT
1. The percentage of the State's rural population in each county was calculated using
county rural population data from CNOI Table 3.
36
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2. Each county's rural VMT was calculated by distributing State rural VMT from the
HPMS areawide data base, based on the percentage of the State's rural population
in each county using the following equation:
POP
where:
VMTR c = Rural VMT in county C (calculated)
VMTR'S = Rural VMT, State total (HPMS)
POPRC = Rural population in county C (CNOI)
POPB^S = Rural population, State total (CNOI)
6. Small Urban VMT
1. The percentage of the State's small urban population in each county was
calculated using county urban population living outside census-defined urbanized
areas from CNOI Table 3.
2.. Each county's small urban VMT was calculated by distributing State small urban
VMT from the HPMS areawide data base based on the percentage of the State's
small urban population in each county using the following equation:
POP
-VMT su'c
Vm'i
where:
VMTSUC = Small urban VMT in county C (calculated)
VMTsas = Small urban VMT, State total (HPMS) -
POPSUC = Small urban population in county C (CNOI)
= small urban population, State total (CNOI)
c. Urban Area VMT
1. For each urbanized area, the percentage of its population in each county
containing a portion of the urbanized area using data from CNOI Table 13.
2. Each county's share of. an urban area's VMT was calculated by distributing urban
area VMT from the HPMS areawide data base based on the percentage of the
urban area's population in each county using the following equation:
POP
(3)
UAyS
where:
Urban area's VMT in county C (calculated)
Urban area's VMT, State total (HPMS)
37
-------
POPUAC = Urban area's population in county C (CNOI)
POPUA]S = Urban area's population, State total (CNOI)
In a few cases, a single county contained parts of more than one urban area. For
those counties, urban VMT was calculated as the sum of the county's proportion of VMT
from each of the large urban areas in the county and the county's small urban VMT.
2. Allocation of VMT to the AIRS-AMS Vehicle Types
The VMT estimates in the HPMS data base are not divided by vehicle type. In order
for motor vehicle emission estimates to be separated into the appropriate AMS source
categories, VMT estimates were distributed to six different vehicle types: light-duty
gasoline vehicles (LDGV), light-duty gasoline trucks (LDGT), heavy-duty gasoline vehicles
(HDGV), light-duty diesel vehicles (LDDV), light-duty diesel trucks (LDDT), and heavy-
duty diesel vehicles (HDDV). For each of the 6 AMS vehicle types, emissions are further
divided into 12 roadway types. Therefore, each county's VMT estimates are divided into
72 AMS categories. Table IV-2 lists the 6 AMS vehicle types and the 12 roadway types
used in this inventory. Below is the methodology for allocating VMT among these six
different vehicle types for the 1990 Interim Inventory.
The primary data sources used in this methodology were the HPMS areawide data
base and the Bureau of the Census Truck Inventory and Use Survey (TIUS) (BOG, 1990).
In addition, travel data from the MOBILE4 Fuel Consumption Model was used to divide
LDV VMT into its gasoline and diesel components (EPA, 1989b).
The HPMS areawide data base contains travel activity by vehicle type and functional
system (expressed as a percentage of travel) for each State. These data served as the
basis for the vehicle type distribution. The problem with these data is that the vehicle
type categories used are different from the AMS source categories. The vehicle type
categories in HPMS are:
• motorcycles
• passenger cars
• other 2-axle, 4-tire, single-unit vehicles
• buses
• 2-axle 6-tire, single-unit vehicles
• 3-axle, single-unit trucks
• four or more axle, single-unit trucks
• four or fewer axle, single-trailer trucks
• 5-axle, single-trailer trucks
• six or more axle, single-trailer trucks
• five or fewer axle, multi-trailer trucks
• 6-axle, multi-trailer trucks
• seven or more axle, multi-trailer trucks
The following three steps redistributed the HPMS travel activity data into the AMS
source categories. The steps below were repeated for each State, and the resulting data
reflect travel activity percentages by AMS source category and functional system for each
State. These numbers were then applied to the county-level VMT estimates to obtain the
final VMT estimates needed for the inventory.
38
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Table IV-2
AMS Vehicle/Road Types
Vehicle Types
Light-Duty Gasoline Vehicle (LDGV)
Light-Duty Gasoline Truck (LDGT)
Heavy-Duty Gasoline Vehicle (HDGV)
Light-Duty Diesel Vehicle (LDDV)
Light-Duty Diesel Truck (LDDT)
Heavy-Duty Diesel Vehicle (HDDV)
Road Types
Interstate: Rural
Other Principal Arterial: Rural
Minor Arterial: Rural
Major Collector: Rural
Minor Collector: Rural
Local: Rural
Interstate: Urban
Other Freeway & Expressways: Urban
Other Principal Arterial: Urban
Minor Arterial: Urban
Collector: Urban
Local: Urban
39
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a. Calculate LDGV and LDDV Travel Percentages
The HPMS passenger car travel activity category was assumed to match the AMS
light-duty vehicle (LDV) categories. Therefore, the only calculation required to calculate
travel activity for the LDGV and LDDV categories was to divide the passenger car travel
activity into its gasoline and diesel components. Distribution of LDV travel to gasoline
and diesel vehicles was estimated using data from EPA's MO8ILE4 Fuel Consumption
Model (EPA, 1989b). Specifically, the distribution was calculated using the fuel
consumption model's estimates of 1990 gasoline and diesel VMT using the following
formulas:
LDGVPC,*
LDGVVMT
LDWMT
LDWMT
(5)
where:
LDGV
3 f
LDDV
3 f
PC
, f
LDGWMT
LDDWMT
LDWMT
Percentage of travel by LDGVs in State s on functional system
f (calculated)
Percentage of travel by LDDVs in State s on functional system
f (calculated)
Percentage of travel by passenger cars in State s on functional
system /(HPMS)
1990 national LDGV VMT (MOBILE4 FCM)
1990 national LDDV VMT (MOBILE4 FCM)
1990 national LDV VMT (MOBILE4 FCM)
In 1990, 98.4 percent of the LDV travel was by LDGVs and 1.6 percent was by
LDDVs.
b. Divide Truck Travel into its Light- and Heavy-Duty Components
The travel activity of the remaining 11 HPMS vehicle type categories (motorcycles are
not included in the inventory) was distributed to the light-duty truck (LDT) and heavy-
duty vehicle (HDV) categories using data from Table 11 of the TIUS. Table 11 contains
data on truck miles by vehicle size, truck type and axle arrangement. The TIUS uses the
following categories for vehicle size:
light
medium
light-heavy
heavy-heavy
- average vehicle weight of 10,000 Ibs or less
- average vehicle weight of 10,001 to 19,500 Ibs
- average vehicle weight of 19,501 to 26,000 Ibs
- average vehicle weight of 26,001 Ibs or more
These categories do not match the definitions used by AMS. In AMS, a LDT is
defined as any motor vehicle rated at 8,500 Ibs gross vehicle weight rating (GVWR) or
40
-------
less, and has a vehicle curb weight of 6,000 Ibs or less. By using the TIUS light truck
definition LDT travel activity was slightly overestimated and HDV travel activity was
slightly underestimate A because travel by trucks in the 8,500 to 10,000 Ibs range was
included in the LDT travel activity.
The TIUS divides truck miles among these categories for the following truck type and
axle arrangements:
• 2-axle, single-unit trucks
• 3-axle, single-unit trucks
• four or more axle, single-unit trucks
• 3-axle, truck-tractor with single trailer
• 4-axle, truck-tractor with single trailer
• five or more axle, truck-tractor with single trailer
• 5-axle, truck-tractor with double trailers
• 6-axle, truck-tractor with double trailers
• seven or more axle, truck-tractor with double trailers
(These categories match closely with the HPMS categories and were used to easily
distribute travel activity for HPMS categories that contain some LDT and some HDV
travel activity.)
Table IV-3 shows how the travel activity for the remaining HPMS vehicle type
categories was distributed. For the HPMS vehicle type categories listed in Table IV-3 as
having its travel activity distributed based on TIUS Table 11, the following formulas were
used:
(6)
(7)
where:
LDT., f H = Percentage of LDT travel in State s on functional system f by
HPMS vehicle type H (calculated)
Percentage of HDV travel in State s on functional system / by
HPMS vehicle type H (calculated)
Percentage of travel in State 5 on functional system /"by HPMS
vehicle type H (HPMS)
Truck miles for light trucks for truck type and axle arrangement ta
(TIUS)
Total truck miles for truck type and axle arrangement ta
To obtain the total percentage of LDT and HDV travel by State and functional system, the
travel percentages calculated above were summed using the following formulas:
11
(8)
41
-------
Table IV-3
Distribution of Truck Travel Activity
HPMS Vehicle Type Category
Distribution of Travel Activity
Other 2-axle, 4-tire, single unit vehicles
Buses
2-axle, 6-tire, single unit vehicles
3-axle, single-unit taicks
4 or more axle single-unit trucks
four or fewer axle, single trailer trucks
5-axle, single-trailer trucks
six or more axle, single-trailer trucks
five or fewer axle, multi-trailer trucks
6-axle, multi-trailer trucks
seven or more axle, multi-trailer trucks
Distribution to LOT and HOV based on TIUS
Table 11
All HDV
Distribution to LOT and HDV based on TIUS
Table 11
Distribution to LOT and HDV based on TIUS
Table 11
Distribution to LOT and HDV based on TIUS
Table 11
Distribution to LDT and HDV based on TIUS
Table 11
Distribution to LDT and HDV based on TIUS
Table 11
Distribution to LDT and HDV based on TIUS
Table 11
All HDV
All HDV*
All HDV'
NOTES:
'100 percent of truck miles in TIUS Table 11 in HOV categories.
42
-------
11
HD V
(9)
H-l
where:
LDT.
HDV.
LDT.
s,f,H
HDV.
3,f,H
c.
= Total percentage of LDT travel in State s on functional system /"by
HPMS vehicle type H (calculated)
= Total percentage of HDV travel in State s on functional system /"by
HPMS vehicle type H (calculated)
= Percentage of LDT travel in State s on functional system /"by
HPMS vehicle type H (calculated in equation 6)
= Percentage of HDV travel in State s on functional system /"by
HPMS vehicle type H (calculated in equation 7)
Divide LDT and HDT Travel into its Gasoline and Diesel
Components
The final step was to divide the travel activity percentages calculated in Step 2 into
gasoline and diesel components. TIUS Table 11 also contains data on truck miles by
vehicle size and engine type. The percentage of travel activity distributed to gasoline and
diesel was based upon the proportion of gasoline and diesel truck miles reported in Table
11 for LDTs and HDVs, respectively. The following formulas were used to calculate the
gasoline and diesel components of truck travel:
LDGT,,=LDT,,*
•i • ./
LG™
(10)
LDTM
'LTTM
(11)
:HGTM
'HTTM
,HDTM
HTTM
(13)
where:
LDGTs,f =
LDDTs,f =
LDT3>f =
HDV8,f =
LGTM
Total percentage of LDGT travel in State s on functional system f
(calculated)
Total percentage of LDDT travel in State s on functional system /
(calculated)
Total percentage of LDT travel hi State s on functional system /"by
HPMS vehicle type H (calculated in equation 8)
Total percentage of HDV travel in State s on functional system /by
HPMS vehicle type H (calculated in equation 9)
Truck miles for light gasoline trucks (TIUS)
43
-------
LDTM = Truck miles for light diesel trucks (TIUS)
LTTM = Total truck miles for light trucks (TIUS)
HGTM = Truck miles for heavy gasoline trucks (TIUS)
HDTM = Truck miles for heavy diesel trucks (TIUS)
HTTM = Total truck miles for heavy trucks (TTUS)
The travel percentages by functional system and vehicle type for each State calculated
using the above methodology were then applied to the 1990 county-level VMT estimates
resulting in 1990 county-level VMT estimates for each motor vehicle AMS SCC. County-
level VMT estimates were thus produced for each of the AMS categories shown hi Table
IV-2.
3. Projecting VMT to Other Inventory Years
The 1990 county-level VMT was adjusted to the other inventory years based on State
Energy Data System (SEDS) gasoline consumption data (DOE, 1991a). SEDS contains
annual motor gasoline consumption data for each State. At the time the Interim
Inventory was developed, 1989 was the latest year for which SEDS data existed. The
1990 and 1991 State motor gasoline consumption was projected using 1985 through 1989 •
SEDS gasoline consumption data with the following log linear regression equation:
Average miles per gallon (mpg) estimates from the MOBILE4 Fuel Consumption
Model (EPA, 1989b) were then applied to each State's gasoline consumption in each
inventory year resulting in VMT estimates for the years 1987 through 1991. The mpgs
used in this calculation were:
Average mpg
15.14
15.44
15.73
15.98
16.21
These VMT estimates were used to adjust the 1990 VMT to the other inventory years.
These State-level growth figures were then applied to the 1990 VMT (calculated from the
HPMS data) which produced VMT estimates for the other inventory years. Table IV-4
lists the national VMT estimates for the years 1987 through 1991.
C. EMISSION. FACTOR CALCULATION
Two sets of motor vehicle emission factors were developed for the years 1987 through
1991. The first set, described below, was developed for input to the Flexible Regional
Emissions Data System (FREDS). The FREDS factors were modeled using 60 different
temperatures. These emission factors are used to estimate motor vehicle emissions on
specific ozone episode days using historical climatological data. The second set, described
later hi this chapter, was developed for use hi creating a separate but consistent data
base with annual and seasonal estimates of motor vehicle emissions.
44
-------
Table IV-4
National VMT Estimates
Year VMT (millions)
1987 1,897,412
1988 1,997,672
1989 2,036,376
1990 2,145,859
1991 2,228,069
45
-------
EPA's MOBILES mobile source emission factor model was used to calculate all
emission factors (EPA, 1992). The December 4, 1992, version of MOBILE5 was used for
this inventory. The pollutants modeled were exhaust nonmethane organic gas (NMOG),
evaporative NMOG (which includes resting loss, running loss, and evaporative emissions),
exhaust NOX, and exhaust CO. NMOG emissions include ethane and aldehydes in
addition to Flame lonization Detector (FED) measured hydrocarbons.
Nine speeds and 60 temperatures were modeled for each State. The nine speeds used
in the model were derived from the average overall speed output from the HPMS impact
analysis. Average overall speed data were obtained for the years 1987 through 1990
(1991 was not yet available) (FHWA, 1992b). The average overall speed for each vehicle
type varied less than one mile per hour (MPH) over the 4-year span. Therefore, the same
speeds (from 1990) were used for all years. Table IV-5 lists the average overall speed
output for 1990 from the HPMS impact analysis. To determine the actual speeds to use
in modeling the emission factors, HPMS vehicle types were chosen to represent the speeds
for each AMS vehicle type:
• passenger cars — used for LDVs (speeds for small and large cars
were the same)
• pickup trucks and vans ~ used for LDTs
• multi-trailer trucks with five or more axles -- used for HDVs
To reduce the number of speeds to be modeled, the HPMS speeds were rounded to the
nearest 5 miles per hour. Local speeds, which were not included in the HPMS impact
analysis output, were assumed to be the same as minor collector speeds for rural roads
and collector speeds for urban roads. Table IV-6 lists the average speed used for each
road type/vehicle type combination.
Each of the nine speeds was modeled at mean temperatures varying from 40°F to 95°F
in 5° intervals. Each mean temperature was modeled with diurnal ranges of 0°F, 10°F,
20°F, 30°F, and 40°F. The Federal Test Procedure (FTP) operating mode was modeled in
all cases, with 20.6 percent of VMT accumulated in cold-start mode, 27.3 percent of VMT
accumulated in hot-start mode, and 52.1 percent of VMT accumulated in stabilized mode.
Each State's emission factors were modeled at the July RVP level for the year being
modeled. RVP values for each year were developed using data from that year's summer
Motor Vehicle Manufacturers Association (MVMA) Fuel Volatility Survey (MVMA, 1991).
The following procedure was used to develop one representative July RVP for each
State to be used in the emission factor modeling. Twenty-three cities were included in the
MVMA surveys. EPA's Office of Mobile Sources (QMS) provided a listing that matched
the surveyed cities to a larger number of MSAs according to pipeline distribution maps
(Wolcott, 1992). States that had only one MSA in the QMS listing were assigned that
MSA's RVP for the whole State. For States containing more than one MSA in the OMS
listing, the mean RVP of all MSAs in the State was assigned to the whole State. For
States not containing any MSAs in the OMS listing, the RVP of the closest MSA in the
OMS listing was assigned to the whole State. Table IV-7 lists each State's July RVP
values based on the OMS listing used to estimate emission factors in each inventory year.
