EPA-450/3-75-037
February 1975
REGIONAL EMISSION
PROJECTION SYSTEM
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air i>nd Waste Management
Ofiee of Air Quality Planning and Standards
Triangle Park, Nqrth Carolina 27711
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TECHNICAL REPORT DATA
(Please read Ittiifucror s on the rcicnc before ton
1 HfcPORT NO
EPA-450/3-75-037
4 TITLt AND SUBTITLE
Regional Emission Projection System (REPS)
5. REPORT DATt
6. PERFORMING ORGANISATION CODE
7 AUTHORISI
8. PERFORMING ORGANIZATION REPORT NO
Booz-Allen and Hamilton, Inc.
9 PE RFORMING ORGANIZA1 ION ^AME AND ADOHtSS
Booz-Allen and Hamilton, Inc.
4733 Bethesda Avenue
Bethesda, Maryland 20014
12 SPONSOR'Mti AGENC^ NAML AND ADDRESS
U. S. Environmental Protection Agency
Ofiice of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
1O PROGRAM ELEMENT NO
11 CONTRACT GRANT NO
68-02-1005 T. 0. 5
13. TYPE OF REPORT AND PERIOD COVERED
Fjna]_Re£prt
14 SPONSORING AGENCY CODE
15 SUPPLLMt NTAMY NOTES
16 ABSTRACT
The Regional Emission Projection System (REPS) is a computerized
air pollution emissions projection model to project emissions at the
AQCR level. It combines national and regional economic forecasts with
point and area source inventories from the National Emissions Data
System (NEDS) to project air pollution emission levels for the five
criteria pollutants, on an annual basis, from the present to the year
2000.
DESCRIPTORS
T Hi BU TIOM ST A i fc ME'
Release Unlimited
1!) SECURITY CLASS , Inn Ittpani
Unclassified
20 bt CUBIT Y CL-A.'-S ,; ;ut ruiel
unclassified
21 NO. or
EPA Form 2220-1 (9-7S)
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ATTENTION
AS NOTED IN THE NT IS ANNOUNCEMENT,
PORTIONS OF THIS REPORT ARE NOT LEGIBLE,
HOWEVER, IT IS THE BEST REPRODUCTION
AVAILABLE FROM THE COPY SENT TO NTIS,
Mr. Archibald A. MacQueen
Enviromental Protection Agency
Office of Air Quality and Planning Standards
Research Triangle Park, NC 27711
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EPA-450/3-75-037
REGIONAL EMISSION
PROJECTION SYSTEM
by
Booz-Allen & Hamilton
Management Consultants
4733 Bethesda Avenue
Bethesua, Maryland 20014
Contract No. 68-02-1005
EPA Project Officer: John C. Bosch, Jr.
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
February 1975
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This report is issued by the Environmental Protection Agency to report
technical data of interest to a limited number of readers. Copies are
available free of charge to Federal employees, current contractors
and grantees, and nonprofit organizations - as supplies permit - from
the Air Pollution Technical Information Center, Environmental Protection
Agency, Research Triangle Park, North Carolina 27711; or, for a
fee, from the National Technical Information Service, 5285 Port Royal
Road, Springfield, Virginia 22161.
This report was furnished to the Environmental Protection Agency by
Booz-Alien & Hamilton , Bethesda, Maryland, in fulfillment of Contract
No. 68-02-1005 , The contents of this report are reproduced herein
as received from Booz-Allen & Hamilton. The opinions, findings, and
conclusions expressed are those of the author and not necessarily those
of the Environmental Protection Agency. Mention of company or product
names is not to be considered as an endorsement by the Environmental
Protection Agency.
Pubiication No. EPA-450/3-75-037
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TABLE OF CONTENTS
Page
Number
I. REPS SYSTEM OVERVIEW 1-1
II. EMISSION" PROJECTION METHODOLOGY II-1
1. Evolution of the Framework of the Projection II-l
System
2. Selection of Data Sources II-5
3. Development of Regional Growth Factors 11-11
4. Analysis of Growth and Relocation Trends for 11-22
Five Critical Industries
5. i Description of the Methodology for Projecting 11-34
Future Activity and Emissions
6. ADP Implementation of the REPS System 11-59
in. DESCRIPTION: OF HEPS PROGRAM MODULES m-i
1. Program NE053 (SEAS) III-3
2. Program NE054 (OBEHS) III-9
3. Program XE055 (MAP) III-13
4. Program XE050 (AP-42) 111-18
5. Program XE051 (XEDS-IX) 111-19
6. Program XE253 (REPS, 111-20
7. Subroutine XEA253 (BTUCAL) III-28
8. Subroutine XEB253 (COMBUS) III-30
9. Subroutine XEC253 (IXDPRC) Itf-32
10. Subroutine XED253 (AREASC) 111-34
11. Subroutine XEE253 (TRANS) ' lit-36
12. Program XE052 (NEDS-OUT) 111-38
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INDEX OF FIGURES
Page
Number
1-1 REPS System Flow and Data Sources [-2
II-l REPS P'unctional Elements II-6
11-2 Sample SEAS Output H-13
II-3 Sample OBEKS Output 11-16
II-4 Descriptive Flow Diagram for REPS 11-60
IH-1 General System Flow Chart III-2
III-2 Projection Factors and User Overrides 111-26
ui
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INDEX OF TABLES
y
Page
Number
II-l REPS Processing Logic for Incomplete II-17
OBERS Data
II-2 Rank of Heaviest Nationwide Polluting 11-26
Industries
III-l IXFOHUM Sector Identification Matrix III-6
III-2 OBERS Sector Identification Matrix 111-12
III-3 INFORUM-OBERS-SCC Mapping Matrix 111-15
III-4 Subroutine Entry Points and Entry Criteria 111-25
HI-5 Btu Conversion Table 111-29
LV
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\
x*
I. REPS SYSTEM OVERVIEW
The Regional Emission Projection System (REPS) is a comput-
erized air pollution emissions projection model, for use at the AQCR
level to project annual emissions. It combines exogenous national
and regional economic forecasts with point and area source emission
inventories for Air Quality Control Regions (AQCRs) to project air
pollution emissions levels for the five criteria poDutants on an annual
basis, from the present to the year 2000. The projection methodology
involves the following major steps:
Determine regional growth factors for future years which
reflect the expected change (positive or negative) in pollu-
tion-producing activity. Growth factors are determined
from regional economic and demographic forecasts.
Project present regional emission inventories to future
years using these growth factors. The base year emis-
* sion inventories are those of the National Emissions Data
System (NEDS).
Adjust the emission projections to include the effects of
present and future control regulations. These include
existing regulations from NEDS, and promulgated Federal
standards (incorporated automatically by REPS) and state
or local regulations (supplied by the user).
These three steps in the projection methodology correspond to the
three basic elements of the HEPS system. The general relationship
among these elements and the sor.'-ccs of data used in each element
are illustrated schematically in Figure 1-1. As is indicated in the
figure, the REPS system provides options for extensive user input to
override the key parameters which determine fhe emission forecasts.
REPS can be used to project emissions for any of the 243 Air
Quality Control Regions (AQCRs) and for the nation as a whole. : The
The four AQCRs which include U.S. territories were not con-
sidered because regional economic projections were not avail-
able for them.
1-1
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FIGURE 1-1
REPS System Flow i;nd Data Sources
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base year to which all growth is referenced is selected by the user.
and projections can be made for any year between 1974 and the year
2000. One execution of REPS produces emission projections for a
single AQCR and a single projection year. At the present lime the
system is fully operational on the EPA's UNIVAC 1110 computer sys-
tem at the Research Triangle Computing Center (RTCC), Research
Triangle Park, North Carolina.
The throe basic program elements of the REPS system:
Cr.iculation of Growth Factors from Economic and
Demographic Forecasts
Projection of Emission from Base Year Inventories
Application of Emission Controls
are discussed in detail in the following sections. A more complete
description of the scope and applicability of the REPS system, includ-
ing discussion of:
Outputs of the System
Options for Users to Input Additional Data
Potential Applications
is also given. These six sections provide a brief, bu^ comprehensive,
overview of the HEPS system.
1. CALCULATION OF GROWTH FACTORS FROA1 ECONOMIC
AND DEMOGRAPHIC rOKECASTS
Regional economic and demographic forecasts are used in REPS
to determine the expected change in tho region's pollution producing
activity. The fundamental populate of this approach is thnt a chanqe
in pollution-producing actnity is proportional to a change in purely
economic and demographic parameters, such as total gross output,
employment or population.
There are two primary sources for the economic and Jemo-
graphic forecast data used in REPS: EPA developed national economic
growth projections, and Department of Comnif rco regional activity
projec'ions. National economic growth projections arc taken from a
1-3
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F
I
standard output of the SEAS system, : and include total gross output
for each of 284 economic sectors and subsectors. The SEAS projec-
tions are based on a sophisticated model of che national economy in
which dynamic modeling of the inputs and outputs of each economic
sector with respect to all other sectors is used to project the total
gross output of each sector. These econometric projections for each
sector are modified in the SEAS system to reflect additional factors
which do not influence economic projections for specific industrial
sectors, but which do have a substantial effect on emissions. These
factors include future process changes and materials substitution,
and disaggregation of selected sectors to account for industrial pro-
cesses within one sector which may grow at different rates.
For each region, the relative share of the SEAS national output
forecasts is established using the OI3ERS economic projections for
AQCRs, which contain regional foi ecasts of population and employ-
ment, in addition to projections of regional earnings for 28 industrial
sectors. The OBERS projections are reviewed and updated regularly
by the Department of Commerce. The methodology used in preparing
the OBKRS projections involves two basic steps. First, the economic
growth of each sector was projected at the national level. Then these
national totals were distributed regionally in accordance with historic
and projected trends in the regional distributions of economic activity,
tempered by available industry- and region-specific growth informa-
tion.
The SEAS and OBERS projections have been supplemented in
REPS by a special analysis of growth and relocation trends for five
industries which are among the heaviest industrial polluters. These
critical industries include electric power generation, steel, chemicals,
pulp manufacturing and petroleum refining. The output of this analysis
is a file of data on now plants expected to become operational in the
future. For each plant, the SCC 1 Co-^c, fhe AQCR, the projected
startup year and the plant capacity are given. These data may be in-
put to fhe program at the user's option.
Strategic Environmental Assessment System, an econometric
and emission forecasting model developed by the Office of Re-
search and Development, Environmental Protection Agency,
Washington, D.C.
Regional Economic Activity in the U.S., 1972 OBERS Projec-
tionp, developed by ihe U. S. Departments of Commerce and
Agriculture for- the L". S. Water Resources Council.
Source Classification Codes defined in NEDS.
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To incorporate the economic nnd demographic forecast data into
the REPS program, dimensionless growth factors, reflecting the
change in economic and demographic parameters for the projection
year relative to the base year, tire computed. By determining the
relationship between SCC processes and the SEAS and OBERS indus-
trial sectors, regional growth factors for each specific SCC process
are calculated in REPS.
2. PROJECTION OF EA1ISS1ON FRO.M BASE YEAR INVENTORIES
Regional emissions in the base year, to which the growth factors
described above are applied, are taken from the point and area source
inventories of the EPA's National Emission Data System (NEDS). The
REPS model uses the following elements of (he data contained in the
NEDS point source inventory for each source:
SCC process code
Net annual emissions
Control efficiency
Emissions permitted bv existing regulations and compli-
ance to those regulations.
REPS also uses the data in the area source inventory which define the
levels of area source emission-producing activity in the base year.
This activity includes transportation, fuel combustion, evaporation
and miscellaneous area sources. Appropriate growth factors are
applied to the data in order to calculate emissions in the projection
year. The REPS system has the advantage of building emissions pro-
jections on known activity and source data from NEDS. Clearly, the
accuracy of 'he projected emissions will depend on the accuracy of
NEDS in the base year. New activities and industrial sources enter-
ing the r-.gion and not now accounted for in NEDS will appear in the
projections only if entered into REPS via user options.
An alternative 'o the above approach, which was considered but
not adopted in developing REPS, wo'ild be to determine projected
regional economic activit\, and then to translate the projected activity
(given in terms of either dollars or physical units) directly to pro-
jected emissions without using a base vear emission inventory. Since
regional economic projec'ions usually provide- no more than two or
1-3
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three digit SIC industrial detail (e. g. , steel manufacturing), all indus-
trial sectors would have to be disaggregated to the SCC process level
(e.g. , open hearth, BOF, etc. ) to reflect the actual process mix of
the region. This is necessary, of course, because of the wide varia-
tion in emission characteristics for different processes. Even if the
projected regional process mix were determined, national average
emission factors would have to be used to convert the regional eco-
nomic process activity to projected emissions.
The REPS approach, on the other hand, uses the actual process
mix in the base year, as given in the NEDS inventory, to define the
process mix upon which (he projections are based, rather than relying
on disaggregating industrial sector data. In addition, the base year
emission data entered in NEDS are provided by the polluting facilities
and are often based on stack tests or local emission factors. To trans-
late economic data to emissions with comparable accuracy would re-
quire knowledge of these local or plant-specific emission factors.
3. APPLICATION OF EAILSSIOX CON1ROLS
The final step of (he REPS emission projection methodology is to
adjust the projected emissions to include the effect of emission con-
trols required for each type of source in the projection year. This is
a very important consideration because control regulations ma}' re-
quire a reduction in emissions that more than offsets the projected in-
crease in activity. Thus net emissions 11133' de-crease over time in
spite of expected increases in industrial activity.
The REPS system includes the i-ffecl of control regulations in
two ways. First, if any point source has been granted a control vari-
ance which will have expired by the projection year, projected emis-
sions are reduced to the level allowable under those regulations. Data
on current controls are taken from the NEDS point source inventory.
Second, Federal New Source Performance Standards which govern
new and retrofit industrial equipment, are included in the REPS sys-
tem. Standards already promulgated in the Federal Register are in-
cluded, as well as proposed standards which are likely to be promul-
gated in the future ma\ be input at the user'? option. The proposed
standards were supplied by the Emission Standards and Engineering
Division of the EPA's Office of .Air Qualify Planning and Standards.
The effect of Now Source Performance Standc.rd^ on future emission
is determined in the REPS svsteni by estimating the portion of
1-6
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' ) projected activity which will involve equipment or facilities governed
'? by these standards.
z'
i,
i The emission control data noted above may be supplemented by
{ accessing the State Implementation Plan file which is expected to be
{ an operational element of the Aerometric and Emissions Reporting
| ' System (AEROS) in the near future. The REPS program is designed
j to accept these data as soon as they are available. This file will con-
i tain emission control regulations to be implemented as part of state
programs to maintain acceptable ambient air quality. Additional emis-
sion controls required by state or local regulations may be supplied by
^ the user. This point is discussed later in the system overview.
4. OUTPUTS OF THE SYSTEM
The output of the REPS system is in two forms. One is the pro-
jected point and area source emission inventory given in the standard
; format of the NEDS system. All of the NEDS summary reporting pro-
grams may, therefore, be executed against the projected inventory.
One of these reporting programs is the NE11 program, which aggre-
gates all emissions into the National Emission Report (NER) format.
Also, air quality models which convert annual emission levels, as
given i-> the emission inventory, directly to ambient air quality, may
be used.
The other principal output of the REPS system is a printed sum-
mary of projection statistics and error messages which occurred dur-
ing execution of the program. This printout is valuable both for inter-
preting the projection results, and interpreting any computer problems
which may have occurred. This summary contains:
Listing of user-supplied override data
Assumptions and defaults exercised
Base year and projected fuel mix
Automobile emission factors for the projection year
Other related projection data developed by the program.
Any errors encountered during program execution are also included in
the output. Standard error messages include:
1-7
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Coding errors for user-supplied data
V
Any inability of the program to locate reference data from
mass storage files.
Diagnostic messages explaining the path followed during program exe-
cution to overcome these errors are included in the printout.
5. OPTIONS FOR USERS TO INPUT ADDITIONAL DATA
The REPS system is complete and autonomous to the extent that
the program automa:ically accesses all the input data described previ-
ously to project a complete emission inventory. However, there is
provision in the system for extensive user input and override capa-
bility. Override data superccdes or replaces those parameters cal-
culated automatically by the system which are used to forecast changes
in pollution-producing activity levels. The general categories of data
which may be overriden include:
All economic and demographic growth factors (SCC-
specific)
Projected fuel use and fuel mix
Projected transportation activity.
