June 1971
Demonstration of a Regional Air
Pollution Cost/Benefit Model
n
Environmental Protection Agency
Office of Air Programs
Washington, D.C.
Contract No. PH 22-68-60
TRW
RWI
MS •*<•>'.- I
h
WASHINGTON OPtRATIONS
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FIG. (a) DESIGN DESCRIPTION
25% of the total air flow enters the primary flame zone,
mixing instantaneously with fuel over the edge of the
cup.
25% of the total air flow is added linearly to primary,
secondary and tertiary flame zones by means of outer
wall film cooling.
50% of the total air flow is added to the secondary flame
zone by means of air injection at the junction of the
primary and secondary flame zones and about five
inches downstream of the rotating cup. With no
recirculation of any of this air into the primary flame
zone.
FIG. (c) AIR ADDITION ALONG COMBUSTOR
MSTAKCl -WCHM
FIG. (e) GAS TEMPERATURE ALONG COMBUSTc HI
FIG. (b) COMBUSTOR CROSS SECTION
FIG. (d) AIR / FUEL RATIO ALONG COMBUSTOR
Fib.
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FIG. (a) DESIGN DESCRIPTION
25% of the total air flow enters the primary zone, mixing
instantaneously with the fuel over the edge of "the cup.
25% of the total air flow is added linearly to the primary,
secondary and tertiary flame zones by means of outer
•wall film cooling.
50% of the total air flow is added to primary and second-
ary flame zones equally by means of air injection at the
junction of the primary and secondary flame zones and
about five inches downstream of the rotating cup.
50% of this air enters the primary zone by flowing
upstream in opposition to the flame.
FIG. (c) AIR ADDITION ALONG COMBUSTOR
FIG. (e) GAS TEMPERATURE ALONG COMBUSTOH
-4 1 rl
FTG. (b) COMBUSTOR CROSS SECTION
FIG.
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FIG. (a) DESIGN DESCRIPTION
35% of the total air flow entera the primary flame zone,
mixing instantaneously with fuel over the edge of the
cup.
5% of the total air flow is added linearly to primary,
secondary and tertiary flame zones by means of outer
wall film cooling.
60% of the total air flow is added to the secondary flame
zone by means of air injection at the Junction of the
primary and secondary flame zones and about five
inches downstream of the rotating cup. With no
recirculation of any of this air into the primary flame
zone.
I '
I •'
i
FIG. (c) AIR ADDITION ALONG COMBUSTOR
M COOUNQ FLOW -*
rtLHCOOUJ
"Urn"'*"
SBCCKDAHT runt
URO UCBtCULATTOM
TOTAL A - .Ml L8./MC.
FIG. (e) GAS TEMPERATURE ALONG COMBUSTOR
FIG. (b) COMBUSTOR CROSS SECTION
FIG. (d) Am / FUEL RATIO ALONG COMBUSTOR
FIG. (f) NO, CO CONTENT
Q
o
I
ZERO RECIHCULATIOK
D19TAKCE - INCHES
FIGURE 43. DESIGN A - CONFIGURATION NO. 3
79
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FIG. (a) DESIGN DESCRIPTION
35% of the total air flow enters the primary zone, mixing
instantaneously with the fuel over the edge of the cup.
5% of the total air flow is added linearly to the primary,
secondary and tertiary flame zones by means of outer
wall film cooling.
60% of the total air flow is added to primary and second-
ary flame zones equally by means of air injection at the
junction of the primary and secondary flame zones and
about five inches downstream of the rotating cup.
50% of this air enters the primary zone by flowing
upstream in opposition to the flame.
FIG. (c) AIR ADDITION ALONG COMBUSTOR
FIG. (e) GAS TEMPERATURE ALONG COMBUSTOR
FIG. (b) COMBUSTOR CROSS SECTION
FIG. (d) AIR / FUEL RATIO ALONG COMBUSTOH
FI|G. (f) NO, CO CONTENT
o
FIGURE 44. DESIGN A - CONFIGURATION NO. 4
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FIG. (a) DESIGN DESCRIPTION
15.7% of the total air flow enters the primary zone,
mixing instantaneously with the fuel over the edge
of the cup.
29.4% of the total air flow is added linearly to the
primary and secondary flame zones by means of
outer wall film cooling, half of which is injected
downstream from the primary and the other half
upstream from the tertiary flame zone.
27,5% of the total air flow is added to the secondary
flame zone by means of air injection at the Juncture
between the primary and secondary flame zones and
about five inches downstream of the rotating cup.
With no recirculation of this air into the primary
flame zone.
27.5% of the total air flow is added to the tertiary
flame zone by means of air injection at the exit of
the secondary flame zone.
FIG. (c) AIR ADDITION ALONG COMBUSTOR
. ,,} GAS TEMPERATURE ALONG COMBUSTOR
-0 }
FIG. (b) COMHUSTOR CROSS SECTION
FIG. (d) ADI / FUEL RATIO ALONG COMBUSTOR
FIG. (f) NO. CO CONTENT
DISTANCE - INCIlts
FIGURE .45. DESIGN B - CONFIGURATION NO. 1
83
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FIG. (a) DESIGN DESCRIPTION
15.7% of the total air flow enters the primary zone, mix-
Ing instantaneously with the fuel at the edge of the cup.
29.4% of the total air flow is added linearly to the primary
and secondary flame zones by means of outer wall film
cooling, half of which is injected downstream from the
primary and the other half upstream from the tertiary
flame zone.
27.5% of the total air flow is added to the secondary flame
zone by means of air, injection at the juncture of the
primary and secondary flame zones and about five inches
downstream of the rotating cup. Half of this air (or
13.75% of the total air flow) recirculates back upstream
into the primary flame zone.
27.5% of the total air flow is added to the tertiary flame
zone by means of air injection at the exit of the
secondary flame zone.
HO. (b) COMBUSTOR CROSS SECTION
0
Q
FIG. (c) AIR ADDITION ALONG COMI1USTOH
FIG. (d) AIR / FUEI, RATIO ALONG COMBUSTOR
FIG. (e) GAS TEMPERATURE ALONG COMBUSTOR
FIG. (f) NO, CO CONTENT
FIGURE 46. DESIGN B - CONFIGURATION NO. 2
85
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11130-W004-RO-00
DEMONSTRATION OF A REGIONAL
AIR POLLUTION COST/BENEFIT MODEL
July 1971
Prepared for
Environmental Protection Agency
Office of Air Programs
Contract No. PH 22-68-60
TRW SYSTEMS GROUP
7600 Colshire Drive,
McLean, Virginia 22101
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The work upon which this
publication is based was performed
pursuant to Contract No. PH 22-68-60
with the Air Pollution Control Office,
Environmental Protection Agency.
ii
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TABLE OF CONTENTS
Page
1.0 INTRODUCTION ....................... ... 1
1.1 THE COST/BENEFIT MODEL .................. !
1.2 COST/BENEFIT DESIGN^AND DATA LIMITATIONS ......... 4
1.3 RESULTS OF COST/BENEFIT MODEL DEMONSTRATION ....... . 6
2.0 REGIONAL AIR POLLUTION ANALYSIS COST/BENEFIT MODEL ....... 9
2.1 GENERAL BACKGROUND AND OVERVIEW ............. 9
2.1.1 Computer Simulation Modeling ........... 10
2.1.2 Air Pollution Cost/Benefit Analysis ....... 13
2.1.3 Role of the RAPA Cost/Benefit Model in the
Hierarchy of RAPA Analysis Tools ......... 13
2.1. A RAPA Cost/Benefit Model, Program Overview .... 17
2.2 IMPLEMENTATION PLANNING PROGRAM ............. 17
2.2.1 Component Programs of IPP ............ 19
2.2.2 Point Source Cost Calculations in IPP ...... 29
2.2.3 IPP Regional Strategies Output .......... 29
2.2.3.1 Tabulated Output for
Cost/Benefit Analysis ......... 29
2.2.3.2 Punched Card Output for
Cost/Benefit Model. . ......... 34
2.3 CENSUS TRACT DATA .................... 41
2.4 AIR POLLUTION DAMAGE FUNCTIONS .............. 44
2.4.1 Direct Damage Functions ............. 44
2.4.2 Market Effects Damage Functions ......... 50
2.5 INTERFACE MODULE ..................... 52
2.5.1 Input ...................... 52
2.5.2 Analytical Technique for Estimating
Census Tract Air Quality ............. 54
iii
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TABLE OF CONTENTS (Cont'd)
Page
2.5.3 Output 61
2.6 DAMAGE COSTS MODULE '. ' 62
2.6.1 Input 65
2.6.2 Output . . . 65
2.7 PROPERTY VALUE MODULE 68
2.7.1 Input 72
2.7.2 Output , 72
2.8 PROPERTY ASSIGNMENT MODULE 76
2.8.1 Determination of Equilibrium Property
Values in the Property Assignment Module 79
2.8.2 Input . 82
2.8.3 Output 83
2.9 PROPOSED MODEL ADDITIONS 85
3.0 MODEL DEMONSTRATION 87
3.1 INPUT DATA FOR THE NCIAQCR DEMONSTRATION 87
3.1.1 Census Data 88
3.1.2 Pollutant Concentration/Strategy Data 88
3.2 ESTIMATION OF DIRECT DAMAGE COSTS 109
3.3 ESTIMATION OF PROPERTY VALUE EFFECTS 113
4.0 REFERENCES 119
APPENDICES
A THE IMPLEMENTATION PLANNING PROGRAM, CONTROL COS.T
CALCULATIONS 121
B SOURCES OF CENSUS TRACT INFORMATION REQUIRED FOR
RAPA COST/BENEFIT MODEL 147
C PRO FORMA DAMAGE FUNCTION DEVELOPMENT . 163
D DEMONSTRATION RESULTS TO THE POLITICAL JURISDICTION LEVEL .... 177
E USER'S MANUAL ......... 203
IV
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FIGURES
Page
1.1-1 Structure of the RAPA Cost/Benefit Model 3
2.1-1 Computer Simulation Modeling 11
2.1-2 Cost/Benefit Model in the Context of the RAPA Program .... 15
2.1-3 RAPA Cost/Benefit Model (Existing Version) 16
2.1-4 RAPA Cost/Benefit Model, Program Structure 18
2.2-1 Structure of the Implementation Planning Program 20
2.2-2 Role of Implementation Planning Program; RAPA
Cost/Benefit Model 21
2.2-3 Typical Emission Standard Curve Relation to
Control Device Application. 25
2.2-4 Allowable Particulate Emissions Based on
Industrial Process Weight (EST 19) 27
2.2-5 Output Format - Emission Standards Effects 31
2.2-6 Output Format - Jurisdiction Summary 32
2.2-7 Output Format - Control Strategy Summary 35
2.2-8 Output Format - Ground Level Concentrations 36
2.2-9 Existing Ground Level Particulate Concentrations in the
NCIAQCR as Computed by the Verified Air Pollutant
Concentration Program 38
2.2-10 Predicted Particulate Concentrations After the Enactment
of the Proposed Emission Control Strategy in all
Political Jurisdictions 40
2.3-1 Population and Housing Data Relation to RAPA
Cost/Benefit Model 42
2.4-1 Damage Functions: Role in the RAPA Cost/Benefit Model .... 45
2.4-2 Wilson and Minnotte Function for Damages Due to Soiling ... 46
2.4-3 Pro Forma Damage Functions Used in RAPA Cost/Benefit
Model NCIAQCR Demonstration 48
2.5-1 RAPA Cost/Benefit Model; Interface Module 53
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FIGURES (Cont'd)
Page
2.5-2 RAPA Cost/Benefit Model; Receptor Point
Census Tract Association 55
2.5-3 Receptor Points Superimposed on Census
Tracts of the NCIAQCR - . 56
2.5-4 Receptor Points Superimposed on Census
Tracts of the NCIAQCR, Close-Up View of Central City 57
2.5-5 Output Format - Tabulated Census Tract Pollutant
Concentration Data ' ... 62
2.6-1 RAPA Cost/Benefit Model; Damage Costs Module 64
2.6-2 Sample Damage Costs Summary Output 67
2.7-1 RAPA Cost/Benefit Model; Property Value Module 69
2.7-2 Sample Output, Property Value Module 74
2.8-1 RAPA Cost/Benefit Model; Property Value Assignment Module . . 77
2.8-2 Sample Output, Assignment Module 84
3.1-1 List of Census Tract Attributes for the
Washington, D. C. SMSA 89
3.1-2 Existing Ground Level Particulate Concentrations in the
NCIAQCR as Computed by the Verified Diffusion Model 104
3.1-3 Existing Ground Level Sulfur Dioxide Concentrations in
the NCIAQCR as Computed by the Verified Diffusion Model . . . 106
3.2-1 Pro Forma Functions Utilized in NCIAQCR Cost/Benefit
Demonstration 110
C.2-3 Pro Forma Damage Functions for SO- and Particulates ..... 175
E.l-1 Overall System Flow 204
E.3-1 Job Control Language and Deck Set-Up for Interface
Module (C0NVRT) 209
E.3-2 DRIVER for Interface Module - Program Listing 213
E.3-3 Input Data Form for Census Tract/Receptor Point
Association
217
vi
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FIGURES (Cont'd)
Page
E.3-4 Printed Input RPPC Data Summary, C0NVRT 219
E.3-5 Printed Output CTPC Data Summary, C0NVRT 220
E.3-6 C0NVRT Subprogram, Interface Module-Program Listing 221
E.3-7 Subroutine 0RDER, Interface Module-Program Listing 225
E.4-1 Job Control Language and Deck Set-Up for Damage
Costs Module (DAMAGE) 228
E.4-2 Sample Output from Damage Costs Module, Title Page
and Census Tract Attributes as Input 235
E.4-3 Sample Output from Damage Cost Module, Census Tract
Pollutant Concentrations as Input 236
E.4-4 Sample Output from Damage Costs Module, Census Tract
Damage Cost Summary 237
E.4-5 Program Listing for DRIVER Main Program - Damage
Cost Module 238
E.4-6 Program Listing for DAMAGE Subprogram - Damage
Costs Module 239
E.5-1 Job Control Language and Deck Set-Up for
Property Value Module 247
E.5-2 Sample Output, Title Page and Census Tract Attributes
Summary from Property Value Module 255
E.5-3 Sample Output, Census Tract Pollutant Concentrations
(SO- and Particulates) Summary from Property Value Module. .256
E.5-4 Sample Output, Census Tract Property Values Summary
from Property Value Module 257
E.5-5 Program Listing for DRIVER, Main Program for
Property Value Module 258
E.5-6 Program Listing for Subprogram PR0P, Property Value Module .259
E.6-1 Job Control Language and Deck Set-Up for Assignment Module . 269
E.6-2 Sample Output, Title Page and Census Tract Attributes -
Assignment Module 273
E.6-3 Sample Output, Census Tract Pollutant Concentration
Summary (SO- and Particulates) Assignment Module 274
vii
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FIGURES (Cont'd)
Page
E.6-4 Sample Output, Census Tract Property Value Bids
From Assignment Module 275
E.6-5 Program Listing for DRIVER, Main Program for
Assignment Module 276
E.6-6 Program Listing for ASSIGN Subprogram,
Assignment Module 277
viii
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TABLES
Page
2.2-1 Particulate Control Strategies - National
Capital Interstate Air Quality Control Region 39
2.4-1 Regression Results of Anderson-Crocker Study
for the Washington, D. C. SMSA 51
3.1-1 Particulate and Sulfur Oxides Control Strategy
Summaries - NCIAQCR 108
3.2-1 NCIAQCR - Regional Damage Values Summary ... Ill
3.3-1 Type I Property Values: NCIAQCR Regional Summary 115
3.3-2 Adjusted Type I Property Values: NICAQCR, Regional
Summary 116
A.2-1 Pollution Reduction Devices or Methods Applied
to Point Sources in IPP 123
A. 2-2 IPP Control Device Preset Data 124
A. 3-1 Fuel Parameters 136
A.3-2 Boiler Efficiencies 137
A. 3-3 (f.) Coal Particulate Emission Factors 138
A. 3-4 (f ) Oil and Gas Particulate Emission actors 139
B.l-1 Census Tract Attributes, Notation and Definitions 149
B.2-1 Sample Tables from the Censuses of Population and
Housing with Annotations 153
B.3-1 List of NTIS Tapes of Population and Housing Data
(1960 for the United States by Standard Location Area) . . . 161
C.2-1 Estimates of Nationwide Emissions, 1968 166
C.2-2 National Total Annual Costs of Pollution for Types of
Pollutants and Effects in 1968 173
C.2-3 Coordinates for Damage Function Development 174
ix
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TABLES (Cont'd)
Page
D.l-1 NCIAQCR: Regional Damage Values Summary 178
D.l-2 NCIAQCR: Damage Summary for Political Jurisdiction //I -
District of Columbia. . 179
D.l-3 NCIAQCR: Damage Summary for Political Jurisdiction //2 -
Montgomery County . 180
D.l-4 NCIAQCR: Damage Summary for Political Jurisdiction //3 -
Prince Georges County 181
D.l-5 NCIAQCR: Damage Summary for Political Jurisdiction //4 -
Alexandria City 182.
D.l-6 NCIAQCR: Damage Summary for Political Jurisdiction #5 -
Arlington County 183
D.l-7 NCIAQCR: Damage Summary for Political Jurisdiction //6 -
Fairfax County 184
D.l-8 NCIAQCR: Damage Summary for Political Jurisdiction #7 -
Falls Church City .185
D.2-1 Type I Property Values: NCIAQCR Regional Summary 186 '
D.2-2 Type I Property Values: Political Jurisdiction 1,
District of Columbia Summary 187
D.2-3 Type I Property Values: Political Jurisdiction 2,
Montgomery County, Md. Summary 188
D.2-4 Type I Property Values: Political Jurisdiction 3,
Prince Georges County, Md. Summary 189
D.2-5 Type I Property Values: Political Jurisdiction 4,
Alexandria, Virginia Summary 190
D.2-6 Type I Property Values: Political Jurisdiction 5,
Arlington County, Virginia Summary 191
D.2-7 Type I Property Values: Political Jurisdiction 6,
Fairfax County, Virginia Summary 192
D.2-8 Type I Property Values: Political Jurisdiction 7,
Falls Church, Virginia Summary 193
D.3-1 Adjusted Type I Property Values: NCIAQCR,
Regional Summary 194
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TABLES (Cont'd)
Page
D.3-2 Adjusted Type I Property Values - Political
Jurisdiction 1, District of Columbia 195
D.3-3 Adjusted Type I Property Values - Political
Jurisdiction 2, Montgomery County 196
D.3-4 Adjusted Type I Property Values - Political
Jurisdiction 3, Prince Georges County 197
D.3-5 Adjusted Type I Property Values - Political
Jurisdiction 4, Alexandria 198
D.3-6 Adjusted Type I Property Values - Political
Jurisdiction 5, Arlington County -199
D.3-7 Adjusted Type I Property Values - Political
Jurisdiction 6, Fairfax County 200
D.3-8 Adjusted Type I Property Values - Political
Jurisdiction 7, Falls Church 201
E.2-1 Format Information for Census Tract Attribute Data Cards. . . 206
E.3-1 Formats for Transform Data Cards 211
E.3-2 Receptor Air Quality Data Card Formats 215
E.3-3 Census Tract Pollutant Concentration Output Data Formats. . . 218
E.A-1 Damage Function Slope and Intercept, Input Data Format -
Damage Costs Module 231
E.4-2 Census Tract Attributes as Read by DAMAGE 232
E.4-3 Census Tract Air Quality Data Formats for SO- or
Particulates, Damage Costs Module .233
E.5-1 Sulfation Rate and Regression Coefficient Input Data
Formats, Property Value Module 250
E.5-2 Census Tract Attribute Data Formats as Read by the
Property Value and Assignment Modules 251
E.5-3 Census Tract Air Quality Input Data Formats for SO ,
Property Value and Assignment Modules 252
E.5-4 Census Tract Air Quality Input Data Formats for
Particulates, Property Value and Assignment Module 253
xi
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TABLES (Cont'd)
Page
E.6-1 Assignment Module Input Format for Regression
Coefficients (Type I) 270
E.6-2 Census Tract Attribute Data Formats as Read
by Assignment Module 271
xii
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1.0 INTRODUCTION
The RAPA Cost/Benefit Model which is the subject of this report
represents the last major computer program to be developed under the
three-year Regional Air Pollution Analysis (RAPA) contract at TRW Systems
Group. Appropriately, it also provides the last basic link in the chain
of computer programmed air pollution analysis tools that were originally
conceptualized during the first phase of the contract.
This report serves two major purposes: (1) it offers a program
description and user's manual for the RAPA Cost/Benefit Model; (2) it
presents the results of a demonstration cost/benefit analysis for the
National Capital Interstate Air Quality Control Region.
1.1 THE COST/BENEFIT MODEL
The aim of cost/benefit analysis is to maximize the present value
of all benefits less that of all costs incurred, subject to specified
constraints. Cost/benefit analysis has been considered for use in the
evaluation of transportation systems, criminal rehabilitation programs,
urban renewal projects, and other social programs.
In air pollution control, cost/benefit analysis can be employed to
compare the social costs and benefits resulting from a potential air
resource management policy with those to be expected from a continuation
of the existing level of effort (the "base alternative"). After defining
the project life (the period of time over which costs and benefits will
be measured), the costs and benefits of alternative air resource policies
are computed and discounted back to the base year for purposes of compara-
tive analysis. The resulting data may then be used in the evaluation of
alternative policies.
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An integration of economics, cost/benefit and systems analysis
procedures is necessary to analytically evaluate the air resource problem.
Such a combination of techniques provides a consistent methodology,for
integrating the quantitative results of research into the air resource
planning and decision-making process.
The RAPA Cost/Benefit Model combines the system analysis techniques
of the Implementation Planning Program (IPP) with the economic relation-
ships of the Benefit Model.
The IPP, which is one of the chain of RAPA models, was developed
earlier and is an integral part of the C/B Model. It provides two major
outputs: (1) the regional air quality display; and (2) point source
control costs. The Benefits Model Segment accepts as an input from the
IPP the regional air quality display and, through the application of
receptor data and damage functions, produces damage cost estimates as
output.
The relationship between IPP and the Benefits Model Segment is pre-
sented in Figure 1.1-1. Notice that the control cost estimates are provided
directly from printouts of the IPP, whereas, the damage cost estimates are
printouts of the Benefits Model Segment. The types of available information
and the printout formats for the IPP and the Benefits Model Segment are re-
ported in this document. The two separate outputs require the analysts to
combine the control and damage cost estimates and provide an interpretation
consistent with conventional cost/benefit analysis procedures.
The Cost/Benefit Model is a cross-sectional model (i.e., air pollution
control strategies are evaluated at one instantaneous point in time). This
means that the Model must be applied in annual intervals over the length of
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COSTS SEGMENT I I IENEFITS MODEL SEGMENT
u>
Census
Data
KMULAIIOM 4 HOUSING DMA
Air Quality
Census
Data
IMM.IMCNTATION flANNING MOCIAM
(Iff)
Control
Costs
Census Tract
Air Quality
DAMAGI COSTS MODULE
COST/UNEFn ANALYSIS
(MANUAL PROCESSING)
Figure 1.1-1. Structure of the RAPA Cost/Benefit Model,
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the project life if conventional cost/benefit analyses are to be conducted.
After estimating the control costs and benefits of control strategies over
time, they can then be discounted back to the current years before the
benefit/cost relationships of alternative strategies are evaluated for
decision-making purposes.
The major portion of this document is devoted to the description of
the software of the Benefits Model Segment. As shown in Figure 1.1-1, the
Model relates the predicted pollution concentration (i.e., air quality dis-
play) to receptor data and damage functions. The exposure of receptors to
pollutants (a measure of "dosage") is determined by the air quality-recep-
tor relationship. The damage function (which relates the annual cost of
air pollution damage to pollution concentration) when applied to the dosage
estimate, determines the damage cost estimate desired. Estimates of bene-
fits (i.e., a reduction in damages) are calculated by subtracting damage
estimates for alternative strategies from the damages caused by existing
atmospheric conditions.
The design philosophy of the Cost/Benefit Model has been based on
the use of data which are either readily available or which are identifiable
and capable of being collected within a reasonable period of time. The
models are thus practical devices which use the best decision-making
information available.
1.2 COST/BENEFIT DESIGN AND DATA LIMITATIONS
There are three fundamental limitations in the structure of the
Cost/Benefit Model. First, the Model is essentially static in that costs
and benefits are treated as scalar current values rather than streams of
future costs and benefits to be realized as control is continuously applied
and as a region undergoes social and economic change. Forecasting
-------
capabilities would be desirable in the Model to predict the future emission
potential, distribution of receptors, technological changes, land-use plans,
etc. Second, the Model treats pollutants individually. That is, cost/
benefit comparisons are made on the basis of one pollutant at a time, neg-
lecting effects which levels and control measures for other pollutants may
have on the benefits and control costs for the pollutant under consideration.
Selection of a truly efficient strategy requires that the Model be capable
of simultaneous evaluation of strategies for all pollutants. Third, the
Model is limited to only two pollutants primarily because of the use of a
long-term-average diffusion segment. Transportation planning, land-use
planning, power plant siting and other strategies may be incorrectly evalu-
ated if pollutants such as carbon monoxide, hydrocarbons, nitrogen oxides,
and others are ignored. The investigation of integrating other atmospheric
diffusion models into the Cost/Benefit Model appears worthwhile.
Besides limitations in the Model structure, there are also a number
of restrictions regarding data inputs to the system. As the Model now
stands, control costs and benefits are accounted for only partially. The
only control costs currently included in the Model are point source control
costs (i.e., no account has been taken of area source costs or control
agency costs). Area source costs for a region are likely to be substantial,
and will include the cost of reducing emissions from: (1) the incineration
of solid waste not disposed of in municipal incinerators; (2) residential,
commercial and institutional fuel combustion; (3) mobile sources; and (4)
small industrial process sources. Control agency costs have often been
considered small relative to other control costs, but may represent fifteen
percent or more of the total regional cost of reduced emissions. Accounting
for control agency costs may be important when strategies based on totally
-------
different principles are evaluated and compared. An example may be the
comparison of the current system of direct regulations to a system of
emission charges.
Finally, probably the greatest deficiencies in the Model are caused
by the lack of acceptable damage functions. Damage functions relate one's
"willingness-to-pay" to avoid air pollution (i.e,,:the social value of
cleaning up the atmosphere) to the pollution concentration to which a
person or thing is exposed. Such relationships are difficult to develop,
and documented results regarding the economic effects of air pollution on
health, materials, vegetation, soiling, esthetics, and residential property
values are just now becoming available. To be compatible with the require-
ments of the Model, this data must be transformed into the damage function
form. For now, even without damage functions, the C/B Model can be used
for "exposure" studies since knowledge of the relationship between pollutant
concentration and receptors is by itself valuable for decision-making.
1.3 RESULTS OF COST/BENEFIT MODEL DEMONSTRATION
The specifications for the Cost/Benefit Model described in the pre-
vious section were developed and presented in a previous RAPA report
[Woodcock, 1971]. This document presents a description of the 'programmed
Benefits Model Segment, a user's manual, and the results of a study which
was conducted to illustrate the operation characteristics of the Cost/
Benefit Model.
The various component modules of the Implementation Planning Program
(IPP) and the Benefits Model Segment (including the input data, output data,
analytical procedures and output formats, etc.) are presented in Chapter
2.0.
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A presentation of the Model demonstration in the National Capital
Interstate Air Quality Control Region (NCIAQCR) is presented in Chapter
3.0 of this document. Included in the presentation are the control costs
and air quality impacts of the alternative control strategies which were
considered in the demonstration, and the benefits which accrue as each of
these control strategies is applied to the region based on (a) the Pro
Forma Damage Function, and (b) the Property Value impact before and after
establishment of market equilibrium. The Washington region was selected
because of the availability of an extensive analysis of alternative control
strategies which was done as a part of the preparation of the Washington
AQCR Implementation Plan. These demonstration results provide source data
which can be used as the basis for an analysis of the cost/benefit impact
of these alternative control strategies. This effort was only a portion
of the RAPA Phase III activity and the contract resources did not permit
a sufficiently complete interpretation of the results. Consequently, no
analysis of the results is presented: a forthcoming Office of Air Programs
report will cover this subject.
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2.0 REGIONAL AIR POLLUTION ANALYSIS COST/BENEFIT MODEL
2.1 GENERAL BACKGROUND AND OVERVIEW
The National and Regional Air Pollution Systems Analysis Program,
contracted to TRW by DHEW in July 1968, had as its objectives the design,
assembly and delivery of analytic tools to be used in regional and national
air pollution planning and management. The view at the time was that the
regional and national aspects of the air pollution problem required similar
analytical processes and data. Computer programs were to be developed which
would give decision-makers a means of determining the most effective tactics
and strategies for both the national and regional control efforts. The
overlapping of the national and regional data and analysis requirements
would minimize the development cost.
The RAPA Cost/Benefit Model completes the set of computer programmed
air pollution analysis tools conceived early in the history of the contract
The completed cost/benefit project combines the results of systems analysis
with cost/benefit analysis; the combination of techniques provides a con-
sistent methodology for integrating the quantitative results of research
i
into the air resource planning and decision process. This integration is
accomplished by interpreting the results of different research efforts on a
common economic scale.
The systems analysis techniques employed in regional air pollution
analysis involve computer simulation modeling of the regional air pollution
control process. This is accomplished through the Implementation Planning
Program, an earlier "link" in the RAPA chain of models. The cost/benefit
analysis is accomplished through the component programs and modules of the
RAPA Cost/Benefit Analysis Model. The basic concepts of deterministic
computer simulation analysis and cost/benefit analysis are discusses below.
-------
2.1.1 Computer Simulation Modeling
The concept of computer simulation modeling, represented., in Figure
2.1-1 is based on the use of mathematical models to simulate the behavior
of real physical phenomena. Usually, these phenomena are too complex to
simulate directly. In such cases, the mathematical models actually repre-
sent theoretical models which are idealizations or approximations of the
actual phenomena.
A mathematical model is one or more empirical or theoretical equations
(or inequalities) which translate a real system (physical, economic, etc.)
into a numerical representation. In the case of air pollution control, the
real-world system includes such aspects as pollution sources, atmospheric
processes, receptors, and pollution control techniques. All of these are
elements in a system. The mathematical models describe the relevant fea-
tures of each element, as well as the relationships between elements. For
example, equations are provided for the characteristics of control devices
and for the relationships between the application of a control device and
the resulting ground-level concentration at a specified receptor location.
The mathematical models are then incorporated into a mathematical
simulation which describes an algorithm or procedure for executing the
models under prescribed conditions. For air resource applications, these
conditions include given meteorological situations, certain industrial
process rates, etc. The execution of the model results in a time or event
history of responses for each model individually or for the entire system
of interrelated models; this process is a mathematical simulation of a sys-
tem described by mathematical models. If the mathematical models are execu-
ted according to the instructions contained in a computer program, then the
mathematical simulation is referred to as a computer simulation or computer
simulation modej^
10
-------
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Figure 2.1-1. Computer Simulation Modeling
11
-------
Normally, the results of a computer simulation are first used in a
comparison with actual results'of observations],of "the real system under
conditions similar to those in the simulation. In the case of an air
pollution control simulation, these observations include measurements of
air quality at various locations. If the computer simulation results
reasonably approximate the actual observations, .then the simulation is
said to be verified. A verified computer simulation implies a degree of
confidence in the computer program's ability to simulate the real system.
Based on this degree of confidence, the simulation can be used, .to predict
the behavior of the real' system under^conditions for which observations
are not available. However, care must be exercised, in employing the
computer simulation to predict the behavior of the system under circum-
stances far from those involved in the verification process;
The enormous data-handling capabilities of digital computers and
the programmed ability to step through complex sets of relationships have
made the computer simulation solution an indispensible tool in the study
of large-scale complex systems problems. With the development of accurate
models and reliable simulations, the user can get a measure of the cost and
effectiveness of various alternatives. These alternatives can then be
ranked in order according to their desirability against prescribed criteria
for specific objectives.
12
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2.1.2 Air Pollution Cost/Benefit Analysis
The formal theory of cost/benefit analysis requires that the costs
and benefits of a proposed project or policy be: (1) measured relative
to some base-line (i.e., initial time and conditions) and (2) evaluated
over a definite period of time (e.g., project life-time).
The existing version of the RAPA Cost/Benefit Model as well as all
the other components of the RAPA Program assume that all system responses
of interest occur instantaneously. Consequently, the Cost/Benefit Model
represents a special limited version of cost benefit analysis, known as
cross-sectional modeling. In the cross-sectional cost/benefit model, the
base-line or initial conditions are first analyzed, then assuming that all
responses are instantaneous, the effects of alternative policies are eval-
uated. The benefits are based on more than one parameter (e.g., air quality,
population, income, etc.) and the relations may be deduced from a statisti-
cal analysis on the different parameters. At the present time, the inability
to provide forecasts for the future concerning the availability and demand
for fuel, price structures, industrial process developments and control
technology advances make the cross-sectional approach the practical state
of the art.
2.1.3 Role of the RAPA Cost/Benefit Model In The Hierarchy of RAPA Analysis
Tools
The first production computer program of the Regional Air Pollution
Analysis (RAPA) Program was the Air Quality Display Model [TRW, November
1969]. This program employs a mathematical simulation of the atmospheric
diffusion process [Martin and Tikvart, 1968] to determine estimated arith-
metic average pollutant concentrations at ground level over an annual period.
It also contains a statistical model [Larsen, 1969] which produces geometric-
mean and maximum concentration values for several different averaging times.
13
-------
In July 1969, at the conclusion of the first year's efforts (Phase I), TRW
demonstrated the operation of a prototype Regional Air Pollution 'Analysis
Program using the St. Louis Air Quality Control Region as the data base.
The diffusion and statistical models of AQDM provided a key module
for the more ambitious Implementation Planning Program, the initial version
of which (IPP I) was ready in March 1970. The production version of the
Implementation Planning Program (IPP II) was published in November 1970 and
is described at some length in Section 2.2. It was actually the prototype
IPP I, however, which provided the critical interface with.the RAPA Cost/
Benefit Model for the current demonstration, since shakedown runs were still
underway for IPP II during the programming phase of the RAPA Cost/Benefit
Mode [TRW, November 1970].
The current prototype Cost/Benefit Model, produced as part of the
Phase III RAPA effort, provides another basic block for the general RAPA
Program. A series of economic models have also been developed by.the CONSAD
Research Corporation under sub-contract to TRW. The relation of all these
computer programs to one another in the existing concept of the RAPA Program
is illustrated in Figure 2.1-2. The prototype RAPA Cost/Benefit Model
(illustrated in Figure 2.1-3) represents a partial development of the con-
cept illustrated in Figure 2.1-2.
The Benefits Model Segment consists of an Interface Module and three
analysis modules (Damage Cost Module, Property Value Module, Property Assign-
ment Module). The Interface Module converts receptor point air quality data
(provided by the Implementation Planning Program) into census tract (average)
air quality. The Implementation Planning Program also serves as the Costs
Segment of the prototype Cost/Benefit Model; only the direct point sources
control costs are included in the analysis at the present time.
14
-------
• AIIOUALIIV
DATA
• MEIEOROLOG-
ICAl DATA
• EMISSION
INVENTORY
• CONTROL
TECHNIQUES
AND COSTS
IMPLEMENTATION PLANNING PROGRAM
(TRW SYSTEMS)
r
ATMOSPHERIC
DIFFUSION
MODEL
CALIBRATION
PROCEDURE
1
CONTROL
COST FILE
EXISTING
AIR QUALITY
DISPLAY
CONTROL
STRATEGY
MODEL
« i
POINT
SOURCE
CONTROL
COST
• RECEPTOR
DATA
• DAMAGE
FUNCTIONS
• DIRECT EFFECTS
• ADJUSTMENTS
. • MARKET EFFECTS
COST/BENEFIT MODEL
(PARTIALLY UNDER DEVELOPMENT)
ECONOMIC MODa SYSTEM
(CONSAO RESEARCH CORP)
REGIONAL VARIABLES .
AT PREVIOUS YEAR: !
VALUE ADDED
CAPITAL STOCK
CONSUMPTION
REGIONAL INCOME,
POPULATION AND
MIGRATION
GOVERNMENT
EXPENDITURE
REGIONAL INDUSTRIAL
INVESTMENT RE-
QUIRED EY AIR
POLLUTION ABATEMENT
STRATEGY
NATIONAL
INPUT/OUTPUT
MODEL
ECONOMIC GAINS
OF AIR POLLUTION
CONTROL
REGIONAL
ECONOMETRIC
MODEL
REGIONAL INCOME
AND CONSUMPTION
INUUSIKIAL
OUTPUT
INVESTMENT
EMPLOYMENT
CAIVAL STOCK
REGIONAL
UNEMPLOYMENT
LABOR fOitCE
CHANGES OF REGIONAL
INCOME, CONSUMP-
TION, VALUE ADDED,
INVESTMENT AND EM-
PLOYMENT BY INDUS-
TRY, REGIONAL UNCM-
PLOYMCNI GENERATED
BY DIKECT COSTS AMD
BENf.FIIS OF EACH
ABATEMENT STRAIEGY
I (KAKIIALLY UNUIK DEVtLUKMtNI)
Figure 2.1-2. Cost/Benefit Model In The Context Of The RAPA Program.
-------
COSTS SEGMENT
0\
COST/BENEFIT ANALYSIS
(MANUAL PROCESSING)
Figure 2.1-3. RAPA Cost/Benefit Model (Existing Version)
-------
2.1.4 RAPA Cost/Benefit Model. Program Overview
The computer program modules which comprise the RAPA Cost/Benefit
Model process population and housing census information along with pollu-
tant concentration data. The resulting information output supports air
resource cost/benefit analysis procedures.
Figure 2.1-4 illustrates the various modules of the C/B Model, their
principal inputs and outputs, and the interfaces between the modules. As
shown by the figure, the program modules of the C/B Model do not function
together in a fully integrated system as do the programs and program seg-
ments of IPP illustrated in Figure 2.1-2. Rather, these modules are essen-
tially independent; each supports a specific cost/benefit analysis procedure.
They are linked by a common data set (shown as a card deck in Figure 2.1-4)
of census tract attributes (population and property), and a common interface
module (CONVRT) which supplies the census tract pollutant concentration data.
This modular character of the RAPA C/B Model permits easy modification of
existing capabilities and aids future expansion of the model through addition
of new modules.
2.2 IMPLEMENTATION PLANNING PROGRAM
The Implementation Planning Program (IPP) is a collection of computer
programs which have been developed for the Environmental Protection Agency
for use by the states (Federal Register, Vol. 36, No. 67, Part II, April 7,
1971) as an analytical tool to assist in the preparation of implementation
plans* for sulfur oxides and particulates. Through the application of
An implementation plan details all the steps to be taken for abatement
and control of emissions from existing sources of pollutants within an air
quality control region, to insure attainment of the ambient air quality
standards within a reasonable time.
17
-------
oo
BENEFITS MODR SEGMENT
POPULATION & HOUSING DATA
CENSUS
TABLES
AND MAP
CEN
TIACT ATTRI-
BUTE DATA
MPLEMENTATION PLANNING PROGRAM (IPf>)
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVa
POLLUTANT CON-
CENTRATIONS)
INTERFACE MODULE
PROPERTY VALUE MODULE
PROPERTY ASSIGNMENT MODULE
CENSUS TRACT] (CENSUS
MR QUALITY TRACT AIR
SUMMARY _J IQUALITY DATA
PROPERTY
ASSIGNMENT
SUMMARY
DAMAGE COSTS MODULE
DAMAGE FUNCTIONS
DAMAGE
FUNCTION
PARAMETERS
DAMAGE
COSTS
SUMMARY
COST/BENEFIT ANALYSIS
(MANUAL PROCESSING)
Figure 2.1-4. RAPA Cost/Benefit Model, Program Structure.
-------
of computer simulation modeling techniques, the Implementation Planning
Program is used in selecting appropriate emission standards, evaluating
the resulting air quality, and determining the costs associated with the
various alternative control strategies.
2.2.1 Component Programs of IPP
The distinct computer programs which comprise IPP are designed to
run in sequence, as shown in Figure 2.2-1. The function of each program is
described below in the order of the program's normal operating sequence in
IPP. The role of IPP in the RAPA Cost/Benefit Model is shown (see the
shaded portion) in Figure 2.2.2.
(1) Source Data Management Program. This program creates, updates,
and lists the primary data file (defined as the Source File). The Source
File contains all the sources of pollutants in a given Air Quality Control
Region which are to be considered by the Implementation Program. These
sources of pollutants are divided into categories of point and area sources,
A point source of emission is defined here as any individual stationary
source for which specific information is input to the program, and is
usually specified on the basis of a single stack. An area source includes
the total emissions from all sources within a given square area which are
either too small or too numerous to specify on an individual point source
basis. The total emissions for an area source are assumed to be uniformly
distributed over the area. Area sources generally include small fuel
combustion sources, on-site solid waste disposal, mobile sources, etc.
Data on area sources are included in determining the ground level pollution
concentration values.
The Source File itself provides direct input to the Air Pollutant
Concentration Program, the Control Cost Program and the Regional Strategies
19
-------
CSOUKI
DATA
.' r
1
SOUICE OAtA MANAGEMENT
FtOGIAM
. CetAU, UPDATE, LIST
c
$OU«CE
LISTING
~1
I SOURCE OATA MANAGEMENT X^
Alt POLLUTANT
CONCENTRATION
PROGRAM
i
.. ,_J
POUHTANT
COHCINIRA-
TION TABLES
FILE UPDATE POOCtAM
SCHJUCE CONTIItUTION
FILE MEtCE PtOCMM
CONIHOL
COST FILE
LISTING
CONTtOlCCST
UPDATE DATA
•EGIONAL
SOURCE
CONIRIW
TION FILE
STEP II
AIR POLLUTANT
CONCENTRATION
SEGMENT
STEP III
CONTROL
COST
SEGMENT
EMISSION
STANDAIDS
TAILU
EMISSION
STANDARDS
OATA
UGIONAI STRATEGIES
PtOGlAM
EMISSION
STANDARDS
CONTIOl
niATEGV
UJMMAIICS
I
DEVICE DATA
REGIONAL DATA
CONTROL COST
PROGRAM
i
P
CCNIICl
COST lABlti
EMISSION
STANDARDS
FILE LISTING
V FIU r
(MISSION STANOAIOS
FILE UPDATE
MOGtAM
I
I
I »TEP IV(b) . CONTROL STRATEGIES SEGMENT STEP IV(»1 I
Figure 2.2-1. Structure of the Implementation Planning Program.
20
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COSTS SEGMENT
MfUMENTATION PLANNING PROGRAM (Iff)
REGIONAL
STRATEGIES
PROGRAM
CONT«OL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVEL
POLLUTANT CON-
CENTHATIONS)
COST/«ENEF(T ANALYSIS
(MANUAL PROCESSING)
Figure 2.2-2. Role of Implementation Planning Program RAPA Cost/Benefit Model,
-------
Program. The point source emission inventory data elements which must be
supplied to the Source Data Management Program include source identification,
location, source type, emission quantities, stack information, existing con-
trols, operating schedules, fuel usage and characteristics, and process rate.
The area source emission inventory data elements include location, identifi -
cation, emission quantities, effective release height, and area.
(2) Air Pollutant Concentration Segment
The major program in this segment, the Air Pollutant Concentration
Program, is designed to estimate the spatial distribution of sulfur dioxide
and particulate matter concentrations throughout the region. The pollutant
concentration output from this program is derived from (1) an atmospheric
diffusion model [Martin and Tikvart, 1968], which transforms the regional
source emissions and meteorological data for a given annual (or other long-
term) period into estimated ground-level arithmetic average pollutant con-
centration values, and (2) a statistical model [Larsen, 1969] which trans-
forms the annual arithmetic mean concentration data (at a limited number of
stations) into expected maximum and short-term concentration values for
specified averaging times.
Validation of the program is accomplished through use of internally
calculated least-squares regression lines. These lines relate the esti-
mated arithmetic mean concentration values produced by the .program to input
measured arithmetic mean pollutant concentration values. This calibration
procedure makes adjustments for errors introduced by approximations in the
diffusion equations, deficiencies in the meteorological and emission input
data, and the neglect of topographical influences in the model.
Program output consists of data tables and a punched card deck for the
arithmetic mean pollutant concentration values and, if requested, data tables
22
-------
for the short-term pollutant concentration values. The punched card deck is
designed for use with an x-y plotter which produces contour-line maps (iso-
pleths) of the various concentrations levels in the region. In addition to
this output, the contribution from each source to each pollutant receptor
defined within the region is output on magnetic tape (defined as the Source
Contribution File) for use by the Regional Strategies Program.
The meteorological data elements required by the Air Pollutant Concen-
tration Program include stability wind rose data (wind direction, wind speed,
stability class), mixing height, ambient temperature and ambient pressure.
The required air quality data elements include the locations of sampling
stations, background pollutant concentration values and the standard geometric
deviation (24-hour average) at each station.
The other program contained in the Air Pollutant Concentration Segment
is the Source Contribution File Merge Program. If more than one run of the
Air Pollutant Concentration Program is required to provide the desired
receptor density, the Source Contribution File Merge Program must be used
to combine the several output files into a single file, as required by the
Regional Strategies Program.
(3) The Control Cost Segment
In general, each point source will have several control-measure options
for reducing its pollutant emission to meet each applied emission standard.
The purposes of the Control Cost Program are to simulate the application of
the alternative control devices available to each point source and to deter-
mine estimates of the total annual cost and efficiency of pollutant removal
for each such application. The output consists of tables of control appli-
cation data for each of the point sources defined in the Source File. The
23
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data generated by the program are output in printed tabular form and on
magnetic tape (defined as the Control Cost File) for use by the Emission
Standards Program.
Figure 2.2-3 illustrates the results from a typical application of three
control devices to a specific point source (e.g., an asphalt batching plant
of a particular size). The total -annual costs shown include the manufacturer's
price, installation costs, annual capital charge, and the operation and main-
tenance costs. In computing these major expense items, the program takes
into account factors such as equipment depreciation schedules, interest rates
on capital, and cost or credit for pollutant disposal. The details of the
cost calculations are covered in Appendix A.
The Control Cost Program requires regional data and control device
information including device identification, device efficiency and rated
life, device labor requirements, device costs (i.e., price, installation
and operating), device applicability criteria, labor costs, alternate fuel
costs, utilities costs and interest rate. A list of the control devices
that are considered in the Control Cost Program is provided in Appendix A.
The program provides the option of using internally preset values for cer-
tain parameters (see Appendix A).
The Control Cost Update Program, the other program in the Control Cost
Segment, permits the user to input corrected or additional data into the
device-source records on the existing Control Cost File and to list the
contents of the file.
(4) Control Strategies Segment
The function of the Control Strategies Segment is to' apply a specified
control strategy so that the least costly control technology that satisfies
24
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CYCLONE
($9,000)
ALLOWABL EMISSION RANGE
PIANT CAPACITY
Figure 2.2-3. Typical Emission Standard Curve Relation to Control Device Application
-------
the appropriate emission standard is applied to each source. An emission
standard is a limitation placed on individual (point) sources of a particular
pollutant. An implementation plan usually specifies different emission stan-
dards that are to be applied to different types of'sources of each pollutant.
These emission standards may be expressed in terms of mass of pollutant per
unit gas volume or per unit time and will usually vary according to the size
of the source. A typical emission standard used in IPP (EST19) is shown in
Figure 2.2-4.
On the other hand, an emission control strategy consists of selected
emission standards covering all significant (point) source types. For par-
ticulate emissions, the significant source types considered by IPP include
fuel combustion, industrial processes and solid waste disposal. For sulfur
•oxides, only fuel combustion and industrial processes are considered.
The Control Strategies Segment provides sufficient output information
to evaluate the regional impact of selected strategies from the standpoints
of; (1) the types of sources affected by the strategy; (2) the degree to
which these sources are affected in terms of control costs; (3) the result-
ing changes in pollutant emissions; and (4) the regionally aggregated
values of control costs by source category, total reduction in pollutant
emissions, changes in regional fuel-use patterns, and resulting air quality
levels.
The Control Strategies Segment performs the simulation process through
use of the Emission Standards Program and the Regional Strategies Program.
The analyst first selects all candidate emission standards (e.g., Figure
2.2-4) for consideration by the Emission Standards Program. The program
then compares the requirements of each standard with the data generated by
26
-------
IUU
£1
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-------
the Control Cost Program. The program selects the most cost-effective de-
vice for each point source under each standard. In the example shown in
Figure 2.2-3, the program would select the wet scrubber.
The data generated by the Emission Standards Program are output in
the form of printed tables for user review and on magnetic tape (defined
as Emission Standards File) for use by the Regional Strategies Program.
The table output illustrates the actual control measures selected for each
source, the annual costs, and data on the degree to which emissions have
been controlled. If necessary, the Emission Standards File may be updated
by the Emission Standards File Update Program, the third program in the
Control Stretegies Segment.
