oEPA
            United States
            Environmental Protection
            Agency
Office of Air Quality
Planning and Standards
Research Triangle Park NC 27711
EPA-45Q/4-91-019
July 1991
            Air
           PROCEDURES FOR
               PREPARING
       EMISSIONS PROJECTIONS

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                               EPA^450/4-91-019
    PROCEDURES FOR
         PREPARING
EMISSIONS PROJECTIONS
                By

        E. H. Pechan & Associates, Inc.
          Springfield, VA 22151
         EPA Contract No. 68D00120

       EPA Project Officer Keith Baugues
    Office Of Air Quality Planning And Standards
         Office Of Air And Radiation
      U. S. Environmental Protection Agency
       Research Triangle Park, NC 27711

              July 1991

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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 publicatioa Any mention of trade names or commercial
products is not intended to constitute endorsement or recommendation for use.
                                     EPA-450/4-91-019
                                            11

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                             CONTENTS

                                                            Page

TABLES	v

FIGURES	vi

ACRONYMS AND ABBREVIATIONS	vii

FOREWORD	ix

   I. INTRODUCTION AND SUMMARY	1
      A. BACKGROUND	1
      B. OVERVIEW	1
      C. KEY POINTS IN THE GUIDANCE	'	3
      D. REPORT ORGANIZATION	6

  II. TYPES OF PROJECTIONS	9
      A. BASELINE EMISSIONS PROJECTIONS	9
      B. CONTROL STRATEGY PROJECTIONS	10
      C. RULE EFFECTIVENESS AND RULE PENETRATION	11
      D. ACTUAL AND ALLOWABLE EMISSIONS	12

 III. PROJECTIONS OF FUTURE ACTIVITY 	 15
      A. GENERAL GROWTH INDICATORS 	  	 15
          1. Employment	15
          2. Earnings	16
          3. Value Added	16
          4. Product Output	17
      B. REGIONAL PROJECTIONS USING BEA DATA	17
      C. POINT SOURCES	..23
      D. AREA SOURCES	26
      E. MOBILE SOURCES	 29
          1. Highway Vehicles	29
          2. Aircraft	40
          3. Railroads	40
          4. Gasoline Marketing	40

  IV. MEASURING THE EFFECTS OF CURRENT AND FUTURE CONTROLS  . 43
      A. VOLATILE ORGANIC COMPOUNDS	43
      B. OXIDES OF NITROGEN	49
        .1. Electric Utilities. . . •	 52
          2. Non-Utility Generators	58
          3. Industrial Sources	58
      C. CARBON MONOXIDE	59
      D. MOBILE SOURCES	59
          1. Highway Vehicles	59
          2. Railroads ."	60
          3. Aircraft	60
          4. Non-Road- Engines and Vehicles	61
                               111

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                        CONTENTS (continued)
   V. COMBINING GROWTH AND CONTROL EFFECTS 	 62
      A. OPTIONS	62
      B. GROWTH AND RETIREMENT RELATIONSHIPS 	 63
      C. FUTURE DIRECTIONS -- EMISSION PREPROCESSOR
         SYSTEM (EPS) ENHANCEMENTS 	 68

  VI. VALIDATION	70

 VII. CASE STUDIES		 73
      A. SOUTHERN CALIFORNIA EMISSION PROJECTIONS	73
          1. Population Projections	73
          2. Baseline Emission Projections 	 79
      B. REGIONAL OZONE MODELING FOR NORTHEAST TRANSPORT
         -- PROJECTION YEAR AND CONTROL STRATEGY
         EMISSIONS INVENTORIES 	 	 	 85
          1. Inventory Structure	 85
          2. Projection and Control Algorithms for Point
             and Area Sources. .	86
          3. Projection and Control Algorithms for Mobile
             Sources	88
          4. Summary of Future Scenarios	88

VIII. BIOGENIC EMISSIONS PROJECTIONS 	 91

   IX. QUALITY ASSURANCE PROCEDURES	93
      A. INTRODUCTION	 93
          1. Definitions of Quality Assurance	 93
          2. Purpose of Quality Assurance	93
      B. DESCRIPTION OF TASKS	94
          1. Types of QA Procedures	94
          2. Program Elements Requiring QA	95

  X. DOCUMENTATION	 97

      REFERENCES	99

      BIBLIOGRAPHY	103

      APPENDIX A:   Projected Electric Generating Unit
      Additions .by State, Company,  and Plant, 1990-1999,
      As of December 31, 1989	A-l

      APPENDIX B:   Projection Inventory QA Checklist .... B-l

      APPENDIX C:  Historical Earnings Data 	 C-l
                                IV

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                              TABLES
Number                                                      Page

III.l     Industrial Groupings for the BEA Regional
            Projections	19
III.2     BEA Regional Projections	24
III.3     Growth Indicators for Projecting
           . Emissions for Area Source Categories 	 27
III.4     Annual Vehicle Miles of Travel by Functional
            System	33
III.5     Total Public Road Mileage by Functional System .   . 34
III.6     Sample Projection of Car Registration from a
            1990 Base Year	37
III.7     MOBILE4.1 Fuel Consumption Model Normalized
            On-Road Fleet Gasoline Efficiency Ratios .... 42
IV. 1      CAAA Mandated Motor Vehicle Programs	 45
IV.2      Proposed New Control Technique
            Guidelines (CTGs) Under the CAAA 	 46
IV.3      Estimated Control Efficiencies of
            Existing CTG Controls	47
IV.4      Representative Stationary Source VOC
            RACT Control Levels	48
IV.5      CAAA Provisions Summary	50
IV. 6      Stationary Source RACT Controls for NOX	53
IV.7      CAA NOX Limits  for  Utility  Boilers  for
            2000 and Later	 57
V.I       Industrial Retirement Rates	65
V.2       Retirement Rates Developed From Internal Revenue
            Service Depreciation Guidelines	66
VII.1     Base and Nonbase Industries for the SCAG Region.   . 78
VII.2     Stationary Source SCAG Region Control Factors
            For the Years 2000 and 2010	80
VII.3     SCAG Region SIC Code Growth Factors for the
            Year 2000	81
VII.4     Baseline Socioeconomic Forecasts for the South
            Coast Air Basin	84
VII.5     Equations Used to Predict Future Point and
            Area Source Emissions	87
VII.6     Equations Used to Predict Future Mobile
            Source Emissions	89
                                v

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                             FIGURES

I.I       Projection Approach Summary	4
III.l     Ratio of Annual VMT to Road Mileage by
            Roadway Function Class	  . 35
VII.1     Relationship Between SCAG Demographic and
            Economic Projections 	 75
VII.2     SCAG Economic Projection Model	77
                                VI

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                    ACRONYMS AND ABBREVIATIONS





AFSEF      AIRS  Facility Subsystem Emission  Factors



AIRS       Aerometric  Information  Retrieval  System



AUSM       Advanced Utility  Simulation Model



BEA        Bureau  of Economic Analysis



BEIS       Biogenic Emissions Inventory  System



.BLS        Bureau  of Labor Statistics



CAA        Clean Air Act



CAAA       Clean Air Act Amendments of 1990



GARB       California  Air Resources Board



CHIEF      Clearinghouse for Inventories and Emission  Factors



CMSA       Consolidated  Metropolitan Statistical Area



CO         Carbon  Monoxide



CTG        Control Technique Guidelines



EPS        Emission Preprocessor System



FMVCP      Federal Motor Vehicle Control Program



GNP        Gross National Product



HPMS       Highway Performance Monitoring System



I/M        Inspection  and Maintenance



LNB        Low NOX Burners



MACT       Maximum Available Control Technology



MPO        Metropolitan  Planning Organization



MSA        Metropolitan  Statistical Area



NAAQS      National  Ambient  Air Quality Standard



NAPAP      National  Acid Precipitation Assessment  Program



NEDS       National  Emissions Data  Systems



N02         Nitrogen  Dioxide





                               vii

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NOX       Oxides  of Nitrogen



NSPS      New  Source  Performance Standard



O3        Ozone



OAQPS     Office  of Air Quality Planning and Standards



QA        Quality Assurance



QC        Quality Control



RACT      Reasonably  Available Control Technology



RE        Rule Effectiveness



ROM       Regional Oxidant Model



ROMNET    Regional Oxidant Modeling for Northeast Transport



RP        Rule Penetration



RPC       Regional Planning Commission



RVP       Reid Vapor  Pressure



SCAG      Southern California Association of Governments



SCAQMD    South Coast Air Quality Management District



SCC       Source  Classification Code



SIC       Standard Industrial Classification



SIP       State Implementation Plan



SOCMI     Synthetic Organic Chemical Manufacturing Industry



THC       Total Hydrocarbon




TSDF      Treatment Storage and Disposal Facility



VMT       Vehicle Miles Traveled



VOC       Volatile Organic Compound
                              Vlll

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                             FOREWORD
                                       y

     The  purpose of  this document  is to  provide  guidance  for
projecting  emissions  to future years.   It  focuses  primarily on
procedures  for projecting how  the  combination of future emission
controls and changes in source activity will influence future air
pollution emission  rates.   While many of the  procedures  in this
document can be applied to other pollutants  (i.e.,  PM-10,  SO2,  and
toxics),  the  methods are directed towards  ozone  precursors  and
carbon monoxide.  Later guidance should more specifically address
other pollutants.

     Software which incorporates the techniques  outlined  in this
document is expected to be released  in the  spring of 1992.   This
will be accomplished by modifying the Emission Preprocessor System
to include the effects  of growth and controls.  In the long term --
over the next three years '— EPA plans to  develop a new emission
preprocessor  (Emissions Preprocessor Analysis  Module)  which will
also simulate growth and control effects.
                               IX

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I INTRODUCTION AND SUMMARY
     A. BACKGROUND

     As a result of the U.S. Environmental Protection Agency's
 (EPA) program dealing with the control of atmospheric ozone  (O3)
and carbon monoxide  (CO), state and local air pollution control
agencies responsible for 03 or CO nonattainment areas must
prepare base year emission inventories and project emissions to
future years to serve as a basis for State Implementation Plans
 (SIPs).  The purpose of this document is to provide detailed,
comprehensive guidance for projecting emissions to future years.
It is assumed that readers of this report are familiar with all
of the companion EPA documents that describe how to prepare a
base year (currently 1990) emission inventory  (these are listed
in the Bibliography).  That material is not repeated here.

     The focus of this report is on procedures for projecting how
the combination of future emission controls and changes in source
activity will influence future air pollution emission rates.
While most of the emphasis in this document is on estimating
future O3 precursor emissions,  CO emission projection procedures
are presented as well.
     B. OVERVIEW

     The goal in making projections is to try to account for as
many of the important variables that affect future year emissions
as possible.  Each nonattainment area is encouraged to
incorporate in its analysis the variables that have, historically
been shown to affect its economy and emissions the most, as well
as the changes that are expected to take place over the next 10
to 20 years.

     Each area should examine the source types that currently
dominate its inventory and each should perform some rough
calculations to see if that source distribution is likely to.
change much in the near future.  This should suggest the emphasis
that might be placed on projection methods for predominant source
categories (if there are any).

     In the typical ozone nonattainment .area,  there is normally a
wide range of ozone-precursor-emitting source types.  Thus, it is
probably only in exceptional cases where there are only one or
two major source types that, dominate the inventory.  Large point-
source emitters in ozone nonattainment areas are already subject
to Reasonably Available Control Technology (RACT)  requirements
and,  in some cases, control technique guidelines (CTGs), which
may be identical.  Therefore, there are likely to be many
different volatile organic compound (VOC) emitters in ozone
nonattainment areas whose"emissions need to be tracked with time.
In cases where there are a few dominant sources, special

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techniques should be used to ensure that those sources are
modeled using more sophisticated techniques than those used for
the rest of the inventory.

     Whether or not an area expects to have any interest in
estimating control costs and making selections of measures based
on cost effectiveness will influence the choice of projection
methods.  The area's needs for inputs to a grid-based model are
also a factor in making projections.

     Cost analyses are best performed using as much source-
specific information as possible.  Equations used to estimate
control costs typically use uncontrolled emissions, stack gas
flow rate, and/or unit capacity as independent variables.  It is
also important to know what controls are already in place and
what their control effectiveness level is.  Requirements in the
Clean Air Act (CAA) Amendments of 19.90 (CAAA) for new, more
stringent control techniques cannot be completely evaluated
unless comparisons can be made at the source level.  Whether or
not a source will meet RACT or Maximum Available Control
Technology (MACT) requirements with existing controls can only be
determined at the source level.

     Likewise, grid-based models require source locations
(coordinates) as input, so a projection approach that makes its
computations at this level is preferred.   The alternative is to
assume that all growth and retirement occurs at existing
facilities and that there is no variation in growth or control
within each source category.

     The organization of the base year inventory and the methods
used to make emission projections are also related.  As an
example, emission inventory source categories and the categories
used in the projection analysis should be determined by the
regulations likely to be applied.  The CTG documents currently
being prepared for the source types are listed below.

   • Synthetic Organic Chemical Manufacturing Industry (SOCMI)
     Reactor Processes
     SOCMI Distillation Processes
     Plastic Parts (Business Machines)  Coatings
     Plastic Parts Coatings (Other)
     Web. Offset Lithography
     Auto Body Refinishing
     Clean-Up Solvents
     Petroleum and Industrial Wastewater
     Wood Furniture Manufacturing
     SOCMI Batch Processes
     Volatile Organic Liquid Storage Tanks

     It is important that the VOC emissions for each of these
source types be included in the base year emission estimates,  and
that each of these categories be treated separately in the

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emission projections.  Otherwise, the emission benefit of the new
CTGs will be unquantifiable.

     There is a need for flexibility in being able to adapt
control strategy planning to accommodate changing information.
New knowledge about emissions and their control becomes available
on an irregular basis that does not always correspond with State
Implementation Plan  (SIP) schedules.  Therefore, states need to
be prepared to occasionally update ozone standard attainment
analyses to take into account the most recent information.

     Choice of a projection technique may also be affected by the
number of years between the base year and the projection year.
At a miniaoua, each nonattainiaent area has to make a projection to
its attainment deadline year in order to be able to demonstrate
that it will meet the ambient standard.  Ozone noriattainment
dates are 1993 for marginal ozone nonattainment areas, 1996 for
moderate, 1999 for serious, 2005 .for severe (except for New York
and Houston, which have until 2007),. and 2010 for extreme.  Areas
with attainment deadlines after 1996 will also have emission
projection requirements to measure progress until attainment.

     Emissions projections for CO nonattainment areas must be
submitted to EWl by November 1992*  Draft osone precursor
emission projections are due at. the same time.  Final ozone
precursor eadsstofc projections through 199$ for moderate and
above areas must 4be submitted to EPA by November 1993.  Final
projections beyond 1996 are due for serious and above areas by
November^ 1994.
     C. KEY POINTS IN THE GUIDANCE

     This section summarizes the most important points in this
guidance document.  Basic methods and a structure for performing
emission projections are also summarized in Figure I.I.

   • EPA assumes that, at a minimum,  state and local agencies
     will have available detailed projections of population and
     employment that can be used to estimate future activity
     levels.

   • For the purpose of base year and projection year emission
     inventories under the CAAA, EPA will allow the use of an 80
     percent default value for rule effectiveness, but will also
     give states the option to derive local category-specific RE
     factors.

   • Any emission projection made for use in SIP modeling shall
     use an allowable emission rate for that purpose.

   • For the purposes of preparing industrial emission
     projections for a SIP,  it is expected that,  at a minimum,
     earnings projections will be used.  Real earnings data are

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                                              Figure 1.1
                                Projection Approach Summary
               Point Sources
                Stationary Area Sources
                         Highway Vehicles
                         Off-Road Vehicles
Activity
Level
BEA
Earnings
Projections

Survey
Approach

Table III.3
Indicators

BEA
Earnings
Projections

Travel
Demand
Model

Trend
Analysis

Table III.3
Indicators

BEA
Earnings
Projections
Emission
  Rates
                   CTG
               non-CTG PACT
NSPS
                Title ill MACT
               Title IV for NOx
Emissions Peductions
will be related to
commercial/consumer
solvent regulations and
whether areas extend
rules to apply to smaller-
sized sources as wellas
what can be achieved by
current rules.
MOBILES or EMFAC7E
Future rates depend on
EPA regulatory decisions.

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available for all states at the 2-digit SIC level from the
Bureau of Economic Analysis.  Data on value added or
projected product outputs should be used where available.

It is recommended that point source survey approaches be
used only when there is a dominant industry in an area whose
emission growth is not likely to be captured in regional
projections, and where there is a reasonable expectation
that significant growth may occur.

Area source projections can be made using local studies or
surveys, or through surrogate growth indicators.

Motor vehicle emission projections are to be made using
motor vehicle emission factor models and estimates of future
activity (vehicle miles traveled).  For states and U. S.
territories other than California,. MOBILES will be the
preferred tool for estimating motor vehicle emission rates
for years after 1990.  MOBILES is not scheduled for release
until May 1992.  In the interim, EPA is planning revisions
to MOBILE4.1 to allow states to make CO projections.

The preferred method for performing YMT projections is to
use a validated zonal-based travel demand model.  For areas
that do not have a validated travel demand model,  VMT
projections may be based on VMT trends from 1985 to 1990 as
measured by the Federal Highway Administration's Highway
Performance Monitoring System.

As highway vehicle emission rates are further reduced, other
mobile sources such as aircraft, railroad locomotive diesel
engines, vessels, and non-road engines become a more
significant portion of the emission inventory.  EPA is
currently evaluating regulatory initiatives for all of these
source types, so emission projections need to be made using
the latest available information on likely regulations for
these sources (most of which was not available in time to be
included in this document).

Base case emission projections for any area should,  at a
minimum, include an estimate of the effects of current
regulations and standards,  plus the likely effect of
controls mandated by the CAAA.  Chapter IV of this report
provides guidance on measuring the effects of current and
future controls.

EPA is in the process of upgrading the Emission Preprocessor
System (EPS) to provide a computerized tool to implement the
guidance in this document.   The revised program is expected
to be available for distribution to the states by May 1992.
Longer term, EPA plans to develop a new emissions
preprocessor, the Emissions Preprocessor Analysis Module
(EPAM).

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   • Guidance addressing the issue of performing emission
     projections for tracking Reasonable Further Progress  (RFP)
     will be published separately.  This RFP tracking document is
     scheduled for publication in November 1991.


     D. REPORT ORGANIZATION

     Chapter II of this report describes the different types of
projections that might be required of a state or local air
pollution control agency.  Rule effectiveness, rule penetration,
and use of actual versus allowable emissions in projections are
also discussed in Chapter II.

     The -'two most important steps la performing any emission
projection ares < <1> estimating future source activity levels aM
(2) quaxttIfylrig the effects of current and future controls.
T£e0e, ti#o topl^jupe aiactxasedvi»^0epa|taV'e--cliapters«  Methods for
projecting changes in future air pollution generating activities
are described in Chapter III.  Techniques"for quantifying the
effects of current and future controls are described in Chapter
IV.  Chapter IV necessarily focuses on the new control
initiatives mandated by the CAAA.

     Chapter V describes some options for combining the effects
of growth and control in a manner that meets the needs for
attainment planning and-providing model inputs.  Validation of
emission projections, primarily by comparing them with other
recently completed studies, is discussed in Chapter VI.

     It is useful to examine the techniques that have been
applied in ozone nonattainment areas where some control strategy
planning has already been performed.  Chapter VII provides two
such examples.  The South Coast Air Quality Management District
(SCAQMD) has performed such analyses and has prepared future year
emission projections in a form suitable for input to a grid-based
photochemical model.  In the simplest sense, this approach relied
on developing a growth factor and a control factor for each major
source category.   These growth and control factors were then
applied universally within the air basin.

     The Regional Oxidant Modeling for Northeast Transport
(ROMNET) study is another recent example where future year
control scenarios were evaluated.  It provides examples of
preparing grid-based modeling inputs as well.

     Biogenic emission projections are discussed in Chapter VIII.
In most cases, it is expected that biogenic emissions will be the
same in the projection year as they are in the base year.
Quality assurance procedures for projections are described in
Chapter IX.  Requirements for documenting projection methods and
future year emission estimates are the subject of Chapter X.

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     Appendix A lists projected electric generating unit
additions by state, company, and plant, from 1990 to 1999.
Appendix B is a quality assurance checklist.

     The use of historical earnings data to adjust 1990 emission
values to match with observed ozone episodes in other years is
described in Appendix C.

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8

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II TYPES OF  PROJECTIONS


     This chapter  introduces some basic concepts  in making
emission projections, such as the_ difference between baseline and
control strategy jproject^ions. ^ TJbieV«WpJiisis of tnisguidanee
jdocument-iet'^                                estimates in a
form * witflbl*.* f 6^^ev:€iiM?ro : toodtel^g-'illfcm^^         » 'Thus ,*
 , % . k    v~v.svA™™™v.v»vl,/^v.vK.,,v.,,v™^^                  ----- •hvwOww.«t«(»~~( ...... v.v.,..v.,., ------ , , .  , .
while a baseline emissions projection is useful in  establishing a
starting point for examining the effects of various control
scenarios, it is expected that most of the analytical effort will
be put in developing several control strategy projections to
simulate how the CO or ozone standard might be attained.   Rule
effectiveness and  rule penetration are important  concepts to
understand before  developing an emission projection methodology.
They are defined in this chapter.  Finally, the need to  make
emission projections using estimates of allowable emissions is
explained.


     A. BASELINE EMISSIONS PROJECTIONS

     Baseline emissions projections are estimates of future year
emissions from point, area, and mobile sources that take into
account expected growth in an area, existing air  pollution
control regulations in effect at the time the projections are
made,  and regulations expected to take effect at  future
intervals.   Baseline projections are needed by an agency to
measure reasonable further progress and to determine additional
emissions reductions necessary to attain the National Ambient Air
Quality Standards  (NAAQS) .  Baseline emissions projections
represent the "typical" situation.

     Recommendations for making projections are outlined briefly
below.  More specific guidance is presented in the  chapters that
follow.
     TO a large -^tlaiyx pro3«ctl6a^i»ventorie«'' are, based on
     forecasts of industrial grrowtn, population growth, changes
     ^ Jl^                                           The air
     pblXutibri 'c°^
     independent forecasts, but should rely on the local
     metroppli-tan planning organization  (MPO) , regional planning
     commission  (RFC), or other planning agency to supply them.
     This course has several advantages.  First, development of
     forecasts is costly and time consuming and would be a
     duplication of effort.  Second, the air pollution control
     agency should bas.e its emissions projections on the same
     forecasts used by other governmental planning agencies .
     This consistency is needed to establish the credibility of
     any proposed control programs based on emissions
     projections.  However, the air pollution control agency
     should keep in mind any potential biases which may be
     inherent in the forecast data supplied by other agencies.
     Comparison with regional forecasts such as those produced by

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      the  Bureau of Economic Analysis (BEA)  can assist in finding
      these  potential  biases.   E?A aesxiies that,  afc r»otti»i«
      stiate  anc£ -local  agencies will have available detailed
      P^jectio»»^o«^o4mllil:ii0tt.:a»  are i  open . t°. ....!9fti6Svt_ipn because °f
    • speculative nature.  9*he 'fcecnnical "'^repLlblldtv^f ''"
     projections -is a function of their  reasonableness,  te,
     amount of ; research on: and documentation of  assumptions; .-'and
     t&e procedures or methodologies used to wake the
     projections.  Some' degree of uncertainty will  always
     accompany emissions projections;  this should be  acknowledged
     openly and  addressed to the extent  possible.   The art  of
     projecting  emissions is not in eliminating  uncertainty, but
     in minimizing it.  internal and external reviews of
     emissions projectioEsf will  improve  their technical- 
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projecting emissions from categories emitting the hazardous air
pollutants listed in Title III.

     The effects of controls on area sources can usually be
simulated by changes in either emission factors or.activity
levels, depending on the source and nature of the control
measure(s) being considered.


     C. RULE EFFECTIVENESS AND RULE PENETRATION

     Past inventories have assumed that regulatory programs would
be implemented with full effectiveness, achieving all of the
required or intended emissions reductions and maij^a^inj^that
level over time.  jSfafoiclaja^^
pttoream9>&1!tt*£edb tbaanflOQ- percent effective in^stjsourcy
categories ttounost.*areas of the ^country.  The concept "of applying
rule effectiveness  (RE) has evolved from this observation.  In
short, RE reflects the ability of a regulatory program to achieve
all the emissions reductions that could be achieved by full
compliance with the applicable regulations at all sources at all
times.

     Several factors should be taken into account when estimating
the effectiveness of a regulatory program.  These include the
following:  (1) the nature of the regulation (i.e., whether any
ambiguities or deficiencies exist, whether record keeping
requirements are prescribed); (2) the nature of the compliance
procedures (i.e., taking into account the lotig-term performance
capabilities of the control); (3) the performance of the source
in maintaining compliance over time (e.g., training programs,
maintenance schedules, record keeping practices); and (4) the
performance of the implementing agency in assuring compliance
(e.g., training programs, inspection schedules, follow-up
procedures).

     For the purpose of base year and projection year emission
inventories under the CAAA, EPA 'will- allow tfce use of att 80
percent default value for rule effectiveness, but will, also give
states tfce option to derive local category-specific RE factors
according to guidance contained in Procedures For Estimating And
Applying Rule Effectiveness In Post-1987 Base Year Inventories
For Ozone And Carbon Monoxide State Implementation Plans (U.S.
EPA,  1989).

     In both baseline and control strategy projections,  the RE
determined for the source category should be applied to all
sources in the category  (both point and area sources) with the
following exceptions:  (1) sources not subject to the regulation;
(2) sources achieving compliance by means of an irreversible
process change that completely eliminates emissions; (3) sources
for which emissions are directly determined by calculating
solvent use over some time period, assuming all solvent was
emitted from the source during that time period; and (4) those
with measured emissions  (continuous emission monitors).

                                11

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      The  RE factor shall  be  applied  to  the  estimated control
 efficiency in the  calculation  of  emissions  from a source.   An
 example of the application is  given  below.

      Uncontrolled  emissions  =  50  Ibs/day
      Estimated control  efficiency =  90%
      Rule effectiveness = 80%
      Emissions after  control = 50 [  1 - (0.'90) (0.80) ]
                             = 14 Ibs/day

 (The  application of RE  results in a  total emissions  reduction of
 72 percent,  not 90 percent)                           .

      3Ctt aMitio» t6xious j-u,le-|>e»e.i«atio»- pp?> is another
 important regulatory  coins iteration* ^hicli ik the extent to  which
 a ^^^^^..'^^Jc^^..^lJ»nion^''tt^^j^a£^_^eA»9d^^  when
 jprb5ect"lng"'estlinat¥d""emissions
 for source categories where  a  rule or regulation applies,
 agencies  should incorporate  an estimate of  the  amount of rule
 penetration by means  of the  following formula:

                    Uncontrolled emissions
 Rule  Penetration = covered by  the regulation      x 100%
                    Total  uncontrolled emissions

 Once  uncontrolled  emissions  and rule penetration are determined,
 RE should be applied  as discussed above.  An example category
 follows:

      Uncontrolled  emissions  =  1,000 tpy
      Control  efficiency required  by the regulation = 95%
      Rule penetration = 60%
      Rule effectiveness = 80%
      Emissions  from the category  =
      (1,000)11 -  (0.60)(0.95)(0.80)] = 544 tpy
     Further discussions of the use of rule effectiveness and
rule penetration are included in Procedures For The Preparation
Of Emission Inventories For Carbon Monoxide"And Precursors Of
Ozone. Volume I  (U.S. EPA, 1991) .
     D. ACTUAL AND ALLOWABLE EMISSIONS

     In projecting emissions, states must clearly identify when
the projections use actual and when they use allowable emissions.
Actual emissions are defined as the product of an actual
emissions rate for a current year (based on known physical
characteristics), the actual operating capacity  ("throughput"),
and the actual operating schedule of the facility.  Allowable
emissions are the product of an enforceable emissions rate (e.g.,
pounds of VOC per gallon of solids applied), the anticipated
operating rate or activity level (e»g,» gallons of solids applied
                                12

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per Hour-) , ,:-aiid;,t;he fmtlcipatedopiBratinff schedule , (hours ""per
                                   for use i» SIP modeling shall
use an allowable  emission rate for that purpose.  There are"
instances,  such as  RFP modeling,  where actual emission rates
might be used, but  these will  be  the exception,  not the rule.
Methods used  to estimate future activity levels  are not affected
by the choice between actual and  allowable emission rates.  Thus,
allowal&a^eMgsi^^
condiitlcmi^ : withjtlia; ^BX^^ta^J^^^f^^ ..lp.a? (8760 hrs /y r ) ,
but "are T calculated  b^                 anticipated operating rate
by the maximum allowable emission rate.   For example,  if a unit
with a low NOX burner is emitting  0.3  Ib NOX/106  Btu, but the
allowable emission  rate is 0.4 Ib NOX/106 Btu, the 0.4 rate would
apply in the  future case,  unless  the control strategy changed the
applicable regulation.

     Consider the case:

     1990 Emission  Inventory  (E.I.)
     [The assumed source test  measured emissions are 0.3 Ib NOX/
     106 Btu.]

     [3 x 1012 Btu/yr]  [0.3 Ib  NOX/106 Btu] = 9 x 10s Ib NOx/yr
     = Actual Base  Year Emissions

     1996 Baseline
     [Assume  a 6  percent growth rate over period,  and  control
     only to  required  level . ]

     [3 x 1012 Btu/yr]  [1.06 growth rate]  [0.4 Ib NOX/106 Btu]  =
     1.3 x 106 Ib NOx/yr = Projected Allowable Emissions

     1996 Control Strategy Projection
     [Assume  a new  NOX limit of 0.2 Ib NOX/106  Btu.]

     [3 x 106 Btu/yr]  [1.06 growth rate]  [Q.2  Ib NOX/106 Btu]  =
     6.4 x 10s Ib NOx/yr = Projected Control Strategy Emissions

     It should also be  understood that there can be a  difference
between allowable emissions and projected allowable emissions.
The distinction is  that  current activity  levels  and projected
activity levels can be  different.
                                13

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14

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 Ill PROJECTIONS  OF  FUTURE ACTIVITY

     This  chapter presents  information on procedures that can be
 used by  states to estimate  future activity levels, including
 those  that will  generate pollution.  These procedures range from
 surveys  of individual  facility expansion plans to use of national
 data bases.  At  the start of the chapter/ some general guidelines
 for choosing among  activity indicators are presented.  This is
 followed by a description of EPA's preferred data source for
 performing projections of future activity for most stationary
 source categories,  the "Bureau of Economic Analysis Regional
 Projections to 2040"  (BEA,  1990a; 1990b; 1990c).  [These data are .
 available from the  EPA-OAQPS Emission Inventory Branch in
 machine-readable form via the CHIEF Bulletin Board system,]
 Specific guidance for point, area, and mobile source categories
 is then  presented.
     A. GENERAL GROWTH INDICATORS

     EPA encourages areas to use the best possible growth
indicators appropriate for the region and source category of
interest.  For those unfamiliar with developing or applying
growth indicators, general rules of thumb for choosing among
indicators can be applied.  Typical indicators (listed in
priority order) are provided below:

   • Product Output .
   • Value Added
   • Earnings
   • Employment

     (The effectiveness of each of these four growth indicators
will be discussed below.)