In addition the user may enter new data into ihe system whicii supple-
ments rather than overrides existing data. The user may specify local
emission control regulations which are more stringent than Federal
standards. The user may also input emissions inventory data for new
poinf sources expecfed to be operational in the future but which are not
already included in either the base year inventory or in the data on new
facilities for the five critical industries read by the program at the
option of the user.
6. POTENTIAL APPLICATIONS
Ihe HEPS Fy.stem is a tool whica may be i;r>cd to support any
program which involves estimating future omission levels. The pri-
mary goal of the KEPS system design and development effort was to
achieve maximum flexibility, as exemplified by the comprehensive
capability of the svstem to accept user supplied data.
1-8
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In particular the system may be used for the following applica-
tions:
Projected emissions, aggregated by emission source cate-
gory, may be used to identify the future major pollution
source categories in a region
The projected percent change in emissions from the base
year may be determined for aggregated emission source
categories
Emissions may be projected for alternate regional growth
scenarios to determine the sensitivity of the projections
to estimated growth rates
The projection scenario approach may also be used to
evaluate alternate emission control strategies.
The system is particularly well suited to projecting the effect of alter-
native growth/control scenarios mentioned above because of the ease
in modifying existing data or entering additional data into the model,
and because of the relatively efficient operation of the REPS program
from a computer systems standpoint. The flexibility which is charac-
teristic o,£ the REPS system maximizes its utility for the above appli-
cations and other potential uses.
1-9
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-*SW *
II. EMISSION PROJECTION METHODOLOGY
>,
f ' The purpose of this chapter is to describe in detail the method
| used in the REPS syrtem to develop emission projections. Familiarity
with both the general framework of the projection system and the spe-
cific procedures used to project emissions for each category of emis-
sion sources is essential for useful implementation of the system.
Factors which were considered in developing the general structure of
the system are discussed below.
1. EVOLUTION OF THE FRAMEWORK OF THE PROJECTION
SYSTEM
The objective of the REPS program was to develop a computer-
ized model to project annual emissions for Air Quality Control Re-
gions. Certain characteristics of the output of the system were
defined at the outset of the project. These included:
Projection of emissions at only one geographic level
Consideiation of only the five criteria pollutants particu-
lates, SO , NO , hydrocarbons and carbon monoxide
X X
Projection of all emissions in terms of tons per calendar
year
Capability to generate projections for any year between
1974 and 2000
Use of econometric forecasts as the basis for estimating
future emission-producing activity.
There would be areas of potential inaccuracy inherent to any
projection model developed according to these criteria. The AQCH
The system was, however, designed to accommodate input data
at a variety of different geographic levels (e.g., States, SMSAs).
II-1
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V
>
vrr»**(fa&e$jlW *H« Wef**~*&v
is a sufficiently small geographic region that the absolute accuracy
of any economic project;ons for AQCRs must be regarded with some *
caution. This is because it is extremely difficult to predict with con-
fidence local economic migration which results in economic growth of
one AQCR at the expense of neighboring AQCRs. Also, the industrial
sectors or categories for which economic projections are given are
usually defined on the basis of Standard Industrial Classification" (SIC)
codes. Emissions, on the other hand, are usually categorized accord-
ing to related emission processes or equipment, such as the EPA
Source Classification Code. Therefore, the correspondence between
economic sectors and emission source categories is not always straight-
forward. Lastly, activity levels for non-industrial source categories,
such as commercial or residential fuel use and some modes of trans-
portation, are not as directly related to purely economic indicators
as industrial activity. (The method used to calculate appropriate
growth factors for these sources is discussed later in this chapter.)
Although the general framework for REPS was specified by the
EPA at the outset, the approach to be used in meeting these broad ob-
jectives had to be developed. Two basic approaches were considered
originally. One of them involved using regional economic forecasts to
project a present regional emission inventory to the future. The other
approach involved determining projected regional economic activity and
translating the projected activity directly to projected emissions without
using the present emission inventory.
There are two significant disadvantages of the latter approach
which precluded its use in UEPS. First, economic projections pro-
viding the greatest industrial detail are typically given at the national
level, not the regional level. Regional disaggregation of national
forecasts would be required to determine projected regional economic
activity. The accuracv of any such national projections would be de-
graded substantially by regional disaggregation below the state level.
Second, economic projections typically provide detail at no better
that the two or three digit SIC level, which is not sufficient to identify
the mix of various industrial processes within an industrial sector for
a given region. The process mix must bo known to compute emissions
with any degree of accuracy.
Consequently the first approach 'mentioned above was implemented
in REPS. This approach, which was summarized in the preceding chap-
ter, involves the following operations. Present regional emission levels
Executive Office of the President, Office of Management and
Budget, Standard Industrial Classification Manual, 1972.
II-2
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are defined using a detailed emission inventory, and growth factors are
developed for future years for each emission source category. These
growth factors reflect the expected change in pollution-producing activity,
Base year emissions and activity are multiplied by these growth factors
to project future emissions, which are modified to reflect future emis-
sion control regulations. This method is the more accurate of the two
considered for three reasons:
The base year process mix, upon which the projections
are based, is defined by the region's base year emission
inventory. Although it is known that the NEDS inventory
of emissions is not entirely accurate for some AQCRs,
continuing efforts are being made to improve its accuracy
and the potential for obtaining very precise base year
emissions at some point in the near future through use of
NEDS is high.
The base year emissions for a given point source are
often based on stack tests or local emission factors, and
are more accurate than those which could be computed
from regional economic activity and national average
emission factors.
Emissions may be forecast on a point source basis, rather
than an aggregated source category basis. This is de-
sirable because equivalent uncontrolled emissions (and
hence equivalent pollution-producing activity) may be com-
puted for each point source, provided the extent of emis-
sion control employed in the base year is known.
The last factor is especially critical because of wide variation
among regions in control required for a given process or industry, and
the wide variation among poinf sources within a region with respect to
compliance with those regulations.
There are some disadvantages associated with the basic ap-
proach used in REPS and it is appropriate to review them briefly
here. The most accurate procedure 1o use in forecasting emissions
would be to project emission-producing activity, which in the case of
industrial process emissions is plant throughput, for each point
source. In the method used in REPS, uncontrolled emissions for
each point source are assumed to be equivalent to throughput and are
multiplied by I he same growth factor that is used for all point sources
11-3
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-» \
' '
related to the given industrial process. Clearly the accuracy of the
projections will be influenced by this approximation. In addition,
projecting the base year inventory to the future excludes the following
kinds of developments from affecting the future process mix within a
region:
Change in the process mix for a given industry to reflect
conversion from outdated or obsolete processes to more
modern ones (e. g., conversion from open hearth furnaces
to BOFs or electric arc furnaces in the steel industry)
Introduction of new processes within an industry already
present in the region
Relocation of new industries into or away from the region.
If such data are known by the user, they n ay be input to REPS through
the extensive user-input capability of the sy :' f:i. A final area for
potential inaccuracy in the REPS projection method is the inability to
allocate with precision that portion of projected activity governed by
Federal New Source Performance Standards, which are often more
stringent than regulations governing existing equipment. Uncertainty
in the projected emissions can occur if an increase in activity is due
to utilization of idle capacity rather than installation of new equip-
ment. The method used in REPS to apply both new source and exist-
ing source regulation? to the emission projections is also discussed
later in this chapter.
The discussion in the preceding chapter dealt with the general
framework of the REPS system. The following section describes in
detail th'? four sources of input data actually, used in REPS to develop
the emission projections within this general framework, and the re-
maining sections present specific information on the methodology
used and the assumptions made in projecting emissions for each source
category.
11-4
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2. SELECTION OF DATA SOURCES
Future emissions are projected by the REPS system based on
four sources of input data:
Economic and demographic forecast data from the SEAS
system " and the OBERS projections^
Base year emission inventories and related data from the
EPA National Emissions Data System (NEDS;
Growth and relocation trends for five heavily polluting
industries
Additional data supplied by the system user.
The three steps in the REPS projection methodology, as shown in
Figure 1-1 and discussed in Chapter I, are;
. Determining regional growth factors for pollution-
producing activity
Projecting present emission inventories to the future
Adjusting the emission projections to include the effect
of required emission controls.
As indicated schematically in Figure II-l, the four data sources are
combined to produce the output of the REPS system, projections of
activity and emissions which include the effect of future emission con-
trol regulations. General observations concerning the selection of
Environmental Protection Agency, Office of Research and
Development, Prototype Development of the Strategic Environ-
mental Assessment System (SEAS), April 1974, Draft.
U. S. Department of Commerce, Bureau of Economic Analysis,
Projections of Economic Activity for Air Quality Control
Regions (OBERS Projections), August 1973.
II-5
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FIGURE II-1
REPS Functional Elements
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PROJECTION OF
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PROJECTION OF
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CE EMISSIONS INVENT
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APPLICATION OF
REQUIRED EMISSION
CONTROLS
II-6
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the SEAS and OBERS projection data, and the NEDS inventory for use
in REPS are given below. Development of the growth and relocation
trends for five critical industries and identification of the data which
may be supplied by the user are topics discussed later in this chapter.
(1) SEAS Projection Data
The projections of national industrial growth by sector,
as developed by the SEAS .system, were user) for a number of
reasons:
The data are obtained from a sophisticated and
widely accepted input-output model of the national
economy and the accuracy of the projections was,
therefore, felt to be relatively high.
Substantial industrial detail is available because
284 economic sectors are represented in the
econometric model.
The SEAS data are especially valuable for project-
ing emissions because the SEAS system models the
effects of materials and fuels suostitution, tech-
nological innovations and industrial process changes.
These factors are iill critical for predicting future
levels of emission-producing activity.
The SEAS system was developed by EPA. Use of
the SEAS projection data in HEPS makes it possible
to compare emission forecasts generated by two
EPA models which utilize somewhat different
methodologies.
The REPS system is designed to produce annual emission.
projections to the year 2000, while the last year for which SEAS
projection data ,vere available was 1985. Consequently, national
growth for all industry sectors during the period 1985 to 2000
was assumed to bo 3.8 percent per year, which has been the
rate of real growth in GXP in the recent past. * Regional growth
It is assumed that the recent decline in real GXP is a transient
phenomenon.
II-7
-------
for all industiial sectors for this period \voald not necessarily be *
3.8 percent per year since t'.e OBERS data is used to compute the
regional share of national growth. This assumption does not rep-
resent a substantial degradation in the accuracy of the projections
for the years 1985 to 2000 because less confidence should also be
placed in the other sources of forecast data for long-term projections.
(2) QBERS Projection Data
The OBERS regional economic projections were used to region-
alize the SEAS forecasts. Although this approach involves sever?.!
basic assumptions and certainly introduces some decree of en or in
the final results, it was adopted for two basic reasons:
The OBEHS projections, developed by the U. S. depart-
ment of Commerce, are based en extensive local data
accumulated by the I'.S. Government, some of which
are confidential or proprietary and <"hich are consequently
no! available in other projection models
The OBERS tapes are one of the fe\v sources of regional
projection data available at the AQCK level directly.
The SEAS projections are given in terms of total gross output;
the OBEHS projections in terms of earnings. Both data are in
terms of constant dollars, which eliminates the effects of inflation
and permits real growth factors to be computed. In regionalizing
the SEAS projections of gross output, a scaling factor from OBERS,
based on projected growth m sector earnings, is used. Although
the relationship between output and earnings will not necessarily be
uniform throughout the country or even \vithin an AQCR, it is fc't
*hat the assumption made here will not introduce any severe errors.
Also fui damental to the projection methodology is the assump-
t'on that the giowth as computed from the SEAS and O1>ERS projection
Earnings, vhich comprise about 80"'( of persona! income or. an all-
indu.s'.ry basis, are defined as the sum of wages, salaries, other
labor inco-ie and proprietors' income. Because employees cent-rally
si.'ire proportionately with capital in the productivity gains c an in-
dustry, changes in earnings of employees tend to be proportional to
changes m total production levels.
11-8
-------
f 1SH
data is proportional to growth in pollution-production activity such
as plant throughput. In addition, the HEPS methodology is based
on the assumption that relative prices of industrial products will
remain static. This assumption may introduce error if the prices
of exhaustible mineral and energy resources increase substantially
relative to other industrial products, but it is difficult to estimate
the magnitude of the error with any degree of confidence.
(3) NEDS Regional Emission Inventory and Related Data
The XEDS inventory contains the following types of data
for point sources:
Base year emissions
Emissions perrritted by existing regulations and
compliance with these regulations
Operating data for new plants expected to become
operational in the future.
Tne area source inventory defines the levels of emission-
producing area source activity; it does not contain emission
data explicitly.
Two data sources related to the NEDS inventory are used
by REPS in developing the'emission projections. One is the
compilation of emission factors as published in EPA document
AP-42. " The other is a summary of Federal Xew Source Per-
formance Standards (XSPS) which govern emissions from new
and retrofit industrial equipment. This summary includes
standards already promulgated in the Federal Register, as well
as proposed standards which are likely to be promulgated in the
future. The proposed standards were supplied by the Emission
Standards and Engineering Division of the EPA's Office of Air
Quality Planning and Standards, and are given following page 11-35.
The computer file containing the emission factors used by
REPS is updated more often than :locument AP-42 and contains
current emission factor data.
11-9
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The NEDS system is used in REPS because it contains all
the data required for projecting a complete emission inventoryV
In addition to net base year emissions for existing point sources,
it contains data concerning both base year emission regulations
and future ooint sources, as defined previously. The data are
referenced sy AQCR, and the format of the data is uniform from
region to region. Since the projections are produced in this
data format, they are compatible with any of the NEDS/AEROS
summary programs or air quality models.
Some characteristics of the NEDS system should be kept
in mind when evaluating the emission projections developed by
REPS. First, the projected emission inventories will be no
more complete or accurate than the base year inventories from
which they art; developed. The extent to which the NEDS inven-
tory is complete, accurate and timely is in many cases difficult
to evaluate. The NEDS inventory for a given AQCR is considered
in REPS to be accurate for calendar year 1974, even though the
data may have been collected and submitted prior to that year.
This was done primarily because all jurisdictions are required
to update their inventories regularly, so that all data in the
NEDS system are in principle timely and complete.
The remainder of this chapter is devoted to a detailed descrip-
tion of all the sources of data mentioned previously, and a compre-
hensive explanation of how those data are used to develop projections
of activity and emissions. This discussion is presented in three
sections:
The development of growth factors from economic and
demographic forecast data
The analysis of growth and relocation trends for the five
critical industries
The methodology for projection future emissions and
activity and applying emission control regulations.
This discussion of the REPS rrethodology is followed by a summary
of the method used to implement the projection model on the EPA's
UNIVAC 1110 computer system, on which REPS is fully operational.
11-10
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3. DEVELOPMENT OF REGIONAL GROWTH FACTORS
The regional growth factors computed from exogenous economic
forecasts are used to estimate future activity and emissions. These
growth factors reflect changes in economic activity levels forecast
for the region, and are of fhree general types:
Economic growth for industrial sectors containing groups
of specific industrial processes
Growth for aggregated groups of economic sectors (in
terms of employment or earnings)
Growth in population.
The above growth factors are computed from the two sources noted
earlier:
National economic growth projections developed by EPA
using the SEAS projection system
The OBERS regional activity projections published by the
Department of Commerce.
The approach used in REPS to develop the industrial sector
growth factors from SEAS and OBERS data is presented in detail be-
low. That discussion is followed by a description of the method used
to compute the growth factors both for population and for aggregated
economic groups which are both computed from OBERS data exclu-
sively.
^ Industrial Sector Growth
The SEAS model of the national economy developed by
EPA, and incorporating the econometric and input-output models
created and maintained by the Bureau of Business and Economic
Research at the University of Maryland, produces fo> ecasts of
total gross output (TGO) for each producing sector in constant
dollars for each year between 1974 and 1985. " Since the sector
Refer to SEAS documentation for a detailed description of this
model.
11-11
-------
TGO is expressed in constant dollars for all years, dimension-
less growth factors reflecting change in sector TGO can be
computed. Thus, the growth in sector TGO can be directly
associated with changes in physical output. For those sectors
which have been disaggregated, the subsector outputs are ex-
pressed in physical units from which the dimensionless national
growth factor for the subsector can be computed. Sectors and
subsectors in general are defined at the industry group (2- or
3-digit SIC) level. Of the 185 primary sectors and 99 subsec-
tors, only 95 produce air pollution emissions and these are the
only ones considered in the REPS system.