Finally, the analyst selects a set of standards to be applied (i.e.,
an emission control strategy) by the Regional Strategies Program. The
program summarizes the existing, allowable and controlled emissions for the
sources and generates new air quality data based on allowable or existing
emission rates (whichever is less). Reduction of each area source emission
rate is accomplished by user input scale factors. The Regional Strategies
Program requires inputs from the Emission Standards File, the Source File
(area source data), and the Source Contribution File.
Output from the Regional Strategies Program consists of regional and
political jurisdictional summaries of regional costs, regional emissions,
number of sources affected by a given standard, and figures of merit for
each strategy (e.g., cost per ton of pollutant removed, cost per microgram
or per cubic meter of reduced ground-level concentrations).
The ground level concentration data for the controlled conditions are
also output in punched card form. This deck becomes direct input for the
RAPA Cost/Benefit Model. In addition, the tabular output provides essential
28
-------
data for the Costs Segment of the Cost/Benefit analysis. Due to the
importance of the output of the Control Strategies Program to the Cost/
Benefit Model, further details are provided in Section 2.2.2.
2.2.2 Point Source Cost Calculations in IFF
The only cost data employed in the RAPA Cost/Benefit Model at the
present time are generated entirely within the Control Cost Program and
Regional Strategies Program of IFF. The IPP model currently only estimates
the direct costs of emission control to the major point sources. These
point sources cover both the public and private sectors of the regional
economy, however, and their control costs generally form a significant
portion of the total control cost to the region. These costs are generally
acceptable for cross-sectional cost/benefit analysis.
Possible procedures for estimating control agency and area source
control costs have been given by K. Woodcock [1971]. These procedures form
a potential basis for extending the present RAPA Cost/Benefit Model in the
future.
Appendix A provides the details of the point source control cost
calculations as performed in IPP.
2.2.3 IPP jlegional Strategies Output
The Regional Strategies Program output from IPP provides direct
punched card input for the RAPA Cost/Benefit Model and tabulated data
required in the cost/benefit analysis.
2.2.3.1 Tabulated Output for Cost/Benefit Analysis
The Regional Strategies Program provides four types of tabulated
data useful in cost/benefit analysis. These are as follows:
29
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Emission Standard Effects on Source Emissions
The tabulation shown in Figure 2.2-5 is presented for each source
type/political jurisdiction combination. A header indicating the regional
identification, control strategy number and descriptive name, and date pre-
cedes each table. The source type, emission standard number and jurisdic-
tion also are printed before the main tabular listing. The following items
make up the column headings in this tabulation:
• Source Identification. Each source is identified by
its SIC code, site and process numbers.
• Control Device. The device selected by the Emission
Standards Program for this standard is identified by
its numeric code (see Appendix A). The computed
annual cost and device efficiency are also shown.
• Required Efficiency. This decimal efficiency represents
the degree of pollutant reduction required by the source
to bring its potential emissions into compliance with
the allowable emission defined by the control standard.
If the source already has an existing control device
then the required efficiency will be larger than that
needed to bring the existing (partially controlled)
emissions into compliance with the standard.
• Emissions. Three emission rates are displayed for each
source: the existing emissions, the emissions allowable
under the emission control standard, and the controlled
emissions resulting from the application of the listed
control device. The allowable emissions are utilized
in the computation of air quality resulting from the
application of the control strategy.
Jurisdictional Summary
Following the presentation of the Emission Standard Effects on Source
Emissions for each of the three source types within a political jurisdiction,
a Jurisdictional summary is printed (Figure 2.2-6). Again, a table header
30
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CITY STRATEGY II PART ICJLAT = ti.l./P.E.
EMISSION STANDARD EFFECTS ON
1N3USTHIAL PkOCFSS STANJAiO
STATf A
S FQS
I f Ul »TE C."\T*"L
SIC
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L
21 19
2819
2819
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ANNUAL
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1*1 INDICATES "OS' rFFICKENT OfVlCE -AS USEO BUT ALLO^ABLF «AS \ " 1 IT'al.-.l.
!••( INllCtTFS MO OtvlCE AvAILAQLc TJ CJNTani THE SOURCE
ICI INDIC1TFS >'.£S CJOLINk. »«S aEjUIHEO PF IQR m DEVICE A^'P L 1C A I | 1'j .
Figure 2.2-5. Output Format - Emission Standards Effects
-------
to
CENTRAL CITY STRATEGY II PARTICULATE H.I./P.E.
JURISDICTION SUMMARY
STATE A JURISDICTION
NHVEXREP 18. I9f0
REGULATION TYPE
AND NUMBER
FUEL COMBUSTION
B
INDUSTRIAL PROCESS
SDL 10 HASTE DISPOSAL
JURISDICTION TOTAL
TOTAL
APPLICABLE
POINT SOURCES
2
B
••
12
L -JU r ^- . -
TOTAL 1
CONTROLLED 1
POINT S1JRCESI
•
2
G ••
I
T
EXISTING EMISSIONSI
FOS
POINT SOURCES
(TONS/OAYI
.
5. TO
%*.»e_
2.88
'.
54.06
L.
EMISSION
DEDUCT ION
1TONS/0*VI
ALL C k tB. ItCUI EQLLLC
C.CC 5.68
3.bT 44.26
C.29 2.iO
J.96 • S2.44
ANNUAL
CdNTROL COST
(MILL DNS OF t|
B. 186
0.118
0.121
1
8.4*3
COMTROL COST
PER TON
BEHOVE T |*/TON>
«M.«
2C.81
1*1 .SO
L
462. M
1*1 S3ME SOURCES COULD NOT ATTAIN THE ALLOWABLE EHISSI1N
(*•! NO DEVICE AVAILABLE TO CONTPOL SOME S1U»CES.
(Gl GAS C10LING APPLIED TO SOME STU«CEISI.
..o.a.s.
EXISTING EMISSIONS (TONS/DAY*
POINT SOURCES.... •><•.!
ARE* SOURCES 16.1
TOTAL EMISSIONS.. JO.I
CONTROLLED REDUCTION.. %).?
CONTROLLED EMISSIONS ITONS/OAYI
PCINT SOURCES.... 1.6
AREA SOURCES. 14.d
TOTAL EMISSIONS.. Ift.o
: PERCENTAGE PEDUCTIJN... 76.6 t
-_.a_U-t-I_5_0-l.C_I_i.Q_W__£_U_
CPtL (TONS/DAY)
RESID. OIL (GAL/OAVI
CIST. DIL IOAL/UAVI
O.C
C.C
O.C
GtS-llOOO CJ. F1./-)AVI... 912161)6.000
JURISDICTION CONTROL COST-EFFtCTI
V E N. ? S S
REOUCTION IN T?TAL POINT SOUR.rE EMISSION
462. Si DOLL »as/TON
Figure 2.2-6. Output Format -- Jurisdiction Summary
-------
is provided which identifies the control region and the emission control
strategy under consideration. The run date and political jurisdiction are
also displayed. The following data elements are included in the tabular
presentation:
• Regulation Type and Number. The emission standard
applied to each source type is identified by number.
0 Total Applicable Point Sources. The number of point
sources is listed both by source category and as a
total for the jurisdiction.
• Total Controlled Point Sources. The number of sources
required to reduce their pollutant emissions are tabu-
lated in this column. Indicators are provided when
certain of the sources cannot be properly controlled by
the devices considered in the Control Co_st Program.
• Existing Emissions for Point Sources. This column
summarizes the existing pollutant emissions by source
category.
• Emission Reduction. Two measures of emission reduction
are included under this heading. Allowed emissions
refer to the emission levels specified by the emission
standards making up the control strategy. Controlled
emissions indicate the amount of reduction produced by
the control devices selected by the program to bring
each source into compliance with the allowable emission
levels. It must be noted that the two sets of figures
in this column are not strictly comparable since the
control device selected may produce a greater reduction
than is required by the standard. Also, in some cases,
there may be no control device available which allows
a source to meet the emission level specified by the
standard.
• Annual Control Cost. This column presents the
accumulated control costs of the control devices
assigned to each point source under the control
strategy.
• Control Cost per Ton Removed. The figures presented
in this column represent the product of the annual
control cost divided by the number of tons of
pollutant removed annually by the control device.
These figures give an estimate of the cost effective-
ness of control by source categories and overall
effectiveness.
In addition to the main tabulation, described above, the Jurisdictional
Summary also contains a summary of the emission pattern prior to and follow-
ing the application of the control strategy. Both point and area source
33
-------
emissions are included in this summary. The reduction in area source emis-
sions shown indicates the effect of the area source scale factors input by
the user. The jurisdictional fuel use patterns following application of
the control strategy are also displayed.
Control Strategy Summary
Figure 2.2-7 provides an overall summary of the pollutant reductions
required under the control strategy. The header information and column
headings are the same as for the jurisdictional summaries described above.
This tabulation represents the summation of control information over the
entire air quality control region. One additional piece of information
is included in this output which was not in the previous summaries. The
reduction in ground level concentration indicates the number of dollars
required to produce an average one microgram/cubic meter reduction in the
regional pollutant levels. This value will vary between control strategies
and thus provides another measure of effectiveness of each strategy.
Control Strategy Effects on Ground Level Concentrations
The result of the pollutant emission reductions on ambient air quality
throughout the region is displayed in Figure 2.2-8. The table header iden-
tifies the control region, control standard and the run date. The air qua-
lity standard for the pollutant being controlled is also shown. Each recep-
tor location is identified with a unique number and by its X and Y coordinates.
The expected pollutant concentration following the application of the control
strategy is indicated in micrograms/cubic meter. The amount of reduction
from the existing ambient conditions is also displayed in a separate column.
The amount by which the concentration at each receptor point is in excess of
the ambient air quality standard is also shown.
2.2.3.2 Punched Card Output for Cost/Benefit Model
The control strategies effects on ground level concentrations provided
in printed tabular form (Figure 2.2-7) was described above. This data is
also produced in punched card form so that an isopleth plot can be produced
for easy visualization of the resulting pollutant concentrations.
-------
CENTRAL CITY STRATEGY II PARTICULATE H.I./P.f.
CONTROL STRATEGY SUMMARY
N1VFHBIP 18. I«»7C
JU» ISDICTIOH
AND NUMBER
STATE A
STATF B
1
2
STRATEGY TOTAL
1 1 1
1 TOTAL I TOTAL IEXISTINS EIISSIONS
1 APPLICABLE 1 CONTROLLED 1 FOR
(POINT SOUPCESIPOINT SOU»CESI POINT SOURCES
t_ i I lIOUS/DAirl
1
1
1
1
1
.. .1.
12 1
1
1
J_
1
26 I
7
8
15
J
54.06
28. 2C
L
82.26
L
EMISSION
SFOUCTIOK
I TONS/DAY I
J.96" 52. 44
6.16 25.17
.- ..
1C. 12
L :
77.81
CJNTHOL CnST
(MILLIONS OF »l
L
a.
16.
25.
L
164
217
__J
CONTROL COST
PER TON
PfOVED ( »/TONI
L
462
1767
8B7
L- __
.53
.31
."»»
(•I SOME SOURCES COULD NOT ATTAIN THt ALLOWABLE EMISSION
(••I NO DEVICE AVAILABLE TO CONTROL SO«E
ICI GAS COOLING APPLIED TO SO«E SOURCEISI.
EXISTING EIISSIOSS ITONS/OAY)
POINT SOURCES.... 82.3
AREA SOURCES 20.1
TOTAL EltSSIDMS.. 1?2.3
CONTPOLIED BEOUCT IDN. . 79.5
CONTROLLED EMISSIONS ITOM5/OATI
POINT SOURCES.... *.i
»OEA SOURCES 18.<•
TOTAL ("ISSI3NS.. 22.8
PERCENTAGE REDUCTION... 77.7 f
CO*L (TONS/DAYI
RESID. OIL (GAL/DAYI.
DIST. OIL (GAL/OAYI..
c.c
P.C
c.c
GAS tIOOP CU. FT./DAVI...2T661312C.C^P
REGIONAL CTNTRTL COST-EFFECTIVENESS
REDUCTION IN TOTAL PCINT SOURCE EMISSION HATE 887. -*i DOLLARS/TON
REUUCTIJN IN UF1U»vD LEVEL CONCENTRATION . . . ?5C838<.C. C DLL AR S/«l CkOG>< AH/CU9IC "E Tf R
Figure 2.2-7. Output Format - Control Strategy Summary
-------
CENTRAL CITY STRATEGY II PAKTICOLATE H.I./P.E.
NOVEMBER 18. I97C
AIR QUALITY STANDAKO OS. 0
JT1 ORIGINIKlLdMfTE4SI: »•
CONTROL STRATEGY EFFECTS ON GROUND LEVEL CONCENTRATIONS
HIC«OGBAHS/CUBIC
c.o v- o.o
RECEPTOR
LOCATIONS
UTH.MLO-FTERS
& ______ i ____ I
60.00
60. OC
6S.OO
6S.OO
bS.OC
90.30
60.00
90.00
40. CO
«c
«iS
56
72
TI
cc
CC
3C
60
1T
AMOUNT F?nuCE3
IN Exf.FSS
Nf« CONCENTRATION VALUE)
I
M1CRJGRABS/CJB1C KfcTERI MICPCGRAIIS/CUH1C MLTEHI MIC ROMANS/CUB 1C »IETEi;l
01 C.S0869<>E CO
Cl L.->C7166F CC
0.8^63idE Cl C.b%74bCE CO
C.62723CE Cl
0.8<.l^ilt Cl
G.2P2217E C2
0.09S8/3E Cl
0.191SS8E
Figure 2.2-8. Output Format - Ground Level Concentrations
-------
Figure 2.2-9 illustrates the existing ground-level particulate concen-
trations in the NCIAQCR as predicted by the calibrated Air Pollutant Concen-
tration Program. In this region, the goal of the implementation plan was
to attain an annual arithmetic average of particulate concentrations of
3 3
86.6 yg/m as an interim standard and 65.2 pg/m as a long-term standard.
In testing the acceptability of a strategy, the IPP model is used to
ascertain that the annual average concentration does not exceed the long-
term air quality standard at any point in the AQCR.
To meet the above standards, a control strategy for reduction of the
particulate concentration was required. The isopleths in Figure 2.2-9
indicate that annual average concentrations above 90 pg/m were observed
in the NCIAQCR. Concentrations of up to 107.7 pg/m could be expected
3 3
within this 90 pg/m isopleth (the 100 pg/m isopleth was too small to be
drawn on the map). Analytical results for 19 control strategies are pre-
sented in Table 2;2-1. The reduction in emissions from point and area
sources is indicated, as well as the control cost expected and the pollutant
concentrations at the maximum receptor in the region. Strategy 18 was se-
lected for the District of Columbia, on the basis of (1) control costs, (2)
expected air quality (which, within experimental error, approximated the
air quality standard), and (3) the assumption that the emission control
technologies required to meet the strategy were technically feasible and
economically reasonable. Particulate levels expected after the application
of the proposed control strategy are illustrated in Figure 2.2-10.
In addition to providing isopleths of air pollutant concentration
levels over the region, the punched card output provides direct input to
the RAPA Cost/Benefit Model (CONVRT). The data which is initially on a
receptor basis must be converted to census tract mean concentrations.
The method used to accomplish this and the computer program module which
automatically performs the transformation are discussed in Section 2.6.
37
-------
NOTE
: Annual Concentration In yg/m3
Figure 2.2-9.
Existing Ground Level Particulate Concentrations in
the NCIAQCR as Computed by the Verified Air Pollutant
Concentration Program.
38
-------
Table 2.2-1. Particulate Control Strategies - National Capital Interstate Air Quality Control Region.
POINT SOURCES
AREA SOURCES
CONTROL COST
Strategy
Number
Existing**
1
2
3
4
5
6
7
8
9
10
18
Percent
Reduction
—
36.3
87. A
62.2
52.7
86.4
78.2
76.0
36.3
41.0
77.0
70.4
New Emission Rate
(tons/day)
[84.7)
54.0
10.7
32.0
40.1
11.6
18.4
19.9
54.0
50.0
19.5
25.0
Percent
Reduction
—
18.0
51.4
47.5
48.6
51.4
51.4
51; 4
36.3
18.6
51.4
51.4
New Emission Rate
(tons/day)
(75.6)
62.0
36.7
39.7
38.9
36.7
36.7
36.7
48.2
61.6
36.7
36.7
•$ x 106
—
0.5
13.9
4.0
4.4
11.8
11.6
11.6
0.5
0.6
11.6
10.8
$/ton removed
—
47
514
210
267
471
489
489
47
44
489
498
Maximum
Receptor
(pg/m3)
—
107.7
92.2
90.0
76.0
69.4
69.7
69.7
89.8
81.8
70.0
68.2
**
Existing conditions based on the 1969 inventory collected for the NCIAQCR and the validated
diffusion model.
-------
Note: Annual Concentrations in
Figure 2.2-10. Predicted Particulate Concentrations
After the Enactment of the Proposed
Emission Control Strategy, in all
Political Jurisdictions.'
-------
2.3 CENSUS TRACT DATA
A central task of the RAPA Cost/Benefit Model is to provide a measure
of the effects of air pollution on people and property. In order to perform
this task, the model must be supplied data on regional air quality, popula-
tion and property distributions (Figure 2.3-1, shaded portions). The air
quality data is generated by IPP, previously described in Section 2.2. The
population and property data on the other hand, are available from the
Bureau of the Census. The census tract data was selected because the
decennial censuses of population and housing provide the required detailed
information on the population of a region and the individual and household
characteristics. These data are supplied on a census tract basis.
The Department of Commerce defines census tracts as follows:
"Census tracts are small, permanently established, geographical
areas into which large cities and their environs have been di-
vided for statistical purposes. Tract boundaries are selected
by local committee and approved by the Bureau of the Census.
.They remain the same for a long time so that statistical com-
parisons can be made from year to year and from census to census.
The average tract has over 4,000 people and is originally laid
out with attention to achieving some uniformity of population
characteristics, economic status, and living conditions. In each
decennial census, the Bureau of the Census tabulates population
and housing information for each tract—hence, the name "census
tract".*
The criteria* employed in defining census tracts are as follows:
• Population Size - A census tract should contain between
2500 and 8000 inhabitants, but may contain somewhat
more. Tracts covering a large population are desirable
if the population is homogeneous. The average size for
all tracts should not be less than 4000 inhabitants.
*These descriptions have been condensed from the Census Tract Manual .
41
-------
BENEFITS MODEL SEGMENT
: POPULATION & HOUSING DATA
IMPLEMENTATION PLANNING PROGRAM (IPP)
RECEPTOR
AIR QUALITY
DATA
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVEL
POUUTANT CON-
CENTRATIONS)
PROPERTY VALUE MODULE
PROPERTY ASSIGNMENT MODULE
PROPERTY
ASSIGNMENT
SUMMARY
PROPERTY
VALUE
SUMMARY
DAMAGE COSTS MODULE
DAMAGE FUNCTIONS
DAMAGE
FUNCTION
PARAMETERS
COST/BENEFIT ANALYSIS
(MANUAL PROCESSING)
Figure 2.3-1. Population and Housing Data Relation to RAPA Cost/Benefit Model,
-------
• Boundaries - Census tract boundaries should follow
permanent and easily recognized lines (state lines,
highways, railroads, rivers, streams, channels, and
the like). Alleys are normally not used and should
not be unless named.
• Homogeneity - Census tracts should contain, insofar
as it practicable, persons of similar racial or
nationality characteristics, of similar economic
status, and of similar housing. If a tract includes
both expensive homes and slum dwellings, for example,
average statistics for the tract as a whole will not
reflect the condition of either group.
• Geographic Shape and Size - In general, a census tract
should be compact. It is desirable to avoid panhandles,
L's, dumbbells, and other elongated shapes. Irregular
boundaries should be avoided wherever possible.
The cost/benefit analysis example for this report involves the
Washington, D. C. Standard Metropolitan Statistical Area (SMSA). An SMSA
(except in New England) has the following properties:
(1) It contains either one county or a group of contiguous
counties.
(2) The county group must contain either one central city
of at least 50,000 inhabitants or "twin cities" with
a total population of at least 50,000 inhabitants.
(3) The counties included in the SMSA must either contain
the central city or form a socially and economically
integrated metropolitan area with the central city.
The Washington, D. C. SMSA consists of: the District of Columbia;
Arlington County, Fairfax County, Alexandria City and Falls Church City in
Virginia; Montgomery County and Prince Georges County in Maryland.
The census data employed here is from the 1960 census. The 1970
census information is not available in published form at the present time.
Appendix B provides information on the census tract attributes themselves
and the sources of census tract information.
43
-------
2.4 AIR POLLUTION DAMAGE FUNCTIONS
If costs and benefits of air pollution control are to be analyzed on
a quantitative basis, then they must somehow be related on a common scale.
The traditional scale of convenience for cost/benefit analysis is "price."
However, since there is no marketplace as such for clean air, the price
must somehow relate to society's willingness to pay to reduce air pollution,
(i.e., the effects). The willingness to pay for clean air can be best re-
lated to the avoidance of the damages of air pollution to the society.
Thus, the benefits of improved air quality are the reduction in damages
that would otherwise occur due to the presence of pollutants. The next
logical requirement is to express these damages on a price scale (in
dollars). The relation of the damage functions to the various modules of
the RAPA Cost/Benefit Model is illustrated in Figure 2.4-1.
2.4.1 Direct Damage Functions
There have been various attempts recently to produce damage functions;
most of these have been efforts to quantify one or more of the direct effects
of air pollution. A simple example which illustrates the basic form is the
damage function developed by Wilson and Minnotte* for the Washington, D.C.,
metropolitan area (Figure 2.4-2). The damage function relates per capita
annual soiling cost to concentrations of suspended particulates. The
authors utilized the results of air pollution statistical studies in the
Washington, D. C., area conducted by Irving Michelson. Michelson's study
R. D. Wilson and D. M. Minnotte, "A Cost-Benefit Approach to Air
Pollution Control," Journal of the Air Pollution Control Association,
Vol. 19, No. 5, p. 306, May 1969.
44
-------
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVEL
POLLUTANT CON-
CENTRATIONS)
Figure 2.4-1. Damage Functions: Role in the RAPA Cost/Benefit Model,
-------
160 -
<
^4
Q_
120
.
O I—
O —•
O.
CJ<
z o
80
o
CO
II
>-
40
Y =1.85 X - 42
20
40
60
80
100
X = SUSPENDED PARTICULATE CONCENTRATION (ug/mj)
Figure 2.4-2. Wilson and Minnotte Function for Damages Due To Soiling
46
-------
used responses to a questionnaire to determine the frequency of certain
household cleaning chores in areas of high and low air pollution within
the metropolitan area.*
This function provides a simple linear relation between the annual
per capita soiling cost and the average annual particulate concentration
in ug/m3. Soiling, of course, represents a small part of the direct
damages due to air pollutants. The direct damage function employed in
the Cost/Benefit Model Demonstration for the NCIAQCR is also a linear
function of the same form as the Wilson-Minnotte relation. However, the
Pro Forma Damage Function (Figure 2.4-3) used here represents an effort to
provide a gross estimate of national damages across the full range of
direct effects. A detailed explanation of the development of these damage
functions (note that there are two functions, one for S09 and one for par-
ticulates) is given in Appendix C. Before continuing on, however, we
should note that linear damage functions merely represent the best that
can be done at the present time. There is no reason to believe that they
are universal. In fact, one would expect further research to reveal a
direct damage function of the form shown below.
Per Capita
Annual Damage
Cost
Pollutant
Concentration
An initial slow rise followed by sharply increasing slope is to be expected.
I. Michelson, "The Household Cost of Living in Polluted Air in the Washington,
D. C. Metropolitan Area," A Report to the U. S. Public Health Service.
47
-------
00
co
cS
01
oo
03
60
50
M
CO
0)
30
«0 (X
4J CO
•H O
«w
o ^
PM
u
20
10
0.47X
40 80 120
X = Weighted Air Quality (wg/m3)
Jigure 2.4-3. Pro Forma Damage Functions- Used In RAPA Cost/Benefit Model NCIAQCR Demonstration
-------
This feature would result from the "threshold" effects exhibited by many
forms of pollution damage. Similarly, a leveling off at high concentrations
due to "saturation" effects may be anticipated.
Damage functions are generally expressed in relation to the population
(or number of households) and pollution concentration. In the RAPA Cost/
Benefit Model, damage functions are applied to each census tract in an AQCR
(or SMSA) to determine the census tract damage cost. The sum of the damage
costs for all census tracts in an AQCR determines the AQCR damage cost.
The damage estimates of the direct effects of pollution are estimated
as a function of particulate and/or sulfur dioxide concentrations for the
base alternative (i.e., the existing condition) as well as for predicted
concentrations under a given emission control strategy. Social benefit is
considered to be the difference between the damages from the base alterna-
tive and damages after application of the control strategy. This concept
is demonstrated in the following figure:
DIRECT EFFECTS
POLLUTION CONCENTRATION (ug/nT)
.C1 = (DAMAGE COSTjP^-Cg = (DAMAGE COST)P2
SOCIAL BENEFIT = C] - C2
49
-------
2.4.2 Market Effects Damage Functions
Economists Robert J. Anderson, Jr., and Thomas D. Crocker, using
statistical analysis, have found a negative correlation between particulate
and S0_ concentrations and residential property values. The statistical
results of the Anderson and Crocker regression analysis for the Washington,
D. C. SMSA are summarized in Table 2.4-1.
The Anderson-Crocker functions (i.e., the four types of regression
equations) actually provide an estimate of market effects resulting from
the preference of the residents of the SMSA to live in areas of. higher air
quality. These market effects result from the conscious and subconscious
perception of the direct effects and reflect adjustments made in the market-
place. However, the impact of direct effects on deterioration of materials,
etc. are also reflected to a degree in these functions and cannot be
separated out.
The RAPA Cost/Benefit Model demonstration has utilized the Anderson-
Crocker damage function (Type I regression equation) applied to the
Washington, D. C. SMSA (see Section 2.7).
In utilizing property value functions of this type to estimate the
social benefits from market effects, the differences between the annualized
household property values under the two strategies (illustrated below) must
be determined. In practice, these values were produced from the Property
Value Module discussed later in this chapter.
50
-------
Table 2.4-1. Regression Results of Anderson-Crocker Study For The Washington, D. C. ,
SMSA
DEPENDENT
Regression Coefficients
• —
INDEPENDENT
Cons t .
In
In
In
In
In
In
In
In
R2
s2
T
(PSN)
(PPT)
(MFI)
(DLP)
(OLD)
.(NWT)
(DIS)
(MUM)
' —Type I
3.3901 <
-.0712 1
-.0610 <
.7677 1
.0044 I
-.016 1
.0251 1
-.0582 (
.6966
.0222
275
[.4012)
[.0222)
[.0318**)
[.0447)
[.0059**)
[.0103)
[.0064)
[.0158)
Type II
1.1617
.0010
-.1698
.9970
.0113
-.0213
.0321
-.0312
.9064
.7897
.0179
121
(.5622*)
(.0270**)
(.0509)
(.0587)
(.0079**)
(.0107*)
(.0080)
(.0097)
(.1948)
Type III
.2428
-.0905,
.0049
.5109
.0121
-.0606
-.0043
-.0216
.6963
.0181
218
(.4441**)
(.0239)
(.0316**)
(.0492)
(.0055*)
(.0125)
(.0066**)
(.0152**)
Type IV
.4705 1
-.0727 1
-.0302 1
.4650 <
-.0054 1
-.0408 1
-.0124 1
-.0111 1
.7549
.0136
218
[.3859**)
[.0207)
[.0275**)
[,0431)
[.0048**)
[.0108)
[.0058*)
[.0132**)
* Not significantly different from zero at the .01 level.
** Not significantly different from zero at the .05 level.-
-*•** R. J. Anderson, Jr., and T. D. Crocker, "Air Pollution and Housing:
Some Findings" Paper No. 264, Institute for Research in the Behavioral,
Economics, and Management Sciences, Purdue University, Lafayette,
Indiana, January 1970.
-------
o.
,aPV
o
LU
t/1
o
LU
1
MARKET EFFECTS
POLLUTION CONCENTRATION (ug/nT)
SOCIAL BENEFIT = PV2 - PV]
2.5 INTERFACE MODULE
The Interface Module (CONVRT) calculates the mean concentrations of
particulate matter and sulfur dioxide for each census tract (CTPC) in the
air quality control region or standard mean statistical area of interest.
The resulting data set(s) of census tract pollutant concentrations (CTPC)
and the card deck of census tract attributes provide the only interfaces
between the remaining analysis modules of the RAPA Cost/Benefit Model.
The relation of the Interface Module to the other modules of 'the RAPA
Cost/Benefit Model is illustrated in Figure 2.5-1.
2.5.1 Input
The receptor point pollutant concentrations are produced in punched
card form by the Regional Strategies Segment of IPP .(see Section 2.2). A
card deck is produced by IPP for each strategy/pollutant combination,
52
-------
Ln
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS
GROUND LEVEL
POLLUTANT CON
CENTRATIONS)
Figure 2.5-1. RAP A Cost/Benefit Model; Interface Module.
-------
and CONVRT processes these decks, one at a time, with the census tract
attribute data. However, the capability for multiple runs exists which
permits the processing of a number of decks in sequence. The technique
for doing this is detailed in Appendix E.
The user must also provide the Interface Module with an association
(in punch card form) of specific receptor points with each census tract for
purposes of determining the census tract air quality (see Appendix E for
card formats). The next sub-section elaborates the analytical techniques
used to form the census tract/receptor point association. Figure 2.5-2
indicates the relation of the association procedure in the overall flow of
the RAPA Cost/Benefit Model.
2.5.2 Analytical Technique for Estimating Census Tract Air Quality
The Regional Strategies Segment of IPP computes air pollutant concen-
tration values at specified receptor points distributed over the region.
Up to 225 regularly spaced receptors may be specified, together with 50
individually located receptors. These 'receptor locations are used for
both particulates and sulfur oxides. The regularly spaced receptors are
defined by intersections in a grid pattern having equidistant vertical and
horizontal spacing. The grid pattern is determined by the location of its
southwest corner (with respect to the origin of the source coordinate sys-.
tern), the number of rows and columns of receptors, and the distance between
adjacent rows and columns. Figure 2,5-3 shows the relationship between the
receptor points and census tracts for Washington, D. C. The regular grid
system (indicated by solid circles) has been divided into a "coarse" system
covering the entire SMSA and a "fine" system covering the central city.
The individually specified receptors are indicated by empty circles. Figure
2.5-4 is a close-up view of the central city and the "fine" grid system.
54
-------
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS
GROUND LEVEL
POLLUTANT CON
CENTRATIONS)
Fieure 2.5-2. RAPA Cost/Benefit Model; Receptor Point Census Tract Association.
-------
CELL'S TKAnS IN THE \V*SI'.:>T. iVN «-"
•j'tf •*
0 Location of receptor point and receptor point number, Ki.,
9 Regular grid system receptor
o Specially located recrptor
Figure 2.5-3. Receptor Points Superimposed on
Census Tracts of the NCIAQCR.
56
-------
li^M"-<«>y^'^'-r*Y
Figure 2.5-4.
Receptor Points Superimposed on Census Tracts of the NCIAQCR,
Close-Up View of Central City.
57
-------
A procedure was developed for relating the receptor point pollutant
concentration data as calculated by IPP to mean values for the census tracts.
These mean values are referred to as the census tract pollutant concentra-
tions (CTPC). It is assumed that these mean values are representative of
the actual concentrations anywhere in the census tract, i.e., that the
pollutant concentrations are reasonably homogeneous over the area of a
census tract* The procedure uses the existing receptor grid of IPP and the
census tract data in the format presented in Appendix E.
An obvious procedure would involve re-orienting the receptor grid
.'system so that the receptor coincides with the centroid of each census
tract. These centroidal concentration values could then be used to
approximate the census tract pollutant concentrations. However, since the
number of census tracts generally exceeds the maximum number of 50 individ-
ually located receptors, the special multiple run procedures would have to
be employed in the Air Pollutant Concentration Segment of IPP in order to
build up a sufficient number of special receptors*. These procedures signi-
cantly increase costs in operational computer time.
The NCIAQCR, with 1960 census data, requires 362 special receptor
points. This number would increase to 650 receptors when the 1970 census
data is reported, while a region the size of New York City would require
on the order of 3,000 special receptors. Even if an initial redesign of
IPP were made to accept up to 275 or more special receptors in a single
run of the Air Pollutant Concentration Program, the additional cost of
computer time would be excessive. Instead, the analytical procedure des-
cribed here was developed to form the interface.
*The procedures for accomplishing this are detailed in Section 3.2 Air
Quality Implementation Planning Program, Vol. II.
58
-------
The method that was employed in determining the CTPC for each census
tract is as follows:
(1) Draw the Universal Transverse Mercator grid system which
is used in IPP on the census tract base map for the region.
(2) Using this reference grid, locate the receptor points on
the base map. These receptors locations are provided in
the Regional Strategies Segment output (see Section 2.2).
(3) Examine one census tract and visually determine the
combination of receptors that would appear to yield
the most, representative air quality for the census
tract (isopleth plots can provide valuable assistance
here).
(4) List the receptor numbers of the receptor points that
were selected for the census tract on a specially
prepared data form (Appendix E).
(5) Calculate the CTPC by taking the arithmetic average of
the pollutant concentration values of the selected re-
ceptors. This is done for both particulates and sulfur
oxides.
(6) Repeat the process for each census tract in the air quality
control region.
This operation is conducted once for each AQCR by the researcher
before the cost/benefit analysis of the region is begun. In practice,
after the special forms of Step (4), above, have been completed, the
information is placed on punch cards (format in Appendix E). Step (5) is
then automatically performed by the CONVRT module of the RAPA Cost/
Benefit Model.
The six steps of the entire procedure are illustrated below for a
hypothetical example. Consider the following two situations:
59
-------
CENSUS TRACT A
CENSUS TRACT B
RP-21
CONTROL STRATEGY RESULTS:
Receptor Calculated .,
Point Air Quality (ug/m )
RP-21 78.6
RP-23 79.5
RP-25 77.9
Receptor
Point
RP-10
RP-13
RP-15
RP-17
Calculated ~
Air Quality (ug/m )
97.0
98.7
97.5
98.2
For Census Tract-A, the researcher will likely choose the three
Receptor Points RP-21, RP-23 and RP-25 to represent the census tract.
He will then list these receptor points on the prepared form. This same
combination of receptor points will be used each and every time a strategy
is evaluated using the C/B model. To compute the air quality for Census
Tract-A, the following equation is used:
(CTAQ)
(AQ)
21
(AQ)
25
n
where:
• (CTAQ) = Air quality for Census Tract-A.
(AQ)n, (AQ)23, and
Air Quality for the
Receptor points RP-21,
RP-23, and RP-25,
respectively.
60
-------
• n = Number of receptor points chosen to represent
Census Tract-A.
For the example, then, the calculated air quality for Census Tract-A is:
(CTAQ)=78'6+79'5+77-9 - 78.7 .g/m3
A 3
For Census Tract-B, the researcher will probably choose receptor
point RP-15 to represent the census tract. Since RP-15 is relatively
near the centroid of the census tract, it will likely give a better
estimate of the census tract than will any combination of the four
receptor points shown. Following the procedure illustrated for Census
Tract-A, the calculated air quality will be as follows:
_ g_ . _
(CTAQ)_ -- — = ^-^- =97.5 ug/mJ
B n 1
2.5.3 Output
The interface module produces both printed tables and punched card
output. The information contained in both is essentially the same, al-
though the formats are different. Figure 2. 5 -.5 shows a sample of the
tabulated data produced by CONVRT; it includes the census tract identifi-
cation, political jurisdiction number (Washington, D.C. = 1, Montgomery
County = 2, Prince Georges County = 3, Arlington County = 4, Fairfax
County = 5, Alexandria = 6, Falls Church = 7), pollutant concentration
(micrograms per cubic meter) and the background concentration value*.
In addition, a tabulated summary of the receptor point pollutant concen-
trations that were supplied as input is available to the user. The
output table is optional, and can be surpressed .
* For a discussion of the background pollutant concentration, see Chapter
4- Air Quality Implementation Planning Program. Vol. I.
61
-------
TRACT PULLUTAKT CONf£Nr«4TIUNS — ' HUTPUT
N>
wASHi;£H
CUUIC (ttrEK)
.WHSER POLITICAL CHSSoS PULLUf AM .CONCeNfftA f ION
JURIS-HCr |;1M T-IACr IH1C«||GR**S >•?« CU'ilC -^fc-O
1.
2
S
6
7
S
n
1 1
1 4
14
1 %
16
1 7
13
23
21 .
22
1
2
1
S
6
7
8
0
10
1 1
12
1 i
6*. 73
61.08
61.01
63.3".
65.1-1
56. bd
56.65
5*. PS
56.R3
SI. 77
fc 1 . 4O
Is ":"
16
^tl. 78
Figure 2.5-5. Output Format-Tabulated Census Tract Pollutant Concentration Data.
-------
2.6 DAMAGE COSTS MODULE
The Damage Costs Module (DAMAGE) illustrated in Figure 2.6-1 employs
a general purpose linear damage function to calculate annual damage costs
on a per capita basis as a function of pollutant concentration. A separate
function is used for particulates and sulfur oxides, but the general form
is the same:
dc = Ax CTPC + AQ, (2.1)
where d is the annual per capita damage cost (dollars/year)
c
CTPC is the census tract pollutant concentration
(A ,A ) are coefficients which are provided to the program and vary
with the pollutant (particulates or S0_).
The total damage cost on a census tract basis is then calculated
from:
D = POP x d , (2.2)
where D is the census tract damage cost (dollars/year) on an annual basis
POP is the total population of the census tract.
The coefficients (A ,A ) provide a measure of the costs of damage to the
physical health of the population, residential property, materials and
vegetation. A discussion of the Pro Forma Damage Functions used in the
NCIAQCR demonstration and their derivation is provided in Appendix C.
The program can be easily modified to accept a general polynomial
damage function of the form:
d = A + A. x CTPC + A. x (CTPC)2 + ... + A., x (CTPC)N,
col i N
where all the coefficients (A , A.. , ... , A_) and the order of the
polynomial, N, are provided as input data. This will probably become a
desirable modification in the future, as more research is done on damage
63
-------
COSTS SEGMENT
IMPLEMENTATION PLANNING PROGRAM (IPP)
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVEL
POLLUTANT CON-
CENTRATIONS)^
'DAMAGE
FUNCTION
PARAMfTERS
DAMAGE COSTS MODULE
i^
r*
DAMAGE
DAMAGE
COSTS
SUMMARY
COST/8ENEFIT ANALYSIS
(MANUAL PROCESSING)
Fieure 2.6-1. RAPA Cost/Benefit Model; Damage Costs Module,
-------
functions, However, the linear form incorporated into the existing module
is adequate for the state-of-the-art.
2.6.1 Input
The Damage Costs Module requires the following inputs:
(1) The slope and intercepts (A. , A ) for the linear damage function.
The input is in the form of a punched card (format in Appendix).
(2) The card deck of census tract attributes for the region. This
deck contains all the census tract attributes listed in
Appendix E and provides common input for all of the
analysis modules. However, each module reads into core
only those attributes required for the particular analysis.
DAMAGE only stores the total population and census tract
identification numbers.
(3) The census tract pollutant concentration data deck produced by
the interface module.
These inputs are required separately in separate runs for each
pollutant/strategy combination.
2,6.2 Output
The output of the Damage Costs Module includes two tabulated summaries
of the input data:
(1) Census tract attributes (identification number and total
population).
(2) Census tract pollutant concentrations.
Both of these input data summaries are optional and can be surpressed.
The principal output consists of tabulated values of exposure and
damage costs for each census tract identified by number and political
65
-------
jurisdiction. The damage costs in dolars per year are calculated from
equation C2.2). The exposure, E. , of census tract "i" is defined as:
e = CTPC x POP (2.3)
(people-micrograms per cubic meter)
For each political jurisdiction, total and arithmetic averages are given
for the damage costs and exposure, i.e., the following quantities:
totals,
NPJ NPJ
X °ci * I] V (2'4)
averages
NPJ WPJ
n 1 T
Dci ' NPJ 4^ ei '
(2.5)
1=1 "••'• "i0 1=1
where NPJ is the total number of census tracts in the political jurisdiction.
An additional quantity, the pollutant concentration weighted with respect to
population, pc, is given for each political jurisdiction. This quantity is
calculated:
NfJ
~ ' (2.6)
The corresponding quantities for (2.4), (2.5) and (2.6) are also given on
a region-wide basis, i.e., the summations are performed over all census
tracts. Figure 2.6-2 shows a sample of this damage costs summary output.
66
-------
TRACT OAMACE rnsT
WASHINGTON. n.r.. EXISTING -- sin EUR DIOXIDE
NUMBER
12*
126
127
129
110
111
112
111
"t
136
118
1*0
141
141
45
344
1*5
146
147
1*8
3*9
151
151
154
1)9
157
158
159
160
361
16?
16}
20
164
165
166
3
366
POL IT ICAI CENSUS
JURISDICTION TRACT
26
77
23
29
10
11
12
11
is
16
17
18
19
40
41
42
41
44
43
POLITICAL JURISDICTION TOTALS
POLITICAL JURISDICTION AVERAGES
POLITICAL JURISDICTION AIR QUALITY
6 1
6; 2
6 1
6 *
6 5
6 6
6 7
6 4
6 9
6 10
6 1 1
6 12
6 13
6 I*
A 15
6 16
6 17
6 11
& 1 9
6 20
POLITICAL JURISDICTION TOTALS
POLITICAL JURISOICTION AVERAGES
POLITICAL JURISOICTION AIR QUALITY
7 1
7 2
7 1
POLITICAL JURISDICTION TOTALS
POLITICAL JURISDICTION AVERAGES
POLITICAL JURISOICTION AM QUALITY
EXPOSURE
1B5797.
7 1744R.
208235.
24*27! .
25482*.
751 RSB.
227976.
552622.
160903.
607554.
180097.
771 7Q1.
383*78.
282928.
178903.
10R656.
156264.
91747.
17544911.
278776.
47.82
1 mill. '
121194.
181645.
2018*.
321*59.
193*57.
1 15312.
1*0*50.
2*5716.
38975*.
521011.
250777.
257125.
747757.
261378.
56798.
342126.
146116.
42 Ha i.
*896983.
744449.
51.81
1 1 1 1 79 .
?70';55.
98520.
482254.
160751.
47.11
REGIONAL TOTALS 129200000.
REGIONAL AVERAGES
REGIONAL AIR QUALITY
151005.
65.05
DAMAGE
COST
48 909 .
l»4771.
111328.
(12194.
11*796.
111702.
120611.
»<172?6.
95782.
170917.
4*068.
145 1O4.
209227.
>lhOOO.
IM112.
93391.
47795.
H15HH.
41175.
4T119H7. .
1*9600.
(WEIGHTED W.R.T.
75»45.
66386.
<>91 H4.
10812.
176620..
105614.
74SHI .
146712.
1&R41R.
117717.
2LB446.
295029.
116141.
139793.
113419.
1*1*91.
31M2.
187932.
774S4.
211187.
2695037.
114757.
(WEIGHTED W.R.T.
60612.
144533.
51020.
258169.
16056.
(WEICHTE3 W.R.T.
71551808.
203961.
• WEIGHTED W.R. T.
_EO?.ULAIIOM
POPULATION)
POPULATIONI
POPULATION!
Figure 2.6-2. Sample Damage Costs Summary Output
67
-------
2.7 PROPERTY VALUE MODULE
The Property Value Module (PROP) calculates residential property
values using the Anderson-Crocker regression equation [Anderson-and Crocker,
1970]. The relation of PROP in the flow of the RAPA Cost/Benefit Model is
shown in Figure 2.7-1. This equation is a multi-linear function of the form
In (PV) = a + b In (PSN) + C In (PPT) + d In (MFI)
+ e In (DLP) + f In (OLD) + g In (NWT)
+ H In (DIS) + i In (MRM) . (2.7)
PV is the average residential property value per household in the census
tract, of which the module calculates four types:
• Type I - Median property value of owner occupied housing
(MPV) is calculated for all census tracts having more than
one person per acre (see Table B.l-1 in Appendix B for
explanation of MPV).
• Type II - Median property value of owner occupied housing
(MPV) is calculated for all census tracts having more than
one person per acre and for which single family residential
units constitute at least 75% of all housing units.
• Type III - Median gross rent of renter occupied housing (MGR)
is calculated for all census tracts having more than one per-
son per acre (see Table E.l-1 in Appendix E for explanation
of MGR).
• Type IV - Median contract rent of renter occupied housing
(MCR) is calculated for all census tracts having more than
one person per acre (see Table B.l-1 in Appendix B for
explanation of MCR).
The independent variables:
• DIS - Distance of census tract from central business district
(intersection of Pennsylvania Avenue and K Street in Washington,
D. C.).
• DLP - Number of dilapidated housing units.
• MFI - Mean family income.
68
-------
BENEFITS MODEL SEGMENT
POPULATION 1 HOUSING DATA
CENSUS
TABLES
AND MAP
MANUAL
PROCESS-
ING
CENS
TRACT ATTRI-
BUTE DATA
MPLEMENTATIQN PLANNING PROGRAM (IPP)
RECEPTOR
AIR QUALITY
DATA
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVEL
POLLUTANT CON-
CENTRATIONS)
PROPERTY VALUE MODULE
m
PROPERTY ASSIGNMENT MODULE
PROPERTY
VALUE
SUMMARY
DAMAGE COSTS MODULE
I
DAMAGE FUNCTIONS
DAMAGE
FUNCTION
PARAMETERS
COST/BENEFIT ANALYSIS
(MANUAL PHOCESSING)
Figure 2.7-1. RAPA Cost/Benefit Model; Property Value Module,
-------
• MRM - Median number of rooms in a housing unit.
• NWT - Number of housing units occupied by nonwhite.
• OLD - Number of housing units over ten years old in 1959.
are all included in the list of census tract attributes in Table B.l-1,
Appendix B. The two remaining variables in equation (2.7) are:
• PPT - Annual arithmetic mean suspended particulates, i.e.,
the particulate concentration as calculated by CONVRT
(micrograms per cubic meter).
• PSN - Annual arithmetic mean sulfation (milligrams per 100
square centimeter).
The CONVRT module supplies the annual average SO. concentration (at ground
level) in micrograms per cubic meter. Consequently, there is a need to
convert these values to the sulfation rate (made by the lead peroxide
candle or plate technique). This is accomplished through the following
relations:
Average SO Concentration (parts per million) = K x sulfation rate
(yg/100cm2)
Average S0_ Concentration (pg/m3) = 2660 x average SO- Concentration
(parts per million)
K is the sulfation rate constant. Experimental data indicates that K is a
function of temperature, humidity, other pollutants present and other factors.
However, the functional dependence is unknown. On the basis of published
data, 0.020 <_ K <_ 0.050. A commonly accepted value (used in this study) is
just the median of this range, i.e., K = 0.035.
The coefficients (a,b,c,d,e,f,g,h,i) are the regression coefficients.
These values have been determined by Anderson and Crocker for the Washington,
D.C. SMSA, the St. Louis SMSA and the Kansas City SMSA using a least squares
70
-------
regression analysis of the 1960 census data and 1967 air quality data.
This temporal mismatch is a deficiency. However, 1970 census data will not
be published for a year or so and 1960 air quality data is non-existent.
In fact, the 1967 data* is itself minimal and coarse compared to the census
tract scale. The sulfation, for example, is given in only four levels:
• <0.6 VJg/100cm2-day
• 0.6 - 1.0
• 1.1 - 1.5
• >1.5.
The baseline (Existing) conditions in the present analysis employed 1969
air quality data.
The existing version of PROP does not determine the regression coeffi-
cient independently; these must be supplied as input data. A desirable
addition to the RAPA Cost/Benefit Model at some future date would be a
Regression Analysis Module which would accept the census tract attributes
and contemporaneous (i.e., existing) air quality data and calculate the
values of the coefficients by the method of least squares.
The independent variables of equation (3.7) include only a few of the
census tract attributes listed in Table 2.3-1.
Anderson and Crocker did perform regression analyses on a number of
other potentially significant parameters, including crime rate, tax rates,
per capita school expenditures, measures of neighborhood homogeneity with
Implementation Plan for Controlling Sulfur Oxide and Particulate Air Pollu-
tants. Prepared for Health Services Administration, Department of Human
Resources, Government of District of Columbia, Contract No. 70170, TRW
Systems Group.
71
-------
respect to educational level and occupation, educational attainment measures,
population and residential unit density, proportion of units in each tract
having basements, etc. These additional variables were found not to be
statistically significant for the purposes of property value.
As might be expected, the coefficients b and c of the pollutants
were found to be negative in all cases. Consequently, the Anderson-Crocker
equation is a type of damage function for residential property values.
2.7.1 input
The input data elements required by the program are as follows:
(1) Census tract attribute deck - the only attributes read by
PROP are census tract number, POP, MIL, SFH, ALL, MPV, MGR,
MCR, MFI, DLP, OLD, NWT, and MRM.
(2) Census tract pollutant concentrations for both SO and particu-
lates, i.e., a pair of strategy/pollutant concentration decks
must be input.
(3) Sulfation factor, K (card input, format in Appendix).
(4) Four sets of regression coefficients (a,b,...,h,i) for the
Anderson-Crocker property value equation. One set is required
for each of the four types of property value (input card formats
in Appendix F).
