I
EPA 540/9-76-001
January 1976
\
A BENEFIT-COST SYSTEM
FOR
CHEMICAL PESTICIDES
Office of Pesticide Programs
Office of Water and Hazardous Materials
Environmental Protection Agency
Washington, D.C. 20460
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A BENEFIT COST SYSTEM FOR
CHEMICAL PESTICIDES
By
Ralph Kennedy
Robert Lowrey
Alan Bernstein
Frederick Rueter
with
Herbert Cole
Henry F. Smyth
Final Report
June 1975
Contract No. 68-01-297(
For
Environmental Protection Agency
Strategic Studies Unit, OPP WH-566
401 M Street, S.W.
Waterside Mall, Room 507E
Washington, D.C 20460
ATTN: John C harbonneau
Project Officer
EPA- 540/9-76-001
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EPA RL.VIEW NOTICE
This EPA Report has been reviewed by the Office
of Pesticide Programs and approved for publication.
Approval does not signify that the contents necessarily
reflect the views, and policies of the Environmental
Protection Agency, or does mention of trade names or
comercial products constitute endorsement or
recommendation for use.
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PREFACE
CONSAD Research Corporation prepared this report during the
period October 8, 1974 - June 30, 1975, under Contract Number 68.-
01-2970 for the Strategic Studies Unit, Office of Pesticide Programs,
Environmental Protection Agency. Dr. John Charbonneau was the
EPA Project Officer.
Mr. Ralph Kennedy, Dr. Robert Lowrey, Mr. Alan Bernstein,
and Dr. Frederick Rueter were the principal CONSAD personnel
assigned to this project.
Dr. Herbert Cole, plant pathologist and chemical pesticides
expert, The Pennsylvania State University, and Dr. Henry F. Smyth,
Jr., toxicologist and Advisory Fellow, Mellon Institute, were the
principal consultants.
ii
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PART I
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TABLE OF CONTENTS
Page
PREFACE jj
EXECUTIVE SUMMARY vii
1.0 INTRODUCTION 1.1
1.1 Purpose Li
1.2 Focus 1.1
1.3 Methodology 1.3
2.0 THE BIOLOGICAL BASIS FOR BENEFIT-
COST ASSESSMENT OF PESTICIDE USE 2. 1
2. 1 Introduction 2. 1
2. 2 Pest Control Alternatives 2. 2
2. 3 Benefits and Costs from Pest Control 2. 5
2. 4 Measuring Benefits and Costs 2. 6
2. 5 Evaluation of a Pesticide in
Terms of Parallel C rnparisons
with Similar Materials 2. 10
2.5.1 Efficacy 2.11
2.5.2 General and Environmental Chemistry 2.12
2.5.3 ProductHazard 2.13
2.6 Summary 2.14
2.7 References 2.15
3.0 THE ECONOMIC EVALUATION OF THE
BENEFITS AND COSTS OF PESTICIDE USE 3. 1
3. 1 Introduction 3 1
3. 2 Evaluation of Benefits and Costs 3. 2
3.2. 1 Net Internal Benefits 3.2
3.2. 1. 1 Perfectly Competitive Industry:
Cost-Reducing Use 3. 3
3. 2. 1. 2 Perfectly Competitive Industry:
Price-tncrea sing Use 3. 8
3.2. 1.3 Oligopolistic Industry 3.9
3. 2. 1.4 Measurements of Net
Internal Benefits 3.9
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TABLE OF CONTENTS (continued)
Page
3.2. 1.5 The Desirability of Marginal
Production Cost Data 3. 14
3.2.2 NetExt3rnalBenefits 3.16
3. 2. 2. 1 Health Benefits and Costs
Accruing to Households 3. 17
3. 2. 2. 2 Health Benefits and Costs
Accruing to Public Agencies 3. 18
3. 2. 2. 3 Environmental Benefits and
Costs Accruing to Households 3. 18
3.2.2.4 Environmental Benefits and Costs
Accruing to Public Agencies 3. 19
3. 2. 2. 5 Regulatory Benefits and Costs
Accruing to Public Agencies . 19
3.2. 3 The Treatment of the Displacement
of Competitive Pesticides 3. 20
3.2.4 Discounting Fnture Benefits and Costs 3.21
3. 2. 5 The Economic Benefits and Costs
Associated with Each Category
of Pesticide Use 3.23
3. 3 Structure of the Benefit-Cost Submodels 3. 29
4.0 THE FOOD, FEED, AND
FIBER PRODUCTION SUBMODEL 4. 1
4.1 Background 4.1
4.2 Net Benefits to Society from PesticideUse 4.1
4. 2. 1 Acres of Crops Treated by Pesticides 4. 3
4.2.2 Change in Crop Output
Attributable to Pesticides 4. 10
4.2.3 Change in Crop Prices
Attributable to Pesticides 4. 12
4.2.4 Change in Consumerst Surplus
Attributable to Pesticides 4. 15
4. 3 Costs of Pesticide Application 4. 16
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TABLE OF CONTENTS (continued)
Page
5.0 THE HEALTH EFFECTS SUBMODEL 5. 1
5. 1 Background 1
5. 2 Outputs of the Health Effects Submodel 5. 1
5. 2. 1 Health Damages 5. 1
5.2. 1. 1 Definition of Health Damages
Based on Human Experience Data 5.6
5. 2. 1.2 Definition of Health Damages
Bas d on Experimental
Toxicology Data 5.9
5. 2. 1.3 Refinement and Quantification
of Health Damages 5. 15
5.2.2 Health Benefits 5. 17
5. 3 Inputs to the Health Effects Submodel 5. 18
5. 4 Relating Inputs and Outputs
of the Health Effects Submodel 5. 20
5. 5 Application of the Health Eiiects Submodel 5.23
6.0 THE ENVIRONMENTAL EFFECTS SUBMODEL 6. 1
6. 1 Conceptual Structure and Assumptions 6. 1
6. 2 Accumulation and Degradation Processes 6. 4
6. 2. 1 Application Rates Per Acre 6. 6
6.2.2 DecayRatesinSoil 6.7
6.2.3 Runoff Rates 6.22
6. 3 Biological Uptake 6. 22
6.4 Population Damages 6.27
6. 5 Monetary Evaluations 6. 32
6. 6 Areas for Future Work 6. 32
7.0 SUMMARY OF THE bENEFiT-
COST SYSTEM PROCEDURES 7. 1
7. 1 Criteria for Design of the Benefit-
Cost System and Input Requirements 7. 1
7. 2 Outputs of the Benefit-Cost System 7. 2
7. 3 Calculation Procedures 7. 3
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TABLE OF CONTENTS (continued)
Page
APPENDIX A: Taxonomie s for Alternative
Pest Control Methods A. I
APPENDIX B: Benefits and Costs from Pest Control B. 1
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EXECUTIVE SUMMARY
In this report, the application of benefit-cost analysis in the
registration of chemical pesticides is developed. A comprehensive
benefit-cost system, designed to be used both in the registration of
new pesticides, as well as in the reregistration of existing pesticides,
is described. It is a workable system, not an ideal one; that is, it
reflects the current state-of-the-art and it uses the presently avail-
able data. As technology improves, more data become available, and
knowledge increases, components of the system can be upgraded to
reflect these changes. Nevertheless, the present system is intended
to provide convenient, summary formats of the most promininent indi-
cators of benefits and costs, so that all benefits and costs, especially
those which are conceptually and empirically difficult to measure - -
such as long-term human health and indirect environmental effects --
are formatted and depicted in the most comparable presentation ros—
sible.
The criteria for the development of the system included:
The system must be generally applicable over a
broad range of pesticide types and uses,
The system must contain flexibility for use with
pesticides which have not yet been registered, as
well as those which require a reregistration
decision, and it must enable the forecasting of
benefits and costs for five-year intervals,
• The system must comprehend all possible bene-
fits and costs attributable to chemical pesticides,
and
• The system must as closely as possible reflect
processes that are seen in the “real-world ’ pes-
ticides context, including farmers decisions to
use pesticides, the movement of residues through
soil and water into the food chain, and the appear-
ance of pesticide residues in human tissue.
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These criteria had an all-pervasive effect on how the benefit-cost sys-
tem was developed, especially in the sense that alternative assumptions
and calculating procedures were required, depending, for example, on
whether the pesticide seeking (re) registration was an agricultural or
public health type, and depending on what agency or component of society
bore the costs and reaped the benefits.
These alternative assumptions, or conditions, which could be
imposed on the benefit-cost system, and to which the system had to be
responsive, dictated that the system had to be developed on a biologic-
ally sound basis. Therefore, following an introduction to the study in
Chapter 1. 0, Chapter 2. 0 was devoted to describing the biological basis
for benefit-cost assessment of pesticide use. Four categories of pests
were identified, the destruction or control of which would be the mecha-
nism by which benefits were achieved:
• Plant pathogens: Organisms which have adverse
effects on valuable plants, these effects being,
called tidiseases, ti
• Weeds: Plants which are unwanted, and which
compete with valuable plants for water, nutrients,
and other life-components,
• Insects and other arthropods: Animals which feed
upon or otherwise antagonize and damage plants,
animals, people, natural and man-made objects,
and structures, and
• Vertebrates: Animals which have the same effects
in general as the insects and other arthropods.
Furthermor , the various types of pest control available to handle these
pest problems were identified as follows:
• Genetic resistence, tolerance or immunity on the
part of the plant or crop or other organism attacked
by the pest,
• Biological control of the pest by parasites, predators
or other living organisms,
• Cultural control by avoidance, water management or
other techniques,
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• Physical and mechanical control, and
• Chemical control.
These categories of pests and pest control alternatives are shown in
detail in Chapter 2. 0 and Appendix A.
The last category, chemical pesticides, was selected as the main
focus of the study, and the benefit-cost approach required that users
and uses of this group be identified. The users of chemical pesticides,
or more specifically, those entities receiving benefits or incurring
costs from chemical pesticide use, were broadly defined as follows:
• Private institutions, agency or individual,
Manufacturer of pesticide,
Formulator,
• . Distributor,
• * Wholesaler,
• . Retailer,
Applicator,
Agricultural producer,
Field worker,
Private individual.
• Public agencies,
Federal government,
State government,
Local government.
• Society as a whole.
• Non-human environmental components,
Marine aquatic,
Fresh water aquatic,
• • Terrestrial.
Five categories of chemical pesticide use were defined as:
Pesticide use in food, feed, and fiber production,
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• Pesticide use in health/disease vector and nuisance
pest control,
• Pesticide use in commercial-industrial situations,
• Pesticide use in providing aesthetic improvement,
and
• Pesticide use in providing environmental management.
Benefits received and costs incurred by the above users for each use
category were then outlined. Details of this taxonomy are further
explained in Chapter 2. 0 and Appendix B.
This biological basis for benefit-cost assessment of pesticide
use provided support for the subsequent creation of benefit-cost
matrices and analytical procedures. Thus, based upon the analysis
in Chapter 2. 0, the third chapter provides an economic-theoretic
basis for the use of benefit-cost concepts for analyzing pesticide use,
and a three-dimensional matrix for the identification of: (1) pesticide
use categ3ries, (2) distribution of benefits and costs, and (3) the sepa-
ration of benefits and costs which are internal (direct) from those
wh h are external (indirect). The use of this matrix is to ensure the
complete analysis of all benefits and costs, to aid in preventing double-
counting, and to enable the identification of the agencies, entities or
other components of society who receive the benefits and pay the costs
of pesticide use.
Upon examining the matrices, it becomes evident that there are
market uncertainties for the pesticide producer and economic, social,
and environmental uncertainties for users, consumers, and society as
a whole. Therefore, it was necessary to develop a series of flexible
algorithms and analytic techniques that could be used in each of the
pesticide use categories, when necessary. These algorithms are
referred to as “submodels’ t in this study, and alternative techniques
for quantifying each submodel are available. All submodels pertinent
to a pesticide registration decision should be used.
Hence, those segments of the benefit-cost matrices developed
in Chapter 3.0 that will receive the most use during pesticide product
registration decisions have been fully developed as submodels. These
include the food, feed, and fiber production submodel developed in
Chapter 4. 0, the health effects submodel developed in Chapter 5. 0,
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and the environmental effects submoc3el developed in Chapter 6. 0. In
each of these three chapters, procedures for calculating the relevant
benefits and costs -- outlined in Appendix B and in the matrices of
Chapter 3. 0 - - are discussed, along with the data requirements and
possible data sources. Overall, the models are intended to draw on
existing public agency and research data, as well as data supplied by
the registration process itself. With these data, a range of benefits
and costs can be assessed which are likely to occur if a proposed pes-
ticide is registered. For pesticides on which substantial historical
and test data exist, the range can be made quite narrow, but in the
case of very innovative and unknown chemical compositions, the range
must be broadly defined as best it can be, by drawing on toxicity, per-
sistence, and effectiveness data for similar materials and formulations.
A summary of the three submodels presented in Chapters 4. 0,
5.0, and 6. 0 concludes the description of the benefit-cost system.
Through this summary (Chapter 7. 0), the user of the methodology gets
a ufeel t for what the system can provide in terms of assessing benefits
and costs associated with the use of a pesticide. This, in turn, allows
the user to see the dimensions on which a decision concerning registra-
tion or reregistration of a pesticide product can be made.
The benefit-cost system, and in particular, the procedures devel-
oped in Chapters 4. 0, 5. 0, and 6. 0 is then tested during an hypothetical
phenoxy herbicide seeking registration for use on wheat, oats, and
barley crops. The results of this case study appear in a separate
volume.
It is important to recognize that the complexity of the benefit-cost
calculations described in the system will differ when:
• The pesticide is proposed for reregIstration instead
of for its first registrations
• The pesticide is known to be highly toxic or highly
persistent, relative to most other pesticides, to the
extent that even moderate rates of exposure to people
might have severe acute or chronic health effects,
and
• The range of crops or other types of uses is either
very extensive, or very narrow, with accompanying
ranges of probable geographic dispersion of the pes-
ticide.
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Thus, the flexibility of the algorithms and analytic techniques cornpris-
ing the benefit—cost system is crucial. Furthermore, the system is
intended to be used in a decision-making context, with the systematic
development of comparable calculations of benefits and disbenefits
(costs) for one specific pesticide, in comparison with alternative pes-
ticides or other pest control programs.
It is also important to point out that the analytic techniques used
in each submodel are not based on detailed physical models. Data
deficiencies and a lack of knowledge exist which do not allow for the
development or use of such models. This is particularly true when
trying to assess the health and environmental benefits and costs of a
new pesticide solely from animal toxicology and other experimental
data. The development of techniques whereby comparisons can be
made with similar pesticides already established on the market is use-
ful, but can give biased results. However, these comparison proce-
dures are used, as they provide the best information available at the
present time.
Continued progress in understanding the relationships between
efficacy in a test situation and the expected results when a pesticide is
used commercially, and between animal toxicology and other experi-
mental data and expected human health and environmental impacts on
a broad scale, can add precision to the algorithms and analytic tech-
niques presented in this study. The methodology is a dynamic one and
must be updated and improved as more knowledge and better informa-
tion become available in the future,.
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1.0 INTRODUCTION
1.1 Purpose
In this study, the application of benefit-cost analycis in the regis-
tration of chemical pesticides is developed by:
• Presenting a taxonomy of commonly recognized
pests and pest control alternatives.
• Providing a taxonomy of entities receiving bene-
fits and incurring costs for various uses of pes-
ticides.
• Describing a matrix of benefits and costs appli-
cable to each pesticide use category.
• Reviewing applicable methodologies for assessing
the appropriate benefits and costs.
• Developing a benefit-cost system by using flexible
algorithms and analytic techniques that can effi-
ciently measure and format the benefits and costs
using available information.
• Testing the benefit-cost system using an hypothet-
ical phenoxy herbicide as a case study.
12 Focus
In the development of the benefit-cost system to be used in the
registration process of chemical pesticides, the focus has been on
structuring a system that will be applicable to the registration of new
pesticides, as well as the reregistration of existing pesticides. Fur-
thermore, in developing the procedures to be employed in measuring
benefits and costs, it was assumed that the registration or reregistra-
tion decision will be with respect to one pcsticid product when used
for a particular use or multiple similar uses. Therefore, specifica-
tion of the use(s) of the pesticide product must be made -- e.g., the
1. 1
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(those) crop(s) to receive the pesticide product. Then, the basic deci-
sion criterion involves a comparison of the benefits and costs associ-
ated with the use of the pesticide product in the manner specified with
respect to some alternative practice. In the theoretical specification
of benefits and costs, monitoring and regulating costs of the registra-
tion process are considered, but detailed computation techniques are
not developed in the benefit-cost system.
Although the benefit-cost system has been developed with the
above focus, the basic computation techniques can be used in other
areas of pesticide regulation, for example:
• Suspect chemical review,
• Review prior to possible cancellation/suspension
actions, and
• Analysis in support of ongoing cancellation/sus-
pension hearings.
However, if this were done, the bounds of the benefit-cost analysis
would change. That is, instead of analyzing the benefits and costs
associated with one pesticide prrduct when used for a particular use
or multiple similar uses, the analysis may now focus on:
• All products containing a given active ingredient,
or
• All products containing a given active ingredient
registered for a particular use or several speci-
fied uses.
Needless to say, the benefit-cost analysis would not proceed in an ider-
tical manner. The complexity of the benefit-cost calculations would
differ and the data problems may also change. Furthermore, the
decision criteria would be more complex, as attempts would now be
made to cancel selected uses such that net benefits are maximized.
In addition, the monitoring and regulating costs would be vastly differ-
ent as cancellation decisions are much more costly than registration
decisions in terms of data gathering, personnel, legal hearings, etc.
1.2
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Nevertheless, the benefit-cost system that is developed in this
study can provide the direction for pesticide regulatory decision-
making in areas other than registration and reregistration of chemical
pesticides. Flexibility must be exercised, however, in applying the
techniques to areas other than those intended for by the present benefit-
cost system.
1.3 Methodology
The analysis begins in Chapter 2. 0 by describing the biological
basis for benefit-cost assessment of pesticide use. The commonly
recognized pests are described, followed by the various pest control
alternatives available to counteract these pests. Benefits and costs
associated with various uses of pesticides are outlined, along with
those entities receiving benefits or incurring costs from pesticide use.
General problems associated with the measurement of benefits and
costs are then touched upon. Thus, the chapter provides the basis for
the creation of benefit-cost matrices and the analytic procedures that
follow.
Chapter 3. 0 continues with an economic-theoretic basis for the
use of benefit-cost concepts in analyzing pesticide use. Benefits and
costs are described as being either internal to the decision-making
process or external to the decision-making process. A set of matrices
are developed outlining the various benefits and costs received or
incurred by the various entities in the pesticide use decision process.
One matrix is presented for each pesticide use category, i. e. , pesti-
cides used in food, feed, and fiber productions pesticides used in
health/disease vector and nuisance pest control, pesticides used in
commercial-industrial situations, pesticides used in providing aesthetic
improvement, and pesticides used in providing environmental manage-
ment.
Upon examining the matrices, it becomes evident that there are
market uncertainties for the pesticide producer and economic, social,
and environmental uncertainties for users, consumers, and society as
a whole. Therefore, it was necessary to develop a series of flexible
algorithms and analytic techniques that could be used in each of the
pesticide use categories, when necessary. These algorithms are
referred to as “submodels” in this study, and alternative techniques
forquantifying each submodel are available. All submodels pertinent
to a pesticide registration decision should be used.
1.3
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Hence, those segments of the benefit-cost matrices developed in
Chapter 3. 0 that will receive the most use during pesticide product
registration decisions have been fully developed as submodels. These
include the food, feed, and fiber production submodel developed in
Chapter 4. 0, the health effects submodel. developed in Chapter 5. 0,
and the environmental effects submodel developed in Chapter 6. 0. In
each of these three chapters, procedures for calculating the relevant
benefits and costs -- outlined in Appendix B and in the matrices of
Chapter 3 O -- are discussed, along with the data requirements and
possible data sources. Overall, the models are intended to draw on
existing public agency and research data, as well as data supplied by
the registration process itself. With these data, a range of benefits
and costs can be assessed which are likely to occur if a proposed pes-
ticide is registered. For pesticides on which substantial historical
and test data exist, the range can be made quite narrow, but in the
case of very innovative and unknown chemical compositions, the range
must bc broadly defined as best it can be, by drawing oi toxicity, per-
sistence, and effectiveness data for similar materials and formulations.
Furthermore, summary formats of the most prominent indicators of
benefits and costs are provided, so that all benefits and costs, and
especially those which are conceptually and empirically difficult to
measure --- such as long-term health and indirect environmental
effects -- are formatted and depicted in the most comparable presen-
tation possible.
Chapter 7. 0 completes the description of the benefit-cost system
by providing a summary of the three submodels presented in Chapters
4. 0, 5. 0, and 6. 0. In this way, the user of the methodology gets a
“feel” for what the system can provide in terms of assessing benefits
and costs associated with the use of a pesticide. This, in turn, allows
the user to see the dimensions on which a decision- concerning regis-
tration or reregistration of a pesticide product can be made.
The testing of the benefit-cost system, and in particular, the
procedures developed in Chapters 4. 0, 5. 0, and 6. 0, completes the
study and is accomplished using an hypothetical phenoxy herbicide
seeking registration for use on wheat, oats, and barley crops. The
results of this case study appear in a separate volume.
1.4
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2.0 THE BIOLOGICAL BASIS FOR BENEFIT-
COST ASSESSMENT OF PESTICIDE USE
2, 1 Introduction
Pesticides are used to manipulate biological components of the
earth ecosystem. Public Law 92-516 defines “pest” as “(1) any insect,
rodent, nematode, fungus, weed or (2) any other form of terrestrial
or aquatic plant or animal life or virus, bacteria, or other micro-
organism (except viruses, bacteria, or other micro-organisms on or
in living man or other living animals) which the Administrator (EPA)
declares to be a pest.” The term pesticide in Act 92-516 is defined
as “(1) any substance or mixture of substances intended for preventing,
destroying, repelling or mitigating any pest and (2) any substance or
mixture of substances intended for use as a plant regulator, def&iant,
or desiccant.”
The term pest applied to a living organism ref1ect a subjective
decision on the part of human society as a whole, or some componeat
of society, that a certain organism existing in a certain manner is
undesirable or unwanted. Perhaps the classic instance oIthi human
decision is that of weeds which are defined as plants out of place or in
an unwanted situation.
Pesticides represent all kinds of chemical configurations and
molecular arrangements, even including insect viral pathogens. The
unifying thread of all pesticides is that they possess physiological
activity against living organisms. The one exception to this statement
is the growth regulator category. These materials rather than being
toxicants or antagonists are designed to modify or change plant growth
in ways deemed desirable for certain human purposes. In a legal
sense, to protect public health, as well as.the environment, Public
Law 92-5 16 has placed plant growth regulators in the pesticide cate-
gory even though they are not used as toxicants.
This placement presents some difficulty in the analysis of pest
control and pesticide use from a theoretical biological viewpoint. By
way of solution, we have included plant growth regulators in the weed
controltaxonomies where they seem to present little practical diffi-
culty in benefit-cost analysis.
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In its broadest sense, pest control involves all manipulations of
organisms in the earth ecosystem to favor those organisms, commod-
ities, and structures valued by man. Chemical pest control, i. e.,
use of substances under the regulatory purvues of 92-516, represents
only a fraction of the available alternative techniques or systems that
may be used in pest control. From man’s first beginnings he has been
seeking better, more effecUve ways of accomplishing these alterations
in organismal ascendency.
2.2 Pest Control Alternatives
It appeared essential to the contractor that one of the first tasks
to be accomplished prior to initiation of any benefit-cost procedures
was to create biologically sound taxonomies of pest control alternatives
so that the consequences of a registration denial or cancellation could
reflect, as closely as possible, the expected results from non-use of
the pesticide in question. These should be all-encompassing frame-
works that would maintain their integrity well into the future and could
be modified through additions if needed but hopefully would not need
such modification.
Nature and natural systems represent a continuum. Man con-
stantly categorizes and classifies nature with partitions and boxes.
The sciences and technologies of pest control involve numerous aca-
demic disciplines and departments. Traditionally, these have been
separate entities with little interchange. Thus, insect control, plant
disease control, and weed control investigations have proceeded largely
along separate lines. Substantial gaps in knowledge have existed at the
interfaces of these traditional investigation areas. Indeed, in some
instances the investigations have resulted in pest control systems with
paradoxical effects when the individual procedures and practices are
brought together on a single crop, animal, or commodity.
For benefit-cost procedures to be a truly effective means of
viewing pest control alternatives, such procedures must be grounded
in the best possible theoretical framework that will allow analysis of
pesticide benefits and costs in the continuum of natural systems.
Excerpted from nature, such procedures will accomplish nothing and
may be worse than intuitive judgment in mediating pesticide registra-
tion decisions.
2. 2
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For example, pesticide control of a given insect may result in a
20 percent yield increase for the crop in question. However, control
of the insect may allow a weed host previously insect-suppressed to
compete with the crop and reduce the crop yield by 30 percent. Appli-
cation ofa herbicide to control the weed results in complete weed con-
trol but reduces the crop yield by 10 percent through phytotoxicity, as
well.as predisposi.ng it to a plant pathogen that results in a 30 percent
yield decrease unless sprayed with a fungicide for its control which
will again result in optimum yield. Such examples, although seemingly
rare, may well be all too common if pest control alternatives are not
comprehensively examined in detail. Benefit-cost analysis, if not
equally comprehensive in all respects, will also result in distortions
and inaccuracies. Extended research is necessary to gain insights of
this nature. Therefore, these insights may only be possible for rereg-
istration decisions, unless information is already available for new
registrations as well.
In order to provide a biologically sound framework for this anal-
ysis technique, a taxonomy of commonly recognized pests and taxon-
ornies of pest control alternatives for the four major categories of
pests are synthesized (see Appendix A). These are:
Plant pathogens: those organisms that form a con-
tinuing relationship with plants resulting in adverse
effects termed disease.
Weeds: plants that compete with desired species
for water, nutrients, and other environmental com-
ponents, as well as occupy space on waters and
lands deemed essential for other uses.
Insect and other arthropods: that feed upon, antag-
onize, or deform plants, animals, man, commod-
ities or structures.
Vertebrates: that feed upon, or antagonize man and
his plants, animals, and possessions.
Information used in creation of these taxonomies was obtained from
numerous publications and texts, the more useful of which are cited
in Section 2.7.
2. 3
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In viewing previous existing attempts at delineation of pest con-.
trol alternatives, two problems were apparent: (1) incompleteness
and omission of certain alternatives, and (2) overlapping, whereby a
control method could be placed in any of several categories. Com-
pleteness is believed to have been achieved and most of the errors of
omission were corrected. The problem of overlap is still unsolved
and at this stage it appears insolvable except through arbitrary decis-
ion on placement of specific methods in certain cells.
Introduction of a new pesticide in most instances (at the present
stage in evolution of agricultural technology) represents introduction
of an alternative material for a pesticide control technique already in
existence and in this sense the new introduction (i. e., registration in
a regulatory sense) may: provide for greater efficacy; provide a solu-
tion to an organismal tolerance problem on the part of pre-existing
materials; or merely broaden the spectrum of materials available for
specific uses. In a few instances, the new material may represont a
method for control of a previously insolvable pest problem and thus
represent a new technique. In a few other instances, the substance
may represent replacement of a previously existing non-chemical
technique, e.g., crop rotation, with a new chemical technique. Other
non-pesticidal reasons for introduction may be lower human and animal
toxicity or lower environmental hazard in any or all areas.
Public Law 92 -516 states in Sec. 2(C)(5) that the Administrator
shall register a pesticide if he determines that when used as intended,
it is efficacious, complies with labeling and other requirements, and
will not cause “unreasonable adverse effects on the environment.’ In
addition, in the legislative history, there appears a discussion that
comparison of one pesticide with another is a ‘ 1 natural” in economics. *
New pesticides to be registered will receive much closer scrutiny in
all probability than did many older pre—existing materials. In a prag-
matic sense, during registration, comparison of a new environmentally
safer product with an older one having significant hazard may be impos-
sible to avoid. Furthermore, in any cancellation or suspension pro-
ceedings, it would appear that availability of, and comparison with,
suitable, safer alternative materials becomes a crucial consideration,
especially with major food, feed, and fiber crops and severe pest prob-
lem s
*U. S. House of Representatives Report No. 92-511, Ninety-
second Congress, First Session, 1971, p. 14.
2. 4
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Hence the benefit-cost analysis must provide a basis for com-
parison of the pesticide under evaluation with other existing pesticides
and other means of control so that a meaningful estimate of the net
contribution -- i c., incremental benefit -- of the pesticide registra-
tion under consideration will be insured.
2.3 Benefits and Costs from Pest Control
Pesticides are used in numerous and diverse ways and for dif-
ferent purposes, often having little natural relationships to each other.
It readily became evident that a single benefit-cost matrix could not
provide a basis for analysis of all uses. Hence, to provide a theoret-
ically sound basis, pesticide usage was divided into five categories
that seem to account for all possible uses or purpose of uses, and yet
each are similar enough to allow one analysis procedure for each cate-
gory. These are as follows:
• Pesticide use in food, feed, and fiber production :
to include such items as crop production, animal
production, cotton, forest products, and all other
crops and commodities including storing, proces-
sing, and consumption of these commodities.
• Pesticide use in health/disease vector and nuisance
pest control : to include such items as mosquito
abatement, household pests, rabies vectors, ants
in lawns, caterpillars in a resort community.
• Pesticide use in commercial-industrial situations :
to include utility and highway rights-of-way, oil
tank farms and industrial sites, factory buildings,
structural pests in wood, in commercial and home
situations.
• Pesticide use in providing aesthetic improvement :
to include shade trees, turfgrass, golf courses,
home lawns and flowers and all vegetation where
appearance is the criterion of quality measurement
such as a resort landscape.
2. 5
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Pesticide use in providing environmental manage-
ment : to include fishery resource regulation (i.e.,
lamprey eel), forest pests where ecosystem balance
is deemed essential, and all other uses where envi—
ronmental quality and ecological considerations are
the overriding basis for pesticide use.
Within each of these categories, taxonomies of entities receiving
benefits and incurring costs were created from a biological-social
science basis (see Appendix B). It is recognized that in each of these
taxonomies, the approach is not on an economic basis. This is done
in Chapter 3.0 in the creation of the matrices. Obviously, as created,
the taxonomies list as many as possible of the individual entities
involved in incurring costs or receiving benefits, recognizing that in
may instances, the benefits or costs transfer through, accruing at
various points within the taxonomy.
2. 4 Measuring Benefits and Costs
One major problem i benefit-cost analysis with pesticides is
the diversity of benefits and costs, especially with regard to external-
ities. Many of these are almost intangible in the sense that they rep-
resent feelings about future problems such as genetic damage, muta-
tions, and ecosystem disruption, yet in the short run they may repre-
sent bases for pesticide cancellation or non-registration. Many exter-
nalities are non-quantifiable even though of a tangible nature, often
because of the absence of any data or lack of reliable data. This is
especially true in the realm of environmental effects. Taken as a
whole, there is a tremendous mass of information dealing with envi-
ronrnental damage. Most is only descriptive.
For example, the Mrak Commission report (Parts I and II, HEW,
December, 1969) cites numerous studies of potential environmental
injury from pesticides, generally in terms of the kinds of physiologic
upset induced by given levels of pesticides under laboratory conditions.
Ext rapolation of such data to the natural situation becomes extremely
difficult, if not impossible, without confirmatory data that measures
ambient pesticide levels, as well as sampling for injury in nature. In
most instances, the kind of data simply does not exist that would aliow
one to say, for example, that DDT when used in New Brunswick for
spruce budworm control resulted in an X.percentage reduction in
2. 6
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salmon reproduction and a Y percentage reduction in trout. These
problems are recognized by most competent scientists working in the
pesticide environment area, and world-wide experimentation is under
way to quantify environmental effects where possible.
Perhaps an equally serious problem from the biological point of
view is the lack of knowledge concerning internal benefits from certain
kinds of pesticide use. Pesticide evaluation in terms of efficacy has
traditionally been carried out in replicated small plot areas for plants
and with small pens or cages for animals. Where non-mobile weeds
or 8011-borne insects and plant pathogens have been involved, the
small plot yield response benefits from pest reduction may be repre-.
sentative of actual field situations. For example, the yield responses
from replicated herbicide plots in a weedy corn field are likely to be
indicative of the yield response from the whole field or other commer-
cial fields of similar species and degree of weediness. This would be
especially true if the experimentation were carried out utilizing the
best possible experimental designs and statistical analysis procedures.
Such research and data obtained are relatively straightforward and
provide an excellent measure of one type of internal pesticide benefit
from the herbicide use in question.
In general, chemical weed control represents the most straight-
forward situation in pesticide use. Herbicides and growth regulators
are used against non-mobile target organisms. The universality of
their occurrence allows experimentation to occur on portions of com-
mercial fields with extrapolation to commercial results being readily
possible, as well as being reasonably valid.
The situation with mobile plant pathogens and insects is not
nearly as clear cut. Crop, commodity, and animal loss assessment
is a severely neglected branch of most of the pest-related academic
disciplines. The academic reward structure has not provided incen-
tives for research in these areas. As a result, much of the informa-
tion available represents estimates of the crudest sort with very little
or no statistical basis.
This situation is belatedly being corrected. Current Smithsonian
Science Information Exchange (SSIE) research project listings indicate
that many new agricultural research projects have been initiated within
the last year to determine economic thresholds for insect and weed
infestations and disease outbreaks. in addition, research is under
way involving pest loss appraisal techniques. The best information
2. 7
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currently available woridwise has been compiled in the Food and Agri-
culture Organization of the United Nations (FAO/UN) Manual, “Crop
Loss Assessment Methods -- Pests, Diseases and Weeds. “* This
manual is updated through supplements issued periodically. These
methods, developed by competent researchers throughout the world,
deal with single problems, i. e., one insect, or one disease, and are
very useful within these constraints. The interpretive problems arise
when several insects, weeds or diseases of various genera occur
simultaneously on the same crop plant or animal. As mentioned pre-
viously, essentially no information exists for these complex situations.
However, this problem is being recognized and hopefully research will
soon be underway in various locations.
A more serious problem in pest control benefit and cost appraisal
is the cryptic or representational error present in field experiments
with mobile pests or pathogens. This has been recognized by a few
researchers but has been documented most prominently by V n der
Plank in his text, Plant Diseases: Epidemics and Control . *
A brief consideration of this problem is essential since much of
the experimentation in use today in pesticide efficacy evaluation con-
tains this interpretive error. Most pesticide field exper ments consist
of small plots treated with various chemical configurations and inchde
numbers of untreated check plots. The various treatments are com-
pared with each other, as well as with the untreated check plots. In
agricultural research, the individual plots are taken to represent
farmers’ fields or orchards and results obtained from the plots are
interpreted to bear a close relationship to what would take place under
commercial conditions of use.
Various experimental designs and statistical procedures are
normally employed to deal with the plot-to-plot variation and experi-
mental error. It is an accepted principle of field plot research that
test plots must not interfere with each other; thus, the intensity of
pest development in one plot should not influence pest development in
*Available from the Commonwealth Agricultural Bureau, Central
Sates Branch, Farnham House, Farnhaxn Royal, Slough SLZ 3BN,
England.
**Van der Plank, J. C., Plant Diseases: Epidemics and Control ,
New York, Academic Press, 1963.
2. 8
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an adjacent plot, either upward or downward. In fertilizer experi-
ments, one or two guard rows are normally left between plots and this
suffices to prevent fertilizer overlap and interference between treat-
ment plots. In weed control plots with a pre-existing weed population
and no in-season movement of seeds, this is also the case. However,
when plots are established for control of insects or mobile air-borne
plant pathogens, a few guard rows are meaningless and .he unsprayed
or untreated check plots may remain a season-long source of inoculum
and spread for heavy contamination of the treatment plots. In this
instance, the pesticide has a much harder task of pest suppression
than in a farmer’s field; hence, with protectant materials, the experi-
mental or test pesticides are usually not as effective on a unit weight
or volume basis as they would be under commercial conditions.
In past years where the insurance concept of pesticide use was
prevalent and the general objective was to subject the material to the
most severe conditions conceivable, such an approach might have been
justifiable. However, at the present state of pesticide science and
technology, this approach may result in two serious problems:
- Chemical dosage programs developed on the basis
of such tests will result in overuse of chemicals
at much higher than necessary rates, as well as
shorter treatment intervals. This may be one of
the reasons why “pest management” programs
with reduced dosages have been strikingly effective.
In relation to commercial conditions, the range in
pest damage or loss between no treatment and treat-
ment may be either too great or not great enough
but seldom will there be an accurate representation
of commercial expectations. The new systemic
pesticides which provide complete absolute pest
suppression will result in a drastic difference,
especially if everything in the plots favor pest
development.
Thus, excessive pesticide benefits are calculated. On the other
band, with a protectant pesticide which provides partial suppression,
the difference will be much less than in a commercial field and the
benefits would be calculated to be less than would actually be derived
from commercial use. Neither error in the benefit calculation can be
tolerated. A possible approach to alleviate this problem would be to
2. 9
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check and compare test data for the new pesticide with both test data
and commercial field data for a parallel pesticide. This concept is
further discussed below.
2. 5 Evaluation of a Pesticide in
Terms of Parallel Comparisons
with Similar Materials
In the registration of either a new pesticide containing new active
ingredients or a new formulation of an existing material, much can be
learned by parallel comparison of the new pesticide with existing regis-
tered materials. Existing pesticides of long standing registration expe-
rience will often have received intensive research attention in many
areas of environmental and human health concerns, particularly if
there is evidence that harm has resulted. As a result of this research
emphasis over a period of years, a record of the presence or absence
of acute or chronic problems such as human or wildlife effects, injury
to applicators, etc., will be established.
New pesticide materials of similar or related chemical configu-
ration may present similar problems. Some of these will only become
evident after long usage and research experience. From a scientific
view, comparison of parallels represents one of the most viable tech-
niques for anticipation of future problems. Such comparison may allow
registration of materials for general use when at initial review the
potential for hazard would seem to dictate that the product should be
a restricted use registration, or such comparison may allow registra-
tion of materials for restricted use when at initial review the potential
for hazard would seem to dictate that the product hould not be regis-
tered at all. The technique thus can be used both to expedite, as well
as to preclude or restrict registration.
Data and testing procedures for registration should be within
methodology guidelines that allow meaningful comparisons between
experimental results for a single chemical, as vel1 as between chem-
icals. it is recognized that effective investigation requires imagina-
tion and initiative on the part of the researcher. On the other hand,
diversity between experimental techniques and designs often precludes
any kind of comparison between experiments. Unfortunately, much of
the pesticide registrations to date have been supported by data gathered
in such diverse manners.
2. 10
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Therefore, as a first step, listings of acceptable protocols (i. e.,
procedures must be developed for as many as possible of the categories
of data needed for registration. Considering the individualism existing
among research scientists, standardized test protocols do not appear
in the realm of possibility. Perhaps even more important, the com-
plexity of evaluation requirements indicates that standardization would
not be scientifically sound in many areas of testing.
However, listing of acceptable procedures should be completed
as soon as possible by competent scientists involved in this work.
Initial efforts in this area have been started by committees (E 35)
formed within the American Society for Testing and Materials (ASTM)
framework. However, progress to date in most areas after almost
two years effort is negligible especially with regard to efficacy testing.
Through its Registration Guidelines, EPA will initiate an open-ended
specification of acceptable procedures. Much greater emphasis is
needed in this work, especially through stimulus by the EPA, as well
as the pesticide chemical industry.
If registration data are submitted through procedures and methods
included under acceptable protocol guidelines of both ASTM and EPA,
the benefit-cost procedure can proceed on a much sounder basis.
Especially pertinent to the prese it discussion is the fact that parallel
comparison of pesticides, to be most meaningful, should be based on
data generated through similar evaluation procedures.
The data required for para]lel comparison must involve all areas
of pesticide evaluation, including efficacy and human and environmental
hazard. The data requirements for registration as published in the
Federal Register of October 16, 1974, and outlined in the following
paragraphs are suggested as a basis for data needed for parallel chem-
ical comparisons and for benefit-cost analysis.
2. 5. 1 Efficacy
Evidence of product efficacy is normally demonstrated through
laboratory and/or field testing procedures which closely approach
actual use(s). The following general data are needed:
Minimum effective dosage and dosage range,
Description of application techniques, including
equipment used in application, method, timing,
and site oiapplication,
2.11
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Evaluation of the action of the product in preventing,
destroying, repelling or mitigating a pest; acceler-
ating or retarding the rate of growth or otherwise
altering the behavior of plants; defoliating plants or
artificially accelerating the drying of plant tissue,
and
Evaluation of the chemical and physical compatibil-
ities of components of formulated pesticides, includ-
ing the compatibility of mixtures of pesticides with
dilutents, emulsifiers, fertilizers, solvents,
spreaders, and stickers.
2. 5.2 General and Environmental Chemistry
The following general data are needed:
For all pesticide product uses,
Name, chemical indentity and composition of
the pesticide,
Physical and chemical properties of both active
ingredients and formulations,
Basic manufacturing process and purity of
starting and intermediate materials,
Composition and methods of analysis for the
principal component( s), including significant
impurities in the technical material,
Methods of analysis for active ingredient(s) in
the formulated product,
Storage stability of the formulated product under
a relevant range of conditions,
Data in support of safe container disposal tech-
nique s.
For outdoor terrestrial uses,
Pesticide data and movement in soil,
Rate, mechanisms, and degree of degra-
dation of the parent pesticide and its degra-
dation products,
• .• Analytical procedures for separation and
identification of degradation products,
2.12
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Characterization of bound residues,
Residue data for rotational crops.
Soil persistence data under actual use conditions,
Laboratory scale leaching data on the product
pesticide and the soil degradation products,
Laboratory scale runoff data,
Rate of hydrolysis.
For uses on or adjacent to aquatic sites,
Dissipation rate of parent pesticide and impor-
tant degradation products in distilled water,
Degradation in bottom sediments and in water
containing suspended solids,
Duration of biological activity in the aquatic
- environment,
Laboratory and/or field data on pesticide move-
ment in water and uptake by aquatic plants, organ-
isms, and crops irrigated with treated water,
Levels of residues in milk, animal tissue and
eggs, when livestock or poultry can reasonably
be expected to be exposed to and/or consume
treated water,
• Fish uptake and dissipation data,
Photodegradation data on the parent pesticide,
Rate of volatilization of the pesticide under typical
conditions of use.
2.5.3 Product Hazard
Laboratory and field studies: When data on active ingredient(s)
and formulation do not allow a satisfactory decision on product hazard,
further studies are needed for major metabolites, degradates and/or
reaction products.
Human effects,
Acute effects data including oral, dermal, irihala-
tion, and ocular exposure hazard,
Subacute, chronic, and delayed effects data includ-
ing potential mutagenic, teratogenic, oncogenic,
metabolic or other chronic effects hazards,
2.13
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Safety data including diagnostic and ; ntidotal
information, and precautions necesN ry for
reentry into treated areas.
Environmental effects,
Data on the hazard to fish and wildlife including
mammalian toxicity, acute and 8Ul)t( 1tC avian
toxicity, acute aquatic organism toXicity, and
subacute, delayed or chronic elfectH hazards.
Comparison of the foregoing types of data for . new pesticide
product with existing registrations should provide a ood basis for
selecting a parallel pesticide with similar characteristics as the new
pesticide product. This will, in turn, provide additi na1 insights about
a new pesticide, normally only available for pesticidv. 5 presently or
previously registered. It is recognized that satisfying data needF for
a new pesticide by using information about its para)Iei may produce
biased results. Nevertheless, a good basis for estiuiatjons in a bene-
fit-cost analysis can be achieved. Protocols for data presentation
should be such that the data are amenable to benefit-:ost proccd’.re
without excessive transformation.
26 Summary
Benefit-cost analysis is no better than the data available for use
as inputs into the analysis. Data without validity, rc’iiabj1jt or rele-
vance produces results that are worthless if not completely misleading.
In this chapter, taxonomies of pest control alternatives, pesticide
use categories, and benefits and costs have been created These have
a sound biological and rational basis and support creation of benefit-
cost matrices and analytical procedures.
It must be remembered, however, that the data presently avail-
able on pesticides benefits and costs are limited and subject to bias,
as well as inaccurate assumptions. The results obtained must be
viewed in this light. However, the analytic procedu s should be none-
theless valid and of even greater significance in the future as better
information becomes available to work with.
2.14
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2.7 References
1. National Academy of Sciences., Principles of Controllin
Pests and Diseases of Plants and Animals ; Vol. 1: Plant-Disease
Development and Control; Vol. 2: Weed Control; Vol. 3: Insect-Pest
Management and Control; Vol. 4: Control of Plant Parasitic Nerna-
todes; and Vol. 5: The Vertebrates that are Pests: Problems and
Control.
2. Baker, K. F., and W. C. Snyder, Ecology of Soil-Borne
Plant Pathogens: Prelude to Biological Control , Berkeley, California,
University of California Press, 1965.
3. Christie, J. R., Plant Nernotodes, Their Bionomics and
Control , Jacksonville, H. & W. B. Drew Company, 1959.
4. Sasser, J. N., and W. R. Jenkins (eds.), Nematology ,
Chapel Hill, University of North Carolina Press, 1969.
5. Large, E. C. , “Measuring Plant Disease,” Annual Revie-x ’
of Phytopathology , Vol. 4, p. 9.
6. Torgeson, D. C. (ed.), Fungicides, Vol. 1 , New York,
Academic Press, 1967.
7. Anonymous, Scientific Aspects of Pest Control , Washington,
D.C, National Academy of Science, 1966.
8. Walker, J. C., Plant Pathology , 2nd edition, New York,
McGraw-Hill Book Company, Inc., 1957.
9. }larsfall, 3. C., and A. E. Dirnond, Plant Pathology: An
Advanced Treatise, Vol. III , New York, Academic Press, 1960.
10. Van der Plank, 3. G., Plant Diseases: Epidemics and
Control , New York, Academic Press, 1963.
11. Chant, D. A., “Strategy and Tactics of Insect Control,
Canadian Entomologist , Vol. 96, 1964, pp. 167-182.
12. Smaliman, B. N., “Perspectives of Insect Control,”
Canadian Entomologist , Vol. 96, 1964, p. 182.
2. 15
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13. Van den Bosch, R., and V. M. Stern, “The Integration of
Chemical and Biological Control of Orthropod Pests,” Annual Review
of Entomology , Vol. 7, 1962, p. 367.
14. Beck, S. ID ,,, “Resistance of Plants to Insects,” Annual
Review of Entomology , Vol. 10, 1965, p. 207.
15. DeBach, P. (ed.), Biological Control of Insect Pests and
Weeds , London, Chapman and Hall Ltd., 1964.
16. Brown, R. Z., Biological Factors in Domestic Rodent
Control , Atlanta, U. S. Department of Health, Education and l Telfare,
Communicable Disease Center, 1960.
17. Gottschalk, J. S., “Animal Control: Where Do We Go
From Here?” Portland, Oregon, National Woolgrowers Association
Convention, January, 1966.
18. Goldman, E. A., “The Control of Injurious Animals,”
Science , Vol. 75, 1942, p. 309.
19. Linhart, S. B., “Rabies in Wildlife and Control Methods
in New York State,” New York Fish and Game Journal , Vol. 7, 1960,
p.1.
20. Frings, H., and M. Frings, “Pest Control with Sound,”
Sound , Vol. 2, 1963, p. 39.
21. Lewis J. H., “Planting Practice to Reduce Crop Damage
by Jack Rabbits,” Journal of Wildlife Management , Vol. 10, 1946,
p. 277.
22. Balser, D. C., “Management of Predator Populations with
Antifertility Agents,” Journal of Wildlife Management . Vol. 28, p. 352.
23. Anonymous, Restoring the Quality of Our Environment ,
Report of the Environmental Pollution Panel, President’s Science
Advisory Committee, Washington, D.C., U. S. Government Printing
Office, 1965.
2. 16
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3.0 THE ECONOMIC EVALUATION OF THE
BENEFITS AND COSTS OF PESTICIDE USE
3.1 Introduction
For theoretical clarity in the development of the biological basis
for benefit-cost assessment of pesticide use, Chapter 2. 0 has estab-
lished distinctions between five categories of pesticide use. These
distinctions are extremely useful in producing descriptions of the
effects arising from the manufacture, distribution, and application of
pesticides in each of these five use categories. However, the general
similarity of the types of effects which are sustained by each entity
which receives benefits or incurs costs across all of these categories
would make the presentation of a detailed description of the economic
evaluation of each effect in each use category superfluous.
The analysis which is developed in this chapter first demonstrates
that the total net benefit which accrues to society as a result of the
adoption of a new pesticide can be evaluated most easily if it is decom-
posed into the net internal benefit and the net external benefit which are
generated by this adoption. The net internal benefit is then theoretic-
ally proven to be equal to the sum of the change in consumers’ surplus
obtained by users of the final products which are treated with the new
pesticide, the increase in monopoly profits which are earned by the
producers and distributors of both the pestici 1e and the products which
are treated with the pesticide, and the change in economic rent realized
by owners of fixed inputs throughout the nation. However, practical
consideration of the quantification problems and the relative empirical
significance of these component benefits and costs leads to the conclu-
sion that this net internal benefit shouldbe estimated solely as the
change in consumers’ surplus attributable to the adoption of the new
pesticide.
In a similar manner, the analysis next establishes theoretically
that the net external benefit is equal to the net total of the health arid
e ivironmental costs and benefits which accrue to households and public
agencies and the monitoring and regulating costs which are borne by
public agencies. Suggested techniques for estimating the magnitudes
of these individual benefits and costs are then described.
3. 1
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Finally, a specification, in matrix form of the relationship of
these economic evaluations to the five pesticide use categories is pre-
sented.
3.2 Evaluation of Benefits and Costs
In describing techniques for the measurement of benefits and
costs, it is convenient to distinguish between net internal benefits and
net externa 1 benefits. Net internal benefits are the net total of benefits
and costs which are incurred voluntarily by decision-making entities
and whose values are determined through prices and markets; while
net external benefits are the net total of benefits and costs which accrue
involuntarily to members of society other than the decision-making
entity and whose values are not reflected in the price of the product.
Obviously, these net benefits may be positive or negative. To calcu-
late these net benefit measures correctly, caution must be exercised
to eliminate any pecuniary effects which might be present in the mdi-
vidual benefit and cost measures prior to aggregating these individual
measures.
3.2. 1 Net Internal Benefits
To estimate the net internal benefits attributable to a new pesti-
cide, it is necessary to consider both the competitive situation in the
industry which will use the pesticide and the role to be performed by
the new pesticide. For example, for a pesticide used in food, feed,
and fiber production, the role could be (1) a new use which increases
yield and thus reduces cost per unit; (2) a new use which increases the
quality if the product and thus increases price per unit; or (3) a new
use which replaces other, more expensive, factors of production
(including the replacement of an existing pesticide with a less costly
one) and, thus, reduces cost per unit. Of course, a new pesticide
might perform a combination of these roles. It might be a cheaper
replacement for an existing pesticide and produce a higher yi 1d than
could be obtained with that pesticide. In this case, care must be taken
to include all benefits and costs associated with each role.
Since more definitive conclusions about the measurement of net
internal benefit can be derived for the use of a new pesticide by a per-
fectly competitive industry than for its use by an oligopolistic industry,
the perfectly competitive case will be discussed first. Moreover, this
3.2
-------
discussion will begin with the consideratIon of a pesticide which per-
forms a cost-reducing role.
3.2. 1. 1 Perfectly Competitive Industry:
Cost-Reducing Use
Producers in a perfectly competitive industry cannot retain for
very long any increased profit arising from the use of a new pesticide
which reduces cost per unit of output. Industry supply will increase
in response to this new profit opportunity and market price will fall
until pure profit returns to zero. Thus, in this situation, the net
internal benefit of using a new pesticide can be determined b , mea-
suring the change in consumers’ surplus (i. e., the change in the value
received by consumers in excess of the amount which they have paid
for the final product). This conclusion is demonstrated in Exhibit 3.1,.
where the behavior of a representative firm in the industry is illus-
trated in the diagram on the left, while the behavior of the indust:y as
a whole is illustrated in the diagram on the right. The representative
firm is initially at long-run equilibrium, where it produces the quan-
tity F1 and sells this output at the price P 1 . Simultaneously, demand
for the product of the industry is D and the supply function of the incus-
try -- the horizontal summation of the marginal cost curves (the MC l ’s)
of all firma inthe industry-- is S 1 .
Now, a new pesticide which reduces the cost per unit of output is
introduced. The average cost curve declines from ACi to AC 2 and the
marginal cost curve shifts from MC 1 to MG 2 . The first users of the
pesticide will increase production to Q’F’Z and initially will earn a profit
of(Pi - C ) per unit of output. However, as all firms in the industry
adopt the new pesticide, the industry supply function will increase to
52 and the market price will fall to P2. Thus, the representative firm
returns to the zero-profit position where it produces QF2 units of out-
put and each unit of production receives its “normal” rate of return.
The preceding analysis represents the simplest possible case
and, hence, innumerable extensions of this analysis could be developed.
However, the vast majority of these extensions would, have only minor
implications for the estimation of the net internal benefits attributable
to a new pesticide. Consequently, only three of these extensions which
are particularly important for this estimation will be developed here.
3. 3
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EXHIBIT 3.1
Price
P 1
P 2
MC 1
AC 1
I I
I I
t I
•1
D
/1 MC 2
Si
P 1
S 2
AC 2
F1
QIl Q 12
-------
First, not all firms in a perfectly competitive industry have
identical cost functions. Thus, the availability of a new pesticide will
offer different initial profit opportunities to different firms within the
industry. Nevertheless, there is a tendency for the minimum average
cost of all firms in the industry to converge as time passes. Less
efficient firms are forced to become more efficient or to go out of
business; while firms with more efficient resources (e. g., better land)
find that the prices of these resources are bid up until there is no com-
petitive advantage to using these resources instead of the best alterna-
tive resources.
Second, the preceding analysis also ignores processing and dis-
tribution costs. That is, the demand and supply curves employed in
this analysis are the curves which prevail in the market where the
producer sells his product; while the change in consumers’ surplus
which must be measured is the change in consumers’ surplus which
prevails in the market for the final product. Yet, the processing and
distribution costs per unit of output should not change merely as a
result of the introduction and use of the new pesticide. Therefore,
supply, demand, and price in the retail market can be represented by
shifting all points in Exhibit 3. 1 upward by the amount of processing
and distribution costs. This adjustment has no effect upon the mea-
sured value of the change in consumers’ surplus. However, an excep-
tion to this conclusion will arise if the. use of a pesticide at the farm
level produces contamination or health costs which are borne by the
processor or distributor. These costs will reduce consumers’ sur-
plus and will be treated later in this chapter.
The third extension of the preceding analysis involves the case
where only a portion of the producers of a particular product can bene-
fit from a new pesticide. For example, suppose that a new herbicide
increases cotton yields in the Delta but produces no benefit in Western
production areas. The introduction and use of this herbicide will have
a depressing effect upon the price of cotton. Moreover, this price
decrease initially will be associated with the earning of pure economic
profits in the Delta and the incurring of economic losses in the Western
eas. However, these profits and losses should be rapidly capitalized
into fixed input values. Thus, it is expected that Western producers
will incur capital losses (i. e., reduced land prices) while Delta
farmers will enjoy capital gains. Similarly, cotton production will
fall in the West and increase in the Delta.
3. 5
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Ideally, the net total of all changes in the values of fixed inputs
which are generated by the adoption of a new pesticide -- the net change
in economic rent in the nation arising from the use of that pesticide --
should be calculated and included as a component of the net internal
benefit attributable to the introduction and use of the pesticide. Unfor-
tunately, the precise ampunt of change in production and economic rent
will depend upon the relative profitability of the alternative uses of
those fixed inputs whose values in their present uses have decreased
and, hence, cannot be estimated without a fairly detailed model
describing the interrelationships in the entire agricultural economy.
Consequently, the empirical difficulties associated with the measure-
ment of the changes in economic rent throughout the n-ttion precludes
the inclusion of this component of net internal benefit into the benefit-
cost methodology. Perhaps the best that can be done is to hope that
these effects are at least partially offsettLg from the aggregate stand-
point. Nevertheless, some attempt should be made to identify the rela-
tive impact of the introduction and ure of a new pesticide. Will one
area gain relative to another? Will producers of one size gain relative
to other producers? Will users of one method of production gain rela-
tive to producers using an alternative method?
Despite all of these qualifications, the primary conclusion
remains that the measurement of the net internal benefits of the use of
a new cost-reducing pesticide in a perfectly competitive industry must
begin with the measurement of the increase in consumers’ surplus gen-
erated by this innovation. The gain in consumers’ surplus is repre-
sented in Exhibit 3. 1 by the area P 2 P 1 ab. To measure this area most
easily, it is desirable to divide this total area into two components:
the rectangular area PZPIac and the triangular area abc. Then, the
rectangular area can be measured as the product of the change in prke
caused by the adoption of the new pe sticide and the initial equilibrium
output level; the triangular area can be approximated by one-half of the
product of this change in price and the change in output associated with
this price change; and the total change in consumerst surplus can be
estimated as the sum of these two components. Detailed techniques
for calculating the change in price and the change in output attributable
to the adoption of a new pesticide are developed in Chapter 4. 0.
With the exception of the monopoly profits obtained by the pro-
ducer of the pesticide as a result of his patent, this measurement of
consumers’ surplus will capture the net effect of all internal benefits
and costs which arise from the use of the new pesticide. This con-
sumers’ surplus is derived from the reduced price of the product and
3.6
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constitutes a net gain after the subtraction of all internal costs, includ-
ing:
The cost of the pesticide to the producer of the final
product. If the decision of the pesticide rnanufac-
turer to produce this pesticide is economically
rational, this cost must include:
The cost of management, labor, capital, and
materials used in producing and marketing the
pesticide, and
The proportion of the total contamination, envi-
ronmental, and health costs which are borne by
the manufacturer.
• The cost of application of the pesticide, including:
The cost of management, labor, capital, and
materials (other than the pesticide) used in
application, and
The portion of the total contamination, envi-
ronmental, and health costs which are borne
by the applicator.
• The net long-run gain (equals zero in perfect compe-
tition) to producers of the final product. This gain
will include:
Changes in the costs of management, labor,
capital, and materials used in production, and
The proportion of the total contamination, envi-
ronmental, and health costs which are borne by
the producer.
The contamination, environmental, and health costs
which are borne by firms further down the processor-
distributor chain.
3. 7
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It is important to recognize that ideally the internal costs whiéh
are incorporated into the measurement of the change in consumers’
Surplus which is attributable to the use of a new pesticide should not
include the costs associated with the research and development of that
pesticide. By the time that a manufacturer submits an application for
the registration of a pesticide to the EPA, all of these research and
development costs already have been incurred. More importantly, it
is impossible at this time for the manufacturer to avoid incurring or
to recover these costs by selling or diverting to other uses those
resources whose utilization generated these costs. Therefore, since
these costs must be incurred by the manufacturer -- and by society --
regardless of the outcome of the registration decision, the inclusion
of these costs in the calculations which determine the outcome of this
decision would be inappropriate and could produce an economically
inefficient allocation of resources. If the registration process refuses
to permit the marketing of a pesticide whose benefits exceed all costs
associated with the manufacture and use of that pesticide except its
research and development costs, society would be denied a net benefit
equal to the difference between the benefits of the pesticide and its non-
research and development costs. Moreover, this net benefit could be
used to partially defray the unavoidable research and development costs
and, thereby, to offset to some extent the loss which has been imposed
upon the manufacturer and society for this relatively unproductive
research and development effort.
Clearly, this same rationale is applicable to any other element
of cost which has been incurred and is irrecoverable when the regis-
tration procedure is initiated. Consequently, the production cost data
which is incorporated in the benefit-cost analysis of a pesticide should
include only those cost elements which are avoidable if registration is
denied. Specifically, no data concerning the research and development
costs of creating a new pesticide should be collected unless these data
are required to eliminate this cost element from a more aggregative
set of cost data.
3.2. 1.2 Perfectly Competitive Industry:
Price-Increasing Use
A new pesticide which increases the quality of a product produced
by a perfectly competitive industry will, in the long run, cause an
increase in price equal to the increase in cost per unit which is attrib-
utable to the use of the pesticide. Early adopters of the pesticide once
again will earn a pure economic profit. However, as more producers
3.8
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adopt the pesticide, competition will, cause the price to fall until eco-
nomic profits return to zero. Thus, once again, the entire net internal
benefit is passed onto the consumers in the form of consumers’ sur-
plus, which in this case consists of the added-value of the higher qual-
ity product less the additional costs which have been required to attain
this increase in quality. This change in consumers’ surplus can be
estimated in the same manner as the change in consumers’ surplus
which is attributable to the use of a new pesticide which reduces cost
per unit of output. Moreover, all of the qualifications and assumptions
which have been expressed for a cost-reducing use apply equally well
to a price-increasing use.
3.2. 1. 3 Oligopolistic Industry
If any of the firms which are involved in the production, process-
ing, distribution, or use of either the new pesticide or products whose
production processes utilize the new pesticide are members of oligopo-
listic industries, the preceding analysis must be qualified slightly.
Since oligopolistic industries have at least some control over price,
not all of the net internal benefits will be passed on to the consumers.
The firms may be able to retain a portion of these benefits as pure eco-
norni.c profits. In addition, these net internal benefits may be slightly
smaller than they would have been if all relevant industries were per-
fectly competitive.
However, if there are at least several firms in each of these
relevant industries, these effects should be small and, hence, can be
reasonably ignored. Therefore, the net internal benefits associated
with the use of a new pesticide in an oligopolistic situation will be esti-
mated, using essentially the same techniques which have been devel-
oped for the measurement of consumers’ surplus in the perfectly com-
petitive situation. However, in the oligopolistic situation, the division
of these net internal benefits between producers and consumers will
not be determined, since the computation of the proportions of these
benefits which accrue to producers and consumers would require
detailed knowledge of the competitive structure of each relevant indus-
try.