The SEAS projections of national total gross output used in
the program are a standard output of the "base case" scenario. A
sample page of SI \S ouiput is shown in Figure 11-2. For each sec-
tor, the data for 1974 are national and the data for later years cor-
respond to the quantity (growth factor -1.00) No attempt to modify
ths SEAS project ">n data was made in REPS because the projections
are felt to be of sufficient validity and accuracy for the purpose of
the REPS system.
The SEAS projection data are processed by calculating lor
each sector and subsectnr the national growth factor for each
projection year with respect to the base year (1974). For pro-
jection year t and base year to, national growth GXa for SEAS
sector a is given by
GX (t) = TGO (t)/TGO (t ) , (1)
a a a o
where TGOa is the total gross output for sector a. The factor
GN is always dimensionless since total gross output is defined
in terms of either constant dollars or units of physical output.
The projections of national growth taken from SEAS are
regionalized using the OBERS economic projections, which
contain forecasts of regional growth in earnings for groups of
sectors. The OHERS data are used io def;ne the relative share
of SEAS national growth by industry sector for each AQCR.
The OHERS projections contain forecasts of regional
growth for groups of sectors. These projections were developed
by the Office of Business Economics (OBE>, presently the
Bureau of Economic Analysis of the U.S. Department of Com-
merce, and the Economic Research Service (EHS) of the (". S.
Department of Agriculture. The effort was initiated in 1P64
11-12
-------
FIGURE II-2
Sample SEAS System Output
Reproduced from
best available copy.
f^O« »«O»Art^r»\O J)lA^^*M-OfV<^*OO-*'nMA^'OOirW *T OO O ,fl ,f OJ f>- O
OOOOOOOQOOO
CT OOOOOOOOOOOOOOOOOOOOCPOOOOOOOOOOOO OOOOOOOOOOOfO OOOOOOOOOOC
trt OOOOOOUOOOOO'^fOC O » J 1 - * i '^ , ' j i ) i ,r.^j,.^-_.( '_)_, U C O « o O -* t_> -^ O Ot~ U O C1 O O O O O
11-13
-------
FIGURE 11-2 (Continued)
I I I
II If I
1 1 t
>Of~-« O '3 O O
- C ZJ (_> <_>
: ti o o D ^ c»
11-14
-------
v ) and is sponsored by the United States Water Resources Council.
Projections of population, employment and earnings have been
developed by state, water resources area, 173 OBE economic
areas, AQCR and SMSA. At the present time only OBERS data
for AQCR's are used by REPS, so that regional emission pro-
jections are available only on an AQCR basis. However, the
1 program was designed so that it can be readily adapted to pro-
duce projections for other geographic regions.
The OBERS projections were developed by the Commerce
and Agriculture Departments by rirst projecting growth in the
national economy and for each industrial sector on a national
scale, and then distributing the national totals regionally in
accordance with expected trends in the regional distributions of
economic activities. The projection and regional allocation
methodologies were based essentially on the extension of his-
torical trends, modified by the inclusion of available industry-
and regional-specific information.
The projection data includes regional population and em-
ployment, and regional earnings for 28 industrial groups defined
mainly at a two-digit SIC level of detail. The earnings pro-
jections are given in terms of constant 1967 dollars. The
OBERS projection data (earnings, population and employment)
are given for the years 1970 to 2000 in 5-year increments as
shown in Figure II-3. Before regional growth factors are cal-
culated in REPS, two operations are performed on the OBERS
data. These involve:
Corrections for any data withheld from publication
because of proprietary disclosures
Linear interpolation for intervening years.
The procedure used to correct incomplete or missing data is
described in more detail below.
Data are omitted from the OBERS projections whenever
publication would result in the disclosure of confidential or
proprietary information. In these cases either partial data are
published and indicated as such, or the data are missing com-
pletely. Thus, the status of any element in the projection data
could be either complete, partial or missing. Since data for
11-15
-------
FIGURE II-3
Sample OBERS Output
o o c. %o o-S-o o jo o5o£ o So oo o 5 o o
8 £ o? § S ooo o-o-o 8 SS ?oSSSS2 §2 o 2 o S o
r *" J * " ? % tit t £ *2 "* " *; t "* *2~ "";"" * * ~ * * * *
* ?
S oo£ o - 8 - & S So oooSooo oS S o o o e
« *
o
a
O*"« O» O O O O O O-O-O O OO OOODOOO OO 3 O S O OOfc
~«_^ -
3 r<
I??
i j ^
I- -0
ilii
±
J|
. r
3 "->
?I
j'l
;»
if
i
5
i
0
^
^
"
1
-
0 J
5; Q
S II
I .1 i
« -
11-16
-------
either the base year or future years could be affected, there
were a total of nine possible situations resulting from the vari-
ous combinations of data status (complete, partial or missing)
and year (base or future). The processing logic of the program
provides for each of these combinations with one of four cor-
rective actions employed. The logical matrix for correcting
incomplete data designed for use in REPS is given in Table II-l.
Table II-l
REPS Processing Logic for Incomplete
OBERS Input Data
Base Year
Data
. Complete
. Complete
. Complete
. Partial
. Partial
. Missing
. Missing
«
. Partial
. Missing
Projection
Year Data
. Complete
. Partial
. Incomplete
. Partial
. Missing
. Partial
. Missing
. Complete
. Complete
Corrective Action Taken
by REPS
None
Assume shift in regional share
is unity. This results in the
INFORUM national growth fac-
tor being used for the regional
growth factor.
Extrapolate base year value
from projection data; use the
extrapolated value or the given
partial value for the base year,
whichever is larger.
Extrapolate base year value
from projection data.
Correcting partial or incomplete OBERS data for at least one
industrial group was necessary for virtually every AQCR.
Following correction for partial or missing data, linear inter-
polation was used to compute projection data for all intervening
years which were not given specifically in the input data. This
operation produced projection data for each year between 1974
and 2000.
11-17
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The shift or change in regional share GS. of national
earnings for OBERS sector b is given by
E
-------
A set of regional growth factors were calculated in this manner
for each AQCR. Each set contains gro\vth factors for each SCC
process in the AQCR, for each year from 1974 to 2000.
(2) Growth for Aggregated Economic (iroups and Population
The process-specific growth factors discussed in the
previous section are used in the REPS system to project point
source emissions. Area source activity is projected using ad-
ditional regional growth factors calculated in REPS from the
OBERS projection data. These include growth in:
Population
Commercial/instUutional employment
Military employment
Earnings for the entire industrial sector.
Regional population projections, based on Series C Census pro-
jections as of August 1973, were available directly from OBERS
data. The m3thod used to develop the other three types of growth
factors is discussed in detail below.
Employment projections for the commercial'institutional
and military sectors were developed by first forming ratios of
national employment to national earnings for each projection
year for these two sectors from published OBERS data. Na-
tional employment forecasts for industrial groups are available
from OBERS but not. employment forecasts at the AQCR level.
These national time-dependent ratios were then used to estimate
regional employment based on projections of regional earnings
for those sectors. If FSit) and ES(t) are notional emplovment
and national earnings for vear t for the commercial/institutional
sector f and military sector g, and E(O represents regional
earnings for these two sectors, then the regional growth factor
GE(tp) for commercial'institutional employment for year t0
relative to base vear to is given bv
f" Fft }
p
-FSJt )
f P
Kb
-------
\
and the growth factor GM(tp) for military employment is given
by
GM(t ) - P
P
TFS (t ) n
h w]
Employment and earnings data for the military sector are given
explicitly in OBERS; employment or earnings for the commercial/
institutional sector wene computed as the sum of employment or
earnings for the following OBERS sectors:
Contract construction
Wholesale and retail trade
Finance, insurance and real estate
Services
Civilian government.
This approach is based on the assumption that regional ratios
of employment to earnings will not differ significantly from the
national ratios actually used. Clearly this assumption intro-
duces some error into the calculation but it -.\ras not felt to be
unreasonable.
A growth factor reflecting the expected change in overall
industrial activity was computed from the CBERS earnings
projections for the following sectors:
Agriculture
Mining
Manufacturing
Transportation, ommunications and public utilities.
The terminology used to represent these growth factors in the
projection equations given later in this chapter are as follows:
Population: GP(t)
Commercial/institutional employment: GE(t)
Military employment: GM(t)
Overall industrial activity: GKt)
11-20
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The value of each of these growtn factors for year t is defined
as (activity level for year t)/(activity level for the base year).
The application of these growth factors to the projection
of emissions levels for area sources is described later in this
chapter. In the following section an approach is described
whereby data on specific regional growth trends for five critical
industries were obtained. These results can be used in REPS
to override the growth factors for these five- sectors which are
computed from SEAS and OBERP. projections. In addition, the
user has the option to override many of the growth factors com-
puted automatically by REPS if more accurate local data are
available. The specific details on user options are presented
in Chapter III.
11-21
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4. ANALYSIS OF GROWTH AND RELOCATION TRENDS FOR
FIVE CRITICAL INDUSTRIES " '
The general forecast methodology employed in HEPS involves
projecting present regional emission inventories to future years based
on economic forecast data. This approach produces emission projec-
tions which do not reflect directly the impact of:
Relocation of new industries within the region
Substantial expansion of activity at specific existing plants
which exceeds that indicated by regional economic growth
projections.
In either case, future emissions as predicted by REPS would be sig-
nificantly understated.
There are two factors which indicate that the industrial compo-
sition of AQCR's with low current industrial concentration tray be
altered. These include:
The relationship of AQCR boundaries to concentrations
of industrial activities, and
The barriers hindering location of new plants in areas of
high industrial development and concentration, and their
consequent location in sparse'y settled areas that desire
new development.
In many instances air quality control regions contain groups of
counties of similar levels of economic development and consequently
sini'lar levels of ambient air quality. There are currently some
AQCRs with high concentrations of heavily polluting activities £.nd
many with low concentrations. A gradual shift cf future industrial
development from arras with a high concentration of industry to ad-
jacent areas with a lower concentration is a reasonable expectation,
based upon the prevailing "central hub" theory of regional develop-
ment. This pattern of future industrial development ;s encouraged by
legal barriers impeding or preventing location of certain industries
in areas with currently high industrial concentrations.
It can be expected that in some cases the SEAS and OBERS
economic projections, in addition to defining incompletely the devel-
opment of new industries within a region may *'ail to quantify precisely
11-22
-------
the expansion of certain existing industrial activities in the region to
the detail necessary to develop accurate emission projections. This
could be the result of migration of existing industries to sparsely
developed AQCRs from neighboring AQCRs for the same reasons that
new industries would choose to locate there. Alternatively, there is
the possibility that the growth rate predicted by SEAS and OBERS data
for a given industrial group (2-3 digit SIC level of detail) may be much
less than the growth rate of one or more of the component industries
of that group. This could happen when the earnings or total gross out-
put of one industry relative to the entire industrial group is small, but
the emissions of that industry are substantial.
If information concerning either relocation of new industries or
significant expansion of existing facilities is available to the user, he
may of course input those data to the system directly. Because such
information may not be available to the user, however, the data base
utilized by REPS was supplemented by an analysis of growth and re-
location trends for five industries which are among the heaviest indus-
trial r^Uuters.
In general the purpose of this analysis was to assemble data on
new plants expected to become operational in the future and on exist-
ing plants expected to increase their output significantly, in order to
improve the accuracy of the data base used by REPS to project emis-
sions. In particular the analysis focused on the following objectives:
Identification of factors necessary for determining the
location of new industrial point sources or expansion of
activity at existing industrial plants within an AQCR
Evaluation cf alternative assumptions concerning future
changes in the location of industrial activities that may be
appropriate for AQCR-level .emission projections
Appraisal of the advantages and limitations of prospective
techniques for determining possible industrial locational
shifts
Generation of specific new plant information, where pos-
sible, for selected industrial sectors.
There arc three basic alternative methodologies for determining*
the potential .''or industry location:
11-23
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Statistical models
Study of selected locational factors
Company new plant announcements.
Each of these approaches is discussed brieHy beiuw:
Statistical Models
A review of statistical models of industry location indi-
cates tnat reasonable projections can be obtained for long-
term systematic shifts in economic activity where large
numbers of economic units are involved, e.g., gasoline
service stations. However, where small numbers of
economic units are involved, the projections become highly
uncertain with respect to the timing and the geographic
location of new plants. For example, if an industry anal-
ysis of existing plant capacity and current and projected
demand indicates the potential for 5 new plants over the
next 10 years, projection of the year-to-year initial oper-
ation of these prospective plants would be highly specula-
tive as would projection of the probable location of these
plants within AQCRs.
In addition, observed trends in the regional orientation of
plants in the industry are used extensively in statistical
models. While these trends reflect true historical devel-
opment, they do not necessarily provide valid indications
of future location of plants when only a small number of
plants is concerned. For example, the fact that no new
plants have been built in a region over a period of 10 years
does not necessarily imply that none will be built there in
the next 10 years. Therefore, analysis of historical trends
in the location of industrial facilities appears to be irrele-
vant to the determination of the probable location of small
numbers of plants.
Study of Locational Factors
Study of selected locational factors for particular indus-
tries can yield information concerning the influence of
changes in the location of markets or resources upon costs.
Individual companies evaluate these factors in the planning
process, and information of this type is often the basis for
11-24
-------
investment plans and decisions relating to construction of
new plants. Therefore, for the intermediate term of
3-5 years, new plant announcements and plant expansions
would include the impact of locational factors.
For a longer term analysis (10-20 years), use of such in-
formation to postulate major shifts in industry location
would, of necessity, rest on speculative grounds with
respect to the timing of such shifts and the probable im-
pact of such shifts upon the industry composition of par-
ticular AQCRs. Because of the large number of uncer-
tainties implied in any such postulated shifts, particular
scenarios have net been developed in this analysis, though
the interface between REPS and exogenous new plant data,
as described later in this section- can utilize such data.
Company Announcements
The major advantages of utilizing company new plant
announcements for identifying and incorporating possible
industrial locational shifts in the emissions projection
system include the fact that:
»
Announcements are usually for specific types of
activities at particular locations; therefore the
pollution potential can be ascertained
The impact of any changing locational factors will
be (should be) weighted in the decision of the company,
The possible disadvantages and limitations of this type of
information are that:
Coverage may be inadequate due to unannounced
expansions or new plants
Plans for many announced plants are sometimes op-
timistic, and the plans may be postponed or can-
celled
Information is generally limited to 3-5 years in
advance of operation
11-25
-------
For the reasons indicated in the preceding discussion, neither
statistical models nor a study of locational factors were used in this
analysis to determine the potential for industry location; the method-
ology used was a review of company new plant announcements to iden-
tify future industry concentrations within relatively small areas.
Following the selection of an analysis methodology, the indus-
tries upon which the an; lysis would focus were identified. This was
done based on nationwide annual emissions data for 197i for the criteria
pollutants, as given in unpublished data produced by the SEAS system.
These data are summarized in Table II-2.
Table 11-2
Rank of Heaviest Nationwide Polluting Industries
1971 Sector Rank
Inforum Ssctor Part SCX- NOV CO HC
x
Electric Generation 21
Steel 44 - 1 6
Industrial Chemicals, Plastics
and Resins, Carbon Black - 6 342
Pulp Manufacturing 6 - 3 3
Petroleum Refining and
Heacing Oil 11 5 2 2 1
Copper Smelting 72 -
Stone and Clay Manufacturing 1 -
Grains 3 -
Cement, Concrete and Gypsum 5 - -
Zinc - 3 -
Glass - - 4
Crude Petroleum and Natural
Gas - 5
Source: Unpublished data provided by EPA, Washington Research
Center which was produced by the SEAS Test System as of
February 1974. Scenario 1.
11-26
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The first five industries listed in Table II-2;
Electric generation **
Steel
Chemicals, plastics and resins
Pulp manufacturing
Petroleum refining
were selected as the critical industries to which the case study analysis
was directed. It can be seen from the table that these five industries
are among the heaviest industrial polluters.
The major steps in collecting the data required for the analysis
of each of these industries were as follows. First, the potential
sources of data were identified following consultation with represen-
tatives of the Department of Commerce and trade associations. These
sources included primarily trade publications and financial and economic
papers. A comprehensive review of these data sources was then per-
formed to accumulate company new plant announcements.
This effort identified a number of plant announcements; however,
not all such data were included in the output of the analysis. The
criteria fcr selection of plant announcements for inclusion in the REPS
system were:
The dollar value of the expansion was greater than $5 million
Expansion as a percent of existing capacity was greater
than 20 percent
New equipment would not be replacing older equipment at
the same location
Sufficient location information was given to permit the AQCR
involved to be identified
The expansion was planned and announced with a high degree
of certainty or confidence.
