ORDES
ESTIMATING REGIONAL LOSSES TO AGRICULTURAL PRODUCERS
FROM AIRBORNE RESIDUALS IN THE
OHIO RIVER BASIN ENERGY STUDY REGION. 1976-2000
PHASE
OHIO RIVER DASIK ENERGY STUDY
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November 1980
ESTIMATING REGIONAL LOSSES TO AGRICULTURAL PRODUCERS
FROM AIRBORNE RESIDUALS IN THE
OHIO RIVER BASIN ENERGY STUDY REGION, 1976-2000
by
Walter P. Page
Faculty Member, West Virginia University
James Ciecka
Faculty Member, DePaul University
Gary Arbogast
Ph.D. Candidate, West Virginia University
Prepared for
OHIO RIVER BASIN ENERGY STUDY (ORBES)
Grant No. EPA R805585 and
Subcontract under Prime Contract EPA R805588
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D.C. 20460
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PREFACE
This is a final report of work completed for the Ohio River Basin Energy
Study (ORBES) estimating monetary losses to agricultural producers from air-
borne residuals in the study region. Walter P. Page, West Virginia Univer-
sity, served as principal investigator for the research.
We wish to thank Randy Holliday and Kung Hun Lee, Ph.D. canditates in
the Department of Economics, West Virginia University, for assistance with
the calculations. Special thanks are extended to Mary Ann Albertazzie for
her competent typing services and cooperative attitude and to the Bureau
of Business Research, West Virginia University, for managing the project.
11
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CONTENTS
Preface ii
Figures iv
Tables vi
1. Introduction 1
2. Estimating Losses Due to Air Pollution:
General Discussion 3
3. Estimation of Agricultural Losses Due to Air Pollution:
The ORBES Region Analysis 13
4. Data Bases and Parameter Estimates 16
5. Empirical Estimation of Monetary Welfare Losses
to Agricultural Producers 21
6. Discussion of Results 26
References 140
Appendix A 142
111
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FIGURES
Number Page
1 Ohio River Basin Energy Study Region Phase II 120
2 Scenario and Impact Models: Sequential Steps in
ORBES Assessment 121
3 Text Figure 5
4 Text Figure 7
5 Text Figure 9
6 Text Figure 9
7 Text Figure 11
8 Text Figure 14
9 Text Figure 23
10 Text Figure 24
11 Total Agricultural Losses for ORBES Scenario 2 by Region
and ORBES-Portions of States, 1976-2000 122
12 Total Utility Related Agricultural Losses for ORBES
Scenario 2 by Region and ORBES-Portions of States, 1976-2000 .. 123
13 Total Agricultural Losses for ORBES Scenario 2d by Region
and ORBES-Portions of States, 1976-2000 124
14 Total Utility Related Agricultural Losses for ORBES
Scenario 2d by Region and ORBES-Portions of States,
1976-2000 125
15 Total Agricultural Losses for ORBES Scenario 7 by Region
and ORBES-Portions of States, 1976-2000 126
16 Total Utility Related Agricultural Losses for ORBES
Scenario 7 by Region and ORBES-Portions of States, 1976-2000 .. 127
IV
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17 Plot of Total Regional Monetary Losses, by Crop,
1976-2000, Scenario 2 128
18 Plot of Utility Related Total Regional Monetary Losses,
by Crop, 1976-2000, Scenario 2 129
19 Plot of Total Regional Monetary Losses, by Crop,
1976-2000, Scenario 2d 130
20 Plot of Utility Related Total Regional Monetary Losses,
by Crop, 1976-2000, Scenario 2d 131
21 Plot of Total Regional Monetary Losses, by Crop,
1976-2000, Scenario 7 132
22 Plot of Utility Related Total Regional Monetary Losses,
by Crop, 1976-2000, Scenario 7 133
23 Plots of Total 0 and SO Crop Damages, 1976-2000,
in the ORBES Region, Scenario 2 134
24 Plots of Total 0 and SO Utility Related Crop Damages,
1976-2000, in the ORBES Region, Scenario 2 135
25 Plots of Total O and SO Crop Damages, 1976-2000,
in the ORBES Region, Scenario 2d 136
26 Plots of Total O and SO Utility Related Crop Damages,
1976-2000, in the ORBES Region, Scenario 2d 137
27 Plots of Total O and SO Crop Damages, 1976-2000,
in the ORBES Region, Scenario 7 138
28 Plots of Total 0 and SO Utility Related Crop Damages,
1976-2000, in the ORBES Region, Scenario 7 139
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TABLES
1. Seasonal Average Prices for Corn 31
2. Seasonal Average Prices for Soybeans 32
3. Seasonal Average Prices for Wheat 33
4. Weighted Prices, by Crop and State for the
Six-State Region, 1965-1978 . 34
5. Six-State Crop Production, 1965-1978:
Corn 35
6. Six-States Crop Production, 1965-1978:
Soybeans 36
7. Six-State Crop Production, 1965-1978:
Wheat 37
8. Estimated Supply Elasticities for Corn, Soybeans, and
Wheat Production in the Ohio River Basin Energy Study Region 38
9. Present Discounted Value of Pollution-Free Cumulative
Production, 1976-2000 39
10. Net Present Value of Minimum Cumulative Crop Loss,
1976 to 2000, from SO and O : Scenario 2 40
11. Net Present Value of Minimum Cumulative Crop Losses
to Utilities, 1976 to 2000, from SO and O : Scenario 2 41
12. Net Present Value of Maximum Cumulative Crop Loss,
1976 to 2000, from SO and O : Scenario 2 42
13. Net Present Value of Maximum Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO and O : Scenario 2 43
14. Net Present Value of Probable Cumulative Crop Loss,
1976-2000, from SO and 0 : Scenario 2 44
15. Net Present Value of Probable Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO and O : Scenario 2 45
VI
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16. Net Present Value of Minimum Total Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2 46
17. Net Present Value of Minimum Utility Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2 48
18. Net Present Value of Maximum Total Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2 50
19. Net Present Value of Maximum Utility Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2 52
20. Net Present Value of Probable Total Cumulative Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 2 54
21. Net Present Value of Probable Total Utility Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 2 56
22. Net Present Value of Total Cumulative Crop Losses,
1976 to 2000, by Pollutant: Scenario 2 58
23. Net Present Value of Utility Cumulative Crop Losses,
1976 to 2000, by Pollutant: Scenario 2 60
24. Net Present Value of Minimum Cumulative Crop Loss,
1976 to 2000, from SO and O : Scenario 2d 62
25. Net Present Value of Minimum Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO2 and 0^: Scenario 2d 63
26. Net Present Value of Maximum Cumulative Crop Loss,
1976 to 2000, from SO and 0 : Scenario 2d 64
27. Net Present Value of Maximum Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO and O : Scenario 2d 65
28. Net Present Value of Probable Cumulative Crop Loss,
1976 to 2000, from SO and O : Scenario 2d 66
29. Net Present Value of Probable Cumulative Crop Losses to
Utilities, 1976 to 2000, from S02 and 03: Scenario 2d 67
30. Net Present Value of Minimum Total Cumulative Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 2d 68
31. Net Present Value of Minimum Utility Cumulative Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 2d 70
32. Net Present Value of Maximum Total Cumulative Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 2d 72
vii
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33. Net Present Value of Maximum Utility Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2d 74
34. Net Present Value of Probable Total Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2d 76
35. Net Present Value of Probable Utility Cumulative Crop Losses,
1976 to 2000, from SO and 0 , by Crop: Scenario 2d 78
36. Net Present Value of Total Cumulative Crop Losses,
1976 to 2000, by Pollutant: Scenario 2d 80
37. Net Present Value of Utility Cumulative Crop Losses,
1976 to 2000, by Pollutant: Scenario 2d 82
38. Net Present Value of Minimum Cumulative Crop Loss,
1976 to 2000, from SO and 0 : Scenario 7 84
39. Net Present Value of Minimum Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO and O : Scenario 7 85
£ «J
40. Net Present Value of Maximum Cumulative Crop Loss,
1976 to 2000, from SO and 0 : Scenario 7 86
41. Net Present Value of Maximum Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO and 0 : Scenario 7 87
42. Net Present Value of Probable Cumulative Crop Loss,
1976 to 2000, from SO and O : Scenario 7 88
43. Net Present Value of Probable Cumulative Crop Losses to
Utilities, 1976 to 2000, from SO and 0 : Scenario 7 89
44. Net Present Value of Minimum Total Cumulative Crop Losses,
1976 to 2000, from SO2 and 6 , by Crop: Scenario 7 90
45. Net Present Value of Minimum Utility Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 7 92
46. Net Present Value of Maximum Total Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 7 94
47. Net Present Value of Maximum Utility Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 7 96
48. Net Present Value of Probable Total Crop Losses,
1976 to 2000, from SO and O , by Crop: Scenario 7 98
Vlll
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49. Net Present Value of Probable Utility Crop Losses,
1976 to 2000, from SO and O_, by Crop: Scenario 7 100
50. Net Present Value of Total Cumulative Crop Losses,
1976 to 2000, by Pollutant: Scenario 7 102
51. Net Present Value of Utility Cumulative Crop Losses,
1976 to 2000, by Pollutant: Scenario 7 104
52. Probable, Year by Year, Individual and Aggregate Three-Crop
Total Monetary Losses: Scenario 2 106
53. Probable, Year by Year, Individual and Aggregate Three-Crop
Power Plant Monetary Losses: Scenario 2 107
54. Probable, Year by Year, Individual and Aggregate Three-Crop
Total Monetary Losses: Scenario 2d 108
55. Probable, Year by Year, Individual and Aggregate Three-Crop
Power Plant Monetary Losses: Scenario 2d : 109
56. Probable, Year by Year, Individual and Aggregate Three-Crop
Total Monetary Losses: Scenario 7 110
57. Probable, Year by Year, Individual and Aggregate Three-Crop
Power Plant Monetary Losses: Scenario 7 Ill
58. Probable Three-Crop Total Annual Monetary Losses
by Pollutant: Scenario 2 112
59. Probable Three-Crop Utility Related Annual Monetary Losses
by Pollutant: Scenario 2 113
60. Probable Three-Crop Total Annual Monetary Losses by
Pollutant: Scenario 2d 114
61. Probable Three-Crop Utility Related Annual Monetary Losses
by Pollutant: Scenario 2d 115
62. Probable Three-Crop Utility Related Annual Monetary Losses
by Pollutant: Scenario 7 116
63. Probable Three-Crop Utility Related Annual Monetary Losses
by Pollutant: Scenario 7 117
64. Net Present Value of Compliance Benefits for SO Emissions:
Scenarios 2dT and 2 Compared 118
IX
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A-l. Net Present Value of Probable Total and Utility Related
Cumulative Crop Loss, 1976 to 2000, from SO and O~ :
Scenario 2 142
A-2. Net Present Value of Probable Total and Utility Related
Cumulative Crop Loss, 1976 to 2000, from SO and 0_:
Scenario 2d 143
A-3. Net Present Value of Probable Total and Utility Related
Cumulative Crop Loss, 1976 to 2000, from SO and 0_:
Scenario 7 144
x
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SECTION 1
INTRODUCTION
This report is part of a larger U.S. Environmental Protection Agency
(EPA) funded study, ORBES, which is charged with assessing " the potential,
environmental, social and economic impacts of the proposed concentration of
power plants in the lower Ohio River Basin." Phase II of the project focuses
on a regional analysis consistent with the above mandate. The study region
is defined to include all of Kentucky and portions of Illinois, Indiana, Ohio,
Pennsylvania, and West Virginia (see Figure 1). The regional boundaries for
this phase of the project include most of the Appalachian and Eastern Interior
coal fields, exclude portions of the states where Great Lakes water problems
would be of concern and include most of the Ohio River drainage basin.
The ORBES project is an integrated technology assessment where a set
of scenario models generate regional energy and fuel use characteristics out
to 2000 which are then examined with a variety of impact models for assess-
ment of the economic, environmental, health and social impacts from the
specified developments. The research design is illustrated in Figure 2.
Within this context, the present work focuses on economic impacts and makes
use of research results from several studies earlier in the sequential
information flow in the ORBES experimental design.
In this research, the principal input to the analysis consists of
physical crop losses, by scenario, provided by The Institute of Ecology (TIE)
[1]. These estimates, however, also rely upon several other research project
outputs earlier in the sequence of information flow (figure 2) in the ORBES
project. To illustrate the point, future energy and fuel use, by scenario,
is derived from a model of ORBES-region energy and fuel use [2], which in
turn provides input data on future coal-fired electric demand in the region
to a siting model for generating facilities [3]. The siting model spatially
and temporally allocates the additional capacity in terms of a set of exclu-
sionary criteria. Given the output of the siting model, emission and con-
centration models [ 4 and 5 ] are used to estimate regional emissions and
concentrations of airborne residuals. This information serves as input to
TIE researchers for estimation of physical crop losses, 1976-2000, in the
ORBES region. The integrated assessment process appears to be optimal in
the sense that sets of analytic results in the information flow are tied to
analytic models which capture the implications of energy and fuel develop-
ments in the region and reflect "state-of-the-art" modelling.
Scenarios in this research design may be thought of as sets of future
energy and fuel use characteristics within the region which vary according
to alternative values for economic or electric demand growth as well as
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alterations of policies, or compliance with policies, governing environmental
standards. In all cases, alternative specifications or assumptions are
designed to be feasible in the sense that they can be justified (documented)
as plausible in terms of existing knowledge or literature. Impact results
are investigated for alternative scenarios which are thought to represent
guantitatively interesting differences.
Results for three different scenarios are reported in this work.
Scenario 2 represents a base case or "business as usual" set of future
economic and energy/fuel use characteristics. The scenario assumes State
Implementation Plans (SIPs) on existing units will be complied with and New
Source Performance Standards (NSPS) and Revised New Source Performance
Standards (RNSPS) will be fully implemented for additions to generating
capacity. Scenario 2d is identical to scenario 2 with respect to NSPS and
RNSPS standards being met, but differs in that SIP requirements are not
complied with. Hence, scenario 2d is more "lax" with respect to air guality
than scenario 2. The last scenario discussed, scenario 7, is identical to
scenario 2 except the growth rate for electric capacity, 1976-2000, is
higher and plant life is assumed to be 45 years (35 years in scenarios 2 and
2d). All other assumptions (SIP, NSPS and RNSPS compliance, etc.) are
identical to those in scenario 2. Comparing results as between scenarios 2
and 2d, then, provides differences in monetarized welfare losses to agri-
cultural producers for alternative policy assumptions concerning compliance
with SIPs. Differences between scenarios 2 and 7 reflect alternative assump-
tions concerning anticipated regional growth in electric demand and plant
life. Reported tables are in 1975 constant dollars. In all cases, state
designations in tables refer to the ORBFS portion of each state and the
ORBES region data is specifically in terms of the region identified in
Figure 1.
Two different analyses were performed by TIE [1] and economic loss
estimates were provided for both cases. The first case, discussed in detail
in the main text, was based on nominal load emissions from utilities in the
ORBES Region. The second case (Tables in Appendix A), was based on peak
load emissions from utilities. The present authors are not in a position to
advise the reader as to which set of figures are most appropriate. That is a
question more appropriately resolved by ecologists and botanist working with
physical dose-response curves. For completeness, we report the results of
both calculations. The results reported in Appendix A (peak load emissions)
are only for the probable case. The range between the minimum and maximum
values would be approximately the same as that reported in the main text for
the nominal load emissions.
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SECTION 2
ESTIMATING LOSSES DUE TO AIR POLLUTION: GENERAL DISCUSSION
In terms of existing literature, the relationship between human health
and ambient air quality has preoccupied economists, statisticians, engineers,
epidemiologists and others in their search for understanding the social costs
of productive activities. This is understandable in that primary air quality
standards largely reflect a concern for human health. There are, however,
significant production externalities and public goods effects associated with
ambient air quality that have received far less attention and which fall
under secondary standards. In this section, we discuss the general character
of social costs and the appropriate economic measure of losses associated
with technical externalities (the case of agricultural losses) [see Mishan [6]
for an elementary analysis of these externalities].
An air pollution damage function is a statement of the level of the
harmful physical effects that result from various levels of contaminants
introduced into the air as a result of human and non-human activities or
processes. Air pollution is costly because it reduces the capacity for the
functioning of human activity and natural processes. The cost of air pollu-
tion may be defined as the value that people place on reducing damages
suffered because of air pollution. The greater the reduction of damage, the
greater will be the value attached by people to damage reduction. Cost,
properly understood, is the entire schedule of valuations associated with
various levels of damage reduction.
A host of problems stand in the way of measuring the cost of air pollu-
tion. No market exists which would permit people to make actual payments
based upon their individual valuation. Many pollution costs are unknown
or at best only vaguely perceived. Certain types of pollution damage.though
real, are not understood. Others do not effect some people directly, although
they still place a value on their elimination. Still other costs are recog-
nized and experienced directly, but individuals do not know the valuations
they would place on their reduction. Ideally, an economic analysis of the
air pollution problem entails a comparison of the schedule of the benefits
of pollution reduction with the schedule of the costs of pollution abatement.
Since optimal pollution abatement requires a comparison of incremental costs
and benefits, it would be necessary to develop a schedule of incremental
benefits. Since it is difficult to develop entire schedules of abatement
benefits, it is at least desirable to estimate the benefits which would
result from marginal reductions from current levels of air pollution.
Ridker [7] describes three approaches to the measurement of the cost of
air pollution. The simplest measure is restricted to the estimation of
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direct effects in the absence of adjustments. Monetary estimates of damage
are based upon physical relationships between levels of pollution and extent
of damage, as measured by technical specialists. The dollar value of damage
is derived from market information or independent economic studies. Estimates
of total damage of a certain type may be obtained this way, as well as valua-
tions derived from incremental reductions of pollution.
The other two approaches to the estimation of the monetary value of air
pollution damage discussed by Ridker allow for individual adjustments to
changes in air quality and for important changes that occur in related
markets as the effects spread through the economy; a general equilibrium
approach. Individual and market responses have an important bearing on the
social costs of air pollution damage. Consequently, it is desirable to
account for these responses in order to measure accurately the benefits which
flow from alternative levels of air pollution abatement.
Examples of individual adjustments to increased air pollution given by
Ridker are changing the amount of time spent in the polluted area and making
greater use of protective measures such as air filters and medication. Such
individual responses reduce the damages suffered from air pollution and
distribute the cost over a variety of categories of goods and services that
must be accounted for. Ridker explains market effects as the impact that
individual responses to air pollution have on the market behavior of persons
not directly affected by pollution. For example, spinach growers around
Los Angeles bear the direct costs of air pollution, but increases in spinach
prices transfer some of the losses from producers to consumers. The effect
of the price increase should be taken into account in order to capture fully
the value of crop damage done by air pollution. Additionally, effects in the
spinach market cause reactions in related markets, such as asparagus, which
should be taken into account.