     Because the major forces behind growth in the economy
include the. quality and availability of natural resources,
capital growth, skill of the labor force, and technological
change, the most accurate growth indicator would best encompass
these factors.  Economic growth involves an increase over time in
the actual output of goods and services, as well as an increase
in the economy's capability of providing these goods and
services.

     1.  Employment

     Theoretically,  as employment increases, production will
presumably increase until diminishing returns begin to have an
affect on markets, and therefore, on production.   The employment
level is a direct measure of growth,  only if the stock of natural
resources and capital,  as well as the level of technology are
held constant.  Technological change has its impact primarily on
the efficiency with which factors of production are used.
                                15

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     Employment data would be a more accurate growth indicator
than population data, since higher levels of employment reflect
economic growth and, more specifically, reflect rises in
pollution-generating activity levels.  However, employment
figures alone would not be convenient measures of the efficiency
with which labor is being used in production.  If technological
improvement occurs, more output can be produced with the same
quantity of labor, holding all other factors constant;
employment, for instance, could feasibly remain constant, while
the real gross national product (GNP) increases as a result of
technological improvements. The employment level alone is
therefore not an effective growth indicator in most cases.

     2.  Earnings

    , A measure of earnings, rather- than employment data, would
better reflect the efficiency with which labor has been used in
production.  Real earnings data are thus preferred to employment
figures for an industry, because earnings data capture
productivity improvements that are not apparent from employment
trends.  As an example of the difference between using earnings
and employment as the basis for projections, the BEA earnings
projections for the Texas chemical industry show an expected
increase in earnings of $3.16 billion to $3.65 billion from 1988
to 2000 — an increase of 15.5 percent over that period.
Employment for this industry/state combination, on the other
hand,  is only expected to increase by 2.7 percent over this time
period.

     3.  Value Added

     Similarly, value added would be a more accurate growth
indicator for industry because it captures factor substitution.
By definition, value added is a measure of factor costs incurred
during production.  Consider the following example (Branson,
1972):  The manufacture of a $12,500 car requires $11,000 worth
of steel,  which in turn requires $2,500 of coal and $7,500 of
iron to manufacture.  The mines sell $10,000 worth of output to
the steel firm, which adds $1,000 in capital and labor costs to
produce $11,000 of steel.  The auto manufacturer adds another
$1,000 to make an auto for $12,000,  and the dealer adds $500 in
services to sell at $12,500 to the customer.  (In this example,
each producer adds value to the final product.)  Total value
added is $10,000 by the mines, $1,000 each by the steel and auto
manufacturers, and $500 by the dealer,  for a total cost of
$12,500.  The price of the final output reflects the value of
each input, or the total value added.

     Consider the steel firm that bought $10,000 of output from
the mines.   The $1,000 of capital and labor costs that were added
also represent the firm's income after selling $11,000 of steel
to the auto manufacturer.  This $1,000 income figure is then used
to pay the firm's factors of production.  For each firm in this
example, the sum of the value added equals the firm's income.


                                16

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Hence, value added is defined as the value of a product sold by a
firm less the value of the goods purchased and used by the firm
to produce the product, and equal to the revenue which can be
used for wages, rent, interest, and profits.  The sum of each
firm's income in this simple example equals $12,500 ($10,000 for
mines, $1,000 for steel firm, etc.), which is also equal to total
value added and is reflected on the income side of GNP.  The
national income figure in total GNP is both a measure of
production and a measure of money income.  It represents the
factor costs of current output and the money earned by the
factors of production.  Used as a growth indicator, value added
would therefore encompass substitution among factors of
production, and would indirectly reflect technological change.
Data representing total value added ($2,500 in this case) are
reflected in the national income figure of GNP, since the sum of
all incomes (wages, interest, rent, and profit) is equal to the
total value added and, therefore, to the total (final) product.

     The periodic Census of Manufactures is a source of published
data on value added.  This survey is performed by the U.S.
Department of Commerce, Bureau of the Census.

     4.  Product Output

     Finally,  the most direct indicator of future emissions
activity is product output.  All four of the factors mentioned
above, employment, resource availability, capital growth, and
technology, are directly related to product output level.  Output
is a good indicator of the prevailing employment situation, as
well as of the resources and capital available to producers.  The
actual output level is determined by the efficiency with which
these resources are being used, which is in turn a reflection of
technological change.  Population changes should also be taken
into account when using product output totals, since product
output per capita is the most meaningful growth indicator. Any
regional projections of future product would thus be preferable
to any of the above indicators, if it is available.

     For the purposes of preparing industrial emission
projections for a State implementation Plaa, it is expected that,
at a minimum/  earnings projections would be used.  Real earnings
data are available for all states at the two-digit standard
Industrial Classification (SIC) level from the BEA.  Data on
value added or projected product outputs should be used where
available,
     B. REGIONAL PROJECTIONS USING BEA DATA

     As stated at the beginning of 'this chapter,  the U.S.
Department of Commerce's BEA data on Regional Projections to 2040
provide a useful set of regional growth data that EPA recommends
for use in preparing emission projections.  The first volume
(BEA, 1990a) presents projections to the year 2040 of economic
                                17

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activity and population for the nation and the states.  The
second and third volumes  (BEA, 1990b; 1990c) present projections
for metropolitan statistical areas  (MSAs) and BEA economic areas,
respectively.  Table III.l shows the level of detail of reporting
for states and how it differs from that available for MSAs and
BEA Economic Areas;  Projections are presented for population in
three age groups, by personal income (classified by major income
component), and by employment and earnings, each of which is
presented for 57 industrial groups.  Projections are available
for 1995, 2000, 2005, 2010, 2020, and 2040; historical data are
available for 1973, 1979, 1983, and 1988.  BEA data are available
in either report or machine-readable form.  [Hard copy reports
are for sale by the Superintendent of Documents, U.S. Government
Printing Office, Washington, DC  20402.]

     A new set of BEA regional projections is published every
five years.  The projections assume the continuance of past
economic relationships and assume no major policy changes.  They
are neither goals for, nor limits on, future economic activity in
any region or state.  Further, they are not an assessment of the
probable success or failure of any regional development program
established by or proposed for a state.

     The methods used by the BEA to prepare their projections are
informative and are therefore summarized below.  A more detailed
treatment of the same information can be found in the BEA
published reports.  The BEA projections were made in two major
steps: first for the. nation and then for the states.  In the
first major step, national long-term projections were developed
for 1995, 2000, 2005, 2010, 2020, and 2040.  (The short-term
projections are of most interest in preparing SIP emission
projections.)  GNP was projected based on projections of
population,  labor force, employment, and GNP per employee.  The
population projections were based mainly on the work of the U.S.
Census Bureau, and the labor force projections were based mainly
on the work of the Bureau of Labor Statistics (BLS).  The GNP
projections,  for the most part,  were the basis for the derivation
of other national measures, including total personal income by
component and both employment and earnings by industry.  For
1995,  alternative national projections of total personal income
by component, and of both employment and earnings by industry
were derived by totaling 1995 econometric projections for the
states.  These sum-of-state econometric projections then were
used as part of the review process to determine the long-term
national projections for 1995.

     In the second major step, state projections of employment
and earnings by industry,  population,  and total personal income
by component were made within the framework of the corresponding
projected national totals.  First,  long-term state projections
for 1995, 2000, 2005,  and 2010 were made,  based on historical
economic relationships within each state between basic industries
(those that mainly serve national markets)  and service industries
(those that mainly serve local markets).  In some cases,  the
                               18

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                               Table IH.l

              Industrial Groupings for the BEA Regional Projections
Industries projected for MSA's and BEA economic areas
Farm
Agricultural services, forestry, fisheries, and other
Mining




Construction
Manufacturing
Nondurable goods










Durable goods







Industries projected for States and the Nation
Farm
Agricultural services, forestry, fisheries, and other1
Mining
Coalmining •
Oil and gas extraction
Metal mining
Noometallic minerals, except fuels
Construction
Manufacturing
Nondurable goods
Food and kindred products
Tobacco manufactures
Textile mill products
Apparel and other textile products
Paper and allied products
Printing and publishing
Chemicals and allied products
Petroleum and coal products
Rubber and miscellaneous plastic products
Leather and leather products
Durable goods
Lumber and wood products
Furniture and fixtures
Stone, clay, and glass products
Primary metal industries
Fabricated metal products
Machinery, except electrical
Electric and electronic equipment
1972 SIC
code
01.02
07.08.09

11.12
13
10
14
15,16,17


20
21
22
23
26
27
28
29
30
31

24
25
32
33
34
35
36
1"Other" refers to U. S. residents employed by international  organizations
 and foreign embassies and consulates located in the United States.
                                   19

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            Table III.I continued



Industrial Groupings for the BEA Regional Projections
Industries projected for MSA's and BEA economic areas




Transportation and public utilities









Wholesale trade
Retail trade
Finance, insurance, and real estate




Services








Industries projected for States and the Nation
»
Transportation nqiitpnvnt, pw-liirting mnfrr vrhir\e$

Motor vehicles and equipment
Instruments and related products


Transportation and public utilities
Railroad transportation
Trucking and warehousing
Local and interurban passenger transit
Transportation by air
Pipelines, except natural gas
Transportation services
Water transportation
Communication
Electric, gas, and sanitary services
Wholesale trade
Retail trade
Finance, insurance, and real estate
Banking and credit agencies
Holding companies and investment services
Insurance
Real estate
Services
Hotels and other lodging places
Personal services
Business and miscellaneous repair services
Auto repair, services, and garages
Amusement and recreation services and motion pictures
Private households
Health services
Legal services
1972 SIC
code
37 except
371
.371
38
39

40
42
41
45
46
47
44
48
49
50.51
52-59

60,61
62,67
63,64
65.66

70
72
73.76
75
78.79
88
80
81
                      20

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            Table ffl.1 continued



Industrial Groupings for the BEA Regional Projections
Industries projected for MSA'i and BEA economic areas



Government and government enterprises
Federal, civilian
Federal, military
State and local
'Industries projected for .States and the Nation
Educational services
Social services and membership organizations
Miscellaneous professional services
Government and government enterprises
Federal, civilian
Federal, military
State and local
1972 SIC
code
82
83,86
84,89




                     21

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long-term  state projections to 2010 were modified to be
consistent with the state economic projections for 1995.

     In each state, employment in each industry was projected
according  to one of two sets of criteria, depending on whether
the industry was classified as basic or service.  Basic
industries are those that make products that are generally
exportable out of a state.  Because of the potentially broad
market for such products, it was assumed that each state competes
for a share of the national market of each basic industry.
Accordingly, employment in each basic industry in each state was
projected  on the basis of the historical trend of the state's
share of employment in that industry on a national level.  The
projections of basic-industry employment reflected the assumption
that the factors affecting a state's employment share in the past
(for example, relative wage rates, access to inputs and markets)
will continue to affect it in the future, but less strongly, so
that in all cases the rate of change in employment share slows.
Thus, each state's share of each basic industry was assumed to
change at -a decelerating rate toward a long-term equilibrium.

     Service industries are those that make products that, in
general, satisfy only local demand.  It was assumed that, in each
state, employment in each service industry is determined by the
level of local demand, which,  in turn, depends on the overall
size of the economic base.  Thus, in each state, service industry
employment was determined by the share of the national market
accounted  for by the .state's basic industries.  Projections of
employment in each service industry were tied to basic-industry
employment by means of the service industry location quotient,
that is, the ratio of a service industry's share of total
employment in a given state to that industry's share of total
national employment.

     Projections of service industry employment location
quotients were based on historical trends for each industry.  In
most cases, the result was convergence toward unity;  convergence
is consistent with the assumption that,  in the long term, the
service components of state economies will become similar to one
another.   In cases where a location quotient was diverging from
unity over time,  the historical trend generally was damped or
reversed in the projection period.

     It was necessary to categorize each of the 57 industries for
which projections were prepared as either basic or service
industries.  While basic industries are primarily dependent on
national demand,  and service industries on local demand,  it is
important to point out that each basic industry in a state is
impacted by,  and has an impact on, other industries in the state.
Thus,  basic industries are seldom oriented exclusively toward the
national economy.   Similarly,  service industries do not
necessarily provide to only local residents and businesses.  In
short,  a local element exists  in most basic industries,  and a
potential  (if not actual)  export element exists in most service
                                22

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industries.  Because it was not feasible to classify each
industry as part-basic and part-service, a state-specific
basic/service dichotomy of the 57 industries was made.  This
dichotomy is shown in Table III.2.

     Long-term projections to 2010 of state earnings by industry
were made in three steps.  First, the historical trend in state
earnings per employee in an industry was extended as a percentage
of national earnings per employee in the corresponding industry.
Second, this measure was multiplied by national earnings per
employee in the industry.  Third, this product was multiplied by
projected state employment in the industry to yield projected
state earnings in the industry.
     C. POINT SOURCES
sources, btheir t3mn using B£A factors (see previoue section) , is
to obtadn ,in£ ormation jon «** individual facility basis* "'""This type
of projection information can be obtained directly through
contacts with plant personnel and through the use of survey
questionnaires.  Questionnaires can be sent out solely to solicit
projection plans, or can be integrated into the periodic update
procedures employed to update the emission inventory to 1990 or
the permits system.  In most situations, however, this
information will not be available for every point source, so
other methods must be employed.

     For some large point sources, projection information may be
available for most, but not all, sources within the given
category.  For example, 10 paint manufacturing plants may operate
in the area of interest, but successful contacts have been made
with only 8 plants.  A reasonable approach would be to evaluate
the growth trends for the eight plants and apply the resulting
average growth trend to the other two plants.

     For smaller point sources, obtaining projection information
for each plant may not be feasible (or desirable) .   In these
cases, the rate of activity growth is best estimated via a
surrogate activity indicator.

     Before plans are adopted for extensive surveying of local
facilities,  areas should be aware that reliance on industry -
(plant) specific forecasts has some pitfalls.  Sources do not
want to give their competitors information on projected
activities,  and will not .include future expansion plans until the
proper feasibility studies have been performed.  Therefore, B£A
recommends that point source survey approaches be used only when
there is a dominant industry in an area whose emission growth is
not likely to be captured in. regional projections/  and where
there is a reasonable expectation that significant growth or
decline may occur.
                                23

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                                         TaHeHI.2
                                 BEA Regional Projections
                             Basic/Service Classification of Industries
vv4^' £ \
Farm
Agricultural Services, Forestry, Fisheries, and other

'<• » .•> 	 v ^° ^%
Always Basic
Always Basic
Mining:
Coal Mining
Oil and Gas Extraction
Metal Mining
Nonmetallic Minerals, except Fuels
Construction
Always Basic
• n _ ~
n
*
Always Service
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
*
Always Basic
n
n
*
Always Basic
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, Clay, and Glass Products
Instruments and Related Products
Miscellaneous Manufacturing Industries
Always Basic
M
n
n
n
n
n
n
n
n
n
Basic only if location quotient exceeds a threshold value.
                                              24

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                                 Table III.2  (continued)
Transportation and Public Utilities
Railroad Transportation
Trucking and Warehousing
Water Transportation
Local and Interurban Passenger Transit
Air Transportation
Pipelines, except Natural Gas
Transportation Services
Communication
Electric, Gas, and Sanitary Services
Wholesale Trade
Retail Trade
Always Basic
*
Always Basic
*
Always Basic
*
*
*
Finance, Insurance, and Real Estate
Banking and Credit Agencies
Holding Companies and Investment Services
Insurance
Real Estate
*
Services
Hotels and other Lodging Places
Personal Services
Private Households
Business and miscellaneous Repair Services
Auto Repair, Services, and Garages
Amusements, Recreation Services, and Movie Theaters
Health Services
Legal Services
Educational Services
Social Services and Membership Organizations
Miscellaneous Professional Services
*
Always Service
*
Government and Government Enterprises
Federal, Civilian
Federal, Military
State and Local
* •
Always Basic
Always Service
* Basic only if location quotient exceeds a threshold value.
                                              25

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     It is expected that base year emission inventory point
source records to be used in emission projections will include
SIC codes for each plant or process.  This is .important, because
almost any activity growth indicatprs will be on an industrial
category  (SIC) basis.  Published lists p£ Aerametric Information
ketrieYal^J^fism/^Am^) Facility subsystem1 source ciassif icafcio»
Codes (SCCs) are organized by SIC code in order to facilitate the
                                         tfce SCC 10 known  (EPA/
             o
        Thereof ore, no default SCC-SIC matches are provided for
point sources in this report, but are available in AFSEF.


     D. AREA SOURCES

     As with point sources, area source projections can be made
     nCocSi^^                                      is^owth
indicators, such as BEA7ATo"'apprbxiiiiiait'e'"th'e'"rlLse or fall in
expected activity.  The most commonly used surrogate growth
indicators are those parameters typically projected by local MPOs
such as population, housing, land use, and employment .
Regardless of the growth indicator employed, the calculation is
the same:  the ratio of the value of the growth indicator in the
projection year to its value in the base year is multiplied by
the area source activity level in the base year to yield the
projection year activity level.

     A major difference between making area source projections
for the basic, county-wide inventory and for the detailed,
photochemical inventory is that, in the latter, emission
estimates must be resolved at the grid-cell level.  This adds a
dimension of complexity to the projection effort, as changing
growth patterns may require that different apportioning factors
be determined for the projection years.  Fortunately, in most
large urban areas where photochemical models are employed, the
local MPO will be. able to provide land use maps, as well as
detailed zonal projections of employment, population, etc., for
future years.  Hence, these projections can be used directly, as
described above, to determine changes in spatial emission
patterns.

     If the surrogate indicators used for apportioning certain
area source emissions are not projected at a subcounty level,
engineering judgment must be used to decide whether spatial.
distributions of various activities will change enough to warrant
the effort of identifying new patterns.  Changes may be warranted
in rapidly growing areas for the more important area source
emitters.  For regions where little growth is expected, and
especially for minor area sources, the same apportioning factors
can be used in baseline and projection inventories.

     Table II 1.3 summarizes preferred growth indicators for each
major area source category.  Potential information sources are
also noted on the table,
                                26

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                 Table III.3
Growth Indicators For Projecting Emissions For
            Area Source Categories
Source Category
Gasoline Marketing
Dry Cleaning
Degreasing (Cold Cleaning)
Architectural Surface Coating
Automobile Refinishing
Small Industrial Surface Coating
Graphic Arts
Asphalt Use - Paving
Asphalt Use - Roofing
Pesticide applications
Commercial/Consumer Solvent
Use
Publicly Owned Treatment Works
(POTWs)
Hazardous Waste Treatment,
Storage and Disposal Facilities
(TSDFs)
Municipal Solid Waste Landfills
Residential Fuel Combustion
Commercial/ Institutional Fuel
Combustion
Industrial Fuel Combustion
Aircraft (Commercial and
General)
Aircraft, Military
Railroads
Ocean-going and River Cargo
Vessels
Vessels, small pleasure craft
Off-Highway Motorcycles
Agricultural Equipment
Construction Equipment
Industrial equipment
Growth Indicators
projected gasoline consumption
population; retail service
employment
industrial employment
population or residential
dwelling units
industrial employment
industrial employment
population
consult industry
industrial employment;
construction employment
historical trends in agricultural
operations
population
site-specific information
state planning forecasts
state waste disposal plan
residential housing units or
population
commercial/ institutional
employment; population
industrial employment (SIC 10-
14, 50-51); or industrial land
use
site-specific forecasts
site-specific forecasts
revenue ton-miles
cargo tonnage
population
population
agricultural land use;
agricultural employment
industry growth (SIC Code 16)
Industrial employment (SIC
codes 10-14, 20-39, 50-51) or
industrial land use area
Information Sources
MOBILE4 fuel consumption model
solvent suppliers; trade associations
trade associations
local MPO
BEA
BEA
state planning agencies; local MPO
consult industry
local industry representatives
state department of agriculture; local
MPO
local MPO; state planning agencies
state planning agencies
state planning agencies; local MPO;
local MPO; state planning agencies
local MPO
local MPO; land use map
projections
local MPO; land use projections;
state planning agencies
local airport authority and
commercial carriers
local airport authorities; appropriate
military agencies
American Association of Railroads
and local carriers
local port authorities; U.S. Maritime
Administration; U.S. Army Corps of
Engineers
local MPO
local MPO
local MPO; Census of Agriculture
local MPO
local MPO
                     27

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Table III.3 (continued)
Source Category
Lawn and Garden Equipment
On-site Incineration
Open Burning
Fires: Managed Burning,
Agricultural Field' Burning, Frost
Control (Orchard Heaters)
Forest Wildfires
Structural Fires
Growth Indicators
single-unit housing
based on information gathered
from local regulatory agencies
based on information gathered
from local regulatory agencies
areas where these activities
occur
historical average
population
Information Sources
local MPO
local regulating agencies and MPO;
state planning agencies
local agencies; state planning
agencies; local MPO
U.S. Forelst Service, state
agricultural extension office
local, state, and federal forest
management officials
local MPO; state planning agencies
         28

-------
     E. MOBILE  SOURCES

     1. Highway Vehicles

        a. Travel Demand Forecasting

     Information on techniques that are acceptable to EPA for
estimating future changes in highway vehicle activity can be
found in a number of recent or planned EPA publications.  These
include the Sec. 187 vehicle miles traveled  (VMT) guidance, the
General Preamble for Title I of the CAAA, which is scheduled to
be published in the fall of 1991, and Sec. 1-0.8 transportation
control measure effectiveness information documents.  In
addition, by November 1991, areas can expect further EPA guidance
for projecting  VMT in areas where projections are needed (i.e.,
ozone nonattainment areas that may be required to perform more
sophisticated analyses than the situations covered by the Sec.
187 VMT guidance) .
         ^ preferred method fox performing
use a validated zonal -based travel demand model.;  SUcit
required by £m guidance *#hen making 'projection^fceyon
-------
to ofctala £^~&wxwte"ot-it&                           " "~   "~
     For areas that do not currently have a validated travel
demand model, short term VMT projections may be based on the
Federal Highway Administration's Highway Performance Monitoring
System  (HPMS) (U.S. DOT, 1987).  Also, EPA guidance allows the
states to use any reasonable method to project VMT growth outside
the domain of the travel demand model and/or HPMS reporting area.

     HPMS was developed in the 1970s for monitoring highway
conditions, and is a continuing data base that can be .used to
determine future needs .  Data are submitted annually by the
states  (via their highway agencies) according to roadway
functional class.  HPMS is of interest to EPA because it will be
the basis for estimating base year VMT and then for tracking
historical changes in VMT with time.

     Areas that only need to project VMT through 1995 or 1996 are
allowed to use a simple, historically based extrapolation method,
if a better method is not locally available.  Because, in
general, economic factors influence VMT,  areas making projections
beyond 1995 or 1996 should include economic variables in their
land use and transportation network travel demand models.

     b. Trend Procedures

     One example of an acceptable procedure for Estimating future
year VMT, in situations for which travel demand models are not
available or required (such as nonattainment area rural fringes
not covered by HPMS or a network model) ,  is to apply a trend
projection method.  This can be done by quantifying road mileage
and associated VMT (stratified by county,  rural/urban area,  and
roadway functional class) ,  and using the relationship between
road mileage and VMT for historical years to estimate future year
VMT.  The hypothesis underlying this technique is that for each
roadway functional class within a specified geographical area
that historical trends reasonably represent short-range future
growth .

     A more detailed description of this trend projection method
follows.  The first step is to estimate average annual traffic
growth rates for the HPMS classified system.  To do this,
available HPMS sample panel data should be employed to estimate
average annual traffic growth rates by:

  . • County
   • Rural/urban designation/sample site
   • Functional class
                               30

-------
     Roadway  functional classes are defined as follows:

          Rural                    Urban

          Interstate               Interstate
          Other  Principal Arterial Other Freeways and Expwys
          Minor  Arterial           Other 'Principal Arterial
          Major  Collector          Minor Arterial
          Minor  Collector          Collector
          Local                    Local

 [Readers interested in more details about roadway, functional
 classifications  should consult the Highway Capacity Manual
 (1985).]

     Growth rates should be estimated using a statistically sound
 procedure to  avoid biases that could result from the" higher
 sampling rates in HPMS for higher volume facilities.  A procedure
 that could be used to estimate growth rates, with or without
 expanded samples  (samples in addition to those normally used in
 HPMS reporting), is as follows:

     1. Aggregate earlier year (1985 through 1990) mileage by
        category.

     2. Aggregate earlier year (1985 through 1990) VMT by
        category.

     3. Compute historical VMT per mile in each category from
        step  1 and 2 results.

     4. Compute VMT growth rates using an ordinary least squares
        linear regression.

     The second step,  after the average annual HPMS growth rates
have been calculated,  is to develop traffic volume growth rates
 for the local street system, which is not covered by HPMS.  It is
 recommended that areas use sample data from the local traffic
counting program to estimate average annual traffic growth rates
by county,  municipal/rural designation,  central business
district/inner city/suburbs (for municipal streets), and
major/minor local street.   It may be difficult to collect
sufficient samples from within the nonattainment area.  (Data
 from similar  counties within the state may be used.)  The exact
procedure will depend on data availability.

     Step three is to estimate base year VMT per mile for the
HPMS classified system.  To do this,  base year VMT per mile can
be obtained for each category from sample HPMS data.  To ensure
that the procedure being used is statistically sound,  comparisons
should be made with national estimates by urban area size group.
                                31

-------
     For  local  street VMT per mile estimates, it is important
that the  samples used represent the range of volumes on local
streets.

     Step four  is to estimate base and future year road mileage.
Base year mileage for the HPMS classified system can be obtained
from HPMS.  Generally, unless additions a-re planned, future year
road mileage  is the same.  Base year mileage in each local system
category  should be obtained from municipalities.  Significant
additions to  this mileage can be expected in the future for
suburban  municipal streets, and possibly rural streets.
Subtractions  may be needed in cases where local streets are
upgraded  to higher functional classifications.

     The  final step is estimating future VMT.  Base year VMT is
estimated by  category as base mileage * VMT per mile.  Growth in
VMT is estimated by category as future mileage * VMT per mile *
linear growth rate * number of years.  Future VMT is obtained by
category  as base VMT plus VMT growth.  Areawide future VMT is
estimated by  adding the totals of all categories.

     Tables III.4 and III.5, along with Figure III.l, provide a
practical example using the trend projection techniques described
above.  Table III.4 presents an example of historical data for
the five  most recent calendar years by roadway functional class.
Urban functional classes are listed.  Similar data should be
compiled  for  rural functional classes.  Table III.5 presents the
corresponding data for road mileage (by urban functional system).
The data  in these two tables are then used to compute the ratio
of annual  VMT to road mileage for each year and roadway
functional class.  Illustrative ratios computed from the data in
Tables III.4  and III.5 are shown in Figure III.l.

     Because  there is significant variability in the relationship
between VMT and road mileage from one area to another,  each
nonattainment area must use data specific to the geographic area
of interest when applying this procedure.

     c. Vehicle Registration Distributions

     EPA's mobile source emission factor models that pre-dated
MOBILE 4.1 contained default vehicle registration mixes (vehicle
registrations by model year).   These values are represented in
MOBILE4,   for  instance,  as registration distribution fractions.
Registration  distribution fractions represent the percentage of
vehicles  registered from each model year, making up the entire
vehicle fleet for a given calendar year and vehicle type.   These
registration  distributions are then used, in turn,  to develop
travel weighting fractions.  Travel weighting fractions are the
model year by model year percentages of total travel within each
vehicle type.

     For preparing 1990 (base year)  modeling inventories,  EPA is
requiring  that local registration data be used to establish
                               32

-------
                                                                  Table 111.4
                                         Annual Vehicle Miles of Travel  by Functional System
Roadway Functional Class
(Urban)
Interstate
Other Freeways
Other Prinipal Arterial
Minor Arterial
Collector
Local
Calendar Years
1985 .
27,176
25,542
28,433
17,130
6,995
6,994
1986
27,737
26,029
30,587
17,694
6,112
7,172
1987
28,650
28,142
36,245
22,941
8,137
4,300
1988
34,545
25,023
36,733
22,941
8,288
12,728
1989
36,699
27,666
37,590
23,244
8,664
18,113
1990
39,382
28,832
38,649
22,995
8,679
22,880
* Data are based on state highway agency estimates for the various functional systems.
* See Table IH.5 for corresponding road mileages.

-------
                                                      Table m.5
                                     Total Public Road Mileage by Functional System
Roadway Functional Class
(Urban)
Interstate
Other Freeways
Other Primary Arterial
Minor Arterial
Collector
Local
Calendar Years
1985
797
1,075
5,975
8,074
6,961
39,305
1986
800
1,081
5,999
7,886
7,213
39,934
1987
.804
1,200
5,402
7,483
6,767
40,858
1988
938
1,112
5,445
7,526
6,803
41,879
1989
955
1,158
5,593
7,832
7,238
42,123
1990
971
1,186
5,679
7,950
7,348
43,279
* See Table in.4 for corresponding travel estimates.

-------
U)
en
         •1
                                          Figure III.l

                Ratio of Annual VMT to Road Mileage by Roadway Functional Class
45



40



35



30



25



20



15 -



10 -



 5
               0
                1985
                                      Interstate
Other Freeways & Expwys
                                     Minor Arterial
                                -rr
                                              -*-
     1986
                                                                     Othefr Principal Arterial
                                    P
                                             Collector
                                                             -*-
                               1987           1988
                                      Year
1989
1990

-------
registration distributions for each vehicle type in MOBILE4.1.
 (Heavy-duty diesel vehicles may be an exception because so much
of heavy-duty diesel truck travel is long haul traffic, and local
registrations by county or MSA may not be an accurate, or
statistically significant, indicator of travel in an area.
National distributions may be better for HDDVs.)  Note that
MOBILE4.1 assumes that registration distributions reflect the
vehicle population operating on July 1.  Care should be taken to
remove duplicate vehicles from the registration data in compiling
the registration distribution.  R.L. Polk, Inc. provides this
service commercially.