With respect to the last criteria, sufficient degree of certainty
was indicated by one of the following conditions:
11-27
-------
Publication of a date for initial operation of the new equip-
ment
Announcement of contracts with engineering or construction
firms
Appropriation of funds approved by the firm's board of
directors.
These conditions are listed in descending level of confidence. If the
announcement indicated a lack of certainty in the proposal expansion,
such as discussing only the conduct of engineering or feasibility
studies, the proposed facility was not included in the output of the
analysis. These selection criteria were used to screen the plant
announcements in order to ensure that only the most probable indus-
trial expansions would be included in REPS, and that those which were
included would have more than a negligible effect on projected emis-
sions.
It should be noted that if the plant announcement did not give the
industrial capacity involved in the expansion, the capacity was esti-
mated based on the dollar value of the appropriation. Also, in some
cases the SCC code associated with the expansion could not be deter-
mined precisely from the announcement a "a consequently was estab-
lished using the judgment of industry report--.
In general the output of the analysis of relocation trends for
critical industries cont~ins data for either specific new plants or ex-
pansions to specific existing facilities. The results of the analysis
vary for the five industries considered, both in terms of the extent
of industry coverage, reliability of the data, and the future period of
time for which expansions were announced. A summary of the results
for each industry are given below:
Chemicals, Plastics and Resins
New plant announcements identified a number of new plants
and plant expansions associated with the rapid growth in the
petrochemical, plastics and synthetic fiber industries.
11-28
-------
Trade publications* follow these developments carefully
based on company announcements and follow-up surveys.
For inorganic chemicals related to fertilizer production,
the Tennessee Valley Authority (TVA) is credited with
careful analysis of new production capacity, though their
publication, Fertilizer Trends, is of limited usefulness
due to the long time lag between data collection and publi-
cation.
Locational shifts within the chemicals industry are not
expected because of the economic advantages associated
with major regions in which a number of chemical plants
already exist. One exception is plants producing sulfuric
acid, since a number of plants in the western states using
smelter gases for acid production are expected to be
closed.
The following limitations of using company announcements
for determining the location of new chemical plants should
be noted:
Many plant expansions are not announced or reported
in the trade press
Many plants produce several chemicals, hence process
identirications are sometimes very general
Heavil^ polluting processes cannot be differentiated
from those which produce lower levels of emissions
Since the number of chemical-producing companies
in any AQCR is sometimes small, data concerning
plant capacity, investment plans, and type of pro-
cess may be considered proprietary information
Many plant expansions do not involve long lead-times
so that most announcements concern only near-term
plans
Chemical and I-Jigineermg News, various issues, 1973-1974.
Modern Plastics, Supply Status Reports 1. 2 and 3. May, June,
July 1974. Americal Chemical Society, Chemistry in the
Economy, 1973. Batelle Columbus Laboratories, Cost of Clean
Air, 1974 (Appendix B).
11-29
-------
Steel
to
Company announcements* cover the plans of companies in
this industry in great detail for a period of up to five years,
particularly for the new mini-mills and the conversion from
open-hearth to EOF furnaces.
For integrated iron and steel producing, however, no new
U.S. mills have been announced despite the current and
projected shortage in processing capacity. Since an-
nounced expansion plans ordinarily do not significantly
alter the share of production for any one region, no
entries for this important segment of the steel industry
were included in the output of the analysis.
Petroleum Refining
Information concerning the location and probable timing of
new petroleum refining capaci^ is maintained by industry
associations for their members. * The status of the plans
and those of non-member firms are monitored by the
Federal Energy Administration, which is the source of
the data used in the analysis. §
Iron Age, various issues, 1973-1974. Business W-jek. May 11,
1974-August 3, 1974. The Wall Street Journal, various issues.
American Metals Market, various issues. Aletals Weekly, various
issues. Batelle Columbus Laboratories, Cost of Clean Air, 1974
(Appendix C).
Business Week, May 11, 1974 and Paul Nelson, "The Booming
Shortage of Primary Processing Capacity, " in Challenge, Jan. /
Feb. 1974, pp. 45-48.
Oil and Gas Journal, various issues, 1973-1974. American
Petroleum Institute, Refining Capacity Added in 1973 and
Publicly Announced Plans t^ Increase Refining Capacity in the
U.S. for 1974-1977, press release.
Federal Energy Office, Trends in Refining Capacity and Utili-
zation, June 1974.
11-30
-------
Pulp Manufacturing
Invesinient plans for this industry are surveyed by trade
associations. Plant and company information from these
surveys are considered priorietary. However, a parallel
survey is ccnducted by a trade publication.* This survey
yielded data comparable to that compiled by the associa-
tions, and was the source of data for this analysis. Some
of the SCCs associated with expansion of pulping activities
were estimated, since information identifying the probable
type of pulping process often is not provided and must be
inferred from other information.
Electric Power Generation
The most extensive information for any of the industries
studied is available for the location and type of new elec-
tric power generating plants. These data are collected
by the Federal Power Commission from Regional Reli-
ability Councils.* This information is based upon long-
term plans of the electric utility companies for increasing
generating capacity.
»
The limitations of these forecasts are as follows:
Assumptions concerning the availability of nuclear
power may be optimistic, thus leading to an under-
statement of the potential increase in fossil-fuel
generating capacity.
Specific locations for some new plants have not
been assigned; hence the AQCR involved cannot
always be identified precisely.
"Capital Spending, " Pulp and Paper, January 1974.
Federal Power Commission, Electric Utility Expansion Plans,
News Release No. 20143, March 20, 1974. Sec also Business
Week, May 11, 1974, and National Coal Association, Steam
Electrir Plant Factors, 1973.
11-31
-------
Potential new sources of fuel are not specified in the
Hata.
Fuel assignments for some plants are highly uncer-
tain; in many cases, several fuels were listed as
potential sources.
In some cases only tentative informatio-i concerning
the type of pollution controls was ava-iable.
Data for plants under 300 MW capacity were not in-
cluded.
Additional use:supplied data concerning forecasts of
regional fuel availability, particularly the availability of
low sulfur coal and oil, would enhance the REPS projec-
tions of emissions for electric generation.
The data developed on new plant locations for the five critical
industries studied during the REPS development effort contain the
following information for each specific plant or facility:
Plant name and description
'. SCC code
AQCR
XEDS plant identification code (if associated with an
existing facility)
Year in which the expanded facilities .are expected to
become operational
Estimated annual capacity.
These data are input to REPS at the option of the user. The data and
the format in which they must be coded for input to REPS are given in
the program documentation in Chapter III. Before entering the data
into REPS, however, the user must obtain the NEDS plant identifica-
tion code for each existing plant in the AQCR for which critical indus-
tries' data are given.
n-32
-------
The general method by v.'hich the critical industries data are
input to the emission projection system is as follows. First the data
are sorted so that only plant expansions which involve the AQCR under
study, and wMich are expected to be operational by the projection year,
are considered. Based on the plant identification code and the plant
SCC, it is determined whether each plant for which expansion is in-
dicated is already included in the base year XEDS inventory. If it is
not, then r. new point source record is created, and future emissions
are estin-ated using the standard REPS projection methodology appro-
priate Tor the given source category. The growth factor used to pro-
ject emissions is adjusted to reflect growth from the year in which the
expanded facility will become operational, instead of from the normal
base year (1974).
In the event that the expansion involves a plant included in the
XEDS inventory, it must be determined whether the plant throughput
as defined in the critical industries data exceeds the plant throughput
as computed from the inventory data and the appropriate emission
factor. The results of this comparison are independent of whether
data for the year in which the expansion becomes operational or for
the projection year are used; this is because the same SCC-specific
growth factor is used to adjust the data from one source to the same
year as the other source. The emissions entered in the projected
inventory for the plant in question are computed from either the ex-
pansion data or XEDS, whichever indicates greater plant throughput.
This assumption results in worst-case emission projections for the
plant involved.
From the preceding discussion it can be seen that the plant-
specific expansion data may have the effect both of enlarging the
projected emission inventor; , and of overriding the SEAS-O3ERS
growth factor for those plants for which expansions ha^e been
announced.
11-33
-------
5. DESCRIPTION OF THE METHODOLOGY FOR PROJECTING
FUTURE .ACTIVITY .AND EMISSIONS
In Section 3 a description of the method used to develop SCC-
specific industrial growth factors and related economic growth factors
was given. In this section the methodology used.in REPS to project
the base year emission inventory to the future using those growth fac-
tors, as well as future emission control requirements, is presented.
The REPS system projects future regional activity and emissions
by applying dimensionless growth factors to base year activity and
emissions as given in the XEDS point and area source emission inven-
tory. The general procedure for projecting point source emissions in
REPS is to compute projection data for each individual point source in
order as contained in the inventory until the entire point source inven-
tory in XEDS for the selected AQCR has been considered. Net emis-
sions for the projection year, including the effect of future emission
control regulations, are computed for all point sources.
The procedure for projecting area source emissions is to com-
pute future area source activity for each record in the NEDS area
source inventory. One NEDS area source data record ordinarily con-
tains a summary of area source activity for a given co.inty. :; For area
sources tfce output of the REPS system is projected activity, and not
emissions, because the NEDS area source inventory does not contain
emissions data explicitly. Area source emissions are computed in the
NEDS system by NEDS/AEROS summary reporting programs such as
NE11.
The REPS system does not include emissions controls for any area
source category except gasoline highway vehicles. Regulations affecting
emissions from these vehicles will have the ultimate effect of lowering
the emission factors appropriate for future years. REPS, in addition to
projecting activity for gasoline highway vehicles, computes weighted
highway vehicle- emission factors which reflect these regulations. These
All NKl.i.'j area .source data records are identified by AQCR;
when RJJPS projects area source activity all area se.jrce records
for the AQCR in question are processed. In the event tnat a
given AQCR contains only a portion of a county, NEDS either
contains an area source record for that portion, or the area
source activity for that portion is included in the record for
another countv.
11-34
-------
\vciqhted emission factors are computed according to the method specified
in document AP-42 (including Supplement No. 2), and include the Affects of
vehicle age and model year distribution. The weighted emission factors
are based on national average data for projected composite emission factors
and for the model year distributions given in Attachment No. 1 to AP-42.
Weighted emission factors for the projection year are used to com-
pute future emissions from gasoline highway vehicles, and these emissions
are included in the HEPS printed output. Program NEli, on the other hand,
when executed against the projected area source inventory, computes future-
emissions based on projected activity but using current vehicle emission
factors. Consequently the projected gasoline vehicle emissions from the
HEPS printout should be substituted for the gasoline vehicle emissions in
the NER or any other emissions summary.
There are t\vo types of poir.t source emission control regulations.
One type, the New Source Performance Standards, governs only equipment
installed after those regulations become effective. The other type governs
all equipment, regardless of whether it was installed before or after pro-
mulgation of the standards. Typically new source standards are more strin-
gent, because investment in new equipment justifies investment in pollution
control. Control peculations may be promulgated at the Federal level or at
the regional level (state or local). There arc four specific classes of con-
trol regulations considered in the HEPS system:
Controls required in the base year, as reported by NEDS. A
point source may, or may not, be in compliance with those re-
quirements dui ing the base year.
Federal New Source Performance Standards (NSPS). Standards
already promulgated m the Federal Hegister and standards ex-
pected to be promulgated in the future are included in the REP<
data file. These data are summarized on the following page.
Local ne\v source performance and .standards tjovermncr existing
equipment, entered by the user.
State Implementation Plans (SIP) contain for manv jurisdictions the
most .stringent of all applicable emission control regulations. At the pres-
ent time ."-sIP data 'k-fimne required control efficiencies arc not MV-«liable
in a computer file. The HEP-> ~v.-iti-rn has the capability of ai'tomaticalh
accessing .MP -:at;j v/hen the. bi-.-ome available. I ntii then, emission
-------
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control required by state or local regulations must be input to REPS
by the user.
A fundamental element of the projection methodology is the pro-
cedure used to incorporate these future point source emission control
requirements in the projection of emissions. Since new source stan-
dards affect the emissions of new equipment exclusively, the activity
level of every point source during the projection year which is attrib-
utable to equipment governed by new source standards must be iden-
tified. This is done by allocating all positive growth in activity after
the year the new standards become effective to new equipment, an
approach which assumes that any increase in activity is due to new
equipment and not to utilization of idle capacity.
The specific methodology for projecting activity and emissions
is described in five sections which follow:
Definition of terminology
Point source industrial process emissions
Point source emissions from stationary fuel combustion
and solid waste disposal
; Transportation area source activity
Area source activity for fuel combustion and solid waste
disposal.
(1) Definition of Terminology
The following notations are used in the equations given in
this chapter:
1. Subscripts
c: Source Classification Code (SCO
d: Sneoific noint source
i: Pollutant (point and area source)
11-36
-------
Particulates
NOX
SOX
HC
CO
j: Fuel (point and area sources)
Anthracite coal
Bituminous coal
Lignite
Residual oil
Distillate oil
Natural gas
Process gas
Coke
Wood
Liquid Petroleum gas
Bagasse
Solid waste with coal
Diesel (stationary sources)
Gasoline (stationary sources)
Aircraft fuel (stationary sources)
k; Customer category for fuel use (point and
area sources)
External combustion, electric generation
External combustion, industrial
External combustion, commercial/
institutional
Internal combustion, electric generation
Internal combustion, industrial
Internal combustion, commercial/
institutional
Internal combustion, eng ne testing
Solid n-aste disposal, government
Solid waste disposal, commercial/
institutional
Solid waste disposal, industrial
11-37
-------
m: Road speed class for highway vehicles
(area sources)
Limited access
Rural
Suburban
Urban
n: Highway vehicle type (area sources)
Light-duty gasoline
Heavy-duty gasoline
Heavy-duty diesel
p: Solid waste disposal method (area sources)
On-site incineration
Open burning
Sludge incineration
Auto body incineration
Rail car incineration
q: Transportation sourre categories (exclud-
ing highway vehicles and aircraft) (area
sources)
Off-highway vehicles, gasoline
Off-highway vehicles, diesel
Rail locomotives
Vessels, diesel
Vessels, residual oil
Vessels, bituminous coal
Vessels, gasoline
r: ^Aircraft type (area sources)
Commercial
Civil
Military.
H-38
-------
2. User Override Data
The value of any parameter designated with "*"
may be overridden at the option of the user. If the user
does not supply an override value, a default value is
automatically calculated by the program. For example,
GP*(t) is the population growth factor, which is used a
number of times in developing the projections; the default
value for this parameter is computed from the OBERS
projections. If the user supplies an alternate value, that
value is substituted every time the program references
the population growth factor.
3. Exogenous User Data
Unlike the user override data described previously,
these data do not override default values calculated by the
program; these data supplement internally calculated data
to provide the user with additional ways to input growth
information to the program. If these exogenous data are
not supplied, the program uses the standard or default
procedures to project emissions. The data which can be
input include:
*
GV (t) = Growth factor for VMT of highway class m
*
GFU (t) = Growth factor for highway vehicle fuel type
*
RT (t) - Projected share of total VMT for highway
vehicle type n
*
GFV* (t) = Growth factor for transportation source cate-
gory q (excludes highway vehicles and aircraft)
*N
GFA (t) = Growth factor for aircraft type r
:!:
PE (t) = Percentage of total residential space con-
ditioning Btu demand satisfied by electricity
RE (t) - Change in the fossil fuel residential Btu demand
due to substitution of electricity.
11-39
-------
4. Notations for Point Source Calculations
The following terms are used in the equations for
projecting point source emissions. The terms refer to
data for individual point sources,
NEDS Inventory and Related Data: The follow-
data are read from the NEDS emission inventory
for each point source for the base year (t ): the
output projections are composed of data in the
same format for the projection year (t ).
E ,.(t) = net emissions for point source
d and pollutant i
AE,.(t)= allowable emissions for point
di , ,, . . .
source d and pollutant i
t = year in which the source will
comply with allowable emis-
sions
C ,.(t) = control efficiency for point
source d and pollutant i
A..(t) = emission factor (from NEDS
* emission factor file) for pol-
lutant i and fuel j
Growth Factors (SCC-specific)
GR (t) = SCC-specific growth factor for
year t corresponding to SCC
process c, computed as
discussed in the previous sec-
tion
Internally Developed Data
EU ,.'t ) = uncontrolled base year
di o ... . ,
emissions for point source d
and pollutant i
11-40
-------
EN ..(t) = future net emissions for
point source d and pollut-
ant i controlled by NSPS
ER ,.(t ) = future net emissions for
point source d and pollut-
ant i controlled by exist-
ing source standards
B ,,.(t) = Btu demand for a given
* point source d for fuel j
within customer cate-
gory k
BF (t) = Btu demand for fuel j
^ within customer cate-
gory k (considering all
point sources)
BC. (t) = total Btu demand for
customer category k
RF*Ct) = fuel use ratio for fuel j
within customer cate-
gory k
GF..(t) = growth factor for fuel j
within customer cate-
gory k
Emission Control Data
*
CN. = control efficiency for
pollutant i as required
by NSPS
*
t = year in which NSPS be-
come effective
*
CR. = control efficiency for
pollutant i as required
by existing source stan-
dards.