In accounting for the market effects of air pollution, it is important
to determine which effects to count as costs, and which effects merely
represent a transfer of costs between parties. Ridker observes, "To a large
extent such market effects represent a transfer of benefits or costs between
economic units rather than an additional set of consequences not taken into
account (in principle at least) by the second measurement strategy." [7].
In what follows, we present a brief discussion of general equilibrium-
oriented cost-benefit analysis which provides the basis for sorting out the
three types of reactions to air pollution damage. Cost-benefit analysis
provides a set of principles which helps develop a consistent set of accounts
in which pollution damage valuations are added up correctly.
The principles underlying our approach to analysis of air pollution
damage functions are stated by Harberger as "three basic postulates for
applied welfare economics" [8]. They are
a) the competitive demand price for a given unit
measures the value of that unit to the demander;
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b) the competitive supply price for a given unit
measures the value of that unit to the supplier;
c) when evaluating net benefits or costs of a given
action (project, program, or policy), the costs
or benefits accruing to each member of the relevant
group (e.g., a nation) should normally be added
without regard to the individual (s) to whom
they accrue.
In what follows, these principles are applied to an example in which a
steel firm emits pollution which causes damages to a spinach crop. The three
postulates are applied to develop economic measures of pollution damages,
taking into account the individual and market responses by the steel firm and
the spinach growers. The theory is applied to efficiently functioning markets
assuming that the effects of pollution on unit production costs can be
measured.
. The market for spinach is depicted in Figure 3.
Spinach
Figure 3
S and D are supply and demand curves for spinach in the absence of
pollution. Air pollution is emitted by a steel mill in the area, raising the
cost of spinach growing to ^ (supply curve with pollution).
S includes costs which farmers incur to mitigate pollution damage:
Increased labor input may be hired; pollution resistant crop varieties
having lower market value may be introduced; agricultural experiment stations
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may devote portions to their budgets to research mitigating pollution
damage; production may be relocated to areas where pollution is less
severe; as well as other productivity enhancing adjustments. It is assumed
that once these and similar adjustments have been made, "§ becomes the
operative supply curve and represents farmers' response to air pollution.
Equilibrium is q . Physical damage functions typically provide estimates
of the percent reduction of crop caused by air pollution. Output q is the
pollution-free damage function estimate of output. If the spinach farmers
are price-takers, then b is the pollution-free equilibrium point.
If liability for pollution damage is assigned to the steel industry, then
pollution damage to spinach is calculated over Oq spinach output. By
bearing liability for pollution, the spinach growers have been subsidizing
the steel industry by gbzf, the production cost added by pollution to the
pollution-free level of output.
The welfare loss in the spinach market is gbef, the producer surplus that
would be gained if pollution damage could be eliminated entirely (gbef =
gbj (surplus without pollution) - fej (surplus with pollution)). The welfare
loss from pollution is less than the associated subsidy to the polluter;
the magnitude of the difference (ebh) depends upon demand and supply elastic-
ities for spinach.
Generally, the optimal social solution to the pollution problem (the level
of pollution reduction that maximized the net present value of benefits
minus costs in both markets) will not entail complete elimination of pollu-
tion; it may not be socially desirable to return the spinach supply curve
all the way to S. If the optimal policy leaves the supply curve to the
left of S, then the welfare gain in the spinach market will be less than
gbef.
In Figure 4,1? represents the supply curve for steel. It excludes pollu-
tion costs imposed upon spinach growers, since these are not borne by the
mill. *§ is unaffected by any other distortions. S is the mill's supply
curve inclusive of pollution damage to the spinach crop. This cost is the
payment to the spinach growers that would be required to compensate them
for crop losses. Defined as a compensating variation [ 9], the difference
between S and §" is the minimum payment the growers would accept in order
to tolerate the presence of pollution, at any level of steel output.
If the mill has no liability for pollution damage, it will produce
at q : It enjoys a subsidy of P gf?1 from the spinach farmers. P gfP
would be the compensating variation owed to the growers if the liability
were shifted to this polluter. It is equal to gbzf in Figure 3. If the
steel firm were required to compensate the growers (and had recourse to no
other type of adjustment), S would be the steel supply curve and output
would fall to q . P P eh would be paid to the spinach farmers as compen-
sation, wiping out all of the P geP of benefits enjoyed in the steel
industry because of the subsidy. The welfare gain enjoyed by the steel
industry is less than the subsidy received from the spinach farmers, just
as the subsidy given by the spinach farmers to the steel industry is less
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than the welfare loss to the spinach industry.
Xs*
steel output
Figure 4
At this point, it would not be possible to calculate the net welfare
effect of imposing pollution liability on the steel firm, because we have
not analyzed the polluter's response to liability. Assume that the steel
firm abates part of its pollution, but must pay compensation to the spinach
producers for all unabated damage. Output and price adjustments do not
exhaust the options of steel mills. By pursuing abatement, they can reduce
their own pollution costs and confer additional benefit on society.
Faced with pollution liability, the mill will spend additional money
on abatement so long as an additional dollar of abatement expenditure reduces
required compensation by more than a dollar. The first dollar spent on
abatement reduces compensation payments by more than a dollar, and likewise
for each succeeding abatement dollar, until required compensation is reduced
no more than additional abatement expenditure. For additional abatement
expenditure, total firm cost (abatement plus compensation) would be greater.
Referring to Figure and 4, the first dollar of abatement expenditure
reduces required compensation payments by more than a dollar. Compensation
is required over all Oq units of spinach output. The steel firm's supply
curve, S, shifts down. Each succeeding dollar of abatement expenditure
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shifts S further until S' is reached, and further abatement would be uneconom-
ical for the steel .firm. Unabated pollution damage to spinach is compensated,
so that the operative supply curve in the spinach market is S. Spinach
output is q and steel output is q'.
S' is the steel firm's least cost solution to the problem of pollution
cost. S1 in Figure 4 is the mill's supply curve inclusive of both abatement
costs and compensation payments, as compared with supply curve S, which the
mill would face if it paid compensation without abatement. At the profit
maximizing level of abatement, the mill incurs P P'vz pollution costs,
including abatement and compensation, and produces q1 level of output.
The response of the steel firm to pollution liability has the effect
of eliminating ztfg + P'P of pollution costs, and the steel firm pays
P P'vz for abatement compensation. There is a welfare loss of P P'vg =
P jg (surplus before liability) - P'jv (surplus after liability) . In the
spinach market, all of fzbg costs have been eliminated. The corresponding
welfare gain is febg. The net welfare gain resulting from assigning full
liability to the polluter, including the compensation requirement, is febg
(spinach market) - P P'vg (steel market). That this is, in general, not
an optimal solution, is explained in the next section. The welfare effect
of the mixed strategy can be viewed as occuring in two steps. The first
step, compensation plus output reduction, shifts the steel firm's supply
curve to S. The second step (introduction of abatement equipment) shifts
the firm's supply curve to S1. To evaluate the welfare effect (the first
step), consider the supply curve shift from "§ to S with output remaining
at q . Required compensation payments are P P..fg. Growers are fully
compensated for damages incurred at q steel output. Steel producers are
induced to reduce their output to q .
It has been noted that the welfare loss in the spinach market (Figure 3)
is smaller than the additions to the cost of producing the pollution-free
amount of spinach. Likewise the subsidy enjoyed in the steel market
(Figure 4) is larger than the welfare gain that results from it. The conse-
quence of these differences is that the net welfare gain calculated in the
preceeding section is generally not the greatest attainable. To establish
this point, consider a special case in which that gain is the maximum
attainable; suppose the demand curves in both markets are perfectly inelastic:
q..h in the spinach market (Figure 5) and q .in the steel market (Figure 6).
With perfect inelastic demand curves there are no output adjustments to
pollution, abatement or compensatory payments as illustrated in Figures 5
and 6. In this case as S" shifts to S in the spinach market, the entire
steel subsidy, fzbg, when removed from the spinach market, constitutes a
welfare gain to spinach consumers. The removal of the subsidy constitutes
a loss to steel consumers equal to P gwP1. But P gwP1 is less than fzbg
(recall that P qfP., = fzbg), the way S' is divided, the difference between
the welfare gain to spinach consumers and the welfare loss to steel consumers
is maximized.
Negatively sloped demand curves change the relationship between gains
and losses in the two markets. Suppose that the spinach demand is more highly
elastic than demand for steel. Then as price falls in the spinach market,
8
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Figure 5
spinach
output
Figure 6
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the welfare gain falls short of the subsidy reduction, more so as demand is
more highly elastic. In the steel market, as price rises with the removal of
the subsidy, the reduction in consumer surplus approaches the full value of
the subsidy as demand is less elastic. The conclusion is that, depending
upon demand elasticities, maximum net social benefit will be achieved with
spinach output less than q and steel output greater than q . The larger is
ezb relative to vgw, the greater will be the divergence from the optimal
solution of the previous section.
Figures 3 and 4 illustrate the determination of maximum net welfare
gain. The first unit of abatement raises S in the steel market slightly.
In the spinach market, S falls relatively much compared to the increase in
steel cost. A relatively large reduction in required compensation over Oq
spinach output is achieved. Also a relatively large gain in surplus is
achieved. The next unit of abatement raises steel production costs more
than the first, and required compensation to spinach growers falls, but by
less than the first decrement. Likewise, the gain in surplus in the spinach
industry increases by a lesser amount than the first increment. Additional
units of abatement are purchased by the steel industry so long as the gains
in surplus in the spinach industry exceed the losses of surplus in the steel
industry. When the gains and losses of surplus are equalized at the margin,
the net welfare gain from abatement is maximized. The solution is labelled
in both markets. The gain is femn - P cdg.
o
To achieve this solution it is required that no compensation be paid
for abatement pollution. The resulting supply curves, labelled S* in both
markets, represent the optimal adjustment, and in this sense are undistorted.
The optimal result is achieved by applying the principle of compensation, or
willingness to pay, to both markets, but not actually paying compensation
for unabated pollution.
Measurement of pollution damage costs consistent with the foregoing
analysis requires knowledge of elasticity of demand and supply both for the
product whose production generates pollution and the product damaged by
pollution. ASsume that spinach .farmers are price-takers in the market for
their output. This is a realistic assumption for agricultural output
affected by air pollution in the ORBES region. While it simplifies demand
analysis on the output side of the agricultural market, nevertheless it is
still necessary to match supply prices with demand prices from time series
price data in a way which is consistent with the agricultural output decision.
On the supply side, it is essential to estimate the effect of pollution
on unit costs of production. In the spinach industry, the supply curve
inclusive of pollution (§") must be estimated. In order to determine S* (the
spinach supply curve with socially optimal abatement), the responsiveness
of units costs to spinach production with pollution reduction must be deter-
mined. In the steel industry, it is necessary to estimate S and the extent
to which unit costs increase with various levels of abatement. We have
assumed less than perfectly elastic demand in the steel industry. In order
to measure the social cost of pollution reduction, it is necessary to
determine the steel demand curve in the relevant output range, because social
cost of abatement will exceed abatement expenditures to the extent that steel
demand is curtailed by increased steel cost.
10
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If physical damage function information is sufficiently complete to permit
estimation of the change in unit costs of both steel and spinach, then it
will be possible to determine the optimal level of abatement. With less
complete damage function information, it would be necessary to settle for
estimation of net present values of discrete abatement strategies.
Up to this point, the analysis has been focused solely on the markets
directly affected by air pollution, and it has been assumed that air pollution
creates the only relevant market distortion. However, a complete analysis
of the problem requires that other distortions, such as tax distortions, be
taken into account, and that reactions in other markets which occur because
of air pollution, be considered.
To illustrate what is involved, suppose that because of air pollution
damage to the spinach crop, the price of spinach rises, causing the demand
curve for asparagus to shift to the right from D to D . Suppose also that
the sale of asparagus is subject to tax. In Figure 7, ^ is the supply
curve for asparagus inclusive of the tax, and S is the undistorted supply
curve showing competitive supply price at each level of output. At the
equilibrium output, q , competitive demand price measured from DH exceeds
1
competitive supply price measured from S. A welfare loss, equal to the
distance between S and "s at q , exists because of the tax. Expansion of
Asparagus
output
Figure 7
11
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output to q along D would eliminate the welfare loss equal to the triangle
between q and q . Consider demand curve D, which represents a small portion
of the increase in demand for asparagus. Output expands slightly, and over
that range of output competitive demand price exceeds competitive supply
price. Consequently> there is a welfare gain associated with the expansion
in output. This condition persists throughout the entire range of output,
yielding a welfare gain equal to the shaded area in the diagram. Since this
effect is caused by market activity attributable to air pollution, it should
be counted as a welfare gain and included in the account of costs and benefits
developed earlier.
In the development of a general equilibrium analysis of the costs and
benefits of air pollution control, ideally the researcher should identify
all such related markets where substantial welfare gains or losses are likely
to occur. A more complete analysis of the steel and spinach markets in the
present example would also have included an analysis of the welfare effect of
tax and other distortions. For a detailed treatment of the analysis of tax
distortions, see Harberger [10],
12
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SECTION 3
ESTIMATION OF AGRICULTURAL LOSSES DUE TO AIR POLLUTION:
THE ORBES REGION ANALYSIS
The discussion in the preceeding section illustrated an ideal analysis
for estimating the optimal pollution level taking into account the pollution
recipient and generator as well as general equilibrium effects on closely
related markets. Resources did not permit undertaking such an activity in
terms of agricultural damages in the ORBES region. The present effort is
restricted to estimation of direct social costs borne by agricultural
producers from airborne residuals in the region. The appropriate monetary
loss value is still the notion of "surplus" (in this case, producer surplus
only) and represents an underestimate of total direct and indirect social
losses in that effects on closely related markets (transportation sector,
etc) are not considered. Nonetheless, this analysis does provide a consist-
ent and theoretically correct measure of direct social costs borne by ORBES-
region agricultural producers. A shortcoming of the analysis is the failure
to estimate the optimal pollution level in the region in terms of agricultur-
al damages. In point of fact, however, such an estimate would be an inappro-
priate guide to setting standards in that other externalities (damage to
property, health damages, etc.) would not be included nor would other
pollution sources (industrial boilers, for instance).
Agricultural damages due to "dirty-air" represent a technological
externality. That is to say, various economic activities produce combustion-
related airborne residuals which directly enter the production (cost)
functions of agricultural producers. These residuals reduce agricultural
productivity below those levels which would be associated with "clean-air"
and represent, therefore, external costs to producers. Producers experience
such losses in terms of reduced productivity per unit input (higher costs
per unit output) and consumers in terms of potentially higher prices for
agricultural goods [11, 12].
The appropriate welfare measures of external costs to agricultural
producers and consumers from a given level of ambient air quality would be
the sum of producer and consumer surplus losses in agriculture [13].
As noted in the preceeding section, full accounting of all social costs
for purposes of cost-benefit or policy analysis would also require estimating
costs and benefits in all closely related markets; a general equilibrium
approach This work focuses only on direct welfare losses in the
agricultural sector experienced by producers.
Figure 8 illustrates the measure of producer welfare losses used in this
13
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Price
Production
Curve S represents a "pollution-free" supply curve for ORBES produc-
Producer surplus with a pollution-free environment consists of the area
work.
ers.
aP b. The effect of SO
~t ~. ^^ ^o.^., ~>. ^~ and O within the region is to reduce productivity
ana, hence, production to Q . This is associated with a shift leftward of
the supply curve to form a new curve, S , passing through the fixed price
line, P , at point d. With the dirty-air supply curve S , producer surplus
is measured by the area cP d. The losses due to SO and 0 , then, consist
of the difference in producer surplus or the area aP b - cP d = acdb. It is
this magnitude that we wish to measure annually over the period 1976-2000 for
the ORBES region.
In this analysis, we assume regional producers are "price takers". That
is, the producers of specified crops operate in competitive markets and
variations in individual output levels do not influence market price. This
is a potentially limiting assumption in the ORBES region as regional corn
production, for instance, constituted 35% of total U.S. production in 1977.
By using a fixed price assumption, then, we may underestimate the producer
surplus losses: The market price for corn might have been lower in 1977 if
all producers were not affected by ambient air quality and, as a consequence,
potential welfare losses would reflect both price (from changes in market
supply) and quantity (from supply shifts within the region) effects. On the
other hand, the potential influence on market price might be negligible or
zero if productivity enhancing methods or crop substitution possibilities
were not feasible in the region [see 11,12 , 13 , 14 , 15 for a discussion of
these matters]. In this case, regional producers would simply derive a
lower "rent" on agricultural land which would ultimately be reflected in
lower land prices than would be realized with clean-air production while
unaffected producers would expand output.
Following the analysis suggested in Figure 8, producer discounted losses
14
-------
are estimated for each year, 1976-2000, with a 10% discount rate. Discounted
'losses are then summed to estimate the present discounted value of cumulative
producer surplus losses. For comparative purposes, we also estimate the
cumulative present discounted value, 1976-2000, of potential clean-air produc-
tion assuming the real price of agriculture goods, 1976-2000, is unchanged
as is clean-air crop production. The above calculations assume (1) prices of
affected crops increase at the same rate as inflation and (2) the size of the
regional agricultural sector is unchanged over time with respect to the
affected crops.
15
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SECTION 4
DATA BASES AND PARAMETER ESTIMATES
The procedure described in the previous section requires estimates of
several parameters. We need estimates of the annual real price and output
of affected agricultural goods, 1976-2000, supply elasticities for each,
the size of the regional agricultural sector with respect to the three crops,
and clean-air production as well as anticipated annual production over the
period in the presence of airborne residuals.
Tables 1-3 contain the seasonal average prices, 1965-1978, for the three
affected crops (corn, soybeans and wheat) in each of the six states wholly
or partially in the ORBES region. No prices were recorded for soybeans in
Pennsylvania and West Virginia as there is no production. These data are
used for calculation of the fixed price lines, one for each crop, represented
in Figure 8. The prices used in the analysis were calculated as weighted
average prices of crops, by state, based on the annual prices received
by farmers over the 1965-78 period. The weighted averages were computed
by weighing state price in each year by the percent that years' production
is of the 1965-1978 total production in the state. The results of these
calculations appear in Table 4. By using weighted averages, we avoid the
influence on average price associated with a few years of unusual crop
conditions. In the analysis, we assume the weighted price for each crop and
state is unchanged, 1976 to 2000. This is eguivalent to assuming agricul-
tural prices increase at the overall inflation rate over the study period.
