Economic Impact Analysis of
                 Proposed Effluent Limitations
               Guidelines and Standards for the
Pesticide Formulating, Packaging, and Repackaging Industry
                     Dr. Lynne G. Tudor, Economist
                  Economic and Statistical Analysis Branch
                     Engineering and Analysis Division
                     Office of Science and Technology

                   U.S. Environmental Protection Agency
                        Washington, DC 20460

-------

-------
                            ACKNOWLEDGEMENTS
      The most credit must be given to Janet Goodwin for her knowledge, experience,
cooperation, and leadership as project officer, and to Shari Zuskin and the whole pesticide
team for their professional manner, conscientious effort, and contributions.
      Credit must also be given to Abt Associates for their assistance and support in
performing the underlying analysis supporting the conclusions detailed in this report Their
study was performed under Contracts 68-CO-0080 and 68-C3-0302.  Particular thanks are
given to Michael Fisher, Robert Sartain, and Randi Currier.

-------

-------
                                  TABLE OF CONTENTS

Executive Summary	  ES. 1

Chapter 1     Introduction and Overview  	  1.1
       1.0    Overview and Definitions	  1.1
       1.1    Summary of the Proposed Regulation	  1.2
                     Best Practicable Control Technology (BPT)	  1.3
                     Best Available Technology Economically Achievable (BAT)
                     and Best Conventional Pollutant Control Technology (BCT)	  1.3
                     Pretreatment Standards for Existing Sources (PSES)	  1.3
                     New Source Performance Standards (NSPS) and.
                     Pretreatment Standards for New Sources (PSNS)	  1.4
       1.2    Selection of the Proposed Regulatory Options	  1.5
                     PFPR Facilities (Subcategory C)	  1.5
                     Refilling Establishments	  1.8
       1.3    Structure of the Economic Impact Analysis	  1.8
       1.4    Organization of the Economic Impact Analysis Report	  1.13

Chapter 2     Data Sources	  2.1
Chapter 3     Profile of the Pesticides Formulating, Packaging, and Repackaging Industry ....  3.1
       3.0    Introduction	  3.1
       3.1    Industry Overview	  3.1
                     Description of Pesticide Formulating, Packaging
                     and Repackaging Activities	  3.1
                     Regulatory Overview	  3.8
       3.2    Industry Structure	  3.10
                     Markets for Industry Products and Services	  3.10
                     Industry Employment  	  3.17
                     U.S. Trade in International Pesticides Markets   	  3.20
       3.3    Market Demand and Consumption	  3.21
                     Consumption of Pesticide Products — Historical and Current	  3.21
                     Price Elasticity of Demand	  3.25
       3.4    PFPR Industry Performance from 1986 to 1988 Compared to the
              Historical Trend hi the Industry and the Economy in General	  3.28
                     Growth in Gross Domestic Product, 1978 to 1991	  3.28
                     Performance of the PFPR Industry Relative to U.S.
                     Business Conditions, 1978 to 1992	  3.31
       3.5    Analysis of Facilities by Water Use Status and By Subgroups	  3.34
                     Comparison of Water-Using and Non-Water-Using Facilities	  3.34
                     Comparison of PFPR Facilities by Major Subgroups  	  3.38
       3.6    Summary  	     3 53

Chapter 4     Facility Impact Analysis	  4.1
       4.0    Introduction	  41
       4.1    Economic Model  	  43
                     Generalized Model of the PFPR Industry	 .  4.3
                     Applied Model of the PFPR Industry	  4.5

-------
       4.2    Impact Measures  	   4.22
                     Baseline	   4.22
                     Post-Compliance Impacts   	   4.22
       4.3    Calculation of Impacts „	 ......,_.	   4.26
                     Facility Closure	   4.26
                     Product Line Conversion   	   4.31
                     Comparison of Annualized Compliance Costs to Revenue	   4.35
       4.4    Facility Impact Results	 .   4.35
                     Impacts under BPT: Baseline and Post-Compliance Analysis  	   4.35
                     Impacts under PSES	   4.35

Chapter 5     Regulatory Flexibility Analysis	  5.1
       5.0    Introduction	  5-1
       5.1    Identifying Small Entities  	  5.3
                     Identifying Potentially Affected Entities  	  5.3
                     Defining "Small Entity"	  5.4
                     Classifying Facilities into Firms	  5.4
                     Estimating Firm Employment	  5.4
       5.2    Assessing the Distribution of Impacts	  5.6
                     Distribution of Potentially Affected Facilities
                     and Economic Impacts by Entity Size	  5.7
                     Distribution of Economic Impacts by Primary PFPR Market  	5.8
                     Distribution of Economic Impacts by Dependence on PFPR Revenue ...  5.9
                     Pesticide Active Ingredient Usage by Impacted I/C Facilities	  5.12
       5.3    Defining an Alternative to Option 3	   5.13
       5.4    Impacts of Option 3/S  	   5.15
       Chapter 5 References   	   5.16

Chapter 6     Community Impact Analysis  /	  6.1
       6.0    Introduction	  6.1
       6.1    Methodology for Assessing Community Impacts	  6.2
                     Estimating Primary Employment Impacts  	  6.3
                     Estimating Secondary Employment Impacts	  6.5
       6.2    Findings From the Community Impact Analysis  	  6.6
       Chapter 6 References	   6.11


Chapter 7     Foreign Trade Impacts	  7.1
       7.0    Introduction	  7.1
       7.1    Methodology for Assessing Foreign Trade Impacts	7.2
                     Trade Impacts Under Proportional Case Assumptions	  7.4
                     Trade Impacts Under, Worst-Case Assumptions	7.6
       7.2    Estimated Changes hi Pesticide Exports and Imports Under
              Worst-Case and Proportional Case Assumptions	  7.7
                     Proportional Case Assumptions	• • •  7.7
                     Worst-Case Assumptions  	  7.7
       7.3    Significance of the Estimated Decreases hi the Net Trade Balance	7.8
                     Proportional Case Assumptions	  7.8
                     Worst-Case Assumptions  	  7.9
        Chapter 7 References	  7.11

-------
Chapter 8      Assessment of Firm-Level Impacts	  8.1
       8.0    Introduction .	  8.1
       8.1    Methodology for Assessing Firm-Level Impacts	  8.2
                     Analysis 1: Baseline Analysis of Firm-Level Financial Performance  ...  8.2
                     Analysis 2: Post-Compliance Analysis of
                     Firm-Level Financial Performance	  8.10
       8.2    Estimated Firm Impacts  	  8.13
       Chapter 8 References	  8.15

Chapter 9      Impacts on New Sources	  9.1
       9.0    Introduction	  9.1
       9.1    Subcategory C	  9.1
                     New Source Performance Standards	  9.1
                     Pretreatment Standards for New Sources	  9.1
       9.2    Subcategory E	  9.2
                     New Source Performance Standards	  9.2
                     Pretreatment Standards for New Sources	  9.2

Chapter 10    Additional Cost Savings From Pollution Prevention Under Option 3/S  	  10.1
        10.0   Introduction  	  10.1
        10.1   Overview of Compliance Cost Savings Opportunities	  10.4
                     Direct cost savings	  10.4
                     Indirect Cost Savings	.• •.  10.5
        10.2   Direct Cost Savings From Recovery and Reuse of PAIs  	  10.6
                     Methodology for Estimating PAI Cost Savings	  10.6
                     Estimated PAI Recoveries and Potential Cost Savings .  . .	  10.7
        10.3   Cost Savings From Reduced Water Use and Water Discharge	  10.9
                     Methodology for Estimating Cost Savings
                     from Reduced Water Use and Water Discharge	  10.9
        10.4   Indirect Cost Savings from Reduced Costs of Permitting and Fees	10.16
                     Review of Permit-Related Cost Savings Opportunities	10.16
                     Examples of Possible Permit-Related Savings	10.20
                     Possible National Savings from Reduced Permitting Costs	 10.22
        10.5   Indirect Cost Savings from Reduced Insurance Premiums  	10.22
                     Mechanisms by Which Pollution Prevention Reduces Environmental Risk 10.22
                     Outlook for Favorable Consideration of Pollution Prevention
                     by the Insurance Industry	10.24
        10.6    Cost Savings from Reduced Cost of Capital	 10.25
        10.7    Attaining Compliance Through Pollution Prevention Versus Combustion   .... 10.27
                     Difficulties in Siting a New Combustion Facility	10.27
                     Difficulties and Costs from the RCRA Permitting Process	10.28
                     Other Changes hi the Regulatory Environment	10.29
        Chapter  10 References	10.31

 Chapter 11     Labor Requirements and Potential Employment Benefits of an
               Effluent Guideline for the Pesticide Formulating, Packaging,
               and Repackaging  Industry	   11.1
        11.0    Introduction	   11.1
        11.1    Estimating the Direct Labor Requirements of the PFPR Rule	   11.2
                      Direct Labor Requirements for Manufacturing Compliance Equipment .   11.2

-------
                      Dkect Labor Requirements for Operating Compliance Equipment  ....   11.5
                      Total Direct Labor Requirements for Complying
                      with the PFPR Effluent Guideline	   11.6
        11.3   Estimating the Indirect and Induced Labor Requirement Effects of the PFPR Rule  11.6
        Chapter 11 References	   11.8

Chapter 12    Assessment of Economic Impacts Of Including Under Regulation
              Additional PAIs Not On the Original List of 272 PAIs	   12.1
        12.0   Introduction	   12.1
        12.1   Estimated Facility Impacts Under Option 3/S'  	   12.2
                      Facilities Using Both Original 272 PAIs and Additional non-272 PAIs  .   12.2
                      Facilities Using Only the Additional Non-272 PAIs	   12.3
                      Aggregate Impacts for All Facilities Using Both Original 272
                      and Additional non-272 PAIs	   12.5
        12.2   Regulatory Flexibility Considerations of Option 3/S'  	   12.8
        12.3   Community Impacts of Option 3/S'	   12.8
        12.4   Foreign Trade Effects Under Option 3/S'  	12.10
        12.5   Firm-Level Impacts of Option 3/S' 	12.11
        12.6   Potential Labor Requirements of Complying with Option 3/S'   	12.12


Appendix A   Pesticide Formulating, Packaging, and Repackaging Facility Survey for 1988	

Appendix B   Mapping of Pesticide Active Ingredients into Clusters	

Appendix C   Methodology for Estimating the Price Elasticity of Demand
              for Pesticide Clusters	 .

Appendix D   Compliance Costs as a Percentage of Revenue for Baseline Facility Closures	

Appendix E   Sensitivity Analysis of the Return on Asset Value used in
              Line Conversion Analysis	

Appendix F   Facility Impact Analysis Assuming a Price-Adjustment Rule	

-------
                                     LIST OF TABLES

Table 3.1: Representative Classes of Pesticides and the Pests They Control	  3.3
Table 3.2: Pesticide Clusters	  3^5
Table 3.3: Pesticide Agricultural Production and Distribution	  3.13
Table 3.4: Total Facility Employment Characteristics by Facility Size	  3.19
Table 3.5: Average Facility Employment Characteristics by Facility Size  	  3.20
Table 3.6: U.S. Participation in International Markets for Pesticides Exports, Imports,
       Trade Balance, and U.S. Share of Total Exports and Imports	  3.22
Table 3.7: User Expenditures for Pesticides by Market	  3.24
Table 3.8: Summary of Estimates of Elasticity of Demand	  3.26
Table 3.9: Gross Domestic Product vs. Product Shipments for SIC 2879:
       Comparisons of Annual Growth Rates	  3.29
Table 3.10: Value of Product Shipments for SIC 2879	...../.  330
Table 3.11: Comparative Statistics of Water Using and Non-Water Using Facilities (1986-1988)  3.35
Table 3.12: National Estimates  of Primary SICs Reported by PFPR Facilities	  3.44
Table 3.13: Average Facility Employment Characteristics by Business Type  	  3.52
Table 3.14: National Estimates  of PFPR Return on Assets By Subgroup, Three Year Average  .  3.54
Table 4.1: Estimated National Distribution of Selected Characteristics of
       Subcategory E Facilities vs. Other PFPR Facilities, Facilities That Use Water  	  4.27
Table 4.2: Analysis Methods and Impact Measures by Facility Subcategory	  4.28
Table 4.3: Projected Population Baseline Closures for Facilities that Use Water
       (Based on 3-year Average Negative Cash Flow)	  4.36
Table 4.4: National Estimates of Economic Impacts upon Subcategory C Facilities
       (Assuming Zero Cost Pass-Through)  . ,	  4.39
Table 4.5: National Estimates of Impacts for Subcategory C Facilities Under Option 3
       and Option 3/S (Assuming Zero Cost Pass Through)	  4.41
Table 4.6: Estimated National Impacts for Subcategory E Faculties   	  4.42
Table 5.1: Distribution of Projected Costs and Impacts of Option 3 on Facilities
       Owned by Small and Other Entities	  5.8
Table 5.2: Distribution by Primary Market of Facilities Incurring Costs
       and of Facilities Expected to Incur Significant Economic Impacts Under Option 3 ....  5.10
Table 5.3: Dependence on PFPR Revenue of Facilities Incurring Impacts
       Under OptionS (by business-size classification and primary market)  	  5.11
Table 5.4: Distribution of Costs and Impacts Under Options 3 and 3/S	  5.15
Table 6.1: Estimated National Employment Losses for Each Regulatory Option  	6.7
Table 6.2: Analysis of Community Employment Impacts Assuming Worst-Case Multiplier
       and Proportional Distribution of Sample-Weighted Employment Losses	  6.8
Table 7.1: Change in Foreign Trade Balance for Subcategory C PSES Options   	7.9
Table 7.2: U.S. Trade Balance hi the Pesticide Market,  1980 -1990	  7.10
Table 8.1: Sample Finn Financial Impacts   	  8.14
Table 10-1: Summary of Estimated PAI Cost Savings Under Proposed Regulatory Option ....  10.8
Table 10-2: Sewer and Water Cost Savings Summary Table	10.15
Table 11-1: Analysis of Possible Employment Generation Effects of an
       Effluent Guideline for the PFPR Industry	  11.4
Table 12.1: National Estimates of Costs and Impacts under PSES, Comparison of Option 3/S'
       with Option 3/S	  12.4
Table 12.2: Estimated National  Impacts for PFPR Facilities Using Only Additional Non-212 PAIs 12.6

-------
Table 12.3: National Estimates of Costs and Impacts for PSES Option 3/S'
       Including Subcategory C Facilities Using Both Original and Additional Non-272 PAIs,
       and Facilities Using Only Additional Non-272 PAIs (Assuming Zero Cost Pass-Through)  12.7
Table 12.4: Estimated Sample Firm Financial Impacts Under Option 3/S'   	12.12
Table 12.5: National Estimates of Employment Losses and Possible Offsetting
       Employment Gains Based on Analysis of All Subcategory C Facilities
       Under PSES Option 3/S'   	12.12

-------
                                    LIST OF FIGURES

Figure 1.1: Economic Impact Analysis of Pesticides Formulating/Packaging/Repackaging
       Industry Effluent Limitations Guidelines: Analytic Components  	  1.10
Figure 3.1: 1988 Pesticide Sales in the U.S. and World Markets	  3.4
Figure 3.2: National Estimates of Composition of Facility 272 PAI-Related Revenues
       Averaged Across All Facilities (Avg. 1986-1988)  	  3.10
Figure 3.3: National Estimates of Distribution of 272 PAI-Related PFPR Revenue
       by Market Type (1988)  	  3.12
Figure 3.4: Production and Distibution Channels: Industrial/Institutional/Commercial
       and Home/Lawn/Garden Markets	  3.15
Figure 3.5a: Employment Trends 1980-1990 (1988 Base Year)	  3.18
Figure 3.5b: Employment Trends 1980-1990 (1988 Base Year)	  3.21
Figure 3.6: User Expenditures for Pesticides by Principal Market (In Million 1988 $)  ......  3.23
Figure 3.7: Gross Domestic Product and Product Shipments for SIC 2879
       Annual Percentage Growth	 .	  3.31
Figure 3.8: Value of Product Shipments for SIC 2879 in 1988 Million Dollars	  3.33
Figure 3.9: National Estimates of Percent of Water Using Facilities and Non-Water Using
       Facilities hi the PFPR Industry by Primary Market	  3.36
Figure 3.10: National Estimates of Water-Using Facilities and Non-Water-Using Facilities
       in the PFPR Industry by Ownership Characteristics	  3.38
Figure 3.11: National Estimate of PFPR Industry Structure by Subgroup	  3.42
Figure 3.12: National Estimates of Water-Using Facilities and Non-Water-Using Facilities
       in the PFPR Industry by Subgroup  	  3.43
Figure 3.13: National Estimate of Percent of Revenue from PFPR Activities by Subgroup ....  3.45
Figure 3.14: National Estimates of Refilling Establishments and the Rest of the PFPR Industry
       by Facility  Type	  3.46
Figure 3.15: National Estimates of Primary Pesticide Markets by Subgroup (1988)  	  3.48
Figure 3.16: National Estimates of Ownership Characteristics by Subgroup	  3.49
Figure 3.17: National Estimates of Average Market Value for PFPR Production Line
       by Subgroup	  3.50
Figure 3.18: National Estimates of Facility Revenues by Subgroup	  3.53

-------

-------
                                    Executive Summary

Introduction
       This Economic Impact Analysis (EIA) assesses the economic impact of proposed guidelines and
standards under the Clean Water Act for the Pesticide Formulating, Packaging, and Repackaging (PFPR)
subcategories of the Pesticide Chemicals Point Source Category (40 CFR 355). The proposed guidelines
and standards will apply to an estimated 3,900 facilities that formulate, package, and repackage pesticide
chemicals.  For the regulation, EPA divided the existing PFPR subcategory into two subcategories:  (i)
Subcategory C: Pesticide Chemicals Formulating, Packaging, and Repackaging;  and (2) Subcategory E:
Repackaging of Agricultural Chemicals Performed at Refilling Establishments. This regulation includes
limitations  for Best Practicable  Control  Technology (BPT), Best Conventional Pollutant  Control
Technology (BCT), Best  Available Technology Economically Achievable  (BAT), New Source
Performance Standards (NSPS) and Pretreatment Standards for Existing and New Sources (PSES and
PSNS).  Because BCT and BAT requirements match the established BPT requirements, no additional
costs are expected for compliance with the BCT and BAT limitations. Accordingly, this EIA focuses on
analyzing alternative PSES options.

       This executive summary reviews the major elements of the EIA, including:  (1) facility impacts
analysis  for PSES regulatory  options and selection of preferred options; (2)  Regulatory Flexibility
Analysis; (3) analysis of additional impact categories — community level impacts, international trade
effects, firm-level impacts,  and  the  effects  on construction of new PFPR facilities;  (4) analysis of
compliance cost-savings from pollution prevention, and assessment of potential labor needs generated by
the regulation; and (5)  analysis of extending the proposed PFPR regulation to encompass additional
pesticide active ingredients (PAIs) beyond those originally studied for regulation.

Analysis of Facility Impacts for PSES Regulatory Options
       The main  source of technical and financial data for the EIA is the Pesticide Formulating,
Packaging, and Repackaging Facility Survey for 1988, which requested  data from a sample of 708
facilities  representing 3,241 facilities that hold product registrations containing one or more of 272 PAIs.
The facility impact analysis included a pre-compliance test to identify facilities that are financially weak
independent of the PFPR regulation.  Approximately 20 percent of facilities failed this test and were
removed from the impact analysis. To assess facility impacts, the pre-compliance financial statements
were adjusted to  reflect the estimated capital and operating costs of alternative regulatory options.
Financial tests based on cash-flow, return on  assets, and the ratio of compliance cost to  facility revenue
                                             ES.l

-------
 were used to identify facility impacts in terms of facility closures — which entail a full loss of facility
 employment — or moderate impacts, which include product line conversions to non-PFPR activities or
 compliance costs exceeding 5 percent of revenue. Product line conversions were conservatively assumed
 to involve loss of all PFPRrrelated employment in a facility.

        In developing this regulatory proposal, EPA defined and analyzed several PSES regulatory options
 for the Subcategory C and Subcategory E facilities. These options and the findings from the facility-level
 impact analysis are summarized below.

        Subcategory C Facilities
        For Subcategory  C facilities,  EPA initially considered 5 PSES options.  Options 1 and 2 are not
 zero discharge options but involve treatment of wastewater and discharge to POTWs. Options 3, 4, and
 5 are zero discharge options but involve different compliance methods with differing costs and impact.
        Option1 consists of end-of-pipe treatment for all wastewaters through the Universal Treatment
        System1  and discharge to POTWs.
        Option 2 adds pollution prevention by recycling  wastewaters  from cleaning the interiors of
        formulating and packaging equipment, and raw material and shipping containers into the product
        to recover product value in the wastewaters.  Other wastewaters are still expected to be treated
        through the Universal Treatment System and discharged to POTWs.
        Option 3 employs  the same technology and pollution prevention practices  as Option 2 but
        achieves zero discharge of all process wastewater by recycling the wastewater back to the facility
        after treatment through the Universal Treatment System.
        Option 4 incorporates the pollution prevention aspects  of  Options 2 and 3, but instead  of
        treatment, adds off-site disposal to an incinerator for the rest of the wastewater.
        Option 5 assumes disposal of all wastewater through off-site incineration.

        EPA analyzed the compliance costs and industry impacts for these options based on facility and
compliance cost data assuming use and control of a set of 272 PAIs. EPA later extended the regulatory
cost analysis to include discharge limitations on all additional PAIs.  The following discussion is based
on the analysis of 272 PAIs. The analyses for the Subcategory C PSES options showed total annualized
compliance costs  ranging from a low of $27>.9 million for Options 2 and 3 to a high of $360.2 million
for Option 5.  Options 2 and 3, which have the least impacts, are each expected to result in one facility
        Universal Treatment System consists of chemical emulsion breaking, hydrolysis, chemical oxidation,
sulfide precipitation and activated carbon filtration treatment technologies.
                                             ES.2

-------
closure and 170 moderate impacts. EPA estimated the greatest impacts for Option 5 at 7 facility closures
and 217 moderate impacts.  Total estimated worst-case job losses range from a low of 426 for Options
2 and 3 to a high of 1,173 for Option 5 (see Table ES-1).2
Table ES-1
National Bsfltnate of Economic Jopiefc on Sfoheategoiy € F*«8»te$
(Assuming Zero Cost Pass Through)
Option 1 Option! Option3 Option 4 Option 5
-Number of Facilities incurring Costs
-Compliance Capital Costs <$ MM 1988)
-Total Annualized Compliance Costs
-Facility Closures
-Moderate Economic impacts
-Estimated Woist-Cass Jofc Losses
(FUs)
-T»tai Pollutant Reniovais flfcs)
-Toxic-Weighted Pollutant Removals
(Ibs-equivalent}
578
$20.8
$32.6
9
171
437

111,653
12,127,075

558
$66.1
$27.9
1
170
426

111,683
12,127,666

558
$66.1
'$27.9
1
170
426

111,996
12,134,051

558
$18.4
$286.5
7
193
1,113

111,996
12,134,051

578
$21.0
$360.2
7
217
1,173

111,996
12,134,051

       From this analysis, EPA initially considered Option 3 as the basis for PSES regulation of
Subcategory C facilities.  Together with Option 2, Option 3 has the lowest compliance costs and impacts
of the options analyzed.  However, by achieving zero discharge, Option 3 more strongly promotes Clean
Water  Act objectives than Option 2.   Moreover,  Option 3 embodies  Best Available Technology
Economically Achievable (BAT), incorporating the best practices of pollution prevention, recycle/reuse,
and water conservation applicable to this subcategory.  Options 4 and 5 also achieve zero discharge, but
at a much higher cost than Option 3.  EPA also found that Option 3 is the most cost-effective of the five
options.  From these findings, EPA concluded that Option 3 was economically achievable. However,
in the  Regulatory  Flexibility Analysis,  discussed  below,  EPA  found  that  Option 3  would
disproportionately affect certain PFPR facilities and modified the option to mitigate these impacts.

       Subcafegory E Facilities
       EPA developed and analyzed two zero discharge options for Subcategory E Facilities: Option 1
achieves zero discharge by storage of wastewater collected from secondary containment structures for use
as make-up water hi pesticide applications; Option 2 achieves zero discharge by collection of wastewater
   2Job losses are considered "worst case" because EPA assumed that line conversions would result in loss of all
PFPR-related employment in a facility, which may not occur.
                                             ES.3

-------
 from secondary containment followed by contract hauling for off-site incineration.  Only 19 of 1,122
 Subcategory E facilities were found to not already be meeting zero discharge.  EPA estimates that the
 19 remaining facilities could comply with Option 1 at zero annual cost and with Option 2 at a total annual
 cost of only $1,837.  Neither option imposes any facility impacts and both were deemed economically
 achievable. EPA selected Option 1 as the basis for the PSES regulation for Subcategory E facilities.

 Regulatory flexibility Analysis
        EPA performed a Regulatory Flexibility Analysis to understand whether Option 3 for Subcategory
 C facilities would disproportionately affect small business-owned facilities and whether the  regulatory
 option should be modified.  Because no impacts were found for the Subcategory E options, EPA did not
 perform a Regulatory Flexibility Analysis for the preferred Option 1.

        In performing the Regulatory Flexibility Analysis for Option 3, EPA had to balance the traditional
 concerns of a Regulatory Flexibility Analysis — moderation of impacts among small-business entities —
 with the broader regulatory objectives of the Clean Water Act.  In particular,  because small business
 concerns largely comprise the PFPR industry, EPA needed  to analyze other facility characteristics hi
 addition to business size classification to understand the characteristics of facilities impacted by Option 3.
 These additional characteristics included principal PFPR market from which facilities derive business,
 PFPR revenue as a percent of total facility revenue, and usage of pesticide active ingredients.

        From this analysis, EPA found that Option 3 would disproportionately affect certain facilities that:
 (1) are owned  primarily by a small business; (2) participate to a large degree in the institutional/
 commercial market; (3) receive a relatively low share of total revenue from PFPR activities; and (4) often
 use relatively low toxicity "sanitizer" PAIs to produce sanitizer products.  Taking these distinguishing
 characteristics into account, EPA defined a modification to Option 3, namely Option 3/S, as the preferred
 regulatory alternative.  Option 3/S is the same as  Option 3  except that it exempts certain non-interior
 wastewater streams from the zero discharge requirement. Specifically, for those facilities that formulate,
 package, or repackage designated  sanitizer PAIs and whose sanitizer production is less than 265,000
 pounds per year, the zero discharge requirement would not apply to non-interior wastewater streams that
 contain only designated sanitizer PAIs.3   These  non-interior wastewater  streams include exterior
    3See Table 8 of the proposed regulation or Section 12 of the Technical Development Document (Development
Document for Best Available Technology, Pretreatment Technology, and New Source Performance Technology for
the Pesticide Formulating,  Packaging, and Repackaging Industry: Proposed) for a list of the sanitizer active
ingredients that are eligible for exemption from the zero discharge requirement under this regulation.
                                              ES.4

-------
equipment and floor wash, leak and spill cleanup, safety equipment rinsate, contaminated precipitation
run-off, laboratory wastewater, air pollution control wastewater, and DOT test bath water.  The zero
discharge requirement would  apply to the interior wastewater streams of these facilities  including
discharge from cleaning the interiors of drum/shipping containers, bulk containers, and other equipment.

       In comparison to Option  3, Option 3/S  imposes lower costs and  fewer  facility impacts,
particularly among small business-owned facilities operating in the histitutional/commercial market. Total
annualized compliance costs under Option 3/S were estimated at $26.1 million, or $1.8 million less than
under Option 3.  Moreover, under Option 3/S, moderate impacts fell by 20 percent, from 170 to 136
facilities (1 facility was assessed as a closure under both options). EPA estimated total job losses at 355
FTEs under Option 3/S,  or 71 fewer job losses than under Option 3.  Among small businesses, total
facility impacts fell by 22 percent, from 150 to 116.

       Because Option 3/S exempts certain discharge streams containing only sanitizer PAIs from the
zero discharge requirement, EPA expects that pollutant removals would be slightly lower under Option
3/S than under Option 3.  EPA estimates that Option 3/S would remove 111,793 pounds of discharges
annually, or 203 pounds less than the amount removed by Option 3.  However, when the discharges are
adjusted for relative toxicity, EPA estimates that Option 3/S would remove only 19 fewer toxic-weighted
pounds  than the total of 12,134,501 toxic-weighted pounds removed under Option  3.  The small
difference in toxic-weighted pounds reflects the generally low toxicity  of sanitizer PAIs.  Taking into
account both the substantial relief to small business-owned facilities provided by Option 3/S and the very
modest loss hi pollution reduction benefits, EPA selected this option as the preferred regulatory option
for PSES limitations to be applied to Subcategory C PFPR facilities.
                     • i .
Other Impacts
        EPA also performed additional impact analyses for the proposed PSES regulation — community
employment, foreign trade effects, firm4evel financial performance, and entry of new sources into the
PFPR industry — and assessed possible  offsets to  the regulation's costs  and economic impacts —
compliance cost-savings from  pollution prevention  and labor needs generated by  the regulation.   The
findings from these analyses are summarized below.
                                             ES.5

-------
         Community Employment Impacts
         Community impacts were assessed on the basis of the employment loss expected to result from
 facility closures or PFPR line conversions, taking into account both primary employment effects in the
 PFPR industry and secondary employment effects in other affected industries.  Although the community
 impact analysis usedhighly conservative assumptions, no Metropolitan Statistical Areas in which impacted
 sample facilities are located were found to  incur employment losses exceeding one  percent of total
 employment, the threshold of significant impact.

        Foreign Trade Impacts
        EPA assessed foreign trade impacts in terms of the change hi net exports of pesticide products
 stemming from lost production  hi impacted facilities.   EPA analyzed foreign trade impacts under two
 cases.  The more realistic, proportional case, which accounts for the relative competitiveness of U.S. and
 foreign producers, indicated that Option 3/S  would lead to a decline hi the net trade balance of $9.2
 million or less than one percent of the average pesticides trade balance value over the period 1980-1990.
 The severely unrealistic, worst case analysis  found that the loss hi the net trade balance for pesticides
 under Option 3/S would be about 4 percent.  In view of the minor impacts, particularly  under the
 proportional case analysis, EPA  concluded that Option 3/S will not significantly impair the international
 trade position hi pesticides.

        Firm-Level Impacts
        The firm-level impact analysis used a  test based on change hi pre-tax return on assets (ROA) to
 assess whether the financial performance of firms owning PFPR facilities will be significantly affected
 by compliance requirements. Because of sample design issues, the results from this analysis apply only
 to 308 firms that own sample facilities and cannot be extrapolated to the PFPR facility population.  The
 analysis accounts for compliance costs both hi sample facilities and hi other PFPR facilities not included
 hi the  sample.  Also, a pre-compliance  test was used  to  identify firms that  are financially weak
 independent  of regulatory requirements:  66 firms  failed this test.  EPA  found  that only 5 of the
 remaining 242 firms would incur adverse financial impacts as a result of regulatory compliance. EPA
judges that this modest frequency of impacts Should not pose a significant burden to the PFPR industry.

        Effects of Regulatory Compliance on New Sources
        For Subcategory  C facilities, EPA proposes to establish New Source Performance Standards
(NSPS) and Pretreatment Standards for New Sources (PSNS) as zero discharge. The economic  impact
                                            ES.6

-------
 analysis for existing sources found that zero discharge (as embodied in Option 3) would be economically
 achievable for existing sources.  Because new sources can include compliance equipment and related
 processes in plant designs before construction and generally at lower  cost than for retrofit applications,
 EPA believes that new sources will be able to comply at costs that are similar to  or less than those for
 existing sources. Accordingly, EPA concludes that a zero discharge requirement  for new source direct
 dischargers would be economically achievable and would not be a barrier to entry.

        Although EPA proposes  to exempt  certain sanitizer PAI waste streams  from the PSES zero
 discharge requirement for existing facilities, EPA does not propose  to extend this exemption to new
 facilities under PSNS. EPA's proposal  to exempt the designated waste streams in existing facilities is
 based on the substantial reduction in impacts among small business-owned facilities coupled with a very
 small increase hi pollutant loadings.  EPA does not have sufficient information for new sources subject
 to PSNS to conclude that the size and economic conditions of those new sources, the impacts on those
 new sources, and the associated loadings of toxic pollutants, would justify a similar exemption.

        For Subcategory E  facilities, EPA proposes NSPS/PSNS equal to the proposed  BAT/PSES
 limitations for existing sources.   Because EPA found that compliance with the proposed option is
 economically achievable for existing facilities, EPA also determined that compliance with NSPS/PSNS
 will be economically achievable and not  a barrier to entry for new sources.

        Cost Savings from Pollution Prevention
       In its regulatory analysis, EPA found that incorporating pollution prevention as an element of
 compliance strategy was economically advantageous.  Although the regulatory cost analysis accounted
 for an estimated $4.7 million hi cost savings from reduced waste management and disposal costs, certain
 additional cost savings — from reduced  water use and sewer discharge, recovery  and reuse of PAIs hi
 wastewaters, reduced  permitting-related  costs, and reduced insurance and cost of capital — were not
recognized.  EPA quantified the potential  savings from reduced water use and sewer charge, and recovery
 and reuse of PAIs; the remaining savings  categories were qualitatively assessed.  From this analysis, EPA
estimated national aggregate annual benefits of $116,000 from reduced water use and sewer charge, and
$628,100 from recovery and reuse of PAIs.  Although permitting cost savings  were not estimated on a
facility-specific basis, EPA identified possible savings amounts per facility varying from a few hundred
dollars a year for some POTW-related  charges to tens of thousands of dollars  for direct discharge
permits.  In aggregate, such savings might amount to as much as  $2 million annually.  EPA was also
                                             ES.7

-------
  unable to quantify savings in insurance premiums and reduced cost of capital.  However, discussions with
  industry and a literature review indicate that these factors may also provide financial benefits for firms
  that choose pollution prevention as a means of complying with the proposed PFPR regulation.

         Labor Requirements of Compliance
         The manufacturing, installation, and operation of equipment and processes for complying with
  the PFPR regulation will require labor resources.  To the extent that these labor requirements translate
  into employment increases in complying firms, the regulation may generate employment benefits that
  partially offset employment losses in impacted facilities.   Accordingly, EPA  estimated  the  labor
  requirements of compliance taking into account both primary labor needs for manufacturing, installing
  and operating compliance equipment and secondary requirements in other affected industries.  From this
  analysis, EPA estimated an annual primary labor requirement of 100 full-tune equivalent positions with
  corresponding payments to labor of $3.4 million (1988 dollars).  Taking into account both primary and
 secondary employment effects, EPA estimated that the total labor requirements of the Option 3/S rule
 would range from 269 to 400 full-tune equivalent positions.

 Compliance Effects Including PAIs Not on the Original List of 272 PAIs Studied for Regulation
        After analyzing the compliance costs and pollutant removals for Option 3/S, EPA decided to
 include under regulation all additional PAIs (except sodium hypochlorite) beyond the 272 PAIs on which
 the initial options analysis and selection were based.  EPA conducted additional analyses including these
 additional non-272 PAIs. To distinguish the analysis and findings for the regulatory option  including
 coverage of the additional non-272 PAIs from the analysis of Option 3/S based on only the 272 PAIs,
 this document refers  to the regulation including coverage of the additional non-272 PAIs as Option
 3/S'.4

        EPA estimated the costs and impacts of Option 3/S' separately for:  (1) facilities  that use the
 original 272 PAIs  and that may also use the additional non-272 PAIs; and (2) facilities that use only the
 additional non-272 PAIs.  Costs and impacts for the first set of facilities were  analyzed on a facility-
 specific basis using the same facility impact assessment methodology outlined at the beginning of this
 summary. In this effort, EPA used data on the usage of the non-272 PAIs from the FATES database to
 supplement the data developed and analyzed on the basis of the 272 PAIs.  Costs  and impacts for the
   "The Federal Register Notice for this regulation refers to the regulatory option with expanded PAI coverage
as Option 3/S. 1.
                                             ES.8

-------
second set of faculties, which use non-272 PAIs only, were estimated by extrapolating aggregate results
from the analysis of facilities using only the original set of 272 PAIs.  These separately estimated costs
and impacts were combined to yield the aggregate values for Option 3/S'.

       Under Option 3/S', EPA estimated that 869 Subcategory C facilities will incur total annualized
costs of $56.1 million, compared to $26.1 million under  Option 3/S.  The associated  facility impacts
amount to 2 facility closures and 250 moderate impacts, compared to 1 facility closure and 136 moderate
impacts under Option 3/S. Worst case job losses were estimated at 688 full-time equivalent positions,
or 333 more than estimated for Option 3/S.  Although these analyses show additional economic impacts
as a result of including  the  additional  non-272 PAIs  under regulation, EPA found that the  selected
option remains economically achievable. Moreover, by including the additional PAIs under regulation,
Option 3/S' promotes more strongly the pollution reduction objectives of the Clean Water Act. Overall,
Option 3/S' achieves substantially greater pollutant removals, approximately 310,000 pounds annually,
than both the initially selected Option 3 and the revised  Option 3/S (both achieve about  112,000
pounds)5.  In addition,  because Option  3/S' retains  the exemption for  certain sanitizer PAI waste
streams, it results in relatively minor impacts among the small business-owned, sanitizer facilities that
EPA had found to incur disproportionate impacts under a uniform  zero discharge requirement.  The
exemption for these waste streams excludes from compliance requirements  a very small quantity of
pollutant discharges containing the exempted sanitizer PAIs, 1,036 pounds annually. Because the sanitizer
PAIs generally have relatively low toxicity, the estimated residual discharges amount to only 196 toxic-
weighted pounds  annually  when  adjusted  for  relative toxicity.   These residual discharges are  an
insignificant fraction of the pre-compliance amount of 34  million toxic-weighted pounds.  On balance,
EPA considers Option 3/S' the superior alternative among the regulatory options considered.

        EPA also performed the additional impact analyses  — community employment, foreign trade, and
firm-level — summarized above, including consideration of the additional non-272 PAIs. None of these
additional analyses found that impacts are likely to be significant as a result of including under regulation
the additional PAIs.
    5The toxic-weighted removals for these options are estimated as follows:  Option 3/S', 33,747,863 pound-
 equivalents; Option 3/S, 12,134,031 pound-equivalents; and Option 3, 12,134,051 pound-equivalents.
                                              ES.9

-------

-------
                                         Chapter 1
                                Introduction and Overview
1.0    Overview and Definitions

       The Federal Water Pollution Control Act Amendments of 1972 established a comprehensive

program to "restore and maintain the chemical, physical, and biological integrity of the Nation's waters"

(Section 101(a)).  To implement these amendments,  the U.S. Environmental Protection Agency (EPA)

issues  effluent limitations  guidelines and  standards for categories  of industrial  dischargers.   The

regulations that the EPA establishes are:
               Best Practicable Control Technology Currently Available (BPT).  These rules apply to
               existing industrial direct  dischargers,  and generally  cover discharge of conventional
               pollutants.1

               Best Available Technology Economically Achievable (BAT).  These rules apply to existing
               industrial direct dischargers and the control of priority and non-conventional pollutant
               discharges.

               Best Conventional Pollutant Control Technology (BCT).  BCT rules are an additional
               level of control beyond BPT for conventional pollutants.

               Pretreatment Standards for Existing Sources (PSES).  These rules apply to  existing
               indirect dischargers (i.e., facilities whose discharges  enter Publicly Owned Treatment
               Works, or POTWs).  They generally cover discharge of toxic and non-conventional
               pollutants that pass through  the  POTW or interfere with its  operation.  They are
               analogous to the BAT controls.

               New Source Performance Standards (NSPS). These rules apply to new industrial direct
               dischargers and cover all pollutant categories.

               Pretreatment Standards for New Sources (PSNS).  These rules apply to new indirect
               dischargers and generally cover discharge of toxic and non-conventional pollutants that
               pass through the POTW or interfere with its operation.
        This Economic Impact  Analysis  (EIA) assesses  the  economic impact  of proposed effluent

 limitations guidelines and standards for the Pesticide Formulating, Packaging, and Repackaging (PFPR)

 subcategories of the Pesticide Chemicals Point Source Category (40 CFR 355). This rulemaking proposes
    Conventional pollutants are defined as biochemical oxygen demand (BOD), total suspected solids (TSS), oil
 and grease, and pH.  Other pollutants may also be regulated at the BPT level.

                                               1.1

-------
limitations for Best  Practicable  Control Technology (BPT), Best  Conventional  Pollutant Control
Technology  (BCT),  Best Available Technology Economically Achievable  (BAT),  New  Source
Performance Standards (NSPS) and Pretreatment Standards for Existing and New Sources (PSES and
PSNS).

        BPT limitations were promulgated for three subcategories of the pesticide chemicals point source
category hi 1978.  Two  of the three subcategories regulated the pesticide manufacturing of active
ingredients, while the third regulated the formulating and packaging of pesticide products. On September
28,  1993, additional effluent limitations  guidelines and  standards were issued  for the pesticide
manufacturing subcategories.

        The promulgated BPT regulation required  zero direct discharge  for  pesticide chemicals
formulating and packaging facilities.  In  1985, EPA promulgated zero  discharge pretreatment standards
(along with BAT limitations and new source standards to implement the BPT requirements).  This
regulation was challenged by industry, and EPA voluntarily withdrew  the regulation hi 1986.

        The proposed regulation analyzed hi this document will apply to  facilities that formulate, package,
and repackage pesticide chemicals.   An estimated 3,900  facilities engage hi this activity nationwide.
About 2,400 of these  facilities engage hi PFPR activities involving the 272 PAIs originally considered
for regulation, and therefore represent the population of PFPR facilities surveyed. The remaining facilities
use only PAIs beyond  these  272 PAIs.   For the proposed regulation,  EPA divided the existing
subcategory for these facilities into two subcategories:   (1) Subcategory C:   Pesticide Chemicals
Formulating, Packaging, and Repackaging (hereinafter, Subcategory, C or PFPR Facilities); and (2)
Subcategory  E:   Repackaging of Agricultural  Chemicals Performed at Refilling Establishments
(hereinafter, Subcategory E or Refilling Establishments). This rule is being proposed in accordance with
EPA's Effluent Guidelines Plan issued under Section 304(m) of the Clean Water Act.

1.1     Summary of the Proposed Regulation
        The regulations proposed hi this rulemaking include BPT, BAT and BCT, PSES, and NSPS and
PSNS, as summarized below.
                                              1.2

-------
       Best Practicable Control Technology (BPT)
       For the current Subcategory C (PFPR facilities), EPA proposes to not amend the existing zero
discharge BPT provisions, established hi 1978, with the exception of adding the word repackaging to the
title.  This change is being made to clarify the types of operations covered and does not expand the
current coverage of the BPT effluent limitations guidelines.

       A new Subcategory E is proposed to apply to the repackaging of agricultural chemicals at refilling
establishments. Zero discharge limitations apply to this new Subcategory.

       Best Available Technology Economically Achievable (BAT) and Best Conventional Pollutant
       Control Technology (BCT)
       Because BPT is based on zero discharge of wastewater pollutants and more stringent limitations
are not possible, BAT and BCT for both subcategories are set at zero discharge of wastewater pollutants.
Because the BAT and BCT limitations are set equivalent to the BPT zero discharge limitation and are
based on the same control technologies, no additional costs are required for compliance with BAT or
BCT.

       Pretreatment Standards for Existing Sources (PSES)
       For  both  Subcategory C, PFPR Facilities, and Subcategory E,  Refilling Establishments, the
Agency proposes  to establish PSES on the basis of zero discharge of wastewater pollutants. The best
available technologies identified as  a basis for these proposed standards consist of pollution prevention,
recycle and reuse of wastewater preceded, where necessary, by treatment of wastewater for recycle and
reuse.  As noted above* because no additional costs are expected for compliance  with BCT or BAT, the
primary focus of this economic impact analysis is  on the development and analysis of  impacts for
alternative PSES options.

       For PFPR Facilities  (Subcategory C), the proposed PSES regulation requires zero discharge of
all wastewater streams containing the pesticide active ingredients within the scope of this regulation with
one exception.  Specifically, hi its Regulatory Flexibility Analysis, EPA found  that the zero discharge
requirement was likely to impose disproportionate impacts among small business-owned facilities that
primarily serve the industrial/commercial market and that use certain lower toxicity sanitizer pesticide
                                              1.3

-------
 active ingredients (PAJs) to formulate, package and repackage sanitizer products.2  To mitigate expected
 impacts among these facilities, EPA decided not to  impose the zero discharge requirement for certain
 waste streams in facilities that formulate, package, or repackage sanitizer PAIs and whose sanitizer
 production is less than 265,000  pounds per year.3  In these facilities,  discharges from non-interior
 process wastewater sources (e.g., floor wash, exterior equipment cleaning, and laboratory rinsates) that
 contain only the designated sanitizer PAIs are exempt from the zero discharge requirement.  All other
 wastewaters at these facilities —   including those from  interior sources  (e.g., bulk tank rinsate,
 drum/shipping container rinsate, and ulterior equipment rinsate) or from non-interior sources that contain
 PAIs other than the designated sanitizer PAIs — are subject to the zero discharge requirement.

        For Refilling Establishments (Subcategory  E), the  zero discharge technology basis  for this
 proposal is secondary containment of bulk storage areas and loading pads, plus the collection and holding
 of rinsates, contaminated stormwater, and leaks and spills.  EPA's Office of Pesticide  Programs is
 proposing a regulation that will require refilling establishments for agricultural pesticides to build
 secondary containment  structures and loading pads to  certain specifications.  The Office of Water's
 regulatory proposal builds on this requirement.  Specifically, it requires that the contaminated stormwater,
 rinsates and leaks and spills that have been collected in secondary containment structures be held until
 they can be reused (e.g., applied as pesticide on a site compatible with the product label or used as make-
 up water in application of pesticide chemicals to an appropriate site).

        New Source Performance Standards (NSPS) and Pretreatment Standards for New Sources
        (PSNS)
        For both subcategories, NSPS and PSNS are being set based on zero discharge for  all new
 sources. In the case of sanitizer chemical facilities,  PSNS is more stringent than PSES by setting zero
 discharge of wastewater pollutants from both the interior and non-interior process wastewater sources.
 However, this greater stringency should not present a barrier to entry for new sanitizer chemical facilities.
    2For further details, see Chapter 5, Regulatory Flexibility Analysis.

    3See Table 8 of the regulation or Section 12 of the Technical Development Document (Development Document
for Best Available Technology, Pretreatment Technology, and New Source Performance Technology for the Pesticide
Formulating/Packaging/Repackaging Industry: Proposed) for a list of the sanitizer active ingredients that are eligible
for exemption from the zero discharge requirement under this regulation.

                                                1.4

-------
1.2    Selection of the Proposed Regulatory Options
       In the developing this regulatory proposal, EPA considered several regulatory options for the
Subcategory C and Subcategory E facilities.

       PFPR Facilities (Subcategory C)
       For PFPR Facilities, EPA initially considered five PSES technology options. Of these regulatory
options, Options 1 and 2 are not zero discharge options but involve treatment of wastewater and discharge
to POTWs. Options 3, 4, and 5 are all zero discharge options but, for the regulatory analysis, assume
different methods of compliance with differing costs and impacts:

       Option 1 consists of end-of-pipe treatment for the entire wastewater volume now generated by
       PFPR facilities through the Universal Treatment System4 and discharge to POTWs.

       Option 2 adds pollution prevention by  recycling wastewaters  generated from cleaning the
       interiors of formulating and packaging equipment, and raw material and shipping containers into
       the product to recover product value in the wastewaters. Other wastewaters are still expected to
       be treated through the Universal Treatment System and discharged to POTWs.

       Option 3 is based on the same technology and pollution prevention practices as Option 2 except
       that zero discharge of all process wastewater would be achieved by recycling the wastewater back
       to  the facility after treatment through the Universal Treatment System.

       Option  4 incorporates the pollution prevention aspects  of Options  2 and  3, but instead of
       treatment, adds off-site disposal to an incinerator of the rest of the wastewater.

        Option 5 assumes disposal of all wastewater through off-site incineration.

        EPA analyzed the compliance costs and industry impacts for these options on the basis of facility
 and compliance cost data assuming use and control of a set of 272 PAIs.  These 272 PAIs are the same
    4T'he Universal Treatment System consists of chemical emulsion breaking, hydrolysis, chemical oxidation,
 sulfide precipitation and activated carbon filtration treatment technologies.

                                               1.5

-------
 as those PAIs whose discharges were originally considered for regulation under the recently promulgated
 effluent limitation guideline for the Pesticide Manufacturers Industry.  From this analysis, EPA initially
 considered Option 3 to be the basis for Pretreatment Standards for Existing Sources for PFPR Facilities
 (Subcategory Q.  This option provides a PSES limitation that is consistent with requirements for direct
 dischargers.  In addition, the compliance costs and facility impacts estimated for this  option were the
 lowest, with Option 2, of the five options analyzed. However, unlike Option 2,  Option 3 more strongly
 promotes the objectives of the Clean Water Act by achieving zero discharge of specified pollutants from
 PFPR facilities.  Specifically, Option 3 embodies Best Available Technology Economically Achievable
 (BAT) by incorporating the best practices of pollution prevention, recycle/reuse, and water conservation
 applicable to this subcategory. Specifically, Option 3 embodies Best Available Technology Economically
 Achievable (BAT), incorporating the best practices of pollution prevention, recycle/reuse, and water
 conservation applicable to this subcategory. In addition, Option 3 achieves greater pollutant removals
 than Options 1 and 2 and the same quantity of removals as Options 4 and 5, but at a much lower cost.
 EPA also found that Option 3  is also the most cost-effective of the five options.  From the economic
 impact analysis, EPA found that Option 3 was both economically achievable and met the objectives of
 the Clean Water Act by achieving zero discharge of specified pollutants from PFPR facilities.

        In the course of its Regulatory Flexibility Analysis, however, EPA found that the zero discharge
 requirement of Option 3 would disproportionately affect certain PFPR facilities that produce "sanitizer"
 products and are primarily owned by small businesses.  These small impacted facilities were also found
 to  differ from  other PFPR  facilities by  their relatively  high  degree of participation  in  the
 institutional/commercial market and their relatively low share of total revenue from PFPR activities.  On
 the basis of these distinguishing characteristics, EPA defined a modification to Option 3, namely Option
 3/S, as the preferred regulatory alternative.  Option 3/S corresponds to Option 3 except that certain non-
 interior source wastewater streams are exempted from the regulatory requirements. Specifically, for those
 facilities that formulate, package, or repackage sanitizer  active ingredients and whose sanitizer production
 is less than 265,000 pounds per year, the zero  discharge requirement would not apply to physically
separate, non-interior \vastewater streams that contain only designated sanitizer PAIs. These non-interior
                                          »
wastewater streams include exterior equipment and floor wash, leak and spill cleanup, safety equipment
rinsate, contaminated  precipitation run-off, laboratory wastewater, air pollution control wastewater, and
DOT test bath water.  The zero discharge requirement would apply to the interior wastewater streams
                                              1.6

-------
of these facilities including discharge from cleaning the interiors of drum/shipping containers, bulk
containers, and other equipment.

       In addition, EPA decided to include under the PSES regulation all additional PAIs beyond the
list of 272 PAIs on which the initial options analysis and selection were based.  EPA conducted additional.
economic impact and cost-effectiveness  analyses of the selected option including  regulation of these
additional PAIs, referred to as additional non-272 PAIs. To distinguish the analysis  and findings for the
regulatory option including coverage of the additional non-272 PAIs from the analysis of Option 3/S
based on only the 272 PAIs, this document refers to the regulation including  coverage of the additional
non-272 PAIs as Option 3/S'.

        Although EPA's analyses indicated somewhat larger economic impacts as a result of including
these additional PAIs under regulation, EPA found that the Option 3/S' regulation remains economically
achievable and, by virtue of including the additional PAIs under regulation, would promote more strongly
the pollution reduction objectives of the Clean Water Act. Overall, Option 3/S' achieves a substantially
greater reduction in pollutant discharges than both the initially selected Option 3 and the revised Option
3/S, which includes the sanitizer PAI exemption.  The total estimated reduction  in discharges  under
Option 3/S' amounts to approximately 310,000 pounds annually, or approximately 175 percent more than
the reduced discharges estimated for the options that regulate only the original 272 PAIs (about 112,000
pounds).  Moreover, because Option 3/S' retains the exemption for certain sanitizer PAI waste streams,
it results in relatively minor economic impacts among the small business-owned, sanitizer facilities that
EPA had found to incur disproportionate impacts because of the uniform zero discharge requirement.
The exemption for these waste streams excludes from compliance requirements very  small quantity of
pollutant discharges containing the exempted sanitizer PAIs, 1,036 pounds annually. Because the sanitizer
PAIs generally have low toxicity, the estimated residual discharges amount to only 196 toxic-weighted
pounds annually when the residual discharges are adjusted for relative toxicity.  In contrast, EPA
estimates that the pre-compliance discharges, adjusted for toxicity, amount  to nearly 34 million toxic-
 weighted pounds  annually.5   Accordingly, the residual discharges,  adjusted for  toxicity,  are an
    5EPA estimates that the total 310,455 pounds of removals for Option 3/S' translate into total toxic-weighted
 removals of 33,747,863 toxic-weighted pounds (see the Cost-Effectiveness Analysis report for information regarding
 toxic-weighted removal calculations and the unweighted and weighted removals achieved by the various regulatory
 options).
                                                1.7

-------
 insignificant fraction of the pre-compliance amount.  On balance, EPA considers Option 3/S' the superior
 alternative among the regulatory options considered.

        Refilling Establishments
        For Refilling Establishments (Subcategory E facilities), EPA developed two viable regulatory
 options, both embodying a zero discharge requirement. Option 1 achieves zero discharge through storage
 of wastewater collected from secondary containment structures for use as make-up water in pesticide
 applications.   Option 2  achieves zero discharge through collection  of wastewater from secondary
 containment followed by contract hauling for off-site incineration.  The Agency proposes Option 1.

 1.3    Structure of the Economic Impact Analysis
        This EIA describes both the methodology employed to assess impacts of the proposed rules and
 the results of the analyses.  The overall structure of the impact analysis  is summarized in Figure 1.1.
 The two main inputs to the analysis are: (1) data on industry baseline financial and operating conditions,
 and (2) projected costs of complying with the proposed regulations.  The industry baseline financial and
 operating data are based principally on the Pesticide Formulating, Packaging, and Repackaging Facility
 Survey for 1988 conducted under Section 308 of the Clean Water Act.6  The Survey, which requested
 facility-level data, was divided into three parts.  The Introduction requested general facility information
 such as facility address and SIC code, as well as information to determine whether analysis of the facility
 should proceed:  for example, business status of the facility and confirmation of the PAIs  formulated,
 packaged, or repackaged by the facility (See Appendix A). Part A of the Survey requested technical data,
 and Part B requested economic and financial data.

        The Survey was sent to a total of 708 facilities. Of these, 610 were randomly selected  from
 3,241  facilities that were identified in the FIFRA and TSCA Enforcement System (FATES) as holding
product registrations  containing one or more of the 272 PAIs initially considered for regulation.  In
 addition, EPA sent questionnaires to 92  pesticide manufacturing facilities identified  by the  Pesticide
    Baseline conditions also include certain costs deemed necessary to comply with particular regulations imposed
under the Resource Conservation and Recovery Act (RCRA), the effluent guidelines for the Organic Chemicals,
Plastics, and Synthetic Fibers (OCPSF) Industry, FIERA maintenance fee requirements, and effluent guidelines for
the pesticide manufacturing industry.  Parts of these regulations took effect after the base year of the Survey, and
imposed costs on certain PFPR facilities. These costs are included in the analysis.
                                               1.8

-------
Manufacturing Census conducted by EPA in 1988, on the premise that they might also conduct PFPR
activities.  Also, six voluntary or pretest questionnaires were submitted.

       The second major input to the analysis is the projected costs of compliance with the regulatory
options. These cost estimates were developed by the EPA. Details on the compliance cost estimates can,
be found in the Technical Development Document for the proposed rule.  Additional information on all
data sources is presented in Chapter 2.

       To evaluate the expected impacts of the regulatory options, six measures of impact are examined
in the EIA:

•      Impacts on facilities that formulate, package,  or repackage pesticides containing PAIs covered
       by the regulation;

•      Impacts on PFPR facilities owned by small businesses;

•      Employment losses and associated community effects;

•      Impacts on the U.S. balance of trade;

•      Impacts on firms owning one or more PFPR facilities expected to incur compliance costs; and

•      Effects on the construction of new facilities and expansion of existing facilities.

       The EIA methodology relies foremost on a facility-level impact analysis.  The results from this
analysis drive the other components  of the EIA (See Figure 1.1.)  The facility-level economic model
estimates post-compliance revenues, costs, and profits. The post-compliance financial data are then used
to analyze three potential effects of the increased costs on facilities: facility closure, conversion of PFPR
                                              1.9

-------
product lines to alternate non-pesticide FPR activities, and compliance costs in excess of five percent of
facility revenue.7
                                             Figure 1.1
              Economic Impact Analysis of Pesticides Formulating/Packaging/Repackaging
                   Industry Effluent Limitations Guidelines: Analytic Components
                                     Key Analytical Components
Analytical Outputs
        The analysis of facility closure is based on comparing the post-compliance facility cash flow to
the baseline cash flow.   The  product line conversion analysis compares the return on assets (ROA)
    In contrast to facility closures and product line conversions, compliance costs in excess of five percent of
facility revenue are assumed not to lead to an operational change at a facility. Compliance costs that are less than
five percent of facility revenue are commonly judged to be economically achievable (see, for example, the EIAs
for effluent limitations for the OCPSF and pesticide manufacturing industries).  Compliance costs equal to five
percent or more of facility revenue, however, do not necessarily indicate a moderate impact.
                                               1.10

-------
achieved post-compliance to the ROA that facilities are expected to be able to earn hi alternative
formulating, packaging, or repackaging activities.

       An additional potential impact of the regulation, evaluated using the results of the facility analysis,
is  the impact on small businesses, which is performed hi accordance with the requirements of the
Regulatory Flexibility Act.  This analysis has two steps.  First, it is determined whether the regulation
is expected to impact a substantial number of small businesses significantly.  Impacts are defined as either
a facility closure, a product line conversion, or compliance costs equal to five percent or more of facility
revenue. Second, if a substantial number of small businesses are projected to sustain significant impacts,
alternative regulatory methods that mitigate or eliminate the economic impacts on small businesses are
examined.  As noted above, the Regulatory Flexibility Analysis provided the basis for developing the
preferred regulatory option, which exempts certain waste streams containing only designated sanitizer
chemicals from the zero discharge requirement and thus benefits typically small business-owned facilities
operating in the institutional/commercial market.

        The facility-level impact analysis drives the analysis of other, secondary impacts, including those
on local communities and foreign trade. Community impacts are assessed on the basis of the employment
loss expected to result from facility closures or PFPR line conversions, taking into account both primary
employment effects in the PFPR industry and secondary employment effects in linked industries and in
consumer-oriented retail and service industries.  The significance of the employment loss is evaluated by
its effect on total community employment.

        Foreign trade impacts may result from changes in the domestic production of pesticides, because
pesticides are traded internationally.  Changes in the balance of trade are calculated based  on both the
estimated decreases in exported production and the increases hi pesticide imports that result from meeting
regulatory requirements. The expected change in net exports (i.e., exports minus imports) is compared
with the baseline (1988) trade balance for the entire pesticide industry, and with average year-to-year
fluctuations in the pesticide products trade balance, to measure the significance of the change.
        EPA also performed a firm-level impact analysis, which amis at understanding whether the firms
 owning PFPR facilities are capable of financing the investments needed to comply with the proposed
 regulation.  Because of sample design issues, the results from this analysis cannot be extrapolated to the

                                               1.11

-------
population of PFPR facilities. However, for those firms that own facilities in the PFPR industry Survey,
the firm-level analysis accounts for compliance costs both in sample facilities and in other PFPR facilities
not included in the sample. The test of financial impact on these firms is based on the change in pre-tax
return on assets resulting from compliance with the PFPR regulation.

       Finally, impacts of the PSNS and NSPS regulations on new sources of pesticide production are
evaluated.

       In addition to these impact-related analyses, the EIA includes two other analyses pertaining to
potential offsets to the costs and economic impacts of the proposed regulations for the PFPR industry.
Specifically, EPA analyzed potential cost-savings from use of pollution prevention as a means of
complying with the proposed regulation. The cost savings from reduced waste management and disposal
costs were directly accounted for in estimating the costs of complying with the various regulatory options
that incorporate pollution prevention practices. However, certain additional cost savings — from reduced
water use, recovery and reuse of PAIs  in wastewaters, reduced permitting-related costs, and reduced
insurance and cost of capital —  were not  recognized in the regulatory cost analyses.  To the extent
possible, EPA quantified these potential additional savings and examined qualitatively the potential savings
in categories that were unable to be quantified. In addition, this analysis  addresses longer term economic
and regulatory environment factors  that may cause contract hauling  and incineration to be more costly
compliance options hi the future.

       EPA also recognized  that  the  manufacturing, installation,  and operation of equipment and
processes for complying with the PFPR regulation would generate labor needs.  To the extent that these
labor needs translate into  employment increases hi complying firms, the regulation has the potential to
generate employment benefits that'may partially offset employment losses that are expected to occur in
facilities impacted by the rule.  Accordingly, EPA analyzed the labor requirements for complying with
the proposed  regulatory option.  This  analysis  is based  on the expected contribution from labor in
manufacturing, installing and  operating compliance equipment and accounts for both primary labor
requirements  in directly  affected industries  and secondary labor needs in linked industries and in
consumer-oriented retail and service industries.
                                              1.12

-------
1.4    Organization of the Economic Impact Analysis Report
       The remaining parts of the Economic Impact Analysis Report are organized as follows.  The
following chapter, Chapter 2, presents a description of the data sources consulted for this EIA. Chapter 3
profiles the pesticide formulating, packaging, and repackaging industry, examining the industry segments
involved in pesticide formulating, packaging, and repackaging, and the prevailing market conditions for
pesticide products.

       Following the background material in Chapters 2 and 3,  Chapters 4 through 9 each describe the
data and methodology used to estimate one type of potential impact  and the resulting impact estimates.
The analysis presented hi these chapters is based on the 272 PAIs originally  studied for regulation.
Chapter 4 details the  methodology used to estimate facility impacts. As stated  above, facility impacts
provide the methodological foundation for this EIA.  First defined are the markets to be analyzed and the
basic model of market structure.  Baseline and post-compliance costs and after-tax cash flows are then
estimated.  This chapter also describes the analyses of facility closures, product line conversions, and
compliance costs in excess of five percent of facility revenue.

        Chapter 5 presents the small business impact and Regulatory Flexibility Analysis. Chapter 6
describes the methodology for and results of the community impact analysis, based on the results of the
facility analysis.   Methods for estimating  international trade  effects,  and the expected effects, are
described in Chapter 7.  Chapter 8 assesses firm-level financial impacts for firms owning one or more
PFPR facilities that are expected to  incur costs in complying with the proposed regulation. Chapter 9
describes the expected effects of the regulation on new PFPR facilities.

        Chapter 10 contains  the analysis of potential cost savings to PFPR facilities that use pollution
prevention in complying with the proppsed regulation.  Chapter 11 presents the  analysis of the potential
labor requirements for complying with the PFPR regulation.

        Chapter 12 assesses the economic impacts of including under the proposed PSES regulation the
 additional PAIs that were not on the original list of 272  PAIs. This chapter applies essentially the same
 methodologies described in the preceding chapters to estimate the economic impacts of complying with
 the proposed regulation with its scope of regulatory coverage expanded to include the additional non-272
 PAIs.   The chapter  addresses impacts on PFPR facilities, community employment, the  pesticides
                                               1.13

-------
international trade balance, and firm financial performance.   The chapter also reviews the regulatory
flexibility considerations and assesses the compliance labor requirements of expanding the regulation to
include the additional PAIs.  •

       The report includes six appendices.  The first appendix, Appendix A, contains the Section 308
Survey of pesticide formulating, packaging, and repackaging facilities.  The second appendix presents
the mapping of PAIs into  clusters.  Appendix C documents the methodology  for calculating price
elasticities of demand for PAI clusters. Appendix D presents annualized compliance costs as a percentage
of facility revenue for those facilities projected to close in the baseline scenario.  Appendix E provides
the results of a sensitivity analysis of  return on assets used as the basis to estimate product  line
conversions.  Appendix F  estimates significant economic impacts  assuming partial pass-through of
compliance costs.
                                              1.14

-------
                                         Chapter 2
                                        Data Sources
       This EIA employs data from many sources at differing levels of aggregation.  The various sources
used are described below.

       The Pesticide Formulating, Packaging, and Repackaging Facility Survey for 1988, a survey of
pesticide formulating, packaging, and repackaging (PFPR) facilities conducted under Section 308 of the
Clean Water Act,1 is  the  principal  source of the  facility-level data.   EPA sent the  questionnaire,
requesting both technical and economic information, to a stratified sample of 707 facilities representing
3,241 facilities in the population.  Part A of the Survey questionnaire requested the data necessary to
perform the technical and treatment cost estimation analysis, including PAI-specific use for 1988.  Part
B of the Survey questionnaire requested detailed economic and financial data, including balance sheet and
income statement information for 1986, 1987, and 1988.  Three years of data were collected so that EPA
could construct a "typical" year on which to base the impact analysis.  A copy of Part B of the Survey
is included as Appendix A.  A copy of Part A of the Survey can be found in the Public  Record.
Throughout the remainder of this document, the term "Survey", if not further specified, will refer to
Part B of the Pesticide Formulating, Packaging, and Repackaging Facility Survey for 1988.

       Mandatory reporting of yearly pesticide production is required by the  Federal Insecticide,
Fungicide, and Rodenticide Act (FIFRA) as part of the pesticide regulation process.  Pesticide-producing
establishments, including formulating, packaging, or repackaging facilities, are  required to provide
information to EPA oh registered pesticide products, such as product registration numbers, product
classification, type and use,  and production rates.  These data are submitted as part of the "Pesticide
Report for Pesticide-Producing Establishments" (EPA Form 3540-16) and are stored in the FIFRA and
TSCA (Toxic Substances Control Act) Enforcement System (FATES) database, which is administered
by EPA's  Office of Prevention, Pesticides and Toxic  Substances (OPPTS).  Accessing the OPPTS
database gave the population data from which the stratified random sample of formulating, packaging,
and repackaging  facilities was drawn.  The databases for the more recent years of  1988-1991 were also
    federal Water Pollution Control Act, 33 U.S.C. 1318.
                                              2.1

-------
accessed to identify any changes in the composition of the industry and to evaluate the applicability of
the proposed regulation.

       The other major data input to the EIA was the estimated compliance costs of the regulation.2
EPA initially considered compliance costs under five regulatory options: Option 1, a Treat and Discharge
Option;  Option 2, a Treat and Discharge with Pollution Prevention Option; Option 3, a Zero Discharge
Based on Treatment and Reuse with Pollution Prevention Option; Option 4, a Zero Discharge Based on
Pollution Prevention and Off-Site Incineration Option; and Option 5, a Zero Discharge Based on Off-Site
Incineration Option. EPA concluded that Option 3 provided the best regulatory approach among these
five options, but also  found that it caused disproportionate impacts hi certain small business-owned
facilities. On the basis of distinct market, technical, and PAI-use characteristics of these facilities, EPA
later defined and analyzed an additional regulatory option for sanitizer chemicals.  This option, called
Option 3/S, corresponds to Option 3 discussed above, but exempts physically separate, exterior-source
wastewater that contains only sanitizer chemicals in facilities with less than 265,000 pounds per year of
production involving sanitizer PAIs. In addition, EPA decided to extend the coverage of Option 3/S from
the 272 PAIs originally studied for regulation to all PAIs (except sodium hypochlorite).  This extended
option, called Option 3/S', is based on the same treatment and reuse with pollution prevention technology
as Option 3/S.

        Two categories  of  compliance costs  associated with pesticide formulating, packaging, and
repackaging were evaluated for each option:  capital costs and operating  and maintenance costs.  All
compliance cost estimates are presented in 1988 dollars, and are based on the assumption that whenever
possible, facilities will build on existing treatment.

        The Survey database and the compliance cost estimates provided the basis for all the impact
analyses in this EIA, including impacts on facilities, small businesses,  communities, foreign trade and
new sources.  EPA also used data from secondary sources in each of the  chapters.  The profile of the
PFPR industry relied  on various issues of Industrial Outlook, published by the International Trade
Administration of the U.S. Department of Commerce, and the Census of Manufactures published by the
Bureau of the Census within the Commerce Department.  These documents provided aggregate industry
    2Full details of the compliance cost estimates can be found in the Technical Development Document.

                                               2.2

-------
data.  The profile also used aggregate import and export data from the United Nations' International
Trade Statistics Yearbook.  Pesticide Industry Sales and Usage, published by EPA's Office of Pesticides
and Toxic Substances, provided market expenditures and global sales for pesticides.

       The facility impact analysis used aggregate financial statistics from Robert Morris Associates'
Annual Statement Studies, and interest rate data from the Federal Reserve Bulletin and Standard and
Poor's Price Index Record. Historical inflation rates were obtained the Statistical Abstract of the United
States, published by the Bureau of the Census.  Estimated costs that facilities would have incurred after
the Survey due to subsequent federal pollution control, regulations were obtained from the respective
rulemaking packages.  These include Resource Conservation and Recovery Act (RCRA)  land disposal
restrictions (40 CFR 268), effluent limitations for the Organic Chemicals, Plastics and Synthetic Fibers
(OCPSF) industry (40 CFR 414), and effluent limitations for the Pesticide Manufacturing Industry (40
CFR 455).  In addition, facility-specific costs due to FIFRA maintenance fees were estimated.

        Data from EPA's Office of Pesticide Programs  (OPP) served as the basis for determining the
substitutability among PAIs.  In 1980, the OPP defined pesticide markets to ensure that EPA reviewed
competing products on roughly the same schedule, so that one pesticide does not have an unfair advantage
over another.  The pesticide markets were defined as clusters of PAIs that are substitutes for a specific
end use.  This classification was adapted and used as the basis for defining pesticide markets in this EIA
 (see Appendix B).

        The regulatory flexibility analysis of  impacts on small businesses and the firm-level analysis
 required data from Dun and Bradstreet's Million Dollar Directory to calculate the number of employees
 at the firm level. The community impact analysis relied on population data from 1992 County and City
 Extra: Annual Metro, City and County Data Book, published by Brennan Press, and the 1990 Census
 of Population and Housing, published by the Bureau  of the Census.   In addition, to estimate the
 aggregate community-level employment impacts stemming from PFPR facility employment losses, EPA
 used industry-specific regional employment multipliers provided by the Bureau of Economic Analysis hi
 the Department of Commerce.  These multipliers are  documented in Regional Multipliers:  A User
 Handbook for the Regional Input-Output Modeling System (RIMS II), Department of Commerce, 1992.
 The foreign trade analysis used import data from the OPP and data on the U.S. trade balance from the
 International Trade Statistics Yearbook and the Statistical Abstract of the United States.

                                               2.3

-------
       The chapter on the economic benefits of pollution prevention used secondary price data from the
Annual Market Study published by Doane Marketing Research, as well as from telephone interviews with
pesticide manufacturers  and data from the OPP.   The OPP maintains PAI-specific price data from a
number of proprietary sources.  The OPP data were among those used to estimate PAI prices, which in
turn were used to estimate the value of the PAIs recovered due to pollution prevention practices.  Data
from Ernst and Young's National Water and Wastewater 1992 Rate Survey were used to calculate savings
due to the recycle/reuse  of wastewater containing PAIs.

       Data  sources  for  the  labor requirements  analysis chapter include total labor contribution
coefficients from the direct requirements matrix of the national input-output tables.  These coefficients
were used to estimate the labor required for manufacturing, installing, and operating the equipment
needed to comply with the proposed PFPR regulation and are documented in The 1982 Benchmark Input-
Output Accounts of the United States, U.S. Department of Commerce,  1991.  The purchase price for
compliance equipment, and the costs of equipment installation and operation were estimated by EPA
project engineers.   The labor requirements analysis also  used a range of employment multipliers to
estimate the aggregate labor requirements  that might result from the manufacturing, installation, and
operation of compliance equipment.  These multipliers were obtained from several sources including
internal EPA publications analyzing employment effects of pollution control outlays and a publication of
the National Utility Contractors Association, A Report on Clean Water Investment and Job Creation,
1992.
                                             2.4

-------
                                         Chapter 3
                         Profile of the Pesticides Formulating,
                         Packaging, and Repackaging Industry
3.0    Introduction
       This industry profile describes the services, products, facilities,  and firms associated with the
formulating, packaging, and repackaging of pesticide active ingredients (PAIs). It is intended to provide
insight into industry's reaction to the proposed effluent guidelines through a discussion of historical and
current market conditions  and the structure and  financial  condition of the industry.   In addition,
information on  employment,  foreign trade,  and facility size  are provided  to  aid  the reader in
understanding the community, foreign trade, and small business impact analyses presented in subsequent
chapters.

        The six sections of this chapter focus on pesticide formulators, packagers, and repackages
(PFPR), but some of the information presented also pertains to manufacturers  of PAIs.   Section 3.1
provides an overview  of the PFPR industry.  Section 3.2 describes the PFPR  industry structure and
includes a discussion of pesticide markets and foreign trade. Market demand is discussed in Section 3.3.
Section 3.4 evaluates the pesticide market years on which the analysis is based to broader market patterns.
Section 3.5 presents an analysis of subgroups of PFPR  facilities and  Section 3.6 concludes with a
summary of the information presented in the profile.

3.1     Industry Overview
        Description of Pesticide Formulating, Packaging and Repackaging Activities
        Classifications of Formulated Pesticide Products
        The Federal Insecticide, Fungicide and Rodenticide Act (FIFRA) defines a pesticide as "(1) any
substance or mixture of substances intended for preventing, destroying, repelling or mitigating any pest,
(2) any substance or mixture of substances intended for use as a plant regulator, defoliant or desiccant."
Section 2(t) of FIFRA  defines a 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  microorganism (except
viruses, bacteria, or other microorganisms on  or in  living man or other  living animals) which the
 administrator declares  to be a pest under Section 25(c)(l)."
                                               3.1

-------
        Pesticides are most commonly categorized by the type of pest they treat, such as bacteria, fungi,
 rodents,  weeds, or insects.  The majority of domestic pesticide production falls into  three classes:
 herbicides, insecticides, and fungicides.  Herbicides are used to control, prevent, or eliminate weeds;
 insecticides are used to prevent or destroy insects; and fungicides are used to control or eliminate bacteria
 and fungi.  These classifications, as well as some of the less common pesticide classifications, are listed
 in Table  3.1.   Herbicides sales dominated sales of any other pesticide type in U.S. markets as well as
 worldwide in 1988, with sales comprising 56 percent of the U.S. pesticide market and 42  percent of the
 world pesticide market.  Insecticides ranked second, comprising 24 percent of the U.S. pesticide market
 and 33 percent of the world pesticide market.  Fungicides ranked third in sales  in both the U.S. and
 world pesticide markets, with sales percentages of 12 percent and 19 percent, respectively.  Each of these
 major pesticide classifications was produced and consumed more heavily than all the smaller pesticide
 product groups combined (see Figure 3.1).1

        In 1980, EPA's Office of Pesticide Programs (OPP) classified pesticides further into cluster
 groups based on their major use to ensure that EPA regulated competing pesticides on roughly the same
 schedule. Six hundred pesticides were classified into 48 clusters according to the major use of the active
 ingredients.  For instance, all herbicides used on corn production were classified into the  same cluster.
 Each cluster therefore contains pesticides that may be roughly substituted for one  another in major end
 use activities.

        The Office of Water's Economic Impact Analysis of Final Effluent Limitations Guidelines and
 Standards for the Pesticide Manufacturing Industry classified PAIs as belonging to  one or more of these
 clusters.2 The Office of Water used OPP's cluster segmentation to define individual markets for groups
 of pesticides because economic variables, such as  demand elasticity, would not  be  meaningful for a
 market defined as all pesticides.  The Office of Water expanded upon OPP's cluster segmentation in three
 ways. First, PAIs registered after  1980 were assigned to one of the 48 clusters.  Second, the 48 clusters
 were expanded to 57 clusters, based upon differences in the sensitivity of product demand to changes in
    1 Pesticide Industry Sales and Usage: 1988 Market Estimates, U.S. EPA, Office of Pesticides and Toxic
Substances, February 1988.

    2U.S. Environmental Protection Agency, Economic Impact Analysis of Final Effluent Limitations Guidelines and
Standards for the Pesticide Manufacturing Industry, September 1993.
                                              3.2

-------
Representative Classes of
Class
Acaricide
Algicide
Attractant
Avicide
Bactericide
Defoliant
Dessicant
Fungicide
Growth regulator
Herbicide
Industrial Microbiocide
Insecticide
Miticide
Molluscicide
Nematicide
Piscicide
Predacide
Repellents
Rodenticide
Silvicide
Slimicide
Sterliants
Source: Minnesota Department of Agriculture,
Table 3.1
Pesticides and the Pests They Control
Target Pest
Mites, ticks
Algae
Insects, birds, other animals
Birds
Bacteria
Unwanted plant leaves
Unwanted plant tops
Fungi
Insect and plant growth
Weeds
Microorganisms
Insects
Mites
Snails, slugs
Nematodes
Fish
Carnivorous animals
Insects, birds, .other animals
Rodents
Trees and woody vegetation
Slime molds
Insects, other animals
Rinse and Win Brochure, 1989.
3.3

-------
                                               Figure 3.1
                             1988 Pesticide Sales In the U.S. and World Markets
                                     Insecticides
                                     Herbicides
 Fungicides
 Other Pesticides
                        $0.6
                        12.0%
                                        $1.2
                                        24.0%
$3.5
19.0%
                     $6.1
                     33.0%
                   56.0%
                                                           $7.7
                                                               42.0%
           U.S. Market (In $ Billions) Total - $4.9 Billion   World Market (In $ Billions) Total - $18.5 Billion
                     Source: Pesticides Industry Sales and Usage, 1988 Market Estimates,
                     U.S. EPA, Office of Pesticide Programs, December, 1989
price (see Table 3.2).3  In addition, although OPP's cluster segmentation assigned each PAI to only one
cluster, the Office of Water allowed for a PAI to be assigned to more than one cluster if it had more than
one important use.


        The data sources for this chapter use assorted classifications in reporting on the PFPR industry.
Bureau of the Census data for the PFPR industry fall in two standard industrial classification (SIC) codes:
1)  SIC 2879,  establishments engaged  primarily  in the manufacture  or formulation of agricultural
chemicals not elsewhere classified, and the formulation and preparation of pesticides and 2) SIC 5191,
establishments engaged primarily in the distribution of animal feeds, fertilizers, agricultural chemicals,
    3 Clusters were split when (1) there was a wide variety of price elasticities of demand among PAIs within a
cluster, and (2) the PAIs among which demand elasticity varied had distinctive uses.  For example, the cluster that
encompasses herbicides used on fruit trees was split into three clusters: herbicides used on grapes, herbicides used
on oranges, and herbicides used on fruit trees (excluding grapes  and oranges).  See Appendix C of the Economic
Impact Analysis of Final Effluent Limitations Guidelines and Standards for the Pesticide Manufacturing Industry for
further details. Also, one cluster, was split since the Pesticide Manufacturing Effluent Limitation Guidelines were
promulgated (for a total of 57 clusters) to distinguish the distinct uses of sporicidal vs. non-sporicidal disinfectants.
                                                  3.4

-------
Table 3.2
Pesticide Clusters
Cluster

H-l
H-2
H-3
H-4
H-5a
H-5b
H-5c
H-6
H-7
H-8
H-9a
H-9b
H-10
'
Primary Application
Herbicides tlSed Cft:
Broad spectrum of uses
Corn
Soybeans, cotton, peanuts, alfalfa
Sorghum, rice, & small -grains
Oranges
Grapes
Fruit trees
Sugarbeets, beans & peas
Drainage ditches, rights of way, forestry & ponds
Turf
Vegetables
Tobacco
Unclassified uses
lnnHct5nirf«« used on/fer/as* 	
I-la
I-lb
I-2a
I-2b
1-3
I-4a
I-4b
1-5
1-6
1-7
1-8
1-9
1-10
1-11
1-12
1-13
Cotton
Soybeans, peanuts, wheat & tobacco
Corn & alfalfa
Sorghum
Fruit, & nut trees, excluding oranges & grapes
Oranges
Grapes
Vegetables ,s
Livestock & domestic animals
Non-agricultural sites (as repellent)
Domestic bug control & for food processing plants
j >
Cluster
Primary Application
Blnfiicldefc W** 
-------
  pesticides,  seeds  and other farm supplies, except grains.4  The U.N.  International Trade  Statistics
  Yearbook classifies pesticides into disinfectants, insecticides, fungicides, and herbicides for retail sale as
  either preparations or PAIs.  The profile also relies on data from the U.S. EPA Formulating, Packaging,
  and Repackaging Survey for 1988 (See Chapter 2).  Data from this survey were aggregated to prevent
  disclosure of confidential business information.  For ease of reading, this chapter reports Survey data
  extrapolated to the entire PFPR population and does not report data for the sample.

         Overview of the Services and Products Provided by the Industry
         The pesticide industry is vertically integrated into two major segments: pesticide manufacturing
  and PFPR.   Pesticide manufacturers produce PAIs.  The PAIs are not directly used in pest control;
  instead they are combined with solid, liquid and/or gaseous diluents through the process of formulating.
  The PFPR Survey defines formulation as the process of "mixing, blending, or diluting one or more active
  ingredients with one or more other pesticide active or inert ingredients, without a chemical reaction that
  converts one active ingredient to another active ingredient, to obtain a manufacturing use product or an
  end use product."  Packagers prepare pesticide formulations for distribution by packaging the product in
 plastic, glass, paperboard, or metal containers.  Repackagers transfer pesticide products or PAIs, usually
 from large tanks to smaller containers for use hi consumer markets. In the PFPR Survey, packaging is
 defined  as "enclosing or placing formulated pesticide active ingredients into marketable containers,"
 while repackaging is defined as  "the direct transference of a single pesticide  active ingredient or single
 formulation  from any marketable container to another marketable container without intentionally mixing
 in any inert, diluents, solvents, or other active ingredients, or other material of any sort." Thus, PFPR
 involves the conversion of PAIs into easy-to-use products at weaker concentrations packaged for the
 distributor and/or end user.
        Marketable pesticide products  are  available  hi  solvent-based formulations, water-based
formulations, and solid-based formulations.  Solvent- and water-based products are applied directly as
a liquid or as an aerosol.  These wet formulations can take the form of suspensions or emulsions.  Solid-
based formulations encompass many types of pesticide products.  Some are prepared by blending solid
active ingredients with inert solids such as clay and sand. Other solid-based pesticide formulations have
     SIC 5191 captures the majority of the facilities that are engaged exclusively in the repackaging of pesticide
products into refillable containers for agricultural use and, therefore, is used hi conjunction with SIC 2879 to define
the PEPR industry throughout this profile.
                                               3.6

-------
liquid active ingredients absorbed by dry carrier materials.  These dry pesticide products can include a
wide variety of powders, dusts, granules, and pellets.  The chemical nature of the PAI, in part, dictates
whether a formulation will be wet or dry.   Active ingredients that are not soluble in water or solvents
require dry formulations.  In addition, consumer preferences can dictate whether pesticide formulations
are wet or dry when applied.

       Overview ofPFPR Production Processes
       The PFPR production processes  involve the dilution of the  highly concentrated PAIs  for
packaging, potential repackaging, and eventual distribution.  Pesticide formulation entails the blending
of PAIs  with a variety of substances, but does not include processes hi which chemical reactions or
separations occur.  Formulators combine PAIs with inert diluents, inorganic carriers,  stabilizers,
emulsifiers, aerosol propellants, wetting agents and other pesticide formulations. In addition, formulating
operations can include particle size reduction, such as milling and coating processes for granule  and
treated seed production.

        The apparatus used in  pesticide formulation is conventional blending equipment.   Liquid
formulations require tanks equipped with mixers, and solid formulations need blending mills. Secondary
equipment  includes pumps, hoppers, conveyers, storage  tanks, and  rotary kilns  for curing solid
formulations.  Solids blending mill capacities vary from several hundred pounds to three tons. Mixing
tank capacity for liquid formulations varies from less than 100 gallons to several thousand gallons.5

        Pesticide  packaging generally occurs  at the same  facility where formulating is conducted.
Combining these activities at one location enables facilities to avoid the cost associated with transporting
the high volume,  dilute formulations.  Packaging typically consists of pouring liquid formulations  into
55-gallon drums,  glass bottles, pails, or other containers for shipping.  Solid formulations are usually
gravity-collected from hoppers into drums or paper bags for distribution.

        Repackaging  of pesticides  involves  transferring formulations  from  storage tanks to smaller
 containers for  consumer use.   Repackagers  typically use a bulk storage tank to  hold the pesticide
    5 Guides to Pollution Prevention: The Pesticide Formulating Industry, U.S. EPA, Risk Reduction Engineering
 Laboratory and Center for Environmental Research Information, February 1990.
                                                3.7

-------
formulations in inventory.  The formulations are moved to "mini-bulk" containers used to transport the
product to farmers'  fields.  The repackaging production process is relatively simple compared to the
formulating and packaging segments of the pesticide industry.  This fact is reflected by the average
market value of production lines for repackaging facilities — about $3,836 — compared to the average
market value of production lines for the remainder of the industry — about $197,666.6

       Regulatory Overview
       The Pesticide Formulating, Packaging and Repackaging (PFPR) industry is regulated directly by
the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), amended in 1988.  Other media- or
information-based regulations also  subject the industry to environmental  requirements  (e.g. under
CERCLA, EPCRA, RCRA, CWA, and CAA).7

       FIFRA requires all pesticides to be labeled and registered with EPA before they are offered to
consumer markets. EPA assigns to each pesticide product a registration number that must appear on the
label along with the pesticide active ingredients (PAIs).  FIFRA's registration standards are based on
avoiding "unreasonable risk" to humans and the environment, taking into account economic, social, and
environmental costs and benefits.  EPA can refuse to register products that pose a potentially high risk
for humans and the environment;  it must also approve any changes hi the formulation or labeling of a
pesticide product.

       Reauthorization of FIFRA in 1988 assessed registration maintenance fees for the PFPR industry
as well as a one-time reregistration fee for the producers of pesticide active ingredients (PAIs).  Annual
registration maintenance fees are levied for each individual pesticide product. Each PFPR registrant pays
    6 Source:  U.S. EPA Formulating, Packaging, and Repackaging Survey. The PFPR Survey defines a product
line as, "Equipment and interconnecting piping or hoses arranged in a specific sequence to mix, blend, impregnate,
or package, or repackage pesticide products. These products contain one or more pesticide active ingredients with
other materials to impart specific desirable physical properties for  a product or device, or to achieve a desired
pesticide active ingredient concentration for a particular product or device, or to package it into marketable
containers.  The line begins with the opening of shipping containers or the transfer of active ingredient(s) and other
materials from a manufacturer or another formulator/packager, or from inventory of bulk storage. The line ends
with the packaging or repackaging of a product into marketable containers or into tanks for application."
    ^CERCLA = Comprehensive Environmental Response Compensation and Liability Act; EPCRA = Emergency
Planning and Community Right-To-Know Act; RCRA = Resource Conservation and Recovery Act; CWA = Clean
Water Act;  and CAA = Clean Air Act.

                                               3.8

-------
$650 for the first registered pesticide product and $1,300 for every additional product.8 The maximum
limit of maintenance fees foria registrant is $55,000 for the first 50 pesticide products and $95,000 for
any number of product registrations.9'10

        Reregistration fees  are  a one-time payment for pesticide manufacturers with PAIs that were
registered before 1984. The fee is charged on a per PAI basis and may range from $50,000 to $150,000:
Reregistration fees are apportioned among producers of each PAI, based on market share.11

        The Best Practicable Technology (BPT) effluent limitation regulations, authorized under the Clean
Water Act, are also  of particular relevance to  this EIA.   BPT standards,  established by EPA, are
generally based on the average of the best existing performance by facilities hi a regulatory category or
sub-category that discharge pollutants from a point source to navigable waters.  BPT regulations have
been promulgated for three segments of the pesticides industry: organic pesticide manufacturers, metallo-
organic pesticide manufacturers, and PFPR.  EPA considers the following when deriving BPT effluent
limitation guidelines:  the costs  and benefits of effluent reductions, the age of equipment and facilities
involved, the process changes  required, the processes utilized, engineering aspects of the control
technologies, non-water quality environmental impacts, and other factors the EPA Administrator deems
appropriate. Under BPT regulations for the PFPR industry, established hi 1978, discharge of process
wastewater pollutants from PFPR operations is prohibited.

        States also have the authority to regulate pesticide products. Most state governments have statutes
that regulate pesticides hi professional, household, and agricultural markets. Many states have adopted
    8 U.S. Environmental Protection Agency, Office of Pesticide Programs, Instructions to Registrants for Filing
 1993 Pesticide Registration Maintenance,Fees, 1992.
    9 A "small business" registrant may pay reduced fees under HERA.  A small business is defined by the Office
 of Pesticide Programs as any company with  ISO or fewer employees and average annual chemical sales of $40
 million or less over the three-year period prior to registration. The maximum limits on registration maintenance
 fees for small businesses is $38,500 for the first 50 products, and $66,500 for any number of products.
    10 Annual maintenance fees may be paid indirectly by organizations other than the pesticide registrant.  For
 example, a trade association which relies on a particular pesticide may voluntarily pay the maintenance fee for that
 pesticide.
    11  U.S. Environmental Protection Agency, Office of Pesticides Toxic Substances, Highlights of the 1988
 Pesticide Law - The Federal Insecticide, Fungicide, and Rodenticide Act Amendments of 1988, December, 1988.