11-41
-------
5.
Notations for Area Source Calculations
The following terms are used in the equations for
projecting area source activity. Unless otherwise noted,
the terms refer to activity data aggregated to the geo-
graphic level of NEDS area source records (usually the
county level).
*
NEDS Inventory and Related Data
FVt}
area source fuel use for
fuel j within customer
category k
SAkp(t)
tonnage of area source
solid waste disposal for
disposal method p within
customer category k
fuel use for highway
vehicle type n
VMT (t)
m
measured vehicle miles
travelled for road speed
class m
FVq(t)
fuel use for off-highway
vehicles, rail and vessels
for source q
LTr(t)
landing-takeoff cycles
(LTD) for aircraft type r
BTU.
J
Btu content per unit fuel
for fuel j
MG
n
average miles per gallon
for highway vehicle
type n
Growth Factors
GP*(t)
population growth factor
for year t
11-42
-------
*
GE (t) = growth factor for com-
mercial/institutional em-
ployment for year t
*
GM (t) = growth factor for military
employment for year t
Gl (t) = growth factor for total
industrial activity for
year t
Internally Developed Data
BA..(t) - Btu demand for fuel j
within customer cate-
gory k
ED. (t) = Btu demand for customer
category k
*
RA (t) = Fuel use ratio for fuel j
within customer cate-
gory k
SD, (t) = Solid waste tonnage for
customer category k
*
RS. (t) = Solid waste disposal
method ratio for method p
within customer cate-
gory k.
(2) Point Source Industrial Process Emissions
The methodology for projecting emissions from industrial
process point sources involves the following general steps:
Net base year emissions are first converted to un-
controlled emissions using the base year control
efficiencies given in NEDS.
II-43
-------
SCC-specific growth factors are applied to the un-
controlled emissions to project future uncontrolled
emissions. This is equivalent to assuming that
changes in uncontrolled emissions are proportional
to changes in plant activity as given by the growth
factors.
Uncontrolled future emissions are reduced to com-
ply with emission control standards for the projec-
tion year.
Fundamental to this approach is the assumption that activity is
proportional to uncontrolled emissions and hence that growth
factors reflecting the expected change in activity levels can be
applied to uncontrolled emissions.
Three types of required emission control which affect pro-
jected emissions are considered in REPS:
Allowable emissions as reported by NEDS
* Federal NSPS and/or local standards governing new
equipment (referred to as "new standards")
Local standards governing existing equipment (re-
ferred to as "existing standards").
The general approach for projecting industrial process
emissions involves developing the emission projections for each
individual point source in sequence. The projection methodology
is discussed in detail below.
The equations given in this section are applicable to each
point source in the inventory. There are three alternate
approaches used to project future emissions; the approach used
for a given point source depends on the type of control informa-
tion, if any, supplied by the user. The alternate approaches
are:
No control standards given.
In this case, projected emissions for each point
source d for pollutant i are given by:
H-44
-------
E ,.(t ) = E ..(t ) GR (t ) <7>
ai p di o c p
Where GR (t ) is the growth factor for .he SCC "c"
c p
corresponding to the point source d in question.
This is equivalent to assuming that the extent of
emission control for the base year will be used for
the projection year.
Only new standards given.
Emissions governed by new standards are given by:
ENdiV = VV -fGVy-GW]- (1-CNi)/(1-Cdi> (8)
Emissions not governed by new standards, but con-
trolled to the same extent as in the base year are
given by:
ER,.(t ) = E (i ) GR (t ) (9)
di p di o en
Projected emissions are therefore:
E ..(t ) = EN ..(t ) + ER (t ) (10)
di p di p di p v '
Both new and existing standards given.
Emissions governed by new standards. EN, -ft ).
are given by equation (8). Emissions governed by
existing standards are given by: .
ER,.(t ) = E,.(t ) GR (t ) - (1 -CK.)/(1 -C. ) (11)
di p di o en i di
and projected emissions art- given by equation (10).
The last step in the projection sequence is to ensure that
projected emissions do not exceed allowable emissions as given
by NEDS. If the projection year, t , is prior to the compliance
year, t , then the source is not required to be in compliance by
11-45
-------
the projection year and projected emissions need not be reduced.
If the projection year is later than the compliance year, howe^ei*
then it is assumed that the source will comply to the regulations
and
E,.(t ) = AE,. no)
di p di *L£I
is substituted for the projected emission level if the projected
emissions exceed the allowed level.
(3) Point Source Emissions from Stationary Fuel Combustion
and Solid Waste Disposal
Emissions from point source fuel combustion, including
electrical generation, are forecast by determining the projected
Biu demand for each customer category, and then apportioning
the Btu demand to the fuels expected to be used for that customer
category to satisfy the projected Etu demand. Specifically, the
projec:ions involve the following steps:
Net base year emissions for each point source are
first converted to uncontrolled emissions using the
base year control efficiencies, and then to fuel con-
sumption using national average emission factors.
The base year fuel use in equivalent Btu? for ?ach
point source is computed based on average Btu con-
; tent factor, vhich are incoi porated directly in REPS.
The future Btu demand for each point source is de-
termined based on SCC-specific growth factors.
The base year and projection year Btu demand for
each customer category are determined by summing
the base year and projected Btu demand for each
point source within each customer category. (Cus-
tomer categories are defined earlier in this section.)
Growth factors for each fuel, for each customer
category are computed based on base year and pro-
jection year Btu demand, and the fuel mix for the
f[-46
-------
projection year for each customer category. In the
absence of user supplied fuel mix data, the base
year fuel mix is used. These growth factors are
then used to project the fuel use for each point
source.
. Future net emissions are then computed based on
the emission factors incorporated in NEDS and emis-
sion controls required during the projection year.
Emissions from solid waste disposal are computed in a
similar way. except that the amount of solid waste burned,
rather than the Btu demand, is determined for each customer
category in tne base year and projection year, and the projected
tonnage is allocated to disposal methods in the same way that
future fuel mix is used to allocate the projected Btu demand.
The equations which follow define the method for project-
ing fuel combustion emissions. The equations are valid for pro-
jecting emissions from solid waste disposal as well; in that case,
subscript "k" refers to solid waste customer categories, and
subscript "p" refers to disposal method. Uncontrolled base year
emissions for pollut-^t i for each point source d are given by:
EUdi(V = W'u-V (13)
Projected Btu demand for each point source d for year t can be
computed from the uncontrolled emissions for only one pollutant
using the emission factor A. for pollutant i and Btu equivalent
BTU. for fuel j: l
J
B,,.(t ) = EU..(t ) BTU. GR (t )/A.. (14)
QKJ P di o . j c p 13
for customer category k and fuel j, where GR (t ) is the growth
factor for the SCC process "c" which corresponds to the point
sources. The specific pollutant i for which data is used to com-
pute the projected Btu demand is determined by selecting the
first pollutant in ascending subscript order for which both base
year emissions E ,.{t ) and the emission factor A., are nonzero.
di o n
For year t , the Btu demand for each fuel j within customer
category k is computed from the Btu demand for each point
source d within that customer category as
11-47
-------
BF, .(t ) = B.. <* > <15>
kj p Z-- dkj p
d
The Btu demand for each customer category is
V
BC.
-------
If the user supplies some, but not all, of the projected fuel use
ratios for a given customer category, then it is assumed that the
fuels for which no ratios are supplied will be used in the base
year proportions. In other words, if some RF^.(t ) are given,
then the remaining RF, .(t ) are given by: * "
KJ p
RF (t ) = "J " /i - "v " T»TI ' /x »\ (22)
kj P " Y" RF, .(t )
L-i kj o
j not
specified
The preceding equations define the growth factor GF (t ) which
is used for each point source in the inventory, within customer
category k, and burning fuel j. The method for applying this
growth factor to the emissions data for each point source is
identical with that given previously for industrial process emis-
sions. That method involved:
Multiplying uncontrolled base year emissions
EU,.(t ) by the appropriate growth factor GF,.(t )
to project future uncontrolled emissions
Allocating the projected increase in activity to the
* portion governed by NSPS and the portion governed
by existing standards, and adjusting the projected
uncontrolled emissions to account for the effects of
required emission control.
(4) Transportation Area Source Activity
Activity for the following five transportation source cate-
gories is projected by the REPS system:
Highway vehicles
Off-highway vehicles
Rail locomotives
Vessels
Aircraft.
The following section contains a description of the projection
methodology for highway vehicles. This is followed by a section
11-49
-------
describing the projection methodology for the four remaining
transportation source categories.
1. Hignway Vehicles
Base year activity for highway vehicles is defined in
XEDS in terms of two types of related data: fuel use by
vehicle type (light-duty gasoline, heavy-duty gasoline and
heavy-duty diesel vehicles) and measured vehicle miles
travelled (VMT) by average road speed class (limited
access, rural, suburban and urban roads). Inclusion of
fuel use data is mandatory for the XEDS area source in-
ventory; VMT data are optional and are included when
available. Consequently the projection data include either
fuel use only, or fuel use and VMT, depending on the type
o! data included in the XEDS base year7 inventory. The
approach used in REPS to project transportation activity
depends in part on the method used in the XEDS summary
reporting programs to compute emissions from transpor-
tation activity. The XE11 program computes emissions in
one of two ways:
If measured VMT are given, the VMT for each
road speed class are allocated to the three
vehicle categories.based on fuel-use and
nationwide estimates of average miles per
gallon. Emissions are computed u?ing emis-
sion factors which reflect the average vehicle
speed for each road speed class.
If measured VMT are not given, fuel use for
each vehicle category is converted to VMT
using nationwide average miles per gallon, and
these data are then converted to emissions
using emission factors which are based on
nationwide average^vehicle speeds.
Thus all growth information developed internally in REPS,
or supplied by the user, must be translated to expected
change in fuel-use or VMT.
While the general approach used in REPS to estimate
future transportation activity involves using scalar growth
11-50
-------
factors to project base year activity to the future, the
specific approach utilized in the program for a given areav
source record depends on both the type of override data,
if any, supplied by the user, and whether VMT data are
given in the base year NEDS inventory. There are five
different calculation methods for projecting future activity;
Table II-3 identifies the approach corresponding to all
possible combinations of user supplied data, as a function
of whether VMT data were given in the base year inventory.
Table II-3
Method of Projecting Highway Vehicle Activity
As Determined By the Input Data
USER SUPPLIED DATA
GVMT
RFU
GFU
VMT GIVEN IN NEDS
NO
3
3
5
5
3
3
3
3
YES
«
1
2
2
4
1
4
1
Projection
Method
(1 through 5)
For example, if both GVMT and RFT are supplied by the
user, and VMT data are included in NEDS, Method 2 is
used to project activity.
The five alternate projection methods arc as follows:
Method 1
Projected VMT for highway class m is given
by
VMT (t ) - VMT (t ) GV (t ) (23)
m p mo m p
11-51
-------
*
If GV (t ) is not given by the user then
VA1T (t ) = VMT (t ) GPV(t ) (24)
m p mo p
Method 2
Projected VMT for highway class m, obtained
as in Method 1, is given by equations 23 and 24.
Projected fuel use for vehicle type n is then
computed from total projected VMT and user-
supplied data defining the projected share of
total VMT:
FU (t ) = > VMT (t ) RT (t )/MG (25)
np \^> m p np n * '
I m J
Method 3
Projected fuel use for vehicle type n is com-
puted based on growth factors for each vehicle
» type:
. FU (t ) = FU (t ) GFU*(t ) (26)
n p no n p
Method 4
Projected fuel use for vehicle type n is com-
puted aj5 in Method 3, according to equation (26).
If GFU"(t ) is not given then
n p
FU (t ) = FU (t ) - GP*(t ) (27)
n p no p
These fuel projections and the base year VMT
are used to compute projected VMT for each
highway class m:
VMT (t ) = VMT (t ) .y (FU (t ) MG )/Y] VMT (t )
m p mo *' n p n *' m o
n m
11-52
-------
Method 5
Projected fuel use for vehicle type n is first
computed as in Method 3, according to equa-
tion (26). These fuel projections are then
adjusted to conform to the user-supplied data
defining the projected share of total YMT for
each vehicle type n:
FU (t ) = V [FU (t ) MG RT'"(t )/.MG
n p * ' I n p n J n p
(29)
The five preceding methods are used to project future
activity (VMT and fuel use) for highway vehicles. These
data are then entered In the projected area source inven-
tory. In addition, HUPS computes emissions from highway
vehicles based on this projected activity and includes these
emissions in the printed output of the system. Emissions
are calculated according to the method specified in EPA
dc":ument AP-42. This method involves computing weighted
emission factors appropriate for projection years which in-
clude the effects of vehicle age and model year distribution.
The data used to compute these weighted emission factors,
also taken from document AP-42 and Attachment No. 1 and
Supplement No. 2 to AP-42, included low altitude, non-
California test emission factors and national model year
distributions, tor more information on the method or data,
consult document AP-42.
2. Off-Highwav Vehicles, Rail, Vessels, and Aircraft
Rase year activity is given in terms of landing-
takeoff cycles (LTD) for aircraft, and in terms of fuel-
use for all other sources. In general, activity is pro-
jected bv multiplying base vrar activity for each source
categorv bv a scalar growth factor reflecting 'he expected
change in activiu for that category. The general equation
for projecting fuel-use for off-highway vehicles, rail
locomotives and vessels for source category q is;
FV (t ) -- TV (t ) G(t ) ,
q p q ° p
11-53
-------
where G(t ) is the appropriate growth factor (see below).
The general equation for projecting LTO cycles for air-
craft type r is
LTr(tp) = LTr(to) - G(tp) . (31)
where again G(t ) is the appropriate growth factor.
The growth factors for non-highway source cate-
gories are as follows:
Off-highway vehicles:
Diesel: G(t ) = GFV (t ), otherwise
* P q P
GI (t )
P *
Gasoline: G(t ) = GFV (t ), otherwise
* P q p
GP (t )
P ^
Rail Locomotives: G(t ) = GFV (t ), other-
* p q p
GP (t )
P
Vessels
Diesel: G(t ) = GFV*(t ), otherwise
P q P
cr
-------
Military: G(t ) = GFA (t ), otherwise
* p r p
GM (t ).
P
The option in each cese is used when the user does not
provide input data.
(5) Area Source Fuel Combustion and Solid Waste Disposal
Activity
In general, future area source fuel combustion is estimated
by projecting the Btu demand for each customer category and
allocating that demand to the fuel mix for the projection year.
Future levels of area source solid waste disposal are estimated
by projecting the future level of solid waste disposal for each
customer category, and distributing that amount among the
various methods of disposal. The specific approaches for pro-
jecting these area source activities are given below. Activity
for each area source reporting region (usually a county) is pro-
jected independently in HEPS. However, user supplied data for
area source projections are applied to all regions. The equa-
tions presented refer to data for a given reporting region.
The methodology for projecting emissions from area source
fuel combustion is as follows. Base year Btu demand for fuel j
and customer category k within the AQCR is given by
BVV = FAk.(to) BTU. (32)
where FA (t ) is the consumption of fuel j within the customer
ki o
category k and BTU. is the Btu equivalent for fuel j. Total base
year Btu demand for customer category k is given by
v^ (33)
BD, (t ) = > BA.. (t )
k o f-^> jk o
Base year fuel use ratios are given by
RA. .(t ) = BA. .(t )/BD. (t ) (34)
kj o kj o k o
U-55
-------
and future Btu demand for each customer category is
BD. (t ) = BD, (t ) G(t ) , (35)
k p k o p
where:
G(t ) = GP (t ) RE (t ) for the residential cus-
P P - P
tomer category. RE"''(t ) is the user-supplied factor
reflecting the change in the projected fossil fuel
Btu demand due to substitution of electricity. If
PE*(t) is the percent of total residential space heat-
ing and cooling Btu demand satisfied by electricity in
year t, then the change in the projected residential
Btu demand for space conditioning is
*
) / 1 - PE*(to) I
- PE(t ) - (36)
If RE (t ) is not supplied by the user, it is assumed
to be 1.0, indicating that electricity in the projec-
tion year will account for the same share of the
residential Btu space conditioning demand as it did
in the base year.