3.2.1.4 Measurement of Net
Internal Benefits
To summarize the conclusions of the preceding analysis, the net
internal benefits attributable to the introduction and use of a new pesti-
cide have been determined to be equal to the sum of (1) the monopoly
3.9
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profits which accrue to the pesticide producer as a result of his patent,
(2) the net change in economic rent realized by owners of fixed inputs
throughout the nation, and (3) the consumers’ surplus obtained by users
in competitive industries or (3’) the consumers’ surplus obtained by
users plus the pure economic profits obtained by producers in oligopo-
listic industries. Moreover, items (3) and (3’) in this summation are
e stiinated using identical procedures.
Although the direct measurement of the four items - - to the
e ent that they can be measured - - constitutes sufficient input into
the calculation of net internal benefits for the purpose of evaluating
the aggregate economic justifiability of the introduction of a new pes-
ticide, it is frequently desirable to obtain some indication of the dis-
tribution of these aggregate net benefits among the various entities
whose individual benefits and costs comprise this sum. In particular,
one indication of these distributional effects can be obtained by evalu-
ating the following accounting equation:
NIB = MP +A ( Y . P + P • Y + 1/2. P . f -
A(Pp+Cp)-Ha Nb
where: NIB = net internal benefits,
MP = the pure economic profit received by the
producer of the pesticide as a result of his
patent,
A = number of production units (acres of land,
head of livestock, yards of cloth, etc.) to
which the new pesticide is applied,
Y = yield of the final product per unit used to
measure A,
= change in yield of the final product attrib-
utable to the use of the new pesticide,
P = price of the final product,
= change in price of the final product attrib-
utable to improved quantity and/or quality
of the product resulting from the use of the
new pesticide,
3.10
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= value per unit used to measure A of the
change in productive input requirements
resulting from the use of the new pesticide,
Pp = price of the new pesticide per unit used to
measure A (1. e., cost of the new pesticide
per acre, per head, etc.),
= cost of applying the new pesticide per unit
used to measure A,
Ha = net contamination, environmental, and
health costs borne by the user of the pesti-
cide, and
Hb = net contamination, environmental, and
health costs borne by firms further down
the producer-consumer chain than the user
of the pesticide.
Observe that the net change in economic rent in the nation, ER,
defined as the net change in the portion of total payments to resources
which does not influence the amount of those resources available for
utilization, is embodied within this accounting equation in the terms:
AERA Y’ PA FA(Pp+Cp)Ha}Tb
Consequently, it is possible to provide a graphical representation of
virtually all of the basic accounting equation within the context of
Exhibit 3.1. Specifically, the expression (A • . Y) is depicted by’
the area P Piac; the expression (A • 1/2 P Y) is described by
the area abc; the expression (A P . Y) is illustrated by the area
Q 11 Q 12 bc; the expression [ A . A F + A (P + C ) + Ha + HbJ is repre-
sented by the area 0j 1 Q 12 bd; and, hence, ER is approximated by the
area bcd. * Only the term MP cannot readily be portrayed within the
context of this exhibit.
*To be perfectly rigorous, the net change in economic rent should
be measured as that portion of the difference between areas P 2 bf and
Piae which does not constitute a pure pecuniary change in payments to
variable resources (i. e., a net change in the portion of total payments
to resources which does influence the amount of those resources
3. 11
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Finally, the procedures which can be used to estimate the values
of each of the terms within this accounting equation are:
MP - When the firm which holds the patent for the
new pesticide licenses another firm to man-
ufacture and sell the pesticide, the amount
paid by the licensee can be used to estimate
the value of the patent. Alternatively, this
value can be estimated by comparing the
rates of return to capital in the pesticide-
producing industries to rates of return in
similar manufacturing industrie s which do
not have patent protection for their products
and processes. Clearly, the implementa-
tion of either of these estimation techniques
would require extensive data acquisition
and manipulation. Moreover, the magnitudr..
of these monopoly profits are extremely
likely to be substantially smaller than the
change in consumers’ surplus attributable
to the introduction of a new pesticide.
Consequently, it is recommended that no
concentrated efforts should be devoted to
the estimation of these monopoly profits.
MP may be zero or positive.
A - Estimate the number of production units
(acres, head, etc.) which are afflicted by
relevant pests and multiply this number by
a factor which reflects the probable propor-
tion of these production units which will be
treated with the new pesticide. This pro..
portion can be estimated from past experi-
ence with similar pesticides used on similar
pests.
available for utilization). Clearly, this quantity cannot be identified
unambiguously in Exhibit 3. 1, although it can be reasonably represented
by the area bcd. For a thorough economic analysis of this issue, see
either E. J. Mishan, “What Is Producer’s Surplus,” American Eco-
nomic Review , Vol. 58, December, 1968, pp. 1269-1282 or E. J.
Misban, Cost-Benefit Analysis , Praeger Publishers, Inc., New York,
1971, pp. 48-56.
3. 12
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Y - Obtain yield estimates from published sta-
tistics.
- Obtain estimates of the change in yield from
experimental trials which test the effective-
ness of the new pesticide. Caution must be
exercised to guarantee that results are used
only from experimental trials in which con-
ditions are similar to those found on the
premises of potential users of the pesticide.
z Y can be positive, zero or negative.
P - Obtain price estimates from published sta-
tistics or from projections made by the
Department of Agriculture or other public
agencies.
- Estimate this change in price from quantity
and/or quality price differentials which are
observed in current markets. P can be
positive, zero or negative (1. e., use of the
new pesticide may increase, not change or
decrease the average quantity and/or qual-
ity and, hence, the average price of the
product).
— Estimate this input substitution effect from
experimental trials which test the effective-
ness of the new pesticide. These changes
in input cost include changes in capital,
labor, and material costs, in ?ddition to
cost of formerly used pesticides which
have been replaced by the new pesticide.
‘F can be zero or negative, but is unlikely
to be positive.
Pp - Estimates of the cost of the new pesticide
must be obtained from the pesticide manu-
facturer. This cost is the product of the
rnanufacturerts proposed selling price at
the retail level and the recommended appli-
cation rate per unit used to measure A.
3. 13
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- Estimate application costs using published
data on charges for custom applic tion. It
is important to recognize that these charges
will simultaneously measure the contamina-
tion, environmental, and health costs which
are associated with application to the extent
that these charges are sufficiently high to
compensate for insurance premiums and
lost time attributable to pesticide-induced
iine s s.
Ha - These contamination, environmental, and
health costs include the cost of additional
liability and health insurance, production
losses caused by illnesses attributable to
the new pesticide, medical bills paid by the
user, and output destroyed by contamination.
Quantities of probable losses can be esti-
mated from published studies of losses
attributable to similar pesticides. Ha can
be negative, zero or positive. A negative
Ha would be obtained if the new pesticide
replaces one which has greater contamina-
tion, environmental, and health costs to the
user,
- These costs can be measured in the same
manner as Ha.
3.2.1.5 The Desirability of Marginal
Production Cost Data
The attainment of economic efficiency requires that the marginal
benefit obtained by society from the use of a pesticide must be equated
to the marginal cost incurred by society from the use of that pesticide.
However, since the registration process makes a separate decision on
the introduction and use of each individual formulation which contains
a particular active’ingredient rather than making a single decision on
the introduction and use of the active ingredient itself, the satisfaction
of this economic efficiency condition may be difficult to guarantee
through the registration process. For example, if a new formulation
containing a particular active ingredient is proposed for registration
and if the approval of this registration will result in an increase in the
3.14
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total quantity of this active ingredient which is introduced into the envi-
ronment (i.e., if this new formulation does not merely displace an
equivalent amount of presently registered formulations which contain
this active ingredient), the marginal cost incurred by society from the
use of this active ingredient will increase. If the utilization of this
active ingredient has been economically efficient prior to the proposal
for registration of the new formulation, the attainment of economic
efficiency subsequent to the approval of this proposal will require not
only that the marginal benefit obtained by society from the use of this
new formulation must be equated to this new level of marginal social
cost, but also that the marginal benefit obtained by society from the
use of each presently registered formulation which contains this active
ingredient must be increased until it becomes equal to this new level
of marginal social cost. Thus, in general, the utilization rate of each
presently registered formulation must be reduced until this new effi-
ciency condition is attained.
The specification of the precise nature of this adjustment requires
the simultaneous consideration of the registration of all formulations
which contain a particular active ingredient. Thus, whenever a new
formulation which contains a particular active ingredient is proposed
for registration, the registration bf all presently registered formula-
tions which contain this active ingredient must be reconsider d. Yet,
while this requirement is deceptively simple to express as a concept,
it clearly is very likely to be extremely difficult to satisfy in practice.
The quantity of information which must be accumulated and analyzed is
prodigious. Moreover, even if this analysis were to be performed, the
existing Federal legislation does not grant to the EPA sufficient author-
ity to enforce the implementation of the policies which would be recom-
mended on the basis of the analysis. Although this legislation author-
izes the promulgation of regulations which specify the application rate
and the pre-harvest application interval of a formulation, it does not
permit the regulation of the total quantity of the formulation which is
applied or, equivalently, the total acreage upon which the formulation
may be applied. Consequently, in terms of the applicability of the
analysis, the simultaneous consideration of all formulations which
contain a particular active ingredient would be an unproductive exer-
cise, since the results of this extensive analysis would be impossible
to implement in detail. Therefore, recognizing both the difficulty of
performing this extended analysis a id the limited possibility of imple-
menting the results of this analysis, it appears reasonable to restrict
the benefit-cost methodology to the evaluation of each individual form-
ulation independently and, subsequently, to compare the independently
derived evaluations of all alternative formulations which can be applied
to the same use to determine the optimal registration pattern.
3. 15
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Nevertheless, within each of these independently derived evalua-
tions, it remains desirable to obtain and utilize data which reflects the
marginal cost of producing the formulation which is being evaluated.
Unfortunately, the published data on pesticide manufacturing costs do
not provide this degree of detail; the potential usefulness of information
of this type as a basis for industry price fixing or output rationing has
motivated the Antitrust Division of the Justice Department to enjoin
industry trade associations from assembling and distributing these
data; and the competitive structure of the pesticide industry makes it
extremely unwise for any pesticide manufacturer or formulator to
divulge this information voluntarily to anyone external to his firm.
Thus, in performing the case studies, ‘it undoubtedly will be necessary
to rely on average production cost data as inputs into the benefit-cost
methodology. Once again, ideally, these average cost data will reflect
production costs net of the cost of research and development and all
other cost elements which have been incurred and are irrecoverable
when the registration process iS utilized.
Utilizing these average cost data as if they were marginal cost
data within the benefit-cost methodology is tantamount to assuming that
the pesticide industry is a constant-cost industry - - that the average
cost curve of the industry is a horizont l line instead of a U-shaped
curve. However, this assumption is not inconsistent with the empir-
ical results derived in numerous statistical studies of production costs
for relatively high Levels of output* and, hence, does not appear to be
unreasonable in the present context.
3.2. 2 Net External Benefits
Many of the costs and benefits attributable to the use of a new
pesticide will not be reflected in the costs incur red by firms and the
prices prevailing in markets. These external costs and benefits
include the health and environmental benefits and costs which accrue
to households and public agencies and the monitoring and regulating
costs which are borne by public agencies. Extreme caution must be
exercised to avoid double-counting when estimating the value of these
external effects. To illustrate the potential severity of this problem,
two examples will be discussed.
*See, for example, 3. Johnston, Statistical Cost Analysis , New
York, McGraw-Hill Book Company, 1960.
3.16
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First, consider a case in which a pesticide manufacturer has an
accidental spill of his pesticide which kills fish in a stream. A gov-
ernment agency replaces these fish and the manufacturer is required
by the courts to reimburse the agency. Since the manufacturer has
made this payment, this cost is an internal cost which will be reflected
in the price which is charged for the pesticide. Thus, it is inappro-
priate to include the cost as an environmental cost which is borne by
a public agency.
Similarly, consider a migrant worker who becomes ill as a
result of long-term exposure to pesticides. He is unable to work,
becomes eligible for public assistance, and has his medical bills paid
by a public agency. The health costs which are borne by the public
agency include the medical bills plus his support payments. In addi-
tion, there is an income loss which is borne by the household of the
disabled worker. However, this income loss is not equal to the wages
that the worker has lost. Rather, the income loss is equal to the dif-
ference between these lost wages and the support payments. To include
both the total lost wages and the support payments as health costs would
constitute double-counting.
Recognizing this potential for errors of measurement, approaches
to the evaluation of the external benefits and costs which are attribut-
able to the production and use of a new pesticide are discussed in the
remainder of this section.
3.2.2.1 Health Benefits and Costs
Accruing to Households
The incidence of adverse health effects can be estimated from
experiences with similar pesticides in the past. The total health cost
borne by households is equal to the sum of medical costs, lost earnings
due to illness or death, and damages for pain and suffering, which
might be estimated by studying court awards in appropriate cases.
Positive health effects could result from a reduction in the adverse
effects of competitive pesticides which are replaced by the new pesti-
cide. The same techniques which have been proposed to measure
health costs can be employed to measure these health effects. These
techniques will be described in greater detail later in this report.
3. 17
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3.2.2.2 Health Benefits and Costs
Accruing to Public Agencies
The health costs which are borne by public agencies primarily
consist of the costs of the public assistance which is provided to sick
and disabled workers and their families. The incidence of adverse
health effects can be estimated from experiences with similar pesti-
cides in the past; while the costs of public assistance can be estimated
from the budgets of relevant public agencies. Furthermore, adverse
health effects to public agency employees applying pesticides must be
included to the extent they are borne by the public agencies.
In addition to these direct costs, the health costs which are borne
by public agencies should include any incremental expenditures on
research into pesticide-related illnesses which are attributable to the
registration and use of the new pesticide. However, these research
costs may be extremely difficult to estimate with any reasonable degree
of accuracy and may have to be ignored. Any health benefits which are
obtained by public agencies will result from a reduction in the adverse
health effects of competitive pesticides which are replaced by the new
pesticide and can be measured in the same manner as health costs will
be estimated.
3. 2. 2. 3 Environmental Benefits and Costs
Accruing to Households
The most likely form of environmental damage which might be
associated with the use of a new pesticide is damage to non-target
species. The incidence of these damages can be estimated from expe-
riences with similar pesticides in the past. These damages can con-
stitute economic losses, aesthetic losses, or both. Economic losses
can be evaluated, using market prices or replacement costs. Revers-
ible aesthetic losses can be evaluated as the cost of restoration or
replacement. Finally, irreversible aesthetic losses can be partially
evaluated by reference to studies which impute from people’ s observed
behavior the minimum amount of income which they would have been
willing to surrender to enjoy particular aestheticexperiences. How-
ever, to completely evaluate these irreversible aesthetic losses, it is
necessary to determine the maximum amount of income which people
would be willing to surrender to enjoy these aesthetic experiences.
3. 18
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Consequently, the available imputation techniques fail to mea-
sure a substantial portion (i. e., the difference between the maximum
and minimum amounts of income) of the consumers’ surplus obtained
from these aesthetic experiences. Moreover, because an individual’s
honest revelation of the maximum amount of income that he would be
willing to pay for a good or service can be used as a basis for charging
him for his consumption of that good or service, it is theoretically
impossible to obtain accurate estimates of irreversible aesthetic
losses using direct surveying techniques. Thus, if the available impu-
tation techniques are determined to be inadequate, it probably will be
necessary to rely on the Delphi approach to estimate irreversible aes-
thetic losses.
• Environmental benefits will arise from the use of a new pesticide
through the reduction of the environmental costs which are attributable
to alternative pesticides. These benefits can be evaluated by utilizing
the same techniques which have been described for the measurerrent
of environmental costs.
3. 2. 2. 4 Environmental Benefits and Costs
Accruing to Public Agencies
The environmental costs which are borne by public ager ies con-
sist of the costs which have been incurred by the public sector to cor-
rect the environmental damages which result from the use of the new
pesticide. The incidence of these damages can be estimated from past
experiences with similar pesticides; w. ,the cQsts of correction of
these damages ca ”n be estimated frofntbé budgets of relevant public
-agencies. Similarly, any environrnentalbenefits which are produced’
by the reduced a e of alte at $esttçide ..cán be estimated in this
same manner.
3. 2. 2. 5 Regulatory Benefits and Costs
Accruing to Public Agencies
The regulatory costs which are borne by public agencies include
all costs associated with the registration or cancellation of the new
pesticide which are expected to be incurred after the initial decision
to register the pesticide as been taken; the costs of monitoring the
impacts of the use of the new pesticide which are borne by the EPA
and other public agencies; any incremental governmental support for
research into the prevention, detection, control, and correction of
pesticide - related contamination, environmental, and health damages
3. 19
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which is attributable to the use of the new pesticide; and the cost of
any Incremental governmeTlt-supported re search into the effectiveness
and proper use of pesticides which is undertaken as a result of the
introduction and use of the new pesticide. To the extent that these
cost elements can be isolated, their magnitudes can be estimated from
the budgets of the relevant public agencies.
However, the two cost elements which are related to govern-
mental support for research may be extremely difficult to isolate with
any reasonable degree of accuracy and may have o be ignored. Any
regulatory benefits which result from the reduced use of alternative
pesticides can be evaluated in the same manner, using the same data
sources. ‘inally, the cost of any additional monitoring of pesticide
use and damage which might be performed by private individuals or
agencies can be imputed from the cost experiences of the public agen-
cies.
3.2. 3 The Treatment of the Displacement
of Competitive Pesticides
The registration and subsequent production of any new pesticide
is likely to cause a decrease in the sales of other presently registered
pesticides and, consequently, a decrease in the utilization of the inputs
which are used in the production of these other pesticides. However,
if the economy is reasonably competitive (I. e., if the prices which are
paid for these inputs reasonably reflect the opportunity cost of using
these inputs) and if the economy is reasonably near to full employment,
this displacement of inputs will comprise merely a transfer of these
inputs from utilization in the production of the other pesticides to utili-
zation in their best alternative employment opportunities. Conse-
quently, the payments to these inputs should not be considered in the
benefit-cost evaluation of the new pesticide. In fact, a consi 1eration
of these payments might lead to an inappropriate decision to refuse
registration of a socially beneficial new pesticide.
Yet, if the registration and subsequent production of the new pes-
ticide will cause a change in the nature or extent of the hazards which
are borne by society, this effect should be considered in the benefit-
cost evaluation of the new pesticide. Specifically, the results of the
benefit-cost evaluation of the new pesticide should be compared to the
results of the benefit-cost evaluation of all presently registered pesti-
cides which can be applied to any of the uses for which the new pesti-
cide is proposed and, ideally, on the basis of this comparison, decis-
ions should be taken on both the registration of the new pesticide and
the cancellation of some alternative pesticides.
3.20
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3.2.4 Discounting Future Benefits and Costs
Obviously, it is extremely unlikely that all of the benefits and costs
attributable to the adoption of a new pesticide will accrue to society at
the same point in time. Consequently, since present benefits of a par-
ticular dollar amount are more valuable than future benefits of the
same dollar amount, at least to the extent that the monetary equivalent
of the present benefits can be invested at a positive rate of return to
yield greater wealth in the future, it is necessary to discount future
benefits and costs to make them commensurable with present values.
While the need for this conversion is generally accepted, there
has been substantial controversy about the appropriate discount rate to
employ in performing this conversion. The essence of this controversy
can be appreciated by considering the two most prominent positions
which have been advocated in this debate.
On the one hand, most market-oriented economists have agreed
that the appropriate discount rate to apply to a public investment is the
opportunity cost of the resources which will be utilized in that invest-
ment as measured by the rate of return which these resources will
earn if they are employed in their best alternative private use..* How-
ever, acceptance of this proposed resolution of the controversy intro-
duces the serious practical problem of determining this rate of return.
Theoretically, the appropriate discount rate for a particular govern-
mental project consists of a weighted average of the different rates of
return which will be earned in private sectors from which the resources
toirriplernent this project will be withdrawn. Unfortunately, in prac-
tice, these private rates of return cannot be observed directly; and the
data series on corporate-profits frorh which they must be estimated are
geridrally poor.
Conversely, some economists have contended that requiring
public investments to earn rates of return which are at least equal to
the rates of return which are earned by equivalent investments in the
private sector will produce an inadequate level of public investment.
Consequently, they contend that a discount rate which is lower than the
*See, for example, William 3. Baurnol, “On the Discount Rate
for Public Expenditures, ‘ in The Analysis and Evaluation of Price
Expenditures: The PPB System, Vol.1 , Washington, U. S. Govern-
ment Printing Office, 1969, pp. 489-503.
3.21
-------
opportunity cost of capital should be applied to governmental projects. *
For this policy to be economically justifiable, it must be true that these
governmental projects produce external economies which cause their
social rate of return to exceed the prevailing private rate of return.
Although this assertion might be valid for some public projects, it
would be incorrect to assume that this deviation between social and
private rates of return would exist - - and, indeed, exist to the same
extent -- for all governmental investments. Moreover, the isolation
and evaluation of externalities of this type frequently constitutes the
primary purpose for performing a benefit-cost analysis. Thus,
assuming the existence of these externalities by employing an artifici-
ally low discount rate in a benefit-cost analysis may be essentially
equivalent to the double-counting of external benefits and inevitably
will introduce a bias into the analysis which favors the implementation
of socially undesirable public projects.
Although a complete resolution of this controversy concerni g
the appropriate social discount rate has not yet been attained, it is
clear that extreme caution should be exercised to insure the theoret-
ical validity of any benefit-cost analysis in which an artificially low
discount rate is employed to evaluate public projects. Consequently,
in general, it is recommended that the discount rate which is employed
in benefit-cost analysis should reflect the opportunity cost of the
resources which will be utilized in the project under consideration and,
hence, should constitute an estimate of the expected real pre-tax rate
of return on private investment. This recommendation is supported by
the Office of Management and Budget, which estimates “the average
rate of return on private investment, before taxes and after inflation,”
to be 10 percent and requires the use of this discount rate in the evalu-
ation of the majority of the programs and projects which it oversees. **
*See, for example, Steven A. Marglin, “The Social Rate of Dis-
count and the Optimal Rate of Investment,” Quarterly Journal of Eco-
nomics , February, 1963, pp. 95-112.
* OIfice of Management and Budget, “Discount Rates to be Used
in Evaluating Time-Distributed Costs and Benefits,” Circular No. A-94
Revised, March 27, 1972.
3.22
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3.2.5 The Economic Benefits and
Costs Associated with Each
Category of Pesticide Use
Exhibits 3.2 through 3. 6 on the following five pages relate the
economic measures of benefits and costs which have been discussed in
the present chapter to the five categories of pesticide use which have
been defined in Chapter 2. 0. Thus, these exhibits contain a specifica-
tion of the distribution of the major types of benefits and costs which
are attributable to the introduction and use of a new pesticide. This
distribution is defined with respect to both the entities which receive
benefits or incur the costs and the use category for which the applica-
tion of the pesticide is intended.
Furthermore, the benefits and costs described in the matrices
may be either quantifiable in dollar terms (i. e., representable by a
monetary value derived using actual market prices), quantifiable n
non-dollar terms (i. e., representable by, at most, an incidence rate,
a probability and/or a number of people, birds, fish, etc., receiving
benefits and/or incurring damages of a certain type), or intangible
(i.e., representable by only a qualitative statement concerning the
type and nature of benefits received and/or damages incurred by a
selected entity).
3.23
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EXIjIBIT 3.2: Pesticides Used in Food, Feed, and Fiber Production
.
Benefits
Costs
Entity Which Receives
Benefits or Incurs Costs
—
Quantifi- Quantifi-
able in labia in
Dollar fNon -Dollar
Terms ITerms Intangible
Quant fi - Quantifi-
able in able in
Dollar Non-Dollar
Terms
Terms Intang
Supplier (Manufacturer,
Distributor, Commercial
Applicator*)
Change in revenue attributable to
sale of pesticide (short-run and
long-run)
-
Change in costs of production,
distribution, etc.
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse health effects borne by
employer
Buainess/Industrial User
I I
Reduced cost of inputs for food
processors and clothing mania-
Lecturers
Increased revenues from addi-
tional sale of processed food
and clothing
Increased production costs due to
contamination of Inputs by
residuals
Portion of costs of change of
adverse health effects borne by
employer
Agriculture/Forestry User
Increased profits (attributable to
change in revenues change
in costs of inputs other than new
pesticide) caused by increased
crop yield
:
I
Change in cost of pesticides
Change in costs of application
Increased production costs due to
contamination of inputs by
residnal
Portion of costs of change of
adverse health effects borne by
employer
lioue bo1d User
•
Public Agency User
1. . I
Vaiue 6f fncreased food and -
clothing production (including
p*bveditut4 ion)
R fbcfjo of a 1 ’verse health
ef(scts (attributable to corn-
‘petitive pestkides)borne by
households
I
Change in productivity of
research performed by agri-
culture departments of
universities
Cost of increased food and
clothing production
Portion ‘of costs of change of
adverse health effects of new-
pesticides borne by households
Damage to non-target species
I
Portionof costs of change of
adverse health effects borne by
agencies
.
I
an analysis of the distribution of benefits and costs among tbese three entities Is determined to be
desirable, a separate row can be established for each type of supplier.
3 24
-------
EXHIBIT 3. 3 Pesticides Used in llealthfDisease Vector and Nuisance Pest Control
Benefits
Costs
Qua ntifi- Quantiij—
Receives able in able in
Incurs Costs Dollar Non-Dollar
Terms Terms Intangible
Quantiui- Quantifi-
able in able in
Dollar Non-Dollar
Terms Terms Intangible
Change in revenue attributable to
Commercial, sale of pesticide (short-run and
long-run)
Change in costs of production,
distribution, etc.
Increased production costs due to
contamination of inputs by
residuals
Portion of cost of change of
adverse health effects borne by
employer
I I
User Reduced cost of inputs other
than new pesticide (especially
labor)
Increased revenues from sale of
additional output
I I
Change in cost of pesticides
Change in cost of application
Increased production costs due to
contamination of inputs by
residuals
Portion of cost of change of
adverse health effects borne by
employer
I I
User Increased profits (attrihutable to
change in revenues change
in costs o inputs other than
new pesticide)
I I
Change in cost of pesticides
Change in cost of application
Increased production costs due to
contamination of inputs by
residuals
Portion of cost of change of
adverse health effects borne by
employer
—I
Value of increased output of
goods
Beneficial health effects arising
from reduction of disease
Improved aesthetic quality of
household arising from reduc-
tion of health/disease vector
I I
I I
Change in cost of pesticides
Change in cost of application
Cost of increased output of goods
Portion of costs of change of
unintended adverse health effects
borne by households
Damage to non-target species
Damage caused by misapplication
by households
I
User
I
Change in cost of pesticides
Change in cost of application
Portion of costs of change of
adverse health effects borne by
agencies
I
•II an analysis of the distribution of benefits and costs among these three estimates is determined to be
desirable, a separate row. can be established for each type of supplier.
3.25
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EXhIBIT 3. 4 Pesticides Used in Providing Aesthetic Improvement
- Benefits
Costs
Entity Which Receives
Benefits or Incurs Costs
Quantifi- Quantifi-
able in able in J
Dollar Non-.Dollatj
Terms Terms I Intangthle
Quantifi- Quantiuj-
able in able in
Dollar Non-Dollar
Terms Terms Intannible
Supplier (Manufacturer,
Distributor, Commercial
Applicators)
Change in revenue attributable to
sale of pestici lc (short-run and
long-run)
.
Change in costs of production,
distribution, etc.
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse health effects borne by
employer
Business/industrial User
I
Reduced cost of labor input due
to improved working conditions
Increased profits due to
improved public image
Increased revenues from sale
of additional output
I
I I
Change in cost of pesticides
Change in cost of application
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change pf
adverse health effects borne by
employer
I I
Agriculture/Forestry User
-
increased profits (attributable to
change in revenues from sale
of additional output and change
in cost of inputs)
I
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse healLh effects borne by
employer
I
household User
Value of increased output of
goods,
Increase in property value
attributable to aesthetic
improvements
Value of aesthetic improvements
to public
Surplus value of aesthetic
improvements to owner
I
Change in cost of pesticides
Change b-t’cost of application
Cost of increased outp it of goods
Portion of costs of change of
adverse health effects borne by
households
Damage to non-target species
Damage caused by misapplication
by households
Public Agency User
I
Incrcascd revenue of marketed
public recreation areas
Increased usageol free public
recreation areas
. 1
I I
Change in cost of pesticides
Change in cost of application
Portion of costs of change of
adverse bealth effects borne by
agencies
Change in cost of other inputs of
public recreation areas
I
*If an analysis of the distribution of benefits and costs among these three entities is determined to be
desirable, a separate ro can be established for each type of supplier.
3.26
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EXhiBiT 3. 5: Pesticides Used in Providing Environmental Management
— - Benefits
Costs
Quantifi- Quantifj
Receives able in able in
Incurs Costs Dollar Non-Dollar
Terms Terms Intangible
Quantifi— Quantifi-
able in table in
Dollar INon-D011ar
Terms lTerms Intangible
Change in revenue attributable to
Commercial sale of pesticide (short-rui and
long-run)
Change in costs of production,
distribution, etc.
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse hea]th effccts borne by
employers
I I
User Increase in revenue of private
recreation and tourism areas
Decreased production costs due
to improvement of quality of
inputs
Increased revenues from sale
of additional output
—--I—-
I
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse health effects borne by
employer
I —I-
User • Decreased production costs due
to improvement in qt ality of
inputs
increased revenue from sale of
additional output
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse health effects borne by
employer
I I
Value of increased output of
goods
Value of aesthetic improvement
of environment
Beneficial health effects due to
environmental improvement
I
Cost of increased output of goods
Portion of costs of change of
adverse health effects borne by
households
Damage to non-target species
I I
User incrcased revenue of marketed
public recreation areas
Increased usage of free public
recreation areas
I I
I
Change in cost of pesticides
Change in cost of application
Portion of costs of change of
adverse health effects borne by
agencies
Change in cost of other inputs of
public recreation areas
I
*11 an analysis of the distribution of benefits and costs among these three entities is determined to be
desirable, a scparate row can be established for each type of supplier.
3.27
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EXHIBIT 3.6: Pesticd s Used in Commercial/Industrial Situations
Entity Which Receives
Benefits or Incurs Costs
Benefits
Costs
Quantifi— Quantifi
able in able in
Dollar Non-Dollar
Terms Terms Intangible
Quantifi— Quantiii—
able in able in
Dollar Non-Dollar
Terms Terms Intangible
Supplier (Manufacturer,
Distributor, Commercial
Applicators)
.
Change in revenue attributable to
sale of pesticide (short-run and
long-run)
Change in costs of production,
distribution, etc.
•
Increased production costs due to
contamination of inputs by
residuals
Portion of cost of change of
adverse health effects borne by
employer
Buslness/iidustrlal User
I I
Increased profits (attributable to
change in revenues change
in costs of inputs othc
new pesticide)
I I
I I
Change in cost of pesticides
Change in cost of application
Increased production costs due to
contamination of inputs by
residuals
Portion of cost of change of
adverse health effects borne by
employer
I I—
I4ricuJtnre/Fore*try User
Increased profits (attributable to
change in revenues from sale
01 addiUo al output and c .angc
in cost of inputs) —
Increased production costs due to
contamination of inputs by
residuals
Portion of costs of change of
adverse health effects borne by
employer
—
Household User
I.• I
Value of increased output of
goods
Reduction of adverse health
effects (attributable to corn-
petitive pesticides) borne by
households
I I
Coat of increased output of goods
Portion of costs of change of
adverse health effects borne by
households
Damage to non-target species
Public Ageacy User
I I
I I
I I
Portion of costs of change of
adverse health effects borne by
agencies
I I
.
SM an analysis of the dictributlon of benefits and costs among these three estimates is determined to be
desirable, A separate row can b established for each type of supplier.
3.28
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3. 3 Structure of the Benefit-Cost Submodels
The preceding discussion describes the economic assumptions
and basic concepts for analyzing benefits and costs of pesticides.
These assumptions and concepts are grounded in the conventional eco-
nomics of industrial production. Thus, the pesticide process is envis-
ioned to occur in numerous firms of varying size, each of which has
its own capital/output factor and its own financial structure. Each
firm may engage in some research and new product development activ-
ities and some level of competition is ensured because of Federal anti-
trust regulations.
Each firm faces many uncertainties as it brings its pesticide
products to the market place, one of which is the Federal registration
process. Without passing this barrier, the pesticide product will not
even be allowed into the market. Once inside the market, the pesticide
product may have to compete for users’ dollars with other pesticides
for each type of use. The increased crop yield is one factor which may
help to ensure a successful competitive career for a pesticide, and the
pesticide manufacturer will strive to establish competitive prices which
will generate adequate returns for his effective products.
These prices become the costs for the agricultural or other pest
control user. The benefits of higher yield become benefits for every-
one who consumes the crop, but the costs of health and environmental
damages may impinge on some people and not on others, depending on
how these effects are engendered.
These uncertainties, including the market uncertainties for the
pesticide producer and the social and environmental cost uncertainties
for users, consumers, and society as a whole, have demanded a series
of flexible algorithms and analytic techniques for use by OPP. These
algorithms are referred to below as “submodels, “ and alternative tech-
niques for quantifying each submode]. are available. All submodels
pertinent to a pesticide registration decision should be used. There-
fore, those segments of the benefit-cost matrix shown above that will
receive the most use during pesticide product registration decisions
have been fully developed as submodels and include the food, feed, and
fiber production, health effects, and environmental effects submodels.*
*A pesticide manufacturing subrnodel could also be fully developed,
if desired, based upon the discussion in this chapter.
3.29
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The structure of these models is described in theremainder of this
report.
Overall, the models are intended to draw on existing public
agency and research data, as well as data supplied by the registration
process itself. With these data, a range of benefits and costs can be
assessed which are likely to occur if a proposed pesticide is regis-
tered. For pesticides on which substantial historical and test data
exist, the range can be made quite narrow, but in the case of very
innovative and unknown chemical compositions, the range must be
broadly defined as best it canbe, bydrawing on toxicity, persistence,
and effectiveness data for similar materials and formulations.
• 30
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4.0 THE FOOD, FEED, AND
FIBER PRODUCTION SUBMODEL
4. 1 Background
The problem of assessing the likely benefits and costs of pesti-
cide use requires the making of some assumptions concerning the
manner in which the pesticide will be used. Although the information
required for the registration of a new pesticide provides much infor-
mation on toxicity, it is likely that some assumptions will be necessary
to permit the estimation of the total number of acres to which the
pesticide will be applied and, subsequently, the total amount of the
pesticide which will be applied.
This problem is further complicated by the possible change ’
which can occur after registration is granted, such as changes in price
or changes in application techniques and costs. Consequently, to
devise a broadly useful benefit-cost system, it is essential to provide
guidelines for making assumptions concerning the manner in which .
n w pesticide will be used.
4. 2 Net Benefits to Society
from Pesticide Use
As shown in the preceding benefit-cost matrices, the major
categories of benefits attributable to pesticide use are: increased food,
feed, and fiber production; reduction of health/disease vectors and
nuisance pests; enhancement of commercial-industrial situations;
aesthetic improvement; and environmental management. The food,
feed, and fiber production category is defined to include both crops
and livestock 1 and covers crops grown for livestock consumption
(feed), and non-food crops such as cotton and flax. Other benefits in
plant production include growth of trees for wood, ornamental shrubs
and flowers, and special product plants.
The concept of benefits from use of chemicals on these plants
assumes that the growing environment can be improved in at least
three ways:
4. 1
-------
Removing harmful animals from the plant environ-
ment, mainly insects,
Removing other plants which compete for nutrients
and sunlight; these other plants are usually called
weeds, and
Changing the plant structure itself, usually by a
chemical cal1ed a growth regulator, thus, the size
and foliage of a pla t are loosely included as part
of its own environment.
Fungicides are a major category of pesticides which are used both in
the field and on harvested crops to prevent fungus growth during stor-
age. However, instead of making a separate category, fungicides can
be included in either of the first two categories above. The intention
of all o these uses, regardless of category, is to improve the health
of the crop plants so that the actual qield is protected or increased.
The analysis presented in Chapter 3. 0 has generated the con-
clusion tFat the value of the net internal benefit attributable to an
increase in yield is appropriately measured by the sum of the changes
in consumers’ s* rplus, economic rent, and monopoly profits which
are produced by this yield increase. Moreover, this analysis also
has demonstrated that the changes in economic rent and monopoly
profits are likely to be both extremely difficult to estimate empirically
and, more importantly, small in magnitude relative to the change in
consumers’ surplus. Consequentty, the analysis asserts that the net
internal benefit attributable to an increase in yield can be reasonably
and appropriately approximated by this change .ir cinsumers’ surplus,
which can be estimate as:
A CS 13 A + 1/2 A
where: A CS 13 the estimated change in consumers’
surplus attributable to the application
of pesticide i to c!rop j in year t,
the change in the price of crop. j
attributable to the application of
pesticide i in year t,
4.2
-------
= the total output of crop j in year (t-l),
and
the change in the total output of crop j
in the nation attributable to the applica-
tion of pesticide i in year t.
This relationship is illustrated graphically in Exhibit 4. 1, where
St _i represents the supply function of the industry in year (t-l), St
represents the supply function of the industry in year t, and D repre-
sents the demand function confronting the industry in both years. In
this diagram, the area jt ‘ j,t-i ac corresponds to the expression
Qj ; the area abc corresponds to the expression
1/ 2 . A Pijt Q t; and, hence, the sum of these two areas -- the
area Pjt P 3 , ab -- corresponds to ACS t , the increase in con-
sumers’ surplus associated with the increase in supply from St_i to
St. .
To calculate ACS 3 t, it is necessary to obtain data which specify
the values of P 3 t, Q , t-i and Although forecasts of Qj, t-i
either are directly available or can be estimated relatively easily from
readily accessible sources, * the calculation of Pi t and Qijt
requires substantial data manipulation. In particular, before it is
possible to estimate the change in the price arid total output of a crop
which will result from the use of a pesticide, it is necessary to deter-
mine both the total number of acres of the crop to which the pesticide
will be applied and the change in the output of that crop per acre which
will result from the use of that pesticide.
4.2.1 Acres of Crops Treated
by Pesticides
The number of acres of any particular crop which are treated
with a pesticide varies with the observations of infestation by the
farmer and with his hopes and expectations of a good yield. Yet, to
assess accurately the benefits likely to be obtained from the use of
*See, for example, U.S. Department of Agriculture, Economic
Research Service, National Economic Analysis Division, “Projections
of the U. S. Farm Subsector and Policy Implications, 1 Working
Materials No. LQ. 4. 74, September, 1974.
4. 3
-------
EXHIBIT 4.1
Price
of
Crop j
(Jit-i
aPijt
pit.
St
Quanttty of
Crop j
S
t—’
I
IC
D
4.4
-------
any proposed new pesticide, and the amount of the pesticide which is
likely to be discharged into the environment, .the benefit-cost system
requires a procedure for calculating and forecasting the amount of the
pesticide which will be applied to a specific crop in each region or
state. To perform these calculations, two important data sources
must be employed: the Census of Agriculture , published by the U. S.
Bureau of the Census, and the survey conducted by USDA on farmers’
use of pesticides. Although these sources do not always agree in
totals, proportions from one source can be transferred to the other
source.
Specifically, although data definitions are not always comparable
between any two Censuses of Agriculture , it is possible to identify
similar data categories and, hence, to calculate both the total number
of acres of crops of all types to which insecticides have been applied
and the total number of acres of crops of all types to which herbicides
have bcen applied. Moreover, these data are available not only for
the entire nation, but also for each state and each county. Thus, it is
possible to calculate these total acreages for each of the ten agricul-
tural regions utilized in the USDA surveys. Obtaining this degree of
comparability is important because the data on pesticide use in the
censuses are not available for either each specific crop or for each
specific pesticide. Consequently, it is necessary, although not espe-
cially desirable, to rely upon proportional allocating factors to dis-
tribute the total acres of crops treated by insecticides or herbicides
among specific crops treated by specific pesticides.
These proportional allocating factors can be calculated using the
data contained in the USDA survey by employing the following equation:
FC = TCA /TA
where: FC. the proportion of the total number of acres
in the nation to which insecticides (herbi-
cides) have been applied which constitute
acres of crop j during the survey year,
TCA. = the total number of acres of crop j in the
nation to which insecticides (herbicides)
have been applied during the survey year,
and
4. 5
-------
TA = the total number of acres of crops of all
types in the nation to which insecticides
(herbicides) have been applied during the
survey year.
Applying these proportional allocating factors to the data which have
been derived from the Censuses of Agriculture produceb the following
result:
TCA.k FC.• TA
3 t kt
where: TCAjkt the total number of acres of crop j in
region k to which insecticides (herbi-
cides) have been applied in year t,
FC 3 the proportion of the total number of acres
in the nation to which insecticides (herbi-
cides) have been applied which constitute
acres of crop j during the survey year,
and
TAkt = the total number of acres of crops of all
types in region k to which insecticides
(herbicides) have been applied in year t.
If the particular use for which the new pesticide is being proposed
for registration requires greater detail concerning the type of crop
than can be obtained in this manner, additional disaggregation can be
performed by using data on acres harvested which are available in the
annual issues of Agricultural Statistics . * In particular, the issue for
1968 specifies the acreage harvested in 1966 for each of the specific
crops contained in the more aggregative crop categories described in
the USDA pesticide survey of 1966. This information can be employed
to calculate:
FC’ . HA./THA
m
*USDA, Agricultural Statistics, 1968 , Washington, D.C., Super-
intendent of Documents, 1969, •Yearbook Statistical Committee, pp.
1 56-Z33.
4. 6
-------
where: the proportion of the total number of
acres of crop category m which have
been harvested which constitutes acres
of specific crop j,
HA the total number of acres of specific
crop j which have been harvested, and
THAm = the total number of acres of crop cate-
gory m which have been harvested.
Applying these proportional allocating factors to the previously derived
estimates of the total number of acres of the aggregate crop category
to which insecticides or herbicides have been applied yields:
TCA .k = FC’ . TCA
mj mjt
where: TCAjkt = the total number of acres of crop j
in region k to which insecticides
(herbicides) have been applied in
year t,
FC’mj the proportion of the total number of
acres of crop category m which have
been harvested which constitutes acres
of specific crop j, and
TCA = the total number of acres of crop cate-
gory m to w ich insecticides (herbicides)
have been applied in year t.
It is now necessary to estimate the proportion of these TCAJkt
acres to which the proposed new pesticide will be applied. Fortunately,
the USDA pesticide survey also provides data which permit the calcu-
lation of the following proportional allocating factors:
FPC TCPA 1 /TCA
4.. 7
-------
where: FPC 1 J the proportion of the total number of acres
of crop j in the nation to which insecticides
(herbicides) have been applied which con-
stitute acres to which pesticide i has been
applied in the survey year,
TCPA 1 J = the total number of acres of crop j in the
nation to which pesticide i has been applied
in the survey year, and
TCA = the total number of acres of crop j in the
nation to which insecticides (herbicides)
have been applied during the survey year.
Moreover, given expectations about the extent to which the proposed
new pesticide will displace each of the presently registered pesticides
which currently are applied to a crop, it is possible to derive the
following agg regative proportional allocating factor:
FPC.. E(FPC . FD.. )
ijt m mj l3mt
where: FPCIJt the proportion of the total number of acres
of crop j in the nation to which pesticide i
will be applied in year t,
FPCmJ the proportion of the total number of acres
of crop j in the nation to which insecticides
(1ierb cides) have been applied which con-
stitutes acres to which pesticide ru has been
applied in the survey year, and
FJ ijmt the proportion of the total number of acres
of crop j in the nation to which pesticide m
is applied in the base year and pesticide i
is expected to be applied in year t.
In forming expectations about the displacement of presently reg-
istered pesticides by proposed new pesticides, it is suggested that, if
the proposed new pesticide constitutes a substantially more efficacious
or less expensive method of controlling the target pest than does the
presently registered pesticide, FDijmt should b.c set close to (or equal
to) one; while, if the proposed new pesticide constitutes a substantially
less efficacious or more expensive method of controlling the target
4. 8
-------
pest than does the presently registered pesticide FDjjmt should be
set close to (or equal to) zero. In a similar fashion, Lf the pesticide
under consideration is a pesticide which is being considered for rereg-
istration, it might be reasonable to set FDjjmt equ to zero for all
m i and to set FD 3 t equal to one (i. e., to set FPCIjt equal to
FPC 1 ). However, these suggestions should not be applied mechani-
cally. Rather, it is advisable that the values which are assigned to
FDijmt should be adjusted to reflect such considerations as the rate
at which the proposed new pesticide will gain acceptance by pesticide
users and the rate at which the pest population develops resistance
to both the proposed new pesticide and currently registered pesticides.
Obviously, adjustments of this type are more justifiable for pesticides
which are confronting their initial registration action. *
Finally, the number of acres of any particular crop to which any
specific pesticide will be applied in each region in each year can be
estimated as:
TCPA.. = FPC . . TCA
ijkt i.it jkt
where: TCPAIjkt = the estimated number of acres of crop j
to which pesticide i will be applied in
region k in year t,
FPC t the proportion of the total number of
acres of crop j in the nation to which
pesticide i will be. applied in ye r t, and
TCAjkt = the total numbei o1 ãcres of crop j in
r.egion k to which ins cticides (herbi-
cides) ha be n ppli diWyear t.
*With respect to a new pesticid , it is unrealistic to expect that
all farmers who can increase their profits by adopting a new pesticide
will recognize this profit opportunity and adopt the pesticide during the
first year in which it is available. Rather, each farmer will decide to
adopt the new pesticide at that point in time when he becomes convinced
that the pesticide will generate an increase in his profits and this point
in time will not be identical for all farmers. Consequently, the esti-
mates of FDijmt which are employed in the evaluation of an T new pesti-
cide should reflect a lagged adjustment process in which the full mar-
ket potential of the pesticide is realized only after the passage of a
considerable period of time. A variety of statistical techniques (e. g.,
Koyck transformations and Almon lags) are available for the estima-
tion of the appropriate adjustment process.
4. 9
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4.2. 2 Change in Crop Output
Attributable to Pesticides
The testing of the efficacy of pesticides in field-like situations is
typically conducted on test farms which are operated by experiment
stations and other agencies in all parts of the country. These experi-
ment stations design test plot experiments in which selected plots are
treated with alternative pesticides, and the results are compared on
the basis of one or more measures of the effectiveness of each of the
pesticides. Typical measures of effectiveness range from the numbers
of insects which are observed on the plants to the actual weight of the
crop yield. Some measures, such as the amount of sugar in sugar
beets or the actual weight of peanut kernels, are relatively difficult to
obtain; and, unfortunately, these measures do not appear often in the
professional reports of these test plot experiments.
More commonly, the results are reported as percentages of
decreased or increased damage from pests. These percentages may
refer to some basic number of damaged fruit, ears of corn, potatoes,
or other unit of yield, but the actual data on changes in damage from
pests expressed in units of weight per acre are often omitted. If these
changes were consistently r.’ ported in physical units, it would be rela-
tively simple to calculate the difference which is observed between the
yield which is obtained when the proposed new pesticide is applied to a
crop and the yield which is obtained when no pesticides are applied to
that crop. * This difference then can be applied to the previously
*It is suggested strongly that this particular comparison is the
most appropriate comparison for the pesticide registration process.
Any other criterion for comparison would be substantially more diffi-
cult to standardize across different test plot experiments to the extent
that it would require both the selection of a particular pesticide and the
specificatIon of a particular application rate of that pesticide as the
basis for that criterion. Moreover, even with no application of pesti-
cides as the basis for comparison, it is possible to compare the rela-
tive effectiveness of any two alternative pesticides merely by calcu-
lating the differences between each of the various indicators in their
individual evaluations. Yet, it must be cautioned that if these compar-
isons are to be valid, it is imperative that the evaluation of each pesti-
cide must be continually updated as additional evidence of the effects of
the application of that pesticide becomes available.
4.10
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estimated number of acres of the crop to which the pesticide has been
applied in the region to calculate the change in crop output which is
expected to be generated by the use of the pesticide. Specifically, the
following equation can be evaluated:
AY.. TCPA..
ijkt ijkt
where: = the change in the total output of crop j
in region k attributable to the applica-
tion of pesticide i in year t,
ikt = the change in the yield per acre of
crop j in region k attributable to the
application of pesticide i in year t, and
TCPA..kt = the estimated number of acres of crop j
to which pesticide i will be applied in
region k in year t.
If only percentage changes in yield per acre are reported in the
experimental results, the unit of measurement for these percentage
changes in yield must be converted to units of weight per acre by com-
bining the percentage changes with data specifying the yield of the crop
per acre for the state and the year in which the experiment was con-
ducted. In general, these data on yield per acre are also reported in
the experimental results. Thus, in situations of this type, the change
in total output of a crop which is attributable to the application of a
particular pesticide can be estimated in the following manner:
AQ ( YIY) Y TCPA..
ijkt ijkt jkt ijkt
where: &Qj.kt the change in the total output of crop j
in region k attributable to pesticide i
in year t,
(4 Y/Y)j.kt = the percentage change in yield per acre
of crop j in region k attributable to the
application of pesticide i in year t,
kt the reported yield per acre of crop j
in region k in year t, and
TCPAj. = the estimated number of acres in crop j
to which pesticide i will be applied in
region k in year t.
4,11
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These estimated regional changes in output can then be aggre-
gated to produce an estimate of the national cJ ange in output attribut-
able to the use of the pesticide:
-‘ ijt AQ 1 j
where: = the change in the total output o crop 5
in the nation attributable to the appli-
cation of pesticide i in year t, and
Qijkt = the change in the total output of crop j
in region k attributable to pesticide i
in year t.
4.2.3 Change in Crop Prices
Attributable to Pesticides
Before the benefit which is generatedby this increase in national
output can be calculated, it is necessary to estimate the effect that this
change in output will have upon the price of the crop. Since this
increase in output is produced by an increase in the supply of the pro-
duct, the effect upon the price of the crop will be determined by the
de: and for the crop. More specifically, the reduction in the price of
the crop which is caused by this increase in output is determined by
the price elasticity of demand for the crop. This price elasticity of
demand is defined as:
E. = (I . ’Q ./Q.)I(tP.IP.)
3 3 3 3
where: E 5 the price elasticity of demand for rop j,
A Q. = the change in the quantity demanded of
crop 5 induced by a change in the price
of crop j,
= the quantity demanded of crop j,
41’ the change in the price of crop 5, and
P. the price of crop j.
3
4.12
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By rearranging terms in this expression, it is possible to determine
the change in price which will be associated with any particular change
in quantity demanded relative to thi.s demand function. Specifically:
= (P. 4Q .)/(Q E )
3 3 .3 3 3
or, expressing this relationship in terms of the variables associated
with the use of a pesticide:
‘ i.jt = 1 ,t—i A0 t)t(0 , t_i E )
where: the change in the price of crop j
attributable to the application of
pesticide i in year t,
= the price of crop j in year (t-l),
3, t—l
the change in the total output of crop j
in the nation attributable to applica-
tion of pesticide i in year t,
Q. = the total output of crop j in year (t-l),
and
E 1 the price elasticity of demand for
crop j.
T6ey lu e this expression, two data elements -- t-l and F --whose
sources have not yet been specified in this report must be obtained.
} 1 Lany so irces of data on farm crop prices are available, and
e i different sources are understandably confusing. For example,
data from agricultural Statistics, 1973 , shows a slight decline in the
price of peanuts from 1965 to 1966, but the same source in a separate
table shows an increase in the price of oil-bearing crops of about ten
percent during the same one-year interval. * Although these two data
sets are admittedly measures of different variables, i.e. , “peanuts,
*Agricultural Statistics, 1973 , cit. , p. 122, Table 174,
shows the decrease, and p. 459, Table 663, shows the increase.
4.13
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and “oil—bearing crops 1 ” this divergence shows the danger of using a
broad crop category price to estimate trends in the price of a specific
crop. One important feature of the data sources mentioned is their
historical time series. In addition, the Annual Price Summary gives
annual data for 20-year periods, and data for even longer periods can
be compiled by using successive volumes of this series of documents.
These long—term data would provide the basis for the development of
a crop price forecasting model, but few such models have actually
been widely used. The preliminary results from such a modeling
study are shown in Projections of the U.S. Farm Sub sector and Policjr
Implications .
The data reported in Projections ..., however, are not for spe-
cific crops, nor are they for specific states. Both of these levels of
detail would be desirable for EPA to have in a benefit-cost system for
the analysis of proposed new pesticides, since it is necessary to use
data at these levels of detail when assessing possible health and envi-
ronmental damages. Therefore, it is recommended that the historical
data contained in the annual issues of Agricultural Statistics and the
Annual Price Summary should be integrated with the aggregate price
forecasts contained in Projections .. . to produce long-term crop
category price indices. The rationale underlying this recommendation
is that in assessing crop prices to be utilized in the determination of
the benefits accruing to society from changes in crop yields attribut-
able to pesticides, tile benefit-cost system will be more conveniently
usable if indices of this type are readily available and capable of direct
integration into the system matrix.
Recent estimates of the price elasticity of demand for agricul-
tural crops appears in Consumer Demand for Food Commodities in the
U. S., with Projections to 1980 . ** Moreover, t*o relatively dated
*USDA, Agricultural Prices Annual Summary, 1973 , Washington,
D.C., Superintendent of Documents, June, 1974, Statistical Reporting
Service, Crop Reporting Board, Pr 1-3 (74), p. 6.
**Smith, Allen, etal., Projections of the ‘U.S. Farm Subsector
and Policy Implications , USDA, Washington, D.C., September, 1974,
Table 19, p. 45, Economic Projections and Analytical Systems, Eco-
nomic Research Service, Working Materials No. LQ. 4. 74.
***George, P.S. and G. A. King, Consumer Demand for Food
Commodities in the U.S., with Projections to 1980 , Giannini Founda-
tion, Monograph Number 26, March, 1971.
4.14
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studies* are available which provide empirical estimates of the price
elasticity of demand for a reasonably wide variety of crops. Although
these studies are likely to be somewhat inaccurate to the extent that
they fail to reflect the substantial increase in agricultural prices which
has occurred sinCe 1973, the general consistency with which they esti-
mate the price elasticities of demand for agricultural crops to lie
between 0.5 and 1. 0 suggests that the use of their empirical estimates
of elasticities in the benefit-cost system is reasonably justifiable until
more current estimates become available.
4.2.4 Change in Consumers’ Surplus
Attributable to Pesticides
The ultimate objective of the analysis in this section is the mea-
surement of the value of the net internal benefit which accrues to
society as a result of an increase in crop yield attributable to the
application of a pesticide. As has been asserted previously, this value
can be approximated reasonably by:
‘ t—l + 1/2 á
where: ACS 13 t the estimated change in consumers’
surplus attributable to the application
of pesticide i to crop j in year t,
the change in the price of crop j attri-
butable to the application of pesticide i
in year t,
Q. the total output of crop j in year (t-1),
j,t—l
and
= the change in the total output of crop j
attributable to the application of
pesticide i in year t.
*Schultz, Henry, The Theory and Measurement of Demand ,
Chicago, illinois, University of Chicago Press, 1938; and Western
Extension Marketing Committee Task Force, A Handbook on the
Elasticity of Demand for Agricultural Products in the United States ,
Western Extension Marketing Committee Publication No. 4, July,
1967.
4.15
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Substituting into this expression the estimator of which has been
derived in the preceding section produces the following final result:
ACSjjt (P ,t .i 0 t)/ + 1/2 t- (1 Q t) 2 J I
(Qj,t—1 E )
where: CSj the estimated change in consumers’
surplus attributable to the application
of pesticide i to crop j in year t,
the price of crop j in year Ct-i),
OLQ ijt = the change in the total output of crop j
in the nation attributable to the applica-
tion of pesticide I in year t,
the price elasticity of demand for crop j,
and
Qjt-l = the total output of crop i in year (t-i).
Thus, to estimate the benefit which accrues to society as a result of an
increase in crop yield attributable to the application of a pesticide, the
only information which is required is a determination of the price of
the crop, an estimate of the increase in the total output of the crop
which will be produced by utilization of the pesticide, a determination
of the total output of the crop, and the value of the price elasticity of
demand for the crop.
4. 3 Costs of Pesticide Application
Since the measurement of the value of the net internal benefit as
the consumers’ surplus generated by an increase in yield appropriately
incorporates all costs of pesticide application 1 there is no need to
calculate these costs independently to determine the aggregate eco-
nornic justifiability of registering a particular new pesticide. Yet, to
the extent that independent calculation of these costs can provide
valuable insights into the distribution of the net internal benefit among
the suppliers and the users of the new pesticide, this calculation may
be desirable for the assessment of the equity effects associated with
the registration of this pesticide.
4.16
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The total cost of applying a pesticide to a crop consists of two
elements - - the cost of the pesticide which is applied and the cost of
performing the application. The total cost of the pesticide which is
applied can be estimated as:
TPC t R t ijkt NAijkt TCPAijkt)
where: TPC t the total cost of the quantity of pesti-
cide i which is applied to crop j in the
nation in year t,
R.t the price of pesticide i in year t,
iJkt the quantity of pesticide i applied per
acre of crop j in region k per appli-
cation of pesticide in year t,
NAi.kt = the number of applications of pesticide i
to crop j in region k in year t, and
TCPA. kt = the total number of acres of crop j to
1) which pesticide i is applied in region k
in year t (estimated in subsection 4.2. 1).
Estimates of the prices of pesticides which are used on large
scales are important to the benefit-cost system because these prices
vary from a few cents per pound of active ingredient to several dollars
per pound of active ingredient. If the benefit-cost system is to identify
adequately all costs associated with the registration of a proposed new
pesticide, then the system must measure the costs which the farmers
will have to bear in obtaining the new pesticide.
Perhaps the most reasonable method of obtaining estimates of
the expected price of a pesticide which has never been offered for sale
in the market is to require the manufacturer of the proposed new pesti-
cide to divulge the price which he expects to charge for the pesticide if
it is registered. However, if EPA is unwilling or unable to require the
manufacturer to reveal this information, two alternative methods of
estimating the probable price of a proposed new pesticide are offered
for consideration:
4. 17
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Match the proposed new pesticide with an existing
pesticide, with which it is likely to compete; then
project the trend of the existing pesticide price
(per pound of active ingredient), or
• Average the historical price data for each year in
a selected time period, for a group of pesticides
which have been used on crops for which the pro-
posed new pesticide is intended; then project the
trend of this price average.
In any of these three cases, the expected price for the proposed new
pesticide can be forecast either by projecting a straight line trend or
by combining the base year data with selected variables from the
OBERS* economic projections, which contain forecasts for 1980, 2000,
and 2020. Obviously, these same forecasting techniques also would be
applicable to the evaluation of a proposal for the reregistration of a
pesticide, although in this case the forecasting techniques would be
applied to historical price data for the pesticide under consideration.
In obtaining base year price data, it is likely that information
from USDA sources, which is published several years after the prices
have prevailed in the market, will be more convenient to utili ae in the
benefit-cost system than data from current price lists because of the
difficulties inherent in collating, comparing, and compiling these cur-
rent data into annual average figures. Moreover, data from the Annual
Price Summary ( . cit., p. 168) incorporates state-level detail.
Thus, different costs can be calculated for different states if this level
of detail is desired.
The total amount of a pesticide which is purchased and applied in
a year depends, in part, upon the quantity of the pesticide which is
applied per acre in each application of the pesticide and the number of
applications of the pesticide which are performed in that year. The
application rate per acre and the frequency of application depend, in
turn, upon the dosage rate specified on the label registered with EPA.
Moreover, the frequency of application will also depend upon the
*TJ S. Water Resources Council, 1972 013 ERS Projections ,
Washington, D.C., Superintendent of Documents, 1972 (see especially
Volume 5).
4.18
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recommendations of local extension agents and the farmerts assess-
ment of the probable infestation of his crop. The maximum application
rate and frequency of application which are recommended by EPA
might be the most likely rate and frequency which will be selected by
the farmer, but it is unlikely that the farmer will want to incur the
expense of applying more pesticide than he thinks is really needed.
Nevertheless, it is suggesied that the benefit-cost system should con-
centrate on the EPA recommendations as sources of data concerning
the application rate and frequency of application of a pesticide.
Finally, because of the possible development of immunity by spe-
cific pests to any pesticide, it is necessary to consider whether the
rate of application per acre or the frequency of application would be
likely to increase over a period of years. Data from two volumes of
the Suggested Guide for the Use of Insecticides to Control Insects
Affecting Crops, Livestock, Households, Stored Products, Forests,
and Forest Products* indicate that the USDA continues to recommend
a constant application rate per acre in successive years. Therefore,
it is recommended that the assumption which is incorporated in the
benefit-cost system should be that the application rate for any pesti-
cide is likely to remain constant at least for three years and, orobaily,
for five years. Given the continuing appearance of new pesticides on
the market, substitution of one pesticide for another appears :o be
more likely to occur than a gradual increase of either the application
rate or the frequency of application. Therefore, no specific allowance
for the development of immunity has been incorporated into the benefit-
cost system. An approach to introducing such an allowance is
described by Hueth and Regev** and their model could be included as
one of the component cells of the overall benefit-cost matrix if a con-
sideration of the immunity phenomenon is desired.
*USDA, Suggested Guide for the Use of Insecticides to Control
Insects Affecting Crops. Livestock, Households, Stored Products,
orests and Forest Products , Washington, D. C., Superintendent of
Documents, 1967, Agricultural Research Service, and Forest Service,
Agricultural Handbook Series No. 313, and 1969, Agricultural Hand-
book Series No. 331, p. 84, 1966, and pp. 83, 150-152, 1968.