2.7.2 Output
The output consists of three optional (surpressed through JCL) sum-
maries of:
(1) The Anderson-Crocker equations for the four property value types.
(2) Census tract attributes listed in Subsection 2.7.1 above.
(3) The SO. and particulate concentrations for each census tract,
identified by census tract number and political jurisdiction.
72
-------
The principal output consists of a tabulation of the four types of
property value, listed by census tract (identified by census tract number
and political jurisdiction). However, if a census tract does not have at
least one person per acre, it is entirely excluded from the listing. If
the remaining census tracts do not meet the criteria for any of the other
three types of property value, then a value of zero is entered for that
property value. The table also includes the values for the exposure in
units of people-micrograms per cubic meter. The exposure is given for both
S0? and particulates. As in the output of the Damage Costs Module, totals
and arithmetic averages of the exposures are given on a political jurisdic-
tion and regional basis. The average pollutant concentrations, weighted
with respect to population for each political jurisdiction and the region
are also given. In addition, political jurisdictions and regional totals
and averages of all four property values are included. A sample of this
output table is shown in Figure 2.7-2.
For Types I and II property values, the political jurisdiction weighted
averages are calculated from:
NPJ
PV. x OWN.
PV = 4^T (2.8)
.OWN
where
NPJ = number of census tracts in the political jurisdiction (for
regional averages, sums are taken over all census tracts in
the region).
OWN = number of owner occupied housing units in the census tract
(see Table B.l-1, Appendix B).
73
-------
CENSUS TRACT PROPERTY VALUE
WASHINGTON, D.C.
NUMBER
POLITICAL
JURISDICTION
355
356
357
358
359
360
361
362
363
17
364
365
366
3
273
6
6
6
6
6
6
6
6
6
POLITICAL
POLITICAL
POLITICAL
7
7
7
POLITICAL
POLITICAL
POLITICAL
REGIONAL
REGIONAL
REGIONAL
CENSUS
TRACT
12
'13
14
15
16
17
18
19
20
JURISDICTION TOTALS
JURISDICTION AVERAGES
JUR
ISDICTION AIR OUALI
1
2
3
JURISDICTION TOTALS
JURI SDICTION "AVERAGES
JURISDICTION AIR OUALI
1 U I AL 5
AVERAGES
AIR ODALinr
EXPOSURE
SULFUR
DIOXIDE
523013.
250777.
257125.
242752.
263378.
56798.
342126.
146136.
421781.
4307625.
253390.
TV 53.71
113179.
270555.
98520.
482254.
' 160751.
TY 47.33
1OU2VU464.
396668.
- "66i 73
EXPOSURE
PARTICULATES
593023.
330677.
339049.
278228.
356825.
70952.
509145.
"203895.
473076.
5159936.
303526.
64.34
134237.
319118.
116086.
569442.
189814.
55.89
421548.
70.92
PROPERTY
VALUE
TYPE 1
20350.
20286.
19766.
20565.
13912.
2C710.
17237.
17641.
21098.
129845216.
20531.
(WEIGHTED
22945.
22866.
30688.
43564656.
24887.
(WEIGHTED
PROPERTY
VALUE
TYPE 2
0.
45304.
0.
50491.
27267.
0.
0.
0.
0.
166420192.
48617.
WITH RESPECT
62874.
56494.
103063.
122922832.
70221.
WITH RESPECT
a.aZ^fel^^B. VS 1 SOU JU4U.
22365. 66579.
(WEIGHTED WITH RESPECT
GROSS
RENT
TYPE 3
78.
84.
82.
87.
60.
89.
69.
74.
7tt.
1140867.
ai.
TO POPULATION)
96.
132.
157.
14C010.
132.
TO POPULATION)
I O 38 U \i . 1
-------
For Types III and IV property values, the political jurisdiction
weighted averages are calculated from:
NPJ
/ PV x RENT.
PV = —i-i (2.9)
NPJ
RENT.
i
where
RENT = number of renter occupied housing units in the census tract
(see Table B.l-1, Appendix B).
75
-------
2.8 PROPERTY ASSIGNMENT MODULE
The Property Assignment Module (ASSIGN) determines census tract
residential property values under different conditions of ambient air
quality. The role of the Property Assignment Module in the RAPA Cost/
Benefit Model is illustrated in Figure 2.8-1. The technique developed for
the Property Assignment Module is an extension of the analysis employed in
the Property Value Module*.
Anderson considered the problem of correctly applying the Anderson-
Crocker regression equations for purposes of determining the benefits from
improved air quality resulting from a regional control strategy. He states
that, "...the appropriate course of action is to treat property values as
though they appropriately measure the net productivity of each location and
to consider the whole land market in each (location) for which benefits are
to be estimated, whether or not...ambient air concentrations change for all
locations in the land market." If a given control strategy produces no
changes in air quality for a given census tract, then (other independent
variables remaining fixed) the property values of that tract, as computed
from the Anderson-Crocker equations, will remain unchanged. Consequently,
the direct application of incremental benefits to census tracts computed
from these regression equations (i.e., from the Property Value Module),
will probably understate the benefits from improved air quality. Anderson
observes that this direct method does not account for the shifts that will
take place in housing markets and only represents "the short-term benefits"
*Based on a procedure proposed by Robert J. Anderson - Private Communication.
76
-------
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS
GROUND LEVEL
POLLUTANT CON-
CENTRATIONS)
Figure 2.8-1. RAPA Cost/Benefit Model; Property Value Assignment Module.
-------
(i.e., the benefits that result before the housing market has reached a
state of equilibrium after the improvement of air quality). Therefore, a
procedure to predict the dynamic movements in the housing market that re-
sult from improved air quality is required.
The method suggested by Anderson is an assignment technique where
the household which is the highest bidder for a property will be assigned
that property. He based his procedure on the theoretical principles
developed by Robert Lind in a paper "Land Market Equilibrium and the
Measurement of Benefit From Urban Programs," illustrates the appropriate
procedure for assigning households to properties*:
"Let the relationship between property value, p, income (I),
and pollution (s) be given by the following equation (which
is similar in form to those in Anderson-Crocker (1970)
P = I/s
and consider a land market in which there are two locations
and two households. Let the households be designated rer-
spectively as '!' and '2' and the locations designated as
'a1 and 'b'. Let the three tables below give the initial
pollution and land market equilibrium situation in this
hypothetical AQCR.
Bids
Is a b
1 6 a 1 1 6 (T)
2 10 b 2 2 © 5
Assigning unoccupied properties to the highest bidder who
does not occupy some other property, equilibrium prices
are circled.
Now consider ai> air pollution control program which lowers
the level of pollution for location 'b' to .5. The bids
and equilibrium are
Bids
a b
6 10 (20)
* Private Communication - R. J. Anderson "Comments on Estimating the
Benefits of Air Pollution Control Based On Property Value Studies of
Anderson and Crocker."
78
-------
Calculating net benefits as the sum of the differences
in net productivity for household 1 and 2 between the
two equilibria, we have
(6 - 3) + (20 - 10) = 13
Suppose we had not calculated this new equilibrium using
the assignment problem model, but had instead for each
location multiplied the change in pollution by the mar-
ginal damage reduction. Since pollution didn't change
at 'a' we would have estimated zero benefits for 'a* and
benefits of approximately 10 for 'b', or total benefits
of 10. By not allowing activities to relocate, through
the equilibrium model, so as to maximize their productivity,
we reduce estimated benefits."
Based on this simple example due to Anderson, a technique was
developed for determining "the equilibrium benefits" for the entire air
quality control region. This method is now employed in the Property
Assignment Module of the RAPA Cost/Benefit Module.
2.8.1 Determination of Equilibrium Property Values in the Property
Assignment Module
The following describes the principles employed in determining the
equilibrium property values, from the Anderson-Crocker Regression Equation
for all census tracts in a given air quality control region. However, the
description is for conceptual purposes only. Efficiency considerations of
computer storage and computation time as well as the desired form of the
output resulted in the programming of an entirely different algorithm for
the Assignment Module. This algorithm, which involves a series of sorts,
can be extracted from the F0RTRAN program listing (Appendix E).
79
-------
Consider the Anderson-Crocker Regression Equation:
In PV - a + b In (PSN) + c In (PPT) + d In (MFI)
-I- e In (DLP) + f In (OLD) + g In (NWT)
+ h In (DIS) + i In (MRM)
All the independent variables except NWT (percent of housing occupied
by nonwhites) and MFI (mean family income) are physical descriptors of the
census tract and of more less permanent structures. These descriptors
remain fixed to the census tract. MFI, on the other hand is a characteris-
tic of the residents (or households) who can move about between census
tracts (or out of the region entirely). NWT is a characteristic of the
residents to be sure, but its role is more ambiguous. It may be argued
that NWT is also a characteristic of the census tract. While NWT does
change for a given census tract, these shifts generally develop over a
longer time scale than is characteristic of the movement of individuals.
Factors such as Group Cohesiveness, valid discrimination, occupational
specialties, etc. contribute "inertia" to NWT. Consequently, for the
purposes of the present study, it has been considered as a property of the
census tracts themselves.
We next form the dummy variable, DV, given by the relation:
In (DV) = In (PV) - d In (MFI) (2.10)
DV is essentially a property of the census tracts (i.e., independent
of household).
Noting that equation (2.9) is equivalent to
DV--SL. , (2.11)
80
-------
We next form the row matrix:
by calculating DV for all N census tracts in the region, and
sorting, so that:
DV, >DV.
J- 2
DVM.
N
Similarly, we form the column vector:
(MFI y
X =
(MFI/
by calculating (MFI) for all N census tracts, and sorting,
so that:
MFI, MFI0> ... >MFIX1
12 N
The square matrix PV.. is then calculated:
DV = X x Y =
U
PVN1 PVN2
and the elements are given by:
PViJ • Xi
PV
. . . PV
IN
NN
(2.12)
(2.13)
(2.14)
(2.15)
(2.16)
(2.17)
It is clear that, the diagonal elements (i = j) represent property
values calculated from the Anderson-Crocker equation:
PVii = PVi' and that
PV > PV >...> PV . The first diagonal element PV , in fact, represents
81
-------
the value obtained from matching the highest mean family income with the
highest valued tract (i.e., highest value of DV). Similarly, the second
element PV_2 in the diagonal represents the second highest MFI in the
region combined with the second highest valued tract, etc.
These quantities represent the equilibrium property values attained
by assuming complete free mobility of households and allowing highest
incomed families to bid on the highest valued property in the marketplace
un-encumbered by other considerations.
The Assignment Module calculates the Type I property values of all
census tract based on these equilibrium conditions*. These values are
also referred to as "bids after shift." The module also calculates the
Type I property values without population shifts (i.e., the values calcu-
lated in the Property Value Module). These are also referred to as "bids
before shift."
2.8.2 Input
The input data required by the Assignment Module consists of the
following:
(1) Census tract attributes (card deck). As in the other
modules, only specific attributes are read into core;
these are census tract numbers, POP, MIL, MPV, MFI,
DLP, OLD, NVT, DIS, MRH.
(2) The sulfation factor K (card format identical with
format for Property Value Module).
(3) Complete set of Type I regression coefficients (card
format identical with format for Property Value Module).
(4) Two census tract pollutant concentration card decks (i.e.,
a pair of SO and Particulate Strategies).
*The algorithm used here needs further work; see cautionary note in Section 3.3.
82
-------
2,8.3 Output
The output of the Assignment Module consists of a series of tabulated
summaries. These include the optional input data summaries:
(1) The Type I Anderson-Crocker Regression Equation
and coefficients.
(2) The listing of census tract attributes used by the
module, identified by census tract number.
(3) The census tract pollutant concentrations for SO
and particulates, identified by census tract number
and political .jurisdiction.
The principal output, however, is a tabulated list of property values
identified by census tract (census tract number and political jurisdiction).
These property values are:
(a) The median property value (MPV) for the census
tract as provided in the census data (in dollars).
(b) The property value bid before shift (i.e,, Type I
property value as calculated in PROP) in dollars.
(c) The property bid after shift (i.e., the equilibrium
value) in dollars.
(d) The difference in property value bid (bid after
shift - bid before shift) in dollars.
In addition, there are totals and averages for each of the four
property value outputs. These are provided in both a political jurisdiction
and regional basis. A sample of this output table is provided in Figure
2.8-2.
83
-------
CENSUS TRACT PROPER!V VALUE BIDS
00
WASHINGTON, C.C.
NUMBER
257
258
259
260
261
262
263
264
265
266
267
263
269
270
17
271
272
275
3
273
POLITICAL
JURISDICTION
6
6
6
6
6
6
6
6
6
6
6
6
6
b
POLITICAL JURISDICTION
POLITICAL JURISDICTION
7
7
7
POLITICAL JURISDICTION
POLITICAL JURISDICTION
REGIONAL TOTALS
REGIONAL AVERAGES
CENSUS
TRACT
6
7
a
9
11
12
13
14
15
16
17
13
19
20
TOTALS
AVERAGES
1
2
1
TOTALS
AVERAGES
MEDIAN
PROPERTY
VALUE
15899.
11396.
22093.
23295.
23295.
12900.
12695.
14300.
16301.
11204.
23295.
13*94.
14003.
16899.
1C1321712.
16100.
18306.
18106.
26108.
35373824.
20208.
4171012416.
17506.
PROPERTY
VALUE
BIO
BEFORE
SHIFT
20971.
17119.
20628.
28263.
22067.
20350.
20286.
19766.
20565.
13912.
20710.
17237.
17641.
21098.
129845216.
20531.
22945.
22866.
30686.
43564656.
24887.
532946124B.
22365.
PROPERTY
VALUE
BID
AFTER
SHIFT
19081.
22830.
22138.
19839.
22220.
21590.
20983.
18588.
11519.
28321 .
19808.
24651.
24353.
24713.
138932352.
2 1968.
14677.
23507.
23747.
3632 1904.
21035.
4879036416.
• 2047S.
DIFFERENCE
IN
PROPERTY
VALUE
BID
-1890.
5711.
1510.
-8424.
153.
1239.
697.
-1177.
-9046.
1441U.
-902.
7414.
6712.
3615.
9087147.
1437.
-8268.
641.
-6941.
-6742747.
-3852.
-450462720.
-1890.
Figure 2.8-2. Sample Output, Assignment Module.
-------
2.9 PROPOSED MODEL ADDITIONS
Experience with the Benefits Model Segment of the RAPA Cost/Benefit
Model has already suggested desirable model additions for the future. The
highest priority should be given to modifying the program to accept NTIS
magnetic tapes.
These tapes offer the same advantage as the census tables, i.e.,
standardized formats, reliable data, completeness, and consistency between
tapes. However, there is the similar problem of preliminary data reduction
to obtain the information in the form of the census tract attributes listed
in Table B.l-1, Appendix B. However, the data reduction could easily be
performed automatically with development of an additional module for the
RAPA Cost/Benefit Model. An additional disadvantage, however, is that
tapes have been produced according to standard location areas and not
standard mean statistical areas. Consequently, to compile complete infor-
mation for the Washington, D. C. SMSA, for example, would require the
acquisition of three NTIS tape reels (PB-170-773, PB-170-779 and PB-170-781)
Nevertheless, it is now felt that the advantages here outweigh the disad-
vantages and that the additional module for the RAPA Cost/Benefit Model
should be developed to read NTIS tapes and perform preliminary data pro-
cessing, if any extensive application of the model beyond the present study
is contemplated.
85
-------
3.0 MODEL DEMONSTRATION
The National Capital Interstate Air Quality Control Region (NCIAQCR)
was selected for the demonstration because of the availability of control
strategy analysis results from IPP. As has been described in Section 2.0,
both IPP and the Benefits Model Segment must be run to provide the basis
for a cost/benefit analysis; control costs and air quality estimates come
from IPP, and the benefits, measured in dollars, come from the Benefits
Model Segment.
In the sections below, the census tract and pollutant concentration
data inputs to the Benefits Model Segment which were used in the demonstra-
tion are described in detail. The resulting outputs, which describe the
direct damage costs, the property value impacts and the property value im-
pacts with market adjustments*, are also described. The interpretation of
these results is currently underway and will be the subject of a forthcoming
Office of Air Programs report.
3.1 INPUT DATA FOR THE NCIAQCR DEMONSTRATION
The inputs which are common to all three modules in the Benefits Model
Segment are described below; those which are specific to a given module are
described in subsequent sections, i.e., the damage function inputs are dis-
cussed in Section 3.2, Estimation of Direct Damage Costs, and the property
value inputs (regression coefficients) are descussed in Section 3.3,
Estimation of Property Value Effects.
*
As a result of looking at Assignment Model results which were contrary to
what was expected, it was realized that an important capability, i.e., that
of accounting for the variation in the number of owner occupied dwellings
from one census tract to another, has been omitted from the model. This
capability is currently being incorporated into the model.
87
-------
3.1.1 Census Data
The population and housing data for the Washington, D. C. SMSA was
based on the 1960 Decennial Census of Population and Housing. The primary
source was a magnetic tape prepared as a part of the research described by
Anderson and Crocker [1970]. However, certain additions and modifications
to these data were made, based on the printed census tables published by
the Bureau of the Census [I960]. Figure 3.1-1 presents the complete list of
census attributes employed in this study for all 366 census tracts of the
Washington, D. C. SMSA (these attributes were defined in Chapter 2.0).
Those census tracts for which only population is listed (second column)
were input to the DAMAGE Module only, i.e., they failed one or both of the
V
tests which must be passed before a census tract is used as input to the
Property Value or Assignment Module.
3.1.2 Pollutant Concentration/Strategy Data
A total of ten strategies were tested in the NCIAQCR cost/benefit
demonstration. Half of these applied to the control of particulate emis-
sions and half applied to the control of sulfur dioxide emissions. The
pollutant concentration data corresponding to these strategies were origi-
nally produced using the prototype version of the Implementation Planning
Program (Appendix A) for the Implementation Plan prepared by TRW for the
Washington, D. C. Region [TRW, August 1970].
The strategies selected for comparison were:
Particulate Strategies
• Existing Particulates (1970) Air Quality data for particulates
under existing conditions throughout the region. The ground
level particulate concentration isopleths for this situation
are shown in Figure 3.1-2. This provides the baseline for
particulate strategies.
88
-------
TRtfT ATTRIBUTED INPUT
OO
VO
CENSUS
THACT
VIIMUFR
O001
0002
OOOl
0004
OOO5
0006
OOO7
00 OH
OOOQ
0010
OO 1 1
0012
no i <
0014
OO15
0016
O017
00 M
O019
0020
OO'l
0022
Oi)'30OI
0023002
Q074
0025
OO7<>
0027
002'
on 10
0031
OO37
0033
on 14
0035
O1 16
0037
O031
00 !••
0041
O042
0043
DO 44
0045
0047
TOTAL
POPULATION
5963.
5723.
6412.
1280.
77B5.
5486. .
BS44.
6235.
6715.
11696.
5203.
5213.
7BO1-
6549.
6177.
5458.
5B77.
92S4.
8536.
7525.
13753.
9471..
2134.
5497.
9710.
2732.
11556.
7O17.
5R31.
4517.
4163.
66OR.
9490.
6RS4.
2628.
4477.
6304.
5177.
5324.
76OI.
3430.
•901B.
4532.
3711.
2450.
6719- '
6400.
AREA IN
SQUARE
M II Ft
0.
0.
301.
0.
0.
320.
717.
0.
O.
819.
41O.
352.
n.
352.
0.
0.
4O1.
582.
357.
467.
29«.
295.
17'.
0.
179.
295.
0.
179.
177.
122.
64.
64.
179.
179.
357.
186.
177.
128.
178.
128.
1 R6.
0. .
243.
58.
5R.
64.
1 1 5.
109.
S 1 NCI F
FAMILY
HOUSING
0.
0.
1419.
0.
O.
1001.
788.
0.
O.
2317.
I11O.
968.
o.
1592.
0.
0.
1773.
838.
2O74.
1251.
7193.
1912.
BOB.
0.
1094.
1541.
O.
1905.
B97.
1157.
107.
734.
1717.
1316.
917.
410.
519.
115.
176.
164.
40B.
0.
641.
441.
710.
392.
646.
654.
ALL
HOUSING
UNI Tt
0.
0.
2555.
0.
O-
2262.
493O.
0.
O.
5497.
1747.
2208.
n.
2424.
O.
0.
2086.
3663.
2492.
2533.
4418.
2821.
171Q.
0.
1491.
2940.
O.
5070.
1368.
1959.
I77B.
1256.
1779.
2579.
1686.
838.
7718.
3422.
2468.
2B93.
3H1 7.
0.
4020.
2137.
1746.
761.
1644.
1865.
MEDIAN MEDIAN
PROPERTY
UAI IIF
0.
0.
17801 .
0.
O.
23202.
20090.
0.
0.
23506.
777
-------
CENSUS TRACT ATTRIBUTFS — INPUT
WASHINGTON. P.C.
CENSUS
TOTAL
ABC 4 IN SINGLE
THACT
N1IH9ER
POPULATION
SQUARE
MILES
FAMILY HOUSING
HOUSING UNITS
MEDIAN MEDIAN MEDIAN MEDIAN DILAPIDATED HOUSING NONHHITE DISTANCE HFIIAN.
PROPERTY
VALUE
CROSS CONTRACT
RENT RENT
FAMILY
INCOME
HOUSING
UNI TS
OVER 10 OCCUPIED BUSINESS ROO^S IN
YEARS OLD HJUSlNf. UlStPICT MMUSIHC
0048
0049
0050
0051
005*001
0052002
0051001
0053002
0054001
0054002
0055
0054
0057001
0057002
oosq
005^
0360 .
0061
006'
0063
0064
0065
0066
0067
0064
0069
0070
0071
007?
0073001
037*00;
007300J
0371004
0073005
0071006
0073007
0073001
O074ooi
0374302
0074001
037S
0076001
007600?
0076003
OJ770O1
0077002
0'177OO3
0077004
8485.
9000.
9234.
2*51.
6033.
1291.
' 5896.
1022.
2624.
fl31.
6180.
3797.
5378.
1404.
1499.
1870.
16°9.
60.
99.
2360.
3262. .
4732.
3005.
6850.
10199.
4R95.
5973.
4028.
5552.
4813.
. S.545,
4433.
5761 .
9045.
6649.
6374.
1044.
63'>3.
SI"?.
12592.
"265.
5931.
t>5t>l).
5340.
6217.
6235.
6419.
11396.
186.
115.
115.
0.
115.
0.
59.
0.
0.
0.
m.
160.
173.
0.
O.
0.
O.
O.
0.
0.
173.
179.
5n.
122.
339.
122.
115.
115.
282.
1453.
0.
28?.
394.
263.
173.
410.
0.
358.
299.
299.
275.
237.
b97.
173.
634.
1862.
5H2.
403.
1171.
926.
442.
0.
341.
0.
871.
0.
0.
0.
70O.
472.
218.
0.
0.
0.
0.
0.
0.
0.
452.
622.
417.
1043.
1196.
848.
885.
694.
556.
730.
0.
383.
30?.
706.
248.
512;
0.
584.
796.
4?2.
1123.
998.
9(.9.
721.
471..
1477.
352.
1723.
2399.
2954.
4064.
0.
3109.
0.
3839.
0.
0.
0.
3594.
2385.
3338.
0.
0.
0.
0.
0.
0.
0.
1004.
2055.
1342.
2026.
2251.
1261.
1641.
1126.
1415.
735.
0.
1662.
1687.
2530.
2411.
2387.
0.
1199.
1720.
3572.
3087.
2219.
2502.
2260.
2419.
1914.
7O1 8.
3178.
12100.
12296.
14003.
0.
13200.
0.
11696.
0.
0.
0.
19594.
21590.
22994.
0.
0.
0.
O.
0.
0.
0.
7303.
14898.
17908.
12900.
12900.
11696.
11696.
11499.
9799.
13200.
0.
12900.
13095.
12900.
12796.
13095.
0.
11696.
12296.
12394.
I IhQh.
12797.
15804.
19693.
12797.
14501.
12695.
13306.
69.
66.
65.
0.
74.
0.
76.
0.
0.
0.
74.
101.
79.
0.
0.
0.
0.
0.
0.
0.
64.
81.
69.
78.
76.
83.
71.
85.
61.
57.
0.
79.
91.
as.
87.
80.
0.
73.
91.
81.
91.
76.
93.
87.
77.
84.
77.
78.
60.
58.
60.
0.
71.
0.
71.
0.
0.
0.
68.
99.
77.
0.
0.
0.
0.
0.
O.
0.
54.
72.
64.
65.
64.
64.
62.
67.
55.
57.
0.
77.
89.
84.
86.
79.
0.
64.
73.
78.
74.
65.
78.
64.
69.
77.
74.
76.
3200.
3474.
3467.
I.
4163.
1.
5187.
1.
1.
1.
48O3.
78S6.
7R95.
•
•
•
2913.
5791.
53BR.
47B4.
5115.
4460.
4717.
4732.
2999.
5250.
1.
6136.
5745.
5100.
6387.
6477.
1.
3429.
5740.
5213.
5SHQ.
6464.
777B.
7959.
5796.
7990.
5779.
5687.
340.
102.
26.
1.
2 !
96.
47.
88.
*
•
•
•
35.
176.
3.
85.
31.
77.
126.
72.
81.
1.
1.
12.
71.
1.
1.
1.
1.
10.
3.
3.
84.
43.
? .
1.
5.
I.
1 .
8.
2292.
2925.
3855.
1.
3100.
1.
3429.
1.
I.
1.
3255.
1043.
3087.
1.
1.
1.
1.
1.
1.
1.
793.
1792.
12 77.
1984.
2135.
1248.
1561.
948.
795.
673.
1 .
1255.
922.
1199.
1697.
2122.
1.
874.
1105.
1119.
2373.
7019.
20t>5.
2120.
2156.
1498.
148h.
1912.
2213.
2657.
2485.
1 .
1232.
1.
663.
1.
1.
1.
683.
221.
94.
1.
1.
1 .
1 .
1 .
1.
929.
591 .
201.
1128.
1651.
H74.
974.
636.
1259.
78.
1.
42.
159.
434.
48.
31.
1.
1140.
U04.
3470.
772.
23.
17.
6.
339.
325.
R5O.
2861.
1.5
1 .5
2 .0
1.0
2.0
1.0
2.5
1.0
1.0
1.0
2 .5
3.0
2.5
.0
.0
.0
.0
. <_'
.0
.0
.5
0.5
0. 1
0.5
1.5
1 .0
0.5
1.0
1 .0
3.5
.1.0
3.5
3.0
4.0
4.O
4.5
1.0
l.b
2.0
3.0
2. '.
7.O
2. r>
3.0
2.0
3.0
3.O
3.5
?• T
7. 8
2. 3
1 .0
2. 3
1.0
2. 1
1.0
(.0
1.0
2. 1
7.7
2. 1
1.0
1.0
1.0
1. .3
1.0
1. '1
1. 'I
3.5
3s 3
3. 3
4. 4
4.4
5. 1
4.«,
'. . 7
4.3
<• . •)
1.0 .
1. 0
4.0
4.0
3. 4
3. 7
1.0
4. 1
4 . C
1. J
4. 'j
4. )
4. 4
4. 1
3.9
5. 7
4.0
4. (,
Figure 3.1-1. List of Census Tract Attributes for the Washington, D. C. SMSA (Cont'd)
-------
CFMSIIC TRACT ATTRIBUTES
INPUT
MASH, | NGTOCl . D.C.
CENSUS
TRACT
N'IMIFR
0077005
007POOI
0078 J32
OJ73003
OQ7R104
0078005
007R006
0079
n'lBo
0031
Oil 33
OJR4
0095
O IRS
OJ87
nnflqnni
OJ9R002
on 3?
0090
OO9I
0092
nr»o3
0094
009500?
0095004
DO 96
MICOJOI
M3COOO2
MUC0003
MQCOOO4
HQC0005
MOC0007
Miro.ion
"HC0009
_._1XOOLlQ_
HJCOOll
MWOOI 7A
*OC0012B
M3COO13
MOCOOI4
MC0015
•OC0016
M3COOI7
MIC 00 IB
TOTAL
POPULATION
6336.
Sill.
6654.
6027.
4736.
8233.
IOO57.
9557.
12185.
5597.
421R.
9R37.
7563.
7073.
37R2.
7201.
7495.
7631.
10732.
2387.
9711.
8055.
7654.
6015.
39SO.
7832.
4596.
10520.
7441.
2133.
4487.
3137.
7071.
1920.
3576.
4425.
4337.
5896.
6641.
13535.
R743.
3063.
S319.
6748.
9367.
5791.
77OR.
3839.
AftFA IN
SQUARE
Mil FS
237.
871.
525.
295.
179..
295.
474.
410.
166.
115.
179.
179.
115.
122.
741-
237.
461.
115.
1805.
2444.
7779.
346.
4in.
723.
461.
467.
410.
640.
O.
0.
27182.
34108.
75167.
0.
73O47.
1671.
30251.
1671.
2707.
1152.
5741.
13702.
27127.
29269.
7371.
704.
346.
231.
SINGLE
FAMILY
HOUSING
1149.
339.
1367.
820.
556.
1327.
1584.
1360.
1679.
727.
592.
1772.
1 199.
1174.
4P3.
1001.
401.
1234.
926.
494.
• 1494.
1079.
1475.
1542.
775.
1646.
1179.
2359.
O.
0.
1 192.
737.
557.
0.
937.
809.
i ion.
1193.
1232.
3143.
7O57.
824.
1353.
1806.
2345.
767.
659.
794.
ALL
HOUSING
UNI TS
1466.
1858.
1908.
1730.
11O7.
2338.
7374.
2785.
3O59.
1588.
2OIO.
2647.
7nnfl.
1669.
R9H.
1935.
71 97.
2141.
7443.
513.
2963.
2253.
7387.
1727.
I7R9.
2231.
1182.
3100.
0.
0.
I77O.
807.
557.
0.
937.
1266.
1140.
1460.
1924.
3153.
7345.
830.
1442.
1846.
2352.
1495.
79(14.
1235.
MEDIAN
PROPERTY
VAI UF
13004.
15199.
12594.
12296.
I4O03.
10797.
1 1B97.
13306.
17494.
12900.
I649R.
12100.
17100.
12296.
11696.
12797.
I779A.
13200.
12594.
13698.
14200.
13004.
I50O3.
16399.
I 44 OO.
14300.
17292.
16399.
0.
0.
172O6.
15306.
11802.
0.
137OO.
16597.
14501 .
13602.
17O01 .
14400.
1 7998.
24909.
19706.
21290.
28001.
18602.
153ft6.
16204.
MEOI AN
GROSS
RFNT
79.
75.
79.
79.
66.
85.
R2.
78.
7H.
73.
73.
77.
77.
80.
75.
84.
77.
78.
75.
I.
82.
78.
9O.
94.
RA.
79.
1.
104.
O.
0.
82.
64.
1.
0.
89.
76.
91.
96.
141.
136.
1.
83.
85.
1.
111.
R9.
95.
MEDIAN
CONTRACT
RFNT
66.
70.
66.
64.
56.
72.
66.
64.
63 .
65.
67.
67.
AA.
65.
6O.
74.
Al .
63.
AA.
I.
75.
70.
R3.
84.
82.
68.
9R.
0.
0.
6O.
45.
1.
0.
1 „
81.
55.
75.
107.
K37.
1.
66.
59.
1 .
110.
flA.
92.
MEU1AN
FAMILY
INCOMF
5151..
3936.
6595.
4569.
4537.
5345.
437O.
4717.
4005.
4760.
6051.
4573.
4777.
4694.
3519.
5172.
457R.
4994.
4944.
6621.
6614.
6342.
7O52.
8039.
67O1.
7692.
9721.
8193.
1 .
I.
6285.
5519.
5O49.
1.
5949.
6775.
5547.
6336.
7518.
8071.
RR04.
7919.
7646.
8095.
11 743.
8527.
6438.
8250.
Oil APIOATEO
HOUSING
UNITS
15.
6.
3.
26.
IO.
50.
1 1 .
86.
45.
34.
77.'
148.
77.
21.
246.
12.
40.
8.
2.
13.
24.
7.
4.
1.
14.
1 .
2.
1.
1.
64.
69.
13.
1.
105.
25.
R4.
56.
7H.
1.
14.
80.
99.
116.
76.
1.
44.
14.
HOUSING
OVER 10
YFARS ni n
978.
1284.
1671.
1373.
971 .
1722.
171 1.
2703.
2037.
1552.
1945.
2594.
1945.
1666.
HR7.
1845.
IR95.
209R.
3359.
490.
2746.
2057.
1903.
1558.
- n
6. 1
5.9
5. R
6.8
4.9
4. n
5. 6
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
vO
WASHINGTON
CFNSUS
. o.c.
TOTAL
AREA IN
TBACT POPULATION SQUARE
NJM3ER MILES
MOC0019
fOC0020
•oroo2i
"QC0022
"1C0023
MOC0074
•OrOIZS
••1COO 26
"1C0027
MOC0029
•OC0079
"or.0030
•OC0031
M1C0032
"OC0135
MDC0036
MOC0037
•1C0039
Micor>39
H-K004J
"•ic on 41
HQC0042
•OC0043
MOC0044
HOC0.146
M1CO047
M1C0049
MQC0050
MOC0351
MOCOOS2
MncooS3
MOC0055
-3C01S6
••1^0057
MIC o.i S3
"1C0360
POCOJ02
PSCOJO3
Pit 0,1 J5
PiCOOOa
3328.
4741.
6621.
6*42.
6748.
1639.
5932.
4443.
3443.
5090.
3645.
5141.
12003.
9797.
16334.
8955.
7927.
8796.
1220.
8275.-
5826.
4732.
2175.
S282.
. 6498.
9711.
4564.
4416.
6792.
1103.
4320.
4895.
4008.
2405.
3456.
4176.
4198.
7523.
9897.
4?47.
..8502. .
2700.
679.
5967.
10J1.
3304.
0.
141.
697.
237.
359.
467.
0.
0.
410.
320.
359.
979.
0.
1590.
\ 793.
1569.
599.
410.
353.
1228.
576.
1 107.
295.
416.
• 2369.
1050.
960.
320.
352.
0.
448.
64O.
410.
0.
449.
1152.
352.
0.
1 727.
3449.
0.
109S.
8931.
O.
29387.
n.
21403.
SINGLE
FAMILY
HOUSING
• 0.
641.
1599.
1327.
775.
1572.
0.
0.
1033.
996.
1466.
1002.
1325.
0.
3905.
2742.
1974.
2217.
253.
7092.
1268.
1232.
520.
1391.
1557.
7460.
1379.
1799.
551.
0.
1302.
1319.
1138.
0.
994.
1128.
1337.
0.
M06.
2700.
0.
699.
O.
1435.
0.
735.
ALL MEDIAN MEDIAN
HOUSING PROPERTY
UNITS VALUE
0.
1407.
1949.
2373.
2143.
0.
0.
1430.
996.
1504.
1014.
1375.
0.
2160.
. 3905.
2746.
7061.
2217.
355.
2096.
1732.
1738.
597.
1391.
1830.
2460.
1329.
1373.
2916.
0.
1318.
. 1457.
1138.
0.
.999.
1147.
1346.
0.
153S.
77OO.
0.
2902.
721.
O.
1460.
O.
798.
0.
17206.
19990.
19303.
18602.
18602.
0.
0.
22100.
19303.
76713.
18996.
17B01.
0.
17706.
17001.
13700.
17103.
15199.
18106.
19398.
18106.
31414.
18996.
18807.
27500.
22607.
72607.
78710.
21205.
0.
19092.
29792.
31288.
0.
26213.
33300.
23110.
0.
31508.
0.
14601.
16301.
0.
15199.
0.
13200.
MEDIAN
GROSS CONTRACT
RENT RENT
0.
97.
130.
1.
103.
127.
0.
0.
137.
1.
1.
I.
1.
0.
1.
148.
113.
1.
1.
1.
1.
109.
1.
1.
I.
169.
1.
1.
1.
105.
0.
154.
197.
0.
1.
0.
1.
0.
105.
1.
0.
105.
1.
O.
76.
O.
62.
0.
93.
10B.
1.
96.
121.
0.
0.
132.
1.
1.
1.
1.
0.
1.
116.
87.
•
•
10 .
*
14 .
• •
101.
0.
127.
150.
1.
0.
1.
0.
1.
0.
9<».
0.
91.
1.
O.
57.
O.
45.
MEDIAN
FAMILY
INCOME
1.
7793.
10322.
10384.
8160.
9500.
1.
1.
11004.
10107.
12607.
10158.
9054.
1.
8300.
9136.
7731.
8596.
8544.
7739.
9750.
9756.
12913.
10457.
9077.
12052.
10894.
12113.
13657.
7966.
1.
9927.
13684.
14429.
1.
13521.
17275.
11778.
9 '60.
14115.
1.
610h.
7016.
1.
7339.
5298.
DILAPIDATED HOUSING
HOUSING
UNITS
,
1.
100007.
1.
1.
3.
1.
1.
42.
4.
1.
1.
1.
1.
1.
1.
48.
6.
2.
1.
15.
1.
16.
1.
1.
1.
1.
1.
2.
19.
1.
3.
•
•
3.
1.
42.
5.
1.
64.
73.
1.
80.
1.
54.
NUNWHI TE
OVER 10 OCCUPIED
YEARS OLD HOUSING
1.
481.
917.
1100.
1075.
1447.
1.
369.
732.
036.
657.
467.
I.
9.
267.
939.
737.
889.
122.
792.
902.
502.
405.
397.
327.
559.
873.
1026.
1741.
1.
1111.
697.
692.
964.
638.
11 29.
1.
«60.
519.
1.
141?.
368.
1.
805.
1 .
558.
1 .
5.
9.
2.
16.
15.
1.
77.
6.
a.
2.
9.
1.
7.
19.
113.
12.
12.
5.
36.
14.
18.
1.
1.
17.
16.
4.
5.
50.
1.
37.
14.
11 .
1 .
7.
27.
5.
1 .
55.
16.
I.
101 .
41 .
1.
795.
1 .
279.
DISTANCE
BUSINESS f
ni STRICT
1 .0
7.5
8.5
8.5
H.O
7.0
1.0
1.0
7.5
9.0
g.O
6.5
9.0
1.0
13.0
12.0
11.0
10.5
11.0
10.0
9.5
9.5
9.0
10.0
10.0
10.0
10.5
9.5
B.5
9.0
1.0
8.5
8.0
7.0
1 .0
7.5
3.0
0.5
1 . O
20. S
1.0
18.0
1. O
19.0
q
1-DI A'«
fl.J-'S IN
HTJS INC
4.4
4. 0
5.7
1. 0
1.3
5. a
6. 3
6. 7
b. i
S. 1
1. J
5 '.9
5. 3
5.9
5.7
5. 1
5.S
7. 1
6. 1
6. 1
6.6
t. 4
7. 3
I:':
s.o
7. O
7.4
1 . O
7. 3
7.5
»>. 1
1 . '1
s. r
T.'j
i . i
4.4
5. ?
1.0
S . ',
i . n
5. 1
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
TBACT ATTRIBUTES — INPUT
\O
OJ
WASHINGTON, n.f.
CENSUS
TnTAI
AH FA IN
TRACT POPULATION SQUARE
NUMBER MII FS
PGCOOO7'
PCC0009
PGC0009
PGC0010
p^.rooi i
PGC0012
PSC0011
P3C0014
pGcooi5
PGC0016
P-.COOl 7
PGC0019
PGC0019
P3C0020
pr.ron?!
PSC0022
P-.COO71
PGC0024
PGCOO25
P."C0026
PGC0027
PGC002S
PGCO029
PC. coo 30
PGC0031
p-;coo3>
p.-,<-oo 11
P3C0034
or.mnis
BGCOOli
PilCJ017
PGC0038
p-.roa 19
PGC0040
pr.roo4i
PGC0042
pcroo4i
P'iC0044
P1CJ045
P6COJ4e>
p-,r:v>4T
PGC0043
occi)049
P3C0050
_£CCOQ51
P'iCOJ52
P'.ronsi
PGCOOS4
1
2B4T.
1910.
161B.
4708.
1966.
8848.
7503.
9710.
1573.
4018.
6754.
11891.
9386.
4142.
4167.
5245.
75'S.
4974.
5009.
12S8.
4529.
4798.
5167.
4510.
4798.
2535.
3548.
5405.
7704.
124*4.
1271.
5569.
1673.
3103.
1HI6.
4910.
1H/.7.
2873.
. S64.»__
16-»2.
4610.
5223.
73S7.
5620.
4652.
5941.
7S1S.
2718.
21021.
0.
0.
372B3.
0.
13647.
• 53546.
10544.
256.
0.
344'4.
1280.
4892.
614.
1985.
2687.
544.
1856. .
557.
237.
295.
3617.
444.
410.
525.
0.
614.
604.
1S710.
7490.
32O.
640.
79S.
640.
677.
416.
17HO.
640.
0.
237.
75S.
0.
241.
480.
170.
416.
75O.
224.
SINC.I f
Al 1
FAMILY HOUSING
HOUSING UNI TS
636.
0.
O.
1021.
O.
2319.
1917.
2543.
897.
0. '
17O6.
3252.
2217.
305.
II IO.
12R9.
11 19.
1162.
' 968.
666.
1103.
1157.
»8O.
954.
721.
0.
7B9.
609.
S79.
3402.
796.
1384.
847.
647.
967.
1310.
564.
710.
0.
650.
1O75.
0.
577.
686.
574.
1189.
547.
626.
673.
0.
0.
1090.
O.
2373.
1984.
2579.
9O5.
0.
1715.
3816.
785R.
1488.
1 1 60.
1299.
70R4.
1360.. .
1596.
891.
1710.
1198.
15O3.
1030.
1O67.
0.
913.
1309.
6O7.
3415.
796.
1410.
993.
903.
967.
1319.
1 1 S7-
901.
0..
1131.
I4RS.
0.
54O.
1633.
IS75.
2010.
7*n.
B69.
MFnlAN MEDIAN
PROPERTY
WAI IIP
12797.
0.
O.
12296.
Q.
15994.
14400.
16204.
16199.
0.
I7&O&.
16B99.
1B19B.
15600.
1 HI Oh.
14603.
17001 .
14501.
142OO.
10405.
11204.
13400.
12695 .
10700.
118O7.
0.
11603.
11499.
9107.
16107.
11106.
15093.
145OI .
14101.
I4h01.
18695.
14100.
11305.
O.
11802.
1 1 R97.
0.
1799B.
17606.
I3O95.
15693.
159«Y. .
19206.
HFDI AN
GROSS CONTRACT
RFNT RFNT
1.
0.
0.
60.
O.
100.
9O.
118.
0.
1 .
. 103.
IO1.
85.
1.
1.
an.
92.
89.
93.
97.
1.
81.
75.
70.
0.
103.
1.
1 .
1.
1.
1.
91.
91.
1.
1.
Rfl.
83.
O.
88.
HI.
0.
1.
83.
85.
110.
1 .
96.
' 1.
0.
0.
48.
O.
78.
66.
86.
1.
0.
1 .
84.
91.
82.
1 .
1.
RR.
88.
B7.
84.
69.
1.
87.
53.
67.
0.
1O3.
•
•
9 .
8 .
»
7fc.
71.
0.
85.
77.
0.
82.
R5.
107.
1 .
92.
MFDIAN DM API DATED
FAMILY
INCOME
575O.
1.
1.
6708.
1 .
7801.
6714.
7943.
• B964.
1.
8519.
8201.
H071 .
56B7.
7716.
6891.
7fcft7.
7662.
7OS7.
5997.
6755.
6628.
6155.
4465.
5378.
1.
6967.
6802.
5591.
8226.
7966.
7856.
7B95.
7639.
7SR6.
11004.
7087.
6555.
1 .
6940.
7017.
1.
9674.
6953.
6H50.
8417.
71AI .
8630.
HOUSING
IINITI
53.
1.
1.
116.
128.
172.
60.
1.
1.
17.
3.
so.
10.
17.
55.
1 .
42.
16.
19.
88.
39.
18.
175.
31.
1.
12.
5.
175.
105.
1.
1.
5.
25.
4.
23.
1 1 .
9.
1.
15.
19.
1.
1.
4.
10.
1.
mi; si NT.
OVER 10
VFAR <; ni n
197.
1.
1.
644.
917.
932.
536.
797.
1.
4 70.
659.
1 1 9h.
1330.
191.
424.
hS5.
655.
11 14.
716.
937.
639.
59'.
763.
676.
1.
1 71.
16.
451.
946.
610.
232.
548.
754.
174.
870.
61 7.
H53.
1.
1000.
1400.
1.
47X.
1092.
191.
867.
f.00.
487.
NJNWHITF DISTANT": HFDIAN
OCCUPIED BUSINESS «03^S IN
HOIK 1 MT. DISTRICT HnilSlwr.
. 7O1.
1.
1.
327.
1 .
143.
70R.
127.
h.
1.
19.
15.
44.
8.
17.
142.
1 1 .
120.
1 1.
4.
77.
63.
112.
984.
1O27.
1 .
7.
5.
14R.
317.
R.
4.
5.
31 .
7.
30.
fll .
2.
1 .
6.
9.
1.
2.
1 I.
12.
17 -
6.
16. O
1.0
1.0
18.0
l.O
13.0
1 >.0
a.o
b.O
l.O
b.U
4.5
IS. S
6.0
7.O
H.U
6.S
4.0
4.0
4.U
.'.5 ..
6.b
5.5
5.i
5.0
1.0
6.5
7.5
1 J.'j
13.0
7.5
7.5
6.5
5.5
ft.S
5.5
5.0
4.5
1.0
S.O
5.5
.5.5 . . .
5.b
/,_•;
7.U
5.7
1. 0
1.0
5.4
1 . 0
5.6
5.7
5.6
5. 7
1.0
5.T
5.5
S. 5
3. 5
5.9
5.2
4.7
5.2
4.fc
4. 3
5. 1
5. 1
4.4
5.b
4.4
1 .0
5.5
5. 1
5. t
5. 7
5. 7
5. 3
5. 1
5.5
5. 1
6. ?
4. 4
5. >
..l.'J .
4 . t:
',.7
1 .n
.6.1. .
4. 1
'l . 1 . ...
4. 9
5. 7
5. 7
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
TRAfT ATTRIBUTES —
WASHINGTON. D.C.
CENSUS
TOTAL
AREA IN SINGLE
ALL
MEDIAN MEDIAN MEDIAN MEDIAN DILAPIDATED HOUSING NDNWHI TE DISTANCE M£0|AN
TRACT
NUMBER
POPULATION
SQUARE
MILES
FAMILY
HOUSING
HOUSING
LIMITS
PROPERTY GROSS CONTRACT
VALUE RSNT RENT
FAMILY
INCOME
HOUSING
UNITS
OVER 10 OCCUPIED BUSINESS ROOKS IN
YEARS OLO HOUSINC DISTRICT HOUSING
PGC0055
PGC0056
PGC0057
PGC005R
PGCO059
PGC0060
PGC0061
PGC.0062
PIC0063
PGC0064
PGCOCJ6S
P3C0066
PGC006T
PGCOO&d
PSC0069
PGC0370
PGC0071
PGC0072
PTC0073
pr,c.0374
a^LOOOl
A4L0002
AHL0003
A3L0004
Alt 00 OS
A126.
4222.
2993.
3053.
4474.
8333.
7716.
2419. .
4142.
4722.
9192.
3741.
3*9.
8409.
5415.
6569.
6045.
3093.
3917.
27'9.
5177.
1608.
5198.
3656.
4999.
3533.
7094.
3456.
5009.
5319.
7369.
71ST.
2925.
6470.
1910.
3005.
4447.
3968.
3041.
2937.
3594. '
4376.
295.
0.
320.
614.
1537.
224.
256.
352.
410.
352.
1024.
1312.
6914.
416.
307.
992.
819.
0.
6281.
1R626. •
557.
845.
0.
0.
' 467.
237.
346.
122.
378.
263.
499.
352.
576.
314.
444.
410.
256.
410.
263.
224.
717.
173.
461.
173.
237.
173.
IIS.
493.
625.
0.
905.
1708.
988.
907.
951.
858.
594.
864.
1072.
1664.
1R24.
651.
1042.
1141.
R52.
0.
756.
2215.
1507.
1858.
0.
0.
1674.
724.
1229.
340.
Ill 1.
906.
1361.
860.
1R39.
604.
1100.
413.
239.
975.
792.
298.
536.
3R3.
99 A.
617.
5R9.
575.
176.
909.
1312.
0.
1562.
1918.
2512.
1404.
125V.
1319.
831.
885.
1314.
2233.
2211.
657.
1047.
1256.
1513.
0.
756.
2239.
1512.
1889.
0.
0.
1205.
878.
1821.
394.
1666.
1176.
13R9.
977.
2020.
1232.
???6.
2538.
4089.
2902.
998.
2867.
542.
1451.
1299.
1411.
1192.
1026.
15O4.
1477.
15693.
0.
15899.
16697.
19303.
13602.
15003.
14706.
12296.
233*8.
13602.
13095.
4999.
15693.
13698.
13602.
22404.
0.
13.
17001.
20292.
22994.
0.
0.
21504.
16301.
18695.
13602.
21504.
17292.
20090.
19594.