46
-------
Table IV-5
HPMS Average Overall Travel Speeds for 1990
(MPH)
Vehicle Type
Small Pass. Cars
Large Pass. Cars
Pickups & Vans
Single 2 Axle
Single 3+ Axle
Multi 4+ Axle
Multi 5+ Axle
Rural
Principal Minor Major Minor
Interstate Arterial Arterial Collector Collector
58.4 46.5 40.1 35.4 30.3
58.4 46.5 40.1 35.4 30.3
56.7 45.6 39.7 35.3 30.5
55.7 44.5 38.8 32.6 24.1
53.3 43.0 37.6 33.1 29.8
43.0 34.0 30.7 27.9 25.7
41.8 33.4 30.2 26.9 22.5
Urban
Other
Freeways
Interstate Expressways
46.3 42.4
46.3 42.4
45.4 41.9
47.1 42.9
45.4 41.5
37.2 34.4
36.4 33.8
Principal
Arterial
18.7
18.7
19.5
18.1
18.0
14.7
14.6
Minor
Arterial Collector
19.3 19.5
19.3 19.5
20.1 20.3
18.2 18.0
18.1 18.1
14.6 14.5
14.5 14.3
-------
Table IV-6
Average Speeds by Road Type and Vehicle Type
(MPH)
Rural
LDV
LOT
HDV
Interstate
60
55
40
Principal
Arterial
45
45
35
Minor Major
Arterial Collector
40 35
40 35
30 25
Minor
Collector
30
30
25
Local
30
30
25
Urban
Interstate
45
45
35
Other Freeways
& Expressways
45
45
35
Principal
Arterial
20
20
15
Minor
Arterial
20
20
15
Collector
20
20
15
Local
20
20
15
00
-------
Table IV-7
July RVPs Used to Model Motor Vehicle Emission Factors
State
AL
AZ
AR
CA
CO
CT
DE
DC
FL
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
Wl
WY
State Reid Vapor Pressure (psi)
1987
10.8
8.6
10.2
8.6
9.7
10.9
11.3
11.0
10.2
10.5
10.1
11.1
11.6
10.5
9.8
11.3
10.4
10.8
11.2
10.8
11.7
10.5
10.2
10.0
9.3
10.2
8.6
10.8
11.3
9.0
11.2
10.5
10.5
11.6
9.9
9.7
11.4
10.8
10.5
10.5
10.4
9.8
9.7
10.8
10.9
10.8
11.4
11.4
9.5
1988
10.9
8.3
9.8
8.5
9.4
11.0
10.8
10.8
10.5
10.7
9.9
10.6
11.1
10.3
9.6
10.9
11.0
11.0
10.8
11.0
11.0
10.3
9.8
9.7
9.5
9.9
8.5
11.0
10.9
8.5
11.0
10.7
10.3
11.4
9.7
9.4
10.9
11.0
10.7
10.3
10.5
9.6
9.4
11.0
10.8
10.2
11.2
10.9
9.4
1989
8.9
8.2
9.4
8.4
8.7
8.6
9.2
9.1
9.0
8.6
9.5
9.5
9.6
9.7
9.1
9.5
8.6
8.6
9.1
8.6
9.8
9.7
9.4
9.3
9.3
9.4
8.3
8.6
9.0
8.2
8.7
8.6
9.7
9.8
8.7
9.1
9.3
8.6
8.6
9.7
8.8
8.4
8.7
8.6
9.0
9.7
9.6
9.6
9.0
1990
8.5
8.1
8.7
8.1
8.3
8.3
8.4
8.2
9.1
8.5
9.1
8.6
8.7
9.6
8.5
8.7
8.3
8.3
8.3
8.3
9.1
9.6
8.7
8.6
3.6
9.1
8.2
8.3
8.4
8.1
8.3
8.5
9.6
9.6
8.2
8.9
8.6
8.3
8.5
9.6
8.5
8.0
8.3
8.3
8.3
9.6
9.1
8.8
8.4
1991
8.5
8.2
8.5
8.2
8.4
8.3
8.3
8.1
9.1
8.3
9.4
8.8
9.0
9.3
8.6
8.8
3.4
8.3
8.2
8.3
9.3
9.8
8.5
8.6
9.2
9.2
8.3
8.3
8.3
8.1
8.4
8.3
9.8
9.7
8.4
9.0
8.5
8.3
8.3
9.8
8.3
8.2
8.4
8.3
8.1
9.7
9.1
9.0
8.8
NOTES: Developed from July MVMA Fuel Volatility Surveys
49
-------
A second group of emission factors modeled with the above parameters was run for
each State with an inspection and maintenance (I/M) program in place in some or all of
its counties in the respective inventory years. The determination of whether or not a
county had an I/M program in place in a given year was based on an EPA report of I/M
program implementation status (EPA, 199 Ic). Emission factors calculated with I/M
benefits in a given inventory year were applied only to counties having an I/M program in
place hi December of the prior year. I/M program characteristics were also supplied by
EPA (EPA, 199 Ic). These program characteristics vary by State and in some cases by
substate areas. The effectiveness statistics used as MOBILES inputs varied by State
based on the characteristics of representative I/M programs in that State. For States
where I/M programs vary by substate regions, a single set of effectiveness statistics, based
on a combination of characteristics of all the I/M programs within the State, was used as
an I/M input to the model.
D. CALCULATION OF MOTOR VEHICLE EMISSIONS
Motor vehicle emissions were estimated for each inventory year using State-specific
seasonal emission factors and the VMT estimates described earlier in the chapter.
Seasonal changes in temperature, gasoline RVP, and travel activity have a large impact
on motor vehicle emissions. In order to accurately estimate annual motor vehicle
emissions, these variations in emission factors by season were incorporated into the
calculation. Seasonal VMT was estimated using the temporal allocation factors developed
for the 1985 NAPAP Inventory (EPA, 1990). Seasonal emission factors were calculated for
each State based on temperature and gasoline RVP. Annual motor vehicle emissions for
each State were calculated as the sum of the seasonal emissions. The remainder of this
chapter describes in detail the procedures used to calculate motor vehicle emissions.
2. Seasonal Emission Factors
The seasonal emission factors created to compute motor vehicle emissions were
calculated using the December 4, 1992 release of MOBILES. The inputs to MOBILES for
the seasonal emission factors were the same as those used to calculate the emission
factors for input to FREDS (described earlier in this chapter) with two exceptions. First,
the seasonal emission factors were calculated for each State based on season-specific
gasoline RVP. Second, the seasonal emission factors were calculated for each State based
on season specific temperatures. The procedures developed for estimating seasonal
gasoline RVP values and seasonal average maximum and minimum temperatures for each
State are described below.
a. Seasonal Gasoline RVP
This section describes the methodology used to apportion RVP values to each State by
season for 1987 through 1991. The steps involved in making these calculations were:
(1) determine the weighted July and January RVP for the 23 MVMA survey cities in each
of the 5 years, (2) assign a July and January RVP to each State for each of the 5 years,
(3) estimate the RVP for the other months for each State and each year, and (4) average
the monthly RVP values to obtain seasonal RVP values for each State and year.
50
-------
In step 1, data from the MVMA fuel volatility surveys for 1987 through 1991 were
used (MVMA, 1987-1991). The basic MVMA data included average January and July
RVP values for regular unleaded, intermediate, and premium unleaded gasoline in the 23
survey cities. Data for all three of these fuel types were not available for all 23 survey
cities, but each city had, at a minimum, RVP data for regular unleaded gasoline in
January and July. According to guidance issued in support of SIP emission inventories, if
the RVP for all three fuel types was given in the survey, the weighted RVP was calculated
as 50 percent of the RVP of regular unleaded gasoline plus 25 percent of the RVP of the
intermediate gasoline plus 25 percent of the RVP of the premium unleaded gasoline.
When the RVP for only one type of fuel was available, in addition to the RVP for regular
unleaded gasoline, the weighted RVP was calculated as 75 percent of the RVP of the
regular unleaded gasoline plus 25 percent of the RVP of either the intermediate or
premium gasoline, whichever was available. When the RVP was available only for
regular unleaded gasoline, the weighted RVP was the same as the RVP of the regular
unleaded gasoline. This procedure was followed separately for each of the 23 cities from
1987 through 1991 for both January and July.
The second step was to assign a weighted January and July RVP for each year to
every State. OMS provided a cross-reference listing of nonattainment areas throughout
the United States with the corresponding MVMA survey city whose RVP should be used
to represent that nonattainment area. These assignments were developed using pipeline
distribution maps. The corresponding January and July weighted RVP values were then
assigned to each of these nonattainment areas for all 5 years. The January or July RVP
values for a given year for all nonattainment areas within a State were then averaged to
estimate a single Statewide January or July RVP value for each year.
The next step was to estimate statewide RVP values for the remaining months, based
on the January and July RVP values. The ASTM schedule of seasonal and geographical
volatility classes was used as the basis for the RVP allocation by month (ASTM, 1988).
This schedule assigns one or two volatility classes to each State for each month of the
year. Volatility classes are designated by a letter from A through E, with A being the
least volatile. Several States are divided into two or more regions, with each region
having its own set of volatility class guidelines. The MOBILE4 User's Guide provides
guidance on which ASTM class to assign to each State for each month, when more than
one region is included for a State, or when two ASTM classes are listed for a given State
in a given month (EPA, 1989c). This guidance was followed here to select a single ASTM
class for each State and each month. The MOBILE4 user's guide also lists RVP limits
that correspond to each ASTM class from A through E (EPA, 1989c). These RVP limits,
in pounds per square inch (psi), are as follows: ASTM class A = 9.0 psi; ASTM class B =
10.0 psi; ASTM class C = 11.5 psi; ASTM class D = 13.5 psi; ASTM class E = 15.0 psi.
The January MVMA RVP for each State (determined in step 2 above) was assigned the
January ASTM class, and the July MVMA RVP for each State was assigned the July
ASTM class. Other months with the same ASTM class designation as either January or
July were assigned the MVMA January or July RVP value. The RVP for months with
intermediate ASTM class designations were calculated by interpolation using the January
and July MVMA RVP values and the ASTM class RVP limits. The equation used for this
interpolation is shown below.
51
-------
IM = [CIA - SA) * (WM - SM) I (WA - SA)] + SM
where:
IM = Intermediate month's (not January or July) MVMA RVP value
IA = Intermediate month's (non-January or July) ASTM RVP limit
SA = Summer (July) ASTM RVP limit
WM = Winter (January) MVMA RVP value
SM = Summer (July) MVMA RVP value
WA = Winter (January) ASTM RVP limit
This was calculated for each intermediate month for each State for each of the 5 years.
The final step in determining seasonal RVP values was to average the monthly RVP
values calculated in step 3. Whiter RVP values were calculated by averaging the
December, January, and February RVP values. Spring RVP was calculated as the
average of the March, April, and May RVP values. Summer RVP was calculated as the
average of the June, July, and August RVP values, and fall RVP was calculated as the
average of September, October, and November RVP values. This was done separately for
each year from 1987 through 1991 and for each State. Table IV-8 lists the 1990 seasonal
RVP values calculated for each State.
6. Seasonal Temperatures
Average seasonal maximum and minimum temperatures for each State were
developed for use as inputs to MOBILE4.1. Daily maximum and minimum temperatures
by State for each month were obtained from National Oceanic and Atmospheric
Administration (NOAA) documents (NOAA, 1982). The NOAA temperatures were
averages based on the 30-year period from 1951 to 1980. Each State's average seasonal
maximum and minimum temperatures were calculated by taking the average of the
monthly maximum and minimum temperatures. Winter temperatures were calculated by
averaging December, January, and February temperatures. Spring temperatures were
calculated by averaging March, April, and May temperatures. Summer temperatures
were calculated by averaging June, July, and August temperatures. Fall temperatures
were calculated by taking the average of September, October, and November
temperatures. Table IV-9 lists the seasonal temperatures used as MOBILES inputs for
each State.
2. Seasonal Allocation of VMT
Motor vehicle travel activity is not constant throughout the year. In order to best
estimate motor vehicle emissions, the annual VMT estimates calculated for the Interim
Inventory were allocated to seasons using the NAPAP temporal allocation factors (EPA,
1990). The NAPAP temporal allocation factors for motor vehicles did not vary by State.
The allocation factors used for each motor vehicle source category are listed in Table IV-
10. Generally speaking, for vehicle type other than trucks, travel activity is highest hi the
summer months.
52
-------
Table IV-8
1990 Seasonal RVP (psi) by State
State
AL
AZ
AR
CA
CO
CT
DE
DC
FL
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SO
TN
TX
UT
VT
VA
WA
WV
Wl
WY
Winter
12.8
10.1
13.4
12.3
11.5
13.2
13.9
12.2
11.9
12.5
12.5
13.7
13.8
13.4
12.5
12.9
12.2
13.1
13.4
13.1
13.8
13.4
13.4
12.4
13.1
13.0
10.9
13.1
13.8
11.6
13.4
12.5
13.4
13.9
13.1
12.4
13.9
13.1 „
12.5
13.0
12.7
12.4
11.5
13.1
12.1
13.6
13.5
13.7
12.2
Spring
10.3
8.5
10.7
10.1
9.6
10.2
10.5
9.1
9.1
10.2
10.5
10.5
10.6
11.2
9.5
9.6
10.0
10.1
10.2
10.1
10.9
11.0
10.7
10.7
10.1
10.5
8.8
10.1
10.5
9.0
10.2
11.0
11.8
11.2
9.6
10.4
10.6
10.1
11.0
10.9
11.1
9.9
10.0
10.1
9.1
11.1
10.8
10.7
9.8
Summer
9.1
8.1
8.7
8.1
8.5
8.3
8.4
8.2
9.1
9.1
9.1
8.6
8.7
10.0
8.5
8.7
8.9
8.3
8.3
8.3
9.1
9.6
9.4
8.6
8.6
9.1
8.2
8.3
8.4
8.1
8.3
9.1
9.6
9.6
8.2
8.8
8.6
8.3
9.1
9.6
9.1
8.0
8.5
8.3
8.2
9.6
9.1
8.8
8.4
Fall
9.7
8.3
10.9
8.7
9.3
10.2
9.4
9.1
9.1
9.6
9.5
9.6
9.7
11.2
9.0
9.6
9.4
10.1
9.3
10.1
10.9
10.3
10.0
10.2
10.1
9.5
8.5
10.1
10.5
9.3
10.2
10.4
10.9
10.4
8.9
9.6
10.6
10.1
10.4
10.0
10.5
8.6
9.3
10.1
9.1
10.4
9.9
9.7
8.8
NOTES: Based on RVPs from the January and July MVMA Fuel Volatility Surveys interpolated to spring and fall.
53
-------
Seasonal Maximum and Minimum Temperatures (°F) by State
State
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
Wl
WY
Min
42
20
41
32
45
18
19
25
29
52
34
66
25
17
21
15
23
27
44
14
26
25
14
5
36
22
14
15
21
12
25
24
21
32
1
22
28
35
24
22
34
7
31
37
22
11
31
30
26
15
17
Winter
Max
62
31
67
53
61
45
36
42
45
72
54
81
40
33
37
31
44
44
64
33
43
38
30
24
59
40
33
35
47
33
43
49
36
54
23
38
50
47
39
38
58
27
50
61
40
28
49
42
44
29
40
Spring
Min
57
32
54
50
50
34
38
42
47
62
50
69
37
39
41
39
44
45
59
33
43
41
33
32
53
44
31
40
31
32
41
40
39
48
30
40
48
42
41
38
51
34
50
54
37
33
47
39
43
35
30
Max
78
46
83
73
67
61
59
62
66
77
72
83
61
59
62
59
67
66
78
52
64
56
53
51
77
65
54
62
64
56
61
70
57
72
53
61
71
61
61
57
76
56
71
78
62
52
68
57
66
53
54
Summer
Min Max
72
46
76
70
59
56
60
64
68
73
68
73
56
62
63
64
68
66
73
55
65
63
55
56
70
66
52
64
45
• 54
62
62
61
67
54
61
69
55
62
61
69
59
69
71
58
56
67
53
62
59
52
91
63
103
92
78
85
83
84
86
89
87
87
86
83
84
84
91
86
90
76
35
79
77
78
92
87
80
86
87
80
82
91
81
88
82
82
91
77
83
80
91
84
89
95
89
78
86
76
84
78
80
Pall
Min
58
36
59
51
54
37
42
47
51
65
52
71
39
43
44
42
47
47
60
38
47
48
39
36
53
52
35
42
31
36
46
43
45
51
31
44
50
45
45
44
52
36
51
55
40
39
51
41
45
41
34
Max
79
47
86
75
73
66
63
66
69
82
73
86
64
63
65
63
69
68
79
59
68
62
57
54
78
67
58
65
69
60
66
71
62
73
57
64
73
64
65
63
76
60
73
79
66
57
71
59
67
59
60
SOURCE: NOAA, 1982.
54
-------
Table 1V-10
Temporal Allocation Factors by
Vehicle Type
Vehicle Type
LDGV
Rural
Urban
LDGT
Rural
Urban
HDGV
Rural and Urban
LDDV
Rural
Urban
LOOT
Rural
Urban
HDDV
Rural and Urban
Winter
0.216
0.234
0.216
0.234
0.250
0.216
0.234
0.216
0.234
0.250
Spring
0.239
0.255
0.239
. 0.255
0.250
0.239
0.255
0.239
0.255
0.250
Summer
0.289
0.265
0.289
0.265
0.250
0.289
0.265
0.289
0.265
0.250
Fall
0.256
0.245
0.256
0.245
0.250
0.256
0.245
0.256
0.245
0.250
SOURCE:
EPA, 1990.
55
-------
3. Emission Summary
An emission summary for the motor vehicle inventories is provided in Table IV-11.
SO2 emissions were not estimated using the procedures described in this chapter because
MOBILES does not include S02 emission factors. National S02 emissions were estimated
by vehicle type using the following S02 emission factors from AP-42:
Emission Factor
Vehicle Type (g/mile)
_____ _
LDGT 0.18
HDGV 0.36
LDDV 0.54
LDDT 0.54
HDDV 2.80
Motor vehicle NMOG emissions are normally highest during the ozone season
(summer) due to increased temperatures and travel activity. Figure IV-1 compares
average annual daily motor vehicle emissions with average ozone season daily motor
vehicle emissions for 1990. Figure IV-1 shows only a slight increase in average daily
motor vehicle NMOG emissions during the ozone season. The small increase in average
daily ozone season NMOG emissions reflects the dramatic difference between summer and
winter gasoline RVPs in 1990. The lower RVP of gasoline used during the summer
months has decreased evaporative NMOG emissions considerably from previous years.
Exhaust VOC emissions are highest at low temperatures.
56
-------
Table IV-11
Summary of Motor Vehicle Emissions
(thousand tons per year)
Pollutant
VOC
Light-Duty Gas Vehicles
Light-Duty Gas Trucks
Heavy-Duty Gas Vehicles
Diesels
Total
NOX
Light-Duty Gas Vehicles
Light-Duty Gas Trucks
Heavy-Duty Gas Vehicles
Diesels
Total
CO
Light-Duty Gas Vehicles
Light-Duty Gas Trucks
Heavy-Duty Gas Vehicles
Diesels
Total
SO2
Light-Duty Gas Vehicles
Light-Duty Gas Trucks
Heavy-Duty Gas Vehicles
Diesels
Total
1987
5,234
1,995
329
439
7,997
3,619
1,249
190
2,960
8,018
45,992
15,485
3,550
1,492
66,519
197
69
9
380
655
1988
5,163
1,935
319
443
7,860
3,648
1,239
199
3,056
8,141
46,014
15,162
3,515
1,558
66,249
208
72
9
401
690
1989
4,516
1,720
271
421
6,927
3,557
1,188
194
2,942
7,880
42,284
14,112
3,238
1,535
61,169
212
74
10
407
703
1990
4,431
1,670
257
421
6,779
3,657
1,189
202
2,977
8,024
42,378
14,051
3,118
1,599
61,146
223
77
10
431
741
1991
4,339
1,625
244
411
6,619
3,689
1,174
202
2,868
7,934
41,798
13,910
2,964
1,624
60,297
232
80
10
447
769
57
-------
Ol
00
200,000
150,000
100,000
c
o
50,000
Figure IV-1
Average Annual Daily Emissions vs. Average Ozone
Season Daily Emissions for Motor Vehicles
voc
fit Avg. Annual
NOx
Avg. Ozone Season
CO
-------
CHAPTER V
AREA SOURCE SOLVENT EMISSIONS
Solvent emissions are included as both point and area sources in the Interim
Inventories. Point source emissions (included in the non-utility point source inventory)
are based on the 1985 NAPAP Emission Inventory. The basis for the area source
component (the solvent inventory) is a material balance on total nationwide solvent
consumption. Total nationwide solvent emissions by end-use category are estimated from
national consumption figures with some adjustments to account for air pollution controls
and waste management practices. The nationwide emission estimates are then
apportioned to States and counties using census data and information on State and local
regulations pertaining to solvent emissions. At this stage, county- and category-level
point source emissions are deducted from the emission totals, and the balance of
emissions is included in the area source solvent inventory. The following sections describe
the development of national solvent emission estimates, apportionment to States and
counties, and short-term projections to the timeframes covered by the Interim Inventory.