     Table III.6 illustrates a methodology that may be followed
for projecting vehicle registration fractions from a 1990 base
year for input into the MOBILE emission factor model.  This
analysis, which is amenable to using a spreadsheet, shows how a
1996 ozone .(July) projection for light-duty gasoline vehicles  .
would be made for a sample area.  Parallel methods may be used
for other vehicle types or other projection years.  The
information in the box below indicates the most important
information needed for estimating future vehicle registration
distributions.
               INFORMATION NEEDED FOR REGISTRATION
                          DISTRIBUTIONS

      1990 vehicle registrations by model year (derived from
      local data)
      January 1 or July 1 survival rates by model year
      An estimate of post-1990 model year vehicle
      registrations
     The first column (A) of Table III.6 shows the model years
included in the 1990 calendar year registration distribution.
(Note that registration data from 25 model years should be used
for MOBILE4.1 and its successors, while MOBILE4 required the use
of only 20 model years.) Column B shows the number of vehicles
registered on July 1, 1990, by model year, which would have been
input to MOBILE4.1 to produce a 1990 inventory.  These should be
local registration data, rather than the default registration
data often used in developing inventories for previous base
years.  Information on registration by model year may be obtained
from the state's Department of Motor Vehicles.  The age of
vehicles from each model year,  as of July 1, 1990,  is listed in
column C.

     Data on vehicle survival rates are needed to estimate the
number of vehicles registered in 1990 that will still be in
operation in the projection year.  The survival rate is defined
as the probability that a vehicle will be in operation at any
given year of age.  In contrast, the scrappage rate is defined as
the probability that a vehicle that has reached a given age will
                                36

-------
                                                  Table 111.6

                  Sample Projection of Car Registration Fractions from a 1990 Base Year
OJ
-o
Passenger
Car Vehicle July 1
Model Registrations Age Survival
Year 7/1/90 7/1/90 Rate
1990 7,875 1 0.9967
1989 10,500 2 0.9906
1988 10,303 3 0.9813
1987 10,303 4 0.9674
1986 10,489 5 0.9470
1985 10,162 6 0.9176
1984 9,870 7 0.8769
1983 7,178 8 0.8230
1982 6,592 9 0.7553
1981 6,901 10 0.6759
1980 6,843 11 0.5892
1979 7,508 . 12 0.5010
1978 6,761 13 0.4168
1977 5,492 14 0.3407
1976 3,733 15 0.2748
1975 2,193 16 0.2194
1974 2,120 17 0.1741
1973 1,669 18 0.1374
1972 1,259 19 0.1082,
1971 926 20 0.0850
1970 596 21 0.0667
1969 533 22 0.0522
1968 421 23 0.0409
1967 284 24 0.0320
1966* 4,491 25+ 0.0251
Total 135,001
Estimated Estimated Passenger
Survival Passenger Passenger Car
Vehicle Rate from Car Vehicle Car Registration
Age 7/1/90 to Registrations Model Age Registrations Fractions
7/1/96 7/1/96 7/1/96 Year 7/1/96 7/1/96 7/1/96
7 0.8799 9,327
8 0.8308 8,723
9 0.7697 7,930
10 0.6987 7,199
11 0.6222 6,526
12 0.5460 5,548
13 0.4753 4,691
14 0.4140 2,971
15 0.3638 2,398
16 0.3246 2,240
17 0.2954 2,021
18 0.2743 2,060
19 0.2595 1,755
20 0.2494 1 ,370
21 0.2426 906
22 0.2381 522
23 0.2351 498
24 0.2331 389


25+ 0.2318 1,973


1996 1 9,124 0.0690
1995 2 11,772 0.0891
1994 3 11,243 0.0851
1993 4 10,979 0.0831
1992 5 10,342 0.0783
1991 6 9,629 0.0729
1990 7 9,327 0.0706

1989 8 8,723 0.0660
1988 9 7,930 0.0600
1987 10 7,199 0.0545
1986 11 6,526 0.0494
1985 12 5,548 0.0420
1984 13 4,691 0.0355
1983 14 2,971 0.0225
1982 15 2,398 0.0181
1981 16 2,240 .0.0170
1980 17 2,021 0.0153
1979 18 2,060 0.0156
1978 19 .1,755 0.0133
1977 20 1,370 0.0104
1976 21 906 0.0069
1975 22 522 0.0040
1974 23 498 0.0038
1973 24 389 0.0029
. 1972+ 25+ 1,973 0.0149
69,047 132,136 1.0000
        .  A
B
D
H
K

-------
be  scrapped within  a year.  For the vehicle registration
projections described here, only survival rates are used.
Survival  rates  for  automobiles, all trucks, and light  trucks were
researched  by the Oak Ridge National Laboratory for vehicles from
0 to 25 years old  (Miaou, 1990) .  Survival rates will  change
somewhat  over time, as well as by area.  Factors influencing
these rates include climate, vehicle construction, and economic
conditions.  Because of these local differences, state or
regional  survival rates should be used if they are available, but
the derivation  and  source of these local rates must be thoroughly
documented.  One method of estimating local survival rates is to
track vehicle identification numbers through an operating I/M
program over the years the program has been in operation.  Such a
method, however, must allow for the transition of vehicles into
and out of  the  area.

     Since  the  car  model year begins October 1, rather than July
1,  the base survival rates must be adjusted to reflect the
survival  rates  on July 1.  The July survival rate for  a car of
age n (JSRn) can be calculated as  follows:
               JSRn = BSR^ - (BSRn.,  -  BSRJ * 0.75

The terms BSRn and BSRn_3 are the  base (October 1)  survival  rates
for vehicles of age n and n-1, respectively.  For a CO
nonattainment analysis,  0.25 should replace 0.75 in the equation
above.  Since the truck model year begins January 1, no
adjustment to the base survival rates needs to be made for a CO
nonattainment analysis, but the 0.75 in the equation above should
be replaced with 0.5 for an ozone nonattainment analysis.

     To determine the number of vehicles in a given model year
that have survived from 1990 to the projection year, given a 1990
registration distribution, the survival rate for a vehicle of age
n in the projection year should be divided by the survival rate
for a vehicle of age n-6.  (For projection years other than 1996,
replace 6 with the number of years from 1990 to the projection
year.)  For example, a 1987 model year car. will be 4 years old in
July 1990 and 10 years old in 1996, so the probability that the
car will survive from 1990 to 1996 is 0.6965/0:9712, or 71.7
percent.  The age of each pre-1991 model year car on July 1,
1996,  is listed in column E, while column F shows the July 1990
to 1996 survival rates.  The number of cars in each model year
surviving to the projection year was calculated in column G by
multiplying the survival rates of column F by the corresponding
1990 registrations shown in column B.

     The number of 1990 model year cars registered in 1996, as
shown in column G, is greater than the number of cars registered
in 1990, shown in column B.  This occurs because the entire 1990
model year fleet has not been sold and registered by July 1.
Therefore,  a projection of the total number of 1990 model year
cars should be made before multiplying by the 1990 to 1996
survival rate in column F.
                                38

-------
     When projecting the registration distribution to 1996, all
vehicles from the 1972 and earlier model years are aggregated in
the 25 year-or-older category.  The total number of 1990
registrations for 1972 and earlier model years should be added
together before multiplying by the July 1990 to 1996 survival
rate.  This aggregation is emphasized by the shading near the
bottom of the spreadsheet.

     The model years included in the July 1, 1996 vehicle
registration calculation are listed in column H, with the age of
each model year car listed in column I.  The shift from the 1990
base year to the 1996 projection year is illustrated with the
lines connecting columns G and H.

     The registrations of column G for the pre-1991 model years
are repeated in column J, and the registrations for the 1991
through 1996 model years are added to the top of column J.
Projections of future model year new vehicle registrations can be
made assuming that annual percentage increases in new vehicle
sales will reflect the local annual percentage increases in VMT
(generally, about 2-3 percent per year).

     The projections for this example indicate no increase in new
car registrations from 1989 to 1990, so the number of car
registrations for the 1989 model year in column B was divided by
the survival rate for a car of age 2 in column C and then
multiplied by the 1990 to 1996 survival rate for a vehicle aged 7
years in 1996 (from column F).  This gives the estimated
passenger car registrations for the 1990 model year in 1996 (in
column G).

     Once the local annual growth rates in new car registrations
have been established, the 1996 registrations for 1991 through
1996 model year cars can be estimated.  The following equation
can be used to calculate the number of registrations in 1996 for
these cars:

                Jn =  (1 + %growth/100)*Jn+1*(Dn/Dn+1) '

J and D in this equation refer to the columns in Table III.6,  n
is the vehicle age,  and %growth is the annual percentage increase
in new car registrations for the applicable model year.  The
final model year (1996 in this example) should be calculated in
the same way and then multiplied by 0.75 since only, three-
quarters of the 1996 model year cars are assumed to be registered
by July 1, 1996.  The registration fractions shown in column K,
which are the necessary inputs for the MOBILE emission factor
model, were calculated by dividing each model year's July 1996
registrations from column J by the July 1996 registration total
shown at the bottom of column J.
                                39

-------
      2. Aircraft

      Air  travel has  experienced strong growth in the past  several
years, and  that growth  is  expected to continue  for  the
foreseeable future.  As a  result, many existing airports are near
traffic capacity  and others will reach their capacity limits in
the near  future.  This  may cause air traffic at small feeder
airports  and regional hubs to grow, while current hubs experience
additional  congestion.  Increased congestion increases taxi/idle
times (and  emissions),  but expanded use of smaller  airports may
relieve some of this congestion.

      EPA  recommends  that major commercial airports  be queried
individually to determine  their specific growth, plans {if  any),
and suggests that thin  information be incorporated  in emission
projections.  It  is  not recommended that national trends in
aircraft  activity be used  in urban scale analyses because  growth
is likely to be site-specific.  For example, older, urban  area
airports  such as  Washington National are less likely to grow than
airports  with newly  expanded facilities such as Raleigh-Durham.

      Projections  of  increased passenger miles may not be a good
indicator of future  aircraft activity, as more  passengers may be
accommodated by adding  larger planes to the commercial fleet.
These larger planes  may be more efficient and cleaner burning
than  the  smaller.planes they replace.  Projections  of landings
and take  offs are needed.

      3. Railroads

      Potential growth in rail travel is a function  of many
different variables, including competition with the trucking
industry.   For any individual area, activity growth is related to
track density and expected operations.  The best source of
information on likely changes during the projection period is the
railroads themselves, either the companies that operate in the
metropolitan area* or through the American Association of
Ra'ilroa'dsf   T^e A^J--^^ Association of Railroads publishes
historical  fleet  statistics.  These are of interest for
projections  in cases where a short-term trend analysis is the
best  indicator of future railroad activity.

      [The latest  edition of Railroad Facts can be obtained by
contacting  the Information and Public Affairs Department of the
Association  of American Railroads,  50 F Street,  NW,  Washington,
DC, Telephone (202)639-2550.]

      4. Gasoline  Marketing

      Expected growth in gasoline marketing activity is closely
tied  to projected fuel  consumption.  A number of national fuel
consumption models have been developed over the years,  and the
most  recent  results  from those models can be used as indicators
of growth in  activity for  the variety of source types that
                                40

-------
constitute the gasoline marketing category.  EPA's Office of
Mobile Sources has its own fuel consumption model, and it is
designed to be compatible with MOBILE4.1 and MOBILES.  Table
III.7 lists the expected fleet fuel efficiency ratios by calendar
year for each gasoline vehicle class in MOBILE4.1, normalized to
1990.  Total fuel consumed by gasoline vehicles is the sum of
that consumed by each gasoline vehicle class.  That, in turn, is
the product of the number of vehicles in each class and the
average number of miles driven by those vehicles divided by the
average fuel economy (mpg)  of those vehicles.

     Forecast the amount of gasoline marketed by:

     a.   Estimating the amount of 1990 gasoline marketed by
          vehicle class from available state and local sales
          data.

     b.   Multiplying that  amount by the appropriate fleet fuel
          economy factors for the forecast year listed in Table
          III.7.  This product is the amount of gasoline that
          would be marketed in that year in the absence of any
          change in vehicle miles traveled (VMT).

     c.   Multiply the result obtained in (b) by. the anticipated
          change in VMT from 1990 to the forecast year expressed
          as a ratio of forecast year VMT/1990 VMT.  This product
          is the amount of  gasoline marketed that includes both
          fuel economy changes due to fleet turnover and changes
          in the total number of vehicle miles traveled in the
          area under consideration.
                               41

-------
                                             Table III.7

                                  MOBBLE4.1 Fuel Consumption Model
                       Normalized On-Road Fleet Gasoline Fuel Efficiency Ratios*

Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020

LDV
1.00
0.98
0.96
0.95
0.94
0.93
0.93
0.92
0.92'
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.92
0.92
0.92
0.92
0.92
0.92
0.92
0.92
0.92
0.92
0.92
0.92
0.93
0.93
0.93

LOT
1.00
0.99
0.97
0.96
0.95
0.95
0.94
0.94
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.94
0.94
0.94
0.94
0.94
0.94

2B-5
1.00
0.99
0.98
0.97
0.96
0.%
0.95
0.94
0.94
0.94
0.93
0.93
0.92
0.92
0.92
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.90
0.90
0.90
0.90
0.90
0.90
0.90
0.90
HDV**
6-8A
1.00
1.00
0.99
0.99
0.99
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.93
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98

8B
1.00
1.00
0.99
0.99
0.99
0.99
0.98
0.98
0.%
0.93
0.90
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales
No Sales

. LDV+LDT
1.00
0.98
0.97
0.%
0.95
0.94
0.94
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.94
0.94
0.94
0.94
0.94
0.94
0.94
0.94
0.94
0.95
0.95
0.95
0.95
0.95

HDV
1.00
0.99
0.97
0.96
0.95
0.95
0.94
0.93
0.93
0.92
0.92
0.91
0.91
0.91
0.90
0.90
0.90
0.90
0.90
0.89
0.89
0.89
0.89
0.89
0.89
0.89
0.89
0.89
0.89
0.89
0.89

All
1.00
0.98
0.97
0.%
0.95
0.94
0.94
0.94
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.94
0.94
0.94
0.94
0.94
0.94
0.94
0.94
0.95
0.95
0.95
0.95
0.95
0.95
0.95
*Fuel efficiency is expressed in gallons per mile. The ratio is unitless.

Note: As of this writing, there are several bills in Congress addressing the issue of Corporate Average Fuel
Economy (CAFE). Table ni.7 assumes that CAFE standards  do not change from current levels.  If Congress
increases CAFE requirements in the future, EPA will revise Table III.7 accordingly.

**Classes 2B-5 trucks weigh 8,500 to 19,500 Ibs, 6-8A are 19,501 to 50,000 Ibs, and 8B 55,001 Ibs or more.

SOURCE:  MOBOJB4.1 Fuel Consumption Model. August 12, 1991.
                                                  42

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 IV MEASURING THE EFFECTS OF CURRENT AND FUTURE CONTROLS
     This chapter describes how ozone and CO nonattainment areas
can include  the probable effects of current and future controls
on precursor emissions in their projections.  The information
presented here is organized by pollutant/(VPC, NOX,  and CO,  in
that order)  and by major emitting-source category for each.  The
focus of the chapter is on new control initiatives spurred by the
CAAA.  Because mobile source controls affect all three of the
pollutants of interest, they are discussed in a separate section.
     A. VOLATILE ORGANIC COMPOUNDS

     The discussion of CAAA requirements affecting VOC emissions
is organized according to the following:

      (1)  National stationary measures
      (2)  Motor vehicle measures
      (3)  Area-specific measures
      (4)  Discretionary measures

The first three types of measures are those considered mandatory
under the CAAA or other legislation, unlike discretionary
measures, which are elective, as explained below.

     National stationary measures are those that affect all
sources nationwide, whether or not they are located in
nonattainment areas.  Source categories affected by national
stationary measures in the CAAA or other legislation include the
following:

   • Hazardous Waste Treatment Storage and Disposal Facilities
      (TSDFs)
   • Municipal Landfills
   • Consumer/Commercial Solvents
   • Architectural Coatings
   • Marine Vessels (loading and unloading)

     In modeling of the above categories, it can be assumed that
VOC emission reductions from all of these categories except
consumer/commercial solvents will have occurred by 1995.
Consumer product rules are scheduled to be issued in four 2-year
intervals beginning in the period from 1994 to 1995, and ending
in the period from 2000 to 2001.

     Motor vehicle measures include a mix of national and area-
specific measures.  National measures (those that affect all
areas) include gasoline Reid Vapor Pressure (RVP) limits,
evaporative/running loss controls, tailpipe/extended useful life
standards, and onboard vapor recovery systems.  Area-specific
measures include stage II (service station) controls, fleet clean
                                43

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fuels programs, and reformulated gasoline.   (The only general
vehicle clean  fuels program mandated is for California only.)

     Reformulated gasoline is mandated in the nine cities with
the most severe ozone pollution beginning in 1995.  Those cities
are listed in  Table IV.1.  States can elect to have the
requirements apply in other cities.      '  •

     Reformulated gasoline will be required to reduce VOC and
toxic emissions by 15 percent by 1995.  Higher reductions (of 20
percent or more) are required by 2000.

     The fleet vehicle clean fuels program is designed to include
areas in serious, severe, and extreme ozone nonattainment with
populations of at least 250,000 and areas with a CO design value
greater than or equal to 16.0 ppm with a population of at least
250,000.  A list of the fleet clean fuels target areas are
included in Table IV. 1.  Clean fuel vehicle phase-in requirements
for fleets are as follows:

     Vehicle Type             MY1998    MY1999    MY2000

     LDVs and LDTs              30%       50%       70%
     HDTs                       50%       50%       50%

     (Standards that must be met by clean fuel vehicles are
listed in Sec.. 243 of the CAAA.)

     Area-specific measures include RACT for stationary sources
that emit at least 50 tons per year of VOC in serious ozone
nonattainment areas,  with the cutoff dropping to 25 tons in
severe nonattainment areas, and to 10 tons in extreme
nonattainment areas (Los Angeles).  Control technique guidelines
for VOC sources are to be issued for 11 stationary source
categories.  These new CTGs are to be applied in moderate,
serious, severe, and extreme ozone nonattainment areas.   Table
IV.2 lists the specific new CTGs that are expected as of this
writing.  Table IV.3 lists existing CTGs applied in ozone
nonattainment areas.   Table IV.4 lists VOC RACT controls applied
as listed above.  Enhanced inspection and maintenance programs
are also required in the CAAA for serious,  severe,  and extreme
ozone nonattainment areas.  Basic inspection and maintenance
(I/M)  is to be required in moderate ozone nonattainment  areas.

     The other area-specific measures are those for attainment
areas within the ozone transport region.   The ozone transport
region includes CT, DE,  ME, MD, MA,  NH,  NJ,  NY,  PA,  RI,  VT,  and
the Washington, DC CMSA.   Ozone transport region controls include
enhanced I/M (if the MSA population is 100,000 or more),  existing
and new CTGs,  RACT to greater than 50 tons per year VOC  sources,
and .a study to determine whether stage II vehicle refueling
controls should be required.
                                44

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                                    Table IV.l
                     CAAA Mandated Motor Vehicle Programs
Reformulated Gasoline Areas

1. Los Angeles, CA
2. New York, NY-NJ-CT
3. Chicago, IL-IN-WI
4. Houston, TX
5. Baltimore, MD
6. Milwaukee, WI
7. Philadelphia, PA-NJ-DE-MD
8. San Diego, CA
9. Hartford, CT
Clean Fuels Areas—Fleet Programs

      1. Atlanta, GA
      2. Fresno, CA
      3. Milwaukee^ WI
      4. Bakersfield, CA
      5. Baltimore, MD
      6. Baton Rouge, LA
      7. Beaumont, TX
      8. Chicago, IL-IN-WI
      9. El Paso, TX
      10. Greater Connecticut
      11. Houston, TX
      12. Los Angeles, CA
      13. Boston, MA-NH
      14. New York, NY-NJ-CT
      15. Philadelphia, PA-NJ-DE-MD
      16. Providence, RI
      17. Sacramento,  CA
      18. San Diego, CA
      19. Washington,  DC-MD-VA
      20. Denver, CO
      21. Springfield, MA
SOURCE: Environmental Protection Agency, Office of Mobile Sources
                                        45

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                                     Table IV.2

                 Proposed New Control Technique Guidelines (CTGs)
                                  Under the CAAA
1.     Synthetic Organic Chemical Manufacturing Industry (SOCMD Reactor Processes
2.     SOCMI Distillation Operations
3.     Plastic Parts (Business Machines) Coatings
4.     Plastic Parts Coatings (Other)
5.     Web Offset Lithography
6.     Autobody Refinishing
7.     Industrial Clean-Up Solvents
8.     Petroleum and Industrial Wastewater
9.     Wood Furniture Coating
10.    SOCMI Batch Processes
11.    Volatile Organic Liquid Storage Tanks
SOURCE: Environmental Protection Agency, Office of Air Quality Planning and Standards
                                          46

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                                          Table IV.3

                              Estimated Control Efficiencies of
                                   Existing CTG Controls
                                                                    Estimated
                                                                 VOC Emission
        Source Category	                              Reduction (%)
        Solvent metal cleaning                                          54%
        Printing and publishing                                         85
        Dry cleaning                                                    70
        Fixed roof crude tanks                                          98
        Fixed roof gasoline tanks                                        96
        EFR crude tanks          .                                      90
        EFR gasoline tanks                                             95
        Bulk gasoline terminals - splash loading                        91
        Bulk terminals — submerged, balanced                          87
        Bulk gasoline terminals — submerged                            79
        Service stations - stage I                                        95
        Petroleum refinery fugitives                                     69
        Petroleum refinery vacuum distillation                           100
        Rubber tire manufacture                                         83
        Green tire spray                                                90
        Automobile surface coating                                      88
        Beverage can surface coating                                    57
        Paper surface coating                                            78
        Degreasing                                                      35*
        Cutback asphalt                                                 100*
        Gasoline bulk terminals and plants.                              51*
        Pharmaceutical manufacture                                     37*
        Oil and natural gas production fields                             37*
        Service stations - stage I                                        76*
SOURCE:  Compiled from EPA, 1978, and the individual Control Technique Guideline Documents

Control efficiencies listed represent the mid-point of a range of control effectiveness. These can be adjusted upward
or downward to reflect State and local regulations or differences in source characteristics by area.

^Control efficiencies listed for these source categories are intended for application where these sources have been
inventoried as area sources. The 78 percent control efficiency listed for paper surface coating applies to both point
and area sources.  All other control efficiencies shown are designed to be applied to point sources.
                                              47

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                                       Table IV.4

                            Representative Stationary Source
                               VOC RACT Control Levels
                                                                 Estimated
                                                              VOC Emission
       Source Category	                        Reduction (%)

       Ethylene oxide manufacture                                    98%
       Phenol manufacture                                           98
       Terephthalic acid manufacture                                  98
       Acrylonitrile manufacture                                      98
       SOCMI fugitives                                              37
       Cellulose acetate manufacture                                  54
       Styrene-butadiene rubber manufacture                           70
       Polypropylene manufacture                                     98
       Polyethylene manufacture                                      98
       Ethylene manufacture                                          98
       Vegetable oil manufacture                                     42
       Carbon black manufacture                                     90
       Miscellaneous surface coating                                  90
       Coke ovens - door and topside leaks                            90
       Coke oven by-product plants                                   63
       Aircraft surface coating                                        79
       Whiskey fermentation - aging                                  85
       Charcoal manufacture                                          80
       Synthetic fiber manufacture                                     54
       Miscellaneous non-combustion                                 90
SOURCE: Battye et al., 1987

Control efficiencies listed represent the mid-point of a range of control effectiveness.  These can be adjusted upward
or downward to reflect State and local regulations or differences in source characteristics by area.
                                            48

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     Discretionary measures, as defined here, are measures  that
areas might  choose to undertake to supplement mandatory measures
 (described above).  Areas may chose additional measures in  the
interest of  reaching attainment or to meet progress requirements.
Depending on problem severity, ozone nonattainment areas must
attain the standards within 5, 10, 15, or 17 years  (20 years for
Los Angeles).  VOC emissions must be reduced by 3 percent per
year until the standard is attained.  For the purposes of
attainment demonstrations, discretionary measures are important
to identify  for areas not expected to meet the standard with
mandatory measures alone.

     Table IV.5 summarizes all of the above for VOC emission
related Title I and II requirements of the CAAA. Dates when each
of these measures are scheduled to start affecting VOC emissions
are also listed in this table.  [Appendix B of EPA's
"Implementation Strategy for the Clean Air Act Amendments of
1990" (U.S.  EPA, 1991a) shows timelines for Titles I through IV
of the Amendments.]

     Two parts of the nonattainment program that are difficult to
quantify, but which have an effect on future VOC emissions, are
offsets and  new source review.  Offsets differ for each category
(moderate, serious, etc.) of ozone nonattainment area.
Presumably,  offsets either act to restrict growth in
nonattainment areas, or they force new emitters to assist
existing facilities in achieving emission reductions.

     Title III of the CAAA calls for controls of many new toxic-
compound-emitting source categories.  Most of these controls will
affect VOC emissions.  From a modeling standpoint, the potential
reductions can be quantified by matching source categories  to be
regulated with AIRS Facility Subsystem SCCs.  The Emissions
Standards Division of OAQPS is responsible for developing a list
of potentially affected categories and associated emission
reductions.

     There are also potential VOC reductions that will be
observed at  companies that have agreed to make voluntary
reductions in their toxic emissions.  These agreements were made
before the CAAA were passed,  and are part of EPA's Early
Reduction Program, so it may be that reductions will be close in
magnitude to those that will now be required under Title III.
Each state agency with a nonattainment area needs to determine
whether there are firms in its area that are planning voluntary
reductions and what the timing of those reductions might be.
     B. OXIDES OF NITROGEN

     NOX emissions  are also affected by the CAAA.   Titles I
(Nonattainment), II (Motor Vehicles), and IV (Acid Rain) all come
in to play.  Title I requires RACT on major stationary-source NOX
emitters in moderate,  serious, severe, and extreme nonattainment
                                49

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                                     Table IV.5

                             CAAA Provisions Summary


Classification of O3 Nonattainment Areas and Deadlines

Classification                    Design Value                 Attainment Date

Marginal                        .121 -  .137 ppm                  1993
Moderate                        .138 -  .159                       1996
Serious                         .160-.179                       1999
Severe                          .180 -  .279                       2005 or 2007*
Extreme                         .280 and above                   2010

Motor Vehicles

  • Enhanced VM in serious, severe, and extreme nonattainment areas [before 1995]

  • Basic VM in moderate nonattainment areas [before 1995]

  • Stage n vehicle refueling controls in moderate, serious, severe and extreme nonattainment
       areas (if onboard is promulgated before Stage n, no new stage n in moderate areas)
       [before  1995]

  • Onboard vehicle vapor recovery systems [phase-in starting in  1996]

  • Improved evaporative test procedures [before 1995]

  • Gasoline volatility controls [before 1995]

  • New emission standards for LDVs and LDTs [phase-in starting at 40% in 1994, 80% in
       1995, and 100% in 1996]

  • Reformulated gasoline in 9 areas (> 0.18  ppm 03) [starting in  1995]

  • Fleet vehicle clean fuels programs in serious, severe, and extreme ozone nonattainment
      areas and CO areas with a design value of 16.0 ppm or more (>250,000 MSA
      population only) [starting in 1998 with phase-in to 2000]

  • California general vehicle clean fuels program [start at 150,000 vehicles in 1996, increase
      to 300,000 in 1999, more stringent standards starting in 2001]
                                         50

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                                Table IV.5 (continued)
Stationary Sources
   • National measures control hazardous waste Treatment Storage and Disposal Facilities
       (TSDF), architectural coating, commercial/consumer solvent, vessel loading and
       unloading, and landfill emissions [before 1995, except consumer solvents]

   • RACT for greater than 50 tpy emitters in serious, 25 tpy emitters in severe, and 10 tpy
       emitters in extreme nonattainment areas [before 1995]

   • 11 Control Technique Guidelines in moderate, serious, severe, and extreme ozone
       nonattainment areas [before 1995]

   • For consumer or commercial products, list categories that account for at least 80 percent
       of the VOC emissions.  The list will be divided into 4 groups for regulation.  Every 2
       years regulate one group [all implemented between 1995 and 2001].

Moderate, serious, severe and extreme ozone nonattainment areas must achieve 15 percent
VOC emission reductions net of growth and noncreditable emission reductions by 1996 and 3
percent per year thereafter until attaining.

Ozone transport region controls [before 1995] include enhanced I/M, existing and new CTGs,
RACT to 50 tpy VOC sources, RACT to 100 tpy for NOx sources, and Stage n vehicle
refueling [study only].
*Severe ozone nonattainment areas with a 1988 ozone design value between 0.190 and 0.280 ppm have an attainment
date of 2007.
                                          51

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areas, where  the  definition of major  source  is  the  same  as  it  is
for VOC emitters.   In addition, RACT  is required for  greater than
100 ton per year  NOX sources in ozone transport regions.  The
controls considered NOX RACT for prior CAA analyses, along with
estimated control efficiencies, are listed in Table IV.6.   There
are increasingly  stringent motor vehicle NOX emission standards
in Title II,  which  should provide significant reductions in
emissions for that  sector.  For example, thie 0.4  gram-per-mile
NOX emission standard for light-duty gas vehicles and light-duty
gas trucks begins to be phased in with 1994  model year vehicles,
and is fully  phased in by the 1996 model year.   Finally,  utility
NOX emissions are affected by Title IV provisions.

     1. Electric  utilities

     In addition  to limiting the amount of SO2 emitted by
electric utilities, Title IV of the CAAA also limits  the amount
of NOX emitted by electric utilities.   The overall targeted NOX
reduction from Title IV, in combination with other  provisions  of
the Act, is approximately 2 million tons from 1980  emission
levels in the 48  contiguous states and the District of Columbia.

     Unlike the SO2 control requirements of the CAAA,  NOX utility
emissions are not capped; the Act only imposes  emission  rate
limits based  on utility boiler type.