The production data for the three crops and six states used in weighting
annual prices received from farmers is contained in Tables 5-7. These data
describe the size, in physical units, of the agricultural sector in the
respective states as well as the six-state area. The reader is cautioned
that production for, say 1978, already includes adverse effects from ambient
air quality.
As our calculation of annual producer surplus losses relies on a
procedure for shifting supply curves, it was important to have reliable
estimates of supply elasticity for each crop. This is the case as the
magnitude of losses identified in Figure 8 (abdc) is uniquely dependent
(given fixed prices) upon the elasticity of supply. It has been our exper-
ience that secondary source information on supply elasticities for the three
crops was not adequate for our purposes. The primary problem was the large
range in estimated values even in the case of studies focusing on producing
areas which overlapped with the ORBES region. The variation in literature
estimates was even more pronounced when considering regional, as contrasted
with national, studies [16]. Further, it was not possible to select
16
-------
literature elasticities for each crop based on similar specifications,
geographic areas, and years covered by data sets. We provide, then, our own
supply elasticity estimates for each crop based on six-state output and
price data, 1965-1978.
We follow, as does most recent literature, the Nerlove distributed lag
structure for estimating agricultural supply elasticities [17]. Nerlove ' s
model incorporates past (observed) information as well as information about
future expectations of the economic agent. Expectations are formulated on
the basis of past information. However, not all past information has equal
influence on the producer. Recent past values are more indicative of future
price expectations than more distant past values. Hence, a decisionmaker 's
formulated future expectation can be expressed as a weighted moving average
of past values in which the weights decline as one goes back in time. Model
construction using an adaptive expectations process is more representative
of decisionmaking and yields inferences more useful for theoretical and
policy analysis than a naive model where the present fully represents the
future .
The model reduces to a form representative of either a stock adjustment
or an adaptive expectations process where a Koyck distributive lag prevails.
In reduced form the two processes are of identical specifications making
them indistinguishable. Following Nerlove [17], this work uses an adaptive
expectations form. In structural form the system is represented as follows:
(1) Q - aP + U
P;
where
Q = observed output in acreage harvested
*
P = expected price
*
P = expected price lagged one period
P
t-1 = observed price lagged one period
a = observed price parameter
6 = reaction or adjustment coefficient ( 0 < 6 < 1 )
and U = error term.
Equation (2) can be made stochastic by the inclusion of an error term, how
ever this does not alter the postulates, the analysis, nor the estimates.
17
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Simplification yields equation (2) as
0) P; = ap^ + d-6) ?;_,
and substituting into equation (1) provides
(4) Q = a6P . + o(1 - 6) P
where from equation 1
Lagging we get,
P* = 1/a Qt - 1/a Ufc.
(5) Pt-1 = 1/a Qt_1 - 1/a
*
and substituting this expression for P into the equation for Q above
and simplifying yields
Qt = "6Pt_-, + o(1-6) 1/a<2t-1 " a 1/Qt(1- 6) Ut_i + Ut
Qt = a6Pt-1 + (1~6) Qt-1 + Ut " (1~6) Vl
and finally
(6) Q = a6P + (1-6) Q + E
In structural form equation (1) relates observed output (acreage
harvested) Q as a function of expected price P an^ an error term U and
equation (2) relates the change in expected price P from one period to the
next to the difference in prior observed and prior expected prices, P .
and P respec
equation (2) as
and P respectively, by an adjustment factor 6 . Alternatively expressing
* * *
P = P + 6(P - P
t t-1 + °V t-1 V t-1)
°r 0 < 6 < 1
Pt ' 6Pt-1 + (1-6) Pt-1
*
for substitution into equation (1) reveals expected price^P as a function
of lagged observed price P and lagged expected price P where the
adjustment factor 6 appropriately determines the corresponding coefficients
of P._1 and P._1 - If the value of 6 is equal to zero, actual price would
not influence expected price. On the other extreme, if 6 is equal to one
the expectations equation reduces to a naive model where expected price
would equal the previous year's actual price. Following Nerlove, 6 can be
18
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called the coefficient of expectation which underlies the postulate that
decisionmakers formulate expected price in some proportion to the difference
in the previous observed price and their previous concept of expected price.
Equation (2) is a first order difference equation that can be solved for
P . Solving yields
(7) P* = £ QCl-Q)*''1 P. ,
t . i-1
1=0
which expresses the decisionmakers concept of expected price as a weighted
average of past prices where the weights decline as one goes back in time,
since 0 < 6 <. 1
Empirical application requires reduction of the Nerlove system to an
estimable form as expressed in equation (6). This is the resultant specifi-
cation for deriving short-run agricultural supply elasticities. In this
reduced form, observed output (acreage harvested) Q becomes a function of
lagged observed price P , lagged observed output Q , and an error ex-
pression. For the short-run elasticity case, the Nerlove model is in reduced
and empirical form becomes a Koyck distributed lag and is estimated
accordingly.
There are problems obtaining unbiased estimates and significant
coefficients with this specification, although the model is widely used for
estimation of crop supply elasticities [18, 19, 20].
While a number of estimating procedures were tried, our best results for
all three crops were obtained with autoregressive procedures utilizing a
maximum likelihood technique for the Koyck lag specification. The best
specifications for equation (6) above for, respectively, soybeans, wheat
and corn were as follows:
(10) Q' = a° + B^ Q^ + B22 P^ + BC3 Pj^ + B^ t + UCfc
where superscripts denote the crop and t represents a time trend. Soybeans
and corn are substitutes in consumption and appear also to be production sub
stitutes within the region. The best results were obtained when corn and
soybeans were treated as substitutes by entering the substitute prices
lagged one period in the estimating equation for each of the two crops
(equations 8 and 10). The resulting mean elasticities for soybeans, wheat,
and corn, respectively, are .263, .56, and .187. In all three cases, these
values are within the range of values reported in existing literature.
Complete results of our estimations are in Table 8.
Estimation was based on price and output data reported in Tables 1-3
19
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and 5-7. The quantity variable which proved most successful was acreage
harvested rather than bushels. This information was calculated from Tables
5-7 and data on yield per acre. After the transformation to acres harvested,
state level data was aggregated to the six-state region. The price series
was calculated by summing over the six states for each reported crop price
and calculating a weighted average where the weights were the proportion
each state's production was of total six-state production.
An adjustment to the formulation of the supply curve for each crop
was required in our estimation of direct producer welfare losses. Econo-
metric estimates of supply curves are based, of course, on observed time
series, cross-section or pooled time series and cross-section data. In
general, the estimated elasticities are valid only over the range of
observations used in estimation. Whatever the estimation techniques, the
supply curve is not well defined outside the range of observations (there
are other approaches to estimation which can avoid this problem, although
they were not feasible in this case). Many literature estimates of
agricultural supply functions, particularly using linear models, suggest
negative intercept terms. This was true in our estimating equation for
soybeans. For dealing with questions of supply responses in the neighbor-
hood of equilibrium, this is not a problem. When conducting welfare analysis
which relies on areas such as aPob in Figure 8, however, this is a serious
problem. If curve S in Figure 8 is drawn with a negative intercept, the
notion of producer surplus as a welfare measure is, in our view, vacuous.
Accordingly, we adjust our empirical supply curves to reflect a "constant
elasticity of supply" over the relevant range. This is equivalent to
assuming b (elasticity) is constant in the equation
Q = aP .
The parameter a is solved for in each year and fixes the position of the
supply curve. This procedure appears justified in that our estimated
elasticities are "mean" elasticities. The adjustment produces analytic
supply curves with zero intercepts and convex from below.
The final information requirement for the analysis is for physical
crop loss estimates to corn, soybeans and wheat from airborne residuals.
As noted in the introduction, this work was performed by The Institute of
Ecology (TIE) [1] and serves as input to our own analysis. Details concern-
ing the estimation of crop losses may be had from the TIE reports [1].
TIE data consists of physical crop losses at three points in time;
1976, 1985, and 2000. To properly estimate cumulative welfare (monetary)
losses to agricultural producers, it is necessary that we have annual loss
estimates. The emissions and concentrations data provided to TIE by Teknekron
Research, Inc. (TRI), as well as the methodology for estimation of
physical crop losses, are roughly linear over the 1976-1985 and 1985-2000
periods. Losses, then, are the product of two linear schedules and linear
interpolation can be used for intervening year estimates of physical losses.
Accordingly, we estimate annual losses by using linear interpolation within
each of the two subperiods. Losses are broken down by crop, by ORBES-portion
of states, by pollutant, and in terms of total and utility-related losses.
20
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SECTION 5
EMPIRICAL ESTIMATION OF MONETARY WELFARE LOSSES
TO AGRICULTURAL PRODUCERS
The procedure for estimating monetarized welfare losses to ORBES-region
agricultural producers from airborne residuals consists of several steps.
The best way to illustrate the procedure is with a detailed example calcula-
tion. For that purpose, we describe below the method of calculating monetar-
ized losses to Illinois (ORBES-portion) corn producers.in 1984. Similar
calculations are performed for the ORBES-portion of each state, each crop,
each year, each scenario, for minimum, maximum, and probable losses. The
example calculation is with respect to scenario #2 conditions and probable
physical losses.
Four different calculations are performed for estimating 1984 monetar-
ized losses to Illinois corn producers:
1. Monetary damage avoided due to implementation of SO regulations.
2. Monetary damage remaining after implementation of SO regulations.
3. Monetary damage attributable to power plant share in O damages.
4. Total monetary damage due to all 0_ sources.
The following data are input to the calculations:
1. The constant real price of Illinois corn ($2.05 per bushel from
Table 4).
2. Illinois corn production in the absence of SO and O pollution
("clean-air production" level of 1,087,859,915 bushels).
3. The corn price elasticity of supply (.18666 from Table 8).
4. Probable corn loss due to SO pollution (calculated from data in
TIE report [1]).
5. Probable corn loss from all sources of O (calculated from data in
TIE report t1]).
6. Percent of O induced corn loss due to power plants (40% as provided .
to us by TIE researchers).
Two assumptions are made. First, the supply function is of the constant
21
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elasticity form, Q = aP , where Q is output of corn, P is price, b is the
price elasticity of corn and a is a parameter implicitly defined by Q, P, and
b. Secondly, we assume that crop losses increase or decrease at a constant
rate between benchmark years (1976, 1985, and 2000).
SO Monetary Estimates
With no further abatement over and above that realized in 1976, SO corn
losses are 263,265 bushels in 1976 and 263,990 bushels in 1985. The growth
rate relating these losses is given by r in the equation
263,990 bu = (263,265)e9r.
The value of r is .00031 and estimated SO physical losses in 1984 are
(263,265)e8(-°°031)
or 263,999 bushels. Corn output in 1984 would have been 1,087,596,006
bushels (1,087,859,915 - 263,909) if 1976 conditions prevailed throughout.
With SIP compliance (scenario #2), corn losses are 263,265 bushels in
1976 and 132,245 bushels in 1985. The growth rate between 1976 and 1985 is
-.07650 and projected loss in 1984 is 142,760 bushels =^(263,265 )e( .
Corn production is estimated to be 1,087,716,155 bushels (=1,087,859,915
bushels - 142,760 bushels) in 1984.
The "pollution-free" output level is 1,087,859,915 in 1984. The reader
is reminded that we assume the size of the agricultural sector is invariant
over time so that the pollution-free output level for any year is always
identical to the 1976 value.
Figure 9 illustrates the calculation of monetary damage in terms of
areas. We define two areas of concern; damage avoided and remaining damage.
Damage avoided is the monetary value of the difference between producer
surplus if 1976 conditions had continued throughout the period and producer
surplus with SIP compliance. This is represented by the area between supply
curves L and M. Remaining damage is the difference in producer surplus
between clean-air production conditions and conditions associated with SIP
compliance (scenario #2) or the area between supply curves R and M. It is
the remaining damage area that we report as the losses to Illinois corn
producers in 1984. The damage avoided area is included in the discussion
only for completeness in the analysis. One can think of the entire area
between curves L and R as the damage that would have resulted from a scenario
which asserts 1976 air quality continues throughout the entire period.
Such a scenario was not analyzed in the ORBES project.
Each of the three supply functions has the form Q = aP and the implied
values of the a parameter for each curve is as follows: L, 952,509,635
bushels; M, 952,614,861 bushels; and R, 952,740,765 bushels.
22
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Corn
price
M
corn
production
Figure 9
The area bounded by the price of corn, the vertical axis and any supply
function is given by
$2.03504
J
0
aP'18666 dP
or
= a(
1
1 .18666
) ($2.03504)
1 .18666
where a takes on different values for L, M, and R. Each such area represents
the appropriate measure of producer surplus for the relevant supply curve.
In this instance, the areas are as follows: L, $1,865,152,087; M,
$1,865,358,135; and R, $1,865,604,673. The difference in areas define
damages avoided and remaining damages. The former is the difference in
areas as between L and M while the latter is between M and R. In this
instance, damages avoided are $206,048 and remaining damages are $246,538.
Remaining damages are what we report as monetarized agricultural loss
estimates for Illinois corn producers from SO levels in 1984. One way to
view the benefits of SIP compliance under scenario #2 would have been to
consider the difference between L and M as the benefits of compliance
($206,048); benefits from not continuing with the same level of air pollu-
tion (SO ) as was experienced in 1976. This perspective was not persued
as the ORBES project does not analyze such a scenario. Conceptually, then,
the damages reported are representative of the difference in consumer surplus
23
-------
between what would have been experienced with clean-air production levels
and what is anticipated to occur under SIP compliance assumption of scenario
#2.
0 Monetary Estimates
Corn losses due to O are 8% of pollution-free output for 1976 and 11%
for 1985. Thus, pollution losses are 87,028,793 bushels in 1976 and
119,664,591 bushels in 1985. The implied growth rate is given by r in the
equation
119,664,591 bushels = (87,028,793 bushels)e
r is .03538 and the estimated loss in 1984 is
115,504,444 bushels = (87,028,793 bushels)e
9r
where
8(.03538)
Forty percent of this loss is attributed to power plants, some 46,201,777
bushels. Corn production in the presence of all sources of 0 pollution is
972,355,471 bushels (=1,087,859,915 bushels - 115,504,444 bushels). If there
were no power plant C>3 pollution, output would be 1,018,557,248 bushels
= (972,355,471 bushels + 46,201,777 bushels). These estimates and the
monetary damage due to all sources of 0 pollution and that part attributed
to power plants are illustrated in Figure 10.
$2.03504
0
M
R
corn
-production
^
V
Figure 10
The monetary damage attributed to 0 power plant pollution is the area
between supply functions M and L. Total 0 damage is the area between R and
L. Before solving for these areas, we find the values of the "a" parameter
in the equation Q = aP . These are given below.
24
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Supply function "a" parameter
L 851,582,711 bushels
M 892,045,932 bushels
R 952,740,765 bushels
The areas bounded by the supply functions, the price line, and the vertical
axis are
Areas bounded by price, vertical
Supply function axis and supply function
L $1,667,522,524
M $1,746,755,383
R $1,865,604,673
Total 0 damage (R-L) is $198,082,149. Power plant damage (M-L) is
$79,2327859.
Total monetary losses to Illinois corn producers in 1984 is the sum of
SO losses ($246,538) and total 0 losses ($198,082,149) for the scenario
#2 probable case. Losses attributable to utilities are SO losses ($246,538)
plus 40% of total 0 losses ($79,232,859).
All results are in constant 1975 dollars with a 10% discount rate applied
to annual losses.
The above procedure, then, is followed for each crop, each state, each
scenario and for minimum, maximum, and probable estimates. Total damages
to the ORBES region are calculated as the sum over the ORBES-portion of each
state.
25
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SECTION 6
DISCUSSION OF RESULTS
All results and quantitative interpretation of nominal load emission
results are found in Tables 9 through 64 and Figures 11 through 28. Results
for the peak load probable case are in Appendix A.
Table 9 contains present discounted value> by crop and area, of pollution-
free cumulative production, 1976-2000. Tables 10-15 contain net present
value of cumulative crop losses, 1976-2000, for scenario #2 in terms of total
and utility related losses for minimum, maximum and probable cases. Tables
16-21 contain similar information to that in Table 10-15 except results are
reported by individual crop. Tables 22 and 23 contain the same information
as found in Tables 10-15 except losses by individual pollutant (SO and O )
are presented. For scenario #2, then, Tables 10-15 provide information on
losses where damages to the three crops are aggregated as well as damages
from both pollutants. Tables 16-21 provide similar information, but damages
to individual crops are presented. Finally, Tables 22 and 23 isolate the
damages by pollutant for the aggregate of the three crops. In all of the
above tables, results are presented in terms of the net present value of
cumulative losses (annual results are not presented). Tables 24-37 and
38-51 provide analagous information for, respectively, scenarios 2d and 7.
Tables 52 through 57 contain annual information on individual and
aggregate crop losses, by scenario, for the probable damage case in terms of
total and utility losses. These tables are in 1975 dollars but values are
not discounted with the 10% rate. The purpose of the tables is to reveal
the time trend (in 1975 dollars) of individual and aggregate monetarized
crop losses, by scenario, for the probable case. Annual minimum and maximum
loss tables are not presented as the time trend of such losses are identical
to those for the probable case although the absolute values, of course, are
different.
Tables 58 through 63 again present annual data as in Tables 52 through
57, except the data breaks out the aggregate three-crop damages in terms of
SO and O- and total damage.
The last table, Table 64, contains information on the benefits from
compliance with SIP regulations (contrast between scenarios 2 and 2d). This
table provides benefit calculations for the minimum, maximum and probable
cases by crop area.
Figures 11 through 16 provide visual representation of the distribution
of regional losses, both total and utility, across ORBES-portions of the
26
-------
six states for all three scenarios based on nominal load emissions. In each
case, the first bar contains information on maximum, probable and minimum
losses while the remaining bars portray the percent of aggregate three-crop
loss percent shares for the ORBES-portion of each state, probable case.
Minimum and maximum percentages are not shown as they are, for all practical
purposes, identical to those for the two probable cases.
The last two sets of figures, Figures 17 through 22 and Figures 23
through 28, contain, respectively, computer plots of data found in Tables
52 to 57 and Tables 58 through 63. The plots are designed to provide the
reader with a more intuitive grasp of the time trends of, respectively,
annual losses by crop and annual aggregate crop losses by pollutant.
There obviously exists a great deal of information contained in these
tables. Below we provide interpretation of those results which are thought
most relevant or interesting in terms of the ORBES project. Interested
readers may find other reported results of more relevance.
In general, we discuss our results with respect to probable losses.