A. OVERALL NATIONAL EMISSIONS ESTIMATES
The overall national solvents material balance can be summarized as follows:
National solvent Solvents Solvents conveyed
emissions (by end- National solvent destroyed by air to waste
use category) = consumption - pollution - management ,.. ^
controls operations
(It should be noted that this overall national material balance yields total solvent
emissions, including both point and area sources.)
National solvent usage estimates by end-use category were obtained from three main
sources. For paints and coatings, the main source was the U.S. Paint Industry Data Base,
prepared by SRI International for the National Paint and Coatings Association (Connolly
et al., 1990). Solvent usage estimates for other categories were obtained from industrial
solvent marketing reports (Frost & Sullivan, 1989; Freedonia, 1989). The base year for
this activity data and for the total solvent emission estimates is 1989.
The solvent emission methodology is designed to incorporate pollution control and
waste management information at the source category level. However, the timeframe of
the current effort was too tight to permit development of category-specific information.
The mass balance term for waste management was based on the EPA's data base for
hazardous waste treatment, storage, and disposal facilities (TSDF), which also forms the
basis for the TSDF portion of the Interim Inventory (EPA, 1989d). In essence, the portion
59
-------
of the TSDF inventory that is attributable to solvents is deducted from the current
solvents inventory in order to avoid double-counting. The TSDF deduction was
apportioned evenly to all industrial categories, and amounts to about 21 percent of total
solvent usage in these categories.
Solvent destruction adjustments in the nationwide material balance were based on
the same assumptions used for the 1985 National Emissions Data System (NEDS) and
the 1985 NAPAP Emissions Inventories. According to the data in NEDS and NAPAP, 16
percent of industrial surface coating emissions are assumed to be destroyed in air
pollution controls.
Table V-l lists the elements in the national solvent material balance by emission
source category. As discussed above, these elements are: national solvent consumption,
solvent destroyed in air pollution controls, solvent sent to .waste management operations,
and net solvent emissions. Table V-l also summarizes the major sources of these data.
B. DISTRIBUTION OF SOLVENT EMISSIONS TO STATES AND COUNTIES
The primary tools used to distribute national solvent emissions to States and counties
are 1988 census data bases (BOC, 1987; BOG, 1988a; BOG, 1988b). For each of the
source categories listed in Table V-l, State- and county-level solvent usage is assumed to
be proportional to a particular census measure. For consumer end-use categories, solvent
usage was distributed based on population. County-level employment data were used for
commercial and industrial end-use categories. Census data on the number of farm acres
treated with chemical sprays were used to distribute pesticide solvent usage. Table V-2
lists the specific census data used for each emission category.
State and local regulations covering solvent emissions were also incorporated in the
spatial distribution step for the solvent inventories. For an industrial or commercial end-
use category, the overall spatial distribution calculation can be summarized as follows:
County County Estimated control efficiency for
emissions (by = National * employment * county
end-use category) emissions National Nationwide average control efficiency /Q\
employment for category
Quantitative information on State- and county-level control efficiency, rule
effectiveness, and rule penetration was obtained primarily from surveys carried out under
EPA's ongoing ROM modeling effort (EPA, 1991d). For States outside the ROM domain,
these parameters were estimated using Bureau of National Affairs regulation summaries.
60
-------
Table V-1
National Material Balance for Solvent Emissions
Category Description
Surface Coating
2401001 Architectural
2401005 Auto refinishing
2401008 Traffic markings
2401015 Flat wood coating
2401020 Wood furniture
2401025 Metal furniture
2401030 Paper coating
2401040 Can coating
2401045 Coil coating
2401055 Electrical insulation
2401060 Appliances
2401065 Machinery
2401070 Motor vehicles (new)
2401075 Aircraft coating
2401080 Marine paints
2401085 Rail equip, coating
2401090 Misc. manufacturing
2401100 Industrial maintenance
2401200 Aerosols, spec, purpose
Vapor Decreasing (Conveyorized and
2415105 Furniture
2415110 Metallurgical proc.
24 1 5 1 20 Fabricated metals
2415125 Industrial machinery
2415130 Electrical equipment
2415135 Transportation equip.
2415140 Instrument mfg.
2415145 Misc. manufacturing
Cold Cleaner Degreasing
2415305 Furniture
2415310 Metallurgical proc.
2415320 Fabncated metals
2415325 Industrial machinery
2415330 Electrical equipment
2415335 Transportation equip.
2415340 Instruments
2415345 Misc. manufacturing
2415355 Automobile dealers
241 5360 Automobile repair
2415365 Other
Other Categories
2420010 Drycleaning (perc.)
2420010 Drycleaning (petroleum)
2420020 Coin-op drycleaning
2425000 Graphic arts
2430000 Rubber/plastics
2440020 Adhesives - industrial
2461021 Cutback asphalt
2461800 Pesticides - farm
2465100 Personal products
2465200 Household products
2465400 Automotive products
2465600 Adhesives - Comml.
Solvent
Usage
(1,000 tpy)
503
133
106
5
221
70
33
156
58
48
34
130
134
11
29
6
210
99
173
Open-Top)
9
29
97
100
98
36
48
17
12
8
38
52
16
12
8
19
191
70
5
135
134
2
276
43
460
200
260
228
186
650
350
Percent
Destroyed by
Air Pollution
Controls1
0
0
0
16
16
16
16
16
16
16
16
16
16
16
16
16
16
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
16
16
0
0
0
0
0
0
0
Percent Sent
to TSDFs*
0
0
0
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
21
0
0
0
0
0
0
Estimated
Emissions
(1,000 tpy)
503
133
106
3
139
44
21
99
37
30
21
82
85
7
18
4
132
78
137
7
23
76
79
77
28
38
13
9
7
30
41
12
9
6
15
151
55
4
107
105
1
174
30
363
200
260
228
186
650
350
Source
SRI International/
National Paint and
Coatings Institute
Total category
number from Frost
& Sullivan.
Industry
breakdowns from
EPA BOAT Report
for spent solvents.
Total category
number from Frost
& Sullivan.
Industry
breakdowns from
EPA BOAT Report
for spent solvents.
Frost & Sullivan
Frost & Sullivan
Frost & Sullivan
Frost & Sullivan
Frost & Sullivan
Freedonia Group
Asphalt Institute
Freedonia Group
Frost & Sullivan
Frost & Sullivan
Freedonia Group
Frost & Sullivan
NOTES: 'Based on the 1985 NEDS methodology. Does not include solvents that are captured and recycled.
'Calculated based on the TSOF sector of the 1985 NAPAP Inventory.
61
-------
Table V-2
Data Bases Used for County Allocation
AMS
Category
Surface Coating
2401001
2401005
2401008
2401015
2401020
2401025
2401030
2401040
2401045
2401055
2401060
2401065
2401070
2401075
2401080
2401085
2401090
2401100
2401200
Vapor Degreasing
2415105
2415110
2415120
2415125
2415130
2415135
2415140
2415145
Description
Architectural
Auto refmishing
Traffic markings
Flat wood coating
Wood furniture
Metal furniture
Paper coating
Can coating
Coil coating
Electrical insulation
Appliances
Machinery
Motor vehicles (new)
Aircraft coating
Marine paints
Rail equip, coating
Misc. manufacturing
Industrial maintenance
Aerosols, spec, purpose
(Conveyorized and Open-Top)
Furniture
Metallurgical proc.
Fabricated metals
Industrial machinery
Electrical equipment
Transportation equip.
Instrument mfg.
Misc. manufacturing
Allocation Data
(from the Census)
Population
Employment in SIC 7532
Population
Employment in SIC 2430
Employment in SIC 25
Employment in SIC 25
Employment in SIC 26
Employment in SIC 341
Employment in SIC 344
Employment in SIC 36
Employment in SIC 363
Employment in SIC 35
Employment in SIC 371
Employment in SIC 372
Employment in SIC 373
Employment in SIC 374
Employment in SIC 20-39
Employment in SIC 20-39
Population
Employment in SIC 25
Employment in SIC 33
Employment in SIC 34
Employment in SIC 35
Employment in SIC 36
Employment in SIC 37
Employment in SIC 38
Employment in SIC 39
Cold Cleaner Degreasing
2415305
2415310
2415320
2415325
2415330
2415335
2415340
2415345
2415355
2415360
2415365
Other Categories
2420010
2420010
2420020
2425000
2430000
2440020
2461021
2461800
2465100
2465200
2465400
2465600
Furniture
Metallurgical proc.
Fabricated metals
Industrial machinery
Electrical equipment
Transportation equip.
Instruments
Misc. manufacturing
Automobile dealers
Automobile repair
Other
On/cleaning (perc.)
Or/cleaning (petroleum)
Coin-op drycleaning
Graphic arts
Rubber/plastics
Adhesives - industrial
Cutback asphalt
Pesticides - farm
Personal products
Household products
Automotive products
Adhesives - Comml.
Employment in SIC 25
Employment in SIC 33
Employment in SIC 34
Employment in SIC 35
Employment in SIC 36
Employment in SIC 37
Employment in SIC 38
Employment in SIC 39
Employment in SIC 55
Employment in SIC 75
Employment in SIC 22
Employment in SIC 7216
Employment in SIC 7216
Employment in SIC 7215
Employment in SIC 27
Employment in SIC 30
Employment in SIC 20-39
Population
Farm acres treated with sprays
Population
Population
Population
Population
62
-------
C. DEDUCTION OF POINT SOURCE EMISSIONS
The area source inventory is produced by deducting point source emissions from the
county-level category emission totals produced in equation 2. The calculation is
performed as follows:
County-level area source Total county-level County-level point
emissions (by end-use = emissions (equation 2) - source emissions (q\
category)
The AMS solvent categories were first matched to the corresponding point source
SCCs. Using the Interim 1990 Point Source Inventory, point source totals by county for
each corresponding AMS SCC were calculated. These emissions were then subtracted
from the total solvent emissions (the 1989 total solvent emissions were projected to 1990
as described below) to yield the area source emission estimate. In the cases of negative
emissions (higher point source emission estimates than total estimated solvent emissions),
the NAPAP methodology (EPA, 1988) was followed - area source emissions were set to
zero.
D. PROJECTING SOLVENT EMISSIONS TO OTHER INVENTORY YEARS
The Interim Inventories give annual area source solvent emissions for 5 calendar
years (from 1987 through 1991). The total solvent inventory was based on 1989 activity-
level data. (Spatial allocations for the solvent area source inventory were based on the
1988 census, which provides the most recent data available at the county level.)
Projections to other years covered by the Interim Inventory are based on State-level
earnings data for major industrial categories, which generally correspond to 2-digit SICs.
A description of the BEA data can be found in Chapter III. The following algorithm is
used for the emission projection:
Projection year emissions Projection year earnings (by
(by county and end-use Base year State and 2-digit SIC)
category) = emissions * Base year earnings / j\
In this equation, the projection year represents the appropriate calendar year for the
Interim Inventory (ranging from 1987 to 1991). The total solvent inventory was first
projected to 1990 to complete the point source deduction described above. After deducting
the point source solvents, this 1990 area source solvent data base was then scaled-
back/projected to the other inventory years.
The county/source category emissions predicted using changes in BEA earnings data
were then scaled according to expected changes in national solvent emissions. Annual
changes in national solvent usage (by end-use category) were taken from the solvent
marketing reports (Frost & Sullivan, 1989; Freedonia, 1989). All county-level emissions
within an end-use category were scaled by a factor so that total national emissions would
be equivalent to the national solvent emission estimates reported in the literature.
E. EMISSION SUMMARY
A summary of solvent emissions by source category is given in Table V-3.
63
-------
Table V-3
Solvent Inventory Emission Summary
Annual VOC Emissions (1,000 tpy)
Source Category
Degreasing
Graphic Arts
Dry Cleaning
Surface Coating
Other Industrial
Nonindustrial
Total
1987
613
127
216
1,910
29
1,778
4,672
1988
682
138
215
1,928
29
1,845
4,838
1989
684
137
212
1,922
29
1,878
4,862
1990
686
136
209
1,917
28
1,911
4,887
1991
687
136
205
1,918
28
1,946
4,919
64
-------
CHAPTER VI
AREA SOURCE EMISSIONS
The basis for the emission estimates for area source (non-solvent) categories is the
1985 NAPAP Area Source Emissions Inventory (EPA, 1989a), with the exception of
nonroad mobile sources. This chapter discusses area source emission estimates performed
for this study other than those for highway vehicles and solvent use. The methodology
used to estimate emissions for the inventory years including the sources for growth
indicators, revisions to emission estimates, updated emission factors, and control
efficiency assumptions are discussed. Nonroad mobile source emission estimates are
based on a 1990 nonroad emission inventory compiled by EPA (EPA, 1992b).
A. GROWTH INDICATORS
Emission estimates from the 1985 NAPAP Inventory were grown to the Interim
Inventory years based on historical BEA earnings data (see Chapter III), historical
estimates of fuel consumption (DOE, 199la), or other category-specific growth indicators.
Table VI-1 shows the growth indicators used for each NAPAP area source category.
The SEDS data (DOE, 1991a) were used as an indicator of emissions growth for the
area source fuel combustion categories and for the gasoline marketing categories shown in
Table VI-1. (SEDS reports fuel consumption by sector and fuel type.) Since fuel
consumption is the activity level used -to estimate emissions for these categories, fuel
consumption is a more accurate predictor of changes in emissions, compared to other
surrogate indicators such as earnings or population. SEDS fuel consumption data were
available through 1989. The 1990 and 1991 values were extrapolated from the 1985
through 1989 data using a log linear regression technique. In addition to projecting 1990
and 1991 data for all fuel consumption categories, the regression procedure was used to
fill in missing data points for fuel consumption categories if at least three data points in
the time series (1985 to 1989) were available.
Due to the year-to-year volatility hi the SEDS fuel consumption data for the
commercial residual oil fuel use category, the regression technique used above did not
yield realistic projections for 1990 and 1991 for this category. Therefore, a different
procedure was used to project 1990 and 1991 data for commercial residual oil fuel use.
State-level sales volumes of residual fuel to the commercial sector were obtained from
Fuel Oil and Kerosene Sales 1990 (DOE, 1991b) for 1989 and 1990. Each State's growth
in sales of residual fuel to the commercial sector from 1989 to 1990 was applied to that
State's 1989 SEDS commercial residual fuel consumption to yield a 1990 consumption
estimate. Sales data for 1991 were not yet available; the growth decline from 1990 to
1991 was assumed to be the same as from 1989 to 1990. A summary of SEDS national
fuel consumption by fuel and sector can be found in Table VI-2.
65
-------
Table VI-1
Area Source Growth Indicators
NAPAP
sec
Category Description
Data
Source
Growth Indicator
1 Residential Fuel - Anthracite Coal SEDS
2 Residential Fuel - Bituminous Coal SEDS
3 Residential Fuel - Distillate Oil SEDS
4 Residential Fuel - Residual Oil
5 Residential Fuel - Natural Gas SEDS
6 Residential Fuel • Wood BEA
7 Commercial/Institutional Fuel - Anthracite Coal SEDS
8 Commercial/Institutional Fuel - Bituminous Coal SEDS
9 Commercial/Institutional - Distillate Oil SEDS
10 Commercial/Institutional - Residual Oil SEDS
11 Commercial/Institutional - Natural Gas SEDS
12 Commercial/Institutional - Wood BEA
13 Industrial Fuel - Anthracite Coal SEDS
14 Industrial Fuel - Bituminous Coal SEDS
15 Industrial Fuel - Coke BEA
16 Industrial Fuel * Distillate Oil SEDS
17 Industrial Fuel - Residual Oil SEDS
18 Industrial Fuel - Natural Gas SEDS
19 Industrial Fuel - Wood BEA
20 Industrial Fuel - Process Gas SEDS
21 On-Site Incineration - Residential BEA
22 On-Site Incineration - Industrial BEA
23 On-Site Incineration-Commercial/lnstitutional BEA
24 Open Burning - Residential BEA
25 Open Burning - Industrial BEA
26 Open Burning - Commercial/Institutional BEA
45 Railroad Locomotives
46 Aircraft LTOs - Military
47 Aircraft LTOs - Civil
48 Aircraft LTOs - Commercial
49 Vessels - Coal
50 Vessels - Diesel Oil
51 Vessels - Residual Oil
54 Gasoline Marketed SEDS
60 Forest Wild Fires
61 Managed Burning • Prescribed
62 Agricultural Reid Burning BEA
63 Frost Control - Orchard Heaters BEA
64 Structural Rres
Res - Anthracite
Res - Bituminous
v
Res - Distillate oil
Zero growth .