17396.
15693.
19399.
14300.
17001.
15899.
18695.
17908.
14394.
12394.
17908.
16399.
1 6794.
14200.
I790R.
15506.
86.
0.
114.
118.
108.
99.
85.
89.
83.
1.
82.
98.
77.
1.
89.
91.
0.
730.
76.
167.
182.
0.
0.
154.
110.
95.
1.
90.
105.
171.
144.
148.
R7.
107:
91.
97.
92.
89.
97.
•1 .
107.
113.
105.
R9.
105.
92.
117.
83.
0.
100.
115.
1O3.
99.
83.
84.
76.
1.
75.
94.
73.
1.
1.
67.
9O.
0.
10.
61.
135.
147.
O.
0.
125.
88.
91.
.1.
79.
95.
141.
132.
116.
80.
102.
89.
96.
90.
79.
88.
1.
103.
98.
97.
RB.
V4.
91 .
112.
7548.
1.
8259.
8717.
8893.
7817.
8308.
7631.
6809.
12357.
7237.
7864.
6823.
8193.
8136.
'6926.
971 1.
1.
643.
7990.
10446.
11464.
1.
1.
11339.
7778.
8920.
4750.
976O.
9154.
10594.
1O087.
9136.
6919.
8570.
8119.
7295.
7631.
9219.
7435.
9H1 9.
6425.
9036.
7115.
8039.
7533.
76?4.
7919.
.
.
•
•
30.
26.
1.
14.
a.
2.
4.
8.
65.
9.
1.
10.
34.
2.
1.
1.
1.
10.
6.
9.
86.
2.
3.
6.
1.
44.
28.
10.
2.
7.
4.
2.
1.
1.
2.
5.
7.
17.
1.
1 .
4.
303.
1.
96.
466.
1 33.
739.
1177.
1080.
767.
611.
1022.
1229.
192O.
186.
241.
855.
1O49.
1.
756.
768.
497.
759.
1.
1.
8O4.
756.
1344.
288.
1331.
1043.
476.
442.
1629.
1091.
1778.
1797.
1356.
2126.
904.
2644.
177.
949.
950.
987.
1126.
476.
1056.
690.
11.
1.
19.
14.
24.
5.
4.
44.
34.
2.
6.
12.
7.
1 .
4.
146.
26.
1.
3.
137.
3.
6.
1 .
1.
7.
1.
72.
319.
34.
3.
3.
4.
2.
12.
7.
29.
29.
33.
1.
14.
11.
2.
83.
56.
3.
1 B.
3.
6.S
1.0
7.0
6.5
7.0
5.5
5.5
5.0
5.5
6.S
6.5
7.5
1O.5
9.0
10.0
9.0
7.5
1.0
3.5
16.5
R.U
7.5
l.O
1.0
6.0
5.5
6.0
6.5
7.O
7.5
9.0
7.0
6.5
6.0
5.0
4.0
4.0
4.5
5.5
6.0
<>.'}
6.5
5.0
_. 5.0
5.5
6.O
6.5
4.3
1.0
4.6
5.7
4.7
4. •)
•1.6
5.3
*. 6
5. 1
4.4
5. 3
5. 3
5.4
5. 5
1.0
'..0
5.5
5. <*
6.2
1. 0
1.0
6. 3
5.6
5.4
5. 1
5. 7
5.6
6. 2
6. 1
6. 0
4. 6
4.4
3.5
2.9
3.9
5.T
3.4
',. 1
1. 1
b. 'j .
4.6
4. i
4.6
3.9
4. ',
VO
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
CFMSUS TRACT ATTRIBUTES — INPUT
VO
HA^HiNCTnM n r
C EMS US
TOTAL
TIACT POPULATION
•J'lHOFR
A*LOO?9
ARL0030
A-U0032
ARLOO33
ARLOJJ4
A** I On 35
A*10036
A3LO037
AHL0033
F&xnooi
FAXOJ02
FA XOilOl
FAX0004
FA XOOO5
FAX0006
F A XOQ O7
F 4X0303
FAX0009
F4X0313
F \XOO 1 1
F4XOJ12
F\xon I 3
.FAX0014
F 4 XOO 1 5
F4X0016
F \XO )l 7
F 4 XOO 1 *
F4XOO 19
F4X002J
FAxnn 7 1
F4X0022
F AXO173
FAX0024
FAXO175
FAX0326
F4XO')77
F4XOJ2.*
F\KOT 31
F^xOJ32
FAX0033
FAX0035
FAX0036
FAX001S
5994.
4198.
4523.
4942.
013.
6976.
1210.
3087.
»719.
3913.
391 3.
3616.
41 n I . -
7999.
9339.
5991.
7784.
1108.
9822.
7974.
6741.
6267.
3970.
6789.
7K.Q.
3831.
7406.
4537.
6735.
13643.
2705.
6192.
6535.
37«S.
4020.
4939.
4425.
5659.
5514.
5059.
11441.
3460.
135*9.
4101.
S71O.
7435.
A<*EA IN
SQUARE
Hll FS
0.
0.
2B«.
•461.
59.
0.
n.
179.
0.
237.
806.
1 O95.
1612.
3686.
0.
9792.
3627.
6852.
1 152.
5532.
n.
27236.
o.
582.
1 671.
1095.
• '650.
4206.
1 843.
10481.
1 152.
576.
765O.
1325.
461.
1095.
805. _
. 14176.
f 65O.
4206*
2650.
472).
3110.
11525.
1 777.
1727.
SINGLE
FAMILY
HmtSINC.
0.
0.
983.
767.
180.
0.
0.
762.
O.
296.
9O7.
1107.
31 h.
2180.
75*1 .
1584.
o.
348.
7735.
2099.
15B3.
1699.
0.
863.
O.
654.
1159.
1135.
1748.
3548.
777*.
786.
1045.
1541.
B7I.
1049.
17R6.
ALL
HOUSING
UNI TS
0.
0.
1001.
2438.
733.
0.
O.
994.
O.
1751.
997.
1154.
i 31 n.
2233.
7597.
1746.
O.
359.
2308.
2107.
1781.
1878.
0.
969.
O.
1205.
2260.
1145.
1783.
3555.
7794.
786.
1671 .
1735.
1050.
1286.
1170. 1170.
L4.22-. LS2Z.
1339. 1581.
1390. 1405.
13?4.
2844.
1018.
3443.
1162.
1497.
1727.
1373.
2925.
1029.
3673.
1192.
1SI7.
1730.
MEDIAN MEDIAN MEDIAN
PROPERTY
VALUE
0.
0.
11696.
15003.
13794.
0.
0.
16597.
O.
13200.
11696.
22203.
15003.
24O05.
22093.
o.
9997.
17103.
17801.
15506.
15994.
O.
11305.
O.
22697.
28999.
33996.
20792.
19891.
1999O.
18902.
16107.
15506.
1R398.
19791.
14501.
21895.
21590.
19791.
19594.
17001 .
19197.
22292.
1B306.
20806.
19497.
13602.
GROSS CONTRACT
RENT RFNT
0. O.
0. 0.
91. 74.
114. 111.
1. 1 .
0. 0.
O. O.
114. 102.
n. o.
94. 91.
110. Rfl.
1. 1.
inn. inn.
118. 97.
96. 61 .
98. 81.
0. O.
1. 1.
157. 137.
121. 92.
IO7. 87.
99. 87.
0. n.
79. 65.
O. O.
95. 93.
107. 1O7.
1. 1.
150. 113.
169. 135.
166. 133.
1. 1.
117. 1O6.
136. 107.
1 .
1.
1 .
1.
1.
125. 11 .
161 . 17 .
1.
144. 11 .
1.
142. 11 .
1.
1 .
1.
MEDIAN DILAPIDATED
FAMILY
INCDMF
1 .
1.
5335.
8831.
467O.
1.
1.
8485.
1 .
7935.
6771 .
9471.
7354.
7473.
1 107O.
7406.
1 .
6843.
8630.
8022.
7593.
6522.
1 .
6033.
1 .
8485.
9858.
13200.
93B6.
948 1.
9967.
7895.
7BB7.
8127.
RB31 .
10270.
8347.
10721.
10651.
6604.
95OO.
7662.
8375.
8699.
B630.
8417.
953H.
7252.
HOUSING
IINI TS
29.
•
•
3.
1 .
1.
7.
15.
7.
42.
163.
37.
1 .
21.
37.
61.
7.
63.
1.
64.
1 .
19.
9.
1.
43.
44..
7.
20.
10.
22.
73.
1.
1.
2.
L.
43.
68.
26.
39.
28.
77.
42.
7.
8.
HOUSING NONHHITE O1STM:CE 1 = 01 »•!
OVER 10 OCCUPIED BUSINESS oO'J-x; in
YFARS OLD HOUSINr, DISTRICT HMU^ 1 '1C.
,
1.
854.
1101.
149.
1.
1.
860.
1 .
943.
519.
384.
i nnn.
418.
661.
532.
1 .
211.
314.
495.
571.
7B1.
1 .
593.
1.
223.
1184.
42.
474.
601.
15.
247.
72B.
1360.
7 73.
29.
3 O9.
204.
144.
423.
787.
554.
235.
572.
537.
198.
1.
1.
970.
4.
730.
I .
1 .
1.
1 .
7.
6 .
69.
92.
237.
51.
13.
16.
29.
3.
6.
1 .
31 .
1 .
5.
70.
6.
731 .
22.
4 .
6.
54.
111.
59.
3.
1 .
1.
38.
64 -
84.
112.
12.
H5.
61 .
3.
1.0
1.0
5.5
5.0
4.0
1 .0
1.0
4.0
1 .0
4.5
7.0
7.5
7. S
9.0
10.5
12.0
1 . 0
18.0
9.0
10.5
7.. 5 .
10. 'j
i .a
1 8.0
1.0
7.5
7.5
".0
11.5
14.5
11.5
7.5
1 7.O
10.5
9.0
9.0
15.0
1.0
3.U
2.0
2.5
.2.0
3.0
3. o
3.U
1 .3
1.0
5, 1
3. 7
5.7
1 .0
1.0
5.6
1.0
3. 3
4.4
6.0
4.7
5. 1
6. 3
5.5
1 . !)
4 ,'j
5. 8
5.4
..5.1
5.0
1.0
4. «
1. 0
4.5
7.4
5. T
6. 0
5. 7
5.3
5. 7
5.9
6. 2
5. 0
S. 1
5. ;
5. r
5. S
5. -t
5.7
5. 7
S. 1
5. 1
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
rENSUS TRACT ATTRIBUTES — INPUT
VO
(MSHINSTON. O.C.
CENSUS
TOTAL
TRACT POPULATION
NimFR
FAX0039
FAX0040
FAX0041
FAX0042
FAX0043
F 4X00 4*
FAX004S
ALX0001
ALX0007
ALX0003
ALXOOO4
ALXOOOS
ALX0005
ALX0007
«L X0109
ALXOOO?
ALX001O
ALX0011
ALX0012
ALXOJ13
4LX0114
ALX0015
ALX0016
41X0017
&LX0318
ALXOO19
AL xon?o
FC0001
FCOOO»
FCOOOI
8527.
. 5402.
4638.
4134.
235<>.
1652.
1961.
2719.
2305.
3509.
422.
6248.
3717.
2561.
6418.
53SI.
4145.
6575.
8502.
4944.
5070.
4496.
5481.
992.
6419.
3220.
7879.
23B7.
576«.
2034.
AREA IN
SQUARE
MILES
2131.
6281.
25344.
31 675.
21047.
33400.
2879.
1574.
960.
851.
0.
0.
614.
819.
935..
621.
0.
346.
442.
352.
JB't.
384.
256.
582.
237.
147.
295.
352.
576.
295.
SINGLE
FAMILY
HOUSING
2191.
1735.
1400.
1109.
649.
981.
494.
494.
443.
898.
0.
0.
996.
6R4.
1589.
1152.
O.
855.
1906.
1192.
1072.
1211.
1236.
132.
1050.
577.
1214.
594.
1452.
533.
ALL
HOUSING
UNITS
2200.
1741.
1408.
1148.
666.
1016.
578.
950.
728.
903.
O.
0.
1002.
781.
1835.
1471.
0.
2463.
2558.
1512..
1691.
1401.
1362.
466.
2285.
1181.
3752.
626.
1661.
608.
MEDIAN
PROPERTY
VALUE
23600.
30792.
24197.
11696.
15003.
13306.
16204.
21807.
24392.
22404.
0.
0.
15899.
11396.
22093.
23295.
0.
23295.
12900.
12695.
14300.
16301 .
11204.
23295.
13494.
14003.
16R99.
18306.
18106.
26108.
MEDIAN
MEDIAN
GROSS CONTRACT
RENT RENT
195.
. 1.
1.
1.
1.
1.
1.
101.
135.
162.
0.
0.
1.
85.
66.
161.
O.
90.
103.
90.
94.
101.
77.
79.
84.
80.
89.
I.
110.
1.
150.
1.
1.
1.
1.
1.
1.
95.
118.
117.
0.
0.
84.
66.
126.
0.
89.
92.
77.
88.
85.
55.
78.
80.
67.
84.
1.
96.
1.
MFDIAN DILAPIDATED
FAMILY
INCOME
10732.
12357.
9109.
6355.
6905.
5R02.
7443.
8682.
9200.
9957.
1.
1.
7832.
5586.
7237.
11441.
7887.
7201.
7281.
7317.
8358.
3889.
7631.
5415.
5603.
7021.
9219.
7959.
11649.
HOUSING
UNITS
10.
10.
85.
134.
45.
50.
49.
3.
4.
2.
1.
1.
7.
75.
12.
2.
1.
6.
2.
63.
5.
3.
63.
6.
72.
147.
203.
1.
16.
2.
HOUSING
OVER 10
YEARS OLD
338.
525.
792.
71i.
415.
662.
389.
476.
79.
36.
1.
1.
88.
798.
1034.
BOH.
1.
1749.
1347.
1375.
1343.
1179.
1220.
444.
1924.
1171.
2317.
404.
1.
1.
NONWH1TE DISTANT
MEDIAN
OCCUPIED BUSINESS ROOMS IN
HOUSING DISTRICT HHilS 1 nr.
27.
42.
104.
115.
21 .
50.
16.
4.
11 .
3.
1 .
1.
7 .
70.
71.
20.
77.
59.
1 7.
8.
1 .
1007.
9.
530.
149.
456.
4.
16.
20.
3.5
3.5
3.5
2.5
2.5
2.0
?.o
8.0
7.0
0. 1
1.0
1.0
B.O
1.0
7.0
6.0
1 .0
5.0
4.5
5.5
5.5
6.5
6.0
4.5
6.0
6.5
7.5
9.5
10.0
8.5
6.1
7.0
5.T
5. 3
5. 1
5.5
5.fc
5. 1
4.4
6.0
1 .3
1 .0
5. 3
3.',
._ 5.2
6.4
1.0
4.0
4. 1
5. 1
5.0
5..'>
-
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
CENSUS
TRACT
0001
0002
0003
~"6C04~
0005
0006
0007
0WN
1034.64
1130.03
796.32
RENT
1424.
1C33.
3945.
0003
0009
0010
0011
0012
0013
0014
0015
0016
0017
0013
0019
0020
0021
0022
0023001
0023002
0024
0025
0026
0027
2061. 11
1034.64
853.34
1415. 16
1130.03
302.72
1925T61
1143.67
2075.59
157S. 14
716.95
772.01
1191.54
1063.49
3158.
624.
1273.
923.
916.
2677.
534.
1331.
2262.
1183.
- 493.
691.
1701.
3775.
CENSUS
TRACT
C028
0029
0030
0031
0032
0033
0034
0035
0035
0037
0039
0039
0040
0041
0042
0043
0044
0045
0046
004 T~
0048
0049
C050
"~ 0051
n 0 C, 7 Q ,~1 1
'COf-2002
0053001
OC53002
0WN
370.92
551. 15
256.98
462.20
873.93
1105.44
375.03
264.01
297.97
175.04
195.93
491.76
444.97
361. 04
286. 66
222.96
173.99
427.09
~" 2l~27C'9"
320. 86
303.08
229.06
2 ••> A . r 3
2 6 0 . 0 .3
RENT
2816.
1360.
1416.
764.
870.
1436.
1244.
508.
2357.
2815.
2107.
2304.
3223..
3480.
1789.
947.
543.
1175.
l~59r.~
1903.
2520.
3453.
2707.
" 3393.
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
00
CENSUS
TRACT
0054001
0054002"
0050055
0050056
0057001
0WN
229.93'
366. 87
95.97
RENT
3033.
1844.
3062.
0057002
0053
0059
0060
0061
0062
0063
0064
0065
0066
0067
0068
0069
0070
0071
0072
0~07300r
0073002
"0073003
0073004
~00730'05
0073006
"C073"00r
30.00
457. 14
294.12
536.99
873.31
424.96
358. 17
297.03
78.96
66. C2
230. 9:0
194.03
230. .06
224.03
399TO~2~~
862.
1345.
925.
1309.
1324.
763.
1194.
633.
1294.
' 649."
1319.
1441.
2131.
2113.
~V9i3~.
CENSUS
TRACT
0073003
W7400T
0WN
RENT
__
00 7~4d~03
0075
"007600'
JJ076C02
0"076003
0077001
"0077002
0077003
"007700 4
_OC77005
'0073001
_P 073 00 2
0^73003"
0073004
"0073005
0078006
0079
0030
0031
. OC32
9 "5. "q'7"
504.21
342/06
_ 555.15
"733.73"
_ 89J'95_
"714.C3
397
1"3"19
303,
T3G~3.
304,
°JL
749
03
,"75
32
~C3
10577'
1116.
~3 L"7 5 .
2424.
"1"432.'
1523.
"1476."
1947.
_.
532.8T
4 1 2_._8 2
" "950. C6~
704. 16
" 9 9 0 i 2 9"
1142.52
45"3.05
1555.
"1756."
636.
"l5C9r
_712.
1 12" 2 .
676.
_
OCS'7"
1534.
"1752
1832
1079.
1471.
17-1.
Ul'3.
Figure 3.1-1. List of Census Tract I ttributes for the Washington, D.C. SMSA (Cont'd)
-------
CENSUS
TRACT
0083001
0033002
0089
0090
0091
0092
0093
0094
OC95001
0095002
0095003
0095004
0096
MOCOOOL
MQC0002
MQC0003
MOC0004
MOC0005
MOC0006
MOC0007
MOC0003
MOC0009
MOC0010
MOC0011
MOC0012A
Tra~CO~OT2~&
MOC0013
MOCOOV4
0WN
230.90
739. L3
512.86
362.35
1265.22
773.21
1214.39
1391.31
242.01
1376.09
1034.64
2214.93
864.37
453.05
335.96
555.02
692.29
753.24
972.63
994.25
2777. CO
1840.63
575.94
933.23
"1331.42
RENT
1940.
1313.
29G3.
139.
1625.
1380.
1104.
303.
1005.
834.
81.
823.
333.
234.
172.
231.
544.
315.
456.
819.
296.
422.
198.
386.
357.
CENSUS
TRACT
MOC0015
.MOC0016"
MOC0017
MGC0018
MOC0019
MO COO 20
MOC0021
MOC0022
MOC0023
MOC0024
MOC0025
MOC0025
MOC0027
~MOCdO>3 "
MOC0029
MOC0030
MCC0031
"'MCC0032
MO COO 3 3
'MO COO 34
VCC0035
4 GCuO 35
MJCOC 37
•j • • i -\ -i ^
.'•'i :J '_ 0 J -T 0
^ C C 0 0 ^ I
'•'. u '„ 0 0 -* 2
0WN
1974.
"7 rr.
750.
717.
~~58'5."
1449.
1241.
575.
1334.
33 1.
369.
I3oo.
915.
1245.
2737.
1950.
3512.
1355.
1736.
2 0 ? :> .
"> \ '
L. 1 : . •
i. j 5 •» .
1 13-.
1C71.
*•* » -It.
~ ~ •
35
94
69
66
-
a'i
54
41
94
03
00
57
^9
93
14
00
59
21
67
4 3
21
'" "*
5 o
CC
97
RENT
142
766.
1937.
469.
803.~
411.
153.
1525.
659.
351.
109.
114.
63.
64.
215.
33.
256.
299.
197.
172.
!.<-*.
1 •' - m
55 3 .
110.
L3i.
Figure 3.1-1. List of Census Tract Attributes for the Washington, B.C. SMSA (Cont'd)
-------
o
o
CENSUS
TRACT
MOC0043
MOC0044
MOC0045
MOCOO~46
MOC0047
MOC0043
MOC0049
MOC0050
MOC0051
MOCC052
MOC0053
MOC0054
MOC0055
MOC0056
MOC0057
~"MTTCD053~
MOC0059
"MOC0060
PGC0001
PGC0002
PGC0003
T5C0004
PGC0005
P~GCOOO~6~
PGC0007
PG'C00153
PGC0009
PGC0010
0WN
1245.14
1390.00
2192.00
2153. 13
1157.43
1114.32
1052.53
1125.52
1026.59
832.71
1040.00
1151.00
1TZ*~ 39
2435.72
929.83
500.20
1013.33
3~86T84
362. 13
704. 16
RENT
129.
345.
210.
" 141."
169.
2515.
241.
272.
78.
104.
92.
165.
3~5~0~
125.
1751.
185.
339.
343~
275.
300.
CENSUS
TRACT
PGCO'Oll
~J>GC0012
PGC0013
PGC0014
PGCOC15
PGC6016
PGC0017
PGCOOT3
PGC0019
PGC0020
PGC0021
"PGC0022"
PGC0023
~PGC002V"
PGC0025
PGC0026
PGC0027
PGC0029
PGC0030
PGC0032
PGC0033
PG00034
0WN
1759.83
1426. 53
2115.40
790.76
1436. 55
"2303.07
1736.70
230.90
930.76
"1046.23
1065. 29
909.6'G
360.06
497. 20
310.73
932.62
679. 26
671. 15
620. 17
632.66
~ 1157:4=
RENT
_
413.
417.
287.
101.
189.
1140.
169.
~~" " "202."
951.
"373.
683.
355.
363.
222.
715.
314.
429.
166.
65.
PGC0037
P'G'CO'O 33"
7 J -i . 0 -,
47.
"797"
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
CENSUS
TRACT
PGC0039
PGC0040
PGC0041
PGC0042
PGC0043
PG~C004"4
PGC0045
PGCC046
PGC0047
PGC0048
PGC0049
PGC0050
PGC0051
PGC0052
PGC0053
PGC0054
PGC0055
PGC0056
PGC0057
PGC0053
PGC0059
PGC0060
PGC0061
PGC0062
PGC0063
PtiC0064
PGCOOS5
PGC0066
01W
737.30
579. 93
866.97
1202.31
465.91
539.9.3
582.89
833.60
513.89
643.72
457. 14
1077.07
534.86
630. 13
532.19
337.15
1465.57
902.35
342. 13
335.36
727.73
44 0 . 9. 3
313.11
955.23
1433.63
RENT
226.
304.
64.
33.
663.
281.
524.
553.
19.
926.
1034.
734.
184.
222.
760.
702.
420.
1503.
547.
349.
499.
363.
52.
304.
703.
CENSUS
TRACT
PGC0067
PGCOO'6'3
PGC0069
PGC0070
PGC007L
PGC0072
PGC0073
PGC0074
ARL0001
ARL0002
ARL0003
ARL6004
ARL0005
ARLOOOb
ARL0007
ARLOC03
ARL0009
ARLOOIO
ARLOOll
ARLOG12'
ARL0013
ARLG014
AS LOO 15
ARLOD1-.
• -> 1 - -N 1 -T
•» "N •_ W ' -• ». "
' A»L oo u
ARL0019
"AiVLCuTT
0WN
1768.70
531. 14
953.37
940. 11
766.63
706.27
1790.05
1235.21
1571.84
930.76
620.17
101 U31
232.99
942.94
759.00
1137.9.7
729.97
1523.^4
430, 10
3 3 7 . c- 3
211.'.-
1 5 : . ~ :
" 741.00
643.72
2~2G.C5
RENT
389.
32.
65.
272.
703.
30.
357.
245.
276.
235.
222.
679.
143.
694.
393.
230.
'220'.
454.
703.
957.
2 1 : ' 3 .
-;"?•>"'
_x * - f •
2065.
324.
2o02.
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
o
to
CENSUS
TRACT
ARL0021
ARL0022
ARL0023
ARL0024
ARL0025
ARL0026
ARL0027
ARL0028
ARL0029
ARL0030
ARL0031
ART 003 2
ARL0033
ARL0034
ARL0035
AH! 003 6
ARL0037
ARTOO~38
FAX0001
FAX0002
FAX0003
F~A~X0004
FAX3005
FAX0006"
FAX0007
FAXO"C"0~8~T'
FAX0009
~FAXOOIO
0WN
43C.09 .
283.98
843.10
546.75
401.82
497.20
103.95
69C.90
617.70
227.01
171..06
623.23
170. .03
623.91
955.23
275.06
1732.90
2123.13
~ V04o;o2
224.93
1846.41
'1730.21
RENT
107.
936.
426.
326.
770.
507.
1381.
657.
366.
1926.
59.
349.
1520.
332.
163.
1003.
376.
308.
53'4.~~
77.
303.
239.
CENSUS
TRACT
FAX0011
FA~X0012
FAX0013
FAX0014
FAX0015
FAXOC16
FAX0017
FAX0013
FAX0019
FAXD020
FAX0021
'FAX00.22
FAX0023
FAX0024
FAX0025
FAX0026
FAX0027
FA~X0023"
FAX0029
FAX0030"
FAX0031
FAXQD32
FAX003?
FAX'C-:34
FAXQ035
"FAX0036 "
FAX0037
FAX-JO 3 3
0WN
1335.42
1 39 9V6~3
545. 12
50'1.20
996.25
939.30
1440.87
3093.32
1900.74
' 573.07"
366. 10
1433.63
719.32
923. 34
1125.52
963.91
1191.54
1"0"3 4". 64
1103.76
1097.73
2421. 15
7-i-3. 13
2749.02
906.37
127^,. 11
1433.26
RENT
417.
397.
275.
658.
1196.
115.
2a7.
329.
351.
" ~95. '
. 700.
246.
113.
107.
146.
" 179.
139.
359.
238.
215.
328.
" 127.
631.
192."
191.
211.
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
o
LJ
CENSUS
TRACT
FAX0039
FAX0040
FAX0041
FAX0042
FAXOC43
FAX0044
FAX0045
ALXOOOl
ALX0002
ALX0003
ALXOOOL
ALX0005
ALX0006
ALX0007
ALX0009
ALX0009
ALX0010
ALX0011
ALX0012
ALX0013
ALX0014
ALX0015
ALX0016
ALXOOL7
ALX0018
ALX0019
ALX0020
FCOOOl
FC0002
FC0003
0WN
1820.74
1333.53
970.68
755.97
391.11
65S.34
381.84
336. 94
91.01
519. -C5
323.04
531.13
54. OC
27.00
37.00
12.00
1.00
804.32
972.63
495.22
80.96
486.87
259.04
743.23
502. 2G
801. 11
447.20
RENT
232.
177.
278.
253.
176.
244.
156.
490.
612.
331.
130.
23L.
951.
242.
1656.
1499.
643.
83d.
398.
804.
361.
16S1.
825.
2381.
110.
812.
140.
Figure 3.1-1. List of Census Tract Attributes for the Washington, D.C. SMSA (Cont'd)
-------
NOTE: Annual Concentration In
Figure 3.1-2. Existing Ground Level Particulate Concentrations in the
NCIAQCR as Computed by the Verified Diffusion Model
104
-------
P 1 - Existing Control Regulations Throughout the Region -
This strategy displays the air quality resulting
from complete compliance with existing control
regulations in the region.
P 3 Existing Regulations in the District and Virginia
- No Emissions in Maryland. Area source emissions
were eliminated and point sources were substantially
reduced by the application of maximum control strategy,
P 18 - Proposed Particulate Control Strategy - District of
Columbia sources were controlled to 0.03 grains/scf
for industrial process sources, 0.06 grains/scf fuel
combustion sources and 0.20 grains/scf for incinera-
tion sources. Maryland and Virginia sources were
controlled to the level specified by their respective
Implementation Plans.
P 2 - Maximum Control Technology - Under this strategy the
best available control device or measure (as defined
in the IPP I Control Cost Model) is applied to each
pollution source. This strategy may be neither
economically nor technically feasible, but does give
a potential lower limit on pollutant emissions.
Sulfur Dioxide Strategies
• Existing S02~(197Q) Air Quality data for S0~ under existing
conditions throughout the region. The ground level S02
concentration isopleths for this situation are shown in
Figure 3.1-3. This provides the baseline for S02 strategies,
• S 10 - Q.06 Grains/scf on Fuel Combustion Sources - 0.03
Grains/scf on All Other Sources of Particulate
Emissions. This strategy was designed to allow
residual fuel oil combustion without control in
well-designed equipment. A further restriction
was applied to large coal-fired units (i.e.,
power generating stations) in that they were
required to meet a 0.03 grains/scf standard.
(This primary particulate emission strategy
tends to produce fuel switching in powerplants
which also reduces SC>2 emissions.)
• S 14 - Existing Regulations in the District and Maryland
- No Emission in Virginia. Hypothetical display
of regional air quality if Virginia's contribution
were removed.
105
-------
•1
NOTE: Annual Concentration in yg/nr
Figure 3.1-3. Existing Ground Level Sulfur Dioxide Concentrations in the
NCIAQCR as Computed by the Verified Diffusion Model
106
-------
• S 15 - Maximum of 0.7 Percent Sulfur Content Fuel in Region.
This gives a small reduction from current 1.0 percent
sulfur restriction now in effect in most of the Region.
(Major exceptions are the Dickerson and Chalk Point
powerplants.)
• S 11 - Existing Regulations. Complete application of existing
regulations affecting sulfur oxide emissions through-
out the Region.
The above strategies for particulate and S02 emissions are listed in order
of decreasing total emissions (i.e., total emissions due to point and area
sources). The complete average annual ground level receptor concentration
data for all of these strategies are too voluminous to present here. Table
3.1-1 summarizes general regionwide values of existing and controlled emis-
sions and the ground level concentration at the maximum receptor.
Included in Table 3.1-1 are the annualized point source control costs
for the entire region. These control costs are the only costs employed in
the demonstration study. Proposed methods for estimating area sources con-
trol costs and other private and public sector costs have been prepared by
Woodcock [1971].
The control cost and emission rates (old and new) are available on
a regionwide and political jurisdiction basis from the IPP Regional
Strategies Program summary table outputs. Samples of these tables are
given in Appendix A. The Regional Strategies Program also provides a
tabulated summary of emission standard effects on individual source emis-
sions including device costs and emission rates in tons/day (existing,
allowable and controlled). In principle, these data can be used to obtain
cost/benefit analysis information on an individual source or census tract
basis. However, as currently designed, the RAPA Cost/Benefit Model cannot
be conveniently used below the political jurisdiction level.
107
-------
Table 3.1-1- Participate and Sulfur Oxides Control Strategy Summaries-NCIAQCR.
Strategy/
Pollutant
Existing
Particulates
POINT SOURCES
Percent
Reduction
•
p l !
New Emission
Rate
(Tons/Day
84.7
AREA SOURCES II CONTROL COST
Percent i New Emission L
Reduction ! Rate |j $xlO
.' (Tons/Day) h
1 1
;i
75.6 !l
• i
r
$/Ton
Removed
. -
Maximum Receptor
(Vg/m3)
107.7
o
oo
Particulates
36.3
54.0
18.0
62.0
0.5
47
Not used in this demonstration.
*See explanation of negative costs in Section 2.3.1.
92.2
P 3
Particulates
P 18 1 2
Particulates
P 2 1
Particulates
Existing
so2
P 10/S 10 **
so2
S 19 2 3
so2
S 14
so2
S 15 l
so2
S 11 !
so2
[ |
,
62.2 32.0
1
70.4 • 25.0 :
87.4 10.7 j
r > .
i- • j
i
542.0 1
36.4 344.8
43.0 308.9
55.0 243.9
67.4 176.6
100.0 0.0 ;
,
_
47.5 39.7 4.0 : 210
1 :
'• '
51.4 36.7 10.8 ; 498 :
; 51.4 36.7 13.9 • 514
118.6
0 118.6 -3.5 4 -48 *
20.8 93.9 14.7 172.7
25.5 88.4 6.1 57.6
31.3 81.4 14.6 109
82.3 21.0 104.5 528
90.0
68.2
64.2
99.3
95
68
77
67
43
**Designed for particulates.
Capable of satisfying regional air quality standards.
20riginally proposed strategy for D.C. (Ref. Implementation Plan Report).
-------
3.2 ESTIMATION OF DIRECT DAMAGE COSTS
The study of direct damage effects for the RAPA Cost/Benefit Model
demonstration involved the use of the Damage Costs Module (Section 2)
with the NCIAQCR population, housing and air quality data detailed in
the preceding sections of this chapter. A linear model of direct damages
and the Pro Forma Damage Functions described in Appendix C were used.
These linear damage functions (shown in Figure 3.2.1 are:
- 0.66X - 5.90
where:
D = 0.47x - 4.70,
P
D = Damage per capita in millions of dollars per year
2 due to sulfur dioxide.
D = Damage per capita in millions of dollars per year due
to particulates.
X = The average annual pollutant concentration (S02 or
particulates) in micrograms per cubic meter (pg/ra^) .
The results of the cost/benefit analysis on a regional basis have been
summarized in Table 3.2-1. The tabulated values are listed by strategy in
separate groups for S0? strategies (above) and particulate strategies (be-
low). Each set of strategies is listed in increasing order of stringency.
For example, the identification S-10" refers to the second SO- strategy
(employed in this study) in order of stringency. This is referenced
number S-10, according to the Washington Implementation Plan Study
[TRW, August 1970] identification scheme given in Section 3.1.
The tabulated results include:
• The total emissions (tons/day) - The sum of the contributions
of all point (controlled) and area (scaled) sources in the
region, (from IPP tabulated output).
109
-------
CO
cS
01
t>0
(0
•-I to
(0 0)
•H
CO D.
4J CO
60
50
40
30
§" 20
o ^
0)
D-,
10
so.
=-$5.90 + 0.66X
=-$4.70 + 0.47X
40 80 120
X = Weighted Air Quality (pg/m3)
Figure 3.2-1. Pro Forma Functions Utilized in NCIAQCR Cost/Benefit Demonstration
-------
Average Air Quality
Weighted With
Strategy
S02:
Existing
S-10
S-14
S-15
S-ll
Particulates:
Existing
P-l
P-3
P-18
P-2
Total
Emission
(Tons /Day)
660.6
463. A
332.3
238.0
21.0
160.3
116.0
71.7
61.7
47. A
Respect To
Population
(Ug/tn3)*
65.0
57.8
52,8
49.3
36.4
69.4
64.4
60.8
57.5
54.1
Point
Emission
(Tons/Day)
542.0
344.8
243.9
176.6
0.0
84.7
54.0
32.0
25.0
10.7
Damage
C$ x 106)
73.6
64.0
57.5
52.9
36.0
55.0
50.8
47.5
44.4
41.2 .
Benefit
($ x 106)
0.0
9.6
16.1
20.7
37.6 .
0.0
4.7
8.0
11.1
14.3
Control Cost
($ x 106>
0.0
-3.5
6.1
14.6
104.5
0.0
0.5
4.0
10.8
13.9
£(People)(gg/m3)
£(People)
Table ,3.2-1. NCIAQCR - Regional Damage Values Summary
-------
The air quality weighted with respect to population (pg/m3)
This value is given by total exposure* divided by the total
population of the region and is a good measure of average
dosage. The units are actually
people - ug/m3 . ,
•*-—c :—a on the annual average basis, (from
Damage Costs Module output).
Total point emissions (tons/day) - The total emissions
(controlled) of all the point sources in the region.
• Damage C$ x 10 ) - The damages in units of millions of dollars
per year, as calculated using the (Pro Forma) damage function
provided, (from Damage Costs Module output tables).
• Benefit ($ x 10 )_ - Calculated from the existing damage contri-
bution, i.e., the reduction in damages resulting as each control
strategy improves air-quality.
• Control Cost ($ x 10 )_ - The total annual cost of controlling
the point source emissions as calculated by IPP, (from tabulated
output).
All costs and damages are on an;annual basis. As expected, the total emis-
sions, point emissions, weighted air quality and damages are all monotone
decreasing functions of stringency. The control costs are generally mono-
tone increasing functions of stringency. The exceptional case is an infre-
quent negative cost**. In general, the appearance of negative control cost
has been interpreted as probably representing a small positive value.
* The concept of exposure is explained in Chapter 2.0. Briefly, it is the
product of the census tract air quality and population, summed over all
census tracts in the region; it has the units people.)" UE
m-
**Actually, the use of S02 emissions to manufacture sulfuric acid, when
applied as a control device in the IPP simulation, can produce negative
costs, i.e., profit. However, this is a rare exception and negative costs
in the IPP I simulations were generally found to be spurious. They usually
result from fuel switching applications. IPP I switched fuels on a speci-
fic price per source basis to a general regional price basis. Consistency
could not always be met even under the best of conditions; this deficiency
has since been corrected in IPP II. However, most of the problems of this
kind, even in IPP I, really related to poor fuel price data which did not
propertly reflect demand for low sulfur fuel or accurately represent price
on a BTU basis. Poor fuel price structure data can produce negative costs
even when using IPP II.
112
-------
3.3 ESTIMATION OF PROPERTY VALUE EFFECTS
The property value analysis is based on the output of the Property
Value Module of the Benefits Model Segment (Chapter 2.0), using the
NCIAQCR population and housing data and the Washington Implementation Plan
Study regional strategy and air quality data (IPP I). The additional in-
put required to run the Property Value Module, i.e., the regression coeffi-
cients for the four Anderson-Crocker property value equations were obtained
from the work of Anderson and Crocker [1970] for Washington, D. C. The
complete equations are as follows*:
Type I
In(PVl) = 3.3901 - 0.0712 In(PSN) - 0.0610 In(PPT)
+ 0.7677 In(MFI) + 0.0044 In(DLP)
- 0.0106 In(OLD) + 0.0251 In(NWT)
- 0.0582 In(DIS) + 0.0 In(MRM)
Type II
ln(PV2) = 1.1617 + 0.0010 In(PSN) - 0.1698 In(PPT)
+ 0.9970 In(MFI) + 0.0113 In(DLP)
- 0.0213 In(OLD) + 0.0321 In(NWT)
- 0.0312 InCDIS) + 0.9064 In(MRM)
Type III
ln(PV3) = 0.2428 - 0.0905 In(PSN) + 0.0049 In(PPT)
+ 0.5109 In(MFI) + 0.012 In(DLP)
- 0.0606 In(OLD) - 0.0043 In (NWT)
- 0.0216 In(DIS) + 0.0 In(MRM)
Type IV
ln(PV4) = 0.4705 - 0.0727 In(PSN) - 0.0302 In(PPT)
+ 0.4650 In(MFI) - 0.0054 In(DLP)
- 0.0408 In(OLD) - 0.0124 In(NWT)
- 0.0111 In(DIS) + 0.0 In(MRM)
*For an explanation of census tract attributes and notation, see Section 2.
113
-------
The impact of various air quality levels on Type I property values
as predicted by the Property Value Module are summarized for the NCIAQCR
in Table 3.3-1; the impact on individual political jurisdictions is de-
scribed in the tables in Appendix D. Note in Table 3.3-1 that there is a
single line of data for each pair of control strategies identified in
Column 1; the second and third columns give the weighted air quality which
results when these two strategies are applied. Column four gives the
regional total Type I property value in millions of dollars. The benefit
listed in Column five must be annualized before it can be compared with
control costs; a reasonable assumption would be that 10% of these benefits
accrue per year. The average Type I property value (Column six) is per
owner occupied unit, i.e., it is computed by multiplying the number of
owner-occupied units in a given census tract by the median property value
for that tract, repeating this multiplication for each tract in the region,
adding up the products and dividing by the total number of owner-occupied
units in the region. The annualized control costs in the last three columns
are from IPP.
The output from the Assignment Module is shown in Table 3.3-2. The
data presented is similar to that in the previous table, except that an
attempt is made to estimate market effects. Thus, the total bid before
shift is simply the total regional property value, ignoring the fact that
people are likely to relocate in the face of changing property values.
Assuming that the households with the highest mean family income
will select the census tract with the highest median property values (and
that the second-highest income will select the census tract with the second
highest median property value, etc.) results in the total and average bid
-------
S02 Strategy/ .
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
11/2
Average S02
Air Quality
Weighted With
Respect To
Population
(ug/m3)*
66.7
59.8
54.4
40.8
36.5
Average
Particulate
Air Quality
Weighted With
Respect To
Population
Gig/m3)*
70.9
65.6
61.8
58.1
54.6'
Total
Type I
Property
Value
$x!06
5,329.
5,401.
5,448.
5,489.
5,602.
Total
Benefit
$x!06
0.0
72.
47.
41.
113.
Average
Type I
Property
Value
$
22,365
22,664.
22,863.
23,034.
23,507.
Average
Benefit
Per
Household
$
0.0
499.
199.
171.
473.
S02
Control
Cost
$x.l06
0.0
-3.5
6.1
14.6
104.5
Partlr-
ulntr
Contrc'J
$x].0fl
0.0
0.5
4.0
10.8
13.9
Total
Control
Cost
$x!0fl
0.0
-3.0
]0.1
25.4
11R.4
£ (People) (ue/m3) .,,D/m3
E (People)M8/m
Table 3.3-1. Type I Property Values: NC1AQCR Regional Summary
-------
Average
SO 2 Strategy/
Particulote Strategy
Existing/Existing
10/1
14/3
15/18
11/2
\verage SO 2
Air Quality
Weighted With
Respect To
Population
(ug/m 3) *
66.7
59.8
54.4
50.8
36.5
Particulate
Air Quality
Weighted With
Respect To
Population
(Mg/m 3) *
70.9
65.4
61.8
58.1
54.6
Total
MPV
(SjdOj)
4.172.
4,172.
4,172.
4,172.
4,172.
Average
MPV
(S)
17506.
17506.
17506.
17506.
17506.
Total
Type I
Bid
Before
Shift
C$xlO 6)
5,329
5,401.
5,448.
5,489.
5,602.
Average
Type I
Bid
Before
Shift
($)
22365.
22664.
22863.
23034.
23507.
Total
Type I
Bid
After
Shift
4,879.
4,941.
4,982.
5,019.
5,100.
Average
Type I
Bid
After
Shift
($)
20,475.
20,735.
20,907.
21,066.
21,402.
Total
Difference
($xlOG)
-450.
-460.
-466.
-469.
-501.
Average
Differei
($)
-1890.
-1929.
-1956.
-1968.
-2105.
*E( People) (Mg/m3)
EfPeople)
Table 3.3-2. Adjusted Type I Property Values: NCIAQCR, Regional Summary
-------
after shift. In every case, there is a lower total regional (and average)
property value after equilibrium has been attained, which is contrary to
what is expected. In looking at these results, it was realized that an
important model capability, which could account for the apparent error,
had been omitted. The current algorithm assumes families from any given
census tract can move to any other census tract, i.e., will find sufficient
housing units. This may be a credible assumption when the total population
of each tract is considered, but it is not valid when looking at market
effects on owner occupied units only. The capability of accounting for
variation is currently being incorporated into the model.
117
-------
4.0 REFERENCES
ANDERSON, Robert J. and Thomas D. CROCKER, January 1970: "Air Pollution
and Housing: Some Findings," Purdue University, Paper 264.
Bureau of Census, U. S. Department of Housing, 1960: "U. S. Censuses of
Population and Housing: 1960," Final Report PHC(1)-166.
LARSEN, Ralph I., January, 1969: "A New Mathematical Model of Air Pollution
Concentration Averaging Time and Frequency," Journal of the Air Pollution
Control Association, Volume 19, No. 1.
MARTIN, Delance 0., and Joseph A. TIKVART, June 1968: "A General Atmos-
pheric Diffusion Model for Estimating the Effects on Air Quality of One or
More Sources," Journal of the Air Pollution Control Association, pp. 68-148.
TRW Systems Group, November 1969: "Air Quality Display Model (AQDM)."
TRW Systems Group, November 1970: "Air Quality Implementation Planning
Program" (IPP), Volume I Operator's Manual, Volume II Programmer's Manual.
TRW Systems Group, August 1970: "Implementation Plan for Controlling Sulfur
Oxide and Particulate Air Pollutants," Report No. 16295.000.
119
-------
APPENDIX A
THE IMPLEMENTATION PLANNING PROGRAM, CONTROL COST CALCULATIONS
1.0 INTRODUCTION
The Implementation Planning Program (IPP) estimates the direct cost
of emission control to the major point sources. These point source control
costs provide the only cost data currently utilized by the RAPA Cost/Benefit
Model. Thus, IPP serves as the Cost Segment for the Cost/Benefit Model.
The details of the cost calculations, as performed in the production version
of IPP (IPP II)* are presented here for convenience.
2.0 CONTROL MEASURES AND DEVICE APPLICATION
In general, assignment of a control device to a particular point
source depends upon a number of engineering factors related to both the
source and device characteristics. Within the Control Cost Program of IPP,
device assignment is performed in two basic steps which produce a list of
pollution control devices for each point source. The first step involves
determining those devices which apply to the general source type (defined
by their SIC and process code). The second step requires examination of
each source within the SIC and process group to determine which of the
applicable devices can actually be assigned (i.e., installed) to the point
source. This second list of control devices actually applied to each source
*
Air Quality Implementation Planning Program, Vol. I, Operator's Manual,
Vol. II, Programmer's Manual, Environmental Protection Agency, National
Air Pollution Control Administration, Washington, D. C., Contract No. PH-
22-68-60, TRW Systems Group, Washington Operations, November 1970.
121
-------
includes only those remaining after certain criteria have been satisfied.
A list of control devices and measures that are considered in the Control
Cost Program is provided in Table A.2-1. The application criteria, device
descriptions, Standard Industrial Classification (SIC) and process codes
are covered in Volume I of the IPP manual.
IPP contains certain pre-set values for device control efficiencies,
cost coefficients and other relevant parameters. These pre-set values
(Table A. 2-2) may be changed by the user through the input data. The
Emission Standards Program of IPP attempts to apply each specified emission
standard to every applicable point source. For each applicable source, the
allowable emission rate is determined and, based on the control device in-
formation provided in the final list from the Control Cost Program, an
appropriate device or measure is selected. Final selection of the appro-
priate control device is based on the following tests:
(a) If the existing emission rate is less than the allowable
emission rate, no device is chosen.
(b) If not (a), then apply the device which results in a
controlled emission less than the allowable emission
defined by the standard.
(c) If more than one device produces sufficiently low emissions,
the device having the lowest annualized cost is selected.
When none of the available devices allows the sources to meet a
particular emission standard, the most efficient device is selected.
To evaluate the impact of the regionwide emission control strategy
on regional air quality, the Regional Strategies Program of IPP adjusts
each receptor concentration value by modifying the contribution of each
122
-------
Table A.2-1. Pollution Reduction Devices or Methods
Applied to Point Sources in IPP.