**Hueth, D., and U. Regev, “Optimal Agricultural Pest Manage-
ment with Increasing Pest Resistance, American Journal of Agricul-
tural Economics , Vol. 56, No. 3, August, 1974, pp. 543-552.
4. 19
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The total cost of performing the application of the pesticide can
be calculated as:
TAC Jt = i (AC.. 1 NA..kt TCPA..kt)
where: TAC..t = the total cost of performing the applica-
tion of pesticide i to crop j in the nation
in year t,
ACijkt the cost per acre of performing the appli-
cation of pesticide i to crop j in region k
in year t,
NAi.kt the number of applications of pesticide i
to crop j in region k in year t, and
TCPA..kt = the total number of acres of crop j to which
pesticide i is applied in region k in year t
(estimated in subsection 4.2. 1).
The methods of estimating both the expected frequency of application of
a proposed new pesticide and the total number of acres to which the
pesticide is expected to be applied have been described previously in
this chapter. Consequently, the only new information which is required
to evaluate this expression is information concerning the cost of per-
forming the application of the pesticide, and reasonable estimates of
this information, can be obtained from the agricultrual extension agents
of each state. Hence, the total cost of applying a pesticide to a crop
can be estimated as:
= TPCjJt + TACIJt
where: the total cost of purchasing and performing
the application of pesticide i to crop j in
the nation in year t,
TPCf t = the total cost of the quantity of pesticide i
which is applied to crop j in the nation in
year t, and
TAC 1 .t the total cost of performing the application
of pesticide i to crop j in the nation in
year t.
4.20
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5.0 THE HEALTH EFFECTS SUBMODEL
5. 1 Background
In the development of a benefit-cost methodology for use in the
registration process of chemical pesticides, it is desirable to have a
health effects submodel that will account for the occupational health
effects, as well as the general public health effects associated with
the development, manufacture, formulation, distribution, application,
and residues of a particular pesticide product . Thus, the health
effects submodel deals with the potential health effects of a pesticide
with respect to the pesticide t s registered use, and it contains proce-
dures which can be applied wherever needed in the overall benefit-
cost structure.
5.2 Outputs of the Health Effects Submodel
In order to make the purpose of this submodel more clearly
understood, its desired outputs ivill be delineated. These outputs will
be discussed in two parts -- health damages and health benefits.
5.2. 1 Health Damages
In general, the outputs from this part of the submodel will be an
identification and enumeration of the groups of people whose health
would be damaged from both’ accidents and environmental exposure
associated with a particular pesticide product.
More specifically, associated with each aspect of the pesticide
product registration decision - - i. e., R and D, manufacture, formu-
lation, distribution, application, and residues -- are potential occu-
pational health damages and potential general public health damages
to certain segments of the population. For example, in the manufac-
ture and formulation of a pesticide for a particular use, there are
potential acute health damages to the employees involved in this pro-
cess. They may take one or more of the following forms:
5. 1
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• Acute injury from “normal” exposure, * i. e.,
irritation to skin, eyes, nose, and throat.
• Acute injury from accidental release under user
controlled condition, i. e.., poisoning, death or
irritation to skin, eyes, nose, and throat.
• Acute injury from other abnormal involuntary
exposure such as an explosion, i. e., poisoning,
death, or irritation to skin, eyes, nose, and
throat.
In addition, the subclinical injuries built up in one’s body from
continued exposure to a pesticide due to the manulacture and formula-
tion process may cause chronic injury in one or more of the following
forms:
• Mutagenicity,
• Teratogenicity,
• Oncogenicity,
• Reproductive impairment, and
• Chronic physiological malfunction.
These same acute and chronic injuries can occur in other seg-
ments of the population and as a result of other processes in the dis-
tribution and use of a pesticide product. The matrix in Exhibit 5. 1
illustrates this concept in more detail, giving some possible causes
of acute and chronic injury for the various processes and polatiori
subgroups.** By examiningeacb aspect associated with the sale and
*“Norinal” exposure is included to reflect the real wor] d situation.
Ideally, there should be no such term as “acute injury from ‘normaP
exposure.” Yet, many ‘would argue, e. g., those in industry, that any
acute injury that is caused from direct exposure to a pesticide is not
all a result of accidental release. Therefore, until this issue is
resolved, one can argue that some acute injury is caused by what many
refer to as “normal” exposure.
**Note that the population subgroups exposed are dependent on
the pesticide’s purpose and location of use. For example, health
hazards to field and farm personnel would only relate to those workers
applying the particular pesticide product and not all farm workers.
Likewise, only those segments of society in the vicinity of the
5. 2
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XHI IT 5. h Health Damages from a Pesticide Product Registration Decision
Nature of
Health Damage
Process Causing Health Damage
Re search
and
Development
Manufacturing
and
Formulation
Distribution
(Transportation
and Storage)
Application
Residues*
Occupational Health Damage.
from contact with pesticide.
Acute injury caused
by normal expo .uro**
in the laboratory or
field, accidental
release. in the lab—
oratory or field, etc.
Acute injury caused
by normal exFo.ure’p*
accidental releases,
explosions. etc.
Acute injury caused
by normal exposure k
accidental releases,
or other transporta-
tion accidents
Acute injury caused
by normal use,**
accidental releases,
misuse, equipment
failure, etc.
Chronic injury
caused by long-term
occupational
exposure* *
General Public Health
Damages from contact
with pesticides
Acute injury caused
by drift from acci-
dental releases as a
result of experi-
mental use permits
Acute injury caused
by drift from acci.
dental releases,
explosions. etc.
.
Acute injury caused
by drift from ace!-
dental releases or
other transportation
accidents
Acute injury caused
by drift from sect-
dental releases or
misuse by a profes.
feslonal applicator
and caused by
normal use, * acci-
dental releases or
misuse by the
household user
Chronic injury
caused by long-term
exposure via buildup
in food chains, etc.
*Resjdues from direct contact with pesticides can be brought about as a byproduct of the R&D, manufacture, formulation, distrlbution or application
processes, However, only .hc application process is a major contributor to residue, from indirect contact with pesticides.
55 ”Noxmal” exposure is included to reflect the real world situation. Ideally, there should be no such term as “acute injury from ‘normal’ exposure
(use).” Yet, many would argue, e.g., those in Industry, that any acute injury that is caused from direct exposure to a pesticide is not all a result of
• accidental release. Therefore, until this issue is resolved, one can argue that some acute Injury is caused by what many refer to as “normal” exposure.
***This chronic injury includes only those injuries caused by residues from direct long-term exposure as a result of direct contact with a pesticide,
whether it be from the R&D. manufacture, formulation, distribution or application processes. Thus, chronic injury from residues from Indirect long—
term exposure as a result of indirect contact, i.e., from daily food intake, is not included here, but in the box below.
-------
use of a pesticide product, the distributional effects can be assessed,
rather than just the total occupational health damage or general public
health damage. That is, those population segments most likely to be
affected can be delineated. This is important as EPA regulatory
activities, in general, are inevitably concerned with equity questions.
These questions are often crucial issues in EPA cancellation hearings.
However, available data Oii health damages may not be sufficient to
allow for an analysis as shown in Exhibit 5. 1.
Nevertheless, the distributional health effects indicated in
Exhibit 5. 1 may be restructured in such a way as to provide meaning-
ful information. For example, those population segments most likely
to incur either occupational health damage or general public health
damage can be delineated based upon the processes causing heaJth
damage. Furthermore, the acute and chronic injuries as outlined
above can be specified as the second dimension to the problem.
Exhibit 5.2 provides a structure for this approach. The assessment
of each type of health damage for each subpopulation incurring health
damage can provide a profile of the distributional health effects as so-
dated with a pesticide registration decision.
However, in order to make an intelligent assessment of these
injuries, definitions of these acute and chronic injuries are . eeded.
Furthermore, two sets of definitions are desirable - - the first based
on human experience data and the second based on experimental toxi-
cology data. Therefore, presented below is one attempt to define
these injuries so that an assessment of the human health damage from
a pesticide product registration can be made.
The definitions appearing in Sections 5.2. 1. 1 and 5.2. 1.2 have
been based on the expert opinion of Dr. Henry F. Smyth, Jr., toxicol-
ogist and Advisory Fellow, Mellon Institute. Furthermore, those in
Section 5.2. 1.2 are consistent with the current experimental testing
procedures required by the EPA Registration Guidelines and have been
derived to follow the “Toxicity Categories” tabulation in the EPA “Pro-
posed Registration. Reregistration and Classification Procedures,”
manufacturing or application of the particular pesticide product are in
danger of possibly incurring acute injury from indirect contact. In
addition, household users and non-farm applicators would not be
affected by a pesticide if used for farm use only.
5.4
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U’
S
U’
EXHIBIT 5. 2: Delineation of Health Damages from a Pesticide Product Registration Decision
Entfty Incurring
Health Damage
Type of Health L mage
Acute Injury
Chronic Injury
T.rato- R.preduc. Physiologic
Mortality M *agenic genie Oncog.nic* tive Xm- Malfunction
( cath) flasard — Hazard Huard pairment )4.eerd*
Morbidity
Ocular
Exposure
hazard
Dezmsl
Exposur.
Hazard
Oral
Exposure
Hazard
Inhalation
Exposure
Iazard
Systemic
Polinning
Occupational Health Damage tot
Pesticide Ri. ]) Manufacturing
and Formulation Workers
Pesticide Transport Personnel
Field Workers and Other Farm
Personnel
Commercial Farm Applicator.
Professional Non-Farm Appli-
cators (VCOs, government
employees etc.)
General Public Health Damage to
Itousehold Users of Pesticides
( hreu h direct eaposure)
Society as a Whole (through
indirect_exposure)
‘In particular. witI respect to central nervoüm System. hematopoetic system, liver and kidneys.
-------
Federal Register (Vol. 39, No. 201, October 16, 1974, p. 36986).
Needless to say, other experts in this field may agree or disagree with
these definitions and thus they do not nor are they intended to represent
the opinion of all experts. Nevertheless, definitions of this sort are
necessary and those that appear below are workable definitions consis-
tent with the current state-of-the-art.
5.2.1. 1 Definition of Health Damages
Based on Human Experience Data
The definitions below are based on the incidence of the particular
injury. Incidence is used in the epiderniological sense as the number
of individuals affected among each 100, 000 exposed to the pesticide
product* in the subpopulation indicated by the left-hand line headings
of Exhibit 5.2.
Therefore, ocular exposure hazard, dermal exposure hazard,
oral exposure hazard, inhalation exposure hazard, and systemic poi-
soning can respectively be defined as the incidence of irritation to the
eyes, irritation to the skin, irritation to the throat from swallowing,
irritation to the nose from inhaling and any adverse response to
absorption through the skin, by mouth and/or by inhalation, attributed
to the pesticide product and sufficiently severe to cause:
• The victim to purchase and apply an ameliorative
preparation, or
• The victim to seek medical advice or treatment, or
• The victim to lose time from work.
The column hQaded “death” can be defined as the incidence of reported
deaths attributed to exposure to the pesticide product.
Under “chronic injury,” mutagenic and teratogenic hazards must
be assessed simultaneously because the distinction between mutagen-
esis and teratogenesis depends on whether DNA is altered, and this is
not routinely reported for isolated human cases. Therefore, combining
*11 information on the pesticide product is not available, then
data on the pesticide in general should be compiled. This information
can then be used to determine the marginal health effects of the pesti-
cide product based on the particular use of the pesticide and the per-
centage of the pesticide used for this particular use,
5.6
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these terms under the title of “hazard to offspring, “they can be defined
as the incidence of stillbirths and abnormal offspring attributed to
exposure of either parent to the pesticide product. Oncogenic hazard
can be defined as the incidence of neoplasms attributed to past expo-
sure to the pesticide product, and reproductive impairment can be
delinedas the incidence of reduction in fertility and of neonatal mor-
tality attributed to exposure of either parent to the pesticide product.
Finally, physiological malfunction hazard can be defined as the inci-
dence of malfunction of any body organ or system attributed to expo-
sure to the pesticide product, provided that it is sufficiently severe to
cause:
The victim to purchase and apply an ameliorative
preparation, or
The victim to seek medical advice or treatment, or
• The victim to lose time from work.
Data describing the numbers of people in each subpopulation who
experienced these effects can only be available for presently or pre-
viously registered pesticide products and thus these definitions can
only be applicable for those pes icide products seeking reregistration
and for those new pesticide products whose parallel pesticide* is a
presently or previously registered pesticide product. There can be
three main sources of these data:
Planned and controlled administration of pesticides
to human subjects, **
Case reports of episodes of accidental or other acute
poisoning, and
• Epidemiological studies which, in turn, comprise
surveys of occupationally-exposed groups (in accord-
ance with a variety of retrospective and prospective
approaches) and studies of the general population.
*Definition of this term appears in Chapter 1. 0 of this report.
*‘ This source is no longer acceptable and therefore any informa-
tion obtained in this manner will have already been reported on.
5. 7
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Gomputer ized oarches, such as MEDLINE and TOXLINE, and
manual searches of the Pesticides Abstracts and other pertinent
sources -- e.g., medical journals, EPA ’s Pesticide Episode Reporting
System (PERS), poison control centers, etc. -- can provide access to
these data, as they exist . Experience has indicated, however, that the
fact that a pesticide is or has been registered, does not mean that data
related to its health effects will be available. For most pesticides,
little is known about their human health effects, particularly when pop-
ulations are exposed to long-term, low level doses of the pesticide.
Furthermore, when using a parallel pesticide, it may be possible that
the parallel has not been in use for a. long enough time period to ade-
quately assess potential health effects of the new pesticide. Therefore,
a continuing review of these types of data will be necessary to achieve
full completion and adequate updating of Exhibit 5. 2, using the defini-
tions defined in this subsection. That is, the following sorts of infor-
mation concerning human exposure to a particular pesticide or pesti-
cide product must be continually sought and updated to properly compute
incidences of those hazards delineated in Exhibit 5. 2:
• Numbers of exposed people in each subpopulation,
• Nature of health damage, i.e., occupational or
general public,
• Type of physiological effects,
• Types of illnesses or disabilities,
• Number of reported deaths and poisonings,
• Type of application associated with accident or
exposure, and
• Nature of treatment, e. g., number of days in a
hospital, number of visits to a physician, medi-
cation taken, etc.
However, in using the above definitions, indications are that the
column which might be filled in with best quantitative accuracy at pres-
ent is that headed tideath. Death certificates can be screened, and
correspondence can (often) narrow down to specific pesticides and sub-
populations those certificates which are ambiguous. Qualitative infor-
mation may be obtained for the other co’umns by a thorough search of
5. 8
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the medical literature and records of poison control centers as men-
tioned above, but it is doubtful that reasonably complete quantitative
information can be obtained, given present medical and health report-
ing procedures.
5.2. 1. 2 Definition of Health Damages Based
on Experimental Toxicology Data
When registration is being sought for a new pesticide product,
adequate human experience data will naturally not be available, if a
parallel pesticide product exists, then human experience data for this
parallel registered product can be used to the extent available. How-
ever, experimental toxicology data are essential to adequately identify
the parallel pesticide(s). Furthermore, if a new pesticide product has
no parallel registered product, experimental toxicology data required
by the registration process must be used to assess the likely human
health effects.
There is world-wide acceptance of the arbitrary “factor of safety”
of 100 which was first proposed by A. 3. Lehman of the Food and Drug
Administration for dealing with new substances to which the human
race has not yet been exposed extensively, and was published in the
Federal Register of March 11, 1955 (p. 1493). It is now applied to all
substances as a conservative factor between animal experiment and
human tolerance, except when a lower factor may be justified because
it is known that the system injured by the substance responds nearly
equally in different species, such as choline sterase, or corneal and
skin injury. It is quite obvious that the number 100 may be too high
for some substances and too low for others. The only way to get a
more defensible number is to determine the relative resistance of the
target system to the substance or, almost as good, to select an expe-
rimerital species which biotransforms the substance qualitatively and
quantitatively like the human.
Legally required precautionary labels warn how to avoid injury
from reasonably foreseeable hazards of handling pesticides. Injuries
in subpopulations which handle a pesticide in its original container
generally result from failure to follow the directions and precautions
for use. Predicting incidence for these subpopulations is essentially
predicting the frequency of failure to follow directions. However, it
is not unreasonable to assume that this frequency is the same for all
pesticides, and that experimental animal results measure the relative
incidence of severe injuries among the careless due to toxicity of the
5. 9
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chemical, hence, the relative frequency of severe injuries between
different pesticides. This argument does not .hold for the subpopula-
tion whose exposure to the pesticides is due to residues in food, water,
and air, because these people never see the labels, and are not injured
due to their own carelessness.
The number of injuries reported in the medical literature for
subpopulation groups (if available) can be combined with estimates of
the size of the groups exposed to the pesticide product and the pub-
lished experimental animal results, to refine the estimates which
would be generated by the definitions below. Therefore, the definitions
are more valid as patterns than as a means to make accurate numer-
ical estimates.
For acute injury, each hazard defined below contemplates injur-
ies similar to those in Section 5. Z. 1. 1 and thus sufficiently severe to
cause:
• The victim to purchase and apply an ameliorative
preparation, or
• The victim to seek medical advice or treatment, or
• The victim to lose time from work.
In addition, each hazard can be expressed as the number of individuals
affected among each 100, 000 exposed to the pesticide product in the
subpopulation indicated by the left-hand headings of Exhibit 5. 2.
Furthermore, due to the uncertainty of extrapolating from animal tox-
icology data to likely human health effects, a range for each hazard
that incorporates the probable value of each hazard is desirable. *
Therefore:
Ocular exposure hazard is defined as eight to twelve
times the number of rabbit eyes among six tested
which suffered irreversible opacity at two days,
plus four to six times the number which suffered
corneal opacity reversible within two days or irri-
tation persisting for seven days, plus 0. 5 to 1. 5
*The basis for these definitions has already been explained (see
the last paragraph on page 5. 4).
5. 10
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times the number which suffered irritation revers-
ible within seven days, when ocularly exposed with
0. 1 ml of the pesticide product, in the solvent and
at the concentration expected to be handled by the
subpopulation of interest.
Dermal exposure hazard is defined as eight to twelve
times the number of rabbits among six tested which
suffered necrosis or marked erythema evident at 72
hours, plus four to six times the number which suf-
fered moderate erythema evident at 72 hours, plus
0.5 to 1. 5 times the number which suffered any vis-
ible lesser degree of irritation evident at 72 hours,
when dermally exposed -- i. e., when applied to
both covered and uncovered skin, both intact and
abraded -- with 0. 01 ml of the pesticide product,
in the solvent and at the concentration expected to
be handled by the subpopulation of interest. To the
sum of these three degrees of primary irritation
should be added eight to twelve times the number of
guinea pigs sensitized to any degree among a group
of 10 tested to account for the dermal sensitizing
potential of the pestcide product.
Oral exposure hazard is defined as 100 divided by
the rat oral LD5O (expressed in mi/kg body weight)
of the pesticide product, in the solvent and at the
concentration expected to be handled by the subpop-
ulation of interest. To obtain a range for this hazard,
one can use the mean LD 50 and the 95 percent confi-
dence interval LD 0 t s.
Inhalation exposure hazard is defined as 4, 000*
divided by the 4-hour rat LC 50 (expressed as milli-
grams per liter of air) of the pesticide product, in
the solvent and at the concentration expected to be
handled by the subpopulation of interest. To obtain
a range for this hazard, one can use the mean LC 50
and the 95 percent confidence interval LC 50 1 s.
This number was derived so that the resulting oral exposure
hazard and inhalation exposure hazard would be equivalent for an oral
LD 50 and an inhalation LC o that are equally toxic according to the
“Toxicity Categories’ tabulation in the October 16, 1974, Federal
R o gist e r .
5. 11
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Systemic poisoning hazard is defined as the sum of
oral exposure hazard, percutaneous exposure hazard*
and inhalation exposure hazard for the subpopulation
of interest. **
Death hazard is defined as one-twentieth of the sys-
temic poisoning hazard for the subpopulation of
interest. ***
For the five chronic injury hazards, each can be defined as the
expected incidence in humans empirically extrapolated from experi-
mental animal data . To empirically extrapolate from animal data,
for a particular chronic effect, the following can be done:****
*Percutaneous exposure hazard is defined as 100 divided by the
rabbit percutaneous LD5O (expressed in mi/kg body weight) of the pes-
ticide product, in the solvent and at the concentration expected to be
handled by the subpopulation of interest. To obtain a range for this
hazard, one can use the mean LD 5 O and the 95 percent confidence
interval LDSO’s. In addition, percutaneous exposure is assumed to
produce systemic poisoning.
**Systernic poisoning can occur via the oral, dermal penetration
or inhalation routes of entry. This definition assumes that for each
person experiencing irritation by oral or inhalation exposure, there
will be an additional person more severely exposed such that systemic
poisoning will result. Therefore, these two exposure hazards are
added to percutaneous exposure hazard.
***Death can occur via the oral, d ermal penetration’o nhala1ión
routes of entry just as systemic poisoning. This definition assumes
that for every 20 perèon.sexperiencing• sy ternic ppisonzng: t e,r& w i1l
be an additional person more severely exposed s.uch’that death i ill
result.
****Thjs procedure is based upon the probi.t rnode-l which haá been
used by many in carcinogen testing of pesticides. For example, see
N. Mantel and W. R. Bryan, “Safety Testing of Carcinogenic Agents,”
Journal of the National Cancer Institute , Vol. 27, 1961, pp. 455-470.
Other models which may be used include the Logistic and One-Hit
Models. For a further discussion of all three models, see Agriculture-
Environmental and Consumer Protection Appropriations for 1975,
Part 8, Food and Drug Administration, “Study of the Delaney Clause
and Other Anti-Cancer Clauses,” pp. 400-436.
5. 12
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Calculate a regression line in terms of logarithm
oral dosage (in mg/kg) vs. probitincidence from a
study yielding fractional incidence, preferably less
than 50 percent, of the chronic effect in question --
e.g., mutations -- for each of two groups of expe-
rimental animals, preferably one a rodent (e.g.,
rat) and one a primate (e. g. , monkey). These will
be lines displaced from each other on the dosage
axis and they will probably have different slopes.
Construct a “human analog” curve midway between
these two curves, and of intermediate slope.
Calculate the expected average daily intake (for all
routes of entry) for the human subpopulation of inter-
est.
Multiply this expected average daily intake by 100
and determine the incidence of the chronic effect
in question for this dosage level by using the “human
analog” curve generated above.
This incidence can be used as the incidence of the
chronic effect in question for the subpopulation of
interest.
If the “human analog” curve described above is generated using experi-
mental animals of a species which is known to metabolize small dosages
of the pesticide by the same pathways, and to approximately the same
extent, as do humans, then the safety factor of 100 would not be needed.
However, it-is unlikely that. data of thi s nature are available; thus, the
reason for using the safety factor.
The necessary data to perform the above assessments consist
of the following:
Animal test studies on rats, rabbits, monkeys, and
other species where acute and chronic injuries are
assessed when subjected to the pesticide product
using various types of exposure - - i. e. , derrual,
oral, ocular, and inhalation -- and various degrees
of exposure.
5.13
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Expected average daily intake for the various sub-
populations from exposure to the pesticide product.
For those occupationally or directly exposed, this
includes the expected daily oral, dermal, ocular,
and inhalation exposure, as well as the expected
average daily dietary intake. For those indirectly
exposed, the primary intake will be the average
daily dietary intake.
Various sources are available to obtain the above information.
The primary source is the registration process and a secondary source
is the published literature. For example, the animal test studies may
be available in the toxicology literature but should also be provided in
the information supplied by the petitioner of a pesticide product regis-
tration. Furthermore, the petitioner seeking to register a pesticide
product should provide information concerning the daily expected oral,
dermal, ocular, and inhalation exposure based upon the application
process and rate necessary for the product to be efficacious. The
expected average daily dietary intake from use of the pesticide product
can be determined based upon allowable tolerances for residues in raw
agricultural food and feed affected by the product, the expected residues
once the food is processed and the daily human diet. The allowable
tolerances must be provided in the registration process and informa-
tion to convert tolerances into expected average daily dietary intake
can be obtained through market basket studies, food processing firms,
processed food samples, and human diet studies,
Although the above definitions are not based upon intricate man-
ipulations of the experimental animal data, they do provide a means
of using these data. Since many new pesticide products will not have
“parallel” products, there is no other alternative but to use these
animal data in completing Exhibit 5.2. At the least, they should pro-
vide insights into the relative likelihood of various acute and chronic
injuries occurring. At best, if the numbers generated by these defini-
tions are coupled with any available human exposure data generated by
Section 5.2.1.1, then accurate estimates of acute and chronic injury
may be possible.
5. 14
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5. 2. 1. 3 Refinement and Quantification
of Health Damages
As indicated in the discussion in Sections 5.2. 1. 1 and 5.2. 1.2,
the health damages assessment could be as detailed as the numbers of
persons in each category incurring various types of health damages;
or simply an assessment of whether the likelihood of the hazard is
highly probable, somewhat probable or not probable at all for each
cell in Exhibit 5.2.
Once these health-damages have been assessed as outlined in
Sections 5.2. 1.1 and 5.2. 1.2, further analysis of matrix cells should
be made, if at all possible. That is, if certain segments of society
bear greater health hazards than others, then the entity “society as a
whole” should be refined to reflect these differences, perhaps using
an age-sex breakdown. In addition, if geographic differences are indi-
cated, based on application procedures, then these too should be delin-
eated if possible.
Finally, attempts will have to be made to transform these prob-
abilities and/or numbers of people most likely incurring the health
damage into monetary values. Furthermore, if these health damages
will occur sometime in .the future, as with chronic injuries, they may
be discounted in order to obtain their present value as discussed in the
theoretical presentation of Chapter 3. 0.
The proper measure of health damages is the value of reducing
the probability of ill health by a marginal amount. * This marginal
amount, however, is difficult to measure. Alternatively, the human
capital approach can he used, although theoretically incorrect accord-
ing to Dr. Lave. Nevertheless, it is logical that a lower bound on the
value of health damages is the loss in productivity due to acute and
chronic injury. *
In addition to this lost productivity, one can further quantify
health damages by measuring the cost of restoring the people who are
“sick” to good health. The difficulty of this measurement is deter-
mining the numbers of people afflicted for each unit of pollution, and,
*From personal correspondence with Dr. Lester Lave, Head,
Department of Economics, Carnegie-Mellon University.
*‘ This is only a lower bound because consumers’ surplus is not
included in such a calculation.
5. 15
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in the case of accumulation of pesticide residues within the body (i.e.,
long-term exposure), the actual amount of illness or affliction that
occurs. However, with respect to occupational health damages, both
acute and chronic, one may argue that they are a cost to the manufac-
turer, formulator, distributor, and professional applicator, and are
thus reflected in the price of their product or service. This will be
true to the extent that the employer provides medical coverage and/or
insurance for his employees, to the extent that the employees demand
higher wages or pensions due to the occupational risks involved, and
to the extent that the employer incurs some cost in employee replace-
ment, when employees are disabled or retire sooner than otherwise
expected. The refo re, for occupationally-exposed persons, health
damages may be estimated as the cost measurement for restoring
people who are sick to good health, reflected, in part, by medical
coverage insurance premiums, differential wage rates, increased
pensions, etc. If these expenses are incurred by the emp .oyer, care
must be taken to insure that they are not included twice, i.e., here
and again in the price of their product of service.
When trying to quantify health damages for a pesticide product,
all three methods of estimating the monetary values of health damages
will be considered, i. e.
• Value of reducing the probability of ill health by a
marginal amount,
• Value of lost productivity, and
• Value of remedial health care and services.
Once the data is generated outlining the health problems related to use
of a pesticide product, monetary evaluation will proceed, if possible,
using that (those) method(s) that would give the most accurate forecast
of the health implications of a pesticide product registration decision.
Numerous sources are available that have attempted to put mone-
tary values on health damages, both short-term and long-term. Listed
below are selected references where representative information may
be obtained:
• Acton, Jan, Evaluating Public Programs to Save
Lives: The Case of Heart Attacks , RAND Corp-
oration, January, 1973 (includes an extensive
bibliography).
5 16
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• American Hospital Association, Hospital Statistics .
• American Medical Association.
• Arrow, K., and M. Kurz, Public Investment, The
Rate of Return and Optimal Fiscal Policy , Baltimore,
Johns Hopkins Press, for Resources for the Future,
1970.
• Baumol, W. , “On the Social Rate of Discount,” . AER ,
Vol. 58, 1968, pp. 788-802.
• Mushkin, S., “Health as an Investment,” Journal of
Political Economy , Vol. 7, No. 5, Part 2, October,
1962.
Rice, Dorothy, Estimating the Cost of Illness ,
Health Economics Series #6, DHEW, 1966 (PHS
Publication No. 947-6).
5.2.2 Health Benefits
Health benefits from a pesticide product registration result from
the application and remaining residues of a pesticide. More specific-
ally, the majority of the health benefits accrue to the general public as
a result of increased food, feed, and fiber production, or decreased
health/disease vector control problems. Thus, health benefits can be
characterized by the following:
• .Less disease, more healthful population,
• Happier, more content people,
• More productive population, and
• Lower medical expenses.
Measurement of these characteristics is once again very difficult
to accomplish. The approach to be employed will attempt to calculate
the health damages that would result if the pesticide product registra-
tion was denied. It is likely, however, that these health damages would
be a diffe rent severity and frequency than those caused by the use of a
pesticide. Nevertheless, if the registration were denied, it is possible
that a health/disease vector control problem would go uncontrolled or
that a decreased food supply would result from decreased yields in the
absence of the pestici.de.
5. 17
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The magnitude of each of these possibilities can be estimated --
e.g., by using the agricultural submodel to determine the decreased
food supply or by using insect pest population forecasts to predict the
health/disease vector control problem. They can then be translated
into the possible health damages that they may have on the general
population. The majority of effects would most likely be increased
illness, possibly resulting in death or a chronic physiologic malfunc-
tion problem. Therefore, health benefits from use of a pesticide can
be viewed as the illness and/or death and/or chronic health problems
that would result if the pesticide was, in fact, not registered. These
damages can be assessed using similar definitions as those developed
in Section 5. 2. 1. 1, “Definition of Health Damages Based on Human
Experience Data.” In this instance, however, the effects would be
attributable to the non-use of the pesticide, rather than exposure to
the pesticide.
Monetary quantification can once again be assessed using the
procedures outlined in Section 5.2. 1. 3. However, it may be a more
formidable task as the health damages caused by the absence of using
a pesticide will probably not be as well defined as those caused by
exposure to a pesticide.
5. 3 Inputs to the Health Effects Submodel
In order to properly assess the outputs of the health effects sub-
model, various input data are requir.ed, some of which were indicated
izi Section 5.2. Tese4a a”will con’sist of the following information,
either presently iequired by the registration process or that should
be required by tKo rçgjM,rati process
• Infprrn tiOn ori( toposed) pesticide manufacturing
process,
• Formulation process for the intended registered
use,
• Distribution -- i. e., transportation and storage --
of pesticide product,
• Method(s) of application,
5. 18
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• Volume of application, i.e., frequency, rate, and
timing,
Disposal of pesticide and pesticide containers,
• Human exposure data documenting any known human
effects that have occurred,
• Toxicity, persistence, and mobility of pesticide and
pesticide product,
Mutagenicity, teratogenicity, and oncogenicity of
pesticide product in experimental animals, i.e.,
animal feed studies, reproduction studies, etc.
• Tolerances for residues in raw agricultural food
and feed,
• Probable accumulation in human tissue, i. e., bio-
logical half—life,
• Expected long-term exposure data, i.e., based on
application rate, expected dermal, ocular, oral,
and inhalation exposure for the various subpopula-.
tions directly exposed to the product. *
• Description of pest populations being controlled,
Efficacy of pesticide, and
• Numbers of people possibly exposed by subpopula-
tion groups.
The use of some of this input data has been discussed earlier and is
further discussed in the following section.
*Not presently required by registration process.
5. 19
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5.4 Relating Inputs and Outputs
of the Health Effects Submodel
Now that the inputs and outputs of this submodel have been delin-
eated, the relationships between the two will be more fully addressed.
These relationships are extremely complex as illustrated in Exhibit 5. 3,
which presents a simplified flow diagram that links the necessary
inputs to the desired outputs. Most of the terms in the exhibit have
been previously defined in this chapter or in the registration regula-
tions. For those that are still undefined, definitions appear below:
Threshold Limit Value (TLV) - - The maximum
time-weighted pesticide concentration to which
industrial workers may be exposed in the work
environment for a 7 or 8 hour day and a 40-week
week; given in milligrams of substance that may
be found per cubic meter of workroom. *
• Fatal Dose in Man - - The estimated amount of
pesticide that can kill a 70 kg man. **
• Permissible Criteria for Drinking Water in Man
—- The maximum permissible level of a pesticide
which may be found in drinking water, which, if
ingested over extended periods, is not expected
to cause harmful or adverse physiological changes
in man.
• Maximal Acceptable Daily Intake in Man - - The
maximum acceptable daily intake of pesticides in
food, which, if ingested over a lifetime, is not
expected to cause harmful or adverse physiological
changes in man. * *
*Ame rican Conference of Governmental Indust rial Hygienists.
**Hayes, W. 3., Clinical Handbook on Economic Poisons , U.S.
DHEW, P1-IS Publication No. 476, Reprint. January, 1967.
***PHS Advisory Committee on Use of the PBS Drinking Water
Standard.
****FAO/WHO, Fvah1at ion of the Toxicity of Pesticide Residues in
Food , 1965.
5.20
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( TLV 1
Data
r -— - - _
- I ______________
1 • ___________________
j
I rrcm ________ P ruIate c ..Ch, tjcal
k .gi atgn .. F fl&lf.LUe
I ti e.
Form. Manufacturing and
I Fon.tulatlcn Proir...
tra m _________________
I Agricuhiural Application Prflce.e.
I I)ubmedal Rats. Fceqoenqr 5
lOdlisti)’ Formulat i on. tots)
i i PUb1IS - V. lum, 5 Location of U 5,
I P.rmi..abl. liars
I Etc. _____
I Tr .p ulon end ______ -
I Distribution Proceasj. . Acute Injury to Oc c u .
• patie n y Eiq .eao d
_______________________ General Public:
N Front i I • Ocular Exposure H aenrd
‘ I ‘P°’ • I. . • inhalation Exposure
___________________ • Or.! Exposure H. .ud
— • Dermal Exporors Hanard
________ : :
so 4 _JHE :
I . Us. Dilution Acute
Oral L05 0 I Fatal Dc . .
Inha lation LC 50 I A Man
I • Acute Primary Fy i
and Deem .! Zrrlt t1 n .
._J o ncology in — — — — — — — -‘
I. thaJ ttOn . Dent . . ! , I
I . 1
- .1 Efficacy .1 Pc.t !cld.s L 13 s. hy
I _____________________ dupprs.doa of
Problem Pat(s)
I “ 4 Dsscrlptlon .1
—
EXHIBIT 5.3
Flaw DIagram .1 1uI .ratation Heeded for Auceaument Of
Health E1l.ct. 1*. to. PesttOfde Product R.g latp at ion Decision
I
OUTPUT:
DATA •I
Total Kwnan MOc.tsry
)i.shth Damage. 1 E,slu.doe of L_
Haslib Dantag.i
S ____ 1
Ot .ntlflcatton Procedup... •
(. Value of i . .t Produc. I
j tlVitY Health
. Medical Enp.n.e. *.asftt.
. WtilIngre.s to Pay to
[ Prev. t En . . .
!t.duc.d DIne.. Total Huzn*n Monetary
and/or Death _____J Health. 3ea.fit u. J Evaluation .t _________
From Use of L— i l fl•
____IL L. ..___
INPUT
DATA
-------
As can be seen from Exhibit 5. 3, specification of each of these relation-
ships (i.e., the arrows) would be a difficult a nd time-consuming task,
for example, when looking at chronic effects from animal test studies
and extrapolating them to possible human effects. In addition, the
available data may not allow for such an exercise.
However, this flow diagram does serve as an indication of what
information would be appropriate in reviewing a pesticide registration
decision in terms of its potential health effects to man. Furthermore,
in a gross sense, it indicates how this information relates to assess-
ing both acute and chronic health effects in man. That is, certain data
inputs are more applicable than others for assessing these effects in
man and emphasis should therefore be put on reviewing information
most applicable to achieving this goal. More specifically, emphasis
will be put on reviewing information necessary to assess health effects
as defined in Sections 5.2. 1. 1, 5.2. 1.2, and 5.2. 1.3, i.e. :
• Size of each subpopulation possibly exposed to
pesticide product.
• Human exposure to pesticide (a minimum will
involve human health effects from experimental
data generated from the R and D effort. If a
reregistration or ttparallelll pesticide product is
involved, then additional human exposure data on
known human health effects would be available).
• Acute toxicology in test animals (both quantitative
and qualitative aspects).
• Subacute toxicology in test animals (both quantita-
tive and qualitative aspects).
• Chronic toxicology in test animals (both quantita-
tive arid qualitative aspects).
• Mutagenic, oncogenic, and teratogenic effects in
test animals.
*Note that this information should be required through the data
requirements of the registration process. Presently, not all this irifor-
mation is required, as indicated previously in Section 5. 3.
5. ZZ
-------
• Expected average daily intake in man for various
subpopulations (based on tolerances for residues
in raw agricultural food and feed and additional
intake from oral, dermal, ocular, and inhalation
exposure from direct exposure to pesticide).
In addition, attempts will be made to only rely on results from an expe-
rimental species whose target organ or body system for the particular
pesticide in question reacts quantitatively and qualitatively like those
of man; or almost as satisfactory which biotransforrris the particular
pesticide quantitatively and qualitatively as does man.
5. 5 Application of the Health Effects Submodel
Sections 5. 2 through 5.4 have outline the health effects submodel
in some detail. In this section, a description is given concerning how
this model should be used.
When a new or presently registered pesticide product is being
considered for registration cr reregistration, respectively, the health
effects must be delineated for both this pesticide product and its next
best alternative. These should be done by looking at the health effects
of the new or presently registered pesticide versus no pesticide and
the health effects of the next best alternative versus no pesticide, for
a period of at least five years.
More specifically, in projecting the likely health effects of reg-
istering a new pesticide product, input data for this new pesticide pro-
duct can be used as outlined in Section 5.2. 1. 2 to obtain an indication
of the pesticide’s likely human health effects. In addition, this input
data could be compared to input data for other similar pesticide pro-
ducts already registered and used, in order to find a presently regis-
tered and used pesticide product that is parallel to the new pesticide
product seeking registration. Once this were accomplished, available
“bard” output data for the parallel registered and used pesticide product
can be assessed, using definitions in Section 5.2. 1. 1, to offer addi-
tional evidence of what the likely human health effects of registering
*The method of comparison is discussed in Chapter 2. 0 of this
report.
5.23
-------
the new pesticide product would be. In the case of a pesticide product
seeking reregistration, greater emphasis can be put on human experi-
ence data than on experimental animal data. These potential health
effects can then be outlined as in Exhibit 5. 2, followed by monetary
quantification described in Section 5.2. 1. 3, if possible.
Next, the health effecLs of the next best alternative mt st be
assessed, following the definitions set forth in Sections 5. 2. 1. 1 and
5.2. 1.2. Once again, these potential health effects can be outlined as
in Exhibit 5. 2, followed by monetary quantification described in Sec-
tion 5.2.1.3, if possible.
Then, these two sets of health effects can be compared to see
the tradeoffs involved in reregistering a pesticide product or register-
ing the new pesticide product versus its next best alternative versus
no pesticide. The ultimate assessment of the health effects data vis-
a-vis a general use or restricted use registration of the pesticide pro-
duct must lie with the Administrator of EPA. He must decide the rela-
tive importance of the health effects and what subpopulations are most
important to consider. These decisions can be made by considering
the numbers of people who may be at risk, the incidence of the heal h
effect and/or the severity of the health effect when it occurs. Thus,
if the number of people who may be at risk is the critical factor, then
chronic injury would be most important. If incidence and severity of
the effect is most important, then acute injury would take precedence.
A weighting scheme could be devised by the Administrator based upon
his views of the relative importance of each of these factors.
Assuming that a new pesticide product is registered, those that
are occupationally exposed should be monitored so that human experi-
mental data can be compiled concerning the health effects from expo-
sure to the pesticide. In addition, this should be a requirerr ient for
pesticides seeking reregistration. By insisting on this surveillance
system, any health effects likely to be incurred by the human popula-
tion will be indicated, as those who are occupationally exposed to the
pesticide would be the first to show signs of human health effects.
5.24
-------
6,0 THE ENVIRONMENTAL EFFECTS SUBMODEL
6. 1 Conceptual Structure and Assumptions
In addition to the human health effects discussed in Chapter 5. 0,
many impacts of pesticides have been detected in the environment in
contexts or at levels where they do not impinge directly on human well-
being, but they do, in fact, impinge on non-target species and wildlife
which are of valid human concern.
It is possible to fully agree with Rerie Dubos who has said that
we need to save condors not for the sake of the condors, but for the
sake of learning enough about ourselves and our social mechanisms in
order to be able to save condors. But there are more direct reasons
for developing a benefit-cost system for pesticides which incorporates
ecologic factors. A Succinct statement of this problem was provided
in 1965 by the Panel appointed by President Lyndon Johnson:
“Man is but one species living in a world with numerous
others; he dcpends on many of these others not only for
his comfort and enjoyment but for his life. Plants pro-
vide the principal mechanism whereby energy from the
sun can serve the earth’s inhabitants. In doing so, they
maintain the o’cygen content of the air and furnish the
basic habitat and food of animals and men. Microorga-
nisms -- bacteria, algae, fungi, and protozoa -- per-
form a myriad of essential functions including the puri-
fication of air, soil, and water, and the recycling of
nutrients. Animals serve man as great converters,
changing plant-stored energy into forms of food he
prefers and supplying him with a wide variety of mate-
rials: leather and furs, oils and pharmaceuticals,
ivory and pearls, bristles and wool. Many insects are
benefIcial, some as pollinators; others as predators
on harmful forms; some as makers of silk and honey.
As contributors to happiness and the quality of life,
plants and animals provide opportunities for enjoyment
of natural beauty, for hunting, fishing, gardening,
scientific study, entertainment, and the satisfaction of
our human curiosity.
6. 1
-------
In the control of pollution, plants, animals, and micro-
organisms are directly useful in two ways: First, living
things, especially microorganisms, have a capacity for
absorption and decomposition of pollutants, with result-
ing purification of air, water and soil. Second, many
species of organisms, each with its own particular
range of sensitivity to each pollutant, stand as ready-
made systems for environmental bioassay and monitor-
ing, and for warnings of danger to man and his environ-
ment. Because living things are interdependent and
interacting, they form a complex, dynamic system.
Tampering with this system may be desirable and
necessary, as in agriculture, which involves artificial
manipulation of the balances of nature on a huge scale.
But such tampering often produces unexpected results,,
or side effects, and these are sometimes very damaging.
Many of the effects of pollution fall into this category.
The statement by the Environmental Pollution Panel provides a
key to the reasons for valuing plants, insects, and wildlife. However,
it also leaves a large gap in the development of specific benefits and
costs for detailed analysis of pesticide impacts. Pesticide effects on
non-target species are of valid concern to society, and, in gneral,
should be accounted as social costs incurred in the course of pesticide
use. More specifically, these effects are generally seen to reduce the
population of the non-target species, in some cases on a relatively
large scale. The biological features of the population are generally
disrupted from what they were previously, and this disruption is pre-
sumed to be outside the intentions of society, by the definition of the
term, Itnon_target species.”
The long-term effects of chemical pesticides on non-target spe-
cies are unpredictable, and some evidence indicates that they might
actually be beneficial * to small groups of the non-target population.
*Environmental Pollution Panel, President’s Science Advisory
Committee, D. F. Hornig, Chairman, Restoring the Quality of Our
Environment , Supe rintendant of Documents, November, 1965.
**f-iolden, A. V ., “Effects of Pesticides on Fish,” in C. A.
Edwards, ed., Environmental Pollution by Pesticides , London,
Plenum Press, 1973, p. Z39.
6. 2
-------
Thus, when some fish in a crowded pond or stream are killed by pesti-
cides, the survivors are seen to grow larger. These benefits are
thought to be transient, however, and benefits of this type will not be
analyzed in detail. The killing of some members of the non-target
population, although presumably “weaker” specimens, will be defined
as a cost to be borne, usually by society at-large, although sometimes
by subgroups within society, such as sportsmen, or wildlife enthusiasts.
The time span over which the costs of the above effects are to be
borne is another important factor. The time period of these effects
varies with the type of pesticide, and with the non-target species which
bears the effects. In the present analysis, these effects are assumed
to be gradually cumulative for a period of five years. During this
period, residues of pesticides applied are assumed to gradually build
up in soil, and in certain species, even though the pesticide ingredients
do decay at varying rates as they filter through the environment.
Although this accumulation has been shown to have biological limits,
no matter how much pesticide is used, for certain pesticides, in cer-
tain species, the present analysis will assume that the level of resi-
due in the entire biomass of a given species will continue to increase
gradually over a five-year period. This assumption is more accept-
able when the pesticide in question is a new registration, rather than
a reregistration.
The overall approach of the environmental submodel is to make
many simplifying assumptions in order to achieve a completely inte-
grated cost structure which interconnects the rate of pesticide applica-
tion with the incremental effects each new amount of a specific pesti-
cide produces. Many of these simplifying assumptions are not justifi-
able in the light of currently available hydrologic, ecologic, and other
models. These sophisticated models typically use large amounts of
data and mathematical formulations which are based on sound chemical
and biologic theory, ** in order to assess in detail all of the factors
Edwards, C. A. , Persistent Pesticides in the Environment ,
Cleveland, Chemical Rubber Company Press, 1973, p. 95.
*Robiason, J. , “Dynamics of Pesticide Residues in the Environ-
ment, “in C. A. Edwards, ed. , . cit., p. 459; and Crawford, N. H.
and A. S. Donigan, Jr., Pesticide Transport and Runoff Model for
Agricultural Lands , Washington, D. C. , Superintendant of Documents,
1973 (EPA-660/2-74-013, Southeast Environmental Research Labora-
tory, Athens, Georgia).
6. 3
-------
and phenomena involved in determining the final effects of a certain
amount of pesticide application. In the light of these mo’iels, and their
complexity, the simplifying assumptions included in the present analy-
sis cannot be justified indefinitely. These assumptions are used for
the present in order to present an overall benefit-cost structure and to
illustrate all of the types of calculations which must be linked together
(Exhibit 6. 1). But eventually, the complex models referenced, and
others, will necessarily be substituted in order to achieve theoretical
soundness and much improved accuracy.
6.2 Accumulation and Degradation Processes
The purpose of this component of the environmental submodel is
to calculate three variables needed for subsequent assessment of effects
on non-target species:
• Amounts of specific pesticides applied per agricultural
acre at regional, and if needed, state, levels of detail;
• Decay rates of these pesticides in the soil; and
• Runoff rates, or rates at which these pesticides enter
the water.
As noted above, these calculations will be based on simplifying assump-
tions, and the algorithms presented can be replaced eventually by more
complex mathematical models.
One of the simplifying assumptions concerns the fate of pesticides
once they have been washed into bodies of water near the agricultural
fields. Most of the pesticides used by farmers are non-soluble in
water, and the only persistence they have before sinking to the bottom
is due to the turbulence of flowing water, or water which is agitated in
some other way.*
*Edwards, C. A. • ‘Pesticide Residues in Soil and Water,” in
C. A. Edwards, ed., cit., pp. 447 ff.
6. 4
-------
EXHIBIT 6.1: Calculations Needed for Environmental Effects Submodel
Amount of non-
agricultural
use
C ’
çyi
-------
Therefore, the pesticides are not seen to accumulate from year
to year in water, as they are known to do in soil. Even though these
chemicals do accumulate in soil, they are broken down by microbes in
the soil, and by chemical processes. Although these decay processes
are not linear, some data suggest that the rate of decay resembles a
straight line over some ranges, especially after the half-life point is
reached. * In other words, a series of assumptions is used to avoid
the use of complex runoff and meteorologic models. The first step in
achieving these decay and runoff rates is to calculate the application
rate per acre for specific pesticides.
6.2,1 Application Rates Per Acre
A separate algorithm permits the independent calculation of
pounds and acres treated, since proportions are available from Eichers,
etal. * This type of calculation is desirable since the ratio of pounds
applied to acres treated is an important variable in soil and water con-
centrations. Arbitrary evaluations of this ratio, such as the use of
USDA or individual state recommended values, could lead to unreliable
estimates of environmental pesticide residues.
Although various data re available on pesticides by groups,
there are very few sources of data on specific pesticides used at
regional and state levels. The USDA-ERS surveys of 1966 and 1971
are one such source (see Exhibit 6. 2 for sample data from the 1966
survey). The data from these surveys provide two kinds of ratios for
each of two years:
— ‘ij — pounds of pesticide i used in region j
‘3 — P 1 — total pounds of pesticide i in all regions
and: acres treated in region j by pesticide i
C 13 a all acres treated in region j by all pesticides
Thus, d 1 is a ratio of pounds for a specific pesticide, and cjj is a ratio
of acres for a specific region. The reason for defining these ratios as
*Edwards, C. A., Persistent Pesticides in the Environment , .
cit., p. 16.
**Eichers, T., et al. , Quantities of Pesticides Used by Farmers
in 1966 , Washington, D.C., Supcrintcndent of Documents, ERS No. 179,
April, 1970.
6.6
-------
they are defined .; iove is to enable the use of existing data on produc-
tion of a given pesticide by disaggregating these data for specific pes-
ticides and regions.
For example, the data from the Pesticide Review on pounds of
pesticides produced is available for specific products, but not for
states and regions (see Exhibit 6. 3). Multiplying the total national
amount of a specific pesticide sold for agricultural use by the factor
will give the amount of pounds applied in region j. Similarly, the
Pesticide Review gives data on the acres of crops treated by pesticides
for states and regions (see Exhibit 6. 4). Applying the factors Cjj to
thes.e acreage data will tell how many acres were treated with each
specific pesticide. In summary, the required algorithms can be
written as summarized in Exhibit 6. 5.
For either or both of the two years, of course, the pounds per
acre could be obtained more simply from the USDA survey data. The
procedure shown in Exhibit 6. 5, however, enables the forecast of pes-
ticides in proportion to each other. Before applying the proportions
for pounds (d 1 ) , it is necessary to ensure that total pounds are agri-
cultural data. Ajustments such as those shown in Exhibit 6. 6 may be
needed.
6. 2. 2 Decay Rates in Soil
The algorithm for calculating decay rates in soil is shown in
Exhibit 6. 7. The procedure shown actually calculates the coefficients
needed to reduce some amount of pesticides, either pounds per acre,
or parts per million, over a multi-year period. These coefficients
must be applied annually to the total amount of pesticides for that year,
including previous residue and new applications. Although some data
exist for historical residue levels, such levels would be irrelevant
for a new pesticide applying for registration. In such a case, esti-
mates of each year’s application from Section 6. 1 above, or from the
parallel chemical technique would be required. Section 6. 1 above
shows how to estimate pounds applied per acre if production in pounds
is known. Manufacturer 1 s forecasts of production amounts would
enable the use of this type of estimation.
*Edwards, C. A., . cit., Tables 1 and Z, pp. 8 ff.
6.7
-------
Tahh’ 24,—-Quintitirs of selected herbicidee uied on crops, by regions, United States, 1966 , /
Type o( herbietde product a’
Po tnd3 of
ncdvc ’ ti rci(cnto
North—
‘Lnke Cur,. N,.rthcrn
Stntea n i t t ’i t .
App ’i—
Soutit—
c ant
P c Southern ° “
Statoa Plainc lain
Pacific : Totil
- 1,000 r c .iiid
Inorganic erb c dc - 1,074 7 132 126 363 251 287 260 838 3.318
0r nn1c Ibtc deo:
Arsontcm la 17 ——— 20 70 6C8 147 ——— 4 866
Pheu’c.xy
2,6—D 721 2,700 9,827 10,376 1,154 302 450 3,590 4,202 6,191 39,313
2,4,5—T 6 145 82 61 38 IC 168 148 3 12 653
25 326 147 855 2 49 -—— 90 98 14 1,612
Othcr pl.vnuxy 4 3 15 0 5 240 3 837 364 1,657
Total phencucy 756 3,174 10,071 11,298 1,199 601 001 3,834 3,140 6,561 43,235
Phenyl urca
Diuro : 87 4 22 -* 70 104 513 254 36 334 1.624
694 336 252 16 20 32 73 1,425
Other phenyl urc 18 16 23 —-- 62 282 90 38 1 114 644
Total plwnvl ure 799 336 297 16 152 418 678 292 37 648 3,693
Propnch lo —-— 318 1,893 32 ——— 2,269
Pro an11 --— ——— -—— ——— ——— ——— 1,453 1,136 ——— ——— 2,539
? tPA 6 49 690 3 110 3 133 999
Total aznkle 6 367 2,585 55 110 3 1,395 1,136 ——— ——— 5,857
Csrt ’n ’ ,.ite,i:
cirr a . 3 irc 72 21 295 1 6 1 79 17 663 1,153
CI AA 36 1,062 3,$1 152 ——— ——— •—— ——— .—— ——— 4 .898
01 iwr ciii I ’n ,int 1’. l 71)3 (t(’I I ’ll 1,07 502 90 353 1,065 3,976
Total cirhaniati’ : 127 1,76( ’ /s.6’i7 326 413 503 169 ——— 370 1,708 10,027
Dlnltro gru up 903 8 348 91 19 1,276 4 06 26 2,046 4,962
EXHIBIT 6.2
-------
EXHIBIT 6.2 (continued)
Table 24.--Qu.ntitiea of selected herbicide. used on crop., by regions, United States, 1966 .IJ——Continued
Pounds of active ingredient.
Type of herbicide product V North— Lake • Corn Northern App.—
esat States Belt Plain. lachton
South— Delta Southern Noun—
east Statea Plain. : Paci ic Tot.
1,000
pounds
Triiizincs:
Atr zlne 2,289 4,722 9,978 2,285 2,492
519 157 334 97 622 23,495
Propazine ——- —-— --— 14 —-—
—-— 31 530 5 —-— 580
Other triezinca 12 8 160 ——— 7
-—— 3/ ——— ——— 6 193
Total triazine : 2,301 4,730 10,138 2,299 2,499
519 188 864 102 628 24,268
Benroic:
2,3 ,6-TBA : ——- 155 2,590 137 —-
— —— ——— -—— 2 54 2,938
knl1i n ——- 463 3,101 140 32
3 26 ——— ——— ——— 3,765
Dicataba ——— 5 37 54 —-—
3/ ——— -—— 57 69 222
Total bcnzoics : ——— 623 5,728 331 32
3 26 ——— 59 123 6,925
Other rganics:
Trifluralin.. 50 148 988 58 499
814 1,634 572 14? 274 5,16 ! .
Othurs 194 409 529 279 127
363 352 349 1R3 .1,300 4,085
Total other organic. 244 557 1,517 337 626
1,177 1,986 921 330 1,574 9,269
Total organic herbicide, (not
including pctrolcurn) : 5,136 11,581 35,348 14,731 5,245
4,570 5,855 7,260 6,064 13,292 109,102
Tc.tal hcrbjcide, (not including:
petroleun) ; 6,210 11,588 35,480 14,877 5,245
4,933 6,106 7,547 6,304 14,130 112,420
Pctro l un 3,208 2,468 643 ——— 763
25,820 2,278 3,279 786 28,386 67,233
Total herhlcidc .a(including
petroleum) 9,418 14,056 36,123 14,877 6,010
30,753 8,384 10,826 7,090 42,516 180,053
/ Does not include Alaska and Hawaii.
2/ Hay include use for purposes other than as h ..rbicidas.
, / Less than 500 pounds.
-------
EXHISIT 6. 2 (conttinied)
Tibi. 2$.——Acrei of specified crop. treatcd with selected herbicides. United Stat.., 1966 j/
type c.f herbicide
product
V
.
Acre.
trc ted
:
North Lnke Corn : App.—
enot Stntes Belt Plntn s lechian
South— Vo lta Sofithorn l ’iaun—
es stntes P1 ins
: Pietlic : Total
;
1 00Q aere _ . ’
2nor ,snic herbictde.
179 6
57 56 ——— 285 116 93 33 294 1.121
0r .,ite horbLc1d ss
Ar n1c.1i
30 . . — 15 110 614 115
101 1,085
Phony 1.
Di iro
I. t nu ran
Oth ,zr phonyl urc
57 4 43
95 4 412
33 1 28
Pr ’pcchto
?rup,ni 1
181. 1,362
5 36 352
86 —-— ——— 3 --— --— --- 1,632
462 473 — -— ——— 935
38 139 6 125 -—— ——— - . — 921
C1.PCind IPC
CDM
Othor c.rban st.s
9 32 360
6 711 2.910
6 312 149
2 43 6 115 —-— 3 165 735
94 --— -—- --- --— --- --— 3,721
171 191 198 51 ——— 281 746 2,105
Dinitro ;ro i
237 109
92 192 159 293 10 91. 34 292 1,511
0
thi ’noxy:
2,4-0 :
2,4,3—T
896
69
5,274 14,592
63 42
19,116
120
1,609
76
304
20
320
213
2,411
334
7,664
22
4,499
26
36,893
1,563
38
855
216
1,552
2
26
--—
1.24
82
1.6
2,911
0t ’er phenoxy :
10
35
74
701
21.
54
26
.-
140
34
1,095
203 149 773 312 14 273 1,828
22 24 33 219 --- —-• —-— 1,264
78 56 1.33 48 3 26 426
Sec footnotes at end of table.
-------
EXHIBIT 6. 2 (continued)
Table 26. -—Acres of specified crops treated with selected herbicides, United States, 1966 l/——Continued
Acres treated
Type of herbicide product 2/ . : : :
— , horth- Lake Corn horthern Appa- South- Delta Southern floun-
east StatO s : Belt Plains lachiart east states: Pleirs : ta : Total
1,000 acre
TrLaz nes:
1.316 3,139 6,224 1,771 1,543 35C 142 174 71 248 14,978
rropozin 11 —— — 19 412 5 ——— 447
0th r triazines 14 15 71 ——— 17 ——— 6 ——— ——— 7 130
Bcnzoic:
2,3,6—TEA --— 80 1,380 103 -—— -—- ——— ——- 3! 64 1,627
——— 445 3,372 202 41 2 24 ——- ——— -—— 4,086
Dicamb 55 80 488 -—— 19 ——— 424 567 1,633
Other or entcs
Trif1tr 1i : 7 159 1,073 90 886 947 2,207 989 240 283 6,953
Others : 66 328 384 192 120 327 255 250 88 189 2,199
Petrolewn 93 105 109 ——- 82 3/ 80 90 37 58 654
1/ Does not include Alaska and Hawaii.
2/ May include use for purposes other than os I erbicides.
3/ Less then 500 acres.
-------
EXHIBIT 6.2 (continued)
Table 29..—Qusi ttttc. of selected types of instctteides used on crops, by regions, United States, 1966 f
Type
of
insecticide
product
‘
:
:
North—
Pounds cf scttv* ingredients
Lake Corn Northern Appa— South— Delta
: Belt Plain. ’ l.ehian e.*t State.
Southern Xoun-
Plains • tam
Pacific Total.
1.000 nound
Irorganic insecticide 2,367
Jota,icels end biological.
$ynthcttc er on1c io,eceicL4 s:
0r nn chlorLneo:
Lindeo
668 915 4 1,027
2 .—— 1 —-— 3 ——— 36 42
729 ——— ——— ——— 63 5,773
45
.-.
56
s.--
18
• -
1
.--
2
9
169
46
/
1,961
53
—--
40
-——
9
—-—
395
2,01.6
189
108
198
3
1,145
723
40
347
13
86
2,854
734
381
430
5
361
48
39
f
1,837
249
10,850
200
7,120
6
2,702
———
1,188
163
1,060
4
26,321
1,056
5
1
43
-——
48
97
---
1,412
39
---
14
4
294
7
23
67
14
260
433
13
1
34
3.
164
3/
3
62
—-—
/
11
735
1.513
704
30
717
12 973
416
333
79
14
18
110
61
14,751
13
154
13.9
.— —
11
74
22
———
43.
18
452
94
.32
2
--—
7
56
•———
28
56
487
788
4
111
403
7
2,521
13,740
7,176
4,982
1,420
560
30,924
3
1
--—
—-—
20
48
52
——-
——-
146
270
1,761 15,399
Tt’C (ODD)
03?
1 uthoxych1or
Nn r tn—
1 eptach1
DieL r ’
A1dr
Cb lc’rdenc
tndos$fa
Tc phcne
Other
Totci or a—och1orince
1,542
Orgnr.ophoepho rua
O isu1foto
100
293
350
429
368
11
11
24
298
60
1,944
lidrin
Mot y1 parathion
———
3.