                                                 3.9

-------
the Uniform State Insecticide,  Fungicide, and Rodenticide Act,  which requires the registration of
pesticides, proper labeling, and penalties for tampering and false branding.  Many states also have
regulations that set standards for handling, treating, and disposing hazardous substances and wastes,
which may impose additional costs on the industry.
3.2     Industry Structure
        Markets for Industry Products and Services
        The PFPR industry serves its markets by offering both products and services to consumers (see
Figure 3.2)12.    Pesticide products  can  be  classified into  three  principal  markets:  agriculture,
industrial/institutional/commercial, and home/lawn/garden.  Services provided by the PFPR industry
include pesticide distribution and application. Additional information on pesticide products and services
is provided below.
                                             Rgure 3.2
                       National Estimates of Composition of Facility 272 PAI-Related Revenues
                                 Averaged Across All Facilities (Avg. 1986-1988)
                                    Revenues from In-Scope PFPR Sales
                                            •  Products
                                            H  Tolling
                                            H  Services
                                   82.0%
                                                           16.0%
                                                      2.0%
          Note: Includes Water Users
          Source: Survey
   12Tolling, or contract work performed for other facilities, may include both products and

                      ,1                         3.10
services.

-------
       Pesticide Products
       The Survey data show that in 1988 the agricultural market was the largest segment of the industry
with an estimated 67 percent of 272 PAI-related pesticide sales nationwide (see Figure 3.3). The home,
lawn and garden market comprised the second largest segment of the industry (estimated at 11 percent),
followed by the industrial/institutional/commercial market (estimated at 7 percent, 5 percent of which is
attributable to the institutional/commercial market, and 2 percent to the industrial market).13  These
three major markets are discussed below.
                   ?
       The agricultural market is diverse in terms of the types and amounts of pesticides used and in
pesticide management practices, which vary significantly among  regions of the country, states, and
sometimes counties. This diversity is an important distinction that separates the agricultural market from
the other pesticide markets, which tend to be more homogeneous nationwide. Approximately 62 percent
of all agricultural acres are treated with at least  one type of pesticide product.14 Herbicides are used
in greater quantities hi the agricultural market than any other type of pesticide.  In 1989, the herbicides
that were used in greatest quantities were Alachlor, Atrazine,  and 2,4-D.15  These pesticides were used
primarily on peanuts, corn, soybeans, cotton, and rice. Insecticides were the second most heavily used
type of pesticides.  In 1989, the insecticides used in greatest  quantities were Carbaryl and Terbufos.16
These pesticides were used primarily on cotton, fruits, vegetables, wheat, and ornamentals. Fungicides
are applied to fewer acres than herbicides or insecticides, but are generally applied to high-value fruit and
vegetables. In 1989, Maneb was used in the largest quantity among fungicides.17
    13 U.S. Environmental Protection Agency,  U.S. Environmental Protection Agency Pesticide Formulating,
Packaging, and Repackaging Facility Survey for 1988.
    14 Pimental, D., et al. (1986). Environmental and Economic Impacts of Reducing U.S. Agricultural Pesticide
Use. Pest Management in Agriculture.  CRC Press.
    15 U.S. EPA (1989). Pesticide Industry Sales and Usage: 1989 Market Estimates.  Office of Pesticides and
Toxic Substances, December.
    16 Ibid.
    17 Ibid.
                                               3.11

-------
                                                    Rgure 3.3
                            National Estimates of Distribution of 272 PAI-Related PFPR Revenue
                            	ByMarket Type (1988)
                      Agriculture
                      Home/Lawn/Garden
                      Industrial/lnstltutkMial/Commerclal
                      Other
                                                           66.8%
                                                                                14.7%
                                                              11.4%
                                                                          7.2%
           Note: Includes both Water-Users and Non-Water Users
           Source: Survey
        Table 3.3 provides a brief description of the steps taken to move an agricultural PAI through
process and distribution channels and then to the end user.   The end  users may include farmers,
government, and commercial  applicators.   Farmers either purchase and apply pesticide products
themselves  or  pay commercial applicators to apply pesticides to their crops.  The government uses
agricultural chemicals to control vegetation around highways, roads, railroads, waterways, pipelines,
power lines, government buildings, military complexes, and parking lots.

        The home/lawn/garden pesticide market includes pesticide products that are commonly used in
and around the home.  These products include rodenticides, insect repellents, lawn and garden pesticides,
disinfectants and other pesticidal cleaners, insecticides to protect pets and eliminate household pests,
herbicides,  fertilizers with herbicides/insecticides, and insect baits and traps.  In general, household
                                          r
pesticides are packaged hi containers that are smaller than those used in the other markets and may also
be less concentrated.  Some household pesticides  are seasonal (e.g., lawn and garden products), while
others meet a demand that remains fairly constant throughout the year.
                                               3.12

-------
                                                 Table 3,3
                             Pesticide Agricultural Production and Distribatioa4
     Agent
Purpose
     Registrant




     Manufacturer


     Formulator/Packager
     Distributor
     Dealer/Co-op/Repackager
Registers the pesticide formulation with EPA. Registration involves a
long, expensive R&D process to develop the pesticide, produce the data
required for registration, and proceed through the registration process.


Synthesizes the active ingredient from'raw materials.


Produces the pesticide formulation by combining the active ingredients)
with other substances,  including surfactants, clays, powders and
solvents; involves mixing or blending operations. Formulation may be
done in-house, by independent formulators, or by tollers who formulate
the product under contract to the manufacturer.


Acts as the "middle man;" buys pesticide from the
registrant/manufacturer/formulator and sells to the dealer.


Sells the pesticide to the user.2
      1  In many cases several steps are performed by one entity. Large companies might register,
        manufacture,  and formulate their pesticides.  Some distributors also formulate several pesticides.
        Additionally,  a single facility might function as a distributor, dealer, and commercial applicator.
        A user is defined as a fanner, government, commercial ground applicator, commercial aerial applicator,
        or home lawn and garden consumer.

      Source:     Based on a table in: Pesticide Containers: A Report to Congress, U.S. EPA, Office of
                 Pesticide Programs, May, 1992.
        The main difference between the household market and the other markets is that the end user,
the household  consumer,  purchases  household pesticides  from a  wide  variety  of common retail
establishments (see Figure 3.4). These include grocery, drug, and discount stores, as well as home and
garden shops and pet supply companies! The producer of household pesticide products can sell directly
to the retail  stores or indirectly through a  distributor  warehouse.   Consumer companies,  another
distribution channel from manufacturers to retail stores, make consumer products, applying their label
to the finished good.  Like formulators, consumer companies can sell directly to retail establishments or
indirectly through  food brokers who distribute products to retail stores.
                                                3,13

-------
        The  industrial/institutibnal/cominercial market  (I/I/C) includes  many  products,  such  as
 disinfectants, cleaning supplies,  and air conditioning biocides, that are generally not perceived as
 pesticides by the public.   In addition, products such as paint and wood preservatives may contain
 substantial amounts of pesticides.  The I/I/C market is estimated to exceed $200 million annually, with
 approximately 45 percent involving health care institutions.18

        The I/I/C market differs significantly from the agricultural market hi many ways.  First, the use
 of I/I/C products is generally more uniform across the country. Disinfectant uses in various parts of the
 United States are approximately the same. (Although the use of pesticides for wood preservation and in
 cooling towers  varies somewhat  according to the climate.)19  Also, I/I/C pesticides are generally
 packaged in smaller quantities than agricultural chemicals.  In addition, I/I/C products tend to be less
 concentrated and therefore less expensive per unit volume of product than agricultural pesticides.

        Another major difference between I/I/C and agricultural markets is that fewer manufacturers of
 pesticides used in the  I/I/C market both  register  and  formulate then: pesticides;  independent
 formulators/packagers are more predominant hi the I/I/C market. In addition, a greater variety of paths
 exist between the formulators and end users. (See Figure 3.4, which illustrates the distribution channels
 within the I/I/C and home/lawn/garden markets.)
    18 U.S. EPA (1992).  Pesticide Container Report to Congress, Draft.  Office of Pesticides  and Toxic
Substances, March.
    19 Ibid.
                                               3.14

-------
                                         Figure3.4
                             Production and Distribution Channels
                             Industrial/lnstitutional/Commerdaland
                                 Home/Lawn/Garden Markets
                Basic Pesticide Manufacturers
          Independent Formulators
                                      Contract  Formulators
                                          Tollers"
                                                      Consumer Companies
                                      Formulators/Distributors
                             Distributors
                                                          Food Brokers, Etc.
                                                   Retailers
                                                                                W  ^ '  \f
                                                 Home, Lawn
                                               and Garden Users
                                              Industrial,
                                            Institutional, &
                                         Commercial Dealers
         institutional Users
Industrial Users
Commercial Users
                                                                       Government Users
  Source: Based on a diagram in Pesticide Containers: A Report to Congress, U.S. EPA,
          Office of Pesticide Programs, May, 1992.
       The distinction between the industrial and institutional/commercial pesticides is based on the

setting in which the pesticide is used. In some cases, the same formulation is used hi different types of

facilities.  Industrial pesticides, such as preservatives, slimicides, or biocides, are typically used in

cooling towers, paper and textile mills, oil  wells, metalworking facilities, food processing facilities,

etc.20   Typical institutional/commercial end-users include personnel  hi  hospitals, nursing homes,

schools,  restaurants, hotels, and contract cleaning businesses that serve stores, apartment houses, office
    20 Ibid.
                                               3.15

-------
buildings, and garages.21  Commercial establishments also use pesticides to protect landscaping and to
maintain cleanliness and health standards. The federal, state and local governments use I/I/C chemicals
on military bases, in hospitals and in other government buildings.

        Producers  of pesticides used  in institutional settings may sell  directly to large users (e.g.,
hospitals), or they may use distributors such as at janitorial supply houses to sell indirectly to smaller
users.  Institutional distributors  usually sell general maintenance products  (e.g., cleaning supplies and
non-pesticide cleaners, as well as sanitizers and disinfectants).  Similarly, producers of industrial and
commercial pesticides may sell directly to the end-user or indirectly through a warehouse.22

        Sanitizers are typically used in the I/I/C market as cleaners, disinfectants, degreasers, and laundry
detergents.   Many sanitizer products,  such as air fresheners and laundry detergents, are sold in low-
concentrated  formulas  to  the  end-user,   who   are 'sommonly   cleaning   services   or   in-house
janitorial/housekeeping staff.  The end-user  may receive sanitizers directly from the formulator  or
indirectly from a warehouse.23
        Pesticide Services
        Much of the-pesticide application for the three major markets is performed by commercial
applicators.  Commercial applicators are trained professionals skilled in applying pesticides in an efficient
and environmentally safe manner.  The National Pest Control Association estimated that in  1990, the
commercial applicator industry included 14,250 firms with annual billings of $3.5 billion.24
    21 U.S. EPA, International Sanitary Supply Association, Research Triangle Institute (1989). Meeting Summary.
Research Triangle Institute, July.

    22 U.S. EPA, and Mitre Corporation (1983).  The Supply and Use Patterns of Disinfectants and Sanitizers at
Selected Sites. January.
    23 Shipments of Soaps and Detergents to Rise 3.2% Through 1988, Says U.S. Report, Soap/Cosmetic/Chemicai
Specialties for January, 1984, pp.30-34.
    24 National Pest Control Association, Inc. (1991). Fact Sheet.

                                                3.16

-------
        Commercial applicators  are contracted  by  the  agricultural  industry  to  apply pesticides  to
agricultural crops, as well as to food products during storage and transit. In addition to repackaging and
distributing pesticide products for the agricultural market, refilling establishments frequently provide
application services to farmers.  Many refilling establishment dealers  will blend pesticide formulations
with fertilized water for application to farmers' crops.25

        In  1985, about 60 percent of the services of the non-agricultural commercial applicator industry
were conducted at residences.26  Household consumers use commercial applicators to manage pests that
typically inhabit dwellings, such as termites, cockroaches, and mice, and to rid their lawn and garden of
pests.  In 1985, 25 percent of the services of the non-agricultural commercial applicator industry were
conducted  at  commercial  settings,  with 7, 6,  and  2 percent of services  conducted at institutional,
industrial,  and government settings, respectively.27  The I/I/C sectors use the services of commercial
applicators to control  pests  in many  settings, including  schools,  health  care  facilities, prisons,  food
processing establishments, hotels, restaurants, factories,  warehouses, and military sites.  Government
entities use the services of commercial applicators to control mosquitos, and to maintain vegetation around
roads, and public recreational areas.

        Industry Employment
        The formulating, packaging, and repackaging of 272 PAIs supported more than 5,000 production
workers in 1988, as illustrated hi Table 3.4 (national estimates based on Survey data).28  Facilities with
more than $50 million in revenues, while accounting for only an estimated six percent of the number of
facilities, employed an estimated 45 percent of the total 272-PAI PFPR production workers. In contrast,
facilities with less than $1  million in revenue constituted an  estimated 26 percent of the number of
facilities but only an estimated three percent of the 272-PAI  PFPR production workers hi the industry.
Table 3.4 provides evidence that PFPR facilities are  diversified, with  over 80 percent of the production
    25 Ibid.
    26 Ibid.
    27 Kline & Company, Inc. (1986).  PCO Industry Thrives; Hits $2.5 Billion Mark. Pest Control Technology,
 December.
       Employment figures are presented in terms of full time equivalents (FTEs).  FTEs are calculated by dividing
 facility annual hours by 2,000.
                                               3.17

-------
 workers involved in activities other than 272-PAI PFPR in 1988.   Production diversity in the PFPR
 industry is roughly consistent across all facility sizes.

        The average number of employees per PFPR facility varies greatly across facility sizes  (See
 Table 3.5).  In 1988, facilities with revenues of $50 million or more had an average of 293 total FTEs
 with 21 PFPR production workers for the 272 PAIs originally considered for this rule (henceforth 272
 PAI-related). Facilities with revenues of less than $1 million averaged only eight total FTEs and less  than
 one FTE for 272 PAI-related PFPR production.

        Figures 3.5a and 3.5b plot employment trends from 1980 to 1990, for SIC 28  (chemicals and
 allied products) and  SIC 51  (non-durable goods wholesalers) against employment levels for the more
 specialized industrial categories of SIC 2879 (agricultural chemicals, not elsewhere classified [n.e.c.], and
pesticide preparations and formulations), and SIC 5191 (farm supply wholesalers). The employment
trends of SIC 28 and SIC 2879 show a fairly close correlation.  Employment in SIC 5191, however, did
not follow employment trends for the broader  industry of SIC 51.  SIC  5191 showed  a decline in
employment from 1980 to 1990 while employment levels for SIC 51 increased over 20 percent during
the same time period.
Sour
U.S.
Cou

— M- SIC 2879
+ SIC 28
oe:
Bureau of the Census
nty Business Patterns,
Figure 3.5a
Employment Trends 1980-1990
(1988 Base Year)
1 °5
•1 17*?

1.025|
095-
0.875
08-





{












W








\














4
\\
m-


















r
-m



















^r-
ilSs














J









•
i.










i










h
p:


















-.IIP
^^
T


















^SR


















jjjk'
Jip-

















-H






m

i 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
1980-1990
                                            3.18

-------
I
      §
*."1K

I Is



              t|_< *-4
s  a
**£
   I

II
   w
            o
          {** f .
                    ts
                    en_

                    CN
                    oo
                    •*
                    o

                    en
                             en
                             CN
                             VO


                             "1
                             oo"
»
                             c-
                             oo
                             vo
                             vo
                        oo
                        CS
                                      ts
                                      r-
                                      ON
                                      o
                                      cs
                        /">
                                                      c
                                                      t~-
                                        en

                                        en
                                                      a
                                                          o

                                                          oo
I
.a

1

I
                                                             60
                                                          II

                                                          .   I
                                                          B3
                                            If
                                                          &M 2
                                                          '^ o o
                                                           S " S
                                                                   t
                                                           w

                                                          I
                                                          — < cs m  CO
                                           3.19

-------
Table 3.5
Average Facility Employment Characteristics1
by Facility Size
(1988 Full-Time Equivalents)
272 PAI-Related Average
Average Average PFPR Other
Size of PFPR Revenues Total Production Production
Facility (In $ Thousands) Employment Employment Employment
Revs, of 37,750.7 293 21 166
$50M and
greater
Revs, of 2,617.0 62 4 33
$10M to
$49.9 M
Revs. of$lM 460.9 18 28
to $9.9M
Revs less than 66.5 8 < 1 4
$1M
Average for 3,038.6 39 3 20
all facilities
Average
Non-
Production
Employment
107
26
8
4
16
Source: Survey.
'includes water users.
       U.S. Trade in International Pesticides Markets
       The U.S. pesticide industry participates substantially in the international market for pesticides,
including both PAIs and final pesticide products.  The volume of international trade in pesticides was
approximately $6 billion in 1988 ($1988). Of that amount, the U.S. pesticide industry accounted for over
24 percent of total  exports ($1,554 million) and more than 10 percent of total imports ($614 million).
Over the ten-year period 1980-1990, domestic exports consistently exceeded imports, contributing a
positive trade balance to the U.S. economy averaging over $950 million (See Table 3.6).29

       Both domestic exports and imports have varied over the past ten years.  Imports, however, have
shown greater variation, ranging from a low of $187 million in 1989 to a high of $614 million in 1988,
   29 International Trade Statistics Yearbook, United Nations, Statistical Office, 1989.

                                              3.20

-------
                                          Figure 3.5b
                                   Employment Trends 1980-1990
                                         (1988 Base Year)
                     SIC 5191
                     SIC 51
                               1.25-r
                              1.175
                              1.025--
                               0.95
                              0.875,
         Source:                 0.8 -
         U.S. Bureau of the Census    1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
         County Business Patterns, 1980-1990
a range of variation of over 200 percent.  Over the same period, domestic exports varied from a low of
$1,036 million in 1989 to a high of $1,554 billion in 1988, a range of variation of about 50 percent.

       The U.S. industry's participation in the international market for pesticides includes both inter-
and intra-company sales and purchases. In particular, a number of firms that manufacture and process
PAIs and final pesticide products are multi-national firms with operations in both the United States and
other countries.  In addition, these multi-national firms include both U.S. and foreign-owned firms.
Some amount of the  international trade in PAIs  and final products involves intm-firm, trans-national
boundary transfers within the multi-national firms.

3.3    Market Demand and Consumption
       Consumption of Pesticide Products — Historical and Current
       Consistent with pesticide production data, user expenditures  for pesticides are greatest in the
agricultural market — about $5.2 billion in 1991 (1988$).  The Industrial, Commercial, and Government
                                              3.21

-------
Table 3,6
U.S. Participation in International Markets for Pesticides
Exports,
Imports, Trade
Balance, and U.S. Share
(all dollar values in


Year
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
Average

U.S.
Exports
1,444,467
1,284,050
1,211,135
1,243,280
1,499,545
1,354,907
1,366,117
1,405,878
1,554,136
1,043,371
1.036.597
1r313,044
U.S. Share
Total
Exports

26.6%
27.7%
27.8%
29.2%
26.8%
25.6%
23.2%
. 24.1%
18.2%
16.4%
24.6%
thousands of

U.S.
Imports
369,795
348,732
297,492
287,637
356,729
455,252
423,276
446,536
613,752
186,594
195.209
361 ,909
of Total Exports
1988 dollars)
U.S. Share
Total , ,
Imports

9.0%
8.3%
7.6%
8.3%
11.0%
8.6%
8.2%
10.3%
3.4%
3.2%
7.R%
and Imports

U.S.
, Trade
Balance
1,074,672
935,318
913,643
955,643
1,142,816
899,655
942,841
959,342
940,384
856,777
841,388
951 r 134
markets combined (T/C/G)30  attracted nearly $1 billion in expenditures in  1991 (1988$) as did the
H/L/G market (see Figure 3.6 and Table 3.7).  Total user expenditures for the  three major markets
exhibited substantial swings over the period of 1981 to 1991. The peak consumption year was 1984 and
the lowest was in 1982.  Cumulatively, however, total pesticide expenditures were approximately the
same in 1981 and 1991.  Pesticide usage for agriculture was the only market of the three with greater
consumption in 1991 than in 1981. All of the markets exhibited relative stability, however, hi total sales
over the decade.
   30 These data are only available aggregated among these markets.
                                              3.22

-------
                                             Figure 3.6
                           User Expenditures for Pesticides by Principal Market
                                          (In Million 1988$)
                                            8,000-
                    Agriculture
                    Industrial/Commercial/Gov't.
                    Home/Lawn/Garden
                    Total
          Source:
          Pesticides Industry Sales and Usage:
          Market Estimates
          U.S. EPA, Office of Pesticide Programs
          (1980-1991).
1981   1983   1985   1987   1989   1991
       Agricultural pesticide purchases reached their lowest level hi 1982, the year in which this segment
of the market experienced its most dramatic annual decline.  Following 1982, agricultural pesticide
purchases continued to fluctuate in the second half of the decade, reaching a peak for the 10-year period
examined in 1990.  In general, the annual changes were less dramatic than the fluctuations that occurred
earlier in the decade, thereby reflecting a more stable market.

       Although purchase of I/C/G products was second to agriculture for most of the 1980s, the I/C/G
market exhibited substantially negative average annual growth over the period examined. Consequently,
by the end of the decade, demand for home, lawn and garden products exceeded the demand for I/C/G
products. I/C/G product sales were highest in 1984 and lowest in 1991.  The decline hi I/C/G product
sales at the end of the decade probably stems in large part from the recession and weakening of the
manufacturing economy that began at that time.
                                               3.23

-------
C3
1
                   oo
                                                          ^-   os
                              oo    ON
                                                               en    en
                                                          rt   o
                         o\
                                                                     •»» j    i. —    vi
                                                                     O    CO    VO
                                                                     i-^    i—i    O
                                    oo   O\
                         «o
                                                                     en   >O
                                                    i— i    >n
                                    O\   <-!
                                    rl   O\
                                    o\   o\
                               8    I   8
g
                                                                          OS    O\
                              O\
                                               en
                              o
                         ts
                              T-l    O
                                         o\
                                         --
                                         8    s   a    s   a    s   s
                                         en
                                                                     os   v
                         cs
                                    o\
                                                          vo   en
                                               8
                                     o    os   o
                                     
-------
       Pesticide sales in the home/lawn/garden market declined slightly over the period examined but
averaged approximately $1 billion over the entire period.  Of the three major markets examined, the
home/lawn/garden market exhibited the greatest stability.

       Price Elasticity of Demand
       Demand elasticity measures the change of quantity demanded by consumers in response to a
change in price. The elasticity of demand for pesticide products can therefore be used to project declines
in revenues that PFPR firms  will experience if they pass compliance costs on to consumers in the form
of price increases. Price elasticity of demand is calculated by dividing percentage change in demand by
a percentage change  in price.  Numeric values associated with price elasticities of demand are generally
expressed relative to a one percent change in price. For example, an elasticity of -0.5 suggests that a 1
percent increase in price would result in a 0.5 percent decrease in the quantity demanded.  High demand
elasticity (i.e.,  a significant reduction in demand resulting from a price increase) may therefore signify
a low level of consumer loyalty to the products offered in that particular market, and indicate a substantial
decline in revenues should producers choose to pass compliance costs on to consumers.

       To assess the price sensitivity for pesticide markets, an estimate of demand elasticity is required
at the cluster level. EPA developed a comprehensive approach to estimated cluster elasticities, including:

(1)     A review of empirical studies of pesticide production and use;
(2)     U.S. Department of Agriculture's analysis of the price elasticity of demand for food commodities;
(3)     Feasibility of employing non-chemical, non-biological pest control methods;
(4)     An analysis of pesticides' contribution to the cost of producing a commodity, based on estimates
        of production costs in the farm sector;
(5)     Analysis of the marginal productivity of pesticides; and
(6)     Expert opinions within EPA's  Office of Pesticide Products.

        The price elasticities of demand vary substantially among the clusters, since each cluster faces
different market forces (Table 3.8).  Elasticity of demand varies among the clusters from -0.12 to -1.38.
Despite the wide range of demand elasticities among  pesticide clusters, 38 of the 47 have relatively
inelastic demand: that is, the absolute  values of the demand elasticities are less than 1.  This finding
                                               3.25

-------
                                      Table 3,8
                   Summary of Estimates of Elasticity of Demand
 Cluster
Elasticity Estimate
 Herbicides on sugar beets, beans, peas
 Herbicides on tree fruits (except oranges), sugar cane, nuts
 Herbicides on tobacco
 Fungicides on fruit and nuts trees (except oranges)
 Fungicides for seed treatment
 Herbicides on vegetables
 Fungicides on grain in storage
 Insecticides on vegetables
 Slimicides
 Fumigants and nematicides
 Insecticides on termites
 Wood preservatives
 Insect repellents at non-agricultural sites
 Domestic bug control and food processing plants
 Mosquito larvacides
 Fungicides on turf
 Industrial preservatives
 Insecticide synergists and surfactants
 Plant regulators, defoliants, desiccants
 Sanitizers - dairies, food processing, restaurants, air treatment
Insecticides on livestock and domestic animals
Industrial microbicides, cutting oils, oil well additives
Preservatives, disinfectants, and slimicides
Fungicides - ornamentals
Insecticides on lawns, ornamentals and forest trees
Molluscides & miscellaneous vertebrate control agents
Rodent toxicants, anti-coagulants, predator control
Unclassified lisas	
       -0.12
       -0.20
       -0.20
       -0.23
       -0.27
       -0.27
       -0.31
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -0.33
       -O V*
                                          3.26

-------
                                           Table 3.8
                      Summary of Estimates  of Elasticity of Demand (cont.)
        Cluster
Elasticity Estimate
        Fungicides on vegetables
        Fungicides - broad spectrum
        Herbicides - broad spectrum
        Insecticides on soybeans, peanuts, wheat, tobacco
        Herbicides on rights of way, drainage ditches
        Herbicides on turf
        Herbicides on soybeans, cotton, peanuts, alfalfa
        Herbicides on corn
        Insecticides on corn and alfalfa
        Insecticides on sorghum
        Herbicides on sorghum, rice, small grains
        Fungicides on citrus
        Herbicides on oranges
        Insecticides on fruit and nut trees, except oranges and grapes
        Insecticides on oranges
        Herbicides - other agricultural uses
        Insecticides on cotton
        Fungicides on grapes
        Herbicides on grapes
       -0.38
       -0.40
       -0.48
       -0.56
       -0.66
       -0.66
       -0.67
       -0.69
       -0.69
       -0.69
       -1.00
       -1.00
       -1.00
       -1.00
       -1.00
       -1.00
       -1.06
       -1.38
       -1.38
        Source: Estimates of the Price Elasticity of Demand for Pesticide Clusters, U.S. EPA
                and Abt Associates Inc., May 1991.  Estimates provided for clusters with
                costs under the proposed rule.
indicates that demand at a cluster level (although not necessarily at the product level) should not vary
significantly with moderate price increases.31
    31For further details on the estimation of pesticide price elasticity of demand see Appendix C of the Economic
Impact Analysis of Proposed Effluent Limitations Guidelines and Standards for the Pesticide Manufacturing Industry.
                                                  3.27

-------
 3.4    PFPR Industry Performance from 1986 to 1988 Compared to the Historical Trend in the
        Industry and the Economy in General
        EPA examined whether the years encompassed in the Survey — 1986 to 1988 — were "typical"
 years relative to overall U.S. business conditions and, in particular, to the historical performance of the
 PFPR industry.  If data  were gathered  for a period hi which the economy — and PFPR industry in
 particular — were in a recession or economic boom, then the economic impact analysis might not
 reasonably represent the financial burdens associated with the capital requirements and expenses of the
 proposed effluent guidelines.

        To examine this issue, EPA analyzed the condition of the general economy and the PFPR sector
 of the economy over the  15-year period  1979-1992 (see Table 3.9).32 In summary, the analysis shows
 that the general economy was in a relatively stable  period of growth during the PFPR survey years,
 exhibiting neither rapid growth nor declines in performance.  Growth  in the PFPR industry was  less
 stable than growth in the general economy from 1986 to 1988, exhibiting one year of decline and two
 years of above average growth.  The average value of shipments for SIC 2879 for  1986 through 1988
 ($5.82 billion) is similar,  however, to the average value of shipments over the 15-year period examined
 ($5.78 billion) (see Table 3.10).  Therefore, the survey years  serve as a reasonable base on which to
 evaluate the achievability of PFPR compliance with an effluent guideline.

        Growth in Gross Domestic Product, 1978 to 1991
        As shown in Table 3.9, real GDP grew at an average annual rate of 2.1 percent from  1979 to
 1992.33  In 1980,  1982,  and 1991, growth from the previous  year is negative, with the decline from
 1981 to 1982 being the most dramatic experienced by the economy during the 15-year period examined.
Following  1982, the economy  began its recovery from the recession of 1981-1982.   This trend is
exhibited in the annual growth  of GDP, which rose significantly in 1983 and reached a peak of 6.3
percent in 1984. For the next five years, 1985 to  1989, GDP rose an average of 3.1 percent, showing
little year-to-year variation. Beginning  hi 1990, annual growth was substantially less, with negative
growth between  1990 and 1991.  During the PFPR survey years,  1986 to 1988, GDP rose an average
   32 Value of shipments product data for 1990 to 1992 are estimates. Estimates may vary substantially from final
numbers.  GDP data for 1992 were not available.
   33 GDP data were indexed to 1988 dollars using the GDP price index. Annual growth is defined as the percent
change in real GDP from the preceding year.

                                             3.28

-------
£
         OS
         0\
         OS
         OS
         o
         OS
         OS
         OS
         00
         Os
         oo
         00
         OS
         00
         OS
         SO
         00
         OS
         oo
         OS
         00
         OS
f-;
o
 en
 vd
 1
         g
         OS
 SO
 o
       II
ss Dom

duct
       13 os
       •§E5
       le
       fi a
       tl
       4) %

       > i


                         .s
                              <*>
of
S
Annual
Growth Rates
                       OS
                       en
Dom
                                                S S
                                     3.29

-------
       §
                  I
•c °^
9* r-l
       8-3 I
                                              u
                                 3.30

-------
of 3.3 percent, which is reasonably similar to the 15-year average for the economy. Figure 3.7 illustrates
the annual growth in GDP from 1978 to 1991.

       Performance of the PFPR Industry Relative to U.S. Business Conditions, 1978 to 1992
       To evaluate the performance of the PFPR industry relative to the general economy from 1978 to
1989, EPA obtained value of product shipments data reported in the U.S. Industrial Outlook.  Value of
product shipments data were indexed to  1988 dollars using the  Producer Price Index for agricultural
chemicals developed by the  Bureau of Labor  Statistics and annual percentage growth  rates were
calculated.34 Figure 3.7 illustrates that the pattern of growth in PFPR shipments generally matches that
of the economy as a whole, although with higher volatility.
                                             Figure 3.7
                      Gross Domestic Product and Product Shipments for SIC 2879
                                     AnnualPercentage Growth
                    1979
1981
                                     1983
                                              1985
                                                       1987
                                                                1989
                                             1991
                                                                              1992
                           —JH—  SIC 2879 Prod. Ship.
                           QDP
      Source: The Economic Report of the President, February 1992; Labstat Series Report, found in
      Producer Price Indexes, U.S. Department of Labor, Bureau of Labor Statistics, monthly; and the
      U.S. industrial Outlook (various years).
      Note: Value of Shipments data for 1990-1992 are estimates.
     34 Value of product shipments data were obtained for standard industrial classification (SIC) 2879, which is
  defined as establishments engaged primarily in the manufacture or formulation of agricultural chemicals not
  elsewhere classified, and the formulation and preparation of pesticides.
                                                3.31

-------
        The average growth rate for the PFPR industry for 1978 to 1992 was  1.7 percent, which is
somewhat lower than the 2.1 percent experienced by the general economy (see Table 3.9).  In addition,
from 1981 to 1983 and from 1984 to 1985, the decline in PFPR industry performance, while consistent
with the downturn experienced in the general economy, was of much greater magnitude.  Variation from
the growth trend in the general economy appeared again within the PFPR industry in 1985 and 1986.
During the three years encompassed in the Survey data (1986-1988), PFPR shipments growth averaged
4.7 percent, which is somewhat higher than the growth in GDP for the same years (3.3 percent) and
higher than the average growth for the PFPR industry from 1978 to 1992 (1.7 percent).

        Deviations from the general business trend that occurred in the PFPR industry from 1978 to 1989
can, in part, be explained by specific occurrences in the industry.  The decline in the performance of the
industry that occurred between 1981 and 1983 was due primarily to the USDA Payment-in-Kind Program,
which took 48 million agricultural acres out of production, resulting in a dramatic decline in pesticide
sales.  Other factors that influenced this decline included more efficient pesticide application techniques
and increased pesticide resistance.35

        The decline that took place from 1981 to 1983 was followed by a surge in the value of product
shipments in 1984.  This increase was accompanied by a 13 percent rise in pesticide exports.36 Other
factors that influenced this surge include the increase in sales of herbicides and growth-control chemicals
(the highest priced subsector of pesticides) as a percent of total pesticide sales and favorable weather
conditions.37 After peaking in  1984, pesticide exports dropped 8.6 percent in 1985, due largely to the
strong dollar and the violation of patent laws by foreign competitors.38   These factors influenced the
decline in the value of product shipments experienced by the PFPR industry between 1984 and 1986.

        From 1987 to 1989, the PFPR industry exhibited fairly stable and strong growth.  Factors that
had negative effects on the industry's sales during the middle of the 1980s had in part been addressed.
      As pests increase their resistance to a pesticide product, the product becomes increasingly ineffective, leading
to a decline in its use.
   36 United Nation's International Trade Statistics Yearbook.
   37 U.S. Industrial Outlook, 1985.
   38 U.S. Industrial Outlook, 1987.

                                              3.32

-------
Many of the countries that were involved in the abuse of intellectual property rights had made efforts to
control these violations.39 Also, the extensive consolidation that took place within the industry between
1986 and 1989 gave companies the revenue base needed to fund the rising research and development costs
associated with introducing new products to the market.  The decline experienced by the industry from
1990 to 1992 is compatible with that experience  in the general economy and, therefore,  is most likely
attributable to a general recessionary trend.

       Performance of the PFPR Industry during the PFPR Survey Years, 1986 to 1988
       Another gauge of whether the Survey years are biased is to examine the performance of the
industry over time compared to performance during the Survey years. If the average profit level during
the survey years is similar to typical industry profit  levels, the survey years provide a reasonable basis
for economic analyses. In the absence of industry-wide profit data, EPA examined the level of revenues
in the industry as measured by the real value of product shipments for SIC 2879. These data show that
the 3-year average value of product shipments for 1986-1988, $5.82 billion, is similar to the average for
the entire 15-year period examined, $5.78 billion (see Table 3.10 and Figure 3.8).
Rgure 3.8
Value of Product Shipments for SIC 2879
in 1988 Million Dollars
7 nnn
ft orin
c nnn«i
CO
QAfinfi-
.1
••so nnn
'*~onnn
1 t\nr\
g



,/
1











1.
T




















I
-Jr











1979
1978 19











60
1
•
T^




























1!
T









1981
19















/
"4


















i
•
/r











1983
82 19













•
T
























+










1985
84 19











I
M






















i.
X
\











1987
86 19
— H— SIC 2879 Product Shipments











J













k













B
T












1989
88 19













1
*
\
























^











i

1991
'90 1992
Source: Labstat Series Report, found in Producer Price Indexes, Department of Labor,
Bureau of Labor Statistics, monthly; and the U.S. Industrial Outlook (various years).
    39 U.S. Industrial Outlook, 1992.
                                              3.33

-------
 3.5    Analysis of Facilities by Water Use Status and By Subgroups
        On the basis of the survey data, the following sections characterize PFPR facilities along several
 important dimensions.  The first section presents a summary comparison of water-using and non-water-
 using facilities.  This comparison  is limited to only a few data items because the Section 308 survey
 requested considerably less detailed  financial and technical data for non-water-using facilities than for
 water-using facilities.  The second section presents a more detailed look at similarities and differences
 among 5 important PFPR industry subgroups. Most of the characterizations in this section are based on
 the more detailed data that apply to water users only.

        Comparison of Water-Using and Non-Water-Using Facilities
        Understanding the financial and market characteristics of water-using and non-water-using PFPR
 facilities is important in the performance of the EIA because non-water-using facilities will not incur costs
 for complying with the PFPR effluent guideline. To the extent that non-water users compete in the same
 PAI and product markets as water users, the competitive behavior of the non-water-using facilities will
 influence substantially the ability of water-using facilities that do incur compliance costs to recover those
 costs through price increases to their customers.
        From Survey responses, an estimated 610 PFPR facilities (25 percent) do not use water hi their
 272 PAI-related PFPR operations (referred to hereafter as "non-water-using facilities").  These facilities
 were not required to complete parts A and B of the Survey, and technical and financial details of their
 operations are therefore not available. For this reason, much of the data provided in the remainder of
 this chapter refer only to facilities that use water in their 272 PAI-related PFPR operations (estimated to
 be 1,794 facilities).  The remainder of this section compares water-using and non-water-using facilities
 on the basis of financial scale and performance, participation in PFPR markets, and facility ownership.
 From the limited data available on which a comparison may be based, the two groups of facilities have
 similar financial and market characteristics overall.

       Analysis of the  survey data indicates that non-water-using facilities have lower revenues (mean
value of $3.6 million) than water-using facilities (mean value of $13.4 million) (See Table 3.11.)  In
addition, the percentage of revenue generated from 272 PAI-related PFPR is very similar for non-water-
using facilities (mean value of 14 percent) and water-using facilities (mean value of 15 percent) (The other
revenues are from non-272 PAIs, other products, or non-PFPR activities). Although the estimated profit

                                              3.34

-------
margin40 is  higher for non-water users (about 11 percent) than for water users  (about 5 percent), the
estimated median profit margin values for the 2 groups are closer in value (2 and 3 percent).
Table 3.11
Comparative Statistics of Water Using and Non-Water Using Facilities
(1986-1988)
Revenue (In Thousands)
Percent of Revenue from
In-Scope PFPR
Profit Margin
Water Users
Mean Median
13,409 2,374
14.8% 4.2%
5.2% 2.3%
Non-Water Users
Mean Median
3,588 1,455
13.9% 3.7%
11.3% 3.3%
Source: Survey.
        The Survey also requested information on the percentage of revenue generated from 272 PAI-
related  pesticide sales by market for both  water-using and non-water-using facilities.  The market
descriptions provided in the Survey were:
        Agriculture
        Institutional/commercial41
        Industrial use
        Wood preservatives and coatings
        Intermediate pesticide products
        Products used as an additive to a non-pesticide product
        Non-agricultural professional use products
        Consumer home, lawn, and garden
    40 Profit margin is calculated as follows: (total facility revenues - all costs)/total facility revenues.

    41 Henceforth the Institutional/Commercial market is distinguished from the industrial market for analysis
regarding the survey data. This was not possible in the general discussion of these markets, as some data were only
available aggregated for these two markets.
                                                3.35

-------
 *       Government, for non-institutional use
 •       Other

 For this analysis, EPA defined a facility's primary market as the market from which that facility received
 at least half of its 272 PAI-related PFPR revenues. The majority of both water-using and non-water-using
 facilities  operate  primarily in the agricultural market  (See Figure 3.9).   Non-water-using facilities
 participate to a large degree  in the agricultural, and home,  lawn and  garden markets. Competition
 between water-using and non-water-using facilities is therefore likely to be effective hi these markets.
 In the Institutional/Commercial (I/C) market and the Industrial market, participation by non-water users
 is less than participation by water users, on a percentage basis.  EPA estimates that the I/C market is the
 primary market for  11  percent of water-using facilities,  but only for 6  percent of non-water-using
 facilities. Similarly,  18 percent of water-using facilities claim that their primary market is the industrial
 market, whereas only 10 percent of non-water-using facilities state that the industrial market is their
primary market.  Non-water using facilities are therefore likely to play  a less substantial competitive role
 in these markets in limiting the ability of water-using facilities to pass on compliance costs  to their
customers.
                                             Figure 3.9
                National Estimates of Percent of Water Using Facilities and Non-Water Using Facilities
                                     In the PFPR Industry by Primary Market*
                                                            7%
100
                                   60
                                  40
                                  20
         * Percentages may not
          sum to 100% due to rounding
             Source: Survey (1986-1988)
                                                            58%
                                                   66%
                                             Water Users
                                                                     Non-Watsr Users
                                               3.36

-------
       The Survey also  requested information on the ownership of the PFPR facilities. The Survey
options presented were:

•      A single facility enterprise
•      A multi-facility company
•      A cooperative
•      A Federal government agency
•      A military or defense organization
•      A state government agency
•      A local government agency
•      Other

The most common ownership type for both water-using and non-water-using facilities is a single facility
enterprise:  an estimated 44 percent of water-using facilities and 52 percent of non-water-using facilities
are estimated to be single facilities  (See Figure 3.10).  The second  most common ownership type is a
multi-facility company (40 percent for water users and 27 percent for non-water users.) Most of the
remaining facilities participate in a cooperative (14 percent of water users and 27 percent of non-water
users).

       On  balance, these data suggest that, relative to water users,  non-water-using facilities are a
smaller,  but competitively viable, segment of the PFPR industry. EPA technical specialists on PFPR
operations report that some PAIs and products require water-based formulation operations. Overall, non-
water users will limit somewhat the ability of water users to pass on compliance costs to their customers,
because enough PAIs and products can be formulated without water (i.e., either in dry form or with non-
water solvents)  The only markets in which competition by non-water users is not likely to limit the pass-
through of compliance costs are the institutional/commercial and industrial markets.
                                              3.37

-------
                                                Figure 3.10
                        National Estimates of Water-Using Facilities and Non-Water-Using Facilities
                                in the PFPR Industry by Ownership Characteristics
                   Other
                   Cooperative
                   Multi Facilities
                   Single Facility
            Source: Survey (1986-88)
                                100
80
                                 60
                                 20
                                              21%
                                                                               27%
                                                        44%
                                                                               52%
                                          Water Users
                               Non-Water Users
        Comparison of PFPR Facilities by Major Subgroups
        To aid in understanding how a PFPR effluent guideline regulation would likely affect facilities
in the PFPR industry, facilities were classified into five groups.  These groups differ hi terms of such
characteristics as markets served, reliance on PFPR as a source of revenue, and primary facility activity.
Because an effluent guideline is likely to affect the different subgroups in different ways, it is important
to distinguish among these five industry  subgroups and understand how the subgroups  differ.   For
example,  facilities that are heavily reliant on PFPR operations as a source of revenue will  likely face
different business decisions when confronted with compliance requirements than those that receive only
a small share of revenue from PFPR operations. These facilities likely face the decision of shutting down
their entire facility operations if the cost of regulatory compliance imposes an unmanageable financial
burden. In contrast, facilities with relatively low reliance on PFPR business as a revenue source should
be able to remain in business even if they decide to terminate their PFPR activities or convert those
operations to another formulation activity not subject to the PFPR effluent guideline.
                                               3.38

-------
       The five subgroups  were developed, in part, as a result of industry comments  to  EPA on
differentiation among PFPR facilities. In the process  of developing this rule, EPA met with interested
trade associations including  the National  Agricultural Chemicals Association  (NACA), the  National
Agricultural Chemical Retailers Association  (NACRA),  and the Chemical Specialties Manufacturers
Association (CSMA).   In addition, between  1991 and  1993, EPA conducted  site visits to 51 PFPR
facilities.   These site  visits were  conducted for several purposes, including strengthening EPA's
understanding of the technical and economic activities conducted  at the facilities.  The five subgroups,
together with a review of the basis for defining the subgroup, are as follows:

•      PFPRfacilities that also manufacture PAIs (hereafter, PFPR/Manufacturing Facilities). From
       industry input during the meetings and site visits and industry responses to the Survey, it became
       apparent that facilities that both manufacture PAIs and perform PFPR processing differ in several
       respects from other  PFPR  facilities.  Apart  from the simple operating difference that these
       facilities also manufacture PAIs, facilities in this subgroup, as shown below, are generally larger
       in terms of annual revenue than facilities in other subgroups,  are more  dependent on PFPR
       business, and are more likely to be part of a larger, multi-facility firm.

•      Refilling Establishments. Discussions with industry also singled out refilling establishments as
        a PFPR industry subgroup.   Refilling establishments are  defined as facilities in which the sole
        PFPR activity is repackaging pesticide products into refillable containers.  These facilities operate
        almost entirely in the agricultural products market, tend to be relatively  small, and  generally
        receive only a small fraction of revenues from PFPR business.
        Sanitizer Facilities.  Further, industry contended that pesticide products used as sanitizers were
        fundamentally different from other pesticide products, particularly in their concentration and end-
        use.  For this analysis, the Sanitizer Facility subgroup was defined to include any facility that
        reported at least half of the PAIs it used as being hi the Sanitizer PAI  Cluster, R-4.42  Like
        Refilling Establishments, Sanitizer Facilities tend to be relatively small and generally receive only
    4^ For this analysis a sanitizer facility is defined separately for water using and non-water using facilities. For
 water-using facilities, a sanitizer facility is defined as a facility with one half or more of its pounds of 272-PAI use
 from Cluster R-4.  For non-water using facilities, pounds of PAI use were not available. A sanitizer facility is
 therefore defined as a facility that uses at least half of the number of 272-PAIs it reports from Cluster R-4.
                                               3.39

-------
       a small fraction of revenues from PFPR business. In contrast, however, they largely serve a very

       different market segment, the institutional/commercial market, and were therefore recognized as

       a different industry subgroup for analyzing regulatory impacts.


       Other PFPR Facilities receiving at least of 25 percent of revenues from PFPR business. These

       so-called Other PFPR Facilities constitute those facilities whose business is  largely in PFPR

       operations and,  by definition, are the "mainstream" PFPR  facilities.  They  participate in all

       phases of PFPR operations, serve a diverse set of markets, and are typically larger in terms of

       annual revenues than other PFPR facilities except for the PFPR/Manufacturing Facilities.


       Other PFPR Facilities receiving less than 25 percent of revenues from PFPR business. These

       facilities also serve diverse markets and are similar in total revenue to Other PFPR Facilities with

       at least 25 percent of PFPR revenue. These low-PFPR dependence facilities were separated from

       the "other" Other Facilities for regulatory analytic purposes, hi recognition that facilities with

       only  peripheral participation hi  the  PFPR  business will likely face different decisions in

       responding to regulation than those for which PFPR is the core business (as noted in the example

       above).
       The information provided in the remainder  of this section characterizes some of the major

financial and operating differences among these facility subgroups. The dimensions on which the five

PFPR industry subgroups are characterized are as follows:
       Number of facilities
       Percentage of facilities using water
       Primary facility activity
       Percent of revenue from PFPR
       Mix of formulating, packaging, and repackaging
       Primary pesticide market
       Facility ownership structure
       Capital costs
       Facility employment
       Facility revenue
       Facility profit levels
                                             3.40

-------
For many of these data items facilities using water — the characterization of subgroups is based only on
water-using facilities.   Data  for  both water-using and non-water-using facilities are used for  the
characterizations based on number of facilities and percentage of facilities using water.

       Number of facilities
       In  1988 (the base year of the Survey),  data reported in the FIFRA and TSCA Enforcement
System yielded an estimate of about 2,500 PFPR facilities in operation. Nearly half of these facilities
(47 percent) are classified as Refilling Establishments (See Figure 3.11).  The next largest subgroup in
terms of number of facilities is Other PFPR (without  differentiation based on share of revenue from
PFPR) at 40 percent of total PFPR facilities.  PFPR revenue data were requested differently for water-
users and  non-water users, and therefore it is not possible to calculate comparable PFPR  revenue
estimates for the two groups.  Therefore non-water users cannot be split based on the share of revenue
from PFPR as water-users can. Using data for only those facilities that use  water, however, the 40
percent of total facilities hi the Other PFPR subgroup would split approximately as follows: 27 percent,
Other PFPR Facilities  with less than 25 percent of revenue from PFPR, and 13 percent, Other PFPR
Facilities with at least 25 percent of revenue from PFPR.

       In  terms of number  of facilities, the remaining  two  subgroups,  Sanitizer Facilities  and
PFPR/Manufactuxers, are much smaller segments of the industry.  Sanitizer Facilities  constitute an
estimated 11 percent of PFPR facilities, while PFPR/Manufacturing Facilities represent only 2 percent
of total PFPR facilities.

       Percentage of facilities using water
       For all industry subgroups, more than a majority of facilities  use water  hi PFPR operations.
Beyond this common feature, however, the industry subgroups break into two distinct classes based on
whether water is used in PFPR operations. Specifically, nearly all of the PFPR/Manufacturing Facilities
and Sanitizer Facilities  are estimated to use water in their PFPR activities. In contrast, only about three-
fourths of Refilling Establishments and two-thirds of Other PFPR Facilities (again, without differentiation
based on share of revenue from PFPR) are estimated to use water (See  Figure 3.12).
                                              3.41

-------
                                              Figure 3.11
                            National Estimate of PFPR Industry Structure by Subgroup
                                        ' 100-1
                • Mfg/PFPR
                H Sanltizers
                D Other
                il Refilling Establishments
80-
                                         60-
                                         40-
                                         20-I
 2%
 11%


40%
                                                                             47%
          Source: Survey, Including Water-Users and Non-Water Users
                                                            PFPR Industry
        Primary facility activity
        The primary Standard Industrial Classification codes reported by facilities in the Survey provide
an indication of the different activities in which the different subgroups participate. (The data reported
below and for all of the remaining summarizations are for water-using facilities only.)

        Over half of the PFPR/Manufacturing Facilities reported a primary SIC of #2879, defined as the
"formulation and preparation of ready-to-use agricultural and household pest control chemicals..."  (See
Table 3.12). About one-quarter of the PFPR/Manufacturing Facilities reported a primary SIC of #2869,
defined as "manufacturing industrial organic chemicals, not elsewhere classified...."

        In contrast, Refilling Establishments are involved  almost exclusively in  agricultural industry-
related products. Specifically, an estimated 67 percent of Refilling Establishments reported a primary
SIC of #5191:   "...wholesale distribution of animal feeds, fertilizers, agricultural chemicals, pesticides,
seeds, and other farm supplies, except grains".  An estimated 13 percent of Refilling Establishments have
aprimary SIC of #5153: "... buying and/or marketing  grain ... and ... beans."
                                               3.42

-------

100 -,
80-
60-
40-
20-
0-
f
Na
1






Rgure3.12

tional Estimates of Water-Using Facilities and Non-Water-Using Facilities
in trie PFPR Industry by Subgroup
| Non-Water Users Q Water Users
H26%




74%





2%

98%

™



7%

93%

1 PFPR/Mfg 1
Refilling Establishments Sanitizers
Source: Survey

• 31%







69%

Other

       The primary SIC codes reported by Sanitizer Facilities indicate their participation in formulating
a broad line of non-agricultural  products  that  are distinct from the product codes  reported  by
PFPR/Manufacturing Facilities and Refilling Establishments.  An estimated 28 percent of Sanitizer
Facilities have a primary SIC of #2842: "...manufacturing furniture, metal, and other polishes; waxes
and  dressings for  fabricated  leather...;  household, institutional,  and industrial plant disinfectants;
nonpersonal deodorants, drycleaning preparations, household bleaches, and other sanitation preparations."
An estimated 24 percent of Sanitizer Facilities reported their primary SIC as #2841:  "...manufacturing
soap, synthetic organic detergents,  inorganic alkaline detergents...."

        Other PFPR Facilities with less than 25 percent PFPR revenue participate hi widely diverse
business classifications, with 33 different primary SIC codes reported by the sampled facilities. These
facilities most frequently  report an SIC code  of #2899:   "...manufacturing miscellaneous chemical
preparations, not elsewhere classified...." These facilities also frequently report a primary SIC code of
#2842 (manufacturing furniture polish, etc.), fully defined above.
                                               3.43

-------
National Estimates of Primary SBCs1 Reported by PfPH Facilities
by Subgroup ,* '" w<
PFPR/Mfg Establishments Sanitizers Other
"••--' - ," <25% ' ' &35%
2879
2869
5191
5153
2842
2841
2899
Other
#of4-digit
primary SICs
reported
53% 45%
23%
67%
13%
28% 10%
24%
27%
24% 20% 48% 63% 55%
11 16 18 33 23
Note: Includes Water Users.
Source: Survey (1986-88).
i Includes all SIC production reported by at least 10 percent of facilities in a subgroup.
        Finally, the "mainstream" Other PFPR Facilities with at least 25percent PFPR revenue reported
 the highest participation in SIC group #2879 (formulating and preparing pesticides):   45 percent of
 facilities listed this SIC code as their primary business classification. This SIC code was also frequently
 reported by PFPR/Manufacturhig Facilities, and was fully defined above.

        Percent of revenue from PFPR
        As discussed in the introduction to this section, the extent to which facilities depend on PFPR
business as a revenue source will influence the decisions that facilities face in deciding whether to comply
with effluent guideline requirements. Accordingly, understanding how the different industry subgroups
vary in their reliance on PFPR revenue is important in structuring the impact analysis.  As discussed
below, the five subgroups fall into two distinct categories with relatively low reliance on PFPR revenues

                                              3.44

-------
exhibited by Refilling Establishments, Sanitizer Facilities, and (by definition) Other PFPR Facilities with
less  than  25 percent PFPR revenue.   In  contrast,  PFPR/Manufacturing  Facilities and Other  PFPR
Facilities with at least 25 percent PFPR revenue receive, on average, well more than a majority of their
revenue from PFPR activities.  Accordingly, it is these two latter subgroups of PFPR facilities that are
more likely to consider termination of their entire  facility operations when  faced with the financial
burdens of complying with effluent guidelines.
       Two  subgroups of  facilities  obtain  a  high percentage  of  their  revenue  from  PFPR:
PFPR/Manufacturing Facilities and Other PFPR Facilities with at least 25 percent PFPR revenue (See
Figure 3.13).   The estimated  median  percentage  of revenue from PFPR  for PFPR/Manufacturing
Facilities is 90 percent.  Other PFPR Facilities with at least 25 percent PFPR revenue are expected by
definition to have a substantial percentage of their revenue from PFPR. The estimated mean and median
percentages of revenue from PFPR for this subgroup are, however, dramatically higher than 25 percent,
at 83 percent and 98 percent, respectively.
                                                  Figure 3.13
                                National Estimate of Percent of Revenue from PFPR Activities
                                                by Subgroup
                                100
             K, .  ,  , .,  ....  ,.                PFPR/Mfg           Other>-25
             Note: Includes Water Users    Refining          "   SanWzer             Other <25
             Source: Survey                               Facilities
        The estimated mean and median percentages of revenue from PFPR for the other three subgroups
are all  very low.   For Refilling Establishments, the estimated mean and median percentages  are  15
                                              3.45

-------
percent and 6 percent, respectively.  For Sanitizer Facilities, the estimated mean PFPR percentage is 17
percent, with a median value of 5  percent.  Other PFPR Facilities with less than 25 percent PFPR
revenue are by definition limited to a low PFPR percentage.  The estimated mean and median percentages
are substantially lower than 25 percent, however, at 6 percent and 3 percent, respectively.

        Mix of formulating, packaging, and repackaging
        The particular set of PFPR activities — that is, formulating,  packaging,  and repackaging —
performed by facilities further define the five industry subgroups and highlight the  differences among
them.  Four of the five groups of facilities — the exception being Refilling Establishments — are
similar in this respect:  the majority of the facilities formulate and package pesticides (about 50 percent
to  80  percent)  followed  by formulating, packaging, and repackaging  as  the  next  most frequent
combination of activities  (about 15 percent to 40 percent).  The sole PFPR activity  undertaken by
Refilling Establishments is the repackaging of pesticides (See Figure 3.14).  On this basis, the Refilling
Establishments subgroup is markedly different from the other four industry subgroups.
                           100-
                            80-
                            60-
                            40-
                            20-
                Rgure3.14
 National Estimates of Refilling Establishments
and the Rest of the PFPR Industry by Facility Type
                    100%
                                                                               26%
                                                                               68%
            Note: Indudes Water Users   Refilling Establishments
            Source: Survey
                            Remainder of PFPR Industry
                                              3.46

-------
       Primary pesticide market
       As described previously in this section, the Survey requested information on the percentage of
revenue generated from 272 PAI-related pesticide revenue by market. For this analysis, EPA defined
a facility's primary market as the market from which that facility received at least half of its 272 PAI-
related PFPR revenues.  Ninety-nine percent of facilities had a primary market.

       Three industry subgroups are heavily concentrated in a single market:

•      For all  Refilling Establishments,  the primary  market  is the agricultural market  (See
       Figure 3.15).
•      An estimated 86 percent of Sanitizer  Facilities identify the institutional/commercial market as
       the primary market.

•      Although an estimated 55 percent of PEPR/Manufacturing Facilities identify agricultural sales
       as their primary market, the market participation of these facilities is somewhat more diverse than
       Refilling Establishments and Sanitizer Facilities, with significant participation levels in "Other,"
       Industrial, and "No Primary Market."

The two Other PFPR facility subgroups participate in a more diverse set of markets.  The three most
frequent primary markets for  Other PFPR Facilities with  at least 25 percent PFPR revenue are the
agricultural market (an estimated 44 percent of facilities), the home, lawn, and garden market (18 percent
of facilities), and the industrial market (11 percent of facilities).  Other  PFPR Facilities with less than
25 per cent PFPR revenue tended to operate primarily in one of the following four markets: the industrial
market (an estimated 34 percent of facilities), the agricultural market (21 percent of facilities), the
institutional/commercial market (18 percent of facilities), or the home, lawn,  and garden market (15
percent of facilities).
        Facility ownership structure
        The Survey also requested information on the ownership of the PFPR facilities.  Sanitizer
 Facilities and the two Other PFPR Facility subgroups exhibit similar ownership structures, with about
 an estimated 60 percent of facilities operating as single facilities and most of the remaining facilities
 operating as part of a multi-facility company (See Figure 3.16).  Nearly 80 percent of

                                               3.47

-------
                                                 Figure 3.15
                                 National Estimates of Primaiy* Pesticide Markets
                                             by Subgroup (1988)
                          ESi  Other Markets
                          IBM  Home, Lawn, & Garden
                          •  Industrial
                              No Primary Market
                              Institutional/Commercial
                              Agriculture
           too

            8O

            6O

            40

            2O

             O
100%
                              86%
                                              18%
                                              18%
                                              44%
                                                             34%
                                                             21%
                   „ _„,          PFPR/MfgOther >-25%
                   Refilling                        Sanldzers                     Other <2S%
          * The primary market of a facility. If one existed, was defined as the market from which the facility
          generated more than 50% of Its revenues. Markets that are primary for less than 5% of facilities in
          a subgroup are Included In 'other markets."
          Note: Includes Water Users
          Source; Survey                          Numbers may not sum to 100% due to rounding.
 PEPR/Manufacturing Faculties, on the other hand, are estimated to be owned by multi-facility companies.
 The dominance of this ownership classification distinguishes the PFPR/Manufacturing Facility from other
 subgroups, because no other subgroup showed more than a majority of ownership by multi-facility
 enterprises.  Refilling Establishments also show a relatively unique ownership configuration with an
 estimated 29 percent of these facilities being owned hi the form of a cooperative.  No more than 3 percent
 of the facilities in other subgroups identified cooperative as the ownership structure.  An estimated 44
 percent of the Refilling Establishments are owned as part of a multi-facility company with the remaining
 29 percent operating as single entities.

        Capital costs
        Firms require capital to begin, improve, or expand production.  The capital required to enter an
 industry may be sufficient to  impede market entry, thereby decreasing competitiveness within that
 industry.  The  ratio of the gross book value of depreciable assets to value added by manufacturing
provides a measure of the capital intensity of an industry.  The value of the ratio indicates the quantity
of capital hi dollars required to generate a single dollar of annual value added:  the higher the ratio, the
higher the capital intensity.  Data from the Bureau of the Census indicate that SICs 20-39, which include
                                                3.48

-------
                                                  Rgure3.16
                                  National Estimates of Ownership Characteristics
                                                 by Subgroup
                   M  Other
         Cooperative    H Multi-Facility    G Single Facility  j
               100
                80
                60
                40
                20
29%
                                          4%
                                          79%
I
                                                        33%
                             44%
                             27%
                                          17%
                                                                                 34%
                                                       67%
                                                                    53%
                                                                                 62%
                      Refilling

             Note: Includes Water Users
             Source: Survey
                                  PFPR/Mfg
                              Other >-25%
                   Sanitizers                  Other <25%
all manufacturing, had a capital intensity ratio of 0.75.43  SIC 2869, which includes the manufacture

of basic pesticides and many other organic chemicals, had a ratio of 1.96, representing a relatively high

capital  intensity for this segment of the pesticide industry.  Comparatively, the formulating/packaging

segment of the pesticide industry (SIC 2879), with a ratio value of 0.88, was less capital-intensive than

pesticide manufacturers but more capital-intensive than all manufacturing industry.44  Finally, Refilling

Establishments, represented by SIC 51, is the least capital-intensive industry in the comparison with a

capital  intensity ratio of 0.54.45'46
    43 U.S. Department of Commerce, Bureau of the Census.  1987 Census of Manufacturers, Preliminary Report
Industry Series: Industrial Organic Chemicals.  Washington, D.C.  July, 1989.

    44 Ibid.


    45 U.S. Department of Commerce, Bureau of the Census. 1987 Census of Wholesalers, Subject Series: Measures
of Value Produced, Capital Expenditures, Depreciable Assets, and  Operating Expenses.  Washington, D.C June
1991.


    46 Note: SIC 51, which represents the wholesaling of non-durable goods, is the most accurate measure of value
added for SIC 5191 available.  The 1987 value added statistics for SIC 519 (statistics are aggregated in the 1987
Census of Wholesalers Subject Series to the three-digit level) were withheld because the coefficient of variance
exceeded acceptable standards established by the Bureau of the Census.
                                                 3.49

-------
       The relative capital intensity of the five subgroups may also be evaluated by looking at the
average market value per PFPR production line reported in the Survey (see Figure 3.17). A high market
value per production line would suggest that significant capital expenditures are required  to  enter a
segment  of the PFPR industry.  PFPR/Manufacturing  Facilities report the highest market value of
production lines with a mean of close to $750,000. Other PFPR Facilities with at least 25 percent PFPR
revenues report an average value of production lines of over $400,000, while Other PFPR Facilities with
less than 25 percent PFPR revenues report an average value of less than $100,000.  Sanitizer Facilities
report still lower value per production line, with an average value per line of less than $70,000. With
an average production line value of $3,800, Refilling Establishments have a markedly lower market value
per line than the other five industry subgroups.  These data are consistent with the depreciable assets to
value added ratios reported by the Bureau of the Census.
Rgure3.17
National Estimates of Average Market Value Per PFPR Production Une
by Subgroup
$MH
800
700
600
500
400
300
200
100
0
D
736




3,836
1,909

,092






G Mean | Median
>
I
Note: Includes Water Users
Source: Survey


i

S" ^00 65,615
1,881
129,314


94,900
34,387
^ 4,943

PFPR/Mfg- Other >-25
Refilling Sanftizers Other <25%
                                             3.50

-------
       Facility employment
       Facility employment also varies substantially among the five industry subgroups.  Of the five
subgroups, PFPR/Manufacturing Facilities employed the most Full Time Employees (FTEs) per facility,
while Refilling Establishments employed the fewest (Table 3.13). On average,  PFPR/Manufacturing
Facilities employed 271 total FTEs and 18 272 PAI-related PFPR production workers in 1988.  In
contrast, Refilling Establishments supported an average of only 10 total FTEs and less than one 272 PAI-
related PFPR production worker.  Sanitizer Facilities had average total employment of 36, yet averaged
only one 272 PAI-related PFPR production worker. For both the Refilling Establishment and Sanitizer
Facility subgroups, the low ratio of 272 PAI-related PFPR production workers to total employment is
consistent with the relative PFPR revenue dependency of these facilities.  Total  employment at Other
PFPR Facilities varied little with reliance  on PFPR revenue,  averaging 53 FTEs for  Other PFPR
Facilities with at least 25 percent PFPR revenue and 64 FTEs for Other PFPR Facilities with less than
25 percent PFPR revenue. As would be expected, however, employment of 272 PAI-related production
workers varied considerably with the dependence on PFPR revenue. For Other PFPR Facilities with at
least 25 percent PFPR revenue, 16 of the average 53 total FTEs
involved 272 PAI-related production.  For Other PFPR Facilities  with less than 25 percent PFPR
revenue, only 1 of the average 64 total FTEs involved 272 PAI-related production.

       Facility revenue
        The subgroups differ substantially in facility size as indicated by average total  facility revenue.
PFPR/Manufacturing Facilities have much  higher annual facility revenues  — the estimated mean is
approximately  $110  million — than do all  other subgroups of facilities (See Figure 3.18).  Refilling
Establishments and Sanitizer Facilities have relatively low  facility revenues, with estimated mean values
of $5 million and $11 million, respectively. Other PFPR Facilities have similar average facility revenues,
regardless of the percentage of their revenue from PFPR.  The estimated mean annual  facility revenues
for both Other PFPR Facility subgroups are about $18 million.
        Facility profit levels
        An indication of the competitiveness of an industry can be determined by looking at the range
 of profitability found in the industry. Because the Survey data do not include costs below the facility
 level, only total facility profits can be calculated. Profits from PFPR activities or 272 PAI-related PFPR
 activities cannot be calculated. The profitability of the PFPR industry was assessed on the basis of return

                                              3.51

-------







Type of fEFR
Facility
Refilling
Establishments
PFPR/
Manufacturing
Facilities
Sanitizer
Facilities
"Other 5:25
Facilities <25
Average for
all facilities
Source: Survey.
1 Revenues represent
fable 3.13
Average Facility Employment Characteristics
- by Business type
(1985 Foll-Time Equivalents)

, "' '*,<,„, 272 PAI»Related
Aterage21^p.AI- Average " JMWRR
Related Revenues Total „, Production
(In $ Tbousands)1 Employment Employment
155.6 10 <1

66,728.3 271 18


250.5 36 1

PFPR Rev. 9,031.3 53 16
PFPR Rev. 405.7 64 1
3,038.6 39 3


a three year average (1986 - 1988), in 1988 dollars.
* * <• ^ j
x
•vS /••

•• v •• * .» w t *" ¥
^ Average Average
Other Nw*-"
Production Production
Employment Employment
5 5

170 83


22 13

14 23
35 27
20 16



 on assets (pre-tax facility profits as a percentage of facility assets). Averaged across the survey years of
 1986 to 1988, the estimated mean return on assets for the facilities engaged in PFPR activities was 23
 percent while the median was almost nine percent (see Table 3.14). The PFPR industry's return on assets
 at the 95thpercentile and 5th percentile was 177 percent and -54 percent, respectively.  These data reflect
 a significant concentration of moderately profitable facilities with a number of facilities reporting both
 very high profitability levels and very low profitability levels relative to the rest of the PFPR industry.
 In short, the PFPR industry exhibits a notable range of profitability.

        Facility profit levels, measured by the return on assets, are similar for four subgroups, with the
 exception of Refilling Establishments (See Table 3.14). Over the Survey period, median return on assets
 are estimated to be 14 percent for Sanitizer Facilities, 13 percent for Other PFPR Facilities with at least
25percent PFPR revenue, 12 percent for Other PFPR Facilities with less than 25 percent PFPR revenue,
and  11 percent for PFPR/Manufacturing Facilities. In contrast, Refilling Establishments are estimated
to have a much lower median return on assets of about 5 percent.
                                              3.52

-------
                                                Rgure3.18
                                     National Estimates of Facility Revenues
                                               by Subgroup
               $mm
                120

                100

                 80

                 60
                 40
                 20
        Mean
                   Median
110.0mm
                           Note: Includes Water Users
                           Source: Survey
                                      34.5 mm
                         18.4mm      18.2mm
                             4.5mm
                                                                            3.7mm
                                  PFPR/Mfg.                 Other >-25
                       Refilling                   Sanitlzers                 Other <25%
3.6     Summary
        The PFPR industry is a major industry, with an estimated 2,404 facilities active in this business.
User expenditures for pesticides are estimated to have been about $7 billion in 1991 (1988$). Although
the industry offers pesticide application services, the main output of the industry is pesticide products.
These products are sold primarily to the agricultural market, with the institutional/commercial sector and
the home/lawn/garden sector also providing major markets.  Overall, user expenditures hi the PFPR
market have not shown a consistent trend of growth or decline over the period 1981 to 1991. Also, the
demand for pesticide products is generally expected to be inelastic: that is, demand for pesticide products
overall is not expected to decline significantly with moderate price increases.

        Much of the data provided hi the profile were developed from the Survey administered to the
PFPR industry in 1990, covering the years 1986-1988. These years are believed to be representative of
the financial performance of the PFPR industry over broader time  periods.  The assessment of the
representativeness of the Survey data is based on the U.S. economic climate from  1986 to 1988 as well
as the growth rate and revenues achieved by the PFPR industry over this tune period.
                                              3.53

-------
Nation
Subgroup of Facility
Refilling Establishments
PFPR/Mfg. Facilities
Sanitizer Facilities
Other 5: 25%
Other < 25%
Across All Facilities
al Estimates of JPJTPR %tur» m Assets*
By Subgroup - """
TJwee Jfear A^age2 ' '""'
Mesa.
6.8%
27.6
29.9
40.1
40.4
23.0
1 Pretax facility profits as a percentage
2 Source: Survey (1986-1988).
Includes Water Users
Me4i*n 5th PerceQtil
4.7% -86.4%
12.5 -15.7
13.6 -56^Li
13.4 -34.1
12.1 -23.0
8.6 -53.9
of total facility assets.
* 95th Perceatile
> 174.4%
87.6
^ 122.1
175.6
192.2
176.9

        Based on data from the Survey, an estimated 25 percent of the PFPR industry operated without
 using water in their 272 PAI-related operations in 1988. These non-water-using facilities appear to be
 somewhat smaller  and less involved in PFPR activities than the water-using facilities.  The median
 profitability between the two groups is similar, however, as are the  major markets  hi which they
 participate and their ownership structure.

        Finally, the PFPR industry consists of five distinct subgroups of facilities: PFPR/Manufacturing
 Facilities, Refilling Establishments,  Sanitizer Facilities,  Other PFPR Facilities with at least 25 percent
PFPR revenue, and Other PFPR Facilities with less than 25 percent PFPR revenue.  These subgroups of
facilities vary in their primary activities, major pesticide markets,  ownership structure, capital  costs,
facility  employment levels, facility  revenue levels, and facility profit levels.  In particular, Refilling
Establishments and Sanitizer Facilities have relatively low facility revenues and Refilling Establishments
have relatively low profitability.
                                              3.54

-------
                                          Chapter 4
                                  Facility  Impact Analysis

4.0     Introduction
        This chapter presents the methodology used to project impacts of the proposed effluent limitations
guidelines and standards at the facility level, and describes the results of the analysis.  As discussed in
Chapter 1, the facility analysis is the principal  building block of the entire economic impact assessment.
The facility impact analysis is characterized by the following:

        (1)     use of economic models to estimate baseline and post-compliance costs and revenues for
               individual facilities;
        (2)     separate  models of the  decision-making process  for three  groups  of pesticide
               formulating/packaging/repackaging (PFPR) facilities: (1) refilling  establishments,  (2)
               PFPR facilities that also manufacture pesticide active ingredients (PAIs) or that receive
               at least 25 percent of their revenue from PFPR activities, and  (3) "other" PFPR facilities;
        (3)     comparison of annualized compliance cost to facility revenue is used to project significant
               economic impacts for all three groups of facilities;
        (4)     application of a discounted cash flow analysis to project closure of PFPR facilities that
               also manufacture PAIs (PFPR/manufacturing facilities) or that receive at least 25 percent
               of their revenue from PFPR; and
        (5)     evaluation of the return on assets at "other" PFPR facilities to project conversion of
               PFPR operations.

        The cost, revenue, and quantity outputs from the first step provide input to the facility closure
and PFPR conversion analyses  of the subsequent steps. Facility closure is the most severe of the three
impacts evaluated, while line conversions and  annualized compliance costs in excess of five percent of
facility  revenue represent more moderate impacts.  In contrast to  facility closures  and product line
conversions, compliance costs in excess of five percent  of facility revenue  are  assumed not to be
associated with an operational change at a facility.  Compliance costs that are less than five percent of
facility  revenue are commonly judged to be economically achievable.  (See, for example, the EIA for
effluent guidelines limitations and standards for  the OCPSF industry and the  pesticide manufacturers
industry).
                                               4.1

-------
        The main body of this economic analysis evaluates the economic impacts of a PSES regulation
 on facilities discharging to a POTW.  A zero direct discharge limit of process wastewater pollutants from
 PFPR was promulgated  under the 1978 pesticide chemicals BPT regulation.   Therefore, for most
 facilities, no costs associated with limitations on direct discharge of pollutants are considered. However,
 16 facilities that both manufacture  PAIs  and PFPR have been combining pesticide manufacturing
 wastewaters with wastewaters generated from PFPR and discharging these wastewaters directly.  These
 facilities have technically  achieved the limits in their NPDES permits, which provide discharge limitations
 for pollutants generated in the PAI manufacturing process but give no allowance for the pollutants present
 in the PFPR wastewater.  These facilities, however, should already have been complying with the BPT
 zero  discharge requirement for thek PFPR  wastewaters.  The effluent guidelines for direct dischargers
 in the pesticide manufacturers subcategory  were recently revised to impose mass-based limitations on
 pesticide manufacturing wastewaters.  The likely result is that the combined pesticides manufacturing and
 PFPR facilities will no longer be able to discharge their PFPR wastewaters directly and still meet the
 limits in their permits.  Any additional costs to these facilities of meeting the 1978 BPT zero discharge
 requirement for  PFPR facilities are not attributable to this  PFPR  rulemaking.   Nevertheless, for
 information purposes, EPA has evaluated the costs to these facilities of achieving zero discharge of their
 PFPR wastewaters given that they have not been achieving zero discharge to date. The impact evaluation
 for these facilities addresses only facility-level impacts.

        The analysis of facility-level impacts relies heavily on the responses to the survey administered
 to a portion of the PFPR industry by EPA1.  As discussed in Chapter 3, EPA sent a questionnaire
 requesting technical and  economic information to 707 PFPR facilities  in 1990.  The questionnaire
 consisted of an introduction, a section requesting technical information (Part A), and a section requesting
 financial and economic data (Part B).   Six hundred and ten PFPR facilities were selected from the
 population of 3,241 facilities thought to be engaged in PFPR activities.  The sample facilities were
 identified largely through the FIFRA  and TSCA Enforcement System (FATES) database.  The sample
 was stratified by  classifying PFPR products as fungicides, herbicides, insecticides, other products,  or
 combinations thereof.  Additional strata were defined by production,  measured in pounds. Within each
    ^e Survey was conducted under the authority of Section 308 of the Federal Water Pollution Control Act (the
Clean Water Act).
                                              4.2

-------
stratum, the population was randomly sampled.2  In addition, 92 pesticide manufacturing facilities were
sent a questionnaire.  For ease of reading, the remainder of this report relates data extrapolated to the
entire PFPR population and does not report data for the sample unless otherwise indicated.

       Questionnaire responses indicated that 2,404 facilities remained in the PFPR business as of 1990
(the year the Survey was conducted).  An estimated 1,794 of these facilities both remained in business
as of 1990 and use water in their PFPR operations.3 An estimated 656 of these facilities discharge water
directly or indirectly from their PFPR operations.  These 656 facilities are therefore the facilitkS'ttat may
be subject to cost increases as a result of the effluent limitations guidelines and standards.

       The remainder of this chapter is organized as follows.  An economic.model of the PFPR industry
is developed in Section 4.1.  Section 4.2 describes the measures used to assess  economic impacts upon
PFPR facilities, and Section 4.3 provides  the detailed impact calculations.  Section 4.4 concludes the
chapter with a presentation of the facility impact  results.

4.1    Economic Model
       Before presenting the specific model used in the analysis to estimate post-compliance costs, prices,
and quantities, a brief overview of the conceptual problem is provided.

        Generalized Model of the PFPR Industry
        The  model of the PFPR  industry focuses on the short  run.  The focus on the short run, by
definition, limits facilities' and firms' options for responding to increased costs for pollution control and
is therefore conservative (i.e., it tends to overstate impacts). For example, in the short run, firms cannot
register new  products or  make major modifications to physical plants.  They are free, however,  to
decrease or increase quantities produced, or change the production mix when faced with new pollution
control requirements.
    2See the Technical Development Document for additional information on the sample design.
    3It is possible that facilities producing only solvent-based pesticides discharge solvents to surface waters. In
 the vast majority of cases, however, solvents are recovered and reused.   The proposed rule would therefore not
 affect these facilities and they are not included in the analysis.
                                                4.3

-------
       Each facility must decide the quantity of each registered pesticide product to produce, given
certain technological and capacity constraints.  Different pesticide products may be produced easily at the
same facility if, for example, they vary only in concentration.  PFPR equipment is typically flexible
enough that the facility may use it to produce a variety of products, perhaps with minor adjustments or
modifications.  A producer may also elect to use a facility at a higher level of capacity (perhaps by adding
an additional shift), thereby increasing the production of one or more pesticides.

       In addition to incorporating the short-run options, the model must capture the nature of regulatory
compliance costs and  their effect on production decisions.  Ideally, these costs are a function of the
production mix.  For  example, different technological controls may be required if a facility decides to
produce pesticide i instead of pesticide j.  A facility may also find that the same controls may be used
for two different pesticides, so that the incremental control costs of producing pesticide i may be very
small as long as pesticide k is also produced.

        Given  all these considerations, the profit maximizing problem for facility f can be depicted as:
 where:
 Qif
 EC*
profit of facility f ;
price of product i, a function of total industry production of product i (Qj), and
industry production of all products competing with product i;
production of product i by facility f (The sum of the Qtf's, f = 1,N equals Qj);
=      total cost to facility f of producing product i; and
total pollution control costs to facility f required under the proposed option to
produce product i.
                                                4.4

-------
Each facility in the industry attempts to maximize profits simultaneously.  The equilibrium solution is
represented by the matrix Q (total industry production), whose typical element Q^ represents facility f s
production of product i, that solves the profit maximizing problem for all facilities simultaneously.

        Data  limitations, however, require that the model be simplified.   In particular, the entire
production choice set (of registered products) available to each facility is unknown. Given this limitation,
it is assumed that a facility may respond to a new effluent guideline only by decreasing current production
of the pesticides currently produced.  This assumption neither allows for the production of new products
(i.e., those that were not being manufactured before the guidelines were introduced), nor does it allow
one PFPR facility to benefit from the compliance costs and subsequent decrease in pesticide production
 of another PFPR facility. Note that this assumption is extremely conservative, since it severely limits
 the options available to each facility and thus overstates the impact of the regulation. A detailed analysis
 of firm-level pesticide registrations would be necessary to relax this assumption.

         Further, given the extremely large number of registered pesticide products, compliance costs
 cannot be allocated to specific products.  Rather, compliance costs are derived in aggregate for PFPR
 operations.4 Facility decision making processes are modeled for PFPR operations as a whole, not for
 individual pesticide products.  Built on this generalized model, the applied economic model of the PFPR
 industry is described below.

         Applied Model of the PFPR Industry
         The construction of a model of the PFPR industry,  and the simulation of the effects  of new
  effluent limitation guidelines and standards, require the following basic steps:

          (1)     Define the markets to be analyzed;
          (2)     Determine the basic model of market structure;
          (3)     Estimate baseline revenue for each facility;
          (4)     Estimate baseline costs  for each facility;
      4See the Technical Development Document for a complete discussion of the methodology by which compliance
   costs are estimated.
                                                  4.5

-------
         (5)     Adjust baseline costs for other government regulations;
         (6)     Project facility compliance costs;
         (7)     Estimate post-compliance prices; and
         (8)     Calculate post-compliance cash flow for each facility.

 These steps are explained below.

        Markets to be Analyzed
        Although a market is defined by competing products, not all pesticides compete with each other
 at the consumer level. For example, pesticides used as herbicides on corn do not compete with pesticides
 used as fungicides on residential gardens.  Neither do all pesticides used as herbicides compete with one
 another.  Because pesticides compete with each  other individually or in groups rather than as a whole,
 EPA defined clusters of PAIs based on competition among the end-use pesticide products containing those
 PAIs.

        The classification of PAIs into clusters was done by EPA's Office of Pesticides Programs (OPP)
 for its regulatory  purposes.  In 1980, the OPP defined pesticide markets to ensure that EPA regulated
 competing products on roughly the same schedule, so that one pesticide does not have an unfair advantage
 over another.  As described hi Chapter 3, the pesticide markets were defined as clusters of PAIs that are
 substitutes for a specific end-use. For example, insecticides used on corn represent one market or cluster.
 The OPP assigned each of the PAIs registered in 1980 to one of 48 separate clusters.5  With the help
 of the OPP, EPA's Office of Water made minor adjustments to these pesticide clusters for use in the EIA
 for effluent limitations for pesticide manufacturers. First, PAIs registered after  1980 were assigned to
 clusters. In addition, clusters were split when a wide range of price elasticities of demand were estimated
 to exist within a single cluster and it was possible to further differentiate corresponding PAI uses within
 the cluster (see Appendix C).  Five clusters were  split, increasing the number of clusters from 48 to 51.6
    In the OPP's classification, each PAI appeared in only a single cluster, since the purpose of the classification
was to develop a regulatory schedule for each PAI.
    One of these clusters was split after the EIA for pesticide manufacturers was released, to distinguish betw
the distinct uses for sporicidal and non-sporicidal disinfectants.

                                               4.6
'een

-------
Finally, PAIs were allocated to more than one cluster when the PAI was known to be used in substantial
quantities for different end uses.  The 272 PAIs originally considered for regulation, along with numerous
non-272 PAIs, are mapped into the 57 separate clusters, as listed in Appendix B.

        It would be preferable to analyze the PFPR industry on a formulated product level, analogous to
the PAI-level and cluster-level analyses performed in the pesticide manufacturer effluent limitations EIA.
Data limitations, however, and the desire to limit industry response burden, do not allow EPA to analyze
the PFPR  industry on a formulated product level,  for  several reasons.   First,  the PFPR industry
formulates PAIs into many thousands of pesticide products, often combining several PAIs with different
functions into one product.  It is not always possible, therefore, to group formulated pesticide products
into  individual clusters. Further, industry would have been heavily burdened by supplying cost and price
information for each pesticide product.  Instead, revenue information was requested in the Survey from
the formulating,  packaging,  or  repackaging of all pesticides.  (Revenue data did  distinguish between
revenue from pesticides containing one of the 272 PAIs originally considered for regulation and pesticides
containing only other PAIs.)  To promote the accuracy and decrease the burden of industry response,
cost data were requested only at the level of the facility.7 Given the difficulties of analyzing business
decisions on the basis of individual PAIs or formulated products, most of the analysis is conducted for
all PFPR operations or for the entire facility.8

        Basic Model of Market Structure
        Assumptions made about market structure have important implications for empirical modeling.
For  example, the standard model  of supply and demand (i.e., perfect competition) necessarily predicts
at least one facility closure if production costs increase.  (When the supply curve shifts up to reflect the
cost increase, quantity must decrease and the marginal facility must close.) Several factors suggest that
markets for pesticide products are highly competitive.  First, the production data obtained from FATES
and  the Survey indicate that, for most clusters, multiple facilities sell pesticide products formulated from
PAIs from the cluster. Second, numerous facilities may formulate and package  products containing the
same PAI.  In contrast, among manufacturers, a PAI typically is produced by only one manufacturer who
    ^Industry had indicated that some categories of costs, such as labor expenses, are not tracked at either the PAI
 or pesticide product level.
    8Oertain sections of the analysis, however, such as the estimates of the price elasticity of demand, are built on
 the PAI clusters, because no data exist on elasticities for formulated pesticide products.
                                                4.7

-------
can sell that PAI to many different PFPR facilities.  Finally, the existence of contract tolling in the PFPR
industry, where small PFPR facilities may formulate products owned by larger firms to smooth capacity
constraints, serves to increase the number of facilities formulating a given product.

        At the same time, other factors suggest that the PFPR industry is less than perfectly competitive,
exhibiting both elements of product differentiation and monopolistic competition. Specifically, firms tend
to produce differentiated products that compete, but that are not perfect substitutes; therefore, product
differentiation  exists within even closely competitive markets.   For  example, different  pesticides,
produced using PAIs within the same  cluster, may be differentially effective on a regional basis due to
climate differences.  Pesticides may also vary in their effectiveness on different varieties of pests and on
different varieties of crops. The structure of the pesticide markets can therefore generally be described
as competitive with differentiated products.  The PFPR industry also has some monopolistic components.
In particular, the existence of vertically integrated firms that both manufacture PAIs and  formulate
products containing those PAIs indicates an aspect of monopolistic competition.  In an industry with these
characteristics, different prices may exist for similar products within  a  single market.  Firms  must
compete for customers in terms of both price and the kinds of products they sell.  Also, new firms may
enter the industry with a new product  whose differentiation from its competitors' products may make it
profitable.

        Baseline Revenue for Each Facility
        Baseline revenues, both for the total facility and for only its PFPR operations, are required to
evaluate- impacts of the regulation. Facility baseline revenue is calculated as the three-year average (1986,
1987, and  1988) of facility revenue as  reported in the PFPR Survey (question 8 of Section B). Revenue
from PFPR operations is similarly calculated as the three-year average of reported Survey data (question
8 minus question 7 of Section B).  These  revenues include PFPR of all pesticides, pesticide contract
work, and  revenue from services that include the provision of pesticide products.
       Baseline Costs for Each Facility
       Baseline facility and PFPR costs are also required for the analysis.  Baseline facility costs are
calculated as the three-year average of facility costs as reported in the Survey (question 19 of Part B).
In contrast to revenues, facilities were not asked to report costs specific to PFPR operations.  Industry
comments on the pre-test of the Survey indicated that some costs, such as labor, are not maintained on
                                               4.8

-------
a product-specific basis, and that such cost estimates would be very burdensome to generate and of only
limited accuracy.  The Information Collection Request (ICR) for the final PFPR Survey recognized that
"some expenses are difficult  to  allocate to specific products within a facility."  The ICR stated  that
"information is requested for the entire facility and EPA will  allocate expenses  to pesticide and non-
pesticide product lines in a uniform manner."  The analysis therefore assumes a constant profit margin
across a facility's operations.  PFPR costs are calculated as:
where:

PC
FC
PR
FR
               three-year average PFPR-related costs;
               three-year average facility costs;
               three-year average pesticide revenue; and
               three-year average facility revenue.
        Baseline Cost Adjustments Due to Other Government Regulations
        Since 1988  (the  Survey base year), the EPA  has  promulgated  three regulations  affecting
 PFPR/manufacturing facilities whose compliance costs are not reflected  in the Survey data.  These
 regulations are (1) Resource Conservation and Recovery Act (RCRA) land disposal restrictions (40 CFR
 268), (2) effluent limitations for the Organic Chemicals, Plastics, and Synthetic Fibers (OCPSF) industry
 (40 CFR 414)9,  and (3)  effluent limitations for the pesticide manufacturing industry (40 CFR 455).
 Also, Congress passed the Federal Insecticide, Fungicide,  and  Rodenticide Act (FIFRA) Amendments
 of 1988, most of which became effective in December, 1988.  The costs associated with the amendments
 therefore may not be included in the Survey responses. These amendments affected all PFPR  facilities.
 To represent the costs faced by the PFPR industry accurately, the costs associated with each of the above
    9Although effluent limitations for the OCSPF industry were promulgated in 1987, the rule was not in effect
 prior to the Survey base year of 1988.
                                               4.9

-------
 regulations are added to reported facility costs.  The regulations and their costs to the PFPR industry are
 discussed below.10

        Hazardous and Solid Waste Amendments. The 1984 Hazardous and Solid Waste Amendments
 (HSWA) to RCRA had several new provisions, some of which went into effect after 1988. In particular,
 the Land Disposal Restrictions included  in HSWA are likely to  have affected manufacturing/PFPR
 facilities. These regulations prohibit land disposal of hazardous waste until it has been treated to the level
 achieved by the Best Demonstrated Available Technology.

        Congress directed the EPA to write the rules in three stages.  Stage 1 regulated solvents and
 dioxin and was promulgated in 1986.  Stage 2, signed July 8, 1987, regulated a group of wastes known
 as the "California list." For Stage 3, the remaining hazardous wastes were divided into thirds, and signed
 into regulation on August  17,  1988;  June 23,  1989;  and May 8,  1990.  Each of these rules became
 effective shortly after promulgation.

        Many PFPR/manufacturing facilities generate RCRA-listed wastes as a result of PAI production,
 and will therefore have incurred costs of complying with the land disposal restrictions.  Particularly for
 the Stage 3 wastes, these costs may not be included in the Survey data. For this reason, the compliance
 costs estimated  for Stage  3  hazardous wastes were  added  to  the  baseline fixed  costs  for
 manufacturing/PFPR facilities.   Because Stages 1 and 2 of the rule became effective by 1987, the costs
 associated with these stages are assumed to be reflected in the Survey data.

        The cost estimates  were developed from two sources.  The 1986 Survey of Hazardous Waste
 Generators (GENSUR) conducted by the EPA's  Office of Solid Waste (OSW) was used to determine the
 waste streams for pesticide manufacturing facilities.  These data were combined with cost data from the
 Regulatory Impact Analyses (RIAs) for the land disposal rules.  Of the 47 manufacturing/PFPR  facilities
 remaining in the PFPR business as of 1990 that use water, 18 facilities were included in the GENSUR
 data base.  The GENSUR data are organized by facility and waste stream.  For each facility and waste
 stream,  the following data were available:
    Regulations not effective until 1988 are added to the costs of each of the Survey years (1986, 1987,  1988).
This may overstate 1988 costs in some cases.  Conversely, costs resulting from regulations that became effective
in 1987 and 1986 are not added to the baseline; therefore, the analysis may understate the costs in those years.
                                             4.10

-------
       (1)     RCRA waste codes (up to 10 codes per waste stream);
       (2)     Quantity of waste generated on-site and quantity disposed of off-site;
       (3)     On-site waste management train (up to 10 waste management procedures); and
       (4)     Off-site disposal train.