Res - Natural gas
Population
Comm - Anthracite
Comm - Bituminous
Comm - Distillate oil
Comm - Residual oil
Comm - Natural gas
Services
Ind - Anthracite
Ind - Bituminous
Total Manufacturing
Ind - Distillate oil
Ind - Residual oil
Ind - Natural gas
Total Manufacturing
Ind - LPG
Population
Total Manufacturing
Services
Population
Total Manufacturing
Services
Railroad ton-miles (national)
Military
Aircraft - civil
Aircraft - commercial
Cargo tonnage (national)
Cargo tonnage (national)
Cargo tonnage (national)
Trans - Motor gasoline
Zero growth
Zero growth
Farm
Farm
Zero growth
66
-------
Table VI-1 (continued)
NAPAP
sec
99
100
102
Category Description
Minor Point Sources
Publicly Owned Treatment Works
Fugitive Emissions From Synthetic Organic
Data
Source
BEA
BEA
BEA
Growth Indicator
Population
Electric, Gas, and Sanitary Services
Mfg - Chemicals and Allied Products
Chemical Manufacturing
103 Bulk Terminal and Bulk Plants BEA
104 Fugitive Emissions From Petroleum Refinery
105 Process Emissions From Bakeries BEA
106 Process Emissions From Pharmaceutical BEA
Manufacturing
107 Process Emissions From Synthetic Rber BEA
Manufacturing
108 Crude Oil and Natural Gas Production Fields BEA
109 Hazardous Waste Treatment, Storage, and BEA
Disposal Facilities (TSDFs)
Trucking and Warehousing
Refinery operating cap
Mfg - Food and Kindred Products
Mfg - Chemicals and Allied Products
Mfg - Textile Mill Products
Oil and Gas Extraction
Total Manufacturing
67
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Table VI-2
SEDS National Fuel Consumption
Category
1985
Anthracite Coal (thousand short
Commercial
Industrial
Residential
524
575
786
1986
tons)
494
470
740
1987
478
437
717
1988
430
434
646
1989
422
392
633
1990
410
387
615
1991
403
385
604
Bituminous Coal (thousand short tons)
Commercial
Industrial
Residential
Distillate Fuel
Commercial
Industrial
Residential
4,205
115,854
2,264
(thousand barrels)
107,233
203,659
171,339
4,182
111,119
2.252
102,246
206,108
173,736
3,717
111,695
2,002
101,891
210,699
176,822
3,935
117,729
2,119
98,479
209,553
182,475
3,323
117,112
1,789
91,891
197,035
178,629
3,470
118,322
1,869
95,385
205,856
184,501
3,515
120,414
1,893
96,712
208,503
187,994
Liquefied Petroleum Gases (thousand barrels)
Industrial 437,964 411,451 447,120 453,599 441,784 457,013 473,897
Motor Gasoline (thousand barrels)
Transportation 2,433,592 2,507,936 2,570,047 2,627,331 2,617,450 2,703,666 2,758,444
All Sectors
2,493,361 2,567,436 2,630,089 2,685,145 2,674,669 2,760,414 2,814,398
Natural Gas (million cubic feet)
Commercial 2,432 2,31 8
Industrial 6,867 6,502
Residential 4,433 4,314
Residual Fuel (thousand barrels)
Commercial 30,956 39,480
Industrial 120,002 132,249
2,430
7,103
4,315
41,667
107,116
2,670
7,479
4,630
42,256
105,448
2,719
7,887
4,777
35,406
95,646
2,810
8,120
4,805
27,776
118,122
2,928
8,495
4,922
28,216
158,077
68
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Additional data were gathered for several categories for use in the emission
projections. Growth indicators other than BEA or SEDS data were developed for
petroleum refinery fugitives and several off-road vehicle source categories, including
aircraft (commercial and civil), railroads, and marine vessels (other than gasoline-
powered).
Activity levels for aircraft are measured by the number of landing-takeoff operations
(LTOs). Annual LTO totals are compiled by the Federal Aviation Administration (FAA)
on a regional basis. Commercial aircraft growth is derived from the summation of air
carrier and air taxi regional totals of LTOs from FAA-operated control towers and FAA
traffic control centers (FAA, 199 la). These data are compiled on a regional basis, so the
regional trends were applied to each State. Civil aircraft growth indicators were also
developed from regional LTO totals. Civil aircraft activity levels were determined from
terminal area activity for the years 1985 through 1989, and from a 1990 forecast of
terminal area activity (FAA, 199 Ib). Military aircraft LTO totals were not available;
consequently, BEA data were used.
Railroad data are provided by the Association of American Railroads (AAR). National
totals of re venue-ton-miles for the years 1985 through 199Q are used to estimate changes
in activity during this period. The national growth is therefore applied to each State and
county (AAR, 1991).
Marine vessel activity is recorded annually by the U.S. Army Corp of Engineers.
Cargo tonnage national totals are used to determine growth in diesel- and residual-fueled
vessel use through the year 1989 (Corp of Engineers, 1991). Gasoline-powered vessels are
used predominantly for recreation, so growth for this category is therefore based on
population.
Petroleum refinery fugitive emissions were grown to the inventory years based on
refinery capacity by State, as reported in DOE's Petroleum Supply Annuals for 1985
through 1990 (DOE, 1991c). State capacity for 1991 was extrapolated based on the data
for the previous years.
B. REVISED EMISSION ESTIMATES
Hazardous waste TSDF emissions were updated using a file from EPA's Emission
Standards Division (ESD), created in April 1989 (EPA, 1989d). This file provided
estimates of TSDF emissions with longitude and latitude as the geographical indicator for
each facility. The longitude and latitude were used to match each emission estimate to
the appropriate State and county.
Area source petroleum refinery fugitive emissions were re-estimated based on a
revised estimate of national petroleum refinery emissions. The national petroleum
refinery emissions used to estimate area source emission in the 1985 NAPAP is from
Trends (EPA, 1986). The emission estimate for blowdown systems was revised to reflect
the high level of control as shown in the point source inventory. Appendix B is a
comparison of Trends and NAPAP emissions and outlines the reasons for revising the
blowdown emission estimate.
69
-------
The area source petroleum refinery fugitive emissions were re-estimated using the
revised national emission total by applying the methodology used to develop the 1985
NAPAP estimate (EPA, 1988). Total county fugitive petroleum refinery emissions were
determined by distributing the revised Trends estimate (excluding process heaters and
catalytic cracking units) based on 1985 county refinery capacity from the DOE Petroleum
Supply Annual (DOE, 1986). Refinery capacity from this publication was allocated to
counties based on the designated location of the refinery. NAPAP was used to aid in the
matching of refineries to location.
Total area source petroleum refinery fugitive emissions were then estimated by
subtracting the point source emissions (SCCs 3-06-004 through 3-06-888) from the total
county-level emissions. Negative values (indicating higher point source emissions than
the totals shown for the county), were re-allocated to counties exhibiting positive emission
values based on the proportion of total refinery capacity for each county to avoid double-
counting of emissions. This resulted in an emission estimate of 351 thousand tons for
1985 compared with the prior NAPAP estimate of 728 thousand tons (area source refinery
fugitives). This revised 1985 estimate was grown to the inventory years, as described
above.
C. EMISSION FACTOR CHANGES
Emission factors for several sources were updated to reflect recent technical
improvements in AP-42 and other emission inventory guidance documents. Emission
factors for all four pollutants were updated for railroads and residential wood combustion.
S02 emission factors for aircraft were also updated. VOC emission factors for vehicle
refueling were updated to reflect changes in gasoline RVP.
Railroad emission factors in NAPAP were derived from data in AP-42. Improved
emission factors for railroad locomotives have recently been developed in a revision to
EPA's mobile source emission inventory guidance (EPA, 1991e). These updated emission
factors were incorporated into the Interim Inventory emission estimates. Railroad
emission factors are summarized in Table VT-3 for line-haul locomotives and yard (switch)
locomotives. Because only one set of emission factors is required for railroads, the
separate emission factors for line-haul and yard locomotives were weighted by fuel usage.
AAR provided data on fuel consumption by line-haul and yard locomotives for Class I
railroads for 1985 through 1990, as shown in Table VI-4.
AP-42 sections for residential wood combustion sources have recently been updated.
With the exception of the SO2 emission factor (which has not changed), emission factors
for each pollutant have decreased. Table VI-5 lists the NAPAP emission factors (which
reflect a combination of wood-burning devices) and the emission factors listed in the
revised AP-42 sections. No data are available to weight these emission factors. Because
of this, and because conventional woodstoves constitute the majority of woodstoves
nationwide, these data were used to calculate all residential wood combustion emissions.
Because conventional stove emissions are higher than other wood-burning devices, this
will provide an upper bound of emissions.
70
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Table VI-3
Railroad Locomotives Diesel Fuel Consumption
1985 to 1990
(million gallons)
Year
1985
1990
Line-Haul
2,889
2,876
Switch
255
258
SOURCE: AAR.1991.
Table VI-4
Railroad Emission Factors
(lbs/1,000 gallons)
NAPAP
Revised'
Line-haul
Yard
New Wtd. Avg.
Wtg. Factor
2,876
258
NOX
370
493.1
504.4
494
CO
130
62.6
89.4
65
HC
90
20.1
48.2
22
SOZ
57
36.0
36.0
36
SOURCE: *EPA, 1991e.
71
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Table VI-5
Residential Wood Combustion Emission Factors
Emission Factors (Ibs/ton)
1985 NAPAP
Conventional Stoves
Noncatalytic Stoves
Pellet Stoves*
Catalytic Stoves
Fireplaces
voc
85.72
28.00
ND
ND
17.20
26.00
CO
242.63
230.80
140.80
39.40
104.80
122.20
NOX
2.92
2.80
ND
13.80
2.00
1.80
sox
0.40
0.40
0.40
0.40
0.40
0.40
NOTES: ND = no data.
' Pellet stoves comprise less than 2 percent of the national population.
72
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Review of emission factors for other area sources show that emission factors for
several off-road categories have been revised in recent technical reports. Aircraft and off-
road vehicles and engines have both undergone significant revision or improvement. Due
to the complexity of the emission factor derivation process for these categories (weighting
by different engine types), however, it is difficult to develop an improved set of emission
factors under the time constraints of this study. Because of this, and because much of the
emission factor data has not changed, the emission factors presented hi NAPAP will
continue to be used in the Interim Inventories.
The SO2 emission rate from aircraft is one exception to this case. AP-42 emission
rates were compared with emission rates published in EPA's emission inventory guidance
(EPA, 199 If). SO2 rates were an average of 54 percent lower, due to changes in fuel
sulfur content. This change was incorporated into the aircraft emission estimates for the
Interim Inventories. (Although new data were available only for civil aircraft, the
emission factor change was incorporated for all aircraft). Aircraft emission factors for
VOC, NOX, and CO have not changed. Table VI-6 is a comparison of S02 emission rates
from aircraft.
The NAPAP gasoline marketing service station emission estimate was broken into
two components — evaporative losses from underground tanks (Stage I) and Stage II
vehicle refueling (including spillage). The NAPAP emission estimate was derived based
on gasoline usage combined with the uncontrolled emission factors from AP-42. These
emission factors are as follows:
Stage I: 7.3 lbs/1,000 gallons
Stage H: 11.0 lbs/1,000 gallons
Spillage: 0.7 lbs/1,000 gallons
These emission factors were used to calculate the fraction of total emissions attributable
to each of the components above. The total percentage is 38.4 percent for Stage I
emissions and 61.6 percent for Stage II emissions, plus spillage.
The stage II emissions were also revised to reflect changes in emission factors. Stage
II emission factors are a function of gasoline RVP and temperature. Gasoline RVPs have
lowered since 1985 in response to the phase I and phase II RVP regulations. MOBILES
was used to calculate stage II emission factors for five sample States (Maryland, Illinois,
New York, Texas, and North Carolina). Factors for each season were calculated based on
the seasonal RVP and temperature (see Tables IV-7, IV-8, and IV-9). These results were
then used to generate a national average annual stage II emission factor. The national
average annual factors for each inventory year are shown in Table VI-7.
In addition to updating the emission factor for stage II, underground tank
breathing/emptying losses were also added to the inventory. The AP-42 emission factor of
1.0 lbs/1000 gallons was used to estimate emissions for each inventory year. Gasoline
usage was back-calculated from the stage II VOC emission estimate and emission factor.
73
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Table VI-6
Civil Aircraft SO2 Emission Factors
Engine
Type
250B17B
501D22A
TPE-331-3
JT3D-7
JT9D-7
PT6A-27
Fuel
Rate
(Ibs/hr)
63
265
245
85
610
2376
2198
1140
112
458
409
250
1013
9956
8188
3084
1849
16142
13193
4648
115
425
400
215
AP-42SO,
Emission
Factor
(Ibs/hr)
0.06
0.27
0.25
0.09
0.61
2.38
2.2
1.14
0.11
0.46
0.41
0.25
1.01
9.96
3.19
3.08
1.8S
16.14
13.19
4.65
0.12
0.43
0.4
0.22
New SO,
Emission
Factor
(Ibs/hr)
0.03
0.14
0.13
0.05
0.33
1.28
1.19
0.62
0.06
0.25
0.22
0.14
0.55
5.38
4.39
1.67
1.00
8.72
7.12
2.51
0.06
0.23
0.22
0.12
Fuel
Rate
Engine Type (Ibs/hr)
PT6A-41 147
510
473
273
DartRDa7 411
1409
1248
645
0-200 8.24
45.17
45.17
25.5
TSIO-360C 11.5
133
99.5
61
O-320 9.48
89.1
66.7
46.5
AP-42SO,
Emission
Factor
(Ibs/hr)
0.15
0.51
0.47
0.27
0.41
1.41
1.25
0.65
0
0.01
0.01
0.01
0
0.03
0.02
0.01
0
0.02
0.01
0.01
New SO,
Emission
Factor
(Ibs/hr)
0.08
0.28
0.26
0.15
0.22
0.76
0.67
0.35
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.00
0.01
0.01
0.01
SOURCE: EPA, 1991b.
74
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Table VI-7
Average Annual Service Station Stage II VOC Emission Factors
Emission Factor
Year grams/gallon lbs/1,000 gallons
1987 4.6 10.0
1988 4.6 10.0
1989 3.9 8.5
1990 3.6 8.0
1991 3.6 8.0
75
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D. CONTROL EFFICIENCY ASSUMPTIONS
Control efficiencies (and an 80 percent rule effectiveness) were incorporated in the
data files for VOC emissions from gasoline marketing (Stage I and vehicle refueling),
petroleum refinery fugitives, and bulk gasoline plants and terminals.
Many areas already have regulations in place for controlling Stage I and Stage II
gasoline marketing emissions. Many current State regulations require the use of Stage I
controls (except at small volume service stations) to reduce emissions by 95 percent.
Emission estimates were revised to reflect these controls in areas designated as having
these requirements as part of their SEPs (Battye, 1987). Stage II vapor recovery systems
are estimated to reduce emissions by 84 percent (Shedd, 1991). Stage II controls are
already in place in the District of Columbia, in St. Louis, Missouri, and in parts of
California. Stage II controls also reduce underground tank breathing/emptying losses.
Emissions in these areas were revised to reflect these controls.
Petroleum refinery fugitives and gasoline bulk plants and terminals are covered by
existing CTGs and are included in many State regulations. Emissions were revised to
reflect these controls in areas with regulations (Battye, 1987). Control efficiencies
assumed for these area source categories were 43 percent for petroleum refinery fugitives
and 51 percent for gasoline bulk plants and terminals. NAPAP area source estimates
have control levels built into these emission estimates. These control levels were first
backed out of the emission estimates. In areas with no controls, the emissions remained
at uncontrolled levels. In areas with regulations, the uncontrolled emissions were reduced
to reflect the above efficiencies.
All emission estimates incorporating control efficiencies were then revised to
incorporate rule effectiveness assumptions. Control efficiencies were discounted to reflect
an 80 percent rule effectiveness.
E. NONROAD MOBILE SOURCE EMISSION ESTIMATES
Nonroad sources include motorized vehicles and equipment that are not normally
operated on public roadways to provide transportation. The nonroad mobile source
emission estimates in the Interim Inventory are based on 1990 nonroad emission
estimates compiled by EPA's Emission Inventory Branch (EIB) (EPA, 1992b). The EIB
nonroad data contains a total emission estimate for non-road sources at the county level.
These emission estimates include all nonroad sources except aircraft, commercial marine
vessels, railroads, and fugitive road dust. The nonroad sources not included in the EIB
estimates were accounted for by growing the applicable NAPAP source categories. The
EIB nonroad emission estimates were.developed from nonroad emission inventories for 27
ozone NAAs by EPA's Office of Mobile Sources (QMS) (EPA, 1992c). The QMS inventories
contained 1990 emission estimates at the SCC-level for each county within 1 of the 27
NAAs. These nonroad data do not include emission estimates for SO2. S02 emissions in
the 1985 NAPAP Inventory from the nonroad sources covered in these estimates was
approximately 92,000 tons.
A three step process was used to convert the OMS NAA emission estimates to county-
SCC-level emission estimates needed for the Interim Inventory. The first step, performed
76
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by EIB, used the QMS 1990 nonroad emission estimates for the 27 ozone NAAs to
estimate nonroad emissions for the rest of the country. The second step used the EIB
total nonroad emission estimates for each county to create 1990 county-SCC-level nonroad
emission estimates. The third step was to adjust the 1990 county-SCC-level nonroad
estimates to the other inventory years (1987 through 1989 and 1991). Each of these three
steps is described below.
1. Creation of National County-Level 1990 Nonroad Emission Estimates
OMS had 1990 nonroad emission inventories prepared for 27 ozone and 6 CO NAAs
(Data from the CO NAAs was not used because it did not include VOC and NO, emission
estimates). Table VI-8 lists the 27 ozone NAAs for which nonroad inventories were
compiled. Each NAA inventory contained county-level emission estimates for 279
different equipment/engine type combinations for each county in the NAA. For this
information to be useful for the Interim Inventory, nonroad emission estimates were
needed for the entire country (excluding Alaska and Hawaii). The following methodology
was used to create 1990 nonroad emission estimates for the entire country:
(1) VOC, NOX, and CO per capita emission factors were developed for each NAA by
summing each pollutant's emission estimates for all equipment/engine categories
for all counties within the NAA and dividing by the NAA population;
(2) for counties entirely within 1 of the 27 NAAs, the emission estimates in the OMS
inventories was used;
(3) for counties partially in 1 of the 27 NAAs, emission estimates were calculated by
multiplying the NAA per capita emission factor by the total county population;
(4) all other counties were assigned a "surrogate NAA" based on geography and
climate, emission estimates were calculated by multiplying the "surrogate NAA"
per capita emission factors by the total county population. Figure VI-1 shows the
"surrogate NAA" each area of the country was assigned.
2. Distribution of Total Nonroad Emissions to SCCs
The resulting emission estimates from step 1 above, represent total county nonroad
emissions. In order to be incorporated into the Interim Inventory, these emissions must
be distributed to the appropriate SCCs. The following methodology was used to distribute
total nonroad emissions to SCCs:
(1) an SCC was assigned to each of the 279 equipment/engine type combinations in
the OMS inventories; the 27 SCCs used are listed in Table VI-9;
(2) for each of the 27 OMS inventories, the percentage of emissions from sources
assigned to each of the 27 SCCs was calculated;
(3) each county's total nonroad emissions were distributed to the 27 sees using the
SCC percentages from its "surrogate NAA".