———
———
74
———
2
8
416
7
2,224
220
3,090
713
1,949
878
41
31
194
1,857
7,991
Parathion
287
386
235
26
690
143
1,350
54
356
618
1,177
323
263
674
2,237
188
298
1,199
1,544
875
8,437
4,286
Daz’nc ,
91
610
1,836
1,496
298
19
149
43
1,019
3,561
T; c) 1,rfon
2
———
•——
1
4
———
11
205
717
54
994
A:inpho -.ethy1
Echio :
575
24
112
7
82
329
———
9
127
2
24
1,153
22
73
7
20
91
18
403
369
1,473
2,004
Othera
176
93
64
49
113
381
21
16
166
952
2,031
484 6,358 26,326 3.6,840 8,329 3,096 2,444 82,779
Total organophosphoru : 1,642
1,406 3,568
3,390 2,310 5,319 4,334 3,359 3,749 5,501 36,578
-------
EXHIBIT 6.2 (continued)
TabI. 29.—— uantities of selected types of insecticides used on crops, by regions, United Stbtes, 1966 /——Continued
Pounds of ective ingredients
Type of insecticide product 2/ : : : :
— North- Lake Corn Northern Appa- South— Dclt Southern Noun—
Pacific Total
east : States Salt : Plains : Iachia n : east States Plains :
1,000 poi nd
Carbamates:
Carbaryl : 1,384 705 1,283 302 l,05 3,033 633 2,293 56 1,096 11,840
Others : 47 51 79 322 —-— 24 ——— ——— 8 —-— 531
Total carbarnatea 1,431 756 l,3ó2 624 1,055 3,057 633 2,293 64 1,096 12,371
Other ayr.thccic organics : ——- --— 12 ——— —-- ——— ——— ——- -—— 11 23
Total Synthetic organic : 4,615 3,923 20,541 4,498 9,723 34,702 21,807 15,981 6,909 9,052 131,751
Total insecticides (not
including petroleum) 6,964 4,591 21,457 4,502 10,750 35,434 21,807 15,981 6,909 9,151 137.566
Petroleum 1,922 6 23 ——— 489 6,879 618 43 ——— 1,177 11,157
Total insecticides : 8,906 4,597 21,480 4,502 11,239 42,313 22,425 16,024 6,909 10,328 148,753
1/ Does not include Alaska nd
2/ Na’j include use for purposes other than as insecticides.
3/ Less than 500 poundø.
-------
EXHIBIT 6. 2 (continued)
Table 31.—-Acree of sti crops treated with selected insecticides, by regions, United States, 1966 1/
Actc* treated
Type of insecticide produce 2/ North- Lake Corn Northern App - South- Delta Southern Moun-
cast States 1 chian : cast States Plains : t in POC ftc : Total
1,000 acre
Inorganic ingecticidca 129 89 55 31 79 105 ——— ——— ——. 6 463
Botanicali and biologicals : 10 ——— 24 ——— 1 1 ——— 5 1 92 134
Synthetic organic Insecticides:
Organoch lcr.ne a:
Linda c 64 132 216 40 17 239 7 164 28 15 922
——— -—— -—— ——— 3 39 183 ——— ——— ——— 225
ZE (OLO) : 82 29 35 3 476 171 7 8 4 24 839
S - 325 223 350 81 766 2,360 1,785 1,206 430 48]. 8,057
t etr.oxvch1or : 402 3 45 1. 212 84 26 ——— 154 1 923
Erdrir. : 12 ‘-—— ——— ——— 47 31 358 71 3 ——— 522
Erpt achlo : 21 150 1,713 135 3 14 43 6 11 2 2,103
Die1drt : 57 61 137 22 98 81 6 132 122 14 730
AIdrin 16 832 11,914 402 345 61 26 13 140 72 13,821
Ch1ordo, e : 13 116 104 ——— 14 119 43 —-— 36 27 472
ndos1fan : 92 22 25 .—— 7 85 ——— 4 25 292 55
: 2 13 307 8 544 1,553 1,233 1,304 212 202 5,383
Other 7 12 ——— ——— 9 90 90 ——— ——— 267 475
Grg. noics hores:
Dt a’iifuC o : 106 138 339 405 433 Ii 38 217 245 76 Z,C08
Bidri : ——- -—— -—— —— — 43 61 368 716 143 99 1,426
h thy1 porethion : I ——— 9 7 179 398 1,949 1,185 115 188 4,511
407 269 910 1,115 295 456 1S 1 1,389 416 694 6,140
liftior. : 285 13 151. 81 285 1 ’ 173 267 420 379 2,230
D la:inon : 226 615 1,626 1,510 369 31 50 ——— 99 429 5,153
Trichiorfon : I ——— —— 4 9 ——— 27 206 275 14 536
4zinp)us cthy1 426 141 51 ——— 98 43 28 14 66 323 1,190
Et io 31 13 130 10 1 470 26 5 20 123 889
0th ra : 203 49 90 49 95 224 117 38 156 1,118 2,139
Carhostes:
Carb ry1 541 178 298 181 516 780 175 579 53 449 3,750
Othert : 64 92 151 775 ——— 23 ——— ——— 5 ——— 1,110
Other synthetic orgonics : ——— -—— 3/ ——- —.- .— . 33 33
Pctro lewr : 70 12 10 ——— 115 172 56 3/ ——— 32 467
1/ Docc not in 1udc Alaska .nd llswoii. 2/ May intludc eec f r purposes other than as ineceticidea. 3/ Less then 500 pounds.
Source: Eichers, T., et al. Quantities of Pesticides Used by Farmers in 1966 , Agricultural Economic
Repor’;No. 179, USDA, ERS, 1970.
-------
EXHIBIT 6. 3
labia 2 ,—-Psac .icj ti cheatcala: Poducrion by ciaase., ‘lotted States, 1967-72
Pesticide
1967
1968
1969
1970
1971
1972 1!
1.000
pown.ia
1,005
pounds
3,000
pound.
1,000
pounds
1,000
pOunds
0,000
pounds
ides
Copper nap benate
Copper solfat 21
Dithioc.arbatic acid isits
Ferha.
Zineb
Netcury fungicides
Psot ch1orohenn1 (PCP) 3/
2,4 ,5- tich1oto heno0 and salts .,.
Other ori&r.ic fungicides
Total 6!
3.473
33.59
3/
2,331
1,361
3,055
912
44,239
5, 1 3z .
63,269
1,718
37,192
V
1,900
2,000 4/
3,061
0,4.48
48,575
28066
66,793
1,545
42,072
3!
1,500 4/
1,938
2,500 4/
940
45,988
3/
85,607
1.730
28,768
39,381.
3 /
3/
3/
1,114
47,170
3 /
30,307
1,695
31,112
,1iO
3/
3/
1
601
50,877
j
60,875
2,206
28,064
40,438
3/
3f
I
547
49,704
3/
49,610
177,856
190,773
182,091
168,470
180, 270
170,569
Herbicides
3,4-5 acid 7/
2,4-0 acid, esters, and salts
, , a niuq salts
Neisic hydraztde
ethantarsonic acid salts
Ptsanyi aercuric acetate (P 9 ( A) 8/ ..
8ilscr
Sodiot, chlerate 9/
2 ,4,S-T acid V
2,4,5-1 acid, eater ., end ss )ta ..,
Other orzen2c herbicides
Total
(77,139)
83,750
3/
3!
518
21
30,000
(14,552)
27,359
506,759
(79,263)
94,116
3/
3/
3/
582
3J
30,000
(17,530)
42,542
235,541
(47,077)
56,998
3/
2,771
3/
534
1,591
30,000
(4,999)
11,626
268,238
(43,576)
3/
. 21
3,271
30,454
457
2,016
30,000
21
12,335
312, 1.32
/
3 1
3/
3/
24,476
337
3/
30,000
2/
21
404,036
V
V
6,472
30,698
307
3!
30,000
. 21
.2/
416,141
439,965
499,574 10/
423,640
434,241
456,649
481,618
Insecticides, f . igant ,, rodenticides 11/
£ldrin—tosaphesse group 12/
Calciun arsenate
541 .. ... .
Dib r .ch1oroprepane
Laad arsenate
Netbyl brenice 13/
Organoph-osphotus inaecUcides 21 ..
NethyI parathion
P C Oathio
Other
019cr Organtc insecticides
Total
Grand total
120,363
2,040
103,411
5,240
5,952
19,665
2/
33,344
11,361
2/
202,600
115,974
3,398
139,401
7,887
9,016 -
20,454
2/
38,363
20, .000
. 21
227,326
107,3)1
1,138
123,003
8,611
9,204
20,033
21
50,572
21
2/
260,892
88.641
1,144
59,316
.2/
4,056
21,0.47
(132,496)
41,353
13,259
75,886
188,632
1)6,264
940
2/
2/
6,168
2/
(138,185)
37,226
3/
100,959
303,261
141.8.58
3/
2/
2/
24,633
(160,642)
51,076
2/
109,564
136,442
503,796
581,619
580,854
495,532
564,818
569,1.57
1,121,447 jç i
1,271,986 10/
1,186,815 I 1,096.143 10/
1,203,937
‘1,221,344
1/ Prelien.nery.
2/ Shipments by producers to a 5riculture (including for use as a ninor plant outrient).
2/ VithteZd to avojd djecIcrcre. 8 igure i ciuded in iotals.
4/ tltisated,
SI Not only a wood preservative for wood rot control but also a htt-bicidc and desinccnt.
6/ Sulfur net included say anou t to 150 i1lieo pounds.
1/ !tg reS to parertheec, e7resent doplication hut are ineloded in totals to be cosparable with the 1971 and 1.972 total ,,
8/ 4lso a fungicide.
91 Latisated shipents to producers of herbicides and dtfoliasstc.
10/ htvf ed,
3j/ loclodes a unall quantity of ,‘othetic soil co ditio ers; .loes not include the fueJ 5 a.nts cirbon tetrachloride,
carbon dl ul .de, ethyjeot dtbron ce, a nd ethylene ilcilor-ide, which have sacy other user; nor does it include
par ich1o -obe ’ ,zene (classed by the lao-lU Co .lcvion so an intesnediele) or inorganic rodersticides.
L lociruies aidrin, chlc ’rdeoe, dtoldntn, amino, heptaehlor, Strobsne . lOG tOXC?hOOt .
.121 Ut.t$a t 5cr control of both insects and weeds.
Tariff Co iss (o ,, bureau of the Csoaaa, bureau of Ptinea, and chosicel industry.
Source: Fowler, D. ,L., and J. Mahan (eds.), Pesticide Review, J973
Washington, D.C., USDA, Agriculture Stabilization and Conservation
Service, 1974.
6. 15
-------
EXIIfl3IT 6.4
fnbt.I t 3.. .2. ’oL - Un. ‘t.ri’ tr ‘r273 ui .) ‘in 1k . a ”.t ,in4 ,ri’U1ry res —d L 3 13 ‘,oI an’ 3’* ’e. • UALtn ’i 3 s ’q , :‘$9
P1_so i 3i t ’rn
Vur. ) 1& e:n’nl V o,t ron’, ’,L It
11
ui I Oth.r Crc;.
________ _____ — —-——- . ‘ - ,-——- ‘-—
£ 2 i :J . ’2 r A”-. ‘i.U’r, Ar--. cL .rn ° ‘ “ '° .Unri 3 -rj j,
,y, ’v ’ 5I,’2’7 .‘7, 1)1 5,317,73 ) 12),,) 2 ’,71)1 235,333 L , ’r 1, 3 L I 731 T), .29 7 ’Y3 ,179 5,132,211 155 ,k11 5335,763
3’. ‘31 1,3(1’ t ’ ) 1,070
5,’,: ‘17 31,3,313 51”, 1’ . •6.’ , ’) ’”1 162,.’)’ i’l,571 2 5,113’ 35,73 . . 217 , ’.31 12,013 ‘ 01 325,637 2,5.8,71 .1 , 2711,51.2 5 , ” ’ , 5 )5
3 71 , il 71 1, , 9 7) 3, 31 7 3 1), 1) 1, ) 3’?’? 157 31 “ “3’ )5 14 502 11211 ‘)l. 1
C. ,. —ri $ 3T ) “ 3 ) 1 3 7 ‘‘, 5 33 rT U I 153 131 2 “1), .‘ 1,) 1) 1 5 3) 3 3
6, 1 ’ ) 3 - , 3 1 ‘ ‘ ‘ 1 1 , 373 7 3’ 5 10 3 11, 3 7
1 . ” I ‘ •3 ‘. 3 •3, ,“, 13 12, 153 ) ),n : 31 ).,T37 5,735 1?, I 353,535 k , ,77 12 . ’ 1
‘.53 3,’. .1 . ‘5 ,Jfl f 1,113 I7,’ ,’ 3 , ‘ 1 ’3 2,. .5 3,’ 1,13.3 197,1)5 771,112 3,31’, 3’), 97
rot’ & ii i ’. ‘ ) 1 1 3’ 3 1 1 33 1 1 3 , 6 1• ) 3 , 413 ,,r, i6’ 3/) 1. 3 S ‘V - ’0 55,, 1) “ 1333
9 , ” 1 53’, ‘ I I .fl . , ’ 13”’’)) , ‘,‘‘, ) ‘j ,3.. f l’. ’, ’ 5 ) 1,51,1,33 1,,1 , ’ ,33 L5, ”fl7 1,)9,13 .. A 2,17’; “ ,,2 ’ 1i,3 ’33 2)l,”.2 3.71’, ‘.1
0 ,_ ’ ’ , ‘,31i ‘ ‘ ‘ “ “ ‘ 33 ‘‘3 ,•, ‘ I ‘, ‘l’l, 2 ‘5’ ’i ‘3’’- ‘ 32 5 25113) 733’”0) 5’J ’ 1(’,) 23,3.1’; ‘fl .3
0.3 A’) )f7 4) 2 1 3 3 1 7 1 /) 1 3 7’ , ‘ 5 H 3 l I 111 117 ‘3 ‘331 327 3 13’,, .13 .3 ’ 31” -‘3
XIII , .1 . .32. ‘51 15,1)3 1, ‘. ‘. ‘, ‘ 12.1’, V 3’ 1,25”, ”1 58. 15 1)1)3 ) ‘13,31)1 151,127 55,22 1,131,73’ ) 9,222,5 1 .) .J, 317.1,12 5 <3,52’, 2• . ‘3
1rs17 . ’ i . 52,217 21,1 ‘ 3,2 , -. 3, I. £7 ..‘r ,’, 1)1)13?) 117, 37. 5),1’57 .3 :, 3 33,1)1 114,’3’1. 1,377,97., 113,3173,177 31,7,5 :3’, ::j
3 lj 1 . 3 I 3) J ‘.0 r I 7 3 3— 213’ 3 3 771 7 7 16 3 tr 1” 77 5
Inn . . .. 3 , 1 .‘ 111.’” 1 ,’ 7, fl 3.’ .7’ ’ 1 ,1:’’.’ ‘‘“ f l ’ 1’ 3 5’,,) II I ), ;7 .‘ , ‘. . ‘ ) 151, . ‘2 (1,,’.’ .) ,‘ , ‘.11,177 6, .27,2’) 51.773 5, , ‘J
55 3 , 1 II 3 II I ’ .1 ( / 11 ‘ 13’ ‘ 71.7 1 5 . .
3 1 3 3) 1 1 1 1/ 3311 2 11 2I . 3) 1 3) 1, 57)” 71)1’, 1
0” ‘ 5,315 , 1 , ,’,: , 1,33’.,?’. 77 ,) 1))) (5)’. 73, ‘ I33 5;;’; 1’) ..’) 5,’. )) fl ’I.,L. . ”l 3,1)1,187 67,2.1 5.3.177
16 . . 1 3 3 . - I ‘3’ I. 13) fl 1 13) “7 5 5 17 21 .4, 19 1 33’. 533 .5 3 31 ,‘3
1,171 5, 75) , 3 5 ,5 ’l s 4)1,3,23 5,3,83.2 ‘353 51, ” . ) ’? 12,13., 5,’’, ‘ 13-5 2,1313 35,:’52 36,2’7 3,217 33, 325
0” )@1’)1 ,1’ ., Al 713 77 )2’ ,fl 33.2,’;, 5,5’3, 112 1.311,132, -4.1,21” 231., )1’8 141,1)31 3,)’, ‘‘2 3,3’..-’) 33,23) 3 ,P3 ,15l 3,3331,735 31, (‘A) 237, .35
i$,152 31,’.’) 1,) ‘.1, 311, I 3,533,531. 715,1.73 2 1 . ,l’39 10(1,0’). 97,’ll 5-2.1.25 53,135 103,139 4,502,1)’7 1 21,55.1)717 96,3 ’i 31 ,”77
no)..) 7$ 7,2 ” ) 55,313 1, 5’, , 1 . 1513,7 73 1.53, ))1 ) 11,151 10’,372 61,91’. 317,21)1 85,771 175,133 2717, r:1 1’ ,, )35,°,,31 775,5.77 2,53.n, ’
“3 “. 13’ 2) 1 1. 1 5 13.3 r 1 17 I ) ) “, 11 5 ‘7i I 3. 1 37 ’7 )13 3 1.1, 3’) 15 0,,.. 375 US 772 41.3 -
is,, , , .n ,n ‘A i 3’ 3 <17 7 ri. 3i5 I , ,) 1 Sfl 17 1,1 1 1.. 1, 1’ 13 fi 2 3’) 1 . 3 2 717 735 113 n. .- “
33,3 .‘525.; ” . 2,3,3.1 o, ’J ) ),5’fl 1,319,1’ ) L .13,’,IL 2313, 155 57,751 12’). ‘-33 387, ’ -s” . ‘17), 127 3,3’,1,2,411 1.0,1.13.5<37 31,77 ) 87, 71
63,111 L ,1L3 25,7 ‘, 2’’1,’)2 533312 241 3,331 1,5,74 8,75.’) 1,535 9,1.12 1’3,)53 53,5323 1.3,))’. 6 i, :fl
P. — 0 ,027* . ’II ) ’I 5531 1,3”1. 7,277 1634,7-2 22.34(1 ) , I . •_‘2. 1,377 11J,U 271 111 L’,1 ’} 1 - rr, 6 2o 1,25) 13,331)
:— - , 1,737 17,73.” 12 ’ ),Tfl ?, fl, ) .;1 P 1,133 3,58) 155,151 )771 1,’)53,’11’3 s8 3,072 113,1)77 1,055,216 5,2)0 61,753
I, . t,t, 33,)) ’ . 13,’ ;’, ) 215,) 1, 11 1 .77 1131,114 ‘1,125 8’,’, 33’. j,1’l 11,737 .6,51) 93., 5.’3 112 ,s 15 7213,8 5) -9,77-0 34,-.27
J..’ I I i ’ S LI.. 1,7 • TI; 335 I 7 1 3 31 5; 7 , ) 15 /7 US .77 ‘ 53 7 , ., 330 2’S 1. (1) 13.3 1. L3 81. 33 5...) 2 , —
forth .zo L a 7 33 12 3< -. . 3 9 5 1 ‘ 5.11 1177 3f’7 1 1 2 ,1, U.) 37 ...33 75,3 1 3 15 ‘, 3 55 579 027 532 5 ,.2 .7) , , . ,5 733 1 ,1 335
, )‘ ,,,n ‘3 1 7” 3 17 3. 377 3 ) 3 , 3. 465 15) 32 ” 213 5 ‘-1 o2 3733 101 1)’) 6 3311 7 2 5 ‘3 5.3 11 25’ 3
110,3.55 1 12,31’) )15,.,5’)-; , 3,137,422 61,511 15,371 113,819 77,731 1,7) ,331 19,81,2 75,1113 2,71’i,657 10,355,7525 22,277 15<7-12’)
235,131. 422,23) 2,2’3 ’ ),-.’.0 8213,555. 18,1)60 1)6,23.) 31,2.1 2 2 .,’J’3 361,12 ’Z) 710,5133 513,731 1,681,313. bl,-513 153,177’
331,35.3 1)T, ’ .2r 223, 1)7 3,731,313 237,23) 17,953 5A),842 Ui /I’)) 1,55 ,29 U6,71) ) ),57,1)73 1,’Q ’),333 1 . 5,263,82 .3 31,71.1. 29 ’ ),2 ’ )()
,‘j’, 1 ].vnn1s 1 5, 5fl LI’,, 33.3 21.7, _1’, 3,11 3,381 55,3, ; ’1.5 1,311 75,811 71 1. 1, 513,1’S 17,532 - 31,557 773,515 3,277,717 21,131) 77.,,173
3’ ) 3.’? ‘,-; 315,62 ) 3,551 33 71.5 o, ’ ’ ,i . 5.3,3 7 7 52 255 5,117 65,358 577 2,2)5
‘, C .,,.,, ma 23 ) 11 1 7, 33 ‘1’, , 1. 1. 2o .1 ). 36,2 523 2.33 36 1 ‘3 1. 25 51.2 53 72” 337’ ] . 6 .. 3 13’) 1 3 14’) 5’ ). 63.1 .3
s.’ .. 57,35.3 5,3,73) ‘.51,777 1 ‘1 ’)1,325 3581,721 13,0(19 35.1”). 20,278 77,74) U3,29-8 153,75’. 3,129,115 3,’1”2,7211 2 )3,33A0 333,757
15,216 61,611 313,7-’.’ 5,1316,13.’) 554,3’)’) 12,525 i ,-25 18,725 153,13.7 2-3,51-? 77,833 553 ,3315 5,358,533 61,555 255,255
1.22,”') 3335,17). 4,233,153 ‘ 22,7231,161 2,51,6,182 95,171 613.058 250,372 2,515,1)3 1,711,552 2,712,3133 5,251,133 20,5)7,2’1.6 1,).)5,3 1 3,313, ‘ ‘5
95,749 2’)),) ’7 2 ,.,,33 223/7.1 121,551 5,13.) 159,67’) 7,102 .35,321 11,353 19,124 173,1)37 254,779 3,326 22,311
7,12.0 26,521, LI, )3n7 1 3,118 351,311 359 2,197 3,7’ , ,)) jul83 122 5,752 31,551 235,550 2,12] I1, -555.
2)775 73,35-’) ‘ 3712,11., , 3,0751,164 313,103 59,277 575,1)61 55,952 1,329,711 1 21,52 ’S 295,051) 503,588 3,217,716 23,U7 233,231
Ws .S Io, ’ 1oi1 32,355 155,719 121,71. , 75,203,10’ ) 252,55 ) 1.5,291 Y/ , 6 3 78,017 1,161,1)1)3 25,11)9 94,032 2,051,77’ 5, ’T1 )’S,2’7’) 77.13) 4.50,? - ’6
o .1 ?1r 1$ 5,7’1.2 19.571 21 /33 5)5,75’) f , 2,’;14 329 4,313 15,551 523,k”3 11,165 43,121 31,63) 175,121 5,331. 3333)
131. 12 16 5’—’ 3’ ‘5 3 5 3 716 1, ’)”,7”; 12 755 .3 773 3,) ) ‘ 13 77- 77 ‘)“I 67 7 1. 95’.) ‘4 9? 3 3)’) 3 1 3 155 5—3
375,74) 8’,,73 , , 15, 1I ,2 , 53,33(4 212,727 5,113 132,0’)”. 6,39’ S 21,132 17,175 u 6,5,8 123,511 6s1., 3 1’,I’ri . 7,331
— 2,180,2Z ,3 6,427,706 3o,s331,’.c .; 2’7’i,971,525 26,128,1553 1,257,101. 17,33k,650 ) .,8ô,033 _ 5$,303,2) ’ 5,947,150 9,675,11.7 34,713,541 355,6d3,739 5,180, ‘91 23,233,545
1. ‘1.74? C,ii,i. ot Agr1C,L1t,.z’ ”.
Source: Fowler, D. L. • and 3. Mahari (eds.), Pesticide Review, 1972 , Washington, D.C., USDA, 1973.
-------
EXHIBIT 6. 5: Algorithms for Pounds Per Acre
(1) PD = PD 1
where:
PD 1 = pounds of pesticide i sold in region j
- of _ pesticidei applied in region j
‘3 - pounds of pesticide i applied nationally
PD = pounds of pesticide i sold nationally (from Exhibit 6. 3)
(2) AC J = cj AC
where:
ACjj = acres treated in region j by pesticide i
— acres in recion j treated bypesticide i
13 — total acres treated in region j
AC = total acres treated in region i (from Exhibit . 4)
(3) PA 1 = PD 1 /AC
where:
PA pounds of pesticide i applied per acre in region j
PD = pounds of pesticide i sold in region j
AC 1 = acres treated in region j by pesticide i
6. 37
-------
EXHIBIT 6.6: Calculation of Average Application
Rates for Insecticides
Production—exports + imports = application in pounds
Example using 1969 data for United States:
1,134,239,000—250,539,492 +820,288 = 885,019,796
Data source: Fowler, D. L. , and J. Mahan, The Pesticide
Review, 1972 , Washington, D.C. , U. S. Department of
Agriculture, June, 1973, Table 3.
Proportion used for agriculture = 0.42500 in 1964
= 0.813 in 1973
Example: (.813) (S85, 019, 796) 719, 521, 094 pounds
0.4250 from F. Matsumura, Current Pesticide Situation in
the United States, ‘ in F. Matsumura, ed. , Environmental
Toxicolocv of Pesticides , New York, Academic Press, 1972,
p. 38.
0.813 from Rosmaric von Rurnker, et al. , Production, Dis-
tribution,Use and Environmental Impact Potential of Selected
Pesticides , EPA-OPP 540/1-74-001, 1974, Table I, p. 7.
acres (19E9) = 43, 328,890 719, 521, 094 = 16. 6060 pounds/acre
(see Exhibit 6.4 above, and 43, 328,890 of insecticides,
use total acres for insect United States average
and nematode control)
6. 18
-------
EXHIBIT 6. 7: Procedure for Calculating Degradation
Rates for Pesticides in Soil
1. The purpose of the procedure is to calculate time periods during
which certain percentages of pesticides will have disappeared.
The percentages of interest are 25, 50, and 85.
2. The sources are:
Edwards, C. A. , Persistent Pesticides in the Environment ,
Cleveland, Chemical Rubber Company Press, 1973, Table 3?
Figure 6, p. 16.
Hurtig, H., “Long—Distance Transport of Pesticides, ‘I in
F. Mat sumura, ed. , Environmental Toxicology of Pesticides ,
New York, Academic Press, 1972, pp. 260-261.
3. Basically, Hurtig gives 75-100 percent loss times for 29
specific pesticides and six groups. Edwards gives half-lives
and 95 percent loss tin es for eight pesticides.
4a. Assume that i-{urtig’s 75-100 percent loss times are equivalent
to Edward’s 95 percent loss times (i.e. , intervals after appli-
cation).
4b. Assume that the major source of pesticides in soil is from
agricultural applications; other sources are highly localized
and will be ignored.
5. Calculate ratio between 95 percent loss time and half-life for
eight pesticides given by Edwards:
Ratio of Half-Life
to 95 Loss Time
Aidrin 0. 10000
Chiordane 0.25000
DDT 0. 28000 Average
Dieldrin 0.31250 o.2z li s
Endrin 0.31429
Heptachior 0.22857
Lindane 0. 18462
Isobenzaii 0. 10000
6. 19
-------
EXHIBIT 6. 7 (continued)
6. Apply average ratio from Step 5 to Hurtig data (75-100 percent
intervals) to obtain half-lives (given in years)
75-l00 Level
Pesticide ( Assume 85 ) Half-Life Interval * *
DDT l0 2.8* 0.933
Aidrin 3* 0. 3* 0. 100
Toxaphene (same 8* 2.5* 0.833
as dieldrin)*
2,4, 5-T 0. 42** 0. 093 : ** 0. 031
MCPA 0. 0. 055 0. 018
2, 4-D 0. 09 * 0. 020 : ** 0. 007
Note: To linearly interpolate percent losses (x percent\ for an
arbitrary interval, e.g. * two years, use:
( Arbitrary interval) - Interval 1 == x - percent I
Interval 2 - Interval 1 percent 2 - percerL I
*See Edwards, 1973, p. 1(.
Hurtig, p. 21.
**App1y arbitrary rule of one-third half-life.
***Apply average ratio of half-life to 95 percent loss time deter-
mined in Step 5, i.e. , use factor of 0. 2 l25. (This calculation assumes
that the relationship between half-life and 95 percent loss time IS the
same for both the phenoxy herbicides and the typical chlorinated hydro-
carbons listed in Step 5.)
6. 20
-------
EXHIBIT 6. 7 (continued)
7. Degradation (Persistence) Factors in Soil
Percent Loss After Time Period*
Pesticide
Months (Years
)________
1
(.08)
6
(0.5)
12
(1)
24
(2)
48
(4)
96
(8)
ic
(16)
DDT
13.
40
39.29
75.28
95*
Aldrin
20
52.
59
95
Toxaphene
27.50
59.55
85
95
2,4,5-T
44.76
85
95
MCPA
54.49
85
95
2,4-D
85
95
*Percents between 25, 50, 85 percent decay points are linearly
inte rpolated.
**If number of months is greater than 85 percent interval, arbi-
trarily assign 95 percent.
6.21
-------
6. 2. 3 Runoff Rates
Before calculating the amount of pesticide which decays in the
soil each year, the amount which runs off into adjacent bodies of water
should be calculated. This amount should be subtracted from the total
residual amount of pesticide remaining from the previous year, plus
what has been applied in the current year. Amounts of pesticides in
water are available from published sources. Some examples of these
residues are shown in Exhibit 6. 8. Since residues in water are rela-
tively transient, it is likely that these amounts are from recent appli-
cations, and they can be connected to application rates. A procedure
for calculating runoff rates from application rates is shown in Exhibit
6.9.
It should be understood that the algorithms presented above are
extreme short-cut methods for calculating a few basic physical vari-
ables so that the overall benefit-cost system will be integrated, and
so that the benefits and costs which are finally obtained will have at
least a minimal basis in the physical phenomena which govern the dis-
tribution of pesticides.
6.3 Biological Uptake
Before proceeding to the biological uptake algorithms, it is
possible to summarize the residue algorithms described in Section 6.2
above, and to set a standard notation for use in the subsequent equa-
tions. In addition to the water residual equations described previously,
the equation shown in Exhibit 6. 1-0 contains a factor for estimating pes-
ticide residues which reach bodies of water more directly than by run-
off from treated acres, such as from rainfall, dust, and air currents,
as well as from spills and dumping. Although this factor is arbitrary,
and is based only on the relative number of acres of water in a region,
it should serve as a reminder that pesticides do, in fact, reach bodies
of water in several different ways. The coefficient used in the calcula-
tion of the direct impingement factor suggests that the meteoro’ogic
effects would result in a linear decline in pesticides which are blown
into water, but the nature of this coefficient should be more accurately
estimated from meteorologic data.
Edwards, C. A., Pesticide Residues in Soil and Water,” .
cit., pp. 440-441.
6.22
-------
EXHIBIT 6.8: Pesticide Rcsiduc s for ’Watcr (numbers are in ng/I)
Pesticide
1 ciZion
North-
cast
App -
chian
North-
em
Pla ins
Lake
States
South-
est
Delta
States
Corn
Belt
South-
em
Plains
Moun-
tairi
Pacific
DDT
135.5
(1971)
33.20
(1971)
416.00
(1966)
9.83
(1968,
1967,
1970)
79.90
11.3
(1966)
Aidrin
17.5
(1966)
26.39
(1967,
1969)
Dicldrin
58.55
(197 1J
35.00
(1966)
26. 17
22. 1
ngI1 is expressed as parts per trillion or 10- 12 Therefore, to convert numbers to ppm, multiply by 106.
-------
EXHIBIT 6. 9: Example of Calculating Runoff Factors
For One Region (Delta Region
Mississippi, Louisiana, A rkansas)
Pounds per acre should be calculated by the procedure shown in
Exhibit 6.5 for the year 1966. In order to simplify this problem,
assume pounds per acre is found to be 16. 6060, as found in
Exhibit 6. 6.
Then the concentration in soil = 8.3030 ppm in 1966 (see
Exhibit 6. 10 below).
The total levels in water = 0. 0004685 ppm (see residues for
water data).
0. 0004685
Runoff factor = 8.3030 = 0. 0000564253
or 0.005643 percent for the region, assumed to be a constant
over time.
The above calculations illustrate procedures for calculating
residues in water based on amounts of insecticides applied.
Data sources:
Pounds per acre = l6. from Exhibit 6. 6 above.
Level in water = 0. 0004685 (sum of three pesticides) from
Exhibit 6. 8 above.
6.24
-------
EXHIBIT 6. 10: Residue Equations
(1) PI Sijk PLSi(j...l)k + Ucv (AAijk/CTjjl()
- PLWjjk] Fioo - DFjkl
(2) PLWIjk [ APWjJIç + BOFIkI [ (CV) (AAjjkfCTijlc)i
(3) WTLIjkp = (PLWijk/LCmkp)
whe re:
PLS k = soil pollution level in region i at time j for
pesticide k, in ppm of pesticide in soil,
c v a constant for converting pounds per acre
to ppm:
1/2 pound/acre = ppm.
Source: C. A. Edwards, ed., 1973, p. 413,
AAjjk = amount of pesticide k applied in region i
betweenj-1 andj,
CT k = the total acres of land treated by pesticide k
in time j and region i,
PLWjJk = water pollution level in region i at time j for
pesticide k, in mg/kg, i.e. , parts per million
of pesticide in water,
DF 11 ç = degradation factor, usually in percent per
year, for region i and pesticide k, for soil,
APWjjk = the water application and drift factor in
region i at time j for pesticide k, a unitless
proportion equal to:
(. 01) (acres of water surface in region i) /
(acres of ‘and surface in region i)
6.. ZS
-------
EXHIBIT 6. 10 (continued)
Source: Lerner, W. , ed. , Statistical Abstract
of the United States , Washington, D. C.,
1973, U. S. Bureau of the Census,
p. l72
ROFjk = proportion of amount of pesticide k applied
which washes off of fields between (j—l) and j,
a unitless measure,
WTLjJkp = proportion of existing residue levels in
region i at time j to predefined lethal concen-
tration level l!m ? (usually 50 percent), for
organism p and pesticide k. This proportion
is a useful indicator in itself, and it is also
used implicitly in equation (2), Exhibit 6. 12,
below.
LCmkp the lethal concentration of pesticide k that
will kill rn percent of species p.
Note: Equations (1) and (2) provide a method for calculating accumu-
lated residuals in soil and ater if application rates per acre are
known. Equation (3) is a preliminary damage indicator.
6.26
-------
The biological uptake equations are simple applications of con-
centration factors described in the literature.(see Exhibit 6. 11).
Although these concentration factors are usually much greater than
one, they may be less than one, i.e. , dilution factors, for some organ-
isms and for some pesticides. In the case of fish, these uptake factors
are thought to depend on absorption through the gills, but may also
involve food chain accumulation. In the case of birds, i he source of
pesticides is almost entirely through the food chain, and the biological
uptake algorithm for birds has been constructed to contain four possible
sources of pesticides in birds diets (invertebrates and plants from soil
and water). These factors could be weighted for the species of bird,
but for now, they are merely averaged.
6.4 Population Damages
Three kinds of population damages are possible because of the
uptake of pesticides: acute (immediate), chronic, and reproductive
disruption (see Exhibit 6. 12). Data were not available for all types of
damage for both birds and fish, because certain types of damages are
not readily observed, and may not occur except in rare cases. For
ex.mple, acute (immediate) toxic effects in birds are rarely observed,
perhaps because their mobility enables them to escape the immediate
application situation.
Conversely, the chronic toxicity phenomenon is difficult to
observe in fish because they are generally extremely fast concentra-
tors of any pesticide which enters the water. Equation (1) in Exhibit
6. 12 for fish reproduction disruption was developed based on one study
which lasted 156 days. In any case, perhaps these equations represent
the types which should eventually be conveniently available to EPA.
One important assumption is that the population for any given
year can be reduced by the amount of individual organisms killed by
pesticides to obtain the population for the following year. This type
of assumption is not necessary to the calculation of actual damages,
SiflCC the flUlTibe r of birds (fish) killed is the essential piece of infor—
rnation. The equation is necessary to tie the successive years together
when not all years are represented by available data. Estimates of
actual population sizes are difficult to find in published sources, and
substitute variables must be used as a basis for estimating total popu—
lation. Three such variables are woodcock killed by hunters (see
6. 27
-------
EXHIBIT 6. 11: Biological Uptake Algorithms
A. Fish
CFH jkp = (KFjkp) (PL \ T iJk)
whe re:
CFHi kp concentration of residue in fish type p, region i,
time j, pesticide k, in ppm,
KF concentration factor for fish category p ,
pesticide k, time j,
— concentration in fish
- , a unitless proportion.
concentration in water
Source: C. A. Edwards, Persistent Pesticides
in the Environment , op. cit., 1973, Table 21,
p. 63.
PLW Jk = water pollution level in region i at time j for
pesticide k, in ppm,
B. Birds
CBDiikp (KBJkp) 114 [ (K 1 B k) (PLSiJk) + (KzBjk) (PLWj k)
± (K3 B k) (PLSj;k + ( I 4 Bjk\ (PLWiIk)]
whe re:
CBDj kp concentration in ppm of pesticide k in bird
- type p. time j, region i,
KB kp = concentration of pesticides into birds from diets
for bird type p, pesticide k, time j,
PLW;jk water pollution level in region i at time 3 for
pesticide k, in ppm,
6.28
-------
EXHIBIT 6. 11 (continued)
Sources:
1<1 Bjk Table 13, Earthworms, Slugs, Anthropods
K2 Bjk Table 15, Freshwater Invertebrates
K 3 Bjk Table 27, Soil into Water
1 <4 Bjk Table 28, Water into Plants
C. A. Edwards, 1973 op. cit . , pp. 36 ff.
Note 1: Concentration into mammals has been observed,
but concentration factor for muscle tissues has
been measured mostly in domestic animals.
Note 2: Although accumulated totals appear to increase
in linear proportion to exposure time for fish,
there is a ‘level].ng off 1 phenomenon in mammals.
The relationship for birds is unclear, but is prob-
ably similar to that for mammals.
(Edwards, op. ., p. 64 ,-p. 95, p. 80)
6.29
-------
EXHIBIT 6. 12: Population Damages
A. Fish
Note 1: Holden (Edwards (ed. ), . cit. , p. 239) cites studies
in which concentration in fish, mg/kg, was 2 mg/kg!
week for 22 weeks, or presumably 44 mg/kg of DDT,
since no bioassay data are given. After this time, the
mortality of fry (brook trout) was about 3. 5 percent
higher than controls.
Therefore, assume:
104 mg/kg/year would result in loss of 3.5 percent
of next yea r 1 s population.
(1) FPPj(jl) FPPi(jl)p [ CFHj(jl)kp!104] (.035) (FPPj( l) )
whe re:
FPP 1 ;p fish population in year j of fish type p,
region i
CFHiJkP = concentration of residue in fish type p,
region i, year j, pesticide k, in ppm
Note 2: This formula assumes that other effects would result
in a population in (j) exactly equal to population in (j-l).
Note 3: The fish concentration variable (CYM’) is not needed
to calculate immediate toxic effects since data on
toxicity arc given in Ttexposuren amounts which are
concentrations in water (see Edwards, op. cit.
Table 22, p. 6).
(2) FPPijkp FPP 1 (j_ 1)lc — [ 1/2 (PLV.’ ( l)k /(LC5o)1
[ 1/2 FPPj(Jl) 1 p}
Ho1dcn, A. V. , “Effects of Pesticides on Fish, in Edwards
(ed.) , 2E cit. , p. 239.
6. 30
-------
EXHIBIT 6. 12 (continued)
where:
= fish population in year j of fish type p in
region i containing pesticide k
PLWIjk water pollution level in region i, year j,
for pesticide k, in ppm
Note 4: The fish population of any type in any year j equals
the previous year’s population less the amount killed
by residues. The proportion of the residue to the
LC 50 determines the proportion of half the population
killed. Assumption: the lethal concentration is linear
from 0 to 50 percent. The above function suggest. ’
that if the ratio of PLW/LC 50 >4, then 100 percent
of the population is killed. The 1/2 factor applied to
this ratio reduces j to 6 months.
B. Birds
Note 1: Immediate toxic effects are not readily measured in
birds, except possibly water fowl. These water fowl
effects occur only in unusual circumstances such as
accidental spills, etc.
(3) BPP 1 = BPP (jl) - - j- (BPPi(j_l)p)
x (CBDj(j 1 )kpfLDIylkp)
where:
= bird population in region i, year j
= concentration of pesticide k in bird type p
in region i, in year j, in ppm
LDmkp = lethal dose, of pesticide I c which, if accurnu-
lated in birds, will kill m percent of the popu_
lation of type p
6.31
-------
Exhibit 6. 13), waterfowl hunting activity (see Exhibit 6. 14), and fish
stocked from fish hatcheries (see Exhibit 6. 1.5).
6. 5 Monetary Evaluations
Various concepts and assumptions for assigning dollar values to
wildlife are available, including costs associated with maintaining sub-
stantial wildlife populations. In the following discussion, this concept
will be discussed, and a second type of costs, those paid by sportsmen,
will also be considered.
Assume that each year’s property acquisition cost is incurred
because of expansion and maintenance of game and fish which may not
actually be caught or killed on the Federal lands. Also assume that
the valu.e of the game or fish killed or caught is equal to the value of
a hunter’s day spent killing or catching. If the game or fish taken are
not replaced, the value of the hunter’s day is not maintained and will
be lost the following year. Similarly, the value of a camper’s day is
the value of maintaining the fish, birds, and other wildlife in national
parks and forests (see Exhibit 6. 16). Finally, assume that campers
“c perience” about the same number of animals per day that hunters
and fishermen take.
6. 6 Areas for Future Work
Upon examining the environmental effects submodel presented in
this chapter; it becomes evident that many components of the submodel
use oversimplified physical models. However, as additional knowledge
is gained and as more data become available, further refinements can
be made.
In addition, some components of the submodel are missing.
More specifically, the submodel addresses the environmental impacts
to birds and fish, but does not address similar impacts to plants and
mammals. Birds and fish are accepted as indicator species for deter—
rnination of environmental impacts resultiflg from pesticide use,
whereas effects on plants and larger mammals have not been as fre-
quently observed.
6. 31
-------
Nevertheless, plants can be affected by the phytotoxicity of the
pesticide, and the LD 50 level for various niaiximals can provide insights
into the pesticid&s toxicity to mammals. However, this information
alone is not adequate to predict the likely impacts to plants and mam-
mals from application of a particular pesticide. The mobility, persis-
tence, and bioaccurnulation of the pesticide are illustrative of additional
factors which must be considered.
Therefore, incorporation of these two components -- i.e. plants
and mammals -- into the present environmental effects submodel is not
a simple procedure. Additional work and research in this area are
required to provide the knowledge and data necessary to perform this
task.
6. 33
-------
EXHIBIT 6. 13: The 1971-72 Woodcock Wing-Collection Survey
— C
C
—fl— — H
D
- -- - K K( E) — L
T
T-
Source: Clark, E. R., WoodcockStatus Report, 1972 , Washington, D.C., U. S. Department
of Interior, Fish and Wildlife Service, Bureau of Sport Fisheries and Wildlife, No. 169,
1973.
A 3
C D
E F
C H
J K M
Woodcock Kill by
Hunting License
Duck Stamp
Duck Stamp
License Holders to
Holders
Sales
Purcha ’ er
Stamp Sales Ratio
StATE* 1969—70 1970—71
1969—70
1970—71_1969—70_1970—71
1970—71 Mean
Cone.
t&.
Ma ins
Mass.
h1f.Ch
Mine.
.H.
N.J.
N.Y.
Ohio
Pa.
Vt.
‘Wis.
77,488
337, 641
202, 766
118,518
941,025
356,607
98,8.87
184,527
758,512
540,718
1., 1 34, 316
138,378
629,445
85,452
348,635
219,373
123, 589
941,426
377,384
97, 360
196, 533
756,060
565,896
1,166, 634
148, 282
634,992
12,889
105, 274
15,939
25, 630
101, 562
144, 562
8,938
32,974
98,403
35, 841
67, 224
6,317
122, 291
15, 779
129,046
18, 182
29,993
131,404
173,877
9,880
35,002
108, 582
43, 508
81,074
7,435
151, 524
1969—70
6. 0119
3.2072
12. 7214
4. 624 2
9. 2655
2.4667
11.0637
5.5965
7. 708 2
15.0866
19, 531
111,991
26,786
33,489
56, 678
13,860
13, 599
29,812
86,501
20, 300
44,641
5,393
47,092
5. 4156
2.7016
12.0 654
4.1206
7. 1644
2. 1704
9.8543
5.6149
6.9 630
13.0067
26,312
99,385
34,420
33,410
80,595
21, 501
9,876
29,086
77,693
13,631
56,816
11,885
94,167
Percent
of
Mean
64.79 2
33.502
140. 539
49.58 2
93.156
26. 29 2
118.603
63. 568
83.184
159. 287
State
Kill
Index
14,203
35,408
43,009
16,585
63,939
4,646
13,921
18, 20
68, 292
27,024
State
Weight
Factor
.0313
.0781
.0948
.0366
.1410
.0102
.0307
.0413
.1506
.059 6
5. 7137
2 .9 544
12.3934
4.3724
8. 2149
2.3186
10.4590
5.6057
7.3356
14.0467
15. 6317
20.924 7
4.6689
16.8737 14.3897
21.9056 19.9438
5.1471 4.1907
177.261
237.283
52. 944
89,922
20,499
37, 399
.198 2
.0452
.0824
Mhirteen States having ubstant ial woodcock harvc:; t ; bc Lug tdcqua ttly rcprescntcd In wing—collection survey.
L
—-M
LL
-------
EXHIBIT 6. 14: Waterfowl Hunting Activity and Bags of Ducks and Geese in the
United States During the 1970 and 1971 Hunting Seasons (Estimates
Uriadjusl:ed for Response Bias; Totals Include Activity by Junior Hunters)
State and
Dat lv duck
S and
Days
in
Number
of odult
Day
per
Total
Seasonal
duck bar
Total
Seas or.al
goose hag
Total
I’.unting eason
po: sc siOfl
1 ts
duck
sca o
huatvrs
p_ t ti
adult
hont’ r
hunter—
d ray
per adult
lion to r
duck
S a
per adult
hun t r
goose
a
United States total: 2
1970 —— 2,390,770 6.65 17,052,000 8.06 20,298,200 0.87 2,151,800
2,3 :$, 350 6.50 16,219,gOO 7.11 17,903,°00 0.71 1,752,400
_______ _____________________ 0 — 2 — 2 — 12 — 1? — 19 — 19
‘Includes regular and all special duck seasons; regulations summarized for regular season only.
2 Availablc for states.
Source: Chamberlain, F. B. , et al. , Waterfowl Status Report, 1972 , Washington, D.C. , U. S.
Government Printing Office, 1972, Bureau of Sport Fisheries and Wildlife Special Scientific
Report Series No. 1 , Wildlife, U. S. Department of Interior.
-------
EXHIBIT 6.15
OfX Ip?ltp
A4C SPEC l’_S
F lS’41 • At ’ ISH L.f.S OIc lauTcO bY OISCbIPTION OP w4TEF 3 STOCKtO, TSCAL VIM 73
ADULTS lb i . .1
, . ,II P ’ j cP. UMBTR ptu ICS 14&JM 1F POUNDS NUMBER PO mOS
TOTAL
$UMO b R PO J DS
C’
4b.4LA.A2 l ,A’,7 1 .AI’4. A4.7 1,B1S I ,7I.,O I I.SIU6. 71O 23, 54.1.719 4.IbO.136 3OJ,A e.4.43 6.364.b lb
Source: U. S. Department of the Interior, Propagation and Distribution of Fishen from
National Fish Hatcheries for the Fiscal Year 1973 , Fish Distribution Report 8,
Fish and Wildlife Service, Bureau of Sport Fisheries and Wildlife, 1974, p. 27.
LA G JUT’ h/S.
00. i9 )
lB
300
2
10C.3 0
20
SP*1M3u14 ’ PASS
ST IP( / ,ASS
l(, ,O 0
b,67B
4
14
10.000
$.6 2i
4
14
PAIMBJ . T4. /11
1.114.. 36. /
227
Z,S? 4 .,36B
227
tiP1 P 7PZIJ
I ,.) ’ .7 ,AiL
t4
1.0 57,831
14.0
ST SHtAC 7. U!
100.928
)
300.628
70
LEHO SAtP’F
2. 11.. 701,
I, nO
2 ,114.100
1,310
I IAL
A, .47, .17
I, ll5
20
4..664 ,SOY
1.74.3
-------
EXHIBIT 6. 16: Cost of Replacing Wildlife
A. Cost Equations
Cost per camper day cost per hunter/fisher day
= cost of providing game and fish
(1) CCD 1 = FC /CD
where:
CCD 1 = cost per camper day, state i, year j
FC 1 Federal park expenditures, state i, year 5
CD 1 = total number of camper days, state i, year j
CCD-
(2) CAN 2 (BRN 5 + PSCjj) + OWlK + OWL 1
where:
CAN = cost per animal, state i, year 3
BRK 5 = number of birds killed per hunter day, average,
state i, year j
FSC 5 = number of fish caught per fisher day, average.
state i, year j
OWKjj = number of other wildlife killed, state i, year
OWL j = number of other wildlife in survey, state i,
year j
B. Data Sources
SPAC
FC = 50 FC
2 SPAC 1
i=1
6. 37
-------
EXHIBIT 6. 16 (continued)
where:
FC = total Federal expenditures, year j, Tables
332, 333, 334, pp. 203-204, U. S. Bureau
of the Census, Statistical Abstract of the
United States , W. Lerner, ed. , 1974, and
SPACj state park acres, state i, year j, Table 341,
p. 207.
Alternatively, obtain Federal expenditure for year j
by state directly.
CD = obtain from Table 334, Statistical Abstracts, 1974 ,
and allocate to states as above, or alternatively
obtain NP acreage by state
waterfowl statistics (see Exhibit 6. 14) and woodcock
statistics (see Exhibit 6. 13)
FSC 1 = sport fishing statistics, or derive from Exhibit 6. 15
OWK = deer killed, U. S. Department of the Interior,
Fish and Wildlife Service, Federal Aid in Fish and
Wildlife Re storation , Annual Publication
OWL U. S. Department of the Interior, Bureau of Public
Lands, Public Land Statistics , 1972, p. 88.
C. Alternative Procedure
Use costs of hunting and fis ’.ing licenses to calculate value of
wild animals, i. c.
cost per bird {BRK 1 HUD J
cost per fish [ FSCjj X FID 1 ]
L •
U. ,. )
-------
EXHIBIT 6. 16 (continued)
whe re:
HLC = total expenditures for hunting licenses, state i,
year 5, Table 346 Statistical Abtract , . cit.
NRH 15 = number of hunters, state i, year 5, Table 34 ,
Statistical Abstract , 2 • cit.
l- 1UD 15 = average number of hunting days per hunter,
state i, year j, Exhibit 6. 14
HFC 5 = total expenditure for fishing business, state i,
year j, Table 346, Statistical Abstracts , . cit.
NBF 5 = number of sport fishermen, state i, year j,
Table 345, Statistical Abstracts , . cit.
= average number of fishing days per sport fisher-
men, state i, year j, sport fishing statistics
6. 39
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7.0 SUMMARY OF THE BENEFIT-
COST SYSTEM PROCEDURES
7. 1 Criteria for Design of the Benefit-
Cost System and Input Requirements
This chapter summarizes the operating characteristics of the
pesticide benefit-cost system. The system has been designed to meet
three very broad criteria:
• It must provide for the complete explication of all
benefits and costs arising from or attendant on
pesticide use,
• It must provide for precise connections between
incremental use of specific pesticides and incre-
ments of benefits and costs, and
• It must operate within the conceptual structure of
economic benefit-cost theory.
In addition to these three broad criteria, there were several specific
criteria related to the eventual use of the system. These criteria
included a requirement for the use of reasonably available data, pref-
erably from the data requirements of the registration process itself or
regularly published government sources, and a requirement for a capa-
bility of single or multiple year calculations for at least five years into
the future. In addition, the system had to be modular, with specific
types or categories of benefits and costs separately assessed and
depicted.
The system meets the first broad criterion of comprehensiveness
by means of a two-dimensional matrix of benefits and costs. Each of
the cells of this matrix are not developed by separate algorithms or
submodels (an approach which would have required a voluminous and
intricately indexed system of repetitive submodels), but the benefits
and costs described in each cell of the matrix direct the user to one of
three major submodels:
• Food, feed, and fiber production,
• Health effects, and
• Environmental effects.
7. 1
-------
Within each of these submodels, flexibility is available for the applica-
tion of specific algorithms according to specific user needs.
The second broad criterion, sensitivity to increrriental use of
pesticides, is provided by a precise connection of most algorithms to
application rates, residual acc’in-xulation, Or to degradation rates.
These connections require that a system user be able to enter the sys-
tem with an estimate of annual application rates for an agricultural
(multi-state) region, but reference data are incorporated to facilitate
such estimates. A simple conversion factor is provided for conversion
of pounds per acre applied to parts per million in soil, but a more com-
plex model is available for optional use.
The third broad criterion, economic soundness, is met by a sep-
a rate theoretical section which supports the calculation of benefits to
consumers based on an increase in consumers’ surplus. The food,
feed, and fiber production (agricultural) submodel provides techniques
for calculating the benefits to farmers due to increased sales (yields),
and for calculating the benefits to consumers due to change in con-
suiners’ surplus. The change in consumers’ surplus is a function of
demand elasticity, which is either selected on the basis of theory or
estimated from published research.
Although the benefit-cost system user would in most cases be
constrained to enter the system through the agricultural submodel in
order to obtain food, feed or fiber production benefits and total amounts
of pesticide applied, the user may wish to enter the system either at the
health effects or at the environmental effects submodels. In order to do
this, the user must have estimates of the pounds of active chemical
applied per acre per year by region, state, or county, and he must also
have the total amount pplied, or the total number of acres treated.
Other information is also needed, such as the biological uptake rate by
various organisms, the toxicity to experimental animals, and the
changes in yield per acre for crops on which the pesticide is used. In
each submodel where these variables are required, techniques are pro-
vided for obtaining them from published sources, or for estimating them.
7. 2 Outputs of the Benefit-Cost System
The outputs of each submodel are a series of tables in standard
format which enable the comparison of effects, i.e. , impacts among
the different sub!nodels, as well as within them. These formatted
7. 2
-------
tables identify the calculation procedure (algorithm) used, the source
of inputs to the algorithm (previous tables or published documents) and
the relative point in the overall methodology where that particular cal—
culation occurs.
The outputs of major comparative significance include:
Value of change in consumers’ surplus,
Cost of application and materials for pesticide
analyzed,
Incidence and number of acute and chronic injuries
in seven human subpopulations, i.e.
Pesticide R and D, manufacturing and formula-
tion workers,
• . Pesticide transport personnel,
• . Field workers and other farm personnel,
Commercial farm applicator,
• . Non-farm professional applicators,
• . Household users, and
• . Society as a whole.
Deaths of fish and waterfowl, and
Dollar value of deaths of fish and waterfowl based on
government expenditures for maintenance and support
of these animals.
Other intermediate variables such as residue levels and crop yield
changes are also calculated and similarly formatted.
7.3 Calculation Procedures
The calculation procedures are kept at a simple level and no
equation has more than six terms. No regressions or other statistical
techniques are required, although probabilistic or hypothesis testing
techniques could be easily inserted at several points. No calculus is
required, although differential equations could be inserted in the con-
sumers’ surplus calculations if desired.
7. 3
-------
A strong effort has been made to use variable notation which
enables time and regional aggregation and disaggregation if needed
(acres treated by pesticides are available at the county level from the
Census of Agriculture) , and these same variables are suitable for the
development of simple programs to use, for example, in programmable
calculators.
The approach of each subinodel is to describe the general types
of data needed and the probable alternative sources for these data
rather than the present the user with a highly specified set of precisely
defined variables. This approach is intended to provide the user with
good flexibility in structuring his own benefit-cost accounts, within the
basic system structure provided. Such an approach, however, does
not simplify the use of the system to the cookbook level. Any user will
find it extremely useful to have a working familiarity with the agricul-
tural experiment literature, the experimental animal toxicity literature,
and the monitoring studies of enviro:imental residues.
Thus, any user who enters the system with a given pesticide will
be forced to imagine a scenario of use in terms of types of crops and
pests. He may well need to refer to some published sources on appli-
cation rates and toxicity (e. g. , the EPA compendium) such as those
referenced in the sections for each submodel.
After developing a few of the specifically formatted tables, the
user may then choose to devise his own summary formats for a given
geographic level. In any case, working through the system for a given
pesticide, which is expected to require two to four work-weeks, will
lead the user to a complete use of the best available data, by means of
a series of logically sound data reduction algorithms.
7.4
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APPENDIX A
TAXONOMIES FOR ALTERNATIVE
PEST CONTROL METHODS
A..1
-------
Public Law 92-516, October 21, 1972
Definition of Pests.
The term pest means (1) any insect, rodent, nematode, fungus,
weed, or (2) any other form of terrestrial or aquatic plant or animal
life or virus, bacteria, or other micro-organism (except viruses, bac-
teria, or other micro-organisms on or in living man or other living
animals) which the Administrator declares to be a pest.
I. Taxonomy of Commonly Recognized Pests
A. Plant pathogens - - plant disease
1. Viruses
2. Mycoplasma
3. Bacteria
a. Actinomycetes
Fungi
Parasitic vascular plants
Nematode s
4.
5.
6.
B. Weeds
Any and all kinds of chlorophyll-bearing vascular plants
may be considered weeds at one time or another. A weed
is a plant out of place, an unwanted plant.
C. Insects and Other Arthropods
1. Insects
2. Arachnids
a. Mites
b Spiders
c. Ticks
D. Vertebrates
1. Fish
2. Reptiles
3. Birds
4. Mammals
a. Chiroptera -- bats
b. Lagomorpha -- rabbits
c. Rodentia - - rodents
d. Carnivora -- coyote, etc.
A.2
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II. Taxonomy of Alternatives for Control of Plant Pathogens
Including Nematodes and Parasitic Vascular Plants
A. Genetic resistance, tolerance, or immunity on the part
of the host plant, crop, or commodity
1. Resistance
a. Vertical
b. Horizontal
2. Tolerance
3. True immunity
B. Biological Control
1. Parasites
2. Predators
3. Competitive displacement of organismal populations
a. Antagonism
i. Antibiosis
b. Food substrate competition
C. Cultural Control
1. Geographic avoidance and planting site selection
2. Tillage
3. Rotation
4. Planting date
5. Harvesting and storage
6. Thinning
7. Pruning
8. Water management
9. Plant nutrition
10. Vegetation barriers
11. Elimination of diseased plants
12. Elimination of alternate hosts
D. Physical and Mechanical Control
1. Environmental modification
a. Heat
b. Cold
c. Humidity
d, Air composition
e. Water
2. Barriers
a. Terrain and governmental quarantine
3. Radiation
E. Chemical Control
1. Protectants and surface eradicants
a. Foliage, fruit
b. Seed and other propagules
A.3
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2. Systemic protectants -- eradicants
a. Local
b. Xylem translocated
c. Phloem translocated
3. Theraputants
4. Growth regulants
a. Chemical resistance and immunity
5. Soil sterilants and eradicants
III. Taxonomy of Alternatives for Control of Weed Plants
A. Genetic tolerance to competition from weeds
1. Growth habit
2. Root structure
3. Nutrient or moisture utilization
B. Biological Control
1. Parasites
2. Predators
3. Pathogens, i.e., infectious diseases
C. Cultural Control
1. Tillage
2. Rotation
3. Crop refuse removal
4. Land utilization
5. Plant nutrition
6. Harvesting methods
7. Thinning
8. Water management
9. Geographic avoidance
D. Physical and Mechanical Control
1. Pulling, chopping, or cutting removal
2. Cultivation by hoe or mechanical equipment
3. Heat
4. Barriers
a. Materials
i. to keep out light
ii. to prevent top or root penetration
b. Terrain
c. Electricity
E. Chemical Control
I. Growth regulation
a. Inhibition or stimulation
b. Sterilization
c. Ma3forrnation
2. Intoxication
A. 4
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IV. Taxonomy of Alternatives for Control of Insects
and Other Arthropods
Definition:
Control is defined as the regulation, guiding, or management of a
process or system; in this case, the system is the ecos ’stem within
which the insect lives and reproduces.