       For purposes of estimating costs associated with the land disposal restriction rules, the data were
first scanned  to  select only  those  components dealing with land  disposal  (i.e.,  landfill, surface
impoundments, and waste piles).  The RIAs for the first and last third of the Stage  3  Land Disposal
Restrictions included total gallons of waste to  be treated  and  total incremental costs by  baseline
management practice and RCRA waste code.  This allows calculation of unit (per gallon) costs for each
RCRA waste by management practice.1 *

       For each pesticide manufacturing facility and waste stream, management and RCRA waste codes
were matched to the corresponding codes in the RIA to obtain unit costs for each facility, waste stream,
and management combination.  These unit costs were then multiplied by the appropriate quantities (i.e.,
gallons of each waste at each facility managed, using each relevant method) to estimate  a total cost for
each RCRA rule.

       Costs of complying with the middle third of the Stage 3  rule were not available in similar detail,
because Stage 3 was not considered to be a major rule. The available information included total quantity
of covered waste generated and total incremental costs by baseline management practice (i.e., not broken
down by RCRA waste code).  It was necessary, therefore, to  assume that the wastes covered by this rule
had the same  unit costs. Given the small number of wastes in this group, this assumption  is not expected
to affect  the analysis substantially.

       Eighteen PFPR/manufacturing facilities that were in business as of 1990, and use water, were
projected to incur costs due to the RCRA rules described above. Total  annualized Stage  3 RCRA after-
tax  costs for these facilities are estimated to be $312,000, in 1988 dollars. Not all of these costs may
have been borne by the PFPR/manufacturing facilities, however; a portion may have been  passed through
    nThe RIA for the first third examined two alternatives and two scenarios within the first alternative. The costs
for Alternative A, Scenario I, were used because this option was closest to the final rule.

                                              4.11

-------
to customers in the form of higher prices. Since there exist no readily available data about the portion
of costs likely to be passed  through to consumers,  the analysis assumes that the burden of the cost
increase is split evenly between the facilities and the customers. In other words, the facilities are assumed
to bear 50 percent of the cost increase.12  These costs, totalling $156,000, were added to the baseline
fixed costs of the affected facilities.

        OCPSF Effluent Limitations Guidelines and Standards.  The final OCPSF Effluent Limitations,
issued November 1987,  established effluent limitations guidelines and standards for OCPSF  process
wastewater.   Compliance  with the  rule  was required  by  no  later  than November,  1990.13   The
regulations for  direct dischargers  covered about 60  priority pollutants; those for indirect dischargers
covered 47 priority pollutants.  For purposes of the regulation, OCPSF process wastewater was defined
to include establishments, or portions thereof, whose products are classified in any one of five SIC codes:
SIC 2821 (plastics and resin materials), SIC 2823 (cellulosic manmade fibers), SIC 2824 (non-cellulosic
synthetic fibers), SIC 2865 (tar crudes, cyclic intermediates,  dyes and  organic pigments) and SIC 2869
(industrial organic chemicals, not elsewhere classified).

        Substantial overlap exists  between facilities subject to the OCPSF effluent guidelines  and the
manufacturer/PFPR facilities covered by the PFPR effluent guidelines. Of the 47 manufacturing facilities
that are PFPR and use water, 15 also manufacture compounds regulated  under the OCPSF rule.  The
estimated costs to comply with the PFPR rule will  be incremental to those of meeting the OCPSF rule.
For this reason, OCPSF costs for all manufacturing/PFPR facilities affected by both rules are added to
    '*Note that if the facilities were assumed to bear the entire cost increase of these regulations (worst case), the
analysis would yield two results.  First, facilities would be more likely to have a significant impact in the baseline,
possibly resulting in fewer facilities impacted by the proposed regulation.  Second, facilities not impacted in the
baseline would be more likely to have a significant impact post-compliance. The net effect of these two results is
indeterminate. Assuming that half of the costs are borne by facilities is therefore a more balanced assumption than
assuming that either all or none of the costs are borne by the facilities.
    13In  1990,  the  U.S.  Fifth Circuit  Court of Appeals remanded  certain  aspects of the rule  for further
consideration. The Agency promulgated a revised final rule in July, 1993.  Revisions were made to certain of the
19 remanded BAT Subpart J pollutants and 11 of the 13 PSES pollutants.  Also, PSES were eliminated for 2,4-
dimethylphenol and phenol due to adequate treatment at POTWs. Independent of the litigation, the EPA corrected
criteria for designating metal- and cyanide-bearing wastewater streams.  Facilities subject to these portions of the
rule are required to comply as of July 1996, or when their existing permit comes up for renewal, whichever data
occur later. Costs were not recalculated for the July, 1993, rule due to  the advanced stage of the PFPR analysis.
These cost changes would not be expected to affect the conclusions of the analysis.

                                               4.12

-------
the economic baseline.  Annualized OCPSF after-tax costs for these 15 facilities total $10.8 million, in
1988 dollars. Because no data on the portion of costs likely to be passed through to customers are readily
available, the analysis again assumes that the burden of the  cost increase is split evenly between the
facilities and the customers. The facilities are assumed to bear 50 percent of the cost increase, resulting
in total annualized costs  borne by the facilities of $5.4 million.

        Pesticide Manufacturer effluent limitations guidelines and standards:  PAI price increases.
Two effects of effluent  guidelines for  pesticide manufacturers are included  in the analysis.  First,  a
portion of the compliance costs resulting from the effluent guidelines are expected  to be passed on to the
manufacturers' customers — that is, PFPR facilities.  The costs to facilities for purchasing certain PAIs
are therefore expected to increase.  The average price increase for each PAI is calculated as the sum of
the increase in price for  that PAI at each facility that  manufactures the PAI multiplied by the proportion
of total production of the PAI at each facility.  In other words,  the price increase of a PAI is the weighted
average of the price increases  over all manufacturing  facilities producing the PAI,  where the weights are
each manufacturer's share of total production of that PAI. Algebraically,  the equation is:
where:
API
PI
   i,J
the average price increase per pound of PAI, i;
the price increase per pound of PAI, i, at manufacturing facility, j; and
pounds of PAI, i, produced at manufacturing facility, j.
 Increases in costs to each  PFPR facility are calculated as the  amount of each  PAI the facility used
 multiplied by the average price increase for each PAI.  The equation is:14
    14This calculation of cost increase assumes that all PAIs are purchased domestically and therefore overstates
 the impact on PFPR facilities.
                                               4.13

-------
 where:
 a
 API
 the total PAI cost increase incurred by PFPR facility, k; and
 the average price increase per pound of PAI i,
 the quantity  of PAI i, used by PFPR facility, k.
        The resulting total estimated PAI price increases for the 634 PFPR facilities in business as of
 1990 that use water and that would be regulated under PSES are $3.4 million per year.  Consistent with
 the handling of the regulatory costs discussed above, half of these costs are assumed to be borne by the
 facilities.

        Pesticide manufacturer effluent limitations guidelines and standards: PFPR facility cost
 increases. The second effect of the effluent limitations guidelines for pesticide manufacturers is that
 pesticide manufacturers are expected to bear a portion of the compliance costs. Not all of the compliance
 costs associated with the pesticide manufacturer effluent limitations are expected to be passed on to PFPR
 facilities in the form of higher PAI prices.   These cost increases are calculated  for each pesticide
 manufacturing facility as follows:
where:
CJ
PP:
Annual compliance costs of pesticide manufacturers effluent limitations borne by facility
j;
Annual compliance costs for PAI, i, at facility j; and
Percentage of PAI i compliance costs assumed to be passed through to customers.
Additional  annualized after-tax costs totalling $5.6 million are added to the baseline costs for the 47
PFPR/manufacturing facilities in business as of 1990 that use water.
                                              4.14

-------
       FIFRA amendments.  The FIFRA Amendments of 1988 strengthened the EPA's authority in
several major areas of pesticide regulation. These new provisions, effective December 24, 1988, affected
the costs incurred by PFPR facilities by requiring pesticide re-registration fees and annual maintenance
fees.  Re-registration fees are levied on manufacturers of PAIs.  For each active ingredient intended for
use on major  food  or  animal feed crops, registrants  are required to pay re-registration fees totalling
$150,000.  For PAIs not intended for major food or feed uses, registrants are  required to pay a fee
between  $50,000 and $150,000 (EPA,  1988 "Highlights of the 1988 Pesticide Law").  PAI fees are
apportioned among registrants of each PAI based on market share.  Since this is a one-time fee, however,
these costs are not added to the baseline.

       In contrast, annual maintenance fees are added to the baseline costs. Unlike the re-registration
fee, which is charged to  PAI manufacturers, the annual  maintenance fee is assessed for each individual
pesticide product.  The fee amount paid generally increases with the number of  registrations held (see
Fee Table A, in "Instructions to Registrants for Filing  1993 Pesticide Maintenance Fees").  A multi-
facility firm  may  register the  products used by its facilities separately or jointly, at its discretion.
Depending on the number of facilities and products, it may be advantageous for the firm to file a single
form listing all of its registrations, or to file separate forms for some or all of its facilities.  For the first
registration, the maintenance fee is $650. Each additional registration costs $1,300, to a maximum of
$55,000  for 50 or fewer  registrations and $95,000 for any number of registrations.

       The FIFRA maintenance fee  schedule allows small businesses to pay lower filing fees than other
businesses if  they hold  more than 30  registrations.  The definition of "small" used in FIFRA is a
registrant that employed 150 or  fewer  personnel as of December  1, 1992, and  during the three-year
period ending on December 31, 1991 had an average annual gross revenue from chemical sales that did
not exceed $40 million.  For purposes of determining whether it is a small business, a registrant must
include its own as well as any corporate parents' or subsidiaries' employees and chemical sales.  Because
the Survey does not include any data on chemical sales  at the firm level, and no secondary  sources
supplying this information were identified, the employment criterion alone is used in the analysis to assign
lower costs to small entities. If the facility is a single-facility firm, employment data are available from
                                              4.15

-------
 the  Survey.   Employment data  for  multi-facility  firms  were  obtained  from  The Million Dollar
 Directory.15 If employment data for a firm were not known, it was assumed not to be a small business,
 providing a conservatively high estimate of FIFRA maintenance fees.

        Data on the number of products containing the original 272 PAIs used at each surveyed facility
 were obtained from the FATES database and from the Survey.  Because the Survey sample does not
 necessarily contain all facilities of a multi-facility firm, the analysis calculates FIFRA maintenance fees
 assuming each  facility pays the fees for all products it uses.  This may have the  effect of overstating
 FIFRA costs to multi-facility firms, since multi-facility firms may combine their registrations.  Because
 Survey respondents were  asked to confirm the  number of 272 PAI products, not the total number of
 pesticide products, the estimated FIFRA maintenance costs may understate the actual costs.

        Based on the number of registered products reported by each PFPR facility, the analysis includes
 the annual maintenance fees in baseline costs.  The estimated FIFRA maintenance costs are deflated to
 1988 dollars using the CPI deflator. Total after-tax FIFRA maintenance fees estimated for the 1,794
 PFPR facilities in business as of 1990 that use water are $6.0 million per year.  Consistent with the
 handling of RCRA and OCPSF, half of these costs ($3.0 million) are assumed to be born by the facilities
 and half are assumed to be passed through to customers in the form of higher prices.

        Estimated Facility Compliance Costs
        Full details of the methods by which the costs of complying with the regulatory options  were
estimated can be found in the Technical Development Document.  A summary of  the cost components
and the annualization method are presented below.

        Compliance costs were projected at the facility level.  For facilities that both manufacture  PAIs
and perform PFPR operations, the compliance costs are based only on the PFPR operations of the
facilities.  These costs will be  incremental to compliance  costs for the manufacturing operations of the
facility. The cost estimates for  PFPR/manufacturing facilities are based on the assumption that, whenever
     See the regulatory flexibility analysis in Chapter 5 for additional information on firm counts and estimating
firm-level employment.

                                             4.16

-------
possible, facilities will build on existing treatment.  Cost estimates for non-manufacturing PFPR facilities
are based on the assumption that there is no existing treatment equipment in place.16

       For the regulatory options considered, two categories of compliance costs were evaluated:  capital
costs and operating and maintenance costs (including compliance self-monitoring and sludge disposal).
The capital costs are one-time "lump sum" costs; the operating and maintenance costs are projected on
an annual basis. Capital costs were annualized (assuming that the capital equipment has a productive life
of ten years)  using the real weighted average cost of capital (discussed below).   The equation for
calculation of total annualized costs is:
                                      ACC   =  OM  +
                                        CPT
                                        PVF
where:
ACC
OM
CPT
PVF
RWACC
annualized compliance costs in 1988 dollars;
estimated annual operating and maintenance costs;
estimated capital costs;
present value factor = £1=1,10 1/(1 + RWACC)'; and
real weighted average  cost of capital.
 Annualized compliance costs  were added to  facility baseline costs  to  perform the post-compliance
 analyses.

        Cost of capital. The cost of capital is the rate at which a firm obtains funds for financing capital
 investments.  The cost of capital to a particular firm depends on how the investment is financed.  One
 option, equity financing, is taken when a firm issues stock or retains earnings. A second option involves
 acquiring additional debt, through bonds,  notes,  or short-term commercial paper.  Typically, acquiring
 debt is the less expensive  option.   As a firm expands its debt holdings,  however, the cost of debt
 increases, forcing the firm to reach an equilibrium between debt and equity financing.  It is assumed in
     I6For the vast majority  of facilities, this is a valid assumption.  The Survey contained very few non-
 manufacturing facilities that had an effective treatment system in place for the treatment and removal of PAIs from
 indirectly discharged wastewater.
                                               4.17

-------
this analysis that firms use some combination of debt and equity to finance compliance costs.  The
measure of a firm's overall cost of financing a capital investment, based on the percentage values of debt
and equity used to finance the investment, is termed the weighted average cost of capital (WACC). Thus,
the WACC is the average after-tax cost of all funds used to finance a capital investment.

        The WACC can be presented in either nominal (i.e., not adjusted for inflation) or real terms (i.e.,
the nominal WACC is adjusted for inflation). This analysis used the real cost of capital to allow for the
use of constant annual compliance costs (i.e., compliance costs that are not inflated over time).  The two
inputs to calculating the real WACC — nominal WACC and the inflation rate — are discussed below.

        Nominal WACC. The nominal WACC was calculated by weighting the cost of equity and the cost
of debt by the percentage of the investment expected to be financed by these two methods.  The equation
used was:
where:
WACC
R
E
I
Y
CT
D
         WACC  =  R(E/I) + Y(l-CT)(D/I)

nominal weighted average cost of capital;
after-tax cost of equity;
amount of investment financed by equity;
total amount of the investment;
pre-tax interest rate on debt;
marginal corporate tax rate; and
amount of investment financed by debt.
The estimates of the nominal WACC vary by firm. The sources of values for the variables in the WACC
equation vary, in some cases, based on whether the firm owns a PFPR/manufacturing facility(ies) or a
facility(ies) that PFPRs but does not  manufacture PAIs.  The input sources and values are discussed
below.

       The percentages of the investment that a firm is assumed to finance through equity (E/I) and debt
(D/I) are assumed to  match the firm's historical mix of equity and debt investment.  The mix of equity
                                            4.18

-------
and debt financing was specified in three different ways, depending upon the facility's ownership and
business structure. First, for all public firms, the mix of debt and equity was gathered from each firm's
annual report for 1988.  Second, private firms owning PFPR/manufacturing facilities were assigned the
median debt and equity mix of the public firms owning PFPR/manufacturing facilities in the sample. The
median values were 52.2 percent debt financing and 47.8 percent equity financing.  Third, for other
private firms, the debt/equity mix was calculated using the debt/assets and equity/assets ratios from the
balance sheet reported by the associated facility in the Survey. If the ratios based on reported data were
not bounded by one and zero,17 the median values of the other private non-manufacturing facilities in
the sample were used.  These median values are 48.5  percent debt financing and 51.5 percent equity
financing.  Data for these "other" private firms  were not taken as the average of the public firms' data
because a sharp  distinction is expected between the private and public firms due to size differences. Data
from the public firms are not expected to be necessarily representative of data from the private firms.
        The after-tax cost of equity (R) is calculated as follows for all public firms:
                                       R   =  i  +
 where:
 i       =


 (Rm-l)=
the risk free rate of return =  10.01 percent (calculated  from the 1982-1991  average
interest rate on 30-year U.S. Treasury Bonds as reported in Statistical Abstract of the
United States, Bureau of the Census, 1989,  1992);1®
Typical risk premium, or the rate of return on market portfolio less the rate of return on
risk free investments = 8.0 percent; and
A measure of the risk of an individual firm compared with the market.  Beta values are
based directly on 1988  Value Line Investment Survey, Part I Summaries & Indexes
specific to each firm.
        For private firms owning PFPR/manufacturing facilities, the cost of equity was  calculated as
 above, except that the beta value was set equal to the median beta value (i.e., equal to 1.175) for the
     17Negative equity was indicated for one firm undergoing restructuring.
     18The variable, i, represents the risk free component of the return on equity. Since equity has no maturity date,
 i is best calculated as the return on long-term Treasury Bonds rather than as the return on 10-year Treasury Bonds.

                                               4.19

-------
 publicly-held firms owning PFPR/manufacturing facilities. For other private firms, cost of equity was
 estimated using the average return on the stock  market from 1982 to 1991, as estimated  from the
 Standard & Poor's 500 Composite Stock Price Index, assuming that all dividends are reinvested.  This
 value is 1 8.08 percent.

        For all firms, an estimate of the interest on loans was developed using the 1982-1991 average
 yield on  10-year Industrial Bonds, which equals 10.68 percent (reported in Standard & Poor's Security
 Price Index Record).19  The marginal corporate tax rate was assumed to be 34 percent.

        Real WACC.  Given the nominal WACC, the real WACC is estimated as:

                                                  * WACC
            RWACC   =
                                                            - I
                                                       8
 where:
 RWACC
 g
the real weighted average cost of capital; and
the rate of inflation = 4.02 percent.
This inflation value is the average of the annual percentage changes of the GNP implicit price deflator
between 1982 and 1991 (Statistical Abstract of the United States, 1992).

        Estimated Post-Compliance Prices
        Changes  in pesticide prices  and demand are determined  interactively in the market  place.
Typically, a producer will raise prices based on the expected actions of competitors and the extent to
which consumers will decrease demand.  Consumers will then respond to the increased prices with  a drop
in demand based on several  factors, including the percent of their production cost contributed by the
product and  the availability of substitute products.  Producers  then examine the  impact of the price
increase and  demand decrease on profitability and reevaluate their price.  Consumers again react.  This
iterative process continues until producers believe they have maximized profit.
     Because of difficulties in interpreting them, the interest rate data reported in the Survey were not used.  See
the memorandum to the Administrative Record entitled "Survey Information on Capital Investments".

                                              4.20

-------
        The main analyses of this El A are conducted assuming that facilities are unable to pass any costs
of the proposed regulation through to customers.  This is an extremely conservative assumption that yields
maximum projected impacts on PFPR facilities.  In fact, this scenario is highly unlikely.  For a zero cost
pass-through analysis to represent a realistic scenario, either the supply curves for pesticide markets must
be perfectly inelastic or the demand curves must be perfectly elastic. A perfectly inelastic supply curve
is associated with goods for which there is a fixed supply. This is not the case for pesticide markets.
Based  on an analysis of the price elasticity of demand for pesticides conducted for the pesticide
manufacturer EIA, demand for pesticide is generally inelastic.20   Because supply  curves for the
pesticide markets are not known, however, and compliance costs are not estimated in a manner that can
necessarily be associated with specific pesticide products,  projecting the percentage of the compliance
costs that will be passed through to customers is difficult.  If the regulation is economically achievable
under an assumption of zero cost pass-through,  this serves as assurance that it would be economically
achievable under a more realistic scenario of partial cost pass-through.

        The analyses were also conducted using a price-adjustment rule  in which facilities attempt to pass
through half of their compliance costs to customers.  This assumption,  while imprecise,  reflects the fact
that some cost pass-through is realistically expected. The average percentage increase in price is simply
calculated by dividing the annualized compliance costs by the three-year average of revenue from 272
PAI-related  PFPR (sum of questions 3, 4, and 5 in Part B of the  Survey.) In conjunction with the
assumed increase in price, a change in facility revenues is calculated from estimated elasticity values for
the mix of facility's pesticide products. The analyses  based  upon the  price-adjustment  rule resulted in
facility impacts under the proposed option which were unchanged from  impacts estimated under the zero
cost pass-through assumption. These price-adjustment analyses are discussed in detail in Appendix F.

        Post-Compliance Cash Flow
        Facility cash flow consists of facility net income plus noncash expenditures.  Baseline, or pre-
compliance, facility cash flow was estimated based on data from the income statement reported in the
Survey.  Cash flow was adjusted to account for the estimated costs of complying with Federal pollution
control regulations effective after 1988, the base year for the analysis. Post-compliance facility cash flow
was calculated by subtracting an adjustment for compliance costs from  estimated baseline cash flow.
   20Estimates of demand elasticities for PAIs are provided in Appendix C.

                                              4.21

-------
4.2     Impact Measures
        The following sections present the facility-level impacts evaluated under the baseline and post-
compliance scenarios.

        Baseline
        The baseline economic  analysis evaluates each  facility's financial operating condition prior to
incurring compliance costs for meeting effluent limitations. The purpose of the baseline analysis is to
identify PFPR facilities that are currently experiencing or are projected to experience significant financial
difficulties regardless of the promulgation of effluent guidelines.  Attribution of all financial impacts to
the effluent limitations rather than to facilities' current financial problems would overstate the burden of
effluent limitations.

        Facility financial viability is analyzed in the baseline scenario by calculating the three-year after-
tax cash flow from the Survey data, incorporating the costs of EPA regulations effective after the Survey
was administered.21   If a facility has lost cash on average over the three-year period, the facility is not
expected to remain in operation and post-compliance impacts are not evaluated.

        Post-Compliance Impacts
        The EIA projects three categories of economic impacts that may result from regulation:  facility
closure, conversion  of PFPR product lines to non-pesticide FPR operations, and compliance costs in
excess of five percent of facility revenue.  Facility closure is the most severe of the three impacts
evaluated, while  line conversions and costs in  excess of five percent of facility revenue represent more
moderate impacts.  In contrast to facility closures and product line conversions, compliance costs in
excess of five percent of facility revenue are not expected to be associated with an operational change at
a facility.  Compliance costs that are less than five percent of facility revenue are commonly judged to
be economically  achievable (see, for example,  the  EIAs for  effluent limitations for the OCPSF and
pesticide  manufacturers  industries).    In addition, compliance  costs equal to five percent of facility
     ' As discussed above, the baseline analysis included the estimated costs associated with four regulations: (1)
Resource Conservation and Recovery Act (RCRA) land disposal restrictions, (2) effluent limitations for the OCPSF
industry, (3) effluent limitations for the Pesticide Manufacturing Industry, and (4) annual maintenance fees set by
EPA under the FIFRA Amendments of 1988.
                                               4.22

-------
revenues do not necessarily indicate a significant impact.  This measure is counted as a moderate impact
under a conservative standard that considers the possibility of such an impact.

        The particular impacts evaluated for a facility are a function of the type of PFPR operations
conducted at the facility and the percentage of the facility's revenue that is derived from PFPR operations.
These characteristics are used as indicators of the options that management  will likely consider in
response to compliance costs.  The grouping of facilities for evaluation of impacts is based, in part, on
subcategories defined for this regulation.  As previously mentioned, two subcategories are considered
under this  regulation.  In the (remanded) 1985 effluent guidelines for the pesticide industry,  all PFPR
facilities were classified under Subcategory C.  This regulation recognizes another subcategory that
previously existed within Subcategory C: Subcategory E, applying to wastewater streams generated by
Refilling Establishments. A Refilling Establishment is defined by 40 CFR Part  165 as an establishment
at which the sole PFPR activity is the repackaging of pesticide products into refillable containers for the
agricultural market. The application of impact measures to these subcategories, as well as the motivation
for establishing Subcategory E, are discussed below.

        Impact Measures for Facilities Regulated Under Subcategory C
        Three impact measures were considered for Subcategory C facilities:  (1)  facility closures; (2)
facility conversions to non-PFPR activities; and (3) compliance costs in excess of five percent of facility
revenue.

        Facility  closures.   Two groups of PFPR facilities regulated under Subcategory C would be
 expected to consider facility closure as a response to effluent limitations: (1) PFPR facilities that also
 manufacture PAIs; and  (2) PFPR facilities earning a significant percentage of their revenue from PFPR
 activities.

         PFPR facilities that also manufacture PAIs (hereafter "PFPR/Manufacturing Facilities") generally
 obtain a high percentage of their revenue from PFPR activities.  Based on responses to the Section 308
 Survey,  the  mean  percentage  of facility  revenue  from  PFPR activities  was 66.5  percent for
 PFPR/Manufacturing Facilities, with a median value of 90.4 percent.   In addition, the manufacturing
 operations are integrated with the PFPR operations and additional costs may be incurred in manufacturing
 operations (e.g., tolling costs) if PFPR operations are discontinued.

                                                4.23

-------
        As discussed in the preceding chapter, Other PFPR Facilities with a substantial percentage of
 revenue from PFPR operations (and that do not manufacture PAIs) may also consider closing the facility
 entirely in the face of burdensome compliance costs.  This analysis assumes  that these Other PFPR
 Facilities that obtain at least 25 percent of their revenue from PFPR activities will consider closing
 entirely.22  This fairly low percentage  of revenue  was chosen so  that evaluation of the most  severe
 economic impact — facility closure — includes all facilities that might feasibly consider this alternative.

        Facility conversions to non-pesticide Formulating/Packaging/Repackaging activities. Facilities
 regulated under Subcategory C that do not manufacture PAIs and that obtain less than 25 percent of their
 revenue from PFPR activities are expected to  face different decisions in response to compliance costs.
 These facilities frequently engage in the formulating and packaging of many non-pesticide products as
 well as pesticide products.  The facilities  are typically not dependent on pesticide  FPR, but include
 pesticides in the line of many chemical preparations that they formulate, package, and repackage.  The
 production lines are not specific to  pesticides, but can FPR a wide range of products. The facilities are
 therefore likely to consider converting their PFPR lines to the formulation of non-pesticide products rather
 than closing the facility or the lines if PFPR production is discontinued.  Alternatively, some facilities
 may decide to toll out the pesticide portion of their  formulating business, while retaining ownership of
 the pesticide product.  The analysis evaluates whether these facilities would be expected to convert their
 pesticide lines to  other formulating/packaging/repackaging  operations as a result of the regulation.
 Because the conversion of pesticide FPR  lines to other FPR operations is not generally expected to result
 in employment loss, such conversion is considered to be a moderate impact. To ensure that impacts are
 not overstated, however, EPA presents  estimates of employment losses  associated with the  closure of
 PFPR lines of facilities expected to convert their PFPR lines. This is a worst case result, and EPA does
 not believe that such employment losses  will actually occur in most cases.
   ^Ideally, the determination of whether management would consider closing a facility entirely would be based
on the percentage of profit, rather than revenue, derived from PFPR activities.  Because costs were not reported
for PFPR activities in the Survey, however, calculation of PFPR profits is not possible.
                                              4.24

-------
       Ratio of annaalized compliance costs to revenue in excess of five percent.  As an additional
measure of economic effects on facilities regulated under Subcategory C, the annualized compliance costs
are compared to facility revenue for each facility.  As discussed above, costs in excess of five percent
of facility revenue are said to result in a moderate economic impact.

       Subcategory E Facilities
       For Subcategory E Facilities (or Refilling Establishments), the only economic measure evaluated
is compliance costs as a percentage of revenue.  As discussed in Chapter 3,  Refilling Establishments
constitute a distinct set of facilities within the PFPR industry.  An estimated 46 percent of the facilities
potentially covered by the PFPR regulation are classified as Subcategory E facilities. These facilities do
not formulate or package pesticides, but maintain bulk storage tanks for pesticides and distribute the
formulated  product,  in refiliable containers  to farmers.   As  presented in Chapter 3,  most Refilling
Establishments surveyed reported a primary  SIC code of #5191, which characterizes the establishments
as "primarily engaged it* the wholesale distribution of animal feeds, fertilizers, agricultural chemicals, •
pesticides,  seeds, and other farm supplies,  except grains."23  In  keeping with  this line of business,
typical ownership of Refilling Establishments differs from that of other PFPR facilities. An estimated
29 percent of Refilling Establishments are owned as a cooperative, e.g., a group of farmers who purchase
and distribute pesticides among themselves.  In contrast, only two percent of other PFPR facilities have
a cooperative form of ownership.

        In general, Refilling Establishments have relatively low facility revenue.  The estimated mean
revenue for Refilling Establishments is $4.8 million per year, in contrast to $16.3 million per year for
the remainder of the industry. Also, Refilling Establishments derive only a  small percentage of their
revenue from pesticide repackaging. The mean percentage of revenue from PFPR activities is 15 percent,
 with a median value  of six percent. Also, the other activities conducted at these facilities do not depend
 on pesticide packaging.  Therefore, for this subcategory, closure of the facility would not be expected
 in response to compliance costs and no  analysis of facility closure is conducted.
     23In contrast, most Subcategory C facilities reported their primary SIC code as #2842: "Establishments primarily
 engaged in the manufacture of furniture, metal, and other polishes".
                                                4.25

-------
        Refilling Establishments have simple production lines, typically consisting of one or more bulk
tanks purchased specifically to hold pesticides.  The investment in the "production line"  is minimal —
the average market value of the production line for the Surveyed facilities is $3,800.  Alternative uses
of  the tank are  limited  and  unlikely to provide significant  profits.   Most  owners  of Refilling
Establishments are therefore not expected to convert their tanks to an alternative use and no analysis of
production line conversion is conducted.

        The economic returns to Refilling Establishments may, however, be affected by compliance with
the proposed regulation. The analysis evaluates the extent of potential  impacts by comparing annualized
compliance costs  to facility revenue.  Costs in excess of five percent  of the facility's revenue are
characterized as  a significant economic impact.   Table 4.1 presents  some  of the characteristics that
distinguish Refilling Establishments from other PFPR facilities.

        Table 4.2 summarizes the impact measures considered in the analysis.

4.3     Calculation of Impacts
        This section provides the  methods and equations used to analyze facility closure, product line
conversion, and compliance costs  in excess of five percent of facility revenue.

        Facility Closure
        A decision to close a facility is typically made at the firm level.  The firm holds pesticide
registrations and can consider transferring both pesticide and other products among facilities. In general,
a facility owner (i.e., a firm) faced with pollution control requirements must'decide whether to make the
additional investment in pollution control, to change the  products produced at the facility (pesticide
products as well as non-pesticide products), or to liquidate the facility. Because data on other products
to which a facility may convert are unavailable or limited, this analysis assumes that either the pollution
control investment is made or the facility is liquidated.
                                              4.26

-------
Table 4.1
Estimated National Distribution of Selected Characteristics of
Subcategory E Fadlities vs. Other PFPR Facilities
(Facilities that Use Water)

• Number of Facilities
• Most Frequently Reported SIC Code
• Mean Percent of Revenue from PFPR
• Facility Revenue
— mean
— median : .
• Estimated Market Value of
Production Lines •
— mean
— median
• Ownership Type
— cooperative
— single facility
— multi-facility
— other
Subcategory E Facilities
830
5191
(67 %)
15 %
$ 4,757,000
$1,730,000
$3,800
$ 1,900
242 (29 %)
227 (27 %)
361 (43 %)
0(0 %)
Subcategory C Facilities*
942
2842 (manufacturing
furniture, metal, and other
polishes)
(14 %)
28 %
$ 16,280,000
$ 3,320,000
$ 166,000
$6,000
15 (2 %)
569 (60 %)
341 (36 %)
17 (2 %)
* Includes only PFPR/Manufacturing and other PFPR facilities regulated under PSES that use water.
Omits facilities that are directly discharging PFPR wastewater. Percentages may sum to more than
100 % due to rounding.
       The evaluation of whether to close a facility  is complex and  involves a  number of factors
including:

       (1)     Present and expected profitability of the facility;
       (2)     Required capital investment in pollution control technology equipment;
       (3)     Expected increase in annual operating costs due to pollution control  requirements; and
       (4)     Expected product price, production costs, and profitability of the facility after pollution
               control equipment is installed and operating.
                                               4.27

-------
Table 4.2
Analysis Methods and Impact Measures by Facility Subcategory
Subcategory C:
PFPR/Manufacturing Facility
or Other PFPR Facility with
& 25 % of revenue from
PFPR (380 population
facilities)
1 . Cash flow analysis to
project facility closure
2. Compliance costs compared
to revenue
Subcategory C:
Non-manufacturer and < 25%
of revenue from PFPR (902
population facilities)
1 . Comparison of ROA for
PFPR with alternative asset
use to project line conversion
2. Compliance costs compared
to revenue
Subcategory E
(1,122 population facilities)
1. Compliance costs compared
to revenue

        Compliance Cost Adjustment
        The calculation used to estimate whether or not a facility will close is intended to model the
decision-making process of the owners of the facility.  The calculation  compares the pre-compliance
profitability of the facility with the post-compliance profitability.  Specifically, this calculation entails a
comparison of pre-compliance after-tax cash flow to post-compliance after-tax cash flow for the facility.
In the majority of cases, a rational owner would not continue operations if a facility's after-tax cash flow
is negative.

        Facility cash flow consists of facility net income plus noncash expenditures.  Baseline, or pre-
compliance, facility cash flow was estimated based on data from the income statement reported  in the
Survey.  Cash flow was adjusted to account for the costs of complying with the RCRA land disposal
restrictions, OCPSF effluent limitations, pesticide manufacturers effluent limitations, and FIFRA annual
maintenance fees.  As discussed above, these rules (or portions thereof) were effective after 1988, the
base year for the analysis. The compliance costs associated with the rules were therefore not reflected
in the Survey  data. Specifically, cash flow for a facility was estimated as:

                                CFO = NI +  DEP -  OC(1-CT)
                                              4.28

-------
where:
        CFO   =      After-tax baseline cash flow;

        NI     =      Net income (i.e., after tax profits calculated from the Census);

        DEP   =      Depreciation expenses (taken directly from the Census);

        OC    =      Cost of compliance with other EPA regulations first effective after 1986 (RCRA
                       land disposal restrictions, OCPSF effluent guidelines, Pesticide Manufacturers
                       effluent guidelines and FIFRA maintenance fees); and

        CT    =      Marginal corporate tax rate (assumed to be 34 percent).
        Post-Compliance Cash Flow
        Facilities for which baseline cash flow was negative (i.e., those predicted to be baseline facility
closures) were not considered as potential facility closures in the post-compliance scenario.  For the
remaining facilities, however, the post-compliance cash flow was evaluated to project facilities that would
close due to the regulation.


        Under the assumption of zero cost pass through, the calculation of post-compliance cash flow
requires only an adjustment  for compliance  costs.  The  compliance costs have two components:
operating/maintenance costs and  capital costs.  Full capital costs, funded both by debt  and equity are
 included. An annualized cost of capital is calculated by dividing the estimated capital and land investment
 by the present value factor.  The present value factor is based on the WACC, as discussed in the section
 on cost of capital.24 The facility will pay reduced taxes as a result of depreciating capital expenditures.
    24  The real WACC is used to construct a present value factor (PVF).  Multiplying annual costs by a PVF
 discounts investments over a fixed time period. Correspondingly, dividing present value costs by the PVF gives
 annualized costs over a fixed period of time. This analysis divided compliance capital and land costs by the PVF
 to annualize these costs. The analysis uses a ten-year discounting horizon as a conservative estimate of the typical
 life of the pollution control equipment.  The PVF is calculated as:
                                             10
                                                       1
 where:
 PVF
 RWACC
                                             1^ (1 + RWACQ*
present value factor;
the real weighted average cost of capital; and

                        4.29

-------
Annual operating and maintenance costs will also be somewhat offset by the corresponding decrease in
taxes the facility will pay due to reduced profit.  The calculation is as follows:
                     CCadj  =  (OMx(l-CZ))
                                                 PVF
                                  rCPT
                                  1  10 '
where:
        CCadj  =      Compliance cost adjustment to cash flow;
        OM    =      Operating and maintenance costs of compliance;
        CT     =      Marginal corporate tax rate;
        PVF    =      Present value factor; and
        CPT    =      Capital costs of compliance.

        Post-compliance after-tax  cash flow is calculated  as baseline after-tax cash flow  less the
adjustment to cash flow for compliance costs. The equation is:

                                  PCCFO  =  CFO  - CCadj
where:
       PCCFO
       CFO
       CCadj
Post-compliance after-tax cash flow;
Baseline after-tax cash flow; and
Adjustment to cash flow due to compliance costs.
As previously discussed, a facility with negative after-tax cash flow in the post-compliance scenario was
assessed as a closure for the economic impact analysis.
                     number of years over which costs are discounted.
                                            4.30

-------
       Product Line Conversion
       In theory, conversion of PFPR production lines to alternative non-pesticide FPR activities would
be expected to occur at the point that the financial return on the assets employed in an alternative activity
exceeds the return from PFPR. The most lucrative alternative activity — and the financial return from
that activity — would vary for each facility based on such factors as the local/regional manufacturing
activity,  capacity  availability,  and business connections.   In general,  however,  it is  expected that
alternative FPR opportunities  exist in the operations  characterized by SIC codes #2899  (chemical
preparations) and #2842 (manufacturing furniture, metal, and other polishes).  These SIC codes were the
most frequently reported primary SIC codes for PFPR facilities obtaining less than 25 percent of their
revenue from PFPR.

       The analysis of product line conversion is based on comparing the return on assets (ROA) that
would be obtained by  continuing PFPR  in the post-compliance scenario with the ROA obtained from
activities classified in SIC 2842 (industry financial data on SIC 2899 are not readily available).  The
analysis  assumes  that the ROA  achieved by  75 percent of facilities  operating in SIC 2842  could
reasonably be expected to be achieved by a converted PFPR line. On average over the three-year period
1986-1988, the lowest quartile ROA (defined as earnings before taxes divided by assets) was 2.9 percent
for SIC 2842.25

       The  analysis of ROA is  conducted in four steps:   (1)  calculation of baseline ROA;   (2)
comparison of baseline ROA to 2.9 percent;  (3) calculation of post-compliance ROA; and (4) comparison
of post-compliance ROA to 2.9 percent.  If a facility's baseline ROA is below 2.9 percent, no further
line conversion analysis is performed for the facility.  If a facility's ROA for PFPR operations falls below
2.9 percent as a result of compliance costs, given that its baseline ROA is above 2.9 percent, the facility
is assessed as likely to convert its PFPR production lines to other  FPR activities.26  These  steps are
discussed below.
    25Robert Morris and Associates (1991). RMA Annual Statement Studies.
    26This comparison basis,  although reasonable, is far from definitive.  In  recognition of the lack of data
regarding the ROA at which facilities would convert the PFPR lines, a sensitivity analysis of the ROA conversion
analysis is presented in Appendix E of the EIA.

                                               4.31

-------
        Calculate Baseline ROA
        ROA is calculated as earnings before taxes (EBT) from PFPR divided by assets associated with
 PFPR.   EBT is calculated as revenue from PFPR  minus costs from PFPR (excluding taxes).  PFPR
 revenue is calculated as a three-year average of the sum of Survey questions 3, 4, 5, and 6 in Part B.
 The PFPR revenue includes revenue from tolling and services, including provision of pesticide products.
 As previously discussed,  the Survey  does  not provide cost data below the facility level.  This report
 therefore assumes  a constant profit  margin for all  product  lines in a facility  and calculates costs
 proportionately to revenue.  Algebraically,
                                      PC  =  C  x  (PR/TK)
where:
PC
C

PR
TR

And,
where:
EBT    =
PR
PC
PFPR costs net of taxes;
Three-year average costs for the entire facility net of taxes (including cost adjustments
for post-1988 regulations);
Three-year average revenues from PFPR activities; and
Three-year average total facility revenues.
                                       EBT  =  PR - PC
Earnings before taxes from PFPR operations;
Three-year average revenues from PFPR activities; and
Estimated three-year average PFPR costs net of taxes.
       Asset values are also available only for the entire facility.  The value of assets associated with
PFPR is calculated by assuming constant asset productivity across all product lines. Algebraically,
                                             4.32

-------
where:
PA
A
PR
TR
                                     PA  =  A x  (PRJTK)
PFPR assets;
Three-year average assets for the entire facility;
Three-year average revenues from PFPR activities; and
Three-year average total facility revenues.
       Using the calculated EBT and PA values, baseline ROA for PFPR operations is calculated as
follows:
                                        ROA   =
                                    EBT
                                    PA
where:
ROA   =
EBT   =
PA
Baseline pre-tax return on PFPR assets;
Earnings before taxes from PFPR operations; and
PFPR assets.
If the baseline PFPR ROA of the facility is less than 2.9 percent, no further line conversion analysis is
performed on the facility.

        Post-Compliance Return on Assets
        Under the zero cost pass-through assumption, the numerator of the ROA, (i.e., EBT), is adjusted
by subtracting  annual  operating and maintenance costs, depreciation,  and the average annual interest
payment due to the debt component of the capital investment calculated over the ten-year assumed life
of the investment.27 The equation is:
    27The average interest payment is chosen as a typical interest payment.
                                              4.33

-------
                           PCROA  =  EBT ~ OM ~ (CP7710) - AIP
                                                 PA  +  CPT
 where:
 PCROA
 EBT
 OM
 CPT
 AIP

 PA
        Post-compliance return on assets;
        Earnings before taxes from PFPR operations;
        Annual operating and maintenance compliance costs;
        Compliance capital costs;
        Facility's average annual interest payment on the debt component of compliance
        capital outlays for the life of the investment; and
        PFPR assets.
        Average annual interest payment. The average annual interest payment is calculated as:
            AIP  =
                                       * CPT) x 0.064  _ D x CPT
                      1 - (1 + 0.064)
                                                    -10
                                                              10
where:
AIP    =
D
CPT    =
Average annual interest payment;
Percent of compliance capital costs assumed to be financed by debt;
Compliance capital costs.
       The value of 6.4 percent is the assumed real  interest rate and was calculated from the inputs
previously described for the WACC.  The nominal interest rate is assumed to be 10.68 percent and the
inflation rate is assumed to be 4.0 percent.  OMB's recommended discount rate of 7.0 percent was also
used, with no significant difference in results.

       The denominator of the ROA ratio, (i.e., assets), is adjusted by adding the compliance capital
outlays to baseline assets to complete the calculation of post-compliance ROA.  If the post-compliance
PFPR ROA  falls below 2.9 percent, given that the baseline ROA was above 2.9 percent, the facility is
assessed as  likely to convert its PFPR production lines to other non-pesticide FPR activities.
                                            4.34

-------
       Comparison of Annualized Compliance Costs to Revenue
       The annualized compliance costs are compared to three-year average facility revenue as an
indication of whether moderate economic impacts are likely.  Facility revenue is obtained directly from
the Survey (question 8, Part B).

4.4    Facility Impact Results
       Using the methodology described above, this section presents the estimated facility impacts of the
BPT and proposed PSES  regulatipns.

       Impacts under BPT: Baseline and Post-Compliance Analysis
       For information purposes, economic impacts were analyzed for the sixteen direct-discharging
PFPR/Manufacturing Facilities  to  comply  with existing BPT regulations and  were found to be
insignificant. None of these sixteen facilities had negative three-year average cash flow in the baseline
analysis, therefore none is expected to close in the baseline scenario. Because these sixteen facilities are
PFPR/Manufacturing Facilities, they were evaluated for possible post-compliance facility closures. No
facility closures are expected under the proposed rule.

       Impacts under PSES
       Baseline Analysis
       The projected baseline facility impacts are shown in Table 4.3. As mentioned above, a baseline
impact is said to occur if a facility's average after-tax cash flow for the three years of Survey data is
negative. Twenty-two percent of facilities regulated under Subcategory C are estimated to have baseline
impacts, while 20 percent of  facilities regulated under Subcategory E are estimated to have baseline
impacts.

        Post-Compliance Analysis of PSES
        Subcategory C facilities: initial options.  For Subcategory C facilities, EPA initially analyzed
the impacts of five possible regulatory options for PSES.  The first option considered was end-of-pipe
treatment based on the Universal Treatment System for the entire wastewater volume and discharge of
                                              4.35

-------
Table 4.3
Projected Population Baseline Closures for Facilities that Use
Water1
(Based on 3-year Average Negative Cash Flow)

Facility closures:
Total facilities:
Percentage of
facilities affected:
Subcategory C
Facilities
203
943
22%
Subcategory E
Facilities
169
830
20%
1. Not including the direct discharging PFPR/manufacturing facilities.
the entire volume.28  The second  option differentiated between two types of wastewater streams at
facilities: (1) "interior" wastewater streams including drum/shipping container rinsate, interior equipment
rinsate, and bulk container rinsate; and (2) "other" wastewater streams including exterior equipment and
floor wash, leak and spill cleanup, safety equipment rinsate, contaminated precipitation run-off, laboratory
wastewater, air pollution control wastewater, and DOT test bath water.  The second option was costed
for treatment and pollution prevention, based on the wastewater generated from interior wastewater
streams being recycled back into the product. (See Chapter 10  for details on the economic benefits to
facilities of incorporating pollution prevention measures.)

        Options 3, 4, and 5 all result in zero discharge.  Option 3 is based  on exactly the same
technology and pollution prevention practices as the  second option but achieves  zero discharge of all
process wastewater by recycling the wastewater after  treatment through the universal treatment system.
Option 4 includes the pollution prevention aspects of Options 2 and 3, but achieves zero discharge based
on the remaining wastewater being incinerated off-site.  Option 5 is based on off-site incineration of all
wastewater.
   28The Universal Treatment System is described fully in the Technical Development Document.  Briefly, such
a system would have the capability to treat wastewater with hydrolysis, chemical oxidation, and activated carbon
depending on the active ingredients  needing to be controlled.  The Universal Treatment  System could  also
accomplish chemical/thermal emulsion breaking, which controls emulsifiers and surfactants that are added to some
pesticide products as inert ingredients.
                                               4.36

-------
       Of these options,  EPA initially  selected Option  3 because, as discussed in the Technical
Development Document,  it represents the performance achievable  with  the  best available treatment
technology. EPA's analysis shows that this option is economically  achievable and, in fact, results in
relatively low economic impacts.  The projected facility-level economic impacts associated with each of
the regulatory options are discussed below and presented in Table 4.4.  As described below, EPA has
ultimately decided to propose a variation of Option 3 for PSES.

       Impacts of Option 1. Under Option 1, 578 Subcategory C facilities are expected to incur costs.
One hundred twenty of these facilities were analyzed for possible facility closure and the remaining 458
were analyzed for line conversions.  A comparison of annualized compliance cost to facility revenue was
conducted  for  all Subcategory C facilities.   The capital  and annualized total costs (which include
amortized capital, annual  operating and maintenance, and monitoring costs) of complying with Option
1 are expected to be $79.0 million and $32.6 million, respectively.  An estimated nine Subcategory C
facilities are projected to close due to compliance with Option 1.  One hundred seventy-one facilities are
expected to incur moderate economic impacts.  Total U.S. job losses are projected, in the worst case,
to be 437 full-time equivalents (FTEs) as a result of the estimated impacts.

       Impacts of Option 2. Under Option 2, 558 Subcategory C facilities are expected to incur costs.
One hundred thirteen of these facilities were analyzed for possible facility closure and the remaining 445
were analyzed for line conversions.  A comparison of annualized compliance cost to facility revenue was
conducted for all Subcategory C facilities. The capital and annualized total costs  (which include amortized
capital, annual operating and maintenance,  and  monitoring costs)  of complying  with Option 2 are
expected to be $66.1 and $27.9 million, respectively. One facility is projected to close due to compliance
with Option 2.  One hundred seventy facilities are expected to incur moderate economic impacts. Total
U.S. job losses are projected, in the  worst case,  to be 426 FTEs  as a result of the estimated  impacts.
The total annualized  compliance costs under  Option 2 are $4.7 million less than under Option  1,
reflecting savings due to waste management disposal savings achieved under Option 2.  Additional savings
resulting from pollution prevention practices are discussed in Chapter 10.
        Impacts of Option 3. Under Option 3, 558 Subcategory C facilities are expected to incur costs.
One hundred thirteen of these facilities were analyzed for possible facility1 closure and the remaining 445
were analyzed for line conversions. A comparison of annualized compliance cost to facility revenue was
                                              4.37

-------
conducted  for all Subcategory C facilities.  The capital and annualized  total costs  (which include
amortized capital, annual operating and maintenance, and monitoring costs) of complying with Option
3 are expected to be $66.1 and $27.9 million, respectively.29  One facility  is projected to close due to
compliance with Option 3.   One hundred seventy facilities are expected to incur moderate economic
impacts.  Total U.S. job losses are  projected,  in  the worst case, to be 426 FTEs as a result of the
estimated impacts. The total annualized compliance costs under Option 3 are  $4.7 million less than under
Option 1,  reflecting  savings due to waste  management disposal savings  achieved under Option 2.
Additional savings resulting from pollution prevention practices are discussed in Chapter 10.

        Impacts of Option 4. Under Option 4, 558 Subcategory C facilities  are expected to incur costs.
One hundred thirteen of these facilities were analyzed for possible facility closure and the remaining 445
were analyzed for line conversions. A comparison of annualized compliance cost to facility revenue was
conducted  for all Subcategory C facilities.  The capital and annualized  total costs  (which include
amortized capital, annual operating and maintenance, and monitoring costs) of complying with Option
4 are expected to be $18.4 and $286.5 million, respectively. Seven Subcategory C facilities are projected
to close due to compliance with Option 4.   One hundred ninety-three facilities are expected to incur
moderate impacts. Total U.S.  job losses are projected, in the worst case, to be  1,113 FTEs as a result
of the estimated impacts.

        Impacts of Option 5.  Under Option 5, 578 Subcategory C facilities  are expected to incur costs.
One hundred twenty of these facilities were analyzed for possible facility closure and the remaining 458
were analyzed for line conversions. A comparison of annualized compliance cost to facility revenue was
conducted  for  all Subcategory C facilities.  The capital and annualized  total costs  (which include
amortized capital, annual operating and maintenance, and monitoring costs) of complying with Option
5 are expected to be $21.0 and $360.2 million, respectively. Seven Subcategory C facilities are projected
to close due to  compliance with Option 5.   Two hundred seventeen facilities are expected to  incur
moderate economic impacts.  Total U.S. job losses are projected,  in the worst case, to  be 1,173 FTEs
as a result of the estimated impacts.
   29Note that the compliance costs projected for Options 2 and 3 are identical because the costs of reusing
wastewater are assumed to approximate the costs of disposing of wastewater.

                                              4.38

-------
       Table 4.4 summarizes the estimated costs and impacts of these options.
Table 4.4
National Estimates of Economic Impacts upon Subcategory C Facilities
(Assuming Zero Cost Pass-Through)

-Facilities Incurring Costs
-Total Capital Compliance
Costs (million of dollars)
-Total Annuaiized
Compliance Costs
(millions of dollars)
-Facility Closures:
(Severe Economic Impacts)
-Facilities Incurring
Moderate Economic Impacts
-Worst Case Expected Job
Losses (FTEs) •;-^--: ,".'/.:.:
Option 1
578
$79.0
$32.6
9
171
437
Option 2
558
$66.1
$27.9
1
170
426
Option 3
558
$66.1
$27.9
. 1
170
426
Option 4
558
$18.4
$286.5
7
193
1,113
Option 5
578
$21.0
$360.2
7
217
1,173
       Identification of differential impacts. As shown above, Option 3 is economically achievable when
viewed across all Subcategory C facilities.  EPA was aware through discussions with industry, however,
that certain segments of the industry exhibit distinctive technical and market characteristics. In particular,
industry identified the institutional/commercial market for pesticide products as having unique technical
and market characteristics. It was not clear a priori that given these characteristics, the regulation would
result in a disproportionate economic burden on the facilities in the institutional/commercial market.

       As discussed in Chapter 5, in analyzing the regulatory alternatives applicable to Subcategory C
facilities pursuant to the Regulatory Flexibility Act, EPA  determined that the costs associated with
installing treatment systems to  recycle non-interior wastewater sources will cause disproportionate
economic impacts at certain  PFPR facilities but the treatment would remove only a very small  amount
of toxic pollutants at these facilities.  These facilities  are distinguished from  other PFPR facilities  in
several  ways:    they  are  typically  small  businesses,  participate ' to  a  large  degree   in the
                                               4.39

-------
  institutional/commercial market, receive a relatively small share of total revenue from PFPR activities,
  and more often use certain active ingredients to formulate sanitizer products.30

         On the basis of these distinguishing characteristics, EPA  defined a modification to Option 3,
  namely Option 3/S, as the preferred regulatory alternative. Option 3/S corresponds to Option 3 except
  that certain non-interior source wastewater streams are exempted from the regulatory requirements.
  Specifically, for those facilities that formulate, package, or repackage sanitizer active ingredients and
  whose sanitizer production is less than 265,000 pounds per year, the zero discharge requirement would
  not apply to physically separate, non-interior wastewater streams that contain only designated sanitizer
  PAIs?1  These non-interior wastewater streams include exterior equipment and floor wash, leak and
  spill cleanup, safety equipment rinsate,  contaminated precipitation run-off, laboratory wastewater, air
  pollution control wastewater, and DOT test bath water. The zero discharge requirement would apply to
  the interior wastewater streams of these facilities including discharge from cleaning the interiors  of
 drum/shipping containers,  bulk containers, and other equipment.

        Impacts of Option  3/S.  Under Option 3/S, 529 Subcategory C facilities are expected to incur
 costs.  One hundred thirteen of these facilities were analyzed for  possible  facility closure and the
 remaining 416 were analyzed for line conversions.  A comparison of annualized compliance cost to
 facility revenue was conducted for all Subcategory C facilities. The capital and annualized total costs
 (which include amortized capital, annual operating and maintenance, and monitoring costs) of complying
 with Option 3/S are expected to be $63.0 and $26.1 million, respectively.  One facility is projected to
 close due to compliance with Option 3.  One hundred thirty-six facilities (20 percent fewer than under
 Option 3) are expected to incur moderate economic impacts. Total  U.S. job losses are projected, in the
 worst case, to be 355 FTEs as a result of the estimated impacts  (17  percent fewer than  under Option 3).

        Table 4.5 compares the impacts projected under Option 3 and 3/S, providing detail for facilities
 with wastewater streams containing only sanitizer PAIs, and thus eligible for the sanitizer PAI exemption.
    30For further details, see Chapter 5, Regulatory Flexibility Analysis.

     'See Table 8 of the regulation or Section 12 of the Technical Development Document (Development Document
for Beat Available Technology, Pretreatment Technology, and New Source Performance Technology for the Pesticide
Formulating/Packaging/Repackaging Industry: Proposed) for a list of the sanitizer active ingredients that are eligible
for exemption from the zero discharge requirement under this regulation.
                                               4.40

-------
                                      Table 4.5
             National Estimates of Impacts for Subcategory C Facilities Under
                               Option 3 and Option 3/S
                          (Assuming Zero Cost Pass Through)
                                                            Option 3
         Option 3/S
Facilities with only wastewater streams containing non-
sanitizer pesticide PAIs
-Facilities Projected to Incur Costs
-Total Capital Compliance Costs
(millions of dollars)
-Total Annualized Compliance Costs
(millions of dollars)
-Facility Closures:
(Severe Economic Impacts)
-Facilities Incurring
Moderate Economic Impacts
-Worst Case Expected Job Losses (FTEs)
391
$59.3

$24.0

  1

119

348
391
$59.3

$24.0

  1

119

348
Facilities with wastewater streams containing only sanitizer
,PAb
-Facilities Projected to Incur Costs
-Total Capital Compliance Costs
(millions of dollars)
-Total Annualized Compliance Costs
(millions of dollars)
-Facility Closures:
(Severe Economic Impacts)
Facilities Incurring
Moderate Economic Impacts
-Worst  Case Expected Job Losses (FTEs)
167
 $6.8

 $3.9

  0

 51

 78
138
 $3.6

 $2.1

  0

 17

  7
All Subcategory C'Facilities
-Facilities Projected to Incur Costs
-Total Capital Compliance Costs
(millions of dollars)
-Total Annualized Compliance Costs
(millions of dollars)
-Facility Closures:
(Severe Economic Impacts)
-Facilities Incurring
Moderate Economic Impacts
-Worst Case Expected Job Losses (FTEs)
558
$66.1


$27.9


  1


170


426
529
$63.0


$26.1


  1


136


355
                                       4.41

-------
       Subcategory E impacts.  For Subcategory E facilities, EPA analyzed the impacts of two possible
regulatory options, both based on zero discharge.  Option 1 assumes that the contaminated wastewater
is used as make-up water in application of pesticide chemicals to the field.  Option 2 assumes that the
wastewater is contract-hauled for incineration.  The Agency is proposing Option 1.

       Of the estimated 1,122 Subcategory E facilities that are potentially subject to the regulation, data
from the Survey indicate that 98 percent, or 1,103  facilities, are already in compliance. They therefore
would not incur any costs  to comply with the proposed regulatory option. In addition, the remaining 19
facilities are expected to be able to achieve compliance with the proposed regulation at zero additional
cost.
       Under Option 2, the same population of facilities (i.e, approximately 19 facilities) are evaluated
for compliance costs.   The  estimated incremental capital and annualized total costs (which include
amortized capital, annual operating and maintenance, and monitoring costs) of complying with Option 2
are estimated to be $11,794  and $1,837, respectively.  (See Table 4.6)  A comparison of annualized
compliance cost to facility revenue was conducted for the 19 facilities with costs under Option 2.  The
estimated mean compliance cost as  a percentage of facility revenue would be  0.026 percent and the
estimated median value 0.032 percent, with a range from 0.001 percent to 0.048 percent.  No facilities
had a cost-to-revenue ratio greater than five percent.
Table 4.6
Estimated National Impacts for Subcategory E Facilities

-Facilities Incurring Costs
-Total Capital Compliance Costs
-Total Annualized Compliance Costs
-Facility Closures:
(Severe Economic Impacts)
-Moderate Economic Impacts
Option 1
0
0
0
0
0
Option 2
19
$11,794
$1,837
0
0
                                              4.42

-------
                                          Chapter 5
                              Regulatory Flexibility Analysis

5.0    Introduction
       This chapter considers the expected effects of the proposed effluent limitations guidelines and
standards for the pesticide formulating, packaging and repackaging (PFPR) industry on small entities
pursuant to the Regulatory Flexibility Act. The Regulatory Flexibility Act (Public Law 96-354) calls for
the Agency to prepare a Regulatory Flexibility Analysis (RFA) for regulations that are expected to have
a significant impact on a substantial number of small entities.1  The purpose of the Act is to ensure that,
while achieving statutory goals, government regulations do not impose disproportionate impacts on small
entities.

       The Regulatory Flexibility Act also calls for record-keeping and reporting requirements to be
indicated, as well as any federal rules  that duplicate, overlap,  or conflict with the proposed rule.  The
proposed effluent guideline imposes no  reporting and  record-keeping requirements.  In addition, no
known Federal  rules duplicate, overlap, or conflict with the  proposed rule.  However, the PSES
guidelines for refilling establishments build upon The Office of Pesticide Programs' proposed regulation
that  will require refilling establishments of agricultural pesticides to  build  secondary containment
structures and loading pads to certain specifications.  Because requirements  associated with several
regulations became  effective since the PFPR Survey was administered, this analysis includes the costs of
complying with  these regulations to ensure a full accounting of environmental regulatory costs.  These
regulations include  the land disposal restrictions under the Resource Conservation and Recovery  Act,
effluent limitations for the Organic Chemicals, Plastics and Synthetic Fibers Industry, effluent limitations
for the Pesticide Manufacturing Industry,  and annual maintenance fees required under the  Federal
Insecticide, Fungicide and Rodenticide Act  Amendments of 1988.  The  costs  of complying with these
regulations are accounted for as part of the baseline conditions so that projected costs and impacts are a
result of the proposed regulation only.

        In performing this analysis,  EPA  had to balance the traditional concerns of a  Regulatory
Flexibility Analysis — moderation of impacts among small-business entities — with the broader regulatory
    '"Small entities" are defined in Section 5.1.
                                               5.1

-------
objectives of the Clean Water Act.  In particular, because the PFPR industry was found to be heavily
dominated by small business concerns, EPA recognized that efforts to moderate economic impacts broadly
among small-business entities would require analyzing various characteristics other than entity size to
understand which facilities were expected to be impacted under Option 3, the regulatory option originally
selected.  The Agency therefore analyzed whether  subgroups of facilities, defined by major pesticide
market,  were disproportionately  affected  and considered whether  technical  and market  factors
distinguished any subgroups in ways that would  warrant  different regulatory approaches  for  those
subgroups.   The analysis considered  a number of classification criteria — including principal market
served, reliance on PFPR activities as a source of revenue, and active ingredients used — in addition to
business size classification as the basis for understanding the distribution of impacts under Option 3 for
Subcategory C facilities.

        This analysis found that adverse impacts most frequently occurred among certain PFPR facilities
that may be characterized as follows:  they are typically small businesses, participate to a large degree
in the institutional/commercial market, receive  a relatively  small share of revenue from PFPR  activities,
and often use certain active ingredients to formulate sanitizer products.  For example, two-thirds  of all
impacted facilities in the I/C market use PAI 56, Hyamine 3500, in their PFPR activities.  On the basis
of the distinguishing characteristics of these affected facilities, EPA defined and analyzed an alternative
to Option 3,  namely Option 3/S, that reduces the regulatory  burden to these facilities.  As described in
Chapter 4 of this document, the proposed alternative, Option 3/S, exempts certain wastewater streams
from  Option 3's zero discharge requirements.  Specifically, Option 3/S exempts physically separated,
non-interior process wastewater streams that contain only designated sanitizer chemicals from the zero
discharge requirement.   All other wastewater streams  must meet  the Option 3  zero  discharge
specifications.  The Option 3/S alternative was  found to  mitigate appreciably the impacts within the
identified group of affected facilities, including  small business-owned  facilities, while the number of
pounds of pollutants that would not be controlled is very small. The Agency found no other subcategory
of facilities that could be provided relief and still meet EPA's stated regulatory objectives under the Clean
Water Act.
       The following sections of this chapter describe the analysis underlying the definition of Option
3/S, and assess its impacts.  Specifically, Section 5.1 discusses the methodology used to identify small
entities.  Section 5.2 then examines the characteristics of facilities assessed as significantly affected under
                                               5.2

-------
Option 3.  Section 5.3 defines and analyzes the alternative regulatory option, Option 3/S, which was
developed to alleviate some of the disproportionate impacts while maintaining most of the environmental
benefits of Option 3.  Section 5.4 compares the estimated impacts under Options 3 and 3/S.

5.1    Identifying Small Entities
       To perform the Regulatory Flexibility Analysis, EPA needed to identify whether facilities were
owned by a small business entity.  This effort involved several steps. First, EPA specified the entities
that could potentially incur costs of compliance and are therefore subject to impacts of the regulation.
Second, the criteria that characterize an entity as "small" were identified based on the Small Business
Administration (SBA) business size classification applicable to the PFPR industry.  This characterization
involved identifying the firm-level ownership of Survey facilities and obtaining or estimating firm-level
employment for the firms that own PFPR facilities. These data were then used to specify whether or not
facilities are owned by a small business, as defined by SBA.

       Identifying Potentially Affected Entities
       As previously discussed, the analysis is based on the sample of  total PFPR facilities surveyed
under authority of section 308 of the Clean Water Act. This sample represents the 1,122 Subcategory
E Refilling Establishments and 1,282 Subcategory C PFPR facilities that were in business in 1988.  The
proposed regulation for Subcategory E Refilling Establishments  requires zero discharge of wastewater
pollutants based on reuse of contaminated wastewater.  As described in Chapter 4, EPA's analysis shows
that the Subcategory E regulation will impose only minor capital outlays and no annual compliance costs.
Accordingly, EPA expects the Subcategory E regulation to  impose no significant economic impacts and
did not perform a regulatory flexibility analysis of this regulation.  The following analysis, therefore,
pertains only to Subcategory C PFPR facilities. The analysis covers 943  Subcategory C PFPR facilities
that would be subject to the PSES regulation and that use water in their PFPR operations.  It is these
facilities that are expected to  incur costs of compliance and thus may be significantly affected  by the
regulation.
                                               5.3

-------
        Denning "Small Entity"
        Because the analysis considered differential impacts according to business-size classification as
well as other facility identification criteria, it was necessary to define "small entity" and classify facilities
in the PFPR industry survey according  to whether they  are owned by a small business.  The Small
Business Administration (SBA) defines small entities in terms of the number of firm employees or firm
revenues by Standard Industrial Classification (SIC) code.  Pesticide formulating and packaging activities
are categorized as SIC 2879. SBA defines a small entity with a SIC code of 2879 as a firm with 500 or
fewer employees. No revenue thresholds are given for this SIC code.  For this analysis, EPA adopted
SBA's small  entity definition.

        Classifying Facilities into Firms2
        Because SBA defines small entities in terms of employment at the firm level, EPA next classified
facilities according to whether they are part of a single or multi-facility firm, and identified the owning
firm for facilities that are part of multi-facility operations. For this classification, EPA relied primarily
on the Survey data but used secondary sources when necessary. If a facility indicated on its questionnaire
that it was a single entity (question 12 in the Introduction), then the facility was classified as a firm.  To
identify other firms, facilities were classified according to their FIFRA identification numbers, which are
generally held at the firm level, or on the basis of facility Dun and Bradstreet numbers (questions 2 and
3 in the Introduction), parent or parent's parent company names, addresses, and Dun and Bradstreet
numbers (questions 13 and 16 in the Introduction).

        Estimating Firm Employment
        Firm employment was estimated  to classify facilities as  being owned by either small or other
entities as defined by the SBA.  For those facilities indicated by their  survey data to be single entities,
firm employment was calculated by summing formulating, packaging and repackaging employee hours,
all other production worker hours, and non-production worker hours as reported in the Survey (question
17 in the Introduction). The sum of these worker hours  was divided by 2,000  to yield the  full time
employee equivalent.
   2For this report, the terms "firm" and "entity" are interchangeable.
                                              5.4

-------
       If the facility was not a single entity, the 1993 Dun and Bradstreet Million Dollar Directory was
consulted for firm employment data.  If a firm was not found in the 1993 directory but had been in the
1992  directory, then  1992 employment  data were  used.3  Of the 399 sample  firms  identified,
employment data were not obtained for 62 firms, or approximately 15.5 percent of the sample.  For these
62 remaining sample firms, employment was estimated from a regression analysis.4 The available firm
employment data were regressed on 1988 parent firm revenue data as reported in  the Survey (question
14 in the Introduction for single entities and question 8A in Section One of Part B  for others).  The
parameter estimate was then applied to the 62 firms to estimate firm employment for these firms.  The
model specified as:

                                 FRMEMP  =  a FRMREV'.+ e
 where
        FRMEMP
        FRMREV
        a
        e
firm employment;
1988 firm revenue;
the parameter estimate; and
the unknown error term.
        A total of 283 observations (sample firms for which both employment and revenue data existed)
 were used in this analysis.  The value of a is 0.000004746, significant to 99.99 percent.  The adjusted
 R2 is 64  percent. This indicates that the parameter  estimate will provide reasonably good estimates of
 firm employment for the 62 firms reporting firm revenue data but lacking firm employment data.  This
 equation  yields an average estimate of one full time  employee per $210,704 in 1988 firm revenue.
     3Where possible, the EIA is based on 1988 data.  However, Dun & Bradstreet employment data are available
 on a subscription basis only for the current year. EPA first assembled firm-level employment data in 1992 and then
 updated these data in 1993.
     4 Refilling establishments and direct dischargers were included in this part of the analysis so that more data
 points would be available for the regression analysis to establish employment figures for firms with missing data.
 A regression analysis was also conducted excluding refilling establishments, however it did not yield a significantly
 different parameter estimate.  The regressions were performed on unweighted sample data.  Sample weights were
 not used for these analyses because the weights apply to facilities but not to firms.

                                                5.5

-------
          If the estimated number of employees at the firm level was greater than the SBA threshold of 500
  employees, then the facility was classified as being owned by a non-small entity. If the estimated number
  of employees at the firm level was equal to or less than the SBA threshold, then the facility was classified
  as being owned by a small entity.  From this comparison, EPA found that 700, or 74 percent, of the 943
  facilities considered in the analysis are owned by small entities.

  5.2     Assessing the Distribution of Impacts
         Of the five regulatory options initially considered, EPA considered selecting Option 3 because
  it achieves zero discharge but results in sufficiently low economic impacts to be judged economically
  achievable.  For the Regulatory Flexibility Analysis, EPA examined the impacts of Option 3 to discern
  whether small business impacts were concentrated among certain classes of facilities according to market
  or PAI use.  In this effort, EPA considered first the extent of small business participation in the PFPR
  industry, and the extent  of impacts among facilities owned  by  small businesses.  However,  because a
 substantial majority of PFPR facilities were found to be owned by small businesses, EPA recognized that
 the analysis of differential impacts would necessarily include  other classification criteria beyond business
 size. Specifically, EPA analyzed the distribution of impacts according to additional classification criteria,
 as follows:  primary market source of PFPR revenues, percent of facility revenue derived from PFPR
 activities, and the PAIs  most frequently used by  the facilities in the PFPR market with the greatest
 concentration of affected  facilities.  Throughout this analysis, EPA performed  a parallel assessment of
 the distribution of impacts by business-size of affected facility.  From this analysis, EPA defined  and
 analyzed an alternative, Option 3/S, to the initially selected regulatory option, Option 3.

        In analyzing the distribution of economic impacts for the Regulatory Flexibility Analysis, EPA
 drew no distinction between the severe (facility closure) and moderate (facility line conversions or costs
 of compliance in excess of 5 percent of facility revenues) impact categories as defined in the preceding
 chapter.5 All economic impacts were combined for assessing the distribution of impacts by the various
 facility classification criteria.
   5Notably, only one facility is projected to incur a severe impact due to compliance under Option 3. This facility
is owned by a small entity.
                                              5.6

-------
        Distribution of Potentially Affected Facilities and Economic Impacts by Entity Size
        EPA estimates that a total of 943 PFPR facilities will be subject to the Subcategory C regulation.
Of these, 700 (74.2 percent) are estimated to be owned by a small firm and 243 (25.8 percent) are owned
by not-small, or other, firms.  Within the total set of facilities subject to regulation, the subset of facilities
that are expected to  incur compliance costs are those in which compliance impacts are possible.  Of the
estimated 943 PFPR facilities, 558 are expected to incur compliance costs.  Of these, 416 (74.6 percent)
are owned by small  firms and 142 (25.4 percent) are owned by other firms (see Table 5.1).  Clearly, a
substantial majority of the PFPR facilities that are subject to impacts are owned by small business entities.

        EPA  also characterized  the  distribution  of economic impacts  according  to business size
classification. Of the 558 facilities that are expected to incur compliance costs, 171  are expected to incur
moderate or severe impacts.  Of these, 150 or 87.7 percent are owned by small entities, a frequency of
impact that exceeds the share of small business-owned facilities in the facility population expected to incur
costs as a result of the regulation (74.6 percent) (see Table 5.1).

        As a second  test of the compliance burdens of Option 3 on small businesses, EPA considered the
ratio of expected compliance costs to total facility revenues.  This analysis found that the mean ratio of
total annual costs of compliance to total facility revenues is higher for facilities owned by small entities,
2.1 percent, than for other entities, 0.3 percent.  This ratio further indicates the extent of burden likely
to be incurred by small business in complying with Option 3  (see Table 5.1).

       EPA determined overall that Option 3 is economically achievable. In particular, only one facility
was  assessed  as a  closure  and  most of the expected economic  impacts are associated  with line
conversions. Even if all the PFPR line conversions close instead of converting to other formulating and
packaging activities, EPA estimates that job losses would not exceed 426 full-time equivalent positions
nationally. Nevertheless, EPA recognized that these moderate impacts would substantially affect small
business entities and was thus concerned with the regulation's burden  on small business.  At the same
time, because a substantial majority of PFPR facilities are owned by small entities, EPA structured its
efforts to determine  the characteristics of impacted facilities and to define an alternative regulation by
using other facility criteria in addition to business size.
                                               5.7

-------
Table 5.1 Distribution of Projected Costs and Impacts of Option 3 on Facilities Owned
by Small and Other Entities

Estimated Population of PFPR
Facilities
Regulated Under
Subcategory C
Facilities With Costs of
Compliance
Facilities Projected to Incur
Impacts
Mean Total Annual Cost of
Compliance to Revenue (For
Facilities With Costs)
Median Total Annual Cost of
Compliance to Revenue
(For Facilities With Costs)
Total
943
(100.0%)
558
(100.0%)
171
(100.0%)
1.6%
0.5%
Facilities Owned
By Small Entities
700
(74.2%)
416
(74.6%)
150
(87.7%)
2.1%
1.0%
Facilities Owned
By Other
Entities
243
(25.8%)
142
(25.4%)
21
(12.3%)
0.3%
0.2%
       Distribution of Economic Impacts by Primary PFPR Market
       In analyzing the characteristics of affected facilities, EPA first examined the primary markets
from which affected facilities derive 272 PAI-related PFPR revenue.  For this analysis, EPA defined a
primary market as one from which a facility receives at least fifty percent of its 272 PAI-related PFPR
revenue.  Impacts were  analyzed by market, with market definitions based on responses to Survey
question #19 (page 1-9 of the Survey).  Responses to this question indicated each facility's total 1988
revenues from 272 PAI-related pesticide products by the following markets:

       •      agricultural
       •      institutional/commercial
       •      industrial
       •      wood preservatives and coatings
       •      pesticide intermediate products
       •      products used as an additive to a non-pesticide product
       •      non-agricultural professional use products
       •      consumer home, lawn,  and garden
                                              5.8

-------
       •      government, for non-institutional use
       •      other.

       This analysis indicated that facilities obtaining at least fifty percent of their 272 PAI-related PFPR
revenue from the Institutional/Commercial (I/C) market bore both a large and disproportionately high
percentage of the impacts under Option 3.  Table 5.2 indicates the distributions by primary market of all
facilities projected to incur costs  under  Option 3, and of those facilities projected to incur significant
economic  impacts under Option 3. As shown in the table, of the 558 facilities expected to incur costs,
267 (47.8 percent) receive 272 PAI-related PFPR revenue primarily from the I/C market.  Moreover,
the distribution of significant economic impacts is even more concentrated among facilities primarily
reliant on the I/C market for 272 PAI-related PFPR revenue.  Of the 171 facilities expected to incur
significant economic impacts, 102 (59.8 percent) receive 272 PAI-related pesticide revenue primarily
from the I/C market.

        Table 5.2 also summarizes primary market  information for small business-owned facilities that
are expected to incur costs or incur significant economic impacts.  Small facilities that are estimated to
incur costs  or impacts show greater concentration in the I/C market than do  facilities  as a  whole.
Specifically, of the 416  small business-owned  facilities that are expected to  incur costs, 227 or 54.6
percent receive 272 PAI-related PFPR  revenue primarily from the I/C market.   In comparison, 47.8
percent of all facilities incurring costs under Option 3 receive 272 PAI-related PFPR revenue primarily
from the I/C market. Similarly, of the  150 small business-owned facilities expected to incur significant
economic impacts,  98 or 65.5 percent  receive  272 PAI-related PFPR revenue primarily from the I/C
market.  Again, the percentage for small business-owned facilities exceeds the value for all facilities of
59.8 percent.  Indeed, of the 102 impacted facilities in the I/C market owned by both small and not-small
businesses,  98, or  96.1 percent are  owned  by  a  small  business.   This  finding  underscores  the
concentration of impacts on small businesses operating in the I/C  market.

        Distribution of Economic Impacts by Dependence on PFPR Revenue
        EPA next examined the distribution of estimated impacts based on facilities' dependence on PFPR
revenue.  This  analysis showed  that facilities  that are  expected  to incur economic impacts generally
receive only a relatively small percentage of their revenue from PFPR activities.  Using the three-year
 (1986-1988) average ratio of PFPR revenue to total facility revenue as reported in the PFPR Survey, EPA
                                               5.9

-------
Table 5.2
Distribution by Primary Market of Facilities Incurring Costs and of
Facilities Expected to Incur Significant Economic Impacts Under Option 3
Primary Market
Agricultural
Institutional/Commercial
Industrial
Wood Preservatives and
Coatings
Pesticide Intermediate
Products
Additives to Non-
Pesticide Products
Non-Agricultural
Professional Use Products
Consumer Home, Lawn
and Garden
Government, for Non-
institutional Use
Other
No Primary Market
Total
Distribution of Facilities Estimated to
Incur Costs Under Option 3
Number and
Percent of All
Facilities with
Costs
61
(10.9%)
267
(47.8%)
114
(20.4%)
18
(3.2%)
12
(2.2%)
1
(0.2%)
15
(2.7%)
56
(10.0%)
6
(1.1%)
1
(0.2%)
7
(1.3%)
558
(100.0%)
Number and
Percent of Small
Business Facilities
with Costs
44
(10.6%)
227
(54.6%)
85
(20.4%)
6
(1.4%)
2
(0.5%)
1
(0.2%)
6
(1.4%)
40
(9.6%)
0
(0.0%)
1
(0.2%)
5
(1.2%)
416
(100.0%)
Distribution of Facilities Estimated
to Incur Impacts Under Option 3
Number and
Percent of AH
Facilities with
Impacts
6
(3.6%)
102
(59.8%)
48
(28.3%)
0
(0.0%)
0
(0.0%)
0
(0.0%)
7
(4.2%)
2
(1.3%)
5
(2.9%)
0
(0.0%)
0
(0.0%)
171
(100.0%)
Number and
Percent of Small
Business Facilities
with Impacts
6
(4.1%)
98
(65.5%)
43
(28.8%)
0
(0.0%)
0
(0.0%)
0
(0.0%)
0
(0.0%)
2
(1.5%)
0
(0.0%)
0
(0.0%)
0
(0.0%)
150
(100.0%)
A facility's primary market is the PFPR market from which it receives at least 50 percent of its PFPR
revenue. Percentages may not sum to 100 percent because of rounding.
estimated that 187 out of the 188 facilities (99.5 percent) assessed as incurring economic impacts under
Option 3 receive less than 25 percent of their revenues from PFPR (see Table 5.3).  Only one facility
that receives more than 25 percent of total facility revenues from PFPR is assessed as likely to incur a
                                              5.10

-------
Table 5.3
Dependence on PFPR Revenue of Facilities Incurring Impacts Under Option 3
(by business-size classification and primary market)
Primary Market
Agricultural
Institutional / Commercial
Industrial
Wood Preservatives and
Coatings
Pesticide Intermediate
Products
Products used as Additives
to Non-Pesticide Products
Non-Agricultural
Professional Use Products
Consumer Home, Lawn
and Garden
Government, for Non-
Institutional Use
Other
No Primary Market
Total
Facilities With Less Than 25
Percent of Revenue from PFPR
Activities
All Facilities
6
102
48
0
0
0
7
1
5
0
0
170
Small-Business
Owned Facilities
6
98
43
0
0
0
0
1
0
0
0
149
Facilities With At Least 25 Percent
of Revenue from PFPR Activities
...... . . , , , *• ,.,:_. :.:.:•;•
All Facilities
0
0
0
0
0
;
0
0
1
0
0
0
1
Small-Business
Owned Facilities
0
0
0
0
0
0
0
1
0
0
0
1
Sum of column may not equal total due to rounding.
significant economic impact under Option 3.  In summary, impacted facilities do not rely predominantly
on PFPR revenues to sustain their facilities economically. In fact, on average these facilities derive only
6.7 percent of their total revenue from PFPR activities. This finding further underscores the relatively
mild character of the impacts estimated for Option 3.
                                              5.11

-------
       Again, small business-owned facilities also exhibit the same pattern of low reliance on PFPR
activity as a source of business revenue. Of the 161 small business-owned facilities that were assessed
as incurring significant economic impacts under Option 3, all but one receive less than 25 percent of total
facility revenue from PFPR activity.

       Pesticide Active Ingredient Usage by Impacted I/C Facilities
       From the foregoing analyses, EPA found that the  impacts of Option 3 were expected to occur
most among facilities that receive a majority of their1 PFPR revenue from the Institutional/Commercial
market, and that rely to a relatively low extent on PFPR business as a source of revenue.  In addition,
EPA concluded that economic impacts are concentrated among facilities that are owned by small firms.
However, this last observation results largely from the fact  that small business-owned facilities represent
a substantial majority of facilities in the PFPR industry.

       Because certain PAIs may be associated  with  certain markets  and given the concentration of
economic impacts among facilities in  the I/C market, EPA next examined the  PAI  usage of these
significantly affected facilities in the I/C market to ascertain any particular patterns of PAI usage. From
this  analysis, EPA found that the PAI  used most frequently by the significantly affected facilities that
receive a majority of their PFPR revenue in the I/C market is PAI 56, Hyamine 3500:  66.3 percent of
the 102 significantly affected facilities in the I/C market use this PAI.  No other PAI was  used half as
frequently among these facilities.  Of these 102 facilities,  98 are owned by a small business and these
facilities also rely extensively on PAI 56:  69.0 percent of the impacted small-business facilities in the
I/C market were found  to use Hyamine 3500 in their PFPR  activities.  Thus, use of PAI 56, Hyamine
3500,  is consistently high among both small business-owned impacted  facilities and other impacted
facilities in the I/C market.

        EPA also considered Hyamine  3500's potential contribution to pollution.   Using the Agency's
toxic weighting factors, which score the toxicity of pollutants on a linear scale relative to copper, EPA
found that PAI 56,  Hyamine 3500, has a relatively low toxicity value of 0.093. Other PAIs commonly
used by impacted facilities primarily in the I/C market were found to be more toxic. The PAI used with
the next highest frequency was found to be over 4,300 times as toxic as Hyamine 3500.6
    6 A full discussion of toxic weighting factors is provided in the cost-effectiveness report.
                                              5.12

-------
       Taking into account both the high frequency of use of Hyamine 3500 (PAI 56) by impacted I/C
facilities and the comparatively low toxicity of that PAI as a component of effluent waste streams, EPA
decided to  examine less stringent requirements with respect to PAI 56 in its efforts to moderate  the
economic impact of Option 3 on the primarily small business-owned facilities in the I/C market.

5.3    Defining an Alternative to Option 3
       From the analyses described above,  EPA determined that the costs  associated  with installing
treatment systems to recycle non-interior wastewater sources would cause economic  impacts at certain
PFPR facilities.  These facilities are distinguished from other PFPR facilities in several ways:  they are
typically small businesses in the Institutional/Commercial market, receive a relatively small share of total
revenue from PFPR activities, and are apt to use PAI 56 in their PFPR activities.  On the basis of these
findings, EPA sought to define a regulatory alternative to Option 3 based on PAI 56, Hyamine 3500.
However, EPA recognized that isolating PAI 56 as the sole basis for a regulatory exemption might confer
a market advantage to Hyamine 3500 relative to other PAIs with which it competes.

        In the EIA for the Pesticide Manufacturers effluent guidelines, EPA defined markets of competing
PAIs. This market definition is more detailed than the broad markets listed in the Survey. For example,
not all pesticides used in the agricultural market compete with each other.  Pesticides  used as herbicides
on corn do not compete with pesticides used as fungicides on apples.  Pesticide markets were therefore
defined as  clusters of PAIs that are substitutes in a specific end-use (e.g., herbicides on corn).  The 272
PAIs, or classes of PAIs, on which this impact analysis is based are mapped into 57 separate clusters
 along with other PAIs with which they compete (see Appendix F).

        Hyamine 3500 (PAI 56) is a member of the R-4 cluster which is defined as:  "Sanitizers for use
 in dairies,  food  processing, restaurants, and air treatment". The other PAIs included in this cluster (from
 the list of 272  on which  this analysis is based) are: Hyamine 2389  (PAI 162),  methyl benzethonium
 chloride (PAI 159), Hyamine 1622  (PAI 105), oxine-sulfate (PAI 51), and HAE (PAI 36). Because the
 sanitizer PAIs have the same general use, they are roughly substitutable. Accordingly, if a regulatory
 exemption were defined  solely on  the basis of Hyamine 3500,  the exemption might confer  a market
 advantage to Hyamine  3500 relative to the other PAIs  in the R-4 cluster with which it competes.  To
 avoid this  result, EPA defined the modification to Option 3, Option 3/S, based on the R-4 cluster instead
 of on the  individual PAI Hyamine 3500.

                                              5.13

-------
        Specifically, EPA defined a regulatory alternative to Option 3 based on the physically separated
 wastewater streams generated  in conjunction with the formulating, packaging,  or  repackaging of the
 sanitizer chemicals comprising the R-4 Cluster.  This option, called Option 3/S, is the same as Option 3
 except for those facilities that formulate, package, or repackage sanitizer active ingredients and whose
 sanitizer production is less than 265,000 pounds per year.  Specifically, in these facilities,  non-interior
 wastewater streams (e.g. from floor wash, exterior equipment cleaning,  and laboratory rinsates) that
 contain only active ingredients from designated sanitizer chemicals would be exempt from the Option 3's
 zero  discharge requirement.  All other PAI wastewater streams at these facilities, including  interior
 wastewater streams containing sanitizer PAIs and  any exterior wastewater  streams  containing both
 sanitizer and other PAIs, would be subject to the zero discharge requirement.   As is the case for Option
 3, the zero discharge requirement for these other wastewater streams can be  met through pollution
 prevention, recycle/reuse,  and treatment when  necessary.   The Option 3 zero discharge requirement
 would apply to all PAI wastewater streams at any facility whose wastewater streams do not qualify for
 the sanitizer PAI exemption.

        In defining this regulatory  alternative, EPA set the 265,000 pounds per year production limit
 based on analysis of the production volume of facilities that would be expected to avoid adverse impacts
 as a result of the Option 3/S sanitizer chemical exemption.  Specifically, in its facility impact analyses,
 EPA found that no facility larger than the 265,000 pounds per year sanitizer production limit would avoid
 a significant impact as a result of the exemption.  Accordingly, in an effort to mitigate significant impacts
 among PFPR  facilities owned by small businesses while retaining as large a share as possible of the
pollution reduction benefits of the originally selected Option 3, EPA decided to limit the Option 3/S
 sanitizer chemical exemption to only those facilities with less than 265,000 pounds per year of production
 involving designated sanitizer PAIs.

        EPA expects that this regulatory alternative will reduce impacts on the most heavily burdened
subgroup of facilities owned by small businesses with only a minimal increase in pollutant releases to the
environment.
                                              5.14

-------
5.4    Impacts of Option 3/S
       Under Option 3/S, which embodies the exemption for R-4 Cluster PAIs contained in physically
separated, non-interior wastewater sources, 530 facilities are expected to  incur costs of compliance,
compared to 558 facilities under Option 3. Of the 530 facilities incurring costs under Option 3/S, 392
(73.4 percent) are owned by a small entity. The number of facilities that are significantly affected (severe
and moderate impacts combined) falls from 171 (under Option 3) to 137 under Option 3/S.  The number
of impacted facilities owned by small businesses falls from 150 to 116, or a decrease of 22.7 percent in
the number of impacted facilities owned by small entities. Moreover, the  percentage of small entity-
owned facilities (out of the total of small entity-owned facilities in the PFPR population) that is estimated
to incur economic impacts falls from 21.4 percent to 16.6 percent (see Table 5.4, below).
Table 5 A Distribution of Costs and Impacts Under Options 3 and 3/S
Regulatory Option
Number of Facilities in Population
Number of Facilities with Costs
Number of Facilities with Impacts
Percent of Facilities in Population
Incurring Impacts
Option 3
Total
943
558
171
18.1%
Small
700
416
150
21.4%
Option 3/S
Total
943
530
137
14.5%
Small
700
392
116
16.6%
       At the same time, Option 3/S is expected to result in only a slight increase in pollutant discharges
relative to Option 3.  EPA estimates that the  Option 3/S exemption will  result  in  total additional
discharges of 203 pounds annually, but only an  additional 19  toxic-weighted pounds7.  The low ratio
of toxic-weighted pounds to unweighted pounds  reflects the low toxicity of PAI 56  and other sanitizer
PAIs when compared to copper.

       Taking into account both the substantial relief to small business-owned facilities provided by
Option 3/S and the very modest loss in pollution reduction benefits, EPA selected this option as the
preferred regulatory option for PSES limitations to be applied to Subcategory  C PFPR facilities.
    7 See Chapter 12 for an analysis of combined discharges resulting from the original 272 PAIs and additional
non-272 PAIs.
                                              5.15

-------
                                    Chapter 5 References

Dun's Marketing Services, Inc. (1993). Million Dollar Directory.  New Jersey.
The Revised EPA Guidelines for Implementing The Regulatory Flexibility Act. (April 1992).
                                             5.16

-------
                                         Chapter 6
                               Community Impact Analysis
6.0    Introduction
       This chapter examines impacts to communities that may result from effluent limitations guidelines
and standards for the pesticide formulating, packaging and repackaging (PFPR) industry.  Community
impacts are evaluated based on estimated employment loss in communities affected by the regulation.
Employment losses are estimated, as applicable, for those facilities found to be affected significantly by
the proposed regulation. The analysis does not consider potential employment increases at non-impacted
facilities.  If the employment losses are expected to cause a greater than one percent decline in total
employment in the affected community, then the community impact is deemed significant.
                                                                  ;
       This chapter focuses on impacts  for the PSES rule applicable to Subcategory  C facilities.
Employment losses are examined for all five PSES regulatory  options considered for Subcategory C
facilities initially, plus the proposed Option 3/S, a modification to the initial Option 3.  Because EPA
selected  Option 3/S as the preferred PSES regulatory approach for the Subcategory  C facilities,
community impacts are examined for this option.

       No community impact analysis was undertaken for the PSES regulation proposed for Subcategory
E facilities, Refilling Establishments. In the facility-level impact analysis presented in Chapter 4, neither
of the two regulatory options considered for Refilling Establishments was found to impose any significant
economic impacts.  Accordingly, with no  employment losses anticipated from the PSES regulation for
Subcategory E facilities, a community impact analysis  is not necessary.

        Within the Subcategory C facilities subject  to PSES requirements, only facilities that use and
discharge water can incur costs and thus be adversely affected by the regulation's requirements.  For this
reason, the scope of the community impact analysis  is  restricted to the 651 Subcategory C facilities that
use and discharge water and are regulated under PSES.
        On the basis of the analysis  presented in this  chapter, the proposed regulatory  option for
 Subcategory C facilities,  Option  3/S,  is  not expected to  cause significant community  impacts:
 community-level employment losses are expected to be well less than one percent.
                                               6.1

-------
        The remaining sections  of this chapter are organized as follows.  Section 6.1  presents the
 methodology for assessing community impacts.  Section 6.2 summarizes the estimated employment losses
 for each regulatory option, and assesses the significance of those losses for Option 3/S.