     When projecting electric utility NOX emissions from a 1990
base year inventory,. emission estimates from existing units,
planned units, and  new sources not yet in the planning stages
must all be compiled.  Calculating future emissions from existing
sources involves  determining:  (1) state-level  growth factor by
fuel type,  (2) future year unit-level capacity  factors,  and (3)
new NOX control  requirements  from the  CAAA,  as  well as any state-
or local-level control requirements.  Calculating future
emissions from planned units includes the following steps:  (1)
obtaining a listing of planned units,  their  capacities,  and start"
dates, (2)  determining the likely site for units  with
undesignated  locations,  and (3). determining  applicable defaults
for all of the unknown variables needed for  the NOX emission
calculation.   Finally,  to calculate NOX emissions from any
additional generation requirements within the state, the
following steps must be followed:  (1) determine  the amount of
additional generation needed that will not be supplied by
existing or planned units., (2)  determine the likely fuel mix to
be used,  and  (3) site the additional generation.  These  are
summarized in the chart on the page following Table IV.6.
                                52

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                               Table IV.6
                Stationary Source RACT Controls for NO,
Source type - Primary Fuel

Ind boiler-pulv. coal
Ind boiler-stoker
Ind boiler-residual oil
Ind boiler-distillate oil
Ind boiler-gas
1C engines-gas
1C engines-oil
Gas turbines-gas
Gas turbines-oil
Process heaters-gas
Process heaters-oil
      Estimated
RACT Control Technique

 Staged combustion air/LNB
 Low excess air
 Staged combustion air/LNB
 Low excess air/LNB
 Rue gas recirculation/LNB
 Change air to fuel ratio
 Change air to fuel ratio
 Water injection
 Water injection
 Staged combustion air
 Staged combustion air
   Emission
Reduction(%)

36%
21
42
36
31
30
30
70
70
45
45
SOURCE: Pechan, 1988.
                                .  53

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                       ELECTRIC UTILITY NOX
                       PROJECTIONS  SUMMARY

  1. Estimate  emissions from existing units:
    - determine  state-level growth  factors
    - estimate unit-level  future year capacity  factors
    - determine  unit-level NOX control requirements

  2. Estimate  emissions from planned units:
    - obtain  listing  of planned units
    - determine  most  likely siting  for undesignated units
    - determine  applicable unit-level NOX emission rates
       (and default  data)

  3. Estimate  emissions from generic units:
    - determine  amount of  additional generation needed  (if any)
    - estimate NOX emission rate
    - determine  siting for generic  units
     To project 1990 utility NOX emissions to a future year, the
expected growth in electricity generation at existing units  from
1990 to the projection year must be determined.  A state-level
growth factor can be calculated based on historical growth  in
generation at existing utility units in the state, or from
estimates provided by utilities within the state.  Growth factors
may differ for coal, oil, and gas-fired utility units.  These
growth factors should be multiplied by each unit's 1990 capacity
factor (the ratio of, a unit's actual 1990 generation to the
potential generation if operated for 8,760 hours per year),  to
produce a unit-specific capacity factor in the projection year.
If the calculated projection year capacity factor is greater than
0.80, 0.80 should be used as the projection year capacity factor,
unless the 1990 capacity factor also exceeds 0.80 (in which  case
the 1990 capacity factor should be used in the projection year).
(Capacity factors for utility units are rarely above 0.8.)   For
states with a growth factor of less than 1, the projection year
capacity factors will be less than the 1990 capacity factors.

     Once the future year capacity factors for each existing unit
have been calculated, the most stringent of the Federal, state,
and local NOX emission rate requirements  must be determined for
each unit.  The.NOx emission control  requirements of  Title IV of
the CAAA become effective for a given unit when that unit becomes
an "affected" SO2  unit.   Phase I  affected SO2 units are those
that must apply SO2 controls beginning in 1995.   These units,
which are specifically listed in the CAAA, are also listed in
Table A-2.  The NOX control requirements  (including  the
compliance dates for these affected units) are as follows:
                                54

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                              Controlled NOX
                              Emission Rate             Date of
     Boiler Type              (lb/106 Btu)    -          Compliance

     Tangentially-fired         0.45                     1/1/95
     Dry Bottom Wall-fired      0.50                     1/1/95
     All Other Boiler Types     1.00          •           1/1/97

          Using the emission rates listed above, the future year
     capacity factor, the capacity, and the heat rate  (the amount of
     energy needed to produce a given unit output) of a given unit,
     the projected NOX emissions can be calculated with the.following
     equation:


Future NOX   Controlled    Capacity    Future      Heat  Rate               i
Emissions  =  NOX Rate   *    (MW)    * Capacity  * (Btu/kWh)  *  4.38 * 10'6 Bti
(k tons/yr) (lb/106  Btu)                Factor

          The final term in this equation is a conversion factor that
     converts the units used for the variables in the equation to a
     resultant emissions figure in kilotons per year.  Units for the
     conversion factor are (kWh * k tons)/(MW * year * Ib).

          Beginning in 2000,  Phase II SO2  units  (all  utility  boilers
     not included in Phase I) become "affected."  Therefore,  the NOX
     control requirements listed above will apply to all Phase II S02
     units starting in the year 2000.  In Phase I and Phase II, if the
     current (1990)  NOX emission rate for  a  unit is already below that
     unit's control requirement, the 1990 emission rate should be
     used.

          Retirements of existing units must also be taken into
     consideration.   When information on the planned year of
     retirement for a specific unit is not available, an assumption of
     55 to 65 years in service is acceptable.   The higher figure has
     been used by EPA in a number of analyses of the CAAA to represent
     a "high emissions case"  for fossil fuel units, while 55 years has
     been used to depict a "low emissions case"  (ICF, 1990).

          After NOX  emissions from existing  units  have  been
     calculated,  the next step is to estimate NOX  emissions from
     planned or announced units.  Information on units that are
     expected to begin operation over the next 10 years are published
     annually in the "Inventory of Power Plants in the United States"
     (DOE, 1991). [This publication is available from the
     Superintendent  of Documents,  U.S. Government Printing Office --
     see Reference section of this document.]   The current listing of
     units projected to begin operation from 1990 to 1999 from Table
     21 of this publication is reproduced in Appendix A of this
     report.

          The NOX emission  rate  that  applies to  each  new unit depends
     on the start-up year and the fuel type, since the NOX  regulations


                                     55

-------
 that  apply  to  these  units will  either be  the current New  Source
 Performance Standard (NSPS) or  a more stringent NSPS,  revised by
 1994  as  set forth in the CAAA.  All NOX emission rate
 requirements from the CAAA  for  utility boilers are  listed in
 Table IV.7.  For  these  units, when no more detailed information
 is available,  a default capacity factor of 0.65 can be assumed
 for a baseload unit,  30 percent for an intermediate load  unit,
 and 10 percent for a peaking unit.  Default heat rates by unit
 technology  and fuel  type can be found in  EPRI's "Technical
 Assessment  Guide"  (EPRI, 1986).

      The information on announced units in the "Inventory of
 Power Plants in the  United  States"  (U.S.  DOE, 1990) includes the
 county that the unit will be located in,  if this information is
 known.   When it is necessary to site an undesignated unit at the
 county or MSA  level,  it can be  assumed that the maximum new unit
 generation  that would be sited  within a nonattainment  MSA would
 be used  to  compensate for units that were recently  retired in the
 MSA.   Any additional new units, that do not have a  county or MSA
 designation, can  be  assumed to  be sited outside of  any
 nonattainment  MSAs.

      The last  step that must be taken is  to determine  whether the
 generation  supplied  by  existing and announced units will  meet the
 state's  generation needs in the projection year.  The  total.
 projected generation demand could possibly be obtained from the
 public utility commission in the state, utilities located within
 the state,  or  a computer model  capable of making this  projection
 based on state-specific information.  The generation that will be
 supplied by existing and planned units in the projection  year
 must  then be compared with  the  projected  total generation demand
 from  in-state  utilities.  If projected demand exceeds  supply, the
 emissions from additional new units must  be accounted  for.

      The amount of additional generation  required to meet the
 electricity  demands  within  the  state in the projection year
 should be assumed  to be supplied by new "generic" units.   All new
 generating  units will be subject to the NSPS requirements.
 Unless this  demand, is expected  to be met  using a single fuel
 type,  the NSPS for coal, oil, and gas must be weighted together
 according to'the amount of  generation supplied by each fuel type
 in the projection  year  at existing and announced units.   This
 weighting should be  performed as follows:

 Proj.  Yr.    Proj.  Yr.       Proj. Yr.       Proj. Yr.
 Fuel-Wtd =  Coal Gen.*0.5 + Oil Gen. *0.3 + Gas Gen. *0.2
 NOX NSPS      Total  Generation from Existing + Announced Units

      In  the  above  equation, 0.5, 0.3, and 0.2 are the  NSPS
 requirements for coal,  oil, and gas, respectively,  in  lb/106 Btu .
 in the projection  year.  The projection-year coal,  oil, and gas
 generation are calculated by finding the  product of the overall
.capacity, the  future  capacity factor, and 8,760 hr/yr  for
 existing and planned units  in each primary fuel category.
                                56

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                                        Table IV.7
           CAA NO, Emission Limits for Utility Boilers for 2000 and Later
        Primary Fuel Type
           Natural Gas
               OU
      Coal, Oil, or Natural Gas
              Coal
      Coal, OU, or Natural Gas
        Subbituminous coal
   Bituminous or Anthracite Coal
      Coal, OU, or Natural Gas
     Coal, OU, or Natural Gas
     Coal, Oil, or Natural Gas
     Coal, Oil, or Natural Gas
Boiler Configuration
All Configurations
All Configurations
Tangentially-fired
All Configurations
Dry Bottom Wall-Tired
All Configurations
All Configurations
Wet Bottom Wall-fired
Cyclone
Cell Burner
All Configurations
Initial Year of
Operation
1983 and Later
1983 and Later
All Years
1994 and Later
All Years
1983 to 1993
1983 to 1993
All Years
All Years
All Years
All Years
NO, Emission
Limit
Qb/MMBtu)
0.201
0.301
0.452
0.503
0.502
0.501
0.601
l.OO4
1.00"
1.00"
l.OO4
Note:  If a boiler falls into more man one of the above categories, only the most stringent
emission limit applies.

SOURCES:
    1   40 CFR, Part 60, Subpart Da, New Source Performance Standards (NSPS).
    2   Clean Air Act Amendments of 1990.
    3   Assumed new NSPS resulting from requirements of CAAA of 1990 to revise NSPS for coal-fired
       utUity boilers.
    4   Assumed retrofit control level resulting from requirements of CAAA of  1990.
                                            57

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     Using this NOX emission rate,  the NOX  emissions  from the
 "generic" new units can be calculated, as  for the other  types of
 units, by substituting the generation required by generic units
 (in MWh) for the term capacity * future capacity factor  * 8,760
 in the equation given above for calculating future year NOX
 emissions, and using the same heat rate as .is assumed for
 announced units.  The same siting assumptions should be used for
 generic units as the one discussed above for the undesignated
 announced units.

     2. Non-Utility Generators                                   .

     Now electric utilities meet the demand for power not just by
 building new generating units, but also by buying power  from
 others.  It is therefore important to consider the potential new
 emissions from co-generators and independent power producers when
 performing emissions projections.  It is also important to
 determine whether any of the shortfall between projected
 electricity demand for a region and projected new utility unit
 construction will be filled by "purchased power." Any NOX
 emission projections should account for this source sector, and
 should ensure that new demand being met by these units be
 subtracted from that expected to be met by the utilities
 themselves.  From a modeling standpoint, the location of the
 source providing generation is very important.  If the co-
 generator or independent power source is located within the
 boundaries of the area being modeled, then the NOX  emissions from
 the source must be included.  On the other hand, if the source is
 located outside of the modeling boundaries, its NOX emissions
 should not be included.

     3. Industrial Sources

     The most straightforward method for estimating future
 industrial NOX  emissions  in  an area  is  to apply  the RACT-level
 controls noted in Table IV.6 to.the population of units above the
 applicable source-size cutoff for the nonattainment area.  Then,
 state-level,  2-digit SIC BEA earnings projections can be used to
 estimate growth in emissions to future years.  More complex
 analyses would include the effects of fuel prices on the
 decisions that plants with boilers make about whether to install
hardware to reduce emissions while continuing to burn the same
 fuel,  or whether to switch fuels to avoid incurring the hardware
 costs.  Decisions about how to fuel newly constructed units may
also be influenced by new RACT requirements.  This may make it
more likely that new units will be smaller (to avoid installing
 controls)  or that they will be sited outside the nonattainment
area boundaries.  Requirements for NOX  RACT controls  for  greater
 than 100 ton-per-year emitters in the Northeast Ozone Transport
Region probably eliminates concerns about siting outside
nonattainment area boundaries for that region since NOX RACT
 control requirements are uniform throughout this entire region,
 regardless of the attainment status.
                              .  58

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     C. CARBON MONOXIDE

     Future carbon monoxide emissions are affected by both the
Title I nonattainment provisions for CO nonattainment areas and
the motor vehicle related provisions in Title II.  CO
nonattainment areas are classified as either moderate or serious,
with serious areas being those with design values of 16.5 ppm and
above.  Primary standard attainment dates are December 1995 for
moderate areas, and December 2000 for serious areas.  Basic I/M
programs are required in moderate areas that do not already have
them.  Enhanced I/M programs are required for areas with a CO
design value greater than 12.7 ppm.  Oxygenated gasoline is
required in all CO nonattainment areas.  More specifically,
Sections 187(b)(3) and 211(m) together require that a state
containing a CO nonattainment area must require that, by November
15, 1992, fuel sold or supplied  (or offered for sale or supply)
within the larger of the Consolidated Metropolitan Statistical
Areas (CMSAs) or MSAs must contain 2.7 percent oxygen by weight
during the period of high CO concentrations.

     (Title II provisions affecting CO emissions include new
emission standards for light-duty trucks and cold temperature CO
standards.)

     In some CO nonattainment areas, wood burning stove emissions
contribute to CO ambient standard exceedances.  In 1988, the wood
stove NSPS was promulgated ("New Residential Wood Heaters" 53 FR
5860, 1988) .  Thus, new wood stoves manufactured after this date
will be much cleaner burning than previous ones.  AP-42 emission
factors for combustion in residential wood stoves show the
difference between Phase II unit (wood heaters meeting NSPS after
July 1,  1990) emission rates and those of conventional units
(U.S. EPA, 1990).  CO emission reductions of 70 to 80 percent are
expected for catalytic and pellet fired Phase II units.
Conventional versus Phase II unit emission factors are scheduled
for inclusion in AP-42, Supplement D (September, 1991) .

     There are also certain state and local regulations that
restrict growth in wood stove emissions that should also be taken
into account in CO emission projections.  For example,  the State
of Colorado regulations limit CO emissions to 200 g/h.

     D.  MOBILE SOURCES

     1.  Highway Vehicles

     EPA issued MOBILE4.1,  an updated version of its motor
vehicle emission factor model,  in July 1991.  States are required
to use MOBILE4.1 in determining 49-state and territories motor
vehicle emission factors for all base year emission inventories
under the CAAA,  adjusted base year inventories,  and CO projection
inventories.   (MOBILE4.1 does not apply to California vehicles.)
MOBILES  is scheduled to be issued November 1991 or as soon as
                                59

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possible  thereafter.  MOBILES will incorporate assumptions about
the VOC and NOX emission reductions of the mandated motor vehicle
measures  of the CAAA  (MOBILE4.1 already -includes the CO
reductions),  as well  as the benefits of the current Federal Motor
Vehicle Control Program.  Specific guidance about estimating
future year motor vehicle emission rates will accompany the
release of MOBILES.

     An updated version of Procedures For Emission Inventory
Preparation.  Volume IV:  Mobile Sources is scheduled for release
in Summer 1991 and will contain information relevant to
projecting both on-road and off-road mobile source emissions.

     2. Railroads

     Diesel engine equipment used by major Class A railroads has
undergone significant modernization in the last decade.  Emission
rates have decreased, so EPA is publishing new emission factor
guidance.  Downward trends in HC and CO emissions have been
observed, while NOX emissions have stabilized or increased
slightly.  New engines are cleaner and more fuel efficient, and
are serviced  more frequently.  Another trend is toward higher
horsepower engines; soon two locomotives may be able to perform
the work  of three.  These trends are reflected in the recently
revised base  year emission inventory guidance for this category.

     Decisions are scheduled to be made by EPA over the next five
years about how to regulate new locomotives.  Because fleet
turnover  is slow,  new standards will not have much of an
emissions impact before 2000.  The State of California is
examining the possibility of using smoke to detect violations of
emissions standards.  High diesel engine smoke levels are
indicative of a malfunctioning engine, which is typically caused
by malmaintenance and/or tampering.  High smoke levels can be
closely correlated with high PM emission levels (Jacobs et al,
1991)

     (Alternatives to diesel fuel are also being investigated by
the railroad  industry and may affect future year emission rates.)

     3. Aircraft

     Aircraft HC emission standards for newly manufactured
engines were  established in 1984 and have led to declines in
fleet average emission factors.   This trend is reflected in the
recently revised base year emission inventory guidance for this
category.

     Airlines continually acquire newer aircraft,  gradually '
phasing out older models.   While commercial aircraft often remain
in service for more than 25 years, fleet turnover phases out
aircraft using engines that do not meet the federal HC emission
standard.
                                60

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     Airport noise regulations also are forcing changes to the
commercial aircraft  fleet.  National noise regulations, which
were recently passed by Congress, are forcing airlines to phase
out the use of loud  aircraft by 2000.  This can be accomplished
by retiring the loud, older aircraft; replacing their engines
with newer, quieter  ones; or modifying the engines to muffle the
noise.  The first two alternatives result In aircraft with
reduced emissions.   Because this legislation is so new, the
airlines have yet to formulate plans for addressing these
requirements.  However, as the equipment is updated, changes to
the fleet will be reflected in the Federal Aviation
Administration's reports on aircraft activity.  Since-there is .a
significant engineering and development leadtime for producing
new aircraft engines, most of the commercial aircraft to be added
to the fleet in the  next five to seven years will be powered by
engines whose emissions are characterized in Supplement D to AP-
42.

     4. Non-Road Engines and Vehicles

     The CAAA require EPA to study non-road engine and vehicle
emissions to determine whether they cause or significantly
contribute to air pollution episodes.  The CAAA require that this
study be completed by November 1991 and be used by EPA to
determine whether non-road engines and vehicles contribute to
nonattainment problems.  It is further required that EPA
promulgate, by November 1992, any appropriate emission
regulations for non-road engines and vehicles.

     The categories  of non-road engines to be regulated will be
determined after the comment period for the November 1991 study.
By the following November,  more specific information should be
available on expected control techniques and their control
effectiveness.  In the meantime,  the State of California is
currently developing regulations for non-road engines and
vehicles (CARB,  1990) .   The California Air Resources Board (CARB)
has issued guidance  containing estimates of control effectiveness
for those future California regulations to. local air quality
planning authorities in that state.   California's estimates may
be useful in anticipating the benefits from any future EPA
regulations.   EPA's base year emission inventory guidance for
estimating off-road  equipment populations should also be
consulted for information relevant to projections.
                                61

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V COMBINING  GROWTH AND CONTROL EFFECTS
     A. OPTIONS

     When a  state or MPO gets to the point where it needs to
estimate the combined effects of activity growth and emissions
control on air pollution emissions for a projection year, choices
need to be made about the level of detail at which it is
desirable to perform the calculations and report the results.
Three options can be identified (there are certainly others) that.
are representative of approaches that have been tested. They are
listed below.

     (1)  Aggregating all base year emissions and control
          information at the county level and performing all
          projections on that basis.

     (2)  Allocating all base year emissions to grid cells
          compatible with the Urban Airshed Model, and estimating
          future changes in emissions for each grid cell/source
          category combination.

     (3) .Retaining source-specific information in the base year
          inventory and performing point source projections, on a
          source-by-source basis (with area source emission
          projections performed at the county level).

     Advantages and disadvantages to each of these three
approaches do exist, so a selection among the approaches should
be made by considering them separately, as well as by using the
criteria described in the Overview section of Chapter I of this
report as a  guideline.  It is also important to consider the
potential projection approach when compiling the base year
emission inventory, so that any data needed for a projection
approach can be efficiently collected at that time.

     Option  1 is the most computationally efficient method for
performing projections,  but is likely the. most problematic for
preparing inputs to a grid-based modeling approach.  Advantages
of this approach include the ability to quantify the effects of
some-policies,  such as new source review and emission offsets,
that are not amenable to analyses when source-by-source detail is
used to estimate emissions.   Another advantage is the ability to
incorporate assumptions about plant retirement rates in the
emission calculations.  Offsetting these advantages is the loss
of detail about source characteristics, including current
controls and their control effectiveness, that occurs when
emissions are aggregated at the source category/county level.
Aggregating  information also creates potential problems for
performing quality control functions,  in that errors may be
difficult to pinpoint.  Cost per ton values can be used to
estimate control costs with this approach.
                                62

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     Option 2 is an approach that has been used by the South
Coast Air Quality Management District (see Chapter VII for a more
detailed example).  For an area interested in grid-based
modeling, this approach produces emission forecasts that are
compatible with data input requirements.  An accurate application
of such an approach relies on the ability of the emissions
modeler to select source categories in a way that minimizes
differences in control levels and control techniques with the
modeling domain.  It also relies on there being little change in
the spatial distribution of emissions from the base year to the
projection year.  In this approach, growth and control factors
are the same for each source category (see Tables VII.1 and VII.2
for examples).  If control costs are of interest, the detailed
cost computations at the source level have to be made outside the
modeling framework.  The resulting cost effectiveness values
(cost per ton) can then be used in the modeling approach to
estimate total areawide costs for different combinations of
control options.

     Option 3 is similar to option 2 in that the basic
relationship used to estimate future emissions is simply:

Base Year Emissions * Growth Factor * Control Factor =
Future Year Emissions

     Option 3 is of value where retaining source-specific
information is desirable.  For many control strategy
applications, this information may be essential.  Having source-
specific information is always preferable when control costs are
to be estimated.  It also allows one the opportunity to drop
individual sources or plants from the data file if plant closures
are planned.  In addition,  source sizes are beneficial when
estimating the effect of applying controls down to a specific
size cutoff.  Finally,  the requirement to use allowable emission
rates in emission projections may make it necessary to retain
source-specific information,  unless source categories can be
defined in a way that makes all allowable emission rates the same
within a category.   While retaining source-level data has its
advantages,  it also increases computation time (probably of
little concern for urban-scale analyses)  and forces an analyst to
derive more complex routines for simulating new source growth at
other than existing facilities or for modeling the new offset
requirements for ozone nonattainment areas.
     B. GROWTH AND RETIREMENT RELATIONSHIPS

     Changes in stationary source activity levels are accounted
for in the general projection modeling approach as represented by
option 1 above, by a combination of growth and retirement rates.
This is done because regulations affecting new sources differ
from those affecting existing sources.  Therefore, different
control assumptions are identified for each.  Growth rates and
controls are applied to estimate new source emissions.
                                63

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Retirement rates are applied to estimate how emissions  from
existing sources will decrease.

     The most recent industry-by-industry projections of growth
applicable to an air pollution analysis are 'those performed by
the BEA  (BEA, 1990a; 1990b; 1990c) and discussed in detail  in
Chapter III.  These growth rates were calculated based  on
earnings and, therefore, are assumed to represent net growth for
an industry.  In other words, retirement of existing sources is
taken into account.  Retirement rates for existing sources  are
shown in Table V.I.  These estimates of plant retirement rates
were developed by Data Resources, Inc. (U.S. DOE, 1979) in
support of an industrial sector technology model development
effort.

     Table V.2 presents retirement rates developed from Internal
Revenue Service Depreciation Guidelines.  Annual retirement rates
for this table are estimated as the reciprocal of two times the
depreciation period in years.  As the average depreciation
periods are on the order of 10 to 20 years, most of the annual
retirements range from 2.5 to 5.0 percent per year.  A  choice
between using the retirement rates in Table V.I versus  Table V.2
is probably best made by selecting the one with the categories
that match best with the base year inventory being used.

     The equation which should be used, to incorporate the growth
and retirement rate data in an emissions projection is  as
follows:

Qn =  Q0  {[(1 + Gi)6  -  1]  Fn + (1 - Ri)c Fe + [1 -(1 - Ri)'] Fn}    (1)

where :

     Qn    =    emissions in projection year
     Q0    =    emissions in base year
     R;    =    retirement rate
     Fe    =    emission factor ratio for existing sources
     Gj    =    growth rate
     F    =    emission factor ratio for new sources
      n
     The first term in the equation represents new source growth
and controls, the second term accounts for retirement and
controls for existing sources, and the third term accounts for
replacement source controls.  It should be noted that. the Gi term
in equation  (1) represents net growth.  If a total growth rate
(G'i)  is used,  the first  term in equation (1)  should be changed
to [(1 + G'i -  Ri)c - 1]  Fn.

     Emission factor ratios are specified separately for new and
existing sources because regulations affecting new sources can
differ from those affecting existing sources.  Therefore,
different control assumptions are identified for each.  Emission
factor ratios for any projection year can be defined as the
estimated average emission rate within a source category for that
                                64

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                                            Table V.I
                  Industry
                                  Industrial Retirement Rates
SIC
  Average Annual
 Retirement Rates
(percentage per year)
                 Agricultural Production                   01
                 Agricultural Services                     07
                 Forestry                                08
                 Fishing, Hunting, and Trapping            09
                 Metal Mining                           10
                 Anthracite Mining                        11
                 Bituminous Coal and Lignite Mining        12
                 Oil and Gas Extraction                   13
                 Mining and Quanying                    14
                 Building and Construction                 15
                 Construction Other than Buildings          16
                 Construction - Special Trade              17
                 Food and Kindred Products                20
                 Tobacco                                21
                 Textile Mill Products                     22
                 Apparel                                 23
                 Lumber and Wood Products               24
                 Furniture and Fixtures                    25
                 Paper and Allied Products                 28
                 Printing and Publishing                   27
                 Chemicals and Allied Products             28
                 Petroleum Refining                       29
                 Rubber and Miscellaneous Plastics          30
                 Leather and Leather Products              31
                 Stone, Clay, Glass and Concrete            32
                 Primary Metal Industries                  33
                 Fabricated Metal Products                 34
                 Machinery, Except Electrical              35
                 Electrical Machinery                     36
                 Transportation Equipment                 37
                 Miscellaneous Instruments                 38
                 Miscellaneous Manufacturing Industries     39
                 Railroad Transportation                   40
                 Interurban Transit                        41
                 Motor Freight Transportation              42
                 U.S. Postal Service                       43
                 Water Transportation                     44
                 Air Transportation                        45
                 Pipe Lines, Except Natural Gas            46
                 Transportation Services                   47
                 Communication                          48
                 Electric, Gas and Sanitary Services         49
                 General Government, Except Finance       91
                 Justice, Public Order, and Safety           92
                 Public Finance and Taxation               93
                      4.26%
                      4.26%
                      4.26%
                      4.-26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.56%
                      3.35%
                      3.20%
                      3.18%
                      6.37%
                      3.68%
                      5.07%
                      4.92%
                      5.07%
                      4.48%
                      2.97%
                      4.09%
                      4.93%
                      4.97%
                      3.23%
                      4.10%
                      4.61%
                      4.09%
                      4.83%
                      4.41%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
                      4.26%
SOURCE: US. Department of Energy. 1979.
                                                 65

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                                             Table V.2
                                  Retirement Rates Developed Prom
                           Internal Revenue Service Depreciation Guidelines
 Source Types
  Annual
 Retirement
   Rate
 Exploration for & Production of Petroleum &
  Natural Gas Deposits & Storage
 Natural Gas Production Plant
 Liquified Natural Gas Plant (& Storage)
 Petroleum Refining of Crude Petroleum
 SOCMI
 Manufacture of Vegetable Oils/Vegetable Products
 Manufacture of Finished Plastic Parts
 Manufacture of Basic Plastic Parts,
  Phonograph, Records, Motion Picture
  Films & Tapes, Pens, etc.
 Manufacture of Rubber Products
 Manufacture of Primary Steel Mill Products
 Manufacture of Primary Nonferrous Metals
 Manufacture of Electronic Components
 Manufacture of Electrical & Non-Electrical
  Machines,  and Other Mechanical Products
 Manufacture of Tobacco & Tobacco Products
 Manufacture of Other Food Products & Beverages
 Manufacture of Leather & Products
 Manufacture of Yam, Thread, & Woven Fabric
  (Includes Tire Fabric &  Ind. Belts)
 Manufacture of  Pulp & Paper
 Manufacture of  Converted Paper, Paperboard
  & Pulp Products (i.e., for bags, envelopes, etc.)
Manufacture of Glass Products
Manufacture of Stone & Clay Products
Mining Equipment for Sand, Gravel, and Minerals
Manufacture and Production of Substitute Natural
  Gas - Coal Gasification
 0.036

 0.036
 0.022
 0.031
 0.050
 0.028
 0.045
 0.042

 0.036
 0.033
 0.036
 0.083
 0.050

 0.033
 0.042
 0.045
 0.045

 0.038
 0.050

0.036
0.033
0.050
0.028
                                                 66

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                                                                                       Annual
                                                                                      Retirement
  Source Types                                                                         Rate
  Exploration for & Production of Petroleum &                                           0.036
   Natural Gas Deposits & Storage
  Natural Gas Production Plant                                                         0.036
  Manufacture of Fabricated Metal Products                                              0.042
   (i.e., cans, tinwire, etc.)
  Manufacture of Motor Vehicles                                                        0.042
  Manufacture of Wood Products & Furniture                                            0.050
  Manufacture of Locomotives & Railroad Cars                                           0.042
  Ship and Boat Building Machinery and Equipment                                      0.042
  Manufacture of Aerospace Products                                                    0.050
  Graphic Arts Industry                                                                 0.045
  Utility -  Electric Steam Production Equipment                                           0.018
  Industrial-Steam & Electric Generation Equipment                                       0.023
  Electric Utility Combustion Turbine                                                    0.025
Source:  U. S. EPA, 1988
                                                   67

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 future year divided by the average emission rate for that same
 category in the base year.  Emission factor ratios are also
 referred to in some references as control factors.