001 Wet Scrubber - High Efficiency
002 Wet Scrubber - Medium Efficiency
003 Wet Scrubber - Low Efficiency
004 Gravity Collector - High Efficiency
005 Gravity Collector - Medium Efficiency
006 Gravity Collector - Low Efficiency
007 Centrifugal Collector - High Efficiency
008 Centrifugal Collector - Medium Efficiency
009 Centrifugal Collector - Low Efficiency
010 Electrostatic Precipitator - High Efficiency
Oil Electrostatic Precipitator - Medium Efficiency
012 Electrostatic Precipitator - Low Efficiency
013 Gas Scrubber
014 Mist Eliminator - High Velocity
015 Mist Eliminator - Low Velocity
016 Fabric Filter - High Temperature
017 Fabric Filter - Medium Temperature
018 Fabric Filter - Low Temperature
019 Catalytic Afterburner
020 Catalytic Afterburner with Heat Exchanger
021 Direct Flame Afterburner
022 Direct Flame Afterburner with Heat Exchanger
027 Eliminate Coal Combustion
028 Eliminate Coal and Residual Fuel Oil Combustion
029 Change all Fuel Use to Natural Gas
030 No Fuel Use Over a Maximum Sulfur Content (Specified
by the User in the Regional Data Base )
031 Same as Device 030 but with a Different Allowable
Sulfur Content
032 Same as Device 030 but with a Different Allowable
Sulfur Content
039 Catalytic Oxidation - Flue Gas Desulfurization
041 Dry Limestone Injection
042 Wet Limestone Injection
043 Sulfuric Acid Plant - Contact Process
044 Sulfuric Acid Plant - Double Contact Process
045 Sulfur Plant
123
-------
Table A.2-2. IPP Control Device Preset Data
N>
Rated
Efficiency
ID
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
27
28
29
30
31
32
39
41
42
43
44
45
Device Name
WET SCRUBBER HI EFFIC
WET SCRUBBER MED EFFIC
WET SCRUBBER LOW EFFIC
CRAV COLLECTOR HI EFFIC
CRAV COLLECTOR MED EFFIC
CRAV COLLECTOR LOW EFFIC
CYCLONE HI EFFIC
CYCLONE MED EFFIC
CYCLONE LOW EFFIC
ELECT PRECIP HI EFFIC
ELECT PRECIP MED EFFIC
ELECT PRECIP LOW EFFIC
CAS SCRUBBER
MIST ELIMINATOR HI VEL
MIST ELIMINATOR LOW VEL
FABRIC FILTER HI TEMP
FABRIC FILTER MED TEMP
FABRIC FILTER LOW TEMP
CATALYTIC AFTERBURNER
CATALYTIC AB WITH HE
DIRECT FLAME AFTERBURNER
DIRECT FLAME AB WITH HE
ELIMINATE COAL
ELIMINATE COAL AND R OIL
SWITCH TO GAS
SULFUR LIMITATION 1
SULFUR LIMITATION 2
SULFUR LIMITATION 3
CATALYTIC OXIDATION
DRY LIMESTONE INJECTION
WET LIMESTONE INJECTION
H2504 PLANT-CONTACT
H2504 PLANT-2 CONTACT
SULFUR PLANT
so2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
80.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
. 0.0
0.0
0.0
90.0
50.0
80.0
97.5
99.5
95.0
Part
98.0
90.0
80.0
60.0
40.0
30.0
85.0
75.0
60.0
99.0
95.0
90.0
80.0
99.0
85.0
99.0
99.0
99.0
95.0
95.0
95.0
95.0
0.0
. 0.0
0.0
0.0
0.0
0.0
0.0
0.0
98.0
0.0
0.0
0.0
Manufacturers Price Coefficient
1
0.289E 01
0.289E 01
0.126F 01
-0.445E 00
-0.420E-01
0.300E-02
0.241E 01
0.151E 01
0.244E 00
0.424E 02
0.312E 02
0.197E 02
0.317E 01
0.266E 01
0.177E 01
0.145E 01
0.348E 01
0.266E 01
0.755E 01
0.755E 01
0.571E 01
0.571E 01
5.0
0.0
0.0
0.0
0.0
0.0
-0.124E 02
0.0
0.111E-05
0.0
0.0
0.0
2
0.228E 00
0.228E 00
0.145E 00
0.326E 00
0.155E 00
0.560E-01
0.197E 00
0.157E 00
0.990E-01
0.623E 00
0.441E 00
0.318E 00
0.251E 00
0.325E 00
0.217E 00
0.831E 00
0.448E 00
0.325E 00
0.151E 01
0.151E 01
0.117E 01
0.117E 01
0.0
0.0
0.0
0.0
0.0
0.0
0.167E 01
0.995E-06
0.481E-16
0.800E 00
0.800E 00
0.810E 00
3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.603E-16
0.0
0.0
0.0
0.0
•3S
*J 4J
2 ii
e
-------
source according to its "new" emission rate. The "new" emission rate for
each source is determined as follows:
(a) If the existing emission rate is less than the allowable
emission, the existing emission rate is used. Otherwise
the allowable emission rate under the appropriate emission
standard is used*.
(b) For area sources, the scale factor (user supplied input) is
applied to the existing emission rate and the resulting
emission rate is used by the program in the determination
of new air quality. However, no cost estimates are made
for control of area sources.
*
This is only true for IPP II. The rationale is that in practice, it is
technically possible to supply, and sources will purchase devices which
meet requirements only. IPP I used the controlled emission rate to deter-
mine new air quality. The controlled rate may be less than the allowable
rate due to the limited number of devices and parameters that can be dealt
with in practice in the simulation.
125
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3.0 CONTROL COST CALCULATIONS
The total annual cost resulting from the assignment of a control device
to a point source involves the component costs: purchase cost, installation
cost, interest charges, and operating and maintenance costs. The calculations
as performed in IPP involving each of these component costs are described in
the subsections below.
In addition to the control devices described, a set of emission control
methods have been included in the Control Cost Program. These methods are
designed to provide a reduction in combustion source emissions by using fuel
substitutions to modify the existing fuel use pattern.
3.1 PURCHASE COST
The purchase cost of control devices depends, in general, upon the
characteristics and complexity of the control device and the size of the
pollution source to be controlled. In the Control Cost Program, these
parameters are used to determine a basic purchase cost equation for each
control device. The general form of this equation is:
2
y = a + bx + ex ,
The coefficients a, b and c in this equation correspond to "Manufacturer's
Price Coefficient" 1, 2 and 3, in Table A.2-2, respectively.
126
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When the corrosive gas stream from acid manufacturing facilities.
are controlled, more expensive control device construction materials must
be used. For these cases the Control Cost Program, utilizes the following
factors to Increase the device purchase price:
If exit temperature _< 330°F, multiply purchase cost by 1.7.
If exit temperature > 300°F, multiply purchase cost by 5.0
3.2 INSTALLATION COST
The cost of installing a control device on a particular source is
calculated on the basis of an installation cost factor. This factor is
expressed as a percentage, of the purchase price and is a user input item
for each control device. The program sums purchase cost and installation
charge to determine the j^otal installed cost for each source-device
combination.
For some control device installations, however, extensive modifications
of the source are required and it is not possible to identify a purchase cost
figure independent of the installation charge. For these devices, the total
installed cost is estimated by the purchase price equations described in
Subsection 3.1. No additional factor is required in these cases to
account for installation at a source site. Devices in this category are the
flue gas desulfurization units (039, 041, 042) and by-product manufacturing
facilities (043, 044, 045).
3.3 ANNUAL CAPITAL CHARGE
After the total installed cost (purchase plus installation) of a
device has been determined, an annualized capital charge is calculated,
based on the user inputs: rated life of the control device and prevailing
127
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interest rate. Therefore, the annual cost comprises both depreciation of
the initial total investment (installed cost from Subsection 3.2) and
the interest costs.
The particular accounting technique employed here is called the
Capital Recovery Factor (C.R.F.). The use of the C.R.F. allows the write-
off of the initial investment to be divided into a uniform series of end-
of-year payments.
The C.R.F. multipled by the initial investment cost (debt) determines
the uniform end-of-year payments necessary to repay the debt in "N" years
(the rated life of the device) with an interest rate "i" (decimal equivalent)
The C.R.F. is calculated by the following relation:
c.R.F. =
(1 + i)N - 1
The annual capital charge is then computed to be the product of the total
installed cost and the C.R.F. value.
In practice, the capital recovery concept operates as follows:
(1) Payments are made at the end of each year in the amount
determined by multiplying the capital recovery factor
by the initial debt.
(2) Interest payments are made to the bondholders at the
end of each year in the amount determined by multiplying
the interest rate by the initial debt.
(3) The difference between the equal annual payments and the
interest payments to the bondholders is placed into a
depreciation account where it is assumed to draw interest
at the same rate paid to the bondholders.
128
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The total yearly cost to the source for controlling pollution by
means of a specified device is then the sum of the annual capital charge
and the annualized operating and maintenance expense discussed in the
next subsection.
3.4 OPERATING AND MAINTENANCE EXPENSE
Operating and maintenance (O&M) expenses are usually a major portion
of the annualized control device cost. The factors which must be con-
sidered in determining the annual O&M cost of a particular source-device
combination consist of: the amount of power (calculated as electrical
power) necessary to maintain the effluent gas flow through the control de-
vice, the quantity of labor required, the cost of liquid or additional fuel
used by the device, and the cost or credit resulting from disposal of the
collected pollutant. These factors are used in the following equations
to determine the O&M cost for each type of control device pre-set in ipp.
For control devices 001 through 022, a single equation is used to
compute the annual O&M cost:
O&M = AB + CD -I- EF + GI + JK + LM,
where A = electricity quantity (kwhr/yr) (a)*
B = electricity cost ($/kwhr) (input as regional
data)
C = water quantity (gal/yr) (b)
D = water cost ($/gal) (input as regional data)
E » chemical quantity (ton/yr) (c)
F = chemical cost ($/ton) (input as device data)
G = fuel quantity (cu.ft./yr) (d)
I = fuel cost ($/cu. ft.) (natural gas value, input
as regional data)
J = disposal quantity (ton/yr) (e)
K = disposal cost ($/ton) (input as device data)
L = labor quantity (hr/yr) (f)
M = labor cost ($/hr) (input as regional data)
*
The letters refer to the following items which describe the computation
of these data elements.
129
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The computation of these data elements are as follows:
(a) Electricity Quantity (kwhr/yr) = (1.955 10"4)pVH
where p = pressure drop (in H_0)
V = exhaust gas volume (ACFM) this is the new
computed volume (x) in the case of a wet
device
H = operating hours (hr/yr)
If the device is one of the electrostatic precipitators
(010, Oil, 012), the following quantities are added to
the electricity quantity:
Device 010, add (0.34 10"3) VH
Device Oil, add (0.26 10"3) VH
Device 012, add (0.19 10"3) VH
(b) Liquid Quantity (gal/yr) = (3.0 ID*2) VH
The liquid quantity is only computed for wet devices
(001, 002, 003, 013). For these cases the exhaust gas
volume (V) will always be the new computed volume.
(c) Chemical Quantity (ton/yr) = P H
5
where P = amount of SO. removed by the device [(ton/day)/(8*shifts)]
(d) Fuel Quantity = fVH
where f = 0.490, if device 019
0.245, if device 020
1.000, if device 021
0.404, if device 022
0.000, all other devices
It should be noted that additional fuel is only used for
the catalytic and direct flame afterburners. The program
assumes that the additional fuel is natural gas.
130
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(e) Disposal Quantity - Emission rate for pollutant in
question (tons/day) times new device efficiency (after ad-
justment) for same pollutant times 365 (days/year).
This is computed for each of the pollutants.
(f) Labor Quantity = LH
Where H = operating time (hr/yr)
L = labor (labor hours/operation hours)
There are four, user input, labor values which relate
to the source size being controlled (small, medium,
large, and extra large). Source size is measured by V,
actual cubic feet of exhaust gas per minute (as corrected).
The program selects the appropriate value as follows:
Use the "small" value for V <_ 40,000
Use the "medium" value for 40,000 < V <_ 250,000
Use the "large" value for 250,000 < V <_ 1,000,000
Use the "extra large" value for V > 1,000,000
For any particular control device, only some of the terms in the above
i
equation will be non-zero. An electrostatic precipitator, for instance,
will not use liquid, chemicals, or additional fuel. The quantity JK how-
ever, will always be calculated.
Operating and maintenance costs for the remaining control devices
cannot be estimated by the above calculations. These devices are generally
more complex (involving sulfur oxide removal), and separate equations have
been developed to compute their O&M expenses. These equations are based
on manufacturers' specifications and operating experience reported in the
literature.
For the three flue gas desulfurization measures considered, the fol-
lowing calculations of operating cost are used.
131
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Device 039 - Catalytic Oxidation
O&M = 0.05'(total installed cost)
+ AB + JK
Where A, B, J, and K are as defined
above.
Device 041 - Dry Limestone
O&M = 365 P (0.17 + 7.0 SC ) + 25,000
c c
Device 042 - Wet Limestone
O&M = 365 P (0.196 + 3.82 SC ) +
130,000 C °
where P = coal burned in ton/day (Source File)
S = coal sulfur content, decimal (Source File)
C = chemical cost in $/ton (input as device data)
The O&M costs associated with the use of sulfuric acid or sulfur
by-product manufacturing as a pollutant control measure (devices 043, 044,
and 045) are computed from the following equation:
O&M - JK - (Purchase Cost)/(Rated Life) -I- y
where, for each device:
J • disposal quantity, as calculated in Item (e) above,
K - input disposal cost
Purchase Cost = value computed in Subsection 3.1, Item (f)
Rated Life » input as device data
y » value as calculated below. The variable P used in these
computations is the percentage concentration of sulfur
dioxide, by volume, in the exhaust gas as given in Sub-
section 3.1, item (f).
132
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Devices 043, 044 - Sulfur ic Acid Plant - Single Contact and
Double Contact Process
Iog1()y = 0.75 log1Qx + a
where y = annual cost (in 10 $)
x = sulfur emission in ton/day
if 0 <_ P < 3.0, then a =• 1.6903
3.0 £ P < 6.0, then a = 1.4445
6.0 <_ P < 10.0, then a = 1.2076
P > 10.0, then a = 1.721
Device 045 - Sulfur Plant
I°g10y =0.81 log1Qx + a
where y =» annual cost (in 10 $)
x = sulfur emission (above)
if 0 £ P < 5.0, then a = -1.210
5.0 <_ P < 7.0, then a = 1.375
P >_ 7.0, then a = 1.435
In addition to the O&M costs described in this Subsection, the program
calculates the cost of necessary cooling of the effluent gas stream prior
to device application. This cost is calculated whenever the temperature
of the gas entering the cooling device (approximated by the exhaust gas
temperature) exceeds 532°K (500°F). The cost computations, performed for
each source assigned device combination, are as follows:
If exhaust gas volume is greater than or equal to 2000 ACFM but les*
than 6800 ACFM,
Cost ($) - 1131.7 [ e['A36 ln (8/1000)] + 124 + .07185 S'
- 71 ?
+ S[(. 0003225 + .000016286 ) H
. .0000019 (.24T - 71.26) H
"* -. "*" •
, ,
«** J
133
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If exhaust gas volume is greater than or equal to 6800 ACFM but less
100,000 ACFM
Cost ($) = 720.17 e
(.668 In (S/1000)]
+ 124 + .07185 S'
-I- S[(.0003225 + .000016286 -24T " 71-2) H
, .0000019 (.24T - 71.2) H + -Q4]
where
S = exhaust gas volume (ACFM)
S1 = volume of cooled gas to control device (ACFM @ 500°F)
= S[526.2 + .023T]/T
H =» operating hours per year
= 365 • (number of shifts/day) • 8
T = exhaust gas temperature (°K)
If the gas volume is less than 2000 ACFM the program will not apply
the device being considered, and will go on to the next assigned device.
If the gas volume is greater than 100,000 ACFM, the program will divide
the ACFM value into equal parts, each of which is less than 100,000 ACFM.
The gas cooling data will then be calculated using the procedure described
above. The resulting cost and cooled exhaust gas volume is then multiplied
by the number^of equal parts to produce the total values for the device.
The costs calculated above combine purchase, installation, and operat-
ing costs for the gas cooling measure (assumed to be of the water spray
type) and are on an annualized basis. The new exhaust gas volume (S') and
new exhaust gas temperature (532°K) become the new source-device character-
istics.
134
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The total annual device cost, output by the program, is then the
annual capital cost (defined in Subsection 3.3) plus the O&M cost and,
if applicable, the gas cooling cost described in this subsection.
3.5 FUEL PARAMETERS AND GENERAL CALCULATIONS
The fuel substitution portion of the Control Cost Program uses the
data items shown in Table A. 3-1 (obtained from the locations indicated).
Prior to entering a specific fuel substitution routine, the program
calculates the following quantities in the manner shown. These quanti-
ties are calculated once for each point source and are used later in the
yarious fuel substitution calculations.
(1) BTU contribution of each fuel burned, B
(a) Bi(BTU/year) = AA ti± (Boiler Eff^ 365*
(2) Annual cost of each fuel burned, P
(a) Pi($/year) = (^ At 365
(3) Potential emission from each fuel burned, E
sc
**
(a) E(ton/day) =• 19.0 A S 10"3
(b) ESR(ton/day) = 79.3 ^ SR 10~6
(c) ESD(ton/day) = 71.8^ SD 10"6
(d) ESG(ton/day) = 0.2 AQ 10~9
(e) EpC (ton/day) = 0.5 AC a ^ 10"3
(f) EpR(ton/day) = 0.5 A^ f2 10"6
tSee Table A.3-1 for subscript identification.
*See Table A.3-2 for (Boiler Eff)i values.
**See Tables A.3-3 and A.3-4 for f.. and f- values, respectively,
135
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Table A.3-1. Fuel Parameters
Symbol
H.
Ni
Ni
MA,
Variable Name
Source ID number
Amount of each existing
fuel burned
Sulfur content of each
existing fuel burned
Heat content of each
existing fuel burned
Ash content of coal
burned
Units
Tons, gallons, cu.
ft. per day*
Percent by weight
BTU per ton, gallon
or cu. ft.*
Percent by weight
(decimal equivalent)
Existing device efficiency
for each pollutant Decimal fraction
Emission rate for each
pollutant
Unit cost of each exist-
ing fuel burned
Sulfur content of each
new fuel available
Heat content of each new
fuel available
Ash content of each new
coal available
Maximum allowable sulfur
content for each fuel type
Tons per day
Dollars per ton
gallon, cu. ft.*
Percent by weight
(decimal equivalent)
BTU per ton, gallon
or cu. ft.*
Percent by weight
Percent by weight
i subscripts refer to type of fuel (C - coal, R - residual
D - distillate^ oil, G - gas)
J subscripts refer to pollutant (S - SO , P - particulate)
Where Obtained
Source data
Source data
Source data
Source data
Source data
Source data
Source data
Region data
Region data
Region data
Region data
Region data
oil,
For coal, oil and gas respectively.
136
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Table A.3-2. Boiler Efficiencies
BTU Range
Annual BTU Output >_ 0.1 x 10'
Annual BTU Output < 0.1 x 10
Coal
.87
.75
Efficiency
Residual Distillate Natural
Oil Oil Gas
.86
.77
.86
.77
.82
.80
NOTE: Boiler efficiencies are utilized in the following manner to
calculate the amounts of new fuel required:
q
1. Assume annual BTU > 0.1 x 10
2. Use efficiencies from first row.
3. Compute: H. A Eff. for each fuel (i) and total them
together
9
4. If total in No. 3 is less than 0.1 x 10 , then the
initial assumption (step 1) was incorrect and the
computation is redone using the set of
efficiencies from the second row.
137
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Table A.3-3. (f^) Coal Partlculate Emission Factors
Process No. Combustion Type £
1
00 All types not listed 15
10 Pulverized, general 16
20 Pulverized, Dry bottom 17
30 Pulverized, Wet bottom without
fly ash reinjection 13
40 Pulverized, Wet bottom with
fly ash reinjection 24
50 Cyclone 2
60 Spreader Stoker without fly
ash reinjection 13
70 Spreader Stoker with fly
ash reinjection 20
80 All other stokers 5
90 Hand fired 20/a*
a = ash content of coal burned, percent by weight (decimal equivalent),
138
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Table A.3-4. (f ) Oil and Gas Particulate Emission Factors
SIC Codes*
Fuel
Residual Oil
Distillate Oil
Natural Gas
4911
8
6.5
15
2xxx, 3xxx
23
15
18
All Other
23
15
19
*A list of Standard Industrial Classification (SIC) Codes and process
Codes are given in Air Quality Implementation Planning Program - Volume I
Operators Manual, Contract No. PH 22-68-60, November 1970.
139
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(g) EpD(ton/day) = 0.5 Ad l^ 10"6
(h) EpG(ton/day) = 0.5 AQ ^ 10"9
S_, SR, SQ and a are all expressed as a percent (i.e., a
number between 0 and 100). The coefficients were obtained
by combining conversion dimensional factors with appropriate
emission factors (generated by HEW).
To insure the compatibility of the input data, the program next com-
pares the input total emission rates (e.) with the calculated fuel emission
rates (E ). This comparison is made as follows (where the emission rates have
have been corrected for any existing control devices):
(ESC + ESR + ESD + ESG) (1 - V = ES
(EPC + EPR + EPD + EPG>
ES EP
If 0.8 < — < 1.2 and 0.8 < — < 1.2, then the input data is
- es - ~ep
assumed to be correct for the purposes of this test. However, if the
ratio of the emission rates is not within these limits for either pollu-
tant, the program terminates operations on that source, prints the follow-
ing data, and begins operating on the next source:
(Source ID Number) - fuel data error - E. = (Calculated Emission Rate)
e = (Input Emission Rate)
After making these calculations, the program begins application of specific
fuel substitution measures.
3.6 SPECIFIC FUEL SUBSTITUTION MEASURES
The program contains three fuel elimination methods (Devices 027,
028, and 029) and three fuel sulfur content limitation methods (Devices
140
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030, 031, and 032). The fuel elimination methods are primarily intended
to control particulate emissions and as a result, are likely to yield
misleading results if applied to sulfur oxides emissions.
The operational characteristics of the fuel substitution measures are
as follows:
(a) (Device 027) Elimination of Coal
This method converts any coal which a source may be burn-
ing to residual oil, distillate oil, or natural gas with
an equal or lower sulfur content. If the source is not
burning coal (i.e., B = 0), this method is inapplicable
and the program moves to the next control method. If the
source is burning coal (i.e., Bc ^ 0), the program examines
the alternate fuel information in the regional data, and
picks the grade of residual oil with the highest sulfur
content less than or equal to the sulfur content of the
coal being replaced. In the event there is no residual
fuel oil in the region data input which satisfies the
above requirements, the program will examine distillate
oil and attempt, in the same manner as above, to select
an alternate fuel. If no distillate oil is available
which meets the requirements, the program switches to
natural gas (if available) as the only possible alternate
fuel. If gas is not available, the program moves to the
next control method. In this case the program prints an
error message to the effect that the specified fuel sub-
stitution could not be made. The quantity of new
(substituted) fuel needed is determined by the require-
ment that the usable heat input (BTU/hr) must remain un-
changed after the fuel substitution.
(b) (Device 028) Elimination of Coal and Residual Oil
This control method operates in the same manner as
Device 027, except that the first fuel switch attempted
(from coal and residual oil) is to the proper grade of
distillate oil.
(c) (Device 029) Elimination of Coal and All Fuel Oil
This control method operates in the same manner as
Device 027, except that all existing fuels are switched
to gas.
141
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(d) (Devices 030. 031, 023) Fuel Limitation Based on Maximum
Allowable Sulfur Content
The three fuel sulfur content limitation methods differ
only in that a unique set of allowable sulfur content
levels may be input for each method. For each method,
an allowable sulfur content for coal, oil and gas must
be input.
The program is designed to replace existing high sulfur
content fuels with lower suflur content fuels (of the
same type if possible) taken from the input region data
base.
The basic series of steps followed by the program for
assigning fuel usage under the various sulfur limitations
are outlined below:
(1) Each existing fuel being burned is examined to deter-
mine if the specified sulfur limitation is exceeded.
(2) If the limit is exceeded, then a search is made of the
regional data base for a fuel of the same type (i.e.,
coal, residual oil, etc.) having the proper percent
sulfur.
(3) If no fuel of the same type meets the requirements,
then alternate fuel types are considered. Alternate
fuel types are examined in the following order until
a suitable fuel is found: Residual Oil (grades 1
through 5), Distillate Oil (grades 1 through 3), and
Natural Gas.
3.7 FUEL SUBSTITUTION COMPUTATIONS
After a suitable fuel grade has been determined, the Control Cost
Program carries out a series of calculations leading to the determination
of the cost and the various fuel use and emission parameters. The first
step is to compute the amount of each new fuel required. This is accom-
plished through use of the annual cost (P.) and annual BTU contribution
(B.), as calculated in Subsection 3.5, The specific procedure for the
fuel elimination and sulfur content limitation methods are as follows:
142
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Devices 027. 028. 029
For these devices, the total usable heat produced by the elimi-
nated fuels (Bi,i = C and/or R and/or D) must equal the total
usable heat produced by the substitute fuel (BNi>i = R or D or
G), i.e.,
Bi " BNi
Substitute fuels are sought having the same or lower
sulfur content as the fuel to be eliminated. If these
requirements cannot be satisfied for a given fuel substi-
tution, the program will attempt to meet the conditions
with a more costly fuel substitution (e.g., for device
027, if residual oil is not acceptable switch to
distillate oil is attempted).
Devices 030. 031. 032
For the sulfur limitation methods, a number of fuels may
be eliminated in favor of a number of others, but the
substitutions are made on a one-for-one basis so that the
usable heat produced by an eliminated fuel will be exactly
matched by the usable heat produced by the corresponding
substitute fuel, i.e.,
B (i=C,R,D, or G) = B (i=C,R, or D)
The process is repeated until the requirements are met or
the fuel types available for substitution are exhausted,
in which case the program will print a message to the
user and go on to the next control method (device) in the
table.
The amount(s) of new fuel(s) is then determined from the following
equation:
BN1
V HN1(Boiler Eff .)HN± (i ~ C>R>D» or G)
The annual cost of each new fuel is then computed as:
PNi = ^i CNi'
Summing P for all new fuels used gives the annual cost of the fuel(s).
The annual costs of the fuels to be eliminated (P ) are then summed. The
total additional annual fuel cost (C ,,) is the total new fuel sum minus
add
the total old fuel sum.
143
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The new (controlled) emission rates are now calculated by use of the
following equations:
6NS = 1 - ES + <19-° V; SNC
S ~
NR
+ (0.2 ANG 10'9) (1 -Ds)
6NP
f2 10~) + (0'5 *ND f2
9*
(0-5 A f Kf)
The decimal efficiencies of the control method are calculated from:
e e
- NS _ NP
NS eg ' NP ~ II
The final calculations for the fuel substitution methods consist
of: (1) summing the total fuel, by fuel category, used by the source
after application of each method and (2) for devices 030, 031, and 032,
calculating the sulfur dioxide allowable emission rate.
The sulfur dioxide allowable emission rate for devices 030, 031,
and 032 is based upon the existing source emissions and upon the existing
and allowable sulfur content. If a source already uses fuel with a sulfur
content at or below the allowable levels then the allowable emission rate
is set equal to existing emissions. If sulfur content levels higher than
the maximum allowable are being used then the following computation is
carried out for each fuel type.
*Thus, in general
1A4 .
-------
Allowable Sulfur Content.
Allowable Emission. = Existing Emission. -—: : • n,. —
i i Existing Sulfur Content.
where the existing emission rate used in this equation represent the emis-
sions from a particular fuel type. These allowable emissions are then
summed by fuel type to provide an overall allowable source emission rate
under the sulfur content limitation specified by the control measure.
145
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APPENDIX B
SOURCES OF CENSUS TRACT INFORMATION REQUIRED FOR RAPA COST/BENEFIT MODEL
1.0 INTRODUCTION
The census data contains information that can be expressed in terms
of census tract attributes. Table B.l-1 contains a list of census tract
attributes most of which have been identified for cost/benefit analyses
1 2
purposes by T. C. Crocker ' (notation follows that of Crocker). This list
although not complete, is fairly extensive. However, only those attributes
indicated by an asterisk have found application in the present model.
2
Crocker has identified additional census tract attributes which are of
importance, but are not available from the censuses of population and
housing. These include:
• AMD - the averages (arithmetic mean) monthly dustfall
by census tract.
• SOT - the average (arithmetic mean) monthly sulfur
dioxide concentration
• CRM - provides a measure of the crime rate: available
for Washington, D. C. from a Congressional hearing
Crime in the District of Columbia (1965).
• SCH - the annual expenditure per student.
• TAX - the tax rate; available for Washington, D. C.,
from D. C. Appropriations for 1965: Hearings before
Subcommittee on Appropriations, U. S. Senate, 98th Con-
gress, 2nd Session Vol. L, W.D.C. (1965) p. 350.
Air Pollution and Housing; Some Findings, by R. J. Anderson and T. D.
Crocker, Paper No. 264, January 1970, Graduate School of Industrial
Administration, Purdue University, Lafayette, Indiana.
2
T. D. Crocker, Private Communication.
147
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The census tract attributes required for the RAPA Cost/Benefit Model
(those indicated by an asterisk in Table B.l-1) are obtainable by the two
methods described in the remainder of this appendix.
148
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Table B.l-1. Census Tract Attributes, Notation and Definitions
Attribute Description
AGE The median age for all males.
ALL* The number of all housing units.
BMT The number of housing units with a basement.
BTH The number of housing units with more than one
bathroom.
CAR The number of units whose residents have no
automobiles available.
CLK The number of clerical and sales workers, i.e.,
the sum of the clerical and kindred workers and
the sales workers classification in Table P-3 of
population and housing censuses.
CTY The number of workers who work in the central city.
DIS* The distance (to the nearest half mile) from down-
town of city center to middle of census tract.
DLP The number of dilapidated housing units.
FRM The number of units of less than four rooms.
MCR* Median contract rent of renter occupied units.
Contract rent is the rent agreed upon regardless
of any furnishing, utilities or services that
may be included.
MFI* Median family income for families only.
MGR* Median gross rent of renter occupied units.
Gross rent is the contract rent plus the
average monthly cost of utilities (water,
electricity, gas) and fuels such as wood,
coal and oil if these items are paid for
by the renter in addition to the contract rent.
MIL* Number of square miles in the census tract
MPV* Median property value of owner-occupied housing
units. Value is the owner's estimate of how
much the property would sell for on today's
market (April 1960 for present study). This
category is restricted to property with only
one housing unit and no-business.
**"Map" refers to map supplied with published census tract tables.
Census
Table
(P-3)
(H-l)
(H-l)
(H-l)
(H-2)
(P-3)
(P-3)
(Map)**
(H-l)
(H-l)
(H-2)
(H-2)
(Map)
(H-2)
149
-------
Table B.1-1. Census Tract Attributes, Notation and Definitions
(Continued)
Attribute
MRM*
MSC
MVD
NEW
NWT*
OLD*
OWN*
POP*
RENT*
RET
SAL
SFH*
SKL
SND
SSK
UEM
Census
Description Table
Median number of rooms. (H-l)
Median school years completed. (P-ll)
Number of units having residents who moved in
from 1958 to March 1960. (H-2)
Number of units ten years old or less. (H-l)
Total number of nonwhite occupied units, i.e.,
the sum of nonwhite owner occupied and nonwhite
renter occupied units. (H-l)
Number of units more than ten years old. (H-l)
Number of all owner occupied housing units (H-l)
Total population (D-l)
Number of all renter occupied housing units. (H-l)
Number of males (white and nonwhite) 65 years
or older. (P-2)
Number of salaried workers, i.e., the sum of
the professional, technical, and kindred workers
and managers, officials, and proprietors, including
farm classifications, (Male and Female summed). (P-3)
Number of single family housing units, i.e.,
housing with only one unit in the structure. (H-l)
Number of skilled workers, i.e., the number of
workers in the craftsmen, foremen, and kindred
workers classification, (Male and Female summed). (P-3)
Number of sound housing units with all plumbing
facilities. (H-l
Number of semi-skilled workers, i.e., the number
of workers in the operatives and kindred workers
classification. (Male and Female summed). (P-3)
Number of unemployed persons. (Male and Female
summed).
150
-------
Table B.1-1. Census Tract Attributes, Notation and Definitions
(Continued)
Census
Attribute Description Table
USK Number of unskilled workers, i.e., the sum of the
private household workers in the operatives and
kindred workers classification, (Male and Female
summed). (P-3)
VAC Number of available vacant housing units. (H-l)
WKR Number of civilian workers, (Male and Female summed). (P-3)
• Tables P-l, P-2, P-3 present population characteristics for
all tracts.
• Tables H-l and H-2 present housing characteristics for all
tracts.
• All tabulated results from:
U. S. Censuses of Population and Housing: 1960
Final Report PHC (1) - 166.
U. S. Department of Commerce
Bureau of Census
151
-------
2.0 BUREAU OF THE CENSUS TABULATED SUMMARIES
A reliable but laborious technique of obtaining the attributes for
each census tract is to reduce them manually from the tabulated summaries
of the censuses of population and housing available from the Bureau of the
Census. Samples of the important tables from this source are shown in
Figure B.2-1. Annotations have been provided to indicate the sources of
the major census tract attributes given in Table B.l-1.
152
-------
Figure B«2-l
Sample Tables from the Censuses of
Population and Housing with Annotations.
153
-------
jAilrruk (*) denote* s'aMt
1'opyUiios prr hoi*e!.cM not s
-i «Ho*i» »).»rt b».«* U Icii i'"*i
in Mu
SUBJtCT
NJTIVE. FO*. 0» Kl/.tO PtRlNTAlf..
UNITED rlK'jOCH
POPULATION in MO'JSFHJLCS
HIAO or pa:«T FAI:LY
CHILD C»iCM 18 Cc K'.tt
POPJLATISN IN SAOU? iJ-'ATEHS . . . . .
• ITM HUSJAKD mo:* us
»ITH c?'> CH-.LCf-f.N ujotn IB . . • .
TMCT
3001
"*•£
12
42
757
10
51
2*
UT
116
5*
222
27
a 917
i 6.1 i
1 364
Jtl
t IA4
1 194
90
30
30
3.C1
1 203
1 222
2C1
59 u
ICO
3" 2
—
• SCHOOL f.-MOLL*-: '<~
TOTAL INSaLLEOi 5 TC 34 ,•£•"$ 0.1 .
PCSSOSS 35 >;»as"o.a »:.; o.vs. . .
HO ICXC3. Utr} COH--l.tf(.:
COLU:C'I 13 3 I-:AF.$
^ rEOIAN JCHCW. VCAP.< CC.'/'LETtD
•rcsiotf^t IN :;:>
"t^SCN: 5 lrc».RJ i'_3 AN3 3VSJ
106
2:i
fau *
"i« >»6
Census Table P-l.
General Characteristics of the
Population by Census Tracts: 1960-Con.
154
-------
(Mr-dim not »!iu\vn whnv I-ISP U IMJ ili:in .SO)
SUBJECT
AGE
13 YfAHS .............
14 YEARS
• :9 YEARS
21 YEAR* AND OVER
13 TO 19 YEARS
20 TO 21 TEARS
45 TO 49 1EARS
TRACT
0001
HALE FEMALE
2 316
40
30
38
36
32
36
34
43
32
34
39
42
40
47
38
46
40
25
32
23
1 561
2 316
202
181
12?
112
til
151
171
160
186
141
105
84
45
• 23
11
AQC 37.0
1 631
34
3»
26
32
30
41
31
36
40
38
35
29
41
49
37
3S
46
28
31
23
29
1 896
2 631
186
165
134
90
148
169
191
187
218
206
IfZ
146
173
77
>T
11
41.8
SUBJECT
70 TO 7u YEARS
75 YEARS AND OVER
MARITAL STATUS
TOVALl 14 YEARS AND OVER .
NON 14 YEARS AND OVER
TRA-:T
00»l
MALE FtXALE
2 167
164
164
199
172
.113
101
102
147
160
153
I7J
iS2
129
ii » 94-J
—*• 79-
—~- 74.
149
12
7
12
9
7
11
10
*
11
T
13
13
12
— *• 11-1
_•- 5"
— *• 3-
41.1
1 114
1 332
17
T9
16
123
27
91
a
»
...
2 U9i
139
I7C
187
157
124
84
13i
1«
184
181
203
173
138
It*
123
137
2
8
7
8
JET10
6
14
T
7
«
IS
17
7
1
9
6
44. «
a 127
439
1 2*1
37
5*
:23
24
12
1
II
I
Census Table P-2.
Age, Color, and Marital Status of the
Population, by Sex, By Census Tracts: 1960-Con.
155
-------
(Bwod aa 25-ponea; umple. Pcnst not «bown wben ban it 1m lhu> 2C£|
..__
UCrl —
SAL,
CLX
3
* gg««LE* 14 YC/RS OLD AND OVER. .
MAAM&0 rOM£N 1N L.F.. WJSBANQ PRES. .
fcCRAFT.'.MCNi FOREMEN* 4 KINDRED iOUKtRS.
b Sf.VICC »KRS,t EXC. P«IV. HOUSE HOLD. •
* CRAFTSMEN. FO«tf£H. * KIN'CRCD lORKEFSi
-SERVICE liCRS.i CXC. P«!V. HOUSEHOLD. •
PRIVATE **QE AND SALARY fQRKCRS* • t •
TRACT
0001
i en
1 IB*
Al*t
1^1 tei
1 «S«
32«
a i2T
831
— "W
— »- 12
1 2f>»
427
93
1 4SB
v^ 17V
• 101
•^> |2i
— *. II*
— fc 103
,-*. 1',
T2
«•• 91
-^ T7I
— «. 2*
,-*-. ftl
-*• 60
• |
1 TO}
312
21
SUBJECT
Fl'RNITUtE 4 L'JM9£ft & ROOD PRODUCTS •
FOOD AS'3 KIKO^EO PnODUC'S
PRINT.. PJSLISH'O,. 4 A>.L!EO If.OOS. .
0*:
-------
f d.i'» I
,.'U|
SU3JECT
TCNU*£i COL'*i WO VACANCT
STATUS
•NKE. . ... :..:;:..;::
FOS SALE ONLY
CO-:3[T|ON *N3 Pt'JMilNS
'.ACMNS OKUT h07 t«T£*
L»C«INS OTMcR PuU-ils; FACILITIES. .
•JTll ALL O.V--HIS1 TACILITiCi ....
LACHM 0TKCR PL'JX^iJiS *»e!LI'l-'i. .
OUAPI3ATE5
94TMP.OOHS
A03.43
' RSO.XS
» R.vo-s
• RCC.'IJ OR X3»E ; .
TB»CT
0001
ALL i io»
41 131
VAC :<,
:a
!b
17
5M6i 6»
i
41
t>t-t» 1
B-^J1 IJO
B7W si:
&
»- li
• » • 141
aii
2->7
2^5
IftRK 5 A
:
suej'cr
UNITS IN STRUCTURE
YEfcft S?R;!tTUH» BUILT
HCATINS riujrvtNT
S'JtLf-IN P01N filTS
OTNSR .MciNS IITH3;rl FuUE
PERSONS
6 PfHSONS OA Mb^t
KCDIANt
PESSONS PCH ROOM
C.50 Cff LESS
0.31 TO 0.15 '
C.7» TO 1.00 '
1 .01 OR POQC
I
TR».T
0001
5rH i 04«
»»»
:J»
10
• • •
N£W 'is
OLOti ^"3
i&
t :.»
MC
20
3
•
rss
.XJ
).V>
:J|
•5C
:.»
>.o
1.09
il«
Table H-2.-YEAR MOVED INTO UNir
OR RENT OP OCCUPIED HOUSING
', AUTOMOBILES AVAILABLE. AND VALUE
UNITS. BY CENSUS TRACTS' 1960-Con.
(iw.« dat^ V.xind on raroplt; lunlJAC. not ir.t»D *.itre t.xw* ij uzrufHci'-n-.; st-e taxt.
Plun ( f-) or u.-.ius (-) a/u-r nurhcr u-Jir*'.t-i mfdi»n »k"%-fr cr U-Iw t^^t n-;mb»r'
SUBJECT
AtL OCCtPJtO UNITS
TEAR HOVED INTO UNIT
AUTOMOBILCS AVAILAOLE
VALU:
T«V:T
OOOl
1 6»
*V0 J6U
311
513
J'.V
»67
2D>
CAR Ml
1 021
1
177
»06
130
5'JBjE.CT
OROSS KEHT
CON TRACT «O!T
rfOU* OXLf.«5
TMCT
too i
«7
KPVu tio
•ki
» » »
• • •
2«
1(U
«4
M
4
»15ft. ^
*CK ''SI
Census Table H-l.
Occupancy and Structural Characteristics of
Housing Units, by Census Tracts: 1960-Con.
157
-------
IMJICT
t|M *oveo INTO wir
AUrOMMILU AVAlLASlt
»*i.Wt
»l3tOCr9 TO M9i933 * * .
•10.030 TC IZ«.933
coNTtucr RIMT
IVtJieT
UAH ftovtc INTO vrttr
AUTOWCSILCS AVAII.A9U
CClTAACT JICST
IMJA*
169 137
o *i«
1T» OH
3 3*»>
IS 93*
TT JT9
• » 495
'U« 00*
**> 76$
IT i3o
• 300 S3>
f|
299 039
•
T 3-»
* *l*
1 **l
If 17*
• 337
• 59
ft 3>0
i 973
i 73>
IT 7»)
12
11?
733
> 74J
* «)>
t 7*1
• *
IT O3
4)
. o*c.
TO JlC
Tl 93*
33k
3 l«2
27 2)3
1* 33*
T 269
11 191
J3 >*09
IT* 33*
• lift
I 73 137
T3
CHV'CHt
VA.
1 912
794
• 109
• ••
31,4
371
t 0*2
ti
106
513
jl
111
97
TOTAL
25 C»)
• 3 *33
• Sfci
i »33
10 T39
21 134
1> «7A
|| 176
19 433
• 3
157
It 001
91
TRACT
0001
t 743
320
2*9
TO
923
•31
T*
690
1 •»
*
||
2)}
3*
12*
1 •*•
U9
i
"|U»
5> 979
3 1M
3) 97*
• 19
U 973
•
290
1 «7«
I T21
T 020
2T »30
119
y i«3
119
TRACT
0002
1 333
jll
• 17
173
*7*
37%
T*
4)1
tsa
14
f 1
113
1)1
_-
1)7
91)
111
-««•«'
;«.,«
4 3)13
2 3**
2 t.S
1 SJ3
4 704
29
201
t 396
t 737
301
131
l« TOO
1 371
J_
103
| 993
•7
.oooi
I 304
373
*17
I *IJ
2«*
j)
4||
lit
1ST
94
t *ll
||
211
Ji»
9*
| 3*-1
91
sitn^
tvi
19 T92
4 *62
f 14)
T 012
r.»
t 104
U 333
27
••
1 SOI
f 39«
1 (33
19 3CO
T 174
20
jl
923
3 2*3
HI
113
T 039
10*
•A
TIACT
OOC4
3*2
90
%j
Vt9
§4
19O
103
34
290
1 **
***
_
12
273
)> COO*
Ti
...
•
}|
t • •
>.
IUI
13 IIT
4 307
4 T«»
3 T.*)
114
4 4)4
1)1
111
II 1)3
tl
3 TIT
1 3)7
1 tT»
)93
11 TOO
I 20)
13
It
111
37)
3it
47
11)
1 IS*
103
IH,«TO,.
TRACT
0003
} Til
| l)l
• 1 04]
373
1 4*1
114
T*
1 lit
3)1
||
t)J
33*
33 OC3*
1 1*3
1*
IS
It
311
T4|
1 OV3
|9t
tit
3 C-l
II)
3T ait
13 C41
10 171
10 I'l
) 144
.
14 341
371
413
a t?i
» in
* 43)
* T31
at 333
10 ID
*|
1T1
TO)
I TO)
a ii«
a 451
173
t*
* ISO
It
).e.
TRACT
000*
a in
4*4
TIS
1 0*3
an
ii
n*
1 Oil
tt
If
1)3
II*
4)3
13 >:>
1 0)3
$
I*
31
141
151
1)1
t)
t)
1 Oil
II
Mi net
COUITTt
19.
VI t9)
34 Til
IT 0?0
13 sr»
3 4J4
11 771
a TT*
• o*a
14 7)7
1 741
4 tl*
II ID
it :it
i DI
3 1)4
IS 103
)) Tl*
3)
407
I *4S
13 o:>
t 4)9
1 T)t
1 141
tl
31 319
TRACT
0007
* 7*1
1 100
I 71*
431
149
I T4I
17*
II
1 )«»
Til
a
§3
III
III
1)1
10 103
3 ItS
|)
I*
|3
1 Itl
at*
»3
III
1 11)
COMTTi
VI.
M 49|
11 3<1
11 11)
1 470
34*151
* 144
1 10)
T III
11 TT3
IT
T»7
I 311
T )5«
• til
4 43)
11 ICO
31 *0)
l|
T|
1 333
10 O!
100
31 307
t|
TH.CT
0001
a t*o
lit
4)3
331
1 IT*
311
to
1 It*
|
§
19
It)
13 CC3»
«7|
||
1C)
Itt
it
lit
r.»
CIX»A!»'
1* I*T
21 199
13 9li
1) CJ7
1 3*7
It 9*>
1 T»
{ 791
44 3tl
71)
1 4»
t 451
14 7j)
It 01'
t 411
II 7J3
1* 1)1
IT
114
497
1 31?
3 T))
4 4)*
3 lit
*7T
1CT
II 3))
II
T««:T
0031
1 I)S
in
ItT
t»:
14J
*4T
4)3
113
1 391
II
II)
137
1 c:>
13 CI3'
...
:o
11
41
|3|
1 M
i: «
lit
Census Table H-2.
Year Moved into Unit, Automobiles Available
and Value or Rent of Occupied Housing Units
by Census Tracts: 1960.
158
-------
Pluj (+) uf cuw (— ) »
* mi\ttiui »bov» u* Lrlu* ihM a
M<CT
n»* novcg INTO UNIT
1UTOHOSIV.I* AVAILABLt
. . VU.UC
6X011 HUT
K101AN 03O.A*! . .
COMT/UCT UlsiT
SUSJCCT
TIA* HOYIO JNTO Wt(T
»VTOH3MIC1 AVAILA91C
XW.U*
OHOSt IC.1T
«txT<« OCC\.»ltO
ooio
1 Til
1 29T
1 liT
60}
2 171
611
*0
1 617
2 027
3
•61
661
• 31
11 100
1 111
12
IT
1 Oil
616
1 010
6}
6*
1 II)
"
ocii
* 3)1
I S97
62*
»J3
•t
i in
1 **T
t .
Tl
Itt
161
to
16
11 030
1 161
76
7tl
VJt
61
1 lit
7»
boil
in
961
111
1 021
lot
t)
341
1 Oil-
II
2*1
271
371
21 390
626
•
11
70
106
111
11
IJT
0021
t 7*1
261
16
1 101
101
7*1
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11
II
1* 100
1 111
• » t
1
11
116
11
11
1 ID
13
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• 1*
919
350
117
• 9
36*
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11
111
27*
12*
• 23 200
1 27)
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11
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31t
32*
121
UT
1 24*
119
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1
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1 177
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1 30*
761
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1 126
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39
129
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1 67)
14*
It*
197
19
1 111
tit
t
10
17
67
11
1 41k
I
611
111
71
17
61
1 •?)
64
Census Table H-2. Year Moved into Unit, Automobiles Available,
and Value or Rent of Occupied Housing Units,
by Census Tracts: 1960. (Continued)
159
-------
3.0 NTIS MAGNETIC TAPES
The National Technical Information Service (NTIS) of the Department
of Commerce offers magnetic tapes containing information pertinent to
various business and scientific fields of interest. Most types are in BCD
mode and are available as: (1) 7-track, 556 or 800 characters per inch
(cpi), odd or even parity; or (2) 9-track, 800 cpi, odd parity. Included
in this series are tapes containing information from the censuses of
population and housing.
Information is given in a format that lists each item of information
together with its location. Information includes family relationship
within a household, school enrollment of children, income, employment
status, number of personnel employed by industry and in agriculture,
tenancy and vacancy status of housing units, value of property, heating
fuels used, and numbers of workers classified according to type of work.
Tapes currently available are listed in Table B.3-1.
160
-------
Table B.3-1
List of NTIS Tapes of Population and Housing Data
( 1960 for the United States by Standard Location Area )
PB-170 771 — Population and Housing Data for the United States by
Standard Location Areas, 1960 Census: Hawaii, Vermont,
Idaho, Nebraska, Arkansas, Delaware, Rhode Island,
South Dakota, Montana, Colorado, 1 reel.
PB-170 772 — Same Title, Louisiana, North Carolina, Indiana, 1 reel.
PB-170 773 — Same Title, Minnesota, Mississippi, South Carolina,
Oklahoma, District of Columbia, 1 reel.
PB-170-774 — Same Title, Ohio, 1 reel.
PB-170-775 ~ Same Title, Nevada, Washington, 1 reel.
PB-170-776 — Same Title, Michigan, Wisconsin, 1 reel
PB-170-777 — Same Title, Pennsylvania, 1 reel.
PB-170-778 — Same Title, Alaska, West Virginia, Oregon, Alabama,
Florida, 1 reel.
PB-170-779 — Same Title Iowa, Maryland, Kansas, Maine, North Dakota,
New Mexico, Wyoming, 1 reel.
PB-170-780 — Same Title, Texas, Connecticut, 1 reel.
PB-170-781 — Same Title, Virginia, Tennessee, Kentucky, Arizona, 1 reel.
PB-170-782 — Same Title, Missouri, Utah, New Hampshire, New Jersey, 1 reel.
PB-170-783 — Same Title, Georgia, Massachusetts, 1 reel.
PB-170-784 -- Same Title, Illinois, 1 reel.
PB-170-785 — Same Title, New York, Part I, 1 reel.
PB-170-786 — Same Title, California, Part I, 1 reel.
PB-170-787 -- Same Title, New York, Part II, California, Part II, 1 reel.
161
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APPENDIX C
PRO FORMA DAMAGE FUNCTION DEVELOPMENT
1.0 INTRODUCTION
Linear relations have been developed by the Office of Air Programs
for predicting the multiple effects of specific pollutants (sulfur dioxides
and particulates). These damage functions are based on the estimates com-
puted by Barrett and Waddell in "The Cost of Air Pollution Damages: A
Status Report"**. This study reviewed approximately 36 research studies of
air pollution damages that were in various stages of completion. About a
third of the studies have been published, another third completed and
unpublished and a third in progress.
The Barrett-Waddell survey estimated annual national air pollution
damages (1968) due to the pollutants: sulfur dioxide, particulates, photo-
chemical oxidants and nitrogen oxides. Particulates and sulfur dioxide
account for 88 percent of the total damage.
Four major damage categories were analyzed, and damage cost estimates
were determined for each category. These were: (1) residential property;
(2) materials; (3) health; and, (A) vegetation.
The sources of the pollutants included: stationary fuel combustion,
transportation, industrial processes, solid waste disposal and miscellaneous
sources. The damages attributed to each source category were also reported.