 6.1     Methodology for Assessing Community Impacts
        Facility closures, either totally or in part, may result in employment losses.  The significance of
 such employment losses at the community level is measured relative to the community's pre-compliance
 employment. Typically, a community is defined as the Metropolitan Statistical Area (MSA) in which the
 facility is located.1 The MSA is assumed to represent the labor market area within which residents could
 reasonably commute to work. If the facility is not located within an MSA, then the community is defined
 on the basis of the county,  and county-level  employment is used to determine the significance of
 employment losses. Either way,  if the estimated employment loss from facility impacts is greater than
 one percent of the pre-regulation community employment, the community-level  employment impact is
 considered significant.

       EPA considers community employment impacts taking into account both primary  impacts and
 secondary impacts.  Primary impacts consist of the employment losses that are expected to occur as a
 direct result of the regulation.  Secondary economic impacts and associated employment losses occur in
 other businesses than those directly affected by regulation and result from two mechanisms.  First,
 reductions  in output at directly affected facilities  influence  activity and employment levels in linked
 industries (indirect effects).  Second, the losses in employment and employee earnings in both the directly
and indirectly affected facilities result in reduced personal consumption expenditures, which may further
affect employment levels  in the community (induced effects).  If the aggregate impacts, including both
primary and secondary employment effects, amount to an employment decline of greater than one percent
in an affected community, then community impacts are deemed significant.
   'MSAs are defined by the U.S. Office of Management and Budget.

                                             6.2

-------
        Estimating Primary Employment Impacts
       . As presented in Chapter 4, three measures of significant economic impacts atPFPR facilities were
evaluated:  facility closure, conversion of a PFPR product line, and compliance costs in excess of five
percent of facility revenue.  Employment losses corresponding to these impact measures are calculated
as follows.

        Facility Closure
        A facility closure is classified as a severe impact. For a projected facility closure, all employment
at the associated facility is assumed to be lost. The number of employees at a facility is calculated from
data provided in the PFPR Survey (Introduction, question 17). The number of employees is equal to the
sum of annual PFPR production worker hours, all other production worker hours, and all non-production
worker hours, divided by 2,000.2 Algebraically,
                                  EMP =
                           FPR  + OTH + NPR
                                   2,000
where:
EMP   =
FPR    =
OTH   =
NPR   =
total facility full-time-equivalent employment;
total annual worker hours attributable to PFPR production;
total annual worker hours attributable to other production; and
total annual non-production worker hours.
       Line Conversion
       EPA considers a line conversion to be a moderate impact.  In general, EPA expects that these
facilities  would  retain some or all of the employment previously associated with PFPR activities.
Production might shift to non-pesticide formulating, packaging, or repackaging activities or to pesticides
for which compliance is  less  costly.   In contrast, the community  impact analysis  takes a  more
conservative, worst-case assessment of the possible employment effects by assuming that the affected
facilities close their PFPR production lines entirely, with all associated employment assumed lost.
   2(50 weeks/year) X (40 hours/week) = 2,000 hours/year.

                                              6.3

-------
       Employment losses associated with 272 PAI-related PFPR3 product line closures are calculated
by adding PFPR production worker hours to the portion of non-production worker hours attributable to
PFPR production (from the Survey Introduction, question 17).  Non-production worker hours associated
with PFPR were not reported separately in the Survey. To estimate the non-production worker hours
associated with PFPR activities, non-production worker hours were allocated between PFPR activities and
non-PFPR activities in the same ratio as production worker hours:
                                                    FPR
                           PFPREMP -
                                         2,000
                                                             x NPR
                                 2,000
where:
PFPREMP
full time equivalent employment attributable to PFPR;
and the other variables are as defined above.
       Compliance Costs Equal to Five Percent or More of Facility Revenue
       Compliance costs equal to five percent or more of facility revenue are also considered by EPA
to be a moderate economic impact.  As discussed in Chapter 4, this impact measure is not associated with
an operational change.  Total annual compliance costs that are less than five percent of facility revenue
are commonly judged to be economically achievable, but compliance costs equal to five percent or more
of facility revenue do not necessarily indicate a significant impact.  Accordingly, for this analysis, no
employment loss is estimated to occur in conjunction with compliance costs that are at least five percent
of facility revenue.

       As a practical matter, the assumption that these facilities will incur no employment losses is of
little consequence to the analysis of community-level employment impacts.   Most facilities that are
projected  to incur moderate impacts fall in the possible line conversion category, and are therefore
assumed to lose all  PFPR employment  in the community impact analysis. Specifically, under Options
    3"PFPR employment" in this analysis refers to PFPR employment involving the 272 PAIs originally considered
for regulation.

                                              6.4

-------
2, 3, and 3/S, fewer than 10 percent of the projected moderate impacts result from compliance costs equal
to five percent or more of facility revenue.  As a result, at least 90 percent of the moderate impacts under
these options are associated with employment loss. Under Option 1, about 88 percent of the moderate
impacts are associated with employment loss.  Under Options 4 and 5, moderate impacts associated with
employment loss constitute 63 percent and 62 percent, respectively.

       Estimating Secondary Employment Impacts
       Secondary employment  impacts  are  estimated based on  multipliers that relate  a change in
employment in a directly affected industry to aggregate employment change including the employment
affects in:  (1) linked industries (indirect effects) and (2) consumer businesses whose employment is
affected by changes in the earnings and expenditures of the employees in  the directly and indirectly
affected industries (induced effects).  Even when based on highly unlikely, worst-case assumptions, the
primary employment losses estimated for the PFPR regulation are very small:  under Option 3/S, 355
full-time equivalent job losses are spread over 137 facilities nationally. Given the minimal character of
the expected primary losses nationally, EPA expected that aggregate  community-level  employment
impacts — that is, including both primary and secondary  impacts — would, in all likelihood, also be
minimal.

        For this  analysis, EPA used  a worst-case multiplier  scenario to confirm  that  aggregate
community-level employment impacts are not likely to be significant under Option 3/S. Specifically, EPA
used a single, worst-case multiplier that is likely to substantially overstate aggregate, community-level
effects.  This analysis is based on the  highest state-level multiplier for the relevant industry, and also
assumes that all of the employment losses associated with a sample facility impact and the facilities that
it represents in the underlying PFPR population occur in the location of the sample facility.  Even with
both of these relatively extreme assumptions, aggregate community-level impacts are estimated to be well
less than the one percent threshold of significance.
                                               6.5

-------
 6.2    Findings From the Community Impact Analysis
        As discussed in previous chapters, the main data source for this analysis is the PFPR industry
 Survey. National estimates of employment losses for each of the six regulatory options were calculated
 from the sample facility impacts and the sample weights applicable to those observations.  Table 6.1
 presents the estimates of national employment losses for each option and the number of facilities at which
 these job losses are expected to occur.  As summarized in the table, worst-case estimates of national job
 losses range from a high of 1,173 FTEs under  Option 5 to a low of 356 under the proposed option,
 Option 3/S.  The job losses are distributed over a large number of facilities, with an average job loss at
 any single impacted facility ranging from 2.4 FTEs (Option 1) to 6.2 FTEs (Option 4).

        To confirm that Option 3/S would not be expected to result in significant community employment
 impacts, EPA analyzed aggregate employment effects using two assumptions that are likely to overstate
 substantially the possible employment impacts in affected communities.  The first assumption involves
 the allocation of the employment losses estimated to occur in non-sample, impacted facilities — that is,
 the facilities  in the underlying PFPR facility population that are represented by the sample facilities for
 which impacts were assessed. As noted in the introduction, community impacts are considered significant
 if employment losses  are estimated to exceed  one percent of community employment.  If data are
 available for all facilities in an industry, such changes in MSA employment can be calculated for each
 facility and location for which a significant impact is assessed.  When the impact analysis is based on a
 sample of the total facilities in an industry, however, the assessment of facility impacts among sample
 observations applies only to the specific locations containing the affected sample facilities. To extrapolate
 the impacts from these sample facilities to the population of total facilities requires using sample weights
 that have been stratified along analytically relevant dimensions (e.g., states or communities for the
 community impact analysis).  The PFPR Survey  sample on which this analysis is based, however, was
 not stratified to provide statistically valid estimates along such dimensions.  It is therefore not possible
 to estimate the geographic distribution of national  employment losses at a regionally subaggregated level.

        Although a statistically valid analysis of population level employment impacts on a regional  or
 community level cannot be performed, analyses based on assumptions regarding the locational distribution
 of primary employment impacts can demonstrate that compliance with the proposed regulation  is unlikely
to have a significant impact on community employment.   Under Option 3/S,  115  FTE  losses are
 associated with the 26 sample facilities assessed as incurring economic impacts. Further,  these 115 FTEs

                                              6.6

-------
Table 6.1: Estimated National Employment Losses for Each Regulatory Option
Regulatory
Option
Option 1
Option 2
Option 3
Option 3/S
Option 4
Option 5
Number of Facilities
with Estimated
Employment Losses
179
171
171
137
180
191
FIE Loss due
to Facility
Closures
71
68
68
68
736
736
FTE Loss due
to Line
Conversions
366
358
358
287
377
437
Total
FTE
loss
437
426
426
356
1113
1173
: Average FTE
.•- , 'Loss per""/ '
Impacted
Facility
2.4
2.5
2.5
2.6
6.2
6.1
are distributed over 18 states and 22 MSAs (see Table 6.2). In addition to the 115 employment losses
in affected sample facilities, EPA projects an additional 241 employment losses  in 110 facilities in
unknown states and MSAs for a total of 356 job losses. These additional facility impacts and employment
losses are those that are estimated to occur in the PFPR facility population that is represented by sample
facilities.  It is these 241 FTE losses for which location of employment loss may not be specified for the
community impact analysis.

       For this analysis, EPA assigned these 241 employment losses that are not directly accounted for
by the affected sample observations to the known locations of the affected sample facilities in proportion
to sample facility weights.  Thus, all of the facilities that are represented by an affected sample facility,
and their associated employment loss, are assumed to be located in the same MSA as the affected sample
facility. This assumption regarding the locational distribution of facility  impacts is expected to overstate
employment losses in each MSA, because the non-sample facility  impacts would likely be distributed
among other MSAs that are unknown.                                                     .

       The second assumption involves the multiplier used to estimate the aggregate employment impacts
associated with the direct  employment  losses  in  impacted PFPR facilities.  Specifically, EPA used a
worst-case regional impact multiplier from the Regional Input-Output Modeling System developed by the
                                                                  i
Bureau of Economic Analysis (BEA) within the Department of Commerce.  BEA publishes state-level
                                             6.7

-------
Table 6.2: Analysis of Community Employment Impacts Assuming Worst-Case
Multiplier and Proportional Distribution of Sample- Weighted Employment Losses
State
CA
CA
CO
CT
FL
GA
IA
LA
MD
MN
MO
MO
OH
OR
PA
SC
TN
TN
TX
TX
UT
WA
Total
Primary Impacts Only
Estimated FTE
Loss in Sample
Facility MSA
1.9
0.2
0.7
3.8
0.0
0.1
0.1
0.1
0.4
37.2
56.9
1.5
3.7
0.7
2.7
0.8
1.1
0.4
0.3
1.9
0.3
0.1
114.8
Implicit
Sample-
Weight
5.0
4.9
1.2
4.9
7.2
4.9
5.0
7.2
4.0
4.9
1.2
4.9
5.1
4.9
7.3
7.2
4.9
4.9
5.7
4.0
7.2
7.2
3.1
Sample-
Weighted
FTE Loss
9.7
0.8
0.8
18.6
0.1
0.7
0.3
0.4
1.5
181.0
68.3
7.1
18.5
3.3
19.5
5.5
5.2
2.1
1.8
7.5
2.2
1.0
355.7
Primary and Secondary Impacts
Maximum
State
Multiplier
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2
9.2

Multiplier-
Adjusted
FTE Loss
89.1
7.0
7.4
171.2
0.9
6.6
2.3
3.4
13.5
1,665.2
628.8
65.4
170.6
30.1
179.0
50.7
47.5
18.9
16.9
68.8
19.8
9.3
3,272.5
Percent Loss
in
Employment
0.0020%
0.0006%
0.0028%
0.0403%
0.0006%
0.0004%
0.0010%
0.0006%
0.0011%
0.1181%
0.0738%
0.0051%
0.0217%
0.0044%
0.0180%
0.0148%
0.0100%
0.0035%
0.0023%
0.0656%
0.0039%
0.0008%

The community-level employment impact values presented in this table provide a worst-case
illustration of possible impacts in the MSAs in which those sample facilities assessed as incurring
economic impacts were located. The employment losses are likely to overstate substantially actual
impacts because of the use of a maximum employment impact multiplier and because impacts in
unspecified locations are assumed to occur in the same MSA in which the sample facility is located.
In fact, the unspecified facility employment impacts are likely to be distributed among these and other
unknown MSAs in a way that does not yield as high a concentration of impacts at the sample facility
locations as indicated in this analysis.
employment multipliers by industry classifications.  For this analysis, EPA used the highest state-level
employment multiplier applicable to the Chemical and Petroleum  Refining Industry, the 2-digit BEA
industry that is most likely to include facilities engaged in PFPR business. The highest total employment
                                              6.8

-------
impact multiplier reported by BEA is for the state  of Texas and has a value of 9.20.   Use of this
multiplier is likely to exaggerate possible secondary employment impacts for the following reasons:

«      Using:a state, as opposed to MSA, multiplier  is likely to overstate multiplier effects. The state-
       level multiplier registers the expected effect throughout the state resulting from changes in activity
       levels in the subject industry within the state.  To the extent that some of these effects occur in
       locations beyond the  MSA in which the primary impacts occur,  the state-level multiplier will
       exaggerate the employment impacts in the MSA.

•      The state multiplier value of 9.20 is the highest among those published for the relevant industry.
       By comparison, the average value of the state-level multipliers for this industry is 4.42 and the
       minimum value is 2.05.  Moreover, only 3  of the 26 sample facilities assessed as incurring
       impacts that could result in job losses are located in Texas. Using the Texas multiplier therefore
       exaggerates substantially the impacts that will occur in other states.
        Still, even with these highly unrealistic assumptions, the analysis shows that Option 3/S is
unlikely to result in significant employment impacts at the community level.  Specifically, the largest
weighted aggregate employment impact under this analysis is associated with an MSA in the state of
Minnesota.  The estimated sample facility-based employment loss in the MSA is 37.2 FTEs. The sample
weight associated with this facility is 4.9, meaning that, in the impact analysis, the facility represents
itself plus 3.9 other facilities in the underlying PFPR facility population whose locations may not be
estimated.   Applying the sample weight brings the primary employment impact to 181.0.  Further,
applying the industry impact multiplier for Texas  of 9.20 brings the weighted aggregate employment
impact to 1,665.2 full-time equivalent employment positions.  This unrealistically high value exceeds all
the other simulated MSA-level impacts by nearly a factor of three.  Although this value also yields the
highest percentage loss in MSA employment, at 0.1181 percent, it is still less than one-eighth of the one
percent significant impact threshold (see Table 6.2).  Moreover, if the employment impact for this MSA
is calculated on the basis of Minnesota's employment multiplier of 3.4 for the subject industry, the
calculated decrease in employment would amount to 615 full-time equivalent positions or a 0.0436 percent
employment loss.   In all likelihood, this value still substantially overstates the expected employment
impacts in the Minnesota MSA because the non-sample facility impacts, associated with the affected
facility's weight are assigned to the same MSA as the sample facility.
                                               6.9

-------
       The next highest percentage employment impacts are 0.0738 percent, in Missouri, and 0.0656
percent, in Texas, or approximately l/14th and l/15th of the one percent impact threshold, respectively.
Thus, even using highly unrealistic assumptions, this analysis finds that Option 3/S would not likely cause
a significant loss of employment in any affected MSA.

       From this analysis, EPA concludes that the proposed PFPR effluent guideline for Subcategory
C facilities, Option 3/S, should not impose a significant burden, as measured by loss of employment,
on any community.
                                             6.10

-------
                                   Chapter 6 References

Slater, Courtenay and Hall, George, (eds.) (1990).  1992 County and City Extra: Annual Metro, City
       and County Data Book.  Lanham, MD.

U.S. Department of Commerce (1990). Bureau of the Census, The 1990 Census of Population and
       Housing. Washington, D.C.

U.S. Department of Commerce (1992).  Bureau of Economic Analysis, Regional Multipliers: A User
       Handbook for the Regional Input-Output Modeling System (RIMSII).  Washington, D.C.

U.S. Department of Commerce (Feb 1987). National Bureau of Standards, The Federal Information
       Processing Standards Guide (PIPS Pub 55-2). Washington D.C.
                                           6.11

-------

-------
                                          Chapter 7
                                  Foreign Trade Impacts
7.0    Introduction
       Products  created by pesticide formulators,  packagers,  and repackagers  (PFPR)  are  traded
internationally. Changes in domestic PFPR production resulting from effluent regulations may therefore
affect the balance of trade.  This chapter considers  the potential impacts that compliance with PFPR
effluent limitation guidelines may have on foreign trade.

       Specifically, this chapter examines the changes in both exports and imports that could occur as
a result of a PSES regulation for Subcategory C (PFPR) Facilities.  Trade impacts are examined for the
six PSES options considered for Subcategory C (PFPR) Facilities, namely:  the five options initially
considered plus the proposed option, Option 3/S, which  is a modification of Option 3.   Among these
options, the estimated impacts of Option 3 and Option 3/S are examined more closely within the context
of the current international pesticide market.

       EPA analyzed foreign trade impacts under two cases: a proportional case, which assesses trade
impacts based on the relative competitiveness of U.S.  and foreign producers in international markets; and
a worst case, which makes  severely conservative assumptions regarding U.S. competitiveness.   Both
analyses showed relatively minor trade impacts from the proposed regulatory option, Option 3/S.  The
proportional case analysis indicated that the net trade balance would decrease about one percent under
Option 3/S,  or substantially less than the average year-to-year fluctuation in the U.S. pesticide  trade
balance.  The worst case analysis involved very conservative assumptions that  are likely to overstate
substantially the possible trade impacts, but serves to illustrate the minimal impact that the regulation is
expected to have on foreign trade even with these highly adverse assumptions. This analysis found that
the loss  in the net trade balance for pesticides under Option 3/S would not exceed five percent of the
average trade balance in pesticides over the period 1980-1990. Moreover, the calculated loss is less than
the average year-to-year change in the pesticides trade balance over this period. For these reasons, EPA
expects that the  proposed Option 3/S will  not significantly impair  the international trade position  in
pesticides.
                                               7.1

-------
        The following sections of this chapter report the analysis on  which this conclusion is based.
Section 7.1 describes the methodology used to estimate possible changes in exports and imports resulting
from the regulatory options.  Section 7.2 summarizes the findings of that analysis, and  Section 7.3
assesses the significance of those findings for Option 3 and the proposed option, Option 3/S.

7.1     Methodology for Assessing Foreign Trade Impacts
        Compliance with effluent limitation guidelines may affect the U.S. trade balance for pesticide
products by reducing exports and increasing imports. Exports may decline because previously exported
products are no longer produced, or because production costs and sales prices for domestic producers are
increased, thus making domestic products less competitive in foreign markets.  Imports may increase as
domestic purchasers seek new sources of PFPR products that are no longer offered by affected facilities
or that are offered at higher prices.

        This analysis focuses on the possible change in exports and imports associated with reductions
in output in facilities that may be adversely affected by the PFPR rule.  These decreases in  exports and
increases in imports are derived from facilities that (1) were assessed as a closure or (2) were assessed
as a product line conversion. Facilities falling in the third impact category — compliance costs exceeding
five percent of facility revenue — are not expected to lose PFPR production and were not considered in
this analysis.  Facilities that cease or reduce PFPR production may affect the pesticides trade balance in
two ways:

        First, their former export sales may be lost, all or in part, to foreign producers thereby reducing
        total domestic exports of pesticide products. The impact on the trade balance will depend on the
        success of other domestic producers in retaining the export markets formerly served  by facilities
        whose PFPR production declines or ceases as a result of regulation.

        Second, their former sales  for domestic consumption may  be lost, all or in part, to imports
        thereby increasing total imports of pesticide products.  Again, the impact on the trade balance
        will depend on the success of other domestic producers in retaining those domestic sales markets
        and preventing import sales from capturing them.
                                              7.2

-------
        For both effects, foreign and remaining domestic PFPR producers are assumed to compete for
the former domestic and export sales markets of those facilities whose PFPR production is lost as a result
of regulation. The outcome of the competition between foreign and domestic producers determines the
change in the two components of the trade balance:  exports and imports. The combination of these two
changes — that is, increased imports plus the loss in exports — yields the decline in the net trade balance
for pesticide products.  The two foreign trade analyses presented  in this chapter involve different
assumptions regarding the outcome of the competition between foreign and domestic producers.   In the
proportional  case analysis,  EPA  assumed  that domestic  producers  would  remain as competitive in
domestic and export sales markets at the margin as they are currently, and therefore would maintain a
portion of the  markets  lost  by  impacted facilities.   In the worst case  analysis, EPA  made the
unrealistically severe assumption that foreign producers would fully capture both the former export and
domestic sales of facilities whose PFPR production declines or ceases as a  result of regulation.  The
results of these analyses were then examined relative to the average U.S. pesticide trade balance and the
fluctuations that exist within this market.

       The Survey provides data on the composition of sales for impacted facilities, including total 272
PAI-related PFPR  revenue and the percent  of PFPR  revenues attributable to  exports (in  1988).1
Facilities that are assessed as closures are assumed to cease producing all PFPR products.  In addition,
facilities assessed as incurring a product-line conversion are also assumed to cease production of all PFPR
products.   In some instances, facilities considering a  product-line conversion may find it financially
advantageous to continue PFPR activities.  However, because product-specific revenue  and financial
performance  data are not available,  such product-line comparisons were not possible and the analysis
conservatively assumes that a line conversion means that all PFPR production at the facility ceases.  This
assumption is expected to overstate impacts.

       Although the analysis does not consider the possible change in exports or imports resulting from
product price increases, highly conservative assumptions, particularly in the worst-case analysis, underlie
the calculation of net  trade effects stemming from  output changes in affected  facilities.  Thus, EPA
    1 For this analysis, "PFPR revenues" refers to revenues from PFPR activities involving the 272 PAIs originally
studied for regulation. One impacted facility did not provide a percent of PFPR revenue attributable to exports;
for this facility, the weighted average of all facilities regulated under PSES was used.
                                               7.3

-------
believes that the assessed trade effects, even without price increases as a variable, provide a conservative
assessment of the potential trade impacts of the proposed regulation.

       Trade Impacts Under Proportional Case Assumptions
       In this analysis, domestic  and foreign producers are assumed to compete for the domestic and
export sales of facilities that cease PFPR production as a result of the effluent guideline.  Domestic and
foreign producers share  in the market  on a proportional  basis that  corresponds to  their average
participation in domestic and export markets before regulation. The shares of these markets that are won
by foreign producers reflect the long-run success of foreign  and  domestic producers in competing for
domestic and export markets.

       Estimating Change in Exports
       When a facility ceases PFPR production, the markets that it served, both domestic and export,
are assumed to  be competed for by other domestic producers and foreign producers.   Under  the
proportional  case it is assumed that domestic producers  capture the same share  of the lost  export
production as the average  share  of exports to total domestic production.   In other  words,  domestic
producers are assumed to be approximately as competitive at the margin in recovering lost exports as they
are on average in achieving export sales out of total production.  On the basis of export and  domestic
shipments  data for  the 1988-1992 period, the share of pesticide exports expected to be  captured by
domestic producers is 30.2 percent.2 Foreign producers are thus assumed  to capture 69.8 percent of
the former exports from significantly impacted facilities.
        The calculation is as follows:
                         EXPDECR; =  %EXPt x FPRREV. x (1  -
 Where:
 EXPDECR;
 %EXP;
The calculated decrease in facility export revenue in 1988 dollars;
The percent of PFPR revenue that a facility earned from exports in 1988; and
    2 Based upon 1988-1992, the only years for which these data were available. (Source: The International Trade
                                              7.4

-------
FPRREV;
EXP/TDP
The three-year (1986-1988) average facility revenue from PFPR activities in 1988
dollars.
The  average ratio  of Exports to  Total Domestic  Production  for  pesticide
chemicals (30.2 percent)
       Estimating Change in Imports
       The decline in PFPR production due to compliance may result in increased imports as foreign
producers acquire a share of the domestic  market formerly served by  an  impacted facility.  In the
proportional case, the former sales for domestic consumption are assumed to be split between domestic
and foreign producers based on the average ratio of imports to total domestic consumption.  That is,
foreign producers would be approximately as competitive on the margin  as they have been historically
in gaining a share of the U.S.  market for PFPR products. From data for the 1988-1992 period, foreign
producers are assumed to capture 17.9 percent of the domestic market  formerly served by impacted
facilities.3  Domestic producers are therefore assumed to retain 82.1 percent of this market.
       The calculation is as follows:
                    IMPINCRt = [FPRREVi - (%EXPt x FPRREV)] x
                                                IMP
                                                TDC
 Where:
 IMPINCRj
 FPRREV
 IMP/TDC
 The annual increase in PFPR imports in 1988 dollars;
 The three-year (1986-1988) average facility revenue from PFPR activities in 1988
 dollars;
 The percent of PFPR revenue that a facility earned from exports in 1988;
 The average ratio of Imports to Total Domestic Consumption (17.9 percent)
    3 Based upon 1988-1992 data, the only years for which these data were available.  (Source:  The International
 Trade Commission).
                                              7.5

-------
        Estimating the Change in Net Trade Balance
        The deterioration in  the  net trade balance for pesticide products  is calculated by adding the
 increase in imports and the reduction in exports (expressed as a positive value).  The resulting value is
 the net loss in the domestic trade balance for pesticide products.

        Trade Impacts Under Worst-Case Assumptions
        Under  the  worst-case assumptions, foreign producers are  assumed to win completely the
 competition for the former export and domestic sales markets of impacted facilities.  That is, the sales
 for domestic consumption are fully  replaced by increased imports and the sales for export are fully
 replaced by foreign producers. These assumptions maximize the possible adverse trade impact associated
 with reduced production and sales of PFPR products by significantly impacted facilities.

        Estimating Change in Exports
        In the worst-case analysis, all PFPR production previously exported  by impacted facilities is
 assumed to be lost to foreign producers.  This  is a worst-case assumption because it does not allow for
 other U.S. facilities to acquire a portion of the affected facilities' export sales. The calculated decline
 in exports is therefore expected to overstate the actual change that would result from compliance. The
 calculation is as follows:

                                EXPDECRt = %EXP. x  FPRREVf
Where:
EXPDECRj
%EXPj
FPRREV:
The calculated decrease in facility export revenue in 1988 dollars;
The percent of PFPR revenue that a facility earned from exports in 1988; and
The three-year (1986-1988) average facility revenue from PFPR activities in 1988
dollars.
       The total decrease in U.S. exports of pesticide products resulting from compliance is calculated
by summing the sample-weighted losses in facility exports over all affected facilities.
                                              7.6

-------
       Estimating Change in Imports
       In the worst-case analysis, all of the former sales for domestic consumption in impacted facilities
is assumed to be replaced by imports.  This assumption is highly conservative in that it does not allow
for domestic producers  to replace any of the lost domestic sales.  In all likelihood,  this assumption
provides an even greater exaggeration of the potential trade impacts of the PFPR regulation than that
applied to exports.  This greater exaggeration results from both the larger quantity of product affected
(i.e., domestic sales by affected facilities generally exceed their exports) and the extreme improbability
that imports would displace all of the former domestic sales of affected facilities. The  calculation is as
follows:
                         IMPINGR;  = FPRSEVi - (%EXP. x FPRREV)
Where:
IMPINCRj
FPRREV;

%EXP:
The annual increase in PFPR imports in 1988 dollars;
The three-year (1986-1988) average facility revenue from PFPR activities in 1988
dollars; and
The percent of PFPR revenue that a facility earned from exports in 1988.
       The total increase in pesticide product imports resulting from compliance  is calculated by
summing the sample-weighted import increases over all affected facilities.

       Estimating the Change in Net Trade Balance
       Again, adding the increase in imports and the reduction in exports (expressed as a positive value)
yields the net loss in the domestic trade balance for pesticide products.

7.2    Estimated Changes in Pesticide Exports and Imports Under Worst-Case and Proportional
       Case Assumptions
       The findings from the analyses outlined above are summarized below.
       Proportional Case Assumptions
       Using the methodology outlined above, EPA calculated possible changes in the exports and
imports of pesticide products resulting from the PSES regulations applicable to Subcategory C (PFPR)
                                             7.7

-------
facilities.  Under the proportional case assumptions, the decrease in exports is expected to range from
$2,685,000 per year under Options 2, 3, and 3/S to $6,256,000 under Options 4 and 5.  The increase
in imports is expected to range from $6,505,000 under Option 3/S to $35,660,000 under Option 5.  The
resulting estimated annual decrease in the Net Trade Balance ranges from $9,190,000 under Option 3/S
to $41,916,000 under Option 5.  Option 3/S, the proposed option, results in the lowest projected decline
in trade balance among all of the regulatory options considered (see Table 7.1).

       Worst-Case Assumptions
       Under the worst-case assumptions, the annual reductions in PFPR exports range from $3,846,000
under Options 2, 3, and 3/S to $8,963,000 under Options 4 and 5. Increases in PFPR imports range
from $36,338,000 per year under Option 3/S to $199,219,000 per year under Option 5.  The resulting
decline in the PFPR trade balance ranges from $40,184,000 per year under Option 3/S to $208,182,000
per year under Option 5.  Overall, the deterioration  in the net trade balance under the worst-case
assumptions is about 4.5 to 5 times as great as the impact amount calculated under the proportional case
assumptions.  Option 3/S, the proposed regulatory option, achieves the lowest deterioration in the net
trade balance among the regulatory options considered (see Table 7.1).

7.3     Significance of the Estimated Decreases in the Net Trade Balance
        EPA assessed the significance of these trade impact findings for Options  3 and 3/S.

       Proportional Case Assumptions
        To assess the significance of the calculated change in the net trade balance, the calculated values
for Options 3  and 3/S were  considered  in the context of the international  pesticide  market.   Two
comparisons illustrate the significance of the calculated changes in the international trade balance.  First,
EPA compared the calculated change in the net trade balance with the actual trade balance values for
pesticides over the period  1980-1990.  As summarized in Table 7.2, the net trade balance for the period
 1980-1990 averaged approximately $950 million.  Under Option 3, the decline in the net trade balance
would constitute a 1.04 percent decrease in the pesticide trade balance.  Under Option 3/S, the proposed
regulatory option, the estimated decline in the pesticides trade balance would be less than one percent.
        As a second measure of the significance of the calculated losses in the pesticide trade balance,
 EPA compared  the percentage change in the average trade balance implied by the Options 3 and 3/S
                                              7.8

-------
Table 7.1 Change in Foreign Trade Balance for Subcategory C PSES Options
($000, 1988)
Regulatory
Option
Option 1
Option 2
Option 3
Option 3/S
Option 4
Option 5
Proportional Case Assumptions
Increase in
Imports
7,188
7,187
7,187
6,505
34,824
35,660
Decrease in
Exports
2,841
2,685
2,685
2,685
6,256
6,256
Decrease in
Trade Balance
10,029
9,872
9,872
9,190
41,080
41,916
Worst-Case Assumptions
Increase in
Imports
40,155
40,149
40,149
36,338
194,548
199,219
Decrease in
Exports
4,070
3,846
3,846
3,846
8,963
8,963
Decrease in
Trade Balance
44,225
43,995
43,995
40,184
203,511
208,182
calculations with the actual year-to-year percentage changes in the trade balance that occurred over the
ten-year analysis period. Between 1980 and 1990, the pesticide trade balance fluctuated between a low
of $841 million and a high of $1,143 million.  The year-to-year swings were  quite wide:  six years
showed negative changes over this period ranging from -1.9 percent to  -21.3 percent; and four years
showed positive changes ranging from 1.7 percent to  19.7 percent.  One measure of trade balance
volatility is the average of the absolute value of these  year-to-year percentage changes,  which is 8.0
percent.  That is,  on a year-to-year basis, and without regard to the direction of change, the average
change in  the net trade balance  for the period 1980-1990 was 8.0 percent.  As reported above, the
implied declines in the average net trade balance calculated for Options 3 and 3/S are  1.04 percent and
0.97  percent, respectively.  Both  values are considerably smaller than the  8.0 percent year-to-year
fluctuation in the pesticides net trade as observed in recent years (see Table 7.2).

        Worst-Case Assumptions
        Under the worst-case assumptions, the estimated decrease in the net trade balance in the pesticide
 industry is more significant than that projected under the proportional case assumptions. However, even
these highly unrealistic, worst-case estimates indicate that trade impacts  should not be unduly burdensome
 when viewed in the context of the U.S. trade balance for pesticides. The conservatively calculated loss
 in the trade balance of $44 million for Option 3 amounts to 4.6 percent of the ten-year average value of
 $950 million.  The $40 million loss calculated for Option 3/S represents only 4.2 percent of the ten-year
 average.   Although these values  are higher as a percentage of the  10-year average trade balance than
                                                7.9

-------
Table 7.2: U.S. Trade Balance in the Pesticide Market, 1980 -1990
Year
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
Average
Trade Balance
($000,000, 1988)
1,075
935
914
955
1,143
900
943
959
940
857
841
951
Percent Change

-13.0%
-2.2%
4.5%
19.7%
-21.3%
4.8%
1.7%
-2.0%
-8.8%
-1.9%

Absolute Percent
Change

13.0%
2.2%
4.5%
19.7%
21.3%
4.8%
1.7%
2.0%
8.8%
1.9%
8.0%
Source: United Nations International Trade Statistics Yearbook, 1980-1990.
those calculated for the proportional case analysis, they still remain well below the average 8.0 percent
year-to-year fluctuation observed over the past 10 years.

       Taking into account the small effect of the calculated trade balance impacts relative to the existing
pesticides trade balance under both the worst-case assumptions and the more realistic proportional case
assumptions, EPA judges that Options 3 and 3/S would not be expected to impose a significant impact
                                                        \
on the U.S. pesticides trade balance.
                                              7.10

-------
                                     Chapter 7 References




Economic Report of The President (1993).  Washington, D.C.




International Trade Commission, (Telephone Interview 2/2/94). Washington, D.C.




United Nations (1980-1990). Statistical Office. International Trade Statistics yearbook.  New York.
                                             7.11

-------

-------
                                          Chapters
                           Assessment of Firm-Level Impacts

8.0    Introduction
       The assessment of economic achievability of the PFPR regulation is based  primarily on the
facility-level impact analysis. EPA, however, also conducted a firm-level analysis, as impacts at the level
of the firm may exceed facility level impacts, particularly when a firm owns more than one facility that
will be subject to regulation. This chapter examines the impact of compliance with the proposed options,
Option 3/S for Subcategory C  facilities and Option 1 for Subcategory E facilities,  on firms owning
facilities subject to PFPR effluent guidelines. All firms that own at least one sample facility using water
in its PFPR operations are included in the analysis.1  The analysis involves aggregating financial and
compliance cost data for sample facilities by firm, and imputing compliance costs for non-sample facilities
owned by the firm based on sample facility compliance costs  and firm PFPR revenue not attributable to
sample facilities.   This  analysis also considers baseline  cost  adjustments  from  other  regulatory
requirements for both sample and non-sample facilities owned by the firm.  Because of sample design
considerations, the findings from the firm-level analysis, which is based on facilities in the sample survey,
cannot be extrapolated on a statistically valid basis to the population level of PFPR industry firms.

       Firm-level impacts are  evaluated based on estimated post-compliance pre-tax return on assets
(ROA) relative to a threshold ROA based on current industry performance.  Pre-tax ROA is a measure
of the profitability of a firm's capital assets, independent of the effects of taxes.  This financial measure
provides  information  regarding the competitive position of the firm within the industry, as well as
operating  margin and asset management capability.  If a firm cannot sustain a competitive ROA when
baseline costs and compliance costs are considered, then the firm will likely have difficulty financing the
capital outlays for complying with the regulation.

       After grouping sample facilities by owning firm, EPA initially considered 308 firms that own at
least one water using  sample facility.  However, 66 of these firms were found to have a baseline ROA
    1 Facilities which do not use water in their PFPR operations were not required to indicate percent of firm
revenue attributable to PFPR operations in 1988, making this analysis impossible for firms represented in the sample
by only facilities which do not use water in their PFPR operations.

                                               8.1

-------
of less than the threshold level, and therefore were not considered for impacts from compliance with the
regulatory option. The remaining 242 firms were analyzed for impacts.

        From this analysis, EPA found that only 5 of the 242 firms analyzed would be expected to incur
significant financial impacts as a result of the proposed PFPR regulations. The Agency judges that these
firm-level impacts should not pose a significant burden to the PFPR industry.

        The remaining sections of this  chapter  are organized as follows.  Section 8.1 presents the
methodology for calculating  baseline and post-compliance ROA for the 242 firms, and Section 8.2
summarizes the projected firm-level economic impacts.

8.1     Methodology for Assessing Firm-Level  Impacts
        The assessment of firm-level impacts involves two separate analyses.  First, EPA assessed firm-
level financial performance in the baseline, or before application of the PFPR regulatory requirements.
Firms that were found financially weak in this analysis were excluded from the second analysis.  In the
second  analysis,  firm-level financial  performance was  assessed taking  into account PFPR regulatory
requirements.

        Analysis  1: Baseline Analysis of Firm-Level Financial Performance
        The baseline analysis evaluates each firm's financial operating condition before  considering the
compliance costs of the PFPR regulation. This analysis identifies firms that are expected to be financially
weak relative to the overall industry independent of regulatory requirements.  Firms that have a baseline
ROA less than the threshold value are not considered for compliance impacts because their  financial
weakness results from current circumstances.
       The analysis of firm-level impacts is based on pre-tax ROA, which is defined as pre-tax income
or earnings before taxes (EBT) divided by total firm assets. In the facility-level impact analysis, pre-tax
ROA was calculated at the facility level using data from the  PFPR industry Survey.  In the firm-level
analysis, however, the relevant income statement and balance sheet data for calculating pre-tax ROA
necessarily are from  firm-level  financial  statements.  EPA  first  assembled  the  necessary financial
statement data for calculating pre-tax ROA for the year 1988. EPA then adjusted these data to reflect
ongoing environmental regulatory compliance requirements as previously described in the facility-level
                                              8.2

-------
analysis. The ROA with baseline adjustments was then compared to the industry threshold to evaluate
financial performance on a pre-compliance basis.  The steps in this analysis are summarized below.

       Assembling Facilities  by  Common Firm Ownership and  Obtaining Data for  Calculating
        Unadjusted ROA
       In the same  way as discussed for the  analysis  of small  business impacts (Chapter 5), EPA
identified the ownership of facilities in the PFPR industry Survey and grouped facilities by firm for
performing the firm-level analysis.  All firms with at least one water-using facility in the Survey were
considered for the analysis of firm-level impacts. From this grouping, EPA identified 308 firms.  These
firms fell in three general categories that are relevant for understanding the data sources and development
of the unadjusted baseline ROA for the analysis:

        1.      Public-reporting firms.  After grouping facilities, EPA found that 97 of the sample
               facilities (92 of which use water in their PFPR operations) were owned by 36 public-
               reporting firms. Firm-level financial data to calculate the unadjusted ROA for these
               firms were obtained from annual reports or Standard and Poor's S&P Reports.

        2.      Private  single-facility firms.  From Survey data, EPA found that 180 facilities were
               private (i.e., non-public-reporting), single-facility firms.  In the Survey, these facilities
               reported being single-facility firms and also reported firm-level revenues equal to facility-
               level revenues. Total firm assets for 1988 was taken directly from the PFPR Survey, and
               EBT was calculated using facility-level income statement data  from the Survey2.

        3.      Multiple facility private firms. The remaining 129 facilities (127 of which use water in
               their PFPR operations) were grouped into 92 multiple facility private firms.  Because the
               needed  EBT and  assets data were unavailable for  these firms,  EPA  estimated the
               unadjusted values using industry-wide ratios developed from the Robert Morris Associates
               (RMA)  publication Annual Statement Studies.  Specifically, EPA calculated an industry
               aggregate sales-to-assets ratio and pre-tax profit as a percentage of total sales  for use in
               imputing a firm-level, unadjusted ROA for these firms.  The 1988 median ratio of sales
    2 EBT = Total Facility Revenue - Total Costs and Expenses + Taxes.
                                              8.3

-------
               to assets was averaged over all RMA-reported industries in SIC code 28 (Chemicals and
               Allied Products), weighted by total  value of shipments within each SIC code.3  The
               inverse of this value, or the assets-to-sales ratio (calculated as 48.20), was then multiplied
               by the 1988 firm revenues reported  in the Survey to yield 1988 total  firm assets, the
               denominator for the firm-level pre-tax ROA calculation.

               EBT was calculated in the same manner using the weighted average of the RMA median
               1988  value for pre-tax profit as a percent of sales.  The resulting  weighted average
               (4.9187 percent) was multiplied by 1988 firm revenue to yield  1988 EBT, the numerator
               for the firm-level pre-tax ROA calculation.

               This method of imputing an unadjusted ROA means that all multiple facility, non-public-
               reporting firms start with the same unadjusted baseline ROA of 10.2 percent.  However,
               the baseline adjustments for ongoing compliance requirements reduce this value for all
               firms  by varying amounts so that the adjusted ROA varies by  firm.

       Adjusting Baseline ROA for Ongoing Compliance Costs
       The estimation of baseline ROA  at the firm level is analogous to the  calculation of the facility
level baseline ROA described in Chapter 4. As in the facility level calculation, environmental compliance
costs expected to be incurred by firms after the survey was submitted (1988) were included in the baseline
analysis. These include costs from:

        1.      Resource Conservation and Recovery Act (RCRA) land disposal restrictions;

       2.      Effluent limitations for the Pesticide Manufacturing Industry, which  consists  of a) the
               total annualized  cost of compliance with  the rule (including capital and operating and
               maintenance costs), and b) pesticide active ingredient (PAI)  price increases  to PFPR
               facilities as a result of the rule;
   3 1992 total shipments data were used, as 1988 data were not available for all relevant SIC codes.  (Source:
1992 U.S. Industrial Outlook). The resulting weighted average sales-to-assets ratio was 0.020745.

                                              8.4

-------
        3.      Effluent limitations for the Organic Chemicals,  Plastics and Synthetic Fibers (OCPSF)
               industry; and

        4.      The annual product maintenance fees mandated by the 1988 amendments to the Federal
               Insecticide, Fungicide, and Rodenticide Act (FIFRA).

        All PFPR facilities are expected to incur costs from FIFRA and PAI price increases resulting
from the Pesticide Manufacturers rule. Half of these costs are expected to be borne by the facility, and
the other half is expected to be recovered through product price increases (see Chapter 4).  Only facilities
that manufacture PAIs are expected to incur costs from RCRA, OCPSF, and the cost of complying with
the Pesticide Manufacturers effluent guidelines rule.  As in the facility level analysis, EPA expects that
half of the RCRA and OCPSF costs will be borne by the facility, while the other half is passed on to
consumers through higher PAI prices.  The portion of the total annual costs of compliance with  the
Pesticide Manufacturers rule that is borne by the facility is calculated in the same manner'as documented
in the EIA for the Pesticide Manufacturers effluent limitations guideline.4

        The adjustments to firm-level baseline ROA account for additional environmental compliance
costs for both PFPR facilities included in the Survey and PFPR facilities owned by a firm but that were
not included in the sample.  The  estimation of costs for these non-sample facilities is based on  the
estimated firm revenue from  PFPR activities that is not accounted for by the sample facilities.  These
non-sample facilities are expected to incur baseline costs associated only with the FIFRA regulation and
PAI price increases resulting from the Pesticide Manufacturers  effluent guideline.  The other baseline
costs pertain only to manufacturing facilities, all of which  are included in the sample if they also engage
in PFPR activities.  Thus, the non-sample PFPR facilities are by definition not manufacturers and  are
therefore not subject to the other baseline costs.

        In addition, some firms included in the analysis own pesticide manufacturing facilities that do  not
engage in PFPR activities, and were therefore excluded from the PFPR industry Survey.  However,  the
identity and ownership of these facilities is known from the analyses that EPA performed for the Pesticide
Manufacturers effluent guideline. The costs of the above rules that apply specifically to manufacturing
   4 For details, see Chapter 4 of the Manufacturer's EIA.

                                              8.5

-------
facilities (i.e., OCPSF, RCRA, and the annualized cost of compliance with the Pesticide Manufacturers
effluent guidelines) are included in the adjustments to baseline values for firms owning such facilities.5
       Pre-tax ROA, baseline with adjustments, is calculated as follows:
                 ROABL =
                          EBT - COSTSAMPBL  - COSTMFGBL - OTHCOST,
                                             EL
                                         ASSET + OCPSFcap
Where:
ROABL
EBT
COSTSAMPBL

COSTMFGBL

OTHCOSTBL

ASSET
OCPSFcap
Firm, pre-tax ROA, baseline with adjustments, in 1988;
Unadjusted pre-tax firm earnings in 1988;
Annual baseline costs attributable to all sample facilities owned by the
firm;
Annual baseline costs attributable to facilities owned by the firm which
manufacture PAIs but do not PFPR;
Annual baseline  costs attributable to facilities which PFPR, and are
owned by the firm but not included in the sample;
Unadjusted firm assets in 1988; and
The sum  of capital costs resulting from the OCPSF rule for all facilities
owned by the firm.
       The calculation of each of the adjustments to baseline ROA is discussed more fully below.

       COSTSAMPBL, is the sum of annual baseline costs for sample facilities owned by the firm.  As
previously mentioned, only facilities that manufacture PAIs are subject to baseline costs for RCRA,
OCPSF, and MFGCOMP.  Therefore, the costs of these regulations apply only to sample facilities that
also manufacture PAIs. The calculation is as follows:
     Data for these costs are from the Pesticide Manufacturers' EIA, 1992.

                                             8.6

-------
COSTSAMPBL = £ (RCRA(
               1=1
               +
                                             ,. + MFGPAIi + FIFRA^ MFGCOMPJ
Where :
COSTSAMPBL  =  Baseline additional costs for PFPR facilities owned by the firm and in the Survey;
RCRA         =  Annual costs of RCRA regulation borne by facility i;
OCPSF        =  Annual costs of OCPSF regulation borne by facility i;
MFGPAI       =  Annual cost of PAI price increases from Pesticide Manufacturers regulation borne
                  by facility i;
MFGCOMP    =  Annual costs of compliance with the Pesticide Manufacturers effluent guidelines for
                  facility i; and
FIFRA         =  Annual costs of FIFRA regulation borne by facility i; and
nj             =  The number of PFPR facilities in the Survey owned by the firm.

Each of these cost elements  was calculated as part of the facility-level impact analysis documented in
Chapter 4.

       COSTMFGBL is the sum of annual baseline costs for non-PFPR facilities that manufacture PAIs.
These facilities were not included in the PFPR Survey but were analyzed for the Pesticide Manufacturers
rule.  Because these facilities are neither subject to the FIFRA regulation, which applies only to final
products, nor to the higher PAI prices from the Pesticide Manufacturers rule, these cost elements are
excluded from COSTMFGBL.  The remaining cost elements were taken from EPA calculations for the
Pesticide Manufacturers rule. The calculation is as follows:
COSTMFG
                               BL
                                                OCPSF t + MFGCOMP)
 Where :
 COSTMFGBL   =  Baseline additional costs for non-PFPR facilities owned by the firm that manufacture
                                                                i
                   PAIs;
                                            8.7

-------
 RCRA
 OCPSF
 MFGCOMP

 n2
=  Annual costs of RCRA regulation borne by manufacturing facility i;
=  Annual costs of OCPSF regulation borne by manufacturing facility i;
=  Annual costs of compliance with the Pesticide Manufacturers effluent guidelines for
    manufacturing facility i; and
=  The number of non-PFPR manufacturing facilities owned by the firm.
        OTHCOSTBL is the additional baseline costs that the firm is expected to incur from non-sample
facilities engaged in PFPR  activities.  Only costs associated with FIFRA and PAI price increases from
the Pesticide Manufacturers rule are considered in the calculation, as these are the only baseline costs that
the non-sample facilities are expected to incur, as  explained above.  To  estimate these  costs, EPA
extrapolated the baseline cost adjustments that were  estimated for each firm's facilities that are in the
Survey to the calculated PFPR revenue of the firm that was not covered by the Survey (this amount is
referred to as  PFPR residual revenue).  This calculation assumes that, within a firm, the additions to
baseline cost per dollar of residual PFPR revenue are the same as the addition to baseline costs per dollar
of PFPR revenue calculated for the firm's facilities in the sample.
       To calculate OTHCOSTBL, EPA first calculated each firm's PFPR revenue that is not represented
by facilities in the Survey by subtracting the sum of PFPR revenue for each  sample facility from the
reported total PFPR revenue of the firm. EPA also calculated for each firm the amount of the baseline
cost adjustments per dollar of PFPR revenue for the facilities in the Survey. This ratio of additional costs
to PFPR revenue was then multiplied by PFPR residual revenue to yield the estimated amount of baseline
cost adjustments from each  firm's PFPR facilities that are not  in the  Survey.   The formula for the
calculation is as follows:
                OTHCOSTBL  =
Where:
OTHCOSTBL    =  Baseline additional costs that the firm is expected to incur from non-sample PFPR
                   facilities;
FPRREV        =:  Reported 1988 revenues from PFPR for facility i;
                                             8.8

-------
FRMPFPR
MFGPAI

FIFRA
=  Expected firm revenues from PFPR in 1988;6
=  Annual cost of PAI price increases from Pesticide Manufacturers regulation borne
   by facility i;
=  Annual costs of FIFRA regulation borne by facility i; and
=  The number of PFPR facilities in the Survey owned by the firm.
       The last adjustment needed to calculate firm-level pre-tax ROA in baseline is OCPSFcap, the sum
of capital costs associated with the OCPSF rule.  This value is added to the total assets value in the
denominator of the ROA calculation and pertains only to facilities that manufacture PAIs as explained
above. The calculation is as follows:
                                      =£ OCPSFcap^ OCPSFcapi
                                       i=l             i=l
Where:
OCPSFcap
ni
=  Capital costs of complying with the OCPSF rule for manufacturing facility i;
=  The number of PFPR facilities in the Survey owned by the firm; and
=  The number of non-PFPR manufacturing facilities owned by the firm.
        Comparing Adjusted Baseline ROA with the Industry Threshold
        After applying each of the adjustments to baseline values as described above, EPA compared the
adjusted ROA  to  an industry threshold value to assess the  financial performance of firms before
consideration of PFPR regulatory requirements. EPA calculated the industry ROA threshold using pre-
tax ROA data from Robert Morris Associates (RMA) for 1988.  Specifically, EPA calculated the average
pre-tax ROA for the lowest-quartile among respondents for all RMA-reported industries in SIC code 28.
In computing the average, EPA weighted the lowest-quartile ROA reported for each industry group by
the total value of shipments for that SIC code as reported in the 1987 Census of Manufacturers.  The
resulting threshold ROA is 2.4 percent.
    6 Calculated by multiplying 1988 firm revenues by percent of firm revenue attributable to PFPR in 1988, as
 reported in the Survey. If facilities owned by the same firm reported different percentages, EPA conservatively
 used the highest reported percentage of firm revenue attributed to PFPR activities.  Similarly, if facilities owned
 by the same firm reported different firm revenues, the highest reported firm revenue was used.

                                              8.9

-------
         EPA compared both the unadjusted and adjusted pre-tax ROA values for each of the 308 firms
 in the baseline analysis to the threshold ROA value. Of these 308 firms, 63 firms, all of which are non-
 public-reporting, single facility firms, have an ROA of less than 2.4 percent before including the baseline
 cost adjustments  described above.   When  the baseline cost  adjustments are included in the  ROA
 calculation,  3  additional firms fell below  the ROA threshold level.  These 66  firms are assessed as
 experiencing financial weakness independent of the proposed effluent guidelines.  Accordingly, attributing
 their economic hardships to the regulation would overstate impacts. These 66 firms with a baseline ROA
 of less than 2.4 percent were excluded from the remainder of the firm-level analysis.

        Analysis 2: Post-Compliance Analysis of Firm-Level Financial Performance
        The post-compliance economic analysis evaluates each firm's financial operating condition taking
 into account  the costs of complying with  the proposed regulatory options. EPA analyzed the firm-level
 impact of the proposed regulatory options, Option 3/S for Subcategory  C facilities and Option  1 for
 refilling establishments7, based on the change in pre-tax ROA.  The post-compliance ROA includes both
 the baseline cost adjustments described above and the costs of compliance under the proposed options.
 If, as a result of the estimated costs of complying with  the PFPR regulation, a  firm's pre-tax ROA fell
 below the 2.4 percent threshold, then the firm was assessed as incurring a financial burden as a result
 of the proposed PFPR regulation.

       The estimation of post-compliance ROA is analogous to the calculation of the facility-level post-
 compliance ROA described in Chapter 4: that is, it takes account of the estimated costs of complying
 with the  proposed  PFPR regulation. Like tine firm-level baseline ROA analysis,  however, the firm-level
 post-compliance analysis accounts for costs that the firm is expected to incur from non-sample PFPR
facilities owned by the firm. Lacking information on these facilities, EPA again  estimated the additional
 compliance costs to the firm associated with non-sample PFPR facilities based on the calculated residual
 PFPR revenue (i.e., the firm PFPR revenue that is not attributable to the sample PFPR facilities).  This
 calculation assumes that, within a firm, the PFPR compliance costs incurred by non-sample facilities will
 be the same per dollar of residual PFPR  revenue as the compliance costs per dollar of PFPR revenue
 calculated for the firm's sample facilities.  Unlike the estimation of baseline ROA, it was not necessary
 for EPA to consider non-PFPR manufacturing facilities  in this analysis,  as these facilities would not be
    7 Facilities are expected to meet regulatory requirements with zero cost under Option 1.

                                             8.10

-------
subject to the PFPR regulation.  For clarity in this discussion, the baseline cost adjustments described
above that affect the numerator in the ROA calculation are combined into one variable, COSTBL, as
follows:
                   COSTM = COSTSAMPm + COSTMFGa,  + OTHCOST,
                        1BL
                                       BL
                                                      BL
                                                                   1BL
       Post-compliance ROA is calculated as follows:
                      EBT - COSTBL - OMCOMP - (CAPCOMP/W) - INTPMT
             ROAPC =
                                 ASSET + OCPSFcap + CAPCOMP
Where:
ROAPC         =  Estimated firm pre-tax ROA, calculated post-compliance;
EBT           =  Firm earnings before taxes in 1988;
COSTBL        =  Firm baseline cost adjustments, as defined above;
OMCOMP      =  Annual firm operating  and maintenance costs of complying with the regulatory
                  option;
CAPCOMP     =  Total firm capital costs  of complying with the regulatory option;
ASSET         =  Unadjusted firm assets in 1988;
OCPSFcap      =  Total firm capital costs of complying with the OCPSF effluent guideline (a baseline
                  adjustment); and
INTPMT       =  Average yearly interest payment over 10 years on the capital costs of compliance,
calculated as follows:
INTPMT =
           D  x CAPCOMP x °-064
                                                          x CAPCOMP
                                                              10
Where:
       D       =  Percent of firm's compliance capital outlays financed by debt;
       O."064   =  The assumed real interest rate of 6.4 percent (see Chapter 4).
The analysis assumes a straight line depreciation schedule over ten years (CAPCOMP/10).
                                          8.11

-------
       The percent of compliance capital outlays financed by debt, D, was derived differently for public-
reporting firms, private single entity firms, and  private multiple facility firms.  For public-reporting
firms,  EPA used the ratio of debt to total assets reported in each firms' balance sheet for 1988.8  For
private, single entity firms,  the percent of capital financed by debt was calculated using data from the
PFPR survey (see Chapter 4).  For private, multiple facility firms, EPA averaged the facility-level ratios
of debt to total compliance capital used in the facility-level impact analysis. The individual facility values
were weighted by each facility's capital cost of compliance.

       Calculation of firm-level, post-compliance ROA requires estimates of the compliance capital and
operating costs for the share of a firm's PFPR revenue not covered by Survey facilities. As noted above,
EPA estimated PFPR compliance costs for each firm's residual PFPR revenue by extrapolating the costs
calculated for a firm's sample facilities based on the ratio of compliance cost to PFPR revenue.  The
following discussion describes the separate calculations for the operating and capital costs.

       The equation below  summarizes the calculation of the firm's annual compliance operating and
maintenance costs, OMCOMP.  The first part of the equation accounts for operating and maintenance
costs among the sample facilities. The second part of the equation accounts for the additional operating
and  maintenance costs of those facilities associated with the firm's  residual PFPR revenue.   In a
calculation similar to that used for the baseline cost adjustments, these costs are estimated based on the
amount of firm PFPR revenue that is not accounted for by  the sample facilities and the ratio of sample
facility compliance operating and maintenance costs to sample facility PFPR  revenue.  The  analysis
assumes that the compliance cost-to-revenue ratio among non-sample facilities is the same as that for the
sample facilities owned by the firm, in aggregate.  The calculation is as follows:
                           "                "  OMCOMP.              "
             OMCOMP = £ OMCOMP. + £ - '- x(FRMPFPR- Y FPRREV,)
                          fa          '   fa  FPRREVi              fa
   8 For all but two foreign-owned firms, these data were obtained from the firms' 10-K statements.  The debt-to-
total-assets values for the two foreign-owned firms were calculated using data from S&P Reports.

                                              8.12

-------
Where:
OMCOMP;
    = the annual operating and maintenance costs of complying with the regulation for
       sample facility i; and other variables are as defined above.
       The total capital  costs of the regulatory option to the firm, CAPCOMP,  are calculated in a
parallel manner to OMCOMP.  Again, the first part of the equation below accounts for capital costs
among the sample facilities while the second part of the equation accounts for the additional compliance
capital costs of those facilities associated with the firm's residual PFPR revenue. Also, the analysis again
assumes that the compliance capital cost-to-revenue ratio among non-sample facilities is the same as that
for the sample facilities owned by the firm, in aggregate.  The calculation is as follows:
CAPCOMP  =
CAPCOMP,
 FPKREV,
                                                                     -^) FPRREVt)
Where:
CAPCOMP;
     =  the total capital cost of the regulatory option for facility i; and the other variables
        are as defined above.
8.2    Estimated Firm Impacts
       Among the 308 firms initially considered for the analysis, 66 firms, all single entities, had a
baseline  ROA of  less than the established threshold, and were therefore not considered for  post-
compliance impacts. Of the remaining 242 firms analyzed, EPA found that 5 (2 percent) have a post-
compliance ROA less  than the 2.4 percent threshold.  These  firms may experience some financial
hardship as a result of complying with the proposed PFPR regulation.  Two of these firms are private,
multiple  facility firms and three are private, single entity firms.  All of the private, single entity  firms
estimated to incur  impacts were also found to incur impacts at the facility level. From these findings,
EPA judges that firm-level impacts are not expected to be significant.  The results of these analyses are
summarized in Table 8.1.
                                              8.13

-------
Table 8.1: Sample Firm Financial Impacts
Firm Type
Public-Reporting Firms
Private Multi-Facility Firms
Private Single Entity Firms
Total
Baseline
Number of
Projected
Impacts
0
0
66
66
Number of
Firms
Considered
36
92
180
308
Post-Compliance
Number of
Projected
Impacts
0
2
3
5
Number of
Firms
Considered
36
92
114
242
8.14

-------
                                    Chapter 8 References


EIA: Effluent Limitations Guidelines and Standards for The Pesticide Manufacturing Industry, EPA,
       1992.

RMA Annual Statement Studies, Robert Morris Associates (1991). Philadelphia, PA.

S&P Reports, Standard and Poor's (1993, 1994)

U.S.Industrial Outlook (1992), U.S. Department of Congress, Washington, D.C.
                                            8.15

-------

-------
                                         Chapter 9
                                 Impacts on New Sources
       9.0    Introduction
       In this chapter, the effects of the New Source Performance Standards (NSPS) and Pretreatment
Standards for New Sources (PSNS) proposed regulations upon new discharge sources are considered.
New facilities have the opportunity to incorporate the best available demonstrated technologies, including
process changes, in-plant controls, and end-of-pipe treatment technologies,  and to  use facility site
selection to ensure adequate treatment system installation. The impacts of the proposed regulations on
new sources are expected to  be less burdensome than the  impacts of the BAT/PSES regulations on
existing sources. Designing a new technology prior to facility construction is typically far less expensive
than retrofitting a facility for  a new technology.  The proposed NSPS and PSNS regulations,  and the
reasonableness of the associated costs, are discussed below by  Subcategory.

       9.1    Subcategory C
       New Source Performance Standards
       EPA is proposing to establish NSPS for Subcategory  C as zero discharge, equivalent to BAT
requirements  for existing sources.  Zero  discharge  represents best available and best  demonstrated
technology for the pesticide formulating,  packaging and repackaging subcategory as a  whole.  The
economic impact analysis shows that this regulatory approach, termed Option  3 in the analysis, would
be economically achievable for the industry.  EPA believes  that new sources will be able to comply at
costs that are similar to or less than the costs for existing sources, because new sources can apply control
technologies, including dedicated lines and pressurized hoses for equipment cleaning, more efficiently
than sources that need to retrofit for those technologies. EPA's analysis concludes that a zero discharge
requirement for  new source direct dischargers would be economically achievable and would not be a
barrier to entry.
       Pretreatment Standards for New Sources
       EPA is proposing to set PSNS (which cover indirect dischargers) equivalent to NSPS (which
cover direct dischargers), i.e., at zero discharge for all PFPR waste streams.  For the reasons stated
above with respect to NSPS, EPA finds that the PSNS regulations would be economically achievable and
not a barrier to entry.
                                              9.1

-------
       Although EPA has proposed to exempt the non-interior wastestreams of small sanitizer facilities
from this zero discharge requirement for existing pretreatment facilities (PSES), EPA is not proposing
to include this same exemption for the  new source pretreatment facilities (PSNS).  The rationale for
finding that the exemption for those sanitizer wastestreams is appropriate for existing sources is based
on EPA's findings  that the impacts on  existing small  entities would be significantly reduced by the
exemption, while the associated additional loading of toxic pollutants would be small.  EPA does not have
sufficient information about new source pretreatment facilities to conclude that the size and economic
condition of those new sources, the impacts on those new sources, and the associated loadings of toxic
pollutants, would justify a similar exemption for the non-interior wastestreams for sanitizer facilities.

       9.2    Subcategory E
       New Source Performance Standards
       EPA is proposing NSPS for Subcategory E facilities as equivalent to the zero discharge BAT
limitations  for existing sources.   Since compliance with BAT has been found to  be economically
achievable  for  existing facilities, EPA has determined that compliance with NSPS  will  also be
economically achievable and not a barrier to entry for new sources.

       Pretreatment Standards  for New Sources
       EPA is proposing PSES for Subcategory E facilities as equivalent to the zero discharge PSES
proposed limitations for existing sources. Since compliance with the proposed option has been found to
be economically  achievable for existing facilities, EPA has determined that compliance with NSPS will
also be economically achievable and not a barrier to entry for new sources.
                                              9.2

-------
                                         Chapter 10
      Additional Cost Savings From Pollution  Prevention Under Option 3/S

10.0   Introduction
       Traditionally,  the Environmental Protection Agency has evaluated the economic feasibility of
effluent limitation guidelines and standards by considering the impacts  on an industry of projected
compliance costs, for example, the costs of installing and  operating a treatment technology. However,
facilities may offset some of their compliance costs by achieving regulatory compliance through use of
pollution prevention measures.  The cost analysis of the proposed PSES regulation for Subcategory C
facilities  (Option 3/S) assumes that,  where possible, facilities will use certain pollution prevention
measures to achieve zero discharge. These measures include, for example, recovery and  reuse of rinse
waters and other wastewaters that contain reusable PAIs.  By recovering and reusing the PAIs contained
in such wastewaters, facilities may save on the purchase cost  of PAIs, water consumption costs,  and
sewage treatment costs.  The cost analyses described in Chapter  4 for the proposed regulation include the
costs of implementing such pollution prevention measures and reflect the pollution prevention-related cost
savings from reduced waste management  and disposal costs.  The cost savings accounted for in the
Chapter 4 analysis amount to $4.7 million on an annualized basis.   The  regulatory cost  analyses,
however,  do not include certain additional offsetting cost savings that may accrue to facilities from
pollution prevention.

       To provide a more  comprehensive accounting of the  costs of achieving compliance with the
proposed PFPR regulation, EPA identified and assessed the additional mechanisms by which facilities
might achieve cost savings through use of pollution prevention.  This  chapter describes  some of these
additional potential savings.

        According to  Section 6602(b) of the Pollution Prevention Act of 1990, pollution should be
prevented at the source whenever feasible.  EPA has established pollution prevention as the first priority
within an environmental management  hierarchy that includes prevention, recycling, treatment, disposal
and release.  Pollution prevention means  "source reduction,"  or  any  practice that, as defined by  the
Pollution Prevention Act (1990):
                                              10.1

-------
        •      Reduces the amount of any hazardous substance, pollutant, or contaminant entering any
               waste stream or otherwise released into the environment (including fugitive emissions)
               prior to recycling, treatment, or disposal;

        •      Reduces the hazards to public health and the environment associated with the release of
               such  substances, pollutants, or contaminants; and

        •      Increases efficiency in the use of water or other resources.1

        Pollution prevention is a means for a facility to achieve optimal industrial efficiency by reducing
the use  and generation of hazardous  chemicals  prior  to treatment,  storage, control,  out-of-process
recycling,  and disposal.2   Changes  in processes,  reduced generation of hazardous components  and
reagents, improved housekeeping practices, "in-process" recycling,  and reduced water use  are all
considered  effective  pollution  prevention.   Unlike  end-of-pipe  risk management efforts,  pollution
prevention can reduce worker, community, and environmental exposure to hazardous materials without
transferring pollutants from one medium to another thereby altering the exposure route.

        Pollution prevention, recycle, and reuse practices that can be implemented by PFPR facilities fall
into three categories:

        •      Actual production practices (e.g.,  triple rinsing of shipping containers directly into
               formulations, scheduling production to minimize frequency of rinsing, storing rinsewaters
               for future formulations,  and dedicating equipment  and process  lines for  specific
               pesticides);

        •      Housekeeping practices (e.g., preventative maintenance, use of spill cleanup water in
               formulations); and
    'Habicht, F. Henry II (1992).  Memorandum, EPA Definition of Pollution Prevention, May 28, 1992.

    Anderson, Steven and Herb, Jeanne (1992).  "Building Pollution Prevention into Facilitywide Permitting,"
Pollution Prevention Review, Autumn.

                                               10.2

-------
       •       Practices employing equipment that by design promote prevention (e.g., use of low flow
               hoses, squeegees, and steam cleaners).

The PFPR industry  already uses these practices to  varying degrees.  In some cases, adopting these
practices as a means of regulatory compliance can provide various cost savings and qualitative benefits
as enumerated below.

       The potential cost savings (over and above the $4.7 million discussed in Chapter 4) from using
pollution prevention  as a method of complying with the proposed PFPR regulation were estimated from
responses to the PFPR industry Survey and associated technical and economic analyses.  A total of 595
population PFPR facilities are included in this assessment of savings resulting from  compliance with the
proposed regulation. This subset of facilities includes all PFPR facilities using 272 PAIs that (1) were
reported in business as of the date of their survey response,  2)  completed all parts of the survey as
requested (i.e., are "clean") for both technical and economic information, and 3) are water users who
discharge water either directly using the best practicable technology through a National  Pollutant
Discharge Elimination Discharge System  (NPDES) permit, or indirectly into a water body through a
publicly owned treatment works (POTW).  More specific subsets were identified for particular sections
of the analysis.

        EPA identified  five mechanisms  by which facilities may offset  some  of their regulatory
compliance costs through pollution prevention.  Two mechanisms  are associated with the direct costs of
PFPR activities:  recovery of PAIs, and recovery of water (reducing water  and discharge costs). The
other three mechanisms,  termed indirect cost savings, arise from reductions in facility and firm costs (or
other business-enhancing benefits) that are not directly associated with PFPR  processing of PAIs.  These
indirect cost savings mechanisms include: reductions in permitting costs, reductions  in business insurance
premiums, and reductions in firm cost of capital.
        Using Survey data for PFPR facilities subject to regulation, EPA estimated facility-specific
 savings for the two direct cost mechanisms listed above. Aggregate annual cost savings from recovery
 and reuse of PAIs and from reduced  water use and discharge were estimated at about $765,000.
 Although EPA was not able to estimate facility-specific savings for the.three indirect cost mechanisms,
 EPA assessed these opportunities on the basis of discussions with permitting authority and insurance and
                                               10.3

-------
finance industry personnel and a review of relevant literature.  From these discussions and reviews, EPA
concluded that the indirect cost mechanisms would also offer cost-savings opportunities to PFPR industry
firms that adopt pollution prevention measures as part of their compliance strategy.

       Section 10.1 presents an overview of the two  major categories of cost-savings opportunities
considered in this analysis:  direct and indirect cost savings. Sections 10.2 - 10.6 assess five specific
cost-savings mechanisms. The first two are direct cost mechanisms:  recovery of PAIs, and recovery of
water (reducing water and discharge costs).  The other three are indirect cost mechanisms:  reductions
in permitting costs, reductions in business insurance premiums, and reductions in firm cost of capital.
Section 10.7 assesses cost savings from pollution prevention with costs incurred where combustion is the
vehicle of regulatory compliance.

10.1   Overview of Compliance Cost Savings Opportunities
        Conservative compliance cost estimates associated with Option 3/S were presented in the previous
chapters as part  of the  economic impact  analysis  of this regulation.  Although these cost estimates
incorporated the cost of implementing pollution prevention measures, the estimates recognized only a part
of the potential cost savings that would accompany their implementation.  Additional cost savings that
can accrue through compliance by pollution prevention are detailed in this chapter. For this analysis,
EPA categorized potential cost savings as direct or  indirect.
        Direct cost savings
        Direct cost savings arise from changes in the costs of PFPR activities, including off-site costs.
 EPA identified and analyzed two direct cost savings mechanisms:
 •      Recovery of PAIs; and
 •      Recovery of water (reducing water and discharge costs).

        During the formulating, packaging, and  repackaging  of pesticides, various processes  can  be
 employed that recover both PAIs and water.  In addition, other pollution prevention practices, such as
 the use of dedicated lines for specific PAIs or products, and recovering spills and using them in product
 formulations, can nominally increase cost savings. From an analysis of sample facilities' process designs,
 EPA estimated the potential for  PAI and  water  recovery.  The recovered PAIs, water and potential
 savings in discharge were then costed or estimated from current and historical price data.

                                                10.4

-------
       Indirect Cost Savings
       Indirect cost savings arise from reductions in costs that are not directly associated with pesticide
formulating, packaging and repackaging activities.  EPA identified and assessed three indirect cost savings
mechanisms:
•      Reductions in permitting costs;
•      Reductions in insurance premiums; and
•      Reductions in the cost of capital.

       A facility that reduces its discharges  by pollution prevention  can reduce,  and in  some cases
eliminate,  its POTW  and NPDES permitting requirements  and associated costs.   These costs,  and
potential savings, include both payments to permitting authorities and internal costs such as staff time for
preparing  permit applications,  maintaining  compliance monitoring  programs,  and  preparing  and
submitting permitting compliance reports.

        Other indirect cost savings stem from the treatment of the firm by liability and business insurers
and the public capital  markets.  Certain liability and business insurance premiums are based in part on
the community and  worker  safety risks posed by  a facility  and the risk  of non-compliance  with
environmental and safety regulations.  As insurers become more aware of the benefits  of managing
environmental risks through pollution prevention, policies may offer reduced premiums for facilities with
 rigorous pollution prevention programs.  In  addition, reductions  in financial and  operating risk from
 pollution prevention programs may reduce the cost of capital for PFPR industry firms.  These indirect
 cost mechanisms are more  difficult to quantify than the direct cost mechanisms enumerated above. As
 a result, EPA was not able to estimate facility-specific savings for the indirect cost mechanisms.  Instead,
 EPA assessed these opportunities on the basis of discussions with permitting authority and insurance and
 finance industry personnel and a review of relevant literature.  From these discussions and reviews,  EPA
 concluded that the indirect cost mechanisms would also offer cost-savings opportunities to PFPR industry
 firms that  adopt pollution  prevention measures  as part of their compliance strategy.  As part of this
 assessment, EPA estimated a range of potential savings from reductions in permitting costs.

         Some additional indirect cost savings  may  accrue to those facilities  that choose pollution
 prevention over combustion  as a method of  regulatory  compliance.  Many facilities may initially find
 combustion to be the most cost-effective compliance strategy.  However, when viewed over a longer time

                                                10.5

-------
horizon,  pollution prevention  may become  a  less costly option for several reasons.  In particular,
combustion units face:  increased costs and length of time for permitting; increased regulatory attention;
possible capacity constraints due to placing a low priority on considering permits for new hazardous waste
combustion  units; and troublesome  community  relations.   These factors  may  combine to escalate
combustion costs, making it a  more expensive  compliance method over the long term.  EPA discusses
these issues at greater length in the final section of this chapter.

10.2   Direct Cost Savings From Recovery and Reuse of PAIs
       Residual Pesticide Active Ingredients (PAIs) that remain in the wastewater stream after cleaning
of equipment (e.g.,  interior equipment rinsing)  can be recovered in many facilities that currently
discharge wastewater, and can be reused in the next batch of formulations requiring that particular PAI
or combination of PAIs and inert ingredients. The dedication of lines for specific PAIs and the recovery
of wastewater contaminated by only a single PAI facilitate PAI savings. When PAIs are commingled in
a waste stream, the wastewater may not be immediately reusable, or may not be reusable at all.

       EPA estimated the potential cost savings from recovery and reuse of PAIs from wastewater for
545 facilities. Only water using facilities with compliance costs were analyzed for potential PAI savings.
Facilities using a dedicated line or a  single contaminant wastewater process  are able to reuse the PAIs
present in the wastewater, thereby requiring the input of fewer new PAIs.  For example, a facility using
10 pounds of PAIs in a formulation with one pound being released into the waste stream would need to
use only 9 pounds of new PAIs the next time the same PAI formulation was required if the facility is able
to recover and reuse the one pound of otherwise discharged PAIs.  To estimate the cost savings from
reduction in PAI use, EPA estimated  the quantity of PAIs that each facility could be expected to recover
and  reuse.  The value of the PAIs  recovered was estimated based on PAI-specific prices from the
Pesticide Manufacturers effluent guideline or from manufacturers and other secondary sources.
        Methodology for Estimating PAI Cost Savings
        From engineering analyses of the PFPR industry Survey facilities, EPA estimated that complying
facilities would be able to recover and reuse 116 PAIs in the  course of complying with the proposed
PFPR regulation. The prices per pound for each of these 116 PAIs were gathered from several sources.
The El A for the Pesticide Manufacturers effluent guideline gathered price data for PAIs subject to that
rule.  In cases where  more than  one price was reported for a PAI, EPA calculated  an average price
                                              10.6

-------
weighted by the amount of domestic sales per price for each PAL  Some PAI prices were constructed
from the revenue received for the final pesticide product at the manufacturing facilities.  In addition,
chemical product distributors provided some prices. Ten PAIs lacked any pricing data; however, values
were estimated for these PAIs by averaging the available PAI prices within clusters of PAI use.  The
prices for all PAIs were converted to 1988 dollars using the Producers Price Index for chemicals.

       To assess the value of savings over the period of compliance with the proposed rule, EPA
considered the possibility that PAI prices might increase in the future at a rate greater than the general
rate of inflation. However, a review of historical data for the Producers' Price Index (PPI) for chemical
products and the Consumer Price Index (CPI) gave no evidence that the PAI prices would be expected
to increase at a rate greater than the rate of inflation. Therefore,  EPA chose not to adjust PAI prices for
increases beyond inflation.

       The quantity of PAIs not used in the product and the amount that could be potentially recovered
were obtained from the PFPR industry Survey. The recoverable PAI quantities (for each facility, by PAI)
were multiplied by the  price for each PAI, and summed by PAI  to obtain an estimated facility cost
savings, as follows:
                                           1=1
where:

Qj =   the quantity of PAI i saved;
P; =   the price of PAI i; and
n  =   the number of PAIs used by the facility.
        Estimated PAI Recoveries and Potential Cost Savings
        Potential cost savings were estimated for end-of-pipe PAI loadings under Option 3/S.    EPA
 estimates the average amount of PAI loadings per facility (with potential PAI recoveries) at 336 pounds
 per year, valued at $3,042.  Over all facilities, EPA estimates total PAI loadings of 118,688 pounds
 annually with a value of $1,075,332.
                                              10.7

-------
         Several factors prevent all of the PAI loadings from being recovered and reused, for example:
  mixed wastewater streams, PAIs caught in filters, and accidental contamination.  Engineering analyses
  indicate that 354 PFPR  facilities  are currently capable of recovering  and reusing 116 PAIs.   EPA
  estimates that facilities may recover, on average, about 220 pounds of PAIs per facility, which represent
  77,816 pounds  of PAIs per year in aggregate.  As a result, about 65 percent of the aggregate PAI
  loadings are estimated to be recoverable and reusable.  At the facility level, on average each facility with
  PAI savings can expect to recover 57.7 percent of the pounds of PAIs currently being discharged, and
  57.6 percent of the dollar value of PAIs currently being discharged.EPA estimated that on average each
  facility with PAI savings would save approximately $1,777 per year, with a total value of $628,065 (in
  1988 dollars).  On average, these savings represent about 0.65 percent  of these facilities' total annual
  compliance cost. The sample facility with the highest savings is estimated to save $427,000 per year.
 To the extent that facilities increase recoveries, for example, by further isolating waste streams, these
 recovery percentages and associated gams from pollution prevention will increase.
Table 10-1
Summary of Estimated PAI Cost Savings Under Proposed Regulatory Option

Industry Total (354 facilities)
Average Facility Savings
Founds of PAI Recovered
78,816
220
Total Value of PAIs
Recovered ($1988)
$628,065
$1,777
        To better understand the potential for PAI cost savings from regulatory compliance strategies
 incorporating pollution prevention,  EPA looked more closely at the distribution of cost savings over
 facilities, and specifically at the characteristics of those facilities achieving the highest savings. Overall,
 most facilities with savings  were estimated to  achieve very modest amounts of PAI  recoveries and,
 accordingly, to achieve only modest financial gains from PAI recovery.  Over half of the facilities with
 estimated savings were found to achieve less than 10 pounds of recoveries per year with  only a few
 dollars of associated cost savings.

       For a few facilities,  PAI recovery and  associated cost savings will be much higher.  On the
whole, these facilities showed few common characteristics with the exception that they tend to be larger
PFPR faculties that also manufacture PAIs.   To illustrate, the five sample facilities, which represent
                                              10.8

-------
 approximately  10 facilities in the overall population, that will realize the greatest savings from PAI
 recovery are diverse in terms of primary market and PAIs used. Three of the facilities receive at least
 90 percent of their total facility revenue from PFPR activities, one facility derives about 38 percent of
 its total facility revenue from PFPR, and one facility depends  upon PFPR activities for only about 9
 percent of its total revenue.  Four out of the five  facilities also manufacture pesticides.  Two of the
 facilities share the same primary market: the agricultural market. None of the facilities would experience
 regulatory relief from the sanitizer exemption. The number of PAIs used by these facilities ranges from
 one to twenty-five. One PAI, an  insecticide,  is used by three out of the five facilities and two PAIs,  an
 insecticide and  a synergist, are used by two of the facilities. Only one of the sample facilities is a direct
 discharger; the remainder are indirect dischargers. In sum, these data exhibit little pattern to suggest that
 only certain types of facilities could be expected to achieve substantial benefits from recovery and reuse
 of PAIs.

 10.3    Cost Savings From Reduced Water Use and Water Discharge
        Wastewater from which PAIs have been recovered can be reused with the same line or processes
 in a PFPR facility from which it was taken. Economic benefits can accrue from the reduced demand for
 new water as well as from decreased volume of wastewater discharge and associated sewage system costs.

        Methodology for Estimating Cost Savings from Reduced Water Use and Water Discharge
        The methodology followed by EPA in estimating water-related cost savings involved calculating
the potential reductions in water use and discharges by facility and multiplying these values by estimated
water and sewer rates.  Water and sewer  rates were obtained  from Ernst  &  Young's  Water  and
Wastewater 1992 Survey of the monthly rates for the 100 largest metropolitan areas. EPA supplemented
this rate information with data on water rates for facility locations not covered by the Ernst & Young
data.  Also, EPA adjusted these rates to reflect expected increases in water and sewer rates at greater than
the general rate of inflation.

       Estimating Reduced Water Use and Discharge Volumes
       The potential cost savings to facilities were calculated separately for water and sewer use.   In
analyzing  sewer cost savings, EPA assumed  100 percent reduction or reuse of water that is currently
discharged.  However, not all facilities may be able to achieve complete reduction, especially facilities
                                              10.9

-------
 that do not have dedicated lines.  The estimated volume of discharge savings is based on the current
 volume of POTW and NPDES discharges as reported by facilities in the PFPR industry Survey.

        Water cost savings were based on the assumption that water currently discharged to a POTW or
 under NPDES will be recycled and therefore the amount of new water required for production will be
 reduced by this amount. The sum of reported POTW and NPDES discharge volumes therefore represents
 the water volume for calculating water consumption savings as well.

       The discharge volume may provide a reasonable  estimate of the potential  change in  water
 consumption.  However, use of the reported discharge volume for calculating the  change in  water
 consumption may understate the potential monetary value of water consumption-related savings because
 of the typical structure of water consumption rates.  In particular, as discussed more fully in a later
 section of this chapter, municipalities are more frequently using increasing block rate structures for  water
 consumption. Under an increasing block structure, the water consumption unit price increases with the
 volume of consumption per time period.  As a result, under an increasing block rate formula, the  value
 of cost savings for a given volume of reduced water consumption will increase as the gross quantity of
 consumption by a facility increases.  For example, a facility that saves 5,000 gallons per month out of
 gross consumption of 50,000 gallons may achieve a higher monetary value of savings than a facility that
 saves 5,000 gallons out of 10,000 gallons of gross consumption.

       The PFPR industry Survey did not require facilities to report either their gross water consumption
 or the amount of water that remains in the PFPR product. If either of these values were known, it would
 be possible to calculate more accurately the value of water consumption savings based on the marginal
 price that would otherwise be charged for the water that is saved through pollution prevention. In the
 absence of this gross consumption information, this analysis assumes the pre-compliance discharge volume
 is the gross consumption volume, and the price for valuing water use savings is taken from rate schedules
 accordingly.  To the extent that gross consumption exceeds the discharge volume and PFPR facilities face
 increasing block structures for water use rates, this assumption may understate the unit price being used
to value water use savings, thereby understating potential cost savings.  Furthermore,  the Survey only
contained information regarding PFPR water use.  If a facility also manufactures PAIs, it may save even
greater volumes of water by implementing pollution prevention measures.  Therefore potential cost
savings may be further understated.
                                             10.10

-------
        Estimating Rates for Valuing Reduced Water Use and Discharge
        Ernst & Young, in The 1992 Water & Wastewater Rate Survey reports water and sewer rates for
100 major metropolitan areas. The rates were reported as monthly water and  sewer charges based on
volume used and  discharged.  Ernst & Young adjusted the actual water and wastewater rates so that
comparisons can be made among cities.  Rates were grouped  into seven volume categories, beginning
with small increments,  then shifting to larger increments with larger water consumption volumes.

        Although rates for facilities located in rural areas were not included in the Ernst & Young report,
a rate analyst from the Denver Water Department stated that urban and rural water and  sewer rates in
the same  region would differ by only small amounts.3  Accordingly,  EPA developed an average rate
schedule for each state in which PFPR sample facilities with estimated water savings were located based
on the Ernst & Young information for major cities; some states had listings for as many as 9 cities. All
of the rates were adjusted to annual rates (i.e., multiplied by twelve).  As described below,  rates were
also adjusted to reflect the amount by which growth in water and sewer rates were estimated to exceed
the general rate of inflation.  These rates were used to calculate annual cost savings to PFPR facilities
that undertake pollution prevention activities.4

        If water and sewage rates are expected to increase at a rate faster than the general  rate of
inflation,  then using current rates to value reduced water consumption and discharge will understate the
potential benefits of pollution prevention to PFPR facilities.  Accordingly, EPA reviewed literature and
discussed this issue  with water and sewer industry specialists to understand whether water and  sewage
rates could be expected to increase at a rate faster than the general rate of inflation.  From this review,
EPA identified several factors that are contributing to water and sewer rates' surpassing the general rate
   3Montoya, Angela, Telephone Interview of March 21, 1994.

   4 To verify that the Ernst & Young rates would reasonably approximate rural rates, EPA obtained actual water
and sewer rates from 9 water and sewer offices in rural areas to compare with the urban rates that were compiled
by Ernst and Young.  Using these rates,  illustrative examples were  developed for facilities  within the 9
communities.  Annual cost savings for water use and sewer discharge for each example were calculated using the
state-average rates based on the Ernst & Young survey and the actual rates obtained from rural water and sewer
offices. The savings calculated by both methods were not found to vary in a statistically significant way to suggest
that the Ernst & Young survey-based rates would either overstate or understate the cost savings from reduced water
consumption and discharge.

                                              10.11

-------
 of inflation.  These findings, as summarized in the following paragraphs, lead EPA to adjust the Ernst
 & Young rates for expected future increases in water and sewer rates.

        General trend of water and sewer pricing.   Municipalities and towns across the country  are
 reevaluating water rates and structures to account for conservation pressures, increased financial pressures
 on utilities  resulting from regulatory requirements,  supply and capacity  limitations,  and financial
 management  issues.5  Distinct changes in the  water rates  and structures in regions across the country
 have resulted.  The  changes already realized,  as well as ongoing trends, could significantly affect  the
 savings achievable by PFPR facilities that adopt pollution prevention measures to recover and  reuse
 wastewaters.

        Rate structures for water pricing.  Water and sewer utilities adopt a variety of rate structures to
 achieve revenue requirements  while  also  promoting  other public policy  objectives (e.g.,  water
 conservation).  The three prevalent rate structures include:
        1.      Declining block rates — prices decrease as consumption increases
        2.      Uniform rates — prices do not vary with consumption
        3.      Increasing block rates — prices increase with consumption.
 Each  of  these structures results in  significantly  different  water  costs,  especially  for  larger
 industrial/commercial users. The decision to adopt a particular structure depends on local considerations
 including:  effects on consumers,  local usage patterns, water supply, local  financial practices,  state
 regulatory environment, conservation, competitiveness with local communities, revenue stability, legality,
 and simplicity.6 As a result of these different factors that may affect a community,  the ultimate rate
 structure  and cost to consumers vary widely from region  to region.  Increasingly, communities are
 moving away from the older declining block structure, which encourages consumption, to the  increasing
 block structure, which encourages water conservation and reduced sewage discharge.

        Regional trends in rates and  structures.  Water and sewer  rates vary  by region,  reflecting
 localized conditions of water availability and quality. The Northeast is undergoing the most significant
    5Duke, Ellen and Montoya, Angela (1993). "Trends in Water Pricing: Results of Ernst and Young's National
Rate Survey," American Water Works Association Journal, May.
    6Jbid.
                                              10.12

-------
shift away from declining rates.  In 1992, 44 percent of the utilities used a declining block rate, down
from 75 percent in 1986; the utilities reported shifting mainly to uniform rates, although some are moving
to increasing block rates.  An aging  infrastructure that is placing greater demand on the total water
system, contamination of the groundwater, and the drought during the 1980s made it difficult for utilities
in the Northeast to deliver quantities of water while maintaining quality during peak periods, leading to
use  of seasonal or excess use charges.   The trend away from declining block rates to conservation-
oriented rates is expected to continue in the Northeast.  The shift in the South away from declining rate
structures has been more gradual.   However, 25 percent of utilities in the region are using increasing
block rates.  Because of substantial economic growth, the South faces the challenge of protecting surface
and  groundwater resources as well as periodic water shortages.  These factors have resulted, and will
continue to result, in pressures towards increasing block, conservation pricing.  Midwestern water users
enjoy a relatively plentiful  source of water resources through their geographic proximity to the Great
Lakes.  Like the Northeast, the largest problem in the Midwest is the ability to deliver quality water
during peak periods, making excess use and seasonal pricing structures attractive.  The region  is also
increasing its reliance on increasing block rates. In 1986,  no facilities used increasing block rates;  in
1992, 10 percent used this approach.  The West has the greatest proportion of increasing block rates at
32 percent.  The water supply is so  low in some areas of the West that major cities must rely on
"imported" water from other  regions.  In the West, conservation measures have become imperative.
Because the West has experienced significant rate increase in the recent past, the incremental change in
water rates in the future is not expected to be as great as in other regions (i.e., Northeast and South).7

        Projected increases and impact of water rates on the PFPR industry.  On the basis of factors such
as those delineated in the preceding paragraphs, industry experts  indicate that water and  sewer rates
across the nation are likely to  increase at a rate at least as great as the general rate of inflation over the
next few years.8  Moreover, significant variations  by region are possible.  Although the trend toward
conservation pricing has been slower in the Midwest, where a majority of the PFPR facilities are located,
the trend is expected to continue and  thus affect the PFPR facilities in that region.   Industry experts
   7Duke, Ellen and Montoya, Angela (1993).
   8Duke, Ellen and Montoya, Angela (1993).

                                              10.13

-------
 indicate that the Northeast and Southern regions are likely to experience the greatest increase in water
 rates in the near future9; a large number of PFPR facilities are located in the Southern states.