     As part of the process in estimating how future year
 emissions might be different from base year emissions, it is
 important to consider the potential effects of technology changes
 on emission rates.  Because a large fraction of organic emissions
 are from evaporation, control approaches can result in different
 product formulations, which in turn can produce dramatically
 different emission rates and reactivity profiles.  Examples
 include the substitution of water-based for oil-based paints, new
 lower emitting less reactive solvents, and elimination of some
 high emitting products, such as cutback asphalt, in ozone
 nonattainment areas.  The provisions in the CAAA that require
 nonattainment regulations for consumer or commercial product
 categories that account for at least 80 percent of the VOC
 emissions would be expected to trigger considerable new product
 development and reformulation.  Therefore, it is important that
 the states track rulemaking efforts for these categories to
 establish how technology changes might affect' future emission
 rates.
     C. FUTURE DIRECTIONS -- EMISSION PREPROCESSOR
        SYSTEM (EPS) ENHANCEMENTS

     EPA is in the process of upgrading the Emissions
Preprocessor System  (EPS) to provide a computerized tool for
implementing the projection and control guidance in this
document.  The enhancements will allow for anthropogenic
emissions to be projected and/or controlled on a county-level
basis by source category.  The projections will be accomplished
by applying a growth factor to the base emissions.  Controls and
RE will be handled as control factors (also described as emission
factor ratios earlier in this chapter),  which are fractions less
than or equal to one.  Allowable emissions will be handled
similarly, incorporating both growth and controls."

     In addition, a utility is being added to EPS to aid the user
in generating the growth factor input file based on BEA data.
This utility will not generate the projection factors, but will
create the projection factor input file from existing BEA growth
factors by source category.  Other enhancements should make EPS
more flexible and easier to operate.

     The revised version of EPS will be a menu-driven system
based in FORTRAN, with the menu portion programmed with SAS.  The
new system should be available for distribution to the states by
May of 1992.
                                68

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69

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VI VALIDATION


     There are a number of methods that can .be applied to
validate historical emission estimates.  Stack tests or
continuous emission monitoring data can be used as a validation
tool for stationary source emission estimates.  Similarly, motor
vehicle travel estimates can be validated by traffic counts on
selected roadways.  Validating future year emission estimates is
more problematic, however.

     It is recommended that, before state and local agencies
submit their emission projections to EPA, that some validation,
or reasonableness, checks be performed.  These can be done for
the complete inventory of sources, as well as for individual
components such as highway vehicles.  In short, the validation
method being suggested is a comparison of projection results with
those of other recently completed studies for the same or similar
areas to identify and understand any inconsistencies.

     One emission projection effort that may prove useful in
validating SIP emission projections is that performed as part of
the ROMNET study.  The ROMNET inventory uses the 1985 National
Acid Precipitation Assessment Program (NAPAP) Emissions Inventory
as its source of base year operating and emissions data.  The
ROMNET modeling domain includes 12 full states and the District
of Columbia, portions of another 7 states,  and a portion of
Ontario,  Canada.  The 12 full states included in the ROMNET study
were: New Hampshire, Massachusetts, Rhode Island, Connecticut,
Delaware,  Virginia, West Virginia, New York, New Jersey,
Pennsylvania, Maryland, and Ohio.  The inventory has been
subjected to additional quality assurance (QA) procedures and
updates based on more current or accurate information gathered
from the sources themselves, or provided by state agencies.
ROMNET includes both baseline emission projections and strategy
emission projections.

     These inventories concentrate on the large, point sources of
NOX  and VOC  inherent in the  NAPAP plan  and methodology.
Emissions sources (plants) of less than 100 tpy are not included
as point sources in the inventory.  Individual points emitting
less than 25 tpy are also not included.  Sources of CO have
undergone less rigorous QA.   Area source categories (including
mobile sources) are based on the NAPAP list of area source
categories rather than the SIP categories.   Both inventories use
temporal allocation software developed for the 1985 NAPAP
emissions inventory to derive seasonal,  daily, and hourly
allocation factors and generate similarly resolved emissions.

     ROMNET projection inventories relied principally on BEA
employment projections for approximately 90 2-digit SIC groups.
Control scenarios have been simulated using these groupings
rather than individual plant projections.  Utility emissions were
projected based on the Advanced Utility Simulation Model (AUSM)
                                70

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results.  The  states reviewed all growth projections and,  in some
cases, substituted  their own data.

     The Office of  Technology Assessment  (OTA) analyzed  (1989)
the VOC emissions reductions from a number of source-specific
control strategies  (1989), including the following, which  are
reasonably representative of the new measures mandated for ozone
nonattainment  areas in the CAAA.

   • Adoption  of RACT on all existing stationary sources for
     which a regulation already exists in any SIP.
   • Adoption  of new CTGs — RACT-level controls for several
     existing  stationary sources of VOC for which EPA has  not
     issued control guidelines, and which have not previously
     been subject to regulation in any SIP.
   • Emissions controls on hazardous waste TSDFs.
   • Establishment  of new Federally regulated controls on
     architectural  surface coatings.
   • Onboard vapor  recovery systems on motor vehicles to capture
     gasoline  vapor during refueling.
   • Stage II  control devices on gasoline pumps to capture
     gasoline  vapor during motor vehicle refueling.
   • Inspection and Maintenance (I/M) programs for highway
     vehicles.
   • More stringent exhaust emission standards for gasoline
     highway vehicles.
   • New Federal restrictions on gasoline volatility.
   • The use of methanol instead of gasoline as a fuel for
     vehicles  in centrally owned fleets in the worst
     nonattainment  cities.

     Compared  with VOC emissions for a 1985 base year,  by  1994,
application of the measures outlined above was estimated to
result in a 34 percent reduction,  on average, of emissions in
nonattainment  cities.  Because of uncertainty in the emissions
inventory,  differences in source category contributions by area,
and the degree to which future emissions can be controlled, total
emissions reductions from the measures analyzed ranged from 18 to
37 percent of  1985  levels.  The percentage reductions for most
categories are about the same in 1994 and 2004,  except for
onboard VRS controls and new highway vehicle standards,  which
increase because more of the older vehicles will have been
replaced by newer,  lower-emitting vehicles.  Additional emissions
reductions in  2004  from onboard VRS and other highway vehicle
emission standards,  as a percentage of total 1985 emissions,  are
estimated by OTA to be about 4 percent.

     EPA-sponsored analyses (Pechan,  1991)  of the CAAA have shown
that ozone nonattainment areas that institute all of the measures
required for areas  in the severe and extreme categories can
conceivably achieve VOC reductions of about 45 percent
(as a percentage of 1987 emissions)  by 1995,  and close to 50
percent by 2000.  While these emissions reductions are higher
than those estimated by the OTA,  the OTA figures do not include
reductions that might be achieved from consumer/commercial

                               71

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product rules or from reformulated gasoline.  Note that the
Pechan analysis assumes that EPA will choose not to adopt Phase
II or Tier II light-duty vehicle emissions standards.  If
adopted, these emissions standards would not provide emission
benefits until after 2000, in any event.
                               72

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VII CASE STUDIES
     Two recently completed projection analyses for modeling
studies provide some useful experience to those who may be
unaccustomed to performing emission projections.  The Southern
California Association of Governments (SCAG) and the SCAQMD
prepared baseline projections of activity and emissions for the
South Coast Air Basin  (SCAG, 1989, and SCAQMD, 1989) .  This
information was used to prepare a grid based emission inventory
for both current and future years.  For areas planning to use a
grid based model for their attainment demonstration, this example
should assist in showing how this type of analysis can be
performed.  Because growth in the Los Angeles area is heavily
affected by migration from outside the United States,  there was
more emphasis in the South Coast analysis on population
projections than might otherwise be the case.  This factor is
probably less important in other nonattainment areas.

     The ROMNET analysis (Possiel, 1991) was to support a
regional modeling exercise, but it is expected that SIP analyses
will be consistent with the level of detail of this analysis.
Hence, it is a relevant example.
     A. SOUTHERN CALIFORNIA EMISSION PROJECTIONS

     Southern California based its emission projections on an
analysis of population and employment through the year 2010.  The
region began with a draft baseline projection that was a
calculation of what the population and employment growth of the
SCAG region would be if the demographic and economic forces.
experienced over the previous decade were to continue through the
year 2010.  This baseline projection also reflected national and
state-level projections of demographic and economic trends and,
in a few cases, data which indicated that future trends were
likely to diverge from historic trends.  The baseline projection
did not assume any government intervention with demographic,
economic, or housing market trends.

     1. Population Projections

     There are three primary components of population growth:
births, deaths, and net migration.  The first two components
constitute natural increase (births minus deaths),  and the third,
net migration, can be separated into net domestic migration
(within the United States) and net foreign migration (people
moving from other countries)  which includes both legal and.
illegal immigrants.

     The SCAG projection anticipated that natural increase will
play a more dominant role in the region's growth than it has in
the past.  Between 1975 and 1980, half of the population growth
was the result of natural increase.  Between 2000 and 2010,
                                73

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natural increase is projected to contribute 75 percent of the
region's total growth.  This increase is attributable to the
growing Hispanic population (with high fertility rates) and the
decreasing ratio between migration and the region's population.
Overall, natural increase represents 63 percent of the region's
population growth between 1980 and 2010.

     Migration includes both inward and outward movement.  Net
migration in the SCAG region was projected to be negative from
1980 to 2010.  Net out migration is small relative to the total
population of the region, however.  Between 1980 and 2010, about
9.0 million people are expected to leave, while 8.1 million are
projected to enter.  This indicates a very mobile population.

     Recent trends have shown high levels of immigration to the
SCAG region.  Potential reasons for this may include the
following: •

   • Job opportunities relative to other areas
   • Proximity to Mexico and Central America
   • Pacific Rim location
   • A similar climate to Latin American and Asian-Pacific
     countries
   • Large ethnic communities and cultural centers already
     located in the region

     For both the nation and the SCAG region,  the population will
be aging.  The changing age structure of the population was
reflected in the SCAG baseline projection, with the median age of
males increasing by 5.8 years and females by 6.4 years by 2010.
Projected male versus female age differences will continue.  This
difference is primarily the result of higher female survival
rates.

     At the national level,  the median age of males is projected
to increase by eight years and the median age of females by nine
years.  The population of the SCAG region is expected to remain
younger than the nation's population with the influx of
immigrants who are typically young,  and the relatively higher
fertility rates of the Hispanic population.

     The projection model used by the South Coast links economic
data to population dynamics, and is based on the assumption that
patterns of migration into and out of a region are influenced by
labor market variables.  The demographic projections,  following a
cohort-component procedure,  are developed independently from the
economically driven projections.   Results of the demographic
model are then compared with those of the economic projections
and the migration assumptions are adjusted as a function of
projected employment.  Figure VII.1 illustrates the relationship
between the demographic and economic projections.

     SCAG's baseline employment projection model is based on a
detailed shift/share analysis of industries in the Los Angeles
                               74

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                            Figure VII.1
           Relationship Between SCAG Demographic
                    and Economic Projections
Demographic Model                              •       Economic Model
  1980 Census
  SCAG Region
  Out-Migration
    Domestic
    Migration
     Legal
   Immigration
 Undocumented
   Immigration
 Natural Increase
 (Births-Deaths)
     Draft
   Population
   Projection
                                  Adjustments
U.S. Population &
Labor Force Pop.
   1980-2020
                                                          I
   U.S. Total
     Jobs
                                                          L
 Cal. & SCAG's
  Share of U.S.
   Total Jobs
      I
                                                      SCAG's Jobs
                                                       Projection
  Comparison
   of Jobs to
  Labor Force
                                                          I
  Labor Force
   Population
                                • 75

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basin compared with  State and national projections  for those
industries.  A flow  chart of the major components of the modeling
process  is shown  in  Figure VII.2.

     As  Figure VII.2 shows, the model begins with national job
projections prepared by the BLS Office of Economic  Growth.  This
includes detailed industry-by-industry projections  of employment
and output for 155 sectors of the U.S. economy.  From the
national projections, the model derives California's and the
region's share of national growth.  To perform the  sharing
analyses, industries are divided into base and nonbase, where
base industries are  those with national, international or state
markets  (e.g., manufacturing) and nonbase are those dependent on
demand from local markets (i.e., population serving).

     The state model used 83 sectors for California's share of
the U.S. economy* with 66 base and 17 nonbase industries.  The
regional model used  66 industries because the regional economy is
less broad than the  state economy (and ends up with 49 base and
17 nonbase industries).  Table VII.1 shows the list of base and
nonbase  industries used in the SCAG analysis.

     Regional projections were needed for each of the individual
base industries.  Historical annual wage and salary employment
data were used from the Employment Development Department.  The
model uses these  data to examine the following:

   • Each industry's 1984 share of employment in the state
   • The industry's historical average share of employment over
     the last 12 years
   • Its share of total job growth over the same period
   • Changes in the industry's share of employment over time

     For each industry,  a share factor was selected from one of
the above indicators.  These share factors were then applied to
the projected state growth levels in each of the base industries
to yield an estimate of total growth in the base industries for
the region for a projection year.

     Nonbase industry jobs were projected based on the historical
relationship between base jobs and total jobs.  This job
multiplier is used with the total base employment figure for the
projection year to estimate total employment.  The difference
between projected total jobs and projected base industry jobs is
total nonbase industry jobs.

     Total nonbase industry jobs then had to be allocated to the
individual categories shown in Table VII.1.   The model did this
by calculating the ratio of the share of each nonbase industry to
total jobs in the SCAG region compared with that industry's state
share of the state's total jobs.   The ratio was then used as a
weighting factor to adjust statewide nonbase shares to reflect
regional shares.
                                76

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                               Figure VII.2
                  SCAG Economic Projection Model
 •Q
 O
 "c
National Projection of Jobs
       By Industry
                                                           U.S. Population
                                    U.S. Labor Force
                                    Population Rates
   Base Industry
   Share Analysis
O
                            Classification
                                into
                     Base and Non Base Industries
                     Projection of Base Industries
                         Base Job Multiplier
                             Total Jobs
                                                       Non Base Industry
                                                        Share Analysis
                               Projection of Non Base
                                    Industries
   Base Industry
  Share Analysis
c
o
O)
0)
GC
(3
<
O
V)
                            Classification
                                into
                    Base and Non Base Industries
                     Projection of Base Industries
   Base Job Multiplier
                             Total Jobs
                                 Non Base Industry
                                  Share Analysis
                               Projection of Non Base
                                    Industries
                                     77

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                                 Table VII.l
           Base and Nonbase Industries for the SCAG Region
                                  NONBASE
Self-Employed & Household Workers
Construction
Local Transit
Travel Services
Communications
Utilities
Retail Trade
Finance
Insurance
Real Estate
                                    BASE
             High Technology
Computers
Communication Equipment
Electronic Components
Measure Control Instruments
Medical
Other Instruments
Computer Service

         Diversified Manufacturing
Other Food Products
Textiles
Apparel
Other Lumber & Wood Products
Furniture
Paper Products
Printing
Chemicals
Rubber, Plastic Products
Leather
Stone, Clay, Glass
Primary Metal Products
Fabricated Metal Products
Machinery (except computers)
Machinery (except communications equip.
         and electronic components)
Motor Vehicles
Misc. Transportation Equipment
Misc. Manufacturing
Personal Services
Repair Services
Theaters
Medical Services
Legal Services
Educational Services
Nonprofit Organizations
Professional Services
Local Government
Local Education
         Defense Oriented
Aircraft
Ship Building and Repair
Missiles, Space
Department of Defense

          Resource Based
Agriculture
Mining
Canned, Frozen Food
Logging
Petroleum Products

       Basic Transportation
Railroads
Truck Transportation
Water Transportation
Air Transportation
Pipeline Transportation

            Other Basic
Wholesale Trade-Durable
Wholesale Trade Nondurable
Hotels
Motion Picture
(filming and distribution)
Amusements
Other Business Services
Agricultural Services
Federal Civilian
State Government
State Education
                                      78

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     A key  component  relating  employment and population
projections is  the  civilian  labor  force.  The civilian labor
force is  the number of noninstitutionalized or nonmilitary
personnel 16 years  old or older who are working or actively
seeking work.   The  civilian  labor  force can be determined in  two
ways.  One  is from  an employment projection and the other is
through the labor force participation rates of the demographic
mix  in the  area.

     2. Baseline Emission Projections

     a. Stationary  Sources

     The  next step  in the SCAG region projection effort was to
estimate  future baseline emissions.  Baseline emissions in this
case were defined as  those expected if no additional air quality
regulations are introduced.  These emissions are forecasted using
control measures in effect at  the time of the projection, and
growth rates for population, industry, and motor vehicle
activity.   For  the  SCAG region study, growth rates were as
determined  using the  techniques described in the preceding
section.

     Future year baseline emissions are estimated for each
individual  source category using the relationship shown in- the
equation  below:
                    .= EmisBase (CF) (GF)                   (1)
where :
                    = future year emissions
                    = base year emissions
          CF        = control factor (the level of control imposed
                      on a single source category as a result of
                      existing state and local air quality regulations)
          GF        = growth factor from SCAG regional modeling

     Control factors for selected stationary source categories
for the SCAG region are illustrated in Table VII. 2.  Control
factors are shown, for total organic gases, oxides of nitrogen,
and sulfur oxides.  Similarly, examples of growth factors for the
counties in the SCAG region are shown in Table VII. 3.

     b. Mobile Sources

     Within the SCAQMD, mobile sources consist of two
subcategories:  on-road and off -road sources.  On-road vehicle
emissions are calculated using socio-economic data provided by
SCAG,  spatial distribution data from Caltrans' Direct Travel
Impact Model (DTIM) ,  and emission factors from the California Air
Resources Board's motor vehicle emission factor model, EMFAC7 .
Emissions from off-road vehicle categories (e.g., trains, ships,
utility engines) were calculated as area sources.
                                79

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                                 Table VII.2

                Stationary Source SCAG Region Control Factors
                         For the Years 2000 and 2010*
CONTROL
CODE
104
105
107
110
111
114
117
124
301
302
303
308
309
CONTROL
NAME
. Residential Space
Heaters
Residential Water
Heaters
Non-Utility I.C.
Engines: Gas
Cement Kilns
Glass Melting Furnaces
Sulfur in Fuel
Refinery Boilers and Heaters
Utility Turbines: Gas
Architectural Coatings: Oil Based
Architectural Coatings: Water Based
Architectural Coatings: Solvent
Metal Parts & Products: Surface Coating
Metal Parts & Products:
CONTROL FACTORS
TOG NOX SOX
0.78
0.57
0.33
0.74
0.50
-
0.64
1.00
0.53
0.53
0.53
0.85
0.85
-
-
-
-
-
0.80
-
-

-
-
-
_
316
Solvent

Cut-Back Asphalt Paving Material
0.67
           * Control categories not listed in this table have control factors equal to one.
                                       80

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             Table VII.3

SCAG Region SIC Code Growth Factors
          for The Year 2000 .
SECTOR
Agriculture
Mining
Construction
Manufacture
Trans. Util.
Retail
Wholesale
Fin-Ins-Re
Services
Government
Self Employ
Employ-NRet
Scrv.-lnst
Population
Housing Un.
Food
Apparel
Furniture
Paper
Printing
Chemicals
Pciroleum
Rubber &. Plas
S.C & G
Pri.Mctals
Fab.Meials
Mach-NElect
Elect. Equip
SIC
CODE
01-09
10-14
15-19
20-39
40-49
52-59
50-51
60-69
70-89
90-97
	
52-59
50-97
—
— ~~
20
23
25
26
27
28
29
.. 30
32
33
34
35
36
LOS
ANGELES
COUNTY
1.056
0.992
1.107
1.133
1.195
1.228
1.179
1.269
1.507
1.073
1.008
1.231
1.302
1.134
1.183
0.966
0.944
1.370
0.964
1.244
1.171
1.046
1.1988
1.086
1.032
1.136
1.172
1.383
ORANGE
COUNTY
1.057
0.976
1.509
1.352
1.812
1.527
1.808
1.621
2.007
1.178
1.562
1.596
1.675
1.359
1.429
0.661
0.557
1.983
0.955
1.790
.. 1.375
1.130
1.435
1.063
0.993
1.394
1.482
1.488
RIVERSIDE
COUNTY
1.030
1.000
2.651
1.159
1.770
2.027
1.463
1.938
2.358
1.466
1.429
1.670
1.893
2.151
2.242
0.298
1.060
3.199
0.698
1.651
1.060
1.130
1.504
1.000
1.008
1.606
1.731
1.799
SAN
BERNARDINO
COUNTY
1.043
1.000
1.844
1.226
1.865
1.853
1.647
1.682
2.052
1.427
1.382
1.605
1.775
1.803
1.847
1.306
1.060
1.723
0.980
1.842
0.964
1.130
1.294
1.154
1.356
1.356
1.176
1.487
               ..  81

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Trans Equip
Aircraft
Instrument
Other Mfg.
37
372
38
21,2
4,31.9
1.003
1.132
1.088
1.000
1.097
1.137
1.368
1.049
0.672
1.140
1.441
0.880
1.265
1.145
1.286
0.723
NOTE: These growth factors are relative to 1984 base year.
                                                         82

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     EMFAC is the California ARB's model for estimating emission
factors for on-road motor vehicles.  Originally, EMFAC closely
paralleled EPA's model, MOBILE, with the-exception of its
different treatment of trip end emissions.  As the California-
specific vehicle emission data base grew, the model has become an
independent entity as needed to reflect California's motor
vehicle fleet.                           '•  ..

     The emission factors generated by EMFAC are used in
conjunction with activity data in BURDEN to develop the motor
vehicle emission inventory.  BURDEN is a county-specific program
that uses vehicle activity from either local travel demand models
or the California Department of Transportation's statewide travel
model activity disaggregated to the county level.

     The above calculation allowed the SCAQMD to compute total
baseline emissions of criteria air pollutants as well as the
relative contributions by stationary and mobile sources.  To
determine the spatial distribution of population and emissions,
the Air Basin was divided into a grid system composed of 5 km by
5 km grid cells and the emissions were allocated to these grid
cells.

     c. Summary

     Table VII.4 summarizes the key resulting socioeconomic
parameters used in the emission forecasts for 2000 and 2010 in
the region.

     South Coast Air Basin baseline emission projections
(accounting for regulations adopted as of June 1990)  show that
organics,  NOX/  SOX, and PM10 are not expected to decrease
appreciably between 1987 and 2010 (SCAQMD,  1991).  This is a
result of regional growth in population,  housing, and motor
vehicle use.  Baseline CO emission projections showed a 50
percent expected decline by 2010.

     Significant differences in the spatial distributions of net
changes in emissions of VOC,  NOX/  and CO  between  1987  and  2010
were predicted within the air basin.   VOC,  NOX, and CO emissions
are expected to decrease significantly in the western part of the
basin, but are predicted to increase in the east.  This
underscores the importance of accurately assessing spatial
changes in emissions when emission projections are to be input to
a grid-based model.

     Once the SCAQMD computes their expected baseline emissions
for 2000 or 2010, they apply additional control measures,  which
they have divided into three tiers,  depending on their readiness
for implementation.  Thus,  for any individual proposed rule not
included in the baseline emissions calculation,  the associated
emission reduction, or control factor,  is estimated with
reference to the future year baseline.   The effects of individual
measures in reducing criteria pollutant emissions are too
                                83

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 Socioeconomic
 Category

 Population
 (Millions)

 Housing Units
 (Millions)
 Total Employment
 (Millions)
 VMT
 (Million Miles)

 In-Use Vehicles
 (Millions)

 Vehicle Trips
 (Millions)
            Table VII.4

Baseline Socioeconomic Forecasts for
    the South Coast Air Basin*

            Year               ' -Year
    1987    2000  (% Growth)    2010  (% Growth)
     12.0     14.3   (+19)
     4.4     5.5  (+25)
     6.0     7.4  (+22)
   240.1    323.5  (+35)
     7.9     9.2  (+17)
    29.2    35.3   (+21)
 15.7  (+31)

  6.1   (+39)

  8.2   (+36)

387.6  (+62)

 10.3   (+31)

 40.0   (+37)
* No AQMP measures included.

SOURCE: SCAQMD, 1991.
                                   84

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voluminous  to list  in  this  example.  Readers  interested  in more
details  are referred to  the SCAQMD  (1991) report.  The net result
of applying the  three  tiers of  control measures  in the South
Coast  is a  significant additional reduction in expected  criteria
pollutant emissions from the baseline emission levels estimated
for  2010.   Estimated annual average ton per day  emission
reductions  from  the 2010 baseline for the-SCAB are as follows:
                    Organics       83%
                    NOX            62
                    CO   .          51
Note that because of the severity of the air pollution problem in
the South Coast Air Basin, that the reduction percentages listed
above are considerably higher than what is expected to be
achieved in a typical honattainment area.


     B. REGIONAL OZONE MODELING FOR NORTHEAST TRANSPORT —
        PROJECTION YEAR AND CONTROL STRATEGY EMISSIONS
        INVENTORIES

     EPA's ROMNET program was undertaken to quantify the
concentrations of ozone and ozone precursors transported among
urban areas in the Northeast, and to assess strategies for .
attaining the ozone National Ambient Air Quality Standard
(NAAQS).  Inventory development for ROMNET was overseen by an
Emissions Committee and a Strategies Committee, each of which
included representatives from the states in the region.

     In the projection phase of ROMNET, emissions were estimated
for the year 2005 under a number of different emissions control
scenarios.  This section focuses on the methodologies used to
predict future emissions.  The ROMNET final report gives
additional details on the emission control strategies analyzed,
and the magnitudes of predicted emissions (Possiel et al., 1991).

     1. Inventory Structure

     For each future emission.scenario, a detailed emissions
inventory was prepared to serve as input to the Regional Oxidant
Model (ROM).  Each ROMNET inventory contains anthropogenic
emissions data for total hydrocarbons (THC),  volatile organic
compounds (VOC),  nitrogen oxides (NOX),  and carbon  monoxide  (CO),
which are precursors in urban ozone formation.  NOX emissions are
divided into NO and N02;  and  organic  emissions are  broken  into 11
reactivity classes based on the Carbon Bond IV system.

     All of the ROMNET future emissions inventories derive from
the 1985 ROMNET emissions inventory (Battye,  1989), which in turn
was based largely on the 1985 NAPAP emissions data base (Saeger,
1989) .
                                85

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     Each ROMNET inventory contains separate files  for point
sources, stationary area sources, and mobile sources.  The
distinction between point and area sources is the same as.that
used in NEDS  (plant emissions of 100 tons or more per year of any
criteria pollutant, or 5 tons per year of lead).

     The area  source inventory does not address individual
sources, but instead gives emissions for aggregated groups of
sources that are too small or numerous to be covered by the point
source inventory.  Area sources in the  ROMNET inventory include
minor fuel combustion sources; open burning and solid waste
disposal; structural and forest fires; nonhighway transportation
sources such as  trains, airplanes and off-highway vehicles;
solvent evaporation from paints and other solvent uses; and some
industrial fugitive emissions and process vent emissions.  The
mobile source  inventory includes only highway vehicle emissions.

     Emissions are apportioned into a Mercator grid system, with
each grid square covering one-sixth of a degree latitude and one-
fourth of a degree longitude (or an area roughly 20 km by 20 km) .
Each inventory gives hourly emissions for three day-types:
typical weekday,  Saturday, and Sunday.  Data in the point and
area source inventories reflect emissions on clear hot summer
days, which characterize a typical episode with exceedances of
the ozone NAAQS.

     2. Projection and Control Algorithms for Point and Area
        Sources

     Table VII.5 depicts the basic algorithm used in ROMNET for
determining future point and area source emissions.   The
algorithm is somewhat more complicated if NSPS apply,  since these
standards affect only new, modified and reconstructed emissions
sources.

     The algorithm in Table VII.5 is implemented at the finest
level of detail  allowed by the point and area source inventories.
In the point source inventory,  growth and control factors were
applied to each  individual source.   For area sources,  the factors
were applied at  the county and emissions category level.   In this
way,  growth in an emission category was spread equally among all
of the individual sources in the category.

     Growth rates used in the projection algorithm vary by state
and also for different industrial categories within each state.
The growth rate  represents an increase or decrease in the basic
activity that causes emissions.   In general,  each point source
and each industrial area source category was assigned a growth
rate based on its 2-digit SIC code.   For utilities and industrial
cogeneration,  growth factors were applied on a more detailed
level,  based on  the fuel burned and the combustion method.
Future emissions from nonindustrial area sources were projected
based on population growth.
                               86

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                                    Table VIL5

                     Equations Used to Predict Future Point and
                                Area Source Emissions
                    =     E^xGFxdOO-Eff^/dOO-Eff^)              (1)

       GF                 (1 + i/lOO)20                                  (2)


Variable definitions:

       £2005          =     estimated emissions in 2005 (tons/year)

       E1985          =     emissions in 1985 (tons/year)

       GF           =     growth factor from 1985 to 2005 in the activity causing
                          emissions (dimensionless)

       r             =     growth rate (percent per year)

                    =     control efficiency for the 2005 inventory (percent)

                    =     control efficiency in the initial 1985 inventory (percent)
                                         87

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     ROMNET control  strategy efficiencies can be applied  for  the
entire region,  for the Northeast Corridor, or at the  state, MSA,
or county level.  The degree of spatial -resolution depended on
the specific control scenario.

     Emissions  sources in the point source inventory  were grouped
into approximately 90 different source groups, or "pods," for the
purpose of applying  controls.  ROMNET strategy efficiencies and
existing control efficiencies were defined at the pod level
within the appropriate geographic area.  The ROMNET area  source
inventory was divided into 64 separate categories, derived from
the 109 NAPAP and NEDS categories but excluding highway vehicles
 (which were treated  separately from other area sources) and
particulate emissions categories.  Each area source category  was
treated separately for the purpose of applying controls.

     3. Projection and Control Algorithms for Mobile  Sources

     Table VII. 6 illustrates the general algorithm used to
predict future  mobile source emissions.  Because of the
temperature sensitivity of mobile source emissions,  the mobile
projection algorithm was designed so that day-specific
inventories can be generated to reflect temperatures  at the grid
level .
     The projection algorithm begins with 1985 emissions
evaluated at a standard temperature  (mean temperature = 85°F;
diurnal variation = 2.0°F) ,  and neglecting any -local I/M programs.
Predicted state-specific growth rates for VMT are applied to give
"uncontrolled" emissions for 2005  (U20o5) •  keeping per-mile
emission factors at their 1985 levels.

     Two control factors are then applied to give 2005 emissions
for a given ROMNET strategy.  The first control factor includes
regional controls such as the Federal Motor Vehicle Control
Program (FMVCP) and regional reductions in RVP.  Grid-level
temperature, adjustments are also made in this step.  The second
control factor is applied at the county level and accounts for
local control measures such a I/M programs.