* Taken from: A Pro Forma Air Pollution Damage Function. Environmental
Protection Agency, Office of Air Programs, (Unpublished Paper).
** HEW, NAPCA, Raleigh, North Carolina, (Unpublished Paper).
163
-------
Descriptions of the points are as follows:
(C.), = Per capita cost of effects for pollutant, i, in 1968.
(C.)0 = Per capita cost of effects of pollutants from
'i'2
miscellaneous, uncontrollable sources (i.e.,
background concentrations) for pollutant, i.
(X.).. = Average annual urban concentration of pollutant, i,
considered to be a background level.
(X.)» = Average annual concentration of pollutant, i, found
in the nation's urban areas in 1968.
The development of the four coordinates, C.. , C X , X , are dependent
upon the following general data inputs:
(1) Urban Population—the U. S. Urban population for 1968.
(2) Damage Cost Estimates
A. The total national air pollution damage cost
estimate for sulfur dioxide and particulate
emissions (1968).
B. The total national air pollution damage cost
estimate for sulfur dioxide and particulate
emissions from miscellaneous sources (i.e.,
background levels).
(3) Pollution Concentration Estimates
A. The weighted average pollution concentration
(sulfur dioxide and particulates) to which the
1968 U. S. urban population was exposed.
B. The background pollutant concentration for
sulfur dioxide and particulates.
The specific data gathered for the development of the damage function
were as follows:
(1) Urban Population
The "current" definition of urban population was used in
determining the statistics for 1968. The "current"
definition refers to "all the population residing in
urban-fringe areas and in unincorporated places of
164
-------
2,500 or more.*" In 1960, the urban population was
125,269,000, or, 69.9 percent of the nation's
population.
In 1970, 73.5 percent of the nation's population was
urban. An urban population of 144,000,000 was determined
for 1968 by interpolating between the 1960 and 1970
statistics.
(2) Damage Cost
A. In the Barrett-Waddell report, the 1968 annual damage
costs of particulates and sulfur dioxides are estimated,
based on the measured air quality for that year.
B. Barrett and Waddell report that 9.6 tons/year of
particulates and 0.6 tons/year of sulfur dioxides
originate from miscellaneous sources (see Table C.2-1).
It is assumed that these emissions contribute to the
background (i.e., uncontrollable emission) concentra-
tions of pollutants. Thus, 33.9 percent of particulate
and 1.8 percent of sulfur dioxide emissions are considered
uncontrollable (i.e., emissions generated from construction
activities, dust off the street or ground, etc.).
Assuming a direct relationship between quantity of
emissions generated and the cost of damages, background
damage cost estimates can be determined for particulate
and sulfur dioxide emissions, respectively.
(3) Pollution Concentration
A. The most difficult task in developing the damage function
was estimating the weighted average pollution concentration
(WAPC) for the nation. The WAPC is the concentration to
which the average urban resident is exposed. WAPC is
determined by the following formula:
n
(WAPC) = - PC (1)
where :
PT = total U. S. urban population
P. = urban population in region i.
Ci = weighted average pollution concentration (WAPC)
in region i.
* Department of Commerce, Bureau of the Census, U. S. Census of Population;
1960, Vol. I.
** Analogous to the quantity PC defined on a political jurisdiction and
regional basis in Chapter 2.
165
-------
Table C.2-1. Estimates of Nationwide Emissions, 1968
(10 tons/yr)
Transportation
Fuel combustion in
Stationary Sources
Industrial processes
Solid waste disposal
Miscellaneous
Total (1968)
CO
63.8
1.9
9.7
7.8
16.9
100.1
Particulates
1.2
8.9
7.5
1.1
9.6
28.3
SO
X
0.8
24.4
7.3
0.1
0.6
33.2
HC
16.6
0.7
4.6
1.6
8.5
32.0
NO
X
8.
10.
0.
0.
1.
20.
*Source: Division of Air Quality and Emissions Data, BCS, NAPCA.
166
-------
Available "population" and "air quality" statistics were used to
determine WAPC. However, these data were insufficient to develop WAPC
without following additional assumptions:
(1) Air quality data was not available for all the
urban regions in the nation (i.e., for the population of
144 million identified by the 1968 Census). The source
of air quality data was a recently published data book,
Regional Aerometrics Data Book; Sulfur Dioxides and
Particulates by OAP's Division of Air Quality and
Missions Data. In this document, 176 "air sheds"
are identified; 31 "air sheds" being designated air
quality control regions and the remaining being SMSA's.
All of the nation's 235 currently designated SMSA's are
included.
A total of 61 "air sheds" had sulfur dioxide concen-
trations for 1968; 132 "air sheds" had particulate concen-
trations reported. The population of the 61 and 132 air
sheds were 108.7 million and 132.4 million, respectively.
Consequently, it was necessary to make the assumption that
the air pollutant concentrations reported for the identified
air sheds were absolutely identical to the air quality to
which the 144 million people in the urban population were
exposed (i.e., the data for the 61 S0? and 132 particulate
air sheds were representative of all urban areas).
(2) The air quality data reported in the Data Book was not an
average pollution concentration for the region. There is
no way of knowing where the monitoring sites were located
in the air sheds in 1968. Although some air sheds had as
167
-------
many as seven or eight air quality measurements reported,
there was no way of statistically determining the average
regional pollution concentration.
The problem of obtaining a representative air quality estimate is
illustrated in Figure C.2-2. A cross-sectional slice of a metropolitan
area is illustrated. Three hypothetical sampling sites are shown—S,, S_,
and S.. With the Data Book, there is no way of knowing where the sites
are located or how representative the measurements are relative to the
air quality for the remainder of the region.
The desirable air quality estimate is also represented in Figure C.2-2
as the average regional pollution concentration (ARPC). This estimate is
the same as the WAPC, except the estimate is regional rather than national
in scope. Naturally, the ARPC will fall somewhere between the maximum
regional pollution concentration and the background level.
The assumption was made that the air quality concentration reported
in the Data Book was equal to ARPC (i.e., the C indicated above). There
were some qualifying conditions. The Data Book reported air quality mea-
surements taken at urban, suburban and rural monitoring stations. Only
the urban measurements were used in the analysis. In cases where more
than one urban measurement was reported, the arithmetic average of all
urban stations was determined to be the ARPC.
168
-------
Pollutant
Concentration
(Mg/m3)
S., i = 1,2,3 = Sampling Stations
Suburbs
Center City
Suburbs
Maximum Regional
Pollutant Concentration
Average Regional
Pollutant Concentration
(ARPC)
Background Pollutant
Concentration
Geographical Cross-Section of Metropolitan Area
Figure C.2-2. Cross-Section of Metropolitan Area Air Quality
-------
The sulfur dioxide estimates were reported as annual arithmetic
averages. Suspended particulates estimates were reported as average
geometric averages*. The WAPC was calculated for sulfur dioxide and
particulate emissions, using equation (1). The results were:
(WAPC)SQ = 96 yg/m3
x
(WAPC)part< = 97 yg/m3
It was interesting to compare these results with the direct sum of
all ARPC for the 61 and 132 relevant air sheds reporting such data. The
averages without weighting were:
SO = 40.4 ug/m3
X
Suspended particulates = 90.5 yg/m3.
The vast difference between the non-weighted and population-weighted
averages results from the existing high concentration of pollutants in the
high population regions. ARPC for particulates ranged from 29 to 331
yg/m3. The ARPC range for sulfur dioxides was 5 to 350 yg/m3.
Background concentration for sulfur dioxide and particulates were
determined from various sources. The calibration procedures of the IPP
model predicts a background level. Also, measurements taken on the perdm-
eter of air quality control regions are often considered to be near back-
ground levels. The values used in developing the functions were:
Sulfur Dioxide Background: 10 yg/m3
Suspended Particulate Background: 40 yg/m3
*Since the standard deviation of the measurements used to determine the
annual geometric mean were not available, there was no way of converting
the geometric mean to the arithmetic mean. Thus, it was assumed that the
geometric mean was equal to the arithmetic mean.
170
-------
The tentative (pro forma) damage functions that were derived are
linear approximations of the damage cost estimates, on a national basis, as
related to urban pollution concentrations. It was assumed that all damage
costs are realized in the urban areas of the country (as defined by the
Bureau of the Census). This is reasonable, since the great majority of the
people and economic activity are located in these areas where the pollutant
concentrations are the greatest. Vegetation damage was estimated less than
one percent of the total annual damage. However, since many of the "urban
areas" do include agricultural croplands, this estimate was incorporated
into the damage function.
The linear damage functions relate the per capita annual damage cost
of each pollutant, sulfur dioxide and particulates (in $/per capita/year)
to pollutant concentration in ug/m3.
2.0 DEVELOPMENT OF THE NATIONAL DAMAGE FUNCTION
In general, the linear damage function is determined by two points,
A and B. Point A represents the average per capita damage cost to the
urban residents exposed to the 1968 pollution concentration levels of the
nation's AQCRs. Point B represents the minimum air pollution damage re-
sulting from miscellaneous sources (construction activities, urban activity,
natural sources, etc.).
From this description, it is easy to see that four coordinates are
needed to determine the function:
Cl
C2
Xl X2
Definition of Linear Damage Function
171
-------
The data and assumptions thus far reported were inadequate to
determine damage functions for suspended particulates and sulfur dioxide.
The coordinates for developing the two linear functions are reported in
Tables C.2-2 and C.2-3. The National Damage Functions are shown in Figure
C.2-3. Due to the tentative character, they are referred to as the Pro
Forma Damage Functions. They serve to provide a demonstration of the use
of the Damage Module in the Benefits Segment of the RAPA Cost/Benefit Model.
Conversely, the RAPA Cost/Benefit Model will serve to test the reasonable-
ness of the present formulation.
172
-------
Table C.2-2. National Total Annual Costs of Pollution
For Types Of Pollutants and Effects in 1968.
Effects
SO
Particulates Oxidant
NO
Total
Residential
Property
Materials
Health
Vegetation
Total
2,808
2,202
3,272
13
8,295
2,392
691
2,788
7
5,878
5,200
1,127 732 4,752
6,060
60 40 120
1,187 772 16,132
Source: "The Cost of Air Pollution Damages: A Status Report," Barrett, I.B.,
and Waddell, T. E., HEW, NAPCA (unpublished report).
173
-------
Table C.2-3
Coordinates for Damage Function Development
Variables
Suspended
Particulates
$40.80/capita
$13.80/capita
10 ug/m3
97 yg/m3
Sulfur
Dioxide
$57.50/capita
$ 1.03/capita
40 ug/m3
96 yg/m3
174
-------
250
a
4J
•H
O.
O
o>
eu
to
o
CJ
00
OJ
I
o.
cd
M
II)
PU
II
>•
200
150
100
100 200 300
Weighted Air Pollution Concentration (pg/m3)
Figure C.2-3. Pro Forma Damage Functions for S09 and Particulates
-------
APPENDIX D
DEMONSTRATION RESULTS TO THE POLITICAL JURISDICTION LEVEL
The cost/benefit results of the demonstration at the regional level,
along with a description of each of the output variables, is presented in
Section 3.0. In this appendix, the results for each of the seven political
jurisdictions which make up the NCIAQCR are listed; these results were
aggregated to obtain the regional summaries presented in Section 3.0 (and
repeated here to make the appendix a complete data package). Tables D.l-1
through D.l-8 present Damage Module output; Tables D.2-1 through D.2-8
present Property Value Module output, and Tables D.3-1 through D.3-8 pre-
sent Assignment Module output. Interpretation of the various aggregates,
averages, etc., presented in these tables should include reference to
Sections 2.0 and 3.0 where the various weighting factors used in preparing
this output are described. In particular, the cautionary note in Section
3.0 regarding the Assignment Module should be reviewed, i.e., the results
are contrary to what is expected and apparently because of an omission in
the assignment algorithm.
177
-------
Average Air Quality
Weighted With
oo
Strategy
Existing
S-10
S-14
S-15
S-ll
P articulates:
Existing
P-l
P-3
P-18
P-2
Total
Emission
(Tons /Day)
660.6
463.4
332.3
238.0
21.0
160.3
116.0
71.7
61.7
47.4
Respect To
Population
(Mg/ra3)*
65.0
57.8
52.8
49.3
36.4
69.4
64.4
60.8
57.5
54.1
Point
Emission
(Tons/Day)
542.0
344.ff
243.9
176.6
0.0
84.7
54.0
32.0
25.0
10.7
Damage
($ x 106)
73.6
64.0
57.5
52.9
36.0
55.0
50.8
47.5
44.4
41.2 ,
Benefit
($ x 106)
0.0
9.6
16.1
20.7
37.6 ,
0.0
4.7
8.0
11.1
14.3
Control Cost
($ x 106)
0.0
-3.5
6.1
14.6
104.5
0.0
0.5
4.0
10.8
13.9
E(People)(ue/m3) u
E(People)
Table D.l-1. NCIAQCR - Regional Damage Values Summary
-------
VO
Average Air Quality
Weighted With
Strategy
fV
Existing
S2-10
S3-14
S4-15
S5-11
Particulates:
Existing
P2-1
P3-3
P4-18
P5-2
Total
Emission
(Tons /Day)
156.2
138.4
129.7
110.8
63.5
54.9
32.9
32.9
27.0
23.9
Respect To
Population
(Mg/m3)*
77.4
71.2
63.1
59.4
37.2
77.4
70.8
67.2
61.2
56.8
Point
Emission
(Tons /Day)
92.7
74.9
66.2
47.3
0.0
31.9
9.9
9.9
4.2
0.-9
Damage
($ x 106)
34.5
31.4
27.3
25.4
14.2
24.2
21.8
20.6
18.4
16.8
Benefit
($ x 106)
0.0
3.1
7.2
9.1
20.3
0.0
2.4
3.6
5.8
7.4
Control Cost
($ x 106)
0.0
-3.696
0.971
3.768
27.214
0.0
0.441
0.441
8.415
6.336
£(People)(ug/m3)
E(People)
Table D.l-2. NCIAQCR: Damage Summary for Political Jurisdiction //I - District of Columbia
-------
oo
o
Average Air Quality
Weighted With
Strategy
fV
Existing
S2-10
S3-14
S4-15
S5-11
Particulates:
Existing
P2-1
P3-3
P4-18
P5-2
Total
Emission
(Tons /Day)
174.1
88.2
62.6
47.7
13.2
23.6
22.0
10.1
10.6
10.2
Respect To
Population
(Mg/m3)*
54.2
46.6
4A.2
41.0
35.9
62.3
59.7
55*4
55.3
52.7
Point
Emission
(Tons /Day)
161.0
75.0
49.5
34.5
0.0
13.7
12.1
0.2
0.7
0.3
Damage
C$ x 106)
10.2
8.5
7.9
7.3
6.1
8.4
8.0
7.3
7.3
6.8
Benefit
($ x 106)
0.0
1.7
2.3
2.9
4.1
0.0
.4
1.1
1.1
1.6
Control Cost
($ x 106)
0.0
-0.052
0.873
2.315
13.642
0.0
-0.034
-7.377
-7.786
-7.323
£(People)(ug/P3)
£(People)
Mg/m3
Table D.l-3. NCIAQCR: Damage Summary for Political Jurisdiction //2 - Montgomery County
-------
CD
Average Air Quality
Weighted With
Strategy
S02:
Existing
S2-10
S3-14
S4-15
S5-11
Particulates:
Existing
P2-1
P3-3
P4-18
P5-2
Total
Emission
(Tons /Day)
193.5
100.1
71.0
52.7
15.0
30.3
28.6
18.5
20.7
19.9
Respect To
Population
(M8/m3)*
69.8
61.1
55.6
51.7
37.0
74.9
66.9
61.4
58.4
56.3
Point
Emission
(Tons/Day)
178.5
85.1
56.0
37.7
0.0
12.7
11.0
0.9
3.1
2.3
Damage
C$ x 106)
14.3
12.2
10.9
10.0
6.6
10.8
9.5
8.6
8.1
7.7
Benefit Control Cost
($ x 106) ($ x 106)
0.0
2.1 .
3.4
4.3
.7.7
0.0
1.3
2.2
2.7
3.1
0.0
0.286
1.616
3.249
26.032
0.0
0.066
2.216
1.397
2.216
£(People)(ug/m3)
£(People)
ug/m;
Table D.l-4. NCIAQCR: Damage Summary for Political Jurisdiction //3 - Prince Georges County
-------
00
to
Strategy
S°2;
Existing
S2-10
S3-14
S4-15
S5-11
Particulates
Existing
P2-1
P3-3
P4-18
P5-2
E (People)
Average Air Quality
Weighted With
Total Respect To Point
Emission Population Emission
(Tons/Day) (Mg/m3)* (Tons/Day)
55.7
55.7
44.4
33.1
5.0
10.9
10.9
10.9
6.9
3.3
(UB/ra3) , ,
54.6
47.2
44.7
42.4
35.8
62.0
59.4
57.4
55.9
51.6
50.7
50.7
39.4
28.2
0.0
7.7
7.7
7.7
3.7
Oil
Damage
C$ x 106)
4.9
4.1
3.9
3.6
2.9
4.0
3.8
3.6
3.5
3.2
Benefit Control Cost
($ x 106) ($ x 106)
0.0
.8
1.0
1.3
'2.0,
0.0
.2
.4
.5
.8
0.0
0.0
0.733
1.893
18.393
0.0
0.0
0.0
0.032
1.205
£(People)
Table D.l-5. NCIAQCR: Damage Summary for Political Jurisdiction #4 - Alexandria City
-------
oo
Strategy
S02:
Existing
S2-10
S3-14
S4-15]
S5-11
Particulates:
Existing
P2-1
P3-3
P4-18
P5-2
Average Air Quality
Weighted With
Total Respect To Point
Emission Population Emission
(Tons/Day) (ug/m3)* (Tons/Day)
12.3
12.3
10.8'
9.8
7.1
4.8
4.8
4.8
4.8
3.4
47.8
39.6
38.5
35.2
34.5
55.1
52.9
51.5
50.9
48.5
5.3
5.3
3.7
2.7
0.0
1.5
1.5
1.5
1.5
0.1
Damage
($ x 106)
6.7
5.3
5.1
4.5
4.4
5.6
5.3
5.1
5.0
4.7
Benefit Control Cost
($ x 106) ($ x 106)
0.0
1.4
1.6
2.2
2.3
0.0
.3
.5
.6
.9
0.0
0.0
0.840
1.125
1.844
0.0
0.0
0.0
0.0
0.784
£ (People) (ug/m3) a ,3
£(People)
Table D.l-6. NCIAQCR: Damage Summary for Political Jurisdiction //5 - Arlington County
-------
00
Average Air Quality
Weighted With
Strategy
fV
Existing
S2-10
S3-14
S4-15
S5-11
Particulates:
Existing
P2-1
P3-3
P4-18
P5-2
Total
Emission
(Tons /Day)
14.1
14.1
13. A
12.8
11.3
22.7
21.4
21.4
21.4
20.9
Respect To
Population
Cwg/m3)*
53.8
46.3
43.9
40.9
35.4
63.8
61.3
59.3
54.6
50.6
Point
Emission
(Tons /Day)
2.8
2.8
2.1
1.5
0.0
8.7
7.4
7.4
7.4
6.9
Damage
C$ x 106)
2.7
2.2
2.1
1.9
1.6
2.3
2.2
2.1
1.9
1.7
Benefit Control Cost
($ x 106) ($ x 106)
0.0
.5
.6
.8
1.1
0.0
.1
.2
.4
.6
0.0
0.0
0.341
0.514
0.935
0.0
0.033
0.033
0.033
0.955
£(PeoPle)(ue/m3)
Z(People)
Mg/m3
Table D.l-7. NCIAQCR: Damage Summary for Political Jurisdiction #6 - Fairfax County
-------
CO
Ln
Average Air Quality
Weighted With
Strategy
S02:
Existing
S2-10
S3- 14
S4-15
S5-11
Particulates:
Existing
P2-1
P3-3
P4-18
P5-2
Total
Emission
(Tons /Day)
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
Respect To
Population
(yg/m3)*
47.3
40.4
39.1
36.0
34.8
55.9
53.7
52.2
51.8
49.1
Point
Emission
(Tons/Day)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.'o
Damage
($ x 106)
0.26
0.21
0.20
0.18
0.17
0.22
0.21
0.20
0.20
0.19
Benefit Control Cost
($ x 106) ($ x 106)
0.0
.05
.06
.08
.09,
0.0
.01
.02
.02
.03
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
£(People)(ug/m3)
I(People)
ug/m3
Table D.l-8. NCIAQCR: Damage Summary for Political Jurisdiction //7 - Falls Church City
-------
S02 Strategy/
Particulate Strategy
Exist ing /Exist ing
10/1
14/3
15/18
11/2
Average S02
Air Quality
Weighted With
Respect To
Population
(pg/m3)*
66.7
59. 8
54/4
40.8
36.5
Average
Particulate
Air Quality
Weighted With
Respect To
Population
Cug/m3)*
70.9
65.6
61.8
58.1
54.6
Total
Type I
Property
Value
$x!06
5,329.
5,401.
5,448.
5,489.
5,602.
Total
Benefit
$xl06
0.0
72.
47.
41.
113.
Average
Type I
Property
Value
$
22,365
22,664.
22,863.
23,034.
23,507.
Average
Benefit
Per
Household
$
0.0
499.
199.
171.
473.
S02
Control
Cost
$xl06
0.0
-3.5
6.1
14.6
104.5
Partic-
ulate
Control
$xi06
0.0
0.5
4.0
10.8
13.9
Total
Control
Cost
$xl06
0.0
-3.0
10.1
25.4
118.4
oo
Z(People)(ug/m3)
Z(People)
Ug/m:
Table D.2-1. Type I Property Values: NCIAQCR Regional Summary
-------
oo
S02 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
11/2
Average SC>2
Air Quality
Weighted With
Respect To
Population
(ug/m3)*
79.0
73.0
64.5
60.7
37.2
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(ug/m3)*
78.5
71.4
67.8
61.5
57.1
Total
Type I
Property
Value
$x!06
1,298.
1,313.
1,328.
1,342.
1,393.
Total
Benefit
$x!06
0.
15.
15.
14.
51.
Average
Type I
Property
Value
$
20,117.
20,349.
20,588.
20,793.
21,586.
Average
Benefit
Per
Household
$
0.0
232.
239.
205.
793.
S02
Control
Cost
$xl06
0.0
-3.696
0.971
3.768
27.214
Partic-
ulate
Control
$X106
0.0
0.441
0.441
8.415
6.336
Total
Control
Cost
$xl06
o.o
-3.255
1.412
12.183
33.550
^(People)(pg/m3)
E(People)
Ug/nr
Table D.2-2. Type I Property Values: Political Jurisdiction 1, District of Columbia Summary
-------
oo
oo
S02 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/12
11/2
Average S02
Air Quality
Weighted With
Respect To
Population
Cug/m3)*
54.6
47.6
45.0
41.8
36.0
Average
Particulate
Air Quality
Weighted With
Respect To
Population
Cug/m3)*
63.1
60.5
55.9
55.8
53.1
Total
Type I
Property
Value
$xl06
1,427.
1,444.
1,456.
1,463.
1,482.
Total
Benefit
$x!06
0.
17.
12.
7.
19.
Average
Type I
Property
Value
$
25,098
25,400.
25,615.
25,746.
26,073.
Average
Benefit
Per
Household
$
0.0
302.
215.
131.
328.
S02
Control
Cost
$xio6
0.0
-.052
.873
2.315
13.642.
Partic-
ulate
Control
$xl06
0.0
-.034
-7.377
-7.788
-7.323
Total
Control
Cost
$xl06
0.0
-.086
-6.504
-5.471
6.319
^(People) (ug/m3) = . s
E(People) M8/
Table D.2-3. Type I Property Values: Political Jurisdiction 2, Montgomery County, Md. Summary
-------
oo
\o
S02 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/8
11/2
Average SC>2
Air Quality
Weighted With
Respect To
Population
(pg/m3)*
73.1
64.8
58.5
54.4
37.3
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(pg/m3)*
78.4
69.2
63.3
59.6
57.3
Total
Type I
Property
Value
$xl06
978.
994.
1,006.
1,015.
1,044.
Total
Benefit
$x!06
0.
16.
12.
9.
29.
Average
Type I
Property
Value
$
20,382.
20,713.
20,973.
21,154.
21,763.
Average
Benefit
Per
S02
Control
Household Cost
$
0 .0
331.
260.
181.
609.
$x!06
0.0
.286
1.616
3.249
26.032
Partic-
ulate
Control
$.10°
0.0
.066
2.216
1.397
Total
Control
Cost
$x!06
0.0
.352
3.832
4.646
2.216 28.248
*E(People)(ug/m3)
E(People)
Pg/nr
Table D.2-4. Type 1 Property Values: Political Jurisdiction 3, Prince Georges Co.,Md..Summary
-------
VO
O
S02 Strategy/
Particulate Strategy
Exist ing /Exist ing
10/1
14/3
15/18
11/2
Average S02
Air Quality
Weighted With
Respect To
Population
tPB/m3)*
54.1
47.0
44.5
42.3
35.8
Average
Particulate
Air Quality Total
Weighted With Type I
Respect To Property
Population
Cyg/m3)*
61.9
59.3
57.4
55.9
51.6
Value
$xiQ6
453.
458.
460.
463.
470.
Total
Average
Type I
Property
Average
Benefit
Per
S02 Partic- Total
Control ulate Control
Benefit Value Household Cost
$x!06 $ $ $x!06
0.
5.
2.
3.
7.
22,992.
23,259.
23,389.
23,519.
23,861.
0.0
267.
130.
130.
342.
0.0
0.0
.733
1.873
18.333
Control Cost
$xlOG $x!06
0.0
0.0
0.0
0.032
1.205
0.0
0.0
.733
1.928
19.588
£(People)(ug/m3)
E(People)
Table D.2-5. Type I Property Values: Political Jurisdiction 4, Alexandria, Va. Summary
-------
S02 Strategy/
Particulate Strategy
Exis.t ing /Exist ing
H^
vO
H^
10/1
14/3
15/18
11/2
Average S02
Average
Particulate
Air Quality Air Quality Total
Weighted With Weighted With Type I
Respect To Respect To Property
Population Population Value
(pg/m3)* (pg/m3)* $xI06
48.3
40.2
39.0
35 7
•J ~t • /
34.7
55.
53.
52.
C I
-J-L .
48.
6
5
0
7
1,001.
1,017.
1,021.
1,028.
1,033.
Average
Type I
Total Property
Benefit Value
$X106 $
0.
16.
4.
7.
5.
24,297.
24,646.
24,772.
24,947.
25,071.
Average
Benefit S02 Partic- Total
Per Control ulate Control
Household Cost Control Cost
$ Sxin6 .<*vin6 6^1 n6
0.0
349.
126.
175.
124.
T --— —
0.0
0.0
.840
1.125
1.844
Y **«tv
0.0
0.0
0.0
0.0
.784
V^ J.U
0.0
0.0
Q/,n
. otu
1.125
2.628
(People)(ug/m3)
Z (People)
Mg/nr
Table D.2-6. Type I Property Values: Political Jurisdiction 5, Arlington Co., Va., Summary
-------
vO
N)
S02 Strategy/
Particulate Strategy
Exist ing /Existing
10/1
14/3
15/18
11/2
Average S02
Air Quality
Weighted With
Respect To
Population
Cpg/m3)*
53.7
46.4
44.0
41.0
35.5
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(pg/m3)*
64.3
61.7
59.8
54.6
50.7
Total
Type I
Property
Value
$xl06
130.
132.
132.
134.
135.
Total
Benefit
$x!06
0.
2.
0.
2.
1.
Average
Type I
Property
Value
$
20,531.
20,802.
20,914.
21,119.
21,387.
Average
Benefit
Per
Household
$
0.0
271.
112.
205.
268.
S02
Control
Cost
$xl06
0.0
0.0
.341
.514
.935
Partic-
ulate
Control
$x!06
0.0
.033
.033
.033
.955
Total
Control
Cost
$x!06
0.0
.033
.374
.547
1.890
I(People)(ug/m3)
E (People)
Mg/m-
Table D.2-7. Type I Property Values: Political Jurisdiction 6, Fairfax Co.,Va. Summary
-------
S02 Strategy/
Particulate Strategy
Exist ing /Exist ing
10/1
14/3
15/18
Q
11/2
Average S02
Air Quality
Weighted With
Respect To
Population
(Ug/m3)*
47.3
40.4
39.1
36.0
34.8
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(Ug/m3)*
55.9
53.7
52.2
51.8
49.1
Total
Type I
Property
Value
$x!06
44.
44.
44.
45.
45.
Total
Benefit
$x!06
0.
0.
0.
1.
0.
Average
Type I
Property
Value
$
24,887.
25,299.
25,333.
25,491.
25,646.
Average
Benefit
Per
Household
$
0.0
412.
34.
158.
155.
S02
Control
Cost
$x!06
0.0
0.0
0.0
0.0
0.0
Partic-
ulate
Control
$xl06
0.0
• 0.0
0.0
0.0
0.0
Total
Control
Cost
$x!06
0.0
0.0
0.0
0.0
0.0
£(People)(ug/m3)
E (People)
Pg/nr
Table D.2-8. Type I Property Values: Political Jurisdiction 7, Falls Church, Va. Summary
-------
SO 2 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
t- 11/2
Average SO 2
Air Quality
Weighted With
Respect To
Population
(VR/m ) *
66.7
59.8
54.4
50.8
36.5
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(yg/m3) *
70.9
65.4
61.8
58.1
54.6
Total
MPV
C$$106)
4.172.
4,172.
4,172.
4,172.
4,172.
Average
MPV
(S)
17506.
17506.
17506.
17506.
17506.
Total
Type I
Bid
Before
Shift
($xlO 6)
5,329
5,401.
5,448.
5,489.
5,602.
Average
Type I
Bid
Before
Shift
'<$)
22365.
22664.
22863.
23034.
23507.
Total
Type I
Bid
After
Shift
($^106)
4,879.
4,941.
4,982.
5,019.
5,100.
Average
Type I
Bid
After
Shift
. ($)
20,475.
20,735.
20,907.
21,066.
21,402.
Total
Difference
C$xlO G)
-450.
-460.
-466.
-469.
-501.
Average
Difference
($)
-1890.
-1929.
-1956.
-1968.
-2105 .
<£>
*E(people)(MB/ni3)
E(People)
Vg/m3
Table D.3-1. Adjusted Type I Property Values: NCIAQCR, Regional Summary
-------
SO 2 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
£ 11/2
Average SO 2
Air Quality
Weighted With
Respect To
Population
(ug/m 3) *
79. 0
73. 0
64.5
60.7
37.2
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(pg/m 3) *
78.5
71.4
67.8
61.5
57.1
Total
MPV
($xip6)
982.
982.
982.
982.
982.
Average
MPV
($)
15227.
15227.
15227.
15227.
15227.
Total
Type I
Bid
Before
Shift
($xlO 6)
1,298.
1,313.
1,328.
1,342.
1,393.
Average
Type I
Bid
Before
Shift
($)
20117.
20349.
20588.
20793.
21586.
Total
Type I
Bid
After
Shift
($xlQ6)
1,708.
1,724.
1,750.
1,772.
1,869.
Average
Type 1
Bid
After
Shift
($)
26467.
26726.
27126.
27471.
28972.
Total
Difference
($xiQ 6)
410.
411.
422.
431.
477.
Average
Difference
($)
6350.
6377.
6538.
6679.
7386.
*E(People)(ug/m3)
E(People)
Table D.3-2. Adjusted Type I Property Values - Political Jurisdiction 1, District of Columbia
-------
SO 2 Strategy/
Particulate Strategy
Exist ing/ Exist ing
10/1
14/3
15/18
11/2
Average SO 2
Air Quality
Weighted With
Respect To
Population
(yg/m 3) *
54.6
47.6
45.0
41.8
36.0
Average
Particulate
Air Quality
Weighted With
Respect To
Population
O-g/tn3)*
63.1
60.5
55.9
55.8
53.1
Total
MPV
($ xlO 6)
1,181.
1,181.
1,181.
1,181.
1,181.
Average
MPV
($>
20775.
20775.
20775.
20775.
20775.
Total
Type I
Bid
Before
Shift
($xlO 6)
1,427.
1,444.
1,456.
1,463.
1,482.
Average
Type I
Bid
Before
Shift
($)
25098
25400.
25615.
25746.
26074.
Total
Type 1
Bid
After
Shift
($x!06)
957.
959.
966.
963.
934.
Average
Type I
Bid
After
Shift
($>
16840
16880.
16990.
16943.
16438.
Total
Difference
($*106)
-469.
-484.
-490.
-500.
-578.
Average
Difference
($)
-8258.
-8520.
-8625.
-8803.
-9636.
'£(People)(ug/m3)
I(People)
pg/m3
Table D.3-3. Adjusted Type I Property Values - Political Jurisdiction 2, Montgomery County
-------
SO2 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
« 11/2
Average SO 2
Air Quality
Weighted With
Respect To
Population
(ijg/m ) *
73.1
64.8
58.5
54.4
37.3
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(pg/m 3) *
78.4
64.2
63.3
59.6
57.3
Total
MPV
($xl06)
716.
716.
716.
716.
716.
Average
MPV
($)
14936.
14936.
14936.
14936.
14936.
Total
Type I
Bid
Before
Shift
($ xlO 6)
978.
994.
1,006.
1,015.
1,044.
Average
Type I
Bid
Before
Shift
'<$)
20382.
20713.
20973.
21154.
21763.
Total
Type I
Bid
After
Shift
($xl06)
794.
813.
837.
849.
912.
Average
Type I
Bid
After
Shift
($)
16550.
16955.
17449.
17703.
19019.
Total
Difference
($xlO 6)
-184.
-180.
-169.
-166.
-132.
Average
Difference
($)
-3831.
-3759.
-3524.
-3451.
-2744.
*E(People)(ug/m3)
E(People)
pg/m3
Table D.3-4. Adjusted Type I Property Values - Political Jurisdiction 3, Prince Georges County
-------
SO 2 Strategy/
Particulate Strategy
Exist ing/ Exist ing
10/1
14/3
15/18
H- 11/2
Average SO 2
Air Quality
Weighted With
Respect To
Population
(ug/m ) *
54.1
47.0
44.5
42.3
55.8
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(ug/m3) *
61.9
59.3
57.4
55.9
51.9
Total
MPV
($ xlO 6)
357.
357.
357.
357.
357.
Average
MPV
(S)
18111.
18111.
18111.
18111.
18111.
Total
Type I
Bid
Before
Shift
($ $10 6)
453.
458.
460.
463.
470.
Average
Type I
Bid
Before
Shift
<$)
22992.
23259.
23389.
23519.
23861.
Total
Type I
Bid
After
Shift
($xlO&)
345.
345.
342.
340.
339.
Average
Type I
Bid
After
Shift
m
17510.
17554.
17367.
17286.
17196.
Total
Difference
($xlO 6)
-108.
-112.
-119.
-122.
-131.
Average
Difference
($)
-5482.
-5705.
-6022
-6229.
-6665.
00
*E(people)(yg/m3) _ / 3
L(People) WB'
Table D.3-5. Adjusted Type I Property Values - Political Jurisdiction 4, Alexandria
-------
SO 2 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
11/2
<£>
Average SO 2
Air Quality
Weighted With
Average
Particulate
Air Quality
Weighted With
Total Average Total Average
Type I Type I Type I Type I
Bid Bid Bid
Population
(pg/m 3) *
48.3
40.2
39.0
35.7
34.7
Respect TO
Population
(pg/m 3) *
55.6
53.5
52.0
51.3
48.7
Total
MPV
(SxlQ 6)
798.
798.
798.
798.
798.
Average
MPV
($)
19366.
19366.
19366.
19366.
19366.
Before
Shift
($xlO 6)
1,001.
1,017.
1,021.
1,028.
1,033.
Before
Shift
'($)
24297.
24676.
24772.
24947.
25071.
After
Shift
($x!06)
900.
922.
911.
917.
872.
After
Shift
m"
21836.
22357.
22114.
22241.
21154.
Total
Difference
f$xi 0 f>)
-101.
-96.
-110.
-112.
-161.
Average
Difference
{$)
-2461.
-2319.
-2658.
-2706.
-3916.
*E(People)(ug/m3)
E(People)
Pg/m3
Table D.3-6. Adjusted Type I Property Values - Political Jurisdiction 5, Arlington County
-------
SO 2 Strategy/
Particulate Strategy
Exist ing /Exist ing
10/1
14/3
15/18
11/2
to
0
Average SO 2
Air Quality
Weighted With
Respect To
Population
(pg/m 3) *
53.7
46.4
44.0
41.0
35.5
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(pg/tn 3) *
64.3
61.7
59.8
54.6
50.7
Total
MPV
($xlO 6)
102.
102.
102.
102.
102.
Average
MPV
($)
16100.
16100.
16100.
16100.
16100.
Total
Type I
Bid
Before
Shift
($xlO 6)
130.
132.
132.
134.
135.
Average
Type I
Bid
Before
Shift
($)
20531.
20802.
20914.
21119.
21387.
Total
Type I
Bid
After
Shift
($x!06)
139.
140.
139.
141.
138.
Average
Type I
Bid
After
Shift
. ($)
21968.
22062.
21975.
22322.
21745.
Total
Difference
($xlO 6)
9.
S.
7.
8.
2.
Average
Difference
($)
1437.
1260.
1062.
1203.
359.
0 *E( People) (pg/m 3) = .
E(People)
Table D.3-7. Adjusted Type I Property Values - Political Jurisdiction 6, Fairfax County
-------
SO 2 Strategy/
Particulate Strategy
Existing/Existing
10/1
14/3
15/18
11/2
Average SO 2
Air Quality
Weighted With
Respect To
Population
(ug/m 3) *
47.3
40.4
39.1
36,0
34.'8
Average
Particulate
Air Quality
Weighted With
Respect To
Population
(ug/m 3) *
55.9
53.7
52.2
51.8
49.1
Total
MPV
($xl06)
35.
35.
35.
35.
35.
Average
MPV
($)
20208.
20208.
20208.
20208.
20208.
Total
Type I
Bid
Before
Shift
($xlO 6)
44.
44.
44.
45.
45.
Average
Type I
Bid
Before
Shift
($)
24887.
25229.
25333.
25491.
25646.
Total
Type I
Bid
After
Shift
C$xl06)
37.
37.
37.
37.
36.
Average
Type I
Bid
After
Shift
($)
21035.
21397.
21207.
21269.
20797.
Total
Difference
($xl06)
-7.
-7.
-7.
-7.
-S.
Average
Difference
($)
-3852.
-3832.
-4126.
-4222.
-4848.
NJ
O
*E(people)(pg/m3)
ECpeople)
Mg/m3
Table D.3-8. Adjusted Type I Property Values - Political Jurisdiction 7, Falls Church
-------
APPENDIX E
USER'S MANUAL FOR THE BENEFITS SEGMENT
OF THE RAPA COST/BENEFIT MODEL
1.0 INTRODUCTION
The existing version of the RAPA Cost/Benefit Model Segment is a
prototype of the cost/benefit computer model originally conceived for the
RAPA program. As a prototype, it has been designed in complete modular
form, allowing easy modification and expansion. It is expected that desir-
able changes will become apparent as the model is applied in the context of
actual studies. In fact, the results of the NCIAQCR demonstration presented
in this report have already pointed the way toward future program development.
Figure E.l-1 illustrates the overall system flow for the RAPA Cost/Bene-
fit Model. It also provides a convenient cross-reference for the figures and
subsections of this appendix which pertain to the individual modules and their
input/output. As currently designed, the Benefits Segment consists of an
interface module (C0NVRT), and a series of analysis modules (DAMAGE, PR0P,
ASSIGN). The Interface Module provides the only automatic data processing
interface with the Implementation Planning Program, which serves as the Cost
Segment. Each of the analysis modules are completely independent of one
another; they individually receive input from the Interface Module and a
common census tract attribute data deck.
The remaining sections of this chapter present input formats, complete
sample outputs, program listings, Job Control Language (JCL) cards and other
information of assistance to the program user. All of the modules are
written in F0RTRAN IV (Level G) and are designed to run on an IBM System
360 computer with a monitoring system (the machine employed for the demon-
stration was a model 50). The presentation in this appendix assumes that
203
-------
N>
O
•P-
CONTROL STRAT-
EGIES SUMMARIES
(CONTROL COSTS,
GROUND LEVEL
POLLUTANT CON-
CENTRATIONS)
Figure E.l-1. Overall System Flow
-------
all required input is in the form of punched cards. However, if a disk
pack is available at the user's facility, the JCL cards can be readily
modified so that all module interfaces occur via disk (or magnetic tape) .
This approach was actually followed for the demonstration runs.
2.0 CENSUS TRACT ATTRIBUTE DATA
The data deck of census tract attributes provides a common input for
all of the analysis modules of the Benefits Segment. Two data cards are
required for each census tract in the region, plus a title card (one per
region). Consequently, for the NCIAQCR demonstration, a total of
(2 x 366) + 1 = 733 census tract attribute cards were required.
The complete format information for the title card and the two data
cards is given in Table E.2-1. In the table, KCT is the individual census
tract identification number. The quotients Ql and Q2 are used to test for
the different categories of census tract property values (see Section 3.5);
Ql is used to distinguish Type I and Type II census tracts, and Q2 is used
to test for Type III and Type IV census tracts, i.e.,
SFH
01 - 02
Q1 - MIL ' Q2 ALL '
The above parameters (P0P, MIL, SFH, ALL), as well as the others listed in
Table E.2-1, have been identified in Section 2.3 are are listed in Table
E.3-1. In general, the information given on the first census tract attri-
bute card is required for identification purposes and output information.
The second card contains the attributes (already in natural log form) used
in the regression equations.
205
-------
Table E.-2-1.
Format Information for Census Tract Attribute Data Cards
Parameter
Columns
Format
CARD 1(ONE CARD ONLY PER REGION)
TITLE1
-left justified,
CARD 2
KCT
(Blank)
Ql
Q2
P0P
MIL
SFH
ALL
0WN
RENT
CARD 3
KCT
(Blank)
MPV
MGR
MCR
Ln(MFI)
Ln(DLP)
Ln(0LD)
Ln(NWT)
Ln(DIS)
Ln(MRM)
1-80
beginning in
1-9
10
11-16
17-22
23-30
31-38
39-46
47-54
55-62
63-70
1-9
10
11-18
19-25
26-32
33-40
41-48
49-56
57-64
65-72
73-80
20A4
column three
2A4.A1
IX
F6.2
F6.3
F8.2
F8.2
F8.2
F8.2
F8.2
F8.2
2A4.A1
IX
F8.2
F7.2
F7.2
F8.3
F8.3
F8.3
F8.3
F8.3
F8.4
Repeat cards 2 and 3 for each census tract in the region.
206
-------
The individual analysis modules only read into core a subset of the
attributes given on these cards. The remaining sections of this appendix,
on the individual modules, indicate the specific attributes used.
207
-------
3.0 INTERFACE MODULE
3.1 DESCRIPTION
The Interface Module (C0NVRT) accepts receptor point pollutant
concentration data (particulate matter or sulfur dioxide) in punched card
form, as produced by the Regional Strategies Segment of IPP*, and calcu-
lates the corresponding mean concentrations for each census tract (CTPC)
in the region. The CTPC data are output for use in the analysis module
of the Benefits Segment (Figure E.l-1).
3.2 JOB CONTROL LANGUAGE AND DECK SET-UP
Figure E.3-1 illustrates the JCL and sample deck set-up for C0NVRT.
The deck set-up indicates the presence of source programs and object pro-
grams. In practice, the user may want to run all source decks (e.g., if
a code modification has been made requiring recompilation), all object
programs or a combination of both. The last option is a possibility
since the C0NVRT module has three main parts: the DRIVER or main program,
C0NVRT subprogram and subroutine 0RDER. If the user confines code modifi-
cations to any one of these parts, he need only recompile the source deck
for that part; the remaining program parts can be in the form of object
(compiled machine language) decks. It is recommended that the user retain
the JCL as shown and include or exclude the source or object decks as
desired.
*A similar punched card deck is output from the IPP Air Pollutant Concen-
tration Segment, but it is in a format which is incompatible with the
Benefits Segment.
208
-------
JOB SETUP FOR CGNW MOOEL
//CUUVHT FXEC PHOC-FOKTGClU
//FOKT.SYSIN DO •
RECKS
//LKEO.SYSIN 00 *
OJJECT DECKS
TRANSFf.HM DATA DECK
//ai.FT05F002 00 *
AIK gUALITY DATA DECK t\ (FRuM I PI1)
AIK OUALITY CATA DECK (2 |Fi
-------
The object and/or source decks are followed by the transform data
deck and the IPP air quality deck(s) (receptor point pollutant concentra-
tion data). The example shows four air quality decks. C0NVRT utilizes
the F0RTRAN END option which permits the user to process, in sequence, from
one to 999 individual air quality/strategy decks produced by the Regional
Strategies Segment of IPP. He need only include the JCL cards illustrated
being sure to increase the sequence number by one for each deck and ending
with the //G0.FT05FXXX DD DUMMY card and End Of File (/*) as shown. The
sequence number is the last three digits in the above expression, signified
by XXX. Thus, in order to process "N" air quality decks, the last portion
of the program deck should be:
//G0.FT05FXXX DD *
AIR QUALITY DATA DECK "N"
/*
//G0.FT05FYYY DD DUMMY
/*
, where XXX=N+1 and YYY=N+2.
For more specific information on JCL, the user is referred to the
appropriate IBM manuals. In addition, the systems programmers at the
user's computing facility should be consulted about special features, etc.
The format for the transform data deck is shown in Table E.3-1.
210
-------
Table E.3-1.
Formats for Transform Data Cards
Parameter
Columns
Format
(BLANKS
JPJ
(BLANK)
JCT
JSCT
(BLANK)
NN(<6)
M(l)
M(2)
M(3)
I
2-3
4
5-7
8
9
10
11-15
16-20
21-25
IX
12
IX
13
11
IX
11
15
15
15
M(NN)
36-40
15
See Figure,E.3-3.
LIN FT05F001 DD *
(NCT cards required)
211
-------
3.3 DIMENSIONS AND INPUT DATA FORMATS
The listing for the DRIVER or main program of the Interface Module
is shown in Figure'E.3-2. This portion of the program contains the only
dimension information (Figure E.3-2 has values for the NCIAQCR demonstration
which must be altered to meet specifics of the AQCR or SMSA of interest.
The cards that require dimension changes are indicated by an asterisk in
column 80. The principal dimensions are given by:
NCT/XXX/-The number of census tracts, plus one,
NRP/YYY/-The number of receptor points.
For the NCIAQCR region demonstration, there were 366 census tracts. There-
fore, XXX was set equal to 367 in the dimension statement. YYY was set
equal to 300. The variables: N,JPJ,JCT,JSCT,CTPC and IDCT (Figure E.3-2)
are then dimensioned the same as NCT. RPPC is dimensioned the same as NRP.
The second dimension in the array M is set equal totthe value of NCT; the
first dimension is the maximum number of receptor points (6) that may be
associated with a given census tract for the purposes of transforming to
census tract pollutant concentrations (see Section 3.3.2).
The input/output devices are identified by the data sets:
LIN(X)-input, i.e., card reader.
L0UT(Y)-output, i.e., printer ,
LOUT(2)-output, i.e., card punch
In the listing, X=5, Y=6 and Z=7.
The transformation of receptor point pollutant concentration data
into census tract pollutant concentration values has been discussed in
Chapter 3 (Section 3.3). The program has been designed to accept up to
and including six different receptors in association with each census
212
-------
K1RTHA.M IV C LEVEL 19
MAIN
DATE « 71133
13/56/2*
C DRIVER FOR CONVERSION ROUTINE
t
C
0001
oooz
DIMENSION MI6.367I ,NI 3671 ,JPJ( 3671 ,JCT 13671, JSCTI 3671 ,RPPC< 300 1, »
1 CTPCI367I.IDCTI367) *
C
DATA LIN/5/, LOUT/6/. HO/7/ ,NCT/ J67/ .NUP/ 300/ *
C
C
C NCT • 366 * 1 •
C
0033
C
CALL CONVRT 1 LIN, LOUT ,L 1 O.NCT .NRP.M, Ni JP J, JCT , JSCT . RPPC.CTPC. 1 OCT 1
C
C
300*
OOPS
STOP
C
C
END
Figure E.3-2 DRIVER for Interface Module - Program Listing
213
-------
tract, when calculating these CTPC values. Table E.3-2 lists the complete
data formats for the transform data cards. Figure E.3-2 illustrates the
prepared data form used to list receptor numbers of the receptor points
selected for the transform.
In Table E.3-2, JPJ is the political jurisdiction number, JCT is the
census tract number, and JSCT is the sub-census tract number. NN is the
total number of receptor points associated with that census tract for
transformation purposes; NN is less than or equal to six. The NN values of
M(J) identify these receptor points by the numbering scheme given in Chapter
3 (Section 3.3.2). There should be a total of NCT data cards in the trans-
form data deck.
The receptor point pollutant concentration values are produced by IPP
as punched card output. Table E.3-2 provides the complete format data for
the air quality data decks indicated in Figure E.l-1. Cards 1 and 2 are
not produced by IPP and must be added by the user to the front of the deck
(i.e., to the NRP Type 3 data cards from IPP).