        From these considerations, EPA decided to adjust the state-average water and sewer rates by a
 factor to  account for the likelihood that water and sewer rates will increase at a rate exceeding the rate
 of inflation over a ten-year analysis period. Duke and Montoya (1993) state that in the long term, water
 and sewer rates for commercial/industrial facilities (across all regions) are likely to increase at a rate
 somewhat higher than the increase in the Consumer Price Index.  EPA estimates that the real rate of price
 increases could range from 2 to 4 percent. Over a ten-year period, a 2 percent real rate of price increase
 translates into an average price that is 11 percent higher in inflation-adjusted terms than the price at the
 beginning of the period,  while the 4 percent real rate translates into a 22 percent higher average price.
 For this analysis, EPA calculated water and sewer-based savings using rates increased at both the two and
 four percent real rates of price increase.

        Estimated Cost Savings from Reduced Water Use and Discharge
        Water and sewer cost savings were estimated for the 529 Subcategory C facilities estimated to
 incur costs of complying with the PSES regulation.  EPA estimated that 519 facilities could be expected
 to achieve water and sewer cost savings by use of pollution prevention.  For those facilities achieving cost
 savings, the mean water  and sewer savings is estimated at $227 to $251 per year.10  The maximum
 annual savings for an individual facility is approximately $13,000.  On average, these savings represent
 about one percent of the total annualized compliance costs for the facilities expected to achieve water and
 sewer cost savings.  However, the maximum percentage of compliance costs estimated to be saved at a
 specific facility is about  11 percent of total annual  compliance costs.  On the basis of the individual
 facility  values,  EPA estimates  national aggregate annual benefits from water and sewer savings  of
 $128,013 to $141,477.   In general, the sewer  cost  component of individual facility savings  is
 approximately two-thirds the water cost savings, although wide variations in pricing do exist.  The
 combined water and sewer cost savings for average and median facilities as well as for industry totals are
presented in Table 10-2.
   9Montoya, Angela (1994) Telephone Conversation of March 21.
     Range results from use of the 2 percent and 4 percent real rates of price increase for water and sewer rates.
                                              10.14

-------
Table 10-2
Sewer and Water Cost Savings Summary Table*

Industry-wide Aggregate
Average Facility Savings
Median Facility Savings
Weighted Cost Savings
(2 percent rate of real price
increase)
$128,013.24
$226.72
$96.76
Weighted Cost Savings
(4 percent rate of real price
increase)
$141,476.53
$250.57
$106.94
Includes facilities with cost savings.
       Most facilities are estimated to achieve relatively modest savings:  the estimated median facility
cost savings range from $97 to $107 per year.  However, some facilities were estimated to achieve
substantial savings, both absolutely and as a percentage of total regulatory compliance costs. Specifically,
the maximum total cost savings for any one facility is estimated at $12,762 -  12,976.  Although cost
savings average 0.81 percent of total compliance costs, the analysis found that 10 facilities would be
expected to achieve water and sewer cost savings representing between three and eleven percent of their
total annual compliance cost. As previously mentioned, these cost savings only represent the savings due
to PFPR operations.  Some facilities may  save additional water and sewer costs by using pollution
prevention measures in their manufacturing processes as well.

        EPA considered whether  the sample facilities with the larger savings values exhibited  any
particular characteristics.   As would  be expected, facilities show a greater cost savings the higher the
volume of water used.  Many of the  facilities that captured the highest cost  savings are categorized as
manufacturers in our survey. The manufacturing category includes facilities that have high water use and
discharge volumes because they tend to formulate and package  large volumes of PAIs.  No regional
correlations are apparent.  Of the 10 sample  facilities with expected water and sewer  cost savings
exceeding 3 percent of the total compliance cost, 8 primarily serve the institutional market.   The
remaining two facilities were categorized as a consumer home products facility and an industrial facility.

        The actual cost savings from reduced water use and discharge could be higher than estimated.
As discussed in the methodology section,  the data needed  to  accurately  calculate the  cost savings
associated with a change in water consumption were unavailable (i.e., the survey did not require facilities
to report total water use or the amount of water  retained in the product). Because water use is priced in
                                              10.15

-------
 block rates, the water cost savings based on actual pre- and post-compliance water consumption could
 result in a much higher cost savings than that calculated by applying a price based only on the amount
 of water saved, and manufacturing facilities will likely save water in their manufacturing processes as
 well.

 10.4   Indirect Cost Savings from Reduced  Costs of Permitting and Fees
        PFPR facilities  may reduce  the costs  of obtaining and renewing discharge  permits by using
 pollution prevention measures to comply with the proposed regulatory option. Permitting costs include
 application fees, annual maintenance fees, renewal fees,  costs of preparing engineering reports, and
 monitoring and reporting  costs.  A  review  of permitting information from  several states with PFPR
 facilities showed that permitting costs and payment structures vary considerably from state  to state.  In
 general, however, reducing or eliminating discharge volumes through pollution prevention should permit
 facilities to save on permitting costs.  In most cases, facilities would have to retain some form of permit,
 but would be expected to pay lower permitting costs.  In some cases, these savings may be substantial.
        Review of Permit-Related Cost Savings Opportunities
        To understand the permit-related cost savings that PFPR facilities might achieve, EPA reviewed
 information on permitting procedures and costs for several states with PFPR facilities.11  EPA  also
 discussed the opportunity for permit-related cost savings with permitting authority and POTW personnel
 in several states.  From this  review,  EPA found that the permitting  costs and payment structures
 associated with discharging wastewater vary widely among states and regions.  For example,  several
 states vary permit application and maintenance fees based on facility discharge volumes and complexity
 of discharge streams. Some states indicated that their permit fee structures have been explicitly designed,
 or are being designed, to promote pollution prevention as a discharge reduction or elimination method.
 The more common permit-related cost items are as follows:
    UEPA generally contacted states that are assessed as potentially being impacted, and that represent diverse
geographic regions.

                                              10.16

-------
       Indirect Dischargers
       •     State Permit Application Fees
       •     Annual Compliance Costs
       •     POTW User Fees
       •     Periodic Monitoring Costs
       •     Costs of Preparing Permit Applications
       •     Fines for Exceeding Discharge Limits
       Direct Dischargers
       •      NPDES Fees
       •      Permit Application Fees
       •      Annual Compliance Fees
       •      Fines for Exceeding Discharge Limits
       •      Periodic Monitoring Costs
       •      Costs of Preparing Permit Application

       From the contacts with state agencies, EPA identified a variety of pricing schemes for each
potential  permit-related cost. These cost items frequently vary in a way that would allow facilities to
reduce expenses by achieving compliance through pollution prevention, as summarized below.

       Discharge permits: indirect dischargers.  Some states do not require indirect discharge permits;
therefore no cost is required for  obtaining a permit. Of those that do require permits, the payment
structure varies substantially. Several of the ways in which permit costs vary indicate that permit-related
cost savings should be available to facilities that comply with the PFPR regulation by means of pollution
prevention:
•      In some states, the discharge permit fee is based on the complexity of the facility's pretreatment
       system,  which must be inspected and approved.  Pollution prevention should at the very least
       simplify the necessary pretreatment system, and perhaps eliminate the need for a pretreatment
       system altogether, thus eliminating or reducing this fee component.
       One state, New Jersey, based its application fee on the annual volume of pollutant discharges,
       while another state, Illinois, based its permit application fee  on the amount of water that the
                                              10.17

-------
        facility is expected to discharge daily. In both cases, achieving zero discharge through pollution
        prevention would reduce permit costs.

•      Florida charged a "zero discharge" fee that was  substantially lower  in cost than the regular
        permitting fee and was expected to  cover the cost of inspecting the facility's treatment and
        recycling  systems.  In some cases, once the facility is proven to be a "zero discharger," the
        permitting fee is waived for reapplications and renewals.  Pennsylvania, in  contrast, does not
        require zero dischargers to obtain a permit.

        In all  these cases, facilities that comply  with the PFPR regulation by means  of pollution
prevention should be able to reduce or eliminate the permitting fee.  Among the states contacted, the fees
for a permit application ranged as high as $1.9 million. Accordingly, the possible dollar savings can be
substantial. The initial permit is typically valid for a period of 5 years.  Renewal fees tend to be less than
the original application fee though still substantial.

        Discharge permits: direct dischargers. Most states contacted do not have an application fee for
direct dischargers. In one state,  however, there is a flat  application fee that  must be paid every five
years,  and in another state the fee charged is $6,850 upon first applying for the five-year permit, and
$2,150 for renewals. A facility that achieved zero discharge through pollution prevention could avoid
these charges.

        Annual compliance fees: indirect dischargers.  One state charges an annual  compliance fee, which
provides the permitting authority with additional revenues to run its permitting and monitoring programs.
At $100 per year, this fee was  relatively  inexpensive compared to permit application fees.   Again,
achievement of zero discharge through pollution prevention should eliminate the need to pay this fee.

        Annual compliance fees:  direct dischargers.   The corresponding compliance fee for direct
dischargers in the same state described above ranges from $100 to $5,000, depending  on the complexity
of the facility's treatment system for the discharged water.  Pollution prevention  may  eliminate or
substantially reduce this fee amount.
                                              10.18

-------
       User fees charged by POTWs: indirect dischargers.  Most POTWs levy a user fee for industrial
dischargers. These fees can be substantial and typically vary with discharge volume, thus providing an
opportunity for facilities that comply by pollution prevention to achieve cost savings. For example, in
some states contacted, the user fees charged by the POTWs are based on the amount of process water
used or discharged, as well as the level of biological oxygen demand (BOD), total suspended solids
(TSS), and other pollutants such as ammonia or nitrogen that are found in the discharged wastewater.
The range of user fees  among the POTWs contacted ranged from $0 to tens of thousands per year,
depending on the flow and content of the discharged water.

       Monitoring costs: direct and indirect dischargers.  Most states contacted did not require facilities
to pay an  explicit monitoring fee because the POTW user fees were expected to cover that expense. An
exception  would be if the facility was found to be out of compliance and therefore required extended
monitoring. In most such cases, facilities would be charged for that expense.  In a few states, facilities
are required to pay monitoring fees on a regular basis.  The reported costs varied from $500 to $600 per
year. Monitoring and analysis when a facility is found to be in violation can cost from $150 to thousands
of dollars per incident.  Thus, in some but not all cases, facilities would save on monitoring costs by
using pollution prevention as the zero discharge compliance method.

       Fines for exceeding discharge limits: direct and indirect dischargers.  Most states that were
contacted  fine facilities that exceed their discharge limits.  One POTW indicated that depending upon the
degree of violation, a facility could pay up to $10,000 in fees per discharge violation. The facility could
also be held liable for any damage resulting to the POTW, which could cost tens of thousands of dollars.
Excess discharge of pesticide ingredients in particular may disrupt the balance of POTW process bacteria,
which may be quite costly to remedy.    The risk of such costs would be eliminated by achieving
compliance through pollution prevention.

        NPDES fees:  direct dischargers. The NPDES fees for direct dischargers also vary greatly from
state to state.  In some states, the NPDES fee was simply a flat amount. However, some states based
NPDES fees on the volume of pollutants discharged. One state contacted bases its NPDES fees on two
factors:   the threat of the discharge to water quality, and the complexity of the discharge.  Fees for
NPDES permits range from $0 to $73,000 for a five-year permit.  In those states in which fees vary with
                                              10.19

-------
quantity of discharge or risk imposed by the discharge, use of pollution prevention  as a compliance
method should enable facilities to reduce or eliminate fee outlays.

        In  addition  to  the  permit-related savings enumerated above,  permitting authority  personnel
confirmed  that state policies are changing in a way to promote use of pollution prevention and that
permitting  procedures and fee structures are being revised to encourage pollution prevention.

        Finally, some permitting authority personnel noted that facilities may not fully eliminate permit-
related  fees by use of pollution prevention.  Indeed, in some states, facilities may be  required to keep
discharge permits even  though they technically become zero-discharge operations. However, permitting
authority personnel stated that facilities should generally be able to defray their costs based on the reduced
application and maintenance fees frequently charged to  zero dischargers and the reduced time for facility
personnel to complete applications.

        Examples of Possible Permit-Related Savings
        Although it is  not possible  to calculate  an expected savings per  facility from the information
obtained for this study, it is possible to develop illustrative scenarios within the framework of some of
the pricing policies of representative states that will  illustrate potential cost savings that from use of
pollution prevention measures.   Several examples based on state-specific permitting fee structures are
outlined in the following paragraphs.

        Example A: A facility operating in Massachusetts and deemed to be a Category 112 Significant
Industrial User13 that discharges wastewater  into the Massachusetts Water Resources Authority  sewer
system. If this facility undertakes pollution prevention measures that eliminate its wastewater discharges,
the resulting cost savings to the facility would be:
    12A Category 1 SIU facility is "an industrial user subject to Categorical Pretreatment Standards under 40 CFR
403.6 and 40 CFR , Chapter 1."
    13One criterion for a Significant Industrial User (SIU) is that the facility discharge 25,000 gallons of process
wastewater per day.
                                               10.20

-------
       $1,430 every two years in permitting fees, and
       $3,700 per year in monitoring fees14
This facility would save an average of $4,415 each year in monitoring and permit fees.

       Example B:  A facility operating in California, classified as a category la15 direct discharge
facility.  If this facility uses  pollution prevention and wastewater recycling measures to eliminate its
wastewater discharges, the facility  would save $10,000 each year in NPDES permit costs.

       Example C:  If the hypothetical facility described in Example B does not eliminate all of its
discharge,  but reduces it to become a category Ilia16 facility, then the cost of the facility's NPDES
permit would decrease from $ 10,000 per year to $ 1,000 per year.  The facility would save $9,000 a year
in NPDES permit fees.

        Example D:  A facility located in New Jersey is charged $28,000 every five years  based upon
the volume and toxicity of the loadings discharged to a local  POTW, and an annual monitoring fee of
$300. After compliance  the  facility discharges only very dilute amounts of active ingredient from the
laundry  and showers.  As a  result the facility is only charged $7,000 every five years and an annual
monitoring fee of $300.  The facility saves an average of $4,200 per year in permit fees.

        The examples above indicate some scenarios that could result in  substantial cost savings to
facilities under current pricing schemes.  From the interviews conducted for this study, EPA expects that
many states, regions, and POTWs will modify their pricing schemes to further ensure that the permitting
process  itself does not discourage pollution prevention and, furthermore, many states hope to encourage
facilities to engage in pollution prevention.  States indicate that they plan to use pricing incentives, shorter
     14Assuming the facility is one with "medium monitoring point scores", which are facilities with pretreatment
 systems which are monitored between two and three times per year, on average.
     15Category I describes a facility whose discharges "could cause the long-term loss of a designated beneficial
 use of the receiving water", and a complexity "a" category includes "any major NPDES discharger."
     16A category  in facility describes a facility whose discharges could "degrade water quality without violating
 water quality objectives, or cause a minor impairment of designated beneficial uses compared with Categories I and
 H."
                                                10.21

-------
permit waiting periods, and a shorter, less complicated permit application to further encourage pollution
prevention.

       Possible National Savings from Reduced Permitting Costs
       Because of the large variation in pricing strategies, it is not possible to estimate accurately the
permit-related savings that facilities may achieve through pollution prevention.  However, EPA made
broad assumptions to illustrate the possible magnitude of permit-related savings that facilities might realize
through use of pollution prevention. Because two of the above examples showed annual savings of about
$4,000 per year, that amount was used as a benchmark.  Assuming that one-third of PFPR facilities incur
no savings, one-third save $4,000 per year from reduced permitting costs, and one-third save $8,000 per
year (twice the benchmark amount), the aggregate cost savings to the industry would be about $2,800,000
each year.

       Overall, PFPR facilities have  a substantial  opportunity to  reduce permit-related  costs  by
undertaking pollution prevention measures.  These costs are expected to rise in the future, as states and
municipalities modify their permit pricing structures to encourage pollution prevention.

10.5   Indirect Cost Savings from Reduced Insurance Premiums
       Although liability and general business insurance policies do not currently incorporate explicit
discounts for use of pollution prevention, trends  in insurance coverage show that reduced chemicals-
related risk should be reflected in reduced insurance premiums. Specifically,  the insurance industry has
begun to recognize that pollution prevention efforts can reduce a number of business  and liability risks.
As a result, insurance firm representatives  indicate that PFPR facilities with wastewater recycling and
zero discharge may be charged lower premiums than facilities that discharge to a POTW.  The lower
insurance premiums could result from several mechanisms.   Although  it is not possible to quantify the
value of these savings, EPA finds that PFPR facilities should benefit from reduced premiums by using
pollution prevention to comply with the proposed PFPR regulation.

       Mechanisms by Which Pollution Prevention Reduces Environmental Risk
       To understand whether PFPR facilities that use pollution prevention as a compliance method
might be charged lower insurance premiums,  EPA discussed this issue with several business insurance
                                             10.22

-------
representatives.  The discussions with industry representatives reveal a trend to incorporate pollution
prevention considerations into the underwriting process, potentially resulting in a premium credit.

       Over the past decade and a half, the insurance industry has established classification criteria to
distinguish increases  and decreases in risk  in  industries using chemicals  and with chemical wastes.
Ultimately, liability and business insurance premiums are set to reflect the overall environmental  risk at
industrial facilities and take these risk classification criteria into account.  Important factors in evaluating
facility environmental risk include:

        •      Determination of exposure rating
        •      Assessment of compliance history
        •      Determination of process/waste constituents
        •      Determination of the concentration of constituents17

Within the risk classification process, pollution prevention as a means of compliance may benefit PFPR
facilities through several mechanisms, as follows:

        Reduced Use ofPAIs Results in Reduced Exposure Risk
        PAI  recovery and recycling should reduce the volume of PAIs a facility  needs to  purchase,
receive,  and manage during the normal PFPR production process.  In turn, a reduced volume of pesticide
ingredients shipped and handled at a facility can result in lower risk of hazardous exposures for workers
and the surrounding community.  Insurance industry representatives note, however, that depending on
PAI handling and storage practices, exposure risk might not be reduced.  And, in  some instances, the
storage of recovered PAIs for reuse could actually increase business  facility risk. Careful management
procedures should offset this potential increase in risk.  Moreover, if the compliance method used by the
facility involves hauling waste to an off-site combustion unit or landfill, transportation of the waste poses
a risk that could be avoided by adopting on-site pollution prevention measures.
    17Aulisi, Andrew of Commerce and Industry Insurance Company.  Written correspondence of May 12, 1993.
                                               10.23

-------
       Elimination of Discharges Results in Lower Risk of Leaks or Accidental Excess Discharges
       Facilities that use pollution prevention to eliminate discharges will reduce the risk of accidental
discharges of polluting materials.  No contaminated wastewater would be released into POTWs, resulting
in both a reduced risk of potential accidents or leaks, and a lower risk of excessive discharge into the
community. As noted above, excess discharges of PAIs into a POTW can substantially disrupt POTW
processes, exposing firms to considerable liability. Reduction in, or elimination of, these risks should
result in a lower risk rating for a facility, with the potential for lower insurance premiums.

       Reduced Use of PAIs and Elimination of Discharges Reduces the Risk of Exceeding Permit Levels
       For those facilities currently discharging to a POTW  or directly under a NPDES permit,
compliance by pollution prevention may result in reduced insurance premiums because of a reduced risk
of being found in violation of discharge limits.  With no contaminated wastewater being discharged, the
risk of exceeding permit levels (through accidental leak or facility clean-up) decreases substantially.  If
those same facilities chose to comply by contract hauling and combustion of their wastewater, the risk
of noncompliance would remain high.  On-site storage of wastes for more than 90 days (or 45 days for
facilities storing large  volumes  of hazardous wastes) instead  of reducing waste through pollution
prevention measures requires RCRA permitting, which may place facilities in a higher risk category for
insurance pricing.18 In addition, the risk of exposure increases through on-site storage and potential
transportation risks.

       Outlook for Favorable Consideration of Pollution Prevention by the Insurance Industry
       A representative from the Commerce and Industry Insurance Company (a member company of
American International Group, Inc.) provided insight into  the  likelihood that the business  insurance
industry would grant premium reductions for use of pollution prevention.  In evaluating facility risk, the
insurance industry relies heavily on the performance record  of technologies and processes in managing
the risks  that insurance policies are purchased to  insure  against.   Currently, pollution prevention
technologies and processes are not widely used and not well understood by both process industries (i.e.,
in this case, the PFPR industry) and the insurance industry.  As a result, the insurance industry might
not yet view pollution prevention in a favorable light in evaluating facility risk.  In some  instances, as
    18Roepe, Wayne. Telephone conversation of March 21, 1994.
                                              10.24

-------
noted above,  insurance firms might view wastewater recycling and PAI recovery activities as adding to,
or at least not reducing, facility operating risks.

        However, as various aspects of the pollution prevention process become more accepted and their
efficient and  effective performance is better established and documented, insurance firms will be more
likely to account for the potential risk-reducing benefits of pollution prevention programs in setting
insurance premiums. The surface impoundments, holding tanks,  underground piping, sludge generation,
process  modifications,  and chemical storage required for wastewater  recycling may create  risks of
operating system failures  and pollutant  exposures.19   As these aspects of the pollution prevention
process become more widely used, and better understood and proven, the insurance industry will more
likely recognize their  broader  risk-reduction benefits  and change  facility risk ratings  accordingly.
Reduced insurance premiums could then result.

 10.6   Cost Savings from Reduced Cost of Capital
        Compliance by pollution prevention under Option 3/S can provide financial benefits to firms by
 reducing the cost of capital.  Decreases  in the amount of pesticides being used can reduce contingent
 liabilities associated with  worker safety and environmental compliance issues, and may also provide
 preferential  recognition and valuation in the public capital markets.

         The factors that influence the cost of capital to a firm include:  the firm's expected financial
 performance; the variability of the firm's financial performance; the financial structure of the firm and
 the associated variability in the performance of the instruments by which the firm's assets are financed;
 and the relationship of the variability in the firm's own financial performance to that of other firms and
 competing  investment opportunities.  These factors determine the overall riskiness of a  firm as  an
 investment  or lending opportunity.  In general,  actions that reduce the  riskiness or expected variability
 of a firm's financial  performance will  reduce  its cost of capital.  Adoption of pollution prevention
 measures may reduce the riskiness of the firm's financial performance through:

  •      Avoidance of contingent liabilities. For similar reasons to those outlined above for reduced
         insurance costs, use of pollution prevention measures by PFPR facilities can reduce contingent
      19Aulisi, Andrew of Commerce and Industry Insurance Company.  Written correspondence of May 12, 1993.
                                                10.25

-------
 liabilities that pose a risk for creditors and investors.  For example, more efficient use of PAIs
 and the use of dedicated lines for each PAI and/or product can reduce the overall level of worker
 exposure to PAIs. In addition, the reduction or reuse of PAIs can reduce or eliminate pollutant
 discharges, thereby reducing risks to the surrounding community from accidental spills or leakage
 and also  reducing the risk of being found in violation of discharge limits.  Risks associated with
 transporting waste to off-site disposal  operations are  also eliminated if pollution prevention is
 chosen as the method of compliance over off-site disposal. Each of these contingencies may pose
 a financial risk to the firm.  In a worst-case scenario, a fine or legal suit in any one of these areas
 could force a firm into bankruptcy. Elimination or reduction of such contingent liabilities should
 reduce uncertainty about future financial performance and result in lower required returns by
 creditors and investors.

 Increased managerial control of the firm.  Facilities that prevent pollution associated with PAI
 use will be better able to control the financial impact of environmental  regulations.  Firms that
 limit but continue to  discharge effluent  are left with the risk of achieving compliance with
 possibly more stringent environmental requirements in the future. Firms that implement pollution
 prevention to eliminate discharges  are proactively avoiding, and  therefore controlling, the
 possibility of these future compliance costs.  The removal  of this cost uncertainty should make
 those firms that adopt pollution prevention less risky to invest in or lend to.

 Preferential recognition and valuation by investors and lenders.  Some investors preferentially
 search for firms that apply effective and proactive pollution prevention programs.  For example,
 some mutual funds include a social/environmental responsibility component in  their  charter.
 Firms that are perceived as environmentally responsible may be awarded a higher valuation and
 lower cost of capital hi the public  capital markets.

 Improved firm financial performance. Finally, some consumers may favor products of firms that
 are perceived as environmentally responsible (as  defined by the individual consumer).  To the
 extent that a mechanism exists for consumers to be aware that a given  firm has  undertaken
pollution  prevention programs, consumers  may  favor that firm's products  over those of its
competitors and thus improve the firm's business prospects.
                                      10.26

-------
       In summary, although it is not possible to quantify the benefits to a firm from reduced cost of
capital, EPA believes that these benefits may ultimately play a significant role in improving the financial
circumstances of facilities and firms that choose pollution prevention as a means of complying with the
proposed PFPR effluent limitation guideline.

10.7   Attaining Compliance Through Pollution Prevention Versus Combustion
       In the short term, some facilities may view pollution prevention as a more expensive option than
combustion for complying with the proposed PFPR regulation. However, over a longer horizon, several
factors may cause combustion, whether on-site or off-site, to become more costly  and thereby increase
the relative financial attractiveness of pollution prevention. These factors, which  are discussed briefly
below, stem from issues in the permitting, construction, and environmental regulation of combustion
facilities.

       Difficulties in Siting a New Combustion Facility
        EPA has developed a Draft Strategy for Combustion and Hazardous  Waste which sets strategic
goals pertaining to combustion facilities.   One of the primary goals of this strategy is to "establish  a
strong preference for source reduction over waste management, and thereby reduce the long-term demand
for combustion and other waste management facilities".20 The Agency proposes to accomplish this goal
in part by enhancing  public participation  in the permitting of incinerators  and boilers and industrial
furnaces (BIFs), enhancing inspection and enforcement for incinerators and BIFs,  and setting stricter
emission  controls  and limits for combustion units.  The strategy specifies that  "hazardous  waste
combustion units should be required...to meet the more stringent paniculate matter standard that is now
 applicable to  municipal waste combusters".21   "Hazardous waste combustion units" refers to non-
 incinerator BIFs, which currently burn a significant volume of hazardous waste, but which, until 1991,
 faced no RCRA regulation of their air emissions.   In addition to the disparity of the air emission
 requirements, some non-incinerator combustion units enjoy an exemption from RCRA requirements on
 the waste resulting from their combustion activities.  More stringent requirements on BIFs, which are
     20Draft Strategy for Combustion of Hazardous Waste (1993). EPA, May.
                                              10.27

-------
 currently less expensive alternatives to incineration22, may ultimately diminish the disparity between
 the cost of using BIFs and incinerators.  Moreover, in the short term, EPA will give low priority to
 considering requests for additional combustion capacity, and in the long term plans to work with states
 and hazardous waste generators to reduce the amount of process wastes going to combustion units.

        Building new combustion capability (e.g., for on-site destruction of PFPR facility wastewaters)
 could take up to 7 years, in large part because of RCRA permitting requirements, according to hazardous
 \vaste disposal experts.23  Preparing a permit application to show compliance with RCRA is especially
 difficult for cement kiln operators; some states  refuse to issue the air pollution clearances needed to
 conduct a trial burn as part of the application procedure.24

        In addition, regulations that restrict and monitor the use of BIFs are likely to emerge in the near
 future. Additional regulations could mean that BIFs, currently among the least expensive methods for
 both on- and off-site waste destruction, may become more expensive.  In sum, combustion as a method
 of waste disposal for PFPR operations is likely to become more expensive as combustion units face
 tighter environmental regulation.

        Difficulties and Costs from the RCRA Permitting Process
        Permits under the Resource Conservation and Recovery Act are required to operate incinerators
 (and cement kilns, industrial boilers, and furnaces, if these facilities are to be used for waste destruction).
 Obtaining and retaining these permits is usually a lengthy and expensive process.  Community resistance
 to permit issuance and the potential for litigation also  add to  the time and cost of obtaining permits.
 These factors further encumber the development of new combustion capability and are likely to make
 existing capacity more scarce relative to demand and more costly in the future.  These market pressures
 will likely cause the price of combustion services to increase substantially over the next decade. Thus,
 any short run economic advantage of combustion may vanish within a few years.
    •^"Outlook for Commercial Hazardous Waste Management Facilities: A Nationwide Perspective," (1992). The
Hazardous Waste Consultant, March/April.

    ^Gager, Russ (1991). "Hazwaste Landfills Struggle for Growth and Safety," Haynat World, June.
    •O4
    '"Outlook for Commercial Hazardous Waste Management Facilities: A National Perspective," (1992). The
Hazardous Waste Consultant, March/April.

                                              10.28

-------
       The application process for a new or renewed permit is costly and time-consuming.  Similar
applications must be filled out for both the state in which the facility operates and for EPA, but only the
state requires an application fee.  State fees are estimated to average $100,000.  In addition, facilities
incur other costs for preparing applications. Also, most state applications require that the facility conduct
a trial  burn to obtain information required in the application.  A trial burn is estimated to cost up to
$100,000.  Permits must typically be renewed at least every 10 years.

       Factors that affect the cost of a  permit application include:

       •      Number of units (e.g., incinerators) at the facility;
       •      Complexity of the waste being burned;
       •      Commercial versus noncommercial facilities;
       •      Cost of the trial burn; and
       •      The extent of community resistance to issuance of new, and renewal of existing, permits.

       Recently,  EPA and  states  have focused on conducting a risk assessment of the  facility to
determine the potential harm to the surrounding community.  Particular attention is given to facilities
operating in urban or agricultural areas.

       Other Changes in the Regulatory Environment
       Other likely changes in  environmental  policy and regulation also add to  the probability  that
combustion will become a less economically attractive compliance method in the future. These concerns
apply  to both  on-site  and off-site combustion.  Facilities  that choose  contract  hauling for  off-site
combustion as a means of compliance face additional liabilities for the storage and transportation of
hazardous wastewaters. On-site combustion can be subject to significant limitations due to: (1) a potential
ban on the issuance of permits for new combustion units; (2) lengthy and expensive siting and permitting
costs; and (3) increasingly negative community reaction to combustion units. Issues associated with other
likely changes in environmental policy and that affect  the choice between combustion  and pollution
prevention are discussed briefly below.
        Environmental management policy is increasingly focused on the issue of cross-media transfers
 of pollutants.  For example, contaminated wastewater that is incinerated results in hazardous ash that
                                               10.29

-------
needs to be disposed, and the airborne release of some pollutants, despite the best available scrubbers and
dry filters.  Some PAIs are therefore displaced to other media, resulting in risk to the community and
increased risk of exposure to workers and the community during storage and transfer.  Requirements for
remedial controls on  cross-media  transfers may cause combustion costs to  increase, thus making
combustion  more expensive. Pollution prevention aims to prevent cross-media transfers and the risks
associated with them by reusing and recycling PAIs instead of disposing of them.

       Another area  of increasing concern that may affect the attractiveness  of combustion  as  a
compliance  method is  the transportation cost and liabilities associated with transporting contaminated
waste streams within a site, and even more so off-site.  The cost of hazardous  waste management and
transportation will likely continue to rise in  the  future and  lessen  the economic attractiveness of
combustion.

       In  summary,   compliance with the proposed  PFPR regulation  through off-site or on-site
combustion  presents costs and  risks that may not be apparent in the  current economic environment.
Facilities that select combustion as a compliance strategy may reasonably anticipate increased costs from
additional regulations and other environmental policy trends  currently at work.
                                             10.30

-------
                                   Chapter 10 References
Anderson, Steven, and Jeanne Herb.  1992. Building Pollution Prevention into Facilitywide Permitting.
       Pollution Prevention Review.  Autumn: 415-422.

Bird, RaeLyn.  1993.  DPRA Inc., Manhattan KS.  Written Correspondence containing price data for
       agricultural chemicals.  December 3.

Coeyman, Marjorie.  1993.  WTI Battles for the Hearts and  Minds of Its Neighbors.  Chemicalweek.
       50-52.

Commerce and Industry Insurance Company.  1993. Written correspondence from a Andrew Aulisi May
       12.

Commerce and Industry  Insurance Company.  1993.   Telephone discussions with a Andrew Aulisi
       April/May.

Doane's Marketing.  1988 and 1989 Price Data for Product Active Ingredient.

Duke, Ellen and Angela Montoya. 1993. Trends in Water Pricing: Results of Ernst & Young's National
       Rate Survey. American Water Works Association Journal. May.

Ernst and Young, Inc.,  1992.  Water and Wastewater 1992  Rate Survey.

Gager, Russ.  1991.  Hazwaste Landfills Struggle for Growth  and Safety. Hazmat World. June. 46-48.

Habicht, Henry.  1992. Memorandum to All EPA Personnel Re:  Definition of "Pollution Prevention."
       May 28.

Hamaguchi,  Mikio.  1993.  Sumitomo Chemical Corporation of America.  New York, NY  Telephone
       interview on December 12.

MacKerron, Conrad,  et al.,  1988.   Environmental  Fears  Hinder  Incineration Growth.   Chemical
       Engineering, September 26.  31-37.

Mann, Patrick and Don Clark.  1993.  Marginal-Cost Pricing:  Its Role in Conservation. Management
       and  Operations.  August.

Melody, Mary.  1991.  Outlook for Commercial Hazardous Waste Management Facilities: A Nationwide
        Perspective. The Hazardous  Waste Consultant.  March/April.  4.1-4.17.

Melody, Mary.  1992. Disposal Options Kindle Cement Kiln, Incinerator Competition. Hazmat World.
        June.  28-34.

Mester Publishing Company.  1993.  Farm Chemicals Handbook 1993.  Willoughby,  Ohio.
                                            10.31

-------
Miller, Jeff.  1993. Prentice Chemical Company. Mount Vale, NJ. Telephone Interview on December
       12.

Montoya, Angela. Denver Water Department, Denver, CO.  Telephone interview of March 21,  1994.

"Outlook For Commercial Hazardous Waste Management Facilities:  A Nationwide Perspective," The
       Hazardous Waste Consultant, March/April 1992.

Roepe, Wayne. U.S EPA, Washington, D.C.  Telephone interview of March 21,  1994.

Schneider, Keith.  1993. Administration to Freeze Growth of Hazardous Waste Incinerators.  New York
       Times, May 18. p.l, col. 2.

U.S. Department of Commerce, Bureau of Economic Analysis.   1988.   Survey of Current Business,
       March.

U.S. Department of Commerce, Bureau of Economic Analysis.   1989.   Survey of Current Business,
       July.

U.S. Department  of Commerce, Bureau of Economic Analysis.  1993.   Survey of Current Business,
       October.

U.S. Environmental Protection  Agency, Office of Research and Development.   1990.   Guides  to
       Pollution Prevention: The Pesticide Formulating Industry, February.

U.S. Environmental Protection Agency,  Office of Water.   1993. Economic Impact Analysis of Final
       Effluent Limitations Guidelines and Standards for the Pesticide Manufacturing Industry.  821-R-
       93-012. September.

U.S. Environmental Protection Agency. 1993.  "Draft Strategy for Combustion of Hazardous Waste,"
       May.
                                           10.32

-------
                                       Chapter 11
     Labor Requirements and Potential Employment Benefits of an Effluent
 Guideline for the Pesticide Formulating, Packaging, and Repackaging Industry

11.0   Introduction
       Firms will need to install and operate compliance systems to comply with an effluent limitations
guideline  for  the  Pesticides  Formulating,  Packaging, and  Repackaging  (PFPR)  industry.    The
manufacture, installation, and operation of these systems will require use of labor resources.  To the
extent that these labor needs translate into employment increases in affected firms,  a PFPR rule has the
potential to generate employment benefits.  If realized, these employment benefits may partially offset
the employment losses that are expected to occur in facilities impacted by the rule. The employment
effects that would occur in the manufacture, installation, and operation of treatment systems are termed
the "direct" employment benefits of the rule. Because these employment effects are directly attributable
to the PFPR rule, they  are conceptually parallel to the employment losses that were estimated for the
facilities that are expected to incur significant impacts as a result of the PFPR rule.

        In addition to direct employment benefits, the PFPR rule may generate other employment benefits
 through two mechanisms.  First, employment effects may occur  in the industries  that  are linked to the
 industries that manufacture  and install compliance equipment; these effects are termed "indirect"
 employment benefits. For example, a firm that manufactures the pumps, piping and other hardware that
 comprise a treatment system will purchase intermediate goods and services from other  firms and sectors
 of the economy.  Thus, increased economic activity in the firm that manufactures the treatment system
 components has the potential to increase activity and employment in  these linked firms and sectors.
 Second, the increased  payments to labor in the directly and indirectly affected industries will lead to
  increased purchases from consumer-oriented service and retail businesses, which in turn lead to additional
  labor demand  and employment benefits  in  those businesses.  These effects are termed "induced"
  employment benefits.

          In view of these possible employment benefits, EPA estimated the labor requirements associated
  with compliance with the proposed PSES effluent guideline for  Subcategory C (PFPR)  facilities, as
  represented by Option 3/S.  The following discussion summarizes the findings from  this effort.  Labor
  requirements -  and thus the possible employment benefits - were estimated in two steps.  EPA first
  estimated the direct employment effects associated with the manufacture, installation, and operation of
  the PFPR compliance equipment. These effects are discussed in Section  11.1. Second, EPA considered
                                               11.1

-------
 the additional employment effects that might occur through the indirect and induced effect mechanisms
 outlined above; these effects are discussed in Section 11.2.

        On the basis of these analyses, EPA found that the PFPR regulation may yield direct employment
 requirements of about 100 full-time equivalent positions on a 10-year annualized basis. When the indirect
 and induced employment effects are included, this value increases to a range of 269  to 400 full-time
 equivalent positions.

 11.1   Estimating the Direct Labor Requirements of the PFPR Rule
        As discussed above, an effluent guideline for the PFPR industry will create demand for labor
 services for manufacturing, installing, and operating compliance equipment. EPA analyzed each of these
 components of direct labor requirements separately.  The sum of the estimated requirements for the three
 labor categories represents  the estimated total direct labor requirement, and thus  the potential direct
 employment benefit, from compliance with the PFPR effluent guideline.

        Direct Labor Requirements for Manufacturing Compliance Equipment
        EPA estimated the direct labor requirements for manufacturing compliance equipment based on
 the cost of the equipment and labor's expected contribution to  the equipment's value in its manufacture.
 Labor's contribution was estimated in dollars and was converted to a full-time employment equivalent
 based on a yearly labor cost. Each component of the calculation is discussed below.

        Cost of Compliance Equipment
        The cost of compliance equipment was estimated as part of the facility-level  impact analysis for
 the regulatory options.  Compliance equipment requirements and associated costs were estimated for each
 facility  in  the Survey that  was assessed as incurring costs.  For the labor requirements  analysis,
 compliance costs and their associated labor requirements were considered only for those facilities that
 were not assessed as a baseline closure, or as a closure or line conversion due to compliance.  That is,
the analysis considers the labor requirement effects associated only with those facilities that were assessed
as likely to comply with the rule and continue PFPR production activities.  These costs were weighted
according to  the number of  facilities each sample facility represents in the underlying PFPR industry
                                             11.2

-------
population and summed to give an aggregate compliance equipment cost for the PFPR industry. The total
estimated capital equipment cost in 1988 dollars for complying with Option 3/S is $41,405,013.

       Labor's Expected Contribution to the Equipment's Value
       Input-output tables assembled by  the Bureau  of Economic Analysis in the Department of
Commerce provide information on the composition of inputs used to produce the outputs of industries
in the U.S. economy.2 The inputs tallied in the input-output tables include the purchase of intermediate
goods, materials and services from other industries as well as the use of labor by the subject industry.
In particular, the direct requirements matrix identifies the value of each input, including labor, that is
required to produce a one dollar value of output for a subject industry. From discussions with PFPR
project engineers, the "Heating, Plumbing, and Fabricated Structural  Metal Products Industry" (Bureau
of Economic Analysis industry classification 40) was identified as the industry with output that most
nearly matches the kinds of equipment needed for compliance with the PFPR effluent guideline.  From
the direct requirements matrix, the labor input, titled compensation of employees, accounts for $0.31016
of each  dollar of output value from the Heating,  Plumbing, and Fabricated Structural Metal Products
Industry. Multiplying labor's  share of output value (0.31016) times the value of equipment purchases
for  complying with the PFPR rule ($41,405,013)  yields labor's contribution to  manufacturing the
 compliance equipment, measured in terms of gross compensation, $12,842,179 (see Table 11-1).

         In the economic impact analysis of the PFPR rule, the manufacture of compliance equipment is
 considered a one-time event that occurs at the beginning of industry's compliance activities. Accordingly,
 the  labor requirements for manufacturing  compliance  equipment  should be viewed  as  a one-time
 requirement.  Elsewhere in the PFPR economic impact analysis, the labor effects associated with facility
 impacts are presented on an annual basis, with the expectation that these job effects would persist over
 the period of  analysis.  Accordingly, to assess consistently the possible labor requirement effects from
 manufacturing compliance equipment, it was necessary to annualize the one-time labor effect.  Consistent
     1 The $41.4 million is the one-time outlay for purchasing the capital equipment estimated to be needed for
  compliance with the PFPR regulation and is not the annual cost of the capital equipment. In the economic impact
  analysis, the capital outlay is annualized over a 10-year period and the resulting value, which is part of the total
  annual cost of compliance, is much less than the $41.4 million value.
     2 See The 1982 Benchmark Input-Output Accounts of the United States, U.S. Department of Commerce, Bureau
  of Economic Analysis, December 1991 and "Benchmark Input-Output Accounts for the U.S. Economy, 1982," in
  Survey of Current Business, July 1991, U.S. Department of Commerce, Bureau of Economic Analysis. The 1982
  tables are the most current information on  the inter-industry input-output structure of the U.S. economy.

                                                11.3

-------
                                             Table 11-1
     Analysis of Possible Employment Generation Effects of an Effluent Guideline for the PFPR Industry
                                       Labor Cost                                Direct Labor
                             Total       Share of     Labor Cost Component      Requirements3
                           Weighted    Production    one-time      annual     one-time   annual
                         Expenditures    Value1        basis         basis2       basis      basis
   Direct Labor Effects From Compliance Equipment:
     Manufacturing        $41,405,013     31.02%   $12,842,179   $1,828,437
     Installation           $11,560,958     42.23%    $4,882,540     $695,164
     Operation                                                      $916,721
                373
                142
 53
 20
 27
   Total Direct Labor Effects
$3,440,322
100
   Notes:
     1  Source:  U.S. Department of Commerce, The 1982 Benchmark Input-Output Accounts of the United
     States, December 1991.
     2  Annualized over 10 years at the social discount rate of 7 percent.
     3  Number of jobs calculated on the basis of an average hourly labor cost of $17.21 and 2,000 hours per
     labor-year.
with the annualization  procedures elsewhere in the economic impact analysis, the one-time labor
compensation value was annualized over a ten-year period at the social discount rate of 7 percent.  The
resulting annual value of gross labor compensation in manufacturing compliance equipment is $ 1,828,437.

       Conversion to Full-Time Employment Equivalent Basis
       To convert the gross payment to labor to a full-time employment equivalent basis, the payment
to labor was divided by an estimated yearly labor cost. The yearly labor cost is based on the same labor
cost, $17.21 per hour, used in the engineering cost analysis to estimate the cost of operating compliance
equipment. The $17.21 per hour is a comprehensive labor cost including an allowance for fringe benefits
(e.g., holidays, vacation, and various insurances) and payroll taxes, and was calculated in 1988 dollars.
Assuming a 2,000 hour work-year, the gross annual labor  cost per full-time employment position is
$35,797.  On a one-time, one-year basis (i.e., not annualized), the outlay for manufacturing compliance
equipment is estimated  to require 373 full-time employment positions.   On .an annualized basis, the
$1,828,437 of gross labor cost for manufacturing compliance equipment  is estimated to require 53  full-
time employment positions.
                                              11.4

-------
       Direct Labor Requirements for Installing Compliance Equipment
       EPA estimated the direct labor requirements for installing compliance equipment in a parallel
manner to that used for analyzing the labor requirements for manufacturing compliance equipment. Each
component of the calculation is discussed below.

       Cost of Installing Compliance Equipment
       The cost of installing compliance equipment was estimated in conjunction with estimating the
purchase  cost of compliance equipment.  Specifically,  on the basis of the kind,  scale,  and cost of
compliance equipment assessed for a facility, PFPR project engineers estimated an installation cost for
the equipment.  The estimated installation costs averaged about 28 percent of the purchase cost of the
compliance equipment for a total of $11,560,958.

        Labor's Expected Contribution to the Equipment's Value
        The Bureau of Economic Analysis  industry group that EPA used as the basis for estimating
 labor's share  of cost in installing compliance equipment is the "Repair and Maintenance  Construction
 Industry" (Bureau of  Economic Analysis industry classification 12).   In this industry group, gross
 payments to  labor account for $0.42233 of each dollar of output value, as recorded  in  the direct
 requirements matrix for the national input-output tables. Multiplying labor's share of value (0.42233)
 by the estimated total installation cost ($11,560,958) yields a gross labor cost for compliance equipment
 installation of $4,882,540. Like the purchase cost of compliance equipment, the installation cost is a one-
 time outlay and, accordingly, an annualized value was calculated using the 10-year amortization period
 and the  7 percent social  discount rate.  The resulting annual value for the labor cost of installing
 compliance equipment is $695,164.

         Conversion to  Full-Time Employment Equivalent Basis
         Conversion to a full-time employment equivalent basis is based on the same yearly labor cost,
  $35,797, as  used in estimating the labor requirements for  the manufacturing of compliance equipment.
  On a one-time, one-year basis, EPA estimates that 142 full-time equivalent positions would be required
  for installing the equipment needed to comply with the proposed Option 3/S PFPR effluent guideline.
  Annualized over 10 years, the corresponding labor requirement for installing compliance equipment is
  20 full-time equivalent positions.
                                                11.5

-------
        Direct Labor Requirements for Operating Compliance Equipment
        PFPR project engineers estimated the annual labor hours  required to  operate compliance
 equipment as the basis for assessing the annual operating and maintenance costs of the PFPR regulatory
 options. On a full-time equivalent basis, the estimated annual labor requirement for operating compliance
 equipment is 27 person-years. This value is assumed to recur annually over the period of analysis. The
 corresponding total annual estimated payments to labor is $916,721 (1988 dollars).

        Total Direct Labor Requirements for Complying with the PFPR Effluent Guideline
        Summing the three components yields  the total  direct labor requirements for complying with the
 proposed PFPR effluent guideline  as represented by Option 3/S.  On a full-time equivalent basis, the
 estimated total annual labor requirement for  complying with Option  3/S  is 100  person-years.  The
 corresponding total annual estimated payments to labor is $3,440,322 (1988 dollars).  To the extent that
 these labor requirements manifest as net  new  labor  needs in the U.S. economy,  the  100  full-time
 employment equivalents have the potential to offset employment losses that may otherwise occur because
 of the rule.

 11.3   Estimating the Indirect and Induced Labor Requirement Effects of the  PFPR Rule
        In addition to its direct labor effects, the  PFPR effluent guideline may  also generate labor
 requirements through the indirect and induced effect mechanisms described in the introduction to this
 chapter. The indirect and induced  effects associated with an economic activity are analyzed by use of
 multipliers. Multiplier estimates generally vary with the industry in which the direct economic activities
 are expected to occur and with the economic characteristics of the location of the  direct activities.

        A range of multipliers was used in  this analysis to illustrate the possible aggregate employment
 effects of a PFPR effluent guideline.  A recent EPA study used multipliers ranging from 3.5 to 3.9 to
 calculate the possible indirect and induced employment effects  of direct activity investments in general
 water treatment and pollution control.3  A study of "clean water investments" commissioned by the
 National Utility Contractors  Association (NUCA)  documented total employment  effect   multipliers
 ranging from 2.8 to 4.O.4 Using the high and  low values for these multipliers, the  indicated aggregate
   3U.S. Environmental Protection Agency, Office of Water (February 1993). Job Creation Fact Sheet, internal
document.

     Apogee Research, Inc., A Report on Clean Water Investment and Job Creation, prepared for National Utility
Contractors Association, March 1992.

                                              11.6

-------
employment effects associated with the direct labor requirement of 100 full-time positions would range
from 280 to 400.

        A more  conservative assessment of these possible employment effects would recognize that the
three categories  of labor requirements analyzed above are likely to have different indirect labor demand
effects. In particular, the direct labor demands for manufacturing and installing compliance equipment
result from additional economic activity in those industries. Accordingly, it is reasonable to expect that
the additional economic activity in manufacturing and installing equipment will translate into increased
activity in the industries that are linked to the direct effect industries and, hence, lead to additional labor
demand in those industries through the indirect effect mechanism.  In contrast, the increased labor
demand in  the  PFPR industry for  operating compliance equipment does  not result from increased
economic activity in that industry.  As a result, increased labor demand in the PFPR industry resulting
from the PFPR effluent guideline may not translate  into increased labor requirements in the industries
that are linked  to  the PFPR industry.  In this case, the appropriate employment multiplier for the
equipment-operations  component of  direct labor   requirements  should  exclude the  indirect effect
 mechanism and include only the induced effect mechanism.   Multipliers  cited in the NUCA study
 referenced above suggest that a multiplier based only on the induced effect mechanism might fall in the
 range of 2.4 to  2.9. Using this lower multiplier range for the equipment-operations component of direct
 labor requirements and the higher, 2.8 to 4.0 range for the manufacturing and installation components,
 the estimated aggregate employment effects of the PFPR effluent guideline would range from 269 to 371
 full-time equivalent positions.
                                                11.7

-------
                                   Chapter 11 References

Apogee Research, Inc. (March 1992).  A Report on Clean Water Investment and Job Creation, prepared
       for National Utility Contractors Association.

U.S. Department of Commerce (1992).  Bureau of Economic Analysis, Regional Multipliers:  A User
       Handbook for the Regional Input-Output Modeling System (RIMSII).  Washington, D.C.

U.S. Department of Commerce (1991).  Bureau  of Economic Analysis, The 1982 Benchmark Input-
       Output Accounts of the United States.

U.S. Department  of Commerce (1991).  Bureau of Economic  Analysis,  "Benchmark Input-Output
       Accounts for the U.S. Economy, 1982," in Survey of Current Business, July 1991.

U.S. Environmental Protection Agency,  Office of  Water (February 1993).  Job Creation Fact
       iSfceef,internal document.
                                           11.8

-------
                                        Chapter 12
         Assessment of Economic Impacts Of Including Under Regulation
                Additional PAIs Not On the Original List of 272 PAIs

12.0   Introduction
       EPA used facility and compliance cost data based on 272 PAIs to analyze alternative PSES
regulatory options for Subcategory C (PFPR) facilities as presented in the preceding chapters.  These 272
PAIs are the same as those PAIs whose discharges were originally considered for regulation under the
recently promulgated effluent limitation guideline for the Pesticide Manufacturers Industry. As described
in the  preceding chapters of  this EIA, EPA specified 5 PSES regulatory  options for  Subcategory C
facilities and  initially selected Option 3 as the preferred option.   EPA  found that this option was both
economically achievable and met the objectives of the Clean Water Act by achieving zero discharge of
specified pollutants from PFPR facilities.  Subsequent analysis of the distribution of likely economic
impacts led EPA to modify Option 3 to mitigate impacts among small business-owned facilities that
primarily serve the industrial/commercial market and that use certain  lower toxicity sanitizer PAIs to
formulate, package and repackage sanitizer products. Specifically, the modified  option, Option 3/S, is
the same as Option 3 except  for those facilities that formulate, package, or repackage  sanitizer active
ingredients and whose sanitizer production is less than 265,000 pounds per year.  In  these facilities,
discharges from  non-interior wastewater sources containing only designated sanitizer chemicals  are
exempt from the zero discharge requirement.

        EPA proposes to include under the proposed regulation all additional PAIs beyond the list of 272
PAIs on which detailed data were gathered in the PFPR industry Survey and  on which the detailed
 analyses presented in preceding chapters are based.  Accordingly, EPA estimated the economic impacts
 of including these  additional PAIs under the proposed PSES regulation for Subcategory C facilities,
 Option 3/S.1  Although EPA estimates additional economic  impacts as  a  result of  including these
 additional PAIs under regulation, EPA finds that the proposed regulation remains economically achievable
 overall and, by virtue of including the additional PAIs  under  regulation,  promotes more strongly the
 pollution reduction objectives of the Clean Water Act.
     lln the remainder of this chapter, the additional PAIs not on the original list of 272 PAIs are referred to as the
  "additional non-272 PAIs" or "non-272 PAIs."
                                               12.1

-------
        This chapter presents the estimated economic impacts of including these additional PAIs under
 the proposed PSES regulation for Subcategory C facilities.  The regulatory option considered in  this
 chapter is the same  as the Option 3/S discussed in the preceding chapters with the exception that its
 regulatory coverage is broadened to include the additional non-272 PAIs.  To distinguish the analysis of
 the proposed regulation including the non-272 PAIs from the preceding analysis based on only the  272
 PAIs, the following discussion refers to the regulation including coverage of the additional non-272 PAIs
 as Option 3/S'.2

        The rest of this chapter largely parallels the discussion presented in the preceding chapters.
 Section 12.1 presents the estimated economic impacts on PFPR facilities of regulating the additional non-
 272 PAIs. Section 12.2 reviews regulatory flexibility considerations of the proposed option.  Community
 impacts of including the additional non-272 PAIs are presented in Section  12.3, with foreign trade effects
 assessed in Section 12.4. Section 12.5 discusses the estimated impacts on firms owning PFPR facilities.
 Finally, Section 12.6 describes  the labor requirements and possible employment benefits of complying
 with the proposed option covering the additional non-272 PAIs.

 12.1   Estimated Facility Impacts Under Option 3/S'
        The  analysis was  conducted on two separate  sets of facilities:  (1) facilities that  formulate,
 package,  or repackage the original 272 PAIs  and that may also use the additional non-272 PAIs3, and
 (2) facilities that use only the additional non-272 PAIs in their pesticide formulating,  packaging and
 repackaging activities.  These separate analyses were then combined to calculate the aggregate facility-
 level effects on the PFPR industry.

        Facilities Using Both Original 272 PAIs and Additional non-272 PAIs
        Compliance cost estimates were developed for the first set of facilities under Option 3/S', which
 extends regulation to the additional non-272 PAIs. The methodology for analyzing impacts among these
 facilities is identical to that described in Chapter 4. In addition, EPA used data on the usage of the non-
 272 PAIs  obtained from the FATES database to supplement the data developed and analyzed on the basis
        Federal Register Notice for this regulation refers to this option as Option 3/S.l.
   3Sixty-four percent of the facilities that PFPR the 272 PAIs originally considered for regulation also PFPR non-
272 PAIs.

                                              12.2

-------
of the 272 PAIs.  Table 12.1, below, presents the estimated costs and impacts of this regulatory option,
Option 3/S', for facilities using both original 272 PAIs and additional non-272 PAIs, and compares these
costs and impacts with those previously presented for Option 3/S.

       The compliance costs and impacts for these facilities under Option 3/S' are somewhat higher than
calculated under Option 3/S.  As a result of the compliance requirements for the additional PAIs, EPA
estimates that 544 Subcategory C facilities using both original 272 PAIs and additional non-272 PAIs will
incur costs, an increase of 15 facilities beyond the 529 facilities estimated under Option 3/S. The capital
and annualized total costs (which include amortized capital, annual operating and maintenance,  and
monitoring costs) of complying  with Option 3/S' are estimated to be  $102.9 and  $40.1 million,
respectively.  The $40.1 million in total annualized compliance costs represents an increase of $15.0
million above the estimated total annual cost for complying with Option 3/S among these facilities.  The
associated facility and employment impacts among these facilities are also somewhat larger under Option
3/S'.  The estimated number of facility closures, 1, is the same for both Option 3/S and Option 3/S',
while the number of moderate impacts increases from 136 under Option 3/S to  167 under Option 3/S'.
The estimated total U.S. job losses remains modest, increasing from 355 FTEs under Option 3/S to 470
FTEs under Option 3/S'.   As described in Chapter 4, the job loss estimates are conservative in that the
analysis assumes full loss of PFPR-related employment among facilities  assessed as line conversions as
well  as full loss of employment in facility closures.

        Facilities Using Only the Additional Non-272 PAIs
        To estimate the impact on the second set of facilities — those facilities that formulate, package
 or repackage only the additional non-272 PAIs — EPA  assumed that  these facilities were similar in
 several ways to those facilities surveyed and analyzed on the basis of using the 272 PAIs:

 «      The percentage of water dischargers  is the same for both sets of facilities;
 •      The percentage of facilities using only the non-272 PAIs and that incur compliance costs under
        Option 3/S' is the same as that estimated for facilities  analyzed as using only the original 272
         PAIs under Option 3/S;
 •      Facilities using only the non-272 PAIs will have the same average compliance cost under Option
         3/S' as estimated for those facilities using only the 272 PAIs under Option 3/S; and
                                               12.3

-------
                                          Table 12.1
                      National Estimates of Costs and Impacts under PSES
                           Comparison of Option 3/S' with Option 3/S
                                                Option 3/S (original 272
                                                      PAIs only)
                 Option 3/S' (original
                272 and non-272 PAIs)
Facilities Not Eligible for Sanitizer PAI Exemption
*# of Facilities Projected to Incur Costs
•Total Annualized Compliance Costs     •"'
(million dollars)
•Facility Closures
(Severe Impacts)
•Moderate Impacts
•Expected Job Losses
 391
$24.0

  1

 119
 348
 391
$35.1

  1

 126
 418
Facilities Eligible for Sanitizer PAI Exemption
•# of Facilities Projected to Incur Costs
•Total Annualized Compliance Costs
(million dollars)
•Facility Closures
(Severe Impacts)
•Moderate Impacts
•Expected Job Losses
 138
 $2.1

  0

  17
  7
 153
 $5.0

  0

 41
 52
All Subcategory C Facilities (except those using
only additional non-272 PAIs)
•# of Facilities Projected to Incur Costs
•Total Annualized Compliance Costs
(million dollars)
•Facility Closures
(Severe Impacts)
•Moderate Impacts
•Expected Job Losses
 529
$26.1

  1

 136
 355
 544
$40.1

  1

 167
 470
Note: Based on analysis of only those facilities that use original 272 PAIs or that use both original 272
PAIs and additional non-272 PAIs;  excludes facilities that use only non-272 PAIs.
      The percentage of facilities using only the non-272 PAIs and that are assessed as closures or
                                              12.4

-------
       moderate impacts is the same as that estimated for facilities analyzed as using only the original
       272 PAIs under Option 3/S.

       On the basis of these assumptions, EPA estimated that 424 facilities using only non-272 PAIs will
incur compliance costs under Option 3/S'. Of these, 311  are PFPR-only facilities and 13 are PFPR and
manufacturing facilities.  In addition, EPA estimated that facilities using only non-272 PAIs will incur
total annual compliance costs of $16.0 million, of which $10.2 million is in PFPR-only facilities and $5.8
million in PFPR and manufacturing facilities.  The corresponding impact estimates are one facility closure
and  83 moderate impacts, all of which are estimated to occur among PFPR-only facilities.  No impacts
are expected among PFPR/manufacturing facilities using only non-272 PAIs (see Table 12.2).

        Aggregate Impacts for All Facilities Using Both Original 272 and Additional non-272 PAIs
        The aggregate costs and impacts for Option 3/S' are the combined impacts for both:  (1) facilities
using both the original 272 PAIs and additional non-272 PAIs; and (2) facilities using only the additional
non-272 PAIs. Summing the results for the separately analyzed facility groups, EPA estimated that 869
 Subcategory C facilities will incur costs under Option 3/S' (see Table 12.3). The total annualized costs
 (which include amortized capital, annual operating and maintenance, and monitoring costs) of complying
 with Option 3/S'  are estimated at $56.1 million. From this analysis, two Subcategory C facilities were
 assessed as closures  as the result of the Option 3/S' compliance requirements while 250 facilities were
 assessed as incurring moderate impacts.  In addition, EPA conservatively estimates total job losses in
 impacted facilities at 688 full-time employment positions.4   EPA  finds that the proposed  effluent
 limitation guideline for Subcategory C facilities, Option 3/S', which includes coverage of the additional
 non-272 PAIs, is economically achievable.

         Option 3/S'  is estimated to achieve a total of 310,455 pounds of pollutant removals annually or
  198,662 pounds  more than that achieved by Option 3/S.5  The residual pollutant loadings under Option
  3/S'  are 1,036 pounds or 833 pounds more than under  Option 3/S.  However, as discussed previously,
      4-These job-loss estimates are considered conservative because EPA assumes that both facility closures ^ PFPR
  line conver ions will result in full loss of all PFPR-related employment at affected facihhes  EPA believe,,  hatttu
  assumption overstates expected employment impacts because line conversions are not likely to cause employment
  losses in all cases.
      5The toxic pounds that this represents will be calculated for final.
                                                 12.5

-------
                                             Table 12.2
         Estimated National Impacts for PFPR Facilities Using Only Additional Non-272 PAIs
                (Estimates for "non-272 PAI only" facilities based on extrapolation of
                    results from detailed analysis of facilities using only 272 PAIs)
                                                     Results from
                                                   Detailed Analysis
                                                      of Facilities
                                                    Using Original
                                                       272 PAIs
Percentage of
 Facilities in
  Preceding
 Population
   Group
Estimates for
  Facilities
 Using Only
 Additional
  Non-272
Estimated Number of Facilities in Business
Estimated Number of Facilities that Use Water
Estimated Number of Facilities that Discharge
Estimated Number of Facilities that Discharge
and Incur Compliance Costs
-PFPR only
- PFPR and Manufacture
Estimated Total Annual Compliance Cost ($
MM, 1588)
• PFPR only
- PFPR and Manufacture
- Total
Total Annual Compliance Cost, Average per
Facility ($, 1988)
-PFPR only
- PFPR and Manufacture
Estimated Number of Facility Impacts
-PFPR only
Closures
Moderate Economic Impacts
« PFPR and Manufacture
Closures
Moderate Economic Impacts
2,404
1,794
656
507
22
$16.7
$9.4
$26.1
$32,871
$429,065
1
136
0
0

74.6%
36.6%
77.4%
3.4%


0.2%
26.8%
0.0%
0.0%
1,475
1,101
402
311
13
$10.2
$5.8
$16.0*
$32,871
$429,065
1
83
0
0
  Percentage calculations are based on findings from detailed analyses of facilities using 272 PAIs.  Each
percentage value indicates the share of the preceding population group (for facilities using 272 PAIs) that is
estimated to fall in that row's named population category.  For example, of the 2,404 PFPR facilities using
272 PAIs, 1,794 or 74.6 percent are estimated to use water.

* Within the 1,475 facilities estimated to use only the non-272 PAIs, the estimated number of facilities
falling in each population group (e.g., water-users or facilities incurring impacts) is  based on applying the
relevant percentage from the analysis of PFPR facilities using the 272 PAIs.  For example, of the  1,475
facilities using only non-272 PAIs, 74.6 percent or 1,101 facilities are estimated to use water.

* The estimates of average facility and total annual compliance cost for non-272 PAI facilities are based on
he estimated average  facility costs for facilities using only the original 272 PAIs.   That is, the  average
facility annual compliance costs of $32,871 and $429,065,  which were calculated from analysis of only the
original  272 PAIs, are  assumed to apply also for the non-272 PAI facilities.   The aggregate annual
compliance cost values for  facilities using only non-272 PAIs were then calculated by multiplying the
average costs per facility by the estimated number of facilities in the relevant non-212 PAI facility category
p.g., 311 PFPR-only facilities x $32,871/per facility =  $10.2 million total annual cost for PFPR-only
'acilities using only non-272 PAIs).
                                              12.6

-------
                                             Table 12.3
                      National Estimates of Costs and Impacts for PSES Option 3/S'
           Including Subcategory C Facilities Using Both Original and Additional Non-272 PAIs,
                           and Facilities Using Only Additional Non-272 PAIs
                                  (Assuming Zero Cost Pass-Through)
                                                                                 Option 3/S'
   Facilities Using Both Original 272 PAIs and Additional Non-272 PAIs
   ®# of Facilities Projected to Incur Costs
   "Total Annualized Compliance Costs
   (million dollars) *
   •Facility Closures:
   (Severe Economic Impacts)
   •Moderate Economic Impacts
   •Expected Job Losses (FTEs)
544
$40.1

  1

167
470
   Facilities Using Only Additional Non-272 PAIs
   •# of Facilities Projected to Incur Costs
   •Total Annualized Compliance Costs
   (million dollars)*
   •Facility Closures:
   (Severe Economic Impacts)
   •Moderate Economic Impacts
   •Expected Job Losses (FTEs)
325
$16.0

  1

 83
218
   All Facilities
   •# of Facilities Projected to Incur Costs
   •Total Annualized Compliance Costs
   (million dollars)*
   •Facility Closures:
   (Severe Economic Impacts)
   •Moderate Economic Impacts
   •Estimated Worst-Case Job Losses (FTEs)
869
$56.1
250
688
   * Total annualized compliance costs are in 1988 dollars.
all of the residual loadings are among the designated sanitizer PAIs, which have relatively low toxicity.
As a  result, on a toxic-equivalent weighted basis, the estimated residual loadings under Option 3/S'
amount to only 196 toxic-weighted pounds annually. In contrast, EPA estimates that the pre-compliance
discharges,  adjusted  for  toxicity,  amount to  nearly  34 million  toxic-weighted pounds annually.
Accordingly, the residual discharges,  adjusted for toxicity,  are an insignificant fraction of the pre-
                                              12.7

-------
 compliance amount (see the Cost-Effectiveness Analysis report for additional detail on the unweighted
 and weighted removals achieved by the proposed regulatory option).

 12.2   Regulatory Flexibility Considerations of Option 3/S'
        For the reasons discussed hi the Regulatory Flexibility Analysis presented in Chapter 5,  EPA
 decided to retain the exemption for designated sanitizer PAIs in extending the proposed PFPR regulation
 to include the additional non-272 PAIs. As documented in Chapter 5, without this exemption, facilities
 owned by small entities that operate primarily in the institutional/commercial (I/C) market were found
 to bear disproportionate impacts. To prevent disproportionate impacts from occurring under the revised
 Option 3/S' and in recognition that the additional number of toxic pounds of pollutants discharged would
 be very small, EPA proposes to include designated sanitizer PAIs within the additional non-272 PAIs
 under the scope of the exemption.

 12.3   Community Impacts of Option 3/S'
        EPA assessed community impacts under Option 3/S' in terms of projected employment losses
 using the same analytic procedure as described in Chapter 6.  Even though the assumptions underlying
 this analysis are more conservative than those underlying the community impacts analysis for regulation
 of the original 272 PAIs, the estimated maximum MSA-level employment losses are well less than the
 one-percent threshold considered significant.

        The methodology used in this analysis is essentially the same as that used in Chapter 6, with an
 additional conservative assumption to capture the employment losses estimated for facilities using only
 the additional non-272 PAIs.  As explained in  Chapter 6,  a statistically valid analysis of population-level
 employment impacts on a regional  or community level cannot be  performed because of sample design
 limitations.  However, analyses based on assumptions regarding the locational distribution of primary
 employment impacts can demonstrate that compliance with the proposed regulation is unlikely to have
 a significant impact on community employment.

      . As described hi Chapter 6, EPA used conservative assumptions that are likely to overstate
possible employment losses in any one MSA.  First, EPA assumed that both closure and line conversion
impacts would result in the loss of all PFPR-related employment at affected facilities. As stated above,
line conversions are not likely to result in a full loss of PFPR-related employment in all cases. Second,

                                             12.8

-------
EPA assumed that all of the direct impact employment losses that are not directly accounted for by the
affected sample observations would occur at the known locations  of the affected  sample facilities in
proportion to sample facility weights.  Third, as before, EPA used the maximum state-level multiplier
(9.2)  for the applicable industry to estimate the secondary employment impacts.  Thus,  the  analytic
procedure and assumptions for addressing impacts within those facilities using the original 272 PAIS and
the additional non-272 PAIs are identical to those described in Chapter 6.
        However, analysis of the employment-related impacts in facilities using only the additional non-
272 PAIs required a modification to the analytic procedure described in Chapter 6.  The impacts in these
facilities are not associated with specific sample  facilities and are thus conceptually similar to those
impacts estimated to occur within the underlying population of PFPR facilities and not in specific sample
facilities as discussed in Chapter 6.  That is, EPA knows none of the locations of these facilities using
only non-272 PAIs and assessed as incurring impacts. To account for the estimated impacts in these non-
272 PAI-only facilities in the community impact analysis, EPA calculated an impact multiplier that was
used to increase the sample facility weights for those sample facilities assessed as incurring impacts.  In
this way, the weights for impacted  sample facilities encompassed the impacts among both classes gf
facilities considered in this analysis: (1) facilities using the original 272 PAIs and additional-non-272
PAIs; and (2) facilities using only the additional non-272 PAIs.

        The multiplier developed to  account for facilities using only non-272 PAIs was calculated as the
ratio  of the estimated total of impacted facilities among all PFPR facilities (i.e., both classes of facilities
defined in the preceding sentence) to the estimated number of  impacted facilities among facilities using
the original 272 PAIs  and  additional  non-272 PAIs (i.e., the first class of facilities defined in the
preceding sentence). Specifically, as summarized above in Table 12.3, EPA estimated a total of 252
facility impacts under Option 3/S':  2 facility closures and 250 moderate economic impacts. Of the 252
impacts,  168 are within facilities using the original 272 PAIs and additional non-272 PAIs (1 closure and
 167 moderate impacts), and 84 are within facilities using only the additional non-272 PAIs (1 closure and
83 moderate impacts) (see Table 12.3). Thus, the ratio of impacts in all facilities to impacts in facilities
using the original 272 PAIs and additional non-272 PAIs is 1.5 (252 / 168 = 1.5).  Thus, to account for
the estimated impacts in the non-272 PAI-only facilities in the community impact analysis, EPA increased
the estimated impacts associated with sample facilities by multiplying the weights of impacted sample
 facilities by 1.5.

                                                12.9

-------
         Use of the 1.5 multiplier to account for impacts among facilities using only non-272 PAIs is yet
  another  conservative assumption  that is  likely to overstate community-level  employment  impacts.
  Specifically, use of the multiplier means that MSAs in which sample facilities are located are assumed
  to incur, in proportion to sample facility weights, the additional employment impacts associated with non-
  sample facilities among those analyzed using  both the original  272 PAIs and non-272 PAIs and  the
  employment impacts associated with facilities using only non-272 PAIs.    EPA believes that this
  assumption further exaggerates the impacts calculated for sample facility MSAs, as these impacts would
  likely be distributed among other MSAs that are unknown.

        The analysis of sample facility impacts for Option 3/S' found that impacts occur among 25 MSAs,
 which  is a modest increase above the 22  MSAs incurring  impacts under Option 3/S as discussed in
 Chapter 6. However, even with the  conservative  assumptions  underlying this  analysis, no MSA is
 expected to incur a significant loss of employment under Option 3/S'. The largest percentage decline in
 employment calculated for any MSA is only 0.2 percent or well less than the significant impact threshold
 of one percent.  If the impacts in this  MSA are assessed on the basis of the state-specific employment
 multiplier, the percentage employment  loss would be only 0.075 percent.  Even this amount exaggerates
 the likely impact because of the assignment of all non-sample facility impacts to the same MSA in which
 the impacted sample facility(ies) are located.

        Accordingly,  EPA anticipates no significant  community-level impacts under Option 3/S'.

 12.4   Foreign Trade Effects Under  Option 3/S'
        EPA assessed the foreign trade  impacts of Option 3/S' using the same methodology as described
 in Chapter 7.  As described above in the analysis of community impacts, EPA accounted for the impacts
 in facilities using only non-272 PAIs by increasing the facility weights for impacted sample facilities by
 a factor of 1.5. As in  Chapter 7, EPA analyzed foreign trade impacts under the proportional case, which
 assesses trade impacts  based on the relative competitiveness of U.S. and foreign producers in international
 markets. From this analysis, EPA estimated that Option 3/S'  would result in a $16,538,000 decrease in
 the pesticide trade balance, or a decline  of 1.74 percent.  This 1.74 percent decrease is well less than the
 average 8 percent year-to-year fluctuation in the pesticides trade balance that occurred between 1980 and
 1990. Overall, EPA judges that the foreign trade impacts of the proposed  regulation are not likely to be
significant.
                                            12.10

-------
12.5   Firm-Level Impacts of Option 3/S'
       EPA also examined the potential firm-level impacts of Option 3/S'. As in Chapter1 8^ a firm-level
analysis was conducted for all firms which own at least one sample facility that uses water in its PFPR
operations,  and therefore for which financial  data  were  available.   Because of  sample design
considerations, the findings from the firm-level analysis, which is based onfacilities in the sample survey,
cannot be extrapolated on a statistically valid basis to the population level of PFPR industry firms.  In
addition, because the impacts and compliance costs incurred by facilities using only the non-272 PAIs
cannot be associated with specific sample facilities  and owning firms, the firm-level analysis does not
include any effects associated with these facilities.  However, the firm-level  impact analysis does reflect
the higher costs among sample facilities of controlling discharges from non-272 PAIs — that is, the higher
costs of complying with Option 3/S' relative to Option 3/S.

        The methodology used to calculate firm-level impacts is identical to the methodology used in
 Chapter 8.  Estimated  compliance costs under Option 3/S'  were allocated to  facilities participating in
 PFPR activities owned by the firm but  not included in the sample.  As in Chapter 8, the firm-level
 financial impact was assessed on the basis of the change in pre-tax return on assets (ROA) and compared
 with a threshold value based on the lowest quartile data for SIC codes in the 2800 group (Chemicals and
 Allied Products) of 2.396 percent.6

         Of the 242 firms considered for impacts under Option 3/S', 9 firms were found to have a post-
 compliance ROA of less than 2.396 percent and are therefore assessed as incurring adverse financial
 impacts as  a result of regulatory compliance. Six of these nine firms are private single entities and three
 are private multi-facility firms.  No firm impacts were found among public-reporting firms. EPA judges
 that these firm-level impacts should not pose a significant burden to the PFPR industry and affirms its
 conclusion that the PFPR regulations being proposed will be economically achievable by the industry (see
 Table  12.4).
      6 The threshold value ROA (2.396 percent) was calculated by weighting the ROA for all available SIC codes
  in the 2800 group by the total value of shipments of that group.
                                               12.11

-------
                                           Table 12.4
                    Estimated Sample Firm Financial Impacts Under Option 3/S'
               Firm Type
          Public-Reporting Firms
        Private Multi-Facility Firms
                                           Baseline
Number of
 Projected
  Impacts
Number of
  Firms
Considered

   ~36
                                Post-Compliance
Number of
 Projected
  Impacts
    =
    0
Number of
  Firms
Considered

   ~36~
    0
    92
                                                                                 92
        Private Single Entity Firms
    66
                 180
                                                                                 114
                  Total
                                       66
                 308
                                                                                242
 12.6   Potential Labor Requirements of Complying with Option 3/S'

        As discussed in Chapter 11, EPA recognized that the manufacture, installation, and operation of
 equipment for complying with the Option 3/S' regulation would require use of labor resources. To the
 extent that these labor needs translate into employment increases in complying firms, the regulation has
 the potential to generate employment benefits that may partially offset the employment losses that are
 expected to occur in facilities impacted by the rule. Using the same methodology as described in Chapter
 11, EPA estimated an annual direct labor requirement of 200 full-time equivalent positions for complying
with the Option 3/S' regulation. Of these 200 positions, 139 are estimated to result from compliance with
Option 3/S'  among facilities using 272 and non-272 PAIs and 61 are estimated to occur among facilities
using only non-272 PAIs.  This labor requirement may partially offset the estimated 688 employment
losses in impacted PFPR facilities (see Table 12.5).
                                          Table 12.5
         National Estimates of Employment Losses and Possible Offsetting Employment Gains
              Based on Analysis of All Subcategory C Facilities Under PSES Option 3/S'
                                                                 :    Estimated Values
                                                                  (FuU-Time Equivalents)
     Estimated Employment Losses Under Option 3/S'
           Employment Losses from Facility Closures
           Employment Losses from Line Conversions
           Total PFPR Facility Employment Losses
                                         356
                                         209
                                         688
     Estimated Labor Requirements and Possible Offsetting Employment Gains Under Option 3/S'
           Labor Requirements for Manufacturing Compliance Equipment             107
           Labor Requirements for Installing Compliance Equipment                  41
           Labor Requirements for Operating Compliance Equipment                  52
           Total Labor Requirements for PFPR Regulatory Compliance    	  200
                                            12.12

-------
                                      Appendix A
  Pesticide Formulating, Packaging, and Repackaging Facility Survey for 1988

       This appendix provides Part B of the Pesticide Formulating, Packaging, and Repackaging Facility
Survey for 1988, which served as one of the main data sources for the EIA.  Part B requested detailed
economic and financial data from the facilities, including balance sheet and income statement information
for 1986, 1987, and 1988 from water-using facilities.
                                           A.I

-------
                    U.S. ENVIRONMENTAL PROTECTION AGENCY


            PESTICIDE FORMULATING. PACKAGING. AND REPACKAGING
                            FACILITY SURVEY FOR 1988


                PART B - FINANCIAL AND ECONOMIC INFORMATION
                                TABLE QF CONTENTS
 Purpose
Additional Submissions	

Authority	


Data Confidentiality	


Questions	.		
                   *

Section 1: Faciiity Financial and Economic Information,


Section 2: Firm Financial Information	
     Page

      B-1
	  B-1


	  B-2


	  B-2


	  B-2


...........  B*3


	  B-17
                                      A.2

-------
                  U.S. EHVIHONMENTAL PROTECTION AGENCY   -, •  • ;
-------
       :.Tt8f tn« rour-aiQK SIC ,'3tanaara :naustnai CUamcanoni Coaas aerinea cv trta 1987 Standard irausinai
                  M*n»mi tnat aooty to t~is racyitv.  ,n aaaitton to tne onmarv SIC Code, reoon tne saconoarv
       ana tertiary SIC Codes. rf aococaae.  I saconaarv or ternary coaes are not aooucana. cnecx tno oox
       aoeiea ^
                                                                            SIC-4*
       3.
            =rimarv SIC Coda
            Saconoarv SIC Cods
                                                                                           NA
            Teniarv SIC Coda.
      !s this faculty's onysxal location tne same as its mailing address?

                                  r             Yes	r>  1  (Sklato.Q.7)
                                                No	;_,  2  (Comnuet
6.    Print the street address of the facdttys physical location.
       Physical iocaoon: snm. or mausnai oarx
                             i   i  i  i   i
                                                                          '  PI R
                                                                          -~ <^. \ i
                                                                 i  i  '  t   i  -.1  i
       City
                                                       Stata     Zip ccca
7.     What wara tna sort and end morons of your facility's 1968 Pestiddas Report for Pestidda-Proauonq
      Estadlshmana (EPA Form 3540-16)?  (Use 01 * January, 02 * February, etc)
a.     1 988 Pestidda Report Start Momn

b.     i38aPeabddaflaoort End Montn
                                                       Start Year

                                                       End Year
       Urtaaa fats* yaar to spaorlad. ad Information reported In this quaationraura shoutd ba for ma same i
       report yaar as tfM hrfonnamm orovided  In your 1968 Pestiddas Report for PetMdria Producing |
       EstatUshmara (EPA Form 3540-16).
                                             A.4

-------
                                                                              B Hesconaent
                                3EGISTSHED PRODUCTS UST
     The yeuow. dut. ana gn«n page, rat fodow comaui .ists of Dramas
         founa on Tatte 1 .  ">«« '^ vw« oocajnea tram your 1388. 1987. ana  1966 EPA
        <£££ P^^Tuonq e^^m^nca «EPA Form 3540.l6.Cdor* oa^rns, DM. u«a to
arfferentate wtwaen ttw yew yatowtor 1988. Uiw tor 1987. ana qrwntor i98a

     You are REQUIRED to correct ONLY your 1988 Hat  after Oecemoer

31. 1988.
                                              A.5

-------
 3.
       n 1988. ware any or me oroauca ustaa on ma 1 988 (vaiowi flegaterea Proauas Ust fomt
       'acurtv?


                  Formulation a tna process mixing, DJenaing, cr diluting ona or more acava
                  'ngrealents wnti  ona or more orner oesuoaa acuve  or man ingredients,
                  
-------
-vhat tvo® of Qf^Rsssson oaai aeacnoes ins ownsrsnio cr tnis facaitv on tne &e. dav of ths rts«ai
artalng in tSil?
                                  i. i. a.. tn@
                       tH§ firm are on© ana tne same
              A mutM§8^Sy eonsanv. i.a.. your mm
              owns two or more tacsa^	
                    A
                          . e.g.. a grauo ol fam^rs
                              dtenaut®
                                 agency, excaoi
                                                          (Cheess on/v on»j
                                                                   4
              A mitey ©r d@f@m® organization	r] 5

           j   A     gov®fnms«« agsncy	Q 8

           1   A Soe^ ^a^erreri^s agancy		Q 7

                            __™_	:	38
                                                                        (oQ.13)
13.    Print the
  -  "controUIng orgarazuion.
                    s<3dms& am DUNS (from Dun & Braastresii Numb^ of the fimi/comoany or
  ti  tiftt'ittt
                                    I  I  I  I   i  i  '  '  I   '  !  '  i   I  !  '  '   !  I  '  '
Name of firm
t  t   f  1  I  t   f  f  t  f   T  I  '  *  >   I  <  I  >  *   I  '
Maiing aodraas of tim'a
I  '   I  !  t  '   '  t  1  !   '  '  I  J  '   '  !  '
                                                      Stat»     Zip Cede


                                        i—i  Notappiicatol*  _    .^x^^1
                                 A.7

-------
      tVhat want tn> ICON mv
-------
      -ow mairv emoovee nours ware scant at this facatfv aunnq eecn montn in tne fiscal year ending in
      19SS?

      Provide the tallowing information tor sacn montn In me fiscal year analog in 19S»:

      a     production worxsr nours sosm in fcmiuiating, packaging, or reoackagmg any of the oroaucts on
            tne 1988 (yeiiowi fleg«erea Products List

      •     aUotneroroaucaonwofxar nours: am

      «     total nonoroductton worker nours.

      Produetien woritira Induds  srnaoyeas (up througn the iine-suoervuor level) erxjagea in fabricating.
      processing, asasm&ing. Inacecdng, receMrig, stcving, handling, pacwng, warenouttng. shtocmg (bu ncc
      deSivenng), maireenancs. reoar. (anaonaJ. and guard services, product development auxMiarv production
      for pianrs own use 
-------
' 8.   rVhai oroducts ana amvxm were orovnea cv your raatiiv in me fissai year erasing in 19€@7
Products on
Regtsisrea
Products Ust

a.


b.

c.
d.


e.
f.


3-




h.



On-sjta formulating, rmsdng
or contorting cnamcate 	


On-srta packaging products 	

On-sita repttckngjng products

On-sta distribution and/or
whoiatating, of products 	

OivaitA rand Minn
wimiviw • •Miiiiiiii ^HUWW .•••••.•••M.«««*.*»«..«.........«..«.»«
Off-sita appHattion of

cnBnwCii pfOQuas/pstt
control swvteM 	
Off-eta contnei ecpjipiram
dscning and nvdntiinimca t.g..
th« us* of paattiH fcr
uurunanc* or air conoioonng
9CJuiprrMfft
«...
Off-site odwr activty (S^to^
I.,
	 ?T M
Yea
No
Psstidds
proauasnoton
Registered
Pesadds
Proauasust
Yea
X-N
No
1 "v







1 •
a
rTH
i
a
a^p.
1
a

i
^4
1
a
_i_j

i
n







^2
a
a2
a
t
2
a


1
2
a
MI
2
n
n
n/* . /
yatU
r-r
1
i— j
1
a
1
a

i
a


e<^c
i
a
--U.
OTT
1
n
a
T T
2
i— •
"/

2
a
2
a
3p
2
a

f\n
PP
2
a
PP
2
n
Non-
produas
YS3
t
I — I
1
r— [
^a,
a
" 1
a
1
a
*?(>
1
a

j
*?
i
D(
c&\
t
n
No
2
'— -
2
.— •
2
a
n?^
q
2
C
/ipp
2
n

,
(OMp
2
a
^PP
2
n
                                  A. 10

-------
•3.   Faoiliv
                          Harass
     ;n tne fiseaft V©^ ©nateii in 1SSI. wnai oareantaqe at vour tacaitv'3 total revenues trom oesBOd® orooucts
     on tne 198S {yg&ssss fl@giaar®a Proauas Usl were trom tne marxets listea Deiow? (Enter "00* /f tf» marxec
      s nor acetfeasfct.  RlgM-jussfy your answer >n me OOXBS.  TTre oercermqes snotod sum to 100%.  DC not
      nctua® ossB&ass noj re&onsa on me 1938 (y&iowi Registered Proaucts ust)
     a.

     b.    inattutlonal/commaresal uaa. e.g.. jannonai.
 *^        hcsgaais. fooe ^iv^s ©sssishmsnts [[[   '

  -;  c.    Induaetei ua@. La., prsai^as to faoiKats
           am/or mseasin sn tnsusmsi crocsss. sucn
           as aimteid^s ua@s In DUO am saosr oroGucuon
           ami tjfe^es u^ in cooing towera [[[   '

  \l  d.

  "  9.    Products
  ^        I.e., i

  L  f.



     g.
 1         Le..                                                               ,
           U^UaH^U I^HjaVslowaUi^H^W ••••••aoB»«o»»»»««««»«»««»""«"»»»"*«*»»»»"«**«"«*"**"**""**""*"**""*""*"""""™™

     h.    Consisn^tiam.tewaanag^rasn ------------------------------------------------------------  L

 Ct   i.     Govms^ea, to1 nos^^^skH^ usa. e.g.,
  '         highway tis^ssmmm. masa^e esaara
           diaries, p^te taints,                                               L

 lO  1-     Qto&maste&fS&a&ftf

                                                                                   100%
20.    Facility 19SS
      In tne
      the
      7988
                            fea 1S^. whst percsntaga o* yowfaea^y's revenues from psertdrta praducss on
                               Pf&tesa Ust was gensratad by exports?  (Errtar W /f no predocs on tfje

-------
you aacomnuB oroaucoon cr ail oroauca cornammq pomctt* acav* ingmMna
                      . '3887
                                                   on faa« i
VM	._.  1   SWo ro 0.34 on o»g» 1-24)   -<  -  __
No	,__  2   'Carnrm/e;
^«	.__;  1   'Voi/ masr comoittu Pan A ana Part a.
                             GotooaqaA-1. OanorcomrvMt
                             paQis 1-24 ana I-2S.)

No	,	2  2   (Cammuf with 0.34 on page /-24J
          A.12

-------
(U
a
<
a,

a


a
a

ui

63
B--


g



U



I

Q-:
O:
5
ir
P"

s
K,


I
                      r4
I
o



•g
2
     1
     a,
     5
                          >•_

                          ^
                    o's'
                    25

                    I!
               GG   I
i
            i

            I  li
i]
                     i
                     «* § I
                     ^ 3 i

                       i i
                       s. :»*
                          I

                          •3

                          J
                             u  o

                             £  £
         u
                          1
                       !i
                       rv*  £^
                       ^  ^
!!
~5 •'^ •
2,3
^2 5
^2 5
~— ^
•f> •+>
o|
"5 ffl
3 >
£J
"i 5
z >.
3 «
VI •_
S"^
1)
«3
« _-
- ^
Q 05
^*^n
e <~
and Indiided on a
soki. Inuslnythd
«s
11
ta 3
•g «g
cL 2
© &.
b^ ^""
§1



2
2
w
«g
e i
> i
~u
U I
_* i
A, \












cat Yasr \WH
a
z



-
""* "M

^ ~ s* •
* -£ •
•* i o
5 -3z
x -^
«£ Uft-
fc_ ,u_
4*. - Z.
~—
__^
'

i a
— 3
«* !**•



r-
1
•^
J a
~! :
W "IV- j
IK*
« -;tv
a. ^o
^.-^^
_^n
]\u
j 1

                                                     - ^-2
                                                     3 I* -3Z
                                                     ^ !^ -*
                                                        5-'=.
                                                         ••  >
                                                i
                         •s
                                                    •1
                                                        co i
                                                           10
                                                          Q

                                                          C3

1
a
©
^
1
~*

i.
i
;
1
»
»
-
w -
^ —
Uft
Q/ ••
1:
_
^,
j
^

^?
H '
5 |
t: 1 i
ii 0 >.
o»s "5
50 0
f fi
°pr 3
o
<=L
1


C
7
                              A. 13

-------
                 -     5

                 1

                 J
                    '—  u-
               Vfi
               N -i
                   _.  «'
                            nu-
A.14

-------
#ct» ootfuoen cairn* «uipminu  isiame* cesiqnea to traax WOTMHT. cnor to NUM. ajaawgt or
                                                                                 to
        ts«icn« t* dun. oaora. voattw. soravs or otnar air pouuarea.
                                      A. 15

-------
                   US. ENVIRONMENTAL PROTECTION AGENCY

            PESTICIDE FORMULATING, PACKAGING, AND REPACKAGING
                          FACILITY SURVEY FOR 1988

              PART C - CONTACT INFORMATION AND CERTIFICATION
                               ATTACH LABEL HERE
Part C consists of three sections:

     Section!:  Technical Information Contact

    Section 2:  Financial and Economic Information Contact

    Section 3:  Certification
                                     A. 16

-------
               PESTICIDE FORMULATING. PACKAGING. AND REPACKAGING
                                  FACILITY SURVEY FOR 1988

                    PART B - FINANCIAL AND ECONOMIC INFORMATION

                                      GENERAL INSTRUCTIONS

PURPOSE
The U.S. Environmental Protection Agency (EPA)  is establishing wastewater effluent limitations guidelines and
standards for the pesticides chemical industry.  The EPA is considering 272 pesticide active ingredients, 126
priority pollutants, and other conventional pollutants for regulation. This survey, the Pesticide Formulating,
Packaging, and Repackaging Facility Survey for 1988. collects data on pesticide formulating, packaging, and
repackaging activities;  wastewater treatment practices;  and financial and economic information for the fiscal
years ending in 1988,1987 and. 1986. This fiscal year may or may not coincide with the calendar year.

Part B requests information  on ownership, major activities and finances for both this facility and the firm owning
this facility.  The information will be used by EPA in assessing the economic achievabilfcy of effluent guidelines for
the pesticide industry.  Specifically, EPA  needs to determine what proportion of facilities may incur significant
adverse economic and  financial impacts as a result of the regulation. In addition to determining impacts on the
industry as a whole, the Agency will determine if these adverse impacts will be concentrated in a particular type or
size of facility.