77
-------
Table VI-8
Ozone Nonattainment Areas with QMS-Prepared
Nonroad Emission Estimates
Atlanta, GA
Baltimore, MD
Baton Rouge, LA
Beaumont, TX
Boston, MA
Chicago, IL
Cleveland, OH
Denver, CO
E! Paso, TX
Hartford, CT
Houston, TX
Miami, FL
Milwaukee, Wl
Muskegon, Ml
New York, NY
Philadelphia, PA
Phoenix, AZ
Portsmouth, NH
Providence, Rl
San Diego, CA
San Joaquin, CA
Seattle, WA
Sheboygan, Wl
South Coast, CA
Springfield, MA
St. Louis, MO
Washington, DC
78
-------
Figure VM
Assignment of Surrogate Nonattainment Areas
New York
—-<
Philadelphia
Boston
Providence
Hartford
Paso Houston
-------
Table VI-9
Source Categories Used for Nonroad Emission Estimates
AMS sec
Category Description
2260001000
2260002000
2260003000
2260004000
2260005000
2260006000
2260007000
2260008000
2265001000
2265002000
2265003000
2265004000
2265005000
2265006000
2265007000
2265008000
2270001000
2270002000
2270003000
2270004000
2270005000
2270006000
2270007000
2270008000
2282005000
2282010000
2282020000
Recreational Vehicles: Gasoline, 2-Stroke
Construction Equipment: Gasoline, 2-Stroke
Industn'al Equipment: Gasoline, 2-Stroke
Lawn & Garden Equipment: Gasoline, 2-Stroke
Farm Equipment: Gasoline, 2-Stroke
Light Commercial: Gasoline, 2-Stroke
Logging Equipment: Gasoline, 2-Stroke
Airport Service Equipment: Gasoline, 2-Stroke
Recreational Vehicles: Gasoline, 4-Stroke
Construction Equipment: Gasoline, 4-Stroke
Industrial Equipment: Gasoline, 4-Stroke
Lawn & Garden Equipment: Gasoline, 4-Stroke
Farm Equipment: Gasoline, 4-Stroke
Light Commercial: Gasoline, 4-Stroke
Logging Equipment: Gasoline, 4-Stroke
Airport Service Equipment: Gasoline, 4-Stroke
Recreational Vehicles: Diesel
Construction Equipment: Diesel
Industrial Equipment: Diesel
Lawn & Garden Equipment: Diesel
Farm Equipment: Diesel
Light Commercial: Diesel
Logging Equipment: Diesel
Airport Service Equipment: Diesel
Recreational Marine Vessels: Gasoline, 2-Stroke
Recreational Marine Vessels: Gasoline, 4-Stroke
Recreational Marine Vessels: Diesel
80
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3. Adjusting 1990 Estimates to Other Inventory Years
The 1990 county-SCC-level nonroad emission estimates were adjusted to 1987
through 1989 and 1991 using historical BEA earnings and population data (BEA, 199 la;
BEA, 1992a). The methodology used to shrink/grow the 1990 emissions is the same as
used to grow the other area source emissions, except instead of growing emission from the
1985 NAPAP estimates based on growth in earnings or population from 1985 to each
inventory year, the nonroad estimates are shrunk/grown based on the change in earnings
or population from 1990 to each other inventory year. The growth indicator used for each
nonroad SCC is listed in Table VI-10.
F. CORRESPONDENCE TO AMS
The last step in the creation of the area source inventory was the matching of NAPAP
categories to the new AMS categories. This matching is provided in Table VI-11. Note
that there is not always a one-to-one correspondence between NAPAP and AMS
categories. For example, the gasoline marketing NAPAP category was split into two
separate AMS categories representing Stage I and Stage II emissions. In addition, three
NAPAP SCCs are not included in the AMS system of codes. Therefore, AMS codes were
created for process emissions from pharmaceutical manufacture and synthetic fiber
manufacture and for SOCMI fugitive emissions.
G. EMISSION SUMMARY
An emission summary by major category for the area source inventories is shown in
Table VI-12.
81
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Table VI-10
Nonroad Source Activity Indicators
AMS SCO Category Description
Activity Indicator
2260001000 Recreational Vehicles: Gasoline, 2-Stroke
2260002000 Construction Equipment: Gasoline, 2-Stroke
2260003000 Industrial Equipment: Gasoline, 2-Stroke
2260004000 Lawn & Garden Equipment: Gasoline, 2-Stroke
2260005000 Farm Equipment: Gasoline, 2-Stroke
2260006000 Light Commercial: Gasoline, 2-Stroke
2260007000 Logging Equipment: Gasoline, 2-Stroke
2260008000 Airport Service Equipment: Gasoline, 2-Stroke
2265001000 Recreational Vehicles: Gasoline, 4-Stroke
2265002000 Construction Equipment: Gasoline, 4-Stroke
2265003000 Industrial Equipment: Gasoline, 4-Stroke
2265004000 Lawn & Garden Equipment: Gasoline, 4-Stroke
2265005000 Farm Equipment: Gasoline, 4-Stroke
2265006000 Light Commercial: Gasoline, 4-Stroke
2265007000 Logging Equipment: Gasoline, 4-Stroke
2265008000 Airport Service Equipment: Gasoline, 4-Stroke
2270001000 Recreational Vehicles: Diesel
2270002000 Construction Equipment: Diesel
2270Q03000 Industrial Equipment: Diesel
2270004000 Lawn & Garden Equipment: Diesel
2270005000 Farm Equipment: Diesel
2270006000 Light Commercial: Diesel
2270007000 Logging Equipment: Diesel
2270008000 Airport Service Equipment: Diesel
2282005000 Recreational Marine Vessels: Gasoline, 2-Stroke
2282010000 Recreational Marine Vessels: Gasoline, 4-Stroke
2282020000 Recreational Marine Vessels: Diesel
Population
Construction
Manufacturing
Population
Farm
Manufacturing
Agricultural Services, Forestry,
Fisheries, and Other
Transportation by Air
Population
Construction
Manufacturing
Population
Farm
Manufacturing
Agricultural Services, Forestry,
Fisheries, and Other
Transportation by Air
Population
Construction
Manufacturing
Population
Farm
Manufacturing
Agricultural Services, Forestry,
Fisheries, and Other
Transportation by Air
Population
Population
Population
82
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Table Vl-11
AMS to NAPAP Source Category Correspondence
AMS
NAPAP
SCC
Category
SCC Category
Stationary Source Fuel Combustion
2102001000 Industrial - Anthracite Coal (Total: All Boiler
Types)
2102002000 Industrial - Bituminous/Subbituminous Coal
(Total: All Boiler Types)
2102004000 Industrial - Distillate Oil (Total: Boilers & 1C
Engines)
2102005000 Industrial - Residual Oil (Total: All Boiler Types)
2102006000 Industrial - Natural Gas (Total: Boilers & 1C
Engines)
2102008000 Industrial - Wood (Total: All Boiler Types)
2102009000 Industrial - Coke (Total: All Boiler Types)
2102010000 Industrial - Process Gas (Total: All Boiler Types)
2103001000 Commercial/Institutional - Anthracite Coal (Total:
All Boiler Types)
2103002000 Commercial/Institutional -
Bituminous/Subbituminous Coal (Total: All Boiler
Types)
2103004000 Commercial/Institutional - Distillate Oil (Total:
Boilers & I.C. Engines)
2103005000 Commercial/Institutional - Residual Oil (Total: All
Boiler Types)
2103006000 Commercial/Institutional - Natural Gas (Total:
Boilers & I.C. Engines)
2103008000 Commercial/Institutional - Wood (Total: All Boiler
Types)
2104001000 Residential - Anthracite Coal (Total: All
Combustor Types)
2104002000 Residential - Bituminous/Subbituminous Coal
(Total: All Combustor Types)
2104004000 Residential - Distillate Oil (Total: All Combustor
Types)
2104005000 Residential - Residual Oil (Total: All Combustor
Types)
2104006000 Residential - Natural Gas (Total: All Combustor
Types)
2104008000 Residential - Wood (Total: Woodstoves and
Fireplaces)
13 Industrial Fuel - Anthracite Coal
14 Industrial Fuel - Bituminous Coal
16 Industrial Fuel - Distillate Oil
17 Industrial Fuel - Residual Oil
18 Industrial Fuel - Natural Gas
19 Industrial Fuel - Wood
15 Industrial Fuel - Coke
20 Industrial Fuel - Process Gas
7 Commercial/Institutional Fuel -
Anthracite Coal
8 Commercial/Institutional Fuel -
Bituminous Coal
9 Commercial/Institutional - Distillate
Oil
10 Commercial/Institutional - Residual
Oil
11 Commercial/Institutional - Natural
Gas
12 Commercial/Institutional - Wood
1 Residential Fuel - Anthracite Coal
2 Residential Fuel - Bituminous Coal
3 Residential Fuel - Distillate Oil
4 Residential Fuel - Residual Oil
5 Residential Fuel - Natural Gas
6 Residential Fuel - Wood
83
-------
Table VI-11 (continued)
AMS
NAPAP
sec
Category
SCC Category
Mobile Sources
2275001001 Aircraft - Military Aircraft (LTOs)
2275020000 Aircraft - Commercial Aircraft (LTOs)
2275050000 Aircraft - Civil Aircraft (LTOs)
2280001000 Marine Vessels - Coal
2280002000 Marine Vessels - Diesel
2280003000 Marine Vessels - Residual Oil
2285002000 Railroads - Diesel
2260001000 Recreational Vehicles: Gasoline, 2-Stroke
2260002000 Construction Equipment: Gasoline, 2-Stroke
2260003000 Industrial Equipment: Gasoline, 2-Stroke
2260004000 Lawn & Garden Equipment: Gasoline, 2-Stroke
2260005000 Farm Equipment: Gasoline, 2-Stroke
2260006000 Light Commercial: Gasoline, 2-Stroke
2260007000 Logging Equipment: Gasoline, 2-Stroke
2260008000 Airport Service Equipment: Gasoline, 2-Stroke
2265001000 Recreational Vehicles: Gasoline, 4-Stroke
2265002000 Construction Equipment: Gasoline, 4-Stroke
2265003000 Industrial Equipment: Gasoline, 4-Stroke
2265004000 Lawn & Garden Equipment: Gasoline, 4-Stroke
2265005000 Farm Equipment: Gasoline, 4-Stroke
2265006000 Light Commercial: Gasoline, 4-Stroke
2265007000 Logging Equipment: Gasoline, 4-Stroke
2265008000 Airport Service Equipment: Gasoline, 4-Stroke
2270001000 Recreational Vehicles: Diesel
2270002000 Construction Equipment: Diesel
2270003000 Industrial Equipment: Diesel
2270004000 Lawn & Garden Equipment: Diesel
2270005000 Farm Equipment: Diesel
2270006000 Light Commercial: Diesel
2270007000 Logging Equipment: Diesel
2270008000 Airport Service Equipment: Diesel
2282005000 Recreational Marine Vessels: Gasoline, 2-Stroke
2282010000 Recreational Marine Vessels: Gasoline, 4-Stroke
2282020000 Recreational Marine Vessels: Diesel
46 Aircraft LTOs - Military
48 Aircraft LTOs - Commercial
47 Aircraft LTOs - Civil
49 Vessels - Coal
50 Vessels - Diesel Oil
51 Vessels - Residual Oil
45 Railroad Locomotives
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
39 Off-Highway Gasoline Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
44 Off-Highway Diesel Vehicles
52 Marine Vessels - Gasoline
52 Marine Vessels - Gasoline
N/A
84
-------
Table VI-11 (continued)
AMS
NAPAP
sec
Category
SCC Category
Industrial Processes
2301020000 Process Emissions from Pharmaceuticals
(PECHAN)
2301030000 Process Emissions from Synthetic Fiber
(PECHAN)
2301040000 SOCMI Fugitives (PECHAN)
2302050000 Food & Kindred Products: SIC 20 - Bakery
Products (Total)
2306000000 Petroleum Refining: SIC 29 - All Processes
(Total)
2310000000 Oil & Gas Production: SIC 13 - All Processes
(Total)
2399000000 Industrial Processes: NEC
Storage & Transport
2501050120 Petroleum & Petroleum Product Storage - Bulk
Stations/Terminals: Breathing Loss (Gasoline)
2501060050 Petroleum & Petroleum Product Storage -
Gasoline Service Stations (Stage I: Total)
2501060100 Petroleum & Petroleum Product Sto'rage -
Gasoline Service Stations (Stage II: Total)
2501060201 Petroleum & Petroleum Product Storage -
Gasoline Service Stations (Underground Tank:
.Breathing & Emptying)
Waste Disposal, Treatment, & Recovery
2601010000 On-Site Incineration - Industrial (Total)
2601020000 On-Site Incineration - Commercial/Institutional
(Total)
2601030000 On-Site Incineration - Residential (Total)
2610010000 Open Burning - Industrial (Total)
2610020000 Open Burning - Commercial/Institutional (Total)
2610030000 Open Burning - Residential (Total)
2630020000 Wastewater Treatment - Public Owned (Total)
2640000000 TSDFs - All TSDF Types (Total: All Processes)
106 Process Emissions from
Pharmaceutical Manufacturing
107 Process Emissions from Synthetic
Fibers Manufacturing
102 Fugitive Emissions From Synthetic
Organic Chemical Manufacturing
105 Process Emissions From Bakeries
104 Fugitive Emissions From Petroleum
Refinery Operations
108 Crude Oil and Natural Gas
Production Fields
99 Minor point sources
103 Bulk Terminal and Bulk Plants
54 Gasoline Marketed (Stage I)
54 Gasoline Marketed (Stage II)
54 Gasoline Marketed (Breathing &
Emptying)
22 On-Site Incineration - Industrial
23 On-Site Incineration -
Commercial/Institutional
21 On-Site Incineration - Residential
25 Open Burning - Industrial
26 Open Burning -
Commercial/Institutional
24 Open Burning - Residential
100 Publicly-Owned Treatment Works
(POTWs)
109 Hazardous Waste Treatment,
Storage, and Disposal Facilities
(TSDF)
85
-------
Table VI-11 (continued)
AMS
NAPAP
sec
Category
SCC Category
Miscellaneous Area Sources
2801500000 Agriculture Production - Crops - Agricultural Reid
Burning (Total)
2801520000 Agriculture Production - Crops - Orchard Heaters
(Total)
2810001000 Other Combustion - Forest Wildfires (Total)
2810015000 Other Combustion - Managed (Slash/Prescribed)
Burning (Total)
2810030000 Other Combustion - Structure Fires
62 Agricultural Field Burning
63 Frost Control • Orchard Heaters
60 Forest Wild Fires
61 Managed Burning - Prescribed
64 Structural Fires
86
-------
Table VI-12
Summary of National Area Source Emissions
voc
Industrial Fuel Combustion
Other Fuel Combustion
Chemical and Allied Product Manufacturing
Petroleum and Related Industries
Other Industrial Processes
Storage and Transport
Waste Disposal & Recycling
Off-Highway
Miscellaneous Combustion
Total
NOX
Industrial Fuel Combustion
Other Fuel Combustion
Chemical and Allied Product Manufacturing
Petroleum and Related Industries
Other Industrial Processes
Storage and Transport
Waste Disposal & Recycling
Off-Highway
Miscellaneous Combustion
Total
1987
18
473
429
414
83
1,316
2,249
2,249
566
7,798
1,413
616
0
0
5
0
67
2,723
132
4,955
1988
19
461
447
415
83
1,348
2,302
2,227
584
7,887
1,499
641
0
0
5
0
66
2,826
134
5,172
1989
20
443
447
414
81
1,265
2,282
2,178
578
7,707
1,557
632
0
0
5
0
64
2,855
133
5,247
1990
21
427
456
414
79
1,268
2,254
2,120
576
7,614
1,602
632
0
0
5
0
63
2,843
133
5,278
1991
21
416
454
419
78
1,273
2,210
2,060
567
7,497
1,682
646
0
0
4
0
61
2,769
132
5,294
87
-------
Table VI-12 (continued)
CO
Industrial Fuel Combustion
Other Fuel Combustion
Chemical and Allied Product Manufacturing
Petroleum and Related Industries
Other Industrial Processes
Storage and Transport
Waste Disposal & Recycling
Off-Highway
Miscellaneous Combustion
Total
S02
Industrial Fuel Combustion
Other Fuel Combustion
Chemical and Allied Product Manufacturing
Petroleum and Related Industries
Other Industrial Processes
Storage and Transport
Waste Disposal & Recycling
Off-Highway
Miscellaneous Combustion
Total
1987
213
6,246
0
0
2
0
1,778
15,333
4,198
27,770
607
479
0
0
2
0
15
240
4
1,347
1988
226
6,081
0
0
2
0
1,730
15,296
4,327
27,662
604
467
0
0
2
0
16
254
4
1,347
1989
234
5,850
0
0
2
0
1,671
14,997
4,286
27,040
608
425
0
0
2
0
15
259
4
1,315
1990
241
5,636
0
0
2
0
1,611
14,642
4,267
26,398
626
394
0
0
2
0
15
265
4
1,308
1991
252
5,495
0
0
2
0
1,570
14,238
4,202
25,759
690
404
0
0
2
0
15
274
4
1,389
88
-------
CHAPTER VH
CANADIAN EMISSIONS
The 1990 Interim Inventory includes emission estimates for three Canadian
provinces: New Brunswick, Quebec, and Ontario. Point and area source emission
estimates were based on the 1985 NAPAP Inventory. Mobile source VMT estimates were
developed based on data provided by Environment Canada, the Canadian Environmental
Ministry. Mobile source emission factors were developed using a version of MOBILES
modified to reflect characteristics of the Canadian vehicle fleet.
A. POINT AND AREA SOURCES
Emission estimates for point and area sources were based on emission estimates from
the 1985 NAPAP Inventory. 1985 NAPAP emissions were grown to inventory years 1987
through 1991 using data from two reports from the Canadian Council of Ministers of the
Environment. One report contained provincial VOC and NOX emission estimates for
major source categories for the years 1985 and 1990 (CCME, 1990). The second report
contained provincial SO2 emission estimates for power generation, primary metals, and
other sources for the years 1980 and 1987 through 1990 (EC, 1990). Growth in stationary
source CO emissions was not calculated because data to calculate CO emission growth
factors were not available.
Source categories in the Canadian reports were matched with the NAPAP categories.
Table VII-1 lists the categories used from the Canadian report and then* corresponding
NAPAP categories. For VOC and NO,,, average annual growth rates were calculated for
each source category hi each province using the 1985 and 1990 data. For SO2, a 1985
emission estimate was calculated assuming straight line growth between 1980 and 1987.
An average annual growth rate was then calculated for each source category in each
province using the 1985 and 1990 data. Table VII-2 lists the growth rates calculated for
each source category in each province. These growth rates were applied to the 1985
NAPAP data to calculate emission estimates for the years 1987 through 1991. Table
VII-3 lists point source emission estimates by major source category. Table VII-4 lists the
area source emission estimates.