A. Genetic resistance or tolerance on the part of the host
plant, animal, or commodity
I. Repellency
2. Intoxication
3. Indirect effects on arthropod population
B. Biological Control
1. Parasites
2. Predators
3. Pathogens, i.e. , infectious diseases
4. Genetic manipulation of insect populations
5. Competitive displacement of insect populations by
other insects
C. Cultural Control
1. Sanitation
2. Tillage
3. Rotation
4. Crop refuse destruction
5. Land utilization
6. Plant nutrition
7. Harvesting and storage
8. Thinning
9. Pruning
10. Water management
11. Geographic avoidance and planting site selection
D. Physical and Mechanical Control
1. Heat
2. Cold
3. Humidity
4. Radiant energy
a. Light traps
b. Light regulation
5. Sound
A.5
-------
6. Barriers
a. Terrain and governmental quarantine
b. Adhesives
c. Material
d. Air
e. Water
f. Electric
7. Traps
8. Radiation
a. Sterilization
b. Intoxication
E. Chemical Control
1. Attractants (combined with other methods)
2. Repellents
3. Sterilization
4. Growth regulation (juvenile hormones, etc.)
5. Intoxication (insecticide)
V. Taxonomy of Alternatives for Control of Vertebrates
A. Genetic resistance or tolerance on the part of the host
plant, animal, or commodity
1. Repellency
2. Intoxication
B. Biological Control
1. Predators
2. Pathogens, i.e., infectious diseases
3. Competitive displacement of pest vertebrate through
ecological manipulation with other organisms
C. Physical and Mechanical Control
1. Traps
2. Sound
3. Light
4. Heat
5. Cold
6. Barriers
7. Sanitation
8. Den, burrow or nest removal
D. Cultural Control
1. Tillage
2. Biological barrier
3. Crop rotation
4. Sanitation, i. e., crop or animal refuse or waste
removal
A.6
-------
5. Land or water utilization
6. Harvesting techniques -
7. Manipulation of plant or animal cultural practices
a. Pruning
b. Housing
c. Planting or stocking procedures
E. Chemical Control
1. Attractants
2. Repellants
3. Sterilization or reproductive impairment
4. Growth regulation
5. Intoxication
A.7
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APPENDIX B
BENEFITS AND COSTS FROM PEST CONTROL
B.1
-------
I. Pesticide Benefits-Costs: Food, Feed, and Fiber
Production and Utilization
A. Entities Receiving Benefits or Incurring Costs
1. Private institutions, agency or individual
a. Manufacturer of pesticide
b Formulator
c. Distrib.itor
d. Wholesaler-retailer
e. Applicator
1. Agricultural producer
g. Field worker
h. Commodity-crop processor
1. Distributor-wholesaler
j. Retailer
k. Consumer
2. Public agencies
a. Federal government
b. State government
c. Local government
3. Society as a whole
4. Non-human environmental components
a. Marine aquatic
i. Phytological
ii. Zoological
b. Fresh-water aquatic
1. Phytological
ii. Zoological
c Terrestrial
i. Phytological
ii. Zoological
B. Pesticide Benefits Taxonomy
1, Invention, production, and distribution system of
pesticide
a. Increased production of goods by manufacturer
b. Increased sales
c. Conversion of natural resource to marketable
goods
d. Gainful employment of people
e. Monetary profit
2. Use in food, feed or fiber production system
a. Increased yield
b. Improved quality or reduced pest losses as
assessed in market place
1. Larger size
13.2
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ii. Better taste
iii. More usable qualities
iv. Free from defect, worms, rots, molds
v. Better storage or shelf life
vi. More suitable for intended purpose
c. Increased monetary profit
3. Food, feed, and fiber processing, utilization, and
distribution
a. Freedom from defects or more suitable for
intended use
b. Better storage and shelf life
c. Prevention of molds, rots, toxins
d. Reduced loss from spoilage
e. Increased monetary profit
4. Consumer
a. Improved quality
i. Taste, shelf life, appearance
ii. Free from defects
iii. Free from spoilage or toxins
iv. Better storage
v. More suitable for intended purpose
vi. More healthful
b. Lower purchase price
c. Non-hazardous pesticide residue
5. Public agencies
a. Less toxic or hazardous, less need for public
agency regulation
b. Lower regulatory or administrative costs
6. Non-human environmental components
a. Less toxic to various components in all phases
of the environment
b. Non-hazardous pesticide residue
i. Does not accumulate in food chain
ii. Is not persistent in environment
C. Pesticide Costs Taxonomy
1. Invention, production, and distribution systems of
pesticides
a. Utilization of scientific resources in discovery
and development
b. Utilization of natural resources .in manufacture
c. Utilization of human labor and technical skills
in manufacture
B.3
-------
d. Utilization of manufacturing facilities
e. Exposure of humans to pesticide during
development, manufacture and distribution
i. Human physiologic effects
- Acute injury
- Chronic injury
• Mutagenicity
• Teratogenicity
• Oncogenicity
• Reproductive impairment
• Chronic physiologic malfunction
Spillage and accidental release of pesticides to
environment
g. Human resources and physical facilities in
distribution and marketing
h. Monetary resources in development, manufac-
ture, and distribution
2. Use in food, feed or fiber production systems
a. Monetary cost to agricultural producer for
pesticide
b. Resources used in application
i. Monetary cost of applicator services
ii. Utilization of human resources by applicator
and employees
c. Storage and disposal of pesticides and containers
d. Spillage and breakage loss and cleanup costs
e. Health effects to applicator and agricultural
producer employees working treated area
i. Acute
- Normal use*
- Accidental exposure and spills
ln this instance and throughout the entire taxonomy, acute injury
from normal use is included to reflect the real world situation. Ideally,
there should be no such term as “acute injury from ‘normal’ exposure. “
Yet, many would argue, e. g. those in industry, that any acute injury
that is caused from direct exposure to a pesticide is not all a result of
accidental release. Therefore, until this issue is resolved, one can
argue that some acute injury is caused by what many refer to as
“normal” exposure.
f.
B.4
-------
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
1. Production system constraints induced by
pesticide use
i. Spray intervals -- harvest dates
ii. Re—entry intervals
iii. Cultural practices
g. Treadmill effect, i. e. , additional pest control
costs
i. Induced pest resistance
ii. Destruction of predators
3. Food, feed, and fiber processing, utilization, and
distribution
a. Residue removal
b. Constraints on byproduct utilization or treat-
ment of processing vastes due to pesticide
residues
c. Exposure of employees to pesticide residues
i. Acute
- Normal use
- Accidental exposure and spills
ii. Chronic
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
4. Consumer
a. Higher purchase price
b. Use constraints
i. Washing peeling to remove residue
c. Exposure to residue and human health effects
i. Acute injury
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
13.5
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5. Public agencies
a. Pesticide research and development; human
and monetary resources
i. Federal government
ii. State government
iii. Land grant experiment stations
b. Human and environmental health effects research;
human and monetary resources
i. Federa’. government
ii. State government
iii. Medical research institutes
c. Regulation of pesticides; human and monetary
resources
6. Non-human environmental components
a. Acute toxicity
b. Chronic toxicity
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
II , Pesticide Benefit-Cost: Health/Disease Vector Nuisance Pests
A. Entities receiving benefits or incurring costs
1. Private institutions, agency or individual
a. Manufacturer of pesticide
b. Formulator
c. Distributor
d. Wholesaler-retailer
e. Applicator
f. Private individual
g. People-oriented business, i. e., recreation-
vacation enterprise
2. Public agency
a. Federal government
b. State government
c. Local government
3. Society as a whole
4. Non-human e nvironmental components
a. Marine aquatic
i. Phytological
ii. Zoological
B.6
-------
b. Freshwater aquatic
1. Phytological
ii. Zoological
c. Terrestrial
i. Phytological
ii. Zoological
B. Pesticide Benefits Taxonomy
1. Invention, production, and distribution system of
pesticide
a. Increased production of goods by manufacturer
b. Increased sales
c. Conversion of natural resource to marketable
goods
d. Gainful employment of people
e. Monetary profit
2. Use in human disease vector and nuisance pest
suppre ssion
a. Gainful employment of pesticide applicator
i. Monetary profit to business
ii. Employment and wages to employees
b. Suppression or elimination of disease or
nuisance pests
i. Better level of health of people in treated
a rea s
- More productivity
- Better outlook on life
- Lower expenses for medical care
- More satisfying life; fewer frustrations
- Less wastage of food, clothing, other
resources
- Freedom to move around outside without
fear of disease
c. Enhancement of life or business enterprises in
treated areas
i. Homes or residences where previously
unsuitable
ii. Business such as resorts where previously
not successful
3. Public agencies
a. Less need for governmental inputs
i. Fewer health surveys
ii. Fewer public health programs
iii. Less hospital care of indigent
iv. Fewer educational programs
B.7
-------
4. Society as a whole
a. Less disease
b. Happier, more content populace
c. Better population distribution
d. More productive populace
e. Greater carrying capacity of the land or
national land area
5. Non-human environmental components
a. Enhanced survival of certain wildlife components
C. Pesticide Costs Taxonomy
1. Invention, production, and distribution systems of
pesticides
a. Utilization of scientific resources in discovery
and development
b. Utilization of natural resources in manufacture
c. Utilization of human labor and technical skills
in manufacture
d. Utilization of manufacturing facilities
e. Exposure of humans to pesticide during devel-
opment, manufacture, and distribution
i. Human physiologic effects
- Acute injury
- Chronic
• Mutagenicity
Teratogenicity
Oncogenicity
• Reproductive impairment
• Chronic physiologic malfunction
f Spillage and accidental release of pesticides to
environment
g. Human resources and physical facilities in
distribution and marketing
h. Monetary resources in development, manufac-
ture, and distribution
2. Use in human disease vector and nuisance pest
suppre ssiori
a. Monetary cost for pesticide
b. Resources used in application
1. Monetary cost of applicator services
ii. Utilization of human resources by applicator
and employees
c. Storage and disposal of pesticides and containers
d. Spillage and breakage, loss and cleanup costs
13.8
-------
e. Health effects to applicators and employees or
householders or other pesticide users
i. Acute effects
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
f. Treadmill effect, i.e. , additional pest control
costs
i. Induced pest resistance
ii. Destruction of predators
3. People, lands, plants, facilities or structures
receiving treatment
a. Damage to facilities or structures
i. Discoloration, residues, etc.
b. Health effects to people living or working in/on
treated lands or structures
i. Acute
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
4. Public agencies
a. Pesticide research and development; human and
monetary resources
i. Federal government
ii. State government
iii. Land grant experiment stations
b. Human and environmental health effects research;
human and monetary resources
i. Federal government
ii. State government
iii. Medical research institutes
c. Regulatiou of pesticides; human and monetary
re sources
B.9
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5. Non-human environmental components
a. Acute toxicity
b. Chronic toxicity
1. Mutagenicity
ii. Teratogenicity
iii. Oncogeni.city
iv. Reproductive impairment
v. Chronic physiologic malfunction
IlL Pesticide Benefit-Cost: Commercial-Industrial Use
A. Entities receiving benefits or incurring costs
1. Private institutions, agency or individual
a. Manufacturer of pesticide
b. Formulator
c. Distributor
d. Wholesaler
e. Applicator
f. Commercial or industrial user (purchase of
product or service from industry or business)
g. Distributor
h. Retailer
i. Consumer
2. Public agencies
a. Federal government
b. State government
c. Local government
3. Society as a whole
4. Non-human environmental components
a. Marine aquatic
1. Phytological
ii. Zoological
b. Freshwater aquatic
1. Phytolcgical
ii. Zoological
c. Terrestrial
i. Phytological
ii. Zoological
B. Pesticide Benefits Taxonomy
1. Invention, production, and distribution system of
pesticide
a. Increased production of goods by manufacturer
b. Increased sales
c. Conversion of natural resource of marketable
goods
B. 10
-------
d. Gainful employment of people
e. Monetary profit
2. Use in pest suppression
a. Gainful employment of pesticide applicator
i. Monetary profit to business
ii. Employment and wages to employees
b. Suppression of problem pest
i. Hazardous vegetation eliminated
- Fewer damages to utility wires from trees
• Lower right-of-way maintenance costs
- Better visibility along roads
• Fewer accidents to motorists
• . Fewer injuries and loss of life
Less waste of materials, 1. e.,
vehicle s
- Fewer fires along railroads and indus-
trial sites
• Less property damage
• Fewer injuries and loss of life
ii. Reduction in materials and property loss
- Less wood decay and insect damage
Less waste of materials and resources
3. Public agencies
a. Lower maintenance costs for roads
b. Lower police and traffic safety costs associated
with accident investigation
4. Society as a whole
a. Reduction or elimination of hazardous vegetation
i. Reduction in loss of human resources
ii. Reduction in loss of material resources
C. Pesticide costs taxonomy
1. Invention., production, and distribution systems of
pesticides
a. Utilization of scientific resources in discovery
and development
b. Utilization of natural resources in manufacture
c. Utilization of human labor and technical skills
in manufacture
d. Utilization of manufacturing facilities
e. Exposure of humans to pesticide during develop-
ment, manufacture, and distribution
13.11
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i. Human physiologic effects
- Acute injury
- Chronic
• Mutagenicity
• Teratogenicity
• Oncogenicity
• Reproductive impairment
• Chronic physiologic malfunction
f. Spillage and accidental release of pesticides to
environment
g. Human resources and physical facilities in
distribution and marketing
h. Monetary resources in development, manufacture,
and distribution
2. Use in commercial industrial situations
a. Monetary cost for pesticide
b. Resources used in application
i. Monetary cost of applicator services
ii. Utilization of human resources by appli-
cator and employees
c. Storage and disposal of pesticides and containers
d. Spillage and breakage loss and cleanup costs
e. Health effects to applicators and employees or
other pesticide users
i. Acute effects
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
f. Treadmill effect, i.e. , additional pest control
costs
i. Induced pest resistance
ii. Destruction of predators
3. People, lands, plants, facilities or structures
receiving treatment
a. Damage to facilities or structures
i. Discoloration, residues, etc.
B. 12
-------
b. Health effects to people living or working in/on
treated lands or structures
i. Acute
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
— Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
4. Public agencies
a. Pestiide research and development; human
and monetary resources
i. Federal government
ii. State government
iii. Land grant experiment stations
b. Human and environmental health effects research;
human and monetary resources
i. Federal government
ii. State government
iii. Medical research institutes
c. Regulation of esticides; human and monetary
resources
5. Non-human environmental components
a. Acute toxicity
b. Chronic toxicity
i. Mutagenicity
ii. Teratogenicity
iii. Oncogenicity
iv. Reproductive impairment
v. Chronic physiologic malfunction
IV. Pe sticide Benefit-Cost: Aesthetic Improvement
A. Entities receiving benefits or incurring costs
1. Private institutions, agency, or individual
a. Manufacturer of pesticide
b. Formulator
c. Distributor
d. Wholesaler-retailer
e. Applicator
f. Private individual
g. People—oriented business, i. e. , resort,
campground, golf course
B. 13
-------
2. Public agency
a. Federal government
b. State government
c. Local government
3. Society as a whole
4. Non-human environmental components
a. Marine aquatic
i. Phytological
ii. Zoological
b. Freshwater aquatic
i. Phytological
ii. Zoological
c. Terrestrial
i. Phytological
ii. Zoological
B. Pesticide Benefits Taxonomy
1. Invention, production, and distribution system of
pesticides
a. Increased production of goods by manufacturer
b. Increased sales
c. Conversion of natural resource to marketable
goods
d. Gainful employment of people
e. Monetary profit
2. Use in pest suppression and aesthetic improvement
a. Gainful employment of pesticide applicator
i. Monetary profit to business
ii. Employment and wages to employees
b. Suppression or elimination of pest
i. More pleasing appearance to treated plants,
animals, or landscape area
- Higher value of homes, neighborhood,
community
- More happy or content people
- Greater attractiveness of recreation or
resort area (monetary profit to owners,
employment and wages to employees)
- Better distribution of residences and
business in geographic sense
3. Public agencies
a. Less need for governmental inputs
1. Chemical weeding -- reduced costs
b. High value real estate -- bigger tax base
i. Homes
ii. Businesses -- resorts, etc.
B. 14
-------
4. Society as a whole
a. More pleasant surroundings for life
b. More content people
C. Pesticide Costs Taxonomy
1. Invention, production, and distribution system of
pesticides
a. Utilization of scientific resources in discovery
and development
b. Utilization of natural resources in manufacture
c. Utilization of human labor and technical skills
in manufacture
d. Utilization of manufacturing facilities
e. Exposure of humans to pesticide during develop-
ment, manufacture, and distribution
i. Human physiologic effects
- Acute injury
- Chronic
Mutagenicity
Teratogenicity
Oncogenicity
Reproductive impairment.
Chronic physiologic malfunction
f. Spillage and accidental release of pesticides to
environment
g. Human resources and physical facilities in
distribution and marketing
h. Monetary resources in development, manufac-
ture, and distribution
2. Use in human aesthetic improvement
a. Monetary cost for pesticide
b. Resources used in application
i. Monetary cost of applicator services
ii. Utilization of human resources by applicator
and employees
c. Storage and disposal of pesticides and containers
d. Spillage and breakage loss and cleanup costs
e. Health effects to applicators and employees or
householders or other pesticide users
i. Acute effects
- Normal use
- Accidental exposure and spills
B. 15
-------
ii. Chrorii effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
f. Treadmill effect, i.e. , additional pest control
costs
i. Induced pest resistance
ii. Destruction of predators
3. People, lands, plants, facilities or structures
receiving treatment
a. Damage to facilities or structures
i. Discoloration, residues, etc.
b. Health effects to people living or working in/on
treated lands or structures
1. Acute
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
4. Public agencies
a. Pesticide research and development; human
and monetary resources
i. Federal government
ii. State government
iii. Land grant experiment stations
b . Human and environmental health effects research;
human and monetary resources
i. Federal government
ii. State government
iii. Medical research institutes
c. Regulation of pesticides; human and monetary
resources
5. Non-human environmental components
a. Acute toxicity
B. .16
-------
b. Chronic toxicity
i. Mutagenicity
ii. Teratogenicity
iii. Oncogenicity
iv. Reproductive impairment
v Chronic physiologic malfunction
V. Pesticide Benefit-Cost: Environmental Management
A. Entities receiving benefits or incurring costs
1. Private institutions, agency or individual
a. Manufacturer of pesticide
b. Formulator
c. Distributor
d. Wholesaler
e. Applicator
f. Private individual
g. People-oriented business, i.e. , resorts, etc.
2. Public agencies
a. Federal government
b. State government
c. Loca) government
3. Society as a whole
4. Non-human environmental components
a. Marine aquatic
1. Phytological
ii. Zoological
b. Freshwater aquatic
i. Phytological
ii. Zoological
c. Terrestrial
i. Phytological
ii. Zoological
B. Pesticide Benefits Taxonomy
1,. Invention, production, and distribution system of
pesticide
a.
b.
C.
Increased production of goods by manufacturer
Increased sales
Conversion of natural resource to marketable
goods
d. Gainful employment of people
e. Monetary profit
B. 17
-------
2. Use in pest suppression and environmental management
a. Gainful employment of pesticide applicator
i. Monetary profit to business
ii. Employment and wages to employees
b. Suppression or elimination of pest
i. Enhanced quality of environment
- More pleasing appearance of ecosystem
- Higher property values (greater attractive-
ness of recreation areas and resorts in
improved area)
- Better distribution of residences and busi-
nesses in geographic sense
3. Public agencies
a. Lower dollar inputs in environmental maintenance
programs
i. Game and fish agencies
ii. Forestry and environmental agencies
4. Society as a whole
a. Enhancement or preservation of environmental
components given value by man
5. Non-human environmental components
a. Maintenance of balanced ecosystems
C. Pesticide Costs Taxor my
1. Invention, production, and distribution systems of
pesticides
a. Utilization of scientific resources in discovery
and development
b. Utilization of natural resources in manufacture
c. Utilization of human labor and technical skills
in manufacture
d. Utilization of manufacturing facilities
e. Exposure of humans to pesticide during develop-
ment, manufacture, and distribution
i. Human physiologic effects
- Acute injury
- Chronic
• Mutagenicity
• Teratogenity
Oncogenicity
Reproductive impairment
• Chronic physiologic malfunction
f. Spillage and accidental release of pesticides to
environment
B. 18
-------
g. Human resources and physical facilities in
distribution and marketing
h. Monetary resources in development, manufacture,
and distribution
2. Use in environmental management
a. Monetary cost for pesticide
b. Resour:es used in application
1. Monetary cost of applicator services
ii. Utilization of human resources by applicator
and employees
c. Storage and disposal of pesticides and containers
d. Spillage and breakage loss and cleanup costs
e. Health effects to applicators and employees or
other pesticide users
i. Acute effects
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
f. Treadmill effect, i.e. , additional pest control
costs
1. Induced pest resistance
ii. Destruction of predators
3. People, lands, plants, facilities or structures
receiving treatment
a. Damage to facilities or structures
1. Discoloration, residues, etc.
b. Health effects to people living or working in/on
treated lands or structures
1. Acute
- Normal use
- Accidental exposure and spills
ii. Chronic effects
- Mutagenicity
- Teratogenicity
- Oncogenicity
- Reproductive impairment
- Chronic physiologic malfunction
B.19
-------
4. Public agencies
a. Pesticide research and development; human and
monetary resources
i. Federal government
ii. State government
iii. Land grant experiment stations
b. Human and environmental health effects research;
human and monetary resources
i. Federal government
ii. State government
iii. Medical research institutes
c. Regulation of pesticides; human and monetary
resources
5. Non-human environmental components
a. Acute toxicity
b. Chronic toxicity
i. Mutagenicity
ii. Teratogenicity
iii. Oncogenicity
iv. Reproductive impairment
v. Chronic physioiogic malfunction
B. 20
-------
PAKT II
-------
TABLE OF CONTENTS
Page
1.0 INTRODUCTION 1.1
2.0 SUMMARY OF RESULTS z. 1
2. 1 General Information Concerning
the Structure of the Case Study 2. 1
2.2 Agriculturallmpacts 2.2
2.3 Health Effects 2.4
2. 4 Environmental Impacts 2. 6
2. 5 Net Benefits from Use of Fenox
When Substituted for Delta 2. 8
2. 6 Critique and Feasibility of
the Benefit-Cost System 2. 9
2. 6. 1 Difficulties in the Submodel
Approach 2.9
2. 6.2 Difficulties in Formatting
Results 2. 11
2.6. 3 Difficulties in Obtaining
Input Data 2. 13
2.6.4 Difficulties in the Conceptual
Design of the Benefit-Cost
System 2.15
3.0 AGRICULTURAL T MPACTS 3.1
3. 1 Net Internal Benefits to Society 3. 1
3. 1. 1 Acres of Crops Treated -
with Fenox 3.2
3. 1.2 Net Changes in Crop Yield 3.6
3.1.3 Net Changes in Crop Prices 3. 13
3. 1.4 Change in Consumers’ Surplus 3.20
3.2 Net Costs of Pesticide Application 3.20
4.0 HEALTH EFFECTS 4.1
4. 1 Description of Study Pesticide
and Its Next Best Alternative 4. 1
U’
-------
TABLE OF CONTENTS (continued)
Page
4. 2 Subpopulation at Risk 4. 1
4. 2. 1 Pesticide R and D, Manufacturing
and Formulation Workers 4. 2
4.2.2 Field Workers and Other
Farm Personnel 4.2
4. 2. 3 Commercial Farm Applicators 4.4
4.2.4 Society As A Whole 4,7
4.3 Net Health Damages 4.10
4.3. 1 Determination of Net Health
Damages Using Animal
Toxicology Data 4. 10
4. 3. 1. 1 Acute Injury Assessment 4. 10
4.3. 1. 1. 1 Ocular Exposure
Hazard 4.13
4.3. 1.1.2 Dermal Exposure
Hazard 4.15
4.3. 1. 1.3 Oral Exposure
Hazard 4. 18
4. 3. 1. 1.4 Inhalation Exposure
Hazard 4. 18
4.3. 1. 1. 5 Percutaneous
Exposure Hazard 4. 19
4.3.1.1.6 Systemic Poisoning
Hazard 4. 19
4.3.1.1.7 DeathHazard 4.20
4. 3. 1.2 Chronic Injury Assessment 4.20
4.3. 1.2. 1 Metabolism and
Elimination 4.21
4. 3. 1.2.2 Mutagenic Hazard 4.22
4.3.1.2.3 Teratogenic Hazard 4.23
4.3. 1.2.4 Oncogenic Hazard,
Reproductive Impair-
ment, and Physiolog-
ical Malfunction
Hazard 4.24
iv
-------
TABLE OF CONTENTS (continued)
Page
4. 3. 2 Determination of Net Health Damages
Using Human Experience Data 4. 26
4. 3. 2. 1 Acute and Chronic Injury
to R and D, Manufacturing
and Formulation Workers 4.26
4. 3. 2. 2 Acute and Chronic Injury
to Field Workers and
Other Farm Personnel 4.29
4. 3.2. 3 Acute and Chronic Injury to
Commercial Farm Applicators 4. 32
4. 3.2.4 Acute and Chronic Injury
to Society 4. 34
4. 3. 3 Summary of Net Health Damages 4. 36
4.4 Net Health Benefits 4. 40
5.0 ENVIRONMENTAL IMPACTS 5. 1
5. 1 Introduction 5. i
5. 2 Transport and Accumulation 5. 2
5.3 Impacts on Biological Systems 5. 10
5.4 Values of Ecologic Damages 5.14
Attachment 5. 1: Alternative Method to Calculate
Environmental Hazard from
Surface Runoff of Fenox or Delta 5.23
Attachment 5.2: A Method of Calculating the
Quantity of Fish in Inland
Waters by Region .5.30
APPENDIX A: Agricultural Analysis of the Use of A. 1
Pesticide Alternatives to DDT on
Sweet Potatoes, Sweet Corn and
Peanuts in 1973 and 1974
V
-------
1.0 INTRODUCTION
In this volume of the report, the benefit-cost system for analyzing
the use of chemical pesticides is described in the form of a case study.
The benefit-cost system described is constructed as a set of submodels
connected by data transfers, and it is divided into separate submode].s
for convenience of application.
The case study application is intended solely to illustrate the use
of the system, while simultaneously providing a descriptive presenta-
tion of its procedures, formulations, underlying assumptions, and data
requirements. Since the case study is only illustrative, it is applied to
an hypothetical pesticide which has chemical features borrowed from a
class of presently registered, well-known pesticides: the phenoxy herb-
icide group, including 2, 4-D; 2, 4, 5-T; MCPA; and Silvex. Other
meml)ers of the phenoxy group were reviewed, but data were most
readily available on the four named.
The hypothetical herbicide fabricated from these data is called
“Fenox.” Feriox is defined as a pre- and post-emergence herbicide
suitable for multiple treatments of wheat, oats, and barley. Thus, the
herbicide has broad applicability and its use might be expected to be
geographically widespread. The study assumes that Fenox has not yet
been registered, but that it has been tested extensively on the three
crops mentioned, and that some basic test data are available on its
health effects and environmental activity. In some calculations, aver-
ages of parameters from the phenoxy herbicide group were used. For
example, an estimate of the number of acres to which Fenox would be
applied was made, based on the number of acres to which phenoxy herb-
icides had been applied in the past. In other cases, the paramet rs
(degradation rates, toxicity, water solubility, and other features) were
selected from one or another of the group. The particular herbicide
reflected in many calculations is not identified, in order to preserve
the hypothetical and illustrative nature of the analysis.
*These pesticides are defined as follows: 2, 4-D - 2, 4-Dichloro-
phenoxyacetic acid; 2, 4, 5-T - 2,4, 5-Trichiorophenoxyacetic acid;
MCPA - 2-methyl-4-chlorophenoxyacetic acid; and Silvex - 2-(2, 4, 5—
trichiorophenoxy) propionic acid.
1. 1
-------
Given the above two assumptions about Fenox (i. e. , that Fenox
is proposed for registration but not yet registered, and that extensive
testing has been performed), it is important to understand the alterna-
tives available to EPA decision-makers, and thus to society as a whole,
when assessing the request to register Fenox.
First, the decision-makers could choose not to register Fenox.
This alternative implies that they have decided it presents an unreason-
able hazard to man and his environment. In order to assess the effects
of non-registration, some broad assumptions must be made about what
practices farmers are now using and what they are likely to be doing
during the five-year registration period. One simple assumption is
that farmers will continue to engage in their present practices, whether
these are mechanical cultivation, flame suppression of weeds or some
alternative chemical herbicide. This state of affairs could be analyzed
in detail if comprehensive data were available on farming practices in
areas where the three crops are grown. But such data probably would
be attained only by a direct, costly survey. In addition, how can the
farrner T s reaction to a newly registered pesticide be predicted? Each
individual farmer will compare the potential of the new product to the
features of his present weed control program and react according to
the outcome of his own benefit-cost analysis. The reaction could result
in a greater input of chemicals into the environment -- no matter what
the EPA does .
This same statement is true if the EPA does, in fact, register
the new pesticide Fenox. The reaction could involve a greater or less
insult to the environment, depending on the cost of alternatives to the
farmer, the size of his farm, his mix of crops, and his expected crop
value. In other words, the farmer begins each season with an almost
clean slate. He knows that some level of infestation will occur, that
some pesticide residual probably remains in the ground, and that some
increase in immunity has occurred since the previous season. For the
coming season he has an array of alternatives which will include not
only choices of single pest control measures but also combinations of
nechanical, chemical, biological, and other strategies. One of his
choices could be a pesticide newly registered by EPA, but sophisticated
models for analyzing the numerous pest control strategies and predict-
ing what most farmers will do are not readily available.
The above discussion implies that in order for the EPA to prop-
erly consider its own alternatives, the EPA must have available a highly
sophisticated model of the farmer’s consideration of his alternatives.
1.2
-------
The benefit-cost analysis presented in this report can avoid the farmer
decision problem by two tactics:
It can assume that the farmer faces the possibility
of using either Fenox or weed control measures
which are non-chemical and thus that have almost
no health or environmental impact, or
It can assume that some proportion of present crop
acreage will be treated with the new herbicide if it
is registered.
The first assumption lacks realism in the sense that the farmer
who has been using a chemical herbicide will probably continue to do
so on those acres where weeds are a severe problem. It is arguable,
however, that a sufficient increase in herbicide prices would force him
either to change his acreage or to revert to mechanical methods. If he
decides to change his acreage, he may increase acreage and reduce his
weed control costs, or he may reduce acreage and adopt more expen-
sive (mechanical or higher-priced chemical) methods in order to main-
tain constant yield per do]lar of investment. Thus, he may change acre-
age and/or shift to mechanical weed control methods. The alternatives
which are hypothetically open to each farmer are numerous, although,
in fact, any on an individual farmer may be severely restricted.
The second assumption is more realistic than the first. A new
herbicide entering the market is likely to have at least one major advan-
tage: there is no widespread immunity to it. Thus, Fenox, if regis-
tered, would prove attractive to many farmers if its price were rea-
sonably competitive.
The two assumptions lead to the development of one possible sce-
nario which provides a basis for the benefit-cost analysis presented in
this volume of the report. In this scenario, the farmers who raise
wheat, oats, and barley are faced with probable obsolescence of sev-
eral herbicides sometime in the future and have a choice of continuing
For a discussion of obsolescence, see G. K. Kohn, IThe Pesti-
cide Industry, “ in James A. Kent (ed.), Riegels Handbook of Industrial
Chemistry , 7th Edition, New York, Van Nostrand Reinhold, Chapter 1,
1974, p. 624.
1.3
-------
with the herbicide presently used, and/or replanning their acreage
utilization, and/or adopting diffe rent (and perhaps more costly) weed
control measures, including new pesticides, and/or rejecting all pest
control measures. Of these four major strategies, the farmer can hold
his costs constant with respect to previous years by continuing with the
herbicide presently used or by expanding acreage and reducing weed
control measures. In the latter case, his savings on weed control will
be applied to increased costs of cultivation.
The above discussion has described how the EPA decision-maker’s
alternatives and the farmer’s alternatives are closely interconnected.
CONSAD Research Corporation recommends that the OPP acquire and
use a set of simple, concise, f]exible farm budget models for use in
estimating probable farmer reactions to a regulatory decision. The
important point in the preceding discussion is that alternative farnier
reactions must be clearly structured before the EPA alternatives --
which are limited to register, deny registration, or cancellation --
can become meaningful.
The EPA, in spite of certain powers derived from its authority to
determine pesticide labels, does not usually make pesticide application
decisions, but the Agency must consider such choices in benefit-cost
analyses relating to regulatory decisions. Thus, the EPA benefit-cost
analysis must involve an approach whereby alternative decisions are
carefully defined based on probable alternative actions of pesticide
users.
One kind of probable alternative action of farmers would be the
shift to greater use of existing pesticides. For any pesticide presently
registered, a gradually increasing use is likely, due to (1) gradually
increasing immunity of other pesticides, and (2) a need for each farmer
to maximize his management indicators, usually yield per acre per
dollar. The first condition has been discussed above and in Volume .1
of the report. The second condition arises from a complex system of
variables in the overall world agricultural context which will not be
explained in this report. * The gradual shift to greater use of existing
pesticides could thus occur either as a consequence of an EPA denial
*See, for example, N. S. Scrimshaw, “The Worldwide Confronta-
tion of Population and Food Supply,” Technology Review , Vol. 77, 1974,
pp. 20-29; and R. Revelle, “Food and Population, Scientific American ,
September, 1974, pp. 160-171.
1.4
-------
of a new registration, or as a consequence of newly registered pesti-
cides entering the market at high prices or with unproven efficacy.
The benefit-cost methodology developed in this report is capable
of providing comparisons among the various types of farmer reactions
discussed above and caused by either registration, or denial of, regis-
tration, of a new pesticide. This capability is illustrated in the case
study by assuming that if Fenox is not registered, its next best alterna-
tive ‘ t Delta (also an hypothetical phenoxy herbicide which is presently
used) will be continued to be used. This alternative was chosen as it is
a probable alternative action of farmers.
Thus, even though the role of EPA is not to compare the agricul-
tural implications of alternative pesticides, the EPA benefit-cost sys-
tem requires this capability. Such comparative analyses are required
in any case in which alternative regulatory actions contemplated by EPA
would place some farmers in the position of making an immediate choice
between two pesticides having different environmental effects and impli-
cations.
In summary, this introductory section has established the rationale
for using benefit-cost analysis as a strategy for comparing alternative
actions available to EPA decision-makers, and by direct connection,
alternative actions by farmers, and other users of pesticides. The
basic assumptions that farmers will have a variety of reactions avail-
able to any EPA action, and that any new pesticide will be used on some
proportion of acres previously treated by older pesticides, were dis-
cus seth
In Chapter 2. 0 of this volume, a summary of the agricultuial
impacts, health effects, an environmental impacts is presented under
the assumption that Fenox is registered for a five-year period and sub-
stituted for Delta. A critique of the application procedures of the bene-
fit-cost system is also provided. Later chapters of this volume deal
with specific detailed analyses, i.e.
Chapter 3. 0 - - Agricultural Impacts: A brief
description of the model and a sample application
which analyzes the use of Fenox and its alternative
Delta on wheat, oats, and barley is presented.
1.5
-------
Chapter 5.0-- Environmental Impacts: A descrip-
tion of the filtering of Fenox and Delta through the
environment is given, and the probable net effects
on selected higher order species, if Fenox is sub-
stituted for Delta, are explored.
Finally, an appendix has been included which illustrates an adap-
tation of the food, feed, and fiber production submodel of the benefit-
cost system for retrospective analysis. The following question is
posed: What has been the economic impact on sweet potato, sweet
corn, and peanut production since EPA banned DDT in 197Z? The
benefit-cost system uses data from the period 1969 to 1973 to estimate
the 1973 and 1974 economic impacts on production of these three crops.
1.6
-------
2.0 SUMMARY OF RESULTS
In this chapter, the detailed results generated in the following
three chapters for the phenoxy herbicide case study are summarized.
This summary is presented in four sections: agricultural impacts,
health effects, environmental impacts, and net benefits. Furthermore,
in the last section of this chapter, a critique and feasibility of the bene-
fit-cost system, described in Volume I and applied in Volume II, is
provided.
However, before these results are presented, some general infor-
mation concerning the structuring of the case study must first be dis-
cussed, so that the results can be adequately understood.
2. 1 General Information Concerning
the Structure of the Case Study
As indicated in Chapter 1. 0, the analysis perfo rrned in the case
study assumes that a company wishes to register an hypothetical phenoxy
herbicide, Fenox, for use on wheat, oats, and barley crops. Further-
more, the next best alternative to Fenox is defined as Delta, another
hypothetical phenoxy herbicide that is presently being used on wheat,
oats, and barley crops. The characteristics of both pesticides are
assumed to be given by any data of record on the presently registered
phenoxy herbicides, i.e. , 2, 4-D; 2,4, 5-T; MCPA; and Silvex. In addi-
tion, both pesticides are assumed to have the same characteristics,
except in the following respects:
The increased yield on each of the three crops with
Fenox is assumed t.o be double the increased yield
with Delta, when both are compared to the yield
obtained using no pesticide.
The total cost of application for Fenox is assumed
to be five percent higher than it is for Delta.
The ocular and dermal exposure hazards of Fenox
are assumed to be approximately 2 and 1. 5 times,
respectively, the ocular and dermal exposure
hazards of Delta.
2. 1
-------
The toxicity of Fenox to birds and fish is assumed
to be twice the toxicity of Delta to birds and fish
(i. e., the LD5O, LC 5 O, etc., of Fenox is one-half
the LD 50 , LC 50 , etc., of Delta).
The period of analysis is defined as five years, the period of a
pesticide product registration. The year 1973 is used as a base year,
as this year is the most recent year for which much of the necessary
data are published, and 1974 through 1978 is the five-year period
studied. Where monetary evaluations are made, each yearts value is
first determined, then discounted back to its value in 1974, and finally
added together to obtain a five-year discounted total value.
Moreover, the results presented below show the additional bene-
fits and costs of Fenox when compared to its next best alternative Delta.
That is, the analysis assumes that if Fenox is not registered, its next
best alternative Delta will be continued to be used.
2. 2 Agricultural Impacts
Assuming that Fenox receives an EPA registration for use on
wheat, oats, and barley crops, it is expected that one-half of the total
wheat, oats, and barley acres treated with phenoxy herbicides (i.e.,
Delta) will be treated with Fenox. This implies that during the five-
year period, 1974- 1978, 3. 04-3.47 million acres of wheat, 0. 70-0.79
million acres of oats, and 1.78-2.04 million acres of barley will be
treated with Fenox rather than Delta in each of the five years, with the
trend over the five years going from the low number in the range to the
high number in the range.
Based upon application rates of 0.90 lb/acre/year of Fenox or
Delta for wheat, 0.20 lb/acre/year of Fenox or Delta for oats, and
0.46 lb/acre/year of Fenox or Delta for barley, it is expected that 3. 4
million pounds and 3.9 million pounds of Fenox rather than Delta will
be applied in 1974 and 1978, respectively, with a gradual increase from
3.4 million pounds to 3. 9 million pounds during the interim years.
Associated with the substitution of Delta with Fenox on the three crops
are additional pesticide application costs, and the five-year total addi-
tional cost when discounted back to 1974 is estimated at 5. 3 million
dollars to the farmer.
2.2
-------
Furthermore, associated with the application of Fenox, rather
than Delta to selected wheat, oats, and barley crops, is an increase in
their respective yields. More specifically, it is expected that if Fenox
is substituted for Delta, an additional 23. 3 million bushels of wheat,
33. 2 million bushels of oats, and 10. 6 million bushels of barley would
have been produced in 1974. In 1978, these figures are expected to be
an additional 26. 6 million bushels of wheat, 38. 2. million bushels of
oats, and 12. 1 million bushels of barley, if Fenox is substituted for
Delta. For the years 1975 through 1977, it is expected that these addi-
tional yields will gradually increase from the 1974 additional yields to
the 1978 additional yields.
Due to these yield increases, crop prices would have been
expected to decrease in 1974 by 1.99 percent for wheat, 6.12 percent
for oats, and 3. 24 percent for barley. In 1978, it is expected that these
price decreases will be 2. 19 percent for wheat, 5. 96 percent for oats,
and 3. 33 percent for barley. For the years 1975 through 1977, the
price decreases are expected to be within the range specified by the
1974 and 1978 figures.*
The increased total crop output and the decreased crop prices, in
each year over the five-year period as a result of substituting Fenox for
Delta, will affect the farmers’ revenue for these three crops. More
specifically, it is expected that the farmers’ revenue for these three
crops over the five-year period 1974 through 1978 will decrease by a
total amount of 141. 8 million dollars when discounted back to 1974.
This measure, however, gives no indication of the change in the
farmers’ profit as a result of substituting Fenox for Delta. Assuming
the farmer can reduce his total cost of crop production (of which one
small element is pesticide application cost) by sufficiently more than
the decrease in his revenue, he will increase his total profit by uTsing
Fenox rather than Delta. Determination of these effects can provide
an understanding of some of the distributional impacts to the farmer
associated with the registration of Fenox.
The agricultural impacts described above (i. e. , the increased
yields and the decreased crop prices, in each year over the five-year
period as a result of substituting Fenox for Delta) will also produce a
These changes in crop prices do not incorporate the effect of
increased pesticide application costs, but rather only the increased
yields in the three crops.
2. 3
-------
net internal benefit to society -- i.e., a change in consumers’ surplus.
The discounted value in 1974 of this net internal benefit is estimated at
564. 1 million dollars for the years 1974 through 1978, if Yenox is sub-
stituted for Delta.
2.3 Health Effects
If Fenox is registered for use on wheat, oats, and barley crops
and substituted for Delta, the following subpopulation groups are
expected to incur additional health damages as a result of this substi-
tution:
• Pesticide R and D, manufacturing, and formulation
workers,
• Field workers and other farm personnel, and
• Commercial farm applicators.
Society as a whole is also at risk to additional health damage in
an indirect manner, either from drift of Fenox rather than Delta as a
result of misuse or accidental spills or from low-level dietary intake
of Fenox rather than Delta. However, the defined characteristics of
the two hypothetical phenoxy herbicides, the human experience data for
parallel pesticides to Delta and Fenox, and the animal toxicology data
for the two pesticides, indicate that Fenox or Delta would he in such a
dilute form that the likelihood is minimal that drift of Fenox rather than
Delta would cause additional harm to society. Furthermore, the dietary
intake of both Fenox and Delta is determined to be sufficiently close to
zero and the available data give no indication of additional damage, if
Fenox is substituted for Delta. Therefore, no additional health damages
are expected to occur to society if Fenox is substituted for Delta.
Therefore, only those occupationally exposed are expected to
incur any additional health damage if Fenox is substituted for Delta.
Results show that the additional health damages will be only ocular and
dermal in nature, with the highest net incidence of health damage
incurring in the manufacturing and formulating subpopulation and the
lowest net incidence of health damage occurring in the commercial
farm applicator subpopulation, as shown in Exhibit 2. 1.
2. 4
-------
EXHIBIT 2. 1: Net Incidence of Health Damages from Substitution
of Delta with Fenox on Wheat, Oats, and Barley Crops
(Given as number per 1, 000 exposed)
Entfty incurring
Health Damage
Chronic Injury
Injury
Terato- Reproduc- Physlotopc
Morbidity
Inhalation
Mortality
(Death)
Ocular
Exposure
Hazard
Dermal
Exposure
Hazard
Oral
Exposure
Hazard
Exposure
Hazard
Systemic
Polsoniri
Mutagenic
Hazard —
genIe
Hazard
Oncogenie
Hazard
live Im.
pairment
M*ltunction
i-’aeard
Occupational Health Damage to:
Pesticide RhO Manufacturing
and Formulation Workers
96
SZ
0
0
0
0
0
0
0
0
0
Pesticide Transport Personnel
Not date
nilned but a
sumeci to b
negligible
ascd on di
cus.ion . w
h OPP per
onnet
Field Workers and Other Farm
Personnel
10.5
4.1
0
0
0
0
0
0
0
0
0
Commercial Farm App lIcators
0.47
0.18
0
0
0
0
0
0
0
0
Prolessional Non-Farm Appli-
cators (FCOs, government
employeee. etc.)
na
na
na
Ca
ia
na
eta
Ca
Ca
Ca
na
C.nerai Public Health Damage to:
Household Users of Perticides
(through direct expolure)
n a
na
na
na
na
eta
eta
eta
eta
eta
ta
Society as a Whole (through
indirect exposure)
0
0
0
0
0 —
0
0
0
0
0
0
— not applicable
Sin particular with respect to central nervous systemi h.rnatopoeti system. liver and kidney..
-------
When these incidence rates are coupled with the number of people
in each subpopulation group expected to be exposed in each of the five
years 1974 through 1978, field workers and other farm personnel are
expected to incur the most additional health damage and commercial
farm applicators the least, in terms of absolute numbers, as shown in
Exhibit 2. 2.
Quantification of these additional health damages, although desir-
able if possible, was not performed. More detailed information con-
cerning the characteristics of the people injured would be needed for
such an analysis. However, these data could not be easily obtained in
sufficient detail to warrant such an analysis in this case study. Never-
theless, in benefit-cost analyses of real pesticides, attempts should be
made to make such a quantification as this information can prove very
useful to the decision-maker. In this case study, it was demonstrated
in the detailed analysis of health effects (Chapter 4. 0) that because the
additional health damages are occupational in nature, the costs of these
damages are partially embodied in the change in the consumers’ surplus
measure determined in the agricultural impacts analysis.
Health benefits from the use of Fenox, if substituted for Delta,
will accrue to society in the form of a more healthful, more productive,
and more content population, as a result of an increased food suppiy
caused by the increased yields in the three crops described earlier in
Section 2. 2. Once again, quantification of these additional health bene-
fits, although desirable if possible, was not performed. However, in
the detailed analysis of health effects (Chapter 4. 0), it was demonstrated
that the additional health benefits that do accrue to society are reflected
in the change in the consumers’ surplus measure determined in the agri-
cultural impacts analysis.
2.4 Environmental Impacts
In the assessment of the net environmental impacts on society
associated with the substitution of Fenox for Delta on wheat, oats, and
barley crops, non-crop environmental benefits were assumed to be
minor or negligible. However, environmental costs are of concern
because, subsequent to the application of Fenox or Delta on wheat, oats,
and barley crops, some of the pesticide is transported away from the
application site where it accumulates in biological organisms such as
birds and fish.
2. 6
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EXHIBIT 2. 2: Number of Additional People Expected to Incur
Health Damage from Substitution of Delta with
Fenox on Wheat, Oats, and Barley Crops
(Given as number per year for 1974-1978)
Kotity Incurring
Health Damage
Type of Health Damage
Acute lr jj
Chronic Injury
Morbidity
Mortality
(Death)
Mutagenic
Hazard
Terato-
genic
Hazard
Oncogenlc*
Hazard
Reproduc-
tive Im—
pairment
Physiologic
Mattunction
Parard’
Ocular
Expoaure
Hazard
Derr a1
Expozure
Hazard
Oral
Exposure
Hazard
Irhalation
Exposure
Hazard
Systemic
Poisoning
Occupational Health Damage to:
Pesticide R&D Manufacturing
and Formulation Worker.
5—7
3-4
0
0
0
0
0
0
0
0
0
Pesticide Transport Personnel
Not dde
iiLncd but u
aumed to b
negligible
,a ed on th
cusilons w
th OPP per
onnel
Field Workers and Other Farm
Per.onrtel
373.374
146-147
0
0
0
0
0
0
0
0
0
Commercial Farm Applicators
1-2
0-1
0
0
0
0
0
0
0
0
0
Pro(e.sionai Non-Farm Appli-
cators (FCO., government
employees, etc.)
iii
na
i a
sir.
si c
na
na
na
as
na
0*
Ceneral Public Health Damage to:
Houiehold Users of Peiticides
(through direct exposure)
na
na
i sa
na
isa
na
na
na
na
0*
0*
Society as a Whole (through
indirect exposure)
0
0
0
0
0
0
0
0
0
0
0
-J
fla a not applicable
*ln particular. with respect to central nervous system, hematopoetic system, liver *nd kidneys.
-------
The environmental analysis assumed that based upon the applica-
tion rates for Fenox or Delta on the three crops, and other defined
characteristics of the two hypothetical herbicides, the amount of either
pesticide accumulated in fish and birds would be similar. However,
the effect of this accumulation will be different because Fenox is defined
to be more toxic than Delta to birds and fish. More specifically, if
Fenox is substituted for Delta, it is expected that during the five-year
registration period of 1974 through 1978, the number of ad’iitional birds
killed will be approximately 2. 5 million. For fish, it is expected that
an additional 154 million will be either killed or not produced during
the five year registration period. These numbers correspond to a
total discounted value in 1974 of 10. 7 million dollars for fish and bird
damages for the five year registration period. It should be emphasized
that this value of additional environmental damage is an underestimate
due to the lack of total costs for restocking and due to the lack of esti-
mates of additional mammals, including both small and large game,
lost due to accumulation of Fenox rather than Delta in the food chain,
2. 5 Net Benefits from Use of Fenox
When Substituted for Delta
The net benefits to society from the use of Feriox when it is sub-
stituted for Delta consist of the net internal benefit plus the net external
benefit of using Fenox if substituted for Delta.
It has been determined in Section 2. 2 that the discounted value in
1974, of the net internal benefit to society, associated with the substi-
tution of Delta with Fenox on wheat, oats, and barley crops, i 5 equal
to 564. 1 million dollars for the five year registration period 1974
through 1978. Furthermore, it has been stated that the additional
health benefits received by society during this time period are embodied
in this measurement, but that the additional health costs incurred by
the occupationally exposed during this time period are only partially
embodied in this measurement.
In addition, not embodied at all in this measufement are the add i-
tional pesticide application costs to the farmer when Fenox is substi-
tuted for Delta. The reason for this is that the crop price forecasting
algorithm used in the case study did not incorporate increased pesticide
application cost factors. The refore, the additional pesticide application
2. 8
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costs of 5. 3 million dollars for the five years when discounted back to
1974 must, in this instance, be subtracted from the net internal benefit.
The net external benefit to society associated with the substitution
of Delta with Fenox consist of additional external costs and thus is nega-
tive. The major external costs consist of the additional environmental
damages caused if Fenox is substituted for Delta. They have been esti-
mated at 10. 7 million dollars for the five-year registration period when
discounted back to 1974. Additional external costs that are not quanti-
fied consist of additional occupational health costs not embodied in the
consumers’ surplus measure, as well as undetermined restocking costs
and costs for additional mammals lost.
Therefore, the five-year net benefits to society (discounted back
to 1974) associated with the substitution of Fenox for Delta on wheat,
oats, and barley crops can be estimated as: 564. 1 million dollars -
5.3 million dollars - 10. 7 million dollars 540. 1 million dollars.
Emphasis must be made that these net benefits are an overestimate as
the value of the net external benefit (or more specifically, external
costs) has not been fully quantified in monetary terms. Nevertheless,
it does appear that the registration of Fenox for use on wheat, oats, and
barley will provide substantial net benefits to society when compared to
its next best alternative Delta. Distributional impacts may favor some
subpopulations and injure others. However, an adequate determination
of these impacts has not been made and therefore cannot be put into a
matrix form for viewing by the decision-maker.
2.6 Critique and Feasibility of
the Benefit-Cost System
2. 6. 1 Difficulties in the Submodel Approach
The purpose of this section is to critique the procedures applied
and the results obtained in the three detailed submodel chapters 3. 0,
4. 0, and 5. 0. As noted in the Introduction, the benefit-cost system is
applied in the format of three submodels, although additional submodels
*In most analyses, these costs will be embodied in the consumers’
surplus measure and will serve only to indicate distributional impacts.
2.9
-------
may be needed in other case applications. The three submodels applied
in the reported case study are the food, feed, and fiber production sub-
model, the health effects submodel, and the environmental effects sub—
model. Each of these submodels has within it a series of algorithms
(i.e., sub-submodels) which are intended to be reasonably standard for
more than one benefit-cost analysis, and hopefully, for many such anal-
y se S.
In other words, the present benefit-cost system attempts to do
what many benefit-cost methodologies attempt to do, usually without a
great deal of success: standardize and format a benefit-cost procedure
which will be reasonably applicable over a series of pesticide benefit-
cost applications, providing both flexibility, as well as a standard,
simplified set of procedures in the same overall system. One approach
to the standardization of the system is the identification of broad sub-
models which provide general headings under which to group algorithms
which typically draw on the same data sources. For example, under
the food, feed, and fiber production submodel, there are grouped aJgo-
rithrns for calculating acreages of crops harvested in future years, those
acreages of these crops to which a given type of pesticide is likely to be
applied, and changes in yield of those acrcages where the pesticide was
applied.
These different algorithms all require input data from time series
agricultural data sets, although different forecast studies and documents
may be available for selection and use in any given benefit-cost applica-
tion. Where such choices exist, an attempt has been made to document
them and to explain the reason for the choice which was made. In addi-
tion to the time series acreage data, several algorithms require farm
management data on pesticide application acreage and rates per acre.
Thus, algorithms which require similar input data are grouped into the
same submodel, since their inputs and outputs are usually linked.
Thus, the algorithms applied in each of the submodels are directed
toward the calculation of benefits and costs which are specific to the
general heading of the submodel. The health effects submodel, for
example, calculates health costs arising from health damages due to
the dispersal of pesticides through the environment. This same sub-
model would also be used to calculate health benefits arising from the
use of a public health pesticide effort (e. g., rodenticide use, mosquito
control, cockroach control). In the typical agricultural pesticide use
situtation, however, there arc no easily defined health benefits, and a
detailed analysis of health benefits is not shown in the present case
2. 10
-------
example. But such benefit calculations would use data on populations
exposed, probabilities of illness, and severity of reaction to disease,
similar to the data used in the health damages calculations presented
in this report.
This lack of development of certain selected submodel compon-
ents, such as health benefits, along with the previously mentioned diffi-
culties associated with devising both a flexible, broadly applicable
system and also a simple, standardized set of procedures, are probably
the most prominent criticisms of the system as developed in the present
report. The lack of development of certain submodel components is not
a severe criticism because neither in a limited system development
effort, nor in a specific case study, should there arise the expectation
that all conceivable sub-analyses would be explicated. Nevertheless,
the reader is left with the vague discomfort that surely some portion of
a benefit or cost to some subpopulation has gone uriquantified. The
problem arises because the comprehensive, fully extensive structure
of the benefit-cost matrix is not applicable in every case study, and yet
those components which are not applicable tend to raise the question,
Wasn’t something left out?
Similarly, the reader does not see displayed before him a com-
pletely symmetrical accounting system, in which every cost leads
directly to some benefit, which enables the ready calculation of a series
of net benefits. A natural response is to question whether the achieve-
ment of some particular benefit contributes ttsubstantially r to any par-.
ticular costs. If, for example, the farmer applies 1. 1 pounds per acre
of Fenox, instead of 0. 9 pounds per acre, he probably achieves a higher
yield for a two or three season period. Does the increment of addi-
tional pesticide ‘ 1 really” have any increased impact on the environment?
These are detailed accounting questions which the system can answer,
but only through successive iterations of large numbers of calculations.
Similarly, which component of the benefits from increased yield is the
component which corresponds directly to some proportion of fish popu-
lation lost? This correspondence is another kind of symmetry which is
rarely attainable.
2. 6,2 Difficulties in Formatting Results
The above points lead to the problem of formatting results. The
formatting problem is serious in most benefit-cost analyses, and
reflects the difficulty not only of what kinds of final ratios or net values
to select as sophisticated indicators, but also of the design of graphic
2.11
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or tabular displays. Typically, the decision-makers who expect a lot
from benefit-cost analysis arc seeking a final summary of results in
some type of accounting format where various component costs are
clearly connected to the ‘corresponding’ benefits, and the final net
values or ratios clearly distinguish among the alternative actions.
People who work on the actual conduct of benefit-cost analyses find
this kind of final summary difficult to achieve, both technically and
ethically.
Such a summary is difficult to achieve technically because of the
dynamic, sequential nature of events which are modeled and analyzed
in a benefit-cost study. The specific benefits and costs occur over long
periods of time, in quasi-causal sequences, the various items ‘ dropping
out” occasionally as the natural sequence of events evolve. Nowhere is
this more true than in the development of ecologic damages and costs,
where increases in costs of maintaining wildlife populations occur spUr-
adicallv as pesticide residues accumulate biologically and add complex-
ity to the ongoing population cycles of various species. The application
of the enviroornenta I effects submnodel in this report: illu strafe a way to
depict each type of cost or damage as it occurs in the natural sequence
of impacts, but a final suinma table is not achieved.
If such a table were derived, showing damages to water quality,
fish, and higlic r species, it would cause some confusion, and would
raise ethical questions about its derivation, since none of the damages
and costs would be independent’ in the sense that they arose separately
from the initial action of pesticide application. All of these successive
costs probably would be avoided if an alternative action were taken
which did not include the registration of the pesticide (e. g. , Fenox).
But they do not necessarily impinge on society as separately measured,
non-overlapping costs.
In other words, is the aesthetic cost of a reduction in stream or
lake water quality the same or a different cost from that of replacing
the fish in that same lake or stream —— after all, the fish die fo i- the
same reason that the water stinks? Thus, summation of these costs
might not be justifiable, and the refore, they a me not pre sented in a
table form in the final summary, but rather in a series of conciSC
paragraphs. But even this less than bard facts approach suffers from
an inability to convey adequate warning to the decision—maker, which,
if added in the form of caveats, could produce a presentation which
loses sight of the essential information and also loses any trace of
conciseness and simplicity of formatting.
2. 12
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2. 6. 3 Difficulties in Obtaining Input Data
One of the most severe data problems appears almost at the out-
set of the benefit-cost system, i. e. , in the initial stages of the agricul-
tural submodel. This is the problem of determining the quantities of
specific pesticides used on specific crops. There are actually four
variables of interest:
• Pesticide used,
• Amount applied,
• Crop treated, and
• Number of acres treated.
In addition, it would be desirable to know the number of applications
per season, the time of each application, the .mount applied each time,
and whether the method was aerial, surface or soil injection.
Having comprehensive data, in some reasonable geographic detail,
of the type defined above would put a completely different light on the
conduct of the type of benefit-cost system described in this report.
Calculations in the agricultural subniodel would bee ome much more
realistic and convenient, and the assessment of subpopulation effects
in the health effects submodel would also improve. The environmental
effects submodel would be able to reflect seasonal timing of impacts,
and would be able to reflect the different effects arising from different
types of application.
The only source of these data available to date has been the two
surveys conducted h the U. S. Department of Agriculture, Economic
Research Service, in 19&6 and 1971. This effort is continuing and
hopefully more recent data will soon be available. The results p ih-
lished in reports of the two previous surveys did not contain data in
geographic detail below the regional level, and data on numbers of
applications per season and type of application method were not given.
Hopefully, the reports of new surveys will have the desired detail.
This is a good place to re-emphasize that the usefulness of a pesticide
benefit-cost system is going to depend heavily on its accessibility and
Eichcrs, T. , Quantities of Pesticides Used by Farmers in 1966 ,
Agricultural Economics Report No. 179, 1970, pp. 4Z 44; and P. A.
Andrilenas, Farmers’ Use of Pesticides in 1971: Quantities , USDA,
ERS, Ag ricultural Economics Report No. 252, 1974.
2. 13
-------
operability by a large number and a large variety of people, agencies,
and firms. If the system has to depend on data collected in special
surveys (i.e. , data not widely available), then the results of analyses
performed using the system will never gain credibility, and will never
be acceptable as factors in regulatory decisions.
A second type of data which is not available and which will present
a problem to the system user is the type of data needed to answer the
question of long-term effects on human health from small amounts of
pesticides in the human body. Although data derived from toxicological
studies of laboratory animals has gained increasing acceptance as the
basis for estimates of incidences of various diseases in people, it is
time to start developing some alternatives to the laboratory animal
techniques. These new approaches should involve the combining of
results from both epidemiological studies of certain ailments, and also
statistical studies of the type which Lester Lave has conducted on the
probabilities of people with certain diseases having been exposed to
certain levels of air pollution in their environments. In addition to
these types of studies, a third type of study in the medical field would
be useful, wherein the mechanisms by which small amounts of certain
classes of molecules in the human body engender certain diseases or
malfunctions are explored. At present, work is in progress on all
three types of studies, but the outlook for early success is uncertain.
As data become available from these three types of studies, these data
should be integrated into the health effects submodel.
Problems in the use of the environmental effects submodel arise
not only from lack of data on impacts and effects, but also from lack of
data on values of wildlife and aesthetic features of the environment.
Nevertheless, what is most lacking in the environmental effects sub-
model are some comprehensive, detailed formulations for expre sing
the routes and mechanisms of impingement of pesticides on wildlife.
A standard model for describing pesticide drift from aerial spraying
should be obtained, plus models for runoff from cropland into lakes
and streams.
*Lave, Lester B., and Eugene P. Seskin, wAir Pollution and
Human Health, “ Science , Vol. 169, No. 3947, August 21, 1970,
pp. 723-733.
2. 14
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2. 6.4 Difficulties in the Conceptual Design
of the Benefit-Cost System
Several conceptual issues continue to exist in the benefit—cost
system, and they were not completely resolved in the case study.
Therefore, numerous assumptions had to be made, and they are pre-
sented and explained in the detailed analyses in Chapters 3. 0, 4. 0,
and 5. 0. Thus, a series of concep :ual reviews of the systcru will be
necessary as better data is developed, so that the assumptious made
can be refined, based upon the most recent knowledge available.
2. 15
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3.0 AGRICULTURAL IMPACTS
3. 1 Net Internal Benefits to Society
The analysis presented in the food, feed, and fiber production
submodel of Volume I of the report has generated the conclusion that
the value of the net internal benefit attributable to an increase in yield
Of an agricultural crop is appropriately measured by the change in
consumers’ surplus which is produced by this yield increase. More-
over, this analysis asserts that this change in consumers surplus,
attributable to the application of Fenox rather than Delta, can be approx-
imated reasonably by:
CS P t Q , + 1/2 Pit.
where: ACSjt the estimated change in consui-ners’
su rp us att r butab e to the appLe ation
of Fe nox to crop in yea r t, when corn —
pared to its next best alternative Delta,
Pjt the net change in the price of one unit
of crop j atl;ributable to the a ppi ication
of Fenox in year t, when compa red to
its next best alternative Delta,
= the total output of crop in year (t—l),
and
the net change in the total output of
crop i in the nation attributable to the
application of Fenox in year t, ‘ahen
compared to its next best alternative
Delta.
Three crops were chosen for analysis - wheat, oats, and barley.
These were selected as important econoniicallv and as representative
of a broad use of herbicides, i.e. , a demand which is not presently
filled by any one herbicide and which is not characterized by an one
weed. Furthermore, as indicated above, two hypothetical phcnoxv
herbicides are being compared -- Fenox which is being proposed for
registration and Delta which is defined as its next best alternative.
3. 1
-------
The agricultural characteristics of Fenox and Delta are based upon any
data of record on phenoxy herbicides and are similar in all respects,
except for their respective increased yields per acre for the same
application rate when compared to no pesticide and their respective
costs of application.
A five-year period, beginning with 1974 and ending with 1978,
was selected for analysis. The year 1974 was chosen because this was
the year in which the study began and 1978 was chosen because it is five
years later, the period of registration for any pesticide. However,
1973 was also chosen as the base year because it is the most recent
year for which production data are available.
Throughout much of the analysis, data for only two years - - 1973
and 1978 -- are presented. However, in the determination of the change
in the consumers’ surplus measure for 1974 through 1978, values for
1974 through 1977 are also presented and then discounted back, along
with the 1978 value, to their value in 1974. A more accurate and desir-
able procedure is to interpolate the data for 1974 through 1977 at each
step in the determination of the consumers’ surplus measure. However,
because this case study is an exercise in showing the applicability of
the methodology using an hypothetical phenoxy herbicide, these increased
calculations were felt to add little to the presentation. Therefore, the
“short-cut” procedure, as indicated above, was used.