Among the impact measures to be considered are changes in the facility's cash flow due to additional operating
and capital costs that result from compliance with the regulation. Thus, income statement  and balance sheet
information for the facility is requested.  Since the capital cost will  be affected  by the method and cost of
financing, the survey requests information on recent capital investments. Other possible impacts include the
dosing of a production line or facility, or conversion to other products.  Therefore,  the survey asks about the
value of the plant and equipment, and possible conversion costs.

ADDITIONAL SUBMISSIONS
If you feel that additional information on other facilities you operate will allow EPA to better estimate the combined
impact  of  the  regulation on vour  firm,  EPA will  accept voluntary  submissions for §11 other facilities that
manufacture or formulate, package, or repackage any Table 1  (pages 5  through 14) pesticides within the
company.

Voluntary submissions will be used to estimate firm level impacts, but will not be extrapolated to estimate the
effects of the regulation on the entire industry.

To  receive a blank questionnaire, please contact Ms. Janet K. Goodwin at (202) 382-7152.  Do not us* the
questionnaire provided to this facility, as each facility has a unique identification number.
                                               A. 17

-------
                                   GENERAL INSTRUCTIONS (continued)


  AUTHORITY

  Data in this mandatory survey are collected under the authority of Section 308 of the Clean Water Act (33 U.S.C.
  Section 1318). Late filing or failure otherwise to comply with these instructions may result in cnminai fines, civ*
  penalties, and other sanctions as provided by law. Provisions concerning confidentiality of the aata collected are
  explained next


  DATA CONFIDENTIALITY

  Regulations governing the confidentiality of business information are contained in 40 CFR Part 2 Subpart B. You
  may assert a business confidentiality claim covering part or ail of the information you may submit, other than
            , as described in 40 CFR 2.203(b):
        *(b)  Method and time of asserting business confidentiality daim.   A business which is  submitting
        information to EPA may assert a business confidentiality daim covering the information by placing on (or
        attaching to) the information, at the time it is submitted to EPA, a cover sheet, stamped or typed legend, or
        other suitable form of notice employing language such as 'trade secret' 'proprietary,' or 'company
        confidential.' Allegedly confidential portions of otherwise non-confidential documents should be dearly
        Identified by the business, and may be submitted separately to facilitate identification and handling by EPA.
        If the business desires confidential treatment only until a certain date or until the occurrence of a certain
        event the notice should so state.*


 If no business confidentiality daim accompanies the information when it Is received bv EPA. EPA may make the
 Information available to the public without further notice to you. Information covered by a daim of confidentiality
 wSI be disdosed by EPA only to the extent, and by means of the procedures, set forth in 40 CFR Part 2 Subpart B.
 In  general, submitted Information protected by a business  confidentiality daim  may be disdosed to  other
 Employees, officers, or  authorized representatives of the United States  concerned with carrying out the dean
 Water Act, or when relevant to any proceeding under the Act  Effluent data are not eligible for confidential
 treatment


 QUESTIONS

 Questions about Part B - Financial and Economic Information may be directed as follows:
 For questions regarding  schedule:

       Dr. Lynns G. Tudor
       U.S. Environmental Protection Agency
    i  Analysis and Evaluation Division WH-586
       401 M Street, S.W.
       Washington, DC 20460
       (202) 382-5834


For questions regarding,  or assistance in completing, any item in Part B of the questionnaire, EPA has established
a toll-free help line:

      EPA Pesticide Formulator/Packager Help Una
      Act Associates Inc.
      (800) 343-3019
      Ask for Jeremy WBson (Ext 5436) or Caty McGuckin (Ext 5155)

                                                A.18

-------
                  U.S. ENVIRONMENTAL PROTECTION AGENCY

          PESTICIDE FORMULATING. PACKAGING. AND REPACKAGING
                           FACILITY SURVEY FOR 1988

               PART B - FINANCIAL AND ECONOMIC INFORMATION
                                 ATTACH UBEL HERE
        SECTION 1:  FACILITY FINANCIAL AND ECONOMIC INFORMATION
Section 1 consists, of questions on the finances of this facility.  A facility is a pesticide-producing
establishment In which pesticide active Ingredients are formulated, packaged, or repackaged Answer the
questions in sequence and do not leave any entry blank. Definitions, specific instructions;: and spaces for
you to comment have been provided. Use the Comments sections on pages .6-16 and B-19 to explain your:
response to any question. Cross-reference each comment with the applicable question number.       ;•;;:

To complete the questions in this section, you need copies of the Registered Products List found on
yellow, blue, and green pages following  page, 1-3.  This information can be obtained from the person at.
your facility who is responsfclefor completing Part A, the technical portion of this questionnaire.       4;iC
                                       A.19

-------
 m eg
to c
00 E
CD O
              a
              tl
             i- CM

             an
Bi CD
    CD
   TJ (O
   eo T
   2 m
   a 
-------
S3 cn
"•^ ^3
5 ^
2 ~
GO. S
^ 
*•* «
2 S -
•s OT *••
ll
J S
CO
f i
—. C J
•J QJ
5 15 a.
= E 2 r-
5 _ £ S
o c

^_ "O5 0
Q IT it
0)
1*5
Ul _
3) >»
ii j
^
c
CM —
O |S.
2 ?
O CO S
Z +• ta
S >

0> 0
^™ ^— M
D | E
a.
•§
1 ^ 1
£5" e
__(

—
— •
-|
-H

~^
-
— '
~
_
j
1
-
-
^
-
_


™"
|—
-
—
^«~
52
"3
o
5 =

U)
ID
i

CM
h»
co
ea
o S
z «

0
•^* «a
D "•

s
" tp
n.*
^ T

—
~|
—


"™
-
^

-
i
%%
a§
1
-
—
^
-
—
_

~
—
-
M
|"li^
00
S



OJ
- s
OJ
r»
6 a
Z «

^ 0
a ' =

s
? or

CM
— . r»
1
O ' gf
z >

o
a =

s

-,


:
™

^

-


-
j
w»
1
• -
~
-I
-
V4
. .


_
~
«l
S



04
n e *>"«"
LJ •=: ^ i.

"§• £ Si c»
O ^^ i^ O W ^^
21 ^i— O ^ O
*•*
Q
^ 2.
a

i
i I

r^ --^ H
n .sa® s
c « co
3 E e <»
M — > &2 Q S
o
(0
iH
a |
—
»
1 ^
? 8*
o

    . c~
    ^c?
     CD
     O)
       a
    §•="
    ^ 01 Q  O
    15 8  £
    a — i 0  "•
O3 ^J 
til
sil
    b *=h jM
    w O w
    O a> ^
    4= OC ^-
     
1  •
J  £
  CM
  a
]
                                          a
                                             .
             «
    CO ^ ~~

    c c S
    0} Q OT
    S-5 3
    i§£

    |13
    > a u»
             i
                            I
                                0
   (0
   e


   1
                                              2
                                              *
f
(O
_e

i


>.

JO

o
®
                                                              fe
            CM       ^
            a  .s ft  §
             ill.  fe
            i-tll  *
                                                     *
                                                     •c*
   i
                                a
                                                              s
M   ^
S  *>•
= OK
S--S,
« S 2
ill
§8"
•2 o <&
ISa
<«e 00 tS
i§3
21?
ial
« e 5
                           u.
                           2
                           s
                     (O
                                    A.21
                                                  ee

-------
                f  . '•IttyWBte^^
 Estimating Procedures
              Estimating Revenues.  In some cases, the facility does not sell its products itself and, thus, does
              not know what revenues are generated  (e.g., is part of a multi-facility firm in which two or more
              facilities contribute to the final products).  In such cases, the final revenues the firm realizes from the
              sale of formuiated/packaged/repackaged products should be allocated to the facilities involved in
              its production and formulating/packaging/repackaging on the basis of each facility's share of
              operating costs. An example of this allocation procedure is given below.

              Estimating Expenses. When certain cost elements (e.g., R&D and Federal taxes) are paid by the
              division or the firm, the facility's share must be estimated.  In this case, base the cost estimate on
              the facility's share of the division's or the firm's U.S. sales.  Use the organizational level closest to
              the facility for which there are the necessary data. If you do not have facility sales, use the revenue
              estimate developed above.
                                 Example of Estimating Facility Revenues

 Assume that the firm owning this facility also owns two other facilities that perform different aspects of the overall
 production, formulation and packaging/repackaging process. For example, assume that:

       •      Facility R manufactures Table 1 active ingredients;

       •      Facility S formulates these active ingredients into pesticide products; and

       •      Facility T packages these pesticide products for sale.

 Further assume that no sales take place (i.e., no revenues are generated) until the finished products  are sold.
 Hence, revenues for each facility must  be estimated.  This is done in terms of each faculty's share of operating
 costs relative to the total operating costs of the firm.  For this example,  assume that the operating costs of
 pesticide production, formulation, and packaging/repackaging are:

       Facility R has operating costs of  $1,000,000
       Facility S has operating costs of  $  500,000
       Facility T has operating costs of  $  500,000

      Total operating costs of firm  =   $2.000,000

Given this distribution of costs, Facility  R would  be assigned one-half of the firm's pesticide revenues. Facility S
wouW be assigned one-quarter, and Facility T would be assigned the other one-quarter. Therefore, if the firm had
pesticide revenues of $3,000,000, and you were Facility S or Facility T, then your estimated revenues would be
$750,000.
                                                                                           (Continue-*)
                                                A.22

-------
1) 03
•m* '
~ - 2
>, 03 5
-2 S •£
§"~*
__
~ r m  0 a
•C >» 3= 'c e
—I >» 2> o >•
"o s as S "•
£ = C § e
V"' — *5 j7*
T3 r~ O *•»
d) ~7 C &
t: -S1 S3 Q
o oc -a ^s
Q. o —
® oj »s «s
® to ^
.a o ® 5
s| a> g ;£
r« C * "O
«2 — «> c
C ? , ^3 ®

I'll * „
1 si! 1 !
2 o o o i> T"
Q. .££ 21 _ ^. >•
if — • ^ o TE a
UJ | | « •§ ^
•J CL ^ ^ " ^
| U | | |
13 2 2 & tn
53 -a « * S>
CD * £ 2 S
8 1^1 8
1
—
-
~



-
mm

""
j
>2
I

-



•
*•
r—


CM
— ' (0
03
CD
T"
$ «
Z o
>
"3
u
T- U>
n =


(A
1 ^
> ca
o*
<2

CM
n
I
o S
2 7? 1
•*" (S
11
s 1
-S. 1
—
-H
-
J^
—

I
:
_


j
j
I

-


•
-
:
«»
T^-
.^«.
^J
'"5s
£1 g
~" "QJ g
~ 03
•i O)
Q v"
-« "r\ s
z 1 £
•£"  Q
 •§
:

-
_
—
_
mm

-


:
%*
^
q

-


^
-
=
*»
53


CM
CO
^
^ •
*- •
—v Ti
2 S
a § •»•
§
^
I S
> ai c
> P^ Q
> *tt ^
. •& ^
"^5™* Q.
2
^
CM 8J
a g K
i 1
o §• S
Z 
0 -
•i: u
*~ "O 4!
a 5 • c
9
-$
s I
r r- ^
^
""
d
«,
.
_
_
~
-


:
1
l

-

_
^
-
=
«»
a


CM
n

n*
T»
o 0
z a
o
~ 2.
n


s .
• ^
^i

CM CO"
DO
2
i
S *
z —
so
U.
5 |
I
>
5 ^r
S  -£-g5
   MJ  S Z
   S S •
   

              § s
              I ^


              1 I
              ^^ ••
                        i
              CD
              •5
              «3
              o
              u
                         o

                         i
                         i
                         m
                                      u
CM
n
                  I
                  s
                  o
                  i
                  OJ
                           o
                           je
                           I
                           i
                  a
                  •5
                  CO

                  I
                  o

                  1^
                                      li
                                      5» 03
                                                CM
                                                a
i

O>
o>

J
                   I  I
                   5.  1
                                                     o
                                 ?
                                 1
                                          0
                                          I
                                          ffl
CM  R-
a  s
         51
                                       3  i
                                       it
                                A.23

-------
                                        a>
                                                                                                            j
                                                                                                                 CM
                                        (D

                                        g
                                        o>
                                        05
                                                                                               a
                                                                                               Q
                                                                                         _    «
                                                                                         n
                                                                                                            ]
 1
 tn
 o>
IU
I
55
                CD
                Q>
                g
                              a      i
               I
                                                                                      CM
                                                                                      n
                                                              a
                                                                                                           «3&r
                                                                                         *5-
                                                                                                                CM
                                                                                              I
                                                                                                                z   —
                        1
                        2
             -    m
            I   I
           I
            §
           i
                              CM
                              n
•sszr
               m'     •

               I      *

               I     8
                                                                    ca
                                                                   1
                                                              CM
                                                             a       s
                                                                                             *co
                                                                                             o.
I
i
                        I

                        I
                        u.
                        2

                                                                                    I       I
                                                                                    i       s
                                                                                    a       s
                                                                                    
-------
t
u
*s
to

00
r-  S
c "•
Q.
8
.g
W"
-
I



-
_
— ,



:
•JS

CM
r^
•"• to
CO
CD
T-
Q £•
>
15
u
a =

(0
r
-H

"


-
_
^



:
*»
^2
-
i :
rn
s
*™
20
•
7
u
5 =

ID
> f&

J
*


-
__
^



:
jj
.
CM CM
LJ C .5 | f

J I * o4
c\ c S» ^i
5 5 •* *2 ° * o
"" a a
o
. - 52.
n a
*i
.1 *%

t
I 1
I s „.
C ., f"»
® o §
•^^. 3 ^
CO W fe
1 f I
S. S s
« I =
CO t
5 S
CO >.
^
-


™
-
I
«»
CM
a
*"»
s
T*
o &
1
u
»- u»
n E
1
«
-


— *
-
:
*»
*» -
CM
a

i

° 5
^_ u
a =

>4
-


«.
-
^
»••
^S1-
CM CM (3s
a n srt §
^ c v **•

^^ E £. S
£ i-&lf 5
|
a a ' |
i if
» >
        I
        •o

        S  —
        a
                OS-
                   CM
                   D
                            08
5   r
2   I
1   1
(D   i^
                1  S
           CM
           a
                                             00
                                             o>
                                             «
                                    a

                   I
                         s
                         •5

                         S
                                4A  ^*
                                 J«
                                                    s
CM
a
                                     .

                                    eo
                                    J8.
                                         *£»


                                    A.25

-------
                                    CD
                                    o
                                         s
                                                                      or
                                                                      eg
1
                                    •
                                     -
                                    a-    =
                                    to
                                    Oi

              «0
  es

   i
                a
                -
              -
              c Q.
              o of
             D


               s w
               I
CO
            n
                                         i
                                             1-ft
                                                 CM
                                                 D
                                                 i-
                                                 o-
                                                 CM
                                                 D
                                                 CM
                               a
                                             *»  >
                                                     f
                                                     Oi
                                                     I
                                                     a
                                                                  CM
                                                                  D
n
    2
                                    12
                                     I
                                     18
 ta
   co
  O
             1:
               CO-4


-------
                                   CO
                                   09
                                   a>
                                   9
                                   o
                                   99
1
0)
§
a


1.
o c
          I
M
ffl

1

I
a>
•e

(0

1

a
o
ia
          0}


          (0
                          CO
                          CO
                          at
                      ... o
          (A
          CD
                                         1
                                         1
                                         J
                                             o
                                                        >

                                                        o
                                                                   CM
                                                                                  -
                                                                               CV

                                                                               O
                                                                            a
                                                                            I
                                             CM
                                             a
                                                        >
                                                        CM
                                                        a
                                                                  O
                                                                  

-
-
-
„
:
«»
•«3r
CM
q
0
*—
n
.
^
                                                                            3  ««"§•   §
                                                                                t- C ,    •»»

         T5


         £
          i
          3
                                    ca
                                   i
                                                    CM

                                                A.27

-------
CO
                        CD
                        CD
                        ta
                        u
                       3
                       •a      i
                        •C-   Z.
                          ^    u
                          I   £
                         S   Z


                          i

                                           n
                                          \M
                         i
                         •o
                                                        3    ?
                         M
                        1
                                                                         Z    -=•
                                                                        •as
                                                                         CM
                                                                         n
      •2
      u.

n    a
                    .28

-------












S
3
C
O
,0.
3
cr
HI
*
<0
.2
.is
3
JS
c
g
i
J5
o
c

__
LL
u*
£•
letailed Facil
a
(O
1
i
m
S3
T-












































I
S
O
^&
!
v
' a
S
hcurrent liabilH
o
z






















1
c
ffi
•g
ra
«
i
j
•g



9
c
i
) value of all i
«M
«m
1
Si
^
a
IU
•g
(0
a)
J2
a:
S
|
Total Non-curr
CO
CM




1
T"
Jj
>
•J
U
E










V*
:
* ™
"i
3
M
Z









1
•1
o
5











~


—

_
.
_;


-

«
s
i
1

<«
-
_
™

™

-
-
...
^—
H

•S

_

-
-
—

-
j

J.^-
*f*
&






'.
I
CM
!~"


O
Z


U

0
^ ^
: ^

y^ "^5

CM
P


6
,_
D

S


•CJ?
^•o
c^*
>
CM ^3
n g
1
1 1
1

•SS
5 1
•5
Ss
^_ ••
1
. s a
^L —
^g £
1 I
E °
1 |
I i
CD J5

«
•J
U
E








^
S
T*
h.
•
u
C









(Year 1888
•
o
5











1
""
-


—
_
J|


-

2
i
^ ^


• s



CM
q
6


q
5
'££
+^~
* cST
•=-25-
e«-
c
€
Wastheamou


A.29

CM
|~ - <2'<3-
•S § en -,
a 6 « Q
9-5 §) ^
^-*u5 g « O
_0 Q. ^
.0
— 2.
G ' ""
•ff
v »y>
^*




CM to'
DC *>"
— CM CO
j^"ca
Hi
•2 ^ <•>
JCD CO C
•g E«




-------
  30.
If you were to discontinue formuiating/packaging/repackaging of pesticides included on the 1988 (yellow)
Registered Products List would you be most likely to:
        a.    Shut down the pesticide formulating/packaging/
              repackaging lines completely?	r\   i  (Skip to Q.32)

        b.    Convert to EPA-registered pesticide products
              containing active ingredients not listed in
              Table 1, pages 5 through 14?	Q  2

        c.    Convert to non-pesticide products?	Q  3

        d.    Convert to EPA-registered pesticide products                            '   (ContinuB>
              containing active ingredients not listed in
              Table 1, pages 5 through 14, and to non-
           .   pesticide products?	 Q  4



 31.    What are the estimated conversion costs of the option reported in Question 30, parts b through d?

                                                $ i   i   i   i s i   it  j 11   i  i  i



 32,     Do you nave room to Install wastewater treatment equipment on your existing facility site, on property you
        currently own or lease?

                                                Yes	r]   1
                                                No	Q   2



 33.    Do you have room to install wastewater treatment equipment away from your existing facility site, on
       adjacent property you could buy or lease?






34.    Do you own, lease, or rent your facBfty?

                                               Lease or rent	Q  j (Continue)
                                               Own	Q  2 (Skip to Q.36)
35.   How (ong is your lease or rental agreement?
                                                                  j	I
                                                                  Years (Continue)
                                                 A.30

-------
36.   What was the 1988 property tax assessed vaiue of the items listed below?  (Enter '00' if the taxes do not
      apply.  Right-justify your answer mine Boxes.)

                           State tax assessed value

      a.     Land	    S  I   '  !   !, I   !  !   !, I   !   '   I

      b.     Buildings	    $  I   !  i   i, I   !.  }.  '•,'ill

      c-     Equipment and machinery	    $  I—1—I—I, I—I—I—I, I'll

      d.     Other (Specify)	   $  I'll,'   '  !   U'   I   I   I


             Total property tax assessed vaiue	    $  I—1—I—I, L-J—!—I, I—I—I—I


                           Local tax assessed value

      f.      Land	    $  I—L_J—I, I—1—UJ, II   I   I

      g-     Buadin9s	    51   i  i   i, i   i  i   i, i   i   i   i

      "•     Equipment and machinery	    $1—I—I—1,1—I—L-1,1—I—I—1

             Other (Specify)	   $  I—!__!—I, I—I—L_J, III!


      )•      Total Propertytax assessed value	    $  I—1—i—l, I—i—!—I, I—l—L_l



37.   What was the 1988 assessed value of the  property, expressed as a percentage of market value (1988 level
      of assessment)?  This information may be included on your tax bill or can be obtained from your state or
      local tax office. (Enter W If the item is not applicable. Right-justify your answer in the boxes.)

      a.     State assessment percentage	   '   ' ..'—si. I—I %

      b.     Local assessment percentage	I	   '   '  '—J. I—I %
                                                                                     (Go to Section 2)
                                                A.31

-------
  COMMENTS FOR SECTION 1.  (Please cross-reference your comments by question numoer.)
  Question
   Number
  i  »
t  r
                                        A.32

-------
                            SECTION 2:  FIRM FINANCIAL INFORMATION
      Section 2 requests economic and financial information for the firm or organization that owned or controlled
      this facility on the last day of the fiscal year ending in 1988. If this is a single facility firm, this information
      should apply to the facility.  For multi-facility firms, you may need to contact your company headquarters.
      Comments on this section may be made on page 8-19.  Please cross-reference the question in your comment
Report the percentage of the firm's total U.S. revenues, for the fiscal year ending in 1988, generated by
each of the activities listed below. (Enter '00' if the activity was not applicable. Right-justify your answer in
the boxes. The sum of all percentages must be 100%).  Note:  Question 1 does not apply to government
agencies.

a.    Percentage of total firm revenues generated
      by manufacturing Pesticide Active Ingredients
      listed on Table 1, pages 5 through 14	
                                                                                      I   I   !   I
                 Percentage of total firm revenues generated
                 by formulating, packaging, or repackaging
                 pesticide products containing active ingredients
                 listed on Table 1, pages 5 through 14	
                 Percentage of total firm revenues generated
                 by all other activities (Specify)	
                                                                            iiii
                                                                            i   i   i  i
                                                                                Total
                                                                                 100%
fr? 2.     Did your firm make any capital investment during fiscal years 1985 to 1989?  Include both pesticide- and
          non-pesticide-related investments for any facility owned by this firm.
                                        Yes
                                        No
                                                                             Q   1  (Continue)
                                                                             Q   2  (Go to Section C)
                                                   A.33

-------
        If
IE
II
»3 ^
m
               01
             I

             1

             I?
              .
             It
             S3
                    
-------
COMMENTS FOR SECTION 2. (Please cross-reference your comments oy question numoer.)

Question
 Number
i  i   i  i
''''
i  i   i  i'
'  '   '—1
I'''
                                            A.35

-------
     YOU HAVE COMPLETED THE RNANCJAL
AND ECONOMIC PORTION OFTHIS QUESTIONNAIRE.

          CONTINUE WITH PART C.
                  A.36

-------
                                 SECTION 3:  CERTIFICATION
 1.    When the Introduction and Parts A and B have been completed, you must read and sign the certification
      statement below.
                                            Certification

I certify under penalty of law that this document was prepared under my direction or supervision in accordance
with a system designed to assure that qualified personnel property gather and evaluate the information submitted.
Based on my inquiry of the person or persons who manage the system, or those persons directly responsible for
gathering the information, the information submitted is, to the best of my knowledge and belief, true, accurate,
and complete,  i am aware that there are significant penalties for submitting false information, Including the
possibility of fine and imprisonment
Signature of certifying official
                              Date
I  I  t   I  I   I  I  I   I  I  I   I  I   I  t  I   I  t
 First name
i  i   i  i  i  itiii  i  i   i  t  i  t  i  i  i  t
Last name
Title of certifying official
                                         Maying Instructions
                                   Thank you for your cooperation.
                   Please mail your completed questionnaire in the enclosed envelope to:
                                        Ms. Janet K. Goodwin
                                 U.S. Environmental Protection Agency
                                 Industrial Technology Division WH-552
                                         401 M Street, S.W.
                                       Washington, DC 20460
                                           (202) 382-7152
                                              A.37

-------

-------
                                       Appendix B
                Mapping of Pesticide Active Ingredients into Clusters
       This appendix lists the 57 clusters used to define PAI markets in the EIA.  As discussed in
Chapters 3  and 4, the clusters were developed by EPA's Office of Water based on previous work by
EPA's Office of Pesticide Programs (OPP). Individual PAIs are listed by the cluster(s) in which the PAI
appears.  Chemical Abstract Service (CAS) numbers are provided where applicable.  Many of these
chemicals have already been regulated in different contexts (see the header of the table for notation
indicating whether PAIs are covered by other regulations, as well as the production/marketing status of
the PAI).
                                             B.I

-------
                                       PESTICIDE CLUSTERS
  C  ]
  (SB)
  (O)
  (J)
  (P)
  (PM*)

  (PM)

  A
  7
         Denotes pesticides that are not marketed in the U.S.
                 Denotes pesticides that have been cancelled for use in the U.S.
                 Denotes pesticides that have been discontinued by manufacturer
                 Denotes a pesticide whose registration has been withdrawn
                 Denotes a Trade or Brand Name
                 Denotes biological pesticide
                 Denotes a Office of Water Subcategory B pesticide
                 Denotes pesticide manufactured under OCPSF Industry Regulations
                 Denotes pesticide manufactured under Inorganic Chemical Industry Regulations
                 Denotes pesticide manufactured under Pharmaceutical Industry Regulations
                 Denotes pesticide covered by Pesticide Manufacturing Industry Regulations (priority pollutant and
                 Denotes pesticide covered by Pesticide Manufacturing Industry Regulations (priority pollutants
                 only)
                 Denotes pesticides not produced 1984-1988
                 Denotes pesticides not produced 1986-1988
                 Denotes pesticides not produced 1984-1985
                 Denotes pesticides not produced 1984-1986
 F-l     Fungicides
         Broad spectrum of uses
 205
 32
 62
 82
 87
 96
 149
 151
 190
 192
 260
 261
        PCNB 82-68-8 (PM*)
        Thiabendazole (Mertect) 148-79-8 (PM)
        Benomyl  17804-35-2 (PM*)
        Chlorothalonil 1897-45-6 (PM*)
        Mancozeb  8018-01-7 (PM*)
        {Amobam} (PM)
        Malachite Green 12069-69-1 (PM)
        Maneb 12427-38-2 (PM*)
        Organo-Copper (SB)
        Organo-tin Fungicides (PM*)
        Thiophanate Methyl 23564-05-8 (PM)
        Thiram  137-26-8 (PM)
Metalaxyl (Ridomil)
Myclobutanil (Systhane, Rally)
Propiconazole (Tilt; CGA-64250; Orbit; Desmel)
Vinclozolin (Ronilan)
Inorganic Pesticides
        Calcium Polysulfide (Lime sulfurs) (I)
        Inorganic Copper Compounds (I)
        Inorganic Sulfur Compounds (T)
F- 2a   Fungicides
        Fruit and nut trees, except oranges and grapes
                                                B.2

-------
        Ziram  137-30-4 (PM*)
        Quinomethionate (Morestan) 2439-01-2 (PM)
        Ferbam  14484-64-1 (PM)
        Dodine 2439-10-3 (PM)
        {Dichlone}  117-80-6 (PM)
        Captan 133-06-2 (PM)
268
164
134
121
99
74
< Dithianon >
Coppers
Glyodin A
Iprodione
Triforine
Pharmaceutical Pesticides
        Streptomycin (P)
Inorganic Pesticides
        {Ammonium Polysulfide} (I)
        Calcium Polysulfide (Lime sulfurs) (I)
        Inorganic Coppers,  cuprus oxide, copper oxide(7j
        Sodium Polysulfide (I)
F-2b
        Fungicides
        Grapes
134     Ferbam  14484-64-1 (PM*)
8       Triadimefon (Bayleton) 43121-43-3 (PM*)
< Glyodin >

Inorganic Pesticides
        Calcium Polysulfide (Lime sulfurs) (I)
        Sulfur (I)
F-3
        Fungicides
        Vegetables
228     Propamocarb Hydrochloride (Previcur N)  25606-41-1 (PM*)
167     Metiram  9006-42-2 (PM)
152     {Niacide} (PM)
99      {Dichlone}  117-80-6 (PM)
73      [Captafol] 2939-80-2 (PM*)
20      Dicloran, DCNA (PM)  99-30-9 - Plant closed; only U.S. producer
18      Anilazine (Dyrene)  101-05-3 (PM)
9       Hexachlorophene (Nabac) 70-30-4 (PM)
Fosetyl-Aluminum (Aliette)
Fluoride Compounds
Inorganic Pesticides
        Inorganic Chromium Compounds (I)
        Coppers, cuprous oxide, copper oxide (I)
                                                 B.3

-------
 F-4
 Fungicides
 Citrus
 267     Zineb (Dithane)  12122-67-7 (PM)
 Phenolics
 211     {Phenyl Phenol} 90-43-7 (PM)
 Sec-Butylamine (O)
 Inorganic Coppers, cuprous oxide, copper oxide (I)
 F- 5    Fungicides
         For use as seed treatments

 250     {HPMTS} (PM)
 227     Propionic acid  79-09-4 (PM)
 120     Metasol DGH (PM)
 80      Chloroneb  2675-77-6 (PM*)
 49      Etridiazol (Terrazole, Etrazole, Truban) 2593-15-9 (PM)
 35      TCMTB (Busan 30A) (PM*)
 {Chloronitropropane (Lanstan)}
 Carboxin
 Imazalil (Fungaflor, Fungazil)
 Triadimenol (Baytan)
 {Fenaminosulf (Lesan)} (O)
 Sodium Hypochlorite (I)
F- 6    Fungicides
        Post harvest fruit and vegetables

67     |Biphenyl, Diphenyl] 92-52-4
Imazalil (Fungaflor, Fungazil)
{Isothan}
Sodium Dehydroacetate (I)
F-7
Fungicides
Grain storage
227     Propionic acid  79-09-4 (PM)
Isobutyric acid (O)
Ammonium Isobutryate
F- 8    Fungicides
        Ornamentals

91      {Cycloheximide (Acti-dione)}  66819 (PM)
132     Fenarimol (Rubigan) 60168-88-9 (PM*)
167     Metiram 9006-42-2 (PM)
189     {Organo-Cadmium} (SB)
                                               B.4

-------
{Dichloroethyl Ether}
{Parinol (Parnon)}
Dodemorph Acetate (Milban)
Fosetyl-Aluminum (Aliette)
Piperalin (O)
F-9
Fungicides
Turf
132     Fenarimol (Rubigan)  60168-88-9 (PM*)
100     {Thiophanate Ethyl} 23564-06-9 (PM)
91      {Cycloheximide (Acti-dione)} 66819 (PM)
Fosetyl-Aluminum (Alliete)
Inorganic Pesticides
        Inorganic Cadmium Compounds (I)
        Nickel Sulfate (I)
F-10
Fungicides
Unclassified
{Ditalimfos}
Pseudomonas Fluoescens (Dagger G) (B)
{Allyl Alcohol} (O)
H-1    Herbicides
        Broad spectrum of uses

138    Glyphosate 38641-90-0 (PM*)
16     2,4-D  1702-17-6 (PM*)
Monocarbide Dihydrogen Sulfate (ENQUIK, N-tac)
Paraquat
Sodium Chlorate (I)
 H- 2   Herbicides
        Corn

 249    Veraolate (Surpass)  1929-77-7 (PM)
 246    EPTC 759-94-4 (PM)
 239    Simazine  122-34-9 (PM*)
 204    Pendimethalin 40487-42-1 (PM*)
 165    Metolachlor 51218-45-2 (PM)
 161    Methanearsonic acid (SB)
 130    Butylate 2008-41-5 (PM)
 69     Bromoxynil 1689-84-5 (PM*)
 60     Atrazine  1912-24-9 (PM*)
 58     Ametryn  834-12-8 (PM)
 54     Alachlor  15972-60-8 (PM*)
                                                 B.5

-------
 32     Cloprop (PM)
 26     Propachlor 1918-16-7 (PM*)
 25     Cyanazine (Bladex) 21725-46-2 (PM*)
 70      23184-66-8 (PM*)
 {Cyprazine (Outfox)}
 {Tridiphane (Tandem)}
 Nicosulfuron (Thiameturon)
 Primisulfuron
 Pyridate
 TCBC, Trichlorobenzyl Chloride (O) v
H- 3    Herbicides
        Soybeans, cotton, peanuts, alfalfa

272     {Chlorpropham}  101-21-3 (PM)
264     Trifluralin 1582-09-8 (PM*)
254     Terbacil 5902-51-2 (PM*)
249     Vernolate (Surpass) 1929-77-7 (PM)
240     Bentazon 25057-89-0 (PM)
224     Prometryn 7287-19-6 (PM*;
204     Pendimethalin 40487-42-1 (PM*)
196     Oxyfluorfen  42874-03-03 (PM)
194     Oryzalin  19044-88-3 (PM)
178     Benefin, Benfluralin  1861-40-1 (PM*)
176     Naptalim (Alanap) 132-66-1 (PM)
175     Norflurazon  27314-13-2 (PM*;
165     MetolacHor  51218-45-2 (PM)
148     Linuron 330-55-2 (PM*)
142     Hexazinone 51235-04-2 (PM)
135     Fluometuron 2164-17-2 (PM)
125     Ethalfluralin (Sonalan)  55283-68-6 (PM*)
92      Dalapon 15-99-0 (PM)
78      {Chloramben}  1954-81-4
53      Acifluorfen 62474-59-9
45      Metribuzui (Sencor) 21087-64-9 (PM*)
39      Pronamide (Kerb)  23950-58-5  (PM*)
17      [2,4-DB] - Salts and Esters still produced 94-82-6 (PM*)
{Dipropetryn}
{Ethylene Glycol bis Tricbloroacetate (Glytac)} (O)
{Fluchloralin}
{Nitralin (Planavin)}
{Perfluidone}
{Profluralin (Tolban)}
Chlorimuron Ethyl (Classic)
Clomazone (Command)
Dichlofop Methyl
Dinitramine v
Huazifop-butyl OPusilade),
Fomesafen (Reflex)
Imazaquin (Scepter)
                                               B.6

-------
Imazethapyr (Pursuit)
Lactofen (Cobra)
Mepiquat-Chloride (Pix)
Methazole
Quizalofop-Ethyl (Assure)
Sethoxydim (Poast)
H- 4    Herbicides
        Sorghum, rice, small grains
269     Triallate (Far Go) 2303-17-5 (PM)
257     {Terbutryn}  886-50-0 (PM*)
247     Molinate 2212-61-1 (PM)
254     Terbacil  5902-51-2 (PM*)
226     {Propazine}  139-40-2 (PM*)
 170     Napropamide 15299-99-7 (PM)
92     Dalapon  75-99-0 (PM)
70       23184-66-9 (PM*)
69     Bromoxynil  1689-84-5 (PM*)
68     Bromacil 314-40-9 (PM*)
66     {Bifenox} 42576-02-3 (PM)
58     Ametryn 834-12-8 (PM*)
41     Propanil 709-98-8 (PM*)
27     MCPA 94-74-6 (PM*)
26     Propachlor  1918-16-7 (PM*)
 {Barban (Carbyne)}
 Bensulfuron Methyl (Londax)
 Butralin
 Chlorsulfuron (Glean)
 Clopyralid (Lontrel)
 Difenzoquat Methyl Sulfate (Avenge)
 Imazamethabenz-Methyl, AC 222, 293 (Assert)
 Isoxaben (EL 107. Prolan)
 Metsulfuron Methyl (Ally)
 Thifensulfiiron-methyl, DPX-M6316 (Harmony, Pi)
 Thiobencarb
 Tribenuron methyl (Express)
 H- 5a   Herbicides
         Oranges

 Glufosinate (Devine) (B)
 H- 5b  Herbicides
         Grapes

 196     Oxyfluorfen 42874-03-03 (PM)
                                                  B.7

-------
 194    Oryzalin 19044-88-3 (PM)
 170    Napropamide 15299-99-7 (PM)
 H- 5c  Herbicides
        Fruits (except oranges and grapes), tree nuts and sugarcane
 194
 170
 92
 58
 44
 Asulam
 Dichlobenil
        Oryzalin  19044-88-3 (PM)
        Napropamide  15299-99-7 (PM)
        Dalapon 75-99-0 (PM)
        Ametryn  834-12-8 (PM*)
        DNOC 534-52-1 (PM)
 H- 6   Herbicides
        Sugar beets, beans and peas
        Terbuthylazine (Gardoprim) 5915-41-3 (PM*)
        Cycloate (Ro-Neet)  1134-23-2 (PM)
        Phenmedipham % 13684-63-4 (PM)
        [Dinoseb]  88-85-7 (PM*)
        Desmedipham (Betanex)  13684-56-5 (PM)
        MCPB 94-81-5 (PM)
256
245
209
112
95
47
{Diallate}
{Sodium TCA}
Chloridazon v
Clopyralid (Lontrel)
Diclop
Diethatyl-Ethyl (Antor)
Ethofumesate
Pyrazon
H- 7    Herbicides
        Drainage ditches, rights of way, forestry and ponds

259     Dazomet, DMTT (busamid, Mylome, Nefiisan) 533-74-4 (PM*)
252     Tebuthiuron 34014-18-1 (PM)
251     Bensulide (Betesan) 741-58-2 (PM)
239     Simazine 122-34-9 (PM*)
238     [Silvex]  93-72-1 (PM)
223     Prometon 1610-18-0 (PM*)
178     Benefin, Benfluralin 1861-40-1 (PM*)
169     Monuron 150-68-5 (PM)
168     Monuron TCA  150-68-5 (PM)
146     Karbutilate  4849-32-5 (PM)
142     Hexazinone  51235-04-2 (PM)
123     Endothall  129-67-9 (PM*)
119     Diuron 330-54-1 (PM*)
                                              B.8

-------
110     DCPA  1861-32-1 (PM*)
68      Bromacil  314-40-9  (PM*)
31      Mecoprop (MCPP)  7085-19-0 (PM*)
30      Dichlorprop  120-36-5 (PM*)
15      Weedone (PM)
14      Chlorfenac  85-34-7 (PM)
Aquashade (Dyes and Water)
Dichlobenil
Diquat
Fluridone (Sonar)
Imazapyr
Sulfometuron Methyl (Oust)
AMS, Ammonium Sulfamate (I)
Organic Pesticides
        Acrolein (O)
        Amitrole (O)
H-8
Herbicides
Turf
259     Dazomet, DMTT (busamid, Mylome, Nefusan)  533-74-4 (PM*)
237     Siduron 1982-49-6 (PM)
{Terbutol}
Flurprimidol (Gutless)
Oxadiazon
Inorganic Pesticides
        Ferrous Sulfate (I)
        Potassium Cyanate (I)
H- 9a   Herbicides
        Vegetables

272     {Chlorpropham}  101-21-3 (PM)
251     Bensulide (Betesan) 741-58-2 (PM)
248     Pebulate (Tillam)  1114-71-2 (PM)
176     Naptalam (Alanap) 132-66-1 (PM)
174     Norea  18530-56-8 (PM)
170     Napropamide 15299-99-7 (PM)
115     {Diphenamid}  957-51-7 (PM)
110     DCPA 1861-32-1 (PM*)
102     Bisethylxanthogen (Herbisan) (PM)
83     Chloroxuron  1982-47-4 (PM)
39     Pronamide (Kerb) 23950-58-5 (PM*)
23     {CDEC (Vegadex)}  95-06-7 (PM)
{CDAA(N,N-Diallyl-2-Chloroacetamide)}
Metabromuron A
Nitrofen (Tok) A
                                                B.9

-------
 H-9b  Herbicides
        Tobacco

 248    Pebulate (Tillam) 1114-71-2 (PM)
 176    Naptalam (Alanap)  132-66-1 (PM)
 174    Norea  18530-56-8 (PM)
 170    Napropamide  15299-99-7 (PM)
 144    Isopropalin 33820-53-0 (PM*)
 115    {Diphenamid}  957-51-7 (PM)
 110    DCPA   1861-32-1 (PM*)
 102    Bisethylxanthogen (Herbisan) (PM)
 39     Pronamide (Kerb) 23950-58-5 (PM*)
 23     {CDEC (Vegadex)}  95-06-7 (PM)
 {CDAA (N,N-DiaUyl-2-CMoroacetamide)}
 Metabromuron A
 Nitrofen A
 Prime +
 H-10
Herbicides
Unclassified
215    Picloram  1918-02-1 (PM)
98     Dicamba  1918-00-9 (PM)
{Erbon}

Allyl Alcohol}
Fenridazone-Potassium (Hybrex)
Trichlopyr
I- la   Insecticides/Nematicides
        Cotton

262     [Toxaphene]  8001-35-2 (PM*)
225     Propargite 2312-35-8 (PM)
222     Profenofos (Curacron)  41198-08-7 (PM)
214     Phosphamidoa 287-99-4(PM)
203     Parathion 56-3S-2(PM*)
199     [EPN (Santox)] 2104-64-5 (PM)
197     Sulprofos (Bolstar) 35400-43-2 (PM*)
195     Oxamyl  2135-22-0 24 (PM)
186     Azinphos-Methyl (Guthion) 86-50-0 (PM*)
156     Methomyl  16752-77-5 (PM*)
124     [Endrin]  72-20-8  (PM*)
108     Dicrotophos (Bidrin) 141-66-2 (PM)
107     Paratbion Methyl  298-00-0 (PM*)
104     Diflubenzuron 35367-38-5 (PM)
94      {Demeton (Systox)}  8065-48-3 (PM*)
90      Fenvalerate (Pydrin) 51630-58-1 (PM*)
63      [Benzene Hexachloride, BHC]  608-73-1 (PM)
                                              B.10

-------
55      Aldicarb  116-06-3 (PM*)
52      Acephate 30560-19-1 (PM*)
1       Dicofol (Kelthane, DTMC)  115-32-2 (PM)
{Bollex}
{Heliothis Polyhedrosis Virus (Elcar)} (B)
Bifenthrin (Talstar)
Chlordimeform Hydrochloride v
Cyfluthrin (Baythroid)
Gossyplure
Grandlure Mixture
Lambda Cyhalothrin (Karate)
Monocrotophos (Azodrin) A
Thiodicarb (Larvin)
Tralomethrin (Scout)
[Chlordimeform (Galecron, Fundal)]
I- Ib   Insecticides/Nematicides
        Soybeans, peanuts, wheat and tobacco

262     [Toxaphene]  8001-35-2 (PM*)
208     Permethrin 52645-53-1  (PM*)
199     [EPN (Santox)] 2104-64-5 (PM)
183     Disulfoton (Disyston)  298-04-4 (PM*)
156     Methomyl  16752-77-5 (PM*)
127     Ethoprop  13194-48-4 (PM)
124     [Endrin]  72-20-8 (PM*)
106     Dimethoate 60-51-5 (PM)
86     Chlorpyrifos  2921-88-2 (PM*)
63     [Benzene Hexachloride,  BHC]  608-73-1 (PM)
55     Aldicarb 116-06-3 (PM*)
{Bollex}
{Heliothis Polyhedrosis Virus (Elcar)} (B)
Chlordimeform Hydrochloride  v
Monocrotophos (Azodrin) A
Tralomethrin (Scout)
[Chlordimeform (Galecron, Fundal)]
 I- 2a   Insecticides/Nematicides
        Corn, alfalfa

 255    Terbufos  013071-79-9 (PM*)
 225    Propargite 2312-35-8 (PM)
 212    Phorate 298-02 (PM*)
 208    Permethrin  52645-53-1 (PM*)
 200    Fonofos 944-22-9 (PM)
 193    {Orthodichlorobenzene} 95-50-1
 182    {Fensulfothion (Dasanit)}  115-90-2 (PM*)
 150    Malathion 121-75-5 (PM*)
 111    Trichlorfon (Dylox)  52-68-6 (PM)
                                                 B.ll

-------
 107     Parathion Methyl 298-00-0 (PM*)
 86      Chlorpyrifos 2921-88-2 (PM*)
 76      Carbofiiran  1563-66-2 (PM*)
 75      Carbaryl  63-25-2 (PM*)
 13      {Landrin 2} 2686-99-9 (PM)
 TEPP (HETP)A
 {Bufenearb (Bux)}
 {Carbophenothion (Trithion)}
 {Tefluthrin (Force)}
 Formetanate Hydrochloride (Carzol)  <
 Thiodicarb (Larvin)
 I- 2b    Insectitides/Nematicides
         Sorghum

 203     Parathion 56-38-2 (PM*)
 193     {Orthodichlorobenzene} 95-50-1
 75      Carbaryl 63-25-2 (PM*)
 13      {Landrin 2}  2686-99-9 (PM)
 {Bufencarb (Bux)}
 {Carbophenothion (Trithion)}
 {Tefluthrin (Force)}
 TEPP(HETP) A
 I- 3    Insecticides
        Fruit (excluding oranges and grapes) and nut trees

 225    Propargite 2312-35-8 (PM)
 214    Phosphamidon 297-99-4 (PM)
 213    Phosalone 2310-17-0 (PM)
 203    Parathion 56-38-2 (PM*)
 195    Oxamyl 2135-22-0 (PM)
 186    Azinphos-Methyl (Guthion) 86-50-0 (PM*)
 185    Phosmet (Imidan) 732-11-6 (PM*)
 156    Methomyl 16752-77-5 (PM*J
 155    Methidathion  950-37-8 fPAfj
 141    {Cycloprate (Zardex)}  54460-46-7 (PM)
 129    Chlorobenzilate (Acaraben)  510-15-6 (PM)
 122    Endosulfan  115-29-7 (PM)
 107    Parathion Methyl 298-00-0 (PM*)
 103    Diazinon (Diazitol, Basudin, Dipofene,  Spectracide) 333-41-5 (PM*)
90      Fenvalerate (Pydrin) 51630-58-1
75      Carfaaryl  63-25-2 (PM*)
59      Amitraz 33089-61-1 (PM)
19      Dinocap 39300-45-3 (PM)
{Chloropropylate (Acalarate)}
2-Naphthol, Beta-Naphthol (O)
Chitin (Clandosan 618)   •
Dialifor (Torak) <
                                               B.12

-------
Formetanate Hydrochloride (Carzol) <
Ovex (Chlorfensom) A
Petroleum Oils
Tetradifon, Tedion v
Tetrasul (Animert V-101) v
I- 4     Insecticides/Nematicides
        Oranges

173     Naled 300-76-5 (PM*)
155     Methidathion  950-37-8  (PM)
126     Ethion 563-12-2 (PM*)
113     {Dioxathion}  78-34-2 (PM*)
75      Carbaryl  63-25-2 (PM*)
19      Dinocap  39300-45-3 (PM)
1       Dicofol (Kelthane, DTMC)  115-32-2 (PM)
Formetanate Hydrochloride (Carzol) <
Petroleum Oils
Tetradifon, Tedion v
Cryolite (Kryocide) (I)
I- 5     Insecticides/Nematicides
        Vegetables

235     Rotenone  83-79-4 (PM)
214     Phosphamidon 297-99-4 (PM)
212     Phorate 298-O2 (PM*)
195     Oxamyl 2135-22-0 (PM)
187     Oxydemeton-Methyl (Metasystox-R) 301-12-2 (PM)
183     Disulfoton (Disyston) 298-04-4 (PM*)
173     Naled  300-76-5 (PM*)
158     Methoxychlor  72-43-5 (PM*)
154     Methamidophos 10265-92-6 (PM*)
150     Malathion 121-75-5 (PM*)
127     Ethoprop  13194-48-4 (PM)
122     Endosulfan 115-29-7 (PM)
107     Parathion Methyl 298-00-0 (PM*)
101     {Ethylan (Perthane)}  72-56-0 (PM)
94      {Demeton (Systox)}  8065-48-3 (PM)
90      Fenvalerate (Pydrin)  51630-58-1 (PM*)
55      Aldicarb 116-06-3 (PM*)
22      Mevinphos (Phosdrin) 7786-34-7 (PM*)
Chitin (Clandosan 618)
Cryolite (Kryocide)
Cyromazine (Larvadex Premix)
Flucythrinate (Pay Off)
Nicotine
Nicotine Sulfate
Pirimicarb (Pirimor)
                                                B.13

-------
 Pirimlphos Methyl (Actellic) A
 Pirimiphos-ethyl (Primicid) A
 Biological Pesticides
        {Sabadilla} (B)
        Bacillus Thuringiensis (Cutlass) (B)
        Bacillus Thuringiensis Tenebrionis (Trident) (B)
        Ryanodine (Ryania) (B)
 I- 6    Insecticides
        Livestock and domestic animals
        {Ronnel}  299-84-3 (PM)
        Pyrethrum (PM)
        Pyrethrins (PM)
        KN Methyl (PM*)
        Penothiazine (PM)
        Coumaphos (Co-Ral) 56-72-4 (PM)
        Lindane  58-89-9 (PM)
        Famphur  52-85-7 (PM;
        Diphenylamine 122-39-4 (PM)
        Crotoxyphos (Ciodrin) 7700-17-6 (PM)
        Tetrachlorvinphos (Stirofos, Gardona, Rabon) 961-11-5 (PM*)
        Benzyl Benzoate  120-51-4 (PM)
        Amitraz  33089-61-1 (PM)
        Chlorfenvinphos (Supona)  470-90-6 (PM)
        DDVP, Dichlorvos (Vapona) 62-73-7 (PM*)
234
232
230
220
210
181
147
131
116
109
84
64
59
24
12
Bomyl A
Butonate v
Crufomate (Ruelene) v
Tabutrex v
Organic Pesticides
        {Benzene} (O)
        Bone Oil (Dippel's Oil) (O)
        Butoxy Polypropylene Glycol (Stabilene, Crag Fly Repellant) (O)
        Diisobutyl Phenoxyethanol (O)
        Linseed Oil (O)
        Muscalure (O)
        Piperazine Dihydrochloride (O)
I- 7     Insecticides
        For use as insect repellants at non-agricultural sites

171     Deet  134-62-3 (PM)
117     MGK326 136-45-8 (PM)
Citronella, Oil of {Indalone, Dihydropyrone} Camphor
Fish Oil (Fruit Builders Oil)
Organic Pesticides
        Ethyl Hexanediol (Turgers 612) (O)
        {Benzaldehyde} (O)
                                                B.14

-------
        N-Butylacetanilide (O)


I- 8     Insecticides
        Domestic bug control and in food processing plants

271     Tetramethrin 7696-12-0 (PM)
270     D-Phenothrin (Sumithrin) (PM)
233     Resmethrin  10453-86-8(PM;
232     Pyrethrum  8003-34-7 (PM)
231     Pyrethrinll  121-29-9 (PM*)
230     Pyrethrin I  121-21-1 (PM*)
229     Pyrethrin Coils (PM)
202     Para-Dichlorobenzene 106-467
201     Propoxur (Baygon)  114-26-1 (PM)
177     MGK Repellant 264  113-48-4 (PM)
173     Naled  300-76-5 (PM*)
150     Malathion  121-75-5 (PM*)
103     Diazinon (Diazitol, Basudin, Dipofene)  333-41-5 (PM*)
85      Chlorpyrifos-Methyl  5598-13-0 (PM)
65      {Lethane 384}   122-56-1 (PM)
65      Lethane 60  301-11-1  (PM)
61      Bendiocarb  22781-23-3 (PM)
57      Allethrin 584-79-2 (PM)
{Isobornyl Thiocyanoacetate (Thanite)}
{Mitin FF}
Bagworm
Chloroethyl Ether
Hydramethyhion (Amdro)
Hydroprene (Altozar)
Isothymyl
MGK Repellant 874 (2-Hydroxyethyl Octyl Sulfide)
N-Ethyl Perfluorooctane
Periplanone-B
Propetamphos
Sulfluramid/GX-071
Inorganic Pesticides
        Ammonium Fluosilicate (Dri-Die) (I)
        Boric Acid (I)
        Silica Gel (I)
        Silicon Dioxide (I)
        Sodium Fluoride (Florocid) (I)
        Sodium Fluosilicate (I)
        Zinc Fluosilicate (I)
 Organic Pesticides
        Ethylene Glycol Ether of Pinene (DHS Activator) (O)
        Napthalene (O)
 I- 9     Insecticides
         Fumigants and nematicides
                                                 B.15

-------
 243
 179
 160
 128
 97
 81
 5
 3
         Metam-Sodium (Vapam)  13742-8 (PM*)
         {Sulfotep (Bladafum)} 3689-24-5 (PM)
         Methyl Bromide 74-83-9 (PM)
         Fenamiphos (Nemacur) 22224-92-6 (PM)
         [DBCP, Dibromochloropropane Nematocide] 96-12-8 (PM)
         Chloropicrin 76-06-2 (PM)
         1,3-Dichloropropene 542-75-6 (PM)
         [Ethylene dibromide]  106-93-4 (PM)
 {Diamidofos (Nellite)}
 {Dichloropropane, Propylene Dichloride}
 {Fostbietan (Nem-a-Tak)}
 Aldoxycarb (Standek)
 Carbon Tetrathiocarbonate
 Chitin (Clandosan 618)
 Isazophos (Triumph, Miral)
 Paraformaldehyde
 Organic Pesticides
        Chloroform (O)
        Epichlorohydrin (O)
        Ethyl Formate (O)
        Ethylene Oxide (O)
        Ethylene Dichloride, EDC (O)
         (O)
        Methylene Chloride  (O)
        Propylene Oxide (O)
        [Carbon Tetrachloride] (O)
 Inorganic Pesticides
        Aluminum Phosphide (Phostoxin)  (I)
        {Hydrogen Cyanide, Hydrocyanic Acid} (I)
        Calcium Cyanide (Cyanogas) (I)

 1-10    Insecticides
        for termite control
198
143
140
86
79
        Sulprofos Oxon (PM)
        Isofenphos  25311-71-1 (PM)
        [Heptachlor] 76-44-8 (PM*)
        Chlorpyrifos 2921-88-2 (PM*)
        [Chlordane] 57-74-9 (PM)
Azadirachtin (Margosan-o-Concentrate) (B)
[Aldrin]
[Dieldrin]
Sulruryl Fluoride (Vikane) (I)
1-11    Insecticides/Nematicides
        Lawns, ornamental and forest trees

184     Fenitrothion  122-14-5 (PM)
180     {Aspon} 3244-90-4 (PM)
166     {Mexacarbate}  315-18-4 (PM)
                                               B.16

-------
143     Isofenphos  25311-71-1 (PM)
103     Diazinon (Diazitol, Basudin, Dipofene) 333-41-5 (PM*)
93      Dienochlor (Pentac, Pentac Aquaflow)  2227-17-0 (PM)
77      Carbosulfan (Advantage)  55285-14-8 (PM)
48      {Aminocarb (Maticil)}  2032-59-9 (PM)
{Bromophos (Nexion)}
(Kinoprene (Enstar)}
Dichlofenthion (Mobilawn)  A
Dispalure (O)
Fluvalinate (Mavrik)
Methyl Eugenol
Biological Pesticides
        Bacillus Popillae and B-Lentimorbus (B)
        Gypchek (B)
        N-Trap Elm Bark  Beetle (B)
        Nuclear Polyhedrosis Virus of Douglas Fir Russock Moth (B)
1-12    Insecticides
        For use as mosquito larvacides

253     Temophos  3383-96-8 (PM)
157     Methoprene 40596-69-8 (PM)
133     Fenthion 55-38-9 (PM*)
38      {LandrinI}  2686-99-9 (PM)
Arosurf MSF
BT, Butrizol >, very low production 1987-88
Dimethrin v
Fenoxycarb
Kerosene
Copper Acetoarsenite (Paris Green) (I)
1-13
Insecticides
Miscellaneous
{Mobam}
Abamectin (Affirm, Avid)
Clofentizine (Apollo)
Dimetilan (Snip) v
Hesythiazox (Savey)
Luretape
Methyl Trithion
Pine Tar
Pro-Drone
[DDT]
Biological Pesticides
        Hirsutella Thompsonii (Mycarl) (B)
        Nosema Locustae Canning (Noloc) (B)
Inorganic Pesticides
        Lead Arsenate, Basic (I)
                                                 B.17

-------
          Lead Arsenate, Acid (I)
          Potassium Nitrate (Saltpeter) (I)
          Sodium Arsenate (I)
 R- 1    Industrial preservatives

         SS^^r1*1? Td t0, C°ntro1
         spoilage, deterioration or fouling of materials
         Plastics, paints, textiles,  paper and adhesives.
                                                        grOWth' odor «•*« bacteria> bacteria causing
         Organo-Mercury (SB)
         Folpet 133-07-3 (PM)
         Copper 8 Quinolinolate 10380-28-6 2A(SB)
         Polyphase (PM)
         Dichlorophene 97-23-4 (PM)
         Thenarsazine oxide (SB)
 191
 137
 88
 42
 11
 6
 Amical
 Biobor
 Biomet 4
 Cetyl Pyridinium Bromide
 Fluorosalan v
 Mereaptobenzothiazole
 Nvosept 95
 Pharmaceuticals
        Tenamycin (P)
 Phenolics
        2-Chlorophenol (O)
        2,4,5-Trichlorophenol (O)
 Quaternary Ammonium Compounds
        Dodecyl Dimethyl Benzyl Ammonium Chloride
Trans-l,2-bis  (Propylsulfonyl) Ethylene
Vancide TH
Vinyzene (O)
Visco P-25-F4
[Onyxide]
R-2
259
241
221
219
217
172
163
118
89
       Slimicides
       Generally have non public health uses
       For use in pulp and paper, cooling towers and sugar mills

       Dazomet, DMTT (busamid, Mylome, Nefusan) 533-74-4 (PM*)
       Sodium Dimethyl Dithiocarbamate 128-04-1 (PM*)
       {Metasol J-26}  12002-57-2 (PM)
       Busan 40 (PM*)
       Busan 77 (PM)
       Nabam  142-59-6 (PM*)
       Nalco D-2303 (PM)
       Nabonate (PM*) •
       Copper EDTA (SB)
                                               B.18

-------
 71      Giv-gard (PM)
 33      Belclene 310 (PM)
 21      Busan 90 (PM)
 1,4-Bis bromoacetoxy)-2-Butene
 2,3-Dibromopropionaldehyde (O)
 2,4,6 Trichlorophenol
 2,6-Bis [(Dimethylamino Methyl] Cyclohexanone (O)
 3,3,4,4-Tetrachlorotetrahydrothiophene 1,2-dioxide
 4-Bromoacetoxymethyl-M-Dioxolane
 Bis (Trichloromethyl) Sulfone
 Chlorinated Levulinic Acids
 Methyl-2-3-Dibromopropionate
 Slimitrole
 Sulfonated Cresol
 XD-1603 (2,2-Dibromo-3-Nitrilopropionamide)
 Inorganic Pesticides
        Potassium Chromate (I)
        Sodium Chromate (I)
R- 3    Industrial Microbiocides
        Cutting oils and oil well additives

28     Octhilinone (PM)
Bioban 1487
Busan 1024
CIS-2-Pinanolu
Grotan
Metronidazoleu
Polyethylene Polyamine N-Oleylamine
R-32104
R- 4    Sanitizers
        For use in dairies, food processing, restaurants and air treatment

162     Hyamine 2389 (PM)
159     Methyl Benzethonium Chloride (PM)
105     Hyamine 1622 121-54-0 (PM)
56      Hyamine 3500 68424-85-1 (PM)
51      Oxine-SulfatefPMj
36      HAE (PM)
3,5-Dibromosalicylanilide
4,5-Dibromosalicylanilide
Alkyl Bis (2-Hydroxyethyl) Sodium
Neomycin (P)
Oley Trimethyl Ammonium Chloride (Aliquat 21)
Quaternary Ammonium Compounds
Benzalkonium Chloride (ETC)
Inorganic Pesticides
        Ammonium Acetate (I)
                                                B.19

-------
         Carbonates: Mg, K, Am, Na (I)
         HCL (I)
         Magnesium Silicate (I)
         Potassium Bromide (I)
         Potassium Hydroxide (I)
         Sodium Bisulfite (I)
         Sodium Bisulfate (I)
         Sodium Hydroxide (I)
 Organic Pesticides
         Butanoic Anhydride (O)
         N-Laurel Diethylenetriamin (O)
         Phenolics
                 Ortho-benzyl-para-chlorophenol
                 Ortho-Phenylphenol
                 Phenol (O)
 R- 5    Synergists
         Used as insecticide synergists, surfactants, dictating agents and carriers

 244     {Sulfoxide}  120-62-7 (PM)
 216     Piperonyl Butoxide 51-03-6 (PM)
 Arbanol Dee v
 Biological Pesticides
         Bacillus Thuringiensis var Kurstaki
         Kurstaki (EG 2348) (B)
         Kurstaki (EG 2371) (B)
 Heliotropin (Tropital) v
 N-Propyl Isome, Propyl Isome
 Pentasodium Diethylenetriamine
 Sesame Oil (Nematrol)
 Turkey Red Oil  (Sulfonated Castor Oil)
 Inorganic Pesticides
         Calcium Sulfete (I)
         Pentaacetate (I)
R- 6   Food preservatives
        Food

Organic Pesticides
        Acetic Acid (O) (Vinegar)
        Benzoic Acid (O)
        Methyl P-Hydroxybenzoate (O)
        Sorbic Acid (O)
Proxel v
R- 7    Wood Preservatives
        For industrial commercial and marine use
                                                B.20

-------
258     (Tetvachlorophenol (Dowicide))  25167-83-3 (PM)
206     PCP, Pentachlorphenol  131-52-2
190     Organo-Copper (SB)
188     Organo-Arsenic (SB)
Chromic Acid
Cobalt Naphthenate
Inorganic Pesticides
        Ammonium Arsenite (I)
        Arsenic Pentoxide (I)
        Calcium Arsenate (I)
        Coal Tar Oils; Tar; Coal Tar Creosote Oils; Coal Tar Distilates; Creosote (I)
        Potassium Bifluoride (I)
        Sodium Pyroarsenate (I)
        Sodium Arsenite  (I)
 R- 8   Disinfectants
        Medical, industrial, institutional, household, veterinary, poultry and livestock
        The term disinfectants refers to several types of antimicrobial pesticides which are intended to destroy
 microorganisms (bacteria, fungi, viruses).  They are public health products and may require efficacy testing. They
 fall into two main categories:

 R-8a   Sporicidal Disinfectants - Also known as sterilizers. They destroy or eliminate all forms of bacteria,
        fungi and viruses and their spores.  This group can be further divided according to whether they are
        applied to critical or non critical surfaces.  Hospital as well as other uses.

 Chlorine Dioxide
 Other Chlorine releasing agents
 Ethelene Oxide
 Formaldehyde (O)
 Glutaraldehyde (O) (Cidex, Glutarex, Sonacide; Sporicidin) also used in the Leather Tanning Industry
 Ozone
 Peracetic acid (decomposes to hydrogen peroxide, acetic acid, and oxygen.   More potent than Hydrogen Peroxide.
 Peroxygen - Hydrogen Peroxide (I)
 R-8b -  Non sporicidal Disinfectants.  May be sporoststic (prevent spore germination or outgrowth or both).
         These disinfectants destroy or irreversibly inactivate (all, many, some) infectious or other undesirable
         organisms, but not necessarily their spores.

 3,4,5-Tribromosalicylanilide
 4-Tert-Amylphenol
 Alcohol (ethyl,  isopropyl) Also an anticeptic
 Aldehydes (other than Glutaraldehyde, e.g.  malonaldehyde, succinaldehyde; adipaldehyde)
 Alkyl (5-Hydroxy-4-Oxo-2(4H) Pyranyl Methyl)
 Bigvanides
         Chlorhexidine
         Chlorhexidine diacetate
 Calcium Hypochlorite (I) (Dairy  Industry)
                                                   B.21

-------
  Chlorine-B
  Furfural (O)
  Gluconic Acid
  Hexahydro-l,3,5-Tris (2-Hydroxypropyl)-S-Triazine <
  Idophors, also have anticeptic uses
         Iodine Compounds
  N-Alfcyl-N-Ethyl Morpholinium Ethyl Sulfate
  Paraformaldehyde (Gas, Farm Uses)
  Uniquat CB 50
  Organic Pesticides
         Phenolics
                 O-Benzyl-p-Chlorophenol; Ortho-benzyl-para-chlorophenol
                 211    Ortho-phenylphenol (PM)
         Propylene Glycol (O)
  Quaternary Ammonium Compounds - Used on non-critical surfaces.
         Alkyl Bis (Hydroxyethyl) Methyl Ammonium Chloride
         Dimethyl Ammonium Chloride
         Didecyl Decyl Dimethyl Ammonium Chloride
         Didecyl Dimethyl Ammonium Chloride
         Octyl Decyl Dimethyl Ammonium Chloride


 R-9    Water disinfection - Public Health Uses
         Swimming pools, sewage effluents and potable water

 Chlorinated Glycorulil
 Chlorine
 EPIC Liquid Algacide
 Inorganic Pesticides
         Aluminum Sulfate (I)
         Calcium Hypochlorite (I)
         Chlorinated Isocyanurates (I)
         Chlorine Dioxide (I)
         Silver (I)
         Sodium Persulfate (I)
         Sodium Bromide (I)
 Quateranary ammonium compounds
         Dialkyl Methyl Benzyl Ammonium Chloride


 R-10   Plant regulators, defoliants and desiccants
        All uses

 263     Folex 150-50-5 (PM)
 236     Tribufos (DBF) 013071-79-9  (PM*)
 153     Mefluidide 53780-36-2 (PM)
 145     Propham (IPC)  122-42-9 (PM)
72      Cacodylic Acid  75-60-5 (SB)
50      Ethoxyquin  91-53-2 (PM)
46      CPA (Fruitone)  (PM)
2       Maleic Hydrazide 123-33-1 (PM)
                                               B.22

-------
Acoel
Ancymidol
Baguacil
Chloroflurenol
Cycocel
Daminozide
Ethephon
Fluoridamid
Fosamine Ammonium
Indole-3 -Butyric Acid
Marstat PN
Mon 4620
Nibroxane
Paclobutrazol (Clipper)
Requat
Sherichem DM
Sodium Chlorate
Thidiazuron
Triacantanol (Triacon)
YEA, Chitosan
Inorganic Pesticides
        Arsenic Acid (I)
        Sulfuric Acid (I)
Organic Pesticides
        Fatty Alcohols (O)
        Octanol (Antak; Flair 85, Offshoot) (O)
        {HBA} (O)
        Ethylene  (O)
        Gibberellic Acid (O)
        Hexachloroacetone (O)
        Methyl Esters of Fatty Acids (O)
        NAA, 1-Naphthalenacetic Acid (O)
R-ll    Preservatives, disinfectants, slimicides

211     {Phenylphenol (Orthoxenol)} 90-43-7 (PM)
7       Dowicil 75 (PM)
Dowicil A-40 (2,3,5-Trichloro-4-(Propylsulfonulpyridine)
Nitrapyrin
Omadine-Sodium
Inorganic Pesticides
        Chromic Acid (I)
        Lime (I)
        Potassium Permanganate (I)
        Potassium lodate (I)
Organic Pesticides
        Abietylamine (O)
        Chlorobenzene (O)
        Hexylene Glycol (O)
                                                 B.23

-------
 Phenolics
         Dowicide 31 and 32 (4 and 6-Chloro-2-Phenylphenol)
 R-12    Molluscides and Misc. Vertebrate control agents
         AH uses

 192     Organo-tin (PM*)
 40      Mercaprodimethur, Methiocarb 2032-65-7 (PM)
 Lamprecid
 Magnesium Sulphate (Epsom Salts) (I)
 Niclosamide (Bayluscide, Bayluscid)
 Stirrup M (O)
 R-13   Bird Chemosterilants, toxicants and repellants
        All uses

 Omitrol
 Paloja
 Inorganic Pesticides
        Copper Oxalate (I)
        Zinc Oxide (I)
 Organic Pesticides
        1,4-benzoquinone (Quinone) (O)
        4-Aminopyridine (Avitrol) (O)
        Polybutene (O)
        Polyethylene (O)
        Polyisobutylene (O)
R-14   Dog/Cat Repellants
        All uses

Ammonium benzoate (Bitrex)
Benzyl diethyl 2,6-xyIylcarbamoylmethyl
Blood
Capsaicin
Citral
Citrus Oil
Cresylic Acid
Geranium Oil
Hefty Dog and Cat Repellant
Trichloroethylene
Organic Pesticides
        Allyl Isothiocyanate (Mustard Oil) (O)
        Anethole (anise camphor) Cinnamic Aldehyde (O)
        Methyl Nonyl Ketone (O)
        Pentanethiol (O)  •
        Pyridine (O)
                                                B.24

-------
        Thymol (P)
R-15    Rodent toxicants, anticoagulants, predator control
        For all uses

265     Warfarin 81-81-2 (PM)
242     {Sodium Fluoroacetate, 1080}  62-74-8 (PM)
136     [Fluoroacetamide]  144-49-O (PM)
114     Diphacinone  82-66-6 (PM)
43      {Fumarin (Bromethalin)}  117-52-2 (PM)
37      Chlorophacinone 3691-35-8 (PM)
29      Pindone (Pival) 83-26-1 (PM)
2-Isovaleryl-l,3-Indandione, Calcium Salt
Alpha-Naphthylthiourea (Antu) (O)
Brodifacoum (Talon)
Bromadiolone (Maki)
Bromethalin Bait  PAI 43 ???
Phorazetim (Gophacide)
PMP (Valone)
R-55 (tert-butyl dimethyltrithioperoxycarbamate)
Red Squill (B)
Strychnine
Strychnine Sulfate
Inorganic Pesticides
        Phosphorus (I)
        Sodium Cynanide (I)
        Zinc Phosphide (I)
Pharmaceutical Pesticides
        Cholecalciferol (Qmntox)(P)
        Epibloc (P)
U- 1    Unclassified

266    Zetax (Zine MET) (PM)
218    Arylane (Busan 85) (PM*)
189    Organo-Cadmium (none registered) (SB)
139    (Glyphosine (Polaris)} 2439-99-8 (PM)
10     Tetrachlorophene  (PM)
                                                  B.25

-------

-------
                                      Appendix C
Methodology for Estimating the Price Elasticity of Demand for Pesticide Clusters
       This appendix provides the complete methodology for estimating the price elasticity of demand
for pesticide clusters.  The price elasticity of demand is used in the EIA to predict the change in demand
given an increase in PAI price due to compliance with the proposed effluent guidelines (See Chapter 4
and Appendix F).  This methodology is identical to that used in the Economic Impact Analysis of Final
Effluent Limitations Guidelines and Standards for the Pesticide Manufacturing Industry.
                                           C.I

-------
ESTIMATES OF THE PRICE ELASTICITY
OF DEMAND FOR PESTICIDE CLUSTERS

Prepared for:
Economic and Statistical Analysis Branch
Engineering and Analysis Division
Office of Science and Technology
Office of Water
U.S. Environmental Protection Agency
Washington, D.C. 20460

Prepared by:
Abt Associates Inc.
Cambridge, MA 02138

May 1991
C.2

-------
                              TABLE OF CONTENTS

1.0   Introduction	*

2.0   Price Elasticity of Demand for Agricultural Pesticides  . .	  3

      2.1    Methodology	3

      2.2    Review of Empirical Studies of the Price Elasticity
             of Demand for Pesticides	  6

    ,2.3    Price Elasticity of Demand for Food Commodities	22

      2.4    Feasibility of Non-Chemical Substitution	30

      2.5    Contribution to the Variable Cost of Production .	36

      2.6    Productivity of Expenditures for Pesticides	38

      2.7    Conclusions - Agricultural Pesticides  	42

3.0   Price Elasticity of Demand for Pesticides Used
      Non-Agriculturally	55

4.0    Conclusions	59

References     .	"*
                                           C.3

-------
  1.0   INTRODUCTION

        Purpose of the Analysis
        Abt  Associates  has submitted  a draft  economic  impact  assessment (EIA) methodology  for  assessing
  the costs of new  effluent  guidelines  for  the pesticide  industry.   The draft  EIA methodology  relies on the
  use of price  elasticities of demand for pesticide clusters.   In this memorandum,   demand elasticities  for each
  cluster  are  estimated  based  on  a review   of empirical  analyses,  the  elasticity  of  demand  for  food
  commodities,  and a consideration  of the  factors predicted by microeconomic  theory to influence  elasticity
  of demand.

        Definition  of the Price Elasticity  of Demand
        In general,  the  economic  concept of elasticity  measures  the sensitivity  of the dependent  variable  to
  a change in  the value of an independent  variable.   In particular,   the price elasticity  of demand  measures
  the sensitivity  of consumers to changes in price.   (Since this  is the elasticity  measure  of concern for this
  report  we may,  for convenience,  use the term  'demand  elasticity'  in place  of the term 'price  elasticity of
  demand'.)

       The price  elasticity   of demand estimates the  degree to which a change in  price results  in a change in
 the quantity  demanded.   It can  be defined as the percentage  change  in  demand divided by the percentage
 change in price.  If consumers cut back their  purchases  to such a large extent  that any price increase  reduces
 total revenue,  then demand  is said  to be elastic,  i.e., customers are sensitive  to price changes.  If consumers
 cut back  their  purchases   only  slightly  in response  to  higher  prices,  resulting   in  an increase  in revenue,
 demand is said to  be inelastic, i.e., customers  are not as sensitive to price changes.   The value of the price
 elasticity of demand is unbounded  and may be positive  or negative.   It is expected,   however,  that price  and
 demand are negatively  correlated,  i.e.,  an increase  in price results in a decrease  in  the quantity  demanded.
 The price elasticity of demand  is therefore usually negative.

      Four possible values,  or ranges  of values, of the price elasticity  of demand are of particular  interest.
 First,  if the  absolute value of the elasticity  of demand is greater  than one, demand is termed elastic.   In
 other words,  the percentage  change  in demand is  greater  than the percentage  change  in  price.  Second,
 demand is said to be inelastic when  the absolute  value  of the  elasticity  of demand is less  than  one  but
greater than  zero.  Third,   if the value of  the elasticity  of demand  is zero,  demand  is said  to be perfectly
inelastic.  That is, consumers  will continue to purchase  a given  quantity  of a good,  despite  any changes  in
price.   Finally,  if demand and  price  change  by equal  percentages,   the  value of the demand elasticity  is
exactly  one, and demand is said to have unit  elasticity.   Numeric values are generally  expressed relative  to
                                                  C.4

-------
a one  percent change in price.   For example,  an elasticity  of -1.5  means that a 1 percent increase  in price
would  result in a 1.5 percent decrease  in  the  quantity  demanded.

      Measurements  of the  price  elasticity  of demand  are  of use in predicting   the incidence  of a price
increase.   As the absolute value  of the  price elasticity  rises,  the  proportion  of the cost increase that can be
passed  on to consumers declines.  If demand  is perfectly  elastic, no  cost pass through is possible.

      Market  Definition
      In order to estimate the price elasticity  of demand  for  pesticides,  a clear definition   of the markets of
concern must be developed.   In this analysis, the markets  are defined  to be 44 separate  clusters  of pesticides.
The clusters  are groups of pesticide  active  ingredients  which  are close substitutes  for  a given  end-use.   For
example,   insecticides  used  on vegetables  is one of the clusters;  herbicides  used on turf  is another.

      The elasticity  of demand for pesticides may  vary  significantly  between  the clusters,  since each cluster
faces different  market forces.  In particular, a distinction  may be drawn between  the  agricultural  end-uses
and the non-agricultural    end-uses.   Agricultural  sales represent  approximately   70 percent of  the  total
expenditures   for  conventional   pesticides   in  the U.S.,  with  the  remainder  split about equally  between
commercial  and  domestic  sales  (U.S. EPA, 1988).  In contrast  to the non-agricultural    markets,  the basic
market structure  within which fungicides,   herbicides,  and insecticides  are used agriculturally   is somewhat
consistent  across users and some documentation  is available  by which  to estimate  the elasticity  of demand.
The price  elasticity  of demand  for  pesticides  used agriculturally  will  be analyzed  first,  followed   by a
discussion   of the elasticity  of demand  for pesticides  used  in the non-agricultural    sector.
                                                     C.5

-------
 2.0  PRICE ELASTICITY  OF DEMAND FOR AGRICULTURAL    PESTICIDES

      Within the agricultural  pesticide  market there exist several industry  sectors including  manufacturers,
 formulators  and packagers,  distributors,   and retailers  of pesticides.   The primary  goal of this analysis  is
 to estimate the elasticity  of demand  faced  by the manufacturers  of the  active ingredients.  However,  most
 studies consider the demand elasticity  of the end-user rather than that of the formulator/packager   (usually
 the  direct  customer   of  manufacturers).    This  analysis  will  assume  that  the  demand  elasticity  of the
 formulator/packager   is equal to the demand elasticity  of the end-user   since data on formulator/packager
 demand elasticity  were not located.  Assuming  competitive  markets, the long-run  elasticities  faced by the
 manufacturing  sector should  be similar to the elasticities  faced by  formulators/packagers.

      2.1  Methodology
      There is no one recognized  source of information  for the price elasticity   of demand for pesticides;
 in fact,  there is an acknowledged   lack of information  in this  area of study.  Abt Associates  conducted  a
 thorough search for analyses  of the price elasticity  of demand for  pesticides  and also sought expert  opinion
 as to the expected elasticities.   The sources considered  included  literature  searches   using the following
 databases  from  Dialog Information   Services:   Economic Literature Index,  Dissertation  Abstracts  Online,
 Agribusiness  U.S.A., Agricola, Agris International,  and NTIS. A search for subject matter containing  the
 following  key words  was conducted:  price elasticity,  or demand,  or demand  elasticity,   and agricultural,  or
 chemical,  or pesticide,  or herbicide,  or fungicide,  or insecticide.   In addition to the literature  search, Abt
 Associates  sought information  from the U.S. EPA Office  of Pesticide   Programs, the  U.S. EPA Office  of
 Policy,   Planning,   and  Evaluation,   several  offices  of  the U.S.  Department  of Agriculture,   the  U.S.
 International   Trade   Commission,    the  Chemical  Specialty   Manufacturers   Association,   the  National
 Agricultural   Chemical  Association,  the World Bank,  Resources for  the Future, the editor of the American
 Journal  of Agricultural   Economics,  a market  research firm, Cornell  University,  North  Carolina State
 University  (Dr. Gerald Carlson),  Texas A&M University  (Dr. Ron Lacewell),  Virginia Polytechnic  Institute
 (Professor  George Norton),   Iowa  State  University,    Stanford University   (Dr. Sandra Archibald),   the
 University  of Massachusetts  (Professor Joe Moffitt), the University   of Arkansas  (Professor Mark Cochran),
 and  Harvard  University.

      The literature search and conversations  with the listed expert sources indicated   that studies of the
price elasticity  of demand  for  pesticides  are sparse,  and that  the existing   analyses  offer  conflicting
conclusions   and are often controversial.  Further,  an attempt at compiling  expert opinions  as to expected
elasticities  failed;  the lack of available  research  on this issue precluded   compact,  ready answers that could
                                                  C.6

-------
be conveyed  by telephone.   In  order to develop the elasticity   estimates, Abt Associates  developed  a five-
pronged approach.

      First,  as described  in Section  2.2,  Abt Associates  considered the  relevant empirical  studies.  Though
these studies do not comprehensively   answer  the question  at hand for reasons  that are presented below,  they
do provide  estimates of demand elasticity  for selected clusters.  The second  input, and the main source of
data  from  which  pesticide   elasticities   are derived  in  this analysis,   is U.S.  Department  of  Agriculture's
(U.S.DA.)  analysis  of the price elasticity  of demand  for  food commodities  (U.S.DA.,  1985, 1989).  The
elasticity  of demand  for farm inputs  can be derived from the elasticity  of the demand  for farm commodities
since demand for production  inputs  must  ultimately  reflect demand for the end  product.   Though the two
elasticities  may not correspond   exactly,  the  elasticity   of  demand  for the food commodities  can serve as a
reasonable   proxy  for  the  elasticity   of demand   for  pesticides   in the absence  of more relevant   data.
U.S.DA.'s  estimates of elasticity  and  the  use of these estimates  for  purposes  of  this  analysis  are discussed
in Section  2.3.

      The other three factors used to estimate the elasticity  of demand  for  pesticides   are (1) the feasibility
of employing   non-chemical   or non-biological   pest  control  methods,  (2)  the percent  of  production  cost
contributed  by the pesticide  of interest,  and (3) the productivity  of expenditures   for  pesticides.  Section 2.4
groups  pesticide  clusters  based on the feasibility   of substituting   another pest control method for chemical
and  biological  pesticides.  The greater  the  feasibility of substitution,  the higher the expected price elasticity
of demand.  Since  the clusters  group  chemical  and  biological  substitutes,   the ^potential  substitutes   for a
cluster  of  pesticides  are  cultural  or environmental    control  technologies,   such  as crop   rotation  or the
introduction  of predatory  insects.  The rankings of the feasibility  of non-chemical   substitution  for a cluster
of pesticides are based on Pimentel  et al. (1991).

      The analysis  of pesticide  contribution  to the cost of  production  of a commodity  is based  on U.S.DA.'s
published   estimates  of the  cost of  production   in the farm  sector (U.S.DA.,  1989a,  1989b,  1988).   The
greater  the contribution   to the cost of production,   the  higher  the expected  price  elasticity  of demand.
Pesticide contribution  to production costs is reported in  Section 2.5.
       Finally,   the productivity   of expenditures  for  pesticides  is examined  in Section  2.6.  In theory,  if
 pesticides  are highly  productive  (i.e.,  the costs of  pest  damage  without  pesticides  greatly exceeds the
 expenses of pesticide application),  a prescribed  pesticide  dosage will  be applied regardless  of some degree
 of price  variation.  In other words,  if pesticides  are highly productive,  the demand  for  pesticides   is likely
 to be inelastic.
                                                      C.7

-------
     O
     CO
     ctf

-------
      Section 2.7 combines the information   from the empirical  studies,  the elasticity  of demand for food
commodities,   the  substitutability   rankings,  the data on  pesticide contribution   to production  cost, and  the
measures of  pesticide  productivity   to estimate  the price elasticity  of  demand  for  agricultural   pesticide
clusters.   The U.S.DA. estimates  of the elasticity  of demand for food commodities  are used as the basis  for
the final  elasticity   estimates.   The other factors  are analyzed  to determine  cases in which  the elasticity   of
demand  for  food commodities  may vary substantially   from the  elasticity  of demand  for pesticides applied
to the food  commodities.   In cases where  there is a clear indication  that  the  elasticity  of demand  for. the
food  commodities   and the elasticity  of demand  for the  pesticides  applied  to the food commodities  differ,
the elasticity  estimates are adjusted  in the appropriate  direction.

      Precise quantification  of the elasticity  of demand,  however,  is not revealed  through  the examination
of feasibility   of substitution,  contribution  to costs, and productivity  of  the  pesticides.   The results only
indicate  whether demand for the pesticides  is likely to be more  or less elastic than  demand for the relevant
food  commodities.   Therefore,  unless  there  is compelling  evidence   that the elasticities  of demand  for food
and  pesticides  applied  to food  differ  substantially,   this analysis  relies on the estimates  of elasticity   of
demand  for food  commodities  to represent  the elasticity  of demand  for  pesticides  applied  to those food
commodities.  It should  be clear that the  resulting  elasticity  estimates serve as indicators  of the approximate
magnitude  of demand elasticity  and not as precise  quantifications    of these elasticities.
      22    Review  of Empirical  Studies  of the Price Elasticity  of Demand  For Pesticides
      The  empirical   analyses  of  the price  elasticity  of  demand  for  pesticides   can  be separated  into
econometric  analyses  and  other  analyses.   The econometric  analyses  of demand  elasticity  employ several
different   dependent  variables.   Variations  in the  dependent   variable  influence   the resulting  demand
elasticities.    In  particular,  the dependent  variables  differ  in the level of- aggregation  of pesticides  and in
whether  pesticides  are measured  in units  of production   or units of use.

      The level  of aggregation  of the pesticides  may influence  demand elasticity  by determining  the number
of close  substitutes  that  are available.   According  to microeconomic  theory,  the more narrowly  a product
is defined,  the more substitutes that are likely  to be available.  For example,  more substitutes  are available
for pork chops  than are available  for meat.               %

      If  a  product  has  many close  substitutes,   it  is likely  to be characterized   by  an elastic  demand.
Consumers  can react to a price increase  by switching products  without  much  loss of utility.   If a product
has a more  limited  number  of substitutes,  consumers   have  little choice  but to bear more of  the  price

                                                      C.9

-------
 increase.  For chemical  pesticides  in general,  substitutes  include  only labor and other non-chemical  pest
 control methods.   These  are also the  only  substitutes  for  fungicides,   herbicides,   or insecticides  since
 pesticides  are generally  effective   against  only  either  pathogens, weeds,  or insects.  Since  the  clusters  used
 in this analysis  were  chosen to include all close chemical  and  biological  substitutes  for  an end-use,  the only
 pest control  alternatives   are non-chemical  and non-biological.    Substitutes  for  specific active  ingredients,
 however,  may include other active ingredients  in addition  to the non-chemical,   non-biological   alternatives.

       For  the purposes  of determining   the  incidence  of  the  cost  increase  resulting   from new  effluent
 regulations,  the ideal price elasticity  of demand  is that corresponding  to each  pesticide cluster.  However,
 few  of the  relevant  analyses  that Abt  Associates  located estimate  elasticity   of demand  for clusters  of
 pesticides.    Some of the analyses  reviewed  in  this report  consider  pesticides  as a group as the dependent
 variable;  other  studies  analyze  herbicides,  fungicides,   and  insecticides   separately  or study  the demand
 elasticity  for pesticides  by crop.  Another  group  looks at specific  active  ingredients.

       In determining   the  elasticity  of demand  for clusters of active ingredients,  it  may at  first  appear
 reasonable to bound the elasticity  of demand  for  clusters  of pesticides by using  the elasticity  of demand  for
 pesticides   as a group as the lower  bound and the elasticity  of demand for  individual  active  ingredients  as
 an upper bound.  Since  pesticides  as a group will include  all  clusters  of pesticides,  it could be argued  that
 a cluster will exhibit  an elasticity  no  lower than the elasticity  of pesticides  as a group.   However,  since  the
 elasticity  of pesticides  as a group  represents  an average  of the elasticities   of clusters  it can not serve  as a
 boundary  for any one cluster.  Similarly,  since  the elasticities   of demand for individual  active ingredients
 within  a cluster  will vary,  the elasticity  of any  one active  ingredient  can  not act as an upper boundary  for
 the elasticity  of the cluster.   For purposes of comparison,   however,  this  analysis  considers  the empirical
 analyses  in two  groups:   those which  consider  pesticides  as a group  and those  which  consider individual
 active ingredients.

      A second  major variation  between  the regression  analyses  of demand  elasticities reviewed  in  this
report is whether the dependent  variable was measured in units of production  (e.g., pounds produced  per
year) or in units of use (e.g., pounds applied per  acre  per year).  Due to potentially  significant  inventories
of pesticides  and the dissimilar market structures  of pesticide  manufacturers  and packagers/formulators    of
pesticides,  units  of production   and use may result in different  estimates  of  elasticity.   Further,  some  studies
defined  the dependent variable  in absolute terms  while others used the percent  of crop treated.  Also, the
dependent  variable  was  alternately  measured in  units  of  expenditure   (e.g.,  dollars)  and units  of quantity
(c.g., pounds).
                                                     C.10

-------
      Finally,  the studies differed  in the specification  of the model  (e.g.,  simultaneous  equations  vs. single
equation  models, inclusion  of an independent  variable  for labor),  the time period included,  and the region
of the country considered.  All of the factors  discussed  above  contribute  to the difficulty  of comparing the
empirical  studies.

      The results of the analyses of elasticity  of demand,  categorized  by  their definition  of the dependent
variable,  are described  below.

Aggregated  dependent  variable  measured  in units  of use
      Five analyses were located which  estimated demand elasticity  for pesticides as a group  and measured
the dependent variable  in units  of pesticide  use.  The  studies are: Pingali  and Carlson  (1985), Miranowski
(1980), U.S. EPA (1974), Huh (1978),  and Burrows  (1983). The results  of these studies  are conflicting.   Huh
reports demand  for herbicides  and insecticides  used on corn as elastic.   Contradicting   this result,  U.§. EPA
(1974) indicates  that demand for corn and soybean herbicides  and  corn  insecticides  is inelastic. Miranowski
also concludes  that demand for  herbicides   used on corn is moderately  inelastic  when  labor  is not included
in the analysis.  However,  the  price coefficient  in his equation is  not significantly  different   from negative
one.   When Miranowski  includes  labor in  his  model,  price is  insignificant,   suggesting   that  labor is  a
substitute  for herbicides   used  on corn.   Miranowski   did not  find  price   to  be  a  significant   factor  in
predicting  the level  of corn insecticides  used.  Therefore,  his  model  offers  little  further  insight  into  the
elasticity  of demand  for insecticides.   Burrows also found  pesticide  price to be insignificant  in explaining
demand  for  pesticides  and mitacides  used  on cotton.   Finally,  Pingali  and Carlson estimate that the  price
elasticity  of demand  for insecticides  and fungicides   used in  orchards  to be significantly   different  from zero,
but not significantly   different   from  negative  one.

       Pingali  and Carlson  estimated  price  elasticity  of  demand  as part of a  larger,  multidisciplinary    study
over the 1976-1980  period  for  forty-seven   orchards  in  Henderson County,  North Carolina.   To analyze  the
effect  of errors  in  subjective    perception   on the  demand  for  pest  controls,   Pingali  and  Carlson  ran a
simultaneous  model  of pest populations  and  pest  controls.   Their model  involved  a five-equation  system
with  two  pest  population  equations   (insect and  disease  infestation   levels),  two  pesticide   equations
(insecticides   and fungicides),   and one pruning  status  or labor equation.