Minimum and maximum results are briefly discussed in order that the reader
may understand the range of possible losses. Minimum and maximum results
are presented in order that the reader may explore further the range of
results. For the most part, however, we think the probable estimates are
the most likely outcome to be experienced in the context of the ORBES
scenarios -
Losses Based on Nominal Load Emissions
As a percent of probable losses, the total regional losses for the
minimum and maximum cases are, respectively, 65.2% and 161.5% of the probable
losses for scenario #2. For losses uniguely attributable to utilities, the
corresponding percentages are 49 and 201.7. For scenario 2d (non-compliance
with SIPs), minimum and maximum estimates for total losses are, respectively,
65.1% and 161.5% of the probable loss while corresponding percentages for
utility related losses are 48.6 and 201.6. Finally, for scenario 7 (high
growth in electric demand and 45 year plant life), minimum and maximum total
losses are, respectively, 66.7% and 160.7% of probable losses while for
utilities the corresponding percentages are 73.7 and 266.2. There exists,
then, rather a large range in estimates as between minimum and maximum
cases. This range in monetary values is attributable to the range in physi-
cal crop damages reported by TIE [see 1]. These absolute amounts correspond
to the percentages represented in the first bar of each bar graph in Figures
11 through 16.
Most results reported here (except annual results) are relative to the
present discounted value of pollution-free cumulative value of production,
1976-2000 (Table 9). These calculations reveal the present value of producer
surplus from corn, soybean and wheat production in the ORBES-region, by
state and for the region, if production levels were consistent with clean-
air and were constant through time. The cumulative value of clean-air
production is unevenly distributed over the region with respect to crops and
ORBES-portion of states. In terms of the three-crop total value,
27
-------
approximately 78% of clean-air value is concentrated in Illinois and Indiana
and 93% in Illinois, Indiana, and Ohio. Corn alone accounts for 57% of total
clean-air discounted value and corn and soybeans together account for 94%.
Clearly, wheat is a minor crop in the ORBES region and ORBES-portions of
Kentucky, Pennsylvania, and West Virginia minor producers of all crops.
One expects, then, that losses will be concentrated both by crop and by ORBES-
portions of states.
The discounted present value of probable cumulative total crop losses
under scenario #2 are 11.9% of the corresponding value of clean-air produc-
tion. Utility losses are 4.8% of the value of clean-air production. These
values are largely invariant across scenarios: In scenario #2d, total and
utility losses, respectively, are 12% and 4.8% of clean-air production while
corresponding percentages in the case of scenario #7 are 12.3 and 4.2. The
first important conclusion, then, is that probable total crop losses, 1976-
2000, are approximately 12% of the discounted present value of clean-air
production and utility related losses approximately 4.8%. These percentages
are invariant with respect to alternative assumptions concerning utility
compliance with SIPs (scenarios 2 and 2d) or alternative rates of regional
growth (scenarios 2 and 7) in electric demand.
The distribution across the ORBES-portions of states of total and utility
losses are also invariant with respect to the three scenarios. In the case
of scenario #2, the percent of total regional losses attributable to ORBES-
portions of states for, respectively, Illinois, Indiana, Kentucky, Ohio,
Pennsylvania and West Virginia, are 53.6, 25.1, 6.9, 14, 0.4 and 0.1. With
respect to. utility losses, the corresponding percentages are 53.6, 25, 6.9,
14, 0.4, and 0.1 (Tables 14 and 15). The percentages are almost identical
for scenarios 2d and 7 (Tables 28, 29, 42 and 43). Similarly, losses are
invariant in the case of minimum and maximum losses. The three-crop total
losses, then, are highly.concentrated: Illinois and Indiana accounting for
approximately 78.6% of total ORBES-region losses and Illinois, Indiana, and
Ohio accounting for 92.6% of losses. This conclusion is invariant with
respect to the three scenarios considered in this work and reflects the
spatial distribution of losses for both total and utility related cases.
Figures 11 through 16 provide visual representation of the above data
for the cases of total and utility related probable losses. As noted earlier,
minimum and maximum percent bar graphs are not presented as the distribution
across ORBES-portions of states is virtually identical.
The distribution of regional losses by crop is also unevenly distributed
for the minimum, maximum and probable cases, although invariant with respect
to scenario conditions. For the probable case (Tables 20, 21, 34, 35, 48,
and 49), total and utility related regional losses for scenario #2 are,
respectively, 40% and 39.9% for corn, 56.7% and 56.7% for soybeans and 3.4%
and 3.4% for wheat. In percentage terms, the largest regional losses, then,
occur in the case of soybeans, the second largest in corn and the least
in wheat production. With respect to both total and utility related losses,
corn and soybean losses dominate the total: 96.7% for total losses and
96.6% for utility related losses. This distribution of losses tends to
reflect the prominent role of both corn and soybeans in the region and the
28
-------
relatively minor role of wheat production. It also reflects the concentration
of pollution-free production of corn and soybeans in Illinois, Indiana, and
Ohio.
In terms of the three-crop losses associated with the two pollutants,
SO and 0 , the conclusions are quite clear: 0 damages dominate both
total and utility-related damages in the ORBES region. For the probable
case, scenario #2, regional-wide total and utility losses, respectively,
from O constitute 99.7% and 99.4% of total SO and O damages while
corresponding percentages for scenarios 2d and 7, respectively, are 99.5%
and 98.0% and 99.7% and 99.4%.
Tables 52 and 57 provide information on the annual losses by crop,
scenario, and total versus utility related, from SO and 0 concentrations
in the region. The reader is reminded that these data are in terms of 1975
dollars but are not discounted to present value. Figures 17 through 22
provide computer plots of that data found in Tables 52 through 57. Examina-
tion of the undiscounted annual data provides two important conclusions;
(1) undiscounted monetary losses for moderate growth in electric demand
(scenarios 2 and 2d) level off after approximately 1985 with respect to both
total and utility losses as well as by crop and (2) high growth in electric
demand entails an increasing value of undiscounted losses, both total and
by crop, through year 2000. Examination of annual undiscounted monetary
losses provides the only case where results are different as between the
three scenarios examined. In the cases of scenarios 2 and 2d, year 2000
undiscounted losses are approximately 61% greater than losses experienced in
1976 whereas in scenario 7 they are 87.3% higher than the 1976 level. The
reader is reminded, however, that the present discounted losses are of the
present value of discounted clean-air production is only marginally higher
for scenario 7 as compared with scenario 2 (8.5% compared with 8.4%).
Nonetheless, the time trend of monetary losses is distinctly different for
scenario 7 as compared with scenarios 2 and 2d and reflects the larger
capacity requirements in the region for scenario 7. The reason for the
small difference in the present value of losses as a percent of clean-air
production relates, of course, to the use of a discount rate.
Tables 58 through 63 provide annual loss information for the region
(probable case) in terms of aggregate three-crop damage attributable to SO
and 0 . Figures 23 through 28 provide computer plots of the corresponding
data. Again, the reader is reminded that the data in Tables 58 through 63
are not discounted values. It is almost always true that the difference
between total and O damages in Figures 23 through 28 is so slight that the
plotting routine fails to pick up the 0 contribution; it generally is 98%
or more of total damages. The figures, then, graphically portray the
overwhelming contribution of 0 to total damages in the ORBES region for the
probable case (the same is true for the minimum and maximum cases). As the
damages by crop portrayed in earlier figures leveled off by 1985 for scenario
2 and 2d, the same pattern emerges with respect to the three-crop total and
O_ contributions for those scenarios. Again, however, the total damages
for the high electric growth scenario (scenario 7) continue to rise through
year 2000, although almost all the incremental increase is attributable to
O damages. This is true for both the total and utility related damages.
29
-------
The final results reported are found in Table 64. The purpose of these
calculations is to assess the benefits which accrue from SIP compliance
(scenario 2) as contrasted with non-compliance (scenario 2d). As 0
contributions from utilities are virtually identical under both scenarios,
the benefit is wholly related to compliance with SCL SIP regulations. The
benefits are very small: benefits as a percent of total clean-air production
for the minimum, maximum and probable cases, respectively, are 0.6%, 4.2%,
and 2.3%.
Several general conclusions emerge from above results. First, monetary
losses to agricultural producers in the ORBES region are on the order of
12% of the present discounted value of clean-air production. Second,
similarly defined losses from utilities are on the order of 4.8%. Third,
losses are highly concentrated in the ORBES-portion of Illinois, Indiana,
and Ohio and primarily related to soybean and corn production. Fourth,
the overwhelming monetary losses are attributable to 0, concentrations in
the region. Fifth, high growth in electric demand produces annual losses
(undiscounted) which rise through year 2000 while scenarios 2 and 2d level-
off after 1985. And sixth, all of the above trends are true with respect
to minimum, maximum, or probable monetary losses.
Appendix Tables A-l to A-3 provide the summary results on regional
agricultural losses based on peak load rather than nominal load emissions.
The tables contain total losses by ORBES-portions of states as well as
utility related losses and reveal the percent losses are of pollution-free
output for the region and ORBES-portions of states as well as the percent
ORBES-portions of state losses are of total regional losses. In the table
footnotes will be found the calculations of the distribution of regional
losses as between SO and 0_ damages. Extensive tables for these calculations
are not presented because tney tend to reflect the same conditions as the
main tables in the text related to nominal load emissions.
Examining Tables A-1 through A-3, the only major difference observed
between economic losses using peak load emissions and those using nominal
load emissions is that losses as a percent of pollution-free output are
uniformly on the order of 2% lower for the case of peak load emissions,
scenarios 2 and 2d. The distribution of these losses by crop and by ORBES-
portions of states tends to be identical to the results reported in the text
as is the range for minimum and maximum losses relative to probable losses.
The only case in which losses as a percent of pollution-free output are
almost identical as between calculations based on peak load and nominal
load emissions occurs with respect to the high growth scenario, scenario #7.
The conclusion when comparing regional losses using peak or nominal load
emissions, then, is that for compliance or non-compliance scenarios the use
of peak load emissions results in a present discounted value of losses
approximately 2% less than was the case with nominal load emissions, whereas
in the high growth scenario the loss value as a percent of pollution-free value
are almost identical for both cases. As noted in the introduction, it is
not the province of the present authors to determine whether peak or
nominal load emissions should be used for the estimation of physical crop
damages. That determination is left to others in the project or to the reader.
30
-------
TABLE 1. SEASONAL AVERAGE PRICES FOR CORN
(Dollars)
Year
1965
1966
1.967
1968
1969
1970
1971
1972
1973
1974
1975
197G
1977
1978
SOURCE:
Illinois Indiana
1.09
1.30
1.04
1.06
1.14
1.42
1.08
1.34
2.50
3.00
2.50
2.35
2.15
2.15
Agricultural
1.06
1.28
1.02
1.03
1.11
1.40
1.03
1.28
2.40
3.00
2.40
2.25
2.00
2.15
Prices,
Kentucky
1.23
1.40
1.16
1.18
1.26
1.56
1.12
1.44
2.50
3.00
2.55
2.35
2.30
2.35
Ohi o
1.08
1.30
1.04
1.03
1.15
1.40
1.06
1.33
2.45
3.00
2.40
2.25
1.95
2.15
Annual Summaries
Pennsylvania
1.36
1.54
1.20
1.23
1.33
1.53
1.31
1.57
2.60
3.00
2.50
2.50
2.35
2.45
1965-78, Crop
West Virginia
1.35
1.43
1.25
1.26
1.34
1.50
1.24
1.48
2.50
3.25
2.65
2.50
2.05
2.20
Reporting Board,
Economic Statistics and Cooperatives Service, U.S. Department of Agriculture.
31
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TABLE 2. SEASONAL AVERAGE PRICES FOR SOYBEANS
(Dollars)
Year
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
SOURCE:
Illinois Indiana
2.55
2.80
2.50
2.45
2.35
2.90
3.05
4.30
5.65
6.60
4.70
7.60
5.90
6.65
Agricultural
2.50
2.80
2.50
2.35
2.30
2.80
3.00
3.90
5.65
7.00
4.70
6.95
5.50
6.75
Prices,
Kentucky
2.45
2.75
2.45
2.40
2.30
2.80
3.00
4.00
5.55
6.95
4.65
7.10
6.20
6.70
Ohio Pennsylvania West Virginia
2.50
2 . 80
2.55
2 . 40
2.35
2.85
3.05
4.00
5.65
6 . 70
4.65
7 . 40
5.65
6.75
Annual Summaries 1965-78, Crop Reporting Board,
Economic Statistics and Cooperatives Service, U.S. Department of Agriculture.
32
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TABLE 3. SEASONAL AVERAGE PRICES FOR WHEAT
(Dollars)
Year
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
SOURCE:
Illinois Indiana
1.35
1.75
1.40
1.20
1.18
1.30
1.40
1.47
3.00
3.85
3.15
3.05
2.10
3.05
Agricultural
1.32
1.71
1.29
1.11
1.14
1.31
1.33
1.40
3.00
3.95
3.20
3.00
2.20
3.00
Prices,
Kentucky
1.34
1.58
1.39
1.22
1.22
1.33
1.47
1.45
3.05
3.70
3.00
2.95
2.00
3.15
Ohio
1.39
1.71
1.31
1.14
1.19
1.41
1.35
1.55
3.80
4.00
3.25
2.90
2.15
3.20
Annual Summaries
Pennsylvania
1.35
1.65
1.31
1.14
1.27
1.42
1.49
1.55
3.30
3,65
2.95
3.00
2.40
3.30
1965-78, Crop
West Virginia
1.63
1.64
1.49
1.23
1.27
1.40
1.56
1.70
3.40
3.75
3.10
3.00
2.20
3.00
Reporting Board,
Economic Statistics and Cooperatives Service, U.S. Department of Agriculture.
33
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TABLE 4. WEIGHTED PRICES, BY CROP AND STATE
FOR THE SIX-STATE REGION, 1965-78*
(1975 dollars)
State
IL
IN
KY
OH
PA
WV
Corn
2.04
1.98
2.16
1.99
2.27
2.29
SOURCES: Illinois, Indiana, Kentucky,
Crop Reporting Services, Agricultural
Soybeans
5.08
4.98
5.31
5.09
Ohio, Pennsylvania,
Statistics, 1965-78,
Wheat
2.49
2.51
2.52
2.57
2.48
2.53
and West Virginia
Crop Reporting
Board, Economic Statistics and Cooperatives Service, U.S. Department of
Agriculture.
Agricultural Prices, Annual Summaries 1965-78, Crop Reporting Board,
Economic Statistics and Cooperatives Service, U.S. Department of Agriculture.
* Weights are calculated as the percent that each year's output is of the
states total production, 1965-78. All prices are in constant 1975
dollars.
34
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TABLE 5. SIX-STATE CROP PRODUCTION, 1965-78:
CORN
(1,000 bushels)
Six-state total
Year
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
IL
919,
848,
1,121,
907,
989,
735,
1,067,
1,014,
981,
811,
1,253,
1,240,
1,163,
1,191,
038
044
952
920
196
560
420
750
590
800
960
130
400
030
IN
441,894
396,006
462,852
416,768
462,000
374,148
556,409
507,936
534,480
387,630
551,740
693,000
633,420
637,200
KY
72,
65,
93,
69,
72,
46,
91,
83,
85,
88,
87,
138,
132,
119,
381
018
440
366
765
950
091
248
850
150
780
720
300
850
SOURCE: Illinois, Indiana, Kentucky,
Crop Reporting Services, Agricultural
OH
225,996
261,660
255,960
248,024
241,251
240,160
322,595
284,280
243,200
265,500
310,620
393,460
380,100
379,050
PA
55
32
81
56
76
81
77
64
81
.89
88
103
106
113
,760
,928
,048
,700
,384
,346
,700
,800
,120
,100
,560
,500
,720
,050
WV production
2,
2,
3,
2,
?,
3,
4,
3,
5,
5,
5,
5,
3,
4,
Ohio, Pennsylvania,
Statistics, 1965-78
900
256
584
773
479
551
071
975
229
016
525
368
996
466
1,717,969
1,605,912
2,018,836
1,701,551
1,845,075
1,481,715
2,119,286
1,958,989
1,931,469
1,647,196
2,298,185
2,574,178
2,419,936
2,444,646
and West Virginia
, Crop Reporting
Board, Economic Statistics and Cooperatives Service, U.S. Department of
Agriculture.
35
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TABLE 6. SIX-STATE CROP PRODUCTION, 1965-78:
SOYBEANS
(1,000 bushels)
Year
IL
IN
KY
OH
PA WV
Six-state total
production
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
177,620
160,407
186,279
209,884
228,820
210,800
235,950
259,440
287,595
206,780
299,520
249,480
336,300
303,270
80,388
73,164
71,001
103,872
105,952
101,618
111,441
108,796
135,135
97,250
119,790
111,520
144,300
140,420
7,080
7,750
10,864
12,349
12,600
14,310
20,798
23,598
26,000
24,990
29,700
28,890
40,920
42,300
SOURCE: Illinois, Indiana, Kentucky,
Crop Reporting Services, Agricultural
50,078
59,992
50,198
70,913
73,013
72,675
80,337
79,765
91,545
81,640
102,300
95,040
119,990
123,750
Ohio, Pennsylvania,
Statistics, 1965-78
315,166
301,313
318,342
397,018
420,385
399,403
448,526
471,599
540,275
410,660
551,310
484,930
641,510
609,740
and West Virginia
, Crop Reporting
Board, Economic Statistics and Cooperatives Service, U.S. Department of
Agriculture.
36
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TABLE 7. SIX-STATE CROP PRODUCTION, 1965-78:
WHEAT
(1,000 bushels)
Year
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
IL
56,800
61,008
71,95.5
51,208
48,374
38,110
46,000
54,000
39,000
51,900
67,470
72,150
67,510
35,340
IN
36,205
44,616
45,769
34,195
34,800
28,144
31,924
39,648
24,605
50,040
64,500
54,000
55,800
31,785
KY
5,376
5,780
7,854
6,240
5,746
5,724
7,200
7,020
5,412
11,340
10,880
10,230
10,138
6,825
SOURCE: Illinois, Indiana, Kentucky,
Crop Reporting Services, Agricultural
OH
40,256
46,137
51,476
44,850
38,646
35,150
41,536
46,305
25,600
59,450
70,560
64,000
72,380
43,875
Ohio,
Stati
PA
14,280
14,400
17,280
12,000
10,650
9,075
9,396
8,608
7,392
11,520
10,144
9,000
8,910
8,085
WV
522
484
740
496
462
518
420
385
279
396
352
352
310
297
Pennsylvania,
sties, 1965-78,
Six-state total
production
153,439
172,425
195,074
148,989
138,678
116,721
136,476
155,966
102,288
184,646
223,906
209,732
215,048
126,207
and West Virginia
Crop -Reporting
Board, Economic Statistics and Cooperatives Service, U.S. Department of
Agriculture.