In the determination of CSjt defined above, five year forecasts
of Q require calculation, but published sources of large-scale data may
be used.* The calculations of and PJt require substantially more
data manipulation. These manipulations are described in detail in the
following sections.
3. 1. 1 Acres of Crops Treated
with Fenox
The first step in arriving at the net internal benefits is to calcu-
late the number of acres of the crops mentioned which were treated by
herbicides during the production years named. Later, it will be neces-
sary to determine the change in yield of the crop which results from the
use of the herbicide.
*For example, see A ricu1tura1 Statistics and the Census of Agri-
culture .
3. 2
-------
The number of acres of any particular crop which are treated
with a pesticide varies with the observations of infestation (insects,
weeds) by the farmer and with his hopes and expectations of a good
yield. Because of data limitations, it is necessary to perform calcu-
lations which allocate the number of acres treated by all herbicides
among the acres of a specific crop treated by a specific herbicide.
Proportional allocating factors can be obtained as shown in Exhibit 3. 1,
which gives the results of applying the formula:
FC = TCAJ/TA,
which calculates the proportion of acres of a specific crop j, to which
all herbicides have been applied.
The results shown in Exhibit 3. 1 can be used to estimate the
actual numbers of acres, based on the corresponding proportion of
crop j, a specific crop, to which all herbicides have been applied in
year t. These calculations are shown in Exhibit 3. 2. The variable
“specific crop acres treated by herbicides” is calculated by applying
the proportion FC , as derived in Exhibit 3. 1, to the acres of all crops
treated by herbicides, to obtain the number of acres treated by all
herbicides for:
• Wheat, and
• Other grains.
The basic data on acres of all crops treated by herbicides are obtained
from the Census of Agriculture , hut the proportions for crops, as well
as for regions, are obtained from the USDA survey. **
If, however,’ the number of acres treated of crop j are actually
acres of a crop category which is more aggregate than the crop under
consideration in the pesticide registration process, additional disaggre-
gation can be performed by using data on acres harvested from Agricul-
tural Statistics , an annual publication of the U. S. Department of Agri-
culture.
*U. S. Bureau of the Census, Department of Commerce, Census
of Agriculture, 1969 , data reproduced in D. L. Fowler and J. N. Mahan,
Pesticide Review, 1972 , USDA, Stabilization and Conservation Service,
197a, p. 35.
**Cjted in Exhibit 3. 1.
3.3
-------
EXHIBIT 3. 1: Calculation of the Proportion of Total
Acres of crop j Treated With Herbicides
Where j = wheat; other grains
=_wheat
— = other grains
1966
Acres
1971
Acres
1966
Acres
1971
Acres
TCA
TA *
Average FCr*
--
16,660,000 25,584,000
112,455,000 213,652,000
0.04815 0. 11975
0. 083950
10,163,000 12,517,000
112,455,000 213,652,000
0.09037 0. 05859
0. 074480
L
“Othcr grains t ’ includes oats, mixed grains, barley, and rye.
**TCA = total crop acres treated by all herbicides, crop j, and
TA total acres of all crops treated by all herbicides.
= TCA•/TA = ( Acres of crop treated )
- \ Total acres treated
** Although the two years data for wheat and other grains show
shifts in the proportion FC , it was not felt that a trend could be indi-
cated by such limited data. Therefore, an average of the two years
data was felt to provide a more reliable estimate.
Sources: T. Eichers, Quantities of Pesticides Used by Farmers
in 1966 , Agricultural Economics Report No. 179, 1970,
pp. 42-44; and P. A. Andrilenas, Farmers 1 Use of
Pesticides in 1971: Quantities , USDA, ERS, Agricu1
tural Economics Report No. 252, 1974.
3.4
-------
EXHIBIT 3.2: Calculation of Acres Treated with All Herbicides
for Selected Years, Regional Shares (TCAjkt)
(Acres in thousands)
*Proportiona calculated from data in P. A. Andrilenas, E• cit., 1974. Appendix
total acres to regional total acres in 1973 and 1978.
*Sec Exhibit 3. 5.
Table 10, pp. 40-4 1. (Used to allocate United States
U i
I
North-
east
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South- Delta
east States
em
Plains
Moun-
tam
Pacific
States
Total
1971
All crop acres treated with
herbicides (regional proportions) 4
.02802
.11870
.31382
.18660
.04414
.04049
.09639
.06563
.05577
.05044
1.00000
1973
All crop acres treated with
herbicides
Wheat acres treated with herbicides
(0. 08395 of all crop acres)
Other grain acres treated with
herbicides (.0. 07448 of all crop
acres)
2, 241
188
167
9,494
797
707
25, 000
2, 099
1,862
14, 925
1,253
1,112
3, 530
296
263
3,239
272
241
7, 710
647
574
5,249
441
391
4,461
375
332
4. 034
339
301
79, 982*4
6,714
5,957
1978
All crop acres treated with
herbicides
Wheat acres treated with herbicides.
(0. 08395 of all crop acres)
Other grain acres treated with
herbicides (0. 07448 of all crop
acres)
2,636
221
196
11, 169
938
832
29, 528
2,479
2, 199
17, 557
1,474
1,308
4, 153
349
309
3,810
320
284
9,069
761
676
6,175
518
460
5,248
441
391
4,746
398
354
94, 091*
7,900
7,008
-------
In the present case study of a fabricated hypothetical phenoxy
herbicide Fenox, it was necessary to disaggregate the crop category
“other grains” to acres for barley and acres for oats (see Exhibit 3. 3).
The acres for wheat treated by herbicides were available directly from
USDA surveys, as shown in Exhibit 3. 2, and the final results for the
three specific crops -- wheat, oats, and barley -- are shown in
Exhibit 3.4. The data for the year 1978 are all obtained by factors
shown in Exhibit 3. 5. In other words, acres harvested were readily
available for 1973, so that the proportions within the category Hother
grains” could be determined. These proportions (FC ) were then
applied to acres treated as shown in Exhibit 3. 2 to obtain the acres
treated as shown in Exhibit 3.4. Since these data were only for 1973,
it was necessary to forecast through 1978 using the published forecasts
cited in Exhibit 3. 5.
It is now necessary to estimate the proportion of these acres
treated by herbicides which were, and which will be, treated by the
hypothetical herbicide Fenox. Using the formula shown in Exhibit 3. 6,
proportional factors can be obtained from USDA survey data. Since the
herbicide Fenox under consideration is hypothetical, hypothetical values
for FDijmt, as shown in Exhibit 3. 7, can b used. These factors deter-
mine the total expected usage, or market penetration factor, if Fenox
were to be registered. As indicated by the factors chosen, it is hypo-
thetically assumed that Fenox, if registered, will be substituted on one-
half the acres treated with phenoxy herbicides (i.e. , Delta). The final
results of applying these factors to the total acres treated (Exhibits 3.4
and 3. 5) are shown in Exhibit 3. 8.
3. 1.2 Net Changes in Crop Yield
The testing of the efficacy of pesticides for improving cropyields
in field—like situations is typically conducted on test farms which are
operated by experiment stations and other agencies in all parts of the
country. If the changes in yield per acre are reported consistently by
the experiment stations in some conventional units of weight, then it
becomes a relatively simple procedure to calculate the difference which
is observed between the yield which is obtained when the proposed new
herbicide is applied to a crop and the yield which is obtained when no
herbicides are applied to that crop. This also facilitates the compari-
son with the next best alternative herbicide, Delta, to get a net effect
for the herbicide under consideration.
3. 6
-------
EXHIBIT 3.3:
1973 Acres Harvested for Selected Crops (Thousands)
Calculation of FC- (Proportion of acres harvested
for a specific crop within a category)
Acres \
Harvested \ Proportion
\ of Total
North-
east
Lake
States_
Corn
North-
em
Plains
Appa-
lachian
South-
east
Delta
South-
em
Plains
Moun-
tam
Pacific
(A) Other grains
barley, rye, oats
(THAm)*
1,029
5,320
1,707
8,504
451
356
95
1,361
3,965
1,882
(B) Barley (HA )
202
938
50
3, 534
239
38
---
325
3,506
1,595
B/A = FC j
. 19631
. 17632
.02929
.41557
. 52993
. 19674
. 00000
.23880
.88424
.84750
(C) Oats (HA )
766
4,250
1,597
4,500
180
169
95
844
439
270
C/A = FC
.74441
.30019
.93556
.52916
.39911
.47472
1.00000
.62013
.11072
.14346
THAm acres harvested in a general crop category m: values for barley and oats are HA . the acres harvested
for specific crops. See USDA, Agricultural Statistics, 1974 , tables for barley and oats (Tables 2, 50, and 59,
pp. 2, 37, and 43).
-J
-------
EXHIBIT 3.4: Calculation of Acres Treated by All Herbicides
for Oats and Barley (TCAjkt) (Acres in thousands)
Region (k)
North-
east
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
South-
em
Plains_
Moun-
tam
Pacific
1973 167
1978 196
707
832
1,862
2,199
1,112
1,308
263
309
241
284
574
676
391
460
332
391
301
354
1973 33
1978 39
125
147
55
64
462
544
139
164
26
30
-—-
---
93
110
294
346
255
300
1973 124
1978 14E
212
250
1,742
2,057
588
692
105
123
114
135
574
676
243
285
37
43
43
51
*TCAmjt total acres treated with herbicides in crop category m.
**TCAjkt = (FC ) (TCAm 5 t)
-------
EXHIBIT 3. 5: Calculation of Total Acres Treated with Herbicides (TCAJkt)
for Wheat, Oats, and Barley, United States Totals
All Crops
(thousands
of acres)
Wheat + Oats
+ Barley
(thousands
of acres)
‘0
Acres Harvested 1964
1969
1971
1973
1978
1985
298, 0001
290,0001
305, 0001
322,0001
378,804
458, 3316
80, 1772
75,038
78,512
75,430
71, 1146
Acres Treated 1964
by Herbicide 7 1969
1971
1973
1978
60,7838 60,783/298,000 = 0.20397 Average
84,914 84,914/290,000 = 0.29281 0.2483910
---
79,982 = (322,000). (0. 24839)
94,091 (378,804). (0. 24839)
16,35411
21,97211
--—
19, 50211
18, 73611
1 USDA, Agricultural Statistics, 1974, Table 625, p. 440.
2 USDA, Agricultural Statistics, 1966, pp. 2, 39, and 45.
3 USDA, Agricultural Statistics, 1971, pp. 2, 36, and 42.
4 USDA, Agricultural Statistics, 1974, pp. 2, 37, and 43.
5 lnterpolated from 1985.data.
6 Smith, Allen, etal., Projections of the U. S. Farm Subsector and Policy Implications, USDA, 1974,
p. 31.
7 Excludes pasture and rangeland.
8 ij. S. Bureau of the Census, 1964 Census of Agriculture, Vol. II, Chapter 10, Table 11, p. 1054.
9 Fowler, D. L., and J. N. Mahan, Pesticide Review, 1972, USDA, 1973.
10 Although the two years data show an upward shift in this proportion, it was not felt that a trend could be
indicated by such limited data. Therefore, an average of the two years data was felt to provide a more
reliable estimate.
11 Wheat, oats, and barley acres treated = (total acres treated with herbicides)
(wheat. oats, and barley acres harvested)
total acres harvested, all crops
-------
C
EXHrBrT 3.6:
Acreage in Specific Herbicide Use, 1966—1971 (National data)
FPC = TCPA JfTCA * (Acres in thousands)
*FPC = the proportion of the total number of acres of crop j in the nation to which herbicides
have been applied which constitute acres to which pesticide i has been applied in the
survey year,
TCPA1J the total number of acres of crop j in the nation to which pesticide i has been applied
in the survey year,
TCA the total number of acres of crop j in the nation to which herbicides have been applied
during the survey year.
Sources: Eichers, T., etal., Quantities of Pesticides Used by Farmers in 1966 , USDA, ERS,
Agricultural Economics Report No. 179, Washington, D.C., 1974, Table 25, pp. 41-44;
and P. A. Andrilenas, Farmers T Use of Pesticides in 1971: Quantities , USDA, ERS,
Agricultural Economics Report No. 252, Washington, D.C., 1974, Table 9, pp. 36-39.
1966
1971
Wheat
Other Grains — Wheat
Other Grains
(A) Total Herbicides
(TCA 3 )
16,600
10,613
25,584
12,517
(B) 2,4-D TCPA J
FPCi
(B/A)
13,733
0.82729
8,053
0. 75879
19,268
0. 75313
7,504
0. 59950
(C) MCPA TCPA 1
FPCIj
(C/A)
766
0. 04614
1,522
0. 14341
3,189
0. 12465
3,850
0. 30758
(D)AllPhenoxy TCPA 1
FPCij
(D/A)
14,577
0.87813
9,692
0.91322
22,567
0.88207
11,585
0.92554
-------
EXHIBIT 3. 7: Calculation of Proportion of Herbicide-Treated
Acres on Which the Hypothetical Phenoxy
Herbicide Fenox Would Be Used (FPCjjt)*
FPCmj
FDijmt
(FPCmj) ( ijmt) —
Wheat
Other
Grains
Wheat
Other
Grains
Wheat
Other
- Grains
2, 4-D
1973
MCPA
0.82729
0.04614
0. 75879
0.14341
0.50
0.50
0. 50
0.50
0.41365
0.02307
0.37940
0.07171
Z,4-D
1978
MCPA
0.75313
0. 12465
0.59950
0.30758
0.50
0.50
0.50
0.50
0.37657
0.06233
0.29975
0. 15379
FPC t = 2,4-D + MCPA: 1973 0.43672 (wheat); 0. 45111 (other grains)
1978 = 0.43890 (wheat); 0. 45354 (other grains)
*FPCIjt (FPCmj) (FDijmt) where FPC 1 t = the proportion of the total number of acres of crop j
in the nation to which pesticide i will beapplied in year t, FPCmj the proportion of the total
number of acres of crop j in the nation to which herbicides have been applied which constitutes
acres to which pesticide m has been applied in the survey year (equivalent to FPC of Exhibit 3. 6),
and FDijmt = the proportion of the total number of acres of crop j in the nation to which pesticide m
is applied in the base year and pesticide i is expected to be applied in year t; i = Fenox and m = Delta.
-------
EXHIBIT 3.8: Calculation of Acres Treated with Hypothetical Herbicide Fenox
TCPAI 3 kt (FPc t) (TCAjkt) (Acres in thousands)
North-
east
.
Lake
States
Corn
Belt
North-
em Appa-
Plains iachian
South-
east
Delta
South-
em
Plains
Moun-
tam
Pacific
Wheat 82
Barley 15
Oats 56
Total 153
348
56
96
917
25
786
547
208
265
129
63
— 47
119
12
51
283
--
259
193
42
110
164
133
17
148
115
19
500
1,728
1,020
239
182
542
345
314
282
Wheat 97
Barley 18
Oats 81
Total 196
412
67
113
1,088
29
933
647
247
314
153
74
56
141
14
61
334
--
307
227
50
129
194
157
20
175
136
23
592
2,050
1,208
283
216
641
406
371
334
*TCPAjJkt = acres of crop j in region k treated with herbicides i in year t.
= acres treated with all herbicides (see Exhibits 3.2 and 3.4).
= estimated proportion of all herbicide-treated acres which are treated with hypothetical
herbicide Fenox (see Ex’hibit 3.7).
0
C.,,
T CA kt
FPC 5 t
-------
The yield difference from the proposed herbicide to its next best
alternative can then be applied to the estimated number of acres of the
crop treated, in order to obtain the total net change in yield for the
specific herbicide, and for the specific weeds. The simplified calcula-
tions for total net increased yield are performed according to the
formula:
= jkt TCPAjkt
where: Q 3 kt = the net change in the total output of
crop j in year t in region k attributable
to the application of Fenox, when com-
pared to its next best alternative Delta,
Yjkt = the net change in the yield per acre of
crop j in region k attributable to the
application of Fenox in year t, when
compared to the next best alternative
Delta, and
TCPAjkt = acres of crop j in region k treated with
Fenox in year t.
The values of jkt used are shown in Exhibit 3. 9, along with the
reports of experimental tests on which they arc based. TCPA kt has
been calculated and is shown in Exhibit 3. 8. The total net change in
yield from the acres treated with Fenox is shown in Exhibit 3. 10 using
the above formula.
3. 1.3 Net Changes in Crop Prices
Before the benefit which is generated by this net increase in
national output can be calculated, it is necessary to estimate the effect
that this net change in output will have upon the price of the crop. Since
this net increase in output results in a net increase in the supply of the
product, the effect upon the price of the crop will be determined by the
demand for the crop. More specifically, the reduction in the price of
the crop which is caused by this net increase in output is determined
by the price elasticity of demand for the crop. This price elasticity is
incorporated in the formula shown in Exhibit 3. 11, where the previous
price, P ,t_i, is obtained from Exhibit 3. 12.
3. 13
-------
EXHIBIT 3.9: Net Change in Yield Per Acre Due
to Use of Fenox Rather Than Delta
Delta* Fenox** Net Change in
(Over No (Over No Yield (Fenox
Herbicide) Herbicide) Over Delta )
Wheat (bu/acre) 7.67 15.34 7.67
Application rate per treat-
ment per acre (in ibs) 0.45 0.45 0.45
Barley (bu/acre) 15.27 30.54 15.27
Application rate per treat-
ment per acre (in ibs) 0.23 0.23 0.23
Oats (bu/acre) 18.75 37.50 18.75
Application rate per treat-
ment per acre (in ibs) 0. 10 0. 10 0. 10
*Source:
For wheat: Blackman, G. E. , and I—I. A. Roberts, ‘ Studies in Selec-
tive Weed Control, “ The Journal of Agricultural Science ,
Vol. 40, 1950, Table 2, p. 64. SMCP compared with
control (data for 1944).
For barley: Blackman, C. E., and H. A. Roberts. . cit., average
of four results compared vdth control, Tables 7 and 8,
pp. 76-77 (data for 1944-1945).
For oats: Blackman, C. E., and H. A . Roberts, 2 • cit., average
of two results compared with control, Table 3, p. 72
(data for 1945).
*- Because Fenox is an hypothetical herbicide, its yield over using no
pesticide is hypothetically assumed to be two times the yield with Delta.
Test plot data have indicated that two similar type pesticides can have
such a large difference in yield and thus this assumption, although
hypothetical has been shown to be the case in some instances with
real pesticides.
3. 14
-------
EXHIBIT 3. 10: Net Change in Yield Due to Use of Fenox Rather Than Delta
(Bushels in thousands)
North-
east
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
South-
em
Plains
Moun-
tam
Pacific
States
Total
Wheat 1973
1978
629
744
2,669
3,160
•7,033
8,345
4,196
4,963
989
1,174
913
1,082
2,171
2,562
1,480
1,741
1,258
1,488
1,135
1,342
22,473
26,601
Barley 1973
1978
229
275
855
1, 023
382
443
3, 176
3, 772
962
1, 130
183
214
---
---
641
764
2,031
2, 397
1,756
2, 077
10, 215
12, 095
Oats 1973
1978
1,050
1,519
1,800
2,119
14,738
17,494
4,969
5,888
881
1,050
956
1, 144
4,856
5,756
2,063
2,419
319
375
356
431
11,988
38, 195
U I
-------
Calculation of Net Price Change Due
to a Net Increase in Total Crop Output
‘ P it (P , t—l s i... E’), where
= the net change in the price of crop j
attributable to the application of
pesticide i (i.e., Fenox) in year t,
= the price of crop j in year (t-i),
= the net change in the total output of crop j
in the nation attributable to application of
pesticide i (1. e. , Fenox) in year t,
= the total output of crop j in year (t-i),
the price elasticity of demanid for
crop j.
EXHIBIT 3.11:
1. Wheat
t = 1973
Pj, t— 1
Q 3 ,t-i
Pj, t —
0 ijt
P jt
t = 1978
E
Put
= $1.76 per bushel (Exhibit 3. 12),
= 22, 473, 000 bushels (Exhibit 3. 10),
= 1, 544, 936, 0L i bushels ( Agricultural
Statistics, 1974 , Table 2),
= - 0.75,
- $0. 03414 per bushel.
= $2.961 per bushel (Exhibit 3. 12),
= 26, 601, 000 bushels (Exhibit 3. 10),
= 1, 616, 926, 600 bushels (A. Smith,
etal., cit., p. 31),
= - 0.75,
= - $0. 06495 per bushel.
3. 16
-------
EXHIBIT 3. 11 (continued)
2. Barley
t = 1973 $1.22 per bushel (Exhibit 3. 12),
= 10, 215, 000 bushels (Exhibit 3. 10),
Q ,t-i = 423, 461, 000 bushels ( Agricultural
Statistics, 1974 , Table 59),
E = - 0.75,
Pi. t - $0. 03924 per bushel.
t = 1978 Pj,t_i = $l.712 per bushel (Exhibit 3.12),
12, 095, 000 bushels (Exhibit 3. 10),
Q ,t-i 484,246, 790 bushels (A. Smith,
etal., op. cit., p. 31),
= - 0.75,
APijt - $0. 05701 per bushel.
3. Oats
t 1973 P ,t . .i $0. 723 per bushel (Exhibit 3. 12),
31, 988, 000 bushels (Exhibit 3. 10),
Q , 1 = 691, 973, 000 bushels ( Agricultural
Statistics, 1974 , Table 50),
-0.75,
I 3 3 t = - $0. 04456 per bushel.
3. 17
-------
EXHIBIT 3. 11 (continued)
t = 1978 ),t—l $0. 921 per bushel (Exhibit 3.12),
38, 195, 000 bushels (Exhibit 3. 10),
Q 3 ,t-i = 854, 074,920 bushels (A. Smith,
al. . cit., p. 31),
E -0.75,
P 3 t = - $0. 05492 per bushel.
3. 18
-------
EXHIBIT 3. 12: Prices Paid to Farmers for Crops
(Data in dollars per bushel)
Crop Year
Average
P!heat
1970—1972
19
1.
7Z*
760
19
3.
73
820
19
2.
77 : :
961
19
1.
8O *
815
1.487
Barley
1.044
1.
220
2.
040
1.
712
1.
274
)ats
0.651
0.
723
1.
090
0.
921
0.
794
*Averaged from Agricultural Statistics, 1974, 1971.
C*Agricu1tural Statistics, 1974 , Tables 2, 50, arid 59.
***Interpolated from 1973 and 1980 data.
****A. Smith, etal. , op. cit., 1974, Table 19, P. 45. (Assumes
a 4 percent inflation and a 1 percent supply shift from the price
level in 1970-1972.)
3. 19
-------
3. 1.4 Change in Consumers’ Surplus
The result of the net price changes from Exhibit 3. 11, when
applied to the total net increase in yield in bushels from Exhibit 3. 10,
gives the total value to society of the net increase in yield - - i. e.,
change in consumers’ surplus -- as shown in Exhibit 3. 13. The values
for 1974 through 1977 have been interpolated and all values have been
discounted back to their value in 1974. Also shown is the five year
total for 1974 through 1978, discounted to its value in 1974.
3. 2 Net Costs of Pesticide Application
In the determination of the net costs of pesticide application, the
assumption is made that the total costs of pesticide application with
Fenox are five percent higher than they are with Delta. This hypothet-
ical assumption does not appear to be unreasonable considering the
hypothetical yield increases assumed for Fenox.
To determine the actual value of this increased cost, the cost of
applying Delta is first determined. The total cost of applying a herbi-
cide to a crop consists of two elements -- the cost of the herbicide
materials and the cost of performing the application. Using standard
spray application costs from Doane’s Agricultural Report , the costs of
application per acre for Delta are shown in Exhibit 3. 14, and the total
cost of application for Delta, to the acres which would be treated with
Fenox rather than Delta, are shown in Exhibit 3. 15.
The five year (1974-1978) total cost discounted back to 1974 is
expected to be 105.4 million dollars if Delta were used. This implies
thatthe costwith Fenox can be expected to be (l.05)x(105.4) = 110.7
million dollars, for a net increase in application cost of 5. 3 million
dollars, if Fenox were substituted for its next best alternative Delta.
This change in costs of pesticide application should normally be
embodied within the change in the consumers’ surplus measure when
one pesticide is substituted for another. This should occur because
the change in the crop price resulting from a change in crop yield and
a change in pesticide application cost should be reflected in the price
forecasting algorithm. Thus, the purpose of separately determining
the net costs of pesticide application is usually to determine the dis-
tributional impacts to the farmer associated with this substitution.
3.20
-------
EXHIBIT 3. 13: CalculatiOn of Net Internal Benefits to Society When
Fenox is Substituted for Its Next Best Alternative Delta*
Year
Current Dollars
— (In millions of dollars)
(In millions of do1lars *
Crop
Total
Wheat Barley Oats Total
Wheat
Barley
Oats
-
1973
1974
1975
1976
1977
1978
1974-1978
53. 1
63.6
74.0
84.5
94.9
105.4
422.4
16.8
19.0
21.2
23.5
25.7
28.0
117.4
31.5
34.8
38.1
41.4
44.7
48.0
207.0
101.4
117.4
133.3
149.4
165.3
181.4
746.8
53. 1
63.6
64.7
64.6
63.4
61.5
317.8
16.8
19.0
18.5
18.0
17.2
16.3
89.0
31.5
34.8
33.0
31.6
29.9
28.0
157.3
101.4
117.4
116.2
114.2
110.5
105.8
564.1
The following equation was used in this calculation: CS t = P t Q ,t-i + 1/2 . Pjt ‘ Q t .
Explanation of the terms appear on p. 3. 1.
‘ *The discounted value is calculated by dividing the current dollars by (1 + r)t, where r is the
discount rate and t is the number of years discounted. The recommended discount rate to be
used is 10 percent when benefits and costs are expressed in constant dollars (see Volume I of
report, pp. 3.21-3.22). Therefore, in this instance, where a 4 percent inflation has been built
into the analysis, the appropriate discount rate is (1.04) x (1.1) - (1) = 0.144, or 14.4 percent.
-------
EXHIBIT 3. 14: Cost of Herbicide Treatments Per Acre for Delta
cost per pound of materials
ACijkt = cost per acre of performing application } Assume values are same for all crops
North-
east
Lake
States
Corn
Belt
North-
erri
Plains
Appa-
lachian
South-
east
Delta
South-
em
Plains
Moun-
tam
Pacific
United
States
Average
1972 Materials*
($/pound)
Application**
($/acre)
1.82
243
1.72
1.35
-
1.75
,
1.89
1.67
1.51
1.74
1.94
1.53
1.45
1.72
1.45
1.79
1.48
1.85
1.75
1.92
1.75
1.75
1.70
1973 Materials
*** ($/pound)
Application
($/acre)
1.90
2.43
1.79
1.35
1.83
1.89
1.74
1.51
1.81
1.94
1.60
1.45
1.79
1.45
1.87
1.48
1.93
1.75
2.00
1.75
1.82
1.70
1978 Materials
* * ($/pound)
Application
($Iacre)
2.28
2.44
2.11
1.36
2.22
1.90
2.09
1.52
2.18
1.95
1.92
1.46
2.11
1.46
2.24
1.49
2.32
1.76
2.41
1.76
2.19
1.71
1980 Materials
**** ($/pound)
Application
($/acre)
2.43
2.45
2.30
1.36
2.34
1.91
2.23
1.52
2.33
1.96
2.05
1.46
2.30
1.46
2.39
1.49
2.47
1.77
2.57
1.77
2.34
1.72
*Agricultural Prices, Annual Summary , 1972, p. 162.
* Doane’s Agricultural Report , March 17, 1972.
** Interpo1ated from 1980 data.
****Forecast from A. Smith, etal., . cit., Table 19, p. 45.
-------
EX} IBXT 3. 1.5: Total Cost of Herbicide Treatn ente with Delta
and pest_emergence)* (Data are in hundreds of dollars)
North-
east
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
South-
em
Plains
Moun-
tairi
Pacific
States
Total
1973
Wheat
0. 90**
5,388
15,002
49,765
25,086
7,107
5,165
12,767
8,961
8,589
7,844
145,674
Barley
0. 46 *
861
1,973
1, 156
7,947
2,969
436
---
1,605
5,836
5, 084
27, 867
Oats
0. 20**
2,935
2,936
32,587
8,926
1,994
1,643
8,439
3,667
661
742
64,530
Total
9,184
19,911
83,508
41,959
12,070
7,244
21,206
14,233
15,086
13,670
238,071
1978
Wheat
0. 90**
6,724
19,030
63,082
31,839
8,969
6,554
16,095
11,341
10,879
9,956
184,469
Barley
0. 46**
1,067
2,473
1,398
9,883
3,620
632
---
2,005
7,202
6,295
34,483
Oats
0. 20*’
4,322 3,551
39,597
10,858
2,428
2,016
10,260
4,422
797
921
79,172
Total —
12, 1131 25, 054
104, 077
52, 580
15, 025
9, 102
26,355
17, 768
18, 878
17, 172
298, 124
Five-year total (1974-1978)
Five-year total (1974-1978) discounted back to 1974****
*TCjjt TPCi t + TAC t where:
TPC t = total material cost (application rate for one treatment 2 TCPAj 3 kt), arid
TAC t = total application cost (ACjjkt 2 TCPAIjkt)
**Applicatiori rates for two treatments per acre (given in lbs/acre).
** The years 1974 through 1977 were interpolated and then the years 1974 through 1978 were added together.
****Each of the five years 1974 through 1978 was discounted back to its value in 1974 and then added together.
The procedure is fully explained in Exhibit 3. 13.
Aasurxie two treatments per acre (pre-
p .)
370, 508
1,053,770
-------
In the present case study, the price forecasting algorithm has
only included the change in crop price due to an increase in crop yield.
Therefore, the net increase in application cost of 5. 3 million dollars
is not included in the consumers’ surplus measure and must he consid—
ered in the determination of net benefits.
A second distributional impact of interest (and related to pesticide
application costs) is the change in the farmers’ profit from substituting
Fenox for Delta. Shoud Fenox be substituted for Delta, there will be
an increase in total crop output accompanied by a decre e in crop
price. This will result in a decrease in total revenue to the farmer as
indicated in Exhibit 3. 16. This measure, however, gives no indication
as to what the change in the farmers’ profit may be. Assuming the
farmer can reduce his total cost of crop production by sufficiently
more than the decrese in his revenue, he will increase his profit by
using Fenox rather than Delta.
*Pesticide application costs are only one small part of the total
cost of crop production. Costs for other inputs would be needed to
determine the change in total cost of crop production, and then the
change in the farmers’ profit.
3.24
-------
EXHIBIT 3. 16 Change in Revenue to Farmers if Fenox is
Registered and Substituted for Delta
Calculated from Exhibit 3. 11 as [ (Pa, t i + Pjj )
x (Qj,t-i + Q t)] - [ (P ,t i) x (Q ,t-i)}
(In millions of dollars)
Wheat Barley Oats Total
1973 -14.0 -4.5 -2.6 -21.1
1978 -28.0 -7.6 -13.8 -49.4
Syear total (l974 -1978) -112.0 -31.6 -46.4 -190.0
5 year total (1974-1978) -84. 1 -23.9 -33.8 -141.8
discounted back to l974
*The years 1.974 through 1977 were interpolated and then the years
1974 throu ih 1978 were added together.
*Each of the five years 1974 through 1978 was discounted back to its
value in 1974 and then added together. The procedure is fully explained
in Exhibit 3. 13.
3. 25
-------
4.0 HEALTH EFFECTS
4. 1 Description of Study Pesticide
and Its Next Best Alternative
In the health effects discussion, Fenox and its next best alterna-
tive, Delta, are defined as fabricated chiorophenoxy herbicides. The
characteristics of Delta are assumed to be given by any data of record
on 2, 4-D; 2,4, 5—T; Silvex; MCPA or Sesone (2, 4 -dichlorophenoxyethyl
sulfate). Based upon hypothetical animal toxicology data, Fenox is hypo-
thetically assumed to be similar to Delta in terms of its chronic injury
hazards. However, its ocular exposure hazard and dermal exposure
hazard are hypothetically assumed to be more severe as indicated later
in the analysis. Both Fenox and Delta are assumed to be formulated as
10 percent water solutions and in such purity that no chiorophenoxy
dioxins can be detected in the product sold. Furthermore, the health
effects associated with the use of Fenox are limited to those effects
caused by its use in wheat, oats, and barley production.
4.2 Subpopilations at Risk
It is assumed that the proposed registration of Fenox is intended
for agricultural use by people involved in the production of wheat, oats,
and barley. Hence, in Exhibit 5. 2 of the health effects subrnodcl in
Volume I of the report, the entities referred to as “professional non-
farm applicators” and “household users of pesticides” need not be con-
sidered, as Fenox’s proposed uses would not give rise to an occasion
where these subgroups would be at risk or impacted by this product.
In addition, the entity “pesticide transport personnel” is assumed to be
at minimal risk (based on past discussions with OPP personnel) and is
not considered in the assessment of health effects.
Therefore, the subpopulations at risk and considered in the follow-
ing discussion of health effects are as follows:
• Pesticide R and D, manufacturing, and formulation
worke rs,
• Field workers and other farm personnel,
4. 1
-------
Commercial farm applicators, and
Society as a whole.
Each of these subgroups is further described, below.
4. 2. 1 Pesticide B and D, Manufacturing
and Formulation Workers
In order that Fenox will be available in sufficient quantity to meet
the demand for its use, a number of manufacturing and formulation
employees will be needed to produce Fenox. From discussions with a
typical formulator of phenoxy herbicide products, it is estimated that
approximately 18 manufacturing and formulating employees are needed
to produce and formulate one million pounds of the typical phenoxy herb-
icide per year. This includes all functions - production, formulation,
maintenance, supe rvision, and laboratory. The refore, assuming that
the demand for Fenox in 1974 for wheat, oats, and barlc y production
will be as described in the agricultural impact analysis, the number
of manufacturing and formulating employees at risk in 1974 would have
been 61. For 1975 through 1978, these numbers would be 63, 67, 68,
and 70, respectively, based on the demand projections for use of Fenox
on wheat, oats, and barley crops.
4.2.2 Field Workers and
Other Farm Personnel
Health effects to this subgroup would only impact on those mem-
bers of the subgroup directly involved with the use of Fenox on wheat,
oats, and barley, whether it be in the application of Fenox on these
crops or the entering of wheat, oats or barley fields sprayed with
Yen ox.
*The cooperation of Aruchem Products, Incorporated, Ambler,
Pennsylvania 19002, is greatly appreciated.
* 13ascd on acres treated with Fenox and application rate data pre-
sented in the agricultural impact analysis, 3. 3 million pounds of Fenox
would have been needed in 1973 arid 3. 9 million pounds would be needed
in 197$. Interpolating this data for 1974-1977 implies that 3.4 million
pounds, 3. 5 mil]ion pounds, 3. 7 million pounds, and 3.8 million pounds,
respectively, will be needed.
4.2
-------
To determine the portion of this subgroup at risk from use of
Fenox in this manner, information from the agricultural impact analy-
sis was used. More specifically, only those states that had wheat, oats
or barley crops were assumed to have field workers who would be at
risk. To estimate the number of agricultural workers in any state
working on wheat, oats or barley crops, the following formula was
used:
CGW• WOBA .
N 1 AW 1 x ___ I
TW 1 CGA 1
where: N 1 = the number of agricultural workers in
state i working on wheat, oats or barley
crops,
AW = the total number of agricultural workers
in state i,
CGW 1 = the number of hired farm workers in
state i working less than 150 days a
year on cash grain crops,
TW the total number of hired farm workers
in state i working less than 150 days,
WOBA = the number of wheat, oats, and barley
acres harvested in state i,
CGA = the number of cash grain acres harvested
in state i.
N 1 then had to be adjusted to reflect the number of workers in the state
that are expected to be exposed to the pesticide. This was accomplished
by assuming that an equal number of agricultural workers work each
acre of wheat, oats or barley. Thus, the number of agricultural
workers in any state working on wheat, oats or barley crops and that
would be exposed to Fenox was estimated as follows:
WOBAF
NE 1 = N 1 x
WOBA
4.3
-------
where: NE the number of agricultural workers in
state i working on wheat, oats or barley
crops expected to be exposed to Fenox,
N 1 = defined as before,
WOBAF 1 = the number of wheat, oats, and barley
acres in state i receiving Fenox,
WOBA 1 = defined as before.
Results of these calculations appear in Exhibit 4. 1. The number of
agricultural workers in 1973, expected to have worked on wheat, oats
or barley crops in the United States that would he treated with Fenox
if registered, is 35, 610. It is assumed that this number will remain
stable over the five year period 1974-1978. *
4.2.3 Commercial Farm Applicators
Commercial application of Fenox on wheat, oats, and barley pre-
dominantly involves aerial application of the product. Presently, there
are approximately 4, 300 aerial farm applicator firms in the United
States, with 7,800 planes and 25, 000 employees. However, of these
25, 000 employees, only 17, 550 are directly involved in the aerial spray-
ing of pesticides. Furthermore, it is estimated that only one-third of
this number, or 5, 850, are engaged in phenoxy herbicide spraying.
Although 5, 850 aerial farm applicators are engaged in phenoxy
herbicide spraying, not all will be at risk if Fenox is registered for
use on wheat, oats, and barley crops. In 1971, approximately 39.4
percent of all phenoxy herbicides used by farmers were used on ‘$iheat,
oats, barley, and other grain crops. Therefore, assuming that this
*This assumption is supported by the fact that the number of agri-
cultural workers in each state has remained fairly constant over the
past couple of years (USDA, Agricultural Statistics, 1974 , p. 434).
Thus, if the proportions, CGW /TW , WOI3AI/CGA 1 , and WOBAF /
WOI3Aj, remain fairly stable, the assumption is not unreasonable.
**Based on a phone conversation with Mr. Farrell Higbee,
National Agricultural Aviation Association, Washington, D.C., April 3,
1975.
***Andrilenas, P. A., Farmers Use of Pesticides in 1971: Quan-
tities , USDA, ERS, Agricultural Economic Report No. 252, July, 1974,
pp. 30, 32.
4. 4
-------
EXHIBIT 4. 1: Derivation of the Number of Agricultural Workers Expected
to be Exposed to Fenox When Applied on Wheat, Oats, and
Barley Crops (All Numbers are in Thousands)
Northeast Region
Maine
New York
New Sersey
Pennsylvania
Delaware
Maryland
Total
Lake States Region
Michigan
Wis cons in
Minnesota
Total
Corn Belt Region
Ohio
Indiana
Illuiio is
Iowa
Missouri
Total
Northern Plains
North Dakota
South Dakota
Nebraska
ICa nsa s
Total
Southern Plains
Oklahoma
Texas
Total
Appalachian Region
Virginia.
West Virginia
Kentucky
Tenne s s cc
North Carolina
Total
AW 1 1 CGW 2
TWL 3 WOBA 4
CGAj 5 WOBAF 6
N 1 NE 1
18
99
19
116
6
32
290
0.276
1.606
0.580
2.076
1.235
3. 079
9.329
41.832
100. 095
30.590
83. 381
12. 549
32.663
301.110
34
477
61
794
48
238
1,652
34
853
144
1,849
243
750
3,873
3.14
44.17
5.64
73.52
4.44
22.03
153.00
4.10
0.89
0.15
1.20
0. 12
0. 96
7.40
0.38
0.08
0.01
0. 11
0. 01
0. 09
0.69
121
173
183
13. 496
2.725
29.489
176. 547 921
120. 433 1,418
139.015 5,454
2,670
3,517
11,064
59.03
90.89
349.60
3. 19
1.58
19.14
0.20
0.10
1.23
477
-
155
143
162
201
187
848
45. 710
24. 014
29. 333
75. 895
51. 891
23. 422
204. 555
435. 995
131. 168
105. 988
165. 000
208. 742
128. 506
739. 404
7,793
1,272
975
1,704
1,352
904
6,207
17, 251
4, 320
6,253
11,470
12, 506
3, 963
38, 512
500. 00
353.90
271. 30
474.22
376.26
251. 58
1,728.00
23. 90 1. 53
i
3. 35 2. 33
6. 17 1.72
11.07 3.08
5.41 1.51
7.77 2. 16
33.78 10.70
58
65
110
111
344
32.201
7.983
27.201
38. 352.
105.737
57.894 13,503
50. 575 5, 039
83.971 3,173
101.346 10,580
293.786 3Z, 295
13,790
8, 165
11,172
16, 060
49, 187
426.42
159. 13
100.20
334.11
1,020.00
31.59 1.00
1 33 0. 20
10.12 0.32
27.67 0.87
‘75.71 2. 39
120
264
384
14.539
36.144
50.683
86.874
253.188
340. 062
4,140
5,689
9, 829
6,534
12,314
18, 848
145.70
I 200.25
1 345. 00
17.49
12.67
30. 16
0.45
0.62
1.06
103
3.17a
95.698
319
898
70.97
1.21
0.27
36
.057
15.603
40
103
8.90
0.05
0.01
148
7.
158
189.
456
231
1,
260
51.
39
1.
03
0.
23
147
9.014
113.410
187
73Q
41.60
2.99
0.67
197
12.355
439.272
297
1,793
66.08
0.92
0.20
631
31.756 853.438
1,074
4,784
239.00
6.20
1.38
4. 5
-------
EXHIBIT 4. 1 (continued)
Southeast Region
South Carolina
Georgia
Alabama
Florida
Total
Delta States
Mississippi
Arkansas
Louisiana
Total
Mountain
Montana
Wyoming
Ida ho
Colorado
Ne i M exico
Utah
Nevada
Arizona
Total
Pacific
Washington
Oregon
California
Total
U.S. -Total
Sources:
64
100
83
115
362
7.549
5.266
3.774
2.124
15.316
107.473
133.247
72.793
120.941
434.454
193
204
108
41
546
672
2,023
749
381
3,825
64.32
67.99
35.99
13.66
182.00
1.29
0.40
0.62
0.22
2.50
0.43
0.13
0.21
0.07
0.84
[ 09
126
68
303
10. 872
28.748
13. 487
53.107
80. 427
90.900
60. 689
232.016
102
284
26
412
360
987
737
2.,084
102.00
284.00
26. 00
412.00
4. 17
11.47
0.53
16.17
4. 17
11.47
0.53
16.17
39
15
44
57
22
21
47
32
277
10. 661
0.720
7. 152
8. 374
1.738
1.149
0. 108
1. 121
31. 023
38. 809
15.751
33. 703
59. 281
22.066
32.755
4. 885
52. 646
28i. 748
6, 322
422
1,955
2, 736
312
403
31
336
12, 517
6,333
456
1,983
3,470
696
416
31
485
1, 387
158.42
10.57
48.99
68. 56
7.81
10.09
0. 78
0.84
314. 00
10.69
0.63
3.71
6. 35
0.78
0.71
3.22
0.47
26.56
0.45
0.02
0.09
0. 16
0.02
0.02
0. 08
0.01
0. 84
75
58
280
413
10.193
4.112
16.583
30.888
218.245
225.409
671.703
1,115.357
3,145
1,402
1,622
6,169
3,221
1,420
2,545
7,186
143.75
64.08
74.14
282.00
3.40
1.04
4.41
8.88
0.16
0.05
0.20
0.41
4,329
578. 104
5,027.371
78, 494
146,937
5,175. 00
29
35.61
1. USDA, Agricultural Statistics, 1974 , Washington, D.C., Superintendent of Docu-
ments, 1974, Table 618. Data is for 1973.
2. U. S. Bureau of the Census, Census of A jcu1ture, 1964 , Vol. 2: General Reports,
Chapter 4, Equipment, Labor, Expenditures, Chemicals, Table 11, p. 77. Data is
for 1969.
3. Ibid .
4. Agricultural Statistics, 1974 , Calculated from Tables 2, 20, and 59. Data is for 1973.
5. Agricultural Statistics, 1974 , Calculated from Tables 2, 20, 27, 39, 50, 59, and 71.
Data is for 1973.
6. Derived from regional totals in agricultural impact analysis; see Chapter 3. 0 of this
volume. Data is for 1973. (State data may not add to regional total due to rounding.)
AW 1 1 CGW 1 2
TW 1 3 WOBA 1 4 CGA 1 5 ‘AOBAFj 6
NE
4. 6
-------
percentage has not drastically changed over the years and that farmer
use of phenoxy herbicides on wheat, oats, and barley is directly related
to aerial farm application of phenoxy herbicides on wheat, oats, and
barley, then it may be estimated that 2, 305 aerial farm applicators
(39.4 percent of 5,830) would be spraying Fenox on wheat, oats, and
barley crops and thus be at risk. It is assumed that this number would
remain fairl.y constant over a short time span of five years.
4.2.4 Society As A Whole
Society is at risk in an indirect manner if Fenox is used on wheat,
oats, and barley. More specifically, acute injury can occur to society
when there is drift of the product in the vicinity of its application as a
result of accidental spiiis or misuse. To estimate the portion of
society at such a risk, the following equation can be used:
r IATOBAF.t
Nt . Rjtx
1=1 RA t
where: Nt the number of people in society at risk
to acute injury from use of Fenox on
the wheat, oats, and barley crops at
time t,
n = the states in which wheat, oats, and
barley are grown,
= the size of the rural population in state i
at time t,
WOBAF t = the number of wheat, oats, and barley
acres in state i receiving Fenox in
year t,
RA 1 t = the total number of rural acres iii state i
in year t, in rural land area expressed
in acres.
*Acute injury to society from the P. and D, manufacture, formula-
tion, and distribution of Fenox for use on wheat, oats, and barley is
assumed to be zero. This is based on information about 2, 4-D and
2,4, 5—T contained in E. W. Lawless, et al. , The Pollution Potential in
Pesticide Manufacturing , EPA, Office of Water Programs, Technical
Studies Report TS-00-72-04, June, 1972.
4. 7
-------
Two data elements - - R t and RAj. - - are not readily available from
the Bureau of the Census but can be obtained through extensive data
manipulation of its readily available data. Therefore, this formula is
recommended for use. However, for illustrative purposes only, the
equation below has been used to estimate that portion of society at risk
to acute injury from the proposed use of Fenox on the wheat, oats, and
barley crops: 4
WOBAF t
Nt = E Pt.x—
i=l A t
where: Nt defined as before,
Pit = the size of the total population in state i
at time t,
n defined as before,
WOBAF t = defined as before,
Ait = the total number of acres in state i in
year t, i.e., total land area expressed
in acres.
Exhibit 4.2 presents the results of the above calculations. As shown
in the exhibit, the number of people in the United States at risk to acute
injury from Fenox’s use on wheat, oats, and barley is estimated to be
762, 000 in 1974. For 1975 through 1978, the numbers of people are
798, 000; 834, 000; 872, 000; and 909, 000, respectively.
The risk of chronic injury to society would only result from
dietary intake of the pesticide. Consequently, the entire United States
population is at such a risk and was estimated at 211, 390, 000 people
as of July 1, 1974.44 For 1975 through 1978, these estimates are
*This equation assumes an equal distribution of people throughout
a state. Because this is not a reasonable assumption, this equation is
far less desirable than the previous one.
44 Bureau of the Census, Population Fstimates and Projections ,
Series P-25, No. 539, January, 1975.
4. 8
-------
EXHIBIT 4. 2: Derivation of the Society at Risk to Acute Injury from Use of Fenox
on Wheat, Oats, and Barley Crops (All numbers are in thousands)
Regions
it
WOBAF tZ
A 3
Nt
1974
1975
1976
l97 _
197!_
1974
1975
1976
1977
1978
1974
1975
1976
1977
1978
Northea ,t
44, 194
44. 605
45, 016
45.433
45, 850
161.6
170.2
178.8
187.4
196.0
91, 591
77 97
82.52
87.78
92.68
97.66
Lakes State.
17,921
18, 139
18.349
18.563
18,777
321.4
536.8
552.2
573.6
592.0
121.964
76.61
79.79
82.57
87.25
90.13
Corn Belt
Northern Plain.
35,696
5,012
36, 028
5,037
36, 360
5,062
36, 693
5,037
37. 025
5,112
1,792.4
1,057.6
1,856.8
1,095.2
1,921.2
1,132.8
1,985.6
1,170.4
2,050.0
1,208.0
164,964
144.238
387.85
36.75
405. 31
38.25
423.23
39.76
441.42
41.28
459.85
42.81
Southern Plain.
14,490
14, 671
14,852
15, 037
15,222
187.2
369.4
381.6
393.8
406.0
Zil . 786
24.44
25.5 ’
26.75
27.95
29. 18
Appalachia
19. 138
1’?, 273
19,408
19. 549
19. 690
247.8
256.6
263.4
274.2
283.0
123, 920
38.27
39.90
41.55
43.20
44.85
So otheast
18,289
18,535
18.781
19,027
19,274
188.8
195.6
202.4
209.2
216.0
125,746
21.46
28.82
30.22
31.64
33.08
Delta State.
7,970
8, 020
8.070
8, 120
8, 171
561.8
581.6
601.4
621.2
641.0
92. 269
48.53
50.55
52.60
54.66
57.76
Mountain
8,824
8,956
9.088
9.220
9,352
325.4
336.8
348.2
359.6
371.0
547, 869
5.24
5.51
5.78
6.05
6.33
Pacific
27, 462
28, 016
28, 574
29. 133
29, 691
292.4
302.8
313.2
323.6
334.0
204, 233
39.32
41.52
43.80
46.15
48.54
United State. Tot .a l
198, 996
201, 276
203. 578
205,881
208, 184
5,506.4
5,701.8
5,900.2
6,098.6
6,297.0
1,879.583
762.44
797.76
834.04
872.28
909. 19
*The rtates in each region are a. defined in Exhibit 4.1.
Sources:
1. Bureau of the Census, Pooulation E timatea and Projectione , Series P—25, No. 477, March, 1972, SerIes I.E Projections.
2. Interpolated from data in Exhibit 3.8 of agricultural impact analysis.
3. Calculated from Bureau of the Census. County and City Data Book , 1972. Table 1.
-------
214,883,000; 217,293,000; 219,703,000; and 222,113,000, respec-
tively. *
4. 3 Net Health Damages
4. 3. 1 Determination of Net Health
Damages Using Animal
Toxicology Data
4.3. 1. 1 Acute Injury Assessment
Below appears an assessment of the increased acute injury,
based upon animal toxicology data, which is caused by exposure to
Fenox rather than Delta. These calculations follow the definitions
developed in Section 5. Z. 1.2 of Volume I of this report. For ease of
understanding the analysis below, these definitions are repeated at this
time.
For acute injury, each hazard defined below contemplates injur-
ies sufficiently severe to cause:
The victim to purchase and apply an ameliorative
preparation, or
• The victim to seek medical advice or treatment, or
• The victim to lose time from work.
In addition, each hazard can be expressed as the number of individuals
affected among each 100, 000 exposed to the pesticide product in the
subpopulation indicated by the left-hand headings of Exhibit 5. 2 of
Volume I of the report. Furthermore, due to the uncertainty of extrap-
olating from animal toxicology data to likely human health effects, a
range for each hazard that incorporates the probable value of each
hazard is desirable. Therefore:
*Bureau of the Census, Population Estimates and Projections ,
Series P-25, No. 477, March, 1972, Series I-F projections.
**See p. 5.4 of Volume I of the report for the basis for these pro-
definitions.
4. 10
-------
• Ocular exposure hazard is defined as eight to twelve
times the number of rabbit eyes among six tested
which suffered irreversible opacity at two days,
plus four to six times the number which suffered
corneal opacity reversible within two days or irri-
tation persisting for seven days, plus 0. 5 to 1. 5
times the number which suffered irritation reversi-
ble within seven days, when ocularly exposed with
0. 1 ml of the pesticide product, in the solvent and
at the concentration expected to be handled by the
subpo.pulation of interest.
• Dermal exposure hazard is defined as eight to twelve
times the number of rabbits among six tested which
suffered necrosis or marked erythema evident at 72
hours, pius four to six times the number which suf-
fered moderate crythema evident at 72 hours, plus
0.5 to 1.5 times the number which suffered any vis-
ible lesser degree of irritation evident at 72 hours,
when dermally exposed - - i.e. , when applied to both
covered and uncovered skin, both intact and abraded
-- with 0. 01 ml of the pesticide product, in the sol-
vent and at the concentration expected to be handled
by the subpopulation of interest. To the sum of these
three degrees of primary irritation should be added
eight to twelve times the number of guinea pigs sen-
sitized to any degree among a group of 10 tested to
account for the dermal sensitizing potential of the
pesticide product.
Oral exposure hazard is defined as 100 divided by
the rat oral LDSO (expressed in mi/kg body weight)
of the pesticide product, in the solvent and at the
concentration expected to be handled by the suhpop-
ulation of interest. To obtain a range for this
hazard, one can use the mean LD5O and the 95
percent confidence interval LDSOTS.
4. 11
-------
Inhalation exposure hazard is defined as 4, 00O
divided by the 4-hour rat LC5O (expressed as mull-
grains per liter of air) of the pesticide product, in
the solvent and at the concentration expected to be
handled by the subpopulation of interest. To obtain
a range of this hazard, one can use the mean LC 50
and the 95 percent confidence interval LC 50 1 s.
• Systemic poisoning hazard is defined as the sum of
oral exposure hazard, percutaneous exposure hazard
and inhalation exposure hazard for the suhpopulation
of interest.
• Death hazard is defined as one-twentieth of the sys-
ternic poisoning hazard for the subpopulation of
interest.
*This number was derived so that the resulting oral exposure
hazard and inhalation exposure hazard would be equivalent for an oral
LD5O and an inhalation LC5O that are equally toxic according to the
‘ 1 Toxicity Categories tabulation in the October 16, 1974, Federal.
Register .
Percutaneous exposure hazard is defined as 100 divided by the
rabbit percutaneous LD5O (expressed in i:.l!kg body weight) of the pes-
ticide product, in the solvent and at the concentration expected to be
handled by the subpopulation of interest. To obtain a range for this
hazard, one can use the mean LD5O and the 95 percent confidence
interval LD5O’S. In addition, percutaneous exposure is assumed to
produce systemic poisoning.
Systemic poisoning caii occur via the oral, dermal penetration
or inhalation routes of entry. This definition assumes that for each
person experiencing irritation by oral or inhalation exposure, there
will be an additional person more severely exposed such that systemic
poisoning will result. Therefore, these two exposure hazards are
added to percutaneous exposure hazard.
** Death can occur via the oral, dermal penetration or inhalation
routes of entry just as systemic poisoning. This definition assumes
that for every 20 persons experiencing systemic poisoning, there will
be an additional person more severely exposed such that death will
result.
4. 12
-------
Emphasis must be made that these definitions will only provide
very rough estimates of what the expected exposure hazard may be.
They are crude estimating techniques and thus the results generated
by them must be interpreted with considerable care and reservation.
4. 3. 1. 1. 1 Ocular Exposure Hazard
Data required to apply this definition are not published in the
scientific literature, but should be available in every petition for regis-
tration to allow drafting of warning and precautionary statements. An
example of original laboratory records (marked “Page 9”) of such a
test on an 8 percent water solution, instead of a 10 percent water solu—
tion, of the sodium salt of 2, 4-D, applying 0. 5 ml, instead of 0. 1 ml
as in the definition, is on the following page. Four of five eyes suffered
irritation reversible within seven days, and this can be interpreted as
five of six. Therefore, applying the definition above, this example gen-
erates an ocular exposure hazard of (1 + 0.5) x (5) 5 + 2.5 per 100, 000
exposed to an 8 percent water solution of Delta.
Hypothetically assuming that a similar test with Fenox would pro-
duce a result of one out of si.x eyes suffering corneal opacity reversible
within two days, plus four out of six eyes suffering irritation reversible
within seven days, an ocular exposure hazard of (5 ± 1) x (1) + (1 ± 0.5)
x (4) = 9 + 3 per 100, 000 exposed to an 8 percent water solution of
Fenox, would he generated.
The above hypothetical result implies a net increase in the ocular
exposure hazard of (9 + 3) - (5 + 2. 5) 4 + 0. 5 per 100, 000 exposed to
an 8 percent water solution, if Fenox is substituted for its next best
alternative Delta.
Manufacturing and formulation workers are assumed to be exposed
to undiluted Fenox or Delta. Further assuming a linear dose- response
curve for Fenox and Delta, the net increase in ocular exposure hazard
to this subgroup is expected to be (12.5) x (4 1- 0.5) 50 -F 6.25 per
100, 000 exposed.
*Most dose-response curves are S-shaped and not linear.
However, in the mid-range of the curve, a linear dose-response rela-
tionship may hold quite well. Therefore, this assumption may be a
reasonable one. Further investigation of this relationship for these
pesticides would be needed in order to verify the validity and sensitivity
of the assumption made.
4. 13
-------
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12.43
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-------
Farm workers and commercial farm applicators are assumed to
be at risk during the mixing and dilution of the pesticide, during the
application of the pesticide, and during the disposal of the pesticide.
No data could be found indicating the relative frequency of accidents
caused by each process. Therefore, the assumption is made that most
accidents will occur during the application process, after the pesticide
is diluted. * Assuming farm workers would dilute the 8 percent water
solution by approximately 100 before using, and assuming a linear
dose-response curve, the net increase in ocular exposure hazard to
each of these two subgroups is expected to be (4 ± 0.5) ÷ (100) = 0. 04
± 0.005 per 100, 000 exposed.
Society as a whole would be exposed to Fenox or Delta if drift
occurred during the manufacturing or application process. However,
should this occur, it is assumed that Fenox or Delta would be in such
a dilute form as to pose virtually no net change in ocular exposure
hazard.
4.3.1.1.2 Dermal Exposure 1-lazard
Data required to apply the definition are not published in the scien-
tific literature. Those for primary irritation should be available in
every petition for registration to allow drafting of warning and precau-
tionary statements. An example of original laboratory records (marked
‘Page 45”) of such a test on a 10 percent acetone solution of 2, 4-D is
on the following page. Spot 3 shows (at 24, not 72 hours) one rabbit
suffered marked erythema, one moderate erythema, and two lesser
degrees of irritation. This result would generate a primary irritation
hazard of (10 + 2) x (1) + (5 + 1) x (1) + (1 + 0.5) x (2) = 17 + 4 per
100, 000 exposed to a 10 percent water solution of Delta. No example
*Further analyses of these two subpopulation groups are needed
before an accurate assessment can be made concerning where the likely
exposure will be. If this information were desired, and if it were
obtained, the technique used above should be modified to incorporate
this new information.
*> From discussions with people knowledgeable in the use of agri-
cultural pesticides (e.g., Dr. Herbert Cole, Pennsylvania State Urn-
versity), this assumption appears to he a reasonable one. Dilution of
the bought product usually occurs and a factor of 100 is one standard
form of dilution.
4. 15
-------
45
• ‘
I on tint injPrt tim
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gi o i untber of snilunis with o.O.n.N s..parat.’l ..
u. 19 Totnl sc.ore . tot.J of fivn an,iuats.
4.16
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-------
of a publication of data on sensitizing potential of a chiorophenoxy herb-
icide product has been found. Experience leads to the conclusion that
sensitization is more likely from the solvent than from the herbicide,
and it is assumed that Delta products use non-sensitizing solvents.
Hypothetically assuming a similar test with Fenox would produce
a result of two rabbits suffering marked erythema, one moderate cry-
theina and one lesser degree of irritation, a dcrmal exposure hazard
01(10 ± 2) x (2) + (5 + 1) x (1) + (1 + 0.5) x (1) 26 + 5.5 per 100, 000
exposed to a 10 percent water solution of Fenox, is generated. As with
Delta, Fenox is assumed to use non-sensitizing solvents, so that no
sensitization is expected.
The above hypothetical results imply a net increase in dermal
exposure hazard of (26 ± 5. 5) - (17 ± 4) = 9 + 1. 5 per 100, 000 exposed
to a 10 percent water solution, if Fenox is substituted for its next best
alternative Delta.
Manufacturing and formulation workers are assumed to be exposed
to undiluted Fenox or Delta. Further assuming a linear dose-response
curve, the net increase in dermal exposure hazard to this subgroup is
expected to be (10) x (9 + 1. 5) = 90 + 15 per 100, 000 exposed.
Farm workers and commercial farm applicators are assumed to
be at risk during the application process. Assuming that they will
dilute the 10 percent water solution by 100 before using and assuming
a linear dose-response curve, the net increase in dermal exposure
hazard to each of these two subgroups is expected to be (9 + 1. 5)
(100) 0.09 + 0.015 per 100, 000 exposed.
Society as a whole would be exposed to Fenox or Delta if dtift
occurred during the manufacturing or application process. However,
should this occur, it is assumed that Fenox or Delta would be in such
a dilute form as to pose virtually no net change in dermal exposure
hazard.
*Opinion of Dr. Henry F. Smyth, Jr., toxicologist and Advisory
Fellow, Mellon Institute.
4. 17
-------
4.3. 1. 1.3 Oral Exposure Hazard
Carpenter, etal. , * reported that the rat oral LD 50 of the chioro-
phenoxy herbicide “Sesone, when intubated as a 10 percent solution in
water, is approximately 0. 84 + 0. 20 mi/kg. This shows that the rat
oral LD5O for the Delta product consisting of 10 percent Delta, 0. 01
percent nonionic wetting agent, in water is assumed to be approximately
0.84 -1- 0.20 mI/kg, leading to an estimate of oral exposure hazard of
(100) ÷ (0.84 + 0.20) or a range of 96. 15 to 156.25 per 100, 000 exposed
to a 10 percent water solution of Delta.
Hypothetically assuming a similar test with Fenox would produce
the same results, the oral exposure hazard with Fenox would be the
same as with Delta. Hence, the net change in oral exposure hazard to
a 10 Th—’rcent water solution is expected to be zero per 100, 000 exposed,
if Fenox is substituted for its next best alternative Delta.
Therefore, it is expected that there will be no net change in oral
exposure hazard to any of the suhpopulations exposed.