       The variables used  in the  pesticide  equations  were obtained  from  input demand  functions  developed
by Pingali  and Carlson.  The  derived  demand functions  had four  groups  of  variables:   biological,  input
prices,  risk aversion,  and human  capital.  The levels  of insecticides  and fungicides   were given  in terms of
pounds of active ingredients  applied per acre of orchard.   The cost per unit of insecticides   and fungicides

                                                      r.n

-------
  were  given  in dollars  per pound of  active ingredients.   A two-stage   least squares estimate  of the system
  resulted  in a price elasticity  of demand  for insecticides  of -1.39.   The  fungicide  price  elasticity of demand
  was estimated  as -0.92.  The elasticities  of demand for both insecticides  and fungicides   were found  to be
  significantly   less than zero but not significantly   different   from negative one.  The model  can therefore  be
  interpreted  to confirm  a negative  correlation between  price and demand; it  does not, however,  indicate with
  certainty whether  demand  is elastic or inelastic.

        Miranowski   (1980)  considered  alternative  pest management  systems  for  corn production  with  rising
  energy prices.   He used historical  data  from  U.S.DA.  agricultural  regions from  1968,  1971,  and 1976  to
  estimate  derived  demand equations  for insecticide  and herbicide  treatment.  Separate weighted  least squares
  regression models  for  insecticide  and herbicide  treatment  were developed  as follows:
 lnST,  + e
y
SCA
RE
p.
share of corn  treated  with  insecticides  (i)  or herbicides  (h),
price of insecticides  (i) or herbicides  (h),
price of fuel,
value of corn  output per acre,
share of corn  acres  in cropland  acres,
lagged  production-oriented   research and extension  expenditures,
farm  wage  rate.
                                                                                        and
       Miranowski  obtained  data  on insecticide  and herbicide  treatment,  as the share of corn  acres treated,
 from  the U.S.DA.  annual pesticide  surveys  for 1968, 1971,  and 1976.   The input price indices,  Pih and Pf,
 were  derived  from data in U.S.DA.'s Agricultural   Prices  -  Annual  Summary (for  1967,  1972, 1977).

       Miranowski  estimated price elasticity  of demand for insecticides   as -0.78.   However,  the coefficient
 was not significantly   different  from  zero.  He reported  results of two  herbicide  demand  models, one with
 and one without  the price of labor.  When the price of labor  is not included  in the analysis,  the coefficient
 on herbicide  price,  -0.75,  is significantly   less than zero but  not significantly   different  from  negative one.
 Therefore  the elasticity  of demand may be  either  elastic or  inelastic,  but only  moderately  so.

      When the wage rate is held constant,  the herbicide price coefficient  is 0.03 and becomes  insignificant.
Though  the results of the  model  with labor held  constant  may be consistent  with  inelastic   demand  for
herbicides,  the  coefficient  on labor  is positive  and  significant,   suggesting  that  labor  and herbicides  are
substitutes.   The coefficients  of the price  of pesticides in the two  herbicide  models  suggest that  the  price
of labor and the price of pesticides are co-linear.  Since the coefficient  for the price  of herbicides  becomes

                                                     C.12

-------
insignificant   when  labor  is included  in the model,  it may be the case that  the  labor price variable  is
dominating  the herbicide  price  variable  with  the result that  change in the dependent  variable  appears to be
largely  a function  of the cost of labor rather  than the price  of herbicides.  However,  when labor is absent
from the model, the coefficient  of the price of pesticides probably includes  some of the influence  of labor
rate changes. The "true" elasticity  of demand  is therefore  likely  to fall between the two coefficients  of -0.78
and 0.03,  still indicating  inelastic  demand.

      Huh (1978)  estimated pesticide  price  elasticity  of demand  in his doctoral  dissertation.   Using cross-
sectional   farm  data from  Minnesota,   Huh  modeled  pounds  of  active  ingredients   of herbicides   and
insecticides  used  on corn  per  farm  (C^).  Exogenous   variables  included  in his final   aggregate  demand
equation  were:

      j£w    =     adjusted and weighted  price  of pesticides (dollars  per pound),
      XT      =     acres of corn per farm,  and
      I\     =     a dummy variable  for crop  rotation  plan (0 when  farmer  did not intend  to plant corn
                   again  in 1978,  1 when farmer intended to plant some or all  of corn  in  1978).

      The results of the regression analysis  were as follows  (standard  errors  are in  parentheses):
InQ,-  =     2.212  -  1.464 In X,w  +1.099 In x, +0.381
                     (0.161)         (0.064)       (0.110)
                                                                   +e
      The coefficient   of the price of  pesticides  was  significantly   less than  zero and also significantly
different   from  negative   one,  indicating   elastic  demand.   However,  since  an  independent  variable  for
pesticide  substitutes (e.g., labor) was not included,  the coefficient   on pesticide price may include the effect
of changes in labor or other substitute  prices  and therefore  have a bias towards  greater  elasticity.   Hub's
model is  therefore  likely  to overstate  the elasticity  of demand  to an unknown  degree.

      As part of an analysis of farmers'  attitude towards alternate  crop protection  methods, U.S. EPA (1974)
described  a survey  of  farmer sensitivity  to pesticide  price changes.  Farmers in Iowa and Illinois  responded
to the survey as follows:
                                                    C.13

-------
      Percent of Respondents
      Iowa         Illinois
       62
       55
       29
       77
       72
56

55

39

61

86

67
(of corn  growers)  believe  all  of their  corn  acres  need
herbicides  each  year
(of corn growers) would not change  herbicide  use if cost
doubled
(of corn insecticide   users) believe all of their corn  acres
need  insecticides
(of corn  growers)  believe  all  of their  corn  acres  need
insecticides
(of corn insecticide   users) would  not change  insecticide
use if cost doubled
(of soybean  growers)  believe  all  of  their  soybean  acres
need  herbicides  each year.
(of soybean  growers)  would  not  change  herbicide  use if
cost doubled
      The results indicate that the majority  of farmers  surveyed  are insensitive  to price changes.  Demand
for corn  and soybean herbicides   and corn insecticides   appears to be inelastic.

      The final study in this category was conducted  by Burrows  (1983).  Burrows  tested the hypothesis  that
integrated  pest  management  (IPM)  will  significantly   reduce  pesticide   use.   He  also  examined   the
methodological  issue of simultaneity  between pesticide  use and  IPM adoption.   Burrows  considered  only
insecticides  and mitacides.   His  data  were  drawn  from  a random  sample  of San Joaquin  Valley  cotton
growers.  The observations  contain  detailed  information  on output,  pesticide  and other input use, cost, and
revenue for 47 growers  spanning  a 5 year period from 1970-1974.

      Burrows performed  a Generalized  Least Squares (GLS)  procedure  for  both single and simultaneous
equation  models.  The dependent  variable is insecticide  and mitacide  use measured  in sales dollars per acre
of cotton grown.  Explanatory  variables  include  average pesticide  price per pound,  an IPM consultant  fee
per acre,  and the expected  yield in pounds per acre.  Weather and cultural practices  are included  as proxies
for both the size of the pest population  and pesticide  persistence in the environment.   A risk proxy,  the ratio
of acres planted  in cotton to total  acres,  is used assuming  that,  for higher ratio values, risk-averse  growers
                                                     C.14

-------
will  be likely to use more pesticides  as insurance  against  crop loss.  Pesticide  price is a quantity-weighted
price index.

      In both the single and simultaneous  models,  pesticide prices are insignificant.   Burrows explained  that
this  may result from limited degrees of freedom  (there are only ten price observations).   He also offered
an alternative   explanation  that  expenditures   may  not be  sensitive   to price  when  conflicting  sources  of
information  - personal experience,   pesticide salespersons,  IPM consultants, and extension  representatives  -
 affect  the decision  to spray.  Another  potential  explanation   is that if  the  expected  rate  of return  from
pesticide use is high,  price movements  over a modest  range would  not have  much  explanatory,  value.  The
price  elasticity  determined  by the  single   equation  model is approximately   unity,  -0.90.   The  elasticity
resulting from the simultaneous  version  of the model  is -1.23.  Since the coefficients   were  not significant,
these values  are  inconclusive.

Aggregated  dependent variable  measured   in units  of  production
      An  earlier  version   of an economic  impact   assessment  of  pesticide  effluent   guidelines  analyzed
aggregated  pesticides and  measured the dependent  variable  in units  of production  (U.S. EPA,  1985).  U.S.
EPA  found  that the price  elasticity  of  demand  for pesticides  as a  group,  as  well as  for  fungicides,
herbicides,  and  insecticides  was significant  and inelastic.   EPA estimated  pesticide  elasticity  of demand
based on  the  following  log-linear  function:                                                               ,
 In PRODt

 where:
 PRODt,  PPRODt..,
a +b In PROD^  +'c In ACRE, +d In RPRIC^  +f
production  of pesticide  active  ingredients  in year  t and t-1
acreage  of .principal   crops  planted  in year t       .,
real unit price  for pesticide active  ingredient in year t
Industrial  production  index in year t
       Elasticities  were  calculated  for herbicides,  . insecticides,   fungicides,   .and  all pesticides.    Pesticide
 production  rates were obtained  from U.S. International  Trade Commission,  Synthetic Chemicals.   The units
 of  production  were  not given.   Pesticide  prices were  average  prices  for  each product  group  and  for  all
 pesticides   and  were  calculated   from  U.S.  International  Trade  Commission,   Synthetic   Chemicals  and
 converted   to real prices using the GNP Deflator.   Based on this  model, EPA  obtained  the following  results:

                                                       C.I 5

-------
 Ln of
 Production
                   Intercept
               Ln  Acres
               Ln Real
               Price
               Ln
               Production
               Previous
               Year
                    Industrial
                    Production
                    Index
 Herbicides
 R2=0.98
-12.93
(-3.51)
3.19
(4.02)
-0.67
(-2.49)
0.299
(1.88)
-0.00651
(-3.24)
 Insecticides
 R2=0.68
 Fungicides
 All Pesticides
 R2=0.89
-3.49
(-132)
-1.46
(-0.47)

-6.42
(-2.26)
1.53
(2.90)
1.04
(2.02)

1.88
(3.02)
-0.32
(-2.51)


-0.35
(-2.07)

-0.49
(-2.37)
0.142
(0.57)


0.05
(0.18)

9.427
(1.84)
       T-statistics  are given  in parentheses.   The analysis  indicated  that demand is inelastic  for  each of the

 three pesticide  groups as well as for pesticides  in general.  All price  elasticities  were  significantly  less than
 zero,  and significantly   lower  than one in absolute  value,  except for  the coefficient  for herbicides which is

 not significantly   different  from  negative one.  The model,  therefore,  indicated  that  the price  elasticity  of
 demand  for insecticides,   fungicides,   and  all pesticides  is inelastic.   According  to the model,  the  price
 elasticity  of demand  for  herbicides  is near unity,  meaning  that demand  may  be either  elastic  or inelastic.


       The analysis suggested  that  the demand for herbicides  is morp elastic than the demand for insecticides

 or fungicides.   EPA explained  that during  the 1970's  herbicides  experienced  a large increase  in  application

 rates and the proportion  of acres  treated  and that "the coefficient  on acres in  the herbicide equation reflects
 this".  The authors  also noted that "one of the reasons the amount  of variation  explained by the fungicide
 equation was so low was that a very large  proportion  of fungicides  were used for non-agricultural   purposes".
 The authors were unable to explain  why business cycles  are important for herbicides  and not for  the  other

 two product  groups.  It should be noted that the study did  not include  a variable  for prices  of substitutes
 or final products.   If these  prices  are correlated   with  pesticide   prices,   the  coefficients   may be  biased.

 Finally,  the authors did not  identify  the type of end-use  (e.g., agriculture,  commercial, domestic)  of the
pesticides  included  in their  analysis.


      Another  factor that may influence   the results  obtained  by EPA is that  the dependent   variable  is
measured  by weight (pounds). This may not accurately   reflect price elasticities  since  more effective   and
                                                     C.16

-------
expensive   pesticides   may be  substituted  for  pesticides   requiring   higher  doses  to be  effective.    EPA
acknowledged  this issue, stating  that there has been  a decrease  in the amount of insecticides  produced  due
to the substitution  of synthetic  pyrethroids  for  more  conventional   pesticide   ingredients.    The synthetic
pyrethroids  are more powerful  than conventional   pesticides,  thus reducing  the weight  of pesticides  required
for pest control.   EPA asserted,  however,  that in terms of total insecticide  production,  these impacts  are
small.

Active  ingredient  as dependent variable:   measured  in units  of use
      The following  three studies  examined demand  elasticity for specific  pesticides  and measured  demand
in units  of use:   Lacewell  and Masch  (1972),  Carlson  (1977),  and Carlson  (1977a).   Lacewell  and Masch
found  that the demand  for the herbicide  2,4-D  was inelastic.   Carlson's  price coefficient  for 2,4-D  was
small  and  negative,  but not  significant,  which  may be consistent  with  price  inelasticity.    Carlson's
significant  price  coefficients  for  insecticide  active ingredients  indicated  that demand is elastic  hi both  the
short-run  and the long-run.

      Lacewell  and Masch  selected a five county  area in the Northern  High Plains of Texas as the study area
to evaluate  the  effect  of a tax vs.  a marketing  quota  farm  program  on  the level of chemicals  used in a
specific  agricultural  region.  The  primary  agricultural  crops of  the area were grain sorghum  and wheat.  To
control weeds in wheat  and  grain  sorghum,  herbicides,  especially   2,4-D,  were utilized.
      Using data on land utilization  for 1969,  Lacewell  and Masch constructed  a linear programming  model
for the five  county region.  For illustrative  purposes, the change  in the quantity  of 2,4-D  used  hi response
to changes  hi the price of 2,4-D  was investigated.   Requirements  for weed control  were assumed to be met
by  one of three weed control alternatives:   (1) use of 2,4-D,  (2)  use of 2,4-D  and  dicamba,  and (3) use of
dicamba,  other  chemicals  and additional  tillage   operations.   The  price  of  2,4-D  was increased  by
increments,  using parametric  programming,   from 52 cents per pound to $37.00  per pound,  at which  point
the model predicted  no 2,4-D  would  be used. In response  to a more marginal  price increase of 78 percent
(from $0.52 to $0.93  per pound),  Lacewell  and Masch  predicted  a decrease in use of 2,4-D  of  30  percent.
This  translates  to an inelastic demand of approximately   -0.38.

      Carlson's two articles  (1977 and 1977a)  used the same log-linear model to examine  demand elasticities
of particular  herbicides  and insecticides.   Carlson  first  considered price elasticity  of demand for pesticides
as part of a study  to determine  the importance  of pest resistance  to insecticides  in affecting  demand  for
specific  compounds.   In his second article,  Carlson  illustrated some advantages  and disadvantages  of price
incentive  systems relative  to quantity  incentive  systems  for  pollution control.

                                                     C.17

-------
      Carlson  used individual   farm  data on insecticide   use from  several  cotton  production  regions  to test

hypotheses  of decreasing  productivity   of  insecticides  and substitutability  between  chemical  types.   His

original  estimation model  is
where

Q
R,,
             quantity  of a given  insecticide  purchased ' in year t (pounds  of actual  material),
             insecticide  price  deflated  by an index  of all agricultural  input prices,
             substitute  insecticide price,    .
             resistance  index,
             agricultural  product  price index,  and
             error term.
      The agricultural  product price variable,  C^, was not statistically  significant   and was deleted  from the

model.  A lagged dependent  variable  was added to account for the assumed effects  of delayed adjustments

to price changes.  Carlson used  this model to analyze several of the largest  selling groups  of insecticides.

The specific  dependent  variables  and their  price  elasticities were  as  follows  (standard errors appear in

parentheses):
       Dependent  Variable

      (A) Domestic and  foreign  sales of cyclic
      organophosphate  insecticides   (1953-1970)

      (B) Same as (A)  except  divided by domestic
      cotton  acreage planted

      (C) Total sales of parathion  and methyl
      parathion  (1953-1970)

      (D) Domestic sales of DDT  (1945-1969)
      (E) Domestic  sales of DDT (1953-1969)
                                                             Price  elasticity

                                                                 -1.461
                                                                 (0.796)

                                                                 -1.552 '
                                                                 (0.780)

                                                                 -1.06
                                                                 (0.273)

                                                             '    -0.667   '
                                                                 (0.397)

                                                                 -1.091
                                                                 (0.625)
      Insecticide  price has the expected  negative  effect  on insecticide  purchases.  Carlson  concludes  that
sales of the compounds are quite responsive  to price,  indicating  that there are many substitute  pest controls
in the long run.  None of the  coefficients,  however,   are significantly   different   from negative one,  so the
model indicates that elasticity  of demand is unlikely  to be either highly  elastic  or highly  inelastic.
                                                     C.18

-------
      In Carlson's  subsequent  article  (1977a)  he reported  a slightly  different  elasticity  for the parathion  and
methyl  parathion group and also includes  the herbicide 2,4-D  in his analysis.  Further he reported long-run
elasticities  for DDT and 2,4-D.   The results were as follows:

      Dependent Variable                                  Price elasticity

      (F) Domestic sales of parathion,  methyl                   -0.945
      parathion  (1953-1969)                                     (0.339)
      (G) Domestic sales of 2,4-D  (1950-1970,     .              -0.193
      except  1965-68)   divided by  cropland index               (0.349)
      (H) Same  as (D)  except  long-run                          -1.53
      (I) Same as (G) except  long-run                           -0.594

             The analysis indicates  that  the elasticity   of DDT increases  substantially  from the short-run  to
the long-run,  as would  be expected  as more substitutes  may  be developed  with time.  The coefficient   for
2,4-D  shows demand to be inelastic, but is insignificant.   Though this result may be consistent with inelastic
demand,  it is inconclusive.

Active  ingredient  as dependent   variable:   measured  in units  of production
      Abt Associates  located  no studies which  fit  this category.
      Table 2.1 summarizes  the empirical  studies  discussed  above;  Figure  2.2  displays  the empirically-
derived  elasticity  estimates  graphically.   As can be seen from Figure  2.2, elasticity  estimates ranged from
approximately   zero to -1.5.   While most  estimates  indicate  that the  demand for  pesticides  is relatively
inelastic,  the results are inconclusive.   Since the studies used  different  models  and,  in particular,  different
dependent  variables,  variation  in  the  estimates  is expected.   The  number of  studies  which  considered
clusters  of pesticides as the  dependent  variable  was insufficient   to draw reliable  conclusions  as to the price
elasticity  of demand for dusters of pesticides.  However,  the results  of the analyses which  did define  the
dependent  variable  as a cluster  of  pesticides  will  be  considered  in the final  estimations   of demand
elasticities.
                                                    C.19

-------
8
CO

1
<
,-5
CM*

® O
& u



^8
            a 5? a s?
                                            1
            41
            II
            I I
                                          v*y •>*
                                          •4j ^i
                                          ^ ^,
            1
                                                           5
                                                           d
                                                I
                                                .2
                                                         S f S  §

                                                         s   ?  a.
                                                   i
I -8

s 1
C V

« .S


S
                                               ,-s
                                       C.20

-------
       II

       t &
       3 -S

       II
         '
  e
O
  ta
  CO
          H  *
P            th«
            o
                        oe  'u m • '2  Ot
                        «  e n g  oo

                        o  <3 o &  d
                 I
                                                   C.21

-------
C/3

Ul
CO
— o

5§
o? U
5 W
                f
                   t!
               i

                                         £  s
                                         I
                                           1  I

                                                  11
                                                           r
                                         F
                                              I
                                                               C.22

-------
3|
Q) r'i
1 S \
alt
t .?
  S
  E
  •s  1
  S  1
  ,
0. O
   1
                         8.

                         £
                         o"
       •
ing

ar (
of
                                                 s-
                                                 o
                                          "^

                                          ti  1

                                    C.23

-------
        on
        
-------
      23.    Price  Elasticity of Demand  for  Food Commodities
      Given that the empirical analyses are insufficient   to derive estimates of demand elasticity  for clusters
of pesticides,  an alternative  method of estimation of the elasticity  was developed.  The method used  in the
remainder  of Section  2 of this report relies  on a consideration  of four  factors:   (1) the price elasticity  of
demand  for food commodities,  (2) the availability  and relative  costs of non-chemical   pest management,  (3)
the  contribution   of pesticides   to  the  variable   cost  of farm  production,   and  (4)  the  productivity   of
expenditures  on pesticides.   Though  these  sources  will not  reveal  precise  quantifications   of  the price
elasticity  of demand  for  pesticides,  they  can be used to indicate  whether  demand  for  the pesticides  is
expected  to be elastic  or inelastic and to construct  approximate  estimates of the elasticity  of demand.

      Since  the  demand  for  particular  inputs  to a product  is  in  part  derived   from demand for  the end
product,   the demand  for  pesticides used in  the  agricultural  sector will  be influenced  by the demand for
food.  The  demand  elasticities  of food commodities,  developed  in this section,  are used to provide  initial
estimates of the elasticity  of demand  for clusters of pesticides.

      Estimates  of the direct  price  elasticity   for foods  at the retail  level are taken from  the U.S.DA. report
entitled  "U.S. Demand for Food:  A Complete  System of Price and Income Effects"  (1985), authored by Kuo
S. Huang.   Using  a constrained  maximum  likelihood   method,   Huang  developed  statistical   procedures for
estimating  a large-scale   demand system  from  time-series  data.    He then  applied  his procedures  to an
estimation  of a domestic food  demand system including forty  food items and  one non-food  item.  The food
items,  direct-price   elasticities,  and standard  errors  of the estimates  are  listed in Table 2.2.  The  estimated
elasticities  ranged  from -0.0385  (cabbage)  to -1.378   (grapes).   Huang  noted that an  exact West for the
statistical significance   of the elasticity  estimates is not applicable,  given the assumptions   of a maximum
likelihood   model.   For the  purposes  of his analysis,  Huang  considered  an  estimate to  be statistically
significant   if the  estimated  elasticity  was larger than  its standard  error.  While estimated elasticities  with
relatively large  standard  errors  may imply that the estimates are not statistically   precise,  only four  of the
thirty-four   commodity  elasticity  estimates  used in  this analysis   had  a standard error greater  than the
elasticity  estimate (butter,  other fresh  fruits,  carrots,  and cabbage).

      Huang also provided  estimates of demand  elasticities  for the  following  aggregated food groups:  meat,
staples,  fats, fruits,  vegetables,  processed fruits  and vegetables,  and desserts.  The direct  price  elasticities
he obtained  were  negative  for all seven food  categories, with magnitudes  ranging  from -0.08 to -0.34.  For
purposes  of the  discussion  here,  however,  the individual  food  items must be reorganized  to correspond  to
the crops included  in  the  clusters.
                                                    C.25

-------
                               Table 2.2
               ESTIMATED DIRECT-PRICE ELASTICITIES
(USDA,

Commodity
Beef & veal
Pork
Other meats
Chicken
Turkey
Eggs
Cheese
Fluid Milk
Evaporated & Dry Milk
Wheat Flour
Rice
Potatoes
Butter
Apples
Oranges
Bananas
Grapes'
Grapefruits
Other Fresh Fruits
Lettuce
Tomatoes
Celery
Onions
Carrots
Cabbage
Other Fresh Vegetables
Fruit Juice
Canned Tomatoes
Canned peas
Canned Fruit cocktail
Dried beans, peas, & nuts
Other processed Fruits & vegetable
Sugar
Ice Cream
1985)
Direct-Price
Elasticity Stan
-0.6166
-0.7297
-1.3712
-0.5308
-0.6797
-0.1452
-0.3319
-0.2588
-0.8255
-0.1092
-0.1467
-0.3688
-0.167
-0.2015
-0.9996
. -0.4002
-1.3780
-0.2191
-0.2357
-0.1371
-0.5584
-0.2516
-0.1964
-0.0388
-0.0385
-0.2102
-0.5612
-0.3811
-0.6926
-0.7323
-0.1248
-0.2089
-0.0521
-0.1212
                                                           0.0483
                                                           0.0327
                                                           0.2045
                                                           0.0608
                                                           0.1332
                                                           0.0225
                                                           0.1174
                                                           0.1205
                                                           0.2642
                                                           0.1026
                                                           0.1438
                                                           0.0689
                                                           0.1748
                                                           0.1469
                                                           0.1465
                                                           0.1334
                                                           0.1829
                                                           0.1067
                                                           0.5471
                                                           0.0656
                                                           0.0624
                                                           0.0636
                                                           0.0693
                                                           0.1816
                                                           0.0405
                                                           0.1436
                                                           0.1006
                                                           0.1072
                                                           0.1746
                                                           0.3677
                                                           0.0313
                                                           0.0921
                                                           0.0172
                                                           0.0848
Source:  U.S.D.A. (1985). U.S. Demand for Food:  A Complete System of
Price and Income Effects.  By Kuo S. Huang.  National Economics
Division, Economic Research Service.. Technical Bulletin No. 1714
                              C.26

-------
      To estimate  an average elasticity  for individual  crops in a cluster,  the elasticities  of the included crops
are weighted  by the quantity  of the relevant  pesticide  applied to that crop, as reported  in Pimentel  et al.
(1991).   This weighting   factor  incorporates  the fact that pesticide  use varies  between  crops; the  elasticity
of demand  for  a crop with heavy pesticide  use will  more greatly  influence  the elasticity  of demand  for the
relevant cluster  of pesticides  than will  the demand for a crop  with low pesticide  use. The resulting  elasticity
estimate  is not  a measure of the elasticity  of the entire cluster  of crops (unless the cluster  consists  of only
one crop).  Rather,  it is  a measure  of  the weighted  average  elasticity  of the individual  commodities  in the
cluster.    The elasticity   of the entire  cluster  will  be  lower  than the average  elasticity   of the individual
commodities  due  to the reduction  in the  number of substitutes.   For example,   people may easily substitute
beef for pork  and therefore  these individual  commodities  may have  relatively  high  elasticities.   However,
substitutes  for  all meats  are  less readily  available  and  this category is likely to have  a lower elasticity  than
the average  elasticity  of individual  meats.

      Since  the elasticity  of the demand  for  food  commodities  is assumed to represent  the elasticity  of
demand for pesticides,  this  elasticity   will also be overstated.  The overestimation  of the value of demand
elasticity  will likely  result in an exaggerated  estimate  of the fraction  of cost increases that is borne by the
manufacturers.   In  the  absence  of more  appropriate  data, however,  this  value provides  a reasonable best
estimate  of the  demand  elasticity  for  clusters  of pesticides.

      Table  2.3  displays  the average elasticities  for the  clusters based  on Huang's analysis.  The  elasticity
estimates for the clusters  represented  range from -0.12 (herbicides on sugar beets, beans,  and peas) to -1.38
(fungicides  on grapes, herbicides  on grapes,  and insecticides  on grapes). This  range of values indicates that
the demand  for the food clusters varies from  highly  inelastic  to somewhat  elastic.

      While the calculations  for most  of the clusters  are straight-forward,    the estimation  of elasticity  for
the six  clusters   containing  crops  that serve as animal  feed required an  intermediate  step.  The  elasticity  of
demand for corn, sorghum,  soybeans,  and  alfalfa  - all crops  that are largely  used  for  animal feed - was
calculated  from Huang's  estimates  of the elasticity  of demand  for animal  food products.
      An average  elasticity  for animal feed crops can be obtained  by weighting  the elasticity  of each animal
product  by the amount  of that product  consumed.  Huang  provides  "the retail weight  equivalent  of civilian
food  disappearance",   a measure  of consumption,   for each food item.  This weighting   calculation  yields an
elasticity  of demand  for animal  products  of -0.55.  However,  for this weighting  method to accurately  reflect
the elasticity  of demand for feed crops, it must be true that a unit of feed yields  equal units of all included
animal  products.   This  is not the case.  The  yield  rates  of dairy products  and eggs are substantially   higher
                                                      C.27

-------
                  \o
               1 *l
               .« .0

IO —i  \O
o o  —<
                          o o o
                                          8 8  £ 8
                          o o\ —•  —
                          O O —'  O

                          O O O  O  O O O O  Q
                                                                            o  o
                  «o
               P-i  O
             
-------
                     VO




                 "8  5|
                 jS  ^j
                  Of)  '^

                  O  RJ

                 ^  5
   u
a
   u
   <4-
   o

   .«

   •s
   •J3
   en


   S
   e
   i
                 .
                    CO
                    3


                    O
0\
VO
O
1
8

8
»— i
S
CD






1
 — vo
00 CN O O
1/1 vo
O\ CN ON
vq -« vo
o o o
i i i
3
B
CO
«
8,
f
CO
e
' . CO CU
ft q} • | W
tO 2- •''3




J5
0.
a
o
o
i
11.
8 -a
CO CB
1 1
£ s
S3 S
J3 Q.
oo O CN O O
— O O O CN
o o o o o
1 1 1 1 1
oo o O O O
o o o o —
SIT) — i O VO
o i/i CN r~
vo O O O vo
O CN Tf CN
CN CN CN — <
O O O O
.1111
•4-1
3
B
to
to
' ' •£« to"
.C B
111
-41S31
UM .BJ jj i t Q
w OJD o *ii'
u
B
es
o
es
00
3
CO
og
tfa ^
« e-
! t

VI Ui
*l> O
IS o
S x
g
_J

o
O

O

O
o
i





to
 O
1 1 1 1
•* >/•> -^ CD
o vo m o
CD 0 0 -^
>n >r> o o
o oo TT m
0 O* 0 «
ON CN in
vo — « O
CD O CD
111
3
°&
CO
i '
«y
co M
a. 1 '
1 1 |1







CO
a
8
CL,
1
0 -
CO *^
II
jo «
S g>
-C co
                                                        C.29

-------
                        \o
                    "8  M
                     a>  a
                        W
                    *  «
                    PH  O
cs   o
    m
 1
ol
                       I
                       o|
S    —  —4 in  o  o r— —
    o  o p  o  o —• o

o'o'o'oo'o'oo'o
                                                                     8
                                                 Tf  VO  — O
                                                 o  o  o o
                                                        s  a  s
                                                            8
                                                                     ooooooooo
                               o  o  o
g  a
                                                      t—  t-
                              8
                               OOOOOOOO—"
O  O  —•  O  O  -* >?;  O  S

OOOOOOOO-^
                                                                                   8
                                                                                   8
            o o
                                                         o\
                                              O  CN  00  -H  I—
                                                 r—  m o\  cs  o
                                                 CM  1/1 O  O  Tt
                                                            8  S  5
                                                                                                                 8
                               OOOOOOOO—'
                                                                     OOOOOOO-lOf)
                                   VO  OO O
                                              o  o  en cs
                                                                                    o  o  c»i  ?3
                               OOOOOOOO
                                         VO  00  O
                                         ^O  C^  C*J

                                         o'  o  o o' o'  o  o'
                                                                                  8
                                   to  is
s  s  a
J2  2  8

                                                  00

                                          •—   I-  JD
    w   o  ra  •»
    od,o
                                                                         80  ^
                                                                         •S   2
                                                                    .=,  a  o
                                                 «  a
                                                 o  S
                                                               5  2
                                                                                                                  00
                                                                                                          00
                               00
                                                                     eo
                                                                C.30

-------
  en

  U
  c
  S

  S

15
CM

cu
  CU
  VB

  'G
  •o
  VI
  ca
  u
  e
  «
2
• — UJ
^ S
I
qi CO
U %
w ?•
U t4_
CU 0
W ,.
& ^
CD CO
•a c _
!a -.§ >

w *S Wr
O, O .X
CU
•c i
i .a
1 «
js w
O W






1
u





t-l
'a
C
























1







CM — ("I VO
o o 10 >/•>
d d d d
i i i i

in oo t— o
— o r- o
odd —




So o o
i/^ O 10
— d >ri \d



vg 5 £i
— CM Ov
— — . \o
? ? ?'

3
c
CL.
CO
C
O co
"° §
•S lg >. o
1«4
.8
w o
11
8 i
en -C
CO %
•a ^
'o t£
1 1
.s S.
— >/•> vo o —
— O O O CM
d d d d d
i i i i i

>n CM CM o o
0000 —



c: c
O O O CM CM
O O — ; O — ;
r~- fi fi O fi



5
O CM rf CM
CM CM CM — <
o' d d o'
1 1 1 1

3
3
2 ^

•fi ^*
1 g 1
1: 2 1 '•§ -
ca ofi O CS*

"3 «>
C3 
§|
| | =:
.— 
O
CO
§
1
o
o
                                 r.3i

-------
 Sources for Table 2.3:

 Values for "own-price elasticity" were obtained from U.S.D.A. (1985).
 Values for "pesticide Use" were obtained from Pimentel et al. (1991).

 Notes  to Table 2.3:

 /I      The price elasticity of demand for bananas is  not included since a separate estimate of the quantity
         of herbicides applied to bananas is not available.  Also, fruit categories are only included if they can
         be assigned to a single cluster.  For example,  "fruit juice" is not included since it could include apple
         and orange juice, and therefore overlap two clusters.

 /2      Vegetable categories are only included if they can be assigned to a single cluster,  for example,
         "other processed fruits and vegetables" is not included since the category overlaps  two clusters.

 /3      Crop  is assumed to be fed to animals. See text for explanation of elasticity estimate.

 /4      The elasticity estimate is for dried beans, peas, and nuts. No separate elasticity estimates for these
         foods are available.

 /5      The elasticity estimate for sugar does not distinguish between sugar beets and sugar cane.

 /6      Elasticity estimate is for wheat flour.

 /7      Includes lemons, cherries, peaches, plums,  and "other fruit"

 /8     According to the 1989 "Agricultural Statistics" published  by the U.S. Department of Agriculture, 34
         % of all tomato acreage is used to produce for the fresh market and 66% of the acreage is  used to
        produce tomatoes for processing. Pesticide use is split between fresh and processed markets using
        these percentages. While this split will not be precise since production per acre and pesticide use
        may vary, it is used as a reasonable approximation.

 /9     Includes cucumbers, peppers, sweet potatoes,  and "other vegetables".

 /10    The category "other gram" is excluded since elasticity estimates are  not available.   Use of herbicides
        on "other grains" is relatively minor,  at 2.7  million kgs per year.

 /ll    Since estimates of the elasticity of cotton are not included in the U.S.D A. report,  cotton is not
        included in the elasticity estimate for the cluster. Herbicide use on cotton, estimate at 8.2 million
        kg/year, is small compared to herbicide use on soybeans. Therefore, the elasticity estimate  for the
        duster should not be substantially affected  by  the absence of an elasticity estimate for cotton.

 /12    Includes pecans and "other nuts"

 /13    The analysis assumes that half of herbicides used on peas are used on canned peas with the
        remainder used on dried peas.

 /14    Includes all herbicides apph'ed to beans and one-half of herbicides applied to peas.

/15    "Percent of Use" equals "Pesticide use on crop"/"Pesticide use on cluster"

/16    "Weighted Elasticity" equals summation of ("percent  of use" multiplied by "own-price elasticity")

/17    Since estimate of the elasticity of demand for tobacco are not included in the U.S.DA. report,
        tobacco is not included in the elasticity estimate for this cluster.  However, since about 80 percent of
        the insecticides applied to crops in this cluster are applied to soybeans, peanuts, and wheat, the
        absence  of an elasticity estimate for tobacco should not dramatically affect the elasticity estimate for
        the cluster.
                                                  C.32

-------
than  the yield rates of meats  per unit  of food.  Therefore,  a weighted  average  of the food elasticities  based
on consumption   would  be biased towards the elasticities  of dairy  products  and eggs. That is, the elasticity
values  for  dairy  products  and eggs would  influence  the resulting  average elasticity more  heavily  than  is
appropriate.

      As can be  seen from  Table 2.2, the elasticities  of demand  for dairy products  and  eggs are generally
lower than the elasticity  of demand  for  meats.  Weighting the elasticities  by consumption  is therefore  likely
to understate  the elasticity   of demand  for  feed crops.  To avoid  this  underestimation,   the  elasticity  of
demand for animal  feed is calculated  based only on the meat products.  The resulting  estimate  of  -0.69  is
conservative  in that it  is likely  to  somewhat  overstate  the  elasticity  of demand  for animal  products,  and
therefore  animal  feed.   This conservative   value,  however,  still  indicates  that demand  for feed crops  is
inelastic.

      Huang's  report analyzed  demand  elasticity  for foods  at the retail  level.   U.S.DA.  has also analyzed
the elasticity  of demand  for farm products  by modeling  the quantity of the farm  product as an input  in food
processing  (U.S.DA., 1989).  The analysis  considers  eight  commodities:   beef and veal,  pork, poultry,  eggs,
dairy, processed  fruits  and vegetables,  fresh  fruit,  and fresh  vegetables.   U.S.D.A.'s results are consistent
with  previous  findings,   and  show  that all  own-price   elasticities  are negative  and  less than  1 in absolute
values.   The  authors found  that,  with the exception  of poultry,  farm-level  demands are nearly  as  large as
the corresponding   retail  elasticities   or somewhat  larger than  the corresponding   retail elasticities.    Since
specific  commodity   elasticities  are not given and since  the  findings  indicate  that  farm-level   elasticities  are
similar  to retail-level  elasticities,  this analysis uses  the more  detailed  values  for elasticities   that are  given
in Huang's report.                                                                         •

      2.4.    Feasibility  of Non-Chemical   Substitution
      In order to further  delineate  variations  in the elasticities  of demand exhibited  by each cluster,  one can
examine the  market characteristics   that, according  to microeconomic  theory,  influence  the price elasticity
of demand.   These  characteristics  include  the availability   of  substitutes  for the  product,  the contribution
of the product  to the cost of production,   and the  productivity  of expenditures  for the product.  This section
discusses   the availability   of substitutes  for  clusters of pesticides.   Section 2.5  considers   the  impact  of
pesticide  contribution to the cost of production while  Section 2.6 evaluates  the productivity  of expenditures
for pesticides.

      As discussed  earlier,  demand  elasticity  is,  theoretically,  a function  of the availability   of substitutes,
among  other factors.  If a product  has many  close substitutes,  it  is likely  to be characterized  by an elastic
                                                      C.33

-------
demand.  Substitutes for a pesticide  active ingredient  include  an alternative  active ingredient  as well as non-
chemical  substitutes.   In constructing  pesticide  clusters,  U.S. EPA's  Office  of  Pesticide  Programs  (OPP)
grouped  all active  ingredients  which  are substitutes  for each other.  The  active ingredients  included  in the
clusters  are both chemical  and biological.    Therefore,  substitutes  for a cluster  include  only  cultural  and
environmental  pest control  technologies1.

      Achievable  reduction  in pesticide use for specific  end-uses   has been studied by Pimentel  et al. (1991).
Pimentel  considered  the  costs  and  benefits  of  replacing  chemical pest control methods  with  currently
available  biological,  cultural,  and environmental  pest control  technologies.  Since both the pesticide  clusters,
as defined  by EPA, include biological pest  control  methods,  the biological  alternatives   listed  by  Pimentel
are not alternatives  to the  clusters.   However,  Abt  Associates  knows  of no analysis  which  considers  only
cultural  and environmental  pest control alternatives.   Further,  the biological pest control methods constitute
only  a small  minority of the pesticides within  the clusters.  Pimentel  et al.'s  analysis  is,  therefore,  used to
measure  the relative substitutability   of the pesticide  clusters.

      In  this report, Pimentel's  study  is  used to develop a general  rating  of the  degree to which  pesticide
substitution  is feasible for  each cluster. The greater  the feasibility  of  substitution,  the higher the  expected
elasticity  of demand for pesticides hi  the cluster.  The ratings  are based on two criteria:  (1)  the percentage
by  which  non-chemical   alternatives   can  replace pesticides,  and (2)  the projected  net cost of replacing
pesticides with  a non-chemical   pest control  method.  Based on these criteria,  the clusters are grouped into
three categories  as shown  in Tables  2.4,  2.5, and 2.6.  Clusters  in the  "high substitutability"   category can,
according to Pimentel  et al.,  achieve  at least a 40  percent reduction  in pesticide  use at an  additional cost
of less than one dollar  per hectare.  Clusters  in the "moderate  substitutability   category can achieve at least
a 20 percent  reduction  in pesticide use at a cost no greater  than five  dollars per hectare.  Clusters which  do
not qualify   for  either of these categories  are listed  under  the heading   "low substitutability".

      The clusters  defined  by OPP often  group several of the crops that are listed in Table 2.4,  2.5,  and 2.6.
To determine  ratings  for the clusters,  the crop-specific   ratings were weighted   by the  pounds of fungicide,
herbicide,  or insecticide   applied to each crop,  as  was relevant   for  the cluster.  The  cluster  ratings,  as
developed  by Abt Associates  based  on Pimentel  et  al. are  as follows:
       1  Most  of the pesticide  clusters  include  at least two  active  ingredients,   indicating  that chemical
   substitutes  exist for most active  ingredients.  The substitutability   between active ingredients  will  vary
   by  region and with meteorological  conditions,   as well as with  specific  crops.   A comparison  of the
   chemical substitutes  available for particular  active  ingredients  is  not undertaken  in this  analysis.
                                                     C.34

-------
                         Non-chemical
          Table 2.4
  Substitutability  for Pesticides  by Cluster
          Fungicides
         High
         Substitutability
Moderate
Substitutability
Low
Substitutabilitv
         soybeans
         other vegetables
         peaches
rice                        cotton
sugar beets                sweet corn
lettuce                     tobacco
carrots                     peanuts
potatoes                   tomatoes
onions
beans
cantaloupe
peppers
sweet potatoes
watermelons
apples
cherries
peas
pears
plums
grapes
oranges
grapefruit
lemons
"other"  fruit
pecans
"other"  nuts
cole
cucumbers
Source:  Abt Associates  estimates  based on Pimentel  et al. (1991)
                                                    C.35

-------
                                                  Table 2.5

                         Non-chemical   Substitutability   for Pesticides  by Cluster

                                                 Herbicides
         High
         Substitutabilitv

         tobacco
         potatoes
         tomatoes
         cucumbers
         apples
         plums
         oranges
         grapefruits
         lemons
         "other"  nuts
Moderate
Substitutabilitv

peanuts
sorghum
pasture
grapes
alfalfa
hay
beans
cherries
peaches
pears
"other"  fruit
pecans
Low
Substitutabilitv

corn
cotton
wheat
soybeans
rice
sugar beets
"other"  grain
lettuce
cole
carrots
sweet corn
onions
cantaloupe
peas
peppers
sweet potatoes
watermelons
"other"  vegetables
Source:  Abt Associates  estimates  based on Pimentel et al. (1991)
                                                   C.36

-------
                                                 Table 2.6

                         Non-chemical   Substitutability   for Pesticides  by Cluster

                                                 Insecticides
         High
         Substitutability

         sorghum
         hay
         tomatoes
         cherries
         peaches
         pears
         plums
         grapes
         "other"  fruit
         pecans
         "other"  nuts
         oranges
         grapefruit
         lemons
Moderate
Substitutabilitv

cotton
wheat
carrots
onions
cucumbers
beans
sugar beets
peas
watermelons
"other"  vegetables
sweet potatoes
peppers
alfalfa
soybeans
rice
tobacco
peanuts
"other"  grains
Low
Substitutabilitv

corn
lettuce
cole
potatoes
sweet corn
cantaloupe
Source:  Abt Associates  estimates  based on Pimentel et al. (1991)
                                                   C.37

-------
Low  Substitutabilitv
fungicides  for use on vegetables
herbicides  for use on corn
herbicides  for use on soybeans,  cotton,  peanuts,  alfalfa
herbicides  for use on sugar  beets, beans,  and peas
insecticides  for use on  corn and  alfalfa
insecticides  for use on  vegetables

Moderate Substitutability
fungicide  for use on fruit and nut trees,  except  oranges  and grapes
fungicides  for use on oranges
fungicides  for use on grapes
herbicides  for use on vegetables
herbicides  for use on sorghum,  rice, small grains
herbicides  for use on grapes
insecticides  for use on  cotton
insecticides  for use on  soybeans,  peanuts,  wheat, and tobacco

High Substitutabilitv
herbicides  for use on tree fruits  (except  oranges), nuts,  and sugarcane
herbicides  for use on oranges
herbicides  for use on tobacco
insecticides  for use on  grapes
insecticides  for use on  oranges
insecticides  for use on  fruit and  nut trees excluding   oranges and grapes
insecticides  on sorghum

      As discussed  earlier,  these data can be  used  to  suggest  pesticide  clusters  for  which  the demand
elasticity  differs  substantially  from the demand  elasticity  for the associated food commodities.  Demand for
the six  pesticide  clusters with  low substitutability   may be inelastic relative to the demand  for the associated
foods.  In the seven cases of high substitutability,   the demand for the pesticide  cluster may be more elastic
than the demand  for the associated foods.  The feasibility   of substitution  for pesticide  clusters is considered
in Section 2.7 in constructing  estimates  of the elasticity  of  demand for the pesticide  clusters.
                                                     C.38

-------
      2.5.    Contribution  to the Variable  Cost of Production
      Economic  theory  predicts  that  a producer's  sensitivity  to price will increase with  the  percentage  of
production  cost contributed  by that input.   To further  distinguish   between  the elasticities of demand  for
the different  clusters  of pesticides,  Abt Associates  has considered  the extent  to which the pesticides  in the
clusters  contribute  to production  costs.

      The U.S.DA.  publishes  cost-of-production    data  summarizing  all operator  and  landlord  costs "and
returns  associated  with  the production  of  several  individual   commodities   (U.S.DA.,   1989a).   The cost
estimates separate the cost of chemicals and  can be used to determine chemical costs as a percentage  of total
variable   costs of  production.    Cost of  chemicals   is included   in two  categories:   "chemicals"   and  "custom
application".   Both  custom  operators  and farmers  apply  pesticides.   The  category  "chemicals"   includes
agricultural  chemical  use  by farmers and does not include labor spent in chemical  application.  Many custom
operators  charge  a flat  rate and do not provide  a cost breakdown   between  labor and  materials.   "Custom
application"  therefore includes  operator-applied   chemicals,  operator labor, and farm operations  other than
chemical  application.    The category  "custom  application"   was  included  in  calculations   of pesticide
contribution  to total cost in order to ensure  that all chemical  costs  are included.   The estimate of pesticide
contribution  to the cost of crop production  will,  however, be overstated.  These data are presented  in Table
2.7 for the commodities   for which  the information  was available.

       The  pesticide   clusters defined  in  this  analysis  separate  agricultural   chemicals  into  fungicides,
insecticides,  and herbicides.    The U.S.DA.  report  does not  separate  the  costs  of chemicals  into these
categories.    In order to divide  the  cost of  chemicals  between  each  of these  types  of pesticides,  Abt
Associates   estimated total expenditures   for  each  pesticide   type   for  the  commodities  considered  in the
U.S.DA.  report.   Total expenditures  were  calculated  by multiplying  the pounds  of fungicide,   herbicide,
or insecticide   applied  to a commodity  (from  Pimentel  et al, 1991) by  the  average price of the relevant
pesticide  type   i.e., fungicides,  herbicides,  and insecticides  (as reported  in  Synthetic  Organic  Chemicals.
1988).  The chemical contribution  to variable  cost was then divided between the  three pesticide  categories
based  on  the  percent  of  expenditures.   The  percentages  of  variable  production  costs for  fungicides,
herbicides,  and insecticides  by commodity  are listed  in Table  2.7.

       The crop-specific    estimates  must be grouped into clusters for purposes of this analysis.  An estimate
 of the contribution  of  pesticide  to variable  cost  for  a cluster  is made  only  if such an estimate  is  available
 for individual   crops contributing  at least 50 percent  of  the pesticide use for the  cluster  (based on Pimentel
 et al., 1991).  Eight  clusters meet this qualification.   These clusters  are listed below in descending  order of
                                                     C.39

-------
                                            Table 2.7


                 Fungicide. Herbicide, and Insecticide Contribution to Variable Costs of

                                            Production
Commodity

soybeans3
peanuts
cotton3
sugarbeets
sorghum3
corn3
rice3
wheat3
potatoes4
barley3
tobacco
oats3
Chemical
Costs as a
Percent of
Variable
  Costs1

    37
    31
    29
    28
    25
    22
    20
    18
    16
    16
    10
     9
Fungicide
Costs as a
Percent of
Variable
Costs2

 0
12
 0
 0
 0
 0
 0
 0
 7
 0
 0
 0
Herbicide
Costs as a
Percent of
Variable
Costs2

35
17
16
23
22
19
19
16
 3
16
 3
 9
Insecticide
Costs as a
Percent of
Variable
Costs2

 3
 3
13
 5
 3
 2
 1
 2
 6
 0
 7
 0
      1Equals ("chemicals" + "custom operations")/"total variable cash expenses"
   *

      2Estimate by Abt Associates using pesticide prices from Synthetic Organic Chemicals, 1988 and
  pounds applied from Pimentel, D. et al, (in press), "Environmental and  Economic  Impacts  of
  Reducing U.S.  Agricultural Pesticides Use", Pest Management in Agriculture, CRC Press.

      3Source for percent of production costs - USD A, 1989. "Economics Indicators of the Farm Sector,
  Costs of Production, 1987".  Economic Research Service.  February.

      4Source for percent of production cost- USDA, 1988. "1985 Potato Cost  and Returns:  Fall
  Production Areas".  Potato facts special edition. Economic Research Service. September.

      5Source for percent of production cost - USDA, 1989. "Tobacco: Situation and Outlook Report".
  Economic Research Service. September.
                                                 n.40

-------
the  percent  of the pesticide   contribution   to cost.   Based  only on contribution   to cost,  the  order also
corresponds  to expected  decreasing  price elasticity  of demand.  The clusters  are:

1)    Herbicide  used on soybeans,  cotton,  peanuts,  alfalfa  (33 percent  of variable  cost)
2)    Herbicides  used on sorghum,  rice,  small grains  (20%)
3)    Herbicides  used on corn  (19%)
4)    Insecticides  used on cotton (13%)
5)    Insecticides  used on soybeans,  peanuts,  wheat,  and tobacco  (3%)
6)    Herbicides  used on tobacco  (3%)
7)    Insecticides  used on sorghum  (3%)
8)    Insecticides  used on corn and alfalfa   (2%)
      U.S.D.A. did not  estimate  the cost of production  for specialty  crops.  These data are compiled  at the
county  level  and collected  by  individual  states, but are not available  on a national level.   It is beyond  the
scope of this study  to collect cost of production  data from each county in each state  for  each crop.  Abt
Associates did, however, obtain cost of production reports for  specialty crops of interest from the states that
represented  a large percentage  of the planted  acreage  of each crop.  From  these reports it was evident  that
the pesticide   contribution  to cost  varied  significantly   between  regions.   Therefore,   it was  decided  that
without  a statistically   valid national  sampling,  the  county-level   data could  not accurately  be used  to
represent  national  cost  data.  No estimates  of the  pesticide  contribution   to  variable  costs of producing
specialty  crops are included  in this  analysis.

      The purpose  of considering  the pesticide  contribution   to  variable cost  is to determine  whether  the
demand  elasticity  for clusters of pesticides  is likely  to  differ substantially from the elasticity of demand  for
the associated food  commodities  (calculated  is Section  2.3).   In  particular,  for  the four  pesticide  clusters
where  chemicals  contribute  over ten  percent  of total variable   cash  expenses,  farmers may be relatively
sensitive  to pesticide  price  changes.   Therefore,  demand  for these pesticide clusters  may be more elastic than
demand  for the associated  food commodities.   This factor  is considered  in Section  2.7, along with  the other
available  data, to estimate  the elasticity  of demand  for  each of  the pesticide  clusters.

      2.6   Productivity of  Expenditures  for Pesticides
      The productivity   of an  input refers  to the  marginal  value  product  of expenditure  for  the input
compared  to  the cost of  the input. When the marginal  value product exceeds the input cost,  the input  is said
to be productive.   If an  input  is highly  productive,  demand for the input  is theoretically  likely  to be
                                                     C.41

-------
insensitive  to small  changes in price.  Three studies  which  examined  the productivity   of expenditures  for
agricultural  pesticides  were located and are discussed  below.

      Headley (1968) estimated partial production elasticities  for the following  input variables  using Cobb-
Douglas  functions:    labor,  land  and buildings,   machinery,   fertilizer,   pesticides,   and "other".   He then
compared the  marginal  value production   of expenditure   for  pesticides   to  the  marginal  factor  cost of
pesticides  to determine the extent  of disequilibrium   in  the  use of pesticides  by  farmers.   The results of
Headley's study indicated  that  the marginal  value  of a one-dollar  expenditure  for chemical  pesticides  is
approximately  $4.00.   Headley noted several limitations   of  his analysis,  including   that his conclusions  are
based on aggregative  analysis and may not apply to local situations.

      Campbell  (1976) considered  this same issue for a cross-sectional   sample  of tree-fruit   farms in British
Columbia.  The statistical  techniques  used by Campbell  include  Ordinary Least Squares and Factor Analysis
Regression.   The data used in fitting Campbell's regression equation were as follows:  the dependent  variable
was the value of output of fruit;  the  input  variables were the values  of services of land and buildings  and
capital  equipment,   and the  values of inputs  of irrigation  water,  labor, fertilizers,  and  pesticide  sprays.
Corresponding   to  Headley's  findings,   Campbell  found   that  the value of  a marginal  dollar's worth of
pesticides  was  significantly   greater  one  dollar,  indicating   a relatively  inelastic  demand.   However,  as
Headley  did, Campbell suggested  caution   in the interpretation  of this  result.  He noted that it is possible
that  his  statistical  procedure  introduced  an upward  bias to the estimate  since the sample data exhibited
fairly high correlations among  some  of the independent  variables,  including  pesticides.

      According  to Lichtenberg  and  Zilberman  (1986),  however,  the studies  of Headley  and Campbell are
methodologically  flawed.   Lichtenberg   and Zilberman argue that econometric  measurements  of pesticide
productivity  that are derived  from standard production  theory models contain significant  upward biases that
result in the overestimation   of pesticide  productivity.    The  authors claim that the constant  elasticity  of the
marginal  effectiveness  curve  produced  by  a standard Cobb-Douglas  specification  will  not  match the actual
behavior  of the marginal effectiveness   curve.   The correct  form  of the marginal  effectiveness   curve,
according to Lichtenberg  and Zilberman,  will show an increase  in pesticide  use in response to pest resistance
and  a decrease  in  use only when  pest resistance is so widespread  that  alternative   measures are most cost
effective.   The true marginal effectiveness   curve will decline at an increasing  rate in the economic region.
Lichtenberg  and Zilberman  cast  doubt  on the high marginal  productivity   of  pesticides  estimated by
Campbell and  Headley.
                                                     C.42

-------
      Given that these studies  do not provide  definitive   estimates  of the productivity  of pesticides  and do
not address the productivity   of  specific   pesticide  clusters,  we develop simple  original  estimates of  the
productivity   of pesticide  clusters.    In  this  analysis,   the productivity   of pesticides  (specified  as either
fungicides,  herbicides,   or insecticides)  on individual  food commodities  is calculated  as follows:
                                               P -•
                                         V x MP
                                            C
where:
C
MP   =
P
the cost of pesticide  treatment  for  the  food commodity  (dollars  per hectare),
the marginal  value product  from  the  pesticide application   (percent  of total production  value),
the productivity    of the  pesticide  on  the  food  commodity   (dollars  per hectare/dollars   per
hectare),  and
the production  value  of the  crop  (dollars per hectare  harvested).
      The data sources for the three input  parameters  were as follows.   The production  value  of the  crops
was  obtained from U.S.D.A.  (1989).  The cost of pesticide  treatment  was taken from  Pimentel  et al. (1991).
No source of specific  estimates of the marginal value  product associated with fungicides,   herbicides,  and
insecticides  on crops was located.  The  analysis  therefore  relied on the expertise of the U.S. EPA Office  of
Pesticide  Programs  (OPP) to estimate  the value of this parameter.  The  OPP  stated  that it was reasonable
to generalize  that the marginal product  associated  with the use of fungicides,   herbicides,  or insecticides  on
a crop equaled ten percent  of the production  value of that crop (telephone communication,   Dave Broussard,
OPP, 2/91).  Since no more  precise  estimates  were  available,  the analysis adopted this  value.

      In reality,   there will be some variation  in the marginal  value product  of fungicides,   herbicides,  and
insecticides  on different  crops.  To the extent that the marginal value  product  for a pesticide  type on a crop
is greater  than 10 percent,  the analysis  will  understate  productivity   and therefore  overstate  the elasticity
of demand.  Similarly,  if the marginal value  product  for  a pesticide  type on a crop  is less  than 10 percent,
the productivity   of the pesticide  will be overstated  and  the elasticity  of demand will be underestimated.

      Weighted   averages  of the  productivity   measures  for  pesticides  used  on  individual   crops  were
calculated  to obtain measures of productivity  for pesticide clusters.  The weighting   factor   was the quantity
of pesticides  included  in the cluster applied  to each crop, as determined by Pimentel  et al. (1991).
Table  2.8 displays  the  productivity   measures   for  the pesticide  clusters  for   which  the  information  was
available.

                                                     C.43

-------
                                       Table 2.8

                            Productivity of Pesticide Clusters
 Cluster
           Productivity
    (Dollars of Marginal Product
per Dollars of Pesticide Expenditures')
Fungicides on:

 Fruit and nut trees, except oranges and grapes
 Grapes
 Vegetables
 Oranges

Herbicides on:

 Sorghum, rice, small grains
 Corn
 Soybeans, cotton, peanuts,  alfalfa
 Sugar beats, beans, peas
 Vegetables
 Oranges
 Tree fruits (except oranges), sugar cane, nuts
 Grapes

Insecticides on:

 Cotton
 Sorghum
 Corn, alfalfa
 Vegetables
 Fruit and nut trees, except  oranges and grapes
 Soybeans, peanuts, wheat, tobacco
 Oranges
 Grapes
                $5.81
                $9.83
                $12.37
                $12.54
               $0.88
               $1.11
               $2.68
               $2.72
               $17.85
               $17.91
               $19.29
               $61.43
               $0.72
               $1.24
               $3.69
               $7.92
               $8.51
               $13.08
               $15.04
               $37.80
                                        C.44

-------
      Note that there is great  variation  in  the  productivity  estimates.  The lowest productivity   estimate is
$0.72,  for insecticides  used  on cotton; Herbicides  used  on grapes had the highest productivity,   at $61.43.
The wide  range is due both  to variability   in the  value  of production  of crops and variability  in the cost of
applying  pesticides  to the crop.   For example,  the value  of production  of cotton  is $487  per hectare while
the value  of a hectare of grapes  is $4,914  per hectare  (U.S.DA., 1989).   In addition,  the average  cost of
insecticide  application   to cotton  is about $118  per hectare while  the costs  of applying  herbicides  to grapes
is $8 per hectare  (Pimentel et al., 1991).  However,  it must again  be  recognized that due to lack of data,  the
analysis  assumes that the marginal  value of  production   of insecticides   on cotton  and herbicides  on grapes
are identical.

      The productivity   of the clusters  is considered  in the next  section, along with  the factors  previously
discussed,  in developing   estimates  of the elasticity  of demand  for  each pesticide  cluster.  Demand for  the
pesticide  clusters  for which  productivity  is low can be expected  to be elastic relative to the demand for  the
associated food commodities,   ceteris paribus.  Similarly,   when  a cluster of pesticides  is highly  productive,
demand  is likely  to be inelastic  compared  with demand   for the  associated  food  commodities.

2.1.   Conclusions   -  Agricultural  Pesticides
      Section  2 of this  report  estimates the  price elasticity of demand  for twenty-four   pesticide  clusters.
Estimates  of the elasticity  of demand for clusters of pesticides  are based  on the  price elasticity  of demand
for the associated  food commodities.  However,  the elasticity of demand for an input  is not solely  a function
of the demand for the end product (unless input ratios are assumed  to be  fixed).   Therefore,  the elasticity
estimates are adjusted as warranted  by  consideration  of three factors:  (1) the feasibility  of substituting  non-
chemical  controls  for the pesticide  cluster,  (2) the contribution   of the pesticide cluster  to the variable  cost
of crop  production,   and (3) the productivity   of the  pesticide cluster.  In addition,  the literature  estimates
of elasticity  are considered   when appropriate.

      Since  the effect  of these  factors is not easily quantified,   we  use this information  to adjust the pesticide
elasticities  estimated  from  the demand for crops  rather  than to attempt  to pinpoint  the value  of demand
elasticity.   Based  on this information,   we  identify  clusters for which  the  elasticity  of the demand  for  the
food commodity  is likely to  differ substantially  from the elasticity of demand for the corresponding  cluster
of pesticides.
      Note that the effect  of the factors considered  may cancel  each other.  For example,  the feasibility   of
non-chemical   substitution   for a cluster  of pesticides  may  be high,  indicating  that the elasticity  of demand
may be higher  for the cluster  of pesticides  than for the associated  crops.  However,  if the productivity   of

                                                      C.45

-------
 the pesticide  duster  is also high,  less elastic  demand  is indicated  for the cluster  of pesticides  than  for  the
 associated  foods.  To decide whether an adjustment  to the  elasticity  of demand  for the food  commodities
 is warranted,  the net indication  of the factors  is considered.   Factors that indicate relatively  elastic demand
 and  factors  that  indicate  relatively  inelastic  demand  cancel  each  other.  If,  on net,  two  factors indicate
 relatively   elastic  or inelastic demand,  an adjustment   to the elasticity  estimate is made.

       Table  2.9 summarizes the information   from the  five  areas of research:   literature  estimates, demand
 elasticities  of food commodities,   feasibility   of substitution,   contribution of chemicals  to production  costs,
 and productivity   estimates.  The information   is summarized   for twenty-one   sectors of agricultural  pesticide
 use.  Three additional  clusters  of  pesticides  are included  in  the following summary  of elasticity of demand
 for  agricultural  pesticides:   fungicides   used on grain  storage,  fungicides   used for  seed treatment,  and
 fungicides  - post-harvest.    Since  these  clusters differ  from  the other agricultural  pesticide clusters  in that
 the pesticides are not applied to crops in the field,  they have not been included in the analysis  to this  point.
 However,   since the pesticides  in these clusters  are used agriculturally,    elasticity  estimates  are discussed in
 this section.  The  best estimate  of elasticity  for each  of the twenty-four  agricultural  clusters is discussed
 below.

 a.     Fungicides  used on vegetables
       The  elasticity  estimate  of -0.38   is taken  directly  from  U.S.DA.'s  (1985) estimate  of the demand
 elasticity for retail  vegetables,  weighted  by  the amount of fungicides  applied to each type of vegetable.  No
 adjustments  are  made since  the  substitutability   for  fungicides   on  vegetables   is low  and  the  marginal
 productivity  of fungicides  on vegetables  is moderate.

 b.     Fungicides  used on fruit  and nuts except oranges
       The  elasticity of demand for  food commodities   in this  cluster,  based  on a weighted-average   of the
 elasticity values  estimated  by  U.S.D.A.  (1985),  is -0.23.   No adjustments are  made  to this value  are made
 to arrive at the elasticity  of demand  for  fungicides  applied to these food commodities.   No corrections  were
necessary  since the substitutability   for  fungicides  on fruit  and  nuts  except  citrus  is moderate  as  is  the
marginal productivity   of fungicides  on fruit  and nut trees, except  oranges. The estimated elasticity  of-0.23
indicates less elastic demand than  does  the analysis  of Pingali  and Carlson  (1985).  However,  the  elasticity
estimate  of Pingali  and  Carlson  consider  only apples  and  is therefore  not  directly   comparable   to  the
elasticity estimate  for  the cluster.  Both the current estimate  arid the Pingali  and Carlson  estimate  indicate
that  demand  is inelastic.

-------
Cluster
                                        Table 2.9
                           Summary of Elasticity Information
               Elasticity of    Feasibility   Fraction of
Literature        Food          of       Contribution to
Estimates      Commodity   Substitution   Production Costs
                                                                                        Marginal
Fungicides on:
vegetables M.A,
%

fruit & nut trees,
except oranges -0,92 (2)
oranges KLA.
grapes NvA, ,
Herbicides on: "
sorghum, rice,
small grains M+A<
^ f
soybeans, cotton,
peanuts, alfalfa inelastic (5)
corn 6.O3, -0.75 (3)
^JUfi (4)
iaefestb {5>
?
oranges N.A.
tree fruits, nuts & ,' ^ ,' „ ,
sugar cane 3$AA*
fff ff f
grapes H.A,.
f > sf SS-.
vegetables N*A«
tobacco N?A»
•^ ', ,
sugar beets, beans "' "• ''
peas N.A.
-;A^^
-0.38 low N.A. ,_$1&3:7
j*' \ "^ -'^
S.^A%VA ^ '*'•'•
f -. " f f , f f ff "•
-0.23 moderats N.A. ' $$M
-1.00 moderate N.A. - ,"lj&L$&
-1.38 moderate N.A. „ "$^«^
"^'(•: " -',
>* "' -;*
-0.44 moderate 0.20 - $0X$8
^- :'V*
-0.67 low 0.33 ^ $21^8
-0.69 low 0.19 . 'v'^^3Lli
'- "<& '"•''
' V. "* *
-1.00 high N.A. "",' $i,7Ji
?" ",*f ^
-0.20 , ,higii N.A. " $J9.2i
" , ' ' ' ,.-''':
-1.38 jnoderate N.A. %^$$|.,43i
^\
-0.27 moderate N.A. ' ,% $17x^5'
N.A. "' Jwgh 0.03 SS&JiQtJ
•• , ' ' '' . C' ?' vj
s -T ' *-»*, -"'I
-0.12 low ,, N.A. 'f$2,7^":
(1) Burrows (1983), cotton only
(2) Pingali and Carlson (1985), apples only
(3) Miranowski (1980), corn only
(4) Huh (1978), corn insecticides and herbicides
(5) U.S. EPA (1974), corn or soybeans, only
                                              C.47

-------
Cluster
                                    Table 2.9 (cont.)
                           Summary of Elasticity Information
               Elasticity of   Feasibility    Fraction of
Literature        Food          of       Contribution to
Estimates      Commodity   Substitution   Production Costs
Marginal
Productivity
^ $• Jit 4 vs %
Insecticides on: "" *
vegetables N-A,
fruit & nut trees ^»3§ (2)
exc. oranges ^1^ * s ~ *"
oranges y&jV ^
** " ^
grapes fi^5
com, alfalfa ,,-0.7$ (5)
§ "
-
soybeans, peanuts, ^#~ „
wheat, & tobacco Jtjela$^?5 <-J$)
cotton ^.^ ~i*2§ (I)
^t-y'"J ,'" -
-0.33 Jowf
-0.21 "" 'shfgh
j •* ""
-1.00 ^; .ra'^j
^ %^* ^^ u
-1.38 % "nbigh
-0.69 " ] \
-------
c.     Fungicides  on  oranges
      The elasticity  estimate  of  -1.0  is taken  directly  from U.S.DA.'s  (1985) estimate  of the demand  for
oranges.  No adjustments  are made since the substitutability   for fungicides   on citrus is moderate,  as is the
marginal  productivity   of fungicides  on oranges.

d.     Fungicides  on  grapes
      The elasticity estimate of -1.38  is again taken directly  from  U.S.DA.'s  (1985) estimate of the demand
for retail  foods.   Since  the feasibility   of substitution  for  fungicides  in this cluster  is  moderate  and  the
marginal  productivity   is moderate, no adjustments  are made.

e.     Herbicides  on  sorghum,  rice, and small grains
      The best estimate  of the elasticity  of this  food  cluster  is based  on the  demand  elasticity   of rice, as
reported  by U.S.DA. (1985)  and on the demand elasticity   of sorghum.  As discussed  above,  the elasticity
of demand for sorghum,  generally  an animal  feed crop, was  calculated  based on the elasticity  of demand
for animal meats.  To  estimate  an elasticity  for the  crops in  this cluster,  the  two  crop elasticities  were
weighted   by the amount of herbicides  applied  to each  crop (as reported  in Pimentel  et al., 1991).  The
resulting  elasticity  estimate  is -0.44.

      However,   it is likely  that the  elasticity  of  demand  for  this  cluster  of herbicides  will  exceed  the
elasticity  of demand  for the associated  crops.  Although  the feasibility  of substitution  for herbicides  in  this
cluster  is moderate,  herbicides  contributed  a relatively   high  percentage   to total variable  costs,  and  the
marginal  productivity   of the herbicides  is very low.  There  is no precise  method  by which to translate these
factors  into  an estimate  of the  elasticity  of  demand  for  herbicides   on sorghum,  rice,  and small  grains.
However,  to account for  the  low marginal  productivity   and  high contribution   to costs of herbicides   on
sorghum,  rice, and small grains, demand  on  herbicides  on this cluster  is assumed to be more  elastic  than
demand  for crops  in this cluster.  The elasticity  estimate is adjusted  from -0.44  to -1.0.

f.     Herbicides   on soybeans, cotton,  peanuts,  and alfalfa
      As discussed earlier  in this  report,  assuming  that  soybeans  and alfalfa  are fed to animals,  the price
elasticity   of demand  for  the crops   in this  cluster,  excluding   cotton,  is  -0.67.    Since the  quantity  of
herbicides  applied  to cotton  is small  in  comparison   to the  quantity   of herbicides   applied  to soybeans,
peanuts,   and  alfalfa,  the  exclusion   of  cotton  should  not  substantially   affect  the  elasticity  estimate2.
       2According to Pimentel et al. (1991), 8.2 million kgs. per year of herbicides are applied to cotton and 60.6
   million kgs. per year of herbicides are applied to soybeans, peanuts, and alfalfa combined.

                                                     C.49

-------
 Supporting  the elasticity  estimate of -0.67,  U.S. EPA (1974)  found the demand for herbicides  on soybeans
 to be inelastic.

       Three additional factors present information  on the expected  price  elasticity of demand  for this cluster
 of herbicides:   the feasibility  of substitution,   the fraction   of  contribution   to production   costs,  and the
 marginal productivity   of the herbicides.  The feasibility   of substitution  for this cluster  of herbicides is low,
 influencing   the  demand  for  the herbicides  to be  inelastic.    However,  herbicides   (including   custom
 application) are estimated to contribute  33 percent of the total cost of production  for this cluster.  This  high
 contribution  to variable  cost is likely to drive  greater elasticity of demand.  Also, the marginal productivity
 of herbicides  in this  cluster  is estimated  as $2.68.  This return  on herbicide  use is fairly  low, suggesting
 somewhat  elastic  demand.

       Given  the opposing factors that influence   demand for herbicides   in this cluster,  it was judged  that
 the estimated  elasticity  of  demand for  the crops,  -0.67,   serves  well  as an estimate  of the  elasticity  of
 demand  for the duster of herbicides.

 g.     Herbicides  on corn
       The estimate  of elasticity of demand  for corn herbicides is -0.69.  This  value  is based on the average
 elasticity  of meats as listed in  U.S.DA.  (1985),  since  the  corn  is  assumed  to be used  as animal  feed.
 Pesticides  in  this cluster contributed  a  relatively  high  percentage to total variable  costs (19% including
 custom  application)  and the marginal  productivity  of these pesticides  is low,  at $1.11.  Both  of this factors
 indicate  elastic demand.   However,  the feasibility  of substitution  for  these  pesticides  is low, indicating
 inelastic  demand.   Therefore,  it was  judged  that no additional  adjustment   to the  elasticity   estimate  was
 warranted.

 h.     Herbicides  on oranges
       The estimate  of the elasticity  of demand  for herbicides on  oranges is  -1.00,   taken from  U.S.DA.'s
 estimate  of the elasticity   of  demand for oranges.  Although  the feasibility  of  substitution  for herbicides on
 oranges is high (indicating  elastic demand),  the  marginal productivity  of the herbicides  is also fairly   high
 (indicating  inelastic demand).  Therefore,  no adjustment  to the U.S.D.A.  estimate  of elasticity  of  demand
 for oranges  is made.
i.
      Herbicides on tree  fruits  (except oranges),  nuts, and sugarcane
      The  elasticity  of demand  for this  cluster,  based  on the  elasticity  of  demand  for  retail food,  is
estimated  as -0.20.   Pesticides  in  this cluster  have a high  feasibility  of substitution   with  non-chemical   pest
                                                    C.50

-------
control methods, indicating  clastic  demand.   However,  the marginal  productivity  of these pesticides is also
moderately  high,  at $19.19,  indicating   inelastic  demand.   Therefore,  no adjustments   are  made to the
elasticity  estimate for  retail food.

j.     Herbicides on grapes
      The price  elasticity  of demand for herbicides  on grapes is estimated  based on the elasticity  of demand
for grapes at the retail level.  The estimated  elasticity  is -1.38.   Since  the marginal  productivity   on grapes
is  extremely  high, the  elasticity  of  demand may be less  than  -1.38.   However,  the marginal productivity   is
the only  factor  indicating   inelastic demand;   the feasibility   of  substitution  for herbicides   on  grapes  is
moderate.  Further,   the degree  of adjustment  to the elasticity estimate  warranted  by the high  marginal
productivity  is unclear.  For these two  reasons, this analysis relies on the elasticity  estimate  for  retail grapes.
However,  it should be noted that this  value  may  overstate  elasticity,  and  therefore  overstate  the impact of
the effluent  guidelines   on pesticide  manufacturers.

k.     Herbicides on vegetables
      The weighted-average    estimate  of demand  for  vegetables  at the retail  level  is -0.27.   Since the
feasibility  of substitution  is moderate  and the marginal  productivity   is moderately  high for this cluster, the
elasticity  estimate for food  is used to represent  the elasticity  of demand for  herbicides  used on these foods.

1.     Herbicides used  on tobacco
      U.S.DA.  did  not estimate  the elasticity  of demand for tobacco at  the  retail  level.  However,  the
addictive  nature of cigarette smoking probably  results in inelastic  demand for tobacco.  It seems  reasonable
to assume demand for  tobacco  is as inelastic  as the least  elastic  demand for retail food, since people seldom
develop  addictions to specific  foods. Since U.S.DA. found that the elasticity of demand for numerous  food
commodities  was lower in absolute  value than -0.20,  the elasticity  of demand for tobacco  is estimated  as -
0.20.

      Since the  feasibility   of substituting  a non-chemical   alternative   for  herbicides  on  tobacco  is high,
demand   for the herbicides   used  on  tobacco may  be  more elastic  than demand  for the tobacco itself.
However,  the  costs of applying herbicides  comprise  only 3 percent  of the total variable costs of production.
Further,   the estimate of the marginal productivity  of herbicides  used on tobacco  is extremely  high. These
two factors indicate  that  demand  for  herbicides  used on tobacco will  be inelastic.   Given these  opposing
factors,  this analysis  assumes that the elasticity  of demand for herbicides   used on tobacco will  match the
elasticity  of demand  for tobacco.  The elasticity  estimate for this cluster  is therefore  -0.20.
                                                     C.51

-------
 m.   Herbicides  on sugar beets, beans,  and peas
       The estimate  of the elasticity  of demand  for this  cluster  is calculated   from  a weighted  average  of
 U.S.DA.'s  (1985) estimate  of demand  for  food at the retail  level.  The  value  is -0.12.   No  adjustments  are
 made since the  indications  regarding elasticity  of  demand for the herbicides  conflict.   The substitutability
 for herbicides  on sugar  beets,  beans,  and peas is low,  indicating   relatively   inelastic  demand,  while  the
 marginal  productivity   of the herbicides  is low, indicating  relatively  elastic demand.

 n.    Insecticides  on vegetables
       The elasticity  for  this cluster is  estimated   as  -0.33,   based  on  a weighted-average    of the values
 estimated  by U.S.DA.  (1985) as the elasticities  of  demand for vegetables.   No adjustments  are made to the
 elasticity  estimate  for vegetables.   The marginal  productivity   of insecticides  in this cluster is moderate,  at
 $7.92.  Although the substitutability   for  insecticides  on vegetables  is low,  there is no quantitative  measure
 of the extent  to which the estimate  should be altered. Further,  this is the only factor indicating  that demand
 is relatively  inelastic.   Therefore,  the elasticity  estimate of -0.33  is used  in this analysis.

 o.     Insecticides  on fruits  and  nuts except  oranges
       The estimate of elasticity  of demand for the food  commodities  in  this cluster,  based on U.S.DA.'s
 (1985) estimates  of elasticity  of demand for food  at the  retail level,  is -0.21.   This  value  differs  notably
 from the elasticity estimate  of Pingali and Carlson  (1985) for insecticides   applied  to apple orchards.  Pingali
 and Carlson  estimated the elasticity  of demand as -1.39.  Since the authors  considered  only  apple orchards,
 the estimates  are not perfectly  comparable.    However,  since apples  receive  over 50 percent of insecticides
 applied  to crops  in this  cluster,   the differences   between  the two estimates  is notable.

       The  marginal productivity  of these insecticides  is moderate and does not suggest that an adjustment
 to the elasticity   estimate  for  retail  food is required.  However,  the feasibility  of non-chemical   substitution
 for these insecticides  is high, indicating  elastic  demand. To account  for  the high feasibility  of substitution
 and the elasticity  estimate of Pingali  and Carlson,  the elasticity  estimate  for this cluster  is adjusted  from -
 0.21 to -1.00.

 p.    Insecticides  on oranges
      The U.SDA. estimate  of the elasticity  of demand for oranges at the  retail level was -1.00.   This value
 is also used   to  represent the  elasticity   of demand  for  insecticides  applied  to oranges.   Although  the
 feasibility   of substitution  of insecticides   used on oranges is high (indicating  relatively  elastic  demand),  the
 marginal   productivity   of the insecticides   is  also fairly   high  (indicating  relatively   inelastic   demand).
Therefore,  no adjustments  are made.
                                                      C.52

-------
 q.     Insecticides  on grapes
       The U.S.DA.  estimate  of the elasticity  of demand for grapes  at the retail level  was -1.38.   This value
 is also used  to represent  the elasticity of demand for insecticides  applied  to grapes.  Although  the feasibility
 of substitution   of insecticides  used on grapes  is high (indicating  relatively  elastic demand),  the marginal
 productivity   of the insecticides  is  also high, at $37.80 (indicating  relatively   inelastic  demand).  Therefore,
 no adjustments  are made  to  the  U.S.D.A.  elasticity  estimate for grapes.
r.
      Insecticides  on corn and alfalfa
      Since  a large  proportion  of production   of each  of these  crops serves  mainly  as animal  feed,  an
elasticity  estimate  for the crops was developed  based  on the retail demand for meat.  As discussed  above,
the elasticity  for corn and alfalfa  is estimated to be -0.69.   This elasticity  estimate is also used to represent
the elasticity  of demand  for insecticides  applied  to these  crops.
      Three literature  values describe  the elasticity  of demand  for crops in this  cluster.   U.S. EPA (1974)
found the demand  for corn insecticides  to be inelastic.  Miranowski's  (1980)  statistically  significant   estimate
of the elasticity  of demand for corn insecticides  was -0.78.  Finally,  Huh (1978)  estimated  the elasticity  of
demand for corn insecticides  and herbicides  as -1.46.  Since these  literature  estimates conflict,  they do not
indicate that an adjustment  to the elasticity  estimate  is needed.

      The feasibility  of substitution  on these crops is low, indicating  that demand  is relatively  inelastic.  The
low  contribution  of insecticides  to the  costs of production  of these crops also indicates  that demand for the
insecticides  will  be relatively  inelastic.   However,   the  marginal productivity   of insecticides  on corn and
alfalfa  is  fairly  low, at $3.69.  Low productivity   is associated  with elastic  demand.   Given  the  Opposing
factors,  no adjustment   is made to the  estimate  of the elasticity  of demand  for corn  and alfalfa.

s.     Insecticides  on sorghum
      As was the case for corn and alfalfa,  the elasticity  of demand for sorghum  is calculated  based on the
elasticity   of demand  for  meat, since sorghum  is used mainly  as a feed crop.  The  elasticity  estimate  for
sorghum   is -0.69.   Although  the marginal   productivity   of  insecticides  on sorghum  is  low  (indicating
relatively  elastic  demand)  and  the  feasibility  of  substitution  is high  (also indicating  elastic  demand),
insecticides  contribute  only  two  percent  of production  costs (indicating  inelastic  demand).  Given  these
opposing  factors,  no adjustment  to the sorghum  elasticity   estimate is  made.  The elasticity  of insecticides
used on sorghum  is estimated as -0.69.
                                                     C.53

-------
 t.     Insecticides  on soybeans,  peanuts, wheat,  and tobacco
       The estimate of  the  elasticity  of demand  for soybeans,  peanuts,  and wheat  is -0.56.   Although   an
 estimate of the elasticity of demand for  tobacco  is not available,  this omission  should not substantially  affect
 the estimate since 80 percent of insecticides  used in this cluster are applied to soybeans,  peanuts, or wheat.
 The feasibility  of substitution,  fraction  of contribution   to production  costs,  and marginal  productivity   for
 this  cluster of pesticides  do not suggest that an adjustment  to the elasticity   of  demand for the food crops
 is required.  The elasticity  estimate for  this pesticide  cluster  is therefore  -0.56.  This estimate  is consistent
 with the finding  by U.S. EPA (1974) that demand  for  soybeans is inelastic.

 u.     Insecticides  on cotton
       No estimate of the elasticity  of demand for cotton was  given  by U.S.DA.   However,  Burrows (1983)
 empirically  estimated  this  elasticity.   Using a single equation  model, Burrows  estimated  the  elasticity   of
 demand for cotton to be -0.9;  with  a simultaneous  equation model, Burrows estimated the elasticity as -1.23.
 The average of these two estimates is -1.06.

       Since the marginal  productivity  of insecticides  on cotton is extremely   low,  at $0.72,  the demand  for
 the insecticides   is expected  to be  elastic.   Further,  the insecticides   contribute   a fairly  high  fraction,   13
 percent,  of the variable  cash costs of producing  cotton.  The feasibility  of substitution for these insecticides
 is moderate.   Since these factors  are consistent with the elasticity  estimate from  Burrows,  the  elasticity   of
 demand for cotton  insecticides  is estimated to be -1.06.

 V.     Fungicides   on grain storage
       In the absence of more specific information,  the elasticity  of demand for fungicides   on grain storage
 is assumed to  equal the elasticity  of demand  for grains.  Elasticity estimates are available  from Huang (1985)
 for  wheat  and rice.  Other stored grams may be fed to animals.  As discussed  above,  an  estimate for  the
 elasticity  of grains fed  to annuals was developed  as part of this analysis.   However,  since  information  was
 not located on the quantity  of fungicides   applied to each grain and each end-use,  correct weighting  factors
 for  the different   elasticity  estimates  could  not be developed  to estimate  an average  elasticity for all grains
 treated with fungicides  hi storage.  The  elasticity  for this cluster is therefore  estimated as a straight  average
 of the elasticity  of wheat flour (-0.11), rice (-0.15),  and animal  feed grains (-0.69).  The resulting elasticity
 estimate  for fungicides  used on gram in storage is  -0.31.
W.    Fungicides  used for seed treatment
      Since no specific information   on the elasticity of fungicides   used for seed treatment was  located, the
elasticity  of demand  for  fungicides  hi this cluster  is calculated  based on the demand  elasticity for the crops

                                                    C.54

-------
constituting  the majority  of seed plantings,  and for which  an elasticity  estimate was available.  These crops
include  corn (elasticity  estimated  as -0.69),  wheat (-0.11),  dried  beans,  peas, and nuts (-0.12),  and  rice
(-0.15).   Since  no  information  was  located  on the quantity  of fungicides   applied  to seeds of  each crop, a
straight  average of the elasticities  was used  to estimate  the demand elasticity  for this cluster.  The resulting
estimate  for this cluster  is  -0.27.

x.     Fungicides  - post-harvest
      The elasticity of demand  for  fungicides  applied  post-harvest   is based on a weighted   average of the
elasticities  of demand  for the crops to which  fungicides  are applied  in the field.   These crops  are assumed
to be vegetables,  fruit  and  nut trees, and grapes, as these  were  the crops included  in the four  fungicide
clusters  for which   the  elasticity  of fungicides   used  in field  applications  was calculated.   Fungicides  are
assumed  to be  applied  to the crops after harvest  in the same ratios as they were applied  to the crops in the
field.   These  ratios  are used to weight  the demand  elasticities   for  the individual  crops.   The resulting
elasticity   estimate  is -0.65.

      A  complete  list  of Abt Associates'  estimated   price  elasticities  of  demand  for  clusters  defining
agricultural  end-uses  is provided  in Table  2.10.
                                                      C.55

-------
                                                Table 2.10
                  Estimates of Elasticity of Demand for Clusters in the Agricultural Sector
                 Cluster

                 Fungicides on:

                   fruit and nut trees except oranges
                   seed treatment
                   grain storage
                   vegetables
                   post-harvest
                   oranges
                   grapes
Elasticity Estimate
   -0.23
   -0.27
   -0.31
   -0.38
   -0.65
   -1.00
   -1.38
                 Herbicides on:

                  sugar beets, beans, and peas
                  tobacco
                  tree fruits (except oranges, nuts, sugarcane)
                  vegetables
                  soybeans, cotton, peanuts, and alfalfa
                  corn
                  sorghum, rice, and small grains
                  oranges
                  grapes
  -0.12
  -0.20
  -0.20
  -0.27
  -0.67
  -0.69
  -1.00
  -1.00
  -1.38
                Insecticides on:

                  vegetables
                  soybeans, peanuts, wheat, and tobacco
                  corn and alfalfa
                  sorghum
                  fruit and nut trees except oranges
                  oranges
                  cotton
                  grapes
  -0.33
  -0.56
  -0.69
  -0.69
  -1.00
  -1.00
  -1.06
  -1.38
Source: Abt Associates estimates based on Pimentel et al. (1991), USDA (1985), USDA (1989a), USDA
(1989b), USDA (1989c), Burrows (1983), Pingali and Carlson (1985), Miranowski (1980) Huh( 19878) U S
EPA (1974)                                                                                    "  ' '
                                           •   C.56

-------
 3.0    PRICE ELASTICITY   OF  DEMAND  FOR  PESTICIDES  USED  NON-AGRICULTURALLY
       Most of the pesticides  included  in this analysis  are used in the agricultural  sector; pesticides  in non-
 agricultural clusters,  as defined  by OPP, constitute  less than 30 percent  of total  pesticide use by weight  (U,S.
 EPA, 1988).  However,  the non-agricultural   pesticides  are described  by  eighteen  separate  clusters.   Unlike
 in the agricultural  sector,  these clusters represent  eighteen  distinct  and generally  unrelated end-uses,  each
 with its own  customers,  competitors,  and  costs.  The  literature  search described  above yielded  no studies
 of  the price  elasticity  of  demand for  pesticides   in the  non-agricultural    sector.  Since  the scope  of this
 project  does not allow for  the gathering  and examination   of primary data on elasticities  of  demand for each
 of these eighteen  markets  and  since non-agricultural   pesticide  use represents  a relatively  small percent of
 total pesticide  use, the demand  elasticities  for the non-agricultural   sector are developed  based on a reasoned
 consideration  of  two factors.   Consistent  with  the analysis  of agricultural  pesticide  use, these factors  are:
 (1) the availability  of substitutes for a cluster of pesticides,  and (2) the contribution  of pesticides  to the total
 production  cost of the end-user.

       Based on the above  two  factors,   the  eighteen  non-agricultural    clusters  fit into  two categories:   (1)
 pesticides   that  contribute   a small percentage   to  total cost but  have  substitutes,  and (2) pesticides  that
 contribute  a small percentage  of total production   costs and for which   there are limited substitutes.   There
 were no cases in which  it appeared that pesticides  contributed  a substantial  percentage  of total production
 costs.  The two categories  and the  clusters described by them are listed  below,  along with a brief discussion
 of the reasoning  behind  the cluster  categorization.

 (1)  Pesticides  contribute  a small  percentage  of total cost but substitutes  are available
     The  two non-agricultural   herbicide clusters  are included  in this  category:  (a)  herbicides  on ditches,
 rights  of way,  forestry,  and ponds,  and (b) herbicides   on turf.  The available  substitute  is labor, a viable
 alternative  to chemical weed  control.  To determine the shift  to manual/mechanical   weed  control given  an
 increase  in pesticides  price,   one would  need to know:  the  cost  of  herbicide   per  unit  of  area,  the
 effectiveness   of herbicides,   the labor cost of applying   herbicides  per unit of  area, the  labor cost of manual
weed  control  per  unit of  area,  and the effectiveness   of manual  weed control.   Since  these  two  clusters
 together constitute less than one percent of the pesticides  of interest (by weight)  it was decided  not to invest
resources  in the gathering  of these data.

      Rather,  Abt Associates  considered  the cost structure  of the end-users  of pesticides  in these clusters.
Herbicides  used on ditches,  rights  of way, forestry, and ponds  would  generally  be used  by  major industries
such  as railroads   and utilities  and by government  agencies,  such as state highway  departments!   The cost

                                                     C.57

-------
 of herbicides  would be an insignificant  percentage  of their  total production  costs.  Demand for this cluster
 of herbicides   is therefore  likely to be inelastic.  While herbicides  used  on turf  may contribute  a greater
 percentage  to the  total  production  costs  (assuming  that  these pesticides  are used,  for  example,  on  golf
 courses and turf farms)  the costs  should  still be relatively  small.  In addition,   fungicides  are applied  in
 conjunction  with herbicides  to turf.   It is  therefore  likely  that an application  system  would  be in  place  for
 fungicides,  making  the  incremental  costs  of herbicide  application  small.

       Based on  the above  discussion,  this  analysis  assumes  that  demand  for   the  two  non-agricultural
 herbicides  clusters  is inelastic.   Although   the level  of detail of the available  information  does  not result  in
 a quantitative  measure  of the elasticity,   such  a measure  is required.   Since  only one of the two  factors
 considered  above  indicates  inelasticity   (percent   of production  costs),  while  the  other is  inconclusive
 (substitute availability),   this analysis assumes that demand  for these two clusters is only moderately  inelastic,
 and assigns a price elasticity  of -0.66.  The sensitivity  analysis will consider the impacts on active ingredient
 manufacturers  if demand for pesticides  in these clusters  is perfectly  elastic.