G(t ) = GE (t ) for the commercial/institutional
p p
customer category
G(t ) = GI (t ) for the industrial customers cate-
P P
gory.
The projected fuel use for fuel j in customer category k u
FA, .(t ) = BD. (t ) RA.'".(t )/BTU. <37)
kj P k p kj p j
Where RA. .(t ) is the user-supplied fuel mix for the projection
kj P , ::-
year. If the user does not supply RA (t ), then the base year
fuel mixes are used. ^
(38;
RA, .(t ) = RA, .(t )
kj p kj o
II-56
-------
The projection methodology for area source emissions
from solid waste disposal is as follows. The base year solid
waste level for customer category k is given by
SD. (t ) = 5" SA. (t ) (39)
k o * ' kp o
P
where SA, (t ) is the solid waste for customer category k dis-
posed of by method p. The base year disposal method ratios
are given.
RS. (t ) = SA. (t )/SD. (t ) (40)
kp o kp o k o
Future solid waste levels are given by
SD, (t ) = SD. (t ) G(t ) (41 }
k p k o p
Where
_ GP^(t ), for the residential customer cate-
gory
G(t ) = GE (t ), for the commercial/institutional
P . P
customer category
j,
G(t ) - GJ (t ), for the industrial customer cate-
P P
gory.
The projected levels of solid waste for disposal method p within
customer category k is
SA, (t ) = SD, (t ) RS* (t ) (42)
kp p k p kp p
where RS, (t ) is the user-supplied disposal method ratio for
kp p
the projection year. If the user does not supply RS, (t ) then
the base year ratios are used, ^
RS, (t ) -- RS, (t ). (43)
kp p kp o
[1-57
-------
This Section has presented the analytical methods and procedures
used in the REPS projection system. There are implicit in the methods
used a number of important assumptions which have been identified in
the text. It is emphasized that, although the equations which have been
used in REPS are considered to be reasonable, they could certainly
be refined substantially to achieve greater projection accuracy in
many cases, and it is expected that the REPS methodology will be
almost continually improved.
Chapter 111 of this documentation provides a detailed description
of the ccmputational procedures used to translate the methodology de-
fined and described here into a working model. The following, and
final, section of this chapter presents a brief overview of the tech-
niques used to implement the model.
n-58
-------
6. ADP IMPLEMENTATION OF THE REPS SVSTEM
The preceding sections of this chapter contain a presentation
of the functional and mathematical procedures used in the REPS sys-
tem to forecast future activity and emissions. The mathematical
model described by the equations given above has been implemented
on the EPA's UNIVAC 1110 computer svstem and is fully operational
at the present time. In this section an overview of the present com-
puter program configuration of the REPS system is given. This over-
view focuses on identifying the correspondence between elements of
the projection methodology discussed previously and program elements
of the computerized projection system. In addition, a brief functional
description of the various computer programs which form the REPS
system is also given.
A functional system flow diagram is given in Figure II-4. The
figure identifies the various modules of the REPS system, illustrates
the flow of information within the system, and identifies the corre-
spondence between program modules and the four primary sources
of input data discussed earlier in this chapter.
Referring to Figure II--4, it can be seen that the REPS system
is modular in structure, consisting of a number of independent pro-
grams. Additional segmentation within the complex REPS module is
achieved by distributing the program's operations to various subrou-
tines. All the modules are grouped into two distinct subsystems,
the static system and *he dynamic system.
The purpose of the static system is to process all the exogenous
input data which are static in nature and to organize these data for
access by the dynamic system. These exogenous data include the
SEAS and OBERS projections containing economic and demographic
forecast information, and the file of emission factors incorporated
in NEDS. Modules of the static svstem need be executed only if anv
of the exogenous input (fata are modified or updated. The dynamic
system reads all input data, both econometric and emission-related,
which are neressarv to develop emission projections for the AQCR
and for the year of interest. The emission projections are developed
by modifying the data in the base year emission inventors' to reflect
changes in activity levels and emission control, while preserving
the format and structure of the invrntorv records. Projections for
other years or geographic regions require additional executions of
the dynamic svstem.
-------
u
Is
>ft
p >
Is
FIGURE 11-4
Descriptive Flow Diagram for REPS
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The modular approach was used in designing the REPS computer
system in order to maximize the eff-citncy of projecting emission
for a large number of geographic regions. Only the dynamic system
must be executed to produce emission projections. Furthermore,
when running certain projection scenarios, only a limited number of
the modules of the dynamic system may need to be executed. The
modularity of the system eliminates redundant or unnecessary opera-
tions, resulting in the REPS system being a valuable tool for scenario
projections btrause the required CPU time and operator assistance
are minimized.
In order to produce emission projections using the REPS sys-
tem, the user must specify only the AQCR and the projection year.
When he inputs that information via punched cards he may at his op-
tion also input the card deck containing growth data for the five criti-
cal industries. While this is the minimum input required of the user,
he may of course override virtually all the data used by the system to
predict growth for every emission source, and he may supplement
the data concerning future allowable emissions with state or local
emission control regulations. Identification of all available user-
supplied input data is given in Chapter III, which contains complete
program documentation of all REPS modules in standard AEROS for-
mat.
The output of the REPS system is in two forms. One is the
projected point and area source emission inventory given in the stan-
dard format of the NEDS system. All of the NEDS summary reporting
programs may, therefore, be executed against the projected inven-
tory. One of these reporting programs is the NE11 program, which
aggregates all emissions into the National Emission Report (NER)
format. Also, air quality models which convert annual emission
levels, as given in the emission inventory, Hrectly to ambient air
quality, may be used.
The other principal output of the REPS system is a printed sum-
mary of projection statistics and error messages which occurred
during execution of the program. This printout is valuable both for
interpreting the projection results, and interpreting any computer
problems which may have occurred. This summary contains:
Listing of user-supplied override data
Assumptions and defaults exercised
H-61
-------
Base year and projected fuel mix
Automobile emission factors for the projection year
Other related projection data developed by the program.
Any errors encountered during program execution are also included
in the output.
The format of the projected point and area source emission
inventory, as well as identification and interpretation of all possible
diagnostic and error messages is given in Chapter III. A summary
printout of the REPS system for a typical projection scenario is
given on the following pages.
U-62
-------
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III. DESCRIPTION' OF REPS P HOG HAM MODULES
The modules of the REPS system were identified in the previous
chapter. Figaro. III-l, the general REPS system flowchart, shows
the input-output relationships of those program modi.-les. This
chapter contains an abstract and a detailed description of each of
these modules. This information appears exactly as given in the
AEROS program documentation of the HEPS system. Additional
information concerning these modules can be found in the program
documentation; the following topics are discussed for all program
modules, in which the following:
Module flow charts
Input-output description
Test data
Operating instructions
Suggestions, warnings and changes
Program listing.
III-l
-------
\
FIGURE III-l
General System Flowchart
-------
1. PROGRAM \E053 (SKAS)
ABSTRACT
The purpose of the FORTRAN program NK053 (SEAS) is to
extract and process national economic growth projections from the
input file and to write a file which contains those growth factors from
1974 to the voar 2000. It is necessary to execute this program only
when the INFOKU.M economic projections in the input file have been
updated.
The input file is a standard output of the SKAS1' system and was
provided bv EPA Washington. The SKAS projections are based on Die
1NFORK.M input-output econometric model. For further information
consult the REPS design methodology presented earlier in this report,
as well as the SKAS program documentation. The file contains projec-
tions of national total gross output for each INFORUM sector and sub-
sector for the years J971 to 1985 in one year increments, and reflects
the "base case" SKAS scenario. I:; the absence of INFORUM projection
data after this time period, growth for the period 1985 to 2000 for all
sectors was assumed to be 3.8 percent per year. A'aticnal output for
an entire INFOKIM sector is given in millions of 1%7 dollars, and
for sirbsectors within a sector, output is given in physical units. In
eith.er case dimensionless real growth can be computed. Sectors and
subsectors in general are defined at the industry group (2 or 3 digit
SIC) level.
Program NK053 performs three distinct operations:
Locates records which contain the required data fertile
years li)74 (base year) through 1990
Assigns data f:>r each, sector/suhse'^tor to a unique SEAS
output section
Stratc-ju Environmental Assessment Svslem, an econometric
and er.M-j-:un forei acting model. '!:>< SKAS model was devel-
oped bv t!.t K.PA Oii'iie of Research and Development,
Washington, !). C .
Ill-'':
-------
Calculates scalar growth (from the base year) ratios for
each INFORL'M sector and suhsector.
The output file created by the program contains national growth ratios
associated with each IN FORUM sector for each project'on year. This
file is read by the program NF055 (MAP), which also reads the output
file of program N11054 (ORF.RS) containing the growth in regional share
for each of the 28 OBFRS sectors for the same years.
RUN INSCRIPTION
The INFORUM input file is a FORTRAN variable-length, fixed
block file, it is recommended that the program remain at KPA
Washington:; because of the difficuitv in reading IBM-generated,
variable-length FORTRAN records on a UN1VAC system. The file
contains 10 types of records:
Record 1 - Header
Record 2 - General sector and run description
(Begin sets of 8 records, one set for each year's data)
Record 3 - Miscellaneous data
Record 4 - Consumer .pure-liases sector
Record 5 - Output sectors (dollars)
Record 6 - Output subsectors (physical units)
Record 7 - Net imports sectors
Record 8 - Employment sectors
Record 0 - Capital investment sector
Record 10 - Construction sec-tor.
The program NL053 (SI.'AS) and the INFORUM input file are
resident on the IBM 370/158 svsteni located at Optimum Systems.
Inc. (OSI), Bethe-ida, .Md.
III-l
-------
Out of the 10 record types, only two types are required for processing
by the program. These- are Records 5 and G. Record 5. "Uutp.it ^
Sectors" contains tot'-l gross output d ta (in constant dollars) for each
IN'FOKUM sector, while Record (3, "Output Subsectors, " contains
total gross output data in physical units (tons, Btu's. etc.) for each
INK^Rl.M bubsector.
Only 9' of i'ie 185 primary sectors and 99 subsectors produce
air pollution emissions and thu.-» have correspondence to an SCC pro-
cess. Hence the SKAS program calculates growth radios only tor
these sectors and sub.sectors. Table Ill-l show? the sector number
a..signed in this program to each of the 1NFORUM sector-subsector
combinations which correspond to SO" processes. This numbering
system was developed for use internallv by the modules of the RKPS
system. In this case the output sector codes are referenced by pro-
gram NK055 (MAP).
-------
Table 1II-1
IXFORUM Si-ctor Identification Matrix
Description
Cotton
Phosphate Hock
Titanium Ore
Coal
Jndjs. Combustion: Coal
Oi», Petroleum, Gas
Stone and Clay
Meat
Da i r v
Grain
Sugar (Beet)
Sucar (C'ane)
Candy
Liquor
Misc. Food
Text i leg
RllfiS
Wood
Milhvork
Furniture
Pulp
Industrial Chemicals
C'hlonne
Nitric Acid
Hvdrofluorsc Arid
Sulfur'c Acid
Phosphoric Acid
Sod i u ! i! Ca rbona t e
F e rt 1 1 1 ? e r
Pesticides
Misc. Chemicals
' 'arhon Jjiar k
Plastic & MI-.C. Plastics
Plastic Material
Rubber Produr ts
Svnth.i.-tii Rubber
KKPS
IXFOHUM IXFOKU.M Sector
Sector Subsector- (used internally)
4
9
9
14
14
15,60.70
16
23
24
26
28
2«
29
30
33
35,37,38,30.40
3C
41
43
»5,46
47
55
55
55
55
55
55
55
50
GO
61
fil
62.74
62
03,72.73
63
^
9-02
9-03
-
14-01
-
-
-
-
-
28-01
^8-02
-
-
-
-
-
-
-
-
-
-
55-01
55-02
55-03
55 -OG
55-07
55-08
-
-
-
6J-01
- -
-
-
-
400
902
903
1400
1401
1599
1600
2300
2400
260C
2801
2802
2000
JO 00
3300
3599
3600
4100
4300
4509
4700
5500
5501
5502
5505
550G
5507
5508
5000
GOOO
0100
6 I 0 I
6200
6200
6 3 09
6300
III-B
-------
Table III-l (Continued)
UK PS
Description
Cellulose Fi'ut rs
Non-Cellulose Fibers
('leaning Preparations
Paint
Gasoline
Heating Oil
Indus. Combustion: Oil
Paving k Asphalt
Tires & Inner Tubes
Rubber Products
Misc. Plastic Products
Leather Prod.
Glass
Structural Clav
Potterv
-------
Table 1II-1 (Continued)
Description
Non-Ferrous Rolling
Non-Ferrous Casting
Metal Cans
Misc. Manufacturing
Other Fabricated Metals
Electric Utilities
Electricity by Coal
Electricity by Oil
Electricity bv Natural Gas
Electricity: Low Sulfur Coal
Electricity: High Sulfur Coal
Electricity: I.o\v Sulfur Oil
Electricity: High Sulfur Oil
Electricitv: High Temp. Gas
Elfctricitv: Water Reactors
Electricity: Gasified C'oai
Electricity: Natural Gas
Process Spent Fuel Rods
Natural Gas
Indus. Combustion: Gas
Water and Sewer Service
IN FORUM
Sector
89
91
92
93-102,104-143
101
160
160
160
160
160
160
160
160
160
160
160
130
160
16'
16
162
IN FORUM
Subsector
-
-
-
-
-
160-01
160-02
160-03
160-30
160-31
160-32
160-33
160-34
160-35
160-36
160-37
160-33
-
161-01
-
REPS
Sector
(used internally)
8900
9100
9200
9399
10100
16000
16001
16002
16003
16030
16031
16032
16033
1G034
16035
16036
1603?
1G038
16100
16101
15200
III-!!
-------
2. PROGRAM NEC
-------
sectors. The latter are ha ;eci on regional earnings pro-
jections for these sectors, and national ratios of employ
ment to earnings for thes< sectors.
Three output files are created by the program, two permanent and
one temporary. One of the two permanent files contains regional
base year data and projected growth factors for commercial/
institutional employment, military employment, population, and
personal income. This file is RF.P3-GK.MPL, and the data it contains
are referred to in the program documentation as "regional growth in
employment. " This file is read directly by the RKPS program. The
other permanent output file contains regional earnings for each of the
28 OBl'HS industrial sectors, and growth factors reflecting the pro-
jected regional change in share relative to national earnings forecasts.
This file is read by the program NK055 (MAP), which also reads the
national earnings forecasts from SKAS and produces projection growth
factors for each OBKRS hector to be used by the RL'PS program. The
temporary file ;s created to store data read bsr the program from the
ORKRS input tMe for later use by the program. This file may be
scratched after execution of NK05-'- (OB)'RS) program is complete.
HUN INSCRIPTION
There are two distinct phases of this program. During the first
phase the projections for earnings, population and personal income
are read from the input file and are accumulated ever all AQCRs to
produce national projections for each. vcar. I'.ach record is processed
and only those daUi which w'll lie needed by the program during its
second phase are written or. a temporary storage file. During the
second phase of the program the temporary file is read and the regional
growth factor.-, for each industrial sector in each AQC H are computed
in sequence. The permanent output files are written after all the data
for a given AQCK ha\e been developed.
The output data stored on the permanent file later read bv HUPS
consist of the folluwim.'-
National population, personal mrnme, commercial.1'
institutional employment and military employment for
all yr.it-,
I'or each At.vH'i', s_T'"owth. factors for each of the above
variable?- for eacn proicvtiun year, defined as (future level)/
Ill-10
-------
The output data stored on the permanent file later read by MAP
consist of the following:
National earnings data for each OHKHS sector for base
year and projection years
For each AQl'R, factors reflecting the regional shift in
share of national earnings forecasts defined as:
(projected regional earnings)/(projected national earnings)
(base year regional earnings)/(base year national earivngs)
Table III-2 shows for each of the 28 OHHRS sectors the Department of
Commerce code (by which the projection data ai e indexed on the input
file), and the HEPS sector number used internally by RKPS system
modules. These sector numbers (by winch the data referenced in the
.MAP program) are assigned in this program.
111-11
-------
Department of
Commerce
Sector
Table III-2
OBERS Sector Identification .Matrix-
Description
REPS
Sector
(used internally!