The format notation in this table and all other accompanying tables
of this appendix follow standard IBM manual notation*. For example, 15
indicates a five place integer, F5.2 indicates a five place fixed point
decimal number (including decimal point and sign, if any) with two places
after the decimal point, etc. The notation P2F8.0 indicates a F0RTRAN
scale factor applied to an F8.0 number. In this case, the input value is
divided by 100 automatically. In an output format, the value would be
multiplied by 100 before printing. The notation (P)F8.0 indicates an
implied scale factor (see IBM reference). The variables X and Y are the
IBM Systems Reference Library, Job Control Language, Form C28-6539-9,
Tenth Edition, July 1969.
214 -
-------
Table E.3-2.
1
pair
per
region
NRP
data
cards
Receptor Air Quality Data Card Formats
Parameter
Columns
CARD 1
TITLE 1-80
-centered title Information
CARD 2
CARD 3
BACKGR
X
Y
PC
1-5
1-8
9-16
17-26
Format
20A4
F5.2
P2F8.0
(P2)F8.0
(P2)F10.0
215
-------
UTM position coordinates of the receptor and PC is the pollutant concentra-
tion (S0_ or particulates) in micrograms per cubic meter.
The block of data cards described in Table E.3-2 would follow the
//G0FT05F002 DD * card in the JCL (Figure E.3-1). Corresponding data decks
would follow FT05F003 DD *, FT05F004 DD *, etc. However, no data cards are
to follow FT05F005 DD DUMMY.
3.4 OUTPUT AND PROGRAM LISTINGS
The principal output of the Interface Module is the CTPC data deck,-
containing NCT cards. Table E.3-3 lists the data formats for these cards,
a single title card is also output. The parameters in Table E.3-3 are as
follows: I is a census tract sequence number (for user convenience only),
IPJ is the political jurisdiction number, ICT is the census tract number,
ISCT is the sub-census tract number and PC is the census tract pollutant
concentration value (CTPC).
In addition to the punched card output, C0NVRT produces printed
listings of the receptor point pollutant concentration (RPPC) input data
corresponding to Table E.3-2 and the CTPC output data corresponding to
Table E.3-3. Sample printed outputs for the NCIAQCR demonstration using
the EXISTING SO conditions are shown in Figures E.3-4 and E.3-5. Complete
program listings of the DRIVER, C0NVRT subprogram and subroutine ORDER are
given in Figures E.3-6.and E.3-7.
216
-------
n*rr ,
PRORI FM NO _ . ,.
HO OF CA«P<
COMPUTATION AND DATA REDUCTION CENTER /
80 COLUMN FREE KEY PUNCH FOB
1I2I1141SI6171819 HOll 11 121 1 31141151 16|I7|1B|19|20 I 21| 22!23|24|2S! 26|27|28|29|30|31 |32|33|34|3S |J6 |37|M|3»140|41 142|43|44|43| 46| 47]4e| 49| if
01 0
-------
Table E,'.3-3.
Census Tract Pollutant Concentration Output Data Formats
Parameter
Column Position
Format
CARD 1
TITLE 1-80 20AA
-centered title information, one card per region
NCT
cards
CARD 2
I
IPJ
ICT
ISCT
(BLANK)
PC
1-5
6-10
11-15
16
17-20
21-30
15
15
15
11
4X
F10.3
218
-------
RECEPTOR POINT POLLUTANT CliNCENTKAT ICINS — INPUT
MM:) Eft
1
i
3
4
5
6
7
o
4
IT
11
12
13
I".
li
IS
17
H
H
2">
>1
?>
2i
".'
25
><>
2f
'3
2'J
T>
11
<'
< \
V.
. JS
Ifc
»7
IS
19
4-'
<.!
<>'
*}
44
4>
44
47
4H
49
NASHINOTDN. D.C,
X-COUR')INATE
(KILOMEIERSI
ZiO.OO
ZbO.CT
?5P.n
250.00
PiO.OO
2S0.01
25C.cn
26b.OO
2(>i>.CO
?hS.OO
Zu^.m
765. CO
265. CT
2fc5.ni
280.00
28". 00
280. C?
2BC.O.O
2HO.CO
2flO.CO
2HO.CO
2"b.15
2<>b.0.1
205. r,C
295.00
295.00
295. 00
295.CO
310.00
110.00
310.00
lin.nc
3io.no
310. C"
310. CO
325.05
325.00
325.00
325.00
325.00
325.00
375.0D
3*0. CO
340.00
34C.CO
340.00
340.00
340.00
34C.OO
.. EXISTING -- SULFUK UUXIOE
Y-COOfc[l|NArE
I Kl LU.-U: TfcKbl
4265.00
4211". 00
4 2 -15. fir.
411". O^
4325. OC
4'14C.nC
4 15s. 30
4265. DC
42»?.OC.
".7MS.OI;
4-3 in. oo
4J2r).OC
414J.OC
4 VjS.OP
42ob.OO
.42d0.nc
4295..0C
4Jin.r«:
4325. CC
4140.00
4J5b."0
4^/.5.00
<.^HO.OO
42')b.OC
4 J 1C. 00
4320.00
4J4.:.'3C
4 tSb.^O
4265. or
'.2'IC. OC
4295.0C
431C.OO
432b.CO
4340.00
43bb.OO
4265. Of
42HO.OC
4205. C.P
4310.00
4320.00
4340. OC
4 155. "0
4265.00
42HC.OO
4205.00
4310. OC
4325.00
4340.00
4355.00
P3LLUTANT CONCE^TKiFIJN
(MICKLJGCAMS I'EK CU.I1C MEItRI
2?. 21
20.2'.
20.31
20. 37
20.29
2r .28
20.21
20. 48
2'.'.46
20.60
20.72
2". 70
20.62
20.45
2?. 93
23.98
21.25
21. 39
21. 32
21.15
21.13
22.43
22. So
22. 76
22. 79
23. H9
22.25
22. T8
22.67
24 . '. J
26. Ht)
27. 32
25.45
24. 14
22.93
22. 75
25.14
42.43
79.27
3U.44
27.83
24. 99
23.33
26. 51
29. 4H
29.58
31.95
30. 1 1
2U.47
Figure E.3-4. Printed Input RPPC Data Summary, C0NVRT
219
-------
CEMSUS TRACT PlILLUTANT CnNCENTRATIUNS — flUTPUT
MASH1NI.TU*. Q.C.. EXISTING — SULFUR DIOMDE
BACKGROUND • 20.00 ( MICKUOKAMS CEK CUU1C METEKI
.WHER POLITICAL CHNSUS POLLUTANT CONCENTRATION
JURISOICTMN T-tACT (MICh'IGRAMS CFIt CUUIC Mt TE^I
1.
*
*
*
9
C)
n
\2
1 4
U
16
1 7
1 3
19
20
21
11
71
?<,
25
26
27
2d
79
10
31
'12
11
3*
15
.10
17
13
V»
0
<•! ..
*2
<>}
<.*
<••>
*6
47
<,a
i
2
3
1
5
h
7
6
0
IP
1 1
12
14
!<.
15
16
1 7
1«
IS
20
21
22
21. 1
23.2
2«i
2b
26
27
2H
2-1
30
31
32
31
34
J5
16
37
33
3;)
41
41
42
43
4
65. 30
56. Hd
58.98
56.65
54.08
56. AS
h 1. 77
56. at)
fc 1.40
i8.5
-------
FORT R AN. I y
000 1
"0002"
000)
~ooo«r " "
ooos
0006
' OOOT
0008
0009
0010
0011
0012
0011
001*
G .LEVEL. .1?... CO.NYRT P.AIE_5. 711W OttlUU
SU8RUUMNE CONVRT ( LIN, LOUT, LIOtNCT, NRP, M.N.JPJ, JCT.JSCT ,RPPC,
1 CTPC.IOCTI
C
C ••••••••••»«••••*»«••«»•••••«••«•«•*««•••••••••»•••••»••••*•«••••••
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c- •-
c
c
c
c
10
c
20
c
c
30
c
c
c _
c
c
TITLE! CONVRT
AUTHOR! B. GOLDSTEIN
TRH SYSTEMS GROUP
WASHINGTON OPERATIONS
COMPUTER SYSTEM! IBM SYSTEM 360/MOOEL 50
LANGUAGE USED! FORTRAN IV - G LEVEL
ABSTRACT! TO CONVERT RECEPTOR POINT POLLUTANT
CONCENTRATIONS IRPPCI
TO CENSUS TRACT
POLLUTANT CONCENTRATIONS ICTPC).
•*•**•*•**•««•**»«•»•»•»*»»«»•»•»»••«•«•»»*»*•••»•••«••*«•»•*••••
DIMENSION TITLE (201 ,M(6. NCTI .NINCT 1 , JPJ INCT 1 , JCT (NCT) , JSCTCNCT 1 ,
RPPCINRPI ,CTPC(NCTI , 10CTINCTI
KCT = 0
00 10 l-i~,NCT
RCAO(LIN.1100.END«20I JP Jl 1 1 . JCT 1 I 1 .
NIII-NN
-------
jum*N iv c LevEk, n
.-IMVtL
_6Att_-_U16A
._fl6/jj^2_6.
0015
0016
0017
ooia
0019
"002"0
0021
0022
0023
0024
002S
0026
0027
0028
0029
0030
0031
0032
0033
.0034
00 35
0036
0037
0031
'. t
C
C
c
._._£
C
40
C
c
c
so
c
60
c
c
c
c
c
c
c
"c
c
70
c
. .._. —
c
C
eo
c
c
c
c
00 40 l-l.NUP
MEA&lLlNi l400tENO*60l XiViPC
ftPPClll-PC
IFI (COUNT. LT. 491 GO TO 40
WR1TEILOUT, 21001 TITLE
ICOUNT'O i
CONTINUE
ICOUNT«ICOUNT»1
MR1TEILOUT,2200I I.X.V.PC
.
CONTINUE
CONTINUE
00 80 I'l.KCT
SUM-0.0
»on-o.o
NN*NII)
00 70 L-liNN
SU1-SUH»RPPC(NIL, 1 1 1
AOO*AOO»1.0
CONTINUE
PC«SUN/AOO»BACKG«
" ~"
CTPC(H«PC
inCTI II-JPJ1 1 >»1000C»JCT(I I»10»JSCT( II
CONTINUE
CALL OaOEA (KCT, IOCT.CTPCI
Figure|E.3-6. C0NVRT Subprogram, Interface Module-Program Listing (Cont'd)
222
-------
FORTRAN
0019
0040
0041
00*2
0041
0044
004S
0046
004T
0048
0049
OOSO
OOM
0052
00))
0054
005*
0056
0057
OOSH
0059
0060
0061
0062
0063
IV C LEVEL
C
C
C
C.
C
C
C
90
C
C '
C
• c
• c
c
c.
c
• c
c
c
c
100
c
._.._e
110
c .
c
c
c
120
c
c
19 CONVRT DATE • T1169 06/17/26
MR ITEILOUT, 23001 TITLE, 6KKGR
MRITEILIO. 12001 TITLE
ICOUNT-0
00 110 I«1,KCT
IFIICOUMT.LT.4tl CO TO 90
riRITEILOUT, 23001 TITLE. BACKGR
ICOUNT-0
CONTIMOE . ;
ICOUNT-ICOUNT«l
PC'CTPCIII .
10-IOCTIII
IPJ- ID/10000
IO>ID-IPJ*10000
.ICT«IO/10
ISCT-IO-ICT*\0
MIT(( Lin. 24001 I.IPJilCTtlSCT.PC
IFI1SCT.EO.OI GO TO 100
MRITEILOUT.2SOOI .1 , IPJ,ICT, I.SCT.PC .
CO TO 110
•CONTINUE
MR ITEILOUT .76001 I.IPJ,ICT,PC
COMTINUE
CO TO )0
CONTINUE
RETURN
Figure E.3-6|. C0NVRT Subprogram, Interface Module-Program Listing (Cont'd)
223
-------
OUTRAN IV G LEVEL 19
CONVRT
DATE = 71169
06/ 17/26 ,
0064
0065
0066
0067
C
C
1100
C
1200
C
1300
C
K.OO
C
C
FORMAT ( IX, I 2, IX, I 3, 11, IX, 11, 61 51
FORHATI20A4I
FORMATIF5.2I
FURMAT(2P2F8.0iF10.0>
0068
J069
0070
)071
1072
2100 FORMAT!1 1' i
1 'RECEPTOR POINT POLLUTANT CONCENTRATIONS — INPUT'//
2 27X.20AW/
i 26X,' NUMBER' ,llX,'X-CaORDINATE',UX,'Y-COOROINATE',<.X,
* 'POLLUTANT CONCENTRATION'/
5 }2x,2< 11X,' (K.IIOMETEKSI • I ,2X, _ _
6 " 'IMICROGRAMS PER CUBIC METtRI'/l
C
2200 FO<6Xll4,14XlF8.2l15X,F8.2tllX,F10.2>
C
2300 FURHATI'1'(«1X,
1 "CENSUS TKACT POLLUTANT CONCENTRATIONS — OUTPUT'//
2 ' 27X,20A<,/
3 43X, 'BACKGROUND «'tF6.2,< (MICRUO^AMS PEK CUBIC METEH»'//
* 2"»X,'NLMBER'.lOX.'PCLlTICAL', UX,-CENSUS',7X,
5 'POLLUTANT CONCENTRATION'/
6 <.*X, 'JUKI SOI CT ION' ,9X, ' TRACT1 ,6X,
7 MMICROORAMS PER CUbIC METEk»'/l
c"
2400 FORMAT!JI5.I 1.4X.F10.3I
C
2500 FORHATI29X, I<.,16X,I2,14X,l,n,llXfF10.2)
C .
2oOO
)07<.
END
Figure E.3-6. C0NVRT Subprogram, Interface Module-Program Listing (Cont'd)
22A
-------
FORTRAN
IV G LEVEL
3001
\4 UHUER lUATC • 71114 OH/ 33/43
SUBROUTINE ORDER IN.IA.AI •
C
C
C
C
C
r
C
C
C
C
C
C
C
C
C
TITLE: ORDER
AUTHOR: A. GCH>STtiN
TMW SYSTEMS GROUP
WASHINGTON OPERATIONS
COMPUTER SYSTEM: IBM SYSTEM 360/MUOEL 53
LANGUAGE UStD: KJKTRAN IV - G LEVEL
AUSTRAC1: THIS ROUTINE SORTS. IN ASCENDING URUERt
THE "N" CLFMF NIS UF THE " 1 A" AKMAY. »
*
C
C
3002
0003
0"
n4
0005
0-3
06
3007
OOPS
C
C
C
C
C
C
C
3009
•)on
0011
C
0012
3011
COI4
3015
C
10
C
20
OIMCNSION lAI.NIiAIN)
L»N- 1
DO 20 J=1,L
K=J» 1
on 10 I»K,N
IFI IAI 1 I.GE. IAIJ) 1 GO TO 10
IH= 1 Al 1 1
IAI 1 I-IAIJ I
IAI J1=IB
8>A| I )
Al I I'AIJI
Al JI-B
CONTINUE
CONTINUE
C
C
3"
lt>
0017
C
C
KtTURN
END
Figure; E.3-7. Subroutine 0RDER, Interface Module-Program Listing
225
-------
4.0 DAMAGE COSTS MODULE
A.I DESCRIPTION
The Damage Costs Module (DAMAGE) is the principal analysis module
currently incorporated into the Cost/Benefit Model. DAMAGE (see Chapter 2,
Section 2. A) uses a linear equation to calculate annual damage costs on a
per capita basis as a function of the pollutant concentration. A separate
relation is used for particulates and sulfur oxides; the specific slope and
intercept values for the damage equation are supplied by the user as input
data. Without loss of generality, the EXISTING-SO- data for the NCIAQCR
demonstration will be used for illustrative purposes throughout this section.
All of the analysis modules have certain features of program design in
common. The main programs or DRIVER programs contain the only dimension
statements which must be changed by the user to fit the requirements of his
particular study. The dimension statements requiring change are all indi-
cated by an asterisk in column 80. All of the I/O devices are set in the
DRIVER. Some of these can be "dummied out" through the JCL to eliminate
certain output.
The input data sets are coded as follows:
• Data Set 1 - always contains specific operational parameters
required by the program, e.g., slope and intercept of damage
function.
• Data Set 2 - is always the census tract attribute data deck.
• Data Set 3 - is always an SO- air quality data deck.
• Data Set A - is always a particulate air quality data deck.
The output data sets are coded in a similar fashion:
• Data Set 11 - always provides title page information and
census data (input) summaries.
226
-------
• Data Set 12 - always provides CTPC data (input) summaries
• Data Set 13 - always provides the principal output of the
module.
Data sets 11 and 12 provide optional output. The procedure for eliminating
them is described in Section 4.2 for the Damage Costs Module. However,
the procedure applies to all analysis modules.
4.2 JOB CONTROL LANGUAGE AND DECK SET-UP
Figure E.4-1 illustrates the JCL and deck set-up for the Damage Costs
Module. The order follows: source and/or object decks first, output data
set specification, then input data set specification. The input data is
ordered: damage function, slope and intercept, census tract attribute
data deck, then census tract air quality data deck from C0NVRT (S09 or
particulates).
Any of the output categories described in the previous subsection
can be suppressed or "dummied out" through the JCL specifying the output
data set. For example to eliminate Data Set 11, substitute:
//G0.FT11F001 DD DUMMY
for the JCL statement*:
//G0.FT11F001 DD SYS0UT=A,DCB=(RECFM=UA,LRECL=133,BLKSIZE=133).
Figure E.4-1 illustrates the set-up and JCL for processing an S0? census
tract air quality deck. Notice that in this case, Data Set 4 which has been
reserved for particulate air quality data in the program has been dummied
out by an analagous procedure to the one just described. In order to pro-
cess a particulate census tract air quality deck, the last part of the job
deck would appear as follows:
"SYS0UT=A", sets the corresponding output data set to the printer.
227
-------
JOB SETUP FOR DAMAGE MODEL
//DAMAGE tXfcC PRQC-FCRTCCLG
//FORT.SYSIN 00 •
SOURCE DECKS
//LKED.SYSIN DO •
OBJECT DECKS
/*
//GO.FT11F001 OU SYSOUT«A,DCB«IRECFM-UA,LRkCL»13JtBLKSUE«133l
//iO.FTlZFOOl Ml SYSOUT'AtOCO'lRECFM'UA.LitECL'l JJ,ELKS I^t = l33>
//CU.FTI3K)01 UD SYSOUT.A,DCb-
-------
//G0.FT03F001.DD DUMMY
/*
//G0.FT04F001 DD *
Air Quality Data Deck - participates
/*
4.3 DIMENSIONS AND INPUT DATA FORMATS
The only variable dimension in the DRIVER is NCT, which in this case
(and for all existing analysis modules) is the number of census tracts.
For the NCIAQCR demonstration, NCT=366. So in the program listings shown
here:
NCT/366/ .
The I/O data sets are set as follows:
• LINl/l/-Input data set, i.e., card reader - damage function
slope and intercept.
• LIN2/2/-Input data set, i.e., card reader - census tract
attribute data deck.
• LIN3/3/-Input data set, i.e., card reader - air quality
data deck, SO or DUMMY.
• LIN4/4/-Input data set, i.e., card reader-air quality
data deck, particulate or DUMMY.
• L0UTl/ll/-Output data set, i.e., printer-title page and
census tract attributes as input.
• L0UT2/12/-Output data set, i.e. , printer-census tract
pollutant concentrations as input.
• L0UT3/13/-Output data set, i.e., printer-census tract
damage costs with regional and political jurisdiction summaries.
229
-------
The slope and intercept values for the damage equation are provided on a
single punched card. The format is shown in Table E.4-1. The census
tract attribute data deck has been described in Section 2 of this appendix.
However, DAMAGE doesn't read into core all of the attributes shown in
Table E.2-1. Table E.4-2 shows these card formats again, with the fields
not read by DAMAGE indicated by the notation, "(SKIP)". The formats for
the census tract pollutant concentration data cards have been given pre-
viously in Table E.3-3. The CTPC data deck was previously produced by
C0NVRT. Table E.4-3 shows these CTPC data formats again, however, using
notation after the program code in DAMAGE.
230
-------
Table E.4-1.
Damage Function Slope and Intercept, Input Data Format
- Damage Costs Module
Parameter Columns Format
A (slope) 1-10 F10.3
B (intercept) 11-20 F10.3
231
-------
Table E.4-2.
Census Tract Attributes As Read By DAMAGE
NCT Cards
(2 cards
per census
tract)
CARD 1
CARD 2
CARD 3
Parameter
TITLE1
Columns
1-80
Format
20A4
-left justified title information
beginning in column three
KCT
(SKIP)
P0P
(SKIP)
1-9 2A4,A1
10-22 13X
23-30 F8.2
1-80
SOX
232
-------
Table E.4-3.
Census Tract Air Quality Data Formats For
SO. or Particulates, Damage Costs Module
Parameter
Columns
NCT
Cards
CARD 1
CARD 2
TITLE2 1-80
- centered title information
J
JPJ
JCT
JSCT
(BLANK)
AQ
1-5
6-10
11-15
16
17-20
21-30
Format
20A4
15
15
15
II
4X
F10.3
233
-------
4.4 OUTPUT AND PROGRAM LISTINGS
The sample outputs from DAMAGE for the case of EXISTING-SO air
quality data for the NCIAQCR demonstration are shown in Figures E.4-2
E.4-3, and E.4-4. These correspond to data sets 11(L0UT1), 12(L0UT2)
and 13(L0UT3), respectively.
The program listing for the DRIVER portion of the Damage Costs
Module is given in Figure E.4-5. The listing for the DAMAGE subprogram
is given in Figure E.4-6.
234
-------
C.FNFRAI pimpnsF. IIMFAH QAMAC-P FUNCTION
DAMAGE PER CAPITA
0.6601 X AIR QUALITY *
-5.9001
CENSUS TRACT ATTRIBUTES — INPUT
WASHINGTON. O.C.
CFNSUS TRACT NUMBER
TOTAL POPULATION
0001
0002
0003
00 0*
0005
0006
0007
0008
0009
0010
0011
0012
0013
0014
0015
0016
0017
0018
0019
0020
0021
. 0022
0021001
0023002
0024
^^ 0025
^<^^ 0026
5963.
5723.
6412.
1280.
72B5.
5486.
P544.
6235.
6715.
11696.
5203.
5213.
7803.
65*9.
6177.
5458.
597?.
9284.
R536.
7525.
13751.
9471.
4416.
2134.
5497.
9210. —
?73?. ^^^^
^ 0027 _LLWX^^^"
Figure:E.4-2.
Sample Output From Damage Costs
Module, Title Page and Census
Tract Attributes as Input.
235
-------
CENSUS TRACT POLLUTANT CONCENTRATIONS — INPUT
WASHINGTON. D.C.. EXISTING — SULFUR DIOXIDE
NUMBER POLITICAL CENSUS POLLUTANT CONCENTRATION
JURISDICTION TRACT INICROGRAMS PER CUBIC HETERt
I
10
11
12
13
14
I*
16
17
ID
I")
20
21
22
23
24
25
26
27
28
29
10
31
12
33
14
15
16
3T
11
If
4O
41
42
43
44
4)
46
47
48
49
I
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
IT
IB
19
20
21
22
23.1
21.2
2*
25
26
27
28
29
30 .
11
32
31
34
IS
36
17
18
19
40
41
42
41
44
41
46
47
48
64.78
61. OB
61.08
63.34
65.39
56.88
58.98
5h.6S
54.08
56.88
51.77
16. aa
61.40
58.58
55.22
63.78
71.15
70.50
74.51
71.02
78.91
78.91
83.31
89.14
83.31
• 71.55
71.55
71.80
71.80
71.80
71.80
79.56
79.56
86.73
83.56
81.67
72.06
71.80
71.80
68.21
68.23
66.57
72.06
72. O6
72.06
72 .06 •
86.73
• 3.00
86. n
Figured. 4-3,
Sample Output From Damage Cost
Module, Census Tract Pollutant
Concentrations As Input.
236
-------
TRACT DAMAGE C
HASHINCTQN. n.c.. EXISTING -- SIM PIIR DIOXIDE
POL IT ICAL
CENSUS
EXPOSURE
DAMAGE
JURISDICTION
TRACT
COST
3?*
375
126
327
328
379
330
331
332
333
33*
335
336
337
338
319
340
341
342
343
5
S
5
5
5
5
5
5
S
*
5
5
S
5
5
S
5
5
5
S
26
77
28
79
30
31
32
33
34
35
36
37
38
39
40
41
42
4 1
44
45
1R5797.
? 1744H.
20H235.
24B271 .
254824.
2518b8.
227176.
557677.
160903.
(.07554.
180097.
771703.
383478.
4nisnn.
782928.
7f)fcn5H.
170903.
10RA56.
156264.
B3747.
98909.
1 74 771.
Ill 328.
132 \94.
134796.
133702.
120613.
717774.
85782.
370R12.
94668.
145 104.
209227.
7ifcnon.
151 112.
i OR MS.
91391.
57 795.
HlbflH.
43 375.
POLITICAL JURISDICTION TOTALS
12544913.
67319H7.
PflL-IT-IC-At-JUR ISO I-CTION-AVF RAGES* ' ' 27'8776~. ~ "
POLITICAL JURISDICTION AIR QUALITY ....47.B?
-1-49600".
344
. 345
346
347
J 348
- 349
350
351
35?
353
- "'J5~4~
355
356
357
358
359
360
361
362
363
6
6
6_
6
6.
I,
^
6
6' ."* • '
(,
6
6
" 6
6
6
6
6
6
1
- 2-
3
4 ...
5 ^
_.„ 6. ...
7
8 ....
9
"J. ' '.JO':' «.
1 1
12....
1 \
15
16
17
19
1 9
2.0.
. . ,, .1.38.31 3..
181645.
..., ._,- ,-,-20184^
. \-; ' -. v *'4'-' "4 93*4 5V
13S897.
- -3.40.450.
303047.
389754.
.523013.
750777.
.25.7.12.5.
742752.
263378.
56798.
_. .3.42126.
1461 16.
.42-1-181..
• .-1 - ^75741.
— 66-386:' -••-.
991S4.
.S:- . .1* . : u. I -j jA6"jg_ ' *
L:/JiJ:.lf . — '^.'-'.1.05634- ' • - -^ • ' •• '" ' '
\0i t tT.,,1 7
-------
FORTRAN IV C LEVEL 19
MAIN
OATE
Ott/3«./C5
DRIVER FOR DAMAGE FUNCTION ROUTINE
DAT* LIN17l/i.LINZ/Z/.LIN3/3/iL I
I LOJTim/,LOUT3/l*/.LOun/13/,
0004
NCT/366/
C
000?
C
CALL DAMAGE (L1N1,LIN2,L 1 N3, L 1 N4.LUUTI . LOUT2 . LUUT3. NC r 1
C
C
OOOJ
C
StdP
C
dND
Figure 'E.4-5.
Program Listing for DRIVER
Main Program-Damage Costs Module,
238
-------
FORTRAN IV C LEVEL 19
DAMAGE
DATE
71135
0001
SUBROUTINE DAMAGE I UNI . L IN? .1 INI .LI N* .LOUT 1 .LOUT? . LOUTS . NCT I
C
c <
C
C
C
C
C
C
C
C
C
C
r.
c
C
c
c
c
c <
c
TITLE:
AUTHOR:
COMPUTER
LANGUAGE
ABSTRACT:
DAMAGE
B. GOLDSTEIN
TRW SYSTEMS GROUP
WASHINGTON OPERATIONS
SYSTFM: IBM SYSTEM 360/MooEL so
USED: FORTRAN IV - G LEVEL
THIS ROUTINE WILL GENERATE DAMAGE COSTS
RY USING A GENERAL PURPOSE. LINEAR
DAMAGE FUNCTION.
0002
0003
0004
000?
C
c
c
r.
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
DIMENSION TITlEll20>.TIUE2(20),KCTn)
DMFNSION PJI6I .SRI 2) . Tl ( 21 . T2 I 3) . T3 t 3) ,WA(7I
D«TA PJ/' PO' 'LITI'.'CAL • .' JURI1. 'SDIC' . 'T10N'/.
1 SR/'REGI* 'ONAL'/t
Z Tl/' TOT' 'ALS •/.
J 1Z/' AVE1 'RAGE'.'S •/,
•> T)/' SIR' • QUA' . -LI TY1/.
•> WA/MHEI' 'GHTE'.'D W.'.'R.T.1,' POP1 , 'UL AT • , ' ION) • /
DAMAGE FUNCTION:
DC/C • A X ICTAQI * B
WHERE OC/C — DAMAGE COST PER CAPITA
CTAO -- CENSUS TRACT AIR QUALITY
CTDC « (DC/CI X (CTP)
WHERE CTDC — CENSUS TRACT DAMAGE COST
nC/C — DAMAGE COST PER CAPITA
CTP — CENSUS TRACT POPULATION
RCAOILIN1. 1100) A. 8
Figure E.4-6. Program Listing for DAMAGE Subprogram-Damage Costs Module
239
-------
1Q/1I/3B
QQQf, WRI TFII nilT 1 .71001 A.R
OOOT
0009
0009
c
C
C
RE4DIL IN?. 12001 T1TLF1
WRITEI LOUT 1.2200 I TITLE1
ICQNT1«0
C
C
0010
0011
0012
0013
0014
001S
0016
0017
001R
001<>
0070
C
c
c
c
c
c
c
r
c
c
c
RE4DILIN3, 1200,END=10I T1TLE2
UN-LIN3
GO TO 20
10 CONTIN'JE
REAIHLIN4, 1200.END-130I TITLE2
L 1N'L!N4
20 CONTINUE
WRI TEILUUT2, 23001 TITLE2
ICUNT2.0
WRI TE(LnuT3. 24001 TITLE2
ICD'JTlaQ
C
C
0021
0022
0023
0074
0075
0026
OO7T
DO7R
0029
DQin
0031
c
c
c
c
c
c
c
IPJ> 1
SCT»0.0
TCT-0.0
SPHP=0.0
TPnp«o.o
SPOSE-0.0
TPQSF-O.O
SD-0.0
Tn-o.o
DO 1 in 1-1 .NET
R.F4DILIN?. 13001 KCT.POP
c
Figure E.4-6.
Program Listing for DAMAGE Subprogram-Damage Costs Module
(Cont'd)
240
-------
10/11/39
003?
003)
0034
0035
0036
003T
C
C
C
C
C
1FI 1CQNT1.LT.50I GO TO 30
HRITFILOUT1. 22001 TITLE1
ICONT1=0
30 CONT [NUE
ICONT1»1CONT1»1
MR 1 T6 (LOUT 1,2500) KCTiPOP
C
C
0038
0039
0040
0041
00*2
00*3
0044
0045
0046
1)047
0048
0049
0050
0051
0052
0053
0054
3055
OQ56
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
READILIN. 14001 J,JPJ,JCT,JSCT,AQ
IF< ICONT2.LT.49I GO TO 40
WRITEILOUT2t2300) TITLE2
ICONT2-0
40 CONTINUE
ICONT2"ICONT2»1
IFIJSCT.EQ.O) GO TO 50
UR1TEIIOUT2, 26101 J, JPJ, JCT. JSCT.AO
GO TO 60
50 CONTINUE
HRITEILOUT2.2620) J.JPJ.JCT.Ag
fcb CONTINUE
1F( JPJ.EQ. IPJI GO TO BO
IFf ICONT3.LT.46) GO TO TO
HRITEILOUT3. 24001 TITLE2
ICONT3<=0
70 CONTINUE
ICONT3=ICONT)»5
MCT- IFIXI5CT«O.OI )
C
Figure E.4-6.
Program Listing for DAMAGE Subprogram-Damage Costs Module
(Cont'd)
241
-------
fflPTQAS IV C LEVEL
0057 URITFIinilT 1.77101 Mf. T . PJ . Tl . SPflSE . *D
0059
0059
OO6O
0061
0067
OOfct
3064
0065
OO66
00h7
0068
C
C
C
C
C
C
C
C
C
C
c
APn^-SPOSE/SCT
AD.SD/SCT
WO MF( LOUT 3. 77701 P J. 77 . APfl^E . AO
APOSE*SPOSE/SPOr>
WR 1 TFI LOUT 3. 2730) PJ.I3. A POSE. HA
IPJn JPJ
SCT.0.0
SPQP=0.0
spnsF=o.o
in.n.o
80 CONTINUE
r
c
0069
0070
c
c
IFIPQP.LE.O.OI CO TO 110
POSF^O.POP
c
c
0071
1)072
0073
0074
3075
0076
0077
0078
O07q
c
c
c
c
t
0=1 (V*AO*BI *POP
SCT=SCT»1.0
TCT«TCT*1.0
TPQP=TPOP»POP
SPD5E=SPOSE»P05E
TPOSE»TPOSE*POSE
SD«SO»0
TD.TIUT
C
C
0000
0081
003?
c
c
IFI ICrlNT3.LT.49» CO TO 90
•(RITE (LOUT 3, 24001 TITLE2
ICONTJ-0
Figure E.4-6. Program Listing for DAMAGE Subprogram-Damage Costs Module
(Cont'd)
242
-------
FORTRAN IV C LEVEL 19
DAMAGE
DATE » 71135
10/11/36
C
0081
008*
008*
0086
0087
0088
0084
0090
OOT1
0012
009?
00<".
0095
0096
0097
0094
0099
0100
0101
0102
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
90 CONTINUE
ICONT3«ICONT3*1
IFIJSCT.EQ.OI GO TO 100
MR IT El LOUT 3, 28 101 I , JPJ, JCT, JSCT.POSE.D
CO TO 110
100 CC1NT INUE
MR |TE( LOUT 3, 2820 I 1 , JP J. JC T, POSE.O
110 CONT INUE
IF! I CONT3.LT .461 GO TO 120
WRITEILOUT3. 24001 TITLE2
1C(1NT3 = 0
120 CONTINUE
ICONT3»ICONT3»5
MCT= IFimCTtO.Ol)
WHITE! LOUT 3, 27101 MCT , PJ , Tl . SPOSE . SO
APOSE*SPOSE/SCT
AO-SO/SCT
WRITEUOUT3.2T20I P J . T2 . iPOSE . AD
APOSE-SPOSE/SPOP
WRITEtLOUT3i2730l P J. T3i AROSE i MA
C
C
0103
010*
0105
0106
0107
C
C
C
C
Ifl ICONT3.GT.*5) WRITEILOUT3.2400) TITLE?
MCT»IFIXITCT»0.01I
WR I TEI LOUT 3,29101 MC T , SO , T 1 , TPOSE , TO
APUSE-TPOSE/TCT
AO«TO/TCT
.
Figure E.4-6. Program Listing for DAMAGE Subprogram-Damage Costs Module
(Cont'd)
243
-------
iQ/n/ia
c
0108
0109
0110
0111
C
c
c
C
130
MRITEILOUT3,2920> SR ,T2 , AROSE ,AO
APOSE«TPOSE/TPOP
HRITEILOUT3, 29301 SR, T3. APOSE , HA
COST INUF
c
c
0112
Oil]
0114
0115
0116
c
c
1 100
c
1200
C
non
C
I40O
RETURN
FORMATI7Fin.il
FORMAT120A4I
FDRMATI?A4.AI .HX.Ffl.?/«nXI
FORMAT 1 115. 1 1.4X.F10.3I
C
C
OUT
2100
FORMATCl' ,46X, 'GENERAL PURPOSE, LINEAR DAMAGE FUNCTION' Illlllllll
1 }BX. 'DAMAGE PER CAPITA - C.FR.l.'l X AIR DUALITY » 1*.
QUA
2200 FORMAT!1'!' ,49X,'CENSUS TPACT ATTRIBUTES — I NPUT' //41 X, 20A4//
1 45X.'CENSUS TRACT NUMBFR'.BX.«TOTAL PdPULAT I ON'/ I
2300 FHRMATI'I*.42X.'TFNSUS TRACT POLLUTANT CHNCFNTRAT1QNS — INPUT'
//27X.20AW/
4?X. 'NUMBFB' .4X.' PQLI TICAL' .SX. *C
SX,'PULLUTANT CONCENTRATION'/
SIX.'JURISOICTION'.3X.'TRACT'.
4X, MHICROGRAMS PER CUBIC METERI'/I
0120
0126
2400 FORMAT!'1',54X,'CENSUS TRACT DAMAGE COST'//27X.?OA4//
_1 T1X. ' NUMBER ' ,6X.'POLITIC AL'i7X.'CENSUS'.12X.'FXPfl SURF'.
0121
0122
0121
0124
0125
C
c
c
c
f
c
2
2500
2610
2A20
2710
2720
12X
, 'DAMAGE
FDR>4AT(49X>2A4.A1I
FORMAT!
u,
FORMAT! IX,
FORMAT!
FOH1ATI
•0'
39X
145.
145,
,134
,6A4
112.
112.
>4X,
,3A4
'/42X, '
F2S.O)
112.'.'
1 12.F21
6A4.2A4
, F10.0,
JURISDICTION' ,5X,' TRACT ',34X,'CUST' /I
, 11.F19.2)
.21
,F14.0,F19.0)
F19.0I
2730 FORMAT(39X,6A4,3A4,F12.2,6X,7A4/I
Figure E.A-6. Program Listing for DAMAGE Subprogram-Damage Costs Module
(Cont'd)
244
-------
FORTRAN IV G LEVEL 19 DAMAGE DATE • 71135 IO/11/3S
£
0137 2810 FOOMATI1X, 13*.114,1 U.«. ',II,F20.0,F19.01
£
0128 2820 FORMATIIX,134,11*,I 14.F22. 0, F 19. 01
C
0129 2910 FORMAT('01,I3*,6X,2A*,2A«,F28.0,F19.0I
£
0130 2920 FnRMAmiXt2A4,3A4,F24.0.F19.0)
C
0131 2930 FORMAT|<,1X,2A<.,3A4.F26.2,6X,7A4>
C
C
013? END
Figure E.A-6. Program Listing for DAMAGE Subprogram-Damage Costs Module
(Cont'd)
245
-------
.5.0 PROPERTY VALUE MODULE
5.1 DESCRIPTION
The Property Value Module (PR0P) calculates four types of residential
property values using the Anderson-Crocker regression equation. The basis
for the four property value types and the design principles for this module
have been given in Chapter 2, Section 2.4.
PR0P has many programming features in common with DAMAGE, described
in Section 4 of this appendix. It is recommended that the user read the
information given in that section before going further.
The major difference between DAMAGE and PR0P is that PR0P processes
a pair (S0» and particulates) of census tract pollutant concentration data
decks per run. DAMAGE processes either an S0? deck or_ particulate deck
in any single run.
5.2 JOB CONTROL LANGUAGE AND DECK SET-UP
The JCL and deck set-up for PR0P are illustrated in Figure E.5-1. The
order is as follows: source and/or object decks first, output data set
specifications, then input data set specifications. The input data is in
the order: regression line coefficients, census tract attribute data deck,
census tract air quality data deck for S0~, and census tract air quality
data deck for particulates.
246
-------
JOB SETUP FOR PROP MUOEL
EXEC PKOC'FURTGCLG
//FdKT.SrSIN DO *
SUURCC UECKS
//LKEO.SYSIN Oi) *
OdJECT DECKS
/A.O.FU 1H001 00 S»SUUT-A,UCB'tKf.CFM-UA,LKtCLM33,BLKSUE«133»
//OO.FTUFOOl UU SySGuT=A,UC.«"(KtCFN-UA,l>ECL-l33,HllCSUEMJJI
• //60.FI1 JF001 DU SySUUl»A,OCb=(RECF«icUA,LRECL»133,BLKSIiC»l33l
//GO.FI01F001 DO *
Rt-GRESSlUN LINE COEFFICIENTS
//iO.FTOZFOOl 01) «
CENSUS TRACT ATTRIBUTE DATA DECK
AIR aUALlTY DATA DECK - SU/i
//GO.FTO^FOOl DO *
AIR UUALITY DATA DECK - PARTICIPATES
Figure E.5-1t Job Control Language and Deck
Set-Up for Property Value Module,
2A7
-------
5.3 DIMENSIONS AND INPUT DATA FORMATS
The only variable dimension in the DRIVER that must be changed by
the user is? NCT, the number of census tracts. For the NCIAQCR demonstra-
tion, the dimension statement is:
NCT/366/.
The input data sets are set in DRIVER as follows:
• LINl/l/-Input data set, i.e., card reader-regression line
coefficients and sulfation rate factor.
• LIN2/2/-Input data set, i.e. , card reader-census tract
attribute data deck.
t LIN3/3/-Input data set, i.e., card reader-census tract
air quality data deck, SO...
• LIN4/4/-Input data set, i.e., card reader-census tract
air quality data deck, particulates.
The output data sets are set in DRIVER as follows:
• L0UTl/ll/-Output data set, i.e., printer-title page
and census tract attributes (as input).
• L0UT2/22/-Output data set, i.e., printer-census tract
pollutant concentration data for S02 and particulates (as input).
• L0UT3/13/-Output data set, i.e., printer-census tract property
values (Types I, II, III and IV) with regional and political
jurisdiction summaries.
L0UT3 is the principal output data set; the optional input data summaries
of L0UT1 and L0UT2 can be suppressed through the JCL as explained in Section
4 of this appendix.
248
-------
The data formats for the UNI (data set 1) are shown in Table E.5-1.
A single punched card provides the sulfation rate factor, relating sulfation
rate (milligrams per 100 square centimeters) to average sulfur dioxide con-
centration (parts per million). Another punched card contains a complete
set of Anderson-Crocker regression coefficients in the form:
Ln(PV)=CONST + A x Ln(PSN) + B x Ln(PPT) + C x Ln(MFI)
+ D x Ln(DLP) + E x Ln(OLD) + F x Ln(NWT) + G
x Ln(DIS) + H x Ln(MRM).
The Anderson-Crocker equations have been discussed in Chapter 2, Section
2.5. Four coefficient cards are required for the four property values
types: Type I, II, III and IV, in that order.
Table E.5-2 shows the formats for the census tract attributes data
deck. The formats have previously been given in Table E.2-1. However,
the notation "(SKIP)" has been employed in Table E.5-2 to indicate fields
not read into core by PR0P.
Table E.5-3 shows the formats for the SO census tract air quality
data cards and Table E.5-4 shows the formats for the particulate census
tract air quality data cards. These are the same as indicated in Table
E.3-3, showing the output format for these cards from C0NVRT. However,
the notation employed in Tables E.5-3 and E.5-4 follows the program code.
249
-------
Table E.5-1.
Sulfation Rate and Regression Coefficient Input Data
Formats, Property Value Module
Parameter
Columns
Format
I = 1,2,3,4
(four cards)
CARD 1 - one card
FACT0R 1-5
CARD 2
C0NST(I) 1-8
A(I) 9-16
B(I) 17-24
C(I) 25-32
D(I) 33-40
E(I) 41-48
F(I) 49-56
G(I) 57-64
H(I) 65-72
(BLANK) 73-80
F5.3
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
8X
250
-------
Table E.5-2.
Census Tract Attribute Data Formats
As Read by the Property Value and Assignment Modules
Parameter
Columns
CARD 1
SCARD 2
.
tract)
CARD 3
\
TITLE1 1-80
-left justified title
beginning in column t
KCT 1-9
(BLANK) 10
Ql 11-16
Q2 17-22
P0P 23-30
MIL 31-38
SFH 39-46
ALL 47-54
0WN 55-62
RENT 63-70
(SKIP) 1-10
MPV 11-18
MGR 19-25
MCR 26-32
Ln(MFI) 33-40
Ln(DLP) 41-48
Lnl(0LD) 49-56
Ln(NWT) 57-64
Ln(DIS) 65-72
Ln(MRM) 73-80
Format
20A4
2A4.A1
IX
F6.2
F6.3
F8.2
F8.2
F8.2
F8.2
F8.2
F8.2
10X
F8.2
F7.2
F7.2
F8.3
F8.3
F8.3
F8.3
F8.3
F8.4
251
-------
Table E.5-3.
Census Tract Air Quality Input Data Formats for S0?,
Property Value and Assignment Modules
CARD 1
CARD 2
NCT cards
Parameter
Columns
Format
TITLE2 1-80 20A4
- centered title information
Jl
JPJ1
JCT1
JSCT1
(BLANK)
PSN
1-5
6-10
11-15
16
17-20
21-30
15
15
15
11
4X
F10.3
252
-------
Table E.5-4.
Census Tract Air Quality Input Data Formats for Particulates,
Property Value and Assignment Module
CARD 1
CARD 2
Parameter
Columns
Format
TITLE3 1-80 20A4
- centered title information
NCT
Cards
J2
JPJ2
JCT2
JSCT2
(BLANK)
PPT
1-5
6-10
11-15
16
17-20
21-30
15
15
15
11
4X
F10.3
253
-------
5.4 OUTPUT AND PROGRAM LISTINGS
Figures E.5-2, E.5-3 and E.5-4 show sample outputs from the Property
Value Module for the NCIAQCR demonstration using EXISTING S02 and EXISTING
PARTICULATE air quality data. Figures E.5-2 and E.5-3 present the input
data summaries correspoding to Data Set 11 (L0UT1) and Data Set 12 (L0UT2),
respectively. The census tract property value summary corresponding to
Data Set 13 (L0UT3) is shown in Figure E.5-4.
The Program Listings for DRIVER and Subprogram PR0P are given in
Figures E.5-5 and E.5-6.
254
-------
N)
(_n
Ln
LNIPV-ll • 1 3.19O1I • I-O.OT12
» I-0.01O6
LNIPV-21 - ( 1.16171 » ( 0.0010
» 1-0.021)
LNIPV-3) =• ( 0.24281 » 1-0.090%
» (-0.0606
LNIPV-41 = I 0.47051 » (-0.0727
» (-0.0408
MASHINGTONt O.C.
CENSUS TOTAL AREA IN
TO ACT POPULATION SQUARE
.NJXBER _ _._. .. . ..MILES
0001 596). 0.
0002 5723. 0.
0003 6412. 301.
fc-^ 0004 1280. 0.
^ .^jnos 7>qs. n.
^*^^^^__ 5486. 320.
X LN(PSNI) • (-0.0610 X LNIPPTII » ( O.T67T X LNIMFI)) • 1 O.O044 X LNIDLPI)
X LNIOLOII * I O.O251 X LN(NWTII » (-0.058? X LNIDISII • I O.O X INIMPMI)
:
X LN(PSNI) » (-0.1698 X LNIPPTII » 1 0.9970 X LNIMFIII » ( 0.0113 X LNIOLPII
X LNIOLOII » ( 0.0321 X LN(NWTI) V 1-0.0312 X LN(OISI) « ( 0.90h4 X LNIMRH))
X LNIPSNII * ( 0.0049 X LNIPPTII » I 0.51O9 X LNIMFII) » I 0.0121 X LNIDLPII
X LNIOLOII » 1-0.0043 X LNINWTII * (-0.0216 X LNIDI^II > ( O.O X LNIMRH))
X LNIPSNII » (-0.0302 X LNIPPTII » ( 0.46SO X LN(HFII) * 1-0.0054 X LNIOLPM
X LNIOLOII » (-0.0124 X LNINMTII » (-0.0111 X LNIOISI) » ( 0.0 X LNIMRH))
CENSUS TRACT ATTRIBUTES — INPUT
MEDIAN MEDIAN DILAPIDATED HOUSING NJNMHITE DISTANCE
PROPERTY FAMILY HOUSING OVER 10 OCCUPIED BUSINESS
VALUE..,. 1N.COHE UNITS ....YEAR.i_QLO HQUiING DISTRICT,...
0. 1. 1. I. 1. 1.0
0. 1. 1. 1. 1. 1.0
17801. 8647. 1. 2J10. 30. 4.0
0- 1. 1. 1. 1. 1.0
n. |. i. ^ — ^^^^^^^" ^^^"^^^
23202. II Illl i •!'
MEDIAf
HOOHS 1
MOUilf
1 . J
1.0
5.5
1.0
•i "
•Nfc
Figure E.5-2. Sample Output, Title Page and Census Iract Attributes Summary from Property Value Module.
-------
CENSUS TRACT POLLUTANT CONCFNTRAT IflNS — INPUT
MASHINCTON. O.C.t EXISTING — SULFUR 010XIOE
WASHINGTON. O.C.i EXISTING -- PARTICULATFS
NJMBER
POLITICAL
CENSUS
POLLUTANT CONCENTRATION
NUMBER
POL IT ICAL
CENSUS
POLLUTANT CONCCKT«AT I ON
JURISDICTION
TRACT
(MICROGRANS PER CUBIC METERI
JURISDICTION TRACT
INICROCRAHS PER CU3IC M.PfFRI
50
51
5?