4.3.1.1.4 Inhalation Exposure Hazard
No data on the acute inhalation toxicity of a phenoxy herbicide
could be found, However, the ACGII-l threshold limit value (TLV) com-
mittee has reviewed reports of repeated oral feeding studies and con-
cluded that a TLV of 10 mg/rn 3 of air is appropriate for 2, 4-D. * This
is the value assigned to inert dusts such as wood and limestone and can
be taken as the best available opinion that there is no inhalation expo-
sure hazard so long as the time weighted average concentration of
Delta during eight hours does not exceed 10 mg/rn 3 of air.
Hypothetically assuming that Fenox is similat to Delta in this
respect, the same statement can be made.
*Carpenter, C. P., et al., “Mammalian Toxicity of Sesone I-lerh-
icide, “ Agricultural and Food Chemistry , \Tol. 9, No. 5, September!
October, 1961.
**Anie rican Confe rence of Governmental Industrial Hygienists,
Documentation of Threshoid limit Values for Substance in Wori roorn
Air , third edition, 1971, p. 67.
4. 18
-------
One can conclude from these results that the 4-hour LC5O for
rats is a concentration too great to be maintained in air. Since Fenox
and Delta are to be formulated as a 10 percent solution in water and
applied by diluting by 100, one may take the inhalation exposure hazard
for both Fenox and Delta as zero per 100, 000 exposed for all subpopu-
lations.
Thus, the net change in the inhalation exposure hazard is also
expected to be zero per 100, 000 exposed for all subpopulations, if
Fenox is substituted for its next best alternative Delta.
4.3. 1. 1. 5 Percutaneous Exposure Hazard
The 1974 Toxic Substances List published by NIOSH reports the
rat percutaneous LD5O of 2, 4-D -- a Delta parallel -- to be 1, 500 mgI
kg. More useful than that datum is the 1974 report of Feldman and
Maihah on experimental percutaneous penetration in humans. They
found that an acetone solution applied to the uncovered skin at the rate
of four micrograms of 2, 4-D per square centimeter, allowed to dry,
and not washed for 24 hours, resulted in 5. 8 percent of the dose in the
urine. From this it is assumed that the human percutaneous hazard is
approximately one-sixteenth the oral exposure hazard, or a range of
6.0 to 9.8 per 100, 000 exposed to a 10 percent water solution of Fenox.
Hypothetically assuming a similar test with Fenox would produce
the sr uie results, the percutaneous exposure hazard with Fenox would
be the same as with Delta. hence, the net change in pcrcutaneous
exposure hazard is expected to be zero per 100, 000 exposed to a 10 per-
cent solution, if Fenox is substituted for its next best alternative Delta.
Therefore, it is expected that there will be no net change in percu-
taneous exposure hazard to any of the subpopulations exposed.
4.3. 1. 1. 6 Systemic Poisoning Hazard
Systemic poisoning hazard is defined as the sum of the oral, per-
cutaneous, and inhalation exposure hazards. Therefore, if exposed to
a 10 percent water solution of either Fenox or Delta, the systemic
Fe1dman, R. J. , and H. I. Maibach, “Percutaneous Penetration
of Some Pesticides and Herbicides in Man, “ Toxico1o y and f pp1icd
Pharmacology , Vol. 28, 1974, pp. 126-132.
4. 19
-------
poisoning hazard is expected to be between (96. 15 6. 0 + 0) = 102. 15
and (156.25 + 9.8 + 0) = 166.05 per 100, 000 exposed. Thus, the net
change in systemic poisoning hazard is expected to be zero per 100, 000
exposed to a 10 percent water solution, if Fenox is substituted for its
next best alternative Delta.
Therefore, it is expected that there will be no net change in sys-
temic poisening hazard to any of the subpopulations exposed.
4.3. 1. 1.7 Death 1-lazard
Death hazard is defined as one-twentieth of the systemic poison-
ing hazard. Therefore, if exposed to a 10 percent water solution of
either Fenox or Delta, the systemic poisoning hazard is expected to be
between (102. 15) ÷ (20) 5. 1 and (166. 05) ÷ (20) = 8.3 per 100, 000
exposed. Thus, the net change in death hazard is expected to be zero
per 100, 000 exposed to a 10 percent water solution, if Fcnox is substi-
tuted for its next best alternative Delta.
Therefore, it is expected that there will be no net change in death
hazard to any of the subpopulations exposed.
4. 3. 1.2 Chronic Injury Assessment
Based on animal toxicology data, the assessment of the chronic
injury hazards caused by exposure to Delta (and also Fenox, as the two
are assumed to have the same chronic injury hazards), could not be
performed using the probabilistic approach of probit analysis outlined
in Volume I of the report (pp. 5. 12-5. 13). The available data for con-
structing the necessary dose-response regression lines for each desired
effect either were questionable or non-existent. Therefore, mea-ningful
data could not even be fabricated, as there was no basis for such an
exercise. In addition, accurate estimates for the expected average
daily intake could not be found for all routes of entry and all subpopula-
tion groups. These data, although not readily available at the present
time, have been recommended to be included in the data requirements
of the registration process. If this is done, then the procedure can be
used with some success.
See page 4. 1.
4.20
-------
The procedure that is used below relies on published animal toxi-
cology data to determine a so-called “no effect” level in a selected test
species for a selected phenoxy herbicide for the various chronic effects
in question. These “no effect” levels are then reduced by a factor of
safety of 10, explained below, and evaluated in terms of whether the
subpopulation groups could be expected to be exposed to such a level.
This procedure has been used in past studies and is relied upon
when determining non-hazardous levels in humans for new substances
to which the human race has not been exposed to extensively. Toler-
ances for pesticide residues in raw agricultural commodities are also
set using this kind of information. Although not as rigorous or desir-
able as the probabilistic method described in Volume I, it is felt that
this procedure does provide as good an indication of the chronic injury
hazard as would be obtained using the more rigorous method with less
reliable data.
4.3. 1.2. 1 Metabolism and Elimination
Gehring, et al. , and Piper, et al. , taken together, show
that neither the rat nor man metabolize or conjugate small dosages
(5 mg/kg) of 2,4, 5-T -- a Delta parallel -- although larger dosages are
somewhat metabolized by the rat and were not tested in man. In these
species, oral doses are recoverable from the urine. Contrasted with
this, in the dog, at least three unidentified rnetabolites occur in the
urine, and an appreciable part of a dose i : eliminated in the feces.
Accordingly, the rat is an appropriate experimental species for
prediction of human systemic response to intake of Delta. However,
there is some difference in the time of elimination of a dose between
man and rat, the half-life of E mg/kg of Delta in the human body being
23. 1 hours and in the rat body 13. 6 hours. Had there been no difference
*See Federal Register , March 11, 1975, p. 1493.
**Gehring, P. J. • etal., “The Fate of 2,4, 5-T Following Oral
Administration to Man, “ Toxicology and Applied Pharmacology ,
Vol. 26, 1973, pp. 352-361.
Piper, W. N. , et al. , “The Fate of 2,4, 5-T Following Oral
Administration to Rats and Dogs, “ Toxicology and Applied Pharmacol-
y , Vol. 26, 1973, pp. 339-351.
4.21
-------
in time of elimination, one would have been justified in ignoring the
customary arbitrary factor of safety of 100, Despite the fact that the
test dosage of 5 mg/kg is tremendous compared to the WhO estabfl shed
acceptable daily intake (ADI) of 0. 3 mg/kg for residues in food grains,
and is large compared to any likely occupational exposure, it would be
prudent to consider that even realistic dosages will remain somewhat
longer in the human body than in that of the rat. Hence, a factor of
safety of 10, rather than 100, seems appropriate in this instance when
assessing chronic injuries caused by Delta.
Hypothetically assuming that Fenox is like Delta in this respect,
a factor of safety of 10 is also appropriate when assessing chronic
injuries caused by Fenox.
4.3. 1. 2.2 Mutagenic Hazard
Epstein, et al. found no mutagenic result in rats receiving a
single intraperitoneal injection of 125 mg/kg or five daily stomach tube
doses of 75 mg/kg of 2, 4-D -- a Delta parallel. Applying the previously
determined proposed safety factor of 10 to these findings, it is con-
cluded that no mutagenic hazard is expected to occur at a human intake
of 7.5 mg/kg or less.
As shown in a later section, the human dietary intake by
society as a whole from use of Delta on wheat, oats, arid barley can be
expected to be close to zero. Thus, there is no expectation of muta-
genie hazard to society as Delta is not expected to be consumed by
society at the rate necessary to cause harm, when it is used in wheat,
oats or barley production,
*First proposed by A. J. Lehman of the Food and Drug Adminis-
tration for dealing with new substances to which the human race has not
yet been exposed extensively. See Federal Register , March 11, 1975,
p. 1493.
**WHO, Pesticide Residue in Food , WHO Technical Report Series
No. 525, Geneva, WHOIFAO, 1973, p. 29.
* Fpstein, S. S. , etal. , Detection of Chemical Mutagens by the
Dominant Lethal Assay in the Mouse, Toxicology and Applied Pharma-
cology , Vol. 23, 1972, pp. 288-325.
* See Section 4. 3.2.4, ‘Acute and Chronic Injury to Society.
4,22
-------
For the occupationally exposed, although their dietary intake is
expected to also be close to zero, additional human intake can result
from direct oral, dermal, and inhalation exposures t:o Delta when pro-
duced for or used in wheat, oats, and barley production. However, if
the occupational exposure from these three routes of entry, plus any
dietary intake, does not produce an intake of more than 7. 5 mg/kg,
mutagenic hazards in the occupationally exposed can be expected to be
zero. There is no evidence in the literature to date that indicates occu-
pational exposure has or would exceed this amount, unless someone
were trying to commit suicide. Therefore, one can assume the intake
of Delta by the occupationally exposed does not exceed 7. 5 mg/kg, and
based on animal toxicology data, one can expect that there is no muta-
gerlic hazard to those occupationally exposed to Delta.
Considering that Fenox has been defined to be similar to Delta
with respect to chronic injury hazards, one can also expect that there
is no mutagenic hazrd to society or to those occupationally exposed to
Fenox.
Therefore, for all subpopulations, it follows that the net change
in mutagenic hazard is zero per 100, 000 exposed, if Fenox is substi-
tuted for its next best alternative Delta.
4.3.1.2.3 Teratogenic Hazard
Khera and McKinley studied thc tc:atogenic potential of pure
2,4, 5-T -- a Delta parallel -- on rats. At 100 mg/kg, teratogenic pups
were found. At 50 mg/kg, there was no significant difference from the
controls. Applying the previously determined proposed factor of safety
of 10 to this finding, it is concluded that no teratogenic hazard is
expected o occur at a human intake of 5 mg/kg or less.
As shown in a later section, the human dietary intake by society
as a whole from use of Delta on wheat, oats, and barley can be expected
to be close to zero. Thus, there is no expectation of teratogenic hazard
to society as Delta is not expected to be consumed by society at the rate
necessary to cause harm, when it is used in wheat, oats or barley pro-
duction.
Khera, K. S. , and W. P. McKinley, ‘Pre- and Post-Natal
Studies on 2,4, 5-T and 2,4-D and Their Derivatives in Rats, Toxicol-
ology and App ied Pharmacology , Vol. 22, 1972, pp. 14-28.
Onc mg/kg of dioxin was present.
4.23
-------
For the occupationally exposed, although their dietary intake is
expected to also be close to zero, additional human intake can result
from direct oral, dermal, and inhalation exposures to Delta when pro-
duced for or used in wheat, oats, and barley production. However, if
the occupational exposure from these three routes of entry, plus any
dietary intake, does not produce an intake of more than 5 mg/kg in
pregnant women , teratogenic hazards in the occupationally exposed can
be expected to be zero. There is no evidence in the literature to date
that indicates occupational exposure has or would exceed this amount,
unless someone were trying to commit suicide. Therefore, one can
assume the intake of Delta by the occupationally exposed does not
exceed 5 mg/kg, and based on animal toxicology data, one can expect
that there is no teratogenic hazard to those occupationally exposed to
Delta.
Considering that Fenox has been defined to be similar to Delta
with respect to chronic injury hazards, one can also expect that there
is no teratogenic hazard to society or to those occupationally exposed
to Fenox.
Therefore, for all subpopulations, it follows that the net change
in teratogenic hazard is zero per 100, 000 exposed, if Fenox is substi-
tuted for its next best alternative Delta.
4. 3. 1.2.4 Oncogenic Hazard, Reproductive
Impairment, and Physiological
Malfunction Hazard
Hansen, et al. , * reported on a three generation, six litter repro-
duction study and on a two-year feeding to rats of diets containing up to
1, 500 ppm of 2, 4-D -- a Delta parallel. No incidence of tumors or
physiological malfunction could be found from 500 ppm in the diet, but
at 1,500 ppm, there was a reduction in the number of pups which sur-
vived to weaning and in the weights of weanlings. Five hundred ppm in
the diet of adult rats is 25 mg/kg/day. ** Applying the previously
*Hansen, W. H., etal., tt Chronic Toxicity of 2, 4-D5chlorophe-
noxyacetic Acide in Rats and Dogs, It Toxicology and Applied Pharma-
cology , Vol. 20, 1971, pp. 122-129.
**An adult rat weighs 400 grams and cats ZO grams of dry food/day.
Therefore, 1 ppm in the di.et of an adult rat is 0. 02 mg or 0. 05 mg/kg
body weight/day. Thus, 500 ppm is 25 mg/kg/day.
4.24
-------
determined proposed factor of safety of 1 0 to this finding, it is con-
cluded that at a human intake of 2. 5 mg/kg/day or less, no oncogenic
hazard, reproductive impairment or physiological malfunction hazard
is expected.
As shown in a later section, the human dietary intake by society
as a whole from use of Delta on wheat, oats, and barley can he expected
to be close to zero. Thus, there is no expectation of oncogenic hazard,
reproductive impairment or physiologic malfunction hazard to society
as Delta is not expected to be consumed by society at the rate necessary
to cause harm, when it is used in wheat, oats or barley production.
For the occupationally exposed, although their dietary intake is
expected to also be close to zero, additional human intake can result
from direct oral, dermal, and inhalation exposures to Delta when pro-
duced for or used in wheat, oats, and barley production. 1-lowever, if
the occupational exposure from these three routes of entry, plus any
dietary intake, does not produce a daily intake of more than 2. 5 mg/kg,
oncogenic hazard, reproductive impairment and physiological malfunc-
tion hazards can all be expected to be zero. There is no evidence in
the literature to date that indicates occupational exposure has or would
exceed this amount unless someone were trying to commit suicide.
Furthermore, even if an occupationally exposed person inhaled, for
eight hours, air containing 10 mg/m 3 of Delta, this would only repre-
sent a daily intake of 1. 14 mg/kg, well below the 2. 5 mg/kg level.
Therefore, one can assume the intake of Delta by the occupationally
exposed does not exceed 2. 5 mg/kg, and based on animal toxicology
data, one can expect that there is no danger of these types of hazards
occurring to those occupationally exposed to Delta.
Considering that Fenox has been defined .to be similar to Delta
with respect to chronic injury hazards, one can also expect that there
is no oncogenic hazard, reproductive impairment or physiological mal-
function hazard to society or to those occupationally exposed to Fenox.
*This is the TLV for Delta (see page 4. 18).
**A man breathes approximately 1 cubic meter of air per hour
when at work or 8 cubic meters of air per work day. Assuming the air
contains 10 mg/rn 3 of Fenox, he would inhale 80 mg of Fenox a day.
For a 70 kg man, this represents 1. 14 mg/kg/day.
4.25
-------
Therefore, for all subpopulations, it follows that the net change
in oncogenic hazard, reproductive impairment or physicological rnal-
function hazard is zero per 100, 000 exposed, if Fenox is substituted
for its next best alternative Delta.
4. 3.2 Determination of Net Health
Damages Using Human
Experience Data
In this section of the health effects analysis, the effects caused
by Delta are assumed to be given by any human data of record on expo.-
sure to any of the phenoxy herbicides. Furthermore, the human data
that would be generated if people were exposed to Fenox are assumed
to be the same, except in cases where the animal toxicology data have
been hypothesized to be otherwise.
4. 3.2. 1 Acute and Chronic Injury
to R and D, Manufacturing
and Formulation Workers
Acute and chronic injury to R and D, manufacturing and formula-
tion workers producing Fenox for use in wheat, oats, and barley pro-
duction will result from oral, dermal, ocular and/or inhalation expo-
sures. ‘ To estimate the extent of these injuries, a recent study of 73
male workers in a 2, 4, 5-T plant was used. The average age of the
employees was 39. 3 years and the average duration of employment was
8. 3 years. However, duration of employment was not a very significant
factor in the severity of many conditions; rather, individual suscepti-
bility was more important. In this study, the following health
effects, including their frequencies in parentheses, were noted among
the employees as being caused by exposure to 2, 4, 5-T:
*Chronic injury is not expected to result from dietary intake of
Delta because the dietary intake of Delta is expected to be sufficiently
close to zero as discussed under Section 4. 3. 2. 4, tiAcute arid Chronic
Injury to Society.
Poland, A. P. , Ct al. , “A Health Survey of Workers in a 2, 4-D
and 2, 4, 5—T Plant, A rchivcs of Environmental Health , \‘oI . 22,
March, 1971, pp. 316-327.
* Jbid., pp. 316, 324.
4.26
-------
Ocular
Conjunctival injection-I- (4. 1%)
Itching of eyes-f+ (9. 6%)
Blootshoteyes- I-+ (6.9%)
Frequent tearing++ (19. 2%)
Sties++ (9.6%)
Dermal
Severe chloracne+ (17.8%)
Hyperpigrnentation+ (41. 1%)
Hirsutism+ (21.9%)
Scarring+ (35.6%)
Uroporphyrinuria+ (1.4%)
Porphyria+ (0.0%)
• Oral
Inflammation of buccal mucosa+ (1 0. 9010)
Inhalation
Hyperernia of nasal mucosa+ (31. 5%)
• Systemic poisoning
Nausea, vomiting, diarrhea, abdominal
pains, blood in stool+ (30. 0%)
Leg fatigue+ (2. 7%)
Diminished proprioception+ (1.4%)
.• Decreased auditory acuity+ (8. 2%)
• Death
No mention of deaths in the plant from
exposure to 2, 4, 5-T was made. It is
assumed to be zero.
• Mutagenesis, teratogenesis, oncogenesis and
reproductive impairment were not studied.
-1-Based on physical examination.
+-I-These were complaints made by employees.
Major cause was dioxins in 2,4, 5-T; ibid . , p. 316.
*The validity of these findings are conjectural and it is uncertain
if the pesticide is the only cause for the frequencies being what they are.
4.27
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Physiologic malfunction
Abnormal function of cardiovascular,
pulmonary, intermediary metabolic,
or hematologic systems+
Liver disfunction+
Lack of vigor, lessened drive, libido,
emotional instability, diminished ability
to learn+
If one assumes that the R and D, manufacturing and formulation
workers exposed to Delta will be exposed in a similar fashion as those
exposed in the above mentioned a, 4, 5-T plant and that the workers in
the above mentioned plant are no more or less susceptible to health
injury than the employees of the Delta plant, then the above incidences
can be used to estimate the expected incidences for R and D, manufac-
turing and formulation workers exposed to Delta. Thus, the following
incidences have been generated to estimate these various types of injury:
Acute injury
Ocular exposure hazard 96/1000 cxposed
Dermal exposure hazard 103/1000 exposed
Oral exposure hazard 109/1000 exposed
Inhalation exposure hazard 315/1000 exposed
• . Systemic poisoning 300/1000 exposed :
Death None
+Based on physical examination.
*Percentage based on fact that a significant correlation found
between severe chloracne and high score on the manic scale of the
Minnesota Multiphasic Personality Inve ry (MMPI)
**This rate was based on the most prevalent ocular effect exclud-
ing tt frequent tearing 1t because it was felt “frequent tearing ’ t would only
occur while at work and would not result in lost work, the seeking of
medical advice or the taking of medication.
** Dioxins have been shown to be the major cause of chloracne
problems and all dermal effects have been shown to correlate signifi-
cantly with chloracne. Because Delta is assumed to have no detectable
dioxins, derrnal exposure hazard was arbitrarily estimated as one-
fourth the most prevalent dermal effect.
*** This rate was based on the most prevalent systemic poisoning
effect.
(0. 0%)
(0. 0%)
(17. 8%)
4,28
-------
Chronic injury
Physiologic malfunction hazard 45/1000 exposed
As indicated in the beginning of this chapter and in the animal
toxicology section (i.e. , Section 4. 3. 1), only ocular and dermal expo-
sure hazards were assumed to be more severe for Fenox than for Delta.
More specifically, the hypothetical animal toxicology data generated an
ocular exposure hazard for Fenox of approximately two times the ocular
exposure hazard for De1ta * and a dermal exposure hazard for Fenox
of approximately 1. 5 times the dermal exposure hazard of Delta.
This implies that the ocular and dermal exposure hazards for Fenox
can be expected to be 192 and 155, respectively, per 1, 000 manufac-
turing and formulation workers exposed, based on human experience
data. Therefore, the net increase in ocular and derrnal exposure
hazards can be expected to be 96 and 52, respectively, per 1, 000 man-
ufacturing and formulation workers exposed, if Fenox is substituted for
its next best alternative Delta. All other acute and chronic hazards are
assumed to be the same for both Fenox and Delta for a net change of
zero per 1, 000 exposed.
4. 3. 2. 2 Acute and Chronic Injury
to Field Workers and
Other Farm Personnel
Although phenoxy herbicides have been extensively used in agri-
culture, very little information is available that will allow one to cal-
culate the incidence rates for various types of injuries among farm
workers. Perhaps the best information available is from the State of
California. The California Department of Public Health, Bureau of
Occupational Health and Environmental Epid emiology, has published
for a number of years a report titled Occupational Disease in California
Attributed to Pesticides and Other Agricultural Chemicals . The most
recent and complete report seen has been for 1970. However, addi-
tional data for 1971 and 1972 has also been obtained.
*This rate was based on the chloracne rate because psychological
effects correlated significantly with chloracne. However, one-fourth
the chloracne rate was used following similar reasoning as in footnote
on the previous page.
* 5ee Section 4. 3. 1. 1. 1.
***See Section 4. 3. 1. 1.2.
4.29
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In the California report, pesticides are not listed individually,
but rather by types, one of which is herbicides. Therefore, in estimat-
ing the health effects of Delta on farm workers, the assumption is made
that Delta will produce the same kinds of effects on farm workers that
herbicides, in general, produced.
Proceeding with this background information, the 1970 Report
states that there were 711* reports of occupational disease among farm
laborers caused by pesticides and other agricultural chemicals. This
translates into an incidence of 3. 7/l000* farm workers. However,
only 14 percent*** (100 out of 711) of these reports involved herbicides,
implying that the incidence for occupational disease among farm
laborers caused by herbicides is 0. 52/1000 farm workers.
This incidence must then be adjusted to obtain the incidence per
1, 000 farm workers exposed to herbicides , as the present incidence is
based on all farm workers in the state and not just those exposed to
herbicides. This is important because not all cropland are treated
with herbicides and thus not all farm workers arc exposed to herbicides.
In 1970, one study estimated that only 2.33 percent of California s
cropland received 2, 4-D and that the average application rate was 3. 88
lb/acre. Assuming an equal number of farm workers per acre of
California cropland, only 2. 33 percent of the farm workers were
exposed to herbicides in 1970. This implies that the incidence of occu-
pational disease per 1,000 farm workers exposed to herbicides is 0. 52/
0. 0233, or 22. 3 percent. **
*California Department of Public l-Tealth, Bureau of Occupational
Health and Environmental Epidemiology, Occupational Disease ir Cali-
fornia Attributed to Pesticides and Other A ricultura1 Chemicals , 1970,
p.25.
Ibid., p. 10.
** Ibid., p. 25.
****Crockett, A. B., etal., tipesticide Residue Levels in Soils and
Crops, FY 70, National Soils Monitoring Program (II), Pesticides
Monitoring Journal , Vol. 8, No. 2, September, 1974, p. 79.
* * ‘ t must be stated that this incidence is a crude estimate and it
understates the actual incidence of occupational disease because it is
based on reports of occupational disease only . Thus, numerous cases
of occupational disease caused by herbicide exposure are not accounted
for because they never are reported. Yet, this is the best information
available. In the case of a real benefit-cost analysis of a pesticide,
greater care should be taken to get a better estimate if possible.
4.30
-------
Returning to the California study, data shows that of all occupa-
tional disease in 1970 involving herbicides, 14 percent produced sys-
temic poisoning, 5 percent involved a respiratory condition, 39 percent
involved a skin condition, and 43 percent involved an eye condition.
For 1971, these percentages were 11, 4, 35, and 49, respectively, and
for 1972, they were 10, 4, 36, and 50, respectively. No agricultural
worker deaths were reported in 1970.
Applying an average of the above percentages of each occupational
disease involving •herbicides to the incidence of occupational disease per
1,000 farm workers exposed to herbicides, gives the following mci-
dences of acute injury for farm workers exposed to herbicides when
applied at a rate of approximately 0. 88 lb/acre:
• Ocular exposure hazard 10. 5/1000 exposed
• Dermal exposure hazard 8.2/1000 exposed
• Oral exposure hazard Included in systemic
poisoning
• Inhalation exposure hazard 1.0/1000 exposed
• Systemic poisoning 2.6/1000 exposed
• Death None
Assuming that Delta is applied on wheat, oats, and barley in a
similar manner and at a similar rate as herbicides were applied in
California, these incidences can be used as estimates of the acute
injury likely to be incurred by farm workers when exposed to use of
Delta on wheat, oats or barley crops. Considering the fact that Delta
is assumed to be applied at a rate of 0.2-0.9 lb/acre and these mci-
deuces were caused by a 0. 88 lb/acre application rate, this assump-
tion is a reasonable one.
Following the same arguments made above in Section 4. 3. 2. 1,
the ocular and dermal exposure hazards to farm workers exposed to
Fenox can be expected to be 21 and 12.3, respectively, per 1,000
exposed, based on human experience data. This implies a net increase
in ocular and dermal exposure hazards of 10. 5 and 4. 1, respectively,
per 1, 000 farm workers exposed, if Fenox is substituted for its next
best alternative Delta. All other acute hazards are assumed to be the
same for both Fenox and Delta for a net change of zero per 1, 000
exposed.
*California Department of Public Health, . cit. , p. 24.
4. 31
-------
With respect to chronic injury among farm workers caused by
exposure to phenoxy herbicides, no information has been found based
on human experience data. Therefore, the assessment of chronic
injury among farm workers caused by exposure to either Delta or
Fenox must be based solely on results of animal toxicology data.
4. 3. 2. 3 Acute and Chronic Injury to
Commercial Farm Applicators
When looking for information concerning acute and chronic injury
to commercial farm applicators from application of phenoxy herbicides,
one faces the same problems as with the agricultural worker subpopula-
tion. Once again, the only information available appears to be from the
State of California, in the same report cited previously.
In the 1970 California report, there were 227 reports of occupa-
tional disease among agricultural service workers caused by pesticides
and other agricultural chemicals. This translates into an incidence of
9.2/ 1OOO * agricultural service workers. Most of these reports were
received from spraying and pest control service firms and therefore
this incidence does reflect the likelihood of illness among spraying and
pest control worker s* * when exposed to pesticides or other agricul-
tural chemicals. Of these 227 reports, only 11 percent**** (24 out of
227) involved herbicides, implying that the incidence for occupational
disease among agricultural service workers caused by herbicides is
1.0/1000 agricultural service workers. This number also represents
the incidence per 1,000 agricultural service workers exposed to herbi-
cides as all agricultural service workers are exposed to some kind of
*California Department of Public Health, . cit., p. 25.
**Ibid., p. 10.
***The incidence actually understates the rate of occupational
disease among this group for two reasons. First, the incidence is
based on all agricultural service employees when most of the illness
occurred in only one segment of all agricultural service employees,
i.e., spraying and pest control workers. Second, the incidence is
based on reported cases and not actual illnesses. Many go unreported
as with the agricultural worker subpopulation, but this information is
still the best available.
****California Department of Public Health, . cit., p. 25.
4.32
-------
pesticides by the very nature of their business. Thus, the incidence
does not have to he adjusted for only those agricultural service workers
exposed to herbicides.
Applying the average percentage of each type of occupational
disease involving herbicides obtained in the previous section to the inci-
dence of occupational disease per 1, 000 agricultural service workers
exposed to herbicides, gives the following incidences of acute injury for
agricultural service workers exposed to herbicides when applied at a
rate of approximately 0.88 lb/acre:
• Ocular exposure hazard 0.47/1000 exposed
o Dermal exposure hazard 0.37/1000 exposed
Oral exposure hazard Inc luded in systemic
poisoning
• Inhalation exposure hazard 0.04/1000 exposed
• Systemic poisoning 0. 1Z/l000 exposed
• Death None*
Assuming that Delta is applied on wheat, oats, and barley in a
similar manner and at a similar rate as herbicides were applied in
California, these incidences can be used as estimates of the acute
injury likely to be incurred by agricultural service workers when
exposed to use of Delta on wheat, oats or barley crops. Considering
the fact that Delta is assumed to be applied at a rate of 0. Z-0. 9 lb/acre
and these incidences were caused by a 0. 88 lb/acre application rate,
this assumption is a reasonable one.
Following the same arguments made above in Section 4. 3.2. 1,
the ocular and dermal exposure hazards to commercial farm appli—
cators exposed to Fenox can be expected to be 0. 94 and 0. 55, respec-
tively, per 1, 000 exposed, based on human experience data. This
implies a net increase in ocular and dermal exposure hazards of 0.47
and 0. 18, respectively, per 1, 000 commercial farm applicators
exposed, if Fenox is substituted for its next best alternative Delta.
All other acute hazards are assumed to be the same for both Fenox
and Delta for a net change of zero per 1,000 exposed.
No deaths were reported in 1970 for agricultural service workers
from exposure to pesticides.
4. 33
-------
With respect to chronic injury to commercial farm applicators
caused by exposure to phenoxy herbicides, no information has been
found based on human experience data. Therefore, the assessment
of chronic injury among commercial farm applicators caused by expo-
sure to either Delta or Fenox must be based solely on results of animal
toxicology data.
4.3.2.4 Acute and Chronic Injury
to Society
Acute injury to society from use of Delta on wheat, oats, and
barley crops would result from drift of the product during and subse-
quent to the application process. However, in reviewing the published
scientific literature, there have been no reports of acute injury to
society caused by drift of 2, 4-D and 2, 4, 5-T from treated fields. The
lack of such reports and the presence of similar reports for other pes-
ticides, such as organophosphates, leads one to conclude that accidents
of this nature have not been found to occur with phenoxy herbicides.
Therefore, one may also assume that these types of accidents will not
occur with the use of Delta on wheat, oats, and bar1 y. Hence, there
is no reason to believe that acute health injury will accrue to society
when Delta is used on wheat, oats, and barley crops.
Similar arguments are assumed for Fenox; therefore, the result
is expected to be the same as for Delta. This implies that a net change
of zero in the incidence of acute injury to society is expected, if Fenox
is substituted for its next best alternative Delta.
Chronic health injury will accrue to society through their dietary
intake of pesticides in the food they eat, in the air they breathe or in
the water they drink. However, the majority of this intake will occur
in the food. Considering that Delta is being analyzed with respect to
its use on wheat, oats, and barley crops, dietary intake of Delta can
only result from residues left on grains and cereals produced for human
consumption and grains and cereals produced for animal feed that are
then in turn fed to animals slaughtered for human consumption. Pesti-
cide residues in total diet samples have been analyzed for the past seven
*See Report of the Secretary t s Commission on Pesticides and
Their Relationships to Environmental Health , U.S. DIIEW, 1969.
____ p. 384.
4.34
-------
years under the Total Diet Program supervised by the Food and Drug
Administration. In the most recent report, * no phenoxy herbicide was
found in ready-to-eat dairy products, cereals and grains, and meat,
fish and poultry during the period, June 1970-April 1971. In addition,
older reports also showed that no phenoxy herbicide was commonly
found in these same ready—to-eat products. *
The approximate limit of quantification for analysis of chiorophe-.
noxy acid herbicides is 0. 02 ppm. Therefore, there is the pos si-
bility that phenoxy herbicides may he present in these ready-to-eat
products, but at levels where detection is impossible. Even if this
were the case, the levels would still be far below the WHO established
acceptable daily intake (ADI) of 0. 3 mg/kg for 2, 4-D residues in food
grains, because a 70 kg man would have to ingest (0. 3 mg/kg)
x (70 kg) 21 rug of the phenoxy herbicide per day or 1, 050 kg of food
grains per day containing 0. 02. mg/kg of the phenoxy herbicide. This
occurrence can be assumed to be zero, which implies any phenoxy
herbicide intake from its use on wheat, oats, and barley will be well
below the ADI of 0. 3 mg/kg and more likely close to zero.
Therefore, assuming that Delta will be applied to wheat, oats,
and barley crops at similar rates as its related phenoxy herbicides,
there is no indication that Delta will be ingested at any amount (through
the food products generated either directly or indirectly from the pro-
duction of wheat, oats or barley treated with Delta), sufficient enough
to cause any chronic injury. Hence, it is expected that there will be
no chronic injury to society as a result of Delta being used on wheat,
oats, and barley crops.
*Manske, D. D., and P. E. Corneliussen, ‘Pesticide Residue in
Total Diet Samples (VII), Pesticides Monitoring Journal , Vol. 5, No. 2,
September, 1974.
**The older reports referred to are the second, third, and fourth
total diet sample studies. They appeared in the Pesticides Monitoring
Journal , \ T ol. 1, No. 2, September, 1967; Vol. 1, No. 4, March, 1968;
and Vol. 2, No. 4, March, 1969 issues, respectively, and covered the
periods, June 1965-Api-il 1966, June 1966-April 1967, and June 1967-
April 1968, respectively.
* Manske, D. D., and P. E. Corneliussen, cit., p. 111.
****\ TI icJ, 22.- cit. , p. 2.9.
4. 35
-------
Similar arguments are assumed for Fenox; therefore, the result
is expected to be the same as for Delta. This implies that a net change
of zero in the incidence of chronic injury to society is expected, if Fenox
is substituted for its next best alternative Delta.
4. 3. 3 Summary of Net Health Damages
In the previous two sections 4. 3. 1 and 4. 3. 2 -- the change in
incidences of acute and chronic injury from exposure to Fenox when
substituted for Delta, and when used on wheat, oats, and barley crops,
were calculated for various subpopulation groups. This was accorn-
pushed by using two methods - - one relied on animal toxicology data
and the second relied on human experience data.
In some instances, the net incidences determined by the two
methods for the same injury! subpopulation group combination varied
a great deal. In this summary section, each injury!suhpopulation cell
of Exhibit 5.2 of Volume I of the report was completed using the highcr
of the two net inci.dences, so that the assessment of the net health
damages from the substitution of Delta with Fenox on wheat, oats, and
barley crops would be a liberal estimate rather than a conservative
C stimate.
Therefore, Exhibit 4. 3 summarizes the net health damages by
presenting the expected net incidences for the various types of acute
and chronic injuries to he incurred by thc- various subpopulation groups.
One will note that the net health damages expected to result from the
substitution of Delta with Fenox on wheat, oats, and barley crops are
acute in nature and will impact on those occupationally exposed, with
the highest increased incidence occurring in the formulating and man-
ufacturing subpopqlation and the lowest increased incidence occui ring
in the commercial farm applicator subpopulation.
These increased incidence rates can then be coupled with the
number of people in each subpopulation group expected to he exposed
in each of the five years from 1974 through 1978 when Fenox is substi-
tuted for Delta and used in wheat, oats, and barley production. That
is, assuming these increased incidence rates will remain fairly con-
stant over a 5-year period, Exhibit 4.4 presents the number of addi-
tional people in each subpopulation group expected to incur the various
types of health damages in each of the five years, based on the assurnp-
tions made about the size of each subpopulatiori group exposed during
this period. In terms of absolute numbers, field workers and other
farm personnel are expected to incur the most additional health damage
and commercial farm applicators the least.
4.36
-------
-J
EXHIBIT 4. 3: Net Incidence of Health Damages from Substitution of
Delta with Feriox on Wheat, Oats, and Barley Crops
(Given as number per 1,000 exposed)
Entity Incurring
Health Damage
Type of Health Damage --
Acute Injury
- Chronic Injury
Morbidity
Mortality
(Death)
Ouular
Exposure
Hazard
Dermal
Exposure
Hazard
Oral
Exposure
Hazard
Inhalation
Exposure
Hazard
Syatemic
Poisonin
Mutagenie
Hazard
Terato-
genic
Hazard
Reproduc-
Oncogenic* tive Ito-
Hazard pairment
PhysloIo ic
MaHunction
Fsrard*
Occupational Health Damage to:
Pesticide R&D Manufacturing
&nd Formulation Workers
96
52
0
0
0
0
0
0
0
0
0
Pesticide Transport Personnel
Not dote
mined but a
surned to b
. negligible
,ased on di
cussiona w
h OPP per
onnel
Field Workers and Other Farm
Personnel
10.5
4.1
0
0
0
0
0
0
0
0
0
Commercial Farm Applicators
0.47
0. 18
0
0
0
0
0
0
0
0
0
Professional Non-Farm Appli-
cators (FCO ’s, government
employees, etc.)
na
na
na
na
na
na
na
na
na
na
na
General Public Health Damage to:
Household Users of Pesticides
(through direct exposure)
na
0*
0*
0 5
na
0*
0*
0*
0*
na
0*
Society as a Whole (through
indirect exposure)
0
0
0
0
0 -
0
0
0
0
0
0
= not applicable
Cm particular, with respect to central nervous sy5tetn hematopoctic system, liver and kidneys.
-------
EXHIBIT 4. 4 Number of Additional People Expected to Incur
Health Damage from Substitution of Delta with
Fenox on Wheat, Oats, and Barley Crops
(Given in number per year for 1974-1978)
Entity Incurring
Health Damage
Type of Health Damage
Acute Injury
- Chronic Injury
Morbidity
Mortality
(Death)
Ocular
xposure
Hazard
Dermal
£xposure
Hazard
Oral
Exposure
Hazard
lrJ alation
Exposure
Hazard
Systemic
Poisoning
Mutagenic
Hazard
Terato—
genic
Hazard
Oncogenic*
Hazard
Reproduc.
tire Im-
pairment
Physiologtc
Matfuncti n
Pa ard•
Occupational Health Damage to:
Pesticide R&D Manufacturing
and Formulation Workers
5 .7
3-4
0
0
0
0
0
0
0
0
0
Pesticide Transport Personnel
Not dete
mined but a
eumed to b
negligible
ased on di
cutsions w
Lb OPP per
onnel
Field Worker, and Other Farm
PersonneL
373.374
.
146-147
0
0
0
0
0
0
0
0
0
Commercial Farm Applicators
1-2
0-1
0
0
o
o
0
o
o
o
o
Professional Non-Farm Appli -
cators (FCO’., government
employees. etc.)
na
ne
ta
ru
tie
na
tie
ia
i a
na
ta
Cene rat Public Health Damage to:
Household Users of Pesticides
(through direct exposure)
tie
tie
na
na
na
na
na
ia
na
na
na
Soc ely as a Whole (through
(ndirect exposure)
0
0
0
0
0
0
0
0
0
0
0
na — not applicable
CIa particular, with respect to central nervous system, hamatopoetic system, liver and kidney..
-------
In further assessing these additional health damages, the next
step is to determine the monetary value of these damages. This is a
difficult task and additional data concerning the age and sex of the sub-.
populations exposed, the levels of injury at which they will seek med-
ical advice and/or treatment, and the levels of injury at which they will
lose time from work, are just a few of the factors which must he con-
sidered. For example, two different people exposed derrually to the
same degree to a pesticide may react differently. One may seek med-
ical advice, apply some medication and stay home for a day, while the
other may go to the drugstore, buy some over—the-counter medication,
and not stay home from work. Without increased efforts into examining
these processes, monetary estimates of the health hazards would be
misleading. A number of people have been doing work in this area,
and, therefore, efforts in this case study were directed to quantifying,
in non-dollar terms, the types of hazards that would result from expo-
sure to a pesticide. Nevertheless, this type of analysis is recommended
for all benefit-cost analyses, and a monetary evaluation of health costs
should be broken out for specific viewing by the decision-maker, when-
ever possible. This provides the additional advantage of clearly defin-
ing what is meant by each hazard term.
In this particular hypothetical case study, one may argue that the
value of these additional health damages have already been accounted
for in the measure of the change in consumers’ surplus. This is
explained in the following way. Additional health damages are only
incurred by the occupationally exposed. Assuming that these people
realize the risks of their profession, they will demand compensation in
terms of salary medical insurance, pensions, etc. These additional
health costs are borne by the employers of the occupationally exposed
and therefore will be reflected in the change in price of the pesticide,
the change in cost to apply the pesticide, the change in cost to ha rvest
the crop, and finally the change in crop price to the consumer. Conse-
quently, in the absence of additional health damages to these people,
the change in consumers’ surplus would be greater because the change
in price paid by the consumer for the crop would he smaller. Hence,
the change in consumers’ surplus does, in fact, account for the addi-
tional health damage to the occupationally exposed.
*For example, see Dorothy Rice, Estimating the Costs of Illness ,
Health Economics Series //6, DHEW, 1966 (PHS Publication No. 947-6);
Acton, Jan, Evaluating Public Programs to Save Lives: The Case of
Heart Attacks , RAND Corporation, January, 1973 (includes an extensive
bibliography); and Mushkin, S. , “Health As An Investment, “ J ournalof
Political Economy , Vol. 7, No. 5, Part 2, October, 1962.
4.39
-------
Furthermore, this change in consumers’ surplus will account for
all additional health damage if the following assumptions hold:
• The occupationally exposed are aware of the risks,
• They willingly accept them,
• They demand compensation for assuming the risks,
and
• They receive adequate compensation.
In all probability, the four assumptions will not hold for all those occu.-
pationally exposed. Manufacturing and formulating workers and com-
mercial farm applicators are probably aware of the risks. Field
workers and other farm personnel should be aware because of required
warnings necessary under the EPA “Worker Protection Standards for
Agricultural Pesticides” (4OCFR 170). With respect to the other three
sumptions, it is difficult to tell to what extent the occupationally
posed accept the risks, demand compensation, and receive adequate
compensation. Assuming that they do not receive adequate compensa-
tion, there would he additional health costs not embodied in the change
in the consumers’ surplus measure. Therefore, all one can say is that
balanced against the change in the consumers’ surplus measure is some
unknown value of the additional health costs incurred by the occupation-
ally exposed not already accounted for in the change in the consumers’
surplus measure.
Emphasis is again needed that to more adequately present the sit-
uation to a decision-maker, health costs should be valued and separated
out for specific viewing if possible. If a portion or all of these net
health costs are embodied in the change in the consumers’ surplus mea-
sure 1 this can be so stated so that double-counting is avoided.
4. 4 Net Health Benefits
Health benefits from substituting Delta with Fenox on wheat, oats,
and barley accrue to society in the form of a more healthful, more pro-
ductive and more content population. These result from an increased
food supply caused by an increased yield in these three crops.
From the agricultural impacts analysis in Chapter 3. 0, it is esti-
mated that in 1973 an additional 22.5 million bushels of wheat, 32. 0
million bushels of oats, and 10.2 million bushels of barley would have
been produced, if Fcnox had been substituted for Delta.
4.40
-------
In 1978, it is estimated that if Fenox is not registered and Delta
is continued to be used, the decrease in wheat, oats, and barley pro-
duction will be 26. 6 million bushels, 38.2 million bushels, and 12. 1
million bushels, respectively.
Although it is difficult to translate the net benefits (from the
increased food production generated from the use of Fenox rather than
Delta) into monetary terms, in this case one can argue that they are
already accounted for in the change in the consumers’ surplus measure.
It is assumed that society perceives that there are health benefits as so-
ciated with an increased food supply as a result of using Fenox rather
than Delta on wheat, oats, and barley. Moreover, these additional
health benefits are nutritional in nature and only accrue to those who
consume wheat, oats or barley products. Therefore, they receive a
value from this increased food supply in excess of what they pay for
wheat, oats or barley products. Hence, a part of the change in con-
sumers’ surplus represents the value members of society put on the
additional nutritional health benefits resulting from this increased food
supply when Fenox is substituted for Delta and used on wheat, oats, and
barley.
Once again, it would be more desirable to separate out these net
benefits and show them separately to the decision-maker with the state-
ment that they are already accounted for in the change in the consumers’
surplus measure. In this way, they will not be added to the change in
the consumers’ surplus measure, and doiible-counting will be avoided.
4.41
-------
5.0 ENVIRONMENTAL IMPACTS
5. 1 Introduction
Previous chapters of this case study have described how to apply
a series of algorithms or submodel components, to calculate the agri—
cultural impacts and health effects of Fenox when compared with its
next best alternative Delta. Both are fabricated herbicides having cer-
tain assigned features similar to the phenoxy category presently in wide
use (e.g. , 2, 4-D; 2,4, 5-T; MCPA). Furthermore, in this chapter,
Fenox and Delta are a ’sumed to be similar in all respects, except in
their toxicity to birds and fish, as indicated later in the chapter. These
pesticides have been in use for some years and have been widely studied.
Although phenoxy herbicides are characterized by an acid chain,
and in some chemicals by chlorine attachments to the organic ring, the
general conclusion of published studies has been that these herbicides
disappear from the environment within a few months aft:cr application
and that they are not found to accumulate to high levels in various bio-
logical systems, as is the tendency of the organochiorine insecticides.
The present report concentrates on possible year-to-year effects and
does not assign a high persistence to the hypothetical herbicides Delta
and Fenox.
The environmental effects submodel which is applied in this chap-
ter to analyze the change in environmental impacts if Fenox is substi-
tuted for Delta has been described in Volume I of the report, and con-
sists of three major components:
• Transport and accumulation component,
• Biological impacts component, and
• Environmental costs component.
As noted in Volume I, some pesticides have inadvertent or incidental
benefits, but these are assumed to be minor or negligible for both Delta
and Fenox, and the major question is: What are the net environmental
costs of this hypothetical herbicide Fenox when compared to its next
*NSF Advisory Panel on 2, 4, 5-T.
5. 1
-------
best alternative Delta? Furthermore, as in the agricultural impacts
analysis. data for two years -- 1973 and 1978 - - are presented through-
out the analysis. However, in the monetary evaluation of fish and bird
damage, data for the years 1974 through 1977 are also determined and
their values, along with the 1978 value, are discounted back to their
value in 1974.
5. 2 Transport and Accumulation
The non-crop environment is impacted by pesticides without
regard to the crop on which they are applied. Therefore, the total
pounds applied to the three different crops were divided by the total
acreage of the combined crops to obtain an average rate of application
per acre for each region (see Exhibits 5. 1 and 5.2). A more precise
approach would be to determine average application rates for each
region and each crop. However, it was felt that a regional level analy-
sis would be sufficient here as it partially reflects crop differences.
Within a short time (hours) after the application of a herbicide,
it is either absorbed into a plant, absorbed into the soil, or washed
into some hydrologic system present at the site of application. Amounts
absorbed into plants tend to disappear within days, so that the present
study assumes that all herbicides applied in a given year eventually
impinge on the soil or water near the application site.
The movement of herbicides from fields into an hierarchical
hydrologic system is highly complex, and a somewhat detailed modeling
approach is described in Attachment 5. 1 to this chapter. A much sim-
plified estimation procedure is to directly relate amounts of herb .icide
applied to residues found in bodies of water, and to apply the ratios as
needed to forecast future residues (see Exhibits 5. 3, 5. 4, 5. 5, and
5.6). The drift factors in Exhibit 5.4 are substitutes for a meteoro-
logic model which would calculate amounts of spray blown into water.
After subtracting drift and runoff amounts, the remaining herbi-
cide is assigned as residue in soil. The residues of Exhibit 5. 7 reflect
the average decline in amount applied per acre shown in Exhibit 5.2, a
phcnomenon due to a forecast of increased acreage described in the
agricultural impacts chapter above.
5.2
-------
EXHIBIT 5.1: Arriounts of Fenox or Delta Applied by Regions on Selected Crops*
Lfl
See Exhibit 6. 10 of Volume I of report. This is calculated as AAijkp = Amount of pesticide k applied in
region i between j-l and j to crop p, and is equal to (the application rate of pesticide k in region i at time j
to crop p) times (the number of acres of crop p treated with pesticide k in region i at time j).
Application rates for Fenox or Delta are the same for each year: 0.90 lbs/acre for wheat; 0.46 lbs/acre for
barley; and 0.20 lbs/acre for oats (see Chapter 3. 0 on agricultural impacts). The number of acres treated
with Fenox or Delta is contained ‘in Exhibit 3. 8 of the agricultural impacts chapter.
Data in Hundreds of Pounds
North-
North- Lak Corn em Appa- South- Delta
east States Belt Plains lachian east States
South-
em
Plains
Moun-.
tam
Pacific
1973
Wheat
738
3,132
8,254
4,024
1,162
1,072
2,548
1,738
1,476
1,332
Barley
70
258
116
956
290
56
--
194
612
530
Oats
112
192
1,572
530
94
102
518
220
34
38
1978
Total
Wheat
920
3,582
9,942
6,410
1,546
1,230
3,066
2, 152
2, 122
1,900
874
3,708
9,792
5,824
1, 378
1,270
3,006
2,044
1,746
1,576
Barley
82
308
134
1,136
340
64
--
230
722
626
Oats
162
226
1,866
628
112
122
614
258
40
46
Total
1,118
4,242
11,792
7,588
1,830
1,456
3,620
2,532
2,508
2,248
-------
EXHIBIT 5.2: Calculation of Average Application Rates for Fenox or Delta
(Pounds/acre applied)*
North-
Lake
Corn
North-
em
Appa-
South-
Delta
South-
em
Moun-
Pacific
east
.60130
.57040
States
.71640
.71656
Belt
.57534
.57522
Plains
.62844
.62814
lachian
.64686
.64664
- east
.67582
.67408
States
.56568
.56474
Plains
.62376
.62364
-
.67580
.67602
.67376
.67306
*Pounds/acre applied = AAjjk/CTijk (amount of pesticide k applied in region i between j -l arid j)
+(total acres of land treated by pesticide k in time j and region i). AAj 3 k is given in Exhibit 5. 1
and CT Jk is given in Exhibit 3,8 of the agricultural impacts chapter.
-------
EXHIBIT 5. 3: Calculation of Runoff Factors (ROFjk) for Orgariochiorine Insecticides by Region
North-
east
Lake
States
Corn
- Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
States
em
Plains
Moun-
tam
Pacific
States
Average
Application rate
0.654
3.076440
(A) lbs/acre
10.633
0.674
1.064
0.559
5.422
6.635
3.605
1.245
0.880
active
ingredient
3.303
0.623
0.440
0.327
1.538220
(A ’) ppm**
5.317
0.337
0.532
0.280
2.711
(B) Water
194.05
36.00
33.20
468.50
59.79
158. 3080
re siduals***
(ppm x 106)
(B)/(A ’)****
135.89
1246.33
Runoff factor
5758.16
67.67
10.01
259.92
(ROFIk) (106)
a unitless pro-
portion
I = region;
k = pesticide
Three insecticides Aldrin, Dieldrin, and DDT applied in 1971. From P. A. Andrilenas, etal., Farmers’ Use
of Pesticides in l971 Quantities , USDA, ERS, Agricultural Economic Report No. 252, Washington, D. C. , 1974,
Tables 13 and 15, pp. 46, 51.
**Pound per acre 4 2 ppm.
***Edwards, C. A., “pesticide Residues in Soil and Water,” in C. A. Edwards, ed., Environmental Pollution by
Pesticides , London, Plenum Press, 1973, pp. 440-441. Totals for three insecticides applied in selected years,
1966- 1971.
****Use United States average for all regions. See also C. A. Edwards, Persistent Pesticides in the Environment ,
Cleveland, Chemical Rubber Company Press, 1973, p. 35.
‘Jl
U i
-------
EXHIBIT 5. 4: Calculation of Water Application and Drift Factor (APWIJk)*
North-
east
Lake
States
Corn
Belt
North-
erri
Plains
Appa-
lachian
South-
east
Delta
States
South-
em
Plains
Moun-
tam
Pacific
Total
United
States
(A)
Water
6,851
7,868
2, 133
3,705
6, 597
7,004
5, 172
6,341
7,840
4,751
58, 262**
Surface
(sq. mi.
)
(B)
Land
175,203
190, 570
257, 756
303,498
193, 626
193, 096
144, 171
330, 916
856, 047
319, 115
2,963,998
Surface
(sq. ml.
)
.01
/B
.000391
. 000413
. 000083
. 000122
. 000341
. 000363
. 000359
. 000192
. 000092
. 000149
. 000197
APWjJk
*APWIjk water application and drift factor in region i at time j for pesticide k (a unitless proportion)
(.01) (acres of water surface in region i)/(acres of land surface in region i); j time and k pesticide.
**(58, 262 sq. mi.) (640 acres/sq. ml.) = 37, 287, 680 acres.
-------
EXHIBIT 5. 5: Herbicide Residue (Fenox or Delta) in Water* (PLWIjk. in ppm)
North- South-
North- Lake Corn em Appa- South- Delta em Moun-
east States Belt Plains lachiari east States Plains tam Pacific
ROFIk .00164 .00166 00133 .00137 .00159 .00161 .00161 .00144 .00134 .00140
+ APWjjk**
Amount 1973 30065 .35820 28767 31422 32343 .33791 .28284 31188 33790 .33688
Applied
Converted
to ppm ** 1978 .28520 .35828 .28761 .31407 .32332 .33704 .28237 .31182 .33801 .33653
Total
PLWIjk: 1973 . 00050 . 00059 . 00038 . 00044 . 00052 . 00054 . 00046 . 00046 . 00046 . 00048 . 00483
Residue in
Water ’ ’ 1978 .00046 .00059 .00038 .00044 .00052 .00054 .00046 .00046 .00046 .00048 .00479
*The change in herbicide residue in water if Fenox is substituted for Delta is assumed to be zero.
**The United States average for ROFIk is used (see Exhibit 5.3) and regional figures for APWj k are used
(see Exhibit 5.4).
* Source: Exhibit 5.2 and conversion factor of one-half pound/acre ppm.
****PLWIjk [ ROFIk + APWIjkJ {(CV (AAjjk/CTIJk)]
CV is a constant to convert pound/acre to ppm: one-half pound/acre ppm.
-------
EXHIBIT 5.6: Simplified Calculation of Accumulation of Fenox or Delta in Soil, 1973_1977*
1 1
RSDLIk = [ ( -) ( AA/CT) - ( ) (Z AA/CT) (ROFik + APWIJk)] [ 1 - DF 1 j for region i, year j, herbicide k
j 1 j =1
[ Total accumulated] = [ Net application to soil] [ 1 - Degradation rate]
[ Net application to soul [ Annual average amount] [ Number of years.! - [ Annual average amount]
[ Runoff rate] [ Number of years]
North-
.
South-
North-
east
Lake
States
Corn
Belt
em
Plains
Appa-
lachian
South-
east
Delta
States
em
Plains
Moun-
tam
Pacific
Average application
.29293
.35824
.28764
.31415
.32338
.33748
.28261
.31185
.33785
.33671
per year (ppm)
Runoff + drift loss for
.00240
.00300
.00192
.00216
.00258
. 00250
.00240
.00224
.00226
.00236
five years, ppm’ *
Net application
.29053
.35524
.28572
.31199
.32080
.33498
.28021
.30961
.33559
.33435
Residue after degrada-
tion’ [ (Net application)
x (1 - DFjk)]
.01453
.01776
.01429
01560
.01604
. 01675
. 01401
.01548
.01678
.01672
The change in accumulation in soil if Fenox is substituted for Delta is assumed to be zero.
* Runoff rate ROFjk + APWI3k (from Exhibit 5. 5).
= degradation factor 0. 95 in one year for Delta or Fenox (see Volume I of report, Exhibit 6. 7).
Therefore, the amount remaining (1 - DFIk) 0. 05 for each year. For Fenox and Delta, PLS 1973
(i.e., soil pollution level in 1973) is assumed to he zero for all regions.
-------
EXHIBIT 5. 7: Herbicide Residue (Fenox or Delta) in Soil, Per Acre*
North-
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
States
em
Plains
Moun-
tam —
Pacific
Application (ppm)
1973
.30065
.35820
.28767
.31422
.32343
.33791
.28284
.31188
.33790
.33688
(see Exhibit 5.5)
.33704
.28237
.31182
.33801
.33653
1978
.28520
.35828
.28761
.31407
Runoffamount
1973
.00050
.00058
.00038
.00044
.00052
.00054
.00046
.00046
.00046
.00048
(ppm) (PLW)
00052
00054
00046
.00046
00046
. 00048
(see Exhibit 5.5)
1978
. 00046
. 00058
.00038
.00044
.
.
.
.
Previous accum-
1973
. 00
. 00
.00
. 00
. 00
. 00
.00
. 00
. 00
. 00
ulatiori (ppm)
.01604
.01675
.01401
.01548
.01678
.01672
(RSDL)
1973—
.01453
.01776
.01429
.01560
(see Exhibit 5.6)
1977
Net total in soil**
1973
.30015
.35761
.28729
. 31378
.32291
.33737
.28238
.31142
.33744
.33640
1978
.22927
.37545
.30152
.32923
.33884
.35325
.29592
.29592
.35433
.35277
*The change in herbicide residue
**Soil residue application rate -
in soil if Fenox is substituted for Delta ia assumed to be zero.
runoff amount + previous accumulation,
U i
-------
5. 3 Impacts on Biological Systems
The natural accumulation of herbicides in fish and wildlife occurs
both due to direct absorption and ingestion, as well as due to accumula-
tion by means of the food chain. Conceptually, the food chain accumula-
tion is much more complex and difficult to assess, but when approached
from a modeling point of view, the two types of phenomena tend to
merge. For example, suppose an aquatic herbicide is applied to some
water hyacinths, portions of which are then eaten by various species of
water fowl. Some of the herbicide has been absorbed systematically by
the plant; but some of the chemical adheres temporarily to the leaves,
until it is washed off. It is possible to assert that the herbicide which
was absorbed into the plant was accumulated in the ducks as part of
their food chain, while the herbicide which was on the surface of the
leaves was “ingested directly.
Similar phenomena can be identified with fish, which absorb herb-
icides directly through their gills, as well as by eating microorganisms
which have absorbed the chemicals. In order to obtain a simple algo-
rithm for fish accunmiation, data on concentrations of herbicides in
fish tis ue and in water we re ave raged over a period of time a nd over
several geographic locations. The data on concentrations in fish were
in the form of concentration factors, and an average of these factors
was used to assess the feasibility of using such factors for herbicide
accumulation. For the data on insecticides, a reverse calculation of
water concentrations derived from fish calculations is shown in
Exhibit 5.8. Assuming the concentration factors for phenoxy herbi-
cides would be similar, the fishtonccntration factor was then applied
to water concentration data from previous calculations (Exhibit 5. 5,
above), to obtain regional fish concentrations shown in Exhibit 5. 8,
below.
These data, shown in parts per million, should probably be inter-
preted as milligrams per kilogram of fish weight. The process of
accumulation of these residues is much more complex, as noted above,
*Edwards, C. A. , Persistent Pesticides in the Envi ronment ,
Cleveland, Ohio, Chemical Rubber Company Press, l 37l, Table 12,
p. 8; and Menzie, C. M. , “Effects of Pesticides on Fish and Wildlife, “
F. Matsumura, et a]. , eds. , Environmental Toxicolo v of Pesticides ,
Table 8, p. 497.
5. 10
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EXHIBIT 5. 8: Calculation of Herbicide Concentration (Fenox or Delta) in Fish*
CFHijkp = (KF 5 kp) (PLWjjk) (formula from Volume I of report, Exhibit 6. 11)
CFHijkp 7.40523, fish tissue residues, Table 12, p. 8, C. A. Edwards, Persistent..., Cleveland, Ohio,
Chemical Rubber Company Press, Table 11, p. 28 (average of 65 values, amount of DDT
in ppm). For lower ratios 1.30, see T. Nakatsugawa and P. Nelson, “Studies of Insecti-
cide Detoxification in Invertebrates..., ” in F. Matsumura, etal., eds., Environmental... ,
Academic Press, 1972, p. 505.
KFjkp 4831. 0, concentration factor, average of seven organochiorine insecticides, Table 8, p. 497, data
from studies dated 1964-69. Merizie, C. M. , “Effects of Pesticides. . . , “in F. Matsurnura,
etal., eds., Environmental _ Toxicology... , pp. 487-500.
7.40523 + 4831.0 = 0.0015 ppm; this is a typical residue level found in water (See Exhibit 545),.
Therefore, regional concentrations (CPHijkp) = (4831.0) (PLWI 5 k):
North-
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta_
South-
em
Plains
Moun-
tam
Pacifi
Herbicides 1973
Re sidues
(ppm) 1978
2.4155
2.2223
2.8503
2.8503
1.8358
1.8358
2.1256
2. 1256
2.5121
2. 5121
2.6087
2.6087
2.2223
2.2223
2.2233
2.2223
2.2223
2.2223
2.3188
2.3188
*The change in herbicide concentration in fish if Fenox is substituted for Delta is assumed to be zero.
-------
than the use of a singl.e concentration factor implies. Similarly, the
variability in concentration levels is overlooked in the time period and
geographic averages used here. Both fish weight levels and herbicide
concentration levels rise and fall seasonally, and regionally, with
greater variability than is reflected in the two single years and the ten
regions shown in Exhibit 5. 8.
For the calculation of herbicide concentrations in birds, a spe-
cific research effort on herbicide concentrations in gallinules was used.