B. MOBILE SOURCES
Canadian VMT estimates were developed using province-specific vehicle registration
and national average VMT (per vehicle) data for 1988 supplied by Environment Canada
(Lavelle and Terrillon, 1991). 1988 VMT was calculated by multiplying the number of
registered vehicles for each vehicle type hi each province by the average VMT for that
89
-------
Table VIM
Source Categories* Used to Project Canadian Growth
Source Categories
Point Source SCCe
Area Source SCCe
VOC
Transportation
Off-Road Gasoline
Other
Fuel Combustion
Fuel Wood
Res/Comm
Industrial
Industrial Process*
Petrochemicals
Petroleum Refining
Plastics
Crude Oil
Other
102009, 103009
103xxx (except 103009), 105002, 203xxx
102xxx (except 102009), 105001, 202xxx
301 xxx (except 301018), 407xxx, 408xxx
306xxx, 403xxx
301018, 308xxx
310xxx
302xxx-305xxx, 307xxx, 309xxx, 311xxx-399xxx
221 xx
222xx-253xx
116xx
111xx-115xx, 12xxx
13xxx
54xxx
56000
52110
51 xxx, 53xxx, 57xxx,
35xxx
Incineration/Misc
Surface Coatings
Fuel Marketing
Dry Cleaning
Solvent Use
Slash Burning
Other
Power Generation
NO,
Transportation
Off-Road Diesel
Other
Fuel Combustion
Residential
Commercial
Industrial
Natural Gas
Other
Industrial Processes
Incineration/Misc
Power Generation
SO,
Primary Metals
Power Generation
Other
402xxx
404xxx, 406xxx
401001
401002-401888, 490xxx
405xxx, Sxxxxx
101 xxx, 201 xxx
103xxx, 105002, 203xxx
102006, 10500106, 202002
102xxx, 105001, 202xxx (except NG)
Sxxxxx
Sxxxxx
101 xxx, 201 xxx
303xxx
101 xxx, 201 xxx
77000, 78200
27xxx
71000
70000
33100
31 xxx, 32xxx
14xxx
222xx
221xx, 231xx-253xx
11 xxx
12xxx
13100
13200-13520
85xxx
31 xxx, 32xxx, 33xxx
14xxx
85xxx
14xxx
NOTES: 'The major source categories from available Canadian Reports (CCME, 1990; EC, 1990) were
to the corresponding NAPAP SCCs.
90
-------
Table VII-2.
Canadian Emissions and Growth Factors
Source Categories
VOC
New Brunswick
1985 1990
Emissions Emissions
10* tons 10$ tons % Growth
Quebec
1985 1990
Emissions Emissions
10* tons 10* tons % Growth
Ontario
1985 1990
Emissions Emissions
10* tons 10* tons % Growth
Transportation
Off-Road Gasoline
Other
Fuel Combustion
Fuel Wood
Res/Comm
Industrial
Industrial Processes
Petrochemicals
Petroleum Refining
Plastics
Crude Oil
Other
Incineration/Misc
Surface Coatings
Fuel Marketing
Dry Cleaning
Solvent Use
Slash Burning
Other
Power Generation
0.8
1.4
5.3
0.1
0.1
-
1.3
0.1
0.5
0.6
3.8
3.2
0.4
7.5
4.5
0.5
0.1
0.8
1.6
5.2
0.1
0.1
-
1.4
0.2
0.5
0.7
4.1
3.3
0.4
7.8
6.3
0.5
0.1
0.00
14.29
-1.89
0.00
0.00
-
7.69
100.00
0.00
16.67
7.89
3:13
0.00
4.00
40.00
0.00
0.00%
4.8
10.4
39.9
0.4
0.3
5.9
7.1
3.5
0.7
8.3
48.5
233
3.6
69.1
20.2
8.8
0.1
5.0
10.6
46.7
0.4
0.3
6.2
7.5
4.1
0.6
9.1
53.9
23.3
3.7
70.8
26.2
9.2
0.1
4.17
1.92
17.04
0.00
0.00
5.08
5.63
17.14
-14.29
9.64
11.13
0.00
2.78
2.46
29.70
4.55
0.00
19.4
21.6
33.9
1.1
1.1
18.2
15.4
8.1
0.1
30.4
83.3
41.6
5.0
129.6
0.5
4.2
0.4
20.6
23.1
31.2
1.1
1.1
18.7
16.7
9.4
0.1
32.7
94.6
44.3
5.3
136.9
0.6
4.6
0.4
6.19
6.94
-7.96
0.00
0.00
2.75
8.44
16.05
0.00
7.57
13.57
6.49
6.00
5.63
20.00
9.52
0.00
-------
Table VII-2 (continued)
Source Categories
NOX
New Brunswick
1985 1990
Emissions Emissions
10* tons 10f tons % Growth
Quebec
1985 1990
Emissions Emissions
10* tons 10* tons % Growth
Ontario
1985 1990
Emissions Emissions
10* tons 10* tons % Growth
CO
to
Transportation
Off-Road Diesel
Other
Fuel Combustion
Residential
Commercial
Industrial
Natural Gas
Other
Industrial Processes
Inclneration/MIsc
Power Generation
6.9
0.8
1.0
0.6
-
3.9
2.7
1.1
7.9
8.0
0.8
1.0
0.5
-
4.8
3.1
1.5
22.7
15.94
0.00
0.00
-16.67
-
23.08
14.81
36.36
187.34
46.0
16.4
7.5
3.9
-
21.3
6.8
6.0
1.5
45.8
17.3
6.1
4.7
-
24.6
7.8
7.3
3.8
-0.43
5.49
-18.67
20.51
-
15.49
14.71
21.67
153.33
74.0
20.2
15.4
9.7
0.5
45.1
38.2
2.5
97.6
76.1
22.0
14.6
9.5
0.5
50.1
40.5
2.7
74.9
2.84
8.91
-5.19
-2.06
0.00
11.09
6.02
8.00
-23.26
-------
Table VII-2 (continued)
Source Categories
SO2
New Brunswick
1980 1985* 1987 1990 1985-90
Emissions %
10* tons Growth
Quebec
1980 1985* 1987 1990 1985-90
Emissions %
106 tons Growth
Ontario
1980 1985* 1987 1990 1985-90
Emissions %
10* tons Growth
Primary Metals
13.00 15.86 17.00 8.00 -49.55 641.00 508.14455.00189.00 -62.811031.00878.86818.00730.00 -16.94
Power Generation 122.00 147.71 158.00 141.00 -4.55
398.00350.86332.00195.00 -44.42
Other
85.00 53.57 41.00 38.00 -29.07 457.00 272.71199.00207.00 -24.10 335.00280.71259.00325.00 15.78
CO
CO
NOTES: 'Calculated assuming straight-line growth from 1980 to 1987.
-------
Table VI1-3
Summary of Canadian Point Source Emissions
1987-1991
(thousand tons)
Category
VOC
External Fuel Combustion - Utilities
External Fuel Combustion - Industrial
External Fuel Combustion - Commercial/Institutional
Internal Combustion Engines
Chemical Manufacturing
Petroleum Refining
Primary and Secondary Metals
Mineral Products
Food and Agriculture Production
Misc. Industrial Processes
Industrial Organic Solvent Use
Petroleum Product Marketing
Organic Chemical Storage and Transportation
Waste Disposal
Total
NO,
External Fuel Combustion - Utilities
External Fuel Combustion - Industrial
External Fuel Combustion - Commercial/Institutional
Internal Combustion Engines
Chemical Manufacturing
Petroleum Refining
Primary and Secondary Metals
Mineral Products
Food and Agriculture Production
Misc. Industrial Processes
Industrial Organic Solvent Use
Petroleum Product Marketing
Organic Chemical Storage and Transportation
Waste Disposal
Total
1987
626
1,268
0
0
79,233
16,256
10,889
117
0
2,805
3,392
7,823
582
1,142
124,133
109,704
15,477
0
0
1,247
12,510
12,145
10,801
0
11,139
5
19
0
577
173,624
1988
626
1,268
0
0
80,550
16,521
11,071
119
0
2,865
3,465
7,951
587
1,152
126,175
108,136
15,836
0
0
1,271
12,680
12,302
11,013
0
11,390
5
20
0
600
173,253
1989
626
1,268
0
0
81,865
16,787
1 1 ,252
121
0
2,925
3,538
8,079
590
1,162
128,213
106,569
16,196
0
0
1,294
12,849
12,461
11,225
0
11,641
5
20
0
622
172,882
1990
626
1,268
0
0
83,181
17,052
1 1 ,434
123
0
2,985
3,611
8,207
594
1,172
130,253
105,002
16,555
0
0
1,317
13,019
12,619
11,437
0
11,891
5
20
0
646
172,511
1991
626
1,268
0
0
84,494
17,317
11,516
125
0
3,044
3,685
8,334
598
1,183
132,290
103,434
16,914
0
0
1,340
13,189
12,776
11,649
0
12,142
6
21
0
668
172,139
94
-------
Table VII-3 (continued)
Category
CO
External Fuel Combustion - Utilities
External Fuel Combustion - Industrial
External Fuel Combustion - Commercial/Institutional
Internal Combustion Engines
Chemical Manufacturing
Petroleum Refining
Primary and Secondary Metals
Mineral Products
Food and Agriculture Production
Misc. Industrial Processes
Industrial Organic Solvent Use
Petroleum Product Marketing
Organic Chemical Storage and Transportation
Waste Disposal
Total
SO,
External Fuel Combustion - Utilities
External Fuel Combustion - Industrial
External Fuel Combustion - Commercial/Institutional
Internal Combustion Engines
Chemical Manufacturing
Petroleum Refining
Primary and Secondary Metals
Mineral Products
Food and Agriculture Production
Misc. Industrial Processes
Industrial Organic Solvent Use
Petroleum Product Marketing
Organic Chemical Storage and Transportation
Waste Disposal
Total
1987
5,201
411
0
0
129,204
50,005
481,468
422
0
28,758
500
1
0
7,552
703,522
406,819
37,006
36
0
61,688
48,326
1,318,586
37,765
0
38,907
0
43
0
469
1,949,645
1988
5,201
411
0
0
129,204
50,005
481,468
422
0
28,758
500
1
0
7,552
703,522
372,911
37,006
36
0
61,688
48,326
1,218,488
37,765
0
38,907
0
43
0
469
1,815,639
1989
5,201
411
0
0
129,204
50,005
481,468
422
0
28,758
500
1
0
7,552
703,522
339,003
37,006
36
0
61,688
48,326
1,118,390
37,765
0
38,907
0
43
0
469
1,681,633
1990
5,201
411
0
0
129,204
50,005
481,468
422
0
28,758
500
1
0
7,552
703,522
305,096
37,006
36
0
61,688
48,326
1,018,291
37,765
0
38,907
0
43
0
469
1,547,627
1991
5,201
411
0
0
129,204
50,005
481,468
422
0
28,758
500
1
0
7,552
703,522
271,188
37,006
36
0
51,688
48,326
918,192
37,765
0
38,907
0
43
0
469
1,413,620
95
-------
Table VII-4
Summary of Canadian Area Source Emissions
1987-1991
(thousand tons per year)
Category
VOC
Stationary Source Fuel Combustion
Mobile Sources
Industrial Processes
Storage and Transport
Waste Disposal, Treatment, and Recovery
Solvent Usage
Miscellaneous Area Sources
Total
NOX
Stationary Source Fuel Combustion
Mobile Sources
Industrial Processes
Storage and Transport
Waste Disposal, Treatment, and Recovery
Solvent Usage
Miscellaneous Area Sources
Totai
CO
Stationary Source Fuel Combustion
Mobile Sources
Industrial Processes
Storage and Transport
Waste Disposal, Treatment, and Recovery
Solvent Usage
Miscellaneous Area Sources
Total
1987
59,569
56,647
54,008
76.232
67,738
211,406
5,952
531,552
99,998
166,120
27
0
13,483
0
424
280,052
525,557
358,071
0
0
658,906
0
20,997
1,563,531
1988
60,113
57,266
55,707
76,848
70,956
214,779
5,952
541,621
100,687
167,531
27
0
13,919
0
424
282,588
525,557
358,071
0
0
658,906
0
20,997
1,563,531
1989
60,657
57,844
57,406
77,465.
74,174
218,151
5,952
551,689
101,376
168,941
28
0
14,357
0
424
285,126
525,557
358,071
0
0
658,906
0
20,997
1,563,531
1990
61,201
58,502
59,105
78,082
77,392
221,523
5,952
561,757
102,065
170,352
28
0
14,794
0
424
287,663
525,557
358,071
0
0
658,906
0
20,997
1,563,531
1991
61,745
59,121
60,804
78,698
80,610
224,896
5,952
571,826
102,754
171,762
29
0
15,231
0
424
290,200
525,557
358,071
0
0
658,906
0
20,997
1,563,531
96
-------
Table VIM (continued)
Category
SO,
Stationary Source Fuel Combustion
Mobile Sources
Industrial Processes
Storage and Transport
Waste Disposal, Treatment, and Recovery
Solvent Usage
Miscellaneous Area Sources
Total
1987
229,286
46,413
2,459
0
826
. 0
0
278,984
1988
229,286
46,413
2,456
0
826
0
0
278,984
1989
229,286
46,413
2,454
0
826
0
0
278,984
1990
229,286
46,413
2,451
0
826
0
0
278,984
1991
229,286
46,413
2,448
0
826
0
0
278,984
97
-------
vehicle type. VMT was projected to the other inventory years using a VMT growth rate of
1.76 percent for New Brunswick, 2.07 percent for Quebec, and 2.17 percent for Ontario
(Pechan, 1992b). Table VII-5 lists VMT estimates by province for 1990.
Emission factors for highway vehicles were calculated using a version of EPA's
MOBILES that was modified to reflect the characteristics of the Canadian vehicle fleet.
Environment Canada provided instructions on adapting MOBILE4 to the Canadian fleet
(Lavallee and Terrillon, 1991; Lavallee, 1991). This information was used to adapt
MOBILES rather than MOBILE4. The major differences between the Canadian version of
MOBILES and the U.S. version are the basic emission factor equations used to model the
1980 through 1987 model years. The emission control technology and the emissions
performance of vehicles for these model years differed significantly between Canada and
the United States. To reflect these differences, the technology penetration rates were also
modified within the MOBILES computer code for these model years.
98
-------
Table VII-5
1990 Canadian VMT Estimates
(millions of vehicle miles traveled)
New Brunswick
Vehicle Type
LDGV
LDGT
HDGV
LDDT
HDDV
Total
VMT
3,515
1,100
266
99
516
5,495
Ontario
Vehicle Type
LDGV
LDGT
HDGV
LDDT
HDDV
Total
VMT
53,760
8,817
1,286
792
4,460
69,115
Quebec
Vehicle Type
LDGV
LDGT
HDGV
LDDT
HDDV
Total
VMT
34,888
3,862
630
347
1,781
41,508
99
-------
GOT
-------
CHAPTER Vm
QUALITY ASSURANCE AND QUALITY CONTROL
Integral to any inventory effort of this magnitude is a quality assurance/quality
control plan which will ensure the integrity and reasonableness of the data. The
complexity of the algorithms, the size of the data bases, and the number of outside data
sources used to create these inventories mandates a structured and well-documented
quality assurance plan. Data results should also be compared with other sources, since
identifying and explaining differences helps verify the accuracy of the data. This chapter
describes the routine procedures followed during the development of the Interim
Inventories. The following sections provide specific details on the quality assurance
procedures implemented for each inventory.
A. DATA AND PROGRAM INTEGRITY ASSURANCE
During the course of the Inventory development, several procedures were followed to
assure data and program integrity. These routine checks included the following:
Routine Data Base Checks:
• Checking for duplicate records.
• Checking for negative emissions.
• Checking for blank SCCs, State codes, county codes, and other
required data elements.
Data Entry:
• Data entered into the computer (i.e., activity data used for growth)
were verified by checking State and national totals against the
published values.
• Data were reviewed by a second person.
Program Calculations:
• Calculations were routinely corroborated by an independent person to
confirm that the correct algorithms were being applied and that the
correct data were being used for each calculation (e.g., the correct
growth factor was used for the State SIC combination).
101
-------
Reasonableness Checks on Emission Estimates:
• The emission values were routinely checked against other data
sources as a reasonableness check.
B. QUALITY ASSURANCE OF UTILITY INVENTORIES
1. Emission Estimates
Quality assurance was performed on 1990 steam electric utility emissions data for a
sample of eight plants. Emissions of SO2, NO,, CO, and VOC were calculated for the
sample as a check against the emissions calculated by the program. Spreadsheets were
used to calculate the emissions based on the written Form EIA-767 1990 fuel use data
and emission factors corresponding to SCC codes. The sample of plants included EC
Gaston, Paradise, Monroe, Bruce Mansfield, Martin Lake, General JM Gavin, and
Quindaro and Reeves. SO2 emissions were calculated for six of the plants. CO and VOC
emissions were each calculated for one plant. NOX emissions calculations were performed
on four plants: three with control equipment (and various fuel use) and one without
controls. Quality assurance results by pollutant are summarized below.
a. SO2
SO2 emissions were calculated for six of the plants in the sample. Emissions figures
matched exactly for all boilers without a scrubber efficiency, with the exception of General
JM Gavin's oil SO2 emissions. A comparison was made between the computerized raw
Form EIA-767 data and the written Form EIA-767. In this case, the total on the form did
not match the raw computerized data because February's fuel use was different. The
computerized data were used.
For plants with scrubber efficiencies (Paradise, Bruce Mansfield, and Martin Lake),
all S02 emissions data matched, with the .exception of Bruce Mansfield Boiler 3. As with
General JM Gavin, the monthly oil total for this unit did not match the fuel quantity
reported in the Inventory. Again, raw computerized Form EIA-767 data were compared
with the actual Form EIA-767, and were found to be different in August fuel use. The
computerized data were used.
In summary, SO2 emissions data are accurate both for boilers with scrubbers and
those without scrubbers.
6. CO
CO emissions were calculated for Boiler 1 at EC Gaston. The calculated emissions
matched the emissions from the Inventory. CO emission calculations appear to be
accurate, based on this calculation.
102
-------
c. VOC
VOC emissions were calculated for Boiler 2 at EC Gaston. As with CO, the
calculation matched, and it appears that the method for VOC emissions calculations is
correct.
d. NOX
NO, emissions were calculated first for Monroe, a plant without NO, controls, for
Bruce Mansfield, and for Quindaro and Reeves (gas fuel use) — plants which all have NOX
controls. In all cases, emissions matched exactly with the Inventory estimate. It is
believed that NOX emissions for boilers both with and without controls are accurate.