 (2) Pesticides   contribute  a small percentage  of total  production   costs,  and there  are  limited substitutes
       The remaining  sixteen non-agricultural   clusters  are grouped  in  this category.  For each cluster,  the
 cost of pesticides  appeared incidental  to the total cost of production and no readily  available,  cost-effective
 alternatives  to the pesticides were known.   These two factors suggest  inelastic  demand.  Further, only three
 of the sixteen  clusters in this category  constitute  more than one percent  (by weight) of .the  pesticides  of
 interest in this analysis.    Therefore,   little additional  information  on the ultimate  costs  to manufacturers
 would  result from an investigation   of the remaining  thirteen  clusters.   The three clusters  which  included
 at least one percent by weight of the  total  pesticides  of concern  are listed  below with  a brief discussion  of
 their categorization:

 Insecticide  fumigants  and nematicides
       According  to Encyclopedia  Britannica,   "Fumigation,   which  requires some technical   skills and certain
 precautions  in application,  is mostly feasible for non-selective   quick killing of vermin in large commercial
 operations.  For the control of household  pests  it has been, to a considerable  extent,  supplanted  by more
 convenient  methods of extermination   such as the application  of powders  and residual sprays".   Fumigants
are largely used  for killing  insect pests of stored products,  for fumigating   nursery stock,  or for fumigating
sod, principally  for the  control  of plant parasitic  nematodes.   Given the application   in  large  commercial
operations,  the contribution  of fumigants  and nematicides  to production  cost  is likely  to be small.  Further,
since the use of  these products  has become somewhat specialized,  it is probable  that  few  substitutes  exist.
                                                      C.58

-------
Insecticides  for termite control
      Domestic  and commercial  use of chemical termite controls seems unlikely  to contribute  substantially
to total consumer  or commercial  business  expenses.  Also, while  in  the  long-run,   wood  could be replaced
to some extent  as a building  material,  in the  short-run   alternative   protection  from and eradication  of
termites is not  readily available.   Further,  the cost of termite  control  can be viewed  as insurance  against the
much larger cost of destruction  of a building,  making the cost of control appear small.  For the reasonably
foreseeable  future,  the demand  for  chemical termite  control  is likely  to be inelastic.

Wood preservatives  - industrial,   commercial,  marine use
      The wood preservative   industry  developed  because  of  the  need for prolonging   the  life of  wood
structures,  particularly  where  the structures  come  in  contact  with  ground.   Examples  of  treated  wood
include   railroad ties,  telephone   poles,  and marine  pilings.   Wood  may be chemically   treated  to protect
against  fungicides,   insects, and fire.  According  to  U.S.  EPA  (1982), expenditures  on wood preservative
account for  "only  a  small part"  of  the annual  billion  dollar  preserved  wood  market.    Cost-effective
alternatives  to  chemical wood preservation   are not known.   Demand  for pesticides in this cluster is therefore
assumed  to  be  inelastic.

      The remaining  clusters grouped in this  category  are:

•     Insect repellents at non-agricultural   sites
•     Domestic bug  control  and  food processing plants
•     Mosquito larvacides
•     Fungicides  on turf
•     Industrial preservatives   -  plastics,  paints,  adhesives,  textiles,  paper
•     Synergist  -  used as  insecticide  synergists,   surfactants,   cheleating  poultry  and livestock
•     Plant  regulators,  defoliants,  desiccants -  for all uses
•     Sanitizers - dairies,  food processing,  restaurants,  air treatment
•     Insecticides  on livestock  and  domestic animals
•     Fungicides  -  ornamentals
•     Industrial microbiocides,   cutting  oils,  and oil  well  additives
•     Preservatives,   disinfectants,   and  slimicides
•     Slimicides  - pulp and paper,  cooling  towers,  sugar mills
•     Fungicides  -  ornamentals
•     Industrial microbiocides,   cutting  oils,  and oil  well  additives
•     Preservatives,   disinfectants,   and  slimicides
                                                      C.59

-------
        Ideally,  a quantitative  measure  of  the price elasticity  of demand could  be developed  for each of the
 pesticides  clusters  listed above.  However,  the available  data  does not permit  this precision.  Since clusters
 in  this  category  have  no  known  cost-effective    substitutes   and since  the  pesticides  are  generally   an
 insignificant   portion of total production  costs, demand is expected  to be moderately to highly  inelastic.  The
 dusters  in this  category  are assigned  a price  elasticity  of demand of -0.33.   The sensitivity  analysis  will
 examine the impact  on manufacturers   in the  demand is perfectly  elastic.

       Finally,  two  clusters  remain  without  demand elasticity   estimates:  herbicides  for broad spectrum use
 and fungicides   for broad spectrum  use.  The  cluster "herbicides   for broad spectrum  use" contains  only one
 active  ingredient,  2,4-D.  The price elasticity  of demand  for  2,4-D was  estimated by Lacewell  and Masch
 (1972) and by  Carlson  (1977a,b).   Lacewell  and Masch  estimated the  elasticity  as  approximately   -0.38.
 Carlson  estimated   a short-run  elasticity  of -0.19   and a long-run  elasticity  of -0.59.   Averaging  Carlson's
 long-run estimate  and the estimate of Lacewell  and Masch results in an estimate of elasticity  of demand for
 2,4-D  of -0.48.  We use this value as the price elasticity  of demand  for  broad spectrum  herbicides.

       The  elasticity  estimate for broad spectrum  fungicides  is calculated   simply  by a weighted  average  of
 the elasticity  estimates  for  all of the other fungicide   clusters.  The weighting   is  based  on the  quantity  (by
weight)  of active ingredient  applied for  the end-uses  described  by each cluster.  The resulting  elasticity
estimate  is -0.40.   This  value  is in good agreement with the elasticity   of demand for  fungicides  estimated
by U.S. EPA (1985) as -0.35.
                                                    C.60

-------
4.0    CONCLUSIONS

       The estimated  elasticities  for all 44 clusters  are listed in Table 4.0,  in order of increasing  elasticity  of
demand.  As can be seen from the table,  the elasticity  estimates  range from -0.12  (herbicides  on sugar beets,
beans,  and  peas)  to -1.38  (fungicides   on grapes,  herbicides  on grapes,  and  insecticides   on grapes).   The
elasticity  estimates  vary substantially   within the fungicide,  herbicide,   and insecticide  clusters;   the type  of
pesticide  is not predicted  to have a strong   influence  on the elasticity  of demand.

       The demand for  pesticides   in all of  the clusters except  four  is expected to have  unit  elasticity  or to
be inelastic.  Demand is expected to be inelastic  for  the three clusters of pesticides applied  to grapes and
for insecticides  applied  to cotton.  The  main factor driving  the high elasticity for  the grape  clusters is the
high  elasticity  of demand  for  grapes at the retail  level.   Demand for  insecticides  on cotton  is expected  to
be somewhat elastic  based on literature  estimates  of the elasticity  and on the  low marginal  productivity   of
insecticides   applied  to  cotton.

       As  should  be clear from  sections  2  and 3, the methodology   employed   to estimate  the elasticity  of
demand for the clusters  yields  reasonable   best estimates  of elasticities  rather  than  certain quantifications.
The  estimates are likely to accurately  depict whether demand  for a certain cluster of pesticides is extremely
or only moderately  elastic  or inelastic;  the specific  numeric  value should  not  be viewed  as definitive.
However,  no estimates  of elasticity  of demand  for clusters of pesticides  that are more reliable  than those
developed  through this  analysis  are known.   To address  the uncertainty  implicit  in the estimates, a scenario
in which  the manufacturers  bear  the total  costs of regulatory  compliance will also be examined.
                                                       C.61

-------
                                                   Table  4.0
                       SUMMARY  OF ESTIMATES  OF ELASTICITY  OF DEMAND
                          on sugar beets,  beans, peas
                          on tree  fruits  (except oranges), sugar  cane,  nuts
                          on tobacco
                          on fruit  and nuts trees  (except  oranges)
                          for  seed treatment
                          on vegetables
                          on grain in storage
                          on vegetables
 Cluster

 Herbicides
 Herbicides
 Herbicides
 Fungicides
 Fungicides
 Herbicides
 Fungicides
 Insecticides
 Slimicides
 Fumigants  and nematicides
 Insecticides  on termites
 Wood preservatives
 Insect  repellents at non-agricultural   sites
 Domestic bug  control  and food  processing  plants
 Mosquito larvacides
 Fungicides  on turf
 Industrial preservatives
 Insecticide  synergists  and surfactants
 Plant regulators, defoliants,  desiccants
 Sanitizers - dairies, food processing,  restaurants,  air  treatment
 Insecticides  on livestock   and domestic  animals
 Industrial microbiocides,   cutting oils, oil well  addivites
 Preservatives,   disinfectants,  and slimicides
 Fungicides  - ornamentals
 Fungicides  on vegetables
 Fungicides  - broad spectrum
 Herbicides  - broad spectrum
 Insecticides  on soybeans,  peanuts,  wheat, tobacco
 Fungicides  - post harvest
 Herbicides  on  rights of way,  drainage ditches
 Herbicides  on  turf
 Herbicides  on  soybeans,   cotton,  peanuts, alfalfa
 Herbicides  on  corn
 Insecticides  on corn, alfalfa
 Insecticides  on sorghum
 Herbicides  on  sorghum rice, small  grains
 Herbicides  on  oranges
 Fungicides  on  oranges
Insecticides  on fruit  and  nut trees,  except oranges  and grapes
 Insecticides  on oranges
Insecticides  on cotton
Fungicides  on  grapes
Insecticides  on grapes
Herbicides  on  grapes
                                                                            Elasticity  Estimate
 -0.12
 -0.20
 -0.20
 -0.23
 -0.27
 -0.27
 -0.31
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.33
 -0.38
 -0.40
 -0.48
 -0.56
 -0.65
 -0.66
 -0.66
 -0.67
 -0.69
 -0.69
 -0.69
-1.00
-1.00
-1.00
-1.00
-1.00
-1.06
-1.38
-1.38
-1.38
Source: Abt Associates  estimates
                                                    C.62

-------
                                            References

Burrows,  T.  (1983).   Pesticide  Demand  and  Integrated  Pest Management:  A Limited  Dependent
Variable Analysis,   American  Journal  of Agricultural   Economics, November.

Campbell,  H. (1976).   Estimating  the  Marginal Productivity   of Agricultural   Pesticides:  The Case of
Tree-Fruit   Farms  in the Okanagan Valley.  Canadian Journal  of Agricultural   Economics 24(2), 1976.

Carlson, G.  (1977). The Long Run Productivity  of Insecticides,  American  Journal  of Agricultural
Economics,  59,  pp. 543-548,  August.

Carlson, G. (1977a). Economic Incentives for Pesticide  Pollution  Control  in Ttie Practical Application
of Economic Incentives to the  Control  of Pollution:  Tlie Case of  British Columbia,  ed. J. Stephenson.
Vancouver:   University  of British Columbia  Press.

Hall, D.C.,  and L.J.  Moffitt.   (1983).    Stochastically   Efficient   Economic Thresholds  for Discrete
Choices.  USDA-ERS   unpublished  manuscript.   Washington  D.C.

Headley,  J.C. (1968).   Estimating  the Productivity  of Agricultural  Pesticides,  American Journal of
AGriciiltural  Economics,  50:13-23,  February.

Huh, Shing Haeng (1978).  The Preventive  and Incidental   Demand  for Pesticides:   An Economic
Analysis  of the Demand  for Herbicides  and  Insecticides   Used  by Selected Corn  Producers in
Minnesota.  Thesis  submitted  to the Graduate School  of the University   of Minnesota.   June.

Lacewell,  R. and W. Masch, (1972).  Economic  Incentives  to Reduce the Quantity of Chemicals Used
in Commercian  Agriculture.  Southern  Journal of Agricultural   Economics. July.

Lichtenberg,  E. and D. Zilberman (1986).  The Econometrics of  Damage  Control:  Why Specification
Matters. American  Journal  of Agricultural  Economics.  May.

Miranowski,  J.  (1980).  Estimating  the  Relationship between  Pest Management and Energy Prices,  and
the Implications  for Environmental  Damage. American  Journal of Agricultural  Economics. December.

Pimentel,  D., et al. (1991).   Environmental   and Economic  Impacts of Reducing  U.S.  Agricultural
Pesticide  Use,  in ed. Pimentel, D., Pest Management  in Agriculture.   CRC press.

Pingali, P. and  G. Carlson (1985).  Human  Capital,  Adjustments  in  Subjective  Probabilities,  and the
Demand for Pest Controls.  American  Journal of Agricultural  Economics.  November.

U.S.D.A.  (1985).  U.S. Demand for Food:  A Complete  System  of Price and Income Effects.  By  Kuo
S. Huang, National  Economics Division,  Economic Research  Service.  Technical Bulletin No. 1714.

U.S.D.A.  (1988).  1985 Potato Cost and Returns:   Fall Production Areas.  Potato facts  special edition.
Economic Research Service.   September.

U.S.D.A.  (1989).  Retail to Farm  Linkage for a Complete  Demand System of Food Commodities.   By
Michael K. Wohlgenant . and  Richard  C. Haidacher.   Commodity  Economics  Division,  Economic
Research  Service.   Technical  Bulletin  No.  1775.

U.S.D.A.  (1989a).   Economic Indicators  of the Farm  Sector:  Costs of Production, 1987.  ERS, USDA,
ECIFS7-3.   February.

U.S.D.A.  (1989b).  Tobacco:  Situation  and  Outlook Report.  Economic  Research Service.  September.
                                                  C.63

-------
U.S.D.A.  (1989c).   Agricultural   Statistics  1989.  Washington.

U.S.  EPA (1974).   Farmers'  Pesticide  Use  Decisions  and  Attitudes  on Alternate  Crop  Protection
Methods.   Washington.

U.S. EPA (1982).  Regulatory  Impact Analysis  Data Requirements  for Registering  Pesticides  under
the Federal Insecticides,   Fungicides  and Rodenticide  Act.  Office of Pesticide  Programs.   August.

U.S. EPA (1985). Economic  Impact  Analysis  of Effluent  Limitations  Guidelines  and Standards  for
the Pesticide  Chemicals  Industry. September.

U.S. EPA (1988).  Pesticide  Industry  Sales and Usage:  1988 Market Estimates.   Office  of Pesticide
and Toxic Substances.   February.
                                               C.64

-------
                                         Appendix D
    Compliance Costs as a Percentage of Revenue for Baseline Facility Closures

        The facilities which were estimated to close in the baseline in the facility level analysis could not
be analyzed for post-compliance impacts using the standard methodology, as these facilities had a negative
baseline cash flow before the costs of complying with the proposed regulations were  considered (see
Chapter 4).  EPA further analyzed the PSES facilities deemed to be baseline closures to estimate whether
the facilities would be impacted by the initially selected regulation, Option 3/S, if the facilities were able
to remain in business despite their financial weakness. The methodology used was an examination of the
ratio of total annualized compliance costs under Option 3/S to the total  annual  average revenue of the
facility.  As discussed in Chapter 4, a cost to revenue ratio of greater than five percent may mean that
the facility could face economic hardship  as a result of compliance, although no operational changes are
necessarily expected. Such an impact would be a moderate effect.  The Agency found that relatively few
facilities, if able to stay in business, would be moderately impacted by the costs of complying with the
proposed effluent guidelines.

        There are 372 PSES facilities that are estimated to close in the baseline. Of these, 124 would
incur costs under Option 3/S.  Among  these 124  facilities, the mean  and median ratio of costs  of
compliance to total revenue are 3.6 percent and 1.1  percent, respectively.  Only 24 (19 percent), have
a cost of compliance to revenue ratio of greater  than five percent.   These 24  facilities represent 6.5
percent  of all of the PSES facilities  projected to  close in the baseline.  The Agency does not expect
compliance with the Option to represent a significant burden to the facilities which are predicted to close
in the baseline.
                                              D.I

-------

-------
                                         Appendix E
    Sensitivity Analysis of the Return on Asset Value Used in Line Conversion
                                           Analysis
       This appendix provides a sensitivity analysis of the threshold value of return on assets (ROA) used
in the line conversion analysis of facility impacts for PFPR facilities with less than 25 percent of their
revenue from PFPR operations.  The ROA threshold value is used as the criterion for projecting that
PFPR facilities will convert their production lines  from pesticide operations to other non-pesticide
formulating and packaging activities.  If a facility  achieves at least the threshold ROA in the baseline
analysis, but is projected to have post-compliance ROA less than the threshold value, the facility is said
to incur the moderate impact of a line conversion.

       The EIA set the ROA threshold value at 2.9 percent. This value is the lowest quartile value of
firms operating in SIC code 2842 (specialty cleaning, polishing and sanitation preparations), averaged
over the three-year period  1986-1988, as indicated by Robert Morris Associates.  SIC 2842 is chosen as
being representative of alternative FPR activities to  which impacted facilities could turn. This SIC code
was among the  most frequently reported SIC codes  for PFPR facilities obtaining less than 25 percent of
the their revenue from  PFPR operations.

       As a sensitivity analysis to examine the stability of the number of moderate impacts within a range
of plausible thresholds, EPA recalculated impacts using  an ROA threshold of 7.2 percent.  This value
is the median value reported in SIC code 2842, averaged  over the 1986-1988 period.  Thus, the analysis
assumes that a facility would convert its production lines from PFPR activities to other  FPR activities if
the facility could expect to obtain the return on assets of the median firm performing such activities.
Using a  higher threshold value will reduce the number  of facilities considered for moderate impacts,
because facilities achieving less than the threshold value in the baseline are not considered for line
conversion impacts.  The higher threshold, however, increases the number of impacts for those facilities
that are considered for impacts.  The net outcome in terms of the number of moderate impacts from these
two effects is indeterminate;  the number of facilities projected to convert PFPR  lines  may  increase or
decrease as a result of using a higher threshold value.
                                              E.I

-------
       The results of this  sensitivity analysis indicate that two fewer  moderate impacts would be
estimated to occur in the facility population under Option 3 if the line conversion decision were based
on the higher ROA threshold value.  Given this slight decrease in impacts, EPA concludes that the
number of line conversion impacts is stable within a range of plausible ROA threshold values.
                                              E.2

-------
                                         Appendix F
            Facility Impact Analysis Assuming a Price-Adjustment Rule

F.O    Introduction
       The facility impact analysis of the EIA was conducted assuming that facilities are unable to pass
any cost increases through to consumers. As discussed in Chapter 4, this is an extremely conservative
assumption that serves as a worst-case analysis. This appendix provides the results of the facility impact
analysis using a price-adjustment rule in which facilities attempt to pass through half of their compliance
costs  (expressed as a  percentage  of revenue)  to customers in the form of price increases.   This
assumption, while imprecise, reflects the reality that facilities are likely to attempt recovery of their cost
increases by raising prices.  Section 1 of this appendix describes the methodology EPA used to estimate
pre-compliance and post-compliance prices and quantites under this price-adjustment rule, and the effects
on cash flow.  Section 2 provides the results of the analysis.

F.I    Price-Adjustment Methodology
       Producers and consumers jointly determine the quantities and prices of pesticide products sold
in the market place.  Producers raise prices based on the change in their production  costs and the
expected reactions of competitors.  In turn, consumers respond with reduced demand based on several
factors, including the percent of consumers'  production cost contributed by the pesticide product and the
availability of substitute products. Producers then consider the impact of the price increase and demand
decrease on profitability and may  readjust their prices.  The process repeats until an equilibrium  is
reached.

       This analysis summarized in this Appendix approximates an end point of the supply and demand
interaction.  Producers are assumed to follow a pricing rule in which they increase product prices by an
amount that would recover half of each facility's increase in costs if their sales quantity remains constant.
However, as facilities raise prices under the pricing rule, consumers respond  by changing the quantity
of products purchased based on the price  elasticity of demand for pesticides.  Because the quantity
demanded generally changes in response to the facility's increase in price based on the elasticity  of
demand, the result in terms of amount of cost increase recovered by the PFPR facility does not generally
amount to 50 percent of the  compliance costs.
                                              F.I

-------
       The price elasticity of demand is defined as the percentage change in the quantity demanded,
divided by the percentage change in price.  If,  in response to price increases, consumers reduce their
purchases by more than the percentage increase in price, then revenues will decline and demand is said
to be elastic:  customers  are sensitive to price changes.  However, if, in response to price increases,
consumers reduce their purchases by  less  than the percentage  increase in price, then revenues will
increase and demand is said to be inelastic:  customers are not so sensitive to price changes.  The value
of the price elasticity of demand is unbounded and may be positive or negative. In general, though, price
and  demand are negatively correlated —  an increase in price results in a decrease in the quantity
demanded —  and the price elasticity of demand is therefore usually negative.

       Estimates of the price elasticity of demand for  each  pesticide cluster were generated as part of
the EIA for Effluent Limitations Guidelines and Standards for the Pesticide Manufacturing Industry. The
main source of data from which the pesticide elasticities were  derived  was the U.S. Department of
Agriculture's (USDA) analysis of the price elasticity of demand for food commodities (USDA, 1985,
1989).  The elasticity of  demand for farm  inputs can be derived from the elasticity of the demand for
farm commodities since demand for production inputs must ultimately reflect demand for the end product.
Though the two elasticities may not correspond exactly, the elasticity of demand for the food commodities
can serve as a reasonable proxy for the elasticity of demand for pesticides in the absence of more relevant
data. These elasticity estimates were therefore also used to  estimate the demand elasticity faced by all
PFPR facilities.

        A list of the elasticity estimates by cluster is shown in Table F-l in order of increasing elasticity
of demand.  As  can be seen from the table, the elasticity estimates range from the relatively inelastic
value of -0.12  (herbicides on  sugar beets, beans,  and peas) to the relatively elastic value of  -1.38
(fungicides on grapes and herbicides on grapes). The elasticity  estimates vary substantially within the
fungicide, herbicide, and insecticide clusters:  the elasticity of demand does not to appear to  depend in
any systematic way on whether a pesticide  is  a fungicide, herbicide, or insecticide.

        The demand for pesticides hi all but three of the clusters is expected to have unit elasticity (i.e., -
 1) or to  be inelastic.  Demand is expected  to be elastic for fungicides and herbicides applied to grapes
and for insecticides applied to cotton.  The main factor driving the high elasticity for the grape clusters
is the high elasticity of demand for grapes at the retail  level. Demand for insecticides on cotton is
                                                F.2

-------
                                                   Table F.I
                                Summary of Estimates of Elasticity of Demand
Cluster
Elasticity Estimate
Herbicides on sugar beets, beans, peas
Herbicides on tree fruits (except oranges), sugar cane, nuts
Herbicides on tobacco
Fungicides on fruit and nuts trees (except oranges)
Fungicides for seed treatment
Herbides on vegetables
Fungicides on grain in storage
Insecticides on vegetables
Slimicides
Fumigants and nematicides
Insecticides on termites
Wood preservatives
Insect repellents at non-agricultural sites
Domestic bug control and  food processing plants
Mosquito larvacides
Fungicides on turf
Industrial preservatives
Insecticide synergists and surfactants
Plant regulators, defoliants, desiccants
Sanitizers - dairies, food processing, restaurants, air treatment
Insecticides on livestock and domestic animals
Industrial microbicides, cutting oils, oil well additives
Preservatives, disinfectants, and slimicides
Fungicides - ornamentals
Insecticides on lawns, ornamentals and forest trees
Unclassified uses
Fungicides on vegetables
Fungicides - broad spectrum
Herbicides - broad spectrum
          -0.12
          -0.20
          -0.20
          -0.23
          -0.27
          -0.27
          -0.31
          -0.33
          -0.33
          ^0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.33
          -0.38
          -0.40
          -0.48
                                                 F.3

-------
Table F.I
Summary of Estimates of Elasticity of Demand
Cluster
Insecticides on soybeans, peanuts, wheat, tobacco
Fungicides - post harvest .
Herbicides on rights of way, drainage ditches
Herbicides on turf
Herbicides on soybeans, cotton, peanuts, alfalfa
Herbicides on corn
Insecticides on com and alfalfa
Insecticides on sorghum
Herbicides on sorghum, rice, small grains
Herbicides on oranges
Insecticides on fruit and nut trees, except oranges and grapes .
Insecticides on oranges
Herbicides - other agricultural uses
Insecticides on cotton
Fungicides on grapes
Herbicides on grapes
Source: Estimates of the Price Elasticity of Demand for Pesticide Clusters, U.S. EPA and
1991.
Elasticity Estimate
-0.56
-0.65
-0.66
-0.66
-0.67
-0.69
-0.69
-0.69
-0.69
-1.00
-1.00
-1.00
-1.00
-1.06
-1.38
-1.38
Abt Associates, Inc. , May
expected to be somewhat elastic, based on both the literature estimates of the elasticity and the low
marginal productivity of insecticides applied to cotton.
       The methodology used to estimate the elasticity of demand for the PAI clusters yields best
estimates of elasticities.  The estimates are good indicators of whether demand for a certain cluster of
PAIs is extremely or only moderately elastic or inelastic; however, the specific numeric values should
not be viewed as definitive.  The estimated elasticities of demand for clusters Of PAIs, developed through
this analysis, are the most reliable estimates known at this time.

       Baseline Quantities and Prices
       The use of 272 PAIs in pounds by facilities is available from the Survey. EPA matched these
PAIs to the clusters to which the PAIs belonged. The total weight of active ingredients is the facility's
baseline quantity.  A weighted average baseline price was approximated for each facility by dividing the
                                               F.4

-------
facility's revenue from PFPR activities involving the 272 PAIs (the sum of questions 3, 4 and 5 in Part
B of the Survey) by the total weight of 272 PAIs used by the facility.
       Post-Compliance Quantities and Prices
       Because facility-level prices, costs, and compliance costs are not available for individual PAIs,
clusters of PAIs, or pesticide products, an average pesticide demand elasticity was calculated for each
facility based on the 272 PAIs used by the facility.  The average elasticity of demand  faced by a facility
for pesticides was calculated by weighting the cluster elasticity estimates by the facility use of PAIs in
each cluster:
                                             m=l
                                                       PUt
where:
PU
        =      price elasticity of demand for 272 PAI pesticides faced by PFPR facility, k;
        =      price elasticity of demand for cluster m;
        =      use of PAIs in cluster m by facility k (Ibs); and
        =      total use of 272 PAIs by facility k (Ibs).

The change in the quantity of pesticide production resulting from price increases was calculated
 as:
 where:
                                           =  PER, *EkxQk
                change in production of 272 PAI pesticides at facility k (Ibs.);
                percentage unit price increase for 272 PAI pesticide products at facility k (the percentage
                unit price  increase is  the amount necessary, to recover one-half _of the facility's total
                annualized cost of compliance assuming no change in production quantity);
                price elasticity of demand faced by PFPR facility k;  and
                pre-compliance production of 272 PAI pesticides at facility k (Ibs.).
        Post-Compliance Cash Flow
        Under the assumption of a price-adjustment rule, three factors are accounted for in the estimate
 of post-compliance cash flow:
                                                F.5

-------
       •       the compliance costs, including capital and operating and maintenance;
       •       the change in revenue associated with the new price and quantity; and
       •       the decrease in variable costs of production resulting from reduced quantity of sales.

The post-compliance cash flow for a facility is calculated by adjusting baseline cash flow for each of these
factors. The corresponding equation is:
where:
PCCF
CF
CCadj
Radj
Cadj
                           PCCF  =  CF + (-CCadj + Radj + Cadj)
the post-compliance facility cash flow;
facility baseline cash flow;
compliance cost adjustment to cash flow;
the adjustment to cash flow from the change in revenue; and
the adjustment to cash flow from the change in variable costs.
These three adjustments are discussed below.

               Compliance Cost Adjustment
       The compliance cost adjustment is identical to the adjustment under the zero cost pass-through
assumption (see Chapter 4).  Specifically, compliance costs have two  components:  capital  costs and
operating and maintenance costs.  Full capital costs, funded both by debt and equity are included. An
annualized capital cost was calculated by dividing the estimated capital and land investment by the present
value factor, which is based on the weighted average cost of capital,  as  discussed in Chapter 4.  In
addition, the facility will pay reduced taxes as a result of depreciating the capital expenditures.  Annual
operating and maintenance costs are also  offset somewhat by the reduction in taxes from reduced profits.
The calculation is as follows:
                     CCadj  =  (OMx(l-CZ)) +
                                                  PVF
                                                   10
where:
       CCadj  =      Compliance cost adjustment to cash flow;
                                              F.6

-------
       OM    =     Operating and maintenance costs of compliance;
       CT     =     Marginal corporate tax rate;
       PVF    =     Present value factor; and
       CPT    =     Capital costs of compliance.

               Adjustment for Change in Revenue
       The change in revenue contains  two components:  the increase in revenue resulting from the
increase in price and the decrease in revenue resulting from the decrease in quantity.  The change  in
revenue will be partially offset by the corresponding change in taxes.  The calculation is as follows:
                        Radj  =   ((AP  x PCQ)  + (P x  AQ)) x (1-C7)
where:
Radj
AP
PCQ
P
AQ
CT
Adjustment to cash flow due to the change in revenue;
Change in price from baseline to post-compliance;
Post-compliance quantity;                           ,
Baseline price;
Change in quantity from baseline to post-compliance;  and
Marginal corporate tax rate.                        .,.
               Adjustment for Change in Variable Cost of Production
       The final adjustment to baseline cash flow reflects the decrease in variable costs resulting from
decreased production. Variable costs were assumed to decrease in proportion to the decrease in quantity
of pesticides produced.  The decrease is again partially offset by an increase in taxes.  The equation is:
                               Cadj   =  -

                                 x VC\ x (1-CI)
where:
Cadj
AQ
Q
VC
CT
Adjustment to the cash flow due to the change in variable costs;
Change in 272 PAI pesticide quantity from baseline to post-compliance;
Baseline 272 PAI pesticide quantity;
Eestimated variable cost associated with 272 PAI pesticide production; and
Marginal corporate tax rate.
                                              F.7

-------
F.2    Results Using the Price-Adjustment Rule
       Under the price-adjustment rule, the estimated impacts are unchanged from the analysis in the
EIA using a zero cost pass-through methodology. These estimated impacts are presented in Table F-2
for the five PSES options initially considered for regulating Subcategory C facilities.
Table F.2
National Estimates of Economic Impacts upon Subcategory C Facilities
(Assuming A Price Adjustment Rule)

-Facilities Incurring Costs
-Compliance Capital Costs ($000,000)
-Total Annualized Compliance Costs
($000,000)
-Facility Closures . =
-Moderate Economic Impacts
-Worst Case Expected Job Losses (FTEs)
Option 1
578
$79.0
$32.6
9
171
437
Option 2
558
$66.1
$27.9
1
170
426
Option 3
558
$66.1
$27.9
1
170
426
Option 4
558
$18.4
$286.5
7
193
1,113
Option 5
578
$21.0
$360.2
7
217
1,173
                                             F.8

-------
                 Cost-Effectiveness Analysis of
                 Proposed Effluent Limitations
               Guidelines and Standards for the
Pesticide Formulating, Packaging, and  Repackaging Industry
                     Dr. Lynne G. Tudor, Economist
                  Economics and Statistical Analysis Branch
                     Engineering and Analysis Division
                     Office of Science and Technology

                   U.S. Environmental Protection Agency
                        Washington, DC 20460

-------

-------
                                  TABLE OF CONTENTS
Section 1: Introduction	
Section 2: Methodology	
Section 3: Results Using Original 272 PAIs	
Section 4: Results Using Additional Non-272 PAIs  	
Section 5: Comparison of Cost-Effectiveness Values with Promulgated Rules .  . .
Appendix A: Original 272 Pesticide Active Ingredients Considered for Regulation
Appendix B: Toxic Weighting Factors for Pesticide Active Ingredients	
Appendix C: Results of Compliance with the Existing 1978 BPT Regulation  .  . .
Appendix D: Sensitivity Analysis of POTW Removal Efficiency	
 1.1
 2.1
 3.1
 4.1
 5.1
A.I
B.I
C.I
D.I

-------
                                     LIST OF TABLES

Table 1: Weighting Factors Based on Copper Freshwater Chronic Criteria	  2.3
Table 2: National Estimate of Annualized Costs and Removals Under PSES,
       Subcategory C Facilities	  3.1
Table 3: Estimated Industry Incremental Cost-Effectiveness Under PSES,
       Subcategory C Facilities	  3.2
Table 4: Estimated Industry Incremental Cost-Effectiveness Under PSES,
       Disaggregated by Primary Market, Subcategory C Facilities	  3.4
Table 5: National Estimate of Annualized Costs and Removals Under PSES,
       Subcategory E Facilities	  3.6
Table 6: National Estimate of Annualized Costs and Removals Under PSES of Option 3/S',
       Considering Non-272 PAI Costs but not Non-272 PAI Removals,
       Subcategory C Facilities	  4.1
Table 7: National Estimate of Annualized Costs and Removals Under PSES of Option 3/S',
       Considering Non-272 PAI Costs and Removals, Subcategory C Facilities  	  4.2
Table 8: Industry Comparison of Cost-Effectiveness for Indirect Dischargers
       (Toxic and Nonconventional Pollutants Only) Copper Based Weights	  5.2
Table B-l: Toxic Weighting Factors for Pesticide Active Ingredients	B.2
Table C-l: National Estimate of Annualized Costs and  Removals Under BPT,
       Subcategory C Facilities	C. 1
Table C-2: Estimated Industry Incremental Cost-Effectiveness Under BPT,
       Subcategory C Facilities	C.2
Table D-l: National Estimate of Annualized Costs and  Removals Under PSES,
       Subcategory C Facilities, Assuming 50 percent POTW Removal Efficiency for PAIs  . .  .  D.2
Table D-2: Estimated Industry Incremental Cost-Effectiveness Under PSES,
       Subcategory C Facilities, Assuming 50 percent POTW Removal Efficiency for PAIs  . .  .  D.3
Table D-3: National Estimate of Annualized Costs and  Removals Under PSES,
       Subcategory E Facilities, Assuming 50 percent POTW Removal Efficiency for PAIs  . .  .  D.4

-------
                                            Section 1
                                          Introduction

        This analysis is submitted in support of the proposed effluent limitations guidelines and standards
for the Pesticide Formulating,  Packaging, and Repackaging (PFPR) Industry.  The report analyzes the
cost-effectiveness of six alternative Pretreatment Standards for Existing Sources (PSES) regulatory options
for Subcategory  C facilities based on the original 272 pesticide active ingredients (PAIs) studied for
regulation.  An additional  Subcategory C PSES option covering all PAIs (except sodium hypochlorite)
is analyzed.  Also, two PSES regulatory options for Subcategory E facilities are evaluated.

        Section 2 of the report defines cost-effectiveness, discusses the cost-effectiveness methodology,
and describes the relevant  regulatory options.  Section 3 presents the findings of the analysis covering
only the original 272 PAIs.  Section 4 provides the results of the analysis of the option including non-272
PAIs.   In Section 5,  the cost-effectiveness values are compared to cost-effectiveness values for other
promulgated rules.  Four appendices are also included.  Appendix A lists the original 272 pesticide active
ingredients on which  this analysis is based. Appendix B lists the toxic weighting factors for these 272
PAIs.  Appendix C describes the cost-effectiveness results for direct discharging facilities to comply with
the existing  Best Practicable  Control  Technology  Currently Available (BPT)  regulation.   Finally,
Appendix D provides a sensitivity analysis of POTW removal efficiencies for PAIs.

-------

-------
                                           Section 2
                                         Methodology

     .  This section defines cost-effectiveness, describes the steps taken in the cost-effectiveness analysis,
and characterizes the regulatory options considered in the analysis.

       Cost-effectiveness calculations are used in setting effluent limitations guidelines to compare the
efficiency of  one regulatory option  in  removing pollutants  to  another  regulatory  option.   Cost-
effectiveness  is defined as the incremental annual cost of a pollution control option in an industry or
industry  subcategory per incremental  pollutant removal.  The increments considered are relative to
another option or to a benchmark, such as existing treatment. Pollutant removals are measured in copper-
based "pounds-equivalent."  The cost-effectiveness value, therefore, represents the unit cost of removing
the next pound-equivalent of pollutant.  While not required by the Clean Water Act, cost-effectiveness
analysis is a  useful tool for evaluating regulatory options for the removal of toxic pollutants.  Cost-
effectiveness analysis is not intended to analyze the removal of conventional pollutants (oil and grease,
biological oxygen demand, and  total  suspended solids).  The removal of conventional pollutants is
therefore not addressed in this report.

       Three factors are of particular importance in cost-effectiveness calculations: (1) the normalization
of pounds of pollutant removed to copper-based pounds-equivalent; (2) the incremental nature of cost-
effectiveness, and (3) the fact that cost-effectiveness results are used for comparison purposes rather than
on an absolute basis.  First, the analysis is based on  removals of pounds-equivalent - a term used to
describe a pound of  pollutant weighted by its toxicity relative to copper.  These weights are known as
toxic weighting factors.  Copper is used as the standard pollutant for developing toxic weighting factors
because it is a toxic metal commonly released in industrial effluent and removed from that effluent. The
use of pounds-equivalent reflects the fact that some pollutants are more toxic than others.  Also, by
expressing removals  in  common terms, the removals  can  be summed  across pollutants  to  give  a
meaningful basis for comparing cost-effectiveness results among alternative regulatory options or different
regulations.

       Second, cost-effectiveness analysis is done on  an  incremental basis to compare the incremental
or marginal cost and removals of one control option to another control option or to existing treatment.
                                               2.1

-------
       The third point is that no absolute scales exist for judging cost-effectiveness values.  The values
are considered high or low only within a given context, such as similar discharge status or compared to
effluent limitations guidelines for other industries.

       Cost-effectiveness analysis involves a number of steps, which may be summarized as follows:

       •      Determine the relevant wastewater pollutants;
       •      Estimate the relative toxic weights of priority and other pollutants;
       •      Define the pollution control approaches;
       •      Calculate pollutant removals for each control option;
       •      Determine the annualized cost of each control option;
        •      Rank the control options by increasing stringency and cost;
        •      Calculate incremental cost-effectiveness values; and
        •      Compare cost-effectiveness values.

These steps are discussed below.

       Pollutant Discharges Considered in the Cost-Effectiveness Analysis
       Some of the factors considered in selecting pollutants for regulation include toxicity, frequency
of occurrence, and  amount of pollutant in the wastestream.  The cost-effectiveness of the Pesticide
Formulator, Packager, and  Repackager (PFPR) effluent limitations guidelines is based on 272 pesticide
active ingredients (PAIs). A list of these pollutants is shown in Appendix A.  Because priority pollutants
generally do not appear in PFPR wastewater, no priority pollutants are included in the analysis.

       Relative Toxic Weights of Pollutants
        Cost-effectiveness analyses account for differences in toxicity among the regulated pollutants by
using toxic weighting factors (TWFs).   These factors  are necessary because different pollutants have
different potential effects on human and  aquatic life.  For example, a pound of nickel (TWF=0.036) in
an effluent stream has significantly less  potential effect than a pound of cadmium  (TWF=5.12). The
toxic weighting factors are used to  calculate the pound-equivalent unit -  a standardized  measure of
toxicity.
                                               2.2

-------
        In the majority of cases, toxic weighting factors are derived from both chronic freshwater aquatic
criteria (or toxic effect levels) and human health criteria (or toxic effect levels)  established  for the
consumption  of fish.1 These factors are then standardized by relating them to copper.2  The resulting
toxic weighting factors for each PAI  are provided  in  Appendix B.  Some examples of the effects of
different aquatic and human health criteria on weighting factors are shown in Table 1.
Table 1
Weighting Factors Based on Copper Freshwater Chronic Criteria
Pollutant
Copper**
Hexavalent
Chromium
Nickel
Cadmium
Benzene
Human
Health
Criteria*
Otg/i)
—

3,400
4,600
170
12
Aquatic
Chronic
Criteria
Otg/D
12.0

11.0
160.0
1.1
265.0
Weighting
Calculation
5.6/12.0

5.6/3,400 + 5.6/11
5.6/4,600 + 5.6/160
5.6/170 + 5.6/1.1
5.6/12 + 5.6/265
Toxic
Weighting
Factor
0.467

0.511
0.036
5.12
0.488
Criteria are maximum contamination thresholds. Using the above calculation, the greater
the values for the criteria used, the lower the toxic weighting factor. Units for criteria are
micrograms of pollutant per liter of water.
* Based on ingestion of 6.5 grams of fish per day.
** While the water quality criterion for copper has been revised (to 12.0 jwg/1), the cost-
effectiveness analysis uses the old criterion (5.6 jig/1) to facilitate comparisons with cost-
effectiveness values for other effluent limitations guidelines. The revised higher criteria for
copper results in a toxic weighting factor for copper not equal to 1 .0 but equal to 0.467.
    !A complete discussion of the development of the toxic weighting factors can be found in Toxic Weighting
Factors for Pesticide Active  Ingredients and Priority Pollutants  Final Report, July 13, 1993, located in  the
Administrative Record.

     While the water quality criterion for copper has been revised (to 12.0 /tg/1), the cost-effectiveness analysis uses
the old criterion (5.6 /tg/1) to facilitate comparisons with cost-effectiveness values for other effluent limitations
guidelines. The revised higher criterion for copper results in a toxic weighting factor for copper equal to 0.467,
not 1.0.
                                                  2.3

-------
       As indicated in Table 1, the toxic weighting factor is the sum of two criteria-weighted ratios:
the "old" copper criterion divided by the human health criterion for the particular pollutant, and the "old"
copper criterion divided by the aquatic chronic criterion.   For example, using the values reported in
Table 1, 10.96 pounds of copper pose the same relative hazard in surface waters as one pound of
cadmium, since cadmium has a toxic weight 10.96 times  (5.12/0.467  =  10.96) as large  as the toxic
weight of copper.

       Pollution Control Options
       This analysis considers the cost-effectiveness of a Pretreatment Standard for Existing  Sources
(PSES) regulation  applicable to indirect discharging facilities.   Two Subcategories of facilities are
examined:   Subcategory  C  (Pesticide  Formulating,  Packaging, and  Repackaging Facilities),  and
Subeategory E (Refilling Establishments).  Six PSES regulatory options are evaluated for Subcategory
C facilities, and two PSES options are evaluated for Subcategory E facilities.  The six options examined
for Subcategory C facilities are as follows:

        •      Option  1  consists of end-of-pipe treatment for the entire wastewater volume now
               generated by PFPR facilities through the Universal Treatment System3 and discharge to
               POTWs.

        •      Option 2 adds pollution prevention by recycling wastewaters generated from cleaning the
               interiors of formulating  and packaging equipment and  raw  material and shipping
               containers  into  the product  to  recover product value  in  the wastewaters.    Other
               wastewaters are still expected  to be treated  through the Universal Treatment System and
               discharged to POTWs.

        •      Option 3 employs the same technology and pollution prevention practices as Option 2
               but achieves zero discharge of all process wastewater by recycling the wastewater back
               to the facility after treatment through the Universal Treatment System.
    3The Universal Treatment System consists of chemical emulsion breaking, hydrolysis, chemical  oxidation,
sulfide precipitation and activated carbon filtration treatment technologies.
                                               2.4

-------
       •      Option 3/S corresponds to Option 3 except that certain non-interior source wastewater
              streams are exempted from the regulatory requirements.  Specifically, for facilities that
              process sanitizer chemicals, the zero discharge requirement would not apply to physically
              separate, non-interior wastewater streams that contain only six sanitizer chemicals.
              These non-interior wastewater streams include exterior equipment and floor wash, leak
              and spill cleanup, safety equipment rinsate, contaminated precipitation run-off, laboratory
              wastewater,  air pollution control wastewater, and  DOT test bath water.   The zero
              discharge requirement would apply to the interior wastewater streams of these facilities
              including discharge from cleaning the interiors of drum/shipping containers,  bulk
              containers, and other equipment.

       •      Option 4 incorporates the pollution prevention aspects of Options 2 and 3, but instead
              of treatment, adds off-site disposal to an incinerator  of the rest of the wastewater.

       •      Option 5 disposes of all wastewater through off-site incineration.

The two options considered for Subcategory E facilities are:

       •      Option  1 assumes  that contaminated  wastewater  is used  as  make-up  water in the
               application of pesticide chemicals to the field.

       •      Option 2 disposes of wastewater through off-site incineration.
        Calculation of Pollutant Removals
        The reductions in pollutant loadings to the receiving water body were calculated for each control
option.  At-stream  and end-of-pipe pollutant removals may differ because a portion of the end-of-pipe
loadings for indirect dischargers may be removed by the POTW.  As a result, the at-stream removal of
pollutants due to PSES  regulations are considered to be less than end-of-pipe removals.  The cost-
effectiveness analysis is based upon removals at-stream.

        For example, if a facility is discharging 100 pounds of cadmium in its effluent stream to a POTW
and the POTW has a removal efficiency for cadmium of 38 percent, then the cadmium discharged to
                                               2.5

-------
 surface waters is only 62 pounds.  If a regulation results in a reduction of cadmium in the effluent stream
 to 50 pounds, then the amount discharged to surface waters is calculated as 50 pounds multiplied by the
 POTW removal efficiency factor (1 - 0.38, or 0.62).  Cost-effectiveness calculations reflect the fact that
 the actual reduction of pollutant discharge to surface waters is not 50 pounds (the change in the amount
 discharged to the POTW), but 31 pounds (= 62 - 31), the change in the amount ultimately discharged
 to surface waters.4

        Annual ized Costs for Each Control Option
        Full details of the methods by which the costs of complying with the regulatory options were
 estimated can be found in the Technical  Development Document.  A brief summary of the compliance
 cost analysis is provided below.

        Two categories of compliance costs were analyzed:  (1) capital costs, and (2) operating and
 maintenance costs  (including sludge disposal and self-monitoring costs). Although capital costs are one-
 time "lump sum"  costs, operating and maintenance  costs occur annually.  The capital equipment is
 conservatively estimated to have a productive life of ten years.   Using a real  weighted average cost of
 capital, the capital  costs are amortized to account for the cost of financing the investment (through equity
 and debt) over the ten-year period.5  Total annualized costs are equal  to annualized capital costs plus
 operating and maintenance costs.  For ease of estimating costs,  EPA assumed that non-manufacturing
 PFPR facilities have no treatment in place.  For the PFPR/manufacturing facilities, it is assumed that,
 if possible,  the facilities  will build on existing treatment.  The reported costs are the full costs of
 compliance to society, some of which will be borne  by the government in the form of decreased tax
 receipts.  The analysis therefore overstates the burden of the regulations on industry.
     POTW removal efficiencies are not available for PAIs and are assumed to be zero. A laboratory study of the
PAI removal performance that would be achieved by biotreatment at well-operated POTWs applying secondary
treatment is reported in the Domestic Sewage Study (see the Technical Development Document). However, the data
used for that analysis were derived under laboratory conditions, and therefore tend to overestimate POTW removal
efficiencies and are considered to be inappropriate for the cost-effectiveness analysis. A sensitivity analysis based
on 50 percent POTW removal efficiency for all PAIs is considered in Appendix D.
     For details on the real weighted average cost of capital, see the discussion of the facility impact analysis in
Economic Impact Analysis of Proposed Effluent Limitations Guidelines and Standards for the Pesticide Formulating,
Packaging, and Repackaging Industry (hereafter the Proposed EIA).

                                                2.6

-------
        Compliance costs were estimated in terms of 1988 dollars. For the purpose of comparing cost-
 effectiveness values of the options under review to those of other promulgated rules, the compliance costs
 used in the cost-effectiveness analysis are deflated from to 1981 dollars using Engineering News Record's
 Construction Cost Index (CCI).  This adjustment factor is:
                   Adjustment factor   =
       1981 CCI
       1988 CCI
3535
4519
=  0.7823
        Stringency and Cost Ranking
        The regulatory options are ranked to determine relative cost-effectiveness.  Options are first
 ranked in increasing order of stringency, where stringency is aggregate pollutant removals, measured in
 pounds-equivalent. If two or more options remove equal amounts of pollutants, these options are then
 ranked in increasing order of cost.  For example, if two or more options specify zero discharge, the
 removals under each option would be equal.  The options would then be ranked from least expensive to
 most expensive.
        Calculation of Incremental Cost-Effectiveness Values
        After the options have been  ranked by stringency and cost, the incremental cost-effectiveness
values can be calculated. Cost-effectiveness values are calculated separately for Subcategories C and E.
For a given subcategory, the cost-effectiveness value of a particular option is calculated as the incremental
annual  cost of that option divided  by the incremental  pounds-equivalent  removed  by that  option.
Algebraically, this equation is:
where:
       CEk
       ATCk
       PE,,
Cost-effectiveness of Option Tc;
Total annualized compliance cost under Option k; and
Removals in pounds-equivalent under Option k.
                                              2.7

-------
The numerator of the equation is the incremental cost in going from Option k-1 to Option k. Similarly,
the denominator  is the incremental removals associated with the move from  Option k-1  to Option  k.
Thus, cost-effectiveness values are measured in dollars per pound-equivalent of pollutant removed.  The
incremental change can be from another regulatory option or from a baseline scenario.

        Comparisons of Cost-Effectiveness Values
        Two types of comparisons are typically done using cost-effectiveness values.  First, compliance
costs and pollutant removals may be plotted to derive a marginal cost curve to determine which options
offer the most cost-effective regulatory control.  The cost-effectiveness value calculated in the move from
one option to another represents such a marginal cost curve.  Second, the cost-effectiveness of regulatory
options incremental to the baseline scenario can be used to assess the cost-effectiveness of controls
relative to previously promulgated effluent limitations guidelines for other industries.
                                                2.8

-------
                                          Section 3
                             Results Using Original 272 PAIs

       The cost-effectiveness analysis is based on EPA's estimates of the full societal cost of compliance
and wastewater pollutant removals associated with six Pretreatment Standards for Existing Sources (PSES)
options for indirect discharging Subcategory C (Pesticide Formulating, Packaging, Repackaging Facilities)
and two PSES options for Subcategory E (Refilling Establishments).

       Subcategory C
       Table 2 presents the estimated total annualized costs, total pounds and total pounds-equivalent of
pollutants removed for the six  options.
Table 2
National Estimate of Annualized Costs and Removals Under PSES
SUBCATEGORY C FACILITIES
Option
Option 1
Option 2
Option 3/S
Option 3
Option 4*
Option 5*
Annualized
Cost, MM $
(1981 dollars)
$25.4
$21.8
$20.4
$21.8
$224. 1
$281.8
Pound
Removals
111,653
111,683
111,793
111,996
111,996
111,996
Pound-
Equivalent
Removals
12,127,075
12,127,666
12,134,031
12,134,051
12,134,051
12,134,051
These options result in additional costs with no additional removals.
       Table  3  presents the incremental cost-effectiveness values for the six options considered for
Subcategory C.  As the table shows, the cost-effectiveness of Option 1  is $2.10 per pound-equivalent of
pollutant removed.  Option  1 is very cost-effective when compared to the cost-effectiveness values of
other effluent limitations guidelines. Movement from Option 1 to Option 2 and from Option 2 to Option
3/S is cost-effective relative to Option 1 because costs are reduced while removals increase. Movement
from Option 3/S to Option 3 is  substantially less efficient than movement from Option  1 to Option 2 or
                                              3.1

-------
from Option 2 to Option 3/S. The average cost-effectiveness of Option 3 is $1.79 per pound-equivalent
and for Option 3/S is $1.68.  Options 4 and 5 are not cost-effective as they result in additional costs with
no additional removals relative to Option 3.  Option 3/S is the most cost-effective option.  Successive
improvements in weighted removals  are achieved at progressively lower costs by moving from Option
1 through Option 2 to Option 3/S.  Further movement from Option 3/S to Options 3, 4 or 5  provides
minor  additional removals at substantially higher marginal cost.
TableS
Estimated Industry Incremental Cost-Effectiveness Under PSES
SUBCATEGORY C FACILITIES
Option
Incremental from Baseline to Option 1
Incremental from Option 1 to Option 2
Incremental from Option 2 to Option 3/S
Incremental from Option 3/S to Option 3
Incremental from Option 3 to Option 4
Incremental from Option 4 to Option 5
Cost-Effectiveness,
$/lb.
$227.87
-$121,746*
-$12,513*
$6,790
undefined**
undefined**
Cost-Effectiveness,
$/lb-eq.
$2.10
-$6,232*
-$215.86*
$71,252
undefined**
undefined**
Dollar values are in constant 1981 dollars.
* Options are ranked by increasing levels of pollutant removals. Negative cost-effectiveness
numbers mean that costs have decreased from the previous option, while removals have
increased, improving cost-effectiveness.
** These options result in additional costs with no additional removals. Therefore, the
incremental cost-effectiveness ratio (incremental cost/incremental removals) is undefined.
                                               3.2

-------
       EPA is not able to estimate cost-effectiveness values for the regulatory options by PAIs or groups
of PAIs for several reasons.  First, wastestreams containing multiple PAIs are often commingled at PFPR
facilities.   This  commingling occurs because of the physical  set-up of the PFPR lines and  because
products are often made with more than one PAL EPA estimated compliance costs on a facility-specific
basis, in part due to this commingling, therefore costs are not available at a PAI-specific level within a
facility.

        EPA is able, however, to estimate cost-effectiveness values classifying facilities by their primary
markets.  Question 19 of the Survey Introduction asked respondents to report the percentage of pesticide
revenue obtained from nine specific markets:   agricultural, institutional/commercial,  industrial, wood
preservatives, intermediate products, professional use, consumer home/lawn/garden, government use, and
additives.  The analysis assumed that the market from which a facility received at least 50 percent of its
pesticide revenue is the primary market for that facility.  The primary market a facility reports does not
necessarily relate to the PAIs used by that facility.  Many PAIs appear in products that have several uses,
and those products may  be used in more than one  market.  Table 4 provides the estimated industry
incremental cost-effectiveness disaggregated by primary market. As the table illustrates, Option 3/S is
cost-effective when considered relative to other effluent guidelines.
                                                3.3

-------


















„


s
f.
1
a

W 4.4 (^3

Q *#S *~3
-SJ ^ t3
fa bu

Ji, p pC4 ,-y
^ o *C r ^ *^^
» -4-*
•yij QJ

e -S
i .3 & jj
o -~. OS


in *»
1 -S

fl P 5S



*a

C "flj
||



^
III

•3
*£>* *^
si


***»
11,
**"* S ^4
1 i j
>-5 O S




1
•***
jj ft)
& nflt
'SiJ



.2
"a,
O
*,
1
S
i>
.9
It
a
•8
iS
u
.3

*

1
*jj
S
.9

*


1
(U
.9


*
a

"3
i
.3


*
1
!
*,
J
3
.§


•t
1
o
ifi
0
.9




*
§
•3
m
fli
•3


«
1 Incremental
from Baseline 1
Option 1
*
1
'3

cs



VO
T— (
^






^
VO
CO
to-



o
Incremental
from Baseline 1
Option 3/S

e
oo

V*


#
*





Ss
CJ\
a\
£




*
*







*
*



?»
VO
s

OS
CS
8



00
l>
y*|ir







*
*




t«
19 o ro
J ji §
g Q'-'-S-
J J 3


*
*




*
*






*
*





*
*







*
*




*
*


*
4&




*
*








*
*




.3
Incremental
from Option 3
Option 4


*
*




*
*






*
*





*
*







•X-
*




*
*


#
^.




*








*
*




3
Incremental
from Option 4
Option 5

> -3
1 1
iU
t-<
IH |
o 6
u
a 3
w cd
O ^
O ^

1 8
00 -3
'« 1

> p
^ 1
<- y
o .3.
4 2
CQ .£5
> s<
2 «
H VI
g S
c
t« S
o >
O Q

> ^
O A
•a en
1 8
CtJ
^-t *3
C C
 -9
rj •*-*

1 1 ^
r^ W
3 J> co Q la
"§ ™ O O..3
illil
P O1 2 $ .S
* I

-------
       ;Subcategory E
       Table 5 presents the estimated total  annualized  costs, total pounds, and  total  pounds-equivalent of pollutants
•emoved for the two options considered for Subcategory E facilities. Option 1, the proposed option, is expected to be
ichieved with' zero additional costs.
                                                       3.5

-------
Tables
National Estimate of Annualized Costs and Removals Under PSES
SUBCATEGORY E FACILITIES
Option
Option 1
Option 2*
Annualized
Cost,
(1981 dollars)
$0
$1,507
Pound
Removals
1.0
1.0
Pound-
Equivalent
Removals
1.3
1.3
This option results in additional costs with no additional removals.
        Because Option 1 is expected to be met with no additional compliance costs, its cost-effectiveness is zero.  Option
2 requires additional costs but results in no additional removals, so its cost-effectiveness value is undefined. Therefore,
Option  1 is the more cost-effective option.
                                                      3.6

-------
                                                 Section 4
                                Results Using Additional Non-272 PAIs

        EPA.also estimated the cost-effectiveness of including under the proposed option all other PAIs not on the list
 of 272 PAIs studied in detail.  This section presents  the estimated cost-effectiveness of including these additional PAIs
 under the proposed PSES regulation for Subcategory  C facilities.  The regulatory option considered in this section is the
 same as Option 3/S discussed in the preceding section, with the exception that its regulatory coverage is broadened to
 include the additional non-272 PAIs.  To distinguish the analysis of the proposed  regulation including the non-272 PAIs
 from the preceding analysis based only on the 272  PAIs, the following discussion refers to the regulation including
 coverage of the additional non-272 PAIs as Option 3/S'.

       Because toxic weighting factors are not available for the non-272 PAIs, two separate cost-effectiveness analyses
 of Option 3/S' were performed.  The first analysis assumes that no non-272 PAIs are removed from the wastestreams.
 This is a highly conservative approach, because costs to treat the non-272 PAIs are included, but credit is not taken for
 removal of those PAIs.6  The second analysis estimates an average toxic weighting  factor for the non-272 PAIs based
 on the toxic weighting factors of the original 272 PAIs. These analyses and results are discussed below.

       Without Considering Non-272 PAI Removals
       To conservatively estimate the cost-effectiveness of Option 3/S',  EPA calculated the cost-effectiveness of the
option accounting for costs to remove non-272 PAIs but without considering the additional removals of non-272 PAIs.
Table 6 presents the total annualized compliance costs and removals under this assumption.
                                                  Table 6
              National Estimate of Annualized Costs and Removals Under PSES of Option 3/S',
                       Considering Non-272 PAI Costs but not Non-272 PAI Removals
                                     SUBCATEGORY C FACILITIES
  Option
Annualized Cost,
MM $ (1981 dollars)
Pound Removals
                                                                                  Pound-Equivalent
                                                                                  Removals
 Option 3/S'
       $43.9
      111,793
                                                                                         12,134,031
           For a discussion of the compliance cost estimates under Option 3/S', see Chapter 12 of the EIA.

                                                    4.1

-------
       Under this conservative assumption, the average cost-effectiveness of Option 3/S' is $3.62 per pound-equivalent-!
Thus, Option 3/S' is very cost-effective when compared to the cost-effectiveness values of other effluent limitations
guidelines.

       Considering Non-272 PAT Removals
       A more realistic assessment of the cost-effectiveness of Option 3/S'  would recognize the additional pollutantl
removals achieved by the inclusion of the non-272 PAIs.  Toxic weighting factors (TWFs) for these additional PAIs are!
not available, however.  To provide a surrogate for the TWFs for these PAIs, EPA assumed that the weighted average!
toxicity of the pre-compliance loadings of non-272 PAIs  is the same as that for pre-compliance loadings of the original
272 PAIs.  Specifically, EPA estimated an weighted average TWF for the non-272 PAIs by dividing the pre-compliance
pound-equivalent loadings of 272 PAIs by the pre-compliance loadings in pounds. This ratio yielded a weighted average
TWF of 108.3436.  The estimated pre-compliance loadings in pounds of non-272 PAIs was multiplied by this average)
TWF to provide pre-compliance pound-equivalent loadings.

       For the post-compliance analysis, all loadings are among the designated sanitizer PAIs.  To estimate the toxic-
weighted loadings of the non-272 sanitizer PAIs in post-compliance discharge, EPA assumed that the weighted average
toxicity of these loadings would be the same as the simple average of TWFs  for the sanitizer  PAIs among the original
272 PAIs.  Specifically, EPA multiplied the average TWF for 272 sanitizer PAIs  (0.1953)  by the post-compliance I
loadings of non-272 sanitizer PAIs to estimate the pound-equivalent loadings  of these PAIs. The quantity of pollutant
removals  due to Option 3/S' was  then calculated as the difference  between the pre-compliance and post-compliance
loadings.   Table 7 presents  the total and  incremental estimates of compliance costs, pollutant removals, and cost-
effectiveness, using these average TWFs for non-272 PAIs.
                                                     4.2

-------
Table 7
National Estimate of Annuaiized Costs and Removals Under PSES of Option 3/S',
Considering Non-272 PAI Costs and Removals
SUBCATEGORY C FACILITIES
Option
Option 3/S
Incremental from Option 3/S to
Option 3/S'
Option 3/S'
Annuaiized Cost,
MM $ (1981
dollars)
$20.4
$23.5
$43.9
Pound
Removals
111,793
198,662
310,455
Pound-
Equivalent
Removals
12,134,031
21,613,832
33,747,863
Cost-
Effectiveness, $
/ Ib-eq.
$1.68
$1.09
$1.30
Note: Toxicity of the non-272 PAIs is estimated as the average pre-compliance loading-weighted average toxicity
of the 272 PAIs.
        As Table 6 indicates, Option 3/S' is very cost-effective when compared to the cost-effectiveness values of other
effluent limitations guidelines.  Movement from Option 3/S to Option 3/S' is cost-effective;  the incremental cost-
effectiveness value is $1.09 per pound-equivalent.  The average cost-effectiveness of Option 3/S'  is $1.30 per pound-
equivalent.
                                                      4.3

-------

-------
                                                 Section 5
                Comparision of Cost-Effectiveness Values with Promulgated Rules

       Table 8 illustrates the cost-effectiveness values for effluent limitations guidelines issued for indirect dischargers
in other industries. The proposed PSES rule for pesticide formulating, packaging, repackaging facilities is cost-effective
when compared to the cost-effectiveness values for other effluent limitations guidelines.
                                                   5.1

-------
Table 8
Industry Comparison of Cost-Effectiveness for
Indirect Dischargers
(Toxic and Nonconventional Pollutants Only)
Copper Based Weights
(1981 Dollars)*
Industry
Aluminum Forming
Battery Manufacturing
Can Making
Coal Mining***
Coil Coating
Copper Forming
Electronics I
Electronics n
Foundries
Inorganic Chemicals I
Inorganic Chemicals II
Iron & Steel
Leather Tanning
Metal Finishing
Nonferrous Metals Forming
Nonferrous Metals Mfg I
Nonferrous Metals Mfg n
OCPSF
Pesticide Manufacturing
Pharmaceuticals
Plast. Molding & Forming
Porcelain Enameling
Pulp & Paper *****
Pounds Equivalent
Currently Discharged
(To Surface Waters)
(OOO's)
1,602
1,152
252
N/A
2,503
34
75
260
2,136
3,971
4,760
5,599
16,830
11,680
89
3,187
38
5,210
257
340
N/A
1,565
9,539
Pounds Equivalent
Remaining at Selected
Option (To Surface Waters)
(OOO's)
18
5
5
N/A
10
4
35
24
18
3,004
6
1,404
1,899
755
5
19
0.41
72
19
63
N/A
96
103
Cost Effectiveness
Selected Option
Beyond BPT**
($/lb-eq. removed)
155
15
38
N/A**
10
10
14
14
116
9
****
6
111
10
90
15
12
34
18
1
N/A
14
65
* Although toxic weighting factors for priority pollutants varied across these rules, this table reflects
the cost-effectiveness at the time of regulation.
** N/A: Pretreatment Standards not promulgated, or no incremental costs will be incurred.
*** Reflects costs and removals of both air and water pollutants
**** Less than a dollar.
***** Results shown for proposed rules, December 1993.
5.2

-------
                                     Appendix A
       Original 272 Pesticide Active Ingredients Considered for Regulation
This appendix provides the original 272 pesticide active ingredients considered for regulation.
                                          A.I

-------
Pesticide
Number
    1
    2
    3
    4
    5
    6
    7

    8
    9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
  20
  21
  22
  23
  24
  25
  26
  27
  28
  29
  30

  31

  32
  33

  34
  35
 Pesticide Name
 Dicofol [l,l-Bis(chlorophenyl)-2,2,2-trichloroethanol]
 Maleic Hydrazide
 EDB [1,2-Ethylene dibromide]
 Vancide TH [1,3,5-Triethylhexahydro-s-triazine]
 Dichloropropene
 Oxybiphenoarsine
 Dowicil 75 [l-(3-Chloroallyl)-3,5,7-triaza-l-
 azoniaadamantanechloride]
 Triadimefon
 Hexachlorophene (nabac)
 Tetrachlorophene
 Dichlorophene
 Dichlorvos
 Landrin-2 [2,3,5-trimethylphenylmethylcarbamate]
 Fenac [2,3,6-Trichlorophenylacetic acid] or any salt or ester
 2,4,5-T [2,4,5-Trichlorophenoxyacetic acid] or any salt or ester
 2,4-D [2,4-Dichlorophenoxyacetic acid]  or any salt or ester
 2,4-DB [2,4-Dichlorophenoxybutyric acid] or any salt or ester
 Anilazine [2,4-Dichloro-6-(o-chloroanilino)-s-triazine]
 Dinocap
 Dichloran (2,6-dichloro-4-nitroaniline)
 Busan 90 [2-Bromo-4-hydroxyacetophenone]
 Mevinphos
 Sulfallate [2-chloroallyldiethyldithiocarbamate]
 Chlorfenvinphos
 Cyanazine
 Propachlor
 MCPA [2-Methyl-4-chlorophenoxyacetic acid] or any salt or ester
 Octhilinone
 Pindone
 Dichlorprop [2-(2,4-Dichlorophenoxy) propionic acid] or any salt
 or ester
 MCPP [2-(2-Methyl-4-chlorophenoxy)propioiiicacid] or any salt
 or ester
Thiabendazole
Belclene 310 [2-(methylthio)-4-(ethylamino)-6-(l,2-
dimethylamino)-s-triazine]
Cloprop [2-(m-Chlorophenoxy)propionic acid] or any salt or ester
TCMTB[2-(Thiocyanomethylthio)benzothiazole]
 CAS Number

 00115-32-2
 00123-33-1
 00106-93-4
 07779-27-3
 00542-75-6
 00058-36-6
 04080-31-3

 43121-43-3
 00070-30-4
 01940-43-8
 00097-23-4
 00062-73-7
 02686-99-9
 00085-34-7
 00093-76-5
 00094-75-7
 00094-82-6
 00101-05-3
 39300-45-3
 00099-30-9
 02491-38-5
 07786-34-7
 00095-06-7
 00470-90-6
 21725-46-2
 01918-16-7
 00094-74-6
 26530-20-1
 00083-26-1
 00120-36-5

 00093-65-2

 00148-79-8
 22936-75-0

00101-10-0
21564-17-0
                                         A.2

-------
Pesticide
Number
   36
   37
   38
   39
   40
   41
   42
   43

   44
   45
   46
   47

   48
   49
   50
   51
   52
   53
   54
   55
   56

  57
  58
  59
  60
  61
  62
  63
  64
  65

  66
  67
  68
  69
  70
 Pesticide Name
 HAE [2-((Hydroxymethyl)amino) ethanol
 Chlorophacinone
 Landrin-1 [3,4,5-trimethylphenylmethylcarbamate]
 Pronamide
 Methiocarb
 Propanil
 Polyphase antimildew [3-Iodo-2-propynyl butylcarbamate]
 3-(a-Acetonylfurfuryl)-4-hydroxycoumarin [Coumafuryl] or any
 salt or ester
 DNOC (4,6-dinitro-o-cresol)
 Metribuzin
 CPA (4-chlorophenoxyacetic acid) or any salt or ester
 MCPB  [4-(2-Methyl-4-chlorophenoxy)butyric acid] or any salt or
 ester
 Aminocarb [4-(dimethylamino)-m-tolylmethyIcarbamate]
 Etridiazole
 Ethoxyquin
 Quinoliol sulfate (8-Quinoliol sulfate)
 Acephate
 Acifluorfen or any salt or ester
 Alachlor
 Aldicarb
 Hyamine 3500  [Alkyl* dimethyl benzyl ammonium chloride
 * (50%  C14, 40% C12, 10%  C16)]
 Allethrin (all isomers and allethrin coil)
 Ametryn
 Amitraz
 Atrazine
 Bendiocarb
 Benomyl and Carbendazim
 Benzene Hexachloride
 Benzyl benzoate
 Lethane 384 [Beta-Thiocyanoethyl esters of mixed fatty acids
 containing from 10-18 carbons]
 Bifenox
 Biphenyl
 Bromacil or any salt or ester
Bromoxynil or any salt or ester
Butachlor
 CAS Number

 34375-28-5
 03691-35-8
 02686-99-9
 23950-58-5
 02032-65-7
 00709-98-8
 55406-53-6
 00117-52-2

 00534-52-1
 21087-64-9
 00122-88-3
 00094-81-5

 02032-59-9
 02593-15-9
 00091-53-2
 00134-31-6
 30560-19-1
 50594-66-6
 15972-60-8
 00116-06-3
 68424-85-1

 00584-79-2
 00834-12-8
 33089-61-1
 01912-24-9
 22781-23-3
 17804-35-2
 00608-73-1
 00120-51-4
 00301-11-1

 42576-02-3
00092-52-4
00314-40-9
01689-84-5
23184-66-9
                                         A.3

-------
Pesticide
Number    Pesticide Name
   71      Giv-gard |j3-Bromo-/?-nitrostyrene]
   72      Cacodylic acid or any salt or ester
   73      Captafol
   74      Captan
   75      Carbaryl [Sevin]
   76      Carbofiiran
   77      Carbosulfan
   78      Chloramben or any salt or ester
   79      Chlordane
   80      Chloroneb
   81      CMoropicrin
   82      Chlorothalonil
   83      Chloroxuron
   84      Stirofos
   85      Chlorpyrifos methyl
   86      Chlorpyrifos
   87      Mancozeb
   88      Bioquin
   89      Copper EDTA
   90      Fenvalerate
   91      Cycloheximide
   92      Dalapon (2,2-dicbloropropionic acid) or any salt or ester
   93      Dienochlor
   94      Demeton  [O.O-Diethyl O-(and S-) (2-ethylthio)ethyl)
           phosphorothioate]
   95      Desmedipham
   96      Diammonium ethylenebisdithiocarbamate
   97      DBCP [Dibromo-3-chloropropane]
   98      Dicamba [3,6-Dichloro-o-anisic acid] or any salt or ester
   99      Dichlone (Phygon)
   100     Thiophanate ethyl
   101     Perthane [Diethyl diphenyl dichloroethane and related
           compounds]
   102     EXD [Diethyl dithiobis (thionoformate)]
   103     Diazinon
   104     Diflubenzuron
   105     Benzethonium chloride
   106     Dimethoate
CAS Number

 07166-19-0
 00075-60-5
 02425-06-1
 00133-06-2
 00063-25-2
 01563-66-2
 55285-14-8
 00133-90-4
 00057-74-9
 02675-77-6
 00076-06-2
 01897-45-6
 01982-47-4
 00961-11-5
 05598-13-0
 02921-88-2
 08018-01-7
 10380-28-6
 01495-19-18
 51630-58-1
 00066-81-9
 00075-99-0
 02227-17-0
 08065-48-3

 13684-56-5
 03566-10-7
 00096-12-8
 01918-00-9
 00117-80-6
 23564-06-9
 00072-56-0

 00502-55-6
 00333-41-5
 35367-38-5
 00121-54-0
 00060-51-5
                                          A.4

-------
Pesticide                                                                CAS Number
Number    Pesticide Name
  107      Parathion methyl                                               00298-00-0
  108      Dicrotophos                                                   00141-66-2
  109      Crotoxyphos                                                   07700-17-6
  110      DCPA [Dimethyl 2,3,5,6-tetrachloroterephthalate]                  01861-32-1
  111      Trichlorofon                                                   00052-68-6
  112      Dinoseb                                                       00088-85-7
  113      Dioxathion                                                    00078-34-2
  114      Diphacinone                                                   00082-66-6
  115      Diphenamid                                                   00957-51-7
  116      Diphenylamine                                                00122-39-4
  117      MGK 326 [Dipropyl isocinchomeronate]                          00113-48-4
  118      Nabonate [Disodium cyanodithioimidocarbonate]                   00138-93-2
  119      Diuron                                                        00330-54-1
  120      Metasol DGH  [Dodecylguanidine hydrochloride]                   13590-97-1
  121      Dodine (dodecylquanidine acetate)                                02439-10-3
  122      Endosulfan [Hexachlorohexahydromethano-2,4,3-                  00115-29-7
           benzodioxathiepin-3-oxide]
  123      Endothall or any salt or ester                                    00145-73-3
  124      Endrin                                                        00072-20-8
  125      Ethalfluralin                                                   55283-68-6
  126      Ethion                                                        00563-12-2
  127      Ethoprop                                                     13194-48-4
  128      Fenamiphos                                                   22224-92-6
  129      Chlorobenzilate                                                00510-15-6
  130      Butylate                                                       02008-41-5
  131      Famphur                                                      00052-85-7
  132      Fenarimol                                                     60168-88-9
  133      Fenthion                                                      00055-38-9
  134      Ferbam                                                       14484-64-1
  135      Fluometuron                                                   02164-17-2
  136      Fluoroacetamide                                               00640-19-7
  137      Folpet                                                        00133-07-3
  138      Glyphosate [N-(Phosphonomethyl) glycine] or any salt or ester      01071-83-6
  139      Glyphosine                                                    02439-99-8
  140      Heptachlor                                                    00076-44-8
  141      Cycloprate                                                    54460-46-7
  142      Hexazinone                                                   51235-04-2
  143      Isofenphos                                                    25311-71-1
                                         A.5

-------
Pesticide
Number
  144
  145
  146
  147
  148
  149


  150
  151
  152
  153

  154
  155
  156
  157
  158
  159
  160
  161
  162


  163
  164
  165
  166
  167
 168
 169
 170
 171
 172
 173
 174
 175
 176
 177
  Pesticide Name
  Isopropalin
  Propham
  Karbutilate
  Lindane
  Linuron
  Malachite green [Ammomum(4-(p-(dimethylarnino)-alpha-
  phenylbenzylidine)-2,5-cyclohexadien-l-ylidene)-dimethyl
  chloride]
  Malathion
  Maneb
  Manganous dimethyldithiocarbamate
  Mefluidide [N-(2,4-dimethyl-5-(((trifluoromethyl) sulfonyl)-
  amino) phenyl acetamide] or any salt or ester
  Methamidophos
  Methidathion
  Methomyl
  Methoprene
 Methoxychlor
 Methylbenzethonium chloride
 Methylbromide
 Methylarsonic acid or any salt or ester
 Hyamine 2389 [Methyldodecylbenzyl trimethyl ammonium
 chloride 80% and methyldodecylxylylene
 bis (trimethylammoniumchloride) 20%]
 Methylenebisthiocyanate
 Quinmethionate
 Metolachlor
 Mexacarbate
 Metiram
 Monuron TCA
 Monuron
 Napropamide
 Deet
 Nabam
 Naled
 Norea
 Norflurazon
 Naptalam |TC-l-NaphthylphthaIamic acid] or any salt or ester
MGK 264 [N-2-Ethylhexyl bicycloheptene dicarboximide]
 CAS Number

  33820-53-0
  00122-42-9
  04849-32-5
  00058-89-9
  00330-55-2
  00569-64-2


  00121-75-5
  12427-38-2
  15339-36-3
 53780-34-0

  10265-92-6
 00950-37-8
 16752-77-5
 40596-69-8
 00072-43-5
 15716-02-6
 00074-83-9
 00124-58-3
 01399-80-0


 06317-18-6
 02439-01-2
 51218-45-2
 00315-18-4
 09006-42-2
 00140-41-0
 00150-68-5
 15299-99-7
 00134-62-3
 00142-59-6
 00300-76-5
 18530-56-8
 27314-13-2
00132-66-1
00136-45-8
                                       A.6

-------
Pesticide
Number
  178
  179
  180
  181
  182
  183
  184
  185
  186
  187
  188
  189
  190
  191
  192
  193
  194
  195
  196
  197
  198
  199
  200
  201
  202
  203
  204
  205
  206
  207
  208
  209
  210
  211
  212
  213
  214
 215
 Pesticide Name
 Benfluralin
 Sulfotepp
 Aspon
 Coumaphos
 Fensulfothion
 Disulfoton
 Fenitrothion
 Phosmet
 Azinphos Methyl
 Oxydemeton methyl
 Organo-arsenic pesticides
 Organo-cadmium pesticides
 Organo-copper pesticides
 Organo-mercury pesticides
 Organo-tin pesticides
 Orthodichlorobenzene
 Oryzalin
 Oxamyl
 Oxyfluorfen
 Bolstar [Sulprofos]
 Sulprofos Oxon
 Santox (O-Ethyl O-(p-nitrophenyl) phenylphosphonothioate
 Fonofos
 Propoxur (o-Isopropylphenylmethylcarbamate)
 Paradichlorobenzene
 Parathion
 Pendimethalin
 Pentachloronitrobenzene
 Pentachlorophenol or any salt or ester
 Perfluidone
 Permethrin
 Phenmedipham
 Phenothiazine
 Phenylphenol
 Phorate
Phosalone
Phosphamidon
Picloram or any salt or ester
CAS Number

 01861-40-1
 03689-24-5
 03244-90-4
 00056-72-4
 00115-90-2
 00298-04-4
 00122-14-5
 00732-11-6
 00086-50-0
 00301-12-2
00095-50-1
19044-88-3
23135-22-0
42874-03-3
35400-43-2
38527-90-1
02104-64-5
00944-22-9
00114-26-1
00106-46-7
00056-38-2
40487-42-1
00082-68-8
00087-86-5
37924-13-3
52645-53-1
13684-63-4
00092-84-2
00090-43-7
00298-02-2
02310-17-0
13171-21-6
01918-02-1
                                        A.7

-------
Pesticide                                                                 CAS Number
Number   Pesticide Name
  216      Piperonyl butoxide                                             00051-03-6
  217      PEED (Busan 77) [Poly (oxyethylene (dimethylimino) ethylene      31512-74-0
           (dimethylimino) ethylene dichloride]
  218      Busan 85 [Potassium dimethyldithiocarbamate]                     00128-03-0
  219      Busan 40 [Potassium N-hydroxymethyl-N-methyldithiocarbamate]    51026-28-9
  220      KN Methyl [Potassium N-methyldithiocarbamate]                  00137-41-7
  221      Metasol J26 [Potassium N-(alpha-(nitroethyl) benzyl)-              53404-62-9
           ethylenediamine]
  222      Profenofos                                                    41198-08-7
  223      Prometon                                                     01610-18-0
  224      Prometryn                                                    07287-19-6
  225      Propargite                                                    02312-35-8
  226      Propazine                                                     00139-40-2
  227      Propionic acid                                                 00079-09-4
  228      Propamocarb and Propamocarb HCL                             24579-73-5
  229      Pyrethrin coils                                                   	
  230      Pyrethrin I                                                    00121-21-1
  231      Pyrethrin U                                                    00121-29-9
  232      Pyrethrum (other than pyrethrins)                                08003-34-7
  233      Resmethrin                                                    10453-86-8
  234      Ronnel                                                        00299-84-3
  235      Rotenone                                                      00083-79-4
  236      DBF [S,S,S-Tributyl phosphorotrithioate]                         00078-48-8
  237      Siduron                                                       01982-49-6
  238      Silvex [2-(2,4,5-Trichlorophenoxypropionic acid)] or any salt or     00093-72-1
           ester
  239      Simazine                                                      00122-34-9
  240      Bentazon                                                      25057-89-0
  241      Carbam-S [Sodium dimethyldithiocarbanate]                       00128-04-1
  242      Sodium monofluoroacetate                                      00062-74-8
  243      Vapam [Sodium methyldithiocarbamate]                           00137-42-8
  244      Sulfoxide                                                  .    00120-62-7
  245      Cycloate                                                      01134-23-2
  246      EPTC [S-Ethyl dipropylthiocarbamate]                            00759-94-4
  247      Molinate                                                      02212-67-1
  248      Pebulate                                                       01114-71-2
  249      Vernolate                                                      01929-77-7
  250      HPTMS [S-(2-Hydroxypropyl) thiomethanesulfonate]               29803-57-4
                                         A.8

-------
Pesticide                                                                 CAS Number
Number   Pesticide Name
  251      Bensulide                                                      00741-58-2
  252      Tebuthiuron                                                    34014-18-1
  253      Temephos                                                      03383-96-8
  254      Terbacil                                                        05902-51-2
  255      Terbufos                                                       13071-79-9
  256      Terbuthylazine                                                  05915-41-3
  257      Terbutryn                                                      00886-50-0
  258      Tetrachlorophenol or any salt or ester                           ' 25167-83-3
  259      Dazomet                                                       00533-74-4
  260      Thiophanate methyl                                             23564-05-8
  251      Thiram                                                        00137-26-8
  262      Toxaphene                                                     08001-35-2
  263      Merphos [Tributyl phosphorotrithioate]                            00150-50-5
  264      Trifluralin                                                      01582-09-8
  265      Warfarin [3-(a-Acetonylbenzyl)-4-hydroxycoumarin] or any salt      00081-81-2
           or ester
  266      Zinc MET [Zinc 2-mercaptobenzothiazolate]                       00155-04-4
  267      Zineb                                                          12122-67-7
  268      Ziram                                                          00137-30-4
  269      S-(2,3,3-trichloroallyl)diisopropylthiocarbamate                    02303-17-5
  270      Phenothrin                                                     26002-80-2
  271      Tetramethrin                                                   07696-12-0
  272      Chloropropham                                                 00101-21-3
                                         A.9

-------

-------
                                       Appendix B
              Toxic Weighting Factors for Pesticide Active Ingredients
       This appendix provides the toxic weighting factors (TWFs) used in the analysis.  Toxic weighting

factors for pesticide active ingredients are listed in Table B-l.
                                            B.I

-------

-------
                                        Appendix C
           Results of Compliance with the Existing 1978 BPT Regulation
       This  appendix describes the results of the cost-effectiveness  analysis for  direct discharging
facilities to comply with the existing 1978 Best Practicable Control Technology Currently Available (BPT)
regulation.  The analysis is based on EPA's estimates of the full societal cost of compliance and
wastewater pollutant removals associated with six BPT options for direct discharging  Subcategory C
facilities.  These options are analogous to the PSES options described in Section 2.

       Table C-l presents the estimated total annualized costs, total pounds and total pounds-equivalent
of pollutants removed for the six options.
Table C-l
National Estimate of Annualized Costs and Removals Under BPT
SUBCATEGQRY C FACILITIES
Option
Option 1
Option 2
Option 3/S
OptionS
Option 4*
Option 5*
Annualized
Cost, MM $
Wl)
$5.9
$5.5
$5.5
$5.5
$103.6
$107.6
Pound
Removals
49,411
49,415
49,435
49,435
49,435
49,435
Pound-
Equivalent
Removals
72,258,866
72,259,368
72,259,886
72,259,886
72,259,886
72,259,886
*These options result in additional costs with no additional removals.
       Table C-2 presents the incremental cost-effectiveness values for the six options considered.  As
the table shows, the cost-effectiveness of Option 1 is $0.08 per pound-equivalent of pollutant removed.
That is very cost-effective when compared to the cost-effectiveness of other effluent limitations guidelines.
Movement from Option 1 to Option 2 and from Option 2 to Option 3/S is cost-effective relative to Option
1 because costs are reduced while removals increase. Movement from Option 3/S to Option 3 results in
                                             C.I

-------
no additional costs or removals, so the incremental cost-effectiveness value is undefined.  Options 4 and
5 are not cost-effective as they result in additional costs with no additional removals relative to Option
3/S. Option 3/S is the most cost-effective option.  Successive improvements in weighted removals are
achieved at progressively lower costs by moving from Option 1 through Option 2 to Option 3/S.  Further
movement from Option 3/S to  Options 3, 4 or 5 provides minor additional removals at substantially
higher marginal cost.
" "•f-'V'^w-i- -A»r's^,,-4iM^ '„,;,''""' ' '-•
^ Table C-2 t ,..^, «„?,« . ~, . , -,
Estimated Industry Incremental Cbst-Bkwtiveness Under feJ*!1
SOBCATEGQRY C FACILITIES t ^
Option *,,„'"- "-',: ''.
Incremental from Baseline to Option I
Incremental from Option 1 to Option 2
Incremental from Option 2 to Option 3/S
Incremental from Option 3/£ to Option 3
Incremental from Option 3 to Option 4
Incremental from Option 4 to Option 5
Cost-Effectiveness,
^$/iK ,^'"
$120.00
-$90,723*
$0
undefined**
undefined**
undefined**
Cost-Effectiveness,
$/Ib-eq.
$0.08
-$813.34*
$0
undefined**
undefined**
undefined**
Dollar values are in constant 1981 dollars.
* Options are ranked by increasing levels of pollutant removals. Negative cost-effectiveness
numbers mean that costs have decreased from the previous option, while removals have
increased, improving cost-effectiveness.
** Option 3 results hi the same costs and removals as Option 3/S. Options 4 and 5 result in
additional costs with no additional removals. Therefore, the incremental cost-effectiveness
ratio (incremental cost/incremental removals) is undefined.
                                              C.2

-------
                                       Appendix D
                  Sensitivity Analysis of POTW Removal Efficiency

       This appendix describes a sensitivity analysis  applied to the assumption in the PSES  cost-
effectiveness analysis that pesticide active ingredients (PAIs) are not removed by POTWs. There is very
little empirical data on the PAI removals actually achieved by POTWs.  The only data available on
POTW removal efficiencies for PAIs is from the Domestic Sewage Study (DSS) (Report to Congress on
the Discharge of Hazardous Waste to Publicly Owned Treatment Works, February 1986, EPA/530-SW-
86-004).  The DSS provides laboratory data under ideal conditions to estimate biotreatment removal
efficiencies at POTWs for different organic PAI structural groups.  These data, however, are not full-
scale/in-use POTW data and therefore, are not appropriate for use in the cost-effectiveness analysis.

       For the sensitivity analysis it is assumed that POTWs remove 50 percent of the PAIs from the
wastestream.  The results are discussed below for Subcategory C  and Subcategory E facilities.

       Subcategory C
       Table D-l presents the estimated total annualized costs, total pounds and total pounds-equivalent
of pollutants removed for the six options under the assumption of 50 percent POTW removal efficiency
for PAIs.
                                             D.I

-------
Table IM
National Estimate of Annualized Costs and Removals Under PSES
•> -i f f ty jjdjJij,.' -vxr" ff~J"f y^,^ f jv t,i> ,&./• "*% .,,• «;.,
SOBCATEGORY C FACILITIES
Assuming 50 percent POTW Removal Efficiency for PAfe
Option
Option 1
Option 2
Option 3/S
Options
Option 4*
Option 5*
Annualized
Cost., MM $
(1981 dollars)
$25.4
$21.8
$20.4
$21.8
$224.1
$281.8
Pound
Removals
55,827
55,841
55,897
55,998
55,998
55,998
Pound-
Equivalent
Removals
6,063,537
6,063,833
6,067,016
6,067,025
6,067,025
6,067,025
"These options result in additional costs with no additional removals.
        Table D-2 presents the incremental cost-effectiveness values for the six options considered for
Subcategory C under the assumption of the sensitivity analysis. As the table shows, the cost-effectiveness
of Option 1 is $4.20 per pound-equivalent of pollutant removed. Option 1 is very cost-effective when
compared to the cost-effectiveness values  of other effluent limitations guidelines.   Movement  from
Option 1 to Option 2 and from Option 2 to Option 3/S is cost-effective relative to Option 1 because costs
are reduced while removals increase. Movement  from Option 3/S to Option 3 is substantially less
efficient than movement from Option  1 to Option 2 or from Option 2 to Option 3/S.  The average cost-
effectiveness of Option 3 is. $3.59 per pound-equivalent and for Option 3/S is $3.36.  Options 4 and 5
are not cost-effective as they result hi additional costs with no additional removals  relative to Option 3.
Option 3/S is the most cost-effective option.  Successive improvements in weighted removals are achieved
at progressively lower costs by moving from Option 1 through  Option 2 to Option 3/S.  Further
movement from Option 3/S to Options 3, 4 or 5 provides minor  additional removals  at substantially
higher marginal cost.   Thus, the assumption of 50 percent PAI removal efficiency at POTWs does not
alter the result that Option 3/S  is the most cost  effective option, and is cost-effective relative to
promulgated effluent limitations guidelines.
                                              D.2

-------
Table D-2
Estimated Industry Incremental Cost-Effectiveness Under PSES
SDBCATEGORY C FACILITIES
Assuming 50 percent POTW Removal Efficiency for PAIs
Option
Incremental from Baseline to Option 1
Incremental from Option 1 to Option 2
Incremental from Option 2 to Option 3/S
Incremental from Option 3/S to Option 3
Incremental from Option 3 to Option 4
Incremental from Option 4 to Option 5
Ctost-Effectiveness,
$/lb.
$455.73
-$243,491*
-$25,025*
$13,580
undefined**
undefined**
Cost-Effectiveness,
$/!b-eq.
$4.20
-$12,463*
-$431.72*
$142,503
undefined**
undefined**
Dollar values are in constant 1981 dollars.
* Options are ranked by increasing levels of pollutant removals. Negative cost-effectiveness
numbers mean that costs have decreased from the previous option, while removals have
increased, improving cost-effectiveness.
** These options result hi additional costs with no additional removals. Therefore, the
incremental cost-effectiveness ratio (incremental cost/incremental removals) is undefined.
       Subcategory E
       Table D-3 presents the estimated total annualized costs, total pounds, and total pounds-equivalent
of pollutants removed for the two options considered for Subcategory E facilities under the assumption
of 50 percent PAI removal efficiency for POTWs.  Option 1, the proposed option, is expected to be
achieved with zero additional costs.
                                              D.3

-------
Table I>-3
National Estimate of Annualized Costs and Removals Under PSES
SIJBCATE0ORY E FACILITIES
Assuming 50 percent P0TW Removal Efficiency for PAIs
Option
Option 1
Option 2*
Annualized
Cost,
(1981 dollars)
$0
$1,507
Found
Removals
0.5
0.5
Pound-'
Equivalent
Removals
0.6
0.6
"This option results in additional costs with no additional removals.
       Because Option 1 is expected to be met with no additional compliance costs, its cost-effectiveness
is zero. Option 2 requires additional costs but results hi no additional removals, so its cost-effectiveness
value is undefined.  Therefore, Option 1 is still the more cost-effective option, even assuming POTWs
can remove 50 percent of the PAIs in the wastestream.
                                              D.4

-------