     Emissions are projected at the grid and county level for
VOC, NOV  CO,  and VOC  and  NOX species.  For VOC, separate
projections are made for evaporative VOC emissions, VOC from
gasoline exhaust and diesel VOC emissions.  The segregation of
VOC allows a final recalculation of VOC speciation to account for
temperature variations and differential control efficiencies.
The final speciation is day-specific and also varies from grid to
grid depending on grid-level daily temperature profiles.

     4. Summary of Future Scenarios

     Fourteen inventories for future anthropogenic emissions were
produced under ROMNET.  All of these inventories represent
emission scenarios for the year 2005.  Two are projection
                                88

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                                     Table VIL6

               Equations Used to Predict Future Mobile Source Emissions
CFreg

CFlocal
                           poIM
                                1985
                                  CF^xCF,^
                           EFJEFI985

                           (1 - EfWIOO)
Variable definitions:
       U.
        2005
       ?noIM1985
       CF,,
      CF
      \^i i
         local
      EF.,
      EF
         1985
      Eff,
         local
                    projected emissions in 2005 at standard temperature (mean
                    temperature = 85°F; diurnal variation = 20°F), neglecting local
                    inspection and maintenance (I/M) programs and assuming  that
                    emissions remain at 1985 levels on a per-mile basis

                    1985 emissions at standard temperature and neglecting I/M

                    growth rate in vehicle miles traveled (percent per year)

                    projected controlled emissions in 2005, adjusted for grid-level
                    temperatures

                    regional control factor

                    local control factor

                    predicted 2005 emission factor for a given strategy, incorporating
                    regionwide controls (temperature-dependent,  in g/mile)
                    1985 emission factor used to develop E1
                                                               DOIM1985
(g/mile)
                    efficiency for any local controls that are applied above and
                    beyond regional controls (percent)
                                          89

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inventories using different baseline control assumptions, and the
remaining 12 represent various control strategies.  The inventory
development effort was carried out in two main phases.  In Phase
I, VOC controls were applied to different portions of the ROMNET
region, while NOX emissions were held constant.   In Phase II, the
relative impacts of VOC and NO^ controls  were analyzed,  as well
as strategies for reducing VOC reactivity.

     All of these inventories are in the same format as the base
year inventory, with emissions given on a gridded, hourly basis
for a typical summer weekday, Saturday, and Sunday.  Emissions
are given for VOC, NOX,  and NO2.  For mobile sources, tabular
emission factors were prepared for each future inventory,
providing the capability to adjust emissions to reflect grid- and
day-specific temperatures.

     Each of the future anthropogenic inventories was merged with
a biogenic emissions inventory and input to the Regional Oxidant
Model.  The purpose of the modeling effort was to estimate ozone
levels that would be observed under the various future emissions
scenarios.
                               90

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VIII  BIOGENIC EMISSIONS PROJECTIONS


      Recent modeling studies  show the importance of including
natural hydrocarbon emissions in ozone modeling studies.   SPb

                                                           ""*
program is  available  from the  EPA CHIEF Bulletin Board,  which can
be accessed through a personal computer and modem at  (919)  541-
5742 . ]   The system calculates  emissions at  the county level using
episode-specific  data on  temperature  and sunlight intensity.

      In BEIS, biogenic  emissions  are  calculated from  a set  of
emission factors  and  meteorological correction factors that are
specific to various categories of land  use  or  biomass.   The
general algorithm for nonforested areas can be summarized as
follows:

      ER  =   $  ( A,  * EFj * FjtSfT] )

where ER is the total biogenic emission rate (grams/hour) for a
given VOC species  in  a  given grid, ^  reflects  the summation over
all land use types, Aj is the area (square meters) of land use  j
in the  grid, EF.J is the emission factor  (g/m2-hour)  for land use
j, and  Fj[S,T]  is a dimensionless meteorological correction-
parameter that is  a function of temperature and sunlight
intensity.

      The  emission  rate  for forested areas is as follows:

      ERj  =   $  ( Aj *  BFj  * EFj  * F.j[S,T] )

where the new term BFj is the mass of dry leaf in a given
forested area  (g/m2) .   All other terms are the same as is the
first equation, except  that the emission factor EF.J is expressed
in terms of  emissions-per-leaf  biomass  (ug/g) .

      BEIS includes  emission factors for 16  land uses:   oak
forest,  other deciduous forest, coniferous  forest,  corn,
peanuts/rice, tobacco,  grass/pasture, hay/scrub/rangeland,
potato,  sorghum, alfalfa, barley/cotton/oats/rye, wheat,
soybeans, urban areas,  and water  or barren  land.  Emissions  are
highest  for  forested  land and  corn (3-4 mg/m2-hr) .  Emissions
from  foliage and grass  in a typical urbanized  area .are  about a
factor  of four lower  (0.8 mg/m2-hr) ,  and emissions from crops
other than  corn are lower still  (0.02-0.5 mg/m2-hr)  .

     The adjustment parameters  (Fj[S,T]) are fixed for a given
set of meteorological inputs, which are dependent on  the episode
being modeled.  Also,  the emission factor for  a given land  use
(EFj)  is fixed.   Therefore,  land use  area (Aj)  is the  only
parameter that can  be affected  in an  emission  projection
analysis .
                                91

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     A detailed projection of biogenie emissions for a growing
metropolis would be expected to show a reduction in biomass
corresponding  to increased urbanization."-  This would result in a
decrease in biogenie emissions.   Biogenie emissions estimates are
very uncertain,  however,  and projections of these emissions would
be more uncertain.   Biogenics,  therefore,  are held constant for
most projection analyses.                ''  ..

     There are several  reasons for the uncertainty in biogenie
emissions estimates.  Both the emission factors and the
meteorological correction factors are uncertain.  In addition,
the timing of  biogenie  emissions (between morning and afternoon)
is not fully understood.   The timing of emissions can be very
important to grid modeling studies.   Finally,  up-to-date land use
data are not readily available.   BEIS uses county-level land use
data extracted from the Oak Ridge National Laboratory's
GEOECOLOGY data base, which was  developed between 1970 and 1980
(Olson et al.,  1980).   Despite these limitations,  BEIS represents
the state of the art  for  quantifying biogenie emissions. Because
of the importance of  biogenie emissions,  BEIS should be used to
incorporate these.emissions in air quality modeling exercises.
     ...  w -. •• . 4  <«&. «• y. VJ "^-i A,^ •• <"v^. w '•->"•%. v*'%fc v* vXrvy^ft1 \ Xjl^ •$• \ lstlcn
projections^ may-be ^aeBir^pa^^ere^arainat'ic.'"changes iti\ landsXuse.
are forecasted*   For'"example, "the clearing "of forested'land'to
produce a reservoir could  reduce biogenie emissions by up to
25 Ib/hr/square  mile.   BEIS includes an  option that allows the
use of grid or  county-specific land use  areas.   Predictions of
land use changes  can be obtained from local and state planning
agencies.
                                92

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IX QUALITY ASSURANCE PROCEDURES


     A. INTRODUCTION

     1. Definition of Quality Assurance

     Quality assurance  (QA) and quality control (QC) have been
defined and interpreted in many ways.  EPA's Quality Assurance
Handbook  (U.S. EPA, 1984) differentiates between the two terms by
stating that quality control is "the operational techniques and
the activities which sustain a quality of product or service,•
whereas quality assurance is "all those planned or systematic
actions necessary to provide adequate confidence that a product
or service will satisfy given needs."  Quality control may also
be understood as "internal quality control," namely, routine
checks included in normal internal procedures (e.g., periodic
calibrations, duplicate checks, split samples).  Quality
assurance may be viewed as "external quality control," or those
activities that are performed on a more occasional basis, usually
by a person outside the normal routine operations (e.g., on-site
system surveys, independent performance audits).  For the
purposes of this document, QA is used collectively to include all
of the above meanings of both quality assurance and quality
control.

     Other documents pertaining to SIP development QA have been
issued by the EPA (U.S. EPA,  1988 and 1989) .  An additional
document on quality review guidelines will be issued in July
1991.  Prior to finalizing projection inventory QA procedures, an
agency should consult and coordinate QA activities on the
baseline inventory.

     2. Purpose of Quality Assurance

     Implementation of QA prpcedures is important for ensuring
that results are of known data quality and are of adequate
quality for the technical decision to be made.  .It is therefore
important to define and understand the limits of the data to be
used.  This document deals with the development of data which
will be utilized to develop and implement control strategies that
must be effective in bringing an area into compliance with the
NAAQS.  Information used in this phase of the SIP development
should be as accurate as possible to ensure that the control
strategies will be effective.  Errors can be introduced during
the analysis, but the implementation of QA procedures can help to
identify and reduce the impact of these errors.  This document
outlines procedures that can be used to uncover potential errors
in the development of projection inventories.  The procedures
outlined below include the following steps and methods to fix
them.
                              .. 93

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     B. DESCRIPTION OF TASKS

     1. Types of QA Procedures

     There are several procedures that should be employed during
the development of projection year inventories.  These procedures
can be broken down into the following categories: manual review,
computer-assisted review, development and use of QA checklists,
understanding chain of custody, and implementation of audits.

     Manual review should be limited to those activities that can
not be automated.  This includes consistency checks from one
system to another, such as checking the growth factors utilized
to ensure consistency with other growth factors that may be
available.  These other growth factors may not be suitable for
use in this application (due to limited source category coverage
or data format incompatibilities),  but they can be manually
reviewed to ensure that the general growth assumptions are
consistent.  Manual review also includes procedures requiring
intellect.  This includes understanding and making decisions
regarding the reasonableness of the results.

     Computerized checks can be developed to fully utilize the
strength of a computer to perform repetitious tasks.  Whenever a
QA procedure is found to be repetitious,  examination of the
procedure often uncovers a way that the computer can be
introduced to perform the work.  Examples include checks for
missing data,  correct units, and "reasonableness" (whether the
value is within a "reasonable" range).  The software developed
for emission inventory projections should include many of these
computerized checks.  If the computer is utilized to develop
preliminary input files,  however, QA procedures should be
developed and applied.  An example would include the use of
spreadsheet software to develop input files.  If possible,  macros
should be developed that check on the accuracy or suitability of
numbers prior to their use in the projection software.  In
addition,  sums of values should be developed for checking against
the projection software files.  This will serve to uncover such
problems as data translation errors and data format problems.

     Checklists are developed and utilized to ensure that
procedures designed and discussed throughout this document are
implemented,  and that results of these QA procedures are utilized
to enhance the credibility of the analysis.  An example QA
checklist is provided in Appendix B.

     Chain of custody is a procedure for preserving the integrity
of a sample or of data (e.g.,  a written record listing the
location of the sample/data at all  times).   Although no sampling
data are involved in the projection inventories, similar
procedures are developed to guard against the introduction of
errors during conversion or transfer of data.  This includes data
integrity checks when data are transferred from one individual or
organization to another.


                                 94

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     Audits serve to introduce an unbiased person or group into
the QA process.  For the purposes of projection inventories,
audits may only be necessary if the agency developing the SIP
uses a method or a data set that is not consistent with the EPA
guidance.  Most agencies lack the resources necessary to use
methods or data that are not provided in thje EPA guidance.  In
the event that the agency does use alternatives, EPA may audit
the material to ensure that it is consistent with EPA policies.

     2. Program Elements Requiring QA

     There are at least four program elements identified for the
development of the projection inventories.  These are planning,
data collection, data analysis,  and data presentation.  As
discussed below, QA should be included in all these elements.

     Implementation of QA procedures should begin in the planning
phase.  The planning phase will identify the SIP development
participants and their responsibilities.  During the planning
phase, the agency should set aside the time and resources
necessary to conduct adequate QA.  Time should be built into the
schedule to allow for the QA, as well as for the correction of
errors that are found.  Resources include manpower (necessary to
conduct manual review),  computer resources (including the machine
and personnel to program the computer),  or dollars to purchase
contractor assistance or alternative data sources.

     Several QA procedures can be used during the data collection
phase.  This includes checks to ensure data quality and
reliability.  During earlier sections of this report, several
sources of input data (specifically growth factors) were
presented.  Each of these sources has a different level of
suitability.  Included in the suitability determination is an
understanding of the data quality and reliability as well as
format,  ease of use,  and cost.   Data quality must be understood
prior to the use of the data.  Collection of appropriate data is
often a resource-intensive effort; therefore, priorities must be
established for collection and QA of data.  These priorities are
often based on the sources' emissions magnitude.  Other
components may influence priority including which source
categories are included in the control strategy, ballpark costs
of individual controls,  and the pollutant species being emitted.
If the pollutant being controlled is also a toxic compound,
additional QA resources may be warranted to ensure high quality
data.

     Data analysis encompasses the procedures and algorithms used
to determine the answer to the initial question (namely, which
control strategies will work given this projection scenario to
allow for attainment of the NAAQS).  - Errors can be introduced
during any phase of the data analysis.  To minimize the
introduction of errors,  several facets of QA can be employed --
                                95

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data validation, computational checks, reasonableness of results,
and interpretation of results.

     Data validation includes procedures for checking against
miscoding data or misusing data.  This would include errors
introduced during the conversion of units or translation from one
system or format to another and transfer'from one group or
individual to another.  In addition, the data may have internal
limitations.  For example, the data may have been developed for a
purpose that might preclude their use in this application.  One
may still choose to use the data, but the limitations it prsents
should be recognized and documented.                  .

     Computational checks are often developed during the software
development phase.  Additional computational checks can be made
at any time, however.  These include comparison of different data
fields to ensure consistency.  For example,  a growth factor
applied to one source category may need to complement another
category.  If population is expected to increase in an area,
there should be a corresponding growth in VMT and industrial
activity.  (A problem may exist if, during the QA process,
population growth was forecasted without considering industrial
growth.)

     Reasonableness of results requires judgement on the part of
the analyst to ensure that the results are logical.  If the
results are not sensible,  research should be conducted until the
analyst is comfortable with the findings and feels confident that
any anomalies can be explained.  In the example presented above,
population could grow and industrial activity could decline if
another type of change could explain the cause of growth.  This
might hold true in an area experiencing growth in the tourist
industry or in the services industry.

     QA should be introduced during the interpretation of
results.   When conclusions are drawn from the data and analyses,
independent review should be performed to ensure that the results
do indeed support the conclusion.  The results should not be
overanalyzed.  This goes hand-in-hand with the initial purpose of
employing QA procedures: to ensure adequate quality of
information for the data upon which the technical decision to be
made is based.

     Finally, the presentation of results can result in errors or
ambiguities.   Data translation procedures should again be checked
at this stage.  This includes preparation of graphical displays
of the data.   Here unit measurements should be double-checked,
and appropriate headings and legends should be created to ensure
that the data are accurately presented.  Again,  results must be
reasonable,  and all data presentation should strive for
interpretability.
                                96

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X DOCUMENTATION
     Documentation requirements for emissions projections will be
consistent with those presented in the documentation chapters of
Emission Inventory Requirements For Ozone State Implementation
Plans  (U.S. EPA, 1991c) and Emission Inventory Requirements For
Carbon Monoxide State Implementation Plans (U.S. EPA, 1991d) for
the base year emission inventories.  In addition to the
documentation requirements identified for the base year emission
inventory, for projections it will be imperative to document the
explicit control technique and control effectiveness values used
in both the base year and future year emission estimates.
Expected changes in activity levels will have to be documented as
well.

     For highway vehicles, an example of the level of detail of
required documentation can be found in the Sec. 187 VMT
Projection Guidance.  It is especially important to detail the
analyses used to estimate changes in vehicle speeds.

     When future year emission estimates are completed,  they will
have to be submitted to EPA in a form compatible with the
Aerometric Information Retrieval System (AIRS).  Specific
requirements will be described in the Reasonable Further
Progress/Emission Tracking Guidance document scheduled for
release in November 1992.
                               97

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98

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                            REFERENCES
Battye et al,  1987:  W.H. Battye, M.G. Smith, and M. Deese,  "Cost
     Assessment of Alternative National Ambient Air Quality
     Standards for Ozone," Draft Report, prepared by Alliance
     Technology Corporation  (U.S. EPA, Research Triangle Park,
     NC, October 1987).

Battye, 1989:  W.H. Battye,  "ROMNET — Development of a
     Base Year Anthropogenic Emissions Inventory" EPA-450/4-89-
     008, U.S. EPA, Research Triangle Park, NC> May 1989...

BEA, 1990a:  U.S. Department of Commerce, Bureau of Economic
     Analysis, "BEA Regional Projections to 2040, Volume 1:
     States," Washington, DC: U.S. Government Printing Office,
     June 1990.

BEA, 1990b:  U.S. Department of Commerce, "BEA Regional
     Projection to 2040, Volume 2:  Metropolitan Statistical
     Areas," Washington, DC:  U.S. Government Printing Office,
     October 1990.

BEA, 1990c:  U.S. Department of Commerce, Bureau of Economic
     Analysis, "BEA Regional Projections to 2040, Volume 3:  BEA
     Economic Areas," Washington, DC:  U.S. Government Printing
     Office, October 1990.

Branson, 1972:  William H. Branson, "Macroeconomic Theory and
     Policy," Harper & Row, New York, 1972.

CARB, 1990:  California Air Resources Board, "Technical Support
     Document for California Exhaust Emission Standards and Test
     Procedures for 1994 and Subsequent Model Year Utility and
     Lawn and Garden Equipment Engines," December 1990.

EEA, 1988:  Energy and Environmental Analysis,  Inc., "The Motor
     Fuel Consumption Model, Fourth Periodical Report," Prepared
     for Martin Marietta Energy Systems, Inc.,  December 1988.

EPRI, 1986:  Electric Power Research Institute, "TAG - Technical
     Assessment Guide, Volume 1:  Electricity Supply - 1986,"
     Technology and Evaluation Division, EPRI P-4463-SR, December
     1986.

ICF, 1990:  ICF Resources Incorporated, "Comparison of the
     Economic Impacts of the Acid Rain Provisions of the Senate
     Bill. (S.1630) and the House Bill (S.1630)," draft prepared
     for U.S. Environmental Protection Agency,  July 1990.

Jacobs et al., 1991:  Paul E. Jacobs, Donald J. Chernin, and John
     D. Kowalski, "California's Heavy-Duty Vehicle Smoke and
     Tampering Inspection Program," Paper No. 91-96.4, Presented
                              .  99

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                      REFERENCES (continued)


     at the Air and Waste Management Association's  84th Annual
     Meeting and Exhibition, Vancouver, B.C., June  1991.

Miaou, 1990:  Miaou,  Shaw-Pin,  "Study of'Vehicle  Scrappage
     Rates," Oak Ridge National Laboratory, Oak Ridge,  TN,  August
     1990.

National Research Council, 1985:  Transportation  Research Board,
     "Highway Capacity Manual," Special Report 209,  1285.

Olson et al., 1980:   R. Olson, C. Emerson, and M. Nunsgesser,
     " GEOECOLOGY:  A  County-Level Environmental Data Base for  the
     Conterminous United States," ORNL/TM-7531, Oak  Ridge
     National Laboratory, Oak Ridge, Tennessee, 1980.

Pechan, 1988:  "National Assessment of VOC, CO, and  NOX Controls,
     Emissions, and Costs," E.H. Pechan and Associates,  Inc.,
     Springfield,  VA  (prepared for Office of Policy  Planning and
     Evaluation, U.S. EPA, Washington, DC) September 1988.

Pechan, 1991:  E.H. Pechan & Associates, Inc., "Clean Air Act
     Amendments of 1990 — Ozone Nonattainment Control  Cost
     Estimates," Springfield, VA, (in press), U.S. EPA,
     Research Triangle Park,  NC, 1991.

Pierce, 1991:  Thomas Pierce and Keith Baugues, "User's Guide  to
     the Personal Computer Version of the Biogenic Emissions
     Inventory System (PC-BEIS),• EPA-450/4-91-017,  U.S.  EPA,
     Research Triangle Park,  NC, July 1991.

Possiel,  1991:  Norman C. Possiel et al.  "Regional  Ozone
     Modeling for Northeast Transport," EPA-450/4-91-002a,
     U.S.  EPA, Research Triangle Park, NC, 1991.

Saeger, 1989:  M.  Saeger et al., "NAPAP Emissions Inventory
     (Version 2.0): Development of the Annual Data and Modelers'
     Tapes," EPA-600/7-89-012a, U.S. EPA,  Research Triangle Park,
     NC,  November 1989.

SCAG, 1989:  Southern California Association of Governments,
     "Baseline Projection:  Background Information for the
     Development of the SCAG-87 Growth Forecast Policy"
     (Appendix III-D), Los Angeles,  CA,  March 1989.

SCAG, 1991:  Southern California Association of Governments,
     "1991 Air Quality Management Plan,  South Coast Air
     Basin," for the South Coast Air Quality Management District
     (SCAQMD),  May 1991.
                               100

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                      REFERENCES (continued)


SCAQMD,  1989:   South Coast  Air Quality Management District,
      •Future Baseline Emissions  South Coast Air  Basin"  (Appendix
      III-B), El Monte,  CA,  March 1989.

Standards of Performance  for New Stationary Sources:  New
      Residential Wood Heaters, 53 FR 5860, February 26,  1988.

U.S.  Congress,  Office of  Technology Assessment,  "Catching Our
      Breath: Next  Steps for Reducing Ozone, *• OTA-O-412,
      Washington, DC:  U.S. Government Printing Office, July 1989.

U.S.  DOE, 1979:  "Industrial Sector Technology Use Model,
      Industrial Energy Use  in the United States, 1979-2000,"
      Volume I  - Primary Model Documentation, DOE/FE/2344-1, U.S.
      Department of Energy,  Washington, DC, October 1979.

U.S.  DOE, 1989:  U.S.  Department of Energy, "Form EIA-767,  Steam-
      Electric  Plant  Operation and Design Report  1989," Energy
      Information Administration, 1989.

U.S.  DOE, 1990:  U.S.  Department of Energy, "Inventory of Power
      Plants in the United States - 1989," DOE/EIA-0095 (89) ,.
      Office of  Coal,  Nuclear, Electric and Alternate Fuels,
      Washington, DC,  September 1990.

U.S.  DOT, 1987:  U.S.  Department of Transportation, Federal
      Highway Administration, "The Highway Performance Monitoring
      System Analytical  Process, Volume II, Technical Manual,
      Version 2.1," December 1987.

U.S.  EPA, 1984:  "Quality Assurance Handbook for Air Pollution
      Measurement Systems,  Volume I -- Principles," EPA-600/9-76-
      005, Research Triangle Park, NC, December 1984.

U.S.  EPA, 1989:  "Procedures For Estimating And Applying  Rule
      Effectiveness. In  Post-1987 Base Year Emission Inventories
      For Ozone And Carbon Monoxide State Implementation Plans,"
     June,  1989.

U.S. EPA, 1990a:   "AIRS Facility Subsystem Source Classification
     Codes and Emission Factor Listing for Criteria.Air
      Pollutants,"  EPA-450/4-90-003,  U.S. EPA,  Research Triangle
      Park,  NC,  March  1990.

U.S. EPA, 1990b:   "Compilation of Air Pollutant Emission  Factors,
     Volume I:   Stationary  Point and Area Sources," (AP-42)
     Fourth Edition, Supplement C,  Research Triangle Park, NC,
     September 1990.
                               101

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                      REFERENCES (continued)


U.S. EPA, 1991a:  "Implementation Strategy for the Clean Air Act
     Amendments of 1990," Office of Air and Radiation, January
     15, 1991.

U.S. EPA, 1991b:  OAQPS, "Procedures for the Preparation of
     Emission Inventories for Carbon Monoxide and Precursors of
     Ozone, Volume I," Research Triangle Park, NC, May 1991.

U.S, EPA, 1991c:  OAQPS, "Emission Inventory Requirements For
     Ozone State Implementation Plans," EPA-450/4-91-010,
     Research Triangle Park, NC, March 1991.

U.S, EPA, 1991d:  OAQPS, "Emission Inventory Requirements For
     Carbon Monoxide State Implementation Plans," EPA-450/4-91-
     011, Research Triangle Park, NC, March 1991.
                               102

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                           BIBLIOGRAPHY


               The purpose of this section is to identify and
provide bibliographic citations of currently existing EPA
guidance materials for the development of ozone and carbon
monoxide emission inventories and emission, projections.  The list
of existing inventory guidance is divided into four categories:
ozone inventory guidance/requirements, quality assurance/
inventory review guidance, emission factors/models, and general
inventory guidance.  Projection models are listed in a fifth
section.  If updates to an existing document are planned, this is
indicated in the citation.


Ozone Inventory Guidance/Requirements

1.        Emission Inventory Requirements For Ozone State
          Implementation Plans. EPA-450/4-91-010, U.S.
          Environmental Protection Agency, Office of Air Quality
          Planning and Standards, Research Triangle Park, NC,
          April 1991.

2.        Emission Inventory Requirements For Carbon Monoxide
          State Implementation Plans.  EPA-450/4-91-011, U.S.
          Environmental Protection Agency, Office of Air Quality
          Planning and Standards, Research Triangle Park, NC,
          March 1991,

3.        Procedures For The Preparation Of Emission Inventories
          For Carbon Monoxide And Precursors Of Ozone Volume II;
          Emission Inventory Requirements For Photochemical Air
          Quality Simulation Models.  EPA-450/4-91-014, U.S.
          Environmental Protection Agency, Office of Air Quality
          Planning and Standards, Research Triangle Park, NC, May
          1991.

4.        Procedures For Emission Inventory Preparation,  Volume
          IV:   Mobile Sources.  EPA-450/4-81-026d, U.S.
          Environmental Protection Agency, Office of Air Quality
          Planning and Standards, Research Triangle Park, NC,
          July 1989 (also listed below under General Inventory
          Guidance).  [Revised version to be completed in August
          1991.]

5.        Example Emission Inventory Documentation For Post-1987
          Ozone State Implementation Plans (SIPs).  EPA-450/4-89-
          018,  U.S.  Environmental Protection Agency, Office of
          Air Quality Planning and Standards,  Research Triangle
          Park, NC,  October 1989.
                               103

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                     BIBLIOGRAPHY (continued)
6.         Procedures  For Estimating And Applying  Rule
           Effectiveness In  Post-1987 Base Year  Emission
           Inventories For Ozone And Carbon Monoxide  State
           Implementation Plans, U.S. Environmental Protection
           Agency, Office of Air Quality Planning  and Standards,
           Research Triangle Park, NC, June 1989.

7.         SIP Air Pollutant Inventory Management  System (SAMS)
           Version 4.0 and SAMS User's Manual, U.S. Environmental
           Protection  Agency, Office of Air Quality Planning and
           Standards,  Research Triangle Park, NC,  March  1991.


Quality Assurance/Inventory Review Guidance

8.         Guidance For The Preparation Of Quality Assurance Plans
           For O,/CO SIP Emission Inventories,  EPA-450/4-88-023,
           U.S. Environmental Protection Agency, Office  of Air
           Quality Planning and Standards, Research Triangle Park,
           NC, December 1988.

9.         Quality Assurance Program For Post-1987 Ozone And
           Carbon Monoxide State Implementation  Plan  Emission
           Inventories. EPA-450/4-89-004, U.S. Environmental
           Protection  Agency, Office of Air Quality Planning and
           Standards,  Research Triangle Park, NC, March  1989.

10.        Quality Review Guidelines For Post-1987 State
           Implementation Plan (SIP)  Base Year Emission
           Inventories  (Draft), U.S.  Environmental Protection
           Agency, Office of Air Quality Planning  and Standards,
           Research Triangle Park,  NC,  February  1990.  [Final
           version to  be completed in July 1991.]

11.        Guidelines  For Review Of Highway Source Emission
           Inventories  For 1982 State Implementation  Plans.  EPA-
           450/12-80-002, U.S.  Environmental Protection  Agency,
           Research Triangle Park,  NC,  December  1980.  [This
           document will be superseded by the Quality Review
           Guidelines  document above,  to be completed in July
           1991.]


General Inventory Guidance

12.        Procedures  For Emission Inventory Preparation.  U.S.
           Environmental Protection Agency,  Office of  Air  Quality
           Planning and Standards,  Research Triangle,  Park,  NC:
                               104

-------
                     BIBLIOGRAPHY (continued)
            a. Volume I:  Emission Inventory Fundamentals. EPA-
               450/4-81-026a, September 1981.

            b. Volume II:  Point Sources. EPA-450/4-81-026b,
               September 1981.

            c. Volume III:  Area Sources. EPA-450/4-81-026c.
               September 1981.         '   .  -   •

            d. Volume IV:  Mobile Sources. EPA-450/4-81-026d
               (Revised), July 1989.   [Updated version to be
               completed in August 1991.]

            e. Volume V:  Bibliography. EPA-450/4-81-026e,
               September 1981.


Emission Factors/Models

13.        Compilation Of Air Pollutant Emission Factors, Volumes
          I and II and its supplements, Fourth Edition, AP-42,
          U.S. Environmental Protection Agency, Office of Air
          Quality Planning and Standards, Research Triangle Park,
          NC,  September 1985.

14.        AIRS Facility Subsystem Source Classification Codes
          (SCCs)  And Emission Factor Listing For Criteria
          Pollutants. EPA-450/4-90-003, U.S. Environmental
          Protection Agency/  Office of Air Quality Planning and
          Standards,  Research Triangle Park, NC, March 1990.

15.        User's Guide to MOBILE4 (Mobile Source Emission Factor
          Model),  EPA-AA-TEB-89-01,  U.S. Environmental Protection
          Agency,  Office of Mobile Sources,  Ann Arbor, MI,
          February 1989.  [Revised version of MOBILE4 and
          documentation to be completed in July 1991.]

16.        Surface Impoundment Modeling System (SIMS)  Version 2.0
          User's Manual. EPA-450/4-90-019a,  U.S. Environmental
          Protection Agency,  Research Triangle Park,  NC,
          September 1990.

17.        Background Document For Surface Impoundment Modeling
          System (SIMS)  Version 2.0.  EPA-450/4-90-019b, U.S.
          Environmental Protection Agency, Research Triangle
          Park,  NC,  September 1990.
                               105

-------
                     BIBLIOGRAPHY (continued)
Projection Models

          For the most part, the projection models listed below
are designed for national or regional  (state-level) analyses.
Even so, state analysts may be interested in reviewing these
models for general information when planning their own analyses.

18.       Capone, Ronald L., May, Elizabeth H., and Christopher
          J. Peterson, Advanced Utility Simulation"Model (AUSM)
          User's Guide Version 3.0. EPA-600/8-88-071j, Science
          Applications International Corporation, prepared for
          U.S. Environmental Protection Agency, October 1988.