2. Coverage of Plants
Quality assurance was performed on two States in the 1988, 1989, and 1990 utility
files developed by Pechan. The goal of the cross-examination was to ensure that all
plants listed in the Inventory of Power Plants in the United States, 1988, 1989, and 1990
(DOE, 1989-1991) were included in the steam inventories, and vice versa. Steam electric
utilities in Alabama and Pennsylvania were cross-checked as a sample.
For Alabama, the data sets matched exactly for all 3 years. For Pennsylvania, there
was a discrepancy between the data sets for all 3 years. The discrepancy involved two
plants (F.R. Phillips and Springdale) that were in the Inventory of Power Plants, but not
in the steam electric utility inventories. Upon further examination of Form EIA-767 data,
it was determined that these two plants were not in the inventory files because they had
no fuel use during the period from 1988 to 1990.
C. QUALITY ASSURANCE OF NON-UTILITY POINT SOURCES
After completion and initial debugging of the non-utility point source program, a
sample of records were hand-checked to ensure that all calculations were correct and that
the programs were selecting the appropriate growth data for each record (based on the
SIC). Inventory input and output records were then printed along with the growth data
for a sample State. The growth calculation was first verified by looking up the
appropriate earnings data and verifying the grown emission estimate. No errors were
detected hi the calculation. Next, the rule effectiveness calculation was verified by back-
calculating the uncontrolled emissions (based on the reported efficiency) and calculating
the revised emission estimate by discounting the efficiency by 80 percent. It was verified
that the rule effectiveness calculation was completed by the program for VOC, NO,, and
CO emissions. The SO2 emissions were estimated assuming 100 percent rule
effectiveness.
After verification that the projection algorithms were correct, national emission totals
by pollutant were produced and average growth per year was checked for reasonableness.
103
-------
D. QUALITY ASSURANCE OF MOTOR VEHICLE DATA
After estimating VMT for 1990, State totals for each of the 12 roadway types were
computed. These totals were compared with the values in Table VM-2, "Annual Vehicle-
Miles of Travel - 1990" hi Highway Statistics 1990 (FHWA.1991). The VMT estimates
calculated for the 1990 Interim Inventory exactly matched the VMT values ha Highway
Statistics for every roadway type hi every State (except for differences due to rounding).
The national VMT total calculated for 1990 differed by only .08 percent from the national
total hi Highway Statistics.
County-level annual VMT estimates for Maryland for 1990 were obtained from
Maryland's Department of the Environment. These VMT estimates were compared with
the VMT estimates computed for the 1990 Interim Inventory. Total VMT for Maryland
was the same for both sources. Figure VIII-1 shows how the county distribution of VMT
data for the State of Maryland compared with the county distribution of VMT computed
for the Interim Inventory.
Additional quality control for the VMT values was performed for Arizona, Maryland,
and Pennsylvania. The percentage of total VMT occurring in each county was calculated
for these three States, and these percentages were compared with values similarly derived
from the 1985 NAPAP Inventory. This comparison suggested that the VMT distribution
calculated for the 1990 Interim Inventory was similar to that used in the 1985 NAPAP
Inventory. Figure V1II-2 shows how the 1985 NAPAP county VMT distribution compares
with the 1990 Interim Inventory county VMT distribution for Arizona.
The distribution of VMT among the different vehicle types was also checked by
comparing the vehicle distribution of VMT calculated for this Inventory with the vehicle
distribution of VMT in the 1985 NAPAP Inventory for New Jersey, Texas, and
Washington. The LDGV, LDGT, HDGV, and HDDV percentages of VMT were compared
to corresponding values calculated from the 1985 NAPAP Inventory. The LDDV and
LDDT categories were not included in this comparison because they were not accounted
for in the 1985 NAPAP data. LDGV and HDGV percentages were slightly higher in the
1985 data, while the LDGT percentage was slightly higher hi the 1990 data. These
variations were attributed to the different methods of VMT computation used in the two
inventories. Figure VIII-3 shows the comparison described above for New Jersey.
E. QUALITY ASSURANCE OF SOLVENT INVENTORIES
A major portion of the quality assurance effort for the solvents Inventory included
filling in missing data in the census allocation data bases. This results from the practice
of withholding employment data hi cases where a given county contains only a few
facilities. Missing data were filled in based on other census data, such as the number of
facilities in various size ranges.
104
-------
7,000
6,000
5,000
W
o 4,000
>
3,000
2,000
1,000
0
Figure VIII-1
Comparison of Maryland County VMT
1 I I I I
I I I I I I 1 1 I I
1 5 11 15 19 23 27 31 35 39 43 47
3 9 13 17 21 25 29 33 37 41 45 510
FIPS County Code
State of Maryland 1990 Interim Inv.
-------
Figure Vlll-2
Comparison of Arizona County VMT Distribution
70
60
50
5
,240
•*—
o
-------
100
Figure Vlll-3
Comparison of New Jersey Vehicle Type
VMT Distribution
80
H
>
| 60
M—
O
0>
O)
I 40
Q.
20
0
84.343
LDGV
LDGT HDGV
Vehicle Type
1985NAPAP
1990 Interim Inv.
-------
After completion of the solvent inventory, the data base was scanned to check for
missing States and duplicate records. It was discovered that several categories were
duplicated for Alabama. Further investigation showed that the original census allocation
data base had duplicates for this State. This error was corrected and the solvent
emissions were recalculated.
To further ensure that the calculations and allocation procedures are correct, the
solvent emissions were totaled by category and the sum was verified against the initial
solvent material balance.
F. QUALITY ASSURANCE OF AREA SOURCE INVENTORIES
After the final area source inventory program was completed and debugged, the
emission calculations were checked for a sample of 14 area source records to ensure
program integrity. Printouts of the base year (1985 NAPAP) emissions data, the growth
rate data, and emission factor changes were produced. The base year data were used to
find the appropriate growth factor and emission factor change. Inventory year emissions
were calculated and checked against the values produced by the program. No errors were
found.
After completion of the 1990 Inventory, national totals of emissions were produced
and compared with 1985 values to ensure reasonableness of overall emission totals.
State/SCC combinations showing higher than 100 percent changes were reviewed in more
detail. Residual oil combustors exhibited high fluctuations in emissions compared with
other categories. DOE personnel were contacted to review the source for these data. It
was found that, due to the nature of the fuel market, residual fuel shows high fluctuations
in use. It was determined that the California value for 1985 was in error, so this value
was changed by interpolating data from other years. There was no indication that other
values were in error.
Routine scans for blank data found that FIPS county codes were missing for two
counties: Washabaugh, South Dakota, and Nesmond, Virginia. Contact with Virginia air
pollution personnel indicated that Nesmond County was absorbed by Suffolk in the 1970s.
No emissions appeared in the Inventory for Suffolk, so the FIPS county code was changed
to Suffolk. A comparison of road atlases for different years showed that Washabaugh
became Jefferson County. The emission records for Washabaugh appeared to be
duplicates of records for Jefferson County, so they were deleted from the Inventory.
Petroleum refinery emissions were re-estimated for the area source Inventory as
described in Chapter VI. The associated program and data also underwent extensive QA.
Initial review showed that the negative values (counties with point source emissions
higher than the estimated total) were allocated to other counties incorrectly - the values
were added to other counties instead of subtracted, producing higher national emissions.
This was corrected.
After completion of the area source refinery fugitive emissions, the county-level shares
of emissions for the new Inventory were compared with those in the 1985 NAPAP
Inventory. Since emissions are allocated to counties based on the share of refinery
capacity, differences in percentages of total area source emissions would indicate that the
108
-------
capacities used in the allocation differed between the Interim Inventory and NAPAP. The
county level capacity was determined by matching each facility from the Petroleum
Supply Annual to a county based on (1) matching the facility with a NAPAP facility and
using the county reported in NAPAP, or (2) locating the facility based on the city listed in
the Petroleum Supply Annual (DOE, 199 Ic).
Review of the county allocations identified one refinery in Louisiana which was
incorrectly located. This was corrected and the area source emissions were re-allocated.
There were remaining counties which showed higher/lower allocations of area source
refinery fugitive emissions. The location of refineries was double-checked for these
counties. In most cases, the capacity was allocated by matching the refinery to a NAPAP
facility so area source emissions appeared in counties with existing point source facilities.
This scenario appears more likely than allocating area source emissions to counties in
which no point source refineries exist, which is the case for the 1985 NAPAP Inventory.
109
-------
APPENDIX A
COMPUTER FILES
All of the Interim Inventory computer files are available on the NCC IBM mainframe.
Each year's utility and point source files have been combined into a single point source
file. Likewise, each year's solvent and area source files have been combined into a single
area source file. Table A-l lists all of the Interim Inventory files on the IBM NCC
mainframe.
A. POINT SOURCE FILES
The structure for the 1987 through 1991 U.S. point source emission inventory data
files is listed in Table A-2.' These files contain data for both electric utility sources and ail
other point sources. The structure for the Canadian point source emission inventory data
files is listed in Table A-3.
B. AREA SOURCE FILES
The structure for the 1987 through 1991 U.S. area source emission inventory files is
listed in Table A-4. These files contain data for area source solvent usage and all other
area sources. The structure for the 1987 through 1991 Canadian area source emission
inventory files is listed in Table A-5. Table A-12 lists the structure for the AMS-NAPAP
SCC correspondence file.
C. HIGHWAY VEHICLES
The structure for the 1987 through 1991 U.S. highway vehicle emission inventory files
is listed in Table A-6. Table A-7 lists the structure for the 1987 through 1991 U.S. VMT
estimates used to calculate highway vehicle emissions. The structure for the 1987
through 1991 Canadian VMT estimates is listed in Table A-8. Tables A-9 and A-1C list
the structure for the U.S. and Canadian MOBILES emission factor files, respectively.
Table A-ll lists the structure for the county-level I/M correspondence file.
A-l
-------
Table A-1
Interim Inventory Data Files
File Names*
Interim Inventory Component Year 1987 Year 1988
Year 1989
Year 1990 Year 1991
to
United States
Utility (Steam) & Non-Utility Point
Highway Vehicles
Emission Files
VMT
Emission Factors
County I/M Status
Area - Solvents & Other
AMS-NAPAP Correspondence
Canada
Point
Area
Highway Vehicles
VMT
Emission Factors
US87PT.V1.DATA
US87MB.V1.DATA
US87VMT.V1.DATA
US87M52.V1.DATA
CNTYIM.V1.DATA
US87AR.V1.DATA
AMSNAPS.CC.V1.DATA
CN87PT.V1.DATA
CN87AR.V1.DATA
CN87VMT.V1.DATA
CN87EMF2.V1.DATA
US88PT.V1.DATA
US88MB.V1.DATA
US88VMT.V1.DATA
US88M52.V1.DATA
CNTYiM.V1.DATA
US88AR.V1.DATA
AMSNAPSCC.V1.DATA
CN88PT.V1.DATA
CN88AR.V1.DATA
CN88VMT.V1.DATA
CN88EMF2.V1.DATA
US89PT.V1 DATA
US89MBV1.DATA
US89VMT.V1.DATA
US89M52.V1.DATA
CNTYIM.V1.DATA
US89AR.V1.DATA
AMSNAPSCC.V1 .DATA
CN89PT.V1 DATA
CN89AR.V1.DATA
CN89VMT.V1.DATA
CN89EMF2.V1.DATA
US90PT.V1.DATA
US90MB.V1.DATA
US90VMT.V1.DATA
US90M52.V1.DATA
CNTYIM.V1.DATA
US90AR.V1.DATA
AMSNAPSCC.V1.DATA
CN90PT.V1.DATA
CN90AR.V1.DATA
CN90VMT.V1.DATA
CN90EMF2.V1.DATA
US91PT.V1.DATA
US91MB.V1.DATA
US91VMT.V1.DATA
US91M52.V1.DATA
CNTYIM.V1.DATA
US91AR.V1.DATA
AMSNAPSCC.V1.DATA
CN91PT.V1.DATA
CN91AR.V1.DATA
CN91VMT.V1.DATA
CN91EMF2.V1.DATA
NOTES: *AII files begin with prefix WAYROMA. INTERIM.
-------
Filename:
Description:
Location:
File Attributes:
Table A-2
Point Source Files
File Format
WAYROMA.INTERIM.USxxPT.V1 .DATA
Annual U.S. Point Source Data (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
335
61,619
20, 765, 604 (20.76 mb)
Format:
Variable
PLANTID
POINTID
ORISID
8LRID
STKHGT
STKDIAM
STKTEMP
STKFLOW
BOILCAP
WINTHRU
SPRTHRU
SUMTHRU
FALTHRU
HOURS
DAYS
WEEKS
THRUPUT
MAXRATE
HEATCON
SULFCON
ASHCON
NETDC
STKVEL
sec
FIRST
FIPSCNY
SIC
LATC
LONG
SAROAD1 - 4
EMF1 - 4
CONEFF1 - 4
Type
Char
Char
Char
Char
Mum
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Char
Num
Num
Num
Num
Num
Char
Num
Num
Size
4.0
2.0
5.0
5.0
' 4.0
6.2
4.0
10.2
8.2
2.0
2.0
2.0
2.0
2.0
1.0
2.0
11.1
12.3
8.2
5.2
5.2
9.3
9.2
8.0
2.0
3.0
4.0
9.4
9.4
5.0
10.5
7.2
Description
NAPAP Plant ID code
NAPAP Point ID code
ORIS Plant ID (util. only)
Boiler ID code (ubl. only)
Stack Height (ft)
Stack Diameter (ft)
Stack Temperature (°F)
Flow Rate (ftVmin)
Boiler Design Capacity (MMBtu/hr)
Winter Throughput %
Spring Throughput %
Summer Throughput %
Fall Throughput %
Hours/Day in Operation
Days/Week in Operation
Weeks/Year in Operation
Operating Rate (SCC units/yr)
Maximum Design Rate (SCC units/hr)
Fuel Heat Content (MMBtu/SCC unit)
% Fuel Sulfur Content
% Fuel Ash Content
Maximum Nameplate Capacity (MW)
Stack Gas Velocity (ft/sec) -
Source Classification Code
FIPS State Code
FIPS County Code
Standard Industrial Classification Code
Latitude (degrees)
Longitude (degrees)
SAROAD Pollutant Code for VOC, NO,, CO, and SOZ
Emission Factors for VOC, NOX, CO, and SO, (Ibs per SCC unit)
% Control Efficiency for VOC, NO,. CO, and SO2
A-3
-------
Table A-2 (continued)
Format:
Variable Type Size Description
CONPRI1 - 4 Num 3.0 Primary Control Equipment Code for VOC, NO,, CO, and SO,
CONSEC1 - 4 Num 3.0 Secondary Control Equipment Code for VOC, NO,. CO, and SO,
ESTMET1 - 4 Num 1.0 Estimation Method for VOC, NO,. CO, and SO,
EMISS1 - 4 Num 13.4 Emissions (tons/year) for VOC, NO,, CO, and SO2 (controlled with rule effectiveness)
RULEFF1 - 4 Num 3.0 Rute Effectiveness % for VOC. NO,, CO, and SO,
A-4
-------
Table A-3
Canadian Point Source Files
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.CNxxPT.V1 .DATA
Annual Canadian Point Source Data (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
219
1,693
353,838 (<1 mb)
Format:
Variable
PLANTID
POINTID
STKHGT
STKDIAM
STKTEMP
STKFLOW
THRUPUT
HEATCON
SULFCON
ASHCON
STKVEL
sec
AEROSPR
SIC
LATC
LONG
SAROAD1 - 4
CONEFF1 - 4
CONPRI1 - 4
CONSEC1 - 4
ESTMET1 - 4
EMISS1 - 4
Type
Char
Char
Num
Num
Num
Num
Num
Num
Num
Num
Num
Char
Num
Num
Num
Num
Char
Num
Num
Num
Num
Num
Size
4.0
60
40
5.1
4.0
7.0
9.0
5.0
5.2
4.1
9.2
8.0
2.0
5.0
9.4
9.4
5.0
6.1
3.0
3.0
1.0
13.4
Description
NAPAP Plant ID code
NAPAP Point ID code
Stack Height (ft)
Stack Diameter (ft)
Stack Temperature (*F)
Flow Rate (ftYmin)
Operating Rate (SCO units/yr)
Fuel Heat Content (MMBtu/SCC unit)
% Fuel Sulfur Content
% Fuel Ash Content
Stack Gas Velocity (ft/sec)
Source Classification Code
AEROS Province Code
Standard Industrial Classification Code
Latitude (degrees)
Longitude (degrees)
SAROAD Pollutant Code for VOC, NOX. CO, and SO2
% Control Efficiency for VOC. NOX. CO, and SO2
Primary Control Equipment Code for VOC, NO,, CO, and SO2
Secondary Control Equipment Code for VOC, NO,, CO, and SO2
Estimation Method for VOC. NO,, CO. and SO,
Emissions (tons/year) for VOC, NO,, CO, and SO2 (controlled with rule effectiveness)
A-5
-------
Table A-4
Area Source Files
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.USxxAR.V1 .DATA
Annual U.S. Area Source Data (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
157
248,154
39,276,305 (39.27 mb)
Format:
Variable
FIRST
FIPSCNY
sec
SAROAD1 - 4
EMISS1
EMF1
CONEFF1
RULEFF1
PENETR1
OVRLEFF1
ACTIVITY
EMISS2
EMF2
EMISS3
EMF3
EMISS4
EMF4
Type
Num
Num
Char
Char
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Size
2.0
4.0
10.0
5.0
12.4
11.9
5.1
5.1
5.1
5.1
9.0
12.4
11.3
12.4
11.3
12.4
11.3
Description
FIPS State Code
FIPS County Code
Area Source Category Code
SAROAD Pollutant Code for VOC, NOX, CO, and SO,
VOC Emissions (tons/year)
VOC Emission Factor (Ibs/SCC unit)
VOC Control Device Efficiency
VOC Rule Effectiveness %
VOC Rule Penetration Rate
VOC Overall Control Efficiency
Activity Level
NOX Emissions (tons/year)
NOX Emission Factor (Ibs/SCC unit)
CO Emissions (tons/year)
CO Emission Factor (Ibs/SCC unit)
SO2 Emissions (tons/year)
SO2 Emission Factor (Ibs/SCC unit)
A-6
-------
Table A-5
Canadian Area Source Files
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.CNxxAR.V1 .DATA