37
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TABLE 8. ESTIMATED SUPPLY ELASTICITIES FOR CORN, SOYBEANS, AND WHEAT
PRODUCTION IN THE OHIO RIVER BASIN ENERGY STUDY REGION
Variable Estimated coefficient t-Ratio*
2
Elasticity Adjusted R
Corn
0? .61913 2.7324
P° 2349.2 2.8005
P^ -453.73 -1.0510
t ' -13.062 . -.11021
intercept 31901.0 .13761
.61138 .8458
.18666
-.89215 X ID"1
-1.2189
1.5096
Soybeans
0? .88368 11.320
P^ 954.53 6.3970
P° -3343.1 -11.742
t ' 172.04 3.3210
intercept -.33529 X 10 . -3.3090
.85029 .9935
.26297
-.38037
22.989
22.720
Wheat
QW .25636 3.2818
P^ 1166.9 11.048
t -173.41 -7.4699
intercept .34273 X 1Q6 7 : 5033
.26217 .9475
.55956
-80.751
80.932
* Underlined values are significant at the 95% level.
38
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TABLE 9. PRESENT DISCOUNTED VALUE OF POLLUTION-FREE
CUMULATIVE PRODUCTION, 1976-2000*
(millions of 1975 dollars)
ORBES
area
IL
IN
KY
on
PA
WV
ORBES
total
Corn
19891.895
10594.992
2469.632
5155.554
388.398
55.160
38505.632
Soybeans
14151.809
5860.365
1812.788
3492.335
0
0
25317.297
Wheat
1574.944
1210.970
252.171
1055.882
27.554
2.737
4124.257
Three crop total
35618.648
17666.326
4534.591
9703.771
365.952
57.897
67947.185
* Assumes a 10% discount rate.
t- Calculations assume annual pollution-free output, 1976-2000, is always
equal to 1976 pollution-free output and agricultural prices for the
crops, in real terms, are unchanged.
39
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TABLE 10. NET PRESENT VALUE OF MINIMUM CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 : SCENARIO 2*
^ o
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
. Total losses/
(millions of
dollars)
2855.740
1314.390
364.410
734.531
17.644
2.828
5289.550
Percent losses are
of pollution-free
output^
8.0
7.4
8.0
7.6
4.8
4.9
7.8
Percent losses are
of ORBES total
losses
54.0
24.8
6.9
13.9
0.3
0.1
100 ..0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
| Sum may not be 100% due to rounding.
40
-------
TABLE 11. NET PRESENT VALUE OF MINIMUM CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIOS*
ORBES
area
1L
IN
KY
OH
PA
WV
ORBES
total
Total utility
losses/
(millions of
dollars)
861.486
396.626
110.555
220.885
5.302
0.851
1595.700
Percent utility
losses are of
pollution-free
output*
2.4
2.2
2.4
2.3
1.4
1.5
2.3
Percent utility
losses are of
ORBES total
losses
54.0
24.9
6.9
13.8
i
0.3
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
41
-------
TABLE 12. NET PRESENT VALUE OF MAXIMUM CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 : SCENARIO 2*
Ci O
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
7019.260
3292.800
899.155
1829.630
51.309
8.277
13100.400
Percent losses are
of pollution-free
output^
19.7
18.6
19.8
18.9
14.0
14.3
19.3
Percent losses are
of ORBES total
losses
53.6
25.1
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table.16.
| Sum may not be 100% due to rounding.
42
-------
TABLE 13. MET PRESENT VALUE OF MAXIMUM CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 2*
^ O
ORBES
area
IL
IN
KY
OH
PA
WV
ORBKS
total
Total utility
losses/
(millions of
dollars)
3520.310
1648.080
454.121
916.194 .
25.762
4.198
6568.660
Percent utility
losses are of
pollution-free
output^
10.0
9.3
10.0
9.4
7.0
7.3
9.7
Percent utility
losses are of
ORBES total'
losses
53.6
25.1
6.9
13.9
0.4
0.1
100.08
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
| Sum may not be 100% due to rounding.
43
-------
TABLE 14. NET PRESENT VALUE OF PROBABLE CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 ' SCENARIO 2*
<-» O
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
4349.100
2032.810
557.455
1136.640
30.324
4.859
8111.190
Percent losses are
of pollution-free
output^
12.2
11.5
12.3
11.7
8.3
8.4
11.9
Percent losses are
of ORBES total
losses
53.6
25.1
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
^ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
44
-------
TABLE 15. NET PRESENT VALUE OF PROBABLE CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 2*
^ \J
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total utility
losses/
(millions of
dollars)
1747.130
814.237
226.088
455.411
12.180
1.971
3257.020
Percent utility
losses are of
pollution-free
output*
4.9
4.6
5.0
4.7
3.3
3.4
4.8
Percent utility
losses are of
ORBES total
losses
53.6
25.0
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
^ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
45
-------
TABLE 16. NET PRESENT VALUE OF MINIMUM TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2*
c* O
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
Percent losses are of ORBES
are of area total
pollution-free pollution-free
crop output/ crop output/
Percent losses
are of ORBES
total crop
loss^
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
992.573
528.645
123.261
257.255
16.886
2.753
1921.370
5.0 2.6
5.0 1.4
5.0 0.3
5.0 0.7
5.0 §
5.0 |
5.0 5.0#
51.7
27.5
6.4
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
1819.880
752.463
234.218
448.257
0
0
3254.820
12.9 7.2
12.8 3.0
12.9 0.9
12.8 1.8
0 0
0 0
12.9 12. 9#
55.9
23.1
7.2
13.8
0
0
100.0**
(continued)
46
-------
TABLE 16 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
43.292
33.281
6.931
29.019
0.757
0.075
113.356
2.7
2.7
2.7
2.7
2.7
2.8
2.7
1.0 38.2
0.8 29.4
0.2 6.1
0.7 25.6
§ o.i
§ o.i
2.7# 100.0**
47
-------
TABLE I"? NET PRESENT VALUE OF MINIMUM UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO, AND 0 , BY CROP: SCENARIO 2*
£ o
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
Percent losses are of ORBES
are of area total
pollution-free pollution-free
crop output/ crop output/
Percent losses
are of ORBES
total crop
losst
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
992.573
528.645
37.007
77.194
5.067
0.827
576.532
1.5 0.8
1.5. 0.4
1.5 0.1
1.5 0.2
1.5 §
1.5 §
1.5 1 . 5#
51.7
27.5
6.4
13.4 .
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
548.748
226.081
71.392
134.573
0
0
980.794
3.9 2.2
3.9 0.9
3.9 0.3
3.9 0.5
0 0
0 0
3.9 3 . 9#
55.9
23.1
7.3
13.7
0
0
100.0**
(continued)
48
-------
TABLE 17 (continued)
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss^
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
12.997
9.987
2.081
8.708
0.227
0.022
34.022
0.8
0.8
0.8
0.8
0.8
0.8
0.8
0.3
0.2
0.1
0.2
§
§
0.8#
38.2
29.4
6.1
25.6
0.7
0.1
100.0**
49
-------
TABLE 18. NET PRESENT VALUE OF MAXIMUM TOTAL CUMULATIVE CROP LOSSES
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2*
t-* O
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
2853.560
1517.640
356.987
739.787
48.621
8.005
5524.600
14.3
14.3
14.5
14.3
14.4
14.5
14.3
7.4
3.9
0.9
1.9
0.1
§
: 14. s#
51.7
27.5
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
4011.960
1657.510
517.557
987.250
0
0
7174.280
28.3
28.3
28.6
28.3
0
0
28.3
15.8
6.5
2.0
3.9
0
0
28. 3#
55.9
23.1
7.2
13.8
0
0
100.0**
(continued)
50
-------
TABLE 18 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
153.746
117.636
24.611
102.594
2.688
0.273
401.548
9.8
9.7
9.8
9.7
9.8
10.0
9.7
3.7
2.9
0.6
2.5
0.1
§
9.7#
38.3
29.3
6.1
25.5
0.7
0.1
100.0**
51
-------
TABLE 19. NET PRESENT VALUE OF MAXIMUM UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2*
C* O
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
1430.270
759.552
180.281
370.898
24.408
4.058
2769.460
7.2
7.2
7.3
7.2
7.2
7.4
7.2
3.7
2.0
0.5
1.0
0.1
i
7.2#
51.6
27.4
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
2012.590
829.554
261.446
493.852
0
0
3597.440
14.2
14.2
14.4
14.1
0
0
14.2
7.9
3.3
1.0
2.0
0
0
14. 2#
55.9
23.1
7.3
13.7
0
0
100.0**
(continued)
52
-------
TABLE 19 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss^
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
77.451
58.973
12.395
51.444
1.353
0.140
201.757
4.9
4.9
4.9
4.9
4.9
5.1
4.9
1.9 38.4
1.4 29.2
0.3 6.1
1.2 25.5
I °-7
§ o.i
4.9# 100.0**
53
-------
TABLE 20. NET PRESENT VALUE OF PROBABLE TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2*
^
-------
TABLE 20 (continued)
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Wheat
1L
IN
KY
on
PA
WV
ORBES
total
105.759
80.966
16.931
70.613
1.850
0.187
276.306
6.7
6.7
6.7
6.7
6.7
6.8
6.7
2.6
2.0
0.4
1.7
i
i
6.7#
38.3
29.3
6.1
25.6
0.7
0.1
100.0**
55
-------
TABLE 21. NET PRESENT VALUE OF PROBABLE TOTAL UTILITY CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2*
^ *J
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss#
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
670.425
356.243
84.283
173.842
11.433
1.894
1298.120
3.4
3.4
3.4
3.4
3.4
3.4
3.4
1.7
0.9
0.2
0.5
§
i
3.4#
51.6
27.4
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
1033.980
425.495
134.967
253.216
0
0
1847.660
7.3
7.3
7.4
7.3
0
0
7.3
4.1
1.7
0.5
1.0
0
0
7.3#
56.0
23.0
7.3
. 13.7
0
0
100.0**
(continued)
56
-------
TABLE 21 (continued)
,
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Wheat
II,
IN
KY
OH
PA
WV
ORBES
total
42.724
32.498
6.838
28.353
0.746
0.078
111.237
2.7
2.7
2.7
2.7
2.7
2.8
2.7
1.0
0.8
0.2
0.7
§
i
2.7#
38.4
29.2
6.1
25.5
0.7
0.1
100.0**
57
-------
TABLE 22. NET PRESENT VALUE OF TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, BY POLLUTANT: SCENARIO 2*
ORBES
area
IL
IN
KY
OH
PA .
WV
ORBES
total
IL
IN
KY
OH
PA
WV
ORBES
total
SO- losses/ Percent SO losses 0 losses/ Percent 0 losses
2 c, o 3
(millions of are of area total (millions of are of area total
dollars) losses* dollars) losses*
4.077
0.511
1.652
0.164
0.002
0.001
6.408
21.329
3.373
9.088
2.756
0.214
0.119
36.877
Minimum
0.1
i
0.5
§
§
§
0.1
Maximum
0.3
0.1
1.0
0.2
0.4
1.4
0.3
losses
2851.670
1313.880
362.758
734.367
17.641
2.827
5283.140
losses
6997.930
3289.420
890.067
1826.880
51.096
8.159
13063.600
99.9
100.0
99.5
100.0
100.0
100.0
99.9
99.7
99.9
99.0
99.8
99.6
98.6
99.7
(continued)
58
-------
TABLE 22 (continued)
ORBES
area
SO losses/
Ci
(millions of
dollars)
Percent SO losses
Ci
are of area total
losses*
0 losses/
vS
(millions of
dollars)
Percent 0 losses
O
are of area total
losses^
Probable losses
IL
IN
KY
OH
PA
WV
ORBES
total
12.495
1 . 854
5.176
1.257
0.084
0.047
20.912
0.3
0.1
0.9
0.1
0.3
1.0
0.3
4336.600
2030.960
552.280
1135.380
30.240
4.812
8090.270
99.7
99.9
99.1
99.9
99.7
99.0
99.7
* Assumes 10% discount rate.
/ Crops are corn, soybeans, and wheat.
* For total losses, see Tables
s Less than .05%.
59
-------
TABLE 23. NET PRESENT VALUE OF UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, BY POLLUTANT: SCENARIO 2*
ORBES
area
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
Ci & «J «J
(millions of are of area total (millions of are of area total
dollars) lossest dollars) losses^
Minimum losses
IL
IN
KY
OH
PA
WV
ORBES
total
4.077
0.511 .
1.652
0.164
0.002
0.001
6.408
0.5 855.499
0.1 394.163
1.5 108.827
0.1 220.310
§ 5.292
0.1 0.848
0.4 1584.940
99.5
99.9
98.5
99.9
100.0
99.9
99.6
Maximum losses
IL
IN
KY
OH
PA
WV
ORBES
total
21.329
3.373
9.088
2.756
0.214
0.119
36.877
0.6 3498.980
0.2 1644.710
2.0 445.034
0.3 913.438
0.8 25.548
2.8 4.079
0.6 6531.790
99.4
99.8
98.0
99.7
99.2
97.2
99.4 .
(continued)
60
-------
TABLE 23 (continued)
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
-------
TABLE 24. NET PRESENT VALUE OF MINIMUM CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 : SCENARIO 2d*
Ct «J
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
2857.650
1316.340
364.486
734.941
17.651
2.830
5293.900
Percent losses are
of pollution-free
output^
8.0
7.5
8.0
7.6
4.8
4.9
7.8
Percent losses are
of ORBES total
losses
54.0
24.9
6.9
13.9
0.3
0.1
100. 0§
* Assums a 10% discount rate.
f- Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table .16.
§ Sum may not be 100% due to rounding.
62
-------
TABLE 25. NET PRESENT VALUE OF MINIMUM CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND. 0 : : SCENARIO 2d*
^ o
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total utilJty
losses/
(millions of
dollars)
859.576
394.674
110.480
220.475
5.295
0.849
1591.350
Percent utility
losses are of
pollution-free
output*
2.4
2.2
2.4
2.3
1.4
1.5
2.3
Percent utility
losses are of
ORBES total
losses
54.0
24.8
6.9
13.9
0.3
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
63
-------
TABLE 26. NET PRESENT VALUE OF MAXIMUM CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 : SCENARIO 2d*
Cf O
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
7030.850
3305.480
899.582
1832.650
51.891
8.349
13128.800
Percent losses are
of pollution-free
outputs
19.7
18.7
19.8
18.9
14.2
14.4
19.3
Percent losses are
of ORBES total
losses
53.6
25.2
6.9
14.0
0.4
0.1
100.0
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
64
-------
TABLE 27. NET PRESENT VALUE OF MAXIMUM CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 2d*
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total utility
losses/
(millions of
dollars)
3531.890
1660.760
454.548
919.212
26.343
4.269
6597.030
Percent utility
losses are of
pollution-free
output*
9.9
9.4
10.0
9.5
7.2
7.4
9.7
Percent utility
losses are of
ORBES .total
losses
53.3
25.2
6.9
13.9
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
$ Discounted present values of pollution-free output are in
Table .16.
| Sum may not be 100% due to rounding.
65
-------
TABLE 28. NET PRESENT VALUE OF PROBABLE CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 : SCENARIO 2d*
Ci O
ORBES
area
IL
IN
KY
OH
PA
WV
ORUES
total
Total losses/
(millions of
dollars)
4355.690
2039.810
557.691
1138.240
30.575
4.886
8126.900
Percent losses are
of pollution-free
output t
12.2
11.5
12.3
11.7
8.4
8.4
12.0
Percent losses are
of ORBKS total
losses
53.6
25.1
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
66
-------
TABLE 29. NET PRESENT VALUE OF PROBABLE CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 2d*
i- O
ORBES
area
IL
IN
KY
OH
PA
WV
OR RES
total
Total utility
losses/
(millions of
dollars)
1753.730
821.242
226.323
457.013
12.430
1.999
3272.74
Percent utility
losses are of
pollution-free
output*
4.9
4.6
5.0
4.7
3.4
3.5
4.8
Percent utility
losses are of
ORBES tQtal
losses
53.6
25.1
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table
§ Sum may not be 100% due to rounding.
67
-------
TABLE 30. NET PRESENT VALUE OF MINIMUM TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2d
Ci O
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
Percent losses are of ORBES
are of area total
pollution-free pollution-free
crop output/ crop output/
Percent losses
are of ORBES
total crop
IQSS+
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
992.623
528.709
123.262
257.274
16.892
2.754
1921.510
5.0 2.6
5.0 1.4
5.0 0.3
5.0 0.7
5.0 §
5.0 §
5.0 5.0#
51.7
27.5
6.4
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
1821.720
754.338
234.292
448.646
0
0
3259.000
12.9 7.2
12.9 3.0
12.9 . 0.9
12.8 1.8
0 0
0 0
12.9 12. 9#
55.9
23.1
7.2
13.8
0
0
100.0**
(continued)
68
-------
TABLE 30 (continued)
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Wheat
II.
IN
KY
OH
PA
WV
ORBES
total
43.306
33.294
6.932
29.022
0.759
0.075
113.388
2.7
2.7
2.7
2.7
2.8
2.8
2.7
1.1
0.8
0.2
§
0.7
§
2.7#
38.2
29.4
6.1
25.6
0.7
0.1
100.0**
69
-------
TABLE 31. NET PRESENT VALUE OF MINIMUM UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2d*
£ o
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
Percent losses are of ORBES
. are of area total
pollution-free pollution-free
crop output/ crop output/
Percent losses
are of ORBES
total crop
loss*
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
297.881
158.670
37.009
77.213
5.073
0.828
576.674
1.5 0.8
1.5 0.4
1.5 0.1
1.5 0.2
1.5 §
1.5 §
1.5 1 . 5#
51.7
27.5
6.4
13.4
0.9
0.1
100.0**'
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
550.594
227.955
71.466
134.961
0
0
984.976
3.9 2.2
3.9 0.9
3.9 0.3
3.9 0.5
0 0
0 0
3.9 3.9#
55.9
23.1
7.2
13.8
0
0
100.0*-
(continued)
70
-------
TABLE 31 (continued)
Losses to crop
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
13.011
10.000
2.081
8.711
0.229
0.022
34.054
0.8
0.8
0.8
0.8
0.8
0.8
0.8
0.3 38.2
0.2 29.4
0.1 6.1
0.2 25.6
§ °-7
§ o-1
0.8# 100.0**
71
-------
TABLE 32. NET PRESENT VALUE OF MAXIMUM TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2d*
*- O
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
2857.760
1523.000
357.147
741.262
49.109
8.072
5536.340
14.4
14.4
14.5
14.4
14.5
14.6
14.4
7.4
4.0
0,9
1.9
0.1
§
14. 4#
51.6
27.5
6.5
13.4
0.9
0.1
100.0**.