19.       ICF Incorporated, "ICF's Integrated Coal and Electric
          Utility System of Models," Prepared for U.S.
          Environmental Protection Agency* ICF Incorporated,
          Washington, DC, April 1987.

20.       Pechan & Associates,  "User's Guide for the Prototype
          State Emission Reduction and Cost Analysis Model for
          Volatile Organic Compounds (State ERCAM-VOC)," E.H.
          Pechan & Associates,  Inc., Springfield, VA, October
          1990.

21.       Hogan,  1988:  Hogan,  Tim, "Industrial Combustion
          Emissions Model (Version 6.0) User's Manual," Energy
          and Environmental Analysis, Inc.,  prepared for U.S.
          EPA,  Air and Energy Engineering Research Laboratory,
          EPA-600/8-88-007a, February 1988.

22.       Saricks,  Christopher L.,  "The Transportation Energy and
          Emissions Modeling System (TEEMS): Selection Process,
          Structure,  and Capabilities," ANL/EES-TM-295, Argonne
          National Laboratory,  November 1985.

23.       A Progection Methodology For Future State Level
          Volatile Organic Compound Emissions (VOCM)  From
          Stationary Sources Version 2.0.  EPA-600/8-88-090,  U.S.
          Environmental Protection Agency/ Air and Energy
          Engineering Research Laboratory, Research Triangle
          Park,  NC,  July 1988.
                               106

-------
                 APPENDIX A

PROJECTED ELECTRIC GENERATING UNIT ADDITIONS
              (U.S. DOE, 1990)

-------
  Table 21.  Projected  Electric Generating Unit Additions, by
                                                       Company,
emu rumi, 19
State
Plant (County)
Alabama
Alabama Electric Coop Inc
Future Fossil (UNKNOWN) 	 	 	
MdntosrvCAES (Washington) 	 	 	
McWilhams (Cnvington) .. ., 	 	 	

9v- 1999, a;
1 Unit !
| " !
1
- 	 1
2
CT1
CT2
CT3
4
* vi wcemm
Scheduled !
Current/Original j
Jun 98/Jun 95
Jun 91 /Jun 93
Jun 96/Jun 94
Jun 98/Jun 93
Jun 98/Jun 94
Jun 99/Jun 99
Jun 94/Jun 94
si 0 1, i;
Generator
Capacity
1250
110.0
110.0 • .
750
75.0
75.0
100.0
9Q9
Summer
(capability
(megawatt*)
125.0
89.7
89.7
'• 61 7
61.7
61.7
82.5

Unit
I Type'
ST
*GT
»GT
GT
GT
GT
CT

Energy ,
Source' j
LIG
Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas

Unit
Statua
PL
CO
PL
Pi
PL
PL
PL
   Alabama Power Co
    James H Miller Jr (Jefferson)	

 Alaska

   Cordova Electric Coop Inc
    Humpback Creek (Vaktez-Cordova).
  Pelican Utility Co
    Pelican (UNKNOWN) —
 Arizona

  Arizona Public Service Co
    Gila Bend (Maricopa) .......
  Bureau of Reclamation
   Waddell (Maricopa)	

  Century Power Corp
   Springerville (Apache) .
  Colorado Rrver Indian Irr Proj
   Headgate Rock (UNKNOWN) .
Arkansas

  Arkansas Electnc Coop Corp
   NA 1 (Conway)	
   NA 2 (UNKNOWN) 	_	

California

 California Dept-Wtr Resources
   Devil Canyon (San Bernardino)
   Mohave Siphon Power (San Bernardino) ....
 Los Angeles City ol
   Harbor Gen Station (Los Angeles).
 Metropolitan Water District
  Etrwanda (San Bernardino).
 Pacific Gas & Electric Co
  PVUSA 2 (Yoto) 	
  PVUSA 3 (San Luis Obispo)...
  Salt Springs Unit 1 (Amador) .
     1
     2
     3
   ICS
  GT1
  GT2
  GT3
  GT4
  PS1
•0002
    3
   10
    1
    1
 HY3
            Mar 91/Jun 81
 Jun  90/Jan 88
 Jun  90/Jan 88
 Jun  90/Jan 88
           Jun 90/Jun 90
Jun  97/May 92
 Jun 97/Jun 97
 Jun 99/Jun 99
 Jun 99/Jun 99
          May  94/May 91
 Mar 90/Jun 87
 Jun 95/Jun 90
                91 /   91
                91/   91
                91 /   91
          May 93/May 93
          Jun 93/Jun  93
            Jul 93/Jul 93
          Jun 99/Jun  99
          Dec 91/Sep 91
          Dec 91/Oec 91
          Feb  94/Oct 93
          May 94/Feb 94
          Aug 94/Jun 94
          Jan 95/Jan 95
           Jul 93/Jun 86
Jan 92/Jan 90
Jan 92/Jan 91
Jun 94/Jan 87
                             705.5
   £
   £
 •75.0
 75.0
 75.0
 75.0
                             150.0
397.0
397.0
                     6.2
                     6.2
                    10.8
                    10.8
                    10.8
                   100.0
                   78.4
                   78.4
                   10.8
                   10.8
                   10.8
                            240.0
                             26.5
 1.0
 1.0
 6.0
                                          667.0
    .5
    JS
    2
                                             .4
 61.7
 61.7
 61.7
 61.7
                                          153.4
360.0
360.0
               6.3
               6.3
               6.3
                                                                                      11.2
                                                                                      11.2
                                                                                      11.2
                                                                                      82.5
             87.8
             87.8
             11.2
             11.2
             11.2
                                                                                    191.1
                                                                                     28.5
 1.0
 1.0
 6.1
                                                        ST
 HC
 HC
 HC
 GT
 GT
 GT
 GT
                                                       HR
 ST
 ST
             HC
             HC
             HC
                          HC
                          HC
                          HC
                          CT
             HC
             HC
             HC
             HC
             HC
                                                      CW
                                                                                                  HL
SP
SP
HC
                                                                   BIT
  Water
  Water
  Water
                                                                  FO2
Nat Gas
Nat Gas
Nat Gas
Nat Gas
                                                       Water
   SUB
   SUB
           Water
           Water
           Water
                       Water
                       Water
                       Water
                     Nat Gas
          Water
          Water
          Water
          Water
          water
                                                                                                            WH
                                                                Water
   Sun
   Sun
 Water
                                                                              CO
CO
CO
CO
                                                                             CO
 PL
 PL
 PL
 PL
                                                                    PL
CO
CO
               PL
               PL
               PL
                        PL
                        PL
                        PL
                        PL
              CO
              CO
               PL
               PL
               PL
                                                                                                                         PL
                                                                                                                         PL
PL
PL
PL
                                                             A-l

-------
Taoie zi. rrojeciea tuecxnc taeneraung unn Maarao
and Plant, 1990-1999, as of December 31,
State ,._., Scheduled Generato
Company „ Completion Date Nameptat
Plant (County) Currant/Original Capacity
CaHfomia
Pacific Gas & Electric Co
Unid PG&E Hydro 94 (UNKNOWN) 	 1 Jan 94/Jan 90 20.1
Unid PG&E Hydro 96 (UNKNOWN)' 	 NA1 Jan 98/Jan 91 £1
Unid PG&E Hydro 97 (UNKNOWN) 	 NA1 Jan 97/Jan 92 23
West Point (Ama*y) ? "«r ai/j«n a? 7 o
Wise 2 (PlaiT**) 	 NA1 Jmn aa/Jan BS 3.O
Redding City of
Lake Red Bluff (Tf*m™«) < J"1 aa/Jul as 4.O
2 Jut 99/Jul 99 4.0
Lake Redding (Shasta) ,-. 	 ,„-- 1 J«* aa/Jtrf flB 5_o
2 Jul 98/Jul 98 S.O
3 Jul 98/Jul .98 S.O
Spring Creek (Shasta) ' **«y as/May as so.o
. 2 May 9S/May 95 25.0
*j May 95/May 95 2S.O
Colorado
Colorado Springs City of
NbtOfl (WN/""A/N) ' *f aa/Apr a9 ' 7S O
Stanley Canyon (UNKMr>WN) 1 s»p a*/s«r» a4 oo o
Delaware
Delmarva Power 4 Light Co
Hay Road (New Castle) 	 3 May 93/May 93 100.0
4 May 94/May 94 150.0
Florida
Florida Power & Light Co
Martin (Martin) _ 	 _ 	 	 	 . 1GT1 Dec 93/Dec 93 148.6
1GT2 Dec 93/Dec 93 148.6
1ST1 Dec 93/Dec 93 155.0
2GT1 Dec 94/Dec 94 148.6
2GT2 Dec 94/Dec 94 148.6
2ST1 Dec 94/Dec 94 155.0
3GT1 Dec 9S/Dec 95 148.6
3GT2 Dec 95/Dec 95 148.6
3GT3 Dec 9S/Dec 95 148.6
3GT4 Dec 95/Dec 95 148.6
3ST1 Dec 95/Dec 95 153.9
3ST2 Dec 95/Dec 98 153.9
Florida Power Corp
Debary (Voiu-ua) 	 10 Nov 92/Nov 92 84.0
7 Nov 92/Nov 92 84.0
8 Nov 92/Nov 92 84.0
9 Nov 92/Nov 92 84.O
Intercession Oty (Osc»ola) . 10 Nov 93/Nov 93 840
7 Nov 93/Nov 93 84.0
6 Nov 93/Nov 93 84.0
9 Nov 93/Nov 93 84.0
NA 1 (UNKNOWN) 	 1 Nov 96/Nov 96 144.0
2 Nov 96/Nov 96 144.0
3 Nov 96/Nov 96 144.0
NA 2 (UNKNOWN) . 	 1 Nov 97/Nov 97 216.4
3 Nov 99/Nov 99 '216.4
Gainesville Regional Utilities
Deerhaven (Alachua) NA1 Jun 98/Jun 98 35 0
NA2 Jun 99/Jun 99 35.0
Gull Power Co
Caryville (Jackson) 1 May 94/May 95 1260
2 May 97/May 97 126.0
ns, uy s»iaie, company,
1989 (Continued)
» i**n^i«ttn Unit CntTQy Unit

-------
  Table 21.  Projected Electric Generating Unit Additions, by State, .Company,
                 and Plant, 1990-1999, as of December 31,  1989 (Continued)
                   State
                  Company
                Ptaiil (County)
Unit
 ID
Completion Dfttt
Cunvnt/OrtgfcMl
                          Capacity
            Summer
           CapabUty
          
-------
Table 21.  Projected Electric Generating Unit Additions, by State, Company,
          and Plant, 1990-1999, as of December 31,1989 (Continued)
State
Company
Plant (County)
Indiana
Public Service Co ol IN Inc
NA 1 (UNKNOWN) 	




Southern Indiana Gas ft Etec Co
A 8 Brown (Posey) 	 	 	
Iowa
Graettinger City of
Graettinger (Pato Alto) 	
Interstate Power Co
Mason City (Cerro Gordo)

Iowa Electric Light & Power Co
Anamosa (Joni?5)
Iowa Power Inc
Pleasant Hill (Polk) 	 	

Iowa Southern Utilities Co
Grinnell (Poweshiek) _ .. 	

NA 1 (UNKNOWN) 	 	 	

Kansas
Kingman City of
Kingman (Kingman) 	 	 	 	
Mulvane City of
Mulvane (Sedgwick) ._ 	 	

Russell City of
Russell (Russell)

Sabetha City of
Sabetrta (Nema.^a) 	
Wamego City of
Wamego (Pottawatomie) ' .
Kentucky
Kentucky Utilities Co
NA 1 (UNKNOWN)




Louisville Gas & Electnc Co
Cane Run (Jetterson) 	
Trimble County (Trimble)
Vanceburg City ol
Meldahl Gen Station (Bracken) 	
Scheduled :
10 Current/Original .


	 1 Apr 95/Apr 95
2 Apr 95/Apr 95
3 Apr 95/Apr 95
4 Apr 97/Apr 97
5 Apr 99/Apr 99

	 4 Jun »1/Apr 91


	 5 May 90/May 90

1 Jun 91 /Jan 91
2 Jun 91 /Jan 91

MC!1 J*t* Qn/ft«w» AQ

1 Jun 90/May 90
. 2 Jun 90/May 90

1 Aiig fln/fiep 69
Z Aug 90/Sep 89
1 May 93/May 93
2 May 97/May 97


	 • 9 Jun 91 /May 90

7 Jan 91 /Jan 90
8 Jan 91 /Jan 90

	 11 Dec 90/Jan 90
12 Dec 90/Jan 90

	 :.... IC10 Jun 90/Jun 90

.... .. NA1 Jun 94/Jun 91


1 Apr 93/Apr 93
2 Apr 95/Apr 95
3 Apr 96/Apr 96
4 Apr 98/Apr 98
5 Apr 99/Apr 99

	 ; 12 Jul 97/Jul 97
1 Oct 907 Aug 81

	 1 Seo 92/Jun 89
Generator
Capacity !
"•

130.0
130.0
130.0
130.0
130.0

68.2


1.1

30.0
30.0

JQ

41.4
41.4

22J
223
50.0
50.0


6.0

.6
.6

3.6
3.6

2.5

2.4


156.0
156.0
156.0
156.0
156.0

75.0
566.1

23.4
&Mmer :
(megawatts) :


105.6
105.6
• .105.6
105.6
105.6

723


1.0

252
25.2

2

34.5
34.5

16.8
18.8
41.5
41.5


5.6

.5
.5

3.4
3.4

2.3

2.2


126.3
126.3
126.3
126.3
126.3

61.7
480.0

25.1
Unit
Type'


GT
GT
GT
GT
GT

GT


1C

GT
GT

HC

GT
GT

GT
GT
GT
GT


1C

1C
1C

1C
1C

1C

1C


GT
GT
GT
GT
GT

GT
ST

HC
Energy
Source*


Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas

Nat Gas


FO2

FO2
F02

Water

FO2
F02

Nat Gas
Nat Gas
Nat Gas
Nat Gas


FO2

ro;
FO2

Nat Gas
Nat Gas

FO2

Nat Gas


Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas

FO2
BIT

Water
Unit
Statut


PL
PL
PL
PL
PL

.CO


CO

CO
CO

CO-

CO
CO

CO
CO
PL
PL


PL

CO
CO

CO
CO

CO

PL


PL
PL
PL
PL
PL

PL
CO

PL
                                      A-4

-------
  Table 21.  Projected Electric Generating Unit Additions, by State, Company,
                 and Plant,  1990-1999, as of December 31,1989 (Continued)
                   State
                 Company
               Plant (County)
Unit
 ID
   Sctodutad
Completion Date
Currant/Original
Generator
NamepUte
 Capacity
  Summer
 CapaMKy
(megawatts)
 Unit
Type'
 Energy
Source1
 Unit
Status
  Kentucky

   Vanceburg City ol



  Maine

   Bangor Hydro-Electric Co
    Basin Mills (Penobscot) .
    Miltord (Penobscot) 	
    Veazte C (Penobscot)...
   Central Maine Power Co
    Chartes E Monty (Androscoggin).
 Maryland
    1
    2
    3
    7
    •1
 NA1
 NA2
          Sep 92/Jun 89
          Sep 92/Jun 89
  Apr  99/Nov  91
  Apr 99/Jan  97
  Apr 99/Apr  99
  Jan 93/Jan  93
  Apr  96/Nov  90
  Sep 90/Apr 87
  Sep 90/Apr 87
                     23.4
                     23.4
   12.0
   MO
   12.0
    1.2
    8.0
   12.5
   12.5
  Baltimore Gas & Electric Co
    Brandon Shores (Anne Arundel)	       2     Jon 91/Apr 85    685.1
    Pern/man (Harford) •.				      51     Jun 95/Jun 96    170.0
                                             52     Jun 96/Jun 97    170.0
                                             61     Jun 977Jun 97    170.0
                                             62     Jun 98/Jun 98    170.0

  Oelmarva Power & Light Co
    Nanucoke (Dorchester)			—     ST1      May 99/May 67    150.0

  Easton Utilities Comm
    Easlon 2 (Talbot)	-		      24     May 93/Dec 91      6.3
                                            24A      May 93/Oec 91      6.3
                                             25     May 96/Oec 95     15.0
                                             28     May 99/May 99     20.0

  Potomac Electric Power Co
    Chalk Point (Prince Georges)	-	_	_..     GTS      Jun 91/Jun 91      84.0
                                            GT4      Jun 91/Jun 91      84.0
                                            GTS      Jun 91/    90     104.0
                                            GT6      Jun 91/Jun 91     104.0
   Coal Gas CC 1 (Montgomery)	     CT1           92/   94    127.0
                                            CT2           93/   95    127.0
   Coal Gas CC 2 (Montgomery)	_     CT3           96/   96    127.0
                                            CT4           98/   97    127.0
   SMECO CT (Prince Georges) 	     "1      Jun 90/Jun 90      84.0

Massachusetts

  Peabody City ol
   Waters River (Essex)	_	      2     Dec 90/Dec  90      36.4

Minnesota

  Northern Slates Power Co
   Future Base (UNKNOWN)	      1     May 98/May 98     400.0
   NA 1 (UNKNOWN) 	      1     May 94/May 94     100.0
                                             2     May 97/May 97     100.0

Mississippi

  South Mississippi El Pwr Assn
   Moselle (Jones)	       4      Jun 93/Jun 93     80.0
                                             5      Jun 94/Jun 94     40.0
                                             6      Jun 97/Jun 97     80.0
                                             7      Jun 98/Jun 98     40.0
               25.1
               25.1
    12.5
    12.5
    125
     1.1
     8.2
    13.1
    13.1
                                       640.0
                                       137.3
                                       137.3
                                       137.3
                                       137.3
                                       150.0
                                         S.9
                                         5.9
                                        14.1
                                        18.8
                                        68.9
                                        68.9
                                        84.9
                                        84.9
                                       103.8
                                       103.8
                                       103.8
                                       103.8
                                        68.9
                                       30.4
                                      400.0
                                       81.7
                                       81.7
                                       66.6
                                       34.3
                                       66.6
                                       34.3
                HC
                HC
   HC
   HC
   HC
   HC
   HC
   HC
   HC
                                            ST
                                            GT
                                            GT
                                            GT
                                            GT
                                                    ST
                                             1C
                                             1C
                                             1C
                                             1C
                                            GT
                                            GT
                                            GT
                                            GT
                                            CT
                                            CT
                                            CT
                                            CT
                                            GT
                                                   GT
                                            ST
                                            GT
                                            GT
                                           CT
                                           CW
                                           CT
                                           CW
             Water
             Water
    Water
    Water
    Water
    Water
    Water
    Water
    Water
                                      BIT
                                  Nat Gas
                                  Nat Gas
                                  Nat Gas
                                  Nat Gas
                                                               BIT
                                     F06
                                     FO6
                                     F06
                                     FO6
                                  Nat Gas
                                  Nat Gas
                                     F02
                                     FO2
                                     FO2
                                     FO2
                                     FO2
                                     FO2
                                     F02
                                                           Nat Gas
                                    Coal
                                 Nat Gas
                                 Nat Gas
                                 Nat Gas
                                    WH
                                 Nat Gas
                                    WH
                 PL
                 PL
     PL
     PL
     PL
     PL
     PL
    CO
    CO
                                     CO
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL


                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                    CO
                                                                         PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                     PL
                                                          A-5

-------
  Table 21.  Projected Electric Generating Unit Additions, by State, Company,
                 and Plant, 1990-1999, as of December 31,1989 (Continued)
                   Stau
                 Company
               Plant (County)
UnN
     j
CocnpwQofi Dtrt0
Currant/Original
                         NaRMptata I  CapabMty
                          Capacity  I (megawatt*)
                                                  UnM
                                                  Energy
                                                 Sourot'
                                            Unn
                                           SUrtM
  Mittouri
   Empire District Electric Co
    Empire Energy Center (Jasper).
   Kansas City Power & Light Co
    Combustion Turbine 1 (Jackson).
    Combustion Turbine 2 (Jackson).
    Combustion Turbine 3 (Jackson).
    latan (Plane)	
  Springfield City of
    James River (Greene).
    NA 1 (UNKNOWN)	
  St Joseph Light & Power Co
    Lake Road (Buchanan)	
  Union Electric Co
    NA 1 (UNKNOWN) .:	
  UtiliCorp United Inc
   RG 1 & 2 (Cass)	
  NA2
  NA3
    3
    4
  NA4
  HAS
  MAS
  NA7
    1
    2
    3
    2
 GT2
    1
  Jun 96/Jun 95
  Jun 99/Jun 95
  Jun 95/Jun 02
  Jun 97/Jun 97
 Jun 96/Jun 96
 .Jun 97/Jun 97
 Jun 97/Jun 97
 Jun 99/Jun 99
 Jun 94/Mar 96
 Jun 95/Mar 96
 Mar 96/Mar 96
 Mar 99/May 65
May 92/May 93
 Jun 97/Jun 97
         May 90/May 90
         May 9S/May 95
         May 97/May 97
         May 98/May 98
         May 99/May 99
         Jun 927 Jun 85
         Jun 96/Jun 85
  32JO
  32.0
  7SJO-
  75.0
 105.0
 105.0
 105J3
 105.0
 105.0
 105.0
 105.0
 725.8
  71.4
  SO.O
                    18.6
                    75.0
                    75.0
                    75.0
                    75.0
                    22.0
                    22.0
                                  26J3
                                  26J3
                                  62.6
                                  62.6
                                 85.7
                                 85.7
                                 85.7
                                 85.7
                                 85.7
                                 85.7
                                 85.7
                                500.0
                                 58.8
                                 SOJO
              ISA
              61.7
              61.7
              61.7
              61.7
              18.6
              18.6
  GT
  GT
  CA
  CA
  GT
  GT
  GT
  GT
  GT
  GT
  GT
  ST
 GT
 ST
                                             JE
                                            GT
                                            GT
                                            GT
                                            GT
                                            GT
                                            GT
 Nat Gas
 Nat Gas
 Nat Gas
 Mat Gas
 Nat Gas
 Nat Gas
 Nat Gas
 Nat Gas
 Nat Gas
 Nat Gas
 Nat Gas
   SUB
Nat Gas
   Coal
            F02
         Nat Gas
            FO2
            FO2
            FO2
        Nat Gas
        Nat Gas
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
              CO
               PL
               PL
               PL
               PL
               PL
               PL
 Nebraska

  Omaha Public Power District
   NA 1 (UNKNOWN) 	_..
Nevada
 NA1
 NA2
 May  957   96
May 99/May 89
106.0
106.0
                                 86.5
                                 86.5
 GT
 GT
Nat Gas
Nat Gas
PL
PL
  Nevada Power Co
   dart. (ClaTV)	
   Harry Allen (Dark)
   White fine Siat:on (White Pine)
  10
   9
GT1
GT2
GT3
'GJ4
  •1
  •2
  •3
  •1
  *2
Jun 94/Jun 91
Jun 93/Jun 90
Jun 94/Jun 93
Jun 95/Jun 94
Jun 96/Jun 96
Jun 96/Jun 96
Jun 97/Jun 95
Jun 98/Jun 98
Jun 99/Jun 99
Jun 94/Jun 89
Jun 95/Jun 90
 90.0
 90.0
 78.0
 78.0
 78.0
 78.0
250.0
250.0
250.0
812.0
812.0
                                 74.6
                                 74.6
                                 64.1
                                 64.1
                                 64.1
                                 64.1
                                250.0
                                250.0
                                2SO.O
                                750.0
                                750.0
CW
CW
 GT
 GT
 GT
 GT
 ST
 ST
 ST
 ST
 ST
  WH
  WH
   FO2
   F02
   FO2
   FO2
    BIT
    BIT
    err
    err
    en-
PL
PL
PL
PL
PL
PL
PL
PL
PL
PL
New Hampshire

 Public Service Co ol NH
   Seabrooii (Rockmgham)

New Jersey
 Jersey Central Power&Ught Co
   NA 1 (UNKNOWN) 	
   NA 2 (UNKNOWN) 	
   NA 3 (UNKNOWN) 	
  NA 4 (UNKNOWN)
  NA 5 (UNKNOWN)
        Jan 90/Nov 79
         Jun  94/Jun 94
         Jun  95/Jun 96
         Jun  97/Jun 95
         Jun  97/Jun 96
         Jun  98/Jun 97
        May  96/May 96
        May  96/May 96
                          1.200.0
                  100.0
                  200.0
                  200.0
                  100.0
                  300.0
                  200.0
                  100.0
                             1.150.0
             81.7
            161.0
            160.4
             82.5
            239.4
            160.4
             82.5
                                                   NP
                                            GT
                                            GT
                                            CT
                                            CA
                                            GT
                                            CT
                                            CA
                                                           Uranium
           FO2
        Nat Gas
        Nat Gas
        Nat Gas
        Nat Gas
        Nat Gas
        Nat Gas
                                                                          LP
              PL
              PL
              PL
              PL
              PL
              PL
              PL
                                                        A-6

-------
  Table 21.  Projected Electric Generating Unit Additions, by State, Company,
                 and Plant, 1990-1999, as off December 31,1989 (Continued)
State
Company
Plant (County)
IMI
' ID
Scheduled
Current/Original
• Generator
Nameptate
Capacity
j Summer
! CapaMtty
i (megawatt*)
Unit
Type'
Energy '.
: Source1 '
Untt
Statin
   Jersey Central Power&Light Co
    NA 6 (UNKNOWN)	
   Vmeland City of
    Butter (Cumberland) -
           May 99/May 99
           May 99/May 99
           Jun 94/Jun 93
           Jun 94/Jun 94
           Jun 94/Jun 94
                   200.0
                   100.0
                    35.0
                    16.0
                    50.0
              160.4
               82.5
               30.1
               14.2
               42.4
              CT
              CA
              CT
             CW
              CT
        Nat Gas
        Nat Gas
        Nat Gas
           WH
        NalGas
                PL
                PL
                PL
                PL
                PL
 New York

   Niagara Mohawk Power Corp
    High Dam (Oswego)	
    Hudson Falls (Saratoga)	
    Mechanicvine (Saratoga)	
    Mioetto (Oswego)-
    Oswego Falls West (Oswego).
    South Glens Falls (Saratoga).
    Varick (Oswego).
    Yaleville (St Lawrence)
  Power Authority of State of NY
    Crescent (Albany)	
    Lewtston (Niagara)	

    Vischer Ferry (Saratoga) —
     5
     A
   N1
   N1
     6
     7
     8
   N1
     1
     3
  NA1
  NA2
    13
    14
  NA1
  NA2
Dec 94/Nov 68
Dec 94/Nov 85
Dae 94/May 84
Jan 98/Nov 89
Dae 94/Nov 87
Dec 94/Nov 87
Dec 94/Nov 87
Dec 94/Nov 89
Jan 98/Nov 90
Dec 94/Sep 93
 Jun 90/Jan 86
 Jun 90/Jan 66
 Sep  96/Jul 90
 Nov  96/Jul 90
 Oct 90/Apr 86
 Oct 90/Apr 86
   2.5
  36.1
  12.0
   1.8
   1.9
   1.9
   1.9
  13.8
   4.6
   1.0
   3.0
   3.0
  30.0
  30.0
   3.0
   3.0
   Z5
  393
  123
   1.8
   1.8
   1.8
   1.8
  14.5
   4.6
   1.0
   3.0
   3.0
  30.4
  30.4
   3.0
   3.0
 HC
 HC
 HC
 HC
 HC
 HC
 HC
 HC
 HC
 HC
 HC
 HC
 HR
 HR
 HC
 HC
   Water
   Water
   Water
   Water
   Water
   Water
   Water
   Water
   Water
   Water
  Water
  Water
  Water
  Water
  Water
  Water
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
CO
CO
 PL
 PL
CO
CO
 North Dakota
  Northern States Power Co
   Dakotas (UNKNOWN)	

 Ohio

  Cincinnati Gas & Electric Co
   W H Zimmer (Qermonl)	
   Woodsoate (Butler)	
  Dover City of
   Dover (Tuscarawas)		
 Painesville City of
   Painesville (Lake) .
     1
"ST1
  GT1
 GT10
 GT11
 GT12
  GT2
  GT3
  GT4
  GTS
  GT6
  GT7
  GTB
  GT9
Oklahoma

 Oklahoma Gas & Electric Co
   Conoco (Kay)	
   NA 1 (UNKNOWN)
          May 96/May 96 .
Apr 91/Jun 91
Apr 92/Apr 92
Apr 96/Apr 96
Apr 96/Apr 96
Apr 96/Apr 96
Apr 92/Apr 92
Apr 92/Apr 92
Apr 92/Apr 92
Apr 92/Apr 92
Apr 93/Apr 93
Apr =94/Apr 94
Apr 96/Apr 96
Apr 96/Apr 96
          Aug  90/Jun 89
          Oct 92/Jun  91
         Jan 90/Aug 89
         Nov  90/Nov  90
         Nov  90/Nov  90
         May  98/May  89
         May  99/May  90
                            460.0
1300.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
  75.0
                                                                       18.0
                                                                       20.0
                             22.0
                  26.0
                  26.0
                  100.0
                  170.0
                                         423.0
1286.0
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
  61.7
                               15.3
                               20.0
                                         24.2
              21.9
              21.9
              81.7
             137.3
                                                     ST
ST
GT
GT
GT
GT
GT
GT
GT
GT
GT
GT
GT
GT
                         GT
                         ST
                                                     ST
             GT
             GT
             GT
             GT
                                                                UG
    BIT
Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas
Nat Gas
NalGas
Nat Gas
Nat Gas
Nat Gas
Nat Gas
                    Nat Gas
                         BIT
                                                                BIT
       Nat Gas
       Nat Gas
       Nat Gas
       Nat Gas
                                                                           PL
CO
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
 PL
                     CO
                      PL
                                                                          CO
              CO
              CO
              PL
              PL
                                                            A-7

-------
 Table 21.  Projected Electric Generating Unit Additions, by State, Company,
                and Plant,  1990-1999, as of December 31,1989 (Continued)
Slat*
Company
r*lanl \\sWMnj)
UnN
• to

Scheduled
Completion D&tt

1 ' f**nmfmtn *
! VOTMffVIQr
Nameplate
1 capttdly
t SlMMfMT 1
: CapabWy j
: (magawatu) |
UnN
Type'

EfMcyy 1 Unit
Some** 1 Status
1
 South Carolina

  Duke Power Co
    Bad Creek (Oconee)
  South Carolina Etectric&Gas Co
   Hagood (Charleston) ...
   NA 1 (UNKNOWN)	
   MA 2 (UNKNOWN)	
   NA 3 (UNKNOWN)	
   NA 4 (UNKNOWN)	^—
  South Carolina Pub Serv Auth
   Cross (Berkeley)	
  Sparta nburg City of
   Blalocfc(Spartanburg>.