Annual Canadian Area Source Data (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
80
324
21,061 (<1 mb)
Format:
Variable
Type
Size Description
AEROSPR Num 2.0
SCO Char 5.0
SAROAD1 - 4 Char 5.0
EMISS1 - 4 Num 12.4
AEROS Province Code
Source Classification Code
SAROAD Pollutant Code for VOC, NOX, CO, and SO2
Emissions (tons/year) for VOC, NOX, CO, and SO,
A-7
-------
Table A-6
Mobile Source Emission Files
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.USxxMB.V1 .DATA
Seasonal U.S. Mobile Source Data (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
224
224,856
50,813,500 (50.81 mb)
Format:
Variable
FiPST
FIPSCNTY
AMSSCC
WINEXVOC
WINEVVOC
WINCO
WINNOX
SPREXVOC
SPREWOC
SPRCO
SPRNOX
SUMEXVOC
SUMEWOC
SUMCO
SUMNOX
FALEXVOC
FALEWOC
FALCO
FALNOX
VOCEMISS
NOXEMISS
COEMISS
Type
Char
Char
Char
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Size
2.0
3.0
10.0
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
11.3
Description
FIPS State Code
FIPS County Code
AMS Source Category Code
Winter Exhaust NMOG Emissions (tons/season)
Winter Evaporative NMOG Emissions (tons/season)
Winter CO Emissions (tons/season)
Winter NOX Emissions (tons/season)
Spring Exhaust NMOG Emissions (tons/season)
Spring Evaporative NMOG Emissions (tons/season)
Spring CO Emissions (tons/season)
Spring NOX Emissions (tons/season)
Summer Exhaust NMOG Emissions (tons/season)
Summer Evaporative NMOG Emissions (tons/season)
Summer CO Emissions (tons/season)
Summer NOX Emissions (tons/season)
Fall Exhaust NMOG Emissions (tons/season)
Fall Evaporative NMOG Emissions (tons/season)
Fall CO Emissions (tons/season)
Fall NOX Emissions (tons/season)
Annual NMOG Emissions (tons/year)
Annual NOX Emissions (tons/year)
Annual CO Emissions (tons/year)
A-8
-------
Table A-7
Annual Vehicle Miles Traveled (VMT) Files
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.USxxVMT.V1 .DATA
Annual U.S. VMT Data (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
80
223,200
7,160,833 (7.16 mb)
Format:
Variable
FIRST
FIPSCNY
AMSSCC
VJTYPE
SPEED
VMT
Type
Char
Char
Char
Char
Num
Num
Size
2.0
3.0
10.0
4.0
2.0
9.3
Description
FIPS State Code
FIPS County
AMS Source
Vehicle Type
Speed (mph)
Vehicle Miles
Code
Category Code
Traveled (million
miles/year)
A-9
-------
Filename:
Description:
Location:
Table A-8
Canadian Annual Vehicle Miles Traveled (VMT) Files
File Format
WAYROMA.INTERIM.CNxxVMT.V1 .DATA
Annual Canadian VMT Data (xx = year)
National Computer Center IBM Mainframe
* Attributes:
Format:
Variable
AEROSPR
V_TYPE
VMT
Data type:
Record length:
Number of records
Bytes:
Type
Char
Char
Num
•
•
Size
2.0
4.0
9.3
EBCDIC
SO
15
256 (<1 mb)
Description
AEROS Province Code
Vehicle Type
Vehicle Miles Traveled (million miles/year)
A-10
-------
Filename:
Description:
Location:
File Attributes:
Table A-9
Highway Vehicle Emission Factor File
File Format
WAYROMA.INTERIM.USxxlUI52.V1 .DATA
U.S. Summer MOBILE5.0 Emission Factors (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
105
185,760
19,876,321 (19.87 mb)
Format:
Variable
I M FLAG
ATPFLG
ALTFLAG
STATE
SCENARIO
ASTM
YEAR
SPEED
POL
Type
Num
Mum
. Num
Num
Num
Num
Num
Num
Num
Size
2.0
2.0
2.0
3.0
5.0
2.0
3.0
2.0
2.0
Description
See GNTYIM File and Scenario Flag
See CNTYIM File and Scenario Flag
Altitude Flag
1 - low altitude
2 - high altitude
FIPS State Code
Scenario Flag
1 - I/M program and/or ATP in effect
0 - No program in effect
ASTM Class - zero for all cases
Calendar Year (2-digit- format)
Vehicle Speed Index
1 - 15 mph
2 - 20 mph
3 - 25 mph
4 - 30 mph
5 - 35 mph
6 - 40 mph
7 - 45 mph
8 - 50 mph
9-60 mph
Pollutant Index
1 - exhaust NMOG
2 - evaporative + running loss + resting loss NMOG
LDGV
LDGT
HDGV
LDDV
LDDT
HDDV
RVPJNUS
INUSE_YR
TEMPAMP
TEMPMEAN
T_RANGE
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
9.3
9.3
9.3
9.3
9.3
9.3
5.1
5.0
6.1
6.1
6.1
3 - exhaust CO
4 - exhaust NO,
Light-duty Gasoline Vehicle Emission Factor (grams/mile)
Light-duty Gasoline Truck Emission Factor
(grams/mile)
Heavy-duty Gasoline Vehicle Emission Factor (grams/mile)
Light-duty Diesel Vehicle Emission Factor (grams/mile)
Light-duty Diesel Truck Emission Factor (grams/mile)
Heavy-duty Diesel Vehicle Emission Factor
RVP Used in Case (psi)
2020 for All Cases
Ambient Temperature (°F)
Mean Temperature (°F) ([max + min]/2)
Temperature Range (°F) (max - min)
(grams/mile)
A-ll
-------
Table A-10
Canadian Highway Vehicle Emission Factor File
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.CNxxEMF2.V1 .DATA
Canadian Summer MOBILE5.0 Emission Factors (xx = year)
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
105
1,440
154,081 (<1 mb)
Format:
Variable Name
I M FLAG
ATP FIG
ALTFLAG
PROVINCE
SCENARIO
ASTM
YEAR
SPEED
POL
LDGV
LDGT
HDGV
LDDV
LOOT
HDDV
RVPJNUS
INUSE_YR
TEMPAMP
TEMPMEAN
T_RANGE
Type
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Num
Size
2.0
2.0
2.0
3.0
5.0
2.0
3.0
2.0
2.0
9.3
9.3
9.3
9.3
9.3
9.3
5.1
5.0
6.1
6.1
6.1
Description
See GNTYIM File and Scenario Flag
See CNTYIM File and Scenario Flag
Altitude Flag
1 - low altitude
2 - high altitude
FIPS Province code
Scenario Flag
1 - I/M program and/or ATP in effect
0 - No program in effect
ASTM Class - zero for all cases
Calendar Year (2-digit format)
Vehicle Speed Index
1 - 19.6 mph
2 - 55 mph
Pollutant Index
1 - exhaust NMOG
2 - evaporative + running loss + resting loss NMOG
3 - exhaust CO
4 - exhaust NOX
Light-duty Gasoline Vehicle Emission Factor (grams/mile)
Light-duty Gasoline Truck Emission Factor
(grams/mile)
Heavy-duty Gasoline Vehicle Emission Factor (grams/mile)
Light-duty Diesel Vehicle Emission Factor (grams/mile)
Light-duty Diesel Truck Emission Factor (grams/mile)
Heavy-duty Diesel Vehicle Emission Factor
RVP Used in Case (psi)
2020 for All Cases
Ambient Temperature (QF)
Mean Temperature (°F) ([max + min]/2)
Temperature Range (°F) (max - min)
(grams/mile)
A-12
-------
Table A-11
County I/M Correspondence File
File Format
Filename:
Description:
Location:
File Attributes:
WAYROMA.INTERIM.CNTYlM.V1 .DATA
County I/M Correspondence File
National Computer Center IBM Mainframe
Data type:
Record length:
Number of records:
Bytes:
EBCDIC
80
3,116
252,478 (<1 mb)
Format:
Variable
F_STATE
F_COUNTY
IM85
IM87
IM88
IM89
IM90
IM91
ALTFLAG
Type
Num
Num
Num
Num
Num
Num
Num
Num
Num
Size
2
3
1
1
1-
1
1
1
1
Description
FIPS State Code
FIPS County Code
0=No I/M; 1-l/M
0=No I/M; 1-l/M
0=No I/M; 1*I/M
0=No I/M; 1-l/M
0=No I/M; 1-l/M
0=No I/M; 1-l/M
1=Low Altitude; 2=High Altitude
A-13
-------
Filename:
Description:
Location:
Table A-12
AMS-NAPAP Correspondence File
File Format
WAYROMA.INTERIM.AMSNAP.SCC.V1.DATA
AMS-NAPAP Correspondence File
National Computer Center IBM Mainframe
ributes: Data type:
Record length:
Number of records:
Bytes:
Format:
Variable Type
NAPAPSCC Char
AMSSCC Char
EBCDIC
80
175
14,257 (<
Size
3.0
10.0
1 mb)
Description
NAPAP Source Category Code
AMS Source
Category Code
A-14
-------
APPENDIX B
PETROLEUM REFINERY VOC EMISSIONS
-------
APPENDIX B
PETROLEUM REFINERY VOC EMISSIONS
The 1985 NAPAP petroleum refinery VOC emissions are a combination of point and
area source emissions. Originally, this category was covered only by the point source
SCCs. The national emission estimate from NAPAP was well below that estimated in
Trends (EPA, 1991a), so the area source category Petroleum Refinery Fugitives was
created to reconcile this discrepancy. Trends estimates, allocated to the county level using
refinery capacity statistics, were used as the basis for developing adjusted estimates.
Point source estimates at the county level were subtracted from this total and the
resulting emissions were inventoried under the area source category. County point source
emissions from process heaters and catalytic cracking units were not included in the point
source total for petroleum refineries. Where negative emissions resulted for the area
source category, zero was used for that county and emissions in other counties were
lowered so that national totals matched Trends. A comparison of the Trends and NAPAP
emission estimates are shown in Table B-l.
While estimates for all of the categories differ, the largest magnitude of difference
occurs with blowdown systems. Trends estimates 426 thousand tons, compared with 8.7
thousand tons, which was reported in the NAPAP Point Source Inventory.
Emission differences can be the result of different assumptions concerning any of the
following: emission factors, level of control, or activity levels. Table B-l shows the
NAPAP and Trends control levels. The NAPAP estimate is a combination-of two SCCs:
30600401 (blowdown systems with vapor recovery with flaring) and 30600402 (blowdown
systems without controls).
Table B-2 shows the emissions from the 1985 NAPAP for blowdown systems.
Uncontrolled and controlled emissions are shown.
The NAPAP uncontrolled emissions were calculated based on the controlled emissions
and the control device efficiency reported. Many of the sources reported emissions of zero
and control efficiency of 100 percent. Uncontrolled emissions cannot be back-calculated
for these processes unless the emission factor and operating rate are used. Uncontrolled
emissions were estimated for these processes using the operating rate and Federal
emission factor. There are 129 total blowdown sources in NAPAP. Of these, 21 sources
reported control efficiencies of 100 percent. Eight of these sources have no operating rate
reported, so uncontrolled emissions could not be estimated. These were not included in
the summary statistics hi Table B-2. This indicates that the average efficiency for
blowdown sources is even higher than the 90 percent calculated above. It is also possible
that, since emissions are zero (or near zero) for many blowdown sources, these would not
be included in the inventory at all. (The general NEDS rule is that all sources emitting
B-l
-------
Table B-1
Comparison of Trends and NAPAP - Petroleum Refinery Emissions
Process
Refinery Operations
FCC
TCC
Process Heaters
Oil
Gas
Compressors
Slowdown Systems
Process Drains
Vacuum Jets
Cooling Towers
Asphalt Blowing
Miscellaneous
Area Source
Total
1985 Trends
1,000 tons %
8.4
0.1
0.1
2.5
0.7
426.0
158.6
28.6
27.8
13.8
161.7
828.2
Control
91.0
71.9
0.0
0.0
0.0
47.0
70.0
43.0
0.0
0.0
0.0
1985 NAPAP
1,000 tons %
32.3
1.4
2.7
4.7
3.0
8.8
45.5
11.3
9.6
2.0
80.1
727.8
929.2
Control
95.6
25.9
0.0
60.1
2.8
89.6
49.4
61.6
17.4
33.3
88.7
45.0
Table B-2
1985 NAPAP Slowdown Emissions
Source Category
Slowdown
Vapor Recovery/Flaring
Without Controls*
Total
Uncontrolled
23,682
60,802
84,484
Controlled
7,851
906
8,757
% Control
67
99
90
NOTES: * The SCC description (30600402) for this category is blowdown systems without controls; however,
primary control devices and efficiencies were listed for these sources.
B-2
-------
more than 25 tpy of a criteria pollutant should be included in a facility's inventory, which
results in an increase in the average efficiency.) Of the 129 blowdown sources reported in
the inventory, 109 are with vapor recovery and flares, while 20 sources are without
control. This again indicates that blowdown systems are well controlled.
If the Trends emissions estimate for blowdown is adjusted to 90 percent control,
emissions decrease to 80 thousand tons. The control level reported in Trends is 47
percent.
The second area where the Trends and NAPAP estimates for blowdown emissions
could differ is in the emission factor used. Table B-3 is a comparison of the Trends and
NAPAP emission factors for each process.
The uncontrolled emission rate for the Trends blowdown category is based ^on a 1970
snapshot of emissions, operating rate, and control efficiencies. Trends estimates
emissions based on the following factors:
Old Systems (1970 rates): 178.84 lb/103 bbl
New Systems (NSPS rate): 5.26 lb/103 bbl
(Old systems would then be operating at an average efficiency of 32 percent over
uncontrolled, NSPS systems at 98 percent control.)
The calculation for the NSPS capacity is fairly complicated. The calculation starts
with 1977 capacity. Each successive year, any increase in capacity from the previous year
is considered NSPS capacity plus an additional 1 percent of the previous year's capacity
(to account for retirement). In 1985, 75.8 percent of capacity is categorized as "old" and
24.2 percent "new." This results in the weighted emission factor of 136.8 lbs/103 bbl. The
Trends control efficiency is calculated based on this weighted emission factor and the
estimated uncontrolled emission factor of 290 lb/103 bbl.
There has been no attempt to update the emission factors used in Trends, primarily to
maintain consistency with past estimation methodologies. With the advances in control
technology and application of reasonably available control technology (RACT), existing
sources are most likely operating at a higher efficiency than assumed in Trends.
As a comparison to the NAPAP and Trends estimates, a weighted average emission
factor based on AP-42 was calculated. The factors were weighted by the number of
sources appearing in NAPAP under each SCC. Operating rate would be a more accurate
indication of the weighting, however, since this variable does not have a high level of
confidence within the NAPAP Inventory. The weighted factor is estimated based on 109
sources at 0.8 lbs/1,000 bbl and 20 sources at 580 lbs/1,000 bbl. This results in a
weighted factor of 90.6 lbs/1,000 bbl. Multiplying this by the 1985 activity level from
Trends (5549.4 million bbl) and applying the NAPAP efficiency of 90 percent yields total
blowdown emissions of 25,000 tons per year.
As a lower bound for blowdown emissions, assume that all systems have a vapor
recovery system and flare. Using the emission factor of 0.8 lbs/1,000 bbl, the lower bound
estimate of national blowdown emissions is 2.2 thousand tons.
B-3
-------
Table B-3
Comparison of NAPAP and Trends Emission Factors
Process
Trends
(lbs/1,000 bbl)
NAPAP
(lbs/1,000 bbl refinery feed)
Refinery Operations
FCC
TCC
Process Heaters
Oil
Gas
Compressors
Slowdown Systems
Process Drains
Vacuum Jets
Cooling Towers
Asphalt Towers
Miscellaneous
140.8
55.7
12.6
2.8
0.2
290.0
190.0
42.8
10.0
5.0
58.3
140.8
55.7
0.3
2.8
3.7
0.8
580.0
200.0
18.0
10.0
60.0
lbs/1,000 bbl fresh feed
lbs/1,000 bbl fresh feed
lbs/1,000 gal
"lbs/106cf
(vapor recovery)
(no control)
Ibs/ton asphalt
B-4
-------
As yet another comparison, the Control Techniques Guideline (CTG) for petroleum
refinery processes, published in 1977 (Group I summary document), was reviewed. This
was after a review of the 1970 snapshot of emissions from which the emission factors
were derived for Trends. This comparison further indicated that the control level in
Trends is underestimation, because existing sources in nonattainment areas must apply
RACT according to the CTG. The uncontrolled emission rate quoted in this source is 301
lbs/1,000 bbl (close to that used in Trends). The CTG recommends venting all vapors to a
flare or a vapor recovery system with an average reduction of 98 percent (or 6 lbs/1,000
bbl). Using this controlled emission factor, nationwide emissions are estimated at 17,000
tons.
It is not entirely clear why the AP-42 emission factors differ from those in the CTG.
One guess is that the CTG factor is for process unit turnarounds which may only include
planned releases. AP-42 accounts for both planned and accidental releases. For the
controlled rate, AP-42 assumes complete combustion or smokeless burning (required in
most States). This is accomplished by injecting steam into the combustion zone of the
flare to provide turbulence and to aspirate air. This is probably more stringent than the
control recommended by the CTG.
The summary of VOC control techniques (published by EPA in 1986) lists the
uncontrolled emission factor for process unit turnarounds at 300 lbs/1,000 bbl. The
emission factor for refineries that control process unit turnarounds by depressurizing to a
control device is listed at 5.26 lbs/1,000 bbls. These again match Trends. Using the
controlled emission factor of 5.26 lbs/1,000 bbls yields national emissions of 14.6 thousand
tons.
A summary of alternative estimates of blowdown emissions is shown in Table B-4.
From the information presented, it is clear that blowdown emissions are well controlled.
Of the alternatives listed in Table B-4, the AP-42 emission factor weighted by the number
of sources was chosen for use in the inventory. The emission factors from the CTG and
Trends are from earlier documents. The AP-42 section on petroleum refineries was
completed in 1980, the other factors date back to the 1970s. In addition, there are
probably blowdown systems not included in the inventory because they are well controlled
and have zero or near zero emissions. While weighting by throughput would be more
accurate, this is simply not available.
Table B-4
Alternative Estimates of National VOC Emissions
Petroleum Refinery Blowdown Systems (1,000 tons per year)
Methodology VOC Emissions
Trends " ~~~ " ~~~ 426.0
Trends, 90 percent Efficiency 80.0
AP-42 emission factor, weighted by number of sources
reported in NAPAP with vapor recovery and flares, and without 25.0
CTG emission factor, with vapor recovery 17.0
NAPAP Point Source Inventory 8.7
AP-42 emission factor, with vapor recovery systems and flaring 2.2
B-5
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