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
4018.070
1663.710
517.796
988.544
0
0
7188.110
28.4
28.4
28.6
28.3
0
0
28.4
15.9
6.6
2.0
3.9
0
0
28. 4#
55.9
23.1
7.2
13.8
0
0
100.0**
[continued)
72
-------
TABLE 32 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
155.020
118.772
24.639
102.844
2.782
0.277
404.335
9.8
9.8
9.8
9.7
10.1
10.1
9.8
3.8
2.9
0.6
2.5
0.1
§
9.8#
38.3
29.4
6.1
25.4
0.7
0.1
100.0**
73
-------
TABLE 33. NET PRESENT VALUE OF MAXIMUM UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2d*
Ct O
Percent losses
Percent losses are of ORBES
Losses to crops are of area total
ORBES (millions of pollution-free pollution-free
.area dollars) crop output/ crop output/
Percent losses
are of ORBES
total crop
losst
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
1434.470 7.2 3.7
764.905 7.2 2.0
180.441 7.3 0.5
372.373 7.2 1.0
24.896 7.4 0.1
4.125 7.5 §
2781.210 7.2 7.2#
51.6
27.5
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
2018.700 14.3 8.0
835.747 14.3 3.3
261.684 14.4 1.0
495.145 14.2 2.0
000
000
3611.270 14.3 14. 3#
. 55.9
23.1
7.2
13.7
0
0
100.0**
(continued)
74
-------
TABLE 33 (continued)
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
78.725
60.109
12.423
51.694
1.447
.144
204.543
5.0
5.0
4.9
4.9
5.3
5.3
5.0
1.9
1.5
0.3
1.3
§
§
5.0#
38.5
29.4
6.1
25.3
0.7
0.1
100.0**
75
-------
TABLE 34. NET PRESENT VALUE OF PROBABLE TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM S0g AND 0 , BY CROP: SCENARIO 2d*
-------
TABLE 34 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Wheat
II.
IN
KY
OH
PA
WV
ORBES
total
106.533
81.653
16.945
70.764
1.916
0.190
278.001
6.8
6.7
6.7
6.7
7.0
6.9
6.7
2.6 38.3
2.0 29.4
0.4 6.1
1.7 25.5
§ 0.7
§ 0.1
6.7# 100.0**
77
-------
TABLE 35. NET PRESENT VALUE OF PROBABLE UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 2d*
" o
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
Percent losses are of ORBES
are of area total
pollution-free pollution-free
crop output/ crop output/
Percent losses
are of ORBES
total crop
loss*
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
672.014
358.261
84.332
174.396
11.618
1.919
1302.540
3.4 1.7
3.4 0.9
3.4 0.2
3.4 0.5
3.4 §
3.5 §
3.4 3.4#
51.6
27.5
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
1038.220
429.795
135.139
254.113
0
0
1857.270
7.3 4.1
7.3 1.7
7.5 0.5
7.3 1.0
0 0
0 0
7.3 7.3#
55.9
23.1
7.3
13.7
0
0
100.0**
(continued)
78
-------
TABLE 35 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
43.498
33.185
6.852
28.504
0.812
0.080
112.933
2.8
2.7
2.7
2.7
2.9
2.9
2.7
1.1 38.5
0.8 29.4
0.2 6.1
0.7 25.2
§ 0.7
1 °'1
2.7# 100.0**
79
-------
TABLE 36. NET PRESENT VALUE OF TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, BY POLLUTANT: SCENARIO 2d*
ORBES
area
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
£ £3 ij
(millions of are of area total (millions of are of area total
dollars) losses^ dollars) losses*
Minimum losses
IL
IN
KY
OH
PA
WV
ORBES
total
5.986
2.462
1.728
0.575
0.010
0.002
10.763
0.2 2851.670
0.2 1313.880
0.5 362.758
0.1 734.367
0.1 17.641
0.1 2.827
0.2 5283.140
99.8
99.8
99.5
99.9
99.9
99.9
99.8
Maximum losses
IL
IN
KY
OH
PA
WV
ORBES
total
32.913
16.055
9.515
5.774
0.795
0.190
65.241
0.5 6997.930
0.5 3289.420
1.1 890.067
0.3 1826.880
1.5 51.096
2.3 8.159
0.5 13063.600
99.5
99.5
98.9
99.7
98.5
97.7
99.5
(continued)
80
-------
TABLE 36 (continued)
ORBES
area
SO losses/
(millions of
dollars)
Percent SO losses
are of area total
lossest
0 losses/
\J
(millions of
dollars)
Percent .0 losses
O
are of area total
lossest
Probable losses
1L
IN
KY
OH
PA
WV
ORBES
total
19.093
8.858
5.411
2.859
.334
.073
36.630
0.4
0.4
1.0
0.3
1.1
1.5
0.5
4336.600
2030.960
552.280
1135.380
30.240
4.812
8090.270
99.6
99.6
99.0
99.7
98.9
98.5
99.5
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
+ For total losses, see Tables
81
-------
TABLE 37. NET PRESENT VALUE OF UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, BY POLLUTANT: SCENARIO 2d*
ORBES
area
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
2 c, o o
(millions of are of area total (millions of are of area total
dollars) losses^ dollars). losses^
Minimum losses
IL
IN
KY
OH
PA
WV
ORBES
total
5.986
2.462
1.728
0.575
0.010
0.002
10.763
0.7
0.6
1.6
0.3
0.2
0.3
0.7
855.500
394.163
108.827
220.310
5.292
0.848
1584.940
99.3
99.4
98.4
99.7
99.8
99.7
99.3
Maximum losses
IL
IN
KY
OH
PA
WV
ORBES
total
32.913
16.055
9.515
5.774
0.795
0.190
65.241
0.9
1.0
2.1
0.6
3.0
4.4
1.0
3498.980
1644.710
445.034
913.438
25.548
4.079
6531.790
99.1
99.0
97.9
99.4
97.0
95.6
99.0
(continued)
82
-------
TABLE 37 (continued)
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
£ £ O O
ORBES (millions of are of area total (millions of are of are total
area dollars) losses^ dollars) lossest
Probable losses
IL 19.093
IN 8.858
KY 5.411
OH 2.859
PA 0.334
WV 0 . 074
ORBES
total 36.630
1.1 1734.640 98.9
1.1 812.383 98.9
2.4 220.912 97.6
0.6 454.154 99.4
2.7 12.096 97.3
3.7 1.925 96.3
1.1 3236.110 98.9
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
* For total losses, see Tables
83
-------
TABLE 38. NET PRESENT VALUE OF MINIMUM CUMULATIVE CROP LOSS,
1976"TO 2000, FROM SO AND 0 : SCENARIO 7*
Ct O
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
3003.140
1381.950
383.451
772.612
18.560
2.966
5562.680
Percent losses are
of Pollution-free
outputt
8.4
7.8
8.5
8.0
5.1
5.1
8.2
Percent losses are
of ORBES total
losses
54.0
24.8
6.9
13.9
0.3
0.1
100. 0§
* .Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table.il6.
g Sum may not be 100% due to rounding.
84
-------
TABLE 39. NET PRESENT VALUE OF MINIMUM CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 7*
£> O
ORBES
area
IL
IN
KY.
OH
PA
WV
ORBES
total
Total utility
losses/
(millions of
dollars)
1144.760
525.090
147.043
293.733
7.197
1.113
2118.940
Percent utility
Losses are of
pollution-free
output $
3.2
3.0
3.2
3.0
2.0
1.9
3.1
Percent utility
losses are of
ORBES total
losses
54.0
24.8
6.9
13.7
0.3
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
85
-------
TABLE 40. NET PRESENT VALUE OF MAXIMUM CUMULATIVE CROP LOSS,
1976 TO 2000, FROM S00 AND 0 : SCENARIO 7*
3
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
7150.440
3351.810
917.578
1865.090
51.907
8.353
13345.200
Percent losses are
of pollution-free
output*
20.1
19.0
20.2
19.2
14.2
14.4
19.6
Percent losses are
of ORBES total
losses
53.6
25.1
6.9
14.0
0.4
0.1
100. Oi
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
| Sum may not be 100% due to rounding.
86
-------
TABLE 41. NET PRKSENT VALUE OF MAXIMUM CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 7*
ORBES
area
II,
IN
KY
OH
PA
WV
ORBES
total
Total utility
losses/
(millions of
dollars)
4102.660
1919.450
529.861
1068.940
29.321
4.815
7655.050
Percent utility
losses are of
pollution-free
output^
11.5
10.9
11.7
11.0
8.0
8.3
11.3
Percent utility
losses are of
ORBES total
losses
53.6
25.1
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
87
-------
TABLE 42. NET PRESENT VALUE OF PROBABLE CUMULATIVE CROP LOSS,
1976 TO 2000, FROM SO AND 0 : SCENARIO 7*
£ o
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
Total losses/
(millions of
dollars)
4473.010
2087.100
574.105
1167.980
30.790
4.927
8337.920
Percent losses are
of pollution-free
output*
12.6
11.8
12.7
12.0
8.4
8.5
12.3
Percent losses are
of ORBES total
losses
53.6
25.0
6.9
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ Discounted present values of pollution-free output are in
Table 16.
§ Sum may not be 100% due to rounding.
88
-------
TABLE 43. NET PRESENT VALUE OF PROBABLE CUMULATIVE CROP LOSSES
TO UTILITIES, 1976 TO 2000, FROM SO AND 0 : SCENARIO 7*
^ «J
ORBES
area
II.
IN
KY
OH
PA
WV
ORBES
total
Total utility
losses/
(millions of
dollars)
1538.950
714.997
200.413
400.329
10.591
1.713
2867.000
Percent utility
losses are of
pollution-free
output*
4.3
4.0
4.4
4.1
2.9
3.0
4.2
Percent utility
Losses are of
ORBES total
losses
53.7
25.0
7.0
14.0
0.4
0.1
100. 0§
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
+ Discounted present values of pollution-free output are in
Table 16.
i
§ Sum may not be 100% due to rounding.
89
-------
TABLE 44. NET PRESENT VALUE OF MINIMUM TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 7*
< o
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss^
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
1040.430
554.119
129.208
269.657
17.701
2.886
2014.000
5.2
5.2
5.2
5.2
5.2
5.2
5.2
2.7
1.4
0.3
0.7
i
§
5.2#
51.7
27.5
6.4
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
1916.580
792.376
246.857
472.037
0
0
3427.850
13.5
13.5
13.6
13.5
0
0
13.5
(continued)
90
7.6
3.1
1.0
1.9
0
0
13. 5#
55.9
23.1
7.2
13.8
0
0
100.0**
-------
TABU': 44 ( conl.i lined)
Losses to crops
ORBKS (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output./
Percent losses
are of OHBKS
total
polluti on-free
crop out.put/
Percent, losses
are of ORBKS
tota I crop
Wheat
IN
KY
Oil
PA
WV
ORBES
total
/16.125
35.456
7.385
30.917
0.858
0.080
120.821
2.9
2.9
2.9
2.9
3.1
2.9
2.9
1 .1
0. 9
0.2
0.7
.'-I9.3
6.1
25.6
0.7
0.1
10 o.o *
91
-------
TABLE 45. NET PRESENT VALUE OF MINIMUM UTILITY CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 7*
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss^
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
333.337
177.503
41.422
86.395
5.672
0.925
645.254
1.7
1.7
1.7
1.7
1.7
1.7
1.7
0.9
0.5
0.1
0.2
§
§
1.7#
51.7
27.5
6.4
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
625.527
257.740
81.479
153.435
0
0
1118.180
4.4
4.4
4.5
4.4
0
0
4.4
2.5
1.0
0.3
0.6
0
0
4.4#
. 55.9
23.0
7.3
13.7
0
0
100.0**
(continued)
92
-------
TABI.K 45 (continued!
Losses to crops
ORBKS (mi 1.1 ions of
area dollars)
Percent Josses
are of area
pollution-free
crop output/
Percent losses
are of ORBKS
total.
pollution-free
crop output/
Percent, losses
are of ORRKS
tota I <:rop
Loss):
Wheat
] 1,
JN
KY
Oil
PA
WV
ORBKS
total
14.
Jl.
2.
9.
0.
0.
38.
806
375
.170
920
259
026
756
0
0
0
0
0
0
0
.9
.9
.9
.9
.9
.9
.9
0.4 38.
0.3 29.
O.I ' rt .
0.2 25.
ij 0.
§ 0.
0..9# 100.
v
3
1
6
7
1
0**
93
-------
TABLE 46. NET PRESENT VALUE OF MAXIMUM TOTAL CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 7*
b O
Losses to crops
ORBES (millions of
area dollars)
Percent losses
Percent losses are of ORBES Percent losses
are of area total are of ORBES
pollution-free pollution-free total crop
crop output/ crop output/ losst
Corn
IL
IN
KY
Old
PA
WV
ORBES
total
2878.640
1530.690
360.746
746.301
49.088
8.068
5573.540
14.5 7.5 51.6
14.4 4.0 27.5
14.6 0.9 6.5
14.5 1.9 13.4
14.5 0.1 0.9
14.6 § 0.1
14.5 14. 5# 100. 0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
4110.790
1697.980
531.044
1011.360
0
0
7351.170
29.0 16.2 55..9
29.0 6.7 23.1
29.3 2.1 7.2
29.0 4.0 13.8
0 00
0 00
29.0 29. 0# 100.0**
(continued)
94
-------
TAW.K 46 (continued)
Losses to crops
OKUKS (mi 11 ions of
area dolLars)
Percent, losses
are of area
Pollution-free
crop output/
Percent losses
are of ORBES
total
po.l I ut. i.on-f rce
crop output/
'ercen t I osses
are of ORBKS
l.oI.a I crop
loss-t-
Wheat.
1L
IN
KY
Oil
PA
WV
ORBKS
tol.al
161
123
25
107
>
0
420
.007
.138
.788
.433
.819
.285
.469
10
10
10
10
10
10
10
.2
.2
. 2
.2
. 2
.4
.2
3.9 38
3.0 29
0 . tt 6
2 . fi 25
0 . .1. 0
S °
10. 2// 100
.3
. 3
-1
.ei
.7
. 1
.0**
95
-------
TABLE 47. NET PRESENT VALUE OF MAXIMUM UTILITY CROP LOSSES,
1976 TO 2000, FROM S09 AND 0_, BY CROP: SCENARIO 7*
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
loss*
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
1491.820
792.021
188.568
386.866
25.496
4.222
2888.990
7.5
7.5
7.6
7.5
7.5
7.7
7.5
3.9
2.1
0.5
1.0
0.1
i
7.5#
51.6
27.4
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
2140.540
882.092
278.663
525.148
0
0
3826.440
15.1
15.1
15.4
15.0
0
0
15.1
8.5
3.5
1.1
2.1
0
0
15. 1#
55.9
23.1
. 7.3
13.7
0
0
100.0**
(continued)
96
-------
TAHLK 47 (continued)
ORBUS
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBKS
total.
pollut i on-free
crop output/
Percent
are of
total
losses
OHHES
crop
Wheat
IJ.
IN
KY
OH
PA
WV
ORBES
total
84.409
64.243
13.524
56.080
1.479
0.152
219.886
5.4
5.3
5.4
5.3
5.4
5.5
5.3
2.0
1.6
0.3
1.4
§
§
' -5.3#
38
29
6
25
0
0
100
.4
.2
.2
.5
.7
.1
.0**
97
-------
TABLE 48. NET PRESENT VALUE OF PROBABLE TOTAL CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 7*
u O
Percent losses
Percent losses are of ORBES
Losses to crops are of area total
ORBES (millions of pollution-free pollution-free
area dollars) crop output/ crop output/
Percent losses
are of ORBES
total crop
losst
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
1696.950
902.874
211.973
439.929
28.912
4.738
3285.380
8.5 4.4
8.5 2.3
8.6 0.6
8.5 1.1
8.5 0.1
8.6 |
8.5 8.5#
51.7
27.5
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
2668.700
1102.140
344.949
656.433
0
0
4772.220
18.9 10.5
18.8 . 4.4
19.0 1.4
18.8 2.6
0 0
0 0
18.8 18. 8#
55.9
23.1
7.2
13.8
0
0
100.0**
(continued)
98
-------
TABLE 48 (continued)
Losses to crops
ORKES (millions of
area dollars)
Percent Losses
are of area
Pollution-free
crop output/
Percent losses
are of OUBKS
total
pollution-free
crop output/
Percent, losses
arc <>(' UKUliS
total crop
Loss*
Wheat
11,
IN
KY
OH
PA
WV
ORBES
total
107.359
82.089
17.184
71.618
1.878
0.190
280.317
6.8 2.6
6.8 2.0
6.8 0.4
6.8 1.7
6.8 §
6.9 |
6.8 6 . 8#
38.3
29.3
6.1
25.5
0.7
0.1
100.0**
99
-------
TABLE 49. NET PRESENT VALUE OF PROBABLE UTILITY CROP LOSSES,
1976 TO 2000, FROM SO AND 0 , BY CROP: SCENARIO 7*
ORBES
area
Losses to crops
(millions of
dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBES
total crop
losst
Corn
IL
IN
KY
OH
PA
WV
ORBES
total
710.664
377.551
89.524
184.305
12.134
2.003
1376.180
3.6
3.6
3.6
3.6
3.6
3.6
3.6
1.8
1.0
0.2
0.5
§
i
3.6#
51.6
27.4
6.5
13.4
0.9
0.1
100.0**
Soybeans
IL
IN
KY
OH
PA
WV
ORBES
total
1128.110
464.169
147.606
276.252
0
0
2016.130
8.0
7.9
8.1
7.9
0
0
8.0
4.5
1.8
0.6
1.1
i
I
8.0#
56.0
23.0
7.3
13.7
0
0
100.0**
(continued)
100
-------
TABU1; 49 (continued)
Losses to crops
ORBES (millions of
area dollars)
Percent losses
are of area
pollution-free
crop output/
Percent losses
are of ORBES
total
pollution-free
crop output/
Percent losses
are of ORBKS
total crop
losst
Wheat
IL
IN
KY
OH
PA
WV
ORBES
total
45.565
34.576
7.289
30.189
0.797
0.082
118.498
2.9
2.9
2.9
2.9
2.9
3.0
3.0
1.1 38.5
0.8 29.2
0.2 6.2
0.7 25.5
§ 0-7
§ o.i
3.0# 100.0**
101
-------
TABLE 50. NET PRESENT VALUE OF TOTAL CUMULATIVE CROP LOSSES,
1976 TO 2000, BY POLLUTANT: SCENARIO 7*
ORBES
area
IL
IN
KY .