Although this procedure resulted in the less detailed depiction of accum-
ulation mechanisms than a more explicit food chain model would allow,
these research data were among the few data available which dealt
directly with herbicides, instead of organochiorine insecticides. As
noted above, herbicides, especially the phenoxy type, degrade rapidly
in soil, and are thought to sink rapidly in bodies of water, so that data
on their transportation in fish and wildlife are lacking, and coefficients
for concentration are only available if they are based on estimates for
insecticides. The research published by Schultz and Whitney, how-
ever, is an exception. Data from this study are shown in Exhibit 5.9,
along with the results of applying the Loxaha.tchie “uptake coefficient”
to the application rates from Exhibit 5. 2 above. The resulting bird
concentrations are in units of milligrams per kilogram of bird tissue.
Emphasis is needed here that a much more specific model of this pro-
cess would be desirable. In such a model, the application rate in lbs/
acre would be converted to density in water and then into residues in
tissue using a biological uptake factor. S ’ch a model would be more
realistic but would require large amounts of additional data to develop.
As described in Volume I of this report, there are three types of
fish and wildlife damages which typically occur as a result of herbicide
application: acute (immediate) toxic effects; accumulation (chronic)
toxic effects; and reproductive disruption due to genetic damage or to
some damage to reproductive mechanisms. For fish, birds, and rnam-
mals, a matrix of three rows and three columns would be ideal for ana-
lyzing these types of effects, or population reductions. Lack of data,
however, make it impossible to fill in all nine cells of such a matrix,
*Schultz, D. P., and E. W. Whitney, “Monitoring 2, 4-D Residues
at Loxahatchie National Wildlife Refuge, “ Pesticide Monitoring Journal ,
Vol. 7, No. 3/4, March, 1974, Tables 1 and 4.
5. 12
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EXHIBIT 5. 9 Summary of Herbicide Uptake (Fenox or Delta) by Gallinuies*
Amount of Application
Residue in Breast
Muscle (mg/kg)
Residue in Liver
(rrig /kg)
Total I esidue
(mg/kg)
0. 975 mg/kg
Uptake coefficient 4 lb/acre
North-
east
Lake
States
Corn
Belt —
North-
em
Pla s_
Appa-
lachian
South-
east
Delta
South-
em
Plains
Moun-
tam
Pacific
Application rates 1973
.60130
.71640
.57534
.62844
.64686
.67582
.56568
.62376
.67580
.67376
(lbs/acre)
(see Exhibit 5.2) 1978
.57040
.71656
.57522
.62814
.64664
.67408
.56474
.62364
.67602
.67306
Concentration 1973
.14657
.17462
.14024
.15318
.15767
.16473
.13788
.15204
.16473
.16423
in water fowl =
(application rate) 1978
.13904
.17406
.. 14020
.15311
.15762
.16431
.13766
15201
.16478
.16406
x (uptake coefficient)
(ppm)
______
‘ The change in herbicide concentration in birds if Fenox is substituted for Delta is assumed to be zero.
‘ °Source: Schultz, D. P., and E. W. Whitney, 1 Monitoring 2, 4-D Residues. Pesticide Monitoring Journal ,
Vol. 7, No. 3/4, March, 1974, Tables 1 and 4, pp. 146, 152.
4 lbs/acre (2 applications
2 months apart)
0. 300
= 0.243750
0.675
U,
0. 975
-------
so that the effects which could be assessed are shown in Exhibits 5. 10,
5.11, and 5. 12. These effects include additional chronic and reproduc-
five effects to fish and additional chronic effects to birds if Fenox is
substituted for its next best alternative Delta.
The calculation of additional acute damages to fish is based on
the lethal concentration concept, which has been widely researched
(see source reference in Exhibit 5. 10). The calculations shown in
Exhibit 5. 10, and in Volume I of this report, assume that if the entire
biornass of freshwater fish in the United States receives exposure to
some given level, then some proportion of the individual fish will
receive an equivalent to, or an excess of, the 50 percent lethal concen-
tration, and half of those receiving that level of dose will die. it is
further assumed that the proportion which experience the LC5O will be
equal to the proportion of the LC5O which is found in the waters of the
United States, averaged over geographic areas. These above assump-.
tions can be debated and as more data become available they can be
refined.
Further assumptions were necessary to estimate the population
of fish of major species which exists in the United States. A more
detailed approach to the estimation of fish populations is shown in
Attachment 5.2 of this chapter.
5.4 Values of Ecologic Damages
The Statistical Abstract of the United States* gives data which
are useful in assessing the value of the fish and wildlife killed and not
produced each year aue to pesticides. These data represent expéndi-
tures by public agencies, including Federal, state, and local, to main-
tain wildlife and wildlife habitats. ideally, costs of wildlife should be
divided into costs of maintaining habitats, and costs of restocking, and
then thcse costs could be weighted according to the amount of each that
was incurred due to pesticide damages. The data available, however,
as shown in Exhibit 5. 13, only enable a total cost of maintenance, and
U. S. Bureau of the Census, Statistical Abstract of the United
States, 1974 , W. Lerner, cd., Washington, D.C., Superintendent of
Documents, 1974.
5. 14
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EXHIBIT 5. 10: Summary of Additional Population Damages
to Fish in Fenox is Substituted for Delta
Assume LC 50 = 106 ppm for Delta
Source: Average of 23 studies of 2, 4-D and 2,4, 5-T compiled in J. M. Lawrence and E. B.
Hollingsworth, S pplement to A guatic He rbicide Data (supplement to Agricultural
Handbook 231), Washington, D.C., USDA, 1969.
Hypothetically assume LC 50 53 ppm for Fenox
Concentration in 1973 . 00483
Water (ppm) 1978 . 00479
(see Exhibit 5.5)
Net acute effect 1973 .0000455 .00483/53 - .00483/106 .0000455
(net population 1978 .0000452 .00479/53 - .0047 ,/106 .0000452
kill factor) (see Volume I of report, Exhibit 6. 12)
Population total, 37, 287, 680, 000
each year*
Additional number 1973 1,700,000
of fish killed, if 1978 1, 682, 000
Fenox is substi-
tuted for Delta
*Assumption: Federal and state agencies stock enough to maintain constant population, regardless
of number caught or killed b’y pesticides. Assume carrying capacity of 1, 000 fish per acre of water
(see Exhibit 5.4). However, a more precise approach to ‘standing crop” is shown in Attachment 5.2
to this chapter.
-------
EXHIBIT 5. 11: Summary of Additional Reproductive Effectb
on Fish if Fenox is Substituted for Delta
Net reduction of fish population in year j = [ CFH1 kpf 1041 [ .035 (FPPIjk)1*
Concentration in 1973 2.33337 Therefore, CFHjjk/104 = .02244
fish tissue
(CFHIJk) 1978 2. 31405 Therefore, CFHiJkI1O 4 = .02225
average for
10 regions
(see Exhibit 5.8)
Fish production, 37, 287, 680, 000 Therefore, (FPP) (. 035) = 1, 305, 069, 000
each year (FPP)
(see Exhibit 5. 10)
IJ1
Net number of 1973 (1,305,069,000) (.02244) = 29, 286, 000
fish not produced
due to reproduc- 1978 (1,305,069,000) (.02225) 29, 038, 000
tive impairment
if Fenox is sub-
stituted for Delta
This formula is from Volume I of the report (Exhibit 6. 12) and hypothetically assumes that an
intake of 104 mg/kg/year of Delta or 52 mg/kg/year of Fenox would result in a loss of 3. 5 percent
of next year’s population. These assumptions imply that a net reduction of 3. 5 percent would result
from an exposure of 104 mg/kg/year if Fenox is substituted for Delta.
-------
EXHIBIT 5. 12: Summary of Additional Effects of Gallinules
if Fenox is Substituted for Delta
Assume LD25 = 21.50 mg/kg/day for 30 days for Delta.
Source: Matsumura, F., tBiological Effects of Toxic Pesticidal Contaminants..., ‘ in F. Matsumura,
etal. (eds.), Environmental Toxicology of Pesticides , New York, Academic Press, 1972, p. 536.
Hypothetically assume LD 5 10. 75 mg/kg/day for 30 days for Fenox.
Number of birds killed [ (Average residue in tissue)/LDZ5] [ (1/4) (Total bird population)J
(formula from Volume I of report, Exhibit 6. 12)
Total bird population 7. 42 14 birds per acre of water, from tT Ecological Factors Affecting Waterfowl
Production, H Bureau of Sport Fisheries and Wildlife, U. S. Department of the
Interior, Washington, D.C. , p. 8 (Resource Publication Series No. 98),
Tables 5 and 10, pp. 19, 25.
Average residue 1973 . 155589
in tissue
(see Exhibit 5.9) 1978 .154745
Total bird popu- 276, 726, 788
lation (see
Exhibit 5. 4 for
water area)
Net number of 1973 501, 000
birds killed if
Fenox is sub- 1978 498, 000
stituted for Delta
Assume: Stocking by government agencies prevents significant population decline.
-------
EXHIBIT 5. 13: Cost of Maintaining Wildlife Population*
FC = Total Federal expenditures (1973) $297, 900, 000
Source: 1974 Statistical Abstract , Table 332.
Camper days + hunter days + fisher days = 112,839,000 + 203, 689, 000 + 706, 187,000 1, 022, 715, 000
recreation days
Source: 1974 Statistical Abstract , Tables 336, 337, 339, and 345.
FC $297,900,000
CRD cost per recreation day (camper days + hunter days + fisher days) 1, 022, 715,000 = $0. 29128
recreation days
U,
* Based on formula in Volume I of report, Exhibit 6. 16.
-------
an average cost per recreation day, to be calculated. The next step is
to calculate the number of wildlife obtained, or “expericnced’ during
each recreation day. These calculations are shown in Exhibit 5. 14.
Implicitly assumed in this calculation is the idea that experiencing one
wildlife is equivalent to experiencing either two birds or two fish. This
is a philosophical issue not to be resolved here and the assumption can
be debated. This exhibit also shows the average value of each animal
(either bird, fish or wildlife) experienced by each person each recrea-
tion day.
Finally, Exhibit 5. 15 shows the additional dollar value of fish and
bird damages, based on numbers of additional fish and birds lost due to
the use of Fenox rather than Delta, as shown in Exhibits 5. 10, 5. 11,
and 5. 12 above. It should be emphasized that the values shown in
Exhibit 5. 15 are severe underestimatioris, due to the lack of total costs
of restocking, and due to the lack of good estimates of total mammals,
including both small and large game, lost due to accumulation of Fenox
rather than Delta in the food chain. Volume I of this report suggested
some ways of approaching the assessment of these values, but data
limitations have thus far prevented the application of such methods.
5. 19
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EXHIBIT 5. 14: Value of WildlIfe*
1. BRK = number of birds killed per hunter day = 1.3429
Source: Chamberlain, E. B., etal., Waterfowl Status Report, 1972 , Washington, D.C., U. S.
Government Printing Office, 1972, Stock No. 241000353, Bureau of Sport Fisheries and
Wildlife, Special Scientific Report Series No. 166, Wildlife, U. S. Department of the
Interior, Table C-li, p. 143.
2. FSC = number of fish caught per fishing day = 303, 488, 443 fish stocked 4- 706, 187, 000 fisher days
0.42976
Source: Number of fish caught is approximately equal to the number stocked, see U. S. Depart-
ment of the Interior, Propagation and Distribution of Fishes from National Fish Hatch-
eries for the Fiscal Year 1973 , Fish Distribution Report No. 8, Fish and Wildlife
Service, Bureau of Sport Fisheries and Wildlife, 1974, p. 27.
Number of fishing days from 1974 Statistical Abstract , Table 345.
2,071 (1971)
1,323 (1971)
49(1971)
529 (1971) 72
Total 3, 972 Average per hunter day = 203,689, 000 = • 0000195
3,. OWK number of other wildlife killed:
Dali and Stone Sheep
Grizzly and Brown Bear
Bighorn and Desert Bighorn Sheep
Source: Brakefield, T.. tT Bighorns and Bears, “ Part 2, The American Hunter , Vol. 2, No. 8,
August, 1974, pp. 63-66; and Part 1, Vol. 2, No. 7, July, 1974, pp. 63-67.
-------
EXHIBIT 5. 14 (continued)
4. OWL wildlife stocked in 1973
Deer 738 Small game 181
Antelope 285 Turkey 733
Elk 301 Pheasants 230
Mountain sheep 19 Grouse 40
Other big game 31
Fur animals 128 Total, all types 2,686
Source: U. S. Department of the Interior, Fish and Wildlife Service, Federal Aid in Fish and
Wildlife Restoration , Washington, D. C. , Wildlife Management Institute and Sport
Fishing Institute, 1974, Table 13, p. 32.
5. Animals experienced per person day = [ (2) (BRK + FSC)J + [ (OWK + OWL)/recreation day] = 3. 54533
6. Cost/animal CRD - $0.29128 $0 08216
animals per person day 3. 54533
*Based on formula in Volume I of report, Exhibit 6. 16.
-------
EXHIBIT 5. 15: Additional Value of Fish and
Bird Damages if Fenox is
Substituted for De1ta
Number Total Value
Birds 1973 501,000 $ 41,000
1978 498,000 $ 41,000
5-yeartotal(1974-l978) 2,500,000 $ 205,000
5-year total (1974-1978)
discounted back to 1974*** $ 171, 000
Fish 1973 1,700,000 $ 2,546,000
+ 29, 286, 000
1978 1,682,000 $ 2,524,000
+ 29, 038, 000
5-year total(1974-1978)** 154,000,000 $12,664,000
5-year total (1974-1978)
discounted back to l974 $10, 564, 000
*Source: Exhibits 5. 10, 5. 11, 5. 12, and 5. 14 above.
* The years 1974 through 1977 were interpolated and thcn the years
1974 through 1978 were added together.
** Each of the five years 1974 through 1978 was discounted back to
its value in 1974 and then added together. The procedure is fully
explained in Exhibit 3. 13, with the modification that a discount rate of
10 percent is used because no inflation has been built into the present
monetary evaluation.
5.22
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ATTACHMENT 5. 1: Alternative Method to Calculate
Environmental Hazard from
Surface Runoff of Fenox or Delta
The potential hazard to the environment via surface runoff of pes-
ticides can be estimated by the following four-step procedure:
• Pesticide concentration in the soil according to
application rate and soil density,
• A soil runoff factor away from the application site,
• Sediment delivery rate of contaminated soil from
the field runoff to a waterway, and
• Calculation of the harmful effects of pesticides
entering the waterway, in terms of lost wildlife.
Let C represent the pesticide concentration in the soil in ppm.
Therefore:
C (RIMS) io
where: R the given application rate in lbs/acre,
MS = the mass of the soil which depends upon
the volume (Vg) of the contaminated soil
and the unit weight of soil (Ws).
Assuming that the depth of concentration ranges from o -ie to six Inches
and averages three inches, the volume of one acre is then:
(.25 feet) (43, 500 sq. ft/acre)
10,890 Cu. ft/acre
The mass of the soil, equal to (V 3 ) (We), can be calculated if W 5 or the
unit weight of soil is known. Ws generally varies between 85-145 pounds
per cubic foot depending upon the level of moisture and the soil type.
Therefore, one can assume that W averages 100 pounds per cubic foot.
Based on application rates for Fenox or Delta of 0. 90 lb/acre for wheat,
0.46 lb/acre for barley, and 0.20 iblacre for oats, the pesticide con-
centration in the soil is equal to:
5.23
-------
C = (R/MS) x 106
where: MS = (0. 25) (43, 560) (100) = 1.089 x io 6 lb/acre
c
or. 1.089 (10)6 lb/acre X 1.089
where: R varies from 0.20 to 0.90 lb/acre.
C for each of the three crops treated is shown in Exhibit 5. 16.
An average soil loss for cultivated land is available for seven
regions in terms of tons per acre (TA) lost and is shown in Exhibit 5. 17.
TA times the acres of wheat, oats, and barley to which Fenox or Delta
is applied gives the loss of contaminated soil for each region, in tons,
where the contaminated soil contains a concentration of Fenox or Delta
equal to C ppm.
A sediment delivery ratio which relates the soil delivered to a
waterway to the soil runoff from the crop site can then be calculated.
This relationship has been estimated as:
Log D = 1.534 - 0. 142 Log A
where: D = sediment delivery ratio,
A drainage area in hec.tares,
and is shown graphically in Exhibit 5. 18. The recommended drainage
area for use in this calculation should be no larger than Aggregated
Statistical Areas (ASAs), of which there are 99 in the continental United
States. These areas must then be aggregated by USDA regions ii order
to estimate the sediment associated with a particular use of Fenox or
Delta.
The application of a sediment delivery ratio to the soil loss calcu-
lation yields the amount of pesticide-contaminated, soil with a concen-
tration level of C ppm which is deposited in waterways. A water solu-
bility factor of Fenox or Delta can then be applied to the delivered
volume of sediment which will yield the quality of the water in terms
of Fenox or Delta content. Sophisticated models of solubility of pesti-
cides in waterways would include flow, volume, and temperature of the
waterways. Given that the phenoxy herbicides have relatively low solu-
bility levels in water -- 620 ppm for 2, 4-D at 20 C and 40 ppm for
5.24
-------
EXHIBIT 5. 16: Pesticide Concentration in Soil
Based on Pesticide Application Pate
Pesticide
Crop Treated Concentration (ppm )
Wheat (at 0. 9 lb/acre) 0.83
Barley (at 0. 46 lb/acre) 0. 42
Oats (at 0.10 lb/acre) 0.09
5.25
-------
EXHIBIT 5. l7 Average Soil Loss for Cultivated Land*
S A —,
/ CH
I
/
4.....
l 4• \. .;.tZ 7.
S.
3.1
;“
I .
/ —
r-’
\)
‘I
i ,/
/
—
If
I “I
‘I, . /
: : —. ::5T
<).O /•
1
1
15.0
:.1::. . - :, : : i : Sc L :., i..a S t l
i::c :.- , C r 9 ’ :, t e Center for A ;icu1turaI
- . .. . . ..d... I z \ ’:., I
Par A
3. 0
4 -
_ij. , — .. .
;:
2.3
7
/, .
ç71
N
0
SOUVH
/
I
20. 0
1. 5 tons/acre .
! per sq. ft.
8
/
2C. .O
-------
Drir a; Ar (ir.. r.rc )
-
- — _____
- ‘. - _ _ - .. TTL - _ - .j
— —— — —— — — ——— — — I — — — — — — I —
— _ . — — - — — ._ .L —
______ t. I I ______ I I
________ ——--——-—:
_____ —
rL T ____
—‘ — —‘
I — — —-. — .__I — — — — — -—I
I I 3
EE IJ Er T
- - - -
I I — —— —— —:
-J — —— ---- . - .--.- — -a - ;..
-I _ . — -- -— - I -
I; J ——--———————-- ————I - ——-J — . — — ——
• 1- ,‘-:— . — :
I I I
13.0 130.3
EXHIBIT 5. 18: r: .‘. z . .:’; 1T. c - .
c . ‘ i;i..:. . .. o; , 3
•J• (,,:
-------
2,4, 5-T at 30° C* -- Fenox or Delta can be considered to possess a
low solubility level in water.
The environmental effects due to pesticide runoff would then be
calculated based on the Fenox or Delta content of the water and the
tolerances of various fish in water to this exposure. Exhibit 5. 19
shows the 48-hour median tolerance limits for various herbicides.
*AID, Pesticide Manual , Part II, pp. 201, 211.
5.28
-------
EXHIBIT 5. 19
43 h Mcdian To!crancc Limits ror Hcrbicidcs*
Fih t. i.d 40 Ii TL ? iiJ . U
I - ( o. .tli.) —
bltic; iU 90 25
I:LIt:.-Ittut,( h l , tsc 55 25
2.:l,r;—11L\ fII . o I ,7i(J
l;tt’g iitt,titlt l’a,s I ,2j() 25
2 •I- I) - Il u - ll :175 21
I;, , - , -IututI I , l,a: s 350 25
bluegill 15 25
)argenlotit!i bass 10 25
4.(2,4.D! )) blu egilL 8 25
larg ’rnoutlt bass 10 25
ACI’. M-SG t ) chinook salmon 155 20
An:inotria,.ole coho salmon 325 20
Iargt:rnouih bass > 1,000 20
Baron . chinook salmon 23 20
• channel cat 6-9 19
C 56 . bluegill 30 25
• • • largemouth bass I 35 25
Chiorax • • rainbow rout 1,800 18
• channel cat 2,307 20
Clilorca rainbms- trout 1 100 I I )
CI PC • j bluegill ‘ 12 25
• largernoutli bas3 10 25
on tic hi , c i l).,v , am d } rdcsstlc 2 ; I cjr.d, Lcwi, snd rrycr 25 ; Mab Cr 30 , and
oud S,ced ’.
Tabic 10—ton!.
JJc,bicide Fish 1c !rd 111 l FL 7 n:( .. C
D quat • - . chinool: sain :on 2 0-5 20
Diuron • • coho salmon 1$ 20
Dowpon • • . ,, ,, 3) ! : 20
bro vn rottt 210 II )
EDO • . bluegill 1 )1 25
• • • lar emoutJi bass 15 25
Endothal . . . ,, ,, 2 0 1t 25
chinook salmon I 3h 25
F-98 (,\crokin) ,, ,, t, -oo ’
1-Ivaminc I 1 1. 12 coho salrimti 5.1 2 t I
Kur n . . chinook saltuno I -2. 2 ))
Monuron • colto satriton III ) . I 2) )
Nemagon bluegill 20 25
l:irgensnuth bass 2 !) 25
Omazcnc . • • citittosi: s:iltuo ’t 08:1 20
Phygon XL • • )arc emout 0 h:tss 0ti 2))
clnuimn-l t.t OIl 1 0
Shril D 50 • • rainbow trout 210 I I I
Simazitic • • • chinook aliuon ( 1- li 20
• • rainbow trout 85 Ill
Sodium TCA • chinook salmon 070 2 )1
TC . • . . clianitsI rat > 2,011!) 2’)
)I.j, y,,t ,r I,r 24). mt. I , ur, tur lU I, 5 , ,’rm. i, tic ,Ltt.t_
Source: J. I C Erichsen Jones, Fish and River Pollution, Butterworths,
London, 1964.
5.29
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ATTACHMENT 5. 2: A Method for Calculating the
Quantity of Fish in Inland
Waters by Region
The amount of fishlife in a reservoir, lake or stream an be
described in two ways, i.e., carrying capacity and standing crop.
Carrying capacity is the maximum poundage of a fish species that a
given aquatic habitat may support over a given period of time. This
concept describes the potential of the waterway to support fish life,
given the biological characteristics of the waterway.
The concept of a standing crop is intended to estimate the actual
quantity of fish, usually in pounds per acre, in a body of water at a
point in time. In other words, the standing crop estimate is a census
of fish at a given moment.
Some general points should be kept in mind while discussing both
of these concepts:
The relationship between the standing crop and the
carrying capacity of a body of water is usually
unclear.
The greater the number of species, the larger the
standing crop due to a more efficient use of avail-
able food.
• Pounds of fish per acre, not fish per acre, is the
generally accepted index in order to correct for
seasonal variations, e. g., the large number of
fish hatched annually which do not survive for a
long period of time.
• Carrying capacity is dependent more upon surface
area than depth or volume of water.
Exhibit 5.20 shows standing crop in pounds per acre for various
species of fish. This exhibit was constructed to show the relative effi-
ciency of the species listed with the realization that these fish gene r-
ally are seen in combination with other species.
5.30
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EXHIBIT 5. 20
Standing Croi in Pounds Per A r
2 4 6 O 20 4P60 C0 200 4C0 moo 2000
Trout ____________
Wa leye
Ro•k
I Ir A
\ hRl / LJII]
: i
Ch. (‘ati h
Pum ih II ((I
/
!.‘‘ •lii* :‘:-. .• .. .
.... . ... . .‘..
) I
1 Iu ,,iH —
ii TJ
I’LIIlIk . r tTTI
( tp Ti2 J J__
lull ti’ ( .‘ —
- _ J
1CO 1000
!ean fur L;tkt anti
Source: Bennett, George W., Management of Lakes and Ponds ,
Znd edition, Van Nostrand Reinhold, New York, 1971.
5.31
-------
The average of the mean pounds per acre for the 19 species is
approximately 36. This could be easily modified for each region by
weighting the mean pound per acre for each species according to the
relative popularity of each species. Also, additional species could be
included if that type is popular in any one region. This standing crop
data can then be applied to the water surface area for each region so
that a regional volume of fish, in pounds, can be constructed. Both
regional inland water surface area and regional standing crop data are
shown in Exhibit 5.21.
Unfortunately, this method overstates the quantity of fish due to
the use of total regional water area and because it is unlikely that all
the regional bodies of water contain fishlife. However, no inventory of
bodies of water containing fish could be found. An alternative method
would be to aggregate reservoirs, lakes, and rivers and assume that
all fishlife is contained in these three types of water. This is difficult,
however, because the standing crop are in terms of area, while reser-
voirs are generally stated in volume and rivers are described by length.
5. 32
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EXHIBIT 5.21: Regional Water Area and Standing Crop
Region
Northeast
Appalachia
Southeast
Comb cit
Lake States
Delta States
Northern Plains
Southern Plains
Mount a in
Pacific
Total
Inland
Water Area
(1, 000 acres)
3, 509
4, 222.
4, 482
1, 365
5, 035
3, 310
2, 371
4, 058
5, 017
3, 040
36, 409
Standing Crop
(1, 000 ibs)
126, 32.4
151, 994
161, 352
49, 140
181, 260
119, 160
85, 356
146, 088
180,612.
109, 440
1, 310, 724
Ca1cu1ation from 1974 Statistical Abstract , p. 72.
* Ca1culated as follows: Standing crop (36 lbs. of fish per acre)
(water area in acres).
5. 33
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APPENDIX A
AGRICULTURAL ANALYSIS OF THE USE OF
PESTICIDE ALTERNATIVES TO DDT ON
SWEET POTATOES, SWEET CORN AND
PEANUTS IN 1973 AND 1974
A.1
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1.0 FORM OF ANALYSIS AND
OVERALL CONG LUSIONS
1. 1 Background and Agricultural Context
The purpose of this report is to describe certain impacts which
the cancellation of the registration for Dichioro Diphenyl Trichioro-
ethane (DDT) has had on the production of certain selected crops. The
three crops selected in this analysis, sweet corn, peanuts, and sweet
potatoes are three in a series which are part of a general retrospective
study conducted by EPA-OPP on the impacts of the 1972 cancellation
decision. The general method used in this analysis was to apply com-
ponents of a general benefit-cost system for chemical pesticide use.
The system has been developed in general form into a set of compon-
ents or submodels which may be selected and applied as needed for any
regulatory decision of interest.
The selection of sweet corn, peanuts, and sweet potatoes fo: this
particular effort in the context of a larger review dictated that certain
conditions must be considered in the agricultural context of the study:
• The use of DDT on the three crops in both volume
and extent,
The pests involved,
• The alternative pesticides selected after cancella-
tion, and
• The costs of the alternative pesticides.
In addition to the above considerations, the analysis of the use of DDT
on sweet potatoes was defined to be the use of DDT on stored sweet
potatoes, not sweet potatoes in the field. This particular consideration
actually separated the analysis of sweet potatoes from the analysis of
the other two crops, making it a different study, but the results are
combined into a single discussion in this report.
The overall structure of the report conforms to the components
of the general benefit-cost system that were used to analyze the pro-
duction impacts of the cancellation. These components, which were
A.2
-------
stiected from the more comprehensive “food, feed, and fiber” sub-
model of the general system, provided the following analyses:
• Prices paid by farmers for pesticides,
• Amounts of pesticides applied, and
• Acres of crops treated by pesticides.
In addition, reviews of the three crop situations with respect to changes
in yields and changes in commodity prices were conducted. These
reviews indicated that application of model components designed to ana-
lyze yield and price treands would not be suitable for these crops, due
to extensive grouping of crop data in standard data sources and lack of
data for small geographic units (see Chapter 5. 0 below).
The agricultural context of the three crops includes a general
decline in the domestic production of DOT since its peak in 1963 of
187, 782, 000 pounds. However, data on exports indicate that production
may be increasing. Exports climbed from 35, 424, 000 pounds in 1972
to 73, 712, 000 pounds in 1973. Production data for these two years were
not published in order to avoid individual firm disclosures. In any
case, for the last two years published, 1969 and 1970, DDT declined
from a production level of 123, 103, 000 pounds to 59, 316 pounds. The
exact structure of this decline, and of the possible recovery, are not
important because the registration of DDT was cancelled by EPA in
1972. The question which arises is whether this loss of DDT would
have resulted in the reduction of yields, and possible losses of income,
dependent on the price elasticity of demand, if farmers were not able
to find substitute pest control measures.
It is possible to estimate the effect of non-availability by assess-
ing the value of the crop produced in the post-cancellation period, and
by evaluating the cost and effectiveness of selected alternatives. To
make such an estimation requires data from many sources and the
integration of this data in order to achieve a concise, condensed pic-
ture of the effects. Results of this type tend to be highly simplified
and must be interpreted with considerable care and reservation. A
diagram illustrates how different figures were introduced and applied
in the benefit-cost analysis (Exhibit 1. 1). This diagram shows that
*Observation provided by the Criteria and Evaluation Division, Office
of Pesticide Programs, EPA.
S. Department of Agriculture, Agricultural Statistics, 1974 ,
Washington, 0. C., U.S. Government Printing Office, 1974, Table
664and Table 665, p. 473.
A. 3
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EXHIBIT 11:
Types of Data Used in Agricultural
Analysis of Insecticide Benefits
and Costs
A.4
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many data components are required to obtain a final calculation of net
gains and losses, but that in the application of the calculation proce-
dures, some data components, such as yield changes, may be so small
that they have no impact on the final calculation of “net” gains and
losses.
1.2 Conceptual Problems and Assumptions
Conceptually, the period of years during which the effectiveness
of two pesticides is comparatively analyzed should be the same period
for each of the two pesticides only if they were introduced and used in
an identical manner. Therefore, two pesticides which were introduced
and registered in different years should not be analyzed during a com-
mon two-year or five-year interval. The reason for this difficulty is
biological. Soon after its first season in use, the pest population,
especially if they are insects, begins building an immunity to the pesti-
cide, and the effectiveness declines as this immunity increases. The
overall impact of this trend appears both in the production of crops and
in the relative market positions of the two pesticides.
Specifically, the production of crops on which the older pesticide
is used will decline, and crop yields on which the newer pesticide is
used will increase for a few seasons, and then decline. This relative
effectiveness will be reflected directly in the proportion of the total
pesticide market which each one captures. If one pesticide disappears
from the marketplace, other pesticides will compete for the acres to
which it had previously been applied. But when farmers adopt these
competing pesticides, they will not obtain an easily predictable yield.
They will probably not obtain the yield that they would have obtained if
the previous pesticide had not disappeared from view, nor will they
obtain the yield which they would have obtained if they had been using
the selected alternative pesticide for the same number of growing
seasons as the number during which they had applied the now unavail-
able pesticide.
The above discussion implies that whenever the EPA cancels the
registration of a pesticide, yields of the crops on which that pesticide
had been used will increase, if a substitute pesticide is selected and
applied, because there will be no residual immunity within the pest
population to the newly substituted pesticide. Admittedly, if the newly
substituted pesticide is vastly less effective than the cancelled pesticide,
A. S
-------
the yields obtained could be less than during the last few seasons of the
previous pesticide, even though the residual immunity would have been
reducing its effectiveness. But given the large number of pesticides
presently registered, and the degree of overlap in registrations, it is
reasonable to assert that some alternative pesticide will be available
which has approximately the same basic effectiveness as the cancelled
pesticide.
More realistically, the users of agricultural pesticides will
respond to a registration cancellation in a more sophisticated and
experimental fashion than the immediate adoption of the “next most
equivalent” pesticide. The farmer’s response would probably include
a careful balancing of at least three variables:
• The cost of using the substitute pesticide, including
the cost of the materials,
• The cost of substituting additional acres for use of
a pesticide, and
The price at which the commodity is likely to sell
during the year.
If the farmer’s situation indicates that he should keep his crop acres
approximately constant, and that he should select a substitute pesticide
for the one no longer available, and if the substitute selected is avail-
able at a cost which is a reasonable percentage of his production costs
(e.g., 4 to 5 percent), then the farmer will probably treat the same
acres that he had treated before.
In summary, the above discussion has shown some of the diffi-
culties in predicting the reactions of the agricultural community in the
event of the cancellation of a pesticide by the EPA. The reactions of
various types of farmers could have been observed after the cancella-
tion of DDT in 1972, but no comprehensive case study has appeared.
In the absence of such a study, the simplest assumption is that farmers
will select some alternative pesticide and continue to treat approxi-
mately the same acreage which they had previously treated.
In addition to the problem of whether, in reality, the farmer
treats the same number of acres when he changes pesticides is the
problem of whether he treats the same number of acres from year to
year when he is using a single pesticide. The reason that such shifts
A.6
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in acreage might occur is that commodity prices might stimulate the
farmer to reduce production costs and climatic factors might reduce
the level of pest infestation, thus requiring less pesticide. If, however)
a short period of a few seasons is analyzed, it is possible to assume
that the infestation levels and other conditions remain constant, and
therefore, the treatment “policy” of the farmer will remain constant,
meaning that he will treat the same numberof acres with the same
amounts of pesticides each season.
1.3 Interviews with Extension Agents
In order to further structure the benefit-cost analysis, it was
necessary to determine what substitutions of pesticides had actually
occurred after the cancellation of the registration of DDT, and what
the cost implications of these substitutions were. As noted above, no
comprehensive narrative or analysis of choices and trends since the
1972 cancellation has appeared, and a large-scale study of this type
was outside the time frame of the present project. Therefore, a small-
scale survey was conducted of extension personnel at six agricultural
universities in states which ire prominent in production of the three
study crops.
1. 3. 1 Sweet Corn
Data on total weight produced are provided by Agricultural Statis-
tics.* These production figures are divided into corn for market and
corn for processing (Exhibit 1.2). The leading production state for
fresh market corn is Florida and the leading producing state for sweet
corn to be processed is Minnesota. A third state, Oregon, was added
to the survey because, in terms of total production, the Pacific region
is second only to the Lake States region, and Oregon is the largest pro-
ducer of corn to be processed in the Pacific region.
The states selected thus did not include a representative state
from the Corn Belt region. It should be noted that the largest produc-
tion of corn to be processed in this region occurs in Illinois, but the
*Agricultural Statistics, 1974 . ibid., Table 242, p. 172.
A. 7
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EXHIBIT 1.2: Production of Sweet Corn by Regions, 1973
Production
Fresh by Use
Market Processing Total
Region ( 1000 cwt) ( tons) Pounds
Northeast 3,477 78,350 504,400,000
Appalachian 555
Southeast 5,042 504,200,000
Delta
CornBe lt 1,374 271,100 679,600,000
LakeStates 761 1,065,400 2,206,900,000
Northern Plains
Southern Plains 160 16, 000, 000
Mountain 217 141,500 304,700,000
Pacific 1,357 517,650 1,171,000,000
Leading states: Fresh Market: Florida, 437, 500, 000 pounds;
Processing: Minnesota, 1,109,800,000 pounds.
Source: Agricultural Statistics, 1974 , ibid., Table 242, p. 172.
A. 8
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amount is still less than one-half of the tons produced in Minnesota.
The largest producing state in the Corn Belt for fresh market sweet
corn is Ohio, where production is about one-fourth the amount produced
in Florida.
1.3.2 Peanuts
The two major peanut producting regions are the Southeast region
and the Southern Plains region.* Withinthese regions, Georgia and
Texas are the most productive states, although South Carolina peanuts
bring a higher price per pound than Georgia peanuts, and Oklahoma
peanuts are produced at a higher yield per acre than are Texas peanuts.
Three states, Mississippi, South Carolina, and Alabama, have shown
production fluctuations in the past few years, including a drop from
1971 to 1972 and a recovery from 1972 to 1973. Alabama is second
only to Georgia in production, and therefore was selected for the sur-
vey. Texas was selected as representative of the Oklahoma-Texas-
New Mexico group.
1.3.3 Sweet Potatoes
North Carolina and Louisiana are well known as the two leading
states in sweet potato production. ** The present study, as noted above,
has been defined to analyze the problem of damages caused during the
time the sweet potatoes are stored after harvest but before shipment,
during which period the sweet potato weevil is the principal pest. These
weevils also attack in the fields, but careful control during initial plant-
ing helps to reduce this problem.
North Carolina has not been bothered by the weevil either in the
field or in storage situations. Occasional infestations in the southeast-
ern part of the state have been controlled by quarantines. Therefore,
the second largest producing state, Louisiana, was selected for the
survey. Generally speaking, only sweet potatoes intended for future
market sales are stored, since fluctuations in demand over the year enable
a significantly greater return if supplies are available for market when
demand peaks. The storage may last as long as six months, although
*Agricultural Statistics, 1974 , ibid., Table 175, p. 126.
**Agricultural Statistics, 1974, ibid . , Table 269, p. 191.
A.9
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shipment after three months is more common. Any stored sweet
potatoes which have suffered weevil damage during storage are consid-
ered totally unsuitable for market.
1.4 Survey Procedures
Once the states were selected, reference was made to the USDA
extension agent list* to obtain the pesticide specialist at the agricul-
tural university in the selected state. This list gives names and tele-
phone numbers, and these numbers were used to contact the selected
agents by phone. An open, unstructured interview was conducted,
during which the subject of alternatives to DDT and the prices paid for
these alternatives were discussed. Although various substitutes used
since the cancellation of the registration for DDT were mentioned, two
in particular were frequently mentioned first: Carbaryl (Sevin) * for
peanuts, and Lannate for peanuts. Methomyl (Imidan) was mentioned
for use against sweet potato weevils in Louisiana. Various crop-pest
combinations were mentioned, but a more precise picture of which
insecticides were used against which insects is available from EPA
sources*** such as the registration information (Exhibit 1. 3).
Although it is difficult to obtain data on the number of acres of
specific crops which were treated by a given insecticide for a specific
insect, it is, in fact, possible to develop estimates of the number of
acres of crops treated by a given insecticide, the amounts applied, and
the cost to the farmer of these applications. Detailed procedures for
developing these estimates are described in the next three sections of
this report. Using these p ocedures anc the resulting estimates, it was
possible to construct a table showing the probable net costs incurred by
farmers in substituting other insecticides for DDT (Exhibit 1.4).
*U. S. Department of Agriculture, Extension Service, ttLjst of
Extension Specialists at Agricultural Universities,” Washington, D. C.,
1974.
**Ca rba ryl: 1- naphthy l methylca rbamate or 1 -naphthyl N -methyl-
carbarnate; Lannate: S-methyl N - [ (methylcarbamoyl) oxy] thioacetim-
idate; and imidan: N -(Mercaptomethyl) Phtalimide S-(O, 0-Dirnethyl
Phosphorodithioate).
***Environmental Protection Agency, Compendium of Registered
Pesticides , Vol. III, Washington, D. C., 1973.
A. 10
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EXHIBIT 1. 3: Insecticides Substituted
for DDT in 1973-1974
Insect For Which Insecticide Substituted
crop DDT Was Used* After Cance11ation* -
Peanuts White fringe beetle
Cutworm Carbaryl
Sweet corn Cutworm Carbaryl
A rmyworm Lannate Ca rba ryl
European corn borer Lannate Carbaryl
Corn earworm Lannate Carbaryl
Sweet potatoes Sweet potato weevil [ midan
in storage
*List provided by EPA, Criteria and Evaluation Division.
**Based on EPA Compendium and interviews with extension agents.
***No substitute identified for this insect.
A.11
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EXHIBIT 1.4: National Net Costs for 1973 and 1974
Combined of Applying Substitute Insecticides
Instead of DDT (Current dollars, based on
prices shown in Exhibit Z. 1 below)
Sweet
Potatoes
Insecticide Peanuts ( in storage) Market Corn
Carbaryl -$136,470 Notused -$20,163
(Savings) (Savings)
Lannate Not used Not used $590, 983
Imidan Not used $65 Not used
*Exclusive of application costs.
A. 12
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The figures in Exhibit 1. 4 show that the substitution of carbaryl for
DDT will save over a hundred thousand dollars for peanuts. For sweet
potatoes the substitution of Imidan for DDT will have minimal economic
impact. For market corn, the substitution of carbaryl for DPT will
save over twenty thousand dollars, while the substitution of Lannate for
DDT will cost over five hundred and ninety thousand dollars. The details
of these results are presented in the following sections of this report.
A. 13
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2.0 PRiCES PAID BY FARMERS
FOR PESTICIDES
Estimates of the prices of pesticides used are important to the
benefit-cost analysis because these prices vary from a few cents to
several dollars per pound of active ingredient. The benefit-cost anal-
ysis should adequately identify all of the producers’ costs associated
with the substitution of an alternative for DDT. These costs occur in
many forms: materials, labor, equipment, organization, and others.
They arise basically in only three ways:
• If the new pesticide costs more,
• if it must be applied by a different method than
the previous pesticide, or
• If a greater quantity must be applied to obtain
the same results.
These costs will not change if the new pesticide has about the same
price, is applied by the same methods, and is applied in the same
amounts.
In the current pesticide market, prices have escalated because
of intermediate shortages. Any tabulation of these prices based on
earlier prices could have a serious downward bias. Therefore, data
provided by EPA were used in the ‘l974 column of Exhibit 2. 1.
Prices shown in Exhibit 2. 1 are expected to diverge on a regional
basis, except for those obtained from extension agent interviews, which
are probably regional-specific. The 1974 value for DDT was calculated
by averaging the three percentage price increases from 1973 to 1974
for the three other insecticides, and applying this percent (59. 3) to the
1973 national value for DDT. *
*U. S. Department of Agriculture, Crop Reporting Board, Sta-
tistical Reporting Service, Agricultural Prices: Annual Price Sum-
mary, 1973 , Washington, D.C., June, 1974 (PR 1-3, 74), p. 159.
A. 14
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EXHIBIT 2. 1: Pesticide Prices Paid by Farmers
(Dollars per pound of active ingredient)
Percent
Pesticide 1973 1974 Change
Carbaryl, 80 percent 1. 0l * 1 7( **** + 743
wettable powder*
Lannate c* 4. 00** 10. 50**** +162.5
Irnidan ’ 8. 00 * 3. 28 ** — 59. 0
DDT, 50 percent 0. 412** 0. 656 + 59. 3*****
wettable powder
Prices are assumed to be for the mixture indicated and not for
the active ingredient itself.
**Agricultural Prices: Annual Price Summary, 1973 , ibid.,
p. 159.
***Extension Agent Survey, described in Chapter 1.0. Forms of
pesticides were not determined by this survey.
**** Data provided by EPA, Criteria and Evaluation Division.
** *-*Average of percent values for the three other pesticides.
A. 15
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It is possible that the price given for DDT is lower than it would
have been if the registration had not been cancelled. Looking back to
1968, however, the United States average price paid by farmers per
pound of active ingredient was $0. 373, or 3. 9 cents less than in 1973. *
In other words, the increase in DDT prices since 1968 has been 10.46
percent for the five-year period. In the light of this trend, the 59 per-
cent increase from 1973 to 1974 is probably the largest reasonable
increase to be expected, even with intermediate pesticide shortages.
*Agricultural Prices: Annual Price Summary, 1973 , . cit.,
A. 16
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3.0 AMOUNTS OF PESTICIDES APPLIED
The total amounts of pesticides applied on a given crop depend on
the rate per acre, the number of applications, and the number of acres
treated. The rate per acre, in turn, depends on the recommendations
of EPA and USDA, local extension agents, and the farmer’s assess-
ment of the probable infestation. The benefit-cost system concentrates
on the EPA Compendium* amounts, although the USDA recommenda-
tions can be obtained from appropriate agency publications. ** The
results of such a review are shown in Exhibit 3. 1.
Because of the possible development of immunity by specific
insects, it is necessary to consider whether the rate of application per
acre would increase over a period of years. Data from the two volumes
of the Suggested Guide.. . imply that USDA continues to recommend a
constant rate per acre in successive years. Therefore, the assump-
tion for the analysis is that the rate of an insecticide application will
remain constant for at least three years and probably as long as five.
Since the present study is limited to a two-year period, no allowance
for the development of immunity has been incorporated into the analy-
sis. An approach to making such an allowance is described in a model
developed by Hueth and Regev, ** and could be incorporated into a
long-run analysis.
The rates given in the EPA Compendium (Exhibit 3. 1) are the
maximum registered rates for all types of applications. The Compen-
dium , however, is sometimes unclear on the number of applications
per season which are permitted at the given rate. In fact, the results
of interviews with the extension agents showed that successive applica-
tions were sometimes needed. Some concrete distinctions between
DDT and the substitutes emerged from these interviews in terms of
numbers of applications required.
*Com endium of Registered Pesticides , . cit., 1972 and later
revisions.
**TJ. S. Department of Agriculture, Suggested Guide for the Use
of Insecticides to Control Insects Affecting Cro 2 s, Livestock, House-
holds, Stored Products, Forests, and Forest Products , Washington,
D.C., 1967 (Agricultural Research Service and Forest Service, Agri-
cultural 1-lancibook Series No. 331).
***Hueth, D., and U. Regev, “Optimal Agricultural Pest Manage-
ment with Increasing Pest Resistance, “ American Journal of Agricul-
tural Economics , Vol. 56, No. 3, August, 1974, pp. 543-552.
A. 17
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EXHIBIT 3. 1: InsecticIde Application Rates Per Acre
(Data are pounds of active ingredient per acre or pounds
of active, ingredient applied to a 50-pound crate of sweet
potatoes in storage)
-—
Insecti
cides
DDT (Before
.
Crop
Insects
cancellation)
- Carbaryl
Lannate
Imidan
Sweet Corn
Cutworm
Not recommended
2
Not registered
Not registered
Armyworm
Eu ropean
corn borer
Corn earworm
by USDA
2*
2*
2*
2
2
2
0.45
0.45
0.45
Not registered
Not registered
Not registered
Peanuts
White fringe
beetle
Cutworm
3*
Not recommended
Not registered
1
Not registered
Not registered
Not registered
Not registered
by USDA
Sweet Potatoes
Weevil
0. 00063 per
Not registered
Not registered
0. 2 ounces
in Storage
50 pound s**
per 50 pounds
*USDA recommendation ( Suggested Guide for the Use of Insecticides... , . cit.)
**Obtairied from extension agent survey.
-------
For example, a total of three applications of Carbaryl for cut-
worms on peanuts was recommended by extension agents, making the
total application three pounds per acre instead of one. Similarly, suc-
cessive applications of Lannate on sweet corn were recommended, and
some individual applications for multiple pests were probably also
reported, boosting the total seasonal application to 6. 25 pounds per
acre. Finally, the amount of Carbaryl reported used on sweet corn
was less than the EPA Compendium rate, i.e., only 1. 66 pounds. In
summary, the rates obtained in the telephone survey were:
Carbaryl: Sweet corn, 1.66 lbs/acre/season,
Lannate: Sweet corn, 6.25 lbs/acre/season,
Carbaryl: Peanuts, 3.0 lbs/acre/season,
Imidan: Sweet potatoes in storage, 0. 0063 lbs/crate.
A further question in the survey enabled the determination of the rate
of application of DDT to stored sweet potatoes used before 1972: about
one ounce per hundred crates (5, 000 pounds) or 0. 00063 pounds per 50-
pound crate. The rate of Imidan application was reported to be ten
times that of DDT.
A. 19
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4.0 ACRES OF CROPS TREATED
BY PESTICIDES
The number of acres a farmer treats with an insecticide is diffi-
cult to calculate. The recommended rate of pesticide per acre is rela-
tively fixed by label requirements and by the advice of extension agents,
but the number of acres treated varies with the observations of infesta-
tion by the farmer and with his hopes and expectations of a good yield.
In order to assess the benefits likely to be obtained from the use
of any pesticide, and the amount of such a pesticide which is likely to
be discharged into the environment, the benefit-cost system requires
a procedure for calculating and forecasting the amount of a specific
pesticide which will be applied to a specific crop in a given region or
state. The total amount of pesticide applied can be calculated by know-
ng the rate per acre of application and the number of acres of the spe-
cific crop to be treated. In order to make these latter calculations,
two important data sources must be used: the Census of Agriculture ,
published by the U. S. Bureau of the Census, and the surveys taken by
USDA on farmers’ use of pesticides. Although these sources do not
always agree in totals, proportions from one source can be transferred
to another.
More specifically, the proportion of acres of a given crop treated
with a pesticide can be calculated from the USDA survey data. These
proportions can be applied to the acreage totals from the Census of
Agriculture to give total acres treated with general categories of pesti-
cides for each region (Exhibit 4. 1). The Census of Agriculture for the
year 1969 was used in the case study for DDT, and successive censuses
can be incorporated into the benefit-cost system. Since census data
are not presented in crop-specific detail, it is desirable to have pro-
portional allocating factors for distributing the total acres treated with
insecticides to crop-specific insecticide combinations.
Proportional factors for crop categories are available from the
acreage data provided by the USDA survey, * and these acreage data
convert to the crop category proportions shown in Exhibit 4. 2.
*Andrilenas, P. A., etal., Farmers’ Use of Pesticides in 1971:
Quantities , USDA, ERS. Agricultural Economic Report 252, Washing-
ton, D.C., 1974; and Eichers, T. A., Quantities of Pesticides Used by
Farmers in 1966 , Agricultural Economic Report 179, 1970.
A. 20
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EXHIBIT 4. 1: Acre s Treated with Insecticides for Different Regions, 1969
EEEE
Acres treated (or
insects
North-
east
Lake
States
Corn
Belt
Northern
Plain.
Appa-
lachian -
South-
east —
Delta
Southern
Plains
Mountain
P*cific
United
States
Total -
1,399,436
2,451,513
12; 165, 063
4,727,749
1,793,865
3, 585, 356
4, 168, 679
5,093,610
2,448.404
4, 176, 185
42, 009. 920
Acre. treated (or
cernatode .
19,70
49,490
155,092
88,877
253,732
172,453
58,477
103,251
71,244
278,754
1,251,077
Total
1,419, 143
2,501, 063
11,320, 155
4,816, 626
2,047, 597
3,757,809
4,227, 156
5, 196, 861
2,519.648
4,454,939
43, 260, 997
Source: Fowler, D. 1.., and 3. N. Mahan, The Pesticide Review, 1972 , USDA, Agricultural Stabilisatlon
and Conservation Service, Washington, D.C. 20250, 1973, p. 35 (OrIginal source of data: 1969
Census of Agriculture) .
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N
N
EXHIBIT 4.2 Calculation of Crop-Specific Insecticide
Treated Acres in the United States, 1966 and 1971*
CroD (j (acres in thousands
Pe
1966
anuts
1971
Veg
1966
etables
1971
Field Crops
1966 1971
Acres of crop j which were treated
1,412
2,042
3,242
3,258
1,013
2, 065
by all insecticides
Total acres of all crops treated by
67, 210
89, 248
67, 210
89, 248
67, 210
89, 248
all insecticides
Proportion of acres of crop j to tota
0. 02101
0. 02288
0. 02484
0. 03651
0. 01507
0. 02314
acres of all crops treated by all in-
s ecticides
Average proportion FC of two years
of data
0.
02195
0.
03067
0.01910
*FC proportion of the total number of acres in the United States, to which insecticides have been applied
‘for crop j during a given year.
Source: Eichers, T., . cit., 1970, pp. 53-55; and Andrilenas, P. A. . cit., 1974, pp. 48-50.
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One of the crop categories contained in the USDA survey analysis
is “peanuts” so that, for the DDT case study, acreage data can be
obtained directly by applying the proportion factors for that category to
the Census of Agriculture acres. For the other two crops required in
the DDT case study, market sweet corn and sweet potatoes, further
calculations are required in order to allocate the acres given in the
categories “vegetables” and Itfield crops” among these specific crops. *
The only data available to make this allocation was from the annual
issues of the Agricultural Statistics, 1974 (op. cit., pp. 153, 171, 191).
The 1974 issue gives acreage harvested in 1969 for most of the specific
vegetable crops contained in the USDA insecticide survey of 1971.
Therefore, it is possible to total the acres harvested for the vegetable
and field crop groups, and then calculate the proportion of acres har-
vested for market sweet corn and sweet potatoes (Exhibit 4. 3). The
acres treated for the ten USDA agricultural regions are shown in
Exhibit 4. 4.
Thus far, as shown in Exhibit 4.4, the numbers of acres treated
by all insecticides have been calculated for ten agricultural regions and
three specific crops. The next requirement is that the number of acres
treated by DDT for each region be obtained. Although crop-specific
data for each insecticide are not given in the USDA surveys, the pro-
portions of acres treated in a specific region by each specific insecti-
cide can be calculated, and applied to acreage data for each specific
crop. These proportions and the resulting acreages are shown in
Exhibit 4.5.
The data shown in Exhibit 4. 5 were rounded to the nearest
hundred acres and because of the successive proportional allocations,
they probably represent somewhat smaller acreages than were actually
treated by DDT in 1969. Thus, it is surprising to see that less than 50
acres of sweet potatoes were treated by DDT in 1969 in the Appalachian
region, one of the largest sweet potato producing regions. Neverthe-
less, the proportion of field crops which constitute sweet potatoes is
relatively small and the 1971 survey showed only 49, 000 acres of all
field crops nationwide were treated by DDT.**
*See list of crops, p. 22 of P. A. Andrilenas, etal., . cit.
**Andrilenas, P. A., et al., . cit., Table 14, p. 49.
A. 23
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EXHIBIT 4.3: Data for Allocating Acres Treated
from Crop Categories to Specific
Crops for the United States, 1969
Acres Harvested (in thousands)
A
Field
Crops
B
Vege-
tables
C
Sweet
Potatoes
D
Market
Corn
C/A 5
D/B 5
6,6931
3,3332
l36.9
637.8
0.02045
—
0.19136
‘Figure compiled using crops named in list given by: P. A.
Andrilenas, etal., . cit., 1974, Appendix 1, pp. 22-23; and data
from Agricultural Statistics, 1971 . However, data not available for
buckwheat, castor beans, ‘entils, millet, mung beans, sesame, spelt,
sunflowers, velvet beans, and cowpeas, so that total includes acres
for grass and hayseed, peppermint, spearmint, hops, rutabagas, dry
beans, dry field peas, flax, popcorn, broomcorn, sugar cane, and
sweet potatoes only.
2 Agricultural Statistics, 1974 , Table 215, p. 153.
3 Agricultural Statistics, 1974 , Table 269, p. 191.
4 Agricultural Statistics, 1974 , Table 241, p. 171.
5 These ratios are the proportion of “vegetables” which are sweet
potatoes and market corn. The data are acres harvested but must be
used to derive acres treated from acreage data not available in disaggre-
gate form.
A. 24
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EXHIBIT 4. 4 Allocation of Acres Treated by all Insecticides
in the United States, 1969 (Acres in hundreds)
M_
North-
east
I
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
South-
em
Plains
Moun-
tairi
Pacific
United
States
Total
Peanuts 623
Field crops 271
vegetables 435
Sweet potatoes 6
Market corn 83
1,098
477
767
10
147
4,968
2,162
3,472
44
664
2,114
920
1,477
19
283
899
391
628
8
120
1,649
718
1,153
15
221
1,855
807
1,297
17
248
2,281
993
1,594
20
305
1,106
481
773
10
148
1,955
851
1,366
17
261
18,987
8,263
13,268
169
2,539
N
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EXHIBIT 4. 5: Specific Crop Acres Treated with DDT for Different Regions
(Based on 1969 data and 1971 survey factors)
Regions (Data in hundred of acre s
North-
east —
Lake
States
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
em
Plains
Moun-
tam
Pacific
States
Total
Proportion*
Peanuts
Sweet potatoes
Market corn
.00815
5
- -
1
.00124
1
- -
--
.00043
2
- -
--
--
--
- -
--
.04108
37
-
5
.09527
157
i
21
.12729
236
2
32
.03499
80
1
10
.01095
12
- -
2
.00551
11
1
*These proportions obtained from P. A. Andrilenas, etal., p. cit., 1974, Table 15, Appendix II, p. 51.
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The above discussion describes how the benefit—cost system
approaches the calculation of acres of a specific crop, for each state,
which are treated by a specific insecticide, but the calculations
described are only for one year, the year in which the Census of Agri-
culture was taken (1969). The benefit-cost system requires the capa-
bility of selecting any year or period of years, since the registration
period for pesticides is five years. This capability must include the
option of selecting five years in the future, for proposed new pesticides,
as well as five years in the past, for the comparison analysis of sim-
ilar pesticides.
A simplified procedure for updating the 1967 survey acreage to
1973 and 1974 was devised using the preliminary USDA 1985 forecasts. *
The crop category forecast factors were calculated after interpolating
the acreage amounts between 1969 and 1975, as shown in Exhibit 4. 6,
and the results of applying these forecast factors to acreage-treated
data are shown in Exhibit 4. 7.
*Smith, Allen, et al., Projections of the U. S. Farm Subsector
and Policy Implications , USDA, FRS, National Economic Analysis
Division, Washington, D.C., 1974, p. 31.
A. 27
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EXHIBIT 4. 6: Forecast Factors for Acres Treated
by DDT in the United States
As sumption: Fore cast of acres
by DDT.
Thousands of Acres
1 Agricultural Statistics, 1974 , Table 174, p. 125.
2 Smith, A., etal., 22• cit., 1973, Table 12, p. 31.
3 Agricultural Statistics, 1974 , Table 269, p. 191.
4 Agricultural Statistics, 1974 , Table 215, p. 153.
5 All 1974 figures interpolated between 1973 and 1985.
harvested will forecast acres treated
- Peanuts
Sweet Potatoes
Vegetables
1969
1,4561
136.9
3 ,3334
1970-1972
1,4692
119.02
3,5802
1973
Ratio 1973/1969
1 ,496k
1.02747
113.0
0.82542
3,338
1.00150
J9745
Ratio 1974/1969
1,518
1.04258
112.0
0.81812
3,364
1.00930
1985
1,7572
95.02
3,6482
A. 28
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EXHIBIT 4. 7: Acre s Treated by DDT for Different Crop
for Different Regions, 1973-1974 (acres in hundreds)
I
North-
east
Lake
State
Corn
Belt
North-
em
Plains
Appa-
lachian
South-
east
Delta
em
Plains
Moun-
tam
Pa cific
States
Total
1973
Peanuts
5
1
2
—-
38
161
243
82
12
11
555
Sweet potatoes
--
- -
- -
- -
- -
1
2
1
- -
- -
4
Market corn
1
--
--
--
5
21
32
10
2
1
1974
Peanuts
5
1
2
--
39
164
246
83
13
12
565
Sweet potatoes
- -
- -
- -
- -
- -
1
2
1
- -
- -
4
72
Market corn
1
--
- -
- -
5
21
32
10
2
1
Two-year totals -- peanuts: 1, 120; sweet potatoes: 8; market corn: 144.
N
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5.0 TOTAL AMOUNTS OF
INSECTICIDE APPLIED
The results of the preceding discussion were the total number of
acres of each of three crops which would have been treated by DDT in
1973 and 1974 if the registration of that insecticide had not been can-
celled. The final step in calculating the total amount of insecticide
applied is to multiply the rate per acre for peanuts and sweet corn by
the number of acres treated (Exhibit 5. 1).
Sweet potatoes present a different situation since the number of
acres treated is not directly tied to the number of pounds in storage.
The amount of sweet potatoes in storage in 1974 was provided by the
EPA, Criteria and Evaluation Division and, since production varied
only 0. 6 percent from 1972 to 1973, it is plausible to assume that pro-
duction totals will not vary enough to change the resulting storage quan-
tity. The amount determined by the Criteria and Evaluation Division
was 47, 600 pounds, or 952 fifty-pound crates. The final cost calcula-
tion requires multiplying the total pounds applied by the cost per pound
determined in Chapter 2. 0 above. The results of these calculations
are shown in Exhibit 5.2.
A. 30
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Peanuts
1973 1974
Sweet Potatoes
1973 in Storage <* 1974
Market Corn
1973 1974
rate 3.0 lbs/acre*
totalibs 166,500 169,500
Not registered
1.66 lbs/acre*
11,952 11,952
rate Not registered
for crop
total lbs ——
Not registered
for crop
6.25 lbs/ac re*
45, 000 45, 000
rate Not registered
for crop
total lbs
0. 0063 lbs/crate*
6 6
Not registered
for crop
rate 6. 00 lbs/acre
(assume 2 applications)
total lbs 333, 000 339, 000
0. 00063 lbs/crate*
1 1
4. 00 lbs/acre
(assume 2 applications)
28,800 28, 800
*Extension agent survey (see Chapter 3.0 above)
*EPA compendium.
** cOne crate of stored sweet potatoes equals 50 pounds. The storage amount of 952 crates was determined
by EPA.
EXHIBIT 5. 1.: Pounds
(Acres
of Insecticide Applied, United StateE
obtained from Exhibit 4. 7 above)
(J
I. - .
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EXHIBIT 5. 2: Coat. to Farmers of Total Pesticides Applied (current dollara)*
Note: Data for different pesticides are alternative courses of action, except for DDT.
Peanuts
1973 (dollars) 1974
Sweet Potatoes
1973 (dollars) 1974
Market Corn
1973 (dollars) 1974
Carbaryl
2-yeartotal
209, 790 372, 900
582,690
Not registered
for crop
15, 060 26, 294
41 ,354_
Lannate
2-year total
Not registered
for crop
Not registered
for crop
.
180, 000 472, 500
652, 500
Imidan
2-year total
Not registered
for crop
48 20
68
Not registered
for crop
DDT
— 2—year total
Net costs of
274, 392 444, 768
719, 160
Carbaryl -136, 470
1** 2***
3
Imidan 65
23, 731 37, 786
61,517
Carbaryl -20, 163
sub stitutiori
for DDT
Lannate 590, 983
*Exclusi.ve of application costs.
**Actually less than 1 dollar.
***Actually less than 2 dollars.
C
U,
0
0
Ill
z
m
z
-I
-1
0
0
•71
m
0
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