8110
8120
8231
8210
8220
8232
8300
8410
8420
8430
8460
8491
8440
8450
8492
8493
8494
8471
8472
8481
8482
8495
8500
8600
8700
8800
8910
892C
Agriculture
Forestry £ Fisheries
Metal
Coal
Crude Petroleum & Natural Gas
Nonmetalhc, Except Fuels
Contract Construction
Food & Kindred Products
Textile Mill Products
Apparel & Other Fabric Products
Lumber Products &. Furniture
Paper & Ailit d Products
Printing & Publishing
Chemicals
-------
3. PROGRAM Ni:055 (MAP)
ABSTRACT
The FORTRAN' program \K055 (MAP) combines econometric
growth projections from the .\K053 (SKAS) and NK054 (OBERS) pro-
grams to produce regional growth factors from 1974 to 2000 for each
SCT, and creates a mass .storage file containing a list of all SCC codes
and the corresponding regional growth factor. The main element of
this program i.-> a mapping table winch contains the SKAS and OBERS
sector numbers corresponding to each of approximately 350 SCC
codes. The regional growth factor for each SCC is computed from the
growth in national total gross output (as given by NK053)and the shift
in regional share (as given by NK054).
Program NK055 (MAP) is a module in the static subsystem of
the RKPS svstem; due to the nature oi' the data it uses and creates the
program must be executed onlv when one or more of the following con-
ditions occur:
1) Execution of the OBI.'RS program of the RKPS system is
required due to creation of a new Department of Commerce
(OBKRS) regional earnings projection. (The next DOC
update of the OBF.RS protections is scheduled for 1970. )
The IN'K055 program must then be run to update the RKPS
regional growth factors.
2) Execution of the XK053 program of the RKPS system is
required due to update of Ilie 1NFORVA1 econometric
mode), resulting in updated SEAS projections of national
economic- growth. The .\K055 program miibt then be run
to update the RKPS regional growth factors.
3) Addition?., deletions or corrections of the SCC-OBERS-
iNEOUl M sector mapping matrix would necessitate a
rerun o! the MAP program.
Rl'X !)1,.-;C K1PTIO\
in order :o r< late Ihc IM'ORl'M and OB EH.1.: eccnornc projec-
tion data lo t';:>:s^ion or>entcd SCC proces.-.*--;, a comorei.ensivc
m?ip[);ng of S'-ctor re !atioi:.T!«!p-, was (ie\'elo;)ed. Sir.i'e the sector
-------
definitions for the INTOIU'M and OBERS systems arc SIC oriented,
the methodology for creating a cross-index or map from one system
to the other involved a rather simple comparison of the SIC categories
included in each sector. \Vhile in most cases tho mapping involved
aggregating a number of IXFORl'M sectors to form one OBKKS sec-
tor-, there are a few cases where the IXFORl'M sector is mapped to
two or more OBERS sectors. This difficulty inherent in the inverted
mapping was overcome hv aggregating the OBKRH sectors to a level
which no longer requires disaggregation of an IXFORCM sector. Two
examples of situations in which the approach was used are the OBERS
sectors for Agriculture and Forestry-Fisheries, which were aggregated
to form one OBERS sector so that IXFORUM sectors 08 and 10 would
not have to be disaggregated.
The sector definitions for IXFORl Al and OBERS econor .ic pro-
jection data are given previously in Tables III-l and III-2. Table III-2
shows for each of the 28 OHKHS sectors the Department of Commerce
code (bv which the projection data are indexed on the OBEHS input file)
and the REPS sector number used internally by the REPS system.
These sector numbers (bv which the data are referenced in the MAP
program) arc assigned in program XE054. Table ill-l shows the
IXT'ORUM sectors arid subsectors which are associated with air
pollution emissions, and for each sector-subsector combination the
RKPS'asector number used internally by the REPS system. These
sector numbers (by which the data is referenced in the MAI1 program)
are assigned ;n program AE053. Xote that, when the two rightmost
digits of the output sector are ''!', the output sector represents an
aggregation of two 01 ;aore 1X1 ORFAi sector-- or sub.sectorp.
In order to determine the projected growth in gross national
product original ini! and tho shut in regional share for each SCC
process, relationships amoni1 IXFORl'M and OBKRS economic sectors
and all ^C'C' pri.ce.'.-e.- w<:re developed. Tins mappinc or cross-index
is Liven in "ia--lo lii-... "I he IXI OKI A! and OTHERS sector desigriat ions
siio-.'. n in 'I able 11!-.-) an- '.host- v. inch .vere d.-fim d in Tables III-l and III-2,
re.-pccr iveU , *o be i;-o 'ec' ior. xear, a growth
facto;- v.'r,u:h. ri'Ti1 c; - ro'h pro:- c''"i national i \~<>\\'\ \\ (,rc>m 1X1 ORI'M)
ar.fi pro]f-c»._'(i .-'r,i:t >M faoh re-, ion's .-hai< of M.U* nanc-nal grov.'th (froni
(;P.J "'.y'). A cn;r.p!( tr (ic^cnpt ion of t!ic mcti-.ricioloyv utilizc-1 in the
RI'J'S sv- t'.-in to t.m.-.p-jti- tiicM :M-ov.-;h facto:--; i1- ^.ivi-n (.'ailn-r in tins
III-! I
-------
Table III-3
INFORUM-OBERS-SCC Mapping Matrix
?cc
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Table III-3 (Continued)
3P2C1193
30 20 12 93
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111-16
-------
Table III-3 (Continued)
30900199
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III-17
-------
4. PROGRAM NK050 (AP-42)
ABSTRACT
The purpose of the COBOL program NE050 (AP-42) is to con-
vert the NEDS Emission Factor file to field data format. In addition.
it also reduces each 603 character record to an 80 character record.
The program, part of the static system, was first executed for the
initial creation of the KL'l'S Emission Factor file. Subsequent runs
of the program are necessary only if an update to the master NEDS
Emission Factor file has taken place.
Rl'N DESCRIPTION
The COBOL program NE050 (AP-42) converts the NEDS Emis-
sion Factor file to field data and reduces each 603 character record
to an 80 character record. The resulting file contains the SCC value
and the emission factors for the five criteria pollutants. The pro-
gram consists of two components, a COBOL main program and a
FORTRAN subroutine. The main program reads the COBOL-
oriented input file and pdnses the necessary data to the subroutine
(NEA050), which writes the reduced record in field data format,
readable by the REI*S System. The program need only be executed
when the NEDS Emission Factor file is updated; in that case the
entire Emission Factor file must be read as input by program NE050.
Ill-It!
-------
5. PROGRAM \F051 (NKUS-IN)
ABSTRACT
The COBOL program Ni:051 (NKDS-IX) extracts, reduces and
converts into field data those NLDS-Ij'SLR file point and area source
records \vlnrh match the region code (AQCR, state or nation) specified
in tne program run control card. Kach resulting output record contain:-
abbreviated .\L1XS emission inventors data in a form readable bv tiie
FORTRAN program M;25.'i (RLPS).
RT\ DLSCRiPTIOX
C'urrentlv the M.051 (.\i:i)S-I.\) program is designed to process
only one geographic region at a time, either the nation as a whole, a
state, or an AQ( R. If a number of regions are to he processed this
program must be run once for each different region.
The program contains three maior components. One i» a
COBOL main routine which read.-, the entire \LDS-l SLR hie. tests
the geograpi.jc region of the XLDS recori'.-; for acceptance, and passes
control iiiul the nece.-'sarv data fields to the appropriate FORTRAN
.->ubrou:itines. Ti;e other c on.ponents are two subroutines, one for
point record.-. (NLfJUol) anri one for area records (XLAOT)!), v/hu-li
merf'iv write the parsed data in the output file as omi:>.->io'i invcr'.orv
recorrls wliich crintaui .\L1)S ciata in a format cor.ipatibic v/ith pro-
gram \F!2.r).;. T"< order of a rea ^ouj'Cf oul|)iit ret ore;- corresponds
to the order in n-.'neh the ifipu: rec-ord~ v. ere read, wh;l< the point
^ourc'c rffo:d-> are -^orted !>v SC C code fir^t and ti;er! arc- written in
the o'.'tuut :'.ic.
111-1'
-------
6. PROGRAM NI-,253 (REPS)
ABSTRACT
Program NF.253 (REPS module) is the nucleus of the entire
emission projection system. The relationship of this program to
the rest of the system is illustiated m the next section (Flow Charts).
Following all necessary initializations, the program locates all re-
quired growth factors and modifies these as required to reflect user
supplied data. Kach point source and area .source record is then read,
?nd activity and net emissions are calculated for the projection year.
The program writes an output fil" containing the projected records
(these are converted to NEDS-U.^ER file forma, by program NE052)
as well as 2 summary report containing a complete documentation of
all assumptions and postulations used in computing the emission pro-
jections.
RUN DESCRIPTION
The FORTRAN program NE253 (REPS module) consists cf a
main program and five subro itinos. The following section deals with
the main pVogram; and that is followed bv a discussion of the sub-
routines.
1. Main Program
The REPS main program contains essentially all of the
I/O commands for the REPS module. The reduced NEDS-USER
file is read one record at a time along with any of the miscel-
laneous data files which may be required *o process that record.
Basf d on the type of ret ord, the program will call the appro-
priate subroutine for the actual projection calculations. The
data which are passed to the subroutine contain the key base
year NEDS data required in the projection equations in addition
to the growth factor fo- that year. Control is then returned to
the mam program section to write ihe updated projection NEDS
records. Tlu- cvclt- is then repeated until all records are pro-
t«.'.->; f«i. C'urrentlv the- program \:-, set up to "loop"' back for
pro- '-ssing of another region or a different projection year for
the ;>airu' region.
III-UO
-------
The flow of information through the HKPS "Alain", as in
the five subroutines, is essentially sequential through all pto-
gram statements as thev appear in the program listing, except
for minor branching to miscellaneous read and write error
routines. Comment cards appearing throughout the program
listing give very concise explanations of the function of each
section and subsection.
The KFPS ".Mam" program is divided into five functional
sections. Duplication of some oi the programming statements,
neecssarv to make each section independent of the others, was
done to facilitate understanding of the program listing. These
five sections are as follows:
Initialization Section
-XF.LJS Point Processing Sect ion
XF.US Area Processing Section
Frror .Messages A. Formats Section
Final Statistical Section.
The following paragraphs describe- the opeiation uf Ihese
sections:
Initialisation Section: 1 his section is executed once,
at the beginning of the run; its purpose is to perform
all neccssorv functions preliminary to the process-
ing of point and area source emission records. First
the run control card, winch contains the protection
year and .AQC'R, is read. Then all user supplied
data is read and stored. .All miscellaneous input
files containing AQC 11 specific data are read to
locati- the fne segments containing ciata for the AQCH
specified on the run control card. Fmallv, the emis-
sion :nventorv files arc read to obtain data for cal-
culatinu the fuel i:se ami ha.->e vear !>tu demand for
each customer cnte^orv (in subroutine .\K.-\2.">3
UHT ( .M.H. This data is ,'t!-o u.-,ed later in '-om-
P'.it:i,g future r.tu demand in ^ubrout ;ne (OMHIS.
NKDS ;'>;;!» J'roc e.-s:n;- St-.-fio:;- in thi^ s. rtion tl-e
reciu HI: \i"i)S point records '.->ortcd hv SC ( previous!*'
iti t!:c \KDS-1N p-odule) art' read .-.etjuent:^llv an
-------
Projection dtita arc obtained from the different input
files by matthmg their SC'C' value to the SC'C of the
XKDS record. At least a six-digit .SC'C' match is re-
quired at all time->. Hrowth factors are obtained and
recalculated if an override option was exercised.
(A .summary of available user options and overrides
are discussed in detail later in this section. ) Based
on the first digit of the SC'C' of the N'KDS record,
control is parsed to the appropriate point source? sub-
routine for the actual project in calculations. (There
are six such subroutines or entry points; the first
digit of the SC'C' must be between 1 and 6. ) Descrip-
tion of the variables that are passed are given later
in this section. After the emissions have been pro-
jected, control is returned to the "]\lain" program
and the updated projection record is written. Then
another XKDS point record is read, and the cycle is
repeated. At the end of the file of point source
records, control is passed to the XKDS Area Section.
XKDS Area Processing Section: In the initial series
of statements all area source growth factor^ are
calculated prior to reading the first reduced XKUS
area record. Then the two area projection sub-
routines are called in scries, one for transportation
activity projections and the other for non-transportation
activitv projections. Control is tl.^-n passed back to
".Main" for writing the area projection records.
Another area record is read and the process is
repeated. At the end of the li!e of area source
records, control is passed to the Final Statistical
Section.
l-'rror Me^asjes and Format Section: This section
contain.-) all write and format statements for anv
error messages, and i.-> accessed frcm anv other
section onl>' to print out error message.-:. Descrip-
tion^ of son,*1 of the Lev error messages arc in-
cluded in Section 6.
Final Statistical St'Ction: This section prints ^um-
ir.arv result.-) of the run. The.-,e include:
-------
Record count by SC'C type
Percent change in emissions from base year
to projection year for emission source cate-
gories (each source category contains all
SC't's for which the first ihree digits are iden-
tical)
Percent change in area activity from the base
year to the projection year
Emissions by transportation vehicles.
2. Subroutines
The five subroutines of program NE253 (REPS module)
are described in this section.
NEA253: This subroutine (BTUCAL) is executed
only once, at the beginning of the HEPS ".Main"
prugiarn. It generate:; the Btu ratios for each fuel
type for tho^e point records which contain fuel use
data. The Btu ratios are computed for each cus-
tomer category as the Btus consumed for each fuel
divided bv total Btus consumed for all fuels. In
addition to generating the Btu ratios, the subroutine
calculates growth factors for each fuel type within
each customer categoi y based on projected Btu
demand for each customer category.
The four remaining subroutines include two for point source
projections and t\vo for area source projections. There are a
total of seven entrv points to the point source processing sub-
routines, and a total of two entry points to the area source
processing ^ub routines.
NEH253: This subroutine (COMBVS) calculates the
projected point source emissions for those records
m v.hich emissions were the- result of fuel combus-
tion, or solicl waste disposal. It accesses informa-
concerning b:i.<=e vcar fiud u^c and Blu denumd for
each customer cah-gorv, v.hich was calc.ul.itc-d in
thr subroutine BTl (\\L.
-------
M-X'251; lliis subroutine (INUI'HC) calculates the
projt cted emissions for those point records in which
the omissions wore the result of industrial processes,
evaporation, or miscellaneous point sources.
Xl-:n253: This subroutine (AKKASC) is called to cal-
culate projected increase in non-transportation ac-
tivity for area records.
X i:i:2 53: This subroutine (TRANS) is called to cal-
culate projected increase in transportation activity.
Table 1II-4 contains a summary of information concerning
entry to the five subroutines. For each individual entrv point,
the subroutine containing the entrv point is given, as well as
the tvpe of XKDS record which is processed (point or area),
and the criteria used in the "Main" program to branch to the
given entry point.
The Rl'PS system is complete and autonomous to the extent that
the program contains all the data required to project a complete emis-
sion inventory. However, provision is made in the system for exten-
sive override of this data with alternate data supplied at the option of
the user. These user .vupphed data can be divided into two types:
Data which affect the projected change in activitv levels
(growth factor.--,)
Data which affect projected emissions by altering or sup-
plementing the ba.->e vear enussion inventory data.
Instructions for entering user-supplied ciata into the Ul'.PS system are
given in Section 5 of ihe documentation for tins modulo. FiL'ure 111-2 con-
tains, for each emission producing activtv category, the available
user overrides of the first tvpe, together with the factors which are
used bv the program to proier t activity in the absence of user c>< er-
!".-er .--applied data to override SC'C'-specifu- growth lac-tor
rc-vKi bv the program from, the \ A DI >-KT .PS-C O.UP-ST f'!e; all other
override- data reference in I-i.'u?-'' HI-2 ar-e re ad from 'he user override
option.-/ rare! m;/':l .
