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 ------- 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 ------- 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. ------- 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 ------- PART I ------- 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 ‘U ------- 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 iv ------- 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 V ------- 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 vi ------- 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. v i ’ ------- 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, vu’ ------- • 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, ix ------- • 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, x ------- 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. xi ------- 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,. x l i ------- 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 ------- (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 ------- 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 ------- 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 ------- 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. 2. 1 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- = 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 ------- 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 ------- 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 ------- - 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- • 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- • 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 ------- 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 ------- • 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 ------- 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 ------- Toalcology in . Mutubuliam I. T.oratog.nlclty 1 AU wtIi1o T.kctnCe., La.. reailduou -— to bed and 1IL4 Ucicra .MlInn Pracais I- -s-- . --. .-—— —-— - — . — r-4 .W a Oncugonic and M tabnIlc I .. ..IArc.ptabl. i— . IM etih ot i c liatards Lod (Animal Fead In AnIn .aI.g ‘ ILntakn LOIAL....J Cbru .iie Elterts on U .. A nprndu tt. J f rInking W t.r • d t.toI,gtcaI Chicg .. __ _ _ - Dol.. e.pout.a flobi. ç—-j— -j I C. .*raI N . ,voup $yat.m. I t .avol (or Ilematopoatic System. _j to Man in U er, I ldn.y and I J)s’gro .lat Ion in ____________ I Funil l’rucu..ulnp 1 ap.t.tcd Average Dalif and or gp Intake in Man (or VIr I I A/rlc 1. Reildue In A • Sub o I K .’cAdiio kayo!. maI. Fish ..nd Other _______________________ tural 0 (1 ( 1 _______________________ • FSOd p.cto. Sqb t cct to human R d. : ; :: : Injury to — • Water I I Occupattonaiiy Ea .e4 _____________ -r ological flail. ü_M n I and Gpn,,aI PubU*i — — ° ° i 1 . Accumu lation I . .. — — — _ Tea t1c ldi _ !Lcologlcalaod \ . Chinicil Case Repo . I Physiologic — — — — — — — -: — — — — — _I I Oncog.sdcjty . Reproduc tog From Iluntan Exposure to Peg I I lmpsIpsn.a* Controlled Volunteer I MalIun lo . . (Epidemiohog. &ca Z otog1c s di.s I 1 •4 U Available) I F irholdi d __ ( 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 4 -. - A • • Mafrv4*E M.mple $elv.at S MI. (V .’. or vapor) ppm. iiilii. Ky. fnipn tI at R4$sul* Twen(y.fuur Umsr itissuit Rafing Healing on page I p.o d.o.e. I “. ‘ pp. I.qt.r Chreh. D • Rood h.p.. h.p Z o. l • ‘: , /17)0 h - ’ \ \ \ / / ‘i-ia - iI-/ J . % -2- ii c J_ 4 \ . 1(..’ Z ‘ _ c 1 ‘; 1 Z ‘ q i v ‘i’Y2 L_ j L L_ - F tc . . c y’ ø ) ? ? . j i is ,-\ J /s% o K . / ‘ i( jô 44 ioo 2 i 0 / o .3 ‘1 c ‘1 ‘ ‘ ‘jr,— __ \ “J’4 ‘> “I > i’ . / / 1 — ) F j ’) )/-J (j O I-I - L / ?, i i1 1j2 C i J?gf( 7’ ?LiS i ;A br VI 5$IU2* (U.. C.plgals for msrkrJ oysnptnn.):. ‘ i x ‘Y ‘ ‘ ‘ ‘T/ ‘i tc /71 :ii —)- L j_ .— g4 0 ‘ : o.g• % , i , ‘ \ ) ( \ ! ‘ Jmed l.t. Ud. snd $ci.rs Irl a Cornea F. Stain I —in . t.d eaplU.rie . i .—InternaI congestion d—duli % —portlon .t.3n.d u.up ity ooong .strd u —opaque ppplnpo,nt spot. s—edema I—Ugbt or diffu.. h—beniorrhage k—ks ’r.taoonu. d —d.ns.. p—pu. or ezudat. p—perforation rr.heular it ii .cro .l . 12.43 Recorded by. ------- 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 I tnitj .r ;r.;t.eti.tn itt t Ft. • r i’t ) I lIi’tUU - nuiji. r F ytl ’ii1ft flhlilur I — lit )(i3 ,LIIiII, i i i iii ii ur lioni tiN N -‘ niøjor ni-erolsi,. Scioro only worst symptom on entt1 Hpot. S c.. 17 Total St’orn..inean of fir.’ animnl.,. No. ) Totnl S or.’—tnia) of lit’.’ anmala. If soy spot ..c’or.’e uv,’r 4 r.’oord totai s. 20+ nd 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 1 1 HBiT BIi:LL’v TEST #lLVeMkant I 18, 4 Flour ff19, 24 Hour ii •l J)j•J) )I’V ‘ (-‘fl YEAR - ‘3a I 1-? 3’1 ‘-, - ; ‘t I I )ô L ., q —i’ij 3 4 ‘ 5 Lb :: 1 2 — S 4 5 6 - I ‘I 3 4 5 • ut,r , .l Snmplt Dilution , ond Snlv nt Ml. Animal t,• Spot J’ r’a ntion hours Dnt ‘I) • Sum. 0. 4 24 1 - - 1 :3: : . L! . i-:5 —- - — - —-— —— —— -____ ---______---__ _. -- .- — - -- • — — —---____ - -- - ——-—————_____ • LL-Jo -/q t, f,4 t - -,-,- - 0 -0 o.O E e ] 6 I . ., -,-‘ t ‘ - 3 4 5 (I ‘ I ., E•o 3 - 4 5 II- ’ 4’? /, fF1 I 2 1I.3 3 ft?- ii -2 Lfq e 6 • ,- _- t -— JLu3. 1/ -/ 5 ‘/ J T.2 / 1 ; - j•6 I .13 jAf I71. it,g I .ru. •: ,‘v ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- EXHIBIT 11: Types of Data Used in Agricultural Analysis of Insecticide Benefits and Costs A.4 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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 ------- 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) . ------- 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. ------- 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 ------- 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 ------- 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 ------- 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. ------- 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 ------- 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 ------- 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 ------- 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 ------- 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. - . ------- 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 ------- |