South Dakota

  Black Hilts Corp
   CT (UNKNOWN)	
  Northwestern Public Service Co
   Huron (Beadle)	
Tennessee

 Tennessee Valley Authority
   Watts Bar (Rhea)	
Texas

 Brazos Electric Power Coop Inc
   NA 1 (UNKNOWN)	
   R W Miller (Palo Pinto)	
 Oenton City of
  Lewisvilte (Oenton)	
  Roberts (Oenton) 	—
 El Paso Electric Co
  Generic Stat (UNKNOWN)
 Houston Lighting & Power Co
  Malakotl (Henderson)	
 Lubbock City of
  LP&L Cogen Plant (Lubbock).

 San Antonio City of
  GT 98 (Bexar) 	
  4
GT1
GT2
GT3
ST1
  GT 99 (Bexar) 	


  J K Spruce (Bexar)		
         Apr 92/Apr 91
         Apr 92/Apr 91
         Jan 93/Apr 92
         Apr 92/Apr 92
May 91/May 91
May 93/May 93
May 94/May 94
May 94/May 94
May 97/May 9?
        Dec 95/May 85


        Jan 98/Jan 89




         Jul 94/Jul 94
       May 91 /May 91
       May 99/May 99
        Oct 91/Oct 76
        Oct 95/Apr 77
        Jan  98/Jan 98
        Jan  98/Jan 98
        Jan  93/Jan 93
        Jan  95/Jan 95
        Mar 91 /
        Mar 9l/
          86
          88
       Jan 96/Jan 96
       Jan S8/Jan 98
       Dec 96/Mar 87
       Dec 98/Mar 88
       May 90/May 90
       Feb 98/Feb  98
       Feb 98/Feb  98
       Feb 99/May  98
       Feb 99/May  98
       Feb 99/May  99
       May 92/May  92
       May 97/May  97
                  266.3
                  2663
                  266.3
                  266.3
121.8
 96.0
 96.0
 96.0
350.0
                  5562


                    2.5




                   40.0
                   21.2
                   22.6
                 1269.9
                 1269.9
                 300.0
                 300.0
                 100.0
                 100.0
 Z8
 1.0
                  70.0
                  70.0
                 726.8
                 726.8
                          20.0
                  70.0
                  70.0
                  70.0
                  70.0
                  70.0
                 546.0
                 546.0
            273.3
            273.3
            2733
            273.3
 99.1
 78.5
 78.5
 785
350.0
                                      520.0
                                       333
             17.9
             19.2
           1170.0
           1170.0
           236.7
           236.7
            81.7
            81.7
 2.8
 1.0
            57.6
            57.6
           645.0
           645.0
                                      16.9
            57.6
            57.6
            57.6
            57.6
            57.6
           498.0
           498.0
            HR
            HR
            HR
            HR
 GT
 GT
 GT
 GT
 ST
                                                  ST
                        HC
                                          GT
            GT
            GT
            NP
            NP
           CT
           CT
           GT
           GT
HC
HC
           GT
           GT
           ST
           ST
                                                 GT
           GT
           GT
           GT
           GT
           GT
           ST
           ST
          Water
          Water
          Water
          Water
Nat Gas
Nat Gas
Nat Gas
Nat Gas
    BIT
                                                             BIT
                                 Water
                                                         Nat Gas
        Nat Gas
           FO2
        Uranium
        Uranium
       Nat Gas
       Nat Gas
       Nat Gas
       Nat Gas
 Water
 Water
       Nat Gas
       Nat Gas
           LK3
           UG
                                                        Nat Gas
       Nat Gas
       Nat Gas
       Nat Gas
       Nat Gas
       Nat Gas
          SUB
          SUB
              CO
              CO
              CO
              CO
  PL
  PL
  PL
  PL
  PL
                                                               CO
                                              PL
                                                                        PL
              PL
              PL
             CO
             CO
              PL
              PL
              PL
              PL
CO
CO
              PL
              PL
              PL
              PL
                                                                      CO
              PL
              PL
              PL
              PL
              PL
             CO
              PL
                                                     A-8

-------
  Table 21.  Projected Electric Generating Unit Additions, by State, Company,
                 and Plant,  1990-1999, as of December 31,1989 (Continued)
                   State
                  Company
                Plant (County)
!   UnK  j   co.^STSrt.  |  	
i   m   i   Currant/Original  j  Capacity
                                       Summer
                                      Captbttty
                                           Unit
                                         Typ.'
                               Energy
                               Source'
                               UnH
                              Statua
  Virginia

   Virginia Electric & Power Co
                                                      Nov  90/Nov 90
                                                      Nov  90/Ncv 90
                                                      Nov  90/Nov 90
                             89.5.
                             89.5
                             89.5
                                  73.3
                                  733
                                  733
                         GT
                         GT
                         GT
                        FO2
                        FO2
                        FO2
                                                                               CO
                                                                               CO
                                                                               CO
  Washington

   PUD No 1 of Pend OreiUe Cnty
    SulNvan Creek (Pend OreHle).
   PUD No 2 of Grant County
    PEC Headwords (Grant).

   Seattle City ol
    Sooth Fork  Tolt (King)		
   Tacoma City of
    Wynoochee (Grays Harbor).
         Sep 95/Sep 89
         Sep 95/Sep 89
          Apr 90/Apr 89


              94/Nov 85
          Jan 92/Jun  91
          Jan 92/Jun  91
                      8.0
                      8.0
                           6.7


                          15.0


                           33
                                           62
                                           6.8
                                          15.8
                                  7.7
                                  33
                         HC
                         HC
                                             HC


                                             HC
                         HC
                         HC
                      Water
                      Water
                                                               Water
                                                               Water
                      Water
                      Water
                                                                               PL
                                                                               PL
                                               CO


                                                PL
                                                                               PL
                                                                               PL
 Wisconsin

   Madoon Gas & Electric Co
    Combustion Turbine (Dane)
  Maretowoc City of
    Manttowoc (Manrtowoc)
  Marsnfeld Oty ol
    NA (UNKNOWN)	

  Wisconsin Electric Power Co
    Concord (Jetlerson)	

    NA 1 (UNKNOWN)	
    NA 2 (UNKNOWN)	

    NA 3 (UNKNOWN)	

    NA 4 (UNKNOWN) 	

    NA 5 (UNKNOWN)		_-
  Wisconsin Power & Light Co
   NA 1 (Fond Du Lac)._	_
  Wisconsin Public Service Corp
   Ftainbow (OoexJa) 	
   Trappe (UNKNOWN)	
1     Jun 95/Jun 95
2     Jun 99/Jun 98
   8     Dec 98/Dec 98
         Jun 92/Jun 92
   1
   2
   1
   1
   2
   1
   2
   1
   2
   1
   2
CT1
CT2
CT3
CT4
 Jun 93/Jun 93
 Jun 93/Jun 93
 Jun 93/Jun 93
 Jun 94/Jun 94
 Jun 94/Jun 94
 Jun 95/Jun 95
 Jun 95/Jun 95
 Jun 96/Jun 96
 Jun 96/Jun 96
 Jun 97/Jun 97
 Jun 97/Jun 97
Mar 94/Mar 94
Mar 96/Mar 96
Mar .96/Mar 96
Mar 99/Mar 99
        Mar  98/Mar  98
        Mar  98/Mar  98.
                             90.0
                             45.0
                             60.0
                             15.0
75.0
75.0
 3.0
75.0
75.0
75.0
75.0
75.0
75.0
75.0
75.0
90.0
90.0
90.0
90.C
                     1.1
                     4.0
                                 73.7
                                 37.4
                                        '60.0
                                         1Z8
61.7
61.7
 3.0
61.7
61.7
61.7
61.7
61.7
61.7
61.7
61.7
73.7
73.7
73.7
73.7
             1.1
             4.0
                        GT
                        GT
                                                     ST
                                                     GT
                                                        GT
                                                        GT
                                                        HC
                                                        GT
                                                        GT
                                                        GT
                                                        GT
                                                        GT
                                                        GT
                                                        GT
                                                        GT
                                                       GT
                                                       GT
                                                       GT
                                                       GT
           HC
           HC
                    Nat Gas
                    Nat Gas
                                                                 BIT
                                                            Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                           Water
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                         Nat Gas
                                                                 Water
                                                                 Water
                                                                               PL
                                                                               PL
                                                                            PL
                                                                            PL
PL
PL
PL
PL
PL
PL
PL
PL
PL
PL
PL
                                                                                                                        PL
                                                                                                                        PL
                                                                                                                        PL
                                                                                                                        PL
                                                                        PL
                                                                        PL
  * Capacity less man 0.05 megawatts.
  ""   A |»nrty owned unit.
    Notes:  The following units denoted in this table with unit type. CT. are the entire respective proposed combined cycle units, including the steam
generators)- Arkansas Electric Cooperative Corporation. NA 2. unit 1 • Florida Power Corporation. NA 2. units 1 and 2 - Brazos Electric Power Coopera-
tive, NA 1. urats 1 and 2 - Texas Municipal Power Agency, NA 1. unit 2.  Each of the following denoted in this table represents multiple proposed gen-
erators- Jersey Central Power and Light Company. NA 2. unit 1. NA 3. unit 1. NA 4. unit 1. NA 5. unit 1. NA 6. unit 1 - Oklahoma Gas and Electric Com-
pany. NA 1. unit 2 - Texas Utilities Generating Company. NA 2. unit NA1.
    Source: Energy Information Administration. Form EIA-860. "Annual Electric Generator Report"
                                                            A-9

-------
  Table 21.   Projected Electric Generating Unit Additions, by State, Company,
                and Plant, 1990-1999, as of December 31,1989 (Continued)
state
Company
Ptant (County)
I unn
i "
Scheduled
Completion Oat*
Current/Original
GWMTBtOT
»•—,-- --.i, • ,
fUNlWpUM
Capacity
Summer '
CapaMtty {
(megawatts) I
UnN
Type'
Energy
• Source1
'. UnK
; Statin
 Texa*

   San Miguel Electric Coop Inc
    San Miguel (Atascosa)	
   Texas Municipal Power Agency
    NA 1 (UNKNOWN)	
   Texas Utilities Generating Co
    Comanche Peak (SomerveH).
    Forest Grove (Henderson).
    NA 2 (UNKNOWN)	
    Twin Oak (Robertson)	
  Texas-New Mexico Power Co
    TNP ONE (Robertson)	
  "1
  "2
    1
 MAI
    1
    2
    1
    2
    3
    4
          Jun 97/Jan 89
          Apr 967 Apr 96
          Jan 99/Jan 99
 Feb 90/Jan 80
 Dec 91/Jan 82
 Jan 98/Dec 78
 Feb 97/Feb 96
 Jan 95/Jan 81
 Jan 96/May 81
 Feb 90/Jun 90
 Jun 91/Jun 91
 Jun 97/Jun 92
 Jun 98/Jun 93
                            450.0
                   120.0
                   118.9
1215.0
1215.0
 795.8
 375.0
 800.9
 800.9
 194.0
 194.0
 194.0
 194.0
                                        400.0
              97.7
              97.4
1150.0
1150.0
 750.0
 2932
 750.0
 750.0
 142.0
 142.0
 142.0
 142.0
                                                    ST
             GT
             CT
NP
NP
ST
CT
ST
ST
ST
ST
ST
ST
                                                               LK3
        Nat Gas
        Nat Gas
Uranium
Uranium
   UG
Nat Gas
   LIG
   UG
   UG
   LIG
   UG
   UG
                                                                          PL
               PL
               PL
 CO
 CO
 CO
 PL
 CO
 CO
CO
CO
 PL
 PL
 Utah

  Bountiful City City of
   East Canyon Dam (Morgan).
   Joes Valley Dam (Emery) .
   Pine View Dam (Weber)	_

  Deseret Generation & Tran Coop
   Bonanza (Umtah)	
  Logan City ot
   Logan Oesel (Cache) —
  Mt Pleasant Dry ol
   Unit 3 (Sanpete)	
   Unrt 4 (Sanpete)	
 NA1
 NA2
 NA1
 NA2
 NA3
 NA1
IC5A
ICSB
  Weber Basin Water Conserv Oist
   West Gateway (Davis) _	
Vermont

  Momsville Village ot
   Garfiekl (Lanxxlte)	
HC1
HC2
 Jun 91/Jun 87
 Jun 91/Jun 87
 Oct 92/Oct 92
 Oct 92/Oct 89
 Oct 92/Oct 86
Sep  90/Mar 90
         Aug 95/Jan 97
May 90/May 90
May 90/May 90
         Dec 91/Sep 89
         Dec 91/Sep 88
        Dec 92/Oec  88
     94/   94
     94/   94
  2.0
   .5
  1J3
  1.3
  1.0
  1.8
                           400.0
  1.0
  "1.0
                     JS
                    •us
                             4.0
  1.3
  1.3
                                         2.0
                                                                                    \2
                                                                                    1.0
                                                                                    1.8
                                       400.0
   .9
   .9
               .5
              1.4
                                         4.0
                                                                                   \2
                                                                                   \2
             HC
             HC
             HC
             HC
             HC
             HC
                                                   ST
1C
1C
            HL
            HL
                                                   HC
            HC
            HC
         Water
         Water
         Water
         Water
         Water
         Water
                                                               BIT
   (=02
   FO2
         Water
         Water
                                                                                                       Water
         Water
         Water
              CO
              CO
              PL
              PL
              PL
              CO
                                                                PL
CO
CO
              PL
              PL
                                                                                                                    PL
              PL
              PL
 Swanton Village of
   Mighgate Falls (Franklin)	

Virginia

 Culpeper Town of
   Culpeper 2 (Culpeper)	
 Virginia Electric & Power Co
  Chesterfield (Chesterfield) .
  Clover (Halifax)	

  Darbytown (Henrico)	
         Apr 90/Mar  88
                             4.5
                                         4.5
                                          HC
                                                    Water
                                                               CO
1
2
7
7A
BA
8B
"1
"2
1
Jan 95/Jan 95
Jan 95/Jan 95
Jun 90/Apr 92
Jun 90/Apr 92
Jun 92/Jun 92
Jun 92/Jun 92
Dec 93/Dec 93
Dec 94/Dec 94
Nov 90/Nov 90
2.0
2.0
72.0
147.0
147.0
72.0
393.0
393.0
89.5
1.8
1.8
60.2
119.4
119.4
60.2
393.0
393.0
73.3
1C
1C .
cw
CT
CT
CW
ST
ST
GT
FO2
F02
WH
Nat Gas
Nat Gas
WH
Coal
Coal
FO2
PL
PL
CO
CO
PL
PL
PL
PL
CO
                                                        A-10

-------
                   APPENDIX B




PROJECTION INVENTORY QUALITY ASSURANCE CHECKLIST

-------
                                     APPENDIX B

                     PROJECTION INVENTORY QA.CHECKLIST
I. General and Background Information                       *'   •.

    1.   What classification is/are the nonattainment area(s) for the following pollutants?
        a.    Ozone
             	   Marginal (.121 to .137 ppm)
             	   Moderate (.138 to .159 ppm)
             	   Serious (.160 to .179 ppm)
             	   Severe 1 (.180 to .190 ppm)
             	   Severe 2 (.191 to .279 ppm)
             	   Extreme (.280 + ppm)

       'b.    Carbon Monoxide
             	   Moderate (9.1 to 16.4 ppm)
             	   Serious (16.5 +' ppm)

    2.  What are the projection years?	
    3.  What is the projected attainment year?

    4.  What projection models are used?
             Comment	
II.  Types of Projections

    1.   Do the Baseline Emission Projections contain consistent emission estimation methods?
             Yes     	               No    	
             Comment:	
    2.  What were the sources of the Area Source growth arid control data?
             Comment:	
    3.  What inconsistencies between control strategies and inventories exist?
             Comment:    	                       	
       a.    How were the inconsistencies resolved?
             Comment:   	  	  	 	
   4.  Were defaults used in the calculation of Rule Effectiveness?
             Yes    	               No    	
             Comment
                                          B-l

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        a.     What was the source of data for non-defaults?
              Comment	
    5.  Do the projected emissions represent Actual or Allowable emissions?
              Actual   	                Allowable	
              Comment   	   •.	
        a.     If allowable emissions are used, what offset policy is in effect for the area?
              Comment    	.   	
III. Projections of Future Activity

    1.   Are there dominant sources or large VOC facilities in your area?
             Yes      	                No
             Comment	
        a.    Are facility-specific growth and control factors available for these sources?
             Yes     	                No    	
             Comment
    2.   Are Bureau of Economic Analysis (BEA) defaults used to project future activity?
             Yes	                No    	
             Comment
       a.    If BEA defaults are not used, what is the source of the data used to project future
             activity?
             Comment:    	          	
   3.  Are all 57 types of industry defined by the BEA covered in the projection?
             Yes     	               No	
             Comment
       a.    What additional industrial activity data were used?
             Comment
   4.  For what categories were the following future activity indicators used in the projection?
       a.    Product Output
             Yes     	               No    	
             Comment
       b.    Value added
             Yes     	               No
                                            B-2

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             Comment
       c.    Earnings
             Yes    	               No
             Comment        	      	'_
       d.    Employment
             Yes    	               No
             Comment    	
IV. Measuring the effects of Current and Future Controls for VOC, NOX, and CO.

A. VOC Clean Air Act Amendment (CAAA) Requirements
    1.  As required by the CAAA, are the following National Stationary Measures included in the
       assessment of Volatile Organic Compounds (VOCs)?  (These measures apply whether the
       facilities are located in non-attainment areas or not)
       a.    Hazardous Waste Landfills
             Yes    	              No    	
             Comment:	
       b.    Municipal Landfills
             Yes    	               No
             Comment:   _••	
       c.     Consumer/Commercial Solvents (Phase I)
             Yes    	              No    	
             Comment:        	   	  	
       d.    Architectural Coatings
            Yes    	 .             No.
            Comment:
       e.    Marine Vessels
            Yes    	              No
            Comment:
   2.  Are the following included in the assessment of Motor Vehicle Measures as required by the
       CAAA?

       a.    Gasoline RVP Controls (before 1995)
            Yes     	              No    	
            Comment:       	
                                          B-3

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        h.    Are you within the Ozone Northeast Transport region?
             Yes     	               No    	
             If yes the following apply:
             Are the following included in your assessment of Area-Specific Measures?

             (1) enhanced I/M (populations > 100,000)
             Yes     	               No    	
             Comment    	__^_____^_	
             (2) RACT for facilities emitting more than 50 tpy
             Yes     	               No    	
             Comment   	
       i.     Are you in California?
             Yes     	               No	
             If yes:
             Are the following included in your assessment of Area-Specific Measures?

             (1} Clean vehicles program (start at 150,000 vehicles in 1996, increase to 300,000 in
             1999, more stringent standards starting in 2001)
             Yes     	               No    	
             Comment	
   4.  Are Discretionary Measures being applied?  If yes, describe.
             Yes     	                No	
             Comment:
   5.  What are the effects of Title III (toxic) regulations on VOC sources?
             Comment:
B. NOX CAAA requirements
   1.   Are there phase I plants in your area?
             Yes     	               No
             Comment:    	
   2.  Are the following accounted for in your assessment of Utility NO, emissions?
       a.     Utility-Generation Growth Factor? Comment on type and calculation of growth factors.
             Yes    	               No    	
             Comment:
                                           B-4

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    b.    Area-Specific Measures
         (1) stage II controls (moderate and above)
         Yes     	              No    	
         Comment   	
         (2) fleet clean fuels programs (serious and above)
         Yes     	               No    	
         Comment   	
         (3) reformulated gasoline (severe and above)
         Yes     	               No    	
         Comment   	.
3.   Are the following included in your assessment of Area-Specific measures?
    a.    RACT for major non CTG sources (emitting greater then 50 toy in serious, 25 tpy in
         severe, and 10 tpy in extreme - before 1995)
         Yes     	               No    	
         Comment:   	
   b.    All 11 new CTGs (all sources, moderate and above areas)
         Yes     	               No     	
         Comment:   	
   c.    All old CTGs (including RACT fix-up program)
         Yes	               No    	
         Comment:
   d.    Effects of enhanced I/M (serious and above)
         Yes     	               No    	
         Comment:
   e.    Basic I/M (moderate areas)
         Yes    	               No
         Comment:
   f.     Maximum Achievable Control Technology (MACT)
         Yes    	               No    	
         Comment:
   g.     Have there been voluntary reductions for toxic sources?
         Yes    	               No    	
         Comment:   	
                                      B-5

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    b.    Unit-Specific Future Year Capacity Factor? Comment on calculation, or provide an
          example.
          Yes    	               No   	
          Comment    	;	
    c.     Comment on how the Total Projected Generation demand was calculated.
          Comment:  	
    d.    Does Totaj Generation from existing and announced utilities meet the demand?
          Yes	               No    	
          Comment    	
    e.     What is the difference between generation demand of the area and the generation from
          existing and announced units?.
          Comment	•
3.  Was the determination of planned or announced utility plants in the area possible?
          Yes    	               No    	
          Comment                           	                 	
    a.    How were the plants identified?
         Comment:	
    b.    Were capacity factors available for the plants? Comment on how they were computed.
         Yes    	               No    	
         Comment:                 	  		
         (1) If no capacity factors were available, was the default capacity factor of .65 used?
         Yes     	       .  -      No    	
         Comment:
4.   Are the following accounted for in your assessment of NOX?
    a.    RACT for major NOX sources for moderate and above ozone non-attainment areas
         Yes     	               No    	
         Comment:	
    b.    RACT for all sources emitting more than 100 tpy of NO, in ozone northeast transport
         region.
         Yes     	               No    	
         Comment:
                                       B-6

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 C. CO CAAA Requirements
    1.   Are the following accounted for in your assessment of CO?
        a.    Basic I\M for Moderate Areas (before 1995)
             Yes     	              No    	
             Comment   	'	
        b.    Enhanced I\M for Serious Areas (before 1995)
             Yes     	               No    	
             Comment   	
        c.    Oxygenated Gasoline for all Non-Attainment Areas (starting in 1995)
             Yes     	               No    	
             Comment   .     	
V. Combining Growth and Control Effects

    1.  What was the source of the Industrial Growth Rate data?
             Comment	
    2.  Where were Population Data obtained?
             Comment	
       a.    What Source Categories relied upon population statistics for growth calculations?
             Comment:
    3.  Were Retirement Rates used?
             Yes     	               No
             Comment:
       a.    If yes, were the Retirement Rate Data default data from table V.1?
             Yes    	               No    	
             Comment:
             (1) If the data were not from table V.1, how were the data developed?
             Comment:
   4.  How were VMT Data projected?
             Comment:    	
   5.  How were the Emission Factor Ratios for new and existing sources computed?
             Comment:
                                          B-7

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    6.  Provide an example of the application of the equation in Section V.A. for stationary sources.
             Comment    	
    7.  Are Historical Growth Data for the facilities or industries available?
             Yes    	               No    	
             Comment   	   •.
        a.    Were Historical Growth Data obtained for comparison with the projected growth factors?
             Yes     	               No    	
             Comment	' •
    8.   Were Industry- or Plant-Specific Data compared to U.S. Department of Commerce estimates?
             Yes     	               No    	
             Comment	
        a.    Are the discrepancies understood?
             Yes     	ta.               No
             Comment	
VI. Ensuring Consistency with other Emission Inventory Activities

    1.  Are there any other emission inventory projections available for this area?  If so name the
       project
             Yes     	               No    	
             Comment:	
       a.    Are you located in the ROMNET modeling area?
             Yes     	               No    	
             Comment:   	                	  	
       c.    Are you located in the LMOS modeling area?
             Yes     	               No    	
             Comment
    2.  Do the estimates and/or Raw Growth and Retirement Rates compare with the other study?
       Can differences be explained?
             Yes     	               No    	
             Comment:    	  	
                                           B-8

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VII. Tracking Considerations

    1.   Are there SIP and I\M corrections for your area?
             Yes    	               No    _
             Comment    	  '	
        a.    What are the corrections?
             Comment
        b.    How are the resulting emission reductions accounted for?
             Comment      	       	
    2.   Provide an example calculation of the 1996 progress requirement emission target?
             Comment	
    3.   If applicable (serious and above ozone areas), provide an example calculation of the 1999
      emission reduction target
             Comment:
                                           B-9

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       APPENDIX C

HISTORICAL EARNINGS DATA
   (Backcasting Data)

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                            APPENDIX C

                     HISTORICAL EARNINGS DATA


     Historical earnings data are potentially useful in making
emission projections both through establishing trends, which can
be extrapolated into the short-term future, in having the ability
to adjust  1990 base year emission estimates to match with air
pollution  episodes, which may have occurred during 1987, 1988, or
1989 and in updating portions of prior year emission inventories
to 1990.   To date, BEA has published historical earnings
statistics through 1989.  BEA reporting for these statistics are
by state and 3-digit Standard Industrial Classification (SIC)
code.  Because 1990 is such an important year for establishing
base year  emissions, a trend analysis was applied to the
historical data to add estimated 1990 values to the data base.
The procedure applied to estimate 1 990 values is described
briefly below.

     Estimation of annual income data using trend line analysis
is justified on the basis of inflation or trend inertia.  It will
fail during major shifts in economic conditions not already
established in the prior year's values.  Thus, even though the
BEA historical data covered 21 years, from 1969 to 1989, only the
most recent six years (1984 to 1989) of data were used in this
analysis.  Some of the state/SIC categories contained a " (D) "
entry, which indicates that the data were withheld from
publication because of small cell size disclosure policies.  This
(D) entry  was translated to a numeric -99 in the revised data
files.

     In estimating 1990 values, if any data were 0 or -99
(withheld)  in the 1986-1989 period, then the 1990 entry was set
equal to the 1989 data adjusted for inflation.  In cases where
there were at least four years of data prior to and including
1989, a log-linear model of the form of equation (1)

                              i
-------
     Revised data files with the 3-digit SIC code values for each
state for 1986 through 1990 are available from EPA through the
CHIEF Bulletin Board System.  These data-are in spreadsheets.

     One of the purposes for developing the above data files was
to assist states in estimating 1990 emissions given that
significant efforts may have been expended previously to compile
emission inventories for a year other than 1990.  Several ozone
and CO nonattainment areas began preparing 1987, 1988, or 1989
inventories as a result of SIP calls in 1988 or 1989.  These
inventories either have to be updated to 1990 or completely
redone to reflect 1990 conditions.

     For states that receive EPA approval to perform updates to
the 1987/1988/1989 inventories, the BEA data in the spreadsheet
files can be used to adjust prior year emission estimates to 1990
for point sources with emissions less than 100 tons per year.
This can be done for any given state by matching the source
category of interest with the appropriate 3-digit SIC code.  Note
that BEA earnings data are meant only to capture likely changes
in activity levels and that any change in emission rates for a
source or a source category from the original base year emission
inventory to 1990 has to be accounted for separately.  The BEA
data may also be used to update area and non-road mobile source
emission estimates to 1990 for any source category for which the
state/3-digit SIC code is the best surrogate indicator of
activity.  In other words,  if the historical BEA data were used
as an indicator of activity in the original inventory for a
source category,  then the data in the spreadsheet files can be
applied to estimate changes in activity between 1987/1988/1989
and 1990.

     Users of the constant dollar BEA historical data files are
cautioned to only use them to develop growth factors.  Because of
the conversion to constant dollars,  these data will not match
those eventually published by BEA for 1990.

     Once a 1990 base year inventory has been compiled,  there may
be a need to adjust that inventory to correspond with the time
period of an air pollution episode.   For example,  areas planning
to apply the Urban Airshed Model may be modeling episodes that
occurred in 1987,  1988,  or 1989.  The BEA data may be useful for
that purpose as well.   Consultation with EPA is advised before
BEA data are used for that purpose because annual earnings data
may not always be suitable for estimating day specific
conditions.   In cases where this technique is valid,  backcasting
1990 emissions to prior years can be performed by multiplying
1990 emissions for a given source category by the ratio of the
episode year historical earnings to 1990 earnings.   The
historical BEA data in the spreadsheet files can only be used to
adjust 1990 emission estimates to a prior episode year for point
sources with emissions less than 100 tons per year (small point
sources and non-highway vehicle area sources).  Episode year
emission estimates for large point sources and highway vehicles
                               C-2

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will have to be made using information specific to the time
period being modeled.  As with the techniques described above for
using historical BEA data to update 1987/1988/1989 inventories to
1990, it is important to match the source category of interest
with the appropriate 3-digit SIC code.  The earlier mentioned
caveat about BEA earnings data only capturing activity level
changes applies here as well.
                               C-3

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                                     TECHNICAL REPORT DATA
                             (Please read Instructions on the reverse before completing)
1. REPORT NO.
 EPA-450/4-91-019
                                                              3. RECIPIENT'S ACCESSION NO.
 I. TITLE AND SUBTITLE

 Procedures for Preparing Emissions Projections
5. REPORT DATE
  July 1991
                                                              6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
 E.H.  Pechan  and Associates, Inc.
 Springfield,  VA  22151
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
 Emission  Inventory Branch
 Technical Support Division
 Office of Air Quality Planning and  Standards
 Research  Triangle Park,  N.C.   27711
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
   68D00120
12. SPONSORING AGENCY NAME AND ADDRESS
                                                              13. TYPE OF REPORT AND PERIOD COVERED
                                                              14. SPONSORING AGENCY CODE

                                                              EIB/TSD/OAQPS
15. SUPPLEMENTARY NOTES
 EPA Project  Officer:   Keith Baugues
16. ABSTRACT
      The purpose of this  document is to provide guidance for  projecting emissions
 to  future years.   It focuses primarily  on procedures  for projecting how the
 combination  of future emission controls and changes  in source  activity will
 influence future air pollution emission rates.
 7.
                                 KEY WORDS AND DOCUMENT ANALYSIS
                   DESCRIPTORS
                                                b.lDENTIFIERS/OPEN ENDED TERMS  C.  COSATI  Field/Group
Emissions, Emission  Inventories,
Ozone  (Oo) Projections
 8. DISTRIBUTION STATEMENT
                                                19. SECURITY CLASS (ThisReport)
                                                                            21. NO. OF PAGES
                                                                               141
                                                20. SECURITY CLASS (This page)
                                                                            22. PRICE
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        Insert contract or grant number under which report was prepared.

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EPA Form 2220-1  (Rev. 4-77) (Reverie)

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