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
------- |