OH
PA
WV
ORBES
total
IL
IN
KY
OH
PA
WV
ORBES
total
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
£* £* O *J
(millions of are of area total (millions of are of area total
dollars) losses^ dollars) lossest
4.251
0.430
1.934
0.120
0.003
0.001
6.739
22.083
2.877
10.673
2.671
0.261
0.112
38.677
Minimum
0.1
§
0.5
§
§
i
0.1
Maximum
0.3
0.1
1.2
0.1
0.5
1.3
0.3
losses
2998.890
1381.520
381.517
772.492
18.556
2.965
5555.940
losses
7128.350
3348.930
906.905.
1862.420
51.646
8.240
13306.500
99.9
100.0
99.5
100.0
100.0
100.0
99.9
99.7
99.9
98.8
99.9
99.5
98.7
99.7
(continued)
102
-------
TABJ.H 50 (continued)
ORHES
area
SO, losses/
TL,
(millions of
dollars)
Percent SO losses
are of area total
losses^
0 losses/
O
(millions of
dollars)
Percent 0 losses
*J
are of area total
losses^
Probable losses
IL
IN
KY
OH
PA
WV
ORBES
total
13.056
1.595
6.073
1.215
0.104
0.044
22.088
0.3
0.1
1.1
0.1
0.3
0.9
0.3
4459.960
2085.510
568.032
1166.770
30.686
4.883
8315.830
99.7
99.9
98.9
99.9
99.7
99.1
99.7 .
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ For total losses, see Tables
§ Less than .05%.
103
-------
TABLE 51. NET PRESENT VALUE OF UTILITY CUMULATIVE CROP LOSSES,
1976 TO 2000, BY POLLUTANT: SCENARIO 7*
ORBES
area
SO losses/ Percent SO losses 0 losses/ Percent 0 losses
£ £ O O
(millions of are of area total (millions of are of area total
dollars) lossest dollars) losses^
Minimum losses
IL
IN
KY
OH
PA
WV
ORBES
total
4.251
0.430
1.934
0.120
0.003
0.001
6.739
0.4 969.418
0.1 446.188
1.5 123.338
§ 249.629
0.1 5.928
0.1 0.950
0.4 1795.450
99.6
99.9
98.5
100.0
99.9
99.9
99.6
Maximum losses
IL
IN
KY
OH
PA
WV
ORBEb
total
22.083
2.877
10.673
2.671
0.261
0.112
38.677
0.6. 3694.680
0.2 1735.480
2.2 470.082
0.3 965.424
1.0 26.713
2.6 4.262
0.6 6896.640
99.4
99.8
97.8
99.7
99.0
97.4
99.4
(continued)
104
-------
TABLE 51 (continued)
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
total
SO losses/
Ct
(millions of
dollars)
13.056
1.595
6.073
1.215
0.104
0.044
22.088
Percent SO losses 0 losses/
Ct O
are of area total (millions of
lossest dollars)
Probable
0.7
0.2
2.5
0.2
0.8
2.1
0.6
losses
1871.280
874.700
238.346
489.532
12.827
2.041
3488.730
Percent. 0 losses
O
are of area total
lossest
99.3
99.8
97.5
99.8
99.2
97.9
99.4
* Assumes a 10% discount rate.
/ Crops are corn, soybeans, and wheat.
£ For total losses, see Tables
§ Less than .05%.
105
-------
TABLE 52. PROBABLE, YEAR BY YEAR, INDIVIDUAL AND AGGREGATE THREE-CROP
TOTAL MONETARY LOSSES: SCENARIO 2 *
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Corn
300.235
310.939
322.043
333.557
345.496
357.871
370.700
383.996
397.777
397.758
397.741
397.726
397.712
397.699
397.688
397.678
397.669
397.661
397.653
397.646
397.640
397.634
397.629
397.624
Soybeans
339.761
366.561
395.553
426.902
460.793
497.423
537.008
579.783
625.998
625.954
625.916
625.881
625.851
625.824
625.801
625.781
625.764
625.749
625.736
625.726
625.718
625.712
625.708
625.706
Wheat
19.4854
21.1796
23.0336
25.0606
27.2749
29.6925
32.3309
35.2093
38.3488
38.3478
38.3470
38.3462
38.3455
38.3448
38.3442
38.3436
38.3431
38.3426
38.3421
38.3417
38.3413
38.3410
38.3406
38.3403
Total
659.481
698.680
740.629
785.520
833.563
884.987
940.040
998.989
1062.120
1062.060
1062.000
1061.950
1061.910
1061.870
1061.830
1061.800
1061.780
1061.750
1061.730
1061.710
1061.700
1061.690
1061.680
1061.670
* Millions of dollars, undiscounted values
106
-------
TABLE 53. PROBABLE, YEAR BY YEAH, INDIVIDUAL AND AGGREGATE THREE-CROP
POWER PLANT MONETARY LOSSES: SCENARIO 2 *
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Corn
120.637
124.872
129.274
133.846
138.592
143.516
148.624
153.921
159.415
159.396
159.379
159.364
159.350
159.337
159.326
159.316
159.307
159.299
159.291
159.284
159.278
159.272
159.267
159.262
Soybeans
137.344
147.940
159.428
171.873
185.346
199.924
215.692
232.743
251.174
251.130
251.092
251.057
251.027
251.000
250.977
250.957
250.940
250.925
250.912
250.902
250.894
250.888
250.884
250.882
Wheat
7.9389
8.5973
9.3226
10.1195
10.9935
11.9505
12.9974
14.14.14
15.3909
15.3899
15.3891
15.3883
15.3876
15.3869
15.3863
15.3857
15.3852
15.3847
15.3842
15.3838
15.3834
15.3831
15.3827
15.3824
Total
265.920
281.409
298.025
315.839
334.932
355.391
377.313
400.805
425.980
425.916
425.860
425.809
425.765
425.724
425.690
425.659
425.632
425.608
425.587
425.571
425.556
425.544
425.534
425.527
* Millions of dollars, undiscounted values.
107
-------
TABLE 54. PROBABLE, YEAR BY YEAR, INDIVIDUAL AND AGGREGATE THREE-CROP
TOTAL MONETARY LOSSES: SCENARIO 2d*
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Corn
300.340
311.137
322.324
333.915
345.923
358.366
371.259
384.616
398.456
398.442
398.431
398.420
398.411
398.404
398.398
398.393
398.389
398.386
398.384
398.383
398.382
398.383
398.384
398.385
Soybeans
340.003
367.013
396.189
427.703
461.744
498.512
538.227
581.123
627.456
627.422
627.393
627.369
627.349
627.332
627.319
627.310
627.303
627.299
627.298
627.299
627.302
627.308
627.315
627.324
Wheat
19.5288
21.2609
23.1485
25.2056
27.4473
29.8902
32.5523
35.4533
38.6145
38.6126
38.6110
38.6094
38.6080
38.6067
38.6056
38.6046
38.6036
38.6029
38.6022
38.6016
38.6011
38.6007
38.6004
38.6002
Total
659.872
699.411
741.661
786.823
835.114
886.768
942.038
1001.190
1064.530
1064.480
1064.440
1064.400
1064.370
1064.340
1064.320
1064.310
1064.300
1064.290
1064.280
1064.280
1064.290
1064.290
1064.300
1064.310
* Millions of dollars, undiscounted values.
108
-------
TABLE 55. PROBABLE, YEAR BY YEAR, INDIVIDUAL AND AGGREGATE THREE-CROP
POWER PLANT MONETARY LOSSES: SCENARIO 2d*
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Corn
120.742
125.070
129.555
134.203
139.019
144.010
149.182
154.540
160.094
160.080
160.069
160.058
160.049
160.042
160.036
160.031
160.027
160.024
160.022
160.021
160.020
160.021
160.022
160.023
Soybeans
137.587
148.391
160.064
172.674
186.298
201.014
216.911
234.083
252.632
252.598
252.569
252.545
252.525
252.508
252.495
252.486
252.479
252.475
252.474
252.475
252.478
252.484
252.491
252.500
Whcal.
7.9823
8.6786
9.4375
10.2645
11.1659
12.1482
13.2187
14.3854
15.6566
15.6547
15.6531
15.6515
15.6501
15.6488
15.6477
15.6467
15.6458
15.6450
15.6443
15.6437
15.6432
15.6428
15.6425
15.6424
Tot.aJ
266.311
282.140
299.057
317.142
336.483
357.172
379.312
403.009
428.383
428.334
428.291
428.255
428.224
428.199
428.179
428.163
428.151
428.144
428.140
428.140
428.142
428.148
428.155
428.166
* Millions of dollars, undiscounted values.
109
-------
TABLE 56. PROBABLE, YEAR BY YEAR, INDIVIDUAL AND AGGREGATE THREE-CROP
TOTAL MONETARY LOSSES: SCENARIO 7*
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Corn
300.238
310.945
322.051
333.568
345.508
35.7.886
370.717
384.014
397.795
400.096
402.415
404.750
407.100
409.465
411.842
414.235
416.642
419.062
421.498
423.946
426.409
428.887
431.379
433.886
Soybeans
339.763
366.569
395.568
426.924
460.822
497.459
537.050
579.830
626.051
634.172
642.407
650.752
659.209
667.777
676.457
685.250
694.159
703.184
712.326
721.587
730.970
740.474
750.103
759.856
Wheat
19.4899
21.1877
23.0445
25.0735
27.2893
29.7079
32.3468
35.2255
38.3649
38.5504
38.7382
38.9278
39.1187
39.3108
39.5041
39.6985
39.8938
40.0901
40.2875
40.4859
40.6853
40.8857
41.0871
41.2894
Total
659.492
698.702
740.663
785.565
833.619
885.053
940.114
999.070
1062.210
1072.820
1083.560
1094.430
1105.430
1116.550
1127.800
1139.180
1150.700
1162.340
1174.110
1186.020
1198.060
1210.250
1222.570
1235.030
* Millions of dollars, undiscounted values.
110
-------
TABLE 57. PROBABLE, YEAR BY YEAR, INDIVIDUAL AND AGGREGATE THREE-CROP
POWER PLANT MONETARY LOSSES: SCENARIO 7 *
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Corn
120.640
124.878
129.283
133.857
138.604
143.530
148.640
153.939
159.433
163.244
167.063
170.889
174.720
178.557
182.396
186.243
190.094
193.949
197.810
201.676
205.547
209.423
213.306
217.193
Soybeans
137.347
147.948
159.443
171.895
185.376
199.960
215.734
232.790
251.227
259.052
266.991
275.039
283.200
291.471
299.854
308.350
316.961
325.688
334.533
343.496
352.580
361.786
371.116
380.570
Wheat
7.9435
8.6054
9.3334
10.1324
11.0079
11.9659
13.0133
14.1576
15.4070
15.7575
16.1092
16.4614
16.8138
17.1663
17.5187
17.8711
18.2234
18.5755
18.9275
19.2794
19.6313
19.9830
20.3346
20.6862
Total
265.931
281.431
298.059
315.885
334.987
355.457
377.388
400.887
426.067
438.053
450.163
462.390
474.733
487.194
499.769
512.465
525.279
538.213
551.271
564.451
577.758
591.192
604.756
618.449
* Millions of dollars, undiscounted losses.
Ill
-------
TABLE 58. PROBABLE THREE-CROP TOTAL ANNUAL MONETARY LOSSES BY
POLLUTANT: SCENARIO 2
(millions of dollars)
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
SO damage
Ct
3.547
3.230
2.956
2.718
2.511
2.326
2.162
2.016
1.884
1.820
1.764
1.713
1.669
1.628
1.594
1.563
1.536
1.512
1.491
1.474
1.459
1.448
1.438
1.431
0 damage
«J
655.934
695.451
737.673
782.801
831.053
882.660
937.877
996.973
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
Total damage/
659.481
698.680
740.629
785.520
833.563
884.987
940.040
998.989
1062.120
1062.060
1062.000
1061.950
1061.910
1061.870
1061.830
1061.800
1061.780
1061.750
1061.730
1061.710
1061.700
1061.690
1061.680
1061.670
* Values are in constant 1975 dollars.
f- Crops are corn, soybeans, and wheat.
112
-------
TABLE 59. PROBABLE THREE-CROP UTILITY RELATED ANNUAL MONETARY LOSSES
BY POLLUTANT: SCENARIO 2
(millions of dollars)
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
SO damage
3.547
3.230
2.956
2.719
2.511
2.326
2.162
2.016
1.884
1.820
1.764
1.713
1.669
1.628
1.594
1.563
1.536
1.512
1.491
1.474
1.459
1.448
1.438
1.431
0 damage
O
262.373
278.180
295.069
313.121
332.421
353.064
375.151
398.789
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
Total damage/
265.920
281.409
298.025
315.839
334.932
355.391
377.313
400.805
425.980
425.916
425.860
425.809
425.765
425.724
425.690
425.659
425.632
425.608 .
425.587
425.571
425.556
425.544
425.534
425.527
* Values are in constant 1975 dollars.
/ Crops are corn, soybeans, and wheat.
113
-------
TABLE 60. PROBABLE THREE-CROP TOTAL ANNUAL MONETARY LOSSES
BY POLLUTANT: SCENARIO 2d
(millions of dollars)
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
SO damage
£
3.938
3.960
3.988
4.022
4.062
4.108
4.161
4.220
4.287
4.237
4.195
4.159
4.128
4.103
4.083
4,067
4.055
4.048
4.044
4.043
4.046
4.051
4.059
4.070
0 damage
*J
655.934
695.451
737.673
782.801
831.053
882.660
937.877
996.973
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
1060.240
Total damage*
659.872
699.411
741.661
786.823
835.114
886.768
942.038
1001.190
1064.530
1064.480
1064.440
1064.400
1064.370
1064.340
1064.320
1064.310
1064.300
1064.290
1064.280
1064.280
1064.290
1064.290
1064.300
1064.310
* Values are in constant 1975 dollars.
/ Crops are corn, soybeans, and wheat.
114
-------
TABLE 61. PROBABLE THREE-CROP UTILITY RELATED ANNUAL MONETARY LOSSES
BY POLLUTANT: SCENARIO 2d
(millions of dollars)
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
SO damage
3.938
3.960
3.988
4.022
4.062
4.108
4.161
4.220
4.287
4.237
4.195
4.159
4.128
4.103
4.083
4.067
4.055
4.048
4.044
4.043
4.046
4.051
4.059
4.070
0 damage
o
262.373
278.180
295.069
313.121
332.421
353.064
375.151
398.789
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
424.096
Total damage/
266.311
282.140
299.057
317.142
336.483
357.172
379.312
403.009
428.383
428.334
428.291
428.255
428.224
428.199
428.179
428.163
428.151
428.144
428.140
428.140
428.142
428.148
428.155
428.166
* Values are in constant 1975 dollars.
/ Crops are corn, soybeans, and wheat.
115
-------
TABLE 62. PROBABLE THREE-CROP UTILITY RELATED ANNUAL MONETARY
LOSSES BY POLLUTANT: SCENARIO 7
(millions of dollars)
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
SO damage
3.558
3.252
2.990
2.764
2.566
2.393
2.237
2.098
1.971
1.940
1.921
1.910
1.902
1.897
1.892
1.889
1.886
1.883
1.880
1.877
1.875
1.873
1.870
1.867
0 damage
O
655.934
695.451
737.673
782.801
831.052
882.660
937.877
996.972
1060.240
1070.880
1081.640
1092.520
1103.530
1114.660
1125.910
1137.300
1148.810
1160.450
1172.230
1184.140
1196.190
1208.370
1220.700
1233.160
Total damage/
659.492
698.702
740.663
785.565
833.619
885.053
940.114
999.070
1062.210
1072.820
1083.560
1094.430
1105.430
1116.550
1127.800
1139.180
1150.700
1162.340
1174.110
1186.020
1198.060
1210.250
1222.570
1235.030.
* Values are in constant 1975 dollars.
/ Crops are corn, soybeans, and wheat.
116
-------
TABLE 63. PHOBABLE THREE-CROP UTILITY RELATED ANNUAL MONETARY
LOSSES BY POLLUTANT: SCENARIO 7 '
(millions of dollars)
Year
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
SO damage
3.558
3.252
2.990
2.764
2.566
2.393
2.237
2.098
1.971
1.940
1.921
1.910
1.902
1.897
1.892
1.889
1.886
1.883
1.880
1.877
1.875
1.873
1.870
1.867
0 damage
O
262.373
278.180
295.069
313.120
332.421
353.064
375.151
398.789
424.096
436.114
448.242
460.480
472.831
485.297
497.876
510.576
523.393
536.330
549.390
562.574
575.883
589.319
602.886
616.582
Total damage/
265.931
281.431
298.059
315.885
334.987
355.457
377.388
400.887
426.067
438.053
450.163
462.390
474.733
487.194
499.769
512.465
525.279
538.213
551.271
564.451
577.758
591.192
604.756
618.449
* Values are in constant 1975 dollars.
/ Crops are corn, soybeans, and wheat.
117
-------
TABLE 64. NET PRESENT VALUE OF COMPLIANCE BENEFITS FOR SO EMISSIONS:
SCENARIOS 2d AND 2 COMPARED*
(millions of dollars)
IL
IN
KY
OH
PA
WV
ORBES
total
IL
IN
KY
OH
PA
WV
ORBES
total
Corn
0.050
0.063
0.002
0.019
0.006
0.001
0.141
4.203
5.353
0.160
1.475
0.488
0.067
11.746
Soybeans Wheat
Minimum
1.845 0
1.874 0
0.074
0.388 0
0 0
0
4.181 0
Maximum
6.107 1
6.193 1
0.239 0
1.293 0
0 . 0
0 0
13.832 2
benefits
.014
.013
*
.003
.001
*
.031
benefits
.274
.136
.028
.250
.094
.004
.786
Total
benefits
1.909
1.950
0.076
0.410
0.007
0.001
4.353
11.584
12.682
0.427
3.018
0.582
0.071
28.364
Total benefits as
percent of total
clean-air
production/
0.0054
0.0110
0.0017
0-0042
0.0019
0.0017
0.0064
0.0325
0.0717
0.0094
0.0311
0.1590
0.1226
0.0417
(continued)
118
-------
TABLE 64 (continued)
Total
Corn Soybeans Wheat benefits
Total benefits as
percent of total
clean-air
production/
Probable benefits
IL
IN
KY
OH
PA
WV
ORBES
total
1.589
2.018
0.049
0.554
0.184
0.025
4.419
4.235
4.299
0.172
0.897
0
0
9.603
0.774
. 0.687
0.015
0.151
0.066
0.002
1.695
6.598
7.004
0.236
1.602
0.250
0.027
15.717
0.0185
0.0396
0.0052
0.0165
0.0683
0.0466
0.0231
* Assumes a 10% discount rate.
/ Discounted present values of pollution-free output are in Tables
Less than .05%.