-------
Table III-4
Subroutine Entry Points and Kntry C'ritcria
Kntrv Point
Name
COMBUS
Subroutine
Containing
the Kntry
Point
NEB253
Type of
MKUS
Record
Point
Records
Criteria for Branching to the
Kntry Point
Initialization of the subroutine
BTUCAL XEA253 Point - Calculation of Btu's per fuel
Records for those records whose 1st
position of the SCC equals 1,
2, or 5
EXTCMB NKB253 Point - Calculation of emissions for
Records external combustion records
(1st position of the SCC = 1)
1NTCIUB NEB253 Point - Calculation of emissions for
Records internal combustion records
* dpi position of the SCC = 2)
INDP^C NEC253 Point - Calculation of emissions for
Records industrial processes point
sources (1st ->osition of the
SCC =- 3)
EVAPT NEC253 Point - Calculation of emissions for
Rcco -ds evaporation point sources
(1st position of the SCC = 4)
SLDWST XEB253 Point - Calculation of emissions for
Rccorcis solid waste point sources
(1st position of the SCC = 5)
MISPT XKC253 Point - Calculation of miscellane-
Records cus point omissions (1st posi-
tion of the SCC - 6)
AREASC NKD253 Area - Calculation of projected in-
Records crease for all non-transpor-
tation r.rea activities
TRANS
An'a
Rtcords
III-2,")
Calculation of projected trans-
portation area activities re-
lated
-------
CO
01
C
O
en
"D
w §
F~ K
Cv O
c
c
o
c;
i>
o
L,
III-136
-------
The second type of user supplied data affects projected emis-
sions by altering the base year emission inventory data on which t^e
projections are based. This type of user supplied data includes:
Required control efficiency for sources governed by new
source standards
Required control efficiency for sources governed by
existing source standards
N'ew point sources expected to be operating during the
projection year \vhich were not entered in the XKUS file
and wluch were not included in the C'ase Study input data.
(The NEDS file contains some data on plants to become
operational in the future).
User supplied control efficiency is read by the program from the
REPSCO.MPT-ST file; any new point source data is included with the
Case Study card input.
Tl e c a~f Studv i-> a .-p<'< lai analysis of growth and relocation
trends for five mdu.-t r:e.i which are arnonL- the heaviest indus-
trial polluter-.. Tix-st.- critnal indu^'rie- include electric
power general .or., --.t1 tl, ciien, icals, pulp manufacturing and
peliY'lfM:1. rei'inm,". Ti output ol'il.i-^ a:nl v-. i--. wa.- a file of
data on mw pi;'nt- f\|,''ji ted to lpK-vO;;it operatumal ;n th.e fiiturc
wh;; .'i J.T r(-ad bv n.i.- UF'i'S r,.(j(ii.il(^ r.-- tarut at ti:e user's
-------
SniRCHTlXK NF.A253 (B1TCAU
ABSTRACT
The subroutine NE.V253 (BTICAL) is executed only once, at
the beginning of the KEl'S ".Main" program. It generates the Htu
ratios tor each fuel type for those point records which contain fuel
use data. The Btu ratios are computed for each customer category
as the Btus consumed for each fuel divided by total IBtus consumed
for all fuels. In addition to generating the Htu ratios, the subroutine
calculates growth factors for each, fuel type within each customer
category based on projected Btu demand for each customer category.
Unlike the other subroutines in the NE1253 program, NEA253 pre-
reads the NEDS point source records along with the Emission Factor
file and the SCC growth factors. The resulting matrices are passed
to the "Main" program via the CALL statement.
Kl N DESCRIPTION
The processing sequence of the \EAlio3 subroutine is as follows.
Net base year emissions from i'uel combustion are fir.->t converted to
uncontrolled emissions using base year control efficiency information.
These (iata arc then converted to fuel usage based on emission factors
from Uie Emission Factor file and finally converted to Btu equivalents
using an internal matrix (Table III-5). The Btu totals by fuel type and
by SCC classification are used to produce the Htu ratios for the base
year. Growth factors for each SCC are computed using the base year
Btu ratios, the expected ;;ro-,\tli in Btu demand and the fuel mix for the
projection vear.
III--'1!
-------
Table III-5
Btu Conversion Table
Fuel Type
Coat:
Gas:
Oil:
Bituminous coal
Anthracite coal
Coke
Solid waste \v/coal
Lignite coal
Natural gas
Process gas
Residual oil
Distillate oil
Diesel
Gasoline
Aviation fuel
Miscellaneous:
Liquid petroleum gas
Wood (.,ry)
Bagasse
IBtu's (10 ) per Unit Burned
26.2/ton
25.4/ton
24.8/ton
23.'J/ton
14.8/ton
1050. 0/cu ft
145.0/cu ft
150.0/gal
140.0/gal
138.0/gal
125.0/gal
120.0/gal
94. 0/cu ft
lf'.5/cu ft
17.0/cu ft
Sixty percent coal .in;! t'or'y percent- solid \va.?*.e.
Ul-2'i
-------
8. SUBROUTINE NEB253 (COMBUS)
ABSTRACT
The subroutine NEB253 (COY.Bl'S) computes projected emissions
for external and internal combustion and .solid waste point sources.
The subroutine is passed base year emissions and associated data
from the main program N11253 (RKPS) and returns net emissions and
associated data for the projection year in the same data format. The
projected emissions include the effect of control regulations already
in effect as well as performance standards which will become effec-
tive in the future. There is provision for user override of all the fac-
tors used to project future fuel use and net emissions.
HUN INSCRIPTION
The processing routines are identical for external and internal
combustion and solid waste point source emissions. All input and
output data are passed through common storage and the subroutine
argument list. The data passed through common storage includes net
emissions, control efliciencv, allowable emissions, and compliance
information for the base year from the Nl'.DS file. Also passed are
all necessary data en control regulations and projected growth.
There are two types of user-supplied control regulations affect-
ing future point source emissions. One type affects only new equip-
ment which becomes operational after the effective d;i*f of the regu-
lation. T; ese regulation-) are referred to in this section as new source
standards. The other type of regulation is either in effect in the base
year or will be in effect before the projection year, and governs both
existing and new facilities. These regulations are referred to in this
section Uj exist my source >tandards.
The processing sequence to project fuel combustion omissions
is as follows. Net base year emissions are converted to uncontrolled
emission.- (usiny the base vear cont ro! efficiency) and to fuel use
(using emission factors read from the emission factor file). Fuel
UFO for each custornoi rate^nrv is converted to equivalent base year ?
Titu dei!i:o:<:; S(',('-.-.pec, \\ \c LTM. ih factor are used to forecast the
future li'u (ir-mai.d, which i- allocate;! *o fuels based on the expected
fuel mix in Mv pio)ectio!i ear. I nc onf rolled emissions are then
computed ij-ir.i; the emi'-smr, fp.ctors. l.nuj-Pion-; froi:i solid waste
disposal are proiccted in the same ger» ral wa\, except th.at the
-------
amount of solid waste burned, rather than the Btu demand, is pro-
jected for each customer category, and the projected tonnage is
allocated to disposal methods in the same way that future fuel mix
is used to allocate the projected Btu demand.
This approach produces one of the following types of output
records:
When no control standards are supplied: one record with
emissions controlled by the base year control efficiency
When only new source standards are given: one record
with emissions which are affected by the base year con-
trol efficiency and one record with emissions which are
affected by the new source standards
When both existing and new source standards are given:
one record with emissions which are affected by the exist-
ing standards and one record with emissions which are
affected by tiie new source standards.
Thus one or two output records may be produced for each input record.
»
The next step in the processing sequence involves reducing the
projected emissions if the projection year follows the expiration date
of a variance and if projected emissions exceed the allowable emis-
sions from winch the variance was granted. Variance information and
allowable eniib^ions are included in the XEDS emission inventory data.
Projected emissions arc finally returned through common storage
to the mam program.
-------
9. SrnROI"! INE NKC253 (INI)PRC)
ABSTRACT
The subroutine NKC253 (INDPRC) computes projected emissions
for industrial process, evaporation and miscellaneous point sources.
The subroutine is passed base year emissions and associated data
from the main program NE253 (HEPS) and returns net emissions and
associated data for the projection year in the same data format. The
projected emissions include the effect of control regulations already
in effect as well as performance standards which will become effec-
tive in the future.
The general projection methodology, presented earlier in this
report, involves converting net base year emissions to uncontrolled
emissions, forecasting equivalent uncontrolled emissions in the pro-
jection year, and then estimating projected net emissions as affected
by emission control regulations. The methodology is Lased on the
fundamental assumption that uncontrolled emissions are proportional
to emission-producing activity (e.g. , plant throughput) and that
growth in uncontrolled emissions is equivalent to growth in plant
activity as defined by the uimensionless ^lOv.th factors. There is
provision for user override of all growth factors, and user input of
any local emission regulations (the program defaults to proposed
Federal regulations).
RUN DESCRIPTION
The processing rout;nes are identical for industrial process,
evaporation and miscellaneous point source emissions. All input
and output data are passed through common storage; the subroutine
argument list contains only iv.o elements, a parameter to count the
number of calls fo the subroutine, and a switch to control printout
of error messages. The data passed through common storage in-
cludes net omissions, control efficiency, allowable emissions, and
compliance information for 'he base year from the NKDS file. Also
passed are all necessary data on control regulations and projected
growth.
There are two types of user-supplied control regulations
affecting fuUirf point source emissions. One (ype affects onlv new
equipment which becomes operational after the effective date of 'he
regulation. These regulation-- nre referred !o in this section ns
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new source standards. The other type1 of regulation is cither in effect
in the base year or will he in effect before the pi-o|ection year, and
(,'nvern.s both existing and ne\v facilities. These regulations arc- re-
ferred to in this section as existing source .standards.
The processing sequence of the subroutine is as follows. Net
base year emissions are first converted to uncontrolled emissions
usmij the base year control efficiencies. Growth factors and the
effect of user supplied control regulations are applied to the uncon-
i tolled emissions to produce one of the following types of output
records;
When no control standards are .supplied: one record
with emissions controlled by the base year control effi-
ciency
When only new -source standards are ^iver;: one record
with emissions -.vhich are affected by the base year con-
trol efficiency and one record wit! emissions which are
affected by the new source standards
V.'h.cn both .;:;.UaiL- and now .->citrre ->tanuard.-> «ire ^iven:
one record with emissions which art- affected bv the
existing standards and one record with emissions which
are affected by the new source standards.
Thu.s one or two output records may be produce.] for each input
record.
The next .step ;n the proce.->.sincj --cquence inyoi.es rcducin;! the
proieeted emis.-,u)n^ if the !5roie;tion year follow: th.*- exniration date
of a variance and if proiectec! emi.ssic»ns exreeci t!;e aiiov/ahie ci:;i.->-
s.ons froir. whirh !;t \\u :a:ice was i.!r'ant(-f;. \'a nance initjrn-at;on and
;i 1 ic'.vable emi.s.-ion^ are ;m hid^d in fie \i I->S e^i;;;-.-> iu:i in\'<-ntory cata.
IJrc)je(ted «'H. !-.s ui.'is are finallv I'tturnc-ci ti^roi;:.'!- comirion
:":\::M- to (!, :;-.TH; ;; ru^ r;;*.\-.
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10. SrHHOl'TINK XKO253 (ARKASC)
ABSTRACT
The subroutine NED25H (AUEASC) comp.nt-s projected activity
for all area sources other than transportation. Activity and not
emissions is projected because the NKUS-LSEK file contains only
activity data for area sources. Emissions are calculated by NKDS
summary reporting programs (e. g. , NL11) \vhich accept NiJDS-t'SEK
area source data as input. The subroutine is passed base year activ-
ity data from the main program NK2G3 din's) via the argument list,
growth factors are applied to the base year activity, and projected
activity is returned via the argument list (under the same data format*
to the main program. Nontransportation area source activity includes
fuel combustion, solid waste disposal and evaporation. There is pro-
vision for user override of the fuel mix, substitution of electricity
for fossil fuels, and average energy consumption per capita in the
projection year, as well as for growth factors for the activity cate-
gories. I ser override data are available to the subroutine through
common storage.
IU N O
Each time the subroutine is called, all nontransportation area
source activity data from one NK!)S area source record is processed.
The processing sequence is fuel use, solid waste and "vaporation.
Rase year Btu d?man.l for each customer category (residential,
commercial/institutional and industrial) :s computed, modified if
necessary by the expected change in substitution o! electricity ('.;ser-
supplieti), projected to the future Btu demand, and reapportioned to
future fuel use, (in the absence of uyc/r-supplied future fuel mix use
the ba~,e year mix is used). Solid wa.-^te disposal anri evaporation-
producing activity are simply multiplied l:y the projected growth
factory. Default growth farir >'s used when others are not supplier by
the user arc-
iiesulential fuels and solrd wi,.-te disposal: population
Commrrci.'il'institutional fuels and solid v.a>te disposal:
total industrial gross output
III-.'5 4
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Industrial fuel'.; and solid waste disposal: total industrial
gross output.
Evaporation: population.
Projected activity is returned tc the main program through the
areum«-.,t list.
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11. SUBROUTINE NEE253 (TRANS)
ABSTRACT
The subroutine NEE253 (TRANS) computes projected activity
for all transportation sources. Activity and not emissions is pro-
jected because the NEDS -USER file contains only activity data for
all area .sources. Emissions are calculated by NEDS summary re-
porting programs (e.g., NE11) which accept NEDS-USER area
source data as input.
The subroutine is passed base year data on fuel use, activity
and emission? for all transportation sources, and the necessary
growth factors, from the main program NE253 (REPS). Any user-
supplied projection data are also accepted and future transportation
fuel use, activity and emissions (in the same format) are computed
and returned to the main program. All data are passed to and re-
turned from the subroutine through the argument list.
* HUN DESCRIPTION:
The input data passed to the subroutine from the main program
NE3<63 (REPS) include the following transportation activity data from
the NEDS -I SER area source file:
Light-duty vehicles: gasoline use
Heavy-duty vehicles: gasoline and diesel use
Vehicle miles traveled (Y.MT) combined for all vehicles
Off -highway vehicles: gasoline and diesel use
Hail locomotives: diesel use
Vessels: anthracite coal, diesel, residual oil, and
gasoline
t
Aircraft: landing-takooff cycles ( LTO) for commercial,
civilian and military aircraft.
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Since the output of the main program NE253 (REPS) will be projection
data to be converted by program NE052 to standard NEDS-USEK file
format, the output data returned to HEPS must include, and are lim-
ited to, the above categories.
The user may input growth factors for any of the five transpor-
tation categories. The population growth factor is used as the defau'c
growth factor for all transportation sources in the absence of such
overrides. Additional user input options are available for projections
of highway vohicle activity for the three types of highway vehicles:
light- and heavy-duty gasoline and heavy-duty diesel vehicles. These
additional user inputs include growth factors for VMT and the pro-
jected percentage of future VMT for each vehicle type. Input data
and growth factors are combined in the subroutine to produce projec-
tions of transportation activity, which are returned to the main pro-
gram using the input data format.
One additional function is performed by the subroutine. The
first time the subroutine is called by the main program NE253 (HEPS),
weighted emission factors for NOX, CO, 11C (exhaust) and I1C (evap-
oration) ?.re computed for light- and heavy-duty gasoline vehicles.
These are computed from published data on low mileage emission
factors, deterioration of control devices due to vehicle age, average
vehicle speed and weighted annual travel of vehicles of a given age.
Some of these factors are a function of the projection year, so they
cannot be computed until they first pass through the subroutine. The
composite emission factor for J1C is formed as the sum of the
weighted lactors for HC (exhaust) and I
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12. PROGRAM NF.052 (NKIXS-OIT)
ABSTRACT
The COBOL prourain NK052 (NL'US-OUT) is the final module
in the RKPS System. This piogram takes the FORTRAN-oriented
records containing projected regional activity and emissions [the
output of tlie NF253 (HKPS) program] and creates 352 character,
standard format NKUS-USLR file records. The resulting output file
contains both point and area source records. These records are
identical \vith the base vear NLDS records in ciata and format except
for those parameters which were modified to reflect the growth in
activity for the projection vear. Summary reporting programs can
be executed against this file to produce statistical reports for the
projection vear. .An example would DC a projection \LR generated
by the XL11 program. For more information on available reporting
program consult the program documentation library of the EPA
Aerometric and Emissions Reporting System (AKKOS),
RUN DESCRIPTION
The program contains three major elements, a COBOL main
routine and two FORTRAN subroutines (M:A()52, NFB052). One sub-
routine OLH052) reads all the projected point source records and the
other .subroutine (\FA052) reads all the projected area source records.
These subroutines pas» the data to the COBOL mam routine winch
writes the standard 552 character sequential record in NKDS-USLR
file format. Upon completion of tin* program the temporary files
containing the projected po'r.t and area .->ource inventory data (output
of the NL253 program) can !)*" deleted.
ii I-:;;;
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