53
5*
ss
56
57
SB
59
60
61
62
M
6*
65
66
67
69
69
70
71
72
71
7*
75
76
77
78
79
90
91
82
8)
84
AS
86
87
88
"9
00
91
92
91
94
9S
96
97
98
49
SO
51
S2.1
52.2
53. 1
53.2
5*. 1
5*. 2
55
56 '
57. 1
57.2
58
59
60
61
62
63
64
65
66
67
69
69
70
71
72
73.1
73.2
73.3
.73.4
73.5
73.6
73.7
73.8
74. 1
74.2
74. 3
75
76.1
76.2
76.3
77. 1
77.2
77. 3
77.4
77. S
78.1
80.99
72.06
70.78
72.06
70.78
72.06
70.78
67. R2
67.82
65.29
64.72
68.18
69.51
76.87
79.27
77.32
75.45
68.65
75.37
75.37
79.27
89.03
89.03
90.73
68.13
85.98
85.98
79.92
64.24
64.24
65.06
64.73
66.70
66.70
63.95
61.21
82.94
76.87
72.82
76. 87
84.64
87.44
78.56
ST. 80
67.18
92.43
78.21
81. 4&
103.94
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
71
74
75
76
77
78
79
80
Rl
82
83
B4
as
86
87
88
89
90
91
92
93
94
95
96
97
98
49
50
51
52.1
52.2
51. 1
53.2
54.1
54.2
55
56
57. 1
57.2
5H
59
hO
61
62
63
64
65
66
67
63
69
70
71
72
73.1
71.2
73.3
73.4
73.5
71.6
73.7
71. B
74.1
74.2
74.3
75
76.1
76. 7
76.3
77. 1
77.2
77.3
77.4
77. «>
78.1
76.82
71.92
71. 77
71.92
71.77
71.17
71.77
fcB.9B
68.99
6R. 1 1
67.44
fc9.
-------
CENSUS TRACT PROPERTY VALUE
WASHINGTON, O.C.
NUMBER
355
356
357
358
359
360
361
362
363
17
364
365
366
3
. .
Z73
POLITICAL CENSUS
JURISDICTION TRACT
6 12
6 13
6 14
6 15
6 16
6 17
6 18
6 19
6 20
POLITICAL JURISDICTION TOTALS
POLITICAL JURISDICTION AVERAGES
POLITICAL JURISDICTION AIR QUALITY
7 1
7 2
7 3
POLITICAL JURISDICTION TOTALS
POCITICAL' JURISDICTION AVERAGES
POLITICAL JURISDICTION AIR QUALITY
RhblUNAL IUIAL5 1
REGIONAL AVERAGES
REGIONAL AIR -QUALITY
EXPOSURE
SULFUR
DIOXIDE
523013.
250777.
257125.
242752.
263378.
56798.
342126.
146136.
421781.
4307625.
253390.
53.71
113179.
270555.
98520.
482254.
160751.
47.33
396668.
~ 66^ 73
EXPOSURE
PARTICULATES
593023.
330677.
339049.
278228.
356825.
70952.
509145.
203895.
473076.
5159936.
303526.
64.34
134237.
319118.
116086.
569442.
189814.
55.89
421548.
70.92
PROPERTY
VALUE
TYPE 1
20350.
20286.
19766.
20565.
13912.
2C710.
17237.
17641.
21098.
129845216.
20531.
(WEIGHTED
22945.
22866.
30688.
43564656.
24887.
(WEIGHTED
PROPERTY
VALUE
TYPE 2
0.
45304.
0.
50491.
27267.
0.
0.
0.
0.
166420192.
4B617.
WITH RESPECT
62874.
56494.
103063.
122922832.
70221.
WITH RESPECT
3.JI Vftblfl'ttt. "*5 1 ibU JU'tU.
' 22365. 66579.
(WEIGHTED WITH RESPECT
GROSS
RENT
TYPE 3
78.
84.
82.
87.
60.
89.
69.
74.
76.
1140867.
81.
TO POPULATION!
96.
132.
157.
14C010.
132.
TO POPULATION)
ia 38 u n. 14
75.
TO POPULATION!
CONTRACT
RENT
TYPE 4
63.
64.
65.
72.
46.
69.
52.
55.
58.
876339.
62.
78.
90.
108.
96892.
91.
58.
Figure E.5-A. Sample Output, Census Tract Property Values Summary from Property Value Module
-------
FORTRAN IV G LEVEL
MAIN
DATE < 71134
08/35/02
DRIVER FOR PROPERTY VALUE ROUTINE
0001
DAT* UNI/ I/.LIN2/2/11IN3/3/.L
1 LOUU/U/.LOUT2/I2/.LOUT3/U/,
000*
NCT/Jbb/
c
0002
c
CALL PROP
C
c
0001
c
STOP
c
ENO
Figure E.5-5. Program Listing for DRIVER, Main
Program for Property Value Module.
258
-------
FQRTKAN IV G LEVEL
PROP
LJATE = 711S7
19/20/39
0001
c
c <
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
SU.IKGUTINc PPU" (L1N1,LIN2,LIN:»,LIN<.,LI)UTI,LL)UT2,LJUT3,NCTI
r*»«*»«*«»t***»««*»*»*««»»»»«**»00**««***»«****»«***********»«*»*«<
TITLE: PROP
AUTHOR: 0. GCLUSTEIN
TRW SYSTEMS GROUP
WASHINGTON OPERATIONS
CU*PUTtR SYSTEM: INM SYSTEM 3&0/*u'JeL 50
LANGJAJE JSFC1: I-ORTP.AN I i/ - O LEVEL
AttSTivACT: THIS ROUTINE .vILL CEMEAAT*; PK'jt>F*TY ViLOcS
HY USING THE Ai'MDcrtSliiJ-CKOCKER ^EGrtES SI ON
FOUATION.
»***««*««»»«ea**«*«*»««*«********««*«»et««***«*«****«* *««*******»*<
>
J
0002
OC03
000*
0005
DIMENSION CL)N5TI<.|,AK(,bl<*l,CKI,L>t'«),F.
DIMENSION TITLE H 201 .TITLE2120) ,TITL = 3I? 31 .N4MK9) ,KCT(3I
DIMENSION PJ(b) .SRI2I ,T1 (2I.T2I3I .T3I1) ,wA(l Jl
KEAL MILiHPV.MGR .MCR t«F I ,N«T,.MkM
0006 DATA ,MVME/ MPV-', ' (PSN-, • ( PP T ' .'IMF I ',' (OLP1 , ' (OLD1 , • I NWT • , ' ( D I S ' •
1 MMRM'/
C
0007 DATA PJ/' PO','LITJ' ,'CAL ', 'JURT, 'SO IC','TION'/,
1 SR/'REGl' ,'ONAL'/, '
7. I I/' IOT • , • 4LS ' / >
3 T2/' AVE','KAGE','S '/,
<, T3/1 ATP',1 OUA'.'LTTV'/,
5 WA/M Wtl ' ,'GHTE','0 Wl'.'TH ?. ' , 'bSP b ' . ' r.T T','0 r»!j» , ' PJL A ' ,
6 'TION1,1! '/
ANOEUSO.'J-CRUCKEK REGKESS10N' EJuATIUM:
LNIPVI = CONST + A X LNIPSN) » B X LN(PPT) » C X L.Nl^t-II
+ D X LNIDLPI » 5 X Li'JICLTI * F X LN(N'wT)
» G X LNIDI S> * H X L.
WHERE PV — PROPtRTY VALUE (MbOIAN PRCPfcATY VALJEi MEDIAN GROSS
"5F.HT, OR MEDIAN CONTRACT RETT' OF D»NER OCCUPIED
HOUSING FOK A CENSUS TRACT)
PSN — CONCENTRATION OF SULFUR DIOXIDE
Figure|E.5-6. Program Listing for Subprogram PR0P,
Property Value Module
259
-------
FORTRAN IV G LEVEL
PROP
DATE
71187
19/20/39
0003
0009
3010
OC1 1
UUll
0013
0014
0015
0016
0017
0018
0019
0020
UUll
OOZZ
002)
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
— -- c
c
c
OPT — CONCENTRATION OF PARTICIPATES
*Fl — MEDIAN FAMILV INCOME
DLP — NUMBER OF LIVING UNITS DILAPIDATED
OLD — NUMBER OF HUUSES OVtK TEN YEARS OLD IN 1959
NMT — NUMBER OF HOUSING OCCUPIED BY NONtaHITES
OIS — DISTANCE OF CENSUS TRACT FROM CENTRAL BUSINESS
DISTRICT
MRM — MEDIAN NUMBER UF ROOMS IN HOUSING UNIT
CONST — REGRESSION EQUATION CONSTANT
4.8,C,D,E,F,G,H — EQUATION COEFFICIENTS
FACTOR — CONSTANT CORRECTION FACTOR RELATING SULFATlUN
RATT"(HTrLlGRfrNT'PFlT'TOO^ SWART TEWTTHETFR) 70 "
AVERAGE SULFUR OiOXIDb CONCENTRATIONS IPARTS PER
HTTLTOKn ••" " "
HtftOILlNl.llOOl FACTOK,
1 { "CON'S H 1 ITA1 1 JTBTTTTC \ 1 1 , D (TmnTJTF (TITC IT ) iffnT, T5T7V)
UR 1 T E ( L 3UT 1 , 2 1 00 J'TNAHFrnTTTCDNSTTDTATn , NAHFfZ ) , B IT! VWA'HE C3Tt
1 Cl I 1 .NAME <<.) ,0(1 1 , NAME (5), El 1 ), NAME* 6),
/ l-lll,NflMbl/l»(jlll»rgA«tlBl.mii ,NAntl vi , 1 = 1 > «• I
RtftJILINZ.lZOO) TITLtl
nft 1 Tt I LUUT1 ,22001 TITLE1
1 L J N 1 I = U
REA01LIN3, 12001 TITLE2
READJLT^, 1200) TITLE3
WRITE ILHUT2, 23001 (TITLF2(I)«I=3,18).(T[TLE3(I),I=3,ld)
ICONT2 = 0 ' " -~ " " • ~
-a|TE(LOUT3,2'VOO) TI TL£l'f ( I , 1 = 1 .4) ~"
ILUN 1 3 = J
JPJ=1
SCT=0.0
i i. i :: 0 • L)
SPOP~=3.0 ' - - -. _.._._.
TPl)P = 0.0
Figure E.5-6.
Program Listing for Subprogram PR0P,
Property Value Module (Cont'd)
260
-------
FORTRAN IV G LEVEL
PROP
OATE
71167
002*
0025
0026
0027
0029
0029
0030
0031
0032
0033
0034
0035
0030
0037
003B
0039
0040
0041
30*Z
3043
0044
3045
0046
0047
00*8
00*9
0050
0051
•3052
0053
006*
005"5
0056
0057
C
C
C
C
C
C
C
c
cr
c
c
C
C
c
c
c
SPOSE1=0.0
SPUSE2=9.0
TPDSEI=O.O
"tpnse 2=0.0
SCT1=0.0
SCT2=0.0
rcri=o.o
TCT2=0.0
SSCT \=0.0
TTCT1=0.0
SPvl=0.0
SP\/2 = C.O
SPV } = 0.0 ~"
SPV4=0.0
iHVi=o.n
TPV2=0.0
TPV3=0.0 " " " ~
rpv4=o.o
-
CK1 I 10 1=1 iNL I
RE40ILIN2, 1300) rtC T, 01,02", POP .TnLVSFH.AlL.nWN, RENT, MPV.MG^.MC*,
1 Hfl ,DLP,CLJ.NwT,OI S,^>1
. _ _ . . . _ ...
IF( ICUNTl.LT.*rt) GO TO 1C
WR1 TE(LUUri, 22001 TITLE1
1 CON T 1 = 0
1 ~ '
1C CONTINUE
ICONTls|CUNTl+l
_-... ..... ._. ... ,. .__..
AMFME
-------
FJKTHA'J IV 0 LtVt'L 19
19/20/3-V
005S
0059
OOol
0062
0063
006*
0065
J066
0067
0068
0069
0070
0071
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
IT! lCOnT2.LT.ii?) OJ M 2C
«K ITfclLUJT i, 2200) !TlTLI:2IJItJ = 3ilP. ),(TITLF>IJ),J = 3,l3)
IC'.1NT2 = 0
20 CGNT INUE
1C.JNT2=!CONT?» 1
IF( JSCTUJSO.T2.tj.3l GO TLi 30
*RITE< LOUT ^,2610) J 1 , JP J 1 , JC.T1 , JSCT 1 ,PS J , J2 , J" J? , JCT2 , JSCT2 . PP T
f,L. TU
-------
FUKTRAN IV G LEVEL H
PROP
I)
-------
IV 0 LEVEL 1')
PROP
PATE «= 71197
1W20/39
0112
0113
0114
>)1J5
0116
0117
0118
0119
0120
0121
012?
0121
012*
0125
0120
0127
0128
0129
0130
0131
0132
0133
0134
0135
0136
0137
0138
0139
0140
0141
0142
014J
0144
014%
0146
0147
C
c
C
c
c
c
c
c
'C
c
c
c
c
c
c
c
SSCT1 = SSCT 1-DwN
riCTl=TTCTl-U*N - - -
80 CUNTIN'JE
ic r-5cr»i.a
TCT=TCT»l.O
SPGt> = SPOP»PUP
TPOP=TPJP*PUP
SPOSE1=SPOSE 1»PCSE1
SPUSE2=SPOSh2«PGSf 2
TPJSEl=TPJSc l»PGSf 1
T?iJSE2*TPO$t2»PUSE2
SCT1«SCTI»CWN
SCT2«SCT2»HENT
TCTl»TCTl»OWN
rCT2«TCT2»RENT
SSCT1=SSCT1»OWN
TTCT 1 = TTCT l*naN
PV1=PV« 1I*OWN
PV2=PV(2I*OWN
PV3=PV( 3)*«ENT
PV4=PV(4J*RENT
SPV1=SPVI»PVI
SPV2«SPV2»PV2
SPV3«SPV3*PV1
SPV4aSPV4«PV4
TPV1=TPV1»PVI
TPV? = TPV2»i»V?
TPVJ=TPV3*PV3
TPV4«TPV4«PV4
IFt ICONT3.LT. 4»» GO 1C =c
^R ITEILHUTJ.Z^OO) T1TIF1 t ( J, J=l .M
ICOUT3=0
90 CONTINUE
1CQNT3= ICUNT 3+ I
IFCJSCTl.E^.CI GO TC 100 " ~-
JRrTE(LOI/T3,?B10l I .JPJ1 . JCTT, J3CT1 , PnSET,PT3STE2, IPV( J1 , J= 1 , 41
Figure E.5-6. Program Listing for Subprogram PR0P,
Property Value Module (Cont'd)
264
-------
FORTRAN IV G LEVEL
PROP
OATE = 71187
19/20/39
0148
01*9"
0150
0151
0152
0153
015*
0155
0156
0157
0158
0159
01 60
0161
0162
0163
016*
0165
0166
0167
0168
0169
0170
0171
0172
0173
017*
0175
0176
C
C
C
C
C
C
C
— c~
C
L
t
T
C
C
c~
C
C
C
C
C
C
"C
C
GO" TO'ilO
100 "CONTINUE" ~ ~~
WRITEUOUT3,2«2CI I , JPJ1 , JCT 1 ,PGSE 1,POSE2, < PV( Jl ,J=1,*I
110 CONTINUE ~ ~" ._.---..-..-
1F( ICONT3.LT.*5I GO TO 120
MRI TH LOUT 3, 2*001 TITLtl,(J,J=l,*l
ICONT3=0
120 CONTINUE
ICONT3=ICnNT3*5
MCT« IFIX(SCT»C.01I
xfil TFJSt2 , SPVl , SPV2 ,SPV3, SPV*
APOSE1»SPOSE1/SCT
APOSE2=SPOSE2/SCT ' " -. . .
WVl»Si»V17SCTl • ~ ' ' -
APV2=SPV2/SSCT1
APV3=5PV3/SCT2
APV*=SPV*/SCT2
WRITE(L.)UT3,2?20) P J, T2 , APOSE1 1 APOSt^t APV1 , APV2 , APV 3, APV*
APOSEl=SPUiEl/SPOP
apubtii = iPUit2/:>PUH
WKITE .JLOUT 3,27301 P J, T3, APCSEl t iPOSf 2.WA
IF( ICU^r3.GT .**) nKITE(LOUT3.2*00) Tl TL E 1 , 1 J , J = l ,* 1
4CT=IMX|TCTO.C1)
WRITE(LQUT3,2910( ^C T , SK , Tl , TPOSE1 , TKOiE2 ,TPV1 rT \>V S , 1 PV3t TPv*
APUSEl=rPOSEl/TCT
APOSEZ=TP05F2/TCT
APVl=Ti>Vl/TCTl -- .— - -
4PV2=TP\/2/TTCTl
APV3=TPV3/rCT2 - . _ -
Figure E.5-6.
Program Listing for Subprogram PR0P,
Property Value Module (Cont'd)
265
-------
FORTRAN IV G LEVCL 19
PROP
DATE
M187
19/20/39
0177
0178
0179
0180
0181
0182
0181
018A
0183
0186
0187
0189
0189
0190
C
• c'
C
c
c
c
c
1100
c
1200
c
1300
c
1400
c
c
2100
1
2
_ 3
C
2200
1
2
3
5
" - ' j,
7
8
9
A
C
2300
2
3
A
5
6
7
B
9
C
2*00
WRI TEUOUT 3,29201 SS, T2, APCSE 1 , APuSE 2, APV1 , APV2 , APV3, APVA
APOSEl = TPOSEl/Tt>OP
APOSE2=TPUSt2/TPQP
WRI TEILJUT 3,2930) SR,T3 , APOSE1 , At>OS"E2, »A
RETUKM
FORMATIF5. 3/l9Ffl.A~,8X) (
FOR*A T( 20 AAI
FORMAT(3I5,I1,AX,FIC.3»
FORMAT! •!• ,48X,' ANDERSON-CROCKER REGRESSION EQUATION'///
<»(///////l3Xt'LN' ,A*tIl t ' 1 = I'tFT. *»•»',
AC » C.FT.^.' X LN'.AA.'I IM//31X.
FORrtATl'l* ,*9X, 'CENSUS TR ACT~ATTR IBUTES -- I NPUT' // IX ,20A4//
*X, 'CENSUS' .'.X,' TOTAL ',bX,' ARE A IN' ,2X , 'S INGLE ', 5X, • ALL ',
t>X, 'NtOlAN' , 2 X,' MEDIAN' , 2A, 'MLJl AN' t3Xi' MEDIAN',
IX, '01 1 API OAT tO ',2 A. 'HOUSING1 ,2X, 'NON WHITE' , IX , 'DI STANCE ' ,
2X, •*EDlAN'/<,X,MRACr»f3x;iPOPULAnON',3X,'SUUAkE1 ,
2X. 'FA.««ILY',3X, 'HOUSING1 ,2X , • PkOPcRT V • ,2*. 'GROSS* ,
IX, 'CONTRACT ',2X,'FA^rLY',3X, •HUUSrN'G1 ,*X , 'OVER 10 ' ,
2X, 'CCCUPUO', IX, 'BUSINESS' ,1*. 'RUOrtS IN'/4X , • NJMBEi" ,
15X, 'MILES', 3X, 'HOUSING1 ,3X ,' UNI TS ', AX ,' VALUE1 , AX ,' RENT ',
'«X, 'KENT', AX, 'INC CMC' , AX , ' UNI TS ' , AX , • Y£ ARS ULD' ,
IX, 'HOUSING' , 2X, • 01 STR I CT',2X,' HOUSING'/)
FORMAT! '!' ,A2x, 'CENSUS TRACT POLLUTAST CONCENTRATIONS — INPUT'
3X, 'NUMBER1 , AX, 'POLITICAL' , 5X , 'CfcNSUS ' ,
5X, 'POLLUTANT CONCENTRATION',
9X, 'NUMBCR' ,AX, 'POLITICAL' ,bX , 'CENSUS1 ,
5X, 'POLLUTANT CONCENTRATION'/
12X,1JURISDICTIW«,3XT»TR"ACT' .
AX, MMICROGRAMS PER CUBIC METER)',
15X, 'JUKI bUIL 1 IUN • , ;JA» ' 1 KAC 1 • ,
AX, MMICKOGRAMS PEK CUdIC METER)'/)
FOR1ATC I' ,53X, 'CENSUS TRACT PROPERTY V ALUE' // 1 X , 20AA //
2X", 'NUMOFR' ,6X, ' POLITIC AV i7X,« CENSUS' , 12X, 'EXPOSURE' ,
Figure E.5-6. Program Listing for Subprogram PR0P,
Property Value Module (Cont'd)
266
-------
FORTRAN IV G LEVEL 19
PROP
DATE = 71187
19/20/39
9X.J E XPOSURE S12X,«PROPERTY'.5X,'PROPERTY«,bX,'GROSS*t
7 X, •CONTRAlCT' /1 3X t * JURl SDICTIUN'.SX, 'TRACT' , I<>X, • SULFUR1 ,
8X, •J'ARTICULATES* tllX,'VALUE* tBX,'VALUE'>9X,'RENT* ,
9X,"'RENT1/'.8X,"'OIOXIDEt ,2*X,4(7X,•TVPE•,121/I
0191
0192
0193
2500 FORMAT!lX,2A4,AltHO.O,F10.0,F10.0,F9.0,F10.0,F7.0,F8.0,F9.0,F9.0,
1 _ F11.0»F10.0,F8.1.F9.1I
C "
?610 FORMAT(IX,16,112,112,'.',Il,F19.2tl22,ll2,I12t'.>,lltF19.2)
2620 FORMATUX,16.112,112,F21.2,122,112,112,F21.2)
0194
0195
0196
0197
0198
0199
0200
0201
C
C
2710
2720
2730
2810
C
2820
C
C
C
2910
2920
2930
FORMAT!
FORMAT!
FORMAT!
FORMAT!
• 0'
10X
IOX
IX.
FORMAT! IX,
FORMAT!
FORMAT!
•0'
12X
,I5,4X,6A<.,2A4
,6A4,3A<>
,&A4.3A4
15,114,1
15,114,1
.F10.0
.F12.2
14, «.'
tF14
.F17
,F17
,1 1,
.O.F17
.O.F19
.2.11X
F20.0,
.O.F19.0
.O.F13.0
.10A4/I
,F13.0,
.F12.0,
F17.0.F19.0.F13
14,F22.0.F17.0,F19.0,F13
,15,6X,2A4,2A4
,2A4,3A4
.F24.0
FORMATU2Xt2A<«,3A
-------
6.0 ASSIGNMENT MODULE
6.1 DESCRIPTION
The Assignment Module (ASSIGN) determines census tract residential
property values under different conditions of ambient air quality. The
algorithm is described in Chapter 2, Section 2.6.
6.2 JOB CONTROL LAUGUAGE AND DECK SET-UP
Figure E. 6-1 shows the JCL and deck set-up for the Assignment Module.
The ordering parallels that of PR0P identically.
6.3 DIMENSION AND INPUT DATA FORMATS
All variable dimension information and data set descriptions are the
same as given in Section 5.3 of this appendix. However, Data Set 13 is
now:
L0UT3/13/-Output data set, i.e., printer-census tract
property value bids.
The input data formats for Data Set 1 (LIN1) are shown in Table E.6-1
Everything follows the formats for the sulfation rate factor and regression
coefficient input cards described for PR0P. However, only one regression
coefficient set (one input card), corresponding to the Type I property
value equation, is required for ASSIGN.
Table E.6-2 shows the data formats for Data Set 2 (LIN2) , which
corresponds to the census tract attribute deck produced by C0NVRT. However,
ASSIGN reads fewer attributes into core than PR0P. The attributes skipped
are indicated by the notation "(SKIP)".
The input data formats corresponding to Data Set 3 (LIN3) and Data
Set 4 (LIN4) are the same as given for PR0P.
268
-------
JOB SETUP FUR ASSIGN MODEL
//ASSIGN EXEC PROC«FORTGCLC
//FORT.SYSIN DO «
SOUkCE DECKS
//LKCO.SYSIN 00 •
OBJECT DtCKS
//CO.F11 1FU01 00 SYSOur°A,OCR»(ktCFM«UA.lKECL°133,ULKSIZE'133l
//vlO.FU^FOOl OD SYSUUr-A,OCB-
-------
Table E.6-1.. Assignment Module Input Format for
Regression Coefficients (Type I)
Parameter
Columns
Format
CARD 1
FACT0R
CARD 2
C0NST
A
B
C
D
E
F
G
H
1-5
1-8
9-16
17-24
25-32
33-40
41-48
49-56
57-64
65-72
F5.3
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
F8.4
270
-------
Table E.6-2.
Census Tract Attribute Data Formats as Read by Assignment Module
Parameter Columns Format
CARD 1
TITLE1
1-80
20A4
- left justified title information
beginning in column three.
NCT
Census
Tract,
two cards
per census
tract.
CARD 2
KCT
(BLANK)
Ql
(SKIP)
P0P
MIL
CARD 3
(SKIP)
MPV
(SKIP)
Ln(MFI)
Ln(DLP)
\ Ln(OLD)
Ln(NWT)
Ln(DIS)
Ln(MRM)
1-9
10
11-16
17-22
23-30
31-38
1-10
11-18
19-32
33-40
41-48
49-56
57-64
65-72
73-80
2A4.A1
IX
F6.2
6X
F8.2
F8.2
10X
F8.2
14X
F8^3
F8.3
F8.3
F8.3
F8.3
F8.4
271
-------
6.4 OUTPUT AND PROGRAM LISTINGS
Figures E.6-2 and E.6-3 show the input data summaries corresponding
to Data Set 11 (L0UT1) and Data Set 12 (L0UT2) as described in Section 5.4.
The major output from ASSIGN is shown in Figure E.6-4, corresponding to
Data Set 13 (L0UT3). The sample outputs are for the NCIAQCR demonstration
using EXISTING S02 and EXISTING PARTICULATE air quality data.
Program listings for the DRIVER program of the Assignment Module and
the ASSIGN subprogram are given in Figures E.6-5 and E.6-6.
272
-------
ANDERSON-CROCKER REGRESSION EQUATION
LNIPVI » I 3.39011 « 1-0.0712 X INIPSNH * 1-0.0610 X LNIPPTI) •» I 0.7677 X LNIMFII) • ( 0.0044 X LN(DLP))
. .. » 1-0.0106 X.LNIOLUII * I 0.0251 X LNINMTII » (-0.0562 X LNIOISII * < 0.0 X LN(MRMI)
CENSUS .TRACT ATTRIBUTES. _—._ INPUT
ro
•vj
u>
WASHINGTON, O.C.
CENSUS
TRACT
NUMBER
0048
0049
OOSO
0051
0052001
' 00520C2
0051001
0053002
005400 1
0054002
0055
0056
0057001
0057002
0058
TOTAL
POPULATION
AREA IN
SQUARE
MILES
8485.
9000.
8234.
2451.
6033.
1291.
5896.
1022.
2624.
831.
6180.
3797.
537S.
1404.
14B-).
186.
115.
115.
0.
115.
0.
58.
0.
0.
0.
237.
160.
173.
0.
"i r~
MEDIAN
PROPERTY
.VALUE
12100.
12296.
14003.
0.
13200.
0.
11696.
0.
0.
0.
19594.
21590.
22994.
MEDIAN
FAMILY
INCOME
DILAPIDATED
HOUSING
UNITS
HOUSING
OVER 10
YEARS 01P
NONWHITE
OCCUPIED
HOUSING _
DISTANCE
BUSINESS
DISTRICT
MEDIAN
ROOMS IN
. HOUSING
Figure E.6-2. Sample Output, Title Page and Census Tract Attributes-Assignment Module.
-------
NJ
NUMBER
1
2
J
*
5
6_
'7
a
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
78
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
CENSUS -TRACt.POUUTANt-CONCENTRATIONS...T.T. INPUT.
WASHINGTON, O.C., EXISTING — SULFUR DIOXIDE WASHINGTON, D.C. , EXISTING — PARTICIPATES
POLLUTANT CONCENTRATION
IHICROGRAMS PER CUBIC METERI
77~~.29
64.63
64.63
66.70
67. 89
63,56
64.09
62.32
61.<•?
63.56
63.01
63.56
67.06
66.60
65.21
67.97
72. 79
70.70
74.18
71.10
76. 1 3
76. 13
7D.OH
HI.03
78.06
71.46
71.46
71.09
71.69
71.69
71.69
76.03
76.03
79.41
78.31
76.76
71.92
71.6V
71.69
69.34
69. 3<.
68.27
71.92
71.9,;
71.92
71.92
79.41
77.63
79.41
POLITICAL CENSUS
JURISDICTION TRACT
1
2
1
*
5
. ... _ _. 6. ..
7
8
9
10
U
_ L 12 _
13
14
15
16
17
18
19
20
21
22
23. 1
23.2
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
. 43
44
1 45
1 46
1 47
1' 48
POLLUTANT CONCENTRATION
(M1CROGRAMS PER CUBIC HETERI
64.78
61.08
61.08
63.34
65.39
56.88
58.98
56.65
54.08
56.88
51.77
56.88 _. . ._ ..
61.40
58.58
55.22
63.78
71.15
70.50
74.51
71.02
78.91
78.91
83. 31
89. 34
83.31
71.55
71.55
71. HO
71.80
71.80
71.80
79.56
79.56
86.73
83.56
81.67
72.06
71.80
71.80
68.23
68.21
66.57
72.06
72.J06
72.06
72.06
86.73
83.00
86.73
NUMBER POLITICAL CENSUS POLLl
JURISDICTION TRACT IHICROC
I
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
4<*
1
2
3
4
5
6 _.
7
a
9
10
11
_12 . ._.
1 3
14
15
16
17
IB
19
20
21
22
23.1
23.2
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
40
Figure E.6-3.
Sample Output, Census Tract Pollutant Concentration
Summary (SC>2 and Particulates) Assignment Module.
-------
CENSUS TRACT PROPERTY VALUE BIDS
to
-j
WASHINGTON, C.C.
NUMBER
257
258
259
260
261
262
263
264
265
266
267
268
269
270
17
271
272
273
3
273
...
>
POL ITICAL
JUKI SOICT ION
6
6
6
a
6
6
6
6
6
6
6
6
6
6
POLITICAL JURISDICTION
POLITICAL JURISDICTION
7
7
7
POLITICAL JURISDICTION
POLITICAL JURISDICTION
REGIONAL TOTALS
REGIONAL AVERAGES
CENSUS
TRACT
6
7
a
9
11
12
13
14
15
16
17
13
14
20
TOTALS
AVERAGES
1
2
3
TOTALS
AVERAGES
MEDIAN
PROPERTY
VALUE
15899.
11396.
22093.
23295.
23295.
12900.
12695.
1<>300.
16301.
11204.
23295.
13494.
14003.
16899.
1C1321712.
16100.
18306.
18106.
26108.
35373824.
20208.
4171612416.
175O6.
PROPERTY
VALUE
BIO
BEFORE
SHI FT
20971.
171 19.
20628.
28263.
22067.
20350.
20286.
19766.
20565.
13912.
20710.
17237.
17641.
21098.
129845216.
20531.
22945.
22866.
30686.
43564656.
24887.
5329461248.
22365.
PROPERTY
VALUE
BID
AFTER
SHIFT
19081.
22830.
22138.
19839.
22220.
21590.
20983.
18588.
1 1519.
28321 .
19808.
24651.
24353.
24713.
138932352.
21968.
14677.
23507.
23747.
3682 1904.
21035.
4879036416.
20475.
DIFFERENCE
IN
PROPERTY
VALUE
BID
-1890.
5711.
1510.
-8424.
153. .
1239.
697.
-1177.
-9046.
14410.
-902.
7414.
6712.
3615.
9087147.
1437.
-8268.
641.
-6941.
-6742747.
-3852.
-450462720.
-1890.
Figure E.6-4. Sample Output, Census Tract Property Value Bids from Assignment Module.
-------
FORTRAN IV C LEVEL 19
MAIN
DATE
ZO/10/2B
DRIVER FOR ASSIGNMENT ROUTINE
C
C
0001
DIMENSION IDCTI 3661 ,PV< <., 366 I , HH< 366 I ,CTI 366 I ,11(3661
0002
DATA LINl/l/.LIN2/2/,LIN3/3/>LINW4/t
1 LOUTl/ll/,LOUT2/I2/,LOUT3/n/t
NCT/366/
0003
CALL ASSIGN (UNI ,L 1N2, UN3. U N<..LOUT I ,LOUT2 ,LQUT3i
NCT,IDCT.PV.HH.CT,ITI
OOP*
STOP
0005
END
Figure E.6-5. Program Listing for DRIVER, Main
Program for Assignment Module.
276
-------
FORTRAN IV C lEVEt 19
ASSIGN
DATE • 7UB9
08/10/21
oooi.
c
c <
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
0002
c
0003
c
0004
c
" 0005 ' " "
c
0006
c
" c
c
c
c
c
c
c
c
c
c
c
c
c
SUBROUTINE ASSIGN < L INI , LI N2, L IN3, LI N^.LOUT 1 ,LOUT2, LOUT3,
NCT, IDCT,PV,HH,CT,IT,OWN1 ,ONN2)
•*»«»**»«***»****»»**»**»***»T****»Y* *****•*•********»«***»**»***»<
TITLE: ASSIGN
AUTHOR: B. GOLDSTEIN
TRW SYSTEMS GROUP
WASHINGTON OPERATIONS
COMPUTER SYSTEM: IBM SYSTEM 360/MUOEL 50
LANGUAGE USED: FORTRAN IV - G LEVEL
ABSTRACT: TO APPROXIMATE, AS CLOSELY AS POSSIBLE, THE NET
INCREASE IN PRODUCTIVITY OCCASIONED BY REDUCTIONS
IN AMBIENT AIR CONCENTRATIONS OF SULFUR OXIOES
AND PARTICULATES.
'
DIMENSION IDCT(NCT) ,P V (4 ,NCT 1 , HH( NCT ) ,CT 1 NCT > , I T ( NC T 1 ,
i OHNHNCTI ,OMN2 (NCT)
DIMENSION T1TLE1I20),T1TLE2J20),TITLE3I20) ,KCT13)
DIMENSION PJ(b) ,SR(2> ,T1(2>,T213>
REAL MILiMPV.MFl ,NMT,MKM
DATA PJ/» PO't'LITI'i'CAL • , • JURI • , ' SOI C' , • T ION' / ,
I SR/'REGI'.'ONAL1/,
2 Tl/« TOT'.'ALS •/,
3 T2/« AVE't'RAGE't'S •/
ANDERSON-CROCKER REGRESSION EQUATION:
LNJPVI = CONST » A X LNIP5N) » B X LNiPPTI » C X LNIMPII
+ D X LNIOLPI * E X LNIOLOI * F X LN(NWT)
» G X LNIOISI + H X LNIMRMI
WHERE PV -- PROPERTY VALUE OF OWNER OCCUPIED HOUSING
PSN — CONCENTRATION OF SULFUR DIOXIDE
PPT — CONCENTRATION OF PARTICULATES
MFI — MEDIAN FAMILY INCOME
OLP -- NUMBER OF LIVING UNITS DILAPIDATED
OLD ~ NUMBER OF HOUSES OVER TEN YEARS CLD IN 1959
NWT — NUMBER OF HOUSING OCCUPIED BY NONWHITES
i
Figure ;;;.6-6. Program Listing for ASSIGN
Subprogram, Assignment Module.
277
-------
FORTRAN IV G LEVEL 19
ASSIGN
DATE - 71169
08/10/21
_ -
0007
0008
0009
0010
0011
0012
0013
0014
0015
00 Ib
0017
001 8
0019
0020
0021
0022
0023
0024
0025
0026
0027
0028
C
c
C
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
_c
c
c
c
" C~
c
c
c
c
OIS — DISTANCE OF CENSUS TRACT FROM CENTRAL BUSINESS
DISTRICT
NRM — MEDIAN NUMBER OF ROOMS IN HOUSING UNIT
CONST ~ REGRESSION EOUATION CONSTANT
A,B,C.O,E,F,G,H — EQUATION COEFFICIENTS
FACTOR — CONSTANT CORRECTION FACTOR RELATING SULFATION
RATE (MILLIGRAMS PER 100 SQUARE CENTIMETER) TO
AVERAGE SULFUR DIOXIDE CONCENTRATIONS (PARTS PER
MILLION)
RtAOUlNl, 1100) FACTOR, CONST, A, B,C ,l> ,E ,F ,G,H
MR IT El LHUT 1,21001 CONST , A, B,C ,D,E ,F , G,H
REAOUIN2, 1200) TITLE1
WRITE (LOUT 1,2200) TITLE1
ICONT1=0
READIL IN3, 1200) TITLE2
READILIN4, 1200) TITLE3
MR I TE (LOUT 2.2300) 1 UTLE2( II,(=3,18),(TITLE3(I),I=-3,18)
ICQNT2=0
WRITE(L6uT3,2400r~TITLEl
ICONT3=0
N=0
00 SO 1=1, NCT
READILIN2,1300» KCT ,01 .POP ,MIL .CV4N.MPV ,MF I ,OLP .OLO.NMT ,01 S ,MRM
AMFI=EXPtMFl )
ADLP=EXP(DLP)
AOLD=EXP(OLO)
ANWT = EXPTN»iT)
AOIS'EXP(OIS)
AMRM=EXP(MRMI
IF( iCONTl.LT.48l GO TO \Q
MRITEtLOUTl,2200) TITLE1
Figure E.6-6.
Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
278
-------
FORTRAN IV C LEVEL 19
ASSIGN
DATE » 71189
08/10/21
0029
0030
0031
0032
0033
0034
0035
0036
0037
0038
0039
0040
0041
0042
0043
0044
0045
" 0046
0047
00*8
0049
0050
0091
0052
C
C
10
C
C
C
C
C
C
C
C
C
20
C
C
C
C
C
30
C
C
40
C
C
C
C
C
C
C
C
C
C
1CUNT1=0
CONTINUE
ICONU=ICGNT1»1
WRITE! LOUT 1,25001 KCT , POP, M L f MPV, AMFI , AOLP . AOLO , ANrfT , AOI S, ANRM
REAOIL IN3, 1400) J 1 , JPJ1 , JC Tl , JSCT 1 ,P SN
READILIN4, 1400) J2 , JPJ2. JC T2 . JSCT2 >PPT
IF( ICONT2.LT.49I GO TO 20
*IR I TE( LOUT 2,2:1001 1 TI TLE21J ) , J = 3, 18 ) , « TI TLE3 U ) , J=3 , 1 8)
ICONT2=0
CONTINUE
ICONT2=ICONT2*1
IF< JSCT1*JSCT2.EQ.OI GO TO 30
WRITEILUUT2.2610) J 1 , JPJ 1 , JCT1 , JSC Tl ,PSN, J2 , JP J2 , JC T2 , JSCT2, PPT
GO TO 40
CONTINUE
WRITE(LOUT2,2620) Jl, JPJ1, JCT1 ,PSN, J2, JP J2 . JCT2 ,PPT
CONT INUE
IFlQl.LT.l.OI GO TO 50
N=N>1
IDCTt N)=JPJ 1*10000* JCTl* 10* JSCT I
PV( 1 tNI=NPV
PSN=>PSN/«2660.0*FACTOR)
PSN=ALOG«PSNI
PPT=ALOG(PPT I
Figure E.6-6. Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
279
-------
FORTRAN IV G LEVEL 19
ASSIGN
DATE = 71169
08/10/21
0053
005*
0055
0056
0057
0058
0059
0060
0061
0062
0063
006 .GE.CTI 1 1 I 1 I GO TO 70
TENP = CT( 111 1
CT< I II ) = CT( II
CT( I I=TEHP
ITEMPMTU 11 1
ITI I II )=ITI I )
IT( 1 I=ITEMP
TfcNP=OWNU 111 »
OWNK I 1 I ) = OWNH I 1
OMNK I I = TEMP
70 CONTINUE
80 CONTINUE
00 90 1=1 tN
II = IT( I 1
Figure E.6-^6.
Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
280
-------
FORTRAN IV G LEVEL 19
ASSIGN
DATE
71189
08/10/21
0083
0084
0085
0086
0087
0088
0089
0090
0091
0092
0093
0094
0095
0096
0097
0098
0099
0100
0101
0102
0103
0104
0105
0106
0107
oio'a
0109
0110
0111
c
c
c
90
c
c
c
c
c
c
c
c
c
c
c
c
c '
c
c
c
c
c
100
c
PV(3tIII=EXP«HHII )»CT(1I )
OWN2I 1 1 »=J»N1( I I
CJNT INUE
JPJ= 1
MSCT=0
MTCT=0
SCT=0.0
TCT=U.O
SPVl=0.0
SPV2=0.0
SPV3=0.0
SPV4=0.0
TPV1=0.0
TPV2=0.0
TPV3=0.0
TPV4=0.0
00 140 I=1,N
ID=IOCT< II
IPJ= 10/10000
IO=IO-IPJ*10000
ICT= 10/10
ISCT=IO-ICT»10
OWN = 0*N2m
IF( IPJ.EU. JPJ ) GO TO 110
IF( ICONT3.LT.44I GO TO 100
WR1TE(LQUT3, 24001 T1TLE1
ICONT3=0
CONTINUE
ICONT3=lCONT3+4
Figure E.6-6. Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
281
-------
FOKTRAN
0112
0113
Oil*
0115
0116
0117
0114
0119
0120
0121
0122
0123
012*
0125
0126
0127
0128
0129
0130
0131
0132
0133
013*
0135
0136
0137
0138
0139
01*0
01*1
01*2"
01*3
01**
IV G LEVEL
C
C
C
C
C
C
C
C
110
C
C
C
C
C
C
C
C
C
C
C
19 ASSIGN DATE - 71189 08/10/21
HRI TE (LOUT 3 1 27101 MSCT, P J, Tl ,SPV1, SPV2, SPV3 1 SPV*
APVI=SPV1/SCT
APV2=SPV2/SCT
APVJ=SPVJ/SCT
APV'. = SPV*/SCT
WRITE (LOUT 3, 2 7201 P J, T2, APV1 , APV2 i AP V3, APV*
JPJ= 1PJ
*SCT=0
SCT=0.0
SPV1=0.0
SPV2=0.0
SPV3=0.0
SPV*=O.O
CONTINUE
PV(*, I) = PV(3, I I-PV12.I 1
MSCT=MSCT»1
MTCT=MTCT*1
SCT=SCT»OWN
TCT=TCT»OWN
PVl=PV( 1,1 I*OMN
PV2'Pv(2.i )*GWN
PV3=PV(3, J I*OUN
PV*=PV(*,I )»UWN
SPVI=SPV1»PV1
SPV2=SPV2»PV2
SPV3=SPV3+PV3
SPV*=SPV*»PV*
TPV1=TPV1»PV1
TPV2=TPV2»PV2
TPV3=TPV3*PV3
TPV*=TPV**PV*
!F( ICONT3.LT.*6) GO TO 120
WRITEUOUT3. 2*001 TITLF1
Figure E.6-6.
Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
282
-------
:ORTRAN IV G LEVEL 19
ASSIGN
DATE * 71189
08/10/21
0145
0146
0147
0148
0149
0150
0151
0152
0153
0154
0155
0156
0157
0158
0159
0160
0161
0162
0163
0164
~0l'65~
0166
0167"
0168
0169
0170
0171
fflTz
C
c
C
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
ICONT3=0
120 CONTINUE
ICONT3=1CJNT3*1
IF< ISCT.EC.OI GO TO _13Q
WRITEILOUT3, 28101 I , I P J, 1 CT, 1 SCT , ( PVU, I ) , J = l ,4)
GO TO 140
130 CONT INUE
WRITE I LOUT 3, 28201 I,IPJ,lCT,,J=l,4)
140 CONTINUE
IF( ICONT3.LT.44I GO TO 150"
rfRITECLUUT3,2400) TITLE1
ICONT3=0
150 CONT INUE
~ ICO~NT3=ICONT3*4 ~ "" - - --
WRITEILOUT3, 27101 MSCT, PJ , Tl t SPVlt SP V2 t SPV3t SPV4
APvi«SPvi/scT
APV2=SPV2/SCT
" APV3=SPV3/SCT
APV4=SPV4/SCT
WRITEILOUT3, 27201 PJ.T2, APV1 , APV2 , APV3, APV4
1H rCONT3.GT.4"3» WRITE
-------
FORTRAN IV C LEVEL
ASSIGN
DATE = 71189
08/10/21
c_
C
0173 1100
C
0174 1200
C
0175 1300
C
0176 1400
C
C
0177 2100
1
2
3
5
C
0178 2200
I
2
3
4
5
6
7
C
0179 2300
2
3
<»
5
6
7
A
9
" c
0180 2400
1
2
3
*
5
FORMAT(F5.3/9F8.4t
FORMATI20A4)
FORMAT(2A4,Al,lX,F6.2,6X,2Fd.2,16XjF8. 2/1 OX, F8.2, 14X, 5F8. 3.F8. 41
FORMAT!3I5,I1,4X,F1P,3I . .._
FORMAT! ' 1'
14X
' X
1 X
' X
' X
FORMAT!1!'
8X,
6X,
4X,
6X,
7X,
8X,
7X,
FORMAT! • 1'
//I
iX,
5X,
9X,
5X,
12X
4X,
15X
4X,
FORMAT! '!'
8X,
11X
,48X,< ANDERSON-CROCKER REGRESSION EQUATION' //////////
,'LNIPV) = I',F7.4,') * I',F7.4,' X LNIPSNI) «• l',F7.4,
LNIPPTII * C,F7.4,' X LNIMFMI * !',F7.4,
LNIOLP) I'//33X, •«• !',F7.4,' X LN(OLO»I «• !',F7.4,
LNINHTM » C.F7.4,' X LNIOISI) + !',F7.4.
LNIMRM) I ' 1
,49X, 'CENSUS TRACT ATTRIBUTES — I NPUT' // 1X.20A4//
•CENSUS ',7X, • TOT AL'.SX,' AREA I N« ,6X , 'MEDI AN' ,
•MEDIAN1 ,4X, 'OIL API DA TED', 5X, 'HOUSING' , 5X , • NONKHITE' ,
•DI STANCE ',5X,'MEDI AN' /8X, 'TRACT ' ,6X ,' POPULATION' ,
•SQUARE' ,5X,'PROPERTY',5X, 'FAMILY',6X, 'HOUSING' ,
•OVER 10' ,5X, 'OCCUPIED', 4X, 'BUSINESS', 4X, 'ROOMS IN'/
'NUMBER' ,21 X,' MI LESS 7X, 'VALUE',7X,' INCOME' ,7X, 'UNITS',
'YEARS OLD* , 4X , 'HOUSING' ,5X, 'D I STRICT' , 5X , ' HOUS ING' / 1
,42X,'C"ENSUS TRACT POLLUTANT CONCENTR'ATI UNS — INPUT1
•NUMBER' ,4X, ' POL I TIC AL',5X, 'CENSUS',
•POLLUTANT CONCENTRATION',
•NUMBER ', 4X,' POL I TICAL'.SX, 'CENSUS',
'POLLUTANT CONCENTRATION'/
,' JURISDICTION1,^, 'TRACT' ,
MMICROGRAMS PER CUBIC METER*',
, • JURISDICTION ',3X,' TRACT' ,
MMICROGRAMS PER CUBIC METER) '/I
,50X, 'CENSUS TRACT PROPERTY VALUE BIDS'// IX, 20A4//
'NUMBER', 1 IX. 'POLITICAL' , 12X, • CENSUS"', 1 IX ,' MEDIAN' ,
,2! 'PROPERTY', 10X) .'DIFFERENCE'/
24X, 'JURISDICTION' ,10X, • TRACT •, 1 1 X, 'PROPERTY' ,
11X,2( 'VALUE ',13X1, 3X,' IN'/
63X,' VALUE' ,14X,'BID',15X,'BiO',14X,'P~ROPERTV'/ "
8 IX, 'BEFORE* ,12X, 'AFTER* ,14X, 'VALUE'/
7 81X
C
,21 'SHIFT', 13XJ.2X, 'BIO1/!
0181
0182
2500 FORMAT«5xT2A4»Al,FI3.0,F13.0,FT*.0,FI1.0,Fl2.0,F14.0,F1J.O,P11.1,
_ 1 f112.'1!- _ __ _.
CT
2610 FORMAT(IX,I 6,112,112,'.',I1.F19.2,122,112,112t*.*.11,F19.2)
Figure E.6-6.
Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
284
-------
FORTRAN IV G LEVEL 1.9 ASSIGN UATE = 71169 08/10/31
016J 2620 FORMAT!IX,16.11?,I 12,F21.2,122,112,112,F21.21
C
0184 2710 FUKMATI'0' ,111,6X,6A4,2A4,Fl7.O.F18.O.F18.0,F19.0»
C
0185 2720 FOR*AT(20*.6a<.,3A<.,F13.0.F18.0.F16.0.Fiq.O/l
. _ „
0186 2810 FORMAT!IX,111,119,119,'.',II,F17.0,Fid.O.F18.0.F19.0I
C
0187 2820 FORMATI1X,I 11,119,119.F19.0,F18.0,F1B.O,F19.01
C
0188 2910 FORHATCO1 ,1 11,10X , 2A<, ,2 A4 ,F 31 .0,F 18 .0,F 18.0, F19.0I
C
0189 2920 FORMAT(22X,2A4,3A4,F27.0.F18.0,F18.0.F19.0I
C ' ....
C
0190 ENO '
Figure E.6-6. Program Listing for ASSIGN Subprogram,
Assignment Module (Cont'd)
285
------- |