119
-------
FIGURE I
OHIO RIVER BASIN ENERGY STUDY REGION
PHASE II
Ohio River Drainage Basin
-------
SCENARIO AND IMPACT MODELS: SEQUENTIAL
FIGURE 2
STEPS IN ORBES ASSESSMENT
ECONOMIC
GROWTH
ENERGY AND
FUEL
DEMAND
COAL SUPPLY
AND
ALLOCATION
SITING FOR
ELECTRIC
GENERATING
UNITS
POPULATION
PROJECTION
\
UTILITY EMISSIONS
NON-UTILITY
EMISSIONS
LABOR
REQUIREMENTS
AND INDUCED
MIGRATION
SOCIAL IMPACTS
LAND USE IMPACTS
WATER DEMAND
ECONOMIC IMPACTS
IN ELECTRIC SECTOR
HEALTH IMPACTS:
OCCUPATIONAL
HAZARDS
WATER
POLLUTANT
TRANSPORT
AIR
POLLUTION
TRANSPORT
AQUATIC
AND
TERRESTIAL
^ECOLOGICAL
IMPACTS
HEALTH
IMPACTS:
AIRBORNE
RESIDUALS
(ECONOMIC
IMPACT
[ANALYSIS
ITERATIONS
-------
13100.4
10,000
9000 ..
8000 .:
7000 ..
6000
8111.19
to
5000 .
4000
3000 . .
2000 . .
1000 - .
.528.9^5.5.
FIGURE 11
Total Agricultural Losses for ORBES Scenario 2 by Region
and ORBES-Portions of States, 1976-2000*
* The first column provides maximum, probable and minimum
loss values for the region. Remaining columns show
ORBES-portion probable losses for each state as well as
the percent such losses are of probable total regional
losses.
4349.1
2032.81
1 1 Tfi fid
ORBES
total
130.324
455^^^L^^^A
0.
4.859
IL
IN
OH
KY
PA
WV
-------
6568.66
FIGURE 12
5000 ..
4500
4000
3500 ..
3000 -.
2500 ..
2000 . -
1500 -:
1000
500 . .
3257.02
1595.7
Total Utility Related Agricultural Losses for ORBES Scenario 2
by Region and ORBES-Portions of States, 1976-2000*
* The first column provides maximum, probable and minimum
loss values for the region. Remaining columns show
ORBES-portion probable losses for each state as well as
the percent such losses are of probable total regional
losses.
1747.13
814.237
455.411
*,# " 0,
12.18 . 1.971
ORBES
total
IL
IN
OH
KY
PA
WV
-------
13128.8
10,000
9000 ..
8126.9
8000
rooo
6000
5293.9
5000 . .
4000 . .
3000 . .
2000 . ,
1000 . .
FIGURE 13
Total Agricultural Losses for ORBES Scenario 2d by Region
and ORBES-Portions of States, 1976-2000*
* The first column provides maximum, probable and minimum
loss values for the region. Remaining columns show
ORBES-portion probable losses for each state as well as
the percent such losses are of probable total regional
losses.
4355.690
2039.81C
1138.240
3Tl3G-575 i 4.886
ORBES
total
IL
IN
OH
KY
FA
-------
6597.03
5000 . .
4500 -.
4000
3500 , .
ro
ui
3000
2500
2000 -
1500 -?
LOGO
500 . .
3272.74
1591.35
FIGURE 14
Total Utility Related Agricultural Losses for ORBES Scenario 2d
by. Region and ORBES-Portions of States, 1976-2000*
* The first column provides maximum, probable and minimum
loss values for the region. Remaining columns show
ORBES-portion probable losses for each state as well as
the percent such losses are of probable total regional
losses.
1753.730
821.242
457.013
12.430". .1.999
ORDES
total
II
IN
OH
KY
PA
WV
-------
13345.2
10,000,
9000
8337.92
8000
7000 ..
6000 .
5562.68
fO
5000 ..
4000 ,.
3000
2000 ..
1000 ..
FIGURE 15
Total Agricultural Losses for ORBES Scenario 7 by Region
and ORBES-Portions of States, 1976-2000*
* The first column provides maximum, probable and minimum
loss values for the region. Remaining columns show
ORBES-portion probable losses for each state as well as
the percent such losses are of probable total regional
losses.
4473.010
2087;IOC
1167.980
574.105l30.790 4.927
ORBES
total
IL
IN
OH
KY
PA
WV
-------
7655.05
to
-J
2500
4500 ..
4000
3500
3000 "2876.0
2118.94
2000 *
1500 . .
1000 . .
500 . .
FIGURE 16
Total Utility Related Agricultural Losses for ORBES Scenario 7
by Region and ORBES-Portions of States, 1976-2000*
* The first column provides maximum, probable and minimum
loss values for the region. Remaining columns show
ORBES-portion probable losses for each state as well as
the percent such losses are of probable total regional
losses.
1538.950
714.997
400.329
200. 413 10.591
1.713.
ORBES
total-
It,
IN
OH
KY
PA
WV
-------
$_
1400-
1200-
1000-J
800-
600-H
400-
200-
FIGURE 17
Plot of Total Regional Monetary Losses, by Crop,
1976-2000, Scenario 2
(undiscounted values, millions of dollars)
T = Total Monetary Losses
S = Soybean Monetary Losses
C = Corn Monetary Losses
W = Wheat Monetary Losses
-i 1 h
-1 h
H f 1-
< "\ r 'i' i i i'ii
1977 1978 1980 1982 1984
- W
1986 1988 1990 1992 1994 1996 1998 2000
-------
ISJ
VO
700=
6001
5001
4001
300-
200-
10CU
FIGURE 18
Plot of Utility Related Total Regional Monetary Losses,
by Crop, 1976-2000, Scenario 2
(undiscounted values, millions of dollars)
0-L ,_
1977 1978 1980 ' 1982 1984 1986 1988
T
C
S
W
Total monetary losses
Corn monetary losses
Soybean monetary losses
Wheat monetary losses
S 5
W
1
1998 2000
1990
1992 1994
1996
-------
u>
o
1400-
1200-
1000-
800-
600-
400-
200-
FIGURE 19
Plot of Total Regional Monetary Losses, by Crop,
1976-2000, Scenario 2d
(undiscounted values, millions of dollars)
T = Total Monetary Losses
S = Soybean Monetary Losses
C = Corn Monetary Losses
W = Wheat Monetary Losses
w
u 1 1 1 11 1 1 1
1977 1978 1980 1982 1984
1 1 f
1986 1988
"I 1
1990
I 1 1
1992 1994
i 1 1 1 r~
1996 1998 2000
-------
7001
6001
5001
3001
2001
10CU
FIGURE 20
Plot of Utility Related Total Regional Monetary Losses,
by Crop, 1976-2000, Scenario 2d
(undiscounted values, millions of dollars)
T = Total monetary losses
C = Corn monetary losses
S = Soybean monetary losses
W = Wheat monetary losses
,
I
. «
.
1
. w
, "j...,_
1977 1978 i960 1982 1984 1986 1988
1990
1992 1994
1996
1998 2000
-------
u>
r-o
$-
1400-
1200-
1000-
800-
600-
400-
200-
FIGURE 21
Plot of Total Regional Monetary Losses, by Crop,
1976-2000, Scenario 7
(undiscounted values, millions of dollars)
T = Total Monetary Losses
S = Soybean Monetary Losses
C = Corn Monetary Losses
W = Wheat Monetary Losses
ol,,-
1977 1978 1980 1982 1984 1986
I I T I I I T I I I I I I
1988 1990 1992 1994 1996 1998 2000
-------
7001
6001
5001
4001
300IJ
200-
10CU
FIGURE 22
Plot of Utility Related Total Regional Monetary Losses,
by Crop, 1976-2000, Scenario 7
(undiscounted values, millions of dollars)
T
C
S
W
Total monetary losses
Corn monetary losses
Soybean monetary losses
Wheat monetary losses
0~L
1977 1978 1980
1982
1984
-I 1 1
1986 1988
1990
1992
1994
1996
1998
2000
-------
$-
1400-
FIGURE 23
Plots of Total, O and SO Crop Damages, 1976-2000,
in the ORBES Region, Scenario 2
(undiscounted millions of dollars)
1200-
1000-
800-
600-
0 T
400-
200-
T = Total damage
O = O- damage
S = SO damage
1977 1978
1980
1982
1984
1986 1988
1990 1992
1994
I I
1996
I
1998
\ i I
2000
-------
7001
6001
500~
400li
3003
200-
10CUJ
FIGURE 24
Plots of Total, O and SO Utility Related Crop Damages,
1976-2000, in the ORBES Region, Scenario 2
(undiscounted millions of "dollars)
T
0
T -; Total damage
0 = 0_ damage
*5
S = SO damage
~4
"HI 1 1 '
i
1977 1978 1980 1982 1984
1
1986
.
s
-1 1 1 1 1 1 1 1 1 1 1 1 1 1
1988 1990 1992 1994 1996 1998 2000
-------
1000^
. 80(H
600H
400-^
200-J
FIGURE 25
Plots of Total O and SO Crop Damages, 1976-2000,
in the ORBES Region, Scenario 2d
(undiscounted millions of dollars)
O T
T = Total damage
O=O, damage
S = SO damage
1977 1978 ' 1980
ii i
1982 1984
i i
1986
i r
1988
1990
1992
1994
1 I
1996
1998
I i
2000
-------
FIGURE 26
7001
6001
5001
4001
3001
200-
Plots of Total, 03 and SO Utility Related Crop -Damages,
1976-2000, in the ORBES Region, Scenario 2d
(undiscounted millions of dollars)
T
0
100^
0"
i
1977 1978 1980 1982 1984
T =
!
, i
. .
1 r l l T i
1986 1988 1990 1992
0 =
s =
1 -
1994
Total damage
0 damage
SO damage
c
' 1 -t 1 -1 - '1
1996 1998 2000
-------
U)
00
1400-
1200-
1000-
800-
600-
400-
200-
FIGURE 27
Plots of Total O and SO Crop Damages,
in the ORBES Region, Scenario 7
1976-2000,
7
(undis counted millions of dollars)
T = Total damage
O=0 damage
S = SO- damage
1 1 1 T 1 1 1 1 1 1 1 \ 1 1
1977 1978 1980 1982 1984 1986 1988 1990 1992 1994
1996
1998
2000
-------
OJ
10
eoor
soo:
4001
3001
200-
FIGURE 28
Plots of Total, O and SO Utility Related Crop Damages,
1976-2000, in the ORBES Region, Scenario 7
(undiscounted millions of dollars)
T = Total damage
-
10CU
6~
1977
i
i
1 i I J
i
i . . j
0 = 0_ damage
O
1 1 1 1 i i i i
1978 1980 1982 1984 1986 19i
S = SO damage
Ci
<
Q
1 1 1 1 1 1 1
J8 1990 1992 1994 1996
111!
1998 2000
-------
REFERENCES
1, Orie Loucks, Thomas V. Armentano, Roland Usher, and Wayne Williams, The
Institute of Ecology; Richard W. Miller, The Institute of Ecology and
Butler University; and Larry Wong, Indiana University, Crop and Forest
Losses Due to Current and Projected Emissions from Coal-Fired Power
Plants in the Ohio River Basin, Subcontract under Prime Contract
EPA R805588.
2. Walter P. Page, West Virginia University, and Doug Gilmore and Geoffrey
Hewings, University of Illinois at Urbana-Champaign, An Energy and Fuel
Demand Model for the Ohio River Basin Energy Study Region, Grant No.
EPA R805585 and Subcontract under Prime Contract EPA R805588.
3. Gary L. Fowler, University of Illinois at Chicago Circle;. J.C. Randolph,
Indiana University; Robert E. Bailey, The Ohio State University; Steven
I. Gordon, The Ohio State University; Steven D. Jansen, University of
Illinois at Chicago Circle; and W.W. Jones, Indiana University, The
Ohio River Basin Energy Facility Siting Model, Vols. I and II, Grant
Nos. EPA R805588, R805589, and R805609 and Subcontract under Prime
Contract EPA R805588 .
4. James J. Stukel and Brand L. Niemann, University of Illinois at Urbana-
Champaign, Documentation in Support of Key ORBES Air Quality Findings,
Grant No. EPA R805588.
5. Teknekron Research, Inc., Air Quality and Meteorology in the Ohio
River Basin: Baseline and Future Impacts, Subcontract under Prime
Contract EPA R805588 .
6. E.J. Mishan, Welfare Economics, Five Introductory Essays, Random House,
New York, 1964 .
7. Ronald G. Ridker, Economic Costs of Air Pollution, Praeger Publishers,
New York, 1967 .
8. Arnold C. Harberger, "Three Basic Postulates for Applied Welfare
Economics", Journal of Economic Literature, September, 1971.
9. J. R. Hicks, Value and Capital, An Inquiry into Some Fundamental
Principles of Economic Theory, Oxford University Press, 1974.
10. Arnold C. Harberger, "Taxation, Resource Allocation, and Welfare," in
The Role of Direct and Indirect Taxes in the Federal Revenue System ,
Princeton University Press, 1964.
140
-------
11. S. Leung, W. Reed, S. Cauchois and R. Howitt, "Methodologies for
Evaluation of Agricultural Crop Yield Changes: A Review", Corvallis
Environmental Research Laboratories, August 1978.
12. H.M. Benedict and J.A. Jaksch, "Protocol for Economic Assessment of
Damage to Vegetation by Air Pollution", Chapter XI in Methodologies
for Assessment of Air Pollution Effects on Vegetation, Air Pollution
Control Association, Pittsburgh, 1979.
13. R.M. Adams, N. Thanaribulchai and T. Crocker, "Preliminary Assessment
of Air Pollution Damages for Selected Crops within Southern California",
Volume III, Method Developments for Assessing Air Pollution Control
Benefits, EPA, 1976.
14. S. Leung, R. Johnson, T. Ling, M. Noorbakhsh, W. Reed and R. Walthall,
"The Economic Effect of Air Pollution on Agricultural Crops, Application
and Evaluation of Methodology: A Case Study, Interim Report", Eureka
Laboratories, Inc., 1979.
15. J.A. Jaksh, "Economic Evaluation of Air Pollution Damage to Crops: The
Essentials for a Proper Analysis", presented at the 72nd Annual Meeting
of the Air Pollution Control Association, 1979.
16. H. Askari and J.T. Cummings, "Estimating Agricultural Supply Response
with the Nerlove Model: A Survey", International Economic Revue,
Volume 8, No. 2, page 257-292, June, 1977.
17. M. Nerlove,.Dynamics of Supply; Estimation of Farmers Response to Price,
John Hopkins University Press, Baltimore, 1968.
18. S.M. Fischer and P. Temin, "Regional Specialization and the Supply of
Wheat in the United States, 1867-1914", A Review of Economics and
Statistics, Volume LII, pages 134-39, May 1970.
19. J.P. Houck and A. Subotnik, "The U.S. Supply of Soybeans: Regional
Acreage Function", Agricultural Economic Research, Volume XXI, pages
99-108, October 1969.
20. W. Page, "Wheat Culture and Productivity Growth in Small Grain Produc-
tion in the U.S., 1867-1914: A Comment", The Review of Economics and
Statistics, Volume LVI, No. 1, February, 1974.
141
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APPENDIX A
Table A-1
NET PRESENT VALUE OF PROBABLE TOTAL AND UTILITY-RELATED
CUMULATIVE CROP LOSS, 1976 TO 2000,
FROM SO AND 0 : SCENARIO 2*
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
TOTAL
Losses
(millions of
dollars)
3755.56
(1565.78)
1758.51
(727.60)
479.76
. (201.18)
976.00
(403.18)
27.71
(11.58)
4.48
(1.91)
7002.03*
(2911.22)
Percent losses ^are
of pollution-free
output
10.5
(4.4)
10.0
(4.1)
10.6
(4.4)
10.1
(4.2)
7.6
(3.2)
7.7
(3.3)
10.3
(4.3)
Percent losses are
of ORBES total
losses
53.6
(53.8)
25.1
(25.0)
6.1
(6.9)
13.9
(13.8)
0.4
(0.4)
0.1
(0.1)
100.0
(100.0)
* Assumes a 10% discount rate. Numbers in parentheses are for utility-
related losses.
/ Crops are corn, soybeans, and wheat.
# Sum may notbe 100% due to rounding.
& SO losses are .7% of total and O 99.3%.
142
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. Table A-2
NET PRESENT VALUE OF PROBABLE TOTAL AND UTILITY-RELATED
CUMULATIVE CROP LOSS, 1976 to 2000,
FROM SO AND 0 : SCENARIO 2d*
ORBES
area
IL
IN
KY
OH
PA
WV
ORBES
TOTAL
Losses
(millions of
dollars)
3767.02
(1577.24)
. 1771.41
(740.50)
482.59
(204.01)
977.96
(405.11)
27.95
(11.82)
4.51
(1.93)
7031. 41&
(2940.61)
Percent losses
are of
pollution-free
output
10.6
(4.4)
10.0
(4.2)
10.6
(4.5)
10.1
(4.2)
7.6
(3.2)
7.8
(3.3)
10.4
(4.3)
Percent losses
are of
ORBES total
losses
53.6
(53.6)
25.2
(25.2)
6.9
(6.9)
13.9
(13.8)
0.4
(0.4)
0.1
(0.1)
100.0
(100.0)
* Assumes a 10% discount rate. Numbers in parentheses are for utility-
related losses.
/ Crops are corn, soybeans, and wheat.
# Sum may not be 100% due to rounding.
& SO losses are 1.1% of total and O 98.9%.
143
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Table A-3
NET PRESENT VALUE OF PROBABLE TOTAL AND UTILITY-RELATED
CUMULATIVE CROP LOSS, 1976 TO 2000,
FROM SO AND O : SCENARIO 7*
ORBES
area
Losses
(millions of
dollars)
Percent losses are
of pollution-free
output
Percent losses are
of ORBES total
losses*
IL
IN
KY
OH
PA
WV
ORBES
TOTAL
4491.960
(1998.010)
2090.910
(924.048)
574.604
(256.996)
1168.870
(516.399)
30.909
(13.649)
4.978
(2.231)
8362.221
(3711.345)
12.6
(5.6)
11.8
(5.2)
12.7
(5.7)
12.0
(5.3)
8.4
(3.7)
8.6
(3.9)
12.3
(5.5)
53.7
(53.8)
25.0
(24.9)
6.7
(6.9)
14.0
(13.9)
0.4
(0.4)
0.1
(0.1)
100.0
(100.0)
* Assumes a 10% discount rate. Numbers in parentheses are for utility-
related losses.
/ Crops are corn, soybeans and wheat.
$ Sum may not be 100% due to rounding.
& SO losses are .6% of total and O 99.4%.
144
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